`_. Uncompress the archive and change into the ``PyCogent`` directory and type::
$ python setup.py build
This automatically compiles the modules. If you have administrative privileges type::
$ sudo python setup.py install
This then places the entire package into your python/site-packages folder.
If you do not have administrator privileges on your machine you can change the build approach to::
$ python setup.py build_ext -if
which compiles the extensions in place (the ``i`` option) forcibly (the ``f`` option, ie even if they've already been compiled). Then move the cogent directory to where you want it (or leave it in place) and add this location to your python path using ``sys.path.insert(0, "/your/path/to/PyCogent")`` in each script, or by setting shell environment variables (e.g. ``$ export PYTHONPATH=/your/path/to/PyCogent:$PYTHONPATH``)
Testing
-------
``PyCogent/tests`` contains all the tests (currently >3100). You can most readily run the tests using the ``PyCogent/run_tests`` shell script. This is done by typing:
.. code-block:: guess
$ sh run_tests
which will automatically build extensions in place, set up the PYTHONPATH and run ``PyCogent/tests/alltests.py``. Note that if certain optional applications are not installed this will be indicated in the output as "can't find" or "not installed". A "`.`" will be printed to screen for each test and if they all pass, you'll see output like:
.. code-block:: guess
Ran 3299 tests in 58.128s
OK
Tips for usage
--------------
A good IDE can greatly simplify writing control scripts. Features such as code completion and definition look-up are extremely useful. For a complete list of `editors go here`_.
To get help on attributes of an object in python, use
.. code-block:: python
>>> dir(myalign)
to list the attributes of ``myalign`` or
.. code-block:: python
>>> help(myalign.writeToFile)
to figure out how to use the ``myalign.writeToFile`` method. Also note that the directory structure of the package is similar to the import statements required to use a module -- to see the contents of ``alignment.py`` or ``sequence.py`` you need to look in the directory ``cogent/core`` path, to use the classes in those files you specify ``cogent.core`` for importing.
.. _Python: http://www.python.org
.. _Cython: http://www.cython.org/
.. _Numpy: http://numpy.scipy.org/
.. _Matplotlib: http://matplotlib.sourceforge.net
.. _Apple: http://www.apple.com
.. _Pyrex: http://www.cosc.canterbury.ac.nz/~greg/python/Pyrex/
.. _`editors go here`: http://www.python.org/cgi-bin/moinmoin/PythonEditors
.. _mpi4py: http://code.google.com/p/mpi4py
.. _`restructured text`: http://docutils.sourceforge.net/rst.html
.. _gcc: http://gcc.gnu.org/
.. _SQLAlchemy: http://www.sqlalchemy.org
.. _`MySQL-python`: http://sourceforge.net/projects/mysql-python
.. _zlib: http://www.zlib.net/
.. _`compiling matplotlib`: http://sourceforge.net/projects/pycogent/forums/forum/651121/topic/5635916
PyCogent-1.5.3/run_tests 000755 000765 000024 00000000612 11623063350 016212 0 ustar 00jrideout staff 000000 000000 #!/bin/sh
# make sure we remove .pyc files in case someone has renamed a module ..
find . -name '*.pyc' -delete
# for automated testing - check if using alternate python install
PYTHON_EXE=python
if [ $PYTHON_TEST_EXE ]; then
PYTHON_EXE=$PYTHON_TEST_EXE;
fi
set -e
$PYTHON_EXE setup.py build_ext --inplace
export PYTHONPATH=`pwd`:$PYTHONPATH
cd tests
nice $PYTHON_EXE alltests.py "$@"
PyCogent-1.5.3/setup.py 000644 000765 000024 00000015136 12024702176 015761 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from distutils.core import setup
import sys, os, re, subprocess
__author__ = "Peter Maxwell"
__copyright__ = "Copyright 2007-2011, The Cogent Project"
__contributors__ = ["Peter Maxwell", "Gavin Huttley", "Matthew Wakefield",
"Greg Caporaso", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Peter Maxwell"
__email__ = "pm67nz@gmail.com"
__status__ = "Production"
# Check Python version, no point installing if unsupported version inplace
if sys.version_info < (2, 6):
py_version = ".".join([str(n) for n in sys.version_info])
raise RuntimeError("Python-2.6 or greater is required, Python-%s used." % py_version)
# Check Numpy version, no point installing if unsupported version inplace
try:
import numpy
except ImportError:
raise RuntimeError("Numpy required but not found.")
numpy_version = re.split("[^\d]", numpy.__version__)
numpy_version_info = tuple([int(i) for i in numpy_version if i.isdigit()])
if numpy_version_info < (1, 3):
raise RuntimeError("Numpy-1.3 is required, %s found." % numpy_version)
doc_imports_failed = False
try:
import sphinx
except ImportError:
doc_imports_failed = True
# A new command for predist, ie: pyrexc but no compile.
import distutils.ccompiler
class NullCompiler(distutils.ccompiler.CCompiler):
# this basically to stop pyrexc building binaries, just the .c files
executables = ()
def __init__(self, *args, **kw):
pass
def compile(self, *args, **kw):
return []
def link(self, *args, **kw):
pass
# Pyrex makes some messy C code so limit some warnings when we know how.
import distutils.sysconfig
if (distutils.sysconfig.get_config_var('CC') or '').startswith("gcc"):
pyrex_compile_options = ['-w']
else:
pyrex_compile_options = []
# On windows with no commandline probably means we want to build an installer.
if sys.platform == "win32" and len(sys.argv) < 2:
sys.argv[1:] = ["bdist_wininst"]
# Restructured Text -> HTML
def build_html():
if doc_imports_failed:
print "Failed to build html due to ImportErrors for sphinx"
return
cwd = os.getcwd()
os.chdir('doc')
subprocess.call(["make", "html"])
os.chdir(cwd)
print "Built index.html"
# Compiling Pyrex modules to .c and .so
include_path = os.path.join(os.getcwd(), 'include')
# find arrayobject.h on every system an alternative would be to put
# arrayobject.h into pycogent/include, but why ..
numpy_include_path = numpy.get_include()
distutils_extras = {"include_dirs": [include_path, numpy_include_path]}
try:
if 'DONT_USE_PYREX' in os.environ:
raise ImportError
from Cython.Compiler.Version import version
version = tuple([int(v) \
for v in re.split("[^\d]", version) if v.isdigit()])
if version < (0, 11, 2):
print "Your Cython version is too old"
raise ImportError
except ImportError:
print "No Cython, will compile from .c files"
for cmd in ['cython', 'pyrexc', 'predist']:
if cmd in sys.argv:
print "'%s' not available without Cython" % cmd
sys.exit(1)
from distutils.extension import Extension
pyrex_suffix = ".c"
else:
from Cython.Distutils import build_ext
from Cython.Distutils.extension import Extension
pyrex_suffix = ".pyx"
class build_wrappers(build_ext):
# for predist, make .c files
def run(self):
self.compiler = NullCompiler()
# skip build_ext.run() and thus ccompiler setup
build_ext.build_extensions(self)
class build_wrappers_and_html(build_wrappers):
def run(self):
build_wrappers.run(self)
build_html()
distutils_extras["cmdclass"] = {
'build_ext': build_ext,
'pyrexc': build_wrappers,
'cython': build_wrappers,
'predist': build_wrappers_and_html}
# predist python setup.py predist --inplace --force, this is in _darcs/prefs/prefs for instructing darcs predist to execute the subsequent, predist is a darcs word
# Save some repetitive typing. We have all compiled
# modules in place with their python siblings.
def CogentExtension(module_name, extra_compile_args=[], **kw):
path = module_name.replace('.', '/')
kw['extra_compile_args'] = pyrex_compile_options + extra_compile_args
if pyrex_suffix == '.pyx':
kw['pyrex_include_dirs'] = [include_path]
return Extension(module_name, [path + pyrex_suffix], **kw)
short_description = "COmparative GENomics Toolkit"
# This ends up displayed by the installer
long_description = """Cogent
A toolkit for statistical analysis of biological sequences.
Version %s.
""" % __version__
setup(
name="cogent",
version=__version__,
url="http://sourceforge.net/projects/pycogent",
author="Gavin Huttley, Rob Knight",
author_email="gavin.huttley@anu.edu.au, rob@spot.colorado.edu",
description=short_description,
long_description=long_description,
platforms=["any"],
license=["GPL"],
keywords=["biology", "genomics", "statistics", "phylogeny", "evolution",
"bioinformatics"],
classifiers=[
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: GNU General Public License (GPL)",
"Topic :: Scientific/Engineering :: Bio-Informatics",
"Topic :: Software Development :: Libraries :: Python Modules",
"Operating System :: OS Independent",
],
packages=['cogent', 'cogent.align', 'cogent.align.weights', 'cogent.app',
'cogent.cluster', 'cogent.core', 'cogent.data', 'cogent.db',
'cogent.db.ensembl', 'cogent.draw',
'cogent.evolve', 'cogent.format', 'cogent.maths',
'cogent.maths.matrix', 'cogent.maths.stats',
'cogent.maths.stats.cai', 'cogent.maths.unifrac',
'cogent.maths.spatial', 'cogent.motif', 'cogent.parse',
'cogent.phylo', 'cogent.recalculation', 'cogent.seqsim',
'cogent.struct', 'cogent.util'],
ext_modules=[
CogentExtension("cogent.align._compare"),
CogentExtension("cogent.align._pairwise_seqs"),
CogentExtension("cogent.align._pairwise_pogs"),
CogentExtension("cogent.evolve._solved_models"),
CogentExtension("cogent.evolve._likelihood_tree"),
CogentExtension("cogent.evolve._pairwise_distance"),
CogentExtension("cogent.struct._asa"),
CogentExtension("cogent.struct._contact"),
CogentExtension("cogent.maths._period"),
CogentExtension("cogent.maths.spatial.ckd3"),
],
**distutils_extras
)
PyCogent-1.5.3/tests/ 000755 000765 000024 00000000000 12024703635 015404 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/__init__.py 000644 000765 000024 00000001204 12024702176 017511 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
sub_modules = ['alltests',
'benchmark',
'benchmark_aligning',
'test_draw',
'test_phylo',
'timetrial']
for sub_module in sub_modules:
exec ("from %s import %s" % (__name__, sub_module))
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell", "Gavin Huttley", "Rob Knight",
"Matthew Wakefield", "Andrew Butterfield", "Edward Lang"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
PyCogent-1.5.3/tests/alltests.py 000644 000765 000024 00000031543 12024702176 017616 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
#
# suite of cogent package unit tests.
# run suite by executing this file
#
import doctest, cogent.util.unit_test as unittest, sys, os
from cogent.util.misc import app_path
__author__ = "Peter Maxwell and Gavin Huttley"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell", "Gavin Huttley", "Rob Knight",
"Hau Ying", "Helen Lindsay", "Jeremy Widmann",
"Sandra Smit", "Greg Caporaso", "Matthew Wakefield"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
def my_import(name):
"""Imports a module, possibly qualified with periods. Returns the module.
__import__ only imports the top-level module.
Recipe from python documentation at:
http://www.python.org/doc/2.4/lib/built-in-funcs.html
"""
mod = __import__(name)
components = name.split('.')
for comp in components[1:]:
mod = getattr(mod, comp)
return mod
def module_present(modules):
"""returns True if dependencies present"""
if type(modules) == str:
modules = [modules]
try:
for module in modules:
mod = __import__(module)
except ImportError:
return False
return True
def suite():
modules_to_test = [
'test_recalculation.rst',
'test_phylo',
'test_dictarray.rst',
'test_align.test_align',
'test_align.test_algorithm',
'test_align.test_weights.test_methods',
'test_align.test_weights.test_util',
'test_app.test_parameters',
'test_app.test_util',
'test_cluster.test_goodness_of_fit',
'test_cluster.test_metric_scaling',
'test_cluster.test_approximate_mds',
'test_cluster.test_procrustes',
'test_cluster.test_UPGMA',
'test_cluster.test_nmds',
'test_core.test_alphabet',
'test_core.test_alignment',
'test_core.test_annotation',
'test_core.test_bitvector',
'test_core.test_core_standalone',
'test_core.test_features.rst',
'test_core.test_entity',
'test_core.test_genetic_code',
'test_core.test_info',
'test_core.test_location',
'test_core.test_maps',
'test_core.test_moltype',
'test_core.test_profile',
'test_core.test_seq_aln_integration',
'test_core.test_sequence',
'test_core.test_tree',
'test_core.test_usage',
'test_data.test_molecular_weight',
'test_evolve.test_best_likelihood',
'test_evolve.test_bootstrap',
'test_evolve.test_coevolution',
'test_evolve.test_models',
'test_evolve.test_motifchange',
'test_evolve.test_substitution_model',
'test_evolve.test_scale_rules',
'test_evolve.test_likelihood_function',
'test_evolve.test_newq',
'test_evolve.test_pairwise_distance',
'test_evolve.test_parameter_controller',
'test_format.test_bedgraph',
'test_format.test_fasta',
'test_format.test_mage',
'test_format.test_pdb_color',
'test_format.test_xyzrn',
'test_maths.test_fit_function',
'test_maths.test_geometry',
'test_maths.test_matrix_logarithm',
'test_maths.test_period',
'test_maths.test_matrix.test_distance',
'test_maths.test_spatial.test_ckd3',
'test_maths.test_stats.test_alpha_diversity',
'test_maths.test_stats.test_distribution',
'test_maths.test_stats.test_histogram',
'test_maths.test_stats.test_information_criteria',
'test_maths.test_stats.test_period',
'test_maths.test_stats.test_special',
'test_maths.test_stats.test_test',
'test_maths.test_stats.test_ks',
'test_maths.test_stats.test_rarefaction',
'test_maths.test_stats.test_util',
'test_maths.test_stats.test_cai.test_adaptor',
'test_maths.test_stats.test_cai.test_get_by_cai',
'test_maths.test_stats.test_cai.test_util',
'test_maths.test_optimisers',
'test_maths.test_distance_transform',
'test_maths.test_unifrac.test_fast_tree',
'test_maths.test_unifrac.test_fast_unifrac',
'test_motif.test_util',
'test_parse.test_aaindex',
'test_parse.test_agilent_microarray',
'test_parse.test_binary_sff',
'test_parse.test_blast',
'test_parse.test_bowtie',
'test_parse.test_bpseq',
'test_parse.test_cigar',
'test_parse.test_clustal',
'test_parse.test_column',
'test_parse.test_comrna',
'test_parse.test_consan',
'test_parse.test_cove',
'test_parse.test_ct',
'test_parse.test_cut',
'test_parse.test_cutg',
'test_parse.test_dialign',
'test_parse.test_ebi',
'test_parse.test_fasta',
'test_parse.test_fastq',
'test_parse.test_gbseq',
'test_parse.test_gibbs',
'test_parse.test_genbank',
'test_parse.test_gff',
'test_parse.test_greengenes',
'test_parse.test_ilm',
'test_parse.test_illumina_sequence',
'test_parse.test_locuslink',
'test_parse.test_mage',
'test_parse.test_meme',
'test_parse.test_msms',
'test_parse.test_ncbi_taxonomy',
'test_parse.test_nexus',
'test_parse.test_nupack',
'test_parse.test_pdb',
'test_parse.test_psl',
'test_parse.test_structure',
'test_parse.test_pamlmatrix',
'test_parse.test_phylip',
'test_parse.test_pknotsrg',
'test_parse.test_rdb',
'test_parse.test_record',
'test_parse.test_record_finder',
'test_parse.test_rfam',
'test_parse.test_rnaalifold',
'test_parse.test_rna_fold',
'test_parse.test_rnaview',
'test_parse.test_rnaforester',
'test_parse.test_sprinzl',
'test_parse.test_tinyseq',
'test_parse.test_tree',
'test_parse.test_unigene',
'test_seqsim.test_analysis',
'test_seqsim.test_birth_death',
'test_seqsim.test_markov',
'test_seqsim.test_microarray',
'test_seqsim.test_microarray_normalize',
'test_seqsim.test_randomization',
'test_seqsim.test_searchpath',
'test_seqsim.test_sequence_generators',
'test_seqsim.test_tree',
'test_seqsim.test_usage',
'test_struct.test_knots',
'test_struct.test_pairs_util',
'test_struct.test_rna2d',
'test_struct.test_asa',
'test_struct.test_contact',
'test_struct.test_annotation',
'test_struct.test_selection',
'test_struct.test_manipulation',
'test_util.test_unit_test',
'test_util.test_array',
'test_util.test_dict2d',
'test_util.test_misc',
'test_util.test_organizer',
'test_util.test_recode_alignment',
'test_util.test_table.rst',
'test_util.test_transform',
]
try:
import matplotlib
except:
print >> sys.stderr, "No matplotlib so not running test_draw.py"
else:
modules_to_test.append('test_draw')
modules_to_test.append('test_draw.test_distribution_plots')
#Try importing modules for app controllers
apps = [('formatdb', 'test_formatdb'),
('blastall', 'test_blast'),
('blat', 'test_blat'),
('bwa', 'test_bwa'),
('carnac', 'test_carnac'),
('clearcut', 'test_clearcut'),
('clustalw', 'test_clustalw'),
('cmalign', 'test_infernal'),
('cmfinder.pl', 'test_cmfinder'),
('comrna', 'test_comrna'),
('contrafold', 'test_contrafold'),
('covea', 'test_cove'),
('dialign2-2', 'test_dialign'),
('dynalign', 'test_dynalign'),
('FastTree', 'test_fasttree'),
('foldalign', 'test_foldalign'),
('guppy', 'test_guppy'),
('ilm', 'test_ilm'),
('knetfold.pl', 'test_knetfold'),
('mafft', 'test_mafft'),
('mfold', 'test_mfold'),
('mothur', 'test_mothur'),
('muscle', 'test_muscle_v38'),
('msms', 'test_msms'),
('ParsInsert', 'test_parsinsert'),
('pplacer', 'test_pplacer'),
('rdp_classifier-2.2.jar', 'test_rdp_classifier'),
('rdp_classifier-2.0.jar', 'test_rdp_classifier20'),
('Fold.out', 'test_nupack'),
('findphyl', 'test_pfold'),
('pknotsRG-1.2-i386-linux-static', 'test_pknotsrg'),
('RNAalifold', 'test_rnaalifold'),
('rnaview', 'test_rnaview'),
('RNAfold', 'test_vienna_package'),
('raxmlHPC', 'test_raxml_v730'),
('rtax', 'test_rtax'),
('sfold.X86_64.LINUX', 'test_sfold'),
('stride', 'test_stride'),
('hybrid-ss-min', 'test_unafold'),
('cd-hit', 'test_cd_hit'),
('calculate_likelihood', 'test_gctmpca'),
('sfffile', 'test_sfffile'),
('sffinfo', 'test_sffinfo'),
('uclust','test_uclust'),
('usearch','test_usearch')
]
for app, test_name in apps:
should_run_test = False
if app_path(app):
should_run_test = True
elif app.startswith('rdp_classifier') and os.environ.get('RDP_JAR_PATH'):
# This is ugly, but because this is a jar file, it won't be in
# $PATH -- we require users to set an environment variable to
# point to the location of this jar file, so we test for that.
# My new version of app_path can be applied to do smarter checks,
# but will involve some re-write of how we check whether tests can
# be run. -Greg
if app == os.path.basename(os.environ.get('RDP_JAR_PATH')):
should_run_test = True
if should_run_test:
modules_to_test.append('test_app.' + test_name)
else:
print >> sys.stderr, "Can't find %s executable: skipping test" % app
if app_path('muscle'):
modules_to_test.append('test_format.test_pdb_color')
# we now toggle the db tests, based on an environment flag
if int(os.environ.get('TEST_DB', 0)):
db_tests = ['test_db.test_ncbi', 'test_db.test_pdb',
'test_db.test_rfam', 'test_db.test_util']
# we check for an environment flag for ENSEMBL
# we expect this to have the username and account for a localhost
# installation of the Ensembl MySQL databases
if 'ENSEMBL_ACCOUNT' in os.environ:
# check for cogent.db.ensembl dependencies
test_ensembl = True
for module in ['MySQLdb', 'sqlalchemy']:
if not module_present(module):
test_ensembl = False
print >> sys.stderr, \
"Module '%s' not present: skipping test" % module
if test_ensembl:
db_tests += ['test_db.test_ensembl.test_assembly',
'test_db.test_ensembl.test_database',
'test_db.test_ensembl.test_compara',
'test_db.test_ensembl.test_genome',
'test_db.test_ensembl.test_host',
'test_db.test_ensembl.test_metazoa',
'test_db.test_ensembl.test_species',
'test_db.test_ensembl.test_feature_level']
else:
print >> sys.stderr, "Environment variable ENSEMBL_ACCOUNT not "\
"set: skipping db.ensembl tests"
for db_test in db_tests:
modules_to_test.append(db_test)
else:
print >> sys.stderr, \
"Environment variable TEST_DB=1 not set: skipping db tests"
assert sys.version_info >= (2, 6)
alltests = unittest.TestSuite()
for module in modules_to_test:
if module.endswith('.rst'):
module = os.path.join(*module.split(".")[:-1]) + ".rst"
test = doctest.DocFileSuite(module, optionflags=
doctest.REPORT_ONLY_FIRST_FAILURE |
doctest.ELLIPSIS)
else:
test = unittest.findTestCases(my_import(module))
alltests.addTest(test)
return alltests
class BoobyTrappedStream(object):
def __init__(self, output):
self.output = output
def write(self, text):
self.output.write(text)
raise RuntimeError, "Output not allowed in tests"
def flush(self):
pass
def isatty(self):
return False
if __name__ == '__main__':
if '--debug' in sys.argv:
s = suite()
s.debug()
else:
orig = sys.stdout
if '--output-ok' in sys.argv:
sys.argv.remove('--output-ok')
else:
sys.stdout = BoobyTrappedStream(orig)
try:
unittest.main(defaultTest='suite', argv=sys.argv)
finally:
sys.stdout = orig
PyCogent-1.5.3/tests/benchmark.py 000644 000765 000024 00000012073 12024702176 017712 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import sys #,hotshot
from cogent.evolve.substitution_model import Nucleotide, Dinucleotide, Codon
from cogent import LoadSeqs, LoadTree
from cogent.maths import optimisers
from cogent.util import parallel
__author__ = "Peter Maxwell and Gavin Huttley"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell", "Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
ALIGNMENT = LoadSeqs(filename="data/brca1.fasta")
TREE = LoadTree(filename="data/murphy.tree")
def subtree(size):
names = ALIGNMENT.getSeqNames()[:size]
assert len(names) == size
tree = TREE.getSubTree(names) #.balanced()
return names, tree
def brca_test(subMod, names, tree, length, par_rules, **kw):
#names = ALIGNMENT.getSeqNames()[:taxa]
#assert len(names) == taxa
tree = TREE.getSubTree(names) #.balanced()
aln = ALIGNMENT.takeSeqs(names).omitGapPositions()[:length]
assert len(aln) == length, (len(aln), length)
#the_tree_analysis = LikelihoodFunction(treeobj = tree, submodelobj = subMod, alignobj = aln)
par_controller = subMod.makeParamController(tree, **kw)
for par_rule in par_rules:
par_controller.setParamRule(**par_rule)
#lf = par_controller.makeCalculator(aln)
return (par_controller, aln)
def measure_evals_per_sec(pc, aln):
pc.setAlignment(aln)
return pc.measureEvalsPerSecond(time_limit=2.0, wall=False)
def makePC(modelClass, parameterisation, length, taxa, tree, opt_mprobs, **kw):
modelClass = eval(modelClass)
if parameterisation is not None:
predicates = {'silly': silly_predicate}
par_rules = [{'par_name':'silly', 'is_independent':parameterisation}]
else:
predicates = {}
par_rules = []
subMod = modelClass(equal_motif_probs=True, optimise_motif_probs=opt_mprobs,
predicates=predicates, recode_gaps=True, mprob_model="conditional")
(pc, aln) = brca_test(subMod, taxa, tree, length, par_rules, **kw)
return (pc, aln)
def quiet(f, *args, **kw):
import sys, cStringIO
temp = cStringIO.StringIO()
_stdout = sys.stdout
try:
sys.stdout = temp
result = f(*args, **kw)
finally:
#pass
sys.stdout = _stdout
return result
def evals_per_sec(*args):
pc, aln = makePC(*args) #quiet(makeLF, *args)
speed1 = measure_evals_per_sec(pc, aln)
speed = str(int(speed1))
return speed
class CompareImplementations(object):
def __init__(self, switch):
self.switch = switch
def __call__(self, *args):
self.switch(0)
(pc,aln) = quiet(makePC, *args)
speed1 = measure_evals_per_sec(pc,aln)
self.switch(1)
(pc,aln) = quiet(makePC, *args)
speed2 = measure_evals_per_sec(pc,aln)
if speed1 < speed2:
speed = '+%2.1f' % (speed2/speed1)
else:
speed = '-%2.1f' % (speed1/speed2)
if speed in ['+1.0', '-1.0']:
speed = ''
return speed
def benchmarks(test):
alphabets = ["Nucleotide", "Dinucleotide", "Codon"]
sequence_lengths = [18, 2004]
treesizes = [5, 20]
for (optimise_motifs, parameterisation) in [
(False, 'global'), (False, 'local'), (True, 'global')]:
print parameterisation, ['', 'opt motifs'][optimise_motifs]
print ' ' * 14,
wcol = 5*len(sequence_lengths) + 2
for alphabet in alphabets:
print str(alphabet).ljust(wcol),
print
print '%-15s' % "", # "length"
for alphabet in alphabets:
for sequence_length in sequence_lengths:
print "%4s" % sequence_length,
print ' ',
print
print ' '*12 + (' | '.join(['']+['-'*(len(sequence_lengths)*5) for alphabet in alphabets]+['']))
for treesize in treesizes:
print ("%4s taxa | " % treesize),
(taxa, tree) = subtree(treesize)
for alphabet in alphabets:
for sequence_length in sequence_lengths:
speed = test(alphabet, parameterisation=='local',
sequence_length, taxa, tree, optimise_motifs)
print "%4s" % speed,
print '| ',
print
print
print
def silly_predicate(a,b):
return a.count('A') > a.count('T') or b.count('A') > b.count('T')
#def asym_predicate((a,b)):
# print a, b, 'a' in a
# return 'a' in a
#mA = Codon()
#mA.setPredicates({'asym': asym_predicate})
def exponentiator_switch(switch):
import cogent.evolve.substitution_calculation
cogent.evolve.substitution_calculation.use_new = switch
import sys
if 'relative' in sys.argv:
test = CompareImplementations(exponentiator_switch)
else:
test = evals_per_sec
parallel.inefficiency_forgiven = True
if parallel.getCommunicator().Get_rank() > 0:
#benchmarks(test)
quiet(benchmarks, test)
else:
try:
benchmarks(test)
except KeyboardInterrupt:
print ' OK'
PyCogent-1.5.3/tests/benchmark_aligning.py 000644 000765 000024 00000002334 12024702176 021561 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import numpy
import time
from cogent import DNA
from cogent.align.align import classic_align_pairwise, make_dna_scoring_dict
__author__ = "Peter Maxwell"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Peter Maxwell"
__email__ = "pm67nz@gmail.com"
__status__ = "Production"
def _s2i(s):
return numpy.array(['ATCG'.index(c) for c in s])
def test(r=1, **kw):
S = make_dna_scoring_dict(10, -1, -8)
seq2 = DNA.makeSequence('AAAATGCTTA' * r)
seq1 = DNA.makeSequence('AATTTTGCTG' * r)
t0 = time.time()
aln = classic_align_pairwise(seq1, seq2, S, 10, 2, local=False, **kw)
t = time.time() - t0
return (len(seq1)*len(seq2))/t
print t
if __name__ == '__main__':
d = 2
e = 1
options = [(False, False), (True, False), (False, True)]
template = "%10s " * 4
print " 1000s positions per second"
print template % ("size", "simple", "logs", "scaled")
for r in [50, 100, 200, 500]:
times = [test(r, use_logs=l, use_scaling=s) for (l,s) in options]
print template % tuple([r*10] + [int(t/1000) for t in times])
PyCogent-1.5.3/tests/data/ 000755 000765 000024 00000000000 12024703634 016314 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_align/ 000755 000765 000024 00000000000 12024703632 017532 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_app/ 000755 000765 000024 00000000000 12024703632 017220 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_cluster/ 000755 000765 000024 00000000000 12024703632 020121 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_core/ 000755 000765 000024 00000000000 12024703632 017370 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_data/ 000755 000765 000024 00000000000 12024703633 017352 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_db/ 000755 000765 000024 00000000000 12024703632 017025 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_dictarray.rst 000644 000765 000024 00000002302 11634002704 021147 0 ustar 00jrideout staff 000000 000000 >>> import numpy
>>> from cogent import DNA
>>> from cogent.util.dict_array import DictArrayTemplate
>>> a = numpy.identity(3, int)
>>> b = DictArrayTemplate('abc', 'ABC').wrap(a)
>>> b[0]
===========
A B C
-----------
1 0 0
-----------
>>> b['a']
===========
A B C
-----------
1 0 0
-----------
>>> b.keys()
['a', 'b', 'c']
>>> row = b['a']
>>> row.keys()
['A', 'B', 'C']
>>> list(row)
[1, 0, 0]
>>> sum(row)
1
>>> # Dimensions can also be ordinay integers
>>> b = DictArrayTemplate(3, 3).wrap(a)
>>> b.keys()
[0, 1, 2]
>>> b[0].keys()
[0, 1, 2]
>>> sum(b[0])
1
>>> # Or a mix
>>> b = DictArrayTemplate('ABC', 3).wrap(a)
>>> b.keys()
['A', 'B', 'C']
>>> b['A'].keys()
[0, 1, 2]
``DictArray`` should work properly in ``numpy`` operations.
>>> darr = DictArrayTemplate(list(DNA), list(DNA)).wrap([[.7,.1,.1,.1],
... [.1,.7,.1,.1],
... [.1,.1,.7,.1],
... [.1,.1,.1,.7]])
>>> mprobs = numpy.array([0.25, 0.25, 0.25, 0.25])
>>> print mprobs.dot(darr)
[ 0.25 0.25 0.25 0.25]
>>> print numpy.dot(mprobs, darr)
[ 0.25 0.25 0.25 0.25]
PyCogent-1.5.3/tests/test_draw/ 000755 000765 000024 00000000000 12024703633 017376 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_draw.py 000644 000765 000024 00000024321 12024702176 017753 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""This script/module can do any of 5 different actions with the figures it makes.
When run as a script, one of the actions must be specified:
- exercise
The default when used as a module. Drawing code is used to make a
matplotlib figure object but that is all.
- record
Save PNG images of the figures in draw_results/baseline/
To be used before making changes in drawing code.
- check
Compare figures with saved baseline figures. Fail if they don't match.
Failed figures are saved in draw_results/current. Also makes an HTML
page comparing them with the baseline images.
- compare
Save ALL differing figures in draw_results/current and make HTML page
comparing them with the baseline images.
- view
Save all differing figures in draw_results/current and make HTML page
comparing them with the baseline images, along with all the matching
figures too.
"""
import warnings
warnings.filterwarnings('ignore', category=UserWarning, module='matplotlib')
import matplotlib
matplotlib.use('Agg')
import unittest
import sys, os, cStringIO
from cogent import DNA, LoadTree, LoadSeqs
from cogent.core import alignment, alphabet, annotation
from cogent.draw.linear import *
from cogent.draw.dendrogram import *
from cogent.draw.compatibility import partimatrix
__author__ = "Peter Maxwell"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell", "Gavin Huttley", "Rob Knight",
"Matthew Wakefield"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
def file_for_test(msg, baseline=False, prefixed=True):
file_ext = "png"
dirname = 'baseline' if baseline else 'current'
if prefixed:
dirname = os.path.join('draw_results', dirname)
fname = msg.replace(' ', '_') + '.' + file_ext
return os.path.join(dirname, fname)
def fig2png(fig):
f = cStringIO.StringIO()
fig.savefig(f, format='png')
return f.getvalue()
def writefile(fname, content):
dirname = os.path.dirname(fname)
if not os.path.exists(dirname):
os.makedirs(dirname)
f = open(fname, 'wb')
f.write(content)
f.close()
def exercise(msg, fig):
pass
def record(msg, fig):
png = fig2png(fig)
fname = file_for_test(msg, True)
writefile(fname, png)
class CheckOutput(object):
def __init__(self, failOnDifference=True, showAll=False):
if not os.path.exists('draw_results/baseline'):
raise RuntimeError(
'No baseline found. Run "test_draw.py record" first')
self.results = []
self.failOnDifference = failOnDifference
self.showAll = showAll
self.anyFailures = False
def __call__(self, msg, fig):
fname = file_for_test(msg, True)
observed = fig2png(fig)
if os.path.exists(fname):
expected = open(fname, 'rb').read()
different = observed != expected
self.results.append((msg, different))
if different:
self.anyFailures = True
writefile(file_for_test(msg, False), observed)
if self.failOnDifference:
raise AssertionError('See draw_results/comparison.html')
else:
print 'difference from', fname
else:
raise RuntimeError('No baseline image at %s' % fname)
def writeHTML(self):
html = ['Drawing Test Output ',
'']
html.append('%s figures of which %s differ from baseline' % (
len(self.results), sum(d for (m,d) in self.results)))
for (msg, different) in self.results:
fn1 = file_for_test(msg, True, False)
fn2 = file_for_test(msg, False, False)
if different:
html.append('
%s ' % msg)
html.append('Old ')
html.append('New ')
html.append('%s ' % msg)
html.append('%s
' % msg)
html.append('
continued: My Title
=====================================
edge.name x y
-------------------------------------
Human 1.0000 3.0000
HowlerMon 1.0000 3.0000
Mouse 1.0000 3.0000
NineBande 1.0000 3.0000
DogFaced 1.0000 3.0000
edge.0 1.0000 3.0000
edge.1 1.0000 3.0000
-------------------------------------
continued: My Title
=======================
edge.name z
-----------------------
Human 6.0000
HowlerMon 6.0000
Mouse 6.0000
NineBande 6.0000
DogFaced 6.0000
edge.0 6.0000
edge.1 6.0000
-----------------------
Legend: this is a nonsense example.
In the above we specify a maximum width of the table, and also specify row identifiers (using ``row_ids``, the integer corresponding to the column at which data begin, preceding columns are taken as the identifiers). This has the effect of forcing the table to wrap when the simple text format is used, but wrapping does not occur for any other format. The ``row_ids`` are keys for slicing the table by row, and as identifiers are presented in each wrapped sub-table.
Wrapping generate neat looking tables whether or not you index the table rows. We demonstrate here
.. doctest::
>>> from cogent import LoadTable
>>> h = ['A/C', 'A/G', 'A/T', 'C/A']
>>> rows = [[0.0425, 0.1424, 0.0226, 0.0391]]
>>> wrap_table = LoadTable(header=h, rows=rows, max_width=30)
>>> print wrap_table
==============================
A/C A/G A/T
------------------------------
0.0425 0.1424 0.0226
------------------------------
continued:
==========
C/A
----------
0.0391
----------
>>> wrap_table = LoadTable(header=h, rows=rows, max_width=30,
... row_ids=True)
>>> print wrap_table
==========================
A/C A/G A/T
--------------------------
0.0425 0.1424 0.0226
--------------------------
continued:
================
A/C C/A
----------------
0.0425 0.0391
----------------
We can also customise the formatting of individual columns.
.. doctest::
>>> rows = (('NP_003077_hs_mm_rn_dna', 'Con', 2.5386013224378985),
... ('NP_004893_hs_mm_rn_dna', 'Con', 0.12135142635634111e+06),
... ('NP_005079_hs_mm_rn_dna', 'Con', 0.95165949788861326e+07),
... ('NP_005500_hs_mm_rn_dna', 'Con', 0.73827030202664901e-07),
... ('NP_055852_hs_mm_rn_dna', 'Con', 1.0933217708952725e+07))
We first create a table and show the default formatting behaviour for ``Table``.
.. doctest::
>>> t46 = Table(['Gene', 'Type', 'LR'], rows)
>>> print t46
===============================================
Gene Type LR
-----------------------------------------------
NP_003077_hs_mm_rn_dna Con 2.5386
NP_004893_hs_mm_rn_dna Con 121351.4264
NP_005079_hs_mm_rn_dna Con 9516594.9789
NP_005500_hs_mm_rn_dna Con 0.0000
NP_055852_hs_mm_rn_dna Con 10933217.7090
-----------------------------------------------
We then format the ``LR`` column to use a scientific number format.
.. doctest::
>>> t46 = Table(['Gene', 'Type', 'LR'], rows)
>>> t46.setColumnFormat('LR', "%.4e")
>>> print t46
============================================
Gene Type LR
--------------------------------------------
NP_003077_hs_mm_rn_dna Con 2.5386e+00
NP_004893_hs_mm_rn_dna Con 1.2135e+05
NP_005079_hs_mm_rn_dna Con 9.5166e+06
NP_005500_hs_mm_rn_dna Con 7.3827e-08
NP_055852_hs_mm_rn_dna Con 1.0933e+07
--------------------------------------------
It is safe to directly modify certain attributes, such as the title, legend and white space separating columns, which we do for the ``t46``.
.. doctest::
>>> t46.Title = "A new title"
>>> t46.Legend = "A new legend"
>>> t46.Space = ' '
>>> print t46
A new title
========================================
Gene Type LR
----------------------------------------
NP_003077_hs_mm_rn_dna Con 2.5386e+00
NP_004893_hs_mm_rn_dna Con 1.2135e+05
NP_005079_hs_mm_rn_dna Con 9.5166e+06
NP_005500_hs_mm_rn_dna Con 7.3827e-08
NP_055852_hs_mm_rn_dna Con 1.0933e+07
----------------------------------------
A new legend
We can provide settings for multiple columns.
.. doctest::
>>> t3 = Table(['edge.name', 'edge.parent', 'length', 'x', 'y', 'z'], d2D,
... row_order = row_order)
>>> t3.setColumnFormat('x', "%.1e")
>>> t3.setColumnFormat('y', "%.2f")
>>> print t3
===============================================================
edge.name edge.parent length x y z
---------------------------------------------------------------
Human edge.0 4.0000 1.0e+00 3.00 6.0000
HowlerMon edge.0 4.0000 1.0e+00 3.00 6.0000
Mouse edge.1 4.0000 1.0e+00 3.00 6.0000
NineBande root 4.0000 1.0e+00 3.00 6.0000
DogFaced root 4.0000 1.0e+00 3.00 6.0000
edge.0 edge.1 4.0000 1.0e+00 3.00 6.0000
edge.1 root 4.0000 1.0e+00 3.00 6.0000
---------------------------------------------------------------
In some cases, the contents of a column can be of different types. In this instance, rather than passing a column template we pass a reference to a function that will handle this complexity. To illustrate this we will define a function that formats floating point numbers, but returns everything else as is.
.. doctest::
>>> def formatcol(value):
... if isinstance(value, float):
... val = "%.2f" % value
... else:
... val = str(value)
... return val
We apply this to a table with mixed string, integer and floating point data.
.. doctest::
>>> t6 = Table(['ColHead'], [['a'], [1], [0.3], ['cc']],
... column_templates = dict(ColHead=formatcol))
>>> print t6
=======
ColHead
-------
a
1
0.30
cc
-------
Representation of tables
^^^^^^^^^^^^^^^^^^^^^^^^
The representation formatting provides a quick overview of a table's dimensions and it's contents. We show this for a table with 3 columns and multiple rows
.. doctest::
>>> t46
Table(numrows=5, numcols=3, header=['Gene', 'Type', 'LR'], rows=[['NP_003077_hs_mm_rn_dna', 'Con', 2.5386],..])
and larger
.. doctest::
>>> t3
Table(numrows=7, numcols=6, header=['edge.name', 'edge.parent', 'length',..], rows=[['Human', 'edge.0', 4.0000,..],..])
.. note:: within a script use ``print repr(t3)`` to get the same representation.
Table output
------------
Table can output in multiple formats, including restructured text or 'rest' and delimited. These can be obtained using the ``tostring`` method and ``format`` argument as follows. Using table ``t`` from above,
.. doctest::
>>> print t.tostring(format='rest')
+------------------------------+
| Journal impact factors |
+---------------------+--------+
| Journal | Impact |
+=====================+========+
| INT J PARASITOL | 2.90 |
+---------------------+--------+
| J MED ENTOMOL | 1.40 |
+---------------------+--------+
| Med Vet Entomol | 1.00 |
+---------------------+--------+
| INSECT MOL BIOL | 2.85 |
+---------------------+--------+
| J AM MOSQUITO CONTR | 0.81 |
+---------------------+--------+
| MOL PHYLOGENET EVOL | 2.80 |
+---------------------+--------+
| HEREDITY | 1.99 |
+---------------------+--------+
| AM J TROP MED HYG | 2.10 |
+---------------------+--------+
| MIL MED | 0.60 |
+---------------------+--------+
| MED J AUSTRALIA | 1.74 |
+---------------------+--------+
| From ISI |
+------------------------------+
Arguments such as ``space`` have no effect in this case. The table may also be written to file in any of the available formats (latex, simple text, html, pickle) or using a custom separator (such as a comma or tab). This makes it convenient to get data into other applications (such as R or a spreadsheet program).
Here is the latex format, note how the title and legend are joined into the latex table caption. We also provide optional arguments for the column alignment (fist column left aligned, second column right aligned and remaining columns centred) and a label for table referencing.
.. doctest::
>>> print t3.tostring(format='tex', justify="lrcccc", label="table:example")
\begin{longtable}[htp!]{ l r c c c c }
\hline
\bf{edge.name} & \bf{edge.parent} & \bf{length} & \bf{x} & \bf{y} & \bf{z} \\
\hline
\hline
Human & edge.0 & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
HowlerMon & edge.0 & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
Mouse & edge.1 & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
NineBande & root & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
DogFaced & root & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
edge.0 & edge.1 & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
edge.1 & root & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
\hline
\label{table:example}
\end{longtable}
More complex latex table justifying is also possible. Specifying the width of individual columns requires passing in a series (list or tuple) of justification commands. In the following we introduce the command for specific columns widths.
.. doctest::
>>> print t3.tostring(format='tex', justify=["l","p{3cm}","c","c","c","c"])
\begin{longtable}[htp!]{ l p{3cm} c c c c }
\hline
\bf{edge.name} & \bf{edge.parent} & \bf{length} & \bf{x} & \bf{y} & \bf{z} \\
\hline
\hline
Human & edge.0 & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
HowlerMon & edge.0 & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
Mouse & edge.1 & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
NineBande & root & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
DogFaced & root & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
edge.0 & edge.1 & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
edge.1 & root & 4.0000 & 1.0e+00 & 3.00 & 6.0000 \\
\hline
\end{longtable}
>>> print t3.tostring(sep=',')
edge.name,edge.parent,length, x, y, z
Human, edge.0,4.0000,1.0e+00,3.00,6.0000
HowlerMon, edge.0,4.0000,1.0e+00,3.00,6.0000
Mouse, edge.1,4.0000,1.0e+00,3.00,6.0000
NineBande, root,4.0000,1.0e+00,3.00,6.0000
DogFaced, root,4.0000,1.0e+00,3.00,6.0000
edge.0, edge.1,4.0000,1.0e+00,3.00,6.0000
edge.1, root,4.0000,1.0e+00,3.00,6.0000
You can specify any standard text character that will work with your desired target. Useful separators are tabs ('\\t'), or pipes ('\|'). If ``Table`` encounters any of these characters within a cell, it wraps the cell in quotes -- a standard approach to facilitate import by other applications. We will illustrate this with ``t2``.
.. doctest::
>>> print t2.tostring(sep=', ')
abcd, data
"[1, 2, 3, 4, 5]", 0
x, 5.0000
y, *
Note that I introduced an extra space after the column just to make the result more readable in this example.
Test the writing of phylip distance matrix format.
.. doctest::
>>> rows = [['a', '', 0.088337278874079342, 0.18848582712597683,
... 0.44084000179091454], ['c', 0.088337278874079342, '',
... 0.088337278874079342, 0.44083999937417828], ['b', 0.18848582712597683,
... 0.088337278874079342, '', 0.44084000179090932], ['e',
... 0.44084000179091454, 0.44083999937417828, 0.44084000179090932, '']]
>>> header = ['seq1/2', 'a', 'c', 'b', 'e']
>>> dist = Table(rows = rows, header = header,
... row_ids = True)
>>> print dist.tostring(format = 'phylip')
4
a 0.0000 0.0883 0.1885 0.4408
c 0.0883 0.0000 0.0883 0.4408
b 0.1885 0.0883 0.0000 0.4408
e 0.4408 0.4408 0.4408 0.0000
The ``tostring`` method also provides generic html generation via the restructured text format. The ``toRichHtmlTable`` method can be used to generate the html table element by itself, with greater control over formatting. Specifically, users can provide custom callback functions to the ``row_cell_func`` and ``header_cell_func`` arguments to control in detail the formatting of table elements, or use the simpler dictionary based ``element_formatters`` approach. We use the above ``dist`` table to provide a specific callback that will set the background color for diagonal cells. We first write a function that takes the cell value and coordinates, returning the html formmatted text.
.. doctest::
>>> def format_cell(value, row_num, col_num):
... bgcolor=['', ' bgcolor="#0055ff"'][value=='']
... return '%s' % (bgcolor, value)
We then call the method, without this argument, then with it.
.. doctest::
>>> straight_html = dist.toRichHtmlTable()
>>> print straight_html
seq1/2 a...
>>> rich_html = dist.toRichHtmlTable(row_cell_func=format_cell,
... compact=False)
>>> print rich_html
seq1/2
a
c
b
e
a
0.0883 ...
Exporting bedGraph format
-------------------------
One export format available is bedGraph_. This format can be used for viewing data as annotation track in a genome browser. This format allows for unequal spans and merges adjacent spans with the same value. The format has many possible arguments that modify the appearance in the genome browser. For this example we just create a simple data set.
.. doctest::
>>> rows = [['1', 100, 101, 1.123], ['1', 101, 102, 1.123],
... ['1', 102, 103, 1.123], ['1', 103, 104, 1.123],
... ['1', 104, 105, 1.123], ['1', 105, 106, 1.123],
... ['1', 106, 107, 1.123], ['1', 107, 108, 1.123],
... ['1', 108, 109, 1], ['1', 109, 110, 1],
... ['1', 110, 111, 1], ['1', 111, 112, 1],
... ['1', 112, 113, 1], ['1', 113, 114, 1],
... ['1', 114, 115, 1], ['1', 115, 116, 1],
... ['1', 116, 117, 1], ['1', 117, 118, 1],
... ['1', 118, 119, 2], ['1', 119, 120, 2],
... ['1', 120, 121, 2], ['1', 150, 151, 2],
... ['1', 151, 152, 2], ['1', 152, 153, 2],
... ['1', 153, 154, 2], ['1', 154, 155, 2],
... ['1', 155, 156, 2], ['1', 156, 157, 2],
... ['1', 157, 158, 2], ['1', 158, 159, 2],
... ['1', 159, 160, 2], ['1', 160, 161, 2]]
...
>>> bgraph = LoadTable(header=['chrom', 'start', 'end', 'value'],
... rows=rows)
...
>>> print bgraph.tostring(format='bedgraph', name='test track',
... graphType='bar', description='test of bedgraph', color=(255,0,0)) # doctest: +NORMALIZE_WHITESPACE
track type=bedGraph name="test track" description="test of bedgraph" color=255,0,0 graphType=bar
1 100 108 1.12
1 108 118 1.0
1 118 161 2.0
The bedgraph formatter defaults to rounding values to 2 decimal places. You can adjust that precision using the ``digits`` argument.
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> print bgraph.tostring(format='bedgraph', name='test track',
... graphType='bar', description='test of bedgraph', color=(255,0,0),
... digits=0) # doctest: +NORMALIZE_WHITESPACE
track type=bedGraph name="test track" description="test of bedgraph" color=255,0,0 graphType=bar
1 100 118 1.0
1 118 161 2.0
.. note:: Writing files in bedgraph format is done using the ``writeToFile(format='bedgraph', name='test track', description='test of bedgraph', color=(255,0,0))``.
.. _bedGraph: https://cgwb.nci.nih.gov/goldenPath/help/bedgraph.html
Saving a table for reloading
----------------------------
Saving a table object to file for later reloading can be done using the standard ``writeToFile`` method and ``filename`` argument to the ``Table`` constructor, specifying any of the formats supported by ``tostring``. The table loading will recreate a table from raw data located at ``filename``. To illustrate this, we first write out the table ``t3`` in ``pickle`` format and then the table ``t2`` in a csv (comma separated values format).
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> t3 = Table(['edge.name', 'edge.parent', 'length', 'x', 'y', 'z'], d2D,
... row_order = row_order, missing_data='*', space=8, max_width = 50,
... row_ids = True, title = 'My Title',
... legend = 'Legend: this is a nonsense example.')
>>> t3.writeToFile("t3.pickle")
>>> t3_loaded = LoadTable(filename = "t3.pickle")
>>> print t3_loaded
My Title
==========================================
edge.name edge.parent length
------------------------------------------
Human edge.0 4.0000
HowlerMon edge.0 4.0000
Mouse edge.1 4.0000
NineBande root 4.0000
DogFaced root 4.0000
edge.0 edge.1 4.0000
edge.1 root 4.0000
------------------------------------------
continued: My Title
=====================================
edge.name x y
-------------------------------------
Human 1.0000 3.0000
HowlerMon 1.0000 3.0000
Mouse 1.0000 3.0000
NineBande 1.0000 3.0000
DogFaced 1.0000 3.0000
edge.0 1.0000 3.0000
edge.1 1.0000 3.0000
-------------------------------------
continued: My Title
=======================
edge.name z
-----------------------
Human 6.0000
HowlerMon 6.0000
Mouse 6.0000
NineBande 6.0000
DogFaced 6.0000
edge.0 6.0000
edge.1 6.0000
-----------------------
Legend: this is a nonsense example.
>>> t2 = Table(['abcd', 'data'], [[str(range(1,6)), '0'], ['x', 5.0],
... ['y', None]], missing_data='*', title = 'A \ntitle')
>>> t2.writeToFile('t2.csv', sep=',')
>>> t2_loaded = LoadTable(filename = 't2.csv', header = True, with_title = True,
... sep = ',')
>>> print t2_loaded
A
title
=========================
abcd data
-------------------------
[1, 2, 3, 4, 5] 0
x 5.0000
y
-------------------------
Note the ``missing_data`` attribute is not saved in the delimited format, but is in the ``pickle`` format. In the next case, I'm going to override the digits format on reloading of the table.
.. doctest::
>>> t2 = Table(['abcd', 'data'], [[str(range(1,6)), '0'], ['x', 5.0],
... ['y', None]], missing_data='*', title = 'A \ntitle',
... legend = "And\na legend too")
>>> t2.writeToFile('t2.csv', sep=',')
>>> t2_loaded = LoadTable(filename = 't2.csv', header = True,
... with_title = True, with_legend = True, sep = ',', digits = 2)
>>> print t2_loaded # doctest: +NORMALIZE_WHITESPACE
A
title
=======================
abcd data
-----------------------
[1, 2, 3, 4, 5] 0
x 5.00
y
-----------------------
And
a legend too
A few things to note about the delimited file saving: formatting arguments are lost in saving to a delimited format; the ``header`` argument specifies whether the first line of the file should be treated as the header; the ``with_title`` and ``with_legend`` arguments are necessary if the file contains them, otherwise they become the header or part of the table. Importantly, if you wish to preserve numerical precision use the ``pickle`` format.
``cPickle`` can load a useful object from the pickled ``Table`` by itself, without needing to know anything about the ``Table`` class.
.. doctest::
>>> import cPickle
>>> f = file("t3.pickle")
>>> pickled = cPickle.load(f)
>>> f.close()
>>> pickled.keys()
['digits', 'row_ids', 'rows', 'title', 'space', 'max_width', 'header',...
>>> pickled['rows'][0]
['Human', 'edge.0', 4.0, 1.0, 3.0, 6.0]
We can read in a delimited format using a custom reader. There are two approaches. The first one allows specifying different type conversions for different columns. The second allows specifying a whole line-based parser.
You can also read and write tables in gzip compressed format. This can be done simply by ending a filename with '.gz' or specifying ``compress=True``. We write a compressed file the two different ways and read it back in.
.. doctest::
>>> t2.writeToFile('t2.csv.gz', sep=',')
>>> t2_gz = LoadTable('t2.csv.gz', sep=',', with_title=True,
... with_legend = True)
>>> t2_gz.Shape == t2.Shape
True
>>> t2.writeToFile('t2.csv', sep=',', compress=True)
>>> t2_gz = LoadTable('t2.csv.gz', sep=',', with_title=True,
... with_legend = True)
>>> t2_gz.Shape == t2.Shape
True
Defining a custom reader with type conversion for each column
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
We convert columns 2-5 to floats by specifying a field convertor. We then create a reader, specifying the data (below a list but can be a file) properties. Note that if no convertor is provided all data are returned as strings. We can also provide this reader to the ``Table`` constructor for a more direct way of opening such files. In this case, ``Table`` assumes there is a header row and nothing else.
.. doctest::
>>> from cogent.parse.table import ConvertFields, SeparatorFormatParser
>>> t3.Title = t3.Legend = None
>>> comma_sep = t3.tostring(sep=",").splitlines()
>>> print comma_sep
['edge.name,edge.parent,length, x, y, z', ' Human, ...
>>> converter = ConvertFields([(2,float), (3,float), (4,float), (5, float)])
>>> reader = SeparatorFormatParser(with_header=True,converter=converter,
... sep=",")
>>> comma_sep = [line for line in reader(comma_sep)]
>>> print comma_sep
[['edge.name', 'edge.parent', 'length', 'x', 'y', 'z'], ['Human',...
>>> t3.writeToFile("t3.tab", sep="\t")
>>> reader = SeparatorFormatParser(with_header=True,converter=converter,
... sep="\t")
>>> t3a = LoadTable(filename="t3.tab", reader=reader, title="new title",
... space=2)
...
>>> print t3a
new title
======================================================
edge.name edge.parent length x y z
------------------------------------------------------
Human edge.0 4.0000 1.0000 3.0000 6.0000
HowlerMon edge.0 4.0000 1.0000 3.0000 6.0000
Mouse edge.1 4.0000 1.0000 3.0000 6.0000
NineBande root 4.0000 1.0000 3.0000 6.0000
DogFaced root 4.0000 1.0000 3.0000 6.0000
edge.0 edge.1 4.0000 1.0000 3.0000 6.0000
edge.1 root 4.0000 1.0000 3.0000 6.0000
------------------------------------------------------
We can use the ``SeparatorFormatParser`` to ignore reading certain lines by using a callback function. We illustrate this using the above data, skipping any rows with ``edge.name`` starting with ``edge``.
.. doctest::
>>> def ignore_internal_nodes(line):
... return line[0].startswith('edge')
...
>>> reader = SeparatorFormatParser(with_header=True,converter=converter,
... sep="\t", ignore=ignore_internal_nodes)
...
>>> tips = LoadTable(filename="t3.tab", reader=reader, digits=1, space=2)
>>> print tips
=============================================
edge.name edge.parent length x y z
---------------------------------------------
Human edge.0 4.0 1.0 3.0 6.0
HowlerMon edge.0 4.0 1.0 3.0 6.0
Mouse edge.1 4.0 1.0 3.0 6.0
NineBande root 4.0 1.0 3.0 6.0
DogFaced root 4.0 1.0 3.0 6.0
---------------------------------------------
We can also limit the amount of data to be read in, very handy for checking large files.
.. doctest::
>>> t3a = LoadTable("t3.tab", sep='\t', limit=3)
>>> print t3a
================================================================
edge.name edge.parent length x y z
----------------------------------------------------------------
Human edge.0 4.0000 1.0000 3.0000 6.0000
HowlerMon edge.0 4.0000 1.0000 3.0000 6.0000
Mouse edge.1 4.0000 1.0000 3.0000 6.0000
----------------------------------------------------------------
Limiting should also work when ``static_column_types`` is invoked
.. doctest::
>>> t3a = LoadTable("t3.tab", sep='\t', limit=3, static_column_types=True)
>>> t3a.Shape[0] == 3
True
or when
In the above example, the data type in a column is static, e.g. all values in ``x`` are floats. Rather than providing a custom reader, you can get the ``Table`` to construct such a reader based on the first data row using the ``static_column_types`` argument.
.. doctest::
>>> t3a = LoadTable(filename="t3.tab", static_column_types=True, digits=1,
... sep='\t')
>>> print t3a
=======================================================
edge.name edge.parent length x y z
-------------------------------------------------------
Human edge.0 4.0 1.0 3.0 6.0
HowlerMon edge.0 4.0 1.0 3.0 6.0
Mouse edge.1 4.0 1.0 3.0 6.0
NineBande root 4.0 1.0 3.0 6.0
DogFaced root 4.0 1.0 3.0 6.0
edge.0 edge.1 4.0 1.0 3.0 6.0
edge.1 root 4.0 1.0 3.0 6.0
-------------------------------------------------------
If you invoke the ``static_column_types`` argument and the column data are not static, you'll get a ``ValueError``. We show this by first creating a simple table with mixed data types in a column, write to file and then try to load with ``static_column_types=True``.
.. doctest::
>>> t3b = LoadTable(header=['A', 'B'], rows=[[1,1], ['a', 2]], sep=2)
>>> print t3b
======
A B
------
1 1
a 2
------
>>> t3b.writeToFile('test3b.txt', sep='\t')
>>> t3b = LoadTable('test3b.txt', sep = '\t', static_column_types=True)
Traceback (most recent call last):
ValueError: invalid literal for int() with base 10: 'a'
We also test the reader function for a tab delimited format with missing data at the end.
.. doctest::
>>> data = ['ab\tcd\t', 'ab\tcd\tef']
>>> tab_reader = SeparatorFormatParser(sep='\t')
>>> for line in tab_reader(data):
... assert len(line) == 3, line
Defining a custom reader that operates on entire lines
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
It can also be the case that data types differ between lines. The basic mechanism is the same as above, except in defining the converter you must set the argument ``by_column=True``.
We illustrate this capability by writing a short function that tries to cast entire lines to ``int``, ``float`` or leaves as a string.
.. doctest::
>>> def CastLine():
... floats = lambda x: map(float, x)
... ints = lambda x: map(int, x)
... def call(line):
... try:
... line = ints(line)
... except ValueError:
... try:
... line = floats(line)
... except ValueError:
... pass
... return line
... return call
We then define a couple of lines, create an instance of ``ConvertFields`` and call it for each type.
.. doctest::
>>> line_str_ints = '\t'.join(map(str, range(5)))
>>> line_str_floats = '\t'.join(map(str, map(float, range(5))))
>>> data = [line_str_ints, line_str_floats]
>>> cv = ConvertFields(CastLine(), by_column=False)
>>> tab_reader = SeparatorFormatParser(with_header=False, converter=cv,
... sep='\t')
>>> for line in tab_reader(data):
... print line
[0, 1, 2, 3, 4]
[0.0, 1.0, 2.0, 3.0, 4.0]
Defining a custom writer
^^^^^^^^^^^^^^^^^^^^^^^^
We can likewise specify a writer, using a custom field formatter and provide this to the ``Table`` directly for writing. We first illustrate how the writer works to generate output. We then use it to escape some text fields in quotes. In order to read that back in, we define a custom reader that strips these quotes off.
.. doctest::
>>> from cogent.format.table import FormatFields, SeparatorFormatWriter
>>> formatter = FormatFields([(0,'"%s"'), (1,'"%s"')])
>>> writer = SeparatorFormatWriter(formatter=formatter, sep=" | ")
>>> for formatted in writer(comma_sep, has_header=True):
... print formatted
edge.name | edge.parent | length | x | y | z
"Human" | "edge.0" | 4.0 | 1.0 | 3.0 | 6.0
"HowlerMon" | "edge.0" | 4.0 | 1.0 | 3.0 | 6.0
"Mouse" | "edge.1" | 4.0 | 1.0 | 3.0 | 6.0
"NineBande" | "root" | 4.0 | 1.0 | 3.0 | 6.0
"DogFaced" | "root" | 4.0 | 1.0 | 3.0 | 6.0
"edge.0" | "edge.1" | 4.0 | 1.0 | 3.0 | 6.0
"edge.1" | "root" | 4.0 | 1.0 | 3.0 | 6.0
>>> t3.writeToFile(filename="t3.tab", writer=writer)
>>> strip = lambda x: x.replace('"', '')
>>> converter = ConvertFields([(0,strip), (1, strip)])
>>> reader = SeparatorFormatParser(with_header=True, converter=converter,
... sep="|", strip_wspace=True)
>>> t3a = LoadTable(filename="t3.tab", reader=reader, title="new title",
... space=2)
>>> print t3a
new title
=============================================
edge.name edge.parent length x y z
---------------------------------------------
Human edge.0 4.0 1.0 3.0 6.0
HowlerMon edge.0 4.0 1.0 3.0 6.0
Mouse edge.1 4.0 1.0 3.0 6.0
NineBande root 4.0 1.0 3.0 6.0
DogFaced root 4.0 1.0 3.0 6.0
edge.0 edge.1 4.0 1.0 3.0 6.0
edge.1 root 4.0 1.0 3.0 6.0
---------------------------------------------
.. note:: There are performance issues for large files. Pickling has proven very slow for saving very large files and introduces significant file size bloat. A simple delimited format is much more efficient both storage wise and, if you use a custom reader (or specify ``static_column_types=True``), to generate and read. A custom reader was approximately 6 fold faster than the standard delimited file reader.
Table slicing and iteration
---------------------------
The Table class is capable of slicing by row, range of rows, column or range of columns headings or used to identify a single cell. Slicing using the method ``getColumns`` can also be used to reorder columns. In the case of columns, either the string headings or their position integers can be used. For rows, if ``row_ids`` was specified as ``True`` the 0'th cell in each row can also be used.
.. doctest::
>>> t4 = Table(['edge.name', 'edge.parent', 'length', 'x', 'y', 'z'], d2D,
... row_order = row_order, row_ids = True, title = 'My Title')
We subset ``t4`` by column and reorder them.
.. doctest::
>>> new = t4.getColumns(['z', 'y'])
>>> print new
My Title
=============================
edge.name z y
-----------------------------
Human 6.0000 3.0000
HowlerMon 6.0000 3.0000
Mouse 6.0000 3.0000
NineBande 6.0000 3.0000
DogFaced 6.0000 3.0000
edge.0 6.0000 3.0000
edge.1 6.0000 3.0000
-----------------------------
We use the column position indexes to do get the same table.
.. doctest::
>>> new = t4.getColumns([5, 4])
>>> print new
My Title
=============================
edge.name z y
-----------------------------
Human 6.0000 3.0000
HowlerMon 6.0000 3.0000
Mouse 6.0000 3.0000
NineBande 6.0000 3.0000
DogFaced 6.0000 3.0000
edge.0 6.0000 3.0000
edge.1 6.0000 3.0000
-----------------------------
We can also using more general slicing, by both rows and columns. The following returns all rows from 4 on, and columns up to (but excluding) 'y':
.. doctest::
>>> k = t4[4:, :'y']
>>> print k
My Title
============================================
edge.name edge.parent length x
--------------------------------------------
DogFaced root 4.0000 1.0000
edge.0 edge.1 4.0000 1.0000
edge.1 root 4.0000 1.0000
--------------------------------------------
We can explicitly reference individual cells, in this case using both row and column keys.
.. doctest::
>>> val = t4['HowlerMon', 'y']
>>> print val
3.0
We slice a single row,
.. doctest::
>>> new = t4[3]
>>> print new
My Title
================================================================
edge.name edge.parent length x y z
----------------------------------------------------------------
NineBande root 4.0000 1.0000 3.0000 6.0000
----------------------------------------------------------------
and range of rows.
.. doctest::
>>> new = t4[3:6]
>>> print new
My Title
================================================================
edge.name edge.parent length x y z
----------------------------------------------------------------
NineBande root 4.0000 1.0000 3.0000 6.0000
DogFaced root 4.0000 1.0000 3.0000 6.0000
edge.0 edge.1 4.0000 1.0000 3.0000 6.0000
----------------------------------------------------------------
You can get disjoint rows.
.. doctest::
>>> print t4.getDisjointRows(['Human', 'Mouse', 'DogFaced'])
My Title
================================================================
edge.name edge.parent length x y z
----------------------------------------------------------------
Human edge.0 4.0000 1.0000 3.0000 6.0000
Mouse edge.1 4.0000 1.0000 3.0000 6.0000
DogFaced root 4.0000 1.0000 3.0000 6.0000
----------------------------------------------------------------
You can iterate over the table one row at a time and slice the rows. We illustrate this for slicing a single column,
.. doctest::
>>> for row in t:
... print row['Journal']
INT J PARASITOL
J MED ENTOMOL
Med Vet Entomol
INSECT MOL BIOL
J AM MOSQUITO CONTR
MOL PHYLOGENET EVOL
HEREDITY
AM J TROP MED HYG
MIL MED
MED J AUSTRALIA
and for multiple columns.
.. doctest::
>>> for row in t:
... print row['Journal'], row['Impact']
INT J PARASITOL 2.9
J MED ENTOMOL 1.4
Med Vet Entomol 1.0
INSECT MOL BIOL 2.85
J AM MOSQUITO CONTR 0.811
MOL PHYLOGENET EVOL 2.8
HEREDITY 1.99
AM J TROP MED HYG 2.105
MIL MED 0.605
MED J AUSTRALIA 1.736
The numerical slice equivalent to the first case above would be ``row[0]``, to the second case either ``row[:]``, ``row[:2]``.
Filtering tables - selecting subsets of rows/columns
----------------------------------------------------
We want to be able to slice a table, based on some condition(s), to produce a new subset table. For instance, we construct a table with type and probability values.
.. doctest::
>>> header = ['Gene', 'type', 'LR', 'df', 'Prob']
>>> rows = (('NP_003077_hs_mm_rn_dna', 'Con', 2.5386, 1, 0.1111),
... ('NP_004893_hs_mm_rn_dna', 'Con', 0.1214, 1, 0.7276),
... ('NP_005079_hs_mm_rn_dna', 'Con', 0.9517, 1, 0.3293),
... ('NP_005500_hs_mm_rn_dna', 'Con', 0.7383, 1, 0.3902),
... ('NP_055852_hs_mm_rn_dna', 'Con', 0.0000, 1, 0.9997),
... ('NP_057012_hs_mm_rn_dna', 'Unco', 34.3081, 1, 0.0000),
... ('NP_061130_hs_mm_rn_dna', 'Unco', 3.7986, 1, 0.0513),
... ('NP_065168_hs_mm_rn_dna', 'Con', 89.9766, 1, 0.0000),
... ('NP_065396_hs_mm_rn_dna', 'Unco', 11.8912, 1, 0.0006),
... ('NP_109590_hs_mm_rn_dna', 'Con', 0.2121, 1, 0.6451),
... ('NP_116116_hs_mm_rn_dna', 'Unco', 9.7474, 1, 0.0018))
>>> t5 = Table(header, rows)
>>> print t5
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_003077_hs_mm_rn_dna Con 2.5386 1 0.1111
NP_004893_hs_mm_rn_dna Con 0.1214 1 0.7276
NP_005079_hs_mm_rn_dna Con 0.9517 1 0.3293
NP_005500_hs_mm_rn_dna Con 0.7383 1 0.3902
NP_055852_hs_mm_rn_dna Con 0.0000 1 0.9997
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_061130_hs_mm_rn_dna Unco 3.7986 1 0.0513
NP_065168_hs_mm_rn_dna Con 89.9766 1 0.0000
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_109590_hs_mm_rn_dna Con 0.2121 1 0.6451
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
---------------------------------------------------------
We then seek to obtain only those rows that contain probabilities < 0.05. We use valid python code within a string. **Note:** Make sure your column headings could be valid python variable names or the string based approach will fail (you could use an external function instead, see below).
.. doctest::
>>> sub_table1 = t5.filtered(callback = "Prob < 0.05")
>>> print sub_table1
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_065168_hs_mm_rn_dna Con 89.9766 1 0.0000
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
---------------------------------------------------------
Using the above table we test the function to extract the raw data for a single column,
.. doctest::
>>> raw = sub_table1.getRawData('LR')
>>> raw
[34.3081..., 89.9766..., 11.8912, 9.7474...]
and from multiple columns.
.. doctest::
>>> raw = sub_table1.getRawData(columns = ['df', 'Prob'])
>>> raw
[[1, 0.0], [1, 0.0],...
We can also do filtering using an external function, in this case we use a ``lambda`` to obtain only those rows of type 'Unco' that contain probabilities < 0.05, modifying our callback function.
.. doctest::
>>> func = lambda (ty, pr): ty == 'Unco' and pr < 0.05
>>> sub_table2 = t5.filtered(columns = ('type', 'Prob'), callback = func)
>>> print sub_table2
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
---------------------------------------------------------
This can also be done using the string approach.
.. doctest::
>>> sub_table2 = t5.filtered(callback = "type == 'Unco' and Prob < 0.05")
>>> print sub_table2
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
---------------------------------------------------------
We can also filter table columns using ``filteredByColumn``. Say we only want the numerical columns, we can write a callback that returns ``False`` if some numerical operation fails, ``True`` otherwise.
.. doctest::
>>> def is_numeric(values):
... try:
... sum(values)
... except TypeError:
... return False
... return True
>>> print t5.filteredByColumn(callback=is_numeric)
=======================
LR df Prob
-----------------------
2.5386 1 0.1111
0.1214 1 0.7276
0.9517 1 0.3293
0.7383 1 0.3902
0.0000 1 0.9997
34.3081 1 0.0000
3.7986 1 0.0513
89.9766 1 0.0000
11.8912 1 0.0006
0.2121 1 0.6451
9.7474 1 0.0018
-----------------------
Appending tables
----------------
Tables may also be appended to each other, to make larger tables. We'll construct two simple tables to illustrate this.
.. doctest::
>>> geneA = Table(['edge.name', 'edge.parent', 'z'], [['Human','root',
... 6.0],['Mouse','root', 6.0], ['Rat','root', 6.0]],
... title='Gene A')
>>> geneB = Table(['edge.name', 'edge.parent', 'z'], [['Human','root',
... 7.0],['Mouse','root', 7.0], ['Rat','root', 7.0]],
... title='Gene B')
>>> print geneB
Gene B
==================================
edge.name edge.parent z
----------------------------------
Human root 7.0000
Mouse root 7.0000
Rat root 7.0000
----------------------------------
we now use the ``appended`` Table method to create a new table, specifying that we want a new column created (by passing the ``new_column`` argument a heading) in which the table titles will be placed.
.. doctest::
>>> new = geneA.appended('Gene', geneB, title='Appended tables')
>>> print new
Appended tables
============================================
Gene edge.name edge.parent z
--------------------------------------------
Gene A Human root 6.0000
Gene A Mouse root 6.0000
Gene A Rat root 6.0000
Gene B Human root 7.0000
Gene B Mouse root 7.0000
Gene B Rat root 7.0000
--------------------------------------------
We repeat this without adding a new column.
.. doctest::
>>> new = geneA.appended(None, geneB, title="Appended, no new column")
>>> print new
Appended, no new column
==================================
edge.name edge.parent z
----------------------------------
Human root 6.0000
Mouse root 6.0000
Rat root 6.0000
Human root 7.0000
Mouse root 7.0000
Rat root 7.0000
----------------------------------
Miscellaneous
-------------
Tables have a ``Shape`` attribute, which specifies *x* (number of columns) and *y* (number of rows). The attribute is a tuple and we illustrate it for the above ``sub_table`` tables. Combined with the ``filtered`` method, this attribute can tell you how many rows satisfy a specific condition.
.. doctest::
>>> t5.Shape
(11, 5)
>>> sub_table1.Shape
(4, 5)
>>> sub_table2.Shape
(3, 5)
For instance, 3 of the 11 rows in ``t`` were significant and belonged to the ``Unco`` type.
For completeness, we generate a table with no rows and assess its shape.
.. doctest::
>>> func = lambda (ty, pr): ty == 'Unco' and pr > 0.1
>>> sub_table3 = t5.filtered(columns = ('type', 'Prob'), callback = func)
>>> sub_table3.Shape
(0, 5)
The distinct values can be obtained for a single column,
.. doctest::
>>> distinct = new.getDistinctValues("edge.name")
>>> assert distinct == set(['Rat', 'Mouse', 'Human'])
or multiple columns
.. doctest::
>>> distinct = new.getDistinctValues(["edge.parent", "z"])
>>> assert distinct == set([('root', 6.0), ('root', 7.0)]), distinct
We can compute column sums. Assuming only numerical values in a column.
.. doctest::
>>> assert new.summed('z') == 39., new.summed('z')
We construct an example with mixed numerical and non-numerical data. We now compute the column sum with mixed non-numerical/numerical data.
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> mix = LoadTable(header=['A', 'B'], rows=[[0,''],[1,2],[3,4]])
>>> print mix
======
A B
------
0
1 2
3 4
------
>>> mix.summed('B', strict=False)
6
We also compute row sums for the pure numerical and mixed non-numerical/numerical rows. For summing across rows we must specify the actual row index as an ``int``.
.. doctest::
>>> mix.summed(0, col_sum=False, strict=False)
0
>>> mix.summed(1, col_sum=False)
3
We can compute the totals for all columns or rows too.
.. doctest::
>>> mix.summed(strict=False)
[4, 6]
>>> mix.summed(col_sum=False, strict=False)
[0, 3, 7]
It is not currently possible to do a subset of columns/rows. We show this for rows here.
.. doctest::
>>> mix.summed([0, 2], col_sum=False, strict=False)
Traceback (most recent call last):
RuntimeError: unknown indices type: [0, 2]
We test these for a strictly numerical table.
.. doctest::
>>> non_mix = LoadTable(header=['A', 'B'], rows=[[0,1],[1,2],[3,4]])
>>> non_mix.summed()
[4, 7]
>>> non_mix.summed(col_sum=False)
[1, 3, 7]
We can normalise a numerical table by row,
.. doctest::
>>> print non_mix.normalized(by_row=True)
================
A B
----------------
0.0000 1.0000
0.3333 0.6667
0.4286 0.5714
----------------
or by column, such that the row/column sums are 1.
.. doctest::
>>> print non_mix.normalized(by_row=False)
================
A B
----------------
0.0000 0.1429
0.2500 0.2857
0.7500 0.5714
----------------
We normalize by an arbitrary function (maximum value) by row,
.. doctest::
>>> print non_mix.normalized(by_row=True, denominator_func=max)
================
A B
----------------
0.0000 1.0000
0.5000 1.0000
0.7500 1.0000
----------------
by column.
.. doctest::
>>> print non_mix.normalized(by_row=False, denominator_func=max)
================
A B
----------------
0.0000 0.2500
0.3333 0.5000
1.0000 1.0000
----------------
Extending tables
----------------
In some cases it is desirable to compute an additional column from existing column values. This is done using the ``withNewColumn`` method. We'll use t4 from above, adding two of the columns to create an additional column.
.. doctest::
>>> t7 = t4.withNewColumn('Sum', callback="z+x", digits=2)
>>> print t7
My Title
==================================================================
edge.name edge.parent length x y z Sum
------------------------------------------------------------------
Human edge.0 4.00 1.00 3.00 6.00 7.00
HowlerMon edge.0 4.00 1.00 3.00 6.00 7.00
Mouse edge.1 4.00 1.00 3.00 6.00 7.00
NineBande root 4.00 1.00 3.00 6.00 7.00
DogFaced root 4.00 1.00 3.00 6.00 7.00
edge.0 edge.1 4.00 1.00 3.00 6.00 7.00
edge.1 root 4.00 1.00 3.00 6.00 7.00
------------------------------------------------------------------
We test this with an externally defined function.
.. doctest::
>>> func = lambda (x, y): x * y
>>> t7 = t4.withNewColumn('Sum', callback=func, columns=("y","z"),
... digits=2)
>>> print t7
My Title
===================================================================
edge.name edge.parent length x y z Sum
-------------------------------------------------------------------
Human edge.0 4.00 1.00 3.00 6.00 18.00
HowlerMon edge.0 4.00 1.00 3.00 6.00 18.00
Mouse edge.1 4.00 1.00 3.00 6.00 18.00
NineBande root 4.00 1.00 3.00 6.00 18.00
DogFaced root 4.00 1.00 3.00 6.00 18.00
edge.0 edge.1 4.00 1.00 3.00 6.00 18.00
edge.1 root 4.00 1.00 3.00 6.00 18.00
-------------------------------------------------------------------
>>> func = lambda x: x**3
>>> t7 = t4.withNewColumn('Sum', callback=func, columns="y", digits=2)
>>> print t7
My Title
===================================================================
edge.name edge.parent length x y z Sum
-------------------------------------------------------------------
Human edge.0 4.00 1.00 3.00 6.00 27.00
HowlerMon edge.0 4.00 1.00 3.00 6.00 27.00
Mouse edge.1 4.00 1.00 3.00 6.00 27.00
NineBande root 4.00 1.00 3.00 6.00 27.00
DogFaced root 4.00 1.00 3.00 6.00 27.00
edge.0 edge.1 4.00 1.00 3.00 6.00 27.00
edge.1 root 4.00 1.00 3.00 6.00 27.00
-------------------------------------------------------------------
Sorting tables
--------------
We want a table sorted according to values in a column.
.. doctest::
>>> sorted = t5.sorted(columns = 'LR')
>>> print sorted
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_055852_hs_mm_rn_dna Con 0.0000 1 0.9997
NP_004893_hs_mm_rn_dna Con 0.1214 1 0.7276
NP_109590_hs_mm_rn_dna Con 0.2121 1 0.6451
NP_005500_hs_mm_rn_dna Con 0.7383 1 0.3902
NP_005079_hs_mm_rn_dna Con 0.9517 1 0.3293
NP_003077_hs_mm_rn_dna Con 2.5386 1 0.1111
NP_061130_hs_mm_rn_dna Unco 3.7986 1 0.0513
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_065168_hs_mm_rn_dna Con 89.9766 1 0.0000
---------------------------------------------------------
We want a table sorted according to values in a subset of columns, note the order of columns determines the sort order.
.. doctest::
>>> sorted = t5.sorted(columns=('LR', 'type'))
>>> print sorted
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_055852_hs_mm_rn_dna Con 0.0000 1 0.9997
NP_004893_hs_mm_rn_dna Con 0.1214 1 0.7276
NP_109590_hs_mm_rn_dna Con 0.2121 1 0.6451
NP_005500_hs_mm_rn_dna Con 0.7383 1 0.3902
NP_005079_hs_mm_rn_dna Con 0.9517 1 0.3293
NP_003077_hs_mm_rn_dna Con 2.5386 1 0.1111
NP_061130_hs_mm_rn_dna Unco 3.7986 1 0.0513
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_065168_hs_mm_rn_dna Con 89.9766 1 0.0000
---------------------------------------------------------
We now do a sort based on 2 columns.
.. doctest::
>>> sorted = t5.sorted(columns=('type', 'LR'))
>>> print sorted
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_055852_hs_mm_rn_dna Con 0.0000 1 0.9997
NP_004893_hs_mm_rn_dna Con 0.1214 1 0.7276
NP_109590_hs_mm_rn_dna Con 0.2121 1 0.6451
NP_005500_hs_mm_rn_dna Con 0.7383 1 0.3902
NP_005079_hs_mm_rn_dna Con 0.9517 1 0.3293
NP_003077_hs_mm_rn_dna Con 2.5386 1 0.1111
NP_065168_hs_mm_rn_dna Con 89.9766 1 0.0000
NP_061130_hs_mm_rn_dna Unco 3.7986 1 0.0513
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
---------------------------------------------------------
Reverse sort a single column
.. doctest::
>>> sorted = t5.sorted('LR', reverse = 'LR')
>>> print sorted
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_065168_hs_mm_rn_dna Con 89.9766 1 0.0000
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
NP_061130_hs_mm_rn_dna Unco 3.7986 1 0.0513
NP_003077_hs_mm_rn_dna Con 2.5386 1 0.1111
NP_005079_hs_mm_rn_dna Con 0.9517 1 0.3293
NP_005500_hs_mm_rn_dna Con 0.7383 1 0.3902
NP_109590_hs_mm_rn_dna Con 0.2121 1 0.6451
NP_004893_hs_mm_rn_dna Con 0.1214 1 0.7276
NP_055852_hs_mm_rn_dna Con 0.0000 1 0.9997
---------------------------------------------------------
Reverse sort one column but not another
.. doctest::
>>> sorted = t5.sorted(columns=('type', 'LR'), reverse = 'LR')
>>> print sorted
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_065168_hs_mm_rn_dna Con 89.9766 1 0.0000
NP_003077_hs_mm_rn_dna Con 2.5386 1 0.1111
NP_005079_hs_mm_rn_dna Con 0.9517 1 0.3293
NP_005500_hs_mm_rn_dna Con 0.7383 1 0.3902
NP_109590_hs_mm_rn_dna Con 0.2121 1 0.6451
NP_004893_hs_mm_rn_dna Con 0.1214 1 0.7276
NP_055852_hs_mm_rn_dna Con 0.0000 1 0.9997
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
NP_061130_hs_mm_rn_dna Unco 3.7986 1 0.0513
---------------------------------------------------------
Reverse sort both columns.
.. doctest::
>>> sorted = t5.sorted(columns=('type', 'LR'), reverse = ('type', 'LR'))
>>> print sorted
=========================================================
Gene type LR df Prob
---------------------------------------------------------
NP_057012_hs_mm_rn_dna Unco 34.3081 1 0.0000
NP_065396_hs_mm_rn_dna Unco 11.8912 1 0.0006
NP_116116_hs_mm_rn_dna Unco 9.7474 1 0.0018
NP_061130_hs_mm_rn_dna Unco 3.7986 1 0.0513
NP_065168_hs_mm_rn_dna Con 89.9766 1 0.0000
NP_003077_hs_mm_rn_dna Con 2.5386 1 0.1111
NP_005079_hs_mm_rn_dna Con 0.9517 1 0.3293
NP_005500_hs_mm_rn_dna Con 0.7383 1 0.3902
NP_109590_hs_mm_rn_dna Con 0.2121 1 0.6451
NP_004893_hs_mm_rn_dna Con 0.1214 1 0.7276
NP_055852_hs_mm_rn_dna Con 0.0000 1 0.9997
---------------------------------------------------------
Joining Tables
--------------
The Table object is capable of joins or merging of records in two tables. There are two fundamental types of joins -- inner and outer -- with there being different sub-types. We demonstrate these first constructing some simple tables.
.. doctest::
>>> a=Table(header=["index", "col2","col3"],
... rows=[[1,2,3],[2,3,1],[2,6,5]], title="A")
>>> print a
A
=====================
index col2 col3
---------------------
1 2 3
2 3 1
2 6 5
---------------------
>>> b=Table(header=["index", "col2","col3"],
... rows=[[1,2,3],[2,2,1],[3,6,3]], title="B")
>>> print b
B
=====================
index col2 col3
---------------------
1 2 3
2 2 1
3 6 3
---------------------
>>> c=Table(header=["index","col_c2"],rows=[[1,2],[3,2],[3,5]],title="C")
>>> print c
C
===============
index col_c2
---------------
1 2
3 2
3 5
---------------
For a natural inner join, only 1 copy of columns with the same name are retained. So we expect the headings to be identical between the table ``a``/``b`` and the result of ``a.joined(b)`` or ``b.joined(a)``.
.. doctest::
>>> assert a.joined(b).Header == b.Header
>>> assert b.joined(a).Header == a.Header
For a standard inner join, the joined table should contain all columns from ``a`` and ``b`` excepting the index column(s). Simply providing a column name (or index) selects this behaviour. Note that in this case, column names from the second table are made unique by prefixing them with that tables title. If the provided tables do not have a title, a ``RuntimeError`` is raised.
.. doctest::
>>> b.Title = None
>>> try:
... a.joined(b)
... except RuntimeError:
... pass
>>> b.Title = 'B'
>>> assert a.joined(b, "index").Header == ["index", "col2", "col3",
... "B_col2", "B_col3"]
...
Note that the table title's were used to prefix the column headings from the second table. We further test this using table ``c`` which has different dimensions.
.. doctest::
>>> assert a.joined(c,"index").Header == ["index","col2","col3",
... "C_col_c2"]
It's also possible to specify index columns using numerical values, the results of which should be the same.
.. doctest::
>>> assert a.joined(b,[0, 2]).getRawData() ==\
... a.joined(b,["index","col3"]).getRawData()
Additionally, it's possible to provide two series of indices for the two tables. Here, they have identical values.
.. doctest::
>>> assert a.joined(b, ["index", "col3"],["index", "col3"]).getRawData()\
... == a.joined(b,["index","col3"]).getRawData()
The results of a standard join between tables ``a`` and ``b`` are
.. doctest::
>>> print a.joined(b, ["index"], title='A&B')
A&B
=========================================
index col2 col3 B_col2 B_col3
-----------------------------------------
1 2 3 2 3
2 3 1 2 1
2 6 5 2 1
-----------------------------------------
We demo the table specific indices.
.. doctest::
>>> print a.joined(c, ["col2"], ["index"], title='A&C by "col2/index"')
A&C by "col2/index"
=================================
index col2 col3 C_col_c2
---------------------------------
2 3 1 2
2 3 1 5
---------------------------------
Tables ``a`` and ``c`` share a single row with the same value in the ``index`` column, hence a join by that index should return a table with just that row.
.. doctest::
>>> print a.joined(c, "index", title='A&C by "index"')
A&C by "index"
=================================
index col2 col3 C_col_c2
---------------------------------
1 2 3 2
---------------------------------
A natural join of tables ``a`` and ``b`` results in a table with only rows that were identical between the two parents.
.. doctest::
>>> print a.joined(b, title='A&B Natural Join')
A&B Natural Join
=====================
index col2 col3
---------------------
1 2 3
---------------------
We test the outer join by defining an additional table with different dimensions, and conducting a join specifying ``inner_join=False``.
.. doctest::
>>> d=Table(header=["index", "col_c2"], rows=[[5,42],[6,23]], title="D")
>>> print d
D
===============
index col_c2
---------------
5 42
6 23
---------------
>>> print c.joined(d,inner_join=False, title='C&D Outer join')
C&D Outer join
======================================
index col_c2 D_index D_col_c2
--------------------------------------
1 2 5 42
1 2 6 23
3 2 5 42
3 2 6 23
3 5 5 42
3 5 6 23
--------------------------------------
We establish the ``joined`` method works for mixtures of character and numerical data, setting some indices and some cell values to be strings.
.. doctest::
>>> a=Table(header=["index", "col2","col3"],
... rows=[[1,2,"3"],["2",3,1],[2,6,5]], title="A")
>>> b=Table(header=["index", "col2","col3"],
... rows=[[1,2,"3"],["2",2,1],[3,6,3]], title="B")
>>> assert a.joined(b, ["index", "col3"],["index", "col3"]).getRawData()\
... == a.joined(b,["index","col3"]).getRawData()
We test that the ``joined`` method works when the column index orders differ.
.. doctest::
>>> t1_header = ['a', 'b']
>>> t1_rows = [(1,2),(3,4)]
>>> t2_header = ['b', 'c']
>>> t2_rows = [(3,6),(4,8)]
>>> t1 = Table(header = t1_header, rows = t1_rows, title='t1')
>>> t2 = Table(header = t2_header, rows = t2_rows, title='t2')
>>> t3 = t1.joined(t2, columns_self = ["b"], columns_other = ["b"])
>>> print t3
==============
a b t2_c
--------------
3 4 8
--------------
We then establish that a join with no values does not cause a failure, just returns an empty ``Table``.
.. doctest::
>>> t4_header = ['b', 'c']
>>> t4_rows = [(5,6),(7,8)]
>>> t4 = LoadTable(header = t4_header, rows = t4_rows)
>>> t4.Title = 't4'
>>> t5 = t1.joined(t4, columns_self = ["b"], columns_other = ["b"])
>>> print t5
==============
a b t4_c
--------------
--------------
Whose representation looks like
.. doctest::
>>> t5
Table(numrows=0, numcols=3, header=['a', 'b', 't4_c'], rows=[])
Transposing a table
-------------------
Tables can be transposed.
.. doctest::
>>> from cogent import LoadTable
>>> title='#Full OTU Counts'
>>> header = ['#OTU ID', '14SK041', '14SK802']
>>> rows = [[-2920, '332', 294],
... [-1606, '302', 229],
... [-393, 141, 125],
... [-2109, 138, 120],
... [-5439, 104, 117],
... [-1834, 70, 75],
... [-18588, 65, 47],
... [-1350, 60, 113],
... [-2160, 57, 52],
... [-11632, 47, 36]]
>>> table = LoadTable(header=header,rows=rows,title=title)
>>> print table
#Full OTU Counts
=============================
#OTU ID 14SK041 14SK802
-----------------------------
-2920 332 294
-1606 302 229
-393 141 125
-2109 138 120
-5439 104 117
-1834 70 75
-18588 65 47
-1350 60 113
-2160 57 52
-11632 47 36
-----------------------------
We now transpose this. We require a new column heading for header data and an identifier for which existing column will become the header (default is index 0).
.. doctest::
>>> tp = table.transposed(new_column_name='sample',
... select_as_header='#OTU ID', space=2)
...
>>> print tp
==============================================================================
sample -2920 -1606 -393 -2109 -5439 -1834 -18588 -1350 -2160 -11632
------------------------------------------------------------------------------
14SK041 332 302 141 138 104 70 65 60 57 47
14SK802 294 229 125 120 117 75 47 113 52 36
------------------------------------------------------------------------------
We test transposition with default value is the same.
.. doctest::
>>> tp = table.transposed(new_column_name='sample', space=2)
...
>>> print tp
==============================================================================
sample -2920 -1606 -393 -2109 -5439 -1834 -18588 -1350 -2160 -11632
------------------------------------------------------------------------------
14SK041 332 302 141 138 104 70 65 60 57 47
14SK802 294 229 125 120 117 75 47 113 52 36
------------------------------------------------------------------------------
We test transposition selecting a different column to become the header.
.. doctest::
>>> tp = table.transposed(new_column_name='sample',
... select_as_header='14SK802', space=2)
...
>>> print tp
==============================================================================
sample 294 229 125 120 117 75 47 113 52 36
------------------------------------------------------------------------------
#OTU ID -2920 -1606 -393 -2109 -5439 -1834 -18588 -1350 -2160 -11632
14SK041 332 302 141 138 104 70 65 60 57 47
------------------------------------------------------------------------------
Counting rows
-------------
We can count the number of rows for which a condition holds. This method uses the same arguments as ``filtered`` but returns an integer result only.
.. doctest::
>>> print c.count("col_c2 == 2")
2
>>> print c.joined(d,inner_join=False).count("index==3 and D_index==5")
2
Testing a sub-component
-----------------------
Before using ``Table``, we exercise some formatting code:
.. doctest::
>>> from cogent.format.table import formattedCells, phylipMatrix, latex
We check we can format an arbitrary 2D list, without a header, using the ``formattedCells`` function directly.
.. doctest::
>>> data = [[230, 'acdef', 1.3], [6, 'cc', 1.9876]]
>>> head = ['one', 'two', 'three']
>>> header, formatted = formattedCells(data, header = head)
>>> print formatted
[['230', 'acdef', '1.3000'], [' 6', ' cc', '1.9876']]
>>> print header
['one', ' two', ' three']
We directly test the latex formatting.
.. doctest::
>>> print latex(formatted, header, justify='lrl', caption='A legend',
... label="table:test")
\begin{longtable}[htp!]{ l r l }
\hline
\bf{one} & \bf{two} & \bf{three} \\
\hline
\hline
230 & acdef & 1.3000 \\
6 & cc & 1.9876 \\
\hline
\caption{A legend}
\label{table:test}
\end{longtable}
..
Import the ``os`` module so some file cleanup can be done at the end. To check the contents of those files, just delete the following prior to running the test. The try/except clause below is aimed at case where ``junk.pdf`` wasn't created due to ``reportlab`` not being present.
.. doctest::
:hide:
>>> import os
>>> to_delete = ['t3.pickle', 't2.csv', 't2.csv.gz', 't3.tab',
... 'test3b.txt']
>>> for f in to_delete:
... try:
... os.remove(f)
... except OSError:
... pass
PyCogent-1.5.3/tests/test_util/test_transform.py 000644 000765 000024 00000112414 12024702176 023046 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of transformation and composition functions .
"""
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import identity
from cogent.util.transform import apply_each, bools, bool_each, \
conjoin, all, both,\
disjoin, any, either, negate, none, neither, compose, compose_many, \
per_shortest, per_longest, for_seq, \
has_field, extract_field, test_field, index, test_container, \
trans_except, trans_all, make_trans, find_any, find_no, find_all,\
keep_if_more, exclude_if_more, keep_if_more_other, exclude_if_more_other,\
keep_chars,exclude_chars, reorder, reorder_inplace, float_from_string,\
first, last, first_in_set, last_in_set, first_not_in_set, last_not_in_set,\
first_index, last_index, first_index_in_set, last_index_in_set, \
first_index_not_in_set, last_index_not_in_set, perm, comb, cross_comb, _increment_comb
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Sandra Smit", "Zongzhi Liu"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Production"
class has_x(object):
#convenience class for has_field and related functions
def __init__(self, x):
self.x = x
def __hash__(self):
return hash(self.x)
def __str__(self):
return str(self.x)
class has_y(object):
#convenience class for has_field and related functions
def __init__(self, y):
self.y = y
def __hash__(self):
return hash(self.y)
def __str__(self):
return str(self.y)
class metafunctionsTests(TestCase):
"""Tests of standalone functions."""
def setUp(self):
"""Define some standard functions and data."""
self.Numbers = range(20)
self.SmallNumbers = range(3)
self.SmallNumbersRepeated = range(5) * 4
self.Letters = 'abcde'
self.Mixed = list(self.Letters) + range(5)
self.firsts = 'ab2'
self.seconds = '0bc'
self.is_char = lambda x: isinstance(x, str) and len(x) == 1
self.is_vowel = lambda x: x in 'aeiou'
self.is_consonant = lambda x: x not in 'aeiuo'
self.is_number = lambda x: isinstance(x, int)
self.is_odd_number = lambda x: x%2
self.is_odd_letter = lambda x: x in 'acegikmoqs'
self.is_zero = lambda x: x == 0
self.is_small = lambda x: x < 3
self.double = lambda x: x * 2
self.minusone = lambda x: x - 1
#function to test *args, **kwargs)
self.is_alpha_digit = lambda first, second: \
first.isalpha() and second.isdigit()
self.is_digit_alpha = lambda first, second: \
first.isdigit() and second.isalpha()
def test_apply_each(self):
"""apply_each should apply each function to args, kwargs"""
self.assertEqual(apply_each( \
[self.is_char, self.is_vowel, self.is_consonant, self.is_number], \
self.Letters[0]), [True, True, False, False])
self.assertEqual(apply_each( \
[self.is_char, self.is_vowel, self.is_consonant, self.is_number], \
self.Letters[1]), [True, False, True, False])
self.assertEqual(apply_each( \
[self.double, self.minusone], self.SmallNumbers[0]), [0, -1])
self.assertEqual(apply_each( \
[self.double, self.minusone], self.SmallNumbers[1]), [2, 0])
expects = [[True, False], [False, False], [False, True]]
for i in range(len(expects)):
self.assertEqual(apply_each( \
[self.is_alpha_digit, self.is_digit_alpha],
self.firsts[i], self.seconds[i]), expects[i])
self.assertEqual(apply_each( \
[self.is_alpha_digit, self.is_digit_alpha],
self.firsts[i], second=self.seconds[i]), expects[i])
self.assertEqual(apply_each( \
[self.is_alpha_digit, self.is_digit_alpha],
second=self.seconds[i], first=self.firsts[i]), expects[i])
def test_bools(self):
"""bools should convert items to True or False."""
self.assertEqual(bools(self.Letters), [True]*5)
self.assertEqual(bools(self.Numbers), [False] + [True]*19)
def test_bool_each(self):
"""bool_each should return boolean version of applying each f to args"""
self.assertEqual(bool_each([self.double, self.minusone], \
self.SmallNumbers[0]), [False, True])
self.assertEqual(bool_each([self.double, self.minusone], \
self.SmallNumbers[1]), [True, False])
def test_conjoin(self):
"""conjoin should return True if all components True"""
self.assertEqual(conjoin([self.is_odd_letter,self.is_vowel],'a'), True)
self.assertEqual(conjoin([self.is_odd_letter,self.is_vowel], x='b'),
False)
self.assertEqual(conjoin([self.is_odd_letter,self.is_vowel],'c'), False)
self.assertEqual(conjoin([self.is_odd_letter,self.is_vowel],'e'), True)
#technically, this one should be true as well, but I left it off to
#have an even vowel test case...
self.assertEqual(conjoin([self.is_odd_letter,self.is_vowel],'u'), False)
#should short-circuit, i.e. not evaluate later cases after False
self.assertEqual(conjoin([self.is_odd_letter, self.fail], 'b'), False)
self.assertRaises(AssertionError, conjoin, \
[self.is_odd_letter, self.fail], 'a')
def test_all(self):
"""all should return a function returning True if all components True"""
odd_vowel = all([self.is_odd_letter, self.is_vowel, self.is_char])
self.assertEqual(odd_vowel('a'), True)
self.assertEqual(map(odd_vowel, 'abceu'),
[True,False,False,True,False])
odd_number = all([self.is_odd_number, self.is_number])
self.assertEqual(map(odd_number, range(5)), [False,True]*2+[False])
#should short-circuit, i.e. not evaluate later cases after False
self.assertEqual(all([self.is_odd_letter, self.fail])('b'), False)
self.assertRaises(AssertionError, all([self.is_odd_letter,self.fail]),\
'a')
def test_both(self):
"""both should return True if both components True"""
odd_vowel = both(self.is_odd_letter, self.is_vowel)
self.assertEqual(map(odd_vowel, 'abcu'), [True,False,False,False])
#should short-circuit
self.assertEqual(both(self.is_odd_letter, self.fail)('b'), False)
self.assertRaises(AssertionError, both(self.is_odd_letter, self.fail),\
'a')
def test_disjoin(self):
"""disjoin should return True if any component True"""
self.assertEqual(disjoin([self.is_odd_letter,self.is_vowel], 'a'), True)
self.assertEqual(disjoin([self.is_odd_letter,self.is_vowel], 'b'),False)
self.assertEqual(disjoin([self.is_odd_letter,self.is_vowel], 'c'), True)
self.assertEqual(disjoin([self.is_odd_letter,self.is_vowel], x='u'),
True)
#should short-circuit after first True
self.assertEqual(disjoin([self.is_odd_letter, self.fail], 'a'), True)
self.assertRaises(AssertionError, \
disjoin, [self.is_odd_letter, self.fail], 'b')
def test_any(self):
"""any should return a function returning True if any component True"""
odd_vowel = any([self.is_odd_letter, self.is_vowel])
self.assertEqual(odd_vowel('a'), True)
self.assertEqual(map(odd_vowel, 'abceu'), [True,False,True,True,True])
odd = any([self.is_odd_number, self.is_small])
self.assertEqual(map(odd, range(5)), [True]*4+[False])
#should short-circuit after first True
self.assertEqual(any([self.is_odd_letter, self.fail])(x='a'), True)
self.assertRaises(AssertionError, any([self.is_odd_letter,self.fail]),\
'b')
def test_either(self):
"""either should return function returning True if either component True"""
odd_vowel = either(self.is_odd_letter, self.is_vowel)
self.assertEqual(map(odd_vowel, 'abcu'), [True,False,True,True])
#should short-circuit
self.assertEqual(either(self.is_odd_letter, self.fail)(x='a'), True)
self.assertRaises(AssertionError, \
either(self.is_odd_letter, self.fail), 'b')
def test_negate(self):
"""negate should return True if no component True"""
self.assertEqual(negate([self.is_odd_letter,self.is_vowel], 'a'), False)
self.assertEqual(negate([self.is_odd_letter,self.is_vowel], 'b'), True)
self.assertEqual(negate([self.is_odd_letter,self.is_vowel], 'c'), False)
self.assertEqual(negate([self.is_odd_letter,self.is_vowel], 'u'), False)
#should short-circuit after first True
self.assertEqual(negate([self.is_odd_letter, self.fail], x='a'), False)
self.assertRaises(AssertionError, \
negate, [self.is_odd_letter, self.fail], 'b')
def test_none(self):
"""none should return a function returning True if no component True"""
odd_vowel = none([self.is_odd_letter, self.is_vowel])
self.assertEqual(odd_vowel('a'), False)
self.assertEqual(map(odd_vowel, 'abceu'), [False,True] + [False]*3)
odd = none([self.is_odd_number, self.is_small])
self.assertEqual(map(odd, range(5)), [False]*4+[True])
#should short-circuit after first True
self.assertEqual(none([self.is_odd_letter, self.fail])(x='a'), False)
self.assertRaises(AssertionError, none([self.is_odd_letter,self.fail]),\
'b')
def test_neither(self):
"""neither should return function returning True if each component False"""
odd_vowel = neither(self.is_odd_letter, self.is_vowel)
self.assertEqual(map(odd_vowel, 'abcu'), [False,True,False,False])
#should short-circuit
self.assertEqual(neither(self.is_odd_letter, self.fail)(x='a'), False)
self.assertRaises(AssertionError, \
neither(self.is_odd_letter, self.fail), 'b')
def test_compose(self):
"""compose should return function returning f(g(x))"""
ds = compose(self.double, self.minusone)
sd = compose(self.minusone, self.double)
self.assertEqual(ds(5), 8)
self.assertEqual(sd(x=5), 9)
#check that it works when arg lists are different
commafy = compose(','.join, list)
self.assertEqual(commafy('abc'), 'a,b,c')
self.assertEqual(commafy(''), '')
self.assertEqual(commafy('a'), 'a')
def test_compose_many(self):
"""compose_many should return composition of all args"""
from numpy import arange
def to_strings(x):
return map(str, x)
printable_range = compose_many(''.join, to_strings, range)
printable_arange = compose_many(''.join, to_strings, arange)
self.assertEqual(printable_range(3), '012')
self.assertEqual(printable_range(0), '')
self.assertEqual(printable_range(5), '01234')
self.assertEqual(printable_arange(stop=51, start=10, step=10),
'1020304050')
def test_identity(self):
"""identity should return x"""
for i in ['a', 'abc', None, '', [], [1], 1, 2**50, 0.3e-50, {'a':3}]:
assert identity(i) is i
def test_has_field(self):
"""has_field should return True if specified field exists."""
x = has_x(1)
y = has_y(1)
check_x = has_field('x')
self.assertEqual(check_x(x), True)
self.assertEqual(check_x(y), False)
check_y = has_field('y')
self.assertEqual(check_y(x), False)
self.assertEqual(check_y(y), True)
del y.y
self.assertEqual(check_y(y), False)
y.x = 3
self.assertEqual(check_x(y), True)
def test_extract_field(self):
"""extract_field should apply constructor to field, or return None"""
num = has_x('1')
alpha = has_x('x')
y = has_y('1')
extractor = extract_field('x')
self.assertEqual(extractor(num), '1')
self.assertEqual(extractor(alpha), 'x')
self.assertEqual(extractor(y), None)
int_extractor = extract_field('x', int)
self.assertEqual(int_extractor(num), 1)
self.assertEqual(int_extractor(alpha), None)
self.assertEqual(int_extractor(y), None)
def test_test_field(self):
"""test_field should return boolean result of applying constructor"""
num = has_x('5')
alpha = has_x('x')
zero = has_x(0)
y = has_y('5')
tester = test_field('x')
self.assertEqual(tester(num), True)
self.assertEqual(tester(alpha), True)
self.assertEqual(tester(y), False)
int_tester = test_field('x', int)
self.assertEqual(int_tester(num), True)
self.assertEqual(int_tester(alpha), False)
self.assertEqual(int_tester(y), False)
self.assertEqual(int_tester(zero), False)
def test_index(self):
"""index should index objects by specified field or identity"""
num = has_x(5)
let = has_x('5')
zer = has_x('0')
non = has_x(None)
y = has_y(3)
items = [num, let, zer, non, y]
duplicates = items * 3
basic_indexer = index()
i = basic_indexer(items)
self.assertEqual(i, {num:[num], let:[let], zer:[zer], non:[non], y:[y]})
#test reusability
i = basic_indexer([3,3,4])
self.assertEqual(i, {3:[3, 3], 4:[4]})
#test duplicates
d = basic_indexer(duplicates)
self.assertEqual(d, {num:[num]*3, let:[let]*3, zer:[zer]*3, \
non:[non]*3, y:[y]*3})
#test with constructor
str_indexer = index(str)
i = str_indexer(items)
self.assertEqual(i, {'5':[num,let], '0':[zer], 'None':[non], '3':[y]})
#test order correct in duplicates
i = str_indexer(duplicates)
self.assertEqual(i, {'5':[num,let,num,let,num,let], '0':[zer,zer,zer],
'None':[non,non,non], '3':[y,y,y]})
#test with squashing
overwriter = index(str, overwrite=True)
i = overwriter(duplicates)
self.assertEqual(i, {'5':let, '0':zer, 'None':non, '3':y})
def test_test_container(self):
"""test_container should return True or False in a typesafe way."""
test_dict = test_container({'a':1})
test_list = test_container([1,2,3])
test_str = test_container('438hfanvr438')
for item in (1, 2, 3):
assert test_list(item)
assert not test_dict(item)
assert not test_str(item)
assert test_dict('a')
assert not test_list('a')
assert test_str('a')
for item in ('4', 'h', 'fan'):
assert not test_dict(item)
assert not test_list(item)
assert test_str(item)
for item in (['x','y'],{},{'a':3},'@#@',('a','b'),None,False):
assert not test_dict(item)
assert not test_list(item)
assert not test_str(item)
class SequenceFunctionsTests(TestCase):
"""Tests of standalone functions for dealing with sequences."""
def test_per_shortest(self):
"""per_shortest should divide by min(len(x), len(y))"""
self.assertEqual(per_shortest(20, 'aaaaaa', 'bbbb'), 5)
self.assertEqual(per_shortest(20, 'aaaaaa', 'b'), 20)
self.assertEqual(per_shortest(20, 'a', 'bbbbb'), 20)
self.assertEqual(per_shortest(20, '', 'b'), 0)
self.assertEqual(per_shortest(20, '', ''), 0)
#check that it does it in floating-point
self.assertEqual(per_shortest(1, 'aaaaaa', 'bbbb'), 0.25)
#check that it raises TypeError on non-seq
self.assertRaises(TypeError, per_shortest, 1, 2, 3)
def test_per_longest(self):
"""per_longest should divide by max(len(x), len(y))"""
self.assertEqual(per_longest(20, 'aaaaaa', 'bbbb'), 20/6.0)
self.assertEqual(per_longest(20, 'aaaaaa', 'b'), 20/6.0)
self.assertEqual(per_longest(20, 'a', 'bbbbb'), 20/5.0)
self.assertEqual(per_longest(20, '', 'b'), 20)
self.assertEqual(per_longest(20, '', ''), 0)
#check that it does it in floating-point
self.assertEqual(per_longest(1, 'aaaaaa', 'bbbb'), 1/6.0)
#check that it raises TypeError on non-seq
self.assertRaises(TypeError, per_longest, 1, 2, 3)
def test_for_seq(self):
"""for_seq should return the correct function"""
is_eq = lambda x,y: x == y
is_ne = lambda x,y: x != y
lt_5 = lambda x,y: x + y < 5
diff = lambda x,y: x - y
sumsq = lambda x: sum([i*i for i in x])
long_norm = lambda s, x, y: (s + 0.0) / max(len(x), len(y))
times_two = lambda s, x, y: 2*s
empty = []
s1 = [1,2,3,4,5]
s2 = [1,3,2,4,5]
s3 = [1,1,1,1,1]
s4 = [5,5,5,5,5]
s5 = [3,3,3,3,3]
short = [1]
#test behavior with default aggregator and normalizer
f = for_seq(is_eq)
self.assertFloatEqual(f(s1, s1), 1.0)
self.assertFloatEqual(f(s1, short), 1.0)
self.assertFloatEqual(f(short, s1), 1.0)
self.assertFloatEqual(f(short, s4), 0.0)
self.assertFloatEqual(f(s4, short), 0.0)
self.assertFloatEqual(f(s1,s2), 0.6)
f = for_seq(is_ne)
self.assertFloatEqual(f(s1, s1), 0.0)
self.assertFloatEqual(f(s1, short), 0.0)
self.assertFloatEqual(f(short, s1), 0.0)
self.assertFloatEqual(f(short, s4), 1.0)
self.assertFloatEqual(f(s4, short), 1.0)
self.assertFloatEqual(f(s1, s2), 0.4)
f = for_seq(lt_5)
self.assertFloatEqual(f(s3,s3), 1.0)
self.assertFloatEqual(f(s3,s4), 0.0)
self.assertFloatEqual(f(s2,s3), 0.6)
f = for_seq(diff)
self.assertFloatEqual(f(s1,s1), 0.0)
self.assertFloatEqual(f(s4,s1), 2.0)
self.assertFloatEqual(f(s1,s4), -2.0)
#test behavior with different aggregator
f = for_seq(diff)
self.assertFloatEqual(f(s1,s5), 0)
f = for_seq(diff, aggregator=sum)
self.assertFloatEqual(f(s1,s5), 0)
f = for_seq(diff, aggregator=sumsq)
self.assertFloatEqual(f(s1,s5), 2.0)
#test behavior with different normalizer
f = for_seq(diff, aggregator=sumsq, normalizer=None)
self.assertFloatEqual(f(s1,s5), 10)
f = for_seq(diff, aggregator=sumsq)
self.assertFloatEqual(f(s1,s5), 2.0)
f = for_seq(diff, aggregator=sumsq, normalizer=times_two)
self.assertFloatEqual(f(s1,s5), 20)
f = for_seq(diff, aggregator=sumsq)
self.assertFloatEqual(f(s5,short), 4)
f = for_seq(diff, aggregator=sumsq, normalizer=long_norm)
self.assertFloatEqual(f(s5,short), 0.8)
class Filter_Criteria_Tests(TestCase):
"""Tests of standalone functions used as filter criteria"""
def test_trans_except(self):
"""trans_except should return trans table mapping non-good chars to x"""
a = trans_except('Aa', '-')
none = trans_except('', '*')
some = trans_except('zxcvbnm,.zxcvbnm,.', 'V')
self.assertEqual('abcABA'.translate(a), 'a--A-A')
self.assertEqual(''.translate(a), '')
self.assertEqual('12345678'.translate(a), '--------')
self.assertEqual(''.translate(none), '')
self.assertEqual('abcdeEFGHI12345&*(!@'.translate(none), '*'*20)
self.assertEqual('qazwsxedcrfv'.translate(some),'VVzVVxVVcVVv')
def test_trans_all(self):
"""trans_all should return trans table mapping all bad chars to x"""
a = trans_all('Aa', '-')
none = trans_all('', '*')
some = trans_all('zxcvbnm,.zxcvbnm,.', 'V')
self.assertEqual('abcABA'.translate(a), '-bc-B-')
self.assertEqual(''.translate(a), '')
self.assertEqual('12345678'.translate(a), '12345678')
self.assertEqual(''.translate(none), '')
self.assertEqual('abcdeEFGHI12345&*(!@'.translate(none), \
'abcdeEFGHI12345&*(!@')
self.assertEqual('qazwsxedcrfv'.translate(some),'qaVwsVedVrfV')
def test_make_trans(self):
"""make_trans should return trans table mapping chars to default"""
a = make_trans()
self.assertEqual('abc123'.translate(a), 'abc123')
a = make_trans('a', 'x')
self.assertEqual('abc123'.translate(a), 'xbc123')
a = make_trans('ac', 'xa')
self.assertEqual('abc123'.translate(a), 'xba123')
a = make_trans('ac', 'xa', '.')
self.assertEqual('abc123'.translate(a), 'x.a...')
self.assertRaises(ValueError, make_trans, 'ac', 'xa', 'av')
def test_find_any(self):
"""find_any should be True if one of the words is in the string"""
f = find_any('ab')
self.assertEqual(f(''),0) #empty
self.assertRaises(AttributeError,f,None) # none
self.assertEqual(f('cde'),0) #none of the elements
self.assertEqual(f('axxx'),1) #one of the elements
self.assertEqual(f('bxxx'),1) #one of the elements
self.assertEqual(f('axxxb'),1) #all elements
self.assertEqual(f('aaaa'),1) #repeated element
# works on any sequence
f = find_any(['foo','bar'])
self.assertEqual(f("joe"),0)
self.assertEqual(f("only foo"),1)
self.assertEqual(f("bar and foo"),1)
# does NOT work on numbers
def test_find_no(self):
"""find_no should be True if none of the words in the string"""
f = find_no('ab')
self.assertEqual(f(''),1) #empty
self.assertRaises(AttributeError,f,None) # none
self.assertEqual(f('cde'),1) #none of the elements
self.assertEqual(f('axxx'),0) #one of the elements
self.assertEqual(f('bxxx'),0) #one of the elements
self.assertEqual(f('axxxb'),0) #all elements
self.assertEqual(f('aaaa'),0) #repeated element
# works on any sequence
f = find_no(['foo','bar'])
self.assertEqual(f("joe"),1)
self.assertEqual(f("only foo"),0)
self.assertEqual(f("bar and foo"),0)
# does NOT work on numbers
def test_find_all(self):
"""find_all should be True if all words appear in the string"""
f = find_all('ab')
self.assertEqual(f(''),0) #empty
self.assertRaises(AttributeError,f,None) # none
self.assertEqual(f('cde'),0) #none of the elements
self.assertEqual(f('axxx'),0) #one of the elements
self.assertEqual(f('bxxx'),0) #one of the elements
self.assertEqual(f('axxxb'),1) #all elements
self.assertEqual(f('aaaa'),0) #repeated element
# works on any sequence
f = find_all(['foo','bar'])
self.assertEqual(f("joe"),0)
self.assertEqual(f("only foo"),0)
self.assertEqual(f("bar and foo"),1)
# does NOT work on numbers
def test_keep_if_more(self):
"""keep_if_more should be True if #items in s > x"""
self.assertRaises(ValueError, keep_if_more,'lksfj','ksfd') #not int
self.assertRaises(IndexError,keep_if_more,'ACGU',-3) #negative
f = keep_if_more('a',0) #zero
self.assertEqual(f(''),0)
self.assertEqual(f('a'),1)
self.assertEqual(f('b'),0)
# works on strings
f = keep_if_more('ACGU',5) #positive
self.assertEqual(f(''),0)
self.assertEqual(f('ACGUAGCUioooNNNNNA'),1)
self.assertEqual(f('NNNNNNN'),0)
# works on words
f = keep_if_more(['foo'],1)
self.assertEqual(f(''),0)
self.assertEqual(f(['foo', 'bar','foo']),1)
self.assertEqual(f(['joe']),0)
# works on numbers
f = keep_if_more([0,1],3)
self.assertEqual(f(''),0)
self.assertEqual(f([0,1,2,3,4,5]),0)
self.assertEqual(f([0,1,0,1]),1)
def test_exclude_if_more(self):
"""exclude_if_more should be True if #items in s <= x"""
self.assertRaises(ValueError, exclude_if_more,'lksfj','ksfd') #not int
self.assertRaises(IndexError,exclude_if_more,'ACGU',-3) #negative
f = exclude_if_more('a',0) #zero
self.assertEqual(f(''),1)
self.assertEqual(f('a'),0)
self.assertEqual(f('b'),1)
# works on strings
f = exclude_if_more('ACGU',5) #positive
self.assertEqual(f(''),1)
self.assertEqual(f('ACGUAGCUioooNNNNNA'),0)
self.assertEqual(f('NNNNNNN'),1)
# works on words
f = exclude_if_more(['foo'],1)
self.assertEqual(f(''),1)
self.assertEqual(f(['foo', 'bar','foo']),0)
self.assertEqual(f(['joe']),1)
# works on numbers
f = exclude_if_more([0,1],3)
self.assertEqual(f(''),1)
self.assertEqual(f([0,1,2,3,4,5]),1)
self.assertEqual(f([0,1,0,1]),0)
def test_keep_if_more_other(self):
"""keep_if_more_other should be True if #other items > x"""
self.assertRaises(ValueError, keep_if_more_other,'lksfj','ks') #not int
self.assertRaises(IndexError,keep_if_more_other,'ACGU',-3) #negative
f = keep_if_more_other('a',0) #zero
self.assertEqual(f(''),0)
self.assertEqual(f('a'),0)
self.assertEqual(f('b'),1)
# works on strings
f = keep_if_more_other('ACGU',5) #positive
self.assertEqual(f(''),0)
self.assertEqual(f('ACGUNNNNN'),0)
self.assertEqual(f('ACGUAGCUioooNNNNNA'),1)
self.assertEqual(f('NNNNNNN'),1)
# works on words
f = keep_if_more_other(['foo'],1)
self.assertEqual(f(''),0)
self.assertEqual(f(['foo', 'bar','foo']),0)
self.assertEqual(f(['joe','oef']),1)
# works on numbers
f = keep_if_more_other([0,1],3)
self.assertEqual(f(''),0)
self.assertEqual(f([0,1,2,3,4,5]),1)
self.assertEqual(f([0,1,0,1]),0)
def test_exclude_if_more_other(self):
"""exclude_if_more_other should be True if #other items <= x"""
self.assertRaises(ValueError, exclude_if_more_other,'lks','ks') #not int
self.assertRaises(IndexError,exclude_if_more_other,'ACGU',-3) #negative
f = exclude_if_more_other('a',0) #zero
self.assertEqual(f(''),1)
self.assertEqual(f('a'),1)
self.assertEqual(f('b'),0)
# works on strings
f = exclude_if_more_other('ACGU',5) #positive
self.assertEqual(f(''),1)
self.assertEqual(f('ACGUNNNNN'),1)
self.assertEqual(f('ACGUAGCUioooNNNNNA'),0)
self.assertEqual(f('NNNNNNN'),0)
# works on words
f = exclude_if_more_other(['foo'],1)
self.assertEqual(f(''),1)
self.assertEqual(f(['foo', 'bar','foo']),1)
self.assertEqual(f(['joe','oef']),0)
# works on numbers
f = exclude_if_more_other([0,1],3)
self.assertEqual(f(''),1)
self.assertEqual(f([0,1,2,3,4,5]),0)
self.assertEqual(f([0,1,0,1]),1)
def test_keep_chars(self):
"""keep_chars returns a string containing only chars in keep"""
f = keep_chars('ab c3*[')
self.assertEqual(f(''),'') #empty
self.assertRaises(AttributeError,f,None) #None
#one character, case sensitive
self.assertEqual(f('b'),'b')
self.assertEqual(f('g'),'')
self.assertEqual(f('xyz123'),'3')
self.assertEqual(f('xyz 123'),' 3')
#more characters, case sensitive
self.assertEqual(f('kjbwherzcagebcujrkcs'),'bcabcc')
self.assertEqual(f('f[ffff*ff*fff3fff'),'[**3')
# case insensitive
f = keep_chars('AbC',False)
self.assertEqual(f('abcdef'),'abc')
self.assertEqual(f('ABCDEF'),'ABC')
self.assertEqual(f('aBcDeF'),'aBc')
def test_exclude_chars(self):
"""exclude_chars returns string containing only chars not in exclude"""
f = exclude_chars('ab c3*[')
self.assertEqual(f(''),'') #empty
self.assertRaises(AttributeError,f,None) #None
#one character, case sensitive
self.assertEqual(f('b'),'')
self.assertEqual(f('g'),'g')
self.assertEqual(f('xyz123'),'xyz12')
self.assertEqual(f('xyz 123'),'xyz12')
#more characters, case sensitive
self.assertEqual(f('axxxbxxxcxxx'),'xxxxxxxxx')
# case insensitive
f = exclude_chars('AbC',False)
self.assertEqual(f('abcdef'),'def')
self.assertEqual(f('ABCDEF'),'DEF')
self.assertEqual(f('aBcDeF'),'DeF')
def test_reorder(self):
"""reorder should always use the same order when invoked"""
list_test = reorder([3,2,1])
dict_test = reorder(['x','y','z'])
multi_test = reorder([3,2,2])
null_test = reorder([])
first_seq = 'abcde'
second_seq = [3,4,5,6,7]
empty_list = []
empty_dict = {}
full_dict = {'a':3, 'c':5, 'x':'abc','y':'234','z':'qaz'}
for i in (first_seq, second_seq, empty_list, empty_dict):
self.assertEqual(null_test(i), [])
self.assertEqual(list_test(first_seq), ['d','c','b'])
self.assertEqual(list_test(second_seq), [6,5,4])
self.assertEqual(multi_test(first_seq), ['d','c','c'])
self.assertEqual(dict_test(full_dict), ['abc','234','qaz'])
self.assertRaises(KeyError, dict_test, empty_dict)
self.assertRaises(IndexError, list_test, empty_list)
def test_reorder_inplace(self):
"""reorder_inplace should replace object's data with new order"""
attr_test = reorder_inplace([3,2,1], 'Data')
obj_test = reorder_inplace([3,2,2])
seq = [3,4,5,6,7]
class obj(object):
pass
o = obj()
o.XYZ = [9, 7, 5]
o.Data = ['a','b','c','d','e']
orig_data = o.Data
self.assertEqual(obj_test(seq), [6,5,5])
self.assertEqual(seq, [6,5,5])
assert attr_test(o) is o
self.assertEqual(o.XYZ, [9,7,5])
self.assertEqual(o.Data, ['d','c','b'])
assert orig_data is o.Data
def test_float_from_string(self):
"""float_from_string should ignore funny chars"""
ffs = float_from_string
self.assertEqual(ffs('3.5'), 3.5)
self.assertEqual(ffs(' -3.45e-10 '), float(' -3.45e-10 '))
self.assertEqual(ffs('jsdjhsdf[]()0.001IVUNZSDFl]]['), 0.001)
def test_first_index(self):
"""first_index should return index of first occurrence where f(s)"""
vowels = 'aeiou'
is_vowel = lambda x: x in vowels
s1 = 'ebcua'
s2 = 'bcbae'
s3 = ''
s4 = 'cbd'
self.assertEqual(first_index(s1, is_vowel), 0)
self.assertEqual(first_index(s2, is_vowel), 3)
self.assertEqual(first_index(s3, is_vowel), None)
self.assertEqual(first_index(s4, is_vowel), None)
def test_last_index(self):
"""last_index should return index of last occurrence where f(s)"""
vowels = 'aeiou'
is_vowel = lambda x: x in vowels
s1 = 'ebcua'
s2 = 'bcbaef'
s3 = ''
s4 = 'cbd'
self.assertEqual(last_index(s1, is_vowel), 4)
self.assertEqual(last_index(s2, is_vowel), 4)
self.assertEqual(last_index(s3, is_vowel), None)
self.assertEqual(last_index(s4, is_vowel), None)
def test_first_index_in_set(self):
"""first_index_in_set should return index of first occurrence """
vowels = 'aeiou'
s1 = 'ebcua'
s2 = 'bcbae'
s3 = ''
s4 = 'cbd'
self.assertEqual(first_index_in_set(s1, vowels), 0)
self.assertEqual(first_index_in_set(s2, vowels), 3)
self.assertEqual(first_index_in_set(s3, vowels), None)
self.assertEqual(first_index_in_set(s4, vowels), None)
def test_last_index_in_set(self):
"""last_index_in_set should return index of last occurrence"""
vowels = 'aeiou'
s1 = 'ebcua'
s2 = 'bcbaef'
s3 = ''
s4 = 'cbd'
self.assertEqual(last_index_in_set(s1, vowels), 4)
self.assertEqual(last_index_in_set(s2, vowels), 4)
self.assertEqual(last_index_in_set(s3, vowels), None)
self.assertEqual(last_index_in_set(s4, vowels), None)
def test_first_index_not_in_set(self):
"""first_index_not_in_set should return index of first occurrence """
vowels = 'aeiou'
s1 = 'ebcua'
s2 = 'bcbae'
s3 = ''
s4 = 'cbd'
self.assertEqual(first_index_not_in_set(s1, vowels), 1)
self.assertEqual(first_index_not_in_set(s2, vowels), 0)
self.assertEqual(first_index_not_in_set(s3, vowels), None)
self.assertEqual(first_index_not_in_set(s4, vowels), 0)
def test_last_index_not_in_set(self):
"""last_index_not_in_set should return index of last occurrence"""
vowels = 'aeiou'
s1 = 'ebcua'
s2 = 'bcbaef'
s3 = ''
s4 = 'cbd'
self.assertEqual(last_index_not_in_set(s1, vowels), 2)
self.assertEqual(last_index_not_in_set(s2, vowels), 5)
self.assertEqual(last_index_not_in_set(s3, vowels), None)
self.assertEqual(last_index_not_in_set(s4, vowels), 2)
def test_first(self):
"""first should return first occurrence where f(s)"""
vowels = 'aeiou'
is_vowel = lambda x: x in vowels
s1 = 'ebcua'
s2 = 'bcbae'
s3 = ''
s4 = 'cbd'
self.assertEqual(first(s1, is_vowel), 'e')
self.assertEqual(first(s2, is_vowel), 'a')
self.assertEqual(first(s3, is_vowel), None)
self.assertEqual(first(s4, is_vowel), None)
def test_last(self):
"""last should return last occurrence where f(s)"""
vowels = 'aeiou'
is_vowel = lambda x: x in vowels
s1 = 'ebcua'
s2 = 'bcbaef'
s3 = ''
s4 = 'cbd'
self.assertEqual(last(s1, is_vowel), 'a')
self.assertEqual(last(s2, is_vowel), 'e')
self.assertEqual(last(s3, is_vowel), None)
self.assertEqual(last(s4, is_vowel), None)
def test_first_in_set(self):
"""first_in_set should return first occurrence """
vowels = 'aeiou'
s1 = 'ebcua'
s2 = 'bcbae'
s3 = ''
s4 = 'cbd'
self.assertEqual(first_in_set(s1, vowels), 'e')
self.assertEqual(first_in_set(s2, vowels), 'a')
self.assertEqual(first_in_set(s3, vowels), None)
self.assertEqual(first_in_set(s4, vowels), None)
def test_last_in_set(self):
"""last_in_set should return last occurrence"""
vowels = 'aeiou'
s1 = 'ebcua'
s2 = 'bcbaef'
s3 = ''
s4 = 'cbd'
self.assertEqual(last_in_set(s1, vowels), 'a')
self.assertEqual(last_in_set(s2, vowels), 'e')
self.assertEqual(last_in_set(s3, vowels), None)
self.assertEqual(last_in_set(s4, vowels), None)
def test_first_not_in_set(self):
"""first_not_in_set should return first occurrence """
vowels = 'aeiou'
s1 = 'ebcua'
s2 = 'bcbae'
s3 = ''
s4 = 'cbd'
self.assertEqual(first_not_in_set(s1, vowels), 'b')
self.assertEqual(first_not_in_set(s2, vowels), 'b')
self.assertEqual(first_not_in_set(s3, vowels), None)
self.assertEqual(first_not_in_set(s4, vowels), 'c')
def test_last_not_in_set(self):
"""last_not_in_set should return last occurrence"""
vowels = 'aeiou'
s1 = 'ebcua'
s2 = 'bcbaef'
s3 = ''
s4 = 'cbd'
self.assertEqual(last_not_in_set(s1, vowels), 'c')
self.assertEqual(last_not_in_set(s2, vowels), 'f')
self.assertEqual(last_not_in_set(s3, vowels), None)
self.assertEqual(last_not_in_set(s4, vowels), 'd')
def test_perm(self):
"""perm should return correct permutations"""
self.assertEqual(list(perm('abc')), ['abc','acb','bac','bca','cab','cba'])
def test_comb(self):
"""comb should return correct combinations"""
self.assertEqual(list(comb(range(5), 0)),
[])
self.assertEqual(list(comb(range(5), 1)),
[[0], [1], [2], [3], [4]])
self.assertEqual(list(comb(range(5), 2)),
[[0, 1], [0, 2], [0, 3], [0, 4], [1, 2], [1, 3], [1, 4], [2, 3],
[2, 4], [3, 4]])
self.assertEqual(list(comb(range(5), 3)),
[[0, 1, 2], [0, 1, 3], [0, 1, 4], [0, 2, 3], [0, 2, 4], [0, 3, 4],
[1, 2, 3], [1, 2, 4], [1, 3, 4], [2, 3, 4]])
self.assertEqual(list(comb(range(5), 4)),
[[0, 1, 2, 3], [0, 1, 2, 4], [0, 1, 3, 4], [0, 2, 3, 4], [1, 2, 3, 4]])
self.assertEqual(list(comb(range(5), 5)),
[[0, 1, 2, 3, 4]])
def test_cross_comb(self):
"""cross_comb should produce correct combinations"""
v1 = range(2)
v2 = range(3)
v3 = list('abc')
vv1 = ([e] for e in v1)
v1_x_v2 = [[0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2]]
v1v2v3 = [[0, 0, 'a'], [0, 0, 'b'], [0, 0, 'c'], [0, 1, 'a'],
[0, 1, 'b'], [0, 1, 'c'], [0, 2, 'a'], [0, 2, 'b'],
[0, 2, 'c'], [1, 0, 'a'], [1, 0, 'b'], [1, 0, 'c'],
[1, 1, 'a'], [1, 1, 'b'], [1, 1, 'c'], [1, 2, 'a'],
[1, 2, 'b'], [1, 2, 'c']]
self.assertEqual(list( _increment_comb(vv1, v2)), v1_x_v2)
self.assertEqual(list( cross_comb([v1, v2])), v1_x_v2)
self.assertEqual(list(cross_comb([v1, v2, v3])), v1v2v3)
#run tests if invoked from the commandline
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_util/test_trie.py 000644 000765 000024 00000021614 12024702176 021777 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""tests for Trie and compressed Trie class."""
__author__ = "Jens Reeder"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jens Reeder"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jens Reeder"
__email__ = "jens.reeder@gmail.com"
__status__ = "Prototype"
from cogent.util.unit_test import TestCase, main
from cogent.util.trie import Trie, Compressed_Trie, build_prefix_map, build_trie, \
_build_prefix_map
class TrieTests(TestCase):
def setUp(self):
self.data = dict({"0": "ab", "1":"abababa", "2":"abab",
"3":"baba", "4":"ababaa","5":"a", "6":"abababa",
"7":"bab", "8":"babba"})
def test_init(self):
"""Trie init should create an empty trie."""
t = Trie()
self.assertEqual(t.root.labels, [])
self.assertEqual(t.root.children, {})
def test_insert_find(self):
"""An added key should be found by find."""
data = self.data
t = Trie()
for (label, seq) in data.iteritems():
t.insert(seq, label)
for (label, seq) in data.iteritems():
self.assertEqual(label in t.find(seq), True)
self.assertEqual(t.find("cacgchagc"), [])
self.assertEqual(t.find("abababa"), ["1","6"])
def test_insert_unique(self):
"""insert_unique should insert only unique words."""
data = self.data
t = Trie()
for (label, seq) in data.iteritems():
t._insert_unique(seq, label)
self.assertEqual(t.find("ab"), [])
self.assertEqual(t.find("cacgchagc"), [])
self.assertEqual(t.find("abababa"), ["1"])
def test_build_prefix_map(self):
"""prefix_map should map prefix strings."""
self.assertEqual(dict(_build_prefix_map(self.data.iteritems())),
{'1': ['0', '2', '5', '6'],
'8': [],
'3': ['7'],
'4': []})
class Compressed_Trie_Tests(TestCase):
def setUp(self):
self.data = dict({"0": "ab", "1":"abababa", "2":"abab",
"3":"baba", "4":"ababaa","5":"a", "6":"abababa",
"7":"bab", "8":"babba"})
self.trie = build_trie(self.data.iteritems())
def test_init(self):
"""Trie init should create an empty trie."""
t = Compressed_Trie()
self.assertEqual(t.root.labels, [])
self.assertEqual(t.root.children, {})
self.assertEqual(t.root.key, "")
def test_non_zero(self):
"""__non_zero__ should cehck for any data in the trie."""
t = Compressed_Trie()
self.assertEqual(t.__nonzero__(), False)
self.assertEqual(self.trie.__nonzero__(), True)
def test_len(self):
"""__len__ should return the number of seqs in the trie."""
self.assertEqual(len(self.trie), 9)
t = Compressed_Trie()
self.assertEqual(len(t), 0)
def test_size(self):
"""size should return the number of nodes in the trie."""
self.assertEqual(self.trie.size(), 10)
#empty trie contins only root node
t = Compressed_Trie()
self.assertEqual(size(t), 1)
def test_to_string(self):
"""_to_string should create a string representation."""
string_rep = """
key
{
\tkey a['5']
\t{
\t\tkey b['0']
\t\t{
\t\t\tkey ab['2']
\t\t\t{
\t\t\t\tkey a
\t\t\t\t{
\t\t\t\t\tkey a['4']
\t\t\t\t}
\t\t\t\t{
\t\t\t\t\tkey ba['1', '6']
\t\t\t\t}
\t\t\t}
\t\t}
\t}
}
{
\tkey bab['7']
\t{
\t\tkey a['3']
\t}
\t{
\t\tkey ba['8']
\t}
}
"""
self.assertEqual(str(self.trie), string_rep)
def test_insert_find(self):
"""An added key should be found by find."""
data = self.data
t = Compressed_Trie()
for (label, seq) in data.iteritems():
t.insert(seq, label)
for (label, seq) in data.iteritems():
self.assertEqual(label in t.find(seq), True)
self.assertEqual(t.find("abababa"), ["1","6"])
self.assertEqual(t.find("cacgchagc"), [])
def test_prefixMap(self):
"""prefix_map (Compressed_Trie) should map prefix strings."""
self.assertEqual(self.trie.prefixMap(),
{'1': ['6', '2', '0', '5'],
'8': ['7'],
'3': [],
'4': []})
def test_init(self):
"""Trie init should create an empty trie."""
t = Trie()
self.assertEqual(t.root.labels, [])
self.assertEqual(t.root.children, {})
def test_insert_find(self):
"""An added key should be found by find."""
data = self.data
t = Trie()
for (label, seq) in data.iteritems():
t.insert(seq, label)
for (label, seq) in data.iteritems():
self.assertEqual(label in t.find(seq), True)
self.assertEqual(t.find("cacgchagc"), [])
self.assertEqual(t.find("abababa"), ["1","6"])
def test_insert_unique(self):
"""insert_unique should insert only unique words."""
data = self.data
t = Trie()
for (label, seq) in data.iteritems():
t._insert_unique(seq, label)
self.assertEqual(t.find("ab"), [])
self.assertEqual(t.find("cacgchagc"), [])
self.assertEqual(t.find("abababa"), ["1"])
def test_build_prefix_map(self):
"""prefix_map should map prefix strings."""
self.assertEqual(dict(_build_prefix_map(self.data.iteritems())),
{'1': ['0', '2', '5', '6'],
'8': [],
'3': ['7'],
'4': []})
def test_build_trie(self):
"""Build_trie should build trie from seqs."""
t = build_trie(self.data.iteritems(), Trie)
self.assertTrue(isinstance(t, Trie))
for (label, seq) in self.data.iteritems():
self.assertContains(t.find(seq), label)
self.assertEqual(t.find(""), [])
self.assertEqual(t.find("ccc"), [])
class Compressed_Trie_Tests(TestCase):
def setUp(self):
self.data = dict({"0": "ab", "1":"abababa", "2":"abab",
"3":"baba", "4":"ababaa","5":"a", "6":"abababa",
"7":"bab", "8":"babba"})
self.trie = build_trie(self.data.iteritems())
def test_init(self):
"""Trie init should create an empty trie."""
t = Compressed_Trie()
self.assertEqual(t.root.labels, [])
self.assertEqual(t.root.children, {})
self.assertEqual(t.root.key, "")
def test_non_zero(self):
"""__non_zero__ should cehck for any data in the trie."""
t = Compressed_Trie()
self.assertEqual(t.__nonzero__(), False)
self.assertEqual(self.trie.__nonzero__(), True)
def test_len(self):
"""__len__ should return the number of seqs in the trie."""
self.assertEqual(len(self.trie), 9)
def test_size(self):
"""size should return the number of nodes in the trie."""
self.assertEqual(self.trie.size(), 10)
def test_to_string(self):
"""_to_string should create a string representation."""
string_rep = """
key
{
\tkey a['5']
\t{
\t\tkey b['0']
\t\t{
\t\t\tkey ab['2']
\t\t\t{
\t\t\t\tkey a
\t\t\t\t{
\t\t\t\t\tkey a['4']
\t\t\t\t}
\t\t\t\t{
\t\t\t\t\tkey ba['1', '6']
\t\t\t\t}
\t\t\t}
\t\t}
\t}
}
{
\tkey bab['7']
\t{
\t\tkey a['3']
\t}
\t{
\t\tkey ba['8']
\t}
}
"""
self.assertEqual(str(self.trie), string_rep)
def test_insert_find(self):
"""An added key should be found by find."""
data = self.data
t = Compressed_Trie()
for (label, seq) in data.iteritems():
t.insert(seq, label)
for (label, seq) in data.iteritems():
self.assertEqual(label in t.find(seq), True)
self.assertEqual(t.find("abababa"), ["1","6"])
self.assertEqual(t.find("cacgchagc"), [])
def test_prefixMap(self):
"""prefix_map (Compressed_Trie) should map prefix strings."""
self.assertEqual(self.trie.prefixMap(),
{'1': ['6', '2', '0', '5'],
'8': ['7'],
'3': [],
'4': []})
def test_build_trie(self):
"""Build_trie should build trie from seqs."""
t = build_trie(self.data.iteritems())
self.assertTrue(isinstance(t, Compressed_Trie))
for (label, seq) in self.data.iteritems():
self.assertContains(t.find(seq), label)
self.assertEqual(t.find(""), [])
self.assertEqual(t.find("ccc"), [])
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_util/test_unit_test.py 000644 000765 000024 00000144356 12024702176 023063 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for cogent.util.unit_test, extension of the built-in PyUnit framework.
"""
##SUPPORT2425
#from __future__ import with_statement
from cogent.util.unit_test import TestCase, main, FakeRandom #,numpy_err
import numpy; from numpy import array, zeros, log, inf
from sys import exc_info
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Sandra Smit", "Gavin Huttley", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
## SUPPORT2425
#class NumpyErrTests(TestCase):
#"""Tests numpy_err function."""
#def test_usage(self):
#with numpy_err(divide='raise'):
#self.assertRaises(FloatingPointError, log, 0)
#with numpy_err(divide='ignore'):
#self.assertEqual(log(0), -inf)
#with numpy_err(divide='raise'):
#self.assertRaises(FloatingPointError, log, 0)
#def test_err_status(self):
#ori_status = numpy.geterr()
#numpy.seterr(divide='warn')
#with numpy_err(all='ignore'):
#for v in numpy.geterr().values():
#self.assertEqual(v, 'ignore')
#self.assertEqual(numpy.geterr()['divide'], 'warn')
#numpy.seterr(**ori_status)
class FakeRandomTests(TestCase):
"""Tests FakeRandom class."""
def test_call_constant(self):
"""FakeRandom __call__ should return next item from list if constant"""
const = FakeRandom([1])
self.assertEqual(const(), 1)
self.assertRaises(IndexError, const)
def test_call_constant_wrap(self):
"""FakeRandom __call__ should wrap for one-item list if specified"""
const = FakeRandom([1], True)
for i in range(10):
self.assertEqual(const(), True)
def test_call_var(self):
"""FakeRandom __call__ should work with a multi-item list"""
f = FakeRandom([1,2,3])
self.assertEqual(f(), 1)
self.assertEqual(f(), 2)
self.assertEqual(f(), 3)
self.assertRaises(IndexError, f)
def test_call_var_wrap(self):
"""FakeRandom __call__ should work with a multi-item wrapped list"""
f = FakeRandom([1,2,3], True)
result = [f() for i in range(10)]
self.assertEqual(result, [1,2,3,1,2,3,1,2,3,1])
def test_cal_var_args(self):
"""FakeRandom __call__ should ignore extra args"""
f = FakeRandom([[1,2,3]], True)
for i in range(5):
result = f((5,5)) #shape parameter ignored
self.assertEqual(result, [1,2,3])
class TestCaseTests(TestCase):
"""Tests for extension of the built-in unittest framework.
For each test, includes an example of success and failure.
"""
unequal_pairs = [
(1, 0),
([], ()),
(None, 0),
('', ' '),
(1, '1'),
(0, '0'),
('', None),
(array([1,2,3]),array([1,2,4])),
(array([[1,2],[3,4]]), array([[1.0,2.0],[3.0,4.1]])),
(array([1]), array([1,2])),
(zeros(0), array([1])),
(array([1,1,1]), array([1])),
(array([[1,1],[1,1]]), array([1,1,1,1])),
(zeros(0), None),
(zeros(3), zeros(5)),
(zeros(0), ''),
]
equal_pairs = [
(1, 1),
(0, 0),
(5, 5L),
(5, 5.0),
(0, 0.0),
('', ''),
(' ', ' '),
('a', 'a'),
(None, None),
([0, 1], [0.0, 1.0]),
(array([1,2,3]), array([1,2,3])),
(array([[1,2],[3,4]]), array([[1.0,2.0],[3.0,4.0]])),
(zeros(0), []),
(zeros(0), zeros(0)),
(array([]), zeros(0)),
(zeros(3), zeros(3)),
(array([0,0,0]), zeros(3)),
(array([]), []),
]
small = 1e-7
big = 1e-5
within_1e6_abs_pairs = [
(1, 1 + small),
(1 + small, 1),
(1, 1 - small),
(1 - small, 1),
(100000, 100000 - small),
(-100000, -100000 - small),
(-1, -1 + small),
(-1, -1 - small),
(0, small),
(0, -small),
(array([1,2]), array([1,2+small])),
(array([[1,2],[3,4]]), array([[1,2+small],[3,4]]))
]
within_1e6_rel_pairs = [
(1, 1 + 1 * small),
(1 + 1 * small, 1),
(1, 1 - 1 * small),
(1 - 1 * small, 1),
(100000, 100000 - 100000 * small),
(-100000, -100000 - 100000 * small),
(-1, -1 + -1 * small),
(-1, -1 - -1 * small),
(array([1,2]), array([1+small,2])),
(array([[1000,1000],[1000,1000]]), \
array([[1000+1000*small, 1000], [1000,1000]])),
]
outside_1e6_abs_pairs = [
(1, 1 + big),
(1 + big, 1),
(1, 1 - big),
(1 - big, 1),
(100000, 100000 - big),
(-100000, -100000 - big),
(-1, -1 + big),
(-1, -1 - big),
(0, big),
(0, -big),
(1e7, 1e7 + 1),
(array([1,1]), array([1,1+big])),
(array([[1,1],[1,1]]), array([[1,1+big],[1,1]])),
]
outside_1e6_rel_pairs = [
(1, 1 + 1 * big),
(1 + 1 * big, 1),
(1, 1 - 1 * big),
(1 - 1 * big, 1),
(100000, 100000 - 100000 * big),
(-100000, -100000 - 100000 * big),
(-1, -1 + -1 * big),
(-1, -1 - -1 * big),
(1e-30, 1e-30 + small),
(0, small),
(1e5, 1e5 + 1),
(array([1,1]), array([1,1+1*big])),
]
def test_assertNotEqual_None(self):
"""assertNotEqual should raise exception with two copies of None"""
try:
self.assertNotEqual(None, None)
except:
message = str(exc_info()[1])
self.assertEqual(message,
'Observed None and expected None: shouldn\'t test equal')
else:
raise AssertionError, \
"unit_test.assertNotEqual failed on input %s and %s" \
% (`first`, `second`)
def test_assertNotEqual_numbers(self):
"""assertNotEqual should raise exception with integer and float zero"""
try:
self.assertNotEqual(0, 0.0)
except:
message = str(exc_info()[1])
self.assertEqual(message,
'Observed 0 and expected 0.0: shouldn\'t test equal')
else:
raise AssertionError, \
"unit_test.assertNotEqual failed on input %s and %s" \
% (`first`, `second`)
def test_assertNotEqual_unequal(self):
"""assertNotEqual should not raise exception when values differ"""
for first, second in self.unequal_pairs:
try:
self.assertNotEqual(first, second)
except:
raise AssertionError, \
"unit_test.assertNotEqual failed on input %s and %s" \
% (`first`, `second`)
def test_assertNotEqual_equal(self):
"""assertNotEqual should raise exception when values differ"""
for first, second in self.equal_pairs:
try:
self.assertNotEqual(first, second)
except:
message = str(exc_info()[1])
self.assertEqual(message,
'Observed %s and expected %s: shouldn\'t test equal' \
% (`first`, `second`))
else:
raise AssertionError, \
"unit_test.assertNotEqual failed on input %s and %s" \
% (`first`, `second`)
def test_assertEqual_None(self):
"""assertEqual should not raise exception with two copies of None"""
try:
self.assertEqual(None, None)
except:
raise AssertionError, \
"unit_test.assertEqual failed on input %s and %s" \
% (`first`, `second`)
def test_assertEqual_numbers(self):
"""assertEqual should not raise exception with integer and float zero"""
try:
self.assertEqual(0, 0.0)
except:
raise AssertionError, \
"unit_test.assertEqual failed on input %s and %s" \
% (`first`, `second`)
def test_assertEqual_unequal(self):
"""assertEqual should raise exception when values differ"""
for first, second in self.unequal_pairs:
try:
self.assertEqual(first, second)
except:
message = str(exc_info()[1])
self.assertEqual(message,
'Got %s, but expected %s' \
% (`first`, `second`))
else:
raise AssertionError, \
"unit_test.assertEqual failed on input %s and %s" \
% (`first`, `second`)
def test_assertEqual_equal(self):
"""assertEqual should not raise exception when values test equal"""
for first, second in self.equal_pairs:
try:
self.assertEqual(first, second)
except:
raise AssertionError, \
"unit_test.assertEqual failed on input %s and %s" \
% (`first`, `second`)
def test_assertEqual_nested_array(self):
self.assertEqual([[1,0], [0,1]],
[array([1,0]), array([0,1])])
def test_assertEqual_shape_mismatch(self):
"""assertEqual should raise when obs and exp shapes mismatch"""
obs = [1,2,3]
exp = [1,2,3,4]
self.assertRaises(AssertionError, self.assertEqual, obs, exp)
def test_assertFloatEqualAbs_equal(self):
"""assertFloatEqualAbs should not raise exception when values within eps"""
for first, second in self.within_1e6_abs_pairs:
try:
self.assertFloatEqualAbs(first, second, eps=1e-6)
except:
raise AssertionError, \
"unit_test.assertFloatEqualAbs failed on input %s and %s" \
% (`first`, `second`)
def test_assertFloatEqualAbs_threshold(self):
"""assertFloatEqualAbs should raise exception when eps is very small"""
for first, second in self.within_1e6_abs_pairs:
try:
self.assertFloatEqualAbs(first, second, 1e-30)
except:
message = str(exc_info()[1])
diff = first - second
self.assertEqual(message,
'Got %s, but expected %s (diff was %s)' \
% (`first`, `second`, `diff`))
else:
raise AssertionError, \
"unit_test.assertFloatEqualAbs failed on input %s and %s" \
% (`first`, `second`)
def test_assertFloatEqualAbs_unequal(self):
"""assertFloatEqualAbs should raise exception when values differ by >eps"""
for first, second in self.outside_1e6_abs_pairs:
try:
self.assertFloatEqualAbs(first, second)
except:
message = str(exc_info()[1])
diff = first - second
self.assertEqual(message,
'Got %s, but expected %s (diff was %s)' \
% (`first`, `second`, `diff`))
else:
raise AssertionError, \
"unit_test.assertFloatEqualAbs failed on input %s and %s" \
% (`first`, `second`)
def test_assertFloatEqualAbs_shape_mismatch(self):
"""assertFloatEqualAbs should raise when obs and exp shapes mismatch"""
obs = [1,2,3]
exp = [1,2,3,4]
self.assertRaises(AssertionError, self.assertFloatEqualAbs, obs, exp)
def test_assertFloatEqualRel_equal(self):
"""assertFloatEqualRel should not raise exception when values within eps"""
for first, second in self.within_1e6_rel_pairs:
try:
self.assertFloatEqualRel(first, second)
except:
raise AssertionError, \
"unit_test.assertFloatEqualRel failed on input %s and %s" \
% (`first`, `second`)
def test_assertFloatEqualRel_unequal(self):
"""assertFloatEqualRel should raise exception when eps is very small"""
for first, second in self.within_1e6_rel_pairs:
try:
self.assertFloatEqualRel(first, second, 1e-30)
except:
message = str(exc_info()[1])
diff = first - second
self.assertEqual(message,
'Got %s, but expected %s (diff was %s)' \
% (`first`, `second`, `diff`))
else:
raise AssertionError, \
"unit_test.assertFloatEqualRel failed on input %s and %s" \
% (`first`, `second`)
def test_assertFloatEqualRel_unequal(self):
"""assertFloatEqualRel should raise exception when values differ by >eps"""
for first, second in self.outside_1e6_rel_pairs:
try:
self.assertFloatEqualRel(first, second)
except:
message = str(exc_info()[1])
diff = first - second
self.assertEqual(message,
'Got %s, but expected %s (diff was %s)' \
% (`first`, `second`, `diff`))
else:
raise AssertionError, \
"unit_test.assertFloatEqualRel failed on input %s and %s" \
% (`first`, `second`)
def test_assertFloatEqualRel_shape_mismatch(self):
"""assertFloatEqualRel should raise when obs and exp shapes mismatch"""
obs = [1,2,3]
exp = [1,2,3,4]
self.assertRaises(AssertionError, self.assertFloatEqualRel, obs, exp)
def test_assertFloatEqualList_equal(self):
"""assertFloatEqual should work on two lists of similar values"""
originals = [0, 1, -1, 10, -10, 100, -100]
modified = [i + 1e-7 for i in originals]
try:
self.assertFloatEqual(originals, modified)
self.assertFloatEqual([], []) #test empty lists as well
except:
raise AssertionError, \
"unit_test.assertFloatEqual failed on lists of similar values"
def test_assertFloatEqual_shape_mismatch(self):
"""assertFloatEqual should raise when obs and exp shapes mismatch"""
obs = [1,2,3]
exp = [1,2,3,4]
self.assertRaises(AssertionError, self.assertFloatEqual, obs, exp)
def test_assertFloatEqualList_unequal(self):
"""assertFloatEqual should fail on two lists of dissimilar values"""
originals = [0, 1, -1, 10, -10, 100, -100]
modified = [i + 1e-5 for i in originals]
try:
self.assertFloatEqual(originals, modified)
except:
pass
else:
raise AssertionError, \
"unit_test.assertFloatEqual failed on lists of dissimilar values"
def test_assertFloatEqual_mixed(self):
"""assertFloatEqual should work on equal lists of mixed types."""
first = [i[0] for i in self.equal_pairs]
second = [i[1] for i in self.equal_pairs]
self.assertFloatEqual(first, second)
def test_assertFloatEqualAbs_mixed(self):
first = [i[0] for i in self.equal_pairs]
second = [i[1] for i in self.equal_pairs]
"""assertFloatEqualAbs should work on equal lists of mixed types."""
self.assertFloatEqualAbs(first, second)
def test_assertFloatEqualRel_mixed(self):
first = [i[0] for i in self.equal_pairs]
second = [i[1] for i in self.equal_pairs]
"""assertFloatEqualRel should work on equal lists of mixed types."""
self.assertFloatEqualRel(first, second)
def test_assertFloatEqual_mixed_unequal(self):
"""assertFloatEqual should work on unequal lists of mixed types."""
first = [i[0] for i in self.unequal_pairs]
second = [i[1] for i in self.unequal_pairs]
self.assertRaises(AssertionError, \
self.assertFloatEqual, first, second)
def test_assertFloatEqualAbs_mixed(self):
"""assertFloatEqualAbs should work on lists of mixed types."""
first = [i[0] for i in self.unequal_pairs]
second = [i[1] for i in self.unequal_pairs]
self.assertRaises(AssertionError, \
self.assertFloatEqualAbs, first, second)
def test_assertFloatEqualRel_mixed(self):
"""assertFloatEqualRel should work on lists of mixed types."""
first = [i[0] for i in self.unequal_pairs]
second = [i[1] for i in self.unequal_pairs]
self.assertRaises(AssertionError, \
self.assertFloatEqualRel, first, second)
def test_assertEqualItems(self):
"""assertEqualItems should raise exception if items not equal"""
self.assertEqualItems('abc', 'abc')
self.assertEqualItems('abc', 'cba')
self.assertEqualItems('', '')
self.assertEqualItems('abc', ['a','b','c'])
self.assertEqualItems([0], [0.0])
try:
self.assertEqualItems('abc', 'abcd')
except:
message = str(exc_info()[1])
self.assertEqual(message,
'Observed and expected are different lengths: 3 and 4')
else:
raise AssertionError, \
"unit_test.assertEqualItems failed on input %s and %s" \
% (`first`, `second`)
try:
self.assertEqualItems('cab', 'acc')
except:
message = str(exc_info()[1])
self.assertEqual(message,
'Observed b and expected c at sorted index 1')
else:
raise AssertionError, \
"unit_test.assertEqualItems failed on input %s and %s" \
% (`first`, `second`)
try:
self.assertEqualItems('cba', 'yzx')
except:
message = str(exc_info()[1])
self.assertEqual(message,
'Observed a and expected x at sorted index 0')
else:
raise AssertionError, \
"unit_test.assertEqualItems failed on input %s and %s" \
% (`first`, `second`)
def test_assertSameItems(self):
"""assertSameItems should raise exception if items not same"""
x = 0
y = 'abcdef'
z = 3
y1 = 'abc' + 'def'
z1 = 3.0
y_id = id(y)
z_id = id(z)
y1_id = id(y1)
z1_id = id(z1)
self.assertSameItems([x,y,z], [x,y,z])
self.assertSameItems([x,y,z], [z,x,y])
self.assertSameItems('', '')
self.assertSameItems([x,y,z], (x,y,z))
try:
self.assertSameItems([x,y,z], [x,y,z,y])
except:
message = str(exc_info()[1])
self.assertEqual(message,
'Observed and expected are different lengths: 3 and 4')
else:
raise AssertionError, \
"unit_test.assertSameItems failed on input %s and %s" \
% (`[x,y,z]`, `[x,y,z,y]`)
try:
first_list = [x,y,z]
second_list = [y,x,z1]
self.assertSameItems(first_list, second_list)
except self.failureException:
pass
else:
raise AssertionError, \
"unit_test.assertEqualItems failed on input %s and %s" \
% (`[x,y,z]`, `[y,x,z1]`)
# assert y is not y1
# try:
# self.assertSameItems([y], (y1,))
# except self.failureException:
# pass
# else:
# raise AssertionError, \
# "unit_test.assertEqualItems failed on input %s and %s" \
# % (`[y]`, `(y1,)`)
def test_assertNotEqualItems(self):
"""assertNotEqualItems should raise exception if all items equal"""
self.assertNotEqualItems('abc', '')
self.assertNotEqualItems('abc', 'cbad')
self.assertNotEqualItems([0], [0.01])
try:
self.assertNotEqualItems('abc', 'abc')
except:
message = str(exc_info()[1])
self.assertEqual(message,
"Observed 'abc' has same items as 'abc'")
else:
raise AssertionError, \
"unit_test.assertNotEqualItems failed on input %s and %s" \
% (`'abc'`, `'abc'`)
try:
self.assertNotEqualItems('', [])
except:
message = str(exc_info()[1])
self.assertEqual(message, "Observed '' has same items as []")
else:
raise AssertionError, \
"unit_test.assertNotEqualItems failed on input %s and %s" \
% (`''`, `[]`)
def test_assertContains(self):
"""assertContains should raise exception if item not in test set"""
self.assertContains('abc', 'a')
self.assertContains(['a', 'b', 'c'], 'a')
self.assertContains(['a', 'b', 'c'], 'b')
self.assertContains(['a', 'b', 'c'], 'c')
self.assertContains({'a':1, 'b':2}, 'a')
class _fake_container(object):
def __contains__(self, other):
return True
fake = _fake_container()
self.assertContains(fake, 'x')
self.assertContains(fake, 3)
self.assertContains(fake, {'a':'b'})
try:
self.assertContains('', [])
except:
message = str(exc_info()[1])
self.assertEqual(message, "Item [] not found in ''")
else:
raise AssertionError, \
"unit_test.assertContains failed on input %s and %s" \
% (`''`, `[]`)
try:
self.assertContains('abcd', 'x')
except:
message = str(exc_info()[1])
self.assertEqual(message, "Item 'x' not found in 'abcd'")
else:
raise AssertionError, \
"unit_test.assertContains failed on input %s and %s" \
% (`'abcd'`, `'x'`)
def test_assertNotContains(self):
"""assertNotContains should raise exception if item in test set"""
self.assertNotContains('abc', 'x')
self.assertNotContains(['a', 'b', 'c'], 'x')
self.assertNotContains('abc', None)
self.assertNotContains(['a', 'b', 'c'], {'x':1})
self.assertNotContains({'a':1, 'b':2}, 3.0)
class _fake_container(object):
def __contains__(self, other):
return False
fake = _fake_container()
self.assertNotContains(fake, 'x')
self.assertNotContains(fake, 3)
self.assertNotContains(fake, {'a':'b'})
try:
self.assertNotContains('', '')
except:
message = str(exc_info()[1])
self.assertEqual(message, "Item '' should not have been in ''")
else:
raise AssertionError, \
"unit_test.assertNotContains failed on input %s and %s" \
% (`''`, `''`)
try:
self.assertNotContains('abcd', 'a')
except:
message = str(exc_info()[1])
self.assertEqual(message, "Item 'a' should not have been in 'abcd'")
else:
raise AssertionError, \
"unit_test.assertNotContains failed on input %s and %s" \
% (`'abcd'`, `'a'`)
try:
self.assertNotContains({'a':1, 'b':2}, 'a')
except:
message = str(exc_info()[1])
self.assertEqual(message, \
"Item 'a' should not have been in {'a': 1, 'b': 2}")
else:
raise AssertionError, \
"unit_test.assertNotContains failed on input %s and %s" \
% (`{'a':1, 'b':2}`, `'a'`)
def test_assertGreaterThan_equal(self):
"""assertGreaterThan should raise exception if equal"""
self.assertRaises(AssertionError, self.assertGreaterThan, 5, 5)
self.assertRaises(AssertionError, self.assertGreaterThan, 5.0, 5.0)
self.assertRaises(AssertionError, self.assertGreaterThan, 5.0, 5)
self.assertRaises(AssertionError, self.assertGreaterThan, 5, 5.0)
def test_assertGreaterThan_None(self):
"""assertGreaterThan should raise exception if compared to None"""
self.assertRaises(AssertionError, self.assertGreaterThan, 5, None)
self.assertRaises(AssertionError, self.assertGreaterThan, None, 5)
self.assertRaises(AssertionError, self.assertGreaterThan, 5.0, None)
self.assertRaises(AssertionError, self.assertGreaterThan, None, 5.0)
def test_assertGreaterThan_numbers_true(self):
"""assertGreaterThan should pass when observed > value"""
self.assertGreaterThan(10, 5)
def test_assertGreaterThan_numbers_false(self):
"""assertGreaterThan should raise when observed <= value"""
self.assertRaises(AssertionError, self.assertGreaterThan, 2, 5)
def test_assertGreaterThan_numbers_list_true(self):
"""assertGreaterThan should pass when all elements are > value"""
observed = [1,2,3,4,3,2,3,4,6,3]
self.assertGreaterThan(observed, 0)
def test_assertGreaterThan_numbers_list_false(self):
"""assertGreaterThan should raise when a single element is <= value"""
observed = [2,3,4,3,2,1,3,4,6,3]
self.assertRaises(AssertionError, self.assertGreaterThan, observed, 1)
def test_assertGreaterThan_floats_true(self):
"""assertGreaterThan should pass when observed > value"""
self.assertGreaterThan(5.0, 3.0)
def test_assertGreaterThan_floats_false(self):
"""assertGreaterThan should raise when observed <= value"""
self.assertRaises(AssertionError, self.assertGreaterThan, 3.0, 5.0)
def test_assertGreaterThan_floats_list_true(self):
"""assertGreaterThan should pass when all elements are > value"""
observed = [1.0,2.0,3.0,4.0,6.0,3.0]
self.assertGreaterThan(observed, 0.0)
def test_assertGreaterThan_floats_list_false(self):
"""assertGreaterThan should raise when any elements are <= value"""
observed = [2.0,3.0,4.0,1.0, 3.0,3.0]
self.assertRaises(AssertionError, self.assertGreaterThan, observed, 1.0)
def test_assertGreaterThan_mixed_true(self):
"""assertGreaterThan should pass when observed > value"""
self.assertGreaterThan(5.0, 3)
self.assertGreaterThan(5, 3.0)
def test_assertGreaterThan_mixed_false(self):
"""assertGreaterThan should raise when observed <= value"""
self.assertRaises(AssertionError, self.assertGreaterThan, -3, 5.0)
self.assertRaises(AssertionError, self.assertGreaterThan, 3.0, 5)
def test_assertGreaterThan_mixed_list_true(self):
"""assertGreaterThan should pass when all elements are > value"""
observed = [1.0, 2, 3.0, 4.0, 6, 3.0]
self.assertGreaterThan(observed, 0.0)
self.assertGreaterThan(observed, 0)
def test_assertGreaterThan_mixed_list_false(self):
"""assertGreaterThan should raise when a single element is <= value"""
observed = [2.0, 3, 4, 1.0, 3.0, 3.0]
self.assertRaises(AssertionError, self.assertGreaterThan, observed, 1.0)
self.assertRaises(AssertionError, self.assertGreaterThan, observed, 1)
def test_assertGreaterThan_numpy_array_true(self):
"""assertGreaterThan should pass when all elements are > value"""
observed = array([1,2,3,4])
self.assertGreaterThan(observed, 0)
self.assertGreaterThan(observed, 0.0)
def test_assertGreaterThan_numpy_array_false(self):
"""assertGreaterThan should pass when any element is <= value"""
observed = array([1,2,3,4])
self.assertRaises(AssertionError, self.assertGreaterThan, observed, 3)
self.assertRaises(AssertionError, self.assertGreaterThan, observed, 3.0)
def test_assertLessThan_equal(self):
"""assertLessThan should raise exception if equal"""
self.assertRaises(AssertionError, self.assertLessThan, 5, 5)
self.assertRaises(AssertionError, self.assertLessThan, 5.0, 5.0)
self.assertRaises(AssertionError, self.assertLessThan, 5.0, 5)
self.assertRaises(AssertionError, self.assertLessThan, 5, 5.0)
def test_assertLessThan_None(self):
"""assertLessThan should raise exception if compared to None"""
self.assertRaises(AssertionError, self.assertLessThan, 5, None)
self.assertRaises(AssertionError, self.assertLessThan, None, 5)
self.assertRaises(AssertionError, self.assertLessThan, 5.0, None)
self.assertRaises(AssertionError, self.assertLessThan, None, 5.0)
def test_assertLessThan_numbers_true(self):
"""assertLessThan should pass when observed < value"""
self.assertLessThan(10, 15)
def test_assertLessThan_numbers_false(self):
"""assertLessThan should raise when observed >= value"""
self.assertRaises(AssertionError, self.assertLessThan, 6, 5)
def test_assertLessThan_numbers_list_true(self):
"""assertLessThan should pass when all elements are < value"""
observed = [1,2,3,4,3,2,3,4,6,3]
self.assertLessThan(observed, 8)
def test_assertLessThan_numbers_list_false(self):
"""assertLessThan should raise when a single element is >= value"""
observed = [2,3,4,3,2,1,3,4,6,3]
self.assertRaises(AssertionError, self.assertLessThan, observed, 6)
def test_assertLessThan_floats_true(self):
"""assertLessThan should pass when observed < value"""
self.assertLessThan(-5.0, 3.0)
def test_assertLessThan_floats_false(self):
"""assertLessThan should raise when observed >= value"""
self.assertRaises(AssertionError, self.assertLessThan, 3.0, -5.0)
def test_assertLessThan_floats_list_true(self):
"""assertLessThan should pass when all elements are < value"""
observed = [1.0,2.0,-3.0,4.0,-6.0,3.0]
self.assertLessThan(observed, 5.0)
def test_assertLessThan_floats_list_false(self):
"""assertLessThan should raise when a single element is >= value"""
observed = [2.0,3.0,4.0,1.0, 3.0,3.0]
self.assertRaises(AssertionError, self.assertLessThan, observed, 4.0)
def test_assertLessThan_mixed_true(self):
"""assertLessThan should pass when observed < value"""
self.assertLessThan(2.0, 3)
self.assertLessThan(2, 3.0)
def test_assertLessThan_mixed_false(self):
"""assertLessThan should raise when observed >= value"""
self.assertRaises(AssertionError, self.assertLessThan, 6, 5.0)
self.assertRaises(AssertionError, self.assertLessThan, 6.0, 5)
def test_assertLessThan_mixed_list_true(self):
"""assertLessThan should pass when all elements are < value"""
observed = [1.0, 2, 3.0, 4.0, 6, 3.0]
self.assertLessThan(observed, 7.0)
self.assertLessThan(observed, 7)
def test_assertLessThan_mixed_list_false(self):
"""assertLessThan should raise when a single element is >= value"""
observed = [2.0, 3, 4, 1.0, 3.0, 3.0]
self.assertRaises(AssertionError, self.assertLessThan, observed, 4.0)
self.assertRaises(AssertionError, self.assertLessThan, observed, 4)
def test_assertLessThan_numpy_array_true(self):
"""assertLessThan should pass when all elements are < value"""
observed = array([1,2,3,4])
self.assertLessThan(observed, 5)
self.assertLessThan(observed, 5.0)
def test_assertLessThan_numpy_array_false(self):
"""assertLessThan should pass when any element is >= value"""
observed = array([1,2,3,4])
self.assertRaises(AssertionError, self.assertLessThan, observed, 3)
self.assertRaises(AssertionError, self.assertLessThan, observed, 3.0)
def test_assertIsBetween_bounds(self):
"""assertIsBetween should raise if min_value >= max_value"""
self.assertRaises(AssertionError, self.assertIsBetween, 5, 6, 3)
self.assertRaises(AssertionError, self.assertIsBetween, 5, 3, 3)
def test_assertIsBetween_equal(self):
"""assertIsBetween should raise when a value is equal to either bound"""
self.assertRaises(AssertionError, self.assertIsBetween, 1, 1, 5)
self.assertRaises(AssertionError, self.assertIsBetween, 5, 1, 5)
def test_assertIsBetween_None(self):
"""assertIsBetween should raise when compared to None"""
self.assertRaises(AssertionError, self.assertIsBetween, None, 1, 5)
self.assertRaises(AssertionError, self.assertIsBetween, 1, None, 5)
self.assertRaises(AssertionError, self.assertIsBetween, 5, 1, None)
def test_assertIsBetween_numbers_true(self):
"""assertIsBetween should pass when in bounds"""
self.assertIsBetween(5,3,7)
def test_assertIsBetween_numbers_false(self):
"""assertIsBetween should raise when out of bounds"""
self.assertRaises(AssertionError, self.assertIsBetween, 5, 1, 3)
def test_assertIsBetween_numbers_list_true(self):
"""assertIsBetween should pass when all elements are in bounds"""
observed = [3,4,5,4,3,4,5,4,3]
self.assertIsBetween(observed, 1, 7)
def test_assertIsBetween_numbers_list_false(self):
"""assertIsBetween should raise when any elements are out of bounds"""
observed = [3,4,5,4,3,4,5,6]
self.assertRaises(AssertionError, self.assertIsBetween, observed, 1, 5)
def test_assertIsBetween_floats_true(self):
"""assertIsBetween should pass when in bounds"""
self.assertIsBetween(5.0, 3.0 ,7.0)
def test_assertIsBetween_floats_false(self):
"""assertIsBetween should raise when out of bounds"""
self.assertRaises(AssertionError, self.assertIsBetween, 5.0, 1.0, 3.0)
def test_assertIsBetween_floats_list_true(self):
"""assertIsBetween should pass when all elements are in bounds"""
observed = [3.0, 4.0, -5.0, 4.0, 3.0]
self.assertIsBetween(observed, -7.0, 7.0)
def test_assertIsBetween_floats_list_false(self):
"""assertIsBetween should raise when any elements are out of bounds"""
observed = [3.0, 4.0, -5.0, 5.0, 6.0]
self.assertRaises(AssertionError, self.assertIsBetween,observed,1.0,5.0)
def test_assertIsBetween_mixed_true(self):
"""assertIsBetween should pass when in bounds"""
self.assertIsBetween(5.0, 3, 7)
self.assertIsBetween(5, 3.0, 7)
self.assertIsBetween(5, 3, 7.0)
self.assertIsBetween(5.0, 3.0, 7)
self.assertIsBetween(5, 3.0, 7.0)
self.assertIsBetween(5.0, 3, 7.0)
def test_assertIsBetween_mixed_false(self):
"""assertIsBetween should raise when out of bounds"""
self.assertRaises(AssertionError, self.assertIsBetween, 5.0, 1, 3)
self.assertRaises(AssertionError, self.assertIsBetween, 5, 1.0, 3)
self.assertRaises(AssertionError, self.assertIsBetween, 5, 1, 3.0)
self.assertRaises(AssertionError, self.assertIsBetween, 5.0, 1.0, 3)
self.assertRaises(AssertionError, self.assertIsBetween, 5, 1.0, 3.0)
self.assertRaises(AssertionError, self.assertIsBetween, 5.0, 1, 3.0)
def test_assertIsBetween_mixed_list_true(self):
"""assertIsBetween should pass when all elements are in bounds"""
observed = [3,4,5,4.0,3,4.0,5,4,3.0]
self.assertIsBetween(observed, 1, 7)
self.assertIsBetween(observed, 1.0, 7)
self.assertIsBetween(observed, 1, 7.0)
self.assertIsBetween(observed, 1.0, 7.0)
def test_assertIsBetween_mixed_list_false(self):
"""assertIsBetween should raise when any elements are out of bounds"""
observed = [3.0,4,5.0,4,3,4.0,5,6]
self.assertRaises(AssertionError, self.assertIsBetween,observed, 1.0, 5)
self.assertRaises(AssertionError, self.assertIsBetween,observed, 1, 5.0)
self.assertRaises(AssertionError, self.assertIsBetween,observed,1.0,5.0)
self.assertRaises(AssertionError, self.assertIsBetween,observed, 1, 5)
def test_assertIsBetween_numpy_array_true(self):
"""assertIsBetween should pass when all elements are in bounds"""
observed = array([1,2,4,5,6])
self.assertIsBetween(observed, 0, 7)
def test_assertIsBetween_numpy_array_false(self):
"""assertIsBetween should raise when any elements is out of bounds"""
observed = array([1,2,4,5,6])
self.assertRaises(AssertionError, self.assertIsBetween, observed, 2, 7)
def test_assertIsProb_None(self):
"""assertIsProb should raise when compared against None"""
self.assertRaises(AssertionError, self.assertIsProb, None)
def test_assertIsProb_numbers_true(self):
"""assertIsProb should pass when compared against valid numbers"""
self.assertIsProb(0)
self.assertIsProb(1)
def test_assertIsProb_numbers_false(self):
"""assertIsProb should raise when compared against invalid numbers"""
self.assertRaises(AssertionError, self.assertIsProb, -1)
self.assertRaises(AssertionError, self.assertIsProb, 2)
def test_assertIsProb_numbers_list_true(self):
"""assertIsProb should pass when all elements are probs"""
observed = [0, 1, 0]
self.assertIsProb(observed)
def test_assertIsProb_numbers_list_false(self):
"""assertIsProb should raise when any element is not a prob"""
observed = [-2, -4, 3]
self.assertRaises(AssertionError, self.assertIsProb, observed)
def test_assertIsProb_float_true(self):
"""assertIsProb should pass when compared against valid numbers"""
self.assertIsProb(0.0)
self.assertIsProb(1.0)
def test_assertIsProb_float_false(self):
"""assertIsProb should raise when compared against invalid numbers"""
self.assertRaises(AssertionError, self.assertIsProb, -1.0)
self.assertRaises(AssertionError, self.assertIsProb, 2.0)
def test_assertIsProb_float_list_true(self):
"""assertIsProb should pass when all elements are probs"""
observed = [0.0, 1.0, 0.0]
self.assertIsProb(observed)
def test_assertIsProb_float_list_false(self):
"""assertIsProb should raise when any element is not a prob"""
observed = [-2.0, -4.0, 3.0]
self.assertRaises(AssertionError, self.assertIsProb, observed)
def test_assertIsProb_mixed_list_true(self):
"""assertIsProb should pass when all elements are probs"""
observed = [0.0, 1, 0.0]
self.assertIsProb(observed)
def test_assertIsProb_mixed_list_false(self):
"""assertIsProb should raise when any element is not a prob"""
observed = [-2.0, -4, 3.0]
self.assertRaises(AssertionError, self.assertIsProb, observed)
def test_assertIsProb_numpy_array_true(self):
"""assertIsProb should pass when all elements are probs"""
observed = array([0.0,0.4,0.8])
self.assertIsProb(observed)
def test_assertIsProb_numpy_array_true(self):
"""assertIsProb should pass when all elements are probs"""
observed = array([0.0,-0.4,0.8])
self.assertRaises(AssertionError, self.assertIsProb, observed)
def test_assertSimilarMeans_one_obs_true(self):
"""assertSimilarMeans should pass when p > pvalue"""
obs = [5]
expected = [1,2,3,4,5,6,7,8,9,10,11]
self.assertSimilarMeans(obs, expected)
self.assertSimilarMeans(obs, expected, pvalue=0.25)
self._set_suite_pvalue(0.10)
self.assertSimilarMeans(obs, expected)
def test_assertSimilarMeans_one_obs_false(self):
"""assertSimilarMeans should raise when p < pvalue"""
obs = [5]
expected = [.001,.009,.00012]
self.assertRaises(AssertionError, self.assertSimilarMeans, \
obs, expected)
self.assertRaises(AssertionError, self.assertSimilarMeans, \
obs, expected, 0.1)
self._set_suite_pvalue(0.001)
self.assertRaises(AssertionError, self.assertSimilarMeans, \
obs, expected)
def test_assertSimilarMeans_twosample_true(self):
"""assertSimilarMeans should pass when p > pvalue"""
obs = [4,5,6]
expected = [1,2,3,4,5,6,7,8,9]
self.assertSimilarMeans(obs, expected)
self.assertSimilarMeans(obs, expected, pvalue=0.25)
self._set_suite_pvalue(0.10)
self.assertSimilarMeans(obs, expected)
def test_assertSimilarMeans_twosample_false(self):
"""assertSimilarMeans should raise when p < pvalue"""
obs = [1,2,3]
expected = [6,7,8,9,10,11,12,13,14]
self.assertRaises(AssertionError, self.assertSimilarMeans, \
obs, expected)
self.assertRaises(AssertionError, self.assertSimilarMeans, \
obs, expected, 0.1)
self._set_suite_pvalue(0.001)
self.assertRaises(AssertionError, self.assertSimilarMeans, \
obs, expected)
def test_assertSimilarFreqs_true(self):
"""assertSimilarFreqs should pass when p > pvalue"""
observed = [2,2,3,2,1,2,2,2,2]
expected = [2,2,2,2,2,2,2,2,2]
self.assertSimilarFreqs(observed, expected)
self.assertSimilarFreqs(observed, expected, pvalue=0.25)
self._set_suite_pvalue(0.10)
self.assertSimilarFreqs(observed, expected)
def test_assertSimilarFreqs_false(self):
"""assertSimilarFreqs should raise when p < pvalue"""
observed = [10,15,20,10,12,12,13]
expected = [100,50,10,20,700,2,100]
self.assertRaises(AssertionError, self.assertSimilarFreqs, \
observed, expected)
self.assertRaises(AssertionError, self.assertSimilarFreqs, \
observed, expected, 0.2)
self._set_suite_pvalue(0.001)
self.assertRaises(AssertionError, self.assertSimilarFreqs, \
observed, expected)
def test_assertSimilarFreqs_numpy_array_true(self):
"""assertSimilarFreqs should pass when p > pvalue"""
observed = array([2,2,3,2,1,2,2,2,2])
expected = array([2,2,2,2,2,2,2,2,2])
self.assertSimilarFreqs(observed, expected)
self.assertSimilarFreqs(observed, expected, pvalue=0.25)
self._set_suite_pvalue(0.10)
self.assertSimilarFreqs(observed, expected)
def test_assertSimilarFreqs_numpy_array_false(self):
"""assertSimilarFreqs should raise when p < pvalue"""
observed = array([10,15,20,10,12,12,13])
expected = array([100,50,10,20,700,2,100])
self.assertRaises(AssertionError, self.assertSimilarFreqs, \
observed, expected)
self.assertRaises(AssertionError, self.assertSimilarFreqs, \
observed, expected, 0.2)
self._set_suite_pvalue(0.001)
self.assertRaises(AssertionError, self.assertSimilarFreqs, \
observed, expected)
def test_set_suite_pvalue(self):
"""Should set the suite pvalue"""
# force stats to fail
self._set_suite_pvalue(0.99)
obs = [2,5,6]
exp = [1,2,3,4,5,6,7,8,9]
self.assertRaises(AssertionError, self.assertSimilarMeans, obs, exp)
# force stats to pass
self._set_suite_pvalue(0.01)
self.assertSimilarMeans(obs, exp)
def test_assertIsPermutation_true(self):
"""assertIsPermutation should pass when a is a permutation of b"""
observed = [3,2,1,4,5]
items = [1,2,3,4,5]
self.assertIsPermutation(observed, items)
def test_assertIsPermutation_false(self):
"""assertIsPermutation should raise when a is not a permutation of b"""
items = [1,2,3,4,5]
self.assertRaises(AssertionError,self.assertIsPermutation, items,items)
self.assertRaises(AssertionError,self.assertIsPermutation, [1,2],[3,4])
def test_assertSameObj_true(self):
"""assertSameObj should pass when 'a is b'"""
self.assertSameObj("foo", "foo")
self.assertSameObj(None, None)
bar = lambda x:5
self.assertSameObj(bar, bar)
def test_assertSameObj_false(self):
"""assertSameObj should raise when 'a is not b'"""
self.assertRaises(AssertionError, self.assertSameObj, "foo", "bar")
self.assertRaises(AssertionError, self.assertSameObj, None, "bar")
self.assertRaises(AssertionError, self.assertSameObj, lambda x:5, \
lambda y:6)
def test_assertNotSameObj_true(self):
"""assertNotSameObj should pass when 'a is not b'"""
self.assertNotSameObj("foo", "bar")
self.assertNotSameObj(None, 5)
self.assertNotSameObj(lambda x:5, lambda y:6)
def test_assertNotSameObj_false(self):
"""assertSameObj should raise when 'a is b'"""
self.assertRaises(AssertionError, self.assertNotSameObj, "foo", "foo")
self.assertRaises(AssertionError, self.assertNotSameObj, None, None)
bar = lambda x:5
self.assertRaises(AssertionError, self.assertNotSameObj, bar, bar)
def test_assertIsNotBetween_bounds(self):
"""assertIsNotBetween should raise if min_value >= max_value"""
self.assertRaises(AssertionError, self.assertIsNotBetween, 5, 4, 3)
self.assertRaises(AssertionError, self.assertIsNotBetween, 5, 3, 3)
def test_assertIsNotBetween_equals(self):
"""assertIsNotBetween should pass when equal on either bound"""
self.assertIsNotBetween(1, 1, 2)
self.assertIsNotBetween(1.0, 1, 2)
self.assertIsNotBetween(1, 1.0, 2)
self.assertIsNotBetween(1.0, 1.0, 2)
self.assertIsNotBetween(2, 1, 2)
self.assertIsNotBetween(2.0, 1, 2)
self.assertIsNotBetween(2, 1, 2.0)
self.assertIsNotBetween(2.0, 1, 2.0)
def test_assertIsNotBetween_None(self):
"""assertIsNotBetween should raise when compared against None"""
self.assertRaises(AssertionError, self.assertIsNotBetween, None, 1, 2)
self.assertRaises(AssertionError, self.assertIsNotBetween, 1, None, 2)
self.assertRaises(AssertionError, self.assertIsNotBetween, 1, 2, None)
def test_assertIsNotBetween_numbers_true(self):
"""assertIsNotBetween should pass when a number is not in bounds"""
self.assertIsNotBetween(1,2,3)
self.assertIsNotBetween(4,2,3)
self.assertIsNotBetween(-1,-3,-2)
self.assertIsNotBetween(-4,-3,-2)
self.assertIsNotBetween(2,-1,1)
def test_assertIsNotBetween_numbers_false(self):
"""assertIsNotBetween should raise when a number is in bounds"""
self.assertRaises(AssertionError, self.assertIsNotBetween, 2, 1, 3)
self.assertRaises(AssertionError, self.assertIsNotBetween, 0, -1, 1)
self.assertRaises(AssertionError, self.assertIsNotBetween, -2, -3, -1)
def test_assertIsNotBetween_numbers_list_true(self):
"""assertIsNotBetween should pass when all elements are out of bounds"""
obs = [1,2,3,4,5]
self.assertIsNotBetween(obs, 5, 10)
self.assertIsNotBetween(obs, -2, 1)
def test_assertIsNotBetween_numbers_list_false(self):
"""assertIsNotBetween should raise when any element is in bounds"""
obs = [1,2,3,4,5]
self.assertRaises(AssertionError, self.assertIsNotBetween, obs, 3, 7)
self.assertRaises(AssertionError, self.assertIsNotBetween, obs, -3, 3)
self.assertRaises(AssertionError, self.assertIsNotBetween, obs, 2, 4)
def test_assertIsNotBetween_float_true(self):
"""assertIsNotBetween should pass when a number is not in bounds"""
self.assertIsNotBetween(1.0, 2.0, 3.0)
self.assertIsNotBetween(4.0, 2.0, 3.0)
self.assertIsNotBetween(-1.0, -3.0, -2.0)
self.assertIsNotBetween(-4.0, -3.0, -2.0)
self.assertIsNotBetween(2.0, -1.0, 1.0)
def test_assertIsNotBetween_float_false(self):
"""assertIsNotBetween should raise when a number is in bounds"""
self.assertRaises(AssertionError, self.assertIsNotBetween, 2.0,1.0,3.0)
self.assertRaises(AssertionError, self.assertIsNotBetween, 0.0,-1.0,1.0)
self.assertRaises(AssertionError,self.assertIsNotBetween,-2.0,-3.0,-1.0)
def test_assertIsNotBetween_float_list_true(self):
"""assertIsNotBetween should pass when all elements are out of bounds"""
obs = [1.0, 2.0, 3.0, 4.0, 5.0]
self.assertIsNotBetween(obs, 5.0, 10.0)
self.assertIsNotBetween(obs, -2.0, 1.0)
def test_assertIsNotBetween_float_list_false(self):
"""assertIsNotBetween should raise when any element is in bounds"""
obs = [1.0, 2.0, 3.0, 4.0, 5.0]
self.assertRaises(AssertionError,self.assertIsNotBetween, obs, 3.0, 7.0)
self.assertRaises(AssertionError,self.assertIsNotBetween, obs, -3.0,3.0)
self.assertRaises(AssertionError,self.assertIsNotBetween, obs, 2.0, 4.0)
def test_assertIsNotBetween_mixed_true(self):
"""assertIsNotBetween should pass when a number is not in bounds"""
self.assertIsNotBetween(1, 2.0, 3.0)
self.assertIsNotBetween(1.0, 2, 3.0)
self.assertIsNotBetween(1.0, 2.0, 3)
def test_assertIsNotBetween_mixed_false(self):
"""assertIsNotBetween should raise when a number is in bounds"""
self.assertRaises(AssertionError, self.assertIsNotBetween, 2.0, 1.0, 3)
self.assertRaises(AssertionError, self.assertIsNotBetween, 2.0, 1, 3.0)
self.assertRaises(AssertionError, self.assertIsNotBetween, 2, 1.0, 3.0)
def test_assertIsNotBetween_mixed_list_true(self):
"""assertIsNotBetween should pass when all elements are not in bounds"""
obs = [1, 2.0, 3, 4.0, 5.0]
self.assertIsNotBetween(obs, 5.0, 10.0)
self.assertIsNotBetween(obs, 5, 10.0)
self.assertIsNotBetween(obs, 5.0, 10)
def test_assertIsNotBetween_mixed_list_false(self):
"""assertIsNotBetween should raise when any element is in bounds"""
obs = [1, 2.0, 3, 4.0, 5.0]
self.assertRaises(AssertionError,self.assertIsNotBetween, obs, 3.0, 7.0)
self.assertRaises(AssertionError,self.assertIsNotBetween, obs, 3, 7.0)
self.assertRaises(AssertionError,self.assertIsNotBetween, obs, 3.0, 7)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_struct/__init__.py 000644 000765 000024 00000000637 12024702176 022105 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_rna2d', 'test_annotation', 'test_selection', 'test_asa',
'test_manipulation', 'test_contact']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Sandra Smit", "Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_struct/test_annotation.py 000644 000765 000024 00000004315 12024702176 023554 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import os
try:
from cogent.util.unit_test import TestCase, main
from cogent.parse.pdb import PDBParser
from cogent.struct.annotation import xtradata
from cogent.struct.selection import einput
except ImportError:
from zenpdb.cogent.util.unit_test import TestCase, main
from zenpdb.cogent.parse.pdb import PDBParser
from zenpdb.cogent.struct.annotation import xtradata
from zenpdb.cogent.struct.selection import einput
__author__ = "Marcin Cieslik"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Development"
class AnnotationTest(TestCase):
"""tests if annotation get into xtra."""
def setUp(self):
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
def test_xtradata(self):
"""tests if an full_id's in the data dict are correctly parsed."""
structure = einput(self.input_structure, 'S')[('2E12',)]
model = einput(self.input_structure, 'M')[('2E12', 0)]
chain = einput(self.input_structure, 'C')[('2E12', 0, 'B')]
residue = einput(self.input_structure, 'R')[('2E12', 0, 'B', ('LEU', 24, ' '))]
atom = einput(self.input_structure, 'A')[('2E12', 0, 'B', ('LEU', 24, ' '), ('CD1', ' '))]
data_model = {(None, 0):{'model':1}}
xtradata(data_model, structure)
self.assertEquals(model.xtra, {'model': 1})
data_chain = {(None, None, 'B'):{'chain':1}}
xtradata(data_chain, model)
self.assertEquals(chain.xtra, {'chain': 1})
data_chain = {(None, 0, 'B'):{'chain': 2}}
xtradata(data_chain, structure)
self.assertEquals(chain.xtra['chain'], 2)
data_residue = {(None, None, 'B', ('LEU', 24, ' ')):{'residue':1}}
xtradata(data_residue, model)
self.assertEquals(residue.xtra, {'residue': 1})
data_residue = {(None, 0, 'B', ('LEU', 24, ' ')):{'residue':2}}
xtradata(data_residue, structure)
self.assertEquals(residue.xtra, {'residue': 2})
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_struct/test_asa.py 000644 000765 000024 00000021056 12024702176 022147 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import os
import numpy as np
from numpy import sum
from cogent.util.unit_test import TestCase, main
from cogent.app.util import ApplicationNotFoundError
from cogent.parse.pdb import PDBParser
from cogent.struct.selection import einput
from cogent.maths.stats.test import correlation
__author__ = "Marcin Cieslik"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Development"
class DummyFile(object):
def __init__(self, some_string):
self.some_string = some_string
slist = self.some_string.split('\n')
self.some_string_list = [i + '\n' for i in slist]
def readlines(self):
return self.some_string_list
def close(self):
pass
test_file_water = """
HETATM 1185 O HOH 268 141.577 14.676 13.168 1.00 54.76 O
HETATM 1186 O HOH 269 137.019 17.606 19.854 1.00 33.36 O
HETATM 1187 O HOH 270 149.639 55.203 4.611 1.00 49.01 O
HETATM 1188 O HOH 271 156.238 32.191 -4.204 1.00 64.53 O
CONECT 453 685
CONECT 685 453
MASTER 357 0 0 1 10 0 0 6 1187 1 2 12
END
"""
dummy_water = DummyFile(test_file_water)
class asaTest(TestCase):
"""Tests for surface calculations."""
def setUp(self):
self.arr = np.random.random(3000).reshape((1000, 3))
self.point = np.random.random(3)
self.center = np.array([0.5, 0.5, 0.5])
def test_0import(self):
# sort by name
"""tests if can import _asa cython extension."""
global _asa
from cogent.struct import _asa
assert 'asa_loop' in dir(_asa)
def test_1import(self):
# sort by name
"""tests if can import asa."""
global asa
from cogent.struct import asa
def test_asa_loop(self):
"""tests if inner asa_loop (cython) performs correctly"""
self.lcoords = np.array([[-4., 0, 0], [0, 0, 0], [4, 0, 0], [10, 0, 0]])
self.qcoords = np.array([[0., 0, 0], [4., 0, 0]])
self.lradii = np.array([2., 3.])
self.qradii = np.array([3., 2.])
#spoints, np.ndarray[DTYPE_t, ndim =1] box,\
# DTYPE_t probe, unsigned int bucket_size, MAXSYM =200000)
self.spoints = np.array([[1., 0., 0.], [-1., 0., 0.], [0., 1., 0.], \
[0., -1., 0.], [0., 0., 1.], [0., 0., -1.]])
output = _asa.asa_loop(self.qcoords, self.lcoords, self.qradii, \
self.lradii, self.spoints, \
np.array([-100., -100., -100., 100., 100., 100.]), 1., 10)
self.assertFloatEqual(output, np.array([ 75.39822369, 41.88790205]))
def test_asa_xtra(self):
"""test internal asa"""
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
self.assertRaises(ValueError, asa.asa_xtra, self.input_structure, mode='a')
result = asa.asa_xtra(self.input_structure)
a = einput(self.input_structure, 'A')
for i in range(len(result)):
self.assertEquals(result.values()[i]['ASA'], a[result.keys()[i]].xtra['ASA'])
r = einput(self.input_structure, 'R')
for water in r.selectChildren('H_HOH', 'eq', 'name').values():
self.assertFalse('ASA' in water.xtra)
for residue in r.selectChildren('H_HOH', 'ne', 'name').values():
for a in residue:
self.assertTrue('ASA' in a.xtra)
result = asa.asa_xtra(self.input_structure, xtra_key='SASA')
for residue in r.selectChildren('H_HOH', 'ne', 'name').values():
for a in residue:
a.xtra['ASA'] == a.xtra['SASA']
def test_asa_xtra_stride(self):
"""test asa via stride"""
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
try:
result = asa.asa_xtra(self.input_structure, 'stride')
except ApplicationNotFoundError:
return
self.assertAlmostEqual(self.input_structure[(0,)][('B',)]\
[(('LEU', 35, ' '),)].xtra['STRIDE_ASA'], 17.20)
def test_compare(self):
"""compares internal asa to stride."""
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
try:
asa.asa_xtra(self.input_structure, mode='stride')
except ApplicationNotFoundError:
return
asa.asa_xtra(self.input_structure)
self.input_structure.propagateData(sum, 'A', 'ASA', xtra=True)
residues = einput(self.input_structure, 'R')
asa1 = []
asa2 = []
for residue in residues.selectChildren('H_HOH', 'ne', 'name').values():
asa1.append(residue.xtra['ASA'])
asa2.append(residue.xtra['STRIDE_ASA'])
self.assertAlmostEqual(correlation(asa1, asa2)[1], 0.)
def test_uc(self):
"""compares asa within unit cell."""
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
asa.asa_xtra(self.input_structure, symmetry_mode='uc', xtra_key='ASA_UC')
asa.asa_xtra(self.input_structure)
self.input_structure.propagateData(sum, 'A', 'ASA', xtra=True)
self.input_structure.propagateData(sum, 'A', 'ASA_UC', xtra=True)
residues = einput(self.input_structure, 'R')
x = residues[('2E12', 0, 'B', ('GLU', 77, ' '))].xtra.values()
self.assertTrue(x[0] != x[1])
def test_uc2(self):
self.input_file = os.path.join('data', '1LJO.pdb')
self.input_structure = PDBParser(open(self.input_file))
asa.asa_xtra(self.input_structure, symmetry_mode='uc', xtra_key='ASA_XTAL')
asa.asa_xtra(self.input_structure)
self.input_structure.propagateData(sum, 'A', 'ASA', xtra=True)
self.input_structure.propagateData(sum, 'A', 'ASA_XTAL', xtra=True)
residues = einput(self.input_structure, 'R')
r1 = residues[('1LJO', 0, 'A', ('ARG', 65, ' '))]
r2 = residues[('1LJO', 0, 'A', ('ASN', 46, ' '))]
self.assertFloatEqual(r1.xtra.values(),
[128.94081270529105, 22.807700865674093])
self.assertFloatEqual(r2.xtra.values(),
[115.35738419425566, 115.35738419425566])
def test_crystal(self):
"""compares asa within unit cell."""
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
asa.asa_xtra(self.input_structure, symmetry_mode='uc', crystal_mode=2, xtra_key='ASA_XTAL')
asa.asa_xtra(self.input_structure)
self.input_structure.propagateData(sum, 'A', 'ASA', xtra=True)
self.input_structure.propagateData(sum, 'A', 'ASA_XTAL', xtra=True)
residues = einput(self.input_structure, 'R')
r1 = residues[('2E12', 0, 'A', ('ALA', 42, ' '))]
r2 = residues[('2E12', 0, 'A', ('VAL', 8, ' '))]
r3 = residues[('2E12', 0, 'A', ('LEU', 25, ' '))]
self.assertFloatEqual(r1.xtra.values(), \
[32.041070749038823, 32.041070749038823])
self.assertFloatEqual(r3.xtra.values(), \
[0., 0.])
self.assertFloatEqual(r2.xtra.values(), \
[28.873559956056916, 0.0])
def test__prepare_entities(self):
self.input_structure = PDBParser(dummy_water)
self.assertRaises(ValueError, asa._prepare_entities, self.input_structure)
def _test_bio(self):
"""compares asa within a bio unit."""
self.input_file = os.path.join('data', '1A1X.pdb')
self.input_structure = PDBParser(open(self.input_file))
asa.asa_xtra(self.input_structure, symmetry_mode='bio', xtra_key='ASA_BIO')
asa.asa_xtra(self.input_structure)
self.input_structure.propagateData(sum, 'A', 'ASA', xtra=True)
self.input_structure.propagateData(sum, 'A', 'ASA_BIO', xtra=True)
residues = einput(self.input_structure, 'R')
r1 = residues[('1A1X', 0, 'A', ('GLU', 37, ' '))]
r2 = residues[('1A1X', 0, 'A', ('TRP', 15, ' '))]
self.assertFloatEqual(r1.xtra.values(), \
[20.583191467544726, 78.996394472066541])
self.assertFloatEqual(r2.xtra.values(), \
[136.41436710386989, 136.41436710386989])
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_struct/test_contact.py 000644 000765 000024 00000005274 12024702176 023042 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import os
import numpy as np
try:
from cogent.util.unit_test import TestCase, main
from cogent.parse.pdb import PDBParser
from cogent.struct.selection import einput
except ImportError:
from zenpdb.cogent.util.unit_test import TestCase, main
from zenpdb.cogent.parse.pdb import PDBParser
from zenpdb.cogent.struct.selection import einput
__author__ = "Marcin Cieslik"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Development"
class asaTest(TestCase):
"""Tests for surface calculations."""
def setUp(self):
self.arr = np.random.random(3000).reshape((1000, 3))
self.point = np.random.random(3)
self.center = np.array([0.5, 0.5, 0.5])
def test_0import(self):
# sort by name
"""tests if can import _contact cython extension."""
global _contact
from cogent.struct import _contact
assert 'cnt_loop' in dir(_contact)
def test_1import(self):
# sort by name
"""tests if can import contact."""
global contact
from cogent.struct import contact
def test_chains(self):
"""compares contacts diff chains"""
self.input_file = os.path.join('data', '1A1X.pdb') # one chain
self.input_structure = PDBParser(open(self.input_file))
res = contact.contacts_xtra(self.input_structure)
self.assertTrue(res == {})
self.input_file = os.path.join('data', '2E12.pdb') # one chain
self.input_structure = PDBParser(open(self.input_file))
res = contact.contacts_xtra(self.input_structure)
self.assertTrue(res)
self.assertFloatEqual(\
res[('2E12', 0, 'B', ('THR', 17, ' '), ('OG1', ' '))]['CONTACTS']\
[('2E12', 0, 'A', ('ALA', 16, ' '), ('CB', ' '))][0], 5.7914192561064004)
def test_symmetry(self):
"""compares contacts diff symmetry mates"""
self.input_file = os.path.join('data', '2E12.pdb') # one chain
self.input_structure = PDBParser(open(self.input_file))
res = contact.contacts_xtra(self.input_structure, \
symmetry_mode='uc',
contact_mode='diff_sym')
self.assertTrue(res)
self.assertFloatEqual(\
res[('2E12', 0, 'B', ('GLU', 77, ' '), ('OE2', ' '))]['CONTACTS']\
[('2E12', 0, 'B', ('GLU', 57, ' '), ('OE2', ' '))][0], \
5.2156557833123873)
def test_crystal(self):
""""compares contacts diff unit-cell-mates"""
pass
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_struct/test_dihedral.py 000644 000765 000024 00000033544 12024702176 023164 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
#
# test_dihedral.py
#
# Tests the dihedral module.
#
"""Provides tests for functions in the file dihedral.py
"""
__author__ = "Kristian Rother"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Kristian Rother", "Sandra Smit"]
__credits__ = ["Janusz Bujnicki", "Nils Goldmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Kristian Rother"
__email__ = "krother@rubor.de"
__status__ = "Production"
from cogent.util.unit_test import main, TestCase
from cogent.struct.dihedral import dihedral, scalar, angle, \
calc_angle, DihedralGeometryError, AngleGeometryError
from random import random
from numpy import array
from math import pi, cos, sin
class DihedralTests(TestCase):
def get_random_array(self):
"""
Returns a one-dimensional numpy array with three random floats
in the range between -5.0 and +5.0.
"""
return array([(random()-0.5)*10,(random()-0.5)*10,(random()-0.5)*10])
def assertAlmostEqualAngle(self, is_value, should_value, digits=7):
"""
Checks two angles in degrees whether they are the same within
the given number of digits. This has been implemented to make sure
that 359.9999991 == 0.0
"""
maxv = 359.0
for i in range(digits):
maxv += 0.9 * 0.1**i
while is_value < 0.0: is_value += 360
while is_value > maxv: is_value -= 360
while should_value < 0.0: should_value += 360
while should_value > maxv: should_value -= 360
self.assertAlmostEqual(is_value,should_value, digits)
def test_scalar(self):
"""Tests the scalar product function for one-dimensional arrays."""
# test one-dimensional arrays
self.assertEqual(scalar(array([0]),array([0])),0.0)
self.assertEqual(scalar(array([2]),array([3])),6.0)
self.assertEqual(scalar(array([0,0]),array([0,0])),0.0)
self.assertEqual(scalar(array([-1,-4]),array([1,4])),-17.0)
self.assertEqual(scalar(array([1,2]),array([3,4])),11.0)
self.assertEqual(scalar(array([-1,-4]),array([-1,4])),-15.0)
self.assertEqual(scalar(array([0,0,0]),array([0,0,0])),0.0)
self.assertEqual(scalar(array([2.5,0,-1]),array([2.5,0,-1])),7.25)
self.assertEqual(scalar(array([1,2,3]),array([0,0,0])),0.0)
self.assertEqual(scalar(array([1,2,3]),array([1,2,3])),14.0)
self.assertEqual(scalar(array([1,2,3]),array([4,5,6])),32.0)
# test two-dimensional arrays (should not be a feature)
self.assertNotEqual(scalar(array([[0,0],[0,0]]),\
array([[0,0],[0,0]])),0.0)
def test_angle_simple(self):
"""Tests the angle function for one- and two-dimensional vectors."""
# test two-dimensional vectors (not arrays!)
self.assertEqual(angle(array([0,1]),array([1,0])),0.5*pi)
self.assertEqual(angle(array([5,0]),array([13,0])),0.0)
self.assertEqual(angle(array([2,3]),array([26,39])),0.0)
self.assertEqual(angle(array([2,3]),array([-3,2])),0.5*pi)
self.assertEqual(angle(array([-5,0]),array([13,0])),pi)
# test three-dimensional vectors (not arrays!)
self.assertEqual(angle(array([0,0,-1]),array([0,0,1])),pi)
self.assertEqual(angle(array([0,15,-1]),array([0,-15,1])),pi)
self.assertEqual(angle(array([0,0,7]),array([14,14,0])),0.5*pi)
self.assertEqual(angle(array([0,7,7]),array([0,14,14])),0.0)
self.assertAlmostEqual(angle(array([100000000.0,0,1]),\
array([1,0,0])),0.0)
def test_calc_angle_simple(self):
"""Tests the calc_angle function for one- and two-dimensional vectors."""
# test two-dimensional vectors (not arrays!)
self.assertEqual(calc_angle(array([0,1]),array([0,0]),array([1,0])),0.5*pi)
self.assertEqual(calc_angle(array([5,0]),array([0,0]),array([13,0])),0.0)
self.assertEqual(calc_angle(array([4,3]),array([2,0]),array([28,39])),0.0)
self.assertEqual(calc_angle(array([2,-13]),array([0,-10]),array([-3,-12])),0.5*pi)
self.assertEqual(calc_angle(array([-5,0]),array([0,0]),array([13,0])),pi)
# test three-dimensional vectors (not arrays!)
self.assertEqual(calc_angle(array([0,0,-1]),array([0,0,0]),array([0,0,1])),pi)
self.assertEqual(calc_angle(array([0,15,-1]),array([0,0,0]),array([0,-15,1])),pi)
self.assertEqual(calc_angle(array([0,10,7]),array([0,10,0]),array([14,24,0])),0.5*pi)
self.assertEqual(calc_angle(array([0,7,7]),array([0,0,0]),array([0,14,14])),0.0)
self.assertAlmostEqual(calc_angle(array([100000000.0,0,1]),\
array([0,0,0]),array([1,0,0])),0.0)
## def make_scipy_angles(self):
## """Generates the test data given below. Was commented out
## for getting rid of the library dependency"""
## from Scientific.Geometry import Vector
## for i in range(20):
## v1 = self.get_random_array()
## v2 = self.get_random_array()
## vec1 = Vector(v1[0],v1[1],v1[2])
## vec2 = Vector(v2[0],v2[1],v2[2])
## scipy_angle = vec1.angle(vec2)
## out = [(vec1[0],vec1[1],vec1[2]),\
## (vec2[0],vec2[1],vec2[2]),scipy_angle]
## print out,","
def test_angle_scipy(self):
"""
Asserts that dihedral and ScientificPython calculate the same angles.
"""
for v1,v2,scipy_angle in SCIPY_ANGLES:
ang = angle(array(v1),array(v2))
self.assertAlmostEqual(ang, scipy_angle)
def test_angle_fail(self):
"""The angle function should fail for zero length vectors."""
# should not work for zero length vectors
self.assertRaises(AngleGeometryError,angle,\
array([0,0]),array([0,0]))
self.assertRaises(AngleGeometryError,angle,\
array([0,0,0]),array([0,0,0]))
def test_dihedral_eight_basic_directions(self):
"""Checks dihedrals in all 45 degree intervals."""
# using vectors with integer positions.
self.assertAlmostEqualAngle(\
dihedral([-2,-1,0], [-1,0,0], [1,0,0], [2,-1, 0]), 0.0)
self.assertAlmostEqualAngle(\
dihedral([-2,-1,0], [-1,0,0], [1,0,0], [2,-1,-1]), 45.0)
self.assertAlmostEqualAngle(\
dihedral([-2,-1,0], [-1,0,0], [1,0,0], [2, 0,-1]), 90.0)
self.assertAlmostEqualAngle(\
dihedral([-2,-1,0], [-1,0,0], [1,0,0], [2, 1,-1]),135.0)
self.assertAlmostEqualAngle(\
dihedral([-2,-1,0], [-1,0,0], [1,0,0], [2, 1, 0]),180.0)
self.assertAlmostEqualAngle(\
dihedral([-2,-1,0], [-1,0,0], [1,0,0], [2, 1, 1]),225.0)
self.assertAlmostEqualAngle(\
dihedral([-2,-1,0], [-1,0,0], [1,0,0], [2, 0, 1]),270.0)
self.assertAlmostEqualAngle(\
dihedral([-2,-1,0], [-1,0,0], [1,0,0], [2,-1, 1]),315.0)
def test_dihedral_rotation(self):
"""Checks all angles in 0.2 degree intervals."""
# constructs vectors using sin/cos and then calculates dihedrals
precision = 5.0 # the higher the better
v1 = array([1,0,1])
v2 = array([0,0,1])
v3 = array([0,0,2])
for i in range(int(360*precision)):
degrees = i/precision
radians = pi*degrees/180.0
opp_degrees = 360-degrees
if opp_degrees == 360.0: opp_degrees = 0.0
# construct circular motion of vector
v4 = array([cos(radians), sin(radians),2])
self.assertAlmostEqualAngle(dihedral(v4,v3,v2,v1), degrees, 5)
# check rotation in the opposite direction
self.assertAlmostEqualAngle(dihedral(v1,v2,v3,v4), degrees, 5)
def test_dihedral_samples(self):
"""Checks values measured manually from atoms in PyMOL."""
coordinates = [
[(-1.225,4.621,42.070),(-1.407,4.455,43.516),\
(-2.495,4.892,44.221),(-3.587,5.523,43.715)],
[(-2.495,4.892,44.221),(1.513,0.381,40.711),\
(-3.091,4.715,47.723),(-0.567,3.892,44.433)],
[(-0.349,5.577,39.446),(-1.559,3.400,41.427),\
(-4.304,5.563,45.998),(-2.495,4.892,44.221)],
[(-45.819,84.315,19.372),(-31.124,72.286,14.035),\
(-27.975,58.688,7.025),(-16.238,78.659,23.731)],
[(-29.346,66.973,24.152),(-29.977,69.635,24.580),\
(-30.875,68.788,24.663),(-30.668,67.495,24.449)],
[(-34.586,84.884,14.064),(-23.351,69.756,11.028),\
(-40.924,69.442,24.630),(-30.875,68.788,24.663)]
]
angles = [1.201, 304.621, 295.672, 195.184, 358.699, 246.603]
for i in range(len(coordinates)):
v1,v2,v3,v4 = coordinates[i]
self.assertAlmostEqualAngle(dihedral(v1,v2,v3,v4), angles[i],3)
def test_dihedral_linear(self):
"""The dihedral function should fail for collinear vectors."""
v1 = [1,0,0]
v2 = [2,0,0]
v3 = [3,0,0]
v4 = [4,0,0]
# print dihedral(v1,v2,v3,v4)
for i in range(100):
offset = array([int((random()-0.5)*10),\
int((random()-0.5)*10),\
int((random()-0.5)*10)])
v1 = array([int((random()-0.5)*100),\
int((random()-0.5)*100),\
int((random()-0.5)*100)])
v2 = v1 * int((random()-0.5)*100) + offset
v3 = v1 * int((random()-0.5)*100) + offset
v4 = v1 * int((random()-0.5)*100) + offset
v1 += offset
self.assertRaises(DihedralGeometryError,dihedral,v1,v2,v3,v4)
def test_dihedral_identical(self):
"""The dihedral function should fail if two vectors are the same."""
# except for the first and last (the vectors form a triangle),
# in which case the dihedral angle should be 0.0
for i in range(100):
v1 = self.get_random_array()
v2 = self.get_random_array()
v3 = self.get_random_array()
self.assertRaises(DihedralGeometryError,dihedral,v1,v1,v2,v3)
self.assertRaises(DihedralGeometryError,dihedral,v1,v2,v1,v3)
self.assertRaises(DihedralGeometryError,dihedral,v1,v2,v2,v3)
self.assertRaises(DihedralGeometryError,dihedral,v1,v2,v3,v3)
self.assertRaises(DihedralGeometryError,dihedral,v1,v3,v2,v3)
# now the triangular case
# make sure that 359.999998 is equal to 0.0
torsion = dihedral(v1,v2,v3,v1) + 0.000001
if torsion > 360.0: torsion -= 360.0
self.assertAlmostEqualAngle(torsion,0.0,5)
SCIPY_ANGLES = [
[(-4.4891521637990852, -1.2310927013330153, -0.96969777583098771),
(4.2147455310344171, -3.5069051036633514, 2.2430685816310305),
2.2088870817461759] ,
[(0.13959847081794097, 1.7204537912940399, -1.9303780516641089),
(0.35412687539602361, -2.9493521724340743, -4.865941405480644),
1.2704043143950585] ,
[(2.3192363837822327, -3.6376441859213848, -2.2337816400479813),
(-1.0271253661119029, -2.5736009846920425, -4.1470855710278975),
0.83609068310373857] ,
[(-0.38347986357358477, -4.1453876196041719, -2.1354583394773785),
(0.27416747968044608, -2.5747732838982551, -0.68554680652905264),
0.28348352552436806] ,
[(-2.4928231204363449, 1.9263125976608209, -0.34275964486924715),
(0.6721152528064811, 1.5270465172130598, -3.5720133753579564),
1.3701121510959966] ,
[(-1.50101403139692, 2.3218275982958292, 1.044582416480222),
(-3.044743729573085, 2.0655933798619532, 2.9037849925327897),
0.46218988498537578] ,
[(4.9648826388927603, -1.7439743270051977, 1.0432135258334796),
(-3.3694557299188608, 3.7697639370274052, 2.6962018714965055),
2.3004031013653625] ,
[(-3.3337033325729051, -0.79660906888508021, -3.4875326261817454),
(1.4735023133671066, -0.066399047153666846, 0.94171530437632489),
2.8293957790283595] ,
[(-2.1249404252000517, 2.7456001658201568, 1.6891202129451799),
(-0.66412553435299504, 3.371012200444512, -1.1548086037901306),
0.89846374464990042] ,
[(3.3993205618602018, 1.2047703532166887, -1.5839949555795063),
(-4.6759756026580863, -2.8551222890449646, 4.888270217692785),
2.7825564894291754] ,
[(-3.966467296275785, 0.75617096138383189, -3.1711352932360248),
(2.1054362220912326, 4.2867761689586601, -0.65739369331424213),
1.6933117193742961] ,
[(0.44413554305522851, 4.6000690382282361, -3.8338383756621819),
(-2.4947413565865029, 1.8136080147734013, -4.0295344084655405),
0.73110709489481174] ,
[(-1.0971777991639065, -3.3166205797568815, 2.7098739534055563),
(2.1536566381847289, 4.7817155120086055, -0.068554664323454695),
2.4878958372925202] ,
[(2.2696914760438136, 4.8841630875833673, 4.9524177412608861),
(1.2249510822623111, 0.73008672334971658, 1.131607772478449),
0.45741431674591532] ,
[(-2.4456899797216938, 4.7894200033986447, -2.839449354837468),
(0.95035116225980154, 4.2179212878828238, -1.801158217734109),
0.63144509227951684] ,
[(-4.6954041297179474, -2.8326266911591391, -1.1804869511610427),
(3.2585456362256924, -2.2325171051479265, -2.0527260317826901),
1.8363466110668369] ,
[(2.1416146613604283, 3.8577375591718677, 3.1463493245087939),
(-0.32185887240442468, 2.2163051363839505, 2.4704882512058224),
0.52534998201320993] ,
[(-2.8493351354335941, -3.8203784990110954, 2.4657357720402273),
(-2.7799043389229383, 4.358406526726669, -2.8319872383058744),
2.0906833125217235] ,
[(2.274223250163784, -3.6086250253596406, 1.7143006579401876),
(3.2763334328544347, -0.89908959703552171, -4.4068824993431557),
1.4477009361020545] ,
[(0.66737672421842809, -3.4628508908383848, 3.9044108358095366),
(-1.9078974719893915, -0.53231141116878433, 1.3323584972786728),
1.0932781951137689] ,
]
if __name__== '__main__':
main()
PyCogent-1.5.3/tests/test_struct/test_knots.py 000644 000765 000024 00000153205 12024702176 022543 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# test_knots.py
"""Provides tests for classes and functions in the file knots.py
"""
from __future__ import division
from cogent.util.unit_test import TestCase, main
from cogent.util.dict2d import Dict2D
from cogent.struct.rna2d import Pairs
from cogent.struct.knots import PairedRegion, PairedRegionFromPairs,\
PairedRegions, PairedRegionsFromPairs, ConflictMatrix,\
opt_all, contains_true, empty_matrix,\
pick_multi_best, dp_matrix_multi, matrix_solutions,\
opt_single_random, opt_single_property,\
inc_order, inc_length, inc_range,\
find_max_conflicts, find_min_gain,\
conflict_elimination, add_back_non_conflicting,\
num_bps, hydrogen_bonds,\
nussinov_fill, nussinov_traceback, nussinov_restricted
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Sandra Smit, Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Production"
class PairedRegionTests(TestCase):
"""Tests for PairedRegion class"""
def test_init_valid(self):
"""PairedRegion __init__: should work as expected on valid input
"""
pr = PairedRegion(3,10,2)
self.assertEqual(pr.Start, 3)
self.assertEqual(pr.End, 10)
self.assertEqual(pr.Length, 2)
self.assertEqual(pr.Pairs, [(3,10),(4,9)])
pr = PairedRegion(3,10,2, Id=0)
self.assertEqual(pr.Id, 0)
pr = PairedRegion(3,10,2, Id='A')
self.assertEqual(pr.Id, 'A')
self.assertRaises(ValueError, PairedRegion, 4, 10, 0)
def test_init_weird(self):
"""PairedRegion __init__: no error checking
"""
pr = PairedRegion(3,6,4)
self.assertEqual(pr.Start, 3)
self.assertEqual(pr.End, 6)
self.assertEqual(pr.Length, 4)
self.assertEqual(pr.Pairs, [(3,6),(4,5),(5,4),(6,3)])
def test_str(self):
"""PairedRegion __str__: should print pairs"""
pr = PairedRegion(3,10,2)
p = Pairs([(3,10),(4,9)])
self.assertEqual(str(pr), str(p))
def test_len(self):
"""PairedRegion __len__: should return number of pairs"""
pr = PairedRegion(3,10,2)
self.assertEqual(len(pr), 2)
def test_eq(self):
"""PairedRegion __eq__: should use pairs and IDs"""
pr1 = PairedRegion(3,10,2)
pr2 = PairedRegion(3,10,2)
pr3 = PairedRegion(3,10,2, Id='A')
pr4 = PairedRegion(3,10,2, Id='A')
pr5 = PairedRegion(3,20,4, Id='A')
self.assertEqual(pr1==pr2, True) # same pairs, no IDs
self.assertEqual(pr3==pr4, True) # same pairs, same IDs
self.assertEqual(pr1==pr3, False) # same pairs, diff ID
self.assertEqual(pr3==pr5, False) # diff pairs, same IDs
def test_upstream(self):
"""PairedRegions upstream: single and multiple pair(s)"""
pr = PairedRegion(3,10,2)
self.assertEqual(pr.upstream(), [3,4])
pr = PairedRegion(3,10,1)
self.assertEqual(pr.upstream(), [3])
def test_downstream(self):
"""PairedRegions downstream: single and multiple pair(s)"""
pr = PairedRegion(3,10,2)
self.assertEqual(pr.downstream(), [9,10])
pr = PairedRegion(3,10,1)
self.assertEqual(pr.downstream(), [10])
def test_paired(self):
"""PairedRegion paired: single and multiple pair(s)"""
pr = PairedRegion(3,10,2)
self.assertEqual(pr.paired(), [3,4,9,10])
pr = PairedRegion(3,10,1)
self.assertEqual(pr.paired(), [3,10])
def test_regionRange(self):
"""PairedRegion regionRange: single and multiple pair(s)"""
pr = PairedRegion(3,10,2)
self.assertEqual(pr.range(), 4)
pr = PairedRegion(1,10,4)
self.assertEqual(pr.range(), 2)
pr = PairedRegion(1,5,1)
self.assertEqual(pr.range(), 3)
# no error checking
pr = PairedRegion(5,8,3) # 5,6,7,-- 6,7,8
self.assertEqual(pr.range(), -2)
def test_overlapping(self):
"""PairedRegion overlapping: identical and different regions"""
pr1 = PairedRegion(1,10,2)
pr2 = PairedRegion(3,15,2)
self.assertEqual(pr1.overlapping(pr2), False)
self.assertEqual(pr2.overlapping(pr1), False)
pr1 = PairedRegion(1,10,2)
pr2 = PairedRegion(2,15,2)
pr3 = PairedRegion(9,20,4)
self.assertEqual(pr1.overlapping(pr2), True)
self.assertEqual(pr2.overlapping(pr1), True)
self.assertEqual(pr1.overlapping(pr3), True)
bl1 = PairedRegion(2,10,1)
bl2 = PairedRegion(12,20,3)
self.assertEqual(bl1.overlapping(bl2), False)
pr1 = PairedRegion(1,10,2, Id='A')
pr2 = PairedRegion(1,10,2, Id='A')
pr3 = PairedRegion(1,10,2, Id='B')
self.assertEqual(pr1.overlapping(pr2), True)
self.assertEqual(pr1.overlapping(pr3), True) # ignore ID
def test_conflicting(self):
"""PairedRegion conflicting: identical, nested and pseudoknot"""
bl1 = PairedRegion(2,10,3)
bl2 = PairedRegion(12,20,3)
# identical blocks are NOT conflicting...
self.assertEqual(bl1.conflicting(bl1), False) # identical blocks
self.assertEqual(bl1.conflicting(bl2), False) # one after the other
self.assertEqual(bl2.conflicting(bl1), False) # one after the other
bl1 = PairedRegion(1,30,2) #[(1,30),(2,29)]
bl2 = PairedRegion(14,20,2) #[(14,20),(15,19)]
self.assertEqual(bl1.conflicting(bl2), False) # one inside the other
self.assertEqual(bl2.conflicting(bl1), False) # one inside the other
bl1 = PairedRegion(1,10,2) #[(1,10),(2,9)]
bl2 = PairedRegion(4,15,3) #[(4,15),(5,14),(6,13)]
self.assertEqual(bl1.conflicting(bl2), True) # pseudoknot
self.assertEqual(bl2.conflicting(bl1), True) # pseudoknot
def test_score(self):
"""PairedRegion score: should take arbitrary scoring function"""
f = lambda x: x.Length # scoring function
bl1 = PairedRegion(2,10,3)
bl2 = PairedRegion(12,30,4)
bl1.score(f) # set Score attribute for bl1
bl2.score(f) # set Score attribute for bl2
self.assertEqual(bl1.Score, 3)
self.assertEqual(bl2.Score, 4)
def test_PairedRegionFromPairs(self):
"""PairedRegionFromPairs: should handle valid input"""
p = Pairs([(3,10),(4,9),(5,8)])
pr = PairedRegionFromPairs(p, Id='A')
self.assertEqual(pr.Start, 3)
self.assertEqual(pr.End, 10)
self.assertEqual(pr.Length, 3)
self.assertEqual(pr.Id, 'A')
self.assertEqual(pr.Pairs, [(3,10),(4,9),(5,8)])
def test_PairedRegionFromPairs_invalid(self):
"""PairedRegionFromPairs: conflicts and error checking"""
p = Pairs([(3,10),(4,9),(4,None)])
self.assertRaises(ValueError, PairedRegionFromPairs, p)
# no error checking on input pairs...
p = Pairs([(3,10),(4,9),(6,8)]) # not a real paired region
pr = PairedRegionFromPairs(p, Id='A')
self.assertEqual(pr.Start, 3)
self.assertEqual(pr.End, 10)
self.assertEqual(pr.Length, 3)
self.assertEqual(pr.Id, 'A')
# NOTE: Pairs will be different than input because assumption does
# not hold
self.assertEqual(pr.Pairs, [(3,10),(4,9),(5,8)])
self.assertRaises(ValueError, PairedRegionFromPairs, [])
class PairedRegionsTests(TestCase):
"""Tests for PairedRegions class"""
def test_init(self):
"""PairedRegions __init__: should accept list of PairedRegion objects
"""
pr1 = PairedRegion(3,10,2)
pr2 = PairedRegion(12,20,3)
obs = PairedRegions([pr1, pr2])
self.assertEqual(obs[0].Start, 3)
self.assertEqual(obs[1].Id, None)
self.assertEqual(obs[1].End, 20)
def test_init_no_validation(self):
"""PairedRegions __init__: does not perform validation
"""
# can give any list of arbitrary object as input
obs = PairedRegions([1,2,3])
self.assertEqual(obs[0], 1)
def test_str(self):
"""PairedRegions __str__: full and empty list
"""
pr1 = PairedRegion(3,10,2)
pr2 = PairedRegion(12,20,3, Id='A')
prs = PairedRegions([pr1, pr2])
self.assertEqual(str(prs), "(None:3,10,2; A:12,20,3;)")
def test_eq(self):
"""PairedRegions __eq__: with/without IDs, in or out of order
"""
pr1 = PairedRegion(3,10,2)
pr2 = PairedRegion(12,20,3, Id='A')
prs1 = PairedRegions([pr1, pr2])
pr3 = PairedRegion(3,10,3)
pr4 = PairedRegion(20,30,3, Id='A')
prs2 = PairedRegions([pr3, pr4])
pr5 = PairedRegion(3,10,2)
pr6 = PairedRegion(12,20,3, Id='A')
prs3 = PairedRegions([pr5, pr6])
prs4 = PairedRegions([pr6, pr5])
self.assertEqual(prs1==prs2, False)
self.assertEqual(prs1==prs1, True)
self.assertEqual(prs1==prs3, True)
self.assertEqual(prs1==prs4, True)
def test_ne(self):
"""PairedRegions __ne__: with/without IDs, in or out of order
"""
pr1 = PairedRegion(3,10,2)
pr2 = PairedRegion(12,20,3, Id='A')
prs1 = PairedRegions([pr1, pr2])
pr3 = PairedRegion(3,10,3)
pr4 = PairedRegion(20,30,3, Id='A')
prs2 = PairedRegions([pr3, pr4])
pr5 = PairedRegion(3,10,2)
pr6 = PairedRegion(12,20,3, Id='A')
prs3 = PairedRegions([pr5, pr6])
prs4 = PairedRegions([pr6, pr5])
self.assertEqual(prs1!=prs2, True)
self.assertEqual(prs1!=prs1, False)
self.assertEqual(prs1!=prs3, False)
self.assertEqual(prs1!=prs4, False)
def test_byId(self):
"""PairedRegions byId: unique IDs and duplicates
"""
pr1 = PairedRegion(3,10,2, Id='A')
pr2 = PairedRegion(12,20,3, Id='B')
prs1 = PairedRegions([pr1, pr2])
obs = prs1.byId()
self.assertEqual(obs['A'], pr1)
self.assertEqual(obs['B'], pr2)
self.assertEqual(len(obs), 2)
pr3 = PairedRegion(3,10,2, Id='A')
pr4 = PairedRegion(12,20,3, Id='A')
prs2 = PairedRegions([pr3, pr4])
self.assertRaises(ValueError, prs2.byId)
pr3 = PairedRegion(3,10,2)
pr4 = PairedRegion(12,20,3)
prs2 = PairedRegions([pr3, pr4])
self.assertRaises(ValueError, prs2.byId)
self.assertEqual(PairedRegions().byId(), {})
def test_numberOfRegions(self):
"""PairedRegions numberOfRegions: full and empty"""
pr1 = PairedRegion(2,10,2)
pr2 = PairedRegion(11,20,4)
prs1 = PairedRegions([pr1,pr2])
prs2 = PairedRegions([pr1,pr1,pr2,pr2])
self.assertEqual(prs1.numberOfRegions(), 2)
self.assertEqual(prs2.numberOfRegions(), 4)
self.assertEqual(PairedRegions().numberOfRegions(), 0)
def test_totalLength(self):
"""PairedRegions totalLength: full and empty"""
pr1 = PairedRegion(2,10,2)
pr2 = PairedRegion(11,20,4)
prs1 = PairedRegions([pr1,pr2])
self.assertEqual(prs1.totalLength(), 6)
self.assertEqual(PairedRegions().totalLength(), 0)
def test_totalScore(self):
"""PairedRegions totalScore: full, empty, None"""
pr1 = PairedRegion(2,10,2)
pr1.Score = 3
pr2 = PairedRegion(11,20,4)
pr2.Score = 2
pr3 = PairedRegion(11,20,4)
pr3.Score = None
pr4 = PairedRegion(11,20,4)
pr4.Score = "abc"
pr5 = PairedRegion(11,20,4)
prs1 = PairedRegions([pr1,pr2])
prs2 = PairedRegions([pr1,pr3])
prs3 = PairedRegions([pr1,pr4])
prs4 = PairedRegions([pr1,pr5])
self.assertEqual(prs1.totalScore(), 5)
self.assertRaises(ValueError, prs2.totalScore)
self.assertRaises(ValueError, prs3.totalScore)
self.assertRaises(ValueError, prs4.totalScore)
def test_toPairs(self):
"""PairedRegions toPairs: good data"""
pr1 = PairedRegion(2,10,2)
pr2 = PairedRegion(11,20,4)
prs1 = PairedRegions([pr2,pr1])
exp = [(2,10),(3,9),(11,20),(12,19),(13,18),(14,17)]
self.assertEqual(prs1.toPairs(), exp)
prs2 = PairedRegions([pr1,pr1])
exp = [(2,10),(2,10),(3,9),(3,9)]
self.assertEqual(prs2.toPairs(), exp)
self.assertEqual(PairedRegions().toPairs(), Pairs())
def test_byStartEnd(self):
"""PairedRegions byStartEnd: unique and duplicate keys"""
pr1 = PairedRegion(2,10,2)
pr2 = PairedRegion(11,20,4)
prs1 = PairedRegions([pr2,pr1])
exp = {(2,10): pr1, (11,20): pr2}
self.assertEqual(prs1.byStartEnd(), exp)
pr3 = PairedRegion(2,10,2, Id='A')
pr4 = PairedRegion(2,10,3, Id='B')
prs2 = PairedRegions([pr3,pr4])
self.assertRaises(ValueError, prs2.byStartEnd)
def test_lowestStart(self):
"""PairedRegions lowestStart: full and empty object"""
pr1 = PairedRegion(2,10,2)
pr2 = PairedRegion(11,20,4)
pr3 = PairedRegion(2,30,5,Id='A')
prs1 = PairedRegions([pr2,pr1,pr3])
self.assertEqual(prs1.lowestStart(), 2)
self.assertEqual(PairedRegions().lowestStart(), None)
def test_highestEnd(self):
"""PairedRegions highestEnd: full and empty object"""
pr1 = PairedRegion(2,10,2)
pr2 = PairedRegion(11,20,4)
pr3 = PairedRegion(2,30,5,Id='A')
prs1 = PairedRegions([pr2,pr1,pr3])
self.assertEqual(prs1.highestEnd(), 30)
self.assertEqual(PairedRegions().highestEnd(), None)
def test_sortedIds(self):
"""PairedRegions sortedIds: full and empty list"""
pr1 = PairedRegion(2,10,2, Id='C')
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(2,30,5,Id='B')
prs1 = PairedRegions([pr1,pr2,pr3])
self.assertEqual(prs1.sortedIds(), ['A','B','C'])
pr1 = PairedRegion(2,10,2, Id='C')
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(2,30,5,Id='C')
prs1 = PairedRegions([pr1,pr2,pr3])
self.assertEqual(prs1.sortedIds(), ['A','C','C'])
pr1 = PairedRegion(2,10,2)
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(2,30,5,Id=2)
prs1 = PairedRegions([pr1,pr2,pr3])
self.assertEqual(prs1.sortedIds(), [None, 2, 'A'])
def test_upstream(self):
"""PairedRegions upstream: full and empty"""
self.assertEqual(PairedRegions().upstream(), [])
pr1 = PairedRegion(2,10,2, Id='C')
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(4,30,1,Id='B')
prs1 = PairedRegions([pr1,pr2,pr3])
exp = [2,3,11,12,13,14,4]
exp.sort()
self.assertEqual(prs1.upstream(), exp)
def test_downstream(self):
"""PairedRegions upstream: full and empty"""
self.assertEqual(PairedRegions().downstream(), [])
pr1 = PairedRegion(2,10,2, Id='C')
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(4,30,1,Id='B')
prs1 = PairedRegions([pr1,pr2,pr3])
exp = [10,9,20,19,18,17,30]
exp.sort()
self.assertEqual(prs1.downstream(), exp)
def test_pairedPos(self):
"""PairedRegions pairedPos: full and empty"""
self.assertEqual(PairedRegions().pairedPos(), [])
pr1 = PairedRegion(2,10,2, Id='C')
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(4,30,1,Id='B')
prs1 = PairedRegions([pr1,pr2,pr3])
exp = [2,3,11,12,13,14,4,10,9,20,19,18,17,30]
exp.sort()
self.assertEqual(prs1.pairedPos(), exp)
def test_boundaries(self):
"""PairedRegions boundaries: full and empty"""
self.assertEqual(PairedRegions().boundaries(), [])
pr1 = PairedRegion(2,10,2, Id='C')
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(4,30,1,Id='B')
prs1 = PairedRegions([pr1,pr2,pr3])
exp = [2,10,11,20,4,30]
exp.sort()
self.assertEqual(prs1.boundaries(), exp)
def test_enumeratedBoundaries(self):
"""PairedRegions enumeratedBoundaries: full and empty"""
self.assertEqual(PairedRegions().enumeratedBoundaries(), {})
pr1 = PairedRegion(2,10,2, Id='C')
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(4,30,1,Id='B')
prs1 = PairedRegions([pr1,pr2,pr3])
exp = {0:2,2:10,3:11,4:20,1:4,5:30}
self.assertEqual(prs1.enumeratedBoundaries(), exp)
def test_invertedEnumeratedBoundaries(self):
"""PairedRegions invertedEnumeratedBoundaries: full and empty"""
self.assertEqual(PairedRegions().invertedEnumeratedBoundaries(), {})
pr1 = PairedRegion(2,10,2, Id='C')
pr2 = PairedRegion(11,20,4, Id='A')
pr3 = PairedRegion(4,30,1,Id='B')
prs1 = PairedRegions([pr1,pr2,pr3])
exp = {2:0,10:2,11:3,20:4,4:1,30:5}
self.assertEqual(prs1.invertedEnumeratedBoundaries(), exp)
pr1 = PairedRegion(3,10,2)
pr2 = PairedRegion(5,10,3)
prs = PairedRegions([pr1, pr2])
self.assertRaises(ValueError, prs.invertedEnumeratedBoundaries)
def test_merge(self):
"""PairedRegions merge: different, duplicates, empty"""
pr1 = PairedRegion(3,10,2, Id='A')
pr2 = PairedRegion(11,20,3, Id='B')
pr3 = PairedRegion(15,25,1, Id='C')
prs1 = PairedRegions([pr1, pr2])
prs2 = PairedRegions([pr1, pr3])
prs3 = PairedRegions()
exp = PairedRegions([pr1,pr2,pr3])
self.assertEqual(prs1.merge(prs2), exp)
self.assertEqual(prs2.merge(prs1), exp)
self.assertEqual(prs1.merge(prs3), prs1)
self.assertEqual(prs2.merge(prs3), prs2)
def test_conflicting_no_ids(self):
"""PairedRegions conflicting: raises error on duplicate IDs
"""
pr1 = PairedRegion(1,10,2)
pr2 = PairedRegion(11,20,2)
prs = PairedRegions([pr1, pr2])
self.assertRaises(ValueError, prs.conflicting) #conflicting IDs
def test_conflicting(self):
"""PairedRegions conflicting: works when IDs are set and unique
"""
pr1 = PairedRegion(3,10,2, Id='A')
pr2 = PairedRegion(11,20,3, Id='B')
pr3 = PairedRegion(15,25,1, Id='C')
prs = PairedRegions([pr1,pr2,pr3])
self.assertEqual(prs.conflicting(), PairedRegions([pr2,pr3]))
prs = PairedRegions()
self.assertEqual(prs.conflicting(), PairedRegions())
def test_non_conflicting_no_ids(self):
"""PairedRegions nonConflicting: raises error on duplicate IDs
"""
pr1 = PairedRegion(1,10,2)
pr2 = PairedRegion(11,20,2)
prs = PairedRegions([pr1, pr2])
self.assertRaises(ValueError, prs.nonConflicting) #conflicting IDs
def test_non_conflicting(self):
"""PairedRegions nonConflicting: works when IDs are set and unique
"""
pr1 = PairedRegion(3,10,2, Id='A')
pr2 = PairedRegion(11,20,3, Id='B')
pr3 = PairedRegion(15,25,1, Id='C')
prs = PairedRegions([pr1,pr2,pr3])
self.assertEqual(prs.nonConflicting(), PairedRegions([pr1]))
prs = PairedRegions()
self.assertEqual(prs.conflicting(), PairedRegions())
def test_conflictCliques(self):
"""PairedRegions conflictCliques: should work when IDs are unique"""
pr1 = PairedRegion(3,10,2, Id='A')
pr2 = PairedRegion(11,20,3, Id='B')
pr3 = PairedRegion(15,25,1, Id='C')
pr4 = PairedRegion(30,40,2, Id='D')
pr5 = PairedRegion(28,35,1, Id='E')
prs = PairedRegions([pr1,pr2,pr3,pr4, pr5])
obs = prs.conflictCliques()
exp = [PairedRegions([pr2,pr3]),PairedRegions([pr5,pr4])]
for i in obs:
self.failUnless(i in exp)
self.assertEqual(len(obs), len(exp))
prs = PairedRegions()
self.assertEqual(prs.conflictCliques(), [])
def test_PairedRegionsFromPairs(self):
"""PairedRegionsFromPairs: should work on valid input"""
p = Pairs([(1,10),(2,9),(12,20),(13,19),(14,18)])
prs = PairedRegionsFromPairs(p)
self.assertEqual(len(prs), 2)
self.assertEqual(prs[0].Id, 0)
self.assertEqual(prs[0].Pairs, [(1,10),(2,9)])
self.assertEqual(prs[0].Start, 1)
self.assertEqual(prs[0].End, 10)
self.assertEqual(PairedRegionsFromPairs(Pairs()), PairedRegions())
def test_PairedRegionsFromPairs_conflict(self):
"""PairedRegionsFromPairs: should raise error on overlapping pairs"""
p = Pairs([(2,20),(5,10),(10,15)])
self.assertRaises(ValueError, PairedRegionsFromPairs, p)
class ConflictMatrixTests(TestCase):
"""Tests for ConflictMatrix class"""
def test_conflict_matrix_from_pairs(self):
"""ConflixtMatrix __init__: Pairs as input, w/wo conflict """
f = ConflictMatrix
# conflict free
d = [(1,10),(2,9),(12,20),(13,19),(14,18)]
exp = Dict2D({0:{0:False,1:False},1:{0:False,1:False}})
self.assertEqual(f(d).Matrix, exp)
self.failIf(not isinstance(f(d).Matrix, Dict2D))
# 1 conflict
d = [(1,10),(2,9),(12,20),(13,19),(14,18),(15,30),(16,29)]
exp = Dict2D({0:{0:False,1:False,2:False},\
1:{0:False,1:False,2:True},\
2:{0:False,1:True,2:False}})
self.assertEqual(f(d).Matrix, exp)
# 1 conflict
d = Pairs([(1,10),(2,9),(12,20),(13,19),(14,18),(15,30),(16,29)])
exp = Dict2D({0:{0:False,1:False,2:False},\
1:{0:False,1:False,2:True},\
2:{0:False,1:True,2:False}})
m = f(d).Matrix
self.assertEqual(m, exp)
self.assertEqual(m.RowOrder, [0,1,2])
self.assertEqual(m.ColOrder, [0,1,2])
d = [] # empty input
exp = Dict2D()
self.assertEqual(f(d).Matrix, exp)
def test_ConflictMatrix_Pairs_overlap(self):
"""ConflictMatrix __init__: raises error on overlapping pairs"""
p = Pairs([(1,10),(2,9),(3,9),(12,20)])
self.assertRaises(ValueError, ConflictMatrix, p)
def test_conflict_matrix_from_PairedRegions(self):
"""ConflictMatrix __init__: PairedRegions as input, w/wo conflict
"""
f = ConflictMatrix
# conflict free
pr1 = PairedRegion(1,10,2, Id=0)
pr2 = PairedRegion(12,20,3, Id=1)
prs = PairedRegions([pr1,pr2])
exp = Dict2D({0:{0:False,1:False},1:{0:False,1:False}})
self.assertEqual(f(prs).Matrix, exp)
self.failIf(not isinstance(f(prs).Matrix, Dict2D))
pr1 = PairedRegion(1,10,2, Id=0)
pr2 = PairedRegion(12,20,3, Id=1)
pr3 = PairedRegion(15,30,2, Id=2)
prs = PairedRegions([pr1,pr2, pr3])
# 1 conflict
exp = Dict2D({0:{0:False,1:False,2:False},\
1:{0:False,1:False,2:True},\
2:{0:False,1:True,2:False}})
self.assertEqual(f(prs).Matrix, exp)
# 1 conflict
pr1 = PairedRegion(1,10,2, Id=4)
pr2 = PairedRegion(12,20,3, Id=1)
pr3 = PairedRegion(15,30,2, Id=9)
prs = PairedRegions([pr1,pr2, pr3])
exp = Dict2D({1:{4:False,1:False,9:True},\
4:{1:False,4:False,9:False},\
9:{1:True,4:False,9:False}})
m = f(prs).Matrix
self.assertEqual(m, exp)
self.assertEqual(m.RowOrder, [1,4,9])
self.assertEqual(m.ColOrder, [1,4,9])
prs = PairedRegions()
exp = Dict2D()
self.assertEqual(f(prs).Matrix, exp)
# input some weird data. Other errors might occur.
self.assertRaises(ValueError, f, 'ABC')
self.assertRaises(ValueError, f, [('a','b'),('c','d')])
def test_ConflictMatrix_PairedRegions_overlap(self):
"""ConflictMatrix __init__: raises error on overlapping PairedRegions
"""
pr1 = PairedRegion(1,10,2, Id='A')
pr2 = PairedRegion(8,20,2, Id='B')
prs = PairedRegions([pr1, pr2])
self.assertRaises(ValueError, ConflictMatrix, prs)
def test_conflictsOf(self):
"""ConflictMatrix conflictsOf: with/without conflicts"""
p = Pairs([(1,10),(5,15),(20,30),(25,35),(24,32),(0,80)])
cm = ConflictMatrix(p)
self.assertEqual(cm.conflictsOf(0), [])
self.assertEqual(cm.conflictsOf(1), [2])
self.assertEqual(cm.conflictsOf(2), [1])
self.assertEqual(cm.conflictsOf(3), [4,5])
p = Pairs([(1,10),(11,20)])
cm = ConflictMatrix(p)
self.assertEqual(cm.conflictsOf(0), [])
self.assertEqual(cm.conflictsOf(1), [])
self.assertRaises(KeyError, cm.conflictsOf, 2)
def test_conflicting(self):
"""ConflictMatrix conflicting: full and empty Pairs"""
p = Pairs([(1,10),(5,15),(20,30),(25,35),(24,32),(0,80)])
cm = ConflictMatrix(p)
obs = cm.conflicting()
exp = [1,2,3,4,5]
self.assertEqual(obs, exp)
self.assertEqual(ConflictMatrix(Pairs()).conflicting(), [])
def test_nonConflicting(self):
"""ConflictMatrix nonConflicting: full and empty Pairs"""
p = Pairs([(1,10),(5,15),(20,30),(25,35),(24,32),(0,80)])
cm = ConflictMatrix(p)
obs = cm.nonConflicting()
exp = [0]
self.assertEqual(obs, exp)
self.assertEqual(ConflictMatrix(Pairs()).nonConflicting(), [])
def test_conflictCliques(self):
"""ConflictMatrix conflictCliques: full and empty Pairs"""
p = Pairs([(1,10),(5,15),(20,30),(25,35),(24,32),(0,80)])
cm = ConflictMatrix(p)
obs = cm.conflictCliques()
exp = [[1,2],[3,4,5]]
self.assertEqual(obs, exp)
self.assertEqual(ConflictMatrix(Pairs()).conflictCliques(), [])
class DPTests(TestCase):
"""Tests for opt_all and related functions"""
def test_num_bps(self):
"""num_bps: should return length of paired region"""
f = num_bps
pr1 = PairedRegion(0,10,3)
self.assertEqual(f(pr1), 3)
def test_hydrogen_bonds(self):
"""hydrogen_bonds: score GC, AU, and GU base pairs"""
f = hydrogen_bonds('UACGAAAUGCGUG')
pr1 = PairedRegion(0,12,5)
self.assertEqual(f(pr1),10)
f = hydrogen_bonds('UACGAAA') # sequence too short
pr1 = PairedRegion(0,12,5)
self.assertRaises(IndexError, f, pr1)
def test_contains_true(self):
"""contains_true: should return True if True in input"""
f = contains_true
self.assertEqual(f([True]), True)
self.assertEqual(f([True, False]), True)
self.assertEqual(f([1, 0]), True)
self.assertEqual(f([1]), True)
self.assertEqual(f([False]), False)
self.assertEqual(f([3]), False)
self.assertEqual(f(["a","b","c"]), False)
self.assertEqual(f("abc"), False)
def test_empty_matrix(self):
"""empty_matrix: valid input and error"""
f = empty_matrix
p = PairedRegions()
exp = [[[p],[p]], [[p],[p]]]
self.assertEqual(f(2), exp)
self.assertEqual(f(1), [[[p]]])
self.assertRaises(ValueError, f, 0)
def test_pick_multi_best_max(self):
"""pick_multi_best: max, full and empty list"""
pr1 = PairedRegion(2,10,2, Id='A')
pr2 = PairedRegion(4,15,3, Id='B')
pr3 = PairedRegion(20,40,5, Id='C')
pr4 = PairedRegion(22,30,3, Id='D')
for i in [pr1,pr2,pr3,pr4]:
i.score(num_bps)
prs1 = PairedRegions([pr1, pr2])
prs2 = PairedRegions([pr3])
prs3 = PairedRegions([pr4])
self.assertEqualItems(pick_multi_best([prs1, prs2, prs3]), [prs1, prs2])
self.assertEqual(pick_multi_best([]), [PairedRegions()])
def test_pick_multi_best_min(self):
"""pick_multi_best: min, full and empty list"""
f = lambda x: -1
pr1 = PairedRegion(2,10,2)
pr2 = PairedRegion(4,15,3)
pr3 = PairedRegion(20,40,5)
pr4 = PairedRegion(22,30,3)
for i in [pr1,pr2,pr3,pr4]:
i.score(f)
prs1 = PairedRegions([pr1, pr2])
prs2 = PairedRegions([pr3])
prs3 = PairedRegions([pr4])
self.assertEqual(pick_multi_best([prs1, prs2, prs3], goal='min'),\
[prs1])
self.assertEqual(pick_multi_best([], goal='min'), [PairedRegions()])
def test_dp_matrix_multi_toy(self):
"""dp_matrix_multi: test on initial toy example"""
pr0 = PairedRegion(0, 70, 2, Id='C')
pr1 = PairedRegion(10, 30, 4, Id='A')
pr2 = PairedRegion(20, 50, 3, Id='B')
pr3 = PairedRegion(40, 90, 2, Id='E')
pr4 = PairedRegion(60, 80, 3, Id='D')
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4])
obs = dp_matrix_multi(prs)
self.assertEqual(obs[0][0], [PairedRegions()])
self.assertEqual(obs[0][3], [PairedRegions([pr1])])
self.assertEqual(obs[2][5], [PairedRegions([pr2])])
self.assertEqual(obs[4][9], [PairedRegions([pr3,pr4])])
self.assertEqual(obs[2][9], [PairedRegions([pr2,pr4])])
self.assertEqual(obs[1][8], [PairedRegions([pr1,pr4])])
self.assertEqual(obs[1][9], [PairedRegions([pr1,pr3,pr4])])
self.assertEqual(obs[0][9], [PairedRegions([pr1,pr3,pr4])])
def test_dp_matrix_multi_lsu(self):
"""dp_matrix_multi: test on LSU rRNA domain I case"""
pr0 = PairedRegion(56, 69, 3, Id=0)
pr1 = PairedRegion(60, 92, 1, Id=1)
pr2 = PairedRegion(62, 89, 3, Id=2)
pr3 = PairedRegion(75, 109, 6, Id=3)
pr4 = PairedRegion(84, 96, 3, Id=4)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4])
obs = dp_matrix_multi(prs)
self.assertEqual(obs[0][0], [PairedRegions()])
self.assertEqual(obs[0][5], [PairedRegions([pr0])])
self.assertEqual(obs[1][6], [PairedRegions([pr2])])
self.assertEqual(obs[1][7], [PairedRegions([pr1,pr2])])
self.assertEqualItems(obs[2][8],\
[PairedRegions([pr2]),PairedRegions([pr4])])
self.assertEqual(obs[1][9], [PairedRegions([pr3,pr4])])
self.assertEqual(obs[0][9], [PairedRegions([pr0,pr3,pr4])])
def test_dp_matrix_multi_artificial(self):
"""dp_matrix_multi: test on artificial structure"""
pr0 = PairedRegion(0, 77, 2, Id=0)
pr1 = PairedRegion(7, 75, 5, Id=1)
pr2 = PairedRegion(13, 83, 3, Id=2)
pr3 = PairedRegion(18, 41, 5, Id=3)
pr4 = PairedRegion(23, 53, 10, Id=4)
pr5 = PairedRegion(33, 70, 3, Id=5)
pr6 = PairedRegion(59, 93, 9, Id=6)
pr7 = PairedRegion(78, 96, 3, Id=7)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5, pr6, pr7])
obs = dp_matrix_multi(prs)
self.assertEqual(obs[0][0], [PairedRegions()])
self.assertEqual(obs[0][6], [PairedRegions([pr3])])
self.assertEqual(obs[0][7], [PairedRegions([pr4])])
self.assertEqual(obs[9][15], [PairedRegions([pr7])])
self.assertEqual(obs[1][10], [PairedRegions([pr1,pr4])])
self.assertEqual(obs[0][11], [PairedRegions([pr0,pr1,pr4])])
self.assertEqual(obs[3][14], [PairedRegions([pr4, pr6])])
self.assertEqual(obs[3][14], [PairedRegions([pr4, pr6])])
self.assertEqual(obs[0][13], [PairedRegions([pr0, pr1, pr4])])
self.assertEqual(obs[0][14], [PairedRegions([pr4, pr6])])
self.assertEqual(obs[1][15], [PairedRegions([pr4, pr6])])
self.assertEqual(obs[0][15], [PairedRegions([pr0, pr1, pr4, pr7])])
def test_pick_multi_best_saturated(self):
"""pick_multi_best: should only include saturated solutions"""
pr1 = PairedRegion(2,10,2, Id='A')
pr1.Score = 2
pr2 = PairedRegion(15,25,2, Id='B')
pr2.Score = 2
pr3 = PairedRegion(4,22,4, Id='C')
pr3.Score = 0
prs1 = PairedRegions([pr1])
prs2 = PairedRegions([pr2])
prs3 = PairedRegions([pr1, pr3])
self.assertEqualItems(pick_multi_best([prs1, prs2, prs3]),\
[prs2, prs3])
self.assertEqual(pick_multi_best([]), [PairedRegions()])
def test_matrix_solutions(self):
"""matrix_solutions: should return contents of top-right cell"""
pr0 = PairedRegion(56, 69, 3, Id=0)
pr1 = PairedRegion(60, 92, 1, Id=1)
pr2 = PairedRegion(62, 89, 3, Id=2)
pr3 = PairedRegion(75, 109, 6, Id=3)
pr4 = PairedRegion(84, 96, 3, Id=4)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4])
obs = matrix_solutions(prs)
self.assertEqual(obs, [PairedRegions([pr0,pr3,pr4])])
# error, size should be at least 1
prs = PairedRegions()
self.assertRaises(ValueError, matrix_solutions, prs)
pr = PairedRegion(2,20, 5, Id='A')
prs = PairedRegions([pr])
obs = matrix_solutions(prs)
self.assertEqual(obs, [prs])
def test_opt_all_nested(self):
"""opt_all: should return input when already nested"""
p = Pairs([(1,10),(2,9),(20,30),(22,29)])
obs = opt_all(p)
self.assertEqual(len(obs),1)
self.assertEqual(obs[0], p)
p = Pairs()
self.assertEqual(opt_all(p), [[]])
def test_opt_all_overlap(self):
"""opt_all: should raise error on overlapping pairs"""
p = Pairs([(1,10),(2,9),(9,30),(22,29),(1,None)])
self.assertRaises(ValueError, opt_all, p)
def test_opt_all_knot(self):
"""opt_all: single/multiple solution(s)"""
p = Pairs([(1,10),(2,9),(3,15),(4,14),(11,20),(12,19),(25,30)])
obs = opt_all(p)
exp = Pairs([(1,10),(2,9),(11,20),(12,19),(25,30)])
exp_rem = [(3,15),(4,14)]
self.assertEqual(len(obs), 1)
self.assertEqual(obs[0], exp)
self.assertEqual(opt_all(p, return_removed=True)[0][1],\
exp_rem)
p = Pairs([(1,10),(2,9),(4,14),(3,15)])
obs = opt_all(p)
self.assertEqual(len(obs), 2)
self.assertEqualItems(obs, [Pairs([(1,10),(2,9)]),\
Pairs([(3,15),(4,14)])])
exp_rem = [(Pairs([(1,10),(2,9)]),Pairs([(3,15),(4,14)])),\
(Pairs([(3,15),(4,14)]),Pairs([(1,10),(2,9)]))]
self.assertEqualItems(opt_all(p, return_removed=True),\
exp_rem)
def test_opt_all_some_non_conflicting(self):
"""opt_all: some conflicting, other not"""
p = Pairs([(30,40),(10,20),(12,17),(13,None),(17,12),(35,45),(36,44)])
exp = Pairs([(10,20),(12,17),(35,45),(36,44)])
exp_rem = [(30,40)]
self.assertEqual(opt_all(p, return_removed=True),\
[(exp,exp_rem)])
def test_opt_all_scoring1(self):
"""opt_all: one optimal in bps, both optimal in energy"""
p = Pairs([(1,10),(2,9),(4,15),(5,14),(6,13)])
obs_bps = opt_all(p, goal='max', scoring_function=num_bps)
obs_energy = opt_all(p, goal='max',\
scoring_function=hydrogen_bonds('CCCAAAUGGGGUCGUUC'))
exp_bps = [[(4,15),(5,14),(6,13)]]
exp_energy = [[(1,10),(2,9)],[(4,15),(5,14),(6,13)]]
self.assertEqualItems(obs_bps, exp_bps)
self.assertEqualItems(obs_energy, exp_energy)
def test_opt_all_scoring2(self):
"""opt_all: both optimal in bps, one optimal in energy"""
p = Pairs([(0,9),(1,8),(2,7),(3,13),(4,12),(5,11)])
obs_bps = opt_all(p, goal='max', scoring_function=num_bps)
obs_energy = opt_all(p, goal='max',\
scoring_function=hydrogen_bonds('CCCAAAAGGGUUUU'))
exp_bps = [[(0,9),(1,8),(2,7)],[(3,13),(4,12),(5,11)]]
exp_energy = [[(0,9),(1,8),(2,7)]]
self.assertEqualItems(obs_bps, exp_bps)
self.assertEqualItems(obs_energy, exp_energy)
def test_opt_all_scoring3(self):
"""opt_all: one optimal in bps, the other optimal in energy"""
p = Pairs([(0,11),(1,10),(2,9),(4,15),(5,14),(6,13),(7,12)])
obs_bps = opt_all(p, goal='max', scoring_function=num_bps)
obs_energy = opt_all(p, goal='max',\
scoring_function=hydrogen_bonds('CCCCAAAAGGGGUUUU'))
exp_bps = [[(4,15),(5,14),(6,13),(7,12)]]
exp_energy = [[(0,11),(1,10),(2,9)]]
self.assertEqualItems(obs_bps, exp_bps)
self.assertEqualItems(obs_energy, exp_energy)
def test_opt_single_random(self):
"""opt_single_random: should return single solution"""
p = Pairs ([(10,20),(11,19),(15,25),(16,24)])
exp1, exp_rem1 = [(10,20),(11,19)], [(15,25),(16,24)]
exp2, exp_rem2 = [(15,25),(16,24)], [(10,20),(11,19)]
obs = opt_single_random(p)
self.failUnless(obs == exp1 or obs == exp2)
obs = opt_single_random(p, return_removed=True)
self.failUnless(obs == (exp1, exp_rem1) or obs == (exp2, exp_rem2))
def test_opt_single_property(self):
"""opt_single_property: three properties"""
# one solution single region, other solution two regions
p = Pairs ([(10,20),(25,35),(26,34),(27,33),\
(12,31),(13,30),(14,29),(15,28)])
exp = [(12,31),(13,30),(14,29),(15,28)]
exp_rem = [(10,20),(25,35),(26,34),(27,33)]
self.assertEqual(opt_single_property(p), exp)
self.assertEqual(opt_single_property(p, return_removed=True),\
(exp,exp_rem))
# both two blocks, one shorter average range
p = Pairs ([(10,20),(22,40),(23,39),(24,38),\
(17,26),(18,25),(36,43),(37,42)])
exp = [(17,26),(18,25),(36,43),(37,42)]
exp_rem = [(10,20),(22,40),(23,39),(24,38)]
self.assertEqual(opt_single_property(p), exp)
self.assertEqual(opt_single_property(p, return_removed=True),\
(exp,exp_rem))
# both single block over same range, pick lowest start
p = Pairs([(10,20),(15,25)])
exp = [(10,20)]
exp_rem = [(15,25)]
self.assertEqual(opt_single_property(p), exp)
self.assertEqual(opt_single_property(p, return_removed=True),\
(exp,exp_rem))
class EliminationMethodsTests(TestCase):
"""Tests for conflict_elimination and related functions"""
def test_find_max_conflicts(self):
"""find_max_conflicts: simple case"""
f = find_max_conflicts
pr0 = PairedRegion(0, 77, 2, Id=0)
pr1 = PairedRegion(7, 75, 5, Id=1)
pr2 = PairedRegion(13, 83, 3, Id=2)
pr3 = PairedRegion(18, 41, 5, Id=3)
pr4 = PairedRegion(23, 53, 10, Id=4)
pr5 = PairedRegion(33, 70, 3, Id=5)
pr6 = PairedRegion(59, 93, 9, Id=6)
pr7 = PairedRegion(78, 96, 3, Id=7)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5, pr6, pr7])
id_to_pr = prs.byId()
cm = ConflictMatrix(prs)
conf = cm.conflicting()
self.assertEqual(f(conf, cm, prs.byId()), 6)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5, pr7])
id_to_pr = prs.byId()
cm = ConflictMatrix(prs)
conf = cm.conflicting()
self.assertEqual(f(conf, cm, prs.byId()), 2)
prs = PairedRegions([pr0, pr1, pr3, pr4, pr5, pr7])
id_to_pr = prs.byId()
cm = ConflictMatrix(prs)
conf = cm.conflicting()
self.assertEqual(f(conf, cm, prs.byId()), 5)
def test_find_max_conflicts_on_start(self):
"""find_max_conflicts: in case of equal conflicts and gain"""
f = find_max_conflicts
pr0 = PairedRegion(10, 20, 2, Id=0)
pr1 = PairedRegion(15, 25, 2, Id=1)
prs = PairedRegions([pr0, pr1])
id_to_pr = prs.byId()
cm = ConflictMatrix(prs)
conf = cm.conflicting()
self.assertEqual(f(conf, cm, prs.byId()), 1)
def test_find_min_gain(self):
"""find_min_gain: differentiate on gain only"""
f = find_min_gain
pr0 = PairedRegion(0, 77, 2, Id=0)
pr1 = PairedRegion(7, 75, 5, Id=1)
pr2 = PairedRegion(13, 83, 3, Id=2)
pr3 = PairedRegion(18, 41, 5, Id=3)
pr4 = PairedRegion(23, 53, 10, Id=4)
pr5 = PairedRegion(33, 70, 3, Id=5)
pr6 = PairedRegion(59, 93, 9, Id=6)
pr7 = PairedRegion(78, 96, 3, Id=7)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5, pr6, pr7])
id_to_pr = prs.byId()
cm = ConflictMatrix(prs)
conf = cm.conflicting()
self.assertEqual(f(conf, cm, prs.byId()), 5)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr6, pr7])
id_to_pr = prs.byId()
cm = ConflictMatrix(prs)
conf = cm.conflicting()
self.assertEqual(f(conf, cm, prs.byId()), 2)
def test_find_min_gain_conf(self):
"""find_min_gain: in case of equal gain, differentiate on conflicts"""
f = find_min_gain
pr0 = PairedRegion(10,30,3, Id=0)
pr1 = PairedRegion(1,20,6, Id=1)
pr2 = PairedRegion(22,40,2, Id=2)
pr3 = PairedRegion(50,80,3, Id=3)
pr4 = PairedRegion(60,90,8, Id=4)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4])
id_to_pr = prs.byId()
cm = ConflictMatrix(prs)
conf = cm.conflicting()
self.assertEqual(f(conf, cm, prs.byId()), 0)
def test_find_min_gain_start(self):
"""find_min_gain: in case of equal gain and number of conflicts"""
f = find_min_gain
pr0 = PairedRegion(10,30,3, Id=0)
pr1 = PairedRegion(1,20,6, Id=1)
pr2 = PairedRegion(22,40,2, Id=2)
pr3 = PairedRegion(50,80,3, Id=3)
pr4 = PairedRegion(60,90,7, Id=4)
pr5 = PairedRegion(45,55,1, Id=5)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5])
id_to_pr = prs.byId()
cm = ConflictMatrix(prs)
conf = cm.conflicting()
self.assertEqual(f(conf, cm, prs.byId()), 3)
def test_add_back_non_conflicting(self):
"""add_back_non_conflicting: should add all non-confl regions"""
f = add_back_non_conflicting
pr0 = PairedRegion(10,20,3, Id=0)
pr1 = PairedRegion(30,40,2, Id=1)
pr2 = PairedRegion(50,60,2, Id=2)
pr3 = PairedRegion(45,55,3, Id=3) # confl with pr1 and pr2
pr4 = PairedRegion(0,90,7, Id=4) # not confl with 1,2,3
pr5 = PairedRegion(32,38,2, Id=5) # not confl with 1,2,3
prs = PairedRegions([pr0, pr1, pr2])
removed = {3: pr3, 4: pr4, 5: pr5}
exp_prs = PairedRegions([pr0, pr1, pr2, pr4, pr5])
exp_rem = {3: pr3}
self.assertEqual(f(prs, removed), (exp_prs, exp_rem))
def test_add_back_non_conflicting_order(self):
"""add_back_non_conflicting: should add 5' side first"""
f = add_back_non_conflicting
pr0 = PairedRegion(10,20,3, Id=0)
pr1 = PairedRegion(30,40,2, Id=1)
pr2 = PairedRegion(50,60,2, Id=2)
pr3 = PairedRegion(45,55,3, Id=3) # confl with pr1 and pr2
pr4 = PairedRegion(0,90,7, Id=4) # not confl with 1,2,3
pr5 = PairedRegion(80,95,2, Id=5) # not confl with 1,2,3
prs = PairedRegions([pr0, pr1, pr2])
removed = {3: pr3, 4: pr4, 5: pr5}
exp_prs = PairedRegions([pr0, pr1, pr2, pr4 ])
exp_rem = {3: pr3, 5: pr5}
self.assertEqual(f(prs, removed), (exp_prs, exp_rem))
def test_elim_most_conflict(self):
"""conflict_elimination: find_max_conflicts, simple case"""
f = conflict_elimination
func = find_max_conflicts
pr0 = PairedRegion(0, 77, 2, Id=0)
pr1 = PairedRegion(7, 75, 5, Id=1)
pr2 = PairedRegion(13, 83, 3, Id=2)
pr3 = PairedRegion(18, 41, 5, Id=3)
pr4 = PairedRegion(23, 53, 10, Id=4)
pr5 = PairedRegion(33, 70, 3, Id=5)
pr6 = PairedRegion(59, 93, 9, Id=6)
pr7 = PairedRegion(78, 96, 3, Id=7)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5, pr6, pr7])
pairs = prs.toPairs()
exp = PairedRegions([pr0, pr1, pr4, pr7]).toPairs()
exp_rem = PairedRegions([pr2, pr3, pr5, pr6]).toPairs()
self.assertEqual(f(pairs, func), exp)
self.assertEqual(f(pairs, func, return_removed=True), (exp, exp_rem))
def test_elim_mc_circular(self):
"""conflict_elimination: find_max_conflicts, circular removal"""
# simply remove in order of most conflicts, don't add back
prfp = PairedRegionFromPairs
f = conflict_elimination
func = find_max_conflicts
pr0 = prfp([(13, 65), (14, 64)], Id=0)
pr1 = prfp([(15, 102), (16, 101), (17, 100), (18, 99), (19, 98)], Id=1)
pr2 = prfp([(22, 72), (23, 71), (24, 70), (25, 69),\
(26, 68), (27, 67), (28, 66)], Id=2)
pr3 = prfp([(31, 147), (32, 146), (33, 145), (34, 144), (35, 143),\
(36, 142), (37, 141), (38, 140), (39, 139)], Id=3)
pr4 = prfp([(42, 129), (43, 128), (44, 127)], Id=4)
pr5 = prfp([(46, 149), (47, 148)], Id=5)
pr6 = prfp([(49, 92), (50, 91), (51, 90), (52, 89), (53, 88)], Id=6)
pr7 = prfp([(75, 138), (76, 137), (77, 136), (78, 135)], Id=7)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5, pr6, pr7])
exp = PairedRegions([pr3, pr6]).toPairs()
exp_rem = PairedRegions([pr0, pr1, pr2, pr4, pr5, pr7]).toPairs()
self.assertEqual(f(prs.toPairs(), func, add_back=False,\
return_removed=True), (exp, exp_rem))
# add back circular removals
exp = PairedRegions([pr3, pr4, pr6]).toPairs()
exp_rem = PairedRegions([pr0, pr1, pr2, pr5, pr7]).toPairs()
self.assertEqual(f(prs.toPairs(), func, add_back=True,\
return_removed=True), (exp, exp_rem))
def test_elim_min_gain(self):
"""conflict_elimination: find_min_gain, simple case"""
f = conflict_elimination
func = find_min_gain
pr0 = PairedRegion(0, 77, 2, Id=0)
pr1 = PairedRegion(7, 75, 5, Id=1)
pr2 = PairedRegion(13, 83, 3, Id=2)
pr3 = PairedRegion(18, 41, 5, Id=3)
pr4 = PairedRegion(23, 53, 10, Id=4)
pr5 = PairedRegion(33, 70, 3, Id=5)
pr6 = PairedRegion(59, 93, 9, Id=6)
pr7 = PairedRegion(78, 96, 3, Id=7)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5, pr6, pr7])
pairs = prs.toPairs()
exp = PairedRegions([pr4, pr6]).toPairs()
exp_rem = PairedRegions([pr0, pr1, pr2, pr3, pr5, pr7]).toPairs()
self.assertEqual(f(pairs, func), exp)
self.assertEqual(f(pairs, func, return_removed=True), (exp, exp_rem))
def test_elim_min_gain_circular(self):
"""conflict_elimination: find_min_gain, circular removal"""
# simply remove in order of most conflicts, don't add back
prfp = PairedRegionFromPairs
f = conflict_elimination
func = find_min_gain
pr0 = prfp([(5, 170), (6, 169), (7, 168), (8, 167), (9, 166),\
(10, 165)], Id=0)
pr1 = prfp([(25, 62), (26, 61)], Id=1)
pr2 = prfp([(29, 46), (30, 45), (31, 44)], Id=2)
pr3 = prfp([(48, 124), (49, 123)], Id=3)
pr4 = prfp([(67, 183), (68, 182), (69, 181), (70, 180), (71, 179),\
(72, 178), (73, 177), (74, 176), (75, 175), (76, 174)], Id=4)
pr5 = prfp([(82, 172), (83, 171)], Id=5)
pr6 = prfp([(117, 135), (118, 134), (119, 133)], Id=6)
pr7 = prfp([(151, 199), (152, 198), (153, 197), (154, 196),\
(155, 195), (156, 194), (157, 193), (158, 192), (159, 191),\
(160, 190)], Id=7)
prs = PairedRegions([pr0, pr1, pr2, pr3, pr4, pr5, pr6, pr7])
exp = PairedRegions([pr1, pr2, pr4, pr6]).toPairs()
exp_rem = PairedRegions([pr0, pr3, pr5, pr7]).toPairs()
self.assertEqual(f(prs.toPairs(), func, add_back=False,\
return_removed=True), (exp, exp_rem))
# add back circular removals
exp = PairedRegions([pr1, pr2, pr4, pr5, pr6]).toPairs()
exp_rem = PairedRegions([pr0, pr3, pr7]).toPairs()
self.assertEqual(f(prs.toPairs(), func, add_back=True,\
return_removed=True), (exp, exp_rem))
class IncrementalMethodsTests(TestCase):
"""Tests for incremental pseudoknot-removal methods"""
def test_inc_order_forward(self):
"""nested_in_order: starting at 5' end"""
f = inc_order
p = Pairs([(1,10),(2,9),(3,15),(4,14),(11,20),(12,19),(25,30)])
exp = Pairs([(1,10),(2,9),(11,20),(12,19),(25,30)])
exp_rem = Pairs([(3,15),(4,14)])
self.assertEqual(f(p,reversed=False), exp)
self.assertEqual(f(p,return_removed=True), (exp, exp_rem))
p = Pairs([(1,20),(2,30),(3,29),(4,28),(5,27),(7,24)])
exp = Pairs([(1,20)])
exp_rem = Pairs([(2,30),(3,29),(4,28),(5,27),(7,24)])
self.assertEqual(f(p,reversed=False), exp)
self.assertEqual(f(p,return_removed=True), (exp, exp_rem))
self.assertEqual(f([]), [])
p = [(1,10),(3,13)] # input as list of tuples
exp = Pairs([(1,10)])
self.assertEqual(f(p), exp)
p = [(1,10),(4,7),(2,9),(5,None)] # pseudoknot-free
exp = [(1,10),(2,9),(4,7)]
self.assertEqual(f(p), exp)
p = [(1,10),(2,10)] #conflict
self.assertRaises(ValueError, f, p)
def test_inc_order_reversed(self):
"""nested_in_order: starting at 3' end"""
f = inc_order
p = Pairs([(1,10),(2,9),(3,15),(4,14),(24,31),(25,30)])
exp = Pairs([(3,15),(4,14),(24,31),(25,30)])
exp_rem = Pairs([(1,10),(2,9)])
self.assertEqual(f(p,reversed=True), exp)
self.assertEqual(f(p, reversed=True, return_removed=True),\
(exp, exp_rem))
p = Pairs([(1,20),(2,30),(3,29),(4,28),(5,27),(7,24)])
exp = Pairs([(2,30),(3,29),(4,28),(5,27),(7,24)])
exp_rem = Pairs([(1,20)])
self.assertEqual(f(p,reversed=True), exp)
self.assertEqual(f(p, reversed=True, return_removed=True),\
(exp, exp_rem))
self.assertEqual(f([], reversed=True), [])
p = [(1,10),(3,13)] # input as list of tuples
exp = Pairs([(3,13)])
self.assertEqual(f(p, reversed=True), exp)
p = [(1,10),(4,7),(2,9),(5,None)] # pseudoknot-free
exp = [(1,10),(2,9),(4,7)]
self.assertEqual(f(p), exp)
p = [(1,10),(2,10)] #conflict
self.assertRaises(ValueError, f, p)
def test_inc_length(self):
"""inc_length: should handle standard input
"""
f = inc_length
# All blocks in conflict, start empty, add first
p = Pairs([(1,10),(2,9),(3,8),(5,13),(6,12),(7,11)])
exp = Pairs([(1,10),(2,9),(3,8)])
self.assertEqual(f(p), exp)
# Start with length 3 and 2, add 1 block
p = Pairs([(1,10),(2,9),(3,8),(20,30),(21,29),(25,40),(32,38)])
exp = Pairs([(1,10),(2,9),(3,8),(20,30),(21,29),(32,38)])
self.assertEqual(f(p), exp)
p = Pairs([(1,10),(2,9),(3,8),(12,20),(13,19),(15,23),(16,22)])
exp_5 = Pairs([(1,10),(2,9),(3,8),(12,20),(13,19)])
exp_3 = Pairs([(1,10),(2,9),(3,8),(15,23),(16,22)])
self.assertEqual(f(p), exp_5)
self.assertEqual(f(p, reversed=True), exp_3)
self.assertEqual(f(p, return_removed=True),(exp_5,[(15,23),(16,22)]))
p = [(1,10),(4,7),(2,9),(5,None)] # pseudoknot-free
exp = [(1,10),(2,9),(4,7)]
self.assertEqual(f(p), exp)
p = [(1,10),(2,10)] #conflict
self.assertRaises(ValueError, f, p)
def test_inc_length_rev(self):
"""inc_length: should prefer 3' side when reversed is True
"""
f = inc_length
p = Pairs([(1,10),(2,9),(5,20),(6,19)])
self.assertEqual(f(p), [(1,10),(2,9)])
self.assertEqual(f(p, reversed=True), [(5,20),(6,19)])
def test_inc_range(self):
"""inc_range: should handle normal input
"""
f = inc_range
p = [(1,5),(4,20),(15,23),(16,22)]
exp = [(1,5),(15,23),(16,22)]
self.assertEqual(f(p), exp)
self.assertEqual(f(p, return_removed=True), (exp, [(4,20)]))
p = [(1,11),(5,15)] # same range
self.assertEqual(f(p), [(1,11)]) # 5' wins
self.assertEqual(f(p, reversed=True), [(5,15)]) # 3' wins
p = [(1,10),(2,10)] #conflict
self.assertRaises(ValueError, f, p)
def test_inc_range_empty(self):
"""inc_range: should handle empty or pseudoknot-free pairs
"""
f = inc_range
p = []
exp = []
self.assertEqual(f(p), exp)
p = [(1,10),(4,7),(2,9),(5,None)]
exp = [(1,10),(2,9),(4,7)]
self.assertEqual(f(p), exp)
class NussinovTests(TestCase):
"""Tests for restricted nussinov algorithm and related functions"""
def test_nussinov_fill(self):
"""nussinov_fill: basic test"""
p = Pairs([(0,7),(1,6),(2,5),(3,9),(4,8)])
exp = [[0,0,0,0,0,1,2,3,3,3],
[0,0,0,0,0,1,2,2,2,2],
[0,0,0,0,0,1,1,1,1,2],
[0,0,0,0,0,0,0,0,1,2],
[0,0,0,0,0,0,0,0,1,1,],
[0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0],
[0,0,0,0,0,0,0,0,0,0]]
obs = nussinov_fill(p,size=10)
self.assertEqual(obs, exp)
def test_nussinov_traceback(self):
"""nussinov_traceback: basic test"""
p = Pairs([(0,7),(1,6),(2,5),(3,9),(4,8)])
m = nussinov_fill(p,size=10)
exp = set([(0,7),(1,6),(2,5)])
obs = nussinov_traceback(m, 0, 9, p)
self.assertEqual(obs, exp)
def test_nussinov_restricted(self):
"""nussinov_restricted: basic test"""
p = Pairs([(0,7),(1,6),(2,5),(3,9),(4,8)])
obs = nussinov_restricted(p)
obs_rem = nussinov_restricted(p, return_removed=True)
exp = [(0,7),(1,6),(2,5)]
exp_rem = ([(0,7),(1,6),(2,5)],[(3,9),(4,8)])
self.assertEqual(obs, exp)
self.assertEqual(obs_rem, exp_rem)
p = Pairs([(0,7),(1,6),(2,6)])
self.assertRaises(ValueError, nussinov_restricted, p)
p = Pairs([(0,7),(1,6),(2,5)])
exp = Pairs([(0,7),(1,6),(2,5)])
self.assertEqual(nussinov_restricted(p), exp)
def test_nussinov_restricted_bi(self):
"""nussinov_restricted: include bifurcation"""
p = Pairs([(0,7),(1,6),(2,14),(3,13),(4,12),(5,11),\
(8,17),(9,16),(10,15)])
obs = nussinov_restricted(p)
obs_rem = nussinov_restricted(p, return_removed=True)
exp = [(0,7),(1,6),(8,17),(9,16),(10,15)]
exp_rem = ([(0,7),(1,6),(8,17),(9,16),(10,15)],\
[(2,14),(3,13),(4,12),(5,11)])
self.assertEqual(obs, exp)
self.assertEqual(obs_rem, exp_rem)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_struct/test_manipulation.py 000644 000765 000024 00000007652 12024702176 024111 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import os, tempfile
try:
from cogent.util.unit_test import TestCase, main
from cogent.parse.pdb import PDBParser
from cogent.format.pdb import PDBWriter
from cogent.struct.selection import einput
from cogent.struct.manipulation import copy, clean_ical, \
expand_symmetry, expand_crystal
except ImportError:
from zenpdb.cogent.util.unit_test import TestCase, main
from zenpdb.cogent.parse.pdb import PDBParser
from cogent.format.pdb import PDBWriter
from zenpdb.cogent.struct.selection import einput
from zenpdb.cogent.struct.manipulation import copy, clean_ical, \
exapnd_symmetry, expand_crystal
__author__ = "Marcin Cieslik"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Development"
class ManipulationTest(TestCase):
"""tests manipulationg entities"""
def setUp(self):
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
def test_clean_ical(self):
"""tests the clean ical function which cleans structures."""
chainB = self.input_structure.table['C'][('2E12', 0, 'B')]
leu25 = self.input_structure.table['R'][('2E12', 0, 'B', \
('LEU', 25, ' '))]
leu25icA = copy(leu25)
self.assertTrue(leu25icA.parent is None)
self.assertTrue(leu25icA is not leu25)
self.assertTrue(leu25icA[(('N', ' '),)] is not leu25[(('N', ' '),)])
leu25icA.setIc('A')
self.assertEquals(leu25icA.getId(), (('LEU', 25, 'A'),))
chainB.addChild(leu25icA)
self.assertFalse(chainB[(('LEU', 25, 'A'),)] is \
chainB[(('LEU', 25, ' '),)])
self.assertEquals(clean_ical(self.input_structure), \
([], [('2E12', 0, 'B', ('LEU', 25, 'A'))]))
clean_ical(self.input_structure, pretend=False)
self.assertTrue(chainB[(('LEU', 25, 'A'),)] is leu25icA)
self.assertFalse((('LEU', 25, 'A'),) in chainB.keys())
self.assertFalse((('LEU', 25, 'A'),) in chainB)
self.assertTrue((('LEU', 25, 'A'),) in chainB.keys(unmask=True))
self.input_structure.setUnmasked(force=True)
self.assertEquals(clean_ical(self.input_structure), \
([], [('2E12', 0, 'B', ('LEU', 25, 'A'))]))
clean_ical(self.input_structure, pretend=False, mask=False)
self.assertFalse((('LEU', 25, 'A'),) in chainB.keys())
self.assertFalse((('LEU', 25, 'A'),) in chainB)
self.assertFalse((('LEU', 25, 'A'),) in chainB.keys(unmask=True))
def test_0expand_symmetry(self):
"""tests the expansion of a asu to a unit-cell."""
global fn
mh = expand_symmetry(self.input_structure[(0,)])
fd, fn = tempfile.mkstemp('.pdb')
os.close(fd)
fh = open(fn, 'w')
PDBWriter(fh, mh, self.input_structure.raw_header)
fh.close()
def test_1expand_crystal(self):
"""tests the expansion of a unit-cell to a crystal"""
fh = open(fn, 'r')
input_structure = PDBParser(fh)
self.assertTrue(input_structure.values(), 4) # 4 models
sh = expand_crystal(input_structure)
self.assertTrue(len(sh) == 27)
fd, fn2 = tempfile.mkstemp('.pdb')
os.close(fd)
fh = open(fn2, 'w')
a1 = einput(input_structure, 'A')
a2 = einput(sh.values()[3], 'A')
k = a1.values()[99].getFull_id()
name = sh.values()[3].name
a1c = a1[k].coords
a2c = a2[(name,) + k[1:]].coords
self.assertTrue(len(a1), len(a2))
self.assertRaises(AssertionError, self.assertFloatEqual, a1c, a2c)
PDBWriter(fh, sh)
fh.close()
os.unlink(fn)
os.unlink(fn2)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_struct/test_pairs_util.py 000644 000765 000024 00000105505 12024702176 023560 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# test_pairs_util.py
"""Provides tests for gapping/ungapping functions and base pair comparison
"""
from __future__ import division
from cogent.util.unit_test import TestCase, main
from cogent.core.sequence import RnaSequence, ModelSequence, Sequence
from cogent.core.moltype import RNA
from cogent.core.alphabet import CharAlphabet
from cogent.struct.rna2d import Pairs
from cogent.struct.pairs_util import PairsAdjustmentError,\
adjust_base, adjust_base_structures, adjust_pairs_from_mapping,\
delete_gaps_from_pairs, insert_gaps_in_pairs, gapped_to_ungapped,\
get_gap_symbol, get_gap_list, degap_model_seq, degap_seq,\
ungapped_to_gapped,\
pairs_intersection, pairs_union, compare_pairs,\
compare_pairs_mapping, compare_random_to_correct,\
sensitivity, selectivity, get_all_pairs, get_counts, extract_seqs,\
mcc, approximate_correlation, correlation_coefficient, all_metrics
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Shandy Wikman", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Production"
class GappedUngappedTests(TestCase):
"""Provides tests for gapped_to_ungapped and ungapped_to_gapped functions
"""
def setUp(self):
"""setUp: set up method for all tests"""
self.rna1 = RnaSequence('UCAG-RYN-N', Name='rna1')
self.m1 = ModelSequence('UCAG-RYN-N', Name='rna1',\
Alphabet=RNA.Alphabets.DegenGapped)
self.s1 = 'UCAG-RYN-N'
def test_adjust_base(self):
"""adjust_base: should work for pairs object or list of pairs"""
p = Pairs()
self.assertEqual(adjust_base(p,10),[])
pairs = [(1,21),(2,15),(3,13),(4,11),(5,10),(6,9)]
offset = -1
expected = [(0,20),(1,14),(2,12),(3,10),(4,9),(5,8)]
obs_pairs = adjust_base(pairs, offset)
self.assertEqual(obs_pairs, expected)
pairs = Pairs([(0,10),(1,9)])
self.assertEqual(adjust_base(pairs, -1), Pairs([(-1,9),(0,8)]))
self.assertEqual(adjust_base(pairs, 5), Pairs([(5,15),(6,14)]))
self.assertRaises(PairsAdjustmentError, adjust_base, pairs, 3.5)
def test_adjust_base_structures(self):
"""adjust_pairs_structures: simple structure"""
p = Pairs([(3,10),(4,9)])
p2 = Pairs([(2,7), (30,40)])
self.assertEqual(adjust_base_structures([p,p2], -1),\
[[(2,9),(3,8)],[(1,6),(29,39)]])
def test_adjust_base_None(self):
"""adjust_base: should keep Nones or duplicates, ignore conflicts"""
pairs = Pairs([(2,8),(3,7),(6,None),(None,None),(2,10)])
expected = Pairs([(1,7),(2,6),(5,None),(None, None),(1,9)])
self.assertEqual(adjust_base(pairs,-1), expected)
p = Pairs([(1,2),(2,1),(1,2),(2,None)])
self.assertEqual(adjust_base(p, 1), [(2,3),(3,2),(2,3),(3,None)])
def test_adjust_pairs_from_mapping_confl(self):
"""adjust_pairs_from_mapping: should handle conflicts, pseudo, dupl
"""
f = adjust_pairs_from_mapping
p = Pairs([(0,6),(1,5),(2,None),(None,None),(1,4),(3,7),(6,0)])
m = {0:1,1:3,2:6,3:7,4:8,5:10,6:11,7:12}
exp = Pairs([(1,11),(3,10),(6,None),(None,None),(3,8),(7,12),(11,1)])
self.assertEqual(f(p, m), exp)
p = Pairs([(1,11),(3,10),(7,12),(6,None),(None,None),(5,8)])
m = {1: 0, 3: 1, 6: 2, 7: 3, 8: 4, 10: 5, 11: 6, 12: 7}
exp = Pairs([(0,6),(1,5),(3,7),(2,None),(None,None)])
self.assertEqual(f(p,m), exp)
def test_delete_gaps_from_pairs(self):
"""delete_gaps_from_pairs: should work on standard input"""
r = delete_gaps_from_pairs
# empty list
p = Pairs([])
self.assertEqual(r(p,[1,2,3]), [])
# normal list
p1 = Pairs([(2,8), (3,6)])
gap_list = [0,1,4,5,7,9]
self.assertEqualItems(r(p1, gap_list), [(0,3),(1,2)])
p2 = Pairs([(2,8),(3,6),(4,9)])
self.assertEqualItems(r(p2, gap_list), [(0,3),(1,2)])
p3 = Pairs([(2,8),(3,6),(4,10)])
self.assertEqualItems(r(p3, gap_list), [(0,3),(1,2)])
def test_delete_gaps_from_pairs_weird(self):
"""delete_gaps_from_pairs: should ignore conflicts etc"""
r = delete_gaps_from_pairs
gap_list = [0,1,4,5,7,9]
p = Pairs([(2,6),(3,8)])
self.assertEqualItems(r(p, gap_list), [(0,2),(1,3)])
p = Pairs([(2,6),(3,8),(3,None),(6,2),(3,8), (None, None)])
self.assertEqualItems(r(p, gap_list),\
[(0,2),(1,3),(1,None),(2,0),(1,3),(None, None)])
def test_insert_gaps_in_pairs(self):
"""insert_gaps_in_pairs: should work with normal and conflicts"""
p = Pairs([(0,3),(1,2),(1,4),(3,None)])
gaps = [0,1,4,5,7]
self.assertEqual(insert_gaps_in_pairs(p, gaps),\
[(2,8),(3,6),(3,9),(8,None)])
p = Pairs([(0,6),(1,5),(2,None),(3,7),(0,1),(5,1)])
gaps = [0,2,6,9]
self.assertEqual(insert_gaps_in_pairs(p, gaps),\
[(1,10),(3,8),(4,None),(5,11),(1,3),(8,3)])
gaps = [2,3,4,9]
self.assertEqual(insert_gaps_in_pairs(p, gaps),\
[(0,10),(1,8),(5,None),(6,11),(0,1),(8,1)])
p = Pairs([(0,6),(1,5),(2,None),(3,7),(0,1),(5,1)])
gaps = []
self.assertEqual(insert_gaps_in_pairs(p, gaps),\
[(0,6),(1,5),(2,None),(3,7),(0,1),(5,1)])
def test_get_gap_symbol(self):
"""get_gap_symbol: Sequence, ModelSequence, old_cogent, string"""
self.assertEqual(get_gap_symbol(self.rna1), '-')
self.assertEqual(get_gap_symbol(self.m1), '-')
self.assertEqual(get_gap_symbol(self.s1), '-')
self.assertEqual(get_gap_symbol(''), '-')
def test_get_gap_list(self):
"""get_gap_list: Sequence, ModelSequence, old_cogent, string"""
gs = '-'
self.assertEqual(get_gap_list(self.rna1), [4,8])
self.assertEqual(get_gap_list(self.m1), [4,8])
self.assertEqual(get_gap_list(self.s1,gs),[4,8])
self.assertEqual(get_gap_list('',gs), [])
def test_degap_model_seq(self):
"""degap_model_seq: replacement for broken method"""
self.assertEqual(str(degap_model_seq(self.m1)),'UCAGRYNN')
def test_degap_seq(self):
"""degap_seq: Sequence, ModelSequence, old_cogent, string"""
f = degap_seq
gs = '-'
self.assertEqual(f(self.rna1, gs), 'UCAGRYNN')
self.assertEqual(str(f(self.m1, gs)), 'UCAGRYNN')
self.assertEqual(f(self.s1, gs), 'UCAGRYNN')
def test_gapped_to_ungapped(self):
"""gapped_to_ungapped: Sequence, ModelSequence, old_cogent, string
"""
p = Pairs([(0,6),(1,5),(3,9)])
exp = Pairs([(0,5),(1,4),(3,7)])
f = gapped_to_ungapped
self.assertEqual(f(self.rna1, p)[1], exp)
self.assertEqual(f(self.m1, p)[1], exp)
self.assertEqual(f(self.s1, p)[1], exp)
def test_ungapped_to_gapped(self):
"""ungapped_to_gapped: Sequence, ModelSequence, old_cogent, string
"""
p = Pairs([(0,6),(1,5),(3,9)])
exp = Pairs([(0,5),(1,4),(3,7)])
f = ungapped_to_gapped
self.assertEqual(f(self.rna1, exp)[1], p)
self.assertEqual(f(self.m1, exp)[1], p)
self.assertEqual(f(self.s1, exp)[1], p)
class OldAdjustmentFunctionsTests(TestCase):
"""Provides tests for gapped_to_ungapped and ungapped_to_gapped functions
"""
def setUp(self):
"""setUp: set up method for all tests"""
self.ungapped = 'AGAUGCUAGCUAC'
self.gapped = '-AGA--UGC-UAG--CUAC'
self.diff_sym = '*AGA**UGC*UAG**CUAC'
self.simple = Pairs([(2,7),(3,6),(8,12)])
self.simple_g = Pairs([(3,11),(6,10),(12,18)])
self.out_order = Pairs([(6,10),(4,1),(9,7),(5,11)])
self.out_order_g = Pairs([(10,16),(7,2),(15,11),(8,17)])
self.duplicates = Pairs([(3,9),(3,9),(2,10),(0,12)])
self.duplicates_g = Pairs([(6,15),(6,15),(3,16),(1,18)])
self.pseudo = Pairs([(0,7),(2,6),(3,10)])
self.pseudo_g = Pairs([(1,11),(3,10),(6,16)])
def test_adjust_base(self):
"""adjust_base: should work for pairs object or list of pairs"""
p = Pairs()
self.assertEqual(adjust_base(p,10),[])
pairs = [(1,21),(2,15),(3,13),(4,11),(5,10),(6,9)]
offset = -1
expected = [(0,20),(1,14),(2,12),(3,10),(4,9),(5,8)]
obs_pairs = adjust_base(pairs, offset)
self.assertEqual(obs_pairs, expected)
pairs = Pairs([(0,10),(1,9)])
self.assertEqual(adjust_base(pairs, -1), Pairs([(-1,9),(0,8)]))
self.assertEqual(adjust_base(pairs, 5), Pairs([(5,15),(6,14)]))
self.assertRaises(PairsAdjustmentError, adjust_base, pairs, 3.5)
def test_adjust_base_None(self):
"""adjust_base: should keep Nones or duplicates, ignore conflicts"""
pairs = Pairs([(2,8),(3,7),(6,None),(None,None),(2,10)])
expected = Pairs([(1,7),(2,6),(5,None),(None, None),(1,9)])
self.assertEqual(adjust_base(pairs,-1), expected)
p = Pairs([(1,2),(2,1),(1,2),(2,None)])
self.assertEqual(adjust_base(p, 1), [(2,3),(3,2),(2,3),(3,None)])
def test_delete_gaps_from_pairs(self):
"""delete_gaps_from_pairs: should work on standard input"""
r = delete_gaps_from_pairs
# empty list
p = Pairs([])
self.assertEqual(r(p,[1,2,3]), [])
# normal list
p1 = Pairs([(2,8), (3,6)])
gap_list = [0,1,4,5,7,9]
self.assertEqualItems(r(p1, gap_list), [(0,3),(1,2)])
p2 = Pairs([(2,8),(3,6),(4,9)])
self.assertEqualItems(r(p2, gap_list), [(0,3),(1,2)])
p3 = Pairs([(2,8),(3,6),(4,10)])
self.assertEqualItems(r(p3, gap_list), [(0,3),(1,2)])
def test_delete_gaps_from_pairs_weird(self):
"""delete_gaps_from_pairs: should ignore conflicts etc"""
r = delete_gaps_from_pairs
gap_list = [0,1,4,5,7,9]
p = Pairs([(2,6),(3,8)])
self.assertEqualItems(r(p, gap_list), [(0,2),(1,3)])
p = Pairs([(2,6),(3,8),(3,None),(6,2),(3,8), (None, None)])
self.assertEqualItems(r(p, gap_list),\
[(0,2),(1,3),(1,None),(2,0),(1,3),(None, None)])
def test_insert_gaps_in_pairs(self):
"""insert_gaps_in_pairs: should work with normal and conflicts"""
p = Pairs([(0,3),(1,2),(1,4),(3,None)])
gaps = [0,1,4,5,7]
self.assertEqual(insert_gaps_in_pairs(p, gaps),\
[(2,8),(3,6),(3,9),(8,None)])
p = Pairs([(0,6),(1,5),(2,None),(3,7),(0,1),(5,1)])
gaps = [0,2,6,9]
self.assertEqual(insert_gaps_in_pairs(p, gaps),\
[(1,10),(3,8),(4,None),(5,11),(1,3),(8,3)])
gaps = [2,3,4,9]
self.assertEqual(insert_gaps_in_pairs(p, gaps),\
[(0,10),(1,8),(5,None),(6,11),(0,1),(8,1)])
def test_gapped_to_ungapped_simple(self):
"""gapped_to_ungapped: should work for simple case"""
s = RnaSequence(self.gapped)
p = self.simple_g
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.simple)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
def test_gapped_to_ungapped_out_of_order(self):
"""gapped_to_ungapped: should work when pairs are out of order
"""
s = RnaSequence(self.gapped)
p = Pairs(self.out_order_g)
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.out_order)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
def test_gapped_to_ungapped_duplicates(self):
"""gapped_to_ungapped: should work when pairs contains duplicates
"""
s = RnaSequence(self.gapped)
p = Pairs(self.duplicates_g)
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.duplicates)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
def test_gapped_to_ungapped_pseudo(self):
"""gapped_to_ungapped: shouldn't care about pseudoknots
"""
s = RnaSequence(self.gapped)
p = Pairs(self.pseudo_g)
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.pseudo)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
def test_gapped_to_ungapped_no_gaps(self):
"""gapped_to_ungapped: should return same pairs when no gaps
"""
s = RnaSequence(self.ungapped)
p = Pairs(self.simple)
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.simple)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
def test_ungapped_to_gapped(self):
"""ungapped_to_gapped: should work for basic case
"""
s = RnaSequence(self.gapped)
p = self.simple
obs_seq, obs_pairs = ungapped_to_gapped(s,p)
assert obs_seq is s
self.assertEqualItems(obs_pairs, self.simple_g)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
def test_ungapped_to_gapped_out_of_order(self):
"""ungapped_to_gapped: should work when pairs out of order
"""
s = RnaSequence(self.gapped)
p = self.out_order
obs_seq, obs_pairs = ungapped_to_gapped(s,p)
assert obs_seq is s
self.assertEqualItems(obs_pairs, self.out_order_g)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
def test_gapped_to_ungapped_simple(self):
"""gapped_to_ungapped: should work on simple case
"""
s = self.gapped
p = self.simple_g
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.simple)
assert not isinstance(obs_seq, RnaSequence)
assert isinstance(obs_seq, str)
assert isinstance(obs_pairs, Pairs)
def test_gapped_to_ungapped_pseudo(self):
"""gapped_to_ungapped: shouldn't care about pseudoknots
"""
s = self.gapped
p = self.pseudo_g
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.pseudo)
assert not isinstance(obs_seq, RnaSequence)
assert isinstance(obs_seq, str)
assert isinstance(obs_pairs, Pairs)
def test_ungapped_to_gapped_simple(self):
"""ungapped_to_gapped: should work on basic case"""
s = self.gapped
p = self.simple
obs_seq, obs_pairs = ungapped_to_gapped(s,p)
assert obs_seq is s
self.assertEqualItems(obs_pairs, self.simple_g)
assert not isinstance(obs_seq, RnaSequence)
assert isinstance(obs_seq, str)
assert isinstance(obs_pairs, Pairs)
def test_ungapped_to_gapped_duplicates(self):
"""ungapped_to_gapped: should work when pairs are duplicated"""
s = self.gapped
p = self.duplicates
obs_seq, obs_pairs = ungapped_to_gapped(s,p)
assert obs_seq is s
self.assertEqualItems(obs_pairs, self.duplicates_g)
assert not isinstance(obs_seq, RnaSequence)
assert isinstance(obs_seq, str)
assert isinstance(obs_pairs, Pairs)
def test_gapped_to_ungapped_general(self):
"""gapped_to_ungapped: should return object of right type
"""
s = RnaSequence(self.gapped)
p = self.simple_g
#in case of RnaSequence
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.simple)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
#in case of str input
s = self.gapped
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.simple)
assert not isinstance(obs_seq, RnaSequence)
assert isinstance(obs_seq, str)
assert isinstance(obs_pairs, Pairs)
def test_ungapped_to_gapped_general(self):
"""ungapped_to_gapped: should return object of right type
"""
s = RnaSequence(self.gapped)
p = self.simple
#in case of RnaSequence
obs_seq, obs_pairs = ungapped_to_gapped(s,p)
assert obs_seq is s
self.assertEqualItems(obs_pairs, self.simple_g)
assert isinstance(obs_seq, RnaSequence)
assert isinstance(obs_pairs, Pairs)
#in case of str input
s = self.gapped
obs_seq, obs_pairs = ungapped_to_gapped(s,p)
assert obs_seq is s
self.assertEqualItems(obs_pairs, self.simple_g)
assert not isinstance(obs_seq, RnaSequence)
assert isinstance(obs_seq, str)
assert isinstance(obs_pairs, Pairs)
def test_gapped_to_ungapped_general_seq(self):
"""gapped_to_ungapped: when input is Sequence obj, treat as string
"""
s = Sequence(self.gapped)
p = self.simple_g
obs_seq, obs_pairs = gapped_to_ungapped(s,p)
self.assertEqual(obs_seq, self.ungapped)
self.assertEqualItems(obs_pairs, self.simple)
#assert not isinstance(obs_seq, Sequence)
#assert isinstance(obs_seq, str)
assert isinstance(obs_seq, Sequence)
assert isinstance(obs_pairs, Pairs)
def test_adjust_pairs_from_mapping(self):
"""adjust_pairs_from_mapping: should work both ways
"""
#ungapped to gapped
r = RnaSequence('UC-AG-UC-CG-A-')
u_to_g = r.gapMaps()[0]
#{0: 0, 1: 1, 2: 3, 3: 4, 4: 6, 5: 7, 6: 9, 7: 10, 8: 12}
ungapped_pairs = Pairs([(0,8),(1,6),(2,5)])
exp_pairs = Pairs([(0,12),(1,9),(3,7)])
self.assertEqualItems(adjust_pairs_from_mapping(ungapped_pairs,\
u_to_g), exp_pairs)
#gapped to ungapped
r = RnaSequence('UC-AG-UC-CG-A-')
g_to_u = r.gapMaps()[1]
#{0: 0, 1: 1, 3: 2, 4: 3, 6: 4, 7: 5, 9: 6, 10: 7, 12: 8}
gapped_pairs = Pairs([(0,12),(1,9),(3,7)])
exp_pairs = Pairs([(0,8),(1,6),(2,5)])
self.assertEqualItems(adjust_pairs_from_mapping(gapped_pairs,\
g_to_u), exp_pairs)
class PairsComparisonTests(TestCase):
"""Provides tests for comparing different Pairs objects"""
def test_pairs_intersection(self):
"""pairs_intersection: should work on simple case
"""
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([(1,12),(4,9),(5,8)])
self.assertEqualItems(pairs_intersection(p1,p2),[(4,9),(5,8)])
#works when one is empty
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([])
self.assertEqualItems(pairs_intersection(p1,p2),[])
#works also on lists (not Pairs)
p1 = [(3,10),(4,9),(5,8),(20,24)]
p2 = [(1,12),(4,9),(5,8)]
self.assertEqualItems(pairs_intersection(p1,p2),[(4,9),(5,8)])
def test_pairs_intersection_duplicates(self):
"""pairs_intersection: should work on flipped pairs and duplicates
"""
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([(10,3),(4,9),(5,8),(9,4),(4,9),(23,30)])
self.assertEqualItems(pairs_intersection(p1,p2),[(3,10),(4,9),(5,8)])
# Conflicts, duplicates, None, pseudoknots
p1 = Pairs([(3,10),(4,9),(5,8),(20,24),(22,26),(3,2),(9,4),(6,None)])
p2 = Pairs([(1,12),(4,9),(5,8)])
self.assertEqualItems(pairs_intersection(p1,p2),\
[(4,9),(5,8)])
def test_pairs_union(self):
"""pairs_union: should work on simple case
"""
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([(1,12),(4,9),(5,8)])
self.assertEqualItems(pairs_union(p1,p2),\
[(1,12),(3,10),(4,9),(5,8),(20,24)])
#works when one is empty
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([])
self.assertEqualItems(pairs_union(p1,p2),p1)
#works also on lists (not Pairs)
p1 = [(3,10),(4,9),(5,8),(20,24)]
p2 = [(1,12),(4,9),(5,8)]
self.assertEqualItems(pairs_union(p1,p2),\
[(1,12),(3,10),(4,9),(5,8),(20,24)])
def test_union_duplicates(self):
"""pairs_union: should work on flipped base pairs and duplicates
"""
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([(10,3),(4,9),(5,8),(9,4),(4,9),(23,30)])
self.assertEqualItems(pairs_union(p1,p2),\
[(3,10),(4,9),(5,8),(20,24),(23,30)])
# Conflicts, duplicates, None, pseudoknots
p1 = Pairs([(3,10),(4,9),(5,8),(20,24),(22,26),(3,2),(9,4),(6,None)])
p2 = Pairs([(1,12),(4,9),(5,8)])
self.assertEqualItems(pairs_union(p1,p2),\
[(1,12),(3,10),(4,9),(5,8),(20,24),(22,26),(2,3)])
def test_compare_pairs(self):
"""compare_pairs: should work on simple case"""
#all the same
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([(3,10),(4,9),(5,8),(20,24)])
self.assertEqual(compare_pairs(p1,p2),1)
#all different
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([(1,2),(3,4),(5,6)])
self.assertEqual(compare_pairs(p1,p2),0)
#one empty
p1 = Pairs([(3,10),(4,9),(5,8),(20,24)])
p2 = Pairs([])
self.assertEqual(compare_pairs(p1,p2),0)
#partially different
p1 = Pairs([(1,2),(3,4),(5,6),(7,8)])
p2 = Pairs([(1,2),(3,4),(9,10),(11,12)])
self.assertFloatEqual(compare_pairs(p1,p2),.33333333333333333)
#partially different
p1 = Pairs([(1,2),(3,4),(5,6)])
p2 = Pairs([(1,2),(3,4),(9,10)])
self.assertFloatEqual(compare_pairs(p1,p2),.5)
def test_compare_pairs_both_empty(self):
"""compare_pairs: should return 1.0 when both lists are empty
"""
p1 = Pairs([])
p2 = Pairs([])
self.assertEqual(compare_pairs(p1,p2),1)
def test_compare_pairs_weird(self):
"""compare_pairs: should handle conflicts, duplicates, pseudo, None
"""
#Should raise error on conflict
p1 = Pairs([(1,2),(3,4),(5,6),(2,None),(4,3),(None,None)])
p2 = Pairs([(1,2),(3,4),(9,10)])
self.assertRaises(ValueError, compare_pairs, p1, p2)
p1 = Pairs([(1,2),(3,4),(5,6),(4,3),(None,None),(10,None)])
p2 = Pairs([(1,2),(3,4),(9,10)])
self.assertFloatEqual(compare_pairs(p1,p2),.5)
p1 = Pairs([(1,8),(2,10),(7,3)])
p2 = Pairs([(1,8),(10,2),(3,7),(4,6)])
self.assertFloatEqual(compare_pairs(p1,p2), 0.75)
def test_compare_pairs_mapping(self):
"""compare_pairs_mapping: should work with correct mapping
"""
# pos in first seq, base, pos in second seq
#1 U 0
#2 C 1
#3 G 2
#4 A 3
# A 4
#5 C 5
#6 C 6
#7 U
#8 G 7
#all the same
p1 = Pairs([(3,6),(1,8)])
p2 = Pairs([(2,6),(0,7)])
mapping = {1:0,2:1,3:2,4:3,5:5,6:6,7:None, 8:7}
self.assertEqual(compare_pairs_mapping(p1,p2, mapping),1)
#all different
p1 = Pairs([(3,6),(1,8)])
p2 = Pairs([(1,5),(4,7)])
mapping = {1:0,2:1,3:2,4:3,5:5,6:6,7:None, 8:7}
self.assertEqual(compare_pairs_mapping(p1,p2, mapping),0)
#partially the same
p1 = Pairs([(5,6),(1,4),(2,7)])
p2 = Pairs([(5,6),(0,3),(4,7)])
self.assertEqual(compare_pairs_mapping(p1,p2, mapping),.5)
p1 = Pairs([(1,8),(2,7),(3,6),(4,5)])
p2 = Pairs([(0,7),(1,6),(2,5),(3,4)])
self.assertFloatEqual(compare_pairs_mapping(p1,p2, mapping),1/7)
#one empty
p1 = Pairs([(1,8),(2,7),(3,6),(4,5)])
p2 = []
self.assertEqual(compare_pairs_mapping(p1,p2, mapping),0)
#both empty
p1 = []
p2 = []
self.assertEqual(compare_pairs_mapping(p1,p2, mapping),1)
def test_compare_random_to_correct(self):
"""comapre_random_to_correct: should return correct fraction
"""
p1 = Pairs([(1,8),(2,7),(3,6),(4,5)])
p2 = Pairs([(1,8)])
p3 = Pairs([(1,8), (2,7), (4,5)])
p4 = Pairs([(1,8),(2,7),(9,10),(11,12)])
self.assertFloatEqual(compare_random_to_correct(p2,p1),1)
self.assertFloatEqual(compare_random_to_correct(p3,p1),1)
self.assertFloatEqual(compare_random_to_correct(p4,p1),0.5)
self.assertFloatEqual(compare_random_to_correct([],p1),0)
self.assertFloatEqual(compare_random_to_correct(p2,[]),0)
self.assertFloatEqual(compare_random_to_correct([],[]),1)
class GardnerMetricsTest(TestCase):
"""Tests for the metrics from Gardner & Giegerich 2004"""
def setUp(self):
"""setUp: setup method for all tests"""
self.true = Pairs([(0,40),(1,39),(2,38),(3,37),(10,20),\
(11,19),(12,18),(13,17),(26,33),(27,32)])
self.predicted = Pairs([(0,40),(1,39),(2,38),(3,37),(4,36),\
(5,35),(10,22),(11,20),(14,29),(15,28)])
self.seq = ['>seq1\n','agguugaaggggauccgauccacuccccggcuggucaaccu']
def test_conflicts(self):
"""all metrics should raise error when conflicts in one of the structs
"""
ref = Pairs([(1,6),(2,5),(3,10),(7,None),(None,None),(5,2),(1,12)])
pred = Pairs([(6,1),(10,11),(3,12)])
self.assertRaises(ValueError, sensitivity, ref, pred)
self.assertRaises(ValueError, sensitivity, pred, ref)
self.assertRaises(ValueError, selectivity, ref, pred)
self.assertRaises(ValueError, selectivity, pred, ref)
self.assertRaises(ValueError, approximate_correlation, ref, pred,\
self.seq)
self.assertRaises(ValueError, approximate_correlation, pred, ref,\
self.seq)
self.assertRaises(ValueError, correlation_coefficient, ref, pred,\
self.seq)
self.assertRaises(ValueError, correlation_coefficient, pred, ref,\
self.seq)
self.assertRaises(ValueError, mcc, ref, pred, self.seq)
self.assertRaises(ValueError, mcc, pred, ref, self.seq)
def test_get_all_pairs(self):
"""get_all_pairs: should return the number of possible pairs"""
seq = RnaSequence('UCAG-NACGU')
seq2 = RnaSequence('UAAG-CACGC')
self.assertEqual(get_all_pairs([seq], min_dist=4), 6)
self.assertEqual(get_all_pairs([seq2], min_dist=4), 4)
# when given multiple sequences, should average over all of them
self.assertEqual(get_all_pairs([seq,seq2], min_dist=4), 5)
# different min distance
self.assertEqual(get_all_pairs([seq], min_dist=2),10)
# error on invalid minimum distance
self.assertRaises(ValueError, get_all_pairs, [seq], min_dist=-2)
def test_get_counts(self):
"""get_counts: should work with all parameters"""
seq = RnaSequence('UCAG-NAUGU')
seq2 = RnaSequence('UAAG-CACGC')
p = Pairs([(1,8),(2,7)])
p2 = Pairs([(1,8),(2,6),(3,6),(4,9),])
exp = {'TP':1,'TN':0, 'FN':1,'FP':3,\
'FP_INCONS':0, 'FP_CONTRA':0, 'FP_COMP':0}
self.assertEqual(get_counts(p, p2), exp)
exp = {'TP':1,'TN':0, 'FN':1,'FP':3,\
'FP_INCONS':1, 'FP_CONTRA':1, 'FP_COMP':1}
self.assertEqual(get_counts(p, p2, split_fp=True), exp)
seq = RnaSequence('UCAG-NACGU')
exp = {'TP':1,'TN':7, 'FN':1,'FP':3,\
'FP_INCONS':1, 'FP_CONTRA':1, 'FP_COMP':1}
self.assertEqual(get_counts(p, p2, split_fp=True,\
sequences=[seq], min_dist=2), exp)
# check against compare_ct.pm
exp = {'TP':4,'TN':266, 'FN':6,'FP':6,\
'FP_INCONS':2, 'FP_CONTRA':2, 'FP_COMP':2}
seq = 'agguugaaggggauccgauccacuccccggcuggucaaccu'.upper()
self.assertEqual(get_counts(self.true, self.predicted, split_fp=True,\
sequences=[seq], min_dist=4), exp)
def test_extract_seqs(self):
"""extract_seqs: should handle different input formats"""
s1 = ">seq1\nACGUAGC\n>seq2\nGGUAGCG"
s2 = [">seq1","ACGUAGC",">seq2","GGUAGCG"]
s3 = ['ACGUAGC','GGUAGCG']
s4 = [RnaSequence('ACGUAGC'), RnaSequence('GGUAGCG')]
m1 = ModelSequence('ACGUAGC', Name='rna1',\
Alphabet=RNA.Alphabets.DegenGapped)
m2 = ModelSequence('GGUAGCG', Name='rna2',\
Alphabet=RNA.Alphabets.DegenGapped)
s5 = [m1, m2]
f = extract_seqs
self.assertEqual(f(s1), ['ACGUAGC', 'GGUAGCG'])
self.assertEqual(f(s2), ['ACGUAGC', 'GGUAGCG'])
self.assertEqual(f(s3), ['ACGUAGC', 'GGUAGCG'])
self.assertEqual(f(s4), ['ACGUAGC', 'GGUAGCG'])
self.assertEqual(f(s5), ['ACGUAGC', 'GGUAGCG'])
def test_sensitivity(self):
"""sensitivity: check against compare_ct.pm"""
sen = sensitivity(self.true,self.predicted)
self.assertEqual(sen, 0.4)
def test_sensitivity_general(self):
"""sensitivity: should work in general"""
ref = Pairs([(1,6),(2,5),(3,10)])
pred = Pairs([(6,1),(10,11),(3,12)])
# one good prediction
self.assertFloatEqual(sensitivity(ref, pred), 1/3)
# over-prediction not penalized
pred = Pairs([(6,1),(10,11),(3,12),(13,20),(14,19),(15,18)])
self.assertFloatEqual(sensitivity(ref, pred), 1/3)
def test_sensitivity_dupl(self):
"""sensitivity: should handle duplicates, pseudo, None"""
ref = Pairs([(1,6),(2,5),(3,10),(7,None),(None,None),(5,2),(4,9)])
pred = Pairs([(6,1),(10,11),(3,12)])
self.assertFloatEqual(sensitivity(ref, pred), 0.25)
pred = Pairs([(6,1),(10,11),(3,12),(20,None),(None,None),(1,6)])
self.assertFloatEqual(sensitivity(ref, pred), 0.25)
def test_sensitivity_empty(self):
"""sensitivity: should work on emtpy Pairs"""
# both empty
self.assertFloatEqual(sensitivity(Pairs(), Pairs()), 1)
pred = Pairs([(6,1),(10,11),(3,12),(13,20),(14,19),(15,18)])
# prediction emtpy
self.assertFloatEqual(sensitivity(Pairs(), pred), 0)
# reference empty
self.assertFloatEqual(sensitivity(pred, Pairs()), 0)
def test_selectivity(self):
"""selectivity: check against compare_ct.pm"""
sel = selectivity(self.true,self.predicted)
self.assertEqual(sel, 0.5)
def test_selectivity_general(self):
"""selectivity: should work in general"""
ref = Pairs([(1,6),(2,5),(10,13)])
pred = Pairs([(6,1),(3,4),(10,12)])
# one good prediction
self.assertFloatEqual(selectivity(ref, pred), 0.5)
# over-prediction not penalized
pred = Pairs([(6,1),(10,11),(3,12),(13,20),(14,19),(15,18)])
self.assertFloatEqual(selectivity(ref, pred), 0.25)
def test_selectivity_dupl(self):
"""selectivity: duplicates and Nones shouldn't influence the calc.
"""
ref = Pairs([(1,6),(2,5),(10,13),(6,1),(7,None),(None,None)])
pred = Pairs([(6,1),(3,4),(10,12)])
self.assertFloatEqual(selectivity(ref, pred), 0.5)
def test_selectivity_empty(self):
"""selectivity: should handle empty reference/predicted structure"""
# both empty
self.assertFloatEqual(selectivity(Pairs(), Pairs()), 1)
pred = Pairs([(6,1),(10,11),(3,12),(13,20),(14,19),(15,18)])
# prediction emtpy
self.assertFloatEqual(selectivity(Pairs(), pred), 0)
# reference empty
self.assertFloatEqual(selectivity(pred, Pairs()), 0)
def test_approximate_correlation(self):
"""approximate_correlation: check against compare_ct.pm"""
self.assertFloatEqual(approximate_correlation(self.true,\
self.predicted, seqs=self.seq), 0.45)
def test_correlation_coefficient(self):
"""correlation_coefficient: check against compare_ct.pm"""
self.assertFloatEqual(correlation_coefficient(self.true,\
self.predicted, seqs=self.seq, min_dist=4), 0.42906394)
def test_cc_bad_pred(self):
"""correlation_coefficient: should give 0 when TP=0"""
ref = Pairs([(1,7),(2,5)])
pred = Pairs([(0,8)])
seqs = ['CAUCGAUUG']
self.assertEqual(correlation_coefficient(ref, pred, seqs=seqs), 0.0)
def test_mcc(self):
"""mcc: check against compare_ct.pm"""
res = mcc(self.true,self.predicted,self.seq, min_dist=4)
self.assertFloatEqual(res, 0.42906394)
def test_all_metrics(self):
"""all_metrics: check against compare_ct.pm"""
exp = {'SENSITIVITY':0.4, 'SELECTIVITY':0.5, 'AC':0.45,\
'CC':0.42906394, 'MCC':0.42906394}
obs = all_metrics(self.true, self.predicted, seqs=self.seq, min_dist=4)
self.assertEqualItems(obs.keys(), exp.keys())
for k in exp:
self.assertFloatEqual(obs[k], exp[k])
def test_get_counts_pseudo(self):
"""get_counts: should work when pseudo in ref -> classification off"""
# pairs that would normally be compatible, are now contradicting
ref = Pairs([(0,8),(1,7),(4,10)])
pred = Pairs([(0,8),(3,6),(4,10)])
seq = 'GACUGUGUCAU'
exp = {'TP':2,'TN':13-2-1, 'FN':1,'FP':1,\
'FP_INCONS':0, 'FP_CONTRA':1, 'FP_COMP':0}
self.assertEqual(get_counts(ref, pred, split_fp=True,\
sequences=[seq], min_dist=4), exp)
def test_all_metrics_pseudo(self):
"""all_metrics: pseudoknot in ref, check against compare_ct.pm"""
ref = Pairs([(0,8),(1,7),(4,10)])
pred = Pairs([(0,8),(3,6),(4,10)])
seq = 'GACUGUGUCAU'
exp = {'SENSITIVITY':0.6666667, 'SELECTIVITY':0.6666667,\
'AC':0.6666667, 'CC':0.57575758, 'MCC':0.57575758}
obs = all_metrics(ref, pred, seqs=[seq], min_dist=4)
self.assertEqualItems(obs.keys(), exp.keys())
for k in exp:
self.assertFloatEqual(obs[k], exp[k])
def test_all_metrics_weird_input(self):
"""all_metrics: should work when ref or prediction empty or no seqs"""
ref = Pairs([(3,10)])
pred = Pairs()
seqs = ['UACGUAGCUAGCUAGCUACG']
obs = all_metrics(ref, pred, seqs=[seqs], min_dist=4)
exp = {'SENSITIVITY':0, 'SELECTIVITY':0,\
'AC':0, 'CC':0, 'MCC':0}
for k in exp:
self.assertFloatEqual(obs[k], exp[k])
ref = Pairs()
pred = Pairs()
seqs = ['UACGUAGCUAGCUAGCUACG']
obs = all_metrics(ref, pred, seqs=[seqs], min_dist=4)
exp = {'SENSITIVITY':1, 'SELECTIVITY':1,\
'AC':1, 'CC':1, 'MCC':1}
for k in exp:
self.assertFloatEqual(obs[k], exp[k])
ref = Pairs([(3,10)])
pred = Pairs([(1,12)])
seqs = ['UACGUAGCUAGCUAGCUACG']
self.assertRaises(ValueError, all_metrics, ref, pred, seqs="",\
min_dist=4)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_struct/test_rna2d.py 000644 000765 000024 00000127201 12024702176 022410 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for ViennaStructure and related classes.
"""
from cogent.util.unit_test import TestCase, main
from cogent.struct.rna2d import ViennaStructure, Vienna, Pairs,\
Partners, EmptyPartners, WussStructure, wuss_to_vienna, StructureNode, \
Stem, classify, PairError
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Sandra Smit"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class RnaAlphabet(object):
Pairs = {
('A','U'): True, #True vs False for 'always' vs 'sometimes' pairing
('C','G'): True,
('G','C'): True,
('U','A'): True,
('G','U'): False,
('U','G'): False,
}
class Rna(str):
Alphabet = RnaAlphabet
class StemTests(TestCase):
"""Tests for the Stem object"""
def test_init_empty(self):
"""Stem should init ok with no parameters."""
s = Stem()
self.assertEqual((s.Start, s.End, s.Length), (None, None, 0))
def test_init(self):
"""Stem should init with Start, End, and Length"""
s = Stem(Length=3)
self.assertEqual((s.Start, s.End, s.Length), (None, None, 3))
#should set Length to 0 if not supplied and unpaired
s = Stem(Start=3)
self.assertEqual((s.Start, s.End, s.Length), (3, None, 0))
s = Stem(End=3)
self.assertEqual((s.Start, s.End, s.Length), (None, 3, 0))
#should set Length to 1 if not supplied and paired
s = Stem(Start=3, End=5)
self.assertEqual((s.Start, s.End, s.Length), (3, 5, 1))
#parameters should be in order Start, End, Length
#note that you're allowed to initialize an invalid stem, like the
#following one (can't have 7 pairs between 3 and 5); this is often
#useful when building up a tree that you plan to renumber().
s = Stem(3, 5, 7)
self.assertEqual((s.Start, s.End, s.Length), (3, 5, 7))
#not allowed more than 3 parameters
self.assertRaises(TypeError, Stem, 1, 2, 3, 4)
def test_len(self):
"""Stem len() should return self.Length"""
s = Stem()
self.assertEqual(len(s), 0)
s.Length = 5
self.assertEqual(len(s), 5)
s.Length = None
self.assertRaises(TypeError, len, s)
def test_getitem(self):
"""Stem getitem should return a Stem object for the ith pair in the stem"""
s = Stem()
self.assertRaises(IndexError, s.__getitem__, 0)
s.Start = 5
s.End = 8
s.Length = 1
pairs = list(s)
self.assertEqual(pairs, [Stem(5, 8, 1)])
s.Length = 2
pairs = list(s)
self.assertEqual(pairs, [Stem(5,8,1),Stem(6,7,1)])
#WARNING: Stem will not complain when iterating over an invalid helix,
#as per the one below
s.Length = 5
pairs = list(s)
self.assertEqual(pairs, [Stem(5,8,1),Stem(6,7,1),Stem(7,6,1),\
Stem(8,5,1), Stem(9,4,1)])
def test_cmp(self):
"""Stems should compare equal when the data is the same"""
self.assertEqual(Stem(1,2,3), Stem(1,2,3))
self.assertNotEqual(Stem(1,2,5), Stem(1,2,3))
a = Stem(1, 10, 2)
b = Stem(2, 8, 1)
c = Stem(15, 20, 2)
l = [c, b, a]
l.sort()
self.assertEqual(l, [a,b,c])
def test_extract(self):
"""Stems extract should return a list of 'pairs' from a sequence"""
seq = 'UGAGAUUUUCU'
s = Stem(1, 10, 3)
self.assertEqual(s.extract(seq), [('G','U'),('A','C'),('G','U')])
s = Stem(0, 1)
self.assertEqual(s.extract(seq), [('U','G')])
#should put in None if either position hasn't been specified
s = Stem(5)
self.assertEqual(s.extract(seq), [('U', None)])
s = Stem()
self.assertEqual(s.extract(seq), [(None, None)])
#should raise IndexError if the stem contains bases outside the seq
s = Stem(50, 60, 5)
self.assertRaises(IndexError, s.extract, seq)
def test_hash(self):
"""Stems hash should allow use as dict keys if unchanged"""
#WARNING: if you change the Stem after putting it in a dict, all bets
#are off as to behavior. Don't do it!
s = Stem(1, 5, 2)
t = Stem(1, 5, 2)
u = Stem(2, 4, 6)
v = Stem(2, 4, 6)
w = Stem(2, 4, 4)
d = {}
assert s is not t
for i in (s, t, u, v, w):
if i in d:
d[i] += 1
else:
d[i] = 1
self.assertEqual(len(d), 3)
self.assertEqual(d[Stem(1, 5, 2)], 2)
self.assertEqual(d[Stem(2, 4, 6)], 2)
self.assertEqual(d[Stem(2, 4, 4)], 1)
assert Stem(1,5) not in d
def test_str(self):
"""Stem str should print Start, End and Length as a tuple"""
self.assertEqual(str(Stem()), '(None,None,0)')
self.assertEqual(str(Stem(3)), '(3,None,0)')
self.assertEqual(str(Stem(3,4)), '(3,4,1)')
self.assertEqual(str(Stem(3,4,5)), '(3,4,5)')
def test_nonzero(self):
"""Stem nonzero should return True if paired (length > 0)"""
assert not Stem()
assert not Stem(1)
assert Stem(7, 10)
assert Stem(1, 7, 1)
assert Stem(2, 8, 3)
#go strictly by length; don't check if data is invalid
assert Stem(0, 0)
assert Stem(5, None, 10)
assert not Stem(5, 7, -1)
class PartnersTests(TestCase):
"""Tests for Partners object"""
def test_init(self):
"""Partners should init with empty list and stay free of conflicts"""
self.assertEqual(Partners([]),[])
empty = Partners([None]*6)
self.assertEqual(empty,[None,None,None,None,None,None])
self.assertRaises(ValueError,empty.__setitem__,2,2)
empty[2] = 3
self.assertEqual(empty,[None,None,3,2,None,None])
empty[3] = 1
self.assertEqual(empty,[None,3,None,1,None,None])
empty[3] = 5
self.assertEqual(empty,[None,None,None,5,None,3])
empty[1] = None
self.assertEqual(empty,[None,None,None,5,None,3])
def test_toPairs(self):
"""Partners toPairs() should return a Pairs object"""
p = Partners([None,3,None,1,5,4])
self.assertEqualItems(p.toPairs(),[(1,3),(4,5)])
assert isinstance(p.toPairs(),Pairs)
self.assertEqual(Partners([None]*10).toPairs(),[])
def test_not_implemented(self):
"""Partners not_implemented should raise error for 'naughty' methods"""
p = Partners([None,3,1,5,4])
self.assertRaises(NotImplementedError,p.pop)
self.assertRaises(NotImplementedError,p.sort)
self.assertRaises(NotImplementedError,p.__delitem__,3)
class PairsTests(TestCase):
"""Tests for Pairs object"""
def setUp(self):
"""Pairs SetUp method for all tests"""
self.Empty = Pairs([])
self.OneList = Pairs([[1,2]])
self.OneTuple = Pairs([(1,2)])
self.MoreLists = Pairs([[2,4],[3,9],[6,36],[7,49]])
self.MoreTuples = Pairs([(2,4),(3,9),(6,36),(7,49)])
self.MulNoOverlap = Pairs([(1,10),(2,9),(3,7),(4,12)])
self.MulOverlap = Pairs([(1,2),(2,3)])
self.Doubles = Pairs([[1,2],[1,2],[2,3],[1,3]])
self.Undirected = Pairs([(2,1),(6,4),(1,7),(8,3)])
self.UndirectedNone = Pairs([(5,None),(None,3)])
self.UndirectedDouble = Pairs([(2,1),(1,2)])
self.NoPseudo = Pairs([(1,20),(2,19),(3,7),(4,6),(10,15),(11,14)])
self.NoPseudo2 = Pairs([(1,3),(4,6)])
#((.(.)).)
self.p0 = Pairs([(0,6),(1,5),(3,8)])
#(.((..(.).).))
self.p1 = Pairs([(0,9),(2,12),(3,10),(5,7)])
#((.(.(.).)).)
self.p2 = Pairs([(0,10),(1,9),(3,12),(5,7)])
#((.((.(.)).).))
self.p3 = Pairs([(0,9),(1,8),(3,14),(4,13),(6,11)])
#(.(((.((.))).)).(((.((((..))).)))).)
self.p4 = Pairs([(0,35),(2,11),(3,10),(4,9),(6,14),(7,13),(16,28),\
(17,27),(18,26),(20,33),(21,32),(22,31),(23,30)])
#(.((.).))
self.p5 = Pairs([(0,5),(2,8),(3,7)])
self.p6 = Pairs([(0,19),(2,6),(3,5),(8,14),(9,13),(10,12),\
(16,22),(17,21)])
self.p7 = Pairs([(0,20),(2,6),(3,5),(8,14),(9,10),(11,16),(12,15),\
(17,23),(18,22)])
def test_init(self):
"""Pairs should initalize with both lists and tuples"""
self.assertEqual(self.Empty,[])
self.assertEqual(self.OneList,[[1,2]])
self.assertEqual(self.OneTuple,[(1,2)])
self.assertEqual(self.MulNoOverlap,[(1,10),(2,9),(3,7),(4,12)])
self.assertEqual(self.MulOverlap,[(1,2),(2,3)])
def test_toPartners(self):
"""Pairs toPartners() should return a Partners object"""
a = Pairs([(1,5),(3,4),(6,9),(7,8)]) #normal
b = Pairs([(0,4),(2,6)]) #pseudoknot
c = Pairs([(1,6),(3,6),(4,5)]) #conflict
self.assertEqual(a.toPartners(10),[None,5,None,4,3,1,9,8,7,6])
self.assertEqual(a.toPartners(13,3),\
[None,None,None,None,8,None,7,6,4,12,11,10,9])
assert isinstance(a.toPartners(10),Partners)
self.assertEqual(b.toPartners(7),[4,None,6,None,0,None,2])
self.assertRaises(ValueError,c.toPartners,7)
self.assertEqual(c.toPartners(7,strict=False),[None,None,None,6,5,4,3])
#raises an error when try to insert something at non-existing indices
self.assertRaises(IndexError,c.toPartners,0)
def test_toVienna(self):
"""Pairs toVienna() should return a ViennaStructure if possible"""
a = Pairs([(1,5),(3,4),(6,9),(7,8)]) #normal
b = Pairs([(0,4),(2,6)]) #pseudoknot
c = Pairs([(1,6),(3,6),(4,5)]) #conflict
d = Pairs([(1,6),(3,None)])
e = Pairs([(1,9),(8,2),(7,3)]) #not directed
f = Pairs([(1,6),(2,5),(10,15),(14,11)]) # not directed
self.assertEqual(a.toVienna(10),'.(.())(())')
self.assertEqual(a.toVienna(13,offset=3),'....(.())(())')
self.assertRaises(PairError,b.toVienna,7) #pseudoknot NOT accepted
self.assertRaises(Exception,b.toVienna,7) #old test for exception
self.assertRaises(ValueError,c.toVienna,7)
#pairs containging None are being skipped
self.assertEquals(d.toVienna(7),'.(....)')
#raises error when trying to insert at non-existing indices
self.assertRaises(IndexError,a.toVienna,3)
self.assertEqual(Pairs().toVienna(3),'...')
#test when parsing in the sequence
self.assertEqual(a.toVienna('ACGUAGCUAG'),'.(.())(())')
self.assertEqual(a.toVienna(Rna('AACCGGUUAGCUA'), offset=3),\
'....(.())(())')
self.assertEqual(e.toVienna(10),'.(((...)))')
self.assertEqual(f.toVienna(20),'.((..))...((..))....')
def test_tuples(self):
"""Pairs tuples() should transform the elements of list to tuples"""
x = Pairs([])
x.tuples()
assert x == []
x = Pairs([[1,2],[3,4]])
x.tuples()
assert x == [(1,2),(3,4)]
x = Pairs([(1,2),(3,4)])
x.tuples()
assert x == [(1,2),(3,4)]
assert x != [[1,2],[3,4]]
def test_unique(self):
"""Pairs unique() should remove double occurences of certain tuples"""
self.assertEqual(self.Empty.unique(),[])
self.assertEqual(self.MoreTuples.unique(),self.MoreTuples)
self.assertEqual(self.Doubles.unique(),Pairs([(1,2),(2,3),(1,3)]))
def test_directed(self):
"""Pairs directed() should change all pairs so that a}]',-0.01)
self.WussTwoHelix = WussStructure('{[.]}(<>).',1.11)
self.WussThreeHelix = WussStructure('::(<<({__}),,([(__)])-->>)')
self.WussPseudo = WussStructure('<<__AA>>_aa::')
def test_wuss_toPairs(self):
"""WussStructure toPairs() should return a valid Pairs object"""
self.assertEqual(self.WussNoPairs.toPairs(),[])
self.assertEqualItems(self.WussOneHelix.toPairs(),\
[(0,12),(2,11),(3,10),(4,7)])
self.assertEqualItems(self.WussTwoHelix.toPairs(),\
[(0,4),(1,3),(5,8),(6,7)])
self.assertEqualItems(self.WussThreeHelix.toPairs(),\
[(2,25),(3,24),(4,23),(5,10),(6,9),(13,20),(14,19),(15,18)])
self.assertEqualItems(self.WussPseudo.toPairs(),\
[(0,7),(1,6)])
def test_wuss_toPartners(self):
"""WussStructure toPartners() should return valid Partners object"""
self.assertEqual(self.WussNoPairs.toPartners(),[None]*6)
self.assertEqualItems(self.WussThreeHelix.toPartners(),\
[None,None,25,24,23,10,9,None,None,6,5,None,None,20,19,\
18,None,None,15,14,13,None,None,4,3,2])
self.assertEqualItems(self.WussPseudo.toPartners(),\
[7,6,None,None,None,None,1,0,None,None,None,None,None])
class Rna2dTests(TestCase):
def test_Vienna(self):
"""Vienna should initalize from several formats"""
self.NoPairs = Vienna('.......... (0.0)')
self.OneHelix = Vienna('((((())))) (-1e-02)')
self.TwoHelix = Vienna('((.))(()). \t(1.11)')
self.ThreeHelix = Vienna('(((((..))..(((..)))..)))')
self.GivenEnergy = Vienna('((.))',0.1)
self.TwoEnergies = Vienna('((.)) (4.6)',2.1)
self.assertEqual(self.NoPairs, '..........')
self.assertEqual(self.NoPairs.Energy, 0.0)
self.assertEqual(self.OneHelix, '((((()))))')
self.assertEqual(self.OneHelix.Energy, -1e-2)
self.assertEqual(self.TwoHelix, '((.))(()).')
self.assertEqual(self.TwoHelix.Energy, 1.11)
self.assertEqual(self.ThreeHelix, '(((((..))..(((..)))..)))')
self.assertEqual(self.ThreeHelix.Energy, None)
self.assertEqual(self.GivenEnergy.Energy,0.1)
self.assertEqual(self.TwoEnergies.Energy,2.1)
def test_EmptyPartners(self):
"""EmptyPartners should return list of 'None's of given length"""
self.assertEqual(EmptyPartners(0),[])
self.assertEqual(EmptyPartners(1),[None])
self.assertEqual(EmptyPartners(10),[None]*10)
def test_wuss_to_vienna(self):
"""wuss_to_vienna() should transform Wuss into Vienna"""
empty = WussStructure('.....')
normal = WussStructure('[.{[<...}}}}')
pseudo = WussStructure('[..AA..]..aa')
self.assertEqual(wuss_to_vienna(normal),'(.(((...))))')
self.assertEqual(wuss_to_vienna(empty),'.....')
self.assertEqual(wuss_to_vienna(pseudo),'(......)....')
def test_classify(self):
"""classify() should classify valid structures correctly"""
Empty = ''
NoPairs = '.....'
OneHelix = '((((()))))'
ManyHelices = '(..(((...)).((.(((((..))).)))..((((..))))))...)'
Ends = '..(.)..'
FirstEnd = '..((()))'
LastEnd = '((..((.))))...'
Internal = '(((...)))..((.)).'
#following structure is from p 25 of Eddy's WUSS description manual
Eddy = '..((((.(((...)))...((.((....))..)).)).))'
structs = [Empty, NoPairs, OneHelix, ManyHelices, Ends, \
FirstEnd, LastEnd, Internal, Eddy]
EmptyResult = ''
NoPairsResult = 'EEEEE'
OneHelixResult = 'SSSSSSSSSS'
ManyHelicesResult = 'SBBSSSLLLSSJSSBSSSSSLLSSSBSSSJJSSSSLLSSSSSSBBBS'
EndsResult = 'EESLSEE'
FirstEndResult = 'EESSSSSS'
LastEndResult = 'SSBBSSLSSSSEEE'
InternalResult = 'SSSLLLSSSFFSSLSSE'
#following structure is from p 25 of Eddy's WUSS description manual
Eddy = 'EESSSSJSSSLLLSSSJJJSSBSSLLLLSSBBSSJSSBSS'
results = [EmptyResult, NoPairsResult, OneHelixResult,
ManyHelicesResult, EndsResult, FirstEndResult, LastEndResult,
InternalResult, Eddy]
for s, r in zip(structs, results):
c = classify(s)
self.assertEqual(classify(s), r)
long_struct = ".((((((((((((((.((((((..((((.....)))))))))).))..))))))))))))....(((.((((.((((((((......((((((.((..(((((((....)))).)))..))))))))...))))))))...........(((((.(..(((((((((......((((((((((((.........))))))))))))....))))).))))..)..)))))..(((((((((((((((((((......(((((((((((((((((((((((((((((((...(((.......((((((((........)))))))).......)))...))))))))))))))))))))))))))))))).((((........(((((((((((((((((((...))))))))))))))))))).......)))).....((((((((((((((((((((((((((((((.(((...))).)))))))))))))))))))))))...........))))))).))))))))))))))))))).....)))).)))......"
#compare standalone method with classification from tree
c = classify(long_struct)
d = ViennaStructure(long_struct).toTree().classify()
self.assertEqual(c,d)
#Error is raised when trying to classify invalid structures
invalid_structure = '(((..)).))))(...)(...'
self.assertRaises(IndexError, classify, invalid_structure)
class ViennaNodeTests(TestCase):
"""Tests of the ViennaNode class."""
def setUp(self):
"""Instantiate some standard ViennaNodes."""
self.EmptyStr = ''
self.NoPairsStr = '.....'
self.OneHelixStr = '((((()))))'
self.ManyHelicesStr = '(..(((...)).((.(((((..))).)))..((((..))))))...)'
self.EndsStr = '..(.)..'
self.FirstEndStr = '..((()))'
self.LastEndStr = '((..((.))))...'
self.InternalStr = '(((...)))..((.)).'
#following structure is from p 25 of Eddy's WUSS description manual
self.EddyStr = '..((((.(((...)))...((.((....))..)).)).))'
#add in the tree versions by deleting trailing 'Str'
for s in self.__dict__.keys():
if s.endswith('Str'):
self.__dict__[s[:-3]] = \
ViennaStructure(self.__dict__[s]).toTree()
def test_str(self):
"""ViennaNode str should return Vienna-format string"""
for s in [self.EmptyStr, self.NoPairsStr, self.OneHelixStr,
self.ManyHelicesStr, self.EndsStr, self.InternalStr]:
self.assertEqual(str(ViennaStructure(s).toTree()), s)
#test with multiple-base helix in a node
r = StructureNode()
r.append(StructureNode())
r.append(StructureNode(Data=Stem(1,7,5)))
r[1].append(StructureNode())
r.append(StructureNode())
r.append(StructureNode())
r.renumber()
self.assertEqual(str(r), '.(((((.)))))..')
def test_classify(self):
"""ViennaNode classify should return correct classification string"""
self.assertEqual(self.Empty.classify(), '')
self.assertEqual(self.NoPairs.classify(), 'EEEEE')
self.assertEqual(self.OneHelix.classify(), 'SSSSSSSSSS')
self.assertEqual(self.ManyHelices.classify(), \
'SBBSSSLLLSSJSSBSSSSSLLSSSBSSSJJSSSSLLSSSSSSBBBS')
self.assertEqual(self.Ends.classify(), 'EESLSEE')
self.assertEqual(self.FirstEnd.classify(), 'EESSSSSS')
self.assertEqual(self.LastEnd.classify(), 'SSBBSSLSSSSEEE')
self.assertEqual(self.Internal.classify(), 'SSSLLLSSSFFSSLSSE')
self.assertEqual(self.Eddy.classify(), \
'EESSSSJSSSLLLSSSJJJSSBSSLLLLSSBBSSJSSBSS')
def test_renumber(self):
"""ViennaNode renumber should assign correct numbers to nodes"""
#should have no effect on empty structure
se = self.Empty
self.assertEqual(se.renumber(5), 5)
self.assertEqual((se.Start, se.End, se.Length), (None, None, 0))
#with no pairs, should number consecutively
sn = self.NoPairs
self.assertEqual(sn.renumber(5), 10)
self.assertEqual([i.Start for i in sn], [5, 6, 7, 8, 9])
self.assertEqual([i.End for i in sn], [None]*5)
self.assertEqual([i.Length for i in sn], [0]*5)
#spot checks on a complex structure
sm = self.ManyHelices
self.assertEqual(sm.renumber(5), 52)
s0 = sm[0]
self.assertEqual((s0.Start, s0.End, s0.Length), (5, 51, 1))
s5 = sm[0][2][2][0]
self.assertEqual(len(s5), 2)
self.assertEqual((s5.Start, s5.End, s5.Length), (18, 33, 1))
s6 = s5[0]
self.assertEqual((s6.Start, s6.End, s6.Length), (19,None,0))
#test with some helices of different lengths
root = StructureNode()
root.extend([StructureNode() for i in range(3)])
root.insert(1, StructureNode(Data=Stem(3, 7, 5)))
root.insert(3, StructureNode(Data=Stem(6,2,2)))
root.append(StructureNode())
self.assertEqual(root.renumber(0), 18)
self.assertEqual(len(root), 6)
curr = root[0]
self.assertEqual((curr.Start,curr.End,curr.Length), (0, None, 0))
curr = root[1]
self.assertEqual((curr.Start, curr.End, curr.Length), (1, 10, 5))
curr = root[2]
self.assertEqual((curr.Start, curr.End, curr.Length), (11, None, 0))
curr = root[3]
self.assertEqual((curr.Start, curr.End, curr.Length), (12, 15, 2))
curr = root[4]
self.assertEqual((curr.Start, curr.End, curr.Length), (16, None, 0))
curr = root[5]
self.assertEqual((curr.Start, curr.End, curr.Length), (17, None, 0))
def test_unpair(self):
"""StructureNode unpair should break a base pair and add correct nodes"""
i = self.Internal
self.assertEqual(i[0].unpair(), True)
self.assertEqual(str(i), '.((...))...((.)).')
e = self.Ends
self.assertEqual(e[0].unpair(), False)
self.assertEqual(str(e), self.EndsStr)
o = self.OneHelix
self.assertEqual(o[0].unpair(), True)
self.assertEqual(str(o), '.(((()))).')
self.assertEqual(o[1][0][0].unpair(), True)
self.assertEqual(str(o), '.((.().)).')
self.assertEqual(o[1].unpair(), True)
self.assertEqual(str(o), '..(.().)..')
self.assertEqual(o[2][1].unpair(), True)
self.assertEqual(str(o), '..(....)..')
self.assertEqual(o[2].unpair(), True)
self.assertEqual(str(o), '..........')
#test with multiple bases in helix
r = StructureNode()
r.append(StructureNode(Data=Stem(0,0, 5)))
r.renumber()
self.assertEqual(str(r), '((((()))))')
self.assertEqual(r[0].unpair(), True)
self.assertEqual(str(r), '.(((()))).')
def test_pairBefore(self):
"""StructureNode pairBefore should make a pair before the current node"""
#shouldn't be able to make any pairs if everything is paired already
o = self.OneHelix
for i in o:
self.assertEqual(i.pairBefore(), False)
n = self.NoPairs
#shouldn't be able to pair at the start...
self.assertEqual(n[0].pairBefore(), False)
#...or at the end...
self.assertEqual(n[-1].pairBefore(), False)
#...but should work OK in the middle
self.assertEqual(n[1].pairBefore(), True)
self.assertEqual(str(n), '(.)..')
e = self.Ends
self.assertEqual(e[2].pairBefore(), True)
self.assertEqual(e[1].pairBefore(), True)
self.assertEqual(str(e), '(((.)))')
self.assertEqual((e[0].Start, e[0].End, e[0].Length), (0,6,1))
def test_pairAfter(self):
"""StructureNode pairAfter should create pairs after a node"""
n = self.NoPairs
self.assertEqual(n.pairAfter(), True)
self.assertEqual(str(n), '(...)')
self.assertEqual(n[0].pairAfter(), True)
self.assertEqual(str(n), '((.))')
self.assertEqual(n[0][0].pairAfter(), False)
self.assertEqual(str(n), '((.))')
curr = n[0][0]
#check that child is correct
self.assertEqual(len(curr), 1)
self.assertEqual((curr[0].Start, curr[0].End, curr[0].Length), \
(2,None,0))
#check that pair is correct
self.assertEqual((curr.Start, curr.End, curr.Length), (1,3,1))
m = self.ManyHelices
n = m[0][2][0][0]
self.assertEqual(n.pairAfter(), True)
self.assertEqual(str(m), \
'(..((((.))).((.(((((..))).)))..((((..))))))...)')
self.assertEqual(n[0].pairAfter(), False)
def test_pairChildren(self):
"""StructureNode PairChildren should make the correct pairs"""
n = ViennaStructure('.....').toTree() #same as self.NoPairs
self.assertEqual(n.pairChildren(0, 4), True)
self.assertEqual(str(n), '(...)')
n = ViennaStructure('.....').toTree() #same as self.NoPairs
self.assertEqual(n.pairChildren(1, 4), True)
self.assertEqual(str(n), '.(..)')
n = ViennaStructure('.....').toTree() #same as self.NoPairs
#can't pair same object
self.assertEqual(n.pairChildren(1, 1), False)
self.assertEqual(str(n), '.....')
self.assertEqual(n.pairChildren(1, -1), True)
self.assertEqual(str(n), '.(..)')
#can't pair something already paired
self.assertEqual(n.pairChildren(0,1), False)
#IndexError if out of range
self.assertRaises(IndexError, n.pairChildren, 0, 5)
n.append(StructureNode())
n.append(StructureNode())
n.renumber()
self.assertEqual(str(n), '.(..)..')
self.assertEqual(n.pairChildren(0, -2), True)
self.assertEqual(str(n), '((..)).')
def test_expand(self):
"""StructureNode expand should extend helices."""
s = StructureNode(Data=(Stem(1, 10, 3)))
s.append(StructureNode())
#need to make a root node for consistency
r = StructureNode()
r.append(s)
self.assertEqual(str(s), '(((.)))')
s.expand()
self.assertEqual(str(s), '(((.)))')
self.assertEqual((s.Start, s.End, s.Length), (1, 10, 1))
n = s[0]
self.assertEqual((n.Start, n.End, n.Length), (2, 9, 1))
n = s[0][0]
self.assertEqual((n.Start, n.End, n.Length), (3, 8, 1))
n = s[0][0][0]
self.assertEqual((n.Start, n.End, n.Length), (None, None, 0))
s.renumber()
self.assertEqual((s.Start, s.End, s.Length), (0, 6, 1))
n = s[0]
self.assertEqual((n.Start, n.End, n.Length), (1, 5, 1))
n = s[0][0]
self.assertEqual((n.Start, n.End, n.Length), (2, 4, 1))
n = s[0][0][0]
self.assertEqual((n.Start, n.End, n.Length), (3, None, 0))
#check that it's not recursive
s[0][0].append(StructureNode(Data=Stem(20, 24, 2)))
s.expand()
n = s[0][0][-1]
self.assertEqual((n.Start, n.End, n.Length), (20, 24, 2))
n.expand()
self.assertEqual((n.Start, n.End, n.Length), (20, 24, 1))
n = n[0]
self.assertEqual((n.Start, n.End, n.Length), (21, 23, 1))
def test_expandAll(self):
"""StructureNode expandAll should act recursively"""
r = StructureNode()
r.append(StructureNode(Data=Stem(0, 6, 4)))
r.append(StructureNode(Data=Stem(0, 6, 3)))
r.append(StructureNode())
r[0].append(StructureNode())
r[0].append(StructureNode(Data=Stem(0,6,2)))
r[0][-1].append(StructureNode())
r.renumber()
self.assertEqual(str(r), '((((.((.))))))((())).')
r.expandAll()
self.assertEqual(str(r), '((((.((.))))))((())).')
expected_nodes = [
(None, None, 0),
(0, 13, 1),
(1, 12, 1),
(2, 11, 1),
(3, 10, 1),
(4, None, 0),
(5, 9, 1),
(6, 8, 1),
(7, None, 0),
(14, 19, 1),
(15, 18, 1),
(16, 17, 1),
(20, None, 0),
]
for obs, exp in zip(r.traverse(), expected_nodes):
self.assertEqual((obs.Start, obs.End, obs.Length), exp)
def test_collapse(self):
"""StructureNode collapse should collapse consecutive pairs from self"""
one = ViennaStructure('(.)').toTree()
self.assertEqual(one.collapse(), False)
self.assertEqual(str(one), '(.)')
two = ViennaStructure('((.))').toTree()
#can't collapse root node
self.assertEqual(two.collapse(), False)
#should be able to collapse next node
self.assertEqual(two[0].collapse(), True)
self.assertEqual((two[0].Start, two[0].End, two[0].Length), (0,4,2))
self.assertEqual(str(two), '((.))')
three = ViennaStructure('(((...)))..').toTree()
self.assertEqual(three[0].collapse(), True)
self.assertEqual((three[0].Start, three[0].End, three[0].Length), \
(0,8,3))
self.assertEqual(str(three), '(((...)))..')
self.assertEqual(three[0].collapse(), False)
self.assertEqual(three[-1].collapse(), False)
oh = self.OneHelix
self.assertEqual(oh[0].collapse(), True)
self.assertEqual(str(oh), '((((()))))')
def test_collapseAll(self):
"""StructureNode collapseAll should collapse consecutive pairs"""
for s in [self.Empty, self.NoPairs, self.OneHelix, self.ManyHelices,\
self.Ends, self.FirstEnd, self.LastEnd, self.Internal, self.Eddy]:
before = str(s)
s.collapseAll()
after = str(s)
self.assertEqual(after, before)
oh = self.OneHelix[0]
self.assertEqual((oh.Start, oh.End, oh.Length), (0,9,5))
m_obs = self.ManyHelices.traverse()
m_exp = [
(None, None, 0),
(0, 46, 1),
(1, None, 0),
(2, None, 0),
(3, 42, 1),
(4, 10, 2),
(6, None, 0),
(7, None, 0),
(8, None, 0),
(11, None, 0),
(12, 41, 1),
(13, 28, 1),
(14, None, 0),
(15, 27, 2),
(17, 24, 3),
(20, None, 0),
(21, None, 0),
(25, None, 0),
(29, None, 0),
(30, None, 0),
(31, 40, 4),
(35, None, 0),
(36, None, 0),
(43, None, 0),
(44, None, 0),
(45, None, 0),
(46, None, 0),
]
for obs, exp in zip([(i.Start, i.End, i.Length) for i in m_obs], m_exp):
self.assertEqual(obs, exp)
def test_breakBadPairs(self):
"""StructureNode breakBadPairs should eliminate mispaired bases."""
oh_str = ViennaStructure(self.OneHelixStr)
#no change if all pairs valid
oh = oh_str.toTree()
oh.breakBadPairs(Rna('CCCCCGGGGG'))
self.assertEqual(str(oh), str(oh_str))
#break everything if all pairs invalid
oh.breakBadPairs(Rna('CCCCCAAAAA'))
self.assertEqual(str(oh), '..........')
#break a single pair
oh = oh_str.toTree()
oh.breakBadPairs(Rna('GCCCCGGGGG'))
self.assertEqual(str(oh), '.(((()))).')
#break two pairs
oh = oh_str.toTree()
oh.breakBadPairs(Rna('GCCCCCGGGG'))
self.assertEqual(str(oh), '.(((..))).')
#break internal pairs
oh = oh_str.toTree()
oh.breakBadPairs(Rna('GCCGCGGGGG'))
self.assertEqual(str(oh), '.((.().)).')
#repeat with multiple independent helices
th_str = ViennaStructure('((.)).((.))')
th = th_str.toTree()
th.breakBadPairs(Rna('CCUGGCUUCGG'))
self.assertEqual(str(th), th_str)
th.breakBadPairs(Rna('CGUAGCAGUUU'))
self.assertEqual(str(th), '(...).((.))')
th = th_str.toTree()
th.breakBadPairs(Rna('UUUUUUUUUUU'))
self.assertEqual(str(th), '...........')
def test_extendHelix(self):
"""StructureNode extendHelix should extend the helix as far as possible
"""
#single paired node is root[4]
op_str = ViennaStructure('....(......)...')
op = op_str.toTree()
#can't extend if base pairs not allowed
op[4].extendHelix(Rna('AAAAAAAAAAAAAAA'))
self.assertEqual(str(op), op_str)
#should extend a pair 5'
op[4].extendHelix(Rna('AAACCAAAAAAGGAA'))
self.assertEqual(str(op), '...((......))..')
#should extend multiple pairs 5'
op = op_str.toTree()
op[4].extendHelix(Rna('CCCCCUUUUUUGGGG'))
self.assertEqual(str(op), '.((((......))))')
#should extend a pair 3', but must leave > 2-base loop
op = op_str.toTree()
op[4].extendHelix(Rna('AAAACCCCGGGGAAA'))
self.assertEqual(str(op), '....((....))...')
op[4][0].insert(1, StructureNode(Data=Stem(Start=1,End=1,Length=1)))
op.renumber()
self.assertEqual(str(op), '....((.()...))...')
op[4][0].extendHelix(Rna( 'AAAACCCUACGGGGAAA'))
self.assertEqual(str(op), '....(((()..)))...')
#should extend a pair in both directions if possible
op = op_str.toTree()
op[4].extendHelix(Rna('AAACCCAAAAGGGAA'))
self.assertEqual(str(op), '...(((....)))..')
def test_extendHelices(self):
"""StructureNode extendHelices should extend all helices"""
e = ViennaStructure('........')
t = e.toTree()
t.extendHelices(Rna('CCCCCCCCCC'))
self.assertEqual(str(t), e)
#no pairs if sequence can't form them
s = ViennaStructure('(.....(...)..)...((.....))...')
r = Rna('AAAAAAAAAAAAAAAAAAAAAAAAAAAAA')
t = s.toTree()
t.extendHelices(r)
self.assertEqual(str(t), s)
#should be able to extend a single helix
s = ViennaStructure('(.....(...)..)...((.....))...')
r = Rna('CAAAAACAAAGAAGCCCCCCCAGGGGGGG')
t = s.toTree()
t.extendHelices(r)
self.assertEqual(str(t), '(.....(...)..)((((((...))))))')
#should be able to extend multiple helices
s = ViennaStructure('(.....(...)..)...((.....))...')
r = Rna('AAAAACCCAGGGUUCCCCCAUAAAGGGAA')
t = s.toTree()
t.extendHelices(r)
self.assertEqual(str(t), '((...((...))))..(((.....)))..')
def test_fitSeq(self):
"""StructureNode fitSeq should adjust structure to match sequence"""
#this is just a minimal test, since we know that both breakBadPairs()
#and extendHelices() work fine with more extensive tests.
s = ViennaStructure('..(((.....)))......(((.....)))...')
r = Rna( 'UCCCCACUGAGGGGUUUGGGGGGUUUUCGCCCU')
t = s.toTree()
t.fitSeq(r)
self.assertEqual(str(t), '.((((.....))))...(((.((...)).))).')
#run the test suites if invoked as a script from the command line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_struct/test_selection.py 000644 000765 000024 00000004202 12024702176 023362 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import os
try:
from cogent.util.unit_test import TestCase, main
from cogent.parse.pdb import PDBParser
from cogent.struct.selection import einput, select
except ImportError:
from zenpdb.cogent.util.unit_test import TestCase, main
from zenpdb.cogent.parse.pdb import PDBParser
from zenpdb.cogent.struct.selection import einput, select
__author__ = "Marcin Cieslik"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Development"
class AnnotationTest(TestCase):
"""tests selecting entities"""
def setUp(self):
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
def test_einput(self):
"""tests einput."""
structures = einput(self.input_structure, 'S')
models = einput(self.input_structure, 'M')
chains = einput(self.input_structure, 'C')
residues = einput(self.input_structure, 'R')
atoms = einput(self.input_structure, 'A')
self.assertEquals(structures.level, 'H')
self.assertEquals(models.level, 'S')
self.assertEquals(chains.level, 'M')
self.assertEquals(residues.level, 'C')
self.assertEquals(atoms.level, 'R')
atoms2 = einput(models, 'A')
self.assertEquals(atoms, atoms2)
atoms3 = einput(chains, 'A')
self.assertEquals(atoms, atoms3)
structures2 = einput(atoms, 'S')
self.assertEquals(self.input_structure, structures2.values()[0])
residues2 = einput(atoms, 'R')
self.assertEquals(residues, residues2)
def test_select(self):
"""tests select."""
water = select(self.input_structure, 'R', 'H_HOH', 'eq', 'name')
for residue in water:
self.assertTrue(residue.name == 'H_HOH')
non_water = select(self.input_structure, 'R', 'H_HOH', 'ne', 'name')
for residue in non_water:
self.assertTrue(residue.name != 'H_HOH')
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_seqsim/__init__.py 000644 000765 000024 00000000463 12024702176 022057 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_seqsim']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Developmentn"
PyCogent-1.5.3/tests/test_seqsim/test_analysis.py 000644 000765 000024 00000030413 12024702176 023200 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for analysis.py: substitution matrix analysis code."""
from cogent.seqsim.analysis import tree_threeway_counts, \
tree_twoway_counts, counts_to_probs, probs_to_rates, \
tree_threeway_rates, tree_twoway_rates, \
rates_to_array, multivariate_normal_prob
from cogent.seqsim.tree import RangeNode
from cogent.core.usage import DnaPairs, ABPairs
from cogent.seqsim.usage import Rates, Counts, Probs
from numpy import array, average, ones, zeros, float64, ravel, diag, any
from numpy.random import random, randint
from copy import deepcopy
from cogent.parse.tree import DndParser
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class analysisTests(TestCase):
"""Tests of top-level functions."""
def setUp(self):
"""Make a couple of standard trees"""
self.t1 = DndParser('((a,(b,c)),(d,e))', RangeNode)
#selt.t1 indices: ((0,(1,2)5)6,(3,4)7)8
def test_threeway_counts(self):
"""threeway_counts should produce correct count matrix"""
self.t1.makeIdIndex()
ind = self.t1.IdIndex
ind[0].Sequence = array([0,0,0])
ind[1].Sequence = array([0,1,0])
ind[2].Sequence = array([1,0,1])
ind[3].Sequence = array([1,1,0])
ind[4].Sequence = array([1,1,1])
depths = self.t1.leafLcaDepths()
result = tree_threeway_counts(self.t1, depths, ABPairs)
#check we got the right number of comparisons
self.assertEqual(len(result), 20)
#check we got the right keys
for k in [(1,2,0),(2,1,0),(0,1,3),(1,0,3),(0,1,4),(1,0,4),(0,2,3),\
(2,0,3),(0,2,4),(2,0,4),(1,2,3),(2,1,3),(1,2,4),(2,1,4),(3,4,1),\
(4,3,1),(3,4,2),(4,3,2)]:
assert k in result
#spot-check a few results
self.assertEqual(result[(1,2,0)]._data, array([[2,1],[0,0]]))
self.assertEqual(result[(2,1,0)]._data, array([[1,2],[0,0]]))
self.assertEqual(result[(2,1,3)]._data, array([[0,1],[1,1]]))
def test_twoway_counts(self):
"""twoway_counts should produce correct count matrix"""
self.t1.makeIdIndex()
ind = self.t1.IdIndex
ind[0].Sequence = array([0,0,0])
ind[1].Sequence = array([0,1,0])
ind[2].Sequence = array([1,0,1])
ind[3].Sequence = array([1,1,0])
ind[4].Sequence = array([1,1,1])
depths = self.t1.leafLcaDepths()
#check that it works with averaging
result = tree_twoway_counts(self.t1, ABPairs)
#check we got the right number of comparisons: average by default
self.assertEqual(len(result), 10)
#check we got the right keys
for k in [(0,1),(0,2),(0,3),(0,4),(1,2),(1,3),(1,4),(2,3),(2,4),(3,4)]:
assert k in result
#spot-check a few results
self.assertEqual(result[(0,1)]._data, array([[2,.5],[.5,0]]))
self.assertEqual(result[(2,3)]._data, array([[0,1],[1,1]]))
#check that it works when we don't average
result = tree_twoway_counts(self.t1, ABPairs, average=False)
self.assertEqual(len(result), 20)
#check we got the right keys
for k in [(0,1),(0,2),(0,3),(0,4),(1,2),(1,3),(1,4),(2,3),(2,4),(3,4)]:
assert k in result
#reverse should be in result too
assert (k[1],k[0]) in result
#spot-check values
self.assertEqual(result[(0,1)]._data, array([[2,1],[0,0]]))
self.assertEqual(result[(1,0)]._data, array([[2,0],[1,0]]))
def test_counts_to_probs(self):
"""counts_to_probs should skip cases with zero rows"""
counts = {
(0,1): Counts(array([[0,1],[1,0]]), ABPairs),
(1,2): Counts(array([[0,0],[1,0]]), ABPairs), #bad row
(0,3): Counts(array([[0,0],[0,0]]), ABPairs), #bad row
(0,4): Counts(array([[0.0,0.0],[0.0,0.0]]), ABPairs), #bad row
(0,5): Counts(array([[0.1,0.3],[0.0,0.0]]), ABPairs), #bad row
(3,4): Counts(array([[0.1,0.3],[0.4,0.1]]), ABPairs),
(2,1): Counts(array([[0,5],[1,0]]), ABPairs),
}
result = counts_to_probs(counts)
self.assertEqual(len(result), 3)
self.assertFloatEqual(result[(0,1)]._data, array([[0,1],[1,0]]))
self.assertFloatEqual(result[(3,4)]._data, \
array([[0.25,0.75],[0.8,0.2]]))
self.assertFloatEqual(result[(2,1)]._data, array([[0,1],[1,0]]))
def test_probs_to_rates(self):
"""probs_to_rates converts probs to rates, omitting problem cases"""
probs = dict([(i, Probs.random(DnaPairs)) for i in range(100)])
rates = probs_to_rates(probs)
#check we got at most the same number of items as in probs
assert len(rates) <= len(probs)
#check that we didn't get anything bad
vals = rates.values()
for v in vals:
assert not v.isSignificantlyComplex()
#check that we didn't miss anything good
for key, val in probs.items():
if key not in rates:
try:
r = val.toRates()
print r.isValid()
assert r.isSignificantlyComplex() or (not r.isValid())
except (ZeroDivisionError, OverflowError, ValueError):
pass
def test_rates_to_array(self):
"""rates_to_array should pack rates into array correctly"""
m1 = array([[-1,1,1,1],[2,-2,2,2],[3,3,-3,3],[1,2,3,-4]])
m2 = m1 * 2
m3 = m1 * 0.5
m4 = zeros((4,4))
m5 = array([0,0])
r1, r2, r3, r4, r5 = [Rates(i, DnaPairs) for i in m1,m2,m3,m4,m5]
data = {(0,1,0):r1, (1,2,0):r2, (2,0,0):r3, (2,1,1):r4}
#note that array can be, but need not be, floating point
to_fill = zeros((3,3,3,16), 'float64')
result = rates_to_array(data, to_fill)
#check that the thnigs we deliberately set are OK
self.assertEqual(to_fill[0][1][0], ravel(m1))
self.assertNotEqual(to_fill[0][1][0], ravel(m2))
self.assertEqual(to_fill[1,2,0], ravel(m2))
self.assertEqual(to_fill[2][0][0], ravel(m3))
self.assertEqual(to_fill[2][1][1], ravel(m4))
#check that everything else is zero
nonzero = [(0,1,0),(1,2,0),(2,0,0)]
for x in [(i, j, k) for i in range(3) for j in range(3) \
for k in range(3)]:
if x not in nonzero:
self.assertEqual(to_fill[x], zeros(16))
#check that it works omitting the diagonal
to_fill = zeros((3,3,3,12), 'float64')
result = rates_to_array(data, to_fill, without_diagonal=True)
#check that the thnigs we deliberately set are OK
m1_nodiag = array([[1,1,1],[2,2,2],[3,3,3],[1,2,3]])
self.assertEqual(to_fill[0][1][0], ravel(m1_nodiag))
self.assertNotEqual(to_fill[0][1][0], ravel(m1_nodiag*2))
self.assertEqual(to_fill[1,2,0], ravel(m1_nodiag*2))
self.assertEqual(to_fill[2][0][0], ravel(m1_nodiag*0.5))
self.assertEqual(to_fill[2][1][1], zeros(12))
#check that everything else is zero
nonzero = [(0,1,0),(1,2,0),(2,0,0)]
for x in [(i, j, k) for i in range(3) for j in range(3) \
for k in range(3)]:
if x not in nonzero:
self.assertEqual(to_fill[x], zeros(12))
def test_tree_threeway_rates(self):
"""tree_threeway_rates should give plausible results on rand trees"""
#note: the following fails occasionally, but repeating it 5 times
#and checking that one passes is fairly safe
for i in range(5):
try:
t = self.t1
t.assignLength(0.05)
t.Q = Rates.random(DnaPairs).normalize()
t.assignQ()
t.assignP()
t.evolve(randint(0,4,100))
t.makeIdIndex()
depths = t.leafLcaDepths()
result = tree_threeway_rates(t, depths)
self.assertEqual(result.shape, (5,5,5,16))
#check that row sums are 0
for x in [(i,j,k) for i in range(5) for j in range(5) \
for k in range(5)]:
self.assertFloatEqual(sum(result[x]), 0)
assert any(result)
#check that it works without_diag
result = tree_threeway_rates(t, depths, without_diag=True)
self.assertEqual(result.shape, (5,5,5,12))
#check that it works with/without normalize
#default: no normalization, so row sums shouldn't be 1 after
#omitting diagonal
result = tree_threeway_rates(t, depths, without_diag=True)
self.assertEqual(result.shape, (5,5,5,12))
for x in [(i,j,k) for i in range(5) for j in range(5) \
for k in range(5)]:
assert sum(result[x]) == 0 or abs(sum(result[x]) - 1) > 0.01
#...but if we tell it to normalize, row sums should be nearly 1
#after omitting diagonal
result = tree_threeway_rates(t, depths, without_diag=True, \
normalize=True)
self.assertEqual(result.shape, (5,5,5,12))
for x in [(i,j,k) for i in range(5) for j in range(5) \
for k in range(5)]:
s = sum(result[x])
if s != 0:
self.assertFloatEqual(s, 1)
break
except AssertionError:
pass
def test_tree_twoway_rates(self):
"""tree_twoway_rates should give plausible results on rand trees"""
t = self.t1
t.assignLength(0.05)
t.Q = Rates.random(DnaPairs).normalize()
t.assignQ()
t.assignP()
t.evolve(randint(0,4,100))
t.makeIdIndex()
result = tree_twoway_rates(t)
self.assertEqual(result.shape, (5,5,16))
#check that row sums are 0
for x in [(i,j) for i in range(5) for j in range(5)]:
self.assertFloatEqual(sum(result[x]), 0)
#need to make sure we didn't just get an empty array
self.assertGreaterThan((abs(result)).sum(), 0)
#check that it works without_diag
result = tree_twoway_rates(t, without_diag=True)
self.assertEqual(result.shape, (5,5,12))
#check that it works with/without normalize
#default: no normalization, so row sums shouldn't be 1 after omitting
#diagonal
result = tree_twoway_rates(t, without_diag=True)
self.assertEqual(result.shape, (5,5,12))
#check that the row sums are not 1 before normalization (note that they
#can be zero, though)
sums_before = []
for x in [(i,j) for i in range(5) for j in range(5)]:
curr_sum = sum(result[x])
sums_before.append(curr_sum)
#...but if we tell it to normalize, row sums should be nearly 1
#after omitting diagonal
result = tree_twoway_rates(t, without_diag=True, \
normalize=True)
self.assertEqual(result.shape, (5,5,12))
sums_after = []
for x in [(i,j) for i in range(5) for j in range(5)]:
curr_sum = sum(result[x])
sums_after.append(curr_sum)
if curr_sum != 0:
self.assertFloatEqual(curr_sum, 1)
try:
self.assertFloatEqual(sums_before, sums_after)
except AssertionError:
pass
else:
raise AssertionError, "Expected different arrays before/after norm"
def test_multivariate_normal_prob(self):
"""Multivariate normal prob should match R results"""
cov = array([[3,1,2],[1,5,4],[2,4,6]])
a = array([0,0,0])
b = array([1,1,1])
c = array([0.1, 0.2, 0.3])
small_cov = cov/10.0
mvp = multivariate_normal_prob
self.assertFloatEqual(mvp(a, cov), 0.01122420)
self.assertFloatEqual(mvp(a, cov, b), 0.009018894)
self.assertFloatEqual(mvp(a, small_cov, b), 0.03982319)
self.assertFloatEqual(mvp(c, small_cov, b), 0.06091317)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_seqsim/test_birth_death.py 000644 000765 000024 00000026676 12024702176 023652 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
#file test_birth_death.py
"""Unit tests of birth_death.py: implementation of the birth-death model.
"""
from cogent.seqsim.birth_death import ExtinctionError, TooManyTaxaError, \
BirthDeathModel, DoubleBirthDeathModel
from cogent.util.unit_test import TestCase, main, FakeRandom
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Mike Robeson"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class BirthDeathModelTests(TestCase):
"""Tests of the BirthDeathModel class, which makes birth-death trees."""
def test_init_deafults(self):
"""BirthDeathModel should init correctly w/ default params"""
m = BirthDeathModel(0.1, 0.2, 0.3)
self.assertEqual(m.BirthProb, 0.1)
self.assertEqual(m.DeathProb, 0.2)
self.assertEqual(m.TimePerStep, 0.3)
self.assertEqual(m.MaxStep, 1000)
self.assertEqual(m.MaxTaxa, None)
self.assertEqual(m.CurrStep, 0)
self.assertEqual(m.Tree.__class__, m.NodeClass)
self.assertEqual(m.CurrTaxa, [m.Tree])
self.assertEqual(m.ChangedBirthProb,None)
self.assertEqual(m.ChangedDeathProb,None)
self.assertEqual(m.ChangedBirthStep,None)
self.assertEqual(m.ChangedDeathStep,None)
self.assertEqual(m.CurrBirthProb, 0.1)
self.assertEqual(m.CurrDeathProb, 0.2)
def test_init_bad(self):
"""BirthDeathModel should raise exceptions on init with bad data"""
#BirthProb and DeathProb must be probabilities between 0 and 1
self.assertRaises(ValueError, BirthDeathModel, -1, 0.2, 0.3)
self.assertRaises(ValueError, BirthDeathModel, 2, 0.2, 0.3)
self.assertRaises(ValueError, BirthDeathModel, 0.1, -1, 0.3)
self.assertRaises(ValueError, BirthDeathModel, 0.1, 2, 0.3)
#TimePerStep can't be negative or 0
self.assertRaises(ValueError, BirthDeathModel, 0.1, 0.2, -1)
self.assertRaises(ValueError, BirthDeathModel, 0.1, 0.2, 0)
def test_init_extras(self):
"""BirthDeathModel should init OK with extra params"""
m = BirthDeathModel(BirthProb=0.1, DeathProb=0.2, TimePerStep=0.3, \
ChangedBirthProb=0.4, ChangedDeathProb=0.3, ChangedBirthStep=3,\
ChangedDeathStep=4, MaxStep=5, MaxTaxa=10)
self.assertEqual(m.BirthProb, 0.1)
self.assertEqual(m.DeathProb, 0.2)
self.assertEqual(m.TimePerStep, 0.3)
self.assertEqual(m.ChangedBirthProb, 0.4)
self.assertEqual(m.ChangedDeathProb, 0.3)
self.assertEqual(m.ChangedBirthStep, 3)
self.assertEqual(m.ChangedDeathStep, 4)
self.assertEqual(m.MaxStep, 5)
self.assertEqual(m.MaxTaxa, 10)
self.assertEqual(m.CurrStep, 0)
self.assertEqual(m.Tree.__class__, m.NodeClass)
self.assertEqual(m.CurrTaxa, [m.Tree])
def test_step(self):
"""BirthDeathModel step should match hand-calculated results"""
m = BirthDeathModel(BirthProb=0.1, DeathProb=0.2, TimePerStep=1)
born_and_died = FakeRandom([0],True)
born_only = FakeRandom([1,0],True)
died_only = FakeRandom([0,1],True)
neither = FakeRandom([1],True)
kill_alternate = FakeRandom([0,1,1,1], True)
born_alternate = FakeRandom([1,1,1,0], True)
#check that with neither birth nor death, we just continue
m.step(neither)
self.assertEqual(len(m.Tree.Children), 0)
#check that with born_only we get a duplication
m.step(born_only)
self.assertEqual(len(m.Tree.Children), 2)
assert m.Tree not in m.CurrTaxa
for i in m.CurrTaxa:
assert i.Parent is m.Tree
self.assertEqual(i.Length, 1)
#check that with a second round of born_only we duplicate again
m.step(born_only)
self.assertEqual(len(m.Tree.Children), 2)
self.assertEqual(len(list(m.Tree.traverse())), 4)
for i in m.Tree.traverse():
self.assertEqual(i.Length, 1)
for i in m.Tree.Children:
self.assertEqual(i.Length, 1)
#check that branch lengths add correctly
for i in range(4):
m.step(neither)
self.assertEqual(len(m.CurrTaxa), 4)
self.assertEqual(len(m.Tree.Children), 2)
self.assertEqual(len(list(m.Tree.traverse())), 4)
for i in m.Tree.traverse():
self.assertEqual(i.Length, 5)
for i in m.Tree.Children:
self.assertEqual(i.Length, 1)
#check that we can kill offspring correctly
m.step(kill_alternate)
self.assertEqual(len(m.CurrTaxa), 2)
#make sure we killed the right children
m.Tree.assignIds()
for i in m.Tree.Children:
#note that killing a child doesn't remove it, just stops it changing
self.assertEqual(len(i.Children), 2)
self.assertEqual(i.Children[0].Length, 5)
self.assertEqual(i.Children[1].Length, 6)
self.assertEqual([i.Length for i in m.Tree.traverse()], \
[5,6,5,6])
#make sure that born_and_died does the same thing as neither
m.step(born_and_died)
self.assertEqual([i.Length for i in m.Tree.traverse()], \
[5,7,5,7])
m.step(neither)
self.assertEqual([i.Length for i in m.Tree.traverse()], \
[5,8,5,8])
#check that only CurrTaxa are brought forward
self.assertEqual([i.Length for i in m.CurrTaxa], [8,8])
#check that we can duplicate a particular taxon
m.step(born_alternate)
self.assertEqual([i.Length for i in m.CurrTaxa], [9,1,1])
self.assertEqual(m.CurrTaxa[1].Parent.Length, 8)
#check that we can kill 'em all
m.step(died_only)
self.assertEqual(len(m.CurrTaxa), 0)
def test_prob_step_check(self):
"""prob_check and step_check should return error when out of bounds.
Prob values should be between zero and one
Step values should be greater than zero
"""
#ChangedBirthProb = -0.1 , raises ValueError
self.assertRaises(ValueError, BirthDeathModel, 0.1, 0.2, 0.3,\
ChangedBirthProb=-0.1,ChangedBirthStep=3,ChangedDeathProb=0.3,\
ChangedDeathStep=4, MaxStep=5)
#ChangedBirthStep = 0 , raises ValueError
self.assertRaises(ValueError, BirthDeathModel, 0.1, 0.2, 0.3,\
ChangedBirthProb=0.6,ChangedBirthStep=0,ChangedDeathProb=0.3,\
ChangedDeathStep=4, MaxStep=5)
#ChangedDeathProb = 2 , raises ValueError
self.assertRaises(ValueError, BirthDeathModel, 0.1, 0.2, 0.3,\
ChangedBirthProb=0.6,ChangedBirthStep=3,ChangedDeathProb=2,\
ChangedDeathStep=4, MaxStep=5)
#ChangedDeathStep = -1 , raises ValueError
self.assertRaises(ValueError, BirthDeathModel, 0.1, 0.2, 0.3,\
ChangedBirthProb=0.6,ChangedBirthStep=3,ChangedDeathProb=0.3,\
ChangedDeathStep=-1, MaxStep=5)
def test_timeOk(self):
"""BirthDeathModel TimeOk should return True if time not exceeded"""
b = BirthDeathModel(0.1, 0.2, 0.3, MaxStep=5)
assert b.timeOk()
b.CurrStep = 4
assert b.timeOk()
b.CurrStep = 5
assert not b.timeOk()
b.CurrStep = 1000
assert not b.timeOk()
b.MaxStep = None
assert b.timeOk()
b.MaxStep = 1001
assert b.timeOk()
b.step()
assert not b.timeOk()
def test_taxaOk(self):
"""BirthDeathModel TaxaOk should return True if taxa not exceeded"""
b = BirthDeathModel(0.1, 0.2, 0.3, MaxTaxa=5)
born_alternate = FakeRandom([1,1,1,0], True)
born_only = FakeRandom([1,0],True)
kill_only = FakeRandom([0,1,0,1], True)
#start off with single taxon
assert b.taxaOk()
#taxa are OK if there are a few
b.step(born_only) #now 2 taxa
assert b.taxaOk()
b.step(born_only) #now 4 taxa
assert b.taxaOk()
b.step(born_only) #now 8 taxa
assert not b.taxaOk()
b.MaxTaxa = 8
assert not b.taxaOk()
b.MaxTaxa = 9
assert b.taxaOk()
b.MaxTaxa = 17
assert b.taxaOk()
b.step(born_only)
assert b.taxaOk()
b.step(born_only)
assert not b.taxaOk()
#ok if no maximum
b.MaxTaxa = None
assert b.taxaOk()
#not ok if there are no taxa left
b.step(kill_only)
assert not b.taxaOk()
#still not OK if not MaxTaxa
b.MaxTaxa = None
assert not b.taxaOk()
def test_call_exact(self):
"""BirthDeathModel call should produce right # taxa when exact"""
m = BirthDeathModel(0.01, 0.005, 0.1, MaxTaxa=10)
for i in range(10):
try:
result = m(filter=True, exact=True)
self.assertEqual(len(list(result.traverse())), 10)
except (TooManyTaxaError, ExtinctionError), e:
pass
def test_call(self):
"""BirthDeathModel call should produce hand-calculated trees"""
m = BirthDeathModel(0.01, 0.005, 0.1, MaxTaxa=10)
r = FakeRandom(\
[1,0,\
1,1, 1,1,\
1,0, 0,0,\
0,0, 0,0, 1,0,\
0,0, 0,0, 0,1, 0,0, \
1,0, 0,0, 0,0,\
1,0, 0,0, 0,0, 1,0, \
1,0, 1,0, 0,1, 1,1, 1,0, 1,0, \
1,1, 1,1, 1,1, 1,1, 1,0, 1,1, 1,1, 1,1, 1,1], True)
m = BirthDeathModel(0.1, 0.5, 1, MaxTaxa=10)
result = m(filter=False, random_f=r)
self.assertEqual([i.Length for i in result.traverse()], \
[2,2,2,2,2,1,1,1,2,2,2,2])
#try it with pruning
m = BirthDeathModel(0.1, 0.5, 1, MaxTaxa=10)
result = m(filter=True, random_f=r)
self.assertEqual([i.Length for i in result.traverse()], \
[2,2,2,2,1,1,2,2,2,2])
#try it with fewer taxa
m = BirthDeathModel(0.1, 0.5, 1, MaxTaxa=4)
result = m(filter=True, random_f=r)
self.assertEqual([i.Length for i in result.traverse()], \
[2,2,1,1])
def test_changed_values_step(self):
"""Tests if values changed at specified steps in step().
Note, in m.step() CurrStep is logically tested one step later.
"""
m = BirthDeathModel( 0.1, 0.2, 0.3,ChangedBirthProb=0.6,\
ChangedBirthStep=3,ChangedDeathProb=0.3,ChangedDeathStep=4,\
MaxStep=5)
# all values should be as initialized
m.step()
assert m.CurrStep == 1
assert m.BirthProb == 0.1
assert m.DeathProb == 0.2
assert m.CurrBirthProb == 0.1
assert m.CurrDeathProb == 0.2
# continue 2 steps
m.step()
m.step()
# when logically evaluated CurrBirthProb should change
# from 0.1 to 0.6
m.step()
assert m.CurrStep == 4
assert m.BirthProb == 0.1
assert m.DeathProb == 0.2
assert m.CurrBirthProb == 0.6
assert m.CurrDeathProb == 0.2
# All values other than CurrStep should be as above
# except that CurrDeathProb should change from 0.2 to 0.3
m.step()
assert m.CurrStep == 5
assert m.BirthProb == 0.1
assert m.DeathProb == 0.2
assert m.CurrBirthProb == 0.6
assert m.CurrDeathProb == 0.3
class DoubleBirthDeathTests(TestCase):
"""Tests of the double birth-death model."""
def test_double_birth_death(self):
"""double_birth_death should run without errors"""
pass
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_seqsim/test_markov.py 000644 000765 000024 00000012334 12024702176 022656 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env/python
"""test_markov.py: tests of the MarkovGenerator class.
"""
from cogent.seqsim.markov import MarkovGenerator
from StringIO import StringIO
from operator import mul
from sys import path
from cogent.util.unit_test import TestCase, main
from numpy import array
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Jesse Zaneveld", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Development"
class MarkovGeneratorTests(TestCase):
"""Tests of the MarkovGenerator class."""
def setUp(self):
"""Define a few well-known frequencies."""
self.single = MarkovGenerator(['UUUUUUUUUU'], order=0)
self.equal = MarkovGenerator(['UUUUUCCCCC'], order=0)
self.unequal_0 = MarkovGenerator(['UCCCCCCCCC'], order=0)
self.unequal_1 = MarkovGenerator(['UCCCCCCCCC'], order=-1)
self.pairs = MarkovGenerator(['UCAUCAUCAUCAUCA'], order=1)
self.randquads=MarkovGenerator(['AACCUAUCUACUACUAUCUUCAUAUUCC']\
,order=3, calc_entropy=True, delete_bad_suffixes=False)
self.empty = MarkovGenerator('', order=0)
self.linebreaks= MarkovGenerator(StringIO('abb\nbcc\nd\n'))
self.dinucs=MarkovGenerator(['ATACATAC'],order=1)
self.orderfive=MarkovGenerator(['AAAAAGAAAAATAAAAAGAAAAAT'],order=5)
def test_init(self):
"""MarkovGenerator init should give right frequency distributions."""
self.assertEqual(self.empty.Frequencies, {})
self.assertEqual(self.single.Frequencies, {'':{'U':1.0}})
self.assertEqual(self.equal.Frequencies, {'':{'U':0.5,'C':0.5}})
self.assertEqual(self.unequal_0.Frequencies, {'':{'U':0.1,'C':0.9}})
self.assertEqual(self.unequal_1.Frequencies, {'':{'U':0.5, 'C':0.5}})
self.assertEqual(self.pairs.Frequencies, \
{'U':{'C':1},'C':{'A':1},'A':{'U':1}})
#check that recalculating the frequencies doesn't break anything
self.pairs.calcFrequencies()
self.assertEqual(self.pairs.Frequencies, \
{'U':{'C':1},'C':{'A':1},'A':{'U':1}})
exp={'AAC':{'C':1},'ACC':{'U':1},'CCU':{'A':1},'CUA':{'U':0.5,'C':0.5},\
'UAU':{'U':1/3.0,'C':2/3.0},'AUC':{'U':1},'UCU':{'U':0.5,'A':0.5},\
'UAC':{'U':1},'ACU':{'A':1},'CUU':{'C':1},'UUC':{'C':0.5,'A':0.5},\
'UCA':{'U':1},'CAU':{'A':1},'AUA':{'U':1},'AUU':{'C':1},
}
obs = self.randquads.Frequencies
self.assertFloatEqual(obs, exp)
#check that resetting linebreaks has the desired effect
self.assertEqual(self.linebreaks.Frequencies, \
{'a':{'b':1},'b':{'b':0.5,'c':0.5},'c':{'c':1}})
self.linebreaks.Linebreaks = True
self.linebreaks.Text.seek(0)
self.linebreaks.calcFrequencies()
#NOTE: current algorithm won't extend over line breaks. If you want
#to force use of line breaks, read into a single string.
self.assertEqual(self.linebreaks.Frequencies, \
{'a':{'b':1},'b':{'b':0.5,'c':0.5},'c':{'c':1}})
def test_next(self):
"""MarkovGenerator.next should generate text with expected properties"""
#haven't figured how to do this for longer correlation lengths yet
pass
def test_entropy(self):
"""MarkovGenerator._entropy() should correctly calculate average H"""
self.assertFloatEqual(self.randquads.Entropy, \
3.0/25 * 0.91829583405448956 + 8.0/25)
def test_evaluateProbability(self):
"""Should calculate proper P value for seq"""
self.dinucs.Prior=1
q=self.dinucs.evaluateProbability('AT')
self.assertFloatEqual(q,.50)
z=self.dinucs.evaluateProbability('ATAT')
self.assertFloatEqual(z,.25)
p=self.dinucs.evaluateProbability('ATATAT')
self.assertFloatEqual(p,.125)
j=self.dinucs.evaluateProbability('ATACAT')
self.assertFloatEqual(j,.125)
h=self.orderfive.evaluateProbability('AAAAAT')
self.assertFloatEqual(h,.50)
def test_replaceDegenerateBases(self):
"""strips degenerate bases...."""
text = 'AATCGCRRCCYAATC'
m=MarkovGenerator([text],order=2)
self.assertEqual(m.Text, [text])
m.replaceDegenerateBases()
self.assertEqual(m.Text[0][0:6],'aatcgc')
p=m.Text[0][6]
q= p in ['a','t','c','g']
self.assertEqual(q,True)
def test_wordToUniqueKey(self):
"""wordToUniqueKey should generate proper integers"""
m=MarkovGenerator(['aataacaataac'],order=2)
word='gca'
uniqueKey=m.wordToUniqueKey(word)
#a=0 c=1 t=2 g=3
#should be (4^0*3)+(4^1*1)+(4^2*0)=3+4+0=7
self.assertEqual(uniqueKey,7)
def test_evaluateArrayProbability(self):
"""evaluateArrayProbability should calc prob from array indices"""
m=MarkovGenerator(['aaaaaaaatt'],order=0)
#8 a's, 2 t's
m.calcFrequencies()
prob=m.evaluateArrayProbability(array([0,2]))
self.assertFloatEqual(prob,0.16) #0.8*0.2
prob=m.evaluateArrayProbability(array([0,1]))
self.assertFloatEqual(prob,0) #0.8*0
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_seqsim/test_microarray.py 000644 000765 000024 00000013105 12024702176 023524 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the microarray module, dealing with fake expression data."""
from cogent.util.unit_test import TestCase, main
from cogent.seqsim.microarray import MicroarrayNode
from numpy import ones
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Development"
class MicroarrayNodeTests(TestCase):
"""Tests of the MicroarrayNode class"""
def test_init_empty(self):
"""MicroarrayNode empty init should return new object as expected"""
m = MicroarrayNode()
self.assertEqual(m.Length, 0)
self.assertEqual(m.Array, None)
self.assertEqual(m.Name, None)
self.assertEqual(m.Children, [])
self.assertEqual(m.Parent, None)
def test_init(self):
"""MicroarrayNode init should return new object w/ correct attributes"""
m = MicroarrayNode(Name='x')
self.assertEqual(m.Length, 0)
self.assertEqual(m.Array, None)
self.assertEqual(m.Name, 'x')
self.assertEqual(m.Children, [])
self.assertEqual(m.Parent, None)
n = MicroarrayNode(3, 'xyz', Parent=m)
self.assertEqual(n.Length, 3)
self.assertEqual(n.Array, 'xyz')
self.assertEqual(n.Name, None)
self.assertEqual(n.Children, [])
assert n.Parent is m
def test_mutate(self):
"""Microarray mutate should set arrays appropriately"""
#check that it works as the root
a = ones(25, 'float64')
m = MicroarrayNode()
m.setExpression(a)
assert m.Array is not a
self.assertEqual(m.Array, a)
#check that it works on a single node w/ branchlength set
m.Length = 1
m.setExpression(a)
self.assertNotEqual(m.Array, a)
assert min(m.Array) > -4
assert max(m.Array) < 6
#check that it works for the children
m.Length = None
m2, m3, m4 = MicroarrayNode(), MicroarrayNode(), MicroarrayNode()
m5, m6, m7 = MicroarrayNode(), MicroarrayNode(), MicroarrayNode()
m8, m9, m10 = MicroarrayNode(), MicroarrayNode(), MicroarrayNode()
m.Children = [m2,m3, m4]
m2.Children = [m5]
m3.Children = [m6,m7,m8]
m8.Children = [m9,m10]
m2.Length = 2 # should be ~ 2 sd from 1
m3.Length = 0 # should test equal to m.Array
m4.Length = 0.1 # should be ~ 0.1 sd from 1
m5.Length = 1 # should be ~ 3 sd from 1
m6.Length = 0.1 # should be in same bounds as m4
m7.Length = 2 # should be in same bounds as m2
m8.Length = 1 # should be ~ 1 sd from 1
m9.Length = 1 # should be in same bounds as m2
m10.Length = 0 # should test equal to m8
m.setExpression(a)
self.assertNotEqual(m.Array, m2.Array)
self.assertEqual(m.Array, m3.Array)
self.assertNotEqual(m.Array, m4.Array)
self.assertNotEqual(m.Array, m5.Array)
self.assertNotEqual(m.Array, m6.Array)
self.assertNotEqual(m.Array, m7.Array)
self.assertNotEqual(m.Array, m8.Array)
self.assertNotEqual(m.Array, m9.Array)
self.assertNotEqual(m.Array, m10.Array)
self.assertNotEqual(m2.Array, m3.Array)
self.assertNotEqual(m2.Array, m4.Array)
self.assertNotEqual(m2.Array, m5.Array)
self.assertNotEqual(m2.Array, m6.Array)
self.assertNotEqual(m2.Array, m7.Array)
self.assertNotEqual(m2.Array, m8.Array)
self.assertNotEqual(m2.Array, m9.Array)
self.assertNotEqual(m2.Array, m10.Array)
self.assertNotEqual(m3.Array, m4.Array)
self.assertNotEqual(m3.Array, m5.Array)
self.assertNotEqual(m3.Array, m6.Array)
self.assertNotEqual(m3.Array, m7.Array)
self.assertNotEqual(m3.Array, m8.Array)
self.assertNotEqual(m3.Array, m9.Array)
self.assertNotEqual(m3.Array, m10.Array)
self.assertNotEqual(m4.Array, m5.Array)
self.assertNotEqual(m4.Array, m6.Array)
self.assertNotEqual(m4.Array, m7.Array)
self.assertNotEqual(m4.Array, m8.Array)
self.assertNotEqual(m4.Array, m9.Array)
self.assertNotEqual(m4.Array, m10.Array)
self.assertNotEqual(m5.Array, m6.Array)
self.assertNotEqual(m5.Array, m7.Array)
self.assertNotEqual(m5.Array, m8.Array)
self.assertNotEqual(m5.Array, m9.Array)
self.assertNotEqual(m5.Array, m10.Array)
self.assertNotEqual(m6.Array, m7.Array)
self.assertNotEqual(m6.Array, m8.Array)
self.assertNotEqual(m6.Array, m9.Array)
self.assertNotEqual(m6.Array, m10.Array)
self.assertNotEqual(m7.Array, m8.Array)
self.assertNotEqual(m7.Array, m9.Array)
self.assertNotEqual(m7.Array, m10.Array)
self.assertNotEqual(m8.Array, m9.Array)
self.assertEqual(m8.Array, m10.Array)
self.assertNotEqual(m9.Array, m10.Array)
#check that amount of change is about right
#assert 1 > min(m2.Array) > -15
#assert 1 < max(m2.Array) < 15
#assert 1 > min(m4.Array) > 0.4
#assert 1 < max(m4.Array) < 1.6
# might want stochastic tests here...
self.assertIsBetween(m2.Array, -11, 13)
self.assertIsBetween(m4.Array, 0.4, 1.6)
self.assertIsBetween(m5.Array, -15, 17)
self.assertIsBetween(m6.Array, 0.4, 1.6)
self.assertIsBetween(m7.Array, -11, 13)
self.assertIsBetween(m8.Array, -4, 7)
self.assertIsBetween(m9.Array, -11, 13)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_seqsim/test_microarray_normalize.py 000644 000765 000024 00000007700 12024702176 025610 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests of microarray_normalize.py: code for normalizing microarrays.
"""
from cogent.seqsim.microarray_normalize import (zscores, logzscores, ranks,
quantiles,
make_quantile_normalizer, make_normal_quantile_normalizer,
make_empirical_quantile_normalizer,
geometric_mean )
from cogent.util.unit_test import TestCase, main
from numpy import array, arange, reshape, log2
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Micah Hamady", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Development"
class microarray_normalize_tests(TestCase):
"""Tests of top-level functions."""
def test_zscores(self):
"""zscores should convert array to zscores within each column"""
a = reshape(arange(15),(5,3))
z = zscores(a)
self.assertEqual(z[2], array([0,0,0])) #middle should be mean
self.assertFloatEqual(z[0], [-1.41421356]*3)
#check that it works when arrays aren't sorted
a[0] = a[-1]
a[1] = a[-2]
a[0, -1] = 50
z = zscores(a)
self.assertEqual(z[0,0],z[-1,0])
self.assertFloatEqual(z[0,-1], 1.9853692256351525)
self.assertFloatEqual(z[-1,-1], -0.30544141932848506)
def test_logzscores(self):
"""logzscores should perform zscores on log of a"""
a = reshape(arange(1,16),(5,3)) #won't work with zero value
self.assertFloatEqual(logzscores(a), zscores(log2(a)))
def test_ranks(self):
"""ranks should convert array to ranks within each column"""
a = array([[10,20,30],[20,10,50],[30,5,10]])
r = ranks(a)
self.assertEqual(r, array([[0,2,1],[1,1,2],[2,0,0]]))
def test_quantiles(self):
"""quantiles should convert array to quantiles within each column"""
a = array([[10,20,30],[20,10,50],[30,5,10],[40,40,40]])
q = quantiles(a)
self.assertEqual(q, \
array([[0,.5,.25],[.25,.25,.75],[.5,0,0],[.75,.75,.5]]))
def test_make_quantile_normalizer(self):
"""make_quantile_normalizer should sample from right distribution."""
dist = array([1,2,3,4])
qn = make_quantile_normalizer(dist)
a = array([[10,20,30],[20,10,50],[30,5,10],[40,40,40]])
q = qn(a)
self.assertEqual(q, \
array([[1,3,2],[2,2,4],[3,1,1],[4,4,3]]))
#check that it works when they don't match in size exactly
dist = array([2,4,6,7,8,8,8,8])
qn = make_quantile_normalizer(dist)
a = array([[10,20,30],[20,10,50],[30,5,10],[40,40,40]])
q = qn(a)
self.assertEqual(q, \
array([[2,8,6],[6,6,8],[8,2,2],[8,8,8]]))
def test_make_normal_quantile_normalizer(self):
"""make_normal_quantile_normalizer should sample from normal dist."""
nqn = make_normal_quantile_normalizer(20, 10)
a = array([[10,20,30],[20,10,50],[30,5,10],[40,40,40]])
q = nqn(a)
exp = array([[-289.02323062, 20. , -47.44897502],
[ -47.44897502, -47.44897502, 87.44897502],
[ 20. , -289.02323062, -289.02323062],
[ 87.44897502, 87.44897502, 20. ]])
self.assertFloatEqual(q, exp)
def test_make_empirical_quantile_normalizer(self):
"""make_empirical_quantile_normalizer should convert a to dist of data"""
dist = array([4,2,3,1]) #note: out of order
qn = make_empirical_quantile_normalizer(dist)
a = array([[10,20,30],[20,10,50],[30,5,10],[40,40,40]])
q = qn(a)
self.assertEqual(q, \
array([[1,3,2],[2,2,4],[3,1,1],[4,4,3]]))
def test_geometric_mean(self):
"""geometric_mean should return geometric mean."""
a = array([1.05, 1.2, .96])
gmean = geometric_mean(a)
self.assertFloatEqual(gmean, 1.065484802091121)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_seqsim/test_randomization.py 000644 000765 000024 00000006201 12024702176 024231 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the microarray module, dealing with fake expression data."""
from cogent.util.unit_test import TestCase, main
from cogent.seqsim.randomization import shuffle_range, shuffle_between, \
shuffle_except_indices, shuffle_except
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Development"
class randomization_tests(TestCase):
"""Tests of the top-level functionality"""
def setUp(self):
"""Make some standard objects to randomize"""
self.numbers = list('123')
self.letters = list('abcdef')
self.to_test = self.numbers + 2*self.letters + self.numbers
def test_shuffle_range(self):
"""shuffle_range should shuffle only inside range"""
shuffle_range(self.to_test, 3, -3)
self.assertEqual(self.to_test[:3],self.numbers)
self.assertEqual(self.to_test[-3:], self.numbers)
self.assertNotEqual(self.to_test[3:-3], 2*self.letters)
self.assertEqualItems(self.to_test[3:-3], 2*self.letters)
#this time, start is negative and end is positive
shuffle_range(self.to_test, -15, 15)
self.assertEqual(self.to_test[:3],self.numbers)
self.assertEqual(self.to_test[-3:], self.numbers)
self.assertNotEqual(self.to_test[3:-3], 2*self.letters)
self.assertEqualItems(self.to_test[3:-3], 2*self.letters)
def test_shuffle_between(self):
"""shuffle_between should shuffle between specified chars"""
shuffle_peptides = shuffle_between('KR')
seq1 = 'AGHCDSGAHF' #each 10 chars long
seq2 = 'PLMIDNYHGT'
protein = seq1 + 'K' + seq2
result = shuffle_peptides(protein)
self.assertEqual(result[10], 'K')
self.assertNotEqual(result[:10], seq1)
self.assertEqualItems(result[:10], seq1)
self.assertNotEqual(result[11:], seq2)
self.assertEqualItems(result[11:], seq2)
def test_shuffle_except_indices(self):
"""shuffle_except_indices should shuffle all except specified indices"""
seq1 = 'AGHCDSGAHF' #each 10 chars long
seq2 = 'PLMIDNYHGT'
protein = seq1 + 'K' + seq2
result = list(protein)
shuffle_except_indices(result, [10])
self.assertEqual(result[10], 'K')
self.assertNotEqual(''.join(result), protein)
self.assertEqualItems(''.join(result), protein)
self.assertNotEqualItems(''.join(result[:10]), seq1)
def test_shuffle_except(self):
"""shuffle_except_indices should shuffle all except specified indices"""
seq1 = 'AGHCDSGAHF' #each 10 chars long
seq2 = 'PLMIDNYHGT'
protein = seq1 + 'K' + seq2
prot = protein
se = shuffle_except('K')
result = se(prot)
self.assertEqual(result[10], 'K')
self.assertNotEqual(''.join(result), protein)
self.assertEqualItems(''.join(result), protein)
self.assertNotEqualItems(''.join(result[:10]), seq1)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_seqsim/test_searchpath.py 000644 000765 000024 00000064245 12024702176 023511 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests private methods of SearchPath and SearchNode classes.
"""
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import NonnegIntError
from cogent.seqsim.searchpath import SearchPath, SearchNode
__author__ = "Amanda Birmingham"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Amanda Birmingham"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Amanda Birmingham"
__email__ = "amanda.birmingham@thermofisher.com"
__status__ = "Production"
class SearchPathHelper(object):
"""Contains data and function defs used by public AND private tests"""
#all primers have certain forbidden sequences: no runs longer than 3 of
#any purines or pyrimidines
standard_forbid_seq = ['AAAA', 'GAAA', 'AGAA', 'GGAA', 'AAGA', 'GAGA', \
'AGGA', 'GGGA', 'AAAG', 'GAAG', 'AGAG', 'GGAG', \
'AAGG', 'GAGG', 'AGGG', 'GGGG', 'CCCC', 'TCCC', \
'CTCC', 'TTCC', 'CCTC', 'TCTC', 'CTTC', 'TTTC', \
'CCCT', 'TCCT', 'CTCT', 'TTCT', 'CCTT', 'TCTT', \
'CTTT', 'TTTT']
alphabets = {SearchPath.DEFAULT_KEY:"ACGT"}
#end SearchPathHelper
class SearchNodeHelper(object):
"""Contains data and function defs used by public AND private tests"""
#list of possible bases at any position
alphabet = ["A", "C", "G", "T"]
#end SearchNodeHelper
class SearchPathTests(TestCase):
"""Tests public SearchPath methods."""
#-------------------------------------------------------------------
#Tests of clearNodes
def test_clearNodes(self):
"""Should empty path stack and variable forbidden"""
#create a searchpath and add just one node
test = SearchPath(SearchPathHelper.alphabets)
test.generate(1)
#now call clear and make sure path value is "" (empty)
test.clearNodes()
self.assertEquals(test.Value, "")
#end test_clearNodes
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of generate method
def tripletGenerator(self, pathobj, path_length):
"""Helper function to generate primers and catalogue triplets"""
found_triplets = {}
#make a hundred random searchpaths
for i in xrange(100):
curr_path_val = pathobj.generate(path_length)
#now find all the triplets in this path
for r in xrange(path_length-2):
curr_triplet = curr_path_val[r:r+3]
found_triplets[curr_triplet] = True
#end if
#clear out the path
pathobj.clearNodes()
#next rand sequence
return found_triplets
#end tripletGenerator
def test_generate_fullCoverage(self):
"""With no constraints, should produce all possible triplets"""
path_length = 20
test = SearchPath(SearchPathHelper.alphabets)
#make a hundred random searchpaths and see what triplets produced
found_triplets = self.tripletGenerator(test, path_length)
num_found = len(found_triplets.keys())
self.assertEquals(num_found, 64)
#end test_generate_fullCoverage
def test_generate_withForbidden(self):
"""With 2 triplet constraints, should produce all others"""
forbidden_triplet = ["ATG", "CCT"]
path_length = 20
test = SearchPath(SearchPathHelper.alphabets, forbidden_triplet)
#make a hundred random searchpaths and see what triplets produced
found_triplets = self.tripletGenerator(test, path_length)
num_found = len(found_triplets.keys())
self.assertEquals(num_found, 62)
#end test_generate_oneForbidden
def test_generate_nonePossible(self):
"""Should return null if no path can match constraints"""
alphabet = {SearchPath.DEFAULT_KEY:"AB"}
#forbid all combinations of alphabet
forbidden_seqs = ["AA", "AB", "BB", "BA"]
test = SearchPath(alphabet, forbidden_seqs)
output = test.generate(2)
self.assertEquals(output, None)
#end test_generate_nonePossible
def test_generate_multiple(self):
"""Should be able to call generate multiple times to extend path"""
test = SearchPath(SearchPathHelper.alphabets)
output1 = test.generate(2)
output2 = test.generate(3)
#make sure that the length of the path is now three
self.assertEquals(len(output2), 3)
#make sure that the new path is a superset of the old one
self.assertEquals(output1, output2[:2])
#end test_generate_multiple
def test_generate_correctAlph(self):
"""Should get correct alphabet even if node is popped then readded"""
test_alphs = {0:"A",1:"BC",2:"D",3:"E",SearchPath.DEFAULT_KEY:"X"}
forbidden_seqs = ["CD"]
test = SearchPath(test_alphs, forbidden_seqs)
#given these position alphabets and this forbidden seq,
#the only legal 3-node searchpath should be ABD. Make
#a hundred searchpaths and make sure this is the only one
#that actually shows up.
found_paths = {}
for i in xrange(100):
curr_path = test.generate(3)
found_paths[curr_path] = True
test.clearNodes()
#next
#make sure there is only one path found and that it is the right one
found_path_str = str("".join(found_paths.keys()))
self.assertEquals(len(found_paths), 1)
self.assertEquals(found_path_str, "ABD")
#end test_generate_correctAlph
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of findAllowedOption
def test_findAllowedOption_currentAllowed(self):
"""Should return true when current option is allowed"""
#searchpath with no forbidden seqs, so anything should work
test = SearchPath(SearchPathHelper.alphabets)
test._add_node(SearchNode(SearchNodeHelper.alphabet))
allowed_found = test.findAllowedOption()
self.assertEquals(allowed_found, True)
#end test_findAllowedOption_currentAllowed
def test_findAllowedOption_otherAllowed(self):
"""Should return true when curr option is bad but another is good"""
node_vals = []
#create a path and put in 2 nodes; since all the forbidden seqs I
#used to init the path have 4 entries, there should be no chance that
#the path I just created has anything forbidden in it
test = self._fill_path(2, node_vals)
#add the existing path value to the forbidden list
test._fixed_forbidden["".join(node_vals)] = True
test._forbidden_lengths[2] = True
#call findAllowedOption ... should find next available good option
allowed_found = test.findAllowedOption()
self.assertEquals(allowed_found, True)
#end test_findAllowedOption_otherAllowed
def test_findAllowedOption_none(self):
"""Should return false if curr option is bad and no good exist"""
test = self._fill_path(1)
self._empty_top(test)
#get the value of the top node's only remaining option;
#add to forbidden
last_option = test._get_top().Options
test._fixed_forbidden["".join(last_option)] = True
test._forbidden_lengths[1] = True
#now make sure we get back result that no options for path remain
allowed_found = test.findAllowedOption()
self.assertEquals(allowed_found, False)
#end test_findAllowedOption_none
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of removeOption
#Helper function
def _fill_path(self, num_nodes, node_vals = []):
"""create a searchpath and add searchnodes; return path"""
test = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
for i in xrange(num_nodes):
curr_node = SearchNode(SearchNodeHelper.alphabet)
node_vals.append(curr_node.Value)
test._add_node(curr_node)
#next i
return test
#end _fill_path
#Helper function
def _empty_top(self, spath):
"""remove all but one options from the top node"""
top_node = spath._get_top()
num_options = len(top_node.Options)
for i in xrange(num_options-1): top_node.removeOption()
#end _empty_top
def test_removeOption_simple(self):
"""Should correctly remove option from untapped node"""
#create a searchpath and a searchnode
test = self._fill_path(1)
orig_len_minus1 = len(test._get_top().Options) - 1
#also check that remove result is true: node still has options
has_options = test.removeOption()
self.assertEqual(has_options, True)
#get the top node and make sure that it has fewer options
top_node = test._get_top()
option_len = len(top_node.Options)
self.assertEqual(option_len, orig_len_minus1)
#end test_removeOption_simple
def test_removeOption_empty(self):
"""Should return False if removing option leads to empty stack"""
#create a searchpath with just one searchnode, then (almost) empty it
test = self._fill_path(1)
self._empty_top(test)
#now remove the last option, and make sure the stack is now empty
some_left = test.removeOption()
self.assertEquals(some_left, False)
#end test_removeOption_empty
def test_removeOption_recurse(self):
"""Should correctly remove empty node and curr option of next"""
#put two nodes in the search path and almost empty the top one
test = self._fill_path(2)
self._empty_top(test)
test.removeOption()
#make sure there's only one item left in the path
self.assertEquals(len(test._path_stack), 1)
#make sure that it has one fewer options
top_node = test._get_top()
self.assertEquals(len(top_node.Options), len(top_node.Alphabet)-1)
#end test_removeOption_recurse
#-------------------------------------------------------------------
#end SearchPathTests
class SearchNodeTests(TestCase):
"""Tests public SearchNode methods."""
#-------------------------------------------------------------------
#Tests of removeOption method
def test_removeOption_someLeft(self):
"""removeOption should cull options and return T when some left."""
#create a search node and get its current value
test = SearchNode(SearchNodeHelper.alphabet)
last_val = test.Value
some_left = test.removeOption()
#new current value must be different from old
#and return value must be true
self.assertNotEqual(test.Value, last_val)
self.assertEqual(some_left, True)
#end test_removeOption_someLeft
def test_removeOption_noneLeft(self):
"""removeOption should cull options and return F when none left."""
test = SearchNode(SearchNodeHelper.alphabet)
num_options = len(test.Options)
#removeOption num_options times: that should get 'em all
for i in xrange(num_options): some_left = test.removeOption()
#return value should be false (no options remain)
self.assertEqual(some_left, False)
#end test_removeOption_noneLeft
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Test of options property (and _get_options method)
def test_options(self):
"""Should return a copy of real options"""
test = SearchNode(SearchNodeHelper.alphabet)
optionsA = test.Options
del optionsA[0]
optionsB = test.Options
self.assertNotEqual(len(optionsA), len(optionsB))
#end test_options
#-------------------------------------------------------------------
#end SearchNodeTests
class SearchPathTests_private(TestCase):
"""Tests for private SearchPath methods."""
#No need to test __str__: just calls toString in general_tools
#No need to test _accept_option or _remove_accepted_option: they
#simply pass in the base class implementation
#No need to test _in_extra_forbidden: just returns False in base class
#implementation
#-------------------------------------------------------------------
#Helper functions
def _fill_path(self, num_nodes, node_vals = []):
"""create a searchpath and add searchnodes; return path"""
test = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
for i in xrange(num_nodes):
curr_node = SearchNode(SearchNodeHelper.alphabet)
node_vals.append(curr_node.Value)
test._add_node(curr_node)
#next i
return test
#end _fill_path
def _empty_top(self, spath):
"""remove all but one options from the top node"""
top_node = spath._get_top()
num_options = len(top_node.Options)
for i in xrange(num_options-1): top_node.removeOption()
#end _empty_top
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of __init__
def test_init_noForbid(self):
"""Init should correctly set private properties w/o forbid list"""
test = SearchPath(SearchPathHelper.alphabets)
real_result = len(test._fixed_forbidden.keys())
self.assertEquals(real_result, 0)
#end test_init_noForbid
def test_init_withForbid(self):
"""Init should correctly set private properties, w/forbid list"""
user_input = SearchPathHelper.standard_forbid_seq[:]
user_input.extend(["AUG", "aaaaccuag"])
test = SearchPath(SearchPathHelper.alphabets, user_input)
user_input = [i.upper() for i in user_input]
user_input.sort()
real_result = test._fixed_forbidden.keys()
real_result.sort()
self.assertEquals(str(real_result), str(user_input))
#end test_init_withForbid
def test_init_badAlphabets(self):
"""Init should fail if alphabets param is not dictionary-like"""
self.assertRaises(ValueError, SearchPath, "blue")
#end test_init_badAlphabets
def test_init_noDefault(self):
"""Init should fail if alphabets param has no 'default' key"""
self.assertRaises(ValueError, SearchPath, {12:"A"})
#end test_init_noDefault
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of value property (and _get_value method)
def test_value_empty(self):
"""Should return empty string when path is empty"""
test = SearchPath(SearchPathHelper.alphabets)
self.assertEquals(test.Value, "")
#end test_value_empty
def test_value(self):
"""Should return string of node values when nodes exist"""
node_vals = []
test = self._fill_path(3, node_vals)
self.assertEquals(test.Value, "".join(node_vals))
#end test_value
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of _top_index property (and _get_top_index method)
def test_top_index(self):
"""Should return index of top node when one exists"""
test = self._fill_path(3)
top_index = test._top_index
self.assertEquals(top_index,2)
#end test_top_index
def test_top_index_None(self):
"""Should return None when stack has no entries"""
test = SearchPath(SearchPathHelper.alphabets)
top_index = test._top_index
self.assertEquals(top_index, None)
#end test_top_index_None
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of _get_top method
def test_get_top(self):
"""Should return a reference to top node on stack if there is one"""
test = SearchPath(SearchPathHelper.alphabets)
test._add_node(SearchNode(SearchNodeHelper.alphabet))
topnode = SearchNode(SearchNodeHelper.alphabet)
test._add_node(topnode)
resultnode = test._get_top()
self.assertEquals(resultnode, topnode)
#end test_get_top
def test_get_top_None(self):
"""Should return None if stack is empty"""
test = SearchPath(SearchPathHelper.alphabets)
topnode = test._get_top()
self.assertEquals(topnode, None)
#end test_get_top_None
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Test of _get_forbidden_lengths
def test_get_forbidden_lengths(self):
"""get_forbidden_lengths should return dict of forbidden seq lens"""
correct_result = str([3, 4, 9])
user_input = SearchPathHelper.standard_forbid_seq[:]
user_input.extend(["AUG", "aaaaccuag"])
test = SearchPath(SearchPathHelper.alphabets, user_input)
real_dict = test._get_forbidden_lengths()
real_list = real_dict.keys()
real_list.sort()
real_result = str(real_list)
self.assertEquals(real_result, correct_result)
#end test_get_forbidden_lengths
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of _add_node
def test_add_node_first(self):
"""add_node should correctly add first node and increase top index."""
test = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
test_node = SearchNode(SearchNodeHelper.alphabet)
test._add_node(test_node)
self.assertEquals(len(test._path_stack), 1)
self.assertEquals(test._top_index, 0)
#end test_add_node_first
def test_add_node_subsequent(self):
"""add_node should correctly add additional nodes and up top index."""
test = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
test_node = SearchNode(SearchNodeHelper.alphabet)
test_node2 = SearchNode(SearchNodeHelper.alphabet)
test._add_node(test_node)
test._add_node(test_node2)
self.assertEquals(len(test._path_stack), 2)
self.assertEquals(test._top_index, 1)
#end test_add_node_subsequent
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of _get_nmer
def test_get_nmer(self):
"""get_nmer should return correct nmer for n <= length of stack"""
node_values = []
n = 4
test_path = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
for i in xrange(n+1):
curr_node = SearchNode(SearchNodeHelper.alphabet)
test_path._add_node(curr_node)
node_values.append(curr_node.Value)
#next
#get a nmer, and get the last n values that were put on stack;
#should be the same
real_result = test_path._get_nmer(n)
correct_result = "".join(node_values[-n:])
self.assertEquals(real_result, correct_result)
#end test_get_nmer
def test_get_nmer_tooLong(self):
"""get_nmer should return None for n > length of stack"""
test_path = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
test_node = SearchNode(SearchNodeHelper.alphabet)
test_path._add_node(test_node)
#stack is 1 long. Ask for a 2 mer
real_result = test_path._get_nmer(2)
self.assertEquals(real_result, None)
#end test_get_nmer_tooLong
def test_get_nmer_len1(self):
"""get_nmer should return correct result for nmer 1 on full stack"""
test_path = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
test_node = SearchNode(SearchNodeHelper.alphabet)
test_path._add_node(test_node)
correct_result = test_node.Value
real_result = test_path._get_nmer(1)
self.assertEquals(real_result, correct_result)
#end test_get_nmer_len1
def test_get_nmer_len0(self):
"""get_nmer should return an empty string if n is 0"""
#if n is zero, this should return "" even when stack is empty
test_path = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
real_result = test_path._get_nmer(0)
self.assertEquals(real_result, "")
#end test_get_nmer_len0
def test_get_nmer_badArg(self):
"""get_nmer should error if given a non integer-castable n"""
test_path = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
self.assertRaises(NonnegIntError, test_path._get_nmer, "blue")
#end test_get_nmer_badArg
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of _check_forbidden_seqs
def test_check_forbidden_seqs_fixed(self):
"""Should return True if path includes a fixed forbidden seq"""
forbidden_seq = ["G", "U", "A"]
user_input = ["".join(forbidden_seq)]
user_input.extend(SearchPathHelper.standard_forbid_seq)
test = SearchPath(SearchPathHelper.alphabets, user_input)
test._add_node(SearchNode(SearchNodeHelper.alphabet))
#add more values, and cheat so as to make them something forbidden
for bad_val in forbidden_seq:
curr_node = SearchNode(SearchNodeHelper.alphabet)
curr_node._options[0] = bad_val #torque the node's innards
test._add_node(curr_node)
#next bad_val
real_result = test._check_forbidden_seqs()
self.assertEquals(real_result, True)
#end test_check_forbidden_seqs_fixed
def test_check_forbidden_seqs_none(self):
"""Should return False if path includes no forbidden seqs"""
#a seq that isn't in the standard fixed forbidden lib
allowed_seq = ["C", "U", "A", "T"]
test = SearchPath(SearchPathHelper.alphabets, \
SearchPathHelper.standard_forbid_seq)
test._add_node(SearchNode(SearchNodeHelper.alphabet))
#add more values, and cheat so as to make them something known
for known_val in allowed_seq:
curr_node = SearchNode(SearchNodeHelper.alphabet)
curr_node._options[0] = known_val #torque the node's innards
test._add_node(curr_node)
#next bad_val
real_result = test._check_forbidden_seqs()
self.assertEquals(real_result, False)
#end test_check_forbidden_seqs_fixed
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#Tests of _get_alphabet
def test_get_alphabet_exists(self):
"""Should return alphabet for position when one exists"""
alph1 = "G"
alph2 = "ACGT"
test_alphs = {0:alph1, 2:alph1, SearchPath.DEFAULT_KEY:alph2}
test = SearchPath(test_alphs)
real_alph = test._get_alphabet(2)
self.assertEquals(str(real_alph), alph1)
#end test_get_alphabet_exists
def test_get_alphabet_default(self):
"""Should return default alphabet if none defined for position"""
#SearchPathHelper.alphabets has only a default entry
test = SearchPath(SearchPathHelper.alphabets)
real_alph = test._get_alphabet(0)
correct_alph = SearchPathHelper.alphabets[SearchPath.DEFAULT_KEY]
self.assertEquals(str(real_alph), str(correct_alph))
#end test_get_alphabet_default
def test_get_alphabet_badPosition(self):
"""Should raise error if input isn't castable to nonneg int"""
test = SearchPath(SearchPathHelper.alphabets)
self.assertRaises(NonnegIntError, test._get_alphabet, "blue")
#end test_get_alphabet_badPosition
#-------------------------------------------------------------------
#end SearchPathTests_private
class SearchNodeTests_private(TestCase):
"""Tests for private SearchNode methods."""
#No need to test __str__: just calls toString in general_tools
#No need to test _get_value and the value property: just references
#an item in an array
#No need to test _get_alphabet and alphabet property: ibid
#-------------------------------------------------------------------
#Tests of __init__
def test_init_noArg(self):
"""Init should correctly set private properties w/no arg"""
correct_result = str(SearchNodeHelper.alphabet)
test = SearchNode(SearchNodeHelper.alphabet)
options = test.Options
options.sort()
real_result = str(options)
self.assertEquals(real_result, correct_result)
#end test_init_noArg
#-------------------------------------------------------------------
#end SearchNodeTests_private
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_seqsim/test_sequence_generators.py 000644 000765 000024 00000142373 12024702176 025427 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""test_sequence_generator.py: tests of the sequence_generator module.
"""
from cogent.seqsim.sequence_generators import permutations, combinations, \
SequenceGenerator, Partition, Composition, \
MageFrequencies, SequenceHandle, IUPAC_DNA, IUPAC_RNA, BaseFrequency, \
PairFrequency, BasePairFrequency, RegionModel, ConstantRegion, \
UnpairedRegion, ShuffledRegion, PairedRegion, MatchingRegion, \
SequenceModel, Rule, Motif, Module, SequenceEmbedder
from StringIO import StringIO
from operator import mul
from sys import path
from cogent.maths.stats.util import Freqs
from cogent.util.misc import app_path
from cogent.struct.rna2d import ViennaStructure
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Development"
#need to skip some tests if RNAfold absent
if app_path('RNAfold'):
RNAFOLD_PRESENT = True
else:
RNAFOLD_PRESENT = False
class FunctionTests(TestCase):
"""Tests of standalone functions"""
def setUp(self):
self.standards = (0, 1, 5, 30, 173, 1000, 4382)
def test_permuations_negative_k(self):
"""permutations should raise IndexError if k negative"""
self.assertRaises(IndexError, permutations, 3, -1)
def test_permutations_k_more_than_n(self):
"""permutations should raise IndexError if k > n"""
self.assertRaises(IndexError, permutations, 3, 4)
def test_permutations_negative_n(self):
"""permutations should raise IndexError if n negative"""
self.assertRaises(IndexError, permutations, -3, -2)
def test_permutations_k_equals_1(self):
"""permutations should return n if k=1"""
for n in self.standards[1:]:
self.assertEqual(permutations(n,1), n)
def test_permutations_k_equals_2(self):
"""permutations should return n*(n-1) if k=2"""
for n in self.standards[2:]:
self.assertEqual(permutations(n,2), n*(n-1))
def test_permutations_k_equals_n(self):
"""permutations should return n! if k=n"""
for n in self.standards[1:]:
self.assertEqual(permutations(n,n), reduce(mul, range(1,n+1)))
def test_combinations_k_equals_n(self):
"""combinations should return 1 if k = n"""
for n in self.standards:
self.assertEqual(combinations(n,n), 1)
def test_combinations_k_equals_n_minus_1(self):
"""combinations should return n if k=(n-1)"""
for n in self.standards[1:]:
self.assertEqual(combinations(n, n-1), n)
def test_combinations_zero_k(self):
"""combinations should return 1 if k is zero"""
for n in self.standards:
self.assertEqual(combinations(n, 0), 1)
def test_combinations_symmetry(self):
"""combinations(n,k) should equal combinations(n,n-k)"""
for n in self.standards[3:]:
for k in (0, 1, 5, 18):
self.assertEquals(combinations(n, k), combinations(n, n-k))
def test_combinations_arbitrary_values(self):
"""combinations(n,k) should equal results from spreadsheet"""
results = {
30:{0:1, 1:30, 5:142506, 18:86493225, 29:30, 30:1},
173:{0:1, 1:173, 5:1218218079, 18:1.204353e24, 29:7.524850e32, \
30:3.611928e33},
1000:{0:1, 1:1000, 5:8.2502913e12, 18:1.339124e38,29:7.506513e55, \
30:2.429608e57},
4382:{0:1, 1:4382, 5:1.343350e16, 18:5.352761e49, 29:4.184411e74, \
30:6.0715804e76},
}
for n in self.standards[3:]:
for k in (0, 1, 5, 18, 29, 30):
self.assertFloatEqualRel(combinations(n,k), results[n][k], 1e-5)
class SequenceGeneratorTests(TestCase):
"""Tests of SequenceGenerator, which fills in degenerate bases"""
def setUp(self):
"""Defines a few standard generators"""
self.rna_codons = SequenceGenerator('NNN')
self.dna_iupac_small = SequenceGenerator('RH', IUPAC_DNA)
self.empty = SequenceGenerator('')
self.huge = SequenceGenerator('N'*50)
self.binary = SequenceGenerator('01??01', {'0':'0','1':'1','?':'10'})
def test_len(self):
"""len(SequenceGenerator) should return number of possible matches"""
lengths = ((self.rna_codons, 64), (self.dna_iupac_small, 6),
(self.empty, 0), (self.binary, 4))
for item, expected in lengths:
self.assertEqual(len(item), expected)
try:
len(self.huge)
except OverflowError:
pass
else:
raise AssertionError, "Failed to raise expected OverflowError"
def test_numPossibilities(self):
"""SequenceGenerator.numPossibilities() should be robust to overflow"""
lengths = ((self.rna_codons, 64), (self.dna_iupac_small, 6),
(self.empty, 0), (self.binary, 4), (self.huge, 4**50))
for item, expected in lengths:
self.assertEqual(item.numPossibilities(), expected)
def test_sequences(self):
"""SequenceGenerator should produce the correct list of sequences"""
self.assertEqual(list(self.empty), [])
self.assertEqual(list(self.dna_iupac_small), \
['AT','AC','AA','GT','GC','GA'])
codons = []
for first in 'UCAG':
for second in 'UCAG':
for third in 'UCAG':
codons.append(''.join([first, second, third]))
self.assertEqual(list(self.rna_codons), codons)
#test that it still works if we call the generator a second time
self.assertEqual(list(self.rna_codons), codons)
def test_iter(self):
"""SequenceGenerator should act like a list with for..in syntax"""
as_list = list(self.rna_codons)
for obs, exp in zip(self.rna_codons, as_list):
self.assertEqual(obs, exp)
def test_getitem(self):
"""SequenceGenerator should allow __getitem__ like a list"""
as_list = list(self.rna_codons)
for i in range(64):
self.assertEqual(self.rna_codons[i], as_list[i])
for i in range(1,65):
self.assertEqual(self.rna_codons[-i], as_list[-i])
self.assertEqual(self.huge[-1], 'G'*50)
def test_getitem_slices(self):
"""SequenceGenerator slicing should work the same as a list"""
e = list(self.rna_codons)
o = self.rna_codons
values = (
(o[:], e[:]),
(o[0:], e[0:]),
(o[1:], e[1:]),
(o[5:], e[5:]),
(o[0:5], e[0:5]),
(o[1:5], e[1:5]),
(o[5:5], e[5:5]),
(o[0:1], e[0:1]),
(o[len(o)-1:len(o)], e[len(e)-1:len(e)]),
(o[len(o):len(o)], e[len(e):len(e)]),
)
testnum = 0
for obs, exp in values:
testnum += 1
self.assertEqual(list(obs), exp)
big = list(self.huge[1:5])
self.assertEqual(['U'*49+'C', 'U'*49+'A', 'U'*49+'G', 'U'*48+'CU'], big)
class PartitionTests(TestCase):
"""Tests of the Paritition object."""
def test_single_partition(self):
"""If number of objects = bins * min, only one way to partition"""
for num_bins in range(1, 10):
for occupancy in range(10):
self.assertEqual(len(Partition(num_bins*occupancy,
num_bins, occupancy)), 1)
def test_partitions(self):
"""Test several properties of partitions, especially start/end"""
for num_bins in range(1, 5):
for occupancy in range(5):
for num_items in \
range(num_bins*occupancy, num_bins*occupancy + 10):
p = Partition(num_items, num_bins, occupancy)
l = [i for i in p]
l2 = [i for i in p]
#check that calling it twice doesn't break it
self.assertEqual(l, l2)
#check the lengths
self.assertEqual(len(p), len(l))
#check the ranges are the same...
self.assertEqual(l[0][1:], l[-1][0:-1])
#and that they contain the right values.
self.assertEqual(l[0][1:], [occupancy]*(num_bins - 1))
#check the first and last elements
self.assertEqual(l[0][0], l[-1][-1])
self.assertEqual(l[0][0], \
num_items - occupancy * (num_bins - 1))
def test_values(self):
"""Partition should match precalculated values"""
self.assertEqual(len(Partition(20, 4, 1)), 969)
def test_str(self):
"""str(partition) should work as expected"""
p = Partition(20,4,1)
self.assertEqual(str(p), "Items: 20 Pieces: 4 Min Per Piece: 1")
p.NumItems = 13
p.NumPieces = 2
p.MinOccupancy = 0
self.assertEqual(len(p), len(Partition(13, 2, 0)))
self.assertEqual(str(p), "Items: 13 Pieces: 2 Min Per Piece: 0")
class CompositionTests(TestCase):
"""Tests of the Composition class."""
def setUp(self):
"""Define a few standard compositions."""
self.bases_10pct = Composition(10, 0, "ACGU")
self.bases_5pct = Composition(5, 1, "ACGU")
self.bases_extra = Composition(10, 0, "CYGEJ")
self.small = Composition(20, 0, "xy")
self.unique = Composition(20, 1, "z")
def test_lengths(self):
"""Composition should return correct number of elements"""
self.assertEqual(len(self.bases_10pct), len(Partition(10,4,0)))
self.assertEqual(len(self.bases_5pct), len(Partition(20,4,1)))
self.assertEqual(len(self.bases_extra), len(Partition(10,5,0)))
self.assertEqual(len(self.small), len(Partition(5, 2, 0)))
self.assertEqual(len(self.unique), len(Partition(5, 1, 1)))
def test_known_vals(self):
"""Composition should return precalculated elements for known cases"""
self.assertEqual(len(Composition(5,1,"ACGU")), 969)
self.assertEqual(len(Composition(5,0,"ACGU")), 1771)
as_list = list(Composition(5,1,"ACGU"))
self.assertEqual(as_list[0], Freqs('A'*17+'CGU'))
self.assertEqual(as_list[-1], Freqs('U'*17+'ACG'))
def test_updating(self):
"""Composition updates should reset frequencies correctly."""
exp_list = list(Composition(5, 1, "GCAUN"))
self.bases_10pct.Spacing = 5
self.bases_10pct.Alphabet = "GCAUN"
self.bases_10pct.MinOccupancy = 1
self.assertEqual(list(self.bases_10pct), exp_list)
class MageFrequenciesTests(TestCase):
"""Tests of the MageFrequencies class -- presentation for Composition."""
def setUp(self):
"""Define a few standard compositions."""
self.bases_10pct = Composition(10, 0, "ACGU")
def test_str(self):
"""MageFrequencies string conversions work correctly"""
obs_list = list(self.bases_10pct)
self.assertEqual(str(MageFrequencies(obs_list[0])), '1.0 0.0 0.0')
self.assertEqual(str(MageFrequencies(obs_list[-1], "last")), \
'{last} 0.0 0.0 0.0')
self.assertEqual(str(MageFrequencies({'C':2, 'A':3, 'T':5, 'x':17}, \
'bases')), '{bases} 0.3 0.2 0.0')
class SequenceHandleTests(TestCase):
"""Tests of the SequenceHandle class."""
def setUp(self):
"""Define some standard SequenceHandles."""
self.rna = SequenceHandle('uuca', 'ucag')
self.any = SequenceHandle(['u', 1, None])
self.empty = SequenceHandle()
def test_init_good(self):
"""SequenceHandle should init OK without alphabet"""
self.assertEqual(SequenceHandle('abc123'), list('abc123'))
self.assertEqual(SequenceHandle(), list())
self.assertEqual(SequenceHandle('abcaaa', 'abcd'), list('abcaaa'))
self.assertEqual(SequenceHandle([1,2,3]), [1,2,3])
def test_init_bad(self):
"""SequenceHandle should raise ValueError if item not in alphabet"""
self.assertRaises(ValueError, SequenceHandle, 'abc1', 'abc')
self.assertRaises(ValueError, SequenceHandle, '1', [1])
def test_setitem_good(self):
"""SequenceHandle setitem should allow items in alphabet"""
self.rna[0] = 'c'
self.assertEqual(self.rna, list('cuca'))
self.rna[-1] = 'u'
self.assertEqual(self.rna, list('cucu'))
self.any[1] = [1, 2, 3]
self.assertEqual(self.any, ['u', [1, 2, 3], None])
def test_setitem_bad(self):
"""SequenceHandle setitem should reject items not in alphabet"""
self.assertRaises(ValueError, self.rna.__setitem__, 0, 'x')
def test_setslice_good(self):
"""SequenceHandle setslice should allow same-length slice"""
self.rna[:] = list('aaaa')
self.assertEqual(self.rna, list('aaaa'))
self.rna[0:1] = ['u']
self.assertEqual(self.rna, list('uaaa'))
self.rna[-2:] = ['g','g']
self.assertEqual(self.rna, list('uagg'))
def test_setslice_bad(self):
"""SequenceHandle setslice should reject bad items or length change"""
self.assertRaises(ValueError, self.rna.__setslice__, 0, len(self.rna), \
['a']*5)
self.assertRaises(ValueError, self.any.__setslice__, 0, len(self.any), \
['a']*5)
self.assertRaises(ValueError, self.rna.__setslice__, 0, 1, ['x'])
def test_string(self):
"""SequenceHandle str should join items without spaces"""
#use ''.join if items are strings
self.assertEqual(str(self.rna), 'uuca')
self.assertEqual(str(self.empty), '')
#if some of the items raise errors, use built-in method instead
self.assertEqual(str(self.any), str(['u', 1, None]))
def test_naughty_methods(self):
"""SequenceHandle list mutators should raise NotImplementedError"""
r = self.rna
naughty = [r.__delitem__, r.__delslice__, r.__iadd__, r.__imul__, \
r.append, r.extend, r.insert, r.pop, r.remove]
for n in naughty:
self.assertRaises(NotImplementedError, n)
class BaseFrequencyTests(TestCase):
"""Tests of BaseFrequency class: wrapper for FrequencyDistibution."""
def test_init(self):
"""BaseFrequency should init as expected"""
self.assertEqual(BaseFrequency('UUUCCCCAG'), \
Freqs('UUUCCCCAG', 'UCAG'))
self.assertEqual(BaseFrequency('TTTCAGG', RNA=False), \
Freqs('TTTCAGG'))
def test_init_bad(self):
"""BaseFrequency init should disallow bad characters"""
self.assertRaises(Exception, BaseFrequency, 'TTTCAGG')
self.assertRaises(Exception, BaseFrequency, 'UACGUA', False)
class PairFrequencyTests(TestCase):
"""Tests of PairFrequency class: wrapper for Freqs."""
def test_init_one_parameter(self):
"""PairFrequency should interpret single parameter as pair probs"""
obs = PairFrequency('UCCC')
exp = Freqs({('U','U'):0.0625, ('U','C'):0.1875,
('C','U'):0.1875, ('C','C'):0.5625})
for k, v in exp.items():
self.assertEqual(v, obs[k])
for k, v in obs.items():
if k not in exp:
self.assertEqual(v, 0)
self.assertEqual(PairFrequency('UCCC', [('U','U'),('C','C')]), \
Freqs({('U','U'):0.1, ('C','C'):0.9}))
#check that the alphabets are right: should not raise error on
#incrementing characters already there, but should raise KeyError
#on anything that's missing.
p = PairFrequency('UCCC')
p[('U','U')] += 1
try:
p[('X','U')] += 1
except KeyError:
pass
else:
raise AssertionError, "Expected KeyError."
p = PairFrequency('UCCC', (('C','C'),))
p[('C','C')] += 1
try:
p[('U','U')] += 1
except KeyError:
pass
else:
raise AssertionError, "Expected KeyError."
class BasePairFrequencyTests(TestCase):
"""Tests of the BaseFrequency class, constructed for easy initialization."""
def test_init(self):
"""BaseFrequency init should provide correct PairFrequency"""
WatsonCrick = [('A','U'), ('U','A'),('G','C'),('C','G')]
Wobble = WatsonCrick + [('G','U'), ('U','G')]
#by default, basepair should have the wobble alphabet
bpf = BasePairFrequency('UUACG')
pf = PairFrequency('UUACG', Wobble)
self.assertEqual(bpf, pf)
self.assertEqual(bpf.Constraint, pf.Constraint)
#can turn GU off, leading to watson-crickery
bpf = BasePairFrequency('UUACG', False)
#make sure this gives different results...
self.assertNotEqual(bpf, pf)
self.assertNotEqual(bpf.Constraint, pf.Constraint)
#...but that the results are the same when the correct alphabet is used
pf = PairFrequency('UUACG', WatsonCrick)
self.assertEqual(bpf, pf)
self.assertEqual(bpf.Constraint, pf.Constraint)
class RegionModelTests(TestCase):
"""Tests of the RegionModel class. Base class just returns the template."""
def test_init(self):
"""RegionModel base class should always return current template."""
#test blank region model
r = RegionModel()
self.assertEqual(str(r.Current), '')
self.assertEqual(len(r), 0)
#now assign it to a template
r.Template = ('ACGUUCGA')
self.assertEqual(str(r.Current), 'ACGUUCGA')
self.assertEqual(len(r), len('ACGUUCGA'))
#check that refresh doesn't break anything
r.refresh()
self.assertEqual(str(r.Current), 'ACGUUCGA')
self.assertEqual(len(r), len('ACGUUCGA'))
#check composition
self.assertEqual(r.Composition, None)
d = {'A':3, 'U':10}
r.Composition = Freqs(d)
self.assertEqual(r.Composition, d)
#check that composition doesn't break the update
r.refresh()
self.assertEqual(str(r.Current), 'ACGUUCGA')
self.assertEqual(len(r), len('ACGUUCGA'))
class ConstantRegionTests(TestCase):
"""Tests of the ConstantRegion class. Just returns the template."""
def test_init(self):
"""ConstantRegion should always return current template."""
#test blank region model
r = ConstantRegion()
self.assertEqual(str(r.Current), '')
self.assertEqual(len(r), 0)
#now assign it to a template
r.Template = ('ACGUUCGA')
self.assertEqual(str(r.Current), 'ACGUUCGA')
self.assertEqual(len(r), len('ACGUUCGA'))
#check that refresh doesn't break anything
r.refresh()
self.assertEqual(str(r.Current), 'ACGUUCGA')
self.assertEqual(len(r), len('ACGUUCGA'))
#check composition
self.assertEqual(r.Composition, None)
d = {'A':3, 'U':10}
r.Composition = Freqs(d)
self.assertEqual(r.Composition, d)
#check that composition doesn't break the update
r.refresh()
self.assertEqual(str(r.Current), 'ACGUUCGA')
self.assertEqual(len(r), len('ACGUUCGA'))
class UnpairedRegionTests(TestCase):
"""Tests of unpaired region: should fill in w/ single-base frequencies."""
def test_init(self):
"""Unpaired region should generate right freqs, even after change"""
freqs = Freqs({'C':10,'U':1, 'A':0})
r = UnpairedRegion('NN', freqs)
seq = r.Current
assert seq[0] in 'CU'
assert seq[1] in 'CU'
self.assertEqual(len(seq), 2)
fd = []
for i in range(1000):
r.refresh()
fd.append(str(seq))
fd = Freqs(''.join(fd))
observed = [fd['C'], fd['U']]
expected = [1800, 200]
self.assertSimilarFreqs(observed, expected)
self.assertEqual(fd['U'] + fd['C'], 2000)
freqs2 = Freqs({'A':5, 'U':5})
r.Composition = freqs2
r.Template = 'NNN' #note that changing the Template changes seq ref
seq = r.Current
self.assertEqual(len(seq), 3)
assert seq[0] in 'AU'
assert seq[1] in 'AU'
assert seq[2] in 'AU'
fd = []
for i in range(1000):
r.refresh()
fd.append(str(seq))
fd = Freqs(''.join(fd))
observed = [fd['A'], fd['U']]
expected = [1500, 1500]
self.assertSimilarFreqs(observed, expected)
self.assertEqual(fd['A'] + fd['U'], 3000)
class ShuffledRegionTests(TestCase):
"""Shuffled region should randomize string"""
def test_init(self):
"""Shuffled region should init ok with string, ignoring base freqs"""
#general strategy: seqs should be different, but sorted seqs should
#be the same
empty = ''
seq = 'UUUCCCCAAAGGG'
#check that we don't get errors on empty template
r = ShuffledRegion(empty)
r.refresh()
self.assertEqual(str(r.Current), '')
#check that changing the template changes the sequence
r.Template = seq
self.assertNotEqual(str(r.Current), '')
#check that it shuffled the sequence the first time
self.assertNotEqual(str(r.Current), seq)
curr = str(r.Current)
as_list = list(curr)
#check that we have the right number of each type of base
as_list.sort()
exp_as_list = list(seq)
exp_as_list.sort()
self.assertEqual(as_list, exp_as_list)
#check that we get something different if we refresh again
r.refresh()
self.assertNotEqual(str(r.Current), curr)
as_list = list(str(r.Current))
as_list.sort()
self.assertEqual(as_list, exp_as_list)
class PairedRegionTests(TestCase):
"""Tests of paired region generation."""
def test_init(self):
"""Paired region init and mutation should give expected results"""
WatsonCrick = {'A':'U', 'U':'A', 'C':'G', 'G':'C'}
Wobble = {'A':'U', 'U':'AG', 'C':'G', 'G':'UC'}
#check that empty init doesn't give errors
r = PairedRegion()
r.refresh()
#check that mutation works correctly
r.Template = "N"
self.assertEqual(len(r), 1)
r.monomers('UCCGGA')
upstream = r.Current[0]
downstream = r.Current[1]
states = {}
num_to_do = 10000
for i in range(num_to_do):
r.refresh()
curr = (upstream[0], downstream[0])
assert upstream[0] in Wobble[downstream[0]]
states[curr] = states.get(curr, 0) + 1
for i in states.keys():
assert i[1] in Wobble[i[0]]
for i in Wobble:
for j in Wobble[i]:
assert (i, j) in states.keys()
expected_dict = {('A','U'):num_to_do/14, ('U','A'):num_to_do/14,
('C','G'):num_to_do/14*4, ('G','C'):num_to_do/14*4,
('U','G'):num_to_do/14*2, ('G','U'):num_to_do/14*2,}
# the following for loop was replaced with the assertSimilarFreqs
# call below it
#for key, val in expected.items():
#self.assertFloatEqualAbs(val, states[key], 130) #conservative?
expected = [val for key, val in expected_dict.items()]
observed = [states[key] for key, val in expected_dict.items()]
self.assertSimilarFreqs(observed, expected)
assert ('G','U') in states
assert ('U','G') in states
r.monomers('UCGA', GU=False)
upstream = r.Current[0]
downstream = r.Current[1]
states = {}
num_to_do = 10000
for i in range(num_to_do):
r.refresh()
curr = (upstream[0], downstream[0])
assert upstream[0] in WatsonCrick[downstream[0]]
states[curr] = states.get(curr, 0) + 1
for i in states.keys():
assert i[1] in WatsonCrick[i[0]]
for i in WatsonCrick:
for j in WatsonCrick[i]:
assert (i, j) in states.keys()
expected_dict = {('A','U'):num_to_do/4, ('U','A'):num_to_do/4,
('C','G'):num_to_do/4, ('G','C'):num_to_do/4,}
expected = [val for key, val in expected_dict.items()]
observed = [states[key] for key, val in expected_dict.items()]
self.assertSimilarFreqs(observed, expected)
#for key, val in expected.items():
# self.assertFloatEqualAbs(val, states[key], 130) #3 std devs
assert ('G','U') not in states
assert ('U','G') not in states
class SequenceModelTests(TestCase):
"""Tests of the SequenceModel class."""
def test_init(self):
"""SequenceModel should init OK with Isoleucine motif."""
helices = [PairedRegion('NNN'), PairedRegion('NNNNN')]
constants = [ConstantRegion('CUAC'), ConstantRegion('UAUUGGGG')]
order = "H0 C0 H1 - H1 C1 H0"
isoleucine = SequenceModel(order=order, constants=constants, \
helices=helices)
isoleucine.Composition = BaseFrequency('UCAG')
#print
#print
for i in range(10):
isoleucine.refresh()
#print list(isoleucine)
#print
isoleucine.Composition = BaseFrequency('UCAG')
isoleucine.GU = False
#print
for i in range(10):
isoleucine.refresh()
#print list(isoleucine)
#print
class RuleTests(TestCase):
"""Tests of the Rule class"""
def test_init_bad_params(self):
"""Rule should fail validation except with exactly 5 parameters"""
self.assertRaises(TypeError, Rule, 1, 1, 1, 1)
self.assertRaises(TypeError, Rule, 1, 1, 1, 1, 1, 1)
def test_init_bad_length(self):
"""Rule should fail validation if helix extends past downstream start"""
self.assertRaises(ValueError, Rule, 0, 0, 1, 0, 2)
self.assertRaises(ValueError, Rule, 0, 0, 10, 10, 12)
def test_init_bad_negative_params(self):
"""Rule should fail validation if any parameters are negative"""
self.assertRaises(ValueError, Rule, -1, 0, 1, 0, 1)
self.assertRaises(ValueError, Rule, 0, -1, 1, 1, 1)
self.assertRaises(ValueError, Rule, 0, 0, -1, 0, 5)
self.assertRaises(ValueError, Rule, 0, 0, 0, -1, 1)
self.assertRaises(ValueError, Rule, 0, 0, 1, 1, -1)
def test_init_bad_zero_length(self):
"""Rule should fail validation if length is zero"""
self.assertRaises(ValueError, Rule, 0, 0, 1, 1, 0)
def test_init_overlap(self):
"""Rule should fail validation if bases must pair with themselves"""
self.assertRaises(ValueError, Rule, 0, 0, 0, 0, 1)
self.assertRaises(ValueError, Rule, 0, 10, 0, 15, 4)
def test_init_wrong_order(self):
"""First sequence must have lower index"""
self.assertRaises(ValueError, Rule, 1, 0, 0, 5, 3)
def test_init_ok_length(self):
"""Rule should init OK if helix extends to exactly downstream start"""
x = Rule(0, 0, 1, 0, 1)
self.assertEqual(str(x), \
"Up Seq: 0 Up Pos: 0 Down Seq: 1 Down Pos: 0 Length: 1")
#check adjacent bases
x = Rule(0, 0, 0, 1, 1)
self.assertEqual(str(x), \
"Up Seq: 0 Up Pos: 0 Down Seq: 0 Down Pos: 1 Length: 1")
x = Rule(1, 10, 2, 8, 7)
#check rule that would cause overlap if motifs weren't different
self.assertEqual(str(x), \
"Up Seq: 1 Up Pos: 10 Down Seq: 2 Down Pos: 8 Length: 7")
def test_str(self):
"""Rule str method should give expected results"""
x = Rule(1, 10, 2, 8, 7)
self.assertEqual(str(x), \
"Up Seq: 1 Up Pos: 10 Down Seq: 2 Down Pos: 8 Length: 7")
class RuleTests_compatibility(TestCase):
"""Tests to see whether the Rule compatibility code works"""
def setUp(self):
"""Sets up some standard rules"""
self.x = Rule(1, 5, 2, 10, 3)
self.x_ok = Rule(1, 8, 2, 14, 4)
self.x_ok_diff_sequences = Rule(3, 5, 5, 10, 3)
self.x_bad_first = Rule(1, 0, 3, 10, 10)
self.x_bad_first_2 = Rule(0, 0, 1, 8, 2)
self.x_bad_second = Rule(1, 15, 2, 15, 8)
self.x_bad_second_2 = Rule(1, 14, 2, 8, 4)
def test_is_compatible_ok(self):
"""Rule.isCompatible should return True if rules don't overlap"""
self.assertEqual(self.x.isCompatible(self.x_ok), True) #no return value
self.assertEqual(self.x.isCompatible(self.x_ok_diff_sequences), True)
#check that it's transitive
self.assertEqual(self.x_ok.isCompatible(self.x), True)
self.assertEqual(self.x_ok_diff_sequences.isCompatible(self.x), True)
def test_is_compatible_bad(self):
"""Rule.isComaptible should return False if rules overlap"""
tests = [ (self.x, self.x_bad_first),
(self.x, self.x_bad_first_2),
(self.x, self.x_bad_second),
(self.x, self.x_bad_second_2),
]
for first, second in tests:
self.assertEqual(first.isCompatible(second), False)
#check that it's transitive
self.assertEqual(second.isCompatible(first), False)
def test_fits_in_sequence(self):
"""Rule.fitsInSequence should return True if sequence long enough"""
sequences = map('x'.__mul__, range(21)) #0 to 20 copies of 'x'
rules = [self.x, self.x_ok, self.x_ok_diff_sequences, self.x_bad_first,
self.x_bad_first_2, self.x_bad_second, self.x_bad_second_2]
#test a bunch of values for all the rules we have handy
for s in sequences:
for r in rules:
if r.UpstreamPosition + r.Length > len(s):
self.assertEqual(r.fitsInSequence(s), False)
else:
self.assertEqual(r.fitsInSequence(s), True)
#test a couple of specific boundary cases
#length-1 helix
r = Rule(0, 0, 1, 0, 1)
self.assertEqual(r.fitsInSequence(''), False)
self.assertEqual(r.fitsInSequence('x'), True)
self.assertEqual(r.fitsInSequence('xx'), True)
#length-2 helix starting one base from the start
r = Rule(1, 1, 2, 2, 2)
self.assertEqual(r.fitsInSequence(''), False)
self.assertEqual(r.fitsInSequence('x'), False)
self.assertEqual(r.fitsInSequence('xx'), False)
self.assertEqual(r.fitsInSequence('xxx'), True)
self.assertEqual(r.fitsInSequence('xxxx'), True)
class ModuleTests(TestCase):
"""Tests of the Module class, which holds sequences and structures."""
def test_init_bad(self):
"""Module init should fail if seq/struct missing, or mismatched lengths"""
#test incorrect param number
self.assertRaises(TypeError, Module, 'abc')
self.assertRaises(TypeError, Module, 'abc', 'def', 'ghi')
#test incorrect lengths
self.assertRaises(ValueError, Module, 'abc', 'abcd')
self.assertRaises(ValueError, Module, 'abcd', 'acb')
def test_init_good(self):
"""Module init should work if seq and struct same length"""
m = Module('U', '.')
self.assertEqual(m.Sequence, 'U')
self.assertEqual(m.Structure, '.')
m.Sequence = ''
m.Structure = ''
self.assertEqual(m.Sequence, '')
self.assertEqual(m.Structure, '')
m.Sequence = 'CCUAGG'
m.Structure = '((..))'
self.assertEqual(m.Sequence, 'CCUAGG')
self.assertEqual(m.Structure, '((..))')
m.Structure = ''
self.assertRaises(ValueError, m.__len__)
def test_len(self):
"""Module len should work if seq and struct same length"""
m = Module('CUAG', '....')
self.assertEqual(len(m), 4)
m = Module('', '')
self.assertEqual(len(m), 0)
m.Sequence = 'AUCGAUCGA'
self.assertRaises(ValueError, m.__len__)
def test_str(self):
"""Module str should contain sequence and structure"""
m = Module('CUAG', '....')
self.assertEqual(str(m), 'Sequence: CUAG\nStructure: ....')
m = Module('', '')
self.assertEqual(str(m), 'Sequence: \nStructure: ')
def test_matches(self):
"""Module matches should return correct result for seq/struct match"""
empty = Module('', '')
short_p = Module('AC', '((')
short_u = Module('UU', '..')
short_up = Module('UU', '((')
long_all = Module('GGGACGGUUGGUUGGUU', ')))((..((....((((') #struct+seq
long_seq = Module('GGGACGGUUGGUU', ')))))))))))))') #seq but not struct
long_struct = Module('GGGGGGGGGGGGG', ')))((..((....') #struct, not seq
long_none = Module('GGGGGGGGGGGGG', ')))))))))))))') #not struct or seq
#test overall matching
for matcher in [empty, short_p, short_u, short_up]:
self.assertEqual(matcher.matches(long_all), True)
for longer in [long_seq, long_struct, long_none]:
if matcher is empty:
self.assertEqual(matcher.matches(longer), True)
else:
self.assertEqual(matcher.matches(longer), False)
#test specific positions
positions = {3:short_p, 11:short_u, 7:short_up, 15:short_up}
for module in [short_p, short_u, short_up]:
for i in range(len(long_all)):
result = module.matches(long_all, i)
if positions.get(i, None) is module:
self.assertEqual(result, True)
else:
self.assertEqual(result, False)
class MotifTests(TestCase):
"""Tests of the Motif object, which has a set of Modules and Rules."""
def setUp(self):
"""Defines a few standard motifs"""
self.ile_mod_0 = Module('NNNCUACNNNNN', '(((((..(((((')
self.ile_mod_1 = Module('NNNNNUAUUGGGGNNN', ')))))......)))))')
self.ile_rule_0 = Rule(0, 0, 1, 15, 3)
self.ile_rule_1 = Rule(0, 7, 1, 4, 5)
self.ile = Motif([self.ile_mod_0, self.ile_mod_1], \
[self.ile_rule_0, self.ile_rule_1])
self.hh_mod_0 = Module('NNNNUNNNNN', '(((((.((((')
self.hh_mod_1 = Module('NNNNCUGANGAGNNN', ')))).......((((')
self.hh_mod_2 = Module('NNNCGAAANNNN', '))))...)))))')
self.hh_rule_0 = Rule(0, 0, 2, 11, 5)
self.hh_rule_1 = Rule(0, 6, 1, 3, 4)
self.hh_rule_2 = Rule(1, 11, 2, 3, 4)
self.hh = Motif([self.hh_mod_0, self.hh_mod_1, self.hh_mod_2], \
[self.hh_rule_0, self.hh_rule_1, self.hh_rule_2])
self.simple_0 = Module('CCCCC', '(((..')
self.simple_1 = Module('GGGGG', '..)))')
self.simple_r = Rule(0, 0, 1, 4, 3)
self.simple = Motif([self.simple_0, self.simple_1], [self.simple_r])
def test_init_bad_rule_lengths(self):
"""Motif init should fail if rules don't match module lengths"""
bad_rule = Rule(0, 0, 1, 8, 6)
self.assertRaises(ValueError, Motif, [self.simple_0, self.simple_1], \
[bad_rule])
def test_init_conflicting_rules(self):
"""Motif init should fail if rules overlap"""
interferer = Rule(0, 2, 2, 20, 4)
self.assertRaises(ValueError, Motif, [self.ile_mod_0, self.ile_mod_1, \
self.ile_mod_0], [self.ile_rule_0, interferer])
def test_matches_simple(self):
"""Test of simple match should work correctly"""
index = '01234567890123456789012345678901'
seq = 'AAACCCCCUUUGGGGGAAACCCCCUUUGGGGG'
struct = ViennaStructure('((..((..))....))...(((.......)))')
struct_2 = ViennaStructure('((((((..((())))))))).....(((.)))')
#substring right, not pair
self.assertEqual(self.simple.matches(seq, struct, [19, 27]), True)
self.assertEqual(self.simple.matches(seq, struct_2, [19,27]), False)
for first_pos in range(len(seq) - len(self.simple_0) + 1):
for second_pos in range(len(seq) - len(self.simple_1) + 1):
#should match struct only at one location
match=self.simple.matches(seq, struct, [first_pos, second_pos])
if (first_pos == 19) and (second_pos == 27):
self.assertEqual(match, True)
else:
self.assertEqual(match, False)
#should never match in struct_2
self.assertEqual(self.simple.matches(seq, struct_2, \
[first_pos, second_pos]), False)
#check that it doesn't fail if there are _two_ matches
index = '01234567890123456789'
seq = 'CCCCCGGGGGCCCCCGGGGG'
struct = '(((....)))(((....)))'
struct = ViennaStructure(struct)
self.assertEqual(self.simple.matches(seq, struct, [0, 5]), True)
self.assertEqual(self.simple.matches(seq, struct, [10,15]), True)
#not allowed to cross-pair
self.assertEqual(self.simple.matches(seq, struct, [0, 15]), False)
def test_matches_ile(self):
"""Test of isoleucine match should work correctly"""
index = '012345678901234567890123456789012345'
seq_good = 'AAACCCCUACUUUUUCCCAAAAAUAUUGGGGGGGAA'
seq_bad = 'AAACCCCUACUUUUUCCCAAAAAUAUUGGGCGGGAA'
st_good = '...(((((..(((((...)))))......)))))..'
st_bad = '((((((((..(((((...)))))...))))))))..'
st_good = ViennaStructure(st_good)
st_bad = ViennaStructure(st_bad)
for first_pos in range(len(seq_good) - len(self.ile_mod_0) + 1):
for second_pos in range(len(seq_good) - len(self.ile_mod_1) + 1):
#seq_good and struct_good should match at one location
match=self.ile.matches(seq_good,st_good,[first_pos,second_pos])
if (first_pos == 3) and (second_pos == 18):
self.assertEqual(match, True)
else:
self.assertEqual(match, False)
self.assertEqual(self.ile.matches(seq_good, st_bad, \
[first_pos, second_pos]), False)
self.assertEqual(self.ile.matches(seq_bad, st_good, \
[first_pos, second_pos]), False)
self.assertEqual(self.ile.matches(seq_bad, st_bad, \
[first_pos, second_pos]), False)
def test_matches_hh(self):
"""Test of hammerhead match should work correctly"""
index = '0123456789012345678901234567890123456'
seq_good = 'CCCCUAGGGGCCCCCUGAAGAGAAAUUUCGAAAGGGG'
seq_bad ='CCCCCAGGGGCCCCCUGAAGAGAAAUUUCGAAGGGGG'
structure ='(((((.(((()))).......(((())))...)))))'
struct = ViennaStructure(structure)
self.assertEqual(self.hh.matches(seq_good, struct, [0, 10, 25]), True)
self.assertEqual(self.hh.matches(seq_bad, struct, [0, 10, 25]), False)
def test_structureMatches_hh(self):
"""Test of hammerhead structureMatch should work correctly"""
index = '0123456789012345678901234567890123456'
seq_good = 'CCCCUAGGGGCCCCCUGAAGAGAAAUUUCGAAAGGGG'
seq_bad ='CCCCCAGGGGCCCCCUGAAGAGAAAUUUCGAAGGGGG'
structure ='(((((.(((()))).......(((())))...)))))'
struct = ViennaStructure(structure)
self.assertEqual(self.hh.structureMatches(struct, [0, 10, 25]), True)
self.assertEqual(self.hh.structureMatches(struct, [0, 10, 25]), True)
class SequenceEmbedderTests(TestCase):
"""Tests of the SequenceEmbedder class."""
def setUp(self):
"""Define a few standard models and motifs"""
ile_mod_0 = Module('NNNCUACNNNNN', '(((((..(((((')
ile_mod_1 = Module('NNNNNUAUUGGGGNNN', ')))))......)))))')
ile_rule_0 = Rule(0, 0, 1, 15, 5)
ile_rule_1 = Rule(0, 7, 1, 4, 5)
ile_motif = Motif([ile_mod_0, ile_mod_1], \
[ile_rule_0, ile_rule_1])
helices = [PairedRegion('NNN'), PairedRegion('NNNNN')]
constants = [ConstantRegion('CUAC'), ConstantRegion('UAUUGGGG')]
order = "H0 C0 H1 - H1 C1 H0"
ile_model = SequenceModel(order=order, constants=constants, \
helices=helices, composition=BaseFrequency('UCAG'))
self.ile_embedder = SequenceEmbedder(length=50, num_to_do=10, \
motif=ile_motif, model=ile_model, composition=BaseFrequency('UCAG'))
short_ile_mod_0 = Module('NCUACNN', '(((..((')
short_ile_mod_1 = Module('NNUAUUGGGGN', '))......)))')
short_ile_rule_0 = Rule(0, 0, 1, 10, 3)
short_ile_rule_1 = Rule(0, 5, 1, 1, 2)
short_ile_motif = Motif([short_ile_mod_0, short_ile_mod_1], \
[short_ile_rule_0, short_ile_rule_1])
short_helices = [PairedRegion('N'), PairedRegion('NN')]
short_constants = [ConstantRegion('CUAC'), ConstantRegion('UAUUGGGG')]
short_order = "H0 C0 H1 - H1 C1 H0"
short_ile_model = SequenceModel(order=short_order, \
constants=short_constants, \
helices=short_helices, composition=BaseFrequency('UCAG'))
self.short_ile_embedder = SequenceEmbedder(length=50, num_to_do=10, \
motif=short_ile_motif, model=short_ile_model, \
composition=BaseFrequency('UCAG'))
def test_composition_change(self):
"""Changes in composition should propagate."""
rr = str(self.ile_embedder.RandomRegion.Current)
#for base in 'UCAG':
# assert base in rr
#the above two lines should generally be true but fail stochastically
self.ile_embedder.Composition = BaseFrequency('CG')
self.assertEqual(self.ile_embedder.Model.Composition, \
BaseFrequency('CG'))
self.assertEqual(self.ile_embedder.RandomRegion.Composition, \
BaseFrequency('CG'))
self.ile_embedder.RandomRegion.refresh()
self.assertEqual(len(self.ile_embedder.RandomRegion), 22)
rr = str(self.ile_embedder.RandomRegion.Current)
assert ('C' in rr or 'G' in rr)
assert 'A' not in rr
assert 'U' not in rr
def test_choose_locations_too_short(self):
"""SequenceEmbedder _choose_locations should fail if too little space"""
self.ile_embedder.Length = 28 #no positions left over
self.assertRaises(ValueError, self.ile_embedder._choose_locations)
self.ile_embedder.Length = 29 #one position left over
self.assertRaises(ValueError, self.ile_embedder._choose_locations)
def test_choose_locations_exact(self):
"""SequenceEmbedder _choose_locations should pick all locations"""
self.ile_embedder.Length = 30 #two positions left: must both be filled
for i in range(10):
first, second = self.ile_embedder._choose_locations()
self.assertEqual(first, 0)
self.assertEqual(second, 1)
def test_choose_locations_even(self):
"""SequenceEmbedder _choose_locations should pick locations evenly"""
self.ile_embedder.Length = 31 #three positions left
counts = {}
for i in range(1000):
key = tuple(self.ile_embedder._choose_locations())
assert key[0] != key[1]
curr = counts.get(key, 0)
counts[key] = curr + 1
expected = [333, 333, 333]
observed = [counts[(0,1)], counts[(0,2)], counts[(1,2)]]
self.assertSimilarFreqs(observed, expected)
#make sure nothing else snuck in there
self.assertEqual(counts[(0,1)]+counts[(0,2)]+counts[(1,2)], 1000)
def test_choose_locations_with_replacement(self):
"""SequenceEmbedder _choose_locations can sample with replacement"""
self.ile_embedder.Length = 28 #exact fit
self.ile_embedder.WithReplacement = True
for i in range(10):
first, second = self.ile_embedder._choose_locations()
self.assertEqual(first, 0)
self.assertEqual(second, 0)
self.ile_embedder.Length = 29 #one left over: can be 0,0 0,1 1,1
counts = {}
for i in range(1000):
key = tuple(self.ile_embedder._choose_locations())
curr = counts.get(key, 0)
counts[key] = curr + 1
expected = [250, 500, 250]
observed = [counts[(0,0)], counts[(0,1)], counts[(1,1)]]
self.assertSimilarFreqs(observed, expected)
#make sure nothing else snuck in there
self.assertEqual(counts[(0,0)]+counts[(0,1)]+counts[(1,1)], 1000)
def test_insert_modules(self):
"""SequenceEmbedder _insert_modules should make correct sequence"""
ile = self.ile_embedder
ile.Length = 50
ile.RandomRegion.Current[:] = ['A'] * 22
modules = list(ile.Model)
ile.Positions = [0, 0] #try inserting at first position
self.assertEqual(str(ile), modules[0] + modules[1] + 'A'*22)
ile.Positions = [3, 20]
self.assertEqual(str(ile), 'A'*3+modules[0]+'A'*17+modules[1]+'A'*2)
def test_refresh(self):
"""SequenceEmbedder refresh should change module sequences"""
modules_before = list(self.ile_embedder.Model)
random_before = str(self.ile_embedder.RandomRegion.Current)
self.ile_embedder.refresh()
random_after = str(self.ile_embedder.RandomRegion.Current)
self.assertNotEqual(random_before, random_after)
modules_after = list(self.ile_embedder.Model)
for before, after in zip(modules_before, modules_after):
self.assertNotEqual(before, after)
#check that it works twice
self.ile_embedder.refresh()
random_third = str(self.ile_embedder.RandomRegion.Current)
modules_third = list(self.ile_embedder.Model)
self.assertNotEqual(random_third, random_before)
self.assertNotEqual(random_third, random_after)
for first, second, third in \
zip(modules_before, modules_after, modules_third):
self.assertNotEqual(first, third)
self.assertNotEqual(second, third)
def test_countMatches(self):
"""Shouldn't find any Ile matches if all the pairs are GU"""
if not RNAFOLD_PRESENT:
return
self.ile_embedder.NumToDo = 100
self.ile_embedder.Composition = BaseFrequency('GGGGGGGGGU')
self.ile_embedder.Length = 40
good_count = self.ile_embedder.countMatches()
self.assertEqual(good_count, 0)
def test_countMatches_pass(self):
"""Should find some matches against a random background"""
if not RNAFOLD_PRESENT:
return
self.ile_embedder.NumToDo = 100
self.ile_embedder.Composition = BaseFrequency('UCAG')
self.ile_embedder.Length = 40
good_count = self.ile_embedder.countMatches()
self.assertNotEqual(good_count, 0)
def test_refresh_specific_position(self):
"""Should always find the module in the same position if specified"""
first_module = Module('AAAAA', '(((((')
second_module = Module('UUUUU', ')))))')
rule_1 = Rule(0, 0, 1, 4, 5)
helix = Motif([first_module, second_module], [rule_1])
model = SequenceModel(constants=[ConstantRegion('AAAAA'), \
ConstantRegion('UUUUU')], order='C0 - C1', \
composition=BaseFrequency('A'))
embedder = SequenceEmbedder(length=30, num_to_do=100, \
motif=helix, model=model, composition=BaseFrequency('CG'), \
positions=[3, 6])
last = ''
for i in range(100):
embedder.refresh()
curr = str(embedder)
self.assertEqual(curr[3:8], 'AAAAA')
self.assertEqual(curr[11:16], 'UUUUU')
self.assertEqual(curr.count('A'), 5)
self.assertEqual(curr.count('U'), 5)
self.assertNotEqual(last, curr)
last = curr
def test_refresh_primers(self):
"""Module should appear in correct location with primers"""
first_module = Module('AAAAA', '(((((')
second_module = Module('UUUUU', ')))))')
rule_1 = Rule(0, 0, 1, 4, 5)
helix = Motif([first_module, second_module], [rule_1])
model = SequenceModel(constants=[ConstantRegion('AAAAA'), \
ConstantRegion('UUUUU')], order='C0 - C1', \
composition=BaseFrequency('A'))
embedder = SequenceEmbedder(length=30, num_to_do=100, \
motif=helix, model=model, composition=BaseFrequency('CG'), \
positions=[3, 6], primer_5 = 'UUU', primer_3 = 'AAA')
last = ''
for i in range(100):
embedder.refresh()
curr = str(embedder)
self.assertEqual(curr[0:3], 'UUU')
self.assertEqual(curr[6:11], 'AAAAA')
self.assertEqual(curr[14:19], 'UUUUU')
self.assertEqual(curr.count('A'), 8)
self.assertEqual(curr.count('U'), 8)
self.assertEqual(curr[-3:], 'AAA')
self.assertNotEqual(last, curr)
last = curr
def xxx_test_count_long(self):
self.ile_embedder.NumToDo = 100000
self.ile_embedder.Composition = BaseFrequency('UCAG')
print
print "Extended helices"
for length in range(30, 150):
self.ile_embedder.Length = length
good_count = self.ile_embedder.countMatches()
print "Length: %s Matches: %s/100000" % (length, good_count)
print
def xxx_test_count_short(self):
self.short_ile_embedder.NumToDo = 10000
self.short_ile_embedder.Composition = BaseFrequency('UCAG')
print
print "Minimal motif"
for length in range(20, 150):
self.short_ile_embedder.Length = length
good_count = self.short_ile_embedder.countMatches()
print "Length: %s Matches: %s/10000" % (length, good_count)
print
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_seqsim/test_tree.py 000644 000765 000024 00000072754 12024702176 022332 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.parse.tree import DndParser
from cogent.seqsim.tree import RangeNode, balanced_breakpoints, BalancedTree, \
RandomTree, CombTree, StarTree, LineTree
from cogent.core.usage import DnaPairs
from copy import deepcopy
from operator import mul, or_, add
from numpy import array, average, diag
from numpy.random import random, randint
from cogent.seqsim.usage import Rates
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class treeTests(TestCase):
"""Tests for top-level functions."""
def test_init(self):
"""Make sure keyword arguments are being passed to baseclass"""
node = RangeNode(LeafRange=1, Id=2, Name='foo', Length=42)
self.assertEqual(node.LeafRange, 1)
self.assertEqual(node.Id, 2)
self.assertEqual(node.Name, 'foo')
self.assertEqual(node.Length, 42)
def test_balanced_breakpoints(self):
"""balanced_breakpoints should produce expected arrays."""
self.assertRaises(ValueError, balanced_breakpoints, 1)
self.assertEqual(balanced_breakpoints(2), array([0]))
self.assertEqual(balanced_breakpoints(4), array([1,0,2]))
self.assertEqual(balanced_breakpoints(8), \
array([3,1,5,0,2,4,6]))
self.assertEqual(balanced_breakpoints(16), \
array([7,3,11,1,5,9,13,0,2,4,6,8,10,12,14]))
self.assertEqual(balanced_breakpoints(32), \
array([15,7,23,3,11,19,27,1,5,9,13,17,21,25,29,\
0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30]))
def test_BalancedTree(self):
"""BalancedTree should return a balanced tree"""
b = BalancedTree(4)
self.assertEqual(len(list(b.traverse())), 4)
b.assignIds()
self.assertEqual(str(b), '((0,1)4,(2,3)5)6')
def test_RandomTree(self):
"""RandomTree should return correct number of nodes
NOTE: all the work is done in breakpoints, which is thoroughly
tested indepndently. RandomTree just makes permutations.
"""
d = {}
for i in range(10):
r = RandomTree(100)
self.assertEqual(len(list(r.traverse())), 100)
r.assignIds()
#make sure we get different trees each time...
s = str(r)
assert s not in d
d[s] = None
def test_CombTree(self):
"""CombTree should return correct topology"""
c = CombTree(4)
c.assignIds()
self.assertEqual(str(c), '(0,(1,(2,3)4)5)6')
c = CombTree(4, deepest_first=False)
c.assignIds()
self.assertEqual(str(c), '(((0,1)4,2)5,3)6')
def test_StarTree(self):
"""StarTree should return correct star topology and # nodes"""
t = StarTree(5)
self.assertEqual(len(t.Children), 5)
for c in t.Children:
assert c.Parent is t
def test_LineTree(self):
"""LineTree should return correct number of nodes"""
t = LineTree(5)
depth = 1
curr = t
while curr.Children:
self.assertEqual(len(curr.Children), 1)
depth += 1
curr = curr.Children[0]
self.assertEqual(depth, 5)
class RangeTreeTests(TestCase):
"""Tests of the RangeTree class."""
def setUp(self):
"""Make some standard objects to test."""
#Notes on sample string:
#
#1. trailing zeros are stripped in conversion to/from float, so result
# is only exactly the same without them.
#
#2. trailing chars (e.g. semicolon) are not recaptured in the output,
# so were deleted from original Newick-format string.
#
#3. whitespace is stripped, but is handy for formatting, so is stripped
# from original string before comparisons.
self.sample_tree_string = """
(
(
xyz:0.28124,
(
def:0.24498,
mno:0.03627)
A:0.1771)
B:0.0487,
abc:0.05925,
(
ghi:0.06914,
jkl:0.13776)
C:0.09853)
"""
self.t = DndParser(self.sample_tree_string, RangeNode)
self.i = self.t.indexByAttr('Name')
self.sample_string_2 = '((((a,b),c),(d,e)),((f,g),h))'
self.t2 = DndParser(self.sample_string_2, RangeNode)
self.i2 = self.t2.indexByAttr('Name')
self.sample_string_3 = '(((a,b),c),(d,e))'
self.t3 = DndParser(self.sample_string_3, RangeNode)
def test_str(self):
"""RangeNode should round-trip Newick string corrrectly."""
r = RangeNode()
self.assertEqual(str(r), '()')
#should work for tree with branch lengths set
t = DndParser(self.sample_tree_string, RangeNode)
expected = self.sample_tree_string.replace('\n', '')
expected = expected.replace(' ', '')
self.assertEqual(str(t), expected)
#self.assertEqual(t.getNewick(with_distances=True), expected)
#should also work for tree w/o branch lengths
t2 = DndParser(self.sample_string_2, RangeNode)
self.assertEqual(str(t2), self.sample_string_2)
def test_traverse(self):
"""RangeTree traverse should visit all nodes in correct order"""
t = self.t
i = self.i
#first, check that lengths are correct
#naked traverse() only does leaves; should be 6.
self.assertEqual(len(list(t.traverse())), 6)
#traverse() with self_before should count all nodes.
self.assertEqual(len(list(t.traverse(self_before=True))), 10)
#traverse() with self_after should have same count as self_before
self.assertEqual(len(list(t.traverse(self_after=True))), 10)
#traverse() with self_before and self_after should visit internal
#nodes multiple times
self.assertEqual(len(list(t.traverse(True,True))), 14)
#now, check that items are in correct order
exp = ['xyz','def','mno','abc','ghi','jkl']
obs = [i.Name for i in t.traverse()]
self.assertEqual(obs, exp)
exp = [None, 'B', 'xyz', 'A', 'def', 'mno', 'abc', 'C', 'ghi', 'jkl']
obs = [i.Name for i in t.traverse(self_before=True)]
self.assertEqual(obs, exp)
exp = ['xyz', 'def', 'mno', 'A', 'B', 'abc', 'ghi', 'jkl', 'C', None]
obs = [i.Name for i in t.traverse(self_after=True)]
self.assertEqual(obs, exp)
exp = [None, 'B', 'xyz', 'A', 'def', 'mno', 'A', 'B', 'abc', 'C', \
'ghi', 'jkl', 'C', None]
obs = [i.Name for i in t.traverse(self_before=True, self_after=True)]
self.assertEqual(obs, exp)
def test_indexByAttr(self):
"""RangeNode indexByAttr should make index using correct attr"""
t = self.t
i = self.i
#check that we got the right number of elements
#all elements unique, so should be same as num nodes
self.assertEqual(len(i), len(list(t.traverse(self_before=True))))
#check that we got everything
i_keys = i.keys()
i_vals = i.values()
for node in t.traverse(self_before=True):
assert node.Name in i_keys
assert node in i_vals
#can't predict which node will have None as the key
if node.Name is not None:
assert i[node.Name] is node
#check that it works when elements are not unique
t = self.t3
for node in t.traverse(self_before=True):
node.X = 'b'
for node in t.traverse():
node.X = 'a'
result = t.indexByAttr('X', multiple=True)
self.assertEqual(len(result), 2)
self.assertEqual(len(result['a']), 5)
self.assertEqual(len(result['b']), 4)
for n in t.traverse():
assert n in result['a']
assert not n in result['b']
def test_indexbyFunc(self):
"""RangeNode indexByFunc should make index from function"""
t = self.t
def f(n):
try:
return n.Name.isupper()
except AttributeError:
return None
i = self.i
f_i = t.indexByFunc(f)
self.assertEqual(len(f_i), 3)
self.assertEqual(f_i[True], [i['B'], i['A'], i['C']])
self.assertEqual(f_i[False], [i['xyz'], i['def'], i['mno'], \
i['abc'], i['ghi'], i['jkl']])
self.assertEqual(f_i[None], [i[None]])
def test_assignIds(self):
"""RangeNode assignIds should work as expected"""
t = self.t2
index = self.i2
t.assignIds()
#check that ids were set correctly on the leaves
for i, a in enumerate('abcdefgh'):
self.assertEqual(index[a].Id, i)
#check that ranges were set correctly on the leaves
for i, a in enumerate('abcdefgh'):
self.assertEqual(index[a].LeafRange, (i, i+1))
#check that internal ids were set correctly
obs = [i.Id for i in t.traverse(self_after=True)]
exp = [0,1,8,2,9,3,4,10,11,5,6,12,7,13,14]
self.assertEqual(obs, exp)
#check that internal ranges were set correctly
obs = [i.LeafRange for i in t.traverse(self_after=True)]
exp = [(0,1),(1,2),(0,2),(2,3),(0,3),(3,4),(4,5),(3,5),(0,5), \
(5,6),(6,7),(5,7),(7,8),(5,8),(0,8)]
self.assertEqual(obs, exp)
def test_propagateAttr(self):
"""RangeNode propagateAttr should send attr down tree, unless set"""
t = self.t
i = self.i
for n in t.traverse(self_before=True):
assert not hasattr(n, 'XYZ')
t.XYZ = 3
t.propagateAttr('XYZ')
for n in t.traverse(self_before=True):
self.assertEqual(n.XYZ, 3)
#shouldn't overwrite internal nodes by default
a_children = list(i['A'].traverse(self_before=True))
i['A'].GHI = 5
t.GHI = 1
t.propagateAttr('GHI')
for n in t.traverse(self_before=True):
if n in a_children:
self.assertEqual(n.GHI, 5)
else:
self.assertEqual(n.GHI, 1)
t.GHI = 0
t.propagateAttr('GHI', overwrite=True)
for n in t.traverse(self_before=True):
self.assertEqual(n.GHI, 0)
def test_delAttr(self):
"""RangeNode delAttr should delete attr from self and children"""
t = self.t2
for n in t.traverse(self_before=True):
assert hasattr(n, 'Name')
t.delAttr('Name')
for n in t.traverse(self_before=True):
assert not hasattr(n, 'Name')
def test_accumulateAttr(self):
"""RangeNode accumulateAttr should accumulate attr in right direction"""
t = self.t3
#test towards_leaves (the default)
f = lambda a, b: b + 1
for n in t.traverse(self_before=True):
n.Level = 0
t.accumulateAttr('Level', f=f)
levels = [i.Level for i in t.traverse(self_before=True)]
self.assertEqual(levels, [0,1,2,3,3,2,1,2,2])
for n in t.traverse(self_before=True):
n.Level=0
#test away from leaves
f = lambda a, b : max(a, b+1)
for n in t.traverse(self_before=True):
n.Level=0
t.accumulateAttr('Level', towards_leaves=False,f=f)
levels = [i.Level for i in t.traverse(self_before=True)]
self.assertEqual(levels, [3,2,1,0,0,0,1,0,0])
def test_accumulateChildAttr(self):
"""RangeNode accumulateChildAttr should work as expected"""
t = self.t2
i = self.i2
i['a'].x = 3
i['b'].x = 4
i['d'].x = 0
i['f'].x = 1
i['g'].x = 1
i['h'].x = 1
t.accumulateChildAttr('x', f=mul)
self.assertEqual([i.__dict__.get('x', None) for i in \
t.traverse(self_after=True)],
[3, 4, 12, None, 12, 0, None, 0, 0, 1, 1, 1, 1, 1, 0])
t.accumulateChildAttr('x', f=add)
self.assertEqual([i.__dict__.get('x', None) for i in \
t.traverse(self_after=True)],
[3, 4, 7, None, 7, 0, None, 0, 7, 1, 1, 2, 1, 3, 10])
def test_assignLevelsFromRoot(self):
"""RangeNode assignLevelsFromRoot should match hand-calculated levels"""
t = self.t3
t.assignLevelsFromRoot()
levels = [i.Level for i in t.traverse(self_before=True)]
self.assertEqual(levels, [0,1,2,3,3,2,1,2,2])
def test_assignLevelsFromLeaves(self):
"""RangeNode assignLevelsFromLeaves should match hand-calculated levels"""
t = self.t3
t.assignLevelsFromLeaves()
levels = [i.Level for i in t.traverse(self_before=True)]
self.assertEqual(levels, [3,2,1,0,0,0,1,0,0])
t.assignLevelsFromLeaves(use_min=True)
levels = [i.Level for i in t.traverse(self_before=True)]
self.assertEqual(levels, [2,1,1,0,0,0,1,0,0])
def test_attrToList(self):
"""RangeNode attrToList should return correct list of attr"""
t = self.t3
t.assignIds()
t.assignLevelsFromRoot()
#make sure nodes are in the order we expect
self.assertEqual([n.Id for n in t.traverse(self_before=True)],
[8,6,5,0,1,2,7,3,4])
#by default, should return list containing all nodes
obs = t.attrToList('Level')
self.assertEqual(obs, [3,3,2,2,2,2,1,1,0])
#should be able to do leaves only if specified
obs = t.attrToList('Level', leaves_only=True)
self.assertEqual(obs, [3,3,2,2,2])
#should be able to specify larger size
obs=t.attrToList('Level', size=12)
self.assertEqual(obs, [3,3,2,2,2,2,1,1,0,None,None,None])
#should be able to set default
obs=t.attrToList('Level', default='x', size=12)
self.assertEqual(obs, [3,3,2,2,2,2,1,1,0,'x','x','x'])
def test_attrFromList(self):
"""RangeNode attrFromList should set values correctly"""
t = self.t3
t.assignIds()
#by default, should set all nodes from array
t.attrFromList('Level', [3,3,2,2,2,2,1,1,0])
self.assertEqual([n.Level for n in t.traverse(self_before=True)], \
[0,1,2,3,3,2,1,2,2])
#should also work if we choose to set only the leaves (rest should
#stay at default values)
t.Level = -1
t.propagateAttr('Level', overwrite=True)
t.attrFromList('Level', [3,3,2,2,2,2,1,1,0], leaves_only=True)
self.assertEqual([n.Level for n in t.traverse(self_before=True)], \
[-1,-1,-1,3,3,2,-1,2,2])
def test_toBreakpoints(self):
"""RangeNode toBreakpoints should give expected list"""
t = self.t2
t.assignIds()
self.assertEqual(t.toBreakpoints(), [4,2,1,0,3,6,5])
def test_fromBreakpoints(self):
"""RangeNode fromBreakpoints should have correct topology"""
breakpoints = [4,2,1,0,3,6,5]
t = RangeNode.fromBreakpoints(breakpoints)
#check number of leaves
self.assertEqual(len(list(t.traverse())), 8)
self.assertEqual(len(list(t.traverse(self_before=True))), 15)
#check that leaves were created in right order
self.assertEqual([i.Id for i in t.traverse()], range(8))
#check that whole toplogy is right wrt ids...
nodes = list(t.traverse(self_before=True))
obs = [i.Id for i in nodes]
exp = [8, 9, 11, 13, 0, 1, 2, 12, 3, 4, 10, 14, 5, 6, 7]
self.assertEqual(obs, exp)
#...and ranges
obs = [i.LeafRange for i in nodes]
exp = [(0,8),(0,5),(0,3),(0,2),(0,1),(1,2),(2,3),(3,5),(3,4),(4,5), \
(5,8),(5,7),(5,6),(6,7),(7,8)]
self.assertEqual(obs, exp)
def test_leafLcaDepths(self):
"""RangeNode leafLcaDepths should return expected depths"""
t = self.t3
result = t.leafLcaDepths()
self.assertEqual(result, array([[0,1,2,3,3],
[1,0,2,3,3],
[2,2,0,3,3],
[3,3,3,0,1],
[3,3,3,1,0]]))
def test_randomNode(self):
"""RandomNode should hit all nodes equally"""
t = self.t3
result = {}
for i in range(100):
ans = id(t.randomNode())
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 9)
for node in t.traverse(self_before=True):
assert id(node) in result
def test_randomLeaf(self):
"""RandomLeaf should hit all leaf nodes equally"""
t = self.t3
result = {}
for i in range(100):
ans = id(t.randomLeaf())
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 5)
for node in t.traverse():
assert id(node) in result
def test_randomNodeWithNLeaves(self):
"""RandomNodeWithNLeaves should return node with correct # leaves"""
t = self.t3
#check that only the root gets selected with 5 leaves
result = {}
for i in range(20):
ans = id(t.randomNodeWithNLeaves(5))
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 1)
assert id(t) in result
#check that nothing has 6 or 4 (for this tree) leaves
self.assertRaises(KeyError, t.randomNodeWithNLeaves, 6)
self.assertRaises(KeyError, t.randomNodeWithNLeaves, 4)
#check that it works with fewer than 5 leaves
#SINGLE LEAF:
result = {}
for i in range(40):
ans = id(t.randomNodeWithNLeaves(1))
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 5)
self.assertEqual(sum(result.values()), 40)
#TWO LEAVES:
result = {}
for i in range(20):
ans = id(t.randomNodeWithNLeaves(2))
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 2)
self.assertEqual(sum(result.values()), 20)
#THREE LEAVES:
result = {}
for i in range(20):
ans = id(t.randomNodeWithNLeaves(3))
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 1)
self.assertEqual(sum(result.values()), 20)
def test_randomNodeAtLevel(self):
"""RangeNode randomNodeAtLevel should return random node at correct level"""
t = self.t3
#LEAVES:
result = {}
for i in range(40):
ans = id(t.randomNodeAtLevel(0))
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 5)
self.assertEqual(sum(result.values()), 40)
#BACK ONE LEVEL:
result = {}
for i in range(20):
ans = id(t.randomNodeAtLevel(1))
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 2)
self.assertEqual(sum(result.values()), 20)
#BACK TWO LEVELS:
result = {}
for i in range(20):
ans = id(t.randomNodeAtLevel(2))
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 1)
self.assertEqual(sum(result.values()), 20)
#BACK THREE LEVELS (to root):
result = {}
for i in range(20):
ans = id(t.randomNodeAtLevel(3))
if ans not in result:
result[ans] = 0
result[ans] += 1
self.assertEqual(len(result), 1)
self.assertEqual(sum(result.values()), 20)
self.assertEqual(result.keys()[0], id(t))
def test_outgroupLast(self):
"""RangeNode outgroupLast should reorder nodes to put outgroup last"""
t = self.t3
a, b, c, d, e = t.traverse()
self.assertEqual(t.outgroupLast(c,a,b), (a, b, c))
self.assertEqual(t.outgroupLast(c,b,a), (b, a, c))
self.assertEqual(t.outgroupLast(b,d,a), (b, a, d))
self.assertEqual(t.outgroupLast(c,d,e), (d, e, c))
self.assertEqual(t.outgroupLast(a,d,e), (d, e, a))
self.assertEqual(t.outgroupLast(a,d,b), (a, b, d))
#check that it works if we suppress the cache
self.assertEqual(t.outgroupLast(c,a,b, False), (a, b, c))
self.assertEqual(t.outgroupLast(c,b,a, False), (b, a, c))
self.assertEqual(t.outgroupLast(b,d,a, False), (b, a, d))
self.assertEqual(t.outgroupLast(c,d,e, False), (d, e, c))
self.assertEqual(t.outgroupLast(a,d,e, False), (d, e, a))
self.assertEqual(t.outgroupLast(a,d,b, False), (a, b, d))
def test_filter(self):
"""RangeNode filter should keep or omit selected nodes."""
t_orig = self.t2
t = deepcopy(t_orig)
idx = t.indexByAttr('Name')
to_keep = map(idx.__getitem__, 'abch')
curr_leaves = list(t.traverse())
t.filter(to_keep)
curr_leaves = list(t.traverse())
for i in to_keep:
assert i in curr_leaves
for i in map(idx.__getitem__, 'defg'):
assert i not in curr_leaves
#note that it collapses one-child nodes
self.assertEqual(str(t), '(((a,b),c),h)')
#test same thing but omitting
t = deepcopy(t_orig)
idx = t.indexByAttr('Name')
to_omit = map(idx.__getitem__, 'abch')
t.filter(to_omit, keep=False)
curr_leaves = list(t.traverse())
for i in to_omit:
assert i not in curr_leaves
for i in map(idx.__getitem__, 'defg'):
assert i in curr_leaves
#note that it collapses one-child nodes
self.assertEqual(str(t), '((d,e),(f,g))')
#test that it works with internal nodes
t = deepcopy(t_orig)
idx = t.indexByAttr('Name')
to_omit = [idx['a'].Parent.Parent]
t.filter(to_omit, keep=False)
self.assertEqual(str(t), '((d,e),((f,g),h))')
#test that it adds branch lengths
t = deepcopy(t_orig)
idx = t.indexByAttr('Name')
for i in t.traverse(self_after=True):
i.BranchLength = 1
to_omit = map(idx.__getitem__, 'abdefg')
t.filter(to_omit, keep=False)
self.assertEqual(str(t), '(c,h)')
#test that it got rid of the temporary '_selected' attribute
for node in t.traverse(self_before=True):
assert not hasattr(node, '_selected')
#if nothing valid in to_keep, should return empty tree
t = deepcopy(t_orig)
idx = t.indexByAttr('Name')
to_keep = []
t.filter(to_keep, keep=True)
curr_leaves = list(t.traverse())
assert len(curr_leaves), 0
#if nothing valid in to_keep, should return empty tree
t = deepcopy(t_orig)
idx = t.indexByAttr('Name')
to_keep = list('abcde') #note: just labels, not nodes
t.filter(to_keep, keep=True)
curr_leaves = list(t.traverse())
assert len(curr_leaves), 0
def test_addChildren(self):
"""RangeNode add_children should add specified # children to list"""
t = RangeNode()
t2 = RangeNode(Parent=t)
t.addChildren(5)
self.assertEqual(len(t.Children), 6)
assert t.Children[0] is t2
for c in t.Children:
assert c.Parent is t
class OldPhyloNodeTests(TestCase):
"""Tests of the PhyloNode class -- these are all now methods of RangeNode."""
def setUp(self):
"""Make a couple of standard trees"""
self.t1 = DndParser('((a,(b,c)),(d,e))', RangeNode)
#selt.t1 indices: ((0,(1,2)5)6,(3,4)7)8
def test_makeIdIndex(self):
"""RangeNode makeIdIndex should assign ids to every node"""
self.t1.makeIdIndex()
result = self.t1.IdIndex
nodes = list(self.t1.traverse(self_before=True))
#check we got an entry for each node
self.assertEqual(len(result), len(nodes))
#check the ids are in the result
for i in nodes:
assert hasattr(i, 'Id')
assert i.Id in result
def test_assignQ_single_passed(self):
"""RangeNode assignQ should propagate single Q param down tree"""
#should work if Q explicitly passed
t = self.t1
Q = ['a']
t.assignQ(Q)
for node in t.traverse(self_before=True):
assert node.Q is Q
def test_assignQ_single_set(self):
"""RangeNode assignQ should propagate single Q if set"""
t = self.t1
Q = ['a']
assert not hasattr(t, 'Q')
t.Q = Q
t.assignQ()
for node in t.traverse(self_before=True):
assert node.Q is Q
def test_assignQ_single_overwrite(self):
"""RangeNode assignQ should overwrite root Q if new Q passed"""
t = self.t1
Q = ['a']
Q2 = ['b']
t.Q = Q
t.assignQ(Q2)
for node in t.traverse(self_before=True):
assert node.Q is Q2
assert not node.Q is Q
def test_assignQ_multiple(self):
"""RangeNode assignQ should propagate multiple Qs"""
t = self.t1
Q1 = ['a']
Q2 = ['b']
Q3 = ['c']
t.makeIdIndex()
t.IdIndex[7].Q = Q1
t.IdIndex[5].Q = Q2
t.assignQ(Q3)
result = [i.Q for i in t.traverse(self_after=True)]
assert t.Q is Q3
self.assertEqual(result, [Q3,Q2,Q2,Q2,Q3,Q1,Q1,Q1,Q3])
def test_assignQ_multiple_overwrite(self):
"""RangeNode assignQ should allow overwrite"""
t = self.t1
Q1 = ['a']
Q2 = ['b']
Q3 = ['c']
t.makeIdIndex()
t.IdIndex[7].Q = Q1
t.IdIndex[5].Q = Q2
t.assignQ(Q3, overwrite=True)
for i in t.traverse(self_after=True):
assert i.Q is Q3
def test_assignQ_special(self):
"""RangeNode assignQ should work with special Qs"""
t = self.t1
Q1 = 'a'
Q2 = 'b'
Q3 = 'c'
t.makeIdIndex()
special = {7:Q1, 1:Q2}
#won't work if no Q at root
self.assertRaises(ValueError, t.assignQ, special_qs=special)
t.assignQ(Q3, special_qs=special)
result = [i.Q for i in t.traverse(self_after=True)]
self.assertEqual(result, ['c','b','c','c','c','a','a','a','c'])
def test_assignP(self):
"""RangeNode assignP should work when Qs set."""
t = self.t1
for i in t.traverse(self_before=True):
i.Length = random() * 0.5 #range 0 to 0.5
t.Q = Rates.random(DnaPairs)
t.assignQ()
t.assignP()
t.assignIds()
for node in t.traverse(self_after=True):
if node.Parent is not None:
self.assertFloatEqual(average(1-diag(node.P._data), axis=0), \
node.Length)
def test_assignLength(self):
"""RangeNode assignLength should set branch length"""
t = self.t1
t.assignLength(0.3)
for i in t.traverse(self_before=True):
self.assertEqual(i.Length, 0.3)
def test_evolve(self):
"""RangeNode evolve should work on a starting vector"""
t = self.t1
t.Q = Rates.random(DnaPairs)
t.assignQ()
t.assignLength(0.1)
t.assignP()
start = array([1,0,2,1,0,0,2,1,2,0,1,2,1,0,2,0,0,3,0,2,1,0,3,1,0,2,0,0,0,0,0,1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,3])
t.evolve(start)
for i in t.traverse():
self.assertEqual(len(i.Sequence), len(start))
self.assertNotEqual(i.Sequence, start)
#WARNING: Doesn't test base freqs etc. at this point, but those aren't
#really evolve()'s responsibity (tested as self.P.mutate(seq) once
#P is set, which we've already demonstrated works.)
def test_assignPs(self):
"""RangeNode assignPs should assign multiple scaled P matrices"""
t = self.t1
for i in t.traverse(self_before=True):
i.Length = random() * 0.5 #range 0 to 0.5
t.Q = Rates.random(DnaPairs)
t.assignQ()
t.assignPs([1, 0.5, 0.25])
t.assignIds()
for node in t.traverse(self_after=True):
if node.Parent is not None:
self.assertEqual(len(node.Ps), 3)
self.assertFloatEqual(average(1-diag(node.Ps[0]._data), axis=0), \
node.Length)
self.assertFloatEqual(average(1-diag(node.Ps[1]._data), axis=0), \
0.5*node.Length)
self.assertFloatEqual(average(1-diag(node.Ps[2]._data), axis=0), \
0.25*node.Length)
def test_evolveSeqs(self):
"""PhlyoNode evolveSeqs should evolve multiple sequences"""
t = self.t1
for i in t.traverse(self_before=True):
i.Length = 0.5
t.Q = Rates.random(DnaPairs)
t.assignQ()
t.assignPs([1, 1, 0.1])
t.assignIds()
orig_seqs = [array(i) for i in [randint(0,4,200), randint(0,4,200), \
randint(0,4,200)]]
t.evolveSeqs(orig_seqs)
for node in t.traverse(): #only look at leaves
if node.Parent is not None:
self.assertEqual(len(node.Sequences), 3)
for orig, new in zip(orig_seqs, node.Sequences):
self.assertEqual(len(orig), len(new))
self.assertNotEqual(orig, new)
assert sum(orig_seqs[1]!=node.Sequences[1]) > \
sum(orig_seqs[2]!=node.Sequences[2])
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_seqsim/test_usage.py 000644 000765 000024 00000110542 12024702176 022463 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for usage and substitution matrices.
"""
from cogent.util.unit_test import TestCase, main
from cogent.core.moltype import RNA
from cogent.core.usage import RnaBases, DnaBases, RnaPairs, DnaPairs
from cogent.core.alphabet import Alphabet
from cogent.core.sequence import ModelRnaSequence as RnaSequence, \
ModelRnaCodonSequence
from cogent.seqsim.usage import Usage, DnaUsage, RnaUsage, PairMatrix, Counts,\
Probs, Rates, goldman_q_dna_pair, goldman_q_rna_pair,\
goldman_q_dna_triple, goldman_q_rna_triple
from numpy import average, asarray, sqrt, identity, diagonal, trace, \
array, sum
from cogent.maths.matrix_logarithm import logm
from cogent.maths.matrix_exponentiation import FastExponentiator as expm
#need to find test directory to get access to the tests of the Freqs interface
try:
from os import getcwd
from sys import path
from os.path import sep,join
test_path = getcwd().split(sep)
index = test_path.index('tests')
fields = test_path[:index+1] + ["test_maths"]
test_path = sep + join(*fields)
path.append(test_path)
from test_stats.test_util import StaticFreqsTestsI
my_alpha = Alphabet('abcde')
class myUsage(Usage):
Alphabet = my_alpha
class UsageAsFreqsTests(StaticFreqsTestsI, TestCase):
"""Note that the remaining Usage methods are tested here."""
ClassToTest=myUsage
except ValueError: #couldn't find directory
pass
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
NUM_TESTS = 10 #for randomization trials
class UsageTests(TestCase):
"""Tests of the Usage object."""
def setUp(self):
"""Defines some standard test items."""
self.ab = Alphabet('ab')
class abUsage(Usage):
Alphabet = self.ab
self.abUsage = abUsage
def test_init(self):
"""Usage init should succeed only in subclasses"""
self.assertRaises(TypeError, Usage, [1,2,3,4])
self.assertEqual(self.abUsage().items(), [('a',0),('b',0)])
self.assertEqual(self.abUsage([5,6]).items(), [('a',5.0),('b',6.0)])
#should also construct from seq, if not same length as freqs
self.assertEqual(self.abUsage([0,0,1,1,1,0,1,1]).items(), \
[('a',3),('b',5)])
def test_getitem(self):
"""Usage getitem should get item via alphabet"""
u = self.abUsage([3,4])
self.assertEqual(u['a'], 3)
self.assertEqual(u['b'], 4)
def test_setitem(self):
"""Usage setitem should set item via alphabet"""
u = self.abUsage([3,4])
self.assertEqual(u['a'], 3)
u['a'] = 10
self.assertEqual(u['a'], 10)
u['b'] += 5
self.assertEqual(u['a'], 10)
self.assertEqual(u['b'], 9)
def test_str(self):
"""Usage str should print like equivalent list"""
u = self.abUsage()
self.assertEqual(str(u), "[('a', 0.0), ('b', 0.0)]")
u = self.abUsage([1,2.0])
self.assertEqual(str(u), \
"[('a', 1.0), ('b', 2.0)]")
def test_iter(self):
"""Usage iter should iterate over keys"""
u = self.abUsage([1,2])
x = tuple(u)
self.assertEqual(x, ('a', 'b'))
#should be able to convert to dict via iter
d = dict(u)
self.assertEqual(dict(u), {'a':1,'b':2})
def test_cmp(self):
"""Usage cmp should work as expected"""
a = self.abUsage([3,4])
b = self.abUsage([3,2])
c = self.abUsage([3,4])
self.assertEqual(a, a)
self.assertNotEqual(a,b)
self.assertEqual(a,c)
self.assertEqual(a==a, True)
self.assertEqual(a!=a, False)
self.assertEqual(a==b, False)
self.assertEqual(a!=b, True)
self.assertEqual(a==c, True)
self.assertEqual(a!=c, False)
self.assertEqual(a==3, False)
self.assertEqual(a!=3, True)
def test_add(self):
"""Usage add should add two sets of counts together"""
u, v = self.abUsage([1,2]), self.abUsage([6,4])
x = self.abUsage([7,6])
y = self.abUsage([7,6])
self.assertEqual(x, y)
self.assertEqual(x, u+v)
self.assertEqual(u + v, self.abUsage([7,6]))
def test_sub(self):
"""Usage sub should subtract one set of counts from the other"""
u, v = self.abUsage([1,2]), self.abUsage([6,4])
self.assertEqual(v-u, self.abUsage([5,2]))
def test_mul(self):
"""Usage mul should multiply usage by a scalar"""
u = self.abUsage([0,4])
self.assertEqual(u*3, self.abUsage([0,12]))
def test_div(self):
"""Usage div should divide usage by scalar (unsafely)"""
u = self.abUsage([0,4])
self.assertEqual(u/2, self.abUsage([0,2]))
self.assertEqual(u/8, self.abUsage([0.0,0.5]))
#note: don't need to divide by floating point to get fractions
self.assertEqual(u/8.0, self.abUsage([0.0,0.5]))
def test_scale_sum(self):
"""Usage scale_sum should scale usage to specified sum"""
u = self.abUsage([1,3])
self.assertEqual(u.scale_sum(12), self.abUsage([3.0, 9.0]))
self.assertEqual(u.scale_sum(1), self.abUsage([0.25,0.75]))
#default is sum to 1
self.assertEqual(u.scale_sum(), self.abUsage([0.25,0.75]))
def test_scale_max(self):
"""Usage scale_max should scale usage to specified max"""
u = self.abUsage([1,3])
self.assertEqual(u.scale_max(12), self.abUsage([4.0, 12.0]))
self.assertEqual(u.scale_max(1), self.abUsage([1/3.0,1.0]))
#default is max to 1
self.assertEqual(u.scale_max(), self.abUsage([1/3.0,1.0]))
def test_probs(self):
"""Usage probs should scale usage to sum to 1"""
u = self.abUsage([1,3])
self.assertEqual(u.probs(), self.abUsage([0.25,0.75]))
def test_randomIndices(self):
"""Usage randomIndices should return correct sequence."""
d = DnaUsage([0.25, 0.5, 0.1, 0.15])
s = d.randomIndices(7, [0, 0.49, 1, 0.74, 0.76, 0.86, 0.2])
self.assertEqual(s, array([0,1,3,1,2,3,0]))
s = d.randomIndices(10000)
u, c, a, g = [asarray(s==i, 'int32') for i in [0,1,2,3]]
assert 2300 < sum(u) < 2700
assert 4800 < sum(c) < 5200
assert 800 < sum(a) < 1200
assert 1300 < sum(g) < 1700
def test_fromSeqData(self):
"""Usage fromSeqData should construct from a sequence object w/ data"""
class o(object): pass
s = o()
s._data = array([0,0,0,1])
self.assertEqual(self.abUsage.fromSeqData(s), self.abUsage([3,1]))
def test_fromArray(self):
"""Usage fromArray should construct from array holding seq of indices"""
s = array([0,0,0,1])
self.assertEqual(self.abUsage.fromArray(s), self.abUsage([3,1]))
def test_get(self):
"""Usage get should behave like dict"""
u = self.abUsage([3,4])
self.assertEqual(u.get('a', 5), 3)
self.assertEqual(u.get('b', 5), 4)
self.assertEqual(u.get('x', 5), 5)
def test_values(self):
"""Usage values should return list of values in alphabet order"""
u = self.abUsage([3,4])
self.assertEqual(u.values(), [3,4])
def test_keys(self):
"""Usage keys should return list of symbols in alphabet order"""
u = self.abUsage([3,4])
self.assertEqual(u.keys(), ['a','b'])
def test_items(self):
"""Usage items should return list of key-value pairs"""
u = self.abUsage([3,4])
self.assertEqual(u.items(), [('a',3),('b',4)])
def test_entropy(self):
"""Usage items should calculate their Shannon entropy"""
#two equal choices implies one bit of entropy
u = RnaUsage([1,1,0,0])
self.assertEqual(u.entropy(), 1)
u = RnaUsage([10,10,0,0])
self.assertEqual(u.entropy(), 1)
#four equal choices implies two bits
u = RnaUsage([3,3,3,3])
self.assertEqual(u.entropy(), 2)
#only one choice -> no entropy
u = RnaUsage([3,0,0,0])
self.assertEqual(u.entropy(), 0)
#empty usage also has no entropy
u = RnaUsage([0,0,0,0])
self.assertEqual(u.entropy(), 0)
#calculated this one by hand
u = RnaUsage([.5,.3,.1,.1])
self.assertFloatEqual(u.entropy(),1.6854752972273346)
class PairMatrixTests(TestCase):
"""Tests of the PairMatrix base class."""
def setUp(self):
"""Define standard alphabet and matrices for tests."""
self.ab = Alphabet('ab')
self.ab_pairs = self.ab*self.ab
self.empty = PairMatrix([0,0,0,0], self.ab_pairs)
self.named = PairMatrix([[1,2],[3,4]], self.ab_pairs, 'name')
def test_init(self):
"""PairMatrix init requires data and alphabet"""
#should only care about number of elements, not shape
p = PairMatrix([1,2,3,4,5,6,7,8,1,2,3,4,5,6,7,8], RnaPairs)
assert p.Alphabet is RnaPairs
self.assertEqual(len(p._data), 4)
self.assertEqual(len(p._data.flat), 16)
self.assertEqual(p._data[0], array([1,2,3,4]))
self.assertEqual(p._data[1], array([5,6,7,8]))
def test_init_bad(self):
"""PairMatrix init should fail if data wrong length"""
self.assertRaises(ValueError, PairMatrix, [1,2,3,4], RnaPairs)
#should also require alphabet
self.assertRaises(TypeError, PairMatrix, [1,2,3,4])
def test_toMatlab(self):
"""PairMatrix toMatlab should return correct format string"""
self.assertEqual(self.empty.toMatlab(), "m=[0.0 0.0;\n0.0 0.0];\n")
self.assertEqual(self.named.toMatlab(), \
"name=[1.0 2.0;\n3.0 4.0];\n")
def test_str(self):
"""PairMatrix __str__ should return string correpsonding to data"""
self.assertEqual(str(self.named), str(self.named._data))
def test_repr(self):
"""PairMatrix __repr__ should return reconstructable string"""
self.assertEqual(repr(self.named), \
'PairMatrix('+ repr(self.named._data) + ',' +\
repr(self.ab_pairs)+",'name')")
def test_getitem(self):
"""PairMatrix __getitem__ should translate indices and get from array"""
n = self.named
self.assertEqual(n['a'], array([1,2]))
self.assertEqual(n['b'], array([3,4]))
self.assertEqual(n['a','a'], 1)
self.assertEqual(n['a','b'], 2)
self.assertEqual(n['b','a'], 3)
self.assertEqual(n['b','b'], 4)
#WARNING: m[a][b] doesn't work b/c indices not translated!
#must access as m[a,b] instead.
try:
x = n['a']['b']
except ValueError:
pass
#should work even if SubAlphabets not the same
a = Alphabet('ab')
x = Alphabet('xyz')
j = a * x
m = PairMatrix([1,2,3,4,5,6], j)
self.assertEqual(m['a','x'], 1)
self.assertEqual(m['a','y'], 2)
self.assertEqual(m['a','z'], 3)
self.assertEqual(m['b','x'], 4)
self.assertEqual(m['b','y'], 5)
self.assertEqual(m['b','z'], 6)
#should work even if SubAlphabets are different types
a = Alphabet([1,2,3])
b = Alphabet(['abc', 'xyz'])
j = a * b
m = PairMatrix([1,2,3,4,5,6], j)
self.assertEqual(m[1,'abc'], 1)
self.assertEqual(m[1,'xyz'], 2)
self.assertEqual(m[2,'abc'], 3)
self.assertEqual(m[2,'xyz'], 4)
self.assertEqual(m[3,'abc'], 5)
self.assertEqual(m[3,'xyz'], 6)
self.assertEqual(list(m[2]), [3,4])
#gives KeyError if single item not present in first level
self.assertRaises(KeyError, m.__getitem__, 'x')
def test_empty(self):
"""PairMatrix empty classmethod should produce correct class"""
p = PairMatrix.empty(self.ab_pairs)
self.assertEqual(p._data.flat, array([0,0,0,0]))
self.assertEqual(p._data, array([[0,0],[0,0]]))
self.assertEqual(p._data.shape, (2,2))
def test_eq(self):
"""Pairmatrix test for equality should check all elements"""
p = self.ab_pairs
a = PairMatrix.empty(p)
b = PairMatrix.empty(p)
assert a is not b
self.assertEqual(a, b)
c = PairMatrix([1,2,3,4], p)
d = PairMatrix([1,2,3,4], p)
assert c is not d
self.assertEqual(c, d)
self.assertNotEqual(a, c)
#Note: still compare equal if alphabets are different
x = Alphabet('xy')
x = x*x
y = PairMatrix([1,2,3,4], x)
self.assertEqual(y, c)
#should check all elements, not just first
c = PairMatrix([1,1,1,1], p)
d = PairMatrix([1,1,1,4], p)
assert c is not d
self.assertNotEqual(c, d)
def test_ne(self):
"""PairMatrix test for inequality should check all elements"""
p = self.ab_pairs
a = PairMatrix.empty(p)
b = PairMatrix.empty(p)
c = PairMatrix([1,2,3,4], p)
d = PairMatrix([1,2,3,4], p)
assert a != c
assert a == b
assert c == d
#Note: still compare equal if alphabets are different
x = Alphabet('xy')
x = x*x
y = PairMatrix([1,2,3,4], x)
assert y == c
#should check all elements, not just first
c = PairMatrix([1,1,1,1], p)
d = PairMatrix([1,1,1,4], p)
assert c != d
def test_iter(self):
"""PairMatrix __iter__ should iterate over rows."""
p = self.ab_pairs
c = PairMatrix([1,2,3,4], p)
l = list(c)
self.assertEqual(len(l), 2)
self.assertEqual(list(l[0]), [1,2])
self.assertEqual(list(l[1]), [3,4])
def test_len(self):
"""PairMatrix __len__ should return number of rows"""
p = self.ab_pairs
c = PairMatrix([1,2,3,4], p)
self.assertEqual(len(c), 2)
class CountsTests(TestCase):
"""Tests of the Counts class, including inferring counts from sequences."""
def test_toProbs(self):
"""Counts toProbs should return valid prob matrix."""
c = Counts([1,2,3,4,2,2,2,2,0.2,0.4,0.6,0.8,1,0,0,0], RnaPairs)
p = c.toProbs()
assert isinstance(p, Probs)
self.assertEqual(p, Probs([0.1,0.2,0.3,0.4,0.25,0.25,0.25,0.25, \
0.1,0.2,0.3,0.4,1.0,0.0,0.0,0.0], RnaPairs))
self.assertEqual(p['U','U'], 0.1)
self.assertEqual(p['G','U'], 1.0)
self.assertEqual(p['G','G'], 0.0)
def test_fromPair(self):
"""Counts fromPair should return correct counts."""
s = Counts.fromPair( RnaSequence('UCCGAUCGAUUAUCGGGUACGUA'), \
RnaSequence('GUCGAGUAUAGCGUACGGCUACG'),
RnaPairs)
assert isinstance(s, Counts)
vals = [
('U','U',0),('U','C',2.5),('U','A',1),('U','G',2.5),
('C','U',2.5),('C','C',1),('C','A',1),('C','G',0.5),
('A','U',1),('A','C',1),('A','A',1),('A','G',2),
('G','U',2.5),('G','C',0.5),('G','A',2),('G','G',2),
]
for i, j, val in vals:
self.assertFloatEqual(s[i,j], val)
#check that it works for big seqs
s = Counts.fromPair( RnaSequence('UCAG'*1000), \
RnaSequence('UGAG'*1000),
RnaPairs)
assert isinstance(s, Counts)
vals = [
('U','U',1000),('U','C',0),('U','A',0),('U','G',0),
('C','U',0),('C','C',0),('C','A',0),('C','G',500),
('A','U',0),('A','C',0),('A','A',1000),('A','G',0),
('G','U',0),('G','C',500),('G','A',0),('G','G',1000),
]
for i, j, val in vals:
self.assertFloatEqual(s[i,j], val)
#check that it works for codon seqs
s1 = ModelRnaCodonSequence('UUCGCG')
s2 = ModelRnaCodonSequence('UUUGGG')
c = Counts.fromPair(s1, s2, RNA.Alphabet.Triples**2)
self.assertEqual(c._data.sum(), 2)
self.assertEqual(c._data[0,1], 0.5)
self.assertEqual(c._data[1,0], 0.5)
self.assertEqual(c._data[55,63], 0.5)
self.assertEqual(c._data[63,55], 0.5)
def test_fromTriple(self):
"""Counts fromTriple should return correct counts."""
cft = Counts.fromTriple
rs = RnaSequence
A, C, G, U = map(rs, 'ACGU')
#counts if different from both the other groups
s = cft(A, C, C, RnaPairs)
assert isinstance(s, Counts)
self.assertEqual(s['C','A'], 1)
self.assertEqual(s['A','C'], 0)
self.assertEqual(s['C','C'], 0)
#try it with longer sequences
AAA, CCC = map(rs, ['AAA', 'CCC'])
s = cft(AAA, CCC, CCC, RnaPairs)
self.assertEqual(s['C','A'], 3)
self.assertEqual(s['A','C'], 0)
#doesn't count if all three differ
ACG, CGA, GAC = map(rs, ['ACG','CGA','GAC'])
s = cft(ACG, CGA, GAC, RnaPairs)
self.assertEqual(s['C','A'], 0)
self.assertEqual(s['A','C'], 0)
self.assertEqual(s, Counts.empty(RnaPairs))
#counts as no change if same as other sequence...
s = cft(AAA, AAA, CCC, RnaPairs)
self.assertEqual(s['A','A'], 3)
self.assertEqual(s['A','C'], 0)
#...or same as the outgroup
s = cft(AAA, CCC, AAA, RnaPairs)
self.assertEqual(s['A','A'], 3)
self.assertEqual(s['A','C'], 0)
#spot-check a mixed example
s = cft( \
rs('AUCGCUAGCAUACGUCA'),
rs('AAGCUGCGUAGCGCAUA'),
rs('GCGCAUAUGACGAUAGC'),
RnaPairs
)
vals = [
('U','U',1),('U','C',0),('U','A',0),('U','G',0),
('C','U',0),('C','C',0),('C','A',0),('C','G',1),
('A','U',1),('A','C',0),('A','A',4),('A','G',0),
('G','U',0),('G','C',1),('G','A',0),('G','G',1),
]
for i, j, val in vals:
self.assertFloatEqual(s[i,j], val)
#check a long sequence
s = cft( \
rs('AUCGCUAGCAUACGUCA'*1000),
rs('AAGCUGCGUAGCGCAUA'*1000),
rs('GCGCAUAUGACGAUAGC'*1000),
RnaPairs
)
vals = [
('U','U',1000),('U','C',0),('U','A',0),('U','G',0),
('C','U',0),('C','C',0),('C','A',0),('C','G',1000),
('A','U',1000),('A','C',0),('A','A',4000),('A','G',0),
('G','U',0),('G','C',1000),('G','A',0),('G','G',1000),
]
for i, j, val in vals:
self.assertFloatEqual(s[i,j], val)
#check that it works when forced to use both variants of fromTriple
s = cft( \
rs('AUCGCUAGCAUACGUCA'*1000),
rs('AAGCUGCGUAGCGCAUA'*1000),
rs('GCGCAUAUGACGAUAGC'*1000),
RnaPairs,
threshold=0 #forces "large" method
)
vals = [
('U','U',1000),('U','C',0),('U','A',0),('U','G',0),
('C','U',0),('C','C',0),('C','A',0),('C','G',1000),
('A','U',1000),('A','C',0),('A','A',4000),('A','G',0),
('G','U',0),('G','C',1000),('G','A',0),('G','G',1000),
]
for i, j, val in vals:
self.assertFloatEqual(s[i,j], val)
s = cft( \
rs('AUCGCUAGCAUACGUCA'*1000),
rs('AAGCUGCGUAGCGCAUA'*1000),
rs('GCGCAUAUGACGAUAGC'*1000),
RnaPairs,
threshold=1e12 #forces "small" method
)
vals = [
('U','U',1000),('U','C',0),('U','A',0),('U','G',0),
('C','U',0),('C','C',0),('C','A',0),('C','G',1000),
('A','U',1000),('A','C',0),('A','A',4000),('A','G',0),
('G','U',0),('G','C',1000),('G','A',0),('G','G',1000),
]
for i, j, val in vals:
self.assertFloatEqual(s[i,j], val)
#check that it works for codon seqs
s1 = ModelRnaCodonSequence('UUCGCG')
s2 = ModelRnaCodonSequence('UUUGGG')
s3 = s2
c = Counts.fromTriple(s1, s2, s3, RNA.Alphabet.Triples**2)
self.assertEqual(c._data.sum(), 2)
self.assertEqual(c._data[0,1], 1)
self.assertEqual(c._data[63,55], 1)
class ProbsTests(TestCase):
"""Tests of the Probs class."""
def setUp(self):
"""Define an alphabet and some probs."""
self.ab = Alphabet('ab')
self.ab_pairs = self.ab**2
def test_isValid(self):
"""Probs isValid should return True if it's a prob matrix"""
a = self.ab_pairs
m = Probs([0.5,0.5,1,0], a)
self.assertEqual(m.isValid(), True)
#fails if don't sum to 1
m = Probs([0.5, 0, 1, 0], a)
self.assertEqual(m.isValid(), False)
#fails if negative elements
m = Probs([1, -1, 0, 1], a)
self.assertEqual(m.isValid(), False)
def test_makeModel(self):
"""Probs makeModel should return correct substitution pattern"""
a = Alphabet('abc')**2
m = Probs([0.5,0.25,0.25,0.1,0.8,0.1,0.3,0.6,0.1], a)
obs = m.makeModel(array([0,1,1,0,2,2]))
exp = array([[0.5,0.25,0.25],[0.1,0.8,0.1],[0.1,0.8,0.1],\
[0.5,0.25,0.25],[0.3,0.6,0.1],[0.3,0.6,0.1]])
self.assertEqual(obs, exp)
def test_mutate(self):
"""Probs mutate should return correct vector from input vector"""
a = Alphabet('abc')**2
m = Probs([0.5,0.25,0.25,0.1,0.8,0.1,0.3,0.6,0.1], a)
#because of fp math in accumulate, can't predict boundaries exactly
#so add/subtract eps to get the result we expect
eps = 1e-6
# a b b a c c a b c
seq = array([0,1,1,0,2,2,0,1,2])
random_vec = array([0,.01,.8-eps,1,1,.3,.05,.9+eps,.95])
self.assertEqual(m.mutate(seq, random_vec), \
# a a b c c a a c c
array([0,0,1,2,2,0,0,2,2]))
#check that freq. distribution is about right
seqs = array([m.mutate(seq) for i in range(1000)])
#WARNING: bool operators return byte arrays, whose sums wrap at 256!
zero_count = asarray(seqs == 0, 'int32')
sums = sum(zero_count, axis=0)
#expect: 500, 100, 100, 500, 300, 300, 500, 100, 300
#std dev = sqrt(npq), which is sqrt(250), sqrt(90), sqrt(210)
means = array([500, 100, 100, 500, 300, 300, 500, 100, 300])
var = array([250, 90, 90, 250, 210, 210, 250, 90, 210])
three_sd = 3 * sqrt(var)
for obs, exp, sd in zip(sums, means, three_sd):
assert exp - 2*sd < obs < exp + 2*sd
def test_toCounts(self):
"""Probs toCounts should return counts object w/ right numbers"""
a = Alphabet('abc')**2
m = Probs([0.5,0.25,0.25,0.1,0.8,0.1,0.3,0.6,0.1], a)
obs = m.toCounts(30)
assert isinstance(obs, Counts)
exp = Counts([[5.,2.5,2.5,1,8,1,3,6,1]], a)
self.assertEqual(obs, exp)
def test_toRates(self):
"""Probs toRates should return log of probs, optionally normalized"""
a = Alphabet('abc')**2
p = Probs([0.9,0.05,0.05,0.1,0.85,0.05,0.02,0.02,0.96], a)
assert p.isValid()
r = p.toRates()
assert isinstance(r, Rates)
assert r.isValid()
assert not r.isComplex()
self.assertEqual(r._data, logm(p._data))
r_norm = p.toRates(normalize=True)
self.assertFloatEqual(trace(r_norm._data), -1.0)
def test_random_p_matrix(self):
"""Probs random should return random Probsrows that sum to 1"""
for i in range(NUM_TESTS):
p = Probs.random(RnaPairs)._data
for i in p:
self.assertFloatEqual(sum(i), 1.0)
#length should be 4 by default
self.assertEqual(len(p), 4)
self.assertEqual(len(p[0]), 4)
def test_random_p_matrix_diag(self):
"""Probs random should work with a scalar diagonal"""
#if diagonal is 1, off-diagonal elements should be 0
for i in range(NUM_TESTS):
p = Probs.random(RnaPairs, 1)._data
self.assertEqual(p, identity(4, 'd'))
#if diagonal is between 0 and 1, rows should sum to 1
for i in range(NUM_TESTS):
p = Probs.random(RnaPairs, 0.5)._data
for i in range(4):
self.assertFloatEqual(sum(p[i]), 1.0)
self.assertEqual(p[i][i], 0.5)
assert min(p[i]) >= 0
assert max(p[i]) <= 1
#if diagonal > 1, rows should still sum to 1
for i in range(NUM_TESTS):
p = Probs.random(RnaPairs, 2)._data
for i in range(4):
self.assertEqual(p[i][i], 2.0)
self.assertFloatEqual(sum(p[i]), 1.0)
assert min(p[i]) < 0
def test_random_p_matrix_diag_vector(self):
"""Probs random should work with a vector diagonal"""
for i in range(NUM_TESTS):
diag = [0, 0.2, 0.6, 1.0]
p = Probs.random(RnaPairs, diag)._data
for i, d, row in zip(range(4), diag, p):
self.assertFloatEqual(sum(row), 1.0)
self.assertEqual(row[i], diag[i])
class RatesTests(TestCase):
"""Tests of the Rates class."""
def setUp(self):
"""Define standard alphabets."""
self.abc = Alphabet('abc')
self.abc_pairs = self.abc**2
def test_init(self):
"""Rates init should take additional parameter to normalize"""
r = Rates([-2,1,1,0,-1,1,0,0,0], self.abc_pairs)
self.assertEqual(r._data, array([[-2,1,1],[0,-1,1],[0,0,0]]))
r = Rates([-2.5,1,1,0,-1,1,0,0,0], self.abc_pairs)
self.assertEqual(r._data, array([[-2.5,1.,1.],[0.,-1.,1.],[0.,0.,0.]]))
r = Rates([-2,1,1,0,-1,1,2,0,-1], self.abc_pairs, normalize=True)
self.assertEqual(r._data, \
array([[-0.5,.25,.25],[0.,-.25,.25],[.5,0.,-.25]]))
def test_isComplex(self):
"""Rates isComplex should return True if complex elements"""
r = Rates([0,0,0.1j,0,0,0,0,0,0], self.abc_pairs)
assert r.isComplex()
r = Rates([0,0,0.1,0,0,0,0,0,0], self.abc_pairs)
assert not r.isComplex()
def test_isSignificantlyComplex(self):
"""Rates isSignificantlyComplex should be true if large imag component"""
r = Rates([0,0,0.2j,0,0,0,0,0,0], self.abc_pairs)
assert r.isSignificantlyComplex()
assert r.isSignificantlyComplex(0.01)
assert not r.isSignificantlyComplex(0.2)
assert not r.isSignificantlyComplex(0.3)
r = Rates([0,0,0.1,0,0,0,0,0,0], self.abc_pairs)
assert not r.isSignificantlyComplex()
assert not r.isSignificantlyComplex(1e-30)
assert not r.isSignificantlyComplex(1e3)
def test_isValid(self):
"""Rates isValid should check row sums and neg off-diags"""
r = Rates([-2,1,1,0,-1,1,0,0,0], self.abc_pairs)
assert r.isValid()
r = Rates([0,0,0,0,0,0,0,0,0], self.abc_pairs)
assert r.isValid()
#not valid if negative off-diagonal
r = Rates([-2,-1,3,1,-1,0,2,2,-4], self.abc_pairs)
assert not r.isValid()
#not valid if rows don't all sum to 0
r = Rates([0,0.0001,0,0,0,0,0,0,0], self.abc_pairs)
assert not r.isValid()
def test_normalize(self):
"""Rates normalize should return normalized copy of self where trace=-1"""
r = Rates([-2,1,1,0,-1,1,2,0,-1], self.abc_pairs)
n = r.normalize()
self.assertEqual(n._data, \
array([[-0.5,.25,.25],[0.,-.25,.25],[.5,0.,-.25]]))
#check that we didn't change the original
assert n._data is not r._data
self.assertEqual(r._data, \
array([[-2,1,1,],[0,-1,1,],[2,0,-1]]))
def test_toProbs(self):
"""Rates toProbs should return correct probability matrix"""
a = self.abc_pairs
p = Probs([0.75, 0.1, 0.15, 0.2, 0.7, 0.1, 0.05, 0.1, 0.85], a)
q = p.toRates()
self.assertEqual(q._data, logm(p._data))
p2 = q.toProbs()
self.assertFloatEqual(p2._data, p._data)
#test a case that didn't work for DNA
q = Rates(array(
[[-0.64098451, 0.0217681 , 0.35576469, 0.26345171],
[ 0.31144238, -0.90915091, 0.25825858, 0.33944995],
[ 0.01578521, 0.43162879, -0.99257581, 0.54516182],
[ 0.13229986, 0.04027147, 0.05817791, -0.23074925]]),
DnaPairs)
self.assertFloatEqual(q.toProbs(0.5)._data, expm(q._data)(t=0.5))
def test_timeForSimilarity(self):
"""Rates timeToSimilarity should return correct time"""
a = self.abc_pairs
p = Probs([0.75, 0.1, 0.15, 0.2, 0.7, 0.1, 0.05, 0.15, 0.8], a)
q = p.toRates()
d = 0.5
t = q.timeForSimilarity(d)
x = expm(q._data)(t)
self.assertFloatEqual(average(diagonal(x), axis=0), d)
t = q.timeForSimilarity(d, array([1/3.0]*3))
x = expm(q._data)(t)
self.assertFloatEqual(average(diagonal(x), axis=0), d)
self.assertEqual(q.timeForSimilarity(1), 0)
def test_toSimilarProbs(self):
"""Rates toSimilarProbs should match individual steps"""
a = self.abc_pairs
p = Probs([0.75, 0.1, 0.15, 0.2, 0.7, 0.1, 0.05, 0.15, 0.8], a)
q = p.toRates()
self.assertEqual(q.toSimilarProbs(0.5), \
q.toProbs(q.timeForSimilarity(0.5)))
#test a case that didn't work for DNA
q = Rates(array(
[[-0.64098451, 0.0217681 , 0.35576469, 0.26345171],
[ 0.31144238, -0.90915091, 0.25825858, 0.33944995],
[ 0.01578521, 0.43162879, -0.99257581, 0.54516182],
[ 0.13229986, 0.04027147, 0.05817791, -0.23074925]]),
DnaPairs)
p = q.toSimilarProbs(0.66)
self.assertFloatEqual(average(diagonal(p._data), axis=0), 0.66)
def test_random_q_matrix(self):
"""Rates random should return matrix of correct size"""
for i in range(NUM_TESTS):
q = Rates.random(RnaPairs)._data
self.assertEqual(len(q), 4)
self.assertEqual(len(q[0]), 4)
for row in q:
self.assertFloatEqual(sum(row), 0.0)
assert min(row) < 0
assert max(row) > 0
l = list(row)
l.sort()
assert min(l[1:]) >= 0
assert max(l[1:]) <= 1
def test_random_q_matrix_diag(self):
"""Rates random should set diagonal correctly from scalar"""
for i in range(NUM_TESTS):
q = Rates.random(RnaPairs, -1)._data
self.assertEqual(len(q), 4)
for i, row in enumerate(q):
self.assertFloatEqual(sum(row), 0)
self.assertEqual(row[i], -1)
assert max(row) <= 1
l = list(row)
l.sort()
assert min(l[1:]) >= 0
assert max(l[1:]) <= 1
for i in range(NUM_TESTS):
q = Rates.random(RnaPairs, -5)._data
self.assertEqual(len(q), 4)
for i, row in enumerate(q):
self.assertFloatEqual(sum(row), 0)
self.assertEqual(row[i], -5)
assert max(row) <= 5
l = list(row)
l.sort()
assert min(l[1:]) >= 0
assert max(l[1:]) <= 5
def test_random_q_matrix_diag_vector(self):
"""Rates random should init with vector as diagonal"""
diag = [1, -1, 2, -2]
for i in range(NUM_TESTS):
q = Rates.random(RnaPairs, diag)._data
for i, d, row in zip(range(4), diag, q):
self.assertFloatEqual(sum(row, axis=0), 0.0)
self.assertEqual(row[i], diag[i])
def test_fixNegsDiag(self):
"""Rates fixNegsDiag should fix negatives by adding to diagonal"""
q = Rates([[-6,2,2,2],[-6,-2,4,4],[2,2,-6,2],[4,4,-2,-6]], RnaPairs)
m = q.fixNegsDiag()._data
self.assertEqual(m,array([[-6,2,2,2],[0,-8,4,4],[2,2,-6,2],[4,4,0,-8]]))
def test_fixNegsEven(self):
"""Rates fixNegsEven should fix negatives by adding evenly to others"""
q = Rates([[-6,2,2,2],[-3,-2,3,2],[-2,-2,-6,2],[4,4,-6,-2]], RnaPairs)
m = q.fixNegsEven()._data
self.assertEqual(m,array([[-6,2,2,2],[0,-3,2,1],[0,0,-0,0],[2,2,0,-4]]))
def test_fixNegsFmin(self):
"""Rates fixNegsFmin should fix negatives using fmin method"""
q = Rates(array([[-0.28936029, 0.14543346, -0.02648614, 0.17041297],
[ 0.00949624, -0.31186005, 0.17313171, 0.1292321 ],
[ 0.10443209, 0.16134479, -0.30480186, 0.03902498],
[ 0.01611264, 0.12999161, 0.15558259, -0.30168684]]), DnaPairs)
r = q.fixNegsFmin()
assert not q.isValid()
assert r.isValid()
def test_fixNegsConstrainedOpt(self):
"""Rates fixNegsConstrainedOpt should fix negatives w/ constrained opt"""
q = Rates(array([[-0.28936029, 0.14543346, -0.02648614, 0.17041297],
[ 0.00949624, -0.31186005, 0.17313171, 0.1292321 ],
[ 0.10443209, 0.16134479, -0.30480186, 0.03902498],
[ 0.01611264, 0.12999161, 0.15558259, -0.30168684]]), DnaPairs)
r = q.fixNegsFmin()
assert not q.isValid()
assert r.isValid()
def test_fixNegsReflect(self):
"""Rates fixNegsReflect should reflect negatives across diagonal"""
ab = Alphabet('ab')**2
#should leave matrix alone if no off-diagonal elements
q = Rates([0,0,1,-1], ab)
self.assertEqual(q.fixNegsReflect()._data, array([[0,0],[1,-1]]))
q = Rates([-2,2,1,-1], ab)
self.assertEqual(q.fixNegsReflect()._data, array([[-2,2],[1,-1]]))
#should work if precisely one off-diag element in a pair is negative
q = Rates([2,-2,1,-1], ab)
self.assertEqual(q.fixNegsReflect()._data, array([[0,0],[3,-3]]))
q = Rates([-1,1,-2,2], ab)
self.assertEqual(q.fixNegsReflect()._data, array([[-3,3],[0,-0]]))
#should work if both off-diag elements in a pair are negative
q = Rates([1,-1,-2,2], ab)
self.assertEqual(q.fixNegsReflect()._data, array([[-2,2],[1,-1]]))
q = Rates([2,-2,-1,1], ab)
self.assertEqual(q.fixNegsReflect()._data, array([[-1,1],[2,-2]]))
q = Rates([[ 0, 3, -2, -1],
[ 2, -1, 2, -3],
[-1, -1, 2, 0],
[-3, 2, 0, 1]], RnaPairs)
q2 = q.fixNegsReflect()
self.assertEqual(q2._data, \
array([[-7, 3, 1, 3],
[ 2, -5, 3, 0],
[ 2, 0, -2, 0],
[ 1, 5, 0, -6]]))
class GoldmanTests(TestCase):
def setUp(self):
pass
def test_goldman_q_dna_pair(self):
"""Should return expected rate matrix"""
seq1 = "ATGCATGCATGC"
seq2 = "AAATTTGGGCCC"
expected = array([[-(2/3.0), (1/3.0), (1/3.0), 0],
[(1/3.0), -(2/3.0), 0, (1/3.0)],
[(1/3.0), 0, -(2/3.0), (1/3.0)],
[0, (1/3.0), (1/3.0), -(2/3.0)]])
observed = goldman_q_dna_pair(seq1, seq2)
self.assertFloatEqual(observed, expected)
def test_goldman_q_rna_pair(self):
"""Should return expected rate matrix"""
seq1 = "AUGCAUGCAUGC"
seq2 = "AAAUUUGGGCCC"
expected = array([[-(2/3.0), (1/3.0), (1/3.0), 0],
[(1/3.0), -(2/3.0), 0, (1/3.0)],
[(1/3.0), 0, -(2/3.0), (1/3.0)],
[0, (1/3.0), (1/3.0), -(2/3.0)]])
observed = goldman_q_rna_pair(seq1, seq2)
self.assertFloatEqual(observed, expected)
def test_goldman_q_dna_triple(self):
"""Should return expected rate matrix"""
seq1 = "ATGCATGCATGC"
seq2 = "AAATTTGGGCCC"
outgroup = "AATTGGCCAATT"
expected = array([[-(1/2.0), (1/2.0), 0, 0],
[0, 0, 0, 0],
[(1/3.0), 0, -(1/3.0), 0],
[0, 0, 0, 0]])
observed = goldman_q_dna_triple(seq1, seq2, outgroup)
self.assertFloatEqual(observed, expected)
def test_goldman_q_rna_triple(self):
"""Should return expected rate matrix"""
seq1 = "AUGCAUGCAUGC"
seq2 = "AAAUUUGGGCCC"
outgroup = "AAUUGGCCAAUU"
expected = array([[-(1/2.0), (1/2.0), 0, 0],
[0, 0, 0, 0],
[(1/3.0), 0, -(1/3.0), 0],
[0, 0, 0, 0]])
observed = goldman_q_rna_triple(seq1, seq2, outgroup)
self.assertFloatEqual(observed, expected)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/__init__.py 000644 000765 000024 00000002540 12024702176 021666 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_aaindex',
'test_agilent_microarray',
'test_blast',
'test_bpseq',
'test_cigar',
'test_clustal',
'test_cutg',
'test_dialign',
'test_ebi',
'test_fasta',
'test_fastq',
'test_genbank',
'test_illumina_sequence',
'test_locuslink',
'test_mage',
'test_meme',
'test_msms',
'test_ncbi_taxonomy',
'test_nexus',
'test_pdb',
'test_structure',
'test_phylip',
'test_record',
'test_record_finder',
'test_rfam',
'test_rna_fold',
'test_rnaview',
'test_sprinzl',
'test_tree',
'test_unigene'
'test_stride']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann", "Catherine Lozuopone", "Gavin Huttley",
"Rob Knight", "Sandra Smit", "Micah Hamady",
"Jeremy Widmann", "Hua Ying", "Greg Caporaso",
"Zongzhi Liu", "Jason Carnes", "Peter Maxwell",
"Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_parse/test_aaindex.py 000644 000765 000024 00000133710 12024702176 022603 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of the AAIndex parser.
"""
from cogent.util.unit_test import TestCase, main
from cogent.parse.aaindex import AAIndex1Parser, AAIndex2Parser,\
AAIndexRecord, AAIndex1Record, AAIndex2Record, AAIndex1FromFiles,\
AAIndex2FromFiles
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Greg Caporaso", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Greg Caporaso"
__email__ = "caporaso@colorado.edu"
__status__ = "Production"
class test_aaindex1_parser(TestCase):
""" Tests aindex1_parser class """
def setUp(self):
""" Setup some variables """
self._fake_file = list(fake_file_aaindex1.split('\n'))
self.AAIndexObjects = AAIndex1FromFiles(self._fake_file)
def test_init(self):
""" AAI1: Test that init run w/o error """
aa1p = AAIndex1Parser()
def test_read_file_as_list(self):
"""AAI1: Test that a file is correctly opened as a list """
aap = AAIndex1Parser()
AAIndexObjects = aap(self._fake_file)
def test_correct_num_of_records(self):
"""AAI1: Test that one object is created per record """
self.assertEqual(6, len(self.AAIndexObjects))
def test_ID_entries(self):
""" AAI1: Test ID Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].ID, 'ANDN920101')
self.assertEqual(self.AAIndexObjects['ARGP820103'].ID, 'ARGP820103')
self.assertEqual(self.AAIndexObjects['JURD980101'].ID, 'JURD980101')
def test_single_line_Description_entries(self):
""" AAI1: Test Single Line Description Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].Description,\
'alpha-CH chemical shifts (Andersen et al., 1992)')
self.assertEqual(self.AAIndexObjects['ARGP820103'].Description,\
'Membrane-buried preference parameters (Argos et al., 1982)')
def test_multi_line_Description_entries(self):
""" AAI1: Test Multi Line Description Entries """
self.assertEqual(self.AAIndexObjects['JURD980101'].Description,\
'Modified Kyte-Doolittle hydrophobicity scale (Juretic et al., 1998)')
def test_LITDB_entries(self):
""" AAI1: Test LITDB Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].LITDBEntryNum,\
'LIT:1810048b PMID:1575719')
self.assertEqual(self.AAIndexObjects['ARGP820103'].LITDBEntryNum,\
'LIT:0901079b PMID:7151796')
self.assertEqual(self.AAIndexObjects['JURD980101'].LITDBEntryNum,\
'')
def test_Authors_entries(self):
""" AAI1: Test Authors Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].Authors,\
'Andersen, N.H., Cao, B. and Chen, C.')
self.assertEqual(self.AAIndexObjects['ARGP820103'].Authors,\
'Argos, P., Rao, J.K.M. and Hargrave, P.A.')
self.assertEqual(self.AAIndexObjects['JURD980101'].Authors,\
'Juretic, D., Lucic, B., Zucic, D. and Trinajstic, N.')
def test_mult_line_Title_entries(self):
""" AAI1: Test Multi Line Title Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].Title,\
'Peptide/protein structure analysis using the chemical shift index ' +\
'method: upfield alpha-CH values reveal dynamic helices and aL sites')
self.assertEqual(self.AAIndexObjects['JURD980101'].Title,\
'Protein transmembrane structure: recognition and prediction by ' +\
'using hydrophobicity scales through preference functions')
def test_sing_line_Title_entries(self):
""" AAI1: Test Single Line Title Entries """
self.assertEqual(self.AAIndexObjects['ARGP820103'].Title,\
'Structural prediction of membrane-bound proteins')
def test_Citation_entries(self):
""" AAI1: Test Citation Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].Citation,\
'Biochem. and Biophys. Res. Comm. 184, 1008-1014 (1992)')
self.assertEqual(self.AAIndexObjects['ARGP820103'].Citation,\
'Eur. J. Biochem. 128, 565-575 (1982)')
self.assertEqual(self.AAIndexObjects['JURD980101'].Citation,\
'Theoretical and Computational Chemistry, 5, 405-445 (1998)')
def test_Comments_entries(self):
""" AAI1: Test Comments Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].Comments,\
'')
self.assertEqual(self.AAIndexObjects['ARGP820103'].Comments,\
'')
self.assertEqual(self.AAIndexObjects['JURD980101'].Comments,\
'')
self.assertEqual(self.AAIndexObjects['TSAJ990102'].Comments,\
'(Cyh 113.7)')
def test_single_line_Correlating_entries(self):
""" AAI1: Test single line Correlating Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].\
Correlating['BUNA790102'], 0.949)
def test_empty_Correlating_entries(self):
""" AAI1: Test empty Correlating Entries """
self.assertEqual(self.AAIndexObjects['WILM950104'].Correlating, {})
def test_multi_line_Correlating_entries(self):
""" AAI1: Test multi line Correlating Entries """
self.assertEqual(self.AAIndexObjects['ARGP820103'].\
Correlating['ARGP820102'], 0.961)
self.assertEqual(self.AAIndexObjects['ARGP820103'].\
Correlating['MIYS850101'], 0.822)
self.assertEqual(self.AAIndexObjects['ARGP820103'].\
Correlating['JURD980101'], 0.800)
self.assertEqual(self.AAIndexObjects['JURD980101'].\
Correlating['KYTJ820101'], 0.996)
self.assertEqual(self.AAIndexObjects['JURD980101'].\
Correlating['NADH010101'], 0.925)
self.assertEqual(self.AAIndexObjects['JURD980101'].\
Correlating['OOBM770101'], -0.903)
def test_Data_entries(self):
""" AAI1: Test Data Entries """
self.assertEqual(self.AAIndexObjects['ANDN920101'].Data['A'],\
4.35)
self.assertEqual(self.AAIndexObjects['ANDN920101'].Data['Q'],\
4.37)
self.assertEqual(self.AAIndexObjects['ANDN920101'].Data['V'],\
3.95)
self.assertEqual(self.AAIndexObjects['ARGP820103'].Data['A'],\
1.56)
self.assertEqual(self.AAIndexObjects['ARGP820103'].Data['Q'],\
0.51)
self.assertEqual(self.AAIndexObjects['ARGP820103'].Data['V'],\
1.14)
self.assertEqual(self.AAIndexObjects['JURD980101'].Data['A'],\
1.10)
self.assertEqual(self.AAIndexObjects['JURD980101'].Data['Q'],\
-3.68)
self.assertEqual(self.AAIndexObjects['JURD980101'].Data['V'],\
4.2)
class test_aaindex2_parser(TestCase):
def setUp(self):
""" Setup some variables """
self._fake_file = list(fake_file_aaindex2.split('\n'))
self.AAIndexObjects = AAIndex2FromFiles(self._fake_file)
def test_init(self):
""" AAI2: Test that init run w/o error """
aa2p = AAIndex2Parser()
def test_read_file_as_list(self):
"""AAI1: Test that a file is correctly opened as a list """
aap = AAIndex2Parser()
AAIndexObjects = aap(self._fake_file)
def test_correct_num_of_records(self):
"""AAI2: Test that one object is created per record """
self.assertEqual(6, len(self.AAIndexObjects))
def test_ID_entries(self):
""" AAI2: Test ID Entries """
self.assertEqual(self.AAIndexObjects['ALTS910101'].ID, 'ALTS910101')
self.assertEqual(self.AAIndexObjects['BENS940103'].ID, 'BENS940103')
self.assertEqual(self.AAIndexObjects['QUIB020101'].ID, 'QUIB020101')
def test_Description_entries(self):
""" AAI2: Test Description Entries """
self.assertEqual(self.AAIndexObjects['ALTS910101'].Description,\
'The PAM-120 matrix (Altschul, 1991)')
self.assertEqual(self.AAIndexObjects['BENS940103'].Description,\
'Log-odds scoring matrix collected in 74-100 PAM (Benner et al., '+\
'1994)')
self.assertEqual(self.AAIndexObjects['QUIB020101'].Description,\
'STROMA score matrix for the alignment of known distant homologs ' +\
'(Qian-Goldstein, 2002)')
def test_LITDB_entries(self):
""" AAI2: Test LITDB Entries """
self.assertEqual(self.AAIndexObjects['ALTS910101'].LITDBEntryNum,\
'LIT:1713145 PMID:2051488')
self.assertEqual(self.AAIndexObjects['BENS940103'].LITDBEntryNum,\
'LIT:2023094 PMID:7700864')
self.assertEqual(self.AAIndexObjects['QUIB020101'].LITDBEntryNum,\
'PMID:12211027')
def test_Authors_entries(self):
""" AAI2: Test Atuthor Entries """
self.assertEqual(self.AAIndexObjects['ALTS910101'].Authors,\
'Altschul, S.F.')
self.assertEqual(self.AAIndexObjects['BENS940103'].Authors,\
'Benner, S.A., Cohen, M.A. and Gonnet, G.H.')
self.assertEqual(self.AAIndexObjects['QUIB020101'].Authors,\
'Qian, B. and Goldstein, R.A.')
def test_Title_entries(self):
""" AAI2: Test Title Entries """
self.assertEqual(self.AAIndexObjects['ALTS910101'].Title,\
'Amino acid substitution matrices from an information theoretic ' +\
'perspective')
self.assertEqual(self.AAIndexObjects['BENS940103'].Title,\
'Amino acid substitution during functionally constrained divergent ' +\
'evolution of protein sequences')
self.assertEqual(self.AAIndexObjects['QUIB020101'].Title,\
'Optimization of a new score function for the generation of '+\
'accurate alignments')
def test_Citation_entries(self):
""" AAI2: Test citation entries """
self.assertEqual(self.AAIndexObjects['ALTS910101'].Citation,\
'J. Mol. Biol. 219, 555-565 (1991)')
self.assertEqual(self.AAIndexObjects['BENS940103'].Citation,\
'Protein Engineering 7, 1323-1332 (1994)')
self.assertEqual(self.AAIndexObjects['QUIB020101'].Citation,\
'Proteins. 48, 605-610 (2002)')
def test_Comments_entries(self):
""" AAI2: Tests null, single line, multi line comments """
self.assertEqual(self.AAIndexObjects['ALTS910101'].Comments,\
'')
self.assertEqual(self.AAIndexObjects['BENS940103'].Comments,\
'extrapolated to 250 PAM')
self.assertEqual(self.AAIndexObjects['QUIB020101'].Comments,\
'')
self.assertEqual(self.AAIndexObjects['HENS920104'].Comments,\
'# Matrix made by matblas from blosum50.iij ' +
'* # BLOSUM Clustered Scoring Matrix in 1/3 Bit Units ' +
'* # Blocks Database = /data/blocks_5.0/blocks.dat ' +
'* # Cluster Percentage: >= 50 ' +
'* # Entropy = 0.4808, Expected = -0.3573')
def test_Data_entries_20x20_LTM(self):
""" AAI2: correct data entries when 20x20 LTM"""
self.assertEqual(self.AAIndexObjects['ALTS910101'].Data['A']['A'],\
3.)
self.assertEqual(self.AAIndexObjects['ALTS910101'].Data['Y']['R'],\
-6.)
self.assertEqual(self.AAIndexObjects['ALTS910101'].Data['V']['V'],\
5.)
self.assertEqual(self.AAIndexObjects['BENS940103'].Data['A']['A'],\
2.4)
self.assertEqual(self.AAIndexObjects['BENS940103'].Data['Y']['R'],\
-2.0)
self.assertEqual(self.AAIndexObjects['BENS940103'].Data['V']['V'],\
3.4)
self.assertEqual(self.AAIndexObjects['QUIB020101'].Data['A']['A'],\
2.5)
self.assertEqual(self.AAIndexObjects['QUIB020101'].Data['Y']['R'],\
-0.9)
self.assertEqual(self.AAIndexObjects['QUIB020101'].Data['V']['V'],\
4.2)
def test_Data_entries_20x20_Square(self):
""" AAI2: correct data entries when 20x20 squ matrix """
self.assertEqual(self.AAIndexObjects['HENS920104'].Data['V']['Y'],\
-1)
self.assertEqual(self.AAIndexObjects['HENS920104'].Data['Q']['A'],\
-1)
self.assertEqual(self.AAIndexObjects['HENS920104'].Data['N']['N'],\
7)
def test_Data_entries_with_abnormal_fields(self):
""" AAI2: test correct data entries when more than std fields present
Some entires in AAIndex2 have more that 20 fields, this tests that
that data is corrected parsed and identified.
"""
# There are no entries that fit this category that are square
# matrices, which is all we are concerned with at this point,
# so this method should just serve as a reminder to test this
# when we begin parsing data other than square matrices.
pass
def test_Data_entries_21x21_LTM(self):
""" AAI2: correct data entries when 21x21 LTM"""
self.assertEqual(self.AAIndexObjects['KOSJ950101'].Data['-']['-'],\
55.7)
self.assertEqual(self.AAIndexObjects['KOSJ950101'].Data['Y']['-'],\
0.3)
self.assertEqual(self.AAIndexObjects['KOSJ950101'].Data['N']['R'],\
3.0)
def test_Data_entries_22x21_square(self):
""" AAI2: correct data entries when 22x21 square matrix """
# It's not really a sqaure matrix, but it's fully populated ...
self.assertEqual(self.AAIndexObjects['OVEJ920102'].Data['J']['D'],\
0.001)
self.assertEqual(self.AAIndexObjects['OVEJ920102'].Data['-']['I'],\
0.022)
self.assertEqual(self.AAIndexObjects['OVEJ920102'].Data['D']['E'],\
0.109)
class AAIndexRecordTests(TestCase):
""" AAIR: Tests AAIndexRecord class """
def setUp(self):
self.id = "5"
self.description = "Some Info"
self.LITDB_entry_num = "25"
self.authors = "Greg"
self.title = "A test"
self.citation = "something"
self.comments = "This is a test, this is only a test"
self.data = {}
class AAIndex1RecordTests(AAIndexRecordTests):
""" AAIR1: Tests AAIndex1Records class """
def setUp(self):
AAIndexRecordTests.setUp(self)
self.correlating = [0.987, 0.783, 1., 0]
values = []
keys = 'ARNDCQEGHILKMFPSTWYV'
for i in range(20):
values += [float(i) + 0.15]
self.data = dict(zip(keys,values))
self.aar = AAIndex1Record(self.id, self.description,\
self.LITDB_entry_num, self.authors, self.title,\
self.citation, self.comments, self.correlating, self.data)
def test_init(self):
""" AAIR1: Tests init method returns with no errors"""
test_aar = AAIndex1Record(self.id, self.description,\
self.LITDB_entry_num, self.authors, self.title,\
self.citation, self.comments, self.correlating, self.data)
def test_general_init_data(self):
""" AAIR1: Tests init correctly initializes data"""
self.assertEqual(self.aar.ID, str(self.id))
self.assertEqual(self.aar.Description, str(self.description))
self.assertEqual(self.aar.LITDBEntryNum,\
str(self.LITDB_entry_num))
self.assertEqual(self.aar.Authors, str(self.authors))
self.assertEqual(self.aar.Title, str(self.title))
self.assertEqual(self.aar.Citation, str(self.citation))
self.assertEqual(self.aar.Comments, str(self.comments))
self.assertEqual(self.aar.Correlating, self.correlating)
self.assertEqual(self.aar.Data,self.data)
def test_toSquareDistanceMatrix(self):
""" AAIR1: Tests that _toSquareDistanceMatrix runs without returning an error """
square = self.aar._toSquareDistanceMatrix()
def test_toSquareDistanceMatrix_data_integrity_diagonal(self):
""" AAIR1: Tests that diag = 0 when square matrix is built """
square = self.aar._toSquareDistanceMatrix()
# Test diagonal
keys = 'ARNDCQEGHILKMFPSTWYV'
for k in keys:
self.assertEqual(square[k][k], 0.)
def test_toSquareDistanceMatrix_data_integrity(self):
""" AAIR1: Tests that _toSquareDistanceMatrix works right w/o stops """
square = self.aar._toSquareDistanceMatrix()
self.assertFloatEqualAbs(square['R']['A'], square['A']['R'])
self.assertFloatEqualAbs(square['A']['R'], 1.)
self.assertFloatEqualAbs(square['D']['N'], square['N']['D'])
self.assertFloatEqualAbs(square['D']['N'], 1.)
self.assertFloatEqualAbs(square['A']['C'], square['C']['A'])
self.assertFloatEqualAbs(square['A']['C'], 4.)
self.assertFloatEqualAbs(square['V']['A'], square['A']['V'])
self.assertFloatEqualAbs(square['V']['A'], 19.)
self.assertFloatEqualAbs(square['V']['Y'], square['Y']['V'])
self.assertFloatEqualAbs(square['V']['Y'], 1.)
def test_toSquareDistanceMatrix_data_integrity_w_stops(self):
""" AAIR1: Tests that _toSquareDistanceMatrix works right w/ stops """
square = self.aar._toSquareDistanceMatrix(include_stops=1)
self.assertFloatEqualAbs(square['R']['A'], square['A']['R'])
self.assertFloatEqualAbs(square['A']['R'], 1.)
self.assertFloatEqualAbs(square['D']['N'], square['N']['D'])
self.assertFloatEqualAbs(square['D']['N'], 1.)
self.assertFloatEqualAbs(square['A']['C'], square['C']['A'])
self.assertFloatEqualAbs(square['A']['C'], 4.)
self.assertFloatEqualAbs(square['V']['A'], square['A']['V'])
self.assertFloatEqualAbs(square['V']['A'], 19.)
self.assertFloatEqualAbs(square['V']['Y'], square['Y']['V'])
self.assertFloatEqualAbs(square['V']['Y'], 1.)
self.assertFloatEqualAbs(square['V']['*'], None)
self.assertFloatEqualAbs(square['*']['Y'], None)
self.assertFloatEqualAbs(square['*']['*'], None)
self.assertFloatEqualAbs(square['*']['R'], None)
def test_toDistanceMatrix(self):
""" AAIR1: Tests that toDistanceMatrix functions as expected """
dm = self.aar.toDistanceMatrix()
self.assertFloatEqualAbs(dm['R']['A'], dm['A']['R'])
self.assertFloatEqualAbs(dm['A']['R'], 1.)
self.assertFloatEqualAbs(dm['D']['N'], dm['N']['D'])
self.assertFloatEqualAbs(dm['D']['N'], 1.)
self.assertFloatEqualAbs(dm['A']['C'], dm['C']['A'])
self.assertFloatEqualAbs(dm['A']['C'], 4.)
self.assertFloatEqualAbs(dm['V']['A'], dm['A']['V'])
self.assertFloatEqualAbs(dm['V']['A'], 19.)
self.assertFloatEqualAbs(dm['V']['Y'], dm['Y']['V'])
self.assertFloatEqualAbs(dm['V']['Y'], 1.)
def test_toDistanceMatrix_w_stops(self):
""" AAIR1: Tests that toDistanceMatrix works right w/ stops """
square = self.aar.toDistanceMatrix(include_stops=1)
self.assertFloatEqualAbs(square['R']['A'], square['A']['R'])
self.assertFloatEqualAbs(square['A']['R'], 1.)
self.assertFloatEqualAbs(square['D']['N'], square['N']['D'])
self.assertFloatEqualAbs(square['D']['N'], 1.)
self.assertFloatEqualAbs(square['A']['C'], square['C']['A'])
self.assertFloatEqualAbs(square['A']['C'], 4.)
self.assertFloatEqualAbs(square['V']['A'], square['A']['V'])
self.assertFloatEqualAbs(square['V']['A'], 19.)
self.assertFloatEqualAbs(square['V']['Y'], square['Y']['V'])
self.assertFloatEqualAbs(square['V']['Y'], 1.)
self.assertFloatEqualAbs(square['V']['*'], None)
self.assertFloatEqualAbs(square['*']['Y'], None)
self.assertFloatEqualAbs(square['*']['*'], None)
self.assertFloatEqualAbs(square['*']['R'], None)
class AAIndex2RecordTests(AAIndexRecordTests):
""" AAIR2: Tests AAIndex2Records class """
def setUp(self):
AAIndexRecordTests.setUp(self)
# Build LTM data
values = range(210)
keys = 'ARNDCQEGHILKMFPSTWYV'
self.LTMdata = dict.fromkeys(keys)
i = 0
for r in keys:
new_row = dict.fromkeys(keys)
for c in keys:
if keys.find(c) <= keys.find(r):
new_row[c] = values[i]
i +=1
self.LTMdata[r] = new_row
self.aarLTM = AAIndex2Record(self.id, self.description,\
self.LITDB_entry_num, self.authors, self.title,\
self.citation, self.comments, self.LTMdata)
# Build Square matrix data
values = range(400)
self.SQUdata = dict.fromkeys(keys)
i = 0
for r in keys:
new_row = dict.fromkeys(keys)
for c in keys:
new_row[c] = values[i]
i +=1
self.SQUdata[r] = new_row
self.aarSquare = AAIndex2Record(self.id, self.description,\
self.LITDB_entry_num, self.authors, self.title,\
self.citation, self.comments, self.SQUdata)
def test_init(self):
""" AAIR2: Tests init method returns with no errors"""
test_aar = AAIndex2Record(self.id, self.description,\
self.LITDB_entry_num, self.authors, self.title,\
self.citation, self.comments, self.SQUdata)
def test_init_data(self):
""" AAIR2: Tests init correctly initializes data"""
self.assertEqual(self.aarLTM.ID, str(self.id))
self.assertEqual(self.aarLTM.Description, str(self.description))
self.assertEqual(self.aarLTM.LITDBEntryNum,\
str(self.LITDB_entry_num))
self.assertEqual(self.aarLTM.Authors, str(self.authors))
self.assertEqual(self.aarLTM.Title, str(self.title))
self.assertEqual(self.aarLTM.Citation, str(self.citation))
self.assertEqual(self.aarLTM.Comments, str(self.comments))
# def test_matrix_values_col_by_row(self):
# """ Tests that keys and values correctly correspond in data LTM
#
#
# Also tests that reverse keys are same as forward keys.
#
# """
#
# data_matrix = self.aarLTM.Data
# self.assertEqual(data_matrix['A']['A'], 0)
# self.assertEqual(data_matrix['A']['R'], 1)
# self.assertEqual(data_matrix['R']['R'], 2)
# self.assertEqual(data_matrix['C']['H'], 40)
# self.assertEqual(data_matrix['I']['M'], 87)
# self.assertEqual(data_matrix['D']['P'], 108)
# self.assertEqual(data_matrix['W']['V'], 207)
# self.assertEqual(data_matrix['Y']['V'], 208)
# self.assertEqual(data_matrix['V']['V'], 209)
# def test_LTM_values_row_by_col(self):
# """ Tests that keys are correctly linked to values in a LTM
#
# This tests that some random places hold the correct values.
# These are some randomly selected keys with hand calculated
# values. Also included are the extreme values. Technically if
# the first and last three are correct all values should be
# correct.
#
# """
# data_matrix = self.aarLTM.Data
# self.assertEqual(data_matrix['R']['A'], 1)
# self.assertEqual(data_matrix['H']['C'], 40)
# self.assertEqual(data_matrix['M']['I'], 87)
# self.assertEqual(data_matrix['P']['D'], 108)
# self.assertEqual(data_matrix['V']['W'], 207)
# self.assertEqual(data_matrix['V']['Y'], 208)
# self.assertEqual(data_matrix['A']['A'], 0)
# self.assertEqual(data_matrix['R']['R'], 2)
# self.assertEqual(data_matrix['V']['V'], 209)
def test_Square_Matrix_values_row_by_col(self):
""" AAIR2: Tests that key -> value pair integrity in Square matrix
"""
data_matrix = self.aarSquare.Data
self.assertEqual(data_matrix['R']['A'], 20)
#self.assertEqual(data_matrix['H']['C'], 40)
#self.assertEqual(data_matrix['M']['I'], 87)
#self.assertEqual(data_matrix['P']['D'], 108)
#self.assertEqual(data_matrix['V']['W'], 207)
#self.assertEqual(data_matrix['V']['Y'], 208)
self.assertEqual(data_matrix['A']['A'], 0)
self.assertEqual(data_matrix['R']['R'], 21)
self.assertEqual(data_matrix['V']['V'], 399)
def test_toSquareDistanceMatrix_data_integrity(self):
""" AAIR2: Tests that _toSquareDistanceMatrix works right w/o stops
"""
square = self.aarSquare._toSquareDistanceMatrix()
self.assertEqual(square['R']['A'], 20)
self.assertEqual(square['A']['A'], 0)
self.assertEqual(square['R']['R'], 21)
self.assertEqual(square['V']['V'], 399)
def test_toSquareDistanceMatrix_data_integrity_w_stops(self):
""" AAIR2: Tests that _toSquareDistanceMatrix works right with stops
"""
square = self.aarSquare._toSquareDistanceMatrix(include_stops=1)
self.assertEqual(square['R']['A'], 20)
self.assertEqual(square['A']['A'], 0)
self.assertEqual(square['R']['R'], 21)
self.assertEqual(square['V']['V'], 399)
self.assertEqual(square['V']['*'], None)
self.assertEqual(square['*']['Y'], None)
self.assertEqual(square['*']['*'], None)
self.assertEqual(square['*']['R'], None)
# Data for parser tests
fake_file_aaindex1 =\
"""
H ANDN920101
D alpha-CH chemical shifts (Andersen et al., 1992)
R LIT:1810048b PMID:1575719
A Andersen, N.H., Cao, B. and Chen, C.
T Peptide/protein structure analysis using the chemical shift index method:
upfield alpha-CH values reveal dynamic helices and aL sites
J Biochem. and Biophys. Res. Comm. 184, 1008-1014 (1992)
C BUNA790102 0.949
I A/L R/K N/M D/F C/P Q/S E/T G/W H/Y I/V
4.35 4.38 4.75 4.76 4.65 4.37 4.29 3.97 4.63 3.95
4.17 4.36 4.52 4.66 4.44 4.50 4.35 4.70 4.60 3.95
//
H ARGP820101
D Hydrophobicity index (Argos et al., 1982)
R LIT:0901079b PMID:7151796
A Argos, P., Rao, J.K.M. and Hargrave, P.A.
T Structural prediction of membrane-bound proteins
J Eur. J. Biochem. 128, 565-575 (1982)
C JOND750101 1.000 SIMZ760101 0.967 GOLD730101 0.936
TAKK010101 0.906 MEEJ810101 0.891 CIDH920105 0.867
LEVM760106 0.865 CIDH920102 0.862 MEEJ800102 0.855
MEEJ810102 0.853 CIDH920103 0.827 PLIV810101 0.820
CIDH920104 0.819 LEVM760107 0.806 NOZY710101 0.800
PARJ860101 -0.835 WOLS870101 -0.838 BULH740101 -0.854
I A/L R/K N/M D/F C/P Q/S E/T G/W H/Y I/V
0.61 0.60 0.06 0.46 1.07 0. 0.47 0.07 0.61 2.22
1.53 1.15 1.18 2.02 1.95 0.05 0.05 2.65 1.88 1.32
//
H TSAJ990102
D Volumes not including the crystallographic waters using the ProtOr (Tsai et
al., 1999)
R PMID:10388571
A Tsai, J., Taylor, R., Chothia, C. and Gerstein, M.
T The packing density in proteins: standard radii and volumes
J J Mol Biol. 290, 253-266 (1999)
* (Cyh 113.7)
C TSAJ990101 1.000 CHOC750101 0.996 BIGC670101 0.992
GOLD730102 0.991 KRIW790103 0.987 FAUJ880103 0.985
GRAR740103 0.978 CHAM820101 0.978 CHOC760101 0.972
FASG760101 0.940 LEVM760105 0.928 LEVM760102 0.918
ROSG850101 0.909 DAWD720101 0.905 CHAM830106 0.896
FAUJ880106 0.882 RADA880106 0.864 LEVM760107 0.861
LEVM760106 0.841 RADA880103 -0.879
I A/L R/K N/M D/F C/P Q/S E/T G/W H/Y I/V
90.0 194.0 124.7 117.3 103.3 149.4 142.2 64.9 160.0 163.9
164.0 167.3 167.0 191.9 122.9 95.4 121.5 228.2 197.0 139.0
//
H JURD980101
D Modified Kyte-Doolittle hydrophobicity scale (Juretic et al., 1998)
R
A Juretic, D., Lucic, B., Zucic, D. and Trinajstic, N.
T Protein transmembrane structure: recognition and prediction by using
hydrophobicity scales through preference functions
J Theoretical and Computational Chemistry, 5, 405-445 (1998)
C KYTJ820101 0.996 CHOC760103 0.967 NADH010102 0.931
JANJ780102 0.928 NADH010101 0.925 EISD860103 0.901
DESM900102 0.900 NADH010103 0.900 EISD840101 0.895
RADA880101 0.893 MANP780101 0.887 WOLR810101 0.881
PONP800103 0.879 JANJ790102 0.879 NADH010104 0.873
CHOC760104 0.870 PONP800102 0.869 JANJ790101 0.868
MEIH800103 0.861 PONP800101 0.858 NAKH920108 0.858
RADA880108 0.857 PONP800108 0.856 ROSG850102 0.854
PONP930101 0.849 RADA880107 0.842 BIOV880101 0.840
MIYS850101 0.837 FAUJ830101 0.833 CIDH920104 0.832
DESM900101 0.829 WARP780101 0.827 KANM800104 0.826
LIFS790102 0.824 RADA880104 0.824 NADH010105 0.821
NISK800101 0.816 NISK860101 0.808 BIOV880102 0.805
ARGP820102 0.802 ARGP820103 0.800 VHEG790101 -0.814
KRIW790101 -0.824 CHOC760102 -0.851 ROSM880101 -0.851
MONM990101 -0.853 JANJ780103 -0.853 RACS770102 -0.855
PRAM900101 -0.862 JANJ780101 -0.862 GUYH850101 -0.864
GRAR740102 -0.864 MEIH800102 -0.879 KUHL950101 -0.884
ROSM880102 -0.894 OOBM770101 -0.903
I A/L R/K N/M D/F C/P Q/S E/T G/W H/Y I/V
1.10 -5.10 -3.50 -3.60 2.50 -3.68 -3.20 -0.64 -3.20 4.50
3.80 -4.11 1.90 2.80 -1.90 -0.50 -0.70 -0.46 -1.3 4.2
//
H WILM950104
D Hydrophobicity coefficient in RP-HPLC, C18 with 0.1%TFA/2-PrOH/MeCN/H2O
(Wilce et al. 1995)
R
A Wilce, M.C., Aguilar, M.I. and Hearn, M.T.
T Physicochemical basis of amino acid hydrophobicity scales: evaluation of four
new scales of amino acid hydrophobicity coefficients derived from RP-HPLC of
peptides
J Anal Chem. 67, 1210-1219 (1995)
C
I A/L R/K N/M D/F C/P Q/S E/T G/W H/Y I/V
-2.34 1.60 2.81 -0.48 5.03 0.16 1.30 -1.06 -3.00 7.26
1.09 1.56 0.62 2.57 -0.15 1.93 0.19 3.59 -2.58 2.06
//
H ARGP820103
D Membrane-buried preference parameters (Argos et al., 1982)
R LIT:0901079b PMID:7151796
A Argos, P., Rao, J.K.M. and Hargrave, P.A.
T Structural prediction of membrane-bound proteins
J Eur. J. Biochem. 128, 565-575 (1982)
C ARGP820102 0.961 MIYS850101 0.822 NAKH900106 0.810
EISD860103 0.810 KYTJ820101 0.806 JURD980101 0.800
I A/L R/K N/M D/F C/P Q/S E/T G/W H/Y I/V
1.56 0.45 0.27 0.14 1.23 0.51 0.23 0.62 0.29 1.67
2.93 0.15 2.96 2.03 0.76 0.81 0.91 1.08 0.68 1.14
//
"""
fake_file_aaindex2 =\
"""
H ALTS910101
D The PAM-120 matrix (Altschul, 1991)
R LIT:1713145 PMID:2051488
A Altschul, S.F.
T Amino acid substitution matrices from an information theoretic perspective
J J. Mol. Biol. 219, 555-565 (1991)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
3.
-3. 6.
0. -1. 4.
0. -3. 2. 5.
-3. -4. -5. -7. 9.
-1. 1. 0. 1. -7. 6.
0. -3. 1. 3. -7. 2. 5.
1. -4. 0. 0. -5. -3. -1. 5.
-3. 1. 2. 0. -4. 3. -1. -4. 7.
-1. -2. -2. -3. -3. -3. -3. -4. -4. 6.
-3. -4. -4. -5. -7. -2. -4. -5. -3. 1. 5.
-2. 2. 1. -1. -7. 0. -1. -3. -2. -2. -4. 5.
-2. -1. -3. -4. -6. -1. -4. -4. -4. 1. 3. 0. 8.
-4. -4. -4. -7. -6. -6. -6. -5. -2. 0. 0. -6. -1. 8.
1. -1. -2. -2. -3. 0. -1. -2. -1. -3. -3. -2. -3. -5. 6.
1. -1. 1. 0. -1. -2. -1. 1. -2. -2. -4. -1. -2. -3. 1. 3.
1. -2. 0. -1. -3. -2. -2. -1. -3. 0. -3. -1. -1. -4. -1. 2. 4.
-7. 1. -5. -8. -8. -6. -8. -8. -5. -7. -5. -5. -7. -1. -7. -2. -6. 12.
-4. -6. -2. -5. -1. -5. -4. -6. -1. -2. -3. -6. -4. 4. -6. -3. -3. -1. 8.
0. -3. -3. -3. -2. -3. -3. -2. -3. 3. 1. -4. 1. -3. -2. -2. 0. -8. -3. 5.
//
H BENS940103
D Log-odds scoring matrix collected in 74-100 PAM (Benner et al., 1994)
R LIT:2023094 PMID:7700864
A Benner, S.A., Cohen, M.A. and Gonnet, G.H.
T Amino acid substitution during functionally constrained divergent
evolution of protein sequences
J Protein Engineering 7, 1323-1332 (1994)
* extrapolated to 250 PAM
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.4
-0.8 4.8
-0.2 0.3 3.6
-0.3 -0.5 2.2 4.8
0.3 -2.2 -1.8 -3.2 11.8
-0.3 1.6 0.7 0.8 -2.6 3.0
-0.1 0.3 1.0 2.9 -3.2 1.7 3.7
0.6 -1.0 0.4 0.2 -2.0 -1.1 -0.5 6.6
-1.0 1.0 1.2 0.4 -1.3 1.4 0.2 -1.6 6.1
-0.8 -2.6 -2.8 -3.9 -1.2 -2.0 -2.9 -4.3 -2.3 4.0
-1.4 -2.4 -3.1 -4.2 -1.6 -1.7 -3.1 -4.6 -1.9 2.8 4.2
-0.4 2.9 0.9 0.4 -2.9 1.7 1.2 -1.1 0.6 -2.3 -2.4 3.4
-0.8 -1.8 -2.2 -3.2 -1.2 -1.0 -2.2 -3.5 -1.5 2.6 2.9 -1.5 4.5
-2.6 -3.5 -3.2 -4.7 -0.7 -2.8 -4.3 -5.4 0.0 0.9 2.1 -3.6 1.3 7.2
0.4 -1.0 -1.0 -1.0 -3.1 -0.2 -0.7 -1.7 -1.0 -2.6 -2.2 -0.8 -2.4 -3.8 7.5
1.1 -0.2 0.9 0.4 0.1 0.1 0.1 0.4 -0.3 -1.8 -2.2 0.0 -1.4 -2.6 0.5 2.1
0.7 -0.3 0.4 -0.2 -0.6 -0.1 -0.2 -1.0 -0.5 -0.3 -1.1 0.1 -0.4 -2.2 0.1 1.4 2.5
-4.1 -1.6 -4.0 -5.5 -0.9 -2.8 -4.7 -4.1 -1.0 -2.3 -0.9 -3.6 -1.3 3.0 -5.2 -3.4 -3.7 14.7
-2.6 -2.0 -1.4 -2.8 -0.4 -1.8 -3.0 -4.3 2.5 -1.0 -0.1 -2.4 -0.5 5.3 -3.4 -1.9 -2.1 3.6 8.1
0.1 -2.2 -2.2 -2.9 -0.2 -1.7 -2.1 -3.1 -2.1 3.2 1.9 -1.9 1.8 0.1 -1.9 -1.0 0.2 -2.9 -1.4 3.4
//
H QUIB020101
D STROMA score matrix for the alignment of known distant homologs
(Qian-Goldstein, 2002)
R PMID:12211027
A Qian, B. and Goldstein, R.A.
T Optimization of a new score function for the generation of accurate
alignments
J Proteins. 48, 605-610 (2002)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
2.5
0.2 5.2
1.1 0.7 2.5
1 0.1 3.3 5.3
1.2 -1.3 -1.9 -3.1 11.5
-0.1 2 1.9 1.1 -2.5 3.6
1.2 1.9 2.3 3.2 -2.4 1.7 3.7
1.4 -0.2 0.7 0.9 -1.3 -0.3 0.5 7.5
-1.4 1.5 1.4 0.5 -1.7 1.4 0.3 -1.7 6.8
0.3 -1.9 -2.4 -2.9 -3.2 -0.9 -3.1 -3.7 -1.8 4.5
-0.2 -1.5 -2.4 -3.4 -1.6 -1.2 -1.5 -3.8 -2.4 3.4 5.2
-0.2 3.4 1.6 1.4 -3 2.2 1.2 0.4 1.1 -1.5 -2 3.9
-0.2 -1.4 -2.1 -2.8 -1.3 -0.6 -2 -3.8 -0.8 2.2 3.1 -0.5 5.4
-1.6 -3.2 -2.5 -3.7 -0.8 -1.7 -13.7 -4.7 -0.9 2.2 3.7 -2.8 1.7 7
0.7 -0.6 -0.1 -0.2 -3.6 1 0 -0.8 -2.1 -2.4 -1.4 0.2 -1.9 -4.1 8.1
1.7 0.2 1.4 1.7 0.7 0.9 1.1 1.6 -0.1 -1.1 -0.8 1.4 -1.1 -2.5 2 2.8
1.7 0.2 1.4 0.1 0.3 -0.1 1.6 -0.6 -0.2 0 0.3 1 -0.3 -0.8 1.1 2.6 0.4
-3.3 -1.5 -4 -5.7 -0.5 -2.9 -4.7 -4.2 -1.2 -1.8 -1.2 -3 -0.6 3.7 -5 -2.8 -2.9 14.9
-1.8 -0.9 -0.8 -2.9 -0.3 -1.5 -2.2 -4.8 2.9 0.2 0.8 -1.5 0.5 5.2 -3.3 -0.9 -0.8 4.9 8.1
1.9 -2.8 -0.9 -2.5 0.7 -1.5 -1.3 -1.4 -2.5 4.5 3.4 -1 1.7 0.9 -1.1 -3 1.5 -2.5 0.3 4.2
//
H HENS920104
D BLOSUM50 substitution matrix (Henikoff-Henikoff, 1992)
R LIT:1902106 PMID:1438297
A Henikoff, S. and Henikoff, J.G.
T Amino acid substitution matrices from protein blocks
J Proc. Natl. Acad. Sci. USA 89, 10915-10919 (1992)
* # Matrix made by matblas from blosum50.iij
* # BLOSUM Clustered Scoring Matrix in 1/3 Bit Units
* # Blocks Database = /data/blocks_5.0/blocks.dat
* # Cluster Percentage: >= 50
* # Entropy = 0.4808, Expected = -0.3573
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
5 -2 -1 -2 -1 -1 -1 0 -2 -1 -2 -1 -1 -3 -1 1 0 -3 -2 0
-2 7 -1 -2 -4 1 0 -3 0 -4 -3 3 -2 -3 -3 -1 -1 -3 -1 -3
-1 -1 7 2 -2 0 0 0 1 -3 -4 0 -2 -4 -2 1 0 -4 -2 -3
-2 -2 2 8 -4 0 2 -1 -1 -4 -4 -1 -4 -5 -1 0 -1 -5 -3 -4
-1 -4 -2 -4 13 -3 -3 -3 -3 -2 -2 -3 -2 -2 -4 -1 -1 -5 -3 -1
-1 1 0 0 -3 7 2 -2 1 -3 -2 2 0 -4 -1 0 -1 -1 -1 -3
-1 0 0 2 -3 2 6 -3 0 -4 -3 1 -2 -3 -1 -1 -1 -3 -2 -3
0 -3 0 -1 -3 -2 -3 8 -2 -4 -4 -2 -3 -4 -2 0 -2 -3 -3 -4
-2 0 1 -1 -3 1 0 -2 10 -4 -3 0 -1 -1 -2 -1 -2 -3 2 -4
-1 -4 -3 -4 -2 -3 -4 -4 -4 5 2 -3 2 0 -3 -3 -1 -3 -1 4
-2 -3 -4 -4 -2 -2 -3 -4 -3 2 5 -3 3 1 -4 -3 -1 -2 -1 1
-1 3 0 -1 -3 2 1 -2 0 -3 -3 6 -2 -4 -1 0 -1 -3 -2 -3
-1 -2 -2 -4 -2 0 -2 -3 -1 2 3 -2 7 0 -3 -2 -1 -1 0 1
-3 -3 -4 -5 -2 -4 -3 -4 -1 0 1 -4 0 8 -4 -3 -2 1 4 -1
-1 -3 -2 -1 -4 -1 -1 -2 -2 -3 -4 -1 -3 -4 10 -1 -1 -4 -3 -3
1 -1 1 0 -1 0 -1 0 -1 -3 -3 0 -2 -3 -1 5 2 -4 -2 -2
0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 2 5 -3 -2 0
-3 -3 -4 -5 -5 -1 -3 -3 -3 -3 -2 -3 -1 1 -4 -4 -3 15 2 -3
-2 -1 -2 -3 -3 -1 -2 -3 2 -1 -1 -2 0 4 -3 -2 -2 2 8 -1
0 -3 -3 -4 -1 -3 -3 -4 -4 4 1 -3 1 -1 -3 -2 0 -3 -1 5
//
H KOSJ950101
D Context-dependent optimal substitution matrices for exposed helix
(Koshi-Goldstein, 1995)
R LIT:2124140 PMID:8577693
A Koshi, J.M. and Goldstein, R.A.
T Context-dependent optimal substitution matrices.
J Protein Engineering 8, 641-645 (1995)
M rows = -ARNDCQEGHILKMFPSTWYV, cols = -ARNDCQEGHILKMFPSTWYV
55.7
3.0 3.0
3.0 3.0 0.4
0.1 3.0 3.0 2.1
3.0 3.0 3.0 0.1 1.9
2.2 2.4 3.0 0.8 1.3 3.0
25.6 47.2 1.5 1.0 0.7 0.3 1.9
2.3 4.3 0.6 0.2 2.0 0.8 0.1 0.3
3.1 2.8 3.7 0.4 0.1 2.0 14.8 0.9 62.7
1.3 0.4 0.3 4.6 0.3 0.1 1.9 0.5 2.2 5.1
0.6 0.2 0.4 1.9 1.5 0.4 0.2 0.3 15.2 0.2 0.5
48.2 3.3 0.1 3.2 4.9 0.1 1.7 1.7 1.4 3.0 0.6 1.0
0.1 9.7 2.7 0.7 1.1 1.5 15.9 3.9 1.4 7.3 52.1 0.3 0.9
11.0 2.0 0.4 0.6 0.1 0.6 0.5 0.1 0.6 2.9 0.1 0.1 0.1 0.1
9.4 1.5 0.1 1.5 1.6 73.6 0.1 2.6 0.1 0.1 2.1 4.0 0.1 0.1 0.8
0.7 0.3 2.2 0.1 0.1 0.1 0.1 8.4 5.7 2.0 4.5 0.3 47.5 8.2 0.9 1.6
0.1 3.4 7.8 0.5 0.1 0.7 5.3 2.2 0.2 0.7 0.5 5.2 5.3 1.0 1.5 8.6 0.1
4.9 56.8 1.5 1.0 0.3 0.9 5.8 0.1 0.2 1.6 2.1 2.4 0.2 0.1 1.1 20.2 2.0 1.2
2.3 3.3 0.1 0.4 0.1 6 4.8 0.8 0.1 0.1 1.4 0.3 0.6 0.1 1.2 0.6 0.1 0.5 13.3
0.3 4.7 7.5 1.8 0.1 4.4 0.7 0.1 56.9 0.6 0.1 2.3 1.2 2.2 0.1 0.1 0.1 0.1 4.4 0.1
18.4 0.1 0.1 0.1 0.1 0.1 0.4 0.1 0.1 0.1 5 2.6 10.8 1.2 3.5 1.3 0.1 0.1 3.4 0.1 0.1
//
H OVEJ920102
D Environment-specific amino acid substitution matrix for alpha residues
(Overington et al., 1992)
R LIT:1811128 PMID:1304904
A Overington, J., Donnelly, D., Johnson, M.S., Sali, A. and Blundell, T.L.
T Environment-specific amino acid substitution tables: tertiary templates
and prediction of protein folds
J Protein Science 1, 216-226 (1992)
M rows = ACDEFGHIKLMNPQRSTVWYJ-, cols = ACDEFGHIKLMNPQRSTVWYJ
0.355 0.007 0.090 0.100 0.050 0.177 0.037 0.077 0.096 0.056 0.081 0.103 0.106 0.090 0.088 0.163 0.120 0.098 0.065 0.036 0.252
0.001 0.901 0.000 0.000 0.000 0.000 0.000 0.004 0.001 0.000 0.000 0.003 0.000 0.006 0.006 0.004 0.002 0.000 0.007 0.000 0.000
0.038 0.000 0.315 0.109 0.006 0.041 0.027 0.009 0.033 0.004 0.009 0.088 0.051 0.089 0.023 0.065 0.048 0.013 0.012 0.011 0.009
0.044 0.011 0.111 0.305 0.011 0.048 0.026 0.011 0.059 0.013 0.009 0.068 0.069 0.086 0.053 0.033 0.045 0.017 0.012 0.018 0.000
0.017 0.000 0.005 0.007 0.415 0.004 0.009 0.039 0.025 0.097 0.042 0.013 0.006 0.011 0.009 0.009 0.014 0.041 0.053 0.085 0.009
0.065 0.000 0.070 0.042 0.006 0.370 0.017 0.022 0.029 0.013 0.015 0.036 0.043 0.031 0.013 0.068 0.049 0.014 0.009 0.021 0.045
0.010 0.000 0.012 0.011 0.010 0.007 0.571 0.003 0.022 0.005 0.015 0.043 0.006 0.035 0.021 0.016 0.008 0.017 0.009 0.037 0.009
0.029 0.014 0.009 0.008 0.048 0.021 0.004 0.325 0.017 0.076 0.107 0.018 0.007 0.007 0.015 0.014 0.033 0.112 0.016 0.030 0.018
0.053 0.007 0.044 0.081 0.020 0.041 0.044 0.026 0.336 0.029 0.059 0.073 0.045 0.094 0.163 0.041 0.054 0.026 0.041 0.028 0.036
0.038 0.000 0.006 0.018 0.210 0.019 0.004 0.139 0.033 0.415 0.225 0.033 0.016 0.041 0.028 0.029 0.026 0.133 0.037 0.057 0.036
0.013 0.000 0.004 0.003 0.016 0.007 0.000 0.043 0.014 0.053 0.197 0.010 0.000 0.018 0.004 0.003 0.010 0.018 0.021 0.021 0.018
0.031 0.007 0.057 0.035 0.010 0.026 0.054 0.012 0.034 0.012 0.013 0.195 0.015 0.066 0.026 0.037 0.046 0.012 0.002 0.048 0.000
0.022 0.000 0.036 0.035 0.005 0.026 0.011 0.009 0.020 0.006 0.000 0.013 0.424 0.013 0.016 0.039 0.011 0.009 0.002 0.000 0.000
0.025 0.011 0.045 0.039 0.011 0.021 0.031 0.004 0.045 0.015 0.035 0.059 0.015 0.183 0.029 0.030 0.030 0.008 0.007 0.025 0.009
0.019 0.011 0.012 0.023 0.005 0.008 0.019 0.010 0.069 0.009 0.004 0.018 0.013 0.028 0.348 0.030 0.019 0.005 0.007 0.018 0.018
0.086 0.021 0.075 0.047 0.012 0.079 0.033 0.020 0.041 0.020 0.009 0.089 0.082 0.069 0.063 0.264 0.096 0.028 0.005 0.020 0.054
0.043 0.007 0.039 0.033 0.020 0.038 0.014 0.026 0.032 0.015 0.026 0.057 0.028 0.046 0.035 0.065 0.266 0.037 0.016 0.034 0.000
0.055 0.000 0.018 0.021 0.069 0.022 0.044 0.178 0.025 0.111 0.016 0.018 0.025 0.017 0.015 0.129 0.060 0.350 0.012 0.043 0.162
0.009 0.000 0.003 0.004 0.022 0.004 0.007 0.006 0.012 0.006 0.020 0.001 0.001 0.006 0.004 0.002 0.007 0.003 0.588 0.064 0.000
0.009 0.000 0.006 0.006 0.046 0.006 0.029 0.014 0.007 0.013 0.031 0.033 0.003 0.020 0.010 0.007 0.017 0.016 0.078 0.377 0.027
0.009 0.000 0.001 0.000 0.001 0.004 0.001 0.002 0.002 0.002 0.004 0.000 0.000 0.004 0.003 0.006 0.004 0.010 0.000 0.005 0.297
0.028 0.004 0.041 0.074 0.010 0.029 0.017 0.022 0.050 0.031 0.033 0.031 0.045 0.039 0.028 0.047 0.034 0.032 0.002 0.021 0.000
//
"""
# Run tests if called from the command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_agilent_microarray.py 000644 000765 000024 00000002734 12024702176 025046 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for the Microarray output parser
"""
from __future__ import division
from cogent.util.unit_test import TestCase, main
from cogent.parse.agilent_microarray import *
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Production"
class MicroarrayParserTests(TestCase):
"""Tests for MicroarrayParser.
"""
def setUp(self):
"""Setup function for MicroarrayParser tests.
"""
self.sample_file = ['first line in file',
'second line, useless data',
'FEATURES\tFirst\tL\tProbeName\tGeneName\tLogRatio',
'DATA\tFirst\tData\tProbe1\tGene1\t0.02',
'DATA\tSecond\tData\tProbe2\tGene2\t-0.34']
def test_MicroarrayParser_empty_list(self):
#Empty list should return tuple of empty lists
self.assertEqual(MicroarrayParser([]),([],[],[]))
def test_MicroarrayParser(self):
#Given correct file format, return correct results
self.assertEqual(MicroarrayParser(self.sample_file),
(['PROBE1','PROBE2'],
['GENE1','GENE2'],[float(0.02),float(-0.34)]))
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_binary_sff.py 000644 000765 000024 00000043253 12024702176 023316 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import copy
import os
import tempfile
from unittest import TestCase, main
from cogent.parse.binary_sff import (
seek_pad, parse_common_header, parse_read_header, parse_read_data,
validate_common_header, parse_read, parse_binary_sff, UnsupportedSffError,
write_pad, write_common_header, write_read_header, write_read_data,
write_read, write_binary_sff, format_common_header, format_read_header,
format_read_data, format_binary_sff, base36_encode, base36_decode,
decode_location, decode_timestamp, decode_accession, decode_sff_filename,
)
__author__ = "Kyle Bittinger"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Kyle Bittinger"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Kyle Bittinger"
__email__ = "kylebittinger@gmail.com"
__status__ = "Production"
TEST_DIR = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
SFF_FP = os.path.join(TEST_DIR, 'data', 'F6AVWTA01.sff')
class WritingFunctionTests(TestCase):
def setUp(self):
self.output_file = tempfile.TemporaryFile()
def test_write_pad(self):
self.output_file.write('\x01\x02\x03\x04')
write_pad(self.output_file)
self.output_file.seek(0)
buff = self.output_file.read()
self.assertEqual(buff, '\x01\x02\x03\x04\x00\x00\x00\x00')
def test_write_common_header(self):
write_common_header(self.output_file, COMMON_HEADER)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
self.output_file.seek(0)
observed = parse_common_header(self.output_file)
self.assertEqual(observed, COMMON_HEADER)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
def test_write_read_header(self):
write_read_header(self.output_file, READ_HEADER)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
self.output_file.seek(0)
observed = parse_read_header(self.output_file)
self.assertEqual(observed, READ_HEADER)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
def test_write_read_data(self):
write_read_data(self.output_file, READ_DATA)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
self.output_file.seek(0)
num_flows = len(READ_DATA['flowgram_values'])
num_bases = len(READ_DATA['Bases'])
observed = parse_read_data(self.output_file, num_bases, num_flows)
self.assertEqual(observed, READ_DATA)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
def test_write_read(self):
read = READ_HEADER.copy()
read.update(READ_DATA)
write_read(self.output_file, read)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
self.output_file.seek(0)
num_flows = len(read['flowgram_values'])
observed = parse_read(self.output_file)
self.assertEqual(observed, read)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
def test_write_binary_sff(self):
read = READ_HEADER.copy()
read.update(READ_DATA)
header = COMMON_HEADER.copy()
header['number_of_reads'] = 1
write_binary_sff(self.output_file, header, [read])
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
self.output_file.seek(0)
observed_header, observed_reads = parse_binary_sff(
self.output_file, native_flowgram_values=True)
observed_reads = list(observed_reads)
self.assertEqual(observed_header, header)
self.assertEqual(observed_reads[0], read)
self.assertEqual(len(observed_reads), 1)
file_pos = self.output_file.tell()
self.assertTrue(file_pos % 8 == 0)
class ParsingFunctionTests(TestCase):
def setUp(self):
self.sff_file = open(SFF_FP)
def test_seek_pad(self):
f = self.sff_file
f.seek(8)
seek_pad(f)
self.assertEqual(f.tell(), 8)
f.seek(9)
seek_pad(f)
self.assertEqual(f.tell(), 16)
f.seek(10)
seek_pad(f)
self.assertEqual(f.tell(), 16)
f.seek(15)
seek_pad(f)
self.assertEqual(f.tell(), 16)
f.seek(16)
seek_pad(f)
self.assertEqual(f.tell(), 16)
f.seek(17)
seek_pad(f)
self.assertEqual(f.tell(), 24)
def test_parse_common_header(self):
observed = parse_common_header(self.sff_file)
self.assertEqual(observed, COMMON_HEADER)
def test_validate_common_header(self):
header = {
'magic_number': 779314790,
'version': 1,
'flowgram_format_code': 1,
'index_offset': 0,
'index_length': 0,
'number_of_reads': 0,
'header_length': 0,
'key_length': 0,
'number_of_flows_per_read': 0,
'flow_chars': 'A',
'key_sequence': 'A',
}
self.assertEqual(validate_common_header(header), None)
header['version'] = 2
self.assertRaises(UnsupportedSffError, validate_common_header, header)
def test_parse_read_header(self):
self.sff_file.seek(440)
observed = parse_read_header(self.sff_file)
self.assertEqual(observed, READ_HEADER)
def test_parse_read_data(self):
self.sff_file.seek(440 + 32)
observed = parse_read_data(self.sff_file, 271, 400)
self.assertEqual(observed, READ_DATA)
def test_parse_read(self):
self.sff_file.seek(440)
observed = parse_read(self.sff_file, 400)
expected = dict(READ_HEADER.items() + READ_DATA.items())
self.assertEqual(observed, expected)
def test_parse_sff(self):
header, reads = parse_binary_sff(self.sff_file)
self.assertEqual(header, COMMON_HEADER)
counter = 0
for read in reads:
self.assertEqual(
len(read['flowgram_values']), header['number_of_flows_per_read'])
counter += 1
self.assertEqual(counter, 20)
class FormattingFunctionTests(TestCase):
def setUp(self):
self.output_file = tempfile.TemporaryFile()
def test_format_common_header(self):
self.assertEqual(
format_common_header(COMMON_HEADER), COMMON_HEADER_TXT)
def test_format_read_header(self):
self.assertEqual(
format_read_header(READ_HEADER), READ_HEADER_TXT)
def test_format_read_header(self):
self.assertEqual(
format_read_data(READ_DATA, READ_HEADER), READ_DATA_TXT)
def test_format_binary_sff(self):
output_buffer = format_binary_sff(open(SFF_FP))
output_buffer.seek(0)
expected = COMMON_HEADER_TXT + READ_HEADER_TXT + READ_DATA_TXT
observed = output_buffer.read(len(expected))
self.assertEqual(observed, expected)
class Base36Tests(TestCase):
def test_base36_encode(self):
self.assertEqual(base36_encode(2), 'C')
self.assertEqual(base36_encode(37), 'BB')
def test_base36_decode(self):
self.assertEqual(base36_decode('C'), 2)
self.assertEqual(base36_decode('BB'), 37)
def test_decode_location(self):
self.assertEqual(decode_location('C'), (0, 2))
def test_decode_timestamp(self):
self.assertEqual(decode_timestamp('C3U5GW'), (2004, 9, 22, 16, 59, 10))
self.assertEqual(decode_timestamp('GA202I'), (2010, 1, 22, 13, 28, 56))
def test_decode_accession(self):
self.assertEqual(
decode_accession('GA202I001ER3QL'),
((2010, 1, 22, 13, 28, 56), '0', 1, (1843, 859)))
def test_decode_sff_filename(self):
self.assertEqual(
decode_sff_filename('F6AVWTA01.sff'),
((2009, 11, 25, 14, 30, 19), 'A', 1))
COMMON_HEADER = {
'header_length': 440,
'flowgram_format_code': 1,
'index_length': 900,
'magic_number': 779314790,
'number_of_flows_per_read': 400,
'version': 1,
'flow_chars': 100 * 'TACG',
'key_length': 4,
'key_sequence': 'TCAG',
'number_of_reads': 20,
'index_offset': 33464,
}
COMMON_HEADER_TXT = """\
Common Header:
Magic Number: 0x2E736666
Version: 0001
Index Offset: 33464
Index Length: 900
# of Reads: 20
Header Length: 440
Key Length: 4
# of Flows: 400
Flowgram Code: 1
Flow Chars: TACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACG
Key Sequence: TCAG
"""
READ_HEADER = {
'name_length': 14,
'Name': 'GA202I001ER3QL',
'clip_adapter_left': 0,
'read_header_length': 32,
'clip_adapter_right': 0,
'number_of_bases': 271,
'clip_qual_left': 5,
'clip_qual_right': 271,
}
READ_HEADER_TXT = """
>GA202I001ER3QL
Run Prefix: R_2010_01_22_13_28_56_
Region #: 1
XY Location: 1843_0859
Read Header Len: 32
Name Length: 14
# of Bases: 271
Clip Qual Left: 5
Clip Qual Right: 271
Clip Adap Left: 0
Clip Adap Right: 0
"""
READ_DATA = {
'flow_index_per_base': (
1, 2, 3, 2, 3, 3, 2, 1, 1, 2, 1, 2, 0, 2, 3, 3, 2, 3, 3, 0, 2, 0, 2, 0,
1, 1, 1, 2, 0, 2, 2, 1, 0, 0, 3, 0, 2, 1, 0, 1, 1, 3, 1, 2, 2, 2, 3, 2,
1, 0, 2, 0, 3, 0, 3, 3, 1, 3, 0, 0, 0, 0, 2, 1, 0, 2, 0, 2, 0, 2, 2, 2,
2, 3, 2, 2, 0, 1, 0, 0, 0, 2, 1, 3, 2, 0, 3, 3, 2, 1, 2, 0, 2, 2, 1, 2,
1, 2, 0, 1, 3, 0, 0, 3, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 3, 0, 2, 1, 1, 2,
1, 3, 2, 2, 1, 0, 3, 3, 0, 2, 0, 1, 1, 3, 3, 3, 2, 0, 0, 0, 3, 3, 2, 1,
1, 2, 2, 1, 1, 0, 1, 0, 2, 0, 3, 1, 1, 0, 2, 0, 0, 1, 0, 3, 2, 3, 3, 3,
1, 3, 2, 0, 1, 3, 3, 3, 1, 3, 2, 0, 1, 2, 2, 3, 3, 3, 2, 3, 3, 3, 0, 3,
3, 2, 2, 0, 3, 1, 1, 3, 0, 1, 0, 3, 2, 2, 0, 2, 0, 2, 0, 0, 2, 3, 2, 2,
0, 2, 0, 3, 2, 3, 1, 2, 0, 3, 0, 2, 2, 2, 1, 1, 2, 2, 1, 1, 0, 3, 3, 2,
0, 1, 0, 3, 0, 2, 3, 1, 1, 1, 1, 3, 1, 0, 1, 1, 2, 2, 3, 1, 0, 0, 1, 1,
3, 3, 1, 3, 0, 1, 0),
'flowgram_values': (
101, 0, 98, 3, 0, 104, 2, 95, 1, 0, 97, 3, 0, 110, 2, 102, 102, 110, 2,
99, 101, 0, 195, 5, 102, 0, 5, 96, 7, 0, 95, 7, 101, 0, 8, 98, 9, 0,
190, 9, 201, 0, 194, 101, 107, 104, 12, 198, 13, 104, 2, 105, 295, 7,
4, 197, 10, 101, 195, 98, 101, 3, 10, 100, 102, 0, 100, 7, 101, 0, 96,
8, 11, 102, 12, 102, 203, 9, 196, 8, 13, 206, 13, 6, 103, 10, 4, 103,
102, 3, 7, 479, 9, 102, 202, 10, 198, 6, 195, 9, 102, 0, 100, 5, 100,
2, 103, 8, 8, 100, 6, 102, 7, 200, 388, 10, 97, 100, 8, 5, 100, 12, 197,
7, 13, 103, 8, 7, 104, 10, 101, 104, 12, 201, 12, 99, 8, 99, 106, 13,
103, 102, 8, 202, 108, 9, 13, 293, 7, 4, 203, 103, 202, 107, 376, 103,
8, 11, 188, 8, 99, 101, 104, 8, 92, 101, 12, 4, 92, 11, 101, 7, 96, 202,
8, 12, 93, 11, 11, 202, 7, 195, 101, 102, 6, 0, 101, 7, 7, 106, 2, 6,
107, 4, 404, 12, 6, 104, 8, 10, 98, 2, 105, 110, 100, 8, 95, 3, 105,
102, 208, 201, 13, 195, 14, 0, 99, 86, 202, 9, 301, 206, 8, 8, 85, 6,
101, 6, 9, 103, 8, 9, 96, 4, 7, 102, 111, 0, 8, 93, 7, 194, 111, 5, 10,
95, 5, 10, 104, 2, 6, 98, 103, 0, 11, 99, 15, 192, 110, 5, 98, 8, 91, 8,
10, 92, 5, 10, 102, 8, 7, 105, 15, 102, 7, 9, 100, 2, 3, 102, 6, 9, 203,
6, 14, 107, 12, 8, 107, 1, 103, 13, 202, 2, 6, 108, 103, 99, 11, 2, 201,
207, 14, 8, 94, 4, 95, 9, 195, 13, 193, 9, 306, 13, 100, 11, 6, 75, 13,
91, 12, 205, 7, 203, 10, 3, 107, 17, 111, 12, 4, 105, 106, 7, 208, 5, 9,
202, 8, 108, 6, 84, 16, 103, 108, 92, 16, 93, 8, 95, 94, 207, 17, 10,
103, 3, 0, 104, 0, 202, 217, 16, 12, 197, 4, 90, 15, 17, 108, 98, 125,
104, 88, 14, 15, 99, 187, 106, 109, 12, 100, 11, 81, 8, 11, 92, 304,
112, 107, 2, 11, 94, 7, 6, 86, 97, 19, 3, 225, 206),
'Bases': (
'TCAGCAGTAGTCCTGCTGCCTTCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCT'
'CTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCCCGCCTACTATCTAATGGAACGCATCCCC'
'ATCGTCTACCGGAATACCTTTAATCATGTGAACATGTGAACTCATGATGCCATCTTGTATTAATCTTCCT'
'TTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGTGCGCCGG'),
'quality_scores': (
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40,
40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 37, 37, 37, 37, 37,
37, 37, 37, 34, 34, 34, 34, 34, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
38, 32, 32, 32, 32, 38, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
37, 37, 37, 37, 38, 38, 38, 38, 40, 40, 40, 38, 38, 38, 38, 38, 38, 38,
40, 38, 38, 38, 38, 38, 38, 37, 38, 38, 36, 37, 37, 36, 33, 28, 28, 31,
31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 32, 32, 31, 30, 30, 25, 25, 25,
25),
}
READ_DATA_TXT = """
Flowgram: 1.01 0.00 0.98 0.03 0.00 1.04 0.02 0.95 0.01 0.00 0.97 0.03 0.00 1.10 0.02 1.02 1.02 1.10 0.02 0.99 1.01 0.00 1.95 0.05 1.02 0.00 0.05 0.96 0.07 0.00 0.95 0.07 1.01 0.00 0.08 0.98 0.09 0.00 1.90 0.09 2.01 0.00 1.94 1.01 1.07 1.04 0.12 1.98 0.13 1.04 0.02 1.05 2.95 0.07 0.04 1.97 0.10 1.01 1.95 0.98 1.01 0.03 0.10 1.00 1.02 0.00 1.00 0.07 1.01 0.00 0.96 0.08 0.11 1.02 0.12 1.02 2.03 0.09 1.96 0.08 0.13 2.06 0.13 0.06 1.03 0.10 0.04 1.03 1.02 0.03 0.07 4.79 0.09 1.02 2.02 0.10 1.98 0.06 1.95 0.09 1.02 0.00 1.00 0.05 1.00 0.02 1.03 0.08 0.08 1.00 0.06 1.02 0.07 2.00 3.88 0.10 0.97 1.00 0.08 0.05 1.00 0.12 1.97 0.07 0.13 1.03 0.08 0.07 1.04 0.10 1.01 1.04 0.12 2.01 0.12 0.99 0.08 0.99 1.06 0.13 1.03 1.02 0.08 2.02 1.08 0.09 0.13 2.93 0.07 0.04 2.03 1.03 2.02 1.07 3.76 1.03 0.08 0.11 1.88 0.08 0.99 1.01 1.04 0.08 0.92 1.01 0.12 0.04 0.92 0.11 1.01 0.07 0.96 2.02 0.08 0.12 0.93 0.11 0.11 2.02 0.07 1.95 1.01 1.02 0.06 0.00 1.01 0.07 0.07 1.06 0.02 0.06 1.07 0.04 4.04 0.12 0.06 1.04 0.08 0.10 0.98 0.02 1.05 1.10 1.00 0.08 0.95 0.03 1.05 1.02 2.08 2.01 0.13 1.95 0.14 0.00 0.99 0.86 2.02 0.09 3.01 2.06 0.08 0.08 0.85 0.06 1.01 0.06 0.09 1.03 0.08 0.09 0.96 0.04 0.07 1.02 1.11 0.00 0.08 0.93 0.07 1.94 1.11 0.05 0.10 0.95 0.05 0.10 1.04 0.02 0.06 0.98 1.03 0.00 0.11 0.99 0.15 1.92 1.10 0.05 0.98 0.08 0.91 0.08 0.10 0.92 0.05 0.10 1.02 0.08 0.07 1.05 0.15 1.02 0.07 0.09 1.00 0.02 0.03 1.02 0.06 0.09 2.03 0.06 0.14 1.07 0.12 0.08 1.07 0.01 1.03 0.13 2.02 0.02 0.06 1.08 1.03 0.99 0.11 0.02 2.01 2.07 0.14 0.08 0.94 0.04 0.95 0.09 1.95 0.13 1.93 0.09 3.06 0.13 1.00 0.11 0.06 0.75 0.13 0.91 0.12 2.05 0.07 2.03 0.10 0.03 1.07 0.17 1.11 0.12 0.04 1.05 1.06 0.07 2.08 0.05 0.09 2.02 0.08 1.08 0.06 0.84 0.16 1.03 1.08 0.92 0.16 0.93 0.08 0.95 0.94 2.07 0.17 0.10 1.03 0.03 0.00 1.04 0.00 2.02 2.17 0.16 0.12 1.97 0.04 0.90 0.15 0.17 1.08 0.98 1.25 1.04 0.88 0.14 0.15 0.99 1.87 1.06 1.09 0.12 1.00 0.11 0.81 0.08 0.11 0.92 3.04 1.12 1.07 0.02 0.11 0.94 0.07 0.06 0.86 0.97 0.19 0.03 2.25 2.06
Flow Indexes: 1 3 6 8 11 14 16 17 18 20 21 23 23 25 28 31 33 36 39 39 41 41 43 43 44 45 46 48 48 50 52 53 53 53 56 56 58 59 59 60 61 64 65 67 69 71 74 76 77 77 79 79 82 82 85 88 89 92 92 92 92 92 94 95 95 97 97 99 99 101 103 105 107 110 112 114 114 115 115 115 115 117 118 121 123 123 126 129 131 132 134 134 136 138 139 141 142 144 144 145 148 148 148 151 151 152 153 153 154 155 155 155 155 156 159 159 161 162 163 165 166 169 171 173 174 174 177 180 180 182 182 183 184 187 190 193 195 195 195 195 198 201 203 204 205 207 209 210 211 211 212 212 214 214 217 218 219 219 221 221 221 222 222 225 227 230 233 236 237 240 242 242 243 246 249 252 253 256 258 258 259 261 263 266 269 272 274 277 280 283 283 286 289 291 293 293 296 297 298 301 301 302 302 305 307 309 309 311 311 313 313 313 315 318 320 322 322 324 324 327 329 332 333 335 335 338 338 340 342 344 345 346 348 350 351 352 352 355 358 360 360 361 361 364 364 366 369 370 371 372 373 376 377 377 378 379 381 383 386 387 387 387 388 389 392 395 396 399 399 400 400
Bases: tcagCAGTAGTCCTGCTGCCTTCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCCCGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGTGAACTCATGATGCCATCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGTGCGCCGG
Quality Scores: 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 37 37 37 37 37 37 37 37 34 34 34 34 34 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 38 32 32 32 32 38 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 38 38 38 38 40 40 40 38 38 38 38 38 38 38 40 38 38 38 38 38 38 37 38 38 36 37 37 36 33 28 28 31 31 31 31 31 31 31 31 31 31 31 32 32 31 30 30 25 25 25 25
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_blast.py 000644 000765 000024 00000032350 12024702176 022275 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of BLAST parser.
"""
from string import split, strip
from cogent.util.unit_test import TestCase, main
from cogent.parse.blast import iter_finder, query_finder, iteration_set_finder,\
is_blast_junk, is_blat_junk, make_label, PsiBlastQueryFinder, \
TableToValues, \
PsiBlastTableParser, PsiBlastFinder, GenericBlastParser9, \
PsiBlastParser9, LastProteinIds9, QMEBlast9, QMEPsiBlast9, \
fastacmd_taxonomy_splitter, FastacmdTaxonomyParser
__author__ = "Micah Hamady"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Micah Hamady", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Micah Hamady"
__email__ = "hamady@colorado.edu"
__status__ = "Production"
class BlastTests(TestCase):
"""Tests of top-level functions"""
def setUp(self):
"""Define some standard data"""
self.rec = """# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4181 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-06 52.8
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 2
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4181 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4181 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-08 59.0
ece:Z4181 sfl:CP0138 33.98 103 57 2 8 110 6 97 6e-06 50.5
ece:Z4181 spt:SPA2730 37.50 72 45 0 39 110 30 101 1e-05 49.8
ece:Z4181 sec:SC2804 37.50 72 45 0 39 110 30 101 1e-05 49.8
ece:Z4181 stm:STM2872 37.50 72 45 0 39 110 30 101 1e-05 49.8""".split('\n')
self.rec2 = """# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4181 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-06 52.8
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 2
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4181 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4181 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-08 59.0
ece:Z4181 sfl:CP0138 33.98 103 57 2 8 110 6 97 6e-06 50.5
ece:Z4181 spt:SPA2730 37.50 72 45 0 39 110 30 101 1e-05 49.8
ece:Z4181 sec:SC2804 37.50 72 45 0 39 110 30 101 1e-05 49.8
ece:Z4181 stm:STM2872 37.50 72 45 0 39 110 30 101 1e-05 49.8
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4182
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4182 ece:Z4182 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4182 ecs:ECs3718 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4182 cvi:CV2422 41.67 72 42 0 39 110 29 100 2e-06 52.8""".split('\n')
self.rec3 = """# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4181 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 spt:SPA2730 37.50 72 45 0 39 110 30 101 1e-05 49.8
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 2
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4181 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-08 59.0
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4182
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4182 ece:Z4182 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4182 cvi:CV2422 41.67 72 42 0 39 110 29 100 2e-06 52.8""".split('\n')
def test_iter_finder(self):
"""iter_finder should split on lines starting with '# Iteration:'"""
lines = 'abc\n# Iteration: 3\ndef'.split('\n')
self.assertEqual(map(iter_finder,lines), [False, True, False])
def test_query_finder(self):
"""query_finder should split on lines starting with '# Query:'"""
lines = 'abc\n# Query: dfdsffsd\ndef'.split('\n')
self.assertEqual(map(query_finder,lines), [False, True, False])
def test_iteration_set_finder(self):
"""iter_finder should split on lines starting with '# Iteration:'"""
lines = 'abc\n# Iteration: 3\ndef\n# Iteration: 1'.split('\n')
self.assertEqual(map(iteration_set_finder,lines), \
[False, False, False, True])
def test_is_junk(self):
"""is_junk should reject an assortment of invalid lines"""
#Note: testing two functions that call it instead of function itself
lines = 'abc\n# BLAST blah blah\n \n# BLAT blah\n123'.split('\n')
self.assertEqual(map(is_blast_junk, lines), \
[False, True, True, False, False])
self.assertEqual(map(is_blat_junk, lines), \
[False, False, True, True, False])
def test_make_label(self):
"""make_label should turn comment lines into (key, val) pairs"""
a = 'this test will fail: no # at start'
b = '#this test will fail because no colon'
c = '# Iteration: 1'
d = '# Query: ece:Z4147 ygdP; putative invasion protein [EC:3.6.1.-]'
e = '#Iteration: 1' #no space after the hash
self.assertRaises(ValueError, make_label, a)
self.assertRaises(ValueError, make_label, b)
#Note that we _do_ map the data type of known values value, so the
#value of the iteration will be 1, not '1'
self.assertEqual(make_label(c), ('ITERATION', 1))
self.assertEqual(make_label(d), ('QUERY', \
'ece:Z4147 ygdP; putative invasion protein [EC:3.6.1.-]'))
self.assertEqual(make_label(e), ('ITERATION', 1))
def test_TableToValues(self):
"""TableToValues should convert itself into the correct type."""
constructors = {'a':int, 'b':float, 'c':str}
table=[['c','b','a','d'], ['1.5', '3.5', '2', '2.5'],['1','2','3','4']]
self.assertEqual(TableToValues(table, constructors), \
([['1.5',3.5,2,'2.5'],['1',2.0,3,'4']], ['c','b','a','d']))
#check that it works with supplied header
self.assertEqual(TableToValues(table[1:], constructors, list('cbad')), \
([['1.5',3.5,2,'2.5'],['1',2.0,3,'4']], ['c','b','a','d']))
def test_PsiBlastTableParser(self):
"""PsiBlastTableParser should wrap values in table."""
fields = map(strip,
'Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score'.split(','))
table = map(split, """ece:Z4147 ece:Z4147 100.00 176 0 0 1 176 1 176 2e-89 328
ece:Z4147 ecs:ECs3687 100.00 176 0 0 1 176 1 176 2e-89 328
ece:Z4147 ecc:c3425 100.00 176 0 0 1 176 1 176 2e-89 328
ece:Z4147 sfl:SF2840 100.00 176 0 0 1 176 1 176 2e-89 328""".split('\n'))
headed_table = [fields] + table
new_table, new_fields = PsiBlastTableParser(headed_table)
self.assertEqual(new_fields, fields)
self.assertEqual(len(new_table), 4)
self.assertEqual(new_table[1], ['ece:Z4147', 'ecs:ECs3687', 100.0, \
176, 0, 0, 1, 176, 1, 176, 2e-89, 328])
def test_GenericBlastParser9(self):
"""GenericBlastParser9 should read blast's tabular format (#9)."""
rec = self.rec
p = GenericBlastParser9(rec, PsiBlastFinder)
result = list(p)
self.assertEqual(len(result), 2)
first, second = result
self.assertEqual(first[0], {'ITERATION':1,'QUERY':'ece:Z4181',\
'DATABASE':'db/everything.faa', 'FIELDS':'Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score'})
self.assertEqual(len(first[1]), 3)
self.assertEqual(second[0]['ITERATION'], 2)
self.assertEqual(len(second[1]), 7)
self.assertEqual(second[1][-1], \
'ece:Z4181 stm:STM2872 37.50 72 45 0 39 110 30 101 1e-05 49.8'.split())
def test_PsiBlastParser9(self):
"""PsiBlastParser9 should provide convenient results for format #9."""
result = PsiBlastParser9(self.rec2)
self.assertEqual(len(result), 2)
assert 'ece:Z4181' in result
assert 'ece:Z4182' in result
first = result['ece:Z4181']
second = result['ece:Z4182']
self.assertEqual(len(first), 2)
self.assertEqual(len(second), 1)
iter_1 = first[0]
iter_2 = first[1]
self.assertEqual(len(iter_1), 3)
self.assertEqual(len(iter_2), 7)
iter_1_2 = second[0]
self.assertEqual(len(iter_1_2), 3)
self.assertEqual(len(result['ece:Z4181'][1][3]), 12)
self.assertEqual(result['ece:Z4181'][1][3]['ALIGNMENT LENGTH'], 103)
def test_LastProteinIds9(self):
"""LastProteinIds9 should give last protein ids in iter"""
result = LastProteinIds9(self.rec)
self.assertEqual(result, ['ece:Z4181', 'ecs:ECs3717', 'cvi:CV2421',\
'sfl:CP0138', 'spt:SPA2730', 'sec:SC2804', 'stm:STM2872'])
#should also work if threshold set
result = LastProteinIds9(self.rec, False, threshold=8e-6)
self.assertEqual(result, ['ece:Z4181', 'ecs:ECs3717', 'cvi:CV2421',\
'sfl:CP0138'])
#should work on multiple records
result = map(LastProteinIds9, PsiBlastQueryFinder(self.rec2))
self.assertEqual(len(result), 2)
self.assertEqual(result[0], ['ece:Z4181', 'ecs:ECs3717', 'cvi:CV2421',\
'sfl:CP0138', 'spt:SPA2730', 'sec:SC2804', 'stm:STM2872'])
self.assertEqual(result[1], ['ece:Z4182','ecs:ECs3718','cvi:CV2422'])
def test_QMEBlast9(self):
"""QMEBlast9 should return expected lines from all iterations"""
self.assertFloatEqual(QMEBlast9(self.rec3), [\
('ece:Z4181','ece:Z4181',3e-47),
('ece:Z4181','ecs:ECs3717',3e-47),
('ece:Z4181','spt:SPA2730', 1e-5),
('ece:Z4181','ecs:ECs3717',3e-54), #WARNING: allows duplicates
('ece:Z4181','cvi:CV2421',2e-8),
('ece:Z4182','ece:Z4182',3e-47),
('ece:Z4182','cvi:CV2422',2e-6),
])
def test_QMEPsiBlast9(self):
"""QMEPsiBlast9 should only return items from last iterations"""
self.assertFloatEqual(QMEPsiBlast9(self.rec3), [\
('ece:Z4181','ecs:ECs3717',3e-54),
('ece:Z4181','cvi:CV2421',2e-8),
('ece:Z4182','ece:Z4182',3e-47),
('ece:Z4182','cvi:CV2422',2e-6),
])
def test_fastacmd_taxonomy_splitter(self):
"""fastacmd_taxonomy_splitter should split records into groups"""
text = """NCBI sequence id: gi|3021565|emb|AJ223314.1|PSAJ3314
NCBI taxonomy id: 3349
Common name: Scots pine
Scientific name: Pinus sylvestris
NCBI sequence id: gi|37777029|dbj|AB108787.1|
NCBI taxonomy id: 228610
Common name: cf. Acremonium sp. KR21-2
Scientific name: cf. Acremonium sp. KR21-2
""".splitlines()
recs = list(fastacmd_taxonomy_splitter(text))
self.assertEqual(len(recs), 2)
self.assertEqual(recs[0], text[:5]) #includes trailing blank
def test_FastaCmdTaxonomyParser(self):
"""FastaCmdTaxonomyParser should parse taxonomy record to dict"""
text = """NCBI sequence id: gi|3021565|emb|AJ223314.1|PSAJ3314
NCBI taxonomy id: 3349
Common name: Scots pine
Scientific name: Pinus sylvestris
NCBI sequence id: gi|37777029|dbj|AB108787.1|
NCBI taxonomy id: 228610
Common name: cf. Acremonium sp. KR21-2
Scientific name: cf. Acremonium sp. KR21-2
""".splitlines()
recs = list(FastacmdTaxonomyParser(text))
self.assertEqual(len(recs), 2)
for r in recs:
self.assertEqual(sorted(r.keys()), ['common_name','scientific_name',
'seq_id', 'tax_id'])
r0, r1 = recs
self.assertEqual(r0['tax_id'], '3349')
self.assertEqual(r0['common_name'], 'Scots pine')
self.assertEqual(r0['scientific_name'], 'Pinus sylvestris')
self.assertEqual(r0['seq_id'], 'gi|3021565|emb|AJ223314.1|PSAJ3314')
self.assertEqual(r1['tax_id'], '228610')
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_blast_xml.py 000644 000765 000024 00000027220 12024702176 023155 0 ustar 00jrideout staff 000000 000000 #! /usr/bin/env python
#
# test_blast_xml.py
#
__author__ = "Kristian Rother"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Micah Hamady"]
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Kristian Rother"
__email__ = "krother@rubor.de"
__status__ = "Prototype"
from cogent.util.unit_test import main, TestCase
from cogent.parse.blast_xml import BlastXMLResult, MinimalBlastParser7,\
get_tag, parse_hsp, parse_hit, parse_header, parse_parameters,\
HSP_XML_FIELDNAMES, HIT_XML_FIELDNAMES
import xml.dom.minidom
class GetTagTests(TestCase):
"""Tests for the auxiliary function evaluating the tag objects."""
def setUp(self):
self.single_tag = xml.dom.minidom.parseString(\
"bla content bla ")
self.double_tag = xml.dom.minidom.parseString(\
"first content second content This is not a XML tag object ","h1")
class MinimalBlastParser7Tests(TestCase):
"""Tests for the functions required by the Blast XML parsers."""
def setUp(self):
self.hit1 = xml.dom.minidom.parseString(HIT_WITH_ONE_HSP)
self.hit2 = xml.dom.minidom.parseString(HIT_WITH_TWO_HSPS)
self.hsp1 = xml.dom.minidom.parseString(HSP_ONE)
self.hsp2 = xml.dom.minidom.parseString(HSP_TWO)
self.hsp_gaps = xml.dom.minidom.parseString(HSP_WITH_GAPS)
self.param = xml.dom.minidom.parseString(PARAM_XML)
self.header = xml.dom.minidom.parseString(HEADER_XML)
self.complete = xml.dom.minidom.parseString(HEADER_COMPLETE)
def test_parse_header(self):
"""Fields from XML header tag should be available as dict."""
data = parse_header(self.header)
self.assertEqual(data.get('application'), 'my Grandma')
self.assertEqual(data.get('version'), 'has')
self.assertEqual(data.get('reference'), 'furry')
self.assertEqual(data.get('query_letters'), 27)
self.assertEqual(data.get('database'), 'Cats')
def test_parse_parameters(self):
"""Fields from XML parameter tag should be available as dict."""
data = parse_parameters(self.param)
self.assertEqual(data.get('matrix'), 'BLOSUM62')
self.assertEqual(data.get('expect'), '10')
self.assertEqual(data.get('gap_open_penalty'), 11.1)
self.assertEqual(data.get('gap_extend_penalty'), 22.2)
self.assertEqual(data.get('filter'), 'F')
def test_parse_header_complete(self):
"""Fields from header+param tag should be available as dict."""
# try to process header with parameters etc in the XML
data = parse_header(self.complete)
self.assertEqual(data.get('database'), 'Cats')
self.assertEqual(data.get('matrix'), 'BLOSUM62')
def test_parse_hit(self):
"""Should return a list with all values for a hit+hsp."""
data = parse_hit(self.hit1)
self.assertEqual(len(data),1)
d = dict(zip(HIT_XML_FIELDNAMES,data[0]))
self.assertEqual(d['SUBJECT_ID'],"gi|148670104|gb|EDL02051.1|")
self.assertEqual(d['HIT_DEF'],
"insulin-like growth factor 2 receptor, isoform CRA_c [Mus musculus]")
self.assertEqual(d['HIT_ACCESSION'],"2001")
self.assertEqual(int(d['HIT_LENGTH']),707)
# check hit with more HSPs
data = parse_hit(self.hit2)
self.assertEqual(len(data),2)
self.assertNotEqual(data[0],data[1])
def test_parse_hsp(self):
"""Should return list with all values for a hsp."""
data = parse_hsp(self.hsp1)
d = dict(zip(HSP_XML_FIELDNAMES,data))
self.assertEqual(float(d['BIT_SCORE']),1023.46)
self.assertEqual(float(d['SCORE']),2645)
self.assertEqual(float(d['E_VALUE']),0.333)
self.assertEqual(int(d['QUERY_START']),4)
self.assertEqual(int(d['QUERY_END']),18)
self.assertEqual(int(d['SUBJECT_START']),5)
self.assertEqual(int(d['SUBJECT_END']),19)
self.assertEqual(int(d['GAP_OPENINGS']),0)
self.assertEqual(int(d['ALIGNMENT_LENGTH']),14)
self.assertEqual(d['QUERY_ALIGN'],'ELEPHANTTHISISAHITTIGER')
self.assertEqual(d['MIDLINE_ALIGN'],'ORCA-WHALE')
self.assertEqual(d['SUBJECT_ALIGN'],'SEALSTHIS---HIT--GER')
class BlastXmlResultTests(TestCase):
"""Tests parsing of output of Blast with output mode 7 (XML)."""
def setUp(self):
self.result = BlastXMLResult(COMPLETE_XML,xml=True)
def test_options(self):
"""Constructor should take parser as an option."""
result = BlastXMLResult(COMPLETE_XML,parser=MinimalBlastParser7)
self.assertEqual(len(result.keys()),1)
# make sure whether normal Blast parser still works upon code merge!
def test_parsed_query_sequence(self):
"""The result dict should have one query sequence as a key."""
# The full query sequence is not given in the XML file.
# Thus it is not checked explicitly, only whether there is
# exactly one found.
self.assertEqual(len(self.result.keys()),1)
def test_parsed_iterations(self):
"""The result should have the right number of iterations."""
n_iter = 0
for query_id,hits in self.result.iterHitsByQuery():
n_iter += 1
self.assertEqual(n_iter,1)
def test_parsed_hsps(self):
"""The result should have the right number of hsps."""
n_hsps = 0
for query_id,hsps in self.result.iterHitsByQuery():
n_hsps += len(hsps)
self.assertEqual(n_hsps,3)
def test_parse_hit_details(self):
"""The result should have data from hit fields."""
for query in self.result:
first_hsp = self.result[query][0][0]
self.assertEqual(first_hsp['SUBJECT_ID'],
"gi|148670104|gb|EDL02051.1|")
self.assertEqual(first_hsp['HIT_DEF'],
"insulin-like growth factor 2 receptor, isoform CRA_c [Mus musculus]")
self.assertEqual(first_hsp['HIT_ACCESSION'],"2001")
self.assertEqual(first_hsp['HIT_LENGTH'],707)
def test_parse_hsp_details(self):
"""The result should have data from hsp fields."""
for query in self.result:
# should check integers in next version.
first_hsp = self.result[query][0][0]
self.assertEqual(first_hsp['QUERY ID'],1)
self.assertEqual(first_hsp['BIT_SCORE'],'1023.46')
self.assertEqual(first_hsp['SCORE'],'2645')
self.assertEqual(first_hsp['E_VALUE'],'0.333')
self.assertEqual(first_hsp['QUERY_START'],'4')
self.assertEqual(first_hsp['QUERY_END'],'18')
self.assertEqual(first_hsp['QUERY_ALIGN'],'ELEPHANTTHISISAHITTIGER')
self.assertEqual(first_hsp['MIDLINE_ALIGN'],'ORCA-WHALE')
self.assertEqual(first_hsp['SUBJECT_ALIGN'],'SEALSTHIS---HIT--GER')
self.assertEqual(first_hsp['SUBJECT_START'],'5')
self.assertEqual(first_hsp['SUBJECT_END'],'19')
self.assertEqual(first_hsp['PERCENT_IDENTITY'],'55')
self.assertEqual(first_hsp['POSITIVE'],'555')
self.assertEqual(first_hsp['GAP_OPENINGS'],0)
self.assertEqual(first_hsp['ALIGNMENT_LENGTH'],'14')
gap_hsp = self.result[query][0][1]
self.assertEqual(gap_hsp['GAP_OPENINGS'],'33')
HSP_XML = """
1
1023.46
2645
0.333
4
18
5
19
1
1
55
%s
555
14
ELEPHANTTHISISAHITTIGER
SEALSTHIS---HIT--GER
ORCA-WHALE
"""
HSP_ONE = HSP_XML%''
HSP_WITH_GAPS = HSP_XML%'33 '
HSP_TWO = """
2
1023.46
2645
0.333
6
22
5
23
1
1
55
%s
555
18
EPHANT---THISISAHIT-TIGER
ALSWWWTHIS---HITW--GER
ORCA-WHALE
"""
HIT_XML = """
1
gi|148670104|gb|EDL02051.1|
insulin-like growth factor 2 receptor, isoform CRA_c [Mus musculus]
2001
707
%s
"""
HIT_WITH_ONE_HSP = HIT_XML%HSP_ONE
HIT_WITH_TWO_HSPS = HIT_XML%(HSP_WITH_GAPS+HSP_TWO)
PARAM_XML = """
BLOSUM62
10
11.1
22.2
F
"""
HEADER_XML = """
my Grandma
has
Cats
furry
27
%s
"""
HIT_PREFIX = """
"""
HIT_SUFFIX = """
"""
HEADER_COMPLETE=HEADER_XML%(PARAM_XML+HIT_PREFIX+HIT_WITH_ONE_HSP+\
HIT_WITH_TWO_HSPS+HIT_SUFFIX)
COMPLETE_XML = """
"""+HEADER_COMPLETE
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_bowtie.py 000644 000765 000024 00000006674 12024702176 022473 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the bowtie default output parser.
Compatible with bowtie version 0.12.5
"""
from cogent.parse.bowtie import BowtieOutputParser, BowtieToTable
from cogent.util.unit_test import TestCase, main
from cogent import LoadTable
__author__ = "Gavin Huttley, Anuj Pahwa"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight","Peter Maxwell", "Gavin Huttley", "Anuj Pahwa"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Development"
fname = 'data/bowtie_output.map'
expected = [['GAPC_0015:6:1:1283:11957#0/1', '-', 'Mus', 66047927, 'TGTATATATAAACATATATGGAAACTGAATATATATACATTATGTATGTATATATGTATATGTTATATATACATA', 'IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII', 0, ['55:A>G', '64:C>A']],
['GAPC_0015:6:1:1394:18813#0/1', '+', 'Mus', 77785518, 'ATGAAATTCCTAGCCAAATGGATGGACCTGGAGGGCATCATC', 'IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII', 447, []],
['GAPC_0015:6:1:1560:18056#0/1', '+', 'Mus', 178806665, 'TAGATAAAGGCTCTGTTTTTCATCATTGAGAAATTGTTATTTTTCTGATGTTATA', 'IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII', 0, ['9:T>G']],
['GAPC_0015:6:1:1565:19849#0/1', '+', 'Mus', 116516430, 'ACCATTTGCTTGGAAAATTGTTTTCCAGCCTTTCACTCTGAG', 'IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII', 141, []],
['GAPC_0015:6:1:1591:17397#0/1', '-', 'Mus', 120440696, 'TCTAAATCTGTTCATTAATTAAGCCTGTTTCCATGTCCTTGGTCTTAAGACCAATCTGTTATGCGGGTGTGA', 'IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII', 0, ['70:A>C', '71:G>T']]]
class BowtieOutputTest(TestCase):
def test_parsing(self):
"""make sure that the bowtie output file is parsed properly"""
parser = BowtieOutputParser(fname)
header = parser.next()
index = 0
for row in parser:
self.assertEqual(row, expected[index])
index += 1
def test_psl_to_table(self):
"""make sure that the table is built without any errors"""
table = BowtieToTable(fname)
def test_getting_seq_coords(self):
"""get correct information from the table"""
table = BowtieToTable(fname)
index = 0
for row in table:
query_name = row['Query Name']
strand_direction = row['Strand Direction']
query_offset = row['Offset']
self.assertEqual(query_name, expected[index][0])
self.assertEqual(strand_direction, expected[index][1])
self.assertEqual(query_offset, expected[index][3])
index += 1
def test_no_row_converter(self):
"""setting row_converter=None returns strings"""
# straight parser
parser = BowtieOutputParser(fname, row_converter=None)
header = parser.next()
for index, row in enumerate(parser):
query_offset = row[3]
other_matches = row[6]
self.assertEqual(query_offset, str(expected[index][3]))
self.assertEqual(other_matches, str(expected[index][6]))
# table
table = BowtieToTable(fname, row_converter=None)
for index, row in enumerate(table):
query_offset = row['Offset']
other_matches = row['Other Matches']
self.assertEqual(query_offset, str(expected[index][3]))
self.assertEqual(other_matches, str(expected[index][6]))
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_bpseq.py 000644 000765 000024 00000017670 12024702176 022312 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Provides Tests for BpseqParser and related functions.
"""
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.struct.knots import inc_order
from cogent.parse.bpseq import BpseqParseError, construct_sequence,\
parse_header, parse_residues, MinimalBpseqParser, BpseqParser,\
bpseq_specify_output
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Production"
class BpseqParserTests(TestCase):
"""Provides tests for BpseqParser and related functions"""
def test_parse_header(self):
"""parse_header: should work on standard header"""
h1 = ['Filename: d.16.b.E.coli.bpseq','Organism: Escherichia coli',\
'Accession Number: J01695', 'Citation and related information'+\
' available at http://www.rna.icmb.utexas.edu']
self.assertEqual(parse_header(h1),{'Filename':'d.16.b.E.coli.bpseq',\
'Accession Number': 'J01695', 'Organism': 'Escherichia coli',\
'Refs': {},'Citation':'http://www.rna.icmb.utexas.edu'})
assert isinstance(parse_header(h1), Info)
# lines without ':' are skipped
h2 = ['Filename: d.16.b.E.coli.bpseq','Organism: Escherichia coli',\
'Accession Number: J01695', 'Remark this is an interesting seq']
exp = {'Filename':'d.16.b.E.coli.bpseq', 'Refs': {},\
'Organism': 'Escherichia coli', 'Accession Number':'J01695'}
self.assertEqual(parse_header(h2),exp)
def test_construct_sequence(self):
"""construct_sequence: should return correct sequence or raise error
"""
d = {0:'A',1:'C',2:'G',3:'U'}
self.assertEqual(construct_sequence(d),'ACGU')
# doesn't check residue identity
d = {0:'A',1:'-',2:'R',3:'U'}
self.assertEqual(construct_sequence(d),'A-RU')
# error when sequence isn't continuous
d = {0:'A',1:'C',2:'G',5:'U'}
self.assertRaises(BpseqParseError, construct_sequence, d)
# error when first index is not zero
d = {1:'C',2:'G',3:'U',4:'A'}
self.assertRaises(BpseqParseError, construct_sequence, d)
def test_parse_residues(self):
"""parse_residues: should work on valid data
"""
lines = RES_LINES.split('\n')
exp_seq = 'UGGUAAUACGUUGCGAAGCC'
exp_pairs = [(2,8),(3,7),(4,11),(5,10),(6,9),(12,18),(13,17)]
self.assertEqual(parse_residues(lines, num_base=1,\
unpaired_symbol='0'), (exp_seq, exp_pairs))
def test_parse_residues_errors(self):
"""parse_residues: should raise BpseqParseErrors in several cases
"""
not_all_lines = RES_LINES_NOT_ALL.split('\n')
wrong_lines = RES_LINES_WRONG.split('\n')
conflict_lines = RES_LINES_CONFLICT.split('\n')
bp_conflict = RES_LINES_BP_CONFLICT.split('\n')
self.assertRaises(BpseqParseError, parse_residues, not_all_lines,\
num_base=1, unpaired_symbol='0')
self.assertRaises(BpseqParseError, parse_residues, wrong_lines,\
num_base=1, unpaired_symbol='0')
self.assertRaises(BpseqParseError, parse_residues, conflict_lines,\
num_base=1, unpaired_symbol='0')
self.assertRaises(BpseqParseError, parse_residues, bp_conflict,\
num_base=1, unpaired_symbol='0')
def test_parse_residues_diff_base(self):
"""parse_residues: should work with diff base and unpaired_symbol"""
lines = RES_LINES_DIFF_BASE.split('\n')
exp_seq = 'CAGACU'
exp_pairs = [(1,5),(2,4)]
obs = parse_residues(lines, num_base=3, unpaired_symbol='xxx')
self.assertEqual(obs, (exp_seq, exp_pairs))
def test_MinimalBpseqParser(self):
"""MinimalBpseqParser: should separate lines correctly"""
lines = ['Accesion: J01234', 'LABEL : label', '1 U 4', '2 A 10', 'xx',\
'A B C D E']
exp = {'HEADER': ['Accesion: J01234', 'LABEL : label'],\
'SEQ_STRUCT': ['1 U 4', '2 A 10']}
self.assertEqual(MinimalBpseqParser(lines), exp)
def test_BpseqParser(self):
"""BpseqParser: should work on valid data, returning Vienna or Pairs
"""
lines = RES_LINES_W_HEADER.split('\n')
exp_seq = 'UGGUAAUACGUUGCGAAGCC'
exp_pairs = [(2,8),(3,7),(4,11),(5,10),(6,9),(12,18),(13,17)]
self.assertEqual(BpseqParser(lines),(exp_seq, exp_pairs))
self.assertEqual(BpseqParser(lines)[0].Info,\
{'Filename':'d.16.b.E.coli.bpseq',\
'Accession Number': 'J01695', 'Organism': 'Escherichia coli',\
'Refs': {},'Citation':'http://www.rna.icmb.utexas.edu'})
# should work with different base
lines = RES_LINES_DIFF_BASE.split('\n')
exp_seq = 'CAGACU'
exp_pairs = [(1,5),(2,4)]
obs_seq, obs_pairs = BpseqParser(lines, num_base=3,\
unpaired_symbol='xxx')
self.assertEqual(obs_seq, exp_seq)
self.assertEqual(obs_seq.Info, {'Refs':{}})
self.assertEqual(obs_pairs, exp_pairs)
def test_BpseqParser_errors(self):
"""BpseqParser: should skip lines in unknown format"""
exp_seq = 'UGGUAAUACGUUGCGAAGCC'
exp_vienna_m = '....(((..)))((...)).'
exp_pairs = [(2,8),(3,7),(4,11),(5,10),(6,9),(12,18),(13,17)]
#skips lines in unknown format
lines = RES_LINES_UNKNOWN.split('\n')
obs_seq, obs_pairs = BpseqParser(lines)
self.assertEqual(obs_seq, exp_seq)
self.assertEqual(obs_pairs, exp_pairs)
self.assertEqual(obs_seq.Info,\
{'Filename':'d.16.b.E.coli.bpseq',\
'Accession Number': 'J01695', 'Organism': 'Escherichia coli',\
'Refs': {},'Citation':'http://www.rna.icmb.utexas.edu'})
class ConvenienceFunctionTests(TestCase):
"""Tests for convenience functions"""
def test_bpseq_specify_output(self):
"""bpseq_specify_output: different return values"""
f = bpseq_specify_output
lines = RES_LINES_W_HEADER.split('\n')
exp_seq = 'UGGUAAUACGUUGCGAAGCC'
exp_pairs = [(2,8),(3,7),(4,11),(5,10),(6,9),(12,18),(13,17)]
exp_pairs_majority = [(4,11),(5,10),(6,9),(12,18),(13,17)]
exp_pairs_first = [(2,8),(3,7),(12,18),(13,17)]
exp_vienna_majority = '....(((..)))((...)).'
self.assertEqual(f(lines),(exp_seq, exp_pairs))
self.assertEqual(f(lines, remove_pseudo=True),\
(exp_seq, exp_pairs_majority))
self.assertEqual(f(lines, remove_pseudo=True, pseudoknot_function=inc_order),\
(exp_seq, exp_pairs_first))
self.assertEqual(f(lines, return_vienna=True),\
(exp_seq, exp_vienna_majority))
RES_LINES=\
"""1 U 0
2 G 0
3 G 9
4 U 8
5 A 12
6 A 11
7 U 10
8 A 4
9 C 3
10 G 7
11 U 6
12 U 5
13 G 19
14 C 18
15 G 0
16 A 0
17 A 0
18 G 14
19 C 13
20 C 0"""
RES_LINES_NOT_ALL=\
"""1 U 0
2 G 0
3 G 0
6 A 0"""
RES_LINES_WRONG=\
"""1 U0
2 G 0
3 G 0
6 A 0"""
RES_LINES_CONFLICT=\
"""1 U 4
2 G 3
3 G 2
4 A 1
4 A 0"""
RES_LINES_BP_CONFLICT=\
"""1 U 0
2 G 4
3 G 4
4 C 2
5 A 0"""
RES_LINES_DIFF_BASE=\
"""3 C xxx
4 A 8
5 G 7
6 A xxx
7 C 5
8 U 4"""
RES_LINES_W_HEADER=\
"""Filename: d.16.b.E.coli.bpseq
Organism: Escherichia coli
Accession Number: J01695
Citation and related information available at http://www.rna.icmb.utexas.edu
1 U 0
2 G 0
3 G 9
4 U 8
5 A 12
6 A 11
7 U 10
8 A 4
9 C 3
10 G 7
11 U 6
12 U 5
13 G 19
14 C 18
15 G 0
16 A 0
17 A 0
18 G 14
19 C 13
20 C 0"""
RES_LINES_UNKNOWN=\
"""Filename: d.16.b.E.coli.bpseq
Organism: Escherichia coli
Accession Number: J01695
Citation and related information available at http://www.rna.icmb.utexas.edu
1 U 0
2 G 0
3 G 9
UNKNOWN LINE
4 U 8
5 A 12
6 A 11
7 U 10
8 A 4
9 C 3
10 G 7
11 U 6
12 U 5
13 G 19
14 C 18
15 G 0
16 A 0
17 A 0
18 G 14
19 C 13
20 C 0"""
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_cigar.py 000644 000765 000024 00000006075 12024702176 022262 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import unittest, sys, os
from cogent import DNA, LoadSeqs
from cogent.parse.cigar import map_to_cigar, cigar_to_map, aligned_from_cigar, \
slice_cigar, CigarParser
__author__ = "Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Hua Ying", "Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Hua Ying"
__email__ = "hua.ying@anu.edu.au"
__status__ = "Production"
class TestCigar(unittest.TestCase):
def setUp(self):
self.cigar_text = '3D2M3D6MDM2D3MD'
self.aln_seq = DNA.makeSequence('---AA---GCTTAG-A--CCT-')
self.aln_seq1 = DNA.makeSequence('CCAAAAAA---TAGT-GGC--G')
self.map, self.seq = self.aln_seq.parseOutGaps()
self.map1, self.seq1 = self.aln_seq1.parseOutGaps()
self.slices = [(1, 4), (0, 8), (7, 12), (0, 1), (3, 5)]
self.aln = LoadSeqs(data = {"FAKE01": self.aln_seq, "FAKE02": self.aln_seq1})
self.cigars = {"FAKE01": self.cigar_text, "FAKE02": map_to_cigar(self.map1)}
self.seqs = {"FAKE01": str(self.seq), "FAKE02": str(self.seq1)}
def test_map_to_cigar(self):
"""convert a Map to cigar string"""
assert map_to_cigar(self.map) == self.cigar_text
def test_cigar_to_map(self):
"""test generating a Map from cigar"""
map = cigar_to_map(self.cigar_text)
assert str(map) == str(self.map)
def test_aligned_from_cigar(self):
"""test generating aligned seq from cigar"""
aligned_seq = aligned_from_cigar(self.cigar_text, self.seq)
assert aligned_seq == self.aln_seq
def test_slice_cigar(self):
"""test slicing cigars"""
for start, end in self.slices:
# test by_align = True
map1, loc1 = slice_cigar(self.cigar_text, start, end)
ori1 = self.aln_seq[start:end]
if loc1:
slicealn1 = self.seq[loc1[0]:loc1[1]].gappedByMap(map1)
assert ori1 == slicealn1
else:
assert map1.length == len(ori1)
# test by_align = False
map2, loc2 = slice_cigar(self.cigar_text, start, end, by_align = False)
slicealn2 = self.seq[start:end].gappedByMap(map2)
ori2 = self.aln_seq[loc2[0]:loc2[1]]
assert slicealn2 == ori2
def test_CigarParser(self):
"""test without slice"""
aln = CigarParser(self.seqs, self.cigars)
assert aln == self.aln
# test slice
i = 1
for start, end in self.slices:
self.aln.getSeq("FAKE01").addFeature("annot%d"%i, "annot", [(start, end)])
annot = self.aln.getAnnotationsFromAnySequence("annot%d"%i)
slice_aln = aln.getRegionCoveringAll(annot).asOneSpan().getSlice()
i += 1
cmp_aln = CigarParser(self.seqs, self.cigars, sliced = True,
ref_seqname = "FAKE01", start = start, end = end)
assert cmp_aln == slice_aln
if __name__ == '__main__':
unittest.main()
PyCogent-1.5.3/tests/test_parse/test_clustal.py 000644 000765 000024 00000012371 12024702176 022640 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the clustal parsers.
"""
from cogent.parse.clustal import LabelLineParser, is_clustal_seq_line, \
last_space, delete_trailing_number, MinimalClustalParser
from cogent.parse.record import RecordError
from cogent.util.unit_test import TestCase, main
from cogent.core.alignment import Alignment
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Sandra Smit"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
#Note: the data are all strings and hence immutable, so it's OK to define
#them here instead of in setUp and then subclassing everything from that
#base class. If the data were mutable, we'd need to take more precautions
#to avoid crossover between tests.
minimal = 'abc\tucag'
two = 'abc\tuuu\ndef\tccc\n\n ***\n\ndef ggg\nabc\taaa\n'.split('\n')
real = """CLUSTAL W (1.82) multiple sequence alignment
abc GCAUGCAUGCAUGAUCGUACGUCAGCAUGCUAGACUGCAUACGUACGUACGCAUGCAUCA 60
def ------------------------------------------------------------
xyz ------------------------------------------------------------
abc GUCGAUACGUACGUCAGUCAGUACGUCAGCAUGCAUACGUACGUCGUACGUACGU-CGAC 119
def -----------------------------------------CGCGAUGCAUGCAU-CGAU 18
xyz -------------------------------------CAUGCAUCGUACGUACGCAUGAC 23
* * * * * **
abc UGACUAGUCAGCUAGCAUCGAUCAGU 145
def CGAUCAGUCAGUCGAU---------- 34
xyz UGCUGCAUCA---------------- 33
* ***""".split('\n')
bad = ['dshfjsdfhdfsj','hfsdjksdfhjsdf']
space_labels = ['abc uca','def ggg ccc']
class clustalTests(TestCase):
"""Tests of top-level functions."""
def test_is_clustal_seq_line(self):
"""is_clustal_seq_line should reject blanks and 'CLUSTAL'"""
ic = is_clustal_seq_line
assert ic('abc')
assert ic('abc def')
assert not ic('CLUSTAL')
assert not ic('CLUSTAL W fsdhicjkjsdk')
assert not ic(' * *')
assert not ic(' abc def')
assert not ic('MUSCLE (3.41) multiple sequence alignment')
def test_last_space(self):
"""last_space should split on last whitespace"""
self.assertEqual(last_space('a\t\t\t b c'), ['a b', 'c'])
self.assertEqual(last_space('xyz'), ['xyz'])
self.assertEqual(last_space(' a b'), ['a','b'])
def test_delete_trailing_number(self):
"""delete_trailing_number should delete the trailing number if present"""
dtn = delete_trailing_number
self.assertEqual(dtn('abc'), 'abc')
self.assertEqual(dtn('a b c'), 'a b c')
self.assertEqual(dtn('a \t b \t c'), 'a \t b \t c')
self.assertEqual(dtn('a b 3'), 'a b')
self.assertEqual(dtn('a b c \t 345'), 'a b c')
class MinimalClustalParserTests(TestCase):
"""Tests of the MinimalClustalParser class"""
def test_null(self):
"""MinimalClustalParser should return empty dict and list on null input"""
result = MinimalClustalParser([])
self.assertEqual(result, ({},[]))
def test_minimal(self):
"""MinimalClustalParser should handle single-line input correctly"""
result = MinimalClustalParser([minimal]) #expects seq of lines
self.assertEqual(result, ({'abc':['ucag']}, ['abc']))
def test_two(self):
"""MinimalClustalParser should handle two-sequence input correctly"""
result = MinimalClustalParser(two)
self.assertEqual(result, ({'abc':['uuu','aaa'],'def':['ccc','ggg']}, \
['abc', 'def']))
def test_real(self):
"""MinimalClustalParser should handle real Clustal output"""
data, labels = MinimalClustalParser(real)
self.assertEqual(labels, ['abc', 'def', 'xyz'])
self.assertEqual(data, {
'abc':
[ 'GCAUGCAUGCAUGAUCGUACGUCAGCAUGCUAGACUGCAUACGUACGUACGCAUGCAUCA',
'GUCGAUACGUACGUCAGUCAGUACGUCAGCAUGCAUACGUACGUCGUACGUACGU-CGAC',
'UGACUAGUCAGCUAGCAUCGAUCAGU'
],
'def':
[ '------------------------------------------------------------',
'-----------------------------------------CGCGAUGCAUGCAU-CGAU',
'CGAUCAGUCAGUCGAU----------'
],
'xyz':
[ '------------------------------------------------------------',
'-------------------------------------CAUGCAUCGUACGUACGCAUGAC',
'UGCUGCAUCA----------------'
]
})
def test_bad(self):
"""MinimalClustalParser should reject bad data if strict"""
result = MinimalClustalParser(bad, strict=False)
self.assertEqual(result, ({},[]))
#should fail unless we turned strict processing off
self.assertRaises(RecordError, MinimalClustalParser, bad)
def test_space_labels(self):
"""MinimalClustalParser should tolerate spaces in labels"""
result = MinimalClustalParser(space_labels)
self.assertEqual(result, ({'abc':['uca'],'def ggg':['ccc']},\
['abc', 'def ggg']))
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_column.py 000644 000765 000024 00000013751 12024702176 022471 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.foldalign import find_struct
from cogent.parse.pfold import tree_struct_sep
from cogent.parse.column import column_parser
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class ColumnParserTest(TestCase):
"""Provides tests for Column format RNA secondary structure parsers"""
def setUp(self):
"""Setup function"""
#output
self.pfold_out = PFOLD
self.foldalign_out = FOLDALIGN
#expected
self.pfold_exp = [['GCAGAUUUAGAUGC',[(0,13),(1,12),(2,11),(6,10)]]]
self.foldalign_exp = [['GCAGAUUUAGAUGC',[(0,13),(1,12),(2,11),(6,10)]]]
self.find_struct_exp = [[[(0,13),(1,12),(2,11),(6,10)],'GCCACGUAGCUCAG',
'GCCGUAUGUUUCAG']]
def test_pfold_output(self):
"""Test for column_parser for pfold format"""
tree,lines = tree_struct_sep(self.pfold_out)
self.assertEqual(tree,PFOLD_tree)
obs = column_parser(lines)
self.assertEqual(obs,self.pfold_exp)
def test_foldalign_output(self):
"""Test for column_parser for foldalign format"""
obs = column_parser(self.foldalign_out)
self.assertEqual(obs,self.foldalign_exp)
def test_foldalign_find_struct(self):
""" Test for foldalign parser find struct function"""
obs = find_struct(self.foldalign_out)
self.assertEqual(obs,self.find_struct_exp)
FOLDALIGN = ['; FOLDALIGN 2.0.3\n',
'; REFERENCE J.H. Havgaard, R.B. Lyngs\xf8, G.D. Stormo, J. Gorodkin\n',
'; REFERENCE Pairwise local structural alignment of RNA sequences\n',
'; REFERENCE with sequence similarity less than 40%\n',
'; REFERENCE Bioinformatics 21(9), 1815-1824, 2005\n',
'; ALIGNMENT_ID n.a.\n', '; ALIGNING seq1 against seq2\n',
'; ALIGN seq1 \n',
'; ALIGN seq2 \n',
'; ALIGN Score: 929\n',
'; ALIGN Identity: 69 % ( 48 / 70 )\n',
'; ALIGN Begin\n', '; ALIGN\n',
'; ALIGN seq1 GCCACGUAGC UCAG\n',
'; ALIGN Structure (((...(... ))))\n',
'; ALIGN seq2 GCCGUAUGUU UCAG\n',
'; ALIGN \n', '; ALIGN End\n',
'; ==============================================================================\n',
'; TYPE RNA\n', '; COL 1 label\n',
'; COL 2 residue\n', '; COL 3 seqpos\n',
'; COL 4 alignpos\n', '; COL 5 align_bp\n',
'; COL 6 seqpos_bp\n', '; ENTRY seq1\n',
'; ALIGNMENT_ID n.a.\n', '; ALIGNMENT_LIST seq1 seq2\n',
'; FOLDALIGN_SCORE 929\n', '; GROUP 1\n',
'; FILENAME seq1.fasta\n', '; START_POSITION 2\n',
'; END_POSITION 71\n', '; ALIGNMENT_SIZE 2\n',
'; ALIGNMENT_LENGTH 70\n', '; SEQUENCE_LENGTH 76\n',
'; PARAMETER max_length=76\n',
'; PARAMETER max_diff=76\n',
'; PARAMETER min_loop=3\n',
'; PARAMETER score_matrix=\n',
'; PARAMETER nobranching=\n',
'; PARAMETER global=\n',
'; ----------\n',
'N G 1 1 14 0.90\n',
'N C 2 2 13 0.79\n',
'N A 3 3 12 0.87\n',
'N G 4 4 . 0.60\n',
'N A 5 5 . 0.34\n',
'N U 6 6 . 0.34\n',
'N U 7 7 11 0.98\n',
'N U 8 8 . 0.34\n',
'N A 9 9 . 0.56\n',
'N G 10 10 . 0.67\n',
'N A 11 11 7 0.78\n',
'N U 12 12 3 0.87\n',
'N G 13 13 2 0.87\n',
'N C 14 14 1 0.90\n',
'; **********\n']
PFOLD = ['; generated by fasta2col\n',
'; ============================================================\n',
'; TYPE TREE\n', '; COL 1 label\n',
'; COL 2 number\n', '; COL 3 name\n',
'; COL 4 uplen\n', '; COL 5 child\n',
'; COL 6 brother\n', '; ENTRY tree\n',
'; root 1\n', '; ----------\n',
' N 1 seq1 0.001000 . .\n',
'; **********\n', '; TYPE RNA\n', '; COL 1 label\n',
'; COL 2 residue\n', '; COL 3 seqpos\n',
'; COL 4 alignpos\n', '; COL 5 align_bp\n',
'; COL 6 certainty\n', '; ENTRY seq1\n',
'; ----------\n',
'N G 1 1 14 0.90\n',
'N C 2 2 13 0.79\n',
'N A 3 3 12 0.87\n',
'N G 4 4 . 0.60\n',
'N A 5 5 . 0.34\n',
'N U 6 6 . 0.34\n',
'N U 7 7 11 0.98\n',
'N U 8 8 . 0.34\n',
'N A 9 9 . 0.56\n',
'N G 10 10 . 0.67\n',
'N A 11 11 7 0.78\n',
'N U 12 12 3 0.87\n',
'N G 13 13 2 0.87\n',
'N C 14 14 1 0.90\n',
'; **********\n']
PFOLD_tree = ['; generated by fasta2col\n',
'; ============================================================\n',
'; TYPE TREE\n', '; COL 1 label\n',
'; COL 2 number\n', '; COL 3 name\n',
'; COL 4 uplen\n', '; COL 5 child\n',
'; COL 6 brother\n', '; ENTRY tree\n',
'; root 1\n', '; ----------\n',
' N 1 seq1 0.001000 . .\n', '; **********\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_comrna.py 000644 000765 000024 00000015433 12024702176 022452 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.comrna import comRNA_parser,common
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class ComrnaParserTest(TestCase):
"""Provides tests for COMRNA RNA secondary structure format parsers"""
def setUp(self):
"""Setup function """
#output
self.comrna_out = COMRNA
#expected
self.comrna_exp = [['GGCUAGAUAGCUCA',[(0,13),(1,12),(4,9),(5,8)]],
['GGCUAGAUAGCUCA',[(0,13),(1,12),(4,9),(5,8)]],
['GGCUAGAUAGCUCA',[(0,13),(1,12),(4,9),(5,8)]],
['GGCUAGAUAGCUCA',[(0,13),(1,12)]]]
def test_comrna_output(self):
"""Test for comrna format parser"""
obs = comRNA_parser(self.comrna_out)
self.assertEqual(obs,self.comrna_exp)
def test_common_func(self):
"""Test common function in comrna parser """
obs = common(self.comrna_exp)
exp = [['GGCUAGAUAGCUCA',[(0,13),(1,12),(4,9),(5,8)]],
['GGCUAGAUAGCUCA',[(0,13),(1,12)]]]
self.assertEqual(obs,exp)
COMRNA = ['comRNA input.fasta \n', '\n', 'PARAMETERS: \n', 'L = 4, Minimum length of a straight stem;\n', 'E = -5.00, Maximum stem energy allowed for a stem to be analyzed, in kcal/mol;\n', 'S = 0.00, Minimum stem similarity score b/w two stems compared;\n', 'Sh = 0.60, Maximum stem similarity score threshold that will be tested;\n', 'Sl = 0.20, Minimum stem similarity score threshold that will be tested;\n', 'P = 0.50, Minimum percentage of sequences in which a common structure should occur;\n', 'n = 10, Number of common structures to be reported;\n', 'x = 999, Maximum number of pseudoknot crossover pattern allowed between one stem and other stems in a structure;\n', 'a = 1, Use anchor region during stem comparison;\n', 'o = 4, Maximum number of overlapping nucleotides allowed between two stems;\n', 'c = 0.30, Maximum percentage of stem length that is allowed overlapping between two stems;\n', 'j = 0.70, Maximum percentage of stems allowed overlapping between two different cliques;\n', 'r = 0.40, Minimum percentage of stems required to be same for two cliques to be considered same when reporting structures;\n', 'f = 10, Number of flanking nucleotides of a stem to be refolded together during structure refinement;\n', 'v = 5, Maximum length of nucleotides allowed for a new loop to deviate from its length in the original structure pattern;\n', 'g = 0, Use topological sort to assemble stem blocks;\n', '\n', 'Sequence file name: "input.fasta"\n', '\n', 'Sequences loaded ...\n', '1 seq1 72 nt\n', '2 seq2 72 nt\n', '3 seq3 72 nt\n', '4 seq4 72 nt\n', '\n', '\n', 'Number of stems in each energy bin for each sequence:\n', '\n', 'energy[kc/m] -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0\n', 'seq1 2 1 1 6 1 5 9 2 1 3 0 1\n', 'seq2 2 1 1 6 1 5 9 2 1 3 0 1\n', 'seq3 2 1 1 6 1 5 9 2 1 3 0 1\n', 'seq4 2 1 1 6 1 5 9 2 1 3 0 1\n', '\n', '\n', 'Pairwise Sequence Identity (%): \n', '\n', ' 1 2 3 4\n', '\n', ' 1 - 100 100 100\n', ' 2 100 - 100 100\n', ' 3 100 100 - 100\n', ' 4 100 100 100 - \n', '\n', 'Average Pairwise Sequence Identity (%): 100\n', '\n', 'Comparing stems pairwise ... \n', '\n', 'Number of edges that has stem-similarity-score higher than a certain threshold in the stem graph:\n', '\n', 'Score: 0.8 0.78 0.76 0.74 0.72 0.7 0.68 0.66 0.64 0.62 0.6 0.58 0.56 0.54 0.52 0.5 0.48 0.46 0.44 0.42 0.4 0.38 0.36 0.34 0.32 0.3 0.28 0.26 0.24 0.22 0.2\n', 'Num of edges: 12 12 18 18 18 24 24 54 72 78 102 114 114 120 132 132 144 156 168 168 174 180 180 180 180 180 180 180 180 180 180 180\n', '\n', 'Time spent on comparing stems: 0.03 seconds user CPU time; 0.04 seconds real time.\n', '\n', 'Maximum structure finding time: 1 min\n', '\n', '=========================== S = 0.6 ===========================\n', '\n', 'Find conserved stems (cliques) ... ==== 17 cliques ==== 17 unique ====\n', 'Time spent on finding conserved stems: 0 sec CPU time; 0 sec clock time.\n', '\n', 'Construct clique topological graph ... ==== 53 edges ====\n', 'Assemble conserved stems (cliques) ... ==== 44 structures ====\n', 'Time spent on topologically assembling conserved stems: 0 sec CPU time; 0 sec clock time.\n', '\n', 'Report top 10 structures.\n', '-------------------------------------------\n', 'Structure #1: Score = 10.1, pattern: 41, path: 0 1 3 , comseq: 1 2 3 4 , incompatible_seq: 0() 1() 3() \n', '(a) Clique 0: OriginalScore = 3.82, ModifiedScore = 3.82\n', ' 1, seq1 1 GGCUAGA 7 ... 66 UCUGGCC 72 [-13 kc/m]\n', ' 2, seq2 1 GGCUAGA 7 ... 66 UCUGGCC 72 [-13 kc/m]\n', ' 3, seq3 1 GGCUAGA 7 ... 66 UCUGGCC 72 [-13 kc/m]\n', ' 4, seq4 1 GGCUAGA 7 ... 66 UCUGGCC 72 [-13 kc/m]\n', '(b) Clique 1: OriginalScore = 3.45, ModifiedScore = 3.45\n', ' 1, seq1 29 GGAUUGAA 36 ... 54 UUCGAUCC 61 [-11.6 kc/m]\n', ' 2, seq2 29 GGAUUGAA 36 ... 54 UUCGAUCC 61 [-11.6 kc/m]\n', ' 3, seq3 29 GGAUUGAA 36 ... 54 UUCGAUCC 61 [-11.6 kc/m]\n', ' 4, seq4 29 GGAUUGAA 36 ... 54 UUCGAUCC 61 [-11.6 kc/m]\n', '(c) Clique 3: OriginalScore = 2.82, ModifiedScore = 2.82\n', ' 1, seq1 49 GUCGG 53 UUCGAUC 61 CCGGC 65 [-8.4 kc/m]\n', ' 2, seq2 49 GUCGG 53 UUCGAUC 61 CCGGC 65 [-8.4 kc/m]\n', ' 3, seq3 49 GUCGG 53 UUCGAUC 61 CCGGC 65 [-8.4 kc/m]\n', ' 4, seq4 49 GUCGG 53 UUCGAUC 61 CCGGC 65 [-8.4 kc/m]\n', '\n', '\n', 'seq1 1 GGCUAGAUAGCUCA 14 \n', ' aa bb bb aa\n', 'seq2 1 GGCUAGAUAGCUCA 14 \n', ' aa bb bb aa\n', 'seq3 1 GGCUAGAUAGCUCA 14 \n', ' aa bb bb aa\n', 'seq4 1 GGCUAGAUAGCUCA 14 \n', ' aa aa\n', '\n', '\n', '-------------------------------------------']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_consan.py 000644 000765 000024 00000002667 12024702176 022461 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.consan import consan_parser
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class ConsanParserTest(TestCase):
"""Provides tests for CONSAN RNA secondary structure parsers"""
def setUp(self):
"""Setup function"""
#output
self.consan_out = CONSAN
#expected
self.consan_exp = [{'seq1':'GGACACGUCGCUCA','seq2':'G.ACAGAUCGCUCA'},
[(0,13),(2,11),(5,8)]]
def test_consan_output(self):
"""Test for consan format parser"""
obs = consan_parser(self.consan_out)
self.assertEqual(obs,self.consan_exp)
CONSAN = ['Using standard STA scoring\n',
'Using QRADIUS constraints (Quality > 0.9500 SPACED 20) !\n',
'# STOCKHOLM 1.0\n', '\n', '#=GF SC\t 1.000000\n', '#=GF PI\t 0.720000\n',
'#=GF ME\t QRadius Num: 3 Win: 20 Cutoff: 0.95\n',
'\n', 'seq1 \tGGACACGUCGCUCA\n',
'seq2 \tG.ACAGAUCGCUCA\n',
'#=GC SS_cons\t\t >.>..>..<..<.<\n',
'#=GC PN \t\t .......*......\n', '\n', '\n', '\n',
'#=GF TIME 43.0\n', '\n', '//\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_cove.py 000644 000765 000024 00000002641 12024702176 022124 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.cove import coves_parser
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class CovesParserTest(TestCase):
"""Provides tests for Coves RNA secondary structure parsers"""
def setUp(self):
"""Setup function """
#output
self.cove_out = COVE
#expected
self.cove_exp = [['UAGAUGGCUCUCAU',[(0,13),(2,11),(3,10)]]]
def test_cove_output(self):
"""Test coves format parser"""
obs = coves_parser(self.cove_out)
self.assertEqual(obs,self.cove_exp)
COVE = ['coves - scoring and structure prediction of RNA sequences\n', ' using a covariance model\n',
' version 2.4.4, January 1996\n', '\n',
'---------------------------------------------------\n',
'Database to search/score: single.fasta\n',
'Model: single.fasta.cm\n',
'GC% of background model: 50%\n',
'---------------------------------------------------\n', '\n',
'-32.55 bits : seq1\n', ' seq1 UAGAUGGCUCUCAU\n',
' seq1 >.>>......<<.<\n', '\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_ct.py 000644 000765 000024 00000012257 12024702176 021602 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.ct import ct_parser
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class CtParserTest(TestCase):
"""Provides tests for RNA secondary structure parsers"""
def setUp(self):
"""Setup function"""
#output
self.carnac_out = CARNAC
self.dynalign_out = DYNALIGN
self.mfold_out = MFOLD
self.sfold_out = SFOLD
self.unafold_out = UNAFOLD
self.knetfold_out = KNETFOLD
#expected
self.carnac_exp = [['GCAGAUGGCUUC',[(0,11),(2,9),(3,8)]]]
self.dynalign_exp = [['GCAGAUGGCUUC',[(0,11),(2,9),(3,8)],-46.3]]
self.mfold_exp = [['GCAGAUGGCUUC',[(0,11),(2,9),(3,8)],-23.47]]
self.sfold_exp = [['GCAGAUGGCUUC',[(0,11),(2,9),(3,8)],-22.40]]
self.unafold_exp = [['GCAGAUGGCUUC',[(0,11),(2,9),(3,8)],-20.5]]
self.knetfold_exp = [['GCAGAUGGCUUC',[(0,11),(2,9),(3,8)]]]
def test_carnac_output(self):
"""Test for ct_parser for carnac format"""
obs = ct_parser(self.carnac_out)
self.assertEqual(obs,self.carnac_exp)
def test_dynalign_output(self):
"""Test for ct_parser for dynalign format"""
obs = ct_parser(self.dynalign_out)
self.assertEqual(obs,self.dynalign_exp)
def test_mfold_output(self):
"""Test for ct_parser for mfold format"""
obs = ct_parser(self.mfold_out)
self.assertEqual(obs,self.mfold_exp)
def test_sfold_output(self):
"""Test for ct_parser for sfold format"""
obs = ct_parser(self.sfold_out)
self.assertEqual(obs,self.sfold_exp)
def test_unafold_output(self):
"""Test for ct_parser for unafold format"""
obs = ct_parser(self.unafold_out)
self.assertEqual(obs,self.unafold_exp)
def test_knetfold_output(self):
"""Test for ct_parser for knetfold format"""
obs = ct_parser(self.knetfold_out)
self.assertEqual(obs,self.knetfold_exp)
CARNAC = [' 12 seq1\n', ' 1 G 0 2 12 1\n',
' 2 C 1 3 0 2\n', ' 3 A 2 4 10 3\n',
' 4 G 3 5 9 4\n', ' 5 A 4 6 0 5\n',
' 6 U 5 7 0 6\n', ' 7 G 6 8 0 7\n',
' 8 G 7 9 0 8\n', ' 9 C 8 10 4 9\n',
' 10 U 6 11 3 10 \n', ' 11 U 7 12 0 11\n',
' 12 C 8 13 1 12\n']
DYNALIGN = [' 72 ENERGY = -46.3 seq 3\n',
' 1 G 0 2 12 1\n', ' 2 C 1 3 0 2\n',
' 3 A 2 4 10 3\n', ' 4 G 3 5 9 4\n',
' 5 A 4 6 0 5\n', ' 6 U 5 7 0 6\n',
' 7 G 6 8 0 7\n', ' 8 G 7 9 0 8\n',
' 9 C 8 10 4 9\n', ' 10 U 6 11 3 10 \n',
' 11 U 7 12 0 11\n', ' 12 C 8 13 1 12\n']
MFOLD = [' 12 dG = -23.47 [initially -22.40] seq1 \n',
' 1 G 0 2 12 1\n', ' 2 C 1 3 0 2\n',
' 3 A 2 4 10 3\n', ' 4 G 3 5 9 4\n',
' 5 A 4 6 0 5\n', ' 6 U 5 7 0 6\n',
' 7 G 6 8 0 7\n', ' 8 G 7 9 0 8\n',
' 9 C 8 10 4 9\n', ' 10 U 6 11 3 10 \n',
' 11 U 7 12 0 11\n', ' 12 C 8 13 1 12\n']
SFOLD = ['Structure 1 -22.40 0.63786E-01\n',
' 1 G 0 2 12 1\n', ' 2 C 1 3 0 2\n',
' 3 A 2 4 10 3\n', ' 4 G 3 5 9 4\n',
' 5 A 4 6 0 5\n', ' 6 U 5 7 0 6\n',
' 7 G 6 8 0 7\n', ' 8 G 7 9 0 8\n',
' 9 C 8 10 4 9\n', ' 10 U 6 11 3 10 \n',
' 11 U 7 12 0 11\n', ' 12 C 8 13 1 12\n']
UNAFOLD = ['12\tdG = -20.5\tseq1\n', ' 1 G 0 2 12 1\n',
' 2 C 1 3 0 2\n', ' 3 A 2 4 10 3\n',
' 4 G 3 5 9 4\n', ' 5 A 4 6 0 5\n',
' 6 U 5 7 0 6\n', ' 7 G 6 8 0 7\n',
' 8 G 7 9 0 8\n', ' 9 C 8 10 4 9\n',
' 10 U 6 11 3 10 \n', ' 11 U 7 12 0 11\n',
' 12 C 8 13 1 12\n']
KNETFOLD = [' 12 \n', ' 1 G 0 2 12 1\n',
' 2 C 1 3 0 2\n', ' 3 A 2 4 10 3\n',
' 4 G 3 5 9 4\n', ' 5 A 4 6 0 5\n',
' 6 U 5 7 0 6\n', ' 7 G 6 8 0 7\n',
' 8 G 7 9 0 8\n', ' 9 C 8 10 4 9\n',
' 10 U 6 11 3 10 \n', ' 11 U 7 12 0 11\n',
' 12 C 8 13 1 12\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_cut.py 000644 000765 000024 00000002204 12024702176 021756 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.parse.cut import cut_parser
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Development"
class CutParserTest(TestCase):
"""Provides tests for codon usage table parser"""
def test_cut_parser(self):
"""cut_parser should work on first few lines of supplied file"""
lines = """#Species: Saccharomyces cerevisiae
#Division: gbpln
#Release: TranstermMay1994
#CdsCount: 24
#Coding GC 44.99%
#1st letter GC 47.28%
#2nd letter GC 40.83%
#3rd letter GC 46.86%
#Codon AA Fraction Frequency Number
GCA A 0.010 1.040 6
GCC A 0.240 22.420 130
GCG A 0.000 0.000 0
GCT A 0.750 71.610 411
TGC C 0.070 0.520 3
"""
result = cut_parser(lines.splitlines())
self.assertEqual(result, \
{'GCA':6,'GCC':130,'GCG':0,'GCT':411,'TGC':3})
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_cutg.py 000644 000765 000024 00000014671 12024702176 022140 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the CUTG database parsers.
"""
from cogent.parse.cutg import CutgParser, CutgSpeciesParser, InfoFromLabel
from cogent.parse.record import RecordError
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
sample_gene = r""">AB000406\AB000406\100..1506\1407\BAA19100.1\Xenopus laevis\Xenopus laevis mRNA for protein phosphatase 2A regulatory subunit,complete cds./gene="PP2A"/codon_start=1/product="protein phosphatase 2A regulatory subunit"/protein_id="BAA19100.1"/db_xref="GI:1783183"
1 7 4 2 15 6 4 4 11 4 1 7 6 7 4 7 14 7 10 7 4 6 5 2 3 8 3 4 3 6 5 4 6 0 8 5 8 8 20 10 21 13 2 9 5 7 22 16 20 10 10 8 7 3 6 15 12 5 14 11 6 0 1 0
>AB000458#1\AB000458\105..623\519\BAA22881.1\Xenopus laevis\Xenopus laevis Xem1 mRNA for transmembrane protein, complete cds./gene="Xem1"/codon_start=1/product="transmembrane protein"/protein_id="BAA22881.1"/db_xref="GI:2554596"
0 1 1 0 2 1 6 7 10 4 0 1 4 6 1 5 2 1 3 1 1 5 2 5 0 5 2 4 0 2 2 1 1 1 2 5 4 4 2 2 1 3 1 6 4 2 2 5 1 2 3 2 1 2 2 9 3 5 2 6 4 1 0 0
>AB000736\AB000736\27..557\531\BAA19174.1\Xenopus laevis\Xenopus laevis mRNA for myelin basic protein, complete cds./codon_start=1/product="myelin basic protein"/protein_id="BAA19174.1"/db_xref="GI:1816437"
1 1 1 2 5 11 1 0 3 2 0 1 8 4 2 11 3 1 2 1 0 0 5 2 0 5 3 3 0 1 14 3 4 2 1 0 1 4 3 7 3 0 2 3 9 7 1 4 3 3 5 4 0 0 5 2 1 1 0 4 1 0 0 1 """.split('\n')
sample_species = r"""Salmonella enterica: 332
432 1587 640 1808 586 275 758 825 3557 1668 2943 1663 1267 928 1002 1397 1359 1277 1096 1880 1305 1267 911 608 1752 1002 1684 1868 2960 1627 995 2399 1228 2103 1605 1289 2024 2017 4800 1681 1719 3181 1699 2857 700 1723 4347 2560 1577 4174 1031 2938 496 678 1354 3501 1713 1955 3743 2497 1366 214 22 96
Salmonella enterica IIIb 50:k:z: 3
2 5 2 4 3 3 4 6 12 5 7 1 7 5 1 4 7 3 10 13 5 6 9 4 3 5 17 14 14 14 6 18 5 12 15 10 4 11 24 5 16 17 9 19 6 3 11 9 9 18 7 20 2 0 8 17 6 11 16 11 5 2 0 1
Salmonella enterica subsp. VII: 5
4 1 6 7 6 0 8 15 10 9 18 9 15 6 6 19 21 3 21 14 11 22 16 10 11 6 38 13 20 10 8 8 9 9 7 5 7 22 58 21 25 40 24 22 11 16 41 21 6 14 9 11 2 12 10 31 16 23 22 22 3 0 1 4""".split('\n')
strange_db = r'''>AB001737\AB001737\1..696\696\BAA19944.1\Mus musculus\Mus musculus mRNA for anti-CEA scFv antibody, complete cds./codon_start=1/product="anti-CEA scFv antibody"/protein_id="BAA19944.1"/db_xref="GI:2094751"/db_xref="IMGT/LIGM:AB001737"'''
class InfoFromLabelTests(TestCase):
"""Tests of the InfoFromLabel constructor."""
def test_init(self):
"""InfoFromLabel should handle a typical label line"""
i = InfoFromLabel(sample_gene[0])
sa = self.assertEqual
sa(i.GenBank, ['AB000406'])
sa(i.Locus, 'AB000406')
sa(i.CdsNumber, '1'),
sa(i.Location, '100..1506')
sa(i.Length, '1407')
sa(i.Species, 'Xenopus laevis')
sa(i.Description, r'Xenopus laevis mRNA for protein phosphatase 2A regulatory subunit,complete cds./gene="PP2A"/codon_start=1/product="protein phosphatase 2A regulatory subunit"/protein_id="BAA19100.1"/db_xref="GI:1783183"')
sa(i.Gene, 'PP2A')
sa(i.CodonStart, '1')
sa(i.Product, 'protein phosphatase 2A regulatory subunit')
sa(i.GenPept, ['BAA19100.1'])
sa(i.GI, ['1783183'])
j = InfoFromLabel(sample_gene[2])
assert j.Refs is not i.Refs
assert j._handler is not i._handler
assert j._handler is j.Refs
assert j.Refs.GI is not i.Refs.GI
assert j.GI is not i.GI
sa(j.GenBank, ['AB000458']),
sa(j.Locus, 'AB000458')
sa(j.CdsNumber, '1')
sa(j.Location, '105..623')
sa(j.Length, '519'),
sa(j.Species, 'Xenopus laevis')
sa(j.Description, 'Xenopus laevis Xem1 mRNA for transmembrane protein, complete cds./gene="Xem1"/codon_start=1/product="transmembrane protein"/protein_id="BAA22881.1"/db_xref="GI:2554596"')
sa(j.GenPept, ['BAA22881.1']),
sa(j.GI, ['2554596'])
sa(j.Product, 'transmembrane protein')
def test_init_unknown_db(self):
"""InfoFromLabel should handle a line whose database is unknown"""
i = InfoFromLabel(strange_db)
self.assertEqual(i.Locus, 'AB001737')
class CutgSpeciesParserTests(TestCase):
"""Tests of the CutgSpeciesParser."""
def test_init(self):
"""CutgSpeciesParser should read records one at a time from lines"""
recs = list(CutgSpeciesParser(sample_species))
self.assertEqual(len(recs), 3)
a, b, c = recs
self.assertEqual(a.Species, 'Salmonella enterica')
self.assertEqual(a.NumGenes, 332)
self.assertEqual(a['CGA'], 432)
self.assertEqual(a['UGG'], 1366)
self.assertEqual(b.Species, 'Salmonella enterica IIIb 50:k:z')
self.assertEqual(b.NumGenes, 3)
self.assertEqual(b['CGA'], 2)
self.assertEqual(b['UGG'], 5)
self.assertEqual(c.Species, 'Salmonella enterica subsp. VII')
self.assertEqual(c.NumGenes, 5)
self.assertEqual(c['CGA'], 4)
self.assertEqual(c['UGG'], 3)
#check that it won't work if we're missing any lines
self.assertRaises(RecordError, list,
CutgSpeciesParser(sample_species[1:]))
self.assertRaises(RecordError, list,
CutgSpeciesParser(sample_species[:-1]))
#...but that it does work if we only have some of them
recs = list(CutgSpeciesParser(sample_species[2:]))
self.assertEqual(recs[0], b)
self.assertEqual(len(list(CutgSpeciesParser(sample_species[1:],
strict=False))), 2)
class CutgParserTests(TestCase):
"""Tests of the CutgParser.
Note: these are fairly incomplete at present since most of the work is in
parsing the label line, which is tested by itself.
"""
def test_init(self):
"""CutgParser should read records one at a time from lines"""
recs = list(CutgParser(sample_gene))
self.assertEqual(len(recs), 3)
a, b, c = recs
self.assertEqual(a.Species, 'Xenopus laevis')
self.assertEqual(a['CGC'], 7)
self.assertEqual(a.GI, ['1783183'])
self.assertRaises(RecordError, list, CutgParser(sample_gene[1:]))
self.assertEqual(len(list(CutgParser(sample_gene[1:],strict=False))), 2)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_dialign.py 000644 000765 000024 00000010414 12024702176 022574 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import unittest
from cogent import PROTEIN, LoadSeqs
from cogent.parse.dialign import align_block_lines, parse_data_line, DialignParser
__author__ = "Gavin Huttley"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
data = \
"""
DIALIGN 2.2.1
*************
Program code written by Burkhard Morgenstern and Said Abdeddaim
e-mail contact: dialign (at) gobics (dot) de
Published research assisted by DIALIGN 2 should cite:
Burkhard Morgenstern (1999).
DIALIGN 2: improvement of the segment-to-segment
approach to multiple sequence alignment.
Bioinformatics 15, 211 - 218.
For more information, please visit the DIALIGN home page at
http://bibiserv.techfak.uni-bielefeld.de/dialign/
************************************************************
program call: dialign -fa -fn /tmp/ct/seq1.fasta /tmp/ct/seq1.txt
Aligned sequences: length:
================== =======
1) HTL2 57
2) MMLV 58
3) HEPB 62
4) ECOL 54
Average seq. length: 57.8
Please note that only upper-case letters are considered to be aligned.
Alignment (DIALIGN format):
===========================
HTL2 1 ldtapC-LFS DGS------P QKAAYVL--- ----WDQTIL QQDITPLPSH
MMLV 1 pdadhtw-YT DGSSLLQEGQ RKAGAAVtte teviWa---- KALDAG---T
HEPB 1 rpgl-CQVFA DAT------P TGWGLVM--- ----GHQRMR GTFSAPLPIH
ECOL 1 mlkqv-EIFT DGSCLGNPGP GGYGAIL--- ----RYRGRE KTFSAGytrT
0000000588 8882222229 9999999000 0000666666 6666633334
HTL2 37 ethSAQKGEL LALICGLRAa k--------- ---
MMLV 43 ---SAQRAEL IALTQALKm- ---------- ---
HEPB 37 t------AEL LAA-CFARSr sganiigtdn svv
ECOL 43 ---TNNRMEL MAAIv----- ---------- ---
0003333455 5533333300 0000000000 000
Sequence tree:
==============
Tree constructed using UPGMAbased on DIALIGN fragment weight scores
((HTL2 :0.130254MMLV :0.130254):0.067788(HEPB :0.120520ECOL :0.120520):0.077521);
""".splitlines()
class TestDialign(unittest.TestCase):
def setUp(self):
aln_seqs = {"HTL2": "ldtapC-LFSDGS------PQKAAYVL-------WDQTILQQDITPLPSHethSAQKGELLALICGLRAak------------",
"MMLV": "pdadhtw-YTDGSSLLQEGQRKAGAAVtteteviWa----KALDAG---T---SAQRAELIALTQALKm--------------",
"HEPB": "rpgl-CQVFADAT------PTGWGLVM-------GHQRMRGTFSAPLPIHt------AELLAA-CFARSrsganiigtdnsvv",
"ECOL": "mlkqv-EIFTDGSCLGNPGPGGYGAIL-------RYRGREKTFSAGytrT---TNNRMELMAAIv------------------"}
self.aln_seqs = {}
for name, seq in aln_seqs.items():
self.aln_seqs[name] = PROTEIN.Sequence(seq,Name=name)
self.QualityScores = "00000005888882222229999999900000006666666666633334000333345555333333000000000000000"
def test_line_split(self):
"""test splitting of sequence record lines"""
result = parse_data_line("HTL2 1 ldtapcLFSD GS------PQ KAAYVLWDQT ILQQDITPLP SHethsaqkg ")
self.assertEqual(result, ("HTL2", "ldtapcLFSDGS------PQKAAYVLWDQTILQQDITPLPSHethsaqkg"))
result = parse_data_line(" 1111111111 1000001111 1111033333 3333333333 3000000000 ")
self.assertEqual(result, (None, "11111111111000001111111103333333333333333000000000"))
def test_aligned_from_dialign(self):
"""test getting aligned seqs"""
aligned_seq = dict(list(DialignParser(data, seq_maker=PROTEIN.Sequence)))
assert aligned_seq == self.aln_seqs
def test_quality_scores(self):
"""test quality scores correctly returned"""
result = dict(list(DialignParser(data, seq_maker=PROTEIN.Sequence,
get_scores=True)))
assert result["QualityScores"] == self.QualityScores
if __name__ == '__main__':
unittest.main()
PyCogent-1.5.3/tests/test_parse/test_dotur.py 000644 000765 000024 00000004076 12024702176 022331 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# test_dotur.py
from cogent.util.unit_test import TestCase, main
from cogent.parse.dotur import get_otu_lists, OtuListParser
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Development"
class DoturParserTests(TestCase):
"""Tests for DoturParser.
"""
def setUp(self):
"""setup for DoturParserTests.
"""
self.otu_list_string = \
"""unique 3 a b c
0.00 3 a b c
0.59 2 a,c b
0.78 1 a,c,b
"""
self.otu_res_list = [
[0.0,3,[['a'],['b'],['c']]],\
[0.0,3,[['a'],['b'],['c']]],\
[float(0.59),2,[['a','c'],['b']]],\
[float(0.78),1,[['a','c','b']]],\
]
self.otu_lists_unparsed=[\
['a','b','c'],
['a','b','c'],
['a,c','b'],
['a,c,b']
]
self.otu_lists_parsed=[\
[['a'],['b'],['c']],
[['a'],['b'],['c']],
[['a','c'],['b']],
[['a','c','b']]
]
def test_get_otu_lists_no_data(self):
"""get_otu_lists should function as expected.
"""
self.assertEqual(get_otu_lists([]),[])
def test_get_otu_lists(self):
"""get_otu_lists should function as expected.
"""
for obs, exp in zip(self.otu_lists_unparsed,self.otu_lists_parsed):
self.assertEqual(get_otu_lists(obs),exp)
def test_otulistparser_no_data(self):
"""OtuListParser should return correct result given no data.
"""
res = OtuListParser([])
self.assertEqual(list(res),[])
def test_otulistparser_parser(self):
"""OtuListParser should return correct result given basic output.
"""
res = OtuListParser(self.otu_list_string.split('\n'))
self.assertEqual(res,self.otu_res_list)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_ebi.py 000644 000765 000024 00000104537 12024702176 021736 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
""" Provides tests for EbiParser and related classes and functions.
"""
from cogent.parse.ebi import cc_alternative_products_parser, \
cc_basic_itemparser, cc_biophysicochemical_properties_parser, \
cc_interaction_parser, cc_itemfinder, cc_parser, EbiFinder, \
MinimalEbiParser, hanging_paragraph_finder, join_parser, \
join_split_dict_parser, join_split_parser, labeloff, linecode_maker, \
linecode_merging_maker, mapping_parser, pairs_to_dict, period_tail_finder, \
rstrip_, ft_basic_itemparser, ft_id_parser, ft_mutagen_parser, \
ft_mutation_parser, ft_parser, try_int, ra_parser, rc_parser, \
rg_parser, rl_parser, rn_parser, rp_parser, rt_parser, rx_parser, \
gn_parser, single_ref_parser, ac_parser, de_itemparser, dr_parser, \
dt_parser, id_parser, oc_parser, og_parser, os_parser, ox_parser, \
sq_parser, de_parser, RecordError, FieldError, curry, required_labels, \
EbiParser
from cogent.util.unit_test import TestCase, main
from cogent.core.sequence import Sequence
from cogent.core.info import Info
__author__ = "Zongzhi Liu"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Zongzhi Liu", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Zongzhi Liu"
__email__ = "zongzhi.liu@gmail.com"
__status__ = "Development"
def item_empty_filter(d):
"""return a dict with only nonempty values"""
pairs = [(k,v) for (k,v) in d.iteritems() if v]
return dict(pairs)
class EbiTests(TestCase):
""" Tests ebi parsers and generic parsers and general functions """
def setUp(self):
""" Construct some fake data for testing purposes """
pass
def test_item_empty_filter(self):
"""item_empty_filter: known values"""
inputs = [
{1:0, 2:1, 3:'', 4:[], 5:False, 6:{}}]
expects = [
{2:1}]
self.assertEqual(map(item_empty_filter, inputs), expects)
def test_rstrip_(self):
"""rstrip_ should generate the expected function"""
test = ' aaa; '
self.assertEqual(rstrip_('; ')(test),
test.rstrip('; '))
#test default
self.assertEqual(rstrip_()(test),
test.rstrip())
def test_hanging_paragraph_finder(self):
"""hanging_paragraph_finder should give expected results"""
f = hanging_paragraph_finder
test = [
'-aaa:',
' content',
' content',
'-bbb:', #3
' bbb',
'c',]
self.assertEqual(list(f(test)),
[test[0:3], test[3:-1], test[-1:]])
#test all indent lines
all_indent = [' aa', ' bb']
self.assertEqual(list(f(all_indent)), [all_indent])
#test empty lines
self.assertEqual(list(f(['',' '])), [])
def test_period_tail_finder(self):
"""period_tail_finder should yield each group of expected lines."""
test = "a\naa.\nb\nbb.".splitlines()
self.assertEqual(list(period_tail_finder(test)),
[['a','aa.'],['b','bb.']])
def test_EbiFinder(self):
"""EbiFinder should return expected list"""
test = "a\n//\nb\n//".splitlines()
self.assertEqual(list(EbiFinder(test)),
[['a','//'],['b','//']])
test_fail = test + ['c']
self.assertRaises(RecordError,
list, EbiFinder(test_fail))
def test_pairs_to_dict(self):
"""pairs_to_dict should return the expected dict"""
test_dict = {'a': 1, 'b': 2, 'b': 3,}
sorted_items = [('a', 1), ('b', 2), ('b', 3),]
add_one = lambda x: x + 1
double = lambda x: x*2
set_zero = lambda x: 0
handlers ={ 'a': add_one, 'b': double,}
#test default all
self.assertEqual(pairs_to_dict(sorted_items),
{'a': 1, 'b': 3})
#test 'overwrite_value'
self.assertEqual(pairs_to_dict(sorted_items, 'overwrite_value'),
{'a': 1, 'b': 3})
#test no_duplicated_key, raise
self.assertRaises(ValueError, pairs_to_dict,
sorted_items, 'no_duplicated_key')
#test always_multi_value
self.assertEqual(pairs_to_dict(sorted_items, 'always_multi_value'),
{'a': [1], 'b': [2, 3]})
#test allow multi_value
self.assertEqual(pairs_to_dict(sorted_items, 'allow_multi_value'),
{'a': 1, 'b': [2, 3]})
#test raise error when key not found in all_keys
f = curry(pairs_to_dict, all_keys=['a','c'])
self.assertRaises(ValueError, f, sorted_items)
#test handlers
sorted_items.append(('c', 4))
self.assertEqual(pairs_to_dict(sorted_items, handlers=handlers,
default_handler=set_zero), {'a': 2, 'b': 6, 'c': 0})
#test raise error when no valid handlers were found
f = curry(pairs_to_dict, handlers=handlers)
self.assertRaises(ValueError, f, sorted_items)
#test sanity
test_dict = dict(sorted_items)
self.assertEqual(pairs_to_dict(test_dict.items()),
test_dict)
def test_linecode_maker(self):
"""linecode_maker: should return expected tuple"""
tests = ['AA aa.',
'BB bb.',
'CC C cc.',
'DD dd.']
expected_linecodes =[
'AA', 'BB', 'CC C', 'DD dd.']
#pprint(map(linecode_maker, tests))
self.assertEqual(map(linecode_maker, tests),
zip(expected_linecodes, tests))
def test_labeloff(self):
"""labeloff: should return expected lines"""
tests = ['AA aa.',
'BB bb.',
'CC C cc.',
'DD dd.',
'EE',
'']
#expects = [line[5:] for line in tests]
expects = ['aa.', ' bb.', ' cc.', '.','','']
self.assertEqual(labeloff(tests), expects)
def test_join_parser(self):
"""join parser should return expected str."""
test_list = '"aaa\nbbb \nccc"; \n'.splitlines()
test_str = 'aaa bb. '
#test default, list input
self.assertEqual(join_parser(test_list),
'"aaa bbb ccc"')
#test default, str input
self.assertEqual(join_parser(test_str),
'aaa bb')
#test no strip
self.assertEqual(join_parser(test_list, chars_to_strip=''),
'"aaa bbb ccc"; ')
#test strip
self.assertEqual(join_parser(test_list, chars_to_strip='"; '),
'aaa bbb ccc')
#test empty
self.assertEqual(join_parser([]),'')
self.assertEqual(join_parser(['', ' ']),'')
self.assertEqual(join_parser(''),'')
def test_join_split_parser(self):
"""join_split_parser: should return expected"""
f = join_split_parser
assertEqual = self.assertEqual
assertEqual(f(['aa; bb;', 'cc.']),
['aa', 'bb', 'cc'])
assertEqual(f(['aa; bb, bbb;', 'cc.'],delimiters=';,'),
['aa', ['bb','bbb'], 'cc'])
#test item_modifer
assertEqual(f('aa (bb) (cc).', '(', item_modifier=rstrip_(') ')),
['aa','bb','cc'])
assertEqual(f('aa (bb)xx (cc).', '(', item_modifier=rstrip_(') ')),
['aa','bb)xx','cc'])
#test empty
assertEqual(f([]),[''])
assertEqual(f(['', ' ']),[''])
assertEqual(f(''),[''])
def test_join_split_dict_parser(self):
"""join_split_dict_parser: should return expected"""
f = join_split_dict_parser
#test default
self.assertEqual(f('aa=1; bb=2,3; cc=4 (if aa=1);'),
{'aa':'1', 'bb': ['2','3'], 'cc': '4 (if aa=1)'})
self.assertEqual(f('aa=1; bb=2,3; cc=4:5', delimiters=';=,:'),
{'aa':'1', 'bb': ['2','3'], 'cc': '4:5'})
#test strict=False -> splits without dict()
self.assertEqual(f('aa=1; bb.', strict=False), [['aa', '1'], ['bb']])
#test strict -> raise ValueError
self.assertRaises(ValueError, f, 'aa=1; bb.')
self.assertRaises(ValueError, f, 'aa=1; bb=2=3.', ';=')
self.assertRaises(ValueError, f, '')
def test_mapping_parser(self):
"""mapping_parser: should return expected dict"""
fields = [None, 'A', 'B', ('C', int), ('D', float)]
line = 'blah aa bb; 2 3.1;'
expect = dict(A='aa', B='bb', C=2, D=3.1)
self.assertEqual(mapping_parser(line, fields), expect)
#test more splits -> ignore the last splits
line_leftover = line + 'blah blah'
self.assertEqual(mapping_parser(line_leftover, fields), expect)
#test more fields -> truncate the last fields
fields_leftover = fields + ['E']
self.assertEqual(mapping_parser(line, fields_leftover), expect)
#test empty
self.assertEqual(mapping_parser('', fields), {})
def test_linecode_merging_maker(self):
"""linecode_merging_maker: """
f = linecode_merging_maker
lines =['ID id.', 'RN rn.', 'RR invalid', 'RN rn.']
labels = ['ID', 'REF', 'RR', 'RN rn.']
self.assertEqual(map(f, lines), zip(labels, lines))
def test_parse_header(lines):
pass
def test_MinimalEbiParser_valid(self):
"""MinimalEbiParser: integrity of output """
f = curry(MinimalEbiParser, strict=False)
#test valid result: sequence, number of records, keys of a header
valid_result = list(f(fake_records_valid))
self.assertEqual(len(valid_result), 2)
sequence, header = valid_result[0]
self.assertEqual(sequence, 'aaccppgghhh')
#the first fake record use only the required labels, the header is
#deleted of '', which was assigned to sequence
self.assertEqual(list(sorted(header.keys())),
list(sorted(required_labels))[1:]) #[1:] to exclude the ''
#test selected_labels
selected_labels = ['ID', 'DE']
select_result = list(f(fake_records_valid,
selected_labels=selected_labels))
self.assertEqual(list(sorted(select_result[0][1].keys())),
list(sorted(selected_labels)))
#test bad record - unknown linecode or wrong line format
self.assertRaises(ValueError, list,
f(fake_records_valid + ['ID id.', 'RR not valid.','//']))
self.assertRaises(ValueError, list,
f(fake_records_valid + ['ID id.', ' RN bad format.','//']))
self.assertRaises(ValueError, list,
f(fake_records_valid + ['ID id.', 'RN bad format.','//']))
#test bad record - not end with '//'
self.assertRaises(RecordError, list, f(fake_records_valid +
['ID not end with //', ' seq']))
#test strict: lacking required linecodes
#?? How to test the error message? warn message?
#the first record, [:-5], is valid even when strict=True.
the_first_valid = list(f(fake_records_valid[:-5], strict=True))[0]
#[1] get the header_dict
self.assertEqual(len(the_first_valid[1]),9)
self.assertRaises(RecordError, list,
f(fake_records_valid, strict=True))
def test_EbiParser(self):
"""EbiParser: """
f = curry(EbiParser, strict=False)
first_valid = fake_records_valid[:-5]
#test valid
self.assertEqual(len(list(f(fake_records_valid))), 2)
#test skipping bad record which strict=False
#self.assertEqual(len(list(f(fake_records_valid[:-1] +
# ['OX xx=no equal.', '//']))), 1)
##test Raise RecordError from parse_head when strict=True
#self.assertRaises(RecordError, list, f(first_valid[:-1] +
# ['OX xx=no equal.', '//'], strict=True))
class RootParsersKnownValues(TestCase):
"""Test most xx_parsers with known value"""
def test_id_parser(self):
"""id_parser should return expected dict"""
id_line = [
'ID CYC_BOVIN STANDARD; PRT; 104 AA.']
self.assertEqual( id_parser(id_line),
{'DataClass': 'STANDARD', 'Length': 104, 'MolType': 'PRT',
'EntryName': 'CYC_BOVIN'})
def test_sq_parser(self):
"""sq_parser should return expected dict"""
lines = [
"SQ SEQUENCE 486 AA; 55639 MW; D7862E867AD74383 CRC64;"]
self.assertEqual( sq_parser(lines),
{'Crc64': 'D7862E867AD74383', 'Length': 486,
'MolWeight': 55639})
def test_ac_parser(self):
"""ac_parser should return expected list"""
lines = [
"AC Q16653; O00713; O00714;",
"AC Q92892; Q92893;"]
self.assertEqual( ac_parser(lines),
['Q16653', 'O00713', 'O00714', 'Q92892', 'Q92893'])
def test_oc_parser(self):
"""oc_parser should return expected list"""
lines = [
"OC Eukaryota; Metazoa; Chordata;",
"OC Mammalia;"]
self.assertEqual(oc_parser(lines),
['Eukaryota', 'Metazoa', 'Chordata', 'Mammalia'])
def test_dt_parser(self):
"""dt_parser should return expected list of list"""
lines = \
"DT 01-AUG-1988 (Rel. 08, Created)\n"\
"DT 30-MAY-2000 (Rel. 39, Last sequence update)\n"\
"DT 10-MAY-2005 (Rel. 47, Last annotation update)\n".splitlines()
self.assertEqual( dt_parser(lines),
['01-AUG-1988 (Rel. 08, Created)',
'30-MAY-2000 (Rel. 39, Last sequence update)',
'10-MAY-2005 (Rel. 47, Last annotation update)'])
def test_de_itemparser(self):
"""de_itemparser: known values"""
inputs = [
' AAA (aa) ',
'AAA [xx] (aa)',
'AAA',
'',]
expects = [
{'OfficalName': 'AAA', 'Synonyms': ['aa']},
{'OfficalName': 'AAA [xx]', 'Synonyms': ['aa']},
{'OfficalName': 'AAA', 'Synonyms': []},
{'OfficalName': '', 'Synonyms': []}]
#pprint(map(de_itemparser, inputs))
self.assertEqual(map(de_itemparser, inputs), expects)
def test_de_parser(self):
"""de_parser should return expected list"""
inputs = [
"DE Annexin [Includes: CCC] [Contains: AAA] (Fragment).",
"DE A [Includes: II] (Fragment).",
"DE A [Contains: CC].",
"DE A (Fragment).",
"DE A (aa)."]
filtered_dicts = [item_empty_filter(de_parser([e])) for e in inputs]
self.assertEqual(map(len, filtered_dicts), [4, 3, 2, 2, 2])
def test_os_parser(self):
"""os_parser should return expected list"""
lines = [
'OS Solanum melongena (Eggplant) (Auber-',
'OS gine).']
self.assertEqual(os_parser(lines),
['Solanum melongena', 'Eggplant', 'Auber- gine'])
lines = \
"""OS Escherichia coli.""".splitlines()
self.assertEqual(os_parser(lines),
['Escherichia coli'])
def test_og_parser(self):
"""og_parser should return expected list"""
lines = [
"OG XXX; xx.",
"OG Plasmid R6-5, Plasmid IncFII R100 (NR1), and",
"OG Plasmid IncFII R1-19 (R1 drd-19)."]
self.assertEqual(og_parser(lines),
['XXX; xx', [
'Plasmid R6-5', 'Plasmid IncFII R100 (NR1)',
'Plasmid IncFII R1-19 (R1 drd-19)']])
def test_ox_parser(self):
"""ox_parser should return expected dict"""
lines = ["OX NCBI_TaxID=9606;"]
self.assertEqual(ox_parser(lines),
{'NCBI_TaxID': '9606'})
def test_gn_parser(self):
"""gn_parser should return expected list of dict"""
lines = [
"GN Name=hns; Synonyms=bglY, cur, topS;",
"GN OrderedLocusNames=b1237, c1701, ECs1739;"]
self.assertEqual(gn_parser(lines),
[{'Synonyms': ['bglY', 'cur', 'topS'],
'OrderedLocusNames': ['b1237', 'c1701', 'ECs1739'],
'Name': 'hns'}])
lines = [
"GN Name=Jon99Cii; Synonyms=SER1, Ser99Da; ORFNames=CG7877;",
"GN and",
"GN Name=Jon99Ciii; Synonyms=SER2, Ser99Db; ORFNames=CG15519;"]
self.assertEqual(gn_parser(lines),
[{'ORFNames': 'CG7877', 'Synonyms': ['SER1', 'Ser99Da'],
'Name': 'Jon99Cii'},
{'ORFNames': 'CG15519', 'Synonyms': ['SER2', 'Ser99Db'],
'Name': 'Jon99Ciii'}])
def test_dr_parser(self):
"""dr_parser should return expected dict"""
lines = dr_lines
self.assertEqual(dr_parser(lines), dr_expect)
class FT_Tests(TestCase):
"""Tests for FT parsers. """
def test_ft_basic_itemparser(self):
"""ft_basic_itemparser: known values"""
inputs = [
['DNA_BIND >102 292'],
['CONFLICT 327 327 E -> R (in Ref. 2).'],
['PROPEP ?25 48',
' /FTId=PRO_021449.',],
['VARIANT 214 214 V -> I.',
' /FTId=VAR_009122.',],]
expects = [
('DNA_BIND', '>102', 292, ''),
('CONFLICT', 327, 327, 'E -> R (in Ref. 2)'),
('PROPEP', '?25', 48, '/FTId=PRO_021449'),
('VARIANT', 214, 214, 'V -> I. /FTId=VAR_009122')]
#pprint(map(ft_basic_itemparser, inputs))
self.assertEqual(map(ft_basic_itemparser, inputs), expects)
def test_try_int(self):
"""try_int: known values"""
inputs = ['9', '0', '-3', '2.3', '<9', '>9', '?', '?35', '']
expects = [9, 0, -3, '2.3', '<9', '>9', '?', '?35', '']
self.assertEqual(map(try_int, inputs), expects)
def test_ft_id_parser(self):
"""ft_id_parser: known values"""
inputs = [
'',
'ddd',
'/FTId=PRO_021449',
'V -> I. /FTId=VAR_009122',
'E -> R (tumor). /FTId=VAR_002343',]
expects = [
{'Description': '', 'Id': ''},
{'Description': 'ddd', 'Id': ''},
{'Description': '', 'Id': 'PRO_021449'},
{'Description': 'V -> I', 'Id': 'VAR_009122'},
{'Description': 'E -> R (tumor)', 'Id': 'VAR_002343'}]
#pprint(map(ft_id_parser, inputs))
self.assertEqual(map(ft_id_parser, inputs), expects)
def test_ft_mutation_parser(self):
"""ft_mutation_parser: known values"""
inputs = [
'',
'ddd', #should raise error?
'V -> I. /FTId=xxxxxx', #should raise error?
'V -> I',
'E -> R (tumor)',
'missing (tumor)', ]
expects = [
{'MutateFrom': '', 'Comment': '', 'MutateTo': ''},
{'MutateFrom': 'ddd', 'Comment': '', 'MutateTo': ''},
{'MutateFrom': 'V', 'Comment': '', 'MutateTo': 'I. /FTId=xxxxxx'},
{'MutateFrom': 'V', 'Comment': '', 'MutateTo': 'I'},
{'MutateFrom': 'E', 'Comment': 'tumor', 'MutateTo': 'R'},
{'MutateFrom': 'missing ', 'Comment': 'tumor', 'MutateTo': ''}]
#pprint(map(ft_mutation_parser, inputs))
self.assertEqual(map(ft_mutation_parser, inputs), expects)
def test_ft_mutation_parser_raise(self):
"""ft_mutation_parser: raise ValueError"""
pass
def test_ft_mutagen_parser(self):
"""ft_mutagen_parser: known values"""
inputs = [
'C->R,E,A: Loss of cADPr hydrolas',
'Missing: Abolishes ATP-binding', ]
expects = [
{'Comment': ' Loss of cADPr hydrolas',
'MutateFrom': 'C', 'MutateTo': 'R,E,A'},
{'Comment': ' Abolishes ATP-binding',
'MutateFrom': 'Missing', 'MutateTo': ''}]
#pprint(map(ft_mutagen_parser, inputs))
self.assertEqual(map(ft_mutagen_parser, inputs), expects)
def test_ft_id_mutation_parser(self):
"""ft_id_mutation_parser: known values"""
pass
def test_ft_parser(self):
"""ft_parser should return expected dict"""
lines = ft_lines
#pprint(ft_parser(lines))
self.assertEqual(ft_parser(lines), ft_expect)
class CC_Tests(TestCase):
"""tests for cc_parsers. """
def test_cc_itemfinder_valid(self):
"""cc_itemfinder: yield each expected block."""
#pprint(list(cc_itemfinder(labeloff(cc_lines))))
input_with_license = labeloff(cc_lines)
self.assertEqual(len(list(cc_itemfinder(
input_with_license))), 9)
input_without_license = labeloff(cc_lines[:-4])
self.assertEqual(len(list(cc_itemfinder(
input_without_license))), 8)
def test_cc_itemfinder_raise(self):
"""cc_itemfinder: raise RecordError if license block bad."""
input_with_license_lacking_bottom = labeloff(cc_lines[:-1])
self.assertRaises(FieldError, cc_itemfinder,
input_with_license_lacking_bottom)
def test_cc_basic_itemparser(self):
"""cc_basic_itemparser: known results or FieldError"""
valid_topics = [
['-!- topic1: first: line', ' second line'],
['-!- topic2: ', ' first line', ' second line'],
[' topic3: not treated invalid topic format'],]
expects = [
('topic1', ['first: line', 'second line']),
('topic2', ['first line', 'econd line']),
('topic3', ['not treated invalid topic format']),]
self.assertEqual(map(cc_basic_itemparser, valid_topics),
expects)
bad_topic = ['-!- bad_topic without colon', ' FieldError']
self.assertRaises(FieldError, cc_basic_itemparser, bad_topic)
def test_cc_interaction_parser(self):
"""cc_interaction_parser: known values"""
inputs = [
['Self; NbExp=1; IntAct=EBI-123485, EBI-123485;',
'Q9W158:CG4612; NbExp=1; IntAct=EBI-123485, EBI-89895;',
'Q9VYI0:fne; NbExp=1; IntAct=EBI-123485, EBI-126770;',]]
expects =[
[('Self', {'NbExp': '1',
'IntAct': ['EBI-123485', 'EBI-123485']}),
('Q9W158:CG4612', {'NbExp': '1',
'IntAct': ['EBI-123485', 'EBI-89895']}),
('Q9VYI0:fne', {'NbExp': '1',
'IntAct': ['EBI-123485', 'EBI-126770']})]]
self.assertEqual(map(cc_interaction_parser, inputs), expects)
def test_cc_biophysicochemical_properties_parser(self):
"""cc_biophysicochemical_properties_parser: known values"""
#pprint(cc['BIOPHYSICOCHEMICAL PROPERTIES']) #topic specific parser
f = cc_biophysicochemical_properties_parser
valid_inputs = [
['Kinetic parameters:',
' KM=98 uM for ATP;',
' KM=688 uM for pyridoxal;',
' Vmax=1.604 mmol/min/mg enzyme;',
'pH dependence:',
' Optimum pH is 6.0. Active pH 4.5 to 10.5;',]
]
expects = [
{'Kinetic parameters': {
'KM': ['98 uM for ATP', '688 uM for pyridoxal'],
'Vmax': '1.604 mmol/min/mg enzyme'},
'pH dependence': 'Optimum pH is 6.0. Active pH 4.5 to 10.5'},
]
self.assertEqual(map(f, valid_inputs), expects)
def test_cc_alternative_products_parser(self):
"""cc_alternative_products_parser: know values"""
f = cc_alternative_products_parser
valid_inputs = [
['Event=Alternative initiation;'
' Comment=Free text;',
'Event=Alternative splicing; Named isoforms=3;',
' Comment=Additional isoforms seem to exist.',
' confirmation;',
'Name=1; Synonyms=AIRE-1;',
' IsoId=O43918-1; Sequence=Displayed;',
'Name=3; Synonyms=AIRE-3,',
'ai-2, ai-3;', #broken the hanging_paragraph_finder
' IsoId=O43918-3; Sequence=VSP_004089, VSP_004090;',]]
expects = \
[[{'Comment': 'Free text', 'Event': 'Alternative initiation'},
{'Comment': 'Additional isoforms seem to exist. confirmation',
'Event': 'Alternative splicing',
'Named isoforms': '3',
'Names': [{'IsoId': 'O43918-1',
'Name': '1',
'Sequence': 'Displayed',
'Synonyms': 'AIRE-1'},
{'IsoId': 'O43918-3',
'Name': '3',
'Sequence': ['VSP_004089', 'VSP_004090'],
'Synonyms': ['AIRE-3', 'ai-2', 'ai-3']}]}]]
#pprint(map(f,valid_inputs))
self.assertEqual(map(f, valid_inputs), expects)
def test_cc_parser(self):
"""cc_parser: known values and raise when strict"""
cc = cc_parser(cc_lines)
#pprint(cc)
#print cc.keys()
self.assertEqual(list(sorted(cc.keys())),
['ALLERGEN', 'ALTERNATIVE PRODUCTS',
'BIOPHYSICOCHEMICAL PROPERTIES', 'DATABASE', 'DISEASE',
'INTERACTION', 'LICENSE', 'MASS SPECTROMETRY'])
#test Disease topic (default_handler)
self.assertEqual(cc['DISEASE'], [
'Defects in PHKA1 are linked to X-linked muscle glycogenosis '
'[MIM:311870]',
'Defects in ABCD1 are the cause of recessive X-linked '
'adrenoleukodystrophy (X-ALD) [MIM:300100]. X-ALD is a rare '
'phenotype'
])
#test License (default_handler)
#pprint(cc['LICENSE'])
self.assertEqual(cc['LICENSE'], [
'This SWISS-PROT entry is copyright. It is produced through a '
'collaboration removed'])
#pprint(cc['DATABASE']) #join_split_dict
self.assertEqual(cc['DATABASE'], [{
'NAME': 'CD40Lbase',
'NOTE': 'European CD40L defect database (mutation db)',
'WWW': '"http://www.expasy.org/cd40lbase/"'}])
#test strict
cc_lines_with_unknown_topic = ['CC -!- BLAHBLAH: xxxxx'] + cc_lines
#pprint(cc_parser(cc_lines_with_unknown_topic))
self.assertEqual(cc_parser(cc_lines_with_unknown_topic)['BLAHBLAH'],
['xxxxx'])
self.assertRaises(FieldError, cc_parser,
cc_lines_with_unknown_topic, strict=True)
class ReferenceTests(TestCase):
"""Tests for parsers related to reference blocks"""
def test_ref_finder(self):
"""ref_finder: should return a list of ref blocks"""
pass
def test_refs_parser(self):
"""refs_parser: should return a dict of {RN: ref_dict}"""
pass
def test_single_ref_parser(self):
"""single_ref_parser: should return the expected dict"""
fake_ref_block = ['RN [1]',
'RP NUCLEOTIDE',
'RC STRAIN=Bristol N2;',
'RX PubMed=1113;',
'RA Zhang L., Wu S.-L., Rubin C.S.;',
'RT "A novel ";',
'RL J. Biol. Chem. 276:10.',]
rn, others = single_ref_parser(fake_ref_block)
self.assertEqual(rn, 1)
self.assertEqual(len(others), 6)
#test strict: lacking required labels
self.assertEqual(len(single_ref_parser(
fake_ref_block[:-1], strict=False)[1]), 5)
self.assertRaises(RecordError, single_ref_parser, fake_ref_block[:-1],
True)
def test_ra_parser(self):
"""ra_parser should return expected list"""
lines = \
"RA Galinier A., Bleicher F., Negre D.,\n"\
"RA Cozzone A.J., Cortay J.-C.;\n".splitlines()
self.assertEqual( ra_parser(lines),
['Galinier A.', 'Bleicher F.', 'Negre D.', 'Cozzone A.J.',
'Cortay J.-C.'])
def test_rx_parser(self):
"""rx_parser should return expected dict"""
inputs = [
['RX MEDLINE=22709107; PubMed=12788972; DOI=10.1073/pnas.113'],
['RX PubMed=14577811; '\
'DOI=10.1597/1545-1569(2003)040<0632:AMMITS>2.0.CO;2;']]
expects = [
{'DOI': '10.1073/pnas.113', 'MEDLINE': '22709107',
'PubMed': '12788972'},
{'DOI': '10.1597/1545-1569(2003)040<0632:AMMITS>2.0.CO;2',
'PubMed': '14577811'}]
self.assertEqual(map(rx_parser, inputs), expects)
def test_rc_parser(self):
"""rc_parser should return expected dict"""
lines = [
"RC PLASMID=R1 (R7268); TRANSPOSON=Tn3;",
"RC STRAIN=AL.012, AZ.026;"]
self.assertEqual(rc_parser(lines),
{'TRANSPOSON': 'Tn3', 'PLASMID': 'R1 (R7268)',
'STRAIN': ['AL.012', 'AZ.026']})
def test_rt_parser(self):
"""rt_parser should return expected str"""
lines = [
'RT "New insulin-like proteins',
'RT analysis and homology modeling.";']
self.assertEqual( rt_parser(lines),
'New insulin-like proteins analysis and homology modeling')
def test_rl_parser(self):
"""rl_parser should return expected str"""
lines = [
"RL J. Mol. Biol. 168:321-331(1983)."]
self.assertEqual( rl_parser(lines),
'J. Mol. Biol. 168:321-331(1983)')
def test_rn_parser(self):
"""rn_parser should return expected str"""
lines = [ "RN [8]"]
self.assertEqual( rn_parser(lines), 8)
def test_rg_parser(self):
"""rg_parser should return expected str"""
lines = [ "RG The mouse genome sequencing consortium;"]
self.assertEqual( rg_parser(lines),
['The mouse genome sequencing consortium'])
def test_rp_parser(self):
"""rp_parser should return expected str"""
lines = [ "RP X-RAY CRYSTALLOGRAPHY (1.8 ANGSTROMS)."]
self.assertEqual( rp_parser(lines),
'X-RAY CRYSTALLOGRAPHY (1.8 ANGSTROMS)')
#################################
# global test data
ft_lines = \
"""FT CHAIN 29 262 Granzyme A.
FT /FTId=PRO_0000027394.
FT ACT_SITE 69 69 Charge relay system.
FT VARIANT 121 121 T -> M (in dbSNP:3104233).
FT /FTId=VAR_024291.
FT VARIANT 1 7 unknown (in a skin tumor).
FT /FTId=VAR_005851.
FT CONFLICT 282 282 R -> Q (in Ref. 18).
FT STRAND 30 30
FT STRAND 33 34
FT TURN 37 38""".splitlines()
ft_expect = \
{'ACT_SITE': [{'Start': 69, 'End': 69, 'Description': 'Charge relay system'}],
'CHAIN': [{'Description': {'Description': 'Granzyme A',
'Id': 'PRO_0000027394'},
'End': 262,
'Start': 29}],
'CONFLICT': [{'Description': {'Comment': 'in Ref. 18',
'MutateFrom': 'R',
'MutateTo': 'Q'},
'End': 282,
'Start': 282}],
'SecondaryStructure': [('STRAND', 30, 30),
('STRAND', 33, 34),
('TURN', 37, 38)],
'VARIANT': [{'Description': {'Comment': 'in dbSNP:3104233',
'Id': 'VAR_024291',
'MutateFrom': 'T',
'MutateTo': 'M'},
'End': 121,
'Start': 121},
{'Description': {'Comment': 'in a skin tumor',
'Id': 'VAR_005851',
'MutateFrom': 'unknown ',
'MutateTo': ''},
'End': 7,
'Start': 1}]}
dr_lines =\
"""DR MIM; 140050; gene.
DR GO; GO:0001772; C:immunological synapse; TAS.
DR GO; GO:0005634; C:nucleus; TAS.
DR GO; GO:0006915; P:apoptosis; TAS.
DR GO; GO:0006922; P:cleavage of lamin; IDA.
DR GO; GO:0006955; P:immune response; TAS.
DR InterPro; IPR001254; Peptidase_S1_S6.
DR InterPro; IPR001314; Peptidase_S1A.
DR Pfam; PF00089; Trypsin; 1.""".splitlines()
dr_expect =\
{'GO': [['GO:0001772', 'C:immunological synapse', 'TAS'],
['GO:0005634', 'C:nucleus', 'TAS'],
['GO:0006915', 'P:apoptosis', 'TAS'],
['GO:0006922', 'P:cleavage of lamin', 'IDA'],
['GO:0006955', 'P:immune response', 'TAS']],
'Pfam': [['PF00089', 'Trypsin', '1']],
'InterPro': [['IPR001254', 'Peptidase_S1_S6'],
['IPR001314', 'Peptidase_S1A']],
'MIM': [['140050', 'gene']]}
cc_lines = \
"""CC -!- ALLERGEN: Causes an allergic reaction in human. Binds to IgE.
CC bovine dander.
CC -!- ALTERNATIVE PRODUCTS:
CC Event=Alternative splicing; Named isoforms=3;
CC Comment=Additional isoforms seem to exist.
CC confirmation;
CC Name=1; Synonyms=AIRE-1;
CC IsoId=O43918-1; Sequence=Displayed;
CC Name=2; Synonyms=AIRE-2;
CC IsoId=O43918-2; Sequence=VSP_004089;
CC Name=3; Synonyms=AIRE-3;
CC IsoId=O43918-3; Sequence=VSP_004089, VSP_004090;
CC -!- BIOPHYSICOCHEMICAL PROPERTIES:
CC Kinetic parameters:
CC KM=98 uM for ATP;
CC KM=688 uM for pyridoxal;
CC Vmax=1.604 mmol/min/mg enzyme;
CC pH dependence:
CC Optimum pH is 6.0. Active pH 4.5 to 10.5;
CC -!- DATABASE: NAME=CD40Lbase;
CC NOTE=European CD40L defect database (mutation db);
CC WWW="http://www.expasy.org/cd40lbase/".
CC -!- DISEASE: Defects in PHKA1 are linked to X-linked muscle
CC glycogenosis [MIM:311870].
CC -!- DISEASE: Defects in ABCD1 are the cause of recessive X-linked
CC adrenoleukodystrophy (X-ALD) [MIM:300100]. X-ALD is a rare
CC phenotype.
CC -!- INTERACTION:
CC Self; NbExp=1; IntAct=EBI-123485, EBI-123485;
CC Q9W158:CG4612; NbExp=1; IntAct=EBI-123485, EBI-89895;
CC Q9VYI0:fne; NbExp=1; IntAct=EBI-123485, EBI-126770;
CC -!- MASS SPECTROMETRY: MW=24948; MW_ERR=6; METHOD=MALDI; RANGE=1-228;
CC NOTE=Ref.2.
CC --------------------------------------------------------------------------
CC This SWISS-PROT entry is copyright. It is produced through a collaboration
CC removed.
CC --------------------------------------------------------------------------
""".splitlines()
fake_records_valid = """ID CYC_BOVIN STANDARD; PRT; 104 AA.
AC ac1; ac2;
DT dt.
DE de.
OS os.
OC oc.
OX NCBI_TaxID=9606;
RN [1]
SQ SEQUENCE 486 AA; 55639 MW; D7862E867AD74383 CRC64
aac cpp
ggh hh
//
ID idid std; prt; 104 #-5
OX NCBI_TaxID=9606;
DE dede.
ggaaccpp
//""".splitlines()
# Run tests if called from the command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_fasta.py 000644 000765 000024 00000041153 12024702176 022267 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for FASTA and related parsers.
"""
from cogent.parse.fasta import FastaParser, MinimalFastaParser, \
NcbiFastaLabelParser, NcbiFastaParser, RichLabel, LabelParser, GroupFastaParser
from cogent.core.sequence import DnaSequence, Sequence, ProteinSequence as Protein
from cogent.core.info import Info
from cogent.parse.record import RecordError
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
def Dna(seq, *args, **kwargs):
seq = seq.replace('u','t')
seq = seq.replace('U','T')
d = DnaSequence(seq, *args, **kwargs)
return d
class GenericFastaTest(TestCase):
"""Setup data for all the various FASTA parsers."""
def setUp(self):
"""standard files"""
self.labels = '>abc\n>def\n>ghi\n'.split('\n')
self.oneseq = '>abc\nUCAG\n'.split('\n')
self.multiline = '>xyz\nUUUU\nCC\nAAAAA\nG'.split('\n')
self.threeseq='>123\na\n> \t abc \t \ncag\ngac\n>456\nc\ng'.split('\n')
self.twogood='>123\n\n> \t abc \t \ncag\ngac\n>456\nc\ng'.split('\n')
self.oneX='>123\nX\n> \t abc \t \ncag\ngac\n>456\nc\ng'.split('\n')
self.nolabels = 'GJ>DSJGSJDF\nSFHKLDFS>jkfs\n'.split('\n')
self.empty = []
class MinimalFastaParserTests(GenericFastaTest):
"""Tests of MinimalFastaParser: returns (label, seq) tuples."""
def test_empty(self):
"""MinimalFastaParser should return empty list from 'file' w/o labels"""
self.assertEqual(list(MinimalFastaParser(self.empty)), [])
self.assertEqual(list(MinimalFastaParser(self.nolabels, strict=False)),
[])
self.assertRaises(RecordError, list, MinimalFastaParser(self.nolabels))
def test_no_labels(self):
"""MinimalFastaParser should return empty list from file w/o seqs"""
#should fail if strict (the default)
self.assertRaises(RecordError, list,
MinimalFastaParser(self.labels,strict=True))
#if not strict, should skip the records
self.assertEqual(list(MinimalFastaParser(self.labels, strict=False)),
[])
def test_single(self):
"""MinimalFastaParser should read single record as (label, seq) tuple"""
f = list(MinimalFastaParser(self.oneseq))
self.assertEqual(len(f), 1)
a = f[0]
self.assertEqual(a, ('abc', 'UCAG'))
f = list(MinimalFastaParser(self.multiline))
self.assertEqual(len(f), 1)
a = f[0]
self.assertEqual(a, ('xyz', 'UUUUCCAAAAAG'))
def test_multiple(self):
"""MinimalFastaParser should read multiline records correctly"""
f = list(MinimalFastaParser(self.threeseq))
self.assertEqual(len(f), 3)
a, b, c = f
self.assertEqual(a, ('123', 'a'))
self.assertEqual(b, ('abc', 'caggac'))
self.assertEqual(c, ('456', 'cg'))
def test_multiple_bad(self):
"""MinimalFastaParser should complain or skip bad records"""
self.assertRaises(RecordError, list, MinimalFastaParser(self.twogood))
f = list(MinimalFastaParser(self.twogood, strict=False))
self.assertEqual(len(f), 2)
a, b = f
self.assertEqual(a, ('abc', 'caggac'))
self.assertEqual(b, ('456', 'cg'))
class FastaParserTests(GenericFastaTest):
"""Tests of FastaParser: returns sequence objects."""
def test_empty(self):
"""FastaParser should return empty list from 'file' w/o labels"""
self.assertEqual(list(FastaParser(self.empty)), [])
self.assertEqual(list(FastaParser(self.nolabels, strict=False)),
[])
self.assertRaises(RecordError, list, FastaParser(self.nolabels))
def test_no_labels(self):
"""FastaParser should return empty list from file w/o seqs"""
#should fail if strict (the default)
self.assertRaises(RecordError, list,
FastaParser(self.labels,strict=True))
#if not strict, should skip the records
self.assertEqual(list(FastaParser(self.labels, strict=False)), [])
def test_single(self):
"""FastaParser should read single record as seq object"""
f = list(FastaParser(self.oneseq))
self.assertEqual(len(f), 1)
a = f[0]
self.assertEqual(a, ('abc', 'UCAG'))
self.assertEqual(a[1].Name, 'abc')
f = list(FastaParser(self.multiline))
self.assertEqual(len(f), 1)
a = f[0]
self.assertEqual(a, ('xyz', 'UUUUCCAAAAAG'))
self.assertEqual(a[1].Name, 'xyz')
def test_single_constructor(self):
"""FastaParser should use constructors if supplied"""
f = list(FastaParser(self.oneseq, Dna))
self.assertEqual(len(f), 1)
a = f[0]
self.assertEqual(a, ('abc', 'TCAG'))
self.assertEqual(a[1].Name, 'abc')
def upper_abc(x):
return None, {'ABC': x.upper()}
f = list(FastaParser(self.multiline, Dna, upper_abc))
self.assertEqual(len(f), 1)
a = f[0]
self.assertEqual(a, (None, 'TTTTCCAAAAAG'))
self.assertEqual(a[1].Name, None)
self.assertEqual(a[1].Info.ABC, 'XYZ')
def test_multiple(self):
"""FastaParser should read multiline records correctly"""
f = list(FastaParser(self.threeseq))
self.assertEqual(len(f), 3)
for i in f:
assert isinstance(i[1], Sequence)
a, b, c = f
self.assertEqual((a[1].Name, a[1]), ('123', 'a'))
self.assertEqual((b[1].Name, b[1]), ('abc', 'caggac'))
self.assertEqual((c[1].Name, c[1]), ('456', 'cg'))
def test_multiple_bad(self):
"""Parser should complain or skip bad records"""
self.assertRaises(RecordError, list, FastaParser(self.twogood))
f = list(FastaParser(self.twogood, strict=False))
self.assertEqual(len(f), 2)
a, b = f
a, b = a[1], b[1] #field 0 is name
self.assertEqual((a.Name, a), ('abc', 'caggac'))
self.assertEqual((b.Name, b), ('456', 'cg'))
def test_multiple_constructor_bad(self):
"""Parser should complain or skip bad records w/ constructor"""
def dnastrict(x, **kwargs):
try:
return Dna(x, check=True, **kwargs)
except Exception, e:
raise RecordError, "Could not convert sequence"
self.assertRaises(RecordError, list, FastaParser(self.oneX, dnastrict))
f = list(FastaParser(self.oneX, dnastrict, strict=False))
self.assertEqual(len(f), 2)
a, b = f
a, b = a[1], b[1]
self.assertEqual((a.Name, a), ('abc', 'caggac'.upper()))
self.assertEqual((b.Name, b), ('456', 'cg'.upper()))
class NcbiFastaLabelParserTests(TestCase):
"""Tests of the label line parser for NCBI's FASTA identifiers."""
def test_init(self):
"""Labels from genpept.fsa should work as expected"""
i = NcbiFastaLabelParser(
'>gi|37549575|ref|XP_352503.1| similar to EST gb|ATTS1136')[1]
self.assertEqual(i.GI, ['37549575'])
self.assertEqual(i.RefSeq, ['XP_352503.1'])
self.assertEqual(i.Description, 'similar to EST gb|ATTS1136')
i = NcbiFastaLabelParser(
'>gi|32398734|emb|CAD98694.1| (BX538350) dbj|baa86974.1, possible')[1]
self.assertEqual(i.GI, ['32398734'])
self.assertEqual(i.RefSeq, [])
self.assertEqual(i.EMBL, ['CAD98694.1'])
self.assertEqual(i.Description, '(BX538350) dbj|baa86974.1, possible')
i = NcbiFastaLabelParser(
'>gi|10177064|dbj|BAB10506.1| (AB005238) ')[1]
self.assertEqual(i.GI, ['10177064'])
self.assertEqual(i.DDBJ, ['BAB10506.1'])
self.assertEqual(i.Description, '(AB005238)')
class NcbiFastaParserTests(TestCase):
"""Tests of the NcbiFastaParser."""
def setUp(self):
"""Define a few standard files"""
self.peptide = [
'>gi|10047090|ref|NP_055147.1| small muscle protein, X-linked [Homo sapiens]',
'MNMSKQPVSNVRAIQANINIPMGAFRPGAGQPPRRKECTPEVEEGVPPTSDEEKKPIPGAKKLPGPAVNL',
'SEIQNIKSELKYVPKAEQ',
'>gi|10047092|ref|NP_037391.1| neuronal protein [Homo sapiens]',
'MANRGPSYGLSREVQEKIEQKYDADLENKLVDWIILQCAEDIEHPPPGRAHFQKWLMDGTVLCKLINSLY',
'PPGQEPIPKISESKMAFKQMEQISQFLKAAETYGVRTTDIFQTVDLWEGKDMAAVQRTLMALGSVAVTKD'
]
self.nasty = [
' ', #0 ignore leading blank line
'>gi|abc|ref|def|', #1 no description -- ok
'UCAG', #2 single line of sequence
'#comment', #3 comment -- skip
' \t ', #4 ignore blank line between records
'>gi|xyz|gb|qwe| \tdescr \t\t', #5 desciption has whitespace
'UUUU', #6 two lines of sequence
'CCCC', #7
'>gi|bad|ref|nonsense', #8 missing last pipe -- error
'ACU', #9
'>gi|bad|description', #10 not enough fields -- error
'AAA', #11
'>gi|bad|ref|stuff|label', #12
'XYZ', #13 bad sequence -- error
'>gi|bad|gb|ignore| description', #14 label without sequence -- error
'> gi | 123 | dbj | 456 | desc|with|pipes| ',#15 label w/ whitespace -- OK
'ucag', #16
' \t ', #17 ignore blank line inside record
'UCAG', #18
'tgac', #19 lowercase should be OK
'# comment', #20 comment -- skip
'NNNN', #21 degenerates should be OK
' ', #22 ignore trailing blank line
]
self.empty = []
self.no_label = ['ucag']
def test_empty(self):
"""NcbiFastaParser should accept empty input"""
self.assertEqual(list(NcbiFastaParser(self.empty)), [])
self.assertEqual(list(NcbiFastaParser(self.empty, Protein)), [])
def test_normal(self):
"""NcbiFastaParser should accept normal record if loose or strict"""
f = list(NcbiFastaParser(self.peptide, Protein))
self.assertEqual(len(f), 2)
a, b = f
a, b = a[1], b[1] #field 0 is the name
self.assertEqual(a, 'MNMSKQPVSNVRAIQANINIPMGAFRPGAGQPPRRKECTPEVEEGVPPTSDEEKKPIPGAKKLPGPAVNLSEIQNIKSELKYVPKAEQ')
self.assertEqual(a.Info.GI, ['10047090'])
self.assertEqual(a.Info.RefSeq, ['NP_055147.1'])
self.assertEqual(a.Info.DDBJ, [])
self.assertEqual(a.Info.Description,
'small muscle protein, X-linked [Homo sapiens]')
self.assertEqual(b, 'MANRGPSYGLSREVQEKIEQKYDADLENKLVDWIILQCAEDIEHPPPGRAHFQKWLMDGTVLCKLINSLYPPGQEPIPKISESKMAFKQMEQISQFLKAAETYGVRTTDIFQTVDLWEGKDMAAVQRTLMALGSVAVTKD')
self.assertEqual(b.Info.GI, ['10047092'])
self.assertEqual(b.Info.RefSeq, ['NP_037391.1'])
self.assertEqual(b.Info.Description, 'neuronal protein [Homo sapiens]')
def test_bad(self):
"""NcbiFastaParser should raise error on bad records if strict"""
#if strict, starting anywhere in the first 15 lines should cause errors
for i in range(15):
self.assertRaises(RecordError,list,NcbiFastaParser(self.nasty[i:]))
#...but the 16th is OK.
r = list(NcbiFastaParser(self.nasty[15:]))[0]
self.assertEqual(r, ('123', 'ucagUCAGtgacNNNN'))
#test that we get what we expect if not strict
r = list(NcbiFastaParser(self.nasty, Sequence, strict=False))
self.assertEqual(len(r), 4)
a, b, c, d = r
self.assertEqual((a[1], a[1].Info.GI, a[1].Info.RefSeq, \
a[1].Info.Description),
('UCAG', ['abc'], ['def'], ''))
self.assertEqual((b[1], b[1].Info.GI, b[1].Info.GenBank, \
b[1].Info.Description),
('UUUUCCCC', ['xyz'], ['qwe'], 'descr'))
self.assertEqual((c[1], c[1].Info.GI, c[1].Info.RefSeq, \
c[1].Info.Description),
('XYZ', ['bad'], ['stuff'], 'label'))
self.assertEqual((d[1], d[1].Info.GI, d[1].Info.DDBJ, \
d[1].Info.Description),
('ucagUCAGtgacNNNN'.upper(), ['123'], ['456'], 'desc|with|pipes|'))
#...and when we explicitly supply a constructor
r = list(NcbiFastaParser(self.nasty, Dna, strict=False))
self.assertEqual(len(r), 3)
a, b, c = r
a, b, c = a[1], b[1], c[1]
self.assertEqual((a, a.Info.GI, a.Info.RefSeq, a.Info.Description),
('TCAG', ['abc'], ['def'], ''))
self.assertEqual((b, b.Info.GI, b.Info.GenBank, b.Info.Description),
('TTTTCCCC', ['xyz'], ['qwe'], 'descr'))
self.assertEqual((c, c.Info.GI, c.Info.DDBJ, c.Info.Description),
('tcagTCAGtgacNNNN'.upper(), ['123'], ['456'], 'desc|with|pipes|'))
class LabelParsingTest(TestCase):
"""Test generic fasta label parsing"""
def test_rich_label(self):
"""rich label correctly constructs label strings"""
# labels should be equal based on the result of applying their
# attributes to their string template
k = RichLabel(Info(species="rat"), "%(species)s")
l = RichLabel(Info(species="rat", seq_id="xy5"), "%(species)s")
self.assertEqual(k, l)
# labels should construct from Info components correctly
k = RichLabel(Info(species="rat", seq_id="xy5"),
"%(seq_id)s:%(species)s")
self.assertEqual(k, "xy5:rat")
k = RichLabel(Info(species="rat", seq_id="xy5"),
"%(species)s:%(seq_id)s")
self.assertEqual(k, "rat:xy5")
# extra components should be ignored
k = RichLabel(Info(species="rat", seq_id="xy5"), "%(species)s")
self.assertEqual(k, "rat")
# the label should have Info object
self.assertEqual(k.Info.species, "rat")
self.assertEqual(k.Info.seq_id, "xy5")
# label should be constructable just like a normal string
self.assertEqual(RichLabel('a'), 'a')
def test_label_parser(self):
"""label parser factory function cope with mixed structure labels"""
# the label parser factory function should correctly handle label lines
# with mixed separators
make = LabelParser("%(species)s:%(accession)s",
[[0,"accession", str],
[2, "species", str]],
split_with=": ")
for label, expect in [(">abcd:human:misc", "misc:abcd"),
("abcd:human:misc", "misc:abcd"),
(">abcd:Human misc", "misc:abcd"),
(">abcd Human:misc", "misc:abcd"),
(">abcd:Human misc", "misc:abcd")]:
self.assertEqual(make(label), expect)
# should raise an assertion error if template doesn't match at least one field name
self.assertRaises(AssertionError, LabelParser, "%s:%s",
[[0,"accession", str],
[2, "species", str]],
split_with=": ")
class GroupFastaParsingTest(TestCase):
"""test parsing of grouped sequences in a collection"""
def test_groups(self):
"""correctly yield grouped sequences from fasta formatted data"""
data = [">group1:seq1_id:species1",
"ACTG",
">group1:seq2_id:species2",
"ACTG",
">group2:seq3_id:species1",
"ACGT",
">group2:seq4_id:species2",
"ACGT"]
expected = [{"species1": "ACTG", "species2":"ACTG"},
{"species1":"ACGT", "species2":"ACGT"}]
label_to_name = LabelParser("%(species)s", [(0,"Group",str),
(1,"seq_id",str),(2,"species",str)], split_with=":")
parser = GroupFastaParser(data, label_to_name, aligned=True)
count = 0
for group in parser:
got = group.todict()
want = expected[count]
self.assertEqual(got, want)
self.assertEqual(group.Info.Group, "group%s" % (count+1))
count += 1
# check we don't return a done group
done_groups = ["group1"]
parser = GroupFastaParser(data, label_to_name, done_groups=done_groups,
aligned=True)
for group in parser:
got = group.todict()
want = expected[1]
self.assertEqual(got, want)
self.assertEqual(group.Info.Group, "group2")
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_fastq.py 000644 000765 000024 00000004337 12024702176 022312 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.parse.fastq import MinimalFastqParser
__author__ = "Gavin Huttley"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
data = {
"GAPC_0015:6:1:1259:10413#0/1":
dict(seq='AACACCAAACTTCTCCACCACGTGAGCTACAAAAG',
qual=r'````Y^T]`]c^cabcacc`^Lb^ccYT\T\Y\WF'),
"GAPC_0015:6:1:1283:11957#0/1":
dict(seq='TATGTATATATAACATATACATATATACATACATA',
qual=r']KZ[PY]_[YY^```ac^\\`bT``c`\aT``bbb'),
"GAPC_0015:6:1:1284:10484#0/1":
dict(seq='TCAGTTTTCCTCGCCATATTTCACGTCCTAAAGCG',
qual=r'UM_]]U_]Z_Y^\^^``Y]`^SZ]\Ybb`^_LbL_'),
"GAPC_0015:6:1:1287:17135#0/1":
dict(seq='TGTGCCTATGGAAGCAGTTCTAGGATCCCCTAGAA',
qual=r'^aacccL\ccc\c\cTKTS]KZ\]]I\[Wa^T`^K'),
"GAPC_0015:6:1:1293:3171#0/1":
dict(seq="AAAGAAAGGAAGAAAAGAAAAAGAAACCCGAGTTA",
qual=r"b`bbbU_[YYcadcda_LbaaabWbaacYcc`a^c"),
"GAPC_0015:6:1:1297:10729#0/1":
dict(seq="TAATGCCAAAGAAATATTTCCAAACTACATGCTTA",
qual=r"T\ccLbb``bacc]_cacccccLccc\ccTccYL^"),
"GAPC_0015:6:1:1299:5940#0/1":
dict(seq="AATCAAGAAATGAAGATTTATGTATGTGAAGAATA",
qual=r"dcddbcfffdfffd`dd`^`c`Oc`Ybb`^eecde"),
"GAPC_0015:6:1:1308:6996#0/1":
dict(seq="TGGGACACATGTCCATGCTGTGGTTTTAACCGGCA",
qual=r"a]`aLY`Y^^ccYa`^^TccK_X]\c\c`caTTTc"),
"GAPC_0015:6:1:1314:13295#0/1":
dict(seq="AATATTGCTTTGTCTGAACGATAGTGCTCTTTGAT",
qual=r"cLcc\\dddddaaYd`T```bLYT\`a```bZccc"),
"GAPC_0015:6:1:1317:3403#0/1":
dict(seq="TTGTTTCCACTTGGTTGATTTCACCCCTGAGTTTG",
qual=r"\\\ZTYTSaLbb``\_UZ_bbcc`cc^[ac\a\T\ ".strip())# had to add space
}
class ParseFastq(TestCase):
def test_parse(self):
"""sequence and info objects should correctly match"""
for label, seq, qual in MinimalFastqParser('data/fastq.txt'):
self.assertTrue(label in data)
self.assertEqual(seq, data[label]["seq"])
self.assertEqual(qual, data[label]["qual"])
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_flowgram.py 000644 000765 000024 00000131277 12024702176 023016 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""tests for Flowgram and Flowgramcollection objects
"""
__author__ = "Jens Reeder, Julia Goodrich"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jens Reeder","Julia Goodrich"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jens Reeder"
__email__ = "jreeder@colorado.edu"
__status__ = "Development"
from cogent.util.unit_test import TestCase, main
from types import GeneratorType
from numpy import array, transpose
from cogent.core.sequence import Sequence
from cogent.parse.flowgram import Flowgram, build_averaged_flowgram
from cogent.parse.flowgram_parser import parse_sff
class FlowgramTests(TestCase):
def test_init_empty(self):
"""Flowgram should init correctly."""
f = Flowgram()
self.assertEqual(f._flowgram, '')
self.assertEqual(f.flowgram, [])
def test_init_data(self):
"""Flowgram init with data should set data in correct location"""
f = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',KeySeq = "ATCG",
floworder = "TACG", header_info = {'Bases':'TACCCC'})
self.assertEqual(f._flowgram, '0.5 1.0 4.0 0.0')
self.assertEqual(f.flowgram, [0.5, 1.0, 4.0, 0.0])
self.assertEqual(f.Name, 'a')
self.assertEqual(f.keySeq, "ATCG")
self.assertEqual(f.floworder, "TACG")
self.assertEqual(f.Bases, 'TACCCC')
self.assertEqual(f.header_info, {'Bases':'TACCCC'})
f = Flowgram([0.5, 1.0, 4.0, 0.0], Name = 'a',KeySeq = "ATCG",
floworder = "TACG", header_info = {'Bases':'TACCCC'})
self.assertEqual(f._flowgram, '0.5 1.0 4.0 0.0')
self.assertEqual(f.flowgram, [0.5, 1.0, 4.0, 0.0])
def test_cmpSeqToString(self):
"""Sequence should compare equal to same string."""
f = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
self.assertTrue(f.cmpSeqToString('TACCCC'))
self.assertFalse(f.cmpSeqToString('TACCC'))
f = Flowgram('0.5 1.0 4.0 0.0',floworder = "TACG")
self.assertTrue(f.cmpSeqToString('TACCCC'))
self.assertFalse(f.cmpSeqToString('TACCC'))
def test_cmp_flow_to_string(self):
"""Sequence should compare equal to same string."""
f = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
self.assertEqual(f, '0.5 1.0 4.0 0.0')
self.assertNotEqual(f,'0.5 1.0 4.0')
f2 = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
self.assertEqual(f,f2)
def test_cmpBySeqs(self):
"""Flowgrams should be the same if name, bases, or to_seqs are equal"""
f = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
f2 = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
self.assertEqual(f.cmpBySeqs(f2), 0)
f2 = Flowgram('0.5 1.0 4.0 0.0', Name = 'b',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
self.assertEqual(f.cmpBySeqs(f2), 0)
f2 = Flowgram('0.5 1.0 4.0 0.0',floworder = "TACG")
self.assertEqual(f.cmpBySeqs(f2), 0)
def test_cmpByName(self):
"""Flowgrams should be the same if name, bases, or to_seqs are equal"""
f = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
f2 = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
self.assertEqual(f.cmpByName(f2), 0)
self.assertEqual(f.cmpByName(f), 0)
f2 = Flowgram('0.5 1.0 4.0 0.0', Name = 'b',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
self.assertNotEqual(f.cmpByName(f2), 0)
def test_toFasta(self):
"""Flowgram toFasta() should return Fasta-format string"""
even = '0.5 1.0 4.0 0.0'
odd = '0.5 1.0 4.0 1.0'
even_f = Flowgram(even, Name='even', floworder = "TACG")
odd_f = Flowgram(odd, Name='odd', floworder = "TACG")
self.assertEqual(even_f.toFasta(), '>even\nTACCCC')
#set line wrap to small number so we can test that it works
self.assertEqual(even_f.toFasta(LineWrap = 2), '>even\nTA\nCC\nCC')
self.assertEqual(odd_f.toFasta(LineWrap = 2), '>odd\nTA\nCC\nCC\nG')
even_f = Flowgram(even, Name='even', floworder = "TACG",
header_info ={'Bases':'TACCCG'})
odd_f = Flowgram(odd, Name='odd', floworder = "TACG",
header_info ={'Bases':'TACCCGG'})
self.assertEqual(even_f.toFasta(), '>even\nTACCCG')
#set line wrap to small number so we can test that it works
self.assertEqual(even_f.toFasta(LineWrap = 2), '>even\nTA\nCC\nCG')
self.assertEqual(odd_f.toFasta(LineWrap = 2), '>odd\nTA\nCC\nCG\nG')
def test_contains(self):
"""Flowgram contains should return correct result"""
f = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCC'})
assert '0.5' in f
assert '0.5 1.0' in f
assert '2.0' not in f
assert '5.0' not in f
def test_cmp(self):
"""_cmp_ should compare the flowgram strings."""
f1 = Flowgram(['1 2 3 4'])
f2 = Flowgram(['2 2 3 4'])
self.assertNotEqual(f1,f2)
self.assertEqual(f1,f1)
#works also with string
self.assertNotEqual(f1,"1 2 3 5")
self.assertEqual(f1,"1 2 3 4")
self.assertNotEqual(f1,"")
def test_iter(self):
"""Flowgram iter should iterate over sequence"""
f = Flowgram('0.5 1.0 4.0 0.0')
self.assertEqual(list(f), [0.5,1.0,4.0,0.0])
def test_str(self):
"""__str__ returns self._flowgram unmodified."""
f = Flowgram('0.5 1.0 4.0 0.0')
self.assertEqual(str(f), '0.5\t1.0\t4.0\t0.0')
f = Flowgram([0.5, 1.0, 4.0, 0.0])
self.assertEqual(str(f), '0.5\t1.0\t4.0\t0.0')
def test_len(self):
"""returns the length of the flowgram"""
f = Flowgram('0.5 1.0 4.0 0.0')
self.assertEqual(len(f), 4)
f = Flowgram()
self.assertEqual(len(f), 0)
def test_hash(self):
"""__hash__ behaves like the flowgram string for dict lookup."""
f = Flowgram('0.5 1.0 4.0 0.0', floworder = "TACG")
self.assertEqual(hash(f), hash('0.5 1.0 4.0 0.0'))
f = Flowgram()
self.assertEqual(hash(f), hash(''))
def test_toSeq(self):
"""toSeq should Translate flowgram to sequence"""
f = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCG'})
self.assertEqual(f.toSeq(), 'TACCCG')
self.assertEqual(isinstance(f.toSeq(),Sequence), True)
self.assertEqual(f.toSeq(Bases = False), 'TACCCC')
f = Flowgram('0.5 1.0 4.0 0.0 0.0 1.23 0.0 6.1',
Name = 'a',floworder = "TACG",
header_info = {'Bases':'TACCCG'})
self.assertEqual(f.toSeq(), 'TACCCG')
self.assertEqual(f.toSeq(Bases = False), 'TACCCCAGGGGGG')
f = Flowgram('0.5 1.0 4.0 0.0', Name = 'a',floworder = "TACG",
header_info = {})
self.assertEqual(f.toSeq(), 'TACCCC')
self.assertEqual(isinstance(f.toSeq(),Sequence), True)
self.assertEqual(f.toSeq(Bases = False), 'TACCCC')
f = Flowgram('0.5 1.0 4.0 0.0 0.0 1.23 0.0 6.1',
Name = 'a',floworder = "TACG",
header_info = {})
self.assertEqual(f.toSeq(Bases = True), 'TACCCCAGGGGGG')
f = Flowgram('0.4 0.0 0.0 0.0 0.0 1.23 0.0 1.1',
Name = 'a',floworder = "TACG",
header_info = {})
self.assertEqual(f.toSeq(), 'NAG')
def test_getQualityTrimmedFlowgram(self):
"""getQualityTrimmedFlowgram trims the flowgram correctly"""
f = Flowgram('0.5 1.0 4.1 0.0 0.0 1.23 0.0 3.1',
Name = 'a', floworder = "TACG",
header_info = {'Bases':'TACCCCAGGG', 'Clip Qual Right': 7,
'Flow Indexes': "1\t2\t3\t3\t3\t3\t6\t8\t8\t8"})
trimmed = f.getQualityTrimmedFlowgram()
self.assertEqual(trimmed.toSeq(), "TACCCCA")
self.assertEqual(str(trimmed), "0.5\t1.0\t4.1\t0.0\t0.0\t1.23")
# tests on real data
flow1 = self.flows[0]
flow2 = self.flows[1]
flow1_trimmed = flow1.getQualityTrimmedFlowgram()
self.assertEqual(str(flow1_trimmed), "1.06 0.08 1.04 0.08 0.05 0.94 0.10 2.01 0.10 0.07 0.96 0.09 1.04 1.96 1.07 0.10 1.01 0.13 0.08 1.01 1.06 1.83 2.89 0.18 0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97")
self.assertEqual(flow1_trimmed.Bases,
"tcagGCTAACTGTAACCCTCTTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCA")
flow2_trimmed = flow2.getQualityTrimmedFlowgram()
self.assertEqual(str(flow2_trimmed), "1.04 0.00 1.01 0.00 0.00 1.00 0.00 1.00 0.00 1.05 0.00 0.91 0.10 1.07 0.95 1.01 0.00 0.06 0.93 0.02 0.03 1.06 1.18 0.09 1.00 0.05 0.90 0.11 0.07 1.99 0.11 0.02 1.96 1.04 0.13 0.01 2.83 0.10 1.97 0.06 0.11 1.04 0.13 0.03 0.98 1.15 0.07 1.00 0.07 0.08 0.98 0.11 1.92 0.05 0.04 2.96 1.02 1.02 0.04 0.93 1.00 0.13 0.04 1.00 1.03 0.08 0.97 0.13 0.11 1.88 0.09 0.05 1.02 1.89 0.07 0.11 0.98 0.05 0.07 1.01 0.08 0.05 1.01 0.13 1.00 0.07 0.10 1.04 0.10 0.04 0.98 0.12 1.03 0.96 0.11 0.07 1.00 0.09 0.03 1.03 0.11 1.95 1.06 0.13 0.05 1.00 0.13 0.11 1.00 0.09 0.03 2.89 0.08 0.95 0.09 1.03 1.02 1.05 1.07 0.08 0.12 2.81 0.08 0.08 1.00 1.07 0.07 0.05 1.86 0.12 0.98 0.06 2.00 0.11 1.02 0.11 0.08 1.88 0.13 1.03 0.13 0.98 0.15 0.11 1.03 1.03 1.04 0.18 0.98 0.13 0.15 1.04 0.11 1.01 0.13 0.06 1.01 0.06 1.02 0.08 0.99 0.14 0.99 0.09 0.05 1.09 0.04 0.07 2.96 0.09 2.03 0.13 2.96 1.13 0.08 1.03 0.07 0.99 0.11 0.05 1.05 1.04 0.09 0.07 1.00 1.03 0.09 0.06 1.06 1.04 2.94 0.18 0.06 0.93 0.10 1.10 0.11 2.02 0.17 1.00 1.03 0.06 0.11 0.96 0.04 3.00 0.11 0.07 1.99 0.10 2.03 0.12 0.97 0.16 0.01 2.09 0.14 1.04 0.16 0.06 1.03 0.14 1.12 0.12 0.05 0.96 1.01 0.10 0.14 0.94 0.03 0.12 1.10 0.92 0.09 1.10 1.04 1.02 0.12 0.97 2.00 0.15 1.08 0.04 1.03 1.04 0.03 0.09 5.16 1.02 0.09 0.13 2.66 0.09 0.05 1.06 0.07 0.89 0.05 0.12 1.10 0.16 0.06 1.01 0.13 1.00 0.14 0.98 0.09 2.92 1.28 0.03 2.95 0.98 0.16 0.08 0.95 0.96 1.09 0.08 1.07 1.01 0.16 0.06 4.52 0.12 1.03 0.07 0.09 1.03 0.14 0.03 1.01 1.99")
self.assertEqual(flow2_trimmed.Bases,
"tcagAGACGCACTCAATTATTTCCATAGCTTGGGTAGTGTCAATAATGCTGCTATGAACATGGGAGTACAAATATTCTTCAAGATACTGATCTCATTTCCTTTAGATATATACCCAGAAGTGAAATTCCTGGATCACATAGTAGTTCTATTTTTATTTGATGAGAAACTTTATACTATTTTTCATAA")
def test_getPrimerTrimmedFlowgram(self):
"""getPrimerTrimmedFlowgram cuts the barcode of the flowgram correctly"""
f = Flowgram('0.5 1.0 4.1 0.0 0.0 1.23 0.0 3.1',
Name = 'a', floworder = "TACG",
header_info = {'Bases':'TACCCCAGGG', 'Clip Qual Right': 7,
'Flow Indexes': "1\t2\t3\t3\t3\t3\t6\t8\t8\t8"})
trimmed = f.getPrimerTrimmedFlowgram(primerseq="TA")
#test primer trimming
self.assertEqual(trimmed.toSeq(), "CCCCAGGG")
self.assertEqual(str(trimmed), "0.00\t0.00\t4.10\t0.00\t0.00\t1.23\t0.00\t3.10")
for (a,b) in zip(trimmed.flowgram, [0.0,0.0,4.1,0.0,0.0,1.23,0.0,3.1]):
self.assertFloatEqual(a,b)
trimmed = f.getPrimerTrimmedFlowgram(primerseq="TACC")
for (a,b) in zip(trimmed.flowgram, [0.0,0.0,2.1,0.0,0.0,1.23,0.0,3.1]):
self.assertFloatEqual(a,b)
self.assertEqual(trimmed.toSeq(), "CCAGGG")
self.assertEqual(str(trimmed), "0.00\t0.00\t2.10\t0.00\t0.00\t1.23\t0.00\t3.10")
# test that primer trimming does not leave ambig flow at begin
trimmed = f.getPrimerTrimmedFlowgram(primerseq="TACCCC")
for (a,b) in zip(trimmed.flowgram, [0.0,1.23,0.0,3.1]):
self.assertFloatEqual(a,b)
self.assertEqual(trimmed.toSeq(), "AGGG")
self.assertEqual(str(trimmed), "0.00\t1.23\t0.00\t3.10")
# tests on real data
flow1 = self.flows[0]
flow2 = self.flows[1]
flow3 = self.flows[2]
flow1_trimmed = flow1.getPrimerTrimmedFlowgram(primerseq="TCAG"+"GCTAACTGTAA")
self.assertEqual(str(flow1_trimmed), "0.00\t0.00\t2.89 0.18 0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04")
self.assertEqual(flow1_trimmed.Bases,
"CCCTCTTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCActgagcgggctggcaaggc")
flow1_trimmed = flow1.getPrimerTrimmedFlowgram(primerseq="TCAG"+"GCTAACTGTAAC")
self.assertEqual(str(flow1_trimmed), "0.00\t0.00\t1.89 0.18 0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04")
self.assertEqual(flow1_trimmed.Bases,
"CCTCTTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCActgagcgggctggcaaggc")
#test that trimming does not leave 4 zero flows (homopolymer)
flow1_trimmed = flow1.getPrimerTrimmedFlowgram(primerseq="TCAG"+"GCTAACTGTAACCC")
self.assertEqual(str(flow1_trimmed), "0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04")
self.assertEqual(flow1_trimmed.Bases,
"TCTTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCActgagcgggctggcaaggc")
#test that trimming does not leave 4 zero flows (signal <1.5)
flow1_trimmed = flow1.getPrimerTrimmedFlowgram(primerseq="TCAG"+"GCTAACTGTAACCCTC")
self.assertEqual(str(flow1_trimmed), "1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04")
self.assertEqual(flow1_trimmed.Bases,
"TTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCActgagcgggctggcaaggc")
flow1_untrimmed= flow1.getPrimerTrimmedFlowgram("")
self.assertEqual(str(flow1_untrimmed), "1.06 0.08 1.04 0.08 0.05 0.94 0.10 2.01 0.10 0.07 0.96 0.09 1.04 1.96 1.07 0.10 1.01 0.13 0.08 1.01 1.06 1.83 2.89 0.18 0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04")
self.assertEqual(flow1_untrimmed.Bases, "tcagGCTAACTGTAACCCTCTTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCActgagcgggctggcaaggc")
flow2_trimmed = flow2.getPrimerTrimmedFlowgram(primerseq="TCAG"+"AGACGCACT")
self.assertEqual(str(flow2_trimmed), "0.00\t0.05\t0.90 0.11 0.07 1.99 0.11 0.02 1.96 1.04 0.13 0.01 2.83 0.10 1.97 0.06 0.11 1.04 0.13 0.03 0.98 1.15 0.07 1.00 0.07 0.08 0.98 0.11 1.92 0.05 0.04 2.96 1.02 1.02 0.04 0.93 1.00 0.13 0.04 1.00 1.03 0.08 0.97 0.13 0.11 1.88 0.09 0.05 1.02 1.89 0.07 0.11 0.98 0.05 0.07 1.01 0.08 0.05 1.01 0.13 1.00 0.07 0.10 1.04 0.10 0.04 0.98 0.12 1.03 0.96 0.11 0.07 1.00 0.09 0.03 1.03 0.11 1.95 1.06 0.13 0.05 1.00 0.13 0.11 1.00 0.09 0.03 2.89 0.08 0.95 0.09 1.03 1.02 1.05 1.07 0.08 0.12 2.81 0.08 0.08 1.00 1.07 0.07 0.05 1.86 0.12 0.98 0.06 2.00 0.11 1.02 0.11 0.08 1.88 0.13 1.03 0.13 0.98 0.15 0.11 1.03 1.03 1.04 0.18 0.98 0.13 0.15 1.04 0.11 1.01 0.13 0.06 1.01 0.06 1.02 0.08 0.99 0.14 0.99 0.09 0.05 1.09 0.04 0.07 2.96 0.09 2.03 0.13 2.96 1.13 0.08 1.03 0.07 0.99 0.11 0.05 1.05 1.04 0.09 0.07 1.00 1.03 0.09 0.06 1.06 1.04 2.94 0.18 0.06 0.93 0.10 1.10 0.11 2.02 0.17 1.00 1.03 0.06 0.11 0.96 0.04 3.00 0.11 0.07 1.99 0.10 2.03 0.12 0.97 0.16 0.01 2.09 0.14 1.04 0.16 0.06 1.03 0.14 1.12 0.12 0.05 0.96 1.01 0.10 0.14 0.94 0.03 0.12 1.10 0.92 0.09 1.10 1.04 1.02 0.12 0.97 2.00 0.15 1.08 0.04 1.03 1.04 0.03 0.09 5.16 1.02 0.09 0.13 2.66 0.09 0.05 1.06 0.07 0.89 0.05 0.12 1.10 0.16 0.06 1.01 0.13 1.00 0.14 0.98 0.09 2.92 1.28 0.03 2.95 0.98 0.16 0.08 0.95 0.96 1.09 0.08 1.07 1.01 0.16 0.06 4.52 0.12 1.03 0.07 0.09 1.03 0.14 0.03 1.01 1.99 1.05 0.14 1.03 0.13 0.03 1.10 0.10 0.96 0.11 0.99 0.12 0.05 0.94 2.83 0.14 0.12 0.96 0.00 1.00 0.11 0.14 1.98 0.08 0.11 1.04 0.01 0.11 2.03 0.15 2.05 0.10 0.03 0.93 0.01 0.08 0.12 0.00 0.16 0.05 0.07 0.08 0.11 0.07 0.05 0.04 0.10 0.05 0.05 0.03 0.07 0.03 0.04 0.04 0.06 0.03 0.05 0.04 0.09 0.03 0.08 0.03 0.07 0.02 0.05 0.02 0.06 0.01 0.05 0.04 0.06 0.02 0.04 0.04 0.04 0.03 0.03 0.06 0.06 0.03 0.02 0.02 0.08 0.03 0.01 0.01 0.06 0.03 0.01 0.03 0.04 0.02 0.00 0.02 0.05 0.00 0.02 0.02 0.03 0.00 0.02 0.02 0.04 0.01 0.00 0.01 0.05")
self.assertEqual(flow2_trimmed.Bases,
"CAATTATTTCCATAGCTTGGGTAGTGTCAATAATGCTGCTATGAACATGGGAGTACAAATATTCTTCAAGATACTGATCTCATTTCCTTTAGATATATACCCAGAAGTGAAATTCCTGGATCACATAGTAGTTCTATTTTTATTTGATGAGAAACTTTATACTATTTTTCATAActgagcgggctggcaaggc")
#trimming at the end of the flow cycle works
flow3_trimmed = flow3.getPrimerTrimmedFlowgram(primerseq="TCAG"+"ATTAGATACCCNGGTAGG")
self.assertEqual(str(flow3_trimmed), "0.05 0.05 2.04 0.10 0.03 1.06 1.05 1.01 0.07 0.09 2.07 1.01 0.93 2.88 1.06 1.95 1.00 0.05 0.05 2.97 0.09 0.00 0.93 1.01 0.06 0.05 0.99 0.09 0.98 1.01 0.03 1.02 1.92 0.07 0.01 1.03 1.01 0.01 0.05 0.96 0.09 0.05 0.98 1.07 0.02 2.02 2.05 0.09 1.87 0.12 2.15 0.05 0.13 0.92 1.05 1.96 3.01 0.13 0.04 1.05 0.96 0.05 0.05 0.95 0.12 0.01 1.00 2.02 0.03 0.03 0.99 1.01 0.05 0.06 0.98 0.13 0.06 0.97 0.11 1.01 0.08 0.12 1.02 0.12 1.02 2.19 1.03 1.01 0.08 0.11 0.96 0.09 0.08 1.01 0.08 0.06 2.10 2.11 0.12 1.04 0.13 0.09 0.94 1.03 0.08 0.05 3.06 0.12 1.00 0.03 0.09 0.95 0.10 0.03 2.09 0.21 0.99 0.06 0.11 4.06 0.10 1.04 0.04 1.05 1.05 1.04 1.02 0.97 0.13 0.93 0.10 0.12 1.08 0.12 0.99 1.06 0.10 0.11 0.98 0.10 0.02 2.01 0.10 1.01 0.09 0.96 0.07 0.11 2.03 4.12 1.05 0.08 1.01 0.04 0.98 0.14 0.12 2.96 0.13 1.98 0.12 2.08 0.10 0.12 1.99 0.13 0.07 0.98 0.03 0.93 0.86 4.10 0.13 0.10 3.99 1.13 0.07 0.06 1.07 0.09 0.05 1.03 1.12 0.13 0.05 2.01 0.08 0.80 0.05 0.11 0.98 0.13 0.04 1.01 0.07 1.02 0.07 0.11 1.07 2.19 0.06 0.97 0.11 1.03 0.05 0.11 1.05 0.14 0.06 1.03 0.13 0.10 0.97 0.16 0.13 1.00 0.13 0.06 1.02 2.15 0.02 0.16 0.95 0.09 2.06 2.12 0.07 0.07 2.08 0.12 0.97 1.00 0.03 0.99 1.02 1.01 0.03 0.15 0.90 0.07 0.01 2.00 1.01 1.00 0.06 0.11 1.08 1.00 0.03 1.99 0.03 1.00 0.02 1.85 1.93 0.14 1.97 0.91 1.83 0.06 0.04 1.97 0.05 2.08 0.04 0.06 1.05 0.05 2.13 0.16 0.09 1.17 0.01 1.01 1.07 0.09 0.14 0.91 0.06 0.08 1.03 1.04 0.08 0.05 1.05 1.03 1.16 0.06 0.05 1.01 0.06 2.15 0.06 1.99 0.13 0.04 1.08 0.97 0.11 0.07 1.05 0.08 0.07 2.13 0.14 0.09 1.10 0.15 0.00 1.02 0.07 1.05 0.05 0.95 0.09 1.00 0.15 0.95 0.08 0.15 1.11 0.07 0.12 1.05 1.06 0.09 1.03 0.07 0.11 1.01 0.05 0.05 1.05 0.98 0.00 0.93 0.08 0.12 1.85 1.11 0.10 0.07 1.00 0.01 0.10 1.87 0.05 2.14 1.10 0.03 1.06 0.10 0.91 0.10 0.06 1.05 1.02 1.02 0.07 0.06 0.98 0.95 1.09 0.06 0.14 0.97 0.04 2.44")
self.assertEqual(flow3_trimmed.Bases,
"CCACGCCGTAAACGGTGGGCGCTAGTTGTGCGAACCTTCCACGGTTTGTGCGGCGCAGCTAACGCATTAAGCGCCCTGCCTGGGGAGTACGATCGCAAGATTAAAACTCAAAGGAATTGACGGGGCCCCGCACAAGCAGCGGAGCATGCGGCTTAATTCGACGCAACGCGAAGAACCTTACCAAGGCTTGACATATACAGGAATATGGCAGAGATGTCATAGCCGCAAGGTCTGTATACAGG")
flow3_trimmed = flow3.getPrimerTrimmedFlowgram(primerseq="TCAG"+"ATTAGATACCCNGGTAG")
self.assertEqual(str(flow3_trimmed), "0.00\t0.00\t0.00 1.10 0.05 0.05 2.04 0.10 0.03 1.06 1.05 1.01 0.07 0.09 2.07 1.01 0.93 2.88 1.06 1.95 1.00 0.05 0.05 2.97 0.09 0.00 0.93 1.01 0.06 0.05 0.99 0.09 0.98 1.01 0.03 1.02 1.92 0.07 0.01 1.03 1.01 0.01 0.05 0.96 0.09 0.05 0.98 1.07 0.02 2.02 2.05 0.09 1.87 0.12 2.15 0.05 0.13 0.92 1.05 1.96 3.01 0.13 0.04 1.05 0.96 0.05 0.05 0.95 0.12 0.01 1.00 2.02 0.03 0.03 0.99 1.01 0.05 0.06 0.98 0.13 0.06 0.97 0.11 1.01 0.08 0.12 1.02 0.12 1.02 2.19 1.03 1.01 0.08 0.11 0.96 0.09 0.08 1.01 0.08 0.06 2.10 2.11 0.12 1.04 0.13 0.09 0.94 1.03 0.08 0.05 3.06 0.12 1.00 0.03 0.09 0.95 0.10 0.03 2.09 0.21 0.99 0.06 0.11 4.06 0.10 1.04 0.04 1.05 1.05 1.04 1.02 0.97 0.13 0.93 0.10 0.12 1.08 0.12 0.99 1.06 0.10 0.11 0.98 0.10 0.02 2.01 0.10 1.01 0.09 0.96 0.07 0.11 2.03 4.12 1.05 0.08 1.01 0.04 0.98 0.14 0.12 2.96 0.13 1.98 0.12 2.08 0.10 0.12 1.99 0.13 0.07 0.98 0.03 0.93 0.86 4.10 0.13 0.10 3.99 1.13 0.07 0.06 1.07 0.09 0.05 1.03 1.12 0.13 0.05 2.01 0.08 0.80 0.05 0.11 0.98 0.13 0.04 1.01 0.07 1.02 0.07 0.11 1.07 2.19 0.06 0.97 0.11 1.03 0.05 0.11 1.05 0.14 0.06 1.03 0.13 0.10 0.97 0.16 0.13 1.00 0.13 0.06 1.02 2.15 0.02 0.16 0.95 0.09 2.06 2.12 0.07 0.07 2.08 0.12 0.97 1.00 0.03 0.99 1.02 1.01 0.03 0.15 0.90 0.07 0.01 2.00 1.01 1.00 0.06 0.11 1.08 1.00 0.03 1.99 0.03 1.00 0.02 1.85 1.93 0.14 1.97 0.91 1.83 0.06 0.04 1.97 0.05 2.08 0.04 0.06 1.05 0.05 2.13 0.16 0.09 1.17 0.01 1.01 1.07 0.09 0.14 0.91 0.06 0.08 1.03 1.04 0.08 0.05 1.05 1.03 1.16 0.06 0.05 1.01 0.06 2.15 0.06 1.99 0.13 0.04 1.08 0.97 0.11 0.07 1.05 0.08 0.07 2.13 0.14 0.09 1.10 0.15 0.00 1.02 0.07 1.05 0.05 0.95 0.09 1.00 0.15 0.95 0.08 0.15 1.11 0.07 0.12 1.05 1.06 0.09 1.03 0.07 0.11 1.01 0.05 0.05 1.05 0.98 0.00 0.93 0.08 0.12 1.85 1.11 0.10 0.07 1.00 0.01 0.10 1.87 0.05 2.14 1.10 0.03 1.06 0.10 0.91 0.10 0.06 1.05 1.02 1.02 0.07 0.06 0.98 0.95 1.09 0.06 0.14 0.97 0.04 2.44")
self.assertEqual(flow3_trimmed.Bases,
"GCCACGCCGTAAACGGTGGGCGCTAGTTGTGCGAACCTTCCACGGTTTGTGCGGCGCAGCTAACGCATTAAGCGCCCTGCCTGGGGAGTACGATCGCAAGATTAAAACTCAAAGGAATTGACGGGGCCCCGCACAAGCAGCGGAGCATGCGGCTTAATTCGACGCAACGCGAAGAACCTTACCAAGGCTTGACATATACAGGAATATGGCAGAGATGTCATAGCCGCAAGGTCTGTATACAGG")
def test_createFlowHeader(self):
"""header_info dict turned into flowgram header"""
f = Flowgram('0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0', Name='a',
header_info = {'Bases':'TACCCCTTGG','Name Length':'14'})
self.assertEqual(f.createFlowHeader(),
""">a\n Name Length:\t14\nBases:\tTACCCCTTGG\nFlowgram:\t0.5\t1.0\t4.0\t0.0\t1.5\t0.0\t0.0\t2.0\n""")
def test_build_averaged_flowgram(self):
f1 = [0.3, 1.1, 4.0 , 0.01, 0.8, 0.0, 0.0, 2.0]
f2 = [0.6, 0.9, 4.05, 0.1, 1.2, 0.1, 0.4]
f3 = [0.4, 1.2, 4.05, 0.2, 1.3, 0.2]
f4 = [0.7, 1.0, 4.0 , 0.02, 1.5]
flowgrams = [f1,f2,f3,f4]
self.assertFloatEqual(build_averaged_flowgram(flowgrams),
[0.5, 1.05, 4.03, 0.08, 1.2, 0.1, 0.2, 2.0])
self.assertFloatEqual(build_averaged_flowgram([f1,f1,f1,f1,f1,f1]),
[0.3, 1.1, 4.0 , 0.01, 0.8, 0.0, 0.0, 2.0])
def setUp(self):
"""Define some standard data"""
self.rec = """Common Header:
Magic Number: 0x2E736666
Version: 0001
Index Offset: 96099976
Index Length: 1158685
# of Reads: 57902
Header Length: 440
Key Length: 4
# of Flows: 400
Flowgram Code: 1
Flow Chars: TACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACG
Key Sequence: TCAG
>FIQU8OX05GCVRO
Run Prefix: R_2008_10_15_16_11_02_
Region #: 5
XY Location: 2489_3906
Run Name: R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford
Analysis Name: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Full Path: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Read Header Len: 32
Name Length: 14
# of Bases: 104
Clip Qual Left: 5
Clip Qual Right: 85
Clip Adap Left: 0
Clip Adap Right: 0
Flowgram: 1.06 0.08 1.04 0.08 0.05 0.94 0.10 2.01 0.10 0.07 0.96 0.09 1.04 1.96 1.07 0.10 1.01 0.13 0.08 1.01 1.06 1.83 2.89 0.18 0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04
Flow Indexes: 1 3 6 8 8 11 13 14 14 15 17 20 21 22 22 23 23 23 25 27 29 29 32 32 35 38 39 39 39 42 43 45 46 46 46 47 48 51 51 54 54 57 59 61 61 64 67 69 72 72 74 76 77 80 81 81 81 82 83 83 86 88 88 91 94 95 95 95 98 100 103 106 106 109 112 113 116 118 118 121 122 124 125 127 130 131 133 136 138 140 143 144 144 144 147 149 152 152 155 158 158 160 160 163
Bases: tcagGCTAACTGTAACCCTCTTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCActgagcgggctggcaaggc
Quality Scores: 37 37 37 37 37 37 37 37 37 37 37 37 37 40 40 40 40 37 37 37 37 37 39 39 39 39 24 24 24 37 34 28 24 24 24 28 34 39 39 39 39 39 39 39 39 39 39 39 39 40 40 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37
>FIQU8OX05F8ILF
Run Prefix: R_2008_10_15_16_11_02_
Region #: 5
XY Location: 2440_0913
Run Name: R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford
Analysis Name: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Full Path: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Read Header Len: 32
Name Length: 14
# of Bases: 206
Clip Qual Left: 5
Clip Qual Right: 187
Clip Adap Left: 0
Clip Adap Right: 0
Flowgram: 1.04 0.00 1.01 0.00 0.00 1.00 0.00 1.00 0.00 1.05 0.00 0.91 0.10 1.07 0.95 1.01 0.00 0.06 0.93 0.02 0.03 1.06 1.18 0.09 1.00 0.05 0.90 0.11 0.07 1.99 0.11 0.02 1.96 1.04 0.13 0.01 2.83 0.10 1.97 0.06 0.11 1.04 0.13 0.03 0.98 1.15 0.07 1.00 0.07 0.08 0.98 0.11 1.92 0.05 0.04 2.96 1.02 1.02 0.04 0.93 1.00 0.13 0.04 1.00 1.03 0.08 0.97 0.13 0.11 1.88 0.09 0.05 1.02 1.89 0.07 0.11 0.98 0.05 0.07 1.01 0.08 0.05 1.01 0.13 1.00 0.07 0.10 1.04 0.10 0.04 0.98 0.12 1.03 0.96 0.11 0.07 1.00 0.09 0.03 1.03 0.11 1.95 1.06 0.13 0.05 1.00 0.13 0.11 1.00 0.09 0.03 2.89 0.08 0.95 0.09 1.03 1.02 1.05 1.07 0.08 0.12 2.81 0.08 0.08 1.00 1.07 0.07 0.05 1.86 0.12 0.98 0.06 2.00 0.11 1.02 0.11 0.08 1.88 0.13 1.03 0.13 0.98 0.15 0.11 1.03 1.03 1.04 0.18 0.98 0.13 0.15 1.04 0.11 1.01 0.13 0.06 1.01 0.06 1.02 0.08 0.99 0.14 0.99 0.09 0.05 1.09 0.04 0.07 2.96 0.09 2.03 0.13 2.96 1.13 0.08 1.03 0.07 0.99 0.11 0.05 1.05 1.04 0.09 0.07 1.00 1.03 0.09 0.06 1.06 1.04 2.94 0.18 0.06 0.93 0.10 1.10 0.11 2.02 0.17 1.00 1.03 0.06 0.11 0.96 0.04 3.00 0.11 0.07 1.99 0.10 2.03 0.12 0.97 0.16 0.01 2.09 0.14 1.04 0.16 0.06 1.03 0.14 1.12 0.12 0.05 0.96 1.01 0.10 0.14 0.94 0.03 0.12 1.10 0.92 0.09 1.10 1.04 1.02 0.12 0.97 2.00 0.15 1.08 0.04 1.03 1.04 0.03 0.09 5.16 1.02 0.09 0.13 2.66 0.09 0.05 1.06 0.07 0.89 0.05 0.12 1.10 0.16 0.06 1.01 0.13 1.00 0.14 0.98 0.09 2.92 1.28 0.03 2.95 0.98 0.16 0.08 0.95 0.96 1.09 0.08 1.07 1.01 0.16 0.06 4.52 0.12 1.03 0.07 0.09 1.03 0.14 0.03 1.01 1.99 1.05 0.14 1.03 0.13 0.03 1.10 0.10 0.96 0.11 0.99 0.12 0.05 0.94 2.83 0.14 0.12 0.96 0.00 1.00 0.11 0.14 1.98 0.08 0.11 1.04 0.01 0.11 2.03 0.15 2.05 0.10 0.03 0.93 0.01 0.08 0.12 0.00 0.16 0.05 0.07 0.08 0.11 0.07 0.05 0.04 0.10 0.05 0.05 0.03 0.07 0.03 0.04 0.04 0.06 0.03 0.05 0.04 0.09 0.03 0.08 0.03 0.07 0.02 0.05 0.02 0.06 0.01 0.05 0.04 0.06 0.02 0.04 0.04 0.04 0.03 0.03 0.06 0.06 0.03 0.02 0.02 0.08 0.03 0.01 0.01 0.06 0.03 0.01 0.03 0.04 0.02 0.00 0.02 0.05 0.00 0.02 0.02 0.03 0.00 0.02 0.02 0.04 0.01 0.00 0.01 0.05
Flow Indexes: 1 3 6 8 10 12 14 15 16 19 22 23 25 27 30 30 33 33 34 37 37 37 39 39 42 45 46 48 51 53 53 56 56 56 57 58 60 61 64 65 67 70 70 73 74 74 77 80 83 85 88 91 93 94 97 100 102 102 103 106 109 112 112 112 114 116 117 118 119 122 122 122 125 126 129 129 131 133 133 135 138 138 140 142 145 146 147 149 152 154 157 159 161 163 166 169 169 169 171 171 173 173 173 174 176 178 181 182 185 186 189 190 191 191 191 194 196 198 198 200 201 204 206 206 206 209 209 211 211 213 216 216 218 221 223 226 227 230 233 234 236 237 238 240 241 241 243 245 246 249 249 249 249 249 250 253 253 253 256 258 261 264 266 268 270 270 270 271 273 273 273 274 277 278 279 281 282 285 285 285 285 285 287 290 293 294 294 295 297 300 302 304 307 308 308 308 311 313 316 316 319 322 322 324 324 327
Bases: tcagAGACGCACTCAATTATTTCCATAGCTTGGGTAGTGTCAATAATGCTGCTATGAACATGGGAGTACAAATATTCTTCAAGATACTGATCTCATTTCCTTTAGATATATACCCAGAAGTGAAATTCCTGGATCACATAGTAGTTCTATTTTTATTTGATGAGAAACTTTATACTATTTTTCATAActgagcgggctggcaaggc
Quality Scores: 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 38 38 38 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 34 34 34 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 36 36 36 36 36 38 25 25 25 38 37 37 37 37 37 37 33 33 34 37 37 37 37 37 37 37 38 34 20 20 26 26 20 34 38 37 37 37 37 37 37 37 37 37 38 38 38 37 37 37 37 37 37 37 37 37 37
>FIQU8OX06G9PCS
Run Prefix: R_2008_10_15_16_11_02_
Region #: 6
XY Location: 2863_3338
Run Name: R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford
Analysis Name: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Full Path: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Read Header Len: 32
Name Length: 14
# of Bases: 264
Clip Qual Left: 5
Clip Qual Right: 264
Clip Adap Left: 0
Clip Adap Right: 0
Flowgram: 1.04 0.05 1.01 0.07 0.05 0.99 0.03 1.05 0.04 1.05 0.05 0.06 2.05 1.13 0.03 1.00 0.08 1.07 0.09 0.05 1.02 1.11 3.06 0.09 0.04 1.03 0.13 1.97 1.02 1.07 0.06 2.10 0.05 0.05 2.04 0.10 0.03 1.06 1.05 1.01 0.07 0.09 2.07 1.01 0.93 2.88 1.06 1.95 1.00 0.05 0.05 2.97 0.09 0.00 0.93 1.01 0.06 0.05 0.99 0.09 0.98 1.01 0.03 1.02 1.92 0.07 0.01 1.03 1.01 0.01 0.05 0.96 0.09 0.05 0.98 1.07 0.02 2.02 2.05 0.09 1.87 0.12 2.15 0.05 0.13 0.92 1.05 1.96 3.01 0.13 0.04 1.05 0.96 0.05 0.05 0.95 0.12 0.01 1.00 2.02 0.03 0.03 0.99 1.01 0.05 0.06 0.98 0.13 0.06 0.97 0.11 1.01 0.08 0.12 1.02 0.12 1.02 2.19 1.03 1.01 0.08 0.11 0.96 0.09 0.08 1.01 0.08 0.06 2.10 2.11 0.12 1.04 0.13 0.09 0.94 1.03 0.08 0.05 3.06 0.12 1.00 0.03 0.09 0.95 0.10 0.03 2.09 0.21 0.99 0.06 0.11 4.06 0.10 1.04 0.04 1.05 1.05 1.04 1.02 0.97 0.13 0.93 0.10 0.12 1.08 0.12 0.99 1.06 0.10 0.11 0.98 0.10 0.02 2.01 0.10 1.01 0.09 0.96 0.07 0.11 2.03 4.12 1.05 0.08 1.01 0.04 0.98 0.14 0.12 2.96 0.13 1.98 0.12 2.08 0.10 0.12 1.99 0.13 0.07 0.98 0.03 0.93 0.86 4.10 0.13 0.10 3.99 1.13 0.07 0.06 1.07 0.09 0.05 1.03 1.12 0.13 0.05 2.01 0.08 0.80 0.05 0.11 0.98 0.13 0.04 1.01 0.07 1.02 0.07 0.11 1.07 2.19 0.06 0.97 0.11 1.03 0.05 0.11 1.05 0.14 0.06 1.03 0.13 0.10 0.97 0.16 0.13 1.00 0.13 0.06 1.02 2.15 0.02 0.16 0.95 0.09 2.06 2.12 0.07 0.07 2.08 0.12 0.97 1.00 0.03 0.99 1.02 1.01 0.03 0.15 0.90 0.07 0.01 2.00 1.01 1.00 0.06 0.11 1.08 1.00 0.03 1.99 0.03 1.00 0.02 1.85 1.93 0.14 1.97 0.91 1.83 0.06 0.04 1.97 0.05 2.08 0.04 0.06 1.05 0.05 2.13 0.16 0.09 1.17 0.01 1.01 1.07 0.09 0.14 0.91 0.06 0.08 1.03 1.04 0.08 0.05 1.05 1.03 1.16 0.06 0.05 1.01 0.06 2.15 0.06 1.99 0.13 0.04 1.08 0.97 0.11 0.07 1.05 0.08 0.07 2.13 0.14 0.09 1.10 0.15 0.00 1.02 0.07 1.05 0.05 0.95 0.09 1.00 0.15 0.95 0.08 0.15 1.11 0.07 0.12 1.05 1.06 0.09 1.03 0.07 0.11 1.01 0.05 0.05 1.05 0.98 0.00 0.93 0.08 0.12 1.85 1.11 0.10 0.07 1.00 0.01 0.10 1.87 0.05 2.14 1.10 0.03 1.06 0.10 0.91 0.10 0.06 1.05 1.02 1.02 0.07 0.06 0.98 0.95 1.09 0.06 0.14 0.97 0.04 2.44
Flow Indexes: 1 3 6 8 10 13 13 14 16 18 21 22 23 23 23 26 28 28 29 30 32 32 35 35 38 39 40 43 43 44 45 46 46 46 47 48 48 49 52 52 52 55 56 59 61 62 64 65 65 68 69 72 75 76 78 78 79 79 81 81 83 83 86 87 88 88 89 89 89 92 93 96 99 100 100 103 104 107 110 112 115 117 118 118 119 120 123 126 129 129 130 130 132 135 136 139 139 139 141 144 147 147 149 152 152 152 152 154 156 157 158 159 160 162 165 167 168 171 174 174 176 178 181 181 182 182 182 182 183 185 187 190 190 190 192 192 194 194 197 197 200 202 203 204 204 204 204 207 207 207 207 208 211 214 215 218 218 220 223 226 228 231 232 232 234 236 239 242 245 248 251 252 252 255 257 257 258 258 261 261 263 264 266 267 268 271 274 274 275 276 279 280 282 282 284 286 286 287 287 289 289 290 291 291 294 294 296 296 299 301 301 304 306 307 310 313 314 317 318 319 322 324 324 326 326 329 330 333 336 336 339 342 344 346 348 350 353 356 357 359 362 365 366 368 371 371 372 375 378 378 380 380 381 383 385 388 389 390 393 394 395 398 400 400
Bases: tcagATTAGATACCCAGGTAGGCCACGCCGTAAACGGTGGGCGCTAGTTGTGCGAACCTTCCACGGTTTGTGCGGCGCAGCTAACGCATTAAGCGCCCTGCCTGGGGAGTACGATCGCAAGATTAAAACTCAAAGGAATTGACGGGGCCCCGCACAAGCAGCGGAGCATGCGGCTTAATTCGACGCAACGCGAAGAACCTTACCAAGGCTTGACATATACAGGAATATGGCAGAGATGTCATAGCCGCAAGGTCTGTATACAGG
Quality Scores: 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 37 37 37 37 37 37 37 37 37 40 40 38 38 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 40 40 40 37 37 37 37 37 37 37 37 38 38 40 40 40 40 40 38 38 38 38 38 40 40 38 38 38 38 38 40 40 40 40 38 38 38 38 38 38 31 30 30 30 32 31 32 31 32 31 31 28 25 21 20
""".split('\n')
flows, head = parse_sff(self.rec)
self.flows = list(flows)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_flowgram_collection.py 000644 000765 000024 00000110425 12024702176 025221 0 ustar 00jrideout staff 000000 000000 __author__ = "Julia Goodrich"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jens Reeder","Julia Goodrich"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Julia Goodrich"
__email__ = "julia.goodrich@colorado.edu"
__Status__ = "Development"
from cogent.util.unit_test import TestCase, main
from types import GeneratorType
from numpy import array, transpose
from cogent.core.sequence import Sequence
from cogent.parse.flowgram_collection import FlowgramCollection, flows_from_array,\
flows_from_generic,flows_from_kv_pairs,flows_from_empty,flows_from_dict,\
flows_from_sff,assign_sequential_names,flows_from_flowCollection,\
pick_from_prob_density, seqs_to_flows
from cogent.parse.flowgram import Flowgram
from cogent.core.alignment import SequenceCollection
from tempfile import mktemp
from os import remove
class flowgram_tests(TestCase):
"""Tests of top-level functions."""
def test_flows_from_array(self):
"""flows_from_array should return chars, and successive indices."""
a = array([[0,1,2],[2,1,0]]) #three 2-char seqs
obs_a, obs_labels, obs_info = flows_from_array(a)
#note transposition
self.assertEqual(obs_a, [array([0,2]), array([1,1]), array([2,0])])
self.assertEqual(obs_labels, None)
self.assertEqual(obs_info, None)
def test_flows_from_generic(self):
"""flows_from_flow should initialize from list of flowgram objects"""
c = Flowgram('0.0 1.1 3.0 1.0', Name='a')
b = Flowgram('0.5 1.0 4.0 0.0', Name = 'b')
obs_a, obs_labels, obs_info = flows_from_generic([c,b])
self.assertEqual(map(str,obs_a), ['0.0\t1.1\t3.0\t1.0',
'0.5\t1.0\t4.0\t0.0'])
self.assertEqual(obs_labels, ['a','b'])
self.assertEqual(obs_info, [None,None])
f = ['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0']
obs_a, obs_labels, obs_info = flows_from_generic(f)
self.assertEqual(map(str,obs_a), ['0.0 1.1 3.0 1.0',
'0.5 1.0 4.0 0.0'])
self.assertEqual(obs_labels, [None,None])
self.assertEqual(obs_info, [None,None])
def test_flows_from_flowCollection(self):
"""flows_from_flowCollection should init from existing collection"""
c = FlowgramCollection({'a':'0.0 1.1 3.0 1.0','b':'0.5 1.0 4.0 0.0'})
obs_a, obs_labels, obs_info = flows_from_flowCollection(c)
self.assertEqual(map(str,obs_a), ['0.0\t1.1\t3.0\t1.0',
'0.5\t1.0\t4.0\t0.0'])
self.assertEqual(obs_labels, ['a','b'])
self.assertEqual(obs_info, [None,None])
def test_flows_from_kv_pairs(self):
"""seqs_from_kv_pairs should initialize from key-value pairs"""
c = [['a','0.0 1.1 3.0 1.0'],['b','0.5 1.0 4.0 0.0']]
obs_a, obs_labels, obs_info = flows_from_kv_pairs(c)
self.assertEqual(map(str,obs_a), ['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0'])
self.assertEqual(obs_labels, ['a','b'])
self.assertEqual(obs_info, [None,None])
c =[['a',Flowgram('0.0 1.1 3.0 1.0')],['b',Flowgram('0.5 1.0 4.0 0.0')]]
obs_a, obs_labels, obs_info = flows_from_kv_pairs(c)
self.assertEqual(map(str,obs_a), ['0.0\t1.1\t3.0\t1.0','0.5\t1.0\t4.0\t0.0'])
self.assertEqual(obs_labels, ['a','b'])
self.assertEqual(obs_info, [None,None])
def test_flows_from_empty(self):
"""flowss_from_empty should always raise ValueError"""
self.assertRaises(ValueError, flows_from_empty, 'xyz')
def test_flows_from_dict(self):
"""flows_from_dict should init from dictionary"""
c = {'a':'0.0 1.1 3.0 1.0','b':'0.5 1.0 4.0 0.0'}
obs_a, obs_labels, obs_info = flows_from_dict(c)
self.assertEqual(map(str,obs_a), ['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0'])
self.assertEqual(obs_labels, ['a','b'])
self.assertEqual(obs_info, [None,None])
c ={'a':Flowgram('0.0 1.1 3.0 1.0'),'b':Flowgram('0.5 1.0 4.0 0.0')}
obs_a, obs_labels, obs_info = flows_from_dict(c)
self.assertEqual(map(str,obs_a), ['0.0\t1.1\t3.0\t1.0','0.5\t1.0\t4.0\t0.0'])
self.assertEqual(obs_labels, ['a','b'])
self.assertEqual(obs_info, [None,None])
def test_pick_from_prob_density(self):
"""Should take bin probabilitys and bin size and return random"""
i = pick_from_prob_density([0,1.0,0,0],1)
self.assertEqual(i,1)
i = pick_from_prob_density([1.0,0,0,0],.01)
self.assertEqual(i,0.0)
def test_seqs_to_flows(self):
"""seqs_to_flows should take a list of seqs and probs and return """
seqs = [('a','ATCGT'), ('b','ACCCAG'), ('c','GTAATG')]
a = SequenceCollection(seqs)
flows = seqs_to_flows(a.items())
assert isinstance(flows,FlowgramCollection)
for f,i in zip(flows,['0.0 1.0 0.0 0.0 1.0 0.0 1.0 1.0 1.0 0.0 0.0 0.0',
'0.0 1.0 3.0 0.0 0.0 1.0 0.0 1.0',
'0.0 0.0 0.0 1.0 1.0 2.0 0.0 0.0 1.0 0.0 0.0 1.0']):
self.assertEqual(f,i)
probs ={0:[1.0,0,0,0,0],1:[0,1.0,0,0,0],2:[0,0,1.0,0,0],3:[0,0,0,1.0,0]}
flows = seqs_to_flows(a.items(), probs = probs, bin_size = 1.0)
assert isinstance(flows,FlowgramCollection)
for f,i in zip(flows,['0.0 1.0 0.0 0.0 1.0 0.0 1.0 1.0 1.0 0.0 0.0 0.0',
'0.0 1.0 3.0 0.0 0.0 1.0 0.0 1.0',
'0.0 0.0 0.0 1.0 1.0 2.0 0.0 0.0 1.0 0.0 0.0 1.0']):
self.assertEqual(f,i)
class FlowgramCollectionTests(TestCase):
"""Tests sff parser functions"""
Class = FlowgramCollection
def test_guess_input_type(self):
""" _guess_input_type should figure out data type correctly"""
git = self.unordered._guess_input_type
self.assertEqual(git(self.unordered), 'flowcoll')
self.assertEqual(git(['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0']), 'generic')
self.assertEqual(git([Flowgram('0.0 1.1 3.0 1.0'),
Flowgram('0.5 1.0 4.0 0.0')]), 'generic')
self.assertEqual(git([[1,2],[4,5]]), 'kv_pairs') #precedence over generic
self.assertEqual(git([('a',Flowgram('0.0 1.1 3.0 1.0')),
('b',Flowgram('0.5 1.0 4.0 0.0'))]), 'kv_pairs')
self.assertEqual(git([[1,2,3],[4,5,6]]), 'generic')
self.assertEqual(git(array([[1,2,3],[4,5,6]])), 'array')
self.assertEqual(git({'a':'0.0 1.1 3.0 1.0'}), 'dict')
self.assertEqual(git({'a':Flowgram('0.0 1.1 3.0 1.0')}), 'dict')
self.assertEqual(git([]), 'empty')
self.assertEqual(git('Common Header'), 'sff')
def test_init_pairs(self):
"""FlowgramCollection init from list of (key,val) should work"""
Flows = [['a','0.0 1.1 3.0 1.0'],['b','0.5 1.0 4.0 0.0']]
a = self.Class(Flows)
self.assertEqual(len(a.NamedFlows), 2)
self.assertEqual(a.NamedFlows['a'], '0.0 1.1 3.0 1.0')
self.assertEqual(a.NamedFlows['b'], '0.5 1.0 4.0 0.0')
self.assertEqual(a.Names, ['a','b'])
self.assertEqual(list(a.flows), ['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0'])
def test_init_aln(self):
"""FlowgramCollection should init from existing Collections"""
start = self.Class([['a','0.0 1.1 3.0 1.0'],['b','0.5 1.0 4.0 0.0']])
exp = self.Class([['a','0.0 1.1 3.0 1.0'],['b','0.5 1.0 4.0 0.0']])
f = self.Class(start)
self.assertEqual(f, exp)
test_init_aln.__doc__ = Class.__name__ + test_init_aln.__doc__
def test_init_dict(self):
"""FlowgramCollection init from dict should work as expected"""
d = {'a':'0.0 1.1 3.0 1.0','b':'0.5 1.0 4.0 0.0'}
a = self.Class(d)
self.assertEqual(a, d)
self.assertEqual(a.NamedFlows.items(), d.items())
def test_init_name_mapped(self):
"""FlowgramCollection init should allow name mapping function"""
d = {'a':'0.0 1.1 3.0 1.0','b':'0.5 1.0 4.0 0.0'}
f = lambda x: x.upper()
a = self.Class(d, name_conversion_f=f)
self.assertNotEqual(a, d)
self.assertNotEqual(a.NamedFlows.items(), d.items())
d_upper = {'A':'0.0 1.1 3.0 1.0','B':'0.5 1.0 4.0 0.0'}
self.assertEqual(a, d_upper)
self.assertEqual(a.NamedFlows.items(), d_upper.items())
def test_init_flow(self):
"""FlowgramCollection init from list of flowgrams should use indices
as keys"""
f1 = Flowgram('0.0 1.1 3.0 1.0')
f2 = Flowgram('0.5 1.0 4.0 0.0')
flows = [f1,f2]
a = self.Class(flows)
self.assertEqual(len(a.NamedFlows), 2)
self.assertEqual(a.NamedFlows['seq_0'], '0.0 1.1 3.0 1.0')
self.assertEqual(a.NamedFlows['seq_1'], '0.5 1.0 4.0 0.0')
self.assertEqual(a.Names, ['seq_0','seq_1'])
self.assertEqual(list(a.Flows), ['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0'])
def test_flows_from_sff(self):
"""flow_from_sff should init from sff iterator"""
s = self.rec
f = self.Class(s)
self.assertEqual(f.NamedFlows['FIQU8OX05GCVRO'], self.flow)
def test_init_duplicate_keys(self):
"""FlowgramCollection init from kv pairs should fail on dup. keys"""
f = [['a','0.0 1.1 3.0 1.0'],['b','0.5 1.0 4.0 0.0'],
['b','1.5 2.0 0.0 0.5']]
self.assertRaises(ValueError, self.Class, f)
self.assertEqual(self.Class(f, remove_duplicate_names=True).Names,
['a','b'])
def test_init_ordered(self):
"""FlowgramCollection should iter over flows correctly, ordered too"""
first = self.ordered1
sec = self.ordered2
un = self.unordered
self.assertEqual(first.Names, ['a','b'])
self.assertEqual(sec.Names, ['b', 'a'])
self.assertEqual(un.Names, un.NamedFlows.keys())
first_list = list(first.flow_str)
sec_list = list(sec.flow_str)
un_list = list(un.flow_str)
self.assertEqual(first_list, ['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0'])
self.assertEqual(sec_list, ['0.5 1.0 4.0 0.0', '0.0 1.1 3.0 1.0'])
#check that the unordered seq matches one of the lists
self.assertTrue((un_list == first_list) or (un_list == sec_list))
self.assertNotEqual(first_list, sec_list)
def test_flow_str(self):
"""FlowgramCollection flow_str prop returns flows in correct order."""
first = self.ordered1
sec = self.ordered2
un = self.unordered
first_list = list(first.flow_str)
sec_list = list(sec.flow_str)
un_list = list(un.flow_str)
self.assertEqual(first_list, ['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0'])
self.assertEqual(sec_list, ['0.5 1.0 4.0 0.0', '0.0 1.1 3.0 1.0'])
#check that the unordered seq matches one of the lists
self.assertTrue((un_list == first_list) or (un_list == sec_list))
self.assertNotEqual(first_list, sec_list)
def test_iter(self):
"""FlowgramCollection __iter__ method should yield flows inorder"""
f = self.Class(['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0','1.5 0.0 2.0 1.0'], \
Names=['a','b','c'])
for i,b in zip(f,['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0',
'1.5 0.0 2.0 1.0']):
self.assertEqual(i,b)
def test_str(self):
"""FlowgramCollection __str__ should return sff format"""
a = [Flowgram('0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0', Name='a',
header_info = {'Bases':'TACCCCTTGG','Name Length':'14'}),
Flowgram('1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0', Name = 'b',
header_info = {'Bases':'TTATTTACCG','Name Length':'14'})]
f = FlowgramCollection(a, header_info = {'Flow Chars':'TACG'})
self.assertEqual(str(f), """Common Header:\n Flow Chars:\tTACG\n\n>a\n Name Length:\t14\nBases:\tTACCCCTTGG\nFlowgram:\t0.5\t1.0\t4.0\t0.0\t1.5\t0.0\t0.0\t2.0\n\n>b\n Name Length:\t14\nBases:\tTTATTTACCG\nFlowgram:\t1.5\t1.0\t0.0\t0.0\t2.5\t1.0\t2.0\t1.0\n""")
def test_len(self):
"""len(FlowgramCollection) returns length of longest sequence"""
a = [('a','0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0'),
('b','1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0'),
('c','2.5 0.0 4.0 0.0 0.5 1.0 0.0 1.0')]
f = FlowgramCollection(a)
self.assertEqual(len(f), 3)
def test_writeToFile(self):
"""FlowgramCollection.writeToFile should write in correct format"""
a = [Flowgram('0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0', Name='a',
header_info = {'Bases':'TACCCCTTGG','Name Length':'14'}),
Flowgram('1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0', Name = 'b',
header_info = {'Bases':'TTATTTACCG','Name Length':'14'})]
f = FlowgramCollection(a, header_info = {'Flow Chars':'TACG'})
fn = mktemp(suffix='.sff')
f.writeToFile(fn)
result = open(fn, 'U').read()
self.assertEqual(result, """Common Header:\n Flow Chars:\tTACG\n\n>a\n Name Length:\t14\nBases:\tTACCCCTTGG\nFlowgram:\t0.5\t1.0\t4.0\t0.0\t1.5\t0.0\t0.0\t2.0\n\n>b\n Name Length:\t14\nBases:\tTTATTTACCG\nFlowgram:\t1.5\t1.0\t0.0\t0.0\t2.5\t1.0\t2.0\t1.0\n""")
remove(fn)
def test_createCommonHeader(self):
"""create_commor_header should return lines for sff common header"""
a = [Flowgram('0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0', Name='a',
header_info = {'Bases':'TACCCCTTGG','Name Length':'14'}),
Flowgram('1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0', Name = 'b',
header_info = {'Bases':'TTATTTACCG','Name Length':'14'})]
f = FlowgramCollection(a, header_info = {'Flow Chars':'TACG'})
self.assertEqual('\n'.join(f.createCommonHeader()),
"""Common Header:\n Flow Chars:\tTACG""")
def test_toFasta(self):
"""FlowgramCollection should return correct FASTA string"""
f = self.Class( [ '0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0',
'1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0',
'2.5 0.0 4.0 0.0 0.5 1.0 0.0 1.0',
'0.0 1.0 0.0 3.0 1.5 1.0 1.0 2.0'
], header_info = {'Flow Chars':'TACG'})
self.assertEqual(f.toFasta(), '>seq_0\nTACCCCTTGG\n>seq_1\nTTATTTACCG\n>seq_2\nTTTCCCCTAG\n>seq_3\nAGGGTTACGG')
#NOTE THE FOLLOWING SURPRISING BEHAVIOR BECAUSE OF THE TWO-ITEM
#SEQUENCE RULE:
aln = self.Class(['0.5 1.0 0.0 0.0','0.0 1.0 1.0 0.0'],
header_info = {'Flow Chars':'TACG'})
self.assertEqual(aln.toFasta(), '>A\nC\n>T\nA')
def test_toPhylip(self):
"""FlowgramCollection should return PHYLIP string format correctly"""
f = self.Class( [ '0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0',
'1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0',
'2.5 0.0 4.0 0.0 0.5 1.0 0.0 1.0',
'0.0 1.0 0.0 3.0 1.5 1.0 1.0 2.0'
], header_info = {'Flow Chars':'TACG'})
phylip_str, id_map = f.toPhylip()
self.assertEqual(phylip_str, """4 10\nseq0000001 TACCCCTTGG\nseq0000002 TTATTTACCG\nseq0000003 TTTCCCCTAG\nseq0000004 AGGGTTACGG""")
self.assertEqual(id_map, {'seq0000004':'seq_3', 'seq0000001':'seq_0', \
'seq0000003': 'seq_2', 'seq0000002': 'seq_1'})
def test_toNexus(self):
"""FlowgramCollection should return correct Nexus string format"""
f = self.Class( [ '0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0',
'1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0',
'2.5 0.0 4.0 0.0 0.5 1.0 0.0 1.0',
'0.0 1.0 0.0 3.0 1.5 1.0 1.0 2.0'
], header_info = {'Flow Chars':'TACG'})
expect = '#NEXUS\n\nbegin data;\n dimensions ntax=4 nchar=10;\n'+\
' format datatype=dna interleave=yes missing=? gap=-;\n'+\
' matrix\n seq_1 TTATTTACCG\n seq_0'+\
' TACCCCTTGG\n seq_3 AGGGTTACGG\n '+\
' seq_2 TTTCCCCTAG\n\n ;\nend;'
self.assertEqual(f.toNexus('dna'), expect)
def test_toSequenceCollection(self):
"""toSequenceCollection should return sequence collection from flows"""
f = self.Class( [ '0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0',
'1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0',
'2.5 0.0 4.0 0.0 0.5 1.0 0.0 1.0',
'0.0 1.0 0.0 3.0 1.5 1.0 1.0 2.0'
], header_info = {'Flow Chars':'TACG'})
s = f.toSequenceCollection()
assert isinstance(s,SequenceCollection)
for i,j in zip(s.iterSeqs(),['TACCCCTTGG','TTATTTACCG','TTTCCCCTAG',
'AGGGTTACGG']):
self.assertEqual(i,j)
a = [Flowgram('0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0', Name='a',
header_info = {'Bases':'TACTTGG','Name Length':'14'}),
Flowgram('1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0', Name = 'b',
header_info = {'Bases':'TTATTTG','Name Length':'14'})]
f = self.Class(a)
s = f.toSequenceCollection(Bases = True)
assert isinstance(s,SequenceCollection)
for i,j in zip(s.iterSeqs(),['TACTTGG','TTATTTG']):
self.assertEqual(i,j)
def test_addFlows(self):
"""addFlows should return an alignment with the new sequences appended"""
a = [('s4', '0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0'),
('s3', '1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0')]
b = [('s1','2.5 0.0 4.0 0.0 0.5 1.0 0.0 1.0'),
('s2', '0.0 1.0 0.0 3.0 1.5 1.0 1.0 2.0')]
f1 = self.Class(a, header_info = {'Flow Chars':'TACG'})
f2 = self.Class(b, header_info = {'Flow Chars':'TACG'})
self.assertEqual(f1.addFlows(f2).toFasta(),
self.Class(a+b, header_info = {'Flow Chars':'TACG'}).toFasta())
def test_iterFlows(self):
"""FlowgramCollection iterFlows() method should support reordering"""
f = self.Class(['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0','1.5 0.0 2.0 1.0'], \
Names=['a','b','c'])
flows = map(str,list(f.iterFlows()))
self.assertEqual(flows, ['0.0\t1.1\t3.0\t1.0',
'0.5\t1.0\t4.0\t0.0','1.5\t0.0\t2.0\t1.0'])
flows = list(f.iterFlows(flow_order=['b','a','a']))
self.assertEqual(map(str,flows), ['0.5\t1.0\t4.0\t0.0',
'0.0\t1.1\t3.0\t1.0',
'0.0\t1.1\t3.0\t1.0'])
self.assertSameObj(flows[1], flows[2])
self.assertSameObj(flows[0], f.NamedFlows['b'])
def test_Items(self):
"""FlowgramCollection Items should iterate over items in specified order."""
#should work if one row
self.assertEqual(list(self.one_seq.Items), [0.0, 1.1, 3.0, 1.0])
#should take order into account
self.assertEqual(list(self.ordered1.Items),
[0.0, 1.1, 3.0, 1.0] + [0.5, 1.0, 4.0, 0.0])
self.assertEqual(list(self.ordered2.Items),
[0.5, 1.0, 4.0, 0.0] + [0.0, 1.1, 3.0, 1.0])
def test_takeFlows(self):
"""takeFlows should return new FlowgramCollection with selected seqs."""
f = self.Class(['0.0 1.1 3.0 1.0','0.5 1.0 4.0 0.0','1.5 0.0 2.0 1.0'], \
Names=['a','b','c'])
a = f.takeFlows('bc')
self.assertTrue(isinstance(a, FlowgramCollection))
self.assertEqual(a, {'b':'0.5 1.0 4.0 0.0','c':'1.5 0.0 2.0 1.0'})
#should be able to negate
a = f.takeFlows('bc', negate=True)
self.assertEqual(a, {'a':'0.0 1.1 3.0 1.0'})
def test_getFlowIndices(self):
"""FlowgramCollection getSeqIndices should return names of seqs where f(row) is True"""
f = self.ambiguous
is_long = lambda x: len(x) > 10
is_med = lambda x: len(str(x).replace('N','')) > 7 #strips gaps
is_any = lambda x: len(x) > 0
self.assertEqual(f.getFlowIndices(is_long,Bases = True), [])
f.Names = 'cba'
self.assertEqual(f.getFlowIndices(is_med,Bases = True), ['c','a'])
f.Names = 'bac'
self.assertEqual(f.getFlowIndices(is_med,Bases = True), ['a','c'])
self.assertEqual(f.getFlowIndices(is_any,Bases = True), ['b','a','c'])
#should be able to negate
self.assertEqual(f.getFlowIndices(is_med,Bases = True, negate=True),
['b'])
self.assertEqual(f.getFlowIndices(is_any, Bases = True,negate=True), [])
def test_takeFlowsIf(self):
"""FlowgramCollection takeFlowsIf should return flows where f(row) is True"""
is_long = lambda x: len(x) > 10
is_med = lambda x: len(str(x).replace('N','')) > 7
is_any = lambda x: len(x) > 0
f = self.ambiguous
self.assertEqual(f.takeFlowsIf(is_long, Bases = True), {})
self.assertEqual(f.takeFlowsIf(is_med, Bases = True), \
{'a':'0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0',
'c':'1.5 1.0 2.0 0.0 1.5 0.0 0.0 2.0'})
self.assertEqual(f.takeFlowsIf(is_any, Bases = True), f)
self.assertTrue(isinstance(f.takeFlowsIf(is_med, Bases = True),
FlowgramCollection))
#should be able to negate
self.assertEqual(f.takeFlowsIf(is_med, Bases = True,negate=True), \
{'b':'0.0 0.0 0.0 0.0 2.0 1.0 2.0 2.0'})
def test_getFlow(self):
"""FlowgramCollection.getFlow should return specified flow"""
a = [('a','0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0'),
('b','1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0'),
('c','2.5 0.0 4.0 0.0 0.5 1.0 0.0 1.0')]
f = FlowgramCollection(a)
self.assertEqual(f.getFlow('a'), '0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0')
self.assertRaises(KeyError, f.getFlow, 'd')
def test_getIntMap(self):
"""FlowgramCollection.getIntMap should return correct mapping."""
f = self.Class({'seq1':'0.5 1.0 2.0 0.0',
'seq2':'1.5 0.0 0.0 2.0','seq3':'0.0 3.0 0.1 1.0'})
int_keys = {'seq_0':'seq1','seq_1':'seq2','seq_2':'seq3'}
int_map = {'seq_0':'0.5 1.0 2.0 0.0','seq_1':'1.5 0.0 0.0 2.0',
'seq_2':'0.0 3.0 0.1 1.0'}
im,ik = f.getIntMap()
self.assertEqual(ik,int_keys)
self.assertEqual(im,int_map)
#test change prefix from default 'seq_'
prefix='seqn_'
int_keys = {'seqn_0':'seq1','seqn_1':'seq2','seqn_2':'seq3'}
int_map = {'seqn_0':'0.5 1.0 2.0 0.0','seqn_1':'1.5 0.0 0.0 2.0',
'seqn_2':'0.0 3.0 0.1 1.0'}
im,ik = f.getIntMap(prefix=prefix)
self.assertEqual(ik,int_keys)
self.assertEqual(im,int_map)
def test_toDict(self):
"""FlowgramCollection.toDict should return dict of strings (not obj)"""
f = self.Class({'a': '0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0'
, 'b': '1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0'})
self.assertEqual(f.toDict(), {'a':'0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0'
,'b':'1.5 1.0 0.0 0.0 2.5 1.0 2.0 1.0'})
for i in f.toDict().values():
assert isinstance(i, str)
def test_omitAmbiguousFlows(self):
"""FlowgramCollection omitAmbiguousFlows should return flows w/o N's"""
self.assertEqual(self.ambiguous.omitAmbiguousFlows(Bases=True),
{'a':'0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0',
'c':'1.5 1.0 2.0 0.0 1.5 0.0 0.0 2.0'})
self.assertEqual(self.ambiguous.omitAmbiguousFlows(Bases=False),
{'a':'0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0',
'c':'1.5 1.0 2.0 0.0 1.5 0.0 0.0 2.0'})
#check new object creation
self.assertNotSameObj(self.ambiguous.omitAmbiguousFlows(),
self.ambiguous)
self.assertTrue(isinstance(self.ambiguous.omitAmbiguousFlows(
Bases = True), FlowgramCollection))
def test_setBases(self):
"""FlowgramCollection setBases should set Bases property correctly"""
f = self.Class([Flowgram('0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0', Name='a',
header_info = {'Bases':'TACCCCTTGG'}),
Flowgram('0.0 1.0 0.0 0.0 2.0 1.0 2.0 2.0', Name='b',
header_info = {'Bases':'ATTACCGG'}),
Flowgram('1.5 1.0 2.0 0.0 1.5 0.0 0.0 2.0', Name='c',
header_info = {'Bases':'TTACCTTGG'})],
header_info = {'Flow Chars':'TACG'})
f.setBases()
for i,b in zip(f,['TACCCCTTGG','ATTACCGG','TTACCTTGG']):
self.assertEqual(i.Bases,b)
def setUp(self):
"""Define some standard data"""
self.rec = """Common Header:
Magic Number: 0x2E736666
Version: 0001
Index Offset: 96099976
Index Length: 1158685
# of Reads: 57902
Header Length: 440
Key Length: 4
# of Flows: 400
Flowgram Code: 1
Flow Chars: TACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACG
Key Sequence: TCAG
>FIQU8OX05GCVRO
Run Prefix: R_2008_10_15_16_11_02_
Region #: 5
XY Location: 2489_3906
Run Name: R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford
Analysis Name: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Full Path: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Read Header Len: 32
Name Length: 14
# of Bases: 104
Clip Qual Left: 5
Clip Qual Right: 85
Clip Adap Left: 0
Clip Adap Right: 0
Flowgram: 1.06 0.08 1.04 0.08 0.05 0.94 0.10 2.01 0.10 0.07 0.96 0.09 1.04 1.96 1.07 0.10 1.01 0.13 0.08 1.01 1.06 1.83 2.89 0.18 0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04
Flow Indexes: 1 3 6 8 8 11 13 14 14 15 17 20 21 22 22 23 23 23 25 27 29 29 32 32 35 38 39 39 39 42 43 45 46 46 46 47 48 51 51 54 54 57 59 61 61 64 67 69 72 72 74 76 77 80 81 81 81 82 83 83 86 88 88 91 94 95 95 95 98 100 103 106 106 109 112 113 116 118 118 121 122 124 125 127 130 131 133 136 138 140 143 144 144 144 147 149 152 152 155 158 158 160 160 163
Bases: tcagGCTAACTGTAACCCTCTTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCActgagcgggctggcaaggc
Quality Scores: 37 37 37 37 37 37 37 37 37 37 37 37 37 40 40 40 40 37 37 37 37 37 39 39 39 39 24 24 24 37 34 28 24 24 24 28 34 39 39 39 39 39 39 39 39 39 39 39 39 40 40 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37
>FIQU8OX05F8ILF
Run Prefix: R_2008_10_15_16_11_02_
Region #: 5
XY Location: 2440_0913
Run Name: R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford
Analysis Name: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Full Path: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Read Header Len: 32
Name Length: 14
# of Bases: 206
Clip Qual Left: 5
Clip Qual Right: 187
Clip Adap Left: 0
Clip Adap Right: 0
Flowgram: 1.04 0.00 1.01 0.00 0.00 1.00 0.00 1.00 0.00 1.05 0.00 0.91 0.10 1.07 0.95 1.01 0.00 0.06 0.93 0.02 0.03 1.06 1.18 0.09 1.00 0.05 0.90 0.11 0.07 1.99 0.11 0.02 1.96 1.04 0.13 0.01 2.83 0.10 1.97 0.06 0.11 1.04 0.13 0.03 0.98 1.15 0.07 1.00 0.07 0.08 0.98 0.11 1.92 0.05 0.04 2.96 1.02 1.02 0.04 0.93 1.00 0.13 0.04 1.00 1.03 0.08 0.97 0.13 0.11 1.88 0.09 0.05 1.02 1.89 0.07 0.11 0.98 0.05 0.07 1.01 0.08 0.05 1.01 0.13 1.00 0.07 0.10 1.04 0.10 0.04 0.98 0.12 1.03 0.96 0.11 0.07 1.00 0.09 0.03 1.03 0.11 1.95 1.06 0.13 0.05 1.00 0.13 0.11 1.00 0.09 0.03 2.89 0.08 0.95 0.09 1.03 1.02 1.05 1.07 0.08 0.12 2.81 0.08 0.08 1.00 1.07 0.07 0.05 1.86 0.12 0.98 0.06 2.00 0.11 1.02 0.11 0.08 1.88 0.13 1.03 0.13 0.98 0.15 0.11 1.03 1.03 1.04 0.18 0.98 0.13 0.15 1.04 0.11 1.01 0.13 0.06 1.01 0.06 1.02 0.08 0.99 0.14 0.99 0.09 0.05 1.09 0.04 0.07 2.96 0.09 2.03 0.13 2.96 1.13 0.08 1.03 0.07 0.99 0.11 0.05 1.05 1.04 0.09 0.07 1.00 1.03 0.09 0.06 1.06 1.04 2.94 0.18 0.06 0.93 0.10 1.10 0.11 2.02 0.17 1.00 1.03 0.06 0.11 0.96 0.04 3.00 0.11 0.07 1.99 0.10 2.03 0.12 0.97 0.16 0.01 2.09 0.14 1.04 0.16 0.06 1.03 0.14 1.12 0.12 0.05 0.96 1.01 0.10 0.14 0.94 0.03 0.12 1.10 0.92 0.09 1.10 1.04 1.02 0.12 0.97 2.00 0.15 1.08 0.04 1.03 1.04 0.03 0.09 5.16 1.02 0.09 0.13 2.66 0.09 0.05 1.06 0.07 0.89 0.05 0.12 1.10 0.16 0.06 1.01 0.13 1.00 0.14 0.98 0.09 2.92 1.28 0.03 2.95 0.98 0.16 0.08 0.95 0.96 1.09 0.08 1.07 1.01 0.16 0.06 4.52 0.12 1.03 0.07 0.09 1.03 0.14 0.03 1.01 1.99 1.05 0.14 1.03 0.13 0.03 1.10 0.10 0.96 0.11 0.99 0.12 0.05 0.94 2.83 0.14 0.12 0.96 0.00 1.00 0.11 0.14 1.98 0.08 0.11 1.04 0.01 0.11 2.03 0.15 2.05 0.10 0.03 0.93 0.01 0.08 0.12 0.00 0.16 0.05 0.07 0.08 0.11 0.07 0.05 0.04 0.10 0.05 0.05 0.03 0.07 0.03 0.04 0.04 0.06 0.03 0.05 0.04 0.09 0.03 0.08 0.03 0.07 0.02 0.05 0.02 0.06 0.01 0.05 0.04 0.06 0.02 0.04 0.04 0.04 0.03 0.03 0.06 0.06 0.03 0.02 0.02 0.08 0.03 0.01 0.01 0.06 0.03 0.01 0.03 0.04 0.02 0.00 0.02 0.05 0.00 0.02 0.02 0.03 0.00 0.02 0.02 0.04 0.01 0.00 0.01 0.05
Flow Indexes: 1 3 6 8 10 12 14 15 16 19 22 23 25 27 30 30 33 33 34 37 37 37 39 39 42 45 46 48 51 53 53 56 56 56 57 58 60 61 64 65 67 70 70 73 74 74 77 80 83 85 88 91 93 94 97 100 102 102 103 106 109 112 112 112 114 116 117 118 119 122 122 122 125 126 129 129 131 133 133 135 138 138 140 142 145 146 147 149 152 154 157 159 161 163 166 169 169 169 171 171 173 173 173 174 176 178 181 182 185 186 189 190 191 191 191 194 196 198 198 200 201 204 206 206 206 209 209 211 211 213 216 216 218 221 223 226 227 230 233 234 236 237 238 240 241 241 243 245 246 249 249 249 249 249 250 253 253 253 256 258 261 264 266 268 270 270 270 271 273 273 273 274 277 278 279 281 282 285 285 285 285 285 287 290 293 294 294 295 297 300 302 304 307 308 308 308 311 313 316 316 319 322 322 324 324 327
Bases: tcagAGACGCACTCAATTATTTCCATAGCTTGGGTAGTGTCAATAATGCTGCTATGAACATGGGAGTACAAATATTCTTCAAGATACTGATCTCATTTCCTTTAGATATATACCCAGAAGTGAAATTCCTGGATCACATAGTAGTTCTATTTTTATTTGATGAGAAACTTTATACTATTTTTCATAActgagcgggctggcaaggc
Quality Scores: 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 38 38 38 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 34 34 34 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 36 36 36 36 36 38 25 25 25 38 37 37 37 37 37 37 33 33 34 37 37 37 37 37 37 37 38 34 20 20 26 26 20 34 38 37 37 37 37 37 37 37 37 37 38 38 38 37 37 37 37 37 37 37 37 37 37
""".split('\n')
self.flow = """1.06 0.08 1.04 0.08 0.05 0.94 0.10 2.01 0.10 0.07 0.96 0.09 1.04 1.96 1.07 0.10 1.01 0.13 0.08 1.01 1.06 1.83 2.89 0.18 0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04"""
self.unordered = self.Class({'a':'0.0 1.1 3.0 1.0',
'b':'0.5 1.0 4.0 0.0'})
self.ordered1 = self.Class({'a':'0.0 1.1 3.0 1.0',\
'b':'0.5 1.0 4.0 0.0'}, Names=['a','b'])
self.ordered2 = self.Class({'a':'0.0 1.1 3.0 1.0',\
'b':'0.5 1.0 4.0 0.0'}, Names=['b','a'])
self.one_seq = self.Class({'a':'0.0 1.1 3.0 1.0'})
self.ambiguous = self.Class([Flowgram('0.5 1.0 4.0 0.0 1.5 0.0 0.0 2.0', Name='a',
header_info = {'Bases':'TACCCCTTGG'}),
Flowgram('0.0 0.0 0.0 0.0 2.0 1.0 2.0 2.0', Name = 'b',
header_info = {'Bases':'NTTACCGG'}),
Flowgram('1.5 1.0 2.0 0.0 1.5 0.0 0.0 2.0', Name='c',
header_info = {'Bases':'TTACCTTGG'})],
header_info = {'Flow Chars':'TACG'})
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_flowgram_parser.py 000644 000765 000024 00000031350 12024702176 024361 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""tests for sff parser"""
__author__ = "Julia Goodrich, Jens Reeder"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Julia Goodrich","Jens Reeder"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jens Reeder"
__email__ = "jreeder@colorado.edu"
__status__ = "Development"
from types import GeneratorType
from cogent.util.unit_test import TestCase, main
from cogent.parse.flowgram_parser import get_header_info, get_summaries,\
get_all_summaries, split_summary, parse_sff, lazy_parse_sff_handle
class SFFParserTests(TestCase):
"""Tests sff parser functions"""
def setUp(self):
"""Define some standard data"""
self.rec = """Common Header:
Magic Number: 0x2E736666
Version: 0001
Index Offset: 96099976
Index Length: 1158685
# of Reads: 57902
Header Length: 440
Key Length: 4
# of Flows: 400
Flowgram Code: 1
Flow Chars: TACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACG
Key Sequence: TCAG
>FIQU8OX05GCVRO
Run Prefix: R_2008_10_15_16_11_02_
Region #: 5
XY Location: 2489_3906
Run Name: R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford
Analysis Name: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Full Path: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Read Header Len: 32
Name Length: 14
# of Bases: 104
Clip Qual Left: 5
Clip Qual Right: 85
Clip Adap Left: 0
Clip Adap Right: 0
Flowgram: 1.06 0.08 1.04 0.08 0.05 0.94 0.10 2.01 0.10 0.07 0.96 0.09 1.04 1.96 1.07 0.10 1.01 0.13 0.08 1.01 1.06 1.83 2.89 0.18 0.96 0.13 0.99 0.11 1.94 0.12 0.13 1.92 0.21 0.07 0.94 0.17 0.03 0.97 2.76 0.15 0.05 1.02 1.14 0.10 0.98 2.54 1.13 0.96 0.15 0.21 1.90 0.16 0.07 1.78 0.22 0.07 0.93 0.22 0.97 0.08 2.02 0.15 0.19 1.02 0.19 0.09 1.02 0.17 0.99 0.09 0.18 1.84 0.16 0.91 0.10 1.10 1.00 0.20 0.09 1.11 3.01 1.07 1.98 0.14 0.22 1.09 0.17 1.99 0.15 0.20 0.92 0.17 0.07 1.01 2.96 0.15 0.07 1.06 0.20 1.00 0.10 0.12 1.00 0.15 0.08 1.90 0.19 0.10 0.99 0.18 0.09 0.99 1.08 0.15 0.07 1.06 0.14 1.84 0.13 0.11 0.95 1.05 0.13 1.04 1.10 0.18 0.94 0.14 0.10 0.97 1.08 0.12 1.08 0.18 0.08 1.00 0.13 0.98 0.15 0.87 0.13 0.19 1.01 3.06 0.17 0.11 1.04 0.09 1.03 0.10 0.11 2.02 0.16 0.11 1.04 0.04 0.09 1.87 0.13 2.09 0.13 0.10 0.97 0.17 0.08 0.08 0.04 0.12 0.05 0.08 0.07 0.08 0.05 0.07 0.06 0.07 0.03 0.05 0.04 0.09 0.04 0.07 0.04 0.07 0.06 0.03 0.06 0.06 0.06 0.06 0.07 0.09 0.04 0.05 0.08 0.05 0.04 0.09 0.06 0.03 0.02 0.08 0.04 0.06 0.05 0.08 0.03 0.08 0.05 0.05 0.05 0.10 0.05 0.05 0.07 0.06 0.04 0.06 0.05 0.03 0.04 0.05 0.06 0.04 0.04 0.07 0.04 0.04 0.05 0.05 0.04 0.07 0.06 0.05 0.03 0.08 0.05 0.06 0.04 0.06 0.05 0.04 0.04 0.04 0.05 0.06 0.04 0.05 0.04 0.05 0.05 0.06 0.05 0.06 0.04 0.06 0.07 0.06 0.05 0.05 0.05 0.06 0.06 0.04 0.05 0.06 0.03 0.06 0.04 0.06 0.05 0.03 0.06 0.06 0.05 0.06 0.04 0.03 0.06 0.06 0.06 0.03 0.04 0.05 0.05 0.07 0.04 0.05 0.06 0.07 0.07 0.05 0.07 0.06 0.05 0.06 0.05 0.07 0.06 0.05 0.06 0.07 0.05 0.06 0.04 0.06 0.05 0.05 0.06 0.04 0.06 0.04 0.03 0.06 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.06 0.06 0.04 0.04 0.05 0.06 0.04 0.04 0.04 0.05 0.05 0.04 0.05 0.05 0.03 0.06 0.06 0.06 0.04 0.07 0.05 0.05 0.04 0.06 0.06 0.05 0.05 0.07 0.04 0.06 0.06 0.06 0.04 0.06 0.03 0.06 0.04 0.06 0.04 0.09 0.05 0.05 0.05 0.07 0.06 0.05 0.05 0.06 0.05 0.05 0.05 0.04 0.04 0.06 0.05 0.05 0.05 0.05 0.04 0.05 0.05 0.06 0.04 0.05 0.05 0.05 0.05 0.05 0.04 0.06 0.04 0.05 0.05 0.04 0.05 0.05 0.05 0.04
Flow Indexes: 1 3 6 8 8 11 13 14 14 15 17 20 21 22 22 23 23 23 25 27 29 29 32 32 35 38 39 39 39 42 43 45 46 46 46 47 48 51 51 54 54 57 59 61 61 64 67 69 72 72 74 76 77 80 81 81 81 82 83 83 86 88 88 91 94 95 95 95 98 100 103 106 106 109 112 113 116 118 118 121 122 124 125 127 130 131 133 136 138 140 143 144 144 144 147 149 152 152 155 158 158 160 160 163
Bases: tcagGCTAACTGTAACCCTCTTGGCACCCACTAAACGCCAATCTTGCTGGAGTGTTTACCAGGCACCCAGCAATGTGAATAGTCActgagcgggctggcaaggc
Quality Scores: 37 37 37 37 37 37 37 37 37 37 37 37 37 40 40 40 40 37 37 37 37 37 39 39 39 39 24 24 24 37 34 28 24 24 24 28 34 39 39 39 39 39 39 39 39 39 39 39 39 40 40 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37
>FIQU8OX05F8ILF
Run Prefix: R_2008_10_15_16_11_02_
Region #: 5
XY Location: 2440_0913
Run Name: R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford
Analysis Name: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Full Path: /data/2008_10_15/R_2008_10_15_16_11_02_FLX04070166_adminrig_1548jinnescurtisstanford/D_2008_10_15_15_12_26_FLX04070166_1548jinnescurtisstanford_FullAnalysis
Read Header Len: 32
Name Length: 14
# of Bases: 206
Clip Qual Left: 5
Clip Qual Right: 187
Clip Adap Left: 0
Clip Adap Right: 0
Flowgram: 1.04 0.00 1.01 0.00 0.00 1.00 0.00 1.00 0.00 1.05 0.00 0.91 0.10 1.07 0.95 1.01 0.00 0.06 0.93 0.02 0.03 1.06 1.18 0.09 1.00 0.05 0.90 0.11 0.07 1.99 0.11 0.02 1.96 1.04 0.13 0.01 2.83 0.10 1.97 0.06 0.11 1.04 0.13 0.03 0.98 1.15 0.07 1.00 0.07 0.08 0.98 0.11 1.92 0.05 0.04 2.96 1.02 1.02 0.04 0.93 1.00 0.13 0.04 1.00 1.03 0.08 0.97 0.13 0.11 1.88 0.09 0.05 1.02 1.89 0.07 0.11 0.98 0.05 0.07 1.01 0.08 0.05 1.01 0.13 1.00 0.07 0.10 1.04 0.10 0.04 0.98 0.12 1.03 0.96 0.11 0.07 1.00 0.09 0.03 1.03 0.11 1.95 1.06 0.13 0.05 1.00 0.13 0.11 1.00 0.09 0.03 2.89 0.08 0.95 0.09 1.03 1.02 1.05 1.07 0.08 0.12 2.81 0.08 0.08 1.00 1.07 0.07 0.05 1.86 0.12 0.98 0.06 2.00 0.11 1.02 0.11 0.08 1.88 0.13 1.03 0.13 0.98 0.15 0.11 1.03 1.03 1.04 0.18 0.98 0.13 0.15 1.04 0.11 1.01 0.13 0.06 1.01 0.06 1.02 0.08 0.99 0.14 0.99 0.09 0.05 1.09 0.04 0.07 2.96 0.09 2.03 0.13 2.96 1.13 0.08 1.03 0.07 0.99 0.11 0.05 1.05 1.04 0.09 0.07 1.00 1.03 0.09 0.06 1.06 1.04 2.94 0.18 0.06 0.93 0.10 1.10 0.11 2.02 0.17 1.00 1.03 0.06 0.11 0.96 0.04 3.00 0.11 0.07 1.99 0.10 2.03 0.12 0.97 0.16 0.01 2.09 0.14 1.04 0.16 0.06 1.03 0.14 1.12 0.12 0.05 0.96 1.01 0.10 0.14 0.94 0.03 0.12 1.10 0.92 0.09 1.10 1.04 1.02 0.12 0.97 2.00 0.15 1.08 0.04 1.03 1.04 0.03 0.09 5.16 1.02 0.09 0.13 2.66 0.09 0.05 1.06 0.07 0.89 0.05 0.12 1.10 0.16 0.06 1.01 0.13 1.00 0.14 0.98 0.09 2.92 1.28 0.03 2.95 0.98 0.16 0.08 0.95 0.96 1.09 0.08 1.07 1.01 0.16 0.06 4.52 0.12 1.03 0.07 0.09 1.03 0.14 0.03 1.01 1.99 1.05 0.14 1.03 0.13 0.03 1.10 0.10 0.96 0.11 0.99 0.12 0.05 0.94 2.83 0.14 0.12 0.96 0.00 1.00 0.11 0.14 1.98 0.08 0.11 1.04 0.01 0.11 2.03 0.15 2.05 0.10 0.03 0.93 0.01 0.08 0.12 0.00 0.16 0.05 0.07 0.08 0.11 0.07 0.05 0.04 0.10 0.05 0.05 0.03 0.07 0.03 0.04 0.04 0.06 0.03 0.05 0.04 0.09 0.03 0.08 0.03 0.07 0.02 0.05 0.02 0.06 0.01 0.05 0.04 0.06 0.02 0.04 0.04 0.04 0.03 0.03 0.06 0.06 0.03 0.02 0.02 0.08 0.03 0.01 0.01 0.06 0.03 0.01 0.03 0.04 0.02 0.00 0.02 0.05 0.00 0.02 0.02 0.03 0.00 0.02 0.02 0.04 0.01 0.00 0.01 0.05
Flow Indexes: 1 3 6 8 10 12 14 15 16 19 22 23 25 27 30 30 33 33 34 37 37 37 39 39 42 45 46 48 51 53 53 56 56 56 57 58 60 61 64 65 67 70 70 73 74 74 77 80 83 85 88 91 93 94 97 100 102 102 103 106 109 112 112 112 114 116 117 118 119 122 122 122 125 126 129 129 131 133 133 135 138 138 140 142 145 146 147 149 152 154 157 159 161 163 166 169 169 169 171 171 173 173 173 174 176 178 181 182 185 186 189 190 191 191 191 194 196 198 198 200 201 204 206 206 206 209 209 211 211 213 216 216 218 221 223 226 227 230 233 234 236 237 238 240 241 241 243 245 246 249 249 249 249 249 250 253 253 253 256 258 261 264 266 268 270 270 270 271 273 273 273 274 277 278 279 281 282 285 285 285 285 285 287 290 293 294 294 295 297 300 302 304 307 308 308 308 311 313 316 316 319 322 322 324 324 327
Bases: tcagAGACGCACTCAATTATTTCCATAGCTTGGGTAGTGTCAATAATGCTGCTATGAACATGGGAGTACAAATATTCTTCAAGATACTGATCTCATTTCCTTTAGATATATACCCAGAAGTGAAATTCCTGGATCACATAGTAGTTCTATTTTTATTTGATGAGAAACTTTATACTATTTTTCATAActgagcgggctggcaaggc
Quality Scores: 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 38 38 38 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 34 34 34 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 36 36 36 36 36 38 25 25 25 38 37 37 37 37 37 37 33 33 34 37 37 37 37 37 37 37 38 34 20 20 26 26 20 34 38 37 37 37 37 37 37 37 37 37 38 38 38 37 37 37 37 37 37 37 37 37 37
""".split('\n')
def test_get_header_info(self):
"""get_header_info should return a sff file common header as a dict"""
header = get_header_info(self.rec)
self.assertEqual(len(header), 11)
self.assertEqual(header['Key Length'], '4')
self.assertEqual(header['Key Sequence'], 'TCAG')
def test_get_summaries(self):
"""get_summaries should return a generator of the summaries"""
summaries = get_summaries(self.rec,number_list = [1])
sum_list = list(summaries)
self.assertEqual(len(sum_list), 1)
self.assertEqual(isinstance(summaries, GeneratorType), True)
self.assertEqual(len(sum_list[0]), 18)
self.assertEqual(sum_list[0][0], '>FIQU8OX05F8ILF')
summaries = get_summaries(self.rec,name_list = ['FIQU8OX05GCVRO'])
sum_list = list(summaries)
self.assertEqual(len(sum_list), 1)
self.assertEqual(isinstance(summaries, GeneratorType), True)
self.assertEqual(len(sum_list[0]), 18)
self.assertEqual(sum_list[0][0], '>FIQU8OX05GCVRO')
summaries = get_summaries(self.rec,all_sums = True )
sum_list = list(summaries)
self.assertEqual(len(sum_list), 2)
self.assertEqual(isinstance(summaries, GeneratorType), True)
self.assertEqual(len(sum_list[0]), 18)
self.assertEqual(sum_list[0][0], '>FIQU8OX05GCVRO')
self.assertEqual(sum_list[1][0], '>FIQU8OX05F8ILF')
summaries = get_summaries(self.rec,number_list = [0],
name_list =['FIQU8OX05GCVRO'])
self.assertRaises(AssertionError,list,summaries)
summaries = get_summaries(self.rec)
self.assertRaises(ValueError,list, summaries)
def test_get_all_summaries(self):
"""get_all_summaries should return a list of the summaries"""
summaries = get_all_summaries(self.rec)
self.assertEqual(len(summaries), 2)
self.assertEqual(isinstance(summaries,list), True)
self.assertEqual(len(summaries[0]), 18)
self.assertEqual(summaries[0][0], '>FIQU8OX05GCVRO')
self.assertEqual(summaries[1][0], '>FIQU8OX05F8ILF')
def test_split_summary(self):
"""split_summary should return the info of a flowgram header."""
summaries = get_all_summaries(self.rec)
sum_dict = split_summary(summaries[0])
self.assertEqual(len(sum_dict), 18)
self.assertEqual(sum_dict['Name'], 'FIQU8OX05GCVRO')
assert 'Flowgram' in sum_dict
assert 'Bases' in sum_dict
sum_dict = split_summary(summaries[1])
self.assertEqual(len(sum_dict), 18)
self.assertEqual(sum_dict['Name'], 'FIQU8OX05F8ILF')
assert 'Flowgram' in sum_dict
assert 'Bases' in sum_dict
def test_parse_sff(self):
"""SFParser should read in the SFF file correctly."""
flows, head = parse_sff(self.rec)
self.assertEqual(len(flows),2)
self.assertEqual(len(head), 11)
self.assertEqual(head['Key Length'], '4')
self.assertEqual(head['Key Sequence'], 'TCAG')
self.assertEqual(flows[0].Name, 'FIQU8OX05GCVRO')
self.assertEqual(flows[1].Name, 'FIQU8OX05F8ILF')
def test_lazy_parse_sff_handle(self):
"""LazySFParser should read in the SFF file correctly."""
flows, head = lazy_parse_sff_handle(self.rec)
flows = list(flows)
self.assertEqual(len(flows),2)
self.assertEqual(len(head), 11)
self.assertEqual(head['Key Length'], '4')
self.assertEqual(head['Key Sequence'], 'TCAG')
self.assertEqual(flows[0].Name, 'FIQU8OX05GCVRO')
self.assertEqual(flows[1].Name, 'FIQU8OX05F8ILF')
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_gbseq.py 000644 000765 000024 00000016547 12024702176 022303 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import xml.dom.minidom
from cogent.util.unit_test import TestCase, main
from cogent.parse.gbseq import GbSeqXmlParser
__author__ = "Matthew Wakefield"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Matthew Wakefield"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Matthew Wakefield"
__email__ = "wakefield@wehi.edu.au"
__status__ = "Production"
data = """
AY286018
99
single
mRNA
linear
MAM
29-SEP-2003
01-JUN-2003
Macropus eugenii medium wave-sensitive opsin 1 (OPN1MW) mRNA, complete cds
AY286018
AY286018.1
gb|AY286018.1|
gi|31322957
Macropus eugenii (tammar wallaby)
Macropus eugenii
Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Metatheria; Diprotodontia; Macropodidae; Macropus
1
1..99
Deeb,S.S.
Wakefield,M.J.
Tada,T.
Marotte,L.
Yokoyama,S.
Marshall Graves,J.A.
The cone visual pigments of an Australian marsupial, the tammar wallaby (Macropus eugenii): sequence, spectral tuning, and evolution
Mol. Biol. Evol. 20 (10), 1642-1649 (2003)
doi
10.1093/molbev/msg181
12885969
2
1..99
Deeb,S.S.
Wakefield,M.J.
Tada,T.
Marotte,L.
Yokoyama,S.
Graves,J.A.M.
Direct Submission
Submitted (29-APR-2003) RSBS, The Australian National University, Acton, ACT 0200, Australia
source
1..99
1
99
AY286018.1
organism
Macropus eugenii
mol_type
mRNA
db_xref
taxon:9315
country
Australia: Kangaroo Island
gene
1..99
1
99
AY286018.1
gene
OPN1MW
CDS
31..99
31
99
AY286018.1
gene
OPN1MW
note
cone pigments
codon_start
1
transl_table
1
product
medium wave-sensitive opsin 1
protein_id
AAP37945.1
db_xref
GI:31322958
translation
MTQAWDPAGFLAWRRDENE
ggcagggaaagggaagaaagtaaaggggccatgacacaggcatgggaccctgcagggttcttggcttggcggcgggacgagaacgaggagacgactcgg
"""
sample_seq = ">AY286018.1\nGGCAGGGAAAGGGAAGAAAGTAAAGGGGCCATGACACAGGCATGGGACCCTGCAGGGTTCTTGGCTTGGCGGCGGGACGAGAACGAGGAGACGACTCGG"
sample_annotations = '[source "[0:99]/99 of AY286018.1" at [0:99]/99, organism "Macropus eugenii" at [0:99]/99, gene "OPN1MW" at [0:99]/99, CDS "OPN1MW" at [30:99]/99]'
class ParseGBseq(TestCase):
def test_parse(self):
for name,seq in [GbSeqXmlParser(data).next(),GbSeqXmlParser(xml.dom.minidom.parseString(data)).next()]:
self.assertEqual(name, 'AY286018.1')
self.assertEqual(sample_seq, seq.toFasta())
self.assertEqual(str(seq.annotations), sample_annotations)
pass
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_genbank.py 000644 000765 000024 00000043366 12024702176 022606 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the GenBank database parsers.
"""
from cogent.parse.genbank import parse_locus, parse_single_line, \
indent_splitter, parse_sequence, block_consolidator, parse_organism, \
parse_feature, location_line_tokenizer, parse_simple_location_segment, \
parse_location_line, parse_reference, parse_source, \
Location, LocationList
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class GenBankTests(TestCase):
"""Tests of the GenBank main functions."""
def test_parse_locus(self):
"""parse_locus should give correct results on specimen locus lines"""
line = 'LOCUS AF108830 5313 bp mRNA linear PRI 19-MAY-1999'
result = parse_locus(line)
self.assertEqual(len(result), 6)
self.assertEqual(result['locus'], 'AF108830')
self.assertEqual(result['length'], 5313) #note: int, not str
self.assertEqual(result['mol_type'], 'mRNA')
self.assertEqual(result['topology'], 'linear')
self.assertEqual(result['db'], 'PRI')
self.assertEqual(result['date'], '19-MAY-1999')
#should work if some of the fields are missing
line = 'LOCUS AF108830 5313'
result = parse_locus(line)
self.assertEqual(len(result), 2)
self.assertEqual(result['locus'], 'AF108830')
self.assertEqual(result['length'], 5313) #note: int, not str
def test_parse_single_line(self):
"""parse_single_line should split off the label and return the rest"""
line_1 = 'VERSION AF108830.1 GI:4868112\n'
self.assertEqual(parse_single_line(line_1), 'AF108830.1 GI:4868112')
#should work if leading spaces
line_2 = ' VERSION AF108830.1 GI:4868112\n'
self.assertEqual(parse_single_line(line_2), 'AF108830.1 GI:4868112')
def test_indent_splitter(self):
"""indent_splitter should split lines at correct locations"""
#if lines have same indent, should not group together
lines = [
'abc xxx',
'def yyy'
]
self.assertEqual(list(indent_splitter(lines)),\
[[lines[0]], [lines[1]]])
#if second line is indented, should group with first
lines = [
'abc xxx',
' def yyy'
]
self.assertEqual(list(indent_splitter(lines)),\
[[lines[0], lines[1]]])
#if both lines indented but second is more, should group with first
lines = [
' abc xxx',
' def yyy'
]
self.assertEqual(list(indent_splitter(lines)),\
[[lines[0], lines[1]]])
#if both lines indented equally, should not group
lines = [
' abc xxx',
' def yyy'
]
self.assertEqual(list(indent_splitter(lines)), \
[[lines[0]], [lines[1]]])
#for more complex situation, should produce correct grouping
lines = [
' xyz', #0 -
' xxx', #1 -
' yyy', #2
' uuu', #3
' iii', #4
' qaz', #5 -
' wsx', #6 -
' az', #7
' sx', #8
' gb',#9
' bg', #10
' aaa', #11 -
]
self.assertEqual(list(indent_splitter(lines)), \
[[lines[0]], lines[1:5], [lines[5]], lines[6:11], [lines[11]]])
#real example from genbank file
lines = \
"""LOCUS NT_016354 92123751 bp DNA linear CON 29-AUG-2006
DEFINITION Homo sapiens chromosome 4 genomic contig, reference assembly.
ACCESSION NT_016354 NT_006109 NT_006204 NT_006245 NT_006302 NT_006371
NT_006397 NT_016393 NT_016589 NT_016599 NT_016606 NT_022752
NT_022753 NT_022755 NT_022760 NT_022774 NT_022797 NT_022803
NT_022846 NT_022960 NT_025694 NT_028147 NT_029273 NT_030643
NT_030646 NT_030662 NT_031780 NT_031781 NT_031791 NT_034703
NT_034705 NT_037628 NT_037629 NT_079512
VERSION NT_016354.18 GI:88977422
KEYWORDS .
SOURCE Homo sapiens (human)
ORGANISM Homo sapiens
Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;
Mammalia; Eutheria; Euarchontoglires; Primates; Haplorrhini;
Catarrhini; Hominidae; Homo.
?
REFERENCE 2 (bases 1 to 92123751)
AUTHORS International Human Genome Sequencing Consortium.
TITLE Finishing the euchromatic sequence of the human genome""".split('\n')
self.assertEqual(list(indent_splitter(lines)), \
[[lines[0]],[lines[1]],lines[2:8],[lines[8]],[lines[9]],lines[10:15],\
[lines[15]], lines[16:]])
def test_parse_sequence(self):
"""parse_sequence should strip bad chars out of sequence lines"""
lines = """
ORIGIN
1 gggagcgcgg cgcgggagcc cgaggctgag actcaccgga ggaagcggcg cgagcgcccc
61 gccatcgtcc \t\t cggctgaagt 123 \ngcagtg \n
121 cctgggctta agcagtcttc45ccacctcagc
//\n\n\n""".split('\n')
result = parse_sequence(lines)
self.assertEqual(result, 'gggagcgcggcgcgggagcccgaggctgagactcaccggaggaagcggcgcgagcgccccgccatcgtcccggctgaagtgcagtgcctgggcttaagcagtcttcccacctcagc')
def test_block_consolidator(self):
"""block_consolidator should join the block together."""
lines = """ ORGANISM Homo sapiens
Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;
Mammalia; Eutheria; Euarchontoglires; Primates; Catarrhini;
Hominidae; Homo.""".split('\n')
label, data = block_consolidator(lines)
self.assertEqual(label, 'ORGANISM')
self.assertEqual(data, ['Homo sapiens',
' Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;',
' Mammalia; Eutheria; Euarchontoglires; Primates; Catarrhini;',
' Hominidae; Homo.'])
lines = r"""COMMENT
Contact: Spindel ER
Division of Neuroscience""".splitlines()
label, data = block_consolidator(lines)
self.assertEqual(label, "COMMENT")
self.assertEqual(data, ['', ' Contact: Spindel ER',
' Division of Neuroscience'])
def test_parse_organism(self):
"""parse_organism should return species, taxonomy (up to genus)"""
#note: lines modified to include the following:
# - multiword names
# - multiword names split over a line break
# - periods and other punctuation in names
lines = """ ORGANISM Homo sapiens
Eukaryota; Metazoa; Chordata Craniata; Vertebrata; Euteleostomi;
Mammalia; Eutheria; Euarchontoglires; Primates \t abc. 2.; Catarrhini
Hominidae; Homo.""".split('\n')
species, taxonomy = parse_organism(lines)
self.assertEqual(species, 'Homo sapiens')
self.assertEqual(taxonomy, ['Eukaryota', 'Metazoa', \
'Chordata Craniata', 'Vertebrata', 'Euteleostomi', 'Mammalia', \
'Eutheria', 'Euarchontoglires', 'Primates abc. 2.', \
'Catarrhini Hominidae', 'Homo'])
def test_parse_feature(self):
"""parse_feature should return dict containing annotations of feature"""
example_feature=\
""" CDS complement(join(102262..102647,105026..105217,
106638..106719,152424..152682,243209..243267))
/gene="nad1"
/note="Protein sequence is in conflict with the conceptual
translation; author given translation (not conceptual
translation)
start codon is created by C to U RNA editing"
/codon_start=1
/exception="RNA editing"
/product="NADH dehydrogenase subunit 1"
/protein_id="NP_064011.1"
/db_xref="GI:9838451"
/db_xref="IPI:12345"
/translation="MYIAVPAEILGIILPLLLGVAFLVLAERKVMAFVQRRKGPDVVG
SFGLLQPLADGSKLILKEPISPSSANFSLFRMAPVTTFMLSLVARAVVPFDYGMVLSD
PNIGLLYLFAISSLGVYGIIIAGWSSNSKYAFLGALRSAAQMVPYEVSIGLILITVLI
CVGPRNSSEIVMAQKQIWSGIPLFPVLVMFFISCLAETNRAPFDLPEAERELVAGYNV
EYSSMGSALFFLGEYANMILMSGLCTSLSPGGWPPILDLPISKRIPGSIWFSIKVILF
LFLYIWVRAAFPRYRYDQLMGLGRKVFLPLSLARVVAVSGVLVTFQWLP"""
result = parse_feature(example_feature.split('\n'))
self.assertEqual(result['type'], 'CDS')
self.assertEqual(result['raw_location'], \
['complement(join(102262..102647,105026..105217,', \
' 106638..106719,152424..152682,243209..243267))'])
self.assertEqual(result['gene'], ['nad1'])
self.assertEqual(result['note'], ['Protein sequence is in conflict with the conceptual translation; author given translation (not conceptual translation) start codon is created by C to U RNA editing'])
self.assertEqual(result['codon_start'], ['1'])
self.assertEqual(result['exception'], ['RNA editing'])
self.assertEqual(result['product'], ['NADH dehydrogenase subunit 1'])
self.assertEqual(result['protein_id'],['NP_064011.1'])
self.assertEqual(result['db_xref'], ['GI:9838451','IPI:12345'])
self.assertEqual(result['translation'],['MYIAVPAEILGIILPLLLGVAFLVLAERKVMAFVQRRKGPDVVGSFGLLQPLADGSKLILKEPISPSSANFSLFRMAPVTTFMLSLVARAVVPFDYGMVLSDPNIGLLYLFAISSLGVYGIIIAGWSSNSKYAFLGALRSAAQMVPYEVSIGLILITVLICVGPRNSSEIVMAQKQIWSGIPLFPVLVMFFISCLAETNRAPFDLPEAERELVAGYNVEYSSMGSALFFLGEYANMILMSGLCTSLSPGGWPPILDLPISKRIPGSIWFSIKVILFLFLYIWVRAAFPRYRYDQLMGLGRKVFLPLSLARVVAVSGVLVTFQWLP'])
self.assertEqual(len(result), 11)
short_feature = ['D-loop 15418..16866']
result = parse_feature(short_feature)
self.assertEqual(result['type'], 'D-loop')
self.assertEqual(result['raw_location'], ['15418..16866'])
#can get more than one = in a line
#from AF260826
bad_feature = \
""" tRNA 1173..1238
/note="codon recognized: AUC; Cove score = 16.56"
/product="tRNA-Ile"
/anticodon=(pos:1203..1205,aa:Ile)"""
result = parse_feature(bad_feature.split('\n'))
self.assertEqual(result['note'], \
['codon recognized: AUC; Cove score = 16.56'])
#need not always have an = in a line
#from NC_001807
bad_feature = \
''' mRNA 556
/partial
/citation=[6]
/product="H-strand"'''
result = parse_feature(bad_feature.split('\n'))
self.assertEqual(result['partial'], [''])
def test_location_line_tokenizer(self):
"""location_line_tokenizer should tokenize location lines"""
llt =location_line_tokenizer
self.assertEqual(list(llt(['123..456'])), ['123..456'])
self.assertEqual(list(llt(['complement(123..456)'])), \
['complement(', '123..456', ')'])
self.assertEqual(list(llt(['join(1..2,3..4)'])), \
['join(', '1..2', ',', '3..4', ')'])
self.assertEqual(list(llt([\
'join(complement(1..2, join(complement( 3..4),',\
'\n5..6), 7..8\t))'])),\
['join(','complement(','1..2',',','join(','complement(','3..4',\
')', ',', '5..6',')',',','7..8',')',')'])
def test_parse_simple_location_segment(self):
"""parse_simple_location_segment should parse simple segments"""
lsp = parse_simple_location_segment
l = lsp('37')
self.assertEqual(l._data, 37)
self.assertEqual(str(l), '37')
self.assertEqual(l.Strand, 1)
l = lsp('40..50')
first, second = l._data
self.assertEqual(first._data, 40)
self.assertEqual(second._data, 50)
self.assertEqual(str(l), '40..50')
self.assertEqual(l.Strand, 1)
#should handle ambiguous starts and ends
l = lsp('>37')
self.assertEqual(l._data, 37)
self.assertEqual(str(l), '>37')
l = lsp('<37')
self.assertEqual(l._data, 37)
self.assertEqual(str(l), '<37')
l = lsp('<37..>42')
first, second = l._data
self.assertEqual(first._data, 37)
self.assertEqual(second._data, 42)
self.assertEqual(str(first), '<37')
self.assertEqual(str(second), '>42')
self.assertEqual(str(l), '<37..>42')
def test_parse_location_line(self):
"""parse_location_line should give correct list of location objects"""
llt = location_line_tokenizer
r = parse_location_line(llt(['123..456']))
self.assertEqual(str(r), '123..456')
r = parse_location_line(llt(['complement(123..456)']))
self.assertEqual(str(r), 'complement(123..456)')
r = parse_location_line(llt(['complement(123..456, 345..678)']))
self.assertEqual(str(r), \
'join(complement(345..678),complement(123..456))')
r = parse_location_line(llt(['complement(join(123..456, 345..678))']))
self.assertEqual(str(r), \
'join(complement(345..678),complement(123..456))')
r = parse_location_line(\
llt(['join(complement(123..456), complement(345..678))']))
self.assertEqual(str(r), \
'join(complement(123..456),complement(345..678))')
#try some nested joins and complements
r = parse_location_line(llt(\
['complement(join(1..2,3..4,complement(5..6),',
'join(7..8,complement(9..10))))']))
self.assertEqual(str(r), \
'join(9..10,complement(7..8),5..6,complement(3..4),complement(1..2))')
def test_parse_reference(self):
"""parse_reference should give correct fields"""
r = \
"""REFERENCE 2 (bases 1 to 2587)
AUTHORS Janzen,D.M. and Geballe,A.P.
TITLE The effect of eukaryotic release factor depletion on translation
termination in human cell lines
JOURNAL (er) Nucleic Acids Res. 32 (15), 4491-4502 (2004)
PUBMED 15326224"""
result = parse_reference(r.split('\n'))
self.assertEqual(len(result), 5)
self.assertEqual(result['reference'], '2 (bases 1 to 2587)')
self.assertEqual(result['authors'], 'Janzen,D.M. and Geballe,A.P.')
self.assertEqual(result['title'], \
'The effect of eukaryotic release factor depletion ' + \
'on translation termination in human cell lines')
self.assertEqual(result['journal'], \
'(er) Nucleic Acids Res. 32 (15), 4491-4502 (2004)')
self.assertEqual(result['pubmed'], '15326224')
def test_parse_source(self):
"""parse_source should split into source and organism"""
s = \
"""SOURCE African elephant.
ORGANISM Mitochondrion Loxodonta africana
Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;
Mammalia; Eutheria; Proboscidea; Elephantidae; Loxodonta.""".split('\n')
r = parse_source(s)
self.assertEqual(len(r), 3)
self.assertEqual(r['source'], 'African elephant.')
self.assertEqual(r['species'], 'Mitochondrion Loxodonta africana')
self.assertEqual(r['taxonomy'], ['Eukaryota','Metazoa', 'Chordata',\
'Craniata', 'Vertebrata', 'Euteleostomi', 'Mammalia',\
'Eutheria', 'Proboscidea', 'Elephantidae', 'Loxodonta'])
class LocationTests(TestCase):
"""Tests of the Location class."""
def test_init(self):
"""Location should init with 1 or 2 values, plus params."""
l = Location(37)
self.assertEqual(str(l), '37')
l = Location(37, Ambiguity = '>')
self.assertEqual(str(l), '>37')
l = Location(37, Ambiguity='<')
self.assertEqual(str(l), '<37')
l = Location(37, Accession='AB123')
self.assertEqual(str(l), 'AB123:37')
l = Location(37, Accession='AB123', Db='Kegg')
self.assertEqual(str(l), 'Kegg::AB123:37')
l1 = Location(37)
l2 = Location(42)
l = Location([l1,l2])
self.assertEqual(str(l), '37..42')
l3 = Location([l1,l2], IsBounds=True)
self.assertEqual(str(l3), '(37.42)')
l4 = Location([l1,l2], IsBetween=True)
self.assertEqual(str(l4), '37^42')
l5 = Location([l4,l3])
self.assertEqual(str(l5), '37^42..(37.42)')
l5 = Location([l4,l3], Strand=-1)
self.assertEqual(str(l5), 'complement(37^42..(37.42))')
class LocationListTests(TestCase):
"""Tests of the LocationList class."""
def test_extract(self):
"""LocationList extract should return correct sequence"""
l = Location(3)
l2_a = Location(5)
l2_b = Location(7)
l2 = Location([l2_a,l2_b], Strand=-1)
l3_a = Location(10)
l3_b = Location(12)
l3 = Location([l3_a, l3_b])
ll = LocationList([l, l2, l3])
s = ll.extract('ACGTGCAGTCAGTAGCAT')
# 123456789012345678
self.assertEqual(s, 'G'+'TGC'+'CAG')
#check a case where it wraps around
l5_a = Location(16)
l5_b = Location(4)
l5 = Location([l5_a,l5_b])
ll = LocationList([l5])
s = ll.extract('ACGTGCAGTCAGTAGCAT')
self.assertEqual(s, 'CATACGT')
if __name__ == '__main__':
from sys import argv
if len(argv) > 2 and argv[1] == 'x':
filename = argv[2]
lines = open(filename)
for i in indent_splitter(lines):
print '******'
print i[0]
for j in indent_splitter(i[1:]):
print '?????'
for line in j:
print line
else:
main()
PyCogent-1.5.3/tests/test_parse/test_gff.py 000644 000765 000024 00000005026 12024702176 021732 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for GFF and related parsers.
"""
from cogent.parse.gff import *
from cogent.util.unit_test import TestCase, main
from StringIO import StringIO
__author__ = "Matthew Wakefield"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Matthew Wakefield"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Matthew Wakefield"
__email__ = "wakefield@wehi.edu.au"
__status__ = "Production"
headers = [
"""##gff-version 2
##source-version
##date
##Type []
##DNA
##acggctcggattggcgctggatgatagatcagacgac
##...
##end-DNA
""",
"""##gff-version 2
""",
"",
]
# '\t\t\t\t\t\t\t\t|\tscientific name\t|
2\t|\tMonera\t|\tMonera \t|\tin-part\t|
2\t|\tProcaryotae\t|\tProcaryotae <#1>\t|\tin-part\t|
2\t|\tProkaryotae\t|\tProkaryotae <#1>\t|\tin-part\t|
2\t|\teubacteria\t|\t\t|\tgenbank common name\t|
6\t|\tAzorhizobium\t|\t\t|\tscientific name\t|
7\t|\tAzorhizobium caulinodans\t|\t\t|\tscientific name\t|
9\t|\tBuchnera aphidicola\t|\t\t|\tscientific name\t|
10\t|\tFakus namus\t|\t\t|\tscientific name\t|
'''.split('\n')
class NcbiTaxonTests(TestCase):
"""Tests proper parsing of NCBI node file, e.g. nodes.dmp"""
def test_init(self):
"""NcbiTaxon init should return object containing taxonomy data"""
good_1 = '''1\t|\t1\t|\tno rank\t|\t\t|\t8\t|\t0\t|\t1\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|\n'''
good_2 = '''2\t|\t1\t|\tsuperkingdom\t|\t\t|\t0\t|\t0\t|\t11\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|\n'''
good_3 = '''6\t|\t2\t|\tgenus\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t|\n'''
good_4 = '''7\t|\t6\t|\tspecies\t|\tAC\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|\n'''
node_1 = NcbiTaxon(good_1) #make a NcbiTaxon object
node_2 = NcbiTaxon(good_2) #from the corresponding
node_3 = NcbiTaxon(good_3) #line.
node_4 = NcbiTaxon(good_4)
self.assertEqual(node_1.Rank, 'no rank') #confirm object holds
self.assertEqual(node_1.RankId, 28) #right data
self.assertEqual(node_1.ParentId, 1)
self.assertEqual(node_2.Rank, 'superkingdom')
self.assertEqual(node_2.RankId, 27)
self.assertEqual(node_2.ParentId, 1)
self.assertEqual(node_3.Rank, 'genus')
self.assertEqual(node_3.RankId, 8)
self.assertEqual(node_3.ParentId, 2)
self.assertEqual(node_4.Rank, 'species')
self.assertEqual(node_4.RankId, 4)
self.assertEqual(node_4.ParentId, 6)
#test some comparisons
assert node_1 > node_2
assert node_1 > node_3
assert node_1 > node_4
assert node_1 == node_1
assert node_2 < node_1
assert node_2 == node_2
assert node_4 < node_1
assert node_3 > node_4
def test_str(self):
"""NcbiTaxon str should write data in input format from nodes.dmp"""
good = '''2\t|\t1\t|\tsuperkingdom\t|\t\t|\t0\t|\t0\t|\t11\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|\n'''
node = NcbiTaxon(good)
self.assertEqual(str(node), good)
root = '''1\t|\t1\t|\tno rank\t|\t\t|\t8\t|\t0\t|\t1\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|'''
root_node = NcbiTaxon(root)
self.assertEqual(str(root), root)
def test_bad_input(self):
"""NcbiTaxon init should raise ValueError if nodes missing"""
bad_node_taxid = '''\t|\t6\t|\tspecies\t|\tAC\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|\n''' #contains no taxon_id; not valid
bad_node_parentid = '''7\t|\t\t|\tspecies\t|\tAC\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|\n''' #contains no parent_id; not valid
self.assertRaises(ValueError, NcbiTaxon, bad_node_taxid)
self.assertRaises(ValueError, NcbiTaxon, bad_node_parentid)
class NcbiNameTests(TestCase):
"""Tests proper parsing NCBI name file, e.g. names.dmp."""
def test_init(self):
"""NcbiName should init OK with well-formed name line"""
line_1 = '''1\t|\tall\t|\t\t|\tsynonym\t|\n'''
line_2 = '''1\t|\troot\t|\t\t|\tscientific name\t|\n'''
line_3 = '''2\t|\tBacteria\t|\tBacteria \t|\tscientific name\t|\n'''
line_4 = '''7\t|\tAzorhizobium caulinodans\t|\t\t|\tscientific name\t|\n'''
name_1 = NcbiName(line_1) #make an NcbiName object
name_2 = NcbiName(line_2) #from the corresponding line
name_3 = NcbiName(line_3)
name_4 = NcbiName(line_4)
self.assertEqual(name_1.TaxonId, 1) #test that the data
self.assertEqual(name_1.NameClass, 'synonym') #fields in the object
self.assertEqual(name_2.TaxonId, 1) #hold right data
self.assertEqual(name_2.NameClass, 'scientific name')
self.assertEqual(name_3.TaxonId, 2)
self.assertEqual(name_3.NameClass, 'scientific name')
self.assertEqual(name_4.TaxonId, 7)
self.assertEqual(name_4.NameClass, 'scientific name')
def test_str(self):
"""NcbiName str should return line in original format"""
line = '''1\t|\troot\t|\t\t|\tscientific name|\n'''
name = NcbiName(line)
self.assertEqual(str(name), line)
def test_bad_input(self):
"""NcbiName init should raise correct errors on bad data"""
bad_name_taxid = '''\t|\troot\t|\t\t|\tscientific name\t|\n'''#no tax_id
self.assertRaises(ValueError, NcbiName, bad_name_taxid)
class NcbiNameLookupTest(TestCase):
"""Tests of the NcbiNameLookup factory function."""
def test_init(self):
"""NcbiNameLookup should map taxon ids to scientific names"""
names = list(NcbiNameParser(good_names)) #list of objects
sci_names = NcbiNameLookup(names) #NcbiNameLookup object
root = names[1] #NcbiName object made from 2nd line of good_name_file
bacteria = names[2] #from 3rd line of good_name_file
azorhizobium = names[7]
caulinodans = names[8]
assert (sci_names[1] is root) #gets NcbiName object from the
assert (sci_names[2] is bacteria) #NcbiNameLookup object and
assert (sci_names[6] is azorhizobium) #asks if it is the original
assert (sci_names[7] is caulinodans) #NcbiName object
self.assertEqual(sci_names[1].Name, 'root')
self.assertEqual(sci_names[2].Name, 'Bacteria')
self.assertEqual(sci_names[7].Name, 'Azorhizobium caulinodans')
self.assertEqual(sci_names[9].Name, 'Buchnera aphidicola')
class NcbiTaxonLookupTest(TestCase):
"""Tests of the NcbiTaxonLookup factory function."""
def setUp(self):
"""Sets up the class tests"""
self.names = list(NcbiNameParser(good_names))
self.nodes = list(NcbiTaxonParser(good_nodes))
self.taxID_to_obj = NcbiTaxonLookup(self.nodes)
self.names_to_obj = NcbiNameLookup(self.names)
def test_init(self):
"""NcbiTaxonLookup should have correct fields for input NcbiTaxon"""
line1_obj = self.nodes[0] #NcbiTaxon objects made from lines of
line2_obj = self.nodes[1] #good_node_file
line3_obj = self.nodes[2]
line4_obj = self.nodes[3]
line5_obj = self.nodes[4]
assert (self.taxID_to_obj[1] is line1_obj) #gets NcbiTaxon object from
assert (self.taxID_to_obj[2] is line2_obj) #NcbiTaxonLookup object &
assert (self.taxID_to_obj[6] is line3_obj) #asks if it is the original
assert (self.taxID_to_obj[7] is line4_obj) #NcbiTaxon object
assert (self.taxID_to_obj[9] is line5_obj)
self.assertEqual(self.taxID_to_obj[1].ParentId, 1) #checking a few
self.assertEqual(self.taxID_to_obj[2].ParentId, 1) #individual
self.assertEqual(self.taxID_to_obj[6].ParentId, 2) #fields of the
self.assertEqual(self.taxID_to_obj[7].ParentId, 6) #NcbiTaxon objs
self.assertEqual(self.taxID_to_obj[9].ParentId, 7)
self.assertEqual(self.taxID_to_obj[1].Rank, 'no rank')
self.assertEqual(self.taxID_to_obj[2].Rank, 'superkingdom')
self.assertEqual(self.taxID_to_obj[6].Rank, 'genus')
self.assertEqual(self.taxID_to_obj[7].Rank, 'species')
self.assertEqual(self.taxID_to_obj[7].EmblCode, 'AC')
self.assertEqual(self.taxID_to_obj[7].DivisionId, '0')
self.assertEqual(self.taxID_to_obj[7].DivisionInherited, 1)
self.assertEqual(self.taxID_to_obj[7].TranslTable, 11)
self.assertEqual(self.taxID_to_obj[7].TranslTableInherited, 1)
self.assertEqual(self.taxID_to_obj[7].TranslTableMt, 0)
self.assertEqual(self.taxID_to_obj[7].TranslTableMtInherited, 1)
class NcbiTaxonomyTests(TestCase):
"""Tests of the NcbiTaxonomy class."""
def setUp(self):
self.tx = NcbiTaxonomyFromFiles(good_nodes, good_names)
def test_init_good(self):
"""NcbiTaxonomyFromFiles should pass spot-checks of resulting objects"""
self.assertEqual(len(self.tx.ByName), 6)
self.assertEqual(len(self.tx.ById), 6)
self.assertEqual(self.tx[10].Name, 'Fakus namus')
self.assertEqual(self.tx['1'].Name, 'root')
self.assertEqual(self.tx['root'].Parent, None)
self.assertEqual(self.tx.Deadbeats, {})
def test_init_bad(self):
"""NcbiTaxonomyFromFiles should produce deadbeats by default"""
bad_tx = NcbiTaxonomyFromFiles(bad_nodes, good_names)
self.assertEqual(len(bad_tx.Deadbeats), 2)
assert 777 in bad_tx.Deadbeats
assert 666 in bad_tx.Deadbeats
assert bad_tx.Deadbeats[777] == bad_tx[9]
def test_init_strict(self):
"""NcbiTaxonomyFromFiles should fail if strict and deadbeats exist"""
tx = NcbiTaxonomyFromFiles(good_nodes, good_names, strict=True)
self.assertRaises(MissingParentError, NcbiTaxonomyFromFiles, \
bad_nodes, good_names, strict=True)
def test_Ancestors(self):
"""NcbiTaxonomy should support Ancestors correctly, not incl. self"""
result = self.tx['7'].ancestors()
tax_ids = [taxon_obj.TaxonId for taxon_obj in result]
self.assertEqual(tax_ids, [6, 2, 1])
def test_Parent(self):
"""NcbiTaxonomy should support Parent correctly"""
assert self.tx[7].Parent is self.tx[6]
assert self.tx[6].Parent is self.tx[2]
assert self.tx[2].Parent is self.tx[1]
assert self.tx[1].Parent is None
def test_Siblings(self):
"""NcbiTaxonomy should support Siblings correctly"""
sibs = self.tx[7].siblings()
self.assertEqual(len(sibs), 1)
assert sibs[0] is self.tx[10]
def test_Children(self):
"""NcbiTaxonomy should support Children correctly"""
children = self.tx[6].Children
self.assertEqual(len(children), 2)
assert children[0] is self.tx[7]
assert children[1] is self.tx[10]
root_kids = self.tx['root']
self.assertEqual(len(root_kids), 1)
assert root_kids[0] is self.tx[2]
self.assertEqual(len(self.tx[10].Children), 0)
def test_Names(self):
"""NcbiTaxonomy should fill in names correctly"""
self.assertEqual(self.tx['6'].Name, 'Azorhizobium')
self.assertEqual(self.tx['1'].Name, 'root')
self.assertEqual(self.tx['2'].Name, 'Bacteria')
self.assertEqual(self.tx['7'].Name, 'Azorhizobium caulinodans')
def test_lastCommonAncestor(self):
"""NcbiTaxonomy should support lastCommonAncestor()"""
assert self.tx[9].lastCommonAncestor(self.tx[9]) is self.tx[9]
assert self.tx[9].lastCommonAncestor(self.tx[7]) is self.tx[7]
assert self.tx[9].lastCommonAncestor(self.tx[10]) is self.tx[6]
assert self.tx[9].lastCommonAncestor(self.tx[1]) is self.tx[1]
class NcbiTaxonNodeTests(TestCase):
"""Tests of the NcbiTaxonNode class.
Note: only testing methods that differ from the TreeNode base class.
Note: nested_species is explicitly designed to test the case where the nodes
file does _not_ contain the root, and where the id of the de facto
root is not 1, to make sure there's nothing special about a node
called 'root' or with id 1.
"""
def test_getRankedDescendants(self):
"""NcbiTaxonNode getRankedDescendants should return correct list"""
nested_species = '''3\t|\t3\t|\tsuperkingdom\t|\t\t|\t8\t|\t0\t|\t1\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|
11\t|\t3\t|\tkingdom\t|\t\t|\t8\t|\t0\t|\t1\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|
22\t|\t11\t|\tclass\t|\t\t|\t8\t|\t0\t|\t1\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|
44\t|\t22\t|\torder\t|\t\t|\t0\t|\t0\t|\t11\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|
66\t|\t22\t|\torder\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t|\t
77\t|\t66\t|\tfamily\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
99\t|\t66\t|\tfamily\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
88\t|\t44\t|\tfamily\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
101\t|\t77\t|\tgenus\t|\t\t|\t8\t|\t0\t|\t1\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|
202\t|\t77\t|\tgenus\t|\t\t|\t0\t|\t0\t|\t11\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|
606\t|\t99\t|\tgenus\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t|\t
707\t|\t88\t|\tgenus\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
909\t|\t88\t|\tgenus\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
123\t|\t909\t|\tgroup\t|\t\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
1111\t|\t123\t|\tspecies\t|\tAT\t|\t8\t|\t0\t|\t1\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|
2222\t|\t707\t|\tspecies\t|\tTT\t|\t0\t|\t0\t|\t11\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|
6666\t|\t606\t|\tspecies\t|\tGG\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t|\t
7777\t|\t606\t|\tspecies\t|\tAC\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
9999\t|\t202\t|\tspecies\t|\tBA\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
1010\t|\t101\t|\tspecies\t|\tAC\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
5555\t|\t555\t|\tspecies\t|\tAC\t|\t0\t|\t1\t|\t11\t|\t1\t|\t0\t|\t1\t|\t0\t|\t0\t|\t\t|
555\t|\t3\t|\tsuperclass\t|\t\t|\t8\t|\t0\t|\t1\t|\t0\t|\t0\t|\t0\t|\t0\t|\t0\t|\t\t|'''.split('\n')
nested_names = [
'3|a||scientific name|',
'11|b||scientific name|',
'555|c||scientific name|',
'22|d||scientific name|',
'44|e||scientific name|',
'66|f||scientific name|',
'88|g||scientific name|',
'77|h||scientific name|',
'99|i||scientific name|',
'707|j||scientific name|',
'909|k||scientific name|',
'101|l||scientific name|',
'202|m||scientific name|',
'606|n||scientific name|',
'2222|o||scientific name|',
'123|p||scientific name|',
'1111|q||scientific name|',
'1010|r||scientific name|',
'9999|s||scientific name|',
'7777|t||scientific name|',
'6666|u||scientific name|',
'5555|z||scientific name|',
]
tx = NcbiTaxonomyFromFiles(nested_species, nested_names)
dec = tx[3].getRankedDescendants('superclass')
self.assertEqual(len(dec), 1)
assert dec[0] is tx[555]
sp = tx['f'].getRankedDescendants('species')
self.assertSameItems(sp, [tx[1010], tx[9999], tx[7777], tx[6666]])
empty = tx[11].getRankedDescendants('superclass')
self.assertEqual(empty, [])
gr = tx[3].getRankedDescendants('group')
self.assertEqual(gr, [tx[123]])
assert tx[3] is tx['a']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_nexus.py 000644 000765 000024 00000037464 12024702176 022345 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the Nexus Parser
"""
from cogent.util.unit_test import TestCase, main
from cogent.parse.nexus import get_tree_info, parse_nexus_tree, parse_PAUP_log, \
split_tree_info, parse_trans_table, parse_dnd, get_BL_table, parse_taxa, \
find_fields
__author__ = "Catherine Lozupone"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Catherine Lozupone", "Rob Knight", "Micah Hamady"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Catherine Lozupone"
__email__ = "lozupone@colorado.edu"
__status__ = "Production"
Nexus_tree = """#NEXUS
Begin trees; [Treefile saved Wednesday, May 5, 2004 5:02 PM]
[!
>Data file = Grassland_short.nex
>Neighbor-joining search settings:
> Ties (if encountered) will be broken systematically
> Distance measure = Jukes-Cantor
> (Tree is unrooted)
]
Translate
1 outgroup25,
2 AF078391l,
3 AF078211af,
4 AF078393l,
5 AF078187af,
6 AF078320l,
7 AF078432l,
8 AF078290af,
9 AF078350l,
10 AF078356l,
11 AF078306af,
12 AF078429l,
13 AF078256af,
14 AF078443l,
15 AF078450l,
16 AF078452l,
17 AF078258af,
18 AF078380l,
19 AF078251af,
20 AF078179af,
21 outgroup258
;
tree PAUP_1 = [&R] (1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);
tree PAUP_2 = [&R] (1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);
End;""".split('\n')
Nexus_tree_2 = """#NEXUS
Begin trees; [Treefile saved Wednesday, June 14, 2006 11:20 AM]
[!>Neighbor-joining search settings:
> Ties (if encountered) will be broken systematically
> Distance measure = uncorrected ("p")
> (Tree is unrooted)
]
tree nj = [&U] ((((((((((YA10260L1:0.01855,SARAG06_Y:0.00367):0.01965,(((YA270L1G0:0.01095,SARAD10_Y:0.00699):0.01744,YA270L1A0:0.04329):0.00028,((YA165L1C1:0.01241,SARAA02_Y:0.02584):0.00213,((YA165L1H0:0.00092,SARAF10_Y:-0.00092):0.00250,(YA165L1A0:0.00177,SARAH10_Y:0.01226):0.00198):0.00131):0.00700):0.01111):0.11201,(YA160L1F0:0.00348,SARAG01_Y:-0.00122):0.13620):0.01202,((((YRM60L1D0:0.00357,(YRM60L1C0:0.00477,SARAE10_Y:-0.00035):0.00086):0.00092,SARAE03_Y:0.00126):0.00125,SARAC11_Y:0.00318):0.00160,YRM60L1H0:0.00593):0.09975):0.07088,SARAA01_Y:0.02880):0.00190,SARAB04_Y:0.05219):0.00563,YRM60L1E0:0.06099):0.00165,(YRM60L1H0:0.00450,SARAF11_Y:0.01839):0.00288):0.00129,YRM60L1B1:0.00713):0.00194,(YRM60L1G0:0.00990,(YA165L1G0:0.00576,(YA160L1G0:0.01226,SARAA11_Y:0.00389):0.00088):0.00300):0.00614,SARAC06_Y:0.00381);
end;""".split('\n')
Nexus_tree_3 = """#NEXUS
Begin trees; [Treefile saved Wednesday, May 5, 2004 5:02 PM]
[!
>Data file = Grassland_short.nex
>Neighbor-joining search settings:
> Ties (if encountered) will be broken systematically
> Distance measure = Jukes-Cantor
> (Tree is unrooted)
]
Translate
1 outgroup25,
2 AF078391l,
3 'AF078211af',
4 AF078393l,
5 AF078187af,
6 AF078320l,
7 AF078432l,
8 AF078290af,
9 AF078350l,
10 AF078356l,
11 AF078306af,
12 AF078429l,
13 AF078256af,
14 'AF078443l',
15 AF078450l,
16 AF078452l,
17 AF078258af,
18 'AF078380l',
19 AF078251af,
20 AF078179af,
21 outgroup258
;
tree PAUP_1 = [&R] (1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);
tree PAUP_2 = [&R] (1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);
End;""".split('\n')
PAUP_log = """
P A U P *
Version 4.0b10 for Macintosh (PPC/Altivec)
Wednesday, May 5, 2004 5:03 PM
This copy registered to: Scott Dawson
UC-Berkeley
(serial number = B400784)
-----------------------------NOTICE-----------------------------
This is a beta-test version. Please report any crashes,
apparent calculation errors, or other anomalous results.
There are no restrictions on publication of results obtained
with this version, but you should check the WWW site
frequently for bug announcements and/or updated versions.
See the README file on the distribution media for details.
----------------------------------------------------------------
Tree description:
Optimality criterion = parsimony
Character-status summary:
Of 500 total characters:
All characters are of type 'unord'
All characters have equal weight
253 characters are constant
109 variable characters are parsimony-uninformative
Number of parsimony-informative characters = 138
Multistate taxa interpreted as uncertainty
Character-state optimization: Accelerated transformation (ACCTRAN)
AncStates = "standard"
Tree number 1 (rooted using user-specified outgroup)
Branch lengths and linkages for tree #1
Assigned Minimum Maximum
Connected branch possible possible
Node to node length length length
-------------------------------------------------------------------------
40 root 0 0 0
outgroup25 (1)* 40 40 24 52
39 40 57 15 72
AF078391l (2) 39 56 48 81
38 39 33 17 71
37 38 31 14 48
22 37 20 11 33
AF078211af (3) 22 4 2 7
AF078393l (4) 22 1 0 3
36 37 14 5 32
AF078187af (5) 36 18 10 28
35 36 21 16 45
34 35 10 3 23
26 34 5 3 9
24 26 4 3 13
23 24 0 0 3
AF078320l (6) 23 1 1 3
AF078356l (10) 23 2 2 2
AF078350l (9) 24 5 3 5
25 26 9 2 10
AF078306af (11) 25 6 4 10
AF078380l (18) 25 5 3 10
33 34 5 4 15
29 33 3 1 4
28 29 2 2 2
27 28 3 1 3
AF078432l (7) 27 2 2 2
AF078450l (15) 27 3 3 4
AF078251af (19) 28 6 6 7
AF078258af (17) 29 6 6 6
32 33 4 3 15
AF078290af (8) 32 9 8 11
31 32 9 6 18
AF078429l (12) 31 2 1 5
30 31 10 9 18
AF078443l (14) 30 2 1 6
AF078452l (16) 30 4 4 5
AF078256af (13) 35 4 1 6
AF078179af (20) 38 48 34 79
outgroup258 (21)* 40 45 27 67
-------------------------------------------------------------------------
Sum 509
Tree length = 509
Consistency index (CI) = 0.7151
Homoplasy index (HI) = 0.2849
""".split('\n')
line1 = " 40 root 0 0 0"
line2 = "outgroup25 (1)* 40 40 24 52"
line3 = " 39 40 57 15 72"
line4 = "AF078391l (2) 39 56 48 81"
class NexusParserTests(TestCase):
"""Tests of the Nexus Parser functions"""
def test_parse_nexus_tree(self):
"""parse_nexus_tree returns a dnd string and a translation table list"""
Trans_table, dnd = parse_nexus_tree(Nexus_tree)
#check the full dendrogram string is returned
self.assertEqual(dnd['tree PAUP_1'],\
"(1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);")
#check that all taxa are returned in the Trans_table
self.assertEqual(Trans_table['1'], 'outgroup25')
self.assertEqual(Trans_table['2'], 'AF078391l')
self.assertEqual(Trans_table['3'], 'AF078211af')
self.assertEqual(Trans_table['4'], 'AF078393l')
self.assertEqual(Trans_table['5'], 'AF078187af')
self.assertEqual(Trans_table['6'], 'AF078320l')
self.assertEqual(Trans_table['21'], 'outgroup258')
self.assertEqual(Trans_table['20'], 'AF078179af')
self.assertEqual(Trans_table['19'], 'AF078251af')
#check that Nexus files without translation table work
Trans_table, dnd = parse_nexus_tree(Nexus_tree_2)
self.assertEqual(Trans_table, None)
self.assertEqual(dnd['tree nj'], '((((((((((YA10260L1:0.01855,SARAG06_Y:0.00367):0.01965,(((YA270L1G0:0.01095,SARAD10_Y:0.00699):0.01744,YA270L1A0:0.04329):0.00028,((YA165L1C1:0.01241,SARAA02_Y:0.02584):0.00213,((YA165L1H0:0.00092,SARAF10_Y:-0.00092):0.00250,(YA165L1A0:0.00177,SARAH10_Y:0.01226):0.00198):0.00131):0.00700):0.01111):0.11201,(YA160L1F0:0.00348,SARAG01_Y:-0.00122):0.13620):0.01202,((((YRM60L1D0:0.00357,(YRM60L1C0:0.00477,SARAE10_Y:-0.00035):0.00086):0.00092,SARAE03_Y:0.00126):0.00125,SARAC11_Y:0.00318):0.00160,YRM60L1H0:0.00593):0.09975):0.07088,SARAA01_Y:0.02880):0.00190,SARAB04_Y:0.05219):0.00563,YRM60L1E0:0.06099):0.00165,(YRM60L1H0:0.00450,SARAF11_Y:0.01839):0.00288):0.00129,YRM60L1B1:0.00713):0.00194,(YRM60L1G0:0.00990,(YA165L1G0:0.00576,(YA160L1G0:0.01226,SARAA11_Y:0.00389):0.00088):0.00300):0.00614,SARAC06_Y:0.00381);')
def test_parse_nexus_tree_sq(self):
"""remove single quotes from tree and translate tables"""
Trans_table, dnd = parse_nexus_tree(Nexus_tree_3)
#check the full dendrogram string is returned
self.assertEqual(dnd['tree PAUP_1'],\
"(1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);")
#check that all taxa are returned in the Trans_table
self.assertEqual(Trans_table['1'], 'outgroup25')
self.assertEqual(Trans_table['2'], 'AF078391l')
self.assertEqual(Trans_table['3'], 'AF078211af')
self.assertEqual(Trans_table['4'], 'AF078393l')
self.assertEqual(Trans_table['5'], 'AF078187af')
self.assertEqual(Trans_table['6'], 'AF078320l')
self.assertEqual(Trans_table['21'], 'outgroup258')
self.assertEqual(Trans_table['20'], 'AF078179af')
self.assertEqual(Trans_table['19'], 'AF078251af')
def test_get_tree_info(self):
"""get_tree_info returns the Nexus file section that describes the tree"""
result = get_tree_info(Nexus_tree)
self.assertEqual(len(result), 33)
self.assertEqual(result[0],\
"Begin trees; [Treefile saved Wednesday, May 5, 2004 5:02 PM]")
self.assertEqual(result[31], \
"tree PAUP_1 = [&R] (1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);")
def test_split_tree_info(self):
"""split_tree_info splits lines into header, Trans_table, and dnd"""
tree_info = get_tree_info(Nexus_tree)
header, trans_table, dnd = split_tree_info(tree_info)
self.assertEqual(len(header), 9)
self.assertEqual(len(trans_table), 22)
self.assertEqual(len(dnd), 2)
self.assertEqual(header[0],\
"Begin trees; [Treefile saved Wednesday, May 5, 2004 5:02 PM]")
self.assertEqual(header[8], "\tTranslate")
self.assertEqual(trans_table[0], "\t\t1 outgroup25,")
self.assertEqual(trans_table[21], "\t\t;")
self.assertEqual(dnd[0], \
"tree PAUP_1 = [&R] (1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);")
def test_parse_trans_table(self):
"""parse_trans_table returns a dict with the taxa names indexed by number"""
tree_info = get_tree_info(Nexus_tree)
header, trans_table, dnd = split_tree_info(tree_info)
Trans_table = parse_trans_table(trans_table)
self.assertEqual(len(Trans_table), 21)
#check that taxa are returned in the Trans_table
self.assertEqual(Trans_table['1'], 'outgroup25')
self.assertEqual(Trans_table['2'], 'AF078391l')
self.assertEqual(Trans_table['3'], 'AF078211af')
self.assertEqual(Trans_table['4'], 'AF078393l')
self.assertEqual(Trans_table['5'], 'AF078187af')
self.assertEqual(Trans_table['6'], 'AF078320l')
self.assertEqual(Trans_table['21'], 'outgroup258')
self.assertEqual(Trans_table['20'], 'AF078179af')
self.assertEqual(Trans_table['19'], 'AF078251af')
def test_parse_dnd(self):
"""parse_dnd returns a dict with dnd indexed by tree name"""
tree_info = get_tree_info(Nexus_tree)
header, trans_table, dnd = split_tree_info(tree_info)
dnd_dict = parse_dnd(dnd)
self.assertEqual(dnd_dict['tree PAUP_1'],\
"(1,(2,(((3,4),(5,(((((6,10),9),(11,18)),((((7,15),19),17),(8,(12,(14,16))))),13))),20)),21);")
#------------------------------------------------------
def test_get_BL_table(self):
"""get_BL_table returns the section of the log file w/ the BL table"""
BL_table = get_BL_table(PAUP_log)
self.assertEqual(len(BL_table), 40)
self.assertEqual(BL_table[0], \
" 40 root 0 0 0")
self.assertEqual(BL_table[39], \
"outgroup258 (21)* 40 45 27 67")
def test_find_fields(self):
"""find_fields takes BL table line and returns field names mapped to info"""
result = find_fields(line1)
self.assertEqual(result['taxa'], "40")
self.assertEqual(result['bl'], "0")
self.assertEqual(result['parent'], "root")
def test_parse_taxa(self):
"""parse_taxa should return the taxa # from a taxa_field from find_fields"""
result1 = find_fields(line1)
result2 = find_fields(line2)
result3 = find_fields(line3)
result4 = find_fields(line4)
self.assertEqual(parse_taxa(result1["taxa"]), '40')
self.assertEqual(parse_taxa(result2["taxa"]), '1')
self.assertEqual(parse_taxa(result3["taxa"]), '39')
self.assertEqual(parse_taxa(result4["taxa"]), '2')
def test_parse_PAUP_log(self):
"""parse_PAUP_log extracts branch length info from a PAUP log file"""
BL_dict = parse_PAUP_log(PAUP_log)
self.assertEqual(len(BL_dict), 40)
self.assertEqual(BL_dict['1'], ('40', 40))
self.assertEqual(BL_dict['40'], ('root', 0))
self.assertEqual(BL_dict['39'], ('40', 57))
self.assertEqual(BL_dict['2'], ('39', 56))
self.assertEqual(BL_dict['26'], ('34', 5))
self.assertEqual(BL_dict['21'], ('40', 45))
#run if called from command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_nupack.py 000644 000765 000024 00000003125 12024702176 022447 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.nupack import nupack_parser
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class NupackParserTest(TestCase):
"""Provides tests for NUPACK RNA secondary structure format parsers"""
def setUp(self):
"""Setup function"""
#output
self.nupack_out = NUPACK
#expected
self.nupack_exp = [['GGCUAGUCCCUUCU',[(0,9),(1,8),(4,13),(5,12)],-23.30]]
def test_nupack_output(self):
"""Test for nupack format"""
obs = nupack_parser(self.nupack_out)
self.assertEqual(obs,self.nupack_exp)
NUPACK = ['****************************************************************\n', 'NUPACK 1.2\n',
'Copyright 2007-2009 2003, 2004 by Robert M. Dirks & Niles A. Pierce\n',
'California Institute of Technology\n', 'Pasadena, CA 91125 USA\n', '\n',
'Last Modified: 03/18/2004\n',
'****************************************************************\n', '\n',
'\n', 'Fold.out Version 1.2: Complexity O(N^5) (pseudoknots enabled)\n',
'Reading Input File...\n', 'Sequence Read.\n', 'Energy Parameters Loaded\n',
'SeqLength = 14\n', 'Sequence and a Minimum Energy Structure:\n',
'GGCUAGUCCCUUCU\n', '((..{{..))..}}\n', 'mfe = -23.30 kcal/mol\n',
'pseudoknotted!\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_pamlmatrix.py 000644 000765 000024 00000004656 12024702176 023356 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from StringIO import StringIO
from cogent.util.unit_test import TestCase, main
from cogent.evolve.models import DSO78_matrix, DSO78_freqs
from cogent.parse.paml_matrix import PamlMatrixParser
__author__ = "Matthew Wakefield"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Matthew Wakefield"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Matthew Wakefield"
__email__ = "wakefield@wehi.edu.au"
__status__ = "Production"
data = """
27
98 32
120 0 905
36 23 0 0
89 246 103 134 0
198 1 148 1153 0 716
240 9 139 125 11 28 81
23 240 535 86 28 606 43 10
65 64 77 24 44 18 61 0 7
41 15 34 0 0 73 11 7 44 257
26 464 318 71 0 153 83 27 26 46 18
72 90 1 0 0 114 30 17 0 336 527 243
18 14 14 0 0 0 0 15 48 196 157 0 92
250 103 42 13 19 153 51 34 94 12 32 33 17 11
409 154 495 95 161 56 79 234 35 24 17 96 62 46 245
371 26 229 66 16 53 34 30 22 192 33 136 104 13 78 550
0 201 23 0 0 0 0 0 27 0 46 0 0 76 0 75 0
24 8 95 0 96 0 22 0 127 37 28 13 0 698 0 34 42 61
208 24 15 18 49 35 37 54 44 889 175 10 258 12 48 30 157 0 28
0.087127 0.040904 0.040432 0.046872 0.033474 0.038255 0.049530
0.088612 0.033618 0.036886 0.085357 0.080482 0.014753 0.039772
0.050680 0.069577 0.058542 0.010494 0.029916 0.064718
Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val
S_ij = S_ji and PI_i for the Dayhoff model, with the rate Q_ij=S_ij*PI_j
The rest of the file is not used.
Prepared by Z. Yang, March 1995.
See the following reference for notation used here:
Yang, Z., R. Nielsen and M. Hasegawa. 1998. Models of amino acid substitution and
applications to mitochondrial protein evolution. Mol. Biol. Evol. 15:1600-1611.
"""
class TestParsePamlMatrix(TestCase):
def test_parse(self):
matrix,freqs = PamlMatrixParser(StringIO(data))
self.assertEqual(DSO78_matrix,matrix)
self.assertEqual(DSO78_freqs,freqs)
pass
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_pdb.py 000755 000765 000024 00000114601 12024702176 021740 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the pdb parser.
"""
from cogent.util.unit_test import TestCase, main
from cogent.parse.pdb import dict2pdb, dict2ter, pdb2dict, get_symmetry, \
get_coords_offset, get_trailer_offset, \
parse_header, parse_coords, parse_trailer, \
PDBParser
from cogent.core.entity import Structure
from cogent.core.entity import StructureBuilder
from numpy import array, allclose
__author__ = "Marcin Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Production"
class pdbTests(TestCase):
"""Tests of cogent.parse.pdb functions."""
def test_PDBParser(self):
"""tests the UI parsing function.
"""
fh = open('data/2E12.pdb')
structure = PDBParser(fh, 'JUNK')
assert type(structure) is Structure
assert len(structure) == 1
assert (0,) in structure
assert structure.header['space_group'] == 'P 21 21 21'
assert structure.header['experiment_type'] == 'X-RAY DIFFRACTION'
assert structure.header['r_free'] == '0.280'
assert structure.header['dbref_acc'] == 'Q8P4R5'
assert structure.header['cryst1'] == '49.942 51.699 82.120 90.00 90.00 90.00'
assert structure.header['matthews'] == '2.29'
model = structure[(0,)]
assert len(model) == 2
assert structure.raw_header
assert structure.raw_trailer
assert structure.header
assert structure.trailer == {}
assert structure.getId() == ('JUNK', )
def test_parse_trailer(self):
"""testing trailer parsing dummy."""
d = parse_trailer(None)
assert isinstance(d, dict)
def test_parse_coords(self):
"""testing minimal structure building and coords parsing.
"""
builder = StructureBuilder()
builder.initStructure('JUNK')
atom = 'ATOM 10 CA PRO A 2 51.588 38.262 31.417 1.00 6.58 C \n'
hetatm = 'HETATM 1633 O HOH B 164 17.979 35.529 38.171 1.00 1.02 O \n'
lines = ['MODEL ', atom, hetatm]
z = parse_coords(builder, lines)
assert len(z[(0,)]) == 2
assert len(z[(0,)][('A',)]) == 1
assert len(z[(0,)][('B',)]) == 1
z.setTable()
atom1 = z.table['A'][('JUNK', 0, 'A', ('PRO', 2, ' '), ('CA', ' '))]
hetatm1 = z.table['A'][('JUNK', 0, 'B', ('H_HOH', 164, ' '), ('O', ' '))]
self.assertAlmostEqual([51.588 , 38.262 , 31.417][2], list(atom1.coords)[2])
self.assertAlmostEqual([17.979 , 35.529 , 38.171][2], list(hetatm1.coords)[2])
def test_parse_header(self):
"""testing header parsing.
"""
header = ['HEADER TRANSLATION 17-OCT-06 2E12 \n',
'TITLE THE CRYSTAL STRUCTURE OF XC5848 FROM XANTHOMONAS CAMPESTRIS \n',
'TITLE 2 ADOPTING A NOVEL VARIANT OF SM-LIKE MOTIF \n',
'COMPND MOL_ID: 1; \n',
'COMPND 2 MOLECULE: HYPOTHETICAL PROTEIN XCC3642; \n',
'COMPND 3 CHAIN: A, B; \n',
'COMPND 4 SYNONYM: SM-LIKE MOTIF; \n',
'COMPND 5 ENGINEERED: YES \n',
'SOURCE MOL_ID: 1; \n',
'SOURCE 2 ORGANISM_SCIENTIFIC: XANTHOMONAS CAMPESTRIS PV. CAMPESTRIS; \n',
'SOURCE 3 ORGANISM_TAXID: 340; \n',
'SOURCE 4 STRAIN: PV. CAMPESTRIS; \n',
'SOURCE 5 EXPRESSION_SYSTEM: ESCHERICHIA COLI; \n',
'SOURCE 6 EXPRESSION_SYSTEM_TAXID: 562 \n',
'KEYWDS NOVEL SM-LIKE MOTIF, LSM MOTIF, XANTHOMONAS CAMPESTRIS, X- \n',
'KEYWDS 2 RAY CRYSTALLOGRAPHY, TRANSLATION \n',
'EXPDTA X-RAY DIFFRACTION \n',
'AUTHOR K.-H.CHIN,S.-K.RUAN,A.H.-J.WANG,S.-H.CHOU \n',
'REVDAT 2 24-FEB-09 2E12 1 VERSN \n',
'REVDAT 1 30-OCT-07 2E12 0 \n',
'JRNL AUTH K.-H.CHIN,S.-K.RUAN,A.H.-J.WANG,S.-H.CHOU \n',
'JRNL TITL XC5848, AN ORFAN PROTEIN FROM XANTHOMONAS \n',
'JRNL TITL 2 CAMPESTRIS, ADOPTS A NOVEL VARIANT OF SM-LIKE MOTIF \n',
'JRNL REF PROTEINS V. 68 1006 2007 \n',
'JRNL REFN ISSN 0887-3585 \n',
'JRNL PMID 17546661 \n',
'JRNL DOI 10.1002/PROT.21375 \n',
'REMARK 1 \n',
'REMARK 2 \n',
'REMARK 2 RESOLUTION. 1.70 ANGSTROMS. \n',
'REMARK 3 \n',
'REMARK 3 REFINEMENT. \n',
'REMARK 3 PROGRAM : CNS \n',
'REMARK 3 AUTHORS : BRUNGER,ADAMS,CLORE,DELANO,GROS,GROSSE- \n',
'REMARK 3 : KUNSTLEVE,JIANG,KUSZEWSKI,NILGES, PANNU, \n',
'REMARK 3 : READ,RICE,SIMONSON,WARREN \n',
'REMARK 3 \n',
'REMARK 3 REFINEMENT TARGET : NULL \n',
'REMARK 3 \n',
'REMARK 3 DATA USED IN REFINEMENT. \n',
'REMARK 3 RESOLUTION RANGE HIGH (ANGSTROMS) : 1.70 \n',
'REMARK 3 RESOLUTION RANGE LOW (ANGSTROMS) : 30.00 \n',
'REMARK 3 DATA CUTOFF (SIGMA(F)) : 5.000 \n',
'REMARK 3 DATA CUTOFF HIGH (ABS(F)) : NULL \n',
'REMARK 3 DATA CUTOFF LOW (ABS(F)) : NULL \n',
'REMARK 3 COMPLETENESS (WORKING+TEST) (%) : 99.1 \n',
'REMARK 3 NUMBER OF REFLECTIONS : 6937 \n',
'REMARK 3 \n',
'REMARK 3 FIT TO DATA USED IN REFINEMENT. \n',
'REMARK 3 CROSS-VALIDATION METHOD : THROUGHOUT \n',
'REMARK 3 FREE R VALUE TEST SET SELECTION : RANDOM \n',
'REMARK 3 R VALUE (WORKING SET) : 0.220 \n',
'REMARK 3 FREE R VALUE : 0.280 \n',
'REMARK 3 FREE R VALUE TEST SET SIZE (%) : NULL \n',
'REMARK 3 FREE R VALUE TEST SET COUNT : NULL \n',
'REMARK 3 ESTIMATED ERROR OF FREE R VALUE : NULL \n',
'REMARK 3 \n',
'REMARK 3 FIT IN THE HIGHEST RESOLUTION BIN. \n',
'REMARK 3 TOTAL NUMBER OF BINS USED : NULL \n',
'REMARK 3 BIN RESOLUTION RANGE HIGH (A) : 1.70 \n',
'REMARK 3 BIN RESOLUTION RANGE LOW (A) : 1.75 \n',
'REMARK 3 BIN COMPLETENESS (WORKING+TEST) (%) : 97.00 \n',
'REMARK 3 REFLECTIONS IN BIN (WORKING SET) : NULL \n',
'REMARK 3 BIN R VALUE (WORKING SET) : 0.2400 \n',
'REMARK 3 BIN FREE R VALUE : 0.2200 \n',
'REMARK 3 BIN FREE R VALUE TEST SET SIZE (%) : NULL \n',
'REMARK 3 BIN FREE R VALUE TEST SET COUNT : NULL \n',
'REMARK 3 ESTIMATED ERROR OF BIN FREE R VALUE : 0.012 \n',
'REMARK 3 \n',
'REMARK 3 NUMBER OF NON-HYDROGEN ATOMS USED IN REFINEMENT. \n',
'REMARK 3 PROTEIN ATOMS : 1512 \n',
'REMARK 3 NUCLEIC ACID ATOMS : 0 \n',
'REMARK 3 HETEROGEN ATOMS : 0 \n',
'REMARK 3 SOLVENT ATOMS : 122 \n',
'REMARK 3 \n',
'REMARK 3 B VALUES. \n',
'REMARK 3 FROM WILSON PLOT (A**2) : 24.00 \n',
'REMARK 3 MEAN B VALUE (OVERALL, A**2) : NULL \n',
'REMARK 3 OVERALL ANISOTROPIC B VALUE. \n',
'REMARK 3 B11 (A**2) : NULL \n',
'REMARK 3 B22 (A**2) : NULL \n',
'REMARK 3 B33 (A**2) : NULL \n',
'REMARK 3 B12 (A**2) : NULL \n',
'REMARK 3 B13 (A**2) : NULL \n',
'REMARK 3 B23 (A**2) : NULL \n',
'REMARK 3 \n',
'REMARK 3 ESTIMATED COORDINATE ERROR. \n',
'REMARK 3 ESD FROM LUZZATI PLOT (A) : NULL \n',
'REMARK 3 ESD FROM SIGMAA (A) : NULL \n',
'REMARK 3 LOW RESOLUTION CUTOFF (A) : NULL \n',
'REMARK 3 \n',
'REMARK 3 CROSS-VALIDATED ESTIMATED COORDINATE ERROR. \n',
'REMARK 3 ESD FROM C-V LUZZATI PLOT (A) : NULL \n',
'REMARK 3 ESD FROM C-V SIGMAA (A) : NULL \n',
'REMARK 3 \n',
'REMARK 3 RMS DEVIATIONS FROM IDEAL VALUES. \n',
'REMARK 3 BOND LENGTHS (A) : 0.007 \n',
'REMARK 3 BOND ANGLES (DEGREES) : 1.32 \n',
'REMARK 3 DIHEDRAL ANGLES (DEGREES) : NULL \n',
'REMARK 3 IMPROPER ANGLES (DEGREES) : NULL \n',
'REMARK 3 \n',
'REMARK 3 ISOTROPIC THERMAL MODEL : NULL \n',
'REMARK 3 \n',
'REMARK 3 ISOTROPIC THERMAL FACTOR RESTRAINTS. RMS SIGMA \n',
'REMARK 3 MAIN-CHAIN BOND (A**2) : NULL ; NULL \n',
'REMARK 3 MAIN-CHAIN ANGLE (A**2) : NULL ; NULL \n',
'REMARK 3 SIDE-CHAIN BOND (A**2) : NULL ; NULL \n',
'REMARK 3 SIDE-CHAIN ANGLE (A**2) : NULL ; NULL \n',
'REMARK 3 \n',
'REMARK 3 BULK SOLVENT MODELING. \n',
'REMARK 3 METHOD USED : NULL \n',
'REMARK 3 KSOL : NULL \n',
'REMARK 3 BSOL : NULL \n',
'REMARK 3 \n',
'REMARK 3 NCS MODEL : NULL \n',
'REMARK 3 \n',
'REMARK 3 NCS RESTRAINTS. RMS SIGMA/WEIGHT \n',
'REMARK 3 GROUP 1 POSITIONAL (A) : NULL ; NULL \n',
'REMARK 3 GROUP 1 B-FACTOR (A**2) : NULL ; NULL \n',
'REMARK 3 \n',
'REMARK 3 PARAMETER FILE 1 : NULL \n',
'REMARK 3 TOPOLOGY FILE 1 : NULL \n',
'REMARK 3 \n',
'REMARK 3 OTHER REFINEMENT REMARKS: NULL \n',
'REMARK 4 \n',
'REMARK 4 2E12 COMPLIES WITH FORMAT V. 3.15, 01-DEC-08 \n',
'REMARK 100 \n',
'REMARK 100 THIS ENTRY HAS BEEN PROCESSED BY PDBJ ON 19-OCT-06. \n',
'REMARK 100 THE RCSB ID CODE IS RCSB026092. \n',
'REMARK 200 \n',
'REMARK 200 EXPERIMENTAL DETAILS \n',
'REMARK 200 EXPERIMENT TYPE : X-RAY DIFFRACTION \n',
'REMARK 200 DATE OF DATA COLLECTION : 28-JUL-06 \n',
'REMARK 200 TEMPERATURE (KELVIN) : 100 \n',
'REMARK 200 PH : 8.0 \n',
'REMARK 200 NUMBER OF CRYSTALS USED : 10 \n',
'REMARK 200 \n',
'REMARK 200 SYNCHROTRON (Y/N) : Y \n',
'REMARK 200 RADIATION SOURCE : NSRRC \n',
'REMARK 200 BEAMLINE : BL13B1 \n',
'REMARK 200 X-RAY GENERATOR MODEL : NULL \n',
'REMARK 200 MONOCHROMATIC OR LAUE (M/L) : M \n',
'REMARK 200 WAVELENGTH OR RANGE (A) : 0.96437, 0.97983 \n',
'REMARK 200 MONOCHROMATOR : NULL \n',
'REMARK 200 OPTICS : NULL \n',
'REMARK 200 \n',
'REMARK 200 DETECTOR TYPE : CCD \n',
'REMARK 200 DETECTOR MANUFACTURER : ADSC QUANTUM 315 \n',
'REMARK 200 INTENSITY-INTEGRATION SOFTWARE : DENZO \n',
'REMARK 200 DATA SCALING SOFTWARE : HKL-2000 \n',
'REMARK 200 \n',
'REMARK 200 NUMBER OF UNIQUE REFLECTIONS : 6937 \n',
'REMARK 200 RESOLUTION RANGE HIGH (A) : 1.700 \n',
'REMARK 200 RESOLUTION RANGE LOW (A) : 30.000 \n',
'REMARK 200 REJECTION CRITERIA (SIGMA(I)) : 2.000 \n',
'REMARK 200 \n',
'REMARK 200 OVERALL. \n',
'REMARK 200 COMPLETENESS FOR RANGE (%) : 99.7 \n',
'REMARK 200 DATA REDUNDANCY : 4.500 \n',
'REMARK 200 R MERGE (I) : 0.24000 \n',
'REMARK 200 R SYM (I) : 0.06000 \n',
'REMARK 200 FOR THE DATA SET : 8.0000 \n',
'REMARK 200 \n',
'REMARK 200 IN THE HIGHEST RESOLUTION SHELL. \n',
'REMARK 200 HIGHEST RESOLUTION SHELL, RANGE HIGH (A) : 1.70 \n',
'REMARK 200 HIGHEST RESOLUTION SHELL, RANGE LOW (A) : NULL \n',
'REMARK 200 COMPLETENESS FOR SHELL (%) : 97.5 \n',
'REMARK 200 DATA REDUNDANCY IN SHELL : 4.50 \n',
'REMARK 200 R MERGE FOR SHELL (I) : 0.06000 \n',
'REMARK 200 R SYM FOR SHELL (I) : 0.24000 \n',
'REMARK 200 FOR SHELL : 7.900 \n',
'REMARK 200 \n',
'REMARK 200 DIFFRACTION PROTOCOL: MAD \n',
'REMARK 200 METHOD USED TO DETERMINE THE STRUCTURE: MAD \n',
'REMARK 200 SOFTWARE USED: AMORE \n',
'REMARK 200 STARTING MODEL: NULL \n',
'REMARK 200 \n',
'REMARK 200 REMARK: NULL \n',
'REMARK 280 \n',
'REMARK 280 CRYSTAL \n',
'REMARK 280 SOLVENT CONTENT, VS (%): 46.26 \n',
'REMARK 280 MATTHEWS COEFFICIENT, VM (ANGSTROMS**3/DA): 2.29 \n',
'REMARK 280 \n',
'REMARK 280 CRYSTALLIZATION CONDITIONS: PH 8.0, VAPOR DIFFUSION, SITTING \n',
'REMARK 280 DROP, TEMPERATURE 298K \n',
'REMARK 290 REMARK: NULL \n',
'REMARK 300 \n',
'REMARK 300 BIOMOLECULE: 1 \n',
'REMARK 300 SEE REMARK 350 FOR THE AUTHOR PROVIDED AND/OR PROGRAM \n',
'REMARK 300 GENERATED ASSEMBLY INFORMATION FOR THE STRUCTURE IN \n',
'REMARK 300 THIS ENTRY. THE REMARK MAY ALSO PROVIDE INFORMATION ON \n',
'REMARK 300 BURIED SURFACE AREA. \n',
'REMARK 465 \n',
'REMARK 465 MISSING RESIDUES \n',
'REMARK 465 THE FOLLOWING RESIDUES WERE NOT LOCATED IN THE \n',
'REMARK 465 EXPERIMENT. (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN \n',
'REMARK 465 IDENTIFIER; SSSEQ=SEQUENCE NUMBER; I=INSERTION CODE.) \n',
'REMARK 465 \n',
'REMARK 465 M RES C SSSEQI \n',
'REMARK 465 LEU A 94 \n',
'REMARK 465 GLY A 95 \n',
'REMARK 465 ALA A 96 \n',
'REMARK 465 PRO A 97 \n',
'REMARK 465 GLN A 98 \n',
'REMARK 465 VAL A 99 \n',
'REMARK 465 MET A 100 \n',
'REMARK 465 PRO A 101 \n',
'REMARK 465 LEU B 94 \n',
'REMARK 465 GLY B 95 \n',
'REMARK 465 ALA B 96 \n',
'REMARK 465 PRO B 97 \n',
'REMARK 465 GLN B 98 \n',
'REMARK 465 VAL B 99 \n',
'REMARK 465 MET B 100 \n',
'REMARK 465 PRO B 101 \n',
'REMARK 500 \n',
'REMARK 500 GEOMETRY AND STEREOCHEMISTRY \n',
'REMARK 500 SUBTOPIC: CLOSE CONTACTS IN SAME ASYMMETRIC UNIT \n',
'REMARK 500 \n',
'REMARK 500 THE FOLLOWING ATOMS ARE IN CLOSE CONTACT. \n',
'REMARK 500 \n',
'REMARK 500 ATM1 RES C SSEQI ATM2 RES C SSEQI DISTANCE \n',
'REMARK 500 O HOH A 127 O HOH A 149 2.05 \n',
'REMARK 500 \n',
'REMARK 500 REMARK: NULL \n',
'REMARK 500 \n',
'REMARK 500 GEOMETRY AND STEREOCHEMISTRY \n',
'REMARK 500 SUBTOPIC: TORSION ANGLES \n',
'REMARK 500 \n',
'REMARK 500 TORSION ANGLES OUTSIDE THE EXPECTED RAMACHANDRAN REGIONS: \n',
'REMARK 500 (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN IDENTIFIER; \n',
'REMARK 500 SSEQ=SEQUENCE NUMBER; I=INSERTION CODE). \n',
'REMARK 500 \n',
'REMARK 500 STANDARD TABLE: \n',
'REMARK 500 FORMAT:(10X,I3,1X,A3,1X,A1,I4,A1,4X,F7.2,3X,F7.2) \n',
'REMARK 500 \n',
'REMARK 500 EXPECTED VALUES: GJ KLEYWEGT AND TA JONES (1996). PHI/PSI- \n',
'REMARK 500 CHOLOGY: RAMACHANDRAN REVISITED. STRUCTURE 4, 1395 - 1400 \n',
'REMARK 500 \n',
'REMARK 500 M RES CSSEQI PSI PHI \n',
'REMARK 500 ASN A 64 -175.84 -178.56 \n',
'REMARK 500 HIS A 71 -156.72 -164.33 \n',
'REMARK 500 LEU A 72 -70.52 -135.73 \n',
'REMARK 500 ALA A 74 -75.47 -29.45 \n',
'REMARK 500 SER A 75 -5.54 -145.62 \n',
'REMARK 500 GLN A 76 -178.36 65.32 \n',
'REMARK 500 GLU A 77 115.33 61.52 \n',
'REMARK 500 MET A 92 -36.89 93.21 \n',
'REMARK 500 LEU B 25 37.31 -77.89 \n',
'REMARK 500 GLN B 28 37.09 32.85 \n',
'REMARK 500 ARG B 30 132.20 -36.84 \n',
'REMARK 500 ASN B 64 -172.78 -175.93 \n',
'REMARK 500 GLN B 76 67.64 34.46 \n',
'REMARK 500 PRO B 91 -156.99 -48.61 \n',
'REMARK 500 MET B 92 -37.52 -160.44 \n',
'REMARK 500 \n',
'REMARK 500 REMARK: NULL \n',
'REMARK 525 \n',
'REMARK 525 SOLVENT \n',
'REMARK 525 \n',
'REMARK 525 THE SOLVENT MOLECULES HAVE CHAIN IDENTIFIERS THAT \n',
'REMARK 525 INDICATE THE POLYMER CHAIN WITH WHICH THEY ARE MOST \n',
'REMARK 525 CLOSELY ASSOCIATED. THE REMARK LISTS ALL THE SOLVENT \n',
'REMARK 525 MOLECULES WHICH ARE MORE THAN 5A AWAY FROM THE \n',
'REMARK 525 NEAREST POLYMER CHAIN (M = MODEL NUMBER; \n',
'REMARK 525 RES=RESIDUE NAME; C=CHAIN IDENTIFIER; SSEQ=SEQUENCE \n',
'REMARK 525 NUMBER; I=INSERTION CODE): \n',
'REMARK 525 \n',
'REMARK 525 M RES CSSEQI \n',
'REMARK 525 HOH B 115 DISTANCE = 6.82 ANGSTROMS \n',
'REMARK 525 HOH A 116 DISTANCE = 6.52 ANGSTROMS \n',
'REMARK 525 HOH B 119 DISTANCE = 5.12 ANGSTROMS \n',
'REMARK 525 HOH B 121 DISTANCE = 5.21 ANGSTROMS \n',
'REMARK 525 HOH B 123 DISTANCE = 5.18 ANGSTROMS \n',
'REMARK 525 HOH A 124 DISTANCE = 6.99 ANGSTROMS \n',
'REMARK 525 HOH B 124 DISTANCE = 5.13 ANGSTROMS \n',
'REMARK 525 HOH B 134 DISTANCE = 7.25 ANGSTROMS \n',
'REMARK 525 HOH B 140 DISTANCE = 5.54 ANGSTROMS \n',
'REMARK 525 HOH B 141 DISTANCE = 5.94 ANGSTROMS \n',
'REMARK 525 HOH B 142 DISTANCE = 6.60 ANGSTROMS \n',
'REMARK 525 HOH B 143 DISTANCE = 7.39 ANGSTROMS \n',
'REMARK 525 HOH A 145 DISTANCE = 9.25 ANGSTROMS \n',
'REMARK 525 HOH A 150 DISTANCE = 6.01 ANGSTROMS \n',
'REMARK 525 HOH B 152 DISTANCE = 5.46 ANGSTROMS \n',
'REMARK 525 HOH B 153 DISTANCE = 9.74 ANGSTROMS \n',
'REMARK 525 HOH B 154 DISTANCE = 9.32 ANGSTROMS \n',
'REMARK 525 HOH B 155 DISTANCE = 5.41 ANGSTROMS \n',
'REMARK 525 HOH B 163 DISTANCE = 5.16 ANGSTROMS \n',
'DBREF 2E12 A 1 101 UNP Q8P4R5 Q8P4R5_XANCP 1 101 \n',
'DBREF 2E12 B 1 101 UNP Q8P4R5 Q8P4R5_XANCP 1 101 \n',
'SEQRES 1 A 101 MET PRO LYS TYR ALA PRO HIS VAL TYR THR GLU GLN ALA \n',
'SEQRES 2 A 101 GLN ILE ALA THR LEU GLU HIS TRP VAL LYS LEU LEU ASP \n',
'SEQRES 3 A 101 GLY GLN GLU ARG VAL ARG ILE GLU LEU ASP ASP GLY SER \n',
'SEQRES 4 A 101 MET ILE ALA GLY THR VAL ALA VAL ARG PRO THR ILE GLN \n',
'SEQRES 5 A 101 THR TYR ARG ASP GLU GLN GLU ARG GLU GLY SER ASN GLY \n',
'SEQRES 6 A 101 GLN LEU ARG ILE ASP HIS LEU ASP ALA SER GLN GLU PRO \n',
'SEQRES 7 A 101 GLN TRP ILE TRP MET ASP ARG ILE VAL ALA VAL HIS PRO \n',
'SEQRES 8 A 101 MET PRO LEU GLY ALA PRO GLN VAL MET PRO \n',
'SEQRES 1 B 101 MET PRO LYS TYR ALA PRO HIS VAL TYR THR GLU GLN ALA \n',
'SEQRES 2 B 101 GLN ILE ALA THR LEU GLU HIS TRP VAL LYS LEU LEU ASP \n',
'SEQRES 3 B 101 GLY GLN GLU ARG VAL ARG ILE GLU LEU ASP ASP GLY SER \n',
'SEQRES 4 B 101 MET ILE ALA GLY THR VAL ALA VAL ARG PRO THR ILE GLN \n',
'SEQRES 5 B 101 THR TYR ARG ASP GLU GLN GLU ARG GLU GLY SER ASN GLY \n',
'SEQRES 6 B 101 GLN LEU ARG ILE ASP HIS LEU ASP ALA SER GLN GLU PRO \n',
'SEQRES 7 B 101 GLN TRP ILE TRP MET ASP ARG ILE VAL ALA VAL HIS PRO \n',
'SEQRES 8 B 101 MET PRO LEU GLY ALA PRO GLN VAL MET PRO \n',
'FORMUL 3 HOH *122(H2 O) \n',
'HELIX 1 1 GLU A 11 LEU A 24 1 14 \n',
'HELIX 2 2 GLU B 11 LEU B 25 1 15 \n',
'SHEET 1 A 3 ILE A 51 ARG A 55 0 \n',
'SHEET 2 A 3 GLU A 61 ASP A 70 -1 O ASN A 64 N GLN A 52 \n',
'SHEET 3 A 3 GLN A 79 TRP A 82 -1 O ILE A 81 N LEU A 67 \n',
'SHEET 1 B 5 ILE A 51 ARG A 55 0 \n',
'SHEET 2 B 5 GLU A 61 ASP A 70 -1 O ASN A 64 N GLN A 52 \n',
'SHEET 3 B 5 MET A 40 VAL A 45 -1 N THR A 44 O ASP A 70 \n',
'SHEET 4 B 5 ARG A 30 LEU A 35 -1 N ILE A 33 O ILE A 41 \n',
'SHEET 5 B 5 ILE A 86 PRO A 91 -1 O VAL A 87 N GLU A 34 \n',
'SHEET 1 C 5 PRO B 78 TRP B 82 0 \n',
'SHEET 2 C 5 GLN B 66 ASP B 70 -1 N ILE B 69 O GLN B 79 \n',
'SHEET 3 C 5 MET B 40 VAL B 47 -1 N ALA B 46 O ARG B 68 \n',
'SHEET 4 C 5 VAL B 31 LEU B 35 -1 N ILE B 33 O ILE B 41 \n',
'SHEET 5 C 5 ILE B 86 HIS B 90 -1 O VAL B 87 N GLU B 34 \n',
'SHEET 1 D 2 GLN B 52 ARG B 55 0 \n',
'SHEET 2 D 2 GLU B 61 ASN B 64 -1 O ASN B 64 N GLN B 52 \n',
'CRYST1 49.942 51.699 82.120 90.00 90.00 90.00 P 21 21 21 8 \n']
correct_header = {
'bio_cmx': [[[('A',), ('B',)], 1]],
'uc_mxs': array([[[ 1. , 0. , 0. , 0. ],\
[ 0. , 1. , 0. , 0. ],\
[ 0. , 0. , 1. , 0. ],\
[ 0. , 0. , 0. , 1. ]],\
[[ -1. , 0. , 0. , 24.971 ],\
[ 0. , -1. , 0. , 0. ],\
[ 0. , 0. , 1. , 41.06 ],\
[ 0. , 0. , 0. , 1. ]],\
[[ -1. , 0. , 0. , 0. ],\
[ 0. , 1. , 0. , 25.8495],\
[ 0. , 0. , -1. , 41.06 ],\
[ 0. , 0. , 0. , 1. ]],\
[[ 1. , 0. , 0. , 24.971 ],\
[ 0. , -1. , 0. , 25.8495],\
[ 0. , 0. , -1. , 0. ],\
[ 0. , 0. , 0. , 1. ]]]), \
'dbref_acc_full': 'Q8P4R5_XANCP', \
'name': 'TRANSLATION', \
'solvent_content': '46.26', \
'expdta': 'X-RAY', \
'bio_mxs': array([[[ 1., 0., 0., 0.],\
[ 0., 1., 0., 0.],\
[ 0., 0., 1., 0.],\
[ 0., 0., 0., 1.]]]),
'uc_omx': array([[ 49.94256605, 0. , 0. ],\
[ 0. , 51.69828879, 0. ],\
[ 0. , 0. , 82.12203334]]), \
'space_group': 'P 21 21 21', 'r_free': '0.280', \
'cryst1': '49.942 51.699 82.120 90.00 90.00 90.00', \
'experiment_type': 'X-RAY DIFFRACTION', \
'uc_fmx': array([[ 0.020023, 0. , 0. ],\
[ 0. , 0.019343, 0. ],\
[ 0. , 0. , 0.012177]]),\
'date': '17-OCT-06', \
'matthews': '2.29', \
'resolution': '1.70', \
'id': '2E12', \
'dbref_acc': 'Q8P4R5'}
parsed_header = parse_header(header)
for key, val in parsed_header.items():
assert val == correct_header[key]
def test_get_trailer_offset(self):
lines = ['ATOM','CONNECT']
assert get_trailer_offset(lines) == 1
def test_get_coords_offset(self):
lines = ['dummy','ATOM','CONNECT']
assert get_coords_offset(lines) == 1
def test_get_symmetry(self):
"""testing parsing of symmetry operators
"""
lines = [
'REMARK 290 SMTRY1 1 1.000000 0.000000 0.000000 0.00000 \n',
'REMARK 290 SMTRY2 1 0.000000 1.000000 0.000000 0.00000 \n',
'REMARK 290 SMTRY3 1 0.000000 0.000000 1.000000 0.00000 \n',
'REMARK 290 SMTRY1 2 -1.000000 0.000000 0.000000 24.97100 \n',
'REMARK 290 SMTRY2 2 0.000000 -1.000000 0.000000 0.00000 \n',
'REMARK 290 SMTRY3 2 0.000000 0.000000 1.000000 41.06000 \n',
'REMARK 290 SMTRY1 3 -1.000000 0.000000 0.000000 0.00000 \n',
'REMARK 290 SMTRY2 3 0.000000 1.000000 0.000000 25.84950 \n',
'REMARK 290 SMTRY3 3 0.000000 0.000000 -1.000000 41.06000 \n',
'REMARK 290 SMTRY1 4 1.000000 0.000000 0.000000 24.97100 \n',
'REMARK 290 SMTRY2 4 0.000000 -1.000000 0.000000 25.84950 \n',
'REMARK 290 SMTRY3 4 0.000000 0.000000 -1.000000 0.00000 \n',
'REMARK 290 \n',
'REMARK 290 REMARK: NULL \n',
'REMARK 350 \n',
'REMARK 350 COORDINATES FOR A COMPLETE MULTIMER REPRESENTING THE KNOWN \n',
'REMARK 350 BIOLOGICALLY SIGNIFICANT OLIGOMERIZATION STATE OF THE \n',
'REMARK 350 MOLECULE CAN BE GENERATED BY APPLYING BIOMT TRANSFORMATIONS \n',
'REMARK 350 GIVEN BELOW. BOTH NON-CRYSTALLOGRAPHIC AND \n',
'REMARK 350 CRYSTALLOGRAPHIC OPERATIONS ARE GIVEN. \n',
'REMARK 350 \n',
'REMARK 350 BIOMOLECULE: 1 \n',
'REMARK 350 AUTHOR DETERMINED BIOLOGICAL UNIT: DIMERIC \n',
'REMARK 350 APPLY THE FOLLOWING TO CHAINS: A, B \n',
'REMARK 350 BIOMT1 1 1.000000 0.000000 0.000000 0.00000 \n',
'REMARK 350 BIOMT2 1 0.000000 1.000000 0.000000 0.00000 \n',
'REMARK 350 BIOMT3 1 0.000000 0.000000 1.000000 0.00000 \n',
'CRYST1 49.942 51.699 82.120 90.00 90.00 90.00 P 21 21 21 8 \n',
'ORIGX1 1.000000 0.000000 0.000000 0.00000 \n',
'ORIGX2 0.000000 1.000000 0.000000 0.00000 \n',
'ORIGX3 0.000000 0.000000 1.000000 0.00000 \n',
'SCALE1 0.020023 0.000000 0.000000 0.00000 \n',
'SCALE2 0.000000 0.019343 0.000000 0.00000 \n',
'SCALE3 0.000000 0.000000 0.012177 0.00000 \n']
sym = get_symmetry(lines)
correct_sym = {
'bio_cmx': [[[('A',), ('B',)], 1]],
'uc_mxs': array([[[ 1. , 0. , 0. , 0. ],\
[ 0. , 1. , 0. , 0. ],\
[ 0. , 0. , 1. , 0. ],\
[ 0. , 0. , 0. , 1. ]],\
[[ -1. , 0. , 0. , 24.971 ],\
[ 0. , -1. , 0. , 0. ],\
[ 0. , 0. , 1. , 41.06 ],\
[ 0. , 0. , 0. , 1. ]],\
[[ -1. , 0. , 0. , 0. ],\
[ 0. , 1. , 0. , 25.8495],\
[ 0. , 0. , -1. , 41.06 ],\
[ 0. , 0. , 0. , 1. ]],\
[[ 1. , 0. , 0. , 24.971 ],\
[ 0. , -1. , 0. , 25.8495],\
[ 0. , 0. , -1. , 0. ],\
[ 0. , 0. , 0. , 1. ]]]), \
'bio_mxs': array([[[ 1., 0., 0., 0.],\
[ 0., 1., 0., 0.],\
[ 0., 0., 1., 0.],\
[ 0., 0., 0., 1.]]]),
'uc_omx': array([[ 49.94256605, 0. , 0. ],\
[ 0. , 51.69828879, 0. ],\
[ 0. , 0. , 82.12203334]]), \
'uc_fmx': array([[ 0.020023, 0. , 0. ],\
[ 0. , 0.019343, 0. ],\
[ 0. , 0. , 0.012177]]),}
for key in sym:
try:
assert sym[key] == correct_sym[key]
except ValueError:
assert allclose(sym[key], correct_sym[key])
def test_dict2pdb(self):
"""testing pdb dict round-trip.
"""
line = 'ATOM 1 N MET A 1 53.045 42.225 33.724 1.00 2.75 N\n'
d = pdb2dict(line)
line2 = dict2pdb(d)
assert line == line2
d.pop('coords')
assert d == {'ser_num': 1, 'res_long_id': ('MET', 1, ' '),
'h_flag': ' ',
'at_name': ' N ',
'at_long_id': ('N', ' '),
'bfactor': 2.75, 'chain_id': 'A',
'occupancy': 1.0, 'element': ' N',
'res_name': 'MET',
'seg_id': ' ', 'at_id': 'N',
'alt_loc': ' ',
'res_ic': ' ',
'res_id': 1,
'at_type': 'ATOM '}
def test_dict2ter(self):
d = {'ser_num': 1, 'chain_id': 'A', 'res_name': 'MET', 'res_ic': ' ', \
'res_id': 1,}
assert dict2ter(d) == 'TER 2 MET A 1 \n'
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_phylip.py 000644 000765 000024 00000035312 12024702176 022476 0 ustar 00jrideout staff 000000 000000 #!/bin/env python
#file cogent/parse/test_phylip.py
"""Unit tests for the phylip parser
"""
from cogent.parse.phylip import MinimalPhylipParser, get_align_for_phylip
from cogent.parse.record import RecordError
from cogent.util.unit_test import TestCase, main
from StringIO import StringIO
__author__ = "Micah Hamady"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Micah Hamady", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Micah Hamady"
__email__ = "hamady@colorado.edu"
__status__ = "Production"
class PhylipGenericTest(TestCase):
"""Setup data for Phylip parsers."""
def setUp(self):
"""standard files"""
self.big_interleaved = StringIO("""10 705 I
Cow ATGGCATATCCCATACAACTAGGATTCCAAGATGCAACATCACCAATCATAGAAGAACTA
Carp ATGGCACACCCAACGCAACTAGGTTTCAAGGACGCGGCCATACCCGTTATAGAGGAACTT
Chicken ATGGCCAACCACTCCCAACTAGGCTTTCAAGACGCCTCATCCCCCATCATAGAAGAGCTC
Human ATGGCACATGCAGCGCAAGTAGGTCTACAAGACGCTACTTCCCCTATCATAGAAGAGCTT
Loach ATGGCACATCCCACACAATTAGGATTCCAAGACGCGGCCTCACCCGTAATAGAAGAACTT
Mouse ATGGCCTACCCATTCCAACTTGGTCTACAAGACGCCACATCCCCTATTATAGAAGAGCTA
Rat ATGGCTTACCCATTTCAACTTGGCTTACAAGACGCTACATCACCTATCATAGAAGAACTT
Seal ATGGCATACCCCCTACAAATAGGCCTACAAGATGCAACCTCTCCCATTATAGAGGAGTTA
Whale ATGGCATATCCATTCCAACTAGGTTTCCAAGATGCAGCATCACCCATCATAGAAGAGCTC
Frog ATGGCACACCCATCACAATTAGGTTTTCAAGACGCAGCCTCTCCAATTATAGAAGAATTA
CTTCACTTTCATGACCACACGCTAATAATTGTCTTCTTAATTAGCTCATTAGTACTTTAC
CTTCACTTCCACGACCACGCATTAATAATTGTGCTCCTAATTAGCACTTTAGTTTTATAT
GTTGAATTCCACGACCACGCCCTGATAGTCGCACTAGCAATTTGCAGCTTAGTACTCTAC
ATCACCTTTCATGATCACGCCCTCATAATCATTTTCCTTATCTGCTTCCTAGTCCTGTAT
CTTCACTTCCATGACCATGCCCTAATAATTGTATTTTTGATTAGCGCCCTAGTACTTTAT
ATAAATTTCCATGATCACACACTAATAATTGTTTTCCTAATTAGCTCCTTAGTCCTCTAT
ACAAACTTTCATGACCACACCCTAATAATTGTATTCCTCATCAGCTCCCTAGTACTTTAT
CTACACTTCCATGACCACACATTAATAATTGTGTTCCTAATTAGCTCATTAGTACTCTAC
CTACACTTTCACGATCATACACTAATAATCGTTTTTCTAATTAGCTCTTTAGTTCTCTAC
CTTCACTTCCACGACCATACCCTCATAGCCGTTTTTCTTATTAGTACGCTAGTTCTTTAC
ATTATTTCACTAATACTAACGACAAAGCTGACCCATACAAGCACGATAGATGCACAAGAA
ATTATTACTGCAATGGTATCAACTAAACTTACTAATAAATATATTCTAGACTCCCAAGAA
CTTCTAACTCTTATACTTATAGAAAAACTATCA---TCAAACACCGTAGATGCCCAAGAA
GCCCTTTTCCTAACACTCACAACAAAACTAACTAATACTAACATCTCAGACGCTCAGGAA
GTTATTATTACAACCGTCTCAACAAAACTCACTAACATATATATTTTGGACTCACAAGAA
ATCATCTCGCTAATATTAACAACAAAACTAACACATACAAGCACAATAGATGCACAAGAA
ATTATTTCACTAATACTAACAACAAAACTAACACACACAAGCACAATAGACGCCCAAGAA
ATTATCTCACTTATACTAACCACGAAACTCACCCACACAAGTACAATAGACGCACAAGAA
ATTATTACCCTAATGCTTACAACCAAATTAACACATACTAGTACAATAGACGCCCAAGAA
ATTATTACTATTATAATAACTACTAAACTAACTAATACAAACCTAATGGACGCACAAGAG
GTAGAGACAATCTGAACCATTCTGCCCGCCATCATCTTAATTCTAATTGCTCTTCCTTCT
ATCGAAATCGTATGAACCATTCTACCAGCCGTCATTTTAGTACTAATCGCCCTGCCCTCC
GTTGAACTAATCTGAACCATCCTACCCGCTATTGTCCTAGTCCTGCTTGCCCTCCCCTCC
ATAGAAACCGTCTGAACTATCCTGCCCGCCATCATCCTAGTCCTCATCGCCCTCCCATCC
ATTGAAATCGTATGAACTGTGCTCCCTGCCCTAATCCTCATTTTAATCGCCCTCCCCTCA
GTTGAAACCATTTGAACTATTCTACCAGCTGTAATCCTTATCATAATTGCTCTCCCCTCT
GTAGAAACAATTTGAACAATTCTCCCAGCTGTCATTCTTATTCTAATTGCCCTTCCCTCC
GTGGAAACGGTGTGAACGATCCTACCCGCTATCATTTTAATTCTCATTGCCCTACCATCA
GTAGAAACTGTCTGAACTATCCTCCCAGCCATTATCTTAATTTTAATTGCCTTGCCTTCA
ATCGAAATAGTGTGAACTATTATACCAGCTATTAGCCTCATCATAATTGCCCTTCCATCC
TTACGAATTCTATACATAATAGATGAAATCAATAACCCATCTCTTACAGTAAAAACCATA
CTACGCATCCTGTACCTTATAGACGAAATTAACGACCCTCACCTGACAATTAAAGCAATA
CTCCAAATCCTCTACATAATAGACGAAATCGACGAACCTGATCTCACCCTAAAAGCCATC
CTACGCATCCTTTACATAACAGACGAGGTCAACGATCCCTCCCTTACCATCAAATCAATT
CTACGAATTCTATATCTTATAGACGAGATTAATGACCCCCACCTAACAATTAAGGCCATG
CTACGCATTCTATATATAATAGACGAAATCAACAACCCCGTATTAACCGTTAAAACCATA
CTACGAATTCTATACATAATAGACGAGATTAATAACCCAGTTCTAACAGTAAAAACTATA
TTACGAATCCTCTACATAATGGACGAGATCAATAACCCTTCCTTGACCGTAAAAACTATA
TTACGGATCCTTTACATAATAGACGAAGTCAATAACCCCTCCCTCACTGTAAAAACAATA
CTTCGTATCCTATATTTAATAGATGAAGTTAATGATCCACACTTAACAATTAAAGCAATC
GGACATCAGTGATACTGAAGCTATGAGTATACAGATTATGAGGACTTAAGCTTCGACTCC
GGACACCAATGATACTGAAGTTACGAGTATACAGACTATGAAAATCTAGGATTCGACTCC
GGACACCAATGATACTGAACCTATGAATACACAGACTTCAAGGACCTCTCATTTGACTCC
GGCCACCAATGGTACTGAACCTACGAGTACACCGACTACGGCGGACTAATCTTCAACTCC
GGGCACCAATGATACTGAAGCTACGAGTATACTGATTATGAAAACTTAAGTTTTGACTCC
GGGCACCAATGATACTGAAGCTACGAATATACTGACTATGAAGACCTATGCTTTGATTCA
GGACACCAATGATACTGAAGCTATGAATATACTGACTATGAAGACCTATGCTTTGACTCC
GGACATCAGTGATACTGAAGCTATGAGTACACAGACTACGAAGACCTGAACTTTGACTCA
GGTCACCAATGATATTGAAGCTATGAGTATACCGACTACGAAGACCTAAGCTTCGACTCC
GGCCACCAATGATACTGAAGCTACGAATATACTAACTATGAGGATCTCTCATTTGACTCT
TACATAATTCCAACATCAGAATTAAAGCCAGGGGAGCTACGACTATTAGAAGTCGATAAT
TATATAGTACCAACCCAAGACCTTGCCCCCGGACAATTCCGACTTCTGGAAACAGACCAC
TACATAACCCCAACAACAGACCTCCCCCTAGGCCACTTCCGCCTACTAGAAGTCGACCAT
TACATACTTCCCCCATTATTCCTAGAACCAGGCGACCTGCGACTCCTTGACGTTGACAAT
TACATAATCCCCACCCAGGACCTAACCCCTGGACAATTCCGGCTACTAGAGACAGACCAC
TATATAATCCCAACAAACGACCTAAAACCTGGTGAACTACGACTGCTAGAAGTTGATAAC
TACATAATCCCAACCAATGACCTAAAACCAGGTGAACTTCGTCTATTAGAAGTTGATAAT
TATATGATCCCCACACAAGAACTAAAGCCCGGAGAACTACGACTGCTAGAAGTAGACAAT
TATATAATCCCAACATCAGACCTAAAGCCAGGAGAACTACGATTATTAGAAGTAGATAAC
TATATAATTCCAACTAATGACCTTACCCCTGGACAATTCCGGCTGCTAGAAGTTGATAAT
CGAGTTGTACTACCAATAGAAATAACAATCCGAATGTTAGTCTCCTCTGAAGACGTATTA
CGAATAGTTGTTCCAATAGAATCCCCAGTCCGTGTCCTAGTATCTGCTGAAGACGTGCTA
CGCATTGTAATCCCCATAGAATCCCCCATTCGAGTAATCATCACCGCTGATGACGTCCTC
CGAGTAGTACTCCCGATTGAAGCCCCCATTCGTATAATAATTACATCACAAGACGTCTTG
CGAATGGTTGTTCCCATAGAATCCCCTATTCGCATTCTTGTTTCCGCCGAAGATGTACTA
CGAGTCGTTCTGCCAATAGAACTTCCAATCCGTATATTAATTTCATCTGAAGACGTCCTC
CGGGTAGTCTTACCAATAGAACTTCCAATTCGTATACTAATCTCATCCGAAGACGTCCTG
CGAGTAGTCCTCCCAATAGAAATAACAATCCGCATACTAATCTCATCAGAAGATGTACTC
CGAGTTGTCTTACCTATAGAAATAACAATCCGAATATTAGTCTCATCAGAAGACGTACTC
CGAATAGTAGTCCCAATAGAATCTCCAACCCGACTTTTAGTTACAGCCGAAGACGTCCTC
CACTCATGAGCTGTGCCCTCTCTAGGACTAAAAACAGACGCAATCCCAGGCCGTCTAAAC
CATTCTTGAGCTGTTCCATCCCTTGGCGTAAAAATGGACGCAGTCCCAGGACGACTAAAT
CACTCATGAGCCGTACCCGCCCTCGGGGTAAAAACAGACGCAATCCCTGGACGACTAAAT
CACTCATGAGCTGTCCCCACATTAGGCTTAAAAACAGATGCAATTCCCGGACGTCTAAAC
CACTCCTGGGCCCTTCCAGCCATGGGGGTAAAGATAGACGCGGTCCCAGGACGCCTTAAC
CACTCATGAGCAGTCCCCTCCCTAGGACTTAAAACTGATGCCATCCCAGGCCGACTAAAT
CACTCATGAGCCATCCCTTCACTAGGGTTAAAAACCGACGCAATCCCCGGCCGCCTAAAC
CACTCATGAGCCGTACCGTCCCTAGGACTAAAAACTGATGCTATCCCAGGACGACTAAAC
CACTCATGGGCCGTACCCTCCTTGGGCCTAAAAACAGATGCAATCCCAGGACGCCTAAAC
CACTCGTGAGCTGTACCCTCCTTGGGTGTCAAAACAGATGCAATCCCAGGACGACTTCAT
CAAACAACCCTTATATCGTCCCGTCCAGGCTTATATTACGGTCAATGCTCAGAAATTTGC
CAAGCCGCCTTTATTGCCTCACGCCCAGGGGTCTTTTACGGACAATGCTCTGAAATTTGT
CAAACCTCCTTCATCACCACTCGACCAGGAGTGTTTTACGGACAATGCTCAGAAATCTGC
CAAACCACTTTCACCGCTACACGACCGGGGGTATACTACGGTCAATGCTCTGAAATCTGT
CAAACCGCCTTTATTGCCTCCCGCCCCGGGGTATTCTATGGGCAATGCTCAGAAATCTGT
CAAGCAACAGTAACATCAAACCGACCAGGGTTATTCTATGGCCAATGCTCTGAAATTTGT
CAAGCTACAGTCACATCAAACCGACCAGGTCTATTCTATGGCCAATGCTCTGAAATTTGC
CAAACAACCCTAATAACCATACGACCAGGACTGTACTACGGTCAATGCTCAGAAATCTGT
CAAACAACCTTAATATCAACACGACCAGGCCTATTTTATGGACAATGCTCAGAGATCTGC
CAAACATCATTTATTGCTACTCGTCCGGGAGTATTTTACGGACAATGTTCAGAAATTTGC
GGGTCAAACCACAGTTTCATACCCATTGTCCTTGAGTTAGTCCCACTAAAGTACTTTGAA
GGAGCTAATCACAGCTTTATACCAATTGTAGTTGAAGCAGTACCTCTCGAACACTTCGAA
GGAGCTAACCACAGCTACATACCCATTGTAGTAGAGTCTACCCCCCTAAAACACTTTGAA
GGAGCAAACCACAGTTTCATGCCCATCGTCCTAGAATTAATTCCCCTAAAAATCTTTGAA
GGAGCAAACCACAGCTTTATACCCATCGTAGTAGAAGCGGTCCCACTATCTCACTTCGAA
GGATCTAACCATAGCTTTATGCCCATTGTCCTAGAAATGGTTCCACTAAAATATTTCGAA
GGCTCAAATCACAGCTTCATACCCATTGTACTAGAAATAGTGCCTCTAAAATATTTCGAA
GGTTCAAACCACAGCTTCATACCTATTGTCCTCGAATTGGTCCCACTATCCCACTTCGAG
GGCTCAAACCACAGTTTCATACCAATTGTCCTAGAACTAGTACCCCTAGAAGTCTTTGAA
GGAGCAAACCACAGCTTTATACCAATTGTAGTTGAAGCAGTACCGCTAACCGACTTTGAA
AAATGATCTGCGTCAATATTA---------------------TAA
AACTGATCCTCATTAATACTAGAAGACGCCTCGCTAGGAAGCTAA
GCCTGATCCTCACTA------------------CTGTCATCTTAA
ATA---------------------GGGCCCGTATTTACCCTATAG
AACTGGTCCACCCTTATACTAAAAGACGCCTCACTAGGAAGCTAA
AACTGATCTGCTTCAATAATT---------------------TAA
AACTGATCAGCTTCTATAATT---------------------TAA
AAATGATCTACCTCAATGCTT---------------------TAA
AAATGATCTGTATCAATACTA---------------------TAA
AACTGATCTTCATCAATACTA---GAAGCATCACTA------AGA
""")
self.space_interleaved = StringIO(""" 5 176 I
cox2_leita MAFILSFWMI FLLDSVIVLL SFVCFVCVWI CALLFSTVLL VSKLNNIYCT
cox2_crifa MAFILSFWMI FLIDAVIVLL SFVCFVCIWI CSLFFSSFLL VSKINNVYCT
cox2_bsalt MSFIISFWML FLIDSLIVLL SGAIFVCIWI CSLFFLCILF ICKLDYIFCS
cox2_trybb MSFILTFWMI FLMDSIIVLI SFSIFLSVWI CALIIATVLT VTKINNIYCT
cox2_tborr MLFFINQLLL LLVDTFVILE IFSLFVCVFI IVMYILFINY NIFLKNINVY
WDFTASKFID VYWFTIGGMF SLGLLLRLCL LLYFGHLNFV SFDLCKVVGF
WDFTASKFID AYWFTIGGMF VLCLLLRLCL LLYFGCLNFV SFDLCKVVGF
WDFISAKFID LYWFTLGCLF IVCLLIRLCL LLYFSCLNFV CFDLCKCIGF
WDFISSKFID TYWFVLGMMF ILCLLLRLCL LLYFSCINFV SFDLCKVIGF
LDFIGSKYLD LYWFLIGIFF VIVLLIRLCL LLYYSWISLL IFDLCKIMGF
QWYWVYFIFG ETTIFSNLIL ESDYMIGDLR LLQCNHVLTL LSLVIYKLWL
QWYWVYFIFG ETTIFSNLIL ESDYLIGDLR LLQCNHVLTL LSLVIYKLWL
QWYWVYFIFG ETTIFSNLIL ESDYLIGDLR LLQCNHVLTL LSLVIYKVWL
QWYWVYFLFG ETTIFSNLIL ESDYLIGDLR ILQCNHVLTL LSLVIYKLWV
QWYWIFFVFK ENVIFSNLLI ESDYWIGDLR LLQCNNTFNL ICLVVYKIWV
SAVDVIHSFA ISSLGVKVEN LVAVMK
SAVDVIHSFA VSSLGIKVDC IPGRCN
SAIDVIHSFT LANLGIKVD? ?PGRCN
SAVDVIHSFT ISSLGIKVEN PGRCNE
TSIDVIHSFT ISTLGIKIDC IPGRCN
""")
self.interleaved_little = StringIO(""" 6 39 I
Archaeopt CGATGCTTAC CGCCGATGCT
HesperorniCGTTACTCGT TGTCGTTACT
BaluchitheTAATGTTAAT TGTTAATGTT
B. virginiTAATGTTCGT TGTTAATGTT
BrontosaurCAAAACCCAT CATCAAAACC
B.subtilisGGCAGCCAAT CACGGCAGCC
TACCGCCGAT GCTTACCGC
CGTTGTCGTT ACTCGTTGT
AATTGTTAAT GTTAATTGT
CGTTGTTAAT GTTCGTTGT
CATCATCAAA ACCCATCAT
AATCACGGCA GCCAATCAC
""")
self.empty = []
self.noninterleaved_little = StringIO(""" 6 20
Archaeopt CGATGCTTAC CGCCGATGCT
HesperorniCGTTACTCGT TGTCGTTACT
BaluchitheTAATGTTAAT TGTTAATGTT
B. virginiTAATGTTCGT TGTTAATGTT
BrontosaurCAAAACCCAT CATCAAAACC
B.subtilisGGCAGCCAAT CACGGCAGCC
""")
self.noninterleaved_big = StringIO("""10 297
Rhesus tgtggcacaaatactcatgccagctcattacagcatgagaac---agtttgttactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggcttg
gcaaggagccaacataacagatggactggaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagatctgaatgctaatgccctgtatgagagaaaagaatgg
aataagcaaaaactgccatgctctgagaatcctagagacactgaagatgttccttgg
Manatee tgtggcacaaatactcatgccagctcattacagcatgagaatagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtcataaaagcaaacagcctggctta
acaaggagccagcagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cctagcacagagaaaaaggtagatatgaatgctaatccattgtatgagagaaaagaagtg
aataagcagaaacctccatgctccgagagtgttagagatacacaagatattccttgg
Pig tgtggcacagatactcatgccagctcgttacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattttgtaataaaagcaagcagcctgtctta
gcaaagagccaacagagcagatgggctgaaagtaagggcacatgtaatgataggcagact
cctaacacagagaaaaaggtagttctgaatactgatctcctgtatgggagaaacgaactg
aataagcagaaacctgcgtgctctgacagtcctagagattcccaagatgttccttgg
""")
class MinimalPhylipParserTests(PhylipGenericTest):
"""Tests of MinimalPhylipParser: returns (label, seq) tuples."""
def test_empty(self):
"""MinimalFastaParser should return empty list from 'file' w/o labels"""
self.assertEqual(list(MinimalPhylipParser(self.empty)), [])
def test_minimal_parser(self):
"""MinimalFastaParser should read single record as (label, seq) tuple"""
seqs = list(MinimalPhylipParser(self.big_interleaved))
self.assertEqual(len(seqs), 10)
label, seq = seqs[-1]
self.assertEqual(label, 'Frog')
self.assertEqual(seq, \
'ATGGCACACCCATCACAATTAGGTTTTCAAGACGCAGCCTCTCCAATTATAGAAGAATTACTTCACTTCCACGACCATACCCTCATAGCCGTTTTTCTTATTAGTACGCTAGTTCTTTACATTATTACTATTATAATAACTACTAAACTAACTAATACAAACCTAATGGACGCACAAGAGATCGAAATAGTGTGAACTATTATACCAGCTATTAGCCTCATCATAATTGCCCTTCCATCCCTTCGTATCCTATATTTAATAGATGAAGTTAATGATCCACACTTAACAATTAAAGCAATCGGCCACCAATGATACTGAAGCTACGAATATACTAACTATGAGGATCTCTCATTTGACTCTTATATAATTCCAACTAATGACCTTACCCCTGGACAATTCCGGCTGCTAGAAGTTGATAATCGAATAGTAGTCCCAATAGAATCTCCAACCCGACTTTTAGTTACAGCCGAAGACGTCCTCCACTCGTGAGCTGTACCCTCCTTGGGTGTCAAAACAGATGCAATCCCAGGACGACTTCATCAAACATCATTTATTGCTACTCGTCCGGGAGTATTTTACGGACAATGTTCAGAAATTTGCGGAGCAAACCACAGCTTTATACCAATTGTAGTTGAAGCAGTACCGCTAACCGACTTTGAAAACTGATCTTCATCAATACTA---GAAGCATCACTA------AGA')
self.assertEqual(seqs[0][0], 'Cow')
seqs = list(MinimalPhylipParser(self.space_interleaved))
self.assertEqual(len(seqs), 5)
self.assertEqual(seqs[0][0], 'cox2_leita')
self.assertEqual(seqs[-1][0], 'cox2_tborr')
self.assertEqual(len(seqs[0][1]), 176)
self.assertEqual(len(seqs[-1][1]), 176)
seqs = list(MinimalPhylipParser(self.interleaved_little))
self.assertEqual(len(seqs), 6)
self.assertEqual(seqs[1][0], 'Hesperorni')
self.assertEqual(seqs[-1][0], 'B.subtilis')
self.assertEqual(seqs[-1][1], 'GGCAGCCAATCACGGCAGCCAATCACGGCAGCCAATCAC')
seqs = list(MinimalPhylipParser(self.noninterleaved_little))
self.assertEqual(len(seqs), 6)
self.assertEqual(seqs[0][0], 'Archaeopt')
self.assertEqual(seqs[-1][0], 'B.subtilis')
self.assertEqual(seqs[-1][-1], 'GGCAGCCAATCACGGCAGCC')
seqs = list(MinimalPhylipParser(self.noninterleaved_big))
self.assertEqual(len(seqs), 3)
self.assertEqual(seqs[0][0], 'Rhesus')
self.assertEqual(seqs[-1][0], 'Pig')
self.assertEqual(seqs[-1][1], 'tgtggcacagatactcatgccagctcgttacagcatgagaacagcagtttattactcactaaagacagaatgaatgtagaaaaggctgaattttgtaataaaagcaagcagcctgtcttagcaaagagccaacagagcagatgggctgaaagtaagggcacatgtaatgataggcagactcctaacacagagaaaaaggtagttctgaatactgatctcctgtatgggagaaacgaactgaataagcagaaacctgcgtgctctgacagtcctagagattcccaagatgttccttgg')
def test_get_align(self):
"""get_align_for_phylip should return Aligment object for phylip files"""
align = get_align_for_phylip(self.big_interleaved)
align = get_align_for_phylip(self.interleaved_little)
s = str(align)
self.assertEqual(s, '''>Archaeopt
CGATGCTTACCGCCGATGCTTACCGCCGATGCTTACCGC
>Hesperorni
CGTTACTCGTTGTCGTTACTCGTTGTCGTTACTCGTTGT
>Baluchithe
TAATGTTAATTGTTAATGTTAATTGTTAATGTTAATTGT
>B. virgini
TAATGTTCGTTGTTAATGTTCGTTGTTAATGTTCGTTGT
>Brontosaur
CAAAACCCATCATCAAAACCCATCATCAAAACCCATCAT
>B.subtilis
GGCAGCCAATCACGGCAGCCAATCACGGCAGCCAATCAC
''')
align = get_align_for_phylip(self.noninterleaved_little)
s = str(align)
self.assertEqual(s, '''>Archaeopt
CGATGCTTACCGCCGATGCT
>Hesperorni
CGTTACTCGTTGTCGTTACT
>Baluchithe
TAATGTTAATTGTTAATGTT
>B. virgini
TAATGTTCGTTGTTAATGTT
>Brontosaur
CAAAACCCATCATCAAAACC
>B.subtilis
GGCAGCCAATCACGGCAGCC
''')
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_pknotsrg.py 000644 000765 000024 00000002024 12024702176 023032 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.pknotsrg import pknotsrg_parser
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class PknotsrgParserTest(TestCase):
"""Provides tests for pknotsRG RNA secondary structure format parsers"""
def setUp(self):
"""Setup function"""
#output
self.pknotsrg_out = PKNOTSRG
#expected
self.pknotsrg_exp = [['UGCAUAAUAGCUCC',[(0,8),(3,11),(5,13)],-22.40]]
def test_pknotsrg_output(self):
"""Test for pknotsrg format parser"""
obs = pknotsrg_parser(self.pknotsrg_out)
self.assertEqual(obs,self.pknotsrg_exp)
PKNOTSRG = ['UGCAUAAUAGCUCC\n', '(..{.[..)..}.] (-22.40)\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_psl.py 000644 000765 000024 00000003022 12024702176 021760 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the PSL parser.
Compatible with blat v.34
"""
from cogent.parse.psl import make_header, MinimalPslParser, PslToTable
from cogent.util.unit_test import TestCase, main
from cogent import LoadTable
__author__ = "Gavin Huttley, Anuj Pahwa"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight","Peter Maxwell", "Gavin Huttley", "Anuj Pahwa"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Development"
fname = 'data/test.psl'
class Test(TestCase):
def test_header(self):
"""should return correct header"""
expect = ['match', 'mis-match', 'rep. match', "N's", 'Q gap count',
'Q gap bases', 'T gap count', 'T gap bases', 'strand', 'Q name',
'Q size', 'Q start', 'Q end', 'T name', 'T size', 'T start',
'T end', 'block count', 'blockSizes', 'qStarts', 'tStarts']
parser = MinimalPslParser(fname)
version = parser.next()
header = parser.next()
self.assertEqual(header, expect)
def test_psl_to_table(self):
table = PslToTable(fname)
def test_getting_seq_coords(self):
"""get correct sequence coordinates to produce a trimmed sequence"""
table = PslToTable(fname)
for row in table:
query_name = row["Q name"]
query_strand = row["strand"]
q_start = row["Q start"]
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_rdb.py 000644 000765 000024 00000030077 12024702176 021743 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
#test_rdb.py
"""Unit test for RDB Parser
"""
from cogent.util.unit_test import TestCase, main
from cogent.parse.rdb import RdbParser, MinimalRdbParser,is_seq_label,\
InfoMaker, create_acceptable_sequence
from cogent.core.sequence import Sequence, DnaSequence, RnaSequence
from cogent.core.info import Info
from cogent.parse.record import RecordError
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Production"
class RdbTests(TestCase):
"""Tests for top-level functions in Rdb.py"""
def test_is_seq_label(self):
"""is_seq_label should return True if a line starts with 'seq:'"""
seq = 'seq:this is a sequence line'
not_seq = 'this is not a sequence line'
still_not_seq = 'this seq: is still not a sequence line'
self.assertEqual(is_seq_label(seq),True)
self.assertEqual(is_seq_label(not_seq),False)
self.assertEqual(is_seq_label(still_not_seq),False)
def test_create_acceptable_sequence(self):
"""create_acceptable_sequence: should handle 'o' and sec. struct"""
f = create_acceptable_sequence
# should keep any char accepted by RNA.Alphabet.DegenGapped
s = "UCAG---NRYBDHKMNSRWVY?"
self.assertEqual(f(s),s)
# should replace 'o' by '?'
s = "UCAG-oo-ACGU"
self.assertEqual(f(s), "UCAG-??-ACGU")
# should strip out secondary info
s = "{UC^AG-[oo]-A(CG)U}"
self.assertEqual(f(s), "UCAG-??-ACGU")
# should leave other chars untouched
s = "XYZ1234"
self.assertEqual(f(s), "XYZ1234")
class InfoMakerTests(TestCase):
"""Tests for the Constructor InfoMaker. Should return an Info object"""
def test_empty(self):
"""InfoMaker: should return empty Info from empty header"""
empty_header = []
obs = InfoMaker(empty_header)
exp = Info()
self.assertEqual(obs,exp)
def test_full(self):
"""InfoMaker should return Info object with name, value pairs"""
test_header = ['acc: X3402','abc:1','mty: ssu','seq: Mit. X3402',\
'','nonsense',':no_name']
obs = InfoMaker(test_header)
exp = Info()
exp.rRNA = 'X3402'
exp.abc = '1'
exp.Species = 'Mit. X3402'
exp.Gene = 'ssu'
self.assertEqual(obs,exp)
class GenericRdbTest(TestCase):
"SetUp data for all Rdb parsers"""
def setUp(self):
self.empty = []
self.labels = 'mty:ssu\nseq:bac\n//\nttl:joe\nseq:mit\n//'.split('\n')
self.nolabels = 'ACGUAGCUAGCUAC\nGCUGCAUCG\nAUCG\n//'.split('\n')
self.oneseq = 'seq:H.Sapiens\nAGUCAUCUAGAUHCAUHC\n//'.split('\n')
self.multiline = 'seq:H.Sapiens\nAGUCAUUAG\nAUHCAUHC\n//'.split('\n')
self.threeseq =\
'seq:bac\nAGU\n//\nseq:mit\nACU\n//\nseq:pla\nAAA\n//'.split('\n')
self.twogood =\
'seq:bac\n//\nseq:mit\nACU\n//\nseq:pla\nAAA\n//'.split('\n')
self.oneX =\
'seq:bac\nX\n//\nseq:mit\nACT\n//\nseq:pla\nAAA\n//'.split('\n')
self.strange = 'seq:bac\nACGUXxAaKkoo---*\n//'.split('\n')
class MinimalRdbParserTests(GenericRdbTest):
"""Tests of MinimalRdbParser: returns (headerLines,sequence) tuples"""
def test_empty(self):
"""MinimalRdbParser should return empty list from file w/o seqs"""
self.assertEqual(list(MinimalRdbParser(self.empty)),[])
self.assertEqual(list(MinimalRdbParser(self.nolabels, strict=False)),
[])
self.assertRaises(RecordError, list, MinimalRdbParser(self.nolabels))
def test_only_labels(self):
"""MinimalRdbParser should return empty list from file w/o seqs"""
#should fail if strict (the default)
self.assertRaises(RecordError, list,
MinimalRdbParser(self.labels,strict=True))
#if not strict, should skip the records
self.assertEqual(list(MinimalRdbParser(self.labels, strict=False)),
[])
def test_only_sequences(self):
"""MinimalRdbParser should return empty list form file w/o lables"""
#should fail if strict (the default)
self.assertRaises(RecordError, list,
MinimalRdbParser(self.nolabels,strict=True))
#if not strict, should skip the records
self.assertEqual(list(MinimalRdbParser(self.nolabels, strict=False)),
[])
def test_single(self):
"""MinimalRdbParser should read single record as (header,seq) tuple"""
res = list(MinimalRdbParser(self.oneseq))
self.assertEqual(len(res),1)
first = res[0]
self.assertEqual(first, (['seq:H.Sapiens'], 'AGUCAUCUAGAUHCAUHC'))
res = list(MinimalRdbParser(self.multiline))
self.assertEqual(len(res),1)
first = res[0]
self.assertEqual(first, (['seq:H.Sapiens'], 'AGUCAUUAGAUHCAUHC'))
def test_multiple(self):
"""MinimalRdbParser should read multiple record correctly"""
res = list(MinimalRdbParser(self.threeseq))
self.assertEqual(len(res), 3)
a, b, c = res
self.assertEqual(a, (['seq:bac'], 'AGU'))
self.assertEqual(b, (['seq:mit'], 'ACU'))
self.assertEqual(c, (['seq:pla'], 'AAA'))
def test_multiple_bad(self):
"""MinimalRdbParser should complain or skip bad records"""
self.assertRaises(RecordError, list, MinimalRdbParser(self.twogood))
f = list(MinimalRdbParser(self.twogood, strict=False))
self.assertEqual(len(f), 2)
a, b = f
self.assertEqual(a, (['seq:mit'], 'ACU'))
self.assertEqual(b, (['seq:pla'], 'AAA'))
def test_strange(self):
"""MRP: handle strange char. according to constr. and strip off '*'"""
f = list(MinimalRdbParser(self.strange))
obs = f[0]
exp = (['seq:bac'],'ACGUXxAaKkoo---')
self.assertEqual(obs,exp)
class RdbParserTests(GenericRdbTest):
"""Tests for the RdbParser. Should return Sequence objects"""
def test_empty(self):
"""RdbParser should return empty list from 'file' w/o labels"""
self.assertEqual(list(RdbParser(self.empty)), [])
self.assertEqual(list(RdbParser(self.nolabels, strict=False)),
[])
self.assertRaises(RecordError, list, RdbParser(self.nolabels))
def test_only_labels(self):
"""RdbParser should return empty list from file w/o seqs"""
#should fail if strict (the default)
self.assertRaises(RecordError, list,
RdbParser(self.labels,strict=True))
#if not strict, should skip the records
self.assertEqual(list(RdbParser(self.labels, strict=False)), [])
def test_only_sequences(self):
"""RdbParser should return empty list form file w/o lables"""
#should fail if strict (the default)
self.assertRaises(RecordError, list,
RdbParser(self.nolabels,strict=True))
#if not strict, should skip the records
self.assertEqual(list(RdbParser(self.nolabels, strict=False)),
[])
def test_single(self):
"""RdbParser should read single record as (header,seq) tuple"""
res = list(RdbParser(self.oneseq))
self.assertEqual(len(res),1)
first = res[0]
self.assertEqual(first, Sequence('AGUCAUCUAGAUHCAUHC'))
self.assertEqual(first.Info, Info({'Species':'H.Sapiens',\
'OriginalSeq':'AGUCAUCUAGAUHCAUHC'}))
res = list(RdbParser(self.multiline))
self.assertEqual(len(res),1)
first = res[0]
self.assertEqual(first, Sequence('AGUCAUUAGAUHCAUHC'))
self.assertEqual(first.Info, Info({'Species':'H.Sapiens',\
'OriginalSeq':'AGUCAUUAGAUHCAUHC'}))
def test_single_constructor(self):
"""RdbParser should use constructors if supplied"""
to_dna = lambda x, Info: DnaSequence(str(x).replace('U','T'), \
Info=Info)
f = list(RdbParser(self.oneseq, to_dna))
self.assertEqual(len(f), 1)
a = f[0]
self.assertEqual(a, 'AGTCATCTAGATHCATHC')
self.assertEqual(a.Info, Info({'Species':'H.Sapiens',\
'OriginalSeq':'AGUCAUCUAGAUHCAUHC'}))
def alternativeConstr(header_lines):
info = Info()
for line in header_lines:
all = line.strip().split(':',1)
#strip out empty lines, lines without name, lines without colon
if not all[0] or len(all) != 2:
continue
name = all[0].upper()
value = all[1].strip().upper()
info[name] = value
return info
f = list(RdbParser(self.oneseq, to_dna, alternativeConstr))
self.assertEqual(len(f), 1)
a = f[0]
self.assertEqual(a, 'AGTCATCTAGATHCATHC')
exp_info = Info({'OriginalSeq':'AGUCAUCUAGAUHCAUHC',\
'Refs':{}, 'SEQ':'H.SAPIENS'})
self.assertEqual(a.Info, Info({'OriginalSeq':'AGUCAUCUAGAUHCAUHC',\
'Refs':{}, 'SEQ':'H.SAPIENS'}))
def test_multiple_constructor_bad(self):
"""RdbParser should complain or skip bad records w/ constructor"""
def dnastrict(x, **kwargs):
try:
return DnaSequence(x, **kwargs)
except Exception:
raise RecordError, "Could not convert sequence"
self.assertRaises(RecordError, list, RdbParser(self.oneX,dnastrict))
f = list(RdbParser(self.oneX, dnastrict, strict=False))
self.assertEqual(len(f), 2)
a, b = f
self.assertEqual(a, 'ACT')
self.assertEqual(a.Info,Info({'Species':'mit','OriginalSeq':'ACT'}))
self.assertEqual(b, 'AAA')
self.assertEqual(b.Info,Info({'Species':'pla','OriginalSeq':'AAA'}))
def test_full(self):
"""RdbParser: full data, valid and invalid"""
# when only good record, should work independent of strict
r1 = RnaSequence("-??GG-UGAA--CGCU---ACGU-N???---",\
Info=Info({'Species': "unidentified Thermus OPB AF027020",\
'Refs':{'rRNA':['AF027020']},\
'OriginalSeq':'-o[oGG-U{G}AA--C^GC]U---ACGU-Nooo---'}))
r2 = RnaSequence("---CGAUCG--UAUACG-N???-",\
Info=Info({'Species':'Thermus silvanus X84211',\
'Refs':{'rRNA':['X84211']},\
'OriginalSeq':'---CGAU[C(G){--UA}U]ACG-Nooo-'}))
obs = list(RdbParser(RDB_LINES_ONLY_GOOD.split('\n'), strict=True))
self.assertEqual(len(obs), 2)
self.assertEqual(obs[0], r1)
self.assertEqual(str(obs[0]), str(r1))
self.assertEqual(obs[0].Info, r1.Info)
self.assertEqual(obs[1], r2)
self.assertEqual(str(obs[1]), str(r2))
self.assertEqual(obs[1].Info, r2.Info)
obs = list(RdbParser(RDB_LINES_ONLY_GOOD.split('\n'), strict=False))
self.assertEqual(len(obs), 2)
self.assertEqual(obs[0], r1)
self.assertEqual(str(obs[0]), str(r1))
self.assertEqual(obs[0].Info, r1.Info)
# when strict, should raise error on invalid record
f = RdbParser(RDB_LINES_GOOD_BAD.split('\n'), strict=True)
self.assertRaises(RecordError, list, f)
# when not strict, malicious record is skipped
obs = list(RdbParser(RDB_LINES_GOOD_BAD.split('\n'), strict=False))
self.assertEqual(len(obs), 2)
self.assertEqual(obs[0], r1)
self.assertEqual(str(obs[0]), str(r1))
self.assertEqual(obs[0].Info, r1.Info)
self.assertEqual(obs[1], r2)
self.assertEqual(str(obs[1]), str(r2))
self.assertEqual(obs[1].Info, r2.Info)
RDB_LINES_ONLY_GOOD=\
"""acc:AF027020
seq: unidentified Thermus OPB AF027020
-o[oGG-U{G}AA--C^GC]U---ACGU-Nooo---
//
acc:X84211
seq: Thermus silvanus X84211
---CGAU[C(G){--UA}U]ACG-Nooo-
//
"""
RDB_LINES_GOOD_BAD=\
"""acc:AF027020
seq: unidentified Thermus OPB AF027020
-o[oGG-U{G}AA--C^GC]U---ACGU-Nooo---
//
acc:ABC123
seq: E. coli
---ACGU-Nooo-RYXQ-
//
acc:X84211
seq: Thermus silvanus X84211
---CGAU[C(G){--UA}U]ACG-Nooo-
//
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_record.py 000644 000765 000024 00000050015 12024702176 022444 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for parser support libraries dealing with records.
"""
from cogent.parse.record import FieldError, RecordError, Grouper, \
DelimitedSplitter, GenericRecord, MappedRecord, \
TypeSetter, list_adder, dict_adder, \
LineOrientedConstructor, int_setter, str_setter, bool_setter, \
string_and_strip, FieldWrapper, StrictFieldWrapper, raise_unknown_field, \
FieldMorpher, list_extender
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class recordsTests(TestCase):
"""Tests of top-level functionality in records."""
def test_string_and_strip(self):
"""string_and_strip should convert all items to strings and strip them"""
self.assertEqual(string_and_strip(), [])
self.assertEqual(string_and_strip('\t', ' ', '\n\t'), ['','',''])
self.assertEqual(string_and_strip('\ta\tb', 3, ' cde e', None), \
['a\tb', '3', 'cde e', 'None'])
def test_raise_unknown_field(self):
"""raise_unknown_field should always raise FieldError"""
self.assertRaises(FieldError, raise_unknown_field, 'xyz', 123)
class GrouperTests(TestCase):
"""Tests of the Grouper class."""
def test_call(self):
"""Grouper should return lists containing correct number of groups"""
empty = []
s3 = 'abc'
s10 = range(10)
g1 = Grouper(1)
g2 = Grouper(2)
g5 = Grouper(5)
self.assertEqual(list(g1(empty)), [])
self.assertEqual(list(g2(empty)), [])
self.assertEqual(list(g5(empty)), [])
self.assertEqual(list(g1(s3)), [['a'], ['b'], ['c']])
self.assertEqual(list(g2(s3)), [['a','b'], ['c']])
self.assertEqual(list(g5(s3)), [['a','b','c']])
self.assertEqual(list(g1(s10)), [[i] for i in range(10)])
self.assertEqual(list(g2(s10)), [[0,1],[2,3],[4,5],[6,7],[8,9]])
self.assertEqual(list(g5(s10)), [[0,1,2,3,4],[5,6,7,8,9]])
def test_call_bad(self):
"""Grouper call should raise ValueError if NumItems is not an int"""
g_none = Grouper(None)
g_neg = Grouper(-1)
g_zero = Grouper(0)
g_alpha = Grouper('abc')
for g in (g_none, g_neg, g_zero, g_alpha):
iterator = g('abcd')
self.assertRaises(ValueError, list, iterator)
class DelimitedSplitterTests(TestCase):
"""Tests of the DelimitedSplitter factory function."""
def test_parsers(self):
"""DelimitedSplitter should return function with correct behavior"""
empty = DelimitedSplitter()
space = DelimitedSplitter(None)
semicolon = DelimitedSplitter(';')
twosplits = DelimitedSplitter(';', 2)
allsplits = DelimitedSplitter(';', None)
lastone = DelimitedSplitter(';', -1)
lasttwo = DelimitedSplitter(';', -2)
self.assertEqual(empty('a b c'), ['a', 'b c'])
self.assertEqual(empty('abc'), ['abc'])
self.assertEqual(empty(' '), [])
self.assertEqual(empty('a b c'), space('a b c'))
self.assertEqual(semicolon(' a ; b ; c d'), ['a','b ; c d'])
self.assertEqual(twosplits(' a ; b ; c d'), ['a','b', 'c d'])
self.assertEqual(allsplits(' a ; b ; c;;d;e ;'),\
['a','b','c','','d','e',''])
self.assertEqual(lastone(' a ; b ; c;;d;e ;'),\
['a ; b ; c;;d;e',''])
self.assertEqual(lasttwo(' a ; b ; c;;d;e ;'),\
['a ; b ; c;;d','e',''])
self.assertEqual(lasttwo(''), [])
self.assertEqual(lasttwo('x'), ['x'])
self.assertEqual(lasttwo('x;'), ['x', ''])
class GenericRecordTests(TestCase):
"""Tests of the GenericRecord class"""
class gr(GenericRecord):
Required = {'a':'x', 'b':[], 'c':{}}
def test_init(self):
"""GenericRecord init should work OK empty or with data"""
self.assertEqual(GenericRecord(), {})
self.assertEqual(GenericRecord({'a':1}), {'a':1})
assert isinstance(GenericRecord(), GenericRecord)
def test_init_subclass(self):
"""GenericRecord subclass init should include required data"""
self.assertEqual(self.gr(), {'a':'x', 'b':[], 'c':{}})
self.assertEqual(self.gr({'a':[]}), {'a':[], 'b':[],'c':{}})
assert isinstance(self.gr(), self.gr)
assert isinstance(self.gr(), GenericRecord)
def test_delitem(self):
"""GenericRecord delitem should fail if item required"""
g = self.gr()
g['d'] = 3
self.assertEqual(g, {'a':'x','b':[],'c':{},'d':3})
del g['d']
self.assertEqual(g, {'a':'x','b':[],'c':{}})
self.assertRaises(AttributeError, g.__delitem__, 'a')
g['c'][3] = 4
self.assertEqual(g['c'], {3:4})
def test_copy(self):
"""GenericRecord copy should include attributes and set correct class"""
g = self.gr()
g['a'] = 'abc'
g.X = 'y'
h = g.copy()
self.assertEqual(g, h)
assert isinstance(h, self.gr)
self.assertEqual(h.X, 'y')
self.assertEqual(h, {'a':'abc', 'b':[], 'c':{}})
class MappedRecordTests(TestCase):
"""Tests of the MappedRecord class"""
def setUp(self):
"""Define a few standard MappedRecords"""
self.empty = MappedRecord()
self.single = MappedRecord({'a':3})
self.several = MappedRecord(a=4,b=5,c='a',d=[1,2,3])
def test_init_empty(self):
"""MappedRecord empty init should work OK"""
g = MappedRecord()
self.assertEqual(g, {})
def test_init_data(self):
"""MappedRecord should work like normal dict init"""
exp = {'a':3, 'b':4}
self.assertEqual(MappedRecord({'a':3, 'b':4}), exp)
self.assertEqual(MappedRecord(a=3, b=4), exp)
self.assertEqual(MappedRecord([['a',3],['b',4]]), exp)
def test_init_subclass(self):
"""MappedRecord subclasses should behave as expected"""
class rec(MappedRecord):
Required = {'a':{}, 'b':'xyz', 'c':3}
Aliases = {'B':'b'}
r = rec()
self.assertEqual(r, {'a':{}, 'b':'xyz', 'c':3})
#test that subclassing is correct
s = r.copy()
assert isinstance(s, rec)
#test Aliases
s.B = 0
self.assertEqual(s, {'a':{}, 'b':0, 'c':3})
#test Required
try:
del s.B
except AttributeError:
pass
else:
raise AssertionError, "Subclass failed to catch requirement"
def test_getattr(self):
"""MappedRecord getattr should look in dict after real attrs"""
s = self.several
self.assertEqual(s.Aliases, {})
self.assertEqual(s.a, 4)
self.assertEqual(s.d, [1,2,3])
for key in s:
self.assertEqual(getattr(s, key), s[key])
assert 'xyz' not in s
self.assertEqual(s.xyz, None)
self.assertEqual(s['xyz'], None)
s.Aliases = {'xyz':'a'}
self.assertEqual(s['xyz'], 4)
def test_setattr(self):
"""MappedRecord setattr should add to dict"""
s = self.single
#check that we haven't screwed up normal attribute setting
assert 'Aliases' not in s
s.Aliases = {'x':'y'}
assert 'Aliases' not in s
self.assertEqual(s.Aliases, {'x':'y'})
s.x = 5
assert 'x' in s
self.assertEqual(s['x'], 5)
self.assertEqual(s.x, 5)
s.Aliases = {'XYZ':'b'}
s.XYZ = 3
self.assertEqual(s.b, 3)
def test_delattr(self):
"""MappedRecord delattr should work for 'normal' and other attributes"""
s = self.single
s.__dict__['x'] = 'y'
assert 'x' not in s
self.assertEqual(s.x, 'y')
del s.x
self.assertEqual(s.x, None)
self.assertEqual(s, {'a':3})
#try it for an internal attribute: check it doesn't delete anything else
s.b = 4
self.assertEqual(s, {'a':3, 'b':4})
del s.a
self.assertEqual(s, {'b':4})
del s.abc
self.assertEqual(s, {'b':4})
s.Required = {'b':True}
try:
del s.b
except AttributeError:
pass
else:
raise AssertionError, "Allowed deletion of required attribute"""
s.a = 3
self.assertEqual(s.a, 3)
s.Aliases = {'xyz':'a'}
del s.xyz
self.assertEqual(s.a, None)
def test_getitem(self):
"""MappedRecord getitem should work only for keys, not attributes"""
s = self.single
self.assertEqual(s['Required'], None)
self.assertEqual(s['a'], 3)
self.assertEqual(s['xyz'], None)
self.assertEquals(s[list('abc')], None)
s.Aliases = {'xyz':'a'}
self.assertEqual(s['xyz'], 3)
def test_setitem(self):
"""MappedRecord setitem should work only for keys, not attributes"""
s = self.single
s['Required'] = None
self.assertEqual(s, {'a':3, 'Required':None})
self.assertEqual(s.Required, {})
self.assertNotEqual(s.Required, None)
s['c'] = 5
self.assertEqual(s, {'a':3, 'c':5, 'Required':None})
#still not allowed unhashable objects as keys
self.assertRaises(TypeError, s.__setitem__, range(3))
s.Aliases = {'C':'c'}
s['C'] = 3
self.assertEqual(s, {'a':3, 'c':3, 'Required':None})
def test_delitem(self):
"""MappedRecord delitem should only work for keys, not attributes"""
s = self.single
del s['Required']
self.assertEqual(s.Required, {})
s.Required = {'a':True}
try:
del s['a']
except AttributeError:
pass
else:
raise AssertionError, "Allowed deletion of required item"
s.Aliases = {'B':'b'}
s.b = 5
self.assertEqual(s.b, 5)
del s.B
self.assertEqual(s.b, None)
def test_contains(self):
"""MappedRecord contains should use aliases, but not apply to attrs"""
s = self.single
assert 'a' in s
assert 'b' not in s
s.b = 5
assert 'b' in s
assert 'Required' not in s
assert 'A' not in s
s.Aliases = {'A':'a'}
assert 'A' in s
def test_get(self):
"""MappedRecord get should be typesafe against unhashables"""
s = self.single
self.assertEqual(s.get(1, 6), 6)
self.assertEqual(s.get('a', 'xyz'), 3)
self.assertEqual(s.get('ABC', 'xyz'), 'xyz')
s.Aliases = {'ABC':'a'}
self.assertEqual(s.get('ABC', 'xyz'), 3)
self.assertEqual(s.get([1,2,3], 'x'), 'x')
def test_setdefault(self):
"""MappedRecord setdefault should not be typesafe against unhashables"""
s = self.single
x = s.setdefault('X', 'xyz')
self.assertEqual(x, 'xyz')
self.assertEqual(s, {'a':3, 'X':'xyz'})
self.assertRaises(TypeError, s.setdefault, ['a','b'], 'xyz')
def test_update(self):
"""MappedRecord update should transparently convert keys"""
s = self.single
s.b = 999
s.Aliases = {'XYZ':'x', 'ABC':'a'}
d = {'ABC':111, 'CVB':222}
s.update(d)
self.assertEqual(s, {'a':111, 'b':999, 'CVB':222})
def test_copy(self):
"""MappedRecord copy should return correct class"""
s = self.single
t = s.copy()
assert isinstance(t, MappedRecord)
s.Aliases = {'XYZ':'x'}
u = s.copy()
u.Aliases['ABC'] = 'a'
self.assertEqual(s.Aliases, {'XYZ':'x'})
self.assertEqual(t.Aliases, {})
self.assertEqual(u.Aliases, {'XYZ':'x', 'ABC':'a'})
def test_subclass(self):
"""MappedRecord subclassing should work correctly"""
class ret3(MappedRecord):
DefaultValue = 3
ClassData = 'xyz'
x = ret3({'ABC':777, 'DEF':'999'})
self.assertEqual(x.ZZZ, 3)
self.assertEqual(x.ABC, 777)
self.assertEqual(x.DEF, '999')
self.assertEqual(x.ClassData, 'xyz')
x.ZZZ = 6
self.assertEqual(x.ZZZ, 6)
self.assertEqual(x.ZZ, 3)
x.ClassData = 'qwe'
self.assertEqual(x.ClassData, 'qwe')
self.assertEqual(ret3.ClassData, 'xyz')
def test_DefaultValue(self):
"""MappedRecord DefaultValue should give new copy when requested"""
class m(MappedRecord):
DefaultValue=[]
a = m()
b = m()
assert a['abc'] is not b['abc']
assert a['abc'] == b['abc']
class dummy(object):
"""Do-nothing class whose attributes can be freely abused."""
pass
class TypeSetterTests(TestCase):
"""Tests of the TypeSetter class"""
def test_setter_empty(self):
"""TypeSetter should set attrs to vals on empty init"""
d = dummy()
ident = TypeSetter()
ident(d, 'x', 'abc')
self.assertEqual(d.x, 'abc')
ident(d, 'y', 3)
self.assertEqual(d.y, 3)
ident(d, 'x', 2)
self.assertEqual(d.x, 2)
def test_setter_typed(self):
"""TypeSetter should set attrs to constructor(val) when specified"""
d = dummy()
i = TypeSetter(int)
i(d, 'zz', 3)
self.assertEqual(d.zz, 3)
i(d, 'xx', '456')
self.assertEqual(d.xx, 456)
class TypeSetterLikeTests(TestCase):
"""Tests of the functions that behave similarly to TypeSetter products"""
def test_list_adder(self):
"""list_adder should add items to list, creating if necessary"""
d = dummy()
list_adder(d, 'x', 3)
self.assertEqual(d.x, [3])
list_adder(d, 'x', 'abc')
self.assertEqual(d.x, [3, 'abc'])
list_adder(d, 'y', [2,3])
self.assertEqual(d.x, [3, 'abc'])
self.assertEqual(d.y, [[2,3]])
def test_list_extender(self):
"""list_adder should add items to list, creating if necessary"""
d = dummy()
list_extender(d, 'x', '345')
self.assertEqual(d.x, ['3','4','5'])
list_extender(d, 'x', 'abc')
self.assertEqual(d.x, ['3','4','5','a','b','c'])
list_extender(d, 'y', [2,3])
self.assertEqual(d.x, ['3','4','5','a','b','c'])
self.assertEqual(d.y, [2,3])
list_extender(d, 'y', None)
self.assertEqual(d.y, [2,3,None])
def test_dict_adder(self):
"""dict_adder should add items to dict, creating if necessary"""
d = dummy()
dict_adder(d, 'x', 3)
self.assertEqual(d.x, {3:None})
dict_adder(d, 'x', 'ab')
self.assertEqual(d.x, {3:None, 'a':'b'})
dict_adder(d, 'x', ['a', 0])
self.assertEqual(d.x, {3:None, 'a':0})
dict_adder(d, 'y', None)
self.assertEqual(d.x, {3:None, 'a':0})
self.assertEqual(d.y, {None:None})
class LineOrientedConstructorTests(TestCase):
"""Tests of the LineOrientedConstructor class"""
def test_init_empty(self):
"""LOC empty init should succeed with expected defaults"""
l = LineOrientedConstructor()
self.assertEqual(l.Lines, [])
self.assertEqual(l.LabelSplitter(' ab cd '), ['ab','cd'])
self.assertEqual(l.FieldMap, {})
self.assertEqual(l.Constructor, MappedRecord)
self.assertEqual(l.Strict, False)
def test_empty_LOC(self):
"""LOC empty should fail if strict, fill fields if not strict"""
data = ["abc def","3 n","\t abc \txyz\n\n", "fgh "]
l = LineOrientedConstructor()
result = l()
self.assertEqual(result, {})
result = l([])
self.assertEqual(result, {})
result = l([' ','\n\t '])
self.assertEqual(result, {})
result = l(data)
self.assertEqual(result, {'abc':'xyz', '3':'n', 'fgh':None})
def test_full_LOC(self):
"""LOC should behave as expected when initialized with rich data"""
data = ["abc\t def"," 3 \t n"," abc \txyz\n\n", "x\t5", "fgh ",
"x\t3 "]
class rec(MappedRecord):
Required = {'abc':[]}
maps = {'abc':list_adder, 'x':int_setter, 'fgh':bool_setter}
label_splitter = DelimitedSplitter('\t')
constructor = rec
strict = True
loc_bad = LineOrientedConstructor(data, label_splitter, maps, \
constructor, strict)
self.assertRaises(FieldError, loc_bad)
strict = False
loc_good = LineOrientedConstructor(data, label_splitter, maps, \
constructor, strict)
result = loc_good()
assert isinstance(result, rec)
self.assertEqual(result, \
{'abc':['def','xyz'], '3':'n','fgh':False,'x':3})
class fake_dict(dict):
"""Test that constructors return the correct subclass"""
pass
class FieldWrapperTests(TestCase):
"""Tests of the FieldWrapper factory function"""
def test_default(self):
"""Default FieldWrapper should wrap fields and labels"""
fields = list('abcde')
f = FieldWrapper(fields)
self.assertEqual(f(''), {})
self.assertEqual(f('xy za '), {'a':'xy','b':'za'})
self.assertEqual(f('1 2\t\t 3 \n4 5 6'), \
{'a':'1','b':'2','c':'3','d':'4','e':'5'})
def test_splitter(self):
"""FieldWrapper with splitter should use that splitter"""
fields = ['label', 'count']
splitter = DelimitedSplitter(':', -1)
f = FieldWrapper(fields, splitter)
self.assertEqual(f(''), {})
self.assertEqual(f('nknasd:'), {'label':'nknasd', 'count':''})
self.assertEqual(f('n:k:n:a:sd '), {'label':'n:k:n:a', 'count':'sd'})
def test_constructor(self):
"""FieldWrapper with constructor should use that constructor"""
fields = list('abc')
f = FieldWrapper(fields, constructor=fake_dict)
self.assertEqual(f('x y'), {'a':'x','b':'y'})
assert isinstance(f('x y'), fake_dict)
class StrictFieldWrapperTests(TestCase):
"""Tests of the StrictFieldWrapper factory function"""
def test_default(self):
"""Default StrictFieldWrapper should wrap fields if count correct"""
fields = list('abcde')
f = StrictFieldWrapper(fields)
self.assertEqual(f('1 2\t\t 3 \n4 5 '), \
{'a':'1','b':'2','c':'3','d':'4','e':'5'})
self.assertRaises(FieldError, f, '')
self.assertRaises(FieldError, f, 'xy za ')
def test_splitter(self):
"""StrictFieldWrapper with splitter should use that splitter"""
fields = ['label', 'count']
splitter = DelimitedSplitter(':', -1)
f = StrictFieldWrapper(fields, splitter)
self.assertEqual(f('n:k:n:a:sd '), {'label':'n:k:n:a', 'count':'sd'})
self.assertEqual(f('nknasd:'), {'label':'nknasd', 'count':''})
self.assertRaises(FieldError, f, '')
def test_constructor(self):
"""StrictFieldWrapper with constructor should use that constructor"""
fields = list('ab')
f = StrictFieldWrapper(fields, constructor=fake_dict)
self.assertEqual(f('x y'), {'a':'x','b':'y'})
assert isinstance(f('x y'), fake_dict)
class FieldMorpherTests(TestCase):
"""Tests of the FieldMorpher class."""
def test_default(self):
"""FieldMorpher default should use correct constructors"""
fm = FieldMorpher({'a':int, 'b':str})
self.assertEqual(fm({'a':'3', 'b':456}), {'a':3,'b':'456'})
def test_default_error(self):
"""FieldMorpher default should raise FieldError on unknown fields"""
fm = FieldMorpher({'a':int, 'b':str})
self.assertRaises(FieldError, fm, {'a':'3', 'b':456, 'c':'4'})
def test_altered_default(self):
"""FieldMorpher with default set should apply it"""
func = lambda x, y: (str(x), float(y) - 0.5)
fm = FieldMorpher({'3':str,4:int}, func)
#check that recognized values aren't tampered with
self.assertEqual(fm({3:3, 4:'4'}), {'3':'3', 4:4})
#check that unrecognized values get the appropriate conversion
self.assertEqual(fm({3:3, 5:'5'}), {'3':'3', '5':4.5})
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_record_finder.py 000644 000765 000024 00000023462 12024702176 024001 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for recordfinders: parsers that group the lines for a record.
"""
from cogent.parse.record import RecordError
from cogent.parse.record_finder import DelimitedRecordFinder, \
LabeledRecordFinder, LineGrouper, TailedRecordFinder
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Zongzhi Liu"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class TailedRecordFinderTests(TestCase):
"""Tests of the TailedRecordFinder factory function."""
def setUp(self):
"""Define a standard TailedRecordFinder"""
self.endswith_period = lambda x: x.endswith('.')
self.period_tail_finder = TailedRecordFinder(self.endswith_period)
def test_parsers(self):
"""TailedRecordFinder should split records into lines correctly"""
lines = '>abc\ndef\nz.\n>efg\nz.'.split()
fl = self.period_tail_finder
self.assertEqual(list(fl(lines)), \
[['>abc', 'def', 'z.'], ['>efg','z.']])
def test_parsers_empty(self):
"""TailedRecordFinder should return empty list on empty lines"""
fl = self.period_tail_finder
self.assertEqual(list(fl([' ','\n'])), [])
self.assertEqual(list(fl([])), [])
def test_parsers_strip(self):
"""TailedRecordFinder should trim each line correctly"""
fl = self.period_tail_finder
lines = '>abc \n \t def\n z. \t\n>efg \nz.'.split('\n')
self.assertEqual(list(fl(lines)), \
[['>abc', ' \t def', ' z.'], ['>efg','z.']])
def test_parsers_leftover(self):
"""TailedRecordFinder should raise error or yield leftover"""
f = self.period_tail_finder
good = [ 'abc \n',
'def\n',
'.\n',
'ghi \n',
'j.',
]
blank = ['', ' ', '\t \t\n\n']
bad = ['abc']
result = [['abc', 'def','.'], ['ghi','j.']]
self.assertEqual(list(f(good)), result)
self.assertEqual(list(f(good+blank)), result)
self.assertRaises(RecordError, list, f(good+bad))
f2 = TailedRecordFinder(self.endswith_period, strict=False)
self.assertEqual(list(f2(good+bad)), result + [['abc']])
def test_parsers_ignore(self):
"""TailedRecordFinder should skip lines to ignore."""
def never(line):
return False
def ignore_labels(line):
return (not line) or line.isspace() or line.startswith('#')
lines = ['abc','\n','1.','def','#ignore','2.']
self.assertEqual(list(TailedRecordFinder(self.endswith_period)(lines)),
[['abc', '1.'],['def','#ignore','2.']])
self.assertEqual(list(TailedRecordFinder(self.endswith_period,
ignore=never)(lines)),
[['abc', '', '1.'],['def','#ignore','2.']])
self.assertEqual(list(TailedRecordFinder(self.endswith_period,
ignore=ignore_labels)(lines)),
[['abc','1.'],['def','2.']])
class DelimitedRecordFinderTests(TestCase):
"""Tests of the DelimitedRecordFinder factory function."""
def test_parsers(self):
"""DelimitedRecordFinder should split records into lines correctly"""
lines = 'abc\ndef\n//\nefg\n//'.split()
self.assertEqual(list(DelimitedRecordFinder('//')(lines)), \
[['abc', 'def', '//'], ['efg','//']])
self.assertEqual(list(DelimitedRecordFinder('//', keep_delimiter=False)
(lines)), \
[['abc', 'def'], ['efg']])
def test_parsers_empty(self):
"""DelimitedRecordFinder should return empty list on empty lines"""
self.assertEqual(list(DelimitedRecordFinder('//')([' ','\n'])), [])
self.assertEqual(list(DelimitedRecordFinder('//')([])), [])
def test_parsers_strip(self):
"""DelimitedRecordFinder should trim each line correctly"""
lines = ' \t abc \n \t def\n // \t\n\t\t efg \n//'.split('\n')
self.assertEqual(list(DelimitedRecordFinder('//')(lines)), \
[['abc', 'def', '//'], ['efg','//']])
def test_parsers_error(self):
"""DelimitedRecordFinder should raise RecordError if trailing data"""
good = [ ' \t abc \n',
'\t def\n',
'// \t\n',
'\t\n',
'\t efg \n',
'\t\t//\n',
]
blank = ['', ' ', '\t \t\n\n']
bad = ['abc']
result = [['abc', 'def', '//'], ['efg','//']]
r = DelimitedRecordFinder('//')
self.assertEqual(list(r(good)), result)
self.assertEqual(list(r(good+blank)), result)
try:
list(r(good+bad))
except RecordError:
pass
else:
raise AssertionError, "Parser failed to raise error on bad data"
r = DelimitedRecordFinder('//', strict=False)
self.assertEqual(list(r(good+bad)), result + [['abc']])
def test_parsers_ignore(self):
"""DelimitedRecordFinder should skip lines to ignore."""
def never(line):
return False
def ignore_labels(line):
return (not line) or line.isspace() or line.startswith('#')
lines = ['>abc','\n','1', '$$', '>def','#ignore','2', '$$']
self.assertEqual(list(DelimitedRecordFinder('$$')(lines)),
[['>abc', '1', '$$'],['>def','#ignore','2', '$$']])
self.assertEqual(list(DelimitedRecordFinder('$$',
ignore=never)(lines)),
[['>abc', '', '1', '$$'],['>def','#ignore','2','$$']])
self.assertEqual(list(DelimitedRecordFinder('$$',
ignore=ignore_labels)(lines)),
[['>abc','1','$$'],['>def','2','$$']])
class LabeledRecordFinderTests(TestCase):
"""Tests of the LabeledRecordFinder factory function."""
def setUp(self):
"""Define a standard LabeledRecordFinder"""
self.FastaLike = LabeledRecordFinder(lambda x: x.startswith('>'))
def test_parsers(self):
"""LabeledRecordFinder should split records into lines correctly"""
lines = '>abc\ndef\n//\n>efg\n//'.split()
fl = self.FastaLike
self.assertEqual(list(fl(lines)), \
[['>abc', 'def', '//'], ['>efg','//']])
def test_parsers_empty(self):
"""LabeledRecordFinder should return empty list on empty lines"""
fl = self.FastaLike
self.assertEqual(list(fl([' ','\n'])), [])
self.assertEqual(list(fl([])), [])
def test_parsers_strip(self):
"""LabeledRecordFinder should trim each line correctly"""
fl = self.FastaLike
lines = ' \t >abc \n \t def\n // \t\n\t\t >efg \n//'.split('\n')
self.assertEqual(list(fl(lines)), \
[['>abc', 'def', '//'], ['>efg','//']])
def test_parsers_leftover(self):
"""LabeledRecordFinder should not raise RecordError if last line label"""
fl = self.FastaLike
good = [ ' \t >abc \n',
'\t def\n',
'\t\n',
'\t >efg \n',
'ghi',
]
blank = ['', ' ', '\t \t\n\n']
bad = ['>abc']
result = [['>abc', 'def'], ['>efg','ghi']]
self.assertEqual(list(fl(good)), result)
self.assertEqual(list(fl(good+blank)), result)
self.assertEqual(list(fl(good+bad)), result + [['>abc']])
def test_parsers_ignore(self):
"""LabeledRecordFinder should skip lines to ignore."""
def never(line):
return False
def ignore_labels(line):
return (not line) or line.isspace() or line.startswith('#')
def is_start(line):
return line.startswith('>')
lines = ['>abc','\n','1','>def','#ignore','2']
self.assertEqual(list(LabeledRecordFinder(is_start)(lines)),
[['>abc', '1'],['>def','#ignore','2']])
self.assertEqual(list(LabeledRecordFinder(is_start,
ignore=never)(lines)),
[['>abc', '', '1'],['>def','#ignore','2']])
self.assertEqual(list(LabeledRecordFinder(is_start,
ignore=ignore_labels)(lines)),
[['>abc','1'],['>def','2']])
class LineGrouperTests(TestCase):
"""Tests of the LineGrouper class."""
def test_parser(self):
"""LineGrouper should return n non-blank lines at a time"""
good = [ ' \t >abc \n',
'\t def\n',
'\t\n',
'\t >efg \n',
'ghi',
]
c = LineGrouper(2)
self.assertEqual(list(c(good)), [['>abc', 'def'],['>efg','ghi']])
c = LineGrouper(1)
self.assertEqual(list(c(good)), [['>abc'], ['def'],['>efg'],['ghi']])
c = LineGrouper(4)
self.assertEqual(list(c(good)), [['>abc', 'def','>efg','ghi']])
#shouldn't work if not evenly divisible
c = LineGrouper(3)
self.assertRaises(RecordError, list, c(good))
def test_parser_ignore(self):
"""LineGrouper should skip lines to ignore."""
def never(line):
return False
def ignore_labels(line):
return (not line) or line.isspace() or line.startswith('#')
lines = ['abc','\n','1','def','#ignore','2']
self.assertEqual(list(LineGrouper(1)(lines)),
[['abc'], ['1'],['def'],['#ignore'],['2']])
self.assertEqual(list(LineGrouper(1, ignore=never)(lines)),
[[i.strip()] for i in lines])
self.assertEqual(list(LineGrouper(2, ignore=ignore_labels)(lines)),
[['abc','1'],['def','2']])
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_rfam.py 000644 000765 000024 00000056502 12024702176 022122 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""
Provides tests for RfamParser and related classes and functions.
"""
from cogent.parse.rfam import is_header_line, is_seq_line, is_structure_line,\
HeaderToInfo, MinimalRfamParser, RfamFinder, NameToInfo, RfamParser,\
ChangedSequence, is_empty_or_html
from cogent.util.unit_test import TestCase, main
from cogent.parse.record import RecordError
from cogent.core.info import Info
from cogent.struct.rna2d import WussStructure
from cogent.core.alignment import Alignment
from cogent.core.moltype import BYTES
__author__ = "Sandra Smit and Greg Caporaso"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Greg Caporaso", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Development"
Sequence = BYTES.Sequence
class RfamParserTests(TestCase):
""" Tests componenets of the rfam parser, in the rfam.py file """
def setUp(self):
""" Construct some fake data for testing purposes """
self._fake_headers = []
temp = list(fake_headers.split('\n'))
for line in temp:
self._fake_headers.append(line.strip())
del temp
self._fake_record_no_headers =\
list(fake_record_no_headers.split('\n'))
self._fake_record_no_sequences =\
list(fake_record_no_sequences.split('\n'))
self._fake_record_no_structure =\
list(fake_record_no_structure.split('\n'))
self._fake_two_records =\
list(fake_two_records.split('\n'))
self._fake_record =\
list(fake_record.split('\n'))
self._fake_record_bad_header_1 =\
list(fake_record_bad_header_1.split('\n'))
self._fake_record_bad_header_2 =\
list(fake_record_bad_header_2.split('\n'))
self._fake_record_bad_sequence_1 =\
list(fake_record_bad_sequence_1.split('\n'))
self._fake_record_bad_structure_1 =\
list(fake_record_bad_structure_1.split('\n'))
self._fake_record_bad_structure_2 =\
list(fake_record_bad_structure_2.split('\n'))
self.single_family = single_family.split('\n')
def test_is_empty_or_html(self):
"""is_empty_or_html: should ignore empty and HTML line"""
line = ' '
self.assertEqual(is_empty_or_html(line), True)
line = '\n\n'
self.assertEqual(is_empty_or_html(line), True)
line = ''
self.assertEqual(is_empty_or_html(line), True)
line = ' \n\n'
self.assertEqual(is_empty_or_html(line), True)
line = '\t>>')])
# should get empty on missing sequence or missing structure
self.assertEqual(list(MinimalRfamParser(self._fake_record_no_sequences,\
strict=False)), [])
self.assertEqual(list(MinimalRfamParser(self._fake_record_no_structure,\
strict=False)), [])
def test_MinimalRfamParser_strict_invalid_sequence(self):
"""MinimalRfamParser: toggle strict functions w/ invalid seq
"""
#strict = True
self.assertRaises(RecordError,list,\
MinimalRfamParser(self._fake_record_bad_sequence_1))
# strict = False
# you expect to get back as much information as possible, also
# half records or sequences
result = MinimalRfamParser(self._fake_record_bad_sequence_1,strict=False)
self.assertEqual(len(list(MinimalRfamParser(\
self._fake_record_bad_sequence_1,strict=False))[0][1].NamedSeqs), 3)
def test_MinimalRfamParser_strict_invalid_structure(self):
"""MinimalRfamParser: toggle strict functions w/ invalid structure
"""
#strict = True
self.assertRaises(RecordError,list,\
MinimalRfamParser(self._fake_record_bad_structure_1))
# strict = False
self.assertEqual(list(MinimalRfamParser(\
self._fake_record_bad_structure_1,strict=False))[0][2],None)
def test_MinimalRfamParser_w_valid_data(self):
"""MinimalRfamParser: integrity of output """
# Some ugly constructions here, but this is what the output of
# parsing fake_two_records should be
headers = ['#=GF AC RF00014','#=GF AU Mifsud W']
sequences =\
{'U17136.1/898-984':\
''.join(['AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA',\
'AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU']),\
'M15749.1/155-239':\
''.join(['AACGCAUCGGAUUUCCCGGUGUAACGAA-UUUUCAAGUGCUUCUUGCAUU',\
'AGCAAGUUUGAUCCCGACUCCUG-CGAGUCGGGAUUU']),\
'AF090431.1/222-139':\
''.join(['CUCACAUCAGAUUUCCUGGUGUAACGAA-UUUUCAAGUGCUUCUUGCAUA',\
'AGCAAGUUUGAUCCCGACCCGU--AGGGCCGGGAUUU'])}
structure = WussStructure(''.join(\
['...<<<<<<<.....>>>>>>>....................<<<<<...',\
'.>>>>>....<<<<<<<<<<.....>>>>>>>>>>..']))
data = []
for r in MinimalRfamParser(self._fake_two_records, strict=False):
data.append(r)
self.assertEqual(data[0],(headers,sequences,structure))
assert isinstance(data[0][1],Alignment)
# This line tests that invalid entries are ignored when strict=False
# Note, there are two records in self._fake_two_records, but 2nd is
# invalid
self.assertEqual(len(data),1)
def test_RfamFinder(self):
"""RfamFinder: integrity of output """
fake_record = ['a','//','b','b','//']
num_records = 0
data = []
for r in RfamFinder(fake_record):
data.append(r)
num_records += 1
self.assertEqual(num_records, 2)
self.assertEqual(data[0], ['a','//'])
self.assertEqual(data[1], ['b','b','//'])
def test_ChangedSequence(self):
"""ChangedSequence: integrity of output"""
# Made up input, based on a line that would look like:
# U17136.1/898-984 AACA..CAU..CAGAUUUCCU..GGUGUAA.CGAA
s_in = 'AACA..CAU..CAGAUUUCCU..GGUGUAA.CGAA'
s_out = 'AACA--CAU--CAGAUUUCCU--GGUGUAA-CGAA'
sequence = ChangedSequence(s_in)
self.assertEqual(sequence, s_out)
# test some extremes on the seq
# sequence of all blanks
s_in = '.' * 5
s_out = '-' * 5
sequence = ChangedSequence(s_in)
self.assertEqual(sequence, s_out)
# sequence of no blanks
s_in = 'U' * 5
s_out = 'U' * 5
sequence = ChangedSequence(s_in)
self.assertEqual(sequence, s_out)
def test_NameToInfo(self):
"""NameToInfo: integrity of output """
# Made up input, based on a line that would look like:
# U17136.1/898-984 AACA..CAU..CAGAUUUCCU..GGUGUAA.CGAA
s_in = 'AACA..CAU..CAGAUUUCCU..GGUGUAA.CGAA'
#s_out = 'AACA--CAU--CAGAUUUCCU--GGUGUAA-CGAA'
sequence = Sequence(s_in, Name='U17136.1/898-984')
info = NameToInfo(sequence)
#self.assertEqual(seq, s_out)
self.assertEqual(info['Start'], 897)
self.assertEqual(info['End'], 984)
self.assertEqual(info['GenBank'], ['U17136.1'])
def test_NameToInfo_invalid_label(self):
"""NameToInfo: raises error on invalid label """
s = 'AA'
invalid_labels = ['U17136.1898-984','U17136.1/898984']
for l in invalid_labels:
self.assertRaises(RecordError,NameToInfo,\
Sequence(s, Name=l))
a = 'U17136.1/' #missing start/end positions
b = '/898-984' #missing genbank id
obs_info = NameToInfo(Sequence(s,Name=a))
exp = Info({'GenBank':'U17136.1','Start':None,'End':None})
self.assertEqual(obs_info,exp)
obs_info = NameToInfo(Sequence(s,Name=b))
exp = Info({'GenBank':None,'Start':897,'End':984})
self.assertEqual(obs_info,exp)
#strict = False
# in strict mode you want to get back as much info as possible
lab1 = 'U17136.1898-984'
lab2 = 'U17136.1/898984'
obs_info = NameToInfo(Sequence(s,Name=lab1), strict=False)
exp = Info({'GenBank':None,'Start':None,'End':None})
self.assertEqual(obs_info,exp)
obs_info = NameToInfo(Sequence(s,Name=lab2), strict=False)
exp = Info({'GenBank':'U17136.1','Start':None,'End':None})
self.assertEqual(obs_info,exp)
def test_RfamParser(self):
"""RfamParser: integrity of output """
expected_sequences =\
[''.join(['AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA',\
'AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU']),\
''.join(['AACGCAUCGGAUUUCCCGGUGUAACGAA-UUUUCAAGUGCUUCUUGCAUU',\
'AGCAAGUUUGAUCCCGACUCCUG-CGAGUCGGGAUUU']),\
''.join(['CUCACAUCAGAUUUCCUGGUGUAACGAA-UUUUCAAGUGCUUCUUGCAUA',\
'AGCAAGUUUGAUCCCGACCCGU--AGGGCCGGGAUUU'])]
expected_structure = ''.join(\
['...<<<<<<<.....>>>>>>>....................<<<<<...',\
'.>>>>>....<<<<<<<<<<.....>>>>>>>>>>..'])
for r in RfamParser(self._fake_record):
headers,sequences,structure = r
self.assertEqual(headers['Refs']['Rfam'], ['RF00014'])
self.assertEqual(headers['Author'], 'Mifsud W')
self.assertEqualItems(sequences.values(), expected_sequences)
assert isinstance(sequences, Alignment)
self.assertEqualItems([s.Info.GenBank for s in sequences.Seqs],
[['U17136.1'],['M15749.1'],['AF090431.1']])
self.assertEqualItems([s.Info.Start for s in sequences.Seqs],
[897,154,221])
self.assertEqual(structure, expected_structure)
assert isinstance(structure,WussStructure)
def test_RfamParser_strict_missing_fields(self):
"""RfamParser: toggle strict functions correctly """
# strict = True
self.assertRaises(RecordError,list,\
RfamParser(self._fake_record_no_headers))
self.assertRaises(RecordError,list,\
RfamParser(self._fake_record_no_sequences))
self.assertRaises(RecordError,list,\
RfamParser(self._fake_record_no_structure))
# strict = False
self.assertEqual(list(RfamParser(self._fake_record_no_headers,\
strict=False)), [])
self.assertEqual(list(RfamParser(self._fake_record_no_sequences,\
strict=False)), [])
self.assertEqual(list(RfamParser(self._fake_record_no_structure,\
strict=False)), [])
def test_RFamParser_strict_invalid_headers(self):
"""RfamParser: functions when toggling strict w/ record w/ bad header
"""
self.assertRaises(RecordError,list,\
RfamParser(self._fake_record_bad_header_1))
self.assertRaises(RecordError,list,\
RfamParser(self._fake_record_bad_header_2))
# strict = False
x = list(RfamParser(self._fake_record_bad_header_1, strict=False))
obs = list(RfamParser(self._fake_record_bad_header_1,\
strict=False))[0][0].keys()
self.assertEqual(len(obs),1)
obs = list(RfamParser(self._fake_record_bad_header_2,\
strict=False))[0][0].keys()
self.assertEqual(len(obs),1)
def test_RfamParser_strict_invalid_sequences(self):
"""RfamParser: functions when toggling strict w/ record w/ bad seq
"""
self.assertRaises(RecordError,list,
MinimalRfamParser(self._fake_record_bad_sequence_1))
# strict = False
# in 'False' mode you expect to get back as much as possible, also
# parts of sequences
self.assertEqual(len(list(RfamParser(self._fake_record_bad_sequence_1,\
strict=False))[0][1].NamedSeqs), 3)
def test_RfamParser_strict_invalid_structure(self):
"""RfamParser: functions when toggling strict w/ record w/ bad struct
"""
# strict
self.assertRaises(RecordError,list,\
RfamParser(self._fake_record_bad_structure_2))
#not strict
self.assertEqual(list(RfamParser(self._fake_record_bad_structure_2,\
strict=False)),[])
def test_RfamParser_single_family(self):
"""RfamParser: should work on a single family in stockholm format"""
exp_header = Info()
exp_aln = {'K02120.1/628-682':\
'AUGGGAAAUUCCCCCUCCUAUAACCCCCCCGCUGGUAUCUCCCCCUCAGACUGGC',\
'D00647.1/629-683':\
'AUGGGAAACUCCCCCUCCUAUAACCCCCCCGCUGGCAUCUCCCCCUCAGACUGGC'}
exp_struct = '<<<<<<.........>>>>>>.........<<<<<<.............>>>>>>'
h, a, s = list(RfamParser(self.single_family))[0]
self.assertEqual(h,exp_header)
self.assertEqual(a,exp_aln)
self.assertEqual(s,exp_struct)
# This is an altered version of some header info from Rfam.seed modified to
# incorporate different cases for testing
fake_headers = """#=GF AC RF00001
#=GF AU Griffiths-Jones SR
#=GF ID 5S_rRNA
#=GF RT 5S Ribosomal RNA Database.
#=GF DR URL; http://oberon.fvms.ugent.be:8080/rRNA/ssu/index.html;
#=GF DR URL; http://rdp.cme.msu.edu/html/;
#=GF CC This is a short
#=GF CC comment
#=GF SQ 606
#=GF PK not real"""
fake_record_no_headers ="""Z11765.1/1-89 GGUC
#=GC SS_cons ............>>>
//"""
fake_record_no_sequences ="""#=GF AC RF00006
#=GC SS_cons ............>
//"""
fake_record_no_structure ="""#=GF AC RF00006
Z11765.1/1-89 GGUCAGC
//"""
fake_two_records ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//
#=GF AC RF00015
//"""
fake_record ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_header_1 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AUMifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_header_2 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GFAUMifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_sequence_1 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_structure_1 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_structure_2 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
single_family=\
"""K02120.1/628-682 AUGGGAAAUUCCCCCUCCUAUAACCCCCCCGCUGGUAUCUCCCCCUCAGA
D00647.1/629-683 AUGGGAAACUCCCCCUCCUAUAACCCCCCCGCUGGCAUCUCCCCCUCAGA
#=GC SS_cons <<<<<<.........>>>>>>.........<<<<<<.............>
K02120.1/628-682 CUGGC
D00647.1/629-683 CUGGC
#=GC SS_cons >>>>>
//"""
# Run tests if called from the command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_rna_fold.py 000644 000765 000024 00000011264 12024702176 022755 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for the RNAfold dot plot parser
"""
from __future__ import division
from cogent.util.unit_test import TestCase, main
from cogent.parse.rna_fold import *
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Production"
class RnaFoldParserTests(TestCase):
"""Tests for RnaFoldParser.
"""
def setUp(self):
"""Setup function for RnaFoldParser tests.
"""
self.rna_fold_parser_results = ('ACGUGCUAG',
[(1, 7, float(0.01462)),
(2, 9, float(0.11118)),
(3, 7, float(0.00985)),
(4, 8, float(0.01005)),
(4, 9, float(0.01586))])
self.sequence_lines = ['/sequence line before where sequences start\n',
' ACCUGUCUAUCGCUGC&*$#@(*\n',
'ACGGUUAUAUUAUCUCUG\\\n',
') end of sequence\n']
self.sequence_lines_empty = ['/sequence \n',
'\n',
')\n']
self.index_lines = ['unimportant line',
'1 3 0.332 ubox',
'1 4 0.003 ubox']
self.index_lines_no_ubox = ['unimportant line',
'1 2 0.432 u box',
'1 4 0.32 ubo x']
def test_getSequence(self):
self.assertEqual(getSequence(self.sequence_lines),
'ACCUGUCUAUCGCUGC&*$#@(*ACGGUUAUAUUAUCUCUG')
self.assertEqual(getSequence(self.sequence_lines_empty),'')
def test_getIndices(self):
self.assertEqual(getIndices(self.index_lines),[(1,3,float(0.332)),
(1,4,float(0.003))])
self.assertEqual(getIndices(self.index_lines_no_ubox),[])
def test_RnaFoldParser(self):
self.assertEqual(RnaFoldParser([]), ('',[]))
self.assertEqual(RnaFoldParser(RNA_FOLD_RESULTS),
self.rna_fold_parser_results)
RNA_FOLD_RESULTS = ['%!PS-Adobe-3.0 EPSF-3.0\n',
'%%Title: RNA DotPlot\n',
'%%Creator: PS_dot.c,v 1.24 2003/08/07 09:01:00 ivo Exp $, ViennaRNA-1.5\n',
'%%CreationDate: Fri Oct 8 13:15:01 2004\n',
'%%BoundingBox: 66 211 518 662\n',
'%%DocumentFonts: Helvetica\n',
'%%Pages: 1\n',
'%%EndComments\n',
'\n',
'%Options: \n',
'%This file contains the square roots of the base pair probabilities in the form\n',
'% i j sqrt(p(i,j)) ubox\n',
'100 dict begin\n',
'\n',
'/logscale false def\n',
'\n',
'%delete next line to get rid of title\n',
'270 665 moveto /Helvetica findfont 14 scalefont setfont (dot.ps) show\n',
'\n',
'/lpmin {\n',
' 1e-05 log % log(pmin) only probs>pmin will be shown\n',
'} bind def\n',
'\n',
'/box { %size x y box - draws box centered on x,y\n',
' 2 index 0.5 mul add % x += 0.5\n',
' exch 2 index 0.5 mul add exch % x += 0.5\n',
' newpath\n',
' moveto\n',
' dup neg 0 rlineto\n',
' dup neg 0 exch rlineto\n',
' 0 rlineto\n',
' closepath\n',
' fill\n',
'} bind def\n',
'\n',
'/sequence { (\\\n',
'ACGUGCUAG\\\n',
') } def\n',
'/len { sequence length } bind def\n',
'\n',
'/ubox {\n',
' logscale {\n',
' log dup add lpmin div 1 exch sub dup 0 lt { pop 0 } if\n',
' } if\n',
' 3 1 roll\n',
' exch len exch sub 1 add box\n',
'} bind def\n',
'\n',
'/lbox {\n',
' 3 1 roll\n',
' len exch sub 1 add box\n',
'} bind def\n',
'\n',
'72 216 translate\n',
'72 6 mul len 1 add div dup scale\n',
'/Helvetica findfont 0.95 scalefont setfont\n',
'\n',
'% print sequence along all 4 sides\n',
'[ [0.7 -0.3 0 ]\n',
' [0.7 0.7 len add 0]\n',
' [0.7 -0.2 90]\n',
' [-0.3 len sub 0.7 len add -90]\n',
'] {\n',
' gsave\n',
' aload pop rotate translate\n',
' 0 1 len 1 sub {\n',
' dup 0 moveto\n',
' sequence exch 1 getinterval\n',
' show\n',
' } for\n',
' grestore\n',
'} forall\n',
'\n',
'0.5 dup translate\n',
'% draw diagonal\n',
'0.04 setlinewidth\n',
'0 len moveto len 0 lineto stroke \n',
'\n',
'%draw grid\n',
'0.01 setlinewidth\n',
'len log 0.9 sub cvi 10 exch exp % grid spacing\n',
'dup 1 gt {\n',
' dup dup 20 div dup 2 array astore exch 40 div setdash\n',
'} { [0.3 0.7] 0.1 setdash } ifelse\n',
'0 exch len {\n',
' dup dup\n',
' 0 moveto\n',
' len lineto \n',
' dup\n',
' len exch sub 0 exch moveto\n',
' len exch len exch sub lineto\n',
' stroke\n',
'} for\n',
'0.5 neg dup translate\n',
'\n',
'1 7 0.01462 ubox\n',
'2 9 0.11118 ubox\n',
'3 7 0.00985 ubox\n',
'4 8 0.01005 ubox\n',
'4 9 0.01586 ubox\n',
'showpage\n',
'end\n',
'%%EOF\n']
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_rna_plot.py 000644 000765 000024 00000016216 12024702176 023011 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for the RNAplot parser
"""
from __future__ import division
from cogent.util.unit_test import TestCase, main
import string
import re
from cogent.parse.rna_plot import get_sequence, get_coordinates, get_pairs,\
RnaPlotParser
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jermey.widmann@colorado.edu"
__status__ = "Production"
class RnaPlotParserTests(TestCase):
"""Tests for RnaPlotParser.
"""
def setUp(self):
"""Setup function for RnaPlotParser tests.
"""
self.sequence_lines = SEQUENCE_LINES.split('\n')
self.expected_seq = 'AAACCGCCUUU'
self.coordinate_lines = COORDINATE_LINES.split('\n')
self.expected_coords = [[92.500,92.500],\
[92.500,77.500],\
[92.500,62.500],\
[82.218,50.185],\
[85.577,34.497],\
[100.000,27.472],\
[114.423,34.497],\
[117.782,50.185],\
[107.500,62.500],\
[107.500,77.500],\
[107.500,92.500]]
self.pairs_lines = PAIRS_LINES.split('\n')
self.expected_pairs = [[0,10],\
[1,9],\
[2,8]]
self.rna_plot_lines = RNA_PLOT_FILE.split('\n')
def test_get_sequence(self):
"""get_sequence should properly parse out sequence.
"""
#test real data
obs_seq = get_sequence(self.sequence_lines)
self.assertEqual(obs_seq, self.expected_seq)
#test empty list
self.assertEqual(get_sequence([]),'')
def test_get_coordinates(self):
"""get_coordinates should proplerly parse out coordinates.
"""
obs_coords = get_coordinates(self.coordinate_lines)
for (obs1, obs2), (exp1, exp2) in zip(obs_coords,self.expected_coords):
self.assertFloatEqual(obs1,exp1)
self.assertFloatEqual(obs2,exp2)
#test empty list
self.assertEqual(get_coordinates([]),[])
def test_get_pairs(self):
"""get_pairs should proplerly parse out pairs.
"""
obs_pairs = get_pairs(self.pairs_lines)
self.assertEqual(obs_pairs, self.expected_pairs)
#test empty list
self.assertEqual(get_pairs([]),[])
def test_RnaPlotParser(self):
"""RnaPlotParser should properly parse full RNAplot postscript file.
"""
obs_seq, obs_coords, obs_pairs = RnaPlotParser(self.rna_plot_lines)
#test seq is correctly parsed
self.assertEqual(obs_seq, self.expected_seq)
#test coords are correctly parsed
for (obs1, obs2), (exp1, exp2) in zip(obs_coords,self.expected_coords):
self.assertFloatEqual(obs1,exp1)
self.assertFloatEqual(obs2,exp2)
#test pairs are correctly parsed
self.assertEqual(obs_pairs, self.expected_pairs)
#test empty list
self.assertEqual(RnaPlotParser([]),('',[],[]))
SEQUENCE_LINES = """
/sequence (\
AAACCGCCUUU\
) def
/coor [
[92.500 92.500]
[92.500 77.500]
[92.500 62.500]
[82.218 50.185]
[85.577 34.497]
[100.000 27.472]
[114.423 34.497]
[117.782 50.185]
[107.500 62.500]
[107.500 77.500]
[107.500 92.500]
] def
/pairs [
[1 11]
[2 10]
[3 9]
] def
init
% switch off outline pairs or bases by removing these lines
drawoutline
drawpairs
drawbases
% show it
showpage
end
%%EOF
"""
COORDINATE_LINES = """
/coor [
[92.500 92.500]
[92.500 77.500]
[92.500 62.500]
[82.218 50.185]
[85.577 34.497]
[100.000 27.472]
[114.423 34.497]
[117.782 50.185]
[107.500 62.500]
[107.500 77.500]
[107.500 92.500]
] def
/pairs [
[1 11]
[2 10]
[3 9]
] def
init
% switch off outline pairs or bases by removing these lines
drawoutline
drawpairs
drawbases
% show it
showpage
end
%%EOF
"""
PAIRS_LINES = """
/pairs [
[1 11]
[2 10]
[3 9]
] def
init
% switch off outline pairs or bases by removing these lines
drawoutline
drawpairs
drawbases
% show it
showpage
end
%%EOF
"""
RNA_PLOT_FILE = """
%!PS-Adobe-3.0 EPSF-3.0
%%Creator: PS_dot.c,v 1.38 2007/02/02 15:18:13 ivo Exp $, ViennaRNA-1.8.2
%%CreationDate: Wed Apr 14 12:08:23 2010
%%Title: RNA Secondary Structure Plot
%%BoundingBox: 66 210 518 662
%%DocumentFonts: Helvetica
%%Pages: 1
%%EndComments
%Options:
% to switch off outline pairs of sequence comment or
% delete the appropriate line near the end of the file
%%BeginProlog
/RNAplot 100 dict def
RNAplot begin
/fsize 14 def
/outlinecolor {0.2 setgray} bind def
/paircolor {0.2 setgray} bind def
/seqcolor {0 setgray} bind def
/cshow { dup stringwidth pop -2 div fsize -3 div rmoveto show} bind def
/min { 2 copy gt { exch } if pop } bind def
/max { 2 copy lt { exch } if pop } bind def
/drawoutline {
gsave outlinecolor newpath
coor 0 get aload pop 0.8 0 360 arc % draw 5' circle of 1st sequence
currentdict /cutpoint known % check if cutpoint is defined
{coor 0 cutpoint getinterval
{aload pop lineto} forall % draw outline of 1st sequence
coor cutpoint get aload pop
2 copy moveto 0.8 0 360 arc % draw 5' circle of 2nd sequence
coor cutpoint coor length cutpoint sub getinterval
{aload pop lineto} forall} % draw outline of 2nd sequence
{coor {aload pop lineto} forall} % draw outline as a whole
ifelse
stroke grestore
} bind def
/drawpairs {
paircolor
0.7 setlinewidth
[9 3.01] 9 setdash
newpath
pairs {aload pop
coor exch 1 sub get aload pop moveto
coor exch 1 sub get aload pop lineto
} forall
stroke
} bind def
% draw bases
/drawbases {
[] 0 setdash
seqcolor
0
coor {
aload pop moveto
dup sequence exch 1 getinterval cshow
1 add
} forall
pop
} bind def
/init {
/Helvetica findfont fsize scalefont setfont
1 setlinejoin
1 setlinecap
0.8 setlinewidth
72 216 translate
% find the coordinate range
/xmax -1000 def /xmin 10000 def
/ymax -1000 def /ymin 10000 def
coor {
aload pop
dup ymin lt {dup /ymin exch def} if
dup ymax gt {/ymax exch def} {pop} ifelse
dup xmin lt {dup /xmin exch def} if
dup xmax gt {/xmax exch def} {pop} ifelse
} forall
/size {xmax xmin sub ymax ymin sub max} bind def
72 6 mul size div dup scale
size xmin sub xmax sub 2 div size ymin sub ymax sub 2 div
translate
} bind def
end
%%EndProlog
RNAplot begin
% data start here
/sequence (\
AAACCGCCUUU\
) def
/coor [
[92.500 92.500]
[92.500 77.500]
[92.500 62.500]
[82.218 50.185]
[85.577 34.497]
[100.000 27.472]
[114.423 34.497]
[117.782 50.185]
[107.500 62.500]
[107.500 77.500]
[107.500 92.500]
] def
/pairs [
[1 11]
[2 10]
[3 9]
] def
init
% switch off outline pairs or bases by removing these lines
drawoutline
drawpairs
drawbases
% show it
showpage
end
%%EOF
"""
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_rnaalifold.py 000644 000765 000024 00000006172 12024702176 023306 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.rnaalifold import rnaalifold_parser, MinimalRnaalifoldParser
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman","Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class RnaalifoldParserTest(TestCase):
"""Provides tests for RNAALIFOLD RNA secondary structure format parsers"""
def setUp(self):
"""Setup function """
#output
self.rnaalifold_out = RNAALIFOLD
#expected
self.rnaalifold_exp = [['GGCUAGGUAAAUCC',[(0,13),(1,12),(3,10)],-26.50]]
#output 2
self.rnaalifold_out_2 = RNAALIFOLD_2_STRUCTS
#expected
self.rnaalifold_exp_2 = \
[['GGCUAGGUAAAUCC',[(0,13),(1,12),(3,10)],\
float(-26.50)],\
['-GAUCCUAAGCGACGAAGUUYAWSCU------YGKRYARYRWWKKR-',\
[(6,21),(7,20),(8,19),(9,18),(10,17)],\
float(-0.80)]]
def test_rnaalifold_output(self):
"""Test for rnaalifold format parser"""
#Test empty lines
self.assertEqual(rnaalifold_parser(''),[])
#Test one structure
obs = rnaalifold_parser(self.rnaalifold_out)
self.assertEqual(obs,self.rnaalifold_exp)
#Test two structures
obs_2 = rnaalifold_parser(self.rnaalifold_out_2)
self.assertEqual(obs_2,self.rnaalifold_exp_2)
class MinimalRnaalifoldParserTest(TestCase):
"""Provides tests for MinimalRnaalifoldParser structure format parser.
"""
def setUp(self):
"""Setup function """
#output
self.rnaalifold_out = RNAALIFOLD
#expected
self.rnaalifold_exp = [['GGCUAGGUAAAUCC','((.(......).))',\
float(-26.50)]]
#output 2
self.rnaalifold_out_2 = RNAALIFOLD_2_STRUCTS
#expected
self.rnaalifold_exp_2 = \
[['GGCUAGGUAAAUCC','((.(......).))',float(-26.50)],\
['-GAUCCUAAGCGACGAAGUUYAWSCU------YGKRYARYRWWKKR-',\
'......(((((......))))).........................',\
float(-0.80)]]
def test_rnaalifold_output(self):
"""Test for rnaalifold format parser"""
#Test empty lines
self.assertEqual(MinimalRnaalifoldParser(''),[])
#Test one structure
obs = MinimalRnaalifoldParser(self.rnaalifold_out)
self.assertEqual(obs,self.rnaalifold_exp)
#Test two structures
obs_2 = MinimalRnaalifoldParser(self.rnaalifold_out_2)
self.assertEqual(obs_2,self.rnaalifold_exp_2)
RNAALIFOLD = ['GGCUAGGUAAAUCC\n',
'((.(......).)) (-26.50 = -26.50 + 0.00) \n']
RNAALIFOLD_2_STRUCTS = ['GGCUAGGUAAAUCC\n',
'((.(......).)) (-26.50 = -26.50 + 0.00) \n',\
'-GAUCCUAAGCGACGAAGUUYAWSCU------YGKRYARYRWWKKR-\n',
'......(((((......)))))......................... ( -0.80 = -1.30 + 0.50)\n',]
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_rnaforester.py 000644 000765 000024 00000014434 12024702176 023525 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.parse.rnaforester import rnaforester_parser
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class RnaforesterParserTest(TestCase):
"""Provides tests for RNAforester RNA secondary structure format parsers"""
def setUp(self):
"""Setup function
application output is not always actual(real) output from
the application but output in the format of the application
output in question. this to save space and time(mine)"""
#output
self.rnaforester_out = RNAFORESTER
#expected
self.rnaforester_exp = [[{'seq1':'ggccacguagcucagucgguagagcaaaggacugaaaauccuugugucguugguucaauuccaaccguggccacca',
'seq2':'-gccagauagcucagucgguagagcguucgccugaaaagugaaaggucgccgguucgaucccggcucuggccacca'},
'ggccacauagcucagucgguagagcaaacgacugaaaagccaaaggucgccgguucaaucccaacccuggccacca',
[(0, 71), (1, 70), (2, 69), (3, 68), (4, 67), (5, 66), (6, 65), (9, 24),
(10, 23), (11, 22), (12, 21), (26, 42), (27, 41), (28, 40), (29, 39),
(31, 38), (32, 37), (48, 64), (49, 63), (50, 62), (51, 61), (52, 60)]]]
def test_rnaforester_output(self):
"""Test for rnaforester format"""
obs = rnaforester_parser(self.rnaforester_out)
self.assertEqual(obs,self.rnaforester_exp)
RNAFORESTER = ['*** Scoring parameters ***\n', '\n',
'Scoring type: similarity\n', 'Scoring parameters:\n', 'pm: 10\n',
'pd: -5\n', 'bm: 1\n', 'br: 0\n', 'bd: -10\n', '\n', '\n',
'Input string (upper or lower case); & to end for multiple alignments, @ to quit\n',
'....,....1....,....2....,....3....,....4....,....5....,....6....,....7....,....8\n',
'\n', '*** Calculation ***\n', '\n', 'clustering threshold is: 0.7\n',
'join clusters cutoff is: 0\n', '\n', 'Computing all pairwise similarities\n',
'2,1: 0.74606\n', '\n', 'joining alignments:\n', '1,2: 0.74606 -> 1\n',
'Calculate similarities to other clusters\n', '\n', '\n', '*** Results ***\n',
'\n', 'Minimum basepair probability for consensus structure (-cmin): 0.5\n',
'\n', 'RNA Structure Cluster Nr: 1\n', 'Score: 264.25\n', 'Members: 2\n', '\n', 'seq1 ggccacguagcucagucgguagagcaaaggacugaaaauccuugugucguugguu\n',
'seq2 -gccagauagcucagucgguagagcguucgccugaaaagugaaaggucgccgguu\n',
' **** ****************** * ******* **** ****\n', '\n',
'seq1 caauuccaaccguggccacca\n',
'seq2 cgaucccggcucuggccacca\n',
' * ** ** * *********\n', '\n',
'seq1 (((((((..((((........)))).(((((.......))))).....(((((..\n',
'seq2 -((((((..((((........)))).((((.((....)))))).....(((((..\n',
' ***************************** **** *****************\n', '\n', 'seq1 .....))))))))))))....\n',
'seq2 .....))))))))))).....\n',
' **************** ****\n', '\n', '\n',
'Consensus sequence/structure:\n',
' 100% **** ****************** * ******* **** ****\n', ' 90% **** ****************** * ******* **** ****\n', ' 80% **** ****************** * ******* **** ****\n', ' 70% **** ****************** * ******* **** ****\n', ' 60% **** ****************** * ******* **** ****\n', ' 50% *******************************************************\n', ' 40% *******************************************************\n', ' 30% *******************************************************\n', ' 20% *******************************************************\n', ' 10% *******************************************************\n', ' ggccacauagcucagucgguagagcaaacgacugaaaagccaaaggucgccgguu\n', ' (((((((..((((........)))).((((.((....)))))).....(((((..\n', ' 10% *******************************************************\n', ' 20% *******************************************************\n', ' 30% *******************************************************\n', ' 40% *******************************************************\n', ' 50% *******************************************************\n', ' 60% *******************************************************\n', ' 70% ****************************** **** ****************\n', ' 80% ****************************** **** ****************\n', ' 90% ****************************** **** ****************\n', ' 100% ****************************** **** ****************\n', '\n', ' 100% * ** ** * *********\n', ' 90% * ** ** * *********\n', ' 80% * ** ** * *********\n', ' 70% * ** ** * *********\n', ' 60% * ** ** * *********\n', ' 50% *********************\n', ' 40% *********************\n', ' 30% *********************\n', ' 20% *********************\n', ' 10% *********************\n', ' caaucccaacccuggccacca\n', ' .....))))))))))))....\n', ' 10% *********************\n', ' 20% *********************\n', ' 30% *********************\n', ' 40% *********************\n', ' 50% *********************\n', ' 60% *********************\n', ' 70% **************** ****\n', ' 80% **************** ****\n', ' 90% **************** ****\n', ' 100% **************** ****\n', '\n', '\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_rnaview.py 000644 000765 000024 00000120626 12024702176 022647 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
#test_rnaview.py
"""Provides tests for code in the rnaview.py file.
"""
from cogent.util.unit_test import TestCase, main
from cogent.parse.rnaview import is_roman_numeral, is_edge, is_orientation,\
parse_annotation, parse_uncommon_residues, parse_base_pairs,\
parse_base_multiplets, parse_pair_counts, MinimalRnaviewParser,\
RnaviewParser, Base, BasePair, BasePairs, BaseMultiplet, BaseMultiplets,\
PairCounts, RnaViewObjectError, RnaViewParseError, MinimalRnaviewParser,\
parse_filename, parse_number_of_pairs, verify_bp_counts,\
in_chain, is_canonical, is_not_canonical, is_stacked, is_not_stacked,\
is_tertiary, is_not_stacked_or_tertiary, is_tertiary_base_base
__author__ = "Greg Caporaso and Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Greg Caporaso", "Sandra Smit", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Production"
#==============================================================================
# RNAVIEW OBJECTS TESTS
#==============================================================================
class BaseTests(TestCase):
"""Tests for Base class"""
def test_init(self):
"""Base __init__: should initialize on standard data"""
b = Base('A','30','G')
self.assertEqual(b.ChainId, 'A')
self.assertEqual(b.ResId, '30')
self.assertEqual(b.ResName, 'G')
#ResId or ResName can't be None or empty string
self.assertRaises(RnaViewObjectError, Base, None, None, 'G')
self.assertRaises(RnaViewObjectError, Base, '1', 'A', '')
self.assertRaises(RnaViewObjectError, Base, None, '', 'C')
#Can pass RnaViewSeqPos (str)
b = Base('C','12','A','10')
self.assertEqual(b.RnaViewSeqPos, '10')
def test_str(self):
"""Base __str__: should return correct string"""
b = Base('A','30','G')
self.assertEqual(str(b), 'A 30 G')
def test_eq(self):
"""Base ==: functions as expected """
# Define a standard to compare others
b = Base('A','30','G')
# Identical to b
b_a = Base('A','30','G')
# Differ in Chain from b
b_b = Base('B','30','G')
# Differ in ResId from b
b_c = Base('A','25','G')
# Differ in ResName from b
b_d = Base('A','30','C')
# Differ in RnaViewSeqPos
b_e = Base('A','30','G','2')
# Differ in everything from b
b_e = Base('C','12','U','1')
self.assertEqual(b == b, True)
self.assertEqual(b_a == b, True)
self.assertEqual(b_b == b, False)
self.assertEqual(b_c == b, False)
self.assertEqual(b_d == b, False)
self.assertEqual(b_e == b, False)
def test_ne(self):
"""Base !=: functions as expected"""
# Define a standard to compare others
b = Base('A','30','G')
# Identical to b
b_a = Base('A','30','G')
# Differ in Chain from b
b_b = Base('B','30','G')
# Differ in ResId from b
b_c = Base('A','25','G')
# Differ in ResName from b
b_d = Base('A','30','C')
# Differ in everything from b
b_e = Base('C','12','U')
self.assertEqual(b != b, False)
self.assertEqual(b_a != b, False)
self.assertEqual(b_b != b, True)
self.assertEqual(b_c != b, True)
self.assertEqual(b_d != b, True)
self.assertEqual(b_e != b, True)
class BasePairTests(TestCase):
"""Tests for BasePair object"""
def setUp(self):
"""setUp method for all tests in BasePairTests"""
self.b1 = Base('A','30','G')
self.b2 = Base('A','36','C')
self.bp = BasePair(self.b1, self.b2, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation=None)
def test_init(self):
"""BasePair __init__: should initialize on standard data"""
self.failUnless(self.bp.Up is self.b1)
self.failUnless(self.bp.Down is self.b2)
self.failUnless(self.bp.Conformation is None)
self.assertEqual(self.bp.Edges, 'H/W')
self.assertEqual(self.bp.Orientation, 'cis')
self.assertEqual(self.bp.Saenger, 'XI')
def test_str(self):
"""BasePair __str__: should return correct string"""
self.assertEqual(str(self.bp),
"Bases: A 30 G -- A 36 C; Annotation: H/W -- cis -- "+\
"None -- XI;")
def test_eq(self):
"BasePair ==: should function as expected"
# identical
up = Base('A','30','G')
down = Base('A','36','C')
bp = BasePair(up, down, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation=None)
self.assertEqual(bp == self.bp, True)
# diff up base
diff_up = Base('C','12','A')
bp = BasePair(diff_up, down, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation=None)
self.assertEqual(bp == self.bp, False)
# diff down base
diff_down = Base('D','13','U')
bp = BasePair(up, diff_down, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation=None)
self.assertEqual(bp == self.bp, False)
# diff edges
bp = BasePair(up, down, Edges='W/W', Saenger='XI',\
Orientation='cis', Conformation=None)
self.assertEqual(bp == self.bp, False)
# diff orientation
bp = BasePair(up, down, Edges='H/W', Saenger='XI',\
Orientation='tran', Conformation=None)
self.assertEqual(bp == self.bp, False)
# diff conformation
bp = BasePair(up, down, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation='syn')
self.assertEqual(bp == self.bp, False)
# diff saenger
bp = BasePair(up, down, Edges='H/W', Saenger='XIX',\
Orientation='cis', Conformation=None)
self.assertEqual(bp == self.bp, False)
def test_ne(self):
"BasePair !=: should function as expected"
# identical
up = Base('A','30','G')
down = Base('A','36','C')
bp = BasePair(up, down, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation=None)
self.assertEqual(bp != self.bp, False)
# diff up base
diff_up = Base('C','12','A')
bp = BasePair(diff_up, down, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation=None)
self.assertEqual(bp != self.bp, True)
# diff down base
diff_down = Base('D','13','U')
bp = BasePair(up, diff_down, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation=None)
self.assertEqual(bp != self.bp, True)
# diff edges
bp = BasePair(up, down, Edges='W/W', Saenger='XI',\
Orientation='cis', Conformation=None)
self.assertEqual(bp != self.bp, True)
# diff orientation
bp = BasePair(up, down, Edges='H/W', Saenger='XI',\
Orientation='tran', Conformation=None)
self.assertEqual(bp != self.bp, True)
# diff conformation
bp = BasePair(up, down, Edges='H/W', Saenger='XI',\
Orientation='cis', Conformation='syn')
self.assertEqual(bp != self.bp, True)
# diff saenger
bp = BasePair(up, down, Edges='H/W', Saenger='XIX',\
Orientation='cis', Conformation=None)
self.assertEqual(bp != self.bp, True)
def test_isWC(self):
"""BasePair isWC: should return True for GC or AU pair"""
bp = BasePair(Base('A','30','G'), Base('A','36','C'))
self.assertEqual(bp.isWC(), True)
bp = BasePair(Base('A','30','g'), Base('A','36','C'))
self.assertEqual(bp.isWC(), True)
bp = BasePair(Base('A','30','C'), Base('A','36','G'))
self.assertEqual(bp.isWC(), True)
bp = BasePair(Base('A','30','U'), Base('A','36','a'))
self.assertEqual(bp.isWC(), True)
bp = BasePair(Base('A','30','G'), Base('A','36','U'))
self.assertEqual(bp.isWC(), False)
def test_isWobble(self):
"""BasePair isWobble: should return True for GU pair"""
bp = BasePair(Base('A','30','G'), Base('A','36','U'))
self.assertEqual(bp.isWobble(), True)
bp = BasePair(Base('A','30','g'), Base('A','36','U'))
self.assertEqual(bp.isWobble(), True)
bp = BasePair(Base('A','30','u'), Base('A','36','g'))
self.assertEqual(bp.isWobble(), True)
bp = BasePair(Base('A','30','A'), Base('A','36','U'))
self.assertEqual(bp.isWobble(), False)
class BasePairsTests(TestCase):
"""Tests for BasePairs object"""
def setUp(self):
"""setUp method for all BasePairs tests"""
self.a1 = BasePair(Base('A','30','G'), Base('A','36','C'), Saenger='XX')
self.a2 = BasePair(Base('A','31','A'), Base('A','35','U'), Saenger='XX')
self.a3 = BasePair(Base('A','40','G'), Base('A','60','U'), Saenger='V')
self.a4 = BasePair(Base('A','41','A'), Base('A','58','U'),\
Saenger=None)
self.ab1 = BasePair(Base('A','41','A'), Base('B','58','U'))
self.ac1 = BasePair(Base('A','10','C'), Base('C','3','G'))
self.bc1 = BasePair(Base('B','41','A'), Base('C','1','U'))
self.bn1 = BasePair(Base('B','41','A'), Base(None,'1','U'))
self.cd1 = BasePair(Base('C','41','A'), Base('D','1','U'))
self.bp1 = BasePair(Base('A','34','U'), Base('A','40','A'))
self.bp2 = BasePair(Base('A','35','C'), Base('A','39','G'))
self.bp3 = BasePair(Base('B','32','G'), Base('B','38','U'))
self.bp4 = BasePair(Base('B','33','G'), Base('B','37','C'))
self.bp5 = BasePair(Base('A','31','C'), Base('B','41','G'))
self.bp6 = BasePair(Base('A','32','U'), Base('B','40','A'))
self.bp7 = BasePair(Base('A','37','U'), Base('B','35','A'))
self.pairs = BasePairs([self.bp1, self.bp2, self.bp3, self.bp4,\
self.bp5, self.bp6, self.bp7])
def test_init(self):
"""BasePairs __init__: should work with or without Model"""
# init from list
bps = BasePairs([self.a1, self.a2])
self.failUnless(bps[0] is self.a1)
self.failUnless(bps[1] is self.a2)
# init from tuple
bps = BasePairs((self.a1, self.a2))
self.failUnless(bps[0] is self.a1)
self.failUnless(bps[1] is self.a2)
def test_str(self):
"""BasePairs __str__: should produce expected string"""
b1 = BasePair(Base('A','30','G'), Base('A','36','C'), Saenger='XX')
b2 = BasePair(Base('A','31','A'), Base('A','35','U'),\
Orientation='cis',Edges='W/W')
bps = BasePairs([b1, b2])
exp_lines = [
"===================================================================",\
"Bases: Up -- Down; Annotation: Edges -- Orient. -- Conf. -- Saenger",\
"===================================================================",\
"Bases: A 30 G -- A 36 C; Annotation: None -- None -- None -- XX;",\
"Bases: A 31 A -- A 35 U; Annotation: W/W -- cis -- None -- None;"]
self.assertEqual(str(bps), '\n'.join(exp_lines))
def test_select(self):
"""BasePairs select: should work with any good function"""
def xx(bp):
if bp.Saenger == 'XX':
return True
return False
bps = BasePairs([self.a1, self.a2, self.a3, self.a4])
obs = bps.select(xx)
self.assertEqual(len(obs), 2)
self.failUnless(obs[0] is self.a1)
self.failUnless(obs[1] is self.a2)
for i in obs:
self.assertEqual(i.Saenger, 'XX')
def test_PresentChains(self):
"""BasePairs PresentChains: should work on single/multiple chain(s)"""
bps = BasePairs([self.a1, self.a2, self.a3, self.a4])
self.assertEqual(bps.PresentChains, ['A'])
bps = BasePairs([self.a1, self.ab1])
self.assertEqualItems(bps.PresentChains, ['A','B'])
bps = BasePairs([self.a1, self.ab1, self.ac1, self.bc1])
self.assertEqualItems(bps.PresentChains, ['A','B', 'C'])
bps = BasePairs([self.a1, self.ab1, self.bn1])
self.assertEqualItems(bps.PresentChains, [None, 'A','B'])
def test_cliques(self):
"""BasePairs cliques: single/multiple chains and cliques"""
#one chain, one clique
bps = BasePairs([self.a1, self.a2, self.a3, self.a4])
obs_cl = list(bps.cliques())
self.assertEqual(len(obs_cl), 1)
#3 chains, 2 cliques
bps = BasePairs([self.a1, self.a2, self.cd1])
obs_cl = list(bps.cliques())
self.assertEqual(len(obs_cl), 2)
self.assertEqual(len(obs_cl[0]), 2)
self.assertEqual(len(obs_cl[1]), 1)
self.failUnless(obs_cl[1][0] is self.cd1)
self.assertEqual(obs_cl[1].PresentChains, ['C','D'])
#5 chains, 1 clique
bps = BasePairs([self.a1, self.ab1, self.bc1, self.bn1, self.cd1])
obs_cl = list(bps.cliques())
self.assertEqual(len(obs_cl), 1)
self.assertEqual(len(obs_cl[0]), 5)
self.failUnless(obs_cl[0][0] is self.a1)
self.assertEqualItems(obs_cl[0].PresentChains, ['A','B','C','D', None])
def test_hasConflicts(self):
"""BasePairs hadConflicts: handle chains and residue IDs"""
# no conflict
b1 = BasePair(Base('A','30','G'), Base('A','36','C'), Saenger='XX')
b2 = BasePair(Base('A','31','A'), Base('A','35','U'),\
Orientation='cis',Edges='W/W')
b3 = BasePair(Base('A','15','G'), Base('A','42','C'))
bps = BasePairs([b1, b2, b3])
self.assertEqual(bps.hasConflicts(), False)
self.assertEqual(bps.hasConflicts(return_conflict=True), (False, None))
# conflict within chain
b1 = BasePair(Base('A','30','G'), Base('A','36','C'), Saenger='XX')
b2 = BasePair(Base('A','31','A'), Base('A','35','U'),\
Orientation='cis',Edges='W/W')
b3 = BasePair(Base('A','30','G'), Base('A','42','C'))
bps = BasePairs([b1, b2, b3])
self.assertEqual(bps.hasConflicts(), True)
# conflict within chain -- return conflict
b1 = BasePair(Base('A','30','G'), Base('A','36','C'), Saenger='XX')
b2 = BasePair(Base('A','31','A'), Base('A','35','U'),\
Orientation='cis',Edges='W/W')
b3 = BasePair(Base('A','30','G'), Base('A','42','C'))
bps = BasePairs([b1, b2, b3])
self.assertEqual(bps.hasConflicts(return_conflict=True),\
(True, "A 30 G"))
# no conflict, same residue ID, different chain
b1 = BasePair(Base('A','30','G'), Base('A','36','C'), Saenger='XX')
b2 = BasePair(Base('A','31','A'), Base('A','35','U'),\
Orientation='cis',Edges='W/W')
b3 = BasePair(Base('C','30','G'), Base('A','42','C'))
bps = BasePairs([b1, b2, b3])
self.assertEqual(bps.hasConflicts(), False)
class BaseMultipletTests(TestCase):
"""Tests for BaseMultiplet object"""
def test_init(self):
"""BaseMultiplet __init__: should work as expected"""
b1 = Base('A','30','A')
b2 = Base('A','35','G')
b3 = Base('A','360','U')
bm = BaseMultiplet([b1, b2, b3])
self.failUnless(bm[0] is b1)
self.failUnless(bm[2] is b3)
#should work from tuple also
bm = BaseMultiplet((b1, b2, b3))
self.failUnless(bm[0] is b1)
self.failUnless(bm[2] is b3)
def test_str(self):
"""BaseMultiplet __str__: should give expected string"""
b1 = Base('A','30','A')
b2 = Base('A','35','G')
b3 = Base('A','360','U')
bm = BaseMultiplet([b1, b2, b3])
exp = "A 30 A -- A 35 G -- A 360 U;"
self.assertEqual(str(bm), exp)
class BaseMultipletsTests(TestCase):
"""Tests for BaseMultiplets object"""
def test_init(self):
"""BaseMultiplets __init__: from list and tuple"""
b1 = Base('A','30','A')
b2 = Base('A','35','G')
b3 = Base('A','360','U')
bm1 = BaseMultiplet([b1, b2, b3])
b4 = Base('B','12','C')
b5 = Base('B','42','U')
b6 = Base('C','2','A')
bm2 = BaseMultiplet([b4, b5, b6])
bms = BaseMultiplets([bm1, bm2])
self.failUnless(bms[0] is bm1)
self.failUnless(bms[1] is bm2)
self.assertEqual(bms[1][2].ResId, '2')
#should work from tuple also
bms = BaseMultiplets((bm1, bm2))
self.failUnless(bms[0] is bm1)
self.failUnless(bms[1] is bm2)
self.assertEqual(bms[1][2].ResId, '2')
def test_str(self):
"""BaseMultiplets __str__: should give expected string"""
b1 = Base('A','30','A')
b2 = Base('A','35','G')
b3 = Base('A','360','U')
bm1 = BaseMultiplet([b1, b2, b3])
b4 = Base('B','12','C')
b5 = Base('B','42','U')
b6 = Base('C','2','A')
bm2 = BaseMultiplet([b4, b5, b6])
bms = BaseMultiplets([bm1, bm2])
exp_lines = [\
"A 30 A -- A 35 G -- A 360 U;",\
"B 12 C -- B 42 U -- C 2 A;"]
self.assertEqual(str(bms), '\n'.join(exp_lines))
class TestPairCounts(TestCase):
"""Tests for PairCounts object.
Contains only test for __init__. Everything should fucntion as a dict.
"""
def test_init(self):
"""PairCounts __init__: should work as dict"""
res = PairCounts(\
{'Standard':1, 'WS--cis':300, 'Bifurcated': 2, 'HS-tran':0})
self.assertEqual(res['Standard'], 1)
self.assertEqual(res['WS--cis'], 300)
self.assertEqual(res['Bifurcated'], 2)
self.assertEqual(res['HS-tran'], 0)
#==============================================================================
# SELECTION FUNCTIONS TESTS
#==============================================================================
class SelectionFunctionTests(TestCase):
def test_in_chain(self):
b1, b2 = Base('A','30','C'), Base('A','40','G')
bp1 = BasePair(b1, b2)
self.assertEqual(in_chain("A")(bp1), True)
self.assertEqual(in_chain(["A",'B'])(bp1), True)
self.assertEqual(in_chain("B")(bp1), False)
b3, b4 = Base('A','30','C'), Base('B','40','G')
bp2 = BasePair(b3,b4)
self.assertEqual(in_chain("A")(bp2), False)
self.assertEqual(in_chain(["A",'B'])(bp2), True)
self.assertEqual(in_chain("AB")(bp2), True)
self.assertEqual(in_chain("AC")(bp2), False)
b5, b6 = Base('A','30','C'), Base('C','40','G')
bp3 = BasePair(b5,b6)
self.assertEqual(in_chain("A")(bp3), False)
self.assertEqual(in_chain("C")(bp3), False)
self.assertEqual(in_chain(["A",'B'])(bp3), False)
self.assertEqual(in_chain("AC")(bp3), True)
def test_is_canocical(self):
"""is_canonical: work on annotation, not base identity"""
b1, b2 = Base('A','30','C'), Base('A','40','G')
bp = BasePair(b1, b2, Edges='+/+')
self.assertEqual(is_canonical(bp), True)
bp = BasePair(b1, b2, Edges='-/-')
self.assertEqual(is_canonical(bp), True)
bp = BasePair(b1, b2, Edges='W/W')
self.assertEqual(is_canonical(bp), False)
bp = BasePair(b1, b2, Edges='W/W', Orientation='cis',Saenger='XXVIII')
self.assertEqual(is_canonical(bp), True)
def test_is_not_canocical(self):
"""is_not_canonical: opposite of is_canonical"""
b1, b2 = Base('A','30','C'), Base('A','40','G')
bp = BasePair(b1, b2, Edges='+/+')
self.assertEqual(is_not_canonical(bp), False)
bp = BasePair(b1, b2, Edges='-/-')
self.assertEqual(is_not_canonical(bp), False)
bp = BasePair(b1, b2, Edges='W/W')
self.assertEqual(is_not_canonical(bp), True)
bp = BasePair(b1, b2, Edges='W/W', Orientation='cis',Saenger='XXVIII')
self.assertEqual(is_not_canonical(bp), False)
def test_is_stacked(self):
"""is_stacked: checks annotation, not base identity"""
b1, b2 = Base('A','30','C'), Base('A','40','A')
bp = BasePair(b1, b2, Edges='stacked')
self.assertEqual(is_stacked(bp), True)
bp = BasePair(b1, b2, Edges='H/?')
self.assertEqual(is_stacked(bp), False)
def test_is_not_stacked(self):
"""is_not_stacked: opposite of is_stacked"""
b1, b2 = Base('A','30','C'), Base('A','40','A')
bp = BasePair(b1, b2, Edges='stacked')
self.assertEqual(is_not_stacked(bp), False)
bp = BasePair(b1, b2, Edges='H/?')
self.assertEqual(is_not_stacked(bp), True)
def test_is_tertiary(self):
"""is_tertiary: checks annotation, not base identity"""
b1, b2 = Base('A','30','C'), Base('A','40','U')
bp = BasePair(b1, b2, Saenger='!1H(b_b)')
self.assertEqual(is_tertiary(bp), True)
bp = BasePair(b1, b2, Edges='H/?', Saenger='XX')
self.assertEqual(is_tertiary(bp), False)
bp = BasePair(b1,b2, Edges='stacked')
self.assertEqual(is_tertiary(bp), False)
def test_is_not_stacked_or_tertiary(self):
"""is_not_stacked_or_tertiary: checks annotation, not base identity"""
b1, b2 = Base('A','30','C'), Base('A','40','U')
bp = BasePair(b1, b2, Saenger='!1H(b_b)')
self.assertEqual(is_not_stacked_or_tertiary(bp), False)
bp = BasePair(b1, b2, Edges='stacked')
self.assertEqual(is_not_stacked_or_tertiary(bp), False)
bp = BasePair(b1, b2, Edges='W/W', Saenger='XX')
self.assertEqual(is_not_stacked_or_tertiary(bp), True)
def test_is_tertiary_base_base(self):
"""is_tertiary_base_base: checks annotation, not base identity"""
b1, b2 = Base('A','30','C'), Base('A','40','U')
bp = BasePair(b1, b2, Saenger='!1H(b_b)')
self.assertEqual(is_tertiary_base_base(bp), True)
bp = BasePair(b1, b2, Edges='H/?', Saenger='!(s_s)')
self.assertEqual(is_tertiary_base_base(bp), False)
#==============================================================================
# RNAVIEW PARSER TESTS
#==============================================================================
class RnaviewParserTests(TestCase):
"""Tests for RnaviewParser and related code"""
def test_is_roman_numeral(self):
"""is_roman_numeral: should work for all, including comma"""
self.assertEqual(is_roman_numeral('XIII'),True)
self.assertEqual(is_roman_numeral('Xiii'),False)
self.assertEqual(is_roman_numeral('MMCDXXVIII'),True)
self.assertEqual(is_roman_numeral('XII,XIII'),True)
self.assertEqual(is_roman_numeral('n/a'),False)
def test_is_edge(self):
"""is_edge: should identify valid edges correctly"""
self.assertEqual(is_edge('H/W'),True)
self.assertEqual(is_edge('./W'),True)
self.assertEqual(is_edge('+/+'),True)
self.assertEqual(is_edge(' '),False)
self.assertEqual(is_edge('P/W'),False)
self.assertEqual(is_edge('X/W'),True)
self.assertEqual(is_edge('X/X'),True)
def test_is_orientation(self):
"""is_orientation: should fail on anything but 'cis' or 'tran'"""
self.assertEqual(is_orientation('cis'),True)
self.assertEqual(is_orientation('tran'),True)
self.assertEqual(is_orientation('tranxxx'),False)
def test_parse_annotation(self):
"""parse_annotation: should return correct tuple of 4 or raise error
"""
self.assertEqual(parse_annotation(['W/S', 'tran', 'syn', 'syn',\
'n/a']), ('W/S','tran','syn syn','n/a'))
self.assertEqual(parse_annotation(['syn','stacked']),\
('stacked', None,'syn',None))
self.assertEqual(parse_annotation(['W/W','tran','syn','XII,XIII']),\
('W/W', 'tran','syn','XII,XIII'))
self.assertEqual(parse_annotation(['./W','cis','!1H(b_b)']),\
('./W', 'cis',None,'!1H(b_b)'))
self.assertEqual(parse_annotation([]),\
(None, None, None, None))
self.assertRaises(RnaViewParseError, parse_annotation, ['X--X'])
def test_parse_filename(self):
"""parse_filename: should return name of file"""
lines = ["PDB data file name: pdb1t4l.ent_nmr.pdb"]
self.assertEqual(parse_filename(lines), 'pdb1t4l.ent_nmr.pdb')
lines = ["PDB data file name: pdb1t4l.ent_nmr.pdb","other line"]
self.assertRaises(RnaViewParseError, parse_filename, lines)
def test_parse_uncommon_residues(self):
"""parse_uncommon_residues: should fail on some missing residue info
"""
lines = UC_LINES.split('\n')
self.assertEqual(parse_uncommon_residues(lines),\
{('D','16','TLN'):'u',('D','17','LCG'):'g',\
('0','2588','OMG'):'g',(' ','2621','PSU'):'P'})
for l in UC_LINES_WRONG.split('\n'):
self.assertRaises(RnaViewParseError, parse_uncommon_residues, [l])
def test_parse_base_pairs_basic(self):
"""parse_base_pairs: basic input"""
basic_lines =\
['25_437, 0: 34 C-G 448 0: +/+ cis XIX',\
'26_436, 0: 35 U-A 447 0: -/- cis XX']
bp1 = BasePair(Up=Base('0','34','C','25'),\
Down=Base('0','448','G','437'),\
Edges='+/+', Orientation='cis',Conformation=None,Saenger='XIX')
bp2 = BasePair(Up=Base('0','35','U','26'),\
Down=Base('0','447','A','436'),\
Edges='-/-', Orientation='cis',Conformation=None,Saenger='XX')
bps = BasePairs([bp1,bp2])
obs = parse_base_pairs(basic_lines)
for o,e in zip(obs,[bp1,bp2]):
self.assertEqual(o,e)
self.assertEqual(len(obs), 2)
basic_lines =\
['25_437, 0: 34 c-P 448 0: +/+ cis XIX',\
'26_436, 0: 35 U-X 447 0: -/- cis XX']
self.assertRaises(RnaViewParseError, parse_base_pairs, basic_lines)
basic_lines =\
['25_437, 0: 34 c-P 448 0: +/+ cis XIX',\
'26_436, 0: 35 I-A 447 0: -/- cis XX']
bp1 = BasePair(Up=Base('0','34','c','25'),\
Down=Base('0','448','P','437'),\
Edges='+/+', Orientation='cis',Conformation=None,Saenger='XIX')
bp2 = BasePair(Up=Base('0','35','I','26'),\
Down=Base('0','447','A','436'),\
Edges='-/-', Orientation='cis',Conformation=None,Saenger='XX')
bps = BasePairs([bp1,bp2])
obs = parse_base_pairs(basic_lines)
for o,e in zip(obs,[bp1,bp2]):
self.assertEqual(o,e)
self.assertEqual(len(obs), 2)
lines = ['1_2, : 6 G-G 7 : stacked',\
'1_16, : 6 G-C 35 : +/+ cis XIX']
bp1 = BasePair(Up=Base(' ','6','G','1'),\
Down=Base(' ','7','G','2'), Edges='stacked')
bp2 = BasePair(Up=Base(' ','6','G','1'),\
Down=Base(' ','35','C','16'),\
Edges='+/+', Orientation='cis',Conformation=None,Saenger='XIX')
obs = parse_base_pairs(lines)
for o,e in zip(obs,[bp1,bp2]):
self.assertEqual(o,e)
self.assertEqual(len(obs), 2)
def test_parse_base_multiplets_basic(self):
"""parse_base_multiplets: basic input"""
basic_lines =\
['235_237_254_| [20 3] 0: 246 G + 0: 248 A + 0: 265 U',\
'273_274_356_| [21 3] 0: 284 C + 0: 285 A + 0: 367 G']
bm1 = BaseMultiplet([Base('0','246','G','235'),\
Base('0','248','A','237'), Base('0','265','U','254')])
bm2 = BaseMultiplet([Base('0','284','C','273'),\
Base('0','285','A','274'), Base('0','367','G','356')])
bms = BaseMultiplets([bm1,bm2])
obs = parse_base_multiplets(basic_lines)
for o,e in zip(obs,bms):
for base_x, base_y in zip(o,e):
self.assertEqual(base_x,base_y)
self.assertEqual(len(obs), 2)
self.assertEqual(len(obs[0]), 3)
basic_lines =\
['235_237_254_| [20 3] 0: 246 G + 0: 248 A + 0: 265 I',\
'273_274_356_| [21 3] 0: 284 P + 0: 285 a + 0: 367 G']
bm1 = BaseMultiplet([Base('0','246','G','235'),\
Base('0','248','A','237'), Base('0','265','I','254')])
bm2 = BaseMultiplet([Base('0','284','P','273'),\
Base('0','285','a','274'), Base('0','367','G','356')])
bms = BaseMultiplets([bm1,bm2])
obs = parse_base_multiplets(basic_lines)
for o,e in zip(obs,bms):
for base_x, base_y in zip(o,e):
self.assertEqual(base_x,base_y)
self.assertEqual(len(obs), 2)
self.assertEqual(len(obs[0]), 3)
def test_parse_base_multiplets_errors(self):
"""parse_base_multiplets: error checking"""
# Unknown base
basic_lines =\
['235_237_254_| [20 3] 0: 246 X + 0: 248 A + 0: 265 U',\
'273_274_356_| [21 3] 0: 284 C + 0: 285 A + 0: 367 G']
self.assertRaises(RnaViewParseError, parse_base_multiplets,\
basic_lines)
# number of rnaview_seqpos doesn't match number of bases
basic_lines =\
['235_237_| [20 3] 0: 246 X + 0: 248 A + 0: 265 U',\
'273_274_356_| [21 3] 0: 284 C + 0: 285 A + 0: 367 G']
self.assertRaises(RnaViewParseError, parse_base_multiplets,\
basic_lines)
# Number of reported bases incorrect
basic_lines =\
['235_237_254_| [20 3] 0: 246 X + 0: 248 A + 0: 265 U',\
'273_274_356_| [21 5] 0: 284 C + 0: 285 A + 0: 367 G']
self.assertRaises(RnaViewParseError, parse_base_multiplets,\
basic_lines)
def test_parse_number_of_pairs(self):
"""parse_number_of_pairs: good/bad input"""
lines = ["The total base pairs = 31 (from 65 bases)"]
exp = {'NUM_PAIRS':31, 'NUM_BASES':65}
self.assertEqual(parse_number_of_pairs(lines), exp)
lines = ["The total base pairs = 31 (from 65 bases)","XXX"]
self.assertRaises(RnaViewParseError, parse_number_of_pairs, lines)
lines = ["The total base pairs = 31(from 65 bases)"]
self.assertRaises(RnaViewParseError, parse_number_of_pairs, lines)
def test_parse_pair_counts(self):
"""parse_pair_counts: should work for even number of lines"""
lines = PC_COUNTS1.split('\n')
res = parse_pair_counts(lines)
self.assertEqual(res['Standard'], 1)
self.assertEqual(res['WS--cis'], 300)
self.assertEqual(res['Bifurcated'], 2)
self.assertEqual(res['HS-tran'], 0)
lines = PC_COUNTS2.split('\n')
res = parse_pair_counts(lines)
self.assertEqual(res['Standard'], 19)
self.assertEqual(res['WW-tran'], 1)
self.assertEqual(res['HS-tran'], 0)
self.failIf('Bifurcated' in res)
self.assertRaises(RnaViewParseError, parse_pair_counts,\
PC_COUNTS2.split('\n')[:-1])
self.assertEqual(parse_pair_counts([]),{})
def test_verify_bp_counts(self):
"""verify_bp_count: should raise an error if bp counts are wrong"""
lines = RNAVIEW_PDB_REAL.split('\n')
obs = RnaviewParser(lines)
# this shouldn't raise an error
verify_bp_counts(obs['BP'],11,obs['PC'])
# reported number isn't right
self.assertRaises(RnaViewParseError,\
verify_bp_counts, obs['BP'], 12, obs['PC'])
# No longer checks for the base pair counts reported in the
# dictionary, b/c this number doens't match the total when
# modified bases are present.
## PREVIOUS TEST:
# pair_counts isn't right
#obs['PC']['Standard'] = 14
#self.assertRaises(RnaViewParseError,\
# verify_bp_counts, obs['BP'], 11, obs['PC'])
## NEW TEST
obs['PC']['Standard'] = 14
verify_bp_counts(obs['BP'],11,obs['PC'])
def test_MinimalRnaviewParser(self):
"""MinimalRnaviewParser: should divide lines into right classes"""
exp = {'FN': ['PDB data file name: 1EHZ.pdb'], 'UC':\
['uncommon residue I 1 on chain A [#1] assigned to: I',
'uncommon residue 2MG 10 on chain A [#10] assigned to: g'],
'BP':['1_72, A: 1 I-C 72 A: X/X cis n/a',
'58_60, A: 58 a-C 60 A: S/S tran syn !(s_s)'],
'BM':['9_12_23_| [1 3] A: 9 A + A: 12 U + A: 23 A',
'13_22_46_| [2 3] A: 13 C + A: 22 G + A: 46 g'],
'PC':['Standard WW--cis WW-tran HH--cis HH-tran SS--cis SS-tran',
'19 3 1 0 1 0 0',
'WH--cis WH-tran WS--cis WS-tran HS--cis HS-tran',
'0 3 0 2 0 0'],
'NP':['The total base pairs = 30 (from 76 bases)']}
obs = MinimalRnaviewParser(RNAVIEW_LINES.split('\n'))
self.assertEqual(len(obs), len(exp))
self.assertEqual(obs, exp)
def test_MinimalRnaviewParser_short(self):
"""MinimalRnaviewparser: should leave lists empty if no lines found"""
lines = RNAVIEW_LINES_SHORT.split('\n')
res = MinimalRnaviewParser(lines)
self.assertEqual(len(res['FN']), 1)
self.assertEqual(res['UC'], [])
self.assertEqual(res['BM'], [])
self.assertEqual(len(res['PC']), 4)
self.assertEqual(len(res['BP']), 11)
self.assertEqual(len(res['NP']), 1)
def test_RnaviewParser(self):
"""RnaviewParser: should work with/without model and/or verification
"""
rnaview_lines = RNAVIEW_PDB_REAL.split('\n')
obs = RnaviewParser(rnaview_lines)
self.assertEqual(obs['FN'], 'pdb430d.ent')
self.assertEqual(len(obs['UC']),1)
self.assertEqual(len(obs['BP']),19)
self.assertEqual(len(obs['BM']),0)
self.assertEqual(obs['BM'],BaseMultiplets())
self.assertEqual(obs['PC']['Standard'],7)
self.assertEqual(obs['BP'][2].Down.ResName,'c')
self.assertEqual(obs['BP'][6].Edges,'stacked')
self.assertEqual(obs['NP']['NUM_PAIRS'], 11)
self.assertEqual(obs['NP']['NUM_BASES'], 29)
def test_RnaviewParser_error(self):
"""RnaviewParser: strict or not"""
lines = RNAVIEW_LINES_ERROR.split('\n')
self.assertRaises(RnaViewParseError, RnaviewParser, lines, strict=True)
obs = RnaviewParser(lines, strict=False)
self.assertEqual(obs['NP'], None)
self.assertEqual(obs['BP'][1].Up.ResId, '2')
self.assertEqual(obs['PC']['Standard'], 6)
RNAVIEW_LINES=\
"""PDB data file name: 1EHZ.pdb
uncommon residue I 1 on chain A [#1] assigned to: I
uncommon residue 2MG 10 on chain A [#10] assigned to: g
BEGIN_base-pair
1_72, A: 1 I-C 72 A: X/X cis n/a
58_60, A: 58 a-C 60 A: S/S tran syn !(s_s)
END_base-pair
Summary of triplets and higher multiplets
BEGIN_multiplets
9_12_23_| [1 3] A: 9 A + A: 12 U + A: 23 A
13_22_46_| [2 3] A: 13 C + A: 22 G + A: 46 g
END_multiplets
The total base pairs = 30 (from 76 bases)
------------------------------------------------
Standard WW--cis WW-tran HH--cis HH-tran SS--cis SS-tran
19 3 1 0 1 0 0
WH--cis WH-tran WS--cis WS-tran HS--cis HS-tran
0 3 0 2 0 0
------------------------------------------------
"""
RNAVIEW_LINES_SHORT=\
"""PDB data file name: pdb17ra.ent_nmr.pdb
BEGIN_base-pair
1_21, : 1 G-C 21 : +/+ cis XIX
2_20, : 2 G-C 20 : +/+ cis XIX
3_19, : 3 C-G 19 : +/+ cis XIX
4_18, : 4 G-U 18 : W/W cis XXVIII
5_6, : 5 U-A 6 : stacked
5_17, : 5 U-A 17 : -/- cis XX
7_16, : 7 A-U 16 : W/W cis n/a
8_15, : 8 G-C 15 : +/+ cis XIX
9_14, : 9 G-C 14 : +/+ cis XIX
10_14, : 10 A-C 14 : stacked
11_13, : 11 U-A 13 : S/W tran n/a
END_base-pair
The total base pairs = 9 (from 21 bases)
------------------------------------------------
Standard WW--cis WW-tran HH--cis HH-tran SS--cis SS-tran
6 2 0 0 0 0 0
WH--cis WH-tran WS--cis WS-tran HS--cis HS-tran
0 0 0 1 0 0
------------------------------------------------"""
PC_COUNTS1=\
""" Standard WW--cis WW-tran HH--cis HH-tran SS--cis SS-tran
1 0 0 0 0 0 0
WH--cis WH-tran WS--cis WS-tran HS--cis HS-tran
12 0 300 0 0 0
Single-bond Bifurcated
0 2"""
PC_COUNTS2=\
""" Standard WW--cis WW-tran HH--cis HH-tran SS--cis SS-tran
19 3 1 0 1 0 0
WH--cis WH-tran WS--cis WS-tran HS--cis HS-tran
0 3 0 2 0 0"""
UC_LINES=\
"""uncommon residue TLN 16 on chain D [#16] assigned to: u
uncommon residue LCG 17 on chain D [#17] assigned to: g
uncommon residue OMG 2588 on chain 0 [#2430] assigned to: g
uncommon residue PSU 2621 on chain [#2463] assigned to: P"""
UC_LINES_WRONG=\
"""uncommon residue 16 on chain D [#16] assigned to: u
uncommon residue LCG on chain D [#17] assigned to: g
uncommon residue OMG 2588 on chain 0 [#2430] assigned to: """
RNAVIEW_LINES_TOTAL=\
"""PDB data file name: 1EHZ.pdb
uncommon residue PSU 1 on chain A [#1] assigned to: P
uncommon residue 2MG 10 on chain A [#10] assigned to: g
BEGIN_base-pair
1_72, A: 1 P-C 20 A: +/+ cis n/a
1_72, A: 2 A-U 19 A: H/W cis n/a
58_60, A: 10 a-U 60 A: S/S tran syn !(s_s)
END_base-pair
Summary of triplets and higher multiplets
BEGIN_multiplets
9_12_23_| [1 3] A: 1 P + A: 2 U + A: 60 U
13_22_46_| [2 3] A: 20 C + A: 19 U + A: 60 U
END_multiplets
The total base pairs = 30 (from 76 bases)
------------------------------------------------
Standard WW--cis WW-tran HH--cis HH-tran SS--cis SS-tran
19 3 1 0 1 0 0
WH--cis WH-tran WS--cis WS-tran HS--cis HS-tran
0 3 0 2 0 0
------------------------------------------------
"""
RNAVIEW_PDB_REAL=\
"""PDB data file name: pdb430d.ent
uncommon residue +C 27 on chain A [#27] assigned to: c
BEGIN_base-pair
1_29, A: 1 G-C 29 A: +/+ cis XIX
2_28, A: 2 G-C 28 A: +/+ cis XIX
3_27, A: 3 G-c 27 A: +/+ cis XIX
4_26, A: 4 U-A 26 A: -/- cis XX
5_25, A: 5 G-C 25 A: +/+ cis XIX
6_24, A: 6 C-G 24 A: +/+ cis XIX
7_8, A: 7 U-C 8 A: stacked
8_9, A: 8 C-A 9 A: stacked
9_21, A: 9 A-A 21 A: H/H tran II
11_20, A: 11 U-A 20 A: W/H tran XXIV
12_19, A: 12 A-G 19 A: H/S tran XI
13_18, A: 13 C-G 18 A: +/+ cis XIX
14_17, A: 14 G-A 17 A: S/H tran XI
25_26, A: 25 C-A 26 A: stacked
7_23, A: 7 U-C 23 A: W/W tran !1H(b_b)
8_23, A: 8 C-C 23 A: S/H cis !1H(b_b).
10_11, A: 10 G-U 11 A: S/H cis !1H(b_b)
11_21, A: 11 U-A 21 A: W/H tran !1H(b_b)
10_20, A: 10 G-A 20 A: W/. tran !(s_s)
END_base-pair
The total base pairs = 11 (from 29 bases)
------------------------------------------------
Standard WW--cis WW-tran HH--cis HH-tran SS--cis SS-tran
7 0 0 0 1 0 0
WH--cis WH-tran WS--cis WS-tran HS--cis HS-tran
0 1 0 0 0 2
------------------------------------------------"""
RNAVIEW_LINES_ERROR=\
"""PDB data file name: pdb17ra.ent_nmr.pdb
BEGIN_base-pair
1_21, : 1 G-C 21 : +/+ cis XIX
2_20, : 2 G-C 20 : +/+ cis XIX
3_19, : 3 C-G 19 : +/+ cis XIX
4_18, : 4 G-U 18 : W/W cis XXVIII
5_6, : 5 U-A 6 : stacked
5_17, : 5 U-A 17 : -/- cis XX
7_16, : 7 A-U 16 : W/W cis n/a
8_15, : 8 G-C 15 : +/+ cis XIX
9_14, : 9 G-C 14 : +/+ cis XIX
10_14, : 10 A-C 14 : stacked
11_13, : 11 U-A 13 : S/W tran n/a
END_base-pair
The total base pairs = 9(from 21 bases)
------------------------------------------------
Standard WW--cis WW-tran HH--cis HH-tran SS--cis SS-tran
6 2 0 0 0 0 0
WH--cis WH-tran WS--cis WS-tran HS--cis HS-tran
0 0 0 1 0 0
------------------------------------------------"""
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_sprinzl.py 000644 000765 000024 00000033626 12024702176 022700 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
#file evo/parsers/test_sprinzl.py
"""Unit tests for the Sprinzl tRNA database parser.
"""
from string import strip
from cogent.parse.sprinzl import OneLineSprinzlParser, GenomicSprinzlParser,\
_fix_sequence, get_pieces, get_counts, sprinzl_to_vienna
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Jeremy Widmann", "Sandra Smit"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
sample_file = """Accession@@@AA@@@Anticodon@@@Species@@@Strain@@@0@@@1@@@2@@@3@@@4@@@5@@@6@@@7@@@8@@@9@@@10@@@11@@@12@@@13@@@14@@@15@@@16@@@17@@@17A@@@18@@@19@@@20@@@20A@@@20B@@@21@@@22@@@23@@@24@@@25@@@26@@@27@@@28@@@29@@@30@@@31@@@32@@@33@@@34@@@35@@@36@@@37@@@38@@@39@@@40@@@41@@@42@@@43@@@44@@@45@@@e11@@@e12@@@e13@@@e14@@@e15@@@e16@@@e17@@@e1@@@e2@@@e3@@@e4@@@e5@@@e27@@@e26@@@e25@@@e24@@@e23@@@e22@@@e21@@@46@@@47@@@48@@@49@@@5.@@@51@@@52@@@53@@@54@@@55@@@56@@@57@@@58@@@59@@@60@@@61@@@62@@@63@@@64@@@65@@@66@@@67@@@68@@@69@@@7.@@@71@@@72@@@73@@@74@@@75@@@76
GA0000001@@@Ala@@@TGC@@@Haemophilus influenzae@@@Rd KW20@@@-@@@G@@@G@@@G@@@G@@@C@@@C@@@T@@@T@@@A@@@G@@@C@@@T@@@C@@@A@@@G@@@C@@@T@@@-@@@G@@@G@@@G@@@-@@@-@@@A@@@G@@@A@@@G@@@C@@@G@@@C@@@C@@@T@@@G@@@C@@@T@@@T@@@T@@@G@@@C@@@A@@@C@@@G@@@C@@@A@@@G@@@G@@@A@@@G@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@G@@@T@@@C@@@A@@@G@@@C@@@G@@@G@@@T@@@T@@@C@@@G@@@A@@@T@@@C@@@C@@@C@@@G@@@C@@@T@@@A@@@G@@@G@@@C@@@T@@@C@@@C@@@A@@@-@@@-@@@-
GA0000002@@@Ala@@@GGC@@@Chlamydia pneumoniae @@@AR39@@@-@@@G@@@G@@@G@@@G@@@T@@@A@@@T@@@T@@@A@@@G@@@C@@@T@@@C@@@A@@@G@@@T@@@T@@@-@@@G@@@G@@@T@@@-@@@-@@@A@@@G@@@A@@@G@@@C@@@G@@@C@@@A@@@A@@@C@@@A@@@A@@@T@@@G@@@G@@@C@@@A@@@T@@@T@@@G@@@T@@@T@@@G@@@A@@@G@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@G@@@T@@@C@@@A@@@G@@@C@@@G@@@G@@@T@@@T@@@C@@@G@@@A@@@C@@@C@@@C@@@C@@@G@@@C@@@T@@@A@@@T@@@G@@@C@@@T@@@C@@@C@@@-@@@-@@@-@@@-
GA0000003@@@Ala@@@TGC@@@Chlamydia pneumoniae @@@AR39@@@-@@@G@@@G@@@G@@@G@@@A@@@C@@@T@@@T@@@A@@@G@@@C@@@T@@@T@@@A@@@G@@@T@@@T@@@-@@@G@@@G@@@T@@@-@@@-@@@A@@@G@@@A@@@G@@@C@@@G@@@T@@@C@@@T@@@G@@@A@@@T@@@T@@@T@@@G@@@C@@@A@@@T@@@T@@@C@@@A@@@G@@@A@@@A@@@G@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@-@@@G@@@T@@@C@@@A@@@G@@@G@@@A@@@G@@@T@@@T@@@C@@@G@@@A@@@A@@@T@@@C@@@T@@@C@@@C@@@T@@@A@@@G@@@T@@@C@@@T@@@C@@@C@@@-@@@-@@@-@@@-"""
sample_lines = ['\t'.join(i.split('@@@')) for i in sample_file.split('\n')]
class OneLineSprinzlParserTests(TestCase):
"""Tests of OneLineSprinzlParser"""
def setUp(self):
"""standard tRNA file"""
self.tRNAs = sample_lines #open('data_sprinzl.txt').read().split('\n')
def test_minimal(self):
"""OneLineSprinzlParser should work on a minimal 'file'"""
small = ['acc\taa\tac\tsp\tst\ta\tb\tc','q\tw\te\tr\tt\tA\tC\tG']
p = OneLineSprinzlParser(small)
result = list(p)
self.assertEqual(len(result), 1)
self.assertEqual(result[0], 'ACG')
self.assertEqual(result[0].Info.Accession, 'q')
self.assertEqual(result[0].Info.AA, 'w')
self.assertEqual(result[0].Info.Anticodon, 'e')
self.assertEqual(result[0].Info.Species, 'r')
self.assertEqual(result[0].Info.Strain, 't')
def test_init(self):
"""OneLineSprinzlParser should read small file correctly"""
p = OneLineSprinzlParser(self.tRNAs)
recs = list(p)
self.assertEqual(len(recs), 3)
first, second, third = recs
assert first.Info.Labels is second.Info.Labels
assert first.Info.Labels is third.Info.Labels
expected_label_list = "0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 17A 18 19 20 20A 20B 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 e11 e12 e13 e14 e15 e16 e17 e1 e2 e3 e4 e5 e27 e26 e25 e24 e23 e22 e21 46 47 48 49 5. 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 7. 71 72 73 74 75 76".split()
exp_labels = {}
for i, label in enumerate(expected_label_list):
exp_labels[label] = i
self.assertEqual(first.Info.Labels, exp_labels)
self.assertEqual(first.Info.Accession, 'GA0000001')
self.assertEqual(first.Info.AA, 'Ala')
self.assertEqual(first.Info.Anticodon, 'TGC')
self.assertEqual(first.Info.Species, 'Haemophilus influenzae')
self.assertEqual(first.Info.Strain, 'Rd KW20')
self.assertEqual(first, '-GGGGCCTTAGCTCAGCT-GGG--AGAGCGCCTGCTTTGCACGCAGGAG-------------------GTCAGCGGTTCGATCCCGCTAGGCTCCA---'.replace('T','U'))
self.assertEqual(third.Info.Accession, 'GA0000003')
self.assertEqual(third.Info.AA, 'Ala')
self.assertEqual(third.Info.Anticodon, 'TGC')
self.assertEqual(third.Info.Species, 'Chlamydia pneumoniae')
self.assertEqual(third.Info.Strain, 'AR39')
self.assertEqual(third, '-GGGGACTTAGCTTAGTT-GGT--AGAGCGTCTGATTTGCATTCAGAAG-------------------GTCAGGAGTTCGAATCTCCTAGTCTCC----'.replace('T','U'))
genomic_sample = """3\t5950\tsequences\t\t0\t1\t2\t3\t4\t5\t6\t7\t8\t9\t10\t11\t12\t13\t14\t15\t16\t17\t17A\t18\t19\t20\t20A\t20B\t21\t22\t23\t24\t25\t26\t27\t28\t29\t30\t31\t32\t33\t34\t35\t36\t37\t38\t39\t40\t41\t42\t43\t44\t45\te11\te12\te13\te14\te15\te16\te17\te1\te2\te3\te4\te5\te27\te26\te25\te24\te23\te22\te21\t46\t47\t48\t49\t50\t51\t52\t53\t54\t55\t56\t57\t58\t59\t60\t61\t62\t63\t64\t65\t66\t67\t68\t69\t70\t71\t72\t73\t74\t75\t76\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
2\tGA0000001\tAla\t\tTGC\t\tHaemophilus influenzae\t\t\t\t\t\t\t\t\t\tRd KW20\t\t\t\tBacteria; Proteobacteria; gamma subdivision; Pasteurellaceae; Haemophilus\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
\t\t\t\t-\tG\tG\tG\tG\tC\tC\tT\tT\tA\tG\tC\tT\tC\tA\tG\tC\tT\t-\tG\tG\tG\t-\t-\tA\tG\tA\tG\tC\tG\tC\tC\tT\tG\tC\tT\tT\tT\tG\tC\tA\tC\tG\tC\tA\tG\tG\tA\tG\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\tG\tT\tC\tA\tG\tC\tG\tG\tT\tT\tC\tG\tA\tT\tC\tC\tC\tG\tC\tT\tA\tG\tG\tC\tT\tC\tC\tA\t-\t-\t-\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
\t\t\t\t\t=\t=\t*\t=\t=\t=\t=\t\t\t=\t=\t=\t=\t\t\t\t\t\t\t\t\t\t\t\t=\t=\t=\t=\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t=\t=\t=\t=\t*\t=\t=\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
3\tGA0000002\tAla\t\tGGC\t\tChlamydia pneumoniae \t\t\t\t\t\t\t\t\t\tAR39\t\t\t\tBacteria; Chlamydiales; Chlamydiaceae; Chlamydophila; Chlamydophila pneumoniae\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
\t\t\t\t-\tG\tG\tG\tG\tT\tA\tT\tT\tA\tG\tC\tT\tC\tA\tG\tT\tT\t-\tG\tG\tT\t-\t-\tA\tG\tA\tG\tC\tG\tC\tA\tA\tC\tA\tA\tT\tG\tG\tC\tA\tT\tT\tG\tT\tT\tG\tA\tG\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\tG\tT\tC\tA\tG\tC\tG\tG\tT\tT\tC\tG\tA\tC\tC\tC\tC\tG\tC\tT\tA\tT\tG\tC\tT\tC\tC\t-\t-\t-\t-\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
\t\t\t\t\t=\t=\t*\t=\t*\t=\t=\t\t\t=\t=\t=\t=\t\t\t\t\t\t\t\t\t\t\t\t=\t=\t=\t=\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t=\t=\t*\t=\t*\t=\t=\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
4\tGA0000003\tAla\t\tTGC\t\tChlamydia pneumoniae \t\t\t\t\t\t\t\t\t\tAR39\t\t\t\tBacteria; Chlamydiales; Chlamydiaceae; Chlamydophila; Chlamydophila pneumoniae\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
\t\t\t\t-\tG\tG\tG\tG\tA\tC\tT\tT\tA\tG\tC\tT\tT\tA\tG\tT\tT\t-\tG\tG\tT\t-\t-\tA\tG\tA\tG\tC\tG\tT\tC\tT\tG\tA\tT\tT\tT\tG\tC\tA\tT\tT\tC\tA\tG\tA\tA\tG\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\tG\tT\tC\tA\tG\tG\tA\tG\tT\tT\tC\tG\tA\tA\tT\tC\tT\tC\tC\tT\tA\tG\tT\tC\tT\tC\tC\t-\t-\t-\t-\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
\t\t\t\t\t=\t=\t*\t=\t=\t=\t=\t\t\t=\t=\t=\t*\t\t\t\t\t\t\t\t\t\t\t\t*\t=\t=\t=\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t\t\t\t\t\t\t\t=\t=\t=\t=\t=\t=\t=\t=\t=\t*\t=\t=\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t""".split('\n')
class GenomicSprinzlParserTests(TestCase):
"""Tests of the GenomicSprinzlParser class."""
def test_single(self):
"""GenomicSprinzlParser should work with single sequence"""
seqs = list(GenomicSprinzlParser(genomic_sample[0:4]))
self.assertEqual(len(seqs), 1)
s = seqs[0]
self.assertEqual(s, '-GGGGCCTTAGCTCAGCT-GGG--AGAGCGCCTGCTTTGCACGCAGGAG-------------------GTCAGCGGTTCGATCCCGCTAGGCTCCA---'.replace('T','U'))
self.assertEqual(s.Info.Accession, 'GA0000001')
self.assertEqual(s.Info.AA, 'Ala')
self.assertEqual(s.Info.Anticodon, 'UGC')
self.assertEqual(s.Info.Species, 'Haemophilus influenzae')
self.assertEqual(s.Info.Strain, 'Rd KW20')
self.assertEqual(s.Info.Taxonomy, ['Bacteria', 'Proteobacteria', \
'gamma subdivision', 'Pasteurellaceae', 'Haemophilus'])
self.assertEqual(s.Pairing, '.==*====..====...........====.=====.......=====........................=====.......=========*==....')
def test_multi(self):
"""GenomicSprinzlParser should work with multiple sequences"""
seqs = list(GenomicSprinzlParser(genomic_sample))
self.assertEqual(len(seqs), 3)
self.assertEqual([s.Info.Accession for s in seqs], \
['GA0000001', 'GA0000002', 'GA0000003'])
self.assertEqual(seqs[2].Info.Anticodon, 'UGC')
self.assertEqual(seqs[0].Info.Order, seqs[2].Info.Order)
class FixSequenceTests(TestCase):
"""Tests that _fix_structure functions properly."""
def test_fix_sequence(self):
"""Fix sequence should properly replace terminal gaps with CCA"""
seqs = ['','ACGUUCC-','ACGUUC--','ACGUU---','ACGU----']
results = ['','ACGUUCCA','ACGUUCCA','ACGUUCCA','ACGU-CCA']
for s,r in zip(seqs,results):
self.assertEqual(_fix_sequence(s),r)
class SprinzlToViennaTests(TestCase):
def setUp(self):
"""setUp function for SprinzlToViennaTests"""
self.structures = map(strip,STRUCTURES.split('\n'))
self.vienna_structs = map(strip,VIENNA.split('\n'))
self.short_struct = '...===...===.'
#structure too long
self.incorrect1 = ''.join(['..=====*..*==.............==*...=.=...',
'....=.=..........................=====.......=====*=====......'])
#two halves don't match
self.incorrect2 = ''.join(['..=====*..*===............==*...=.=...',
'....=.=..........................=====.......=====*=====.....'])
def test_get_pieces(self):
"""get_pieces: should return the correct pieces"""
splits = [0,3,7,-1,13]
self.assertEqual(get_pieces(self.short_struct, splits),\
['...','===.','..===','.'])
#will include empty strings for indices outside of the structure
self.assertEqual(get_pieces(self.short_struct,[2,10,20,30]),\
['.===...=','==.',''])
#will return empty list if no break-positions are given
self.assertEqual(get_pieces(self.short_struct,[]), [])
def test_get_counts(self):
"""get_counts: should return list of lengths of paired regions"""
self.assertEqual(get_counts('.===.=..'),[3,1])
self.assertEqual(get_counts('...====..'),[4])
self.assertEqual(get_counts('...'),[])
def test_sprinzl_to_vienna(self):
"""sprinzl_to_vienna: should give expected output"""
#This should only work for correct
for sprinzl,vienna in zip(self.structures, self.vienna_structs):
self.assertEqual(sprinzl_to_vienna(sprinzl),vienna)
#Check two obvious errors
self.assertRaises(AssertionError,sprinzl_to_vienna,self.incorrect1)
self.assertRaises(AssertionError,sprinzl_to_vienna,self.incorrect2)
STRUCTURES="""\
.===*===..====...........====.=====.......=====........................=====.......========*===....
.=======..=*=.............=*=.=====.......=====........................=====.......============....
.=======..====...........====.*====.......====*........................=.===.......===.========....
.=====.=..====...........====..===.........===.........................**===.......===**=.=====....
....====..====...........====.*====.......====*........................=====.......=========.......
..=====*..*==.............==*...=.=.......=.=..........................=====.......=====*=====.....
.=.=.==*..*.=*...........*=.*.*=.==.......==.=*........................=====.......=====*==.=.=....
.====*.=..**.=...........=.**.*====.......====*........................=.*.=.......=.*.==.*====....
.====*.=..**.=............=**.*====.......====*........................=.*.=.......=.*.==.*====...."""
VIENNA="""\
.(((((((..((((...........)))).(((((.......)))))........................(((((.......))))))))))))....
.(((((((..(((.............))).(((((.......)))))........................(((((.......))))))))))))....
.(((((((..((((...........)))).(((((.......)))))........................(.(((.......))).))))))))....
.(((((.(..((((...........))))..(((.........))).........................(((((.......)))))).)))))....
....((((..((((...........)))).(((((.......)))))........................(((((.......))))))))).......
..((((((..(((.............)))...(.(.......).)..........................(((((.......))))))))))).....
.(.(.(((..(.((...........)).).((.((.......)).))........................(((((.......)))))))).).)....
.(((((.(..((.(...........).)).(((((.......)))))........................(.(.(.......).).)).)))))....
.(((((.(..((.(............))).(((((.......)))))........................(.(.(.......).).)).)))))...."""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_stockholm.py 000644 000765 000024 00000062130 12024702176 023172 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""
Provides tests for StockholmParser and related classes and functions.
"""
from cogent.parse.stockholm import is_gf_line, is_gc_line, is_gs_line, \
is_gr_line, is_seq_line, is_structure_line, GfToInfo, GcToInfo, GsToInfo, \
GrToInfo, MinimalStockholmParser, StockholmFinder, \
StockholmParser, Sequence, is_empty_or_html
from cogent.util.unit_test import TestCase, main
from cogent.parse.record import RecordError
from cogent.core.info import Info
from cogent.struct.rna2d import WussStructure
from cogent.core.alignment import Alignment
from cogent.core.moltype import BYTES
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Development"
Sequence = BYTES.Sequence
class StockholmParserTests(TestCase):
""" Tests componenets of the stockholm parser, in the stockholm.py file """
def setUp(self):
""" Construct some fake data for testing purposes """
self._fake_headers = []
temp = list(fake_headers.split('\n'))
for line in temp:
self._fake_headers.append(line.strip())
del temp
self._fake_gc_annotation = []
temp = list(fake_gc_annotation.split('\n'))
for line in temp:
self._fake_gc_annotation.append(line.strip())
del temp
self._fake_gs_annotation = []
temp = list(fake_gs_annotation.split('\n'))
for line in temp:
self._fake_gs_annotation.append(line.strip())
del temp
self._fake_gr_annotation = []
temp = list(fake_gr_annotation.split('\n'))
for line in temp:
self._fake_gr_annotation.append(line.strip())
del temp
self._fake_record_no_headers =\
list(fake_record_no_headers.split('\n'))
self._fake_record_no_sequences =\
list(fake_record_no_sequences.split('\n'))
self._fake_record_no_structure =\
list(fake_record_no_structure.split('\n'))
self._fake_two_records =\
list(fake_two_records.split('\n'))
self._fake_record =\
list(fake_record.split('\n'))
self._fake_record_bad_header_1 =\
list(fake_record_bad_header_1.split('\n'))
self._fake_record_bad_header_2 =\
list(fake_record_bad_header_2.split('\n'))
self._fake_record_bad_sequence_1 =\
list(fake_record_bad_sequence_1.split('\n'))
self._fake_record_bad_structure_1 =\
list(fake_record_bad_structure_1.split('\n'))
self._fake_record_bad_structure_2 =\
list(fake_record_bad_structure_2.split('\n'))
self.single_family = single_family.split('\n')
def test_is_empty_or_html(self):
"""is_empty_or_html: should ignore empty and HTML line"""
line = ' '
self.assertEqual(is_empty_or_html(line), True)
line = '\n\n'
self.assertEqual(is_empty_or_html(line), True)
line = ''
self.assertEqual(is_empty_or_html(line), True)
line = ' \n\n'
self.assertEqual(is_empty_or_html(line), True)
line = '\t>..'), True)
self.assertEqual(is_gr_line('#=GR RF cGGacG'), True)
self.assertEqual(is_gr_line(''), False)
self.assertEqual(is_gr_line('X07545.1/505-619 '), False)
self.assertEqual(is_gr_line('#=G'), False)
self.assertEqual(is_gr_line('=GF'), False)
self.assertEqual(is_gr_line('#=GC SS_cons'), False)
def test_is_seq_line(self):
"""is_seq_line: functions correctly w/ various lines """
s = 'X07545.1/505-619 .\
.ACCCGGC.CAUA...GUGGCCG.GGCAA.CAC.CCGG.U.C..UCGUU'
assert is_seq_line('s')
assert is_seq_line('X07545.1/505-619')
assert is_seq_line('M21086.1/8-123')
assert not is_seq_line('')
assert not is_seq_line('#GF=')
assert not is_seq_line('//blah')
def test_is_structure_line(self):
"""is_structure_line: functions correctly w/ various lines """
s = '#=GC SS_cons\
<<<<<<<<<........<<.<<<<.<...<.<...<<<<.<.<.......'
self.assertEqual(is_structure_line(s), True)
self.assertEqual(is_structure_line('#=GC SS_cons'), False)
self.assertEqual(is_structure_line('#=GC SS_cons2'), False)
self.assertEqual(is_structure_line('#=GC SS_cons '), True)
self.assertEqual(is_structure_line(''), False)
self.assertEqual(is_structure_line(' '), False)
self.assertEqual(is_structure_line('#=GF AC RF00001'), False)
self.assertEqual(is_structure_line('X07545.1/505-619'), False)
self.assertEqual(is_structure_line('=GC SS_cons'), False)
self.assertEqual(is_structure_line('#=GC'), False)
self.assertEqual(is_structure_line('#=GC RF'), False)
def test_GfToInfo(self):
"""GfToInfo: correctly builds info object from header information"""
info = GfToInfo(self._fake_headers)
self.assertEqual(info['AccessionNumber'], 'RF00001')
self.assertEqual(info['Identification'], '5S_rRNA')
self.assertEqual(info['Comment'], 'This is a short comment')
self.assertEqual(info['Author'], 'Griffiths-Jones SR')
self.assertEqual(info['Sequences'], '606')
self.assertEqual(info['DatabaseReference'],\
['URL; http://oberon.fvms.ugent.be:8080/rRNA/ssu/index.html;',\
'URL; http://rdp.cme.msu.edu/html/;'])
self.assertEqual(info['PK'],'not real')
def test_GfToInfo_invalid_data(self):
"""GfToInfo: correctly raises error when necessary """
invalid_headers = [['#=GF ACRF00001'],['#=GFACRF00001']]
for h in invalid_headers:
self.assertRaises(RecordError, GfToInfo, h)
def test_GcToInfo(self):
"""GcToInfo: correctly builds info object from header information"""
info = GcToInfo(self._fake_gc_annotation)
self.assertEqual(info['ConsensusSecondaryStructure'], \
'..........<<<<<<<<<<.....>>>>>>>>>>..')
self.assertEqual(info['ReferenceAnnotation'], \
'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx')
def test_GcToInfo_invalid_data(self):
"""GcToInfo: correctly raises error when necessary """
invalid_headers = [['#=GCSS_cons ..<<..>>..'],['#=GCSAxxxxxxx']]
for h in invalid_headers:
self.assertRaises(RecordError, GcToInfo, h)
def test_GsToInfo(self):
"""GsToInfo: correctly builds info object from header information"""
info = GsToInfo(self._fake_gs_annotation)
self.assertEqual(info['BasePair'], \
{'1N77_C':['0 70 cWW CC','1 69 cWW CC','2 68 cWW CC',\
'3 67 cWW CC']})
def test_GsToInfo_invalid_data(self):
"""GsToInfo: correctly raises error when necessary """
invalid_headers = [['#=GSBPS 0 10 cwW CC'],['#=GSACRF00001']]
for h in invalid_headers:
self.assertRaises(RecordError, GsToInfo, h)
def test_GrToInfo(self):
"""GrToInfo: correctly builds info object from header information"""
info = GrToInfo(self._fake_gr_annotation)
self.assertEqual(info['SecondaryStructure'], \
{'1N77_C':'..........<<<<<<<<<<.....>>>>>>>>>>..'})
self.assertEqual(info['ReferenceAnnotation'], \
{'1N77_C':'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'})
def test_GrToInfo_invalid_data(self):
"""GrToInfo: correctly raises error when necessary """
invalid_headers = [['#=GRSS ..<<..>>..'],['#=GRSAxxxxxx']]
for h in invalid_headers:
self.assertRaises(RecordError, GrToInfo, h)
def test_StockholmStockholmParser_strict_missing_fields(self):
"""MinimalStockholmParser: toggle strict functions w/ missing fields"""
# strict = True
self.assertRaises(RecordError,list,\
MinimalStockholmParser(self._fake_record_no_sequences))
# strict = False
# no header shouldn't be a problem
headers, aln, struct = \
list(MinimalStockholmParser(self._fake_record_no_headers,\
strict=False))[0]
self.assertEqual((headers,aln.todict(),str(struct)), \
({'GS':[],'GF':[],'GR':[],\
'GC':['#=GC SS_cons ............>>>']},\
{'Z11765.1/1-89':'GGUC'},'............>>>'))
# should get empty on missing sequence or missing structure
self.assertEqual(list(MinimalStockholmParser(\
self._fake_record_no_sequences,\
strict=False)), [])
def test_MinimalStockholmParser_strict_invalid_sequence(self):
"""MinimalStockholmParser: toggle strict functions w/ invalid seq
"""
#strict = True
self.assertRaises(RecordError,list,\
MinimalStockholmParser(self._fake_record_bad_sequence_1))
# strict = False
# you expect to get back as much information as possible, also
# half records or sequences
result = MinimalStockholmParser(\
self._fake_record_bad_sequence_1,strict=False)
self.assertEqual(len(list(MinimalStockholmParser(\
self._fake_record_bad_sequence_1,strict=False))[0][1].NamedSeqs), 3)
def test_StockholmParser_strict_invalid_structure(self):
"""StockholmParser: toggle strict functions w/ invalid structure
"""
#strict = True
self.assertRaises(RecordError,list,\
StockholmParser(self._fake_record_bad_structure_1))
# strict = False
self.assertEqual(list(MinimalStockholmParser(\
self._fake_record_bad_structure_1,strict=False))[0][2],None)
def test_MinimalStockholmParser_w_valid_data(self):
"""MinimalStockholmParser: integrity of output """
# Some ugly constructions here, but this is what the output of
# parsing fake_two_records should be
headers = ['#=GF AC RF00014','#=GF AU Mifsud W']
sequences =\
{'U17136.1/898-984':\
''.join(['AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA',\
'AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU']),\
'M15749.1/155-239':\
''.join(['AACGCAUCGGAUUUCCCGGUGUAACGAA-UUUUCAAGUGCUUCUUGCAUU',\
'AGCAAGUUUGAUCCCGACUCCUG-CGAGUCGGGAUUU']),\
'AF090431.1/222-139':\
''.join(['CUCACAUCAGAUUUCCUGGUGUAACGAA-UUUUCAAGUGCUUCUUGCAUA',\
'AGCAAGUUUGAUCCCGACCCGU--AGGGCCGGGAUUU'])}
structure = WussStructure(''.join(\
['...<<<<<<<.....>>>>>>>....................<<<<<...',\
'.>>>>>....<<<<<<<<<<.....>>>>>>>>>>..']))
data = []
for r in MinimalStockholmParser(self._fake_two_records, strict=False):
data.append(r)
self.assertEqual(\
(data[0][0]['GF'],data[0][1].todict(),\
str(data[0][2])),(headers,sequences,structure))
assert isinstance(data[0][1],Alignment)
# This line tests that invalid entries are ignored when strict=False
# Note, there are two records in self._fake_two_records, but 2nd is
# invalid
self.assertEqual(len(data),1)
def test_StockholmFinder(self):
"""StockholmFinder: integrity of output """
fake_record = ['a','//','b','b','//']
num_records = 0
data = []
for r in StockholmFinder(fake_record):
data.append(r)
num_records += 1
self.assertEqual(num_records, 2)
self.assertEqual(data[0], ['a','//'])
self.assertEqual(data[1], ['b','b','//'])
def test_StockholmParser(self):
"""StockholmParser: integrity of output """
expected_sequences =\
[''.join(['AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA',\
'AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU']),\
''.join(['AACGCAUCGGAUUUCCCGGUGUAACGAA-UUUUCAAGUGCUUCUUGCAUU',\
'AGCAAGUUUGAUCCCGACUCCUG-CGAGUCGGGAUUU']),\
''.join(['CUCACAUCAGAUUUCCUGGUGUAACGAA-UUUUCAAGUGCUUCUUGCAUA',\
'AGCAAGUUUGAUCCCGACCCGU--AGGGCCGGGAUUU'])]
expected_structure = ''.join(\
['...<<<<<<<.....>>>>>>>....................<<<<<...',\
'.>>>>>....<<<<<<<<<<.....>>>>>>>>>>..'])
for r in StockholmParser(self._fake_record):
headers = r.Info
sequences = r
structure = r.Info['Struct']
self.assertEqual(headers['GF']['AccessionNumber'], 'RF00014')
self.assertEqual(headers['GF']['Author'], 'Mifsud W')
self.assertEqualItems(sequences.values(), expected_sequences)
assert isinstance(sequences, Alignment)
self.assertEqual(structure, expected_structure)
assert isinstance(structure,WussStructure)
def test_StockholmParser_strict_missing_fields(self):
"""StockholmParser: toggle strict functions correctly """
# strict = True
self.assertRaises(RecordError,list,\
StockholmParser(self._fake_record_no_headers))
# strict = False
self.assertEqual(list(StockholmParser(self._fake_record_no_headers,\
strict=False)), [])
self.assertEqual(list(StockholmParser(self._fake_record_no_sequences,\
strict=False)), [])
def test_StockholmParser_strict_invalid_headers(self):
"""StockholmParser: functions when toggling strict record w/ bad header
"""
self.assertRaises(RecordError,list,\
StockholmParser(self._fake_record_bad_header_1))
self.assertRaises(RecordError,list,\
StockholmParser(self._fake_record_bad_header_2))
# strict = False
x = list(StockholmParser(self._fake_record_bad_header_1, strict=False))
obs = list(StockholmParser(self._fake_record_bad_header_1,\
strict=False))[0].Info.GF.keys()
self.assertEqual(len(obs),1)
obs = list(StockholmParser(self._fake_record_bad_header_2,\
strict=False))[0].Info.GF.keys()
self.assertEqual(len(obs),1)
def test_StockholmParser_strict_invalid_sequences(self):
"""StockholmParser: functions when toggling strict w/ record w/ bad seq
"""
self.assertRaises(RecordError,list,
MinimalStockholmParser(self._fake_record_bad_sequence_1))
# strict = False
# in 'False' mode you expect to get back as much as possible, also
# parts of sequences
self.assertEqual(len(list(StockholmParser(\
self._fake_record_bad_sequence_1,\
strict=False))[0].NamedSeqs), 3)
def test_StockholmParser_strict_invalid_structure(self):
"""StockholmParser: functions when toggling strict record w/ bad struct
"""
# strict
self.assertRaises(RecordError,list,\
StockholmParser(self._fake_record_bad_structure_2))
#not strict
self.assertEqual(list(StockholmParser(\
self._fake_record_bad_structure_2,\
strict=False)),[])
def test_StockholmParser_single_family(self):
"""StockholmParser: should work on a family in stockholm format"""
exp_header = {}
exp_aln = {'K02120.1/628-682':\
'AUGGGAAAUUCCCCCUCCUAUAACCCCCCCGCUGGUAUCUCCCCCUCAGACUGGC',\
'D00647.1/629-683':\
'AUGGGAAACUCCCCCUCCUAUAACCCCCCCGCUGGCAUCUCCCCCUCAGACUGGC'}
exp_struct = '<<<<<<.........>>>>>>.........<<<<<<.............>>>>>>'
aln = list(StockholmParser(self.single_family))[0]
h = aln.Info['GF']
a = aln
s = aln.Info['Struct']
self.assertEqual(h,exp_header)
self.assertEqual(a,exp_aln)
self.assertEqual(s,exp_struct)
# This is an altered version of some header info from Rfam.seed modified to
# incorporate different cases for testing
fake_headers = """#=GF AC RF00001
#=GF AU Griffiths-Jones SR
#=GF ID 5S_rRNA
#=GF RT 5S Ribosomal RNA Database.
#=GF DR URL; http://oberon.fvms.ugent.be:8080/rRNA/ssu/index.html;
#=GF DR URL; http://rdp.cme.msu.edu/html/;
#=GF CC This is a short
#=GF CC comment
#=GF SQ 606
#=GF PK not real"""
fake_gc_annotation = """#=GC SS_cons ..........<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
"""
fake_gs_annotation = """#=GS 1N77_C BP 0 70 cWW CC
#=GS 1N77_C BP 1 69 cWW CC
#=GS 1N77_C BP 2 68 cWW CC
#=GS 1N77_C BP 3 67 cWW CC
"""
fake_gr_annotation = """#=GR 1N77_C SS ..........<<<<<<<<<<.....>>>>>>>>>>..
#=GR 1N77_C RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
"""
fake_record_no_headers ="""Z11765.1/1-89 GGUC
#=GC SS_cons ............>>>
//"""
fake_record_no_sequences ="""#=GF AC RF00006
#=GC SS_cons ............>
//"""
fake_record_no_structure ="""#=GF AC RF00006
Z11765.1/1-89 GGUCAGC
//"""
fake_two_records ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//
#=GF AC RF00015
//"""
fake_record ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_header_1 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AUMifsudW
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_header_2 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GFAUMifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_sequence_1 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_structure_1 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons...<<<<<<<.....>>>>>>>....................<<<<<...
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
U17136.1/898-984 AGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUU
M15749.1/155-239 AGCAAGUUUGAUCCCGACUCCUG.CGAGUCGGGAUUU
AF090431.1/222-139 AGCAAGUUUGAUCCCGACCCGU..AGGGCCGGGAUUU
#=GC SS_cons .>>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
fake_record_bad_structure_2 ="""# STOCKHOLM 1.0
#=GF AC RF00014
#=GF AU Mifsud W
U17136.1/898-984 AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUA
M15749.1/155-239 AACGCAUCGGAUUUCCCGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUU
AF090431.1/222-139 CUCACAUCAGAUUUCCUGGUGUAACGAA.UUUUCAAGUGCUUCUUGCAUA
#=GC SS_cons ...<<<<<<<.....>>>>>>>....................<<<<>>>>....<<<<<<<<<<.....>>>>>>>>>>..
#=GC RF xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
//"""
single_family=\
"""K02120.1/628-682 AUGGGAAAUUCCCCCUCCUAUAACCCCCCCGCUGGUAUCUCCCCCUCAGA
D00647.1/629-683 AUGGGAAACUCCCCCUCCUAUAACCCCCCCGCUGGCAUCUCCCCCUCAGA
#=GC SS_cons <<<<<<.........>>>>>>.........<<<<<<.............>
K02120.1/628-682 CUGGC
D00647.1/629-683 CUGGC
#=GC SS_cons >>>>>
//"""
# Run tests if called from the command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_stride.py 000644 000765 000024 00000004522 12024702176 022462 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import os
try:
from cogent.util.unit_test import TestCase, main
from cogent.struct.selection import einput
from cogent.parse.pdb import PDBParser
from cogent.parse.stride import stride_parser
from cogent.app.stride import Stride, stride_xtra
except ImportError:
from zenpdb.cogent.util.unit_test import TestCase, main
from zenpdb.cogent.struct.selection import einput
from zenpdb.cogent.parse.pdb import PDBParser
from zenpdb.cogent.parse.stride import stride_parser
from zenpdb.cogent.app.stride import Stride, stride_xtra
__author__ = "Marcin Cieslik"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Development"
class StrideParseTest(TestCase):
"""Tests for Stride application controller."""
def setUp(self):
input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(input_file))
stride_app = Stride()
res = stride_app(self.input_structure)
self.lines = res['StdOut'].readlines()
def test_stride_parser(self):
"""tests if output is parsed fully"""
id_xtra = stride_parser(self.lines)
assert len(id_xtra) < len(self.input_structure[(0,)][('A',)]) + \
len(self.input_structure[(0,)][('B',)])
self.input_structure[(0,)][('A',)].remove_hetero()
self.input_structure[(0,)][('B',)].remove_hetero()
assert len(id_xtra) == len(self.input_structure[(0,)][('A',)]) + \
len(self.input_structure[(0,)][('B',)])
def test_stride_xtra(self):
"""tests if residues get annotated with parsed data."""
stride_xtra(self.input_structure)
self.assertEquals(\
self.input_structure[(0,)][('A',)][(('H_HOH', 138, ' '),)].xtra, {})
self.assertAlmostEquals(\
self.input_structure[(0,)][('A',)][(('ILE', 86, ' '),)].xtra['STRIDE_ASA'], 13.9)
self.input_structure[(0,)][('A',)].remove_hetero()
self.input_structure[(0,)][('B',)].remove_hetero()
all_residues = einput(self.input_structure, 'R')
a = all_residues.data_children('STRIDE_ASA', xtra=True, forgiving=False)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_structure.py 000755 000765 000024 00000002300 12024702176 023223 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for the pdb parser.
"""
from cogent.util.unit_test import TestCase, main
from cogent.core.entity import Structure
from cogent.parse.structure import FromFilenameStructureParser, FromFileStructureParser
__author__ = "Marcin Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Production"
class structuresTests(TestCase):
"""Tests of cogent.parse.structure UI functions."""
def test_FromFilenameStructureParser(self):
structure = FromFilenameStructureParser('data/1LJO.pdb', 'pdb')
self.assertRaises(TypeError, FromFilenameStructureParser, open('data/1LJO.pdb'), 'pdb')
assert isinstance(structure, Structure)
def test_FromFileStructureParser(self):
structure = FromFileStructureParser(open('data/1LJO.pdb'), 'pdb')
assert isinstance(structure, Structure)
self.assertRaises(TypeError, FromFileStructureParser, 'data/1LJO.pdb', 'pdb')
assert isinstance(structure, Structure)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_tinyseq.py 000644 000765 000024 00000003245 12024702176 022665 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from StringIO import StringIO
import xml.dom.minidom
from cogent.util.unit_test import TestCase, main
from cogent.parse.tinyseq import TinyseqParser
__author__ = "Matthew Wakefield"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Matthew Wakefield"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Matthew Wakefield"
__email__ = "wakefield@wehi.edu.au"
__status__ = "Production"
data = """
31322957
AY286018.1
9315
Macropus eugenii
Macropus eugenii medium wave-sensitive opsin 1 (OPN1MW) mRNA, complete cds
99
GGCAGGGAAAGGGAAGAAAGTAAAGGGGCCATGACACAGGCATGGGACCCTGCAGGGTTCTTGGCTTGGCGGCGGGACGAGAACGAGGAGACGACTCGG
"""
sample_seq = ">AY286018.1\nGGCAGGGAAAGGGAAGAAAGTAAAGGGGCCATGACACAGGCATGGGACCCTGCAGGGTTCTTGGCTTGGCGGCGGGACGAGAACGAGGAGACGACTCGG"
sample_annotations = '[genbank_id "AY286018.1" at [0:99]/99, organism "Macropus eugenii" at [0:99]/99]'
class ParseTinyseq(TestCase):
def test_parse(self):
for name,seq in [TinyseqParser(data).next(),TinyseqParser(xml.dom.minidom.parseString(data)).next()]:
self.assertEqual(name, 'AY286018.1')
self.assertEqual(sample_seq, seq.toFasta())
self.assertEqual(str(seq.annotations), sample_annotations)
pass
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_parse/test_tree.py 000644 000765 000024 00000021446 12024702176 022133 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for tree parsers.
"""
from cogent.parse.tree import DndParser, DndTokenizer, RecordError
from cogent.core.tree import PhyloNode
from cogent.util.unit_test import TestCase, main
#from cogent.parse.newick import parse_string, TreeParseError as RecordError
#def DndParser(data, NodeClass=PhyloNode, unescape_name=True):
# if not unescape_name:
# raise NotImplementedError
# def constructor(children, name, attribs):
# return NodeClass(Children = list(children or []), Name=name, Params=attribs)
# return parse_string(data, constructor)
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Peter Maxwell", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
sample = """
(
(
xyz:0.28124,
(
def:0.24498,
mno:0.03627)
:0.17710)
:0.04870,
abc:0.05925,
(
ghi:0.06914,
jkl:0.13776)
:0.09853);
"""
node_data_sample = """
(
(
xyz:0.28124,
(
def:0.24498,
mno:0.03627)
'A':0.17710)
B:0.04870,
abc:0.05925,
(
ghi:0.06914,
jkl:0.13776)
C:0.09853);
"""
minimal = "();"
no_names = "((,),(,));"
missing_tip_name = "((a,b),(c,));"
empty = '();'
single = '(abc:3);'
double = '(abc:3, def:4);'
onenest = '(abc:3, (def:4, ghi:5):6 );'
nodedata = '(abc:3, (def:4, ghi:5)jkl:6 );'
class DndTokenizerTests(TestCase):
"""Tests of the DndTokenizer factory function."""
def test_gdata(self):
"""DndTokenizer should work as expected on real data"""
exp = \
['(', '(', 'xyz', ':', '0.28124',',', '(', 'def', ':', '0.24498',\
',', 'mno', ':', '0.03627', ')', ':', '0.17710', ')', ':', '0.04870', \
',', 'abc', ':', '0.05925', ',', '(', 'ghi', ':', '0.06914', ',', \
'jkl', ':', '0.13776', ')', ':', '0.09853', ')', ';']
#split it up for debugging on an item-by-item basis
obs = list(DndTokenizer(sample))
self.assertEqual(len(obs), len(exp))
for i, j in zip(obs, exp):
self.assertEqual(i, j)
#try it all in one go
self.assertEqual(list(DndTokenizer(sample)), exp)
def test_nonames(self):
"""DndTokenizer should work as expected on trees with no names"""
exp = ['(','(',',',')',',','(',',',')',')',';']
obs = list(DndTokenizer(no_names))
self.assertEqual(obs, exp)
def test_missing_tip_name(self):
"""DndTokenizer should work as expected on trees with a missing name"""
exp = ['(','(','a',',','b',')',',','(','c',',',')',')',';']
obs = list(DndTokenizer(missing_tip_name))
self.assertEqual(obs, exp)
def test_minimal(self):
"""DndTokenizer should work as expected a minimal tree without names"""
exp = ['(',')',';']
obs = list(DndTokenizer(minimal))
self.assertEqual(obs, exp)
class DndParserTests(TestCase):
"""Tests of the DndParser factory function."""
def test_nonames(self):
"""DndParser should produce the correct tree when there are no names"""
obs = DndParser(no_names)
exp = PhyloNode()
exp.append(PhyloNode())
exp.append(PhyloNode())
exp.Children[0].append(PhyloNode())
exp.Children[0].append(PhyloNode())
exp.Children[1].append(PhyloNode())
exp.Children[1].append(PhyloNode())
self.assertEqual(str(obs), str(exp))
def test_minimal(self):
"""DndParser should produce the correct minimal tree"""
obs = DndParser(minimal)
exp = PhyloNode()
exp.append(PhyloNode())
self.assertEqual(str(obs), str(exp))
def test_missing_tip_name(self):
"""DndParser should produce the correct tree when missing a name"""
obs = DndParser(missing_tip_name)
exp = PhyloNode()
exp.append(PhyloNode())
exp.append(PhyloNode())
exp.Children[0].append(PhyloNode(Name='a'))
exp.Children[0].append(PhyloNode(Name='b'))
exp.Children[1].append(PhyloNode(Name='c'))
exp.Children[1].append(PhyloNode())
self.assertEqual(str(obs), str(exp))
def test_gsingle(self):
"""DndParser should produce a single-child PhyloNode on minimal data"""
t = DndParser(single)
self.assertEqual(len(t), 1)
child = t[0]
self.assertEqual(child.Name, 'abc')
self.assertEqual(child.Length, 3)
self.assertEqual(str(t), '(abc:3.0);')
def test_gdouble(self):
"""DndParser should produce a double-child PhyloNode from data"""
t = DndParser(double)
self.assertEqual(len(t), 2)
self.assertEqual(str(t), '(abc:3.0,def:4.0);')
def test_gonenest(self):
"""DndParser should work correctly with nested data"""
t = DndParser(onenest)
self.assertEqual(len(t), 2)
self.assertEqual(len(t[0]), 0) #first child is terminal
self.assertEqual(len(t[1]), 2) #second child has two children
self.assertEqual(str(t), '(abc:3.0,(def:4.0,ghi:5.0):6.0);')
def test_gnodedata(self):
"""DndParser should assign Name to internal nodes correctly"""
t = DndParser(nodedata)
self.assertEqual(len(t), 2)
self.assertEqual(len(t[0]), 0) #first child is terminal
self.assertEqual(len(t[1]), 2) #second child has two children
self.assertEqual(str(t), '(abc:3.0,(def:4.0,ghi:5.0)jkl:6.0);')
info_dict = {}
for node in t.traverse():
info_dict[node.Name] = node.Length
self.assertEqual(info_dict['abc'], 3.0)
self.assertEqual(info_dict['def'], 4.0)
self.assertEqual(info_dict['ghi'], 5.0)
self.assertEqual(info_dict['jkl'], 6.0)
def test_data(self):
"""DndParser should work as expected on real data"""
t = DndParser(sample)
self.assertEqual(str(t), '((xyz:0.28124,(def:0.24498,mno:0.03627):0.1771):0.0487,abc:0.05925,(ghi:0.06914,jkl:0.13776):0.09853);')
tdata = DndParser(node_data_sample, unescape_name=True)
self.assertEqual(str(tdata), "((xyz:0.28124,(def:0.24498,mno:0.03627)A:0.1771)B:0.0487,abc:0.05925,(ghi:0.06914,jkl:0.13776)C:0.09853);")
def test_gbad(self):
"""DndParser should fail if parens unbalanced"""
left = '((abc:3)'
right = '(abc:3))'
self.assertRaises(RecordError, DndParser, left)
self.assertRaises(RecordError, DndParser, right)
def test_DndParser(self):
"""DndParser tests"""
t_str = "(A_a,(B:1.0,C),'D_e':0.5)E;"
tree_unesc = DndParser(t_str, PhyloNode, unescape_name=True)
tree_esc = DndParser(t_str, PhyloNode, unescape_name=False)
self.assertEqual(tree_unesc.Name, 'E')
self.assertEqual(tree_unesc.Children[0].Name, 'A a')
self.assertEqual(tree_unesc.Children[1].Children[0].Name, 'B')
self.assertEqual(tree_unesc.Children[1].Children[0].Length, 1.0)
self.assertEqual(tree_unesc.Children[1].Children[1].Name, 'C')
self.assertEqual(tree_unesc.Children[2].Name, 'D_e')
self.assertEqual(tree_unesc.Children[2].Length, 0.5)
self.assertEqual(tree_esc.Name, 'E')
self.assertEqual(tree_esc.Children[0].Name, 'A_a')
self.assertEqual(tree_esc.Children[1].Children[0].Name, 'B')
self.assertEqual(tree_esc.Children[1].Children[0].Length, 1.0)
self.assertEqual(tree_esc.Children[1].Children[1].Name, 'C')
self.assertEqual(tree_esc.Children[2].Name, "'D_e'")
self.assertEqual(tree_esc.Children[2].Length, 0.5)
reload_test = tree_esc.getNewick(with_distances=True, \
escape_name=False)
obs = DndParser(reload_test, unescape_name=False)
self.assertEqual(obs.getNewick(with_distances=True), \
tree_esc.getNewick(with_distances=True))
reload_test = tree_unesc.getNewick(with_distances=True, \
escape_name=False)
obs = DndParser(reload_test, unescape_name=False)
self.assertEqual(obs.getNewick(with_distances=True), \
tree_unesc.getNewick(with_distances=True))
class PhyloNodeTests(TestCase):
"""Check that PhyloNode works the way I think"""
def test_gops(self):
"""Basic PhyloNode operations should work as expected"""
p = PhyloNode()
self.assertEqual(str(p), ';')
p.Name = 'abc'
self.assertEqual(str(p), 'abc;')
p.Length = 3
self.assertEqual(str(p), 'abc:3;') #don't suppress branch from root
q = PhyloNode()
p.append(q)
self.assertEqual(str(p), '()abc:3;')
r = PhyloNode()
q.append(r)
self.assertEqual(str(p), '(())abc:3;')
r.Name = 'xyz'
self.assertEqual(str(p), '((xyz))abc:3;')
q.Length = 2
self.assertEqual(str(p), '((xyz):2)abc:3;')
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_parse/test_unigene.py 000644 000765 000024 00000014504 12024702176 022623 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for unigene-specific classes
"""
from cogent.parse.unigene import _read_sts, _read_expression, UniGeneSeqRecord,\
UniGeneProtSimRecord, _read_seq, LinesToUniGene
from cogent.parse.record_finder import GbFinder
from cogent.util.unit_test import TestCase, main
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class unigeneTests(TestCase):
"""Tests toplevel functions."""
def test_read_sts(self):
"""_read_sts should perform correct conversions"""
self.assertEqual(_read_sts('ACC=RH128467 UNISTS=211775\n'), \
{'ACC':'RH128467', 'UNISTS':'211775'})
def test_read_expression(self):
"""_read_expression should perform correct conversions"""
self.assertEqual(_read_expression(\
'embryo ; whole body ; mammary gland ; brain\n'),
['embryo', 'whole body', 'mammary gland', 'brain'])
def test_read_seq(self):
"""_read_seq should perform correct conversions"""
#reset the found fields, since we can't guarantee order of test
#execution and it's persistent class data
UniGeneSeqRecord.found_fields = {}
self.assertEqual(_read_seq('ACC=BC025044.1\n'), \
UniGeneSeqRecord({'ACC':'BC025044.1'}))
self.assertEqual(_read_seq(\
"ACC=AI842963.1; NID=g5477176; CLONE=UI-M-AO1-aem-f-10-0-UI; END=3'; LID=1944; SEQTYPE=EST; TRACE=158501677\n"), \
UniGeneSeqRecord({ 'ACC':'AI842963.1','NID':'g5477176',
'CLONE':'UI-M-AO1-aem-f-10-0-UI', 'END':"3'",
'LID':'1944', 'SEQTYPE':'EST',
'TRACE':'158501677'}) )
def test_LinesToUniGene(self):
"""LinesToUniGene should give expected results on sample data"""
fake_file = \
"""ID Mm.1
TITLE S100 calcium binder
GENE S100a10
CYTOBAND 3 41.7 cM
LOCUSLINK 20194
EXPRESS embryo ; whole body ; mammary gland ; brain
CHROMOSOME 3
STS ACC=RH128467 UNISTS=211775
STS ACC=M16465 UNISTS= 178878
PROTSIM ORG=Homo sapiens; PROTGI=107251; PROTID=pir:JC1139; PCT=91; ALN=97
PROTSIM ORG=Mus musculus; PROTGI=116487; PROTID=sp:P08207; PCT=100; ALN=97
PROTSIM ORG=Rattus norvegicus; PROTGI=116489; PROTID=sp:P05943; PCT=94; ALN=94
SCOUNT 5
SEQUENCE ACC=BC025044.1; NID=g19263549; PID=g19263550; SEQTYPE=mRNA
SEQUENCE ACC=AA471893.1; NID=g2199884; CLONE=IMAGE:872193; END=5'; LID=539; SEQTYPE=EST
SEQUENCE ACC=AI842963.1; NID=g5477176; CLONE=UI-M-AO1-aem-f-10-0-UI; END=3'; LID=1944; SEQTYPE=EST; TRACE=158501677
SEQUENCE ACC=CB595147.1; NID=g29513003; CLONE=IMAGE:30300703; END=5'; LID=12885; MGC=6677832; SEQTYPE=EST
SEQUENCE ACC=BY144053.1; NID=g26280109; CLONE=L930184D22; END=5'; LID=12267; SEQTYPE=EST
//
ID Mm.5
TITLE homeo box A10
GENE Hoxa10
CYTOBAND 6 26.33 cM
LOCUSLINK 15395
EXPRESS kidney ; colon ; mammary gland
CHROMOSOME 6
PROTSIM ORG=Caenorhabditis elegans; PROTGI=7510074; PROTID=pir:T31611; PCT=30; ALN=326
SCOUNT 1
SEQUENCE ACC=AW990320.1; NID=g8185938; CLONE=IMAGE:1513482; END=5'; LID=1043; SEQTYPE=EST; TRACE=94472873
//
"""
records = list(GbFinder(fake_file.split('\n')))
self.assertEqual(len(records), 2)
first, second = map(LinesToUniGene, records)
self.assertEqual(first.ID, 'Mm.1')
self.assertEqual(first.TITLE, 'S100 calcium binder')
self.assertEqual(first.GENE, 'S100a10')
self.assertEqual(first.CYTOBAND, '3 41.7 cM')
self.assertEqual(first.CHROMOSOME, '3')
self.assertEqual(first.LOCUSLINK, 20194)
self.assertEqual(first.EXPRESS, ['embryo', 'whole body', \
'mammary gland', 'brain'])
self.assertEqual(first.STS, [{'ACC':'RH128467','UNISTS':'211775'},
{'ACC':'M16465', 'UNISTS':'178878'}])
exp_prot_sim = map(UniGeneProtSimRecord, [
{'ORG':'Homo sapiens','PROTGI':'107251',
'PROTID':'pir:JC1139','PCT':'91','ALN':'97'},
{'ORG':'Mus musculus','PROTGI':'116487',
'PROTID':'sp:P08207','PCT':'100','ALN':'97'},
{'ORG':'Rattus norvegicus','PROTGI':'116489',
'PROTID':'sp:P05943','PCT':'94','ALN':'94'},])
for obs, exp in zip(first.PROTSIM, exp_prot_sim):
self.assertEqual(obs, exp)
self.assertEqual(first.SCOUNT, 5)
exp_seqs = map(UniGeneSeqRecord, [
{'ACC':'BC025044.1', 'NID':'g19263549','PID':'g19263550',
'SEQTYPE':'mRNA'},
{'ACC':'AA471893.1','NID':'g2199884','END':"5'",
'CLONE':'IMAGE:872193','LID':'539', 'SEQTYPE':'EST'},
{'ACC':'AI842963.1','NID':'g5477176',
'CLONE':'UI-M-AO1-aem-f-10-0-UI','END':"3'",'LID':'1944',
'SEQTYPE':'EST','TRACE':'158501677'},
{'ACC':'CB595147.1','NID':'g29513003',
'CLONE':'IMAGE:30300703','END':"5'",'LID':'12885',
'MGC':'6677832', 'SEQTYPE':'EST'},
{'ACC':'BY144053.1','NID':'g26280109',
'CLONE':'L930184D22','END':"5'",'LID':'12267',
'SEQTYPE':'EST'}])
for obs, exp in zip(first.SEQUENCE, exp_seqs):
self.assertEqual(obs, exp)
self.assertEqual(second.ID, 'Mm.5')
self.assertEqual(second.TITLE, 'homeo box A10')
self.assertEqual(second.GENE, 'Hoxa10')
self.assertEqual(second.CYTOBAND, '6 26.33 cM')
self.assertEqual(second.LOCUSLINK, 15395)
self.assertEqual(second.EXPRESS,['kidney','colon','mammary gland'])
self.assertEqual(second.CHROMOSOME, '6')
self.assertEqual(second.PROTSIM, map(UniGeneProtSimRecord, [
{'ORG':'Caenorhabditis elegans', 'PROTGI':'7510074',
'PROTID':'pir:T31611','PCT':'30',
'ALN':'326'}]))
self.assertEqual(second.SCOUNT, 1)
self.assertEqual(second.STS, [])
self.assertEqual(second.SEQUENCE, map(UniGeneSeqRecord, [
{'ACC':'AW990320.1','NID':'g8185938',
'CLONE':'IMAGE:1513482','END':"5'",'LID':'1043',
'SEQTYPE':'EST','TRACE':'94472873'}]))
#test that the synonym mapping works OK
self.assertEqual(second.SequenceIds[0].NucleotideId, 'g8185938')
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_motif/__init__.py 000644 000765 000024 00000000453 12024702176 021673 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_util']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_motif/test_util.py 000644 000765 000024 00000050546 12024702176 022160 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
#file cogent_tests/motif/test_util.py
from __future__ import division
from cogent.util.unit_test import TestCase, main
from cogent.motif.util import Location, ModuleInstance, Module, Motif,\
MotifResults, MotifFormatter, html_color_to_rgb
from cogent.core.moltype import ASCII
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Production"
class LocationTests(TestCase):
"""Tests of Location class for holding module location.
"""
def setUp(self):
"""Setup for Location tests."""
self.location_no_end = Location('seq1',1)
self.locations = [
Location('seq1',1,5),
Location('seq2',3,54),
Location('seq1',5,3),
Location('seq1',2,3),
Location('seq2',54,2),
Location('seq0',1,3),
]
self.locations_sorted = [
Location('seq0',1,3),
Location('seq1',1,5),
Location('seq1',5,3),
Location('seq1',2,3),
Location('seq2',3,54),
Location('seq2',54,2),
]
def test_init_no_end(self):
"""__init__ should properly initialize Location object"""
self.assertEqual(self.location_no_end.SeqId, 'seq1')
self.assertEqual(self.location_no_end.Start, 1)
self.assertEqual(self.location_no_end.End, 2)
def test_init_complete(self):
"""__init__ should properly initialize Location object"""
self.assertEqual(self.locations[0].SeqId, 'seq1')
self.assertEqual(self.locations[0].Start, 1)
self.assertEqual(self.locations[0].End, 5)
def test_cmp(self):
"""Location object should sort properly with __cmp__ overwritten."""
self.locations.sort()
self.assertEqual(self.locations, self.locations_sorted)
class ModuleInstanceTests(TestCase):
"""Tests for ModuleInstance class."""
def setUp(self):
"""Setup function for ModuleInstance tests."""
self.sequences = [
'accucua',
'caucguu',
'accucua',
'cgacucg',
'cgaucag',
'cuguacc',
'cgcauca',
]
self.locations = [
Location('seq0',1,3),
Location('seq1',2,3),
Location('seq1',1,5),
Location('seq1',5,3),
Location('seq2',3,54),
Location('seq2',54,2),
Location('seq3',4,0),
]
self.Pvalues = [
.1,
.002,
.0000000003,
.6,
.0094,
.6,
.00201,
]
self.Evalues = [
.006,
.02,
.9,
.0200000001,
.09,
.0000003,
.900001,
]
self.modules_no_e = []
for i in xrange(7):
self.modules_no_e.append(ModuleInstance(self.sequences[i],
self.locations[i],
self.Pvalues[i]))
self.modules_p_and_e = []
for i in xrange(7):
self.modules_p_and_e.append(ModuleInstance(self.sequences[i],
self.locations[i],
self.Pvalues[i],
self.Evalues[i]))
self.modules_no_e_sorted = [
ModuleInstance(self.sequences[2],self.locations[2],self.Pvalues[2]),
ModuleInstance(self.sequences[1],self.locations[1],self.Pvalues[1]),
ModuleInstance(self.sequences[6],self.locations[6],self.Pvalues[6]),
ModuleInstance(self.sequences[4],self.locations[4],self.Pvalues[4]),
ModuleInstance(self.sequences[0],self.locations[0],self.Pvalues[0]),
ModuleInstance(self.sequences[3],self.locations[3],self.Pvalues[3]),
ModuleInstance(self.sequences[5],self.locations[5],self.Pvalues[5]),
]
self.modules_p_and_e_sorted = [
ModuleInstance(self.sequences[2],self.locations[2],self.Pvalues[2]),
ModuleInstance(self.sequences[1],self.locations[1],self.Pvalues[1]),
ModuleInstance(self.sequences[6],self.locations[6],self.Pvalues[6]),
ModuleInstance(self.sequences[4],self.locations[4],self.Pvalues[4]),
ModuleInstance(self.sequences[0],self.locations[0],self.Pvalues[0]),
ModuleInstance(self.sequences[5],self.locations[5],self.Pvalues[5]),
ModuleInstance(self.sequences[3],self.locations[3],self.Pvalues[3]),
]
def test_init_no_p_e_values(self):
"""Init should properly initialize ModuleInstance objects."""
module1 = ModuleInstance(self.sequences[0], self.locations[0])
module2 = ModuleInstance(self.sequences[1], self.locations[1])
self.assertEqual(module1.Sequence, 'accucua')
self.assertEqual(module1.Location.SeqId, 'seq0')
self.assertEqual(module2.Sequence, 'caucguu')
self.assertEqual(module2.Location.SeqId, 'seq1')
def test_init_no_e_values(self):
"""Init should properly initialize ModuleInstance objects."""
self.modules_no_e.sort()
self.assertEqual(self.modules_no_e, self.modules_no_e_sorted)
def test_len(self):
"""len() should return correct length of the ModuleInstance sequence."""
for module in self.modules_no_e:
self.assertEqual(len(module), 7)
def test_str(self):
"""str() should return the correct string for each ModuleInstance."""
for module, seq in zip(self.modules_no_e, self.sequences):
self.assertEqual(str(module), seq)
def test_cmp(self):
"""ModuleInstances should sort properly with __cmp__ overwritten."""
self.modules_no_e.sort()
self.modules_p_and_e.sort()
self.assertEqual(map(str,self.modules_no_e),
map(str,self.modules_no_e_sorted))
self.assertEqual(map(str,self.modules_p_and_e),
map(str,self.modules_p_and_e_sorted))
class ModuleTests(TestCase):
"""Tests for Module class."""
def setUp(self):
"""SetUp for Module class tests."""
self.sequences = [
'accucua',
'caucguu',
'accucua',
'cgacucg',
'cgaucag',
'cuguacc',
'cgcauca',
]
self.locations = [
Location('seq0',1,3),
Location('seq1',2,3),
Location('seq1',1,5),
Location('seq1',5,3),
Location('seq2',3,54),
Location('seq2',54,2),
Location('seq3',4,0),
]
self.Pvalues = [
.1,
.002,
.0000000003,
.6,
.0094,
.6,
.00201,
]
self.Evalues = [
.006,
.02,
.9,
.0200000001,
.09,
.0000003,
.900001,
]
self.modules_no_e = []
for i in xrange(7):
self.modules_no_e.append(ModuleInstance(self.sequences[i],
self.locations[i],
self.Pvalues[i]))
self.modules_p_and_e = []
for i in xrange(7):
self.modules_p_and_e.append(ModuleInstance(self.sequences[i],
self.locations[i],
self.Pvalues[i],
self.Evalues[i]))
self.module_no_template = Module(
{
(self.modules_no_e[0].Location.SeqId,
self.modules_no_e[0].Location.Start):self.modules_no_e[0],
(self.modules_no_e[1].Location.SeqId,
self.modules_no_e[1].Location.Start):self.modules_no_e[1],
(self.modules_no_e[2].Location.SeqId,
self.modules_no_e[2].Location.Start):self.modules_no_e[2],
(self.modules_no_e[3].Location.SeqId,
self.modules_no_e[3].Location.Start):self.modules_no_e[3],
(self.modules_no_e[4].Location.SeqId,
self.modules_no_e[4].Location.Start):self.modules_no_e[4],
(self.modules_no_e[5].Location.SeqId,
self.modules_no_e[5].Location.Start):self.modules_no_e[5],
(self.modules_no_e[6].Location.SeqId,
self.modules_no_e[6].Location.Start):self.modules_no_e[6],
}
)
self.module_with_template = Module(
{
(self.modules_no_e[0].Location.SeqId,
self.modules_no_e[0].Location.Start):self.modules_no_e[0],
(self.modules_no_e[1].Location.SeqId,
self.modules_no_e[1].Location.Start):self.modules_no_e[1],
(self.modules_no_e[2].Location.SeqId,
self.modules_no_e[2].Location.Start):self.modules_no_e[2],
(self.modules_no_e[3].Location.SeqId,
self.modules_no_e[3].Location.Start):self.modules_no_e[3],
(self.modules_no_e[4].Location.SeqId,
self.modules_no_e[4].Location.Start):self.modules_no_e[4],
(self.modules_no_e[5].Location.SeqId,
self.modules_no_e[5].Location.Start):self.modules_no_e[5],
(self.modules_no_e[6].Location.SeqId,
self.modules_no_e[6].Location.Start):self.modules_no_e[6],
},
Template = 'accgucg'
)
def test_init(self):
"""Init should properly initialize Module object."""
module = Module(data={(self.modules_no_e[0].Location.SeqId,
self.modules_no_e[0].Location.Start): \
self.modules_no_e[0]})
self.assertEqual(module.Template, None)
self.assertEqual(module.Alphabet, ASCII.Alphabet)
self.assertEqual(module.Pvalue, None)
self.assertEqual(module.Evalue, None)
self.assertEqual(module.keys(),[('seq0',1)])
self.assertEqual(module.values(),[ModuleInstance(self.sequences[0],
self.locations[0],
self.Pvalues[0])])
def test_cmp(self):
"""Module objects should sort properly with __cmp__ overwritten."""
pvals_sorted = [3e-010, 0.002,
0.0020100000000000001,
0.0094000000000000004,
0.10000000000000001,
0.59999999999999998,
0.59999999999999998]
evals_sorted = [.9,
.02,
.900001,
.09,
.006,
.0000003,
.0200000001,
]
modules = []
for instance, pvalue, evalue in zip(self.modules_no_e,
self.Pvalues,
self.Evalues):
modules.append(Module({(instance.Location.SeqId,
instance.Location.Start):instance},
Pvalue=pvalue,
Evalue=evalue))
modules.sort()
for ans, p, e in zip(modules, pvals_sorted, evals_sorted):
self.assertEqual(ans.Pvalue, p)
self.assertEqual(ans.Evalue, e)
def test_LocationDict(self):
"""LocationDict should return correct dictionary of locations."""
location_dict_ans = {
'seq0':[1],
'seq1':[1,2,3],
'seq2':[2,3],
'seq3':[0],
}
location_dict = self.module_no_template.LocationDict
self.assertEqual(location_dict,location_dict_ans)
class MotifTests(TestCase):
"""Tests for Motif class."""
def test_init(self):
"""Init should properly initialize Motif object."""
module = Module({
('a',3): ModuleInstance('guc', Location('a',3,5)),
('b',3): ModuleInstance('guc', Location('b',3,5)),
('c',8): ModuleInstance('guc', Location('c',8,10)),
})
m = Motif(module)
self.assertEqual(m.Modules,[module])
self.assertEqual(m.Info,None)
class MotifResultsTests(TestCase):
"""Tests for MotifResults class."""
def test_init(self):
"""Init should properly initialize MotifResults object."""
module = Module({
('a',3): ModuleInstance('guc', Location('a',3,5)),
('b',3): ModuleInstance('guc', Location('b',3,5)),
('c',8): ModuleInstance('guc', Location('c',8,10)),
})
motif = Motif([module])
results = {'key1':'value1','key2':'value2'}
parameters = {'parameter1':1,'parameter2':2}
mr = MotifResults([module],[motif],results,parameters)
self.assertEqual(mr.Modules,[module])
self.assertEqual(mr.Motifs,[motif])
self.assertEqual(mr.Results,results)
self.assertEqual(mr.parameter1,1)
self.assertEqual(mr.parameter2,2)
class UtilTests(TestCase):
"""Tests for utility functions."""
def test_html_color_to_rgb(self):
"""Tests for html_to_color_rgb."""
html_colors = ['#FF0000','#00FF00','#0000FF','545454']
rgb_colors = [(1.0,0.0,0.0),(0.0,1.0,0.0),(0.0,0.0,1.0),\
(0.32941176470588235,0.32941176470588235,0.32941176470588235)]
for html, rgb in zip(html_colors, rgb_colors):
self.assertEqual(html_color_to_rgb(html),rgb)
def test_make_remap_dict(self):
"""Tests for make_remap_dict."""
pass
class MotifFormatterTests(TestCase):
"""Tests for MotifFormatter class."""
def setUp(self):
"""SetUp for MotifFormatter class tests."""
self.sequences = [
'accucua',
'caucguu',
'accucua',
'cgacucg',
'cgaucag',
'cuguacc',
'cgcauca',
]
self.locations = [
Location('seq0',1,3),
Location('seq1',2,3),
Location('seq1',1,5),
Location('seq1',5,3),
Location('seq2',3,54),
Location('seq2',54,2),
Location('seq3',4,0),
]
self.Pvalues = [
.1,
.002,
.0000000003,
.6,
.0094,
.6,
.00201,
]
self.Evalues = [
.006,
.02,
.9,
.0200000001,
.09,
.0000003,
.900001,
]
self.modules_no_e = []
for i in xrange(7):
self.modules_no_e.append(ModuleInstance(self.sequences[i],
self.locations[i],
self.Pvalues[i]))
self.module_with_template = Module(
{
(self.modules_no_e[0].Location.SeqId,
self.modules_no_e[0].Location.Start):self.modules_no_e[0],
(self.modules_no_e[1].Location.SeqId,
self.modules_no_e[1].Location.Start):self.modules_no_e[1],
(self.modules_no_e[2].Location.SeqId,
self.modules_no_e[2].Location.Start):self.modules_no_e[2],
(self.modules_no_e[3].Location.SeqId,
self.modules_no_e[3].Location.Start):self.modules_no_e[3],
(self.modules_no_e[4].Location.SeqId,
self.modules_no_e[4].Location.Start):self.modules_no_e[4],
(self.modules_no_e[5].Location.SeqId,
self.modules_no_e[5].Location.Start):self.modules_no_e[5],
(self.modules_no_e[6].Location.SeqId,
self.modules_no_e[6].Location.Start):self.modules_no_e[6],
},
Template = 'accgucg', ID='1'
)
self.modules_with_ids =\
[Module({
('a',3): ModuleInstance('guc', Location('a',3,5)),
('b',3): ModuleInstance('guc', Location('b',3,5)),
('c',8): ModuleInstance('guc', Location('c',8,10)),
},ID='1'),
Module({
('a',7): ModuleInstance('cca', Location('a',7,9)),
('b',7): ModuleInstance('cca', Location('b',7,9)),
('c',11): ModuleInstance('cca',Location('c',11,13)),
},ID='2'),
Module({
('a',10): ModuleInstance('gca',Location('a',10,12)),
('b',10): ModuleInstance('gca',Location('b',10,12)),
('c',14): ModuleInstance('gca',Location('c',14,12)),
},ID='3'),
Module({
('a',13): ModuleInstance('ggg',Location('a',13,15)),
('b',13): ModuleInstance('ggg',Location('b',13,15)),
('c',18): ModuleInstance('ggg',Location('c',18,20)),
},ID='4'),
]
self.motifs_with_ids = map(Motif,self.modules_with_ids)
self.motif_results = MotifResults(Modules=self.modules_with_ids,\
Motifs=self.motifs_with_ids)
self.color_map = {'1':"""background-color: #0000FF; ; font-family: 'Courier New', Courier""",
'2':"""background-color: #FFFF00; ; font-family: 'Courier New', Courier""",
'3':"""background-color: #00FFFF; ; font-family: 'Courier New', Courier""",
'4':"""background-color: #FF00FF; ; font-family: 'Courier New', Courier""",
}
self.color_map_rgb = {
'color_1':(0.0,0.0,1.0),
'color_2':(1.0,1.0,0.0),
'color_3':(0.0,1.0,1.0),
'color_4':(1.0,0.0,1.0),
}
def test_getColorMapS0(self):
"""tests for getColorMapS0"""
mf = MotifFormatter()
module_ids = ['1','2','3','4']
self.assertEqual(mf.getColorMapS0(module_ids),self.color_map)
def test_getColorMap(self):
"""tests for getColorMap"""
mf = MotifFormatter()
self.assertEqual(mf.getColorMap(self.motif_results),self.color_map)
def test_getColorMapRgb(self):
"""tests for getColorMapRgb"""
mf = MotifFormatter()
self.assertEqual(mf.getColorMapRgb(self.motif_results),\
self.color_map_rgb)
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_maths/__init__.py 000644 000765 000024 00000001154 12024702176 021670 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_fit_function',
'test_geometry',
'test_matrix',
'test_matrix_logarithm',
'test_optimisers',
'test_stats',
'test_unifrac',
'test_spatial']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Peter Maxwell", "Catherine Lozupone",
"Gavin Huttley", "Sandra Smit", "Marcin Cieslik", "Antonio Gonzalez Pena"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_maths/test_distance_transform.py 000644 000765 000024 00000052105 12024702176 025057 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for distance_transform.py functions.
"""
from __future__ import division
from cogent.util.unit_test import TestCase, main
from cogent.maths.distance_transform import *
from numpy import array, sqrt, shape, ones, diag
__author__ = "Justin Kuczynski"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Justin Kuczynski",
"Zongzhi Liu",
"Greg Caporaso"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Justin Kuczynski"
__email__ = "justinak@gmail.com"
__status__ = "Prototype"
class functionTests(TestCase):
"""Tests of top-level functions."""
def setUp(self):
self.mat_test = asmatrix([[10, 10, 20],
[10, 15, 10],
[15, 5, 5]], 'float')
self.emptyarray = array([], 'd')
self.mtx1 = array([[1, 3],
[0.0, 23.1]],'d')
self.dense1 = array([[1, 3],
[5, 2],
[0.1, 22]],'d')
self.zeromtx = array([[ 0.0, 0.0, 0.0],
[ 0.0, 0.0 , 0.0],
[ 0.0, 0.0, 0.0 ],
[ 0.0, 0.0, 0.0 ]],'d')
self.sparse1 = array([[ 0.0, 0.0, 5.33],
[ 0.0, 0.0 , 0.4],
[ 1.0, 0.0, 0.0 ],
[ 0.0, 0.0, 0.0 ]],'d')
self.input_binary_dist_otu_gain1 = array([[2,1,0,0],
[1,0,0,1],
[0,0,3,0],
[0,0,0,1]])
def get_sym_mtx_from_uptri(self, mtx):
"""helper fn, only for square matrices"""
numrows, numcols = shape(mtx)
for i in range(numrows):
for j in range(i):
if i==j:
break
mtx[i,j] = mtx[j,i] # j < i, so rowxxx;yyy
ignore
aaa;bbb
"""
self.assertEqual(list(taxon_lineage_extractor(lines.splitlines())),
[['xxx','yyy'],['aaa','bbb']])
def test_parse_taxonomy_using_elementtree_xml_parse(self):
"""parse_taxonomy_using_elementtree_xml_parse should return taxonomy associated information"""
g = EUtils(db='taxonomy', rettype='xml', retmode='xml')
ids = '28901[taxid]'
fh = StringIO()
fh.write(g[ids].read())
fh.seek(0)
data = parse_taxonomy_using_elementtree_xml_parse(fh)[0]
obs = (data['Lineage'],data['TaxId'],data['ScientificName'],\
data['Rank'])
exp = ('cellular organisms; Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacteriales; Enterobacteriaceae; Salmonella',\
'28901','Salmonella enterica','species')
self.assertEqual(obs,exp)
def test_taxon_ids_to_lineages(self):
"""taxon_ids_to_lineages should return lineages from taxon ids"""
taxon_ids = ['10090', '9606']
result = [self.mouse_taxonomy, self.human_taxonomy]
self.assertEqualItems(list(taxon_ids_to_lineages(taxon_ids)), result)
# def test_taxon_ids_to_names(self):
# """taxon_ids_to_names should return names from taxon ids"""
# taxon_ids = ['10090', '9606']
# result = set(['Mus musculus', 'Homo sapiens'])
# self.assertEqual(set(taxon_ids_to_names(taxon_ids)), result)
def test_taxon_ids_to_names(self):
"""taxon_ids_to_names should return names from taxon ids"""
taxon_ids = ['10090', '9606']
result = set(['Mus musculus', 'Homo sapiens'])
self.assertEqual(set(taxon_ids_to_names(taxon_ids)), result)
def test_taxon_ids_to_names_and_lineages(self):
"""taxon_ids_to_names should return names/lineages from taxon ids"""
taxon_ids = ['10090', '9606']
exp = [('10090', 'Mus musculus', '; '.join(self.mouse_taxonomy)),
('9606', 'Homo sapiens', '; '.join(self.human_taxonomy))]
obs = list(taxon_ids_to_names_and_lineages(taxon_ids))
self.assertEqualItems(obs, exp)
def test_get_unique_lineages(self):
"""get_unique_lineages should return all lineages from a query"""
result = get_unique_lineages('angiotensin[ti] AND rodents[orgn]')
assert tuple(self.mouse_taxonomy) in result
assert len(result) > 2
def test_get_unique_taxa(self):
"""get_unique_taxa should return all taxa from a query"""
result = get_unique_taxa('angiotensin[ti] AND primate[orgn]')
assert 'Homo sapiens' in result
assert len(result) > 2
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_db/test_pdb.py 000644 000765 000024 00000001470 12024702176 021207 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of data retrieval from PDB."""
from cogent.util.unit_test import TestCase, main
from cogent.db.pdb import Pdb
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class PdbTests(TestCase):
"""Tests of the Pdb class."""
def test_simple_get(self):
"""Simple access of an item should work."""
rec = Pdb()
result = rec['1RMN'].read()
assert result.startswith('HEADER')
assert result.rstrip().endswith('END') #note: trailing whitespace
assert 'HAMMERHEAD RIBOZYME' in result
assert '1RMN' in result
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_db/test_rfam.py 000644 000765 000024 00000001351 12024702176 021365 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of data retrieval from PDB."""
from cogent.util.unit_test import TestCase, main
from cogent.db.rfam import Rfam
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight","Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class RfamTests(TestCase):
"""Tests of the Rfam class."""
def test_simple_get(self):
"""Simple access of an item should work."""
rec = Rfam()
result = rec['rf00100'].read()
assert result.startswith('# STOCKHOLM')
assert 'AM773434.1/1-304' in result
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_db/test_util.py 000644 000765 000024 00000005534 12024702176 021424 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of the db utility functions and classes."""
from cogent.util.unit_test import TestCase, main
from cogent.db.util import UrlGetter, expand_slice, last_nondigit_index,make_lists_of_expanded_slices_of_set_size,make_lists_of_accessions_of_set_size
from os import remove
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class db_util_tests(TestCase):
"""Tests of top-level functions."""
def test_last_nondigit_index(self):
"""last_nondigit_index should return i such that s[i:] is numeric"""
ldi = last_nondigit_index
self.assertEqual(ldi('3'), 0)
self.assertEqual(ldi('345'), 0)
self.assertEqual(ldi('a34'), 1)
self.assertEqual(ldi('abc234'), 3)
self.assertEqual(ldi('abcd'), None)
def test_expand_slice(self):
"""expand_slice should get accession range"""
self.assertEqual(expand_slice(slice('AF1001','AF1003')), \
['AF1001','AF1002','AF1003'])
#can't expand if accession prefixes
self.assertRaises(TypeError, expand_slice, slice('AF100:','AG1002'))
#should keep leading zeros
self.assertEqual(expand_slice(slice('AF0001','AF0003')), \
['AF0001','AF0002','AF0003'])
def test_make_lists_of_expanded_slices_of_set_size(self):
"""make_lists_of_expanded_slices_of_set_size: should return a
list of lists"""
expected_list = ['HM780503 HM780504 HM780505','HM780506']
observed = make_lists_of_expanded_slices_of_set_size(slice('HM780503','HM780506'),size_limit=3)
self.assertEqual(observed,expected_list)
def make_lists_of_accessions_of_set_size(self):
"""make_lists_of_expanded_slices_of_set_size: should return a
list of lists"""
expected_list = ['HM780503 HM780506 HM780660 HM780780']
observed = make_lists_of_accessions_of_set_size(['HM780503','HM780506', 'HM780660', 'HM780780'],size_limit=3)
self.assertEqual(observed,expected_list)
class UrlGetterTests(TestCase):
"""Tests of the UrlGetter class"""
def retrieval_test(self):
"""Urlgetter should init, read and retrieve"""
class Google(UrlGetter):
BaseUrl='http://www.google.com'
g = Google()
#test URL construction
self.assertEqual(str(g), 'http://www.google.com')
#test reading
text = g.read()
assert 'Google ' in text
#test file getting
fname = '/tmp/google_test'
g.retrieve(fname)
g_file = open(fname)
g_text = g_file.read()
self.assertEqual(g_text, text)
g_text.close()
remove(fname)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_db/test_ensembl/__init__.py 000644 000765 000024 00000000637 12024702176 023632 0 ustar 00jrideout staff 000000 000000 __all__ = ['test_assembly', 'test_compara', 'test_database',
'test_feature_level', 'test_genome', 'test_host', 'test_species']
__author__ = "Gavin Huttley, Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
PyCogent-1.5.3/tests/test_db/test_ensembl/test_assembly.py 000644 000765 000024 00000011576 12024702176 024755 0 ustar 00jrideout staff 000000 000000 import os
from cogent.util.unit_test import TestCase, main
from cogent.db.ensembl.host import HostAccount, get_ensembl_account
from cogent.db.ensembl.assembly import Coordinate, CoordSystem, \
get_coord_conversion
from cogent.db.ensembl.genome import Genome
__author__ = "Gavin Huttley, Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
Release = 68
if 'ENSEMBL_ACCOUNT' in os.environ:
args = os.environ['ENSEMBL_ACCOUNT'].split()
host, username, password = args[0:3]
kwargs = {}
if len(args) > 3:
kwargs['port'] = int(args[3])
account = HostAccount(host, username, password, **kwargs)
else:
account = get_ensembl_account(release=Release)
human = Genome(Species = 'human', Release=Release, account=account)
platypus = Genome(Species = 'platypus', Release=Release, account=account)
class TestLocation(TestCase):
def test_init(self):
human_loc = Coordinate(CoordName='x', Start=1000, End=10000, Strand=-1,
genome = human)
# TODO: complete test for platpus
self.assertEqual(human_loc.CoordType, 'chromosome')
self.assertEqual(human_loc.CoordName, 'x')
self.assertEqual(human_loc.Start, 1000)
self.assertEqual(human_loc.End, 10000)
self.assertEqual(human_loc.Strand, -1)
self.assertEqual(human_loc.Species, "Homo sapiens")
self.assertEqual(human_loc.seq_region_id, 27516)
def test_get_coord_conversion(self):
"""should correctly map between different coordinate levels"""
# not really testing the contig coordinates are correct
CoordName, Start, End, Strand = '1', 1000, 1000000, 1
human_loc = Coordinate(CoordName = CoordName, Start = Start, End = End,
Strand = Strand, genome = human)
results = get_coord_conversion(human_loc, 'contig', human.CoreDb)
for result in results:
self.assertTrue(result[0].CoordName == CoordName)
self.assertTrue(result[0].Start >= Start)
self.assertTrue(result[0].End <= End)
self.assertTrue(result[0].Strand == Strand)
def test_coord_shift(self):
"""adding coordinates should produce correct results"""
CoordName, Start, End, Strand = '1', 1000, 1000000, 1
loc1 = Coordinate(CoordName = CoordName, Start = Start, End = End,
Strand = Strand, genome = human)
for shift in [100, -100]:
loc2 = loc1.shifted(shift)
self.assertEqual(loc2.Start, loc1.Start+shift)
self.assertEqual(loc2.End, loc1.End+shift)
self.assertEqual(id(loc1.genome), id(loc2.genome))
self.assertNotEqual(id(loc1), id(loc2))
def test_coord_resize(self):
"""resizing should work"""
CoordName, Start, End, Strand = '1', 1000, 1000000, 1
loc1 = Coordinate(CoordName = CoordName, Start = Start, End = End,
Strand = Strand, genome = human)
front_shift = -100
back_shift = 100
loc2 = loc1.resized(front_shift, back_shift)
self.assertEqual(len(loc2), len(loc1)+200)
self.assertEqual(loc2.Start, loc1.Start+front_shift)
self.assertEqual(loc2.End, loc1.End+back_shift)
self.assertEqual(loc1.Strand, loc2.Strand)
def test_adopted(self):
"""coordinate should correctly adopt seq_region_id properties of
provided coordinate"""
CoordName, Start, End, Strand = '1', 1000, 1000000, 1
c1 = Coordinate(CoordName = CoordName, Start = Start, End = End,
Strand = Strand, genome = human)
CoordName, Start, End, Strand = '2', 2000, 2000000, 1
c2 = Coordinate(CoordName = CoordName, Start = Start, End = End,
Strand = Strand, genome = human)
c3 = c1.adopted(c2)
self.assertEqual(c3.CoordName, c2.CoordName)
self.assertEqual(c3.CoordType, c2.CoordType)
self.assertEqual(c3.seq_region_id, c2.seq_region_id)
self.assertEqual(c3.Start, c1.Start)
self.assertEqual(c3.End, c1.End)
self.assertEqual(c3.Strand, c1.Strand)
c3 = c1.adopted(c2, shift = 100)
self.assertEqual(c3.Start, c1.Start+100)
self.assertEqual(c3.End, c1.End+100)
class TestCoordSystem(TestCase):
def test_call(self):
human_chrom = CoordSystem('chromosome', core_db = human.CoreDb,
species = 'human')
human_contig = CoordSystem(1, species = 'human')
self.assertEqual(human_chrom.coord_system_id, 2)
self.assertEqual(human_contig.name, 'contig')
self.assertEqual(human_contig.attr, 'default_version, sequence_level')
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_db/test_ensembl/test_compara.py 000644 000765 000024 00000025354 12024702176 024557 0 ustar 00jrideout staff 000000 000000 from __future__ import division
import os
from cogent.util.unit_test import TestCase, main
from cogent.db.ensembl.host import HostAccount, get_ensembl_account
from cogent.db.ensembl.compara import Compara
__author__ = "Gavin Huttley, Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
Release = 68
if 'ENSEMBL_ACCOUNT' in os.environ:
args = os.environ['ENSEMBL_ACCOUNT'].split()
host, username, password = args[0:3]
kwargs = {}
if len(args) > 3:
kwargs['port'] = int(args[3])
account = HostAccount(host, username, password, **kwargs)
else:
account = get_ensembl_account(release=Release)
def calc_slope(x1, y1, x2, y2):
"""computes the slope from two coordinate sets, assigning a delta of 1
when values are identical"""
delta_y = y2-y1
delta_x = x2-x1
delta_y = [delta_y, 1][delta_y == 0]
delta_x = [delta_x, 1][delta_x == 0]
return delta_y/delta_x
class ComparaTestBase(TestCase):
comp = Compara(['human', 'mouse', 'rat', 'platypus'], Release=Release,
account=account)
class TestCompara(ComparaTestBase):
def test_query_genome(self):
"""compara should attach valid genome attributes by common name"""
brca2 = self.comp.Mouse.getGeneByStableId("ENSMUSG00000041147")
self.assertEquals(brca2.Symbol.lower(), 'brca2')
def test_get_related_genes(self):
"""should correctly return the related gene regions from each genome"""
brca2 = self.comp.Mouse.getGeneByStableId("ENSMUSG00000041147")
Orthologs = self.comp.getRelatedGenes(gene_region=brca2,
Relationship="ortholog_one2one")
self.assertEquals("ortholog_one2one", Orthologs.Relationships[0])
def test_get_related_genes2(self):
"""should handle case where gene is absent from one of the genomes"""
clec2d = self.comp.Mouse.getGeneByStableId(
StableId='ENSMUSG00000030157')
orthologs = self.comp.getRelatedGenes(gene_region=clec2d,
Relationship='ortholog_one2many')
self.assertTrue(len(orthologs.Members) < 4)
def test_get_collection(self):
brca2 = self.comp.Human.getGeneByStableId(StableId="ENSG00000139618")
Orthologs = self.comp.getRelatedGenes(gene_region=brca2,
Relationship="ortholog_one2one")
collection = Orthologs.getSeqCollection()
self.assertTrue(len(collection.Seqs[0])> 1000)
def test_getting_alignment(self):
mid = "ENSMUSG00000041147"
brca2 = self.comp.Mouse.getGeneByStableId(StableId=mid)
result = list(self.comp.getSyntenicRegions(region=brca2,
align_method='PECAN', align_clade='vertebrates'))[0]
aln = result.getAlignment(feature_types='gene')
self.assertTrue(len(aln) > 1000)
def test_generate_method_clade_data(self):
"""should correctly determine the align_method align_clade options for
a group of species"""
# we should correctly infer the method_species_links, which is a
# cogent.util.Table instance
self.assertTrue(self.comp.method_species_links.Shape > (0,0))
def test_no_method_clade_data(self):
"""generate a Table with no rows if no alignment data"""
compara = Compara(['S.cerevisiae'], Release=Release, account=account)
self.assertEquals(compara.method_species_links.Shape[0], 0)
def test_get_syntenic_returns_nothing(self):
"""should correctly return None for a SyntenicRegion with golden-path
assembly gap"""
Start = 100000
End = Start + 100000
related = list(self.comp.getSyntenicRegions(Species='mouse',
CoordName='1', Start=Start, End=End,
align_method='PECAN', align_clade='vertebrates'))
self.assertEquals(related, [])
def test_get_species_set(self):
"""should return the correct set of species"""
expect = set(['Homo sapiens', 'Ornithorhynchus anatinus',
'Mus musculus', 'Rattus norvegicus'])
brca2 = self.comp.Human.getGeneByStableId(StableId="ENSG00000139618")
Orthologs = self.comp.getRelatedGenes(gene_region=brca2,
Relationship="ortholog_one2one")
self.assertEquals(Orthologs.getSpeciesSet(), expect)
def test_pool_connection(self):
"""excercising ability to specify pool connection"""
dog = Compara(['chimp', 'dog'], Release=Release, account=account,
pool_recycle=1000)
class TestSyntenicRegions(TestCase):
comp = Compara(['human', 'chimp', 'macaque'], account=account,
Release=Release)
def test_correct_alignments(self):
"""should return the correct alignments"""
# following cases have a mixture of strand between ref seq and others
coords_expected = [
[{'CoordName': 4, 'End': 78099, 'Species': 'human', 'Start': 77999, 'Strand':-1},
{'Homo sapiens:chromosome:4:77999-78099:-1':
'ATGTAAATCAAAACCAAAGTCTGCATTTATTTGCGGAAAGAGATGCTACATGTTCAAAGATAAATATGGAACATTTTTTAAAAGCATTCATGACTTAGAA',
'Macaca mulatta:chromosome:1:3891064-3891163:1':
'ATGTCAATCAAAACCAAAGTCTGTATTTATTTGCAGAAAGAGATACTGCATGTTCAAAGATAAATATGGAAC-TTTTTAAAAAGCATTAATGACTTATAC',
'Pan troglodytes:chromosome:4:102056-102156:-1':
'ATGTAAATCAAAACCAAAGTCTGCATTTATTTGCGGAAAGAGATGCTACATGTTCAAAGATAAATATGGAACATTTTTAAAAAGCATTCATGACTTAGAA'}],
[{'CoordName': 18, 'End': 213739, 'Species': 'human', 'Start': 213639, 'Strand':-1},
{'Homo sapiens:chromosome:18:213639-213739:-1':
'ATAAGCATTTCCCTTTAGGGCTCTAAGATGAGGTCATCATCGTTTTTAATCCTGAAGAAGGGCTACTGAGTGAGTGCAGATTATTCGGTAAACACT----CTTA',
'Macaca mulatta:chromosome:18:13858303-13858397:1':
'------GTTTCCCTTTAGGGCTCTAAGATGAGGTCATCATTGTTTTTAATCCTGAAGAAGGGCTACTGA----GTGCAGATTATTCTGTAAATGTGCTTACTTG',
'Pan troglodytes:chromosome:18:16601082-16601182:1':
'ATAAGCATTTCCCTTTAGGGCTCTAAGATGAGGTCATCATCGTTTTTAATCCTGAAGAAGGGCTACTGA----GTGCAGATTATTCTGTAAACACTCACTCTTA'}],
[{'CoordName': 5, 'End': 204974, 'Species': 'human', 'Start': 204874, 'Strand':1},
{'Homo sapiens:chromosome:5:204874-204974:1':
'AACACTTGGTATTT----CCCCTTTATGGAGTGAGAGAGATCTTTAAAATATAAACCCTTGATAATATAATATTACTACTTCCTATTA---CCTGTTATGCAGTTCT',
'Macaca mulatta:chromosome:6:1297736-1297840:-1':
'AACTCTTGGTGTTTCCTTCCCCTTTATGG---GAGAGAGATCTTTAAAATAAAAAACCTTGATAATATAATATTACTACTTTCTATTATCATCTGTTATGCAGTTCT',
'Pan troglodytes:chromosome:5:335911-336011:1':
'AACACTTGGTAGTT----CCCCTTTATGGAGTGAGAGAGATCTTTAAAATATAAACCCTTGATAATATAATATTACTACTTTCTATTA---CCTGTTATGCAGTTCT'}],
[{'CoordName': 18, 'End': 203270, 'Species': 'human', 'Start': 203170, 'Strand':-1},
{'Homo sapiens:chromosome:18:203170-203270:-1':
'GGAATAATGAAAGCAATTGTGAGTTAGCAATTACCTTCAAAGAATTACATTTCTTATACAAAGTAAAGTTCATTACTAACCTTAAGAACTTTGGCATTCA',
'Pan troglodytes:chromosome:18:16611584-16611684:1':
'GGAATAATGAAAGCAATTGTAAGTTAGCAATTACCTTCAAAGAATTACATTTCTTATACAAAGTAAAGTTCATTACTAACCTTAAGAACTTTGGCATTCA'}],
[{'CoordName': 2, 'End': 46445, 'Species': 'human', 'Start': 46345, 'Strand':-1},
{'Homo sapiens:chromosome:2:46345-46445:-1':
'CTACCACTCGAGCGCGTCTCCGCTGGACCCGGAACCCCGGTCGGTCCATTCCCCGCGAAGATGCGCGCCCTGGCGGCCCTGAGCGCGCCCCCGAACGAGC',
'Macaca mulatta:chromosome:13:43921-44021:-1':
'CTGCCACTCCAGCGCGTCTCCGCTGCACCCGGAGCGCCGGCCGGTCCATTCCCCGCGAGGATGCGCGCCCTGGCGGCCCTGAACACGTCGGCGAGAGAGC',
'Pan troglodytes:chromosome:2a:36792-36892:-1':
'CTACCACTCGAGCGCGTCTCCGCTGGACCCGGAACCCCAGTCGGTCCATTCCCCGCGAAGATGCGCGCCCTGGCGGCCCTGAACGCGCCCCCGAACGAGC'}],
[{'CoordName': 18, 'End': 268049, 'Species': 'human', 'Start': 267949, 'Strand':-1},
{'Homo sapiens:chromosome:18:267949-268049:-1':
'GCGCAGTGGCGGGCACGCGCAGCCGAGAAGATGTCTCCGACGCCGCCGCTCTTCAGTTTGCCCGAAGCGCGGACGCGGTTTACGGTGAGCTGTAGAGGGG',
'Macaca mulatta:chromosome:18:13805604-13805703:1':
'GCGCAG-GGCGGGCACGCGCAGCCGAGAAGATGTCTCCGACGCCGCCGCTCTTCAGTTTGCCCGAAGCGCGGACGCGGTTTACGGTGAGCTGTAGGCGGG',
'Pan troglodytes:chromosome:18:16546800-16546900:1':
'GCGCAGTGGCGGGCACGCGCAGCCGAGAAGATGTCTCCGACGCCGCCGCTCTTCAGTTTGCCCGAAGCGCGGACGCGGTTTACGGTGAGCTGTAGCGGGG'}],
[{'CoordName': 16, 'End': 107443, 'Species': 'human', 'Start': 107343, 'Strand':-1},
{'Homo sapiens:chromosome:16:107343-107443:-1':
'AAGAAGCAAACAGGTTTATTTTATACAGTGGGCCAGGCCGTGGGTCTGCCATGTGACTAGGGCATTTGGACCTAGGGAGAGGTCAGTCTCAGGCCAAGTA',
'Pan troglodytes:chromosome:16:48943-49032:-1':
'AAGAAGCAAACAGGTTTATTTTATACACTGGGCCAGGCCGTGGGTCTGCCATGTGACTAGGGAATTTGGACC-----------CAGTCTCAGGCCAAGTA'}]
]
# print self.comp.method_species_links
for coord, expect in coords_expected[1:]:
syntenic = list(
self.comp.getSyntenicRegions(method_clade_id=548, **coord))[0]
# check the slope computed from the expected and returned
# coordinates is ~ 1
got_names = dict([(n.split(':')[0], n.split(':')) for n in syntenic.getAlignment().Names])
exp_names = dict([(n.split(':')[0], n.split(':')) for n in expect.keys()])
for species in exp_names:
exp_chrom = exp_names[species][2]
got_chrom = got_names[species][2]
self.assertEquals(exp_chrom.lower(), got_chrom.lower())
exp_start, exp_end = map(int, exp_names[species][3].split('-'))
got_start, got_end = map(int, got_names[species][3].split('-'))
slope = calc_slope(exp_start, exp_end, got_start, got_end)
self.assertFloatEqual(abs(slope), 1.0, eps=1e-3)
def test_failing_region(self):
"""should correctly handle queries where multiple Ensembl have
genome block associations for multiple coord systems"""
gene = self.comp.Human.getGeneByStableId(StableId='ENSG00000188554')
# this should simply not raise any exceptions
syntenic_regions = list(self.comp.getSyntenicRegions(region=gene,
align_method='PECAN',
align_clade='vertebrates'))
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_db/test_ensembl/test_database.py 000644 000765 000024 00000007404 12024702176 024675 0 ustar 00jrideout staff 000000 000000 import os
from cogent.util.unit_test import TestCase, main
from cogent.db.ensembl.host import HostAccount, get_ensembl_account
from cogent.db.ensembl.database import Database
__author__ = "Gavin Huttley, Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
Release = 68
if 'ENSEMBL_ACCOUNT' in os.environ:
args = os.environ['ENSEMBL_ACCOUNT'].split()
host, username, password = args[0:3]
kwargs = {}
if len(args) > 3:
kwargs['port'] = int(args[3])
account = HostAccount(host, username, password, **kwargs)
else:
account = get_ensembl_account(release=Release)
class TestDatabase(TestCase):
def test_connect(self):
human = Database(account=account, release=Release,
species='human', db_type='core')
gene = human.getTable('gene')
def test_get_distinct(self):
"""should return list of strings"""
db = Database(account=account, release=Release,
species='human', db_type='variation')
tn, tc = 'variation_feature', 'consequence_types'
expected = set(('3_prime_UTR_variant', 'splice_acceptor_variant',
'5_prime_UTR_variant'))
got = db.getDistinct(tn, tc)
self.assertNotEquals(set(got) & expected, set())
db = Database(account=account, release=Release,
species='human', db_type='core')
tn, tc = 'gene', 'biotype'
expected = set(['protein_coding', 'pseudogene', 'processed_transcript',
'Mt_tRNA', 'Mt_rRNA', 'IG_V_gene', 'IG_J_gene',
'IG_C_gene', 'IG_D_gene', 'miRNA', 'misc_RNA', 'snoRNA', 'snRNA', 'rRNA'])
got = set(db.getDistinct(tn, tc))
self.assertNotEquals(set(got) & expected, set())
db = Database(account=account, release=Release, db_type='compara')
got = set(db.getDistinct('homology', 'description'))
expected = set(['apparent_ortholog_one2one', 'ortholog_many2many',
'ortholog_one2many', 'ortholog_one2one', 'within_species_paralog'])
self.assertEquals(len(got&expected), len(expected))
def test_get_table_row_counts(self):
"""should return correct row counts for some tables"""
expect = {'homo_sapiens_core_68_37.analysis': 61L,
'homo_sapiens_core_68_37.seq_region': 55616L,
'homo_sapiens_core_68_37.assembly': 102090L,
'homo_sapiens_core_68_37.qtl': 0L}
human = Database(account=account, release=Release,
species='human', db_type='core')
table_names = [n.split('.')[1] for n in expect]
got = dict(human.getTablesRowCount(table_names).getRawData())
for dbname in expect:
self.assertTrue(got[dbname] >= expect[dbname])
def test_table_has_column(self):
"""return correct values for whether a Table has a column"""
account = get_ensembl_account(release=Release)
var61 = Database(account=account, release=61, species='human',
db_type='variation')
var62 = Database(account=account, release=62, species='human',
db_type='variation')
self.assertTrue(var61.tableHasColumn('transcript_variation',
'peptide_allele_string'))
self.assertFalse(var61.tableHasColumn('transcript_variation',
'pep_allele_string'))
self.assertTrue(var62.tableHasColumn('transcript_variation',
'pep_allele_string'))
self.assertFalse(var62.tableHasColumn('transcript_variation',
'peptide_allele_string'))
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_db/test_ensembl/test_feature_level.py 000644 000765 000024 00000006171 12024702176 025753 0 ustar 00jrideout staff 000000 000000 import os
from cogent import DNA
from cogent.util.unit_test import TestCase, main
from cogent.db.ensembl.host import HostAccount, get_ensembl_account
from cogent.db.ensembl.genome import Genome
from cogent.db.ensembl.assembly import CoordSystem, Coordinate, get_coord_conversion
from cogent.db.ensembl.feature_level import FeatureCoordLevels
__author__ = "Gavin Huttley, Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
Release = 68
if 'ENSEMBL_ACCOUNT' in os.environ:
args = os.environ['ENSEMBL_ACCOUNT'].split()
host, username, password = args[0:3]
kwargs = {}
if len(args) > 3:
kwargs['port'] = int(args[3])
account = HostAccount(host, username, password, **kwargs)
else:
account = get_ensembl_account(release=Release)
class TestFeatureCoordLevels(TestCase):
def setUp(self):
self.chicken = Genome(Species='chicken', Release=Release,
account=account)
def test_feature_levels(self):
ChickenFeatureLevels = FeatureCoordLevels('chicken')
chicken_feature_levels = ChickenFeatureLevels(
feature_types=['gene', 'cpg', 'est'],
core_db=self.chicken.CoreDb,
otherfeature_db=self.chicken.OtherFeaturesDb)
self.assertEquals(chicken_feature_levels['repeat'].levels, ['contig'])
self.assertEquals(set(chicken_feature_levels['cpg'].levels),\
set(['contig', 'supercontig', 'chromosome']))
def test_repeat(self):
# use chicken genome as it need to do conversion
# chicken coordinate correspondent toRefSeq human IL2A region
coord = dict(CoordName=9, Start=23817146, End=23818935)
region = self.chicken.getRegion(**coord)
# repeat is recorded at contig level, strand is 0
repeats = region.getFeatures(feature_types = 'repeat')
expect = [("9", 23817293, 23817321), ("9", 23817803, 23817812),
("9", 23817963, 23817972)]
obs = []
for repeat in repeats:
loc = repeat.Location
obs.append((loc.CoordName, loc.Start, loc.End))
self.assertEquals(set(obs), set(expect))
def test_cpg(self):
# contain 3 CpG island recorded at chromosome level
coord1 = dict(CoordName=26, Start=110000, End=190000)
cpgs1 = self.chicken.getFeatures(feature_types = 'cpg', **coord1)
exp = [("26", 116969, 117955), ("26", 139769, 140694),
("26", 184546, 185881)]
obs = []
for cpg in cpgs1:
loc = cpg.Location
obs.append((loc.CoordName, loc.Start, loc.End))
self.assertEquals(set(exp), set(obs))
# test cpg features record at supercontig level:
coord2 = dict(CoordName='Un_random', Start=29434117, End=29439117)
cpgs2 = self.chicken.getFeatures(feature_types='cpg', **coord2)
self.assertEquals(len(list(cpgs2)), 1)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_db/test_ensembl/test_genome.py 000644 000765 000024 00000076673 12024702176 024421 0 ustar 00jrideout staff 000000 000000 import os
from cogent import DNA
from cogent.util.unit_test import TestCase, main
from cogent.db.ensembl.host import HostAccount, get_ensembl_account
from cogent.db.ensembl.util import convert_strand
from cogent.db.ensembl.genome import Genome
from cogent.db.ensembl.sequence import _assemble_seq
from cogent.db.ensembl.util import asserted_one
__author__ = "Gavin Huttley, Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
Release = 67
if 'ENSEMBL_ACCOUNT' in os.environ:
args = os.environ['ENSEMBL_ACCOUNT'].split()
host, username, password = args[0:3]
kwargs = {}
if len(args) > 3:
kwargs['port'] = int(args[3])
account = HostAccount(host, username, password, **kwargs)
else:
account = get_ensembl_account(release=Release)
class GenomeTestBase(TestCase):
human = Genome(Species="human", Release=Release, account=account)
mouse = Genome(Species="mouse", Release=Release, account=account)
rat = Genome(Species="rat", Release=Release, account=account)
macaq = Genome(Species="macaque", Release=Release, account=account)
gorilla = Genome(Species="gorilla", Release=Release, account=account)
brca2 = human.getGeneByStableId(StableId="ENSG00000139618")
class TestGenome(GenomeTestBase):
def test_other_features(self):
"""should correctly return record for ENSESTG00000035043"""
est = self.human.getEstMatching(StableId='ENSESTG00000035043')
direct = list(est)[0]
ests = self.human.getFeatures(feature_types='est', CoordName=8,
Start=121470000, End=121600000)
stable_ids = [est.StableId for est in ests]
self.assertContains(stable_ids, direct.StableId)
def test_genome_comparison(self):
"""different genome instances with same CoreDb connection are equal"""
h2 = Genome(Species='human', Release=Release, account=account)
self.assertEquals(self.human, h2)
def test_make_location(self):
"""should correctly make a location for an entire chromosome"""
loc = self.human.makeLocation(CoordName=1)
self.assertEquals(len(loc), 249250621)
def test_get_region(self):
"""should return a generic region that extracts correct sequence"""
chrom = 1
Start = 11137
End = Start+20
region = self.human.getRegion(CoordName=chrom, Start=Start, End=End,
ensembl_coord=True)
self.assertEquals(region.Location.Start, Start-1)
self.assertEquals(region.Location.End, End)
self.assertEquals(region.Location.CoordName, str(chrom))
self.assertEquals(region.Location.CoordType, 'chromosome')
self.assertEquals(region.Seq, 'ACCTCAGTAATCCGAAAAGCC')
def test_get_assembly_exception_region(self):
"""should return correct sequence for region with an assembly
exception"""
##old:chrY:57767412-57767433; New: chrY:59358024-59358045
region = self.human.getRegion(CoordName = "Y", Start = 59358024,
End = 59358045, Strand = 1, ensembl_coord = True)
self.assertEquals(str(region.Seq), 'CGAGGACGACTGGGAATCCTAG')
def test_no_assembly(self):
"""return N's for coordinates with no assembly"""
krat = Genome('Kangaroo rat', Release=58)
Start=24385
End=Start+100
region = krat.getRegion(CoordName='scaffold_13754', Start=Start,
End=End)
self.assertEquals(str(region.Seq), 'N' * (End-Start))
def test_getting_annotated_seq(self):
"""a region should return a sequence with the correct annotation"""
new_loc = self.brca2.Location.resized(-100, 100)
region = self.human.getRegion(region=new_loc)
annot_seq = region.getAnnotatedSeq(feature_types='gene')
gene_annots = annot_seq.getAnnotationsMatching('gene')
self.assertEquals(gene_annots[0].Name, self.brca2.Symbol)
def test_correct_feature_type_id_cache(self):
"""should obtain the feature type identifiers without failure"""
self.assertNotEquals(self.human._feature_type_ids.CpGisland, None)
def test_strand_conversion(self):
"""should consistently convert strand info"""
self.assertEquals(convert_strand(None), 1)
self.assertEquals(convert_strand(-1), -1)
self.assertEquals(convert_strand(1), 1)
self.assertEquals(convert_strand('-'), -1)
self.assertEquals(convert_strand('+'), 1)
self.assertEquals(convert_strand(-1.0), -1)
self.assertEquals(convert_strand(1.0), 1)
def test_pool_connection(self):
"""excercising ability to specify pool connection"""
dog = Genome(Species="dog", Release=Release, account=account,
pool_recycle=1000)
def test_gorilla(self):
"""should correctly return a gorilla gene"""
self.gorilla = Genome(Species="gorilla", Release=Release, account=account)
gene = self.gorilla.getGeneByStableId('ENSGGOG00000005730')
self.assertEquals(str(gene.Seq[:10]), 'TGGGAGTCCA')
def test_diff_strand_contig_chrom(self):
"""get correct sequence when contig and chromosome strands differ"""
gene = self.gorilla.getGeneByStableId('ENSGGOG00000001953')
cds = gene.CanonicalTranscript.Cds
self.assertEquals(str(cds), 'ATGGCCCAGGATCTCAGCGAGAAGGACCTGTTGAAGATG'
'GAGGTGGAGCAGCTGAAGAAAGAAGTGAAAAACACAAGAATTCCGATTTCCAAAGCGGGAAAGGAAAT'
'CAAAGAGTACGTGGAGGCCCAAGCAGGAAACGATCCTTTTCTCAAAGGCATCCCTGAGGACAAGAATC'
'CCTTCAAGGAGAAAGGTGGCTGTCTGATAAGCTGA')
def test_get_distinct_biotype(self):
"""Genome instance getDistinct should work on all genomes"""
for genome in self.gorilla, self.human, self.mouse, self.rat, self.macaq:
biotypes = genome.getDistinct('biotype')
class TestGene(GenomeTestBase):
def _eval_brca2(self, brca2):
"""tests all attributes correctly created"""
self.assertEquals(brca2.Symbol.lower(), 'brca2')
self.assertEquals(brca2.StableId, 'ENSG00000139618')
self.assertEquals(brca2.BioType.lower(), 'protein_coding')
self.assertContains(brca2.Description.lower(), 'breast cancer')
self.assertEquals(brca2.Status, 'KNOWN')
self.assertEquals(brca2.CanonicalTranscript.StableId,
'ENST00000380152')
# note length can change between genome builds
self.assertGreaterThan(len(brca2), 83700)
transcript = brca2.getMember('ENST00000380152')
self.assertEquals(transcript.getCdsLength(),len(transcript.Cds))
def test_get_genes_by_stable_id(self):
"""if get gene by stable_id, attributes should be correctly
constructed"""
self._eval_brca2(self.brca2)
def test_get_exons(self):
"""transcript should return correct exons for brca2"""
transcript = self.brca2.getMember('ENST00000380152')
self.assertEquals(len(transcript.TranslatedExons), 26)
self.assertEquals(len(transcript.Cds), 3419*3)
self.assertEquals(len(transcript.ProteinSeq), 3418)
def test_translated_exons(self):
"""should correctly translate a gene with 2 exons but 1st exon
transcribed"""
gene = self.mouse.getGeneByStableId(StableId='ENSMUSG00000036136')
transcript = gene.getMember('ENSMUST00000041133')
self.assertTrue(len(transcript.ProteinSeq) > 0)
# now one on the - strand
gene = self.mouse.getGeneByStableId(StableId='ENSMUSG00000045912')
transcript = gene.Transcripts[0]
self.assertTrue(len(transcript.ProteinSeq) > 0)
def test_failed_ensembl_annotation(self):
"""we demonstrate a failed annotation by ensembl"""
# I'm including this to demonstrate that Ensembl coords are
# complex. This case has a macaque gene which we correctly
# infer the CDS boundaries for according to Ensembl, but the CDS
# length is not divisible by 3.
gene = self.macaq.getGeneByStableId(StableId='ENSMMUG00000001551')
transcript = gene.getMember('ENSMMUT00000002194')
# the following works because we enforce the length being divisble by 3
# in producing ProteinSeq
prot_seq = transcript.ProteinSeq
# BUT if you work off the Cds you will need to slice the CDS to be
# divisible by 3 to get the same protein sequence
l = transcript.getCdsLength()
trunc_cds = transcript.Cds[: l - (l % 3)]
prot_seq = trunc_cds.getTranslation()
self.assertEquals(str(prot_seq),
'MPSSPLRVAVVCSSNQNRSMEAHNILSKRGFSVRSFGTGTHVKLPGPAPDKPNVYDFKTT'\
'YDQMYNDLLRKDKELYTQNGILHMLDRNKRIKPRPERFQNCKDLFDLILTCEERVY')
def test_exon_phases(self):
"""correctly identify phase for an exon"""
stable_id = 'ENSG00000171408'
gene = self.human.getGeneByStableId(StableId=stable_id)
exon1 = gene.Transcripts[1].Exons[0]
# first two bases of codon missing
self.assertEquals(exon1.PhaseStart, 2)
# last two bases of codon missing
self.assertEquals(exon1.PhaseEnd, 1)
# can translate the sequence if we take those into account
seq = exon1.Seq[1:-1].getTranslation()
self.assertEquals(str(seq), 'HMLSKVGMWDFDIFLFDRLTN')
def test_cds_from_outofphase(self):
"""return a translatable Cds sequence from out-of-phase start"""
# canonical transcript phase end_phase
# ENSG00000111729 ENST00000229332 -1 -1
# ENSG00000177151 ENST00000317450 0 -1
# ENSG00000249624 ENST00000433395 1 -1
# ENSG00000237276 ENST00000442385 2 -1
# ENSG00000167744 ENST00000301411 -1 0
canon_ids = 'ENSG00000111729 ENSG00000177151 ENSG00000237276 ENSG00000167744 ENSG00000251184'.split()
for index, stable_id in enumerate(canon_ids):
gene = self.human.getGeneByStableId(StableId=stable_id)
transcript = gene.CanonicalTranscript
prot_seq = transcript.ProteinSeq
def test_gene_transcripts(self):
"""should return multiple transcripts"""
stable_id = 'ENSG00000012048'
gene = self.human.getGeneByStableId(StableId=stable_id)
self.assertTrue(len(gene.Transcripts) > 1)
# .. and correctly construct the Cds and location
for transcript in gene.Transcripts:
self.assertTrue(transcript.getCdsLength()>0)
self.assertEquals(transcript.Location.CoordName,'17')
def test_get_longest_cds_transcript2(self):
"""should correctly return transcript with longest cds"""
# ENSG00000123552 is protein coding, ENSG00000206629 is ncRNA
for stable_id, max_cds_length in [('ENSG00000123552', 2445),
('ENSG00000206629', 164)]:
gene = self.human.getGeneByStableId(StableId=stable_id)
ts = gene.getLongestCdsTranscript()
self.assertEquals(len(ts.Cds), max_cds_length)
self.assertEquals(ts.getCdsLength(), max(gene.getCdsLengths()))
def test_get_longest_cds_transcript1(self):
"""should correctly return transcript with longest cds"""
stable_id = 'ENSG00000178591'
gene = self.human.getGeneByStableId(StableId=stable_id)
ts = gene.getLongestCdsTranscript()
self.assertEquals(ts.getCdsLength(), max(gene.getCdsLengths()))
def test_rna_transcript_cds(self):
"""should return a Cds for an RNA gene too"""
rna_gene = self.human.getGeneByStableId(StableId='ENSG00000210049')
self.assertTrue(rna_gene.Transcripts[0].getCdsLength() > 0)
def test_gene_annotation(self):
"""should correctly annotated a sequence"""
annot_seq = self.brca2.getAnnotatedSeq(feature_types='gene')
gene_annots = annot_seq.getAnnotationsMatching('gene')
self.assertEquals(gene_annots[0].Name, self.brca2.Symbol)
def test_get_by_symbol(self):
"""selecting a gene by it's HGNC symbol should correctly populate all
specified attributes"""
results = self.human.getGenesMatching(Symbol="BRCA2")
for snp in results:
self._eval_brca2(snp)
def test_get_by_symbol_synonym(self):
"""return correct gene if provide a synonymn, rather than symbol"""
synonym = 'FOXO1A'
gene = list(self.human.getGenesMatching(Symbol=synonym))[0]
self.assertEquals(gene.Symbol, 'FOXO1')
def test_get_by_description(self):
"""if get by description, all attributes should be correctly
constructed"""
description='breast cancer 2'
results = list(self.human.getGenesMatching(Description=description))
self.assertEquals(len(results), 1)
self._eval_brca2(results[0])
def test_get_member(self):
"""should return correct exon and translated exon"""
transcript = self.brca2.getMember('ENST00000380152')
# just returns the first
exon_id = 'ENSE00001484009'
exon = transcript.getMember(exon_id)
trans_exon = transcript.getMember(exon_id,'TranslatedExons')
self.assertEquals(exon.StableId, exon_id)
self.assertEquals(trans_exon.StableId, exon_id)
# we check we got Exon in the first call and TranslatedExon in the
# second using the fact that the Exons entry is longer than the
# TranslatedExons one
self.assertGreaterThan(len(exon), len(trans_exon))
def test_get_by_biotype(self):
results = list(self.human.getGenesMatching(BioType='Mt_tRNA', like=False))
self.assertEquals(len(results), 22)
results = list(self.human.getGenesMatching(BioType='Mt_tRNA', like=True))
self.assertEquals(len(results), 607)
def test_get_by_decsr_biotype(self):
"""combining the description and biotype should return a result"""
results = list(self.human.getGenesMatching(BioType="protein_coding",
Description="cancer"))
self.assertTrue(len(results) > 50)
def test_variant(self):
"""variant attribute correctly constructed"""
self.assertTrue(len(self.brca2.Variants) > 880)
def test_get_gene_by_stable_id(self):
"""should correctly handle getting gene by stable_id"""
stable_id = 'ENSG00000012048'
gene = self.human.getGeneByStableId(StableId=stable_id)
self.assertEquals(gene.StableId, stable_id)
# if invalid stable_id, should just return None
stable_id = 'ENSG00000XXXXX'
gene = self.human.getGeneByStableId(StableId=stable_id)
self.assertEquals(gene, None)
def test_intron_number(self):
"""number of introns should be correct"""
for gene_id, transcript_id, exp_number in [
('ENSG00000227268', 'ENST00000445946', 0),
('ENSG00000132199', 'ENST00000319815', 8),
('ENSG00000132199', 'ENST00000383578', 15)]:
gene = asserted_one(self.human.getGenesMatching(StableId=gene_id))
transcript = asserted_one(
[t for t in gene.Transcripts if t.StableId==transcript_id])
if exp_number == 0:
self.assertEqual(transcript.Introns, None)
else:
self.assertEqual(len(transcript.Introns), exp_number)
def test_intron(self):
"""should get correct Intron sequence, regardless of strand"""
# IL2 is on - strand, IL13 is on + strand, both have three introns
IL2_exp_introns = [
(1, 123377358, 123377448, 'gtaagtatat', 'actttcttag'),
(2, 123375008, 123377298, 'gtaagtacaa', 'attattctag'),
(3, 123373017,123374864, 'gtaaggcatt', 'tcttttatag')]
IL13_exp_introns = [
(1, 131994052, 131995109, 'gtgagtgtcg', 'gctcccacag'),
(2, 131995163, 131995415, 'gtaaggacct', 'ctccccacag'),
(3, 131995520, 131995866, 'gtaaggcatc', 'tgtcctgcag')]
for symbol, stable_id, exp_introns in [
('IL2', 'ENST00000226730', IL2_exp_introns),
('IL13', 'ENST00000304506', IL13_exp_introns)]:
gene = asserted_one(self.human.getGenesMatching(Symbol=symbol))
strand = gene.Location.Strand
transcript = asserted_one(
[t for t in gene.Transcripts if t.StableId==stable_id])
introns = transcript.Introns
self.assertEqual(len(introns), len(exp_introns))
idx = 0
for intron in introns:
loc = intron.Location
start, end = loc.Start, loc.End
seq = str(intron.Seq)
exp_rank, exp_start, exp_end, exp_seq5, \
exp_seq3 = exp_introns[idx]
self.assertEqual(loc.Strand, strand)
# test the order using rank
self.assertEqual(intron.Rank, exp_rank)
# test position
self.assertEqual(start, exp_start)
self.assertEqual(end, exp_end)
# test sequence
self.assertEqual(seq[:10], exp_seq5.upper())
self.assertEqual(seq[-10:], exp_seq3.upper())
idx += 1
def test_intron_annotation(self):
"""sequences annotated with Introns should return correct seq"""
for symbol, stable_id, rank, exp_seq5, exp_seq3 in [
('IL2', 'ENST00000226730', 1, 'gtaagtatat', 'actttcttag'),
('IL13', 'ENST00000304506', 3, 'gtaaggcatc', 'tgtcctgcag')]:
gene = asserted_one(self.human.getGenesMatching(Symbol=symbol))
seq = gene.getAnnotatedSeq(feature_types='gene')
intron = asserted_one(seq.getAnnotationsMatching('intron',
'%s-%d'%(stable_id, rank)))
intron_seq = str(seq.getRegionCoveringAll(intron).getSlice())
self.assertEqual(intron_seq[:10], exp_seq5.upper())
self.assertEqual(intron_seq[-10:], exp_seq3.upper())
class TestVariation(GenomeTestBase):
snp_names = ['rs34213141', 'rs12791610', 'rs10792769', 'rs11545807', 'rs11270496']
snp_nt_alleles = ['G/A', 'C/T', 'A/G', 'C/A', 'CAGCTCCAGCTC/-']
snp_aa_alleles = ['G/R', 'P/L', 'Y/C', "V/F", "GAGAV/V"]
snp_effects = ['non_synonymous_codon']*3+[['2KB_upstream_variant', '5KB_upstream_variant', 'non_synonymous_codon']]+['non_synonymous_codon']
snp_nt_len = [1, 1, 1, 1, 12]
map_weights = [1,1,1,1,1]
snp_flanks = [
('CTGAGGTGAGCCAGCGTTGGAGCTGTTTTTCCTTTCAGTATGAATTCCACAAGGAAATCATCTCAGGAGGAAGGGCTCATACTTGGATCCAGAAAATATCAACATAGCCAAAGAAAAACAATCAAGACATACCTCCAGGAGCTGTGTAACAGCAACCGGAAAGAGAAACAATGGTGTGTTCCTATGTGGGATATAAAGAGCCGGGGCTCAGGGGGCTCCACACCTGCACCTCCTTCTCACCTGCTCCTCTACCTGCTCCACCCTCAATCCACCAGAACCATGGGCTGCTGTGGCTGCTCC',
'GAGGCTGTGGCTCCAGCTGTGGAGGCTGTGACTCCAGCTGTGGGAGCTGTGGCTCTGGCTGCAGGGGCTGTGGCCCCAGCTGCTGTGCACCCGTCTACTGCTGCAAGCCCGTGTGCTGCTGTGTTCCAGCCTGTTCCTGCTCTAGCTGTGGCAAGCGGGGCTGTGGCTCCTGTGGGGGCTCCAAGGGAGGCTGTGGTTCTTGTGGCTGCTCCCAGTGCAGTTGCTGCAAGCCCTGCTGTTGCTCTTCAGGCTGTGGGTCATCCTGCTGCCAGTGCAGCTGCTGCAAGCCCTACTGCTCCC'),
('GAAAATATCAACATAGCCAAAGAAAAACAATCAAGACATACCTCCAGGAGCTGTGTAACAGCAACCGGAAAGAGAAACAATGGTGTGTTCCTATGTGGGATATAAAGAGCCGGGGCTCAGGGGGCTCCACACCTGCACCTCCTTCTCACCTGCTCCTCTACCTGCTCCACCCTCAATCCACCAGAACCATGGGCTGCTGTGGCTGCTCCGGAGGCTGTGGCTCCAGCTGTGGAGGCTGTGACTCCAGCTGTGGGAGCTGTGGCTCTGGCTGCAGGGGCTGTGGCCCCAGCTGCTGTGCAC',
'CGTCTACTGCTGCAAGCCCGTGTGCTGCTGTGTTCCAGCCTGTTCCTGCTCTAGCTGTGGCAAGCGGGGCTGTGGCTCCTGTGGGGGCTCCAAGGGAGGCTGTGGTTCTTGTGGCTGCTCCCAGTGCAGTTGCTGCAAGCCCTGCTGTTGCTCTTCAGGCTGTGGGTCATCCTGCTGCCAGTGCAGCTGCTGCAAGCCCTACTGCTCCCAGTGCAGCTGCTGTAAGCCCTGTTGCTCCTCCTCGGGTCGTGGGTCATCCTGCTGCCAATCCAGCTGCTGCAAGCCCTGCTGCTCATCCTC'),
('ATCAACATAGCCAAAGAAAAACAATCAAGACATACCTCCAGGAGCTGTGTAACAGCAACCGGAAAGAGAAACAATGGTGTGTTCCTATGTGGGATATAAAGAGCCGGGGCTCAGGGGGCTCCACACCTGCACCTCCTTCTCACCTGCTCCTCTACCTGCTCCACCCTCAATCCACCAGAACCATGGGCTGCTGTGGCTGCTCCGGAGGCTGTGGCTCCAGCTGTGGAGGCTGTGACTCCAGCTGTGGGAGCTGTGGCTCTGGCTGCAGGGGCTGTGGCCCCAGCTGCTGTGCACCCGTCT',
'CTGCTGCAAGCCCGTGTGCTGCTGTGTTCCAGCCTGTTCCTGCTCTAGCTGTGGCAAGCGGGGCTGTGGCTCCTGTGGGGGCTCCAAGGGAGGCTGTGGTTCTTGTGGCTGCTCCCAGTGCAGTTGCTGCAAGCCCTGCTGTTGCTCTTCAGGCTGTGGGTCATCCTGCTGCCAGTGCAGCTGCTGCAAGCCCTACTGCTCCCAGTGCAGCTGCTGTAAGCCCTGTTGCTCCTCCTCGGGTCGTGGGTCATCCTGCTGCCAATCCAGCTGCTGCAAGCCCTGCTGCTCATCCTCAGGCTG'),
('GCTGAAGAAACCATTTCAAACAGGATTGGAATAGGGAAACCCGGCACTCAGCTCGGCGCAAGCCGGCGGTGCCTTCAGACTAGAGAGCCTCTCCTCCGGTGCGCTGCAAGTAGGGCCTCGGCTCGAGGTCAACATTCTAGTTGTCCAGCGCTCCCTCTCCGGCACCTCGGTGAGGCTAGTTGACCCGACAGGCGCGGATCATGAGCAGCTGCAGGAGAATGAAGAGCGGGGACGTAATGAGGCCGAACCAGAGCTCCCGAGTCTGCTCCGCCAGCTTCTGGCACAACAGCATCTCGAAGA',
'GAACTTGAGACTCAGGACCGTAAGTACCCAGAAAAGGCGGAGCACCGCCAGCCGCTTCTCTCCATCCTGGAAGAGGCGCACGGACACGATGGTGGTGAAGTAGGTGCTGAGCCCGTCAGCGGCGAAGAAAGGCACGAACACGTTCCACCAGGAGAGGCCCGGGACCAGGCCATCCACACGCAGTGCCAGCAGCACAGAGAACACCAACAGGGCCAGCAGGTGCACGAAGATCTCGAAGGTGGCGAAGCCTAGCCACTGCACCAGCTCCCGGAGCGAGAAGAGCATCGCGCCCGTTGAGCG')]
def test_get_variation_by_symbol(self):
"""should return correct snp when query genome by symbol"""
# supplement this test with some synonymous snp's, where they have no
# peptide alleles
for i in range(4):
snp = list(self.human.getVariation(Symbol=self.snp_names[i]))[0]
self.assertEquals(snp.Symbol, self.snp_names[i])
self.assertEquals(snp.Effect, self.snp_effects[i])
self.assertEquals(snp.Alleles, self.snp_nt_alleles[i])
self.assertEquals(snp.MapWeight, self.map_weights[i])
def test_num_alleles(self):
"""should correctly infer the number of alleles"""
for i in range(4):
snp = list(self.human.getVariation(Symbol=self.snp_names[i]))[0]
self.assertEquals(len(snp), self.snp_nt_len[i])
def test_get_peptide_alleles(self):
"""should correctly infer the peptide alleles"""
for i in range(4):
snp = list(self.human.getVariation(Symbol=self.snp_names[i]))[0]
if snp.Effect == 'INTRONIC':
continue
self.assertEquals(snp.PeptideAlleles, self.snp_aa_alleles[i])
def test_get_peptide_location(self):
"""should return correct location for aa variants"""
index = self.snp_names.index('rs11545807')
snp = list(self.human.getVariation(Symbol=self.snp_names[index]))[0]
self.assertEquals(snp.TranslationLocation, 95)
def test_validation_status(self):
"""should return correct validation status"""
def func(x):
if type(x) == str or x is None:
x = [x]
return set(x)
data = (('rs34213141', set(['freq']), func),
('rs12791610', set(['cluster', 'freq']), func),
('rs10792769', set(['cluster', 'freq', '1000Genome',
'hapmap', 'doublehit']), func))
for name, status, conv in data:
snp = list(self.human.getVariation(Symbol=name))[0]
self.assertTrue(status <= conv(snp.Validation))
def test_get_flanking_seq(self):
"""should correctly get the flanking sequence"""
for i in range(4): # only have flanking sequence for 3
snp = list(self.human.getVariation(Symbol=self.snp_names[i]))[0]
self.assertEquals(snp.FlankingSeq, self.snp_flanks[i])
def test_variation_seq(self):
"""should return the sequence for a Variation snp if asked"""
snp = list(self.human.getVariation(Symbol=self.snp_names[0]))[0]
self.assertContains(snp.Alleles, str(snp.Seq))
def test_get_validation_condition(self):
"""simple test of SNP validation status"""
snp_status = [('rs94', False), ('rs90', True)]
for symbol, status in snp_status:
snp = list(self.human.getVariation(Symbol=symbol, validated=True))
self.assertEquals(snp != [], status)
def test_allele_freqs(self):
"""exercising getting AlleleFreq data"""
snp = list(self.human.getVariation(Symbol='rs34213141'))[0]
expect = set([('A', '0.0303'), ('G', '0.9697')])
allele_freqs = snp.AlleleFreqs
allele_freqs = set((a, '%.4f' % f )
for a, f in allele_freqs.getRawData(['allele', 'freq']))
self.assertTrue(expect.issubset(allele_freqs))
class TestFeatures(GenomeTestBase):
def setUp(self):
self.igf2 = self.human.getGeneByStableId(StableId='ENSG00000167244')
def test_CpG_island(self):
"""should return correct CpG islands"""
CpGislands = self.human.getFeatures(region=self.igf2,
feature_types='CpG')
expected_stats = [(630, 757), (652, 537), (3254, 3533)]
obs_stats = [(int(island.Score), len(island)) \
for island in CpGislands]
obs_stats.sort()
self.assertTrue(set(expected_stats) & set(obs_stats) != set())
def test_get_multiple_features(self):
"""should not fail to get multiple feature types"""
regions =\
self.human.getFeatures(feature_types=['repeat','gene','cpg'],
CoordName=1, Start=869936,End=901867)
for region in regions:
pass
def test_repeats(self):
"""should correctly return a repeat"""
loc = self.igf2.Location.resized(-1000, 1000)
repeats = list(self.human.getFeatures(
region=loc, feature_types='repeat'))
self.assertTrue(len(repeats) >= 4)
def test_genes(self):
"""should correctly identify igf2 within a region"""
loc = self.igf2.Location.resized(-1000, 1000)
genes = self.human.getFeatures(region=loc, feature_types='gene')
symbols = [g.Symbol.lower() for g in genes]
self.assertContains(symbols, self.igf2.Symbol.lower())
def test_other_genes(self):
"""docstring for est_other_genes"""
mouse = self.mouse.getRegion(CoordName='5', Start=150791005,
End=150838512, Strand='-')
rat = self.rat.getRegion(CoordName='12', Start=4282534, End=4324019,
Strand='+')
for region in [mouse, rat]:
features = region.getFeatures(feature_types=['gene'])
ann_seq = region.getAnnotatedSeq(feature_types='gene')
genes = ann_seq.getAnnotationsMatching('gene')
self.assertTrue(genes != [])
def test_get_variation_feature(self):
"""should correctly return variation features within a region"""
snps = self.human.getFeatures(feature_types='variation',
region=self.brca2)
# snp coordname, start, end should satsify constraints of brca2 loc
c = 0
loc = self.brca2.Location
for snp in snps:
self.assertEquals(snp.Location.CoordName, loc.CoordName)
self.assertTrue(loc.Start < snp.Location.Start < loc.End)
c += 1
if c == 2:
break
def test_gene_feature_data_correct(self):
"""should apply gene feature data in a manner consistent with strand
and the Cogent sequence annotations slice should return the same
result"""
plus = list(self.human.getFeatures(feature_types='gene',
CoordName=13,
Start=31787610,
End=31871820))[0]
minus = plus.Location.copy()
minus.Strand *= -1
minus = self.human.getRegion(region = minus)
# get Sequence
plus_seq = plus.getAnnotatedSeq(feature_types='gene')
minus_seq = minus.getAnnotatedSeq(feature_types='gene')
# the seqs should be the rc of each other
self.assertEquals(str(plus_seq), str(minus_seq.rc()))
# the Cds, however, from the annotated sequences should be identical
plus_cds = plus_seq.getAnnotationsMatching('CDS')[0]
minus_cds = minus_seq.getAnnotationsMatching('CDS')[0]
self.assertEquals(str(plus_cds.getSlice()),str(minus_cds.getSlice()))
def test_other_feature_data_correct(self):
"""should apply CpG feature data in a manner consistent with strand"""
human = self.human
coord = dict(CoordName=11, Start=2165124,End=2165724)
exp_coord = dict(CoordName=11, Start=2165136, End=2165672)
exp_loc = human.getRegion(Strand=1, ensembl_coord=True, **exp_coord)
exp = exp_loc.Seq
ps_feat = human.getRegion(Strand=1, **coord)
ms_feat = human.getRegion(Strand=-1, **coord)
ps_seq = ps_feat.getAnnotatedSeq(feature_types='CpG')
ps_cgi = ps_seq.getAnnotationsMatching('CpGisland')[0]
self.assertEquals(ps_feat.Seq, ms_feat.Seq.rc())
self.assertEquals(ps_cgi.getSlice().rc(), exp)
ms_seq = ms_feat.getAnnotatedSeq(feature_types='CpG')
ms_cgi = ms_seq.getAnnotationsMatching('CpGisland')[0]
self.assertEquals(ms_cgi.getSlice(), ps_cgi.getSlice())
def test_other_repeat(self):
"""should apply repeat feature data in a manner consistent with strand"""
coord=dict(CoordName=13, Start=32890200, End=32890500)
ps_repeat = self.human.getRegion(Strand=1, **coord)
ms_repeat = self.human.getRegion(Strand=-1, **coord)
exp = DNA.makeSequence('CTTACTGTGAGGATGGGAACATTTTACAGCTGTGCTG'\
'TCCAAACCGGTGCCACTAGCCACATTAAGCACTCGAAACGTGGCTAGTGCGACTAGAGAAGAGGA'\
'TTTTCATACGATTTAGTTTCAATCACGCTAACCAGTGACGCGTGGCTAGTGG')
self.assertEquals(ms_repeat.Seq, ps_repeat.Seq.rc())
ps_annot_seq = ps_repeat.getAnnotatedSeq(feature_types='repeat')
ms_annot_seq = ms_repeat.getAnnotatedSeq(feature_types='repeat')
ps_seq = ps_annot_seq.getAnnotationsMatching('repeat')[0]
ms_seq = ms_annot_seq.getAnnotationsMatching('repeat')[0]
self.assertEquals(ms_seq.getSlice(), ps_seq.getSlice())
self.assertEquals(ps_seq.getSlice(), exp)
def test_get_features_from_nt(self):
"""should correctly return the encompassing gene from 1nt"""
snp = list(self.human.getVariation(Symbol='rs34213141'))[0]
gene=list(self.human.getFeatures(feature_types='gene',region=snp))[0]
self.assertEquals(gene.StableId, 'ENSG00000254997')
class TestAssembly(TestCase):
def test_assemble_seq(self):
"""should correctly fill in a sequence with N's"""
expect = DNA.makeSequence("NAAAAANNCCCCCNNGGGNNN")
frags = ["AAAAA","CCCCC","GGG"]
positions = [(11, 16), (18, 23), (25, 28)]
self.assertEqual(_assemble_seq(frags, 10, 31, positions), expect)
positions = [(1, 6), (8, 13), (15, 18)]
self.assertEqual(_assemble_seq(frags, 0, 21, positions), expect)
# should work with:
# start matches first frag start
expect = DNA.makeSequence("AAAAANNCCCCCNNGGGNNN")
positions = [(0, 5), (7, 12), (14, 17)]
self.assertEqual(_assemble_seq(frags, 0, 20, positions), expect)
# end matches last frag_end
expect = DNA.makeSequence("NAAAAANNCCCCCNNGGG")
positions = [(11, 16), (18, 23), (25, 28)]
self.assertEqual(_assemble_seq(frags, 10, 28, positions), expect)
# both start and end matched
expect = DNA.makeSequence("AAAAANNCCCCCNNGGG")
positions = [(10, 15), (17, 22), (24, 27)]
self.assertEqual(_assemble_seq(frags, 10, 27, positions), expect)
# one frag
expect = DNA.makeSequence(''.join(frags))
positions = [(10, 23)]
self.assertEqual(_assemble_seq([''.join(frags)],10,23,positions),
expect)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_db/test_ensembl/test_host.py 000644 000765 000024 00000011317 12024702176 024104 0 ustar 00jrideout staff 000000 000000 import os
from cogent.util.unit_test import TestCase, main
from cogent.db.ensembl.name import EnsemblDbName
from cogent.db.ensembl.host import get_db_name, get_latest_release,\
DbConnection, HostAccount, get_ensembl_account
from cogent.db.ensembl.species import Species
__author__ = "Gavin Huttley, Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
Release = 68
if 'ENSEMBL_ACCOUNT' in os.environ:
args = os.environ['ENSEMBL_ACCOUNT'].split()
host, username, password = args[0:3]
kwargs = {}
if len(args) > 3:
kwargs['port'] = int(args[3])
account = HostAccount(host, username, password, **kwargs)
else:
account = get_ensembl_account(release=Release)
class TestEnsemblDbName(TestCase):
def test_cmp_name(self):
"""should validly compare names by attributes"""
n1 = EnsemblDbName('homo_sapiens_core_46_36h')
n2 = EnsemblDbName('homo_sapiens_core_46_36h')
self.assertEqual(n1, n2)
def test_name_without_build(self):
"""should correctly handle a db name without a build"""
n = EnsemblDbName("pongo_pygmaeus_core_49_1")
self.assertEqual(n.Prefix, "pongo_pygmaeus")
self.assertEqual(n.Type, "core")
self.assertEqual(n.Build, '1')
def test_ensemblgenomes_names(self):
"""correctly handle the ensemblgenomes naming system"""
n = EnsemblDbName('aedes_aegypti_core_5_58_1e')
self.assertEqual(n.Prefix, 'aedes_aegypti')
self.assertEqual(n.Type, 'core')
self.assertEqual(n.Release, '5')
self.assertEqual(n.GeneralRelease, '58')
self.assertEqual(n.Build, '1e')
n = EnsemblDbName('ensembl_compara_metazoa_6_59')
self.assertEqual(n.Release, '6')
self.assertEqual(n.GeneralRelease, '59')
self.assertEqual(n.Type, 'compara')
class TestDBconnects(TestCase):
def test_get_ensembl_account(self):
"""return an HostAccount with correct port"""
for release in [48, '48', None]:
act_new = get_ensembl_account(release=release)
self.assertEqual(act_new.port, 5306)
for release in [45, '45']:
act_old = get_ensembl_account(release=45)
self.assertEqual(act_old.port, 3306)
def test_getdb(self):
"""should discover human entries correctly"""
for name, db_name in [("human", "homo_sapiens_core_49_36k"),
("mouse", "mus_musculus_core_49_37b"),
("rat", "rattus_norvegicus_core_49_34s"),
("platypus", "ornithorhynchus_anatinus_core_49_1f")]:
result = get_db_name(species=name, db_type="core", release='49')
self.assertEqual(len(result), 1)
result = result[0]
self.assertEqual(result.Name, db_name)
self.assertEqual(result.Release, '49')
def test_latest_release_number(self):
"""should correctly the latest release number"""
self.assertGreaterThan(get_latest_release(), "53")
def test_get_all_available(self):
"""should return a listing of all the available databases on the
indicated server"""
available = get_db_name()
# make sure we have a compara db present -- a crude check on
# correctness
one_valid = False
for db in available:
if db.Type == "compara":
one_valid = True
break
self.assertEqual(one_valid, True)
# now check that when we request available under a specific version
# that we only receive valid ones back
available = get_db_name(release="46")
for db in available:
self.assertEqual(db.Release, '46')
def test_active_connections(self):
"""connecting to a database on a specified server should be done once
only, but same database on a different server should be done"""
ensembl_acct = get_ensembl_account(release='46')
engine1 = DbConnection(account=ensembl_acct,
db_name="homo_sapiens_core_46_36h")
engine2 = DbConnection(account=ensembl_acct,
db_name="homo_sapiens_core_46_36h")
self.assertEqual(engine1, engine2)
def test_pool_recycle_option(self):
"""excercising ability to specify a pool recycle option"""
ensembl_acct = get_ensembl_account(release='56')
engine1 = DbConnection(account=ensembl_acct,
db_name="homo_sapiens_core_46_36h", pool_recycle=1000)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_db/test_ensembl/test_metazoa.py 000644 000765 000024 00000005364 12024702176 024574 0 ustar 00jrideout staff 000000 000000 from cogent.db.ensembl.host import HostAccount, get_ensembl_account
from cogent.db.ensembl.compara import Compara, Genome
from cogent.util.unit_test import TestCase, main
__author__ = "Jason Merkin"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "Hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
Release = 12
account = HostAccount('mysql.ebi.ac.uk','anonymous', '', port=4157)
class MZ_ComparaTestBase(TestCase):
comp = Compara(['D.grimshawi', 'D.melanogaster'], Release=Release,
account=account, division='metazoa')
class MZ_TestCompara(MZ_ComparaTestBase):
def test_query_genome(self):
"""compara should attach valid genome attributes by common name"""
brca2 = self.comp.Dmelanogaster.getGeneByStableId("FBgn0050169")
self.assertEquals(brca2.Symbol.lower(), 'brca2')
def test_get_related_genes(self):
"""should correctly return the related gene regions from each genome"""
# using sc35, a splicing factor
sc35 = self.comp.Dmelanogaster.getGeneByStableId("FBgn0040286")
Orthologs = self.comp.getRelatedGenes(gene_region=sc35,
Relationship="ortholog_one2one")
self.assertEquals("ortholog_one2one", Orthologs.Relationships[0])
def test_get_related_genes2(self):
"""should handle case where gene is absent from one of the genomes"""
# here, it is brca2
brca2 = self.comp.Dmelanogaster.getGeneByStableId(
StableId='FBgn0050169')
orthologs = self.comp.getRelatedGenes(gene_region=brca2,
Relationship='ortholog_one2one')
self.assertEquals(len(orthologs.Members),2)
def test_get_collection(self):
sc35 = self.comp.Dmelanogaster.getGeneByStableId(StableId="FBgn0040286")
Orthologs = self.comp.getRelatedGenes(gene_region=sc35,
Relationship="ortholog_one2one")
collection = Orthologs.getSeqCollection()
self.assertTrue(len(collection.Seqs[0])> 1000)
class MZ_Genome(TestCase):
def test_get_general_release(self):
"""should correctly infer the general release"""
rel_lt_65 = Genome('D.melanogaster', Release=11, account=account)
self.assertEqual(rel_lt_65.GeneralRelease, 64)
self.assertEqual(rel_lt_65.CoreDb.db_name, 'drosophila_melanogaster_core_11_64_539')
rel_gt_65 = Genome('D.melanogaster', Release=13, account=account)
self.assertEqual(rel_gt_65.GeneralRelease, 66)
self.assertEqual(rel_gt_65.CoreDb.db_name, 'drosophila_melanogaster_core_13_66_539')
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_db/test_ensembl/test_species.py 000644 000765 000024 00000006732 12024702176 024567 0 ustar 00jrideout staff 000000 000000 from cogent.util.unit_test import TestCase, main
from cogent.db.ensembl.species import Species
__author__ = "Gavin Huttley, Hua Ying"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley", "hua Ying"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "alpha"
class TestSpeciesNamemaps(TestCase):
def test_get_name_type(self):
"""should return the (latin|common) name given a latin, common or ensembl
db prefix names"""
self.assertEqual(Species.getSpeciesName("human"), "Homo sapiens")
self.assertEqual(Species.getSpeciesName("homo_sapiens"), "Homo sapiens")
self.assertEqual(Species.getCommonName("Mus musculus"), "Mouse")
self.assertEqual(Species.getCommonName("mus_musculus"), "Mouse")
def test_get_ensembl_format(self):
"""should take common or latin names and return the corresponding
ensembl db prefix"""
self.assertEqual(Species.getEnsemblDbPrefix("human"), "homo_sapiens")
self.assertEqual(Species.getEnsemblDbPrefix("mouse"), "mus_musculus")
self.assertEqual(Species.getEnsemblDbPrefix("Mus musculus"),
"mus_musculus")
def test_add_new_species(self):
"""should correctly add a new species/common combination and infer the
correct ensembl prefix"""
species_name, common_name = "Otolemur garnettii", "Bushbaby"
Species.amendSpecies(species_name, common_name)
self.assertEqual(Species.getSpeciesName(species_name), species_name)
self.assertEqual(Species.getSpeciesName("Bushbaby"), species_name)
self.assertEqual(Species.getSpeciesName(common_name), species_name)
self.assertEqual(Species.getCommonName(species_name), common_name)
self.assertEqual(Species.getCommonName("Bushbaby"), common_name)
self.assertEqual(Species.getEnsemblDbPrefix("Bushbaby"), "otolemur_garnettii")
self.assertEqual(Species.getEnsemblDbPrefix(species_name), "otolemur_garnettii")
self.assertEqual(Species.getEnsemblDbPrefix(common_name), "otolemur_garnettii")
def test_amend_existing(self):
"""should correctly amend an existing species"""
species_name = 'Ochotona princeps'
common_name1 = 'american pika'
common_name2 = 'pika'
ensembl_pref = 'ochotona_princeps'
Species.amendSpecies(species_name, common_name1)
self.assertEqual(Species.getCommonName(species_name),common_name1)
Species.amendSpecies(species_name, common_name2)
self.assertEqual(Species.getSpeciesName(common_name2), species_name)
self.assertEqual(Species.getSpeciesName(ensembl_pref), species_name)
self.assertEqual(Species.getCommonName(species_name), common_name2)
self.assertEqual(Species.getCommonName(ensembl_pref), common_name2)
self.assertEqual(Species.getEnsemblDbPrefix(species_name),
ensembl_pref)
self.assertEqual(Species.getEnsemblDbPrefix(common_name2),
ensembl_pref)
def test_get_compara_name(self):
"""should correctly form valid names for assignment onto objects"""
self.assertEqual(Species.getComparaName('pika'), 'Pika')
self.assertEqual(Species.getComparaName('C.elegans'), 'Celegans')
self.assertEqual(Species.getComparaName('Caenorhabditis elegans'),
'Celegans')
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_data/__init__.py 000644 000765 000024 00000000450 12024702176 021463 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_molecular_weight']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_data/test_molecular_weight.py 000644 000765 000024 00000002104 12024702176 024313 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for molecular weight.
"""
from cogent.util.unit_test import TestCase, main
from cogent.data.molecular_weight import WeightCalculator, DnaMW, RnaMW, \
ProteinMW
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class WeightCalculatorTests(TestCase):
"""Tests for WeightCalculator, which should calculate molecular weights.
"""
def test_call(self):
"""WeightCalculator should return correct molecular weight"""
r = RnaMW
p = ProteinMW
self.assertEqual(p(''), 0)
self.assertEqual(r(''), 0)
self.assertFloatEqual(p('A'), 107.09)
self.assertFloatEqual(r('A'), 375.17)
self.assertFloatEqual(p('AAA'), 285.27)
self.assertFloatEqual(r('AAA'), 1001.59)
self.assertFloatEqual(r('AAACCCA'), 2182.37)
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_core/__init__.py 000644 000765 000024 00000001566 12024702176 021513 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_alignment',
'test_alphabet',
'test_annotation',
'test_bitvector',
'test_core_standalone',
'test_entity',
'test_genetic_code',
'test_info',
'test_location',
'test_maps',
'test_moltype',
'test_profile',
'test_sequence',
'test_tree',
'test_tree2',
'test_usage']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Catherine Lozupone", "Peter Maxwell", "Rob Knight",
"Gavin Huttley", "Jeremy Widmann", "Greg Caporaso",
"Sandra Smit", "Justin Kuczynski", "Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_core/test_alignment.py 000644 000765 000024 00000247514 12024702176 022776 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.sequence import RnaSequence, frac_same, ModelSequence, Sequence
from cogent.maths.stats.util import Freqs, Numbers
from cogent.core.moltype import RNA, DNA, PROTEIN, BYTES
from cogent.struct.rna2d import ViennaStructure
from cogent.core.alignment import SequenceCollection, \
make_gap_filter, coerce_to_string, \
seqs_from_array, seqs_from_model_seqs, seqs_from_generic, seqs_from_fasta, \
seqs_from_dict, seqs_from_aln, seqs_from_kv_pairs, seqs_from_empty, \
aln_from_array, aln_from_model_seqs, aln_from_collection,\
aln_from_generic, aln_from_fasta, aln_from_dense_aln, aln_from_empty, \
DenseAlignment, Alignment, DataError
from cogent.core.moltype import AB, DNA
from cogent.parse.fasta import MinimalFastaParser
from numpy import array, arange, transpose
from tempfile import mktemp
from os import remove
import re
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann", "Catherine Lozuopone", "Gavin Huttley",
"Rob Knight", "Daniel McDonald", "Jan Kosinski"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class alignment_tests(TestCase):
"""Tests of top-level functions."""
def test_seqs_from_array(self):
"""seqs_from_array should return chars, and successive indices."""
a = array([[0,1,2],[2,1,0]]) #three 2-char seqs
obs_a, obs_labels = seqs_from_array(a)
#note transposition
self.assertEqual(obs_a, [array([0,2]), array([1,1]), array([2,0])])
self.assertEqual(obs_labels, None)
def test_seqs_from_model_seqs(self):
"""seqs_from_model_seqs should return model seqs + names."""
s1 = ModelSequence('ABC', Name='a')
s2 = ModelSequence('DEF', Name='b')
obs_a, obs_labels = seqs_from_model_seqs([s1, s2])
self.assertEqual(obs_a, [s1,s2]) #seq -> numbers
self.assertEqual(obs_labels, ['a','b'])
def test_seqs_from_generic(self):
"""seqs_from_generic should initialize seqs from list of lists, etc."""
s1 = 'ABC'
s2 = 'DEF'
obs_a, obs_labels = seqs_from_generic([s1, s2])
self.assertEqual(obs_a, ['ABC','DEF'])
self.assertEqual(obs_labels, [None, None])
def test_seqs_from_fasta(self):
"""seqs_from_fasta should initialize seqs from fasta-format string"""
s = '>aa\nAB\nC\n>bb\nDE\nF\n'
obs_a, obs_labels = seqs_from_fasta(s)
self.assertEqual(obs_a, ['ABC','DEF'])
self.assertEqual(obs_labels, ['aa','bb'])
def test_seqs_from_aln(self):
"""seqs_from_aln should initialize from existing alignment"""
c = SequenceCollection(['abc','def'])
obs_a, obs_labels = seqs_from_aln(c)
self.assertEqual(obs_a, ['abc','def'])
self.assertEqual(obs_labels, ['seq_0','seq_1'])
def test_seqs_from_kv_pairs(self):
"""seqs_from_kv_pairs should initialize from key-value pairs"""
c = [['a', 'abc'], ['b', 'def']]
obs_a, obs_labels = seqs_from_kv_pairs(c)
self.assertEqual(obs_a, ['abc','def'])
self.assertEqual(obs_labels, ['a','b'])
def test_seqs_from_empty(self):
"""seqs_from_empty should always raise ValueError"""
self.assertRaises(ValueError, seqs_from_empty, 'xyz')
def test_aln_from_array(self):
"""aln_from_array should return same array, and successive indices."""
a = array([[0,1,2],[3,4,5]]) #three 2-char seqs
obs_a, obs_labels = aln_from_array(a)
self.assertEqual(obs_a, transpose(a))
self.assertEqual(obs_labels, None)
def test_aln_from_model_seqs(self):
"""aln_from_model_seqs should initialize aln from sequence objects."""
s1 = ModelSequence('ACC', Name='a', Alphabet=RNA.Alphabet)
s2 = ModelSequence('GGU', Name='b', Alphabet=RNA.Alphabet)
obs_a, obs_labels = aln_from_model_seqs([s1, s2], \
Alphabet=BYTES.Alphabet)
self.assertEqual(obs_a, array([[2,1,1],[3,3,0]], 'b'))
#seq -> numbers
self.assertEqual(obs_labels, ['a','b'])
def test_aln_from_generic(self):
"""aln_from_generic should initialize aln from list of lists, etc."""
s1 = 'AAA'
s2 = 'GGG'
obs_a, obs_labels = aln_from_generic([s1, s2], 'b', \
Alphabet=RNA.Alphabet) #specify array type
self.assertEqual(obs_a, array([[2,2,2],[3,3,3]], 'b')) #str -> chars
self.assertEqual(obs_labels, [None, None])
def test_aln_from_fasta(self):
"""aln_from_fasta should initialize aln from fasta-format string"""
s = '>aa\nAB\nC\n>bb\nDE\nF\n'
obs_a, obs_labels = aln_from_fasta(s.splitlines())
self.assertEqual(obs_a, array(['ABC','DEF'], 'c').view('B')) #seq -> numbers
self.assertEqual(obs_labels, ['aa','bb'])
def test_aln_from_dense_aln(self):
"""aln_from_dense_aln should initialize from existing alignment"""
a = DenseAlignment(array([[0,1,2],[3,4,5]]), conversion_f=aln_from_array)
obs_a, obs_labels = aln_from_dense_aln(a)
self.assertEqual(obs_a, a.SeqData)
self.assertEqual(obs_labels, a.Names)
def test_aln_from_collection(self):
"""aln_from_collection should initialize from existing alignment"""
a = SequenceCollection(['AAA','GGG'])
obs_a, obs_labels = aln_from_collection(a, Alphabet=RNA.Alphabet)
self.assertEqual(a.toFasta(), '>seq_0\nAAA\n>seq_1\nGGG')
self.assertEqual(obs_a, array([[2,2,2],[3,3,3]]))
def test_aln_from_empty(self):
"""aln_from_empty should always raise ValueError"""
self.assertRaises(ValueError, aln_from_empty, 'xyz')
class SequenceCollectionBaseTests(object):
"""Base class for testing the SequenceCollection object.
Unlike Alignments, SequenceCollections can have sequences that are not equal
length. This module contains all the code that _doesn't_ depend on being
able to look at "ragged" SequenceCollections. It is intended that all
classes that inherit from SequenceCollection should have test classes that
inherit from this class, but that the SequenceCollection tests themselves
will additionally contain code to deal with SequenceCollections of unequal
length.
set self.Class in subclasses to generate the rught constructor.
"""
Class = SequenceCollection
def setUp(self):
"""Define some standard SequenceCollection objects."""
self.one_seq = self.Class({'a':'AAAAA'})
self.ragged_padded = self.Class({'a':'AAAAAA','b':'AAA---', \
'c':'AAAA--'})
self.identical = self.Class({'a':'AAAA','b':'AAAA'})
self.gaps = self.Class({'a':'AAAAAAA','b':'A--A-AA', \
'c':'AA-----'})
self.gaps_rna = self.Class({'a':RnaSequence('AAAAAAA'), \
'b':RnaSequence('A--A-AA'), \
'c':RnaSequence('AA-----')})
self.unordered = self.Class({'a':'AAAAA','b':'BBBBB'})
self.ordered1 = self.Class({'a':'AAAAA','b':'BBBBB'}, \
Names=['a','b'])
self.ordered2 = self.Class({'a':'AAAAA','b':'BBBBB'}, \
Names=['b','a'])
self.mixed = self.Class({'a':'ABCDE', 'b':'LMNOP'})
self.end_gaps = self.Class({'a':'--A-BC-', 'b':'-CB-A--', \
'c':'--D-EF-'}, Names=['a','b','c'])
self.many = self.Class({
'a': RnaSequence('UCAGUCAGUU'),
'b': RnaSequence('UCCGUCAAUU'),
'c': RnaSequence('ACCAUCAGUC'),
'd': RnaSequence('UCAAUCGGUU'),
'e': RnaSequence('UUGGUUGGGU'),
'f': RnaSequence('CCGGGCGGCC'),
'g': RnaSequence('UCAACCGGAA'),
})
#Additional SequenceCollections for tests added 6/4/04 by Jeremy Widmann
self.sequences = self.Class(map(RnaSequence, ['UCAG', 'UCAG', 'UCAG']))
self.structures = self.Class(map(ViennaStructure,
['(())..', '......', '(....)']), MolType=BYTES)
self.labeled = self.Class(['ABC', 'DEF'], ['1st', '2nd'])
#Additional SequenceCollection for tests added 1/30/06 by Cathy Lozupone
self.omitSeqsTemplate_aln = self.Class({
's1':RnaSequence('UC-----CU---C'),
's2':RnaSequence('UC------U---C'),
's3':RnaSequence('UUCCUUCUU-UUC'),
's4':RnaSequence('UU-UUUU-UUUUC'),
's5':RnaSequence('-------------')
})
self.a = DenseAlignment(['AAA','AAA'])
self.b = Alignment(['AAA','AAA'])
self.c = SequenceCollection(['AAA','AAA'])
def test_guess_input_type(self):
"""SequenceCollection _guess_input_type should figure out data type correctly"""
git = self.a._guess_input_type
self.assertEqual(git(self.a), 'dense_aln')
self.assertEqual(git(self.b), 'aln')
self.assertEqual(git(self.c), 'collection')
self.assertEqual(git('>ab\nabc'), 'fasta')
self.assertEqual(git(['>ab','abc']), 'fasta')
self.assertEqual(git(['abc','def']), 'generic')
self.assertEqual(git([[1,2],[4,5]]), 'kv_pairs') #precedence over generic
self.assertEqual(git([[1,2,3],[4,5,6]]), 'generic')
self.assertEqual(git([ModelSequence('abc')]), 'model_seqs')
self.assertEqual(git(array([[1,2,3],[4,5,6]])), 'array')
self.assertEqual(git({'a':'aca'}), 'dict')
self.assertEqual(git([]), 'empty')
def test_init_aln(self):
""" SequenceCollection should init from existing alignments"""
exp = self.Class(['AAA','AAA'])
x = self.Class(self.a)
y = self.Class(self.b)
z = self.Class(self.c)
self.assertEqual(x, exp)
self.assertEqual(z, exp)
self.assertEqual(y, exp)
test_init_aln.__doc__ = Class.__name__ + test_init_aln.__doc__
def test_init_dict(self):
"""SequenceCollection init from dict should work as expected"""
d = {'a':'AAAAA', 'b':'BBBBB'}
a = self.Class(d)
self.assertEqual(a, d)
self.assertEqual(a.NamedSeqs.items(), d.items())
def test_init_name_mapped(self):
"""SequenceCollection init should allow name mapping function"""
d = {'a':'AAAAA', 'b':'BBBBB'}
f = lambda x: x.upper()
a = self.Class(d, label_to_name=f)
self.assertNotEqual(a, d)
self.assertNotEqual(a.NamedSeqs.items(), d.items())
d_upper = {'A':'AAAAA','B':'BBBBB'}
self.assertEqual(a, d_upper)
self.assertEqual(a.NamedSeqs.items(), d_upper.items())
def test_init_seq(self):
"""SequenceCollection init from list of sequences should use indices as keys"""
seqs = ['AAAAA', 'BBBBB', 'CCCCC']
a = self.Class(seqs)
self.assertEqual(len(a.NamedSeqs), 3)
self.assertEqual(a.NamedSeqs['seq_0'], 'AAAAA')
self.assertEqual(a.NamedSeqs['seq_1'], 'BBBBB')
self.assertEqual(a.NamedSeqs['seq_2'], 'CCCCC')
self.assertEqual(a.Names, ['seq_0','seq_1','seq_2'])
self.assertEqual(list(a.Seqs), ['AAAAA','BBBBB','CCCCC'])
def test_init_annotated_seq(self):
"""SequenceCollection init from seqs w/ Info should preserve data"""
a = Sequence('AAA', Name='a', Info={'x':3})
b = Sequence('CCC', Name='b', Info={'x':4})
c = Sequence('GGG', Name='c', Info={'x':5})
seqs = [c,b,a]
a = self.Class(seqs)
self.assertEqual(list(a.Names), ['c','b','a'])
self.assertEqual(map(str, a.Seqs), ['GGG','CCC','AAA'])
if self.Class is not DenseAlignment:
#DenseAlignment is allowed to strip Info objects
self.assertEqual([i.Info.x for i in a.Seqs], [5,4,3])
#check it still works if constructed from same class
b = self.Class(a)
self.assertEqual(list(b.Names), ['c','b','a'])
self.assertEqual(map(str, b.Seqs), ['GGG','CCC','AAA'])
if self.Class is not DenseAlignment:
#DenseAlignment is allowed to strip Info objects
self.assertEqual([i.Info.x for i in b.Seqs], [5,4,3])
def test_init_pairs(self):
"""SequenceCollection init from list of (key,val) pairs should work correctly"""
seqs = [['x', 'XXX'], ['b','BBB'], ['c','CCC']]
a = self.Class(seqs)
self.assertEqual(len(a.NamedSeqs), 3)
self.assertEqual(a.NamedSeqs['x'], 'XXX')
self.assertEqual(a.NamedSeqs['b'], 'BBB')
self.assertEqual(a.NamedSeqs['c'], 'CCC')
self.assertEqual(a.Names, ['x','b','c'])
self.assertEqual(list(a.Seqs), ['XXX','BBB','CCC'])
def test_init_duplicate_keys(self):
"""SequenceCollection init from (key, val) pairs should fail on dup. keys"""
seqs = [['x', 'XXX'], ['b','BBB'],['x','CCC'], ['d','DDD'], ['a','AAA']]
self.assertRaises(ValueError, self.Class, seqs)
aln = self.Class(seqs, remove_duplicate_names=True)
self.assertEqual(str(self.Class(seqs, remove_duplicate_names=True)),
'>x\nXXX\n>b\nBBB\n>d\nDDD\n>a\nAAA\n')
def test_init_ordered(self):
"""SequenceCollection should iterate over seqs correctly even if ordered"""
first = self.ordered1
sec = self.ordered2
un = self.unordered
self.assertEqual(first.Names, ['a','b'])
self.assertEqual(sec.Names, ['b', 'a'])
self.assertEqual(un.Names, un.NamedSeqs.keys())
first_list = list(first.Seqs)
sec_list = list(sec.Seqs)
un_list = list(un.Seqs)
self.assertEqual(first_list, ['AAAAA','BBBBB'])
self.assertEqual(sec_list, ['BBBBB','AAAAA'])
#check that the unordered seq matches one of the lists
self.assertTrue((un_list == first_list) or (un_list == sec_list))
self.assertNotEqual(first_list, sec_list)
def test_init_ambig(self):
"""SequenceCollection should tolerate ambiguous chars"""
aln = self.Class(['AAA','CCC'],MolType=DNA)
aln = self.Class(['ANS','CWC'],MolType=DNA)
aln = self.Class(['A-A','CC-'],MolType=DNA)
aln = self.Class(['A?A','CC-'],MolType=DNA)
def test_aln_from_fasta_parser(self):
"""aln_from_fasta_parser should init from iterator"""
s = '>aa\nAC\n>bb\nAA\n>c\nGG\n'.splitlines()
p = MinimalFastaParser(s)
aln = self.Class(p, MolType=DNA)
self.assertEqual(aln.NamedSeqs['aa'], 'AC')
self.assertEqual(aln.toFasta(), '>aa\nAC\n>bb\nAA\n>c\nGG')
s2_ORIG = '>x\nCA\n>b\nAA\n>>xx\nGG'
s2 = '>aa\nAC\n>bb\nAA\n>c\nGG\n'
d = DenseAlignment(MinimalFastaParser(s2.splitlines()))
self.assertEqual(d.toFasta(), aln.toFasta())
def test_aln_from_fasta(self):
"""SequenceCollection should init from fasta-format string"""
s = '>aa\nAC\n>bb\nAA\n>c\nGG\n'
aln = self.Class(s)
self.assertEqual(aln.toFasta(), s.strip())
def test_SeqLen_get(self):
"""SequenceCollection SeqLen should return length of longest seq"""
self.assertEqual(self.one_seq.SeqLen, 5)
self.assertEqual(self.identical.SeqLen, 4)
self.assertEqual(self.gaps.SeqLen, 7)
def test_Seqs(self):
"""SequenceCollection Seqs property should return seqs in correct order."""
first = self.ordered1
sec = self.ordered2
un = self.unordered
first_list = list(first.Seqs)
sec_list = list(sec.Seqs)
un_list = list(un.Seqs)
self.assertEqual(first_list, ['AAAAA','BBBBB'])
self.assertEqual(sec_list, ['BBBBB','AAAAA'])
#check that the unordered seq matches one of the lists
self.assertTrue((un_list == first_list) or (un_list == sec_list))
self.assertNotEqual(first_list, sec_list)
def test_iterSeqs(self):
"""SequenceCollection iterSeqs() method should support reordering of seqs"""
self.ragged_padded = self.Class(self.ragged_padded.NamedSeqs, \
Names=['a','b','c'])
seqs = list(self.ragged_padded.iterSeqs())
self.assertEqual(seqs, ['AAAAAA', 'AAA---', 'AAAA--'])
seqs = list(self.ragged_padded.iterSeqs(seq_order=['b','a','a']))
self.assertEqual(seqs, ['AAA---', 'AAAAAA', 'AAAAAA'])
self.assertSameObj(seqs[1], seqs[2])
self.assertSameObj(seqs[0], self.ragged_padded.NamedSeqs['b'])
def test_Items(self):
"""SequenceCollection Items should iterate over items in specified order."""
#should work if one row
self.assertEqual(list(self.one_seq.Items), ['A']*5)
#should take order into account
self.assertEqual(list(self.ordered1.Items), ['A']*5 + ['B']*5)
self.assertEqual(list(self.ordered2.Items), ['B']*5 + ['A']*5)
def test_iterItems(self):
"""SequenceCollection iterItems() should iterate over items in correct order"""
#should work if one row
self.assertEqual(list(self.one_seq.iterItems()), ['A']*5)
#should take order into account
self.assertEqual(list(self.ordered1.iterItems()), ['A']*5 + ['B']*5)
self.assertEqual(list(self.ordered2.iterItems()), ['B']*5 + ['A']*5)
#should allow row and/or col specification
r = self.ragged_padded
self.assertEqual(list(r.iterItems(seq_order=['c','b'], \
pos_order=[5,1,3])), list('-AA-A-'))
#should not interfere with superclass iteritems()
i = list(r.NamedSeqs.iteritems())
i.sort()
self.assertEqual(i, [('a','AAAAAA'),('b','AAA---'),('c','AAAA--')])
def test_takeSeqs(self):
"""SequenceCollection takeSeqs should return new SequenceCollection with selected seqs."""
a = self.ragged_padded.takeSeqs('bc')
self.assertTrue(isinstance(a, SequenceCollection))
self.assertEqual(a, {'b':'AAA---','c':'AAAA--'})
#should be able to negate
a = self.ragged_padded.takeSeqs('bc', negate=True)
self.assertEqual(a, {'a':'AAAAAA'})
def test_takeSeqs_moltype(self):
"""takeSeqs should preserve the MolType"""
orig = self.Class(data={'a':'CCCCCC','b':'AAA---', 'c':'AAAA--'}, MolType=DNA)
subset = orig.takeSeqs('ab')
self.assertEqual(set(subset.MolType), set(orig.MolType))
def test_getSeqIndices(self):
"""SequenceCollection getSeqIndices should return names of seqs where f(row) is True"""
srp = self.ragged_padded
is_long = lambda x: len(x) > 10
is_med = lambda x: len(str(x).replace('-','')) > 3 #strips gaps
is_any = lambda x: len(x) > 0
self.assertEqual(srp.getSeqIndices(is_long), [])
srp.Names = 'cba'
self.assertEqual(srp.getSeqIndices(is_med), ['c','a'])
srp.Names = 'bac'
self.assertEqual(srp.getSeqIndices(is_med), ['a','c'])
self.assertEqual(srp.getSeqIndices(is_any),['b','a','c'])
#should be able to negate
self.assertEqual(srp.getSeqIndices(is_med, negate=True), ['b'])
self.assertEqual(srp.getSeqIndices(is_any, negate=True), [])
def test_takeSeqsIf(self):
"""SequenceCollection takeSeqsIf should return seqs where f(row) is True"""
is_long = lambda x: len(x) > 10
is_med = lambda x: len(str(x).replace('-','')) > 3
is_any = lambda x: len(x) > 0
srp = self.ragged_padded
self.assertEqual(srp.takeSeqsIf(is_long), {})
srp.Names = 'cba'
self.assertEqual(srp.takeSeqsIf(is_med), \
{'c':'AAAA--','a':'AAAAAA'})
srp.Names = srp.NamedSeqs.keys()
self.assertEqual(srp.takeSeqsIf(is_med), \
{'c':'AAAA--','a':'AAAAAA'})
self.assertEqual(srp.takeSeqsIf(is_any), srp)
self.assertTrue(isinstance(srp.takeSeqsIf(is_med), SequenceCollection))
#should be able to negate
self.assertEqual(srp.takeSeqsIf(is_med, negate=True), \
{'b':'AAA---'})
def test_getItems(self):
"""SequenceCollection getItems should return list of items from k,v pairs"""
self.assertEqual(self.mixed.getItems([('a',3),('b',4),('a',0)]), \
['D','P','A'])
self.assertRaises(KeyError, self.mixed.getItems, [('x','y')])
self.assertRaises(IndexError, self.mixed.getItems, [('a',1000)])
#should be able to negate -- note that results will have seqs in
#arbitrary order
self.assertEqualItems(self.mixed.getItems([('a',3),('b',4),('a',0)], \
negate=True), ['B','C','E','L','M','N','O'])
def test_getItemIndices(self):
"""SequenceCollection getItemIndices should return coordinates of matching items"""
is_vowel = lambda x: x in 'AEIOU'
#reverse name order to test that it's not alphabetical
self.mixed = self.Class(self.mixed.NamedSeqs, Names=['b','a'])
self.assertEqual(self.mixed.getItemIndices(is_vowel), \
[('b',3),('a',0),('a',4)])
is_lower = lambda x: x.islower()
self.assertEqual(self.ragged_padded.getItemIndices(is_lower), [])
#should be able to negate
self.assertEqualItems(self.mixed.getItemIndices(is_vowel, negate=True),\
[('a',1),('a',2),('a',3),('b',0),('b',1),('b',2),('b',4)])
def test_getItemsIf(self):
"""SequenceCollection getItemsIf should return matching items"""
is_vowel = lambda x: x in 'AEIOU'
#reverse name order to test that it's not alphabetical
self.mixed = self.Class(self.mixed.NamedSeqs, Names=['b','a'])
self.assertEqual(self.mixed.getItemsIf(is_vowel), ['O','A','E'])
self.assertEqual(self.one_seq.getItemsIf(is_vowel), list('AAAAA'))
#should be able to negate
self.assertEqualItems(self.mixed.getItemsIf(is_vowel, negate=True), \
list('BCDLMNP'))
def test_getSimilar(self):
"""SequenceCollection getSimilar should get all sequences close to target seq"""
aln = self.many
x = RnaSequence('GGGGGGGGGG')
y = RnaSequence('----------')
#test min and max similarity ranges
result = aln.getSimilar(aln.NamedSeqs['a'], min_similarity=0.4,\
max_similarity=0.7)
for seq in 'cefg':
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 4)
result = aln.getSimilar(aln.NamedSeqs['a'], min_similarity=0.95, \
max_similarity=1)
for seq in 'a':
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 1)
result = aln.getSimilar(aln.NamedSeqs['a'], min_similarity=0.75, \
max_similarity=0.85)
for seq in 'bd':
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 2)
result = aln.getSimilar(aln.NamedSeqs['a'], min_similarity=0, \
max_similarity=0.2)
self.assertEqual(result, {})
#test some sequence transformations
transform = lambda s: s[1:4]
result = aln.getSimilar(aln.NamedSeqs['a'], min_similarity=0.5, \
transform=transform)
for seq in 'abdfg':
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 5)
transform = lambda s: s[-3:]
result = aln.getSimilar(aln.NamedSeqs['a'], min_similarity=0.5, \
transform=transform)
for seq in 'abcde':
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 5)
#test a different distance metric
metric = lambda x, y: str(x).count('G') + str(y).count('G')
result = aln.getSimilar(aln.NamedSeqs['a'], min_similarity=5, \
max_similarity=10, metric=metric)
for seq in 'ef':
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 2)
#test the combination of a transform and a distance metric
aln = self.Class(dict(enumerate(map(RnaSequence, \
['GA-GU','A-GAC','GG-GG']))), MolType=RNA)
transform = lambda s: RnaSequence(str(s).replace('G','A'\
).replace('U','C'))
metric = RnaSequence.fracSameNonGaps
null_transform = lambda s: RnaSequence(str(s))
#first, do it without the transformation
try:
result = aln.getSimilar(aln.NamedSeqs[0], min_similarity=0.5, \
metric=metric)
except TypeError: #need to coerce to RNA seq w/ null_transform
result = aln.getSimilar(aln.NamedSeqs[0], min_similarity=0.5, \
metric=metric, transform=null_transform)
for seq in [0,2]:
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 2)
#repeat with higher similarity
try:
result = aln.getSimilar(aln.NamedSeqs[0], min_similarity=0.8, \
metric=metric)
except TypeError: #need to coerce to RNA
result = aln.getSimilar(aln.NamedSeqs[0], min_similarity=0.8, \
metric=metric, transform=null_transform)
for seq in [0]:
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 1)
#then, verify that the transform changes the results
result = aln.getSimilar(aln.NamedSeqs[0], min_similarity=0.5, \
metric=metric, transform=transform)
for seq in [0,1,2]:
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 3)
result = aln.getSimilar(aln.NamedSeqs[0], min_similarity=0.8, \
metric=metric, transform=transform)
for seq in [0,1]:
self.assertContains(result.NamedSeqs, seq)
self.assertEquals(result.NamedSeqs[seq], aln.NamedSeqs[seq])
self.assertEqual(len(result.NamedSeqs), 2)
def test_distanceMatrix(self):
"""SequenceCollection distanceMatrix should produce correct scores"""
self.assertEqual(self.one_seq.distanceMatrix(frac_same), {'a':{'a':1}})
self.assertEqual(self.gaps.distanceMatrix(frac_same),
{ 'a':{'a':7/7.0,'b':4/7.0,'c':2/7.0},
'b':{'a':4/7.0,'b':7/7.0,'c':3/7.0},
'c':{'a':2/7.0,'b':3/7.0,'c':7/7.0},
})
def test_isRagged(self):
"""SequenceCollection isRagged should return true if ragged alignment"""
assert(not self.identical.isRagged())
assert(not self.gaps.isRagged())
def test_toPhylip(self):
"""SequenceCollection should return PHYLIP string format correctly"""
align_norm = self.Class( ['ACDEFGHIKLMNPQRSTUVWY-',
'ACDEFGHIKLMNPQRSUUVWF-',
'ACDEFGHIKLMNPERSKUVWC-',
'ACNEFGHIKLMNPQRS-UVWP-',
])
phylip_str, id_map = align_norm.toPhylip()
self.assertEqual(phylip_str, """4 22\nseq0000001 ACDEFGHIKLMNPQRSTUVWY-\nseq0000002 ACDEFGHIKLMNPQRSUUVWF-\nseq0000003 ACDEFGHIKLMNPERSKUVWC-\nseq0000004 ACNEFGHIKLMNPQRS-UVWP-""")
self.assertEqual(id_map, {'seq0000004':'seq_3', 'seq0000001':'seq_0', \
'seq0000003': 'seq_2', 'seq0000002': 'seq_1'})
def test_toFasta(self):
"""SequenceCollection should return correct FASTA string"""
aln = self.Class(['AAA','CCC'])
self.assertEqual(aln.toFasta(), '>seq_0\nAAA\n>seq_1\nCCC')
#NOTE THE FOLLOWING SURPRISING BEHAVIOR BECAUSE OF THE TWO-ITEM
#SEQUENCE RULE:
aln = self.Class(['AA','CC'])
self.assertEqual(aln.toFasta(), '>A\nA\n>C\nC')
def test_toNexus(self):
"""SequenceCollection should return correct Nexus string format"""
align_norm = self.Class( ['ACDEFGHIKLMNPQRSTUVWY-',
'ACDEFGHIKLMNPQRSUUVWF-',
'ACDEFGHIKLMNPERSKUVWC-',
'ACNEFGHIKLMNPQRS-UVWP-'])
expect = '#NEXUS\n\nbegin data;\n dimensions ntax=4 nchar=22;\n'+\
' format datatype=protein interleave=yes missing=? gap=-;\n'+\
' matrix\n seq_1 ACDEFGHIKLMNPQRSUUVWF-\n seq_0'+\
' ACDEFGHIKLMNPQRSTUVWY-\n seq_3 ACNEFGHIKLMNPQRS-UVWP-\n '+\
' seq_2 ACDEFGHIKLMNPERSKUVWC-\n\n ;\nend;'
self.assertEqual(align_norm.toNexus('protein'), expect)
def test_getIntMap(self):
"""SequenceCollection.getIntMap should return correct mapping."""
aln = self.Class({'seq1':'ACGU','seq2':'CGUA','seq3':'CCGU'})
int_keys = {'seq_0':'seq1','seq_1':'seq2','seq_2':'seq3'}
int_map = {'seq_0':'ACGU','seq_1':'CGUA','seq_2':'CCGU'}
im,ik = aln.getIntMap()
self.assertEqual(ik,int_keys)
self.assertEqual(im,int_map)
#test change prefix from default 'seq_'
prefix='seqn_'
int_keys = {'seqn_0':'seq1','seqn_1':'seq2','seqn_2':'seq3'}
int_map = {'seqn_0':'ACGU','seqn_1':'CGUA','seqn_2':'CCGU'}
im,ik = aln.getIntMap(prefix=prefix)
self.assertEqual(ik,int_keys)
self.assertEqual(im,int_map)
def test_getNumSeqs(self):
"""SequenceCollection.getNumSeqs should count seqs."""
aln = self.Class({'seq1':'ACGU','seq2':'CGUA','seq3':'CCGU'})
self.assertEqual(aln.getNumSeqs(), 3)
def test_copyAnnotations(self):
"""SequenceCollection copyAnnotations should copy from seq objects"""
aln = self.Class({'seq1':'ACGU','seq2':'CGUA','seq3':'CCGU'})
seq_1 = Sequence('ACGU', Name='seq1')
seq_1.addFeature('xyz','abc', [(1,2)])
seq_5 = Sequence('ACGUAAAAAA', Name='seq5')
seq_5.addFeature('xyzzz','abc', [(1,2)])
annot = {'seq1': seq_1, 'seq5':seq_5}
aln.copyAnnotations(annot)
aln_seq_1 = aln.NamedSeqs['seq1']
if not hasattr(aln_seq_1, 'annotations'):
aln_seq_1 = aln_seq_1.data
aln_seq_2 = aln.NamedSeqs['seq2']
if not hasattr(aln_seq_2, 'annotations'):
aln_seq_2 = aln_seq_2.data
self.assertEqual(len(aln_seq_1.annotations), 1)
self.assertEqual(aln_seq_1.annotations[0].Name,'abc')
self.assertEqual(len(aln_seq_2.annotations), 0)
def test_annotateFromGff(self):
"""SequenceCollection.annotateFromGff should read gff features"""
aln = self.Class({'seq1':'ACGU','seq2':'CGUA','seq3':'CCGU'})
gff = [
['seq1', 'prog1', 'snp', '1', '2', '1.0', '+', '1','"abc"'],
['seq5', 'prog2', 'snp', '2', '3', '1.0', '+', '1','"yyy"'],
]
gff = map('\t'.join, gff)
aln.annotateFromGff(gff)
aln_seq_1 = aln.NamedSeqs['seq1']
if not hasattr(aln_seq_1, 'annotations'):
aln_seq_1 = aln_seq_1.data
aln_seq_2 = aln.NamedSeqs['seq2']
if not hasattr(aln_seq_2, 'annotations'):
aln_seq_2 = aln_seq_2.data
self.assertEqual(len(aln_seq_1.annotations), 1)
self.assertEqual(aln_seq_1.annotations[0].Name,'abc')
self.assertEqual(len(aln_seq_2.annotations), 0)
def test_replaceSeqs(self):
"""replaceSeqs should replace 1-letter w/ 3-letter seqs"""
a = Alignment({'seq1':'ACGU','seq2':'C-UA','seq3':'C---'})
seqs = {'seq1':'AAACCCGGGUUU','seq2':'CCCUUUAAA','seq3':'CCC'}
result = a.replaceSeqs(seqs)
self.assertEqual(result.toFasta(), \
">seq1\nAAACCCGGGUUU\n>seq2\nCCC---UUUAAA\n>seq3\nCCC---------")
def test_getGappedSeq(self):
"""SequenceCollection.getGappedSeq should return seq, with gaps"""
aln = self.Class({'seq1': '--TTT?', 'seq2': 'GATC??'})
self.assertEqual(str(aln.getGappedSeq('seq1')), '--TTT?')
def test_add(self):
"""__add__ should concatenate sequence data, by name"""
align1= self.Class({'a': 'AAAA', 'b': 'TTTT', 'c': 'CCCC'})
align2 = self.Class({'a': 'GGGG', 'b': '----', 'c': 'NNNN'})
align = align1 + align2
concatdict = align.todict()
self.assertEqual(concatdict, {'a': 'AAAAGGGG', 'b': 'TTTT----', 'c': 'CCCCNNNN'})
def test_addSeqs(self):
"""addSeqs should return an alignment with the new sequences appended or inserted"""
data = [('name1', 'AAA'), ('name2', 'AAA'), ('name3', 'AAA'), ('name4', 'AAA')]
data1 = [('name1', 'AAA'), ('name2', 'AAA')]
data2 = [('name3', 'AAA'), ('name4', 'AAA')]
data3 = [('name5', 'BBB'), ('name6', 'CCC')]
aln = self.Class(data)
aln3 = self.Class(data3)
out_aln = aln.addSeqs(aln3)
self.assertEqual(str(out_aln), str(self.Class(data+data3))) #test append at the end
out_aln = aln.addSeqs(aln3, before_name='name3')
self.assertEqual(str(out_aln), str(self.Class(data1+data3+data2))) # test insert before
out_aln = aln.addSeqs(aln3, after_name='name2')
self.assertEqual(str(out_aln), str(self.Class(data1+data3+data2))) # test insert after
out_aln = aln.addSeqs(aln3, before_name='name1')
self.assertEqual(str(out_aln), str(self.Class(data3+data))) #test if insert before first seq works
out_aln = aln.addSeqs(aln3, after_name='name4')
self.assertEqual(str(out_aln), str(self.Class(data+data3))) #test if insert after last seq works
self.assertRaises(ValueError, aln.addSeqs, aln3, before_name='name5') #wrong after/before name
self.assertRaises(ValueError, aln.addSeqs, aln3, after_name='name5') #wrong after/before name
if isinstance(aln, Alignment) or isinstance(aln, DenseAlignment):
self.assertRaises((DataError, ValueError), aln.addSeqs, aln3+aln3)
else:
exp = set([seq for name, seq in data])
exp.update([seq+seq for name, seq in data3])
got = set()
for seq in aln.addSeqs(aln3+aln3).Seqs:
got.update([str(seq).strip()])
self.assertEqual(got, exp)
def test_writeToFile(self):
"""SequenceCollection.writeToFile should write in correct format"""
aln = self.Class([('a','AAAA'),( 'b','TTTT'),('c','CCCC')])
fn = mktemp(suffix='.fasta')
aln.writeToFile(fn)
result = open(fn, 'U').read()
self.assertEqual(result, '>a\nAAAA\n>b\nTTTT\n>c\nCCCC\n')
remove(fn)
def test_len(self):
"""len(SequenceCollection) returns length of longest sequence"""
aln = self.Class([('a','AAAA'),( 'b','TTTT'),('c','CCCC')])
self.assertEqual(len(aln), 4)
def test_getTranslation(self):
"""SequenceCollection.getTranslation translates each seq"""
for seqs in [
{'seq1': 'GATTTT', 'seq2': 'GATC??'},
{'seq1': 'GAT---', 'seq2': '?GATCT'}]:
alignment = self.Class(data=seqs, MolType=DNA)
self.assertEqual(len(alignment.getTranslation()), 2)
# check for a failure when no moltype specified
alignment = self.Class(data=seqs)
try:
peps = alignment.getTranslation()
except AttributeError:
pass
def test_getSeq(self):
"""SequenceCollection.getSeq should return specified seq"""
aln = self.Class({'seq1': 'GATTTT', 'seq2': 'GATC??'})
self.assertEqual(aln.getSeq('seq1'), 'GATTTT')
self.assertRaises(KeyError, aln.getSeq, 'seqx')
def test_todict(self):
"""SequenceCollection.todict should return dict of strings (not obj)"""
aln = self.Class({'seq1': 'GATTTT', 'seq2': 'GATC??'})
self.assertEqual(aln.todict(), {'seq1':'GATTTT','seq2':'GATC??'})
for i in aln.todict().values():
assert isinstance(i, str)
def test_getPerSequenceAmbiguousPositions(self):
"""SequenceCollection.getPerSequenceAmbiguousPositions should return pos"""
aln = self.Class({'s1':'ATGRY?','s2':'T-AG??'}, MolType=DNA)
self.assertEqual(aln.getPerSequenceAmbiguousPositions(), \
{'s2': {4: '?', 5: '?'}, 's1': {3: 'R', 4: 'Y', 5: '?'}})
def test_degap(self):
"""SequenceCollection.degap should strip gaps from each seq"""
aln = self.Class({'s1':'ATGRY?','s2':'T-AG??'}, MolType=DNA)
self.assertEqual(aln.degap(), {'s1':'ATGRY','s2':'TAG'})
def test_withModifiedTermini(self):
"""SequenceCollection.withModifiedTermini should code trailing gaps as ?"""
aln = self.Class({'s1':'AATGR--','s2':'-T-AG?-'}, MolType=DNA)
self.assertEqual(aln.withModifiedTermini(), \
{'s1':'AATGR??','s2':'?T-AG??'})
def test_omitSeqsTemplate(self):
"""SequenceCollection.omitSeqsTemplate returns new aln with well-aln to temp"""
aln = self.omitSeqsTemplate_aln
result = aln.omitSeqsTemplate('s3', 0.9, 5)
self.assertEqual(result, {'s3': 'UUCCUUCUU-UUC', \
's4': 'UU-UUUU-UUUUC'})
result2 = aln.omitSeqsTemplate('s4', 0.9, 4)
self.assertEqual(result2, {'s3': 'UUCCUUCUU-UUC', \
's4': 'UU-UUUU-UUUUC'})
result3 = aln.omitSeqsTemplate('s1', 0.9, 4)
self.assertEqual(result3, {'s2': 'UC------U---C', \
's1': 'UC-----CU---C', 's5': '-------------'})
result4 = aln.omitSeqsTemplate('s3', 0.5, 13)
self.assertEqual(result4, {'s3': 'UUCCUUCUU-UUC', \
's4': 'UU-UUUU-UUUUC'})
def test_make_gap_filter(self):
"""make_gap_filter returns f(seq) -> True if aligned ok w/ query"""
s1 = RnaSequence('UC-----CU---C')
s3 = RnaSequence('UUCCUUCUU-UUC')
s4 = RnaSequence('UU-UUUU-UUUUC')
#check that the behavior is ok for gap runs
f1 = make_gap_filter(s1, 0.9, 5)
f3 = make_gap_filter(s3, 0.9, 5)
#Should return False since s1 has gap run >= 5 with respect to s3
self.assertEqual(f3(s1), False)
#Should return False since s3 has an insertion run >= 5 to s1
self.assertEqual(f1(s3), False)
#Should retun True since s4 does not have a long enough gap or ins run
self.assertEqual(f3(s4), True)
f3 = make_gap_filter(s3, 0.9, 6)
self.assertEqual(f3(s1), True)
#Check that behavior is ok for gap_fractions
f1 = make_gap_filter(s1, 0.5, 6)
f3 = make_gap_filter(s3, 0.5, 6)
#Should return False since 0.53% of positions are diff for gaps
self.assertEqual(f3(s1), False)
self.assertEqual(f1(s3), False)
self.assertEqual(f3(s4), True)
def test_omitGapSeqs(self):
"""SequenceCollection omitGapSeqs should return alignment w/o seqs with gaps"""
#check default params
self.assertEqual(self.gaps.omitGapSeqs(), self.gaps.omitGapSeqs(0))
#check for boundary effects
self.assertEqual(self.gaps.omitGapSeqs(-1), {})
self.assertEqual(self.gaps.omitGapSeqs(0), {'a':'AAAAAAA'})
self.assertEqual(self.gaps.omitGapSeqs(0.1), {'a':'AAAAAAA'})
self.assertEqual(self.gaps.omitGapSeqs(3.0/7 - 0.01), {'a':'AAAAAAA'})
self.assertEqual(self.gaps.omitGapSeqs(3.0/7), \
{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps.omitGapSeqs(3.0/7 + 0.01), \
{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps.omitGapSeqs(5.0/7 - 0.01), \
{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps.omitGapSeqs(5.0/7 + 0.01), self.gaps)
self.assertEqual(self.gaps.omitGapSeqs(0.99), self.gaps)
#check new object creation
self.assertNotSameObj(self.gaps.omitGapSeqs(0.99), self.gaps)
self.assertTrue(isinstance(self.gaps.omitGapSeqs(3.0/7),
SequenceCollection))
#repeat tests for object that supplies its own gaps
self.assertEqual(self.gaps_rna.omitGapSeqs(-1), {})
self.assertEqual(self.gaps_rna.omitGapSeqs(0), {'a':'AAAAAAA'})
self.assertEqual(self.gaps_rna.omitGapSeqs(0.1), {'a':'AAAAAAA'})
self.assertEqual(self.gaps_rna.omitGapSeqs(3.0/7 - 0.01), \
{'a':'AAAAAAA'})
self.assertEqual(self.gaps_rna.omitGapSeqs(3.0/7), \
{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps_rna.omitGapSeqs(3.0/7 + 0.01), \
{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps_rna.omitGapSeqs(5.0/7 - 0.01), \
{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps_rna.omitGapSeqs(5.0/7 + 0.01), self.gaps_rna)
self.assertEqual(self.gaps_rna.omitGapSeqs(0.99), self.gaps_rna)
self.assertNotSameObj(self.gaps_rna.omitGapSeqs(0.99), self.gaps_rna)
self.assertTrue(isinstance(self.gaps_rna.omitGapSeqs(3.0/7),
SequenceCollection))
def test_omitGapRuns(self):
"""SequenceCollection omitGapRuns should return alignment w/o runs of gaps"""
#negative value will still let through ungapped sequences
self.assertEqual(self.gaps.omitGapRuns(-5), {'a':'AAAAAAA'})
#test edge effects
self.assertEqual(self.gaps.omitGapRuns(0), {'a':'AAAAAAA'})
self.assertEqual(self.gaps.omitGapRuns(1), {'a':'AAAAAAA'})
self.assertEqual(self.gaps.omitGapRuns(2),{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps.omitGapRuns(3),{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps.omitGapRuns(4),{'a':'AAAAAAA','b':'A--A-AA'})
self.assertEqual(self.gaps.omitGapRuns(5), self.gaps)
self.assertEqual(self.gaps.omitGapRuns(6), self.gaps)
self.assertEqual(self.gaps.omitGapRuns(1000), self.gaps)
#test new object creation
self.assertNotSameObj(self.gaps.omitGapRuns(6), self.gaps)
self.assertTrue(isinstance(self.gaps.omitGapRuns(6),
SequenceCollection))
def test_consistent_gap_degen_handling(self):
"""gap degen character should be treated consistently"""
# the degen character '?' can be a gap, so when we strip gaps it should
# be gone too
raw_seq = "---??-??TC-GGCG-GCA-G-GC-?-C-TAN-GCGC-CCTC-AGGA?-???-??--"
raw_ungapped = re.sub("[-?]", "", raw_seq)
raw_no_ambigs = re.sub("[N?]+", "", raw_seq)
dna = DNA.makeSequence(raw_seq)
aln = self.Class(data=[("a", dna),("b", dna)])
expect = self.Class(data=[("a", raw_ungapped),("b", raw_ungapped)]).toFasta()
self.assertEqual(aln.degap().toFasta(), expect)
seqs = self.Class(data=[("a", dna),("b", dna)])
self.assertEqual(seqs.degap().toFasta(), expect)
def test_padSeqs(self):
"""SequenceCollection padSeqs should work on alignment."""
#pad to max length
padded1 = self.ragged_padded.padSeqs()
seqs1 = list(padded1.iterSeqs(seq_order=['a','b','c']))
self.assertEqual(map(str,seqs1),['AAAAAA', 'AAA---', 'AAAA--'])
#pad to alternate length
padded1 = self.ragged_padded.padSeqs(pad_length=10)
seqs1 = list(padded1.iterSeqs(seq_order=['a','b','c']))
self.assertEqual(map(str,seqs1),['AAAAAA----', 'AAA-------',\
'AAAA------'])
#assertRaises error when pad_length is less than max seq length
self.assertRaises(ValueError, self.ragged_padded.padSeqs, 5)
class SequenceCollectionTests(SequenceCollectionBaseTests, TestCase):
"""Tests of the SequenceCollection object. Includes ragged collection tests.
Should not test alignment-specific features.
"""
def setUp(self):
"""Adds self.ragged for ragged collection tests."""
self.ragged = SequenceCollection({'a':'AAAAAA', 'b':'AAA', 'c':'AAAA'})
super(SequenceCollectionTests, self).setUp()
def test_SeqLen_get_ragged(self):
"""SequenceCollection SeqLen get should work for ragged seqs"""
self.assertEqual(self.ragged.SeqLen, 6)
def test_isRagged_ragged(self):
"""SequenceCollection isRagged should return True if ragged"""
self.assertTrue(self.ragged.isRagged())
def test_Seqs_ragged(self):
"""SequenceCollection Seqs should work on ragged alignment"""
self.ragged.Names = 'bac'
self.assertEqual(list(self.ragged.Seqs), ['AAA', 'AAAAAA', 'AAAA'])
def test_iterSeqs_ragged(self):
"""SequenceCollection iterSeqs() method should support reordering of seqs"""
self.ragged.Names = ['a','b','c']
seqs = list(self.ragged.iterSeqs())
self.assertEqual(seqs, ['AAAAAA', 'AAA', 'AAAA'])
seqs = list(self.ragged.iterSeqs(seq_order=['b','a','a']))
self.assertEqual(seqs, ['AAA', 'AAAAAA', 'AAAAAA'])
self.assertSameObj(seqs[1], seqs[2])
self.assertSameObj(seqs[0], self.ragged.NamedSeqs['b'])
def test_toPHYLIP_ragged(self):
"""SequenceCollection should refuse to convert ragged seqs to phylip"""
align_rag = self.Class( ['ACDEFGHIKLMNPQRSTUVWY-',
'ACDEFGHIKLMNPQRSUUVWF-',
'ACDEFGHIKLMNPERSKUVWC-',
'ACNEFGHIKLMNUVWP-',
])
self.assertRaises(ValueError, align_rag.toPhylip)
def test_padSeqs_ragged(self):
"""SequenceCollection padSeqs should work on ragged alignment."""
#pad to max length
padded1 = self.ragged.padSeqs()
seqs1 = list(padded1.iterSeqs(seq_order=['a','b','c']))
self.assertEqual(map(str,seqs1),['AAAAAA', 'AAA---', 'AAAA--'])
#pad to alternate length
padded1 = self.ragged.padSeqs(pad_length=10)
seqs1 = list(padded1.iterSeqs(seq_order=['a','b','c']))
self.assertEqual(map(str,seqs1),['AAAAAA----', 'AAA-------',\
'AAAA------'])
#assertRaises error when pad_length is less than max seq length
self.assertRaises(ValueError, self.ragged.padSeqs, 5)
class AlignmentBaseTests(SequenceCollectionBaseTests):
"""Tests of basic Alignment functionality. All Alignments should pass these.
Note that this is not a TestCase: need to subclass to test each specific
type of Alignment. Override self.Constructor with your alignment class
as a constructor.
"""
def test_Positions(self):
"""SequenceCollection Positions property should iterate over positions, using self.Names"""
r = self.Class({'a':'AAAAAA','b':'AAA---','c':'AAAA--'})
r.Names = ['a','b','c']
self.assertEqual(list(r.Positions), map(list, \
['AAA','AAA','AAA', 'A-A', 'A--', 'A--']))
def test_iterPositions(self):
#"""SequenceCollection iterPositions() method should support reordering of #cols"""
r = self.Class(self.ragged_padded.NamedSeqs, Names=['c','b'])
self.assertEqual(list(r.iterPositions(pos_order=[5,1,3])),\
map(list,['--','AA','A-']))
#reorder names
r = self.Class(self.ragged_padded.NamedSeqs, Names=['a','b','c'])
cols = list(r.iterPositions())
self.assertEqual(cols, map(list, ['AAA','AAA','AAA','A-A','A--','A--']))
def test_takePositions(self):
"""SequenceCollection takePositions should return new alignment w/ specified pos"""
self.assertEqual(self.gaps.takePositions([5,4,0], \
seq_constructor=coerce_to_string), \
{'a':'AAA','b':'A-A','c':'--A'})
self.assertTrue(isinstance(self.gaps.takePositions([0]),
SequenceCollection))
#should be able to negate
self.assertEqual(self.gaps.takePositions([5,4,0], negate=True, \
seq_constructor=coerce_to_string),
{'a':'AAAA','b':'--AA','c':'A---'})
def test_getPositionIndices(self):
"""SequenceCollection getPositionIndices should return names of cols where f(col)"""
gap_1st = lambda x: x[0] == '-'
gap_2nd = lambda x: x[1] == '-'
gap_3rd = lambda x: x[2] == '-'
is_list = lambda x: isinstance(x, list)
self.gaps = self.Class(self.gaps.NamedSeqs, Names=['a','b','c'])
self.assertEqual(self.gaps.getPositionIndices(gap_1st), [])
self.assertEqual(self.gaps.getPositionIndices(gap_2nd), [1,2,4])
self.assertEqual(self.gaps.getPositionIndices(gap_3rd), [2,3,4,5,6])
self.assertEqual(self.gaps.getPositionIndices(is_list), [0,1,2,3,4,5,6])
#should be able to negate
self.assertEqual(self.gaps.getPositionIndices(gap_2nd, negate=True), \
[0,3,5,6])
self.assertEqual(self.gaps.getPositionIndices(gap_1st, negate=True), \
[0,1,2,3,4,5,6])
self.assertEqual(self.gaps.getPositionIndices(is_list, negate=True), [])
def test_takePositionsIf(self):
"""SequenceCollection takePositionsIf should return cols where f(col) is True"""
gap_1st = lambda x: x[0] == '-'
gap_2nd = lambda x: x[1] == '-'
gap_3rd = lambda x: x[2] == '-'
is_list = lambda x: isinstance(x, list)
self.gaps.Names = 'abc'
self.assertEqual(self.gaps.takePositionsIf(gap_1st,seq_constructor=coerce_to_string),\
{'a':'', 'b':'', 'c':''})
self.assertEqual(self.gaps.takePositionsIf(gap_2nd,seq_constructor=coerce_to_string),\
{'a':'AAA', 'b':'---', 'c':'A--'})
self.assertEqual(self.gaps.takePositionsIf(gap_3rd,seq_constructor=coerce_to_string),\
{'a':'AAAAA', 'b':'-A-AA', 'c':'-----'})
self.assertEqual(self.gaps.takePositionsIf(is_list,seq_constructor=coerce_to_string),\
self.gaps)
self.assertTrue(isinstance(self.gaps.takePositionsIf(gap_1st),
SequenceCollection))
#should be able to negate
self.assertEqual(self.gaps.takePositionsIf(gap_1st, seq_constructor=coerce_to_string,\
negate=True), self.gaps)
self.assertEqual(self.gaps.takePositionsIf(gap_2nd, seq_constructor=coerce_to_string,\
negate=True), {'a':'AAAA','b':'AAAA','c':'A---'})
self.assertEqual(self.gaps.takePositionsIf(gap_3rd, seq_constructor=coerce_to_string,\
negate=True), {'a':'AA','b':'A-','c':'AA'})
def test_omitGapPositions(self):
"""SequenceCollection omitGapPositions should return alignment w/o positions of gaps"""
aln = self.end_gaps
#first, check behavior when we're just acting on the cols (and not
#trying to delete the naughty seqs).
#default should strip out cols that are 100% gaps
self.assertEqual(aln.omitGapPositions(seq_constructor=coerce_to_string), \
{'a':'-ABC', 'b':'CBA-', 'c':'-DEF'})
#if allowed_gap_frac is 1, shouldn't delete anything
self.assertEqual(aln.omitGapPositions(1, seq_constructor=coerce_to_string), \
{'a':'--A-BC-', 'b':'-CB-A--', 'c':'--D-EF-'})
#if allowed_gap_frac is 0, should strip out any cols containing gaps
self.assertEqual(aln.omitGapPositions(0, seq_constructor=coerce_to_string), \
{'a':'AB', 'b':'BA', 'c':'DE'})
#intermediate numbers should work as expected
self.assertEqual(aln.omitGapPositions(0.4, seq_constructor=coerce_to_string), \
{'a':'ABC', 'b':'BA-', 'c':'DEF'})
self.assertEqual(aln.omitGapPositions(0.7, seq_constructor=coerce_to_string), \
{'a':'-ABC', 'b':'CBA-', 'c':'-DEF'})
#second, need to check behavior when the naughty seqs should be
#deleted as well.
#default should strip out cols that are 100% gaps
self.assertEqual(aln.omitGapPositions(seq_constructor=coerce_to_string, \
del_seqs=True), {'a':'-ABC', 'b':'CBA-', 'c':'-DEF'})
#if allowed_gap_frac is 1, shouldn't delete anything
self.assertEqual(aln.omitGapPositions(1, seq_constructor=coerce_to_string, \
del_seqs=True), {'a':'--A-BC-', 'b':'-CB-A--', 'c':'--D-EF-'})
#if allowed_gap_frac is 0, should strip out any cols containing gaps
self.assertEqual(aln.omitGapPositions(0, seq_constructor=coerce_to_string, \
del_seqs=True), {}) #everything has at least one naughty non-gap
#intermediate numbers should work as expected
self.assertEqual(aln.omitGapPositions(0.4, seq_constructor=coerce_to_string,
del_seqs=True), {'a':'ABC', 'c':'DEF'}) #b has a naughty non-gap
#check that does not delete b if allowed_frac_bad_calls higher than 0.14
self.assertEqual(aln.omitGapPositions(0.4, seq_constructor=coerce_to_string,
del_seqs=True, allowed_frac_bad_cols=0.2), \
{'a':'ABC', 'b':'BA-','c':'DEF'})
self.assertEqual(aln.omitGapPositions(0.4, seq_constructor=coerce_to_string,
del_seqs=True), {'a':'ABC', 'c':'DEF'}) #b has a naughty non-gap
self.assertEqual(aln.omitGapPositions(0.7, seq_constructor=coerce_to_string,
del_seqs=True), {'a':'-ABC', 'b':'CBA-', 'c':'-DEF'}) #all ok
#when we increase the number of sequences to 6, more differences
#start to appear.
new_aln_data = aln.NamedSeqs.copy()
new_aln_data['d'] = '-------'
new_aln_data['e'] = 'XYZXYZX'
new_aln_data['f'] = 'AB-CDEF'
aln = self.Class(new_aln_data)
#if no gaps are allowed, everything is deleted...
result = aln.omitGapPositions(seq_constructor=coerce_to_string)
self.assertEqual(aln.omitGapPositions(0, del_seqs=False), \
{'a':'', 'b':'', 'c':'', 'd':'', 'e':'', 'f':''})
#...though not a sequence that's all gaps, since it has no positions
#that are not gaps. This 'feature' should possibly be considered a bug.
self.assertEqual(aln.omitGapPositions(0, del_seqs=True), {'d':''})
#if we're deleting only full positions of gaps, del_seqs does nothing.
self.assertEqual(aln.omitGapPositions(del_seqs=True, \
seq_constructor=coerce_to_string), aln)
#at 50%, should delete a bunch of minority sequences
self.assertEqual(aln.omitGapPositions(0.5, del_seqs=True, \
seq_constructor=coerce_to_string), \
{'a':'-ABC','b':'CBA-','c':'-DEF','d':'----'})
#shouldn't depend on order of seqs
aln.Names = 'fadbec'
self.assertEqual(aln.omitGapPositions(0.5, del_seqs=True, \
seq_constructor=coerce_to_string), \
{'a':'-ABC','b':'CBA-','c':'-DEF','d':'----'})
def test_IUPACConsensus_RNA(self):
"""SequenceCollection IUPACConsensus should use RNA IUPAC symbols correctly"""
alignmentUpper = self.Class( ['UCAGN-UCAGN-UCAGN-UCAGAGCAUN-',
'UUCCAAGGNN--UUCCAAGGNNAGCAG--',
'UUCCAAGGNN--UUCCAAGGNNAGCUA--',
'UUUUCCCCAAAAGGGGNNNN--AGCUA--',
'UUUUCCCCAAAAGGGGNNNN--AGCUA--',
], MolType=RNA)
#following IUPAC consensus calculated by hand
#Test all uppper
self.assertEqual(alignmentUpper.IUPACConsensus(),
'UYHBN?BSNN??KBVSN?NN??AGCWD?-')
def test_IUPACConsensus_DNA(self):
"""SequenceCollection IUPACConsensus should use DNA IUPAC symbols correctly"""
alignmentUpper = self.Class( ['TCAGN-TCAGN-TCAGN-TCAGAGCATN-',
'TTCCAAGGNN--TTCCAAGGNNAGCAG--',
'TTCCAAGGNN--TTCCAAGGNNAGCTA--',
'TTTTCCCCAAAAGGGGNNNN--AGCTA--',
'TTTTCCCCAAAAGGGGNNNN--AGCTA--',
])
#following IUPAC consensus calculated by hand
#Test all uppper
self.assertEqual(alignmentUpper.IUPACConsensus(DNA),
'TYHBN?BSNN??KBVSN?NN??AGCWD?-')
def test_IUPACConsensus_Protein(self):
"""SequenceCollection IUPACConsensus should use protein IUPAC symbols correctly"""
alignmentUpper = self.Class( ['ACDEFGHIKLMNPQRSTUVWY-',
'ACDEFGHIKLMNPQRSUUVWF-',
'ACDEFGHIKLMNPERSKUVWC-',
'ACNEFGHIKLMNPQRS-UVWP-',
])
#following IUPAC consensus calculated by hand
#Test all uppper
self.assertEqual(alignmentUpper.IUPACConsensus(PROTEIN),
'ACBEFGHIKLMNPZRS?UVWX-')
def test_isRagged(self):
"""SequenceCollection isRagged should return true if ragged alignment"""
assert(not self.identical.isRagged())
assert(not self.gaps.isRagged())
def test_columnProbs(self):
"""SequenceCollection.columnProbs should find Pr(symbol) in each column"""
#make an alignment with 4 seqs (easy to calculate probabilities)
align = self.Class(["AAA", "ACA", "GGG", "GUC"])
cp = align.columnProbs()
#check that the column probs match the counts we expect
self.assertEqual(cp, map(Freqs, [
{'A':0.5, 'G':0.5},
{'A':0.25, 'C':0.25, 'G':0.25, 'U':0.25},
{'A':0.5, 'G':0.25, 'C':0.25},
]))
def test_majorityConsensus(self):
"""SequenceCollection.majorityConsensus should return commonest symbol per column"""
#Check the exact strings expected from string transform
self.assertEqual(self.sequences.majorityConsensus(str), 'UCAG')
self.assertEqual(self.structures.majorityConsensus(str), '(.....')
def test_uncertainties(self):
"""SequenceCollection.uncertainties should match hand-calculated values"""
aln = self.Class(['ABC', 'AXC'])
obs = aln.uncertainties()
self.assertFloatEqual(obs, [0, 1, 0])
#check what happens with only one input sequence
aln = self.Class(['ABC'])
obs = aln.uncertainties()
self.assertFloatEqual(obs, [0, 0, 0])
#check that we can screen out bad items OK
aln = self.Class(['ABC', 'DEF', 'GHI', 'JKL', '333'], MolType=BYTES)
obs = aln.uncertainties('ABCDEFGHIJKLMNOP')
self.assertFloatEqual(obs, [2.0] * 3)
def test_columnFreqs(self):
"""Alignment.columnFreqs should count symbols in each column"""
#calculate by hand what the first and last positions should look like in
#each case
firstvalues = [
[self.sequences, Freqs('UUU')],
[self.structures, Freqs('(.(')],
]
lastvalues = [
[self.sequences, Freqs('GGG')],
[self.structures, Freqs('..)')],
]
#check that the first positions are what we expected
for obj, result in firstvalues:
freqs = obj.columnFreqs()
self.assertEqual(str(freqs[0]), str(result))
#check that the last positions are what we expected
for obj, result in lastvalues:
freqs = obj.columnFreqs()
self.assertEqual(str(freqs[-1]), str(result))
def test_scoreMatrix(self):
"""Alignment scoreMatrix should produce position specific score matrix."""
scoreMatrix = {
0:{'A':1.0,'C':1.0,'U':5.0},
1:{'C':6.0,'U':1.0},
2:{'A':3.0,'C':2.0,'G':2.0},
3:{'A':3.0,'G':4.0},
4:{'C':1.0,'G':1.0,'U':5.0},
5:{'C':6.0,'U':1.0},
6:{'A':3.0,'G':4.0},
7:{'A':1.0,'G':6.0},
8:{'A':1.0,'C':1.0,'G':1.0,'U':4.0},
9:{'A':1.0,'C':2.0,'U':4.0},
}
self.assertEqual(self.many.scoreMatrix(), scoreMatrix)
def test_sample(self):
"""Alignment.sample should permute alignment by default"""
alignment = self.Class({'seq1': 'ABCDEFGHIJKLMNOP',
'seq2': 'ABCDEFGHIJKLMNOP'})
# effectively permute columns, preserving length
shuffled = alignment.sample()
# ensure length correct
sample = alignment.sample(10)
self.assertEqual(len(sample), 10)
# test columns alignment preserved
seqs = sample.todict().values()
self.assertEqual(seqs[0], seqs[1])
# ensure each char occurs once as sampling without replacement
for char in seqs[0]:
self.assertEqual(seqs[0].count(char), 1)
def test_sample_with_replacement(self):
#test with replacement -- just verify that it rnus
alignment = self.Class({'seq1': 'gatc', 'seq2': 'gatc'})
sample = alignment.sample(1000, with_replacement=True)
self.assertEqual(len(sample), 1000)
# ensure that sampling with replacement works on single col alignment
alignment1 = self.Class({'seq1': 'A',
'seq2': 'A'})
result = alignment1.sample(with_replacement=True)
self.assertEqual(len(result), 1)
def test_sample_tuples(self):
##### test with motif size != 1 #####
alignment = self.Class({'seq1': 'AABBCCDDEEFFGGHHIIJJKKLLMMNNOOPP',
'seq2': 'AABBCCDDEEFFGGHHIIJJKKLLMMNNOOPP'})
shuffled = alignment.sample(motif_length=2)
# ensure length correct
sample = alignment.sample(10,motif_length=2)
self.assertEqual(len(sample), 20)
# test columns alignment preserved
seqs = sample.todict().values()
self.assertEqual(seqs[0], seqs[1])
# ensure each char occurs twice as sampling dinucs without replacement
for char in seqs[0]:
self.assertEqual(seqs[0].count(char), 2)
def test_copy(self):
"""correctly copy an alignment"""
aln = self.Class(data=[('a', 'AC-GT'), ('b', 'ACCGT')])
copied = aln.copy()
self.assertTrue(type(aln), type(copied))
self.assertEqual(aln.todict(), copied.todict())
self.assertEqual(id(aln.MolType), id(copied.MolType))
aln = self.Class(data=[('a', 'AC-GT'), ('b', 'ACCGT')],
Info={'check': True})
copied = aln.copy()
self.assertEqual(aln.Info, copied.Info)
class DenseAlignmentTests(AlignmentBaseTests, TestCase):
Class = DenseAlignment
def test_get_freqs(self):
"""DenseAlignment getSeqFreqs: should work on positions and sequences
"""
s1 = DNA.Sequence('TCAG', Name='s1')
s2 = DNA.Sequence('CCAC', Name='s2')
s3 = DNA.Sequence('AGAT', Name='s3')
da = DenseAlignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
seq_exp = array([[1,1,1,1],[0,3,1,0],[1,0,2,1]])
pos_exp = array([[1,1,1,0],[0,2,0,1],[0,0,3,0],[1,1,0,1]])
self.assertEqual(da._get_freqs(index=1), pos_exp)
self.assertEqual(da._get_freqs(index=0), seq_exp)
def test_getSeqFreqs(self):
"""DenseAlignment getSeqFreqs: should work with DnaSequences and strings
"""
exp = array([[1,1,1,1],[0,3,1,0],[1,0,2,1]])
s1 = DNA.Sequence('TCAG', Name='s1')
s2 = DNA.Sequence('CCAC', Name='s2')
s3 = DNA.Sequence('AGAT', Name='s3')
da = DenseAlignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
obs = da.getSeqFreqs()
self.assertEqual(obs.Data, exp)
self.assertEqual(obs.Alphabet, DNA.Alphabet)
self.assertEqual(obs.CharOrder, list("TCAG"))
s1 = 'TCAG'
s2 = 'CCAC'
s3 = 'AGAT'
da = DenseAlignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
obs = da.getSeqFreqs()
self.assertEqual(obs.Data, exp)
self.assertEqual(obs.Alphabet, DNA.Alphabet)
self.assertEqual(obs.CharOrder, list("TCAG"))
def test_getPosFreqs_sequence(self):
"""DenseAlignment getPosFreqs: should work with DnaSequences and strings
"""
exp = array([[1,1,1,0],[0,2,0,1],[0,0,3,0],[1,1,0,1]])
s1 = DNA.Sequence('TCAG', Name='s1')
s2 = DNA.Sequence('CCAC', Name='s2')
s3 = DNA.Sequence('AGAT', Name='s3')
da = DenseAlignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
obs = da.getPosFreqs()
self.assertEqual(obs.Data, exp)
self.assertEqual(obs.Alphabet, DNA.Alphabet)
self.assertEqual(obs.CharOrder, list("TCAG"))
s1 = 'TCAG'
s2 = 'CCAC'
s3 = 'AGAT'
da = DenseAlignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
obs = da.getPosFreqs()
self.assertEqual(obs.Data, exp)
self.assertEqual(obs.Alphabet, DNA.Alphabet)
self.assertEqual(obs.CharOrder, list("TCAG"))
class AlignmentTests(AlignmentBaseTests, TestCase):
Class = Alignment
def test_get_freqs(self):
"""Alignment _get_freqs: should work on positions and sequences
"""
s1 = DNA.Sequence('TCAG', Name='s1')
s2 = DNA.Sequence('CCAC', Name='s2')
s3 = DNA.Sequence('AGAT', Name='s3')
aln = Alignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
seq_exp = array([[1,1,1,1],[0,3,1,0],[1,0,2,1]])
pos_exp = array([[1,1,1,0],[0,2,0,1],[0,0,3,0],[1,1,0,1]])
self.assertEqual(aln._get_freqs(index=1), pos_exp)
self.assertEqual(aln._get_freqs(index=0), seq_exp)
def test_getSeqFreqs(self):
"""Alignment getSeqFreqs: should work with DnaSequences and strings
"""
exp = array([[1,1,1,1],[0,3,1,0],[1,0,2,1]])
s1 = DNA.Sequence('TCAG', Name='s1')
s2 = DNA.Sequence('CCAC', Name='s2')
s3 = DNA.Sequence('AGAT', Name='s3')
aln = Alignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
obs = aln.getSeqFreqs()
self.assertEqual(obs.Data, exp)
self.assertEqual(obs.Alphabet, DNA.Alphabet)
self.assertEqual(obs.CharOrder, list("TCAG"))
s1 = 'TCAG'
s2 = 'CCAC'
s3 = 'AGAT'
aln = Alignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
obs = aln.getSeqFreqs()
self.assertEqual(obs.Data, exp)
self.assertEqual(obs.Alphabet, DNA.Alphabet)
self.assertEqual(obs.CharOrder, list("TCAG"))
def test_getPosFreqs(self):
"""Alignment getPosFreqs: should work with DnaSequences and strings
"""
exp = array([[1,1,1,0],[0,2,0,1],[0,0,3,0],[1,1,0,1]])
s1 = DNA.Sequence('TCAG', Name='s1')
s2 = DNA.Sequence('CCAC', Name='s2')
s3 = DNA.Sequence('AGAT', Name='s3')
aln = Alignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
obs = aln.getPosFreqs()
self.assertEqual(obs.Data, exp)
self.assertEqual(obs.Alphabet, DNA.Alphabet)
self.assertEqual(obs.CharOrder, list("TCAG"))
s1 = 'TCAG'
s2 = 'CCAC'
s3 = 'AGAT'
aln = Alignment([s1,s2,s3], MolType=DNA, Alphabet=DNA.Alphabet)
obs = aln.getPosFreqs()
self.assertEqual(obs.Data, exp)
self.assertEqual(obs.Alphabet, DNA.Alphabet)
self.assertEqual(obs.CharOrder, list("TCAG"))
def make_and_filter(self, raw, expected, motif_length):
# a simple filter func
func = lambda x: re.findall("[-N?]", " ".join(x)) == []
aln = self.Class(raw)
result = aln.filtered(func,motif_length=motif_length,log_warnings=False)
self.assertEqual(result.todict(), expected)
def test_filtered(self):
"""filtered should return new alignment with positions consistent with
provided callback function"""
# a simple filter option
raw = {'a':'ACGACGACG',
'b':'CCC---CCC',
'c':'AAAA--AAA'}
self.make_and_filter(raw, {'a':'ACGACG','b':'CCCCCC','c':'AAAAAA'}, 1)
# check with motif_length = 2
self.make_and_filter(raw, {'a':'ACAC','b':'CCCC','c':'AAAA'}, 2)
# check with motif_length = 3
self.make_and_filter(raw, {'a':'ACGACG','b':'CCCCCC','c':'AAAAAA'}, 3)
def test_slidingWindows(self):
"""slidingWindows should return slices of alignments."""
alignment = self.Class({'seq1': 'ACGTACGT', 'seq2': 'ACGTACGT', 'seq3': 'ACGTACGT'})
result = []
for bit in alignment.slidingWindows(5,2):
result+=[bit]
self.assertEqual(result[0].todict(), {'seq3': 'ACGTA', 'seq2': 'ACGTA', 'seq1': 'ACGTA'})
self.assertEqual(result[1].todict(), {'seq3': 'GTACG', 'seq2': 'GTACG', 'seq1': 'GTACG'})
result = []
for bit in alignment.slidingWindows(5,1):
result+=[bit]
self.assertEqual(result[0].todict(), {'seq3': 'ACGTA', 'seq2': 'ACGTA', 'seq1': 'ACGTA'})
self.assertEqual(result[1].todict(), {'seq3': 'CGTAC', 'seq2': 'CGTAC', 'seq1': 'CGTAC'})
self.assertEqual(result[2].todict(), {'seq3': 'GTACG', 'seq2': 'GTACG', 'seq1': 'GTACG'})
self.assertEqual(result[3].todict(), {'seq3': 'TACGT', 'seq2': 'TACGT', 'seq1': 'TACGT'})
def test_withGapsFrom(self):
"""withGapsFrom should overwrite with gaps."""
gapless = self.Class({'seq1': 'TCG', 'seq2': 'TCG'})
pregapped = self.Class({'seq1': '-CG', 'seq2': 'TCG'})
template = self.Class({'seq1': 'A-?', 'seq2': 'ACG'})
r1 = gapless.withGapsFrom(template).todict()
r2 = pregapped.withGapsFrom(template).todict()
self.assertEqual(r1, {'seq1': 'T-G', 'seq2': 'TCG'})
self.assertEqual(r2, {'seq1': '--G', 'seq2': 'TCG'})
def test_getDegappedRelativeTo(self):
"""should remove all columns with a gap in sequence with given name"""
aln = self.Class([
['name1', '-AC-DEFGHI---'],
['name2', 'XXXXXX--XXXXX'],
['name3', 'YYYY-YYYYYYYY'],
['name4', '-KL---MNPR---'],
])
out_aln = self.Class([
['name1', 'ACDEFGHI'],
['name2', 'XXXX--XX'],
['name3', 'YY-YYYYY'],
['name4', 'KL--MNPR'],
])
self.assertEqual(aln.getDegappedRelativeTo('name1'), out_aln)
self.assertRaises(ValueError, aln.getDegappedRelativeTo, 'nameX')
def test_addFromReferenceAln(self):
"""should add or insert seqs based on align to reference"""
aln1 = self.Class([
['name1', '-AC-DEFGHI---'],
['name2', 'XXXXXX--XXXXX'],
['name3', 'YYYY-YYYYYYYY'],
])
aln2 = self.Class([
['name1', 'ACDEFGHI'],
['name4', 'KL--MNPR'],
['name5', 'KLACMNPR'],
['name6', 'KL--MNPR'],
])
aligned_to_ref_out_aln_inserted = self.Class([
['name1', '-AC-DEFGHI---'],
['name4', '-KL---MNPR---'],
['name5', '-KL-ACMNPR---'],
['name6', '-KL---MNPR---'],
['name2', 'XXXXXX--XXXXX'],
['name3', 'YYYY-YYYYYYYY'],
])
aln2_wrong_refseq = self.Class((
('name1', 'ACDXFGHI'),
('name4', 'KL--MNPR'),
))
aln2_wrong_refseq_name = self.Class([
['nameY', 'ACDEFGHI'],
['name4', 'KL--MNPR'],
])
aln2_different_aln_class = DenseAlignment([
['name1', 'ACDEFGHI'],
['name4', 'KL--MNPR'],
])
aln2_list = [
['name1', 'ACDEFGHI'],
['name4', 'KL--MNPR'],
]
aligned_to_ref_out_aln = self.Class([
['name1', '-AC-DEFGHI---'],
['name2', 'XXXXXX--XXXXX'],
['name3', 'YYYY-YYYYYYYY'],
['name4', '-KL---MNPR---'],
])
out_aln = aln1.addFromReferenceAln(aln2, after_name='name1')
self.assertEqual(str(aligned_to_ref_out_aln_inserted),
str(out_aln)) #test insert_after
out_aln = aln1.addFromReferenceAln(aln2, before_name='name2')
self.assertEqual(aligned_to_ref_out_aln_inserted,
out_aln) #test insert_before
self.assertRaises(ValueError, aln1.addFromReferenceAln,
aln2_wrong_refseq_name) #test wrong_refseq_name
aln = aln1.addFromReferenceAln(aln2_different_aln_class)
self.assertEqual(aligned_to_ref_out_aln,
aln) #test_align_to_refseq_different_aln_class
aln = aln1.addFromReferenceAln(aln2_list)
self.assertEqual(aligned_to_ref_out_aln,
aln) #test from_list
self.assertRaises(ValueError, aln1.addFromReferenceAln,
aln2_wrong_refseq) #test wrong_refseq
class DenseAlignmentSpecificTests(TestCase):
"""Tests of the DenseAlignment object and its methods"""
def setUp(self):
"""Define some standard alignments."""
self.a = DenseAlignment(array([[0,1,2],[3,4,5]]), \
conversion_f=aln_from_array)
self.a2 = DenseAlignment(['ABC','DEF'], Names=['x','y'])
class ABModelSequence(ModelSequence):
Alphabet = AB.Alphabet
self.ABModelSequence = ABModelSequence
self.a = DenseAlignment(map(ABModelSequence, ['abaa','abbb']), \
Alphabet=AB.Alphabet)
self.b = Alignment(['ABC','DEF'])
self.c = SequenceCollection(['ABC','DEF'])
def test_init(self):
"""DenseAlignment init should work from a sequence"""
a = DenseAlignment(array([[0,1,2],[3,4,5]]), conversion_f=aln_from_array)
self.assertEqual(a.SeqData, array([[0,3],[1,4],[2,5]], 'B'))
self.assertEqual(a.ArrayPositions, array([[0,1,2],[3,4,5]], 'B'))
self.assertEqual(a.Names, ['seq_0','seq_1','seq_2'])
def test_guess_input_type(self):
"""DenseAlignment _guess_input_type should figure out data type correctly"""
git = self.a._guess_input_type
self.assertEqual(git(self.a), 'dense_aln')
self.assertEqual(git(self.b), 'aln')
self.assertEqual(git(self.c), 'collection')
self.assertEqual(git('>ab\nabc'), 'fasta')
self.assertEqual(git(['>ab','abc']), 'fasta')
self.assertEqual(git(['abc','def']), 'generic')
self.assertEqual(git([[1,2],[4,5]]), 'kv_pairs') #precedence over generic
self.assertEqual(git([[1,2,3],[4,5,6]]), 'generic')
self.assertEqual(git([ModelSequence('abc')]), 'model_seqs')
self.assertEqual(git(array([[1,2,3],[4,5,6]])), 'array')
self.assertEqual(git({'a':'aca'}), 'dict')
self.assertEqual(git([]), 'empty')
def test_init_seqs(self):
"""DenseAlignment init should work from ModelSequence objects."""
s = map(ModelSequence, ['abc','def'])
a = DenseAlignment(s)
self.assertEqual(a.SeqData, array(['abc','def'], 'c').view('B'))
def test_init_generic(self):
"""DenseAlignment init should work from generic objects."""
s = ['abc','def']
a = DenseAlignment(s)
self.assertEqual(a.SeqData, array(['abc','def'], 'c').view('B'))
def test_init_aln(self):
"""DenseAlignment init should work from another alignment."""
s = ['abc','def']
a = DenseAlignment(s)
b = DenseAlignment(a)
self.assertNotSameObj(a.SeqData, b.SeqData)
self.assertEqual(b.SeqData, array(['abc','def'], 'c').view('B'))
def test_init_dict(self):
"""DenseAlignment init should work from dict."""
s = {'abc':'aaaccc','xyz':'gcgcgc'}
a = DenseAlignment(s)
self.assertEqual(a.SeqData, array(['aaaccc','gcgcgc'], 'c').view('B'))
self.assertEqual(tuple(a.Names), ('abc','xyz'))
def test_init_empty(self):
"""DenseAlignment init should fail if empty."""
self.assertRaises(TypeError, DenseAlignment)
self.assertRaises(ValueError, DenseAlignment, 3)
def test_get_alphabet_and_moltype(self):
"""DenseAlignment should figure out correct alphabet and moltype"""
s1 = 'A'
s2 = RNA.Sequence('AA')
d = DenseAlignment(s1)
self.assertSameObj(d.MolType, BYTES)
self.assertSameObj(d.Alphabet, BYTES.Alphabet)
d = DenseAlignment(s1, MolType=RNA)
self.assertSameObj(d.MolType, RNA)
self.assertSameObj(d.Alphabet, RNA.Alphabets.DegenGapped)
d = DenseAlignment(s1, Alphabet=RNA.Alphabet)
self.assertSameObj(d.MolType, RNA)
self.assertSameObj(d.Alphabet, RNA.Alphabet)
d = DenseAlignment(s2)
self.assertSameObj(d.MolType, RNA)
self.assertSameObj(d.Alphabet, RNA.Alphabets.DegenGapped)
d = DenseAlignment(s2, MolType=DNA)
self.assertSameObj(d.MolType, DNA)
self.assertSameObj(d.Alphabet, DNA.Alphabets.DegenGapped)
#checks for containers
d = DenseAlignment([s2])
self.assertSameObj(d.MolType, RNA)
d = DenseAlignment({'x':s2})
self.assertSameObj(d.MolType, RNA)
d = DenseAlignment(set([s2]))
self.assertSameObj(d.MolType, RNA)
def test_iter(self):
"""DenseAlignment iter should iterate over positions"""
result = list(iter(self.a2))
for i, j in zip(result, [list(i) for i in ['AD', 'BE', 'CF']]):
self.assertEqual(i,j)
def test_getitem(self):
"""DenseAlignment getitem should default to positions as chars"""
a2 = self.a2
self.assertEqual(a2[1], ['B','E'])
self.assertEqual(a2[1:], [['B','E'],['C','F']])
def test_getSubAlignment(self):
"""DenseAlignment getSubAlignment should get requested part of alignment."""
a = DenseAlignment('>x ABCE >y FGHI >z JKLM'.split())
#passing in positions should keep all seqs, but just selected positions
b = DenseAlignment('>x BC >y GH >z KL'.split())
a_1 = a.getSubAlignment(pos=[1,2])
self.assertEqual(a_1.Names, b.Names)
self.assertEqual(a_1.Seqs, b.Seqs)
#...and with invert_pos, should keep all except the positions passed in
a_2 = a.getSubAlignment(pos=[0,3], invert_pos=True)
self.assertEqual(a_2.Seqs, b.Seqs)
self.assertEqual(a_2.Names, b.Names)
#passing in seqs should keep all positions, but just selected seqs
c = DenseAlignment('>x ABCE >z JKLM'.split())
a_3 = a.getSubAlignment(seqs=[0,2])
self.assertEqual(a_3.Seqs, c.Seqs)
#check that labels were updates as well...
self.assertEqual(a_3.Names, c.Names)
#...and should work with invert_seqs to exclude just selected seqs
a_4 = a.getSubAlignment(seqs=[1], invert_seqs=True)
self.assertEqual(a_4.Seqs, c.Seqs)
self.assertEqual(a_4.Names, c.Names)
#should be able to do both seqs and positions simultaneously
d = DenseAlignment('>x BC >z KL'.split())
a_5 = a.getSubAlignment(seqs=[0,2], pos=[1,2])
self.assertEqual(a_5.Seqs, d.Seqs)
self.assertEqual(a_5.Names, d.Names)
def test_str(self):
"""DenseAlignment str should return FASTA representation of aln"""
self.assertEqual(str(self.a2), '>x\nABC\n>y\nDEF\n')
#should work if labels diff length
self.a2.Names[-1] = 'yyy'
self.assertEqual(str(self.a2), '>x\nABC\n>yyy\nDEF\n')
def test_get_freqs(self):
"""DenseAlignment _get_freqs should get row or col freqs"""
ABModelSequence = self.ABModelSequence
a = self.a
self.assertEqual(a._get_freqs(0), array([[3,1],[1,3]]))
self.assertEqual(a._get_freqs(1), array([[2,0],[0,2],[1,1],[1,1]]))
def test_getSeqFreqs(self):
"""DenseAlignment getSeqFreqs should get profile of freqs in each seq"""
ABModelSequence = self.ABModelSequence
a = self.a
f = a.getSeqFreqs()
self.assertEqual(f.Data, array([[3,1],[1,3]]))
def test_getPosFreqs(self):
"""DenseAlignment getPosFreqs should get profile of freqs at each pos"""
ABModelSequence = self.ABModelSequence
a = self.a
f = a.getPosFreqs()
self.assertEqual(f.Data, array([[2,0],[0,2],[1,1],[1,1]]))
def test_getSeqEntropy(self):
"""DenseAlignment getSeqEntropy should get entropy of each seq"""
ABModelSequence = self.ABModelSequence
a = DenseAlignment(map(ABModelSequence, ['abab','bbbb','abbb']), \
Alphabet=AB.Alphabet)
f = a.getSeqEntropy()
e = 0.81127812445913283 #sum(p log_2 p) for p = 0.25, 0.75
self.assertFloatEqual(f, array([1,0,e]))
def test_getPosEntropy(self):
"""DenseAlignment getPosEntropy should get entropy of each pos"""
ABModelSequence = self.ABModelSequence
a = self.a
f = a.getPosEntropy()
e = array([0,0,1,1])
self.assertEqual(f, e)
class IntegrationTests(TestCase):
"""Test for integration between regular and model seqs and alns"""
def setUp(self):
"""Intialize some standard sequences"""
self.r1 = RNA.Sequence('AAA', Name='x')
self.r2 = RNA.Sequence('CCC', Name='y')
self.m1 = RNA.ModelSeq('AAA', Name='xx')
self.m2 = RNA.ModelSeq('CCC', Name='yy')
def test_model_to_model(self):
"""Model seq should work with dense alignment"""
a = DenseAlignment([self.m1, self.m2])
self.assertEqual(str(a), '>xx\nAAA\n>yy\nCCC\n')
a = DenseAlignment([self.m1, self.m2], MolType=DNA)
self.assertEqual(str(a), '>xx\nAAA\n>yy\nCCC\n')
self.assertEqual(self.m1.Name, 'xx')
def test_regular_to_model(self):
"""Regular seq should work with dense alignment"""
a = DenseAlignment([self.r1, self.r2])
self.assertEqual(str(a), '>x\nAAA\n>y\nCCC\n')
a = DenseAlignment([self.r1, self.r2], MolType=DNA)
self.assertEqual(str(a), '>x\nAAA\n>y\nCCC\n')
self.assertEqual(self.r1.Name, 'x')
def test_model_to_regular(self):
"""Model seq should work with regular alignment"""
a = Alignment([self.m1, self.m2])
self.assertEqual(str(a), '>xx\nAAA\n>yy\nCCC\n')
a = Alignment([self.m1, self.m2], MolType=DNA)
self.assertEqual(str(a), '>xx\nAAA\n>yy\nCCC\n')
self.assertEqual(self.m1.Name, 'xx')
def test_regular_to_regular(self):
"""Regular seq should work with regular alignment"""
a = Alignment([self.r1, self.r2])
self.assertEqual(str(a), '>x\nAAA\n>y\nCCC\n')
a = Alignment([self.r1, self.r2], MolType=DNA)
self.assertEqual(str(a), '>x\nAAA\n>y\nCCC\n')
self.assertEqual(self.r1.Name, 'x')
def test_model_aln_to_regular_aln(self):
"""Dense aln should convert to regular aln"""
a = DenseAlignment([self.r1, self.r2])
d = Alignment(a)
self.assertEqual(str(d), '>x\nAAA\n>y\nCCC\n')
d = Alignment(a, MolType=DNA)
self.assertEqual(str(d), '>x\nAAA\n>y\nCCC\n')
self.assertEqual(self.r1.Name, 'x')
def test_regular_aln_to_model_aln(self):
"""Regular aln should convert to model aln"""
a = Alignment([self.r1, self.r2])
d = DenseAlignment(a)
self.assertEqual(str(d), '>x\nAAA\n>y\nCCC\n')
d = DenseAlignment(a, MolType=DNA)
self.assertEqual(str(d), '>x\nAAA\n>y\nCCC\n')
self.assertEqual(self.r1.Name, 'x')
def test_regular_aln_to_regular_aln(self):
"""Regular aln should convert to regular aln"""
a = Alignment([self.r1, self.r2])
d = Alignment(a)
self.assertEqual(str(d), '>x\nAAA\n>y\nCCC\n')
d = Alignment(a, MolType=DNA)
self.assertEqual(str(d), '>x\nAAA\n>y\nCCC\n')
self.assertEqual(self.r1.Name, 'x')
def test_model_aln_to_model_aln(self):
"""Model aln should convert to model aln"""
a = Alignment([self.r1, self.r2])
d = Alignment(a)
self.assertEqual(str(d), '>x\nAAA\n>y\nCCC\n')
d = Alignment(a, MolType=DNA)
self.assertEqual(str(d), '>x\nAAA\n>y\nCCC\n')
self.assertEqual(self.r1.Name, 'x')
#run tests if invoked from command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_core/test_alphabet.py 000644 000765 000024 00000030176 12024702176 022572 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of the Enumeration and Alphabet objects.
Note: individual Alphabets are typically in MolType and are tested there.
"""
from cogent.core.alphabet import Enumeration, get_array_type, \
uint8, uint16, uint32, array, JointEnumeration, CharAlphabet, \
_make_translation_tables, _make_complement_array
from cogent.core.moltype import RNA
from cogent.util.unit_test import TestCase, main
DnaBases = CharAlphabet('TCAG')
RnaBases = CharAlphabet('UCAG')
AminoAcids = CharAlphabet('ACDEFGHIKLMNPQRSTVWY')
__author__ = "Rob Knight, Peter Maxwell and Gavin Huttley"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell", "Rob Knight", "Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class translation_table_tests(TestCase):
"""Tests of top-level translation table functions"""
def test_make_translation_tables(self):
"""_make_translation_tables should translate from chars to indices"""
a = 'ucag'
itoa, atoi = _make_translation_tables(a)
s = 'ggacu'
obs = s.translate(atoi)
self.assertEqual(obs, '\x03\x03\x02\x01\x00')
orig = obs.translate(itoa)
self.assertEqual(orig, s)
def test_make_complement_array(self):
"""_make_complement_array should identify complements correctly"""
complement_array = _make_complement_array(RNA.Alphabet, RNA.Complements)
test = 'UCAG'
test_array = [RNA.Alphabet.index(i) for i in test]
complements = complement_array.take(test_array)
result = ''.join([RNA.Alphabet[i] for i in complements])
self.assertEqual(result, 'AGUC')
class get_array_type_tests(TestCase):
"""Tests of the get_array_type top-level function."""
def test_get_array_type(self):
"""get_array_type should return unsigned type that fits elements."""
self.assertEqual(get_array_type(0), uint8)
self.assertEqual(get_array_type(100), uint8)
self.assertEqual(get_array_type(256), uint8) #boundary case
self.assertEqual(get_array_type(257), uint16) #boundary case
self.assertEqual(get_array_type(10000), uint16)
self.assertEqual(get_array_type(65536), uint16)
self.assertEqual(get_array_type(65537), uint32)
class EnumerationTests(TestCase):
"""Tests of the Enumeration object."""
def test_init(self):
"""Enumeration init should work from any sequence"""
a = Enumeration('abc')
self.assertEqual(a.index('a'), 0)
self.assertEqual(a.index('b'), 1)
self.assertEqual(a.index('c'), 2)
self.assertEqual(a[0], 'a')
self.assertEqual(a[1], 'b')
self.assertEqual(a[2], 'c')
self.assertEqual(a.ArrayType, uint8)
a = Enumeration('bca')
self.assertEqual(a.index('b'), 0)
self.assertEqual(a.index('c'), 1)
self.assertEqual(a.index('a'), 2)
self.assertEqual(a[0], 'b')
self.assertEqual(a[1], 'c')
self.assertEqual(a[2], 'a')
a = Enumeration([1,'2'])
self.assertEqual(a.index(1), 0)
self.assertEqual(a.index('2'), 1)
self.assertRaises(KeyError, a.index, '1')
#check that it works with gaps
a = Enumeration('ab-', '-')
self.assertEqual(a.Gap, '-')
self.assertEqual(a.GapIndex, 2)
a = Enumeration(range(257)) #too big to fit in uint8
self.assertEqual(a.ArrayType, uint16)
def test_index(self):
"""Enumeration index should return first index of item"""
a = Enumeration('bca')
self.assertEqual(a.index('b'), 0)
self.assertEqual(a.index('c'), 1)
self.assertEqual(a.index('a'), 2)
def test_getitem(self):
"""Enumeration[i] should return character at i"""
a = Enumeration('bca')
self.assertEqual(a[0], 'b')
self.assertEqual(a[1], 'c')
self.assertEqual(a[2], 'a')
def test_toIndices(self):
"""Enumeration toIndices should return indices from elements"""
a = Enumeration('bca')
self.assertEqual(a.toIndices(''), [])
self.assertEqual(a.toIndices('ccabac'), [1,1,2,0,2,1])
def test_isValid(self):
"""Enumeration isValid should return True for valid sequence"""
a = Enumeration('bca')
self.assertEqual(a.isValid(''), True)
self.assertEqual(a.isValid('bbb'), True)
self.assertEqual(a.isValid('bbbaac'), True)
self.assertEqual(a.isValid('bbd'), False)
self.assertEqual(a.isValid('d'), False)
self.assertEqual(a.isValid(['a', 'b']), True)
self.assertEqual(a.isValid(['a', None]), False)
def test_fromIndices(self):
"""Enumeration fromIndices should return elements from indices"""
a = Enumeration('bca')
self.assertEqual(a.fromIndices([]), [])
self.assertEqual(a.fromIndices([1,1,2,0,2,1]), list('ccabac'))
def test_pow(self):
"""Enumeration pow should produce JointEnumeration with n copies"""
a = AminoAcids**3
self.assertEqual(a[0], (AminoAcids[0],)*3)
self.assertEqual(a[-1], (AminoAcids[-1],)*3)
self.assertEqual(len(a), len(AminoAcids)**3)
self.assertEqual(a.ArrayType, uint16)
#check that it works with gaps
a = Enumeration('a-b', '-')
b = a**3
self.assertEqual(len(b), 27)
self.assertEqual(b.Gap, ('-','-','-'))
self.assertEqual(b.GapIndex, 13)
self.assertEqual(b.ArrayType, uint8)
#check that array type is set correctly if needed
b = a**6 #too big to fit in char
self.assertEqual(b.ArrayType, uint16)
def test_mul(self):
"""Enumeration mul should produce correct JointEnumeration"""
a = DnaBases * RnaBases
self.assertEqual(len(a), 16)
self.assertEqual(a[0], ('T','U'))
self.assertEqual(a[-1], ('G','G'))
#check that it works with gaps
a = Enumeration('ab-','-')
b = Enumeration('xz','z')
x = a*b
self.assertEqual(x.Gap, ('-','z'))
self.assertEqual(x.GapIndex, 5)
self.assertEqual(len(x), 6)
self.assertEqual(x, (('a','x'),('a','z'),('b','x'),('b','z'),('-','x'),\
('-','z')))
#check that it doesn't work when only one seq has gaps
c = Enumeration('c')
x = a*c
self.assertEqual(x.Gap, None)
def test_counts(self):
"""Enumeration counts should count freqs in array"""
a = DnaBases
f = array([[0,0,1,0,0,3]])
self.assertEqual(a.counts(f), array([4,1,0,1]))
#check that it works with byte array
f = array([[0,0,1,0,0,3]], 'B')
self.assertEqual(a.counts(f), array([4,1,0,1]))
#should ignore out-of-bounds items
g = [0,4]
self.assertEqual(a.counts(g), array([1,0,0,0]))
#make sure it works for long sequences, i.e. no wraparound at 255
h = [0, 3] * 70000
self.assertEqual(a.counts(h), array([70000,0,0,70000]))
h2 = array(h).astype('B')
self.assertEqual(a.counts(h2), array([70000,0,0,70000]))
i = array([0,3] * 75000)
self.assertEqual(a.counts(i), array([75000,0,0,75000]))
#make sure it works for long _binary_ sequences, e.g. the results
#of array comparisons.
a = array([0,1,2,3]*10000)
b = array([0,0,0,0]*10000)
same = (a==b)
class CharAlphabetTests(TestCase):
"""Tests of CharAlphabets."""
def test_init(self):
"""CharAlphabet init should make correct translation tables"""
r = CharAlphabet('UCAG')
i2c, c2i = r._indices_to_chars, r._chars_to_indices
s = array([0,0,1,0,3,2], 'b').tostring()
self.assertEqual(s.translate(i2c), 'UUCUGA')
self.assertEqual('UUCUGA'.translate(c2i), '\000\000\001\000\003\002')
def test_fromString(self):
"""CharAlphabet fromString should return correct array"""
r = CharAlphabet('UCAG')
self.assertEqual(r.fromString('UUCUGA'), array([0,0,1,0,3,2],'B'))
def test_isValid(self):
"""CharAlphabet isValid should return True for valid sequence"""
a = CharAlphabet('bca')
self.assertEqual(a.isValid(''), True)
self.assertEqual(a.isValid('bbb'), True)
self.assertEqual(a.isValid('bbbaac'), True)
self.assertEqual(a.isValid('bbd'), False)
self.assertEqual(a.isValid('d'), False)
self.assertEqual(a.isValid(['a', 'b']), True)
self.assertEqual(a.isValid(['a', None]), False)
def test_fromArray(self):
"""CharAlphabet fromArray should return correct array"""
r = CharAlphabet('UCAG')
self.assertEqual(r.fromArray(array(['UUC','UGA'], 'c')), \
array([[0,0,1],[0,3,2]], 'B'))
def test_toChars(self):
"""CharAlphabet toChars should convert an input array to chars"""
r = CharAlphabet('UCAG')
c = r.toChars(array([[0,0,1],[0,3,2]], 'B'))
self.assertEqual(c, \
array(['UUC','UGA'], 'c'))
def test_toString(self):
"""CharAlphabet toString should convert an input array to string"""
r = CharAlphabet('UCAG')
self.assertEqual(r.toString(array([[0,0,1],[0,3,2]], 'B')), 'UUC\nUGA')
#should work with single seq
self.assertEqual(r.toString(array([[0,0,1,0,3,2]], 'B')), 'UUCUGA')
#should work with single seq
self.assertEqual(r.toString(array([0,0,1,0,3,2], 'B')), 'UUCUGA')
#should work with empty seq
self.assertEqual(r.toString(array([], 'B')), '')
def test_pairs(self):
"""pairs should cache the same object."""
r = CharAlphabet('UCAG')
rp = r.Pairs
self.assertEqual(len(rp), 16)
rp2 = r.Pairs
self.assertSameObj(rp, rp2)
def test_triples(self):
"""triples should cache the same object."""
r = CharAlphabet('UCAG')
rt = r.Triples
self.assertEqual(len(rt), 64)
rt2 = r.Triples
self.assertSameObj(rt, rt2)
class JointEnumerationTests(TestCase):
"""Tests of JointEnumerations."""
def test_init(self):
"""JointEnumeration init should work as expected"""
#should work for alphabet object
a = JointEnumeration([DnaBases, RnaBases])
self.assertEqual(len(a), 16)
self.assertEqual(a.Shape, (4,4))
self.assertEqual(a[0], ('T','U'))
self.assertEqual(a[-1], ('G','G'))
self.assertEqual(a._sub_enum_factors, array([[4],[1]]))
#should work for arbitrary sequences
a = JointEnumeration(['TCAG', 'UCAG'])
self.assertEqual(len(a), 16)
self.assertEqual(a[0], ('T','U'))
self.assertEqual(a[-1], ('G','G'))
self.assertEqual(a._sub_enum_factors, array([[4],[1]]))
#should work for different length sequences
a = JointEnumeration(['TCA', 'UCAG'])
self.assertEqual(a.Shape, (3,4))
self.assertEqual(len(a), 12)
self.assertEqual(a[0], ('T','U'))
self.assertEqual(a[-1], ('A','G'))
self.assertEqual(a._sub_enum_factors, \
array([[4],[1]])) #note: _not_ [3,1]
def test_toIndices(self):
"""JointEnumeration toIndices should convert tuples correctly"""
a = JointEnumeration(['TCAG','UCAG'])
i = a.toIndices([('T','U'),('G','G'),('G','G')])
self.assertEqual(i, [0, 15, 15])
def test_fromIndices(self):
"""JointEnumeration fromIndices should return correct tuples"""
a = JointEnumeration(['TCAG','UCAG'])
i = a.fromIndices([0, 15, 15])
self.assertEqual(i, [('T','U'),('G','G'),('G','G')])
def test_packArrays(self):
"""JointEnumeration packArrays should return correct array."""
a = JointEnumeration(['xyz', 'abcd', 'ef'])
v = [[0,1,2,0],[3,3,1,0], [1,1,0,0]]
result = a.packArrays(v)
self.assertEqual(result, array([7,15,18,0]))
def test_unpackArrays(self):
"""JointEnumeration unpackArrays should return correct arrays."""
a = JointEnumeration(['xyz', 'abcd', 'ef'])
v = [7,15,18,0]
result = a.unpackArrays(v)
self.assertEqual(result, array([[0,1,2,0],[3,3,1,0], [1,1,0,0]]))
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_core/test_annotation.py 000644 000765 000024 00000020663 12024702176 023164 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import unittest
from cogent import DNA, LoadSeqs
from cogent.core.annotation import Feature, Variable
from cogent.core.location import Map, Span
__author__ = "Gavin Huttley"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
def makeSampleSequence(with_gaps=False):
raw_seq = 'AACCCAAAATTTTTTGGGGGGGGGGCCCC'
cds = (15, 25)
utr = (12, 15)
if with_gaps:
raw_seq = raw_seq[:5] + '-----' +raw_seq[10:-2] + '--'
seq = DNA.makeSequence(raw_seq)
seq.addAnnotation(Feature, 'CDS', 'CDS', [cds])
seq.addAnnotation(Feature, "5'UTR", "5' UTR", [utr])
return seq
def makeSampleAlignment():
seq1 = makeSampleSequence()
seq2 = makeSampleSequence(with_gaps=True)
seqs = {'FAKE01': seq1, 'FAKE02': seq2}
aln = LoadSeqs(data = seqs)
aln.addAnnotation(Feature, 'misc_feature', 'misc', [(12,25)])
aln.addAnnotation(Feature, 'CDS', 'blue', [(15, 25)])
aln.addAnnotation(Feature, "5'UTR", 'red', [(2, 4)])
aln.addAnnotation(Feature, "LTR", "fake", [(2,15)])
return aln
class TestAnnotations(unittest.TestCase):
def setUp(self):
self.seq = makeSampleSequence()
self.aln = makeSampleAlignment()
def test_slice_seq_with_annotations(self):
newseq = self.seq[:5] + self.seq[10:]
for annot_type in ["CDS", "5'UTR"]:
orig = str(list(self.seq.getByAnnotation(annot_type))[0])
new = str(list(newseq.getByAnnotation(annot_type))[0])
assert orig == new, (annot_type, orig, new)
def test_aln_annotations(self):
"""test that annotations to alignment and its' sequences"""
aln_expecteds = {"misc_feature":{'FAKE01': 'TTTGGGGGGGGGG',
'FAKE02': 'TTTGGGGGGGGGG'},
"CDS": {'FAKE01': 'GGGGGGGGGG', 'FAKE02': 'GGGGGGGGGG'},
"5'UTR": {'FAKE01': 'CC', 'FAKE02': 'CC'},
"LTR" : {"FAKE01": "CCCAAAATTTTTT",
"FAKE02": "CCC-----TTTTT"}
}
seq_expecteds = {"CDS": {"FAKE01": "GGGGGGGGGG",
"FAKE02": "GGGGGGGGGG"},
"5'UTR": {"FAKE01": "TTT",
"FAKE02": "TTT"}}
for annot_type in ["misc_feature", "CDS", "5'UTR", "LTR"]:
observed = list(self.aln.getByAnnotation(annot_type))[0].todict()
expected = aln_expecteds[annot_type]
assert observed == expected, (annot_type, expected, observed)
if annot_type in ["misc_feature", "LTR"]:
continue # because seqs haven't been annotated with it
for name in self.aln.Names:
observed = list(self.aln.NamedSeqs[name].data.\
getByAnnotation(annot_type))[0]
observed = str(observed)
expected = seq_expecteds[annot_type][name]
assert str(observed) == expected, (annot_type, name, expected,
observed)
def test_slice_aln_with_annotations(self):
"""test that annotations of sequences and alignments survive alignment
slicing."""
aln_expecteds = {"misc_feature":{'FAKE01': 'TTTGGGGGGGGGG',
'FAKE02': 'TTTGGGGGGGGGG'},
"CDS": {'FAKE01': 'GGGGGGGGGG', 'FAKE02': 'GGGGGGGGGG'},
"5'UTR": {'FAKE01': 'CC', 'FAKE02': 'CC'},
"LTR" : {"FAKE01": "CCCTTTTT",
"FAKE02": "CCCTTTTT"}}
newaln = self.aln[:5]+self.aln[10:]
feature_list = newaln.getAnnotationsMatching("LTR")
for annot_type in ["LTR", "misc_feature", "CDS", "5'UTR"]:
feature_list = newaln.getAnnotationsMatching(annot_type)
new = newaln.getRegionCoveringAll(feature_list).getSlice().todict()
expected = aln_expecteds[annot_type]
assert expected == new, (annot_type, expected, new)
if annot_type in ["misc_feature", "LTR"]:
continue # because seqs haven't been annotated with it
for name in self.aln.Names:
orig = str(list(self.aln.getAnnotationsFromSequence(name,
annot_type))[0].getSlice())
new = str(list(newaln.getAnnotationsFromSequence(name,
annot_type))[0].getSlice())
assert orig == new, (name, annot_type, orig, new)
def test_feature_projection(self):
expecteds = {"FAKE01": "CCCAAAATTTTTT", "FAKE02": "CCC-----TTTTT"}
aln_ltr = self.aln.getAnnotationsMatching('LTR')[0]
for seq_name in ['FAKE01', 'FAKE02']:
expected = expecteds[seq_name]
seq_ltr = self.aln.projectAnnotation(seq_name, aln_ltr)
if '-' in expected:
self.assertRaises(ValueError, seq_ltr.getSlice)
seq_ltr = seq_ltr.withoutLostSpans()
expected = expected.replace('-', '')
self.assertEqual(seq_ltr.getSlice(), expected)
def test_reversecomplement(self):
"""test correct translation of annotations on reverse complement."""
aln_expecteds = {"misc_feature":{'FAKE01': 'TTTGGGGGGGGGG',
'FAKE02': 'TTTGGGGGGGGGG'},
"CDS": {'FAKE01': 'GGGGGGGGGG', 'FAKE02': 'GGGGGGGGGG'},
"5'UTR": {'FAKE01': 'CC', 'FAKE02': 'CC'},
"LTR" : {"FAKE01": "CCCAAAATTTTTT",
"FAKE02": "CCC-----TTTTT"}
}
seq_expecteds = {"CDS": {"FAKE01": "GGGGGGGGGG",
"FAKE02": "GGGGGGGGGG"},
"5'UTR": {"FAKE01": "TTT",
"FAKE02": "TTT"}}
rc = self.aln.rc()
# rc'ing an Alignment or Sequence rc's their annotations too. This means
# slicing returns the same sequence as the non-rc'd alignment/seq
for annot_type in ["misc_feature", "CDS", "5'UTR", "LTR"]:
observed = list(self.aln.getByAnnotation(annot_type))[0].todict()
expected = aln_expecteds[annot_type]
assert observed == expected, ("+", annot_type, expected, observed)
observed = list(rc.getByAnnotation(annot_type))[0].todict()
expected = aln_expecteds[annot_type]
assert observed == expected, ("-", annot_type, expected, observed)
if annot_type in ["misc_feature", "LTR"]:
continue # because seqs haven't been annotated with it
for name in self.aln.Names:
observed = list(self.aln.NamedSeqs[name].data.\
getByAnnotation(annot_type))[0]
observed = str(observed)
expected = seq_expecteds[annot_type][name]
assert str(observed) == expected, ("+", annot_type, name, expected,
observed)
observed = list(rc.NamedSeqs[name].data.\
getByAnnotation(annot_type))[0]
observed = str(observed)
expected = seq_expecteds[annot_type][name]
assert str(observed) == expected, ("-", annot_type, name, expected,
observed)
class TestMapSpans(unittest.TestCase):
"""Test attributes of Map & Spans classes critical to annotation
manipulation."""
def test_span(self):
length = 100
forward = Span(20, 30)
reverse = Span(70, 80, Reverse=True)
assert forward.reversedRelativeTo(100) == reverse
assert reverse.reversedRelativeTo(100) == forward
def test_map(self):
"""reversing a map with multiple spans should preserve span relative
order"""
forward = [Span(20,30), Span(40,50)]
fmap = Map(spans=forward, parent_length=100)
fmap_reversed = fmap.nucleicReversed()
reverse = [Span(70,80, Reverse=True), Span(50,60, Reverse=True)]
rmap = Map(spans=reverse, parent_length=100)
for i in range(2):
self.assertEquals(fmap_reversed.spans[i], rmap.spans[i])
if __name__ == '__main__':
unittest.main()
PyCogent-1.5.3/tests/test_core/test_bitvector.py 000644 000765 000024 00000125020 12024702176 023004 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of the bitvector module.
"""
from cogent.util.unit_test import TestCase, main
from cogent.core.bitvector import is_nonzero_string_char, is_nonzero_char, \
seq_to_bitstring, is_nonzero_string_int, is_nonzero_int, seq_to_bitlist,\
num_to_bitstring, bitcount, Bitvector, MutableBitvector, \
ImmutableBitvector, VectorFromCases, VectorFromMatches, VectorFromRuns, \
VectorFromSpans, VectorFromPositions, PackedBases, \
LongBitvector, ShortBitvector
import re
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Production"
class bitvectorTests(TestCase):
"""Tests of top-level functions."""
def test_is_nonzero_string_char(self):
"""is_nonzero_string_char should return '1' for anything but '0', ''"""
self.assertEqual(is_nonzero_string_char('0'), '0')
self.assertEqual(is_nonzero_string_char(''), '0')
for char in "QWERTYUIOPASDFGHJKL:ZXCGHJMK?{|!@#$%^&*()12345678":
self.assertEqual(is_nonzero_string_char(char), '1')
def test_is_nonzero_char(self):
"""is_nonzero_char should return '0' for any False item or '0'"""
zero = ['', 0, '0', [], {}, None, 0L, 0.0, False]
for z in zero:
self.assertEqual(is_nonzero_char(z), '0')
nonzero = ['z', '1', '00', ' ', 1, -1, 1e-30, [''], {'':None}, True]
for n in nonzero:
self.assertEqual(is_nonzero_char(n), '1')
def test_seq_to_bitstring(self):
"""seq_to_bitstring should provide expected results"""
zero = ['', 0, '0', [], {}, None, 0L, 0.0, False]
self.assertEqual(seq_to_bitstring(zero), '0'*9)
nonzero = ['z', '1', '00', ' ', 1, -1, 1e-30, [''], {'':None}, True]
self.assertEqual(seq_to_bitstring(nonzero), '1'*10)
self.assertEqual(seq_to_bitstring(''), '')
self.assertEqual(seq_to_bitstring('305'), '101')
self.assertEqual(seq_to_bitstring(''), '')
def test_is_nonzero_string_int(self):
"""is_nonzero_string_int should return 1 for anything but '0', ''"""
self.assertEqual(is_nonzero_string_int('0'), 0)
self.assertEqual(is_nonzero_string_int(''), 0)
for char in "QWERTYUIOPASDFGHJKL:ZXCGHJMK?{|!@#$%^&*()12345678":
self.assertEqual(is_nonzero_string_int(char), 1)
def test_is_nonzero_int(self):
"""is_nonzero_int should return 0 for any False item or '0'"""
zero = ['', 0, '0', [], {}, None, 0L, 0.0, False]
for z in zero:
self.assertEqual(is_nonzero_int(z), 0)
nonzero = ['z', '1', '00', ' ', 1, -1, 1e-30, [''], {'':None}, True]
for n in nonzero:
self.assertEqual(is_nonzero_int(n), 1)
def test_seq_to_bitlist(self):
"""seq_to_bitlist should provide expected results"""
zero = ['', 0, '0', [], {}, None, 0L, 0.0, False]
self.assertEqual(seq_to_bitlist(zero), [0]*9)
nonzero = ['z', '1', '00', ' ', 1, -1, 1e-30, [''], {'':None}, True]
self.assertEqual(seq_to_bitlist(nonzero), [1]*10)
self.assertEqual(seq_to_bitlist(''), [])
self.assertEqual(seq_to_bitlist('305'), [1,0,1])
self.assertEqual(seq_to_bitlist(''), [])
def test_number_to_bitstring(self):
"""number_to_bitstring should provide expected results"""
numbers = [0, 1, 2, 7, 8, 1024, 814715L]
for n in numbers:
self.assertEqual(num_to_bitstring(n, 0), '')
single_results = list('0101001')
for exp, num in zip(single_results, numbers):
self.assertEqual(num_to_bitstring(num, 1), exp)
three_results = ['000','001','010','111','000','000','011']
for exp, num in zip(three_results, numbers):
self.assertEqual(num_to_bitstring(num, 3), exp)
#should pad or truncate to the correct length
self.assertEqual(num_to_bitstring(814715, 20),'11000110111001111011')
self.assertEqual(num_to_bitstring(814715, 10),'1001111011')
self.assertEqual(num_to_bitstring(8, 10),'0000001000')
def test_bitcount(self):
"""bitcount should provide expected results"""
numbers = [0, 1, 2, 7, 8, 1024, 814715L]
twenty_results = [0, 1, 1, 3, 1, 1, 13]
for exp, num in zip(twenty_results, numbers):
self.assertEqual(bitcount(num, 20), exp)
self.assertEqual(bitcount(num, 20, 1), exp)
self.assertEqual(bitcount(num, 20, 0), 20 - exp)
three_results = [0,1,1,3,0,0,2]
for exp, num in zip(three_results, numbers):
self.assertEqual(bitcount(num, 3), exp)
self.assertEqual(bitcount(num, 3, 1), exp)
self.assertEqual(bitcount(num, 3, 0), 3 - exp)
for num in numbers:
self.assertEqual(bitcount(num, 0), 0)
self.assertEqual(bitcount(num, 0, 0), 0)
self.assertEqual(bitcount(num, 0, 1), 0)
class BitvectorTests(TestCase):
"""Tests of the (immutable) Bitvector class."""
def setUp(self):
"""Define a few standard strings and vectors."""
self.strings = ['', '0', '1', '00', '01', '10', '11']
self.vectors = map(Bitvector, self.strings)
def test_init(self):
"""Bitvector init should give expected results."""
self.assertEqual(Bitvector(), 0)
self.assertEqual(Bitvector('1001'), 9)
self.assertEqual(Bitvector(['1','0','0','0']), 8)
self.assertEqual(Bitvector([]), 0)
#if passing in non-sequence, must specify length
self.assertRaises(TypeError, Bitvector, 1024)
self.assertEqual(Bitvector(1024, 10), 1024)
bv = Bitvector(10, 3)
self.assertEqual(bv, 10)
self.assertEqual(len(bv), 3)
self.assertEqual(len(Bitvector('1'*1000)), 1000)
#check that initializing a bv from itself preserves length
bv2 = Bitvector(bv)
self.assertEqual(bv2, 10)
self.assertEqual(len(bv2), 3)
def test_len(self):
"""Bitvector len should match initialized length"""
self.assertEqual(len(Bitvector()), 0)
self.assertEqual(len(Bitvector('010')), 3)
self.assertEqual(len(Bitvector(1024, 5)), 5)
self.assertEqual(len(Bitvector(1024, 0)), 0)
self.assertEqual(len(Bitvector('1'*1000)), 1000)
def test_str(self):
"""Bitvector str should match expected results"""
vecs = [Bitvector(i, 0) for i in [0, 1, 2, 7, 8, 1024, 814715L]]
for v in vecs:
self.assertEqual(str(v), '')
vecs = [Bitvector(i, 1) for i in [0, 1, 2, 7, 8, 1024, 814715L,'1'*50]]
single_results = list('01010011')
for exp, vec in zip(single_results, vecs):
self.assertEqual(str(vec), exp)
vecs = [Bitvector(i, 3) for i in [0, 1, 2, 7, 8, 1024, 814715L,'1'*50]]
three_results = ['000','001','010','111','000','000','011','111']
for exp, vec in zip(three_results, vecs):
self.assertEqual(str(vec), exp)
#should pad or truncate to the correct length
self.assertEqual(str(Bitvector(814715, 20)),'11000110111001111011')
self.assertEqual(str(Bitvector(814715, 10)),'1001111011')
self.assertEqual(str(Bitvector(8, 10)),'0000001000')
self.assertEqual(str(Bitvector('1'*50)), '1'*50)
def test_or(self):
"""Bitvector A|B should return 1 for each position that is 1 in A or B"""
results = [
['', '', '', '', '', '', ''], #'' or x
['', '0', '1', '0', '0', '1', '1'], #'0' or x
['', '1', '1', '1', '1', '1', '1'], #'1' or x
['', '0', '1', '00', '01', '10', '11'], #'00' or x
['', '0', '1', '01', '01', '11', '11'], #'01' or x
['', '1', '1', '10', '11', '10', '11'], #'10' or x
['', '1', '1', '11', '11', '11', '11'], #'11' or x
]
vectors = self.vectors
for first_pos, first in enumerate(vectors):
for second_pos, second in enumerate(vectors):
self.assertEqual( str(first | second),
results[first_pos][second_pos])
#test chaining
expected = Bitvector('1110')
observed = Bitvector('1000') | Bitvector('0100') | Bitvector('0110')
self.assertEqual(observed, expected)
#test long
self.assertEqual(Bitvector('10'*50) | Bitvector('01'*50), \
Bitvector('11'*50))
def test_and(self):
"""Bitvector A&B should return 0 for each position that is 0 in A and B"""
results = [
['', '', '', '', '', '', ''], #'' and x
['', '0', '0', '0', '0', '0', '0'], #'0' and x
['', '0', '1', '0', '0', '1', '1'], #'1' and x
['', '0', '0', '00', '00', '00', '00'], #'00' and x
['', '0', '0', '00', '01', '00', '01'], #'01' and x
['', '0', '1', '00', '00', '10', '10'], #'10' and x
['', '0', '1', '00', '01', '10', '11'], #'11' and x
]
vectors = self.vectors
for first_pos, first in enumerate(vectors):
for second_pos, second in enumerate(vectors):
self.assertEqual( str(first & second),
results[first_pos][second_pos])
#test chaining
expected = Bitvector('0110')
observed = Bitvector('1110') & Bitvector('1111') & Bitvector('0111')
self.assertEqual(observed, expected)
#test long
self.assertEqual(Bitvector('10'*50) & Bitvector('11'*50), \
Bitvector('10'*50))
def test_xor(self):
"""Bitvector A^B should return 0 for each identical position in A and B"""
results = [
['', '', '', '', '', '', ''], #'' xor x
['', '0', '1', '0', '0', '1', '1'], #'0' xor x
['', '1', '0', '1', '1', '0', '0'], #'1' xor x
['', '0', '1', '00', '01', '10', '11'], #'00' xor x
['', '0', '1', '01', '00', '11', '10'], #'01' xor x
['', '1', '0', '10', '11', '00', '01'], #'10' xor x
['', '1', '0', '11', '10', '01', '00'], #'11' xor x
]
vectors = self.vectors
for first_pos, first in enumerate(vectors):
for second_pos, second in enumerate(vectors):
self.assertEqual( str(first ^ second),
results[first_pos][second_pos])
#test chaining
expected = Bitvector('0110')
observed = Bitvector('1111') ^ Bitvector('0110') ^ Bitvector('1111')
#test long
self.assertEqual(Bitvector('11'*50) ^ Bitvector('01'*50), \
Bitvector('10'*50))
def test_invert(self):
"""Bitvector ~A should return a vector exchanging 1's for 0's"""
results = map(Bitvector, ['', '1', '0', '11', '10', '01', '00'])
for data, result in zip(self.vectors, results):
self.assertEqual(~data, result)
if len(data):
self.assertNotEqual(data, result)
else:
self.assertEqual(data, result)
#test chaining
self.assertEqual(~~data, data) #inverting twice should give original
self.assertEqual(~~~data, ~data)
#test long
self.assertEqual(~Bitvector('10'*50), Bitvector('01'*50))
self.assertEqual(str(~Bitvector('10'*50)), str(Bitvector('01'*50)))
def test_getitem(self):
"""Bitvector getitem should return states at specified position(s)"""
vec_strings = ['', '0', '1', '10', '10001101', '101'*50]
vecs = map(Bitvector, vec_strings)
for vec_string, vec in zip(vec_strings, vecs):
for char, item in zip(vec_string, vec):
self.assertEqual(char, str(item))
#test some 2- and 3-item slices as well
vec = Bitvector('1001000101001')
self.assertEqual(vec[3:7], Bitvector('1000'))
self.assertEqual(vec[:4], Bitvector('1001'))
self.assertEqual(vec[7:], Bitvector('101001'))
self.assertEqual(vec[1:11:2], Bitvector('01011'))
def test_bitcount(self):
"""Bitvector bitcount should correctly count 1's or 0's"""
vec_strings = ['', '0', '1', '10', '10001101', '101'*50]
vecs = map(Bitvector, vec_strings)
one_counts = [0, 0, 1, 1, 4, 100]
zero_counts = [0, 1, 0, 1, 4, 50]
for v, o, z in zip(vecs, one_counts, zero_counts):
self.assertEqual(v.bitcount(), o)
self.assertEqual(v.bitcount(1), o)
self.assertEqual(v.bitcount(0), z)
def test_repr(self):
"""Bitvector repr should look like a normal object"""
v = Bitvector(3, 10)
v_id = str(hex(id(v)))
expected = '>> from cogent import DNA
>>> from cogent.core.annotation import Feature
>>> s = DNA.makeSequence("AAGAAGAAGACCCCCAAAAAAAAAATTTTTTTTTTAAAAAAAAAAAAA",
... Name="Orig")
>>> exon1 = s.addAnnotation(Feature, 'exon', 'fred', [(10,15)])
>>> exon2 = s.addAnnotation(Feature, 'exon', 'trev', [(30,40)])
The corresponding sequence can be extracted either with slice notation or by asking the feature to do it, since the feature knows what sequence it belongs to.
.. doctest::
>>> s[exon1]
DnaSequence(CCCCC)
>>> exon1.getSlice()
DnaSequence(CCCCC)
Usually the only way to get a ``Feature`` object like ``exon1`` is to ask the sequence for it. There is one method for querying annotations by type and optionally by name:
.. doctest::
>>> exons = s.getAnnotationsMatching('exon')
>>> print exons
[exon "fred" at [10:15]/48, exon "trev" at [30:40]/48]
If the sequence does not have a matching feature you get back an empty list, and slicing the sequence with that returns a sequence of length 0.
.. doctest::
>>> dont_exist = s.getAnnotationsMatching('dont_exist')
>>> dont_exist
[]
>>> s[dont_exist]
DnaSequence()
To construct a pseudo-feature covering (or excluding) multiple features, use ``getRegionCoveringAll``:
.. doctest::
>>> print s.getRegionCoveringAll(exons)
region "exon" at [10:15, 30:40]/48
>>> print s.getRegionCoveringAll(exons).getShadow()
region "not exon" at [0:10, 15:30, 40:48]/48
eg: all the exon sequence:
.. doctest::
>>> s.getRegionCoveringAll(exons).getSlice()
DnaSequence(CCCCCTT... 15)
or with slice notation:
.. doctest::
>>> s[exon1, exon2]
DnaSequence(CCCCCTT... 15)
Though ``.getRegionCoveringAll`` also guarantees no overlaps within the result, slicing does not:
.. doctest::
>>> print s.getRegionCoveringAll(exons+exons)
region "exon" at [10:15, 30:40]/48
>>> s[exon1, exon1, exon1, exon1, exon1]
Traceback (most recent call last):
ValueError: Uninvertable. Overlap: 10 < 15
You can use features, maps, slices or integers, but non-monotonic slices are not allowed:
.. doctest::
>>> s[15:20, 5:16]
Traceback (most recent call last):
ValueError: Uninvertable. Overlap: 15 < 16
Features are themselves sliceable:
.. doctest::
>>> exon1[0:3].getSlice()
DnaSequence(CCC)
When sequences are concatenated they keep their (non-overlapping) annotations:
.. doctest::
>>> c = s[exon1[4:]]+s
>>> print len(c)
49
>>> for feat in c.annotations:
... print feat
...
exon "fred" at [-4-, 0:1]/49
exon "fred" at [11:16]/49
exon "trev" at [31:41]/49
Since features know their parents you can't use a feature from one sequence to slice another:
.. doctest::
>>> print c[exon1]
Traceback (most recent call last):
ValueError: Can't map exon "fred" at [10:15]/48 onto ...
Features are generally attached to the thing they annotate, but in those cases where a free-floating feature is created it can later be attached:
.. doctest::
>>> len(s.annotations)
2
>>> region = s.getRegionCoveringAll(exons)
>>> len(s.annotations)
2
>>> region.attach()
>>> len(s.annotations)
3
>>> region.detach()
>>> len(s.annotations)
2
When dealing with sequences that can be reverse complemented (e.g. ``DnaSequence``) features are **not** reversed. Features are considered to have strand specific meaning (.e.g CDS, exons) and so stay on their original strands. We create a sequence with a CDS that spans multiple exons, and show that after getting the reverse complement we have exactly the same result from getting the CDS annotation.
.. doctest::
>>> plus = DNA.makeSequence("AAGGGGAAAACCCCCAAAAAAAAAATTTTTTTTTTAAA",
... Name="plus")
>>> plus_cds = plus.addAnnotation(Feature, 'CDS', 'gene',
... [(2,6),(10,15),(25,35)])
>>> print plus_cds.getSlice()
GGGGCCCCCTTTTTTTTTT
>>> minus = plus.rc()
>>> minus_cds = minus.getAnnotationsMatching('CDS')[0]
>>> print minus_cds.getSlice()
GGGGCCCCCTTTTTTTTTT
Sequence features can be accessed via a containing ``Alignment``:
.. doctest::
>>> from cogent import LoadSeqs
>>> aln = LoadSeqs(data=[['x','-AAAAAAAAA'], ['y','TTTT--TTTT']])
>>> print aln
>x
-AAAAAAAAA
>y
TTTT--TTTT
>>> exon = aln.getSeq('x').addAnnotation(Feature, 'exon', 'fred', [(3,8)])
>>> aln_exons = aln.getAnnotationsFromSequence('x', 'exon')
>>> aln_exons = aln.getAnnotationsFromAnySequence('exon')
But these will be returned as **alignment** features with locations in alignment coordinates.
.. doctest::
>>> print exon
exon "fred" at [3:8]/9
>>> print aln_exons[0]
exon "fred" at [4:9]/10
>>> print aln_exons[0].getSlice()
>x
AAAAA
>y
--TTT
>>> aln_exons[0].attach()
>>> len(aln.annotations)
1
Similarly alignment features can be projected onto the aligned sequences, where they may end up falling across gaps:
.. doctest::
>>> exons = aln.getProjectedAnnotations('y', 'exon')
>>> print exons
[exon "fred" at [-2-, 4:7]/8]
>>> print aln.getSeq('y')[exons[0].map.withoutGaps()]
TTT
We copy the annotations from another sequence,
.. doctest::
>>> aln = LoadSeqs(data=[['x', '-AAAAAAAAA'], ['y', 'TTTT--CCCC']])
>>> s = DNA.makeSequence("AAAAAAAAA", Name="x")
>>> exon = s.addAnnotation(Feature, 'exon', 'fred', [(3,8)])
>>> exon = aln.getSeq('x').copyAnnotations(s)
>>> aln_exons = list(aln.getAnnotationsFromSequence('x', 'exon'))
>>> print aln_exons
[exon "fred" at [4:9]/10]
even if the name is different.
.. doctest::
>>> exon = aln.getSeq('y').copyAnnotations(s)
>>> aln_exons = list(aln.getAnnotationsFromSequence('y', 'exon'))
>>> print aln_exons
[exon "fred" at [3:4, 6:10]/10]
>>> print aln[aln_exons]
>x
AAAAA
>y
TCCCC
If the feature lies outside the sequence being copied to, you get a lost span
.. doctest::
>>> aln = LoadSeqs(data=[['x', '-AAAA'], ['y', 'TTTTT']])
>>> seq = DNA.makeSequence('CCCCCCCCCCCCCCCCCCCC', 'x')
>>> exon = seq.addFeature('exon', 'A', [(5,8)])
>>> aln.getSeq('x').copyAnnotations(seq)
>>> copied = list(aln.getAnnotationsFromSequence('x', 'exon'))
>>> copied
[exon "A" at [5:5, -4-]/5]
>>> copied[0].getSlice()
2 x 4 text alignment: x[----], y[----]
You can copy to a sequence with a different name, in a different alignment if the feature lies within the length
.. doctest::
>>> aln = LoadSeqs(data=[['x', '-AAAAAAAAA'], ['y', 'TTTT--TTTT']])
>>> seq = DNA.makeSequence('CCCCCCCCCCCCCCCCCCCC', 'x')
>>> match_exon = seq.addFeature('exon', 'A', [(5,8)])
>>> aln.getSeq('y').copyAnnotations(seq)
>>> copied = list(aln.getAnnotationsFromSequence('y', 'exon'))
>>> copied
[exon "A" at [7:10]/10]
If the sequence is shorter, again you get a lost span.
.. doctest::
>>> aln = LoadSeqs(data=[['x', '-AAAAAAAAA'], ['y', 'TTTT--TTTT']])
>>> diff_len_seq = DNA.makeSequence('CCCCCCCCCCCCCCCCCCCCCCCCCCCC', 'x')
>>> nonmatch = diff_len_seq.addFeature('repeat', 'A', [(12,14)])
>>> aln.getSeq('y').copyAnnotations(diff_len_seq)
>>> copied = list(aln.getAnnotationsFromSequence('y', 'repeat'))
>>> copied
[repeat "A" at [10:10, -6-]/10]
We consider cases where there are terminal gaps.
.. doctest::
>>> aln = LoadSeqs(data=[['x', '-AAAAAAAAA'], ['y', '------TTTT']])
>>> exon = aln.getSeq('x').addFeature('exon', 'fred', [(3,8)])
>>> aln_exons = list(aln.getAnnotationsFromSequence('x', 'exon'))
>>> print aln_exons
[exon "fred" at [4:9]/10]
>>> print aln_exons[0].getSlice()
>x
AAAAA
>y
--TTT
>>> aln = LoadSeqs(data=[['x', '-AAAAAAAAA'], ['y', 'TTTT--T---']])
>>> exon = aln.getSeq('x').addFeature('exon', 'fred', [(3,8)])
>>> aln_exons = list(aln.getAnnotationsFromSequence('x', 'exon'))
>>> print aln_exons[0].getSlice()
>x
AAAAA
>y
--T--
In this case, only those residues included within the feature are covered - note the omission of the T in ``y`` opposite the gap in ``x``.
.. doctest::
>>> aln = LoadSeqs(data=[['x', 'C-CCCAAAAA'], ['y', '-T----TTTT']],
... moltype=DNA)
>>> print aln
>x
C-CCCAAAAA
>y
-T----TTTT
>>> exon = aln.getSeq('x').addFeature('exon', 'ex1', [(0,4)])
>>> print exon
exon "ex1" at [0:4]/9
>>> print exon.getSlice()
CCCC
>>> aln_exons = list(aln.getAnnotationsFromSequence('x', 'exon'))
>>> print aln_exons
[exon "ex1" at [0:1, 2:5]/10]
>>> print aln_exons[0].getSlice()
>x
CCCC
>y
----
``Feature.asOneSpan()``, is applied to the exon that straddles the gap in ``x``. The result is we preserve that feature.
.. doctest::
>>> print aln_exons[0].asOneSpan().getSlice()
>x
C-CCC
>y
-T---
These properties also are consistently replicated with reverse complemented sequences.
.. doctest::
>>> aln_rc = aln.rc()
>>> rc_exons = list(aln_rc.getAnnotationsFromAnySequence('exon'))
>>> print aln_rc[rc_exons] # not using asOneSpan, so gap removed from x
>x
CCCC
>y
----
>>> print aln_rc[rc_exons[0].asOneSpan()]
>x
C-CCC
>y
-T---
Features can provide their coordinates, useful for custom analyses.
.. doctest::
>>> all_exons = aln.getRegionCoveringAll(aln_exons)
>>> coords = all_exons.getCoordinates()
>>> assert coords == [(0,1),(2,5)]
Annotated regions can be masked (observed sequence characters replaced by another), either through the sequence on which they reside or by projection from the alignment. Note that ``mask_char`` must be a valid character for the sequence ``MolType``. Either the features (multiple can be named), or their shadow, can be masked.
We create an alignment with a sequence that has two different annotation types.
.. doctest::
>>> aln = LoadSeqs(data=[['x', 'C-CCCAAAAAGGGAA'], ['y', '-T----TTTTG-GTT']])
>>> print aln
>x
C-CCCAAAAAGGGAA
>y
-T----TTTTG-GTT
>>> exon = aln.getSeq('x').addFeature('exon', 'norwegian', [(0,4)])
>>> print exon.getSlice()
CCCC
>>> repeat = aln.getSeq('x').addFeature('repeat', 'blue', [(9,12)])
>>> print repeat.getSlice()
GGG
>>> repeat = aln.getSeq('y').addFeature('repeat', 'frog', [(5,7)])
>>> print repeat.getSlice()
GG
Each sequence should correctly mask either the single feature, it's shadow, or the multiple features, or shadow.
.. doctest::
>>> print aln.getSeq('x').withMaskedAnnotations('exon', mask_char='?')
????AAAAAGGGAA
>>> print aln.getSeq('x').withMaskedAnnotations('exon', mask_char='?',
... shadow=True)
CCCC??????????
>>> print aln.getSeq('x').withMaskedAnnotations(['exon', 'repeat'],
... mask_char='?')
????AAAAA???AA
>>> print aln.getSeq('x').withMaskedAnnotations(['exon', 'repeat'],
... mask_char='?', shadow=True)
CCCC?????GGG??
>>> print aln.getSeq('y').withMaskedAnnotations('exon', mask_char='?')
TTTTTGGTT
>>> print aln.getSeq('y').withMaskedAnnotations('repeat', mask_char='?')
TTTTT??TT
>>> print aln.getSeq('y').withMaskedAnnotations('repeat', mask_char='?',
... shadow=True)
?????GG??
The same methods can be applied to annotated Alignment's.
.. doctest::
>>> print aln.withMaskedAnnotations('exon', mask_char='?')
>x
?-???AAAAAGGGAA
>y
-T----TTTTG-GTT
>>> print aln.withMaskedAnnotations('exon', mask_char='?', shadow=True)
>x
C-CCC??????????
>y
-?----?????-???
>>> print aln.withMaskedAnnotations('repeat', mask_char='?')
>x
C-CCCAAAAA???AA
>y
-T----TTTT?-?TT
>>> print aln.withMaskedAnnotations('repeat', mask_char='?', shadow=True)
>x
?-????????GGG??
>y
-?----????G-G??
>>> print aln.withMaskedAnnotations(['repeat', 'exon'], mask_char='?')
>x
?-???AAAAA???AA
>y
-T----TTTT?-?TT
>>> print aln.withMaskedAnnotations(['repeat', 'exon'],shadow=True)
>x
C-CCC?????GGG??
>y
-?----????G-G??
It shouldn't matter whether annotated coordinates are entered separately, or as a series.
.. doctest::
>>> data = [['human', 'CGAAACGTTT'], ['mouse', 'CTAAACGTCG']]
>>> as_series = LoadSeqs(data = data)
>>> as_items = LoadSeqs(data = data)
We add annotations to the sequences as a series.
.. doctest::
>>> as_series.getSeq('human').addFeature('cpgsite', 'cpg', [(0,2), (5,7)])
cpgsite "cpg" at [0:2, 5:7]/10
>>> as_series.getSeq('mouse').addFeature('cpgsite', 'cpg', [(5,7), (8,10)])
cpgsite "cpg" at [5:7, 8:10]/10
We add the annotations to the sequences one segment at a time.
.. doctest::
>>> as_items.getSeq('human').addFeature('cpgsite', 'cpg', [(0,2)])
cpgsite "cpg" at [0:2]/10
>>> as_items.getSeq('human').addFeature('cpgsite', 'cpg', [(5,7)])
cpgsite "cpg" at [5:7]/10
>>> as_items.getSeq('mouse').addFeature('cpgsite', 'cpg', [(5,7)])
cpgsite "cpg" at [5:7]/10
>>> as_items.getSeq('mouse').addFeature('cpgsite', 'cpg', [(8,10)])
cpgsite "cpg" at [8:10]/10
These different constructions should generate the same output.
.. doctest::
>>> serial = as_series.withMaskedAnnotations(['cpgsite'])
>>> print serial
>human
??AAA??TTT
>mouse
CTAAA??T??
>>> itemwise = as_items.withMaskedAnnotations(['cpgsite'])
>>> print itemwise
>human
??AAA??TTT
>mouse
CTAAA??T??
Annotations should be correctly masked, whether the sequence has been reverse complemented or not. We use the plus/minus strand CDS containing sequences created above.
.. doctest::
>>> print plus.withMaskedAnnotations("CDS")
AA????AAAA?????AAAAAAAAAA??????????AAA
>>> print minus.withMaskedAnnotations("CDS")
TTT??????????TTTTTTTTTT?????TTTT????TT
.. todo::
Not documented, Source features.
PyCogent-1.5.3/tests/test_core/test_genetic_code.py 000644 000765 000024 00000032550 12024702176 023420 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
""" Unit tests for Genetic Code classes.
"""
from cogent import RNA, DNA
from cogent.core.genetic_code import GeneticCode, GeneticCodeInitError,\
InvalidCodonError, GeneticCodes
from cogent.util.unit_test import TestCase, main
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Greg Caporaso", "Rob Knight", "Peter Maxwell"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Greg Caporaso"
__email__ = "caporaso@colorado.edu"
__status__ = "Production"
class GeneticCodeTests(TestCase):
"""Tests of the GeneticCode class."""
def setUp(self):
"""Set up some standard genetic code representations."""
self.SGC = \
"FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG"
self.mt = \
"FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIMMTTTTNNKKSS**VVVVAAAADDEEGGGG"
self.AllG= \
"GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG"
self.WrongLength= [
"GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG"
"",
"GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG",
]
self.NcbiStandard = [
'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG',
1,
'Standard Nuclear',
'---M---------------M---------------M----------------------------',
]
def test_init(self):
"""GeneticCode init should work with correct-length sequences"""
sgc = GeneticCode(self.SGC)
self.assertEqual(sgc['UUU'], 'F')
mt = GeneticCode(self.mt)
self.assertEqual(mt['UUU'], 'F')
allg = GeneticCode(self.AllG)
self.assertEqual(allg['UUU'], 'G')
for i in self.WrongLength:
self.assertRaises(GeneticCodeInitError, GeneticCode, i)
def test_standard_code(self):
"""Standard genetic code from NCBI should have correct properties"""
sgc = GeneticCode(*self.NcbiStandard)
self.assertEqual(sgc.CodeSequence,
'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG')
self.assertEqual(sgc.StartCodonSequence,
'---M---------------M---------------M----------------------------')
self.assertEqual(sgc.StartCodons, {'TTG':'M', 'CTG':'M', 'ATG':'M'})
self.assertEqual(sgc.ID, 1)
self.assertEqual(sgc.Name, 'Standard Nuclear')
self.assertEqual(sgc['UUU'], 'F')
self.assertEqual(sgc.isStart('ATG'), True)
self.assertEqual(sgc.isStart('AAA'), False)
self.assertEqual(sgc.isStop('UAA'), True)
self.assertEqual(sgc.isStop('AAA'), False)
self.assertEqual(len(sgc.SenseCodons), 61)
self.assertContains(sgc.SenseCodons, 'AAA')
self.assertNotContains(sgc.SenseCodons, 'TGA')
def test_standard_code_lookup(self):
"""GeneticCodes should hold codes keyed by id as string and number"""
sgc_new = GeneticCode(*self.NcbiStandard)
sgc_number = GeneticCodes[1]
sgc_string = GeneticCodes['1']
for sgc in sgc_new, sgc_number, sgc_string:
self.assertEqual(sgc.CodeSequence,
'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG')
self.assertEqual(sgc.StartCodonSequence,
'---M---------------M---------------M----------------------------')
self.assertEqual(sgc.StartCodons, {'TTG':'M', 'CTG':'M', 'ATG':'M'})
self.assertEqual(sgc.ID, 1)
self.assertEqual(sgc.Name, 'Standard Nuclear')
self.assertEqual(sgc['TTT'], 'F')
self.assertEqual(sgc.isStart('ATG'), True)
self.assertEqual(sgc.isStart('AAA'), False)
self.assertEqual(sgc.isStop('TAA'), True)
self.assertEqual(sgc.isStop('AAA'), False)
mtgc = GeneticCodes[2]
self.assertEqual(mtgc.Name, 'Vertebrate Mitochondrial')
self.assertEqual(mtgc.isStart('AUU'), True)
self.assertEqual(mtgc.isStop('UGA'), False)
self.assertEqual(sgc_new.changes(mtgc), {'AGA':'R*', 'AGG':'R*',
'ATA':'IM', 'TGA':'*W'})
self.assertEqual(mtgc.changes(sgc_new), {'AGA':'*R', 'AGG':'*R',
'ATA':'MI', 'TGA':'W*'})
self.assertEqual(mtgc.changes(mtgc), {})
self.assertEqual(mtgc.changes(
'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'),
{'AGA':'*R', 'AGG':'*R', 'ATA':'MI', 'TGA':'W*'})
def test_str(self):
"""GeneticCode str() should return its code string"""
code_strings = self.SGC, self.mt, self.AllG
codes = map(GeneticCode, code_strings)
for code, string in zip(codes, code_strings):
self.assertEqual(str(code), string)
#check an example directly in case strings are bad
self.assertEqual(str(self.SGC), \
"FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG")
def test_cmp(self):
"""GeneticCode cmp() should act on code strings"""
sgc_1 = GeneticCode(self.SGC)
sgc_2 = GeneticCode(self.SGC)
self.assertEqual(sgc_1 is sgc_2, False) #ensure different objects
#self.assertNotEqual(sgc_1, sgc_2) # GREG
self.assertEqual(sgc_1, sgc_2)
mtgc = GeneticCode(self.mt)
self.assertNotEqual(sgc_1, mtgc)
def test_getitem_codon(self):
"""GeneticCode getitem should return amino acid for codon"""
#specific checks of a particular codon in the standard code
variant_codons = ['AUU', 'AUU', 'AUU', 'ATT', 'ATU', 'ATU']
sgc = GeneticCode(self.SGC)
for i in variant_codons:
self.assertEqual(sgc[i], 'I')
#full check for the standard code
codons = [a+b+c for a in 'UCAG' for b in 'TCAG' for c in 'UCAG']
for codon, aa in zip(codons, self.SGC):
self.assertEqual(sgc[codon], aa)
#full check for another code
allg = GeneticCode(self.AllG)
for codon, aa in zip(codons, self.AllG):
self.assertEqual(allg[codon], aa)
#check that degenerate codon returns X
self.assertEqual(sgc['NNN'], 'X')
def test_getitem_aa(self):
"""GeneticCode getitem should return codon set for aa"""
#for all G, should return all the codons (in some order)
allg = GeneticCode(self.AllG)
codons = [a+b+c for a in 'TCAG' for b in 'TCAG' for c in 'TCAG']
g_codons = allg['G']
codons_copy = codons[:]
self.assertEqual(g_codons, codons_copy)
#check some known cases in the standard genetic code
sgc = GeneticCode(self.SGC)
exp_ile = ['ATT', 'ATC', 'ATA']
obs_ile = sgc['I']
self.assertEqual(obs_ile, exp_ile)
exp_arg = ['AGA', 'AGG', 'CGT', 'CGC', 'CGA', 'CGG']
obs_arg = sgc['R']
self.assertEqual(obs_ile, exp_ile)
exp_leu = ['TTA','TTG','CTT','CTC','CTA','CTG']
obs_leu = sgc['L']
self.assertEqual(obs_leu, exp_leu)
exp_met = ['ATG']
obs_met = sgc['M']
self.assertEqual(obs_met, exp_met)
#unknown aa should return []
self.assertEqual(sgc['U'], [])
def test_getitem_invalid_length(self):
"""GeneticCode getitem should raise InvalidCodonError on wrong length"""
sgc = GeneticCode(self.SGC)
self.assertRaises(InvalidCodonError, sgc.__getitem__, 'AAAA')
self.assertRaises(InvalidCodonError, sgc.__getitem__, 'AA')
def test_Blocks(self):
"""GeneticCode Blocks should return correct list"""
sgc = GeneticCode(self.SGC)
exp_blocks = [
['TTT', 'TTC',],
['TTA', 'TTG',],
['TCT','TCC','TCA','TCG'],
['TAT','TAC'],
['TAA','TAG'],
['TGT','TGC'],
['TGA'],
['TGG'],
['CTT','CTC','CTA','CTG'],
['CCT','CCC','CCA','CCG'],
['CAT','CAC'],
['CAA','CAG'],
['CGT','CGC','CGA','CGG'],
['ATT','ATC'],
['ATA',],
['ATG',],
['ACT','ACC','ACA','ACG'],
['AAT','AAC'],
['AAA','AAG'],
['AGT','AGC'],
['AGA','AGG'],
['GTT','GTC','GTA','GTG'],
['GCT','GCC','GCA','GCG'],
['GAT','GAC'],
['GAA','GAG'],
['GGT','GGC','GGA','GGG'],
]
self.assertEqual(sgc.Blocks, exp_blocks)
def test_Anticodons(self):
"""GeneticCode Anticodons should return correct list"""
sgc = GeneticCode(self.SGC)
exp_anticodons = {
'F': ['AAA', 'GAA',],
'L': ['TAA', 'CAA', 'AAG','GAG','TAG','CAG'],
'Y': ['ATA','GTA'],
'*': ['TTA','CTA', 'TCA'],
'C': ['ACA','GCA'],
'W': ['CCA'],
'S': ['AGA','GGA','TGA','CGA','ACT','GCT'],
'P': ['AGG','GGG','TGG','CGG'],
'H': ['ATG','GTG'],
'Q': ['TTG','CTG'],
'R': ['ACG','GCG','TCG','CCG','TCT','CCT'],
'I': ['AAT','GAT','TAT'],
'M': ['CAT',],
'T': ['AGT','GGT','TGT','CGT'],
'N': ['ATT','GTT'],
'K': ['TTT','CTT'],
'V': ['AAC','GAC','TAC','CAC'],
'A': ['AGC','GGC','TGC','CGC'],
'D': ['ATC','GTC'],
'E': ['TTC','CTC'],
'G': ['ACC','GCC','TCC','CCC'],
}
self.assertEqual(sgc.Anticodons, exp_anticodons)
def test_translate(self):
"""GeneticCode translate should return correct amino acid string"""
allg = GeneticCode(self.AllG)
sgc = GeneticCode(self.SGC)
mt = GeneticCode(self.mt)
seq = 'AUGCAUGACUUUUGA'
# . . . . . markers for codon start
self.assertEqual(allg.translate(seq), 'GGGGG')
self.assertEqual(allg.translate(seq, 1), 'GGGG')
self.assertEqual(allg.translate(seq, 2), 'GGGG')
self.assertEqual(allg.translate(seq, 3), 'GGGG')
self.assertEqual(allg.translate(seq, 4), 'GGG')
self.assertEqual(allg.translate(seq, 12), 'G')
self.assertEqual(allg.translate(seq, 14), '')
self.assertRaises(ValueError, allg.translate, seq, 15)
self.assertRaises(ValueError, allg.translate, seq, 20)
self.assertEqual(sgc.translate(seq), 'MHDF*')
self.assertEqual(sgc.translate(seq, 3), 'HDF*')
self.assertEqual(sgc.translate(seq, 6), 'DF*')
self.assertEqual(sgc.translate(seq, 9), 'F*')
self.assertEqual(sgc.translate(seq, 12), '*')
self.assertEqual(sgc.translate(seq, 14), '')
#check shortest translatable sequences
self.assertEqual(sgc.translate('AAA'), 'K')
self.assertEqual(sgc.translate(''), '')
#check that different code gives different results
self.assertEqual(mt.translate(seq), 'MHDFW')
#check translation with invalid codon(s)
self.assertEqual(sgc.translate('AAANNNCNC123UUU'), 'KXXXF')
def test_sixframes(self):
"""GeneticCode sixframes should provide six-frame translation"""
class fake_rna(str):
"""Fake RNA class with reverse-complement"""
def __new__(cls, seq, rev):
return str.__new__(cls, seq)
def __init__(self, seq, rev):
self.seq = seq
self.rev = rev
def rc(self):
return self.rev
test_rna = fake_rna('AUGCUAACAUAAA', 'UUUAUGUUAGCAU')
# . . . . . . . . . .
sgc = GeneticCode(self.SGC)
self.assertEqual(sgc.sixframes(test_rna), [
'MLT*', 'C*HK', 'ANI', 'FMLA', 'LC*H', 'YVS'])
# should also actually work with an RNA or DNA sequence!!!
test_rna = RNA.makeSequence('AUGCUAACAUAAA')
self.assertEqual(sgc.sixframes(test_rna), [
'MLT*', 'C*HK', 'ANI', 'FMLA', 'LC*H', 'YVS'])
def test_stop_indexes(self):
"""should return stop codon indexes for a specified frame"""
sgc = GeneticCode(self.SGC)
seq = DNA.makeSequence('ATGCTAACATAAA')
expected = [[9], [4], []]
for frame, expect in enumerate(expected):
got = sgc.getStopIndices(seq, start=frame)
self.assertEqual(got, expect)
def test_Synonyms(self):
"""GeneticCode Synonyms should return aa -> codon set mapping."""
expected_synonyms = {
'A':['GCT','GCC','GCA','GCG'],
'C':['TGT', 'TGC'],
'D':['GAT', 'GAC'],
'E':['GAA','GAG'],
'F':['TTT','TTC'],
'G':['GGT','GGC','GGA','GGG'],
'H':['CAT','CAC'],
'I':['ATT','ATC','ATA'],
'K':['AAA','AAG'],
'L':['TTA','TTG','CTT','CTC','CTA','CTG'],
'M':['ATG'],
'N':['AAT','AAC'],
'P':['CCT','CCC','CCA','CCG'],
'Q':['CAA','CAG'],
'R':['AGA','AGG','CGT','CGC','CGA','CGG'],
'S':['TCT','TCC','TCA','TCG','AGT','AGC'],
'T':['ACT','ACC','ACA','ACG'],
'V':['GTT','GTC','GTA','GTG'],
'W':['TGG'],
'Y':['TAT','TAC'],
'*':['TAA','TAG', 'TGA'],
}
obs_synonyms = GeneticCode(self.SGC).Synonyms
#note that the lists will be arbitrary-order
for i in expected_synonyms:
self.assertEqualItems(obs_synonyms[i], expected_synonyms[i])
#Run tests if called from command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_core/test_info.py 000644 000765 000024 00000011645 12024702176 021745 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for Info class and associated objects (DbRef, DbRefs, etc.).
"""
from cogent.util.unit_test import TestCase, main
from cogent.core.info import DbRef, DbRefs, Info, _make_list
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class DbRefTests(TestCase):
"""Tests of the DbRef object."""
def setUp(self):
"""Define a standard DbRef object"""
self.data = dict(Accession='xyz',Db='abc',Name='qwe',Description='blah',
Data = range(20))
self.db = DbRef(**self.data)
def test_init_minimal(self):
"""DbRef minimal init should fill fields as expected"""
d = DbRef('abc')
self.assertEqual(d.Accession, 'abc')
self.assertEqual(d.Db, '')
self.assertEqual(d.Name, '')
self.assertEqual(d.Description, '')
self.assertEqual(d.Data, None)
#empty init not allowed
self.assertRaises(TypeError, DbRef)
def test_init(self):
"""DbRef init should insert correct data"""
for attr, val in self.data.items():
self.assertEqual(getattr(self.db, attr), val)
def test_str(self):
"""DbRef str should be the same as the accession str"""
self.assertEqual(str(self.db), 'xyz')
self.db.Accession = 12345
self.assertEqual(str(self.db), '12345')
def test_int(self):
"""DbRef int should be the same as the accession int"""
self.assertRaises(ValueError, int, self.db)
self.db.Accession = '12345'
self.assertEqual(int(self.db), 12345)
def test_cmp(self):
"""DbRef cmp should first try numeric, then alphabetic, cmp."""
self.assertLessThan(DbRef('abc'), DbRef('xyz'))
self.assertEqual(DbRef('abc'), DbRef('abc'))
self.assertGreaterThan(DbRef('123'), DbRef('14'))
self.assertLessThan(DbRef('123'), DbRef('abc'))
#check that it ignores other attributes
self.assertEqual(DbRef('x','y','z','a','b'), DbRef('x'))
class infoTests(TestCase):
"""Tests of top-level functions."""
def test_make_list(self):
"""_make_list should always return a list"""
self.assertEqual(_make_list('abc'), ['abc'])
self.assertEqual(_make_list([]), [])
self.assertEqual(_make_list(None), [None])
self.assertEqual(_make_list({'x':'y'}), [{'x':'y'}])
self.assertEqual(_make_list([1,2,3]), [1,2,3])
class DbRefsTests(TestCase):
"""Tests of the DbRefs class."""
def test_init_empty(self):
"""DbRefs empty init should work as expected"""
self.assertEqual(DbRefs(), {})
def test_init_data(self):
"""DbRefs init with data should produce expected results"""
d = DbRefs({'GenBank':'ab', 'GO':(3,44), 'PDB':['asdf','ghjk']})
self.assertEqual(d,{'GenBank':['ab'],'GO':[3,44],'PDB':['asdf','ghjk']})
d.GenBank = 'xyz'
self.assertEqual(d['GenBank'], ['xyz'])
class InfoTests(TestCase):
"""Tests of the Info class."""
def test_init_empty(self):
"""Info empty init should work as expected"""
d = Info()
self.assertEqual(len(d), 1)
self.assertContains(d, 'Refs')
self.assertEqual(d.Refs, DbRefs())
self.assertTrue(isinstance(d.Refs, DbRefs))
def test_init_data(self):
"""Info init with data should put items in correct places"""
#need to check init, setting, and resetting of attributes that belong
#in the Info object and attributes that belong in Info.Refs. Also need
#to check __getitem__, __setitem__, and __contains__.
d = Info({'x':3, 'GO':12345})
self.assertEqual(d.x, 3)
self.assertEqual(d.GO, [12345])
self.assertEqual(d.Refs.GO, [12345])
try:
del d.Refs
except AttributeError:
pass
else:
raise Exception, "Failed to prevent deletion of required key Refs"""
d.GenBank = ('qaz', 'wsx')
self.assertEqual(d.GenBank, ['qaz', 'wsx'])
self.assertContains(d.Refs, 'GenBank')
self.assertContains(d, 'GenBank')
d.GenBank = 'xyz'
self.assertEqual(d.GenBank, ['xyz'])
self.assertSameObj(d.GenBank, d.Refs.GenBank)
d.GO = 'x'
self.assertEqual(d.GO, ['x'])
d.GO.append('y')
self.assertEqual(d.GO, ['x', 'y'])
d.ZZZ = 'zzz'
self.assertEqual(d.ZZZ, 'zzz')
self.assertNotContains(d.Refs, 'ZZZ')
self.assertNotContains(d, 'XXX')
self.assertEqual(d.XXX, None)
def test_identity(self):
"""Info should get its own new Refs when created"""
i = Info()
j = Info()
self.assertNotSameObj(i, j)
self.assertNotSameObj(i.Refs, j.Refs)
#run the following if invoked from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_core/test_location.py 000644 000765 000024 00000045576 12024702176 022634 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for Range, Span and Point classes.
NOTE: Map not currently tested.
"""
from cogent.util.unit_test import TestCase, main
from cogent.core.location import Span, Range, Point, RangeFromString
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class SpanTests(TestCase):
"""Tests of the Span object."""
def setUp(self):
"""Define some standard Spans"""
self.empty = Span(0, 0)
self.full = Span(35, 30) #will convert to (30, 35) internally
self.overlapping = Span(32, 36)
self.inside = Span(31, 32)
self.before = Span(25, 30)
self.after = Span(35, 40)
self.reverse = Span(30, 35, Reverse=True)
self.spans_zero = Span(-5, 5)
def test_init(self):
"""Span object should init with Start, End, and Length"""
s = Span(0)
self.assertEqual(s.Start, 0)
self.assertEqual(s.End, 1)
self.assertEqual(s.Reverse, False)
#to get an empty interval, must specify start and end explicitly
t = Span(0, 0)
self.assertEqual(t.Start, 0)
self.assertEqual(t.End, 0)
self.assertEqual(t.Reverse, False)
#should be able to specify direction also
u = Span(5, 15, Reverse=True)
self.assertEqual(u.Start, 5)
self.assertEqual(u.End, 15)
self.assertEqual(u.Reverse, True)
#should be able to init from another span
v = Span(u)
self.assertEqual(v.Start, 5)
self.assertEqual(v.End, 15)
self.assertEqual(v.Reverse, True)
def test_contains(self):
"""Span object contains its start but not its end"""
self.assertNotContains(self.empty, 0)
self.assertContains(self.full, 30)
self.assertContains(self.full, 34)
self.assertNotContains(self.full, 35)
self.assertContains(self.full, self.inside)
self.assertNotContains(self.full, self.overlapping)
self.assertContains(self.spans_zero, 0)
self.assertContains(self.spans_zero, -5)
self.assertNotContains(self.spans_zero, 5)
def test_overlaps(self):
"""Span objects should be able to overlap points or spans"""
self.assertTrue(self.full.overlaps(self.overlapping))
self.assertFalse(self.full.overlaps(self.before))
self.assertFalse(self.before.overlaps(self.overlapping))
self.assertFalse(self.full.overlaps(self.after))
self.assertFalse(self.after.overlaps(self.before))
self.assertTrue(self.full.overlaps(self.inside))
self.assertTrue(self.spans_zero.overlaps(self.empty))
self.assertTrue(self.empty.overlaps(self.spans_zero))
def test_reverse(self):
"""Span reverse should change direction"""
self.assertFalse(self.empty.Reverse)
self.empty.reverse()
self.assertTrue(self.empty.Reverse)
self.empty.reverse()
self.assertFalse(self.empty.Reverse)
self.assertTrue(self.reverse.Reverse)
self.reverse.reverse()
self.assertFalse(self.reverse.Reverse)
def test_iter(self):
"""Span iter should loop through (integer) contents"""
self.assertEqual(list(iter(self.empty)), [])
self.assertEqual(list(iter(self.full)), [30,31,32,33,34])
self.assertEqual(list(iter(self.spans_zero)),[-5,-4,-3,-2,-1,0,1,2,3,4])
self.assertEqual(list(iter(self.inside)), [31])
self.assertEqual(list(self.reverse), [34,33,32,31,30])
def test_str(self):
"""Span str should print start, stop, reverse"""
self.assertEqual(str(self.empty), '(0,0,False)')
self.assertEqual(str(self.full), '(30,35,False)')
self.assertEqual(str(self.reverse), '(30,35,True)')
def test_len(self):
"""Span len should return difference between start and end"""
self.assertEqual(len(self.empty), 0)
self.assertEqual(len(self.full), 5)
self.assertEqual(len(self.inside),1)
self.assertEqual(len(self.spans_zero), 10)
def test_cmp(self):
"""Span cmp should support sort by 1st/2nd index and direction"""
s, e, f, r, i, o = self.spans_zero, self.empty, self.full, \
self.reverse, self.inside, self.overlapping
n = Span(30, 36)
expected_order = [s, e, f, r, n, i, o]
first = expected_order[:]
first.sort()
second = [r, o, f, s, e, i, n]
second.sort()
for i, j in zip(first, second):
self.assertSameObj(i, j)
for i, j in zip(first, expected_order):
self.assertSameObj(i, j)
def test_startsBefore(self):
"""Span startsBefore should match hand-calculated results"""
e, f = self.empty, self.full
self.assertTrue(e.startsBefore(f))
self.assertFalse(f.startsBefore(e))
self.assertTrue(e.startsBefore(1))
self.assertTrue(e.startsBefore(1000))
self.assertFalse(e.startsBefore(0))
self.assertFalse(e.startsBefore(-1))
self.assertFalse(f.startsBefore(30))
self.assertTrue(f.startsBefore(31))
self.assertTrue(f.startsBefore(1000))
def test_startsAfter(self):
"""Span startsAfter should match hand-calculated results"""
e, f = self.empty, self.full
self.assertFalse(e.startsAfter(f))
self.assertTrue(f.startsAfter(e))
self.assertFalse(e.startsAfter(1))
self.assertFalse(e.startsAfter(1000))
self.assertFalse(e.startsAfter(0))
self.assertTrue(e.startsAfter(-1))
self.assertTrue(f.startsAfter(29))
self.assertFalse(f.startsAfter(30))
self.assertFalse(f.startsAfter(31))
self.assertFalse(f.startsAfter(1000))
def test_startsAt(self):
"""Span startsAt should return True if input matches"""
e, f = self.empty, self.full
s = Span(30, 1000)
self.assertTrue(e.startsAt(0))
self.assertTrue(f.startsAt(30))
self.assertTrue(s.startsAt(30))
self.assertTrue(f.startsAt(s))
self.assertTrue(s.startsAt(f))
self.assertFalse(e.startsAt(f))
self.assertFalse(e.startsAt(-1))
self.assertFalse(e.startsAt(1))
self.assertFalse(f.startsAt(29))
def test_startsInside(self):
"""Span startsInside should return True if input starts inside span"""
e, f, i, o = self.empty, self.full, self.inside, self.overlapping
self.assertFalse(e.startsInside(0))
self.assertFalse(f.startsInside(30))
self.assertFalse(e.startsInside(f))
self.assertTrue(i.startsInside(f))
self.assertFalse(f.startsInside(i))
self.assertTrue(o.startsInside(f))
self.assertFalse(o.endsInside(i))
def test_endsBefore(self):
"""Span endsBefore should match hand-calculated results"""
e, f = self.empty, self.full
self.assertTrue(e.endsBefore(f))
self.assertFalse(f.endsBefore(e))
self.assertTrue(e.endsBefore(1))
self.assertTrue(e.endsBefore(1000))
self.assertFalse(e.endsBefore(0))
self.assertFalse(e.endsBefore(-1))
self.assertFalse(f.endsBefore(30))
self.assertFalse(f.endsBefore(31))
self.assertTrue(f.endsBefore(1000))
def test_endsAfter(self):
"""Span endsAfter should match hand-calculated results"""
e, f = self.empty, self.full
self.assertFalse(e.endsAfter(f))
self.assertTrue(f.endsAfter(e))
self.assertFalse(e.endsAfter(1))
self.assertFalse(e.endsAfter(1000))
self.assertFalse(e.endsAfter(0))
self.assertTrue(e.endsAfter(-1))
self.assertTrue(f.endsAfter(29))
self.assertTrue(f.endsAfter(30))
self.assertTrue(f.endsAfter(34))
self.assertFalse(f.endsAfter(35))
self.assertFalse(f.endsAfter(1000))
def test_endsAt(self):
"""Span endsAt should return True if input matches"""
e, f = self.empty, self.full
s = Span(30, 1000)
t = Span(-100, 35)
self.assertTrue(e.endsAt(0))
self.assertTrue(f.endsAt(35))
self.assertTrue(s.endsAt(1000))
self.assertFalse(f.endsAt(s))
self.assertFalse(s.endsAt(f))
self.assertTrue(f.endsAt(t))
self.assertTrue(t.endsAt(f))
def test_endsInside(self):
"""Span endsInside should return True if input ends inside span"""
e, f, i, o = self.empty, self.full, self.inside, self.overlapping
self.assertFalse(e.endsInside(0))
self.assertFalse(f.endsInside(30))
self.assertFalse(f.endsInside(34))
self.assertFalse(f.endsInside(35))
self.assertFalse(e.endsInside(f))
self.assertTrue(i.endsInside(f))
self.assertFalse(f.endsInside(i))
self.assertFalse(o.endsInside(f))
self.assertFalse(o.endsInside(i))
self.assertTrue(e.endsInside(Span(-1,1)))
self.assertTrue(e.endsInside(Span(0,1)))
self.assertFalse(e.endsInside(Span(-1,0)))
class RangeInterfaceTests(object): #SpanTests):
"""A single-element Range should behave like the corresponding Span."""
def setUp(self):
"""Define some standard Spans"""
self.empty = Range(Span(0, 0))
self.full = Range(Span(30, 35))
self.overlapping = Range(Span(32, 36))
self.inside = Range(Span(31, 32))
self.before = Range(Span(25, 30))
self.after = Range(Span(35, 40))
self.reverse = Range(Span(30, 35, Reverse=True))
self.spans_zero = Range(Span(-5, 5))
def test_str(self):
"""Range str should print start, stop, reverse for each Span"""
#note that the Range adds an extra level of parens, since it can
#contain more than one Span.
self.assertEqual(str(self.empty), '((0,0,False))')
self.assertEqual(str(self.full), '((30,35,False))')
self.assertEqual(str(self.reverse), '((30,35,True))')
class RangeTests(TestCase):
"""Tests of the Range object."""
def setUp(self):
"""Set up a few standard ranges."""
self.one = Range(Span(0,100))
self.two = Range([Span(3,5), Span(8, 11)])
self.three = Range([Span(6,7), Span(15, 17), Span(30, 35)])
self.overlapping = Range([Span(6, 10), Span(7,3)])
self.single = Range(0)
self.singles = Range([3, 11])
self.twocopy = Range(self.two)
self.twothree = Range([self.two, self.three])
self.empty = Range([Span(6,6), Span(8,8)])
def test_init(self):
"""Range init from Spans, numbers, or Ranges should work OK."""
#single span
self.assertEqual(self.one, Span(0,100))
#list of spans
self.assertEqual(self.two.Spans, [Span(3,5), Span(8,11)])
#another range
self.assertEqual(self.two, self.twocopy)
#list of ranges
self.assertEqual(self.twothree.Spans, [Span(3,5), Span(8,11),
Span(6,7), Span(15,17), Span(30,35)])
#list of numbers
self.assertEqual(self.singles.Spans, [Span(3,4), Span(11,12)])
#single number
self.assertEqual(self.single.Spans, [Span(0,1)])
#nothing
self.assertEqual(Range().Spans, [])
def test_str(self):
"""Range str should print nested with parens"""
self.assertEqual(str(self.one), '((0,100,False))')
self.assertEqual(str(self.twothree),
'((3,5,False),(8,11,False),(6,7,False),(15,17,False),(30,35,False))')
self.assertEqual(str(self.single), '((0,1,False))')
def test_len(self):
"""Range len should sum span lengths"""
self.assertEqual(len(self.one), 100)
self.assertEqual(len(self.single), 1)
self.assertEqual(len(self.empty), 0)
self.assertEqual(len(self.three), 8)
def test_cmp(self):
"""Ranges should compare equal if they have the same spans"""
self.assertEqual(self.twothree, Range([Span(3,5), Span(8, 11),
Span(6,7), Span(15, 17), Span(30, 35)]))
self.assertEqual(Range(), Range())
def test_start_end(self):
"""Range Start and End should behave as expected"""
self.assertEqual(self.one.Start, 0)
self.assertEqual(self.one.End, 100)
self.assertEqual(self.overlapping.Start, 3)
self.assertEqual(self.overlapping.End, 10)
self.assertEqual(self.three.Start, 6)
self.assertEqual(self.three.End, 35)
def test_reverse(self):
"""Range reverse method should reverse each span"""
for s in self.overlapping.Spans:
self.assertFalse(s.Reverse)
self.overlapping.reverse()
for s in self.overlapping.Spans:
self.assertTrue(s.Reverse)
self.overlapping.Spans.append(Span(0, 100))
self.overlapping.reverse()
for s in self.overlapping.Spans[0:1]:
self.assertFalse(s.Reverse)
self.assertTrue(self.overlapping.Spans[-1].Reverse)
def test_Reverse(self):
"""Range Reverse property should return True if any span reversed"""
self.assertFalse(self.one.Reverse)
self.one.reverse()
self.assertTrue(self.one.Reverse)
self.assertFalse(self.two.Reverse)
self.two.Spans.append(Span(0,100,Reverse=True))
self.assertTrue(self.two.Reverse)
self.two.reverse()
self.assertTrue(self.two.Reverse)
def test_contains(self):
"""Range contains an item if any span contains it"""
self.assertContains(self.one, 50)
self.assertContains(self.one, 0)
self.assertContains(self.one, 99)
self.assertNotContains(self.one, 100)
self.assertContains(self.three, 6)
self.assertNotContains(self.three, 7)
self.assertNotContains(self.three, 8)
self.assertNotContains(self.three, 14)
self.assertContains(self.three, 15)
self.assertNotContains(self.three, 29)
self.assertContains(self.three, 30)
self.assertContains(self.three, 34)
self.assertNotContains(self.three, 35)
self.assertNotContains(self.three, 40)
#should work if a span is added
self.three.Spans.append(40)
self.assertContains(self.three, 40)
#should work for spans
self.assertContains(self.three, Span(31, 33))
self.assertNotContains(self.three, Span(31, 37))
#span contains itself
self.assertContains(self.two, self.twocopy)
#should work for ranges
self.assertContains(self.three, Range([6, Span(15,16), Span(30,33)]))
#should work for copy, except when extra piece added
threecopy = Range(self.three)
self.assertContains(self.three, threecopy)
threecopy.Spans.append(1000)
self.assertNotContains(self.three, threecopy)
self.three.Spans.append(Span(950, 1050))
self.assertContains(self.three, threecopy)
self.assertNotContains(threecopy, self.three)
def test_overlaps(self):
"""Range overlaps should return true if any component overlapping"""
self.assertTrue(self.two.overlaps(self.one))
self.assertTrue(self.one.overlaps(self.two))
self.assertTrue(self.three.overlaps(self.one))
#two and three are interleaved but not overlapping
self.assertFalse(self.two.overlaps(self.three))
self.assertFalse(self.three.overlaps(self.two))
self.assertTrue(self.one.overlaps(self.empty))
self.assertTrue(self.empty.overlaps(self.one))
self.assertTrue(self.singles.overlaps(self.two))
def test_overlapsExtent(self):
"""Range overlapsExtent should return true for interleaved ranges"""
self.assertTrue(self.two.overlapsExtent(self.three))
self.assertTrue(self.three.overlapsExtent(self.two))
self.assertFalse(self.single.overlapsExtent(self.two))
self.assertFalse(self.single.overlapsExtent(self.three))
self.assertTrue(self.one.overlapsExtent(self.three))
def test_sort(self):
"""Range sort should sort component spans"""
one = self.one
one.sort()
self.assertEqual(one.Spans, [Span(100,0)])
one.Spans.append(Span(-20,-10))
self.assertEqual(one.Spans, [Span(0,100),Span(-20,-10)])
one.sort()
self.assertEqual(one.Spans, [Span(-20,-10),Span(0,100)])
one.Spans.append(Span(-20, -10, Reverse=True))
self.assertEqual(one.Spans, [Span(-20,-10),Span(0,100),
Span(-20,-10,Reverse=True)])
one.sort()
self.assertEqual(one.Spans, [Span(-20,-10),Span(-20,-10,Reverse=True),
Span(0,100)])
def test_iter(self):
"""Range iter should iterate through each span in turn"""
self.assertEqual(list(iter(self.two)), [3,4,8,9,10])
self.two.Spans.insert(1, Span(103, 101, Reverse=True))
self.assertEqual(list(iter(self.two)), [3,4,102,101,8,9,10])
def test_Extent(self):
"""Range extent should span limits of range"""
self.assertEqual(self.one.Extent, Span(0,100))
self.assertEqual(self.three.Extent, Span(6,35))
self.assertEqual(self.singles.Extent, Span(3, 12))
self.assertEqual(self.single.Extent, Span(0,1))
self.three.Spans.append(Span(100, 105, Reverse=True))
self.assertEqual(self.three.Extent, Span(6,105))
self.three.Spans.append(Span(-100, -1000))
self.assertEqual(self.three.Extent, Span(-1000,105))
def test_simplify(self):
"""Range reduce should group overlapping ranges"""
#consolidate should have no effect when no overlap
r = self.two
r.simplify()
self.assertEqual(r.Spans, [Span(3,5), Span(8,11)])
#should consolidate an overlap of the same direction
r.Spans.append(Span(-1, 4))
r.simplify()
self.assertEqual(r.Spans, [Span(-1,5), Span(8,11)])
#should also consolidate _adjacent_ spans of the same direction
r.Spans.append(Span(11,14))
r.simplify()
self.assertEqual(r.Spans, [Span(-1,5), Span(8,14)])
#bridge should cause consolidations
s = Range(r)
s.Spans.append(Span(5,8))
s.simplify()
self.assertEqual(s.Spans, [Span(-1,14)])
#ditto for bridge that overlaps everything
s = Range(r)
s.Spans.append(Span(-100, 100))
s.simplify()
self.assertEqual(s.Spans, [Span(-100,100)])
#however, can't consolidate span in other orientation
s = Range(r)
s.Spans.append(Span(-100, 100, Reverse=True))
self.assertEqual(s.Spans, [Span(-1,5), Span(8,14), \
Span(-100,100,Reverse=True)])
class RangeFromStringTests(TestCase):
"""Tests of the RangeFromString factory function."""
def test_init(self):
self.assertEqual(RangeFromString(''), Range())
self.assertEqual(RangeFromString(' 3 , 4\t, ,, 10 ,'),
Range([3,4,10]))
self.assertEqual(RangeFromString('3,4-10,1-5'),
Range([Span(3), Span(4,10), Span(1,5)]))
#run the following if invoked from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_core/test_maps.py 000644 000765 000024 00000011467 12024702176 021754 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import unittest
from cogent.core.location import Map, Span
from cogent.core.annotation import _Annotatable, Feature, _Feature
from cogent import LoadSeqs, DNA
__author__ = "Peter Maxwell"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell", "Gavin Huttley", "Rob Knight",
"Matthew Wakefield"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
def SimpleAnnotation(parent, locations, Name):
return Feature(parent, '', Name, locations)
def annotate(parent, start, end, Name):
annot = parent.addAnnotation(SimpleAnnotation, locations=[(start, end)], Name=Name)
return annot
def structure(a, depth=0):
annots = [structure(annot, depth+1) for annot in a.annotations]
if not isinstance(a, _Feature):
return ('seq', len(a), annots)
elif annots:
return (a.Name, repr(a.map), annots)
else:
return (a.Name, repr(a.map))
class MapTest(unittest.TestCase):
"""Testing annotation of and by maps"""
def test_spans(self):
# a simple two part map of length 10
map = Map([(0,5), (5,10)], parent_length=10)
# try different spans on the above map
for ((start, end), expected) in [
((0, 4), "[0:4]"),
((0, 5), "[0:5]"),
((0, 6), "[0:5, 5:6]"),
((5, 10), "[5:10]"),
((-1, 10), "[-1-, 0:5, 5:10]"),
((5, 11), "[5:10, -1-]"),
((0, 10), "[0:5, 5:10]"),
((10, 0), "[10:5, 5:0]"),
]:
r = repr(Span(start, end, Reverse=start>end).remapWith(map))
#print (start, end), r,
if r != expected:
self.fail(repr((r, expected)))
def test_maps_on_maps(self):
seq = DNA.makeSequence('ATCGATCGAT' * 5, Name='base')
feat1 = annotate(seq, 10, 20, 'fake')
feat2 = annotate(feat1, 3, 5, 'fake2')
feat3 = annotate(seq, 1, 3, 'left')
seq2 = seq[5:]
self.assertEqual(structure(seq), ('seq', 50,
[('fake', '[10:20]/50',
[('fake2', '[3:5]/10')]),
('left', '[1:3]/50')])
)
self.assertEqual(structure(seq2), ('seq', 45,
[('fake', '[5:15]/45',
[('fake2', '[3:5]/10')])])
)
def test_getByAnnotation(self):
seq = DNA.makeSequence('ATCGATCGAT' * 5, Name='base')
seq.addAnnotation(Feature, 'test_type', 'test_label', [(5,10)])
seq.addAnnotation(Feature, 'test_type', 'test_label2', [(15,18)])
answer = list(seq.getByAnnotation('test_type'))
self.assertEqual( len(answer), 2)
self.assertEqual( str(answer[0]), 'TCGAT')
self.assertEqual( str(answer[1]), 'TCG')
answer = list(seq.getByAnnotation('test_type', 'test_label'))
self.assertEqual( len(answer), 1)
self.assertEqual( str(answer[0]), 'TCGAT')
# test ignoring of a partial annotation
sliced_seq = seq[:17]
answer = list(sliced_seq.getByAnnotation('test_type', ignore_partial=True))
self.assertEqual(len(answer), 1)
self.assertEqual( str(answer[0]), 'TCGAT')
def test_getBySequenceAnnotation(self):
aln = LoadSeqs(data={
'a': 'ATCGAAATCGAT',
'b': 'ATCGA--TCGAT'})
b = aln.getSeq('b')
b.addAnnotation(Feature, 'test_type', 'test_label', [(4,6)])
answer = aln.getBySequenceAnnotation('b', 'test_type')[0].todict()
self.assertEqual(answer, {'b':'A--T', 'a':'AAAT'})
if 0: # old, needs fixes
# Maps
a = Map([(10,20)], parent_length=100)
for (desc, map, expected) in [
('a ', a, "Map([10:20] on base)"),
('i ', a.inverse(), "Map([-10-, 0:10, -80-] on Map([10:20] on base))"),
('1 ', a[5:], "Map([5:10] on Map([10:20] on base))"),
('1r', a[5:].relative_to(b), "Map([15:20] on base)"),
('2 ', a[:5], "Map([0:5] on Map([10:20] on base))"),
('2r', a[:5].relative_to(b), "Map([10:15] on base)"),
('r ', a.relative_to(a[5:]), "Map([-5-, 0:5] on Map([5:10] on Map([10:20] on base)))"),
('r ', a[2:4].relative_to(a[2:6]), "Map([0:2] on Map([2:6] on Map([10:20] on base)))"),
('r ', a[2:4].relative_to(a[2:6][0:3]), "Map([0:2] on Map([0:3] on Map([2:6] on Map([10:20] on base))))")]:
print desc, repr(map),
if repr(map) == expected:
print
else:
print ' <--- ', expected
bad = True
if __name__ == '__main__':
unittest.main()
PyCogent-1.5.3/tests/test_core/test_moltype.py 000644 000765 000024 00000101102 12024702176 022467 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.core import moltype, sequence
from cogent.core.moltype import AlphabetError, \
CoreObjectGroup, AlphabetGroup, make_matches, make_pairs, \
array, MolType, RNA, DNA, PROTEIN, STANDARD_CODON,\
IUPAC_RNA_chars, \
IUPAC_RNA_ambiguities, IUPAC_RNA_ambiguities_complements, \
IUPAC_DNA_chars, IUPAC_DNA_ambiguities, IUPAC_DNA_ambiguities_complements, \
RnaStandardPairs, DnaStandardPairs
from cogent.util.unit_test import TestCase, main
from cogent.data.molecular_weight import DnaMW, RnaMW, ProteinMW
__author__ = "Gavin Huttley, Peter Maxwell, and Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Gavin Huttley", "Peter Maxwell"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
#ind some of the standard alphabets to reduce typing
RnaBases = RNA.Alphabets.Base
DnaBases = DNA.Alphabets.Base
AminoAcids = PROTEIN.Alphabets.Base
#the following classes are to preserve compatibility for older test code
#that assumes mixed-case is OK.
RnaMolType = MolType(
Sequence = sequence.RnaSequence,
motifset = IUPAC_RNA_chars,
Ambiguities = IUPAC_RNA_ambiguities,
label = "rna_with_lowercase",
MWCalculator = RnaMW,
Complements = IUPAC_RNA_ambiguities_complements,
Pairs = RnaStandardPairs,
add_lower=True,
preserve_existing_moltypes=True,
make_alphabet_group=True,
)
DnaMolType = MolType(
Sequence = sequence.DnaSequence,
motifset = IUPAC_DNA_chars,
Ambiguities = IUPAC_DNA_ambiguities,
label = "dna_with_lowercase",
MWCalculator = DnaMW,
Complements = IUPAC_DNA_ambiguities_complements,
Pairs = DnaStandardPairs,
add_lower=True,
preserve_existing_moltypes=True,
make_alphabet_group=True,
)
ProteinMolType = PROTEIN
class make_matches_tests(TestCase):
"""Tests of the make_matches top-level function"""
def test_init_empty(self):
"""make_matches should init ok with no parameters"""
self.assertEqual(make_matches(), {})
def test_init_monomers(self):
"""make_matches with only monomers should produce {(i,i):True}"""
m = make_matches('')
self.assertEqual(m, {})
m = make_matches('qaz')
self.assertEqual(m, {('q','q'):True,('a','a'):True,('z','z'):True})
def test_init_gaps(self):
"""make_matches with only gaps should match all gaps to each other"""
m = make_matches('', '~!')
self.assertEqual(m, {('~','~'):True,('!','!'):True,('!','~'):True,
('~','!'):True})
def test_init_degen(self):
"""make_matches with only degen should work as expected"""
m = make_matches(None, None, {'x':'ab','y':'bc','z':'cd', 'n':'bcd'})
self.assertEqual(m, {('x','x'):False, ('x','y'):False, ('x','n'):False,
('y','x'):False, ('y','y'):False, ('y','z'):False, ('y','n'):False,
('z','y'):False, ('z','z'):False, ('z','n'):False, ('n','x'):False,
('n','y'):False, ('n','z'):False, ('n','n'):False})
self.assertNotContains(m, ('x','z'))
def test_init_all(self):
"""make_matches with everything should produce correct dict"""
m = make_matches('ABC',('-','~'),{'X':'AB','Y':('B','C'),'N':list('ABC')})
exp = {
('-','-'):True,
('~','~'):True,
('-','~'):True,
('~','-'):True,
('A','A'):True,
('B','B'):True,
('C','C'):True,
('A','X'):False,
('X','A'):False,
('B','X'):False,
('X','B'):False,
('B','Y'):False,
('Y','B'):False,
('C','Y'):False,
('Y','C'):False,
('A','N'):False,
('N','A'):False,
('B','N'):False,
('N','B'):False,
('C','N'):False,
('N','C'):False,
('X','X'):False,
('Y','Y'):False,
('N','N'):False,
('X','Y'):False,
('Y','X'):False,
('X','N'):False,
('N','X'):False,
('Y','N'):False,
('N','Y'):False,
}
self.assertEqual(m, exp)
class make_pairs_tests(TestCase):
"""Tests of the top-level make_pairs factory function."""
def setUp(self):
"""Define some standard pairs and other data"""
self.pairs = {('U','A'):True, ('A','U'):True, ('G','U'):False}
def test_init_empty(self):
"""make_pairs should init ok with no parameters"""
self.assertEqual(make_pairs(), {})
def test_init_pairs(self):
"""make_pairs with just pairs should equal the original"""
self.assertEqual(make_pairs(self.pairs), self.pairs)
self.assertNotSameObj(make_pairs(self.pairs), self.pairs)
def test_init_monomers(self):
"""make_pairs with pairs and monomers should equal just the pairs"""
self.assertEqual(make_pairs(self.pairs, 'ABCDEFG'), self.pairs)
self.assertNotSameObj(make_pairs(self.pairs, 'ABCDEFG'), self.pairs)
def test_init_gaps(self):
"""make_pairs should add all combinations of gaps as weak pairs"""
p = make_pairs(self.pairs, None, '-~')
self.assertNotEqual(p, self.pairs)
self.pairs.update({('~','~'):False,('-','~'):False,('-','-'):False,
('~','-'):False})
self.assertEqual(p, self.pairs)
def test_init_degen(self):
"""make_pairs should add in degenerate combinations as weak pairs"""
p = make_pairs(self.pairs, 'AUG','-', {'R':'AG','Y':'CU','W':'AU'})
self.assertNotEqual(p, self.pairs)
self.pairs.update({
('-','-'):False,
('A','Y'):False,
('Y','A'):False,
('A','W'):False,
('W','A'):False,
('U','R'):False,
('R','U'):False,
('U','W'):False,
('W','U'):False,
('G','Y'):False,
('G','W'):False,
('R','Y'):False,
('R','W'):False,
('Y','R'):False,
('Y','W'):False,
('W','R'):False,
('W','Y'):False,
('W','W'):False,
})
self.assertEqual(p, self.pairs)
class CoreObjectGroupTests(TestCase):
"""Tests of the CoreObjectGroup class."""
def test_init(self):
"""CoreObjectGroup should init with basic list of objects."""
class o(object):
def __init__(self, s):
self.s = s
base = o('base')
c = CoreObjectGroup(base)
self.assertSameObj(c.Base, base)
self.assertSameObj(c.Degen, None)
self.assertSameObj(c.Base.Degen, None)
base, degen, gap, degengap = map(o, ['base','degen','gap','degengap'])
c = CoreObjectGroup(base, degen, gap, degengap)
self.assertSameObj(c.Base, base)
self.assertSameObj(c.Base.Degen, degen)
self.assertSameObj(c.Degen.Gapped, degengap)
class AlphabetGroupTests(TestCase):
"""Tests of the AlphabetGroup class."""
def test_init(self):
"""AlphabetGroup should initialize successfully"""
chars = 'AB'
degens = {'C':'AB'}
g = AlphabetGroup(chars, degens)
self.assertEqual(''.join(g.Base), 'AB')
self.assertEqual(''.join(g.Degen), 'ABC')
self.assertEqual(''.join(g.Gapped), 'AB-')
self.assertEqual(''.join(g.DegenGapped), 'AB-C?')
class MolTypeTests(TestCase):
"""Tests of the MolType class. Should support same API as old Alphabet."""
def test_init_minimal(self):
"""MolType should init OK with just monomers"""
a = MolType('Abc')
self.assertContains(a.Alphabet, 'A')
self.assertNotContains(a.Alphabet, 'a') # case-sensitive
self.assertContains(a.Alphabet, 'b')
self.assertNotContains(a.Alphabet, 'B')
self.assertNotContains(a.Alphabet, 'x')
def test_init_everything(self):
"""MolType should init OK with all parameters set"""
k = dict.fromkeys
a = MolType(k('Abc'), Ambiguities={'d':'bc'}, Gaps=k('~'), \
Complements={'b':'c','c':'b'}, Pairs={}, add_lower=False)
for i in 'Abcd~':
self.assertContains(a, i)
self.assertEqual(a.complement('b'), 'c')
self.assertEqual(a.complement('AbcAA'), 'AcbAA')
self.assertEqual(a.firstDegenerate('AbcdA'), 3)
self.assertEqual(a.firstGap('a~c'), 1)
self.assertEqual(a.firstInvalid('Abcx'), 3)
def test_stripDegenerate(self):
"""MolType stripDegenerate should remove any degenerate bases"""
s = RnaMolType.stripDegenerate
self.assertEqual(s('UCAG-'), 'UCAG-')
self.assertEqual(s('NRYSW'), '')
self.assertEqual(s('USNG'), 'UG')
def test_stripBad(self):
"""MolType stripBad should remove any non-base, non-gap chars"""
s = RnaMolType.stripBad
self.assertEqual(s('UCAGwsnyrHBND-D'), 'UCAGwsnyrHBND-D')
self.assertEqual(s('@#^*($@!#&()!@QZX'), '')
self.assertEqual(s('aaa ggg ---!ccc'), 'aaaggg---ccc')
def test_stripBadAndGaps(self):
"""MolType stripBadAndGaps should remove gaps and bad chars"""
s = RnaMolType.stripBadAndGaps
self.assertEqual(s('UCAGwsnyrHBND-D'), 'UCAGwsnyrHBNDD')
self.assertEqual(s('@#^*($@!#&()!@QZX'), '')
self.assertEqual(s('aaa ggg ---!ccc'), 'aaagggccc')
def test_complement(self):
"""MolType complement should correctly complement sequence"""
self.assertEqual(RnaMolType.complement('UauCG-NR'), 'AuaGC-NY')
self.assertEqual(DnaMolType.complement('TatCG-NR'), 'AtaGC-NY')
self.assertEqual(RnaMolType.complement(''), '')
self.assertRaises(TypeError, ProteinMolType.complement, 'ACD')
#if it wasn't a string, result should be a list
self.assertEqual(RnaMolType.complement(list('UauCG-NR')),
list('AuaGC-NY'))
self.assertEqual(RnaMolType.complement(('a','c')), ('u','g'))
#constructor should fail for a dict
self.assertRaises(ValueError, RnaMolType.complement, {'a':'c'})
def test_rc(self):
"""MolType rc should correctly reverse-complement sequence"""
self.assertEqual(RnaMolType.rc('U'), 'A')
self.assertEqual(RnaMolType.rc(''), '')
self.assertEqual(RnaMolType.rc('R'), 'Y')
self.assertEqual(RnaMolType.rc('UauCG-NR'), 'YN-CGauA')
self.assertEqual(DnaMolType.rc('TatCG-NR'), 'YN-CGatA')
self.assertRaises(TypeError, ProteinMolType.rc, 'ACD')
#if it wasn't a string, result should be a list
self.assertEqual(RnaMolType.rc(list('UauCG-NR')),
list('YN-CGauA'))
self.assertEqual(RnaMolType.rc(('a','c')), ('g','u'))
#constructor should fail for a dict
self.assertRaises(ValueError, RnaMolType.rc, {'a':'c'})
def test_contains(self):
"""MolType contains should return correct result"""
for i in 'UCAGWSMKRYBDHVN-' + 'UCAGWSMKRYBDHVN-'.lower():
self.assertContains(RnaMolType, i)
for i in 'x!@#$%^&ZzQq':
self.assertNotContains(RnaMolType, i)
a = MolType(dict.fromkeys('ABC'), add_lower=True)
for i in 'abcABC':
self.assertContains(a, i)
self.assertNotContains(a, 'x')
b = MolType(dict.fromkeys('ABC'), add_lower=False)
for i in 'ABC':
self.assertContains(b, i)
for i in 'abc':
self.assertNotContains(b, i)
def test_iter(self):
"""MolType iter should iterate over monomer order"""
self.assertEqual(list(RnaMolType), ['U','C','A','G', 'u','c','a','g'])
a = MolType('ZXCV')
self.assertEqual(list(a), ['Z','X','C','V'])
def test_isGapped(self):
"""MolType isGapped should return True if gaps in seq"""
g = RnaMolType.isGapped
self.assertFalse(g(''))
self.assertFalse(g('ACGUCAGUACGUCAGNRCGAUcaguaguacYRNRYRN'))
self.assertTrue(g('-'))
self.assertTrue(g('--'))
self.assertTrue(g('CAGUCGUACGUCAGUACGUacucauacgac-caguACUG'))
self.assertTrue(g('CA--CGUAUGCA-----g'))
self.assertTrue(g('CAGU-'))
def test_isGap(self):
"""MolType isGap should return True if char is a gap"""
g = RnaMolType.isGap
#True for the empty string
self.assertFalse(g(''))
#True for all the standard and degenerate symbols
s = 'ACGUCAGUACGUCAGNRCGAUcaguaguacYRNRYRN'
self.assertFalse(g(s))
for i in s:
self.assertFalse(g(i))
#should be true for a single gap
self.assertTrue(g('-'))
#note that it _shouldn't_ be true for a run of gaps: use a.isGapped()
self.assertFalse(g('--'))
def test_isDegenerate(self):
"""MolType isDegenerate should return True if degen symbol in seq"""
d = RnaMolType.isDegenerate
self.assertFalse(d(''))
self.assertFalse(d('UACGCUACAUGuacgucaguGCUAGCUA---ACGUCAG'))
self.assertTrue(d('N'))
self.assertTrue(d('R'))
self.assertTrue(d('y'))
self.assertTrue(d('GCAUguagcucgUCAGUCAGUACgUgcasCUAG'))
self.assertTrue(d('ACGYAUGCUGYEWEWNFMNfuwbybcwuybcjwbeiwfub'))
def test_isValid(self):
"""MolType isValid should return True if any unknown symbol in seq"""
v = RnaMolType.isValid
self.assertFalse(v(3))
self.assertFalse(v(None))
self.assertTrue(v('ACGUGCAUGUCAYCAYGUACGcaugacyugc----RYNCYRNC'))
self.assertTrue(v(''))
self.assertTrue(v('a'))
self.assertFalse(v('ACIUBHFWUIXZKLNJUCIHBICNSOWMOINJ'))
self.assertFalse(v('CAGUCAGUCACA---GACCAUG-_--cgau'))
def test_isStrict(self):
"""MolType isStrict should return True if all symbols in Monomers"""
s = RnaMolType.isStrict
self.assertFalse(s(3))
self.assertFalse(s(None))
self.assertTrue(s(''))
self.assertTrue(s('A'))
self.assertTrue(s('UAGCACUgcaugcauGCAUGACuacguACAUG'))
self.assertFalse(s('CAGUCGAUCA-cgaucagUCGAUGAC'))
self.assertFalse(s('ACGUGCAUXCAGUCAG'))
def test_firstGap(self):
"""MolType firstGap should return index of first gap symbol, or None"""
g = RnaMolType.firstGap
self.assertEqual(g(''), None)
self.assertEqual(g('a'), None)
self.assertEqual(g('uhacucHuhacUIUIhacan'), None)
self.assertEqual(g('-abc'), 0)
self.assertEqual(g('b-ac'), 1)
self.assertEqual(g('abcd-'), 4)
def test_firstDegenerate(self):
"""MolType firstDegenerate should return index of first degen symbol"""
d = RnaMolType.firstDegenerate
self.assertEqual(d(''), None)
self.assertEqual(d('a'), None)
self.assertEqual(d('UCGACA--CU-gacucaguacgua'), None)
self.assertEqual(d('nCAGU'), 0)
self.assertEqual(d('CUGguagvAUG'), 7)
self.assertEqual(d('ACUGCUAacgud'), 11)
def test_firstInvalid(self):
"""MolType firstInvalid should return index of first invalid symbol"""
i = RnaMolType.firstInvalid
self.assertEqual(i(''), None)
self.assertEqual(i('A'), None)
self.assertEqual(i('ACGUNVBuacg-wskmWSMKYRryNnN--'), None)
self.assertEqual(i('x'), 0)
self.assertEqual(i('rx'), 1)
self.assertEqual(i('CAGUNacgunRYWSwx'), 15)
def test_firstNonStrict(self):
"""MolType firstNonStrict should return index of first non-strict symbol"""
s = RnaMolType.firstNonStrict
self.assertEqual(s(''), None)
self.assertEqual(s('A'), None)
self.assertEqual(s('ACGUACGUcgaucagu'), None)
self.assertEqual(s('N'), 0)
self.assertEqual(s('-'), 0)
self.assertEqual(s('x'), 0)
self.assertEqual(s('ACGUcgAUGUGCAUcaguX'), 18)
self.assertEqual(s('ACGUcgAUGUGCAUcaguX-38243829'), 18)
def test_disambiguate(self):
"""MolType disambiguate should remove degenerate bases"""
d = RnaMolType.disambiguate
self.assertEqual(d(''), '')
self.assertEqual(d('AGCUGAUGUA--CAGU'),'AGCUGAUGUA--CAGU')
self.assertEqual(d('AUn-yrs-wkmCGwmrNMWRKY', 'strip'), 'AU--CG')
self.assertEqual(d(tuple('AUn-yrs-wkmCGwmrNMWRKY'), 'strip'), \
tuple('AU--CG'))
s = 'AUn-yrs-wkmCGwmrNMWRKY'
t = d(s, 'random')
u = d(s, 'random')
for i, j in zip(s, t):
if i in RnaMolType.Degenerates:
self.assertContains(RnaMolType.Degenerates[i], j)
else:
self.assertEquals(i, j)
self.assertNotEqual(t, u)
self.assertEqual(d(tuple('UCAG'), 'random'), tuple('UCAG'))
self.assertEqual(len(s), len(t))
self.assertSameObj(RnaMolType.firstDegenerate(t), None)
#should raise exception on unknown disambiguation method
self.assertRaises(NotImplementedError, d, s, 'xyz')
def test_degap(self):
"""MolType degap should remove all gaps from sequence"""
g = RnaMolType.degap
self.assertEqual(g(''), '')
self.assertEqual(g('GUCAGUCgcaugcnvuincdks'), 'GUCAGUCgcaugcnvuincdks')
self.assertEqual(g('----------------'), '')
self.assertEqual(g('gcuauacg-'), 'gcuauacg')
self.assertEqual(g('-CUAGUCA'), 'CUAGUCA')
self.assertEqual(g('---a---c---u----g---'), 'acug')
self.assertEqual(g(tuple('---a---c---u----g---')), tuple('acug'))
def test_gapList(self):
"""MolType gapList should return correct gap positions"""
g = RnaMolType.gapList
self.assertEqual(g(''), [])
self.assertEqual(g('ACUGUCAGUACGHFSDKJCUICDNINS'), [])
self.assertEqual(g('GUACGUIACAKJDC-SDFHJDSFK'), [14])
self.assertEqual(g('-DSHFUHDSF'), [0])
self.assertEqual(g('UACHASJAIDS-'), [11])
self.assertEqual(g('---CGAUgCAU---ACGHc---ACGUCAGU---'), \
[0,1,2,11,12,13,19,20,21,30,31,32])
a = MolType({'A':1}, Gaps=dict.fromkeys('!@#$%'))
g = a.gapList
self.assertEqual(g(''), [])
self.assertEqual(g('!!!'), [0,1,2])
self.assertEqual(g('!@#$!@#$!@#$'), range(12))
self.assertEqual(g('cguua!cgcuagua@cguasguadc#'), [5,14,25])
def test_gapVector(self):
"""MolType gapVector should return correct gap positions"""
g = RnaMolType.gapVector
self.assertEqual(g(''), [])
self.assertEqual(g('ACUGUCAGUACGHFSDKJCUICDNINS'), [False]*27)
self.assertEqual(g('GUACGUIACAKJDC-SDFHJDSFK'),
map(bool, map(int,'000000000000001000000000')))
self.assertEqual(g('-DSHFUHDSF'),
map(bool, map(int,'1000000000')))
self.assertEqual(g('UACHASJAIDS-'),
map(bool, map(int,'000000000001')))
self.assertEqual(g('---CGAUgCAU---ACGHc---ACGUCAGU---'), \
map(bool, map(int,'111000000001110000011100000000111')))
a = MolType({'A':1}, Gaps=dict.fromkeys('!@#$%'))
g = a.gapVector
self.assertEqual(g(''), [])
self.assertEqual(g('!!!'), map(bool, [1,1,1]))
self.assertEqual(g('!@#$!@#$!@#$'), [True] * 12)
self.assertEqual(g('cguua!cgcuagua@cguasguadc#'),
map(bool, map(int,'00000100000000100000000001')))
def test_gapMaps(self):
"""MolType gapMaps should return dicts mapping gapped/ungapped pos"""
empty = ''
no_gaps = 'aaa'
all_gaps = '---'
start_gaps = '--abc'
end_gaps = 'ab---'
mid_gaps = '--a--b-cd---'
gm = RnaMolType.gapMaps
self.assertEqual(gm(empty), ({},{}))
self.assertEqual(gm(no_gaps), ({0:0,1:1,2:2}, {0:0,1:1,2:2}))
self.assertEqual(gm(all_gaps), ({},{}))
self.assertEqual(gm(start_gaps), ({0:2,1:3,2:4},{2:0,3:1,4:2}))
self.assertEqual(gm(end_gaps), ({0:0,1:1},{0:0,1:1}))
self.assertEqual(gm(mid_gaps), ({0:2,1:5,2:7,3:8},{2:0,5:1,7:2,8:3}))
def test_countGaps(self):
"""MolType countGaps should return correct gap count"""
c = RnaMolType.countGaps
self.assertEqual(c(''), 0)
self.assertEqual(c('ACUGUCAGUACGHFSDKJCUICDNINS'), 0)
self.assertEqual(c('GUACGUIACAKJDC-SDFHJDSFK'), 1)
self.assertEqual(c('-DSHFUHDSF'), 1)
self.assertEqual(c('UACHASJAIDS-'), 1)
self.assertEqual(c('---CGAUgCAU---ACGHc---ACGUCAGU---'), 12)
a = MolType({'A':1}, Gaps=dict.fromkeys('!@#$%'))
c = a.countGaps
self.assertEqual(c(''), 0)
self.assertEqual(c('!!!'), 3)
self.assertEqual(c('!@#$!@#$!@#$'), 12)
self.assertEqual(c('cguua!cgcuagua@cguasguadc#'), 3)
def test_countDegenerate(self):
"""MolType countDegenerate should return correct degen base count"""
d = RnaMolType.countDegenerate
self.assertEqual(d(''), 0)
self.assertEqual(d('GACUGCAUGCAUCGUACGUCAGUACCGA'), 0)
self.assertEqual(d('N'), 1)
self.assertEqual(d('NRY'), 3)
self.assertEqual(d('ACGUAVCUAGCAUNUCAGUCAGyUACGUCAGS'), 4)
def test_possibilites(self):
"""MolType possibilities should return correct # possible sequences"""
p = RnaMolType.possibilities
self.assertEqual(p(''), 1)
self.assertEqual(p('ACGUgcaucagUCGuGCAU'), 1)
self.assertEqual(p('N'), 4)
self.assertEqual(p('R'), 2)
self.assertEqual(p('H'), 3)
self.assertEqual(p('nRh'), 24)
self.assertEqual(p('AUGCnGUCAg-aurGauc--gauhcgauacgws'), 96)
def test_MW(self):
"""MolType MW should return correct molecular weight"""
r = RnaMolType.MW
p = ProteinMolType.MW
self.assertEqual(p(''), 0)
self.assertEqual(r(''), 0)
self.assertFloatEqual(p('A'), 107.09)
self.assertFloatEqual(r('A'), 375.17)
self.assertFloatEqual(p('AAA'), 285.27)
self.assertFloatEqual(r('AAA'), 1001.59)
self.assertFloatEqual(r('AAACCCA'), 2182.37)
def test_canMatch(self):
"""MolType canMatch should return True if all positions can match"""
m = RnaMolType.canMatch
self.assertTrue(m('', ''))
self.assertTrue(m('UCAG', 'UCAG'))
self.assertFalse(m('UCAG', 'ucag'))
self.assertTrue(m('UCAG', 'NNNN'))
self.assertTrue(m('NNNN', 'UCAG'))
self.assertTrue(m('NNNN', 'NNNN'))
self.assertFalse(m('N', 'x'))
self.assertFalse(m('N', '-'))
self.assertTrue(m('UCAG', 'YYRR'))
self.assertTrue(m('UCAG', 'KMWS'))
def test_canMismatch(self):
"""MolType canMismatch should return True on any possible mismatch"""
m = RnaMolType.canMismatch
self.assertFalse(m('',''))
self.assertTrue(m('N', 'N'))
self.assertTrue(m('R', 'R'))
self.assertTrue(m('N', 'r'))
self.assertTrue(m('CGUACGCAN', 'CGUACGCAN'))
self.assertTrue(m('U', 'C'))
self.assertTrue(m('UUU', 'UUC'))
self.assertTrue(m('UUU', 'UUY'))
self.assertFalse(m('UUU', 'UUU'))
self.assertFalse(m('UCAG', 'UCAG'))
self.assertFalse(m('U--', 'U--'))
def test_mustMatch(self):
"""MolType mustMatch should return True when no possible mismatches"""
m = RnaMolType.mustMatch
self.assertTrue(m('',''))
self.assertFalse(m('N', 'N'))
self.assertFalse(m('R', 'R'))
self.assertFalse(m('N', 'r'))
self.assertFalse(m('CGUACGCAN', 'CGUACGCAN'))
self.assertFalse(m('U', 'C'))
self.assertFalse(m('UUU', 'UUC'))
self.assertFalse(m('UUU', 'UUY'))
self.assertTrue(m('UU-', 'UU-'))
self.assertTrue(m('UCAG', 'UCAG'))
def test_canPair(self):
"""MolType canPair should return True if all positions can pair"""
p = RnaMolType.canPair
self.assertTrue(p('', ''))
self.assertFalse(p('UCAG', 'UCAG'))
self.assertTrue(p('UCAG', 'CUGA'))
self.assertFalse(p('UCAG', 'cuga'))
self.assertTrue(p('UCAG', 'NNNN'))
self.assertTrue(p('NNNN', 'UCAG'))
self.assertTrue(p('NNNN', 'NNNN'))
self.assertFalse(p('N', 'x'))
self.assertFalse(p('N', '-'))
self.assertTrue(p('-', '-'))
self.assertTrue(p('UCAGU', 'KYYRR'))
self.assertTrue(p('UCAG', 'KKRS'))
self.assertTrue(p('U', 'G'))
d = DnaMolType.canPair
self.assertFalse(d('T', 'G'))
def test_canMispair(self):
"""MolType canMispair should return True on any possible mispair"""
m = RnaMolType.canMispair
self.assertFalse(m('',''))
self.assertTrue(m('N', 'N'))
self.assertTrue(m('R', 'Y'))
self.assertTrue(m('N', 'r'))
self.assertTrue(m('CGUACGCAN', 'NUHCHUACH'))
self.assertTrue(m('U', 'C'))
self.assertTrue(m('U', 'R'))
self.assertTrue(m('UUU', 'AAR'))
self.assertTrue(m('UUU', 'GAG'))
self.assertFalse(m('UUU', 'AAA'))
self.assertFalse(m('UCAG', 'CUGA'))
self.assertTrue(m('U--', '--U'))
d = DnaMolType.canPair
self.assertTrue(d('TCCAAAGRYY', 'RRYCTTTGGA'))
def test_mustPair(self):
"""MolType mustPair should return True when no possible mispairs"""
m = RnaMolType.mustPair
self.assertTrue(m('',''))
self.assertFalse(m('N', 'N'))
self.assertFalse(m('R', 'Y'))
self.assertFalse(m('A', 'A'))
self.assertFalse(m('CGUACGCAN', 'NUGCGUACG'))
self.assertFalse(m('U', 'C'))
self.assertFalse(m('UUU', 'AAR'))
self.assertFalse(m('UUU', 'RAA'))
self.assertFalse(m('UU-', '-AA'))
self.assertTrue(m('UCAG', 'CUGA'))
d = DnaMolType.mustPair
self.assertTrue(d('TCCAGGG', 'CCCTGGA'))
self.assertTrue(d('tccaggg', 'ccctgga'))
self.assertFalse(d('TCCAGGG', 'NCCTGGA'))
class RnaMolTypeTests(TestCase):
"""Spot-checks of alphabet functionality applied to RNA alphabet."""
def test_contains(self):
"""RnaMolType should __contain__ the expected symbols."""
keys = 'ucagrymkwsbhvdn?-'
for k in keys:
self.assertContains(RnaMolType, k)
for k in keys.upper():
self.assertContains(RnaMolType, k)
self.assertNotContains(RnaMolType, 'X')
def test_degenerateFromSequence(self):
"""RnaMolType degenerateFromSequence should give correct results"""
d = RnaMolType.degenerateFromSequence
#check monomers
self.assertEqual(d('a'), 'a')
self.assertEqual(d('C'), 'C')
#check seq of monomers
self.assertEqual(d('aaaaa'), 'a')
#check some 2- to 4-way cases
self.assertEqual(d('aaaaag'), 'r')
self.assertEqual(d('ccgcgcgcggcc'), 's')
self.assertEqual(d('accgcgcgcggcc'), 'v')
self.assertEqual(d('aaaaagcuuu'), 'n')
#check some cases with gaps
self.assertEqual(d('aa---aaagcuuu'), '?')
self.assertEqual(d('aaaaaaaaaaaaaaa-'), '?')
self.assertEqual(d('----------------'), '-')
#check mixed case example
self.assertEqual(d('AaAAaa'), 'A')
#check example with degenerate symbols in set
self.assertEqual(d('RS'), 'V')
self.assertEqual(d('RN-'), '?')
#check that it works for proteins as well
p = ProteinMolType.degenerateFromSequence
self.assertEqual(p('A'), 'A')
self.assertEqual(p('AAA'), 'A')
self.assertEqual(p('DN'), 'B')
self.assertEqual(p('---'), '-')
self.assertEqual(p('ACD'), 'X')
self.assertEqual(p('ABD'), 'X')
self.assertEqual(p('ACX'), 'X')
self.assertEqual(p('AC-'), '?')
class _AlphabetTestCase(TestCase):
def assertEqualSeqs(self, a, b):
"""For when we don't care about the type, just the elements"""
self.assertEqual(list(a), list(b))
def assertEqualSets(self, a, b):
self.assertEqual(set(a), set(b))
class DNAAlphabet(_AlphabetTestCase):
def setUp(self):
self.alpha = DNA.Alphabet
def test_exclude(self):
"""Nucleotide alphabet testing excluding gap motif"""
self.assertEqualSeqs(self.alpha, ['T','C','A','G'])
def test_include(self):
"""Nucleotide alphabet testing including gap motif"""
self.assertEqualSets(self.alpha.withGapMotif(), ['A','C','G','T','-'])
def test_usesubset(self):
"""testing using a subset of motifs."""
self.assertEqualSets(self.alpha.withGapMotif(), ['A','C','G','T','-'])
alpha = self.alpha.getSubset(motif_subset = ['A'])
self.assertEqualSets(alpha, ['A'])
#self.assertRaises(AlphabetError, self.alpha.getSubset, ['A','C'])
alpha = DNA.Alphabet
self.assertEqualSets(alpha, ['T','C','A','G'])
alpha = alpha.getSubset(motif_subset = ['A','T','G'])
self.assertEqualSets(alpha, ['A','G','T'])
class DinucAlphabet(_AlphabetTestCase):
def setUp(self):
self.alpha = DNA.Alphabet.withGapMotif().getWordAlphabet(2)
def test_exclude(self):
"""Dinucleotide alphabet testing excluding gap motif"""
expected = ['-A', '-C', '-G', '-T',
'A-', 'AA', 'AC', 'AG', 'AT',
'C-', 'CA', 'CC', 'CG', 'CT',
'G-', 'GA', 'GC', 'GG', 'GT',
'T-', 'TA', 'TC', 'TG', 'TT']
self.assertEqualSets(
self.alpha.getSubset(['--'], excluded=True)
, expected)
def test_include(self):
"""Dinucleotide alphabet testing including gap motif"""
expected = ['--', '-A', '-C', '-G', '-T',
'A-', 'AA', 'AC', 'AG', 'AT',
'C-', 'CA', 'CC', 'CG', 'CT',
'G-', 'GA', 'GC', 'GG', 'GT',
'T-', 'TA', 'TC', 'TG', 'TT']
self.assertEqualSets(self.alpha, expected)
def test_usesubset(self):
"""testing using a subset of motifs."""
alpha = self.alpha.getSubset(motif_subset = ['AA', 'CA','GT'])
self.assertEqualSeqs(alpha, ['AA', 'CA','GT'])
self.assertRaises(AlphabetError, alpha.getSubset, motif_subset = ['AA','CA','GT', 'TT'])
def test_usesubsetbyfreq(self):
"""testing using a subset of motifs by using motif probs."""
motif_freqs = {'--':0, '-A': 0.0, '-C': 0, '-G': 0, '-T': 0,
'A-': 0, 'AA': 1.0, 'AC': 0.0, 'AG': 0, 'AT': 0,
'C-': 0, 'CA': 1, 'CC': 0, 'CG': 0, 'CT': 0,
'G-': 0, 'GA': 0, 'GC': 0, 'GG': 0, 'GT': 1,
'T-': 0, 'TA': 0, 'TC': 0, 'TG': 0, 'TT': 0}
alpha = self.alpha.getSubset(motif_freqs)
self.assertEqualSets(alpha, ['AA', 'CA', 'GT'])
class CodonAlphabet(_AlphabetTestCase):
def setUp(self):
self.alpha = STANDARD_CODON
def test_ambiguous_gaps(self):
alpha = self.alpha.withGapMotif()
self.assertEqual(len(alpha.resolveAmbiguity('AT?')), 4)
self.assertRaises(Exception, alpha.resolveAmbiguity, 'at-')
self.assertEqual(len(alpha.resolveAmbiguity('???')), 62)
self.assertEqual(len(alpha.resolveAmbiguity('---')), 1)
alpha = self.alpha
self.assertEqual(len(alpha.resolveAmbiguity('AT?')), 4)
self.assertRaises(Exception, alpha.resolveAmbiguity, 'at-')
self.assertEqual(len(alpha.resolveAmbiguity('???')), 61)
self.assertRaises(Exception, alpha.resolveAmbiguity, '---')
def test_exclude(self):
"""testing excluding gap motif"""
alpha = self.alpha
expected = ['AAA', 'AAC', 'AAG', 'AAT', 'ACA',
'ACC', 'ACG', 'ACT', 'AGA', 'AGC',
'AGG', 'AGT', 'ATA', 'ATC', 'ATG',
'ATT', 'CAA', 'CAC', 'CAG', 'CAT',
'CCA', 'CCC', 'CCG', 'CCT', 'CGA',
'CGC', 'CGG', 'CGT', 'CTA', 'CTC',
'CTG', 'CTT', 'GAA', 'GAC', 'GAG',
'GAT', 'GCA', 'GCC', 'GCG', 'GCT',
'GGA', 'GGC', 'GGG', 'GGT', 'GTA',
'GTC', 'GTG', 'GTT', 'TAC', 'TAT',
'TCA', 'TCC', 'TCG', 'TCT', 'TGC',
'TGG', 'TGT', 'TTA', 'TTC', 'TTG',
'TTT']
self.assertEqualSets(alpha, expected)
def test_include(self):
"""testing including gap motif"""
alpha = self.alpha.withGapMotif()
expected = ['---', 'AAA', 'AAC', 'AAG', 'AAT', 'ACA',
'ACC', 'ACG', 'ACT', 'AGA', 'AGC',
'AGG', 'AGT', 'ATA', 'ATC', 'ATG',
'ATT', 'CAA', 'CAC', 'CAG', 'CAT',
'CCA', 'CCC', 'CCG', 'CCT', 'CGA',
'CGC', 'CGG', 'CGT', 'CTA', 'CTC',
'CTG', 'CTT', 'GAA', 'GAC', 'GAG',
'GAT', 'GCA', 'GCC', 'GCG', 'GCT',
'GGA', 'GGC', 'GGG', 'GGT', 'GTA',
'GTC', 'GTG', 'GTT', 'TAC', 'TAT',
'TCA', 'TCC', 'TCG', 'TCT', 'TGC',
'TGG', 'TGT', 'TTA', 'TTC', 'TTG',
'TTT']
self.assertEqualSets(alpha, expected)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_core/test_profile.py 000644 000765 000024 00000100444 12024702176 022446 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Provides tests for classes and functions in profile.py
"""
from __future__ import division
from string import translate
from numpy import array, sum, sqrt, transpose, add, subtract, multiply,\
divide, zeros
from numpy.random import random
from cogent.util.unit_test import TestCase, main#, numpy_err
from cogent.core.moltype import DNA
from cogent.core.sequence import ModelSequence
from cogent.core.profile import Profile, ProfileError, CharMeaningProfile
from cogent.core.alignment import DenseAlignment as Alignment
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Gavin Huttley", "Rob Knight",
"Peter Maxwell"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Production"
class ProfileTests(TestCase):
"""Tests for Profile object"""
def setUp(self):
"""setUp method for all Profile tests"""
self.full = Profile(array([[2,4],[3,5],[4,8]]),"AB")
self.empty = Profile(array([[]]),"AB")
self.empty_row = Profile(array([[1,1],[0,0]]), "AB")
self.empty_col = Profile(array([[0,1],[0,1]]), "AB")
self.consensus = Profile(array([[.2,0,.8,0],[0,.1,.2,.7],[0,0,0,1],\
[.2,.3,.4,.1],[.5,.5,0,0]]),\
Alphabet=DNA, CharOrder="TCAG")
self.not_same_value = Profile(array([[.3,.5,.1,.1],[.4,.6,0,.7],\
[.3,.2,0,0],[0,0,4,0]]),Alphabet=DNA, CharOrder="TCAG")
self.zero_entry = Profile(array([[.3,.2,0,.5],[0,0,.8,.2]]),\
Alphabet="UCAG")
self.score1 = Profile(Data=array([[-1,0,1,2],[-2,2,0,0],[-3,5,1,0]]),\
Alphabet=DNA, CharOrder="ATGC")
self.score2 = Profile(array([[.2,.4,.4,0],[.1,0,.9,0],[.1,.2,.3,.4]]),\
Alphabet="TCAG")
self.oned = Profile(array([.25,.25,.25,.25]),"ABCD")
self.pp = Profile(array([[1,2,3,4],[5,6,7,8],[9,10,11,12]]),"ABCD")
def test_init(self):
"""__init__: should set all attributed correctly"""
self.assertRaises(TypeError, Profile)
self.assertRaises(TypeError, Profile, array([[2,3]]))
#only alphabet
p = Profile(array([[.2,.8],[.7,.3]]),"AB")
self.assertEqual(p.Data, [[.2,.8],[.7,.3]])
self.assertEqual(p.Alphabet, "AB")
self.assertEqual(p.CharOrder, list("AB"))
self.assertEqual(translate("ABBA",p._translation_table),
"\x00\x01\x01\x00")
#alphabet and char order
p = Profile(array([[.1,.2],[.4,.3]]),Alphabet=DNA,
CharOrder="AG")
self.assertEqual(p.CharOrder,"AG")
assert p.Alphabet is DNA
#non-character alphabet
p = Profile(array([[.1,.2],[.4,.3]]),Alphabet=[7,3],
CharOrder=[3,7])
self.assertEqual(p.CharOrder,[3,7])
self.assertEqual(p.Alphabet, [7,3])
self.assertEqual(p.Data, [[.1,.2],[.4,.3]])
def test_str(self):
"""__str__: should return string representation of data in profile
"""
self.assertEqual(str(self.empty_row),str(array([[1,1],[0,0]])))
def test_make_translation_table(self):
"""_make_translation_table: should return correct table from char order
"""
p = Profile(array([[.2,.8],[.7,.3]]),"ABCDE","AB")
self.assertEqual(translate("ABBA",p._translation_table),
"\x00\x01\x01\x00")
def test_hasValidData(self):
"""hasValidData: should work on full and empty profiles"""
full = self.full.copy()
full.normalizePositions()
self.assertEqual(full.hasValidData(),True)
self.assertEqual(self.empty_row.hasValidData(),False)
self.assertEqual(self.empty.hasValidData(),False)
def test_hasValidAttributes(self):
"""hasValidAttributes: should work for different alphabets/char orders
"""
p = Profile(array([[1,2],[3,4]]),Alphabet="ABCD", CharOrder="BAC")
#self.Data doesn't match len(CharOrder)
self.assertEqual(p.hasValidAttributes(),False)
p = Profile(array([[1,2],[3,4]]),Alphabet="ABCD", CharOrder="AX")
#not all chars in CharOrder in Alphabet
self.assertEqual(p.hasValidAttributes(),False)
p = Profile(array([[1,2],[3,4]]),Alphabet="ABCD", CharOrder="CB")
#should be fine
self.assertEqual(p.hasValidAttributes(),True)
def test_isValid(self):
"""isValid: should work as expected"""
#everything valid
p1 = Profile(array([[.3,.7],[.8,.2]]),Alphabet="AB",CharOrder="AB")
#invalid data, valid attributes
p2 = Profile(array([[1,2],[3,4]]),Alphabet="ABCD", CharOrder="BA")
#invalid attributes, valid data
p3 = Profile(array([[.3,.7],[.8,.2]]),Alphabet="ABCD",CharOrder="AF")
self.assertEqual(p1.isValid(),True)
self.assertEqual(p2.isValid(),False)
self.assertEqual(p3.isValid(),False)
def test_dataAt(self):
"""dataAt: should work on valid position and character"""
p = Profile(array([[.2,.4,.4,0],[.1,0,.9,0],[.1,.2,.3,.4]]),\
Alphabet="TCAG")
self.assertEqual(p.dataAt(0,'C'),.4)
self.assertEqual(p.dataAt(1,'T'),.1)
self.assertRaises(ProfileError, p.dataAt, 1, 'U')
self.assertRaises(ProfileError, p.dataAt, -2, 'T')
self.assertRaises(ProfileError, p.dataAt, 5, 'T')
def test_copy(self):
"""copy: should act as expected while rebinding/modifying attributes
"""
p = Profile(array([[1,1],[.7,.3]]),{'A':'A','G':'G','R':'AG'},"AG")
p_copy = p.copy()
assert p.Data is p_copy.Data
assert p.Alphabet is p_copy.Alphabet
assert p.CharOrder is p_copy.CharOrder
#modifying p.Data modifies p_copy.Data
p.Data[1,1] = 100
assert p.Alphabet is p_copy.Alphabet
#normalizing p.Data rebinds it, so p_copy.Data is unchanged
p.normalizePositions()
assert not p.Data is p_copy.Data
#Adding something to the alphabet changes both p and p_copy
p.Alphabet['Y']='TC'
assert p.Alphabet is p_copy.Alphabet
#Rebinding the CharOrder does only change the original
p.CharOrder='XX'
assert not p.CharOrder is p_copy.CharOrder
def test_normalizePositions(self):
"""normalizePositions: should normalize or raise appropriate error
"""
p = self.full.copy()
p.normalizePositions()
self.assertEqual(p.Data,array([[2/6,4/6],[3/8,5/8],[4/12,8/12]]))
self.assertEqual(sum(p.Data,1),[1,1,1])
p = self.empty_col.copy()
p.normalizePositions()
self.assertEqual(p.Data,array([[0,1],[0,1]]))
p = self.empty_row.copy()
self.assertRaises(ProfileError,p.normalizePositions)
p = Profile(array([[0.0,0.0]]),"AB")
self.assertRaises(ProfileError,p.normalizePositions)
#negative numbers!!!!!!
p1 = Profile(array([[3,-2],[4,-3]]),"AB")
p1.normalizePositions()
self.assertEqual(p1.Data,array([[3,-2],[4,-3]]))
p2 = Profile(array([[3,-3],[4,-3]]),"AB")
self.assertRaises(ProfileError,p2.normalizePositions)
def test_normalizeSequences(self):
"""normalizeSequences: should normalize or raise appropriate error
"""
p = self.full.copy()
p.normalizeSequences()
self.assertEqual(p.Data,array([[2/9,4/17],[3/9,5/17],[4/9,8/17]]))
self.assertEqual(sum(p.Data, axis=0),[1,1])
p = self.empty_row.copy()
p.normalizeSequences()
self.assertEqual(p.Data,array([[1,1],[0,0]]))
p = self.empty_col.copy()
self.assertRaises(ProfileError,p.normalizeSequences)
p = Profile(array([[0.0],[0.0]]),"AB")
self.assertRaises(ProfileError,p.normalizeSequences)
#negative numbers!!!!!!
p1 = Profile(array([[3,4],[-2,-3]]),"AB")
p1.normalizeSequences()
self.assertEqual(p1.Data,array([[3,4],[-2,-3]]))
p2 = Profile(array([[3,4],[-3,-3]]),"AB")
self.assertRaises(ProfileError,p2.normalizeSequences)
def test_prettyPrint_without_parameters(self):
"""prettyPrint: should work without parameters passed in"""
p = self.full
self.assertEqual(p.prettyPrint(),"2\t4\n3\t5\n4\t8")
self.assertEqual(p.prettyPrint(include_header=True),\
"A\tB\n2\t4\n3\t5\n4\t8")
self.assertEqual(p.prettyPrint(transpose_data=True),\
"2\t3\t4\n4\t5\t8")
self.assertEqual(p.prettyPrint(include_header=True,\
transpose_data=True),"A\t2\t3\t4\nB\t4\t5\t8")
#empty
self.assertEqual(self.empty.prettyPrint(),"")
self.assertEqual(self.empty.prettyPrint(transpose_data=True),"")
#it will still print with invalid data (e.g if len(CharOrder)
#doesn't match the data
p = self.full.copy()
p.CharOrder="ABC"
self.assertEqual(p.prettyPrint(include_header=True),\
"A\tB\tC\n2\t4\t \n3\t5\t \n4\t8\t ")
#it will truncate the CharOrder if data is transposed
#and CharOrder is longer then the number of rows in the
#transposed data
self.assertEqual(p.prettyPrint(include_header=True,\
transpose_data=True),"A\t2\t3\t4\nB\t4\t5\t8")
def test_prettyPrint_four_cases(self):
"""prettyPrint: with/without header/transpose/limit"""
p = self.full
p = self.pp
self.assertEqual(p.prettyPrint(),\
"1\t 2\t 3\t 4\n5\t 6\t 7\t 8\n9\t10\t11\t12")
self.assertEqual(p.prettyPrint(column_limit=3),\
"1\t 2\t 3\n5\t 6\t 7\n9\t10\t11")
self.assertEqual(p.prettyPrint(column_limit=3, include_header=True),\
"A\t B\t C\n1\t 2\t 3\n5\t 6\t 7\n9\t10\t11")
self.assertEqual(p.prettyPrint(column_limit=3, include_header=False,\
transpose_data=True),\
"1\t5\t 9\n2\t6\t10\n3\t7\t11\n4\t8\t12")
self.assertEqual(p.prettyPrint(column_limit=2, include_header=False,\
transpose_data=True),\
"1\t5\n2\t6\n3\t7\n4\t8")
self.assertEqual(p.prettyPrint(column_limit=3, include_header=True,\
transpose_data=True),\
"A\t1\t5\nB\t2\t6\nC\t3\t7\nD\t4\t8")
def test_reduce_wrong_size(self):
"""reduce: should fail when profiles have different sizes"""
p1 = Profile(array([[1,0],[0,1]]),Alphabet="AB")
p2 = Profile(array([[1,0,0],[1,0,0]]),Alphabet="ABC")
self.assertRaises(ProfileError,p1.reduce,p2)
def test_reduce_normalization_error(self):
"""reduce: fails when input or output can't be normalized"""
#Will raise errors when input data can't be normalized
self.assertRaises(ProfileError,self.empty.reduce,self.empty,add)
self.assertRaises(ProfileError,self.full.reduce,self.empty_row,add)
#don't normalize input, but do normalize output
#fails when one row adds up to zero
p1 = Profile(array([[3,3],[4,4]]),"AB")
p2 = Profile(array([[3,3],[-4,-4]]),"AB")
self.assertRaises(ProfileError,p1.reduce,p2,add,False,True)
def test_reduce_operators(self):
"""reduce: should work fine with different operators
"""
#different operators, normalize input, don't normalize output
p1 = Profile(array([[1,0,0],[0,1,0]]),Alphabet="ABC")
p2 = Profile(array([[1,0,0],[0,0,1]]),Alphabet="ABC")
self.assertEqual(p1.reduce(p2).Data,array([[1,0,0],[0,.5,.5]]))
self.assertEqual(p1.reduce(p2,add,normalize_input=True,\
normalize_output=False).Data,array([[2,0,0],[0,1,1]]))
self.assertEqual(p1.reduce(p2,subtract,normalize_input=True,\
normalize_output=False).Data,array([[0,0,0],[0,1,-1]]))
self.assertEqual(p1.reduce(p2,multiply,normalize_input=True,\
normalize_output=False).Data,array([[1,0,0],[0,0,0]]))
self.assertRaises(ProfileError,p1.reduce,p2,divide,\
normalize_input=True,normalize_output=False)
#don't normalize and normalize only input
p3 = Profile(array([[1,2],[3,4]]),Alphabet="AB")
p4 = Profile(array([[4,3],[2,1]]),Alphabet="AB")
self.assertEqual(p3.reduce(p4,add,normalize_input=False,\
normalize_output=False).Data,array([[5,5],[5,5]]))
self.assertFloatEqual(p3.reduce(p4,add,normalize_input=True,\
normalize_output=False).Data,array([[19/21,23/21],[23/21,19/21]]))
#normalize input and output
p5 = Profile(array([[1,1,0,0],[1,1,1,1]]),Alphabet="ABCD")
p6 = Profile(array([[1,0,0,0],[1,0,0,1]]),Alphabet="ABCD")
self.assertEqual(p5.reduce(p6,add,normalize_input=True,\
normalize_output=True).Data,array([[.75,.25,0,0],\
[.375,.125,.125,.375]]))
#it can collapse empty profiles when normalizing is turned off
self.assertEqual(self.empty.reduce(self.empty,\
normalize_input=False,normalize_output=False).Data.tolist(),[[]])
#more specific tests of the operators will be in the
#separate functions
def test__add_(self):
"""__add__: should not normalize input or output, just add"""
p1 = Profile(array([[.3,.4,.1,0],[.1,.1,.1,.7]]),Alphabet="ABCD")
p2 = Profile(array([[1,0,0,0],[1,0,0,1]]),Alphabet="ABCD")
self.assertEqual((p1+p2).Data, array([[1.3,.4,.1,0],[1.1,.1,.1,1.7]]))
self.assertRaises(ProfileError,self.empty.__add__, p1)
self.assertEqual((self.empty + self.empty).Data.tolist(),[[]])
def test__sub_(self):
"""__sub__: should subtract two profiles, no normalization"""
p1 = Profile(array([[.3,.4,.1,0],[.1,.1,.1,.7]]),Alphabet="ABCD")
p2 = Profile(array([[1,0,0,0],[1,0,0,1]]),Alphabet="ABCD")
self.assertFloatEqual((p1-p2).Data, array([[-.7,.4,.1,0],\
[-.9,.1,.1,-.3]]))
def test__mul_(self):
"""__mul__: should multiply two profiles, no normalization"""
p1 = Profile(array([[1,-2,3,0],[1,1,1,.5]]),Alphabet="ABCD")
p2 = Profile(array([[1,0,0,0],[1,0,3,2]]),Alphabet="ABCD")
self.assertEqual((p1*p2).Data, array([[1,0,0,0],\
[1,0,3,1]]))
def test__div_(self):
"""__div__ and __truediv__: always true division b/c __future__.division
"""
p1 = Profile(array([[2,3],[4,5]]),"AB")
p2 = Profile(array([[1,0],[4,5]]),"AB") #Int 0
p3 = Profile(array([[1,0.0],[4,5]]),"AB") #Float 0.0
p4 = Profile(array([[1,2],[8.0,5]]),"AB") #Float 0.0
self.assertRaises(ProfileError, p1.__truediv__,p2)
#infinity in result data
self.assertRaises(ProfileError, p1.__div__, p3)
self.assertFloatEqual((p1.__div__(p4)).Data, array([[2,1.5],[0.5,1]]))
def test_distance(self):
"""distance: should return correct distance between the profiles
"""
p1 = Profile(array([[2,4],[3,1]]), "AB")
p2 = Profile(array([[4,6],[5,3]]), "AB")
p3 = Profile(array([[4,6],[5,3],[1,1]]), "AB")
p4 = Profile(array([2,2]),"AB")
p5 = Profile(array([2,2,2]),"AB")
p6 = Profile(array([[]]),"AB")
self.assertEqual(p1.distance(p2),4)
self.assertEqual(p2.distance(p1),4)
self.assertEqual(p1.distance(p4),sqrt(6))
self.assertEqual(p6.distance(p6),0)
#Raises error when frames are not aligned
self.assertRaises(ProfileError, p1.distance,p3)
self.assertRaises(ProfileError,p1.distance,p5)
def test_toOddsMatrix(self):
"""toOddsMatrix: should work on valid data or raise an error
"""
p = Profile(array([[.1,.3,.5,.1],[.25,.25,.25,.25],\
[.05,.8,.05,.1],[.7,.1,.1,.1],[.6,.15,.05,.2]]),\
Alphabet="ACTG")
p_exp = Profile(array([[.4, 1.2, 2, .4],[1,1,1,1],[.2,3.2,.2,.4],\
[2.8,.4,.4,.4],[2.4,.6,.2,.8]]),Alphabet="ACTG")
self.assertEqual(p.toOddsMatrix().Data,p_exp.Data)
assert p.Alphabet is p.toOddsMatrix().Alphabet
self.assertEqual(p.toOddsMatrix([.25,.25,.25,.25]).Data,p_exp.Data)
#fails if symbol_freqs has wrong size
self.assertRaises(ProfileError, p.toOddsMatrix,\
[.25,.25,.25,.25,.25,.25])
self.assertRaises(ProfileError, self.zero_entry.toOddsMatrix,\
[.1,.2,.3])
#works on empty profile
self.assertEqual(self.empty.toOddsMatrix().Data.tolist(),[[]])
#works with different input
self.assertEqual(self.zero_entry.toOddsMatrix().Data,\
array([[1.2,.8,0,2],[0,0,3.2,.8]]))
self.assertFloatEqual(self.zero_entry.toOddsMatrix([.1,.2,.3,.4]).Data,\
array([[3,1,0,1.25],[0,0,2.667,.5]]),1e-3)
#fails when one of the background frequencies is 0
self.assertRaises(ProfileError, self.zero_entry.toOddsMatrix,\
[.1,.2,.3,0])
def test_toLogOddsMatrix(self):
"""toLogOddsMatrix: should work as expected"""
#This test can be short, because it mainly depends on toOddsMatrix
#for which everything has been tested
p = Profile(array([[.1,.3,.5,.1],[.25,.25,.25,.25],\
[.05,.8,.05,.1],[.7,.1,.1,.1],[.6,.15,.05,.2]]),\
Alphabet="ACTG")
p_exp = Profile(array(\
[[-1.322, 0.263, 1., -1.322],\
[ 0., 0., 0., 0.],\
[-2.322, 1.678, -2.322, -1.322],\
[ 1.485, -1.322, -1.322, -1.322],\
[ 1.263, -0.737, -2.322, -0.322]]),\
Alphabet="ACTG")
self.assertFloatEqual(p.toLogOddsMatrix().Data,p_exp.Data,eps=1e-3)
#works on empty matrix
self.assertEqual(self.empty.toLogOddsMatrix().Data.tolist(),[[]])
def test__score_indices(self):
"""_score_indices: should work on valid input"""
self.assertEqual(self.score1._score_indices(array([0,1,1,3,0,3]),\
offset=0),[6,2,-3,0])
self.assertFloatEqual(self.score2._score_indices(\
array([3,1,2,0,2,2,3]), offset=0),[.3,1.4,.8,1.4,1.7])
self.assertFloatEqual(self.score2._score_indices(\
array([3,1,2,0,2,2,3]), offset=3),[1.4,1.7])
#Errors will be raised on invalid input. Errors are not handled
#in this method. Validation of the input is done elsewhere
self.assertRaises(IndexError,self.score2._score_indices,\
array([3,1,63,0,4,2,3]), offset=3)
def test__score_profile(self):
"""_score_profile: should work on valid input"""
p1 = Profile(array([[1,0,0,0],[0,1,0,0],[0,0,.5,.5],[0,0,0,1],\
[.25,.25,.25,.25]]),"TCAG")
p2 = Profile(array([[0,1,0,0],[.2,0,.8,0],[0,0,.5,.5],[1/3,1/3,0,1/3],\
[.25,.25,.25,.25]]),"TCAG")
self.assertFloatEqual(self.score2._score_profile(p1,offset=0),\
[.55,1.25,.45])
self.assertFloatEqual(self.score2._score_profile(p1,offset=2),\
[.45])
self.assertFloatEqual(self.score2._score_profile(p2,offset=0),\
[1.49,1.043,.483],1e-3)
#Errors will be raised on invalid input. Errors are not handled
#in this method. Validation of the input is done elsewhere
#In this case you don't get an error, but for sure an unexpected
#result
self.assertFloatEqual(self.score2._score_profile(p1,offset=3).tolist(),\
[])
def test_score_sequence(self):
"""score: should work correctly for Sequence as input
"""
#works on normal valid data
s1 = self.score1.score("ATTCAC",offset=0)
self.assertEqual(s1,\
[6,2,-3,0])
self.assertFloatEqual(self.score2.score("TCAAGT",offset=0),
[.5,1.6,1.7,0.5])
#works with different offset
self.assertFloatEqual(self.score2.score("TCAAGT",offset=2),
[1.7,0.5])
self.assertFloatEqual(self.score2.score("TCAAGT",offset=3),
[0.5])
#raises error on invalid offset
self.assertRaises(ProfileError,self.score2.score,\
"TCAAGT",offset=4)
#works on seq of minimal length
self.assertFloatEqual(self.score2.score("AGT",offset=0),
[0.5])
#raises error when sequence is too short
self.assertRaises(ProfileError, self.score2.score,"",offset=0)
#raises error on empty profile
self.assertRaises(ProfileError,self.empty.score,"ACGT")
#raises error when sequence contains characters that
#are not in the characterorder
self.assertRaises(ProfileError,self.score2.score,"ACBRT")
def test_score_sequence_object(self):
"""score: should work correctly on Sequence object as input
"""
# DnaSequence object
ds = self.score1.score(DNA.Sequence("ATTCAC"),offset=0)
self.assertEqual(ds, [6,2,-3,0])
# ModelSequence object
ms = self.score1.score(ModelSequence("ATTCAC", Alphabet=DNA.Alphabet),\
offset=0)
self.assertEqual(ms, [6,2,-3,0])
def test_score_no_trans_table(self):
"""score: should work when no translation table is present
"""
p = Profile(Data=array([[-1,0,1,2],[-2,2,0,0],[-3,5,1,0]]),\
Alphabet=DNA, CharOrder="ATGC")
# remove translation table
del p.__dict__['_translation_table']
# then score the profile
s1 = p.score(DNA.Sequence("ATTCAC"),offset=0)
self.assertEqual(s1, [6,2,-3,0])
def test_score_profile(self):
"""score: should work correctly for Profile as input
"""
p1 = Profile(array([[1,0,0,0],[0,1,0,0],[0,0,.5,.5],[0,0,0,1],\
[.25,.25,.25,.25]]),"TCAG")
p2 = Profile(array([[0,1,0,0],[.2,0,.8,0],[0,0,.5,.5],[1/3,1/3,0,1/3],\
[.25,.25,.25,.25]]),"TCAG")
p3 = Profile(array([[1,0,0,0],[0,1,0,0],[0,0,0,1]]),"TCAG")
p4 = Profile(array([[1,0,0,0],[0,1,0,0]]),"TCAG")
p5 = Profile(array([[1,0,0,0],[0,1,0,0],[0,0,0,1]]),"AGTC")
#works on normal valid data
self.assertFloatEqual(self.score2.score(p1,offset=0),\
[.55,1.25,.45])
self.assertFloatEqual(self.score2.score(p2,offset=0),
[1.49,1.043,.483],1e-3)
#works with different offset
self.assertFloatEqual(self.score2.score(p1,offset=1),
[1.25,0.45])
self.assertFloatEqual(self.score2.score(p1,offset=2),
[0.45])
#raises error on invalid offset
self.assertRaises(ProfileError,self.score2.score,\
p1,offset=3)
#works on profile of minimal length
self.assertFloatEqual(self.score2.score(p3,offset=0),
[0.6])
#raises error when profile is too short
self.assertRaises(ProfileError, self.score2.score,p4,offset=0)
#raises error on empty profile
self.assertRaises(ProfileError,self.empty.score,p1)
#raises error when character order doesn't match
self.assertRaises(ProfileError,self.score2.score,p5)
def test_rowUncertainty(self):
"""rowUncertainty: should handle full and empty profiles
"""
p = Profile(array([[.25,.25,.25,.25],[.5,.5,0,0]]),"ABCD")
self.assertEqual(p.rowUncertainty(),[2,1])
#for empty rows 0 is returned as the uncertainty
self.assertEqual(self.empty.rowUncertainty().tolist(),[])
p = Profile(array([[],[],[]]),"")
self.assertEqual(p.rowUncertainty().tolist(),[])
#doesn't work on 1D array
self.assertRaises(ProfileError,self.oned.rowUncertainty)
def test_columnUncertainty(self):
"""columnUncertainty: should handle full and empty profiles
"""
p = Profile(array([[.25,.5],[.25,.5],[.25,0],[.25,0]]),"AB")
self.assertEqual(p.columnUncertainty(),[2,1])
#for empty cols nothing is returned as the uncertainty
self.assertEqual(self.empty.columnUncertainty().tolist(),[])
p = Profile(array([[],[],[]]),"")
self.assertEqual(p.columnUncertainty().tolist(),[])
#doesn't work on 1D array
self.assertRaises(ProfileError,self.oned.columnUncertainty)
def test_rowDegeneracy(self):
"""rowDegneracy: should work as expected"""
p1 = self.consensus
p2 = self.not_same_value
self.assertEqual(p1.rowDegeneracy(),[1,1,1,2,1])
self.assertEqual(p1.rowDegeneracy(cutoff=.5),[1,1,1,2,1])
self.assertEqual(p1.rowDegeneracy(cutoff=.75),[1,2,1,3,2])
#when a row seems to add up to the cutoff value, it's not
#always found because of floating point error. E.g. second row
#in this example
self.assertEqual(p1.rowDegeneracy(cutoff=1),[2,4,1,4,2])
#when the cutoff can't be found, the number of columns in the
#profile is returned (for each row)
self.assertEqual(p1.rowDegeneracy(cutoff=1.5),[4,4,4,4,4])
self.assertEqual(p2.rowDegeneracy(cutoff=.95),[4,2,4,1])
self.assertEqual(p2.rowDegeneracy(cutoff=1.4),[4,3,4,1])
self.assertEqual(self.empty.rowDegeneracy(),[])
def test_columnDegeneracy(self):
"""columnDegeneracy: shoudl work as expected"""
p1 = self.consensus
p1.Data = transpose(p1.Data)
p2 = self.not_same_value
p2.Data = transpose(p2.Data)
p1d = p1.columnDegeneracy()
self.assertEqual(p1d,[1,1,1,2,1])
self.assertEqual(p1.columnDegeneracy(cutoff=.5),[1,1,1,2,1])
self.assertEqual(p1.columnDegeneracy(cutoff=.75),[1,2,1,3,2])
#when a row seems to add up to the cutoff value, it's not
#always found because of floating point error. E.g. second row
#in this example
self.assertEqual(p1.columnDegeneracy(cutoff=1),[2,4,1,4,2])
#when the cutoff can't be found, the number of rows in the
#profile is returned (for each column)
self.assertEqual(p1.columnDegeneracy(cutoff=1.5),[4,4,4,4,4])
self.assertEqual(p2.columnDegeneracy(cutoff=.95),[4,2,4,1])
self.assertEqual(p2.columnDegeneracy(cutoff=1.4),[4,3,4,1])
self.assertEqual(self.empty.columnDegeneracy(),[])
def test_rowMax(self):
"""rowMax should return max value in each row"""
p1 = self.consensus
obs = p1.rowMax()
self.assertEqual(obs, array([.8, .7, 1, .4, .5]))
def test_toConsensus(self):
"""toConsensus: should work with all the different options
"""
p = self.consensus
self.assertEqual(p.toConsensus(fully_degenerate=False),"AGGAT")
self.assertEqual(p.toConsensus(fully_degenerate=True),"WVGNY")
self.assertEqual(p.toConsensus(cutoff=0.75),"ARGHY")
self.assertEqual(p.toConsensus(cutoff=0.95),"WVGNY")
self.assertEqual(p.toConsensus(cutoff=2),"WVGNY")
p = self.not_same_value
self.assertEqual(p.toConsensus(fully_degenerate=False),"CGTA")
self.assertEqual(p.toConsensus(fully_degenerate=True),"NBYA")
self.assertEqual(p.toConsensus(cutoff=0.75),"YSYA")
self.assertEqual(p.toConsensus(cutoff=2),"NBYA")
self.assertEqual(p.toConsensus(cutoff=5),"NBYA")
#when you specify both fully_generate and a cutoff value
#the cutoff takes priority and is used in the calculation
self.assertEqual(p.toConsensus(cutoff=0.75,fully_degenerate=True),\
"YSYA")
#raises AttributeError when Alphabet doens't have Degenerates
p = Profile(array([[.2,.8],[.7,.3]]),"AB")
self.assertRaises(AttributeError,p.toConsensus,cutoff=.5)
def test_toConsensus_include_all(self):
"""toConsensus: Should include all possibilities when include_all=True
"""
p1 = Profile(array([[.2,0,.8,0],[0,.1,.2,.7],[0,0,0,1],\
[.2,.3,.4,.1],[.5,.5,0,0]]),\
Alphabet=DNA, CharOrder="TCAG")
self.assertEqual(p1.toConsensus(cutoff=0.4, include_all=True),\
"AGGAY")
p2 = Profile(array([[.25,0.25,.25,0.25],[0.1,.1,.1,0],\
[.4,0,.4,0],[0,.2,0.2,0.3]]),\
Alphabet=DNA, CharOrder="TCAG")
self.assertEqual(p2.toConsensus(cutoff=0.4,\
include_all=True), "NHWV")
def test_randomIndices(self):
"""randomIndices: 99% of new frequencies should be within 3*SD
"""
r_num, c_num = 100,20
num_elements = r_num*c_num
r = random([r_num,c_num])
p = Profile(r,"A"*c_num)
p.normalizePositions()
d = p.Data
n = 1000
#Test only works on normalized profile, b/c of 1-d below
means = n*d
three_stds = sqrt(d*(1-d)*n)*3
result = [p.randomIndices() for x in range(n)]
a = Alignment(transpose(result))
def absoluteProfile(alignment,char_order):
f = a.columnFreqs()
res = zeros([len(f),len(char_order)])
for row, freq in enumerate(f):
for i in freq:
res[row, ord(i)] = freq[i]
return res
ap = absoluteProfile(a,p.CharOrder)
failure = abs(ap-means) > three_stds
assert sum(sum(failure))/num_elements <= 0.01
def test_randomSequence(self):
"""randomSequence: 99% of new frequencies should be within 3*SD"""
r_num, c_num = 100,20
num_elements = r_num*c_num
alpha = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
r = random([r_num,c_num])
p = Profile(r,alpha[:c_num])
p.normalizePositions()
d = p.Data
n = 1000
#Test only works on normalized profile, b/c of 1-d below
means = n*d
three_stds = sqrt(d*(1-d)*n)*3
a = Alignment([p.randomSequence() for x in range(n)])
def absoluteProfile(alignment,char_order):
f = a.columnFreqs()
res = zeros([len(f),len(char_order)])
for row, freq in enumerate(f):
for i in freq:
col = char_order.index(i)
res[row, col] = freq[i]
return res
ap = absoluteProfile(a,p.CharOrder)
failure = abs(ap-means) > three_stds
assert sum(sum(failure))/num_elements <= 0.01
class ModuleLevelFunctionsTest(TestCase):
"""Contains tests for the module level functions in profile.py"""
def setUp(self):
"""setUp to change the alphabet for testing general CharMeaningProfile
"""
self.alt_dna = DNA
DnaDegenerateSymbols = {'R':'AG','N':'TCAG','Y':'TC','?':'TCAG-'}
self.alt_dna.Degenerates = DnaDegenerateSymbols
def test_CharMeaningProfile(self):
"""CharMeaningProfile: should work as expected
"""
p1 = CharMeaningProfile(self.alt_dna,"AGCT")
p1_exp = [('A',[1,0,0,0]),('G',[0,1,0,0]),('C',[0,0,1,0]),\
('T',[0,0,0,1])]
p2 = CharMeaningProfile(self.alt_dna,"TCAG")
p2_exp = [('A',[0,0,1,0]),('G',[0,0,0,1]),('C',[0,1,0,0]),\
('T',[1,0,0,0])]
#split_degen, but only whose chars are all in char order
#so ? is ignored right now
p3 = CharMeaningProfile(self.alt_dna,"TCAG",split_degenerates=True)
p3_exp = [('A',[0,0,1,0]),('G',[0,0,0,1]),('C',[0,1,0,0]),\
('T',[1,0,0,0]),('R',[0,0,.5,.5]),('Y',[.5,.5,0,0]),\
('N',[.25,.25,.25,.25])]
#if we add '-' to the character order, ? is split up as well
p4 = CharMeaningProfile(self.alt_dna,"TCAG-",split_degenerates=True)
p4_exp = [('A',[0,0,1,0,0]),('G',[0,0,0,1,0]),('C',[0,1,0,0,0]),\
('T',[1,0,0,0,0]),('R',[0,0,.5,.5,0]),('Y',[.5,.5,0,0,0]),\
('N',[.25,.25,.25,.25,0]),('-',[0,0,0,0,1]),('?',[.2,.2,.2,.2,.2])]
#Degenerate characters in the character order, when split_degenerates
#is True, won't be split up, they'll get a 1 in their own column.
p5 = CharMeaningProfile(self.alt_dna,"AGN",split_degenerates=True)
p5_exp = [('A',[1,0,0]),('G',[0,1,0]),('N',[0,0,1]),\
('R',[.5,.5,0])]
#defaults char_order to list(alphabet)
p6 = CharMeaningProfile(self.alt_dna)
p6_exp = [('A',[0,0,1,0]),('G',[0,0,0,1]),('C',[0,1,0,0]),\
('T',[1,0,0,0])]
#also accepts empty char_order -> set to list(alphabet)
p7 = CharMeaningProfile(self.alt_dna,"")
p7_exp = [('A',[0,0,1,0]),('G',[0,0,0,1]),('C',[0,1,0,0]),\
('T',[1,0,0,0])]
for obs,exp in [(p1,p1_exp),(p2,p2_exp),(p3,p3_exp),(p4,p4_exp),\
(p5,p5_exp),(p6,p6_exp),(p7,p7_exp)]:
nz = [(chr(i),r.tolist()) for i,r in enumerate(obs.Data) if r.any()]
self.assertEqualItems(nz, exp)
self.assertRaises(ValueError,CharMeaningProfile,self.alt_dna,\
"AGNX",split_degenerates=True)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_core/test_seq_aln_integration.py 000644 000765 000024 00000025635 12024702176 025043 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from __future__ import division
from numpy import array, transpose, alltrue
from cogent.util.unit_test import TestCase, main
from cogent.core.moltype import RNA
from cogent.core.sequence import RnaSequence, Sequence, ModelSequence
from cogent.core.alignment import Alignment, DenseAlignment
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Production"
class AllTests(TestCase):
def setUp(self):
"""setUp method for all tests"""
# named sequences
self.rna1 = RnaSequence('UCAGGG', Name='rna1')
self.rna2 = RnaSequence('YCU-RG', Name='rna2')
self.rna3 = RnaSequence('CAA-NR', Name='rna3')
self.model1 = ModelSequence('UCAGGG', Name='rna1',\
Alphabet=RNA.Alphabets.DegenGapped)
self.model2 = ModelSequence('YCU-RG', Name='rna2',\
Alphabet=RNA.Alphabets.DegenGapped)
self.model3 = ModelSequence('CAA-NR', Name='rna3',\
Alphabet=RNA.Alphabets.DegenGapped)
self.aln = Alignment([self.rna1, self.rna2, self.rna3], MolType=RNA)
self.da = DenseAlignment([self.model1, self.model2, self.model3],\
MolType=RNA, Alphabet=RNA.Alphabets.DegenGapped)
# seqs no name
self.nn_rna1 = RnaSequence('UCAGGG')
self.nn_rna2 = RnaSequence('YCU-RG')
self.nn_rna3 = RnaSequence('CAA-NR')
self.nn_model1 = ModelSequence('UCAGGG',\
Alphabet=RNA.Alphabets.DegenGapped)
self.nn_model2 = ModelSequence('YCU-RG',\
Alphabet=RNA.Alphabets.DegenGapped)
self.nn_model3 = ModelSequence('CAA-NR',\
Alphabet=RNA.Alphabets.DegenGapped)
self.nn_aln = Alignment([self.nn_rna1, self.nn_rna2, self.nn_rna3],\
MolType=RNA)
self.nn_da = DenseAlignment([self.nn_model1, self.nn_model2,\
self.nn_model3], MolType=RNA, Alphabet=RNA.Alphabets.DegenGapped)
def test_printing_named_seqs(self):
"""Printing named seqs should work the same on Aln and DenseAln"""
#Note: the newline trailing each sequence is intentional, because
#we want each FASTA-format record to be separated.
exp_lines_general = ['>rna1','UCAGGG','>rna2','YCU-RG','>rna3','CAA-NR']
self.assertEqual(str(self.aln), '\n'.join(exp_lines_general) + '\n')
self.assertEqual(str(self.da), '\n'.join(exp_lines_general) + '\n')
def test_printing_unnamed_seqs(self):
"""Printing unnamed sequences should work the same on Aln and DenseAln
"""
exp_lines_gen = ['>seq_0','UCAGGG','>seq_1','YCU-RG','>seq_2','CAA-NR\n']
self.assertEqual(str(self.nn_aln),'\n'.join(exp_lines_gen))
self.assertEqual(str(self.nn_da),'\n'.join(exp_lines_gen))
def test_DenseAlignment_without_moltype(self):
"""Expect MolType to be picked up from the sequences."""
m1 = ModelSequence('UCAG',Alphabet=RNA.Alphabets.DegenGapped,\
Name='rna1')
m2 = ModelSequence('CCCR',Alphabet=RNA.Alphabets.DegenGapped,\
Name='rna2')
da = DenseAlignment([m1, m2])
exp_lines = ['>rna1','UCAG','>rna2','CCCR']
self.assertEqual(str(da), '\n'.join(exp_lines) + '\n')
def test_names(self):
# Should both alignments handle names the same way?
self.assertEqual(self.aln.Names, ['rna1','rna2','rna3'])
self.assertEqual(self.da.Names, ['rna1','rna2','rna3'])
# On unnamed sequences the behavior is now the same.
self.assertEqual(self.nn_aln.Names, ['seq_0','seq_1','seq_2'])
self.assertEqual(self.nn_da.Names, ['seq_0','seq_1','seq_2'])
def test_seqFreqs(self):
"""seqFreqs should work the same on Alignment and DenseAlignment"""
# Used alphabet: ('U', 'C', 'A', 'G', '-', 'B', 'D', 'H',\
# 'K', 'M', 'N', 'S', 'R', 'W', 'V', 'Y')
exp = [[1,1,1,3,0,0,0,0,0,0,0,0,0,0,0,0,0],\
[1,1,0,1,1,0,0,0,0,0,0,0,1,0,0,1,0],\
[0,1,2,0,1,0,0,0,0,0,1,0,1,0,0,0,0]]
# This works
self.assertEqual(self.da.getSeqFreqs().Data, exp)
# This used to raise an error, but now works
self.assertEqual(self.aln.getSeqFreqs().Data, exp)
def test_subset_positions_DenseAlignment(self):
model1 = ModelSequence('UCG', Name='rna1',\
Alphabet=RNA.Alphabets.DegenGapped)
model2 = ModelSequence('YCG', Name='rna2',\
Alphabet=RNA.Alphabets.DegenGapped)
model3 = ModelSequence('CAR', Name='rna3',\
Alphabet=RNA.Alphabets.DegenGapped)
sub_da = DenseAlignment([model1, model2, model3],\
MolType=RNA, Alphabet=RNA.Alphabets.DegenGapped)
full_data = array([[0,1,2,3,3,3],[15,1,0,4,12,3],[1,2,2,4,10,12]])
sub_data = array([[0,1,3],[15,1,3],[1,2,12]])
# First check some data
self.assertEqual(self.da.ArraySeqs, full_data)
self.assertEqual(self.da.ArrayPositions, transpose(full_data))
self.assertEqual(sub_da.ArraySeqs, sub_data)
self.assertEqual(sub_da.ArrayPositions, transpose(sub_data))
obs_sub_da_TP = self.da.takePositions([0,1,5])
obs_sub_da_SA = self.da.getSubAlignment(pos=[0,1,5])
# When using the getSubAlignment method the data is right
self.assertEqual(obs_sub_da_SA, sub_da)
self.failIfEqual(obs_sub_da_SA, self.da)
self.assertEqual(obs_sub_da_SA.ArraySeqs, sub_data)
self.assertEqual(obs_sub_da_SA.ArrayPositions, transpose(sub_data))
# For the takePositions method: Why does this work
self.assertEqual(obs_sub_da_TP, sub_da)
self.failIfEqual(obs_sub_da_TP, self.da)
# If the data doesn't match?
self.assertEqual(obs_sub_da_TP.ArraySeqs, sub_data)
self.assertEqual(obs_sub_da_TP.ArrayPositions, transpose(sub_data))
# Shouldn't the __eq__ method check the data at least?
def test_subset_positions_Alignment(self):
rna1 = RnaSequence('UCG', Name='rna1')
rna2 = RnaSequence('YCG', Name='rna2')
rna3 = RnaSequence('CAR', Name='rna3')
sub_aln = Alignment([rna1, rna2, rna3], MolType=RNA)
obs_sub_aln = self.aln.takePositions([0,1,5])
self.assertEqual(obs_sub_aln, sub_aln)
self.failIfEqual(obs_sub_aln, self.aln)
# string representations should be the same. This fails right
# now, because sequence order is not maintained. See separate test.
self.assertEqual(str(obs_sub_aln), str(sub_aln))
def test_takePositions_sequence_order(self):
"""Alignment takePositions should maintain seq order"""
#This works
self.assertEqual(self.da.Names,['rna1','rna2','rna3'])
sub_da = self.da.getSubAlignment(pos=[0,1,5])
self.assertEqual(sub_da.Names,['rna1','rna2','rna3'])
# seq order not maintained in Alignment
self.assertEqual(self.aln.Names,['rna1','rna2','rna3'])
sub_aln = self.aln.takePositions([0,1,5])
self.assertEqual(sub_aln.Names,['rna1','rna2','rna3'])
def test_subset_seqs_Alignment(self):
rna1 = RnaSequence('UCG', Name='rna1')
rna2 = RnaSequence('YCG', Name='rna2')
rna3 = RnaSequence('CAR', Name='rna3')
sub_aln = Alignment([rna2, rna3], MolType=RNA)
aln = Alignment([rna1, rna2, rna3], MolType=RNA)
obs_sub_aln = aln.takeSeqs(['rna2','rna3'])
self.assertEqual(obs_sub_aln, sub_aln)
self.assertEqual(str(obs_sub_aln), str(sub_aln))
# Selected sequences should be in specified order?
obs_sub_aln_1 = self.aln.takeSeqs(['rna3','rna2'])
obs_sub_aln_2 = self.aln.takeSeqs(['rna2','rna3'])
self.failIfEqual(str(obs_sub_aln_1), str(obs_sub_aln_2))
def test_subset_seqs_DenseAlignment(self):
model1 = ModelSequence('UCG', Name='rna1',\
Alphabet=RNA.Alphabets.DegenGapped)
model2 = ModelSequence('YCG', Name='rna2',\
Alphabet=RNA.Alphabets.DegenGapped)
model3 = ModelSequence('CAR', Name='rna3',\
Alphabet=RNA.Alphabets.DegenGapped)
sub_da = DenseAlignment([model1, model2, model3],\
MolType=RNA, Alphabet=RNA.Alphabets.DegenGapped)
# takeSeqs by name should have the same effect as
# getSubAlignment by seq idx?
obs_sub_da_TS = self.da.takeSeqs(['rna1'])
obs_sub_da_SA = self.da.getSubAlignment(seqs=[0])
# These two are now the same. Fixed mapping of key to char array.
self.assertEqual(obs_sub_da_TS, obs_sub_da_SA)
self.assertEqual(str(obs_sub_da_TS), str(obs_sub_da_SA))
def test_aln_equality(self):
# When does something compare equal?
self.assertEqual(self.da == self.da, True)
# one sequence less
other_da1 = DenseAlignment([self.model1, self.model2],\
MolType=RNA, Alphabet=RNA.Alphabets.DegenGapped)
self.assertEqual(self.da == other_da1, False)
# seqs in different order -- doesn't matter
other_da2 = DenseAlignment([self.model1, self.model3, self.model2],\
MolType=RNA, Alphabet=RNA.Alphabets.DegenGapped)
self.assertEqual(self.da == other_da2, True)
# seqs in different encoding -- doesn't matter, only looks at data
other_da3 = DenseAlignment([self.model1, self.model2, self.model3])
# Should this compare False even though the data is exactly the same?
# The MolType is different...
self.assertEqual(self.da == other_da3, True)
assert alltrue(map(alltrue,self.da.ArraySeqs == other_da3.ArraySeqs))
def test_seq_equality(self):
model1 = ModelSequence('UCG', Name='rna1',\
Alphabet=RNA.Alphabets.DegenGapped)
model2 = ModelSequence('UCG', Name='rna1',\
Alphabet=RNA.Alphabets.DegenGapped)
# Shouldn't the above two sequences be equal?
self.assertEqual(model1, model2)
# string comparison is True
self.assertEqual(str(model1), str(model2))
def test_seq_ungapping(self):
rna1 = RnaSequence('U-C-A-G-', Name='rna1')
model1 = ModelSequence('U-C-A-G-', Name='rna1',\
Alphabet=RNA.Alphabets.DegenGapped)
self.assertEqual(rna1, 'U-C-A-G-')
self.assertEqual(rna1.degap(), 'UCAG')
# check is produces the right string from the beginning
self.assertEqual(str(model1), 'U-C-A-G-')
self.assertEqual(model1._data, [0,4,1,4,2,4,3,4])
# ModelSequence should maybe have the same degap method as normal Seq
self.assertEqual(str(model1.degap()), 'UCAG')
def test_the_rest_of_ModelSequence(self):
"""The class ModelSequence has 14 methods, but only 2 unittests.
You might want to add some tests there..."""
#note: mostly these are tested in derived classes, for convenience.
pass
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_core/test_sequence.py 000644 000765 000024 00000111456 12024702176 022623 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Unit tests for Sequence class and its subclasses.
"""
from cogent.core.sequence import Sequence, RnaSequence, DnaSequence, \
ProteinSequence, ModelSequenceBase, \
ModelSequence, ModelNucleicAcidSequence, ModelRnaSequence, \
ModelDnaSequence, ModelProteinSequence, ModelCodonSequence, \
ModelDnaCodonSequence, ModelRnaCodonSequence
from cogent.core.moltype import RNA, DNA, PROTEIN, ASCII, BYTES, AlphabetError
from cogent.util.unit_test import TestCase, main
import re
from pickle import dumps
from numpy import array
__author__ = "Rob Knight, Gavin Huttley and Peter Maxwell"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Gavin Huttley", "Peter Maxwell",
"Matthew Wakefield"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class SequenceTests(TestCase):
"""Tests of the Sequence class."""
SEQ = Sequence
RNA = RnaSequence
DNA = DnaSequence
PROT = ProteinSequence
def test_init_empty(self):
"""Sequence and subclasses should init correctly."""
#NOTE: ModelSequences can't be initialized empty because it screws up
#the dimensions of the array, and not worth special-casing.
s = self.SEQ()
self.assertEqual(s, '')
assert s.MolType in (ASCII, BYTES)
r = self.RNA()
assert r.MolType is RNA
def test_init_data(self):
"""Sequence init with data should set data in correct location"""
r = self.RNA('ucagg')
#no longer preserves case
self.assertEqual(r, 'UCAGG')
def test_init_other_seq(self):
"""Sequence init with other seq should preserve name and info."""
r = self.RNA('UCAGG', Name='x', Info={'z':3})
s = Sequence(r)
self.assertEqual(s._seq, 'UCAGG')
self.assertEqual(s.Name, 'x')
self.assertEqual(s.Info.z, 3)
def test_compare_to_string(self):
"""Sequence should compare equal to same string."""
r = self.RNA('UCC')
self.assertEqual(r, 'UCC')
def test_slice(self):
"""Sequence slicing should work as expected"""
r = self.RNA('UCAGG')
self.assertEqual(r[0], 'U')
self.assertEqual(r[-1], 'G')
self.assertEqual(r[1:3], 'CA')
def test_conversion(self):
"""Should convert t to u automatically"""
r = self.RNA('TCAtu')
self.assertEqual(str(r), 'UCAUU')
d = self.DNA('UCAtu')
self.assertEqual(str(d), 'TCATT')
def test_toDna(self):
"""Returns copy of self as DNA."""
r = self.RNA('TCA')
self.assertEqual(str(r), 'UCA')
self.assertEqual(str(r.toDna()), 'TCA')
def test_toRna(self):
"""Returns copy of self as RNA."""
r = self.DNA('UCA')
self.assertEqual(str(r), 'TCA')
self.assertEqual(str(r.toRna()), 'UCA')
def test_toFasta(self):
"""Sequence toFasta() should return Fasta-format string"""
even = 'TCAGAT'
odd = even + 'AAA'
even_dna = self.SEQ(even, Name='even')
odd_dna = self.SEQ(odd, Name='odd')
self.assertEqual(even_dna.toFasta(), '>even\nTCAGAT')
#set line wrap to small number so we can test that it works
even_dna.LineWrap = 2
self.assertEqual(even_dna.toFasta(), '>even\nTC\nAG\nAT')
odd_dna.LineWrap = 2
self.assertEqual(odd_dna.toFasta(), '>odd\nTC\nAG\nAT\nAA\nA')
#check that changing the linewrap again works
even_dna.LineWrap = 4
self.assertEqual(even_dna.toFasta(), '>even\nTCAG\nAT')
def test_serialize(self):
"""Sequence should be serializable"""
r = self.RNA('ugagg')
assert dumps(r)
def test_stripDegenerate(self):
"""Sequence stripDegenerate should remove any degenerate bases"""
self.assertEqual(self.RNA('UCAG-').stripDegenerate(), 'UCAG-')
self.assertEqual(self.RNA('NRYSW').stripDegenerate(), '')
self.assertEqual(self.RNA('USNG').stripDegenerate(), 'UG')
def test_stripBad(self):
"""Sequence stripBad should remove any non-base, non-gap chars"""
#have to turn off check to get bad data in; no longer preserves case
self.assertEqual(self.RNA('UCxxxAGwsnyrHBNzzzD-D', check=False\
).stripBad(), 'UCAGWSNYRHBND-D')
self.assertEqual(self.RNA('@#^*($@!#&()!@QZX', check=False \
).stripBad(), '')
self.assertEqual(self.RNA('aaaxggg---!ccc', check=False).stripBad(),
'AAAGGG---CCC')
def test_stripBadAndGaps(self):
"""Sequence stripBadAndGaps should remove gaps and bad chars"""
#have to turn off check to get bad data in; no longer preserves case
self.assertEqual(self.RNA('UxxCAGwsnyrHBNz#!D-D', check=False \
).stripBadAndGaps(), 'UCAGWSNYRHBNDD')
self.assertEqual(self.RNA('@#^*($@!#&()!@QZX', check=False \
).stripBadAndGaps(), '')
self.assertEqual(self.RNA('aaa ggg ---!ccc', check=False \
).stripBadAndGaps(), 'AAAGGGCCC')
def test_shuffle(self):
"""Sequence shuffle should return new random sequence w/ same monomers"""
r = self.RNA('UUUUCCCCAAAAGGGG')
s = r.shuffle()
self.assertNotEqual(r, s)
self.assertEqualItems(r, s)
def test_complement(self):
"""Sequence complement should correctly complement sequence"""
self.assertEqual(self.RNA('UAUCG-NR').complement(), 'AUAGC-NY')
self.assertEqual(self.DNA('TATCG-NR').complement(), 'ATAGC-NY')
self.assertEqual(self.DNA('').complement(), '')
self.assertRaises(TypeError, self.PROT('ACD').complement)
def test_rc(self):
"""Sequence rc should correctly reverse-complement sequence"""
#no longer preserves case!
self.assertEqual(self.RNA('UauCG-NR').rc(), 'YN-CGAUA')
self.assertEqual(self.DNA('TatCG-NR').rc(), 'YN-CGATA')
self.assertEqual(self.RNA('').rc(), '')
self.assertEqual(self.RNA('A').rc(), 'U')
self.assertRaises(TypeError, self.PROT('ACD').rc)
def test_contains(self):
"""Sequence contains should return correct result"""
r = self.RNA('UCA')
assert 'U' in r
assert 'CA' in r
assert 'X' not in r
assert 'G' not in r
def test_iter(self):
"""Sequence iter should iterate over sequence"""
p = self.PROT('QWE')
self.assertEqual(list(p), ['Q','W','E'])
def test_isGapped(self):
"""Sequence isGapped should return True if gaps in seq"""
assert not self.RNA('').isGapped()
assert not self.RNA('ACGUCAGUACGUCAGNRCGAUcaguaguacYRNRYRN').isGapped()
assert self.RNA('-').isGapped()
assert self.PROT('--').isGapped()
assert self.RNA('CAGUCGUACGUCAGUACGUacucauacgac-caguACUG').isGapped()
assert self.RNA('CA--CGUAUGCA-----g').isGapped()
assert self.RNA('CAGU-').isGapped()
def test_isGap(self):
"""Sequence isGap should return True if char is a valid gap char"""
r = self.RNA('ACGUCAGUACGUCAGNRCGAUcaguaguacYRNRYRN')
for char in 'qwertyuiopasdfghjklzxcvbnmQWERTYUIOASDFGHJKLZXCVBNM':
assert not r.isGap(char)
assert r.isGap('-')
#only works on a single literal that's a gap, not on a sequence.
#possibly, this behavior should change?
assert not r.isGap('---')
#check behaviour on self
assert not self.RNA('CGAUACGUACGACU').isGap()
assert not self.RNA('---CGAUA----CGUACG---ACU---').isGap()
assert self.RNA('').isGap()
assert self.RNA('----------').isGap()
def test_isDegenerate(self):
"""Sequence isDegenerate should return True if degen symbol in seq"""
assert not self.RNA('').isDegenerate()
assert not self.RNA('UACGCUACAUGuacgucaguGCUAGCUA---ACGUCAG').isDegenerate()
assert self.RNA('N').isDegenerate()
assert self.RNA('R').isDegenerate()
assert self.RNA('y').isDegenerate()
assert self.RNA('GCAUguagcucgUCAGUCAGUACgUgcasCUAG').isDegenerate()
assert self.RNA('ACGYAUGCUGYWWNMNuwbycwuybcwbwub').isDegenerate()
def test_isStrict(self):
"""Sequence isStrict should return True if all symbols in Monomers"""
assert self.RNA('').isStrict()
assert self.PROT('A').isStrict()
assert self.RNA('UAGCACUgcaugcauGCAUGACuacguACAUG').isStrict()
assert not self.RNA('CAGUCGAUCA-cgaucagUCGAUGAC').isStrict()
def test_firstGap(self):
"""Sequence firstGap should return index of first gap symbol, or None"""
self.assertEqual(self.RNA('').firstGap(), None)
self.assertEqual(self.RNA('a').firstGap(), None)
self.assertEqual(self.RNA('uhacucHuhacUUhacan').firstGap(), None)
self.assertEqual(self.RNA('-abc').firstGap(), 0)
self.assertEqual(self.RNA('b-ac').firstGap(), 1)
self.assertEqual(self.RNA('abcd-').firstGap(), 4)
def test_firstDegenerate(self):
"""Sequence firstDegenerate should return index of first degen symbol"""
self.assertEqual(self.RNA('').firstDegenerate(), None)
self.assertEqual(self.RNA('a').firstDegenerate(), None)
self.assertEqual(self.RNA('UCGACA--CU-gacucaguacgua'
).firstDegenerate(), None)
self.assertEqual(self.RNA('nCAGU').firstDegenerate(), 0)
self.assertEqual(self.RNA('CUGguagvAUG').firstDegenerate(), 7)
self.assertEqual(self.RNA('ACUGCUAacgud').firstDegenerate(), 11)
def test_firstNonStrict(self):
"""Sequence firstNonStrict should return index of first non-strict symbol"""
self.assertEqual(self.RNA('').firstNonStrict(), None)
self.assertEqual(self.RNA('A').firstNonStrict(), None)
self.assertEqual(self.RNA('ACGUACGUcgaucagu').firstNonStrict(), None)
self.assertEqual(self.RNA('N').firstNonStrict(), 0)
self.assertEqual(self.RNA('-').firstNonStrict(), 0)
self.assertEqual(self.RNA('ACGUcgAUGUGCAUcagu-').firstNonStrict(),18)
def test_disambiguate(self):
"""Sequence disambiguate should remove degenerate bases"""
self.assertEqual(self.RNA('').disambiguate(), '')
self.assertEqual(self.RNA('AGCUGAUGUA--CAGU').disambiguate(),
'AGCUGAUGUA--CAGU')
self.assertEqual(self.RNA('AUn-yrs-wkmCGwmrNMWRKY').disambiguate(
'strip'), 'AU--CG')
s = self.RNA('AUn-yrs-wkmCGwmrNMWRKY')
t = s.disambiguate('random')
u = s.disambiguate('random')
for i, j in zip(str(s), str(t)):
if i in s.MolType.Degenerates:
assert j in s.MolType.Degenerates[i]
else:
assert i == j
self.assertNotEqual(t, u)
self.assertEqual(len(s), len(t))
def test_degap(self):
"""Sequence degap should remove all gaps from sequence"""
#doesn't preserve case
self.assertEqual(self.RNA('').degap(), '')
self.assertEqual(self.RNA('GUCAGUCgcaugcnvuncdks').degap(),
'GUCAGUCGCAUGCNVUNCDKS')
self.assertEqual(self.RNA('----------------').degap(), '')
self.assertEqual(self.RNA('gcuauacg-').degap(), 'GCUAUACG')
self.assertEqual(self.RNA('-CUAGUCA').degap(), 'CUAGUCA')
self.assertEqual(self.RNA('---a---c---u----g---').degap(), 'ACUG')
self.assertEqual(self.RNA('?a-').degap(), 'A')
def test_gapList(self):
"""Sequence gapList should return correct gap positions"""
self.assertEqual(self.RNA('').gapList(), [])
self.assertEqual(self.RNA('ACUGUCAGUACGHSDKCUCDNNS').gapList(),[])
self.assertEqual(self.RNA('GUACGUACAKDC-SDHDSK').gapList(),[12])
self.assertEqual(self.RNA('-DSHUHDS').gapList(), [0])
self.assertEqual(self.RNA('UACHASADS-').gapList(), [9])
self.assertEqual(self.RNA('---CGAUgCAU---ACGHc---ACGUCAGU---'
).gapList(), [0,1,2,11,12,13,19,20,21,30,31,32])
def test_gapVector(self):
"""Sequence gapVector should return correct gap positions"""
g = lambda x: self.RNA(x).gapVector()
self.assertEqual(g(''), [])
self.assertEqual(g('ACUGUCAGUACGHCSDKCCUCCDNCNS'), [False]*27)
self.assertEqual(g('GUACGUAACAKADC-SDAHADSAK'),
map(bool, map(int,'000000000000001000000000')))
self.assertEqual(g('-DSHSUHDSS'),
map(bool, map(int,'1000000000')))
self.assertEqual(g('UACHASCAGDS-'),
map(bool, map(int,'000000000001')))
self.assertEqual(g('---CGAUgCAU---ACGHc---ACGUCAGU--?'), \
map(bool, map(int,'111000000001110000011100000000111')))
def test_gapMaps(self):
"""Sequence gapMaps should return dicts mapping gapped/ungapped pos"""
empty = ''
no_gaps = 'aaa'
all_gaps = '---'
start_gaps = '--abc'
end_gaps = 'ab---'
mid_gaps = '--a--b-cd---'
gm = lambda x: self.RNA(x).gapMaps()
self.assertEqual(gm(empty), ({},{}))
self.assertEqual(gm(no_gaps), ({0:0,1:1,2:2}, {0:0,1:1,2:2}))
self.assertEqual(gm(all_gaps), ({},{}))
self.assertEqual(gm(start_gaps), ({0:2,1:3,2:4},{2:0,3:1,4:2}))
self.assertEqual(gm(end_gaps), ({0:0,1:1},{0:0,1:1}))
self.assertEqual(gm(mid_gaps), ({0:2,1:5,2:7,3:8},{2:0,5:1,7:2,8:3}))
def test_countGaps(self):
"""Sequence countGaps should return correct gap count"""
self.assertEqual(self.RNA('').countGaps(), 0)
self.assertEqual(self.RNA('ACUGUCAGUACGHSDKCUCDNNS').countGaps(),
0)
self.assertEqual(self.RNA('GUACGUACAKDC-SDHDSK').countGaps(), 1)
self.assertEqual(self.RNA('-DSHUHDS').countGaps(), 1)
self.assertEqual(self.RNA('UACHASADS-').countGaps(), 1)
self.assertEqual(self.RNA('---CGAUgCAU---ACGHc---ACGUCAGU---'
).countGaps(), 12)
def test_countDegenerate(self):
"""Sequence countDegenerate should return correct degen base count"""
self.assertEqual(self.RNA('').countDegenerate(), 0)
self.assertEqual(self.RNA('GACUGCAUGCAUCGUACGUCAGUACCGA'
).countDegenerate(), 0)
self.assertEqual(self.RNA('N').countDegenerate(), 1)
self.assertEqual(self.PROT('N').countDegenerate(), 0)
self.assertEqual(self.RNA('NRY').countDegenerate(), 3)
self.assertEqual(self.RNA('ACGUAVCUAGCAUNUCAGUCAGyUACGUCAGS'
).countDegenerate(), 4)
def test_possibilites(self):
"""Sequence possibilities should return correct # possible sequences"""
self.assertEqual(self.RNA('').possibilities(), 1)
self.assertEqual(self.RNA('ACGUgcaucagUCGuGCAU').possibilities(), 1)
self.assertEqual(self.RNA('N').possibilities(), 4)
self.assertEqual(self.RNA('R').possibilities(), 2)
self.assertEqual(self.RNA('H').possibilities(), 3)
self.assertEqual(self.RNA('nRh').possibilities(), 24)
self.assertEqual(self.RNA('AUGCnGUCAg-aurGauc--gauhcgauacgws'
).possibilities(), 96)
def test_MW(self):
"""Sequence MW should return correct molecular weight"""
self.assertEqual(self.PROT('').MW(), 0)
self.assertEqual(self.RNA('').MW(), 0)
self.assertFloatEqual(self.PROT('A').MW(), 107.09)
self.assertFloatEqual(self.RNA('A').MW(), 375.17)
self.assertFloatEqual(self.PROT('AAA').MW(), 285.27)
self.assertFloatEqual(self.RNA('AAA').MW(), 1001.59)
self.assertFloatEqual(self.RNA('AAACCCA').MW(), 2182.37)
def test_canMatch(self):
"""Sequence canMatch should return True if all positions can match"""
assert self.RNA('').canMatch('')
assert self.RNA('UCAG').canMatch('UCAG')
assert not self.RNA('UCAG').canMatch('ucag')
assert self.RNA('UCAG').canMatch('NNNN')
assert self.RNA('NNNN').canMatch('UCAG')
assert self.RNA('NNNN').canMatch('NNNN')
assert not self.RNA('N').canMatch('x')
assert not self.RNA('N').canMatch('-')
assert self.RNA('UCAG').canMatch('YYRR')
assert self.RNA('UCAG').canMatch('KMWS')
def test_canMismatch(self):
"""Sequence canMismatch should return True on any possible mismatch"""
assert not self.RNA('').canMismatch('')
assert self.RNA('N').canMismatch('N')
assert self.RNA('R').canMismatch('R')
assert self.RNA('N').canMismatch('r')
assert self.RNA('CGUACGCAN').canMismatch('CGUACGCAN')
assert self.RNA('U').canMismatch('C')
assert self.RNA('UUU').canMismatch('UUC')
assert self.RNA('UUU').canMismatch('UUY')
assert not self.RNA('UUU').canMismatch('UUU')
assert not self.RNA('UCAG').canMismatch('UCAG')
assert not self.RNA('U--').canMismatch('U--')
def test_mustMatch(self):
"""Sequence mustMatch should return True when no possible mismatches"""
assert self.RNA('').mustMatch('')
assert not self.RNA('N').mustMatch('N')
assert not self.RNA('R').mustMatch('R')
assert not self.RNA('N').mustMatch('r')
assert not self.RNA('CGUACGCAN').mustMatch('CGUACGCAN')
assert not self.RNA('U').mustMatch('C')
assert not self.RNA('UUU').mustMatch('UUC')
assert not self.RNA('UUU').mustMatch('UUY')
assert self.RNA('UU-').mustMatch('UU-')
assert self.RNA('UCAG').mustMatch('UCAG')
def test_canPair(self):
"""Sequence canPair should return True if all positions can pair"""
assert self.RNA('').canPair('')
assert not self.RNA('UCAG').canPair('UCAG')
assert self.RNA('UCAG').canPair('CUGA')
assert not self.RNA('UCAG').canPair('cuga')
assert self.RNA('UCAG').canPair('NNNN')
assert self.RNA('NNNN').canPair('UCAG')
assert self.RNA('NNNN').canPair('NNNN')
assert not self.RNA('N').canPair('x')
assert not self.RNA('N').canPair('-')
assert self.RNA('-').canPair('-')
assert self.RNA('UCAGU').canPair('KYYRR')
assert self.RNA('UCAG').canPair('KKRS')
assert self.RNA('U').canPair('G')
assert not self.DNA('T').canPair('G')
def test_canMispair(self):
"""Sequence canMispair should return True on any possible mispair"""
assert not self.RNA('').canMispair('')
assert self.RNA('N').canMispair('N')
assert self.RNA('R').canMispair('Y')
assert self.RNA('N').canMispair('r')
assert self.RNA('CGUACGCAN').canMispair('NUHCHUACH')
assert self.RNA('U').canMispair('C')
assert self.RNA('U').canMispair('R')
assert self.RNA('UUU').canMispair('AAR')
assert self.RNA('UUU').canMispair('GAG')
assert not self.RNA('UUU').canMispair('AAA')
assert not self.RNA('UCAG').canMispair('CUGA')
assert self.RNA('U--').canMispair('--U')
assert self.DNA('TCCAAAGRYY').canMispair('RRYCTTTGGA')
def test_mustPair(self):
"""Sequence mustPair should return True when no possible mispairs"""
assert self.RNA('').mustPair('')
assert not self.RNA('N').mustPair('N')
assert not self.RNA('R').mustPair('Y')
assert not self.RNA('A').mustPair('A')
assert not self.RNA('CGUACGCAN').mustPair('NUGCGUACG')
assert not self.RNA('U').mustPair('C')
assert not self.RNA('UUU').mustPair('AAR')
assert not self.RNA('UUU').mustPair('RAA')
assert not self.RNA('UU-').mustPair('-AA')
assert self.RNA('UCAG').mustPair('CUGA')
assert self.DNA('TCCAGGG').mustPair('CCCTGGA')
assert self.DNA('tccaggg').mustPair(self.DNA('ccctgga'))
assert not self.DNA('TCCAGGG').mustPair('NCCTGGA')
def test_diff(self):
"""Sequence diff should count 1 for each difference between sequences"""
self.assertEqual(self.RNA('UGCUGCUC').diff(''), 0)
self.assertEqual(self.RNA('UGCUGCUC').diff('U'), 0)
self.assertEqual(self.RNA('UGCUGCUC').diff('UCCCCCUC'), 3)
#case-sensitive!
self.assertEqual(self.RNA('AAAAA').diff('CCCCC'), 5)
#raises TypeError if other not iterable
self.assertRaises(TypeError, self.RNA('AAAAA').diff, 5)
def test_distance(self):
"""Sequence distance should calculate correctly based on function"""
def f(a, b):
if a == b:
return 0
if (a in 'UC' and b in 'UC') or (a in 'AG' and b in 'AG'):
return 1
else:
return 10
#uses identity function by default
self.assertEqual(self.RNA('UGCUGCUC').distance(''), 0)
self.assertEqual(self.RNA('UGCUGCUC').distance('U'), 0)
self.assertEqual(self.RNA('UGCUGCUC').distance('UCCCCCUC'), 3)
#case-sensitive!
self.assertEqual(self.RNA('AAAAA').distance('CCCCC'), 5)
#should use function if supplied
self.assertEqual(self.RNA('UGCUGCUC').distance('', f), 0)
self.assertEqual(self.RNA('UGCUGCUC').distance('U', f), 0)
self.assertEqual(self.RNA('UGCUGCUC').distance('C', f), 1)
self.assertEqual(self.RNA('UGCUGCUC').distance('G', f), 10)
self.assertEqual(self.RNA('UGCUGCUC').distance('UCCCCCUC', f), 21)
#case-sensitive!
self.assertEqual(self.RNA('AAAAA').distance('CCCCC', f), 50)
def test_matrixDistance(self):
"""Sequence matrixDistance should look up distances from a matrix"""
#note that the score matrix must contain 'diagonal' elements m[i][i]
#to avoid failure when the sequences match.
m = {'U':{'U':0, 'C':1, 'A':5}, 'C':{'C':0, 'A':2,'G':4}}
self.assertEqual(self.RNA('UUUCCC').matrixDistance('UCACGG', m), 14)
self.assertEqual(self.RNA('UUUCCC').matrixDistance('', m), 0)
self.assertEqual(self.RNA('UUU').matrixDistance('CAC', m), 7)
self.assertRaises(KeyError, self.RNA('UUU').matrixDistance, 'CAG', m)
def test_fracSame(self):
"""Sequence fracSame should return similarity between sequences"""
s1 = self.RNA('ACGU')
s2 = self.RNA('AACG')
s3 = self.RNA('GG')
s4 = self.RNA('A')
e = self.RNA('')
self.assertEqual(s1.fracSame(e), 0)
self.assertEqual(s1.fracSame(s2), 0.25)
self.assertEqual(s1.fracSame(s3), 0)
self.assertEqual(s1.fracSame(s4), 1.0) #note truncation
def test_fracDiff(self):
"""Sequence fracDiff should return difference between sequences"""
s1 = self.RNA('ACGU')
s2 = self.RNA('AACG')
s3 = self.RNA('GG')
s4 = self.RNA('A')
e = self.RNA('')
self.assertEqual(s1.fracDiff(e), 0)
self.assertEqual(s1.fracDiff(s2), 0.75)
self.assertEqual(s1.fracDiff(s3), 1)
self.assertEqual(s1.fracDiff(s4), 0) #note truncation
def test_fracSameGaps(self):
"""Sequence fracSameGaps should return similarity in gap positions"""
s1 = self.RNA('AAAA')
s2 = self.RNA('GGGG')
s3 = self.RNA('----')
s4 = self.RNA('A-A-')
s5 = self.RNA('-G-G')
s6 = self.RNA('UU--')
s7 = self.RNA('-')
s8 = self.RNA('GGG')
e = self.RNA('')
self.assertEqual(s1.fracSameGaps(s1), 1)
self.assertEqual(s1.fracSameGaps(s2), 1)
self.assertEqual(s1.fracSameGaps(s3), 0)
self.assertEqual(s1.fracSameGaps(s4), 0.5)
self.assertEqual(s1.fracSameGaps(s5), 0.5)
self.assertEqual(s1.fracSameGaps(s6), 0.5)
self.assertEqual(s1.fracSameGaps(s7), 0)
self.assertEqual(s1.fracSameGaps(e), 0)
self.assertEqual(s3.fracSameGaps(s3), 1)
self.assertEqual(s3.fracSameGaps(s4), 0.5)
self.assertEqual(s3.fracSameGaps(s7), 1.0)
self.assertEqual(e.fracSameGaps(e), 0.0)
self.assertEqual(s4.fracSameGaps(s5), 0.0)
self.assertEqual(s4.fracSameGaps(s6), 0.5)
self.assertFloatEqual(s6.fracSameGaps(s8), 2/3.0)
def test_fracDiffGaps(self):
"""Sequence fracDiffGaps should return difference in gap positions"""
s1 = self.RNA('AAAA')
s2 = self.RNA('GGGG')
s3 = self.RNA('----')
s4 = self.RNA('A-A-')
s5 = self.RNA('-G-G')
s6 = self.RNA('UU--')
s7 = self.RNA('-')
s8 = self.RNA('GGG')
e = self.RNA('')
self.assertEqual(s1.fracDiffGaps(s1), 0)
self.assertEqual(s1.fracDiffGaps(s2), 0)
self.assertEqual(s1.fracDiffGaps(s3), 1)
self.assertEqual(s1.fracDiffGaps(s4), 0.5)
self.assertEqual(s1.fracDiffGaps(s5), 0.5)
self.assertEqual(s1.fracDiffGaps(s6), 0.5)
self.assertEqual(s1.fracDiffGaps(s7), 1)
self.assertEqual(s1.fracDiffGaps(e), 0)
self.assertEqual(s3.fracDiffGaps(s3), 0)
self.assertEqual(s3.fracDiffGaps(s4), 0.5)
self.assertEqual(s3.fracDiffGaps(s7), 0.0)
self.assertEqual(e.fracDiffGaps(e), 0.0)
self.assertEqual(s4.fracDiffGaps(s5), 1.0)
self.assertEqual(s4.fracDiffGaps(s6), 0.5)
self.assertFloatEqual(s6.fracDiffGaps(s8), 1/3.0)
def test_fracSameNonGaps(self):
"""Sequence fracSameNonGaps should return similarities at non-gaps"""
s1 = self.RNA('AAAA')
s2 = self.RNA('AGGG')
s3 = self.RNA('GGGG')
s4 = self.RNA('AG--GA-G')
s5 = self.RNA('CU--CU-C')
s6 = self.RNA('AC--GC-G')
s7 = self.RNA('--------')
s8 = self.RNA('AAAA----')
s9 = self.RNA('A-GG-A-C')
e = self.RNA('')
test = lambda x, y, z: self.assertFloatEqual(x.fracSameNonGaps(y), z)
test(s1, s2, 0.25)
test(s1, s3, 0)
test(s2, s3, 0.75)
test(s1, s4, 0.5)
test(s4, s5, 0)
test(s4, s6, 0.6)
test(s4, s7, 0)
test(s4, s8, 0.5)
test(s4, s9, 2/3.0)
test(e, s4, 0)
def test_fracDiffNonGaps(self):
"""Sequence fracDiffNonGaps should return differences at non-gaps"""
s1 = self.RNA('AAAA')
s2 = self.RNA('AGGG')
s3 = self.RNA('GGGG')
s4 = self.RNA('AG--GA-G')
s5 = self.RNA('CU--CU-C')
s6 = self.RNA('AC--GC-G')
s7 = self.RNA('--------')
s8 = self.RNA('AAAA----')
s9 = self.RNA('A-GG-A-C')
e = self.RNA('')
test = lambda x, y, z: self.assertFloatEqual(x.fracDiffNonGaps(y), z)
test(s1, s2, 0.75)
test(s1, s3, 1)
test(s2, s3, 0.25)
test(s1, s4, 0.5)
test(s4, s5, 1)
test(s4, s6, 0.4)
test(s4, s7, 0)
test(s4, s8, 0.5)
test(s4, s9, 1/3.0)
test(e, s4, 0)
def test_fracSimilar(self):
"""Sequence fracSimilar should return the fraction similarity"""
transitions = dict.fromkeys([ \
('A','A'), ('A','G'), ('G','A'), ('G','G'),
('U','U'), ('U','C'), ('C','U'), ('C','C')])
s1 = self.RNA('UCAGGCAA')
s2 = self.RNA('CCAAAUGC')
s3 = self.RNA('GGGGGGGG')
e = self.RNA('')
test = lambda x, y, z: self.assertFloatEqual( \
x.fracSimilar(y, transitions), z)
test(e, e, 0)
test(s1, e, 0)
test(s1, s1, 1)
test(s1, s2, 7.0/8)
test(s1, s3, 5.0/8)
test(s2,s3, 4.0/8)
def test_withTerminiUnknown(self):
"""withTerminiUnknown should reset termini to unknown char"""
s1 = self.RNA('-?--AC--?-')
s2 = self.RNA('AC')
self.assertEqual(s1.withTerminiUnknown(), '????AC????')
self.assertEqual(s2.withTerminiUnknown(), 'AC')
def test_consistent_gap_degen_handling(self):
"""gap degen character should be treated consistently"""
# the degen character '?' can be a gap, so when we strip either gaps or
# degen characters it should be gone too
raw_seq = "---??-??TC-GGCG-GCA-G-GC-?-C-TAN-GCGC-CCTC-AGGA?-???-??--"
raw_ungapped = re.sub("[-?]", "", raw_seq)
raw_no_ambigs = re.sub("[N?]+", "", raw_seq)
dna = self.DNA(raw_seq)
self.assertEqual(dna.degap(), raw_ungapped)
self.assertEqual(dna.stripDegenerate(), raw_no_ambigs)
self.assertEqual(dna.stripBadAndGaps(), raw_ungapped)
class SequenceSubclassTests(TestCase):
"""Only one general set of tests, since the subclasses are very thin."""
def test_DnaSequence(self):
"""DnaSequence should behave as expected"""
x = DnaSequence('tcag')
#note: no longer preserves case
self.assertEqual(x, 'TCAG')
x = DnaSequence('aaa') + DnaSequence('ccc')
#note: doesn't preserve case
self.assertEqual(x, 'AAACCC')
assert x.MolType is DNA
self.assertRaises(AlphabetError, x.__add__, 'z')
self.assertEqual(DnaSequence('TTTAc').rc(), 'GTAAA')
class ModelSequenceTests(object):
"""Base class for tests of specific ModelSequence objects."""
SequenceClass = None #override in derived classes
def test_toFasta(self):
"""Sequence toFasta() should return Fasta-format string"""
even = 'TCAGAT'
odd = even + 'AAA'
even_dna = self.SequenceClass(even, Name='even')
odd_dna = self.SequenceClass(odd, Name='odd')
self.assertEqual(even_dna.toFasta(), '>even\nTCAGAT')
#set line wrap to small number so we can test that it works
even_dna.LineWrap = 2
self.assertEqual(even_dna.toFasta(), '>even\nTC\nAG\nAT')
odd_dna.LineWrap = 2
self.assertEqual(odd_dna.toFasta(), '>odd\nTC\nAG\nAT\nAA\nA')
#check that changing the linewrap again works
even_dna.LineWrap = 4
self.assertEqual(even_dna.toFasta(), '>even\nTCAG\nAT')
def test_toPhylip(self):
"""Sequence toPhylip() should return one-line phylip string"""
s = self.SequenceClass('ACG', Name='xyz')
self.assertEqual(s.toPhylip(), 'xyz'+' '*27+'ACG')
class DnaSequenceTests(ModelSequenceTests, TestCase):
class SequenceClass(ModelNucleicAcidSequence):
Alphabet = DNA.Alphabets.Base
def test_init(self):
"""Sequence should do round-trip from string"""
orig = ''
r = self.SequenceClass(orig)
self.assertEqual(str(r), orig)
orig = 'TCAGGA'
r = self.SequenceClass(orig)
self.assertEqual(r._data, array([0,1,2,3,3,2]))
self.assertEqual(str(r), orig)
def test_toKwords(self):
"""Sequence toKwords should give expected counts"""
orig = 'ATCCCTAGC'
r = self.SequenceClass(orig)
#if we use k = 1, should just get the characters
w = r.toKwords(1)
self.assertEqual(w, r._data)
w = r.toKwords(1, overlapping=False)
self.assertEqual(w, r._data)
#if we use k = 2, should get overlapping or nonoverlapping k-words
w = r.toKwords(2)
self.assertEqual(w, array([8,1,5,5,4,2,11,13]))
w = r.toKwords(2, overlapping=False)
self.assertEqual(w, array([8,5,4,11]))
#check a case with k = 3, i.e. codons
w = r.toKwords(3, overlapping=False)
self.assertEqual(w, array([33,20,45]))
class CodonSequenceTests(SequenceTests, TestCase):
class SequenceClass(ModelCodonSequence):
Alphabet = DNA.Alphabets.Base.Triples
def test_init(self):
"""Sequence should do round-trip from string"""
orig = ''
r = self.SequenceClass(orig)
self.assertEqual(str(r), orig)
orig = 'TCAGGA'
r = self.SequenceClass(orig)
self.assertEqual(r._data, array([6,62]))
self.assertEqual(str(r), orig)
def test_toKwords(self):
"""Sequence toKwords should give expected counts"""
orig = 'ATCCCTAGC'
r = self.SequenceClass(orig)
#if we use k = 1, should just get the characters
w = r.toKwords(1)
self.assertEqual(w, r._data)
w = r.toKwords(1, overlapping=False)
self.assertEqual(w, r._data)
#if we use k = 2, should get overlapping or nonoverlapping k-words
w = r.toKwords(2)
self.assertEqual(w, array([2132,1325]))
w = r.toKwords(2, overlapping=False)
self.assertEqual(w, array([2132]))
class DnaSequenceGapTests(TestCase):
"""Tests of gapped DNA sequences."""
class SequenceClass(ModelNucleicAcidSequence):
Alphabet = DNA.Alphabets.Gapped
Gap = '-'
def test_init(self):
"""Gapped sequence should init ok"""
orig = 'TC---'
seq = self.SequenceClass(orig)
self.assertEqual(str(seq), orig)
def test_gaps(self):
"""Gapped sequence gaps() should return correct array"""
sc = self.SequenceClass
self.assertEqual(sc('TC').gaps(), array([0,0]))
self.assertEqual(sc('T-').gaps(), array([0,1]))
def test_degap(self):
"""Gapped sequence degap() should return correct array"""
sc = self.SequenceClass
self.assertEqual(sc('T-').degap(), sc('T'))
def test_nongaps(self):
"""Gapped sequence nongaps() should return correct array"""
sc = self.SequenceClass
self.assertEqual(sc('TC').nongaps(), array([1,1]))
self.assertEqual(sc('T-').nongaps(), array([1,0]))
def test_regap(self):
"""Gapped sequence regap() should return correct sequence"""
sc = self.SequenceClass
self.assertEqual(str(sc('TC').regap(sc('A---A-'))), 'T---C-')
class SequenceIntegrationTests(TestCase):
"""Should be able to convert regular to model sequences, and back"""
def test_regular_to_model(self):
"""Regular sequence should convert to model sequence"""
r = RNA.Sequence('AAA', Name='x')
s = RNA.ModelSeq(r)
self.assertEqual(str(s), 'AAA')
self.assertEqual(s.MolType, RNA)
self.assertEqual(s.Name, 'x')
def test_model_to_regular(self):
"""Model sequence should convert to regular sequence"""
r = RNA.ModelSeq('AAA', Name='x')
s = RNA.Sequence(r)
self.assertEqual(str(s), 'AAA')
self.assertEqual(s.MolType, RNA)
self.assertEqual(s.Name, 'x')
def test_regular_to_regular(self):
"""Regular sequence should convert to regular sequence"""
r = RNA.Sequence('AAA', Name='x')
s = RNA.Sequence(r)
self.assertEqual(str(s), 'AAA')
self.assertEqual(s.MolType, RNA)
self.assertEqual(s.Name, 'x')
def test_model_to_model(self):
"""Model sequence should convert to model sequence"""
r = RNA.ModelSeq('AAA', Name='x')
s = RNA.ModelSeq(r)
self.assertEqual(str(s), 'AAA')
self.assertEqual(s.MolType, RNA)
self.assertEqual(s.Name, 'x')
def test_ModelDnaCodonSequence(self):
"""ModelDnaCodonSequence should behave as expected"""
d = ModelDnaCodonSequence('UUUCGU')
self.assertEqual(str(d), 'TTTCGT')
self.assertEqual(d._data, array([0,28]))
self.assertEqual(str(d.toRna()), 'UUUCGU')
self.assertEqual(str(d.toDna()), 'TTTCGT')
def test_ModelRnaCodonSequence(self):
"""ModelRnaCodonSequence should behave as expected"""
r = ModelRnaCodonSequence('UUUCGU')
self.assertEqual(str(r), 'UUUCGU')
self.assertEqual(r._data, array([0,28]))
self.assertEqual(str(r.toRna()), 'UUUCGU')
self.assertEqual(str(r.toDna()), 'TTTCGT')
class ModelSequenceTests(SequenceTests):
"""Tests of the ModelSequence class's inheritance of SequenceI."""
SEQ = ModelSequence
RNA = ModelRnaSequence
DNA = ModelDnaSequence
PROT = ModelProteinSequence
def test_distance_indices(self):
"""ModelSequence distance should work with function of indices"""
s1 = self.RNA('AUGC')
s2 = self.RNA('AAGC')
def f(x,y):
if x == 2 or y == 2:
return 10
return 0
self.assertEqual(s1.distance(s2, f, use_indices=True), 20)
def test_stripBad(self):
"""Sequence stripBad should remove any non-base, non-gap chars"""
#have to turn off check to get bad data in; no longer preserves case
r = self.RNA('UCAGRYU')
r._data[0] = 31
r._data[2] = 55
self.assertEqual(r.stripBad(), 'CGRYU')
def test_stripBadAndGaps(self):
"""Sequence stripBadAndGaps should remove gaps and bad chars"""
#have to turn off check to get bad data in; no longer preserves case
r = self.RNA('ACG--GRN?')
self.assertEqual(r.stripBadAndGaps(), 'ACGGRN')
r._data[0] = 99
self.assertEqual(r.stripBadAndGaps(), 'CGGRN')
def test_gapArray(self):
"""Sequence gapArray should return array of gaps"""
r = self.RNA('-?A-?NRY-')
v = r.gapArray()
self.assertEqual(v, array([1,1,0,1,1,0,0,0,1]))
r = self.RNA('AC')
v = r.gapArray()
self.assertEqual(v, array([0,0]))
r = self.RNA('-?')
v = r.gapArray()
self.assertEqual(v, array([1,1]))
def test_gapIndices(self):
"""Sequence gapIndices should return positions of gaps"""
r = self.RNA('-?A-?NRY-')
v = r.gapIndices()
self.assertEqual(v, array([0,1,3,4,8]))
r = self.RNA('AC')
v = r.gapIndices()
self.assertEqual(v, array([])) #note: always returns array
r = self.RNA('-?')
v = r.gapIndices()
self.assertEqual(v, array([0,1]))
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_core/test_tree.py 000644 000765 000024 00000231602 12024702176 021746 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of classes for dealing with trees and phylogeny.
"""
from copy import copy, deepcopy
from cogent import LoadTree
from cogent.core.tree import TreeNode, PhyloNode, TreeError
from cogent.parse.tree import DndParser
from cogent.maths.stats.test import correlation
from cogent.util.unit_test import TestCase, main
from numpy import array, arange
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Catherine Lozupone", "Daniel McDonald",
"Peter Maxwell", "Gavin Huttley", "Andrew Butterfield",
"Matthew Wakefield", "Justin Kuczynski","Jens Reeder",
"Jose Carlos Clemente Litran"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class TreeTests(TestCase):
"""Tests of top-level functions."""
def test_LoadTree(self):
"""LoadTree should load a tree from a file or a string"""
#NOTE: This method now sits in cogent.__init__
t_str = '(a_a:10,(b_b:2,c_c:4):5);'
#NOTE: Tree quotes these labels because they have underscores in them.
result_str = "('a_a':10.0,('b_b':2.0,'c_c':4.0):5.0);"
t = LoadTree(treestring=t_str)
#t = DndParser(t_str)
names = [i.Name for i in t.tips()]
self.assertEqual(names, ['a_a', 'b_b', 'c_c'])
self.assertEqual(str(t),result_str)
self.assertEqual(t.getNewick(with_distances=True), result_str)
t_str = '(a_a:10.0,(b_b:2.0,c_c:4.0):5.0);'
#NOTE: Tree silently converts spaces to underscores (only for output),
#presumably for Newick compatibility.
result_str = "(a_a:10.0,(b_b:2.0,c_c:4.0):5.0);"
t = LoadTree(treestring=t_str, underscore_unmunge=True)
#t = DndParser(t_str, unescape_name=True)
names = [i.Name for i in t.tips()]
self.assertEqual(names, ['a a', 'b b', 'c c'])
self.assertEqual(str(t),result_str)
self.assertEqual(t.getNewick(with_distances=True),result_str)
def _new_child(old_node, constructor):
"""Returns new_node which has old_node as its parent."""
new_node = constructor()
new_node.Parent = old_node
if old_node is not None:
if new_node not in old_node.Children:
old_node.Children.append(new_node)
return new_node
tree_std = """\
((a:1, b:2, c:3)abc:0.1, (d:4, (e:5, f:6)ef:0.2)def:0.3);
"""
tree_std_dist = \
[[ 0. , 3. , 4. , 5.4, 6.6, 7.6],
[ 3. , 0. , 5. , 6.4, 7.6, 8.6],
[ 4. , 5. , 0. , 7.4, 8.6, 9.6],
[ 5.4, 6.4, 7.4, 0. , 9.2, 10.2],
[ 6.6, 7.6, 8.6, 9.2, 0. , 11. ],
[ 7.6, 8.6, 9.6, 10.2, 11. , 0. ]]
tree_std_tips = ['a', 'b', 'c', 'd', 'e', 'f']
tree_one_level = """(a:1, b:2, c:3)abc;"""
tree_two_level = """((a:1, b:2, c:3)abc:0.1, d:0.3)abcd;"""
tree_one_child = """((a:1, b:2, c:3)abc:0.1, (d:0.2)d_:0.3)abcd;"""
tree_one_child_dist = \
[[ 0. , 3. , 4. , 1.6],
[ 3. , 0. , 5. , 2.6],
[ 4. , 5. , 0. , 3.6],
[ 1.6, 2.6, 3.6, 0. ]]
tree_one_child_tips = ['a', 'b', 'c', 'd']
class TreeNodeTests(TestCase):
"""Tests of the TreeNode class."""
def setUp(self):
"""Define some standard TreeNode for testing"""
self.Empty = TreeNode()
self.Single = TreeNode(Name='a')
self.Child = TreeNode(Name='b')
self.OneChild = TreeNode(Name='a', Children=[self.Child])
self.Multi = TreeNode(Name = 'a', Children='bcd')
self.Repeated = TreeNode(Name='x', Children='aaa')
self.BigName = map(TreeNode, '0123456789')
self.BigParent = TreeNode(Name = 'x', Children = self.BigName)
self.Comparisons = map(TreeNode, 'aab')
nodes = dict([(x, TreeNode(x)) for x in 'abcdefgh'])
nodes['a'].append(nodes['b'])
nodes['b'].append(nodes['c'])
nodes['c'].append(nodes['d'])
nodes['c'].append(nodes['e'])
nodes['c'].append(nodes['f'])
nodes['f'].append(nodes['g'])
nodes['a'].append(nodes['h'])
self.TreeNode = nodes
self.TreeRoot = nodes['a']
self.s = '((H,G),(R,M));'
self.t = DndParser(self.s, TreeNode)
self.s2 = '(((H,G),R),M);'
self.t2 = DndParser(self.s2, TreeNode)
self.s4 = '(((H,G),(O,R)),X);'
self.t4 = DndParser(self.s4, TreeNode)
def test_init_empty(self):
"""Empty TreeNode should init OK"""
t = self.Empty
self.assertEqual(t.Name, None)
self.assertEqual(t.Parent, None)
self.assertEqual(len(t), 0)
def test_init_full(self):
"""TreeNode should init OK with parent, data, and children"""
t = self.Empty
u = TreeNode(Parent=t, Name='abc', Children='xyz')
self.assertEqual(u.Name, 'abc')
assert u.Parent is t
assert u in t
self.assertEqual(u[0].Name, 'x')
self.assertEqual(u[1].Name, 'y')
self.assertEqual(u[2].Name, 'z')
self.assertEqual(len(u), 3)
def test_str(self):
"""TreeNode str should give Newick-style representation"""
#note: name suppressed if None
self.assertEqual(str(self.Empty), ';')
self.assertEqual(str(self.OneChild), '(b)a;')
self.assertEqual(str(self.BigParent), '(0,1,2,3,4,5,6,7,8,9)x;')
self.BigParent[-1].extend('abc')
self.assertEqual(str(self.BigParent), '(0,1,2,3,4,5,6,7,8,(a,b,c)9)x;')
def test_getNewick(self):
"""Should return Newick-style representation"""
self.assertEqual(self.Empty.getNewick(), ';')
self.assertEqual(self.OneChild.getNewick(), '(b)a;')
self.assertEqual(self.BigParent.getNewick(), \
'(0,1,2,3,4,5,6,7,8,9)x;')
self.BigParent[-1].extend('abc')
self.assertEqual(self.BigParent.getNewick(), \
'(0,1,2,3,4,5,6,7,8,(a,b,c)9)x;')
def test_multifurcating(self):
"""Coerces nodes to have <= n children"""
t_str = "((a:1,b:2,c:3)d:4,(e:5,f:6,g:7)h:8,(i:9,j:10,k:11)l:12)m:14;"
t = DndParser(t_str)
# can't break up easily... sorry 80char
exp_str = "((a:1.0,(b:2.0,c:3.0):0.0)d:4.0,((e:5.0,(f:6.0,g:7.0):0.0)h:8.0,(i:9.0,(j:10.0,k:11.0):0.0)l:12.0):0.0)m:14.0;"
obs = t.multifurcating(2)
self.assertEqual(obs.getNewick(with_distances=True), exp_str)
self.assertNotEqual(t.getNewick(with_distances=True),
obs.getNewick(with_distances=True))
obs = t.multifurcating(2, 0.5)
exp_str = "((a:1.0,(b:2.0,c:3.0):0.5)d:4.0,((e:5.0,(f:6.0,g:7.0):0.5)h:8.0,(i:9.0,(j:10.0,k:11.0):0.5)l:12.0):0.5)m:14.0;"
self.assertEqual(obs.getNewick(with_distances=True), exp_str)
t_str = "((a,b,c)d,(e,f,g)h,(i,j,k)l)m;"
exp_str = "((a,(b,c))d,((e,(f,g))h,(i,(j,k))l))m;"
t = DndParser(t_str, constructor=TreeNode)
obs = t.multifurcating(2)
self.assertEqual(obs.getNewick(with_distances=True), exp_str)
obs = t.multifurcating(2, eps=10) # no effect on TreeNode type
self.assertEqual(obs.getNewick(with_distances=True), exp_str)
self.assertRaises(TreeError, t.multifurcating, 1)
def test_multifurcating_nameunnamed(self):
"""Coerces nodes to have <= n children"""
t_str = "((a:1,b:2,c:3)d:4,(e:5,f:6,g:7)h:8,(i:9,j:10,k:11)l:12)m:14;"
t = DndParser(t_str)
exp_str = "((a:1.0,(b:2.0,c:3.0):0.0)d:4.0,((e:5.0,(f:6.0,g:7.0):0.0)h:8.0,(i:9.0,(j:10.0,k:11.0):0.0)l:12.0):0.0)m:14.0;"
obs = t.multifurcating(2, name_unnamed=True)
c0,c1 = obs.Children
self.assertTrue(c0.Children[1].Name.startswith('AUTO'))
self.assertTrue(c1.Name.startswith('AUTO'))
self.assertTrue(c1.Children[0].Children[1].Name.startswith('AUTO'))
self.assertTrue(c1.Children[1].Children[1].Name.startswith('AUTO'))
self.assertEqual(len(c0.Children[1].Name), 22)
self.assertEqual(len(c1.Name), 22)
self.assertEqual(len(c1.Children[0].Children[1].Name), 22)
self.assertEqual(len(c1.Children[1].Children[1].Name), 22)
names = [n.Name for n in t.nontips()]
self.assertEqual(len(names), len(set(names)))
def test_bifurcating(self):
"""Coerces nodes to have <= 2 children"""
t_str = "((a:1,b:2,c:3)d:4,(e:5,f:6,g:7)h:8,(i:9,j:10,k:11)l:12)m:14;"
t = DndParser(t_str)
# can't break up easily... sorry 80char
exp_str = "((a:1.0,(b:2.0,c:3.0):0.0)d:4.0,((e:5.0,(f:6.0,g:7.0):0.0)h:8.0,(i:9.0,(j:10.0,k:11.0):0.0)l:12.0):0.0)m:14.0;"
obs = t.bifurcating()
def test_cmp(self):
"""TreeNode cmp should compare using id"""
nodes = self.TreeNode
self.assertEqual(cmp(nodes['a'], nodes['a']), 0)
self.assertNotEqual(cmp(nodes['b'], nodes['a']), 0)
self.assertNotEqual(cmp(nodes['a'], nodes['b']), 0)
def test_compareName(self):
"""Compare names between TreeNodes"""
nodes = self.TreeNode
self.assertEqual(nodes['a'].compareName(nodes['a']), 0)
self.assertEqual(nodes['a'].compareName(nodes['b']), -1)
self.assertEqual(nodes['b'].compareName(nodes['a']), 1)
def test_compareByNames(self):
"""Compare names between trees"""
self.assertTrue(self.t.compareByNames(self.t2))
self.assertTrue(self.t.compareByNames(self.t))
self.assertFalse(self.t.compareByNames(self.t4))
def test_eq(self):
"""TreeNode should compare equal if same id"""
t, u, v = self.Comparisons
self.assertEqual(t, t)
assert t is not u
self.assertNotEqual(t, u)
self.assertNotEqual(t, v)
f = TreeNode(1.0)
g = TreeNode(1)
self.assertNotEqual(f, g)
f.Name += 0.1
self.assertNotEqual(f, g)
#however, two TreeNodes that have no name should not compare equal
f = TreeNode()
g = TreeNode()
self.assertNotEqual(f,g)
f = TreeNode(Name='foo')
g = f.copy()
self.assertNotEqual(f, g)
def test_ne(self):
"""TreeNode should compare ne by id or data"""
t, u, v = self.Comparisons
self.assertFalse(t != t)
self.assertTrue(t != u)
f = TreeNode(Name='foo')
g = f.copy()
self.assertTrue(f != g)
def test_append(self):
"""TreeNode append should add item to end of self"""
self.OneChild.append(TreeNode('c'))
self.assertEqual(len(self.OneChild), 2)
self.assertEqual(self.OneChild[-1].Name, 'c')
self.OneChild.append(6)
self.assertEqual(len(self.OneChild), 3)
self.assertEqual(self.OneChild[-1].Name, 6)
#check that refs are updated when moved from one tree to another
empty = TreeNode()
empty.append(self.OneChild[-1])
self.assertEqual(len(empty), 1)
self.assertEqual(empty[0].Name, 6)
self.assertEqual(empty[0].Parent, empty)
self.assertEqual(self.OneChild[-1].Name, 'c')
def test_extend(self):
"""TreeNode extend should add many items to end of self"""
self.Empty.extend('abcdefgh')
data = ''.join([i.Name for i in self.Empty])
self.assertEqual(data, 'abcdefgh')
def test_insert(self):
"""TreeNode insert should insert item at specified index"""
parent, nodes = self.BigParent, self.BigName
self.assertEqual(len(parent), 10)
parent.insert(3, 5)
self.assertEqual(len(parent), 11)
self.assertEqual(parent[3].Name, 5)
self.assertEqual(parent[4].Name, '3')
parent.insert(-1, 123)
self.assertEqual(len(parent), 12)
self.assertEqual(parent[-1].Name, '9')
self.assertEqual(parent[-2].Name, 123)
def test_pop(self):
"""TreeNode pop should remove and return child at specified index"""
parent, nodes = self.BigParent, self.BigName
self.assertEqual(len(parent), 10)
last = parent.pop()
assert last is nodes[-1]
assert last.Parent is None
self.assertEqual(len(parent), 9)
assert parent[-1] is nodes[-2]
first = parent.pop(0)
assert first is nodes[0]
assert first.Parent is None
self.assertEqual(len(parent), 8)
assert parent[0] is nodes[1]
second_to_last = parent.pop(-2)
assert second_to_last is nodes[-3]
def test_remove(self):
"""TreeNode remove should remove first match by value, not id"""
nodes = map(TreeNode, 'abc'*3)
parent = TreeNode(Children=nodes)
self.assertEqual(len(parent), 9)
parent.remove('a')
self.assertEqual(len(parent), 8)
self.assertEqual(''.join([i.Name for i in parent]), 'bcabcabc')
new_node = TreeNode('a')
parent.remove(new_node)
self.assertEqual(len(parent), 7)
self.assertEqual(''.join([i.Name for i in parent]), 'bcbcabc')
def test_getitem(self):
"""TreeNode getitem should return item or slice"""
r = self.TreeRoot
n = self.TreeNode
assert r[0] is n['b']
items = n['c'][0:1]
self.assertEqual(len(items), 1)
assert items[0] is n['d']
items = n['c'][0:2]
self.assertEqual(len(items), 2)
assert items[0] is n['d']
assert items[1] is n['e']
items = n['c'][:]
self.assertEqual(len(items), 3)
assert items[0] is n['d']
assert items[-1] is n['f']
def test_slice(self):
"""TreeNode slicing should return list, not TreeNode"""
nodes = self.TreeNode
c, d, e, f = nodes['c'],nodes['d'],nodes['e'],nodes['f']
assert c[:] is not c
self.assertEqual(c[:], [d,e,f])
self.assertEqual(c[1:2], [e])
self.assertEqual(c[0:3:2], [d,f])
def test_setitem(self):
"""TreeNode setitem should set item or extended slice of nodes"""
parent, nodes = self.BigParent, self.BigName
t = TreeNode(1)
parent[0] = t
assert parent[0] is t
assert t.Parent is parent
assert nodes[0].Parent is None
u = TreeNode(2)
parent[-2] = u
assert parent[8] is u
assert u.Parent is parent
assert nodes[8].Parent is None
parent[1:6:2] = 'xyz'
for i in [1,3,5]:
assert nodes[i].Parent is None
self.assertEqual(parent[1].Name, 'x')
self.assertEqual(parent[3].Name, 'y')
self.assertEqual(parent[5].Name, 'z')
for i in parent:
assert i.Parent is parent
def test_setslice(self):
"""TreeNode setslice should set old-style slice of nodes"""
parent, nodes = self.BigParent, self.BigName
self.assertEqual(len(parent), 10)
parent[5:] = []
self.assertEqual(len(parent), 5)
for i in range(5, 10):
assert nodes[i].Parent is None
parent[1:3] = 'abcd'
self.assertEqual(len(parent), 7)
for i in parent:
assert i.Parent is parent
data_list = [i.Name for i in parent]
self.assertEqual(data_list, list('0abcd34'))
parent[1:3] = parent[2:3]
data_list = [i.Name for i in parent]
self.assertEqual(data_list, list('0bcd34'))
def test_delitem(self):
"""TreeNode __delitem__ should delete item and set parent to None"""
self.assertEqual(self.Child.Parent, self.OneChild)
self.assertEqual(len(self.OneChild), 1)
del self.OneChild[0]
self.assertEqual(self.OneChild.Parent, None)
self.assertEqual(len(self.OneChild), 0)
nodes = self.BigName
parent = self.BigParent
self.assertEqual(len(parent), 10)
for n in nodes:
assert n.Parent is parent
del parent[-1]
self.assertEqual(nodes[-1].Parent, None)
self.assertEqual(len(parent), 9)
del parent[1:6:2]
self.assertEqual(len(parent), 6)
for i, n in enumerate(nodes):
if i in [0,2,4,6,7,8]:
assert n.Parent is parent
else:
assert n.Parent is None
def test_delslice(self):
"""TreeNode __delslice__ should delete items from start to end"""
parent = self.BigParent
nodes = self.BigName
self.assertEqual(len(parent), 10)
del parent[3:-2]
self.assertEqual(len(parent), 5)
for i, n in enumerate(nodes):
if i in [3,4,5,6,7]:
assert n.Parent is None
else:
assert n.Parent is parent
def test_iter(self):
"""TreeNode iter should iterate over children"""
r = self.TreeRoot
n = self.TreeNode
items = list(r)
assert items[0] is n['b']
assert items[1] is n['h']
self.assertEqual(len(items), 2)
def test_len(self):
"""TreeNode len should return number of children"""
r = self.TreeRoot
self.assertEqual(len(r), 2)
def test_copyRecursive(self):
"""TreeNode.copyRecursive() should produce deep copy"""
t = TreeNode(['t'])
u = TreeNode(['u'])
t.append(u)
c = u.copy()
assert c is not u
assert c.Name == u.Name
assert c.Name is not u.Name
#note: Name _is_ same object if it's immutable, e.g. a string.
#deepcopy doesn't copy data for immutable objects.
#need to check that we also copy arbitrary attributes
t.XYZ = [3]
c = t.copy()
assert c is not t
assert c[0] is not u
assert c[0].Name is not u.Name
assert c[0].Name == u.Name
assert c.XYZ == t.XYZ
assert c.XYZ is not t.XYZ
t = self.TreeRoot
c = t.copy()
self.assertEqual(str(c), str(t))
def test_copy(self):
"""TreeNode.copy() should work on deep trees"""
t = comb_tree(1024) # should break recursion limit on regular copy
t.Name = 'foo'
t.XYZ = [3]
t2 = t.copy()
t3 = t.copy()
t3.Name = 'bar'
self.assertEqual(len(t.tips()), 1024)
self.assertEqual(len(t2.tips()), 1024)
self.assertEqual(len(t3.tips()), 1024)
self.assertNotSameObj(t, t2)
self.assertEqual(t.Name, t2.Name)
self.assertNotEqual(t.Name, t3.Name)
self.assertEqual(t.XYZ, t2.XYZ)
self.assertNotSameObj(t.XYZ, t2.XYZ)
self.assertEqual(t.getNewick(), t2.getNewick())
t_simple = TreeNode(['t'])
u_simple = TreeNode(['u'])
t_simple.append(u_simple)
self.assertEqual(str(t_simple.copy()), str(t_simple.copy()))
def test_copyTopology(self):
"""TreeNode.copyTopology() should produce deep copy ignoring attrs"""
t = TreeNode(['t'])
u = TreeNode(['u'])
t.append(u)
c = u.copyTopology()
assert c is not u
self.assertEqual(c.Name, u.Name)
#note: Name _is_ same object if it's immutable, e.g. a string.
#deepcopy doesn't copy data for immutable objects.
#need to check that we do not also copy arbitrary attributes
t.XYZ = [3]
c = t.copyTopology()
assert c is not t
assert c[0] is not u
assert c[0].Name is not u.Name
assert c[0].Name == u.Name
assert not hasattr(c, 'XYZ')
t = self.TreeRoot
c = t.copy()
self.assertEqual(str(c), str(t))
def _test_copy_copy(self):
"""copy.copy should raise TypeError on TreeNode"""
t = TreeNode('t')
u = TreeNode('u')
t.append(u)
self.assertRaises(TypeError, copy, t)
self.assertRaises(TypeError, copy, u)
def test_deepcopy(self):
"""copy.deepcopy should work on TreeNode"""
t = TreeNode(['t'])
u = TreeNode(['u'])
t.append(u)
c = deepcopy(u)
assert c is not u
assert c.Name == u.Name
assert c.Name is not u.Name
#note: Name _is_ same object if it's immutable, e.g. a string.
#deepcopy doesn't copy data for immutable objects.
#need to check that we also copy arbitrary attributes
t.XYZ = [3]
c = deepcopy(t)
assert c is not t
assert c[0] is not u
assert c[0].Name is not u.Name
assert c[0].Name == u.Name
assert c.XYZ == t.XYZ
assert c.XYZ is not t.XYZ
t = self.TreeRoot
c = deepcopy(t)
self.assertEqual(str(c), str(t))
def test_Parent(self):
"""TreeNode Parent should hold correct data and be mutable"""
#check initial conditions
self.assertEqual(self.Single.Parent, None)
#set parent and check parent/child relations
self.Single.Parent = self.Empty
assert self.Single.Parent is self.Empty
self.assertEqual(self.Empty[0], self.Single)
assert self.Single in self.Empty
self.assertEqual(len(self.Empty), 1)
#reset parent and check parent/child relations
self.Single.Parent = self.OneChild
assert self.Single.Parent is self.OneChild
assert self.Single not in self.Empty
assert self.Single is self.OneChild[-1]
#following is added to check that we don't screw up when there are
#nodes with different ids that still compare equal
for i in self.Repeated:
assert i.Parent is self.Repeated
last = self.Repeated[-1]
last.Parent = self.OneChild
self.assertEqual(len(self.Repeated), 2)
for i in self.Repeated:
assert i.Parent is self.Repeated
assert last.Parent is self.OneChild
def test_indexInParent(self):
"""TreeNode indexInParent should hold correct data"""
first = TreeNode('a')
second = TreeNode('b')
third = TreeNode('c')
fourth = TreeNode('0', Children=[first, second, third])
self.assertEqual(len(fourth), 3)
self.assertEqual(first.indexInParent(), 0)
self.assertEqual(second.indexInParent(), 1)
self.assertEqual(third.indexInParent(), 2)
del fourth[0]
self.assertEqual(second.indexInParent(), 0)
self.assertEqual(third.indexInParent(), 1)
self.assertEqual(len(fourth), 2)
assert first.Parent is None
def test_isTip(self):
"""TreeNode isTip should return True if node is a tip"""
tips = 'degh'
for n in self.TreeNode.values():
if n.Name in tips:
self.assertEqual(n.isTip(), True)
else:
self.assertEqual(n.isTip(), False)
def test_isRoot(self):
"""TreeNode isRoot should return True if parent is None"""
r = 'a'
for n in self.TreeNode.values():
if n.Name in r:
self.assertEqual(n.isRoot(), True)
else:
self.assertEqual(n.isRoot(), False)
def test_traverse(self):
"""TreeNode traverse should iterate over nodes in tree."""
e = self.Empty
s = self.Single
o = self.OneChild
m = self.Multi
r = self.TreeRoot
self.assertEqual([i.Name for i in e.traverse()], [None])
self.assertEqual([i.Name for i in e.traverse(False, False)], [None])
self.assertEqual([i.Name for i in e.traverse(True, True)], [None])
self.assertEqual([i.Name for i in s.traverse()], ['a'])
self.assertEqual([i.Name for i in s.traverse(True, True)], ['a'])
self.assertEqual([i.Name for i in s.traverse(True, False)], ['a'])
self.assertEqual([i.Name for i in s.traverse(False, True)], ['a'])
self.assertEqual([i.Name for i in s.traverse(False, False)], ['a'])
self.assertEqual([i.Name for i in o.traverse()], ['a','b'])
self.assertEqual([i.Name for i in o.traverse(True, True)],['a','b','a'])
self.assertEqual([i.Name for i in o.traverse(True, False)], ['a', 'b'])
self.assertEqual([i.Name for i in o.traverse(False, True)], ['b', 'a'])
self.assertEqual([i.Name for i in o.traverse(False, False)], ['b'])
self.assertEqual([i.Name for i in m.traverse()], ['a','b','c','d'])
self.assertEqual([i.Name for i in m.traverse(True, True)],\
['a','b','c','d','a'])
self.assertEqual([i.Name for i in m.traverse(True, False)], \
['a', 'b','c','d'])
self.assertEqual([i.Name for i in m.traverse(False, True)], \
['b', 'c', 'd', 'a'])
self.assertEqual([i.Name for i in m.traverse(False, False)], \
['b', 'c', 'd'])
self.assertEqual([i.Name for i in r.traverse()], \
['a','b','c','d', 'e', 'f', 'g', 'h'])
self.assertEqual([i.Name for i in r.traverse(True, True)],\
['a','b','c','d','e','f','g','f','c','b','h','a'])
self.assertEqual([i.Name for i in r.traverse(True, False)], \
['a', 'b','c','d','e','f','g','h'])
self.assertEqual([i.Name for i in r.traverse(False, True)], \
['d','e','g','f','c','b','h','a'])
self.assertEqual([i.Name for i in r.traverse(False, False)], \
['d','e','g','h'])
self.assertEqual([i.Name for i in r.traverse(True, True, False)],\
['b','c','d','e','f','g','f','c','b','h'])
self.assertEqual([i.Name for i in r.traverse(True, False, False)], \
['b','c','d','e','f','g','h'])
self.assertEqual([i.Name for i in r.traverse(False, True, False)], \
['d','e','g','f','c','b','h'])
self.assertEqual([i.Name for i in r.traverse(False, False, False)], \
['d','e','g','h'])
#this previously failed
t = DndParser('((a:6,(b:1,c:2):8):12,(d:3,(e:1,f:1):4):10);')
t0 = t.Children[0]
list(t0.traverse(self_before=False, self_after=True))
list(t0.traverse(self_before=True, self_after=True))
def test_levelorder(self):
t = DndParser("(((A,B)C,(D,E)F,(G,H)I)J,(K,L)M)N;")
exp = ['N','J','M','C','F','I','K','L','A','B','D','E','G','H']
names = [n.Name for n in t.levelorder()]
self.assertEqual(names,exp)
def test_ancestors(self):
"""TreeNode ancestors should provide list of ancestors, deepest first"""
nodes, tree = self.TreeNode, self.TreeRoot
self.assertEqual(nodes['a'].ancestors(), [])
self.assertEqual(nodes['b'].ancestors(), [nodes['a']])
self.assertEqual(nodes['d'].ancestors(), nodes['f'].ancestors())
self.assertEqual(nodes['g'].ancestors(), \
[nodes['f'], nodes['c'], nodes['b'], nodes['a']])
def test_root(self):
"""TreeNode root() should find root of tree"""
nodes, root = self.TreeNode, self.TreeRoot
for i in nodes.values():
assert i.root() is root
def test_children(self):
"""TreeNode Children should allow getting/setting children"""
nodes = self.TreeNode
for n in nodes:
node = nodes[n]
self.assertEqual(list(node), node.Children)
t = TreeNode(Children='abc')
self.assertEqual(len(t), 3)
u, v = TreeNode('u'), TreeNode('v')
#WARNING: If you set Children directly, Parent refs will _not_ update!
t.Children = [u,v]
assert t[0] is u
assert t[1] is v
self.assertEqual(len(t), 2)
def test_siblings(self):
"""TreeNode siblings() should return all siblings, not self"""
self.assertEqual(self.Empty.siblings(), [])
self.assertEqual(self.Child.siblings(), [])
self.assertEqual(self.OneChild.siblings(), [])
nodes, tree = self.TreeNode, self.TreeRoot
a = nodes['a']
b = nodes['b']
c = nodes['c']
d = nodes['d']
e = nodes['e']
f = nodes['f']
g = nodes['g']
h = nodes['h']
self.assertEqual(g.siblings(), [])
self.assertEqual(f.siblings(), [d,e])
self.assertEqual(e.siblings(), [d,f])
self.assertEqual(d.siblings(), [e,f])
self.assertEqual(c.siblings(), [])
self.assertEqual(b.siblings(), [h])
self.assertEqual(h.siblings(), [b])
self.assertEqual(a.siblings(), [])
def test_tips(self):
"""TreeNode tips should return all terminal descendants"""
self.assertEqual(self.Empty.tips(), [])
self.assertEqual(self.Child.tips(), [])
self.assertEqual(self.OneChild.tips(), [self.Child])
nodes, tree = self.TreeNode, self.TreeRoot
a = nodes['a']
b = nodes['b']
c = nodes['c']
d = nodes['d']
e = nodes['e']
f = nodes['f']
g = nodes['g']
h = nodes['h']
self.assertEqual(g.tips(), [])
self.assertEqual(f.tips(), [g])
self.assertEqual(e.tips(), [])
self.assertEqual(d.tips(), [])
self.assertEqual(c.tips(), [d,e,g])
self.assertEqual(b.tips(), [d,e,g])
self.assertEqual(h.tips(), [])
self.assertEqual(a.tips(), [d,e,g,h])
def test_itertips(self):
"""TreeNode itertips should iterate over terminal descendants"""
tree = self.TreeRoot
self.assertEqual([i.Name for i in tree.iterTips()], list('degh')),
def test_nontips(self):
"""TreeNode nontips should return all non-terminal descendants"""
tree = self.TreeRoot
self.assertEqual([i.Name for i in tree.nontips()], list('bcf'))
def test_iterNonTips(self):
"""TreeNode iterNontips should iterate over non-terminal descendants"""
tree = self.TreeRoot
self.assertEqual([i.Name for i in tree.iterNontips()], list('bcf'))
def test_tipChildren(self):
"""TreeNode tipChildren should return all terminal children"""
self.assertEqual(self.Empty.tipChildren(), [])
self.assertEqual(self.Child.tipChildren(), [])
self.assertEqual(self.OneChild.tipChildren(), [self.Child])
nodes, tree = self.TreeNode, self.TreeRoot
a = nodes['a']
b = nodes['b']
c = nodes['c']
d = nodes['d']
e = nodes['e']
f = nodes['f']
g = nodes['g']
h = nodes['h']
self.assertEqual(g.tipChildren(), [])
self.assertEqual(f.tipChildren(), [g])
self.assertEqual(e.tipChildren(), [])
self.assertEqual(d.tipChildren(), [])
self.assertEqual(c.tipChildren(), [d,e])
self.assertEqual(b.tipChildren(), [])
self.assertEqual(h.tipChildren(), [])
self.assertEqual(a.tipChildren(), [h])
def test_nonTipChildren(self):
"""TreeNode nonTipChildren should return all non-terminal children"""
self.assertEqual(self.Empty.nonTipChildren(), [])
self.assertEqual(self.Child.nonTipChildren(), [])
self.assertEqual(self.OneChild.nonTipChildren(), [])
nodes, tree = self.TreeNode, self.TreeRoot
a = nodes['a']
b = nodes['b']
c = nodes['c']
d = nodes['d']
e = nodes['e']
f = nodes['f']
g = nodes['g']
h = nodes['h']
self.assertEqual(g.nonTipChildren(), [])
self.assertEqual(f.nonTipChildren(), [])
self.assertEqual(e.nonTipChildren(), [])
self.assertEqual(d.nonTipChildren(), [])
self.assertEqual(c.nonTipChildren(), [f])
self.assertEqual(b.nonTipChildren(), [c])
self.assertEqual(h.nonTipChildren(), [])
self.assertEqual(a.nonTipChildren(), [b])
def test_childGroups(self):
"""TreeNode childGroups should divide children by grandchild presence"""
parent = TreeNode(Children='aababbbaaabbbababbb')
for node in parent:
if node.Name == 'a':
node.append('def')
groups = parent.childGroups()
self.assertEqual(len(groups), 10)
exp_group_sizes = [2,1,1,3,3,3,1,1,1,3]
obs_group_sizes = [len(i) for i in groups]
self.assertEqual(obs_group_sizes, exp_group_sizes)
parent = TreeNode(Children='aab')
for node in parent:
if node.Name == 'a':
node.append('def')
groups = parent.childGroups()
self.assertEqual(len(groups), 2)
self.assertEqual([len(i) for i in groups], [2,1])
parent = TreeNode(Children='aaaaa')
groups = parent.childGroups()
self.assertEqual(len(groups), 1)
self.assertEqual(len(groups[0]), 5)
parent = TreeNode(Children='aaba')
for node in parent:
if node.Name == 'a':
node.append('def')
groups = parent.childGroups()
self.assertEqual(len(groups), 3)
self.assertEqual([len(i) for i in groups], [2,1,1])
def test_removeNode(self):
"""TreeNode removeNode should delete node by id, not value"""
parent = self.Repeated
children = list(self.Repeated)
self.assertEqual(len(parent), 3)
self.assertEqual(parent.removeNode(children[1]), True)
self.assertEqual(len(parent), 2)
assert children[0].Parent is parent
assert children[1].Parent is None
assert children[2].Parent is parent
self.assertEqual(children[0].compareName(children[1]), 0)
self.assertEqual(parent.removeNode(children[1]), False)
self.assertEqual(len(parent), 2)
self.assertEqual(parent.removeNode(children[0]), True)
self.assertEqual(len(parent), 1)
def test_lowestCommonAncestor(self):
"""TreeNode lowestCommonAncestor should return LCA for set of tips"""
t1 = DndParser("((a,(b,c)d)e,f,(g,h)i)j;")
t2 = t1.copy()
t3 = t1.copy()
t4 = t1.copy()
input1 = ['a'] # return self
input2 = ['a','b'] # return e
input3 = ['b','c'] # return d
input4 = ['a','h','g'] # return j
exp1 = t1.getNodeMatchingName('a')
exp2 = t2.getNodeMatchingName('e')
exp3 = t3.getNodeMatchingName('d')
exp4 = t4
obs1 = t1.lowestCommonAncestor(input1)
obs2 = t2.lowestCommonAncestor(input2)
obs3 = t3.lowestCommonAncestor(input3)
obs4 = t4.lowestCommonAncestor(input4)
self.assertEqual(obs1, exp1)
self.assertEqual(obs2, exp2)
self.assertEqual(obs3, exp3)
self.assertEqual(obs4, exp4)
# verify multiple calls work
t_mul = t1.copy()
exp_1 = t_mul.getNodeMatchingName('d')
exp_2 = t_mul.getNodeMatchingName('i')
obs_1 = t_mul.lowestCommonAncestor(['b','c'])
obs_2 = t_mul.lowestCommonAncestor(['g','h'])
self.assertEqual(obs_1, exp_1)
self.assertEqual(obs_2, exp_2)
def test_lastCommonAncestor(self):
"""TreeNode LastCommonAncestor should provide last common ancestor"""
nodes, tree = self.TreeNode, self.TreeRoot
a = nodes['a']
b = nodes['b']
c = nodes['c']
d = nodes['d']
e = nodes['e']
f = nodes['f']
g = nodes['g']
h = nodes['h']
self.assertEqual(a.lastCommonAncestor(a), a)
self.assertEqual(a.lastCommonAncestor(b), a)
self.assertEqual(a.lastCommonAncestor(g), a)
self.assertEqual(a.lastCommonAncestor(h), a)
self.assertEqual(b.lastCommonAncestor(g), b)
self.assertEqual(b.lastCommonAncestor(d), b)
self.assertEqual(b.lastCommonAncestor(a), a)
self.assertEqual(b.lastCommonAncestor(h), a)
self.assertEqual(d.lastCommonAncestor(f), c)
self.assertEqual(d.lastCommonAncestor(g), c)
self.assertEqual(d.lastCommonAncestor(a), a)
self.assertEqual(d.lastCommonAncestor(h), a)
self.assertEqual(g.lastCommonAncestor(g), g)
self.assertEqual(g.lastCommonAncestor(f), f)
self.assertEqual(g.lastCommonAncestor(e), c)
self.assertEqual(g.lastCommonAncestor(c), c)
self.assertEqual(g.lastCommonAncestor(b), b)
self.assertEqual(g.lastCommonAncestor(a), a)
self.assertEqual(g.lastCommonAncestor(h), a)
t = TreeNode('h')
for i in [a,b,c,d,e,f,g,h]:
self.assertEqual(i.lastCommonAncestor(t), None)
self.assertEqual(t.lastCommonAncestor(i), None)
u = TreeNode('a', Children=[t])
def test_separation(self):
"""TreeNode separation should return correct number of edges"""
nodes, tree = self.TreeNode, self.TreeRoot
a = nodes['a']
b = nodes['b']
c = nodes['c']
d = nodes['d']
e = nodes['e']
f = nodes['f']
g = nodes['g']
h = nodes['h']
self.assertEqual(a.separation(a), 0)
self.assertEqual(c.separation(c), 0)
self.assertEqual(a.separation(b), 1)
self.assertEqual(a.separation(h), 1)
self.assertEqual(g.separation(h), 5)
self.assertEqual(f.separation(d), 2)
self.assertEqual(f.separation(c), 1)
self.assertEqual(c.separation(f), 1)
def test_nameUnnamedNodes(self):
"""nameUnnamedNodes assigns an arbitrary value when Name == None"""
tree, tree_nodes = self.TreeRoot, self.TreeNode
tree_nodes['b'].Name = 'node2'
tree_nodes['c'].Name = None
tree_nodes['f'].Name = None
tree_nodes['e'].Name = 'node3'
tree.nameUnnamedNodes()
self.assertEqual(tree_nodes['c'].Name, 'node1')
self.assertEqual(tree_nodes['f'].Name, 'node4')
def test_makeTreeArray(self):
"""makeTreeArray maps nodes to the descendants in them"""
tree = self.TreeRoot
result, node_list = tree.makeTreeArray()
self.assertEqual(result, \
array([[1,1,1,1], [1,1,1,0], [1,1,1,0],[0,0,1,0]]))
nodes = [node.Name for node in node_list]
self.assertEqual(nodes, ['a', 'b', 'c', 'f'])
#test if works with a dec_list supplied
dec_list = ['d', 'added', 'e', 'g', 'h']
result2, node_list = tree.makeTreeArray(dec_list)
self.assertEqual(result2, \
array([[1,0,1,1,1], [1,0,1,1,0], [1,0,1,1,0], [0,0,0,1,0]]))
def test_reassignNames(self):
"""reassignNames should rename node names based on dict mapping"""
t = self.TreeRoot
mapping = dict([(x, str(i)) for i,x in enumerate('abfg')])
exp_names = ['0','1','2','3','c','d','e','h']
t.reassignNames(mapping)
obs_names = sorted(t.getNodeNames())
self.assertEqual(obs_names, exp_names)
def test_reassignNames_specific_nodes(self):
"""reassignNames should rename nodes based on dict mapping"""
t = self.TreeRoot
nodes = [self.TreeNode['a'], self.TreeNode['b']]
mapping = dict([(x, str(i)) for i,x in enumerate('abfg')])
exp_names = ['0','1','c','d','e','f','g','h']
t.reassignNames(mapping, nodes)
obs_names = sorted(t.getNodeNames())
self.assertEqual(obs_names, exp_names)
def test_getNodesDict(self):
"""getNodesDict returns a dict keyed by name, value is node"""
t = self.TreeRoot
nodes = self.TreeNode
self.assertEqual(t.getNodesDict(), nodes)
def test_getNodesDict_nonunique_names(self):
"""getNodesDict raises if non unique names are in tree"""
t = self.TreeRoot
t.Children[0].Name = 'same'
t.Children[0].Children[0].Name = 'same'
self.assertRaises(TreeError, t.getNodesDict)
def test_removeDeleted(self):
"""removeDeleted should remove all nodes where is_deleted tests true."""
tree = DndParser('((a:3,(b:2,(c:1,d:1):1):1):2,(e:3,f:3):2);',
constructor=TreeNode)
result_not_deleted = deepcopy(tree)
tree.removeDeleted(lambda x: x.Name in [])
self.assertEqual(str(tree),str(result_not_deleted))
deleted = set(['b','d','e','f'])
result_tree = DndParser('((a:3,((c:1):1):1):2);',constructor=TreeNode)
is_deleted = lambda x: x.Name in deleted
tree.removeDeleted(is_deleted)
self.assertEqual(str(tree),str(result_tree))
def test_prune(self):
"""prune should reconstruct correct topology of tree."""
tree = DndParser('((a:3,((c:1):1):1):2);',constructor=TreeNode)
tree.prune()
result_tree = DndParser('((a:3,c:1));',constructor=TreeNode)
self.assertEqual(str(tree),str(result_tree))
samename_bug = DndParser("((A,B)SAMENAME,((C,D)SAMENAME));")
samename_bug.prune()
exp_tree_str = '((A,B)SAMENAME,(C,D)SAMENAME);'
self.assertEqual(str(samename_bug), exp_tree_str)
def test_getNodeMatchingName(self):
"""TreeNode getNodeMatchingName should return node that matches name"""
nodes = self.TreeNode
root = self.TreeRoot
assert root.getNodeMatchingName('g') is nodes['g']
def test_subset(self):
"""subset should return set of leaves that descends from node"""
t = self.t
self.assertEqual(t.subset(), frozenset('HGRM'))
c = t.Children[0]
self.assertEqual(c.subset(), frozenset('HG'))
leaf = c.Children[1]
self.assertEqual(leaf.subset(), frozenset(''))
def test_subsets(self):
"""subsets should return all subsets descending from a set"""
t = self.t
self.assertEqual(t.subsets(), frozenset(
[frozenset('HG'), frozenset('RM')]))
def test_compareBySubsets(self):
"""compareBySubsets should return the fraction of shared subsets"""
result = self.t.compareBySubsets(self.t)
self.assertEqual(result, 0)
result = self.t2.compareBySubsets(self.t2)
self.assertEqual(result, 0)
result = self.t.compareBySubsets(self.t2)
self.assertEqual(result, 0.5)
result = self.t.compareBySubsets(self.t4)
self.assertEqual(result, 1-2./5)
result = self.t.compareBySubsets(self.t4, exclude_absent_taxa=True)
self.assertEqual(result, 1-2./3)
result = self.t.compareBySubsets(self.TreeRoot, exclude_absent_taxa=True)
self.assertEqual(result, 1)
result = self.t.compareBySubsets(self.TreeRoot)
self.assertEqual(result, 1)
class PhyloNodeTests(TestCase):
"""Tests of phylogeny-specific methods."""
def setUp(self):
"""Creates a standard tree"""
nodes = dict([(x, PhyloNode(x)) for x in 'abcdefgh'])
nodes['a'].append(nodes['b'])
nodes['b'].append(nodes['c'])
nodes['c'].append(nodes['d'])
nodes['c'].append(nodes['e'])
nodes['c'].append(nodes['f'])
nodes['f'].append(nodes['g'])
nodes['a'].append(nodes['h'])
self.TreeNode = nodes
self.TreeRoot = nodes['a']
nodes['a'].Length = None
nodes['b'].Length = 0
nodes['c'].Length = 3
nodes['d'].Length = 1
nodes['e'].Length = 4
nodes['f'].Length = 2
nodes['g'].Length = 3
nodes['h'].Length = 2
self.s = '((H:1,G:1):2,(R:0.5,M:0.7):3);'
self.t = DndParser(self.s,PhyloNode)
self.s3 = '(((H:1,G:1,O:1):2,R:3):1,X:4);'
self.t3 = DndParser(self.s3, PhyloNode)
def test_init(self):
"""Check PhyloNode constructor"""
n = PhyloNode('foo', Length=10)
self.assertEqual(n.Name,'foo')
self.assertEqual(n.Length, 10)
n = PhyloNode('bar')
self.assertEqual(n.Name, 'bar')
self.assertEqual(n.Length, None)
n = PhyloNode()
self.assertEqual(n.Name, None)
self.assertEqual(n.Length, None)
def test_totalDescendingBranchLength(self):
"""totalDescendingBranchLength returns total branchlength below self"""
t = self.TreeRoot
exp = 15
obs = t.totalDescendingBranchLength()
self.assertEqual(obs, exp)
node_c = self.TreeNode['c']
exp = 10
obs = node_c.totalDescendingBranchLength()
self.assertEqual(obs, exp)
def test_tipsWithinDistance(self):
"""tipsWithinDistance returns tips that are within distance from self"""
t_str = "(A:1,B:2,(C:3,D:3)E:2,(F,((G:1,H:2)I:2)J:3)K:2)L;"
t = DndParser(t_str, constructor=PhyloNode)
nodes = t.getNodesDict()
e_node = nodes['E']
exp_at_dist_2 = []
exp_at_dist_3 = ['A','C','D']
exp_at_dist_4 = ['A','B','C','D','F']
obs_at_dist_2 = sorted([n.Name for n in e_node.tipsWithinDistance(2)])
obs_at_dist_3 = sorted([n.Name for n in e_node.tipsWithinDistance(3)])
obs_at_dist_4 = sorted([n.Name for n in e_node.tipsWithinDistance(4)])
self.assertEqual(obs_at_dist_2, exp_at_dist_2)
self.assertEqual(obs_at_dist_3, exp_at_dist_3)
self.assertEqual(obs_at_dist_4, exp_at_dist_4)
def test_tipsWithinDistance_nodistances(self):
"""tipsWithinDistance returns tips that are within distance from self"""
t_str = "(A,B,(C,D)E,(F,((G,H)I)J)K)L;"
t = DndParser(t_str, constructor=PhyloNode)
nodes = t.getNodesDict()
e_node = nodes['E']
exp = sorted([n.Name for n in t.tips()])
obs = sorted([n.Name for n in e_node.tipsWithinDistance(0)])
self.assertEqual(obs, exp)
def test_distance(self):
"""PhyloNode Distance should report correct distance between nodes"""
nodes, tree = self.TreeNode, self.TreeRoot
a = nodes['a']
b = nodes['b']
c = nodes['c']
d = nodes['d']
e = nodes['e']
f = nodes['f']
g = nodes['g']
h = nodes['h']
self.assertEqual(a.distance(a), 0)
self.assertEqual(a.distance(b), 0)
self.assertEqual(a.distance(c), 3)
self.assertEqual(a.distance(d), 4)
self.assertEqual(a.distance(e), 7)
self.assertEqual(a.distance(f), 5)
self.assertEqual(a.distance(g), 8)
self.assertEqual(a.distance(h), 2)
self.assertEqual(b.distance(a), 0)
self.assertEqual(b.distance(b), 0)
self.assertEqual(b.distance(c), 3)
self.assertEqual(b.distance(d), 4)
self.assertEqual(b.distance(e), 7)
self.assertEqual(b.distance(f), 5)
self.assertEqual(b.distance(g), 8)
self.assertEqual(b.distance(h), 2)
self.assertEqual(c.distance(a), 3)
self.assertEqual(c.distance(b), 3)
self.assertEqual(c.distance(c), 0)
self.assertEqual(c.distance(d), 1)
self.assertEqual(c.distance(e), 4)
self.assertEqual(c.distance(f), 2)
self.assertEqual(c.distance(g), 5)
self.assertEqual(c.distance(h), 5)
self.assertEqual(d.distance(a), 4)
self.assertEqual(d.distance(b), 4)
self.assertEqual(d.distance(c), 1)
self.assertEqual(d.distance(d), 0)
self.assertEqual(d.distance(e), 5)
self.assertEqual(d.distance(f), 3)
self.assertEqual(d.distance(g), 6)
self.assertEqual(d.distance(h), 6)
self.assertEqual(e.distance(a), 7)
self.assertEqual(e.distance(b), 7)
self.assertEqual(e.distance(c), 4)
self.assertEqual(e.distance(d), 5)
self.assertEqual(e.distance(e), 0)
self.assertEqual(e.distance(f), 6)
self.assertEqual(e.distance(g), 9)
self.assertEqual(e.distance(h), 9)
self.assertEqual(f.distance(a), 5)
self.assertEqual(f.distance(b), 5)
self.assertEqual(f.distance(c), 2)
self.assertEqual(f.distance(d), 3)
self.assertEqual(f.distance(e), 6)
self.assertEqual(f.distance(f), 0)
self.assertEqual(f.distance(g), 3)
self.assertEqual(f.distance(h), 7)
self.assertEqual(g.distance(a), 8)
self.assertEqual(g.distance(b), 8)
self.assertEqual(g.distance(c), 5)
self.assertEqual(g.distance(d), 6)
self.assertEqual(g.distance(e), 9)
self.assertEqual(g.distance(f), 3)
self.assertEqual(g.distance(g), 0)
self.assertEqual(g.distance(h), 10)
self.assertEqual(h.distance(a), 2)
self.assertEqual(h.distance(b), 2)
self.assertEqual(h.distance(c), 5)
self.assertEqual(h.distance(d), 6)
self.assertEqual(h.distance(e), 9)
self.assertEqual(h.distance(f), 7)
self.assertEqual(h.distance(g), 10)
self.assertEqual(h.distance(h), 0)
def test_compareByTipDistances(self):
obs = self.t.compareByTipDistances(self.t3)
#note: common taxa are H, G, R (only)
m1 = array([[0,2,6.5],[2,0,6.5],[6.5,6.5,0]])
m2 = array([[0,2,6],[2,0,6],[6,6,0]])
r = correlation(m1.flat, m2.flat)[0]
self.assertEqual(obs, (1-r)/2)
def test_compareByTipDistances_sample(self):
obs = self.t.compareByTipDistances(self.t3, sample=3, shuffle_f=sorted)
#note: common taxa are H, G, R (only)
m1 = array([[0,2,6.5],[2,0,6.5],[6.5,6.5,0]])
m2 = array([[0,2,6],[2,0,6],[6,6,0]])
r = correlation(m1.flat, m2.flat)[0]
self.assertEqual(obs, (1-r)/2)
# 4 common taxa, still picking H, G, R
s = '((H:1,G:1):2,(R:0.5,M:0.7,Q:5):3);'
t = DndParser(self.s,PhyloNode)
s3 = '(((H:1,G:1,O:1):2,R:3,Q:10):1,X:4);'
t3 = DndParser(self.s3, PhyloNode)
obs = t.compareByTipDistances(t3, sample=3, shuffle_f=sorted)
def test_tipToTipDistances_endpoints(self):
"""Test getting specifc tip distances with tipToTipDistances"""
nodes = [self.t.getNodeMatchingName('H'),
self.t.getNodeMatchingName('G'),
self.t.getNodeMatchingName('M')]
names = ['H','G','M']
exp = (array([[0,2.0,6.7],[2.0,0,6.7],[6.7,6.7,0.0]]), nodes)
obs = self.t.tipToTipDistances(endpoints=names)
self.assertEqual(obs, exp)
obs = self.t.tipToTipDistances(endpoints=nodes)
self.assertEqual(obs, exp)
def test_prune(self):
"""prune should reconstruct correct topology and Lengths of tree."""
tree = DndParser('((a:3,((c:1):1):1):2);',constructor=PhyloNode)
tree.prune()
result_tree = DndParser('((a:3.0,c:3.0):2.0);',constructor=PhyloNode)
self.assertEqual(str(tree),str(result_tree))
def test_str(self):
"""PhyloNode str should give expected results"""
nodes, tree = self.TreeNode, self.TreeRoot
a = nodes['a']
b = nodes['b']
c = nodes['c']
d = nodes['d']
e = nodes['e']
f = nodes['f']
g = nodes['g']
h = nodes['h']
self.assertEqual(str(h), 'h:2;')
self.assertEqual(str(f), '(g:3)f:2;')
self.assertEqual(str(a), '(((d:1,e:4,(g:3)f:2)c:3)b:0,h:2)a;')
#check that None isn't converted any more
h.Length = None
c.Length = None #need to test both leaf and internal node
self.assertEqual(str(a), '(((d:1,e:4,(g:3)f:2)c)b:0,h)a;')
def test_getMaxTipTipDistance(self):
"""getMaxTipTipDistance should get max tip distance across tree"""
nodes, tree = self.TreeNode, self.TreeRoot
dist, names, node = tree.getMaxTipTipDistance()
self.assertEqual(dist, 15.0) # due to nodes with single descendents!!
self.assertEqual(sorted(names), ['e','g'])
self.assertEqual(node.Name, 'b')
def test_setMaxTipTipDistance(self):
"""setMaxTipTipDistance sets MaxDistTips across tree"""
nodes, tree = self.TreeNode, self.TreeRoot
tree.setMaxTipTipDistance()
tip_a, tip_b = tree.MaxDistTips
self.assertEqual(tip_a[0] + tip_b[0], 10)
self.assertEqual(sorted([tip_a[1],tip_b[1]]), ['g','h'])
def test_maxTipTipDistance(self):
"""maxTipTipDistance returns the max dist between any pair of tips"""
nodes, tree = self.TreeNode, self.TreeRoot
max_dist, tip_pair = tree.maxTipTipDistance()
self.assertEqual(max_dist, 10)
try:
self.assertEqual(tip_pair, ('h', 'g'))
except AssertionError:
self.assertEqual(tip_pair, ('g', 'h'))
def test__find_midpoint_nodes(self):
"""_find_midpoint_nodes should return nodes surrounding the midpoint"""
nodes, tree = self.TreeNode, self.TreeRoot
max_dist = 10
tip_pair = ('g', 'h')
result = tree._find_midpoint_nodes(max_dist, tip_pair)
self.assertEqual(result, (nodes['b'], nodes['c']))
tip_pair = ('h', 'g')
result = tree._find_midpoint_nodes(max_dist, tip_pair)
self.assertEqual(result, (nodes['f'], nodes['c']))
def test_rootAtMidpoint(self):
"""rootAtMidpoint performs midpoint rooting"""
nodes, tree = self.TreeNode, self.TreeRoot
#works when the midpoint falls on an existing edge
tree1 = deepcopy(tree)
result = tree1.rootAtMidpoint()
self.assertEqual(result.distance(result.getNodeMatchingName('e')), 4)
self.assertEqual(result.getDistances(), tree1.getDistances())
#works when the midpoint falls between two existing edges
nodes['f'].Length = 1
nodes['c'].Length = 4
result = tree.rootAtMidpoint()
self.assertEqual(result.distance(result.getNodeMatchingName('e')), 5.0)
self.assertEqual(result.distance(result.getNodeMatchingName('g')), 5.0)
self.assertEqual(result.distance(result.getNodeMatchingName('h')), 5.0)
self.assertEqual(result.distance(result.getNodeMatchingName('d')), 2.0)
self.assertEqual(result.getDistances(), tree.getDistances())
def test_rootAtMidpoint2(self):
"""rootAtMidpoint works when midpoint is on both sides of root"""
#also checks whether it works if the midpoint is adjacent to a tip
nodes, tree = self.TreeNode, self.TreeRoot
nodes['h'].Length = 20
result = tree.rootAtMidpoint()
self.assertEqual(result.distance(result.getNodeMatchingName('h')), 14)
self.assertEqual(result.getDistances(), tree.getDistances())
def test_rootAtMidpoint3(self):
""" midpoint between nodes should behave correctly"""
tree = DndParser('(a:1,((c:1,d:2.5)n3:1,b:1)n2:1)rt;')
tmid = tree.rootAtMidpoint()
self.assertEqual(tmid.getDistances(),tree.getDistances())
tipnames = tree.getTipNames()
nontipnames = [t.Name for t in tree.nontips()]
self.assertTrue(tmid.isRoot())
self.assertEqual(tmid.distance(tmid.getNodeMatchingName('d')), 2.75)
def test_rootAtMidpoint4(self):
"""midpoint should be selected correctly when it is an internal node
"""
tree = DndParser('(a:1,((c:1,d:3)n3:1,b:1)n2:1)rt;')
tmid = tree.rootAtMidpoint()
self.assertEqual(tmid.getDistances(),tree.getDistances())
tipnames = tree.getTipNames()
nontipnames = [t.Name for t in tree.nontips()]
# for tipname in tipnames:
# tmid_tip = tmid.getNodeMatchingName(tipname)
# orig_tip = tree.getNodeMatchingName(tipname)
# for nontipname in nontipnames:
# tmid_dist=\
# tmid.getNodeMatchingName(nontipname).distance(tmid_tip)
# orig_dist=\
# tree.getNodeMatchingName(nontipname).distance(orig_tip)
# print nontipname, tipname, 'assert'
# self.assertEqual(tmid_dist, orig_dist)
self.assertTrue(tmid.isRoot())
self.assertEqual(tmid.distance(\
tmid.getNodeMatchingName('d')), 3)
def test_rootAtMidpoint5(self):
"""midpoint should be selected correctly when on an even 2tip tree
"""
tree = DndParser('''(BLO_1:0.649351,BLO_2:0.649351):0.0;''')
tmid = tree.rootAtMidpoint()
self.assertEqual(tmid.getDistances(),tree.getDistances())
tipnames = tree.getTipNames()
nontipnames = [t.Name for t in tree.nontips()]
self.assertTrue(tmid.isRoot())
self.assertFloatEqual(tmid.distance(\
tmid.getNodeMatchingName('BLO_2')), 0.649351)
self.assertFloatEqual(tmid.distance(\
tmid.getNodeMatchingName('BLO_1')), 0.649351)
self.assertFloatEqual(tmid[0].distance(tmid[1]), 2.0* 0.649351)
def test_setTipDistances(self):
"""setTipDistances should correctly set tip distances."""
tree = DndParser('(((A1:.1,B1:.1):.1,(A2:.1,B2:.1):.1):.3,((A3:.1,B3:.1):.1,(A4:.1,B4:.1):.1):.3);',constructor=PhyloNode)
#expected distances for a post order traversal
expected_tip_distances = [0,0,0.1,0,0,0.1,0.2,0,0,0.1,0,0,0.1,0.2,0.5]
#tips should have distance of 0
tree.setTipDistances()
for node in tree.tips():
self.assertEqual(node.TipDistance,0)
idx = 0
for node in tree.traverse(self_before=False,self_after=True):
self.assertEqual(node.TipDistance,expected_tip_distances[idx])
idx+=1
def test_scaleBranchLengths(self):
"""scaleBranchLengths should correclty scale branch lengths."""
tree = DndParser('(((A1:.1,B1:.1):.1,(A2:.1,B2:.1):.1):.3,((A3:.1,B3:.1):.1,(A4:.1,B4:.1):.1):.3);',constructor=PhyloNode)
tree.scaleBranchLengths(max_length=100,ultrametric=True)
expected_tree = '(((A1:20,B1:20):20,(A2:20,B2:20):20):60,((A3:20,B3:20):20,(A4:20,B4:20):20):60);'
self.assertEqual(str(tree),expected_tree)
def test_unrooted(self):
"""unrooted should preserve tips, drop a node"""
rooted = LoadTree(treestring="(B:0.2,(C:0.2,D:0.2)F:0.2)G;")
unrooted = rooted.unrooted()
self.assertEqual(sorted(rooted.getTipNames()),
sorted(unrooted.getTipNames()))
self.assertLessThan(len(unrooted.getNodeNames()),
len(rooted.getNodeNames()))
class Test_tip_tip_distances_I(object):
"""Abstract class for testing different implementations of tip_to_tip."""
def setUp(self):
"""Define a few standard trees"""
constructor = PhyloNode
self.root_std = DndParser(tree_std, constructor)
self.root_one_level = DndParser(tree_one_level, constructor)
self.root_two_level = DndParser(tree_two_level, constructor)
self.root_one_child = DndParser(tree_one_child, constructor)
def test_one_level(self):
"""tip_to_tip should work for one-level multifurcating tree"""
matrix, order = self.fun(self.root_one_level)
self.assertEqual([i.Name for i in order], list('abc'))
self.assertEqual(matrix, array([[0,3,4],[3,0,5],[4,5,0]]))
def test_two_level(self):
"""tip_to_tip should work for two-level tree"""
matrix, order = self.fun(self.root_two_level)
self.assertEqual([i.Name for i in order], list('abcd'))
self.assertFloatEqual(matrix, \
array([[0,3,4,1.4],[3,0,5,2.4],[4,5,0,3.4],[1.4,2.4,3.4,0]]))
class Test_tip_tip_distances_array(Test_tip_tip_distances_I, TestCase):
"""Tests for the array implementation of tip_to_tip distances"""
def setUp(self):
"""Specify which method to call."""
self.fun = lambda x: x.tipToTipDistances()
super(Test_tip_tip_distances_array, self).setUp()
def test_std(self):
"""tip_to_tip should work for small but complex tree"""
dist, tips = self.fun(self.root_std)
tips = [tip.Name for tip in tips]
self.assertEqual(dist, tree_std_dist)
self.assertEqual(tips, tree_std_tips)
def test_one_child(self):
"""tip_to_tip should work for tree with a single child"""
dist, tips = self.fun(self.root_one_child)
tips = [tip.Name for tip in tips]
self.assertEqual(dist, tree_one_child_dist)
self.assertEqual(tips, tree_one_child_tips)
# for use with testing iterative copy method
def comb_tree(num_leaves):
"""Returns a comb node_class tree."""
branch_child = 1
root = TreeNode()
curr = root
for i in range(num_leaves-1):
curr.Children[:] = [TreeNode(Parent=curr),TreeNode(Parent=curr)]
curr = curr.Children[branch_child]
return root
# Moved from test_tree2.py during code sprint on 04/14/10
# Missing tests: edge attributes (Name, Length, Children) only get tested
# in passing by some of these tests. See also xxx's
class TreeInterfaceForLikelihoodFunction(TestCase):
default_newick = "((A:1,B:2)ab:3,((C:4,D:5)cd,E:6)cde:7)"
def _maketree(self, treestring=None):
if treestring is None:
treestring = self.default_newick
return LoadTree(treestring=treestring, underscore_unmunge=True)
def setUp(self):
self.default_tree = self._maketree()
def test_getEdgeNames(self):
tree = self._maketree()
for (a, b, outgroup, result) in [
('A', 'B', None, ['A', 'B']),
('E', 'C', None, ['C', 'D', 'cd', 'E']),
('C', 'D', 'E', ['C', 'D'])]:
self.assertEqual(tree.getEdgeNames(
a, b, True, False, outgroup), result)
def test_parser(self):
"""nasty newick"""
nasty = "( (A :1.0,'B (b)': 2) [com\nment]pair:3,'longer name''s':4)dash_ed;"
nice = "((A:1.0,'B (b)':2.0)pair:3.0,'longer name''s':4.0)dash_ed;"
tree = self._maketree(nasty)
tidied = tree.getNewick(with_distances=1)
self.assertEqual(tidied, nice)
# Likelihood Function Interface
def test_getEdgeNames(self):
tree = self.default_tree
clade = tree.getEdgeNames('C', 'E', getstem=0, getclade=1)
clade.sort()
self.assertEqual(clade, ['C', 'D', 'E', 'cd'])
all = tree.getEdgeNames('C', 'E', getstem=1, getclade=1)
all.sort()
self.assertEqual(all, ['C', 'D', 'E', 'cd', 'cde'])
stem = tree.getEdgeNames('C', 'E', getstem=1, getclade=0)
self.assertEqual(stem, ['cde'])
def test_getEdgeNamesUseOutgroup(self):
t1 = LoadTree(treestring="((A,B)ab,(F,(C,D)cd)cdf,E)root;")
# a, e, ogroup f
t2 = LoadTree(treestring="((E,(A,B)ab)abe,F,(C,D)cd)root;")
expected = ['A', 'B', 'E', 'ab']
for t in [t1, t2]:
edges = t.getEdgeNames('A', 'E', getstem = False, getclade = True,
outgroup_name = "F")
edges.sort()
self.assertEqual(expected, edges)
def test_getConnectingNode(self):
tree = self.default_tree
self.assertEqual(tree.getConnectingNode('A', 'B').Name, 'ab')
self.assertEqual(tree.getConnectingNode('A', 'C').Name, 'root')
def test_getNodeMatchingName(self):
tree = self.default_tree
for (name, expect_tip) in [('A', True), ('ab', False)]:
edge = tree.getNodeMatchingName(name)
self.assertEqual(edge.Name, name)
self.assertEqual(edge.istip(), expect_tip)
def test_getEdgeVector(self):
tree = self.default_tree
names = [e.Name for e in tree.getEdgeVector()]
self.assertEqual(names,
['A', 'B', 'ab', 'C', 'D', 'cd', 'E', 'cde', 'root'])
def test_getNewickRecursive(self):
orig = "((A:1.0,B:2.0)ab:3.0,((C:4.0,D:5.0)cd:6.0,E:7.0)cde:8.0)all;"
unlen = "((A,B)ab,((C,D)cd,E)cde)all;"
tree = self._maketree(orig)
self.assertEqual(tree.getNewickRecursive(with_distances=1), orig)
self.assertEqual(tree.getNewickRecursive(), unlen)
tree.Name = "a'l"
ugly_name = "((A,B)ab,((C,D)cd,E)cde)a'l;"
ugly_name_esc = "((A,B)ab,((C,D)cd,E)cde)'a''l';"
self.assertEqual(tree.getNewickRecursive(escape_name=True), \
ugly_name_esc)
self.assertEqual(tree.getNewickRecursive(escape_name=False), ugly_name)
tree.Name = "a_l"
ugly_name = "((A,B)ab,((C,D)cd,E)cde)a_l;"
ugly_name_esc = "((A,B)ab,((C,D)cd,E)cde)'a_l';"
self.assertEqual(tree.getNewickRecursive(escape_name=True), \
ugly_name_esc)
self.assertEqual(tree.getNewickRecursive(escape_name=False), ugly_name)
tree.Name = "a l"
ugly_name = "((A,B)ab,((C,D)cd,E)cde)a l;"
ugly_name_esc = "((A,B)ab,((C,D)cd,E)cde)a_l;"
self.assertEqual(tree.getNewickRecursive(escape_name=True), \
ugly_name_esc)
self.assertEqual(tree.getNewickRecursive(escape_name=False), ugly_name)
tree.Name = "'a l'"
quoted_name = "((A,B)ab,((C,D)cd,E)cde)'a l';"
quoted_name_esc = "((A,B)ab,((C,D)cd,E)cde)'a l';"
self.assertEqual(tree.getNewickRecursive(escape_name=True), \
quoted_name_esc)
self.assertEqual(tree.getNewickRecursive(escape_name=False),quoted_name)
def test_getNewick(self):
orig = "((A:1.0,B:2.0)ab:3.0,((C:4.0,D:5.0)cd:6.0,E:7.0)cde:8.0)all;"
unlen = "((A,B)ab,((C,D)cd,E)cde)all;"
tree = self._maketree(orig)
self.assertEqual(tree.getNewick(with_distances=1), orig)
self.assertEqual(tree.getNewick(), unlen)
tree.Name = "a'l"
ugly_name = "((A,B)ab,((C,D)cd,E)cde)a'l;"
ugly_name_esc = "((A,B)ab,((C,D)cd,E)cde)'a''l';"
self.assertEqual(tree.getNewick(escape_name=True), ugly_name_esc)
self.assertEqual(tree.getNewick(escape_name=False), ugly_name)
tree.Name = "a_l"
ugly_name = "((A,B)ab,((C,D)cd,E)cde)a_l;"
ugly_name_esc = "((A,B)ab,((C,D)cd,E)cde)'a_l';"
self.assertEqual(tree.getNewickRecursive(escape_name=True), \
ugly_name_esc)
self.assertEqual(tree.getNewickRecursive(escape_name=False), ugly_name)
tree.Name = "a l"
ugly_name = "((A,B)ab,((C,D)cd,E)cde)a l;"
ugly_name_esc = "((A,B)ab,((C,D)cd,E)cde)a_l;"
self.assertEqual(tree.getNewickRecursive(escape_name=True), \
ugly_name_esc)
self.assertEqual(tree.getNewickRecursive(escape_name=False), ugly_name)
tree.Name = "'a l'"
quoted_name = "((A,B)ab,((C,D)cd,E)cde)'a l';"
quoted_name_esc = "((A,B)ab,((C,D)cd,E)cde)'a l';"
self.assertEqual(tree.getNewick(escape_name=True), \
quoted_name_esc)
self.assertEqual(tree.getNewick(escape_name=False),quoted_name)
def test_XML(self):
# should add some non-length parameters
orig = self.default_tree
xml = orig.getXML()
parsed = LoadTree(treestring=xml)
self.assertEqual(str(orig), str(parsed))
# Magic methods
def test_str(self):
"""testing (well, exercising at least), __str__"""
str(self.default_tree)
def test_repr(self):
"""testing (well, exercising at least), __repr__"""
repr(self.default_tree)
def test_eq(self):
"""testing (well, exercising at least), __eq__"""
# xxx not good enough!
t1 = self._maketree()
t2 = self._maketree()
self.assertTrue(t1 == t1)
self.assertFalse(t1 == t2)
def test_balanced(self):
"""balancing an unrooted tree"""
t = LoadTree(treestring='((a,b),((c1,(c2,(c3,(c4,(c5,(c6,c7)))))),(d,e)),f)')
b = LoadTree(treestring='(c1,(c2,(c3,(c4,(c5,(c6,c7))))),((d,e),((a,b),f)))')
self.assertEqual(str(t.balanced()), str(b))
def test_params_merge(self):
t = LoadTree(treestring='((((a,b)ab,c)abc),d)')
for (label, length, beta) in [('a',1, 20),('b',3,2.0),('ab',4,5.0),]:
t.getNodeMatchingName(label).params = {'length':length, 'beta':beta}
t = t.getSubTree(['b', 'c', 'd'])
self.assertEqual(t.getNodeMatchingName('b').params,
{'length':7, 'beta':float(2*3+4*5)/(3+4)})
self.assertRaises(ValueError, t.getSubTree, ['b','c','xxx'])
self.assertEqual(str(t.getSubTree(['b','c','xxx'],ignore_missing=True)),
'(b:7,c)root;')
def test_making_from_list(self):
tipnames_with_spaces = ['a_b','a b',"T'lk"]
tipnames_with_spaces.sort()
t = LoadTree(tip_names=tipnames_with_spaces)
result = t.getTipNames()
result.sort()
assert result == tipnames_with_spaces
def test_getsetParamValue(self):
"""test getting, setting of param values"""
t = LoadTree(treestring='((((a:.2,b:.3)ab:.1,c:.3)abc:.4),d:.6)')
self.assertEqual(t.getParamValue('length', 'ab'), 0.1, 2)
t.setParamValue('zz', 'ab', 4.321)
node = t.getNodeMatchingName('ab')
self.assertEqual(4.321, node.params['zz'], 4)
class SmallTreeReshapeTestClass(TestCase):
def test_rootswaps(self):
"""testing (well, exercising at least), unrooted"""
new_tree = LoadTree(treestring="((a,b),(c,d))")
new_tree = new_tree.unrooted()
self.assert_(len(new_tree.Children) > 2, 'not unrooted right')
def test_reroot(self):
tree = LoadTree(treestring="((a,b),(c,d),e)")
tree2 = tree.rootedWithTip('b')
self.assertEqual(tree2.getNewick(), "(a,b,((c,d),e));")
def test_sameShape(self):
"""test topology assessment"""
t1 = LoadTree(treestring="(((s1,s5),s3),s2,s4);")
t2 = LoadTree(treestring="((s1,s5),(s2,s4),s3);")
t3 = LoadTree(treestring="((s1,s4),(s2,s5),s3);")
assert t1.sameTopology(t2), (t1, t2)
assert not t1.sameTopology(t3), (t1, t3)
assert not t2.sameTopology(t3), (t2, t3)
#=============================================================================
# these are tests involving tree manipulation methods
# hence, testing them for small and big trees
# the tests are written once for the small tree, the big tree
# tests are performed by inheriting from this class, but over-riding
# the setUp.
class TestTree(TestCase):
"""tests for a single tree-type"""
def setUp(self):
self.name = 'small tree - '
self.otu_names = ['NineBande', 'Mouse', 'HowlerMon', 'DogFaced']
self.otu_names.sort()
self.newick = '(((Human,HowlerMon),Mouse),NineBande,DogFaced);'
self.newick_sorted = '(DogFaced,((HowlerMon,Human),Mouse),NineBande);'
self.newick_reduced = '((HowlerMon,Mouse),NineBande,DogFaced);'
self.tree = LoadTree(treestring = self.newick)
def test_sorttree(self):
"""testing (well, exercising at least) treesort"""
new_tree = self.tree.sorted()
if hasattr(self, 'newick_sorted'):
self.assertEqual(
self.newick_sorted,
new_tree.getNewick(with_distances=0))
def test_getsubtree(self):
"""testing getting a subtree"""
subtree = self.tree.unrooted().getSubTree(self.otu_names)
new_tree = LoadTree(treestring = self.newick_reduced).unrooted()
# check we get the same names
self.assertEqual(*[len(t.Children) for t in (subtree,new_tree)])
self.assertEqual(str(subtree), str(new_tree))
def test_getsubtree_2(self):
"""tree.getSubTree() has same pairwise tip dists as tree (len0 node)
"""
t1 = DndParser('((a:1,b:2):4,((c:3, j:17.2):0,(d:1,e:1):2):3)', \
PhyloNode) # note c,j is len 0 node
orig_dists = t1.getDistances()
subtree = t1.getSubTree(set(['a','b','d','e','c']))
sub_dists = subtree.getDistances()
for pair, dist in sub_dists.items():
self.assertEqual((pair,dist), (pair,orig_dists[pair]))
def test_getsubtree_3(self):
"""tree.getSubTree() has same pairwise tip dists as tree
(nonzero nodes)
"""
t1 = DndParser('((a:1,b:2):4,((c:3, j:17):0,(d:1,e:1):2):3)', \
PhyloNode) # note c,j is len 0 node
orig_dists = t1.getDistances()
subtree = t1.getSubTree(set(['a','b','d','e','c']))
sub_dists = subtree.getDistances()
# for pair, dist in sub_dists.items():
# self.assertEqual((pair,dist), (pair,orig_dists[pair]))
t2 = DndParser('((a:1,b:2):4,((c:2, j:16):1,(d:1,e:1):2):3)', \
PhyloNode) # note c,j similar to above
t2_dists = t2.getDistances()
# ensure t2 is same as t1, except j->c or c->j
for pair, dist in t2_dists.items():
if (pair == ('c','j')) or (pair == ('j','c')):
continue
self.assertEqual((pair,dist), (pair,orig_dists[pair]))
sub2 = t2.getSubTree(set(['a','b','d','e','c']))
sub2_dists = sub2.getDistances()
for pair, dist in sub2_dists.items():
self.assertEqual((pair,dist), (pair,orig_dists[pair]))
def test_getsubtree_4(self):
"""tree.getSubTree() handles keep_root correctly
"""
t1 = DndParser('((a:1,b:2):4,(((c:2)cparent:1, j:17):0,(d:1,e:4):2):3)')
# /----4--- /--1-a
# ---------| \--2-b
# | /----0--- /-1---cparent---2---c
# \---3----| \--17-j
# \----2--- /--1--d
# \--4--e
# note c,j is len 0 node
true_dists = {('a', 'b'): 3.0,
('a', 'c'): 11.0,
('a', 'd'): 11.0,
('a', 'e'): 14.0,
('a', 'j'): 25.0,
('b', 'a'): 3.0,
('b', 'c'): 12.0,
('b', 'd'): 12.0,
('b', 'e'): 15.0,
('b', 'j'): 26.0,
('c', 'a'): 11.0,
('c', 'b'): 12.0,
('c', 'd'): 6.0,
('c', 'e'): 9.0,
('c', 'j'): 20.0,
('d', 'a'): 11.0,
('d', 'b'): 12.0,
('d', 'c'): 6.0,
('d', 'e'): 5.0,
('d', 'j'): 20.0,
('e', 'a'): 14.0,
('e', 'b'): 15.0,
('e', 'c'): 9.0,
('e', 'd'): 5.0,
('e', 'j'): 23.0,
('j', 'a'): 25.0,
('j', 'b'): 26.0,
('j', 'c'): 20.0,
('j', 'd'): 20.0,
('j', 'e'): 23.0}
true_root_dists = {'a':5,'b':6,'c':6,'j':20,'d':6,'e':9}
t1_dists = t1.getDistances() #
subtree = t1.getSubTree(set(['d','e','c']))
sub_dists = subtree.getDistances()
true_sub_root_dists = {'c':3,'d':3,'e':6}
sub_sameroot = t1.getSubTree(set(['d','e','c']), keep_root=True)
sub_sameroot_dists = sub_sameroot.getDistances()
sub_sameroot2 = t1.getSubTree(set(['j','c']), keep_root=True)
sub_sameroot_dists2 = sub_sameroot2.getDistances()
# tip to tip dists should be the same
for tip_pair in sub_dists.keys():
self.assertEqual(sub_dists[tip_pair],true_dists[tip_pair])
for tip_pair in t1_dists.keys():
self.assertEqual(t1_dists[tip_pair],true_dists[tip_pair])
for tip_pair in sub_sameroot_dists.keys():
self.assertEqual(sub_sameroot_dists[tip_pair],
true_dists[tip_pair])
for tip_pair in sub_sameroot_dists2.keys():
self.assertEqual(sub_sameroot_dists2[tip_pair],
true_dists[tip_pair])
# sameroot should have longer root to tip dists
for tip in t1.tips():
self.assertFloatEqual(t1.distance(tip),
true_root_dists[tip.Name])
for tip in subtree.tips():
self.assertFloatEqual(subtree.distance(tip),
true_sub_root_dists[tip.Name])
for tip in sub_sameroot.tips():
self.assertFloatEqual(sub_sameroot.distance(tip),
true_root_dists[tip.Name])
for tip in sub_sameroot2.tips():
self.assertFloatEqual(sub_sameroot2.distance(tip),
true_root_dists[tip.Name])
def test_ascii(self):
self.tree.asciiArt()
# unlabeled internal node
tr = DndParser("(B:0.2,(C:0.3,D:0.4):0.6)F;")
obs = tr.asciiArt(show_internal=True, compact=False)
exp = """ /-B\n-F-------|\n | /-C\n \\--------|\n \\-D"""
self.assertEqual(obs, exp)
obs = tr.asciiArt(show_internal=True, compact=True)
exp = """-F------- /-B\n \-------- /-C\n \-D"""
self.assertEqual(obs, exp)
obs = tr.asciiArt(show_internal=False, compact=False)
exp = """ /-B\n---------|\n | /-C\n \\--------|\n \\-D"""
self.assertEqual(obs, exp)
# the following class repeats the above tests but using a big tree and big data-set
class BigTreeSingleTests(TestTree):
"""using the big-tree for single-tree tests"""
def setUp(self):
self.name = 'big tree - '
self.otu_names = ['Horse', 'TombBat', 'Rhino', 'Pig', 'AsianElep',
'SpermWhal', 'Cat', 'Gorilla', 'Orangutan',
'bandicoot', 'Hedgehog', 'Sloth', 'HairyArma',
'Manatee', 'GoldenMol', 'Pangolin']
self.otu_names.sort()
self.newick = '((((((((FlyingFox,DogFaced),((FreeTaile,LittleBro),(TombBat,RoundEare))),(FalseVamp,LeafNose)),(((Horse,Rhino),(Pangolin,(Cat,Dog))),(Llama,(Pig,(Cow,(Hippo,(SpermWhal,HumpbackW))))))),(Mole,Hedgehog)),(TreeShrew,(FlyingLem,((Jackrabbit,(FlyingSqu,(OldWorld,(Mouse,Rat)))),(Galago,(HowlerMon,(Rhesus,(Orangutan,(Gorilla,(Human,Chimpanzee)))))))))),(((NineBande,HairyArma),(Anteater,Sloth)),(((Dugong,Manatee),((AfricanEl,AsianElep),(RockHyrax,TreeHyrax))),(Aardvark,((GoldenMol,(Madagascar,Tenrec)),(LesserEle,GiantElep)))))),(caenolest,(phascogale,(wombat,bandicoot))));'
self.newick_reduced = '(((((TombBat,(((Horse,Rhino),(Pangolin,Cat)),(Pig,SpermWhal))),Hedgehog),(Orangutan,Gorilla)),((HairyArma,Sloth),((Manatee,AsianElep),GoldenMol))),bandicoot);'
self.tree = LoadTree(treestring = self.newick)
def test_getEdgeNames(self):
"""testing (well, exercising at least), getedgenames"""
# Fell over on small tree because "stem descended from root
# joiner was a tip"
a,b = self.otu_names[:2]
clade = self.tree.getEdgeNames(a, b, True, False)
def test_getTipNames(self):
"""testing (well, exercising at least), getTipNames"""
a,b = self.otu_names[:2]
tips = self.tree.getTipNames()
self.assertEqual(len(tips), 55)
#run if called from command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_core/test_usage.py 000644 000765 000024 00000066017 12024702176 022121 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests of classes dealing with base, codon, amino acid usage.
"""
from __future__ import division
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import FunctionWrapper
from cogent.core.usage import InfoFreqs, AminoAcidUsage, BaseUsage, CodonUsage,\
PositionalBaseUsage, UnsafeBaseUsage, EqualBases, DinucUsage
from cogent.core.genetic_code import GeneticCodes, GeneticCode
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Rob Knight", "Sandra Smit"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class InfoFreqsTests(TestCase):
"""Tests of the InfoFreqs base class"""
class kp_empty(InfoFreqs):
pass
class kp(InfoFreqs):
Mask = FunctionWrapper(int)
RequiredKeys = dict.fromkeys([1,2,3])
class has_info(list):
def __new__(cls, data, *args):
return list.__new__(cls, data)
def __init__(self, data, info):
list.__init__(self, data)
self.Info = info
def test_init_empty(self):
"""InfoFreqs empty init should include only required items"""
self.assertEqual(self.kp_empty(), {})
self.assertEqual(self.kp(), {1:0, 2:0, 3:0})
def test_init_data(self):
"""InfoFreqs init with data should count freqs"""
self.assertEqual(self.kp_empty('1qazaz'), {'1':1,'q':1,'a':2,'z':2})
self.assertEqual(self.kp([1,2,3,1]), {1:2, 2:1, 3:1})
#type of exception on invalid conversion currently not specified
self.assertRaises(Exception, self.kp, '123q')
def test_init_info(self):
"""InfoFreqs init from object with Info should get ref to Info"""
s = self.has_info([1,1,1,2,2,3], {'test':'data'})
obj = self.kp(s)
self.assertEqual(obj, {1:3, 2:2, 3:1})
self.assertEqual(obj.Info, {'test':'data'})
#should use its own info if supplied, though
obj = self.kp(s, {'new':'info'})
self.assertEqual(obj, {1:3, 2:2, 3:1})
self.assertNotEqual(obj.Info, {'test':'data'})
self.assertEqual(obj.Info, {'new':'info'})
def test_info(self):
"""InfoFreqs info changes should work as expected."""
class has_attr(object):
def __init__(self, attr):
self.Attr = attr
s = self.has_info([1,1,1,2,2,3,3], {'test':'data'})
obj = self.kp(s)
self.assertEqual(obj, {1:3, 2:2, 3:2})
self.assertEqual(obj.Info, {'test':'data'})
self.assertRaises(AttributeError, obj.__getattr__, 'Attr')
obj.Info = has_attr('Test')
self.assertEqual(obj.Attr, 'Test')
def test_normalize(self):
"""InfoFreqs normalize should delete non-required keys, if any required"""
e = self.kp_empty('1qaa')
self.assertEqual(e, {'1':1,'q':1,'a':2,})
e.normalize()
#should not delete any keys, since kp_empty has no required keys
self.assertEqual(e, {'1':0.25, 'q':0.25, 'a':0.5})
k = self.kp([1,2,3,1,4,4,4])
self.assertEqual(k, {1:2, 2:1, 3:1, 4:3})
k.normalize()
#should delete 4, since it's not required
self.assertEqual(k, {1:0.5, 2:0.25, 3:0.25})
class BaseUsageTests(TestCase):
"""Tests of the BaseUsage class."""
def test_init_empty(self):
"""BaseUsage should init with empty freqs"""
b = BaseUsage()
self.assertEqual(len(b), 4)
for nt in 'UTACGutacg':
assert nt in b
self.assertEqual(b[nt], 0)
for nt in 'UCAG':
assert nt in b.keys()
items = list(iter(b))
items.sort()
self.assertEqual(items, ['A', 'C', 'G', 'U'])
def test_init_data(self):
"""BaseUsage should init with arbitrary data"""
b = BaseUsage('UUUUUGGGCA')
self.assertEqual(b, {'U':5, 'G':3, 'C':1, 'A':1})
b.normalize()
self.assertEqual(b, {'U':0.5, 'G':0.3, 'C':0.1, 'A':0.1})
def test_setitem(self):
"""BaseUsage should map keys on setitem"""
b = BaseUsage()
b['t'] = 3
b['G'] = 3
b.normalize()
i = b.items()
i.sort()
self.assertEqual(i, [('A',0.0),('C',0.0),('G',0.5),('U',0.5)])
def test_getitem(self):
"""BaseUsage should map key on getitem"""
b = BaseUsage({'a':3, 'T':2, 'X':1})
self.assertEqual(b['X'], 1)
self.assertEqual(b['A'], 3)
self.assertEqual(b['U'], 2)
self.assertEqual(b['a'], 3)
self.assertEqual(b['t'], 2)
b.normalize()
assert 'X' not in b
self.assertFloatEqual(b['A'], 0.6)
self.assertFloatEqual(b['u'], 0.4)
def test_getitem_multi(self):
"""BaseUsage should get total frequency on getitem with 2-letter key"""
b = BaseUsage({'a':3, 'T':2, 'C':5, 'X':1})
self.assertEqual(b['AT'], 0.5)
self.assertEqual(b['AC'], 0.8)
self.assertEqual(b['TC'], 0.7)
self.assertEqual(b['AX'], 0.3)
def test_copy(self):
"""BaseUsage copy should work correctly"""
b = BaseUsage({'a':3, 'T':2, 'C':5, 'X':1})
c = b.copy()
self.assertEqual(c['AT'], 0.5)
def test_bases(self):
"""BaseUsage bases() should return same object"""
b = BaseUsage({'a':3, 'T':2, 'C':5, 'X':1})
c = b.bases()
assert b is c
def test_codons(self):
"""BaseUsage codons should return most likely codon freqs"""
b = BaseUsage({'a':3, 'T':2, 'X':1})
c = b.codons()
known = {
'AAA' : .6 * .6 * .6,
'AAU' : .6 * .6 * .4,
'AUA' : .6 * .4 * .6,
'AUU' : .6 * .4 * .4,
'UAA' : .4 * .6 * .6,
'UAU' : .4 * .6 * .4,
'UUA' : .4 * .4 * .6,
'UUU' : .4 * .4 * .4,
}
for codon in c:
if codon in known:
self.assertFloatEqual(c[codon], known[codon])
else:
self.assertEqual(c[codon], 0)
def test_positionalBases(self):
"""BaseUsage positionalBases should have copy of self at each position"""
b = BaseUsage('A')
p = b.positionalBases()
for i in p:
assert i is not b
self.assertEqual(i, {'A':1,'U':0,'C':0,'G':0})
def test_aminoAcids(self):
"""BaseUsage aminoAcids should give the same results as the codons"""
known_data = {
'AAA' : .6 * .6 * .6,
'AAU' : .6 * .6 * .4,
'AUA' : .6 * .4 * .6,
'AUU' : .6 * .4 * .4,
'UAA' : .4 * .6 * .6,
'UAU' : .4 * .6 * .4,
'UUA' : .4 * .4 * .6,
'UUU' : .4 * .4 * .4,
}
known = CodonUsage(known_data)
b = BaseUsage({'a':3, 'T':2, 'X':1})
self.assertEqual(b.aminoAcids(), known.aminoAcids())
#check that the genetic code is passed through correctly
all_g = GeneticCode('G'*64)
self.assertEqual(b.aminoAcids(all_g), AminoAcidUsage({'G':1}))
def test_normalize(self):
"""BaseUsage normalize should work when empty"""
b = BaseUsage()
b.normalize()
self.assertEqual(b, {'U':0,'C':0,'A':0,'G':0})
b = BaseUsage('AACG')
b.normalize()
self.assertEqual(b, {'U':0, 'C':0.25, 'A':0.5, 'G':0.25})
def test_distance(self):
"""BaseUsage distance() should return dist between two BUs"""
#absolute numbers, will normalize to calculate distance
self.assertFloatEqual(BaseUsage('GC').distance(BaseUsage('AU')),1)
self.assertFloatEqual(BaseUsage('AU').distance(BaseUsage('GC')),1)
self.assertFloatEqual(BaseUsage('GCAU').distance(BaseUsage('AUAU')),.5)
#should work even against dict with 'T's
self.assertFloatEqual(BaseUsage('GCAU').distance(\
BaseUsage({'A':2,'T':2,'C':0,'G':0,})),.5)
#rounding error
self.assertEqual(BaseUsage('ACG').distance(BaseUsage('CCGGAA')),0)
#normalized - as in unit simplex
ag = BaseUsage('AG')
ag.normalize()
uc = BaseUsage('UC')
uc.normalize()
self.assertFloatEqual(ag.distance(uc),1)
self.assertFloatEqual(BaseUsage({'A':0.4,'G':0.1,'C':0.4,'U':0.1})\
.distance(BaseUsage({'A':0.1,'G':0.4,'U':0.4,'C':0.1})),0.6)
self.assertFloatEqual(BaseUsage({'A':0.25,'G':0.25,'C':0.25,'U':0.25})\
.distance(BaseUsage({'A':0.25,'G':0.25,'U':0.25,'C':0.25})),0.0)
self.assertFloatEqual(BaseUsage({'A':0.245,'G':0.255,'C':0.245,\
'U':0.255}).distance(BaseUsage({'A':0.255,'G':0.245,'U':0.245,\
'C':0.255})),0.02)
self.assertFloatEqual(BaseUsage({'A':0.245,'G':0.255,'C':0.245,\
'U':0.255}).distance(BaseUsage({'A':0.25,'G':0.25,'U':0.25,\
'C':0.25})),0.01)
self.assertFloatEqual(BaseUsage({'A':0.248,'G':0.252,'C':0.248,\
'U':0.252}).distance(BaseUsage({'A':0.25,'G':0.25,'U':0.25,\
'C':0.25})),0.004)
def test_content(self):
"""BaseUsage content should return sum of specified bases."""
b = BaseUsage('UUUUUCCCAG')
#should work for combinations
self.assertEqual(b.content('UCAG'), 10)
self.assertEqual(b.content('GC'), 4)
self.assertEqual(b.content('AU'), 6)
#should map T to U
self.assertEqual(b.content('AT'), 6)
#should work for single bases
self.assertEqual(b.content('U'), 5)
#shouldn't complain about invalid bases
self.assertEqual(b.content('X'), 0)
def test_add(self):
"""BaseUsage add should sum two base usages"""
b = BaseUsage('U')
b2 = BaseUsage('C')
self.assertEqual(b+b2, BaseUsage('UC'))
b += b2
self.assertEqual(b, BaseUsage('UC'))
def test_toCartesian(self):
"""BaseUsage toCartesian should return x, y, z from instance"""
b = BaseUsage('ACGU')
self.assertEqual(b.toCartesian(), (0.5,0.5,0.5))
b = BaseUsage('A')
self.assertEqual(b.toCartesian(), (0,0,1))
b = BaseUsage('CGA')
self.assertEqual(b.toCartesian(), (1/3.0,1/3.0,1/3.0))
def test_fromCartesian(self):
"""BaseUsage fromCartesian should init instance from x,y,z"""
b = BaseUsage.fromCartesian(0.5,.5,.5)
self.assertFloatEqual(b['A'], 0.25)
self.assertFloatEqual(b['C'], 0.25)
self.assertFloatEqual(b['G'], 0.25)
self.assertFloatEqual(b['U'], 0.25)
b = BaseUsage.fromCartesian(1/3.0, 1/3.0, 1/3.0)
self.assertEqual(b['U'], 0)
self.assertEqual(b['A'], 1/3.0)
class UnsafeBaseUsageTests(TestCase):
"""Tests of the UnsafeBaseUsage class."""
def test_init(self):
"""UnsafeFreqs uses dict init, so must use += after creation for others"""
self.assertRaises(ValueError, UnsafeBaseUsage, 'acguc')
u = UnsafeBaseUsage()
u += 'acgtc'
#note lack of conversion to uppercase RNA!
self.assertEqual(u, {'a':1,'c':2,'g':1,'t':1})
def test_normalize(self):
"""UnsafeFreqs should normalize based on the uppercase RNA alphabet"""
u = UnsafeBaseUsage()
#note that the lower-case u will be discarded, not converted
u += 'AAACCGGGGGu'
u.normalize()
self.assertFloatEqual(u, {'A':0.3, 'C':0.2, 'G':0.5, 'U':0.0})
class CodonUsageTests(TestCase):
"""Tests of the CodonUsage class."""
def test_init_empty(self):
"""Empty CodonUsage init should have 64 codons, all 0"""
u = CodonUsage()
self.assertEqual(len(u), 64)
for i in u:
self.assertEqual(u[i], 0)
#check that the genetic code is the default
assert u.GeneticCode is GeneticCodes[1]
def test_init_string(self):
"""CodonUsage should count codons in string"""
u = CodonUsage('UUUCCCUUUUUUGA')
self.assertEqual(u, CodonUsage({'UUU':3, 'CCC':1, 'GA':1}))
u.normalize()
self.assertEqual(u, CodonUsage({'UUU':0.75, 'CCC':0.25}))
def test_getitem(self):
"""CodonUsage should allow lookup as RNA or DNA, case-insensitive"""
u = CodonUsage()
rna, dna, lc = 'UCAG', 'TCAG', 'ucag'
for a in [rna, dna, lc]:
codons = [i+j+k for i in a for j in a for k in a]
for c in codons:
self.assertEqual(u[c], 0)
def test_bases(self):
"""CodonUsage bases should count bases correctly"""
u = CodonUsage('UUUCCCUAGCCCGGGAA')
b = u.bases()
self.assertEqual(b, BaseUsage('UUUCCCUAGCCCGGGAA'))
#purge_unwanted should get rid of bad codons
b = u.bases(purge_unwanted=True)
self.assertEqual(b, BaseUsage('UUUCCCCCCGGG'))
def test_codons(self):
"""CodonUsage codons should return same object"""
u = CodonUsage('abc')
c = u.codons()
assert u is c
def test_aminoAcids(self):
"""CodonUsage aminoAcids should correctly count amino acids"""
freqs = {'UUC':5, 'AUA':10, 'AUG':10, 'CGC':3, 'AGG':2, 'XYZ':8,
'UAA':2, 'UGA':1}
u = CodonUsage(freqs, "test")
self.assertEqual(u.Info, 'test')
for key, val in u.items():
if key in freqs:
self.assertEqual(val, freqs[key])
else:
self.assertEqual(val, 0)
aa = u.aminoAcids()
self.assertEqual(aa,
AminoAcidUsage({'F':5,'I':10,'M':10,'R':5,'*':3,'X':8}))
#check that it works with a different genetic code
u.GeneticCode = GeneticCodes['2']
aa = u.aminoAcids()
self.assertEqual(aa,
AminoAcidUsage({'F':5,'I':0,'M':20,'R':3,'*':4,'W':1,'X':8}))
#check that it works if a genetic code is supplied explicitly
u.GeneticCode = GeneticCodes[1]
aa = u.aminoAcids()
self.assertEqual(aa,
AminoAcidUsage({'F':5,'I':10,'M':10,'R':5,'*':3,'X':8}))
aa_2 = u.aminoAcids(2)
self.assertEqual(aa_2,
AminoAcidUsage({'F':5,'I':0,'M':20,'R':3,'*':4,'W':1,'X':8}))
#check that we held onto the info object through the above
self.assertEqual(aa_2.Info, 'test')
def test_positionalBases(self):
"""CodonUsage bases should count bases at each position correctly"""
freqs = {'UUC':5, 'AUA':10, 'AUG':10, 'CGC':3, 'AGG':2, 'XYZ':8,
'UAA':2, 'UGA':1}
u = CodonUsage(freqs)
b = u.positionalBases()
assert isinstance(b, PositionalBaseUsage)
first, second, third = b
self.assertEqual(first, BaseUsage({'U':8,'C':3,'A':22,'X':8}))
self.assertEqual(second, BaseUsage({'U':25,'C':0,'A':2,'G':6,'Y':8}))
self.assertEqual(third, BaseUsage({'C':8,'A':13,'G':12,'Z':8}))
#check that it also works when we purge
p = u.positionalBases(purge_unwanted=True)
first, second, third = p
self.assertEqual(first, BaseUsage({'U':5,'C':3,'A':2}))
self.assertEqual(second, BaseUsage({'U':5,'G':5}))
self.assertEqual(third, BaseUsage({'C':8,'G':2}))
#check that it also works with a different genetic code, and,
#incidentally, that the purging didn't affect the original object
u.GeneticCode = GeneticCodes[2] #mt code: different stop codons
p = u.positionalBases(purge_unwanted=True)
first, second, third = p
self.assertEqual(first, BaseUsage({'U':6,'C':3,'A':20}))
self.assertEqual(second, BaseUsage({'U':25,'G':4}))
self.assertEqual(third, BaseUsage({'C':8,'A':11,'G':10}))
def test_positionalGC(self):
"""CodonUsage positionalGC should give correct GC contents."""
c = EqualBases.codons()
self.assertEqual(c.positionalGC(False), [0.5,0.5,0.5,0.5])
c = EqualBases.codons()
self.assertNotEqual(c.positionalGC(True), [0.5,0.5,0.5,0.5])
def test_fingerprint(self):
"""CodonUsage fingerprint should give correct ratios."""
c = EqualBases.codons()
f = c.fingerprint()
self.assertEqual(len(f), 9)
self.assertEqual(f, \
[[.5,.5,.125] for i in range(8)] + [[.5,.5,1]])
#should be able to omit mean...
f = c.fingerprint(include_mean=False)
self.assertEqual(f, [[.5,.5,.125] for i in range(8)])
#...or use all doublets
f = c.fingerprint(include_mean=False, which_blocks='all')
self.assertEqual(len(f), 16)
#...or do just the non-quartet ones
f = c.fingerprint(include_mean=False, which_blocks='split')
self.assertEqual(len(f), 6)
#check that it doesn't fail on an empty codon usage
c = CodonUsage('')
f = c.fingerprint()
self.assertEqual(f[0], [0.5, 0.5, 0])
def test_pr2bias(self):
"""CodonUsage pr2bias should give correct ratios."""
c = EqualBases.codons()
b = c.pr2bias('UU')
self.assertEqual(len(b), 6)
self.assertEqual(b, tuple([.5]*6))
c = CodonUsage()
c['ACU'] = 10
c['ACC'] = 5
c['ACA'] = 15
c['ACG'] = 20
self.assertEqual(c.pr2bias('AC'), (20/25,15/25,20/35,5/15,20/30,5/20))
def test_add(self):
"""CodonUsage add should sum two base usages"""
c = CodonUsage('UUU')
c2 = CodonUsage('CCC')
self.assertEqual(c+c2, CodonUsage('UUUCCC'))
c += c2
self.assertEqual(c, CodonUsage('UUUCCC'))
def test_rscu(self):
"""CodonUsage rscu should calculate synonymous usage correctly"""
c = CodonUsage({'UUU':3,'UUC':1,'ACA':1})
c.rscu()
self.assertEqual(c['UUU'], 0.75)
self.assertEqual(c['UUC'], 0.25)
self.assertEqual(c['ACA'], 1)
self.assertEqual(c['GGG'], 0)
class PositionalBaseUsageTests(TestCase):
"""Tests of the PositionalBaseUsage class."""
def test_init_empty(self):
"""PositionalBaseUsage init when empty should set all freqs to 0"""
p = PositionalBaseUsage()
assert p[0] is not p[1]
assert p[1] is not p[2]
assert p[0] is not p[2]
for i in p:
self.assertEqual(i, BaseUsage())
def test_info(self):
"""PositionalBaseUsage info should work as expected"""
#test a cycle of setting the Info and setting it back again
p = PositionalBaseUsage()
self.assertRaises(AttributeError, getattr, p, 'upper')
p.Info = 'xyz'
self.assertEqual(p.upper(), 'XYZ')
p.Info = None
self.assertRaises(AttributeError, getattr, p, 'upper')
def test_getitem(self):
"""PositionalBaseUsage getitem should return 1st, 2nd, 3rd in order"""
a, c, g = BaseUsage('A'), BaseUsage('C'), BaseUsage('G')
p = PositionalBaseUsage(a, c, g)
assert p.First is a
assert p.Second is c
assert p.Third is g
#make sure they're not all the same object
assert p.First is not g
#test positive indices
assert p[0] is p.First
assert p[1] is p.Second
assert p[2] is p.Third
#test negative indices
assert p[-1] is p.Third
assert p[-2] is p.Second
assert p[-3] is p.First
try:
x = p[3]
except IndexError:
pass
else:
self.fail("Failed to raise IndexError on bad index")
#test iteration
for o, e in zip(p, [a, c, g]):
assert o is e
def test_normalize(self):
"""PositionalBaseUsage normalize should normalize each position"""
a, c, g = BaseUsage('AAGC'), BaseUsage('CCGA'), BaseUsage('GGCA')
p = PositionalBaseUsage(a, c, g)
self.assertEqual(p[0], {'A':2, 'C':1, 'G':1, 'U':0})
p.normalize()
self.assertEqual(p[0], {'A':0.5, 'C':0.25, 'G':0.25, 'U':0})
self.assertEqual(p[1], {'A':0.25, 'C':0.5, 'G':0.25, 'U':0})
self.assertEqual(p[2], {'A':0.25, 'C':0.25, 'G':0.5, 'U':0})
def test_bases(self):
"""PositionalBaseUsage bases should sum bases at each position"""
a, c, g = BaseUsage('AAGC'), BaseUsage('CCGA'), BaseUsage('GGCA')
p = PositionalBaseUsage(a, c, g)
b = p.bases()
self.assertEqual(b, BaseUsage('AAGCCCGAGGCA'))
def test_codons(self):
"""PositionalBaseUsage codons should give expected codon freqs"""
#one of each base should give freqs if 1/64 for everything
orig = CodonUsage('UUUCCCAAAGGG')
b = orig.positionalBases()
final = b.codons()
self.assertEqual(len(final), 64)
for i in final:
self.assertFloatEqual(final[i], 1.0/64)
#two bases at each position should give correct freqs
orig = CodonUsage('UCGAGUUCGUCG')
final = orig.positionalBases().codons()
exp = {
'UCG': 0.75 * 0.75 * 0.75,
'UCU': 0.75 * 0.75 * 0.25,
'UGG': 0.75 * 0.25 * 0.75,
'UGU': 0.75 * 0.25 * 0.25,
'ACG': 0.25 * 0.75 * 0.75,
'ACU': 0.25 * 0.75 * 0.25,
'AGG': 0.25 * 0.25 * 0.75,
'AGU': 0.25 * 0.25 * 0.25,
}
for f in final:
if f in exp:
self.assertFloatEqual(final[f], exp[f])
else:
self.assertEqual(final[f], 0)
def test_positionalBases(self):
"""PositionalBaseUsage positionalBases should return same object"""
p = PositionalBaseUsage()
x = p.positionalBases()
assert p is x
def test_aminoAcids(self):
"""PositionalBaseUsage aminoAcids should return correct amino acids"""
#check hand-calculated values on a particular sequence
orig = CodonUsage('UCGAGUUCGUCG')
final = orig.positionalBases().aminoAcids()
exp = {
'S': 0.75 * 0.75 * 0.75 + 0.75 * 0.75 * 0.25 + 0.25*0.25*0.25,
'W': 0.75 * 0.25 * 0.75,
'C': 0.75 * 0.25 * 0.25,
'T': 0.25 * 0.75 * 0.75 + 0.25 * 0.75 * 0.25,
'R': 0.25 * 0.25 * 0.75,
}
for f in final:
if f in exp:
self.assertFloatEqual(final[f], exp[f])
else:
self.assertEqual(final[f], 0)
#test for unbiased freqs on a couple of different genetic codes
orig = CodonUsage('UUUCCCAAAGGG')
final = orig.positionalBases().aminoAcids()
SGC = GeneticCodes[1]
for aa in final:
self.assertEqual(final[aa], len(SGC[aa])/64.0)
mt = GeneticCodes[2]
final_mt = orig.positionalBases().aminoAcids(mt)
self.assertNotEqual(final, final_mt)
for aa in final_mt:
self.assertEqual(final_mt[aa], len(mt[aa])/64.0)
class AminoAcidUsageTests(TestCase):
"""Tests of the AminoAcidUsage class."""
def test_init_empty(self):
"""AminoAcidUsage should init with empty freqs"""
a = AminoAcidUsage()
for key, val in a.items():
self.assertEqual(val, 0)
self.assertEqual(len(a), 21)
assert 'A' in a
assert 'a' in a
def test_init_data(self):
"""AminoAcidUsage should init with data"""
a = AminoAcidUsage('aadddx')
self.assertEqual(a['A'], 2)
self.assertEqual(a['d'], 3)
self.assertEqual(a['X'], 1)
a.normalize()
self.assertEqual(a['a'], 0.4)
self.assertEqual(a['d'], 0.6)
assert 'x' not in a
def test_bases(self):
"""AminoAcidUsage bases should return most likely base freqs"""
a = AminoAcidUsage('GGG')
self.assertEqual(a.bases(),
{'G':9.0/12,'U':1.0/12,'C':1.0/12,'A':1.0/12})
a = AminoAcidUsage('CAGTWERQWE')
exp = a.codons().bases()
exp.normalize()
self.assertFloatEqual(a.bases(), exp)
def test_codons(self):
"""AminoAcidUsage codons should return most likely codon freqs"""
a = AminoAcidUsage('GGG')
c = CodonUsage('GGUGGCGGAGGG')
c.normalize()
self.assertEqual(a.codons(), c)
a = AminoAcidUsage('D')
c = CodonUsage('GAUGAC')
c.normalize()
self.assertEqual(a.codons(), c)
a = AminoAcidUsage('GDDFMM')
c = CodonUsage('GGUGGCGGAGGG'+'GAUGAC'*4+'UUUUUC'*2+'AUG'*8)
c.normalize()
self.assertEqual(a.codons(), c)
a = AminoAcidUsage('II*')
c = CodonUsage('AUUAUCAUA'*2+'UAAUAGUGA')
c.normalize()
self.assertEqual(a.codons(), c)
#check that it works with a nonstandard code
code = GeneticCode('A'*4+'C'*28+'G'*32)
a = AminoAcidUsage('AAA')
c = CodonUsage('UUUUUCUUAUUG')
c.normalize()
self.assertEqual(a.codons(code), c)
#check that it works with unequal codon frequencies
unequal = CodonUsage({'GGU':5,'GGC':2,'GGA':2,'GGG':1,'UUU':3,'UUC':1})
a = AminoAcidUsage('GFFF')
exp = {
'GGU':0.5*0.25,
'GGC':0.2*0.25,
'GGA':0.2*0.25,
'GGG':0.1*0.25,
'UUU':0.75*0.75,
'UUC':0.25*0.75
}
obs = a.codons(codon_usage=unequal)
for codon, freq in obs.items():
self.assertFloatEqual(freq, exp.get(codon, 0))
def test_positionalBases(self):
"""AminoAcidUsage positionalBases should return best positional bases"""
a = AminoAcidUsage('WQRSFADDQW')
exp = a.codons().positionalBases()
obs = a.positionalBases()
for o, e in zip(obs, exp):
self.assertFloatEqual(o, e)
def test_aminoAcids(self):
"""AminoAcidUsage aminoAcids should return same object"""
a = AminoAcidUsage('REWQDFTDSF')
b = a.aminoAcids()
assert a is b
class DinucUsageTests(TestCase):
"""Tests of the DinucUsage class."""
def test_init_from_seq(self):
"""DinucUsage should init correctly from string."""
s1 = 'AAAAA'
s2 = 'ACTACG'
fd = filter_dict
self.assertEqual(fd(DinucUsage(s1)), {'AA':4})
#NOTE: will map DNA seq tp RNA.
self.assertEqual(fd(DinucUsage(s2)), {'AC':2,'CU':1,'UA':1,'CG':1})
#check that it works for non-overlapping
self.assertEqual(fd(DinucUsage(s1, Overlapping=False)), {'AA':2})
self.assertEqual(fd(DinucUsage(s2, Overlapping=False)), \
{'AC':1,'UA':1,'CG':1})
#check that it works for the 3-1 case
self.assertEqual(fd(DinucUsage(s1, Overlapping='3-1')), {'AA':1})
self.assertEqual(fd(DinucUsage(s2, Overlapping='3-1')), \
{'UA':1})
s3 = 'ACG'*5
self.assertEqual(fd(DinucUsage(s3, Overlapping='3-1')), \
{'GA':4})
s4 = s3 + 'GAA'
self.assertEqual(fd(DinucUsage(s4, Overlapping='3-1')), \
{'GA':4,'GG':1})
def test_distance(self):
"""Dinuc distance should calculate Euclidean dist. correctly"""
s1 ='AA'+'GG'*10
s2 = 'AA'*5 + 'GG'*7
d1 = DinucUsage(s1, Overlapping=False)
d2 = DinucUsage(s2, Overlapping=False)
self.assertEqual(d1.distance(d1), 0)
self.assertEqual(d1.distance(d2), 5)
self.assertEqual(d2.distance(d1), 5)
def filter_dict(d):
"""Removes zero keys from dict-like object."""
result = dict(d)
for k, v in d.items():
if not v:
del result[k]
return result
#run if called from command-line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_cluster/__init__.py 000644 000765 000024 00000000700 12024702176 022231 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_goodness_of_fit', 'test_UPGMA', 'test_metric_scaling', 'test_procrustes', 'test_nmds', 'test_approximate_mds']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Catherine Lozuopone", "Peter Maxwell", "Rob Knight", "Justin Kuczynski"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_cluster/test_approximate_mds.py 000644 000765 000024 00000413537 12024702176 024745 0 ustar 00jrideout staff 000000 000000 #!usr/bin/env python
"""Unit tests for fast metric scaling functions"""
from cogent.util.unit_test import TestCase, main
from cogent.cluster import goodness_of_fit
from cogent.cluster.approximate_mds \
import nystrom
from cogent.cluster.approximate_mds \
import calc_matrix_a, calc_matrix_b, build_seed_matrix
from cogent.cluster.approximate_mds import rowmeans, \
affine_mapping, adjust_mds_to_ref, recenter, combine_mds, \
cmds_tzeng, CombineMds
from numpy import array, matrix, random, argsort
__author__ = "Andreas Wilm"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Andreas Wilm"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Andreas Wilm"
__email__ = "andreas.wilm@ucd.ie"
__status__ = "FIXME"
PRINT_STRESS = False
# Bigish symmetrical matrix for testing: The following is a distance
# matrix of 100 points making up a 16-dimensional spiral. Idea was
# copied from Tzeng et al. 2008 (PMID 18394154).
#
# Note: the objects are ordered, i.e. permuting the distances will
# give better MDS approximations
#
FULL_SYM_MATRIX = array([
[ 0. , 9.94319, 7.11402, 7.30016, 9.1998 , 7.52661,
10.1122 , 11.71544, 11.72171, 12.23729, 16.55706, 15.07764,
17.41182, 19.23286, 22.03428, 20.37969, 21.79021, 23.31804,
25.27884, 25.33384, 25.51721, 25.23346, 27.13757, 27.77099,
31.89744, 30.12906, 30.853 , 31.25053, 32.01368, 32.92915,
34.80687, 34.67094, 34.61157, 33.95445, 36.09099, 34.39821,
35.29278, 33.43954, 35.50327, 34.96861, 34.61776, 31.52205,
31.5479 , 31.86234, 30.85453, 29.69611, 29.41756, 28.83014,
30.11403, 28.76504, 23.7291 , 25.6983 , 25.97412, 25.13513,
24.45972, 21.55045, 21.69278, 19.95303, 16.26348, 17.11013,
14.32254, 17.62265, 15.44168, 17.37134, 13.90914, 11.73735,
12.23879, 12.84236, 16.11693, 14.78883, 14.85241, 16.81082,
15.84987, 19.49531, 19.10495, 20.82333, 22.2353 , 24.10629,
25.58022, 26.94421, 29.15922, 29.35633, 30.44926, 33.44155,
33.20634, 35.10944, 37.58041, 36.97612, 37.4974 , 39.19126,
41.96371, 39.49224, 44.24451, 44.49713, 46.20998, 45.17665,
43.34276, 45.20143, 42.75318, 46.74111],
[ 9.94319, 0. , 9.15502, 9.50864, 4.67066, 8.73786,
10.65396, 7.07033, 7.65245, 11.7303 , 13.97535, 14.44678,
14.4366 , 17.67632, 17.78924, 17.34483, 20.92378, 19.64563,
22.37953, 22.50652, 22.59182, 23.16428, 25.36422, 24.53657,
28.53754, 28.8102 , 28.67001, 29.99149, 29.0992 , 30.78134,
32.60362, 33.06432, 32.35053, 31.31204, 33.96212, 32.70361,
34.0075 , 31.79899, 34.1394 , 34.08447, 34.40636, 32.09843,
31.55098, 32.21933, 29.68935, 30.64989, 29.84656, 30.31266,
30.95073, 29.50086, 25.13342, 26.92125, 26.77764, 25.45479,
26.64139, 24.28835, 23.54393, 21.14658, 19.0042 , 19.69926,
17.01569, 17.70308, 16.76036, 18.85088, 15.67933, 13.11373,
14.57384, 14.49709, 13.93834, 13.97627, 15.28133, 15.43603,
15.38908, 19.14731, 18.0164 , 19.25691, 20.79821, 21.17772,
23.34925, 24.69467, 25.91663, 26.0043 , 27.48027, 31.09767,
29.88905, 31.87226, 35.07482, 34.08161, 34.96767, 36.59085,
39.56174, 37.35437, 42.00158, 42.65467, 44.21824, 42.7808 ,
41.49634, 42.89946, 41.51576, 45.2993 ],
[ 7.11402, 9.15502, 0. , 6.86568, 9.13056, 6.40397,
9.71158, 8.69917, 8.75907, 9.94964, 12.60852, 10.83371,
13.24922, 15.56278, 18.00935, 17.28358, 18.64376, 18.74751,
21.30424, 20.79329, 22.52019, 21.17382, 24.35227, 24.04257,
27.79547, 27.14583, 27.9384 , 28.31876, 29.19352, 30.31387,
32.49497, 32.53298, 32.54342, 31.6677 , 34.4333 , 33.06171,
33.8104 , 32.32825, 34.54666, 33.66703, 34.21985, 31.60984,
31.44096, 32.23245, 30.68488, 30.737 , 30.20034, 30.13288,
31.62192, 30.13293, 25.84322, 27.91135, 28.12311, 27.30813,
27.01853, 24.69093, 24.94734, 23.21836, 20.37644, 20.92257,
17.85377, 20.91217, 19.36837, 20.86528, 17.38101, 14.14065,
15.49992, 14.33989, 17.43602, 15.89444, 14.88863, 15.37154,
15.57648, 18.73803, 17.66276, 19.14902, 19.51857, 21.56308,
22.21288, 23.47894, 25.86362, 25.36028, 26.33286, 29.98075,
29.33639, 31.30981, 33.73965, 33.6759 , 34.04663, 35.63369,
38.24726, 36.06871, 40.78921, 41.34813, 43.00012, 42.36618,
40.24461, 42.30763, 40.55066, 44.09355],
[ 7.30016, 9.50864, 6.86568, 0. , 7.99096, 7.60197,
10.10639, 9.22165, 8.8801 , 9.49238, 13.66406, 12.57744,
13.13858, 15.46775, 17.73952, 16.56614, 18.40617, 19.64056,
21.45177, 22.03097, 21.88416, 22.61383, 24.92398, 25.28642,
29.08492, 27.8259 , 29.18638, 29.3961 , 30.42798, 31.81182,
33.20848, 33.36339, 34.03547, 33.03364, 35.82444, 34.7116 ,
35.8487 , 33.89059, 36.02136, 35.60052, 36.08047, 33.37669,
33.34017, 33.79942, 32.42774, 31.97527, 31.72587, 31.85386,
33.66607, 32.0357 , 26.92882, 29.3656 , 29.6113 , 28.77098,
27.98344, 25.49869, 26.08835, 24.3511 , 21.22304, 21.25266,
18.87943, 21.25316, 19.09945, 20.88305, 16.98734, 14.43121,
14.87293, 12.60412, 16.25858, 14.52592, 14.10743, 13.84321,
13.02127, 16.58691, 15.13994, 17.45726, 18.68005, 20.17601,
21.41715, 23.0355 , 25.07801, 24.73817, 26.67714, 29.31584,
29.02044, 31.28387, 33.55744, 33.39091, 34.49413, 36.29427,
39.09789, 36.46602, 41.84873, 41.95262, 44.21519, 43.15904,
41.86844, 43.70448, 41.85398, 45.9426 ],
[ 9.1998 , 4.67066, 9.13056, 7.99096, 0. , 8.10903,
8.12191, 6.68991, 6.01745, 8.81851, 12.76517, 13.05449,
13.25358, 16.08166, 16.85701, 14.96082, 18.58137, 18.78881,
21.03104, 21.37792, 20.97864, 22.24007, 23.27987, 23.47925,
27.51623, 27.08492, 27.63842, 28.49791, 28.08892, 29.94971,
31.60411, 32.35099, 31.64065, 30.7586 , 33.58783, 32.51966,
33.71852, 31.59205, 34.09468, 34.22325, 34.16007, 32.3283 ,
31.89116, 32.43132, 30.52192, 31.02961, 30.1106 , 31.0687 ,
31.53677, 30.2114 , 25.7518 , 27.6139 , 28.20037, 27.20175,
27.57982, 25.10337, 25.22312, 22.84998, 20.28434, 20.93006,
18.50018, 19.27925, 17.75401, 20.49716, 16.24356, 13.95706,
14.68697, 14.86848, 14.61363, 14.13096, 14.51717, 15.68778,
14.51018, 17.43174, 16.76305, 18.13449, 19.68793, 19.75357,
21.78947, 23.32496, 24.54554, 24.18059, 26.19812, 29.52194,
28.20267, 30.01717, 33.36934, 32.26088, 33.40864, 34.83176,
38.18059, 35.81903, 40.65885, 41.40321, 43.17206, 41.53149,
40.71829, 42.49124, 40.79031, 44.66045],
[ 7.52661, 8.73786, 6.40397, 7.60197, 8.10903, 0. ,
6.16569, 7.32563, 7.75387, 7.69682, 10.69552, 9.88725,
11.3961 , 14.00163, 16.23874, 15.6289 , 16.73334, 17.44048,
19.99725, 19.9533 , 20.46002, 19.84823, 22.72976, 23.22363,
27.33355, 26.83688, 27.09796, 28.27618, 28.3494 , 29.75656,
31.77772, 32.50386, 32.5482 , 31.99727, 34.67355, 33.19062,
34.46902, 33.13995, 35.80184, 35.25591, 35.33808, 33.38177,
33.04059, 33.91149, 32.75336, 32.5993 , 32.43664, 32.23116,
33.38874, 32.62237, 28.36209, 30.55605, 30.3347 , 29.56765,
29.58556, 27.53405, 26.86667, 25.00712, 21.74171, 23.02809,
19.62897, 22.0497 , 20.71073, 20.89719, 18.9401 , 14.67542,
15.87359, 14.84921, 15.9765 , 14.6316 , 13.43337, 14.09887,
13.393 , 15.35339, 15.15473, 15.57783, 16.38066, 18.12999,
19.33544, 20.47957, 22.53012, 23.41117, 23.94749, 27.14785,
27.12172, 29.01223, 32.1432 , 31.53822, 31.97442, 34.20046,
36.96213, 35.11644, 39.86917, 40.59916, 42.25278, 42.35218,
40.45489, 42.53407, 40.64863, 44.57547],
[ 10.1122 , 10.65396, 9.71158, 10.10639, 8.12191, 6.16569,
0. , 8.95464, 7.95483, 6.96854, 10.2321 , 9.1072 ,
11.40191, 13.88653, 16.49484, 12.77356, 14.76539, 17.37815,
19.05223, 19.09134, 19.48543, 19.25793, 20.07018, 21.44923,
26.16354, 24.71872, 25.7368 , 26.60446, 26.8787 , 27.97926,
30.01728, 31.59176, 31.2204 , 30.74726, 33.36662, 32.19782,
33.24557, 32.26498, 35.20755, 35.27066, 34.3224 , 33.45572,
33.21501, 33.77282, 32.98931, 33.29691, 32.48639, 32.89237,
33.31269, 33.17576, 29.06571, 31.25932, 31.50259, 31.19405,
31.33608, 28.94501, 28.98748, 26.83509, 23.67883, 25.4293 ,
22.19619, 23.92894, 22.48331, 23.70778, 20.61034, 16.80414,
17.54135, 17.64634, 18.13698, 16.73796, 15.0992 , 16.73965,
15.39915, 15.3146 , 16.21818, 15.90665, 16.80116, 17.15962,
18.1004 , 20.22697, 21.04317, 22.01882, 23.10616, 25.70386,
25.33855, 26.90823, 30.27089, 29.34631, 29.92087, 31.66778,
35.17056, 33.31352, 37.56416, 39.27059, 40.62456, 40.2062 ,
39.40489, 41.81369, 39.33236, 43.20546],
[ 11.71544, 7.07033, 8.69917, 9.22165, 6.68991, 7.32563,
8.95464, 0. , 3.7505 , 6.85568, 7.69523, 9.7299 ,
8.8292 , 12.08808, 12.84075, 12.41397, 15.7665 , 13.80821,
17.10528, 17.0151 , 18.03523, 18.49492, 21.4005 , 20.91953,
24.56468, 24.98275, 25.20224, 26.47583, 26.01966, 28.37676,
30.43507, 31.12544, 31.08021, 29.96861, 33.06401, 32.57304,
33.997 , 32.11079, 34.68809, 34.12659, 35.42161, 33.62916,
33.16394, 34.14988, 31.96731, 33.13473, 32.68089, 33.34788,
34.37908, 32.97516, 29.38917, 31.30679, 31.86587, 30.67301,
31.14565, 29.06828, 29.04268, 27.11562, 24.63125, 25.08637,
22.31814, 23.71491, 22.41495, 23.87865, 20.79483, 17.13811,
18.05839, 16.67094, 16.67337, 15.59013, 15.29917, 14.46026,
14.31921, 16.68845, 14.41634, 16.10611, 16.76691, 16.68857,
18.02822, 19.23566, 20.91886, 19.93191, 21.22647, 25.60087,
24.01222, 26.23519, 29.55426, 29.01695, 29.67471, 31.85062,
34.7836 , 32.77038, 38.06911, 38.63774, 40.78472, 39.75408,
38.43139, 40.51321, 39.43324, 43.19846],
[ 11.72171, 7.65245, 8.75907, 8.8801 , 6.01745, 7.75387,
7.95483, 3.7505 , 0. , 6.25554, 7.94184, 9.40809,
9.37058, 12.64537, 13.25671, 11.69312, 15.73247, 14.29708,
17.17558, 17.07269, 18.18613, 18.66698, 20.99351, 20.83302,
24.42795, 24.65435, 25.16361, 26.40833, 26.00333, 28.48816,
30.39505, 31.12778, 31.04052, 30.02038, 33.06101, 32.51077,
33.91746, 32.16109, 34.72522, 34.26106, 35.29431, 33.7662 ,
33.40285, 34.11146, 32.13639, 33.33042, 32.66608, 33.38514,
34.29769, 32.89254, 29.26526, 31.06269, 32.01605, 30.75263,
31.17672, 28.89607, 29.20958, 27.32181, 24.53975, 25.21252,
22.16274, 23.60181, 22.19147, 23.8951 , 20.57865, 17.20223,
17.67657, 16.61788, 17.05001, 15.68349, 15.30447, 14.95815,
14.4235 , 16.70277, 14.6234 , 16.24885, 16.87216, 16.49137,
17.85663, 19.18505, 20.91421, 19.70914, 21.64589, 25.6927 ,
24.18448, 26.08005, 29.35354, 29.00965, 29.70327, 31.74665,
34.68077, 32.64932, 37.91062, 38.78521, 40.83826, 39.61926,
38.5705 , 40.69567, 39.56802, 43.04025],
[ 12.23729, 11.7303 , 9.94964, 9.49238, 8.81851, 7.69682,
6.96854, 6.85568, 6.25554, 0. , 7.3016 , 8.07212,
8.2089 , 9.98656, 12.42781, 10.62705, 12.28722, 13.48977,
16.04661, 16.19534, 16.3577 , 17.32154, 19.0178 , 20.5046 ,
23.95953, 23.43756, 24.50878, 25.26128, 25.60517, 28.0269 ,
30.02525, 31.11886, 31.15891, 30.49865, 33.86459, 33.37975,
34.65544, 33.14589, 36.03802, 35.51766, 36.24468, 35.04257,
34.67094, 35.65553, 34.59658, 34.79422, 34.36677, 35.45895,
36.3779 , 35.3327 , 31.54706, 33.65312, 34.74652, 33.95725,
33.40518, 31.44167, 31.93944, 30.05815, 26.96615, 27.64338,
24.84473, 26.74278, 24.89471, 26.39705, 22.80323, 19.30856,
19.43576, 18.22819, 18.64491, 17.05169, 14.82973, 15.51568,
14.01205, 14.33961, 13.3435 , 14.52817, 14.70497, 14.77414,
15.56051, 16.74031, 18.93591, 17.75143, 19.27456, 22.94456,
21.91537, 23.84675, 27.42168, 26.76934, 27.66108, 29.75946,
33.0935 , 30.98471, 36.65424, 37.30058, 39.65202, 39.12975,
38.02632, 40.69416, 39.21815, 43.02089],
[ 16.55706, 13.97535, 12.60852, 13.66406, 12.76517, 10.69552,
10.2321 , 7.69523, 7.94184, 7.3016 , 0. , 6.34024,
6.29442, 9.31874, 10.60831, 9.48152, 11.679 , 9.86008,
12.78319, 12.47705, 15.20036, 14.79868, 18.06249, 17.95878,
21.80304, 21.94482, 22.94088, 24.29869, 24.32754, 26.55776,
29.0597 , 30.47032, 31.03937, 29.92437, 33.13454, 33.19895,
34.69406, 33.79095, 36.57048, 36.01451, 37.16413, 36.42303,
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28.54674, 30.22502, 28.99081, 29.49656, 27.01958, 22.64011,
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30.02343, 28.55089, 33.83448, 35.47091, 37.51809, 37.42083,
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12.22157, 12.42638, 14.81562, 13.24075, 15.91179, 16.17176,
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13.88653, 12.08808, 12.64537, 9.98656, 9.31874, 8.1817 ,
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34.19767, 35.53408, 35.0925 , 35.58014, 35.82126, 37.49003,
38.6495 , 38.10808, 35.42106, 37.82413, 38.53678, 38.03388,
37.13566, 36.62481, 36.8622 , 35.93997, 33.1206 , 33.81829,
31.46152, 33.72103, 32.12859, 33.34453, 30.4796 , 26.68134,
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25.73473, 23.91935, 30.1514 , 29.62866, 33.12758, 33.46496,
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16.49484, 12.84075, 13.25671, 12.42781, 10.60831, 12.01962,
7.34823, 7.38877, 0. , 9.98466, 10.45042, 7.01399,
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35.06246, 36.69763, 35.34281, 36.84744, 36.8362 , 38.82735,
39.99487, 39.19622, 36.6623 , 39.10442, 39.88191, 38.95773,
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25.22857, 23.0396 , 29.71055, 29.41731, 32.39176, 32.91178,
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12.77356, 12.41397, 11.69312, 10.62705, 9.48152, 9.83166,
7.61967, 8.41906, 9.98466, 0. , 7.63615, 9.92392,
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32.12772, 33.40582, 31.97045, 34.19075, 30.2786 , 26.83978,
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14.76539, 15.7665 , 15.73247, 12.28722, 11.679 , 10.03616,
8.88048, 6.8504 , 10.45042, 7.63615, 0. , 10.17132,
8.68748, 9.45034, 8.94115, 9.44003, 9.64568, 12.4589 ,
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24.33233, 25.80959, 27.19217, 26.53318, 30.11932, 30.64921,
32.34859, 31.49555, 34.6749 , 33.71667, 36.43731, 36.39199,
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40.59642, 39.92405, 37.99061, 40.17349, 40.90994, 39.98119,
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34.29651, 36.10593, 34.99984, 35.8496 , 33.74472, 29.52144,
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22.96009, 22.50932, 28.30391, 28.4628 , 31.64773, 32.1907 ,
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10.84203, 9.2088 , 9.5126 , 10.04376, 8.68748, 6.48226,
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29.57591, 29.31235, 32.28865, 31.99324, 33.95671, 34.64837,
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40.56478, 40.68159, 40.97394, 40.4026 , 37.91905, 39.08311,
36.66186, 38.48701, 37.36496, 38.4644 , 36.32379, 32.42384,
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13.85173, 13.32047, 13.81794, 14.45423, 14.59398, 17.7774 ,
18.83897, 18.33698, 23.71274, 24.45456, 27.512 , 27.97503,
27.44909, 29.9473 , 29.47687, 32.87905],
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11.15163, 10.31162, 10.22698, 10.49189, 9.45034, 6.68 ,
5.22655, 0. , 9.1845 , 6.24097, 10.68858, 8.9892 ,
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20.11514, 21.80086, 23.21553, 22.42534, 25.94406, 26.90792,
28.49847, 28.38986, 31.34822, 30.44753, 32.95536, 33.76841,
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39.01639, 38.73035, 37.37737, 39.86314, 40.9369 , 40.37831,
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36.62329, 38.68787, 37.66226, 39.09107, 36.48663, 32.61225,
34.05121, 32.23 , 32.67538, 31.35308, 29.36674, 27.44256,
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13.84417, 13.90252, 14.58239, 15.61773, 14.72379, 17.00739,
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25.82034, 28.7832 , 28.60458, 31.58328],
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12.21275, 9.70575, 8.29332, 11.12076, 8.94115, 9.57466,
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12.03637, 13.28049, 13.52418, 15.33503, 14.2314 , 18.60678,
18.65654, 20.52313, 22.48976, 21.9616 , 25.69566, 26.5576 ,
28.88904, 27.73913, 31.08385, 31.06195, 33.13063, 33.66469,
33.0211 , 34.43139, 34.32978, 35.45315, 35.945 , 38.07486,
39.28353, 39.22602, 37.42741, 40.16763, 41.16595, 40.59288,
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34.30145, 32.81646, 32.20425, 31.53711, 29.60455, 27.68888,
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14.39659, 14.09233, 14.84183, 13.11227, 14.67681, 17.10835,
19.10648, 17.05555, 23.72982, 22.93954, 26.36839, 26.99544,
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12.34706, 10.45564, 10.75866, 12.59852, 9.44003, 9.48408,
8.01445, 6.24097, 8.42136, 0. , 9.19567, 8.28483,
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17.47779, 19.26536, 20.81256, 20.47412, 24.07951, 24.48853,
26.31214, 26.12805, 29.5516 , 28.71938, 30.9913 , 31.6734 ,
31.05312, 32.90775, 32.68055, 34.31807, 34.6565 , 36.33305,
37.55324, 37.84719, 36.54117, 39.18647, 39.96285, 39.6461 ,
39.38249, 39.77171, 39.84257, 39.44919, 37.48819, 38.87541,
36.52095, 39.03388, 38.04894, 39.2854 , 37.05129, 33.33446,
34.86519, 33.37436, 33.51843, 32.6792 , 30.40374, 28.64096,
28.81112, 27.30426, 26.30338, 25.2772 , 23.65439, 21.82505,
19.44844, 19.69742, 19.3097 , 17.16471, 14.47088, 16.52024,
15.93936, 15.41702, 15.60782, 15.3568 , 14.63636, 16.4597 ,
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24.12467, 26.69992, 26.15777, 29.63547],
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16.11929, 13.73927, 15.09764, 12.42193, 9.64568, 13.97397,
10.22964, 10.68858, 9.37678, 9.19567, 0. , 6.87271,
10.56088, 8.63342, 11.01072, 10.93865, 11.45914, 14.5144 ,
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23.99425, 24.33084, 28.06753, 28.67934, 28.75474, 31.08502,
30.53155, 31.69899, 32.62122, 33.92971, 33.80767, 36.2285 ,
36.50334, 37.53278, 36.5014 , 39.07491, 40.15724, 40.40674,
39.85148, 40.40163, 40.9679 , 40.5153 , 38.42327, 40.1212 ,
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36.38785, 35.95878, 35.6227 , 34.90092, 32.5457 , 31.91806,
31.28384, 28.86779, 28.98518, 27.6702 , 26.58669, 23.92989,
21.86083, 22.75265, 21.11808, 18.7693 , 18.18955, 18.2176 ,
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16.58338, 15.70851, 18.99807, 20.56008, 22.44251, 22.97965,
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16.0975 , 14.84133, 14.55 , 13.54166, 12.4589 , 13.15679,
9.35169, 8.9892 , 10.39484, 8.28483, 6.87271, 0. ,
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12.50632, 15.65258, 16.85322, 16.28059, 19.40831, 20.28063,
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28.64062, 29.85524, 29.8061 , 32.57415, 32.29469, 34.31277,
34.99807, 35.82 , 35.31492, 37.94267, 38.60944, 38.67121,
38.95962, 39.63135, 39.99892, 39.64319, 38.13686, 39.73796,
37.88513, 39.57072, 38.9161 , 40.94059, 38.2891 , 35.07866,
36.89862, 36.20281, 36.05376, 35.34433, 33.67934, 32.25061,
32.36628, 30.7808 , 30.11484, 29.01616, 27.92706, 25.32419,
23.29639, 24.12436, 22.42396, 19.7537 , 19.01006, 19.94131,
18.33339, 16.81857, 15.99741, 15.0617 , 14.77595, 14.59106,
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12.50172, 10.75227, 12.03637, 9.68535, 10.56088, 7.72073,
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13.12007, 15.09318, 15.76199, 15.39935, 19.70394, 21.41588,
23.13548, 22.85749, 26.18616, 25.68635, 28.9516 , 30.93716,
30.0345 , 32.15204, 31.65812, 34.38793, 34.38638, 37.50663,
38.17473, 38.39304, 38.36668, 40.71544, 42.31539, 42.04724,
41.86037, 42.90939, 43.56974, 43.4618 , 42.34263, 43.41177,
41.79768, 43.79152, 42.99372, 45.43309, 42.39361, 39.51926,
41.2064 , 40.11474, 39.74911, 39.34168, 37.45432, 35.8801 ,
35.90349, 34.72309, 33.54021, 32.87432, 31.3026 , 28.63784,
26.36769, 26.4844 , 25.34082, 21.25983, 19.4387 , 21.35453,
18.66931, 16.58331, 15.29044, 14.5311 , 14.07159, 12.69685,
13.75561, 12.45704, 16.48731, 16.18279, 18.19724, 18.82112,
17.69826, 20.07196, 20.9814 , 23.64271],
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24.71872, 24.98275, 24.65435, 23.43756, 21.94482, 19.82228,
20.33958, 18.12427, 19.17678, 16.80266, 14.65608, 17.80094,
13.03384, 12.5549 , 13.28049, 11.98782, 8.63342, 8.27576,
9.87641, 0. , 7.98874, 5.38369, 9.95786, 10.82054,
11.0462 , 12.89802, 15.44491, 14.85573, 17.38129, 19.47045,
20.77089, 21.32264, 24.07172, 24.28534, 25.596 , 27.93375,
27.86256, 28.87872, 29.7082 , 31.88982, 31.87346, 34.12199,
35.33819, 36.0731 , 35.88703, 38.71968, 40.48097, 40.65492,
40.04445, 40.78432, 42.24041, 42.36186, 40.86445, 42.22587,
40.89454, 43.17864, 41.97252, 44.85097, 41.45324, 38.91288,
40.27944, 39.6453 , 40.59724, 39.49418, 37.70761, 36.65188,
36.33936, 34.78051, 33.80123, 33.49258, 32.35566, 29.75799,
27.30116, 28.38011, 27.09472, 23.18208, 22.41711, 22.75371,
20.88887, 19.50611, 15.96133, 15.86852, 14.98222, 13.66391,
14.86599, 12.41707, 15.52539, 16.68747, 18.30724, 16.95519,
17.37892, 20.49274, 18.30611, 21.75684],
[ 30.853 , 28.67001, 27.9384 , 29.18638, 27.63842, 27.09796,
25.7368 , 25.20224, 25.16361, 24.50878, 22.94088, 21.65753,
21.24043, 19.27123, 18.69286, 18.81578, 17.17587, 18.12113,
15.11671, 13.42965, 13.52418, 11.05565, 11.01072, 9.50557,
7.6598 , 7.98874, 0. , 6.64528, 4.59801, 8.21652,
10.31466, 11.16178, 12.08679, 11.83932, 15.09664, 17.18703,
19.54388, 19.20711, 22.42597, 21.78585, 24.86467, 26.82595,
26.17402, 28.22608, 28.33647, 30.77347, 31.09911, 33.82732,
34.63993, 35.32224, 35.64687, 38.19558, 40.17273, 39.9043 ,
39.71271, 40.82968, 41.59044, 41.89523, 40.82556, 42.24267,
40.88634, 43.2909 , 42.33337, 45.05862, 42.17539, 39.71804,
41.17056, 40.67256, 40.65653, 40.19097, 38.65435, 37.60561,
37.35235, 36.34129, 35.23204, 34.77337, 33.6225 , 30.92734,
29.00015, 29.40958, 28.36382, 25.0391 , 22.59333, 24.07796,
21.93502, 20.62995, 18.16191, 17.02272, 15.54819, 14.56199,
15.3057 , 12.64367, 16.45475, 15.71403, 16.86429, 16.85299,
15.00269, 17.43522, 17.0517 , 20.42138],
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26.60446, 26.47583, 26.40833, 25.26128, 24.29869, 22.19242,
22.37157, 19.82935, 20.74564, 19.22611, 17.02335, 19.85319,
16.15319, 14.83639, 15.33503, 13.27899, 10.93865, 10.31176,
9.49731, 5.38369, 6.64528, 0. , 7.92917, 9.13679,
9.53346, 10.47996, 12.16654, 11.7129 , 15.01867, 17.3945 ,
18.42663, 18.36001, 21.25014, 21.14056, 23.39958, 25.64935,
25.29954, 27.11021, 27.88541, 29.88329, 29.87818, 33.15122,
33.91166, 34.60562, 34.9862 , 37.6223 , 39.74094, 40.05704,
39.15768, 40.26411, 41.81453, 42.1735 , 41.17397, 42.24356,
41.4135 , 43.87194, 42.72225, 46.08496, 42.30557, 40.15065,
41.69059, 41.24556, 41.85591, 41.23647, 39.41798, 38.64347,
38.26693, 37.14527, 36.28322, 36.14132, 34.9677 , 32.65462,
30.32245, 31.15585, 30.05495, 26.14201, 24.6254 , 25.64368,
23.38049, 21.94394, 18.90934, 18.07516, 17.34202, 14.70928,
16.17006, 13.04202, 15.86513, 15.06125, 16.67207, 15.02326,
14.43571, 17.62774, 15.52057, 19.39125],
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26.8787 , 26.01966, 26.00333, 25.60517, 24.32754, 23.10866,
22.50594, 20.31297, 19.36248, 19.70099, 18.67632, 18.97979,
16.32212, 15.19843, 14.2314 , 12.97288, 11.45914, 9.92433,
7.49547, 9.95786, 4.59801, 7.92917, 0. , 9.46759,
9.53989, 10.77149, 10.67123, 10.77957, 14.38107, 16.55356,
18.86377, 17.93757, 21.53923, 21.5 , 24.50229, 26.72856,
25.8231 , 27.87236, 28.08681, 30.54159, 30.74741, 34.21383,
34.31615, 35.0456 , 35.81848, 38.00399, 40.05607, 39.79457,
39.61693, 41.10429, 41.69482, 42.04974, 41.08039, 42.4485 ,
41.31527, 43.35611, 42.53551, 45.50379, 42.54538, 40.30517,
41.79641, 41.68827, 40.95449, 40.88777, 39.44077, 38.47113,
38.21591, 37.33843, 36.35944, 35.80693, 34.8564 , 31.85679,
30.32951, 30.47848, 29.27892, 25.8884 , 23.90214, 25.36182,
23.14462, 21.09032, 19.56871, 17.40934, 16.72036, 15.08113,
16.01239, 13.78221, 17.09382, 15.61569, 17.24015, 16.33925,
15.18723, 17.0286 , 16.96968, 20.31666],
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27.97926, 28.37676, 28.48816, 28.0269 , 26.55776, 24.91478,
24.89152, 23.84286, 23.2144 , 22.40398, 20.67866, 23.36183,
20.01859, 18.37361, 18.60678, 15.95134, 14.5144 , 12.30625,
12.71031, 10.82054, 8.21652, 9.13679, 9.46759, 0. ,
8.89237, 11.56402, 9.66796, 8.7428 , 11.95979, 14.08575,
15.80045, 16.65181, 19.74296, 20.61442, 21.15351, 24.45494,
23.9113 , 26.09147, 26.17295, 29.57049, 28.96665, 31.93696,
32.42409, 34.06939, 34.49619, 37.51745, 38.87821, 39.44799,
39.80638, 40.83166, 41.71964, 41.67128, 41.61213, 43.2428 ,
42.36568, 44.39476, 43.77865, 46.84558, 43.53456, 41.47749,
43.3667 , 43.24129, 43.27906, 42.89426, 41.53307, 41.05796,
40.77052, 39.41463, 39.1773 , 38.1895 , 37.36602, 34.97812,
33.00745, 34.10653, 32.18818, 29.92886, 27.45379, 28.27133,
25.75202, 25.34647, 22.44188, 20.82485, 19.82573, 16.70077,
18.83691, 15.85836, 15.60841, 17.8028 , 15.28365, 15.19425,
13.84108, 16.11862, 13.96013, 17.63429],
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30.01728, 30.43507, 30.39505, 30.02525, 29.0597 , 26.51025,
26.47231, 24.56468, 24.62428, 23.49591, 21.7796 , 24.33233,
20.19876, 20.11514, 18.65654, 17.47779, 14.09155, 12.50632,
13.12007, 11.0462 , 10.31466, 9.53346, 9.53989, 8.89237,
0. , 7.18087, 9.42639, 10.38858, 11.58877, 12.91252,
14.59769, 15.59285, 18.95488, 20.67684, 20.8958 , 24.70048,
24.0165 , 25.43853, 26.95084, 29.21772, 29.55268, 32.62558,
32.93689, 34.88785, 35.60229, 38.44528, 39.2932 , 39.98048,
39.73092, 41.86321, 42.40135, 43.0919 , 42.45519, 44.1862 ,
43.47623, 45.37599, 44.76722, 47.773 , 44.99764, 42.85482,
45.0001 , 44.84355, 44.80852, 44.71783, 43.31817, 42.17357,
42.00564, 40.73932, 40.54667, 39.4803 , 38.72058, 36.16405,
34.29426, 35.27955, 33.02234, 30.89456, 29.48465, 28.8475 ,
27.86781, 25.48297, 22.56247, 20.68579, 20.34994, 17.57016,
17.81885, 16.39775, 15.34486, 15.15469, 14.83316, 14.19401,
15.20368, 15.44059, 11.80224, 16.78251],
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31.59176, 31.12544, 31.12778, 31.11886, 30.47032, 27.84524,
28.19409, 25.91998, 26.05861, 25.94766, 24.38931, 25.80959,
22.03234, 21.80086, 20.52313, 19.26536, 17.70246, 15.65258,
15.09318, 12.89802, 11.16178, 10.47996, 10.77149, 11.56402,
7.18087, 0. , 8.74195, 9.19296, 8.9676 , 10.89087,
13.36331, 12.96807, 15.25494, 15.85912, 18.74728, 20.99385,
20.58536, 21.90675, 23.7641 , 25.59202, 26.79648, 29.58366,
30.67949, 31.89102, 33.4665 , 36.09133, 37.70993, 37.82863,
37.1605 , 39.86674, 40.65224, 42.17263, 41.48734, 42.91311,
42.56542, 45.03955, 44.26307, 47.54766, 44.95504, 43.36693,
45.22628, 45.15693, 45.74134, 45.58144, 44.57787, 43.24457,
43.23535, 43.03554, 41.97252, 41.7482 , 41.05749, 38.72517,
37.14338, 37.61494, 36.50124, 33.46255, 32.11582, 32.19497,
31.24603, 29.25163, 25.58682, 24.49213, 23.73966, 21.92186,
20.66609, 18.42641, 19.3634 , 16.24486, 17.24548, 15.15315,
13.59916, 12.73676, 10.23459, 14.84621],
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31.2204 , 31.08021, 31.04052, 31.15891, 31.03937, 28.94428,
29.03612, 27.59428, 27.01352, 26.54727, 25.59948, 27.19217,
24.49275, 23.21553, 22.48976, 20.81256, 18.65296, 16.85322,
15.76199, 15.44491, 12.08679, 12.16654, 10.67123, 9.66796,
9.42639, 8.74195, 0. , 4.97625, 7.39172, 8.51026,
10.14648, 9.50175, 13.1454 , 14.11243, 15.8578 , 19.62747,
18.29823, 20.97263, 21.55663, 24.21139, 24.16038, 28.57247,
28.2877 , 29.74339, 31.3773 , 33.75635, 35.79133, 36.21335,
36.02599, 38.43108, 39.29054, 40.11502, 40.44974, 41.86014,
41.7082 , 43.69002, 43.19493, 47.14492, 43.81483, 42.6301 ,
44.81877, 45.24839, 44.99179, 45.27901, 44.24326, 44.00885,
43.62399, 43.42716, 43.097 , 42.57723, 41.90128, 39.82617,
38.47462, 39.17248, 37.86386, 34.99443, 33.29005, 34.59372,
32.25062, 30.55199, 28.63669, 26.61145, 26.02174, 22.74625,
23.58481, 21.28107, 21.00584, 19.89187, 18.45627, 16.11799,
14.52011, 14.22711, 12.12231, 15.73701],
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30.74726, 29.96861, 30.02038, 30.49865, 29.92437, 28.23706,
28.11855, 26.89288, 25.91131, 25.58126, 25.17219, 26.53318,
23.76956, 22.42534, 21.9616 , 20.47412, 19.02075, 16.28059,
15.39935, 14.85573, 11.83932, 11.7129 , 10.77957, 8.7428 ,
10.38858, 9.19296, 4.97625, 0. , 6.72148, 10.12496,
12.00924, 10.13169, 12.83076, 14.2167 , 16.72792, 19.37301,
18.59613, 21.00058, 20.66568, 24.48285, 23.84352, 28.26891,
28.32281, 29.3094 , 30.90888, 33.39326, 35.6437 , 35.93431,
36.08269, 37.85734, 39.11931, 39.73362, 40.26473, 41.36942,
41.39021, 43.28881, 42.72848, 46.85017, 43.10439, 42.13604,
43.99537, 44.34038, 44.26734, 44.39004, 43.65807, 43.18833,
42.95227, 42.93121, 42.14583, 41.96176, 41.49189, 39.07646,
37.79461, 38.59134, 37.2521 , 34.09993, 32.53784, 33.99566,
31.15287, 30.43379, 27.85509, 26.08889, 25.78955, 22.49509,
23.83891, 20.37192, 20.98593, 20.20119, 18.99761, 15.27863,
13.7462 , 13.92431, 12.80535, 16.20137],
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33.36662, 33.06401, 33.06101, 33.86459, 33.13454, 31.0608 ,
31.78424, 30.55842, 30.18725, 29.12877, 28.8489 , 30.11932,
26.89441, 25.94406, 25.69566, 24.07951, 22.11715, 19.40831,
19.70394, 17.38129, 15.09664, 15.01867, 14.38107, 11.95979,
11.58877, 8.9676 , 7.39172, 6.72148, 0. , 6.43367,
8.98397, 8.67729, 10.0527 , 12.31282, 13.61151, 17.29523,
16.952 , 18.20422, 19.0518 , 23.06074, 23.05218, 26.13901,
26.38234, 28.09777, 30.76486, 33.11761, 35.1361 , 35.41829,
35.86916, 38.17342, 39.25199, 40.55388, 40.93513, 42.5099 ,
42.56349, 44.52465, 44.12784, 48.09543, 45.13455, 44.19635,
46.17291, 46.91914, 47.23808, 47.21417, 46.86937, 46.30617,
46.18952, 46.3353 , 45.46555, 45.29483, 44.96068, 42.56432,
41.36339, 42.23577, 40.86225, 37.9703 , 36.62617, 37.63698,
35.45185, 34.21791, 31.08457, 29.69294, 28.68309, 26.09517,
26.05857, 23.59887, 22.7285 , 22.24654, 20.53253, 16.26812,
15.10008, 13.99427, 10.96839, 13.95765],
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32.19782, 32.57304, 32.51077, 33.37975, 33.19895, 30.49635,
31.68759, 30.76624, 30.6706 , 29.7836 , 29.1434 , 30.64921,
27.73295, 26.90792, 26.5576 , 24.48853, 22.68976, 20.28063,
21.41588, 19.47045, 17.18703, 17.3945 , 16.55356, 14.08575,
12.91252, 10.89087, 8.51026, 10.12496, 6.43367, 0. ,
5.13455, 7.19981, 9.26742, 11.82888, 10.17125, 14.78769,
13.87506, 15.22203, 17.04526, 19.97496, 20.45104, 22.81966,
22.94849, 25.40346, 27.90575, 30.36558, 31.45698, 32.01961,
32.50931, 35.50764, 35.83888, 37.37873, 37.77828, 39.79016,
39.73051, 41.74234, 41.66611, 45.21051, 42.9827 , 41.96344,
44.45906, 45.37185, 45.70899, 45.86452, 45.49593, 45.23056,
45.08133, 45.40294, 45.13354, 44.55667, 44.24469, 42.6187 ,
41.59934, 42.40437, 41.24915, 39.18714, 37.89513, 38.80147,
37.34563, 35.75256, 33.50089, 31.99846, 30.98915, 28.78806,
28.57053, 27.01304, 25.56683, 25.4267 , 23.23683, 21.19257,
19.15064, 17.6646 , 13.95903, 16.88417],
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33.24557, 33.997 , 33.91746, 34.65544, 34.69406, 31.58452,
33.16023, 32.23747, 32.78994, 31.07416, 30.36341, 32.34859,
29.57591, 28.49847, 28.88904, 26.31214, 23.99425, 21.80124,
23.13548, 20.77089, 19.54388, 18.42663, 18.86377, 15.80045,
14.59769, 13.36331, 10.14648, 12.00924, 8.98397, 5.13455,
0. , 7.16407, 9.04734, 11.89485, 7.77198, 14.16043,
13.10023, 14.59801, 16.76365, 19.57846, 19.38376, 22.39702,
21.86462, 24.72382, 27.4199 , 29.752 , 30.72862, 31.93212,
32.14663, 35.16599, 35.88763, 37.34873, 38.05632, 39.9811 ,
40.13104, 42.11747, 42.08783, 46.05367, 43.28691, 42.38342,
45.19904, 46.24403, 46.80226, 47.00371, 46.37995, 46.44777,
46.32251, 46.58154, 46.66496, 46.07288, 45.61367, 44.385 ,
43.10472, 44.24015, 42.9754 , 40.85532, 39.73088, 40.79164,
39.14055, 37.3534 , 35.4027 , 33.98145, 32.97956, 30.08218,
30.29887, 29.00976, 26.63001, 27.03646, 24.48703, 22.05865,
20.62081, 19.57784, 14.73243, 17.36648],
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32.26498, 32.11079, 32.16109, 33.14589, 33.79095, 31.13131,
32.00993, 30.8686 , 31.0901 , 29.98562, 29.95065, 31.49555,
29.31235, 28.38986, 27.73913, 26.12805, 24.33084, 22.2785 ,
22.85749, 21.32264, 19.20711, 18.36001, 17.93757, 16.65181,
15.59285, 12.96807, 9.50175, 10.13169, 8.67729, 7.19981,
7.16407, 0. , 5.29396, 8.67893, 9.00802, 11.50156,
10.13767, 12.58519, 13.75226, 16.33162, 16.16096, 21.27586,
20.36335, 22.08521, 24.78172, 26.80699, 28.87533, 29.58085,
29.35632, 32.37612, 33.42273, 35.02844, 35.98014, 37.25958,
38.02517, 40.01821, 39.69333, 44.39596, 40.98925, 40.81211,
43.15676, 44.3192 , 44.52264, 45.11777, 44.80329, 44.7664 ,
44.57585, 45.54288, 45.13382, 45.13769, 45.036 , 43.45157,
42.69738, 43.68518, 42.70208, 40.23943, 39.23902, 40.71097,
38.75821, 37.46691, 35.83383, 33.96711, 33.65132, 30.88072,
31.70992, 29.12309, 28.97938, 27.45576, 26.55069, 22.69609,
21.31464, 19.94906, 16.52504, 20.00963],
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35.20755, 34.68809, 34.72522, 36.03802, 36.57048, 34.00834,
35.12134, 34.10976, 34.2731 , 33.17048, 33.33854, 34.6749 ,
32.28865, 31.34822, 31.08385, 29.5516 , 28.06753, 25.59015,
26.18616, 24.07172, 22.42597, 21.25014, 21.53923, 19.74296,
18.95488, 15.25494, 13.1454 , 12.83076, 10.0527 , 9.26742,
9.04734, 5.29396, 0. , 7.02491, 7.91346, 9.49832,
8.97779, 10.53213, 11.64105, 15.08541, 14.93272, 19.4389 ,
19.22241, 20.51852, 24.28367, 26.21266, 28.62454, 29.21067,
29.13434, 32.23565, 33.74681, 35.77881, 37.02082, 38.04921,
39.25933, 41.2876 , 41.02127, 45.92867, 42.53998, 42.80247,
45.02922, 46.2601 , 46.99824, 47.39798, 47.50405, 47.43771,
47.28364, 48.66654, 47.8922 , 48.31191, 48.29145, 46.78708,
46.0658 , 47.00178, 46.27576, 43.40774, 42.66151, 44.23342,
42.09818, 41.14137, 38.8066 , 37.42541, 36.96229, 34.28354,
34.64723, 31.85059, 31.58249, 30.04064, 28.92462, 24.27898,
22.53438, 20.85881, 17.8264 , 20.38759],
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35.27066, 34.12659, 34.26106, 35.51766, 36.01451, 33.61703,
34.61314, 33.50914, 33.85408, 33.35028, 33.29967, 33.71667,
31.99324, 30.44753, 31.06195, 28.71938, 28.67934, 26.20645,
25.68635, 24.28534, 21.78585, 21.14056, 21.5 , 20.61442,
20.67684, 15.85912, 14.11243, 14.2167 , 12.31282, 11.82888,
11.89485, 8.67893, 7.02491, 0. , 11.6549 , 10.73557,
9.71187, 12.80952, 12.4755 , 15.06586, 16.27814, 20.16314,
21.00477, 21.04933, 24.7121 , 26.38835, 29.5294 , 29.42525,
28.82948, 32.05309, 33.66472, 36.01266, 37.14096, 37.87527,
38.78613, 41.51105, 41.02762, 45.8564 , 42.62709, 42.66475,
44.95803, 45.70734, 46.90492, 47.20804, 47.14969, 46.86 ,
46.8637 , 48.70376, 47.41032, 48.23058, 47.81376, 46.72845,
45.78045, 46.55168, 46.44799, 43.06789, 41.80521, 44.2389 ,
41.92408, 40.96925, 38.73615, 37.92498, 36.83463, 34.6773 ,
34.46336, 31.84197, 32.48614, 29.86623, 29.37943, 25.34313,
22.18623, 20.58748, 18.68724, 20.88898],
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34.3224 , 35.42161, 35.29431, 36.24468, 37.16413, 34.00148,
36.07251, 35.42056, 36.35145, 34.18506, 33.88558, 36.43731,
33.95671, 32.95536, 33.13063, 30.9913 , 28.75474, 27.03954,
28.9516 , 25.596 , 24.86467, 23.39958, 24.50229, 21.15351,
20.8958 , 18.74728, 15.8578 , 16.72792, 13.61151, 10.17125,
7.77198, 9.00802, 7.91346, 11.6549 , 0. , 8.82796,
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15.72496, 18.98626, 22.36856, 24.60879, 26.09397, 27.63374,
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13.10023, 10.13767, 8.97779, 9.71187, 8.51924, 3.87115,
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14.59801, 12.58519, 10.53213, 12.80952, 8.99769, 4.46637,
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34.85416, 33.79277, 34.32978, 32.68055, 32.62122, 29.8061 ,
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22.39702, 21.27586, 19.4389 , 20.16314, 16.59245, 11.67969,
12.97798, 10.38464, 10.99449, 9.85696, 10.17757, 0. ,
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21.86462, 20.36335, 19.22241, 21.00477, 15.72496, 12.43841,
12.90918, 10.82867, 11.78021, 10.89332, 8.53509, 7.83858,
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27.98701, 29.72961, 30.14266, 35.2683 , 32.68231, 34.49442,
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33.17576, 32.97516, 32.89254, 35.3327 , 37.62287, 35.23732,
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14.31407, 12.8995 , 11.37028, 10.39258, 8.32038, 8.41089,
6.82238, 0. , 8.71731, 7.76443, 12.45335, 12.2652 ,
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25.76323, 27.71115, 27.8258 , 33.66319, 30.48156, 32.98226,
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50.39015, 50.58997, 50.40001, 49.3039 , 49.05992, 47.89894,
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40.30443, 39.8812 , 36.95114, 39.24277],
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29.06571, 29.38917, 29.26526, 31.54706, 34.72634, 32.32311,
34.34605, 35.42106, 36.6623 , 34.70021, 36.40368, 37.99061,
38.021 , 37.37737, 37.42741, 36.54117, 36.5014 , 35.31492,
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17.64249, 17.10962, 14.90543, 12.86851, 10.85168, 11.19326,
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20.41051, 22.31093, 22.02977, 28.4554 , 24.40348, 27.41917,
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49.68564, 46.61442, 48.6812 , 48.31756, 48.12534, 44.56241,
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40.62842, 39.86314, 40.16763, 39.18647, 39.07491, 37.94267,
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19.73502, 18.97275, 16.80241, 14.75476, 12.70132, 13.48331,
11.88195, 7.76443, 5.57175, 0. , 9.15475, 8.56349,
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52.28684, 49.36971, 51.53462, 50.93333, 50.99637, 47.03863,
45.1501 , 44.98107, 42.0262 , 44.83658],
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37.11372, 38.53678, 39.88191, 38.15456, 39.92573, 40.90994,
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42.31539, 40.48097, 40.17273, 39.74094, 40.05607, 38.87821,
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30.72862, 28.87533, 28.62454, 29.5294 , 26.09397, 21.99594,
21.71174, 20.8149 , 19.058 , 17.21257, 15.99258, 14.05563,
13.2132 , 12.45335, 8.63071, 9.15475, 0. , 5.69041,
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19.20324, 20.11261, 21.17791, 26.23138, 24.1575 , 26.74297,
29.9642 , 32.63265, 34.33692, 35.4078 , 37.27436, 38.82324,
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51.90866, 52.35132, 53.40064, 52.18807, 52.39054, 51.76294,
53.60591, 51.35824, 52.66349, 52.69263, 52.29538, 49.4784 ,
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40.72945, 40.37831, 40.59288, 39.6461 , 40.40674, 38.67121,
42.04724, 40.65492, 39.9043 , 40.05704, 39.79457, 39.44799,
39.98048, 37.82863, 36.21335, 35.93431, 35.41829, 32.01961,
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22.56943, 21.56576, 19.18607, 17.61602, 17.25635, 14.64482,
14.82213, 12.2652 , 9.25549, 8.56349, 5.69041, 0. ,
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17.3385 , 18.54959, 19.51911, 24.47804, 23.22298, 25.99818,
28.67918, 31.37243, 33.06567, 34.08613, 36.44189, 37.65905,
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47.25139, 48.43046, 49.49756, 48.83554, 49.72558, 52.67093,
51.57562, 52.08085, 53.1481 , 52.11595, 52.16829, 52.09858,
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36.48557, 37.13566, 38.89602, 37.77484, 39.20976, 39.92003,
40.56478, 40.3905 , 40.07303, 39.38249, 39.85148, 38.95962,
41.86037, 40.04445, 39.71271, 39.15768, 39.61693, 39.80638,
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21.94117, 21.19765, 20.42547, 15.71376, 16.51621, 15.51254,
16.05954, 12.90017, 9.12862, 8.47478, 8.86444, 7.69056,
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28.95484, 31.3744 , 33.67799, 34.68713, 36.28302, 37.6514 ,
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47.29764, 48.35452, 49.81537, 48.72589, 49.68722, 52.42257,
51.63792, 51.8305 , 52.84663, 51.78041, 52.05071, 51.83186,
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35.26936, 36.62481, 38.43435, 36.36806, 38.61636, 39.6808 ,
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18.55392, 15.09061, 9.36863, 8.49044, 10.50088, 9.58872,
8.27573, 0. , 7.81203, 9.63841, 11.81341, 10.38626,
14.34691, 16.65127, 16.01583, 22.86644, 18.67511, 22.78851,
24.49932, 27.34599, 30.249 , 30.89222, 32.98648, 35.07533,
34.59757, 39.54874, 39.14111, 41.24033, 42.66911, 44.16304,
45.54425, 47.06384, 48.51593, 47.55693, 48.77945, 51.948 ,
50.60804, 51.67431, 52.94916, 52.10773, 52.46879, 52.27757,
54.53359, 51.56906, 54.55259, 53.99784, 54.65517, 51.26881,
49.40055, 49.64106, 46.62981, 49.95592],
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28.98748, 29.04268, 29.20958, 31.93944, 35.36933, 33.23999,
35.32999, 36.8622 , 38.31651, 37.32521, 39.27939, 39.62528,
40.97394, 40.75477, 40.65161, 39.84257, 40.9679 , 39.99892,
43.56974, 42.24041, 41.59044, 41.81453, 41.69482, 41.71964,
42.40135, 40.65224, 39.29054, 39.11931, 39.25199, 35.83888,
35.88763, 33.42273, 33.74681, 33.66472, 31.99623, 27.04794,
26.75678, 26.22855, 24.54862, 21.66767, 21.60589, 19.49451,
19.55994, 17.41787, 12.44362, 11.99477, 9.15299, 7.27847,
8.48397, 7.81203, 0. , 6.39087, 8.34311, 9.09498,
12.01051, 14.03886, 14.66736, 19.35195, 18.37439, 21.53225,
24.01021, 26.91727, 28.70851, 29.95311, 32.23778, 33.96847,
33.87564, 38.86784, 38.83989, 40.22175, 41.76582, 43.56084,
45.32808, 46.48406, 47.93843, 47.98325, 48.86364, 51.79319,
51.20293, 51.97604, 53.74581, 52.60551, 52.8835 , 53.24671,
55.09278, 52.73899, 55.52021, 54.91969, 55.45876, 53.12569,
50.8073 , 50.61611, 47.78862, 51.26349],
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26.83509, 27.11562, 27.32181, 30.05815, 33.57977, 31.99141,
33.72941, 35.93997, 37.10258, 35.80232, 38.1003 , 38.71391,
40.4026 , 40.04084, 40.1262 , 39.44919, 40.5153 , 39.64319,
43.4618 , 42.36186, 41.89523, 42.1735 , 42.04974, 41.67128,
43.0919 , 42.17263, 40.11502, 39.73362, 40.55388, 37.37873,
37.34873, 35.02844, 35.77881, 36.01266, 33.83917, 29.67531,
29.24043, 29.18584, 26.69301, 25.03361, 23.78436, 22.64066,
22.19041, 20.38048, 14.25313, 14.44966, 11.56439, 11.07301,
13.22617, 9.63841, 6.39087, 0. , 7.5008 , 7.8237 ,
10.40305, 10.70596, 11.78864, 17.10573, 14.52165, 18.11827,
20.90729, 23.93647, 25.20954, 26.57818, 28.98693, 31.46102,
31.12039, 35.92599, 36.4427 , 37.60689, 39.32328, 41.32062,
43.23691, 44.71995, 45.92899, 46.36053, 47.3359 , 50.52313,
49.48781, 50.80266, 53.15541, 51.87092, 52.39965, 52.58596,
55.23165, 52.76786, 55.52018, 55.73155, 55.94518, 53.73325,
51.74464, 51.99425, 49.21381, 52.79329],
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23.67883, 24.63125, 24.53975, 26.96615, 30.77296, 28.83607,
31.33676, 33.1206 , 34.93565, 33.52616, 35.6578 , 36.21198,
37.91905, 38.03854, 37.85329, 37.48819, 38.42327, 38.13686,
42.34263, 40.86445, 40.82556, 41.17397, 41.08039, 41.61213,
42.45519, 41.48734, 40.44974, 40.26473, 40.93513, 37.77828,
38.05632, 35.98014, 37.02082, 37.14096, 35.09395, 31.04348,
30.87281, 30.1669 , 29.07142, 26.60748, 26.22532, 24.21162,
24.20944, 22.61928, 17.25268, 17.32829, 15.31776, 13.97117,
14.5959 , 11.81341, 8.34311, 7.5008 , 0. , 5.83413,
5.46876, 8.07889, 8.10377, 12.28344, 11.70756, 14.58617,
16.50391, 20.31629, 22.0821 , 22.97453, 25.272 , 27.72545,
27.36277, 32.25835, 32.61786, 33.89607, 35.73057, 37.77336,
39.95231, 41.07814, 42.85021, 43.44198, 44.85383, 47.6269 ,
47.47827, 48.41191, 50.90451, 49.78713, 50.24847, 51.22179,
53.41837, 51.29034, 54.5929 , 54.6199 , 55.51699, 53.60744,
51.63282, 52.1621 , 49.27814, 52.86302],
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25.4293 , 25.08637, 25.21252, 27.64338, 31.75893, 30.27728,
32.09544, 33.81829, 35.54241, 34.40962, 36.74788, 37.08048,
39.08311, 39.0819 , 38.93651, 38.87541, 40.1212 , 39.73796,
43.41177, 42.22587, 42.24267, 42.24356, 42.4485 , 43.2428 ,
44.1862 , 42.91311, 41.86014, 41.36942, 42.5099 , 39.79016,
39.9811 , 37.25958, 38.04921, 37.87527, 36.84287, 32.13853,
31.9451 , 31.64604, 29.81017, 27.25091, 26.73652, 25.72832,
25.95339, 23.14501, 17.45389, 17.19026, 16.37099, 14.85007,
14.29243, 10.38626, 9.09498, 7.8237 , 5.83413, 0. ,
6.41631, 8.54307, 7.54798, 13.83722, 10.47169, 14.98237,
16.51711, 19.64403, 21.76762, 22.8833 , 25.40245, 27.78937,
27.30865, 32.95778, 32.79115, 34.89289, 36.70972, 38.8788 ,
41.05635, 42.15574, 44.18684, 44.13238, 45.71765, 48.95971,
48.28665, 49.59359, 52.1083 , 51.08147, 51.81738, 52.5753 ,
55.01953, 52.46332, 56.32081, 55.78484, 57.09844, 54.71573,
52.72249, 53.32 , 50.79307, 54.50537],
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22.19619, 22.31814, 22.16274, 24.84473, 28.54674, 27.08538,
29.33582, 31.46152, 33.22748, 32.12772, 34.53888, 34.29651,
36.66186, 36.62329, 37.02688, 36.52095, 38.22838, 37.88513,
41.79768, 40.89454, 40.88634, 41.4135 , 41.31527, 42.36568,
43.47623, 42.56542, 41.7082 , 41.39021, 42.56349, 39.73051,
40.13104, 38.02517, 39.25933, 38.78613, 37.83474, 33.7628 ,
33.52238, 33.19261, 31.49645, 29.58843, 29.27758, 27.49107,
27.98701, 25.76323, 20.41051, 20.41925, 19.20324, 17.3385 ,
17.74386, 14.34691, 12.01051, 10.40305, 5.46876, 6.41631,
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12.97536, 16.14407, 18.65999, 19.26615, 21.70973, 23.98596,
23.83313, 29.46502, 29.31874, 31.04096, 32.71498, 35.20378,
37.43086, 38.47346, 40.74117, 41.15986, 42.72724, 46.03943,
45.7643 , 46.92375, 49.81399, 49.07544, 49.48923, 50.83285,
53.02921, 51.02381, 54.85708, 54.85699, 56.10978, 54.39723,
52.29678, 53.08869, 50.68305, 54.16762],
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23.92894, 23.71491, 23.60181, 26.74278, 30.22502, 29.42086,
31.07569, 33.72103, 34.83971, 33.40582, 36.56434, 36.10593,
38.48701, 38.68787, 38.83153, 39.03388, 40.08247, 39.57072,
43.79152, 43.17864, 43.2909 , 43.87194, 43.35611, 44.39476,
45.37599, 45.03955, 43.69002, 43.28881, 44.52465, 41.74234,
42.11747, 40.01821, 41.2876 , 41.51105, 39.87093, 36.48198,
36.04839, 35.58516, 33.32921, 32.22904, 31.33041, 29.94017,
29.72961, 27.71115, 22.31093, 22.11879, 20.11261, 18.54959,
20.29587, 16.65127, 14.03886, 10.70596, 8.07889, 8.54307,
6.56254, 0. , 4.33833, 8.76183, 7.88595, 10.96004,
13.3731 , 17.00054, 17.6708 , 18.90909, 22.24521, 24.80605,
24.44948, 29.94102, 30.21988, 31.68858, 33.75574, 35.95484,
38.6216 , 39.86389, 41.58399, 42.28369, 44.38077, 47.67845,
47.02336, 48.24653, 51.67294, 50.62617, 51.37421, 52.55434,
55.1481 , 53.295 , 56.77537, 57.33105, 58.35886, 56.29047,
54.80877, 55.50578, 53.14199, 56.6705 ],
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22.48331, 22.41495, 22.19147, 24.89471, 28.99081, 28.13654,
29.78355, 32.12859, 33.64244, 31.97045, 35.07799, 34.99984,
37.36496, 37.66226, 37.52198, 38.04894, 38.99665, 38.9161 ,
42.99372, 41.97252, 42.33337, 42.72225, 42.53551, 43.77865,
44.76722, 44.26307, 43.19493, 42.72848, 44.12784, 41.66611,
42.08783, 39.69333, 41.02127, 41.02762, 39.81846, 36.14058,
35.83875, 35.3853 , 33.38918, 31.80973, 31.04823, 30.09775,
30.14266, 27.8258 , 22.02977, 22.02562, 21.17791, 19.51911,
20.04847, 16.01583, 14.66736, 11.78864, 8.10377, 7.54798,
5.82652, 4.33833, 0. , 9.49269, 5.60066, 10.13634,
11.30708, 15.06618, 16.60802, 17.5898 , 20.66387, 23.36406,
22.74647, 28.44725, 28.42199, 30.43171, 32.53739, 34.61086,
37.28059, 38.61696, 40.54339, 40.91422, 43.13823, 46.37182,
45.76609, 47.10957, 50.41253, 49.41508, 50.26066, 51.50842,
54.21112, 52.03406, 56.08765, 56.26153, 57.72116, 55.39809,
54.07596, 54.94413, 52.52346, 56.22352],
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23.70778, 23.87865, 23.8951 , 26.39705, 29.49656, 28.78396,
30.69899, 33.34453, 34.72378, 34.19075, 36.59537, 35.8496 ,
38.4644 , 39.09107, 39.07799, 39.2854 , 41.12947, 40.94059,
45.43309, 44.85097, 45.05862, 46.08496, 45.50379, 46.84558,
47.773 , 47.54766, 47.14492, 46.85017, 48.09543, 45.21051,
46.05367, 44.39596, 45.92867, 45.8564 , 44.45979, 41.01457,
40.75469, 40.18287, 38.71385, 37.16025, 37.12763, 34.51412,
35.2683 , 33.66319, 28.4554 , 28.80888, 26.23138, 24.47804,
25.72337, 22.86644, 19.35195, 17.10573, 12.28344, 13.83722,
9.42892, 8.76183, 9.49269, 0. , 10.77901, 10.05965,
11.4491 , 14.23453, 15.65154, 15.89031, 19.35493, 21.37071,
21.35245, 26.88469, 27.14093, 28.27884, 30.5466 , 33.50676,
36.4934 , 37.19752, 39.64894, 41.31134, 43.32302, 46.1664 ,
46.66713, 48.02232, 51.58657, 50.8496 , 51.44928, 53.70231,
55.7896 , 54.36972, 58.30467, 58.85498, 60.2241 , 59.29777,
57.3284 , 58.22332, 56.01087, 59.61459],
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20.61034, 20.79483, 20.57865, 22.80323, 27.01958, 26.43445,
27.88792, 30.4796 , 32.11209, 30.2786 , 33.28937, 33.74472,
36.32379, 36.48663, 36.60449, 37.05129, 38.17204, 38.2891 ,
42.39361, 41.45324, 42.17539, 42.30557, 42.54538, 43.53456,
44.99764, 44.95504, 43.81483, 43.10439, 45.13455, 42.9827 ,
43.28691, 40.98925, 42.53998, 42.62709, 41.3634 , 37.91637,
37.69173, 37.57579, 35.4746 , 34.28055, 32.98749, 32.6424 ,
32.68231, 30.48156, 24.40348, 24.85666, 24.1575 , 23.22298,
23.44249, 18.67511, 18.37439, 14.52165, 11.70756, 10.47169,
8.76253, 7.88595, 5.60066, 10.77901, 0. , 7.37848,
7.94763, 11.60285, 13.60009, 14.22662, 16.93863, 20.48684,
19.57347, 25.10732, 25.49894, 27.55298, 29.7128 , 32.13686,
34.70808, 36.23865, 38.20019, 38.77183, 41.07158, 44.37704,
43.59581, 45.48707, 49.01208, 48.08088, 49.19229, 50.28702,
53.56762, 51.16563, 55.41252, 55.96844, 57.4112 , 55.34975,
54.10888, 55.4712 , 53.09032, 56.86156],
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16.80414, 17.13811, 17.20223, 19.30856, 22.64011, 22.12388,
23.6909 , 26.68134, 28.69735, 26.83978, 29.56233, 29.52144,
32.42384, 32.61225, 33.43265, 33.33446, 34.9892 , 35.07866,
39.51926, 38.91288, 39.71804, 40.15065, 40.30517, 41.47749,
42.85482, 43.36693, 42.6301 , 42.13604, 44.19635, 41.96344,
42.38342, 40.81211, 42.80247, 42.66475, 41.50962, 38.79497,
38.4327 , 38.53515, 36.61224, 35.884 , 35.06947, 34.1041 ,
34.49442, 32.98226, 27.41917, 28.34247, 26.74297, 25.99818,
26.57937, 22.78851, 21.53225, 18.11827, 14.58617, 14.98237,
11.01716, 10.96004, 10.13634, 10.05965, 7.37848, 0. ,
6.85229, 8.33375, 10.64638, 10.34292, 12.47002, 15.48307,
15.00604, 20.17726, 20.87708, 22.2614 , 24.11224, 27.27657,
29.58244, 31.1899 , 33.13339, 34.40247, 36.49848, 39.87239,
39.52611, 41.18787, 45.18565, 44.54115, 45.31625, 47.01201,
50.01015, 48.42501, 52.3525 , 53.37068, 54.80933, 53.68554,
52.36036, 53.92575, 51.51095, 55.33784],
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17.54135, 18.05839, 17.67657, 19.43576, 23.11653, 23.17097,
24.95077, 27.47971, 29.37637, 27.6592 , 30.64956, 30.75883,
33.65172, 34.05121, 34.30145, 34.86519, 36.38785, 36.89862,
41.2064 , 40.27944, 41.17056, 41.69059, 41.79641, 43.3667 ,
45.0001 , 45.22628, 44.81877, 43.99537, 46.17291, 44.45906,
45.19904, 43.15676, 45.02922, 44.95803, 44.11761, 40.96397,
40.95094, 40.71094, 39.11164, 38.25288, 37.28719, 36.48373,
36.84283, 34.95939, 29.65847, 30.26402, 29.9642 , 28.67918,
28.95484, 24.49932, 24.01021, 20.90729, 16.50391, 16.51711,
12.97536, 13.3731 , 11.30708, 11.4491 , 7.94763, 6.85229,
0. , 7.42181, 9.81149, 8.48963, 11.54921, 15.39613,
14.38347, 19.86861, 19.77106, 22.06307, 24.50788, 26.82158,
29.77616, 30.96037, 33.5255 , 34.52259, 36.99302, 40.18245,
39.99496, 42.1269 , 45.88592, 45.21708, 46.21675, 48.21974,
51.36139, 49.18705, 54.05609, 54.84453, 56.72943, 55.20246,
53.91346, 55.78262, 53.64081, 57.31579],
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17.64634, 16.67094, 16.61788, 18.22819, 21.4745 , 21.90119,
22.44497, 25.54979, 27.27617, 26.30551, 29.02811, 28.63502,
31.82761, 32.23 , 32.81646, 33.37436, 35.95878, 36.20281,
40.11474, 39.6453 , 40.67256, 41.24556, 41.68827, 43.24129,
44.84355, 45.15693, 45.24839, 44.34038, 46.91914, 45.37185,
46.24403, 44.3192 , 46.2601 , 45.70734, 45.79608, 42.64609,
42.4804 , 42.71524, 40.61639, 39.99024, 39.461 , 38.65803,
39.96906, 37.85604, 32.03859, 33.37055, 32.63265, 31.37243,
31.3744 , 27.34599, 26.91727, 23.93647, 20.31629, 19.64403,
16.14407, 17.00054, 15.06618, 14.23453, 11.60285, 8.33375,
7.42181, 0. , 9.27097, 6.7636 , 9.28897, 10.82079,
10.31003, 16.92184, 15.97901, 18.91758, 20.92638, 24.2509 ,
26.79505, 28.28992, 30.96807, 32.00602, 34.44939, 37.75691,
37.62064, 40.16677, 43.88795, 43.79662, 44.82826, 47.13516,
50.10628, 48.05767, 53.25517, 53.82784, 55.9775 , 54.96514,
53.63403, 55.43629, 53.67147, 57.5573 ],
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18.13698, 16.67337, 17.05001, 18.64491, 21.88627, 23.31711,
22.73515, 25.74229, 26.28932, 26.20587, 29.40351, 28.32294,
32.1881 , 32.67538, 32.20425, 33.51843, 35.6227 , 36.05376,
39.74911, 40.59724, 40.65653, 41.85591, 40.95449, 43.27906,
44.80852, 45.74134, 44.99179, 44.26734, 47.23808, 45.70899,
46.80226, 44.52264, 46.99824, 46.90492, 46.84759, 44.26794,
43.60742, 44.28372, 42.02245, 41.63577, 40.85783, 41.22222,
41.25252, 39.53608, 34.25637, 35.15239, 34.33692, 33.06567,
33.67799, 30.249 , 28.70851, 25.20954, 22.0821 , 21.76762,
18.65999, 17.6708 , 16.60802, 15.65154, 13.60009, 10.64638,
9.81149, 9.27097, 0. , 5.4579 , 8.31392, 11.37399,
10.06637, 15.80099, 16.19604, 17.81404, 20.35224, 22.68455,
26.33321, 27.22424, 29.39485, 31.26857, 33.44303, 36.96176,
36.64784, 38.92403, 43.95773, 42.77504, 44.24492, 46.45457,
49.95585, 48.08682, 53.30444, 53.83046, 55.9695 , 55.1559 ,
54.03066, 55.76022, 54.37677, 58.38252],
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16.73796, 15.59013, 15.68349, 17.05169, 19.79573, 21.43302,
21.53386, 24.75989, 25.69016, 25.12388, 28.14274, 27.26777,
30.80285, 31.35308, 31.53711, 32.6792 , 34.90092, 35.34433,
39.34168, 39.49418, 40.19097, 41.23647, 40.88777, 42.89426,
44.71783, 45.58144, 45.27901, 44.39004, 47.21417, 45.86452,
47.00371, 45.11777, 47.39798, 47.20804, 47.06841, 44.55381,
44.22534, 44.57255, 42.49394, 42.34816, 41.59448, 41.17685,
41.86267, 40.08616, 34.87194, 36.01863, 35.4078 , 34.08613,
34.68713, 30.89222, 29.95311, 26.57818, 22.97453, 22.8833 ,
19.26615, 18.90909, 17.5898 , 15.89031, 14.22662, 10.34292,
8.48963, 6.7636 , 5.4579 , 0. , 6.20725, 9.55298,
8.01646, 13.88004, 13.47562, 15.73658, 18.32946, 21.00988,
24.41039, 25.357 , 28.05329, 29.56878, 32.10165, 35.5989 ,
35.30488, 37.94608, 42.47888, 41.88941, 43.10642, 45.66534,
48.94918, 47.14171, 52.39688, 53.39353, 55.47101, 54.71155,
53.48973, 55.54874, 54.10548, 57.89195],
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15.0992 , 15.29917, 15.30447, 14.82973, 18.19257, 19.21266,
19.39791, 22.16485, 23.88593, 23.22648, 25.25644, 25.1948 ,
28.93245, 29.36674, 29.60455, 30.40374, 32.5457 , 33.67934,
37.45432, 37.70761, 38.65435, 39.41798, 39.44077, 41.53307,
43.31817, 44.57787, 44.24326, 43.65807, 46.86937, 45.49593,
46.37995, 44.80329, 47.50405, 47.14969, 46.96281, 44.89301,
44.42682, 45.13821, 43.59005, 43.03802, 42.32162, 42.52243,
43.03579, 41.63043, 36.40332, 37.78748, 37.27436, 36.44189,
36.28302, 32.98648, 32.23778, 28.98693, 25.272 , 25.40245,
21.70973, 22.24521, 20.66387, 19.35493, 16.93863, 12.47002,
11.54921, 9.28897, 8.31392, 6.20725, 0. , 8.05145,
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21.18762, 22.23008, 25.12185, 26.96778, 29.22174, 32.55304,
32.67088, 35.01998, 40.03592, 39.3736 , 40.65807, 43.06865,
46.5909 , 44.99134, 50.2539 , 51.23541, 53.43403, 53.31284,
52.11044, 54.48838, 52.87226, 56.74007],
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16.73965, 14.46026, 14.95815, 15.51568, 16.9958 , 18.09438,
17.15086, 20.06477, 21.52732, 22.09752, 24.3272 , 22.50728,
26.4393 , 27.44256, 27.68888, 28.64096, 31.91806, 32.25061,
35.8801 , 36.65188, 37.60561, 38.64347, 38.47113, 41.05796,
42.17357, 43.24457, 44.00885, 43.18833, 46.30617, 45.23056,
46.44777, 44.7664 , 47.43771, 46.86 , 47.70312, 45.34457,
44.91905, 45.55069, 43.80397, 43.69836, 43.57751, 43.43884,
44.67317, 43.15796, 38.15373, 39.81268, 38.82324, 37.65905,
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23.98596, 24.80605, 23.36406, 21.37071, 20.48684, 15.48307,
15.39613, 10.82079, 11.37399, 9.55298, 8.05145, 0. ,
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18.50621, 19.6109 , 22.38789, 24.44886, 26.89026, 29.8127 ,
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44.60558, 43.27327, 48.91205, 49.33654, 52.18163, 52.20071,
51.11608, 53.03856, 51.85091, 55.85643],
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17.26961, 20.06272, 21.55272, 21.38396, 23.56296, 23.05361,
26.65776, 27.60226, 27.2861 , 28.81112, 31.28384, 32.36628,
35.90349, 36.33936, 37.35235, 38.26693, 38.21591, 40.77052,
42.00564, 43.23535, 43.62399, 42.95227, 46.18952, 45.08133,
46.32251, 44.57585, 47.28364, 46.8637 , 47.32522, 45.22525,
44.77389, 45.47875, 43.89376, 43.42436, 43.1737 , 43.36506,
44.36291, 42.86376, 37.65245, 39.32254, 38.79999, 37.7809 ,
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23.83313, 24.44948, 22.74647, 21.35245, 19.57347, 15.00604,
14.38347, 10.31003, 10.06637, 8.01646, 5.69215, 5.15882,
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18.54691, 19.63637, 22.4477 , 24.28556, 26.89341, 29.828 ,
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44.64997, 43.08337, 48.79588, 49.29285, 52.03523, 51.96351,
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15.3146 , 16.68845, 16.70277, 14.33961, 16.33478, 17.67573,
16.50911, 19.02226, 20.82185, 19.8089 , 20.85461, 22.12662,
25.03495, 26.2458 , 25.60395, 27.30426, 28.86779, 30.7808 ,
34.72309, 34.78051, 36.34129, 37.14527, 37.33843, 39.41463,
40.73932, 43.03554, 43.42716, 42.93121, 46.3353 , 45.40294,
46.58154, 45.54288, 48.66654, 48.70376, 48.293 , 47.30472,
46.85295, 47.62256, 46.64783, 46.41609, 45.94993, 46.36946,
47.1119 , 46.50258, 41.47684, 43.59766, 42.81333, 42.43773,
42.17949, 39.54874, 38.86784, 35.92599, 32.25835, 32.95778,
29.46502, 29.94102, 28.44725, 26.88469, 25.10732, 20.17726,
19.86861, 16.92184, 15.80099, 13.88004, 9.9497 , 10.42401,
7.97303, 0. , 7.5317 , 5.31432, 7.67385, 11.29427,
13.88518, 15.65731, 17.41581, 21.03678, 23.50462, 25.23083,
26.39159, 28.81917, 34.13332, 33.45212, 35.14618, 38.06477,
41.77849, 40.61566, 45.83126, 47.30105, 49.72211, 50.48444,
50.07272, 52.69689, 50.98398, 55.16405],
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16.21818, 14.41634, 14.6234 , 13.3435 , 14.10467, 16.69031,
14.97885, 17.40359, 18.79088, 18.83186, 20.80185, 19.74132,
23.12291, 24.4287 , 24.28611, 26.30338, 28.98518, 30.11484,
33.54021, 33.80123, 35.23204, 36.28322, 36.35944, 39.1773 ,
40.54667, 41.97252, 43.097 , 42.14583, 45.46555, 45.13354,
46.66496, 45.13382, 47.8922 , 47.41032, 48.42568, 46.71893,
46.45624, 47.08008, 45.65345, 45.84523, 45.7186 , 45.84661,
47.23168, 45.86231, 41.28355, 43.22273, 43.14353, 42.01543,
41.8008 , 39.14111, 38.83989, 36.4427 , 32.61786, 32.79115,
29.31874, 30.21988, 28.42199, 27.14093, 25.49894, 20.87708,
19.77106, 15.97901, 16.19604, 13.47562, 11.36293, 8.2677 ,
7.41391, 7.5317 , 0. , 6.63347, 8.51215, 10.2156 ,
13.17845, 14.2086 , 17.41713, 18.82641, 21.82783, 24.56628,
25.20903, 28.13747, 32.64308, 32.72029, 34.13216, 37.76093,
40.74152, 39.28459, 45.54548, 46.22894, 49.39464, 49.45139,
48.79067, 51.31535, 50.31884, 54.28067],
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14.84698, 17.54345, 18.59526, 18.86371, 19.89348, 19.63274,
22.70202, 24.17496, 23.68602, 25.2772 , 27.6702 , 29.01616,
32.87432, 33.49258, 34.77337, 36.14132, 35.80693, 38.1895 ,
39.4803 , 41.7482 , 42.57723, 41.96176, 45.29483, 44.55667,
46.07288, 45.13769, 48.31191, 48.23058, 48.33951, 47.3816 ,
46.96242, 47.68002, 46.63616, 46.92581, 46.70514, 46.8006 ,
47.84897, 47.29211, 42.71965, 44.89829, 44.0194 , 43.33093,
43.46606, 41.24033, 40.22175, 37.60689, 33.89607, 34.89289,
31.04096, 31.68858, 30.43171, 28.27884, 27.55298, 22.2614 ,
22.06307, 18.91758, 17.81404, 15.73658, 12.71091, 10.41686,
9.92165, 5.31432, 6.63347, 0. , 4.70483, 7.62293,
10.77344, 12.04317, 14.09367, 18.36526, 20.64699, 22.23753,
23.95215, 26.43932, 31.57022, 31.17569, 32.66191, 36.26804,
39.40728, 38.57361, 43.9427 , 45.43841, 47.97621, 49.1094 ,
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16.80116, 16.76691, 16.87216, 14.70497, 14.07395, 15.74665,
14.0348 , 16.56831, 17.84671, 18.34015, 18.69289, 17.89876,
21.31299, 22.32386, 22.83922, 23.65439, 26.58669, 27.92706,
31.3026 , 32.35566, 33.6225 , 34.9677 , 34.8564 , 37.36602,
38.72058, 41.05749, 41.90128, 41.49189, 44.96068, 44.24469,
45.61367, 45.036 , 48.29145, 47.81376, 48.32094, 47.69802,
47.13319, 48.15121, 47.08335, 47.45754, 47.35142, 47.56391,
48.73064, 48.17182, 43.82151, 46.04871, 45.29074, 44.64622,
44.62028, 42.66911, 41.76582, 39.32328, 35.73057, 36.70972,
32.71498, 33.75574, 32.53739, 30.5466 , 29.7128 , 24.11224,
24.50788, 20.92638, 20.35224, 18.32946, 14.59198, 12.23247,
12.10268, 7.67385, 8.51215, 4.70483, 0. , 7.52323,
8.61132, 9.93048, 12.5578 , 16.40777, 18.25766, 20.46284,
22.14114, 24.25493, 29.68935, 29.77053, 30.84631, 34.5401 ,
37.42484, 37.09933, 42.31915, 43.87867, 46.39273, 48.0183 ,
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17.15962, 16.68857, 16.49137, 14.77414, 12.99207, 15.65608,
13.16584, 15.07742, 15.16618, 15.42575, 17.03854, 15.79792,
18.64901, 20.26882, 19.6321 , 21.82505, 23.92989, 25.32419,
28.63784, 29.75799, 30.92734, 32.65462, 31.85679, 34.97812,
36.16405, 38.72517, 39.82617, 39.07646, 42.56432, 42.6187 ,
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46.71132, 47.49823, 46.48834, 47.51112, 47.22145, 47.96634,
48.82056, 48.3848 , 44.61234, 46.77149, 46.65033, 45.80397,
46.06782, 44.16304, 43.56084, 41.32062, 37.77336, 38.8788 ,
35.20378, 35.95484, 34.61086, 33.50676, 32.13686, 27.27657,
26.82158, 24.2509 , 22.68455, 21.00988, 18.34641, 15.69246,
15.51953, 11.29427, 10.2156 , 7.62293, 7.52323, 0. ,
5.61253, 7.21393, 8.09939, 12.2139 , 14.96738, 16.37581,
17.99627, 20.35805, 25.70473, 25.34467, 26.89611, 30.90733,
34.04257, 33.31594, 39.15504, 40.74492, 43.65432, 44.59624,
44.58934, 47.23448, 46.50554, 50.1937 ],
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18.1004 , 18.02822, 17.85663, 15.56051, 12.74353, 14.72969,
12.28025, 13.83543, 14.82818, 14.24007, 14.62848, 14.13342,
16.46835, 17.63621, 18.43043, 19.44844, 21.86083, 23.29639,
26.36769, 27.30116, 29.00015, 30.32245, 30.32951, 33.00745,
34.29426, 37.14338, 38.47462, 37.79461, 41.36339, 41.59934,
43.10472, 42.69738, 46.0658 , 45.78045, 46.66074, 46.77432,
46.36086, 47.35146, 46.45531, 47.68894, 47.41203, 48.21386,
49.2878 , 49.04825, 45.47536, 47.87025, 47.77203, 47.25139,
47.29764, 45.54425, 45.32808, 43.23691, 39.95231, 41.05635,
37.43086, 38.6216 , 37.28059, 36.4934 , 34.70808, 29.58244,
29.77616, 26.79505, 26.33321, 24.41039, 21.18762, 18.50621,
18.54691, 13.88518, 13.17845, 10.77344, 8.61132, 5.61253,
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14.78111, 17.10354, 22.23733, 22.66218, 23.80291, 27.72151,
30.83746, 30.51189, 35.9164 , 37.93316, 40.70448, 42.1526 ,
42.22162, 45.16766, 44.28871, 47.87966],
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20.22697, 19.23566, 19.18505, 16.74031, 13.92433, 16.18704,
14.13143, 14.50581, 14.49505, 16.84456, 16.26612, 14.08034,
16.81846, 18.1981 , 18.32631, 19.69742, 22.75265, 24.12436,
26.4844 , 28.38011, 29.40958, 31.15585, 30.47848, 34.10653,
35.27955, 37.61494, 39.17248, 38.59134, 42.23577, 42.40437,
44.24015, 43.68518, 47.00178, 46.55168, 47.9282 , 47.78838,
47.34189, 48.3686 , 47.75785, 48.68155, 48.74309, 49.40067,
50.56509, 50.09211, 47.05548, 49.21038, 49.32322, 48.43046,
48.35452, 47.06384, 46.48406, 44.71995, 41.07814, 42.15574,
38.47346, 39.86389, 38.61696, 37.19752, 36.23865, 31.1899 ,
30.96037, 28.28992, 27.22424, 25.357 , 22.23008, 19.6109 ,
19.63637, 15.65731, 14.2086 , 12.04317, 9.93048, 7.21393,
6.28487, 0. , 7.47856, 9.53171, 11.18018, 13.01788,
15.47366, 17.28446, 22.4102 , 22.68226, 23.79207, 28.38873,
30.63132, 30.55106, 36.61026, 37.86975, 41.02305, 43.05683,
42.18162, 45.17244, 45.04898, 48.29225],
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21.04317, 20.91886, 20.91421, 18.93591, 15.69868, 17.54084,
14.59832, 15.50799, 15.15638, 15.52977, 15.56155, 14.92898,
16.44223, 18.06242, 17.7009 , 19.3097 , 21.11808, 22.42396,
25.34082, 27.09472, 28.36382, 30.05495, 29.27892, 32.18818,
33.02234, 36.50124, 37.86386, 37.2521 , 40.86225, 41.24915,
42.9754 , 42.70208, 46.27576, 46.44799, 47.12264, 47.81124,
47.27088, 48.33511, 47.61879, 49.1594 , 48.88315, 49.99774,
50.75426, 50.93521, 47.78609, 50.23529, 49.88537, 49.49756,
49.81537, 48.51593, 47.93843, 45.92899, 42.85021, 44.18684,
40.74117, 41.58399, 40.54339, 39.64894, 38.20019, 33.13339,
33.5255 , 30.96807, 29.39485, 28.05329, 25.12185, 22.38789,
22.4477 , 17.41581, 17.41713, 14.09367, 12.5578 , 8.09939,
5.75247, 7.47856, 0. , 9.46928, 10.77391, 10.07175,
12.78621, 14.47174, 20.14208, 19.79391, 21.44302, 25.49215,
28.64581, 28.7825 , 33.76637, 36.05478, 38.72334, 40.7433 ,
41.16185, 43.95332, 43.33299, 46.9185 ],
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22.01882, 19.93191, 19.70914, 17.75143, 14.25548, 16.84414,
13.82806, 13.55086, 12.82821, 13.17945, 13.83998, 11.06895,
12.42447, 13.71252, 14.75941, 17.16471, 18.7693 , 19.7537 ,
21.25983, 23.18208, 25.0391 , 26.14201, 25.8884 , 29.92886,
30.89456, 33.46255, 34.99443, 34.09993, 37.9703 , 39.18714,
40.85532, 40.23943, 43.40774, 43.06789, 45.05578, 45.64705,
45.18382, 46.28713, 45.29908, 47.14392, 46.89426, 48.4731 ,
49.53957, 48.90653, 46.48006, 48.6807 , 49.61055, 48.83554,
48.72589, 47.55693, 47.98325, 46.36053, 43.44198, 44.13238,
41.15986, 42.28369, 40.91422, 41.31134, 38.77183, 34.40247,
34.52259, 32.00602, 31.26857, 29.56878, 26.96778, 24.44886,
24.28556, 21.03678, 18.82641, 18.36526, 16.40777, 12.2139 ,
9.62946, 9.53171, 9.46928, 0. , 7.70034, 11.03984,
9.3173 , 11.00972, 16.06011, 16.8982 , 18.3223 , 22.22843,
24.9604 , 24.69864, 30.94594, 32.41159, 35.92687, 36.56528,
36.93542, 40.15198, 40.34494, 43.38612],
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23.10616, 21.22647, 21.64589, 19.27456, 15.27649, 17.82539,
14.44424, 13.77702, 12.71296, 15.12571, 13.72169, 11.02782,
12.98025, 12.60611, 14.24738, 14.47088, 18.18955, 19.01006,
19.4387 , 22.41711, 22.59333, 24.6254 , 23.90214, 27.45379,
29.48465, 32.11582, 33.29005, 32.53784, 36.62617, 37.89513,
39.73088, 39.23902, 42.66151, 41.80521, 44.3409 , 44.93698,
44.30438, 46.10429, 45.03967, 46.92675, 46.8966 , 48.58388,
49.65108, 49.34591, 47.17699, 49.53981, 50.40164, 49.72558,
49.68722, 48.77945, 48.86364, 47.3359 , 44.85383, 45.71765,
42.72724, 44.38077, 43.13823, 43.32302, 41.07158, 36.49848,
36.99302, 34.44939, 33.44303, 32.10165, 29.22174, 26.89026,
26.89341, 23.50462, 21.82783, 20.64699, 18.25766, 14.96738,
11.75449, 11.18018, 10.77391, 7.70034, 0. , 9.07328,
6.77896, 9.73201, 14.62719, 15.04701, 15.37031, 19.6617 ,
22.50593, 22.25054, 28.56357, 29.72752, 32.81706, 34.96093,
34.29057, 37.67062, 38.17835, 41.31302],
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25.70386, 25.60087, 25.6927 , 22.94456, 19.74988, 20.46911,
17.8433 , 16.34443, 15.97897, 17.63489, 14.82471, 15.65033,
14.62265, 16.39878, 14.81143, 16.52024, 18.2176 , 19.94131,
21.35453, 22.75371, 24.07796, 25.64368, 25.36182, 28.27133,
28.8475 , 32.19497, 34.59372, 33.99566, 37.63698, 38.80147,
40.79164, 40.71097, 44.23342, 44.2389 , 45.66062, 46.70672,
46.30564, 47.57535, 47.61192, 49.05016, 49.20629, 50.70632,
51.8766 , 52.28837, 49.92586, 52.72328, 52.96687, 52.67093,
52.42257, 51.948 , 51.79319, 50.52313, 47.6269 , 48.95971,
46.03943, 47.67845, 46.37182, 46.1664 , 44.37704, 39.87239,
40.18245, 37.75691, 36.96176, 35.5989 , 32.55304, 29.8127 ,
29.828 , 25.23083, 24.56628, 22.23753, 20.46284, 16.37581,
13.17307, 13.01788, 10.07175, 11.03984, 9.07328, 0. ,
8.87214, 9.85187, 12.31734, 12.2625 , 14.04632, 18.81453,
21.19061, 21.12454, 27.04242, 28.49102, 31.8115 , 34.8203 ,
35.12966, 38.15204, 38.01118, 41.47549],
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25.33855, 24.01222, 24.18448, 21.91537, 18.25877, 20.57828,
16.98162, 16.4955 , 14.73869, 15.48099, 14.34678, 14.30857,
13.85173, 13.84417, 14.39659, 15.93936, 17.45544, 18.33339,
18.66931, 20.88887, 21.93502, 23.38049, 23.14462, 25.75202,
27.86781, 31.24603, 32.25062, 31.15287, 35.45185, 37.34563,
39.14055, 38.75821, 42.09818, 41.92408, 43.92436, 45.20662,
44.68842, 46.38933, 45.31081, 47.7489 , 47.28112, 49.48718,
50.44647, 50.39015, 48.24647, 50.9 , 51.90866, 51.57562,
51.63792, 50.60804, 51.20293, 49.48781, 47.47827, 48.28665,
45.7643 , 47.02336, 45.76609, 46.66713, 43.59581, 39.52611,
39.99496, 37.62064, 36.64784, 35.30488, 32.67088, 30.67153,
30.30008, 26.39159, 25.20903, 23.95215, 22.14114, 17.99627,
14.78111, 15.47366, 12.78621, 9.3173 , 6.77896, 8.87214,
0. , 8.06218, 11.429 , 11.46571, 13.13148, 16.10375,
20.41288, 19.36076, 25.3713 , 27.60118, 30.25563, 31.87386,
32.4665 , 36.03614, 36.48471, 39.63076],
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26.90823, 26.23519, 26.08005, 23.84675, 20.80091, 21.7296 ,
19.04357, 17.40327, 16.7043 , 16.55105, 15.01213, 14.46629,
13.32047, 13.90252, 14.09233, 15.41702, 15.00264, 16.81857,
16.58331, 19.50611, 20.62995, 21.94394, 21.09032, 25.34647,
25.48297, 29.25163, 30.55199, 30.43379, 34.21791, 35.75256,
37.3534 , 37.46691, 41.14137, 40.96925, 42.83903, 44.90814,
44.1482 , 45.72293, 45.41523, 47.3948 , 47.34997, 49.72993,
50.26925, 50.58997, 49.03127, 51.39158, 52.35132, 52.08085,
51.8305 , 51.67431, 51.97604, 50.80266, 48.41191, 49.59359,
46.92375, 48.24653, 47.10957, 48.02232, 45.48707, 41.18787,
42.1269 , 40.16677, 38.92403, 37.94608, 35.01998, 32.99654,
32.67363, 28.81917, 28.13747, 26.43932, 24.25493, 20.35805,
17.10354, 17.28446, 14.47174, 11.00972, 9.73201, 9.85187,
8.06218, 0. , 9.67155, 9.04695, 10.17736, 13.59906,
16.54233, 17.9564 , 22.847 , 24.60167, 27.9245 , 29.98479,
31.1793 , 34.37541, 34.48999, 37.48156],
[ 37.58041, 35.07482, 33.73965, 33.55744, 33.36934, 32.1432 ,
30.27089, 29.55426, 29.35354, 27.42168, 23.91183, 24.02904,
22.24141, 20.09447, 19.42872, 19.58731, 17.11687, 17.74227,
13.81794, 14.58239, 14.84183, 15.60782, 15.51133, 15.99741,
15.29044, 15.96133, 18.16191, 18.90934, 19.56871, 22.44188,
22.56247, 25.58682, 28.63669, 27.85509, 31.08457, 33.50089,
35.4027 , 35.83383, 38.8066 , 38.73615, 40.98259, 43.03585,
42.80237, 43.99917, 44.16385, 46.55753, 46.70348, 48.60454,
49.99599, 50.40001, 49.42958, 52.21003, 53.40064, 53.1481 ,
52.84663, 52.94916, 53.74581, 53.15541, 50.90451, 52.1083 ,
49.81399, 51.67294, 50.41253, 51.58657, 49.01208, 45.18565,
45.88592, 43.88795, 43.95773, 42.47888, 40.03592, 37.56207,
37.5192 , 34.13332, 32.64308, 31.57022, 29.68935, 25.70473,
22.23733, 22.4102 , 20.14208, 16.06011, 14.62719, 12.31734,
11.429 , 9.67155, 0. , 6.56064, 6.38088, 10.37223,
11.02495, 11.31594, 17.26136, 19.1381 , 22.65982, 24.77406,
25.9365 , 29.3083 , 29.80644, 32.34705],
[ 36.97612, 34.08161, 33.6759 , 33.39091, 32.26088, 31.53822,
29.34631, 29.01695, 29.00965, 26.76934, 24.08524, 24.20871,
22.05366, 19.53993, 18.50832, 18.96449, 16.34701, 17.97385,
14.45423, 15.61773, 13.11227, 15.3568 , 13.46033, 15.0617 ,
14.5311 , 15.86852, 17.02272, 18.07516, 17.40934, 20.82485,
20.68579, 24.49213, 26.61145, 26.08889, 29.69294, 31.99846,
33.98145, 33.96711, 37.42541, 37.92498, 39.58649, 41.8455 ,
41.36941, 42.7842 , 43.17606, 45.24034, 45.24956, 47.90274,
48.57102, 49.3039 , 48.33632, 51.04052, 52.18807, 52.11595,
51.78041, 52.10773, 52.60551, 51.87092, 49.78713, 51.08147,
49.07544, 50.62617, 49.41508, 50.8496 , 48.08088, 44.54115,
45.21708, 43.79662, 42.77504, 41.88941, 39.3736 , 37.45707,
37.10411, 33.45212, 32.72029, 31.17569, 29.77053, 25.34467,
22.66218, 22.68226, 19.79391, 16.8982 , 15.04701, 12.2625 ,
11.46571, 9.04695, 6.56064, 0. , 5.98419, 8.35946,
11.68013, 10.99161, 17.01812, 18.26248, 21.8055 , 23.90279,
25.4595 , 28.64282, 28.83705, 32.02712],
[ 37.4974 , 34.96767, 34.04663, 34.49413, 33.40864, 31.97442,
29.92087, 29.67471, 29.70327, 27.66108, 24.27307, 24.33682,
22.98183, 20.64083, 20.11721, 20.24747, 17.47794, 18.06633,
14.59398, 14.72379, 14.67681, 14.63636, 13.79958, 14.77595,
14.07159, 14.98222, 15.54819, 17.34202, 16.72036, 19.82573,
20.34994, 23.73966, 26.02174, 25.78955, 28.68309, 30.98915,
32.97956, 33.65132, 36.96229, 36.83463, 38.84249, 41.35057,
40.89437, 42.32976, 42.72795, 45.04445, 45.31637, 47.29044,
48.20799, 49.05992, 48.54484, 51.18106, 52.39054, 52.16829,
52.05071, 52.46879, 52.8835 , 52.39965, 50.24847, 51.81738,
49.48923, 51.37421, 50.26066, 51.44928, 49.19229, 45.31625,
46.21675, 44.82826, 44.24492, 43.10642, 40.65807, 38.73435,
38.59252, 35.14618, 34.13216, 32.66191, 30.84631, 26.89611,
23.80291, 23.79207, 21.44302, 18.3223 , 15.37031, 14.04632,
13.13148, 10.17736, 6.38088, 5.98419, 0. , 7.87813,
8.5264 , 10.22297, 15.17486, 17.26896, 20.15363, 23.01967,
23.76411, 27.20938, 27.40981, 30.03519],
[ 39.19126, 36.59085, 35.63369, 36.29427, 34.83176, 34.20046,
31.66778, 31.85062, 31.74665, 29.75946, 27.16596, 26.71437,
25.33998, 23.14301, 22.55747, 21.6386 , 19.00668, 21.34884,
17.7774 , 17.00739, 17.10835, 16.4597 , 13.68436, 14.59106,
12.69685, 13.66391, 14.56199, 14.70928, 15.08113, 16.70077,
17.57016, 21.92186, 22.74625, 22.49509, 26.09517, 28.78806,
30.08218, 30.88072, 34.28354, 34.6773 , 36.13211, 39.45815,
38.88697, 40.70953, 41.05225, 43.71142, 43.29447, 46.48555,
46.79335, 47.89894, 47.60107, 50.27656, 51.76294, 52.09858,
51.83186, 52.27757, 53.24671, 52.58596, 51.22179, 52.5753 ,
50.83285, 52.55434, 51.50842, 53.70231, 50.28702, 47.01201,
48.21974, 47.13516, 46.45457, 45.66534, 43.06865, 41.86474,
41.46073, 38.06477, 37.76093, 36.26804, 34.5401 , 30.90733,
27.72151, 28.38873, 25.49215, 22.22843, 19.6617 , 18.81453,
16.10375, 13.59906, 10.37223, 8.35946, 7.87813, 0. ,
8.67141, 8.22265, 10.68938, 14.39115, 15.81638, 18.19258,
20.24196, 24.13398, 23.94398, 26.50431],
[ 41.96371, 39.56174, 38.24726, 39.09789, 38.18059, 36.96213,
35.17056, 34.7836 , 34.68077, 33.0935 , 30.02343, 29.08875,
28.35413, 25.73473, 25.22857, 25.58849, 22.61177, 22.96009,
18.83897, 18.61744, 19.10648, 17.9459 , 16.58338, 16.3054 ,
13.75561, 14.86599, 15.3057 , 16.17006, 16.01239, 18.83691,
17.81885, 20.66609, 23.58481, 23.83891, 26.05857, 28.57053,
30.29887, 31.70992, 34.64723, 34.46336, 36.84814, 40.11168,
39.62182, 41.06713, 42.00461, 44.46337, 44.9994 , 47.1459 ,
48.1779 , 49.234 , 49.68564, 52.28684, 53.60591, 53.53316,
53.22438, 54.53359, 55.09278, 55.23165, 53.41837, 55.01953,
53.02921, 55.1481 , 54.21112, 55.7896 , 53.56762, 50.01015,
51.36139, 50.10628, 49.95585, 48.94918, 46.5909 , 44.60558,
44.64997, 41.77849, 40.74152, 39.40728, 37.42484, 34.04257,
30.83746, 30.63132, 28.64581, 24.9604 , 22.50593, 21.19061,
20.41288, 16.54233, 11.02495, 11.68013, 8.5264 , 8.67141,
0. , 8.20946, 9.70989, 11.26803, 13.99325, 18.01633,
18.62262, 21.68822, 22.49918, 24.09327],
[ 39.49224, 37.35437, 36.06871, 36.46602, 35.81903, 35.11644,
33.31352, 32.77038, 32.64932, 30.98471, 28.55089, 27.8246 ,
26.6982 , 23.91935, 23.0396 , 23.63285, 20.87814, 22.50932,
18.33698, 17.9266 , 17.05555, 16.78672, 15.70851, 15.56181,
12.45704, 12.41707, 12.64367, 13.04202, 13.78221, 15.85836,
16.39775, 18.42641, 21.28107, 20.37192, 23.59887, 27.01304,
29.00976, 29.12309, 31.85059, 31.84197, 34.73249, 37.08534,
36.88549, 38.47232, 39.14698, 41.62923, 41.76229, 44.6641 ,
45.75658, 46.43048, 46.61442, 49.36971, 51.35824, 51.2622 ,
50.71905, 51.56906, 52.73899, 52.76786, 51.29034, 52.46332,
51.02381, 53.295 , 52.03406, 54.36972, 51.16563, 48.42501,
49.18705, 48.05767, 48.08682, 47.14171, 44.99134, 43.27327,
43.08337, 40.61566, 39.28459, 38.57361, 37.09933, 33.31594,
30.51189, 30.55106, 28.7825 , 24.69864, 22.25054, 21.12454,
19.36076, 17.9564 , 11.31594, 10.99161, 10.22297, 8.22265,
8.20946, 0. , 10.97595, 10.25467, 13.79501, 15.37994,
15.98122, 19.6484 , 20.7999 , 23.08624],
[ 44.24451, 42.00158, 40.78921, 41.84873, 40.65885, 39.86917,
37.56416, 38.06911, 37.91062, 36.65424, 33.83448, 32.39523,
32.11611, 30.1514 , 29.71055, 28.70622, 25.97138, 28.30391,
23.71274, 22.92496, 23.72982, 21.70309, 18.99807, 17.98122,
16.48731, 15.52539, 16.45475, 15.86513, 17.09382, 15.60841,
15.34486, 19.3634 , 21.00584, 20.98593, 22.7285 , 25.56683,
26.63001, 28.97938, 31.58249, 32.48614, 33.17741, 37.64673,
37.35607, 38.78739, 39.86511, 43.11111, 42.8692 , 45.39504,
46.03133, 47.85874, 48.6812 , 51.53462, 52.66349, 53.32599,
53.35513, 54.55259, 55.52021, 55.52018, 54.5929 , 56.32081,
54.85708, 56.77537, 56.08765, 58.30467, 55.41252, 52.3525 ,
54.05609, 53.25517, 53.30444, 52.39688, 50.2539 , 48.91205,
48.79588, 45.83126, 45.54548, 43.9427 , 42.31915, 39.15504,
35.9164 , 36.61026, 33.76637, 30.94594, 28.56357, 27.04242,
25.3713 , 22.847 , 17.26136, 17.01812, 15.17486, 10.68938,
9.70989, 10.97595, 0. , 11.45306, 8.11042, 12.83722,
15.11178, 18.41451, 17.69405, 18.89004],
[ 44.49713, 42.65467, 41.34813, 41.95262, 41.40321, 40.59916,
39.27059, 38.63774, 38.78521, 37.30058, 35.47091, 33.86684,
32.88203, 29.62866, 29.41731, 30.21742, 27.04819, 28.4628 ,
24.45456, 24.15302, 22.93954, 21.98327, 20.56008, 20.15022,
16.18279, 16.68747, 15.71403, 15.06125, 15.61569, 17.8028 ,
15.15469, 16.24486, 19.89187, 20.20119, 22.24654, 25.4267 ,
27.03646, 27.45576, 30.04064, 29.86623, 33.3556 , 36.20666,
35.71787, 37.64475, 39.12616, 40.95347, 41.88106, 45.2002 ,
46.10588, 47.20917, 48.31756, 50.93333, 52.69263, 52.90649,
51.86422, 53.99784, 54.91969, 55.73155, 54.6199 , 55.78484,
54.85699, 57.33105, 56.26153, 58.85498, 55.96844, 53.37068,
54.84453, 53.82784, 53.83046, 53.39353, 51.23541, 49.33654,
49.29285, 47.30105, 46.22894, 45.43841, 43.87867, 40.74492,
37.93316, 37.86975, 36.05478, 32.41159, 29.72752, 28.49102,
27.60118, 24.60167, 19.1381 , 18.26248, 17.26896, 14.39115,
11.26803, 10.25467, 11.45306, 0. , 9.27356, 12.57009,
12.95849, 14.74353, 15.81852, 18.51871],
[ 46.20998, 44.21824, 43.00012, 44.21519, 43.17206, 42.25278,
40.62456, 40.78472, 40.83826, 39.65202, 37.51809, 35.84499,
35.32819, 33.12758, 32.39176, 32.68447, 29.54295, 31.64773,
27.512 , 26.40181, 26.36839, 24.07691, 22.44251, 21.20001,
18.19724, 18.30724, 16.86429, 16.67207, 17.24015, 15.28365,
14.83316, 17.24548, 18.45627, 18.99761, 20.53253, 23.23683,
24.48703, 26.55069, 28.92462, 29.37943, 31.06652, 35.37051,
34.81861, 36.9269 , 38.19473, 40.97874, 41.23793, 44.23507,
44.94675, 46.79585, 48.12534, 50.99637, 52.29538, 52.95174,
52.68216, 54.65517, 55.45876, 55.94518, 55.51699, 57.09844,
56.10978, 58.35886, 57.72116, 60.2241 , 57.4112 , 54.80933,
56.72943, 55.9775 , 55.9695 , 55.47101, 53.43403, 52.18163,
52.03523, 49.72211, 49.39464, 47.97621, 46.39273, 43.65432,
40.70448, 41.02305, 38.72334, 35.92687, 32.81706, 31.8115 ,
30.25563, 27.9245 , 22.65982, 21.8055 , 20.15363, 15.81638,
13.99325, 13.79501, 8.11042, 9.27356, 0. , 11.3311 ,
10.74328, 12.86819, 13.30844, 14.52224],
[ 45.17665, 42.7808 , 42.36618, 43.15904, 41.53149, 42.35218,
40.2062 , 39.75408, 39.61926, 39.12975, 37.42083, 36.03478,
35.61998, 33.46496, 32.91178, 31.55284, 30.34684, 32.1907 ,
27.97503, 27.03924, 26.99544, 26.11801, 22.97965, 21.39029,
18.82112, 16.95519, 16.85299, 15.02326, 16.33925, 15.19425,
14.19401, 15.15315, 16.11799, 15.27863, 16.26812, 21.19257,
22.05865, 22.69609, 24.27898, 25.34313, 27.70613, 31.85248,
31.64177, 33.11543, 33.86518, 37.50522, 37.14262, 41.08682,
41.40908, 42.67964, 44.56241, 47.03863, 49.4784 , 49.96028,
49.67751, 51.26881, 53.12569, 53.73325, 53.60744, 54.71573,
54.39723, 56.29047, 55.39809, 59.29777, 55.34975, 53.68554,
55.20246, 54.96514, 55.1559 , 54.71155, 53.31284, 52.20071,
51.96351, 50.48444, 49.45139, 49.1094 , 48.0183 , 44.59624,
42.1526 , 43.05683, 40.7433 , 36.56528, 34.96093, 34.8203 ,
31.87386, 29.98479, 24.77406, 23.90279, 23.01967, 18.19258,
18.01633, 15.37994, 12.83722, 12.57009, 11.3311 , 0. ,
9.90814, 11.78426, 11.47244, 12.76638],
[ 43.34276, 41.49634, 40.24461, 41.86844, 40.71829, 40.45489,
39.40489, 38.43139, 38.5705 , 38.02632, 36.17692, 34.76023,
34.74136, 32.47884, 31.62541, 32.34425, 30.10012, 31.04573,
27.44909, 25.82034, 26.43948, 24.12467, 23.45606, 21.13788,
17.69826, 17.37892, 15.00269, 14.43571, 15.18723, 13.84108,
15.20368, 13.59916, 14.52011, 13.7462 , 15.10008, 19.15064,
20.62081, 21.31464, 22.53438, 22.18623, 26.09503, 29.10527,
28.85684, 30.98764, 31.76617, 35.00647, 35.24283, 38.38866,
39.40758, 40.30443, 42.7187 , 45.1501 , 47.59661, 47.72114,
47.40003, 49.40055, 50.8073 , 51.74464, 51.63282, 52.72249,
52.29678, 54.80877, 54.07596, 57.3284 , 54.10888, 52.36036,
53.91346, 53.63403, 54.03066, 53.48973, 52.11044, 51.11608,
51.03286, 50.07272, 48.79067, 48.50627, 47.23087, 44.58934,
42.22162, 42.18162, 41.16185, 36.93542, 34.29057, 35.12966,
32.4665 , 31.1793 , 25.9365 , 25.4595 , 23.76411, 20.24196,
18.62262, 15.98122, 15.11178, 12.95849, 10.74328, 9.90814,
0. , 6.63421, 10.22093, 9.98474],
[ 45.20143, 42.89946, 42.30763, 43.70448, 42.49124, 42.53407,
41.81369, 40.51321, 40.69567, 40.69416, 39.05643, 37.39742,
37.0847 , 35.00942, 33.79263, 35.03969, 33.17501, 33.47638,
29.9473 , 28.7832 , 28.60162, 26.69992, 26.30876, 23.4717 ,
20.07196, 20.49274, 17.43522, 17.62774, 17.0286 , 16.11862,
15.44059, 12.73676, 14.22711, 13.92431, 13.99427, 17.6646 ,
19.57784, 19.94906, 20.85881, 20.58748, 25.22437, 28.10747,
27.61326, 29.72708, 30.50207, 33.76313, 34.57233, 37.70556,
38.86882, 39.8812 , 42.53511, 44.98107, 47.05231, 47.06461,
46.87143, 49.64106, 50.61611, 51.99425, 52.1621 , 53.32 ,
53.08869, 55.50578, 54.94413, 58.22332, 55.4712 , 53.92575,
55.78262, 55.43629, 55.76022, 55.54874, 54.48838, 53.03856,
53.18936, 52.69689, 51.31535, 50.97824, 49.8669 , 47.23448,
45.16766, 45.17244, 43.95332, 40.15198, 37.67062, 38.15204,
36.03614, 34.37541, 29.3083 , 28.64282, 27.20938, 24.13398,
21.68822, 19.6484 , 18.41451, 14.74353, 12.86819, 11.78426,
6.63421, 0. , 8.83043, 8.80103],
[ 42.75318, 41.51576, 40.55066, 41.85398, 40.79031, 40.64863,
39.33236, 39.43324, 39.56802, 39.21815, 38.09928, 35.57779,
36.06984, 33.91675, 34.18837, 33.47656, 31.31277, 33.5043 ,
29.47687, 28.60458, 28.39343, 26.15777, 24.09575, 22.23873,
20.9814 , 18.30611, 17.0517 , 15.52057, 16.96968, 13.96013,
11.80224, 10.23459, 12.12231, 12.80535, 10.96839, 13.95903,
14.73243, 16.52504, 17.8264 , 18.68724, 20.37247, 24.43796,
24.23459, 25.83973, 27.94986, 30.48797, 31.19456, 34.12645,
34.90814, 36.95114, 39.36061, 42.0262 , 43.63606, 44.40938,
43.90372, 46.62981, 47.78862, 49.21381, 49.27814, 50.79307,
50.68305, 53.14199, 52.52346, 56.01087, 53.09032, 51.51095,
53.64081, 53.67147, 54.37677, 54.10548, 52.87226, 51.85091,
51.82288, 50.98398, 50.31884, 49.73738, 48.80525, 46.50554,
44.28871, 45.04898, 43.33299, 40.34494, 38.17835, 38.01118,
36.48471, 34.48999, 29.80644, 28.83705, 27.40981, 23.94398,
22.49918, 20.7999 , 17.69405, 15.81852, 13.30844, 11.47244,
10.22093, 8.83043, 0. , 7.46263],
[ 46.74111, 45.2993 , 44.09355, 45.9426 , 44.66045, 44.57547,
43.20546, 43.19846, 43.04025, 43.02089, 41.43184, 39.06011,
40.03816, 38.06303, 37.85652, 37.35049, 35.47796, 36.83706,
32.87905, 31.58328, 32.42605, 29.63547, 27.8713 , 25.49112,
23.64271, 21.75684, 20.42138, 19.39125, 20.31666, 17.63429,
16.78251, 14.84621, 15.73701, 16.20137, 13.95765, 16.88417,
17.36648, 20.00963, 20.38759, 20.88898, 22.75393, 27.26505,
27.25467, 28.4507 , 30.43803, 33.78487, 34.11927, 36.59337,
37.3594 , 39.24277, 42.55081, 44.83658, 46.86818, 47.37281,
47.26843, 49.95592, 51.26349, 52.79329, 52.86302, 54.50537,
54.16762, 56.6705 , 56.22352, 59.61459, 56.86156, 55.33784,
57.31579, 57.5573 , 58.38252, 57.89195, 56.74007, 55.85643,
55.93366, 55.16405, 54.28067, 53.71283, 52.57763, 50.1937 ,
47.87966, 48.29225, 46.9185 , 43.38612, 41.31302, 41.47549,
39.63076, 37.48156, 32.34705, 32.02712, 30.03519, 26.50431,
24.09327, 23.08624, 18.89004, 18.51871, 14.52224, 12.76638,
9.98474, 8.80103, 7.46263, 0. ]])
class FastMetricScmdsScalingTests(TestCase):
"""test the functions to do metric scaling"""
def setUp(self):
"""creates inputs"""
self.dist_func = lambda x, y: (FULL_SYM_MATRIX[x, y])
self.num_objects = FULL_SYM_MATRIX.shape[0]
def test_scmds_cmds_tzeng(self):
"""cmds_tzeng() should return eigenvectors and eigenvalues,
sorted by the eigenvalues
"""
dim = 3
(eigvec, eigval) = cmds_tzeng(FULL_SYM_MATRIX, dim)
self.assertTrue(len(eigval) == dim)
self.assertTrue(eigvec.shape == (FULL_SYM_MATRIX.shape[0], dim))
self.assertTrue(sorted(eigval, reverse=True) == eigval.tolist())
self.assertFloatEqual(eigval[0], 27336.883436)
self.assertFloatEqual(eigval[-1], 536.736247)
self.assertFloatEqual(eigvec[0, 0], -14.978621)
self.assertFloatEqual(eigvec[-1, -1], 0.673001)
# full pcoa
dim = FULL_SYM_MATRIX.shape[0]
(eigvec, eigval) = cmds_tzeng(FULL_SYM_MATRIX, dim)
self.assertTrue(len(eigval) == dim)
self.assertTrue(eigvec.shape == (FULL_SYM_MATRIX.shape[0], dim))
self.assertTrue(sorted(eigval, reverse=True) == eigval.tolist())
self.assertFloatEqual(eigval[0], 27336.883436043929)
self.assertFloatEqual(eigval[-1], 0.000000)
self.assertFloatEqual(eigvec[0, 0], -14.978621)
self.assertFloatEqual(eigvec[-1, -1], 0.000000)
def test_scmds_rowmeans(self):
"""rowmeans() should return a vector of row-means for a 2d matrix.
"""
rm = rowmeans(FULL_SYM_MATRIX[:10])
self.assertTrue(rm.shape[0] == 10)
self.assertFloatEqual(float(rm[0]), 25.983320)
self.assertFloatEqual(float(rm[-1]), 23.967050)
def test_scmds_recenter(self):
"""recenter() should recenter an mds solution
"""
mds_coords = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[ 5.18887751, -1.2130882 , -0.86476508],
[-3.10404298, -0.6620052 , -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[ 4.23608631, 0.7933192 , 1.16523198]])
centered_coords = recenter(mds_coords)
self.assertTrue(centered_coords.shape == mds_coords.shape)
center_of_gravity = sum([centered_coords[:, x].sum() \
for x in range(centered_coords.shape[1])])
self.assertFloatEqual(center_of_gravity, 0.0)
def test_scmds_affine_mapping(self):
"""affine_mapping() should return a touple of two matrices of
certain shape
"""
matrix_x = matrix([
[-24.03457111, 10.10355666, -23.17039728, 28.48438894,
22.57322482],
[ 0.62716392, 20.84502664, 6.42317521, -7.66901011,
14.37923852],
[ -2.60793417, 2.83532649, 2.91024821, 1.37414959,
-4.22916659]])
matrix_y = matrix([
[-29.81089477, -2.01312927, -30.5925487 , 23.05985801,
11.68581751],
[ -4.68879117, 23.62633294, 1.07934315, 0.57461989,
20.52800221],
[ -0.51503505, 1.18377044, 0.83671471, 1.81751358,
-3.28812925]])
dim = matrix_x.shape[0]
(tu, tb) = affine_mapping(matrix_x, matrix_y)
self.assertTrue(tu.shape[0] == dim and tb.shape[0] == dim)
self.assertTrue(tu.shape[0] == tu.shape[1])
self.assertFloatEqual(tu[0, 0], 0.966653)
self.assertFloatEqual(tu[-1, -1], 0.994816)
self.assertFloatEqual(tb[0, 0], -6.480975)
self.assertFloatEqual(tb[-1, -1], 0.686521)
def test_scmds_adjust_mds_to_ref(self):
"""adjust_mds_to_ref() should return an adjusted mds solutions"""
overlap = 5
dim = 3
size = 10
fake_mds_coords_ref = FULL_SYM_MATRIX[:size, :dim]
fake_mds_coords_add = FULL_SYM_MATRIX[overlap:size+overlap, :dim]
mds_adj = adjust_mds_to_ref(fake_mds_coords_ref,
fake_mds_coords_add, overlap)
self.assertTrue(mds_adj.shape == fake_mds_coords_add.shape)
self.assertFloatEqual(mds_adj[0, 0], 7.526609)
self.assertFloatEqual(mds_adj[-1, -1], 18.009350)
def test_scmds_combine_mds(self):
"""combine_mds() should merge two mds solutions
"""
overlap = 3
dim = 3
mds_coords_1 = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[ 5.18887751, -1.2130882 , -0.86476508],
[-3.10404298, -0.6620052 , -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[ 4.23608631, 0.7933192 , 1.16523198]])
mds_coords_2 = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[ 5.18887751, -1.2130882 , -0.86476508],
[-3.10404298, -0.6620052 , -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[ 4.23608631, 0.7933192 , 1.16523198]])
comb_mds = combine_mds(mds_coords_1,
mds_coords_2, overlap)
self.assertTrue(comb_mds.shape == (
mds_coords_1.shape[0]*2-overlap, dim))
self.assertFloatEqual(comb_mds[0, 0], -3.783335)
#self.assertFloatEqual(comb_mds[-1, -1], 0.349951)
def test_scmds_class_combinemds(self):
"""class CombineMds() should be able to join MDS solutions
"""
# tmp note
# tile1 = FULL_SYM_MATRIX[0:5, 0:5]
# tile2 = FULL_SYM_MATRIX[2:7, 2:7]
# mds_coords_1 = cmds_tzeng(tile1, 3)
# mds_coords_2 = cmds_tzeng(tile2, 3)
overlap = 3
mds_coords_1 = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[ 5.18887751, -1.2130882 , -0.86476508],
[-3.10404298, -0.6620052 , -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[ 4.23608631, 0.7933192 , 1.16523198]])
mds_coords_2 = matrix([
[-3.78333558, -2.90925004, 2.75333034],
[ 5.18887751, -1.2130882 , -0.86476508],
[-3.10404298, -0.6620052 , -3.91668873],
[-2.53758526, 3.99102424, 0.86289149],
[ 4.23608631, 0.7933192 , 1.16523198]])
comb_mds = CombineMds()
comb_mds.add(mds_coords_1, overlap)
comb_mds.add(mds_coords_2, overlap)
final_mds = comb_mds.getFinalMDS()
self.assertTrue(final_mds.shape == (mds_coords_1.shape[0]*2-overlap,
mds_coords_1.shape[1]))
#self.assertFloatEqual(final_mds[0, 0], 0.0393279)
#self.assertFloatEqual(final_mds[-1, -1], -5.322599)
class FastMetricNystromScalingTests(TestCase):
"""test the functions to do metric scaling"""
def setUp(self):
"""creates inputs"""
self.big_seed_matrix = FULL_SYM_MATRIX[:49]
self.small_seed_matrix = FULL_SYM_MATRIX[:25]
def test_calc_matrix_a(self):
"""calc_matrix_a should calculate a k x k matrix of
(predefined) association matrix K of certain (predefined)
value"""
nseeds = self.small_seed_matrix.shape[0]
matrix_e = self.small_seed_matrix[:, 0:nseeds]
matrix_a = calc_matrix_a(matrix_e)
self.assertFloatEqual(matrix_a[0, 0], 250.032270)
self.assertFloatEqual(matrix_a[-1][-1], 316.875461)
def test_nystrom_build_seed_matrix(self):
"""build_seed_matrix() should return a seedmatrix and an order
"""
seedmat_dim = 10
dist_func = lambda x, y: (FULL_SYM_MATRIX[x, y])
(seedmat, order) = build_seed_matrix(
FULL_SYM_MATRIX.shape[0], seedmat_dim, dist_func)
self.assertTrue(len(order) == FULL_SYM_MATRIX.shape[0])
self.assertTrue(sorted(order) == range(FULL_SYM_MATRIX.shape[0]))
self.assertTrue(seedmat.shape == (
seedmat_dim, FULL_SYM_MATRIX.shape[0]))
# build_seed_matrix randomises order
ind = argsort(order)
i = random.randint(0, seedmat.shape[0])
j = random.randint(0, seedmat.shape[1])
self.assertFloatEqual(seedmat[i, j], FULL_SYM_MATRIX[ind[i], ind[j]])
def test_nystrom(self):
"""nystrom() should return an MDS approximation"""
dim = 3
mds_coords = nystrom(self.big_seed_matrix, dim)
self.assertTrue(len(mds_coords.shape) == 2)
self.assertTrue(mds_coords.shape[0] == self.big_seed_matrix.shape[1])
self.assertTrue(mds_coords.shape[1] == dim)
self.assertFloatEqual(mds_coords[0, 0], -10.709626)
self.assertFloatEqual(mds_coords[-1, -1], -1.778160)
def test_nystrom_seed_number(self):
"""nystrom() should give better MDS approximations the more
seeds were used"""
dim = 3
mds_coords = nystrom(self.big_seed_matrix, dim)
stress = goodness_of_fit.Stress(FULL_SYM_MATRIX, mds_coords)
kruskal_stress_big_mat = stress.calcKruskalStress()
if PRINT_STRESS:
print("INFO: Kruskal stress for Nystrom MDS (big_seed_matrix, dim=%d) = %f" % \
(dim, kruskal_stress_big_mat))
self.assertTrue(kruskal_stress_big_mat < 0.04)
mds_coords = nystrom(self.small_seed_matrix, dim)
stress = goodness_of_fit.Stress(FULL_SYM_MATRIX, mds_coords)
kruskal_stress_small_mat = stress.calcKruskalStress()
if PRINT_STRESS:
print("INFO: Kruskal stress for Nystrom MDS (small_seed_matrix, dim=%d) = %f" % \
(dim, kruskal_stress_small_mat))
self.assertTrue(kruskal_stress_small_mat < 0.06)
self.assertTrue(kruskal_stress_small_mat > kruskal_stress_big_mat)
def test_calc_matrix_b(self):
"""calc_matrix_b should calculate a k x n-k matrix of
association matrix K
"""
nseeds = self.small_seed_matrix.shape[0]
matrix_e = self.small_seed_matrix[:, 0:nseeds]
matrix_f = self.small_seed_matrix[:, nseeds:]
matrix_b = calc_matrix_b(matrix_e, matrix_f)
self.assertTrue(matrix_b.shape == matrix_f.shape)
self.assertFloatEqual(matrix_b[0, 0], -272.711227)
self.assertFloatEqual(matrix_b[-1, -1], -64.898372)
#run if called from the command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_cluster/test_goodness_of_fit.py 000644 000765 000024 00000011273 12024702176 024707 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import unittest
import numpy
import cogent.cluster.goodness_of_fit as goodness_of_fit
__author__ = "Andreas Wilm"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Andreas Wilm"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Andreas Wilm"
__email__ = "andreas.wilm@ucd.ie"
__status__ = "Production"
def example_distmat_and_mdscoords():
"""Return an example distance matrix and corresponding MDS coordinates
Arguments:
* None
Returns:
* Tuple of:
** a distance matrix as numpy.matrix and
** MDS coordinates as numpy.array
"""
distmat = numpy.array([
[ 0. , 0.039806, 0.056853, 0.21595 , 0.056853, 0.0138 ,
0.203862, 0.219002, 0.056853, 0.064283],
[ 0.039806, 0. , 0.025505, 0.203862, 0.0208 , 0.039806,
0.194917, 0.21291 , 0.0208 , 0.027869],
[ 0.056853, 0.025505, 0. , 0.197887, 0.018459, 0.056853,
0.191958, 0.203862, 0.018459, 0.025505],
[ 0.21595 , 0.203862, 0.197887, 0. , 0.206866, 0.206866,
0.07956 , 0.066935, 0.203862, 0.206866],
[ 0.056853, 0.0208 , 0.018459, 0.206866, 0. , 0.056853,
0.203862, 0.21595 , 0.0138 , 0.0208 ],
[ 0.0138 , 0.039806, 0.056853, 0.206866, 0.056853, 0. ,
0.197887, 0.209882, 0.056853, 0.064283],
[ 0.203862, 0.194917, 0.191958, 0.07956 , 0.203862, 0.197887,
0. , 0.030311, 0.200869, 0.206866],
[ 0.219002, 0.21291 , 0.203862, 0.066935, 0.21595 , 0.209882,
0.030311, 0. , 0.21291 , 0.219002],
[ 0.056853, 0.0208 , 0.018459, 0.203862, 0.0138 , 0.056853,
0.200869, 0.21291 , 0. , 0.011481],
[ 0.064283, 0.027869, 0.025505, 0.206866, 0.0208 , 0.064283,
0.206866, 0.219002, 0.011481, 0. ]])
mds_coords = numpy.array([
[ 0.065233, 0.035019, 0.015413],
[ 0.059604, 0.00168 , -0.003254],
[ 0.052371, -0.010959, -0.014047],
[-0.13804 , -0.036031, 0.031628],
[ 0.063703, -0.015483, -0.00751 ],
[ 0.056803, 0.031762, 0.021767],
[-0.135082, 0.023552, -0.021006],
[-0.150323, 0.011935, -0.010013],
[ 0.06072 , -0.01622 , -0.007721],
[ 0.065009, -0.025254, -0.005257]])
return (distmat, mds_coords)
class GoodnessOfFitTestCase(unittest.TestCase):
def setUp(self):
"""
set up
"""
(self.distmat, self.mds_coords) = example_distmat_and_mdscoords()
self.stress = goodness_of_fit.Stress(self.distmat, self.mds_coords)
def test_kruskalstress1(self):
"""
testing goodness_of_fit.calcKruskalStress()
"""
val = "%0.6f" % self.stress.calcKruskalStress()
self.assertEqual(val, '0.022555')
def test_sstress(self):
"""
testing goodness_of_fit.calcSstress()
"""
val = "%0.6f" % self.stress.calcSstress()
self.assertEqual(val, '0.008832')
def test_calc_pwdist(self):
"""
testing (private) goodness_of_fit._calc_pwdist
"""
# this is a square in 2D
square_mds = numpy.array([[0,0], [1,0], [1,1], [0,1]])
# this is what the distance matrix should look like
square_distmat = numpy.array([[ 0. , 1. , 1.41421356, 1. ],
[ 1. , 0. , 1. , 1.41421356],
[ 1.41421356, 1. , 0. , 1. ],
[ 1. , 1.41421356, 1. , 0. ]])
derived_distmat = self.stress._calc_pwdist(square_mds)
# check if dervied and original array are (more or less) the same
self.assert_((derived_distmat-square_distmat).sum() < 0.000001)
def test_argument_mixup_exception(self):
"""
test if mds_coords and distmat are mix-up is detected
"""
self.assertRaises(AssertionError,
goodness_of_fit.Stress,
self.mds_coords, self.distmat)
# should give something like
# AssertionError: orig_distmat shape bigger than mds_coords shape. Possible argument mixup
def test_size_exception(self):
"""
test if check on number of rows works
"""
self.assertRaises(AssertionError,
goodness_of_fit.Stress,
self.distmat, self.mds_coords.transpose())
# should give something like
# AssertionError: orig_distmat and mds_coords do not have the same number of rows/objects.
if __name__ == '__main__':
unittest.main()
PyCogent-1.5.3/tests/test_cluster/test_metric_scaling.py 000644 000765 000024 00000021251 12024702176 024520 0 ustar 00jrideout staff 000000 000000 #!usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.cluster.metric_scaling import make_E_matrix, \
make_F_matrix, run_eig, get_principal_coordinates, \
principal_coordinates_analysis, output_pca, PCoA
from numpy import array
import numpy
Float = numpy.core.numerictypes.sctype2char(float)
__author__ = "Catherine Lozupone"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Catherine Lozupone", "Peter Maxwell", "Rob Knight",
"Justin Kuczynski", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Catherine Lozupone"
__email__ = "lozupone@colorado.edu"
__status__ = "Production"
class MetricScalingTests(TestCase):
"""test the functions to do metric scaling"""
def setUp(self):
"""creates inputs"""
#create a test input matrix
self.matrix = array([[1,2,3], [4,5,6]], Float)
#create a symmetrical matrix
self.sym_matrix = array([[0.5, 1.0, 1.5, 2.0],
[1.0, 2.0, 3.0, 4.0],
[1.5, 3.0, 2.0, 1.0],
[2.0, 4.0, 1.0, 0.5]])
self.tree_dnd = """((org1:0.11, org2:0.22,(org3:0.12, org4:0.23):0.33)
:0.2,(org5:0.44, org6:0.55):0.3, org7:0.4);"""
self.all_envs = ['env1', 'env2', 'env3']
self.envs_dict = {"org1": array([1,1,0]),
"org2": array([0,1,0]),
"org3": array([0,1,0]),
"org4": array([0,0,1]),
"org5": array([1,1,0]),
"org6": array([1,1,0]),
"org7": array([0,0,1]),
}
#sample data set from page 111 of W.J Krzanowski. Principles of
#multivariate analysis, 2000, Oxford University Press
self.real_matrix = array([[0,0.099,0.033,0.183,0.148,0.198,0.462,0.628,0.113,0.173,0.434,0.762,0.53,0.586],\
[0.099,0,0.022,0.114,0.224,0.039,0.266,0.442,0.07,0.119,0.419,0.633,0.389,0.435],\
[0.033,0.022,0,0.042,0.059,0.053,0.322,0.444,0.046,0.162,0.339,0.781,0.482,0.55], \
[0.183,0.114,0.042,0,0.068,0.085,0.435,0.406,0.047,0.331,0.505,0.7,0.579,0.53], \
[0.148,0.224,0.059,0.068,0,0.051,0.268,0.24,0.034,0.177,0.469,0.758,0.597,0.552], \
[0.198,0.039,0.053,0.085,0.051,0,0.025,0.129,0.002,0.039,0.39,0.625,0.498,0.509], \
[0.462,0.266,0.322,0.435,0.268,0.025,0,0.014,0.106,0.089,0.315,0.469,0.374,0.369], \
[0.628,0.442,0.444,0.406,0.24,0.129,0.014,0,0.129,0.237,0.349,0.618,0.562,0.471], \
[0.113,0.07,0.046,0.047,0.034,0.002,0.106,0.129,0,0.071,0.151,0.44,0.247,0.234], \
[0.173,0.119,0.162,0.331,0.177,0.039,0.089,0.237,0.071,0,0.43,0.538,0.383,0.346], \
[0.434,0.419,0.339,0.505,0.469,0.39,0.315,0.349,0.151,0.43,0,0.607,0.387,0.456], \
[0.762,0.633,0.781,0.7,0.758,0.625,0.469,0.618,0.44,0.538,0.607,0,0.084,0.09], \
[0.53,0.389,0.482,0.579,0.597,0.498,0.374,0.562,0.247,0.383,0.387,0.084,0,0.038], \
[0.586,0.435,0.55,0.53,0.552,0.509,0.369,0.471,0.234,0.346,0.456,0.09,0.038,0]])
#test tree
dnd = """
"""
def test_principal_coordinate_analysis(self):
"""principal_coordinate_analysis returns array of principal coors"""
#I took the example in the book (see intro info), and did the
#principal coordinates analysis, plotted the data and it looked
#right
matrix = self.real_matrix
pcs, eigvals= principal_coordinates_analysis(matrix)
bigfirstorder = eigvals.argsort()[::-1]
pcs = pcs[bigfirstorder]
eigvals = eigvals[bigfirstorder]
self.assertEqual(len(pcs), 14)
self.assertFloatEqual(abs(pcs[0,0]), 0.240788133045)
self.assertFloatEqual(abs(pcs[1,0]), 0.233677162)
def test_PCoA(self):
"""PCoA returns a cogent Table result"""
matrix = self.real_matrix
names = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l',
'm', 'n']
pairwise_dist = {}
for i, name1 in enumerate(names):
for j, name2 in enumerate(names):
combo = (name1, name2)
if combo not in pairwise_dist:
pairwise_dist[combo] = matrix[i,j]
#perform with the PCoA function
result = PCoA(pairwise_dist)
self.assertEqual(result[7,1], 'a')
self.assertFloatEqual(abs(result[7,2]), 0.240788133045)
def test_make_E_matrix(self):
"""make_E_matrix converts a distance matrix to an E matrix"""
matrix = self.matrix
E_matrix = make_E_matrix(matrix)
self.assertFloatEqual(E_matrix[0,0], -0.5)
self.assertFloatEqual(E_matrix[0,1], -2.0)
self.assertFloatEqual(E_matrix[1,0], -8.0)
self.assertFloatEqual(E_matrix[1,2], -18.0)
def test_make_F_matrix(self):
"""make_F_matrix converts an E_matrix to an F_matrix"""
#matrix = self.matrix
matrix = array([[1,2,3],[4,5,6],[7,8,9]])
F_matrix = make_F_matrix(matrix)
self.assertEqual(F_matrix, array([[0.0, -2.0, -4.0],
[2.0, 0.0, -2.0],
[4.0, 2.0, 0.0]]))
def test_run_eig(self):
"""run_eig returns eigenvectors and values"""
matrix = self.sym_matrix
eigvals, eigvecs = run_eig(matrix)
#make sure that the number of eigvecs and eigvals is equal to dims
self.assertEqual(len(eigvals), 4)
self.assertEqual(len(eigvecs), 4)
def test_get_principal_coordinates(self):
"""get_principal_coordinates normalizes eigvecs with eigvalues"""
matrix = array([[1,1,1],[2,2,2],[3,3,3]])
vec = array([0,1,-4])
result = get_principal_coordinates(vec, matrix)
self.assertEqual(result[0], array([0,0,0]))
self.assertEqual(result[1], array([2,2,2]))
self.assertEqual(result[2], array([6,6,6]))
def test_output_pca(self):
"""output_pca1 creates a Table output for pcs results"""
#make arbitary values for inputs
eigvals = array([4.2,3.2,5.2])
names = ['env1', 'env2', 'env3']
pca_matrix = array([[-0.34, -0.22, 0.57], [-0.12, 0.14, -0.018],
[1.8, 1.9, 2.0]])
output_table = output_pca(pca_matrix, eigvals, names)
self.assertEqual(str(output_table),
'''\
================================================================
Type Label vec_num-0 vec_num-1 vec_num-2
----------------------------------------------------------------
Eigenvectors env1 1.80 -0.34 -0.12
Eigenvectors env2 1.90 -0.22 0.14
Eigenvectors env3 2.00 0.57 -0.02
Eigenvalues eigenvalues 5.20 4.20 3.20
Eigenvalues var explained (%) 41.27 33.33 25.40
----------------------------------------------------------------''')
def test_integration(self):
"""Integration test of PCoA should work correctly"""
u = array([[ 0. , 0.7123611 , 0.76849198, 0.80018563, 0.68248524, 0.74634629],
[ 0.7123611 , 0. , 0.86645691, 0.80485282, 0.83381301, 0.73881726],
[ 0.76849198, 0.86645691, 0. , 0.82308396, 0.77451746, 0.76498872],
[ 0.80018563, 0.80485282, 0.82308396, 0. , 0.84167365, 0.77614366],
[ 0.68248524, 0.83381301, 0.77451746, 0.84167365, 0. , 0.72661163],
[ 0.74634629, 0.73881726, 0.76498872, 0.77614366, 0.72661163, 0. ]])
e = make_E_matrix(u)
f = make_F_matrix(e)
eigvals, eigvecs = run_eig(f)
bigfirstorder = eigvals.argsort()[::-1]
#eigvecs = eigvecs[bigfirstorder]
#eigvals = eigvals[bigfirstorder]
principal_coords = get_principal_coordinates(eigvals, eigvecs)
principal_coords = principal_coords[bigfirstorder]
expected = array([
[ 2.85970001e-02, -3.74940557e-01, 3.35175925e-01,
-2.54123944e-01, 2.82568441e-01, -1.72768652e-02],
[ 2.29038532e-01, 2.23340550e-01, -2.38559794e-01,
-4.12346397e-01, 1.86069108e-01, 1.24580018e-02],
[ 7.05527166e-02, -2.08929136e-01, -3.09988697e-01,
2.33436419e-01, 2.88756308e-01, -7.38276099e-02]])
self.assertFloatEqual(abs(principal_coords[[0,1,2]]), abs(expected))
#run if called from the command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_cluster/test_nmds.py 000644 000765 000024 00000010233 12024702176 022474 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from numpy import array, sqrt, size
from cogent.cluster.nmds import NMDS, metaNMDS
from cogent.maths.distance_transform import dist_euclidean
__author__ = "Justin Kuczynski"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Justin Kuczynski"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Justin Kuczynski"
__email__ = "justinak@gmail.com"
__status__ = "Development"
class NMDSTests(TestCase):
"""test the nonmetric_scaling module, using floating point numpy arrays
"""
def setUp(self):
"""creates inputs"""
self.mtx = array([[0,3,4,8],
[3,0,1,27],
[4,1,0,3.5],
[8,27,3.5,0]],'d')
self.nm = NMDS(self.mtx, verbosity=0)
def test_getStress(self):
"""stress should be small
this is preliminary, better to check for convergence to similar states
with random starting points enabled"""
stress = self.nm.getStress()
self.assertLessThan(stress, 1e-1)
def test_getPoints(self):
"""points should be of the right number and dimensionality
this is preliminary, better to check for convergence to similar states
with random starting points enabled"""
pts = self.nm.getPoints()
self.assertEqual(size(pts, 0), 4)
self.assertEqual(size(pts, 1), 2)
def test_2(self):
"""l19 data should give stress below .13"""
ptmtx = array(
[[7,1,0,0,0,0,0,0,0],
[4,2,0,0,0,1,0,0,0],
[2,4,0,0,0,1,0,0,0],
[1,7,0,0,0,0,0,0,0],
[0,8,0,0,0,0,0,0,0],
[0,7,1,0,0,0,0,0,0],#idx 5
[0,4,2,0,0,0,2,0,0],
[0,2,4,0,0,0,1,0,0],
[0,1,7,0,0,0,0,0,0],
[0,0,8,0,0,0,0,0,0],
[0,0,7,1,0,0,0,0,0],#idx 10
[0,0,4,2,0,0,0,3,0],
[0,0,2,4,0,0,0,1,0],
[0,0,1,7,0,0,0,0,0],
[0,0,0,8,0,0,0,0,0],
[0,0,0,7,1,0,0,0,0],#idx 15
[0,0,0,4,2,0,0,0,4],
[0,0,0,2,4,0,0,0,1],
[0,0,0,1,7,0,0,0,0]], 'float')
distmtx = dist_euclidean(ptmtx)
nm = NMDS(distmtx, verbosity=0)
self.assertLessThan(nm.getStress(), .13)
def test_3(self):
"""l19 data should give stress below .13 in multi-D"""
ptmtx = array(
[[7,1,0,0,0,0,0,0,0],
[4,2,0,0,0,1,0,0,0],
[2,4,0,0,0,1,0,0,0],
[1,7,0,0,0,0,0,0,0],
[0,8,0,0,0,0,0,0,0],
[0,7,1,0,0,0,0,0,0],#idx 5
[0,4,2,0,0,0,2,0,0],
[0,2,4,0,0,0,1,0,0],
[0,1,7,0,0,0,0,0,0],
[0,0,8,0,0,0,0,0,0],
[0,0,7,1,0,0,0,0,0],#idx 10
[0,0,4,2,0,0,0,3,0],
[0,0,2,4,0,0,0,1,0],
[0,0,1,7,0,0,0,0,0],
[0,0,0,8,0,0,0,0,0],
[0,0,0,7,1,0,0,0,0],#idx 15
[0,0,0,4,2,0,0,0,4],
[0,0,0,2,4,0,0,0,1],
[0,0,0,1,7,0,0,0,0]], 'float')
distmtx = dist_euclidean(ptmtx)
for dim in range(3,18):
nm = NMDS(distmtx, verbosity=0, dimension=dim)
self.assertLessThan(nm.getStress(), .13)
def test_metaNMDS(self):
"""l19 data should give stress below .13"""
ptmtx = array(
[[7,1,0,0,0,0,0,0,0],
[4,2,0,0,0,1,0,0,0],
[2,4,0,0,0,1,0,0,0],
[1,7,0,0,0,0,0,0,0],
[0,8,0,0,0,0,0,0,0],
[0,7,1,0,0,0,0,0,0],#idx 5
[0,4,2,0,0,0,2,0,0],
[0,2,4,0,0,0,1,0,0],
[0,1,7,0,0,0,0,0,0],
[0,0,8,0,0,0,0,0,0],
[0,0,7,1,0,0,0,0,0],#idx 10
[0,0,4,2,0,0,0,3,0],
[0,0,2,4,0,0,0,1,0],
[0,0,1,7,0,0,0,0,0],
[0,0,0,8,0,0,0,0,0],
[0,0,0,7,1,0,0,0,0],#idx 15
[0,0,0,4,2,0,0,0,4],
[0,0,0,2,4,0,0,0,1],
[0,0,0,1,7,0,0,0,0]], 'float')
distmtx = dist_euclidean(ptmtx)
nm = metaNMDS(1, distmtx, verbosity=0)
self.assertLessThan(nm.getStress(), .13)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_cluster/test_procrustes.py 000644 000765 000024 00000012352 12024702176 023750 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from numpy import array, sqrt, dot, trace, transpose, pi, cos, sin, dot,\
trace, append
from cogent.cluster.procrustes import procrustes, get_disparity, center, \
normalize
__author__ = "Justin Kuczynski"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Justin Kuczynski"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Justin Kuczynski"
__email__ = "justinak@gmail.com"
__status__ = "Production"
class procrustesTests(TestCase):
"""test the procrustes module, using floating point numpy arrays
"""
def setUp(self):
"""creates inputs"""
# an L
self.data1 = array([[1, 3],
[1, 2],
[1, 1],
[2, 1]], 'd')
# a larger, shifted, mirrored L
self.data2 = array([[4, -2],
[4, -4],
[4, -6],
[2, -6]], 'd')
# an L shifted up 1, right 1, and with point 4 shifted an extra .5
# to the right
# pointwise distance disparity with data1: 3*(2) + (1 + 1.5^2)
self.data3 = array([[2, 4],
[2, 3],
[2, 2],
[3, 2.5]], 'd')
# data4, data5 are standardized (trace(A*A') = 1).
# procrustes should return an identical copy if they are used
# as the first matrix argument.
shiftangle = pi/8
self.data4 = array([[1,0],
[0,1],
[-1,0],
[0,-1]],'d')/sqrt(4)
self.data5 = array([[cos(shiftangle), sin(shiftangle)],
[cos(pi/2-shiftangle), sin(pi/2-shiftangle)],
[-cos(shiftangle), -sin(shiftangle)],
[-cos(pi/2-shiftangle), -sin(pi/2-shiftangle)]],
'd')/sqrt(4)
def test_procrustes(self):
"""tests procrustes' ability to match two matrices.
the second matrix is a rotated, shifted, scaled, and mirrored version
of the first, in two dimensions only
"""
# can shift, mirror, and scale an 'L'?
a,b,disparity = procrustes(self.data1, self.data2)
self.assertFloatEqual(b, a)
self.assertFloatEqual(disparity,0.)
# if first mtx is standardized, leaves first mtx unchanged?
m4, m5, disp45 = procrustes(self.data4, self.data5)
self.assertFloatEqual(m4, self.data4)
# at worst, data3 is an 'L' with one point off by .5
m1, m3, disp13 = procrustes(self.data1, self.data3)
self.assertLessThan(disp13, .5**2)
def test_procrustes2(self):
"""procrustes disparity should not depend on order of matrices"""
m1, m3, disp13 = procrustes(self.data1, self.data3)
m3_2, m1_2, disp31 = procrustes(self.data3, self.data1)
self.assertFloatEqual(disp13, disp31)
# try with 3d, 8 pts per
rand1 = array([[ 2.61955202, 0.30522265, 0.55515826],
[ 0.41124708, -0.03966978, -0.31854548],
[ 0.91910318, 1.39451809, -0.15295084],
[ 2.00452023, 0.50150048, 0.29485268],
[ 0.09453595, 0.67528885, 0.03283872],
[ 0.07015232, 2.18892599, -1.67266852],
[ 0.65029688, 1.60551637, 0.80013549],
[-0.6607528 , 0.53644208, 0.17033891]])
rand3 = array([[ 0.0809969 , 0.09731461, -0.173442 ],
[-1.84888465, -0.92589646, -1.29335743],
[ 0.67031855, -1.35957463, 0.41938621],
[ 0.73967209, -0.20230757, 0.52418027],
[ 0.17752796, 0.09065607, 0.29827466],
[ 0.47999368, -0.88455717, -0.57547934],
[-0.11486344, -0.12608506, -0.3395779 ],
[-0.86106154, -0.28687488, 0.9644429 ]])
res1, res3, disp13 = procrustes(rand1,rand3)
res3_2, res1_2, disp31 = procrustes(rand3, rand1)
self.assertFloatEqual(disp13, disp31)
def test_get_disparity(self):
"""tests get_disparity"""
disp = get_disparity(self.data1, self.data3)
disp2 = get_disparity(self.data3, self.data1)
self.assertFloatEqual(disp, disp2)
self.assertFloatEqual(disp, (3.*2. + (1. + 1.5**2)))
d1 = append(self.data1, self.data1, 0)
d3 = append(self.data3, self.data3, 0)
disp3 = get_disparity(d1,d3)
disp4 = get_disparity(d3,d1)
self.assertFloatEqual(disp3, disp4)
# 2x points in same configuration should give 2x disparity
self.assertFloatEqual(disp3, 2.*disp)
def test_center(self):
centered_mtx = center(self.data1)
column_means = centered_mtx.mean(0)
for col_mean in column_means:
self.assertFloatEqual(col_mean, 0.)
def test_normalize(self):
norm_mtx = normalize(self.data1)
self.assertFloatEqual(trace(dot(norm_mtx,transpose(norm_mtx))), 1.)
# match_points isn't yet tested, as it's almost a private function
# and test_procrustes() tests it implicitly.
#run if called from command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_cluster/test_UPGMA.py 000644 000765 000024 00000013662 12024702176 022415 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.core.tree import PhyloNode
from numpy import array
import numpy
Float = numpy.core.numerictypes.sctype2char(float)
from cogent.cluster.UPGMA import find_smallest_index, condense_matrix, \
condense_node_order, UPGMA_cluster, inputs_from_dict2D, upgma
from cogent.util.dict2d import Dict2D
__author__ = "Rob Knight"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
class UPGMATests(TestCase):
"""test the functions to cluster using UPGMA using numpy"""
def setUp(self):
"""creates inputs"""
self.pairwise_distances = {('a', 'b'): 1.0,
('a', 'c'):4.0,
('a', 'd'):20.0,
('a', 'e'):22.0,
('b', 'c'):5.0,
('b', 'd'):21.0,
('b', 'e'):23.0,
('c', 'd'):10.0,
('c', 'e'):12.0,
('d', 'e'):2.0}
#create a list of PhyloNode objects
a, b, c, d, e = map(PhyloNode, 'abcde')
self.node_order = [a, b, c, d, e]
#create a numpy matrix object to cluster
self.matrix = array(([9999999, 1, 4, 20, 22], \
[1, 9999999, 5, 21, 23], \
[4, 5, 9999999, 10, 12], \
[20, 21, 10, 9999999, 2], \
[22, 23, 12, 2, 9999999]), Float)
#create a numpy matrix with zero diagonals to test diagonal mask
self.matrix_zeros = array(([0, 1, 4, 20, 22], \
[1, 0, 5, 21, 23], \
[4, 5, 0, 10, 12], \
[20, 21, 10, 0, 2], \
[22, 23, 12, 2, 0]), Float)
#create a numpy matrix with zero diagonals to test diagonal mask
self.matrix_five = array(([5, 1, 4, 20, 22], \
[1, 5, 5, 21, 23], \
[4, 5, 5, 10, 12], \
[20, 21, 10, 5, 2], \
[22, 23, 12, 2, 5]), Float)
def test_UPGMA_cluster(self):
"""upgma works on pairwise distance dict
"""
pairwise_dist = self.pairwise_distances
cluster = upgma(pairwise_dist)
self.assertEqual(str(cluster), '(((b:0.5,a:0.5)edge.1:1.75,c:2.25)edge.0:5.875,(d:1.0,e:1.0)edge.2:7.125)root;')
def test_find_smallest_index(self):
"""find_smallest_index returns the index of smallest value in array
"""
matrix = self.matrix
index = find_smallest_index(matrix)
self.assertEqual(index, (0,1))
def test_condense_matrix(self):
"""condense_array joins two rows and columns identified by indices
"""
matrix = self.matrix
index = find_smallest_index(matrix)
result = condense_matrix(matrix, index, 9999999999)
self.assertFloatEqual(result[0, 0], 5000000.0)
self.assertEqual(result[1, 4], 9999999999)
self.assertEqual(result[0, 1], 9999999999)
self.assertEqual(result[0, 2], 4.5)
self.assertEqual(result[2, 0], 4.5)
self.assertEqual(result[0, 4], 22.5)
self.assertEqual(result[4, 4], 9999999)
self.assertEqual(result[4, 0], 22.5)
def test_condense_node_order(self):
"""condense_node_order condenses nodes in list based on index info
"""
matrix = self.matrix
index = find_smallest_index(matrix)
node_order = self.node_order
node_order = condense_node_order(matrix, index, node_order)
self.assertEqual(node_order[1], None)
self.assertEqual(node_order[0].__str__(), '(a:0.5,b:0.5);')
self.assertEqual(node_order[2].__str__(), 'c;')
self.assertEqual(node_order[3].__str__(), 'd;')
self.assertEqual(node_order[4].__str__(), 'e;')
def test_upgma_cluster(self):
"""UPGMA_cluster clusters nodes based on info in a matrix with UPGMA
"""
matrix = self.matrix
node_order = self.node_order
large_number = 9999999999
tree = UPGMA_cluster(matrix, node_order, large_number)
self.assertEqual(str(tree), \
'(((a:0.5,b:0.5):1.75,c:2.25):5.875,(d:1.0,e:1.0):7.125);')
def test_UPGMA_cluster_diag(self):
"""UPGMA_cluster works when the diagonal has lowest values
"""
#test that checking the diagonal works
matrix = self.matrix_zeros
node_order = self.node_order
large_number = 9999999999
tree = UPGMA_cluster(matrix, node_order, large_number)
self.assertEqual(str(tree), \
'(((a:0.5,b:0.5):1.75,c:2.25):5.875,(d:1.0,e:1.0):7.125);')
def test_UPGMA_cluster_diag(self):
"""UPGMA_cluster works when the diagonal has intermediate values
"""
#test that checking the diagonal works
matrix = self.matrix_five
node_order = self.node_order
large_number = 9999999999
tree = UPGMA_cluster(matrix, node_order, large_number)
self.assertEqual(str(tree), \
'(((a:0.5,b:0.5):1.75,c:2.25):5.875,(d:1.0,e:1.0):7.125);')
def test_inputs_from_dict2D(self):
"""inputs_from_dict2D makes an array object and PhyloNode list"""
matrix = [('1', '2', 0.86), ('2', '1', 0.86), \
('1', '3', 0.92), ('3', '1', 0.92), ('2', '3', 0.67), \
('3', '2', 0.67)]
row_order = ['3', '2', '1']
matrix_d2d = Dict2D(matrix, RowOrder=row_order, \
ColOrder=row_order, Pad=True, Default = 999999999999999)
matrix_array, PhyloNode_order = inputs_from_dict2D(matrix_d2d)
self.assertFloatEqual(matrix_array[0][2], 0.92)
self.assertFloatEqual(matrix_array[1][0], 0.67)
self.assertEqual(PhyloNode_order[0].Name, '3')
self.assertEqual(PhyloNode_order[2].Name, '1')
#run if called from command line
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/__init__.py 000644 000765 000024 00000001726 12024702176 021341 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = """
test_dynalign test_raxml test_stride
test_blast test_foldalign test_rnaalifold
test_carnac test_ilm test_rnaforester
test_clustalw test_knetfold test_rnaview
test_cmfinder test_mfold test_sfold
test_comrna test_muscle test_unafold
test_consan test_nupack test_util
test_contrafold test_parameters test_vienna_package
test_cove test_pfold test_gctmpca
test_dialign test_pknotsrg test_fasttree
test_msms""".split()
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Micah Hamady", "Rob Knight", "Catherine Lozupone",
"Sandra Smit", "Gavin Huttley", "Greg Caporaso",
"Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Rob Knight"
__email__ = "rob@spot.colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_app/test_blast.py 000644 000765 000024 00000035572 12024702176 021754 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from string import split, strip
from os import popen, remove
from glob import glob
from cogent.util.unit_test import TestCase, main
from cogent.parse.blast import QMEBlast9
from cogent.app.blast import seqs_to_stream,\
make_subject_match_scorer, make_shotgun_scorer, keep_everything_scorer, \
ids_from_seq_lower_threshold, PsiBlast, psiblast_n_neighbors
__author__ = "Micah Hamady"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Micah Hamady", "Rob Knight", "Catherine Lozupone"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Micah Hamady"
__email__ = "hamady@colorado.edu"
__status__ = "Prototype"
class BlastTests(TestCase):
"""Tests of top-level functions"""
def setUp(self):
"""Define some standard data"""
self.rec = """# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4181 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-06 52.8
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 2
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4181 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4181 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-08 59.0
ece:Z4181 sfl:CP0138 33.98 103 57 2 8 110 6 97 6e-06 50.5
ece:Z4181 spt:SPA2730 37.50 72 45 0 39 110 30 101 1e-05 49.8
ece:Z4181 sec:SC2804 37.50 72 45 0 39 110 30 101 1e-05 49.8
ece:Z4181 stm:STM2872 37.50 72 45 0 39 110 30 101 1e-05 49.8
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4182
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4182 ece:Z4182 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4182 ecs:ECs3718 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4182 cvi:CV2422 41.67 72 42 0 39 110 29 100 2e-06 52.8""".split('\n')
self.rec2 = """# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4181 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 spt:SPA2730 37.50 72 45 0 39 110 30 101 1e-05 49.8
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 2
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4181 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-08 59.0
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4182
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4182 ece:Z4182 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4182 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-06 52.8""".split('\n')
self.rec3 = """# BLASTP 2.2.10 [Oct-19-2004]
# BLASTP 2.2.10 [Oct-19-2004]
# Query: ece:Z4181
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4181 ece:Z4182 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4181 spt:SPA2730 37.50 72 45 0 39 110 30 101 1e-05 49.8
# BLASTP 2.2.10 [Oct-19-2004]
# Iteration: 1
# Query: ece:Z4182
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4182 ece:Z4182 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4182 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-06 52.8
# BLASTP 2.2.10 [Oct-19-2004]
# Query: ece:Z4183
# Database: db/everything.faa
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
ece:Z4183 ece:Z4182 100.00 110 0 0 1 110 1 110 3e-47 187
ece:Z4183 ecs:ECs3717 100.00 110 0 0 1 110 1 110 3e-54 211
ece:Z4183 cvi:CV2421 41.67 72 42 0 39 110 29 100 2e-08 59.0""".split('\n')
self.query_1 = """>gi|100002553| Bd2556c Bd2556c two-component system sensor histidine kinase 3092017:3094158 reverse MW:81963
MRLKNRLNNWISIRMGMVIVIFLGVSCGSMRSSTPPPAKDRLTEIDSLERLLPDCPTIASTLPLLRRLAFLYQQQSEMKVYNERLYENAMAVDSISVAYLGLKNLAEYYYDQSVRDSLEYYCSLVDSIAKARHEYPNVLFDVKSLSSQDLLWLGNYELAMSEAMDLYRLASNLDHRYGLLRCSETLGLIYQRIRRDSDAVVSFQESLDLLKDIKDVPDIMDTKVRLTSYQLESSVRTKQYASTERILGQYMALLDEQYKIYQEKNDLLSIKREYWLLYSFYTSFYLSQGDLENAKRSLDQASSYADSNWVEGDYAINTYLTVKARYHKAAGDIPLALHCINEVLETERLPEDIQFKADILKEQGQLGEVMALYDELYSTLTKRRGTSFLRQVNQLRTLHELHEKELKETELKEAGQRIARKQDLLIFILSISVVLLILLYVLFLYYRHLRSLKNQLQREKELLLESQRQLIKEKTRAEEASLMKSAFLANMSHEVRTPLNAIVGFSGLLVEPSTDEEERKEYSSIIRNNTDLMLNLVNDVLDLSRMETGDLHFDIKDHLLLVCCQMALESVRHRIPDGVKLTFSPAGEPIVVHVDNLRLQQLLTNLLTNAAKFTEKGEINLSFQLEPDRKKVCIAVTDTGAGIPLEKQATIFNRFEKLDDYKPGVGLGLSICLLIAERLDGALFIDSSYTDGARFVLILSCEIDSSIYNPPIEV"""
self.query_2 = """>gi|100002557| Bd2560c Bd2560c conserved hypothetical protein 3097971:3098210 reverse MW:8927
MGKNQLIHGNEFHLLKQAEIHKATGKLVESLNLAAGSTGGFDIYKVVEAYFTDLEKRKEINDLLGISEPCETRVTEECFS
"""
self.fasta_recs = """>gi|100002550| Bd2553c Bd2553c conserved hypothetical protein 3090609:3091013 reverse MW:14682
MMDFISVPLVVGIVCAGIYGLFELFVRKRERLAIIEKIGDKLDTSAFDGKLGLPNYMRNFSFSSLKAGCLLAGIGLGLLVGFIINMCMATNSYYDDGWYRHEVAGTAYGASVLLFGGIGLIIAFVIELKLGKNNK
>gi|100002551| Bd2554 Bd2554 RNA polymerase ECF-type sigma factor 3091112:3091717 forward MW:23408
LLPQVVTYLPGLRPLSTMELYTDTYYIQRIQAGDVACFACLLDKYSRPIHSLILKVVRSQEEAEELAQDTFMKVFKNLASFKGDCSFSTWIYRIAYNTAISSVRKKRYEFLAIEETTLENVSEEEITNLFGQTESTEQVQRLEVALEQLLPDERALILLFYWKEKTIEELVSITGLTASNIKVKLHRIRKKLFVLLNGMDHE
>gi|100002552| Bd2555 Bd2555 conserved hypothetical protein 3091713:3092066 forward MW:13332
MSKINTNKEQPDLLGDLFKRIPEEELPASFRSNVMRQIMLESAKAKKRDERFSLLAAIVASLIMISLAIVSFVYMEIPKIAIPTISTSALAFYLYIGAITLILLLADYKLRNLFHKKG
>gi|100002553| Bd2556c Bd2556c two-component system sensor histidine kinase 3092017:3094158 reverse MW:81963
MRLKNRLNNWISIRMGMVIVIFLGVSCGSMRSSTPPPAKDRLTEIDSLERLLPDCPTIASTLPLLRRLAFLYQQQSEMKVYNERLYENAMAVDSISVAYLGLKNLAEYYYDQSVRDSLEYYCSLVDSIAKARHEYPNVLFDVKSLSSQDLLWLGNYELAMSEAMDLYRLASNLDHRYGLLRCSETLGLIYQRIRRDSDAVVSFQESLDLLKDIKDVPDIMDTKVRLTSYQLESSVRTKQYASTERILGQYMALLDEQYKIYQEKNDLLSIKREYWLLYSFYTSFYLSQGDLENAKRSLDQASSYADSNWVEGDYAINTYLTVKARYHKAAGDIPLALHCINEVLETERLPEDIQFKADILKEQGQLGEVMALYDELYSTLTKRRGTSFLRQVNQLRTLHELHEKELKETELKEAGQRIARKQDLLIFILSISVVLLILLYVLFLYYRHLRSLKNQLQREKELLLESQRQLIKEKTRAEEASLMKSAFLANMSHEVRTPLNAIVGFSGLLVEPSTDEEERKEYSSIIRNNTDLMLNLVNDVLDLSRMETGDLHFDIKDHLLLVCCQMALESVRHRIPDGVKLTFSPAGEPIVVHVDNLRLQQLLTNLLTNAAKFTEKGEINLSFQLEPDRKKVCIAVTDTGAGIPLEKQATIFNRFEKLDDYKPGVGLGLSICLLIAERLDGALFIDSSYTDGARFVLILSCEIDSSIYNPPIEV
>gi|100002554| Bd2557c Bd2557c two-component system sensor histidine kinase 3094158:3095507 reverse MW:51247
LERKYNGEGKIFPVKRHRCLMSCYYCELYTMKGNSGKAQAYLDQATAYLDSSFGDRVEAQYLRTKSFYYWKEKDYRHALSAVNLALKINRDLDKLEMKKAVLQSSGQLQEAVTIYEEIINKTETINTDAFDRQIEQLRVLNDLNDLEKQDRELKLKSEQEALKQKQIVVSIGLLLVLMGLLYMLWRIYMHTKRLRNELLQEKDSLTASEKQLRVVTKEAEAANKKKSAFIANISHEVRTPLNAIVGFSELLASSEYSEEEKIRFAGEVNHSSELLLNLVNDVLDLSRLESGKIKFSVKPNDLVACCQRALDSIRHRVKPGVRLTFTPSIESYTLNTDALRLQQLLTNLLSNAAKFTSEGEINLSFTVDEGKEEVCFSVTDTGCGIPEDKCEKIFERFEKLDDFIQGTGLGLSVCQIISEQLNGSLSVDISYKDGARFVFIHPTNLIETPI
>gi|100002555| Bd2558c Bd2558c hypothetical protein 3095527:3095985 reverse MW:17134
LRGKNIHLGRVGCNYGKLLIFIDIYFVSLRIVSDKSMSRGFLRKSSVNTFIGIVWILFAVGTSAQNAVSKFRADSIRQSLSRIQKPQDKIPLLKELIGLYWQLPEEVLALKEIIDIAMPLDSIGIVYDAMAGLSRYYPAIRTFVRVGGALETV
>gi|100002556| Bd2559 Bd2559 30S ribosomal protein S1 3096095:3097882 forward MW:67092
MENLKNIQPVEDFNWDAFEQGETYTEVSKDDLVKTYDETLNTVKDKEVVMGTVTSMNKREVVVNIGFKSDGVVPMSEFRYNPDLKIGDEVEVYIESQEDKKGQLILSHKKARATRSWDRVNEALEKDEIIKGYIKCRTKGGMIVDVFGIEAFLPGSQIDVKPIRDYDVFVGKTMEFKIVKINQEFKNVVVSHKALIEAELEQQKKDIISKLEKGQVLEGTVKNITSYGVFIDLGGVDGLIHITDLSWGRVSHPEEIVQLDQKINVVILDFDDEKKRIALGLKQLTPHPWDALDTNLKVGDKVKGKVVVMADYGAFIEIAPGVEGLIHVSEMSWTQHLRSAQDFMKVGDEIEAVILTLDRDERKMSLGIKQLKADPWENIEERFPVGSRHAAKVRNFTNFGVFVEIEEGVDGLIHISDLSWTKKIKHPSEFTQIGAEIEVQVLEIDKENRRLSLGHKQLEENPWDVFETIFTVGSIHEGTIIEVLDKGAVISLPYGVEGFATPKHLVKEDGSQAQVDEKLSFKVIEFNKEAKRIILSHSRIFEDEQKGAKATSEKKASSKRGGKKEEESGMVTGPVEKTTLGDIEELAALKEKLSGK
>gi|100002557| Bd2560c Bd2560c conserved hypothetical protein 3097971:3098210 reverse MW:8927
MGKNQLIHGNEFHLLKQAEIHKATGKLVESLNLAAGSTGGFDIYKVVEAYFTDLEKRKEINDLLGISEPCETRVTEECFS
>gi|100002558| Bd2561 Bd2561 phosphoglycolate phosphatase 3098389:3099033 forward MW:24182
MKKLVIFDLDGTLLNTIADLAHSTNHALRQNGFPTHDVKEYNFFVGNGINKLFERALPEGEKTAENILKVREEFLKHYDLHNTDRSVPYPGVPELLALLQERGIKLAVASNKYQAATRKLIAHFFPSIQFTEVLGQREGVKAKPDPSIVNEIVERASISKESTLYVGDSDVDMQTAINSEVTSCGVTWGFRPRTELEKYAPDHIAEKAEDILKFI
>gi|100002559| Bd2562 Bd2562 conserved hypothetical protein 3099382:3100299 forward MW:35872
MSGNIKKIVEPNSGIDYSLEKDFKIFTLSKELPITTYPSYIRLGIVIYCVKGNAKIDIYSNKHIITPKELIIILPGQLVALTDVSVDFQIRYFTITESFYSDILSGISRFSPHFFFYMRQHYYFKMEDVETLSFVDFFELLIRKAVDPENQYRRESVILLLRILFLDIYNHYKVNSLDSTATIDVHKKELTHKFFQLVMSNYKVNRSVTFYANSLCITPKYLTMVVKEVSGKSAKDWITEYMILELKGLLTNSTLNIQEIVEKTQFSNQSSLGRFFRRHTGLSPLQYRKKYLTTEQRTNFSKNNTI
"""
def test_seqs_to_stream(self):
"""seqs_to_stream should iterate over seqs"""
sts = seqs_to_stream
self.assertEqual(list(sts('>a\nTG\n>b\nWW\n', \
'_input_as_multiline_string')),\
[['>a','TG'],['>b','WW']])
#skipping test for file open
self.assertEqual(list(sts(['TG','WW'], '_input_as_seqs')), \
[['>0','TG'],['>1','WW']])
self.assertEqual(list(sts(['>a','TG','>b','WW'], \
'_input_as_lines')),\
[['>a','TG'],['>b','WW']])
self.assertRaises(TypeError, sts, 'abc', 'xyz')
def test_make_subject_match_scorer(self):
"""make_subject_match_scorer should keep ids matching n queries"""
qm1 = make_subject_match_scorer(1)
qm3 = make_subject_match_scorer(3)
qm5 = make_subject_match_scorer(5)
qmes = wrap_qmes(QMEBlast9(self.rec3))
self.assertEqualItems(qm1(qmes), ['ece:Z4181','ece:Z4182','ece:Z4183'])
self.assertEqualItems(qm3(qmes), ['ece:Z4181','ece:Z4183'])
self.assertEqualItems(qm5(qmes), [])
def test_make_shotgun_scorer(self):
"""make_shotgun_scorer should keep ids matching n queries"""
sg1 = make_shotgun_scorer(1)
sg2 = make_shotgun_scorer(2)
sg3 = make_shotgun_scorer(3)
sg4 = make_shotgun_scorer(4)
sg5 = make_shotgun_scorer(5)
qmes = wrap_qmes(QMEBlast9(self.rec3))
self.assertEqualItems(sg1(qmes), keep_everything_scorer(qmes))
self.assertEqualItems(sg2(qmes), \
['ece:Z4181','ece:Z4182','ece:Z4183','cvi:CV2421','ecs:ECs3717'])
self.assertEqualItems(sg3(qmes), \
['ece:Z4181','ece:Z4182','ece:Z4183'])
self.assertEqualItems(sg4(qmes), \
['ece:Z4182'])
self.assertEqualItems(sg5(qmes), [])
def test_keep_everything_scorer(self):
"""keep_everything_scorer should keep all ids found."""
k = keep_everything_scorer(wrap_qmes(QMEBlast9(self.rec2)))
self.assertEqualItems(k, \
['ece:Z4181','ecs:ECs3717','spt:SPA2730','cvi:CV2421','ece:Z4182'])
def test_ids_from_seq_lower_threshold(self):
"ids_from_seq_lower_threshold returns psiblast hits, decreasing sens"
bdb_seqs = self.fasta_recs
f = open('test_bdb', 'w')
f.write(bdb_seqs)
f.close()
temp = popen('formatdb -i test_bdb -o T -p T')
params = {'-j':2,
'-d':'test_bdb'}
query = self.query_1.split('\n')
app = PsiBlast(params=params,
InputHandler='_input_as_lines')
#the command below should result in finding itself and 2554
#it should run for max_iterations
result = ids_from_seq_lower_threshold(query, n=12, \
max_iterations=4, app=app, core_threshold=1e-50, \
lower_threshold=1e-20, step=10000)
self.assertEqual(result[0],\
[('gi|100002553', '0.0'), ('gi|100002554', '0.0')])
self.assertEqual(result[1], 4)
#if n=2, it should find the same sequences but only run for 1 iteration
#since it would hit n after the first blast search
result = ids_from_seq_lower_threshold(query, n=2, \
max_iterations=4, app=app, core_threshold=1e-50, \
lower_threshold=1e-20, step=10000)
self.assertEqual(result[0],\
[('gi|100002553', '0.0'), ('gi|100002554', '0.0')])
self.assertEqual(result[1], 1)
query = self.query_2.split('\n')
#query_2_s e-value for itself is 9e-47, it should not be found
#with the lower_threshold set to 1e-48
result = ids_from_seq_lower_threshold(query, n=12, \
max_iterations=4, app=app, core_threshold=1e-50, \
lower_threshold=1e-48, step=10000)
self.assertEqual(result[0], [])
#it also should not be found if the max_iterations is set to 1
result = ids_from_seq_lower_threshold(query, n=12, \
max_iterations=1, app=app, core_threshold=1e-50, \
lower_threshold=1e-20, step=10000)
self.assertEqual(result[0], [])
for fname in ['formatdb.log'] + glob('test_bdb*'):
remove(fname)
def test_psiblast_n_neighbors(self):
"psiblast_n_neighbors psiblasts and stops when n neighbors are reached"
bdb_seqs = self.fasta_recs
f = open('test_bdb', 'w')
f.write(bdb_seqs)
f.close()
temp = popen('formatdb -i test_bdb -o T -p T')
params = {'-j':11}
lines = bdb_seqs.split('\n')
results = psiblast_n_neighbors(lines, n=12, blast_db='test_bdb', \
method='lower_threshold', params=params,\
core_threshold=1e-50, step=10000)
#there should be 10 result entries since there were 10 queries
self.assertEqual(len(results), 10)
for i in results:
#each query should at least find itself
self.failUnless(len(results[i][0]) >= 1)
#each query should iterate 8 times since it can never reach max
self.assertEqual(results[i][1], 11)
for fname in ['formatdb.log'] + glob('test_bdb*'):
remove(fname)
def wrap_qmes(qmes):
"""Converts qmes into a dict of {q:{m:e}}"""
d = {}
for q, m, e in qmes:
if q not in d:
d[q] = {}
d[q][m] = e
return d
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_app/test_blat.py 000644 000765 000024 00000064113 12024702176 021562 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.app.util import get_tmp_filename
from cogent.app.blat import Blat, assign_reads_to_database, \
assign_dna_reads_to_dna_database, \
assign_dna_reads_to_protein_database
from os.path import join, exists
from os import remove
from re import search
__author__ = "Adam Robbins-Pianka"
__copyright__ = "Copyright 2007-2012, The QIIME Project"
__credits__ = ["Adam Robbins-Pianka", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Adam Robbins-Pianka"
__email__ = "adam.robbinspianka@colorado.edu"
__status__ = "Prototype"
class BlatTests(TestCase):
files_to_remove = []
def setUp(self):
"""Sets up files for testing.
"""
self.test_db_prot_filename = get_tmp_filename().replace('"', '')
self.test_db_prot = open(self.test_db_prot_filename, 'w')
self.test_db_dna_filename = get_tmp_filename().replace('"', '')
self.test_db_dna = open(self.test_db_dna_filename, 'w')
self.test_query_filename = get_tmp_filename().replace('"', '')
self.test_query = open(self.test_query_filename, 'w')
# write the global variables at the bottom of this file to the
# temporary test files. Can't use file-like objects because the
# external application needs actual files.
self.test_db_prot.write('\n'.join(test_db_prot))
self.test_db_dna.write('\n'.join(test_db_dna))
self.test_query.write('\n'.join(test_query))
# close the files
self.test_db_prot.close()
self.test_db_dna.close()
self.test_query.close()
# prepare output file path
self.testout = get_tmp_filename().replace('"', '')
self.files_to_remove += [self.test_db_prot_filename,
self.test_db_dna_filename,
self.test_query_filename, self.testout]
def tearDown(self):
"""Removes temporary files created during the tests
"""
for filename in self.files_to_remove:
if exists(filename): remove(filename)
def test_assign_reads_to_database(self):
"""Tests that assign_reads_to_database works as expected.
Checks the output file against the expected result when known
database and query files are used.
"""
exp = [l for l in assign_reads_exp if not l.startswith('#')]
obs_lines = assign_reads_to_database(self.test_query_filename,
self.test_db_dna_filename,
self.testout).read().splitlines()
obs = [l for l in obs_lines if not l.startswith('#')]
self.assertEqual(obs, exp)
def test_assign_dna_reads_to_dna_database(self):
"""Tests that assign_dna_reads_to_dna_database works as expected.
Checks the output file against the expected result when known
database and query files are used.
"""
exp = [l for l in assign_reads_exp if not l.startswith('#')]
obs_lines = assign_dna_reads_to_dna_database(self.test_query_filename,
self.test_db_dna_filename,
self.testout).read().splitlines()
obs = [l for l in obs_lines if not l.startswith('#')]
self.assertEqual(obs, exp)
def test_assign_dna_reads_to_protein_database(self):
"""Tests that assign_dna_reads_to_protein_database works as expected.
Checks the output file against the expected result when known
database and query files are used.
"""
exp = [l for l in assign_reads_prot_exp if not l.startswith('#')]
obs_lines = assign_dna_reads_to_protein_database(
self.test_query_filename,
self.test_db_prot_filename,
self.testout).read().splitlines()
obs = [l for l in obs_lines if not l.startswith('#')]
self.assertEqual(obs, exp)
def test_get_base_command(self):
"""Tests that _get_base_command generates the proper command given
various inputs.
"""
test_parameters_blank = {}
files = (self.test_query_filename, self.test_db_dna_filename,
self.testout)
exp_blank = 'blat %s %s %s' % (files[1], files[0], files[2])
# initialize a Blat instance with these parameters and get the
# command string
b = Blat(params = {}, HALT_EXEC=True)
# need to set the positional parameters' values
b._input_as_list(files)
cmd = b._get_base_command()
# find the end of the cd command and trim the base command
cmd_index = search('cd ".+"; ', cmd).end()
cmd = cmd[cmd_index:]
self.assertEqual(cmd, exp_blank)
test_parameters_1 = {
'-t': 'dna',
'-q': 'dna',
'-ooc': '11.ooc',
'-tileSize': 1,
'-stepSize': 2,
'-oneOff': 1,
'-minMatch': 2,
'-minScore': 3,
'-minIdentity': 4,
'-maxGap': 5,
'-makeOoc': 'N.ooc',
'-repMatch': 6,
'-mask': 'lower',
'-qMask': 'lower',
'-repeats': 'lower',
'-minRepDivergence': 7,
'-dots': 8,
'-out': 'psl',
'-maxIntron': 9}
exp_1 = 'blat %s %s ' % (files[1], files[0]) + \
'-dots=8 -makeOoc="N.ooc" -mask=lower -maxGap=5 ' + \
'-maxIntron=9 -minIdentity=4 -minMatch=2 ' + \
'-minRepDivergence=7 -minScore=3 -oneOff=1 -ooc="11.ooc" ' + \
'-out=psl -q=dna -qMask=lower -repMatch=6 -repeats=lower ' + \
'-stepSize=2 -t=dna -tileSize=1 %s' % files[2]
# initialize a Blat instance with these parameters and get the
# command string
b = Blat(params = test_parameters_1, HALT_EXEC=True)
# need to set the positional parameters' values
b._input_as_list(files)
cmd = b._get_base_command()
# find the end of the cd command and trim the base command
cmd_index = search('cd ".+"; ', cmd).end()
cmd = cmd[cmd_index:]
self.assertEqual(cmd, exp_1)
test_parameters_2 = {
'-tileSize': 1,
'-stepSize': 2,
'-minMatch': 2,
'-minScore': 3,
'-minIdentity': 4,
'-maxGap': 5,
'-makeOoc': 'N.ooc',
'-out': 'psl',
'-maxIntron': 9}
exp_2 = 'blat %s %s ' % (files[1], files[0]) + \
'-makeOoc="N.ooc" -maxGap=5 -maxIntron=9 -minIdentity=4 ' + \
'-minMatch=2 -minScore=3 -out=psl -stepSize=2 ' + \
'-tileSize=1 %s' % files[2]
# initialize a Blat instance with these parameters and get the
# command string
b = Blat(params = test_parameters_2, HALT_EXEC=True)
# need to set the positional parameters' values
b._input_as_list(files)
cmd = b._get_base_command()
# find the end of the cd command and trim the base command
cmd_index = search('cd ".+"; ', cmd).end()
cmd = cmd[cmd_index:]
self.assertEqual(cmd, exp_2)
assign_reads_exp = """# BLAT 34 [2006/03/10]
# Query: NZ_GG770509_647533119
# Database: test_db.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_GG770509_647533119 NZ_GG770509_647533119 100.00 1371 0 0 1 1371 1 1371 0.0e+00 2187.0
NZ_GG770509_647533119 NZ_ACIZ01000148_643886127 85.49 634 92 0 336 969 337 970 4.5e-234 807.0
NZ_GG770509_647533119 NZ_ACIZ01000148_643886127 86.08 237 33 0 1135 1371 1137 1373 1.2e-77 287.0
NZ_GG770509_647533119 NZ_ACIZ01000148_643886127 83.12 154 26 0 976 1129 977 1130 2.2e-48 190.0
NZ_GG770509_647533119 NZ_GG739926_647533195 78.42 329 71 0 656 984 657 985 4.8e-97 351.0
NZ_GG770509_647533119 NZ_GG739926_647533195 89.09 110 11 1 1138 1246 1141 1250 1.1e-30 131.0
NZ_GG770509_647533119 NZ_GG739926_647533195 86.96 69 9 0 1021 1089 1023 1091 3.2e-20 96.0
NZ_GG770509_647533119 NZ_GG739926_647533195 75.26 97 22 2 356 450 356 452 2.3e-13 73.0
NZ_GG770509_647533119 NZ_GG739926_647533195 90.57 53 5 0 1319 1371 1315 1367 2.5e-10 63.0
NZ_GG770509_647533119 NZ_GG739926_647533195 81.82 22 4 0 989 1010 992 1013 1.5e+02 24.0
# BLAT 34 [2006/03/10]
# Query: NZ_GG739926_647533195
# Database: test_db.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_GG739926_647533195 NZ_GG739926_647533195 100.00 1367 0 0 1 1367 1 1367 0.0e+00 2235.0
NZ_GG739926_647533195 NZ_ACIZ01000148_643886127 76.22 572 136 0 414 985 414 985 1.7e-158 556.0
NZ_GG739926_647533195 NZ_ACIZ01000148_643886127 76.80 181 42 0 1023 1203 1022 1202 6.4e-53 205.0
NZ_GG739926_647533195 NZ_ACIZ01000148_643886127 96.00 50 2 0 1209 1258 1207 1256 6.4e-14 75.0
NZ_GG739926_647533195 NZ_ACIZ01000148_643886127 88.68 53 6 0 1315 1367 1321 1373 1.6e-09 61.0
NZ_GG739926_647533195 NZ_ACIZ01000148_643886127 77.27 22 5 0 992 1013 990 1011 8.5e+02 22.0
NZ_GG739926_647533195 NZ_GG770509_647533119 79.29 280 58 0 657 936 656 935 9.9e-82 301.0
NZ_GG739926_647533195 NZ_GG770509_647533119 89.09 110 11 1 1141 1250 1138 1246 1.1e-30 131.0
NZ_GG739926_647533195 NZ_GG770509_647533119 86.96 69 9 0 1023 1091 1021 1089 3.2e-20 96.0
NZ_GG739926_647533195 NZ_GG770509_647533119 75.26 97 22 2 356 452 356 450 2.3e-13 73.0
NZ_GG739926_647533195 NZ_GG770509_647533119 90.57 53 5 0 1315 1367 1319 1371 2.5e-10 63.0
NZ_GG739926_647533195 NZ_GG770509_647533119 80.00 30 6 0 956 985 955 984 1.2e-03 41.0
NZ_GG739926_647533195 NZ_GG770509_647533119 81.82 22 4 0 992 1013 989 1010 1.5e+02 24.0
# BLAT 34 [2006/03/10]
# Query: NZ_ACIZ01000148_643886127
# Database: test_db.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_ACIZ01000148_643886127 NZ_ACIZ01000148_643886127 100.00 1373 0 0 1 1373 1 1373 0.0e+00 2165.0
NZ_ACIZ01000148_643886127 NZ_GG770509_647533119 85.49 634 92 0 337 970 336 969 4.5e-234 807.0
NZ_ACIZ01000148_643886127 NZ_GG770509_647533119 86.08 237 33 0 1137 1373 1135 1371 1.2e-77 287.0
NZ_ACIZ01000148_643886127 NZ_GG770509_647533119 83.12 154 26 0 977 1130 976 1129 2.2e-48 190.0
NZ_ACIZ01000148_643886127 NZ_GG739926_647533195 76.22 572 136 0 414 985 414 985 1.7e-158 556.0
NZ_ACIZ01000148_643886127 NZ_GG739926_647533195 76.80 181 42 0 1022 1202 1023 1203 6.4e-53 205.0
NZ_ACIZ01000148_643886127 NZ_GG739926_647533195 96.00 50 2 0 1207 1256 1209 1258 6.4e-14 75.0
NZ_ACIZ01000148_643886127 NZ_GG739926_647533195 88.68 53 6 0 1321 1373 1315 1367 1.6e-09 61.0
NZ_ACIZ01000148_643886127 NZ_GG739926_647533195 77.27 22 5 0 990 1011 992 1013 8.5e+02 22.0
""".splitlines()
assign_reads_prot_exp = """# BLAT 34x13 [2009/02/26]
# Query: NZ_GG770509_647533119_frame_1
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_GG770509_647533119_frame_1 NZ_GG770509_647533119 96.83 441 0 7 1 427 1 441 8.9e-254 872.0
# BLAT 34x13 [2009/02/26]
# Query: NZ_GG770509_647533119_frame_2
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_GG770509_647533119_frame_2 NZ_ACIZ01000148_643886127 85.37 41 6 0 359 399 362 402 8.0e-13 72.0
NZ_GG770509_647533119_frame_2 NZ_ACIZ01000148_643886127 93.75 16 1 0 419 434 421 436 1.3e+00 31.0
NZ_GG770509_647533119_frame_2 NZ_GG739926_647533195 75.86 29 7 0 320 348 326 354 2.9e-04 43.0
# BLAT 34x13 [2009/02/26]
# Query: NZ_GG770509_647533119_frame_3
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_GG770509_647533119_frame_3 NZ_ACIZ01000148_643886127 80.61 98 19 0 210 307 209 306 7.5e-39 158.0
NZ_GG770509_647533119_frame_3 NZ_ACIZ01000148_643886127 66.33 98 33 0 43 140 44 141 8.9e-27 118.0
NZ_GG770509_647533119_frame_3 NZ_ACIZ01000148_643886127 78.95 38 8 0 310 347 308 345 2.3e-08 57.0
NZ_GG770509_647533119_frame_3 NZ_ACIZ01000148_643886127 66.67 30 10 0 178 207 178 207 2.5e-01 33.0
NZ_GG770509_647533119_frame_3 NZ_GG739926_647533195 53.00 100 47 0 131 230 134 233 1.9e-18 90.0
NZ_GG770509_647533119_frame_3 NZ_GG739926_647533195 68.89 45 14 0 238 282 241 285 5.9e-09 59.0
NZ_GG770509_647533119_frame_3 NZ_GG739926_647533195 72.09 43 12 0 63 105 66 108 3.0e-08 56.0
# BLAT 34x13 [2009/02/26]
# Query: NZ_GG739926_647533195_frame_1
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_GG739926_647533195_frame_1 NZ_GG739926_647533195 100.00 437 0 0 1 437 1 437 1.7e-263 904.0
NZ_GG739926_647533195_frame_1 NZ_ACIZ01000148_643886127 69.86 73 22 0 213 285 209 281 1.1e-20 98.0
NZ_GG739926_647533195_frame_1 NZ_ACIZ01000148_643886127 53.33 60 28 0 148 207 145 204 1.3e-06 51.0
NZ_GG739926_647533195_frame_1 NZ_ACIZ01000148_643886127 60.53 38 15 0 66 103 64 101 1.9e-03 41.0
NZ_GG739926_647533195_frame_1 NZ_ACIZ01000148_643886127 76.92 26 6 0 2 27 3 28 9.7e-03 38.0
NZ_GG739926_647533195_frame_1 NZ_ACIZ01000148_643886127 69.57 23 7 0 288 310 285 307 4.8e+00 29.0
NZ_GG739926_647533195_frame_1 NZ_ACIZ01000148_643886127 90.00 10 1 0 134 143 132 141 1.6e+04 18.0
# BLAT 34x13 [2009/02/26]
# Query: NZ_GG739926_647533195_frame_2
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_GG739926_647533195_frame_2 NZ_GG770509_647533119 66.67 42 14 0 270 311 276 317 2.3e-08 57.0
NZ_GG739926_647533195_frame_2 NZ_GG770509_647533119 60.00 45 18 0 185 229 188 232 3.9e-06 49.0
NZ_GG739926_647533195_frame_2 NZ_GG770509_647533119 80.00 20 4 0 247 266 251 270 5.6e-01 32.0
# BLAT 34x13 [2009/02/26]
# Query: NZ_GG739926_647533195_frame_3
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_GG739926_647533195_frame_3 NZ_ACIZ01000148_643886127 94.44 18 1 0 390 407 385 402 4.3e-03 39.0
# BLAT 34x13 [2009/02/26]
# Query: NZ_ACIZ01000148_643886127_frame_1
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_ACIZ01000148_643886127_frame_1 NZ_ACIZ01000148_643886127 100.00 436 0 0 1 436 1 436 2.1e-261 897.0
NZ_ACIZ01000148_643886127_frame_1 NZ_GG739926_647533195 78.57 42 9 0 240 281 244 285 4.0e-10 63.0
NZ_ACIZ01000148_643886127_frame_1 NZ_GG739926_647533195 60.53 38 15 0 64 101 66 103 1.9e-03 41.0
NZ_ACIZ01000148_643886127_frame_1 NZ_GG739926_647533195 76.92 26 6 0 3 28 2 27 9.7e-03 38.0
NZ_ACIZ01000148_643886127_frame_1 NZ_GG739926_647533195 69.57 23 7 0 285 307 288 310 4.8e+00 29.0
# BLAT 34x13 [2009/02/26]
# Query: NZ_ACIZ01000148_643886127_frame_2
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_ACIZ01000148_643886127_frame_2 NZ_GG770509_647533119 79.59 147 26 2 182 324 189 335 2.3e-61 233.0
NZ_ACIZ01000148_643886127_frame_2 NZ_GG770509_647533119 72.73 33 9 0 128 160 137 169 5.0e-04 42.0
NZ_ACIZ01000148_643886127_frame_2 NZ_GG770509_647533119 90.91 22 2 0 70 91 76 97 2.5e-03 40.0
# BLAT 34x13 [2009/02/26]
# Query: NZ_ACIZ01000148_643886127_frame_3
# Database: /home/adro2179/metagenome/test_db_prot.fasta
# Fields: Query id, Subject id, % identity, alignment length, mismatches, gap openings, q. start, q. end, s. start, s. end, e-value, bit score
NZ_ACIZ01000148_643886127_frame_3 NZ_GG770509_647533119 84.21 38 4 1 360 395 367 404 3.0e-08 56.0
NZ_ACIZ01000148_643886127_frame_3 NZ_GG770509_647533119 94.12 17 1 0 413 429 425 441 1.6e+00 31.0
NZ_ACIZ01000148_643886127_frame_3 NZ_GG739926_647533195 78.57 28 5 1 321 347 326 353 1.5e-03 41.0"""
assign_reads_prot_exp = assign_reads_prot_exp.splitlines()
test_db_prot = """>NZ_GG770509_647533119
YLEFDPGSERTLAAGLTHASRASGRRVSNAWERTICYGITQGNLCYRMetWKVGKSARVGLASWWGKGSPRRRSIAGLRGSATLGLRHGPDSYGRQQWGILDNGRKPDPAMetPRERPGCKALSPVKMetTVTGEEAPANFVPAAAVIRRGLALFGFTGRKAHVGGLLSQGNPGAQPRNCLYWKSVWRVEFRVRNSIFGGTPVAKAAHWTNRGAKAWGANRIRYPGSPRRKRMetLAVGASVAQLTHTFRLGSAVARLKLKGIDGGPHKRWSMetWFNSKQRAEPYQPLTSTGAAWLSSARVVRCWVKSRNERNPRPLPAWALGDCRAGGRWGRQVLMetALTGWATHVLQWWSVGSEHASVSSPPSQFGCTLQLECRSWNRSRISMetPRIRSRALYTPPVTPWELVLPEGACAGDHGRVSDWGEVVTRPGNLRLDHLLS
>NZ_GG739926_647533195
WEFDPGSGTLATGLTHASRGTGARVSNAYPTFPRPRDNLPKGRLIPYVQSRSRMGMRPISLLAGQRPTKASIGRGSERKAPHTGTETRSRLLREAAVRNIGQWAEATSQVACRTTAYGLTAFMRGYAGTAIRTGFRASSRGNTEGPGVIRIYWVRERRPPCKRAVKSSGPTAALRRELLGLSAPEAGGIRGVAVKCLDITKNPDCEGSPLWRLTLRLEGAGIEQDIPWSARTMDTRCPALGGQAKALSIPPGEYAGNGETQRNRGPAQAEEHVVFDDTRGTLPGLELRCCMVVVSSCREVSAQVPRAQPLSAVAIGRALCGHCRRKVEEGGDDVKSARPLRPGPHTCYNGRQRAVRAQVRVNPLRSQFGWGLQPDPRSWIRSRISHGAVNTFPGLVHTARQAMKAGGASPCRPRAKPVIGAKSQGSRTGRCGWNTSF
>NZ_ACIZ01000148_643886127
NMEFDPGSGTLAACLIHASRTSGGRVSNTWVTCPVGDNIWKQMLIPHKESRFWMDPRRISLVRRLTKAMIRSRTERLIGHIGTETRPKLLREAAVGNLPQWTQVWSNAAVKKAFGSNSVVGEDDGIQPESHGLRASSRGNTVASVIRIYWASERRRFFKSDVKALGLTEEVHRKLGNLSAEEDSGTPCVAVKCVDIWKNTSGEGGCLVLTLRLESMGSEQDIPWSMPTMNARCWSFSAAANALSIPPGEYDRKVETQRNRGPAQAVEHVVFEATRRTLPGLDIDRWCMVVVSSCREMLGVPQRAQPLLVASMGTLVRLPVTNRRKVGMTSNHHAPYDLGYTRATMDGNELRDREVKLISSILSSDVGCNSPTEVGIASNRGSARRGEYVPGPCTHRPSHHESLHPKPVRSEPSKVGQMIRVKSQGSRRRTCGWITS"""
test_db_prot = test_db_prot.splitlines()
test_db_dna = """>NZ_GG770509_647533119
UACUUGGAGUUUGAUCCUGGCUCAGAACGAACGCUGGCGGCAGGCUUAACACAUGCAAGUCGAGCGAGCGGCAGACGGGUGAGUAACGCGUGGGAACGUACCAUUUGCUACGGAAUAACUCAGGGAAACUUGUGCUAAUACCGUAUGUGGAAAGUCGGCAAAUGAUCGGCCCGCGUUGGAUUAGCUAGUUGGUGGGGUAAAGGCUCACCAAGGCGACGAUCCAUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGCAAGCCUGAUCCAGCCAUGCCGCGUGAGUGAUGAAGGCCCUAGGGUUGUAAAGCUCUUUCACCGGUGAAGAUGACGGUAACCGGAGAAGAAGCCCCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAAGGGGGCUAGCGUUGUUCGGAUUUACUGGGCGUAAAGCGCACGUAGGCGGACUUUUAAGUCAGGGGUGAAAUCCCGGGGCUCAACCCCGGAACUGCCUUUGAUACUGGAAGUCUUGAGUAUGGUAGAGGUGAGUGGAAUUCCGAGUGUAGAGGUGAAAUUCGUAGAUAUUCGGAGGAACACCAGUGGCGAAGGCGGCUCACUGGACCAACUGACGCUGAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAAUGUUAGCCGUCGGGGCUUCGGUGGCGCAGCUAACGCAUUAAACAUUCCGCCUGGGGAGUGCGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGCAGAACCUUACCAGCCCUUGACAUCGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGCCCUUAGUUGCCAGCAUGGGCACUCUAAGGGGACUGCCGGUGAUAAGCCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUACGGGCUGGGCUACACACGUGCUACAAUGGUGGUCAGUGGGCAGCGAGCACGCGAGUGUGAGCUAAUCUCCGCCAUCUCAGUUCGGAUGCACUCUGCAACUCGAGUGCAGAAGUUGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUUGGUUUUACCCGAAGGCGCUUGCUAGGCAGGCGACCACGGUAGGGUCAGCGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCGGCUGGAUCACCUCCUUUCU
>NZ_GG739926_647533195
UAAUGGGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCUACAGGCUUAACACAUGCAAGUCGAGGGACCGGCGCACGGGUGAGUAACGCGUAUCCAACCUUCCCGCGACCAAGGGAUAACCUGCCGAAAGGCAGACUAAUACCUUAUGUCCAAAGUCGGUCACGGAUGGGGAUGCGUCCGAUUAGCUUGUUGGCGGGGCAACGGCCCACCAAGGCAUCGAUCGGUAGGGGUUCUGAGAGGAAGGCCCCCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGAGGAAUAUUGGUCAAUGGGCGGAAGCCUGAACCAGCCAAGUAGCGUGCAGGACGACGGCCUACGGGUUGUAAACUGCUUUUAUGCGGGGAUAUGCAGGUACCGCAUGAAUAAGGACCGGCUAAUUCCGUGCCAGCAGCCGCGGUAAUACGGAAGGUCCGGGCGUUAUCCGGAUUUAUUGGGUUUAAAGGGAGCGCAGGCCGCCGUGCAAGCGUGCCGUGAAAAGCAGCGGCCCAACCGCUGCCCUGCGGCGCGAACUGCUUGGCUUGAGUGCGCCGGAAGCGGGCGGAAUUCGUGGUGUAGCGGUGAAAUGCUUAGAUAUCACGAAGAACCCCGAUUGCGAAGGCAGCCCGCUGUGGCGACUGACGCUGAGGCUCGAAGGUGCGGGUAUCGAACAGGAUUAGAUACCCUGGUAGUCCGCACGGUAAACGAUGGAUACCCGCUGUCCGGCUCUGGGCGGCCAAGCGAAAGCGUUAAGUAUCCCACCUGGGGAGUACGCCGGCAACGGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGAGGAACAUGUGGUUUAAUUCGAUGAUACGCGAGGAACCUUACCCGGGCUUGAAUUGUGAAGGUGCUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUCGGCUCAAGUGCCAUAACGAGCGCAACCCCUCUCCGCAGUUGCCAUCGGCCGGGCACUCUGCGGACACUGCCGCCGCAAGGUGGAGGAAGGUGGGGAUGACGUCAAAUCAGCACGGCCCUUACGUCCGGGGCCACACACGUGUUACAAUGGCCGGCAGAGGGCUGUCCGCGCGCAAGUGCGGGUGAAUCCCCUCCGGUCCCAGUUCGGAUGGGGUCUGCAACCCGACCCCAGAAGCUGGAUUCGCUAGUAAUCGCGCAUCAGCCAUGGCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCAAGCCAUGAAAGCCGGGGGUGCCUGAAGUCCGUGUCGGCCUAGGGCAAAACCGGUGAUUGGGGCUAAGUCGUAACAAGGUAGCCGUACCGGAAGGUGCGGCUGGAACACCUCCUUUCU
>NZ_ACIZ01000148_643886127
AAUAUGGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAACGAGUGGCGGACGGGUGAGUAACACGUGGGUAACCUGCCCUUAAGUGGGGGAUAACAUUUGGAAACAGAUGCUAAUACCGCAUAAAGAAAGUCGCUUUUGGAUGGACCCGCGGCGUAUUAGCUAGUUGGUGAGGUAACGGCUCACCAAGGCAAUGAUACGUAGCCGAACUGAGAGGUUGAUCGGCCACAUUGGGACUGAGACACGGCCCAAACUCCUACGGGAGGCAGCAGUAGGGAAUCUUCCACAAUGGACGCAAGUCUGAUGGAGCAACGCCGCGUGAGUGAAGAAGGCUUUCGGGUCGUAAAACUCUGUUGUUGGAGAAGAUGACGGUAUCCAACCAGAAAGCCACGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGUGGCAAGCGUUAUCCGGAUUUAUUGGGCGUAAAGCGAGCGCAGGCGGUUUUUUAAGUCUGAUGUGAAAGCCCUCGGCUUAACCGAGGAAGUGCAUCGGAAACUGGGAAACUUGAGUGCAGAAGAGGACAGUGGAACUCCAUGUGUAGCGGUGAAAUGCGUAGAUAUAUGGAAGAACACCAGUGGCGAAGGCGGCUGUCUGGUCUGACUGACGCUGAGGCUCGAAAGCAUGGGUAGCGAACAGGAUUAGAUACCCUGGUAGUCCAUGCCGUAAACGAUGAAUGCUAGGUGUUGGAGCUUCAGUGCCGCAGCUAACGCAUUAAGCAUUCCGCCUGGGGAGUACGACCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAGGUCUUGACAUCGACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUGACUAGUUGCCAGCAUGGGCACUCUAGUAAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGACCUGGGCUACACACGUGCUACAAUGGAUGGCAACGAGUUGCGAGACCGCGAGGUCAAGCUAAUCUCUUCCAUUCUCAGUUCGGAUGUAGGCUGCAACUCGCCUACAGAAGUCGGAAUCGCUAGUAAUCGCGGAUCAGCACGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGAGAGUUUGUAACACCCGAAGCCGGUGCGUAGCGAGCCGUCUAAGGUGGGACAAAUGAUUAGGGUGAAGUCGUAACAAGGUAGCCGUAGGAGAACCUGCGGCUGGAUCACCUCCUUUCU"""
test_db_dna = test_db_dna.splitlines()
test_query = """>NZ_GG770509_647533119
UACUUGGAGUUUGAUCCUGGCUCAGAACGAACGCUGGCGGCAGGCUUAACACAUGCAAGUCGAGCGAGCGGCAGACGGGUGAGUAACGCGUGGGAACGUACCAUUUGCUACGGAAUAACUCAGGGAAACUUGUGCUAAUACCGUAUGUGGAAAGUCGGCAAAUGAUCGGCCCGCGUUGGAUUAGCUAGUUGGUGGGGUAAAGGCUCACCAAGGCGACGAUCCAUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGCAAGCCUGAUCCAGCCAUGCCGCGUGAGUGAUGAAGGCCCUAGGGUUGUAAAGCUCUUUCACCGGUGAAGAUGACGGUAACCGGAGAAGAAGCCCCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAAGGGGGCUAGCGUUGUUCGGAUUUACUGGGCGUAAAGCGCACGUAGGCGGACUUUUAAGUCAGGGGUGAAAUCCCGGGGCUCAACCCCGGAACUGCCUUUGAUACUGGAAGUCUUGAGUAUGGUAGAGGUGAGUGGAAUUCCGAGUGUAGAGGUGAAAUUCGUAGAUAUUCGGAGGAACACCAGUGGCGAAGGCGGCUCACUGGACCAACUGACGCUGAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAAUGUUAGCCGUCGGGGCUUCGGUGGCGCAGCUAACGCAUUAAACAUUCCGCCUGGGGAGUGCGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGCAGAACCUUACCAGCCCUUGACAUCGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGCCCUUAGUUGCCAGCAUGGGCACUCUAAGGGGACUGCCGGUGAUAAGCCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUACGGGCUGGGCUACACACGUGCUACAAUGGUGGUCAGUGGGCAGCGAGCACGCGAGUGUGAGCUAAUCUCCGCCAUCUCAGUUCGGAUGCACUCUGCAACUCGAGUGCAGAAGUUGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUUGGUUUUACCCGAAGGCGCUUGCUAGGCAGGCGACCACGGUAGGGUCAGCGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCGGCUGGAUCACCUCCUUUCU
>NZ_GG739926_647533195
UAAUGGGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCUACAGGCUUAACACAUGCAAGUCGAGGGACCGGCGCACGGGUGAGUAACGCGUAUCCAACCUUCCCGCGACCAAGGGAUAACCUGCCGAAAGGCAGACUAAUACCUUAUGUCCAAAGUCGGUCACGGAUGGGGAUGCGUCCGAUUAGCUUGUUGGCGGGGCAACGGCCCACCAAGGCAUCGAUCGGUAGGGGUUCUGAGAGGAAGGCCCCCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGAGGAAUAUUGGUCAAUGGGCGGAAGCCUGAACCAGCCAAGUAGCGUGCAGGACGACGGCCUACGGGUUGUAAACUGCUUUUAUGCGGGGAUAUGCAGGUACCGCAUGAAUAAGGACCGGCUAAUUCCGUGCCAGCAGCCGCGGUAAUACGGAAGGUCCGGGCGUUAUCCGGAUUUAUUGGGUUUAAAGGGAGCGCAGGCCGCCGUGCAAGCGUGCCGUGAAAAGCAGCGGCCCAACCGCUGCCCUGCGGCGCGAACUGCUUGGCUUGAGUGCGCCGGAAGCGGGCGGAAUUCGUGGUGUAGCGGUGAAAUGCUUAGAUAUCACGAAGAACCCCGAUUGCGAAGGCAGCCCGCUGUGGCGACUGACGCUGAGGCUCGAAGGUGCGGGUAUCGAACAGGAUUAGAUACCCUGGUAGUCCGCACGGUAAACGAUGGAUACCCGCUGUCCGGCUCUGGGCGGCCAAGCGAAAGCGUUAAGUAUCCCACCUGGGGAGUACGCCGGCAACGGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGAGGAACAUGUGGUUUAAUUCGAUGAUACGCGAGGAACCUUACCCGGGCUUGAAUUGUGAAGGUGCUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUCGGCUCAAGUGCCAUAACGAGCGCAACCCCUCUCCGCAGUUGCCAUCGGCCGGGCACUCUGCGGACACUGCCGCCGCAAGGUGGAGGAAGGUGGGGAUGACGUCAAAUCAGCACGGCCCUUACGUCCGGGGCCACACACGUGUUACAAUGGCCGGCAGAGGGCUGUCCGCGCGCAAGUGCGGGUGAAUCCCCUCCGGUCCCAGUUCGGAUGGGGUCUGCAACCCGACCCCAGAAGCUGGAUUCGCUAGUAAUCGCGCAUCAGCCAUGGCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCAAGCCAUGAAAGCCGGGGGUGCCUGAAGUCCGUGUCGGCCUAGGGCAAAACCGGUGAUUGGGGCUAAGUCGUAACAAGGUAGCCGUACCGGAAGGUGCGGCUGGAACACCUCCUUUCU
>NZ_ACIZ01000148_643886127
AAUAUGGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAACGAGUGGCGGACGGGUGAGUAACACGUGGGUAACCUGCCCUUAAGUGGGGGAUAACAUUUGGAAACAGAUGCUAAUACCGCAUAAAGAAAGUCGCUUUUGGAUGGACCCGCGGCGUAUUAGCUAGUUGGUGAGGUAACGGCUCACCAAGGCAAUGAUACGUAGCCGAACUGAGAGGUUGAUCGGCCACAUUGGGACUGAGACACGGCCCAAACUCCUACGGGAGGCAGCAGUAGGGAAUCUUCCACAAUGGACGCAAGUCUGAUGGAGCAACGCCGCGUGAGUGAAGAAGGCUUUCGGGUCGUAAAACUCUGUUGUUGGAGAAGAUGACGGUAUCCAACCAGAAAGCCACGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGUGGCAAGCGUUAUCCGGAUUUAUUGGGCGUAAAGCGAGCGCAGGCGGUUUUUUAAGUCUGAUGUGAAAGCCCUCGGCUUAACCGAGGAAGUGCAUCGGAAACUGGGAAACUUGAGUGCAGAAGAGGACAGUGGAACUCCAUGUGUAGCGGUGAAAUGCGUAGAUAUAUGGAAGAACACCAGUGGCGAAGGCGGCUGUCUGGUCUGACUGACGCUGAGGCUCGAAAGCAUGGGUAGCGAACAGGAUUAGAUACCCUGGUAGUCCAUGCCGUAAACGAUGAAUGCUAGGUGUUGGAGCUUCAGUGCCGCAGCUAACGCAUUAAGCAUUCCGCCUGGGGAGUACGACCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAGGUCUUGACAUCGACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUGACUAGUUGCCAGCAUGGGCACUCUAGUAAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGACCUGGGCUACACACGUGCUACAAUGGAUGGCAACGAGUUGCGAGACCGCGAGGUCAAGCUAAUCUCUUCCAUUCUCAGUUCGGAUGUAGGCUGCAACUCGCCUACAGAAGUCGGAAUCGCUAGUAAUCGCGGAUCAGCACGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGAGAGUUUGUAACACCCGAAGCCGGUGCGUAGCGAGCCGUCUAAGGUGGGACAAAUGAUUAGGGUGAAGUCGUAACAAGGUAGCCGUAGGAGAACCUGCGGCUGGAUCACCUCCUUUCU"""
test_query = test_query.splitlines()
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_bwa.py 000644 000765 000024 00000042272 12024702176 021413 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from os.path import join, exists
from os import remove, getcwd
from cogent.app.bwa import BWA, BWA_index, BWA_aln, BWA_samse, \
BWA_sampe, BWA_bwasw, create_bwa_index_from_fasta_file, \
assign_reads_to_database
from cogent.app.util import get_tmp_filename, ApplicationError
__author__ = "Adam Robbins-Pianka"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Adam Robbins-Pianka", "Daniel McDonald", "Jai Ram Rideout"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Adam Robbins-Pianka"
__email__ = "adam.robbinspianka@colorado.edu"
__status__ = "Production"
class BWAtests(TestCase):
"""Tests for the BWA app controller
"""
# keeps track of which files are created during the tests so that they
# can be removed during tearDown
files_to_remove = []
def setUp(self):
"""Performs setup for the tests.
Nothing to set up for these tests.
"""
pass
def tearDown(self):
"""Properly and politely terminates the test.
Removes files created during the tests.
"""
for f in self.files_to_remove:
if exists(f):
remove(f)
def test_check_arguments(self):
"""Tests the "check_arguments" method of the BWA base class.
Arguments passed to certain parameters of the various subcommands can
take only certain values. The check_arguments function enforces these
constraints. This function ensures that the rules are being enforced
as expected.
"""
# set up test parameters
# should pass
index_params_is = {'-a': 'is'}
# should pass
index_params_bwtsw = {'-a': 'bwtsw'}
# should fail, -a must be one of "is" or "bwtsw"
index_params_invalid = {'-a': 'invalid'}
# should fail, -p must specify a prefix that is an absolute path
index_params_invalid_prefix = {'-p': 'invalid'}
# should pass
index_params_valid_prefix = {'-p': '/prefix'}
# instantiate objects built from the above parameters
index_is = BWA_index(params=index_params_is, HALT_EXEC=True)
index_bwtsw = BWA_index(params=index_params_bwtsw, HALT_EXEC=True)
index_invalid = BWA_index(params=index_params_invalid, HALT_EXEC=True)
index_invalid_prefix = BWA_index(params=index_params_invalid_prefix, \
HALT_EXEC=True)
index_valid_prefix = BWA_index(params=index_params_valid_prefix, \
HALT_EXEC=True)
# Should not be allowed
self.assertRaisesRegexp(ApplicationError, "Invalid argument",
index_invalid.check_arguments)
self.assertRaisesRegexp(ApplicationError, "Invalid argument",
index_invalid_prefix.check_arguments)
# Should execute and not raise any exceptions
index_is.check_arguments()
index_bwtsw.check_arguments()
index_valid_prefix.check_arguments()
# The rest of the _valid_arguments are for checking is_int and is_float
# and they all use the same function from the base-class, so testing
# just one of the subcommands should suffice
# -n must be a float (expressed either as a float or as a string)
# -o must be an int (expressed either as an int or as a string)
# pass, both valid
aln_params_valid = {'-n': 3.0, '-o': 5, '-f':'/sai_out'}
# fail, second invalid
aln_params_invalid1 = {'-n': 3.0, '-o': 'nope', '-f':'/sai_out'}
# fail, first invalid
aln_params_invalid2 = {'-n': '3.5.1', '-o': 4, '-f':'/sai_out'}
# fail, did not specify -f
aln_params_invalid3 = {'-n': 3.0, '-o': 5}
# instantiate objects
aln_valid = BWA_aln(params=aln_params_valid, HALT_EXEC=True)
aln_invalid1 = BWA_aln(params=aln_params_invalid1, HALT_EXEC=True)
aln_invalid2 = BWA_aln(params=aln_params_invalid2, HALT_EXEC=True)
aln_invalid3 = BWA_aln(params=aln_params_invalid3, HALT_EXEC=True)
test_paths = {'prefix': '/fa_in', 'fastq_in': '/fq_in'}
# Should Halt Exec (AssertionError) right before execution
self.assertRaisesRegexp(AssertionError, 'Halted exec', aln_valid,
test_paths)
# also need to make sure the base command is correct
self.assertIn('; bwa aln -f /sai_out -n 3.0 -o 5 /fa_in /fq_in',
aln_valid.BaseCommand)
# Should fail
self.assertRaisesRegexp(ApplicationError,
"Invalid argument", aln_invalid1,
test_paths)
self.assertRaisesRegexp(ApplicationError,
"Invalid argument", aln_invalid2,
test_paths)
self.assertRaisesRegexp(ApplicationError,
"Please specify an output file",
aln_invalid3, test_paths)
def test_input_as_dict(self):
"""Tests the input handler (_input_as_dict)
The input handler should throw exceptions if there are not enough
arguments, or if there are unrecognized arguments, or if a file path
appears to be a relative filepath.
"""
# Arguments for BWA_bwasw, which was chosen since it is the only one
# that also has an optional argument (optional arguments are denoted
# by a leading underscore)
missing = {'prefix':'/fa_in', '_query_fasta_2': '/mate'}
extra = {'prefix':'/fa_in', 'query_fasta':'/query_fasta',
'extra':'/param'}
rel_fp = {'prefix':'fa_in', 'query_fasta':'/query_fasta'}
valid = {'prefix':'/fa_in', 'query_fasta':'/query_fasta'}
valid_with_mate = {'prefix':'/fa_in', 'query_fasta':'/query_fasta',
'_query_fasta_2':'/mate'}
# instantiate the object
bwasw = BWA_bwasw(params={'-f':'/sam_out'}, HALT_EXEC=True)
# should raise ApplicationError for wrong I/O files; failure
self.assertRaisesRegexp(ApplicationError, "Missing required input",
bwasw, missing)
self.assertRaisesRegexp(ApplicationError, "Invalid input arguments",
bwasw, extra)
self.assertRaisesRegexp(ApplicationError, "Only absolute paths",
bwasw, rel_fp)
# should raise AssertionError (Halt Exec); success
# tests valid arguments with and without the optional
# _query_fasta_2 argument
self.assertRaisesRegexp(AssertionError, 'Halted exec', bwasw, valid)
self.assertRaisesRegexp(AssertionError, 'Halted exec', bwasw,
valid_with_mate)
def test_get_base_command(self):
"""Tests the function that generates the command string.
Tests whether an object can be instantiated and then called using
one set of files, and then another set of files.
Since the structure of the various sublcasses is consistent, testing
that the correct command is generated by one of the subclasses should
suffice here.
"""
# instantiate one instance
aln = BWA_aln(params = {'-n': 1.0, '-f':'/sai_out'}, HALT_EXEC=True)
# set up two different sets of files
first_files = {'prefix':'/fa_in1', 'fastq_in':'/fq_in1'}
second_files = {'prefix':'/fa_in2', 'fastq_in':'/fq_in2'}
# make sure both sets run, and that the command appears to be correct
self.assertRaisesRegexp(AssertionError,
'Halted exec', aln, first_files)
self.assertIn('; bwa aln -f /sai_out -n 1.0 /fa_in1 /fq_in1',
aln.BaseCommand)
self.assertRaisesRegexp(AssertionError, 'Halted exec', aln,
second_files)
self.assertIn('; bwa aln -f /sai_out -n 1.0 /fa_in2 /fq_in2',
aln.BaseCommand)
# instantiate another object, to test that there is no cross-talk
# between instances with the same baseclass
aln2 = BWA_aln(params = {'-n': 2.5, '-o': 7, '-f':'/sai_out'},
HALT_EXEC=True)
self.assertRaisesRegexp(AssertionError, 'Halted exec', aln2,
first_files)
self.assertIn('; bwa aln -f /sai_out -n 2.5 -o 7 /fa_in1 /fq_in1',
aln2.BaseCommand)
def test_get_result_paths(self):
"""Tests the function that retrieves the result paths.
aln, sampe, samse, bwasw return only one file.
BWA_index returns 5 files, and the name depends on whether or not the
-p option is on or not
"""
# instantiate objects
index = BWA_index(params = {}, HALT_EXEC=True)
index2 = BWA_index(params = {'-p':'/prefix'}, HALT_EXEC=True)
aln = BWA_aln(params = {'-f':'/sai_out'}, HALT_EXEC=True)
samse = BWA_samse(params = {'-f':'/sam_out'}, HALT_EXEC=True)
sampe = BWA_sampe(params = {'-f':'/sam_out'}, HALT_EXEC=True)
bwasw = BWA_bwasw(params = {'-f':'/sam_out'}, HALT_EXEC=True)
# pass in the data, and make sure the output paths are as expected.
# -p is off here
index_data = {'fasta_in':'/fa_in'}
results = index._get_result_paths(index_data)
self.assertEqual(results['.amb'].Path, '/fa_in.amb')
self.assertEqual(results['.ann'].Path, '/fa_in.ann')
self.assertEqual(results['.bwt'].Path, '/fa_in.bwt')
self.assertEqual(results['.pac'].Path, '/fa_in.pac')
self.assertEqual(results['.sa'].Path, '/fa_in.sa')
# pass in the data, and make sure the output paths are as expected.
# -p is on here
results = index2._get_result_paths(index_data)
self.assertEqual(results['.amb'].Path, '/prefix.amb')
self.assertEqual(results['.ann'].Path, '/prefix.ann')
self.assertEqual(results['.bwt'].Path, '/prefix.bwt')
self.assertEqual(results['.pac'].Path, '/prefix.pac')
self.assertEqual(results['.sa'].Path, '/prefix.sa')
# pass in the data, and make sure the output path is as expected
aln_data = {'prefix':'/fa_in', 'fastq_in':'/fq_in'}
results = aln._get_result_paths(aln_data)
self.assertEqual(results['output'].Path, '/sai_out')
samse_data = {'prefix':'/fa_in', 'sai_in':'/sai_in',
'fastq_in':'/fq_in'}
results = samse._get_result_paths(samse_data)
self.assertEqual(results['output'].Path, '/sam_out')
sampe_data = {'prefix':'/fa_in', 'sai1_in':'/sai1_in',
'sai2_in':'/sai2_in', 'fastq1_in':'/fq1_in',
'fastq2_in':'/fq2_in'}
results = sampe._get_result_paths(sampe_data)
self.assertEqual(results['output'].Path, '/sam_out')
def test_create_bwa_index_from_fasta_file(self):
"""Test create_bwa_index_from_fasta_file
Makes sure that the file paths are as expected.
"""
# get a new temp file for the input fasta
fasta_in = get_tmp_filename(suffix=".fna")
# write the test fasta (see end of this file) to the temp file
fasta = open(fasta_in, 'w')
fasta.write(test_fasta)
fasta.close()
# make sure to remove this fasta file upon tearDown
self.files_to_remove.append(fasta_in)
# run the function
results = create_bwa_index_from_fasta_file(fasta_in, {})
# for each of the 5 output files (not counting stdout, stderr, and
# the exitStatus), make sure the file paths are as expcted.
for filetype, result in results.iteritems():
if filetype not in ('ExitStatus'):
# be sure to remove these 5 files
self.files_to_remove.append(result.name)
if filetype not in ('StdOut', 'ExitStatus', 'StdErr'):
self.assertEqual(fasta_in + filetype, result.name)
def test_assign_reads_to_database(self):
"""Tests for proper failure in assign_reads_to_database
"""
# sets of params that should cause failure
no_alg = {}
wrong_alg = {'algorithm': 'not_an_algorithm'}
no_aln_params = {'algorithm': 'bwa-short'}
# dummy files -- checking for failure as expected, so the function
# won't get as far as actually running the program
database = '/db'
query = '/query'
out = '/sam'
self.assertRaisesRegexp(ApplicationError,
"Must specify which algorithm",
assign_reads_to_database, query, database, out,
no_alg)
self.assertRaisesRegexp(ApplicationError, "Unknown algorithm",
assign_reads_to_database, query, database, out,
wrong_alg)
self.assertRaisesRegexp(ApplicationError,
"aln is an intermediate step",
assign_reads_to_database, query, database, out,
no_aln_params)
test_fasta = '''>NZ_GG770509_647533119
UACUUGGAGUUUGAUCCUGGCUCAGAACGAACGCUGGCGGCAGGCUUAACACAUGCAAGUCGAGCGAGCGGCAGACGGGUGAGUAACGCGUGGGAACGUACCAUUUGCUACGGAAUAACUCAGGGAAACUUGUGCUAAUACCGUAUGUGGAAAGUCGGCAAAUGAUCGGCCCGCGUUGGAUUAGCUAGUUGGUGGGGUAAAGGCUCACCAAGGCGACGAUCCAUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGCAAGCCUGAUCCAGCCAUGCCGCGUGAGUGAUGAAGGCCCUAGGGUUGUAAAGCUCUUUCACCGGUGAAGAUGACGGUAACCGGAGAAGAAGCCCCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAAGGGGGCUAGCGUUGUUCGGAUUUACUGGGCGUAAAGCGCACGUAGGCGGACUUUUAAGUCAGGGGUGAAAUCCCGGGGCUCAACCCCGGAACUGCCUUUGAUACUGGAAGUCUUGAGUAUGGUAGAGGUGAGUGGAAUUCCGAGUGUAGAGGUGAAAUUCGUAGAUAUUCGGAGGAACACCAGUGGCGAAGGCGGCUCACUGGACCAACUGACGCUGAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAAUGUUAGCCGUCGGGGCUUCGGUGGCGCAGCUAACGCAUUAAACAUUCCGCCUGGGGAGUGCGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGCAGAACCUUACCAGCCCUUGACAUCGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGCCCUUAGUUGCCAGCAUGGGCACUCUAAGGGGACUGCCGGUGAUAAGCCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUACGGGCUGGGCUACACACGUGCUACAAUGGUGGUCAGUGGGCAGCGAGCACGCGAGUGUGAGCUAAUCUCCGCCAUCUCAGUUCGGAUGCACUCUGCAACUCGAGUGCAGAAGUUGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUUGGUUUUACCCGAAGGCGCUUGCUAGGCAGGCGACCACGGUAGGGUCAGCGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCGGCUGGAUCACCUCCUUUCU
>NZ_GG739926_647533195
UAAUGGGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCUACAGGCUUAACACAUGCAAGUCGAGGGACCGGCGCACGGGUGAGUAACGCGUAUCCAACCUUCCCGCGACCAAGGGAUAACCUGCCGAAAGGCAGACUAAUACCUUAUGUCCAAAGUCGGUCACGGAUGGGGAUGCGUCCGAUUAGCUUGUUGGCGGGGCAACGGCCCACCAAGGCAUCGAUCGGUAGGGGUUCUGAGAGGAAGGCCCCCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGAGGAAUAUUGGUCAAUGGGCGGAAGCCUGAACCAGCCAAGUAGCGUGCAGGACGACGGCCUACGGGUUGUAAACUGCUUUUAUGCGGGGAUAUGCAGGUACCGCAUGAAUAAGGACCGGCUAAUUCCGUGCCAGCAGCCGCGGUAAUACGGAAGGUCCGGGCGUUAUCCGGAUUUAUUGGGUUUAAAGGGAGCGCAGGCCGCCGUGCAAGCGUGCCGUGAAAAGCAGCGGCCCAACCGCUGCCCUGCGGCGCGAACUGCUUGGCUUGAGUGCGCCGGAAGCGGGCGGAAUUCGUGGUGUAGCGGUGAAAUGCUUAGAUAUCACGAAGAACCCCGAUUGCGAAGGCAGCCCGCUGUGGCGACUGACGCUGAGGCUCGAAGGUGCGGGUAUCGAACAGGAUUAGAUACCCUGGUAGUCCGCACGGUAAACGAUGGAUACCCGCUGUCCGGCUCUGGGCGGCCAAGCGAAAGCGUUAAGUAUCCCACCUGGGGAGUACGCCGGCAACGGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGAGGAACAUGUGGUUUAAUUCGAUGAUACGCGAGGAACCUUACCCGGGCUUGAAUUGUGAAGGUGCUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUCGGCUCAAGUGCCAUAACGAGCGCAACCCCUCUCCGCAGUUGCCAUCGGCCGGGCACUCUGCGGACACUGCCGCCGCAAGGUGGAGGAAGGUGGGGAUGACGUCAAAUCAGCACGGCCCUUACGUCCGGGGCCACACACGUGUUACAAUGGCCGGCAGAGGGCUGUCCGCGCGCAAGUGCGGGUGAAUCCCCUCCGGUCCCAGUUCGGAUGGGGUCUGCAACCCGACCCCAGAAGCUGGAUUCGCUAGUAAUCGCGCAUCAGCCAUGGCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCAAGCCAUGAAAGCCGGGGGUGCCUGAAGUCCGUGUCGGCCUAGGGCAAAACCGGUGAUUGGGGCUAAGUCGUAACAAGGUAGCCGUACCGGAAGGUGCGGCUGGAACACCUCCUUUCU
>NZ_ACIZ01000148_643886127
AAUAUGGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAACGAGUGGCGGACGGGUGAGUAACACGUGGGUAACCUGCCCUUAAGUGGGGGAUAACAUUUGGAAACAGAUGCUAAUACCGCAUAAAGAAAGUCGCUUUUGGAUGGACCCGCGGCGUAUUAGCUAGUUGGUGAGGUAACGGCUCACCAAGGCAAUGAUACGUAGCCGAACUGAGAGGUUGAUCGGCCACAUUGGGACUGAGACACGGCCCAAACUCCUACGGGAGGCAGCAGUAGGGAAUCUUCCACAAUGGACGCAAGUCUGAUGGAGCAACGCCGCGUGAGUGAAGAAGGCUUUCGGGUCGUAAAACUCUGUUGUUGGAGAAGAUGACGGUAUCCAACCAGAAAGCCACGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGUGGCAAGCGUUAUCCGGAUUUAUUGGGCGUAAAGCGAGCGCAGGCGGUUUUUUAAGUCUGAUGUGAAAGCCCUCGGCUUAACCGAGGAAGUGCAUCGGAAACUGGGAAACUUGAGUGCAGAAGAGGACAGUGGAACUCCAUGUGUAGCGGUGAAAUGCGUAGAUAUAUGGAAGAACACCAGUGGCGAAGGCGGCUGUCUGGUCUGACUGACGCUGAGGCUCGAAAGCAUGGGUAGCGAACAGGAUUAGAUACCCUGGUAGUCCAUGCCGUAAACGAUGAAUGCUAGGUGUUGGAGCUUCAGUGCCGCAGCUAACGCAUUAAGCAUUCCGCCUGGGGAGUACGACCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAGGUCUUGACAUCGACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUGACUAGUUGCCAGCAUGGGCACUCUAGUAAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGACCUGGGCUACACACGUGCUACAAUGGAUGGCAACGAGUUGCGAGACCGCGAGGUCAAGCUAAUCUCUUCCAUUCUCAGUUCGGAUGUAGGCUGCAACUCGCCUACAGAAGUCGGAAUCGCUAGUAAUCGCGGAUCAGCACGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGAGAGUUUGUAACACCCGAAGCCGGUGCGUAGCGAGCCGUCUAAGGUGGGACAAAUGAUUAGGGUGAAGUCGUAACAAGGUAGCCGUAGGAGAACCUGCGGCUGGAUCACCUCCUUUCU'''
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_app/test_carnac.py 000644 000765 000024 00000006563 12024702176 022074 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.carnac import Carnac
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class CarnacTest(TestCase):
"""Tests for Carnac application controller"""
def setUp(self):
self.input = carnac_input
def test_stdout_input_as_lines(self):
"""Test carnac stdout input as lines
If error check computation time in carnac_stdout!!
Usually 00:00:00 but on slower systems may be different"""
c = Carnac(InputHandler='_input_as_lines')
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in carnac_stdout])
res = c(self.input)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test carnac stdout input as string
If error check computation time in carnac_stdout!!
Usually 00:00:00 but on slower systems may be different"""
c = Carnac()
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in carnac_stdout])
f = open('/tmp/input.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = c('/tmp/input.fasta')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('/tmp/input.fasta')
def test_get_result_path(self):
"""Tests carnac result path"""
c = Carnac(InputHandler='_input_as_lines')
res = c(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus',\
'ct1','eq1','ct2','eq2','out_seq1','out_seq2','graph','align'])
self.assertEqual(res['ExitStatus'],0)
assert res['ct1'] is not None
assert res['eq1'] is not None
assert res['out_seq1'] is not None
res.cleanUp()
carnac_input = ['>seq1\n',
'GGCCACGTAGCTCAGTCGGTAGAGCAAAGGACTGAAAATCCTTGTGTCGTTGGTTCAATTCCAACCGTGGCCACCA\n', '>seq2\n',
'GCCAGATAGCTCAGTCGGTAGAGCGTTCGCCTGAAAAGTGAAAGGTCGCCGGTTCGATCCCGGCTCTGGCCACCA\n']
carnac_stdout = [' Sequences \n', '\n',
' sequence 1 (length 76, gc 52): seq1\n',
' sequence 2 (length 75, gc 60): seq2\n', '\n',
' Finding all potential stems \n', '\n',
' sequence 1 : 12 potential stems\n',
' sequence 2 : 18 potential stems\n', '\n', ' Pairwise foldings \n', '\n',
' seq 1 / seq 2: 3 vs 3 stems\n', '\n',
' Combination of pairwise foldings: 6 classes of stems in 3 connex components\n', '\n',
' sequence 1: 1 cofoldings with 12 stems -> 3 selected stems + 2 remaining stems \n',
' sequence 2: 1 cofoldings with 18 stems -> 3 selected stems + 1 remaining stems \n', '\n', ' Overall computation time : 00:00:00\n', '\n',
' Parameter values :\n', '\n', ' AP_THD 8\n',
' SUB -5\n', ' SIZE_HAIRPIN 3\n', ' CORRECT_THD 1\n',
' INI_THD -500\n', ' DIST_1 50\n', ' DIST_2 300\n',
' Energy tresholds : -800 - -1300\n',
' Allowing single hairpins : no\n', ' SIZE_MAX_HP 8\n',
' THD_HP -1500\n', ' FLT 1\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_cd_hit.py 000644 000765 000024 00000020513 12024702176 022066 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import getcwd, rmdir
from cogent.core.moltype import PROTEIN, DNA
from cogent.util.unit_test import TestCase, main
from cogent.app.cd_hit import CD_HIT, CD_HIT_EST, cdhit_from_seqs, \
cdhit_clusters_from_seqs, clean_cluster_seq_id, parse_cdhit_clstr_file
__author__ = "Daniel McDonald"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Daniel McDonald"
__email__ = "mcdonadt@colorado.edu"
__status__ = "Development"
class CD_HIT_Tests(TestCase):
"""Tests for the CD-HIT application controller"""
def test_base_command(self):
"""CD_HIT BaseCommand should return the correct BaseCommand"""
c = CD_HIT()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cd-hit']))
c.Parameters['-i'].on('seq.txt')
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cd-hit -i "seq.txt"']))
c.Parameters['-c'].on(0.8)
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cd-hit -c 0.8' +
' -i "seq.txt"']))
def test_changing_working_dir(self):
"""CD_HIT BaseCommand should change according to WorkingDir"""
c = CD_HIT(WorkingDir='/tmp/cdhit_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cdhit_test','/"; ','cd-hit']))
c = CD_HIT()
c.WorkingDir = '/tmp/cdhit_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cdhit_test2','/"; ','cd-hit']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cdhit_test')
rmdir('/tmp/cdhit_test2')
def test_cdhit_from_seqs(self):
"""CD_HIT should return expected seqs"""
res = cdhit_from_seqs(protein_seqs, PROTEIN, {'-c':0.8})
self.assertEqual(res.toFasta(), protein_expected)
class CD_HIT_EST_Tests(TestCase):
"""Tests for the CD-HIT application controller"""
def test_base_command(self):
"""CD_HIT_EST BaseCommand should return the correct BaseCommand"""
c = CD_HIT_EST()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cd-hit-est']))
c.Parameters['-i'].on('seq.txt')
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cd-hit-est -i "seq.txt"']))
c.Parameters['-c'].on(0.8)
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cd-hit-est -c 0.8' +
' -i "seq.txt"']))
def test_changing_working_dir(self):
"""CD_HIT_EST BaseCommand should change according to WorkingDir"""
c = CD_HIT_EST(WorkingDir='/tmp/cdhitest_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cdhitest_test','/"; ','cd-hit-est']))
c = CD_HIT_EST()
c.WorkingDir = '/tmp/cdhitest_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cdhitest_test2','/"; ','cd-hit-est']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cdhitest_test')
rmdir('/tmp/cdhitest_test2')
def test_cdhit_from_seqs(self):
"""CD_HIT should return expected seqs"""
res = cdhit_from_seqs(dna_seqs, DNA, {'-c':0.8})
self.assertEqual(res.toFasta(), dna_expected)
def test_cdhit_from_seqs_synonym(self):
"""CD_HIT should return expected seqs with -c synonym"""
res = cdhit_from_seqs(dna_seqs, DNA, {'Similarity':0.8})
self.assertEqual(res.toFasta(), dna_expected)
class CD_HIT_SupportMethodTests(TestCase):
"""Tests for supporting methods"""
def test_clean_cluster_seq_id(self):
"""clean_cluster_seq_id returns a cleaned sequence id"""
data = ">foobar..."
exp = "foobar"
obs = clean_cluster_seq_id(data)
self.assertEqual(obs, exp)
def test_parse_cdhit_clstr_file(self):
"""parse_cdhit_clstr_file returns the correct clusters"""
data = cdhit_clstr_file.split('\n')
exp = [['seq0'],['seq1','seq10','seq3','seq23','seq145'],\
['seq7','seq17','seq69','seq1231']]
obs = parse_cdhit_clstr_file(data)
self.assertEqual(obs, exp)
def test_cdhit_clusters_from_seqs(self):
"""cdhit_clusters_from_seqs returns expected clusters"""
exp = [['cdhit_test_seqs_0'],['cdhit_test_seqs_1'],\
['cdhit_test_seqs_2'],['cdhit_test_seqs_3'],\
['cdhit_test_seqs_4'],['cdhit_test_seqs_5'],\
['cdhit_test_seqs_6','cdhit_test_seqs_8'],\
['cdhit_test_seqs_7'],['cdhit_test_seqs_9']]
obs = cdhit_clusters_from_seqs(dna_seqs, DNA)
self.assertEqual(obs, exp)
dna_seqs = """>cdhit_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>cdhit_test_seqs_1
ACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
>cdhit_test_seqs_2
CCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
>cdhit_test_seqs_3
CCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
>cdhit_test_seqs_4
GCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>cdhit_test_seqs_5
CCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
>cdhit_test_seqs_6
CGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
>cdhit_test_seqs_7
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
>cdhit_test_seqs_8
CGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
>cdhit_test_seqs_9
GGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA"""
dna_expected = """>cdhit_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>cdhit_test_seqs_1
ACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
>cdhit_test_seqs_2
CCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
>cdhit_test_seqs_4
GCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>cdhit_test_seqs_5
CCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
>cdhit_test_seqs_7
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT"""
protein_seqs = """>seq1
MGNKWSKSWPQVRDRMRRAAPAPAADGVGAVSQDLAKHGAITSSNTAATNDDCAWLEAQTEEEVGFPVRPQVPLRPMTYK
>seq2
MGGKWSKSSIVGWSTVRERMRKTPPAADGVGAVSQDLDKHGAVTSSNTAFNNPDCAWLEAQEDEDVGFPVRPQVPLRPT
>seq3
MGGKWSKSSIVGWPAIRERMRRARPAADRVGTQPAADGVGAVSQDLARHGAVTSSNTSHNNPDCAWLEAQEEEEVGVR
>seq4
MGKIWSKSSIVGWPEIRERMRRQRPHEPAVEPAVGVGAASQDLANRGALTTSNTRTNNPTVAWVEAQEEEGEVVRPQ
>seq5
MGKIWSKSSLVGWPEIRERMRRQTQEPAVEPAVGAGAASQDLANRGAITIRNTRDNNESIAWLEAQEEEFPVRPQV
>seq6
MGKIWSKSSLVGWPEIRERIRRQTPEPAVGVGAVSQDLANRGAITTSNTKDNNQTVAWLEAQEEPVRPQVPLRPM
>seq7
MGNALRKGKFEGWAAVRERMRRTRTFPESEPCAPGVGQISRELAARGGIPSSHTPQNNESHQEEEVGFPVAPQV
>seq8
MGNAWSKSKFAGWSEVRDRMRRSSSDPQQPCAPGVGAVSRELATRGGISSSALAFLDSHKDEDVGFPVRPQVP
>seq9
MGNVLGKDKFKGWAAVRERMRKTSSDPDPQPCAPGVGPVSRELSYTPQNNAALAFLESHEDEDVGFPVXPQV
>seq10
MGNVLGKDKFKGWSAVRERMRKTSPEPEPCAPGVRGGISNSHTPQNNAALAFLESHQDEDVGFPVRPQVPL"""
protein_expected = """>seq1
MGNKWSKSWPQVRDRMRRAAPAPAADGVGAVSQDLAKHGAITSSNTAATNDDCAWLEAQTEEEVGFPVRPQVPLRPMTYK
>seq2
MGGKWSKSSIVGWSTVRERMRKTPPAADGVGAVSQDLDKHGAVTSSNTAFNNPDCAWLEAQEDEDVGFPVRPQVPLRPT
>seq3
MGGKWSKSSIVGWPAIRERMRRARPAADRVGTQPAADGVGAVSQDLARHGAVTSSNTSHNNPDCAWLEAQEEEEVGVR
>seq4
MGKIWSKSSIVGWPEIRERMRRQRPHEPAVEPAVGVGAASQDLANRGALTTSNTRTNNPTVAWVEAQEEEGEVVRPQ
>seq5
MGKIWSKSSLVGWPEIRERMRRQTQEPAVEPAVGAGAASQDLANRGAITIRNTRDNNESIAWLEAQEEEFPVRPQV
>seq7
MGNALRKGKFEGWAAVRERMRRTRTFPESEPCAPGVGQISRELAARGGIPSSHTPQNNESHQEEEVGFPVAPQV
>seq8
MGNAWSKSKFAGWSEVRDRMRRSSSDPQQPCAPGVGAVSRELATRGGISSSALAFLDSHKDEDVGFPVRPQVP
>seq9
MGNVLGKDKFKGWAAVRERMRKTSSDPDPQPCAPGVGPVSRELSYTPQNNAALAFLESHEDEDVGFPVXPQV"""
cdhit_clstr_file = """>Cluster 0
0 2799aa, >seq0... *
>Cluster 1
0 2214aa, >seq1... at 80%
1 2215aa, >seq10... at 84%
2 2217aa, >seq3... *
3 2216aa, >seq23... at 84%
4 527aa, >seq145... at 63%
>Cluster 2
0 2202aa, >seq7... at 60%
1 2208aa, >seq17... *
2 2207aa, >seq69... at 73%
3 2208aa, >seq1231... at 69%"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_clearcut.py 000644 000765 000024 00000024203 12024702176 022436 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import getcwd, remove, rmdir, mkdir, path
import tempfile, shutil
from cogent.core.moltype import DNA, RNA, PROTEIN
from cogent.core.alignment import DataError
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.clearcut import Clearcut, build_tree_from_alignment,\
_matrix_input_from_dict2d, build_tree_from_distance_matrix
from cogent.util.dict2d import Dict2D
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Development"
class GeneralSetUp(TestCase):
def setUp(self):
"""Clearcut general setUp method for all tests"""
self.seqs1 = ['ACUGCUAGCUAGUAGCGUACGUA','GCUACGUAGCUAC',
'GCGGCUAUUAGAUCGUA']
self.labels1 = ['>1','>2','>3']
self.lines1 = flatten(zip(self.labels1,self.seqs1))
self.seqs2=['UAGGCUCUGAUAUAAUAGCUCUC','UAUCGCUUCGACGAUUCUCUGAUAGAGA',
'UGACUACGCAU']
self.labels2=['>a','>b','>c']
self.lines2 = flatten(zip(self.labels2,self.seqs2))
self.temp_dir = tempfile.mkdtemp()
#self.temp_dir_spaces = '/tmp/test for clearcut/'
#try:
# mkdir(self.temp_dir_spaces)
#except OSError:
# pass
try:
#create sequence files
f = open(path.join(self.temp_dir, 'seq1.txt'),'w')
f.write('\n'.join(self.lines1))
f.close()
g = open(path.join(self.temp_dir, 'seq2.txt'),'w')
g.write('\n'.join(self.lines2))
g.close()
except OSError:
pass
class ClearcutTests(GeneralSetUp):
"""Tests for the Clearcut application controller"""
def test_base_command(self):
"""Clearcut BaseCommand should return the correct BaseCommand"""
c = Clearcut()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','clearcut -d -q']))
c.Parameters['--in'].on('seq.txt')
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','clearcut -d --in="seq.txt" -q']))
def test_changing_working_dir(self):
"""Clearcut BaseCommand should change according to WorkingDir"""
c = Clearcut(WorkingDir='/tmp/clearcut_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/clearcut_test','/"; ','clearcut -d -q']))
c = Clearcut()
c.WorkingDir = '/tmp/clearcut_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/clearcut_test2','/"; ','clearcut -d -q']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/clearcut_test')
rmdir('/tmp/clearcut_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
#shutil.rmtree(self.temp_dir_spaces)
def test_build_tree_from_alignment(self):
"""Clearcut should return a tree built from the passed alignment"""
tree_short = build_tree_from_alignment(build_tree_seqs_short,\
moltype=DNA)
num_seqs = flatten(build_tree_seqs_short).count('>')
self.assertEqual(len(tree_short.tips()), num_seqs)
tree_long = build_tree_from_alignment(build_tree_seqs_long, moltype=DNA)
seq_names = []
for line in build_tree_seqs_long.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree_long.tips():
if node.Name not in seq_names:
self.fail()
#repeat with best_tree = True
tree_long = build_tree_from_alignment(build_tree_seqs_long,\
best_tree=True,\
moltype=DNA)
seq_names = []
for line in build_tree_seqs_long.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree_long.tips():
if node.Name not in seq_names:
self.fail()
#build_tree_from_alignment should raise DataError when constructing
# an Alignment from unaligned sequences. Clearcut only allows aligned
# or a distance matrix as input.
self.assertRaises(DataError,build_tree_from_alignment,\
build_tree_seqs_unaligned,DNA)
def test_matrix_input_from_dict2d(self):
"""matrix_input_from_dict2d formats dict2d object into distance matrix
"""
data = [('sample1aaaaaaa', 'sample2', 1.438), ('sample2', 'sample1aaaaaaa', 1.438), ('sample1aaaaaaa', 'sample3', 2.45678), ('sample3', 'sample1aaaaaaa', 2.45678), ('sample2', 'sample3', 2.7), ('sample3', 'sample2', 2.7)]
data_dict2d = Dict2D(data, Pad=True, Default=0.0)
matrix, int_map = _matrix_input_from_dict2d(data_dict2d)
#of = open('temp.txt', 'w')
#of.write(matrix)
#of.close()
matrix = matrix.split('\n')
self.assertEqual(matrix[0], ' 3')
self.assertEqual(matrix[1], 'env_0 0.0 1.438 2.45678')
self.assertEqual(matrix[2], 'env_1 1.438 0.0 2.7')
self.assertEqual(matrix[3], 'env_2 2.45678 2.7 0.0')
self.assertEqual(int_map['env_1'], 'sample2')
self.assertEqual(int_map['env_0'], 'sample1aaaaaaa')
self.assertEqual(int_map['env_2'], 'sample3')
def test_build_tree_from_distance_matrix(self):
"""build_tree_from_distance_matrix builds a tree from a dict2d
"""
data = [('sample1aaaaaaa', 'sample2', 1.438), ('sample2', 'sample1aaaaaaa', 1.438), ('sample1aaaaaaa', 'sample3', 2.45678), ('sample3', 'sample1aaaaaaa', 2.45678), ('sample2', 'sample3', 2.7), ('sample3', 'sample2', 2.7)]
data_dict2d = Dict2D(data, Pad=True, Default=0.0)
result = build_tree_from_distance_matrix(data_dict2d)
self.assertEqual(str(result), '((sample1aaaaaaa:0.59739,sample2:0.84061),sample3:1.85939);')
align1 = ">seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n---GCUACGUAGCUAC-------\n>seq_2\nGCGGCUAUUAGAUCGUA------"
build_tree_seqs_short = """>clearcut_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>clearcut_test_seqs_1
GACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>clearcut_test_seqs_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>clearcut_test_seqs_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>clearcut_test_seqs_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>clearcut_test_seqs_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>clearcut_test_seqs_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>clearcut_test_seqs_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>clearcut_test_seqs_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>clearcut_test_seqs_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
build_tree_seqs_long = """>clearcut_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>clearcut_test_seqsaaaaaaaa_1
GACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>clearcut_test_seqsaaaaaaaa_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>clearcut_test_seqsaaaaaaaa_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>clearcut_test_seqsaaaaaaaa_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>clearcut_test_seqsaaaaaaaa_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>clearcut_test_seqsaaaaaaaa_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>clearcut_test_seqsaaaaaaaa_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>clearcut_test_seqsaaaaaaaa_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>clearcut_test_seqsaaaaaaaa_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
#Unaligned seqs. First two sequences are 3 nucleotides shorter.
build_tree_seqs_unaligned = """>clearcut_test_seqs_0
CCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>clearcut_test_seqs_1
CCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>clearcut_test_seqs_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>clearcut_test_seqs_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>clearcut_test_seqs_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>clearcut_test_seqs_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>clearcut_test_seqs_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>clearcut_test_seqs_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>clearcut_test_seqs_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>clearcut_test_seqs_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_clustalw.py 000644 000765 000024 00000057360 12024702176 022504 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for application controller for ClustalW v1.83"""
import re
from os import getcwd, remove, rmdir, mkdir, path
import shutil
from cogent.core.alignment import Alignment
from cogent.core.moltype import RNA
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.clustalw import Clustalw, alignUnalignedSeqsFromFile,\
alignUnalignedSeqs, alignTwoAlignments, addSeqsToAlignment,\
buildTreeFromAlignment, build_tree_from_alignment, \
bootstrap_tree_from_alignment, align_unaligned_seqs, \
align_and_build_tree, add_seqs_to_alignment, align_two_alignments
from cogent.parse.fasta import MinimalFastaParser
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Rob Knight", "Daniel McDonald",\
"Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Development"
cw_vers = re.compile("CLUSTAL W [(]1\.8[1-3][.\d]*[)]")
class GeneralSetUp(TestCase):
def setUp(self):
"""Clustalw general setUp method for all tests"""
self.seqs1 = ['ACUGCUAGCUAGUAGCGUACGUA','GCUACGUAGCUAC',
'GCGGCUAUUAGAUCGUA']
self.aln1_fasta = ALIGN1_FASTA
self.labels1 = ['>1','>2','>3']
self.lines1 = flatten(zip(self.labels1,self.seqs1))
self.stdout1 = STDOUT1
self.aln1 = ALIGN1
self.dnd1 = DND1
self.multiline1 = '\n'.join(flatten(zip(self.labels1, self.seqs1)))
self.seqs2=['UAGGCUCUGAUAUAAUAGCUCUC','UAUCGCUUCGACGAUUCUCUGAUAGAGA',
'UGACUACGCAU']
self.labels2=['>a','>b','>c']
self.lines2 = flatten(zip(self.labels2,self.seqs2))
self.aln2 = ALIGN2
self.dnd2 = DND2
self.twoalign = TWOALIGN
self.alignseqs = ALIGNSEQS
self.treeduringalignseqs = TREEDURINGALIGNSEQS
self.treefromalignseqs = TREEFROMALIGNSEQS
self.temp_dir_space = "/tmp/clustalw test"
self.build_tree_seqs_short = """>clustal_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>clustal_test_seqs_1
GACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>clustal_test_seqs_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>clustal_test_seqs_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>clustal_test_seqs_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>clustal_test_seqs_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>clustal_test_seqs_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>clustal_test_seqs_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>clustal_test_seqs_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>clustal_test_seqs_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
self.build_tree_seqs_long = """>clustal_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>clustal_test_seqsaaaaaaaa_1
GACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>clustal_test_seqsaaaaaaaa_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>clustal_test_seqsaaaaaaaa_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>clustal_test_seqsaaaaaaaa_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>clustal_test_seqsaaaaaaaa_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>clustal_test_seqsaaaaaaaa_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>clustal_test_seqsaaaaaaaa_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>clustal_test_seqsaaaaaaaa_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>clustal_test_seqsaaaaaaaa_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
try:
mkdir('/tmp/ct')
except OSError: #dir already exists
pass
try:
#create sequence files
f = open('/tmp/ct/seq1.txt','w')
f.write('\n'.join(self.lines1))
f.close()
g = open('/tmp/ct/seq2.txt','w')
g.write('\n'.join(self.lines2))
g.close()
#create alignment files
f = open('/tmp/ct/align1','w')
f.write(self.aln1)
f.close()
g = open('/tmp/ct/align2','w')
g.write(self.aln2)
g.close()
#create tree file
f = open('/tmp/ct/tree1','w')
f.write(DND1)
f.close()
except OSError:
pass
class ClustalwTests(GeneralSetUp):
"""Tests for the Clustalw application controller"""
def test_base_command(self):
"""Clustalw BaseCommand should return the correct BaseCommand"""
c = Clustalw()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','clustalw -align']))
c.Parameters['-infile'].on('seq.txt')
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ',\
'clustalw -infile="seq.txt" -align']))
c.Parameters['-align'].off()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','clustalw -infile="seq.txt"']))
c.Parameters['-nopgap'].on()
c.Parameters['-infile'].off()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','clustalw -nopgap']))
def test_changing_working_dir(self):
"""Clustalw BaseCommand should change according to WorkingDir"""
c = Clustalw(WorkingDir='/tmp/clustaltest')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/clustaltest','/"; ','clustalw -align']))
c = Clustalw(WorkingDir='/tmp/clustaltest/')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/clustaltest/','/"; ','clustalw -align']))
c = Clustalw()
c.WorkingDir = '/tmp/clustaltest2/'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/clustaltest2/','/"; ','clustalw -align']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/clustaltest')
rmdir('/tmp/clustaltest2')
def test_stdout_input_as_string(self):
"""Clustalw input_as_string shoud function as expected"""
c = Clustalw(WorkingDir='/tmp/ct')
res = c('/tmp/ct/seq1.txt')
self.assertEqual(cw_vers.sub("", res['StdOut'].read()),
cw_vers.sub("", self.stdout1))
self.assertEqual(res['StdErr'].read(),'')
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
def test_stdout_input_as_lines(self):
"""Clustalw input_as_lines should function as expected"""
c = Clustalw(InputHandler='_input_as_lines',WorkingDir='/tmp/ct')
res = c(self.lines1)
#get info on input file name and change output accordingly
name = c.Parameters['-infile'].Value
out = self.stdout1.split('\n')
out[16] =\
'Guide tree file created: ['+name.rsplit(".")[0]+'.dnd]'
out[23] =\
'CLUSTAL-Alignment file created ['+name.rsplit(".")[0]+'.aln]'
self.assertEqual(cw_vers.sub("", res['StdOut'].read()),
cw_vers.sub("", '\n'.join(out)))
self.assertEqual(res['StdErr'].read(),'')
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
def test_stdout_input_as_lines_local(self):
"""Clustalw input_as_lines should function as expected"""
c = Clustalw(InputHandler='_input_as_lines',WorkingDir=self.temp_dir_space)
res = c(self.lines1)
#get info on input file name and change output accordingly
name = c.Parameters['-infile'].Value
out = self.stdout1.split('\n')
out[16] =\
'Guide tree file created: ['+name.rsplit(".")[0]+'.dnd]'
out[23] =\
'CLUSTAL-Alignment file created ['+name.rsplit(".")[0]+'.aln]'
self.assertEqual(cw_vers.sub("", res['StdOut'].read()),
cw_vers.sub("", '\n'.join(out)))
self.assertEqual(res['StdErr'].read(),'')
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
def test_stdout_input_as_seqs(self):
"""Clustalw input_as_seqs should function as expected"""
c = Clustalw(InputHandler='_input_as_seqs',WorkingDir='/tmp/ct')
res = c(self.seqs1)
#get info on input file name and change output accordingly
name = c.Parameters['-infile'].Value
out = self.stdout1.split('\n')
out[16] =\
'Guide tree file created: ['+name.rsplit(".")[0]+'.dnd]'
out[23] =\
'CLUSTAL-Alignment file created ['+name.rsplit(".")[0]+'.aln]'
self.assertEqual(cw_vers.sub("", res['StdOut'].read()),
cw_vers.sub("", '\n'.join(out)))
self.assertEqual(res['StdErr'].read(),'')
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
def test_stdout_input_as_multiline_string(self):
"""Clustalw input_as_multiline_string should function as expected"""
c = Clustalw(InputHandler='_input_as_multiline_string',\
WorkingDir='/tmp/ct')
res = c(self.multiline1)
name = c.Parameters['-infile'].Value
out = self.stdout1.split('\n')
out[16] =\
'Guide tree file created: ['+name.rsplit(".")[0]+'.dnd]'
out[23] =\
'CLUSTAL-Alignment file created ['+name.rsplit(".")[0]+'.aln]'
self.assertEqual(cw_vers.sub("", res['StdOut'].read()),
cw_vers.sub("", '\n'.join(out)))
self.assertEqual(res['StdErr'].read(),'')
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
def test_alignment_trees(self):
"""Clustalw alignment should work correctly with new/usetree"""
c = Clustalw(params={'-quicktree':True,'-type':'DNA','-gapopen':10},\
WorkingDir='/tmp/ct')
res = c('/tmp/ct/seq1.txt')
self.assertEqual(res['Align'].name,'/tmp/ct/seq1.aln')
self.assertEqual(res['Dendro'].name,'/tmp/ct/seq1.dnd')
res.cleanUp()
c.Parameters['-usetree'].on('/tmp/ct/tree1')
c.Parameters['-output'].on('PHYLIP')
res = c('/tmp/ct/seq1.txt')
self.assertEqual(res['Align'].name,'/tmp/ct/seq1.phy')
self.assertEqual(res['Dendro'].name,'/tmp/ct/tree1')
res.cleanUp()
c.Parameters['-newtree'].on('newtree')
c.Parameters['-outfile'].on('outfile')
res = c('/tmp/ct/seq1.txt')
self.assertEqual(res['Align'].name, c.WorkingDir + 'outfile')
self.assertEqual(res['Dendro'].name, c.WorkingDir + 'newtree')
res.cleanUp()
def test_profile_newtree(self):
"""Clustalw profile should work correctly with new/usetree"""
c = Clustalw(params={'-profile':None,'-profile1':'/tmp/ct/seq1.txt',\
'-profile2':'/tmp/ct/seq2.txt','-newtree1':'lala'},\
WorkingDir='/tmp/ct')
c.Parameters['-align'].off()
res = c()
self.assertEqual(res['Align'],None)
self.assertEqual(res['Dendro1'].name,'/tmp/ct/lala')
self.assertEqual(res['Dendro2'].name,'/tmp/ct/seq2.dnd')
res.cleanUp()
def test_sequences_newtree(self):
"""Clustalw sequences should work correctly with new/usetree"""
c = Clustalw(params={'-sequences':None,'-newtree':'lala',\
'-profile1':'/tmp/ct/align1','-profile2':'/tmp/ct/seq2.txt'},\
WorkingDir='/tmp/ct')
c.Parameters['-align'].off()
res = c()
self.assertEqual(res['Align'],None)
self.assertEqual(res['Dendro'].name,'/tmp/ct/lala')
res.cleanUp()
#is this a bug in clustal. It's creating an empty file 'seq2.aln'
#but doesn't report it in the stdout
remove('/tmp/ct/seq2.aln')
def test_tree_outputtree(self):
"""Clustalw tree should work correctly with outputtree"""
c = Clustalw(params={'-tree':None,'-outputtree':'dist',\
'-infile':'/tmp/ct/align1'},WorkingDir='/tmp/ct/')
c.Parameters['-align'].off()
res = c()
self.assertEqual(res['Tree'].name,'/tmp/ct/align1.ph')
self.assertEqual(res['TreeInfo'].name,'/tmp/ct/align1.dst')
res.cleanUp()
class clustalwTests(GeneralSetUp):
"""Tests for module level functions in clustalw.py"""
def test_alignUnalignedSeqs(self):
"""Clustalw alignUnalignedSeqs should work as expected"""
res = alignUnalignedSeqs(self.seqs1,WorkingDir='/tmp/ct')
self.assertNotEqual(res['StdErr'],None)
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
#suppress stderr and stdout
res = alignUnalignedSeqs(self.seqs1,WorkingDir='/tmp/ct',\
SuppressStderr=True,SuppressStdout=True)
self.assertEqual(res['StdOut'],None)
self.assertEqual(res['StdErr'],None)
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
def test_alignUnalignedSeqsFromFile(self):
"""Clustalw alignUnalignedSeqsFromFile should work as expected"""
#make temp file
res = alignUnalignedSeqsFromFile('/tmp/ct/seq1.txt')
self.assertEqual(cw_vers.sub("", res['StdOut'].read()),
cw_vers.sub("", self.stdout1))
self.assertEqual(res['StdErr'].read(),'')
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
#suppress stderr and stdout
res = alignUnalignedSeqsFromFile('/tmp/ct/seq1.txt',\
SuppressStderr=True, SuppressStdout=True)
self.assertEqual(res['StdOut'],None)
self.assertEqual(res['StdErr'],None)
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.aln1))
self.assertEqual(res['Dendro'].read(),self.dnd1)
res.cleanUp()
def test_alignTwoAlignments(self):
"""Clustalw alignTwoAlignments should work as expected"""
res = alignTwoAlignments('/tmp/ct/align1','/tmp/ct/align2',\
'twoalign.aln')
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.twoalign))
self.assertNotEqual(res['Dendro1'],None)
self.assertNotEqual(res['Dendro2'],None)
#are there new trees created during the profiling?
#the produced trees are not the same as when aligning individually
#self.assertEqual(res['Dendro1'].read(),self.dnd)
#self.assertEqual(res['Dendro2'].read(),self.dnd2)
res.cleanUp()
def test_addSeqsToAlignment(self):
"""Clustalw addSeqsToAlignment shoudl work as expected"""
res = addSeqsToAlignment('/tmp/ct/align1','/tmp/ct/seq2.txt',\
'alignseqs')
self.assertEqual(cw_vers.sub("", res['Align'].read()),
cw_vers.sub("", self.alignseqs))
self.assertEqual(res['Dendro'].read(),self.treeduringalignseqs)
res.cleanUp()
def test_buildTreeFromAlignment(self):
"""Clustalw buildTreeFromAlignment shoudl work as expected"""
pre_res = addSeqsToAlignment('/tmp/ct/align1','/tmp/ct/seq2.txt',\
'alignseqs',WorkingDir='/tmp/ct')
res = buildTreeFromAlignment('/tmp/ct/alignseqs',WorkingDir='/tmp/ct')
self.assertEqual(res['Tree'].read(),self.treefromalignseqs)
res.cleanUp()
pre_res.cleanUp()
def test_build_tree_from_alignment(self):
"""Clustalw should return a tree built from the passed alignment"""
tree_short = build_tree_from_alignment(self.build_tree_seqs_short, \
RNA, best_tree=False)
num_seqs = flatten(self.build_tree_seqs_short).count('>')
self.assertEqual(len(tree_short.tips()), num_seqs)
tree_long = build_tree_from_alignment(self.build_tree_seqs_long, \
RNA, best_tree=False)
seq_names = []
for line in self.build_tree_seqs_long.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree_long.tips():
if node.Name not in seq_names:
self.fail()
tree_short = build_tree_from_alignment(self.build_tree_seqs_short, \
RNA, best_tree=True, params={'-bootstrap':3})
num_seqs = flatten(self.build_tree_seqs_short).count('>')
self.assertEqual(len(tree_short.tips()), num_seqs)
def test_align_unaligned_seqs(self):
"""Clustalw align_unaligned_seqs should work as expected"""
res = align_unaligned_seqs(self.seqs1, RNA)
self.assertEqual(res.toFasta(), self.aln1_fasta)
def test_bootstrap_tree_from_alignment(self):
"""Clustalw should return a bootstrapped tree from the passed aln"""
tree_short = bootstrap_tree_from_alignment(self.build_tree_seqs_short)
num_seqs = flatten(self.build_tree_seqs_short).count('>')
self.assertEqual(len(tree_short.tips()), num_seqs)
tree_long = bootstrap_tree_from_alignment(self.build_tree_seqs_long)
seq_names = []
for line in self.build_tree_seqs_long.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree_long.tips():
if node.Name not in seq_names:
self.fail()
def test_align_and_build_tree(self):
"""Aligns and builds a tree for a set of sequences"""
res = align_and_build_tree(self.seqs1, RNA)
self.assertEqual(res['Align'].toFasta(), self.aln1_fasta)
tree = res['Tree']
seq_names = []
for line in self.aln1_fasta.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree.tips():
if node.Name not in seq_names:
self.fail()
def test_add_seqs_to_alignment(self):
"""Clustalw add_seqs_to_alignment should work as expected."""
seq2 = dict(MinimalFastaParser(self.lines2))
align1 = dict(MinimalFastaParser(ALIGN1_FASTA.split('\n')))
res = add_seqs_to_alignment(seq2,align1,RNA)
self.assertEqual(res.toFasta(), SEQ_PROFILE_ALIGN)
def test_align_two_alignments(self):
"""Clustalw align_two_alignments should work as expected."""
align1 = dict(MinimalFastaParser(ALIGN1_FASTA.split('\n')))
align2 = dict(MinimalFastaParser(ALIGN2_FASTA.split('\n')))
res = align_two_alignments(align1,align2,RNA)
self.assertEqual(res.toFasta(), PROFILE_PROFILE_ALIGN)
def test_zzz_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
remove('/tmp/ct/seq1.txt')
remove('/tmp/ct/seq2.txt')
remove('/tmp/ct/align1')
remove('/tmp/ct/align2')
remove('/tmp/ct/tree1')
rmdir('/tmp/ct')
shutil.rmtree(self.temp_dir_space)
STDOUT1=\
"""
CLUSTAL W (1.83) Multiple Sequence Alignments
Sequence format is Pearson
Sequence 1: 1 23 bp
Sequence 2: 2 13 bp
Sequence 3: 3 17 bp
Start of Pairwise alignments
Aligning...
Sequences (1:2) Aligned. Score: 46
Sequences (1:3) Aligned. Score: 41
Sequences (2:3) Aligned. Score: 30
Guide tree file created: [/tmp/ct/seq1.dnd]
Start of Multiple Alignment
There are 2 groups
Aligning...
Group 1: Sequences: 2 Score:171
Group 2: Sequences: 3 Score:162
Alignment Score 33
CLUSTAL-Alignment file created [/tmp/ct/seq1.aln]
"""
ALIGN1=\
"""CLUSTAL W (1.83) multiple sequence alignment
1 ACUGCUAGCUAGUAGCGUACGUA
2 ---GCUACGUAGCUAC-------
3 GCGGCUAUUAGAUCGUA------
****
"""
ALIGN1_FASTA = ">seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n---GCUACGUAGCUAC-------\n>seq_2\nGCGGCUAUUAGAUCGUA------"
DND1=\
"""(
1:0.21719,
2:0.32127,
3:0.37104);
"""
ALIGN2 =\
"""CLUSTAL W (1.83) multiple sequence alignment
a UAGGCUCUGAUAUAAUAGCUCUC---------
b ----UAUCGCUUCGACGAUUCUCUGAUAGAGA
c ------------UGACUACGCAU---------
* *
"""
ALIGN2_FASTA = ">a\nUAGGCUCUGAUAUAAUAGCUCUC---------\n>b\n----UAUCGCUUCGACGAUUCUCUGAUAGAGA\n>c\n------------UGACUACGCAU---------"
DND2=\
"""(
a:0.30435,
b:0.30435,
c:0.33202);
"""
TWOALIGN=\
"""CLUSTAL W (1.83) multiple sequence alignment
1 ---ACUGCUAGCUAGUAGCGUACGUA------
2 ------GCUACGUAGCUAC-------------
3 ---GCGGCUAUUAGAUCGUA------------
a UAGGCUCUGAUAUAAUAGCUCUC---------
b ----UAUCGCUUCGACGAUUCUCUGAUAGAGA
c ------------UGACUACGCAU---------
"""
ALIGNSEQS=\
"""CLUSTAL W (1.83) multiple sequence alignment
1 ----------ACUGCUAGCUAGUAGCGUACGUA
2 -------------GCUACGUAGCUAC-------
3 ----------GCGGCUAUUAGAUCGUA------
a -------UAGGCUCUGAUAUAAUAGCUCUC---
c -------------------UGACUACGCAU---
b UAUCGCUUCGACGAUUCUCUGAUAGAGA-----
"""
TREEDURINGALIGNSEQS=\
"""(
1:0.34511,
(
2:0.25283,
(
(
3:0.21486,
a:0.19691)
:0.11084,
b:0.31115)
:0.06785)
:0.02780,
c:0.20035);
"""
TREEFROMALIGNSEQS=\
"""(
(
(
1:0.17223,
(
2:0.14749,
c:0.13822)
:0.19541)
:0.07161,
a:0.25531)
:0.03600,
3:0.29438,
b:0.23503);
"""
SEQ_PROFILE_ALIGN = """>a\n-------UAGGCUCUGAUAUAAUAGCUCUC---\n>b\nUAUCGCUUCGACGAUUCUCUGAUAGAGA-----\n>c\n-------------------UGACUACGCAU---\n>seq_0\n----------ACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n-------------GCUACGUAGCUAC-------\n>seq_2\n----------GCGGCUAUUAGAUCGUA------"""
PROFILE_PROFILE_ALIGN = """>a\nUAGGCUCUGAUAUAAUAGCUCUC---------\n>b\n----UAUCGCUUCGACGAUUCUCUGAUAGAGA\n>c\n------------UGACUACGCAU---------\n>seq_0\n---ACUGCUAGCUAGUAGCGUACGUA------\n>seq_1\n------GCUACGUAGCUAC-------------\n>seq_2\n---GCGGCUAUUAGAUCGUA------------"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_cmfinder.py 000644 000765 000024 00000146657 12024702176 022445 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.app.cmfinder import CMfinder,CombMotif
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class CmfinderTest(TestCase):
"""Tests for Cmfinder application controller"""
def setUp(self):
self.input = cmfinder_input
def test_input_as_lines(self):
"""Test Cmfinder stdout input as lines"""
c = CMfinder(InputHandler='_input_as_lines')
res = c(self.input,remove_tmp=False)
#Filename in stdout, can't compare stdout since impossible to
#predict filename
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test Cmfinder stdout input as string"""
c = CMfinder()
exp ='%s\n' % '\n'.join([str(i).strip('\n') for i in cmfinder_stdout])
f = open('input.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = c('input.fasta',remove_tmp=False)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
remove('input.fasta')
def test_get_result_path(self):
"""Tests cmfinder result path"""
c =CMfinder(InputHandler='_input_as_lines')
res = c(self.input,remove_tmp=False)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus',
'cm_1','cm_2','cm_3','motif_1','motif_2','motif_3','latest',
'_input_filename'])
self.assertEqual(res['ExitStatus'],0)
assert res['cm_1'] is not None
assert res['cm_2'] is not None
assert res['cm_3'] is not None
assert res['motif_1'] is not None
assert res['motif_2'] is not None
assert res['motif_3'] is not None
res.cleanUp()
class CombMotifTest(TestCase):
"""Tests for CombMotif application controller
_input_as_lines function not used!!"""
def setUp(self):
""" """
a = open('input.fasta.cm.h1.1','w')
txt = '\n'.join([str(i).strip('\n') for i in cm1])
a.write(txt)
a.close()
b = open('input.fasta.cm.h1.2','w')
txt = '\n'.join([str(i).strip('\n') for i in cm2])
b.write(txt)
b.close()
c = open('input.fasta.cm.h1.3','w')
txt = '\n'.join([str(i).strip('\n') for i in cm3])
c.write(txt)
c.close()
d = open('input.fasta.motif.h1.1','w')
txt = '\n'.join([str(i).strip('\n') for i in motif1])
d.write(txt)
d.close()
e = open('input.fasta.motif.h1.2','w')
txt = '\n'.join([str(i).strip('\n') for i in motif2])
e.write(txt)
e.close()
f = open('input.fasta.motif.h1.3','w')
txt = '\n'.join([str(i).strip('\n') for i in motif3])
f.write(txt)
f.close()
g = open('input.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in cmfinder_input])
g.write(txt)
g.close()
def test_combmotif(self):
"""Tests CombMotif result path & input as string"""
cbm =CombMotif()
res = cbm('input.fasta')
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus',
'comb1','latest'])
self.assertEqual(res['ExitStatus'],0)
assert res['comb1'] is not None
res.cleanUp()
remove('input.fasta')
remove('input.fasta.cm.h1.1')
remove('input.fasta.cm.h1.2')
remove('input.fasta.cm.h1.3')
remove('input.fasta.motif.h1.1')
remove('input.fasta.motif.h1.2')
remove('input.fasta.motif.h1.3')
remove('input.fasta.cm.h1.2.3')
cmfinder_input = ['>seq1\n', 'GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC\n', '>seq2\n', 'GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC\n', '>seq3\n', 'GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC\n', '>seq4\n', 'GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC']
cmfinder_stdout = ['Seq_0_Cand0_20_69 -0.000000\n', 'UAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUG\n', '((((((...((((((((...((..........))))))))))..))))))\n', 'Seq_0_Cand1_29_61 -0.000000\n', 'GGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCC\n', '((((((((...((..........))))))))))\n', 'Seq_0_Cand2_36_68 -0.000000\n', 'AGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCU\n', '(((.((....((((......))))...)).)))\n', 'Alignment saved in file input.fasta.align.h1.1\n', 'Alignment saved in file input.fasta.align.h1.2\n', 'Alignment saved in file input.fasta.align.h1.3\n']
cm1 = ['INFERNAL-1 [0.7]\n', 'NAME (null)\n', 'STATES 154\n', 'NODES 40\n', 'W 200\n', 'el_selfsc 0.000000\n', 'NULL -0.363 -0.170 0.415 0.000 \n', 'MODEL:\n', '\t\t\t\t[ ROOT 0 ]\n', ' S 0 -1 0 1 4 -7.615 -7.822 -0.033 -6.236 \n', ' IL 1 1 2 1 4 -1.686 -2.369 -1.117 -4.855 1.023 -0.442 -0.708 -0.076 \n', ' IR 2 2 3 2 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 1 ]\n', ' ML 3 2 3 5 3 -8.950 -0.012 -7.267 -1.824 -2.170 -3.369 1.788 \n', ' D 4 2 3 5 3 -5.620 -0.734 -1.403 \n', ' IL 5 5 3 5 3 -1.925 -0.554 -4.164 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATR 2 ]\n', ' MR 6 5 3 8 5 -7.656 -0.026 -7.471 -7.683 -8.575 -1.639 -3.134 1.386 -2.615 \n', ' D 7 5 3 8 5 -5.352 -0.707 -2.978 -4.409 -2.404 \n', ' IR 8 8 3 8 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 3 ]\n', ' MP 9 8 3 13 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 10 8 3 13 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 11 8 3 13 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 12 8 3 13 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 13 13 5 13 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 14 14 6 14 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 4 ]\n', ' MP 15 14 6 19 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 16 14 6 19 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 17 14 6 19 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 18 14 6 19 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 19 19 5 19 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 20 20 6 20 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 5 ]\n', ' MP 21 20 6 25 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 22 20 6 25 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 23 20 6 25 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 24 20 6 25 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 25 25 5 25 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 26 26 6 26 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 6 ]\n', ' MP 27 26 6 31 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 28 26 6 31 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 29 26 6 31 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 30 26 6 31 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 31 31 5 31 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 32 32 6 32 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 7 ]\n', ' MP 33 32 6 37 4 -7.615 -7.822 -0.033 -6.236 -5.208 -5.325 -4.370 -0.894 -3.401 -4.617 3.483 -4.720 -7.134 -1.459 -5.156 -3.274 0.375 -6.308 -1.634 -4.773 \n', ' ML 34 32 6 37 4 -3.758 -3.940 -0.507 -2.670 1.023 -0.442 -0.708 -0.076 \n', ' MR 35 32 6 37 4 -4.809 -3.838 -1.706 -0.766 1.023 -0.442 -0.708 -0.076 \n', ' D 36 32 6 37 4 -4.568 -4.250 -2.265 -0.520 \n', ' IL 37 37 5 37 4 -1.686 -2.369 -1.117 -4.855 1.023 -0.442 -0.708 -0.076 \n', ' IR 38 38 6 38 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 8 ]\n', ' ML 39 38 6 41 3 -8.593 -0.013 -7.247 2.232 -3.180 -3.632 -2.819 \n', ' D 40 38 6 41 3 -6.174 -1.687 -0.566 \n', ' IL 41 41 3 41 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 9 ]\n', ' ML 42 41 3 44 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 43 41 3 44 3 -6.174 -1.687 -0.566 \n', ' IL 44 44 3 44 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 10 ]\n', ' ML 45 44 3 47 3 -8.950 -0.012 -7.267 2.232 -3.180 -3.632 -2.819 \n', ' D 46 44 3 47 3 -5.620 -0.734 -1.403 \n', ' IL 47 47 3 47 3 -1.925 -0.554 -4.164 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATR 11 ]\n', ' MR 48 47 3 50 3 -8.950 -0.012 -7.267 -1.639 -3.134 1.386 -2.615 \n', ' D 49 47 3 50 3 -6.390 -1.568 -0.620 \n', ' IR 50 50 3 50 3 -1.925 -0.554 -4.164 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATR 12 ]\n', ' MR 51 50 3 53 5 -7.656 -0.026 -7.471 -7.683 -8.575 -2.124 1.984 -3.766 -2.279 \n', ' D 52 50 3 53 5 -5.352 -0.707 -2.978 -4.409 -2.404 \n', ' IR 53 53 3 53 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 13 ]\n', ' MP 54 53 3 58 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 55 53 3 58 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 56 53 3 58 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 57 53 3 58 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 58 58 5 58 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 59 59 6 59 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 14 ]\n', ' MP 60 59 6 64 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 61 59 6 64 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 62 59 6 64 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 63 59 6 64 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 64 64 5 64 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 65 65 6 65 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 15 ]\n', ' MP 66 65 6 70 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 67 65 6 70 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 68 65 6 70 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 69 65 6 70 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 70 70 5 70 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 71 71 6 71 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 16 ]\n', ' MP 72 71 6 76 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.687 -4.001 -5.006 -0.279 -3.289 -5.690 -0.341 -4.598 -4.707 -1.022 -5.894 -2.187 4.037 -4.560 -1.931 -3.750 \n', ' ML 73 71 6 76 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 74 71 6 76 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 75 71 6 76 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 76 76 5 76 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 77 77 6 77 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 17 ]\n', ' MP 78 77 6 82 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -4.629 -4.281 -5.803 -0.660 -4.305 -6.778 -1.192 -5.008 -5.286 -1.451 -6.272 -2.306 -0.329 -5.298 3.329 -4.356 \n', ' ML 79 77 6 82 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 80 77 6 82 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 81 77 6 82 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 82 82 5 82 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 83 83 6 83 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 18 ]\n', ' MP 84 83 6 88 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 85 83 6 88 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 86 83 6 88 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 87 83 6 88 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 88 88 5 88 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 89 89 6 89 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 19 ]\n', ' MP 90 89 6 94 4 -7.615 -7.822 -0.033 -6.236 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 91 89 6 94 4 -3.758 -3.940 -0.507 -2.670 1.023 -0.442 -0.708 -0.076 \n', ' MR 92 89 6 94 4 -4.809 -3.838 -1.706 -0.766 1.023 -0.442 -0.708 -0.076 \n', ' D 93 89 6 94 4 -4.568 -4.250 -2.265 -0.520 \n', ' IL 94 94 5 94 4 -1.686 -2.369 -1.117 -4.855 1.023 -0.442 -0.708 -0.076 \n', ' IR 95 95 6 95 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 20 ]\n', ' ML 96 95 6 98 3 -8.593 -0.013 -7.247 2.232 -3.180 -3.632 -2.819 \n', ' D 97 95 6 98 3 -6.174 -1.687 -0.566 \n', ' IL 98 98 3 98 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 21 ]\n', ' ML 99 98 3 101 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 100 98 3 101 3 -6.174 -1.687 -0.566 \n', ' IL 101 101 3 101 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 22 ]\n', ' ML 102 101 3 104 3 -8.593 -0.013 -7.247 2.232 -3.180 -3.632 -2.819 \n', ' D 103 101 3 104 3 -6.174 -1.687 -0.566 \n', ' IL 104 104 3 104 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 23 ]\n', ' ML 105 104 3 107 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 106 104 3 107 3 -6.174 -1.687 -0.566 \n', ' IL 107 107 3 107 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 24 ]\n', ' ML 108 107 3 110 3 -8.593 -0.013 -7.247 -2.124 1.984 -3.766 -2.279 \n', ' D 109 107 3 110 3 -6.174 -1.687 -0.566 \n', ' IL 110 110 3 110 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 25 ]\n', ' ML 111 110 3 113 3 -8.593 -0.013 -7.247 -2.124 1.984 -3.766 -2.279 \n', ' D 112 110 3 113 3 -6.174 -1.687 -0.566 \n', ' IL 113 113 3 113 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 26 ]\n', ' ML 114 113 3 116 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 115 113 3 116 3 -6.174 -1.687 -0.566 \n', ' IL 116 116 3 116 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 27 ]\n', ' ML 117 116 3 119 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 118 116 3 119 3 -6.174 -1.687 -0.566 \n', ' IL 119 119 3 119 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 28 ]\n', ' ML 120 119 3 122 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 121 119 3 122 3 -6.174 -1.687 -0.566 \n', ' IL 122 122 3 122 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 29 ]\n', ' ML 123 122 3 125 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 124 122 3 125 3 -6.174 -1.687 -0.566 \n', ' IL 125 125 3 125 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 30 ]\n', ' ML 126 125 3 128 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 127 125 3 128 3 -6.174 -1.687 -0.566 \n', ' IL 128 128 3 128 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 31 ]\n', ' ML 129 128 3 131 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 130 128 3 131 3 -6.174 -1.687 -0.566 \n', ' IL 131 131 3 131 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 32 ]\n', ' ML 132 131 3 134 3 -8.593 -0.013 -7.247 -2.124 1.984 -3.766 -2.279 \n', ' D 133 131 3 134 3 -6.174 -1.687 -0.566 \n', ' IL 134 134 3 134 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 33 ]\n', ' ML 135 134 3 137 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 136 134 3 137 3 -6.174 -1.687 -0.566 \n', ' IL 137 137 3 137 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 34 ]\n', ' ML 138 137 3 140 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 139 137 3 140 3 -6.174 -1.687 -0.566 \n', ' IL 140 140 3 140 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 35 ]\n', ' ML 141 140 3 143 3 -8.593 -0.013 -7.247 -2.124 1.984 -3.766 -2.279 \n', ' D 142 140 3 143 3 -6.174 -1.687 -0.566 \n', ' IL 143 143 3 143 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 36 ]\n', ' ML 144 143 3 146 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 145 143 3 146 3 -6.174 -1.687 -0.566 \n', ' IL 146 146 3 146 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 37 ]\n', ' ML 147 146 3 149 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 148 146 3 149 3 -6.174 -1.687 -0.566 \n', ' IL 149 149 3 149 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 38 ]\n', ' ML 150 149 3 152 2 -9.084 -0.003 -1.824 -2.170 -3.369 1.788 \n', ' D 151 149 3 152 2 -8.445 -0.004 \n', ' IL 152 152 3 152 2 -1.823 -0.479 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ END 39 ]\n', ' E 153 152 3 -1 0 \n', '//\n']
cm2 = ['INFERNAL-1 [0.7]\n', 'NAME (null)\n', 'STATES 103\n', 'NODES 24\n', 'W 200\n', 'el_selfsc 0.000000\n', 'NULL -0.363 -0.170 0.415 0.000 \n', 'MODEL:\n', '\t\t\t\t[ ROOT 0 ]\n', ' S 0 -1 0 1 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 \n', ' IL 1 1 2 1 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 2 2 3 2 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 1 ]\n', ' MP 3 2 3 7 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 4 2 3 7 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 5 2 3 7 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 6 2 3 7 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 7 7 5 7 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 8 8 6 8 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 2 ]\n', ' MP 9 8 6 13 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 10 8 6 13 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 11 8 6 13 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 12 8 6 13 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 13 13 5 13 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 14 14 6 14 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 3 ]\n', ' MP 15 14 6 19 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 16 14 6 19 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 17 14 6 19 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 18 14 6 19 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 19 19 5 19 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 20 20 6 20 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 4 ]\n', ' MP 21 20 6 25 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.687 -4.001 -5.006 -0.279 -3.289 -5.690 -0.341 -4.598 -4.707 -1.022 -5.894 -2.187 4.037 -4.560 -1.931 -3.750 \n', ' ML 22 20 6 25 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 23 20 6 25 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 24 20 6 25 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 25 25 5 25 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 26 26 6 26 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 5 ]\n', ' MP 27 26 6 31 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -4.629 -4.281 -5.803 -0.660 -4.305 -6.778 -1.192 -5.008 -5.286 -1.451 -6.272 -2.306 -0.329 -5.298 3.329 -4.356 \n', ' ML 28 26 6 31 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 29 26 6 31 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 30 26 6 31 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 31 31 5 31 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 32 32 6 32 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 6 ]\n', ' MP 33 32 6 37 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 34 32 6 37 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 35 32 6 37 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 36 32 6 37 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 37 37 5 37 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 38 38 6 38 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 7 ]\n', ' MP 39 38 6 43 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 40 38 6 43 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 41 38 6 43 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 42 38 6 43 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 43 43 5 43 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 44 44 6 44 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 8 ]\n', ' MP 45 44 6 49 4 -7.487 -8.733 -0.052 -5.186 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 46 44 6 49 4 -2.408 -4.532 -1.293 -1.473 1.023 -0.442 -0.708 -0.076 \n', ' MR 47 44 6 49 4 -4.102 -12.528 -0.390 -2.485 1.023 -0.442 -0.708 -0.076 \n', ' D 48 44 6 49 4 -12.737 -14.007 -2.036 -0.404 \n', ' IL 49 49 5 49 4 -2.817 -4.319 -0.613 -2.698 1.023 -0.442 -0.708 -0.076 \n', ' IR 50 50 6 50 3 -1.925 -0.554 -4.164 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATR 9 ]\n', ' MR 51 50 6 53 3 -8.950 -0.012 -7.267 -1.639 -3.134 1.386 -2.615 \n', ' D 52 50 6 53 3 -6.390 -1.568 -0.620 \n', ' IR 53 53 3 53 3 -1.925 -0.554 -4.164 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATR 10 ]\n', ' MR 54 53 3 56 5 -7.656 -0.026 -7.471 -7.683 -8.575 -1.639 -3.134 1.386 -2.615 \n', ' D 55 53 3 56 5 -5.352 -0.707 -2.978 -4.409 -2.404 \n', ' IR 56 56 3 56 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 11 ]\n', ' MP 57 56 3 61 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 58 56 3 61 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 59 56 3 61 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 60 56 3 61 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 61 61 5 61 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 62 62 6 62 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 12 ]\n', ' MP 63 62 6 67 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 64 62 6 67 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 65 62 6 67 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 66 62 6 67 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 67 67 5 67 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 68 68 6 68 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 13 ]\n', ' MP 69 68 6 73 4 -7.615 -7.822 -0.033 -6.236 -4.629 -4.281 -5.803 -0.660 -4.305 -6.778 -1.192 -5.008 -5.286 -1.451 -6.272 -2.306 -0.329 -5.298 3.329 -4.356 \n', ' ML 70 68 6 73 4 -3.758 -3.940 -0.507 -2.670 1.023 -0.442 -0.708 -0.076 \n', ' MR 71 68 6 73 4 -4.809 -3.838 -1.706 -0.766 1.023 -0.442 -0.708 -0.076 \n', ' D 72 68 6 73 4 -4.568 -4.250 -2.265 -0.520 \n', ' IL 73 73 5 73 4 -1.686 -2.369 -1.117 -4.855 1.023 -0.442 -0.708 -0.076 \n', ' IR 74 74 6 74 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 14 ]\n', ' ML 75 74 6 77 3 -8.593 -0.013 -7.247 -2.124 1.984 -3.766 -2.279 \n', ' D 76 74 6 77 3 -6.174 -1.687 -0.566 \n', ' IL 77 77 3 77 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 15 ]\n', ' ML 78 77 3 80 3 -8.593 -0.013 -7.247 -2.124 1.984 -3.766 -2.279 \n', ' D 79 77 3 80 3 -6.174 -1.687 -0.566 \n', ' IL 80 80 3 80 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 16 ]\n', ' ML 81 80 3 83 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 82 80 3 83 3 -6.174 -1.687 -0.566 \n', ' IL 83 83 3 83 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 17 ]\n', ' ML 84 83 3 86 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 85 83 3 86 3 -6.174 -1.687 -0.566 \n', ' IL 86 86 3 86 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 18 ]\n', ' ML 87 86 3 89 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 88 86 3 89 3 -6.174 -1.687 -0.566 \n', ' IL 89 89 3 89 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 19 ]\n', ' ML 90 89 3 92 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 91 89 3 92 3 -6.174 -1.687 -0.566 \n', ' IL 92 92 3 92 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 20 ]\n', ' ML 93 92 3 95 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 94 92 3 95 3 -6.174 -1.687 -0.566 \n', ' IL 95 95 3 95 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 21 ]\n', ' ML 96 95 3 98 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 97 95 3 98 3 -6.174 -1.687 -0.566 \n', ' IL 98 98 3 98 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 22 ]\n', ' ML 99 98 3 101 2 -9.084 -0.003 -2.124 1.984 -3.766 -2.279 \n', ' D 100 98 3 101 2 -8.445 -0.004 \n', ' IL 101 101 3 101 2 -1.823 -0.479 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ END 23 ]\n', ' E 102 101 3 -1 0 \n', '//\n']
cm3 = ['INFERNAL-1 [0.7]\n', 'NAME (null)\n', 'STATES 103\n', 'NODES 24\n', 'W 200\n', 'el_selfsc 0.000000\n', 'NULL -0.363 -0.170 0.415 0.000 \n', 'MODEL:\n', '\t\t\t\t[ ROOT 0 ]\n', ' S 0 -1 0 1 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 \n', ' IL 1 1 2 1 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 2 2 3 2 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 1 ]\n', ' MP 3 2 3 7 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 4 2 3 7 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 5 2 3 7 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 6 2 3 7 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 7 7 5 7 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 8 8 6 8 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 2 ]\n', ' MP 9 8 6 13 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 10 8 6 13 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 11 8 6 13 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 12 8 6 13 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 13 13 5 13 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 14 14 6 14 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 3 ]\n', ' MP 15 14 6 19 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 16 14 6 19 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 17 14 6 19 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 18 14 6 19 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 19 19 5 19 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 20 20 6 20 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 4 ]\n', ' MP 21 20 6 25 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.687 -4.001 -5.006 -0.279 -3.289 -5.690 -0.341 -4.598 -4.707 -1.022 -5.894 -2.187 4.037 -4.560 -1.931 -3.750 \n', ' ML 22 20 6 25 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 23 20 6 25 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 24 20 6 25 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 25 25 5 25 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 26 26 6 26 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 5 ]\n', ' MP 27 26 6 31 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -4.629 -4.281 -5.803 -0.660 -4.305 -6.778 -1.192 -5.008 -5.286 -1.451 -6.272 -2.306 -0.329 -5.298 3.329 -4.356 \n', ' ML 28 26 6 31 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 29 26 6 31 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 30 26 6 31 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 31 31 5 31 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 32 32 6 32 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 6 ]\n', ' MP 33 32 6 37 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 34 32 6 37 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 35 32 6 37 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 36 32 6 37 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 37 37 5 37 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 38 38 6 38 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 7 ]\n', ' MP 39 38 6 43 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 40 38 6 43 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 41 38 6 43 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 42 38 6 43 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 43 43 5 43 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 44 44 6 44 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 8 ]\n', ' MP 45 44 6 49 4 -7.487 -8.733 -0.052 -5.186 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 46 44 6 49 4 -2.408 -4.532 -1.293 -1.473 1.023 -0.442 -0.708 -0.076 \n', ' MR 47 44 6 49 4 -4.102 -12.528 -0.390 -2.485 1.023 -0.442 -0.708 -0.076 \n', ' D 48 44 6 49 4 -12.737 -14.007 -2.036 -0.404 \n', ' IL 49 49 5 49 4 -2.817 -4.319 -0.613 -2.698 1.023 -0.442 -0.708 -0.076 \n', ' IR 50 50 6 50 3 -1.925 -0.554 -4.164 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATR 9 ]\n', ' MR 51 50 6 53 3 -8.950 -0.012 -7.267 -1.639 -3.134 1.386 -2.615 \n', ' D 52 50 6 53 3 -6.390 -1.568 -0.620 \n', ' IR 53 53 3 53 3 -1.925 -0.554 -4.164 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATR 10 ]\n', ' MR 54 53 3 56 5 -7.656 -0.026 -7.471 -7.683 -8.575 -1.639 -3.134 1.386 -2.615 \n', ' D 55 53 3 56 5 -5.352 -0.707 -2.978 -4.409 -2.404 \n', ' IR 56 56 3 56 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 11 ]\n', ' MP 57 56 3 61 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -6.059 -3.399 -7.491 -0.050 -6.698 -4.090 -1.804 -6.314 -5.110 3.545 -5.426 -1.969 -1.163 -4.250 -3.694 -5.400 \n', ' ML 58 56 3 61 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 59 56 3 61 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 60 56 3 61 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 61 61 5 61 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 62 62 6 62 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 12 ]\n', ' MP 63 62 6 67 6 -9.400 -9.339 -0.017 -8.115 -8.395 -8.790 -3.884 -3.075 -5.228 4.065 -4.750 -5.113 -1.228 -4.059 -4.861 -0.314 -6.063 -1.931 -0.504 -4.796 -2.719 -3.753 \n', ' ML 64 62 6 67 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 1.023 -0.442 -0.708 -0.076 \n', ' MR 65 62 6 67 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 1.023 -0.442 -0.708 -0.076 \n', ' D 66 62 6 67 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319 \n', ' IL 67 67 5 67 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 1.023 -0.442 -0.708 -0.076 \n', ' IR 68 68 6 68 5 -2.408 -0.496 -5.920 -4.087 -5.193 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATP 13 ]\n', ' MP 69 68 6 73 4 -7.615 -7.822 -0.033 -6.236 -4.629 -4.281 -5.803 -0.660 -4.305 -6.778 -1.192 -5.008 -5.286 -1.451 -6.272 -2.306 -0.329 -5.298 3.329 -4.356 \n', ' ML 70 68 6 73 4 -3.758 -3.940 -0.507 -2.670 1.023 -0.442 -0.708 -0.076 \n', ' MR 71 68 6 73 4 -4.809 -3.838 -1.706 -0.766 1.023 -0.442 -0.708 -0.076 \n', ' D 72 68 6 73 4 -4.568 -4.250 -2.265 -0.520 \n', ' IL 73 73 5 73 4 -1.686 -2.369 -1.117 -4.855 1.023 -0.442 -0.708 -0.076 \n', ' IR 74 74 6 74 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 14 ]\n', ' ML 75 74 6 77 3 -8.593 -0.013 -7.247 -2.124 1.984 -3.766 -2.279 \n', ' D 76 74 6 77 3 -6.174 -1.687 -0.566 \n', ' IL 77 77 3 77 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 15 ]\n', ' ML 78 77 3 80 3 -8.593 -0.013 -7.247 -2.124 1.984 -3.766 -2.279 \n', ' D 79 77 3 80 3 -6.174 -1.687 -0.566 \n', ' IL 80 80 3 80 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 16 ]\n', ' ML 81 80 3 83 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 82 80 3 83 3 -6.174 -1.687 -0.566 \n', ' IL 83 83 3 83 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 17 ]\n', ' ML 84 83 3 86 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 85 83 3 86 3 -6.174 -1.687 -0.566 \n', ' IL 86 86 3 86 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 18 ]\n', ' ML 87 86 3 89 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 88 86 3 89 3 -6.174 -1.687 -0.566 \n', ' IL 89 89 3 89 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 19 ]\n', ' ML 90 89 3 92 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 91 89 3 92 3 -6.174 -1.687 -0.566 \n', ' IL 92 92 3 92 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 20 ]\n', ' ML 93 92 3 95 3 -8.593 -0.013 -7.247 -1.639 -3.134 1.386 -2.615 \n', ' D 94 92 3 95 3 -6.174 -1.687 -0.566 \n', ' IL 95 95 3 95 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 21 ]\n', ' ML 96 95 3 98 3 -8.593 -0.013 -7.247 -1.824 -2.170 -3.369 1.788 \n', ' D 97 95 3 98 3 -6.174 -1.687 -0.566 \n', ' IL 98 98 3 98 3 -1.442 -0.798 -4.142 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ MATL 22 ]\n', ' ML 99 98 3 101 2 -9.084 -0.003 -2.124 1.984 -3.766 -2.279 \n', ' D 100 98 3 101 2 -8.445 -0.004 \n', ' IL 101 101 3 101 2 -1.823 -0.479 1.023 -0.442 -0.708 -0.076 \n', '\t\t\t\t[ END 23 ]\n', ' E 102 101 3 -1 0 \n', '//\n']
motif1 = ['# STOCKHOLM 1.0\n', '#=GF AU CMfinder 0.2\n', '\n', '#=GS seq1 WT 1.00\n', '#=GS seq2 WT 1.00\n', '#=GS seq3 WT 1.00\n', '#=GS seq4 WT 1.00\n', '\n', '#=GS seq1 DE 20.. 69\t89.835533\n', '#=GS seq2 DE 20.. 69\t89.835533\n', '#=GS seq3 DE 20.. 69\t89.835533\n', '#=GS seq4 DE 20.. 69\t89.835533\n', '\n', 'seq1 UAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUG\n', '#=GR seq1 SS .<<<<<...<<<<<<<...................>>>>>>>..>>>>>.\n', 'seq2 UAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUG\n', '#=GR seq2 SS .<<<<<...<<<<<<<...................>>>>>>>..>>>>>.\n', 'seq3 UAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUG\n', '#=GR seq3 SS .<<<<<...<<<<<<<...................>>>>>>>..>>>>>.\n', 'seq4 UAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUG\n', '#=GR seq4 SS .<<<<<...<<<<<<<...................>>>>>>>..>>>>>.\n', '#=GC SS_cons :<<<<<---<<<<<<<___________________>>>>>>>-->>>>>:\n', '#=GC RF UAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUG\n', '//\n']
motif2 = ['# STOCKHOLM 1.0\n', '#=GF AU CMfinder 0.2\n', '\n', '#=GS seq1 WT 1.00\n', '#=GS seq2 WT 1.00\n', '#=GS seq3 WT 1.00\n', '#=GS seq4 WT 1.00\n', '\n', '#=GS seq1 DE 29.. 61\t59.381535\n', '#=GS seq2 DE 29.. 61\t59.381535\n', '#=GS seq3 DE 29.. 61\t59.381535\n', '#=GS seq4 DE 29.. 61\t59.381535\n', '\n', 'seq1 GGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCC\n', '#=GR seq1 SS <<<<<<<<<<<.........>>>..>>>>>>>>\n', 'seq2 GGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCC\n', '#=GR seq2 SS <<<<<<<<<<<.........>>>..>>>>>>>>\n', 'seq3 GGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCC\n', '#=GR seq3 SS <<<<<<<<<<<.........>>>..>>>>>>>>\n', 'seq4 GGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCC\n', '#=GR seq4 SS <<<<<<<<<<<.........>>>..>>>>>>>>\n', '#=GC SS_cons <<<<<<<<<<<_________>>>-->>>>>>>>\n', '#=GC RF GGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCC\n', '//\n']
motif3 = ['# STOCKHOLM 1.0\n', '#=GF AU CMfinder 0.2\n', '\n', '#=GS seq1 WT 1.00\n', '#=GS seq2 WT 1.00\n', '#=GS seq3 WT 1.00\n', '#=GS seq4 WT 1.00\n', '\n', '#=GS seq1 DE 36.. 68\t59.230255\n', '#=GS seq2 DE 36.. 68\t59.230255\n', '#=GS seq3 DE 36.. 68\t59.230255\n', '#=GS seq4 DE 36.. 68\t59.230255\n', '\n', 'seq1 AGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCU\n', '#=GR seq1 SS .<<........>><<<<<.......>>>>>...\n', 'seq2 AGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCU\n', '#=GR seq2 SS .<<........>><<<<<.......>>>>>...\n', 'seq3 AGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCU\n', '#=GR seq3 SS .<<........>><<<<<.......>>>>>...\n', 'seq4 AGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCU\n', '#=GR seq4 SS .<<........>><<<<<.......>>>>>...\n', '#=GC SS_cons :<<________>><<<<<_______>>>>>:::\n', '#=GC RF AGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCU\n', '//\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_comrna.py 000644 000765 000024 00000004311 12024702176 022111 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.comrna import comRNA
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class ComrnaTest(TestCase):
"""Tests for comRNA application controller"""
def setUp(self):
self.input = comrna_input
def test_input_as_lines(self):
"""Test comrna input as lines"""
c = comRNA(InputHandler='_input_as_lines')
res = c(self.input)
#Can't compare stdout since comRNA app controller uses tmp filenames
#that are impossible to predict.
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test comrna input as string"""
c = comRNA()
f = open('/tmp/single.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = c('/tmp/single.fasta')
#Can't compare stdout since comRNA app controller uses tmp filenames
#that are impossible to predict.
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/single.fasta')
def test_get_result_path(self):
"""Tests comrna result path"""
c = comRNA(InputHandler='_input_as_lines')
res = c(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
comrna_input = ['>seq1\n', 'GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC\n', '>seq2\n', 'GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC\n', '>seq3\n', 'GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC\n', '>seq4\n', 'GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_consan.py 000644 000765 000024 00000004561 12024702176 022122 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.app.consan import Consan
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class ConsanTest(TestCase):
"""Tests for Consan application controller"""
def setUp(self):
self.input1 = consan_input1
self.input2 = consan_input2
def test_stdout_input_as_lines(self):
"""Test Consan stdout input as lines"""
c = Consan(InputHandler='_input_as_lines')
input = self.input1
input.extend(self.input2)
res = c(input)
#Impossible to compare stdout since copmutation time is in the output
#which may differ between runs
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test Consan stdout input as string"""
c = Consan()
f = open('/tmp/seq1.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input1])
f.write(txt)
f.close()
s = open('/tmp/seq2.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input2])
s.write(txt)
s.close()
res = c(['/tmp/seq1.fasta','/tmp/seq2.fasta'])
#Impossible to compare stdout since copmutation time is in the output
#which may differ between runs
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_get_result_path(self):
"""Tests Consan result path"""
c = Consan(InputHandler='_input_as_lines')
input = self.input1
input.extend(self.input2)
res = c(input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
consan_input1 = ['>seq1\n',
'GGCCACGTAGCTCAGTCGGTAGAGCAAAGGACTGAAAATCCTTGTGTCGTTGGTTCAATTCCAACCGTGGCCACCA']
consan_input2 = ['>seq2\n',
'GCCAGATAGCTCAGTCGGTAGAGCGTTCGCCTGAAAAGTGAAAGGTCGCCGGTTCGATCCCGGCTCTGGCCACCA']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_contrafold.py 000644 000765 000024 00000005463 12024702176 022776 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.contrafold import Contrafold
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class ContrafoldTest(TestCase):
"""Tests for Contrafold application controller"""
def setUp(self):
self.input = contrafold_input
def test_stdout_input_as_lines(self):
"""Test contrafold stdout input as lines"""
c = Contrafold(InputHandler='_input_as_lines')
exp= '%s\n' % '\n'.join([str(i).strip('\n') for i in contrafold_stdout])
res = c(self.input)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test contrafold stdout input as string"""
c = Contrafold()
exp= '%s\n' % '\n'.join([str(i).strip('\n') for i in contrafold_stdout])
f = open('/tmp/single.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = c('/tmp/single.fasta')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('/tmp/single.fasta')
def test_get_result_path(self):
"""Tests contrafold result path"""
c = Contrafold(InputHandler='_input_as_lines')
res = c(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
contrafold_input = ['>seq1\n',
'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n',
'\n']
contrafold_stdout = ['1 G 0\n', '2 G 71\n', '3 C 70\n', '4 U 9\n', '5 A 0\n',
'6 G 0\n', '7 A 0\n', '8 U 0\n', '9 A 4\n', '10 G 0\n', '11 C 0\n',
'12 U 0\n', '13 C 0\n', '14 A 0\n', '15 G 0\n', '16 A 0\n', '17 U 0\n',
'18 G 0\n', '19 G 0\n', '20 U 69\n', '21 A 68\n', '22 G 67\n', '23 A 66\n',
'24 G 65\n', '25 C 64\n', '26 A 0\n', '27 G 62\n', '28 A 0\n', '29 G 61\n',
'30 G 60\n', '31 A 59\n', '32 U 58\n', '33 U 57\n', '34 G 56\n', '35 A 55\n',
'36 A 54\n', '37 G 51\n', '38 A 50\n', '39 U 49\n', '40 C 0\n', '41 C 0\n',
'42 U 0\n', '43 U 0\n', '44 G 0\n', '45 U 0\n', '46 G 0\n', '47 U 0\n',
'48 C 0\n', '49 G 39\n', '50 U 38\n', '51 C 37\n', '52 G 0\n', '53 G 0\n',
'54 U 36\n', '55 U 35\n', '56 C 34\n', '57 G 33\n', '58 A 32\n', '59 U 31\n',
'60 C 30\n', '61 C 29\n', '62 C 27\n', '63 G 0\n', '64 G 25\n', '65 C 24\n',
'66 U 23\n', '67 C 22\n', '68 U 21\n', '69 G 20\n', '70 G 3\n', '71 C 2\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_cove.py 000644 000765 000024 00000170752 12024702176 021603 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.cove import Coves,Covet
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class CovetTest(TestCase):
"""Tests for Covet application controller"""
def setUp(self):
self.input = cove_input
def test_stdout_input_as_lines(self):
"""Test covet stdout input as lines"""
c = Covet(InputHandler='_input_as_lines')
res = c(self.input,remove_tmp=False)
#Can't test for stdout since different models are created each run
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test covet stdout input as string"""
c = Covet()
f = open('single.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = c('single.fasta',remove_tmp=False)
#Can't test for stdout since different models are created each run
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
remove('single.fasta')
def test_get_result_path(self):
"""Tests covet result path"""
c = Covet(InputHandler='_input_as_lines')
res = c(self.input,remove_tmp=False)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus','cm'
,'_input_filename'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
class CovesTest(TestCase):
"""Tests for Coves application controller"""
def setUp(self):
self.input = cove_input
def test_stdout_input_as_string(self):
"""Test coves stdout input as string"""
c = Coves()
exp= '%s\n' % '\n'.join([str(i).strip('\n') for i in coves_stdout])
f = open('single.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
#Create cm file needed for coves
s = open('single.fasta.cm','w')
txt = '\n'.join([str(i).strip('\n') for i in cove_cm])
s.write(txt)
s.close()
res = c('single.fasta')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('single.fasta')
remove('single.fasta.cm')
def test_get_result_path(self):
"""Tests coves result path"""
c = Coves()
f = open('single.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
#Create cm file needed for coves
s = open('single.fasta.cm','w')
txt = '\n'.join([str(i).strip('\n') for i in cove_cm])
s.write(txt)
s.close()
res = c('single.fasta')
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
cove_input = ['>seq1\n',
'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n',
'\n']
coves_stdout = ['coves - scoring and structure prediction of RNA sequences\n',
' using a covariance model\n', ' version 2.4.4, January 1996\n',
'\n', '---------------------------------------------------\n',
'Database to search/score: single.fasta\n',
'Model: single.fasta.cm\n',
'GC% of background model: 50%\n',
'---------------------------------------------------\n', '\n',
'-32.55 bits : seq1\n',
' seq1 GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUC\n', ' seq1 >.>..>.>.>.......>.>.>.>..>.>>...........<<.<..<.<.<.<......\n', '\n',
' seq1 CCGGCUCUGGC\n', ' seq1 .<.<.<..<.<\n', '\n']
cove_cm = 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if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_dialign.py 000644 000765 000024 00000010501 12024702176 022237 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import getcwd, remove, rmdir, mkdir, path
import tempfile, shutil
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.dialign import Dialign
__author__ = "Gavin Huttley"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
class GeneralSetUp(TestCase):
def setUp(self):
"""Dialign general setUp method for all tests"""
self.seqs1 = ['LDTAPCLFSDGSPQKAAYVLWDQTILQQDITPLPSHETHSAQKGELLALICGLRAAK',
'PDADHTWYTDGSSLLQEGQRKAGAAVTTETEVIWAKALDAGTSAQRAELIALTQALKM',
'RPGLCQVFADATPTGWGLVMGHQRMRGTFSAPLPIHTAELLAACFARSRSGANIIGTDNSVV',
'MLKQVEIFTDGSCLGNPGPGGYGAILRYRGREKTFSAGYTRTTNNRMELMAAIV']
self.labels1 = ['>HTL2','>MMLV', '>HEPB', '>ECOL']
self.lines1 = flatten(zip(self.labels1,self.seqs1))
self.out = \
"""
DIALIGN 2.2.1
*************
Program code written by Burkhard Morgenstern and Said Abdeddaim
e-mail contact: dialign (at) gobics (dot) de
Published research assisted by DIALIGN 2 should cite:
Burkhard Morgenstern (1999).
DIALIGN 2: improvement of the segment-to-segment
approach to multiple sequence alignment.
Bioinformatics 15, 211 - 218.
For more information, please visit the DIALIGN home page at
http://bibiserv.techfak.uni-bielefeld.de/dialign/
************************************************************
program call: dialign2-2 -fa -fn /tmp/di/seq1.fasta /tmp/di/seq1.txt
Aligned sequences: length:
================== =======
1) HTL2 57
2) MMLV 58
3) HEPB 62
4) ECOL 54
Average seq. length: 57.8
Please note that only upper-case letters are considered to be aligned.
Alignment (DIALIGN format):
===========================
HTL2 1 ldtapC-LFS DGS------P QKAAYVL--- ----WDQTIL QQDITPLPSH
MMLV 1 pdadhtw-YT DGSSLLQEGQ RKAGAAVtte teviWa---- KALDAG---T
HEPB 1 rpgl-CQVFA DAT------P TGWGLVM--- ----GHQRMR GTFSAPLPIH
ECOL 1 mlkqv-EIFT DGSCLGNPGP GGYGAIL--- ----RYRGRE KTFSAGytrT
0000000588 8882222229 9999999000 0000666666 6666633334
HTL2 37 ethSAQKGEL LALICGLRAa k--------- ---
MMLV 43 ---SAQRAEL IALTQALKm- ---------- ---
HEPB 37 t------AEL LAA-CFARSr sganiigtdn svv
ECOL 43 ---TNNRMEL MAAIv----- ---------- ---
0003333455 5533333300 0000000000 000
Sequence tree:
==============
Tree constructed using UPGMAbased on DIALIGN fragment weight scores
((HTL2 :0.130254MMLV :0.130254):0.067788(HEPB :0.120520ECOL :0.120520):0.077521);
"""
self.temp_dir = tempfile.mkdtemp()
try:
#create sequence files
f = open(path.join(self.temp_dir, 'seq1.txt'),'w')
f.write('\n'.join(self.lines1))
f.close()
except OSError:
pass
class DialignTests(GeneralSetUp):
"""Tests for the Dialign application controller"""
def test_base_command(self):
"""Dialign BaseCommand should return the correct BaseCommand"""
c = Dialign()
self.assertEqual(c.BaseCommand,
''.join(['cd ','"%s/"; ' % getcwd(),'dialign2-2']))
c.Parameters["-fa"].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd ','"%s/"; ' % getcwd(),'dialign2-2 -fa']))
def test_align(self):
"""test aligning samples"""
c = Dialign(WorkingDir=self.temp_dir,
params={"-fn":path.join(self.temp_dir,"seq1.txt")})
c.Parameters["-fa"].on()
res = c(path.join(self.temp_dir, 'seq1.txt'))
align = "".join(res["Align"].readlines())
def test_cleaning_up(self):
"""not a test, just removes the temp files"""
shutil.rmtree(self.temp_dir)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_dotur.py 000644 000765 000024 00000012721 12024702176 021773 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# test_dotur.py
from os import getcwd, remove, rmdir, mkdir, path
import tempfile, shutil
from cogent.core.moltype import DNA, RNA, PROTEIN
from cogent.core.sequence import DnaSequence, RnaSequence
from cogent.core.alignment import DataError
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.dotur import Dotur, dotur_from_alignment, dotur_from_file,\
remap_seq_names
from cogent.parse.dotur import OtuListParser
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Development"
def rna_distance(first,second):
first = RnaSequence(first)
return first.fracDiff(second)
class DoturTests(TestCase):
def setUp(self):
"""Dotur general setUp method for all tests"""
self.seqs1_unaligned = {'1':'ACUGCUAGCUAGUAGCGUACGUA',\
'2':'GCUACGUAGCUAC',\
'3':'GCGGCUAUUAGAUCGUA'}
self.seqs2_aligned = {'a': 'UAGGCUCUGAUAUAAUAGCUCUC---------',\
'c': '------------UGACUACGCAU---------',\
'b': '----UAUCGCUUCGACGAUUCUCUGAUAGAGA'}
self.seqs2_unaligned = {'a': 'UAGGCUCUGAUAUAAUAGCUCUC',\
'c': 'UGACUACGCAU',\
'b': 'UAUCGCUUCGACGAUUCUCUGAUAGAGA'}
#self.seqs1 aligned to self.seqs2 with self.seqs2 included.
self.seqs1_and_seqs2_aligned = \
{'a': 'UAGGCUCUGAUAUAAUAGC-UCUC---------',\
'b': '----UAUCGCUUCGACGAU-UCUCUGAUAGAGA',\
'c': '------------UGACUAC-GCAU---------',\
'1': '-ACUGCUAGCUAGUAGCGUACGUA---------',\
'2': '----------GCUACGUAG-CUAC---------',\
'3': '-----GCGGCUAUUAG-AU-CGUA---------',\
}
self.otu_list_string = \
"""unique 3 a b c
0.00 3 a b c
0.59 2 a,c b
0.78 1 a,c,b
"""
self.otu_res_list = [
[0.0,3,[['a'],['b'],['c']]],\
[0.0,3,[['a'],['b'],['c']]],\
[float(0.59),2,[['a','c'],['b']]],\
[float(0.78),1,[['a','c','b']]],\
]
self.distance_matrix_string = \
"""
3
a 0.0 0.78125 0.59375
b 0.78125 0.0 0.71875
c 0.59375 0.71875 0.0
"""
self.int_keys = {'seq_1': 'b', 'seq_0': 'a', 'seq_2': 'c'}
self.otu_lists_unmapped = [\
[['seq_0'], ['seq_1'], ['seq_2']],
[['seq_0'], ['seq_1'], ['seq_2']],
[['seq_0', 'seq_2'], ['seq_1']],
[['seq_0', 'seq_2', 'seq_1']],
]
self.otu_lists_mapped = [\
[['a'], ['b'], ['c']],
[['a'], ['b'], ['c']],
[['a', 'c'], ['b']],
[['a', 'c', 'b']],
]
self.temp_dir = tempfile.mkdtemp()
self.temp_dir_spaces = '/tmp/test_for_dotur/'
try:
mkdir(self.temp_dir_spaces)
except OSError:
pass
try:
#create sequence files
f = open(path.join(self.temp_dir, 'seqs1.sto'),'w')
f.write('')
f.close()
self.d_mat_file = path.join(self.temp_dir, 'dmat.txt')
d_mat = open(self.d_mat_file,'w')
d_mat.write(self.distance_matrix_string)
d_mat.close()
except OSError:
pass
def test_base_command(self):
"""Dotur BaseCommand should return the correct BaseCommand"""
c = Dotur()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','dotur']))
c.Parameters['-l'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','dotur -l']))
def test_changing_working_dir(self):
"""Dotur BaseCommand should change according to WorkingDir"""
c = Dotur(WorkingDir='/tmp/dotur_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/dotur_test','/"; ','dotur']))
c = Dotur()
c.WorkingDir = '/tmp/dotur_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/dotur_test2','/"; ','dotur']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/dotur_test')
rmdir('/tmp/dotur_test2')
def test_remap_seq_names(self):
"""remap_seq_names should function as expected."""
for unmapped, mapped in zip(self.otu_lists_unmapped,\
self.otu_lists_mapped):
self.assertEqual(remap_seq_names(unmapped,self.int_keys),mapped)
def test_dotur_from_alignment(self):
"""dotur_from_alignment should behave correctly."""
res = dotur_from_alignment(aln=self.seqs2_aligned,moltype=RNA,\
distance_function=rna_distance)
self.assertEqual(res,self.otu_res_list)
def test_dotur_from_file(self):
"""dotur_from_alignment should behave correctly."""
res = dotur_from_file(self.d_mat_file)
self.assertEqual(res,self.otu_res_list)
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_dynalign.py 000644 000765 000024 00000004373 12024702176 022447 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.app.dynalign import Dynalign
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class DynalignTest(TestCase):
"""Tests for Dynalign application controller"""
def setUp(self):
self.input1 = dynalign_input1
self.input2 = dynalign_input2
def test_stdout_input_as_lines(self):
"""Test Dynalign stdout input as lines"""
d = Dynalign(InputHandler='_input_as_lines')
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in dynalign_stdout])
res = d([self.input1,self.input2])
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test Dynalign stdout input as string"""
d = Dynalign()
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in dynalign_stdout])
f = open('/tmp/dyn1','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input1])
f.write(txt)
f.close()
s = open('/tmp/dyn2','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input2])
s.write(txt)
s.close()
res = d(['/tmp/dyn1','/tmp/dyn2'])
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_get_result_path(self):
"""Tests Dynalign result path"""
d = Dynalign(InputHandler='_input_as_lines')
res = d([self.input1,self.input2])
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus',\
'seq_1_ct','seq_2_ct','alignment'])
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
dynalign_input1 = [';\n', 'testSeq1\n', '\n',
'GGCTAGATAGCTCAGGTCGGTTCGATCCCGGCTCTGGCC1']
dynalign_input2 = [';\n', 'testSeq2\n', '\n',
'GGCTAGATAGCTGTGTCGTCGGTTCGATCCCGGCTCTGGCC1']
dynalign_stdout = ['12%\n', '25%\n', '38%\n', '51%\n', '64%\n', '76%\n',
'89%\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_fasttree.py 000644 000765 000024 00000022403 12024702176 022451 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for FastTree v1.1 application controller.
Also functions on v2.0.1, v2.1.0 and v2.1.3"""
from shutil import rmtree
from os import getcwd
from cogent.util.unit_test import TestCase, main
from cogent.app.fasttree import FastTree, build_tree_from_alignment
from cogent.core.alignment import Alignment
from cogent.parse.fasta import MinimalFastaParser
from cogent.parse.tree import DndParser
from cogent.core.moltype import DNA
__author__ = "Daniel McDonald"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Daniel McDonald", "Justin Kuczynski"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Daniel McDonald"
__email__ = "mcdonadt@colorado.edu"
__status__ = "Development"
class FastTreeTests(TestCase):
def setUp(self):
self.seqs = Alignment(dict(MinimalFastaParser(test_seqs.split())))
def test_base_command(self):
app = FastTree()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','FastTree']))
app.Parameters['-nt'].on()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','FastTree -nt']))
def test_change_working_dir(self):
app = FastTree(WorkingDir='/tmp/FastTreeTest')
self.assertEqual(app.BaseCommand, \
''.join(['cd "','/tmp/FastTreeTest','/"; ','FastTree']))
rmtree('/tmp/FastTreeTest')
def test_build_tree_from_alignment(self):
tree = build_tree_from_alignment(self.seqs, DNA)
# test expected output for fasttree 1.1 and 2.0.1
try:
for o,e in zip(tree.traverse(), DndParser(exp_tree).traverse()):
self.assertEqual(o.Name,e.Name)
self.assertFloatEqual(o.Length,e.Length)
except AssertionError:
for o,e in zip(tree.traverse(), DndParser(exp_tree_201).traverse()):
self.assertEqual(o.Name,e.Name)
self.assertFloatEqual(o.Length,e.Length)
test_seqs = """>test_set1_0
GGTAGATGGGACTACCTCATGACATGAAACTGCAGTCTGTTCTTTTATAGAAGCTTCATACTTGGAGATGTATACTATTA
CTTAGGACTATGGAGGTATA
>test_set1_1
GGTTGATGGGACTACGTAGTGACATGAAATTGCAGTCTGTGCTTTTATAGAAGTTTGATACTTGGAGCTCTCTACTATTA
CTTAGGACTATGGAGGTATA
>test_set1_2
GGTTGATGGGCCTACCTCATGACAATAAACTGAAGTCTGTGCTTTTATAGAGGCTTGATACTTGGAGCTCTATACTATTA
CTTAGGATTATGGAGGTCTA
>test_set1_3
GGTTGATGGGACTACCTCATGACATGAAACTGCAGTCTGTGCTTTTATAGAAGCTTGATACTTGGAGATCTATACTATTA
CTTAGGACTATGGAGGTCAC
>test_set1_4
GGTTGGTGGGACTACCTCATGACATGAAGATGCAGTCTGTGCTTGTATAGAAGCTTGAAACTTGGATATCTATACTATTA
CTTAAGACTATGGAGGTCTA
>test_set1_5
GGTTGATGCGACTACCTCATGACATGAGACTGCAGTCTGTGCTTTTACTGAAGCTTGATACTTGGAGATCTATACTATTA
CTTAGGACTATGGAGGTTTA
>test_set1_6
GGTTGATGGGACTACCTCATGACATGAAAATGCAGTCTGTCCTTTTATAGAAGCTTGATACTTGTAGATCTATACTGTTA
CTTAGGACTATGGAGGTCTA
>test_set1_7
GGTTGATGGGACTCCCTCATGACATAAAACTGCAGTCTGTGCTTTTACAGAAGCTTGATACTTGGAGATCTATACTATTA
CATAGGACTATGGAGGTCTA
>test_set1_8
GGTTGATGGCACTACCTCATGAGATGAAACTGCAGTCTGTGCTTTTATAGAAGCTTGATACTTGGATATCTATACTATAA
CTTAGTACTATGGAGGCCTA
>test_set1_9
GGTTTATGTTACTACCTCATGACATGAAACGGCAGCATGTGCTTTTATAGAAGCTTGATACTTGGAGATCTAAACTATTA
CTTAGGACTATGGAGGTCTA
>test_set2_0
AGCGAATCATACTCTGGAAAGAAAAGGACGACTCCTTTGCTCGCGGTCTAGCTGCTACAGCTTCACCGAGTACATCTGAA
TGATGGTTGAACCGGGTTCA
>test_set2_1
AGAGAATAGTACTCTGGAAAGACAAGGACGACTCCTTTGATCGCGGTCTAGCTGCTACAGCTTCACCGAGTACATCTGAA
TGATGGTTGAACCGGATTCA
>test_set2_2
AGAGTATAATACTCTGGAAAGAAAAGGACGACTCCTTTGATCGCGGTCTAGCTGCTACAGCTTCACCGAGTACATCTTAA
TGATGGTTGAACCGGGGTCA
>test_set2_3
AGAGAATCATACTCTGGAAAGAAATGGACGACTCCTTTGATCGCGGTCCAGCTGCTACAGCTTCACCGAGTACATCTGAA
TGATGGTTGGACCGGGTTCA
>test_set2_4
AGAGAATAATAGTCTGGAAAGAAAAGGACGACTCCTTTGTTCCCGGTCTAGCTGCTACAGCTTCCCCGAGTACATCTGAA
TGATGGTTGAACCGGGTTCA
>test_set2_5
ACAGAATACTACTCTGGAAAGAAAAGGCCGACTCCTTTGATCGCTGTCTAGCTGCGACAGCTGCACGGAGTCCATCCGAA
TGATGGTTGAACCGGGTTCA
>test_set2_6
AGAGAATAATACTCTGGACAGAAATGGACGACTCCTTTGATCGCGGTCTAGCTGCTACAGCTTCACCGAGTACATCTGAA
TGATGGCTGAACCGGGTTCA
>test_set2_7
AGAGAATATTACTCTGGAAAGAAAAGGACGACTCCTTGGATCGCGGTCTAGCTGCTACAGCTTCAGCGAGTACATCGGAA
TGATGGTTTAACCGGGTTCA
>test_set2_8
AGTGAATAATACTCTGGAAAGAAAAGGACGACTCCTTTGATCGCGGTCTAGCTGCTAGAGCTTCACCGAGTACATCTGAA
TGATGGTTGAACCGGGTTCA
>test_set2_9
AGAGATTAATACTCTGGATAGAAAATGACGACTCCTTTGATCGCGGTCTAGCTGCTACAGATTGACCTATTACATCTGAA
TGATGGTTGAACCGGGTTCA
>test_set3_0
TTGTCTCCATTGAGCACTCTAATCTTGCCGTGTATTCAGGAAAGGAGGATAGAACTCGGACAGTATTCTGAACATTACAG
AATCGCCGTATTTACGGTGT
>test_set3_1
TTGTCTCCATTGAGCACTCTAATCATGCCGTGTATTCAGGAACGGAGGAGAGGACTCGGTCAGTATTCGGAACATTACAG
AATGGCGTTATTTACGGTGT
>test_set3_2
TTGTCTCCATTGAGCACTCTAATCTTGCCGTGTATTCAGGAACGGAGGATAGAACTCGGACAGAATCCTGAATATTACAA
AATCGGGTTATTTACGGTGT
>test_set3_3
TTGTCTCCATTGAGCACTCTAATCTTGCCGTGTTTTCAGGAACGGAGGATAGAACTCGGACAGTAGCCTGAACATTACAG
AATCCCGTTATTTACGGTGT
>test_set3_4
TTGTCTCCATCGAGCACTCTAATCTTGCCGTGTATTCAGGAACGGAGGATTGAACTCGGACAGTATCCTGAACATTACAG
AATCGCGTTATTTACGGTGT
>test_set3_5
TTGTCTCCATTGAGCACGCTAAGCTTGCCGTGTATTCAGGAACGGAGGATAGAACTCGGACAGTATCCTGAACATTACAG
AATCGCGTTATTTACGGTGT
>test_set3_6
TTGTCGTCATTGAGCACTCTAATCTTGCCGTGTATTCAGGAACGAAGGATAGAACTCGGACAGTATCCTGAACTTTGCAA
AATCGCGTTATTTACGGTGT
>test_set3_7
TTGTCTCCATTGAGCACTCTAATCTAGCCGTGTAGTCAGGAACGGAGGATGGAACGCGCACAGTATCCTGAACATAACAG
AATCGCGTTATTTACGGTGT
>test_set3_8
TTGTCTCCATTGAGCACTCTAATCTTGCCGTATATTCCCGAACGGAGGATAGAACTCGGACAGTAGCCTGAACAGTACAG
AATCGCGTTATTTACGGTGT
>test_set3_9
TTGTCTCCCTTGAGCACTCTAATCTTGCCGTGTATTCAGGAACGGAGGATAGAACTCGGACAGTATCCTGAACATTACAG
AATCGCGTTATTTACGGTGT
>test_set4_0
CTTTTACCGGGCTGCCCGAGAGCACTATCTGCGTCGTGCCCTGCTTCGATGCCCACACTACCATCATACTATTCGTGAAT
TTGCGGCCGCTAAGATCCGA
>test_set4_1
CTTTTATCGGGGTGCCTGATAGCACCATCTGCGTCGTGCCCTGCTTCGATGCCTAAACCACCGTCATGCTATTTGTGAAT
TTGAGGTCGCTAAGAGCCCA
>test_set4_2
CTTTTATCGGGGTGCCCGAGAGCACCATCTGCGTCGTGCCCTGCTTCGATGCCCAGGCCACCATCATACTATTTGTGGCT
TAGGGGTCGCTAAGAGCCGA
>test_set4_3
CTTTTATCGGGGGGCCCGAGAGCACCACCTGCGTCGTGCCCTGCTTCGATGCCCAAACCACCATCATACTATTTGTGAAT
TTGGGGTCGCTAAGAGCCGA
>test_set4_4
CTTTTATAGGGGTGCCCGAGAGCACCATCTGCGTCGTGCCCAGCTTCGATTTCCAAACCACCATCATACTATTTGTGAAC
TTGGGGACGTTAAGAGCCGA
>test_set4_5
CTTTTCGCGGGGTGCCCGAGAGCACCATCTGCGTCGCGCCCTGCTTCGGTGCCCATACCACCATCATAATATTTGGGAAA
TTGGGATCGCTAAGAGTCGA
>test_set4_6
CTTTTCTCGGGGTGCCCGAGAGCCCCATCTGCGTTGTGCCCTGCTACTATGCCCAAACCACCATCATACTATTTGTGAAT
GTGGCGTCGCTCAGAGCCGA
>test_set4_7
CTTTTATCGGGGTGCCCGAGAGCACCATCTGCGTCGTGCCCTGCTTCGATGCCCACGTCACCATACTACTATTTGTGAAT
TTGGGGTCGCTAATAGCCGA
>test_set4_8
CTTTTATCGGGGGGCCCGAGAGCATCATCTGCGTCGTGCCCTGCTTCGATGCCCAAACTACCATCATACTATTTGTGAAT
TTGGGGTTTCTAAGAGCCGA
>test_set4_9
CTTTTACCGGGGTGACCGAGAGCACCATCTGCGCCGTGCCCTGCTTCGAGGCCCAAACCACCATCATACTGTTTGTGAAT
CAGGGGTTGCTAAGAGCCGA"""
exp_tree = """((test_set2_0:0.02121,(test_set2_8:-0.03148,(((test_set3_6:0.05123,(test_set3_5:0.01878,((test_set3_0:0.03155,test_set3_1:0.06432)0.664:0.01096,(((test_set3_3:0.02014,test_set3_8:0.04240)0.880:0.01129,(test_set3_7:0.05900,test_set3_4:0.01449)0.756:0.00571)0.514:0.00038,test_set3_9:0.00907)0.515:0.00020)0.834:0.00164)0.708:0.01349)0.754:0.19207,test_set3_2:-0.16026)0.999:1.34181,(test_set1_2:0.00324,((test_set1_0:0.04356,test_set1_1:0.07539)0.393:0.00223,((test_set1_3:0.01998,(test_set1_9:0.07362,((test_set1_4:0.06701,test_set1_8:0.05195)0.397:0.00350,(((test_set4_4:0.06931,(((test_set4_2:0.03637,test_set4_7:0.04823)0.726:0.01237,((test_set4_5:0.09845,test_set4_6:0.08151)0.593:0.00959,((test_set4_3:0.01520,test_set4_8:0.03654)0.590:0.00869,test_set4_9:0.07865)0.499:0.00229)0.479:0.00187)0.430:0.00179,test_set4_0:0.08643)0.651:0.00975)0.478:0.04249,test_set4_1:0.03754)1.000:1.66272,test_set1_6:-0.12006)0.803:0.15777)0.490:0.00569)0.562:0.00182)0.879:0.00579,(test_set1_7:0.03234,test_set1_5:0.04114)0.520:0.00487)0.567:0.00688)0.651:0.06887)0.923:0.48284)0.994:1.24321)0.517:0.05040)0.522:0.00306,test_set2_4:0.03835,((test_set2_9:0.07472,(test_set2_3:0.03380,test_set2_6:0.01794)0.540:0.00679)0.583:0.00234,(test_set2_2:0.03055,((test_set2_5:0.08864,test_set2_7:0.04212)0.724:0.00563,test_set2_1:0.02522)0.905:0.00645)0.566:0.00081)0.642:0.00394);"""
# for FastTree version 2.0.1
exp_tree_201 = """(((test_set2_8:0.00039,(((test_set3_6:0.05278,(test_set3_5:0.02030,(((test_set3_0:0.03166,test_set3_1:0.06412)0.783:0.00945,(test_set3_7:0.06330,test_set3_4:0.02026)0.896:0.00014)0.911:0.00014,((test_set3_3:0.02053,test_set3_8:0.04149)0.790:0.00995,test_set3_9:0.01011)0.927:0.00015)0.922:0.00015)0.780:0.00976)0.763:0.03112,test_set3_2:0.00014)0.881:1.40572,(((((test_set1_9:0.07378,(test_set1_7:0.03123,test_set1_5:0.04198)0.756:0.00995)0.883:0.00016,(test_set1_3:0.02027,((test_set1_0:0.04231,test_set1_1:0.07523)0.377:0.00928,test_set1_2:0.07433)0.868:0.00016)0.131:0.00015)0.872:0.00016,test_set1_8:0.06287)0.438:0.00975,(test_set1_6:0.00014,((((test_set4_4:0.07405,(test_set4_6:0.07814,test_set4_5:0.10163)0.688:0.00645)1.000:0.00015,((test_set4_2:0.03960,test_set4_7:0.05092)0.776:0.01382,(test_set4_9:0.07780,test_set4_0:0.08964)0.197:0.00703)0.862:0.00014)0.798:0.00014,(test_set4_3:0.01000,test_set4_8:0.04167)0.782:0.01024)1.000:0.07368,test_set4_1:0.00014)1.000:1.73333)0.598:0.03127)0.122:0.00091,test_set1_4:0.06300)0.634:0.46513)0.918:1.50492)0.600:0.01987,test_set2_0:0.03067)0.466:0.00015,test_set2_4:0.04129,((test_set2_2:0.03073,(test_set2_1:0.03068,(test_set2_5:0.09729,test_set2_7:0.05209)0.421:0.00015)0.851:0.00015)0.771:0.00015,(test_set2_9:0.07415,(test_set2_3:0.03110,test_set2_6:0.02061)0.776:0.00997)0.985:0.00016)0.879:0.00015);"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_fasttree_v1.py 000644 000765 000024 00000017033 12024702176 023062 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for FastTree v1.0.0 application controller"""
from shutil import rmtree
from os import getcwd
from cogent.util.unit_test import TestCase, main
from cogent.app.fasttree_v1 import FastTree, build_tree_from_alignment
from cogent.core.alignment import Alignment
from cogent.parse.fasta import MinimalFastaParser
from cogent.parse.tree import DndParser
from cogent.core.moltype import DNA
__author__ = "Daniel McDonald"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Daniel McDonald"
__email__ = "mcdonadt@colorado.edu"
__status__ = "Development"
class FastTreeTests(TestCase):
def setUp(self):
self.seqs = Alignment(dict(MinimalFastaParser(test_seqs.split())))
def test_base_command(self):
app = FastTree()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','FastTree']))
app.Parameters['-nt'].on()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','FastTree -nt']))
def test_change_working_dir(self):
app = FastTree(WorkingDir='/tmp/FastTreeTest')
self.assertEqual(app.BaseCommand, \
''.join(['cd "','/tmp/FastTreeTest','/"; ','FastTree']))
rmtree('/tmp/FastTreeTest')
def test_build_tree_from_alignment(self):
tree = build_tree_from_alignment(self.seqs, DNA)
for o,e in zip(tree.traverse(), DndParser(exp_tree).traverse()):
self.assertEqual(o.Name,e.Name)
self.assertFloatEqual(o.Length,e.Length)
test_seqs = """>test_set1_0
GGTAGATGGGACTACCTCATGACATGAAACTGCAGTCTGTTCTTTTATAGAAGCTTCATACTTGGAGATGTATACTATTA
CTTAGGACTATGGAGGTATA
>test_set1_1
GGTTGATGGGACTACGTAGTGACATGAAATTGCAGTCTGTGCTTTTATAGAAGTTTGATACTTGGAGCTCTCTACTATTA
CTTAGGACTATGGAGGTATA
>test_set1_2
GGTTGATGGGCCTACCTCATGACAATAAACTGAAGTCTGTGCTTTTATAGAGGCTTGATACTTGGAGCTCTATACTATTA
CTTAGGATTATGGAGGTCTA
>test_set1_3
GGTTGATGGGACTACCTCATGACATGAAACTGCAGTCTGTGCTTTTATAGAAGCTTGATACTTGGAGATCTATACTATTA
CTTAGGACTATGGAGGTCAC
>test_set1_4
GGTTGGTGGGACTACCTCATGACATGAAGATGCAGTCTGTGCTTGTATAGAAGCTTGAAACTTGGATATCTATACTATTA
CTTAAGACTATGGAGGTCTA
>test_set1_5
GGTTGATGCGACTACCTCATGACATGAGACTGCAGTCTGTGCTTTTACTGAAGCTTGATACTTGGAGATCTATACTATTA
CTTAGGACTATGGAGGTTTA
>test_set1_6
GGTTGATGGGACTACCTCATGACATGAAAATGCAGTCTGTCCTTTTATAGAAGCTTGATACTTGTAGATCTATACTGTTA
CTTAGGACTATGGAGGTCTA
>test_set1_7
GGTTGATGGGACTCCCTCATGACATAAAACTGCAGTCTGTGCTTTTACAGAAGCTTGATACTTGGAGATCTATACTATTA
CATAGGACTATGGAGGTCTA
>test_set1_8
GGTTGATGGCACTACCTCATGAGATGAAACTGCAGTCTGTGCTTTTATAGAAGCTTGATACTTGGATATCTATACTATAA
CTTAGTACTATGGAGGCCTA
>test_set1_9
GGTTTATGTTACTACCTCATGACATGAAACGGCAGCATGTGCTTTTATAGAAGCTTGATACTTGGAGATCTAAACTATTA
CTTAGGACTATGGAGGTCTA
>test_set2_0
AGCGAATCATACTCTGGAAAGAAAAGGACGACTCCTTTGCTCGCGGTCTAGCTGCTACAGCTTCACCGAGTACATCTGAA
TGATGGTTGAACCGGGTTCA
>test_set2_1
AGAGAATAGTACTCTGGAAAGACAAGGACGACTCCTTTGATCGCGGTCTAGCTGCTACAGCTTCACCGAGTACATCTGAA
TGATGGTTGAACCGGATTCA
>test_set2_2
AGAGTATAATACTCTGGAAAGAAAAGGACGACTCCTTTGATCGCGGTCTAGCTGCTACAGCTTCACCGAGTACATCTTAA
TGATGGTTGAACCGGGGTCA
>test_set2_3
AGAGAATCATACTCTGGAAAGAAATGGACGACTCCTTTGATCGCGGTCCAGCTGCTACAGCTTCACCGAGTACATCTGAA
TGATGGTTGGACCGGGTTCA
>test_set2_4
AGAGAATAATAGTCTGGAAAGAAAAGGACGACTCCTTTGTTCCCGGTCTAGCTGCTACAGCTTCCCCGAGTACATCTGAA
TGATGGTTGAACCGGGTTCA
>test_set2_5
ACAGAATACTACTCTGGAAAGAAAAGGCCGACTCCTTTGATCGCTGTCTAGCTGCGACAGCTGCACGGAGTCCATCCGAA
TGATGGTTGAACCGGGTTCA
>test_set2_6
AGAGAATAATACTCTGGACAGAAATGGACGACTCCTTTGATCGCGGTCTAGCTGCTACAGCTTCACCGAGTACATCTGAA
TGATGGCTGAACCGGGTTCA
>test_set2_7
AGAGAATATTACTCTGGAAAGAAAAGGACGACTCCTTGGATCGCGGTCTAGCTGCTACAGCTTCAGCGAGTACATCGGAA
TGATGGTTTAACCGGGTTCA
>test_set2_8
AGTGAATAATACTCTGGAAAGAAAAGGACGACTCCTTTGATCGCGGTCTAGCTGCTAGAGCTTCACCGAGTACATCTGAA
TGATGGTTGAACCGGGTTCA
>test_set2_9
AGAGATTAATACTCTGGATAGAAAATGACGACTCCTTTGATCGCGGTCTAGCTGCTACAGATTGACCTATTACATCTGAA
TGATGGTTGAACCGGGTTCA
>test_set3_0
TTGTCTCCATTGAGCACTCTAATCTTGCCGTGTATTCAGGAAAGGAGGATAGAACTCGGACAGTATTCTGAACATTACAG
AATCGCCGTATTTACGGTGT
>test_set3_1
TTGTCTCCATTGAGCACTCTAATCATGCCGTGTATTCAGGAACGGAGGAGAGGACTCGGTCAGTATTCGGAACATTACAG
AATGGCGTTATTTACGGTGT
>test_set3_2
TTGTCTCCATTGAGCACTCTAATCTTGCCGTGTATTCAGGAACGGAGGATAGAACTCGGACAGAATCCTGAATATTACAA
AATCGGGTTATTTACGGTGT
>test_set3_3
TTGTCTCCATTGAGCACTCTAATCTTGCCGTGTTTTCAGGAACGGAGGATAGAACTCGGACAGTAGCCTGAACATTACAG
AATCCCGTTATTTACGGTGT
>test_set3_4
TTGTCTCCATCGAGCACTCTAATCTTGCCGTGTATTCAGGAACGGAGGATTGAACTCGGACAGTATCCTGAACATTACAG
AATCGCGTTATTTACGGTGT
>test_set3_5
TTGTCTCCATTGAGCACGCTAAGCTTGCCGTGTATTCAGGAACGGAGGATAGAACTCGGACAGTATCCTGAACATTACAG
AATCGCGTTATTTACGGTGT
>test_set3_6
TTGTCGTCATTGAGCACTCTAATCTTGCCGTGTATTCAGGAACGAAGGATAGAACTCGGACAGTATCCTGAACTTTGCAA
AATCGCGTTATTTACGGTGT
>test_set3_7
TTGTCTCCATTGAGCACTCTAATCTAGCCGTGTAGTCAGGAACGGAGGATGGAACGCGCACAGTATCCTGAACATAACAG
AATCGCGTTATTTACGGTGT
>test_set3_8
TTGTCTCCATTGAGCACTCTAATCTTGCCGTATATTCCCGAACGGAGGATAGAACTCGGACAGTAGCCTGAACAGTACAG
AATCGCGTTATTTACGGTGT
>test_set3_9
TTGTCTCCCTTGAGCACTCTAATCTTGCCGTGTATTCAGGAACGGAGGATAGAACTCGGACAGTATCCTGAACATTACAG
AATCGCGTTATTTACGGTGT
>test_set4_0
CTTTTACCGGGCTGCCCGAGAGCACTATCTGCGTCGTGCCCTGCTTCGATGCCCACACTACCATCATACTATTCGTGAAT
TTGCGGCCGCTAAGATCCGA
>test_set4_1
CTTTTATCGGGGTGCCTGATAGCACCATCTGCGTCGTGCCCTGCTTCGATGCCTAAACCACCGTCATGCTATTTGTGAAT
TTGAGGTCGCTAAGAGCCCA
>test_set4_2
CTTTTATCGGGGTGCCCGAGAGCACCATCTGCGTCGTGCCCTGCTTCGATGCCCAGGCCACCATCATACTATTTGTGGCT
TAGGGGTCGCTAAGAGCCGA
>test_set4_3
CTTTTATCGGGGGGCCCGAGAGCACCACCTGCGTCGTGCCCTGCTTCGATGCCCAAACCACCATCATACTATTTGTGAAT
TTGGGGTCGCTAAGAGCCGA
>test_set4_4
CTTTTATAGGGGTGCCCGAGAGCACCATCTGCGTCGTGCCCAGCTTCGATTTCCAAACCACCATCATACTATTTGTGAAC
TTGGGGACGTTAAGAGCCGA
>test_set4_5
CTTTTCGCGGGGTGCCCGAGAGCACCATCTGCGTCGCGCCCTGCTTCGGTGCCCATACCACCATCATAATATTTGGGAAA
TTGGGATCGCTAAGAGTCGA
>test_set4_6
CTTTTCTCGGGGTGCCCGAGAGCCCCATCTGCGTTGTGCCCTGCTACTATGCCCAAACCACCATCATACTATTTGTGAAT
GTGGCGTCGCTCAGAGCCGA
>test_set4_7
CTTTTATCGGGGTGCCCGAGAGCACCATCTGCGTCGTGCCCTGCTTCGATGCCCACGTCACCATACTACTATTTGTGAAT
TTGGGGTCGCTAATAGCCGA
>test_set4_8
CTTTTATCGGGGGGCCCGAGAGCATCATCTGCGTCGTGCCCTGCTTCGATGCCCAAACTACCATCATACTATTTGTGAAT
TTGGGGTTTCTAAGAGCCGA
>test_set4_9
CTTTTACCGGGGTGACCGAGAGCACCATCTGCGCCGTGCCCTGCTTCGAGGCCCAAACCACCATCATACTGTTTGTGAAT
CAGGGGTTGCTAAGAGCCGA"""
exp_tree = """(test_set1_3:0.02062,(test_set1_8:0.05983,test_set1_9:0.07093)0.652:0.00422,((test_set1_5:0.04140,test_set1_7:0.03208)0.634:0.00995,((test_set1_0:0.04748,(test_set1_1:0.07025,(test_set1_2:-0.00367,((((((test_set3_4:0.01485,test_set3_7:0.05863)0.862:0.00569,(test_set3_5:0.02048,(test_set3_3:0.02036,test_set3_8:0.04218)0.724:0.01088)0.397:0.00005)0.519:0.00018,((test_set3_0:0.03139,test_set3_1:0.06448)0.699:0.01095,test_set3_9:0.00940)0.505:0.00036)0.721:0.01080,test_set3_6:0.05333)0.808:0.16470,test_set3_2:-0.12547)1.000:1.42295,((test_set4_1:-0.24707,((test_set4_3:0.00903,test_set4_8:0.04272)0.650:0.00955,(test_set4_4:0.07633,((test_set4_5:0.09853,test_set4_6:0.08143)0.577:0.00748,((test_set4_0:0.08822,test_set4_9:0.07914)0.371:0.00130,(test_set4_2:0.03477,test_set4_7:0.04983)0.764:0.01228)0.665:0.00370)0.535:0.00147)0.633:0.00116)0.850:0.32065)0.998:1.45908,(((test_set2_2:0.03125,((test_set2_8:0.01770,(test_set2_0:0.02172,test_set2_4:0.04082)0.482:0.00228)0.575:0.00249,(test_set2_9:0.07291,(test_set2_3:0.03201,test_set2_6:0.01973)0.538:0.00746)0.690:0.00319)0.746:0.00073)0.788:0.00569,(test_set2_5:0.08827,test_set2_7:0.04250)0.717:0.00533)0.504:0.04532,test_set2_1:-0.01642)0.997:1.14023)0.625:0.41298)0.822:0.20836)0.783:0.07781)0.487:0.00591)0.469:0.00151,(test_set1_4:0.06606,test_set1_6:0.02981)0.703:0.00956)0.560:0.00216)0.468:0.00050);"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_foldalign.py 000644 000765 000024 00000003453 12024702176 022577 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.foldalign import foldalign
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class FoldalignTest(TestCase):
"""Tests for Foldalign application controller"""
def setUp(self):
self.input = FOLDALIGN_INPUT
def test_input_as_lines(self):
"""Test foldalign stdout input as lines"""
f = foldalign(InputHandler='_input_as_lines')
res = f(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test foldalign stdout input as string"""
f = foldalign()
t = open('/tmp/single.col','w')
t.write('\n'.join(self.input))
t.close()
res = f('/tmp/single.col')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/single.col')
def test_get_result_path(self):
"""Tests foldalign result path"""
f = foldalign(InputHandler='_input_as_lines')
res = f(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
FOLDALIGN_INPUT = ['>seq1\n', 'GGCCACGTAGCTCAGTCGGTAGAGCAAAGGACTGAAAATCCTTGTGTCGTTGGTTCAATTCCAACCGTGGCCACCA','>seq2\n', 'GCCAGATAGCTCAGTCGGTAGAGCGTTCGCCTGAAAAGTGAAAGGTCGCCGGTTCGATCCCGGCTCTGGCCACCA']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_formatdb.py 000755 000765 000024 00000065300 12024702176 022440 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# Author: Greg Caporaso (gregcaporaso@gmail.com)
# test_formatdb.py
""" Description
File created on 16 Sep 2009.
"""
from __future__ import division
from os.path import split, exists
from cogent import LoadSeqs
from cogent.util.unit_test import TestCase, main
from cogent.app.util import get_tmp_filename
from cogent.util.misc import remove_files
from cogent.app.blast import blastn
from cogent.app.formatdb import FormatDb, build_blast_db_from_seqs,\
build_blast_db_from_fasta_path, build_blast_db_from_fasta_file
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Greg Caporaso"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Greg Caporaso"
__email__ = "gregcaporaso@gmail.com"
__status__ = "Production"
class FormatDbTests(TestCase):
def setUp(self):
self.in_seqs1_fp =\
get_tmp_filename(prefix='FormatDbTests',suffix='.fasta')
self.in_seqs1_file = open(self.in_seqs1_fp,'w')
self.in_seqs1_file.write(in_seqs1)
self.in_seqs1_file.close()
self.in_seqs1 = LoadSeqs(self.in_seqs1_fp,aligned=False)
self.test_seq = test_seq
self.in_aln1_fp =\
get_tmp_filename(prefix='FormatDbTests',suffix='.fasta')
self.in_aln1_file = open(self.in_aln1_fp,'w')
self.in_aln1_file.write(in_aln1)
self.in_aln1_file.close()
self.in_aln1 = LoadSeqs(self.in_aln1_fp)
self.files_to_remove = [self.in_seqs1_fp,self.in_aln1_fp]
def tearDown(self):
remove_files(self.files_to_remove)
def test_call(self):
"""FormatDb: Calling on a nucleotide data functions as expected
"""
fdb = FormatDb(WorkingDir='/tmp')
result = fdb(self.in_seqs1_fp)
# test sucessful run
self.assertEqual(result['ExitStatus'],0)
expected_result_keys = set(\
['log','nhr','nin','nsd','nsi','nsq','ExitStatus','StdOut','StdErr'])
self.assertEqual(set(result.keys()),expected_result_keys)
inputfile_basename = split(self.in_seqs1_fp)[1]
# got all the expected out files, and filepaths are as expected
outpaths = []
for ext in ['log','nhr','nin','nsd','nsi','nsq']:
outpath = '/tmp/%s.%s' % (inputfile_basename,ext)
outpaths.append(outpath)
self.assertEqual(result[ext].name,outpath)
result.cleanUp()
# all created files are cleaned up
for outpath in outpaths:
self.assertFalse(exists(outpath),\
"%s was not cleaned up." % outpath)
def test_blast_against_new_db(self):
"""Formatdb: blastall against a newly created DB functions as expected
"""
fdb = FormatDb(WorkingDir='/tmp')
result = fdb(self.in_seqs1_fp)
blast_res = blastn(self.test_seq,blast_db=self.in_seqs1_fp)
result.cleanUp()
# Test that a blast result was returned
self.assertTrue('s1' in blast_res,\
"Not getting any blast results.")
# Test that the sequence we expect was a good blast hit
subject_ids = [r['SUBJECT ID'] for r in blast_res['s1'][0]]
self.assertTrue('11472384' in subject_ids,\
"Not getting expected blast results.")
def test_build_blast_db_from_seqs(self):
"""build_blast_db_from_seqs convenience function works as expected
"""
blast_db, db_files = build_blast_db_from_seqs(self.in_seqs1,output_dir='/tmp')
self.assertTrue(blast_db.startswith('/tmp/Blast_tmp_db'))
self.assertTrue(blast_db.endswith('.fasta'))
expected_db_files = set([blast_db + ext\
for ext in ['.nhr','.nin','.nsq','.nsd','.nsi','.log']])
self.assertEqual(set(db_files),expected_db_files)
# result returned when blasting against new db
self.assertEqual(\
len(blastn(self.test_seq,blast_db=blast_db)),1)
# Make sure all db_files exist
for fp in db_files:
self.assertTrue(exists(fp))
# Remove all db_files exist
remove_files(db_files)
# Make sure nothing weird happened in the remove
for fp in db_files:
self.assertFalse(exists(fp))
def test_build_blast_db_from_fasta_path(self):
"""build_blast_db_from_fasta_path convenience function works as expected
"""
blast_db, db_files = \
build_blast_db_from_fasta_path(self.in_seqs1_fp)
self.assertEqual(blast_db,self.in_seqs1_fp)
expected_db_files = set([self.in_seqs1_fp + ext\
for ext in ['.nhr','.nin','.nsq','.nsd','.nsi','.log']])
self.assertEqual(set(db_files),expected_db_files)
# result returned when blasting against new db
self.assertEqual(\
len(blastn(self.test_seq,blast_db=blast_db)),1)
# Make sure all db_files exist
for fp in db_files:
self.assertTrue(exists(fp))
# Remove all db_files exist
remove_files(db_files)
# Make sure nothing weird happened in the remove
for fp in db_files:
self.assertFalse(exists(fp))
def test_build_blast_db_from_fasta_path_aln(self):
"""build_blast_db_from_fasta_path works with alignment as input
"""
blast_db, db_files = build_blast_db_from_fasta_path(self.in_aln1_fp)
self.assertEqual(blast_db,self.in_aln1_fp)
expected_db_files = set([blast_db + ext\
for ext in ['.nhr','.nin','.nsq','.nsd','.nsi','.log']])
self.assertEqual(set(db_files),expected_db_files)
# result returned when blasting against new db
self.assertEqual(\
len(blastn(self.test_seq,blast_db=blast_db,e_value=0.0)),1)
# Make sure all db_files exist
for fp in db_files:
self.assertTrue(exists(fp))
# Remove all db_files exist
remove_files(db_files)
# Make sure nothing weird happened in the remove
for fp in db_files:
self.assertFalse(exists(fp))
def test_build_blast_db_from_fasta_file(self):
"""build_blast_db_from_fasta_file works with open files as input
"""
blast_db, db_files = \
build_blast_db_from_fasta_file(open(self.in_aln1_fp),output_dir='/tmp/')
self.assertTrue(blast_db.startswith('/tmp/BLAST_temp_db'))
self.assertTrue(blast_db.endswith('.fasta'))
expected_db_files = set([blast_db] + [blast_db + ext\
for ext in ['.nhr','.nin','.nsq','.nsd','.nsi','.log']])
self.assertEqual(set(db_files),expected_db_files)
# result returned when blasting against new db
self.assertEqual(\
len(blastn(self.test_seq,blast_db=blast_db,e_value=0.0)),1)
# Make sure all db_files exist
for fp in db_files:
self.assertTrue(exists(fp))
# Remove all db_files exist
remove_files(db_files)
# Make sure nothing weird happened in the remove
for fp in db_files:
self.assertFalse(exists(fp))
in_seqs1 = """>11472286
GATGAACGCTGGCGGCATGCTTAACACATGCAAGTCGAACGGAACACTTTGTGTTTTGAGTTAATAGTTCGATAGTAGATAGTAAATAGTGAACACTATGAACTAGTAAACTATTTAACTAGAAACTCTTAAACGCAGAGCGTTTAGTGGCGAACGGGTGAGTAATACATTGGTATCTACCTCGGAGAAGGACATAGCCTGCCGAAAGGTGGGGTAATTTCCTATAGTCCCCGCACATATTTGTTCTTAAATCTGTTAAAATGATTATATGTTTTATGTTTATTTGATAAAAAGCAGCAAGACAAATGAGTTTTATATTGGTTATACAGCAGATTTAAAAAATAGAATTAGGTCTCATAATCAGGGAGAAAACAAATCAACTAAATCTAAAATACCTTGGGAATTGGTTTACTATGAAGCCTACAAAAACCAAACATCAGCAAGGGTTAGAGAATCAAAGTTGAAACATTATGGGCAATCATTAACTAGACTTAAGAGAAGAATTGGTTTTTGAGAACAAATATGTGCGGGGTAAAGCAGCAATGCGCTCCGAGAGGAACCTCTGTCCTATCAGCTTGTTGGTAAGGTAATGGCTTACCAAGGCGACGACGGGTAGCTGGTGTGAGAGCACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGAGGAATTTTCCACAATGGGCGCAAGCCTGATGGAGCAATGCCGCGTGAAGGATGAAGATTTTCGGATTGTAAACTTCTTTTAAGTAGGAAGATTATGACGGTACTACTTGAATAAGCATCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGATGCAAGCGTTATCCGGAATTACTGGGCGTAAAGCGTGTGTAGGTGGTTTATTAAGTTAAATGTTAAATTTTCAGGCTTAACTTGGAAACCGCATTTAATACTGGTAGACTTTGAGGACAAGAGAGGCAGGCGGAATTAGCGGAGTAGCGGTGAAATGCGTAGATATCGCTAAGAACACCAATGGCGAAGGCAGCCTGCTGGTTTGCACCTGACACTGAGATACGAAAGCGTGGGGAGCGAACGGGATTAGATACCCCGGTAGTCCACGCCGTAAACGATGGTCACTAGCTGTTAGGGGCTCGACCCCTTTAGTAGCGAAGCTAACGCGTTAAGTGACCCGCCTGGGGAGTACGATCGCAAGATTAAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAACGTGAGGTTTAATTCGTCTCTAAGCGAAAAACCTTACCGAGGCTTGACATCTCCGGAAGACCTTAGAAATAAGGTTGTGCCCGAAAGGGAGCCGGATGACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTTGTGAAATGTTCGGTTAAGTCCGTTAACGAGCGCAACCCTTGCTGTGTGTTGTATTTTTCACACAGGACTATCCTGGTCAACAGGGAGGAAGGTGGGGATGACGTCAAGTCAGCATGGCTCTTACGCCTCGGGCTACACTCGCGTTACAATGGCCGGTACAATGGGCTGCCAACTCGTAAGGGGGAGCTAATCCCATCAAAACCGGTCCCAGTTCGGATTGAGGGCTGCAATTCGCCCTCATGAAGTCGGAATCGCTAGTAACCGCGAATCAGCACGTCGCGGTGAATGCGTTCTCGGGTCTTGTACACACTGCCCGTCACACCACGAAAGTTAGTAACGCCCGAAGTGCCCTGTATGGGGTCCTAAGGTGGGGCTAGCGATTGGGGTG
>11472384
AGAGTTTGATCCTGGCTCAGATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGCAGCACGGGGGCAACCCTGGTGGCGAGTGGCGAACGGGTGAGTAATACATCGGAACGTGTCCTGTAGTGGGGGATAGCCCGGCGAAAGCCGGATTAATACCGCATACGCTCTACGGAGGAAAGGGGGGGATCTTAGGACCTCCCGCTACAGGGGCGGCCGATGGCAGATTAGCTAGTTGGTGGGGTAAAGGCCTACCAAGGCGACGATCTGTAGCTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGACAATGGGGGCAACCCTGATCCAGCAATGCCGCGTGTGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTTGTCCGGAAAGAAAACGCCGTGGTTAATACCCGTGGCGGATGACGGTACCGGAAGAATAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGTGCGCAGGCGGTCCGCTAAGACAGATGTGAAATCCCCGGGCTTAACCTGGGAACTGCATTTGTGACTGGCGGGCTAGAGTATGGCAGAGGGGGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGGAATACCGATGGCGAAGGCAGCCCCCTGGGCCAATACTGACGCTCATGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCCTAAACGATGTCAACTAGTTGTCGGGTCTTCATTGACTTGGTAACGTAGCTAACGCGTGAAGTTGACCGCCTGGGGAGTACGGTCGCAAGATTAAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGATGATGTGGATTAATTCGATGCAACGCGAAAAACCTTACCTACCCTTGACATGTATGGAATCCTGCTGAGAGGTGGGAGTGCCCGAAAGGGAGCCATAACACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGTCCCTAGTTGCTACGCAAGAGCACTCTAGGGAGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAGTCCTCATGGCCCTTATGGGTAGGGCTTCACACGTCATACAATGGTCGGAACAGAGGGTCGCCAACCCGCGAGGGGGAGCCAATCCCAGAAAACCGATCGTAGTCCGGATCGCACTCTGCAACTCGAGTGCGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTTTACCAGAAGTGGCTAGTCTAACCGCAAGGAGGACGGTCACCACGGTAGGATTCATGACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTTCTCGAGCGAACGTGTCGAACGTTGAGCGCTCACGCTTATCGGCTGTGAAATTAGGACAGTAAGTCAGACAGACTGAGGGGTCTGTAGCTCAGTCGGTTAGAGCACCGTCTTGATAAGGCGGGGGTCGATGGTTCGAATCCATCCAGACCCACCATTGTCT
>11468680
TAAACTGAAGAGTTTGATCCTGGCTCAGATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGCAGCACGGGTGCTTGCACCTGGTGGCGAGTGGCGAACGGGTGAGTAATACATCGGAACATGTCCTGTAGTGGGGGATAGCCCGGCGAAAGCCGGATTAATACCGCATACGATCTACGGATGAAAGCGGGGGACCTTCGGGCCTCGCGCTATAGGGTTGGCCGATGGCTGATTAGCTAGTTGGTGGGGTAAAGGCCTACCAAGGCGACGATCAGTAGCTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGACAATGGGCGAAAGCCTGATCCAGCAATGCCGCGTGTGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTTGTCCGGAAAGAAATCCTTGGCTCTAATACAGTCGGGGGATGACGGTACCGGAAGAATAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGTGCGAGCGTTAATCGGAATTACTGGGCGTAAAGCGTGCGCAGGCGGTTTGCTAAGACCGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATTGGTGACTGGCAGGCTAGAGTATGGCAGAGGGGGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGGAATACCGATGGCGAAGGCAGCCCCCTGGGCCAATACTGACGCTCATGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCCTAAACGATGTCAACTAGTTGTTGGGGATTCATTTCCTTAGTAACGTAGCTAACGCGTGAAGTTGACCGCCTGGGGAGTACGGTCGCAAGATTAAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGATGATGTGGATTAATTCGATGCAACGCGAAAAACCTTACCTACCCTTGACATGGTCGGAATCCCGCTGAGAGGTGGGAGTGCTCGAAAGAGAACCGGCGCACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGTCCTTAGTTGCTACGCAAGAGCACTCTAAGGAGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAGTCCTCATGGCCCTTATGGGTAGGGCTTCACACGTCATACAATGGTCGGAACAGAGGGTTGCCAACCCGCGAGGGGGAGCTAATCCCAGAAAACCGATCGTAGTCCGGATTGCACTCTGCAACTCGAGTGCATGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTTTACCAGAAGTGGCTAGTCTAACCGCAAGGAGGACGGTCACCACGGTAGGATTCATGACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTTCCAGAGCTATCTCGCAAAGTTGAGCGCTCACGCTTATCGGCTGTAAATTTAAAGACAGACTCAGGGGTCTGTAGCTCAGTCGGTTAGAGCACCGTCTTGATAAGGCGGGGGTCGTTGGTTCGAATCCAACCAGACCCACCATTGTCTG
>11458037
GACGAACGCTGGCGGCGTGCCTAACACATGCAAGTCGAACGGTTTCGAAGATCGGACTTCGAATTTCGAATTTCGATCATCGAGATAGTGGCGGACGGGTGAGTAACGCGTGGGTAACCTACCCATAAAGCCGGGACAACCCTTGGAAACGAGGGCTAATACCGGATAAGCTTGAGAAGTGGCATCACTTTTTAAGGAAAGGTGGCCGATGAGAATGCTGCCGATTATGGATGGACCCGCGTCTGATTAGCTGGTTGGTGGGGTAAAGGCCTACCAAGGCGACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTGTATGATGAAGGTTTTCGGATTGTAAAGTACTGTCTATGGGGAAGAATGGTGTGCTTGAGAATATTAAGTACAAATGACGGTACCCAAGGAGGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCGCGTAGGCGGATAGTTAAGTCCGGTGTGAAAGATCAGGGCTCAACCCTGAGAGTGCATCGGAAACTGGGTATCTTGAGGACAGGAGAGGAAAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGATATGTGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGACTGTAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCTGTAAACGATGAGTGCTAGGTGTAGAGGGTATCGACCCCTTCTGTGCCGCAGTTAACACAATAAGCACTCCGCCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGACGCAACGCGAAGAACCTTACCAGGGCTTGACATCCTCTGAACTTGCTGGAAACAGGAAGGTGCCCTTCGGGGAGCAGAGAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAATCCCGCAACGAGCGCAACCCCTGTATTTAGTTGCTAACGCGTAGAGGCGAGCACTCTGGATAGACTGCCGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGTTCTGGGCTACACACGTGCTACAATGGCCGGTACAGACGGAAGCGAAGCCGCGAGGCGGAGCAAATCCGAGAAAGCCGGTCTCAGTTCGGATTGCAGGCTGCAACTCGCCTGCATGAAGTCGGAATCGCTAGTAATCGCAGGTCAGCATACTGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAAAGTCTGCAACACCCGAAGCCGGTGAGGTAACCGACTCGAGATTCGAGGCTCGAAGTTCGAGGATCGAAGTGTAAGCGAAATTAATAAGTCTTAGTAAAGCTAAAAAGCATTAAGACCGATAAGATGATCTTGCAATCGAACATCGAACATCGAATTTCGAACCTCGAGTTGGAGCTAGCCGTCGAAGGTGGGGCCGATAATTGGGGTG
>11469739
AGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAAGTCGAACGAGAAGCTAACTTCTGATTCCTTCGGGATGATGAGGTTAGCAGAAAGTGGCGAACGGGTGAGTAACGCGTGGGTAATCTACCCTGTAAGTGGGGGATAACCCTCCGAAAGGAGGGCTAATACCGCATAATATCTTTATCCCAAAAGAGGTAAAGATTAAAGATGGCCTCTATACTATGCTATCGCTTCAGGATGAGTCCGCGTCCTATTAGTTAGTTGGTGGGGTAATGGCCTACCAAGACGACAATGGGTAGCCGGTCTGAGAGGATGTACGGCCACACTGGGACTGAGATACGGCCCAGACTCCTACGGGAGACAGCAGTGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCGACGCCGCGTGGATGATGAAGGCCCTTGGGTTGTAAAATCCTGTTCTGGGGGAAGAAAGCTTAAAGGTCCAATAAACCCTTAAGCCTGACGGTACCCCAAGAGAAAGCTCCGGCTAATTATGTGCCAGCAGCCGCGGTAATACATAAGGAGCAAGCGTTATCCGGAATTATTGGGCGTAAAGAGCTCGTAGGCGGTCTTAAAAGTCAGTTGTGAAATTATCAGGCTCAACCTGATAAGGTCATCTGAAACTCTAAGACTTGAGGTTAGAAGAGGAAAGTGGAATTCCCGGTGTAGCGGTGAAATGCGTAGATATCGGGAGGAACACCAGTGGCGAAGGCGGCTTTCTGGTCTATCTCTGACGCTGAGGAGCGAAAGCTAGGGGAGCAAACGGGATTAGATACCCCGGTAGTCCTAGCTGTAAACGATGGATACTAGGTGTGGGAGGTATCGACCCCTTCTGTGCCGTAGCTAACGCATTAAGTATCCCGCCTGGGGAGTACGGTCGCAAGGCTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGACGCAACGCGAAGAACCTTACCGGGACTTGACATTATCTTGCCCGTCTAAGAAATTAGATCTTCTTCCTTTGGAAGACAGGATAACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCACAACGAGCGCAACCCTTGTGCTTAGTTGCTAACTTGTTTTACAAGTGCACTCTAGGCAGACTGCCGCAGATAATGCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTACGTCCCGGGCTACACACGTGCTACAATGGCCTGTACAGAGGGTAGCGAAAGAGCGATCTTAAGCCAATCCCAAAAAGCAGGCCCCAGTTCGGATTGGAGGCTGCAACTCGCCTCCATGAAGTAGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAAAGTTGGCGATACCTGAAGTTACTAGGCTAACCTGGCACTCAACTAAGTTCACTAACTTATTTGCTTAAAATAAGGCTTAATGTGCTTAGTTGAGTGCCGGGAGGCAGGTACCGAAGGTATGGCTGGCGATTGGGGTGAAGTCGTAACAAGGTGGAAA
>11469752
AGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAATACATGCAAGTCGAGCGGCAGCGAGTTCCTCACCGAGGTTCGGAACAGTTGACAGTAAACAGTTGACAGTAAACAGTAACTTCAGAAATGAAGCGGACTGTGAACTGTTTACTGTAACCTGTTAGCTATTATTTCGAGCTTTAGTGAGGAATGTCGGCGAGCGGCGGACGGCTGAGTAACGCGTAGGAACGTACCCCAAACTGAGGGATAAGCACCAGAAATGGTGTCTAATACCGCATATGGCCCAGCACCTTTTTTAATCAACCACGACCCTAAAATCGTGAATAATTGGTAGGAAAAGGTGTTGGGTTAAAGCTTCGGCGGTTTGGGAACGGCCTGCGTATGATTAGCTTGTTGGTGAGGTAAAAGCTCACCAAGGCGACGATCATTAGCTGGTCTGAGAGGATGATCAGCCAGACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTAGGGAATCTTCCACAATGGGCGAAAGCCTGATGGAGCAACGCCGTGTGCAGGATGAAAGCCTTCGGGTCGTAAACTGCTTTTATATGTGAAGACTTCGACGGTAGCATATGAATAAGGATCGGCTAACTCCGTGCCAGCAGCCGCGGTCATACGGAGGATCCAAGCGTTATCCGGAATTACTGGGCGTAAAGAGTTGCGTAGGTGGCATAGTAAGTTGGTAGTGAAATTGTGTGGCTCAACCATACACCCATTACTAAAACTGCTAAGCTAGAGTATATGAGAGGTAGCTGGAATTCCTAGTGTAGGAGTGAAATCCGTANATATTAGGAGGAACACCGATGGCGTAGGCAGGCTACTGGCATATTACTGACACTAAGGCACGAAAGCGTGGGGAGCGAACGGGATTAGATACCCCGGTAGTCCACGCTGTAAACGATGGATGCTAGCTGTTATGAGTATCGACCCTTGTAGTAGCGAAGCTAACGCGTTAAGCATCCCGCCTGTGGAGTACGAGCGCAAGCTTAAAACATAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCGTGTTGTTTAATTCGATGATAAGCGAAGAACCTTACCAAGGCTTGACATCCCTGGAATTTCTCCGAAAGGAGAGAGTGCCTTCGGGAATCAGGTGACAGGTGATGCATGGCCGTCGTCAGCTCGTGTCGTGAGATGTTTGGTTAAGTCCATTAACGAGCGCAACCCTTGTAAATAGTTGGATTTTTCTATTTAGACTGCCTCGGTAACGGGGAGGAAGGAGGGGATGATGTCAGGTCAGTATTTCTCTTACGCCTTGGGCTACAAACACGCTACAATGGCCGGTACAAAGGGCAGCCAACCCGCGAGGGGGAGCAAATCCCATCAAAGCCGGTCTCAGTTCGGATAGCAGGCTGAAATTCGCCTGCTTGAAGTCGGAATCGCTAGTAACGGTGAGTCAGCTATATTACCGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCAAGGCATGAAAGTCATCAATACCTGACGTCTGGATTTATTCTGGCCTAAGGTAGGGGCGATGATTGGGCCTAAGTCGTAACAAGGTAA
>11460523
AGAGTTTGATCCTGGCTCAGAACGAACGCTGGCGGCGTGCTTAACACATGCAAGTCGAACGCGAAATCGGGCACTCAATTTTGCTTTTCAAACATTAACTGATGAAACGACCAGAGAGATTGTTCCAGTTTAAAGAGTGAAAAGCAGGCTTGAGTGCCTGAGAGTAGAGTGGCGCACGGGTGAGTAACGCGTAAATAATCTACCCCTGCATCTGGGATAACCCACCGAAAGGTGAGCTAATACCGGATACGTTCTTTTAACCGCGAGGTTTTAAGAAGAAAGGTGGCCTCTGATATAAGCTACTGTGCGGGGAGGAGTTTGCGTACCATTAGCTAGTTGGTAGGGTAATGGCCTACCAAGGCATCGATGGTTAGCGGGTCTGAGAGGATGATCCGCCACACTGGAACTGGAACACGGACCAGACTCCTACGGGAGGCAGCAGTGAGGAATATTGCGCAATGGGGGCAACCCTGACGCAGCGACGCCGCGTGGATGATGAAGGCCTTCGGGTCGTAAAATCCTGTCAGATGGAAAGAAGTGTTATATGGATAATACCTGTATAGCTTGACGGTACCATCAAAGGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTGTTCGGAATTACTGGGCGTAAAGCGCGCGTAGGCGGTCTGTTATGTCAGATGTGAAAGTCCACGGCTCAACCGTGGAAGTGCATTTGAAACTGACAGACTTGAGTACTGGAGGGGGTGGTGGAATTCCCGGTGTAGAGGTGAAATTCGTAGATATCGGGAGGAATACCGGTGGCGAAGGCGACCACCTGGCCAGATACTGACGCTGAGGTGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGTCAACTAGGTGTTGGGATGGTTAATCGTCTCATTGCCGGAGCTAACGCATTAAGTTGACCGCCTGGGGAGTACGGTCGCAAGATTAAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGTATGTGGTTTAATTCGACGCAACGCGCAGAACCTTACCTGGTCTTGACATCCCGAGAATCTCAAGGAAACTTGAGAGTGCCTCTTGAGGAACTCGGTGACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGTCTTTAGTTGCCATCATTAAGTTGGGCACTCTAAAGAGACTGCCGGTGTCAAACCGGAGGAAGGTGGGGATGACGTCAAGTCCTCATGGCCTTTATGACCAGGGCTACACACGTACTACAATGGCATAGACAAAGGGCAGCGACATCGCGAGGTGAAGCGAATCCCATAAACCATGTCTCAGTCCGGATTGGAGTCTGCAACTCGACTCCATGAAGTTGGAATCGCTAGTAATCGTAGATCAGCATGCTACGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGGGAGTTGGTTGTACCAGAAGCAGTTGAGCGAACTATTCGTAGACGCAGGCTGCCAAGGTATGATTGGTAACTGGGGTGAAGTCGTAACAAGGTAACC
>11460543
TGGTTTGATCCTGGCTCAGGACAAACGCTGGCGGCGTGCCTAACACATGCAAGTCGAACGAGAAGCCAGCTTTTGATTCCTTCGGGATGAGAAAGCAGGTAGAAAGTGGCGAACGGGTGAGTAACGCGTGGGTAATCTACCCTGTAAGTAGGGGATAACCCTCTGAAAAGAGGGCTAATACCGCATAATATCTTTACCCCATAAGAAGTAAAGATTAAAGATGGCCTCTGTATATGCTATCGCTTCAGGATGAGCCCGCGTCCTATTAGTTAGTTGGTAAGGTAATGGCTTACCAAGACCACGATGGGTAGCCGGTCTGAGAGGATGTACGGCCACACTGGGACTGAGATACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCGCAATGGGGGAAACCCTGACGCAGCGACGCCGCGTGGATGATGAAGGCCTTCGGGTTGTAAAATCCTGTTTTGGGGGACGAAACCTTAAGGGTCCAATAAACCCTTAAATTGACGGTACCCCAAGAGAAAGCTCCGGCTAATTATGTGCCAGCAGCCGCGGTAATACATAAGGAGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGAGTTCGTAGGCGGTCTTAAAAGTCAGGTGTGAAATTATCAGGCTTAACCTGATACGGTCATCTGAAACTTTAAGACTTGAGGTTAGGAGAGGAAAGTGGAATTCCCGGTGTAGCGGTGAAATGCGTAGATATCGGGAGGAACACCAGTGGCGAAGGCGGCTTTCTGGCCTAACTCTGACGCTGAGGAACGAAAGCTAGGGGAGCAAACGGGATTAGATACCCCGGTAGTCCTAGCTGTAAACGATGGATACTAGGTGTGGGAGGTATCGACCCCTTCTGTGCCGWCACTAACGCATTAAGTATCCCGCCTGGGGAGTACGGTCGCAAGGCTAAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGACGCAACGCGAAGAACCTTACCGGGGCTTGACATTGTCTTGCCCGTTTAAGAAATTAAATTTTCTTCCCTTTTAGGGAAGACAAGATAACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCACAACGAGCGCAACCCTTATTCTTAGTTGCTAGTTTGTTTACAAACGCACTCTAAAGAGACTGCCGCAGATAATGCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTACGTCCCGGGCTACACACGTGCTACAATGGCCTGTACAGAGGGTAGCGAAAGAGCGATCTCAAGCTAATCCCTTAAAACAGGTCTCAGTTCGGATTGGAGGCTGCAACTCGCCTCCATGAAGTCGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGAAAGTTGGCGATACCTGAAGTTACTGTGCTAACCCGGCACTCAACTAAGTACATTAAGTCTTATTTTAAGCTATTGTATTTAGTTGAGTGCCGGGAGGCAGGTACCTAAGGTATGGCTAGCGATTGGGGTGAAGTCGTAACAAGGTAGCCG
>11480235
TGGTTTGATCCTGGCTCAGGATTAACGCTGGCGGCGCGCCTTATACATGCAAGTCGAACGAGCCTTGTGCTTCGCACAAGGAAATTCCAAGCACCAAGCACCAAATCTCAAACAAATCCCAATGACCAAAATTCCAAAAACCTAAACATTTTAAATGTTTAGAATTTGGAAAATTGGAATTTGGAATTTATTTGTTATTTGGAATTTATGATTTGGGATTTTCTCGCGCGGAGANCNTNAGTGGCGAACGGGTGAGTAATACGTTGGTATCTACCCCAAAGTAGAGAATAAGCCCGAGAAATCGGGGTTAATACTCTATGTGTTCGAAAGAACAAAGACTTCGGTTGCTTTGGGAAGAACCTGCGGCCTATCAGCTTGTTGGTAAGGTAACGGCTTACCAAGGCTTTGACGGGTAGCTGGTCTGGGAAGACGACCAGCCACAATGGGACTTAGACACGGCCCATACTCCTACGGGAGGCAGCAGTAGGGAATCTTCGGCAATGCCCGAAAGGTGACCGAGCGACGCCGCGTAGAGGAAGAAGATCTTTGGATTGTAAACTCTTTTTCTCCTAGACAAAGTTCTGATTGTATAGGAGGAATAAGGGGTTTCTAAACTCGTGCCAGCAGAAGCGGTAATACGAGTGCCCCAAGCGTTATCCGGAATCATTGGGCGTAGAGCGTTGTATAGGTGGTTTAAAAAGTCCAAAATTAAATCTTTAGGCTCAACCTAAAATCTGTTTTGGAAACTTTTAGACTTGAATAAAATCGACGSGAGTGGAACTTCCAGAGTAGGGGTTACATCCGTTGATACTGGAAGGAACGCCGAAGGCGAAAGCAACTCGCGAGATTTTATTGACGCCGCGTACACGAAAGCGTGGGGAGCGAAAAGTATTAGATACACTTGTAGTCCACGCCGTAAACTATGGATACTAGCAATTTGAAGCTTCGACCCTTCAAGTTGCGGACTAACGCGTTAAGTATCTCGCCTGGGAAGTACGGCCGCAAGGCTAAAACTCAAAGGAATAGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGACGATAAGCGTGGAACCTTACCAGGGCTTAGACGTACAGAGAATTCCTTGGAAACAAGGAAGTGCTTCGGGAACTCTGTACTCAGGTACTGCATGGCTGTCGTCAGTATGTACTGTGAAGCACTCCCTTAATTGGGGCAACATACGCAACCCCTATCCTAAGTTAGAAATGTCTTAGGAAACCGCTTCGATTCATCGGAGAGGAAGATGGGGACGACGTCAAGTCAGCATGGTCCTTGATGTCCTGGGCGACACACGTGCTACAATGGCTAGTATAACGGGATGCGTAGGTGCGAACCGAAGCTAATCCTTAAAAAACTAGTCTAAGTTCGGATTGAAGTCTGCAACTCGACTTCATGAAGCCGGAATCGCTAGTAACCGCAAATCAGCCACGTTGCGGTGAATACGTTCTCGGGCCTTGTACTCACTGCCCGTCACGTCAAAAAAGTCGGTAATACCCGAAGCACCCTTTTAAAGGGTTCTAAGGTAGGACCGATGATTGGGACGAAGTCGTAACAAGGTAGCCG
>11480408
AATTTAGCGGCCGCGAATTCGCCCTTGAGTTTGATCCTGGCTCAGGACGAACGCTGGCGGCGTGCTTAACACATGCAAGTCGAACGGGGATATCCGAGCGGAAGGTTTCGGCCGGAAGGTTGGGTATTCGAGTGGCGGACGGGTGAGTAACGCGTGAGCAATCTGTCCCGGACAGGGGGATAACACTTGGAAACAGGTGCTAATACCGCATAAGACCACAGCATCGCATGGTGCAGGGGTAAAAGGAGCGATCCGGTCTGGGGTGAGCTCGCGTCCGATTAGATAGTTGGTGAGGTAACGGCCCACCAAGTCAACGATCGGTAGCCGACCTGAGAGGGTGATCGGCCACATTGGAACTGAGAGACGGTCCAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGGGCAATGGGCGAAAGCCTGACCCAGCAACGCCGCGTGAGTGAAGAAGGCCTTCGGGTTGTAAAGCTCTGTTATGCGAGACGAAGGAAGTGACGGTATCGCATAAGGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGGGCGAGCGTTGTCCGGAATGACTGGGCGTAAAGGGCGTGTAGGCGGCCGTTTAAGTATGGAGTGAAAGTCCATTTTTCAAGGATGGAATTGCTTTGTAGACTGGATGGCTTGAGTGCGGAAGAGGTAAGTGGAATTCCCAGTGTAGCGGTGAAATGCGTAGAGATTGGGAGGAACACCAGTGGCGAAGGCGACTTACTGGGCCGTAACTGACGCTGAGGCGCGAAAGCGTGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCACGCGGTAAACGATGAATGCTAGGTGTTGCGGGTATCGACCCCTGCAGTGCCGGAGTAAACACAATAAGCATTCCGCCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAGGGAATTGACGGGGGCCCGCACAAGCAGCGGAGCATGTTGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTCTTGACATCCAGTTAAGCTCATAGAGATATGAGGTCCCTTCGGGGGAACTGAGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTATGGTCAGTTACTAACGCGTGAAGGCGAGGACTCTGACGAGACTGCCGGGGACAACTCGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACAAACGTGCTACAATGGTGACTACAAAGAGGAGCGAGACTGTAAAGTGGAGCGGATCTCAAAAAAGTCATCCCAGTTCGGATTGTGGGCTGCAACCCGCCCACATGAAGTTGGAGTTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTTGGGAGCACCCGAAGTCAGTGAGGTAACCGGAAGGAGCCAGCTGCCGAAGGTGAGACCGATGACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTAAGGGCGAATTCGTTTAAACCTGCAGGACTAG
"""
test_seq = """>s1 (11472384)
AGAGTTTGATCCTGGCTCAGATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGCAGCACGGGGGCAACCCTGGTGGCGAGTGGCGAACGGGTGAGTAATACATCGGAACGTGTCCTGTAGTGGGGGATAGCCCGGCGAAAGCCGGATTAATACCGCATACGCTCTACGGAGGAAAGGGGGGGATCTTAGGACCTCCCGCTACAGGGGCGGCCGATGGCAGATTAGCTAGTTGGTGGGGTAAAGGCCTACCAAGGCGACGATCTGTAGCTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGACAATGGGGGCAACCCTGATCCAGCAATGCCGCGTGTGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTTGTCCGGAAAGAAAACGCCGTGGTTAATACCCGTGGCGGATGACGGTACCGGAAGAATAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGTGCGCAGGCGGTCCGCTAAGACAGATGTGAAATCCCCGGGCTTAACCTGGGAACTGCATTTGTGACTGGCGGGCTAGAGTATGGCAGAGGGGGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGGAATACCGATGGCGAAGGCAGCCCCCTGGGCCAATACTGACGCTCATGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCCTAAACGATGTCAACTAGTTGTCGGGTCTTCATTGACTTGGTAACGTAGCTAACGCGTGAAGTTGACCGCCTGGGGAGTACGGTCGCAAGATTAAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGATGATGTGGATTAATTCGATGCAACGCGAAAAACCTTACCTACCCTTGACATGTATGGAATCCTGCTGAGAGGTGGGAGTGCCCGAAAGGGAGCCATAACACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGTCCCTAGTTGCTACGCAAGAGCACTCTAGGGAGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAGTCCTCATGGCCCTTATGGGTAGGGCTTCACACGTCATACAATGGTCGGAACAGAGGGTCGCCAACCCGCGAGGGGGAGCCAATCCCAGAAAACCGATCGTAGTCCGGATCGCACTCTGCAACTCGAGTGCGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTTTACCAGAAGTGGCTAGTCTAACCGCAAGGAGGACGGTCACCACGGTAGGATTCATGACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTTCTCGAGCGAACGTGTCGAACGTTGAGCGCTCACGCTTATCGGCTGTGAAATTAGGACAGTAAGTCAGACAGACTGAGGGGTCTGTAGCTCAGTCGGTTAGAGCACCGTCTTGATAAGGCGGGGGTCGATGGTTCGAATCCATCCAGACCCACCATTGTCT
"""
in_aln1 = """>a1
AAACCTTT----TTTTAAATTCCGAAGAGTTTGATCCTGGCTCAGATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGCAGCACGGGGGCAACCCTGGTGGCGAGTGGCGAACGGGTGAGTAATACATCGGAACGTGTCCTGTAGTGGGGGATAGCCCGGCGAAAGCCGGATTAATACCGCATACGCTCTACGGAGGAAAGGGGGGGATCTTAGGACCTCCCGCTACAGGGGCGGCCGATGGCAGATTAGCTAGTTGGTGGGGTAAAGGCCTACCAAGGCGACGATCTGTAGCTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGACAATGGGGGCAACCCTGATCCAGCAATGCCGCGTGTGTGAAGAAGGCCTTC
>a2
AAACCTTT----TTTTAAATTCCGCAGAGTTTGATCCTGGCTCAGATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGCAGCACGGGGGCAACCCTGGTGGCGAGTGGCGAACGGGTGAGTAATACATCGGAACGTGTCCTGTAGTGGGGGATAGCCCGGCGAAAGCCGGATTAATACCGCATACGCTCTACGGAGGAAAGGGGGGGATCTTAGGACCTCCCGCTACAGGGGCGGCCGATGGCAGATTAGCTAGTTGGTGGGGTAAAGGCCTACCAAGGCGACGATCTGTAGCTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGACAATGGGGGCAACCCTGATCCAGCAATGCCGCGTGTGTGAAGAAGGCCTTC
>a3
AAACCTTT----TTTTAAATTCCGGAGAGTTTGATCCTGGCTCAGATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGCAGCACGGGGGCAACCCTGGTGGCGAGTGGCGAACGGGTGAGTAATACATCGGAACGTGTCCTGTAGTGGGGGATAGCCCGGCGAAAGCCGGATTAATACCGCATACGCTCTACGGAGGAAAGGGGGGGATCTTAGGACCTCCCGCTACAGGGGCGGCCGATGGCAGATTAGCTAGTTGGTGGGGTAAAGGCCTACCAAGGCGACGATCTGTAGCTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGACAATGGGGGCAACCCTGATCCAGCAATGCCGCGTGTGTGAAGAAGGCCTTC
>a4
AAACCTTT----TTTTAAATTCCGTAGAGTTTGATCCTGGCTCAGATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGCAGCACGGGGGCAACCCTGGTGGCGAGTGGCGAACGGGTGAGTAATACATCGGAACGTGTCCTGTAGTGGGGGATAGCCCGGCGAAAGCCGGATTAATACCGCATACGCTCTACGGAGGAAAGGGGGGGATCTTAGGACCTCCCGCTACAGGGGCGGCCGATGGCAGATTAGCTAGTTGGTGGGGTAAAGGCCTACCAAGGCGACGATCTGTAGCTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGACAATGGGGGCAACCCTGATCCAGCAATGCCGCGTGTGTGAAGAAGGCCTTC
"""
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_app/test_gctmpca.py 000755 000765 000024 00000772543 12024702176 022276 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# Author: Greg Caporaso (gregcaporaso@gmail.com)
# test_gctmpca.py
""" Tests of the Generalized Continuous-Time Markov Process Coevolutionary
Algorithm (GCTMPCA) application controller.
"""
from __future__ import division
from os import environ
from cogent.util.unit_test import TestCase, main
from cogent.app.util import ApplicationError
from cogent.util.misc import app_path
from cogent.app.gctmpca import Gctmpca, gctmpca_aa_order, \
default_gctmpca_aa_priors, gctmpca_base_order
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Greg Caporaso"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Greg Caporaso"
__email__ = "gregcaporaso@gmail.com"
__status__ = "Beta"
class GctmpcaTests(TestCase):
""" Tests of the Gctmpca coevolution detection app controller """
def setUp(self):
""" """
self.run_slow_tests = int(environ.get('TEST_SLOW_APPC',0))
self.sample_seqs = sample_seqs.split('\n')
self.sample_tree = sample_tree.split('\n')
self.sample_species_names = sample_species_names.split('\n')
self.sample_priors = sample_priors
self.sample_sub_matrix = sample_sub_matrix
self.sample_seq_to_species = sample_seq_to_species.split('\n')
self.sample_data = {'mol_type':'rna','seqs1':self.sample_seqs,\
'tree1':self.sample_tree,'seq_names':self.sample_species_names,\
'species_tree':self.sample_tree,\
'seq_to_species1':self.sample_seq_to_species,\
'char_priors':self.sample_priors,'sub_matrix':self.sample_sub_matrix,
'single_pair_only':1,'pos1':1265,'pos2':1270,'epsilon':0.1}
self.trivial_seqs = trivial_seqs.split('\n')
self.trivial_tree = trivial_tree.split('\n')
self.trivial_species_names = trivial_species_names.split('\n')
self.trivial_seq_to_species = trivial_seq_to_species.split('\n')
#self.trivial_priors = trivial_priors.split('\n')
#self.trivial_sub_matrix = trivial_sub_matrix.split('\n')
self.trivial_data = {'mol_type':'protein','seqs1':self.trivial_seqs,\
'tree1':self.trivial_tree,'seq_names':self.trivial_species_names,\
'species_tree':self.trivial_tree,\
'seq_to_species1':self.trivial_seq_to_species,\
'single_pair_only':0,'epsilon':'0.7'}
self.myog_seqs = myog_seqs.split('\n')
self.myog_tree = myog_tree.split('\n')
self.myog_species_names = myog_species_names.split('\n')
self.myog_seq_to_species = myog_seq_to_species.split('\n')
#self.myog_priors = myog_priors.split('\n')
#self.myog_sub_matrix = myog_sub_matrix.split('\n')
self.myog_data = {'mol_type':'protein','seqs1':self.myog_seqs,\
'tree1':self.myog_tree,'seq_names':self.myog_species_names,\
'species_tree':self.myog_tree,\
'seq_to_species1':self.myog_seq_to_species,\
'single_pair_only':0,'epsilon':'0.1'}
self.app = Gctmpca()
def test_calculate_likelihood_in_path(self):
"""Gctmpca: calculate_likelihood binary in path """
assert app_path('calculate_likelihood'),\
"calculate_likelihood is not in your path -- other tests will fail!"
def test_trivial_data(self):
"""Gctmpca: full computation works with trivial example """
if not self.run_slow_tests: return
expected = ['position 1\tposition 2\tscore\n','2\t3\t3.705879\n']
#app = Gctmpca(HALT_EXEC=True)
#app(self.trivial_data)
#exit(-1)
actual = list(self.app(self.trivial_data)['output'])
self.assertEqual(actual,expected)
def test_trivial_data_pairwise(self):
"""Gctmpca: pairwise computation works with trivial example """
if not self.run_slow_tests: return
expected = ['position 1\tposition 2\tscore\n']
self.trivial_data['single_pair_only'] = 1
self.trivial_data['pos1'] = 1
self.trivial_data['pos2'] = 2
actual = list(self.app(self.trivial_data)['output'])
self.assertEqual(actual,expected)
def test_myog_data_pairwise(self):
"""Gctmpca: pairwise computation works with myog example """
if not self.run_slow_tests: return
expected = ['position 1\tposition 2\tscore\n','44\t108\t0.364928\n']
self.myog_data['single_pair_only'] = 1
self.myog_data['pos1'] = 44
self.myog_data['pos2'] = 108
actual = list(self.app(self.myog_data)['output'])
self.assertEqual(actual,expected)
def test_rna_sample_data(self):
"""Gctmpca: works with provided sample data """
expected = ['position 1\tposition 2\tscore\n',\
'1265\t1270\t33.862890\n']
actual = list(self.app(self.sample_data)['output'])
self.assertEqual(actual,expected)
def test_amino_acid_defaults(self):
"""Gctmpca: cogent defaults match those presented by Yeang et al.
"""
expected_aa_order = 'ARNDCQEGHILKMFPSTWYV'
self.assertEqual(gctmpca_aa_order,expected_aa_order)
gctmpca_priors_string = \
"0.087127\t0.040904\t0.040432\t0.046872\t0.033474\t0.038255\t" +\
"0.049530\t0.088612\t0.033618\t0.036886\t0.085357\t0.080482\t" +\
"0.014753\t0.039772\t0.050680\t0.069577\t0.058542\t0.010494\t" +\
"0.029916\t0.064718\n"
gctmpca_priors = dict(zip(gctmpca_aa_order,\
map(float,gctmpca_priors_string.strip().split('\t'))))
cogent_priors = default_gctmpca_aa_priors
self.assertFloatEqual(cogent_priors,gctmpca_priors)
def test_default_sub_matrix_and_priors_used(self):
"""Gctmpca: works with provided sample data mixed w/ defaults"""
# Works with default priors and sub matrix
expected = ['position 1\tposition 2\tscore\n',\
'1265\t1270\t33.862890\n']
del self.sample_data['char_priors']
del self.sample_data['sub_matrix']
actual = list(self.app(self.sample_data)['output'])
self.assertEqual(actual,expected)
def test_gctmpca_cl_input_result_sanity(self):
"""Gctmpca: correct number of parameters on command line"""
actual = self.app._gctmpca_cl_input(self.sample_data)
self.assertTrue(actual.startswith('0 0 "/tmp/tmp'))
# Many of the intermediate paramters are randomly generated
# file names.
self.assertTrue(actual.endswith('.txt" 1 - 1265 1270'))
parameter_count = len(actual.split())
self.assertEqual(parameter_count,22)
def test_gctmpca_cl_input_result_sanity_w_some_default(self):
"""Gctmpca: correct number of parameters on command line w some defaults
"""
# remove some parameters and make sure the result changes
del self.sample_data['single_pair_only']
del self.sample_data['pos1']
del self.sample_data['pos2']
actual = self.app._gctmpca_cl_input(self.sample_data)
self.assertTrue(actual.startswith('0 0 "/tmp/tmp'))
# Many of the intermediate paramters are randomly generated
# file names.
self.assertTrue(actual.endswith('.txt" 0 -'))
parameter_count = len(actual.split())
self.assertEqual(parameter_count,20)
def test_input_as_gctmpca_char_priors(self):
"""Gctmpca: priors input handler works as expected """
priors = {'A':0.50,'C':0.25,'G':0.15,'U':0.10}
expected = ['0.5\t0.25\t0.15\t0.1','']
actual = self.app._input_as_gctmpca_char_priors(priors,'ACGU')
self.assertEqual(actual,expected)
expected = ['0.1\t0.15\t0.25\t0.5','']
actual = self.app._input_as_gctmpca_char_priors(priors,'UGCA')
self.assertEqual(actual,expected)
def test_input_as_gctmpca_rate_matrix(self):
"""Gctmpca: rate matrix input handler works as expected """
m = {'A':{'A':-13.4,'C':3.2,'D':2.2},\
'C':{'A':3.4,'C':-3.2,'D':22.2},\
'D':{'A':0.4,'C':0.0,'D':-1.}}
expected = ['-13.4\t3.2\t2.2','3.4\t-3.2\t22.2','0.4\t0.0\t-1.0']
actual = self.app._input_as_gctmpca_rate_matrix(m,'ACD')
self.assertEqual(actual,expected)
expected = ['-1.0\t0.4\t0.0','2.2\t-13.4\t3.2','22.2\t3.4\t-3.2']
actual = self.app._input_as_gctmpca_rate_matrix(m,'DAC')
self.assertEqual(actual,expected)
def test_unsupported_function_raises_error(self):
"""Gctmpca: attempting an intermolecular experiment causes error """
self.sample_data['comparison_type'] = 1
self.assertRaises(NotImplementedError,self.app,self.sample_data)
def test_gctmpca_cl_input_error(self):
"""Gctmpca: missing required data causes ApplicationError """
# missing all
self.assertRaises(ApplicationError,self.app,{})
# missing one
# mol_type
data = {'seqs1':self.sample_seqs,\
'tree1':self.sample_tree,'seq_names':self.sample_species_names,\
'species_tree':self.sample_tree,\
'seq_to_species1':self.sample_seq_to_species}
self.assertRaises(ApplicationError,self.app,data)
# seqs1
data = {'mol_type':'rna',\
'tree1':self.sample_tree,'seq_names':self.sample_species_names,\
'species_tree':self.sample_tree,\
'seq_to_species1':self.sample_seq_to_species}
self.assertRaises(ApplicationError,self.app,data)
# tree1
data = {'mol_type':'rna','seqs1':self.sample_seqs,\
'seq_names':self.sample_species_names,\
'species_tree':self.sample_tree,\
'seq_to_species1':self.sample_seq_to_species}
self.assertRaises(ApplicationError,self.app,data)
# 'seq_names'
data = {'mol_type':'rna','seqs1':self.sample_seqs,\
'tree1':self.sample_tree,\
'species_tree':self.sample_tree,\
'seq_to_species1':self.sample_seq_to_species}
self.assertRaises(ApplicationError,self.app,data)
# species_tree
data = {'mol_type':'rna','seqs1':self.sample_seqs,\
'tree1':self.sample_tree,'seq_names':self.sample_species_names,\
'seq_to_species1':self.sample_seq_to_species}
self.assertRaises(ApplicationError,self.app,data)
# seq_to_species1
data = {'mol_type':'rna','seqs1':self.sample_seqs,\
'tree1':self.sample_tree,'seq_names':self.sample_species_names,\
'species_tree':self.sample_tree}
self.assertRaises(ApplicationError,self.app,data)
# pos1 if single_pair_only == 1
data = {'mol_type':'rna','seqs1':self.sample_seqs,\
'tree1':self.sample_tree,'seq_names':self.sample_species_names,\
'species_tree':self.sample_tree,\
'seq_to_species1':self.sample_seq_to_species,\
'single_pair_only':1,'pos2':5}
self.assertRaises(ApplicationError,self.app,data)
# pos2 if single_pair_only == 2
data = {'mol_type':'rna','seqs1':self.sample_seqs,\
'tree1':self.sample_tree,'seq_names':self.sample_species_names,\
'species_tree':self.sample_tree,\
'seq_to_species1':self.sample_seq_to_species,\
'single_pair_only':1,'pos1':5}
self.assertRaises(ApplicationError,self.app,data)
# pos1 & pos2 if single_pair_only == 2
data = {'mol_type':'rna','seqs1':self.sample_seqs,\
'tree1':self.sample_tree,'seq_names':self.sample_species_names,\
'species_tree':self.sample_tree,\
'seq_to_species1':self.sample_seq_to_species,\
'single_pair_only':1}
self.assertRaises(ApplicationError,self.app,data)
sample_seqs = """146 1542
cy.Mic.aer CCGAGCUCGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGCGUGCCUAACACAUGCAAGUCGAACGGGAAUC--------UUCG-------GAUU-CUAGUGGCGGACGGGUGAGUAACGCGUAAGAAUCUAACUUCAGGACGGGGACAACAGUUGGAAACGACUGCUAAUACCCGAUG-UGCCGCAGGGUGAAACC--------UAAU------UGGCCUGGAGAAGAGCUUGCGUCUGAUUAGCUAGUUGGUGGGGUAAGGGCCUACCAAGGCGACGAUCAGUAGCUGGUCUGAG-GGAUGAGCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGCCUGACGGAGCAACGCCGCGUGAGGGAGGAAGGUCUUUGGAUUGUAAACCUCUUUUCUCAAGGAAGAAG----------UUCU-------------AACGGUUCUUGAGGAAUCAGCCUCGGCUAACUCCGUGCCAGCAGCCCCGGUAAUACGGGGGAGGCAAGCGUUAUCCGGAAUUAUUGGGCGUAAAGCGUCCGCAGGUGGUCAGCCAAGUCUGCCGUCAAAUCAGGUUGCUUAACGACCUAAAGGCGGUGGAAACUGGCAGACUAGAGAGCAGUAGGGGUAGCAGGAAUUCCCAGUGUAGCAGUGAAAUGCGUAGAGAUUGGGAAGAACAUCGGUGGCGAAAGCGUGCUACUGGGCUGUCUCUGACACUCAGGGACGAAAGCUUGGGGAGCGAACGGGAUUAGAUACCCCUGUAGUCCUAGCCGUAAACGAUGGAUACUAGGUGUGGGUUGUAUCGCCCGAGGCGGGCCAAAGAUAACGCGUUAUGUAUCCCCCCUGGAGAGUACGCACGCAAGUUUGAAUCUCAAAGGUAUUGACGGGGGCCCGCACAAGCGGUGGAGUAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCAAG-AUUGACAUGUCGCGAACCCUGGUGAAAGCUGGGGGUGCCUUCGGGAGCGCCAACACAGAUGGUGUAUAGCUGUCGCCAGCUCGUGUCGUGAGAUGUUGGGUUAUGUCCCGCAAAGAGCGCACCCCUCGUUCUUAGUUGCCAGCAUUAAG-UGGACGACUCUAAGGAGACUGCCGGUGACAAACCGGAGGAAGGUGGUGAUGACGUCAAGUCAGCAUGCCCCUUACGUCUUGGGCGACACACGUACUACAGUCGUCGGAACAAAAGGCAGUCAACUCGCGAGAGCCAGCGUAUCCCGCAAACCCGGCCUCAGUUCAGAUUGCAGGCUGCAACUCGCCUGCAUGAAGGAGGAAUCGCUAGUAAUCGCCGGUCAGCAUACGGCGGUGAAUUCGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGAAGCUGGUCACGCCCGAAGUCAUUACCUCAACCGCAAGAGGGGGGAUGCCUAAGGCAGGGCUAGUGACUGGGGUmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
cy.Osc.aga -----mmmmmmmmmmmmmmmmmmmmmmGAUGAACGCUGGCGGUCUGCUUAACACAUGCAAGUCGAACGGAAUCC--------UUCG--------GGAUUUAGUGGCGGACGGGUGAGUAACACGUAAGAACCUGCCUCUAGGACGGGGACAACAGUUGGAAACGACUGCUAAACCCGGAUG-AGCCGAAAGGUAAAAGA--------UUAA------UCGCCUAGAGAGGGGCUUGCGUCUGAUUAGCUAGUUGGUGAGGUAAGAGCCCACCAAGGCGACGAUCAGUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGC-UGACGGAGCAAGACCGCGUGGGGGAGGAAGGUUCUUGGAUUGUCAACCCCUUUUCUCAGGGAAGAACA---------CAAU-------------GACGGUACCUGAGGAAAAAGCAUCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGGGGAUGCAAGCGUUAUCCGGAAUGAUUGGGCGUAAAGAGUCCGUAGGUAGUCAUCCAAGUCUGCUGUUAAAGAGCGAGGCUUAACCUCGUAAAGGCAGUGGAAACUGGAAGACUAGAGUGUAGUAGGGGCAGAGGGAAUUCCUGGUGUAGCGGUGAAAUGCGUAGAGAUCAGGAAGAACACCGGUGGCGAAGGCGCUCUGCUGGGCUAUAACUGACACUGAGGGACGAAAGCUAGGGGAGCGAAUGGGAUUAGAUACCCCAGUAGUCCUAGCGGUAAACGAUGGAAACUAGGUGUGGCCUGUAUCGCCCGGGCCGUGCCGAAGCAAACGCGUUAAGUUUCCCGCCUGGGGAGUACGCACGCAAGUGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGUAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCAGGACUUGACAUCUCUGGAAUCUCCUUGAAAGGGGAGAGUGCCGUAAGGAACCAGAAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUCGUUAGUUGCCAUCAUUAAG-UUGGGAACUCUAGCGAGACUGCCGGUGACAAACCGGAGGAAGGUGAGGAUGACGUCAAGUCAGCAUGGCCCUUACGUCCUGGGCGACACACGUACUACAAUGCGAGGGACAGAGAGCAGCCAACCCGCGAGGGAGAGCGAAUCUCAUAAACCCUGGCACAGUUCAGAUUGCAGGCUGCAACUCGCCUGCAUGAAGGAGGAAUCGCUAGUAAUCGGAGGUCAGCAUACUGCGGUGAAUCCGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGAAGUGAGCCACGCCCGAAGUCAUUACUCUAACCGAAAGGAGGAGGGUGCCGAAGGCGGGGUUGAUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUACCGGAAGGUGUGGCUGGAUCACCUCCUUU
cy.Pho.amb -----mmmmmmmmmmmmmmmmmmmmmmGAUGAACGCUGGCGGUCUGCUUAACACAUGCAAGUCGAACGAACUC---------UUCG---------GAGUUAGUGGCGGACGGGUGAGUAACGCGUGAGAGUCUAGCUUCAGAACGGGGACAACAGAGGGAAACCACUGCUAAUACCCGAUG-UGCCGAGAGGUGAAAGA--------UUUA------UCAUCUGAAGAUGAGCUCGCGUCCGAUUAGCUAGUUGGUAAGGUAAGAGCUUACCAAGGCGACGAUCGGUAGCUGGUCUGAGAGGAUGACCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGC-UGACGGAGCAAGACCGCGUGAGGGAGGAAGGCUCUUGGGUUGUAAACCUCUUUUCUCUGGGAAGAAG----------AUCU-------------GACGGUACCAGAGGAAUCAGCAUCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGAUGCAAGCGUUAUCCGGAAUUAUUGGGCGUAAAGCGUCCGUAGGUGGCGGUUCAAGUCUGCCGUUAAAACCAGUAGCUUAACUACUGACAGGCGGUGGAAACUGAACAGCUAGAGUGUGGUAGGGGUAGAGGGAAUUCCCAGUGUAGCGGUGAAAUGCGUAGAGAUUGGGAAGAACACCGGUGGCGAAAGCGCUCUGCUGGACCACAACUGACACUCACGGACGAAAGCUAGGGGAGCGAAAGGGAUUAGAUACCCCAGUAGUCCUAGCCGUAAACGAUGGAUACUAGGUGUAGUAGGUAUCGCCCCUACUGUGCCGUAGCUAACGCGUUAAGUAUCCCGCCUGGGGAGUACGGUCGCAAGAUUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGUAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCAGGACUUGACAUGUCGCGAAUCUCUCUGAAAGGAGAGAGUGCCUUCGGGAGCGCGAACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCACGUUUUUAGUUGCCAUCAUUAAG-UUGGGCACUCUAGAGAGACUGCCGGUGACAAACCGGAGGAAGGUGUGGAUGACGUCAAGUCAGCAUGCCCCUUACGUCCUGGGCUACACACGUACUACAAUGGCUGGGACAAAGAGCUGCAAGCGAGCGAUCGCAAGCCAAUCUCAUAAACCCAGUCUUAGUUCAGAUCGCAGGCUGCAACUCGCCUGCGUGAAGGCGGAAUCGCUAGUAAUCGCAGAUCAGAAUGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGAAGCUGGUCACGCCCGAAGUCGUUAUCCUAACCUUCGGGAGGGAGAUGCCUAAGGCAGGGCUGGUGACUGGGGUGAAGUCGUAACAAGGUAGC-GUACCGGAAGGmmmmmmmmmmmmmmmm-----
cy.Tri.ten -----mmmmmmmmmmmmmmmmmmmmmmmAUGAACGCUGGCGGUCUGCUUAACACAUGCAAGUCGAACGGACUC---------UUCG---------GAGUUAGUGGCGGACGGGUGAGUAACGCGUGAGAAUCUGCCUUCAGGUCUGGGACAACAGAAGGAAACUUCCGCUAAUCCCGGAUG-AGCCUUAGGGUAAAAGA--------UAAA------UUGCCUGGAGAUGAGCUUGCGUCUGAUUAGCUAGUUGGUGUGGUAAAAGCAUACCAAGGCAACGAUCAGUAGCUGGUCUGAGAGGAUGAGCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGCAAGCCUGACGGAGCAAGACCGCGUGGGGGAGGAAGGCUCUAGGGUUGUAAACCCCUUUUCUUUGGGAAGAAG----------AAAU-------------GACGGUACCAAAGGAAUCAGCCUCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGAGGCAAGCGUUAUCCCGAAUGAUUGGGCGUAAAGCGUCCGCAGGUGGCCAUGUAAGUCUGCUGUUAAAACCCAGGGCUUAACUCUGGUCAGGCAGUGGAAACUACAAAGCUAGAGUUCGGUAGGGGCAAAGGGAAUUCCCGGUGUAGCGGUGAAAUGCGUAGAUAUCGGGAAGAACAUCGGUGGCGAAAGCGCUUUGCUAGACCGAAACUGACGCUCAGGGACGAAAGCUAGGGGAGCGAAUGGGAUUAGAUACCCCAGUAGUCCUAGCCGUAAACGAUGGAUACUAGGUGUUGCCUGUAUCGCCCAGGCAGUGCCGUAGCUAACGCGUUAAGUAUCCCGCCUGGGGAGUACGCACGCAAGUGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGUAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCAGGGCUUGACAUGUCGCGAAUCUCAAGGAAACUUGAGAGUGCCUUCGGGAGCGCGAACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUCUUUAGUUGCCAUCAUUAAG-UUGGGCACUCUGGAGAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAGUCAGCAUGCCCCUUACGCUCUGGGCUACACACGUACUACAAUGGUUGGGACAGAGGGCAGCGAACCCGAGAGGGGAAGCCAAUCCCCAAAACCCAGCCUCAGUUCAGAUUGCAGGCUGCAACUCGCCUGCAUGAAGGAGGAAUCGCUAGUAAUCGCAGGUCAGCAUACUGCGGUGAAUCCGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGAAGUUGGCCACGCCCGAAGUCAUUACUCUAACCGAAAGGAGGGGGAUGCCGAAGGCAGGGCUGAUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUACCGGAAmmmmmmmmmmmmmmmmmm-----
pl.Zea.may -----UACCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUGCAAGUAUGAACUAA-----CGAA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUGUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCAAAACCCUCC-GGGCGGAUCGCA--CGGUUCGCGGCG-ACG-CAUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGGGGCCUACCAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACCG-GGCGCGUUAGUGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGC-CGGGC---------CGGG-UG-CC-GCCGUGGCA----G--AACCA------CC-----AUUAAUAGGGCAGUGGGGGCACGUAUUUCAUAGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACAACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGAUCAGCGG-UAAUCCCCGCUGGCCCUUAUGAGAAAUCA--AAGUCGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGCGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---CUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGUCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAACUAGCUAUGCCAUC--UUAGCUUCUUAGAGGGACUAUGGCCGUUUAGGCCGCG-AAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGUAUCCAACGAGUACCUUGGCCGACAGGCC-GG-UAAUCUUGGAAAUUUCAUCGUGAUGGGGAUAGAUCAUUGCAAUUGUUGGUCUUCAACGAGGAAUGCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGGUCCGGUGA-AGUGUUCGGACUCGGUUCGCCGGAAGUCCAUUGAACCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUG-----
pl.Pan.gin ----CAACCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUGUAAGUAUGAACUAA-----CAGA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUGUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCAAAACCCUCU-GGACGGAUCGCA--CGGCUCGCGGCG-ACG-CAUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACUAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACCG-GGCUG-AUUCAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGU-UGGGUC-----GGCCGGUCCG-CC--UCUCGGUG---UG--CACCA------UC-----AUUAACAGGGCAGUGGGGGCACGUAUUUCAUAGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACAACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGAUCAGUGGAUUUUCUCCACUGGCCCUUAUGAGAAAUCA--AAGUUGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---CUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAAAUAGCUAUGUUAUA--CCAGCUUCUUAGAGGGACUAUGGCCUUUUAGGCCACGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGUAUUCAACGAGUACCUUGGCCGACAGGCCCGGGUAAUCUU-GAAAUUUCAUCGUGAUGGGGAUAGAUCAUUGCAAUUGUUGGUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGGUCCGGUGA-AGUGUUCGGAUGCGGUUCGAAAGAAGUCCACUGAACCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCAGAAGGAUCAGNN-----
pl.Ara.tha -----UACCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUGUAAGUAUGAACGAA-----CAGA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUGUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCAAAACCCUAU-GGACGGAUCGCA--UGGUCUGUGGCG-ACG-CAUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUGGUAACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACCG-GGCUCUUUCGAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGA-UGGGUC-----GGCCGGUCCG-CC--UUU-GGUG---UG--CAUUG------UC-----AUUAACAGGGCAGUGGGGGCACGUAUUUCAUAGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACAACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGAUCAGCGGAUUAUCUCCGCUGGCCCUUAUGAGAAAUCA--AAGUUGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---CUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAACUAGCUACGUCAUC--CCGGCUUCUUAGAGGGACUAUGGCCGUUUAGGCCAAGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGUAUUCAACGAGACCCUU-GCCGACAGGCCCGGGUAAUCUU-GAAAUUUCAUCGUGAUGGGGAUAGAUCAUUGCAAUUGUUGGUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGAUCCGGUGA-AGUGUUCGGACGCGGUUCGCGAGAAGUCCACUAAACCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUG-----
pl.Gly.max -----UACUUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUGUAAGUAUGAACUAA-----CAGA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUGUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCAAAACCCUCU-GGACGGAUCGCA--CGGUUUGCGGCG-ACG-CAUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACCG-GGCUC-AUUGAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAUGAUCCAUUGAAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGU-UGGGUC-----GAUCGGUCCG-CC--UCC-GGUG---UG--CACCG------UC-----AUUAACAGGGCAGUGGGGGCACGUAUUUCAUAGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACAACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGAUCAGCGGAUUUUCUCCGCUGGCCCUUAUGAGAAAUCA--AAGUCGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCU-AAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---CUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAAAUAGCUAUGUUAAC--CCAGCUUCUUAGAGGGACUAUGGCCGCUUAGGCCACGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGUAUUCAACGAGUACCUUGGCCGACAGGUCCGGGUAAUCUU-GAAAUUUCAUCGUGAUGGGGAUAGAUCAUUGCAAUUGUUGGUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGGUCCGGUGA-AGUGUUCGGAUGCGGUUCGUGAGAAGUCCACUGAACCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUG-----
pl.Pis.sat -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNNNNNNNNAAGCCAUGCAUGUGUAAGUAUGAACUAA-----CAGA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUGUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCAAAACCCUUU-GGACGGAUCGCA--CGGUUUGUGGCG-ACG-CAUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUAACAC-GGGGAGGUAGUGACAAUAAAUCAAUACCG-GGCUC-AUUGAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGU-UGGGUU-----GAUCGGUCCG-CC--UCU-GGUG---UG--CACCG------UU-----AUUAACAGGGCAGUGGGGGCACGUAUUUCAUAGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACAACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGAUCAGCGGAUUUUCUCCGCUGGCCCUUAUGAGAAAUCA--AAGUCGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---CUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAAAUAGCUAUGUUAAC--CCAGCUUCUUAGAGGGACUAUGGCCGCUUAGGCCACGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGUAUUCAACGAGUACCUUGGCCGACAGGCCCGGGUAAUCUU-GAAAUUUCAUCGUGAUGGGGAUAGAUCAUUGCAAUUGUUGGUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGGUCCGGUGA-AGUGUUCGGAUGCGGUUCGUGAGAAGUCCACUGAACCUUAUCAUUUAGAGGAAGGAGAAGUCGNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
pl.Lyc.esc -----UACCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUGUAAGUAUGAACAAA-----CAGA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUGUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCAAAACCCUCUGGGACGGAUCGCA--CGGAUCGCGGCG-ACG-CAUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACCG-GGCUC-UAUGAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGA-UGGGCC-----GGCCGGUCCG-CC--CUA-GGUG-UG----CACCG------UC-----AUUAACAGGGCAGUGGGGGCACGUAUUUCAUAGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACAACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGAUCGGCGGAUUUUCUCCGCCGGCCCUUAUGAGAAAUCA--AAGUUGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---CUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAACUAGCUAUGCUAUC--CCAGCUUCUUAGAGGGACUA-GCCU-UUUAGGCCGCGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCC-CACGCGCGCUACACUGAUGUAUUCAACGAGUACCUU-GCCGACAGGCCCGGGUAAUCUU-GAAAUUUCAUCGUGAUGGGGAUAGAUCAUUGCAAUUGUUGGUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGAUCCGGUGA-AAUGUUCGGACGCGGUUCGCGAGAAGUCCAUUGAACCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUG-----
pl.Sol.tub -----UACCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUGUAAGUAUGAACAAA-----CAGA--------UGU-GAAACUGCGAAUGGCUCAU-AAAUCAGUUAAGUUUGUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCAAAACCCUCU-GGACGGAUCGCA--CGGAUCGCGGCG-ACG-CAUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACCG-GGCUC-UAUGAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGA-UGGCAC-----GGCCGGUCCG-CC--CUA-GGUG---UG--CACCG------UC-----AUUAACAGGGCAGUGGGGGCACGUAUUUCAUAGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACAACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGACCGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGGUCGGCGGAUUUUCUCCGCCGGCCCUUAUGAGAAAUCA--AAGUUGGUUCCGGGG-GAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---CUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAACUAGCUAUGCUAUC--CCAGCUUCUUAGAGGGACUACGGCCUUUUAGGCCGCGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGUAUUCAACGAGUACCUUGGCCGACAGGCCCGGGUAAUCUU-GAAAUUUCAUCGUGAUGGGGAUAGAUCAUUGCAAUUGUUGGUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGAUCCGGUGA-AAUGUUCGGACGCGGUUCGCGAGAAGUCCAUUGAACCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUG-----
pl.Gin.bil -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNUCAAAAUAAGCCAUGCAUGUGUAAGUAUGAACUCU-----CAGA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUCUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCACAAUCCUCU-GGACGGAUCGCA--CGGCUGGCGGCG-ACG-CUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGGCCUACCAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACUG-GGCUC-AUCGAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGC-CGGGUC-----GGCCGGUCCG-CC-UUUUCGGUG---UG--CACCG------CC-----AUUAAUAGGGCGGUGGGGGCACGUAUUUCAUUGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACCACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACUAGGGAUCGGCGGAUUUACUCCGCCGGCCCUUGUGAGAAAUCA--AAGUUGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAACUAGCUAUGCUUCG--CCAGCUUCUUAGAGGGACUAUGGCCCUUCAGGCCAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGUAUUCAACGAGUACCUGGGCCGAGAGGCCCGGGAAAUCUGCGAAAUUUCAUCGUGAUGGGGAUAGAUCAUUGCAAUUAUUGAUCUUAAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAACUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGAUCCGGUGA-AGUGUUCGGACGCGCUUCGCGAGAAGUUCAUUGAACCUUAUCAUUUAGAGGAAGGAGAAGNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
pl.Pin.luc -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNUCAAAAUAAGCCAUGCAUGUCUAAGUAUGAACAU------CAGA--------UGU-GAAACUGCGGAUGGCUCAUUAAAUCAGUUAAGUUUCUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCACAAUCCCUU-GGACGGAUCGCA--CGGUUUGUGGCG-ACG-CUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGGCCUACCAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACUG-GGCUC-AUCGAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGA-CGUCAC-----GGUCGGUCCG-CC-UUCUUGGUG---UG--CACUG------CC-----AUUAAUAGGGCUGUGGGGGCACGUAUUUCAUUGUCAGAGGUGAAAUUCUUGGAUUUAUGGAAGACGAACCACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGAUCGGCGGAUCUACUCCGCCAGCCCUUCUGAGAAAUCA--GAGUGGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAACUAGCUACGCUUCC--CCAGCUUCUUAGAGGGACUAUGGCCUCCUAGGCCAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGCAACCAACGAGCUCCUGGCCCGAAAGGUUUGGGAAAUCUUCCAAAUUGCAUCGUGAUGGGGAUAGACCAUUGCAAUUAUUGAUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGAUCCGGUGA-AGUGUUCGGACGCGCUUC-CGAGAAGUUCAUUGAACCUUAUCAUUUAGAGGAAGGAGAAGNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
pl.Tai.cry -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNUCAAAAUAAGCCAUGCAUGUCUAAGUAUGAACUAU-----CAGA--------UGU-GAAACUGCGGAUGGCUCAUUAAAUCAGUUAAGUUUCUUUGAUGGACUCGGAUAACCGUAGUAAUCUAGAGCUAAUACGUGCACAAUCCCUU-GGACGGAUCGCA--CGGUCUGCGGCG-ACG-CUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGGCCUACCAUGGUGGUGACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACUG-GGCUC-AUCGAGUUGGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGU-CGUCAC-----GGUCGGUCCG-CC-ACUC-GGUG---UG--CACUG------CC-----AUUAAUAGGGCUGUGGGGGCACGUAUUUCAUUGUCAGAGGUGAAAUUCUUGGAUUUAUGGAAGACGAACCACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUCAGAUACCGUCCUAGUCUCAACCAUAAACGAUGCCGACCAGGGAUCGGCGGAUCUACUCCGCCAGCCCUUCUGAGAAAUCA--GAGUGGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACGCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUCUAACUAGCUACGCUUCC--CCAGCUUCUUAGAGGGACUAUGGCCGUUUAGGCCAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGCAACCAACGAGCUCCUGGCCCGAAAGGUUCGGGAAAUCUUCCAAAUUGCAUCGUGAUGGGGAUAGACCAUUGCAAUUAUUGAUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGAUCCGGUGA-AGUGUUCGGACGCGCUUU-CGAGAAGUUCAUUGAACCUUAUCAUUUAGAGGAAGGAGAAGNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
pr.Sar.neu -----AACCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUUAAAAUAAGCCAUGCAUGUCUAAGUAUAAGCU-------UAUA--------GGC-GAAACUGCGAAUGGCUCAUUAAAACAGUUAAGUUUAUUUGAUGGACAUGGAUAACCGUGGUAAUCUAUGGCUAAUACAUGCGCAUACCCUCGGGUCGGAUCGCAU-UGGUUUUCGGCG-AUG-GAUCAUUCAAGUUUCUGACCUAUCAGCUUGACGGUACUGUAUUGGACUACCGUGGCAGUGACGGGUACGGGGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCUA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACUC-AGGGAGGUAGUGACAAGAAAUCAACACUG-GAAAU-UAUAUUUUAGUGAUUGAUGAUGGGAAUCCAAACC------------------------------CCUUCAGAGUAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGUGCU-GGAAGC-GCCAGUCCCCC--------UUUG-------------------CACUUGGG--AUUAAUAGGGCAGUGGGGGCACGUAUUUAACUGUCAGAGGUGAAAUUCUUAGAUUUGUUAAAGACGAACUACUGCGAAAGCAUGCCAAAGAUGUUUUAUU---AAUCAAGAACGAAAGUUAGGGGCUCGAAGACGAUCAGAUACCGUCGUAGUCUUAACCAUAAACUAUGCCGACUAGAGAUAGGAAAAUCCUCUUCUCCUGCCCUUAUGAGAAAUCA--AAGUCGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGCGUGGAGC-UGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAG-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUUAACCUCUAAAUAGGGUCAAUUUG-UAUCACUUCUUAGAGGGACUUUGCGUGUCUAACGCAAGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCUGCACGCGCGCUACACUGAUGCAUCCAACGAGCACCCUGGCCGACAGGUCUAGGUAAUCUUUGAGUAUGCAUCGUGAUGGGGAUAGAUUAUUGCAAUUAUUAAUCUUCAACGAGGAAUGCCUAGUAGGCGCAAGUCAGCAGCUUGCGCCGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAGUGUUCCGGUGA-AUUAUUCGGAUGUUCUACCUGGGAAGUUUUGUGAACCUUAACACUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCAGAAGGAUCANNN-----
pr.Pla.mal -----AACCUGGUUGAUCUUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAAGUGAAAGUAUAUGCAUAU----U--------AUAUGUAGAAACUGCGAACGGCUCAUUAAAACAGUUAAGUCUACUUGACAUAUAAGGAUAACUACGGAAAACUGUAGCUAAUACUUGCUUAAUACUUAUGUAAACACAUAA--UAAUUCG-UAGU-GUG-UAUCAAUCGAGUUUCUGACCUAUCAGCUUGAUGUUAGGGUAUUGGCCUAACAUGGCUAUGACGGGUACGGGGAAUUAGAGUUCGAUUCCGGAGAGGGAGCCUGAGAAAUAGCUACCACAUCUA-GGAAGGCAGCAGGCGCGUAAAUUACCCAAUUCUAAAGA-AGAGAGGUAGUGACAAGAAAUCAAUGCAA-GGCCA-AUUUGGUUUGCAAUUGAUGAUGGGAAUUUAAAAC------------------------------CUCCCAGA-AGGCAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAAUUGUUGCAGUUAAAACGCUCGUAGUUGAAGG-AUC-AAU-AUUUUAAUAAU--GCUU-GCCAUU-UAAUAUCUUCUU-AUU---AUAA--AAUUAAUAGGAUAGCGGGGGCAUGUAUUCAGAUGUCAGAGGUGAAAUUCUUAGAUUUUCUGGAGACAAGCAACUGCGAAAGCAUGCCUAAAAUACUUCAUU---AAUCAAGAACGAAAGUUAAGGGAGUGAAGACGAUCAGAUACCGUCGUAAUCUUAACCAUAAACUAUGCCGACUAGGUGUUGGAUGAAUAUUUCCUUCAGUCCUUAUGAGAAAUCA--AAGUCGGUUCUGGGGCGAGUAUUCGCGCAAGCGAGAAAGUUAAAAGAACCGACGGAAGGGGACAC-AGGCGUGGAGCUUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACUAGUUUAAGACAG-UA---UUAA-------------------------U--UU--CUUGGAUGGUGAUGCAUGGCCGUUUUUAGUUCGUGAAAUGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGAUCUUAACCUCUAAUUAGCGGUAAUAAU---AAGCUUCUUAGAGGAACGAUGUGUGUCUAACACAAGGAAGUUUAAGGCAACAACAGGUCGUGAUGUCCUUAGUGAACUAGGCUGCACGCGUGCUACACUGAUAUGUAUAACGAGGUUGCUCACUGAA-AGUGUAGGUAAUCUUUCAAUAUAUAUCGUGAUGGGGAUAGAUUAUUGCAAUUAUUAAUCUUGAACGAGGAAUGCCUAGUAAGCAUGAUUCAUCAGAUUGUGCUGACUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAAGAUAUGAUGA-AUUGUUUGGAAAGAAUUAUCUGGAAAAAUCGUAAAUCCUAUCUUUUAAAGGAAGGAGAAGUCGUAACAAGGUUUCCGUCGGUGAACCUGCGGAAGGAUCAUUA-----
pr.Sti.hel -----NNNNNNNNNNNNNNNNNNNNNNNUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAACUG------UAUA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUAUUUGAUGGACUCGGAUAACUGUAGUAAUCUACAGCUAAUACGUGCUUAGUCCUCU-GGACGAAUCGCA--UAGCUUGUGGCG-AUG-UUUCAUUCAAACUUCUGCCCUAUCAACUUGACGGUAGGAUAGAGGCCUACCAUGGUGGUGACGGGUACGGAGGAUUAGGGUUCGGUUCCGGAGAGGGAGCCUGAGAAAUGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-AGGGAGGUAGUGACAAUAAAUCAAUACCG-GGCAU-UAAAUGUUGGUAAUUGAUGAUAACGAUCUAAACC------------------------------CAUAUAGAGUAUCCAUUGGAGGCAAGUCUGGUGCCNNCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUUNAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGU-GGCUUUC-----UGCGGUCCG-C---UUC-GGUG---UG--CACUG------CU-----AUUAAGAGGGCAGUGGGGGCACGUAUUUCAUUGUCAGAGGUGAAAUUCUUGGAUUUAUGAAAGACGAACUUCUGCGAAAGCAUGCCAAGUAUGUCUUAUU---AAUCAAGAACGAAAGUUGGGGGCUCGAAGACGAUUAGAUACCGUCGUAGUCUCAACCAUAAACGAUGCCGACUAGGGAUCGGUGGGUUCGCUCCUCCGGCCCUUAUGAGAAAUCA--AAGUCGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGCGUGGANNCUGCGGCUUAAUUUGACUCAACACGGGAAAACUUACCAGGUCCAGACAA-GA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGGUUGCCUUGUCAGGUUGAUUCC-GGAACGAACGAGACCUCAGCCUCUAAAUAGUNNNUGUCUU-GCCGACUUCUUAGAGGGACUAUUGUCGUUUAGGCAAUGGAAGUAUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGCAUUCAACGAGUACCUUGGCCGAGAGGCC-GGGUAAUCUU-GAAACUGCAUCGUGAUGGGGAUAGAUUAUUGCAAUUAUUAGUCUUCAACGAGGAAUGCCUAGUAAGCGCGAGUCAUCAGCUCGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGGGUGUGCUGGUGA-AGNNUUCGGAUGAGAUCU-CGAGAAGUUCGUUAAACCCUCCCACCUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
pr.Mal.mat -----CACCUGGUUGAUCCUGCCAGUAG-CAUACGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAACAAC-----UGUA--------UGU-GAAACUGCGAAUGGCUCAUUAUAUCAGUUAAGUUUAUUUGAUGGACAUGGAUAACCGUAGUAAUCUAGAGCUAAUACAUGCAUAAGCCUUC-GGCCGGAUCGAU--C--UUCGGAUCG-AUG-CAUCAUUCAAGUUUCUGCCCUAUCAGCUUGAUGGUAGGGUAUUGGCCUACCAUGGCUUUAACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAAUGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGUAAAUUACCCAAUCCUGACAC-AGGGAGGUAGUGACAAUAAAUCAAUGCCG-GGCUUAUUUAAGUUGGCAAUUGAUGAGAACAAUUUAAAUC------------------------------CCUAUCGAGGAUCAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUACUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGUGGU-UGUGGCA-----AACAGUCCG-CCC-AACAGGUGU---GU--GCUA---------U-G-AUUAAUAGGGUAGUGGGGGUACGUAUUCAAUUGUCAGAGGUGAAAUUCUUGGAUUUAUGGAAGACGAACUACUGCGAAAGCAUACCAAAUAUGUUUUAUU---AAUCAAGAACGAAAGUUAGGGGAUCGAAGAUGAUUAGAUACCAUCGUAGUCUUAACCAUAAACUAUGCCGACUAGGGAUUGGUGGCGUUACUCCAUCAGCCCUUAUGAGAAAUCA--AAGUCGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGAAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-GA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCCCCGCCUCUAAAUAGUCGUACUUAGUGUCGGCUUCUUAGAGGGACUUUUGGUGACUAACCGAAGGAAGUUGGGGGCAAUAACAGGUCGUGAUGCCCUUAGUGUCCUGGGCCGCACGCGCGCUACACUGACACACGCAACGAG-UCCUUGAUUGAAAAAUCCGGGUAAUCUUUAAAUGUGUGUCGUGAUAGGGAUAGAUUAUUGCAAUUAUUAAUCUUGAACGAGGAAUUCCUAGUAAAUGCGAGUCAUCAGCUCGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCACCUACCGAUGAAUGAUUCGGUGA-AAAUUCCGGAUGUGGGCAAUAGGAAGUUAUUUAAACCUCAUCAUUUAGAGGAAGGUGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCAGAAGAUCCAGCUUCCUC
pr.Cyc.gla -----NNNNNNNNNNNNNNNNNNNNUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAAU--------AAUA--------AGU-GAAACUGCGAAUGGCUCAUUAAAACAGUUAAGUUUAUUUGAUGAACAUGGAUAACCGUGGUAAUCUAGAGCUAAUACAUGCAUAGGCCUCACGGCCGGAUCCCC-----AACU-GGGG-AUAAGAUCANUCAAGUUUCUGCCCUAUCAGCUUGAUGGUAGUGUAUUGGACUACCAUGGCAGUAACGGGUACGGAGAAUUAGGGUUCGGUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCUA-GGAAGGCAGCAGGCGCGUAAAUUACCCAAUGCAGAUUC-UGCGAGGUAGUGACAAUACAUCAACCUGG-GGUC-UCACGACUACGGGAUUGAUGAGAACAAUUUAAAAA------------------------------CCUAACGAGGAACAAGUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCACUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGUGGU-UGNGCGC------AGUGGUCG-GUC-AUC--GAUC------GCCCG-------------AUUAAUAGGGCAGUGGGGGCAAGUAUUUAAUUGUCAGAGGUGAAAUUCUUGGAUUUAUUAAAGACUAACUUAUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUAGGGGAUCAAAGACGAUCAGAUACCGUCCUAGUCUUAACUAUAAACUAUACCGACUCGGUUUUGGUGGGGUAUCUCUAUCAGCCCGUAUGAGAAAUCA--AAGUCGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGUGUGGACGCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCAAAACAG-UG---UUGA-------------------------U--UC--UGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGCUUAAUUGC-GUAACGAACGAGACCUUAACCUCUUAAUAGAUGCCUGUAC--UAUUCUUCUUAGAGGGACUAUGCGUUUCAAGCGCAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCCUAGUGUCCUGGGCCGCACGCGCGCUACACUGACCCACUCAGCAAGCUCCUGGCCUGGAAAGGUUGGGUAAUCUUGCAAUAUGGGUCGUGUUAGGGAUCGAUCUUUGCAAUUAUAGAUCUUGAACGAGGAAUACCUAGUAAGUGCAAGUCAUCAGCUUGUACUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGGUCCGGUGA-ACCUUCUGGACAGUCGCAACGCGAAGUUAAGUAAACCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUNNNNNNNNNNNNNNNNNNNNNNNNN-----
pr.Tet.bor -----AACCUGGUUGAUCCUGCCAGUA--CAUAUGCU-UGUCUUAAAAUAACCCAUGCAUGUGCCAGUUCA-GU--------UGAA--------AGC-GAAACUGCGAAUGGCUCAUUAAAACAGUUAAGUUUAUUUGAUAAACAUGGAUAACCGAGCUAAUGUUGGGCUAAUACAUGCUUAAUUCCCUGGAACGAAUCGAA--G--CUUGCUUCG-AUA-AAUCAUCUAAGUUUCUGCCCUAUCAGCUCGAUGGUAGUGUAUUGGACUACCAUGGCAGUCACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAAGGAGCCUGAGAAACGGCUACUACAACUC-GGUCGGCAGCAGGGAAGAAAAUUGGCCAAUCCUAAUUC-AGGGAGCCAGUGACAAGAAAUCAAGCUGG-GAAACCUA-GUUUUCGGCAUUGAUGAGAAAAGUGUUAAUC------------------------------UCUAGCGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGUGUU-CAGGUUCU-----UUCGA--------CUCG------------UCG----------G-GAAUUAAUAGGGCAGUGGGGGCAAGUAUUUAAUAGUCAGAGGUGAAAUUCUUGGAUUUAUUAAGGACUAACUAAUGCGAAAGCAUGCCAAAGAUGUUUUAUU---AAUCAAGAACGAAAGUUAGGGGAUCAAAGACGAUCAGAUACCGUCGUAGUCUUAACUAUAAACUAUACCGACUCGGGAUCGGCUGGAUAAUCCAGUCGGCCCGUAUGAGAAAUCA--AAGUCGGUUCUGGGGGAAGUAUGGACGCAAGUCUGAAACUUAAAGGAAUUGACGGAACAGCACACCAGAAGUGGAACCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACGAGCGCAAGACAA-AG---UUGA-------------------------U--UC--UUUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUUAACCUCUAACUAGUCUGCUAACA--UGUACUUCUUAGAGGGACUAUUGGCAAGAAGCCAAUGGAAGUUUAAGGCAAUAACAGGUCGUGAUGCCCCUAGCGUGCUCGGCCGCACGCGCGUUACAAUGACUGGCGCAGAAAGUUCCUGUCCUGGGAAGGUAGGGUAAUCUUUUAAUACCAGUCGUGUUAGGGAUAGUUCUUUGGAAUUGUGGAUCUUGAACGAGGAAUUUCUAGUAAGUGCAAGUCAUCAGCUUGCGUUGAUUAUGUCCCUGCCGUUUGUACACACCGCCCGUCGCUUGUAGUAACGAAUGGUCUGGUGA-ACCUUCUGGAUGCGGGCAACGGAAAAAUAAGUAAACCCUACCAUUUGGAACAACAAGAAGUCGUAACAAGGUAUCUGUAGGUGAACCUGCAGAUGGAUCAUUA-----
pr.Rho.sal -----UACCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUUAGUGUAAAUA-------UGU---------UAU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUACGUUUAUUUGAUGGACAUGGAUAACCGUAGUAAUCUAGAGCUAAUACAUGCACAGGUCUUACGACCGAACACAG--C--CUUGAGUGU-GUG-AUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGGCCUACCAUGGUUUUAACGGGUACGGAGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAGACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCC-GACUU-GGGGAGGUAGUGACAAUAAAUCAAUACAG-GGCU--UAC-AGUUUGUUAUUGAUGAGAACAAUUUAAAUC------------------------------UCUUACGAGGAUCAAUUAGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCUAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUCGGGGC-UCGGGGA-----GGCUGUCGG-C---UUCG--------GUGGACGC-----------AUAUUAACAGGGCAGUGGGGCCGUAUAUUUCGUUGUCAGAGGUGAAAUUCUUGGAUUUACGAAAGAUAAACUUCUGCGAAAGCACGGCAAGGAUGUUUUAUU---GAUCAAGAACGAAAGUUAGGGGAUCGAAGACGAUCAGAUACCGUCGUAGUCUUAACCAUAAACUAUGCCGACUAGGGAUCAGUGGAUUUGCUCCAUUGGCCCUUGUGAGAAAUCA--AAGUUGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCUUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCAGCCUGUAACUAGUGACGCUUU--GCCCACUUCUUAGAGGGACUAUUUGUGUUUAAUGAAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGAAUGCAACGAGCUCCUUAUUCGAAAGAAUCGGGUAAACUUUGAAAAUUCAUCGUGAUGGGGAUAGAUUAUUGCAAUUAUUAAUCUUCAACGAGGAAUUCCUAGUAAGCGCGAGUCAUCAGCUCGUGCUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGGUCCGGUGA-AAUCUUCGGAUGCAGUUAUCGAGAAGUUGAUUGAACCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUG-----
pr.Por.aca -----NNNNNNNNNNNNNNNNNNNNNAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAACGCC-----UAUA-------UCGU-GAAACUGCGAAUGGCUCAUUAAAACAGUUAAGUUCCUUUGGGAAACUUGGAUAGCCGUAGUAAUCUAGAGCUAAUACAUGCCGACGCCUCACGGUCGGAUCGCA--CGGCAUGUGGCG-ACG-CCUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGAGUAUUGGCCUACCAUGGUGUCGACGGGUACGGGGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCCAACAC-GGGGAGGUAGUGACAAAAAAUCAAUAGGG-GGCCCUUUACGGUCUCUAAUUGGUGAGAACAAUUUAAAUU------------------------------CCUAUCAAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAACGCUCGUAGUCGGGAG-CACCUC-------CACGGGCC-GGGUUCUGUUGC---CAG-UUGGG-------------AUUAAUAGGGCAGUGGGGGCACGUAUUUCAUUGUCAGAGGUGAAAUUCUUGGAUUGAUGGAAGACGCACAACUGCGAAAGCAUGCCAUGGAUGUUUUAUU---GAUCAAGAACGAAAGUUAGGGGAUCGAAGACGAUCAGAUACCGUCGUAGUCUUAACCAUAAACGAUGCCGACUGGGGAUUGGCGGGUUUUCUCCGUCAGCCCCUAUGGGAAACCA--AAGUUGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGAAAACUUACCAGGUCCGGACAA-GA---CUGA-------------------------U--UU--UUUGGUUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GUAACGAACGAGACCUCGUCCUCUAAAUAGGUGCGCCCCGUCUUACCUUCUUAGAGGGACUAUCCGCGUCUAGCGUAUGGAAGAUUGAGGCAAUAAUAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGCAUUCAACAAGAGCCUGGACCGGAAGGCUCGGGUAACCUUUGAAACUGCAUCGUGAUGGGGAUAGAUCAUUGCAAUUAUUGAUCUUGAACGAGGAAUUCCUUGUAGGCGUAGGUCACUAGCCUGCGCCGAAUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUCCUACCGAUGAAUGGUCCGAUGA-AGUGUUCGGAUGCGGUUA-UUAGAAGUUCAUUAAAUCUUAUCAUUUAGAGGAAGGAGAAGUCGUAACAAGGUUUCCNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
pr.Bla.hom -----NNNNNNNNNNNNNNNNNNNNNNGUCAUACGCU-CGUCUCAAAAUAAGCCAUGCAUGUGUAAGUGUAAAU--------ACUA--------UUU-GGAACUGCGAAUGGCUCAUUAUAUCAGUUAAGUUUAUUUGGUGAACUUGGAUAACCGUAGUAAUCUAGGGCUAAUACAUGAGAGUCCUUGGUAGGCGUAUCGCA--UGCUUAAUAGCG-AUG-AGUCUUUCAAGUUUCUGCCCUAUCAGCUUGAUGGUAGUAUAUGGGCCUACCAUGGCAGUAACGGGUACGAAGAAUUUGGGUUCGAUUUCGGAGAGGGAGCCUGAGAGAUGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGUAAAUUACCCAAUCCUGACAC-AGGGAGGUAGUGACAAUAAAUCAAUGCGG-GACU--AUC-AGUUUGCAAUUGUUGAGAACAAUGUACAAC------------------------------UCUAUCGAUAAGCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAACGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGU-GAUCGCU-----GUUGUGAGA-C---UUCGUCUCU---CG--ACAU-------------GUUAAAAGGACAGUGGGGGUACAUAUUCACUAGUUAGAGGUGAAAUUCUCGGAUUUAUGGAAGAUGAACAAGUGCGAAAGCAUACCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGCUAGGGGAUCGAAGAGGAUUAGAUACCCUCGUAGUCUUAGCUAUAAACGAUACCGACUAGGGGUUAGUAGA-AAGCUUUAUUAGUCCUUAUGAGAAAUCA--AAGUCGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUUACCAGGUCCAGACAA-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGCUAAUUCC-GAAACGAACGAGACCUCCGCCUUUAACUAGUGACGUUGUG---UUGCUUCUUAUAGGGACACUAUAUGUAAAAUGUAGGGAAGCUGGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCUGCACGCGCGCGACACUGAUCUAUUCAACGAG--GCUGGGUCGAGAGACUUGGCAAAUCUUUGAAAGUAGAUCGUGAUGGGGAUUGAUGCUUGUAAUUGUUCAUCAUGAACGAGGAAUUCCUAGUAAACGCAAGUCAUCAACUUGCAUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCACCUACCGAUGAAUGGUCCGGUGA-ACACUUUGGAUUGAGUAAAGGAGAAGUCGUGUAAAUCUUAUCAUUUAGAGGAAGGUGAAGUCGUAACAAGGUUUCCNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
pr.Try.equ -----NNNNNNNNUGAUUCUGCCAGUAGUCAUAUGCU-UGUUUCAAGAUUAGCCAUGCAUGCCUCAGAAUCACUGC------U----------GCAG-GAAUCUGCGCAUGGCUCAUUACAUCAGACGAAUCUGCGCCAAAAUACUGGAUAACUUGGCGAAAGCCAAGCUAAUACAUGAACUCGGAUUA-UCCGAAAGCCG---GC-CUUGCUCGG-CGUCUACUGAC-GAACAACUGCCCUAUCAGCCAGAUGGCCGUGUAGUGGACUGCCAUGGCGUUGACGGGAGCGGGGGAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAAUAGCUACCACUUCUC-GGAGGGCAGCAGGCGCGCAAAUUGCCCAAUGUCGAAAACGAUGAGGCAGCGAAAAGAAAUGAGCGACC-GUGCCCUAGUGCAGGUUGUUUUAUGGGGGAUACUCAAACC--------------------------CAUCCAUAUCGAGUAACAAUUGGAGACAAGUCUGGUGCCAGCACCCGCGGUAAUUCCAGCUCCAAAAGCGUAUAUUAAUGCUGUUGCUGUUAAAGGGUUCGUAGUUGGGGC-CACGUAG-------UGUGCC--GUGACCUC-GGACGUGUUGACCCACGC--------CCUGAAGGAGGGAGUUGGGGGAGCGUACUGGUGCGUCAGAGGUGAAAUUCUUAGACCGCACCAAGACGAACUACAGCGAAGGCACUUCAAGGAUACCUUCUC---AAUCAAGAACCAAAGUGUGGGGAUCAAAGAUGAUUAGAGACCAUUGUAGUCCACACUGCAAACCAUGACACCCAUGAAUUGGGGAA----UU-UCUUACUCUUCACGCGAAAGCUUGGAGGUGUCUCAGGGGGGAGUACGUUCGCAAGAGUGAAACUUAAAGAAAUUGACGGAAUGGCACACAAGACGUGGAGCGUGCGGUUUAAUUUGACUCAACACGGGGAACUUUACCAGAUCCGGACAG-GA---UGGA-------------------------U--CC--CCUGAAUGGUGGUGCAUGGCCGCUUUUGGUCGGUGGAGUGAUUUGUUUGGUUGAUUCC-GUAACGGACGAGAUCCAAGCUGCCCAGUAGGUGCCGUUUU-GGCCCCUUCUCUGCGGGAUUCCUUGCUUUCGGCAAGGUGAGAUUUUGGGCAACAGCAGGUCGUGAUGCUCCUCAUGUUCUGGGCGACACGCGCACUACAAUGUCAGUGAGAACAGUCCCUUG-AUCAAAAGAGC-GGGGAAACCAAAUCACGUAGACCCACUUGGGACCGAGUAUUGCAAUUAUUGGUCGCCAACGAGGAAUGUCUCGUAGGCGCAGCUCAUCAAACUGUGCCGAUUACGUCCCUGCCAUUUGUACACACCGCCCGUCGUUGUUUCCGAUGAUGGUGCAAUACA-GGUGAUCGGACGUCGUCU-CCGAAAGUUCACCGAUAUUGCUUCAAUAGAGGAAGCAAAAGUCGUAACAAGGUAGCUGUAGNNNNNNNNNNNNNNNNNNNNNNN-----
an.Dro.mel -----AUUCUGGUUGAUCCUGCCAGUAGUUAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUACACACG-------UUAA--------AGU-GAAACCGCAAAAGGCUCAUUAUAUCAGUUAGGUUCCUUAGAUCGACUUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCAAAACAUUUAUGUGCAGAUCGUA--UGGCUUGCGACG-ACA-GAUCUUUCAAAUGUCUGCCCUAUCAACUUGAUGGUAGUAUCUAGGACUACCAUGGUUGCAACGGGUACGGGGAAUCAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCUA-GGAAGGCAGCAGGCGCGUAAAUUACCCACUCCCAGCUC-GGGGAGGUAGUGACGAAAAAUCAAUACAG-GACUCAUCCGAGCCUGUAAUUGAUGAGUACACUUUAAAUC------------------------------CUUAACAAGGACCAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCGGUUAAAACGUUCGUAGUUGUGCU-UCAUAC-----GGGUAGUACA-ACU-AAUUGUUA-GU-----ACUU----ACCUUUUG-AUUAAUAGAACAGUGGGGGCAAGUAUUACGACGCGAGAGGUGAAAUUCUUGGACCGUCGUAAGACUAACUUAAGCGAAAGCAUGCCAAAGAUGUUUUAUU---AAUCAAGAACGAAAGUUAGAGGUUCGAAGGCGAUCAGAUACCGCCCUAGUUCUAACCAUAAACGAUGCCAGCUAGCAAUUGGGUGUUUUUCUCUCUCAGUGCUUCCGGGAAACCA--AAGCUGGCUCCGGGGGAAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGAAAACUUACCAGGUC-GAACAA-UG---UUGA-------------------------U--CC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUCGUGGAGUGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACUCAAAUAUUUAAAUAGAUAC--UGUGCACUAGCUUCUUAAAUGGACAAAUUGCGUCUAGCAAUAUGAGA-UU-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUCCUGGGCUGCACGCGCGCUACAAUGAAAGUAUCAACGUGUUCCUAGACCGAGAGGUCCGGGUAAACCGUGAACCACUUUCAUGCUUGGGAUUGUGAACUGAAACUG-UUCACAUGAACUUGGAAUUCCCAGUAAGUGUGAGUCAUUAACUCGCAUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUUAUUUAGUGA-GGUCUCCGGAGUGAUCUUGGCAAAAGUUGACCGAACUUGAUUAUUUAGAGGAAGUAAAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUA-----
an.Lam.aep -----NACCUGGUUGAUCCUGCCAGUAG-CAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUGCGUGCAAACGG------GUUA--------AGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAGGUUCCUUUGAUCGGCUUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCUGAGCGCUCCGGCGCAGAUCGCA--CGGCUGGUGGCG-ACG-UAUCUUUCGAAUGUCUGCCCUAUCAACUUGAUGGCAGGCUCCGUGCCUACCAUGGUGACCACGGGUACGGGGAAUCAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCACUCCCGACUC-GGGGAGGUAGUGACGAAAAAUCAAUACAG-GACUCUUUCGAGCCUGUAAUUGAUGAGUACACUUUAAAUC------------------------------CUUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGCUGUUGCAGUUAAAAAGCUCGUAGUUGGGGA-AGGGGCU-----UGCGGUCCG-CC--GCGAGGUGU--GU--CACUC-------CUG--CAUUAAGAGGGCUGCGGGGGCACGUAUUGUGCCGUUAGAGGUGAAAUUCUUGGAUCGGCGCAAGACGAGCGAAAGCGAAAGCAUGCCAAGAAUGUCUUAUU---AAUCAAGAACGAAAGUCGGAGGUUCGAAGGCGAUCAGAUACCGCCCUAGUUCCGACCAUAAACGAUGCCAACUGGCGAUCAGGCGGUCCCCCUGCCUGGCGCUUGCGGGAAACCA--AAGUGGGUUCCGGGGGAAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGAAAACUCACCCGGCCCGGACAG-GA---UUGA-------------------------U--CC--CGUGGGUGGUGGUGCAUGGCCGUUCGUAGUUGGUGGAGCGAUUUGUCUGGUUCAUUCC-GAAACGAACGAGACUCCGACGUCUAACUAGCUACGCUGUG--UGAGCUUCUUAGAGGGACGAGUGGCUUUCAGCCACACGAGA-UU-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUCCGGGGCCGCACGCGCGCUACACUGAAUGGAUCAGCGUGCGCCUUCGCCGGCAGGCGUGGGUAACCCGUGAAACCCAUUCGUGAUAGGGAUUGGGGAUUGGAACUGUUCCCCAUGAACGAGGAAUUCCCAGUAAGCGCGAGUCAUAAGCUUGCGUUGAUUAAGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGGAUGGUUUAGUGA-GGUCCUCGGAUGGCCGCGAUGAGAAGACGAUCGAACUUGACUGUCUAGAGGAAGUAAAAGUCGUNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
an.Xen.lae -----UACCUGGUUGAUCCUGCCAGUAG-CAUAUGCU-UGUCUCAAAAUAAGCCAUGCACGUGUAAGUACGCACGG------GGUA--------AGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAGGUUCCUUUGAUCGACUUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCCGAGCGCCCCAGCGCCGAUCGCA--CGUCCCGCGGCG-ACG-AUACAUUCGGAUGUCUGCCCUAUCAACUUGAUGGUACUUUCUGCGCCUACCAUGGUGACCACGGGUACGGGGAAUCAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCACUCCCGACGC-GGGGAGGUAGUGACGAAAAAUCAAUACAG-GACUCUUUCGAGCCUGUAAUUGAUGAGUACACUUUAAAUC------------------------------CUUAACGAGGAUCUAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGCUGCAGUUAAAAAGCUCGUAGUUGGGGA-UCGAGCU-----GGCGGUCCG-CC--GCGAGGCG---GC--UACCC-------CUG--CAUUAAGAGGGCGGCGGGGGCACGUAUUGUGCCGCUAGAGGUGAAAUUCUUGGACCGGCGCAAGACGAACCAAAGCGAAAGCAUGCCAAGAAUGUUUUAUU---AAUCAAGAACGAAAGUCGGAGGUUCGAAGACGAUCAGAUACCGUCGUAGUUCCGACCAUAAACGAUGCCGACUAGCGAUCCGGCGGUCCCCCCGCCGAGCGCUUCCGGGAAACCA--AAGUCGGUUCCGGGGGGAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGAAACCUCACCCGGCCCGGACAG-AA---UUGA-------------------------U--CC--UGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACUCCUCCAUCUAACUAGUUACGCCCGG--CCAACUUCUUAGAGGGACAAGUGGCGUUCAGCCACACGAGA-UC-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUCCGGGGCUGCACGCGCGCUACACUGAACGGAUCAGCGUGUACCUGCGCCGACAGGUGCGGGUAACCCGUGAACCCCGUUCGUGAUAGGGAUCGGGGAUUGCAAUUAUUUCCCAUGAACGAGGAAUUCCCAGUAAGUGCGGGUCAUAAGCUCGCGUUGAUUAAGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGGAUGGUUUAGUGA-GGUCCUCGGACGGCCGCCACGAGAAGACGAUCAAACUUGACUAUCUAGAGGAAGUAAAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUA-----
an.Hom.sap -----UACCUGGUUGAUCCUGCCAGUAG-CAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUACGCACGG------GGUA--------AGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAGGUUCCUUUGGUCGACUUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCCGGGCGC-CGCGCGCCGAUCGCA--CGCCCCGCGGCG-ACG-ACCCAUUCGAACGUCUGCCCUAUCAACUUGAUGGUAGUCGCCGUGCCUACCAUGGUGACCACGGGUACGGGGAAUCAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCACUCCCGACCC-GGGGAGGUAGUGACGAAAAAUCAAUACAG-GACUCUUUCGAGCCUGUAAUUGAUGAGUCCACUUUAAAUC------------------------------CUUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGCUGCAGUUAAAAAGCUCGUAGUUGGGGA-GCGGGC-----GGGCGGUCCG-CC--GCGAGGCG-AGCC---ACCC------CCGU---AUUAAGAGGGCGGCGGGGGCACGUAUUGCGCCGCUAGAGGUGAAAUUCUUGGACCGGCGCAAGACGGACCAGAGCGAAAGCAUGCCAAGAAUGUUUUAUU---AAUCAAGAACGAAAGUCGGAGGUUCGAAGACGAUCAGAUACCGUCGUAGUUCCGACCAUAAACGAUGCCGACCGGCGAUGCGGCGGUCCCCCCGCCGGGCGCUUCCGGGAAACCA--AAGUCGGUUCCGGGGGGAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGAAACCUCACCCGGCCCGGACAG-CA---UUGA-------------------------U--CC--CGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACUCUGGCAUCUAACUAGUUACGCCGAGCCCCAACUUCUUAGAGGGACAAGUGGCGUUCAGCCACCCGAGA-UU-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUCCGGGGCUGCACGCGCGCUACACUGACUGGCUCAGCGUGUACCUACGCCGGCAGGCGCGGGUAACCCGUGAACCCCAUUCGUGAUGGGGAUCGGGGAUUGCAAUUAUUCCCCAUGAACGAGGAAUUCCCAGUAAGUGCGGGUCAUAAGCUUGCGUUGAUUAAGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGGAUGGUUUAGUGA-GGCCCUCGGACGGCCGCCCUGAGAAGACGGUCGAACUUGACUAUCUAGAGGAAGUAAAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUA-----
an.Mus.mus -----UACCUGGUUGAUCCUGCCAGUAG-CAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUACGCACGG------GGUA--------AGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAGGUUCCUUUGGUCGACUUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCCGGGCGCUCCCGCGCCGAUCGCA--CGCCCCGCGGCG-ACG-ACCCAUUCGAACGUCUGCCCUAUCAACUUGAUGGUAGUCGCCGUGCCUACCAUGGUGACCACGGGUACGGGGAAUCAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCACUCCCGACCC-GGGGAGGUAGUGACGAAAAAUCAAUACAG-GACUCUUUCGAGCCUGUAAUUGAUGAGUCCACUUUAAAUC------------------------------CUUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGCUGCAGUUAAAAAGCUCGUAGUUGGGGA-GCGGGC-----GGGCGGUCCG-CC--GCGAGGCGA--GU--CACCC------CCGU--CAUUAAGAGGGCGGCGGGGGCACGUAUUGCGCCGCUAGAGGUGAAAUUCUUGGACCGGCGCAAGACGGACCAGAGCGAAAGCAUGCCAAGAAUGUUUUAUU---AAUCAAGAACGAAAGUCGGAGGUUCGAAGACGAUCAGAUACCGUCGUAGUUCCGACCAUAAACGAUGCCGACUGGCGAUGCGGCGGUCCCCCCGCCGGGCGCUUCCGGGAAACCA--AAGUCGGUUCCGGGGGGAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGG-GCCUGCGGCUUAAUUUGACUCAACACGGGAAACCUCACCCGGCCCGGACAG-CA---UUGA-------------------------U--CC--CGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACUCUGGCAUCUAACUAGUUACGCCGAGCCCCAACUUCUUAGAGGGACAAGUGGCGUUCAGCCACCCGAGA-UU-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUCCGGGGCUGCACGCGCGCUACACUGACUGGCUCAGCGUGUACCUGCGCCGGCAGGCGCGGGUAACCCGUGAACCCCAUUCGUGAUGGGGAUCGGGGAUUGCAAUUAUUCCCCAUGAACGAGGAAUUCCCAGUAAGUGCGGGUCAUAAGCUUGCGUUGAUUAAGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGGAUGGUUUAGUGA-GGCCCUCGGACGGCCGCCCUGAGAAGACGGUCGAACUUGACUAUCUAGAGGAAGUAAAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUA-----
an.Rat.nor -----UACCUGGUUGAUCCUGCCAGUAG-CAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUACGCACGG------GGUA--------AGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAGGUUCCUUUG-UCGACUUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCCGGGCGCUCCCGCGCCGAUCGCA--CGCUCCGCGGCG-ACG-ACCCAUUCGAACGUCUGCCCUAUCAACUUGAUGGUAGUCGCCGUGCCUACCAUGGUGACCACGGGUACGGGGAAUCAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCACUCCCGACCC-GGGGAGGUAGUGACGAAAAAUCAAUACAG-GACUCUUUCGAGCCUGUAAUUGAUGAGUCCACUUUAAAUC------------------------------CUUAACGAGGAUCCAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGCUGCAGUUAAAAAGCUCGUAGUUGGGGA-GCGGGC-----GGGCGGUCCG-CC--GCGAGGCGA--GU--CACCC-------CCG--CAUUAAGAGGGCGGCGGGGGCACGUAUUGCGCCGCUAGAGGUGAAAUUCUUGGACCGGCGCAAGACGGACCAGAGCGAAAGCAUGCCAAGAAUGUUUUAUU---AAUCAAGAACGAAAGUCGGAGGUUCGAAGACGAUCAGAUACCGUCGUAGUUCCGACCAUAAACGAUGCCGACUGGCGAUGCGGCGGUCCCCCCGCCGGGCGCUUCCGGGAAACCA--AAGUCGGUUCCGGGGGGAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGG-GCCUGCGGCUUAAUUUGACUCAACACGGGAAACCUCACCCGGCCCGGACAG-CA---UUGA-------------------------U--CC--CGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACUCUGGCAUCUAACUAGUUACGCCGAGCCCCAACUUCUUAGAGGGACAAGUGGCGUUCAGCCACCCGAGA-UU-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUCCGGGGCUGCACGCGCGCUACACUGACUGGCUCAGCGUGUACCUACGCCGGCAGGCGCGGGUAACCCGUGAACCCCAUUCGUGAUGGGGAUCGGGGAUUGCAAUUAUUCCCCAUGAACGAGGAAUUCCCAGUAAGUGCGGGUCAUAAGCUUGCGUUGAUUAAGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGGAUGGUUUAGUGA-GGCCCUCGGACGGCCGCCCUGAGAAGACGGUCGAACUUGACUAUCUAGAGGAAGUAAAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUA-----
an.Ast.amu -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-------NNAA--------AGU-GAAACUGCGGACGGCUCAUUAAAUCAGUUAGGUUCCUUGGAGCGACAUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCAAAGCGCUUACGCGCCGAUCGCA--CGGUCUGCGGCG-ACG-GAUCCUUCGAAUGUCUGCCCUAUCAACUUGAUGGUACGUUAUGCGCCUACCAUGGUCGUAACGGGUACGGAGAAUCAGGGUUCGAUUCCGGAGAGGGAGCUUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCACUCC-GACAC-GGGGAGGUAGUGACGAAAAAUCAAUACAG-GACUCUUUCGAGCCGGUAAUUGAUGAGUACACUUUAAAUC------------------------------CUUAACGAGGAUCUAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAAUUGCUGCAGUUAAAAAGCUCGUAGUUGGGGC-GCAGCGU-----GGCGGUCCG-C---AAG--GCC---G---CACUC-------CCG---AUUAAGAGGGCUGAGGGGGCACGUAUUGCGGUGUGAGAGGUGAAAUUCUUGGAUCGCCGCAAGACGACCGACUGCGAAAGCAUGCCAAGAAUGUUUUAUU---AAUCAAGAACGAAAGUUAGAGGUUCGAAGGCGAUCAGAUACCGCCCUAGUUCUAACCAUAAACGAUGCCGACU--CGAUC-GCCGGUCCACGCGGCGGGCGUCUGCGGGAAACCA--AAGUCGGUUCCGGGGGAAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCCGGCCCGGACAA-GA---UUGA-------------------------U--UC--UGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACUCUGGCUUCUAAAUAGUCGCGCGCCG--CUGACUUCUUAGAGGGACAAGUGCGGUUCAGCCACGCGAGA-UU-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCGGGGC-GCACGCGCGCUACACUGAAGGGAUCAGCGGGCGCCUUGUCUGGAAGGCCUGGGCAAUCCGUGAACCCCCUUCGUGCUUGGGAUAGGGACUUGCAAUUGUCUCCCUUAAACGAGGAAUUCCCAGUAAGCGCAAGUCAUCAGCUCGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGUUUAGUGA-GAUCCUCGGAGGGCCUCUGCCGGAAGACCAUCGAACUUNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
an.Str.int -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-------NNNN--------CGACGAAACUGCGGAUGGCUCAUUAAAUCAGUUAGGUUCAUUGGAUCGACAUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCGUAGCGCUUCCGCGCCGAUCGCA--CGGUUUGCGGCG-ACG-GAUCCUUCGAAUGUCUGCCCUAUCAACUUGAUGGUACGUUAUGCGCCUACCAUGGUCGUCACGGGUACGGAGAAUCAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCACUCCCGACAC-GGGGAGGUAGUGACGAAAAAUCAAUACAG-GACUCUUUCGAGCCUGUAAUUGAUGAGUACACUUUAAAUC------------------------------CUUAACGAGGAUCCACUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAGUAGCGUAUAUUAAAGCUGUUGCAGUUAAAAAGCUCGUAGUUG-GGGCCCAGGC------UGCGGUCCG-C--CGUGU-GUG---U----ACUC-------A-G---AUUAAGAGGGCUGAGGGGGCACGUAUUGCGGUGUGAGAGGUGAAAUUCUUGGAUCGCCGCAAGACGAACGACUGCGAAAGCAUGCCAAGAAUGUUUUAUU---AAUCAAGAACGAAAGUUAGAGGUUCGAAGGCGAUCAGAUACCGCCCUAGUUCUAACCAUAAACGAUGCCGACUGACGAUCCGCCGGUCCCCGCGGCGGGCGUCUAAGGGAAACCA--AAGUCGGUUCCGGGGGAAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGAAAACUCACCCGGCCCGGACAA-GA---UUGA-------------------------U--UC--UGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACUCUGGCUUCUAAAUAGUUGCGCGCCG--UCAACUUCUUAGAGGGACAAGUGGCGUUUAGCCAGGCGAGA-UU-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCGGGGC-GCACGCGCGCUACACUGGCGGAAUCAGCGGGUGCCUUGGCCGGAAGGUCUGGGUAAUCCGUGAACCUCCUCCGUGAUGGGGAUAGGGAGUUGCAAUUAUCUCCCUUGAACGAGGAAUUCCCAGUAAGCGCGAGUCAUCAGCUCGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGUUUAGUGA-GAUCCUCGGACGUCGUUUGCGAGAAGACGAUCAAANNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
an.Cae.ele ----AUACCUGAUUGAUUCUGUCAGCGCG-AUAUGCUAAGU--AAAAAUAAGCCAUGCAUGCUUUGAUUCA-----------AA------------U-GAAAUUGCGUACGGCUCAUUAGAGCAGAUACACCUUAUCCGGGAAUAUGGAUAACUGCGGAAAUCUGGAGCUAAUACAUGCAAUACCCGCAAGGGUUUACUGU---CAGUUCGUGACU-CUA-UCCGGAAAGGGUGUCUGCCCUUUCAACUAGAUGGUAGUUUAUUGGACUACCAUGGUUGUUACGGGUACGGAGAAUAAGGGUUCGACUCCGGAGAGGGAGCCUUAGAAACGGCUACCACGUCCA-GGAAGGCAGCAGGCGCGAAACUUAUCCACUGUUG-AGU--AUGAGAUAGUGACUAAAAAUAAAGACUC-AUCC-UUUU-GG-GAGUUAUUUAUGAGUUGAAUACAAAUG------------------------------AUCUUCGAGUAGCAAGGAGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCUCCUAGUGUAUCUCGUUAUUGCUGCGGUUAAAAAGCUCGUAGUUGGGUU-CGUGCCGAGUUCGC------------AUU----------------UGCGU-CAAC-GU-GUUAAGAGGGCAAAGGGGGCACGUAUCAUUACGCGAGAGGUGAAAUUCGUGGACCGUAGUGAGACGCCCAACAGCGAAAGCAUGCCAAGAAUGUCUUAUU---AAUCAAGAACGAAAGUCAGAGGUUCGAAGGCGAUUAGAUACCGCCCUAGUUCUGACCGUAAACGAUGCCAUCUCGCGAUUCGG-AGUUUUCCUGCCGAGGGCUAUCCGGAAACGA--AAGUCGGUUCCGGGGGUAGUAUGGUUGCAAAGCUGAAACUUAAAGAAAUUGACGGAAGGGCACACAAGGCGUGGAGCUUGCGGCUUAAUUUGACUCAACACGGGAAAACUCACCCGGUCCGGACAC-UA---UUGA-------------------------U--CU--GGUGGUUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUUAUUCC-GAAACGAGCGAGACUCUAGCCUCUAAAUAGUUGGCGUUCG--AUAACUUCUUAGAGGGAUAAGCGGUGUUUAGCCGCACGAGA-UU-GAGCGAUAACAGGUCGUGAUGCCCUUAGUGUCCGGGGCUGCACGCGUGCUACACUGGUGGAGUCAGCGGGUUCCUAUGCCGAAAGGUAUCGGUAAACCGUGAAAUUCUUCCAUGUCCGGGAUAGGGUAUUGUAAUUAUUGCCCUUAAACGAGGAAUGCCUAGUAAGUGUGAGUCAUCAGCUCACGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUAUCCGGGACGAACUGAUUCGAGA-AGAGUGGGGAUGUCGUAACCGGAAACCAUUUUUAUCGCAUUGGUUUGAACCGGGUAAAAGUCGUAACAAGGUAGCUGUAGGUGAACCUGCAGCUGGAUCAUCG-----
an.Bra.pli -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNNNNNNNNNNNNNAUGCAUGUCUAAGUACAUACC-------AGCA--------GGU-GAAACCGCGAAUGGCUCAUUAAAUCAGUUAGGUUCCUUAGAUCGACAUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCAAAGCUCGUAUGAGCUGAUCGCA--UGGCUAGCGGCG-ACG-UAUCUUUCAAGUGUCUGCCCUAUCAACUUGAUGGUAAGCGAUUUGCCUACCAUGGUUGUAACGGGUACGGGGAAUCAGGGUUCGAUUCCGGAGAGGGAGCAUGAGAAACGGCUACCACAUCUC-GGAAGGCAGCAGGCGCGCAAAUUACCCACUCCUAGAAC-GGGGAGGUAGUGACGAAAAAUCAAUACCG-GACUCAAU-GAGCCGGUAAUUGAUGAGUACAGUUUAAAAC------------------------------CCUAACGAGGAUCUAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGUAUAGCAUGGGUACGC------------UUUU---------------GCUGU-U-AC-ACAAUUAAUAGGGCAGAGGGGGCACGUAUUGCGGUGUUAGAGGUGAAAUUCUUGGAUCGCCGCAAGACGAACAACUGCGAAAGCAUGCCAAGAAUGUUUUAUU---AAUCAAGAACGAAAGUUGGAGGUUCGAAGACGAUUAGAUACCGUCCUAGUUCCAACCAUAAACGAUGCCAACUAGCGAUUAGCUGCUUUUCACAGCUAGCGCUUCCGGGAAACCA--AAGUUGGUUCCGGGGGAAGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGUAGCCUGCG-CUUAAUUUGACUCAACACGGGAAAUCUCACCCGGCCCGGACAU-AA---UUGA-------------------------U--UC--GGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACUCUAGCCUCUAAAUAGUACGUCCUUUUGGGUACUUCUUAGAGGGACAAGUAGCGGUAAGCUACACGAAA-UU-GAGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCGGGGGCAUACGCGCGCUACACUGAAGGGAUAAGCGUGUUCCUGCUCCGAAAGGAGUGGGUAAUCCGUGAAA-CCCUUCGUGAUUGGGAUCGGGGCUUGAAAUUAUUCUCCGUGAACGAGGAAUUCCCAGUAAGCGCGAGUCAUAAGCUCGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGUUUAGUGA-GAUCUUCGGAUGGUCGCAACGAGAAGAUGAUCAAACUUGAUCAUUUAGAGGAAGUAAAAGUCGUAACAAGGUUUCCGUANNNNNNNNNNNNNNNNNNNNNNNN-----
fu.Sch.pom -----UACCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAGCAAU-----UGUA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUACGUUUAUUUGAUAGACUUGGAUAACCGUGGUAAUCUAGAGCUAAUACAUGCUAAAUCCUUUUGGACGAAUCGCA--UGGCUUGCGGCG-AUG-GUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGGCCUACCAUGGUUUUAACGGGUACGGGGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCCGACAC-GGGGAGGUAGUGACAAGAAAUCAAUGCAG-GGCCCUUUCGGGUUUGUAAUUGAUGAGUACAAUGUAAAUA------------------------------CCUAACGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGAGC-CUGGUCG-----ACUGGUCCG-CCG--AAGCGUG---UU--UACUG-------UCA--UAUUAAUAGGGUAGUGGGGGCACGUAUUCAAUUGUCAGAGGUGAAAUUCUUGGAUUUAUUGAAGACGAACUACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUAGGGGAUCGAAGACGAUCAGAUACCGUCGUAGUCUUAACCAUAAACUAUGCCGACUAGGGAUCGGGCAAUUUACUUGCUCGGCCCUUACGAGAAAUCA--AAGUCGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACAAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAA-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGCUUAAUUGC-GAAACGAACGAGACCUUAACCUCUAAAUAGCUGGAUUUU---UUAGCUUCUUAGAGGGACUAUUGGCAUAAAGCCAAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGACGGAGCCAACGAGUACCUUGGCCGGAAGGUCUGGGUAAUCUUUUAAACUCCGUCGUGCUGGGGAUAGAGCAUUGCAAUUAUUGCUCUUCAACGAGGAAUUCCUAGUAAGCGCAAGUCAUCAGCUUGCGUUGAAUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGCUUAGUGA-GGCCUCUGGAUGGCUGCAACGAGAAGUUGGACAAACUUGGUCAUUUAGAGGAAGUAAAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCAGAAGGAUCAUUA-----
fu.Asp.nid -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNNNNNNNNNNNNNNNNNNNNNNNAAGUAUAAGCAA------UAUA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUACGUUUAUUUGAUAGACAUGGAUACCUGUGGUAAUCUAGAGCUAAUACAUGCUAAACCCUUCGGGGCGAAUCGCA--UGGCUUGCGGCG-AUG-GUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUGGCAACGGGUACGGGGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAA-CC-GACAC-GGGGAGGUAGUGACAAUAAAUUGAUACGG-GGCUCUUUUGGGUUCGUAAUUGAUGAGAACAAUUUAAAUC------------------------------CCUAACGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGU-CUGGCUG-----GCCGGUCCG-C--CUCAC-GCG---AG--UACUG-------UC---CAUUAAUAGGGUAGUGGGGGCGAGUAUUCAGCUGUCAGAGGUGAAAUUCUUGGAUUUGCUGAAGACUAACUACUGCGAAAGCACGCCAAGGAUGUUUUAUU---AAUCAGGAACGAAAGUUAGGGGAUCGAAGACGAUCAGAUACCGUCGUAGUCUUAACCAUGAACUAUGCCGACUAGGGAUCGGGCGGUUUUCCCGCUCGGCCCUUACGAGAAAUCA--AAGUUGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGAAAUUGACGGAAGGGCACACAAGGCGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAA-AA---UUGA-------------------------U--UU--UUUGGAUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGCUUAAUUGC-GAAACGAACGAGACCUCGGCCCUUAAAUAGCCCGGUGUCC--CUGGCUUCUUAGGGGGACUAUCGCC-UCAAGCCGAUGGAAGUGCGCGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGACAGGGGCAGCGAGUCCCUUGGUCGAGAGGCCCGGGUAAUCUUUUAAACCCUGUCGUGCUGGGGAUAGAGCAUUGCAAUUAUUGCUCUUCAACGAGGAAUGCCUAGUAGGCACGAGUCAUCAGCUGCUGCCGAUUACGUCCCUGCCCUUUGUACACACCGCCUGUCGCUACUACCGAUGAAUGGCUCGGUGA-GGCCUCNGGAUGNCUGCAACGGAAAGCUGGUUAAACCCGNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
fu.Asp.tam -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNNNAAAAUAAGCCAUGCAUGUCUAAGUAUAAGCAC------UAUA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUACGUUUAUUUGAUAGACAUGGAUACCUGUGGUAAUCUAGAGCUAAUACAUGCUAAACCUUUCGGGGCGAAUCGCA--UGGCUUGCGGCG-AUG-GUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUGGCAACGGGUACGGGGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCCGACAC-GGGGAGGUAGUGACAAUAAAUUGAUACGG-GGCUCUUUUGGGUUCGUAAUUGAUGAGUACAAUCUAAAUC------------------------------CCUAACGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGU-CUGGCUG-----GCCGGUCCG-C--CUCAC-GCG---AG--UACUG-------UC---CAUUAAUAGGGUAGUGGGGGCGAGUAUUCAGCUGUCAGAGGUGAAAUUCUUGGAUUUGCUGAAGACUAACUACUGCGAAAGCACGCCAAGGAUGUUUUAUU---AAUCAGGAACGAAAGUUAGGGGAUCGAAGACGAUCAGAUACCGUCGUAGUCUUAACCAUAAACUAUGCCGACUAGGGAUCGGGCGGUAUGCCCGCUCGGCCCUUACGAGAAAUCA--AAGUUGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGAAAUUGACGGAAGGGCACACAAGGCGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAA-AA---UUGA-------------------------U--UU--UUUGGAUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGCUUAAUUGC-GAAACGAACGAGACCUCGGCCCUUAAAUAGCCCGGUGUUU--CUGGCUUCUUAGGGGGACUAUCGGC-UCAAGCCGAUGGAAGUGCGCGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGACAGGGCCAGCGAGUCCCUUGACCGAGAGGUCCGGGUAAUCUUUUAAACCCUGUCGUGCUGGGGAUAGAGCAUUGCAAUUAUUGCUCUUCAACGAGGAAUGCCUAGUAGGCACGAGUCAUCAGCUCGUGCCGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGCUCGGUGA-GGCCUUCGGAUGGCCGCAACGGAAAGUUGGUCAAACCCGGUCAUUUAGAGGAAGUAAAAGUCGUAACAAGGUUUCNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
fu.Neu.cra -----UACCUGGUUGAUUCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUUUAAGCA-------UAAA--------CGC-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUAUUUGAUAGACAUGGAUAACCGUGGUAAUCUAGAGCUAAUACAUGCUAAACCCUUCGGGGCGAAUCGCA--UGGCUUGUGGCG-AUG-GUUCAUUCAAAUUUCUGCCCUAUCAACUUGACGGCUGGGUCUUGGCCAGCCAUGGUGACAACGGGUACGGAGGGUUAGGGCUCGACCCCGGAGAAGGAGCCUGAGAAACGGCUACUACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCCGACAC-GGGGAGGUAGUGACAAUAAAUUGAUACAG-GGCUCUUUUGGGUUUGUAAUUGAUGAGUACAAUUUAAAUC------------------------------CCUAACGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGAGGUUAAAAAGCUCGUAGUUGGGGC-UCGGCC-----GU-CGGUCCG-C--CUCAC-GCG---UG--CACUA-------CU---GAUUAAUAGGGCAGUGGGGGCAAGUAUUCAAUUGUCAGAGGUGAAAUUCUUGGAUUUAUUGAAGACUAACUACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAGGAACGAAAGUUAGGGGAUCGAAGACGAUCAGAUACCGUCGUAGUCUUAACCAUAAACUAUGCCGAUUAGGGAUCGGACGGUUUUCCCGUUCGGCCCUUACGAUAAAUCA--AAAUGGGCUCCUGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGAAAUUGACGGAAGGGCACACCAGGGGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAG-GA---UUGA-------------------------U--UU--CGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGCUUAAUUGC-GAAACGAACGAGACCUUAACCUCUAAAUAGCCCGUAUUUG--CUGGCUUCUUAGAGGGACUAUCGGC-UCAAGCCGAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGACACAGCCAGCGAGCUCCUUGGCCGGAAGGUCCGGGUAAUCUUUUAAACUGUGUCGUGCUGGGGAUAGAGCAUUGCAAUUAUUGCUCUUCAACGAGGAAUCCCUAGUAAGCGCAAGUCAUCAGCUUGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGCUCAGUGA-GGCUUCCGGAUGGCCGCAACGGAAAGCUAUCCAAACUCGGUCAUUUAGAGGAAGUAAAAGUCGUAACAAGGUCUCCGUUGGUGAACCAGCGGAGGGAUCAUUA-----
fu.Can.gla -----UAUCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAGCAA------UAUA--------AGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUACGUUUAUUUGAUAGACAUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCUUAAUCUUCUUAGACGAAUCGCA--UGGCUUGUGGCG-AUG-GUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUUUCAACGGGUACGGGGAAUAAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUGACAC-AGGGAGGUAGUGACAAUAAAUCGAUACAG-GGCCCAUUCGGGUUUGUAAUUGAUGAGUACAAUGUAAAUA------------------------------CCUAACGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGAUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGC-CUGGGU-----AGCCGGUCCG-A--UUUUU-UCG---UG--UACUG------AAU--GCAUUAAUAGGGCGGUGGGGGCAAGUAUUCAAUUGUCAGAGGUGAAAUUCUUGGAUUUAUUGAAGACUAACUACUGCGAAAGCAUGCCAAGGACGUUUUAUU---AAUCAAGAACGAAAGUUAGGGGAUCGAAGAUGAUCAGAUACCGUCGUAGUCUUAACCAUAAACUAUGCCGACUAGGGAUCGGGUGGUUUACCCACUCGGCCCUUACGAGAAAUCA--AAGUCGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCG-CUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAA-AA---UUGA-------------------------U--UU--UGUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGCUUAAUUGC-GAAACGAACGAGACCUUAACCUCUAAAUAGUGGUGCAUUU--UCCACUUCUUAGAGGGACUAUCGGUUUCAAGCCGAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGCGUUCUGGGCCGCACGCGCGCUACACUGACGGAGCCAGCGAGUACCUUGGCCGAGAGGUCUUGGUAAUCUUUGAAACUCCGUCGUGCUGGGGAUAGAGCAUUGUAAUUAUUGCUCUUCAACGAGGAAUUCCUAGUAAGCGCAAGUCAUCAGCUUGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUAGUACCGAUGAAUGGCUUAGUGA-GGCCUCAGGACUGCUGCGAGGAGAAUCUGGUCAAACUUGGUCAUUUAGAGGAACUAAAAGUCGUAACAAGGUUUCCGUAGGUGAA-CUGCGGAAGGAUCAUUA-----
fu.Sac.cer -----UAUCUGGUUGAUCCUGCCAGUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAGCAA------UAUA--------AGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUACGUUUAUUUGAUAGACAUGGAUAACCGUGGUAAUCUAGAGCUAAUACAUGCUUAAUCUCUUUAGACGAAUCGCA--UGGCUUGUGGCG-AUG-GUUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGUGGCCUACCAUGGUUUCAACGGGUACGGGGAAUAAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCUAAUUC-AGGGAGGUAGUGACAAUAAAUCGAUACAG-GGCCCAUUCGGGUUUGUAAUUGAUGAGUACAAUGUAAAUA------------------------------CCUAACGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGC-CCGGUU-----GGCCGGUCCG-A--UUUUU-UCG---UG--UACUG-----AUUUC--CAUUAAUAGGGCGGUGGGGGCAGGUAUUCAAUUGUC-GAGGUGAAAUUCUUGGAUUUAUUGAAGACUAACUACUGCGAAAGCAUGCCAAGGACGUUUUAUU---AAUCAAGAACGAAAGUUAGGGGAUCGAAGAUGAUCUGGUACCGUCGUAGUCUUAACCAUAAACUAUGCCGACUAG--AUCGGGUGGUUUACCCACUCGGUCCUUACGAGAAAUCA--AAGUCGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACUAGGAGUGGAGCCUGCGGC-UAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAA-AA---UUGA-------------------------U--UU--UGUGGGUGGUGGUGCAUGGCCGUUCUCAGUUGGUGGAGUGAUUUGUCUGCUUAAUUGC-GAAACGAACGAGACCUUAACCUCUAAAUAGUGGUGCAUUU--UCCACUUCUUAGAGGGACUAUCGGUUUCAAGCCGAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGCGUUCUGGGCCGCACGCGCGCUACACUGACGGAGCCAGCGAGUACCUUGGCCGAGAGGUCUUGGUAAUCUUUGAAACUCCGUCGUGCUGGGGAUAGAGCAUUGUAAUUAUUGCUCUUCAACGAGGAAUUCCUAGUAAGCGCAAGUCAUCAGCUUGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUAGUACCGAUGAAUGGCUUAGUGA-GGCCUCAGGACUGCUGCAAGGAGAAUUUGGACAAACUUGGUCAUUUAGAGGAACUAAAAGUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUA-----
fu.Bul.hui -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-NNNNNCAAAAUAAGCCAUGCAUGUCUAAGUAUAAACAAA-----CAUA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUAUUUGAUGGACAUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCUGAGCCCUCU-GGGCGAAUCGUA--UGGCUUGCGACG-AUG-CUUCAUUCAAAUAUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGGCCUACCAUGGUAUCAACGGGUACGGGGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCCGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACAG-GGCUCUAUUGGGUUUGUAAUUGAUGAGUACAAUUUAAAUC------------------------------CCUAACGAGGAACAACUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAGUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUCGGGGC-CCGGCGG-----GACGGUCCG-C---CUUAGGUG---UG--UACUU-----CU-----UAUUAAUAGGGCGGUGGGGGCAAGUAUUCCGUUGCUAGAGGUGAAAUUCUUAGGUUUACGGGAGACUAACUACUGCGAAAGCAUGCCAAGGACGUUUUAUU---GAUCAAGAACGAAGGUUAGGGGAUCAAAAACGAUUAGAUACCGUUGUAGUCUUAACAGUAAACUAUGCCGACUAGGGAUCGGUUCCAAUAAGGAAUCGGCCCUUACGAGAAAUCA--AAGUCGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGUGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAA-GA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACCUUAACCUCUAAAUAGCCCGGCUUUG--AUGGCUUCUUAGAGGGACUAACGGCGUUUAGCCGUUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGACUGAGCCAGCGAGUCCCUUGGCCGAGAGGUCUGGGUAAUCUUUGAAACUCAGUCGUGCUGGGGAUAGAGCAUUGCAAUUAUUGCUCUUCAACGAGGAAUACCUAGUAAGCGUGAGUCAUCAGCUCGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGCUUAGUGA-GAUCUCCGGAUGGCGGCAAUGAGAAGUUGAUCAAACUUGGUCAUUUAGAGGAAGUAAAAGUCGUAACAAGGUUNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
fu.Den.sul -----NNNNNNNNNNNNNNNNNNNNUAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAACAAG-----UGUA--------UGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUAUUUGAUGGACAUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCAAAGCCCUCGCGGGCGAAUCGCA--UGGCUUGCGGCG-AUG-CUUCAUUCAAAUAUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGGCCUACCAUGGUUUCAACGGGUACGGGGAAUAAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCCGACAC-GGGGAGGUAGUGACAAUAAAUCAAUAUAG-GGCUCUUUUGGGUUUAUAAUUGAUGAGUACAAUUUAAAUC------------------------------UCUAACGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGAGAC-CUGGCCG-----GGCGGUCUG-CC--UCACGGUA---UG--UACUU--------C---UAUUAAUAGGGUAGUGGGGGCAAGUAUUCAGUUGCUAGAGGUGAAAUUCUUGGAUUUACUGAAGACUAACUACUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAGGUUAGGGGAUCGAAAACGAUCAGAUACCGUUGUAGUCUUAACAGUAAACUAUGCCGACUAGGGAUCGGGCGAUCUUGUCGCUCGGCCCUUACGAGAAAUCA--AAGUCGGUUCUGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGAGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAG-UA---UUGA-------------------------A--UU--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACCUUAACCUCUUAAUAGCCAGGCUUUU--CCGGCUUCUUAGAGGGACUGUCUGCGUCUAGCAAACGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGACAGAGCCAGCGAGCACCUUGGCCGGAAGGUCUGGGUAAUCUUUGAAACUCUGUCGUGCUGGGGAUAGAGCAUUGCAAUUAUCGCUCUUCAACGAGGAAUUCCUAGUAAGCGUGAGUCAUCAGCUCGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGCUUAGUGA-GGUCUUGGGAUGGCUGCAAUGAGAACUUGAUCAAACUUGGUCAUUUAGAGGAA-UAAAA-UCGUAACAAGG-UUCC-UAGNNNNNNNNNNNNNNNNNNNNNNN-----
fu.Fel.oga -----NNNNNNNNNNNNNNNNNNNNNAGUCAUAUGCU-UGUCUCAAAAUAAGCCAUGCAUGUCUAAGUAUAAACAAA-----CAUA--------GGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUAUUUGAUGGACAUGGAUAACUGUGGUAAUCUAGAGCUAAUACAUGCUGAGCCCUCU-GGGCGAAUCGCA--UGGCUUGCGGCG-AUG-CUUCAUUCAAAUAUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGACCUACCAUGGUAUCAAC-GGUACGGGGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCCGACAC-GGGGAGGUAGUGACAAUAAAUCAAUACAG-GGCUCUAAUGGGUUUGUAAUUGAUGAGUACAAUUUAAAUC------------------------------CCUAACGAGGAACAACUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAGUACCGUAUAUUAAAGUUGUUGCAGUUAAAACGCUCGUAGUCGGGGC-CUGGCGG-----GGUGGUCCG-CC--UUACGGUG---UG--UACUU--------C---CAUUAAUAGGGCGGUGGGGGCAAGUAUUCCGUUGCUAGAGGUGAAAUUCUUAGAUUUACGGAAGACUAACUUCUGCGAAAGCAUGCCAAGGACGUUUUAUU---GAUCAAGAACGAAGGUUAGGGGAUCAAAAACGAUUAGAUACCGUUGUAGUCUUAACAGUAAACUAUGCCGACUAGGGAUCGG-CCA-UUCCUG-CUCGGCCCU-ACGAG-AAUCA--AAGUCGGUUCUGGGGG-AGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGUGUGGAGCCUGCGGCUUAAUUUGACUCAACACGGGGAAACUCACCAGGUCCAGACAA-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGCCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACCUUAACCUCUAAAUAGUCAGGCUCCG--UCGACUUCUUAGAGGGACUGUCGGCGUUUAGCCGACGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGACCGCACGCGCGCUACACUGACUGAGCCAGCGAGUCCCUUGUCCGAGAGGUCUGGGUAAUCUUUG-AA-UCAGUCGUGCUG-GGAUAGAGCAUUGCAAUUAUUGCUCUUCAACGAGGAAUACCUAGUAAGCGUGAGUCAUCAACUCGCGUUGAUUACGUCCCUGCCCUUUGUACACACCGUCUGUCGCUACUACCGAUGAAUGGCUUAGUGA-GGUCUCCGGAUGGCAGCAAUGGGAAGUUGAACAAACUUGGUCAUUUAGAGGAAGUAAAAGUCAUAACAAGGUUUCCGUANNNNNNNNNNNNNNNNNNNNNNNN-----
fu.Gig.mar -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNCU-UGUCUCAAAAUAAGCCAUGCAUGUCU-AGUAUAAUCG-------AUAC--------GGU-GAAACUGCGAAUGGCUCAUUAAAUCAGUUAAGUUUAUUUGAUAGACUUGGAUAACCGUGGUAAUCUAGAGCUAAUACAUGCUAAAUCCUCU-GGACGAAUCGUA--UGGCUUGUGACG-AUG-UAUCAUUCAAAUUUCUGCCCUAUCAACUUGAUGGUAGGAUAGAGGCCUACCAUGGUUUUAACGGGUACGGGGAAUUAGGGUUCGAUUCCGGAGAGGGAGCCUGAGAAACGGCUACCACAUCCA-GGAAGGCAGCAGGCGCGCAAAUUACCCAAUCCCGAUAC-GGGGAGGUAGUGACAAUAAAUCAAUACAG-GGCUCUUAUGGGUUUGUAAUUGAUGAGUACAAUUUAAAUC------------------------------UCUAACGAGGAACAAUUGGAGGCAAGUCUGGUGCCAGCAGCCGCGGUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCUCGUAGUUGGGGG-UUCUACC-----GUUGGUCGG-GC--AAUUGUCU----G--UACUGC------G----UAUUAAUAGGGUAGUGGGGGCAAGUAUUCAAUUGUCAGAGGUGAAAUUCUUGGAUUUAUUGAAGACUAACUUCUGCGAAAGCAUGCCAAGGAUGUUUUAUU---AAUCAAGAACGAAAGUUAGGGGAUCGAAGACGAUCAGAUACCGUCGUAGUCUUAACCAUAAACUAUGCCGACUAGGGAUCGGACGAUUUUCUCGUUCGGC-CUUACGGGAAACCA--AAGUGGGUUCCGGGGGGAGUAUGGUCGCAAGGCUGAAACUUAAAGGAAUUGACGGAAGGGCACACCAGGGGUGGACCGUGCGGCUUAAUUUGACUCAACACGGGAAAACUCACCAGGUCCAGACAA-AA---UUGA-------------------------U--UC--UAUGGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGUGAUUUGUCUGGUUAAUUCC-GAAACGAACGAGACCUUAACCUCUAAAUAGUCAGGCUUUU--ACGACUUCUUAGAGGGACUAUCGGCGUUUAGCCGAUGGAAGUUUGAGGCAAUAACAGGUCGUGAUGCCCUUAGUGUUCUGGGCCGCACGCGCGCUACACUGAUGAAGUCAUCGAGUUCCUUUACCGGAAGGUAUGGGUAAUCUUUGAAACUUCAUCGUGAUGGGGAUAGAGCAUUGCAAUUAUUGCUCUUCAACGAGGAAUCCCUAGUAAGCAUGAGUCAUCAGCUCGUGCUGAUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUACCGAUGAAUGGCUUAGUGA-GACCCUCGGACGAUAUCACUGAGAAGUUGGUCAAACUUGGUCAUUUAGAGGAAGUAAAAGUCGUAACAAGGUUUCCGUNNNNNNNNNNNNNNNNNNNNNNNNN-----
fl.Bac.spl NCUAUGAAGAGUUUGAUCCUGGCUCAGGAUNAACGCUAGCGACAGGCUUAACACAUGCAAGUCGAGGGGCAUCAUGAGGUA-GCAA-UACCUUGAUGGCGACCGGCGCACGGGUGCGUAACGCGUAUGAACCUGCCUGAUACCGGGGUAUAGCCCAUGGAAACGUGGAUUAACACCCCAUAGUACUGCAUAGUUAAAU---------GUUY------AAGGUAUCGGAUGGGCAUGCGUCCUAUUAGUUAGUUGGCGGGGUAACAGCCCACCAAGACGAUGAUAGGUAGGGGUUCUGAGAGGAAGGUCCCCCACAUUGGAACUGAGACACGGUCCAAACUCCUACGGGAGGCAGCAGUGAGGAAUAUUGGUCAAUGGACGUAAGUCUGAACCAGCCAAGUCGCGUGAGGGAAGACUGCCUNUGGGUUGUAAACCNCUUUUAUAAGGGAAGAAUAAGUUCUA--CGUG----UAGAAUGAUGCCUGUACCUUAUGAAUAAGCAUCGGCUNACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGAUGCGAGCGUUAUCCGGAUUUAUUGGGUUUAAAGGGUGCGUAGGCGGUUUAUUAAGUUAGUGGUUAAAUAUUUGAGCUCAACUC-AAUUGUGCCAUUAAUACUGGUAAACUGGAGUACAGGCGAGGUAGGCGGAAUAAGUUAAGUAGCGGUGAAAUGCAUAGAUAUAACUUAGAACUCCGAUUGCGAAGGCAGCUUACCAGACUGUAACUGACGCUGAUGCACGAGAGCGUGGGUAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGCUCACUNGUUCUSUGCGA-UAUA--UUGUACGGGAUUAAGCGAAAGUAUUAAGUGAGCCACCUGGGGAGUACGUCGGCAACGAUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGAGGAACAUGUGGUUUAAUUCGAUGAUACGCGAGGAACCUUACCUGGGUUUAAA-UGAAAUGCCGUAUUUGGAAACAGAUAUUCUC-UUCG-GAGCUUUUUCR-AGGUGCUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUCGGGUUAAGUCCCAUAACGAGCGCAACCCUUACCGUUAGUUGCUAGCAUAAUG-AUGAGCACUCUAACGGGACUGCCACCGUAA-GGUGGAGGAAGGCGGGGAUGACGUCAAAUCAGCACGGCCCUUACACCCAGGGCUACACACGUGUUACAAUGGCCGGUACAGAGGGCCGCUACCAGGUGACUGGAUGCCAAUCUC-AAAAGCCGGUCGUAGUUCGGAUUGGAGUCUGUAACCCGACUCCAUGAAGUUGGAUUCGCUAGUAAUCGCGCAUCAGCCUGGCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCAAGCCAUGGAAGCCGGGGGUGCCUGAAGUCCGUAACC-----GCGA----GGAUCGGCCUAGGGCAAAACUGGUAACNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
fl.Cyt.mar ACGAUGAAGAGUUUGAUCCUGGCUCAGGAUNAACGCUAGCGGCAGGCCUAACACAUGCAAGUCGAACGGUAACAGGGAAAAGCUUGCUUUUCUGCUGACGAGUGGCGCACGGGUGCGUAACGCGUAUGAAUCUGCCUUGUACUGGAGUAUAGCCCAGGGAAACUUGGAUUAAUCCUCCAUAGUCUAGCAUUAGUAAAG---------GUUA-------CGGUACAAGAUGAGCAUGCGUCCUAUUAGCUAGUAGGUGUGGUAACGGCACACCUAGGCAACGAUAGGUAGGGGUCCUGAGAGGGAGAUCCCCCACACUGGUACUGAGACACGGACCAGACUCCUACGGGAGGCAGCAGUGAGGAAUAUUGGACAAUGGGCGCAAGCCNNAUCCAGCCAUGCCGCGUGCAGGAAGACUGCCUAUGGGUUGUAAACUNCUUUUAUACGGGAAGAAUAAGGUCUA--CGAG----UAGGCUGAUGACGGUACCGUAAGAAUAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGNNNAUACGGAGNGUGCNAGCGUUAUCCGGAAUCAUUGGGUUUAAAGGGUCCGUAGGUGGACUAAUAAGUCAGUGGUGAAAGUCUGCAGCUUAACUGUAGAAUUGCCAUUGAUACUGUUAGUCUUGAAUUGUUAUGAAGUAACUAGAAUAUGUAGUGUAGCGGUGAAAUGCAUAGAUAUUACAUAGAAUACCGAUUGCGAAGGCAGGUUACUAAUAAUAYAUUGACACUGAUGGACGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGGUUACUAGCUGUCCGGCCCAUUGAGGGCUGGGUGGCCAAGCGAAAGUGAUAAGUAACCCACCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGGCCNGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGAUACGCGAGGAACCUUACCAGGGCUUAAA-UGGUCUGACAGGAGUGGAAACAUUCUUUUC--UUCG--GACGAUUACA-AGGUGCUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUCAGGUUAAGUCCUAUAACGAGCGCAACCCCUGUGGUUAGUUGCCAUCGAAAUG-UCGGGAACUCUAGCCAGACUGCCAGUGCAA-ACUGGAGGAAGGUGGGGAUGACGUCAAAUCAUCACGGCCCUUACGUCCUGGGCCACACACGUGCUACAAUGGUAGGUACAGAGAGCAGCCACUUUGCAAAGAGGAGCGAAUCUA-UAAAACCUAUCACAGUUCGGAUCGGGGUCUGCAACUCGACCCCGUGAAGCUGGAAUCGCUAGUAAUCGCAUAUCAGCCUGAUGCGGUGAAUACGUUCCCGGGCNUUGUACACACCGCCCGUCAAGNCAUGGAAGCNNGGGGUACCUGAAGUCCGUCACC-----GUAA----GGAGCGGCCUAGGGUAAGACCGGUAACUGGGGCNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
fl.Fla.xan -----NNNNNNNNNNNNNNNNNNNNNNNNNNAACGCUAGCGGCAGGCUUAACACAUGCAAGUCGAGGGGUAUAGUUC-----UUCG-----GAAUUAGAGACCGGCGCACGGGUGCGUAACGCGUAUGAAUCUACCUUUCACAGAGGGAUAGCCCAGAGAAAUUUGGAUUAAUACCUUAUAGUAUAGCAUUAUUAAAGA--------UUUA------UCGGUGAAAGAUGAGCAUGCGUCCCAUUAGUUAGUUGGUAAGGUAACGGCUUACCAAGGCAACGAUGGUUAGGGGUCCUGAGAGGGAGAUCCCCCACAUUGGUACUGAGACACGGACCAGACUCCUACGGGAGGCACCAGUGAGGAAUAUUGGACAAUGGGCGCAAGCCUGACCCAGCCAUGCCGCGUGCAGGAUGACGGUCUAUGGAUUGUAAACUGCUUUUAUACAGGAAGAAACAGUUCUA--CGUG----UAGAACCUUGACGGUACUGUAAGAAUAAGGAUCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGAUCCCAAGCUUAUCCGGAAUCAUUGGGUUUAAAGGGUCCGUAGGCGGUCAGAUAAGUCAGUGGUGAAAGCCCAUCGCUCAACGGUGGAACGGCCAUUGAUACUGUCUGACUUGAAUUAUUAGGAAGUAACUAGAAUAUGUAGUGUAGCGGUGAAAUGCUUAGAGAUUACAUGGAAUACCAAUUGCGAAGGCAGGUUACUACUAAUAUAUUGACGCUGAUGGACGAAAGCGUGGGUAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGGAUACUAGCUGUUGGGC--GCAA---GUUCAGUGGCUAAGCGAAAGUGAUAAGUAUCCCACCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGAUACGCGAGGAACCUUACCAAGGCUUAAA-UGGAUUGACCGGUUUGGAAACAGACUUUUC--GCAA--GACAUUUACA-AGGUGCUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUCAGGUUAAGUCCUAUAACGAGCGCAACCCCUGUUGUUAGUUGCCAGCGACAAG-UCGGGAACUCUAACAAGACUGCCAGUGCAA-ACUGGAAGAAAGUGGGGAUGACGUCAAAUCAUCACGGCCCUUACGCCUUGGGCUACACACGUGCUACAAUGGCCGGUACAGAGAGCAGCCACUGGGCGAGCAGGAGCGAAUCUA-UAAAACCGGUCACAGUUCGGAUCGGAGUCUGCAACUCGACUCCGUGAAGCUGGGAUCGCUAGUAAUCGCAGAUCAGCCUGAUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCAAGCCAUGGAAGCUGGGGGUGCCUGAANUCGGUAACC-----GCAA----GGAGCUGCCUANGGUAAAACUGGUAACUAGGGCUAAGUCGUAACAAGGUANCCNUANNNNNNNNNNNNNNNNNNNNNNNN-----
fl.Mar.psy -----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNGNCCUAAUACAUGCAAGUCGAGGGGUGGCCAGUGUC--CCGN----GNUACAGNNCACCGGCGCACGGGUGNGUAACGCAUAUAAAUCUACCUCGUACUGAGGGAUAACCCACAGAAAUAUGGNUUAAUACCUCAUANUAUAGCCUGAUCAAAG---------UUCG-------CGGUACAAGAUGAGUAUGCGUUCUAUUAGCUAGAUGGUGGGGUAACGGCUCACCAUGACAGCGAUAAAUAGGGGCCCUGAGAGGGGGAUCCCCCACACUGGUACUGAGACACGGACCAGACUCCUACGGGAGGCAGCAGUGAGGAAUAUUGGACAAUGGGCGAGAGCCUGAUCCAGCCAUGCCGCGUGCAGGANGACUGCCUAUGGGUUGUAAACUGCUUUUAUACAGGAAGAAACCCCUCCA--CNUG----UG-AGGAUUGACGGUACNGUAGGAAUAAGGAUCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGAUCCAAGCGUUAUCCGGAAUCAUUGGGUUUAAAGGGUCCGUAGGCGGGACAAUCAGUCAGCGGUGAAAGUCUGUGGCUCAACCAUAGAAUUGCCAUUGAUACUGUUGUUCUUGAAUACUUAUGAAGUGGUUGGAAUAUGUAGUGUAGCGGUGAAAUGCAUAGAUAUUACAUAGAACACCUAUUGCGAAGGCAGGUCACUAAUAAGACACUGACGCUGAUGGACGAAAGCGUGGGUAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGGUUACUAGCUGUUCGGGA-UUCG--GACUGAGUGGCUAAGCGAAAGUGAUAAGUAUUCCACCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGGNCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGAUACGCGAGGAACCUUACCAGGGCUUAAA-UGUAUUGACAGGUUUAGAGAUAUACUUUUC--UUCG--GACAUUUACA-AGGUGCUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUUAGGUUAAGUCCUAUAACGAGCGCAACCCCUGUUGUUAGUUGCCAGCGGAAUG-UCGGGAACUCUAACAAGACUGCCCGUGCAA-ACUGGAGGAAGGUGGGGAUGACGUCAAAUCAUCACGGCCCUUACGUCAUGGGCUACACACGUGCUACAAUGGUAGGGACAGAGAGCAGCCACUUGGCGAGAAGGAGCGAAUCUA-UAAACCCUAUCACAGUUCGGAUCGGAGUCUGCAACUCGACUCCGUGAAGCUGGAAUCGCUAGUAAUCGCAUAUCAGCCUGAUNCGGUGAAUACGUUCCCGGACCUUGUACACACCGCCCGUCAAGCCAUGGAAGCCGGGAGUGCCUGAAGUCCAUCACC-----GCAA----GGAGCGGCCUAGGGUAAGAUCCGUGACUAGGGNNAAGUCGUAACAAGGUANNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
fl.Pre.eno -----NNNNNNNNNNNNNNNNNNNNNNGAUGAACGCUAGCUACAGGCCUAACACAUGCAAGUCGAGGGGCAUCA-UGAUGAUCUUGAUCGUU-GAUGGCGACCGGCGCACGGGUGAGUAACGCGUAUCAACCUACCCAUGACUAAGGGAUAACCCGUCGAAAGUCGGCCUAAGACCUUAUGUAAUCGCAUGAUGAAAGA--------UUAA------UUGGUGAUGGAUGGGGAUGCGUCUGAUUAGCUUGUCGGUGAGGUAACGGCUCACCGAGGCAACGAUCAGUAGGGGUUCUGAGAGGAAGGUCCCCCACAUUGGAACUGAGACACGGUCCAAACUCCUACGGGAGGCAGCAGUGAGGAAUAUUGGUCAAUGGACGAUAGUCUGAACCAGCCAAGUAGCGUGCAGGAUGACGGCCUAUGGGUUGUAAACUGCUUUUAUGCGGGGAUAAAGUGAGGGA--CGUG----UCCCUCAUUGCAUGUACCGCAUGAAUAAGGACCGGCUAAUUCCGUGCCAGCAGCCGCGGUAAUACGGAAGGUCCAGGCGUUAUCCGGAUUUAUUGGGUUUAAAGGGAGCGUAGGCUGCCGUUUAAGCGUGUUGUGAAAUGUACCGGCUCAACCGGUGAUGUGCAGCGCGAACUGGAUGGCUUGAGUACGAAGAGGGAAUGCGGAACUCGUGGUGUAGCGGUGAAAUGCUUAGAUAUCACGAGGAACUCCGAUCGCGAAGGCAGCAUUCCGUUUCGUGACUGACGCUGAUGCUCGAAAGUGCGGGUAUCGAACAGGAUUAGAUACCCUGGUAGUCCGCACGGUAAACGAUGGAUGCUCGCUGUUGGAUA-UUUU--UAUUCAGUGGCUAAGUGAAAGCAUUAAGCAUCCCACCUGGGGAGUACGCCGGCAACGGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACNAGCGGAGGAACAUGUGGUUUAAUUCGAUGAUACGCGAGGAAC-UUACCCGGGCUUGAA-UUAGAGGAAAGAUCCAGAGAUGGUGAUGCCC-UUCG-GGGUUCUGUGA-AGGUGCUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUCGGCUUAAGUGCCAUAACGAGCGCAACCCUUUUCCUUAGUUGCCAUCGGCAAG-CCGGGCACUCUGAGGAUACUGCCUCCGCAA-GGAGGAGGAAGGUGGGGAUGACGUCAAAUCAGCACGGCCCUUACGUCCGGGGCUACACACGUGUUACAAUGGCGCGUACAGAGAGCUGGGUUUGCGCAAGCACUCUCAAAUCUU-UAAAACGCGUCUCAGUUCGGACCGGGGUCUGCAACCCGACCCCGCGAAGCUGGAUUCGCUAGUAAUCGCGCAUCAGCCUGGCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCAAGCCAUGAAAGCNGGGGGCGCCUGAAGUCCGUGACC-----GCAA----GGAUCGGCCUAGGCGAGACCCGGUGAUUNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN-----
fu.Fus.gon CGAACGAAGAGUUUGAUCCUGGCUCAGGAUGAACGCUGACAGAAUGCUUAACACAUGCAAGUCG-ACUCGAGUC--------UUCG--------GACUUGGGUNGCGGACGGGUGAGUAACGCGUAAAAACUUGCCUCAUAGUCUGGGACAACAUCUGGAAACGGAUGCUAAUACCGGAUAUUAUGGCAUUAUGAAAGC--------UAUA-----UGCGCUAUGAGAGAGCUUUGCGUCCCAUUAGCUAGUUGGUGAGGUAACGGCCCACCAAGGCGAUGAUGGGUAGCCGGCCUGAGAGGGUUAACGGCCACAAGGGGACUGAGACACGGCCCNUACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGACCAAAGUCUGAUCCAGCAAUUCUGUGUGCACGAUGACGUUUUUCGGAAUGUAAAGUGCNUUCAGUCGGGAAGAAGC---------AAGU-------------GACGGUACCGACAGAAGAAGCGACGGCUAAAUACGUGCCAGCAGCCGCGGUAAUACGUAUGUCGCNAGCGUUAUCCGGAUUUAUUGGGCGUAAAGCGCGUCUAGGCGGCAAGGAAAGUCUGAUGUGAAAAUGCGGGGCUCAACUCCGUAUU-GCGUUGGAAACUGCCUUNCUAGAGUNCUGGAGAGGUAGGCGGAACUACAAGUGUAGAGGUGAAAUUCGUAGAUAUUUGUAGGAAUGCNNAUGGGGAAGCCAGCCUACUGGACAGAUACUGACGCUAAAGCGCNAAAGCGUGGGUAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCUGUAAACGAUGAUUACUAGGUGUUGGGG--GUCA-AACCUCAGCGCCNAAGCUAACGCGAUAAGUAAUCCGCCUGGGGAGUACGUACGCAAGUAUGAAACUCAAAGGAAUUGACGGGGACCNGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGANNNAACGCGAGGAACCUUACCAGCGUUUGACAUCCUACAAAGAGUGCAGAGAUGCGCUUGUGCUUUCGAGAAUGUAGUGACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUAUCGUAUGUUACCAGCCUUUAG-UUGGGGACUCAUGCGAUACUGCCUGCGACGAGCAGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGCCCCUUAUACGCUGGGCUACACACGUGCUACAAUGGGUAGUACAGAGAGCGGCGAACCCGCGAGGGGGAGCAAAUCUCAGAAAACUAUUCUUAGUUCGGAUUGUACUCUGCAACUCGAGUACAUGAAGUUGGAAUCGCUAGUAAUCGCAAAUCAGCAUGUUGCGGUGAAUACGUUCUCGGGUCUUGUACACACCGCCCGUCACACCACGAGAGUUGGUUGCACCUGAAGUAGCAGGCCUAACCGUAAGGAAGGAUGCUCCGAGGGUGUGGUUAGCGANUGGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
fu.Fus.nul -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-mmmmmmmmmmmmmmm--mmmm--mmmmmmmmmmmGGGUGGCGGACGGGUGAGUAACGCGUAAAAACUUGCCUCACAGCUAGGGACAACAUUUAGAAAUGAAUGCUAAUNCCUNAUAUUAUGGCAUUAUGAAAGC--------UAUA-----AGCACUGUGAGAGAGCUUUGCGUCCCAUUAGCUAGUUGGAGAGGUAACAGCUCACCAAGGCGAUGAUGGGUAGCCGGCCUGAGAGGGUGAACGGCCACAAGGGGACUGAGACACGGCCCNNNCUCCUACGGGAGGCNGCAGUGGGGAAUAUUGGACAAUGGACCGAGGUCUGAUCCAGCAAUUCUGUGUGCACGAUGAAGUUUUUCGGAAUGUAAAGUGCUUUCAGUUGGGAAGAAAG---------AAAU-------------GACGGUACCAACAGAAGAAGUGACGGCUAAAUACGUGCCAGCAGCCGCGGUAAUACGUAUGUCACGAGCGUUAUCCGGAUUUAUUGGGCGUAAAGCGCGUCUAGGUGGUUAUGUAAGUCUGAUGUGAAAAUGCAGGGCUCAACUCUGUAUU-GCGUUGGAAACUGUAUAACUAGAGUACUGGAGAGGUAAGCGGAACUACAAGUGUAGAGGUGAAAUUCGUAGAUAUUUGUAGGAAUGCCGAUGGGGAAGCCAGCUUACUGGACAGAUACUGACGCUAAAGCGCGAAAGCGUGGGUAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAUUACUAGGUGUUGGGG--GUCG-AACCUCAGCGCCCAAGCUAACGCGAUAAGUNAUCCGCCUGGGGAGUACGUACGCAAGUAUGAAACUCAAAGGAAUUGACGGGGAC-CGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGACGNAACGCGAGGAACCUUACCAGCGUUUGACAUCUUAGGAAUGAGAUAGAGAUNUUUCAGUGUCUUCGGAAACCUAAAGACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUNUCGUAUGUUACCAUCAUUAAG-UUGGGGACUCAUGCGAUACUGCCUNCGAUGAGUAGGAGGAAGGUGGGGAUGACGUNNAGUCAUCAUGCCCCUNAUACGCUGGGCUACACACGUGCUACAAUGGGUAGAACAGAGAGUUGCAAAGCCGUGAGGUGGAGCUAAUCUCAGAAAACUNUUCUUAGUUCGGAUUGUACUCUGCAACUCGAGUACAUGAAGUUGGAAUCGCUAGUAAUCGCGAAUCAGCAUGUCGCGGUGAAUACGUUCUCGGGUCUUGUACACACCGCCCGUCACACCACGAGAGUUGGUUGCACCUGAAGUAGCAGGCCUAACCGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
fu.Lep.buc -----mmmmmmmmmmAUCCUGGCUCAGGAUGAACGCUGACAGAAUGCUUAACACAUGCAAGUCUUUGGC--RAAUCUGUG--CUUG--CACAGCCUAGC-CAAGGCGGACGGGUGAGUAACGCGUAAAAACUUGCCCUGCAGACAGGGAUAACAGACGGAAACGACUGAUAAUACCUGAUAYAAUUGCAUAAUGAAAA---------GUGA-------UGCUGCAGGAGAGCUUUGCGUCCUAUUAGCUUGUUGGUGAGGUAANGGCUCACCAAGGCGAUGAUAGGUAGCCGGCCUGAGAGGGUGAACGGCCACAAGGGGACUGAGAUACGGCCCUUACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGGGCANCCCUGAUCCAGCAAUUCUGUGUGCACGAAGAAGGUUUUCGGAUUGUAAAGUGCUUUCAGCAGGGAAGAAGA---------AAGU-------------GACGGUACCUGCAGAAGAAGCGACGGCUAAAUACGUGCCAGCAGCCGCGGUAAUACGUAUGUCGCAAGCGUUAUCCGGAAUUAUUGGGCAUAAAGGGCAUCUAGGCGGCCAGACAAGUCUGGGGUGAAAACUUGCGGCUCAACCGCAAGCCUGCCCUGGAAACUGUUUGGCUAGAGUGCUGGAGAGGUGGACGGAACUGCACGAGUAGAGGUGAAAUUCGUAGAUAUGUGCAGGAAUGCCGAUGAUGAAGAUAGUUCACUGGACGGNAACUGACGCUGWAGUGCGVAARCUGGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCCACCCGUAAACGAUGAUUACUGGGUGUGGGCAU-GAAG-AGUGUCCGUGCCGAAGCUAAUGCGAUAAGUAAUCCGCCUGGGGAGUACGKCCGCAAGGCUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGACGCAACGCGAGGAACCUUACCAGAUCUUGACAUCCUACGAAUGCCUGUGAGAACAGGCAGUGCCUUCGGGAACGUWGAGACAGGUGGUGCAUGGCUGUCGACAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUAUCGCUAGUUGCCAUCAUUAAG-UUGGGGACUCUAGCGAGACUGCCUGCGAAGAGCAGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGCCCCUUAUGAUCUGGGCUACACACGUGCUACAAUGGCCGGNACAAAGAGCUGCAAAACGGUAACGUUUAGCCAAUCUU-UAAAGCCGGUCCAAGUUCGGAUUGAAGUCUGCAACUCGACUUCAUGAAGCCGGAAUCGCUAGUAAUCGCAGAUCAGCAUGCUGCGGUGAAUACGUUCUCGGGUCUUGUACACACCGCCCGUCACACCACGAGAGUUGUUUGNACCUGAAGCCGCCGGUCCAACCGUAAGGAGGAAGGCGUCUAAGGUGUGGAUAGUGAUUGGGGUGAAGUCGUAACAAGGUAAGUCGmmmmmmmmmmmmmmmmmmmmmmmmm-----
fu.Lep.mic -----mmmmmmmmmmmmmmmGGCUCAGGAUAAACGCUGACAGAAUGCUUAACACAUGCAAGUCG-AUGAUGGGAGCUAG---CUUG---CUAGAAGAAGUCAUGGCGGACGGGUGAGUAACGUGUAAAAACUUACCAUAUAGACUGGGAUAACAGAGGGAAACUUCUGAUAAUACUGGAUA-AGUUGCAUAAUGAAAGUA-------GCAA-----UACGCUAUAUGAGAGCUUUGCAUCCUAUUAGCUAGUUGGUGGGGUAAAAGCCUACCAAGGCGAUGAUAGGUAGCCGGCCUGAGAGGGUGGACGGCCACAAGGGGACUGAGAUACGGCCCUUACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGAGGCAACUCUGAUCCAGCAAUUCUGUGUGUGUGAAGAAGGUUUUAGGACUGUAAAACACUUUUAGUAGGGAAGAAAG---------AAAU-------------GACGGUACCUACAGAAGAAGCGACGGCUAAAUACGUGCCAGCAGCCGCGGUAAUACGUAUGUCGCGAGCGUUAUCCGGAAUUAUUGGGCUUAAAGGGCAUCUAGGCGGUUAAACAAGUUGAAGGUGAAAACCUGUGGCUCAACCAUAGGCUUGCCUACAAAACUGUAUAACUAGAGUACUGGAAAGGUGGGUGGAACUACACGAGUAGAGGUGAAAUUCGUAGAUAUGUGUAGGAAUGCCGAUGAUGAAGAUAACUCACUGGACAGCAACUGACGCUGAAGUGCGAAAGCUAGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCUAGCUGUAAACGAUGAUCACUGGGUGUGGGGAU-UCGA-AGUCUCUGUGCCGAANCAAAAGCGAUAAGUGAUCCGCCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGUGGUGGAGCAUGUGGUUUAAUUCGACGCAACGCGAGGAACCUUACCAGAUCUUGACAUCCUCCGAAGAGCAUAGAAGUAUGCUUGUGCCUACGGGAACGGAGAGACAGGUGGUGCAUGGCUGUCGACAGCUCGUGUUGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGAAACCCCUAUCAUUAGUUACCAUCAUUAAG-UUGGGGACUCUAAUGAAACUGCCUACGAAGAGUAGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGCCCCUUAUGAUCUGGGCUACACACGUGCUACAAUGGAUAGUACAAAGAGAAGCUUUGURGCGAUACAUGNCNANACUAAGAAAGCUAUUCUUAGUUCGGAUUGAAGUCUGCAACUCGACUUCAUGAAGUUGGAAUCACUAGUAAUCGUGAAUCAGCAUGUCACGGUGAAKACGUUNUCGGGUNUUGUACACACCGCCCGUCACACCACGAGAGUUGUUUGCACCUGAAAUUACUGGCCUAACUGUAAAGGGGGAGGUACUGAAGGUGUGGAUAGCGAUUGGGGUGAAGUCGUAACAAGGUAAmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
gr.The.ros GGGAUGGAGAGUUUGAUCCUGGCUCAGGGGGAACGCUGGCGGCGUGCCUAAUGCAUGCAAGUCGGACGGGANGCACGCN---CUCU---GGCGUGCCGACCGUGGCGGACGGGUGCGUAACACGUGGGAACCCUCCCGGGUGCGGGGGAUAACCCGGGGAAACUCGGGCUAAUACCCCAUACGCUUGGUGAAGGAAAGGCGCAG---GCGA-CUGUGCUGUGCUCGGAGGGCCCUGCGGCCUAUCAGCUAGACGGUAGGGUAACGGCCUACCGUGGCGAUGACGGGUAGCUGGUCUGAGAGGAUGGCCAGCCACACGGGCACUGAGACACGGGCCCGACUCCUACGGGAGGCAGCAGCAGGGAAUCUUCCGCAAUGGGGGCAACCCUGACGGAGCGACGCCGCGUGCGGGAGGAAGCCCUUCGGGGUGUAAACCGCUGUUCGGGGGGACGAUC----------GAGC-------------GACGGUACCCUCGGAGCAAGUCCCGGCUAACUACGUGCCAGCAGCCGCGGUAAGACGUAGGGGGCGAGCGUUACCCGGAGUCACUGGGCGUAAAGGGCGUGUAGGCGGCUGGGUACGCCGCGUGUGAAAGUCCCCGGCUCAACCGGGGAGGGUCGCGCGGGACGGCCUGGCUCGAGGGCGGGAGAGGCGGGUGGAAUUCCCGGUGUAGCGGUGAAAUGCGUAGAGAUCGGGAGGAACGCCGGUGGCGAAGGCGGCCCGCUGGCCCGUACCUGACGCUGAGGCGCGAAGGCGUGGGGAGCGAACCGGAUUAGAUACCCGGGUAGUCCACGCAGUAAACGAUGCGGGCGAGGUGUGGGUGGUUUGACCCCAUCCGUGCCGGCGCCAACGCAGUAAGCCCGCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCAGCGGAGCGUGUGGUUUAAUUCGACGCAACGCGAAGAACCUUACCAGGGCUUGACAUGCACCGAACCUGGCUGAAAGGCUGGGGUGCCGUGAGGAGCGGUGGCACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGGGGUCAGUUAC------GCGG-----GUG-UCUGACCCGACUGCCGGGGAAAGCCCGGAGGAAGGAGGGGAUGACGUCAAGUCAGCAUGGCCCUGACGCCCUGGGCGACACACACGCUACAGUGACCGGGACAGUGGGCAGCGAAGGGGCGACCUGGAGCCAAUCCCGCAAACCCGGUCGUGGUGGGGAUCGCAGGCUGCAACCCGCCUGCGUGAACGCGGAGUUGCUAGUAACCGCCGGUCAGCCUACGGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACGUCACGAAAGCUGGCUUCACCUGAAGCUGGUGGGCCAACCGCACGGGGGCAGCCGUCGAGGGUGGGGCUGGUGAUUGGGACGAAGUCGUAACAAGGUAGCCGUACCGGAAGGNNNNGGUGGAUCACCUCCUUU
pt.Iso.pal NNUCCGAAGGGUUUGAUCCUGGCUCAGAAUGAACGUUGGCGGCGUGGAUUAGGCAUGCAAGUCGAACGGCC-----------GCAA----------GGCUAGUGGCGAAAGGGUGAGUAAGGCGACGGAACCUACCCCGAGGUUGG-CAUAGCCGGGGGAAACUCCGGGUAAUUCCCAGCGAUGUCGCAUCGC-AAAGGU-------GCAA----UUCCGCCUCGGGACGGGCCGUNGUGGUAUUAGGUAGUUGGUGGGGUCACGGCCCACNAAGCCGACGAUGCCUACCGGGCGUGCGAGCGUGGCCCGGCACACUGGGACUGAGACACUGCCCAGACUCCUACGGGAGGCUGCAGUCGAG-AUCUUCGGCAAUGGGCGCAAGCCUGACCGAGCGACGCGCNGUGGAGGAAGACGGCCCUUGGGUUGUAAACUCCUGNCNNGGGGAAGGAAGGGUCGGC---GAAG---AGCCNAUCUUGACCGC-UCCCUGGAGGAAGCACGGGCUAAGUUCGUGCCAGCAGCCGCGGUAAGACGAACCGUGCAAACGUUAUUCGGAAUCACUGGGCUUAAAGGGCGCGUAGGCGGAAGGGCGCGUCGGCGUUGAAAUNCCCCGGCUCAACCGGGNNAGCGGCGUCGAAACGGCCCUUCNGGAGGGGCGUAGAGGGACUCGGAACUUCCGGUGGAGCGGUGAUAUGCGUUGAGAUCGGAAGGAANGCCCGUGGCGAAAGCGGAGUCCUGGACGCUUACUGACGCUGAGGCGCGAAAGCCAGGGGAGCAAACGGGAUUAGAUACCCCGGUAGUCCUGGCUGUAAACRAUGGGCACUUGGCAGUGGGUUCUCGA-GGGUCCACUGCCNNNGGGAAACCGUGAAGUGCCNNGCCUGGGGAGUAUGGUCGCAAGGCUGAAACUCAAAGGAAUUCACGGGGGCUCACACAAGCGGUGGAGGAUGUGGCUUAAUUCGAANNUACGCGAAAAACCUUACCAGGGCUUGACAUGAGGGAUAGCCGGCGGAAACGUCGGUGCGCCGCAAGUGGAACCUAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGCCGUGAGGUGUCGGGUUAAGUCCCUUAACGAGCGAAACCCCUGCGGCNAGUUGCCAACACUCUG-GUGGGGACUCU-GCCAGACCGCCGGCGUGAAGCCGGAGGAAGGCGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUGCCNAGGGCUGCACACGUGCUACUAUGGCGGGGACAAAGCGUCGCCACGCCGUAAGGCCGAGCCAACCGCGUAAACCCCGCCCCAGUUCGGAUCGAGGGCUGCAACCCGCCCUCGUGAAGCCGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUGUGUUCCUGAGCCUUGUACACACCGCCCGUCAAGNCACCAAAGGGGGGGGCACCCGAAGUCGAAGA-UC----UCAC---GACGGGCGCCGAAGGUGAAACUCCNNAUGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
pt.Pla.bra -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-------mmmm-------mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-------mmmm-----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmCAAUGGGCGAAAGCCUGACCAAGCGAUGCCGCGUGCGGGAUGAAGGCCCUUGGGUUGUAAACCGCUGUCAGGGGGGAUGAAACU--------UUCG----------GUUGACAGA-GCCCCAGAGGAAGCACGGGCUAAGUACGUGCCAGCAGCCGCGGUAACACGUACUGUGCGAACGUUAUUCGGAAUCACUGGGCUUAAAGGGUGCGUAGGCGGCCUGGAUAGUCAGAUGUGAAAUCCCGCGGCUCAACCGUGGAACUGCAUUUGAAACUGCCAGGCUUGAGUGAGACAGGGGUGUGUGGAACUUCUCGUGGAGCGGUGAAAUGUGUUGAUAUGAGAAGGAACACCGGUGGCGAAAGCGACACACUGGGUCUUAACUGACGCUGAGGCACGAAAGCCAGGGGAGCGAACGGGAUUAGAUACCCCGGUAGUCCUGGCUGUAAACGUUGAGUACUAGUUGGUGGGAACUUCG-GUUCUCACGGACGUAGCAAAAGUGUUAAGUACUCCGCCUGGGGAGUAUGGUCGCAAGGCUGAAACUCAAAGGAAUUGACGGGGGCUCACACAAGCGGUGGAGCAUGUGGCUUAAUUCGAGGCAACGCGAAGAACCUUACCUAGACUUGACAUGAUGGAUAGCUGGCUGAAAGGUCAGUGACGCUUCGGUGGAACAUGCACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCUUGAACGAGCGCAACCCCUGUCGCCAGUUGCCAGCAAUAAUGUUGGGGACUCUGGCGAGACCGCCGGUGUUAAACCGGAGGAAGGUGGGGACGACGUCAAGUCAUCAUGGCCUUUAUGUCUAGGGCUGCACACGUGCUACAAUGCGGCGUACAAAGGGAAGCC-ACCCGCGAGGGGGAGCAAAUCUCAGAAAGCGCCGCUCAGUUCGGAUUGUAGGCUGCAACUCGCCUACAUGAAGCUGGAAUCGCUAGUAAUCGCAGGUCAGCAUACUGCGGUGAAUGUGUUCCUGAGCCUUGUACACACCGCCCGUCAAGCCACGAAAGGGGGGGGCAUCCUAAGUCACUGAGCUA---AUC---UGGCAGGUGCCUAAGAUGAACUCCCUGAUUGGGACUAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCGGCUGGAUCACCUCCUU-
pt.Pla.mar -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-------mmmm--------mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-------mmmm----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmCUAGGGGGUGUGAGAGCAUGGCCCCCACCACUGGGACUGAGACACUGCCCAGACACCUACGGGUGGCUGCAGUCGAGAAUCUUCGGCAAUGGACGCAAGUCUGACCGAGCGACGCCGCGUGCGGGAUGAAGGCCCUUGGGUUGUAAACCGCUGUCAGAGGGGAUGAAAUGCAGAAGGGUUAU--CCCUUUUGUUUGACAGA-GCCUCAGAGGAAGCACGGGCUAAGUCCGUGCCAGCAGCCGCGGUAACACGUACUGUGCGAACGUUAUUCGGAAUCACUGGGCUUAAAGGGUGCGUAGGCGGUUUAGUAAGUAGGGUGUGAAAUGCCAGGGCUCAACCUUGGCACGGCGCUCUAAACUGCUAAACUUGAGUGAGAUAGGGGUGUACGGAACUUCCGGUGGAGCGGUGAAAUGCGUUGAUAUCGGAAGGAACACCGGUGGCGAAAGCGGUACACUGGGUCUUAACUGACGCUGAGGCACGAAAGCUAGGGUAGCGAACGGGAUUAGAUACCCCGGUAGUCCUAGCCGUAAACGAUGAGUACUAGUUGGGAGGAGCUUCG-GCUCAUCCGGACGUAGCGAAAGCAUUAAGUACUCCGCCUGGGGAGUAUGGUCGCAAGGCUGAAACUCAAAGGAAUUGACGGGGGCUCACACAAGCGGUGGAGCAUGUGGCUUAAUUCGAGGCAACGCGAAGAACCUUACCUGGAUUUGACAUGUUGUAUAGCUCUGUGAAAGCAGAGUGACGCUUCGGUGGAACUUGCACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUCGCGUUAAGUCGCUGAACGAGCGAAACCCCUAUCCUUAGUUGCCAGCACUCAUGGUGGGGACUCUAAGGAGACUGCCGGUGUCAAACCGGAGGAAGGUGGGGACGACGUCAAGUCAUCAUGGCCUUUAUGUCCAGGGCUGCACACGUGCUACAAUGCGGCGUACAAAGGGAAGCAAAAUCGCGAGAUCAAGCAAAUCCCAAAAAGCNUCGCUCAGUUCGGAUUGCAGGCUGCAACUCGCCUGCAUGAAGUUGGAAUCGCUAGUAAUCGCAGGUCAGCUUACUGCGGUGAAUAUGAACCUGAGCCUUGUACACACCGCCCGUCAAGCCACGAAAGCGGGGGGCGUCCAAAGUmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ch.Zea.may CUCAUGGAGAGUUCGAUCCUGGCUCAGGAUGAACGCUGGCGGCAUGCUUAACACAUGCAAGUCGAACGGGAAGU--------GGU---------GUUUCCAGUGGCGAACGGGUGAGUAACGCGUAAGAACCUGCCCUUGGGAGGGGAACAACAACUGGAAACGGUUGCUAAUACCCCGUA-GGCUGAGGAGCAAAAGGA-------GAAA-----UCCGCCCAAGGAGGGGCUCGCGUCUGAUUAGCUAGUUGGUGAGGCAAUAGCUUACCAAGGCGAUGAUCAGUAGCUGGUCCGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUC-GGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGCCUGACGGAGCAAUGCCGCGUGGAGGUGGAAGGCCUACGGGUCGUCAACUUCUUUUCUCGGAGAAGAA-----------ACAA------------UGACGGUAUCUGAGGAAUAAGCAUCGGCUAACUCUGUGCCAGCAGCCGCGGUAAGACAGAGGAUGCAAGCGUUAUCCGGAAUGAUUGGGCGUAAAGCGUCUGUAGGUGGCUUUUCAAGUCCGCCGUCAAAUCCCAGGGCUCAACCCUGGACAGGCGGUGGAAACUACCAAGCUGGAGUACGGUAGGGGCAGAGGGAAUUUCCGGUGGAGCGGUGAAAUGCAUUGAGAUCGGAAAGAACACCAACGGCGAAAGCACUCUGCUGGGCCGACACUGACACUGAGAGACGAAAGCUAGGGGAGCAAAUGGGAUUAGAGACCCCAGUAGUCCUAGCCGUAAACGAUGGAUACUAGGUGCUGUGCGACUCGCCCGUGCAGUGCUGUAGCUAACGCGUUAAGUAUCCCGCCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAAGGCGAAGAACCUUACCAGGGCUUGACAUGCCGCGAAUCCUCUUGAAAGAGAGGGGUGCCCUCGGGAACGCGGACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGCCGUAAGGUGUUGGGUUAAGUCUCGCAACGAGCGCAACCCUCGUGUUUAGUUGCCACUA-UGAG-UUUGGAACCCUGAACAGACCGCCGGUGUUAAGCCGGAGGAAGGAGAGGAUGAGGCCAAGUCAUCAUGCCCCUUAUGCCCUGGGCGACACACGUGCUACAAUGGGCGGGACAAAGGGUCGCGAUCUCGCGAGGGUGAGCUAACUCCAAAAACCCGUCCUCAGUUCGGAUUGCAGGCUGCAACUCGCCUGCAUGAAGCAGGAAUCGCUAGUAAUCGCCGGUCAGCCUACGGCGGCGAAUCCGUUCCCGGGCCUUGUACACACCGCCCGUCACACUAUAGGAGCUGGCCAGGUUUGAAGUCAUUAC-CUAACCGUAAGGAGGGGGAUGCCUAAGGCUAGGCUUGCGACUGGAGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGCGGCUGGAUCACCUCCUUU
ch.Dau.car CUCAUGGAGAGUUCGAUCCUGGCUCAGGAUGAACGCUGGCGGCAUGGAAAACACAUGCAAGUCGGACGGGAAGU--------GGU---------GUUUCCAGUGGCGGACGGGACUGUAACGCGUAAGAACCUGCCCUUGGGUGGGGAACAACAGCUGGAAACGGCUGCUAAUACCCCGUA-GGCUGAGGAGCAAAAGGA-------GGAA-----UCCGCCCGAGGGAGGGCUCGCGUCUGAU-AGCUAGUUGGUGAGGCAAUAGCUUACCAAGGCGAUGAUCAGUAGCUGGUCCGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUC-GGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGC--GACGGAGCAAUGCCGCGUGGAGGUAGAAGGCCCACGGGUCGUGAACUUCUUUUCCCGGAGAAGAA-----------GCAA------------UGACGGUAUCUGGGGAAUAAGCAUCGGCUAACUCUGUGCCAGCAGCCGCGGUAAUACAGAGGAUGCAAGCGUUAUCCGGAAUGAUUGGGCGUAAAGCGUCUGUAGGUGGCUUUUUAAGUCCGCCGUCAAAUCCCAGGGCUCAACCCUGGACAGGCGGUGGAAACUACCAAGCUGGAGUACGGUAGGGGCAGAGGGAAUUUCCGGUGGAGCGGUGAAAUGCGUAGAGAUCGGAAAGAACACCAACGGCGAAAGCACUCUGCUGGGCCGACAUUGACACUGAGAGACGAAAGCUAGGGGAGCGAAUGGGAUUAAAUACCCCAUUAGUCCUAGCCGUAAACGAUGGAUACUAGGCGCUGUGCG-AUCGCCCGUGCAGUGCUGUAACUACCGCGUUAAGUAUCCCGCCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGGCGCGCACAAUCGGUGGAGCAUGUGGUUUAAUUCGAUGCAAAGCGAAGAACCUUACCAUGGCUUGACAUGCCGCGAAUCCUCUUGAAAGAGAGGGGUGCCUUCGGGAACGCGGACACAGGUGGUGAAUGGCUGUCGUCAGCUCGUGCCGUAAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUGUUUAGUUGCCAUCG-UUGAGUUUGGAACCCUGAACAGACUGCCGGUGAUAAGCCGGAGGAAGGUGAGGAUGACGUCAAGUCAUCAUGCCCCUUAUGCCCUUGGCGACACUCGUGCUACAAUGGCCGGGACAAAGGGUUGCGAUCCCGCGAGGGUGAGCUAACCCCAAAAACCCGUCCUCAGUUGGGAUUGCAGGCUGCAACUCGCCUGCAUGAAGCCGGAAUCGCUAGUAAUCGCCGGUCAGCCUACGGCGGUGAAUUCGGUACCGGGCCUUGUACACACCGCCCGUCACACUAUGGGAGCUGGCCAUGCCCGAAGUCGUUAC-CUAACCGCAAGG-GGGGGAUGCCGAA-GCAGGGCUAGUGACUGGAGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGCGGCUGGAUCACCUCCUmm
ch.Gly.max CUCAUGGAGAGUUCGAUCCUGGCUCAGGAUGAACGCUGGCGGCAUGCCUUACACAUGCAAGUCGGACGGGAAGU--------GGU---------GUUUCCAGUGGCGGACGGGUGAGUAACGCGUAAGAACCUACCCUUGGGAGGGGAACAACAGCUGGAAACGGCUGCUAAUACCCCGUA-GGCUGAGGAGCAAAAGGA--------GAA-----UCCGCCCGAGGAGGGGCUCGCGUCUGAUUAGCUAGUUGGUGAGGC-AUAGCUUACCAAGGCGAUGAUCAGUAGCUGGUCCGAGA-GAUGAUCAGCCACACUGGGACUGAGACGAGGCCCAGACUCUUC-GGGAGGCAGCAGUGGGGAAUUUUCCGCAAUG-GCGAAAGC-UGACGGAGCAAUGCCGCGUGAAGGUAGAAGGCCUAC-GGUCAUGAACUUCUUUUCCCGGAGAAGAA-----------GCAA------------UGACGGUAUCCGGGGAAUAAGCAUCGGCUAACUCUGUGCCAGCGGCCGCGGUAAGACAGAGGAUGCAAGCGUUAUCCGGAAUGAUUGGGCG-AAAG-GUCUGUAGGUGGCUUUUUAAGUUCGCCGUCAAAUCCCAGGGCUCAACCCUGGACAGGCGGUGGAAACUACCAAGCUGGAGUACGGUAGGGGCAGAGGGAAUUUCCGGUGGAGCGGUGAAAUGCGUAGAGAUCGGAAAGAACACCAACGGCGAAAGCACUCUGCUGGGCCGACACUGACACUGAGAGACGAAACUUAGGGGAGCGAAUGGGAUUAGAUACCCCAGUAGUCCUAGCCGUAAACGAUGGAUACUAGGCGCUGUGCGUAUCGCCCGUGCAAUGCUGUA-CUAACGCGUUAAGUAUCCCGCCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGG-CCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAAAGCGAAGAACCUUACCAGGGCUUGACAUGCCGCGAAUCCUCUUGAAAGAGAGGGGUGC-UUCGGGAACGCGGACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGCCGUAAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUGUUUAGUUGCCAACA-UUUAGUUUGGAACCCUGAGCAGACUGCCGGUGAUAAGCCGGAGGAAGGUGAGGAUGACGUCGAGUCAUCAUGCCCCUUAUGCCCUGGGCGACACACGUGCUACAAU-----GGACAAAGGAUCGCGAUCCCGCGA-GGUGAGCUAACUCCAAAAACCCGUCCUCAGUUCGGAUUGUAGGCUGCAACUCGCCUGCAUGAAGCCGGAAUCGCUAGUAAUCGCCGGUCAGCCUACGGCGGUGAAUUCGUUCCCGGGCCUUGUACACACCGCCCGUCACACUAUGGGAGCUGGCCAUGC-CGAAGUCGUUAC-CUAACCGCAA-GAGGGGGAUGCCGAA-G--GGGCUAGUGACUGGAGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGCGGCUGGAUCACCUCCUUm
ch.Pis.sat CUCAUGGAGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGCAUGCUUUACACAUGCAAGUCGGACGGGAAGU--------GGU---------GUUUCCAGUGGCGAACGGGUGAGUAACGCGUAAGAACCUGCCCUUGGGAGGGGGACAACAGCUGGAAACGGCUGCUAAUACCCCGUA-GGCUGAGGAGCGAAAGGA-------GGAA-----UCCGCCCAAGGAGGGGCUCGCGUCUGAUUAGCUAGUUGGUGAGGUAAUAGCUUACCAAGGCGAUGAUCAGUAGCUGGUCCGAGAGGAUGAUCAGCCACACUGGGACUGAGACAAGGUCCAGACUCCUC-GGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGCCUGACGGAGCAAUGCCGCGUGGAGGUAGA-GGCCCCUGGGUCAUGAACUUCUUUUCCCGGAGAAGAA-----------AAAA------------UGACGGUAUCCGGGGAAUAAGCAUCGGCUAACUCUGUGCCAGCAGCCGCGGUAAGACAGAGGAUGCAAGCGUUAUCCGGAAUGAUUGGGCGUAAAGCGUCUGUAGGUGGCUUUUUAAGUUCGCUGUCAAAUACCAGGGCUCAACCCUGGACAGGUGGUGAAAACUACUAAGCUAGAGUACGGUAGGGGCAGAGGGAAUUUCCGGUGGAGCGAUGAAAUGCGUAGAGAUCGGAAGGAACACCAACGGCGAAAGAACUCUGCUGGGCCGACACUGACACUGAGAGACGAAAGCUAGGGGAGCGAAUGGGAUUAGAGACCCCAGUAGUCCUAGCCGUAAACGAUGGAUACUAAGUGCUGUGCGAAUCGCCCGUGCAACGCUGUA-CUAACGCGUUAAGUAUCCCGCCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGG-CCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAAAGCGAAGAACCUUACCAGGGCUUGACAUGC-GCGAAUCCUCUUGAAAGAGAGGAGUGCCUUCGGGAAUGC-GACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUGUUUAGUUGCCAACG-UUUAGUUUGGAACUCUGAACAGACUGCCGGUGAUAAGCCGGAGGAAGGUGAGGAUGACGUCAAGUCAUCAUGCCCCUUAUGCCCUGGGCUACACAC-UGCUACAAUGGACCGGACAAAGGAUCGCGACCCCGCGAGGGUGAGCUAACUUCAAAAACCUGUCCUCAGUUCGGAUUGUAGGCUGCAACUCGCCUACAUGAAGCCGGAAUCGCUAGUAAUCGCCGGUCAGCCUACGGCGGUGAAUUCGUUCCCGGGCCUUGUACACACCGCCCGUCACACUAUGGGAGCUGGCCAUGCCCGAAGUCAUUAC-CUAACCGCAAGGAGGGGGAUGCCGAAGGCAGGGCUAGUGACUGGAGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGCGACUGGAUCACCUCCUUU
ch.Nic.tab CUCAUGGAGAGUUCGAUCCUGGCUCAGGAUGAACGCUGGCGGCAUGCUUAACACAUGCAAGUCGGACGGGAAGU--------GGU---------GUUUCCAGUGGCGGACGGGUGAGUAACGCGUAAGAACCUGCCCUUGGGAGGGGAACAACAGCUGGAAACGGCUGCUAAUACCCCGUA-GGCUGAGGAGCAAAAGGA-------GGAA-----UCCGCCCGAGGAGGGGCUCGCGUCUGAUUAGCUAGUUGGUGAGGCAAUAGCUUACCAAGGCGAUGAUCAGUAGCUGGUCCGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUC-GGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGC--GACGGAGCAAUGCCGCGUGGAGGUAGAAGGCCCACGGGUCGUGAACUUCUUUUCCCGGAGAAGAA-----------GCAA------------UGACGGUAUCUGGGGAAUAAGCAUCGGCUAACUCUGUGCCAGCAGCCGCGGUAAUACAGAGGAUGCAAGCGUUAUCCGGAAUGAUUGGGCGUAAAGCGUCUGUAGGUGGCUUUUUAAGUCCGCCGUCAAAUCCCAGGGCUCAACCCUGGACAGGCGGUGGAAACUACCAAGCUGGAGUACGGUAGGGGCAGAGGGAAUUUCCGGUGGAGCGGUGAAAUGCGUAGAGAUCGGAAAGAACACCAACGGCGAAAGCACUCUGCUGGGCCGACACUGACACUGAGAGACGAAAGCUAGGGGAGCGAAUGGGAUUAGAUACCCCAGUAGUCCUAGCCGUAAACGAUGGAUACUAGGCGCUGUGCG-AUCGCCCGUGCAGUGCUGUAGCUAACGCGUUAAGUAUCCCGCCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGGCGCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAAAGCGAAGAACCUUACCAUGGCUUGACAUGCCGCGAAUCCUCUUGAAAGAGAGGGGUGCCUUCGGGAACGCGGACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGCCGUAAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUGUUUAGUUGCCAUCG-UUGAGUUUGGAACCCUGAACAGACUGCCGGUGUUAAGCCGGAGGAAGGUGAGGAUGACGUCAAGUCAUCAUGCCCCUUAUGCCCUUGGCGACACACGUGCUACAAUGGCCGGGACAAAGGGUCGCGAUCCCGCGAGGGUGAGCUAACCCCAAAAACCCGUCCUCAGUUCGGAUUGCAGGCUGCAACUCGCCUGCAUGAAGCCGGAAUCGCUAGUAAUCGCCGGUCAGCCUACGGCGGUGAAUUCGUUCCCGGGCCUUGUACACACCGCCCGUCACACUAUGGGAGCUGGCCAUGCCCGAAGUCGUUAC-CUAACCGCAAGG-GGGGGAUGCCGAA-GCGGGGCUAGUGACUGGAGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGCGGCUGGAUCACCUCCUUU
ch.Pin.thu CUCAUGGAGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGCAUGCUUAACACAUGCAAGUCGGACGGGAAGU--------GGU---------GUUUCCAGUGGCGGACGGGUGAGUAACGCGUAAGAACCUGCCCUUGGGAGGGGAACAACAGCUGGAAACGGCUGCUAAUACCCCAUA-GGCUGAGGAGCAAAAGGA-------GGAA-----UCCGCCCAAGGAGGGGCUCGCGUCUGAUUAGUUAGUUGGUGAGGCAAUGGCUUACCAAGGCGACGAUCAGUAGCUGGUCCGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUC-GGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGCCUGACGGAGCAAUGCCGCGUGAAGGCAGAAGGCCCACGGGUCAUGAACUUCUUUUCUCGGAGAAGAA-----------AAAA------------UGACGGUAUCUGAGGAAUAAGCAUCGGCUAACUCUGUGCCAGCAGCCGCGGUAAGACAGAGGAUGCAAGCGUUAUCCGGAAUGAUUGGGCGUAAAGCGUCUGUAGGUGGCUUUUCAAGUCCGCCGUCAAAUCCCAGGGCUCAACCCUGGACAGGCGGUGGAAACUACCAAGCUGGAGUACGGUAGGGGCAGAGGGAAUUUCCGGUGGAGCGGUGAAAUGCGUUGAGAUCGGAAAGAACACCAACGGCGAAAGCACUCUGCUGGGCCGACACUGACACUGAGAGACGAAAGCUAGGGGAGCAAAUGGGAUUAGAUACCCCAGUAGUCCUAGCCGUAAACGAUGGAUACUAAGUGCUGUGCGUAUCGCCCGCGCAGUGCUGUAGCUAACGCGUUAAGUAUCCCGCCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUCAAUUCGAUGCAAAGCGAAGAACCUUACCAGGGCUUGACAUGCCGUGAAUCCUCCCGAAAGAGAGGAGUGCCUUCGGGAACGCGGACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGCCGUAAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUGUUUAGUUGCCAGCA-UUUAGUUUGGAACCCUGAACAGACUGCCGGUGAUAAGCCGGAGGAAGGUGAGGAUGACGUCAAGUCAUCAUGCCCCUUACGCCCUGGGCGACACACGUGCUACAAUGACCGGGACAAAGGGUCGCGACCCCGCGAGGGCAAGCUAACCUCAAAAACCCGGCCUCAGUUCGGAUUGCAGGCUGCAACUCGCCUGCAUGAAGCCGGAAUCGCUAGUAAUCGCCGGUCAGCCUACGGCGGUGAAUCCGUUCCCGGGCCUUGUACACACCGCCCGUCACACUAUGGGAGCUGGCCAUGCCCCAAGUCGUUAC-CUAACCGCAAGGAGGGGGAUGCCGAAGGCUGGGCUAGUGACUGGAGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGCGGCUGGAUCACCUCCUUU
ch.Chl.mir CCUGCAGAGAGUUYGAUCCUGGCUCAGGAUGAACGCUGGCGGCAUGCUUAACACAUGCAAGUCGAACGGAGAUUUUAUGUUUCUUGAAACAUAAAAUCUUAGUGGCGGACGGGUGAGGAACGCGUAAGAACCUACCUUUAGGGGAGGGACAACAACUGGAAACGGUUGCUAAUACCUCAUA-UGCUGAGGAGUAAAAGGGUUAUAAAUACGAUUAUUCCGCCUAAAGAUGGGCUUGCGUCUGAUUAGCUUGUUGGUGGGGUAAUUGCUUACCAAGGCGACGAUCAGUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUC-GGGAGGCAGCAGURAGGAAUUUUCCGCAAUGGGCGAAAGCCUGACGGAGCAAUGCCGCGUGGAGGAUGACAGCCUGUGGGUCGUAAACUCCUUUUCUCAGAAAAGAA-----------GAUC------------UGACGGUAUCUGAGGAAUAAGCAUCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGAUGCAAGCGUUAUCCGGAAUGAUUGGGCGUAAAGCGUCUGUAGGUGGUUUAUUAAGUCUACUGUUAAAGAUCAGGGCUUAACCCUGAGCCGGCAGUGGAAACUAAUAAGCUUGAGUACGGUAGGGGCAGAGGGAAUUCCCGGUGUAGCGGUGAAAUGCGUAGAGAUCGGGAAGAACACCAAUGGCGAAAGCACUCUGCUGGGCCGAAACUGACACUGAGAGACGAAAGCUAGGGGAGCGAAUGGGAUUAGAUACCCCAGUAGUCCUAGCCGUAAACGAUGGAUACUAAGUGCUGUGCGACUCAACCGUCCAGUACUGUAGCUAACGCGUGAAGUAUCCCGCCUGGGGAGUAUGCUCGCAAGGGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGYUUAAUUCGAUGCAACGCGAAGAACCUUACCAGGGCUUGACAUGCCAUUUAGUCUUUUGAAAAAAAGACAUAUUUUUAGAUUGGUGGACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCUUUACUUGCCAUUACUAGCUGUUGGGAAAUUAGAGAGACUGCCGGUGAGAAGCCGGRGGAAGGUGAGGAUGACGUCAAGUCAGCAUGCCCCUUAUGCCCUGGGCGACACACGUGCUACAAUGGCCGGGACAAUGAGAUGCAACCUCGCGAGAGCAAGCUAACCUCAAAAACCCGGUCUCAGUUCGGAUUGCAGGCUGCAACUCGCCUGCAUGAAGUCGGAAUCGCUAGUAAUCGCUGGUCAGCCUACAGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGCUGGCUAUGCCCAAAGUCGUUAC-CCAACCGUAAGGAGGGGGAUGCCUAAGGCAGAGCUAGUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGNGGNUGGAUCACCUCCUUG
ch.Eug.gra GAAAUGACGAGUUUGAUCCUUGCUCAGGGUGAACGCUGGCGGUAUGCUUAACACAUGCAAGUUGAACGAAAUUACUA-----GCAA-----UAGUAAUUUAGUGGCGGACGGGUGAGUAAUAUGUAAGAAUCUGCGCUUGGGUGAGGAAUAACAGAUGGAAACGUUUGCUAAUGCCUCAUAUUACUGUGAAGUUAAAGA--------GAAU-----UUCGCCUAGGCAUGAGCUUGCAUCUGAUUAGCUUGUUGGUGAGGUAAAGGCUUACCAAGGCGACGAUCAGUAGCUGAUUUGAGAGGAUGAUCAGCCACACUGGGAUUGAGA-ACGGAACAGACUUUUC-GGAAGGCAGCAGUGAGGAAUUUUCCGCAAUGGGCGCAAGCCUGACGGAGCAAUACCGCGUGAAGGAAGAAGGCCUUUGGGUUGUAAACUUCUUUUCUCAAAGAAGAA-----------GAAA------------UGACGGUAUUUGAGGAAUAAGCAUCGGCUAAUUCCGUGCCAGCAGCCGCGGUAAUACGGGAGAUGCGAGCGUUAUCCGGAAUUAUUGGGCGUAAAGAGUUUGUAGGCGGUCAAGUGUGUUUAAUGUUAAAAGUCAAAGCUUAACUUUGGAAGGGCAUUAAAAACUGCUAGACUUGAGUAUGGUAGGGGUGAAGGGAAUUUCCAGUGUAGCGGUGAAAUGCGUAGAGAUUGGAAAGAACACCAAUGGCGAAGGCACUUUUCUAGGCCAAUACUGACGCUGAGAAACGAAAGCUGAGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCUUGGCCGUAAACUAUGGAUACUAAGUGGUGCUG--AAAG----UGCACUGCUGUAGUUAACACGUUAAGUAUCCCGCCUGGGGAGUACGCUUGCACAAGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACACGAAGAACCUUACCAGGAUUUGACAGGCUAGGAGGAAGUUUGAAAGAACGCAGUACCUUCGGGUAUCUAGACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUUUUUUUAAUUAAC-----GCUU-----GUCAUUUAGAAAUACUGCUGGUUAUU-ACCAGAGGAAGGUGAGGACGACGUCAAGUCAUCAUGCCCCUUAUAUCCUGGGCUACACACGUGCUACAAUGGUUAAGACAAUAAGUUGCAAUUUUGUGAAAAUGAGCUAAUCUU-AAAACUUAGCCUAAGUUCGGAUUGUAGGCUGAAACUCGCCUACAUGAAGCCGGAAUCGCUAGUAAUCGCCGGUCAGCUUACGGCGGUGAAUACGUUCUCGGGCCUUGUACACACCGCCCGUCACACCAUGGAAGUUGGCUGUGCCCGAAGUUAUUAU-CUGCCUGAAAAGAGGGAAAUACCUAAGGCCUGGCUGGUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGUGGCUGGAACAAUUCCCmm
ch.Cya.par ACCAUGGAGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGUAUGCUUAACACAUGCAAGUCGAACGAAGAUC--------GCAA--------GAUCUUAGUGGCGGACGGGUGAGUAACGCGUGAGAAUCUACCCUUAGGAGGGGGACAACAGUUGGAAACGACUGCUAAUACCCCAUA-UGCCUUCGGGUGAAAAGA-------GUAA-----UCUGCCUGAGGAAGAGCUCGCGUCUGAUUAGCUAGUUGGUGGGGUAAAGGCCUACCAAGGCGACGAUCAGUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGAUACGGCCCAGACUCCUC-GGGAGGCAGCAGUGGGGAAUUUUCCGCAAUGGGCGAAAGCCUGACGGAGCAAUACCGCGUGAGGGAAGACGGCCUGUGGGUUGUAAACCUCUUUUCUUAGGGAAGAA-----------UCAA------------UGACGGUACCUAAGGAAUAAGCAUCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGAUGCAAGCGUUAUCCGGAAUCAUUGGGCGUAAAGAGUUCGUAGGUGGCUAAGCAAGUCUGUUGUUAAAGGCUGGGGCUUAACCCCAAAAAGGCAAUGGAAACUGUUUGGCUUGAGUACGGUAGGGGCAGAGGGAAUUCCUGGUGUAGCGGUGAAAUGCGUAGAUAUCAGGAAGAACACCGAUGGCGAAAGCACUCUGCUGGGCCGUUACUGACACUGAGGAACGAAAGCUAGGGUAGCAAAUGGGAUUAGAUACCCCAGUAGUCCUAGCCGUAAACUAUGGAUACUAGGUGUUGUGCGUAUCGCCCGUACAGUACCGUAGCUAACGCGUUAAGUAUCCCGCCUGGGGAGUACGCUCGCAAGAGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGUAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCAGGGUUUGACAUGUCGCGAAUUUUCUUGAAAGAGAAAAGUGCCUUCGGGAACGCGAACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUUUUUAGUUGCCAUCA-UCAG-UUGGGCACUCUAAAGAGACUGCCGGUGACAAGCCGGAGGAAGGUGGGGAUGACGUCAAGUCAGCAUGCCCCUUAUACCCUGGGCUACACACGUACUACAAUGGUCGGGACAAUAGGUUGCCAACUUGCGAAAGUGAGCUAAUCCGUUAAACCCGGCCUCAGUUCAGAUUGCAGGCUGCAACUCGCCUGCAUGAAGGUGGAAUCGCUAGUAAUCGCCGGUCAGCUUACGGCGGUGAAUUCGUUCCCGGGCCUUGUACACACCGCCCGUCACACCACGGGAGUCGGCCAUGCCCGAAGUCGUUAC-CUAACCAUUUGGAGGGGGAUGCCUAAGGCAGGGCUGGUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGCGGCUGGAUCACCUCCUUU
ch.Cya.cal AUAAUGGAGAGUUUGAUCCUGGCUCAGGAUUAACGCUGGCGGUAUGCCUAACACAUGCAAGUCGUACGAGAAU----------UUU---------AUUCUAGUGGCGGACGGGUGAGUAACACGUGAGAAUCUACCUCUAGGAGGGGGAUAACAGUUGGAAACGAUUGCUAAAACCCCAUA-UGCCUUAUGGUGAAAAGA-------UUUA-----UCUGCCUGGAGAUGAGCUCGCGGCUGAUUAGCUAGUUGGUAGGGUAAUGGCUUACCAAGGCAACGAUCAGUAGCUGGUCUUAGAGGAUGAUCAGCCACACUGGAACUGAGAUACGGUCCAGACUCCUC-GGGAGGCAGCAGUGGGGAAUUUUCCACAAUGGGCGAAAGCCUGAUGGAGCAAUACCGUGUGAGGGAUGAAGGCCUGUGGGUUGUAAACCUCUUUUUUCAGGAAAGAA-----------ACUU------------UGACGGUACCUGAAGAAUAAGCAUCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGAUGCAAGCGUUAUCCGGAAUCACUGGGCGUAAAGCGUCUGUAGGUGGUUUAUCAAGUCUGCUGUUAAAGCUUGAGGCUUAACCUCAAAAAAGCAGUGGAAACUGAUAGACUAGAGAAUGGUAGGGGCAGAGAGAAUUCUCAGUGUAGCGGUGAAAUGCGUAGAUAUUGAGAAGAAUACCGAUAGCGAAGGCGCUCUGCUGGGCCAUUACUGACACUCAGAGACGAAAGCUAGGGGAGCAAAUGGGAUUAGAUACCCCAGUAGUCCUAGCCGUAAACUAUGGAUACUAGAUGUUGUGUGAGUAAAUUGUGCAGUAUCGAAGCUAACGCGUUAAGUAUCCCGCCUGGGAAGUACGCUCGCAAGAGUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGC-GUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCAGGACUUGACAUGUUACUAAUUUCCUUGAAAGAGGAAAGUGCCUUUGGGAAAGUAAACACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCUUUAGUUACCAUCA-UUAAGUUGGGGACUCUAAAGAGACUGCCGGUGAUAAACCGGAGGAAGGUAAGGAUGAGGUCAAGUCAUCAUGCCCCUUAUGUCCUGGGCUACACACGUGCUACAAUGGUUAGGACAAUAAGUCGCAAAUUCGUGAGAACUAGCUAAUCUUAUAAACCUAAUCUCAGUACGGAUUGUAGGCUGCAACUCGCCUACAUGAAGACGGAAUCGCUAGUAAUCGCUGGUCAGCUCACAGCGGUGAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCAUGGGAGCUGGCCAUGUCCGAAAUCAUUAC-UUAACUUAAUGGAGGAGGAUGCUUAAGGCAGGGCUAGUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUACUGGAAGGUGCGGCUGGAUUACCUCCUUU
ga.Esc.col AAAUUGAAGAGUUUGAUCAUGGCUCAGAUUGAACGCUGGCGGCAGGCCUAACACAUGCAAGUCGAACGGUAACAGGAAGAAGCUUGCUUCUUUGCUGACGAGUGGCGGACGGGUGAGUAAUGUCUGGGAAACUGCCUGAUGGAGGGGGAUAACUACUGGAAACGGUAGCUAAUACCGCAUAACGUCGCAAGACCAAAGAGGGGGACCUUCGGGCCUCUUGCCAUCGGAUGUGCCCAGAUGGGAUUAGCUAGUAGGUGGGGUAACGGCUCACCUAGGCGACGAUCCCUAGCUGGUCUGAGAGGAUGACCAGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGCAAGCCUGAUGCAGCCAUGCCGCGUGUAUGAAGAAGGCCUUCGGGUUGUAAAGUACUUUCAGCGGGGAGGAAGGGAGUAAAGUUAAUACCUUUGCUCAUUGACGUUACCCGCAGAAGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGCACGCAGGCGGUUUGUUAAGUCAGAUGUGAAAUCCCCGGGCUCAACCUGGGAACUGCAUCUGAUACUGGCAAGCUUGAGUCUCGUAGAGGGGGGUAGAAUUCCAGGUGUAGCGGUGAAAUGCGUAGAGAUCUGGAGGAAUACCGGUGGCGAAGGCGGCCCCCUGGACGAAGACUGACGCUCAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGUCGACUUGGAGGUUGUGCCCUUGAGGCGUGGCUUCCGGAGCUAACGCGUUAAGUCGACCGCCUGGGGAGUACGGCCGCAAGGUUAAAACUCAAAUGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCUGGUCUUGACAUCCACGGAAGUUUUCAGAGAUGAGAAUGUGCCUUCGGGAACCGUGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUUGUGAAAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUCCUUUGUUGCCAGCGGUCCGGCCGGGAACUCAAAGGAGACUGCCAGUGAUAAACUGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGGCCCUUACGACCAGGGCUACACACGUGCUACAAUGGCGCAUACAAAGAGAAGCGACCUCGCGAGAGCAAGCGGACCUCAUAAAGUGCGUCGUAGUCCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGUGGAUCAGAAUGCCACGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGUUGCAAAAGAAGUAGGUAGCUUAACCUUCGGGAGGGCGCUUACCACUUUGUGAUUCAUGACUGGGGUGAAGUCGUAACAAGGUAACCGUAGGGGAACCUGCGGUUGGAUCACCUCCUUA
ga.Hae.par --ACUGAAGAGUUUGAUCNUGGCUCAGAUUGAACGCUGGCGGCAGGCUUAACACAUGCAAGUCGAACGGUAACGGGUUGAAACUUGUUUCAAUGCUGACGAGUGGCGGACGGGUGAGUAAUGCUUGGGAAUCUGGCUUAUGGAGGGGGAUAACCAUUGGAAACGAUGGCUAAUACCGCAUAGAAUCGGAAGAUUAAAGGGUGGGACUUUUUAGCCACCUGCCAUAAGAUGAGCCCAAGUGGGAUUAGGUNGUUGGUGAGGUNAAGGCUCACCAAGCCUNCGAUCUCUAGCUNGUCUNAGAGGAUGGCCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCGCNAUGGGGGGAACCCUGACGCAGCNAUGCCGCGUGAAUGAAGAAGGCCUUCGGGUUGUAAAGUUCUUUCGGUGGUGAGGAAGGUUNGUGUGUUAAUAGCACACUAAUUUGACGUUAGCCACAGAAGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUNAUACGGAGGGUGCGAGCGUUNAUCGGAAUAACUGGGCUUAAAGGGCACGCAGGCGGUAAAUUAAGUGAGAUGUGAAAUCCCCGAGCUUAACUUAGGAAUUGCAUUUCAGACUNGUUUACUAGAGUACUUUAGGGAGGGNUAGAAUUCCACGUGUAGCGGUGAAAUGCGUAGAGAUGUGGAGGAAUACCGAAGGCGAAGGCAGCCCCUUGGGAAGCUACUGACGCUCAUGUGCNNAAGCGUGGGGAGCAAACAGGAUUNGAUACCCUGGUAGUCCACGCUGUAAACGCUGUCGAUUUGGGGAUUGGGC-UUNN-GGCUUGGUGCCCGUAGCUAACGUGAUAAAUCGACCGCCUNGGGAGUACGGCCGCAAGGUUAAAACUCAAAUNAAUUGACGGGGGCCCGCACNAGCGGUGGAGCAUGUGGUUUNAUUCGANNNAACGCGAAGAACCUUACCUACUCUUGACAUCCUAAGAAUCCUGUAGAGAUACGGGAGUGCCUUCGGGAGCUUAGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUUGUGAAAUGUUGGGUUNAGUCCCGCAACGAGCGCAACCCUUAUCCUUUGUUGCCAGCACUUCGGGUGGGAACUCAAAGGAGACUGCCAGUGAUNAACUGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGGCCCUUACGAGUAGGGCUACACACGUGCUACAAUGGUGCAUACAGAGGGAAGCGAGCCUGCGAGGGGGAGCGAAUCUCAGAAAGUGCAUCUAAGUCCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGCAAAUCAGAAUGUUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGUUGUACCAGAAGUAGAUAGCUUAACCUUCGGGAGGGCGUUUACCACGGUAUGAUUCAUGACUmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ga.Leg.lyt -----mmmmmmmmmmmmmmmmmmmmmmmmmmmACGCUGGCGGCAUGCUUAACACAUGCAAGUCGAACGGCAGCACAGUCUAGCUUGCUAGACGGGUGGCGAGUGGCGAACGGGUGAGUAACGCGUAGGAAUAUACCUUGAAGAGGGGGACAACUUGGGGAAACUCAAGCUAAUACCGCAUAAUGUCUGAGGACGAAAGCCGGGGACCGUAAGGCCUGGCGCUUUAAGAUUAGCCUGCGUCCGAUUAGCUAGUUGGUAGGGAAAGGGCCUACCAAGGCGACGAUCGGUAGCUGGUCUGAGAGGAUGACCAGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGGGGAACCCUGAUCCAGCAAUGCCGCGUGUGUGAAGAAGGCCUGAGGGUUGUAAAGCACUUUCAGUGGGGAGGAGGCUUGUUAGGUUAAGAGCUAAAUAAGUGGACGUUACCCACAGAAGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUAAUCGGAAUUACUGGGCGUAAAGAGUGCGUAGGUGGUUUGGUAAGUUAUCUGUGAAAUCCCUGGGCUCAACCUGGGCAGGUCAGAUAAUACUGCUGAACUCGAGUAUGGGAGAGGGUAGUGGAAUUUCCGGUGUAGCGGUGAAAUGCGUAGAGAUCGGAAGGAACACCAGUGGCGAAGGCGGCUACCUGGCCUAAUACUGACACUGAGGCACGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGUCAACUAGCUGUUGGUUAUAUGAUAUAAUUAGUGGCGCAGCAAACGCGAUAAGUUGACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCUACCCUUGACAUACAGUGAACUUUGCAGAGAUGCAUUGGUGCCUUCGGGAACACUGAUACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGUAACGAGCGCAACCCUUAUUGUUCGUUGCCAGCGCUAAUGGCGGGAACUCUAAUGAGACUGCCGGUGACAAACCGGAGGAAGGCGGGGACGACGUCAAGUCAUCAUGGCC-UUACGGGUAGGGCUAGACACGUGCUACAAUGGUUGAUACAGAGGGAAGCGAAGGAGCGAUCUGGAGC-AAUCUUAGAAAGUCAAUCGUAGUCCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGCGAAUCAGCAUGUCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGCUG-ACCAGAAGUAGAUAGUCUAACCGCAAGGGGGACGUUUAmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ga.Mar.psy -----mmAGAGUUUGAUCAUGGCUCAGAUUGAACGCUGGCGGCAGGCUUAACACAUGCAAGUCGAACGGUAACAGGAAAUAGCUUGCUAUUUUGCUGACGAGUGGCGGACGGGUGAGUAAUGCUUGGGAAUUUGCCGAAAGGUGGGGGACAACAGUUGGAAACGACUGCUAAUACCGCAUAAUGUCUACGGACCAAAGGUGGCCUCUUUUAAUGCUAUCGCCUUUCGAUGAGCCCAAGUGGGAUUAGCUAGUUGGUAAGGUAAUGGCUUACCAAGGCUUCGAUCCCUAGCUGGUCUUAGAGGAUGACCAGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGAGGAAACUCUGAUGCAGCCAUGCCGCGUGUGUGAAGAAGGCUUUCGGGUUGUAAAGCACUUUCAGCGAGGAGGAAAGGGUGUUGGUUAAUAUCCAAUAUCUGUGACGUUACUCGCAGAAGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAAGGUGCGAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGCGCGUAGGCGGUUUAAUAAGUCAGAUGUGAAAGCCCAGGGCUCAACCUGGGAACUGCAUUUUGAACUGUUAAACUAGAGUUUUGUAGAGGANGGUAGAAUUUCAGGUGUAGCGGUGAAAUGCGUAGAGAUCUGAAGGAAUACCAGUGGCGAAGGCGGCCACCUGGACAAAGACUGACACUGAGGCGCGAAAGCGUGGGUAGCAAACGGGAUUAGAUACCCCGGUAGUCCACGCAGUAAACGAUGUCUAUUAGAAGUUUGUGGCUAUAUGCCGUGGGUUUCAAAGUUAACGCAUUAAAUAGACCGCCUGGGGAGUACGGCCGCAAGGUUAAAACUCAAAUGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCAUCCCUUGACAUCCAGAGAAUCACCUAGAGAUAGAUGAGUGCCUUCGGGAACUCUGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUUGUGAAAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUCCUUAGUUGCCAGCACUAAUGGUGGGAACUCUAGGGAGACUGCCGGUGAUAAACCGGAGGAAGGUGGGGACGACGUCAAGUCAUCAUGGCCCUUACGGGAUGGGCUACACACGUGCUACAAUGGCAAAUACAAAGGGUUGCUAACCUGCGAGGGUAUGCGAAUCUCAUAAAGUUUGUCGUAGUCCGGAUCGGAGUCUGCAACUCGACUCCGUGAAGUUGGAAUCGCUAGUAAUCGUGGAUCAGAAUGCCACGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGCUGCACCAGAAGUCAUUAGCUUAACCUUCGGGAUGGCGAUGACCACGGUGUGGUUCAUGACUGGGGUGAAGUCGUAACAAGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ga.Oce.pus CAACUUGAGAGUUUGAUCCUGGCUCAGAACGAACGCUGGCGGCAGGCCUAACACAUGCAAGUCGAGGGAGAAGCUAUC----UUCG----GAUAGUGGAGACCGGCAGACGGGUGAGUAACACGUGGGAACRUACCGAGUAGUGGGGGAUAACAGUUGGAAACGACUGCUAAUACCGCAUACGCCCUUCGGGGGAAAGA--------UUUA------UCGCUAUUCGAUUGGCCCGCGUUAGAUUAGCUAGUUGGUAAGGUAACGGCUUACCAAGGCGACGAUCUAUAGCUGGUUUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCGCAAUGGAGGAAACUCUGACGCAGCCAUGCCGCGUGAGUGAAGAAGGCCUUAGGGUUGUAAAGCUCUUUCAGACGUGAU--------------GAUG-----------AUGACAGUAGCGUCAAAAGAAGUUCCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAAGGGAACUAGCGUUGUUCGGAUUUACUGGGCGUAAAGAGCAUGUAGGCGGAUUGGACAGUUGAGGGUGAAAUCCCAGAGCUCAACUCUGGAACGGCCUUCAAUACUUCCAGUCUAGAGUCCGUAAGGGGGUGGUGGAAUUCCGAGUGUAGAGGUGAAAUUCGUAGAUAUUCGGAGGAACACCAGUGGCGAAGGCGACCACCUGGUACGGUACUGACGCUGAGAUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAGUGCUAGUUGUCAGGAUGUUUA-CAUCUUGGUGACGCAGCUAACGCAUUAAGCACUCCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGGCCNGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAANNAACGCGAAGAACCUUACCNAUUCUUGACAUACCUGUCGAUUUCCAGAGAUGGAUUUCUCAG-UCGCUGGACAGGAUACAGGUGCUGCAUGGCNGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCACCCCUAGUUGCCAGCAUUUAG-UUGGGCACUCUAUGGGAACUGCCGGUGACAAGCNGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGGCCCUUACGGAUUGGGCUACACACGUGCUACAAUGGUAACUACAGUGGGCAGCGACGUCGCGAGGCGAAGCAAAUCUC-CAAAAGUUAUCUCAGUUCGGAUUGUUCUCUGCAACUCGAGAGCAUGAAGUCGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUUGGUUUUACCCGAAGACGGUGGGCUAACCUUUAGGAGGCAGCCGGCCACGGUAAGGUCAGCGACUGGGNmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ga.Pho.pho -----mmmmmmmmmmmmmmmmmmmmmmAUUGAACGCUGGCGGCAGGCCUAACACAUGCAAGUCGAACGGUAACAGAU-GANACUUGUNUCAU-GCUGACGAACGGCGGACGGGUGAGUAAUGCCUGGGAAUAUACCCUGAUGUGGGGGAUAACUAUUGGAAACGAUAGCUAAUACCGCAUAAUCUCUUCGGAGCAAAGAGGGGGACCUUCGGGCCUCUCGCGUCAGGAUUAGCCCAGGUGGGAUUAGCUAGUUGGUGGGGUAAUGGCUCACCAAGGCGACGAUCCCUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGGGAAACCCUGAUGCAGCCAUGCCGCGUGUAUGAAGAAGGCCUUCGGGUUGUAAAGUACUUUCAGUUGUGAGGAAGGCGUUGGAGUUAAUAGCUUCAGCGCUUGACGUUAGCAACAGAAGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGUUCCGAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGCAUGCAGGCGGUCUGUUAAGCAAGAUGUGAAAGCCCGGGGCUCAACCUCGGAACAGCAUUUUGAACUGGCAGACUAGAGUCUUGUAGAGGGGGGUAGAAUUUCAGGUGUAGCGGUGAAAUGCGUAGAGAUCUGAAGGAAUACCGGUGGCGAAGGCGGCCCCCUGGACAAAGACUGACGCUCAGAUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGUCUACUUGAAGGUUGUGGCCUUGAGCCGUGGCUUUCGGAGCUAACGCGUUAAGUAGACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAUGAAUUGACGGAGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCUACUCUUGACAUCCAGAGAAUUCGCUAGAGAUAGCUUAGUGCCUUCGGGAACUCUGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUUGUGAAAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUCCUUGUUUGCCAGCACUAAUGGUGGGAACUCCAGGGAGACUGCCGGUGAUAAACCGGAGGAAGGUGGGGACGACGUCAAGUCAUCAUGGCCCUUACGAGUAGGGCUACACACGUGCUAGAAUGGCGUAUAGAGAGGGCUGCAAGCUAGCGAUAGUGAGCGAAUCCGAGAAAGUACGUCGUAGUCCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGUGAAUCAGAAUGUCACGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGCUGCACCAGAAGUAGAUAGCUUAACCUUCGGGAGGGCGUUUACCACGGUGUGGUUCAUGACUGGGGUGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ga.Pse.asp -----mmmmmmmmmmmmmmmmmmmmmmAUUGAACGCUGGCGGCAGGCCUAACACAUGCAAGUCGAGCGGAUGAGAAGAG---CUUG---CUCUUCGAUUCAGCGGCGGACGGGUGAGUAAUGCCUAGGAAUCUGCCUGGUAGUGGGGGACAACGUUUCGAAAGGAACGCUAAUACCGCAUACGUCCUACGGGAGAAAGCAGGGGACCUUCGGGCCUUGCGCUAUCAGAUGAGCCUAGGUCGGAUUAGCUAGUUGGUGAGGUAAUGGCUCACCAAGGCGACGAUCCGUAACUGGUCUGAGAGGAUGAUCAGUCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGAAAGCCUGAUCCAGCCAUGCCGCGUGUGUGAAGAAGGUCUUCGGAUUGUAAAGCACUUUAAGUUGGGAGGAAGGGCAUUAACCUAAUACGUUAGUGUUUUGACGUUACCGACAGAAUAAGCACCGGCUAACUCUGUGCCAGCAGCCGCGGUAAUACAGAGGGUGCAAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGCGCGUAGGUGGUUCGUUAAGUUGGAUGUGAAAUCCCCGGGCUCAACCUGGGAACUGCAUCCAAAACUGGCGAGCUAGAGUAGGGUAGAGGGUGGUGGAAUUUCCUGUGUAGCGGUGAAAUGCGUAGAUAUAGGAAGGAACACCAGUGGCGAAGGCGACCACCUGGACUCAUACUGACACUGAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGUCAACUAGCCGUUGGGAACCUUGAGUUCUUAGUGGCGCAGCUAACGCAUUAAGUUGACCGCCUGGGGAGUACGGCCGCAAGGUUAAAACUCAAAUGUAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAGGCCUUGACAUGCAGAGAACUUUCCAGAGAUGGAUUGGUGCCUUCGGGAACUCUGACACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGUAACGAGCGCAACCCUUGUCCUUAGUUACCAGCACUCAUGGUGG-CACUCUAAGGAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGGCCCUUACGGCCUGGGCUACACACGUGCUACAAUGGUCGGUACAGAGGGUUGCCAAGCCGCGAGGUGGAGCUAAUCCCACAAAACCGAUCGUAGUCCGGAUCGCAGUCUGCAACUCGACUGCGUGAAGUCGGAAUCGCUAGUAAUCRCGAAUCAGAAUGUCGCGGUGAAUACGUUCCCGGGSCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGUUGGACCAGAAGUAGCUAGUCUAACCUUCGGGAGGACGGUUACCACGGUGUGAUUCAUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCmmmmmmmmmmmmm-----
ga.Sal.typ -----mmAGAGUUUGAUCCUGGCUCAGAUUGAACGCUGGCGGCAGGCCUAACACAUGCAAGUCGAACGGUAACAGGAAGCAGCUUGCUGCUUUGCUGACGAGUGGCGGACGGGUGAGUAAUGUCUGGGAAACUGCCUGAUGGAGGGGGAUAACUACUGGAAACGGUGGCUAAUACCGCAUAACGUCGCAAGACCAAAGAGGGGGACCUUCGGGCCUCUUGCCAUCAGAUGUGCCCAGAUGGGAUUAGCUUGUUGGUGAGGUAACGGCUCACCAAGGCGACGAUCCCUAGCUGGUCUGAGAGGAUGACCAGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGCAAGCCUGAUGCAGCCAUGCCGCGUGUAUGAAGAAGGCCUUCGGGUUGUAAAGUACUUUCAGCGGGGAGGAAGGUGUUGUGGUUAAUAACCGCAGCAAUUGACGUUACCCGCAGAAGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGCACGCAGGCGCUCUGUCAAGUCGGAUGUGAAAUCCCCGGGCUCAACCUGGGAACUGCAUUCGAAACUGGCAGGCUUGAGUCUUGUAGAGGGGGGUAGAAUUCCAGGUGUAGCGGUGAAAUGCGUAGAGAUCUGGAGGAAUACCGGUGGCGAAGGCGGCCCCCUGGACAAAGACUGACGCUCAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGUCUACUUGGAGGUUGUGCCCUUGAGGCGUGGCUUCCGGAGCUAACGCGUUAAGUAGACCGCCUGGGGAGUACGGCCGCAAGGUUAAAACUCAAAUGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCUGGUCUUGACAUCCACAGAACUUUCCAGAGAUGGAUUGGUUCCUUCGGGAACUGUGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUUGUGAAAUGUCGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUCCUUUGUUGCCAGCGGUUAGGCCGGGAACUCAAAGGAGACUGCCAGUGAUAAACUGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGGCCCUUACGACCAGGGCUACACACGUGCUACAAUGGCGCAUACAAAGAGAAGCGACCUCGCGAGAGCAAGCGGACCUCAUAAAGUGCGUCGUAGUCCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGUGGAUCAGAAUGCCACGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGUUGCAAAAGAAGUAGGUAGCUUAACCUUCGGGAGGGCGCUUACCACUUUGUGAUUCAUGACUGGGGUGAAGUCGUAACAAGGUAACCGUAGGGGAACCUGCGGCUGGAUCACCUCCUU-
ga.Vib.cho -----mmAGAGUUUGAUNNUGGCUCAGAUUGAACGCUGGCGGCAGGCCUAACACAUGCAAGUCGAGCGGCAGCACAGAGGAACUUGUUCCUUGGGUGGCGAGCGGCGGACGGGUGAGUAAUGCCUGGGAAAUUGCCCGGUAGAGGGGGAUAACCAUUGGAAACGAUGGCUAAUACCGCAUAACCUCGCAAGAGCAAAGCAGGGGACCUUCGGGCCUUGCGCUACCGGAUAUGCCCAGGUGGGAUUAGCUAGUUGGUGAGGUAAGGGCUCACCAAGGCGACGAUCCCUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGCAAGCCUGAUGCAGCCAUGCCGCGUGUAUGAAGAAGGCCUUCGGGUUGUAAAGUACUUUCAGUAGGGAGGAAGGUGGUUAAGUUAAUACCUUAAUCAUUUGACGUUACCUACAGAAGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGCAUGCAGGUGGUUUGUUAAGUCAGAUGUGAAAGCCCUGGGCUCAACCUAGGAAUCGCAUUUGAAACUGACAAGCUAGAGUACUGUAGAGGGGGGUAGAAUUUCAGGUGUAGCGGUGAAAUGCGUAGAGAUCUGAAGGAAUACCGGUGGCGAAGGCGGCCCCCUGGACAGAUACUGACACUCAGAUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGUCUACUUGGAGGUUGUGCCCUAGAGGCGUGGCUUUCGGAGCUAACGCGUUAAGUAGACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAUGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCUACUCUUGACAUCCAGAGAAUCUAGCGGAGACGCUGGAGUGCCUUCGGGAGCUCUGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUUGUGAAAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUCCUUGUUUGCCAGCACUAAUGGUGGGAACUCCAGGGAGACUGCCGGUGAUAAACCGGAGGAAGGUGGGGACGACGUCAAGUCAUCAUGGCCCUUACGAGUAGGGCUACACACGUGCUACAAUGGCGUAUACAGAGGGCAGCGAUACCGCGAGGUGGAGCGAAUCUCACAAAGUACGUCGUAGUCCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGCAAAUCAGAAUGUUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGCUGCAAAAGAAGCAGGUAGUUUAACCUUCGGGAGGACGCUUGCCACUUUGUGGUUCAUGACUGGGGUGAAGUCGUAACAAGGUAGCGCUAGGGGAACCUGGCGCUGGAUCACCUCCUUU
ga.Xan.pis -----mmmmmmmmmmmmmmmmmmmmmmAGUGAACGCUGGCGGCAGGCCUAACACAUGCAAGUCGAACGGCAGCACAGUAAGACUUGUCUUAUGGGUGGCGAGUGGCGGACGGGUGAGGAAUACAUCGGAAUCUACUCUUUCGUGGGGGAUAACGUAGGGAAACUUACGCUAAUACCGCAUACGACCUACGGGUGAAAGCGGAGGACCUUCGGGCUUCGCGCGAUUGAAUGAGCCGAUGUCGGAUUAGCUAGUUGGCGGGGUAAAGGCCCACCAAGGCGACGAUCCGUAGCUGGUCUGAGAGGAUGAUCARCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGCAAGCCUGAUCCAGCCAUGCCGCGUGGGUGAAGAAGGCCUUCGGGUUGUAAAGCCCUUUUGUUGGGAAAGAAAAGCAGUCGGUUAAUACCCGAUUGUUCUGACGGUACCCAAAGAAUAAGCACCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAAGGGUGCAAGCGUUACUCGGAAUUACUGGGCGUAAAGCGUGCGUAGGUGGUGGUUUAAGUCUGUUGUGAAAGCCCUGGGCUCAACCUGGGAAUUGCAGUGGAUACUGGGUCACUAGAGUGUGGUAGAGGGUAGCGGAAUUCCCGGUGUAGCAGUGAAAUGCGUAGAGAUCGGGAGGAACAUCCGUGGCGAAGGCGGCUACCUGGACCAACACUGACACUGAGGCACGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGCGAACUGGAUGUUGGGUGCUUUG-GCACGCAGUAUCGAAGCUAACGCGUUAAGUUCGCCGCCUGGGGAGUACGGUCGCAAGACUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGUAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCUGGUCUUGACAUCCACGGAACUUUCCAGAGAUGGAUUGGUGCCUUCGGGAACCGUGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCCUUAGUUGCCAGCACUAAUGGUGGGAACUCUAAGGAGACCGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGGCCCUUACGACCAGGGCUACACACGUACUACAAUGGUAGGGACAGAGGGCUGCAAACCCGCGAGGGCAAGCCAAUCCCAGAAACCCUAUCUCAGUCCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGCAGAUCAGCAUGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUUUGUUGCACCAGAAGCAGGUAGCUUAACCUUCGGGAGGGCGCUUGCCACGGUGUGGCCGAUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAUCGGAAGGUGCmmmmmmmmmmmmm-----
ra.Dei.mur -----mmmmmmmmmmmmmmmmmmmmAGGGUGAACGCUGGCGGCGUGCUUAAGACAUGCAAGUCGAACGGCCCU---------UUCG--------GAGGGCAGUGGCGCACGGGUGAGUAACGCGUAACGACCUGCCCCCAAGUCUGGAAUAACCCUCCGAAAGGAGGGCUAAUACCGGAUGUGCUGCUUGCAGUAAAGGC-------GCGA-----GCCGCUUGGGGAUGGGGUUGCGUUCCAUCAGCUAGAUGGUGGGGUAAAGGCCUACCAAGGCGACGACGGAUAACCGGCCUGAGAGGGUGGCCGGUCACAGGGGCACUGAGACACGGGUCCCACUCCUACGGGAGGCAGCAGUUAGGAAUCUUCCCCAAUGGACGAAAGUCUGAGGGAGCGACGCCGCGUGAGGGAUGAAGGUCUUCGGAUUGUAAACCUCUGA-AUCAGGGACGAAAGACGCU----UUA------GGCGGGAUGACGGUACCUGAG-UAACAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUACCCGGAAUCACUGGGCGUAAAGGGCGUGUAGGCGGUACUUUAAGUCUGACUUUAAAGACCGUGGCUGAACCACGGAAGUGGGUUGGAUACUGGCGUGCUGGACCUCUGGAGAGACAACCGGAAUUCCUGGUGUAGCGGUGGAAUGCGUAGAUACCAGGAGGAACACCGAUGGCGAAGGCAGGUUCUUGGACAGAAGGUGACGCUGAGGCGCGAAAGUGUGGGGAGCGAACCGGAUUAGAUACCCGGGUAGUCCACACCCUAAACGAUGUACGUUGGCUGAUGGCGG-GAUG--CCGUCAUGGGCGAAGCUAACGCGAUAAACGUACCGCCUGGGAAGUACGGCCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAGGUCUUGACAUCCCAUGAACCUUGCAGAGAUGUGAGGGUGCCUUCGGGAACAUGGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGCCUUGUGUUGCCAGCAGUUCGGCUGGGCACUCACGAGGGACUGCCUGUGA-AAGCAGGAGGAAGGCGGGGAUGACGUCUAGUCAGCAUGGUCCUUACGACCUGGGCGACACACGUGCUACAAUGGAUGGUACAACGCGCAGCCAAGUCGCGAGACUGAGCGAAUCGCUGAAAGCCAUCCCCAGUUCAGAUCGGAGUCUGCAACUCGACUCCGUGAAGUUGGAAUCGCUAGUAAUCGCGGGUCAGCAUACCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUAGAUUGCAGCUGAAACCGCCGGGAGCU--UCAC---GGCAGGCGUCUAGGCUGUGGUUUAUGACUGGGGUGAAGUCGUAACAAGGUAACUGUACCGGAAGGUGCGGCUGGAmmmmmm-----
ra.Dei.rad UUUAUGGAGAGUUUGAUCCUGGCUCAGGGUGAACGCUGGCGGCGUGCUUAAGACAUGCAAGUCGAACGCGGUC---------UUCG---------GACCGAGUGGCGCACGGGUGAGUAACACGUAACGACCUACCCAGAAGUCAUGAAUAACUGGCCGAAAGGUCAGCUAAUACGUGAUGUGGUGCGUGCACUAAAGA--------UUUA------UCGCUUCUGGAUGGGGUUGCGUUCCAUCAGCUGGUUGGUGGGGUAAAGGCCUACCAAGGCGACGACGGAUAGCCGGCCUGAGAGGGUGGCCGGCCACAGGGGCACUGAGACACGGGUCCCACUCCUACGGGAGGCAGCAGUUAGGAAUCUUCCACAAUGGGCGCAAGCCUGAUGGAGCGACGCCGCGUGAGGGAUGAAGGUUUUCGGAUCGUAAACCUCUGA-AUCUGGGACGAAAGAGCC-----UUCG------GGCAGAUGACGGUACCAGAG-UAAUAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUACCCGGAAUCACUGGGCGUAAAGGGCGUGUAGGCGGAUAUUUAAGUCUGGUUUUAAAGACCGAGGCUCAACCUCGGGAGUGGACUGGAUACUGGAUGUCUUGACCUCUGGAGAGGUAACUGGAAUUCCUGGUGUAGCGGUGGAAUGCGUAGAUACCAGGAGGAACACCAAUGGCGAAGGCAAGUUACUGGACAGAAGGUGACGCUGAGGCGCGAAAGUGUGGGGAGCAAACCGGAUUAGAUACCCGGGUAGUCCACACCCUAAACGAUGUACGUUGGCUAAGCGCAG-GAUG--CUGUGCUUGGCGAAGCUAACGCGAUAAACGUACCGCCUGGGAAGUACGGCCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAGGUCUUGACAUGCUAGGAAGGCGCUGGAGACAGCGCCGUGCCUUCGGGAACCUAGACACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGCUUCCAGUUGCCAGCA-UUCAGUUGGGCACUCUGGAGGGACUGCCUGUGA-AAGCAGGAGGAAGGCGGGGAUGACGUCUAGUCAGCAUGGUCCUUACGUCCUGGGCUACACACGUGCUACAAUGGAUAGGACAACGCGCAGCAAACAUGUGAGUGUAAGCGAAUCGCUGAAACCUAUCCCCAGUUCAGAUCGGAGUCUGCAACUCGACUCCGUGAAGUUGGAAUCGCUAGUAAUCGCGGGUCAGCAUACCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUAGAUUGCAGUUGAAACCGCCGGGAGCC--UCAC---GGCAGGCGUCUAGACUGUGGUUUAUGACUGGGGUGAAGUCGUAACAAGGUAACUGUACCGGAAGGUGCGGUUGGAUCACCUCCUUU
sp.Bor.par -----mmmmAGUUUGAUCCUGGCUUAGAACUAACGCUGGCAGUGCGUCUUAAGCAUGCAAGUCAGACGGAAUGUA-------GCAA-------UACAUUCAGUGGCGAACGGGUGAGUAACGCGUGGAAAUCUACCUAUGAGAUGGGGAUAACUAUUAGAAAUAGUAGCUAAUACCGAAUAAGGUCGAUGGAUGAAAGAAGCCU---UUAA--AGCUUCGCUUGUAGAUGAGUCUGCGUCUUAUUAGCUAGUUGGUAGGGUAAGAGCCUACCAAGGCUAUGAUAAGUAACCGGCCUGAGAGGGUGAACGGUCACACUGGAACUGAGAUACGGUCCAGACUCCUACGGGAGGCAGCAGCUAAGAAUCUUCCGCAAUGGGCGAAAG-CUGACGGAGCGACACUGCGUGAACGAAGAAGGUCGAAAGAUUGUAAAGUUCUUUUAUAAAUGAGGAAUAAGCUUUGUAGAAA-UGACAAGGUGAUGACGUUAAUUUAUGAAUAAGCCCCGGCUAAUUACGUGCCAGCAGCCGCGGUAAUACGUAAGGGGCGAGCGUUGUUCGGGAUUAUUGGGCGUAAAGGGUGAGUAGGCGGAUAUGUAAGUCAUGCGUAAAAUACCACAGCUCAACUGUGGAACUAUGCUGGAAACUGCAUGACUAGAGUCUGAUAGGGGAAGUUAGAAUUCCUGGUGUAAGGGUGGAAUCUGUUGAUAUCAGGAAGAAUACCAGAGGCGAAGGCGAACUUCUGGGUCAAGACUGACGCUGAGUCACGAAAGCGUAGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCUACGCUGUAAACGAUGCACACUUGGUGUUAAUC--GAAA---GGUUAGUACCGAAGCUAACGUGUUAAGUGUGCCGCCUGGGGAGUAUGCUCGCAAGAGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGAUACGCGAGGAACCUUACCAGGGCUUGACAUAACAGGAUGUAGUUAGAGAUAACUAUUCCCCGUUUGGGGUCUGUAUACAGGUGCUGCAUGGUUGUCGUCAGCUCGUGCUGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUUGUCUGUUACCAGCAUUAAAGAUGGGGACUCAGACGAGACUGCCGGUGAUAAGCCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGGCCCUUAUGUCCUGGGCUACACACGUGCUACAAUGGCCUGUACAAAGCGAUGCGAAACAGUGAUGUGAAGCAAAACGCAUAAAGCAGGUCUCAGUCCAGAUUGAAGUCUGAAACUCGACUUCAUGAAGUUGGAAUCGCUAGUAAUCGUAUAUCAGAAUGAUACGGUGAAUACGUUCUCGGGCCUUGUACACACCGCCCGUCACACCACCCGAGUUGAGGAUACCCGAAGCUAUUAUUCUAACCGCAAGGAGGAAGGUAUCUAAGGUAUGUUUAGUGAGGGGGGUGAAGUCGUAACAAGGUAGCCGUACUGGAAAGUGUGGCUGGAUCACCU-----
sp.Lep.mey -----mmmmmmmmmmmmmmmmmmmmmmmmSUARCGCUGGCGGCGCGUCUUAAACAUCCAA-UCAAGCGGAGUA---------GCAA---------UACUCAGCGGCGAACGGGUGAGUAACACGUGGGAAUCUUCCUCCGAGUCUGGGAUAACUUUUCGAAAGGGAAGCUAAUACUGGAUAGUCCCAUAAGGGUAAAGA--------UUCA------UUGCUUGGAGAUGAGCCCGCGUCCGAUUAGCUAGUUGGUGAGGUAAUGGCUCACCAAGGCGACGAUCGGUAGCCGGCCUGAGAGGGUGUUCGGCCACAAUGGAACUGAGACACGGUCCAUACUCCUACGGGAGGCAGCAGUUAAGAAUCUUGCUCAAUGGGGGGAACCCUGAAGCAGCGACGCCGCGUGAACGAUGAAGGUCUUCGGAUUGUAAAGUUCAAUAAGCAGGGAAAAAUAAGCA-----GCAA-------UGUGAUGAUGGUACCUGCCUA--AAGCACCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAUGGUGCAAGCGUUGUUCGGAAUCAUUGGGCGUAAAGGGUGCGUAGGCGGACAUGUAAGUCAGGUGUGAAAACUGGGGGCUCAACUCCCAGCCUGCACUUGAAACUAUGUGUCUGGAGUUUGGGAGAGGCAAGUGGAAUUCCAGGUGUAGCGGUGAAAUGCGUAGAUAUCUGGAGGAACACCAGUGGCGAAGGCGACUUGCUGGCCUAAAACUGACGCUGAGGCACGAAAGCGUGGGUAGUGAACGGGAUUAGAUACCCCGGUAAUCCACGCCCUAAACGUUGUCUACCAGUUGUUGGGGGUUUAA--CCCUCAGUAACGAACCUAACGGAUUAAGUAGACCGCCUGGGGACUAUGCUCGCAAGAGUGAAACUCAAAGGAAUUGACGGGGGUCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGAUACGCGAAAAACCUCACCUAGGCUUGACAUGAGUGGAAUCAUGUAGAGAUACAUGAGCC--UUCG--GGCCGCUUCACAGGUGCUGCAUGGUUGUAAUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCACCUUAUGUUGCCAUCA-UUCAGUUGGGCACUCGUAAGGAACUGCCGGUGACAAACCGGAGGAAGGCGGGGAUGACGUCAAAUCCUCAUGGCCUUUAUGUCUAGGGCAACACACGUGCUACAAUGGCCGGUACAAAGGGUAGCCAACUCGCGAGGGGGAGCUAAUCUCAAAAACCCGGUCCCAGUUCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGACCUUGUACACACC-CCCGUCACACCACCUGAGUGGGGAGCACCCGAAGUGGUCUUGCCAACCGCAAGGAAGCAGACUACUAAGGUGAAACUCGUGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
sp.Tre.soc -----mmmmmGUUUGAUCCUGGCUCAGAACGAACGCUGGCGGCGCGUCUUAACCAUGCAAGUCGAGCGGCAGGCA-------GCAA-------UGCCGAGAGCGGCGGACUGGUGAGUAACACGUGGAAACGAACCCCGAUGCCCGGGACAGCCUGUAGAAAUAGAGGGUAAUACCGGAUAGAUCAGGAACGGGAAAGGAGC-----UUCG---GCUCCGCGCCGGGAUCGGUCUGCGGCCCAUCAGCUAGACGGCGGGGUAAGGGCCCGCCGUGGCGAGGACGGGUAUCCGGCCUGAGAGGGCGGACGGACACAUUGGGACUGAGAUACGGCCCAGACUCCUACGGGAGGCAGCAGGUAAGAAUAUUCCGCAAUGGGGGGAACCCUGACGGAGCGACGCCGCGUGAACGAAGAAGGCCGGAAGGUUGUAAAGUUCUUUUCUGUCCGAGGAAUAAGUGUAG-GGAAA-UGCCUGCAUGGUGACGGUAGGGCAGGAAUAAGCACCGGCUAAUUACGUGCCAGCAGCCGCGGUAACACGUAAGGUGCGAGCGUUGUUCGGAAUUAUUGGGCGUAAAGGGCAUGCAGGCGGGUCGCCAAGCUUGGUAAGAAAUACCGGGGCUCAACUCCGGAGCUAUAUUGAGAACUGGCGAGCUAGAGUUGCCGAAGGGUAUCCGGAAUUCCGCGUGAAGGGGUGAAAUCUGUAGAUAUGCGGAAGAACACCGAUGGCGAAGGCAGGAUACCGGCGGACGACUGACGCUGAGGUGCGAAGGUGCGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCGCACAGUCAACGAUGUACACUGGGCGUGUGCGC-AAGA--GCGUGCGUGCCGAAGCAAACGCGAUAAGUGUACCGCCUGGGGAGUAUGCCCGCAAGGGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGGUACGCGAGGAACCUUACCUGGGUUUGACAUCAGAGGGAUCAUAUAGAGAUAUGUGAGCGUAGCAAUACGGCUCUUGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUACUGCCGGUUACUAACAGUAAUGCUGAGGACUCAGGCGGAACUGCCUGCGACAAGCAGGAGGAAGGCGGGGACGACGUCAAGUCAUCAUGGCCCUUAUGUCCAGGGCUACACACGUGCUACAAUGGCCGCCACAGAGCGGGGCGAAGCCGAGAGGCGGAGCAGAACGCAGAAAAGCGGUCGUAGUCCGGAUUGAAGUCUGAAACUCGACUUCAUGAAGCUGGAAUCGCUAGUAACCGCACAUCAGCACGGCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUCCGAGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
sp.Tre.suc GGCAUGGAGAGUUCGAUCCUGGCUCAGAACGAACGCUGGCGGCGCGUCUUAAGCAUGCAAGUCGGGCGGGAUUCACGCG---CUUG---CGCGUGGUGAGAGCGGCGGACUGGCGAGUAACACGUGGGGACGCGCCCUCCGGACGGGAAUAGCCUGCAGAAAUGCAGGGUAAUGCCGGAUGCGAACUGGAGUGGAAAGCCCC-----CACG---GGGGCGCCGGAGGAGCGGCCCGCGGCCCAUCAGCUGGUAGGCGGUGCAAGGGACCACCUAGGCUACGACGGGUACCCGGCNUAAGAGGGCGGACGGGCACAUUGGGACUGAGAUACGGCCCAGACUCNUACGGGAGGCAGCAGCUAAGAAUAUUCCGCAAUGGGGGGAACNNUGACGGAGCGACGCCGCGUGGGCGAGGAAGGCCGGAAGGUUGUAAAGCCCUUUUGCGCGCGAGGAAUNAGGGGAG-GGGAA-UGCCUUCCCGGUGACUGUAGCGCGCGAAUAAGCGCCGGCUAAUUACGUGCCAGCAGCCGCGGUNACACGUAAGGCGCNAGCGUUGUNCGGAAUNAUUGGGCGUAAAGGGCGUGUAGGCGGCCCUGCAAGCCUNGCGUGAAAUCCCGGGGCNCAACCCCGNAACCGCGCUGGGAACUGCUGGGCUUGAGCCGCUGUGGCGCAGCCGGAAUUNCAGGUGUAGGGGUGAAAUCUGUAGAUAUCUGGAAGAACACCGAUGGCGAAGGCAGGCUGCGAGCGGACGGCUGACGCUGAGGCGCGAAGGCGCGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCGCGCAGUAAACGAUGCACACUGGGUGNUCGGGC-AUGA--GCCCGGNUGCCGAAGCGAACGCGUUAAGUGUGCCGCCUGGGGAGUAUGCCCGCAAGGGUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUAUAAUUCGANNNNUAGCGAGGAACCUUACCUGGGCUUGACAUAACAGGGACCGCCUGGAGACAGGCGGACGCAGCAAUGCGCCUGUGAACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUGCCGCCAGUUGCCAGCAUUAGAGGUGGGCACUCUGGCGGAACUGCCGGCGACAAGCAGGAGGAAGGCGGGGACGACGUCAAGUCAUCAUGGCCCUUAUGUCCAGGGCUACACACGUGCUACAAUGGCAGGCACAGAGUGAAGCGAGGCCGCGAGGCGGAGCGAAACGCAGAAAACCUGCCGUAGUCCGGAUCGGAGUCUGAAACCCGACUCCGUGAAGCUGGAAUCGCUAGUAAUCGCGCAUCAGCACGGCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUCCGAGUCGGGGAUUCCCGAAGCGGGCAGGCCAACCGAAAGGGGGCNNCUCUNNAAGGUNUGCUUmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
th.The.afr UUCAUGGAGGGUUUGAUCCUGGCUCAGGGUGAACGCUGGCGGCGUGCCUUACACAUGCAAGUCGAGCGAAGCUGCUGGUGGAUUCGANGCCNGUAGACUNAGCGGCGGACGGGUGAGUAACGCGUAGGGACCUACCCCUCAGAGGGGGAUAACUGGGGGAAACCUCAGCUAAUACCCNAUACGUUCUAAGGAAGAAAGGAGC-----AAUA---GCUCUGCUGAGNNNGGGGCCUGCGACCCAUCAGGUAGUUGGUGAGGUAACGGCUCACNAAGCCUACGACGGGUAGCCGGUCUGAGAGGAUGGCCGNCNACAAGGGCACUGAGACACGGGCCNNACUCCUACGGGAGGCAGCAGUGGGGGAUUUUGGACAAUGGGCGAAAGCCUNAUCCAGCGACGCCGNGUGCGGGACGAAGCCCUUCGGGGUGUAAACCGCUGUGGUGGGAGACGAAUAAGGUGAG-GGGAA-AGCCUCACUGAUGACGGUAUCCCACUAGAAAGCCCCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGGGCNAGCGUUACCCGGAUUUACUGGGCGUAAAGGGGGCGUAGGCGGCCGUGAAAGUCCGGUGUGAAAACUCACGGCUCAACCGUGGGACUGCGCUGGAAACUACACGGCUUGAGGACGGUAGAGGGAGACGGAACUGCUGGUGUAGGGGUGAAAUCCGUAGAUAUCAGCAGGAACGCCGGUGGAGAAGUCGGUCUCCUGGGCCGUNCCUGACGCUGAGGCCCNAAAGCUAGGGGAGCAAACCGGAUUAGAUACCCGGGUAGUCCUAGCCGUAAACGAUGCCCNCUAGGUGUGGGGGAG-UAA-UUCCUCCGUGCUGAAGCUAACGCGAUAAGUGGGCCGCCUGGGGAGUAUGCCCGCAAGGGUGAAACUCAAAGGAAUUGACGGGACCCNGCACAAGCGGUGGAGCGUGUGGUUUAAUUGGACGCUAAGCCAAGAACCUUACCAGGGCUUGACAUGUGGUGUACUGNCNCGAAAGGGGAGGGCCUGGUUACGGGAGCCAGCACAGGUGGUGCACGGUCGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUGCCCUUAGUUGCCAGCGGUUCGGCCGGGCACUCUAAGGGNACUGCCGGCGACGAGCCGGAGGAAGGAGGGGAUGACGUCAGAUACUCGUGCNCCUUAUGCCCUNGGCGACACACGCGCUACAAUGGGUGGGACAGCGGGAAGCGAGCCAGCGAUGGUGAGCGAAGCCCUUAAACCCACCCUCAGUUCGGAUUGCAGGCUGAAACCCGCCUGCAUGAAGCCGGAAUCGCUAGUAAUCGCGGAUCAGCCCGCCGCGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm----mmmm---mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
th.The.hyp -----mmmmGGUUUGAUCCUGGCUCAGGGUGAACGCUGGCGGCGUGCCUAACACAUGCAAGUCGAGCGGGUACCC-------GCAA-------GGGUACCAGCGGCGCACGGGUGAGUAACACGUGGGAAUCUACCCCUCGGAGGGGGAUAACCGGGGGAAACCCCGGCUAAUACCCCAUACGAUCGAAGGA-GAAAGGGGC-----GUUU---CCUCCGCCGAGGGAUGAGCCCGCGUCCCAUCAGGUAGUUGGUGGGGUAAUGGCCCACCAAGCCUACGACGGGUAGCCGGCCUGAGAGGGUGGUCGGCCACAAGGGCACUGAGACACGGGCCCUACUCCUACGGGAGGCAGCAGUGGGGAAUCUUGGACAAUGGGCGAAAGCCUGAUCCAGCGACGCCGCGUGGGGGAUGAAGCCCUUCGGGGUGUAAACCCCUGUUGCGAGGGAGGAAUAAGGCCUG-GGAAA-UGCCAGGCCGAUGACUGUACCUCGCGAGGAAGCCCCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGGGCGAGCGUUACCCGGAUUCACUGGGCGUAAAGCGGGUGUAGGCGGCUCGGUAAGUCGGGUGUGAAAUCCCACAGCUCAACUGUGGAAUUGCGCCCGAAACUGCUGAGCUUGGGGCCGGUAGAGGGAGACGGAACUGCCGGUGUAGGGGUGAAAUCCGUAGAUAUCGGCAGGAACGCCGGUGGGGAAGCCGGUCUCCUGGGCCGCGCCCGACGCUGAGACCCGAAAGCUAGGGGAGCAAACCGGAUUAGAUACCCGGGUAGUCCUAGCCGUAAACGAUGCCCACUAGGUGUGGGGGA-UUAA-UUCCUCCGUGCUGUAGCUAACGCGUUAAGUGGNCCGCCUGGGGAGUACGCCCGCAAGGGUGAAACUCAAAGGAAUUGGCGGGACCCCGCACAAGCGGUGGAGCGCGUGGUUUAAUUGGAUGCUGAGCCAAGAACCUUACCAGGGUUUGACAUGAGGUGUACCGACCCGAAAGGGGAGGGCCCCUUUUGGGGAGGCUGCACAGGUGGUGCACGGCCGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAAUCCCUGCCCUUAGUUGACAACGGUUCGGCCGGGUACUCUAAGGGGACUGCCGGUGACGANUCGGAGGAAGGAGGGGACGACGUCAGGUACUCGUUCCCUUUAUGCCCUGGGCUACACACGCGCUACACUGGGUGGUACAAUGGGUUGCGACCCCNCGAGGGGGAGCCAAUCCC-UAAAACCACCCCCAGUUCGGAUCGCAGGCUGCAACCCGCCUGCGUGAAGCCGGAAUCGCUAGUAAUCGCGGAUCAACCCGCCGCGGUGAAUACGUUCCCGGGGUUUGCACACACCGCCCGUCAAACCACCCGAGUCGGGGGCACCCGAAGACGCUCUCCUAACCGAAAGGAGGGAGGCGUUGAGGGUGAACCUGGUGAGGGGGGCUAAGUCGUAACAAGGUAACCGUACUGGAAGGUGCmmmmmmmmmmmmm-----
th.The.sub -----mmmmmmmmmmmmmmmmmmmmAGGGUGAACGCUGGCGGCGUGCUUAACACAUGCAAGUCGCGCGGGGA-AACCCC---UUCG---GGGGGAGUACCAGCGGCGCACGGGUGAGUAACACGUGGGAACCUACCCCUCAGCGGGGGAUAACCGGGGGAAACUCCGGCUAAUACCCCAUAUUAUCGACAGAUGAAAGGAGC-----GUUU---GCUUCGUUGAGGGAUGGGCCCGCGGCCCAUCAGGUAGUUGGUGAGGUAAUGGCUCACCAAGCCUACGACGGGUAGCCGACCUGAGAGGGUGACCGGCCACAAGGGCACUGAGACACGGGCCCUACUCCUACGGGAGGCAGCAGUGGGGAAUUUUGGACAAUGGGCGAAAGCCUGAUCCAGCGACGCCGCGUGAGGGACGAAGCCCUUCGGGGUGUAAACCUCUGUUGUGAGGGACGAAUAAGAUCUG-GGAAA-UGCCAGAUCGAUGACGGUACCUCACGAGAAAGCCCCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGGGCAAGCGUUACCCGGAUUCACUGGGCGUAAAGGGGGCGCAGGCGAUCCAGUAUGUCGGGUGUGAAAUCCCACAGCUCAACUGUGGAAUCGCACCCGAAACUACUGGGCUUGGGGCUGGUAGAGGGAGACGGAACUGCUGGUGUAGGGGUGAAAUCCGUAGAUAUCAGCAGGAACGCCGGUGGGGAAGCCGGUCUCCUGGGCCAAGCCCGACGCUGAGGCCCGAAAGCUAGGGGAGCAAACCGGAUUAGAUACCCGGGUAGUCCUAGCCGUAAACGAUGCCCACUAGGUGUGGGGGAG-UCA-UUCCUCCGUGCUGUAGCUAACGCGUUAAGUGGGCCGCCUGGGGAGUACGCCCGCAAGGGUGAAACUCAAAGGAAUUGGCGGGGACCCGCACAAGCGGUGGAGCGUGUGGUUUAAUUGGAUGCUAAGCCAAGAACCUUACCAGGGCUUGACAUGAGGUGUACCAACCCGAAAGGGGAAGGCCCUUUUUAGGGAGCCUGCACAGGUGGUGCACGGCCGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUGCCCUU-GUUGCCAGCGGUUCGGCCGGGCACUCUAAGGGGACCGCCGGCGACGAGCCGGAGGAAGGAGGGGACGACGUCAGGUACUCGUGCCCUUUAUGCCCUGGGCUACACACGCGCUACAAUGGGUGGUACAGUGGGUCGCGACCUCGCGAGAGGGAGCCAAUCCC-CAAAACCAUCCUCAGUUCAGAUCGCAGGCUGCAACCCGCCUGCGUGAAGCCGGAAUCGCUAGUAAUCGCGGAUCAGCCAGCCGCGGUGAAUACGUUCCCGGGGUUUGCACACACCGCCCGUCAAGCCACCCGAGUCGGGGGCACCUGAAGACGCCUUCCUAACCGAAAGGAGGGAGGUGGUGAAGGUGAAUCUGGCGAGGGGGGCUAAmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ar.Sul.sol -----AUUCCGGUUGAUCCUGCCGGACCC-GACCGCUAUCGGGGUAGGUAAGCCAUGGGAGUCUUACACUCCCG--------GUAA---------GGGAGUGUGGCGGACGGCUGAGUAACACGUGGCAACCUACCCUCGGGACGGGGAUAACCCCGGGAAACUGGGGAUAAUCCCCGAUA-GGGAGGAAUCCUAAAGGCUAUAGGCUUUCUUGUAGCCGCCCGAGGAUGGGGCUACGGCCCAUCAGGCUGUCGGUGGGGUAAAGGCCCACCGAACCUAUAACGGGUAGGGGCCGUGGAAGCGGGAGCCUCCAGUUGGGCACUGAGACAAGGGCCCAGGCCCUACGGGGCGCACCAGGCGCGAAACGUCCCCAAUGCGCGAAAGCGUGAGGGCGCUACCCCGAGUGCCC----------GCAA-------G-AGGCUUUUCCCCGCUCU--------------AAAA-------------------GGCGGGGGAAUAAGCGGGGGCAAGUCUGGUGUCAGCCGCCGCGGUAAUACCAGCUCCGCGAGUGGUCGGGGUGAUUACUGGGCCUAAAGCGCCUGUAGCCGGCCCACCAAGUCGCCCCUUAAAGUCCCCGGCUCAACCGGGGAACUGGGGGCGAUACUGGUGGGCUAGGGGGCGGGAGAGGCGGGGGGUACUCCCGGAGUAGGGGCGAAAUCCUUAGAUACCGGGAGGACCACCAGUGGCGGAAGCGCCCCGCUAGAACGCGCCCGACGGUGAGAGGCGAAAGCCGGGGCAGCAAACGGGAUUAGAUACCCCGGUAGUCCCGGCUGUAAACGAUGCGGGCUAGGUGUCGAGUAGUUAGCCUACUCGGUGCCGCAGGGAAGCCGUUAAGCCCGCCGCCUGGGGAGUACGGUCGCAAGACUGAAACUUAAAGGAAUUGGCGGGGGAGCACACAAGGGGUGGAACCUGCGGCUCAAUUGGAGUCAACGCCUGGAAUCUUACCGGGGG-AGACCC-UA---------------CAAC-------------C--UC--GCGGAGAGGAGGUGCAUGGCCGUCGCCAGCUCGUGUUGUGAAAUGUCCGGUUAAGUCCGGCAACGAGCGAGACCCCCACCCCUAGUUGGUAUUCUUCCG-AGAACCACACUAGGGGGACUGCCGGCGUAA-GCCGGAGGAAGGAGGGGGCCACGGCAGGUCAGCAUGCCCCGAAACUCCCGGGCCGCACGCGGGUUACAAUGGCAGGGACAACGGGAUGCUACCUCGAAAGGGGGAGCCAAUCCU-UAAACCCUGCCGCAGUUGGGAUCGAGGGCUGAAACCCGCCCUCGUGAACGAGGAAUCCCUAGUAACCGCGGGUCAACAACCCGCGGUGAAUACGUCCCUGCUCCUUGCACACACCGCCCGUCGCUCCACCCGAGCGCGAAAGGGGUGA-GGUCCCUGC------GAUA-----AGGGGAUCGAACUCCUUUCCCGCGAGGGGGGAGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCGGCUGGAUCACCUCAm--
ar.The.pen GCCAGACUCCGGUUGAUCCUGCCGGACCC-GACCGCUAUCGGGGUGGGUAACCCAUGGAAGUCUAGGAGCCGGGC-------UACG--------GCCGGCUCCGGCGGACGGCUCAGUAGCACGUGGCAACCUACCCUCGGGAGGGGGAUAACCCCGGGAAACUGGGGAUAAACCCCCAUA-GGCGGGAACGCGAAAGGCCACGGUACAUGCCGUGGCCGCCCGAGGAUGGGGCUGCGCCCUAUCAGGUAGUUGGCGGGGUAACGGCCCGCCAAGCCGAUAACGGGUGGGGGCCGUGAGAGCGGGAGCCCCGAGAUGGGCACUGAGACAAGGGCCCAGGCCCUACGGGGUGCACCAGGGGCGAAACUUCCGCAAUGCGGGAAACCGUGACGGAGUCACCCCGAGUGCCC----------GAAG-------GGUGGCUUUUGCCCGGUCU--------------AAAA-------------------GCCGGGCGAAUAAGCGGGGGCAAGCUUGGUGUCAGCCGCCGCGGUAAUACCAACCCCGCGAGUGGUCGGGACGUUUAUUGGGCCUAAAGCGUCCGUAGCCGGCCCGGUAAGUCCCUCCUUAAAGCCCACGGCUCAACCGUGGGAGCGGAGG-GAUACUGCCGGGCUAGGGGGCGGGAGAGGCCGGGGGUACUCCUGGGGUAGGGGCGAAAUCCUAUAAUCCCAGGAGGACCACCAGUGGCGAAGGCGCCCGGCUAGCACGCGCCCGACGGUGAGGGACGAAAGCUGGGGGAGCAAAGGGGAUUAGAUACCCCCGUAGUCCCAGCUGUAAACGAUGCGGGCUAGGUGUUGGACGGUUCGCCCGUCCAGUGCCGUAGGGAAGCCGUUAAGCCCGCCGCCUGGGGAGUACGGCCGCAAGGCUGAAACUUAAAGGAAUUGGCGGGGGAGCACACAAGGGGUGAAGCUUGCGGUUUAAUUGGAGUCAACGCCGGAAACCUUACCGGGGG-CGACAC-GA---------------CGAC-------------C--AA--GCUGAGAGGAGGUGCAUGGCCGUCGCCGGCUCGUGCCGUGAGGUGUCCUGUUAAGUCAGGGAACGAGCGAGACCCCCGCCCCUAGUUGCUACCCAUUCG-UGGGGCACUCUAGGGGGACUGCCGGCGAUAAGCCGGAGGAAGGUGGGGGCUACGGCAGGUCAGUAUGCCCCGAAACCCCCGGGCUACACGCGAGCUGCAAUGGCGGGGACAGCGGGUUCCGACCCCGAAAGGGGGAGGUAAUCCCUUAAACCCCGCCUCAGUAGGAAUCGAGGGCUGCAACUCGCCCUCGUGAACGUGGAAUCCCUAGUAACCGCGUGUCACCAACGCGCGGUGAAUACGUCCCUGCUCCUUGCACACACCGCCCGUCGCUCCACCCGAGGGAGGCCUAGGUGA-GGCCUCCGCC-----GACG----AGGGAGGUCGAACCUGGGCCUCCCAAGGGGGGAGAAGUCGUAACAAGGUGGCCGUAGGGGAACCUGCGGCCGGAUCACCUCmm--
ar.Hal.val -----AUUCCGGUUGAUCCUGCCGGAGGC-CAUUGCUAUCGGAGUCCAUUAGCCAUGCUAGUUGCACGAGU-----------UUAG-----------ACUCGUAGCAUAUAGCUCAGUAACACGUGGCAAACUACCCUACAGACCGCAAUAACCUCGGGAAACUGAGGCCAAUAGCGGAUA-UAACGGAGGUUGAAAGU--------UCCG------GCGCUGUAGGAUGUGGCUGCGGCCGAUUAGGUAGAUGGUGGGGUAACGGCCCACCAUGCCGAUAAUCGGUACAGGUUGUGAGAGCAAGAGCCUGGAGACGGUAUCUGAGACAAGAUACCGGGCCCUACGGGGCGCAGCAGGCGCGAAACCUUUACACUGCACGACAGUGCGAUAGGGGGACUCCGAGUGUGG----------AUAU------ACCUCGCUUUUCUGUACCGU--------------AAGG-------------------GGUACAGGAACAAGGACUGGCAAGACCGGUGCCAGCCGCCGCGGUAAUACCGGCAGUCCGAGUGAUGGCCGAUAUUAUUGGGCCUAAAGCGUCCGUAGCUUGCUGUGUAAGUCCAUUGGGAAAUCCACCAGCUCAACUGGUCGGCGUCCGGGGAAACUACACAGCUUGGGGCCGAGAGACUCAACGGGUACGUCCGGGGUAGGAGUGAAAUCCUGUAAUCCUGGACGGACCACCAAUGGGGAAACCACGUUGAGAGACCGGACCCGACAGUGAGGGACGAAAGCCAGGGUCUCGAACCGGAUUAGAUACCCGGGUAGUCCUGGCUGUAAACAAUGCUCGCUAGGUAU-GUCAGCCAUGCACGUAAUGUGCCGUAGUGAAGACGAUAAGCGAGCCGCCUGGGAAGUACGUCCGCAAGGAUGAAACUUAAAGGAAUUGGCGGGGGAGCACACAACCCGAGGAGCCUGCGGUUUAAUUGGACUCAACGCCGGACAUCUCACCGGUCC-CGACAU-UAA--------------UGAC-------------U--CC--ACUGAGAGGAGGUGCAUGGCCGCCGUCAGCUCGUACCGUGAGGCGUCCUGUUAAGUCAGGCAACGAGCGAGACCCACACUUCUAGUUGCCAGCAACCUG-UUGGGUACACUAGGAGGACUGCCAUUGCUAAAAUGGAGGAAGGAAUGGGCAACGGUAGGUCAGUAUGCCCCGAAUGGACCGGGCAACACGCGGGCUACAAUGGCUAUGACAGUGGGAUGCAACGCCGAAAGGCGACGCUAAUCUC-CAAACGUAGUCGUAGUUCGGAUUUCGGGCUGAAACCCGCCCGCAUGAAGCUGGAUUCGGUAGUAAUCGCGUGUCAGAAGCGCGCGGUGAAUACGUCCCUGCUCCUUGCACACACCGCCCGUUAAAGCACCCGAGUGGGGUCCGGAUGA-GGCCGUC--------AUGC-------ACGGUUGAAUCUGG-CUCCGCAAGGGGGCUUAAGUCGUAACAAGGUAGCCGUAGAGGAAUCUGCGGCUGGAUCACCUCCU--
ar.Hal.sac -----AUUCCGGUUGAUCCUGCCGGAGGC-CAUUGCUAUUGGGAUUCAUUAGCCAUGCUAGUCGCACGAGU-----------UCAG-----------ACUCGUGGCGAAUAGCUCAGUAACACGUGGCAAACUACCCUUCGGAGCUCCAUACCCUCGGGAAACUGAGGCUAAUAGAGCAUA-CCACGGAAGUGCAAAGC--------UCCG------GCGCCGAAGGAUGUGGCUGCGGCCGAUUAGGUAGACGGUGGGGUAACGGCCCACCGUGCCAAUAAUCGGUACGGGUCAUGAGAGUGAGAACCCGGAGACGGAAUCUGAGACAAGAUUCCGGGCCCUACGGGGCGCAGCAGGCGCGAAACCUUUACACUGCACGACAGUGCGAUAAGGGAAUCCCAAGUGCGG----------AUAG------ACUGCGCUUUUGUACACCGU--------------AGGG-------------------GGUGUACGAAUAAGGGCUGGCAAGACCGGUGCCAGCCGCCGCGGUAAUACCGGCAGCCCGAGUGAUGGCCGAUCUUAUUGGGCCUAAAGCGUCCGUAGCUGGCCGCACAAGUCCAUCGGAAAAUCCACCCGCUCAACGGGUGGGCGUCCGGGGAAACUGUGUGGCUUGGGACCGGAAGGCGCGACGGGUACGUCCGGGGUAGGAGUGAAAUCCCGUAAUCCUGGACGGACCGCCGAUGGCGAAAGCACGUCGCGAGGACGGAUCCGACAGUGAGGGACGAAAGCCAGGGUCUCGAACCGGAUUAGAUACCCGGGUAGUCCUGGCCGUAAACAAUGUCUGUUAGGUGU-GGCUCCUACGUGGGUGCUGUGCCGUAGGGAAGCCGCUAAACAGACCGCCUGGGAAGUACGUCCGCAAGGAUGAAACUUAAAGGAAUUGGCGGGGGAGCAUACAACCGGAGGAGCCUGCGGUUUAAUUGGACUCAACGCCGGACAUCUCACCAGCAU-CGACUU-UAA--------------UGAU-------------C--CU--UCAGAGAGGAGGUGCAUGGCCGCCGUCAGCUCGUACCGUGAGGCGUCCUGUUAAGUCAGGCAACGAGCGAGACCCGCAUCCUUACUUGCCAGCAGGCGA-CUGGGGACAGUAGGGAGACCGCCGUGGCCAACACGGAGGAAGGAACGGGCAACGGUAGGUCAGUAUGCCCCGAAUGUGCUGGGCAACACGCGGGCUACAAUGGUCGAGACAAAGGGUUCCAACUCCGAAAGGAGACGGUAAUCUCAGAAACUCGAUCGUAGUUCGGAUUGUGGGCUGCAACUCGCCCACAUGAAGCUGGAUUCGGUAGUAAUCGCGUGUCACAAGCGCGCGGUGAAUACGUCCCUGCUCCUUGCACACACCGCCCGUCAAAGCACCCGAGUGAGGUCCGGAUGA-GGCGCGU---------UCC-------CGCGUCGAAUCUGG-CUUCGCAAGGGGGCUUAAGUCGUAACAAGGUAGCCGUAGGGGAAUCUGCGGCUGGAUCACCUCCU--
ar.Nat.mag -----AUUCCGGUUGAUCCUGCCGGAGGU-CAUUGCUAUUGGAGUCCAUUAGCCAUGCUAGUUGUACGAGU-----------UUAG-----------ACUCGUAGCAGAUAGCUCAGUAACACGUGGCAAACUACCCUAUGGAUCCAGACAACCUCGG-AAACUGAGGCUAAUCUGGAAUA-CGACGGAGGUCGAAAGC--------UCCG------GCGCCAUAGGAUGUGGC--CGGCCGAUUAGGUAGACGGUGGGGUAACGGCCCACCGUGCCGAUAAUCGGUACGGGUUGUGAGAGCAAGAGCCCGGAGACGGUAUCUGAGACAAGAUACCGGGCCCUACGGGGCGCAGCAGGCGCGAAACCUUUACACUGCACGCCAGUGCGAUAAGGGGACUCCAAGUGCGG----------AUAU------ACCUCGCUUUUUGCGACCGU--------------AAGG-------------------GGUCGCGGAAUAAGUGCUGGCAAGACCGGU-CCAGCCGCCGCGGUAA-ACCGGCAGCACGAG--AUGACCGGUGUUAUUGGGCCUAAAGCGUCCGUAGCUGGCCGCGCAAGUCUAUCGGGAAAUCUCUUCGCUUAACGGAGAGGCGUCCGGGGAAAA-AUGUGGCUUGGGACCGGAAGACCAGAGGGGUACGUCUGGGGUAGGAGUGAAAUCCCGUAAUCCUGGACGGACCACCGGUGGCGAAAGCGCCUCUGGAAGACGGAUCCGACGGUGAGGGACGAAAGCUCGGGUCACGAACCGGAUUAGAUACCCGGGUAGUCCGAGCUGUAAACGAUGUCUGCUAGGUGU-GACAAGUACGCCUGUGUUGUGCCGUAGGGAAGCCGUGAAGCAGACCGCCUGGGAAGUACGUCCGCAAGGAUGAAACUUAAAGGAAUUGGCGGGGGAGCAUACAACCGGAGGAGCCUGCGGUUUAAUUGGACUCAACGCCGGACAUCUCACCAGCAC-CGACAU-UAA--------------GGAU-------------C-UGC--AUUGAGAGGAGGUGCAUGGCCGCCGUCAGCUCGUACCGUGAGGCGUCCUGUUAAGUCAGGCAACGAGCGAGACCCGCUCUCCUAAUUGCCAGCAACUUU-UUGGGUACAUUAGGAGGACUGCCGCUGCCAAAGCGGAGGAAGGAACGGGCAACGGUAGGUCAGUAUGCCCCGAAUGUGCUGGGCAACACGCGGGCUACAAUGGCCACGACAGUGGGAUGCAACGCCGAAAGGCGACGCUAAUCUCCUAAACGUGGUCGUACUUCGGAUUGAGGGCUGAAACUCGCCCUCAUGAAGCUGGAUUCGGUAGUAAUCGCGCCUCAGAAGGGCGCGGUGAAUACGUCCCUGCUCCUUGCACACACCGCCCGUCAAAGCACCCGAGUGGGGUCCGGAUGA-GGCCCGG--------UUUA-------CGGGUCGAAUCUGG-CUCCGCAAGGGGGCUUAAGUCGUAACAAGGUAGCCGUAGGGGAAUCUGCGGCUGGAUCACCUCCA--
ar.Met.fer CGCCAACUCCGUUUGAUCCUGGCGGAGGC-CACUGCUAUGGGGGUCCAUAAGCCAUGCAAGUCGAACGGGC-----------CUUG----------UGCCCGUGGCGAACGGCUCAGUAACACGUGGAAACCUACCCUGGGGUCCGGGAUAACCCCGGGAAACUGGGGCUAAUCCCGGAUA-GGCGGGAACGCGAAAGGUC------UUUU----GACCGCCCCAGGAUGGGUCUGCGGCCGAUUAGGUAGUUGGUAGGGUAACGGCCUACCAAGCCUACGAUCGGUACGGGUUGUGAGAGCAAGAGCCCGGAGACGGGGCCUGAGACAAGGCCCCGGGCCCUACGGGGCGCAGCAGGCGCGAAAACUCCGCAAUGCGCGAAAGCGCGACGGGGGGACCCCCAGUGCCU----------GUAA-------AGUGGCUUUUCCGGAGUGU--------------AAAA-------------------GCUCCGGGAAUAAGGGCUGGCAAGACCGGUGCCAGCCGCCGCGGUAACACCGGCAGCCCGAGUGGUGGCCGCGUUUAUUGGGCCUAAAGCGUCCGUAGCCGGUCCGGUAAGUCUCCGGUGAAAGCCCGCAGCUCAACUGCGGGAGUAGCCGAGAUACUGCCGGACUUGGGGCCGGGAGAGGCCGGAGGUACCCCCGGGGUAGGGGUGAAAUCCUGUAAUCCCGGGGGGACCACCUGUGGCGAAGGCGUCCGGCUGGAACGGGCCCGACGGUGAGGGACGAAAGCCAGGGGAGCGAACCGGAUUAGAUACCCGGGUAGUCCUGGCCGUAAACGAUGCGGACUUGGUGUUGGGGCACUCGUUGCCCCAGUGCCGAAGGGAAGCCGUUAAGUCCGCCGCCUGGGGAGUACGGCCGCAAGGCUGAAACUUAAAGGAAUUGGCGGGGGAGCACACAACGCGUGGAGCCUGCGGUUUAAUUGGAUUCAACGCCGGACACCUCACCGGGGG-CGACGC-GA---------------UGAU-------------C--UA--GCCGAGAGGAGGUGCAUGGCCGCCGUCAGCUCGUACCGUGAGGCGUCCUGUUAAGUCAGGCAACGAGCGAGACCCGCGCCCCUAGUUGCCAGCGGGUAA-CCGGGCACACUAGGGGGACCGCCAGCGAUAAGCUGGAGGAAGGUGCGGGCGACGGUAGGUCCGUAUGCCCCGAAACCCCCGGGCUACACGCGGGCUACAAUGGCCGGGACAAUGGGUACCGACCCCGAAAGGGGGAGGUAAUCCCAUAAACCCGGCCGUAGUUCGGAUCGAGGGCUGCAACUCGCCCUCGUGAAGCUGGAAUGCGUAGUAAUCGCGGGUCACUAUCCCGCGGUGAAUACGUCCCUGCUCCUUGCACACACCGCCCGUCACGCCACCCAAACGGGGUUCGGAUGA-GGCCAUGCC------UCU-------GAUGGUCGAAUCCGGGCCCCGUGAGGAGGGCGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCGGCUGGAUCACmmmmm--
ar.Met.jan -----AUUCCGGUUGAUCCUGCCGGAGGC-CACUGCUAUCGGGGUCCAUAAGCCAUGCGAGUCA-AGGGGCUCC--------UUCG--------GGGAGCACCGGCGCACGGCUCAGUAACACGUGGCAACCUACCCUCGGGUGGGGGAUAACCUCGGGAAACUGAGGCUAAUCCCCCAUA-GGGGGGAACCCGAAAGGC-------GUAA-----GCUGCCCGAGGAUGGGGCUGCGGCGGAUUAGGUAGUUGGUGGGGUAACGGCCCACCAAGCCUACGAUCCGUACGGGCCCUGAGAGGGGGAGCCCGGAGAUGGACACUGAGACACGGGUCCAGGCC-UACGGGGCGCAGCAGGCGCGAAACCUCCGCAAUGCGCGAAAGCGCGACGGGGGGACCCCGAGUGCCC----------CCU--------GUGGGCUUUUCCGGAGUGU--------------AAAC-------------------GCUCCGGGAAUAAGGGCUGGCAAGUCCGGUGCCAGCAGCCGCGGUAAUACCGGCGGCCCAAGUGGUGGCCACUGUUAUUGGGCCUAAAGCGUCCGUAGCCGGCCCGGUAAGUCUCUGCUUAAAU-CUGCGGCUCAACCGCAGGGCUGGCA-AGAUACUGCCGGGCUUGGGACCGGGAGAGGCCGGGGGUACCCCAGGGGUAGCGGUGAAAUGCGUUGAUCCCUGGGGGACCACCUGUGGCGAAGGCGCCCGGCUGGAACGGGUCCGACGGUGAGGGACGAAGGCCAGGGGAGCAAACCGGAUUAGAUACCCGGGUAGUCCUGGCUGUAAACUCUGCGGACUAGGUGUCGCGUCGUUCGCCGACGCGGUGCCGAAGGGAAGCCGUUAAGUCCGCCGCCUGGGGAGUACGGUCGCAAGACUGAAACUUAAAGGAAUUGGCGGGGGAGCAUACAACGGGUGGAGCCUGCGGUUUAAUUGGAUUCAACGCCGGGCAUCUUACCAGGGG-CGACGC-GA---------------UGAC-------------C--AC--GCCGAGAGGUGGUGCAUGGCCGUCGUCAGCUCGUACCGUGAGGCGUCCUGUUAAGUCAGGUAACGAGCGAGACCCGUGCCCCAUGUUGCUACCUCUCCG-GAGGGCACUCAUGGGGGACCGCCGGCGCUAAGCCGGAGGAAGGUGCGGGCAACGACAGGUCCGCAUGCCCCGAAUCCCCUGGGCUACACGCGGGCUACAAUGGCCGGGACAAUGGGACGCGACCCCGAAAGGGGGAGCGAAUCCCCUAAACCCGGUCGUAGUCCGGAUCGAGGGCUGUAACUCGCCCUCGUGAAGCCGGAAUCCGUAGUAAUCGCGCCUCACCAUGGCGCGGUGAAUGCGUCCCUGCUCCUUGCACACACCGCCCGUCACGCCACCCGAGUUGAGCCCAAGUGA-GGCCCUGCC------GCAA------GAGGGUCGAACUUGGGUUCAGCGAGGGGGGCGAAGUCGUAACAAGGUAGCCGUAGGGGAA-CUGCGGCUGGAUCACCUCCm--
ar.Met.ore -----NUUCUGGUUGAUCCUGCCAGAGGU-CACUGCUAUCAGUGUUCAUAAGCCAUGCGAGUCAAAUGUUC-----------UUCG----------UGAACAUGGCGUACUGCUCAGUAACNNGUGGAAAUCUGCCCUAAGGUCUGGCAUAACRCCGGGAAACUGAUGAUAAUUCCAGAUG-GACCGGAAGGUAAAAGC--------UCCG------GCGCCUUAGGAUGAAUCUGCGGCCUAUCAGGUUGUAGUGGGUGUAACGUACCUACUAGCCGACGACGGGUACGGGNUGUGAGAGCAAGAGCCCGGAGAUGGAUUCUGAGACAUGAAUCCAGGCCCUACGGGGCGCAGCAGGCGCGAAAACUUUACAAUGCGGGAAACCGCGAUAAGGGGACACUGAGUGCCC----------CUU--------GUUGGC-UGUCCCAUGUAU--------------AAAU-------------------GCAUGUGUUACAAGGGCCGGCAAGACCGGUGCCAGCCGCCGCGGUAACACCGGCGGCCCGAGUGGUGGCCACUAUUAUUGGGUCUAAAGGGUCCGUAGCCGGUUUGAUCAGUCUUCCGGGAAAUCUGACAGCUCAACUGUUAGGCUUCCGGGGAUACUGUCAGGCUUGGGACCGGGAGAGGUAAGAGGUACUACAGGGGUAGGAGUGAAAUCUUGUAAUCCCUGUGGGACCACCAGUGGCGAAGGCGUCUUACCAGAACGGGUCCGACGGUGAGGGACGAAAGCUGGGGGCACGAACCGGAUUAGAUACCCGGGUAGUCCCAGCCGUAAACGAUGCUCGCUAGGUGUCUGGGAUUGCGCGUUUCAGGUGCCGCAGGGAAGCCGUGAAGCGAGCCACCUGGGAAGUACGGCCGCAAGGCUGAAACUUAAAGGAAUUGGCGGGGGAGCAUACAACGGGUGGAGCCUGCGGUUUAAUUGGNNNNAACGCCGGAAAACUCACCUGGGG-CGACAC-UA---------------CGAA-------------C--UC--GCUGAGAGGANGUGCAUGGCCGUCGUCAGUUCGUACUGUGAAGCAUCCUGUUAAGUCAGGCAACGAGCGAGACCCGUGCCCACUGUUGCCAGCAUUUCG-AUGGGUACUCUGUGGGNACCGCCGCUGCUAAAGCGGAGGAAGGUGCGGGCUACGGUAGGUCAGUAUGCCCCGAAUCUCCAGGGCUACACGCGGGCUACAAUGGACGGGACAAUGGGCUCCUACCCCGAAAGGGGNUGGCAAUCUCACAAACCCGGCCGUAGUUCGGAUCGAGGGCUGUAACUCGCCCUCGUGAAGCUGGAAUCCGUAGUAAUCGCGUUUCAAUAUAGCGCGGUGAAUACGUCCCUGCUCCUUGCACACACCGCCCGNCAAACCACCCGAGUGAGGUAUGGGUGA-GGGCACAAC------AAA------GUGUGUUCGAACCUAAAUUUCGCAAGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm--
ar.The.chi -----mmmmmmmmmmmmmmmmmmGGAGGC-CACUGCUAUGGGGGUCCAUAAGCCAUGCGAGUCAAGGGGGCGUCC-------UUCU------GGGAC-CCACCGGCGGACGGCUCAGUAACACGUCGGAACCUACCCUCGGGAGGGGGAUAACCCCGGGAAACUGGGGCUAAUCCCCCAUA-GGCCGGAAGGCGAAAGGGACC----GUAA--GGUCCCGCCCGAGGAUGGGCCGGCGGCCGAUUAGGUAGUUGGUGGGGUAACGGCCCACCAAGCCGAAGAUCGGUACGGGCCGUGAGAGCGGGAGCCCGGAGAUGGACACUGAGACACGGGUCCAGGNCCUACGGGGCGCAGCAGGCGCGAAACCUCCGCAAUGCGGGAAACCGCGACGGGGGGACCCCCAGUGCCUC---------UCU--------CACGGCUUUUCCGGAGUGU--------------AAAA-------------------GCUCCGGGAAUAAGGGCUGGCNAGGCCGGUGNNAGCCGCCGCGGUAAUACCGGCGGCCCGAGUGGUGGCCACUAUUAUUGGGCCUAAAGCGGCCGUAGCCGGGCCCGUAAGUCCCUGGCGAAAUCCCACGGCUCAACCGUGGGGCUCGCUGGGAUACUGCGGGCCUUGGGACCGGGAGAGGCCGGGGGUACCCCCGGGGUAGGGGUGAAAUCCUAUAAUCCCGGGGGGACCGCCAGUGGCGAAGGCGCCCGGCUGGAACGGGUCCGACGGUGAGGGCCGAAGGCCAGGGGAGCGAACCGGAUUAGAUACCCGGGUAGUCCUGGCUGUAAAGGAUGCGGGCUAGGUGUCGGGCNAUUCG-NCGCCCGGUGCCGUAGGGAAGCCGUUAAGCCCGCCGCCUGGGGAGUACGGCCGCAAGGCUGAAACUUAAAGGAAUUGGCGGGGGAGCAUACAAGGGGUGGAGCGUGCGGUUUAAUUGGAUUCAACGCCGGGAACCUCACCGGGGG-CGACGC-GA---------------CGAA-------------C--GC--GCCGAGAGGAGGUGCAUGGNCGCCGUCAGCUCGUACCGUGAGGCGUCCACUUAAGUGUGGUAACGAGCGAGACCCGCGCCCCCAGUUGCCAGUNCGCU--GGAGGCACUCUGGGGGGACUGCCGGCGAUAAGCCGGAGGAAGGGGCGGGCGACGGUAGGUCAGUAUGCCCCGAAACCCCCGGGCUACACGCGCGCUACAAUGGGCGGGACAAUGGGACCCGACCCCGAAAGGGGAAGGGAAUCCCCUAAACCCGCCCUCAGUUCGGAUCGCGGGCUGCAACUCGCCCGCGUGAAGCUGGAAUCCCUAGUACCCGCGCGUCAUCAUCGCGCGGCGAAUACGUCCCUGCUCCUUGCACACACCGCCCGUCACUCCACCCGAGCGGGGCCCGGGUGA-GGCCCGACUC-----UUCG----GGACGGGUCGAGCCUGGGCUCCGUGAGGGGGGAGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm--
ar.The.ste -----mmmmmmmmmmmmmmmmmmmmmmmm-mmmmmmmmmmGAGGUCCAUAACCCAUGCGAGUCAUGGGGCGCG---------UCUG---------CGCGCACCGGCGGACGGCUCAGUAACACGUCGGAACCUACCCUCGGGAGGGGGAUAACCCCGGGAAACUGGGGCUAAUCCCCCAUA-GGCCGGAAGGCGAAAGGUC-------UCU----GACCGCCCGAGGAUGGGCCGGCGGCCGAUUAGGUAGUUGGUGGGGUAACGGCCCACCAAGCCGAAGAUCGGUACGGGCCAUGAGAGUGGGAGCCCGGAGAUGGACACUGAGACACGGGUCCAGGCCCUACGGGGCGCAGCAGGCGCGAAACCUCCGCAAUGCGGGCAACCGCGACGGGGGGACCCCCAGUGCCG----------AUA--------CACGGCUUUUCCGGAGUGU--------------AAAA-------------------GCUCCGGGAAUAAGGGCUGGCAAGGCCGGUGGCAGCCGCCGCGGUAAUACCGGCGGCCCGAGUGGUGGCCGCUAUUAUUGGGCCUAAAGCGUCCGUAGCCGGGCCCGUAAGUCCCUGGCGAAAUCCCACGGCUCAACCGUGGGGCUUGCUGGGAUACUGCGGGCCUUGGGACCGGGAGAGGCCGGGGGUACCCCUGGGGUAGGGGUGAAAUCCUAUAAUCCCAGGGGGACCGCCAGUGGCGAAGGCGCCCGGCUGGAACGGGUCCGACGGUGAGGGACGAAGGCCAGGGGAGCGAACCGGAUUAGAUACCCGGGUAGUCCUGGCUGUAAAGGAUGCGGGCUAGGUGUCGGGCGAUUCGCUCGCCCGGUGCCGGAGGGAAGCCGUUAAGCCCGCCGCCUGGGGAGUACGGCCGCAAGGCUGAAACUUAAAGGAAUUGGCGGGGGAGCAUACAAGGGGUGGAGCGUGCGGUUUAAUUGGAUUCAACGCCGGGAACCUCACCGGGGG-CGACGC-GA---------------CGAA-------------C--GC--GCCGAGAGGAGGUGCAUGGCCGCCGUCAGCUCGUACCGUGAGGCGUCCACUUAAGUGUGGUAACGAGCGAGACCCGCGCCCCCAGUUGCCAGUCUGCU--GGAGGCACUCUGGGGGGACCGCCGGCGAUAAGCCGGAGGAAGGAGCGGGCGACGGUAGGUCAGUAUGCCCCGAAACCCCCGGGCUACACGCGCGCUACAAUGGGCGGGACAAUGGGAUCCGACCCCGAAAGGGGAAGGGAAUCCCCUAAACCCGCCCUCAGUUCGGAUUGCGGGCUGCAACUCGCCCGCAUGAAGCUGGAAUCCCUAGUACCCGCGUGUCAUCAUCGCGCGGCGAAUACGUCCCUGCUCCUUGCACACACCGCCCGUCACUCCACCCGAGCGGGGUCCGGAUGA-GGCCUGGCUCC----UUCG---GGGACGGGUCGAGUCUGGGCUCCGUGAGGGGGGAGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUACGGCUCGAUCACCUCCUAU
hi.Act.eur -----mmmmmmmmmmmmCCUGGCUCAGGACGAACGCUGGCGGCGUGCUUAACACAUGCAAGUCGAACGGGAUCCAAAGGC--UUUU-UGUUUUUGGUGAGAGUGGCGAACGGGUGAGUAACACGUGAGAACCUGCCCCCUUCUUUUGGAUAACCGCAUGAAAGUGUGGCUAAUACAGGAUAUUCCAGCAUUGGGAAAGGU-------UUGG-----UCUGGUGGGGGAUGGGCUCGCGGCCUAUCAGCUUGUUGGUGGGGUGAUGGCCUACCAAGGCGGUGACGGGUAGCCGGCCUGAGAGGGUGGGCGGUCACACUGGGACUGAGAUACGNCCCAGANUCCUACGGGAGGCAGCAGUGGGGGAUUUUGCACAAUGGGCGCAAGCCUGAUGCAGCGACGCCGCGUGAGGGAUGAAGGCCUUCGGGUUGUAAACCUCUUUCGCUGGGUUGAAAGGCCAUGCU---UUG----GGUGUGGUUGAUUUGAACUGGUAAAGAAGUACCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUACUAGCGUUGUCCGGAUUUAUUGGGCGUAAAGGGCUUGUAGGUGGUUUGUCGCGUCUGUCGUGAAAUCCUGUGGCUUAACCAUGGGCUUGCGGUGGGUACGGGCAGGCUUGAGUGCGGUAGGGGAGACUGGAAUUCCUGGUGUAGCGGUGGAAUGCGCAGAUAUCAGGAGGAACACCGGUGGCGAAGGCGGGUCUCUGGGCCGUUACUGACACUGAGGAGCGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCAUGCUGUAAACGUUGGGCACUAGGUGUGGGGGCCGUGU-GGUUUCUGCGCCGUAGCUAACGCAUUAAGUGUCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGCGGAGCAUGCGGAUUAAUUCGAUGCAACGCGAAGAACCUUACCAAGGCUUGACAUGACCGGUACAGUGUAGAGAUAUGCUGGCC--UUUU-UGGCUGGUGUGCAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCUCGUGUUGCCAGCAUUUGG-UUGGGGACUCUCGAGAGACUGCCGGGGUUAACUCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGUCUUGGGCUUCACGCAUGCUACAAUGGAUGGUACAGAGGGUUGCGAUACUGUGAGGUGGAGCUAAUCCCUUAAAGCUGUUCUCAGUUCGGAUCGUAGUCUGCAACUCGACUACGUGAAGGUGGAGUCGCUAGUAAUCGCAGAUCAGCACGCUGCGGUGAAUACGUUCUCGGGUCUUGUACACACCGCCCGUCACGUCACGAAAGUUGGUAACACCCGAAmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
hi.Bif.inf UUUGUGGAGGGUUCGAUUCUGGCUCAGGAUGAACGCUGGCGGCGUGCUUNACNCNUGCNAGUCGAACGGGAUCCAUCGGGC-UUUG--CUUGGUGGUGAGAGUGGCGAACGGGNGAGUNAUGCGUGACGACCUGCCCCAUACACCGGAAUAGCUCCUGGAAACGGGUGGUAAUGCCGGAUGUUCCAGCAUUGGGAAAGU--------UUC-------GCGGUAUGGGAUGGGGUCGCGUCCUAUCAGCUUGACGGCGGGGUAACGGCCCACCGUGGCUUCGACGGGUAGCCGGCCUGAGAGGGCGACCGGCCACNUUGGGACUGAGAUNCGGCCNNGNCUCCUACGGGAGGCNGCNGUGGGNNAUAUUGCACNAUGGGCGCAAGCCUNAUGCAGCGACGCNGCGUGAGGGAUGGAGGCCUUCGGGUUGUNAACCUCUUUUNUCGGGGAGCAAGC---------GUGA-----------GUGAGUUUACCCNUUGAAUNAGCACCGGCUAACUACGUGCCAGCNGCCGCGGUAAUACGUAGGGUGCNAGCGUUAUCCGGAAUUAUUGGGCGUNAAGGGCUCGUAGGCGGUUCGUCGCGUCCGGUGUGAAAGUCCAUCGCUUAACGGUGNAUCCGCGCCGNGUACGGGCGNGCUUGAGUGCGGUAGGGGAGACUGGAAUUCCCGGUGUAACGGUGGAAUGUGUAGAUAUCGGGAAGAACACCAAUGGCGAAGGCAGGUCUCUGGGCUGUUACUGACGCUGAGGAGCNAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUNAACGGUGGAUGCUGGAUGUGGGGCCNUUCCCGGGUUCCGUGUCGGAGCUAACGCGUUAAGCAUCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGAAAUUGACGGGGGCCNGCACAAGCGGCGGAGCAUGCGGAUUNAUUCGANNNAACGCGAAGAACCUUACCUGGGCUUGACNUGUCCCGACGAUCCCAGAGAUGGNNNN-UCC-UUCG-GGNCGGGNUCACNGGUGGCGCAUGGUCGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGCCCCGUGUUGCCAGCGGUGUG-CCGGNNACUCACGGGNNACCGCCGGGGUUNACUCGGAGGAAGGUGGGGAUGACGUCAGAUCAUCAUGCCCCUUACGUCCAGGGCUUCACGCAUGCUACAAUGGCCGGUACAACGGGAUGCGACGCGGCGACGCGGAGCGGAUCCCUGAAAACCGGNCUCAGUUCGGAUCGCAGUCUGCAACUCGACUGCGUGAAGGCGGAGUCGCUAGUAAUCGCGAAUCAGCACGUCGCGGUGAAUGCGUUCCCNGGCNUUGUACACACNGCCCGUCAAGUCAUGAAAGUGGGCAGCACCCGAAGCCGGUGGCCUAACCCUUGGGANGGAGCCGUCUNAGGUGAGGCUCGUGANNGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
hi.Cel.cel -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmGGCGUGCUUAACACAUGCAAGUCGAACGGUGACGACGGGG--CUUG--CCCUGUCUGAUCAGUGGCGAACGGGUGAGUAACACGUGAGAACCUGCCCUUGACUCUGGGAUAACCGCGGGAAACGGCGGCUAAUACCGGAUAUGAGAGCAUUCUGAAAGA--------UUUA------UCGGUCAAGGAUGGGCUCGCGGCCUAUCAGCUUGUUGGUGGGGUGAUGGCCUACCAAGGCGACGACGGGUAGCCGGCCUGAGAGGGCGACCGGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGCAAGCCUGAUGCAGCGACGCCGCGUGAGGGAUGAAGGCCUUCGGGUUGUAAACCUCUUUCAGCAGGGAAGAAGC---------GAAA-----------GUGACGGUACCUGCAGAAGAAGCGCCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGCGCAAGCGUUGUCCGGAAUUAUUGGGCGUAAAGAGCUCGUAGGCGGUUUGUCGCGUCUGCUGUGAAAACCUGAGGCUCAACCUCGGGCUUGCAGUGGGUACGGGCAGACUAGAGUGCGGUAGGGGUGACUGGAAUUCCUGGUGUAGCGGUGGAAUGCGCAGAUAUCAGGAGGAACACCGAUGGCGAAGGCAGGUCACUGGGCCGCAACUGACGCUGAGGAGCGAAAGCAUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCAUGCCGUAAACGUUGGGCACUAGGUGUGGGGCUCUUCCCGAGUUCCGUGCCGCAGCAAACGCAUUAAGUGCCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGAAAUUGACGGGGGCCCGCACAAGCGGCGGAGCAUGCGGAUUAAUUCGAUGCAACGCGAAGAACCUUACCAAGGCUUGACAUAACCGGAAAAGUGCAGAGAUGUGCUCCCC--GCAA--GGUCGGUGUACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUCCUAUGUUGCCAGCACCAUG-GUGGGGACUCAUAGGAGACUGCCGGGGUCAACUCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGUCUUGGGCUUCACGCAUGCUACAAUGGCCGGUACAAAGGGCUGCGAUACCGCGAGGUGGAGCGAAUCCCAAAAAGCCGGUCUCAGUUCGGAUUGGGGUCUGCAACUCGACCCCAUGAAGUCGGAGUCGCUAGUAAUCGCAGAUCAGCACGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCAAGUCACGAAAGUCGGUAACACCCGAAGCCGGUGGCCCAACCCUUGGGAGGGAGCCGUCGAAGGUGGGACUGGCGAUUGGGACUAAGUCGUAACAAGGUAGCCGUmmmmmmmmmmmmmmmmmmmmmmmmm-----
hi.Cor.oti -----mmmmmmmmmmmmmmmmmmmmmmmmCGAACGCUGNCGGCGUGCUUAACACAUGCAAGUCGAACGGAAAGGCCUACUUUCUUGAUUGCGGGUGCUCGAGUGGCGAACGGGUGAGUAACACGUGAGGAUCUGCCCCCAACUUGGGNAUAAGCCUGGGAAACUGGGUCUAAUUCCCGAUAGGACUUGGUGGUGAAAACGA------UUUU---CUAGUGGUUGGGGAUGAGCUCGCGGCCUAUCAGCUUGUUGGUGGGGUAAUGGCCUACCAAGGCGGCGACGGGUAGCCGGCCUGAGAGGGUGGACGGCCACAUUGGGACUGAGAUACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGGAAGCCUGAUGCAGCGACGCCGCGUGGGGGAUGACGGCCUUCGGGUUGUAAACUCCUUUCGACCGCGAGGAAGCCGCCUGG--UUGG----AAGGGUGGUGACGGUAGUGGUAGAAGAAGCACCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUGCGAGCGUUGUCCGGAUUUACUGGGCGUAAAGAGCUCGUAGGUGGCUUGUCGCGUCGUCUGUGAAAGUCUGGGGCUUAACUCCGGGUGUGCAGGCGAUACGGGCUGGCUUGAGUGCUGUAGGGGAGACUGGAAUUCCUGGUGUAGCGGUGGAAUGCGCAGAUAUCAGGAGGAACACCGAUGGCGAAGGCAGGUCUCUGGGCAGUCACUGACGCUGAGGAGCGAGAGCAUGGGUAGCGAACAGGAUUAGAUACCCUGGUAGUCCAUGCUGUAAACGGUGGGCGCUAGGUGUGGGGACUUUCCUGGUUUCCGUGUCCUAGCUAACGCGUUAAGCGCCCCGCCUGGGGAGUACGNCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGCGGAGCAUGUGGAUUAAUUCGAUGCAACGCGAAGAACCUUACCUGGGUUUGACAUGACUAGAUUAGGCGAGAGAUCGUCUGUCCC-UUUG-UGGCUGGUGUGCAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGUAACCCUUGUCUUAUGUUGCCAGCACUGUG-GUGGGGACUCGUGAGAGACUGCCGGGGUGAACUCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGUCCAGGGCUUCACACAUGCUACAAUGGCCGGUACAGUAGGUUGCGAGACCGUGAGGUGGAGCUAAUCCUGUAAAGCUGGUCGUAGUUCGGAUUGGGGUCUGCAACUCGACCCCAUGAAGUCGGAGUCGCUAGUAAUCGCAGAUCACCAUGCUGCGGUGAAUACGUUCUCGGGCCUUGUACACACCGCCCGUCACGUCAUGAAAGUUGGUAACACCCGAAGCCGNUUGCUCC-ACUUAGNUGGGGUGGUNUCGAAGGUGGGAUCGGCGAUmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
hi.Mic.par -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmGCAAGUCGAGCGGAAAGGCCC-----UUCG----GGGGUACUCGAGCGGCGAACGGGUGAGUAACACGUGAGAACCUGCCCCUGACUCUGGGAUAAGCCUGGGAAACCGGGUCUAAUACCGGAUAUGACAGCAUUGUGAAAGU--------UUUU------UCGGUUGGGGAUGGGCUCGCGGCCUAUCAGCUUGUUGGUGGGGUGAUGGCCUACCAAGGCGACGACGGGUAGCCGGCCUGAGAGGGCGACCGGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCGCAAUGGGCGGAAGCCUGAGCCAGCGACGCCGCGUGGGGGAUGACGGCCUUCGGGUUGUAAACCUCUUUCAGCAGGGACGAAGUU--------GACG----------------UGUACCUGUAGAAGAAGCGCCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGCGCGAGCGUUGUCCGGAAUUAUUGGGCGUAAAGAGCUCGUAGGUGGCUUGUUGCGUCUGCCGUGAAAGCCCGUGGCUUAACUACGGGUCUGCGGUGGAUACGGGCAGGCUAGAGGCUGGUAGGGGCAAGCGGAAUUCCUGGUGUAGCGGUGAAAUGCGCAGAUAUCAGGAGGAACACCGGUGGCGAAGGCGGCUUGCUGGGCCAGUUCUGACGCUGAGGAGCGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCUGUAAACGUUGGGCGCUAGGUGUGGGGGUCUUCCCGAUUCCUGUGCCGUAGCUAACGCAUUAAGCGCCCCGCCUGGGGAGUACGGC-GCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGCGGAGCAUGUUGCUUAAUUCGAGCCAACGCGAAGAACCUUACCAAGGUUUGACAUAACCGGAAACACUCAGAGACGGGUGCCUCC-UUU--GGACUGGUGUACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUUCCAUGUUGCCAGCACUUUGGGUGGGGACUCAUGGGAGACUGCCGGGGUCAACUCGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGCCCCUUAUGUCUUGGGCUGCAAACAUGCUACAAUGGUCGGUACAGAGGGUUGCGAUACCGUGAGGUGGAGCGAAUCCCUAAAAGCCGGUCUCAGUUCGGAUUGGGGUCUGCAACUCGACCCCAUGAAGUCGGAGUCGCUAGUAAUCGCAGAUCAGCACGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACGUCACGAAAGUCGGCAACACCCGAAGCCCGUGGCCCAACCCUUGGGGGGGAGCGGUCGAAGGUGGGGCUGGCGAUUGGGACGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
hi.Mic.ech -----mmmmmmmmUGAUCCUGGCGCAGGACGAACGCUGGCGGCGUGCUUAACACAUGCAAGUCGAGCGGAAAGGCCC-----UUCG-----GGGUACUCGAGCGGCGAACGGGUGAGUAACACGUGAGAACCUGCCCUAGGCUUUGGGAUAACCCCGGGAAACCGGGCCUAAUACCGAAUAGGACCGCAUGGUGAAAG---------UUUU------UCGGCCUGGGAUGGGCUCGCGGCCUAUCAGCUUGUUGGUGGGGUGAUGGCCUACCAAGCCGACGACGGGUAGCCGGCCUGAGAGGGCGACCGGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGGAAGCCUGAUGCAGCGACGCCGCGUGAGGGAUGACGGCCUUCGGGUUGUAAACCUCUUUCAGCAGGGACGAAGC---------GUAA-----------GUGACGGUACCUGCAGAAGAAGCGCCAGCCAACUACGUGCCAGCAGCCGCGGUAAGACGUAGGGCGCGAGCGUUGUCCGGAUUUAUUGGGCGUAAAGAGCUCGUAGGCGGCUUGUCGCGUCGACUGUGAAAACCCGCAGCUCAACUGCGGGCCUGCAGUCGAUACGGGCAGGCUAGAGUUCGGUAGGGGAGACUGGAAUUCCUGGUGUAGCGGUGAAAUGCGCAGAUAUCAGGAGGAACACCGGUGGCGAAGGCGGGUCUCUGGGCCGAUACUGACGCUGAGGAGCGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCUGUAAACGUUGGGCGCUAGGUGUGGGGGGCCUCCGGUUCUCUGUGCCGCAGCUAACGCAUUAAGCGCCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGCGGAGCAUGCGGAUUAAUUCGAUGCAACGCGAAGAACCUUACCUGGGUUUGACAUGCCGCAAAACCGGCAGAGAUGUCGGGUCC--UUCG--GGGGCGGUCACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUUCGAUGUUGCCAGCGCUAUG-GCGGGGACUCAUCGAAGACUGCCGGGGUCAACUCGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGCCCCUUAUGUCCAGGGCUUCACGCAUGCUACAAUGGCCGGUACAAUGGGCUGCGAUACCGUGAGGUGGAGCGAAUCCCAAAAAGCCGGUCUCAGUUCGGAUCGGGGUCUGCAACUCGACCCCGUGAAGUCGGAGUCGCUAGUAAUCGCAGAUCAGCACGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACGUCACGAAAGUCGGCAACACCCGAAGCCGGUGGCCCAACCCUUGGGAGGGAGCCGUCGAAGGUGGUGCUGGCGAUUGGGACGAAGUCGUAACAAGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
hi.Myc.cel -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmAACACAUGCAAGUCGAACGGAAAGGCCU-----UUNG----GGGGUGCUCGAGUGGCGAACGGGUGGGUAACACGUGGGGAUCUGCCCUGCACUUCGGGAUAAGCUUGGGAAACUGGGUCUAAUACCGGAUAGGACCGCAUGGUGAAAGC--------UUUU------GCGGUGUGGGAUGGGCCCGCGGCCUAUCAGCUUGUUGGUGGGGUGAUGGCCUACCAAGGCGACGACGGGUAGCCGGCCUGAGAGGGUGUCCGGCCACACUGGGACUGAGAUACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGCAAGCCUGAUGCAGCGACGCCGCGUGGGGGAUGACGGCCUUCGGGUUGUAAACCUCUUUCACCAUCGACGAAGCUGCCGG---UUUU-----CCGGUGGUGACGGUAGGUGGAGAAGAAGCACCGGCCAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUGCGAGCGUUGUCCGGAAUUACUGGGCGUAAAGAGCUCGUAGGUGGUUUGUCGCGUUGUUCGUGAAAUUCCCUGGCUUAACUGGGGGCGUGCGGGCGAUACGGGCAGACUGGAGUACUGCAGGGGAGACUGGAAUUCCUGGUGUAGCGGUGGAAUGCGCAGAUAUCAGGAGGAACACCGGUGGCGAAGGCGGGUCUCUGGGCAGUAACUGACGCUGAGGAGCGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGGUGGGUACUAGGUGUGGGUUUCUUCCUGGGAUCCGUGCCGUAGCUAACGCAUUAAGUACCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGCGGAGCAUGUGGAUUAAUUCGAUGCAACGCGAAGAACCUUACCUGGGUUUGACAUGACAGGACGACUGCAGAGAUGUGGUUUCC--CUUG-UGGCCUGUGUGCAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCUCAUGUUGCCAGCGCGAUG-GCGGGGACUCGUGAGAGACUGCCGGGGUCAACUCGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGCCCCUUAUGUCCAGGGCUUCACACAUGCUACAAUGGCCGGUACAAAGGGCUGCGAUGCCGUGAGGUUUAGCGAAUCCUUUAAAGCCGGUCUCAGUUCGGAUCGGGGUCUGCAACUCGACCCCGUGAAGUCGGAGUCGCUAGUAAUCGCAGAUCAGCAUGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACGUCAUGAAAGUCGGUAACACCCGAAGCCAGUGGCCUAACCGCAA-GAGGGAGCUGUCGAAGGUGGGAUCGGCGAUUGGGACGAAGUCGUAACAAGGUAGCCGUACCGGAAGUGmmmmmmmmmmmmmmm-----
hi.Myc.int -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmGGCGGCGUGCUUAACACAUGCAAGUCGAACGGAAAGGCCCC----UUCG----GGGGUACUCGAGUGGCGAACGGGUGAGUAACACGUGGGAAUCUGCCCUGCACACUGGGAUAAGCCUGGGAAACUGGGUCUAAUACCGGAUAGGACCGCAUGGUGAAAGC--------UUUU------GCGGUGUGGGAUGGGCCCGCGGCCUAUCAGCUUGUUGGUGGGGUGACGGCCUACCAAGGCGACGACGGGUAGCCGGCCUGAGAGGGUGUCCGGCCACACUGGGACUGAGAUACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGCAAGCCUGAUGCAGCGACGCCGCGUGGGGGAUGACGGCCUUCGGGUUGUAAACCUCUUUCAGCAGGGACGAAGC---------GCAA-----------GUGACGGUACCUGCAGAAGAAGCACCGGCCAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUGCGAGCGUUGUCCGGAAUUACUGGGCGUAAAGAGCUCGUAGGUGGUUUGUCGCGUUGUUCGUGAAAUCUCACGGCUUAACUGUGAGCGUGCGGGCGAUACGGGCAGACUAGAGUACUGCAGGGGAGACUGGAAUUCCUGGUGUAGCGGUGGAAUGCGCAGAUAUCAGGAGGAACACCGGUGGCGAAGGCGGGUCUCUGGGCAGUAACUGACGCUGAGGAGCGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGGUGGGUACUAGGUGUGGGUUUCUUCCUGGGAUCCGUGCCGUAGCUAACGCAUUAAGUACCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGCGGAGCAUGUGGAUUAAUUCGAUGCAACGCGAAGAACCUUACCUGGGUUUGACAUGACAGGACGCGUCUAGAGAUAGGCGUUCC--CUUG-UGGCCUGUGUGCAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCUCAUGUUGCCAGCGGAAUG-CCGGGGACUCGUGAGAGACUGCCGGGGUCAACUCGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGCCCCUUAUGUCCAGGGCUUCACACAUGCUACAAUGGCCGGUACAAAGGGCUGCGAUGCCGCGAGGUUAAGCGAAUCCUUUAAAGCCGGUCUCAGUUCGGAUCGGGGUCUGCAACUCGACCCCGUGAAGUCGGAGUCGCUAGUAAUCGCAGAUCAGCACGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACGUCAUGAAAGUCGGUAACACCCGAAGCCAGUGGCCUAACCUUUGGGAGGGAGCUGUCGAAGGUGGGAUCGGCGAUUGGGACGAAGUCGUAAmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
hi.Noc.fla -----mmmmmmmmmmmmmmmmmmmmmmGACGAACGCUGGCGGCGUGCUUAACACAUGCAAGUCGAGCGGAAAGGCCC-----UUCG-----GGGUACUCGAGCGGCGAACGGGUGAGUAACACGUGAGAAUCUGCCCCAGGCUCUGGGAUAGCCACCGGAAACGGUGAUUAAUACCGGAUACGACAGCAUUGUGAAAG---------UUUU------UCGGCCUGGGAUGUGCUCGCGGCCUAUCAGCUUGUUGGUGAGGUAAUGGCUCACCAAGGCUUCGACGGGUAGCCGGCCUGAGAGGGUGACCGGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGGAAGCCUGAUCCAGCAACGCCGCGUGAGGGAUGACGGCCUUCGGGUUGUAAACCUCUUUCAGCACAGACGAAGC---------GCAA-----------GUGACGGUAUGUGCAGAAGAAGGACCGGCCAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUCCGAGCGUUGUCCGGAAUUAUUGGGCGUAAAGGGCUCGUAGGCGGUCUGUCGCGUCGGGAGUGAAAACCAGGUGCUUAACACCUGGCCUGCUUUCGAUACGGGCAGACUAGAGGUACUCAGGGGAGAAUGGAAUUCCUGGUGUAGCGGUGAAAUGCGCAGAUAUCAGGAGGAACACCGGUGGCGAAGGCGGUUCUCUGGGAGUAUCCUGACGCUGAGGAGCGAAAGUGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACACCGUAAACGUUGGGCGCUAGGUGUGGGAUCCUUCCCGGGUUCCGUGCCGCAGCUAACGCAUUAAGCGCCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGCGGAGCAUGCGGAUUAAUUCGAUGCAACGCGAAGAACCUUACCUGGGUUUGACAUAACCGGAAAGCUGCAGAGAUGUAGCCCCU--UUU---AGUCGGUGUACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUCCUAUGUUGCCAGCAAUUCGGUUGGGGACUCAUAGGAGACUGCCGGGGUCAACUCGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGCCCCUUAUGUCCAGGGCUUCACGCAUGCUACAAUGGCCGGUACAAAGGGCUGCGAUCCCGUGAGGGUGAGCGAAUCCCAAAAAGCCGGUCUCAGUUCGGAUUGGGGUCUGCAACUCGACCCCAUGAAGUCGGAGUCGCUAGUAAUCGCAGAUCAGCACGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACGUCACGAAAGUCGGCAACACCCGAAGCCAGUGGCCCAACCCUUGGGGGGGAGCUGUCGAAGGUGGGGCUGGCGAUUGGGACGAAGUCGUAACAAGGUAGCCGUACCGGAAGGUGCmmmmmmmmmmmmm-----
hi.Str.rim -UCACGGAGAGUUUGAUCCUGGCUCAGGACGAACGCUGGCGGCGUGCUUAACACAUGCAAGUCGAACGAUGAAGCCC-----UUCG-----GGGUGGAUUAGUGGCGAACGGGUGAGUAACACGUGGGAAUCUGCCCUGCGCUCUGGGACAAGCCCUGGAAACGGGGUCUAAUACCGGAUAUGACAGCAUUGUGAAAGC--------UCCG------GCGGUGCAGGAUGAGCCCGCGGCCUAUCAGCUUGUUGGUUAGGUAAUG-CCUACCAAGGCGGCGACGGGUAGCCGGCCUGAGAGGGCGACCGGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGCGCAAGCCUGAUGCAGCGACGCCGCGUGAGGGAUGACGGCCUUCGGGUUGUAAACCUCUUUCAGCAGGGAAGAAGC---------GCAA-----------GUGACGGUACCUGCAGAAGAAGCGCCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGCGCAAGCGUUGUCCGGAAUUAUUGGGCGUAAAGAGCUCGUAGGCGGCUUGUCGCGUCGGAUGUGAAAGCCCGGGGCUUAACCCCGGGUCUGCAUUCGAUACGGGCAGGCUAGAGUUCGGUAGGGGAGAUCGGAAUUCCUGGUGUAGCGGUGAAAUGCGCAGAUAUCAGGAGGAACGCCGGUGGCGAAGGCGGAUCUCUGGGCCGAUACUGACGCUGAGGAGCGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGUUGGGAACUAGGUGUGGGCGACUUCCCGUCGUCCGUGCCGCAGCUAACGCAUUAAUUGCCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGCGGAGCAUGUGGCUUAAUUCGACGCAACGCGAAGAACCUUACCAAGGCUUGACAUAACCGGAAACCUCUGGAGACAGGGGCCCC--CUUG-UGGUCGGUGUACAGGUGGUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUG-GCUCUGUUGCCAGCAUUUCGGAUGGGGACUCACAGGAGACCGCCGGGGUCAACUCGGAGGAAGGUGGGGACGACCUCAAGUCAUCAUGCCCCUUAUGUCUUGGGCUGCACACGUGCUACAAUGGCCGGUACAAUGAGCUGCGAUACCGCGAGGUGGAGCGAAUCUCAAAAAGCCGGUCUCAGUUCGGAUUGGGGUCUGCAACUCGACCCCAUGAAGUCGGAGUCGCUAGUAAUCGCAGAUCAGCAUGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACGUCACGAAAGUCGGUAACACCCGAAGCCGGUGGCCCAACCCUUGGGAGGGAAUCGUCGAAGGUGGGACUGGCGAUUGGGACGAAGUCGUAACAAGGUAGCCGUACCGGAAGGUGCGGCUGGAUCACCUCCUUU
lo.Ach.lai UAUAUGGAGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAACGAAGCAUC-------UUCG-------GAUGCUUAGUGGCGAACGGGUGAGUAACACGUAGAAACCUACCUUUAACUCGAGGAUAACUCCGGGAAACUGGAGCUAAUACUGGAUA-GGAUGAA-AUUUAAAGA--------UUUA------UCGGUUUAAGAGGGGUCUGCGGCGCAUUAGUUAGUUGGUGGGGUAAGAGCCUACCAAGACGAUGAAUCGUAGCCGGACUGAGAGGUCUACCGGCCACAUUGGGACUGAGA-ACGGCCCAAACUCCUACGGGAGGCAGCAGUAGGGAAUUUUCGGCAAUGGGGGAAACCCUGACCGAGCAACGCCGCGUGAACGACGAAGUACUUCGGUAUGUAAAGUUCUUUUAUAUGGGAAGAAAAAUU------AAA----------AAUUGACGGUACCAUAUGAAUAAGCCCCGGCUAACUAUGUGCCAGCAGCCGCGGUAAUACAUAGGGGGCGAGCGUUAUCCGGAUUUACUGGGCGUAAAGGGUGCGUAGGUGGUUAUAAAAGUUUGUGGUGUAAGUGCAGUGCUUAACGCUGUGA-GGCUAUGAAAACUAUAUAACUAGAGUGAGACAGAGGCAAGUGGAAUUCCAUGUGUAGCGGUAAAAUGCGUAAAUAUAUGGAGGAACACCAGUGGCGAAGGCGGCUUGCUGGGUCUAUACUGACACUGAUGCACGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAGAACUAAGUGUUGGCC--AUAA---GGUCAGUGCUGCAGUUAACGCAUUAAGUUCUCCGCCUGAGUAGUACGUACGCAAGUAUGAAACUCAAAGGAAUUGACGGGACCCCGCACAAGCGGUGGAUCAUGUUGUUUAAUUCGAAGAUACACGAAAAACCUUACCAGGUCUUGACAUACUCUGAAAGGCUUAGAAAUAAGUUC-GG--AGG---CUCAGAUGUACAGGUGGUGCACGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUUGCUAGUUACCAUCA-UUAAGUUGGGGACUCUAGCGAGACUGCCAGUGAUAAAUUGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGACCUGGGCUACAAACGUGAUACAAUGGCUGGAACAAAGAGAAGCGAUAGGGUGACCUGGAGCGAAACUCACAAAAACAGUCUCAGUUCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGCAAAUCAGCAUGUUGCGGUGAAUACGUUCUCGGGGUUUGUACACACCGCCCGUCAAACCACGAAAGUGGGCAAUACCCAACGCCGGUGGCCUAACCGAAAGGAGGGAGCCGUCUAAGGUAGGGUCCAUGAUUGGGGUUAAGUCGUAACAAGGUAUCCCUACGGmmmmmmmmmmmmmmmmmmmmm-----
lo.Bac.alc -----mmmmmmmUUGAUCCUGGCUCAGGACGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAGCGGACCAAAGGGAG--CUUG--CUCCCAGAGGUUAGCGGCGGACGGGUGAGUAACACGUGGGAACCUGCCCUGUAGACUGGGAUAACAUCGAGAAAUCGGUGCUAAUACCGGAUA-AUCAACAUUGUAAAAGAUGGC----UCCG--GCUAUCACUAACAGAU-GGCCUGCGGCGCUUUAGCUAGUUGGUAAGGUAAUGGCUUACCAAGGCGACGAUGCGUAGCCGACCUGAGAGGGUGAUCGGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUCUUCCGCAAUGGACGAAAGUCUGACGGAGCAACGCCGCGUGAGUGAUGAAGGUUUUCGGAUCGUAAAGCUCUGUUGUUAGGGAAGAACAAGUGCCGUUAAUA-GGUCGGCACCUUGACGGUACCUAACCAGAAAGCCACGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGUGGCAAGCGUUGUCCGGAAUUAUUGGGCGUAAAGCGCGCGCAGGCGGUCUUUUAAGUCUGAUGUGAAAUAUCGGGGCUCAACCCCGAGGGGUCAUUGGAAACUGGGA-GCUUGAGUACAGAAGAGGAGAGUGGAAUUCCNCGUGUNGCGGUGAAAUGCGUAGAUAUGUGGAGGAACACCAGUGGCGAAGGCGACUCUCUGGUCUGUAACUGACGCUGAGGCGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAGUGCUAGGUGUUAGGGGUUUCGUGCCCUUAGUGCCGAAGUUAACACAUUAAGCACUCCGCCUGGGGAGUACGGCCGCAAGGCUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCAGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAGGUCUUGACAUCCUUUGACCACUCUAGAGAUNGAGC--UUUCUUCGGGGACAAAGUGACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGAUCUUAGUUGCCAGCA-UUUAGUUGGGCACUCUAAGGUGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUNAUGCCCCUUAUGACCUNGGCUACACACGUGCUACAAUGGAUGGUACAAAGGGCAGCGAAACCGCGAGGUCGAGCCAAUCCCAUAAAGCCAUUCUCAGUUCGGAUUGUAGGCUGCAACUCGCCUACAUGAAGCCGGAAUUGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCACGAGAGUUUGUAACACCCmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
lo.Bac.sub UUAUCGGAGAGUUUGAUCCUGGCUCAGGACGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAGCGGACAG-GUGGGAG-CUUG-CUCC---GAUGUUAGCGGCGGACGGGUGAGUAACACGUGGGAACCUGCCUGUAAGACUGGGAUAACUCCGGGAAACCGGGGCUAAUACCGGAUG-GUUGGCAUCAUAAAAGGUGGC----UUCG--GCUACCACUUACAGAUGGACCCGCGGCGCAUUAGCUAGUUGGUGAGGUAACGGCUCACCAAGGCAACGAUGCGUAGCCGACCUGAGAGGGUGAUCGGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUCUUCCGCAAUGGACGAAAGUCUGACGGAGCAACGCCGCGUGAGUGAUGAAGGUUUUCGGAUCGUAAAGCUCUGUUGUUAGGGAAGAACAAGUACCGUUAACA-GGGCGGUACCUUGACGGUACCUAACCAGAAAGCCACGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGUGGCAAGCGUUUUCCGGAAUUAUUGGGCGUAAAGGGCUCGCAGGCGGUUUCUUAAGUCUGAUGUGAAAGCCCCCGGCUCAACCGGGGAGGGUCAUUGGAAACUGGGGAACUUGAGUGCAGAAGAGGAGAGUGGAAUUCCACGUGUAGCGGUGAAAUGCGUAGAGAUGUGGAGGAACACCAGUGGCGAAGGCGACUCUCUGGUCUGUAACUGACGCUGAGGAGCGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAGUGCUAAGUGUUAGGGGGUUCCGCCCCUUAGUGCUGCAGCUAACGCAUUGAGCACUCCGCCUGGGGAGUACGGUCGCAAGACUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACUAGGUCUUGACAUCCUCUGACAAUCCUAGAGAUAGGACGUCCC-UUCG-GGGCAGAGUGACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGAUCUUAGUUGCCAGCA-UUCAGUUGGGCACUCUAAGGUGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGACUUGGGCUACACACGUGCUACAAUGGACAGAACAAAGGGCAGCG-AACCGCGAGGUUAAGCCAAUCCCACAAAUCUGUUCUCAGUUCGGAUCGCAGUCUGCAACUCGACUGCGUGAAGCUGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCACGAGAGUUUGUAACACCCGAAGUCGGUGAGGUAACCUUU-GGAGCCAGCCGCCGAAGGUGGGACAGAUGAUUGGGGUGAAGUCGUAACAAGGUAGCCGUAUCGGAAGGUGCGGCUGGAUCACCUCCUUU
lo.Car.mob -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmGGACGGGUNAGUAACACGUGGGNACCNGCCCAUAAGUGGGGGAUAACAUUCGGAAACGGAUGCUAAUACCGCAUA-ACUCUCCUGAUAAAAGACGGU----UUCC--GCUGUCGCUNAUNGAUNGACCCGCGGCGUNUUAGCUNGUUGGUGAGGUAAUGGCUCACCAAGGCNAUGAUGCNUAGCCGACCUGAGAGGGUNAUCGGCNACACUGGGACUGAGACACGGCCNAGACUCCUACGGGAGGCAGCNGUAGGGAAUCUUCCGCAAUGGACGAAAGUCUGACGGAGCNAUGCCGCGUGAGUGAAGAAGGUUUUCGGAUCGUAAAACUNUGUUGUUAGAGAAGAACNAGGAUGAGCUAAC-UNCUCAUCCCCUGACGGUAUCUNACCAGAAAGCCAUGGCUAACUACGUGCCAGCAGCCGCGGUNAUACGUAGAUGGCNAGCGUUGUCCGGAUUUAUUGGGCGUNAAGCGAGCGCAGGCGGUUCUUUAAGUCUNAUGUGAAAGCCCCCAGCUCNACUGGGNAAGGUCAUUGGAAACUGGGGAACUUGAGUGCAGAAGAGGAGAGUGGAAUUCCACGUGUAGCGGUGAAAUGCGUAGAUAUGUGGAGGAACACCAGUGGCGAAGGCGACUCUCUNGUCUGUNACUGACGCUNAGGCUCGNAAGCGUNGGGAGCAAACAGGAUUAGAUACCCUNGUNGUCCACGCCGUAAACGAUGAGUGCUNAGUGUUGGAGGGUUCCGCCCUUCAGUGCUGCAGCUNACGCAUUAAGCACUNCGCCUNGGGAGUACGGCCGCAAGGCUGAAACUCAAAGGAAUUGACGGGGA-CCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGNAACGCGAAGAACCUUACCAGGUCUUGACAUCCUUUGACCACUCUAGAGAUAGAGCU-UUCCUUCGGGGACAAAGUGACAGGUGGNGCAUNGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUNAAGUCCCGCAACGAGCGCAACCCUNAUUACUAGUUGCCAGCA-UUCAGUUGGGCACUCUAGUGAGACUGCCGGUGAUAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGACCUNGGCUACACACGUGCUACAAUGGAUGGUACAACGAGUCGCAAGACCGCGAGGUCAAGCUAAUCUCUUAAAGCCAUUCUCNGUUCGGAUUGCAGGCUGCNACUCGCCUNCAUGAAGCCGGAAUCGCUAGUAAUCGCGGAUCNGAACGCCGCGGUNAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCACGAGAGUUUGUAACACCCGAAGUCGGUGAGGUNACCUUUUGGAGCCAGCCGCCUAAGGUNGGAUAGAUmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
lo.Eub.lac -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmCGGCGUGCUUNACMCRUGCGAGUCGAGCGAAGCACUUAGGWAAUUCGUUCCUAUUUGACUGAGCGGCGGACGGGUGAGUAACGCGUGGGAACCUCCCUCAUACAGGGGGAUAACAGUUAGAAAUGACUGCUAAUACCGCAUAAGACCGCAUGGUAAAAAC--------UCCG------GUGGUAUGAGAUGGACCCGCGUCUGAUUAGUUAGUUGGUGGGGUAACGGCCUACCAAGGCGACGAUCAGUAGCCGACCUGAGAGGGUGACCGGCCACAUUGGGACUGAGACACGGCCCAAACUCCUACGGGAGGCAGNAGNGGGGAAUAUUGCACAAUGGGGGANACCCUGAUGCAGCGACGCCGCGUGAGCGAAGAAGUAUUUCGGUAUGUAAAGCUCUAUCAGCAGGGAAG-------------AAAA------------UGACGGUACCUGACUAAGAAGCCCCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGGGCAAGCGUUAUCCGGAUUUACUGGGUGUAAAGGGAGCGUAGACGGAGCAGCAAGUCUGAUGUGAAAACCCGGGGCUCAACCCCGGGACUGCAUUGGAAACUGUUGAUCUGGAGUGCCGGAGAGGUAAGCGGAAUUCCUAGUGUAGCGGUGAAAUGCGUAGAUAUUAGGAGGAACACCAGUGGCGAAGGCGGCUUACUGGACGGUAACUGACGUUGAGGCUCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGACUACUAGGUGUCGGGUGGAAA-GCCAUUCGGUGCCGCAGC-AACGCAAUAAGUAGUCCACCUGGGGAGUACGUUCGCAAGAAUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAANAACCUUACCUGCUCUUGACAUCCGGUGACGGCAGAGUAAUGUCUGCUUUUC-UUCG-GAACCCGGUGACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUAUCUUCAGUAGCCAGCG-GUAAGCCGGGCACUCUGGAGAGACUGCCAGGGAUAACCUGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGAGCAGGGCUACACACGUGCUACAAUGGCGUAAACAAAGGGAAGCGAACCCGCGAGGGUGGGCAAAUCCCANAAAUAACGUCUCAGUUCGGAUUGUAGUCUGCAACUCGACUACAUGAAGCUGGAAUCGCUAGUAAUCGCGAAUCAGAAUGUCGCGGUGAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCAUGGGAGUCAGUAACGCCCGAAGUCAGUGACCCAACCGUmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
lo.Lac.car UUAUAUGAGAGUUUGAUCCUGGCUCAGGACGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAACGCACGAAGUUGAAGACUUGUCUUUAACCAAGUGAGUGGCGGACGGGUGAGUAACACGUGGGAACCUGCCCAUUAGAGGGGGAUAACAUUCGGAAACGGAUGCUAAUACCGCAUA-GUUUGCAUAAGGAAAGGUGGC----UUCG--GCUACCACUAAUGGAUGGACCCNCGGCGUAUUAGCUAGUUGGUGAGGUAAUGGCUCACNAAGGCAAUGAUACGUAGCCGACCUGAGAGGGUGAUCGGCCACACUGGGACUGAGACACGGCNNNNACUCCUACGGGAGGCAGCAGUAGGGAAUCUUCCGCAAUGGACGAAAGUCUGACGGAGCAACGCCGCGUGAGUGAAGAAGGUUUUCGGAUCGUAAAACUCUNUUGUUAAAGAAGAACAAGGAUGAGAUAAC-UGCUCAUCCCUNNACGGUAUUUAACCAGAAAGCCACGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGUGGCAAGCGUUGUCCGGAUUUAUUGGGCGUAAAGCGAGCGCAGGCGGUUCUUUAAGUCUNAUGUGAAAGCCCNCNGCUCAACCGGGNAGGGUCAUUGGAAACUGGAGAACUUGAGUGCAGAAGAGGAGAGUGGAAUUCCACGUGUAGCGGUGAAAUGCGUAGAUAUGUGGAGGAACACCAGUGGCGAAGGCGACUCUCUNGUCUGUAACUGACGCUGAGGCUCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAGUGCUAAGUGUUGGAGGGUUCCGCCCUUCAGUGCUGCAGCUAACGCAUUAAGCACUCCGCCUGGGGAGUACGGCCGCAAGGCNNNAACUCAAAGGAAUUGNCGGGGACCNGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAANNAACGCGAAGAACCUUACCAGGUCUUGACAUCCUUUGACCACUCUAGAGAUAGAGCUUUCCCUUCGGGGACAAAGUGACAGGUGGNGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUUACUAGUUGCCAGCA-UUUAGUUGGGCACUCUAGUGAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGACCUGGNCUACACACGUGCUACAAUGGAUGGUACAACGAGUCGCAAGGUCGCGAGGCCAAGCUAAUCUCUUAAAGCCAUUCUCAGUUCGGAUUGUAGGCUGCAACUCGCCUNCAUGAAGCCGGAAUCGCUAGUAAUCGCGGAUCAGAACGCCGCGGUGAAUACGUUCCCGGGUCUUGUACACACCGCNCGUCACACCACGAGAGUUUGUAACACCCGAAGCCGGUGAGGUAACCUUU-GGAGCCAGCCGUCUAAGGUGGGAUAGAUAAUUNGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
lo.Myc.cap -AAAAUGAGAGUUUGAUCCUGGCUCAGGAUAAACGCUGGCGGCUGGCCUAAUACAUGCAAGUCGAACGGGGGUG--------CUUG--------CACCUCAGUGGCGAACGGGUGAGUAACACGUAUCAACU-ACCUUAUAGCGGGGGAUAACUUUUGGAAACGAAAGAUAAUACCGCAUGUAGAUGCAUAUCAAAAGAACC-----GUUU---GGUUCACUAUGAGAUGGGGAUGCGGCGUAUUAGCUAGUAGGUGAGAUAAUAGCCCACCUAGGCGAUGAUACGUAGCCGAACUGAGAGGUUGAUCGGCCACAUUGGGACUGAAAUACGGCCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUUUUUCACAAUGGACGAAAGUCUGAUGAAGCAAUGCCGCGUGAGUGAUGACGGCCUUCGGGUUGUAAAGCUCUGUUGUAAGGGAAGAAAAAAUAGAGUAGAAA-UGACUUUAUCUUGACAGUACCUUACCAGAAAGCCACGGCUAACUAUGUGCCAGCAGCCGCGGUAAUACAUAGGUGGCAAGCGUUAUCCGGAUUUAUUGGGCGUAUAGGGUGCGUAGGCGGUUUUGCAAGUUUGAGGUUAAAGUCCGGAGCUCAACUCCGGUU-CGCCUUGAAGACUGUUUUACUAGAAUGCAAGAGAGGUAAGCGGAAUUCCAUGUGUAGCGGUGAAAUGCGUAGAUAUAUGGAAGAACACCUGUGGCGAAAGCGGCUUACUGGCUUGUUAUUGACGCUGAGGCACGAAAGCGUGGGGAGCAAAUAGGAUUAGAUACCCUAGUAGUCCACGCCGUAAACGAUGAGUACUAAGUGUUGGG---GUAA----CUCAGCGCUGCAGCUAACGCAUUAAGUACUCCGCCUGAGUAGUAUGCUCGCAAGAGUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGUGGUGGAGCAUGUGGUUUAAUUCGAAGCAACACGAAGAACCUUACCAGGGCUGACA-UCCAGUGAAAGCUAUAGAGAUAUAGU--AG--AGG---UUCAUUGAGACAGGUGGUGCAUGGUUGUCGUCAGUUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAACGCAACCCUUGUCGUUAGUUACUAACA-UUAAGUUGAGAACUCUAACGAGACUGCUAGUG-UAAGCUAGAGGAAGGUGGGGAUGACGUUAAACUACUAUGCCCUUUAUGUCCUGGGCUACACACGUGCUACAAUGGCUGGUACAAAGAGUUGCAAUCCUGUGAAGGGGAGCUAAUCUCAAAAAACCAGUCUCAGUUCGGAUUGAAGUCUGCAACUCGACUUCAUGAAGCCGGAAUCACUAGUAAUCGCGAAUCAGCUUGUCGCGGUGAAUACGUUCUCGGGUCUUGUACACACCGCCCGUCACACCAUGAGAGUUGGUAAUACCAGAAGUAGGUAGCUUAACCAUUUGGAGAGCGCUUCCCAAGGUAGGACUAGCGAUUGGGGUGAAGUCGUAACAAGGUAUCCGUACGGGAACGUGCGGAUGGAUCACCUCCUUU
lo.Myc.myc -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmCUGGCGGCAUGCCUAAUACAUGCAAGUCGAACGGAGGUG--------CUUG--------CACCUCAGUGGCGAACGGGUGAGUAACACGUAUCAACCUACCUCAUAGCGGGGGAUAACUUUUGGAAACGAAAGAUAAUACCGCAUGUAGAUGCAUAUCAAAAGAACC-----GUUU---GGUUCACUAUGAGAUGGGGAUGCGGCGUAUUAGCUAGUAGGUGAGAUAAUAGCCCACCUAGGCGAUGAUACGUAGCCGAACUGAGAGGUUGAUCGGCCACAUUGGGACUGAGAUACGGCCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUUUUUCACAAUGGACGAAAGUCUGAUGAAGCAAUGCCGCGUGAGUGAUGACGGCCUUCGGGUUGUAAAGCUCUGUUGUAAGGGAAGAAAAAAUAAAGUAGAAA-UGACUUUAUCUUGACAGUACCUUACCAGAAAGCCACGGCUAACUAUGUGCCAGCAGCCGCGGUAAUACAUAGGUGGCAAGCGUUAUCCGGAUUUAUUGGGCGUAUAGGGUGCGUAGGCGGUUUUGCAAGUUUGAGGUUAAAGUCCGGAGCUCAACUCCGGUU-CGCCUUGAAAACUGUAUUACUAGAAUGCAAGAGAGGUAAGCGGAAUUCCAUGUGUAGCGGUGAAAUGCGUAGAUAUAUGGAAGAACACCUGUGGCGAAAGCGGCUUACUGGCUUGUUAUUGACGCUGAGGCACGAAAGCGUGGGGAGCAAAUAGGAUUAGAUACCCUAGUAGUCCACGCCGUAAACGAUGAGUACUAAGUGUUGGG---GUAA----CUCAGCGCUGCAGCUAACGCAUUAAGUACUCCGCCUGAGUAGUAUGCUCGCAAGAGUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGUGGUGGAGCAUGUGGUUUAAUUCGAAGCAACACGAAGAACCUUACCAGGGCUUGACAUCCAGUGAAAGCUAUAGAGAUAUAGU--AG--AGG---UUCAUUGAGACAGGUGGUGCAUGGUUGUCGUCAGUUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAACGCAACCCUUGUCGUUAGUUACUAACA-UUAAGUUGAGAACUCUAACGAGACUGCUAGUG-UAAGCUAGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGUCCUGGGCUACACACGUGCUACAAUGGCUGGUACAAAGAGUUGCAAUCCUGUGAAGGGGAGCUAAUCUCAAAAAACCAGUCUCAGUUCGGAUUGAAGUCUGCAACUCGACUUCAUGAAGCCGGAAUCACUAGUAAUCGCGAAUCAGCUUGUCGCGGUGAAUACGUUCUCGGGUCUUGUACACACCGCCCGUCACACCAUGAGAGUUGGUAAUACCAGAAGUAGGUAGCUUAACCGUUUGGAGAGCGCUUCCCAAGGUAGGACUAGCGAUUGGGGUGAAGUCGUAACAAGGUAUCCGUACGGGAACmmmmmmmmmmmmmmmmm-----
lo.Spi.cit UUUAAUGAGAGUUUGAUCCUGGCUCAGGAUGAACGCUGGCGGCAUGCCUAAUACAUGCAAGUCGAACGGGGUG---------CUUG---------CACCCAGUGGCGAACGGGUGAGUAACACGUAUCAAUCUACCCAUUAGCGGGGGAUAACAGUUGGAAACGACUGAUAAUACCGCAUA-CGACGCAUGUUAAAAGGUCC-----GUUU---GGAUCACUAAUGGAUGAGGAUGCGGCGUAUUAGUUAGUUGGUGGGGUAAUGGCCUACCAAGACAAUGAUACGUAGCCGAACUGAGAGGUUGAUCGGCCACAUCGGGACUGAGACACGGCCCGAACUCCUACGGGAGGCAGCAGUAGGGAAUUUUUCACAAUGG-CGAAAGCCUGAUGGAGCAAUGCCGCGUGACUGAAGACGGUCUUCGGAUUGUAAAAGUCUGUUGUAAGGGAAGAACAGUAAGUAUAGAAA-UGAUACUUAUUUGACGGUACCUUACCAGAAAGCCACGGCUAACUAUGUGCCAGCAGCCGCGGUAAUACAUAGGUGGCAAGCGUUAUCCGGAUUUAUUGGGCGUAAAGCGUGCGCAGACGGUUUAACAAGUUUGGGGUCAAAUCCUGGAGCUCAACUCCAGUU-CGCCUUGAAAACUGUUAAGCUAGAGUGUAGGAAAGGUCGAUGGAAUUCCAUGUGUAGCGGUGAAAUGCGUAGAUAUAUGGAGGAACACCAGUGGCGAAGGCGGUCGACUGGCCUAUCACUGACGUUUAGGCACGAAAGCGUAGGGAGCAAAUAGGAUUAGAUACCCUAGUAGUCUACGCCGUAAACGAUGAGUACUAAGUGUCGGAC---UAA---GUUCGGUGCUGCAGCUAACGCAUUAAGUACUCCGCCUGAGUAGUAUGCUCGCAAGAGUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAAGGCUUGACAUCCAGUGAAAGCUGUAGAAAUACAGU--GG--AGG---UUCAUUGAGACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGCCGUGAGGUGUUUGGUUAAGUCCAGUAACGAGCGCAACCCUUGCCGUUAGUUACUC-CA-UUAAUUGAGAUACUCUAACAGGACUGCUAGUG-UAAGCUAGAGGAAGGUGGGGAUGACGUCAAAUCAGCAUGCCCCUUAUAUCCUGGGCUACACACGUGCUACAAUGGUCGGUACAAACAGUUGCGAUCUCGUAAGAGGGAGCUAAUCUGAAAAAGCCGAUCUCAGUUCGGAUUGAGGGCUGCAACUCGCCCUCAUGAAGCCGGAAUCGCUAGUAAUCGCGAAUCAGCAUGUCGCGGUGAAUACGUUCUCGGGUCUUGUACACACCGCCCGUCACACCAUGAGAGUUGAUAAUACCAGAAGUCGGUAUUCUAACCGCAAGGAGGAAGCCGCCCAAGGUAGGAUUGAUGAUUAGGGUGAAGUCGUAACAAGGUAUCCGUACGAGAACGUGCGGAUGGAUCACCUCCUUU
lo.Sta.hom -----mmAGAGUUUGAUNNUGGCUCAGGAUGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAGCGAACAGACGAGGAG-CUUG-CUCCUUUGACGUUAGCGGCGGACGGGUGAGUAACACGUGGGAACCUACCUAUAAGACUGGGAUAACUUCGGGAAACCGGAGCUAAUACCGGAUA-AUAUGCAUAGUGAAAGAUGGC----UUU---GCUAUCACUUAUAGAUGGACCUGCGCCGUAUUAGCUAGUUGGUAAGGUAACGGCUUACCAAGGCAACGAUACGUAGCCGACCUGAGAGGGUGAUCGGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUCUUCCGCAAUGGGCGAAAGCCUGACGGAGCAACGCCGCGUGAGUGAUGAAGGUCUUCGGAUCGUAAAACUCUGUUAUUAGGGAAGAACAAACGUGUAAUAAC-UGUGCACGUCUUGACGGUACCUAAUCAGAAAGCCACGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGUGGCAAGCGUUAUCCGGAAUUAUUGGGCGUAAAGCGCGCGUAGGCGGUUUUUUAAGUCUGAUGUGAAAGCCCACGGCUCAACCGUGGAGGGUCAUUGGAAACUGGAAAACUUGAGUGCAGAAGAGGAAAGUGGAAUUCCAUGUGUAGCGGUGAAAUGCGCAGAGAUAUGGAGGAACACCAGUGGCGAAGGCGACUUUCUGGUCUCUAACUGACGCUGAUGUGCGAAAGCGUGGGGAUCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAGUGCUAAGUGUUAGGGGGUUCCGCCCCUUAGUGCUGCAGCUAACGCAUUAAGCACUCCGCCUGGGGAGUACGACCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCAAAUCUUGACAUCCUUUGACCCUUCUAGAGAUAGAAG--UUUCUUCGGGGACAAAGUGACAGGUGGUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAAGCUUAGUUGCCAUCA-UUAAGUUGGGCACUCUAAGUUGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGCCCCUUAUGAUUUGGGCUACACACGUGCUACAAUGGACAAUACAAAGGGCAGCGAAACCGCGAGGUCAAGCAAAUCCCAUAAAGUUGUUCUCAGUUCGGAUUGUAGUCUGCAACUCGACUACAUGAAGCUGGAAUCGCUAGUAAUCGUAGAUCAGCAUGCUACGGUGAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCACGAGAGUUUGUAACACCCGAAGCCGGUGGAGUAACCAUUUGGAGCUAGCCGUCGAAGGUGGGACAAAUGAUUGGGGUGAAGUCGUAACAAGGUAGCCGUAUCGGAAGGUGCGGCUGGAUCACCUCCUUU
mt.Dro.mel -----UUAAAGUUUUAUUUUGGCUUAAAA-AUUUGUUAUUAAUUUGAUU--UAUAUGUAAAUUU--------------------------------------UUGU------GUGAUU-UUA-UAUU-AUUUAAA-----------------------------------------------------------------------------------------AAAU--AAAUA------U-------------------------------AAA-----AUU---------------------------UAUC--------------------------------------GCAGUAAUUAAUAUUAUU-AAUUA-AAAAAUUUAGAAAUAGCAAUAUAAA---------------------------------------------------------------------------------------------AAAGUAUUGACUAAAUUGGUGCCAGCAGUCGCGGUUAUACCAUUAAUACAAAUAAAUUUUU---------UUAGUAUUAAUUAAAUUAAU---------------------------------------------------------------------------UUAU-------UAA--AAUUAAAUAUAU-A---GUUUUUA-UAUU-----------------UAAUUA----AU-AAAAA------------AAUUGAGUUAAA-UUAA---UAAAAAACUAGGAAUACCC-UA--UAUU-UAA--AAU-GUAAAUAAAUUG--------------------------------------------------------CUAAAG--UAGUA-AUAGUAU-UUCUGAAACUUAAAAAAUUUGGCGGUAUUUUAUCUA-CUAGA--GA-CC-U--GUUUUAUCGUAAUCC-ACGA-GGACCUUACUUAAAU-GUAAU-------------------------------------------------AGUUUAUAUACCGUCGUUAUCAGAAUAUUUU--UAGA-A---AUAAU---AU--------UCAAUAAUUUUAAU--------------------------------------------------------------AAAAA-UUUAUAUCAGAUCAAGGUGUAGCUUAUAUUUAAG--UAAUAAUGGGUUA-AA----UAAA-------------------------------------UUUAUA------------UGAAUAAAAUUAUGAAAA---AAUUUUUGAAAGUGGAUUUAGUAGUAAAAUUAU-AGA---UAAUAAUUUGAUUUUAGCUCUAAAAUAUGUACACAUCGCCCGUCGCUCUUAUU---------------------------------AUUA------------------------------GGUAAGAUAAGUCGUAACAUAGUAGAUGUACUGGAAAGUGUAUCUAGAAUGA-------
mt.Gal.gal -----AAAAGACUUAGUCCUAACCUUUCU-AUUGGUUUUUGCUAGACAUA-UACAUGCAAGUAU--------------------------------------CCGCAUCCCAGUGAAA-AUGCCCCCACCUUUCUUCCC-------------------------------------------------------------------------------------AAGC-AAAAGGAGCAGGUAUCGGCA-CACU-------------------CAGU----AGCCC---AAGACGCCUU-GCU---UAAGCCAC-----------------------ACCCCCC-GGGUACUAGCAGUAAUUAACCUUAAGCAAUAA-GUUAAACUUGACUUAGCCAUAGCAA--------------------------------------------------------------------------------------------CCCAGGGUUGGUAAAUCUUGUGCCAGCCACCGCGGUCAUACAAGAAACCCAAAUCAAUAGCU-----ACCCGGCGUAAAGAGUGGCCACAU--------------------------------------------------------------------GUUAUCUCACC-------AAA--AUGCAACCAAGCUAUAAGCGAUCC-AC--------CUAACCCAAC--CCAA-----AU-CUUAG------------AAUUUAACCACGAAGG----ACCCAAACUGGGAAUACCC-CA--UAUG-CCU--AGCCCUAAAUCUAGAUACCU-----------------------------------C-CAAC--ACAUGUAUCCGCCU---GAGAACGAGCCAAAGCUUAAAACUCUAAGGACUUGGCGGUGCCCCACCCA-CUAGA--GA-CC-U--GCUAUAUCGUAAUCC-ACGA-UCACCCAACCACCCC-GCCA---GCA--------------------------------------------AGCCUACAUACCGCCGUCGCCAGCCCACCUCAAUGAA-G---ACAACA--GUG------AGCUCAAUAGCCCCU---------------------------------------------------------------CGCU-AAUAAGACAGGUCAAGGUAUAGCCUAUGGGGUGG--GAGAAAUGGGCUA-AUU---UUCUA------------------------------------AGAACA----------AACGAAAAAGGAUGUGAAACC-CGCCCUUAGAAGGAGGAUUUAGCAGUAAAGUGAGAUUACCCAGCUCACUUUAAGACGGCUCUGAGGCACGUACAUACCGCCCGUCACCCUCUUCACAAGCCAUCAACAUCAAUA-------------AAUA--------UAUACUCCCC-UCCCGGCUAAAGACGAGGCAAGUCGUAACAAGGUAAGUGUACCGGAAGGUGCACUUAGACUACN------
mt.Bos.tau -----CAUAGGUUUGGUCCCAGCCUUCCU-GUUAACUCUUAAUAAACUUA-CACAUGCAAGCAU--------------------------------------CUACACCCCAGUGAGA-AUGCCCUCUGGUUAUUAA---------------------------------------------------------------------------------------AACU-AAGAGGAGCUGGCAUCAGCA-CACA-------------------CUGU----AGCUC---ACGACGCCUU-GC----UUAACCAC-----------------------A-CCCCA-GGGAAACAGCAGUGACAAAAAUUAAGCCAUAA-ACAAAGUUUGACUAAGUUAUAUUAA---------------------------------------------------------------------------------------------UUAGGGUUGGUAAAUCUCGUGCCAGCCACCGCGGUCAUACGAUUAACCCAAGCUAACAGGA-----GUACGGCGUAAAACGUGUUAAAGC----------------------------------------------------------------------ACCAUCCAA-------AAA--UUCUAACUAAGCUAAAAGCAUUAA-AA--------UAAAAAUAAAUGACAAA----AC-CCUAC------------AGCCGA-GCACUAAAG----ACCCAAACUGGGAAUACCC-CA--UAUG-CUU--AGCCCUAAACACAGAUAAUU-----------------------------------C-AUAC--AAAAUUAUUCGCCA---GAGUACUAGC-AC-GCUUAAAACUCAAAGGACUUGGCGGUGCUUUAUCCU-CUAGA--GA-CC-U--GCUAUAUCGUAAACC-CCGA-AAACCUCACCAAUUC-GCUA---AUA--------------------------------------------AGUCUAUAUACCGCCAUCUUCAGCAAACCCU--AAAG-G---AAAAAA--GUA------AGCGUAAUUAUGAUA---------------------------------------------------------------CAUA-AAAACGUUAGGUCAAGGUGUAACCUAUGAAAUGG-GAAGAAAUGGGCUA-AUU---CUCU-------------------------------------AGAGAA------UAAGCACGAAAGUUAUUAUGAAAC--CAAUAACCAAAGGAGGAUUUAGCAGUAAACUAAGAAGA---UGCUUAGUUGAAUUAGGCCAUGAAGCACGCACACACCGCCCGUCACCCUCCUCAAAUAGAUUCAGUGCAU-CUAA-----------CCUA---------UUAAACGCACUAGCUACAUGAGAGGAGACAAGUCGUAACAAGGUAAGCAUACUGGAAAGUGUGCUUGGAUAAAU------
mt.Hom.sap -----AAUAGGUUUGGUCCUAGCCUUUCU-AUUAGCUCUUAGUAAGAUUA-CACAUGCAAGCAU--------------------------------------CCCCGUUCCAGUGAGU-UCACCCUCUAAUCACCAC---------------------------------------------------------------------------------------GAUC-AAAAGGAACAAGCAUCAGCA-CGCA-------------------AUGC----AGCUC---AAAACGCUUA-GC----CUAGCCAC-----------------------ACCCCCC-GGGAAACAGCAGUGAUUAACCUUUAGCAAUAA-ACAAAGUUUAACUAAGCUAUACUAA-------------------------------------------------------------------------------------------CCCCAGGGUUGGUCAAUUUCGUGCCAGCCACCGCGGUCACACGAUUAACCCAAGUCAAUAGAA-----UC-CGGCGUAAAGAGUGUUUUAGA----------------------------------------------------------------------UCACCCCUCCA-----AAA--ACUCACCUGAGUUAAAAACGUUGA-CA--------C-AAAAUAGACUACAAA----GC-UUUAA------------AUCUGAAACAGAAAAG----ACCCAAACUGGGAAUACCC-CA--UAUG-CUU--AGCCCUAAACCUCAACAGUU-----------------------------------A-AUAC--AAAACUGCUCGCCA---GAACACGAGC-AC-GCUUAAAACUCAAAGGACCUGGCGGUGCUUCAUCCC-CUAGA--GA-CC-U--GCUGUAUCGUAAACC-CCGA-CAACCUCACCACCUC-GCU---------------------------------------------------AGCCUAUAUACCGCCAUCUUCAGCAAACCCU-AUGAG-G---ACAAA---GUA------AGCGCAAGUACCCA----------------------------------------------------------------CGUA-AAGACGUUAGGUCAAGGUGUAGCCCAUGAGGUGG-CAAGAAAUGGGCUA-AUU---UUCU-------------------------------------AGAAAA---------CUACGAUAGCCCUUAUGAAACU-UAAGGGUCGAAGGUGGAUUUAGCAGUAAACUAAGAGGA---UGCUUAGUUGAACAGGGCCCUGAAGCGCGUACACACCGCCCGUCACCCUCCUCAAGUAUACUUCAAAGGACAUUU-----------ACUA---------AAACCCUACGCAUUUAUAU-AGAGGAGACAAGUCGUAACAUGGUAAGUGUACUGGAAAGUGCACUUGGACGAAC------
mt.Mus.mus -----NAAAGGUUUGGUCCUGGCCUUAUA-AUUAAUUAGAGGUAAAAUUA-CACAUGCAAACCU--------------------------------------CCAUAGACCGGUGUAA-AAUCCCUUAAUUUACUUA---------------------------------------------------------------------------------------AAAU-UUAAGGAGAGGGUAUCAGCA-CAUU-------------------AAAU----AGCUU---AAGACACCUU-GC----CUAGCCAC-----------------------ACCCCCC-GGGACUCAGCAGUGAUAAAUAUUAAGCAAUAA-ACAAAGUUUGACUAAGUUAUACCUC--------------------------------------------------------------------------------------------U-UAGGGUUGGUAAAUUUCGUGCCAGCCACCGCGGUCAUACGAUUAACCCAAACUAAUUAUC------UUCGGCGUAAAACGUGUCAACUA---------------------------------------------------------------------UAAAUAAUAA-------AAA--AUCCAACUUAUAUAAAAUUGUUAG-GA--------CCAAACUCAAUAACAAA----AU-UCUAG------------UUAU-AAACACGAAAG----ACCCAAACUGGGAAUACCC-CA--UAUG-CUU--AGCCAUAAACCUAAAUAAUU----------------------------------AA-UUAC--AAAACUAUUUGCCA---GAGAACUAGC-AU-GCUUAAAACUCAAAGGACUUGGCGGUACUUUAUCCA-CUAGA--GA-CC-U--GCUAUAUCGUAAACC-CCGC-CUACCUCACCAUCUC-GCUA---AUU--------------------------------------------AGCCUAUAUACCGCCAUCUUCAGCAAACCCU--AAAG-G---AUUAAA--GUA------AGCAAAAGAAUCA-A---------------------------------------------------------------CAUA-AAAACGUUAGGUCAAGGUGUAGCCAAUGAAAUGG-GAAGAAAUGGGCUA-AUU---UUCUU------------------------------------AGAACA---------UUACUAUACCCUUUAUGAAAC--UAAAGGACUAAGGAGGAUUUAGUAGUAAAUUAAGAAGA---AGCUUAAUUGAAUUGAGCAAUGAAGUACGCACACACCGCCCGUCACCCUCCUCAAAUUAAAUUAAACUUAACAUA-----------UUAA--------UUUCUAGACA-UCCGUUUAUGAGAGGAGAUAAGUCGUAACAAGGUAAGCAUACUGGAAAGUGUGCUUGGAAUAAU------
mt.Sac.cer AUUUAUAAGAAUAUGAUGUUGUUUCAGAUUAAGCGCUAAAUAAGGACAUGACGCAUACGAGUCAU-CGU-UU-AUUA-UU------GAUAAUA-AAU--AUGUGGUGUAAACGUGAGUAUUUAUUAGGAAUUAAAACUAUAG-----------AUAAGCUAAACUUAA------UAUA----UUAUAUAAAUA-AAAG-GAUA---UAUA--A-UAUUUACUAUAGUC-AAGCCAAUA-UGGUUUGGUA-GUAGGUUUAUUAGAGUUAAACCUAGCCACGAUCCAU-AAUCGUAAUGAAAGUUAGAACGAUCACGUUGACUCUGAAAUAU-AGUCAA-UAUCUU-AAGAUACAGCAGUGAGGAAUAUUGGACAAUGA-UCAAAGAUUGAUCCAGUUACUUAUUA-GGAUGAU-UAUAAA-AUAUUUUAUUUUAUUUUAUUAAUAUUUAUUAAUAAUAAUAAUA--AAUUAA-UUUAUUAUAUUAAUAUUAUUUAAU---GUCCUGACUAAAUUUGUGCCAGCAGUCGCGGUAACACAAAGAGGGCGAGCGUUAAUCAUAA-----UGGUUUAAAGGAUCCGUAGAUGAAUUAUA------------------------UAU-------------------------------UAGAGUUAAAAAA-------AGAAUUAUAAUAGUAAAGAAAUAAAUAAU-UAUA------AGACUAAUAUAUGUAAA-A--AA-UUAAAUAU-UA------CAUUGA-GGAUUAAGAG---U-GCG-AAACGGAAUAUUC-GU--UAGUUUCU--AGUAGUAAACUAUGAAUAC-AAUUAUUUAUAAU-UAUUAUAUAUAAAAAUAA---U-GAAUG-AAAGUAUUCCACCUGAAGAGUACGUUA-CA-UAAUGAAACUCAAAACAAUAGACGGUUACAGAUUAA-GCAGU--GA-CA-U--GAUUUUUCGUAAUCC-ACGA-UAACUUUACCAUAUU-G----A-AUAU----UAUAAU---AUAUU-AU---------UU---AUA-UUA-AGGCGUUACAUUGUUGUCUUUAGUUCGUGCU--CAAGUU--AGAUUAAA-UGUGCAACGAGCAAAACUCCAUAUAUAAUU--UUAU--------------------AUUA--UUUAU----UA--A-UAUAAAG--AAAGGAAUUAAGACAAAUCAUAAUGAUCCUUAUAAUAUGGGUAAUAGACGUGCUA-A-AUAAAAUGAUAAUAAAUAAUUUAAUU--U-AAUAUAAC----UUUUAAUAUAUUUUUUUUAUAUGAAUUAUAAUCUGAAAUUCGAUUAUAUGAAAAAAGAAUUGCUAGUAAUCGUAAAUGU---UGUUACGGUGAAUAUUC-UAACUGUUUCGCACUAAUCACUCAUCAGGCGUUGAAACAUAUUAUUAUCUUAUUAUUAUAUAAAUUU-UAA-UAUAUUUAUUUAUAUCAGAAAUAAUAUGAAUUAAUGCGAAGUUG-AAUACAGUUACCGUAGGGGAACCUGCGGUGGGCUUAUAAAUAUC
mt.Zea.may CAAAAUCUGAGUUUGAUCCUGGCUCAGAAGGAACGCUAGCUAUAUGCUUAACACAUGCAAGUCGA-CGU-UGUUUUC-GGGGUUGAGUUGAGA-ACA--AAGUGGCGAACGGGUGCGUAACGCGUGGGAAUCUGCCGAACAG-----------UCGGGCCAAUCCUGAA-----GAAA----GCU-CAAAGC----------------------------CUGUUUGAUGAGCCUGCGUAGUAUUGGUA-GUUGGUCAGGUAAAGGCUGACCAAGCCAUGAUGCUU-AGCUGGUCUUUUCGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCGGACUCCCC-G-GGGGCAGCAGUGGGGAAUCUUGGACAAUGG-GCAAAGCCCGAUCCAGCAAUAUCGC--GAGUGAA-GAAGGCAAUGGCUUGUAAAGCUCUUUCGUCGAGUGCGCGAUC-----------------------AUGACAGGACUCGAGGAA-AAGCCCCGGCUAACUCCGUGCCAGCAGCCGCGGUAAGACGGGGGGGGCAAGUGUUCUUCGGAAUGACUGGGCGUAAAGGGCACGUAGGCGGUGAAUCGGGUUGAAAGUGA-AAGUCGCCAAAAAGGCGGA---A--UGCUU-------CGA-AC-UUGAGUGAGCAGA-------GGAAUUUCGUGUGUAGGGAAAUCCAUCUA-CGAA------GGAACGCCAAAAGCAAG-A--UC-UCUGGGUCCCU------CGCUGG-GUGCGAUGGG---GAGCG-AACAGGAAUACCC-UG--UAGU-CCA--UGCCGUAAACGAUGAGUGUUCGCCCUUGGUCUGUACGGCGGAUCAGGGCCCA---C-UAGCGUGAAACACUCCGCCUGGGGAGUACGGUC-CA-GACCGAAACUCAAAGGAAUUGACGGGGGCCUGACAA-GCGGU--GA-CA-U--GGUUUUUCGUACAAC-GCGC-AAACCUUACCAGCCC-GACA-A-UGAACAAAACCUGU---UAACG-GGA--------ACU--UUC-AUA-AGGUGCUGCAUGGCUGUCGUCAGCUCGUGUC--UGGAUG--UGGUCAAGUCCUAUAACGAGCGAAACCCUCGUUUUGUGUUGCUGAGAAG----UGCCGCACUCACGAGGGACUGCCAGU-GA--ACUGGAGGAAGGUGGGGAUGACGUCAAGUCCGCAUGGCCCUUAUGGGCUGGGCCACACACGUGCUA-AAUGGCAAUGACAAUGGGAAGCAAGGCU--AAGGCGGAGC----UCCGGAAAGAUUGCCUCAGUUCGGAUUGUUCUCUGCAACUCGGGAACAUGAAGUAGAAAUCGCUAGUAAUCGCGGAUGC---UGCCGCGGUGAAUAUGUACCCGGGCCCUGUACACACCGCCCGUCACACCCUGGGAAUUGGUUUCGCCCGAAGCUCGGACCAUGAUCACUAUAUUGGCGCAUACCACGGUGGGGUCUUCGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGUGGCUGGAUUGAAUCC---
mt.Gly.max CAAAAUAAGAGUUUGAUCCUGGCUCAGAAGGAACGCUAGCUAUAUGCUUAACACAUGCAAGUCGA-CGU-UGUUUUC-GGGGUGC-GUUGAAA-ACA--AAGUGGCGAACGGGUGCGUAAUGCGUGGGAAUCUGCCGAACAG-----------UCGGGCCAAUCCUGAA-----GAAA----GCU-AAAAGC----------------------------CUGUUUGAUGAGCCUGCGUAGUAUUGGUA-GUUGGUCAGGUAAAGGCUGACCAAGCCAUGAUGCUU-AGCUGGUCUUUUCGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCGGACUCCCC-G-GGGGCAGCAGUGGGGAAUCUUGGACAAUGG-GCAAAGCCCGAUCCAGCAAUAUCGC--GAGUGAA-GAAGGCAAUGGCUUGUAAAGCUCUUUCGUCGAGUGCGCGAUC-----------------------AUGACAGGACUCGAGGAA-AAGCCCCGGCUAACUCCGUGCCAGCAGCCGCGGUAAGACGGGGGGGGCAAGUGUUCUUCGGAAUGACUGCGCGUAAAGGGCACGUAGGCGGUGAAUCGGGUUGAAAGUGA-AAGUCGCCAAAAACGUGGA---A--UGCUU-------CGA-AC-UUGAGUGAGCAGA-------GGAAUUUCGUGUGUAGGGAAAUCCAUCUA-CGAA------GGAACGCCAAAAGCAAG-A--UC-UCUGGGUCCCU------CGCUGG-GUGCGAUGGG---GAGCG-AACGGGAAUACCC-UG--UAGU-CCA--UGCCGUAAACGAUGAGUGUUCGCCCUUGGUCU--ACG--GGAUCAGGGCCCA---C-UAGCGUGAAACACUCCGCCUGGGGAGUACGGUC-CA-GACCGAAACUCAAAGGAAUUGACGGGGGCCUGACAA-GCGGU--GA-CA-U--GGUUUUUCGUACAAC-GCGC-AAACCUUACCAGCCC-GACA-A-UGAACAAAACCAGU---UAACG-GGA--------ACU--UUC-AUA-AGGUGCUGCAUGGCUGUCGUCAGCUCGUGUC--UGGAUG--UGGUCAAGUCCUAUAACGAGCGAAACCCUCGUUUUGUGUUGCUGAGAAGAAU-UGCCGCACUCACGAGGGACUGCCAGU-UA--ACUGGAGGAAGGUGGGGAUGACGUCAAGUCCGCAUGGCCCUUAUGGGCUGGGCCACACACGUGCUA-AAUGGCAAUUACAAUGGGAAGCAAGGCU--AAGGCGGAGC----UCCGGAAAGAUUGCCUCAGUUCGGAUUGUUCUCUGCAACUCGGGAACAUGAAGUUGGAAUCGCUAGUAAUCGCGGAUGC---UGCCGCGGUGAAUAUGUACCCGGGCCCUGUACACACCGCCCGUCACACCCUGGGAAUUGGUUUCGCCCGAAGCUCGGACCAUGAUCACUAUAUUGGCGCAUACCACGGUGGGGUCUUCGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGUGGCUGGAUGGAAUCC---
mt.Tet.pyr AAUUUAUUGAGUGUGGUCAUGGCUCGGGAUUAACGCUAAUUAGACGCCUAACACAUGCGAGUU---UA--UAUAUUA-GAU-----UC---UA-AAU--GUAUAGCGUCAAGGUGAGUAAAUACA--UAAUAUGCCUUUAAGAAAUAAAGUUAAUUUA-AAAAUACAAA--UGCAUAAA---UUAUAAACUAA----G-AUUA--AU-UAA-G-UAAUUAUUUCUAAAAUGUUUAAU--AAAUAAA-U--AUUUAUUUUU---AGUAAAAUA-AGCCUGAUGUUU--AGUUGAAUU-UAGAGUUGUUCAACCACAUACGGGUUGAAAAC-UACCCUA-UCUAU----UGAC-AGCAGUGAGGA-UUUUGG-CAAUAU-GCAAAACA--A-CCAGCGAACUAAU--AAACGAAGAAGUAGCAA-UUGU-A-AAGUUUAAUUAACAAAUG---------------------------------AGUA-UAU-CUAGA-GAAGCUCUGGCUAAACAUGUACCAGCAGCCGCGGUAAUACAUGAGGAGCGAGCGUUACUCAUAUUGACUGAGUGUAUUAAAUACGUAGGAUGUUAUAAUUACUACUUUAAA-AAUGUAAU-AAAAA----UAAAU-C-UGU-------GUUA--U-AAUAAUUAUAUUA-------AGA-CUUAUAGAACAACGAAAUGUACACU-AUAU------AGCUAGCCAUAAACAAG-A--UC-UCUAAUUA-UA------AUCUGA-GUAUGACGGG---UAUCG-AUGAGGAUCUCCC-UA--UAGU-CCG--UACUGUAAAAGAUGAAUACUUUAUGAA---------C-----UUCAGAAU-A---C-UAGCA--AAGUAUUCUGCUUGGGGAGUAUUAUC-CA-GAUUAAAACUUAACUGAAUUGGCGGGAAUUUGUCGA-ACGGU--GA-CA-U--GGUUUUGCGUAAUCC-ACGC-AAAUCUUACCAACGU-UAG--C-UUUAUUAAUAUGGU----CACUA-UA--------AG---UAA-AGU-CGGAAUUGCAUGGCUGUCGUCAGUUCGUGCU--UGAGUU--GGAUUAAGUUCUUUAACGAAUGCAACCCUAUAAAUAAGUCUUUAAUAG-----UUUAUUAUUCUUGUUUAAUCUAUAUCAAUAUGAAUUAGGGGUUUUAGGCUGAAGUCAAGUCCCUAUGGUCUUUAUACGUUGGGCUACACACGUGUUA-AA-GGUAAAAACAAAGAGACGCAAUAGA--AAUCUGGAGC----CUC-AAAAAUUACCU-CAGUUCAGAUUGUCUCAUGAAAUUCUGAGGCAUGAAGAUGAAAUCGUUAGUAAUUGUAAAUAA---UGUUACAGUGAAAUAUUAGUCAAAUUUUGCACACAC-GCCCAUCACGCUCGGAAAGUCAAUAUUAGCGGAAG---AUUUGAAAUCUUUA-GGAAAGUAGUAUCUAAUCUAAUAUUGGUAAUCUGAGUGAAGUUGACACAAGGUACUGGUAGGGGAACCUGUUGGUGGAAUAUAUUAUUA
al.Aci.cry -----mmmmmmmmmmmmmmmmmmmmmmAGCGAACGCUGGCGGCAUGCUUAACACAUGCAAGUCGCACGGGCAGG--------GCAA--------CCUGUCAGUGGCGGACGGGUGAGUAACGCGUAGGAAUCUAUCCUUGGGUGGGGGACAACCGUGGGAAACUACGGCUAAUACCGCAUGAUCCCUGAGGGGCAAAGGC-------GAAA-----GUCGCCUGAGGAGGAGCCUGCGUCUGAUUAGGUAGUUGGUGGGGUAAAGGCCUACCAAGCCUGCGAUCAGUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGAAAGCCUGAUCCAGCAAUGCCGCGUGGAUGAAGAAGGUCUUCGGAUUGUAAAGUCCUUUUGGCGGGGACGA------------UGAU-------------GACGGUACCCGCAGAAUAAGCUCCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAAGGGGGCUAGCGUUGCUCGGAAUGACUGGGCGUAAAGGGCGCGUAGGCGGACGGCACAGUCAGGCGUGAAAUUCCUGGGCUCAACCUGGGGACUGCGUCUGAGACGUGUUGUCUUGAGUAUGGAAGAGGGUUGUGGAAUUUCCAGUGUAGAGGUGAAAUUCGUAGAUAUUGGAAAGAACACCGGUGGCGAAGGCGGCAACCUGGUCCAUUACUGACGCUGAGGCGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCUGUAAACGAUGUGUGCUGGAUGUUGGGGUGUUA-GCACUUCAGUGUCGUAGCUAACGCGGUAAGCACACCGCCUGGGGAGUACGGCCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGCAGAACCUUACCAGGAUUUGACAUGGGAGUACCGGUCCAGAGAUGGACUUUCCC-GCAA-GGGGUCCCGCACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGCCUUCAGUUGCCAGCAUUUUGGGUGGGCACUCUGAAGGAACUGCCGGUGACAAGCCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUGUCCUGGGCUACACACGUGCUACAAUGGCGGUGACAGUGGGAAGCCAGGUGGUGACACCGAGCUGAUCUCAAAAA-GCCGUCUCAGUUCGGAUUGCACUCUGCAACUCGAGUGCAUGAAGGUGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAUUUGGUUUGACCUUAAGUUGGUGCGCUAACCGCAAGGAGGCAGCCAACCACGGUCGGGUCAGAGACUGGGGUGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
al.Met.rho -----mmmmmmmmmmmmmmmmmmmmmmAGCGAACGCUGUCGGCAGGCUUAUCACAUGUAAGUCGAGAGGGCACC--------UUCG--------GGUGUCAGCGGCAGACGGGUGAGUAACACGUGGGAACGUGCCCUUCGGUUCGGAAUAACUCAGGGAAACUUGAGCUAAUACCGGAUACGCCCUUAUGGGGAAAGG--------UUUA------CCGCCGAAGGAUCGGCCCGCGUCUGAUUAGCUUGUUGGUGGGGUAACGGCCUACCAAGGCGACGAUCAGUAGCUGGUCUGAGAGGAUCAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGCAAGCCUGAUCCAGCCAUGCCGCGUGAGUGAUGAAGGCCUUAGGGUUGUAAAGCUCUUUUGUCCGGGACGA------------UAAU-------------GACGGUACCGGAAGAAUAAGCCCCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAAGGGGGCUAGCGUUGCUCGGAAUCACUGGGCGUAAAGGGCGCGUAGGCGGCUUUUUAAGUCGGGGGUGAAAGCCUGUGGCUCAACCACAGAAUUGCCUUCGAUACUGGAAAGCUUGAGACCGGAAGAGGACAGCGGAACUGCGAGUGUAGAGGUGAAAUUCGUAGAUAUUCGCAAGAACACCAGUGGCGAAGGCGGCUGUCUGGUCCGGUUCUGACGCUGAGGCGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAAUGCCAGCCGUUGGCCUGCUUG-CAGGUCAGUGGCGCCGCUAACGCAUUAAGCAUUCCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGCAGAACCUUACCAUCCCUUGACAUGGCGUG-UACCCAGGGAGACUUGGGAUCCUCUUCGGAGGCGCGCACACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCACGUCCUUAGUUGCCAUCAUUCAG-UUGGGCACUCUAGGGAGACUGCCGGUGAUAAGCCGGAGGAAGGUGUGGAUGACGUCAAGUCCUCAUGGGCCUUACGGGAUGGGCUACACACGUGCUACAAUGGCGGUGACAGUGGGACGCGAAGGAGCGAUCUGGAGCAAAUCCCCAAAA-GCCGUCUCAGUUCGGAUUGCACUCUGCAACUCGGGUGCAUGAAGGCGGAAUCGCUAGUAAUCGUGGAUCAGCAUGCCACGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUUGGUCUUACCCGACGGCGCUGCGCCAACCGCAAGGAGGCAGGCGACCACGGUAGGGUCAGCGACUGGGGUGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
al.Rhi.fre -AACUUGAGAGUUUGAUCCUGGCUCAGAACGAACGCUGGCGGCAGGCUUAACACAUGCAAGUCGAGCGCCCC----------GCAA----------GNNNAGCGGCAGACGGGUGAGUAACGCGUGGGAAUCUACCCUUUUCUACGGAAUAACGCAGGGAAACUUGUGCUAAUACCGUAUGAGCCCUUCGGGGGAAAGA--------UUUA------UCGGGAAAGGAUGAGCCCGCGUUGGAUUAGCUAGUUGGUGGGGUAAAGGCCUACCAAGGCGACGAUCCAUAGCUGGUCUGAGAGGAUGAUCAGCCACAUUGGGACUGAGACACGGCCCAAACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGCAAGCCUGAUCCAGCCAUGCCGCGUGAGUGAUGAAGGCCCUAGGGUUGUAAAGCUCUUUCACCGGUGAAGA------------UAAU-------------GACGGUAACCGGAGAAGAAGCCCCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAAGGGGGCUAGCGUUGUUCGGAAUUACUGGGCGUAAAGCGCACGUAGGCGGACAUUUAAGUCAGGGGUGAAAUCCCGGGGCUCAACCCCGGAACUGCCUUUGAUACUGGGUGUCUAGAGUCCGGAAGAGGUGAGUGGAAUUCCGAGUGUAGAGGUGAAAUUCGUAGAUAUUCGGAGGAACACCAGUGGCGAAGGCGGCUCACUGGUCCGGUACUGACGCUGAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAAUGUUAGCCGUCGGGCAGUUUA-CUGUUCGGUGGCGCACGUAACGCAUUAAACAUUCCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGCAGAACCUUACCAGCCCUUGACAUCCCGAUCGGAUACGAGAGAUCGUAUCCUCAGUUCGCUGGAUCGGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGCCCUUAGUUGCCAGCAUUUAG-UUGGGCACUCUAAGGGGACUGCCGGUGAUAAGCCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUACGGGCUGGGCUACACACGUGCUACAAUGGUGGUGACAGUGGGCAGCGAGACCGCGAGGUCGAGCUAAUCUCCAAAA-GCCAUCUCAGUUCGGAUUGCACUCUGCAACUCGAGUGCAUGAAGUUGGAAUCGCUAGUAAUCGCAGAUCAGCAUGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUUGGUUCUACCCGAAGGUAGUGCGCUAACCGCAAGGAGGCAGCUAACCACGGUAGGGUCAGCGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCGGCUGGAUCACCUCC---
al.Ric.pea -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmGCUUAACACAUGCAAGUCGAACGGACUAAUU---GGGCUUG-CUCCAA-UUAGUUAGUGGCAGACGGGUGAGUAACACGUGGGAAUCUACCCAUCAGUACGGAAUAACUUUUAGAAAUAAAAGCUAAUACCGUAUAUUCUCUGCGGAGGAAAGA--------UUUA------UCGCUGAUGGAUGAGCCCGCGUCAGAUUAGGUAGUUGGUGAGGUAAUGGCUCACCAAGCCGACGAUCUGUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGAAAGCCUGAUCCAGCAAUACCGAGUGAGUGAUGAAGGCCUUAGGGUUGUAAAGCUCUUUUAGCAAGGAAGA------------UAAU-------------GACGUUACUUGCAGAAAAAGCCCCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGGGCUAGCGUUGUUCGGAAUUACUGGGCGUAAAGAGUGCGUAGGCGGUUUCGUAAGUUGGAAGUGAAAGCCCGGGGCUUAACCUCGGAAUUGCUUUCAAAACUACUAAUCUAGAGUGUAGUAGGGGAUGAUGGAAUUCCUAGUGUAGAGGUGAAAUUCUUAGAUAUUAGGAGGAACACCGGUGGCGAAGGCGGUCAUCUGGGCUACAACUGACGCUGAUGCACGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAGUGCUAGAUAUCGGAAGAUUC--UCUUUCGGUUUCGCAGCUAACGCAUUAAGCACUCCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGGCUCGCACAAGCGGUGGAGCAUGCGGUUUAAUUCGAUGUUACGCGAAAAACCUUACCAACCCUUGACAUGGUGGUCGGAUCGCAGAGAUGCUUUUCUCAGCUCGCUGGACCACACACAGGUGUUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCAUUCUUAUUUGCCAGCGGUAAUGCCGGGAACUAUAAGAAAACUGCCGGUGAUAAGCCGGAGGAAGGUGGGGACGACGUCAAGUCAUCAUGGCCCUUACGGGUUGGGCUACACGCGUGCUACAAUGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-mmmm-mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
al.Sph.ter -----mmmmAGUUUGAUCCUGGCUCAGAACGAACGCUGGCGGCAUGCCUAACACAUGCAAGUCGAACGAGAUC---------UUCG---------GAUCUAGUGGCGCACGGGUGCGUAACGCGUGGGAAUCUGCCCUUGGGUUCGGAAUAACUCAGAGAAAUUUGUGCUAAUACCGUAUAAUGUCUUCGGACCAAAGA--------UUUA------UCGCCCAAGGAUGAGCCCGCGUAGGAUUAGCUAGUUGGUGGGGUAAAGGCUCACCAAGGCGACGAUCCAUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGGACAAUGGGCGAAAGCCUGAUCCAGCAAUGCCGCGUGAGUGAUGAAGGCCCUAGGGUUGUAAAGCUCUUUUACCCGGGAUGA------------UAAU-------------GACAGUACCGGGAGAAUAAGCUCCGGCUAACUUCGUGCCAGCAGCCGCGGUAAUACGAGGGGAGCUAGCGUUGUUCGGAAUUACUGGGCGUAAAGCGCGCGUAGGCGGUUUUUUAAGUCAGAGGUGAAAGCCCGGGGCUCAACCCCGGAAUAGCCUUUGAAACUGGAAAGCUAGAAUCUUGGAGAGGUCAGUGGAAUUCCGAGUGUAGAGGUGAAAUUCGUAGAUAUUCGGAAGAACACCAGUUGCGAAGGCGGCUGACUGGACUGGUAUUGACGCUGAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGAUAACUAGCUGUCCGGGCU-AUAGAGCUUGGGUGGCGCACGUAACGCAUUAAGUUAUCCGCCUGGGGAGUACGGCCGCAAGGUUAAAACUCAAAGGAAUUGACGGGGGCCUGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGCAGAACCUUACCAGCGUUUGACAUCCUGAGCGGUUACCAGAGAUGGUUUCCUUAGUUCGCUGGAUAGGUGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCAUCCCUAGUUGCCAUCAUUAAG-UUGGGCACUCUAAGGAAACUGCCGGUGAUAAGCCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUACGCGCUGGGCUACACACGUGCUACAAUGGCGGUGACAGUGGGCAGCAACCUCGCGAGAGGUAGCUAAUCUCCAAAA-GCCGUCUCAGUUCGGAUUGUUCUCUGCAACUCGAGAGCAUGAAGGCGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCAGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUUGGUUUCACCCGAAGGCCCAGAGCCAACCGCACGGAGGAAAGG------UGAAUGCCUAGUUA-UGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
be.Hyd.pal -----mmmmmmmmmmmmmmmmmmmmmmAUUGAACGCUGGCGGCAUGCUUUACACAUGCAAGUCGAACGGUAACAGGCC----GCAA----GGUGCUGACGAGUGGCGAACGGGUGAGUAAUGCAUCGGAACGUGCCCAGUCGUGGGGGAUAACGCAGCGAAAGCUGCGCUAAUACCGCAUACGAUCUAUGGAUGAAAGCGGGGGACCGUAAGGCCUCGCGCGAUUGGAGCGGCCGAUGUCAGAUUAGGUAGUUGGUGGGGUAAAGGCUCACCAAGCCAACGAUCUGUAGCUGGUCUGAGAGGACGACCAGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUGGACAAUGGGCGCMAGCCUGAUCCAGCAAUGCCGCGUGCAGGAAGAAGGCCUUCGGGUUGUAAACUGCUUUUGUACGGAACGAAAAGGCUCUGGUUAAUACCUGGGGCACAUGACGGUACCGUAAGAAUAAGCACCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUGCAAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGUGCGCAGGCGGUUUUGUAAGACAGGCGUGAAAUCCCCGGGCUCAACCUGGGAAUUGCGCUUGUGACUGCAAGGCUGGAGUGCGGCAGAGGGGGAUGGAAUUCCGCGUGUAGCAGUGAAAUGCGUAGAUAUGCGGAGGAACACCGAUGGCGAAGGCAAUCCCCUGGGCCUGCACUGACGCUCAUGCACGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGUCAACUGGUUGUUGGGUCUCUUC-UGACUCAGUAACGAAGCUAACGCGUGAAGUUGACCGCCUGGGGAGUACGGCCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGUGGAUGAUGUGGUUUAAUUCGAUGCAACGCGAAAAACCUUACCCACCUUUGACAUGUACGGAAUUUGCCAGAGAUGGCUUAGUGCUGAAAAGAGCCGUAACACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCAUUAGUUGCUAC---GAAA---GGGCACUCUAAUGAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUAGGUGGGGCUACACACGUCAUACAAUGGCCGGUACAAAGGGUCGCAAACCCGCGAGGGGGAGCUAAUCCAUCAAAGCCGGUCGUAGUCCGGAUCGCAGUCUGCAACUCGACUGCGUGAAGUCGGAAUCGCUAGUAAUCGUGGAUCAGCAUGUCACGGUGAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCAUGGGAGCGGGUCUCGCCAGAAGUAGUUAGCCUAACCGCAAGGAGGGCGAUUACCACGGCGGGGUUCGUGACUGGGGUGGAGUCGUAACAAGGUAGCCGUAUCGGAAGGmmmmmmmmmmmmmmmm-----
be.Nei.fla -AACAUAAGAGUUUGAUCCUGGCUCAGAUUGAACGCUGGCGGCAUGCUUUACACAUGCAAGUCGAACGGCAGCACAGAGAAGCUUGCUUCUUGGGUGGCGAGUGGCGAACGGGUGAGUAAUAUAUCGGAACGUACCGAGUAAUGGGGGAUAACUAAUCGAAAGAUUAGCUAAUACCGCAUAUUCUCUGAGGAGGAAAGCAGGGGACCUUCGGGCCNUGCGUUAUUCGAGCGGCCGAUAUCUGAUUAGUUAGUUGGUGGGGUAAAGGCCUACCAAGGCGACGAUCAGUAGCGGGUCUGAGAGGAUGAUCCGCCACACUGGGACUGAGACACGGCCNNGNCUCCUACGGGAGGCAGCAGUGGGGAAUUUUGGACAAUGGGCGCAAGCCUNAUCCAGCCAUGCCGCGUGUCUGAAGAAGGCCUUCGGGUUGUAAAGGACUUUUGUCAGGGAAGAAAAGGCUGUUGCUAAUAUCGACAGCUGAUGACGGUACCUGAAGAAUAAGCACCGGCUAACUACGUGCCAGCAGCCGCGNNNAUACGUAGGGUGCNAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGAGCGCAGACGGUUACUUAAGCAGGAUGUGAAAU-CCCGGGCUCAACCCGGNNACUGCGUUCUGAACUGGGUAACUAGAGUGUGUCAGAGGGAGGUAGAAUUCCACGUGUAGCAGUGAAAUGCGUAGAGAUGUGGAGGAAUACCGAUGGCGAAGGCAGCCUCCUGGGAUAACACUGACGUUCAUGCUCGAAAGCGUGGGUAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGUCAAUUAGCUGUUGGGCAACUUGAUUGCUUAGUAGCGUAGCUAACGCGUGAAAUUGACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGUGGAUGAUGUGGAUUAAUUCGAUGNAACGCGAAGAACCUUACCUGGUCUUGACAUGUACGGAAUCCUCCGGAGACGGAGGNGUGCCUUCGGGAGCCGUAACACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCRACGAGCGCAACCCUUGUCAUUAGUUGCCAUCAUUUAG-UUGGGCACUCUAAUGAGACUGCCGGUGACAAGCCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUGACCAGGGCUUCACACGUCAUACAAUGGUCGGUACAGAGGGUAGCCAAGCCGCGAGGUGGAGCCAAUCUCACAAAACCGAUCGUAGUCCGGAUUGCACUCUGCAACUCGAGUGCAUGAAGUCGGAAUCGCUAGUAAUCGCAGGUCAGCAUACUGCGGUGAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGGGAUACCAGAAGUAGGUAGGGUAACCGCAAGGAGUCCGCUUACCACGGUAUGCUUCAUGACUGGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
be.Pse.syz -----mmmmmmmmmmmmmmmmmmmmmmmmmmAACGCUGGCGGCAUGCCUUACACAUGCAAGUCGAACGGCAGCGGGGGUAG-CUUG--CUACCUCCGGCGAGUGGCGAACGGGUGAGUAAUACAUCGGAACGUGCCCUGUAGUGGGGGAUAACUA-UCGAAAGACUGGCUAAUACCGCAUACGACCUGAGGGUGAAAGUGGGGC-CCGCAAGGCCUCAUGCUAUAGGAGCGGCCGAUGUCUGAUUAGCUAGUUGGUGGGGUAAAGGCCCACCAAGGCGACGAUCAGUAGCUGGUCUGAGAGGACGAUCAGCCACACUGGGACUGAGAGACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUGGACAAUGGGGGCAACCCUGAUCCAGCAAUGCCGCGUGUGUGAAGAAGGCCUUCGGGUUGUAAAGCACUUUUGUCCGGAAAGAAAUCGCUUCGGUUAAUACCUGGAGUGGAUGACGGUACCGGAAGAAUAAGGACCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUCCAAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGUGCGCAGGCGGUUGUGCAAGACCGAUGUGAAAUCCCCGGGCUUAACCUGGGAAUUGCAUUGGUGACUGCACGGCUAGAGUGUGUCAGAGGGGGGUAGAAUUCCACGUGUAGCAGUGAAAUGCGUAGAGAUGUGGAGGAAUACCGAUGGCGAAGGCAGCCCCCUGGGAUAACACUGACGCUCAUGCACGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGUCAACUAGUUGUUGGGGA-UUCAUUUCCUUAGUAACGUAGCUAACGCGUGAAGUUGACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGUGGAUGAUGUGGAUUAAUUCGAUGCAACGCGAAAAACCUUACCUACCCUUGACAUGCCACUAACGAAGCAGAGAUGCAUUAGUG-UGAAAAGAAAGUGGACACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCUCUAGUUGCUA-C--GAAA---GGGCACUCUAGAGAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUGGGUAGGGCUUCACACGUCAUACAAUGGUGCAUACAGAGGGUUGCCAAGCCGCGAGGUGGAGCUAAUCCCAGAAAAUGCAUCGUAGUCCGGAUCGUAGUCUGCAACUCGACUACGUGAAGCUGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGCUUUACCAGAAGUAGUUAGCCUAACCGCAAGGAGGGCGAUUACCAC-GUAGGGUUCAUGACUGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
be.Rho.pur GAACUGAAGAGUUUGAUCCUGGCUCAGAUUGAACGCUGGCGGCAUGCCUUACACAUGCAAGUCGAACGGUAACGGGNCC---UUCG---GGCGCCGAACGAGUGGCGAACGGGUGAGUAAUGCAUCGGAACAUGCCCUGAAGUGGGGGAUAACGUAGCGAAAGUUACGCUAAUACCGCAUAUUCUGUGAGCAGGAAAGCAGGGGACCUUCGGGCCUUGCGCUUUGGGAGUGGCCGAUGUCGGAUUAGCUAGUUGGUGGGGUAAAAGCCUACCAAGGCAACGAUCCGUAGCGGGUCUGAGAGGAUGAUCCGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUGGACAAUGGGCGAAAGCCUGAUCCAGCCAUGCCGCGUGAGUGAAGAAGGCCUUCGGGUUGUAAAGCUCUUUCGGCGGGGAAGAAAUCGGGUUUCCUAAUACGGAACCCGGAUGACGGUACCCGAAGAAGAAGCACCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUGCNAGCGUUAAUCGGAAUUACUGGGCGUAAAGCGUGCGCAGGCGGUUGUGUAAGACAGACGUGAAAUCCCCGGGCUCAACCUGGGAACUGCGUUUGUGACUGCACAGCUAGAGUACGGCAGAGGGGGGUGGAAUUCCACGUGUAGCAGUGAAAUGCGUAGAGAUGUGGAGGAACACCGAUGGCGAAGGCAGCCCCCUGGGCCAAUACUGACGCUCAUGCACGNAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGUCAACUAGGUGUUGGUGGGGUUAACCCAUUAGUGCCGUAGCUAACGCGUGAAGUUGACCGCCUGGGGAGUACGGCGGCAAGGUUAAAACUCAAAGGAAUUGACGGGGANCCGCACAAGCGGUGGAUGAUGUGGAUUAAUUCGAUGCAACGCGAAAAACCUUACCUACCCUUGACAUGUCAGGAAUCCUGAGGAGACUCGGGAGUGCCGAAAGGNACCUGAACACAGGUGCUGCAUGGCNGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCAUUAAUUGCCAUCAUUCAG-UUGGGCACUUUAAUGAAACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUGGGUAGGGCUUCACACGUCAUACAAUGGUCGGUCCAUAGGGUUGCNAACCCGCGAGGGGGAGCUAAUCCCAGAAAGCCGAUCGUAGUCCGGAUUGCAGUCUGCAACUCGACUGCAUGAAGUCGGAAUCGCUAGUAAUCGCGGAUCAGCAUGUCGCGGUGAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCAUGGGAGCGGGUUCUGCCAGAAGUAGUUAGCCUAACCGCAAGGAGGGCGAUUACCACGGCAGCGUUCGUmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
be.Tha.ter -----mmmmmmmmmmmmmmmmmmmmmmmmmmAACGCUGGCGGCAUGCUUUACACAUGCAAGUCGAACGGCAGCACGGGC---UUCG---GCCUGGUGGCGAGUGGCGAACGGGUGAGUAAUGCAUCGGAACGUGCCCAUUUGUGGGGGAUAACUACGCGAAAGCGUGGCUAAUACCGCAUACGCCCUGAGGGGGAAAGCGGGGGAUUUUCGAACCUCGCGCAAUUGGAGCGGCCGAUGUCAGAUUAGCUUGUUGGUGAGGUAAAGGCUCACCAAGGCGACGAUCUGUAGCGGGUCUGAGAGGAUGAUCCGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUGGACAAUGGGGGCAACCCUGAUCCAGCCAUGCCGCGUGAGUGAAGAAGGCCUUCGGGUUGUAAAGCUCUUUCAGCCGGGAAGAAAACGCACUCUCUAACAUAGGGUGUGGAUGACGGUACCGGAAGAAGAAGCACCGGCUAACUACGUGCCAGCAGCCGCGGUAAUACGUAGGGUGCGAGCGUUAAUCGGAAUUACUGGGCGUAAAGGGUGCGCAGGCGGUUUUGUAAGACAGAUGUGAAAUCCCCGGGCUUAACCUGGGAACUGCGUUUGUGACUGCAAGGCUAGAGUACGGCAGAGGGGGGUGGAAUUCCGCGUGUAGCAGUGAAAUGCGUAGAUAUGCGGAGGAACACCGAUGGCGAAGGCAACCCCCUGGGCCUGUACUGACGCUCAUGCACGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGUCAACUAGUCGUUCGGAGCGCAAUGCACUGAGUGACGCAGCUAACGCGUGAAGUUGACCGCCUGGGGAGUACGGCCGCAAGGUUAAAACUCAAAGGAAUUGACGGGGACCCGCACAAGCGGUGGAUGAUGUGGAUUAAUUCGAUGCAACGCGAAAAACCUUACCUACCCUUGACAUGUCUGGAACCUUGGUGAGAGCCGAGGGUGCCUUCGGGAGCCAGAACACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCAUUAGUUGCCAUCAUUUAG-UUGGGCACUCUAAUGAGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUGGGUAGGGCUUCACACGUCAUACAAUGGUCGGUACAGAGGGUUGCCAAGCCGCGAGGUGGAGCCAAUCCCACAAAGCCGAUCGUAGUCCGGAUCGUAGUCUGCAACUCGACUACGUGAAGUCGGAAUCGCUAGUAAUCGCAGAUCAGCAUGCUGCGGUGAAUACGUUCCCGGGUCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGUUUCACCAGAAGUAGGUAGCUUAACCUUCGGGAGGGCGCUUACCACGGUGAGAUUCAUGACUGGGGUGAAGUCGUAACAAGGUAGCCGUAUCGGAAmmmmmmmmmmmmmmmmmm-----
de.Des.vib -----mmmmmmmmmmmmmmUGGCUCAGAAUGAACGCUGGCGGCGUGCUUAACACAUGCAAGUCGAACGAGAAAGGGAUUG--CUUG-CAAUCCUGAGUAGAGUGGCGCACGGGUGAGUAACACGUAGAAAUCUGUCUCCAAGCCUGGGAUAACUAUUCGAAAGGGUAGCUAAUACCGGAUAAAGUUAUAAAAUGAAAGAUUGCCUCUCNUGAAGCAAUUGUUUGGGGGUGAGUUUGCGUACCAUUAGCUUGUUGGUGGGGUAAAGGCCUACCAAGGCAACGAUGGUUAGCUGGUCUGAGAGGAUGAUCAGUCACACUGGAACUGGAACACGGUCCAGACUCCUACGGGAGGCAGCAGUGAGGAAUUUUGCGCAAUGGGGGCAACCCUGACGCAGCAACGCCGCGUGAGUGAAGAAGGCCUUUGGGUCGUAAAGCUCUGUCAACAGGGAAGAAGUUAUUAUCUAUAAUAGUGGAUACUAUUGACGGUACCUGUGGAGGAAGCGCCGGCUAACUCCGUGCCAGCAGCCGCGGUAACACGGGGGGCGCAAGCGUUAUUCGGAAUUAUUGGGCGUAAAGGGCGCGUAGGCGGUCUUGUCCGUCAGGUGUGAAAGCCCGGGGCUCAACCCCGGAAGUGCACUUGAAACAGCAAGACUUGAAUACGGGAGAGGAAAGCGGAAUUCCUGGUGUAGAGGUGAAAUUCGUAGAUAUCAGGAGGAACACCGAUGGCGAAGGCAGCUUUCUGGACCGAUAUUGACGCUGAGGCGCGAAGGCGUGGGUAGCGAACGGGAUUAGAUACCCCGGUAGUCCACGCAGUAAACGUUGUACACUCGGUGUGGCGGAUAUUAAAUCUGCUGUGCCCAAGCUAACGCAUUAAGUGUACCGCCUGGGAAGUACGGUCGCAAGACUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGACGCAACGCGAAGAACCUUACCUGGGUUUGACAUCCUGUGAAUAUUGGGUAAUUGCCAUAGUGCCUUCGGGAGCACAGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUUGGUUAAGUCCAGCAACGAGCGCAACCCUUAUCGUCAGUUGCCAGCACUAAUGGUGGGAACUCUGGCGAGACUGCCCCGGUCAACGGGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUAUCCAGGGCUACACACGUGCUACAAUGGUAGGUACAAAGGGCAGCGACUCUGCAAAAAGAAGCGAAUCCCAAAA-GCCUAUCUCAGUCCGGAUUGGGGUCUGCAACUCGACCCCAUGAAGUUGGAAUCGCUAGUAAUCGCGGAUCAGCAUGCCGCGGUGAAUAUGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGAAGUUGAUUAUACCCGACGUCGCUGGGCUAACUUUUAAGGGGCAGGCGCCUAAGGUAUGGUCGAUAACUGGGGUGAAGUCGUAACAAGGUAGCCGUUGGAGmmmmmmmmmmmmmmmmmmmm-----
de.Des.ter -----mmmmmmmmmmmmmmmmmmmmmmAUUGAACGCUGGCGGCGUGCCUAACACAUGCAAGUCGUGCGUGAAAGGGC-----UUCG----GCCUGAGUAAAGCGGCGCACGGGUGAGUAACGCGUGGAGAUCUGCCCAUGAGUUGGGAAUAACGGCUGGAAACGGUCGCUAAUACCGAAUACGCUC-CAUGGGGAAAGGUGGCCUCUCUUGAAGCUACCGCUCAUGGAUGAGUCCGCGUCCCAUUAGCUUGUUGGCGGGGUAAUGGCCCACCAAGGCGACGAUGGGUAGCCGACCUGAGAGGGUGAUCGGCCACACUGGGACUGGAACACGGCCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCGCAAUGGGCGAAAGCCUGACGCAGCGACGCCGCGUGAGGGAUGAAGGCCUUCGGGUCGUAAACCUCUGUCAGGAGGGAAGAACCGCCAUGGUGUAAU-CAGCCAUGGUCUGACGGUACCUCCAAAGGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUAAUCGGAAUCACUGGGCGUAAAGCGCACGUAGGCUGUUUGGUAAGUCAGGGGUGAAAUCCCGCAGCUCAACUGCGGGAUUGCCCUUGAUACUGCUGGACUUGAGUUCGGGAGAGGGUGGCGGAAUUCCAGGUGUAGGAGUGAAAUCCGUAGAUAUCUGGAGGAACAUCAGUGGCGAAGGCGGCCACCUGGACCGAUACUGACGCUGAGGUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCUGUAAACGAUGGAUGCUAGGUGUCGGGGC-CUUG-AGCUUCGGUNCCGCAGCUAACGCGUNAAGCAUCCCGCCUGGGGAGUACGGUCGNNAGGNUGAAACUCAAAGAAAUUGACGGGNNCCCGCACAAGC-GUGGAGUAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCCAGGCUUGACAUCCGGGAAACCCUCCCGAAAAGGAGGGGUGCUUUCGAGAAUCCCGAGACAGGUGCUGCNUGGNUGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUGUUCAUAGUUGCUACCAGUAAUGCUGGGCACUCUAUGGAGNNNNCCCCGGUUAACGGGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGGCCCUUACNNCUNNGGCUACACACGUACUACAAUGGCGCACACAAAGGGCAGCGAUACCGUGAGGUGGAGCCAAUCCCAAAAAAUGCGUCCCAGUCCGGAUUGCAGUCUGCAACUCGACUGCAUGAAGUUGGAAUCGCUAGUAAUUCGAGAUCAGCAUGCUCGGGUGAAUGCGUUCCCGGGCCUUGUACACACCGCCCGUCACACCACGAAAGUCGGUUUUACCCGAUACCGGUGAGCCAACCGCAAGGAGGCAGCCGUCUACGGUAGGGCCGAUGAUUGGGGUGAAGUCGUAACNNNGUAGCCGUAGGGGAACCUGCGGCUmmmmmmmmm-----
de.Des.suc -----mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmGUAUGCCUAACACAUGCAAGUCGAACGCGAACGGAAUC---UUCG--GAUUCCNAGUAGAGUGGCGCACGGGUGAGUAACACGUGGAAACCUGCCCUAGAGUCUGGGAUAACACUCCGAAAGGAGUGCUAAUACCGGAUAAGACCCUCGGGGAAAAGA--------UUUA------UUGCUCUAGGAUGGGUCCGCGGUCCAUUAGCUAGUUGGUGGGGUAAUGGCCUACCAAGGCUGCGAUGGAUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUUUUGCGCAAUGGGCGAAAGCCUGACGCAGCAAUACCGCGUGAAGGAUGAAGGCCCUUGGGUCGUAAACUUCUGUCAGAGGGGAAGAAAUACUC-----GCAA------GAGUGCUGACGGUACCCUCAAAGGAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUGUUCGGAAUUAUUGGGCGUAAAGAGCAUGUAGGCGGUCUGUUAAGUCUGGUGUGAAAGCCCGGGGCUCAACCCCGGAAGUGCAUUGGAUACUGGC-GACUUGAGUAUGGGAGAGGAAAGUGGAAUUCCGAGUGUAGGAGUGAAAUCCGUAGAUAUUCGGAGGAACACCAGUGGCGAAGGCGGCUUUCUGGACCAAUACUGACGCUGAGAUGCGAAAGCGUGGGGAGCGAACAGGAUUAGAUACCCUGGUAGUCCACGCCGUAAACGAUGGGUACUAGGUGUUGCGGGUAACCCUCCUGCAGUGCCGCAGCUAACGCAUUAAGUACCCCGCCUGGGGAGUACGGCCGCAAGGCUAAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGACGCAACGCGAAGAACCUUACCUAGGCUUGACAUCCCGAUCACUCUAUGGAAAAAUAGAGGUCAGCUUGCUGGAUCGGUGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUGUCCUUAGUUGCCAUCAUUAAG-UUGGGCACUCUAGGGAGACUGCCGGUGUUAAACCGGAGGAAGGUGGGGAUGACGUCAAGUCCUCAUGGCCCUUAUGCCUAGGGCUACACACGUGCUACAAUGGCCGGUACAAAGGGCAGCAAUACCGCGAGGUGGAGCGAAUCCCAAAAAGCCGGUCUCAGUUCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUUGGAAUCGCUAGUAAUCGCGUAUCAGCAUGACGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCACGGGAGUCUAUUGUACCGGAAACCGGUGGGCUAACCUUCGGGGAGCAGCCGUUUAUGGUAUGAUCGGUAACUGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ep.Alv.pom -----mmAGAGUUUGAUCAUGGCUCAGAGUGAACGCUGGCGGCGUGCUUAACACAUGCAAGUCGAACGGUAACAGGUC----UUCG---GAGUGCUGACGAGUGGCGAACGGGUGAGUAAUGUAUAGUAAUUUUCCCCUUGGAGAGGGAUAGCCACUGGAAACGGUGAUUAAUACCUCAUACUCCUAAAAAGGGAAAGG--------UUUA----UUCUGCCAAGGGAUAAGACUAUAUCCUAUCAGCUAGUUGGUAGUGUAAGGGACUACCAAGGCAAUGACGGGUAGCUGGUCUGAGAGGAUGAUCAGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACAAUGGGGGAAACCCUGAUGCAGCAACGCCGCGUGGAGGAAGAAGCAUUUAGGUGUGUAAACUCCUUUUAUCAAGGAAGAA-----------GA-C-------------GACGGUACUUGAUGAAUAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUACUCGGAAUCACUGGGCGUAAAGCGCAUGUAGGCGGUUGAUUAAGUUAGAAGUGAAAGCCUACGGCUCAACCGUAGAACAGCUUCUAAAACUGAUUAACUAGAGUCUGGGAGAGGAAGAUGGAAUUAGUAGUGUAGGGGUAAAAUCCGUAGAGAUUACUAGGAAUACCGAAAGCGAAGGCGAUCUUCUGGAACAGGACUGACGCUGAGAUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGAAUGUUAGUCGUUGGAGUGCUAGCCACUUCAGCGAUGCAGCUAACGCAUUAAACAUUCCGCCUGGGGAGUACGSCCGCAAGGUUAAAACUCAAAGGAAUAGACGGGGACCCGCACAAGUGGUGGAGCAUGUGGUUUAAUUCGAAGAUACGCGAAGAACCUUACCUGGCCUUGACAUAAUCAGAACCCACCAGAGAUGGUGGGGUGCCUUCGGGAGCUGAUAUACAGGUGCUGCACGGCUGUCGUCAGCUCGUGUCGUGUGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUGACUAGUUACUAACAGUUAGGCUGAGGACUCUAGUCAGACUGCCUUCG-UAAGGAGGAGGAAGGUAAGGACGACGUCAAGUCAUCAUGGCCCUUACGGCCAGGGCGACACACGUGCUACAAUGGGAAGGACAAAGAGAAGCAAAACUGCGAGGUGGAGYAAAUCU-AUAAACCUUCUCUCAGUUCGGAUUGCAGUCUGCAACUCGACUGCAUGAAGCUGGAAUCACUAGUAAUCGUGAAUCAGCCUGUCACGGUGAAUACGUUCCCGGGUCUUGUACUCACCGCCCGUCACACCAUGGGAGUUGAUUUCACCCGAAGUGGGGAUGCUA---AAUA---GGCUACCCACCACGGUGGAAUUAGCGACUGGGGUGAAGUCGUAACAAGGUAACCGUAGGAGAACCUGCGGCUGGAUCACCUCCUUA
ep.Cam.fet -UUAUGGAGAGUUUGAUCCUGGCUCAGAGUGAACGCNGGCGGCGUGCCUAAUACAUGCAAGUCGAACGGAGUAUUAAGAGAGCUUGNU--NUUAAUACNUAGUGGCGCACGGGUGAGUAAUGUAUAGUAAUCUGCCCUACACUGGAGGACAACAGUUAGAAAUGACUGCUAAUACUCCAUACUCCUAUAACGGGAAAG---------UNUU------UCGGUGUAGGAUGAGACUAUAUUGUAUCAGCUAGUUGGUAAGGUAAUGGCUUACCAAGGCUNUGACGCAUAACUGGUCUGAGAGGAUGAUCAGUCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUAUUGCUCAAUGGGGGAAACCCUGAAGCAGCAACGCCGCGUGGAGGAUGACACUUUUCGGAGCGUAAACUCCNUUUGUUAGGGAAGAA-----------CCAU-------------GACGGUACCUAACGAAUAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCNAGCGUUACUCGGAAUCACUGGGCGUAAAGGACGCGUAGGCGGAUUAUCAAGUCUUUUGUGAAAUCUAACAGCUAAACUGUUAAACUGCUUGAGAAACUGAUAAUCUAGAGUGAGGGAGAGGCAGAUGGAAUUGGUGGUGUAGGGGUAAAAUCCGUAGAGAUCACCAGGAAUACCCAUUGCGAAGGCGAUCUGCUGGAACUCAACUGACGCUAAUGCGUGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCUCUAAACGAUGUAUACUAGUUGUUGCUGUGCUAGUCACGGCAGUAAUGCACCUAACGGAUUAAGUAUACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUAGACGGGGACCCGCACAAGCGGUGGAGNNNGUGGUUUAAUUCGANNNUACGCGAAGAACCUUACCUGGGCUUGAUAUCCAACUAAUCUCUUAGAGAUAAGAGAGUGCUCUUGAGAAAGUUGAGACAGGUGCUGCACGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCACGUAUUUAGUUGCUAACAGUUCGGCUGAGCACUCUAAAUAGACUGCCUUCG-CAAGGAGGAGGAAGGUGUGGACGACGUCAAGUCAUCAUGGCCCUUAUGCCCAGGGCGACACACGUGCUACAAUGGCAUAUACAAUGAGAUGCAAUAUCGCGAGAUGGAGCAAAUCUAUAAA-AUAUGUCCCAGUUCGGAUUGGAGUCUGCAACUCGACUCCAUGAAGCCGGAAUCGCUAGUAAUCGUAGAUCAGCCUGCUACGGUGAAUACGUUCCCGGGUCUUGUACUCACCGCCCGUCACACCAUGGGAGUUGAUUUCACUCGAAGUCGGAAUGCUA---AAC---UAGCUACCGCCCACAGUGGAAUCAGCGACUGGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ep.Cam.lar -UUAUGGAGAGUUUGAUCCUGGCUCAGAGUGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGNACGAUGAAGCGA-CUAGCUUGAG---UUGUGGAUUAGUGGCGCACGGGUGAGUAAGGUAUAGUAAUCUGCCCUACACAAGAGGACAACAGUUGGAAACGACUGCUNAUACUCUAUACUCCUACAAAGGGAAAG---------UUUU------UCGGUGUAGGAUGAGACUAUAUAGUAUCAGCUAGUUGGUGAGGUAAUGGCUCACCAAGGCUNUGACGCUUAACUGGUCUGAGAGGAUGAUCAGUCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUAUUGCGCAAUGGGGGAAACCCUGACGCAGCAACGCCGCGUGGAGGAUGACACUUUUCGGAGCGUAAACUCCUUUUCUUAGGGAAGAA-----------UUCU-------------GACGGUACCUAAGGAAUAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCNAGCGUUACUCGGAAUCACUGGGCGUAAAGGGCGCGUAGGCGGAUUAUCAAGUCUCUUGUGAAAUCCAACGGCUUAACCGUUGAACUGCUUGGGAAACUGGUAAUCUAGAGUGGGGGAGAGGCAGAUGGAAUUGGUGGUGUAGGGGUAAAAUCCGUAGAUAUCACCAAGAAUACCCAUUGCGAAGGCGAUCUGCUGGAACUUAACUGACGCUAAGGCGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGUAUGCUAGUUGUUGGGGUGCUAGUCAUCUCAGUAAUGCAGCUAACGCAUUAAGCAUACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUAGACGGGGACCCGCACAAGCGGUGGAGCAUGUGGUUUNAUNCGAAGAUACGCGAAGAACCUUACCUGGGCUUGAUAUCCUAAGAACCUUAUAGAGAUAUGAGGGUGCUCUUGAGAACUUAGAGACAGGUGCUGCACGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCACGUAUUUAGUUGCUAACACUUCGGGUGAGCACUCUAAAUAGACUGCCUUCG-UAAGGAGGAGGAAGGUGUGGACGACGUCAAGUCAUCAUGGCCCUUAUGCCCAGGGCGACACACGUGCUACAAUGGCAUAUACAAUGAGACGCAAUACCGCGAGGUGGAGCAAAUCUAUAAA-AUAUGUCCCAGUUCGGAUUGUUCUCUGCAACUCGAGAGCAUGAAGCCGGAAUCGCUAGUAAUCGUAGAUCAGCCUGCUACGGUGAAUACGUUCCCGGGUCUUGUACUCACCGCCCGUCACACCAUGGGAGUUGAUUUCACUCGAAGCCGGAAUACUA---AAC---UAGUUACCGUCCACAGUGGAAUCAGCGACUGGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ep.Hel.pyl UUUAUGGAGAGUUUGAUCCUGGCUCAGAGUGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAACGAUGAAGCUU-CUAGCUUGAG--AGUGCUGAUUAGUGGCGCACGGGUGAGUAACGCAUAGGCAUGUGCCUCUUAGUUUGGGAUAGCCAUUGGAAACGAUGAUUAAUACCAGAUACUCC-UACGGGGGAAAGA--------UUUA------UCGCUAAGAGAUCAGCCUAUGUCCUAUCAGCUUGUUGGUAAGGUAAUGGCUUACCAAGGCUAUGACGGGUAUCCGGCCUGAGAGGGUGAACGGACACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUAUUGCUCAAUGGGGGAAACCCUGAAGCAGCAACGCCGCGUGGAGGAUGAAGGUUUUAGGAUUGUAAACUCCUUUUGUUAGAGAAGA------------UAAU-------------GACGGUAUCUAACGAAUAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUACUCGGAAUCACUGGGCGUAAAGAGCGCGUAGGCGGGAUAGUCAGUCAGGUGUGAAAUCCUAUGGCUUAACCAUAGAACUGCAUUUGAAACUACUAUUCUAGAGUGUGGGAGAGGUAGGUGGAAUUCUUGGUGUAGGGGUAAAAUCCGUAGAGAUCAAGAGGAAUACUCAUUGCGAAGGCGACCUGCUGGAACAUUACUGACGCUGAUGCGCUAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGGAUGCUAGUUGUUGGAGGGUUAGUCUCUCCAGUAAUGCAGCUAACGCAUUAAGCAUCCCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUAGACGGGGACCCGCACAAGCGGUGGAGCANGUGGUUUAAUUCGANNNNACACGAAGAACCUUACCUAGGCUUGACAUUGAGAGAAUCCGCUAGAAAUAGUGGAGGUCUCUUGAGACCUUGAAAACAGGUGCUGCACGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCNUUUCUUAGUUGCUAACAGUUAUGCUGAGAACUCUAAGGAUACUGCCUCCG-UAAGGAGGAGGAAGGUGGGGACGACGUCAAGUCAUCAUGGCCCUUACGCCUAGGGCUACACACGUGCUACAAUGGGGUGCACAAAGAGAAGCAAUACUGUGAAGUGGAGCCAAUCUUCAAA-ACACCUCUCAGUUCGGAUUGUAGGCUGCAACUCGCCUGCAUGAAGCUGGAAUCGCUAGUAAUCGCAAAUCAGCCUGUUGCGGUGAAUACGUUCCCGGGUCUUGUACUCACCGCCCGUCACACCAUGGGAGUUGUGUUUGCCUUAAGUCAGGAUGCUA---AAU---UGGCUACUGCCCACGGCACACACAGCGACUGGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
ep.Hel.tro -----mmmmmmmmmmmmmmmmmmUCAGAGUGAACGCUGGCGGCGUGCCUAAUACAUGCAAGUCGAACGAUGAAGCUU-UUAGCUUGAG---AAGUGGAUUAGUGGCGCACGGGUGAGUAAUGCAUAGGAACAUGCCCCAUAGUCUGGGAUAGCCACUGGAAACGGUGAUUAAUACCGGAUACUCCUUACGAGGGAAAG---------UUUU------UCGCUAUGGGAUUGGCCUAUGUCCUAUCAGCUUGUUGGUGAGGUAAUGGCUCACCAAGGCUAUGACGGGUAUCCGGCCUGAGAGGGUGAUCGGACACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUAGGGAAUAUUGCUCAAUGGGCGAAAGCCUGAAGCAGCAACGCCGCGUGGAGGAUGAAGGUUUUAGGAUUGUAAACUCCUUUUCUAAGAGAAGA------------UUAU-------------GACGGUAUCUUAGGAAUAAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCAAGCGUUACUCGGAAUCACUGGGCGUAAAGAGCGCGUAGGCGGGGUAAUAAGUCAGAUGUGAAAUCCUGUAGCUUAACUACAGAACUGCAUUUGAAACUGUUAUUCUAGAGUGUGGGAGAGGUAGGUGGAAUUCUUGGUGUAGGGGUAAAAUCCGUAGAGAUCAAGAGGAAUACUCAUUGCGAAGGCGACCUGCUGGAACAUUACUGACGCUGAUGCGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGAUGAAUGCUAGUUGUUGCCCUGCUUGUCAGGGCAGUAAUGCAGCUAACGCAUUAAGCAUUCCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAGGAAUAGACGGGGACCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGAUACGCGAAGAACCUUACCUAGGCUUGACAUUGAUAGAAUCUGCUAGAGAUAGCGGAGUGCCUUCGGGAGCUUGAAAACAGGUGCUGCACGGCUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUCGUCCUUAGUUGCUAGCAGUUCGGCUGAGCACUCUAAGGAGACUGCCUUCG-UAAGGAGGAGGAAGGUGAGGACGACGUCAAGUCAUCAUGGCCCUUACGCCUAGGGCUACACACGUGCUACAAUGGGGCGCACAAAGAGGAGCAAUAUCGUGAGAUGGAGCAAAUCUCAAAA-ACGUCUCUCAGUUCGGAUUGUAGUCUGCAACUCGACUACAUAAAGCUGGAAUCGCUAGUAAUCGCAAAUCAGCAUGUUGCGGUGAAUACGUUCCCGGGUCUUGUACUCACCGCCCGUCACACCAUGGGAGUUGUAUUCGCCUUAAGUCGGAAUGCCA---AAC---UGGCUACCGCCCACGGCGGAUGCAGCGACUGGGGUGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
un.Aer.mar -----mmmmmmmmmmmmmmUGGCUCAGGACGAACGCUGGCGGCGUGCCUAAGACAUGCAAGUCGAGCGGGGAGAUUGGGGAGCUUGCUCUCUGGUCUCCUAGCGGCGGACGGGUGAGUAACACGUGGGAACCUGCCCGGCAGUGGGGGAUAACCCUGGGAAACUGGGGCUAAUACCGCAUACGGUCGCAUGAAGAAAGGCCGUC---GUGA-GGCGGUCGCUGCCGGAGGGGCCCGCGGCCCAUCAGCUCGUUGGUGGGGUAACGGCCCACCAAGGCGACGACGGGUAGCCGGCCUGAGAGGGUGGUCGGCCACACUGGGACUGAGACACGGCCCAGACUCCUACGGGAGGCAGCAGUCGGGAAUCUUGCGCAAUGGGCGAAAGCCUGACGCAGCGACGCCGCGUGGGGGAGGAAGCCCUUCGGGGUGUAAACCCCUGUCGUCCGGGACGAAGGUGGGGGG-UGAAA--GGCCCUCUGCUGACGGUACCGGAGGAGGAAGCCCCGGCUAACUACNUGCCAGCAGCCGCGGUAAGACGUAGGGGGCGAGCGUUGUCCGGAAUCACUGGGCGUAAAGGGCGCGUAGGCGGCCUGGCAAGUCGGAUGUGAAAGGUCCCGGCUCAACCGGGGAGGUGCAUUCGAAACUGCCGGGCUUGAGGGCAGGAGAGGGCAGCGGAAUUCCCGGUGGAGCGGUGAAAUGCGUAGAGAUCGGGAGGAACACCAGUGGCGAAGGCGGCUGCCUGGCCUGGCCCUGACGCUGAGGCGCGACAGCGUGGGGAGCGAACGGGAUUAGAUACCCCGGUAGUCCACGCCGUAAACGAUGGGUGCUAGGUGUGGGAGGUUCGACCCCUUCCGUGCCGGAGCUAACGCACUAAGCACCCCGCCUGGGGAGUACGGCCGCAAGGCUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAAGCAACGCGAAGAACCUUACCUGGGCUUGACAUCCCGCGAACCUGGCCGAAAGGCUGGGGUGCCUUCGGGAGCGCGGUGACAGGUGCUGCAUGGUUGUCGUCAGCUCGUGUCGUGAGAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCCGCCCUGUGUUGCCAGCGGUACGGCCGGGCACUCACAGGGGACUGCCGGUGACAAACCGGAGGAAGGUGGGGAUGACGUCAAAUCAUCAUGGCCCUUAUGCCCAGGGCUACACACGUGCUACAAUGGCCGGUACAACGGGUUGCGAACCCGCGAGGGGGAGCCAAUCCCUAAAAGCCGGUCUCAGUUCGGAUCGCAGGCUGCAACUCGCCUGCGUGAAGCCGGAAUCGCUAGUAAUCGCGGAUCAGAAUGCCGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCACGGGAGCCGGCAACACCCGAAGCCGGUGGCCCAACCGUAAGGAGGGAGCCGUCGAAGGUGGGGCCGGUGACUGGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
un.Fle.sin UGGAUGGAGAGUUUGAUCCUGGCUCAGAACGAACGCUGGCGGCGUGCUUAACACAUGCAAGUCAGGGGGAAUCCUCCC----UUCG--GGGAGGUAGUACNCCGGCGCACGGGUGAGUAACGCGUGAGGACCUACCCAUUAGACCUGGAUAACCCGGCGAAAGUUGGGCUAAGACAGGAUGUGUUAUCAUUGAUAAAGCAGGU----UUCG--GCUUGUGCUAAUGGAUGGGCUCGCGUCUGAUUAGCUAGUUGGUAAGGUAAAGGCUUACCAAGGCGACGAUCAUUAGGCGGCCUGAGAGGGUGGUCGCCCACACUGGAACUGAGACACGGUCCAGNCUCCUACGGGAGGCAGCAGUGGGGAAUUUUGCGCAAUGGGCGAGAGCCUGACGCAGCGACGCCGCGUGGACGAGGAAGGCCUUCGGGUCGUAAAGUCCNUUUUUACGGGAAGAAAGUUAUUAACAUAAC-UGGUUAAUAUUUGACGGUACCGUAAGAAUAAGCCCCGGCUAACUCCGUGCCAGCAGCCGNNNUNAUACGGAGGGGGCNAGCGUUGUUCGGAAUUACUGGGCGUAAAGCGUACGUAGGCGGCGUGGUAAGUCGGAGGUUAAAGGCUACGGCUNAACCGUAGUAGGGCNUUUGAUACUAUCAUGCUAGAGUGUCGGAGGGGGNAGCGGAAUUCCCUGUGUAGCGGUGAAAUGCGUAGAUAUAGGGAAGAACNCCAGUAGCGAAGGCGGCUACCUGGCCGAUCACUGACGCUGAGGUACGAGAGCGUGGGUAGCAAACAGGAUUAGAUACCCUGGUAGUCCACGCUGUAAACGAUGGACGCUAGGUGUUGGAGGAACCGCCCCUUCAGUGCCGAAGCCAACGCGUUAAGCGUCCNGCCUGGGGAGUACGACCGCAAGGUUAAAACUCAAAGGAAUUGACGGGGGCCNGCACAAGCGGUGGAGCACGUNGUUUAAUUCGAUGNUAACCGAAGAACCUUACCUGGUCUUGACAUCCUCCGGAGGGACUAGAGAUAGUUCUGNUGCNUNGGNAGCGGAGAGACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCCUAUUCAUAGUUGCCAUCGGUAAGGCCGGGCACUCUAUGGAUACUGCCCGUGAUAAACGGGAGGAAGGUGGGGACGACGUCAAGUCAUCAUGGCCUUUAUGACCAGGGCUACACACGUGCUACAAUGGUACGUACAGAGGGCAGCGAAGCCGCGAGGUGNAGCGAAUCCCUAAAAGCGUGCCUUAGUUCGGAUUGUAGUCUGCAAUUCGACUACAUGAAGGCGGAAUCGCUAGUAAUCGCAGGUCAGCAAACUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCNCNUCACACCACGGGAGUUAGUUGUACCUGAAGCCGGUGGCCCAAC-UGCG-GAGGGAGCCGNUUAUGGUAUGACUGGCAACNGGGGmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm-----
un.Mag.bav -----mmAGAGUUUGAUUUUGGCUCAGAGCGAACGCUGGCGGCGUGCCUAACACAUGCAAGUCGAACGGAUCAUGAGUC---GCAA---GAUUCAUGGUUAGUGGCGCACGGGUGAGUAACGCGUAGGAAUCUGCCUUCAGGACCGGAACAACCAUUGGAAACGAUGGCUAAUCCCGGAUAAGACCGCAAGGUAAAAGGA-------GCAA-----UUCACCUGGAGAUGAGCCUGCGUCCUAUCAGGUAGUUGGUAAGGUAACGGCUUACCAAGCCUAAGACGGGUAGCCGGUCUGAGGGGAUGAACGGCCACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGAGGAAUUUUGCGCAAUGGGGGAAACCCUGACGCAGCGACGCCGCGUGGAGGAAGAAGGCCUUCGGGUUGUAAACUCCUUUUGUAGGGAAAGA------------UGAU-------------GACGGUACCUUACGAAUAAGCCACGGCUAACUCUGUGCCAGCAGCCGCGGUAAGACAGAGGUGGCAAGCGUUGCUCGGAAUUACUGGGCUUAAAGGGUGCGUAGGCGGUUAGAUAAGUUUGGGGUGGAAUGCUCGGGCUCAACCCGGGAAUUGCCUUGAAAACUGUUUAACUUGAGUAAGCGAGGGGAUGGCGGAAUUCCUGGUGUAGCGGUGAAAUGCGUAGAUAUCAGGAGGAAGGCCGGUGGCGAAGGCGGCCAUCAGGCGCUUAACUGACGCUGAGGCACGAAAGCGUGGGGAUCAAACAGGAUUAGAUACCCUGGUAGUCCACGCCCUAAACGGUGGGUACUAGGUAUAGGGCUCGAUA-GGGUUCUGUGCCGAAGGGAAACCAAUAAGUACCCCGCCUGGGAAGUACGGCCGCAAGGUUGAAACUCAAAGGAAUUGACGGGGGCCCGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGACGCAACGCGAGGAACCUUACCUGGGUUUGACAUGAAGUGUAGGAGUCCGAAAGGAUAACGCUCCGCAAGGAGAGCUUGCACAGGUGCUGCAUGGCUGUCGUCAGCUCGUGCCGUGAGGUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUAUUCUCUGUUGCCAUCGGUAAAGCCGGGCGCUCUGAGAAAACUGCCGGCGAUGAGUUGGAGGAAGGUGGGGAUGACGUCAAGUCAUCAUGGCCCUUAUGUCCAGGGCUACACACGUGCUACAAUGGCUAUUACAGAGGGAAGCAAGAUCGCGAGGUGGAGCAAAUCCC-UAAAAAUAGUCUUAGUUGGGAUCGGAGUCUGCAACUCGACUCCGUGAACGUGGAAUCGCUAGUAAUCGCAGAUCACUACGCUGCGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCACGAAAGUCUGCUGUACCCGAAGCGGGUGAGCUAACCGCAAGGAGGCAGCUCACGAAGGUAUGGUAGGUGAUUGGGGUGAAGUCGUAACAAGGUAGCCGUAGGGGAACCUGCGGCUGGAUCACCUCCUUU
"""
sample_tree = """((((ch.Cya.cal:0.01909,ch.Cya.par:0.00974):0.00562,((ch.Eug.gra:0.03679,ch.Chl.mir:0.03448):0.00792,(ch.Pin.thu:0.00289,(((ch.Pis.sat:0.00728,ch.Gly.max:0.00560):0.00207,(ch.Nic.tab:0.00032,ch.Dau.car:0.00404):0.00191):0.00189,ch.Zea.may:0.00644):0.00207):0.00992):0.00674):0.00976,(((al.Aci.cry:0.02022,(al.Met.rho:0.01428,((al.Sph.ter:0.01856,al.Rhi.fre:0.01560):0.00577,(al.Ric.pea:0.03909,ga.Oce.pus:0.02219):0.00897):0.00740):0.00884):0.01161,(((be.Rho.pur:0.01507,be.Nei.fla:0.01667):0.00857,(be.Tha.ter:0.01119,(be.Pse.syz:0.01745,be.Hyd.pal:0.01564):0.00716):0.00536):0.01090,(ga.Xan.pis:0.01723,(ga.Pse.asp:0.01325,(ga.Leg.lyt:0.02104,(ga.Mar.psy:0.01684,((ga.Pho.pho:0.01267,ga.Hae.par:0.02272):0.00386,(ga.Vib.cho:0.01167,(ga.Sal.typ:0.00374,ga.Esc.col:0.00568):0.00939):0.00726):0.00652):0.01339):0.00892):0.00829):0.00892):0.01675):0.00927,((((de.Des.suc:0.02147,(de.Des.ter:0.02837,de.Des.vib:0.02735):0.01258):0.01172,(ra.Dei.rad:0.01597,ra.Dei.mur:0.01346):0.02678):0.00841,(((lo.Eub.lac:0.03050,sp.Lep.mey:0.03062):0.01102,((((lo.Lac.car:0.00581,lo.Car.mob:0.01332):0.01048,(lo.Sta.hom:0.01349,lo.Bac.sub:0.01148):0.01015):0.00661,lo.Bac.alc:0.01312):0.01687,((hi.Bif.inf:0.02108,((((hi.Myc.int:0.00581,hi.Myc.cel:0.00922):0.00960,hi.Cor.oti:0.01993):0.00689,(hi.Mic.par:0.01467,(hi.Mic.ech:0.00986,(hi.Noc.fla:0.01240,(hi.Str.rim:0.01912,hi.Cel.cel:0.01370):0.00521):0.00437):0.00594):0.00601):0.01040,hi.Act.eur:0.02348):0.00923):0.01618,((un.Fle.sin:0.03037,(((th.The.sub:0.01159,th.The.hyp:0.01299):0.01239,th.The.afr:0.02464):0.02101,(sp.Tre.suc:0.02298,sp.Tre.soc:0.02704):0.02202):0.01363):0.01096,(un.Aer.mar:0.01630,(((pt.Pla.mar:0.01738,pt.Pla.bra:0.02107):0.03072,pt.Iso.pal:0.03183):0.02494,gr.The.ros:0.03608):0.01201):0.01061):0.00862):0.01055):0.00806):0.00855,(((lo.Spi.cit:0.02091,(lo.Myc.myc:0.00530,lo.Myc.cap:0.00444):0.01268):0.01693,lo.Ach.lai:0.02594):0.01425,((fu.Lep.mic:0.01902,fu.Lep.buc:0.01886):0.01380,(fu.Fus.nul:0.01817,fu.Fus.gon:0.01127):0.01341):0.01792):0.00949):0.00816):0.00698,(((un.Mag.bav:0.02918,sp.Bor.par:0.03882):0.01142,((fl.Fla.xan:0.01205,(fl.Mar.psy:0.01497,fl.Cyt.mar:0.01590):0.00762):0.01329,(fl.Pre.eno:0.03031,fl.Bac.spl:0.02532):0.01223):0.02551):0.01015,((((ep.Hel.tro:0.01074,ep.Hel.pyl:0.01136):0.01095,(ep.Cam.lar:0.00615,ep.Cam.fet:0.00894):0.01470):0.01449,ep.Alv.pom:0.01917):0.01597,(((mt.Gly.max:0.02673,mt.Zea.may:0.02336):0.10722,((mt.Tet.pyr:0.10091,mt.Sac.cer:0.10584):0.04143,(((mt.Hom.sap:0.01752,(mt.Mus.mus:0.02097,mt.Bos.tau:0.01663):0.01043):0.01436,mt.Gal.gal:0.02956):0.02679,mt.Dro.mel:0.05506):0.07927):0.04096):0.05555,((ar.Met.ore:0.02764,((ar.Hal.sac:0.01549,(ar.Nat.mag:0.01515,ar.Hal.val:0.01643):0.00712):0.02421,(ar.Met.fer:0.01448,((ar.The.ste:0.00873,ar.The.chi:0.00962):0.01420,(ar.Met.jan:0.01611,(ar.The.pen:0.01914,ar.Sul.sol:0.02566):0.02002):0.00655):0.00998):0.01266):0.01176):0.03812,(pr.Try.equ:0.13823,((pr.Tet.bor:0.03717,pr.Cyc.gla:0.02400):0.01721,((pr.Pla.mal:0.11785,pr.Sar.neu:0.02921):0.01926,(pr.Por.aca:0.03748,((pr.Rho.sal:0.02632,(pr.Bla.hom:0.03851,pr.Mal.mat:0.03042):0.01478):0.00979,(((fu.Gig.mar:0.01786,((fu.Den.sul:0.00925,(fu.Fel.oga:0.00867,fu.Bul.hui:0.00910):0.00830):0.00765,(((fu.Sac.cer:0.00875,fu.Can.gla:0.00407):0.01253,(fu.Neu.cra:0.01565,(fu.Asp.tam:0.00163,fu.Asp.nid:0.00344):0.01020):0.00840):0.00546,fu.Sch.pom:0.01836):0.00563):0.00700):0.00993,((an.Bra.pli:0.02731,an.Cae.ele:0.06299):0.01757,(((an.Str.int:0.01379,an.Ast.amu:0.01332):0.01183,((((an.Rat.nor:0.00272,an.Mus.mus:0.00282):0.00216,an.Hom.sap:0.00628):0.01405,an.Xen.lae:0.00769):0.00993,an.Lam.aep:0.01238):0.01437):0.01557,an.Dro.mel:0.06939):0.01211):0.01858):0.00917,(pr.Sti.hel:0.02282,(((pl.Tai.cry:0.00186,pl.Pin.luc:0.00267):0.00699,pl.Gin.bil:0.00367):0.00467,((pl.Ara.tha:0.00614,((pl.Pis.sat:0.00081,pl.Gly.max:0.00234):0.00290,((pl.Sol.tub:0.00344,pl.Lyc.esc:0.00378):0.00372,pl.Pan.gin:0.00361):0.00180):0.00148):0.00251,pl.Zea.may:0.01435):0.00597):0.01283):0.01173):0.00837):0.01080):0.01141):0.01545):0.04435):0.08751):0.03645):0.02229):0.00860):0.00878):0.00657):0.01503):0.00749,(cy.Pho.amb:0.01236,(cy.Tri.ten:0.01069,cy.Osc.aga:0.01588):0.00501):0.00887,cy.Mic.aer:0.03275);
"""
sample_species_names = """cy.Mic.aer
cy.Osc.aga
cy.Pho.amb
cy.Tri.ten
pl.Zea.may
pl.Pan.gin
pl.Ara.tha
pl.Gly.max
pl.Pis.sat
pl.Lyc.esc
pl.Sol.tub
pl.Gin.bil
pl.Pin.luc
pl.Tai.cry
pr.Sar.neu
pr.Pla.mal
pr.Sti.hel
pr.Mal.mat
pr.Cyc.gla
pr.Tet.bor
pr.Rho.sal
pr.Por.aca
pr.Bla.hom
pr.Try.equ
an.Dro.mel
an.Lam.aep
an.Xen.lae
an.Hom.sap
an.Mus.mus
an.Rat.nor
an.Ast.amu
an.Str.int
an.Cae.ele
an.Bra.pli
fu.Sch.pom
fu.Asp.nid
fu.Asp.tam
fu.Neu.cra
fu.Can.gla
fu.Sac.cer
fu.Bul.hui
fu.Den.sul
fu.Fel.oga
fu.Gig.mar
fl.Bac.spl
fl.Cyt.mar
fl.Fla.xan
fl.Mar.psy
fl.Pre.eno
fu.Fus.gon
fu.Fus.nul
fu.Lep.buc
fu.Lep.mic
gr.The.ros
pt.Iso.pal
pt.Pla.bra
pt.Pla.mar
ch.Zea.may
ch.Dau.car
ch.Gly.max
ch.Pis.sat
ch.Nic.tab
ch.Pin.thu
ch.Chl.mir
ch.Eug.gra
ch.Cya.par
ch.Cya.cal
ga.Esc.col
ga.Hae.par
ga.Leg.lyt
ga.Mar.psy
ga.Oce.pus
ga.Pho.pho
ga.Pse.asp
ga.Sal.typ
ga.Vib.cho
ga.Xan.pis
ra.Dei.mur
ra.Dei.rad
sp.Bor.par
sp.Lep.mey
sp.Tre.soc
sp.Tre.suc
th.The.afr
th.The.hyp
th.The.sub
ar.Sul.sol
ar.The.pen
ar.Hal.val
ar.Hal.sac
ar.Nat.mag
ar.Met.fer
ar.Met.jan
ar.Met.ore
ar.The.chi
ar.The.ste
hi.Act.eur
hi.Bif.inf
hi.Cel.cel
hi.Cor.oti
hi.Mic.par
hi.Mic.ech
hi.Myc.cel
hi.Myc.int
hi.Noc.fla
hi.Str.rim
lo.Ach.lai
lo.Bac.alc
lo.Bac.sub
lo.Car.mob
lo.Eub.lac
lo.Lac.car
lo.Myc.cap
lo.Myc.myc
lo.Spi.cit
lo.Sta.hom
mt.Dro.mel
mt.Gal.gal
mt.Bos.tau
mt.Hom.sap
mt.Mus.mus
mt.Sac.cer
mt.Zea.may
mt.Gly.max
mt.Tet.pyr
al.Aci.cry
al.Met.rho
al.Rhi.fre
al.Ric.pea
al.Sph.ter
be.Hyd.pal
be.Nei.fla
be.Pse.syz
be.Rho.pur
be.Tha.ter
de.Des.vib
de.Des.ter
de.Des.suc
ep.Alv.pom
ep.Cam.fet
ep.Cam.lar
ep.Hel.pyl
ep.Hel.tro
un.Aer.mar
un.Fle.sin
un.Mag.bav
"""
sample_seq_to_species = """cy.Mic.aer\tcy.Mic.aer
cy.Osc.aga\tcy.Osc.aga
cy.Pho.amb\tcy.Pho.amb
cy.Tri.ten\tcy.Tri.ten
pl.Zea.may\tpl.Zea.may
pl.Pan.gin\tpl.Pan.gin
pl.Ara.tha\tpl.Ara.tha
pl.Gly.max\tpl.Gly.max
pl.Pis.sat\tpl.Pis.sat
pl.Lyc.esc\tpl.Lyc.esc
pl.Sol.tub\tpl.Sol.tub
pl.Gin.bil\tpl.Gin.bil
pl.Pin.luc\tpl.Pin.luc
pl.Tai.cry\tpl.Tai.cry
pr.Sar.neu\tpr.Sar.neu
pr.Pla.mal\tpr.Pla.mal
pr.Sti.hel\tpr.Sti.hel
pr.Mal.mat\tpr.Mal.mat
pr.Cyc.gla\tpr.Cyc.gla
pr.Tet.bor\tpr.Tet.bor
pr.Rho.sal\tpr.Rho.sal
pr.Por.aca\tpr.Por.aca
pr.Bla.hom\tpr.Bla.hom
pr.Try.equ\tpr.Try.equ
an.Dro.mel\tan.Dro.mel
an.Lam.aep\tan.Lam.aep
an.Xen.lae\tan.Xen.lae
an.Hom.sap\tan.Hom.sap
an.Mus.mus\tan.Mus.mus
an.Rat.nor\tan.Rat.nor
an.Ast.amu\tan.Ast.amu
an.Str.int\tan.Str.int
an.Cae.ele\tan.Cae.ele
an.Bra.pli\tan.Bra.pli
fu.Sch.pom\tfu.Sch.pom
fu.Asp.nid\tfu.Asp.nid
fu.Asp.tam\tfu.Asp.tam
fu.Neu.cra\tfu.Neu.cra
fu.Can.gla\tfu.Can.gla
fu.Sac.cer\tfu.Sac.cer
fu.Bul.hui\tfu.Bul.hui
fu.Den.sul\tfu.Den.sul
fu.Fel.oga\tfu.Fel.oga
fu.Gig.mar\tfu.Gig.mar
fl.Bac.spl\tfl.Bac.spl
fl.Cyt.mar\tfl.Cyt.mar
fl.Fla.xan\tfl.Fla.xan
fl.Mar.psy\tfl.Mar.psy
fl.Pre.eno\tfl.Pre.eno
fu.Fus.gon\tfu.Fus.gon
fu.Fus.nul\tfu.Fus.nul
fu.Lep.buc\tfu.Lep.buc
fu.Lep.mic\tfu.Lep.mic
gr.The.ros\tgr.The.ros
pt.Iso.pal\tpt.Iso.pal
pt.Pla.bra\tpt.Pla.bra
pt.Pla.mar\tpt.Pla.mar
ch.Zea.may\tch.Zea.may
ch.Dau.car\tch.Dau.car
ch.Gly.max\tch.Gly.max
ch.Pis.sat\tch.Pis.sat
ch.Nic.tab\tch.Nic.tab
ch.Pin.thu\tch.Pin.thu
ch.Chl.mir\tch.Chl.mir
ch.Eug.gra\tch.Eug.gra
ch.Cya.par\tch.Cya.par
ch.Cya.cal\tch.Cya.cal
ga.Esc.col\tga.Esc.col
ga.Hae.par\tga.Hae.par
ga.Leg.lyt\tga.Leg.lyt
ga.Mar.psy\tga.Mar.psy
ga.Oce.pus\tga.Oce.pus
ga.Pho.pho\tga.Pho.pho
ga.Pse.asp\tga.Pse.asp
ga.Sal.typ\tga.Sal.typ
ga.Vib.cho\tga.Vib.cho
ga.Xan.pis\tga.Xan.pis
ra.Dei.mur\tra.Dei.mur
ra.Dei.rad\tra.Dei.rad
sp.Bor.par\tsp.Bor.par
sp.Lep.mey\tsp.Lep.mey
sp.Tre.soc\tsp.Tre.soc
sp.Tre.suc\tsp.Tre.suc
th.The.afr\tth.The.afr
th.The.hyp\tth.The.hyp
th.The.sub\tth.The.sub
ar.Sul.sol\tar.Sul.sol
ar.The.pen\tar.The.pen
ar.Hal.val\tar.Hal.val
ar.Hal.sac\tar.Hal.sac
ar.Nat.mag\tar.Nat.mag
ar.Met.fer\tar.Met.fer
ar.Met.jan\tar.Met.jan
ar.Met.ore\tar.Met.ore
ar.The.chi\tar.The.chi
ar.The.ste\tar.The.ste
hi.Act.eur\thi.Act.eur
hi.Bif.inf\thi.Bif.inf
hi.Cel.cel\thi.Cel.cel
hi.Cor.oti\thi.Cor.oti
hi.Mic.par\thi.Mic.par
hi.Mic.ech\thi.Mic.ech
hi.Myc.cel\thi.Myc.cel
hi.Myc.int\thi.Myc.int
hi.Noc.fla\thi.Noc.fla
hi.Str.rim\thi.Str.rim
lo.Ach.lai\tlo.Ach.lai
lo.Bac.alc\tlo.Bac.alc
lo.Bac.sub\tlo.Bac.sub
lo.Car.mob\tlo.Car.mob
lo.Eub.lac\tlo.Eub.lac
lo.Lac.car\tlo.Lac.car
lo.Myc.cap\tlo.Myc.cap
lo.Myc.myc\tlo.Myc.myc
lo.Spi.cit\tlo.Spi.cit
lo.Sta.hom\tlo.Sta.hom
mt.Dro.mel\tmt.Dro.mel
mt.Gal.gal\tmt.Gal.gal
mt.Bos.tau\tmt.Bos.tau
mt.Hom.sap\tmt.Hom.sap
mt.Mus.mus\tmt.Mus.mus
mt.Sac.cer\tmt.Sac.cer
mt.Zea.may\tmt.Zea.may
mt.Gly.max\tmt.Gly.max
mt.Tet.pyr\tmt.Tet.pyr
al.Aci.cry\tal.Aci.cry
al.Met.rho\tal.Met.rho
al.Rhi.fre\tal.Rhi.fre
al.Ric.pea\tal.Ric.pea
al.Sph.ter\tal.Sph.ter
be.Hyd.pal\tbe.Hyd.pal
be.Nei.fla\tbe.Nei.fla
be.Pse.syz\tbe.Pse.syz
be.Rho.pur\tbe.Rho.pur
be.Tha.ter\tbe.Tha.ter
de.Des.vib\tde.Des.vib
de.Des.ter\tde.Des.ter
de.Des.suc\tde.Des.suc
ep.Alv.pom\tep.Alv.pom
ep.Cam.fet\tep.Cam.fet
ep.Cam.lar\tep.Cam.lar
ep.Hel.pyl\tep.Hel.pyl
ep.Hel.tro\tep.Hel.tro
un.Aer.mar\tun.Aer.mar
un.Fle.sin\tun.Fle.sin
un.Mag.bav\tun.Mag.bav
"""
sample_priors = {'A':0.2528,'C':0.2372,'G':0.3099,'U':0.2001}
sub_matrix = """-1.4150\t0.2372\t0.9777\t0.2001
0.2528\t-1.1940\t0.3099\t0.6313
0.7976\t0.2372\t-1.2349\t0.2001
0.2528\t0.7484\t0.3099\t-1.3111
"""
sample_sub_matrix = {}
for row_c,row in zip(gctmpca_base_order,sub_matrix.split('\n')):
sample_sub_matrix[row_c] = dict(zip(gctmpca_base_order,row.split()))
trivial_seqs = """3 4
A1.. AACF
A12. AADF
A123 ADCF
"""
trivial_tree = """(A1..:0.5,(A12.,A123):0.5);
"""
trivial_species_names = """A1..
A12.
A123
"""
trivial_seq_to_species = """A1..\tA1..
A12.\tA12.
A123\tA123
"""
myog_seqs = """42 153
Alligator...... ELSDQEWKHVLDIWTKVESKLPEHGHEVIIRLLQEHPETQERFEKFKHMKTADEMKSSEKMKQHGNTVFTALGNILKQKGNHAEVLKPLAKSHALEHKIPVKYLEFISEIIVKVIAEKYPADFGADSQAAMRKALELFRNDMASKYKEFGYQG
Aptenodytes.... GLNDQEWQQVLTMWGKVESDLAGHGHAVLMRLFKSHPETMDRFDKFRGLKTPDEMRGSEDMKKHGVTVLT-LGQILKKKGHHEAELKPLSQTHATKHKVPVKYLEFISEAIMKVIAQKHASNFGADAQEAMKKALELFRNDMASKYKEFGFQG
Balaenoptera... VLTDAEWHLVLNIWAKVEADVAGHGQDILISLFKGHPETLEKFDKFKHLKTEAEMKASEDLKKHGNTVLTALGGILKKKGHHEAELKPLAQSHATKHKIPIKYLEFISDAIIHVLHSRHPADFGADAQAAMNKALELFRKDIAAKYKELGFQG
Bos............ GLSDGEWQLVLNAWGKVEADVAGHGQEVLIRLFTGHPETLEKFDKFKHLKTEAEMKASEDLKKHGNTVLTALGGILKKKGHHEAEVKHLAESHANKHKIPVKYLEFISDAIIHVLHAKHPSDFGADAQAAMSKALELFRNDMAAQYKVLGFHG
Callithrix..... GLSDGEWQLVLNVWGKVEADIPSHGQEVLISLFKGHPETLEKFDKFKHLKSEDEMKASEELKKHGVTVLTALGGILKKKGHHEAELKPLAQSHATKHKIPVKYLEFISDAIVHVLQKKHPGDFGADAQGAMKKALELFRNDMAAKYKELGFQG
Canis.......... GLSDGEWQIVLNIWGKVETDLAGHGQEVLIRLFKNHPETLDKFDKFKHLKTEDEMKGSEDLKKHGNTVLTALGGILKKKGHHEAELKPLAQSHATKHKIPVKYLEFISDAIIQVLQSKHSGDFHADTEAAMKKALELFRNDIAAKYKELGFQG
Caretta........ GLSDDEWNHVLGIWAKVEPDLSAHGQEVIIRLFQLHPETQERFAKFKNLTTIDALKSSEEVKKHGTTVLTALGRILKQKNNHEQELKPLAESHATKHKIPVKYLEFICEIIVKVIAEKHPSDFGADSQAAMKKALELFRNDMASKYKEFGFQG
Castor......... GLSDGEWQLVLHVWGKVEADLAGHGQEVLIRLFKGHPETLEKFNKFKHIKSEDEMKASEDLKKHGVTVLTALGGVLKKKGHHEAEIKPLAQSHATKHKIPIKYLEFISEAIIHVLQSKHPGBFGADABGAMNKALELFRKDIAAKYKELGFQG
Ctenodactylus.. GLSDGEWQLVLNAWGKVETDIGGHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKASEDLKKHGTTVLTALGNILKKKGQHEAELAPLAQSHATKHKIPVKYLEFISEAIIQVLESKHPGDFGADAQGAMSKALELFRNDIAAKYKELGFQG
Didelphis...... GLSDGEWQLVLNAWGKVEADIPGHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKASEDLKKHGATVLTALGNILKKKGNHEAELKPLAQSHATKHKISVQFLEFISEAIIQVIQSKHPGDFGGDAQAAMGKALELFRNDMAAKYKELGFQG
Elephas........ GLSDGEWELVLKTWGKVEADIPGHGETVFVRLFTGHPETLEKFDKFKHLKTEGEMKASEDLKKQGVTVLTALGGILKKKGHHEAEIQPLAQSHATKHKIPIKYLEFISDAIIHVLQSKHPAEFGADAQGAMKKALELFRNDIAAKYKELGFQG
Equus.......... GLSDGEWQQVLNVWGKVEADIAGHGQEVLIRLFTGHPETLEKFDKFKHLKTEAEMKASEDLKKHGTVVLTALGGILKKKGHHEAELKPLAQSHATKHKIPIKYLEFISDAIIHVLHSKHPGDFGADAQGAMTKALELFRNDIAAKYKELGFQG
Gallus......... GLSDQEWQQVLTIWGKVEADIAGHGHEVLMRLFHDHPETLDRFDKFKGLKTPDQMKGSEDLKKHGATVLTQLGKILKQKGNHESELKPLAQTHATKHKIPVKYLEFISEVIIKVIAEKHAADFGADSQAAMKKALELFRNDMASKYKEFGFQG
Graptemys...... GLSDDEWHHVLGIWAKVEPDLSAHGQEVIIRLFQVHPETQERFAKFKNLKTIDELRSSEEVKKHGTTVLTALGRILKLKNNHEPELKPLAESHATKHKIPVKYLEFICEIIVKVIAEKHPSDFGADSQAAMRKALELFRNDMASKYKEFGFQG
Inia........... GLSDGEWQLVLNIWGKVEADLAGHGQDVLIRLFKGHPETLEKFDKFKHLKTEAEMKASEDLKKHGNTVLTALGGILKKKGHHEAELKPLAQSHATKHKIPIKYLEFISEAIIHVLHSRHPGDFGADAQAAMNKALELFRKDIAAKYKELGFHG
Kogia.......... VLSEGEWQLVLHVWAKVEADIAGHGQDILIRLFKHHPETLEKFDRFKHLKSEAEMKASEDLKKHGVTVLTALGAILKKKGHHEAELKPLAQSHATKHKIPIKYLEFISEAIIHVLHSRHPADFGADAQGAMSKALELFRKDIAAKYKELGYQG
Lagostomus..... GLSDGEWQLVLNVWGKVEADLGGHGQEVLIRLFKGHPETLEKFDKFKHLKAEDEMRASEDLKKHGTTVLTALGGILKKRGQHAAELAPLAQSHATKHKIPVKYLEFISEAIIQVLQSKHPGDFGADAQAAMSKALELFRNDIAAKYKELGFQG
Lagothrix...... GLSDGEWQLVLNIWGKVEADIPSHGQEVLISLFKGHPETLEKFDKFKHLKSEDEMKASEELKKHGVTVLTALGGILKKKGQHEAELKPLAQSHATKHKIPVKYLEFISDAIIHALQKKHPGDFGADAQGAMKKALELFRNDMAAKYKELGFQG
Lutra.......... GLSDGEWQLVLNVWGKVEADLAGHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKGSEDLKKHGNTVLTALGGILKKKGKHEAELKPLAQSHATKHKIPIKYLEFISEAIIQVLQSKHPGBFGADAQGAMKRALELFRNDIAAKYKELGFQG
Macropus....... GLSDGEWQLVLNIWGKVETDEGGHGKDVLIRLFKGHPETLEKFDKFKHLKSEDEMKASEDLKKHGITVLTALGNILKKKGHHEAELKPLAQSHATKHKIPVQFLEFISDAIIQVIQSKHAGNFGADAQAAMKKALELFRHDMAAKYKEFGFQG
Meles.......... GLSDGEWQLVLNVWGKVEADLAGHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKGSEDLKKHGNTVLTALGGILKKKGHQEAELKPLAQSHATKHKIPVKYLEFISDAIAQVLQSKHPGNFAAEAQGAMKKALELFRNDIAAKYKELGFQG
Mus............ GLSDGEWQLVLNVWGKVEADLAGHGQEVLIGLFKTHPETLDKFDKFKNLKSEEDMKGSEDLKKHGCTVLTALGTILKKKGQHAAEIQPLAQSHATKHKIPVKYLEFISEIIIEVLKKRHSGDFGADAQGAMSKALELFRNDIAAKYKELGFQG
Ochotona....... GLSDGEWQLVLNVWGKVEADLAGHGQEVLIRLFKNHPETLEKFDKFKNLKSEDEMKGSDDLKKHGNTVLSALGGILKKKGQHEAELKPLAQSHATKHKIPVKYLEFISEAIIQVLQSKHPGDFGADAQGAMSKALELFRNDMAAKYKELGFQG
Ondatra........ GLSDGEWQLVLHVWGKVEADLAGHGQDVLIRLFKAHPETLEKFDKFKHIKSEDEMKGSEDLKKHGBTVLTALGGILKKKGHHEAEIKPLAQSHATKHKIPIKYLEFISEAIIHVLZSKHPSBFGADVZGAMKRALELFRNDIAAKYKELGFQG
Orcinus........ GLSDGEWQLVLNVWGKVEADLAGHGQDILIRLFKGHPETLEKFDKFKHLKTEADMKASEDLKKHGNTVLTALGAILKKKGHHDAELKPLAQSHATKHKIPIKYLEFISEAIIHVLHSRHPAEFGADAQGAMNKALELFRKDIAAKYKELGFHG
Ornithorhynchus GLSDGEWQLVLKVWGKVEGDLPGHGQEVLIRLFKTHPETLEKFDKFKGLKTEDEMKASADLKKHGGTVLTALGNILKKKGQHEAELKPLAQSHATKHKISIKFLEYISEAIIHVLQSKHSADFGADAQAAMGKALELFRNDMAAKYKEFGFQG
Orycteropus.... GLSDAEWQLVLNVWGKVEADIPGHGQDVLIRLFKGHPETLEKFDRFKHLKTEDEMKASEDLKKHGTTVLTALGGILKKKGQHEAEIQPLAQSHATKHKIPVKYLEFISEAIIQVIQSKHSGDFGADAQGAMSKALELFRNDIAAKYKELGFQG
Ovis........... GLSDGEWQLVLNAWGKVEADVAGHGQEVLIRLFTGHPETLEKFDKFKHLKTEAEMKASEDLKKHGNTVLTALGGILKKKGHHEAEVKHLAESHANKHKIPVKYLEFISDAIIHVLHAKHPSNFGADAQGAMSKALELFRNDMAAEYKVLGFQG
Pan............ GLSDGEWQLVLNVWGKVEADIPGHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKASEDLKKHGATVLTALGGILKKKGHHEAEIKPLAQSHATKHKIPVKYLEFISECIIQVLHSKHPGDFGADAQGAMNKALELFRKDMASNYKELGFQG
Papio.......... GLSDGEWQLVLNVWGKVEADIPSHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKASEDLKKHGATVLTALGGILKKKGHHEAEIKPLAQSHATKHKIPVKYLELISESIIQVLQSKHPGDFGADAQGAMNKALELFRNDMAAKYKELGFQG
Phocoenoides... GLSEGEWQLVLNVWGKVEADLAGHGQDVLIRLFKGHPETLEKFDKFKHLKTEAEMKASEDLKKHGNTVLTALGGILKKKGHHDAELKPLAQSHATKHKIPIKYLEFISEAIIHVLHSRHPAEFGADAQGAMNKALELFRKDIATKYKELGFHG
Physeter....... VLSEGEWQLVLHVWAKVEADVAGHGQDILIRLFKSHPETLEKFDRFKHLKTEAEMKASEDLKKHGVTVLTALGAILKKKGHHEAELKPLAQSHATKHKIPIKYLEFISEAIIHVLHSRHPGDFGADAQGAMNKALELFRKDIAAKYKELGYQG
Pongo.......... GLSDGEWQLVLNVWGKVEADIPSHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKASEDLKKHGATVLTALGGILKKKGHHEAEIKPLAQSHATKHKIPVKYLEFISESIIQVLQSKHPGDFGADAQGAMNKALELFRKDMASNYKELGFQG
Proechimys..... GLSDGEWQLVLNVWGKVEGDLSGHGQEVLIRLFKGHPETLEKFDKFKHLKAEDEMRASEELKKHGTTVLTALGGILKKKGQHAAELAPLAQSHATKHKIPVKYLEFISEAIIQVLQSKHPGDFGADAQGAMSKALELFRNDIAAKYKELGFQG
Rousettus...... GLSDGEWQLVLNVWGKVEADIPGHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKASEDLKKHGATVLTALGGILKKKGQHEAQLKPLAQSHATKHKIPVKYLEFISEVIIQVLQSKHPGDFGADAQGAMGKALELFRNDIAAKYKELGFQG
Saimiri........ GLSDGEWQLVLNIWGKVEADIPSHGQEVLISLFKGHPETLEKFDKFKHLKSEDEMKASEELKKHGTTVLTALGGILKKKGQHEAELKPLAQSHATKHKIPVKYLELISDAIVHVLQKKHPGDFGADAQGAMKKALELFRNDMAAKYKELGFQG
Spalax......... GLSDGEWQLVLNVWGKVEGDLAGHGQEVLIKLFKNHPETLEKFDKFKHLKSEDEMKGSEDLKKHGNTVLTALGGILKKKGQHAAEIQPLAQSHATKHKIPIKYLEFISEAIIQVLQSKHPGDFGADAQGAMSKALELFRNDIAAKYKELGFQG
Tachyglossus... GLSDGEWQLVLKVWGKVETDITGHGQDVLIRLFKTHPETLEKFDKFKHLKTEDEMKASADLKKHGGVVLTALGSILKKKGQHEAELKPLAQSHATKHKISIKFLEFISEAIIHVLQSKHSADFGADAQAAMGKALELFRNDMATKYKEFGFQG
Tupaia......... GLSDGEWQLVLNVWGKVEADVAGHGQEVLIRLFKGHPETLEKFDKFKHLKTEDEMKASEDLKKHGNTVLSALGGILKKKGQHEAEIKPLAQSHATKHKIPVKYLEFISEAIIQVLQSKHPGDFGADAQAAMSKALELFRNDIAAKYKELGFQG
Varanus........ GLSDEEWKKVVDIWGKVEPDLPSHGQEVIIRMFQNHPETQDRFAKFKNLKTLDEMKNSEDLKKHGTTVLTALGRILKQKGHHEAEIAPLAQTHANTHKIPIKYLEFICEVIVGVIAEKHSADFGADSQEAMRKALELFRNDMASRYKELGFQG
Zalophus....... GLSDGEWQLVLNIWGKVEADLVGHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKRSEDLKKHGKTVLTALGGILKKKGHHDAELKPLAQSHATKHKIPIKYLEFISEAIIHVLQSKHPGDFGADTHAAMKKALELFRNDIAAKYRELGFQG
Ziphius........ GLSEAEWQLVLHVWAKVEADLSGHGQEILIRLFKGHPETLEKFDKFKHLKSEAEMKASEDLKKHGHTVLTALGGILKKKGHHEAELKPLAQSHATKHKIPIKYLEFISDAIIHVLHSRHPSDFGADAQAAMTKALELFRKDIAAKYKELGFHG
"""
myog_seq_to_species = """Alligator...... Alligator......
Aptenodytes.... Aptenodytes....
Balaenoptera... Balaenoptera...
Bos............ Bos............
Callithrix..... Callithrix.....
Canis.......... Canis..........
Caretta........ Caretta........
Castor......... Castor.........
Ctenodactylus.. Ctenodactylus..
Didelphis...... Didelphis......
Elephas........ Elephas........
Equus.......... Equus..........
Gallus......... Gallus.........
Graptemys...... Graptemys......
Inia........... Inia...........
Kogia.......... Kogia..........
Lagostomus..... Lagostomus.....
Lagothrix...... Lagothrix......
Lutra.......... Lutra..........
Macropus....... Macropus.......
Meles.......... Meles..........
Mus............ Mus............
Ochotona....... Ochotona.......
Ondatra........ Ondatra........
Orcinus........ Orcinus........
Ornithorhynchus Ornithorhynchus
Orycteropus.... Orycteropus....
Ovis........... Ovis...........
Pan............ Pan............
Papio.......... Papio..........
Phocoenoides... Phocoenoides...
Physeter....... Physeter.......
Pongo.......... Pongo..........
Proechimys..... Proechimys.....
Rousettus...... Rousettus......
Saimiri........ Saimiri........
Spalax......... Spalax.........
Tachyglossus... Tachyglossus...
Tupaia......... Tupaia.........
Varanus........ Varanus........
Zalophus....... Zalophus.......
Ziphius........ Ziphius........
"""
myog_tree = """((((((((Alligator......:0.14157,(Caretta........:0.02868,Graptemys......:0.02361):0.07084):0.02380,Varanus........:0.11672):0.04036,(Aptenodytes....:0.09769,Gallus.........:0.07336):0.03201):0.06365,(Ornithorhynchus:0.02648,Tachyglossus...:0.03235):0.05190):0.00632,(Didelphis......:0.03986,Macropus.......:0.06472):0.01338):0.01350,((((((Balaenoptera...:0.05296,(Kogia..........:0.01638,Physeter.......:0.01630):0.03528):0.00341,Ziphius........:0.04397):0.01061,(Inia...........:0.01297,(Orcinus........:0.01876,Phocoenoides...:0.01392):0.01971):0.00818):0.02315,((Bos............:0.01434,Ovis...........:0.01180):0.06631,Equus..........:0.03500):0.00381):0.00467,Elephas........:0.09030):0.01398,((Canis..........:0.05867,Zalophus.......:0.04591):0.00949,(((Castor.........:0.03609,Ondatra........:0.04888):0.01934,Lutra..........:0.01988):0.00609,Meles..........:0.04293):0.00277):0.00653):0.00260):0.00531,(((Callithrix.....:0.00920,(Lagothrix......:0.01063,Saimiri........:0.01551):0.00387):0.03812,((Pan............:0.00842,Pongo..........:0.01118):0.01307,Papio..........:0.01307):0.01907):0.00421,Rousettus......:0.02439):0.00691):0.00513,((Ctenodactylus..:0.03010,(Lagostomus.....:0.01528,Proechimys.....:0.01740):0.01892):0.00914,Orycteropus....:0.04642):0.00078,(((Mus............:0.07859,Spalax.........:0.02599):0.01114,Ochotona.......:0.03134):0.00969,Tupaia.........:0.02462):0.00576);
"""
myog_species_names = """Alligator......
Aptenodytes....
Balaenoptera...
Bos............
Callithrix.....
Canis..........
Caretta........
Castor.........
Ctenodactylus..
Didelphis......
Elephas........
Equus..........
Gallus.........
Graptemys......
Inia...........
Kogia..........
Lagostomus.....
Lagothrix......
Lutra..........
Macropus.......
Meles..........
Mus............
Ochotona.......
Ondatra........
Orcinus........
Ornithorhynchus
Orycteropus....
Ovis...........
Pan............
Papio..........
Phocoenoides...
Physeter.......
Pongo..........
Proechimys.....
Rousettus......
Saimiri........
Spalax.........
Tachyglossus...
Tupaia.........
Varanus........
Zalophus.......
Ziphius........
"""
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_app/test_guppy.py 000644 000765 000024 00000010172 12024702176 022000 0 ustar 00jrideout staff 000000 000000 #!/bin/env python
__author__ = "Jesse Stombaugh"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jesse Stombaugh"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jesse Stombaugh"
__email__ = "jesse.stombaugh@colorado.edu"
__status__ = "Production"
from os import getcwd, remove, rmdir, mkdir
from os.path import splitext
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from random import randint
from cogent.app.guppy import Guppy, build_tree_from_json_using_params
from cogent.app.util import ApplicationError,get_tmp_filename
from cogent.core.tree import PhyloNode
from cogent.parse.tree import DndParser
class Genericguppy(TestCase):
def setUp(self):
'''setup the files for testing guppy'''
# create a list of files to cleanup
self._paths_to_clean_up = []
self._dirs_to_clean_up = []
# get a tmp filename to use
basename=splitext(get_tmp_filename())[0]
# create and write out RAxML stats file
self.json_fname=basename+'.json'
json_out=open(self.json_fname,'w')
json_out.write(JSON_RESULT)
json_out.close()
self._paths_to_clean_up.append(self.json_fname)
def tearDown(self):
"""cleans up all files initially created"""
# remove the tempdir and contents
map(remove,self._paths_to_clean_up)
map(rmdir,self._dirs_to_clean_up)
class guppyTests(Genericguppy):
"""Tests for the guppy application controller"""
def test_guppy(self):
"""Base command-calls"""
app=Guppy()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','guppy']))
app.Parameters['--help'].on()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','guppy --help']))
def test_change_working_dir(self):
"""Change working dir"""
# define working directory for output
working_dir='/tmp/Guppy'
self._dirs_to_clean_up.append(working_dir)
app = Guppy(WorkingDir=working_dir)
self.assertEqual(app.BaseCommand, \
''.join(['cd "','/tmp/Guppy','/"; ','guppy']))
def test_build_tree_from_alignment_using_params(self):
"""Builds a tree from a json file"""
# define working directory for output
outdir='/tmp/'
# set params
params={}
params["tog"] = None
# build tree
tree = build_tree_from_json_using_params(self.json_fname,
output_dir=outdir,
params=params)
self.assertEqual(tree.getNewick(),
DndParser(TREE_RESULT, constructor=PhyloNode).getNewick())
JSON_RESULT="""\
{"tree":
"((seq0000004:0.08408[0],seq0000005:0.13713[1])0.609:0.00215[2],seq0000003:0.02032[3],(seq0000001:0.00014[4],seq0000002:0.00014[5])0.766:0.00015[6]):0[7];",
"placements":
[
{"p":
[[0, -113.210938, 0.713818, 0.064504, 0.000006],
[1, -114.929894, 0.127954, 0.137122, 0.000007],
[2, -114.932766, 0.127587, 0.000008, 0.000006],
[6, -117.743534, 0.007675, 0.000141, 0.027211],
[3, -117.743759, 0.007674, 0.020310, 0.027207],
[4, -117.747386, 0.007646, 0.000131, 0.027266],
[5, -117.747396, 0.007646, 0.000131, 0.027266]
], "n": ["seq0000006"]
},
{"p": [[0, -113.476305, 1.000000, 0.035395, 0.000006]], "n":
["seq0000007"]
}
], "metadata":
{"invocation":
"guppy -t %s -r %s -s %s --out-dir \/tmp %s"
}, "version": 1, "fields":
["edge_num", "likelihood", "like_weight_ratio", "distal_length",
"pendant_length"
]
}
""".replace('\n','').replace(' ','')
TREE_RESULT="""\
((((seq0000004:0.035395,seq0000007:6e-06)\
:0.029109,seq0000006:6e-06)\
:0.019576,seq0000005:0.13713)\
0.609:0.00215,seq0000003:0.02032,(seq0000001:0.00014,seq0000002:0.00014)\
0.766:0.00015)\
:0;
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_ilm.py 000644 000765 000024 00000235564 12024702176 021433 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.ilm import ILM, xhlxplot, hlxplot
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class xhlxplotTest(TestCase):
"""Tests for xhlxplot application controller"""
def setUp(self):
self.input = xhlx_input
def test_input_as_lines(self):
"""Test xhlxplot stdout input as lines"""
x = xhlxplot(InputHandler='_input_as_lines')
res = x(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test xhlxplot input as string"""
x = xhlxplot()
f = open('/tmp/ilm.mwm','w')
f.write('\n'.join(self.input))
f.close()
res = x('/tmp/ilm.mwm')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/ilm.mwm')
def test_get_result_path(self):
"""Tests xhlxplot result path"""
x = xhlxplot(InputHandler='_input_as_lines')
res = x(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
class IlmTest(TestCase):
"""Tests for ilm application controller"""
def setUp(self):
self.input = ilm_input
def test_stdout_input_as_lines(self):
"""Test ilm input as lines"""
i = ILM(InputHandler='_input_as_lines')
res = i(self.input)
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in ilm_stdout])
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
#Exitstatus platform dependent?? Works but gives exitstatus 224
#self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test ilm input as string"""
ilm = ILM()
f = open('/tmp/ilm.mwm','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = ilm('/tmp/ilm.mwm')
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in ilm_stdout])
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
#Exitstatus platform dependent??
#self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/ilm.mwm')
def test_get_result_path(self):
"""Tests ilm result path"""
i = ILM(InputHandler='_input_as_lines')
res = i(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
#self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
class hlxplotTest(TestCase):
"""Tests for hlxplot application controller"""
def setUp(self):
self.input = hlx_input
def test_input_as_lines(self):
"""Test hlxplot input as lines"""
h = hlxplot(InputHandler='_input_as_lines')
res = h(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test hlxplot stdout input as string"""
h = hlxplot()
f = open('/tmp/ilm.mwm','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = h('/tmp/ilm.mwm')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/ilm.mwm')
def test_get_result_path(self):
"""Tests hlxplot result path"""
h = hlxplot(InputHandler='_input_as_lines')
res = h(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
ilm_stdout =['\n', 'Final Matching:\n', '1 72\n', '2 71\n', '3 70\n', '4 69\n', '5 68\n', '6 67\n', '7 66\n', '8 0\n', '9 0\n', '10 25\n', '11 24\n', '12 23\n', '13 22\n', '14 0\n', '15 0\n', '16 0\n', '17 0\n', '18 48\n', '19 47\n', '20 46\n', '21 45\n', '22 13\n', '23 12\n', '24 11\n', '25 10\n', '26 0\n', '27 43\n', '28 42\n', '29 41\n', '30 40\n', '31 39\n', '32 38\n', '33 37\n', '34 56\n', '35 55\n', '36 54\n', '37 33\n', '38 32\n', '39 31\n', '40 30\n', '41 29\n', '42 28\n', '43 27\n', '44 0\n', '45 21\n', '46 20\n', '47 19\n', '48 18\n', '49 65\n', '50 64\n', '51 63\n', '52 62\n', '53 61\n', '54 36\n', '55 35\n', '56 34\n', '57 0\n', '58 0\n', '59 0\n', '60 0\n', '61 53\n', '62 52\n', '63 51\n', '64 50\n', '65 49\n', '66 7\n', '67 6\n', '68 5\n', '69 4\n', '70 3\n', '71 2\n', '72 1\n']
hlx_stdout = 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00\x00\x00\x00\x00\x00\x00\x008\xff\xff\xff\xf4\x01\x00\x008\xff\xff\xff8\xff\xff\xff8\xff\xff\xffG\x01\x00\x008\xff\xff\xff\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x008\xff\xff\xff8\xff\xff\xff\xf4\x01\x00\x008\xff\xff\xff8\xff\xff\xff8\xff\xff\xff\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x008\xff\xff\xff8\xff\xff\xff8\xff\xff\xff\xd6\x01\x00\x008\xff\xff\xff\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x008\xff\xff\xff8\xff\xff\xff8\xff\xff\xff8\xff\xff\xff\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x008\xff\xff\xff8\xff\xff\xff8\xff\xff\xff\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x008\xff\xff\xff\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00"]
ilm_input = xhlx_stdout
hlx_input = ['seq1:GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC\n']
xhlx_input = ['seq1:GGCTAGATAGCTCAGATGGTAGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_infernal.py 000644 000765 000024 00000070446 12024702176 022444 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# test_infernal.py
from os import getcwd, remove, rmdir, mkdir, path
import tempfile, shutil
from cogent.core.moltype import DNA, RNA, PROTEIN
from cogent.core.alignment import DataError
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.infernal import Cmalign, Cmbuild, Cmcalibrate, Cmemit, Cmscore,\
Cmsearch, Cmstat, cmbuild_from_alignment, cmbuild_from_file, \
cmalign_from_alignment, cmalign_from_file, cmsearch_from_alignment,\
cmsearch_from_file
from cogent.parse.rfam import MinimalRfamParser, ChangedRnaSequence, \
ChangedSequence
from cogent.format.stockholm import stockholm_from_alignment
from cogent.struct.rna2d import ViennaStructure, wuss_to_vienna
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Development"
class GeneralSetUp(TestCase):
def setUp(self):
"""Infernal general setUp method for all tests"""
self.seqs1_unaligned = {'1':'ACUGCUAGCUAGUAGCGUACGUA',\
'2':'GCUACGUAGCUAC',\
'3':'GCGGCUAUUAGAUCGUA'}
self.struct1_unaligned_string = '....(((...)))....'
self.seqs1_unaligned_gaps = {'1':'ACUGCUAGCUAGU-AGCGUAC--GUA',\
'2':'--GCUACGUAGCUAC',\
'3':'GCGGCUAUUAGAUCGUA--'}
self.seqs2_aligned = {'a': 'UAGGCUCUGAUAUAAUAGCUCUC---------',\
'c': '------------UGACUACGCAU---------',\
'b': '----UAUCGCUUCGACGAUUCUCUGAUAGAGA'}
self.seqs2_unaligned = {'a': 'UAGGCUCUGAUAUAAUAGCUCUC',\
'c': 'UGACUACGCAU',\
'b': 'UAUCGCUUCGACGAUUCUCUGAUAGAGA'}
self.struct2_aligned_string = '............((.(...)))..........'
self.struct2_aligned_dict = {'SS_cons':self.struct2_aligned_string}
self.lines2 = stockholm_from_alignment(aln=self.seqs2_aligned,\
GC_annotation=self.struct2_aligned_dict)
#self.seqs1 aligned to self.seqs2 with self.seqs2 included.
self.seqs1_and_seqs2_aligned = \
{'a': 'UAGGCUCUGAUAUAAUAGC-UCUC---------',\
'b': '----UAUCGCUUCGACGAU-UCUCUGAUAGAGA',\
'c': '------------UGACUAC-GCAU---------',\
'1': '-ACUGCUAGCUAGUAGCGUACGUA---------',\
'2': '----------GCUACGUAG-CUAC---------',\
'3': '-----GCGGCUAUUAG-AU-CGUA---------',\
}
self.seqs1_and_seqs2_aligned_struct_string = \
'............((.(....)))..........'
#self.seqs1 aligned to self.seqs2 without self.seqs2 included.
self.seqs1_aligned = \
{'1': 'ACUGCUAGCUAGUAGCGUACGUA',\
'2': '---------GCUACGUAG-CUAC',\
'3': '----GCGGCUAUUAG-AU-CGUA',\
}
self.seqs1_aligned_struct_string = \
'...........((.(....))).'
self.temp_dir = tempfile.mkdtemp()
self.temp_dir_spaces = '/tmp/test for infernal/'
try:
mkdir(self.temp_dir_spaces)
except OSError:
pass
try:
#create sequence files
f = open(path.join(self.temp_dir, 'seqs1.sto'),'w')
f.write(self.lines2)
f.close()
#create cm file.
self.cmfile = path.join(self.temp_dir, 'aln2.cm')
cm = open(self.cmfile,'w')
cm.write(ALN1_CM)
cm.close()
#create alignment file used to create cm file.
self.aln2_file = path.join(self.temp_dir, 'aln2.sto')
af = open(self.aln2_file,'w')
af.write(self.lines2)
af.close()
except OSError:
pass
class CmalignTests(GeneralSetUp):
"""Tests for the Cmalign application controller"""
def test_base_command(self):
"""Infernal BaseCommand should return the correct BaseCommand"""
c = Cmalign()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmalign']))
c.Parameters['-l'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmalign -l']))
def test_changing_working_dir(self):
"""Infernal BaseCommand should change according to WorkingDir"""
c = Cmalign(WorkingDir='/tmp/cmalign_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmalign_test','/"; ','cmalign']))
c = Cmalign()
c.WorkingDir = '/tmp/cmalign_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmalign_test2','/"; ','cmalign']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cmalign_test')
rmdir('/tmp/cmalign_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
def test_cmalign_from_alignment(self):
"""cmalign_from_alignment should work as expected.
"""
#Align with cmalign_from_alignment without original alignment.
aln, struct = cmalign_from_alignment(aln=self.seqs2_aligned,\
structure_string=self.struct2_aligned_string,\
seqs=self.seqs1_unaligned_gaps,moltype=RNA,include_aln=False)
#Check correct alignment
self.assertEqual(aln.todict(),self.seqs1_aligned)
#Check correct struct
self.assertEqual(wuss_to_vienna(str(struct)),\
self.seqs1_aligned_struct_string)
#should work with gapped seqs. Need to test this is taken care of
# since cmalign segfaults when there are gaps in the seqs to be aligned.
aln, struct = cmalign_from_alignment(aln=self.seqs2_aligned,\
structure_string=self.struct2_aligned_string,\
seqs=self.seqs1_unaligned_gaps,moltype=RNA)
#alignment should be correct
self.assertEqual(aln.todict(),self.seqs1_and_seqs2_aligned)
#structure should be correct
self.assertEqual(wuss_to_vienna(str(struct)),\
self.seqs1_and_seqs2_aligned_struct_string)
#should work with ungapped seqs.
aln, struct = cmalign_from_alignment(aln=self.seqs2_aligned,\
structure_string=self.struct2_aligned_string,\
seqs=self.seqs1_unaligned_gaps,moltype=RNA)
#alignment should be correct
self.assertEqual(aln.todict(),self.seqs1_and_seqs2_aligned)
#structure should be correct
self.assertEqual(wuss_to_vienna(str(struct)),\
self.seqs1_and_seqs2_aligned_struct_string)
#should return standard out
aln, struct,stdout = cmalign_from_alignment(aln=self.seqs2_aligned,\
structure_string=self.struct2_aligned_string,\
seqs=self.seqs1_unaligned_gaps,moltype=RNA,\
return_stdout=True)
#Test that standard out is same length as expected
self.assertEqual(len(stdout.split('\n')),\
len(CMALIGN_STDOUT.split('\n')))
def test_cmalign_from_file(self):
"""cmalign_from_file should work as expected.
"""
#Align with cmalign_from_file without original alignment.
aln,struct = cmalign_from_file(cm_file_path=self.cmfile,\
seqs=self.seqs1_unaligned,\
moltype=RNA)
#Check correct alignment
self.assertEqual(aln.todict(),self.seqs1_aligned)
#Check correct struct
self.assertEqual(wuss_to_vienna(str(struct)),\
self.seqs1_aligned_struct_string)
#Align with cmalign_from_file using original alignment.
aln,struct = cmalign_from_file(cm_file_path=self.cmfile,\
seqs=self.seqs1_unaligned,\
moltype=RNA,\
alignment_file_path=self.aln2_file,\
include_aln=True)
#alignment should be correct
self.assertEqual(aln.todict(),self.seqs1_and_seqs2_aligned)
#structure should be correct
self.assertEqual(wuss_to_vienna(str(struct)),\
self.seqs1_and_seqs2_aligned_struct_string)
class CmbuildTests(GeneralSetUp):
"""Tests for the Cmbuild application controller"""
def test_base_command(self):
"""Infernal BaseCommand should return the correct BaseCommand"""
c = Cmbuild()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmbuild']))
c.Parameters['-A'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmbuild -A']))
def test_changing_working_dir(self):
"""Infernal BaseCommand should change according to WorkingDir"""
c = Cmbuild(WorkingDir='/tmp/cmbuild_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmbuild_test','/"; ','cmbuild']))
c = Cmbuild()
c.WorkingDir = '/tmp/cmbuild_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmbuild_test2','/"; ','cmbuild']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cmbuild_test')
rmdir('/tmp/cmbuild_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
def test_cmbuild_from_alignment(self):
"""cmbuild_from_alignment should work as expected.
"""
#Test unaligned seqs and unaligned struct fail.
#DataError should be raised with Alignment is constructed
self.assertRaises(DataError,cmbuild_from_alignment,\
self.seqs1_unaligned,self.struct1_unaligned_string)
#Test aligned seqs and unaligned struct fail.
self.assertRaises(ValueError,cmbuild_from_alignment,\
self.seqs2_aligned,self.struct1_unaligned_string)
#Test get cm back without alignment.
cm_res = cmbuild_from_alignment(self.seqs2_aligned,\
self.struct2_aligned_string)
cm_lines = cm_res.split('\n')
ALN1_CM_lines = ALN1_CM.split('\n')
#Check that the same number of lines are in both CMs
self.assertEqual(len(cm_lines),len(ALN1_CM_lines))
#The first 13 lines are unique to the specific run. The res of the
# CM should be the same, since built from the same data.
self.assertEqual(cm_lines[13:],ALN1_CM_lines[13:])
#Make sure same alignment is returned if return_alignment=True
cm_res, cm_aln = cmbuild_from_alignment(self.seqs2_aligned,\
self.struct2_aligned_string,return_alignment=True)
self.assertEqual(cm_aln,self.lines2)
def test_cmbuild_from_file(self):
"""cmbuild_from_file should work as expected.
"""
cm_res = cmbuild_from_file(self.temp_dir+'/seqs1.sto')
cm_lines = cm_res.split('\n')
ALN1_CM_lines = ALN1_CM.split('\n')
#Check that the same number of lines are in both CMs
self.assertEqual(len(cm_lines),len(ALN1_CM_lines))
#The first 13 lines are unique to the specific run. The res of the
# CM should be the same, since built from the same data.
self.assertEqual(cm_lines[13:],ALN1_CM_lines[13:])
#Make sure same alignment is returned if return_alignment=True
cm_res, cm_aln = cmbuild_from_alignment(self.seqs2_aligned,\
self.struct2_aligned_string,return_alignment=True)
self.assertEqual(cm_aln,self.lines2)
class CmcalibrateTests(GeneralSetUp):
"""Tests for the Cmcalibrate application controller"""
def test_base_command(self):
"""Infernal BaseCommand should return the correct BaseCommand"""
c = Cmcalibrate()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmcalibrate']))
c.Parameters['--mpi'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmcalibrate --mpi']))
def test_changing_working_dir(self):
"""Infernal BaseCommand should change according to WorkingDir"""
c = Cmcalibrate(WorkingDir='/tmp/cmcalibrate_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmcalibrate_test','/"; ','cmcalibrate']))
c = Cmcalibrate()
c.WorkingDir = '/tmp/cmcalibrate_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmcalibrate_test2','/"; ','cmcalibrate']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cmcalibrate_test')
rmdir('/tmp/cmcalibrate_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
class CmemitTests(GeneralSetUp):
"""Tests for the Cmemit application controller"""
def test_base_command(self):
"""Infernal BaseCommand should return the correct BaseCommand"""
c = Cmemit()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmemit']))
c.Parameters['-u'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmemit -u']))
def test_changing_working_dir(self):
"""Infernal BaseCommand should change according to WorkingDir"""
c = Cmemit(WorkingDir='/tmp/cmemit_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmemit_test','/"; ','cmemit']))
c = Cmemit()
c.WorkingDir = '/tmp/cmemit_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmemit_test2','/"; ','cmemit']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cmemit_test')
rmdir('/tmp/cmemit_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
class CmscoreTests(GeneralSetUp):
"""Tests for the Cmscore application controller"""
def test_base_command(self):
"""Infernal BaseCommand should return the correct BaseCommand"""
c = Cmscore()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmscore']))
c.Parameters['-l'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmscore -l']))
def test_changing_working_dir(self):
"""Infernal BaseCommand should change according to WorkingDir"""
c = Cmscore(WorkingDir='/tmp/cmscore_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmscore_test','/"; ','cmscore']))
c = Cmscore()
c.WorkingDir = '/tmp/cmscore_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmscore_test2','/"; ','cmscore']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cmscore_test')
rmdir('/tmp/cmscore_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
class CmsearchTests(GeneralSetUp):
"""Tests for the Cmsearch application controller"""
def test_base_command(self):
"""Infernal BaseCommand should return the correct BaseCommand"""
c = Cmsearch()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmsearch']))
c.Parameters['-p'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmsearch -p']))
def test_changing_working_dir(self):
"""Infernal BaseCommand should change according to WorkingDir"""
c = Cmsearch(WorkingDir='/tmp/cmsearch_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmsearch_test','/"; ','cmsearch']))
c = Cmsearch()
c.WorkingDir = '/tmp/cmsearch_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmsearch_test2','/"; ','cmsearch']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cmsearch_test')
rmdir('/tmp/cmsearch_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
def test_cmsearch_from_alignment_no_hits(self):
"""cmsearch_from_alignment should work as expected
"""
search_res = cmsearch_from_alignment(aln=self.seqs2_aligned,\
structure_string=self.struct2_aligned_string,\
seqs=self.seqs1_unaligned,moltype=RNA)
self.assertEqual(search_res,[])
def test_cmsearch_from_alignment(self):
"""cmsearch_from_alignment should work as expected
"""
exp_search_res = [['a', 5, 23, 1, 19, 12.85, '-', 37],\
['b', 1, 19, 1, 19, 14.359999999999999, '-', 47]]
search_res = cmsearch_from_alignment(aln=self.seqs2_aligned,\
structure_string=self.struct2_aligned_string,\
seqs=self.seqs2_unaligned,moltype=RNA)
for search, exp in zip(search_res, exp_search_res):
self.assertEqual(search[1:],exp)
def test_cmsearch_from_file_no_hits(self):
"""cmsearch_from_file should work as expected
"""
search_res = cmsearch_from_file(cm_file_path=self.cmfile,\
seqs=self.seqs1_unaligned,moltype=RNA)
self.assertEqual(search_res,[])
def test_cmsearch_from_file(self):
"""cmsearch_from_file should work as expected
"""
exp_search_res = [['a', 5, 23, 1, 19, 12.85, '-', 37],\
['b', 1, 19, 1, 19, 14.359999999999999, '-', 47]]
search_res = cmsearch_from_file(cm_file_path=self.cmfile,\
seqs=self.seqs2_unaligned,moltype=RNA)
for search, exp in zip(search_res, exp_search_res):
self.assertEqual(search[1:],exp)
class CmstatTests(GeneralSetUp):
"""Tests for the Cmstat application controller"""
def test_base_command(self):
"""Infernal BaseCommand should return the correct BaseCommand"""
c = Cmstat()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmstat']))
c.Parameters['-g'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','cmstat -g']))
def test_changing_working_dir(self):
"""Infernal BaseCommand should change according to WorkingDir"""
c = Cmstat(WorkingDir='/tmp/cmstat_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmstat_test','/"; ','cmstat']))
c = Cmstat()
c.WorkingDir = '/tmp/cmstat_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/cmstat_test2','/"; ','cmstat']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/cmstat_test')
rmdir('/tmp/cmstat_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
ALN1_CM = """INFERNAL-1 [1.0rc1]
NAME aln1-1
STATES 61
NODES 18
ALPHABET 1
ELSELF -0.08926734
WBETA 1e-07
NSEQ 3
EFFNSEQ 3.000
CLEN 19
BCOM cmbuild aln1.cm aln1.sto
BDATE Sun Oct 5 18:45:35 2008
NULL 0.000 0.000 0.000 0.000
MODEL:
[ ROOT 0 ]
S 0 -1 0 1 4 -2.071 -2.210 -1.649 -2.140
IL 1 1 2 1 4 -0.556 -5.022 -1.818 -7.508 0.000 0.000 0.000 0.000
IR 2 2 3 2 3 -0.310 -2.439 -6.805 0.000 0.000 0.000 0.000
[ MATL 1 ]
ML 3 2 3 5 3 -8.003 -0.020 -6.657 -0.389 0.377 -1.236 0.597
D 4 2 3 5 3 -7.923 -3.436 -0.146
IL 5 5 3 5 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 2 ]
ML 6 5 3 8 3 -8.003 -0.020 -6.657 0.711 -1.015 -1.162 0.507
D 7 5 3 8 3 -7.923 -3.436 -0.146
IL 8 8 3 8 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 3 ]
ML 9 8 3 11 3 -8.003 -0.020 -6.657 -0.389 0.377 -1.236 0.597
D 10 8 3 11 3 -7.923 -3.436 -0.146
IL 11 11 3 11 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 4 ]
ML 12 11 3 14 3 -8.003 -0.020 -6.657 -0.392 0.246 -1.238 0.703
D 13 11 3 14 3 -7.923 -3.436 -0.146
IL 14 14 3 14 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 5 ]
ML 15 14 3 17 3 -8.003 -0.020 -6.657 -1.340 -2.411 1.644 -1.777
D 16 14 3 17 3 -7.923 -3.436 -0.146
IL 17 17 3 17 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 6 ]
ML 18 17 3 20 3 -8.003 -0.020 -6.657 0.830 0.106 -1.204 -0.492
D 19 17 3 20 3 -7.923 -3.436 -0.146
IL 20 20 3 20 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 7 ]
ML 21 20 3 23 3 -8.003 -0.020 -6.657 -1.143 -1.575 -1.925 1.560
D 22 20 3 23 3 -7.923 -3.436 -0.146
IL 23 23 3 23 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 8 ]
ML 24 23 3 26 3 -8.391 -0.018 -6.709 0.821 -1.044 -1.178 0.385
D 25 23 3 26 3 -6.905 -0.258 -2.688
IL 26 26 3 26 3 -1.925 -0.554 -4.164 0.000 0.000 0.000 0.000
[ MATR 9 ]
MR 27 26 3 29 5 -7.411 -0.031 -7.227 -7.439 -8.330 -0.726 0.967 -1.567 0.142
D 28 26 3 29 5 -5.352 -0.707 -2.978 -4.409 -2.404
IR 29 29 3 29 5 -2.408 -0.496 -5.920 -4.087 -5.193 0.000 0.000 0.000 0.000
[ MATP 10 ]
MP 30 29 3 34 6 -9.266 -9.205 -0.019 -7.982 -8.261 -8.656 -1.570 -1.865 -1.898 0.327 -1.331 -2.318 0.651 0.994 -1.872 0.282 -2.224 -0.666 1.972 -1.608 -0.242 1.187
ML 31 29 3 34 6 -6.250 -6.596 -1.310 -1.005 -6.446 -3.975 0.660 -0.612 -0.293 -0.076
MR 32 29 3 34 6 -6.988 -5.717 -1.625 -5.695 -0.829 -3.908 0.660 -0.612 -0.293 -0.076
D 33 29 3 34 6 -9.049 -7.747 -3.544 -4.226 -4.244 -0.319
IL 34 34 5 34 6 -2.579 -2.842 -0.760 -4.497 -5.274 -4.934 0.000 0.000 0.000 0.000
IR 35 35 6 35 5 -2.408 -0.496 -5.920 -4.087 -5.193 0.000 0.000 0.000 0.000
[ MATP 11 ]
MP 36 35 6 40 4 -7.331 -7.538 -0.041 -5.952 -4.114 0.397 -4.664 0.815 -4.665 -4.015 -0.462 -4.315 -3.939 3.331 -3.732 -0.830 -0.398 -3.640 -1.958 -3.517
ML 37 35 6 40 4 -3.758 -3.940 -0.507 -2.670 0.660 -0.612 -0.293 -0.076
MR 38 35 6 40 4 -4.809 -3.838 -1.706 -0.766 0.660 -0.612 -0.293 -0.076
D 39 35 6 40 4 -4.568 -4.250 -2.265 -0.520
IL 40 40 5 40 4 -1.686 -2.369 -1.117 -4.855 0.000 0.000 0.000 0.000
IR 41 41 6 41 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 12 ]
ML 42 41 6 44 5 -7.411 -0.031 -7.227 -7.439 -8.330 1.826 -2.947 -2.856 -2.413
D 43 41 6 44 5 -4.959 -0.803 -4.221 -2.596 -2.508
IL 44 44 3 44 5 -2.408 -0.496 -4.087 -5.920 -5.193 0.000 0.000 0.000 0.000
[ MATP 13 ]
MP 45 44 3 49 4 -7.331 -7.538 -0.041 -5.952 -1.592 -1.722 -1.807 0.471 -1.387 -2.146 1.822 0.774 -1.836 0.505 -2.076 -0.521 1.055 -1.515 -0.260 0.958
ML 46 44 3 49 4 -3.758 -3.940 -0.507 -2.670 0.660 -0.612 -0.293 -0.076
MR 47 44 3 49 4 -4.809 -3.838 -1.706 -0.766 0.660 -0.612 -0.293 -0.076
D 48 44 3 49 4 -4.568 -4.250 -2.265 -0.520
IL 49 49 5 49 4 -1.686 -2.369 -1.117 -4.855 0.000 0.000 0.000 0.000
IR 50 50 6 50 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 14 ]
ML 51 50 6 53 3 -8.323 -0.016 -6.977 0.481 -1.091 -0.011 0.192
D 52 50 6 53 3 -6.174 -1.687 -0.566
IL 53 53 3 53 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 15 ]
ML 54 53 3 56 3 -8.323 -0.016 -6.977 1.148 -1.570 -0.075 -1.007
D 55 53 3 56 3 -6.174 -1.687 -0.566
IL 56 56 3 56 3 -1.442 -0.798 -4.142 0.000 0.000 0.000 0.000
[ MATL 16 ]
ML 57 56 3 59 2 * 0.000 -0.726 0.967 -1.567 0.142
D 58 56 3 59 2 * 0.000
IL 59 59 3 59 2 -1.823 -0.479 0.000 0.000 0.000 0.000
[ END 17 ]
E 60 59 3 -1 0
//
"""
CMALIGN_STDOUT = """# cmalign :: align sequences to an RNA CM
# INFERNAL 1.0rc1 (June 2008)
# Copyright 2007-2009 (C) 2008 HHMI Janelia Farm Research Campus
# Freely distributed under the GNU General Public License (GPL)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# command: cmalign --withali aln1.sto -o all_aligned.sto aln1.cm seqs1.fasta
# date: Sun Oct 5 22:04:30 2008
#
# cm name algorithm config sub bands tau
# ------------------------- --------- ------ --- ----- ------
# aln1-1 opt acc global no hmm 1e-07
#
# bit scores
# ------------------
# seq idx seq name len total struct avg prob elapsed
# ------- -------- ----- -------- -------- -------- -----------
1 1 23 -9.98 5.71 0.260 00:00:00.01
2 2 13 -6.79 6.73 0.710 00:00:00.00
3 3 17 -7.43 5.86 0.754 00:00:00.01
# Alignment saved in file all_aligned.sto.
#
# CPU time: 0.02u 0.00s 00:00:00.02 Elapsed: 00:00:00
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_knetfold.py 000644 000765 000024 00000003666 12024702176 022454 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.app.knetfold import Knetfold
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class KnetfoldTest(TestCase):
"""Tests for Knetfold application controller"""
def setUp(self):
self.input = knetfold_input
def test_input_as_lines(self):
"""Test Knetfold stdout input as lines"""
k = Knetfold(InputHandler='_input_as_lines')
res = k(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test Knetfold stdout input as string"""
k = Knetfold()
f = open('/tmp/single.fasta','w')
f.write('\n'.join(self.input))
f.close()
res = k('/tmp/single.fasta')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/single.fasta')
def test_get_result_path(self):
"""Tests knetfold result path"""
k = Knetfold(InputHandler='_input_as_lines')
res = k(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus',
'ct','coll','sec','fasta','pdf','mx0','mx1','mx2','mx3'])
self.assertEqual(res['ExitStatus'],0)
assert res['ct'] is not None
assert res['coll'] is not None
assert res['sec'] is not None
assert res['fasta'] is not None
res.cleanUp()
knetfold_input = ['>seq1\n',
'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n',
'\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_mafft.py 000644 000765 000024 00000012340 12024702176 021730 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import getcwd, remove, rmdir, mkdir, path
import tempfile, shutil
from cogent.core.moltype import RNA
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.mafft import Mafft, align_unaligned_seqs, \
add_seqs_to_alignment, align_two_alignments
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Development"
class GeneralSetUp(TestCase):
def setUp(self):
"""Mafft general setUp method for all tests"""
self.seqs1 = ['ACUGCUAGCUAGUAGCGUACGUA','GCUACGUAGCUAC',
'GCGGCUAUUAGAUCGUA']
self.labels1 = ['>1','>2','>3']
self.lines1 = flatten(zip(self.labels1,self.seqs1))
self.aligned1 = {'1': 'acugcuagcuaguagcguacgua',\
'2': 'gcuacguagcuac----------',\
'3': 'gcggcuauuagau------cgua',\
}
self.seqs2=['UAGGCUCUGAUAUAAUAGCUCUC','UAUCGCUUCGACGAUUCUCUGAUAGAGA',
'UGACUACGCAU']
self.labels2=['>a','>b','>c']
self.lines2 = flatten(zip(self.labels2,self.seqs2))
self.aligned2 = {'a': 'UAGGCUCUGAUAUAAUAGCUCUC---------',\
'b': 'UA----UCGCUUCGACGAUUCUCUGAUAGAGA',\
'c': 'UG------------ACUACGCAU---------',\
}
self.temp_dir = tempfile.mkdtemp()
self.temp_dir_spaces = '/tmp/test for mafft/'
try:
mkdir(self.temp_dir_spaces)
except OSError:
pass
try:
#create sequence files
f = open(path.join(self.temp_dir, 'seq1.txt'),'w')
f.write('\n'.join(self.lines1))
f.close()
g = open(path.join(self.temp_dir, 'seq2.txt'),'w')
g.write('\n'.join(self.lines2))
g.close()
except OSError:
pass
class MafftTests(GeneralSetUp):
"""Tests for the Mafft application controller"""
def test_base_command(self):
"""Mafft BaseCommand should return the correct BaseCommand"""
c = Mafft()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','mafft']))
c.Parameters['--quiet'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','mafft --quiet']))
c.Parameters['--globalpair'].on()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','mafft --globalpair --quiet']))
c.Parameters['--maxiterate'].on(1000)
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ',"""mafft --maxiterate 1000 --globalpair --quiet"""]))
def test_changing_working_dir(self):
"""Mafft BaseCommand should change according to WorkingDir"""
c = Mafft(WorkingDir='/tmp/mafft_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/mafft_test','/"; ','mafft']))
c = Mafft()
c.WorkingDir = '/tmp/mafft_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/mafft_test2','/"; ','mafft']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/mafft_test')
rmdir('/tmp/mafft_test2')
def test_general_cleanUp(self):
"""Last test executed: cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
def test_align_unaligned_seqs(self):
"""align_unaligned_seqs should work as expected"""
res = align_unaligned_seqs(self.seqs1, RNA)
self.assertEqual(res.toFasta(), align1)
res = align_unaligned_seqs(self.lines2, RNA)
self.assertEqual(res.toFasta(), align2)
def test_add_seqs_to_alignment(self):
"""add_seqs_to_alignment should work as expected."""
res = add_seqs_to_alignment(self.lines1,self.aligned2, RNA)
self.assertEqual(res.toFasta(), add_seqs_align)
def test_align_two_alignments(self):
"""align_two_alignments should work as expected."""
res = align_two_alignments(self.aligned1, self.aligned2, RNA)
self.assertEqual(res.toFasta(), align_two_align)
align1 = ">seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\nGCUACGUAGCUAC----------\n>seq_2\nGCGGCUAUUAGAU------CGUA"
align2 = ">a\nUAGGCUCUGAUAUAAUAGCUCUC---------\n>b\nUA----UCGCUUCGACGAUUCUCUGAUAGAGA\n>c\nUG------------ACUACGCAU---------"
add_seqs_align = """>1\nACUGC-UAGCUAGUAGCGUACGUA--------\n>2\nGCUACGUAGCUA-----------C--------\n>3\nGCGGCUAUUAGAUCGUA---------------\n>a\nUAGGCUCUGAUAUAAUAGCUCUC---------\n>b\nUA----UCGCUUCGACGAUUCUCUGAUAGAGA\n>c\nUG------------ACUACGCAU---------"""
align_two_align = """>1\nACUGCUAGCUAGUAGCGUACGUA---------\n>2\nGCUACGUAGCUAC-------------------\n>3\nGCGGCUAUUAGAU------CGUA---------\n>a\nUAGGCUCUGAUAUAAUAGCUCUC---------\n>b\nUA----UCGCUUCGACGAUUCUCUGAUAGAGA\n>c\nUG------------ACUACGCAU---------"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_mfold.py 000644 000765 000024 00000005203 12024702176 021734 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.app.mfold import Mfold
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class MfoldTest(TestCase):
"""Tests for Mfold application controller"""
def setUp(self):
self.input = mfold_input
def test_stdout_input_as_lines(self):
"""Test Mfold stdout input as lines"""
m = Mfold(InputHandler='_input_as_lines')
res = m(self.input)
#Impossible to compare stdout since tmp filenames in app controller
#can't be predicted and are in stdout
#Test exitstatus = 0 and stdout is not none
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test Mfold stdout input as string"""
m = Mfold()
f = open('/tmp/single.fasta','w')
f.write('\n'.join(self.input))
f.close()
res = m('/tmp/single.fasta')
#Impossible to compare stdout since tmp filenames in app controller
#can't be predicted and are in stdout
#Test exitstatus = 0 and stdout is not none
assert res['StdOut'] is not None
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
remove('/tmp/single.fasta')
def test_get_result_path(self):
"""Tests mfold result path"""
m = Mfold(InputHandler='_input_as_lines')
res = m(self.input)
self.assertEqualItems(res.keys(),['ps','_1.ps','_1.ss','StdOut', 'StdErr', 'ExitStatus', 'ct_all', 'ct1', 'log', 'ann', 'h-num', 'det', 'pnt', 'sav', 'ss-count', '-local.seq', 'rnaml', 'out', 'plot','pdf1'])
self.assertEqual(res['ExitStatus'],0)
assert res['ct_all'] is not None
assert res['log'] is not None
assert res['ann'] is not None
assert res['h-num'] is not None
assert res['det'] is not None
assert res['pnt'] is not None
assert res['sav'] is not None
assert res['ss-count'] is not None
assert res['-local.seq'] is not None
assert res['rnaml'] is not None
assert res['out'] is not None
assert res['plot'] is not None
res.cleanUp()
mfold_input = ['>seq1\n', 'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n', '\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_mothur.py 000644 000765 000024 00000013467 12024702176 022164 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# test_mothur.py
from __future__ import with_statement
from cStringIO import StringIO
from os import remove, rmdir
from tempfile import mkdtemp, mkstemp
from cogent.util.unit_test import TestCase, main
from cogent.app.mothur import Mothur, mothur_from_file
__author__ = "Kyle Bittinger"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Kyle Bittinger", "Jose Carlos Clemente Litran"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Kyle Bittinger"
__email__ = "kylebittinger@gmail.com"
__status__ = "Development"
class MothurTests(TestCase):
def setUp(self):
self.small_fasta = (
'>aaaaaa\nTAGGCTCTGATATAATAGCTCTC---------\n'
'>cccccc\n------------TGACTACGCAT---------\n'
'>bbbbbb\n----TATCGCTTCGACGATTCTCTGATAGAGA\n'
)
self.small_otus = (
'unique\t3\taaaaaa\tcccccc\tbbbbbb\t\n'
'0.62\t2\taaaaaa\tbbbbbb,cccccc\t\n'
'0.67\t1\tbbbbbb,cccccc,aaaaaa\t\n'
)
self.small_otus_parsed = [
(float('0'), [['aaaaaa'], ['cccccc'], ['bbbbbb']]),
(float('0.62'), [['aaaaaa'], ['bbbbbb', 'cccccc']]),
(float('0.67'), [['bbbbbb', 'cccccc', 'aaaaaa']]),
]
self.complement_fasta = (
'>a\n--AGGGGTAATAA--\n'
'>b\n--TTATTACCCCT--\n'
'>c\n-------AAAAAA--\n'
)
self.complement_otus = (
'unique\t3\ta\tb\tc\t\n'
'0.43\t2\tc,a\tb\t\n'
'1.00\t1\tb,c,a\t\n'
)
def test_get_help(self):
"""Mothur.getHelp() should return help string"""
expected_help = (
'See manual, available on the MOTHUR wiki:\n'
'http://schloss.micro.umass.edu/mothur/'
)
self.assertEqual(Mothur.getHelp(), expected_help)
def test_compile_mothur_script(self):
"""Mothur._compile_mothur_script() should return valid Mothur script"""
app = Mothur()
app._input_filename = 'test.fasta'
observed_script = app._compile_mothur_script()
expected_script = (
'#unique.seqs(fasta=test.fasta); '
'dist.seqs(fasta=test.unique.fasta); '
'read.dist(column=test.unique.dist, name=test.names); '
'cluster(method=furthest)')
self.assertEqual(observed_script, expected_script)
def test_get_result_paths(self):
"""Mothur._get_result_paths() should guess correct output paths"""
app = Mothur()
app._input_filename = 'test.fasta'
observed_paths = {
'distance matrix': app._derive_dist_path(),
'otu list': app._derive_list_path(),
'rank abundance': app._derive_rank_abundance_path(),
'species abundance': app._derive_species_abundance_path(),
'unique names': app._derive_names_path(),
'unique seqs': app._derive_unique_path(),
}
expected_paths = {
'distance matrix': 'test.unique.dist',
'otu list': 'test.unique.fn.list',
'rank abundance': 'test.unique.fn.rabund',
'species abundance': 'test.unique.fn.sabund',
'unique names': 'test.names',
'unique seqs': 'test.unique.fasta',
}
self.assertEqual(observed_paths, expected_paths)
def test_working_directory(self):
"""Mothur.WorkingDir attribute should not be cast to FilePath object"""
app = Mothur(WorkingDir='/tmp')
self.assertEquals(str(app.WorkingDir), '/tmp')
def test_call_with_multiline_string(self):
"""Mothur.__call__() should return correct otu's for input as single string"""
app = Mothur()
result = app(self.small_fasta)
observed_otus = result['otu list'].read()
self.assertEquals(observed_otus, self.small_otus)
result.cleanUp()
def test_call_with_lines(self):
"""Mothur.__call__() should return correct otu's for input as lines"""
lines = self.small_fasta.split('\n')
app = Mothur(InputHandler='_input_as_lines')
result = app(lines)
observed_otus = result['otu list'].read()
self.assertEquals(observed_otus, self.small_otus)
result.cleanUp()
def test_call_with_path(self):
"""Mothur.__call__() should return correct otu's for input as path"""
working_dir = mkdtemp()
_, filename = mkstemp(dir=working_dir, suffix='.fasta')
with open(filename, 'w') as f:
f.write(self.small_fasta)
app = Mothur(InputHandler='_input_as_path', WorkingDir=working_dir)
result = app(filename)
observed_otus = result['otu list'].read()
self.assertEquals(observed_otus, self.small_otus)
remove(filename)
result.cleanUp()
rmdir(working_dir)
def test_call_with_working_dir(self):
"""Mothur.__call__() should return correct otu's when input dir is changed"""
working_dir = mkdtemp()
app = Mothur(WorkingDir=working_dir)
result = app(self.small_fasta)
observed_otus = result['otu list'].read()
self.assertEquals(observed_otus, self.small_otus)
result.cleanUp()
rmdir(working_dir)
def test_call_with_complement(self):
"""Mothur.__call__() should return correct otu's for input sequences which are reverse complements"""
app = Mothur()
result = app(self.complement_fasta)
observed_otus = result['otu list'].read()
self.assertEquals(observed_otus, self.complement_otus)
result.cleanUp()
def test_mothur_from_file(self):
"""mothur_from_file() should return parsed otus"""
f = StringIO(self.small_fasta)
f.seek(0)
parsed_otus = mothur_from_file(f)
self.assertEquals(parsed_otus, self.small_otus_parsed)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_msms.py 000644 000765 000024 00000005026 12024702176 021615 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import os, tempfile
from cogent.util.unit_test import TestCase, main
from cogent.parse.pdb import PDBParser
from cogent.app.msms import Msms, surface_xtra
from cogent.struct.selection import einput
__author__ = "Marcin Cieslik"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Development"
class MsmsTest(TestCase):
"""Tests for Msms application controller"""
def setUp(self):
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
def test_stdout_input_from_entity(self):
"""Test Stride when input is an entity"""
s = Msms()
res = s(self.input_structure)
self.assertEqual(res['ExitStatus'], 0)
stdout = res['StdOut'].read()
assert stdout.find('1634 spheres 0 collision only, radii 1.600 to 1.850') != -1
assert not res['StdOut'].read()
assert res['ExitStatus'] == 0
assert list(sorted(res.keys())) == list(sorted(['FaceFile', 'StdOut', 'AreaFile', 'StdErr', 'VertFile', 'ExitStatus']))
af = res['AreaFile'].readlines()
assert len(af) == 1635, len(af)
ff = res['FaceFile'].readlines()
assert ff[1].strip() == "#faces #sphere density probe_r"
assert ff[2].strip() == "25310 1634 1.00 1.50" or \
ff[2].strip() == "51712 1634 1.00 1.50"
assert len(ff) == 25313 or len(ff) == 51715
vf = res['VertFile'].readlines()
assert vf[1] == '#vertex #sphere density probe_r\n'
assert vf[2].strip() == '12657 1634 1.00 1.50' or \
vf[2].strip() == '25858 1634 1.00 1.50'
assert len(vf) == 12660 or len(vf) == 25861
res.cleanUp()
def test_surface_xtra(self):
res = surface_xtra(self.input_structure)
assert res.shape == (12658, 3) or res.shape == (25859, 3)
assert res is self.input_structure.xtra['MSMS_SURFACE']
chains = einput(self.input_structure, 'C')
chainA, chainB = chains.sortedvalues()
resA = surface_xtra(chainA)
assert len(resA) == 6223 or len(resA) == 12965
resB = surface_xtra(chainB)
assert len(resB) == 6620 or len(resB) == 13390
assert chainB.xtra['MSMS_SURFACE'] is resB is \
self.input_structure[(0,)][('B',)].xtra['MSMS_SURFACE']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_muscle.py 000644 000765 000024 00000026175 12024702176 022136 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import getcwd, remove, rmdir, mkdir, path
from subprocess import Popen, PIPE, STDOUT
import tempfile, shutil
from cogent.core.moltype import RNA, DNA
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.muscle import Muscle, muscle_seqs, aln_tree_seqs, \
align_unaligned_seqs, build_tree_from_alignment, \
align_and_build_tree, add_seqs_to_alignment, align_two_alignments
__author__ = "Catherine Lozupone"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Catherine Lozupone", "Rob Knight", "Daniel McDonald",
"Jai Ram Rideout"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Catherine Lozupone"
__email__ = "lozupone@colorado.edu"
__status__ = "Development"
class GeneralSetUp(TestCase):
def setUp(self):
"""Muscle general setUp method for all tests"""
# Check if muscle version is supported for this test
acceptable_version = (3,6)
command = "muscle -version"
proc = Popen(command,shell=True,universal_newlines=True,\
stdout=PIPE,stderr=STDOUT)
stdout = proc.stdout.read()
version_string = stdout.strip().split(' ')[1].strip()[1:]
try:
version = tuple(map(int,version_string.split('.')))
pass_test = version[:2] == acceptable_version
except ValueError:
pass_test = False
version_string = stdout
self.assertTrue(pass_test,\
"Unsupported muscle version. %s is required, but running %s." \
% ('.'.join(map(str,acceptable_version)), version_string))
self.seqs1 = ['ACUGCUAGCUAGUAGCGUACGUA','GCUACGUAGCUAC',
'GCGGCUAUUAGAUCGUA']
self.labels1 = ['>1','>2','>3']
self.lines1 = flatten(zip(self.labels1,self.seqs1))
self.seqs2=['UAGGCUCUGAUAUAAUAGCUCUC','UAUCGCUUCGACGAUUCUCUGAUAGAGA',
'UGACUACGCAU']
self.labels2=['>a','>b','>c']
self.lines2 = flatten(zip(self.labels2,self.seqs2))
self.temp_dir = tempfile.mkdtemp()
self.temp_dir_spaces = '/tmp/test for muscle/'
try:
mkdir(self.temp_dir_spaces)
except OSError:
pass
try:
#create sequence files
f = open(path.join(self.temp_dir, 'seq1.txt'),'w')
f.write('\n'.join(self.lines1))
f.close()
g = open(path.join(self.temp_dir, 'seq2.txt'),'w')
g.write('\n'.join(self.lines2))
g.close()
except OSError:
pass
def tearDown(self):
"""cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
class MuscleTests(GeneralSetUp):
"""Tests for the Muscle application controller"""
def test_base_command(self):
"""Muscle BaseCommand should return the correct BaseCommand"""
c = Muscle()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','muscle']))
c.Parameters['-in'].on('seq.txt')
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','muscle -in "seq.txt"']))
c.Parameters['-cluster2'].on('neighborjoining')
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','muscle -cluster2 neighborjoining' +
' -in "seq.txt"']))
def test_maxmb(self):
"""maxmb option should not break Muscle"""
app = Muscle()
app.Parameters['-maxmb'].on('250')
outfile = tempfile.NamedTemporaryFile()
app.Parameters['-out'].on(outfile.name)
infile = tempfile.NamedTemporaryFile()
infile.write(
">Seq1\nAAAGGGTTTCCCCT\n"
">Seq2\nAAAGGGGGTTTCCACT\n")
infile.flush()
result = app(infile.name)
observed = result['MuscleOut'].read()
expected = (
">Seq1\nAAA--GGGTTTCCCCT\n"
">Seq2\nAAAGGGGGTTTCCACT\n"
)
self.assertEqual(observed, expected)
def test_changing_working_dir(self):
"""Muscle BaseCommand should change according to WorkingDir"""
c = Muscle(WorkingDir='/tmp/muscle_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/muscle_test','/"; ','muscle']))
c = Muscle()
c.WorkingDir = '/tmp/muscle_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/muscle_test2','/"; ','muscle']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/muscle_test')
rmdir('/tmp/muscle_test2')
def test_aln_tree_seqs(self):
"aln_tree_seqs returns the muscle alignment and tree from iteration2"
tree, aln = aln_tree_seqs(path.join(self.temp_dir, 'seq1.txt'),
tree_type="neighborjoining",
WorkingDir=self.temp_dir,
clean_up=True)
self.assertEqual(str(tree), '((1:1.125,2:1.125):0.375,3:1.5);')
self.assertEqual(len(aln), 6)
self.assertEqual(aln[-2], '>3\n')
self.assertEqual(aln[-1], 'GCGGCUAUUAGAUCGUA------\n')
def test_aln_tree_seqs_spaces(self):
"aln_tree_seqs should work on filename with spaces"
try:
#create sequence files
f = open(path.join(self.temp_dir_spaces, 'muscle_test_seq1.txt'),'w')
f.write('\n'.join(self.lines1))
f.close()
except OSError:
pass
tree, aln = aln_tree_seqs(path.join(self.temp_dir_spaces,\
'muscle_test_seq1.txt'),
tree_type="neighborjoining",
WorkingDir=getcwd(),
clean_up=True)
self.assertEqual(str(tree), '((1:1.125,2:1.125):0.375,3:1.5);')
self.assertEqual(len(aln), 6)
self.assertEqual(aln[-2], '>3\n')
self.assertEqual(aln[-1], 'GCGGCUAUUAGAUCGUA------\n')
remove(self.temp_dir_spaces+'/muscle_test_seq1.txt')
def test_align_unaligned_seqs(self):
"""align_unaligned_seqs should work as expected"""
res = align_unaligned_seqs(self.seqs1, RNA)
self.assertEqual(res.toFasta(), align1)
def test_build_tree_from_alignment(self):
"""Muscle should return a tree built from the passed alignment"""
tree_short = build_tree_from_alignment(build_tree_seqs_short, DNA)
num_seqs = flatten(build_tree_seqs_short).count('>')
self.assertEqual(len(tree_short.tips()), num_seqs)
tree_long = build_tree_from_alignment(build_tree_seqs_long, DNA)
seq_names = []
for line in build_tree_seqs_long.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree_long.tips():
if node.Name not in seq_names:
self.fail()
def test_align_and_build_tree(self):
"""Should align and build a tree from a set of sequences"""
res = align_and_build_tree(self.seqs1, RNA)
self.assertEqual(res['Align'].toFasta(), align1)
tree = res['Tree']
seq_names = []
for line in align1.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree.tips():
if node.Name not in seq_names:
self.fail()
def test_add_seqs_to_alignment(self):
"""Should add sequences to an alignment"""
res = add_seqs_to_alignment(seqs_to_add, align1)
self.assertEqual(res.toFasta(), added_align_result)
def test_align_two_alignments(self):
"""Should align to multiple sequence alignments"""
res = align_two_alignments(align1, aln_to_merge)
self.assertEqual(res.toFasta(), merged_align_result)
align1 = ">seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n---GCUACGUAGCUAC-------\n>seq_2\nGCGGCUAUUAGAUCGUA------"
# for use in test_add_seqs_to_alignment()
seqs_to_add = ">foo\nGCUACGUAGCU\n>bar\nGCUACGUAGCC"
added_align_result = ">bar\n---GCUACGUAGCC---------\n>foo\n---GCUACGUAGCU---------\n>seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n---GCUACGUAGCUAC-------\n>seq_2\nGCGGCUAUUAGAUCGUA------"
# for use in test_align_two_alignments()
aln_to_merge = ">foo\nGCUACGUAGCU\n>bar\n--UACGUAGCC"
merged_align_result = ">bar\n-----UACGUAGCC---------\n>foo\n---GCUACGUAGCU---------\n>seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n---GCUACGUAGCUAC-------\n>seq_2\nGCGGCUAUUAGAUCGUA------"
build_tree_seqs_short = """>muscle_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>muscle_test_seqs_1
GACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>muscle_test_seqs_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>muscle_test_seqs_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>muscle_test_seqs_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>muscle_test_seqs_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>muscle_test_seqs_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>muscle_test_seqs_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>muscle_test_seqs_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>muscle_test_seqs_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
build_tree_seqs_long = """>muscle_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>muscle_test_seqsaaaaaaaa_1
GACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>muscle_test_seqsaaaaaaaa_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>muscle_test_seqsaaaaaaaa_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>muscle_test_seqsaaaaaaaa_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>muscle_test_seqsaaaaaaaa_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>muscle_test_seqsaaaaaaaa_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>muscle_test_seqsaaaaaaaa_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>muscle_test_seqsaaaaaaaa_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>muscle_test_seqsaaaaaaaa_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_muscle_v38.py 000644 000765 000024 00000026177 12024702176 022640 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import getcwd, remove, rmdir, mkdir, path
from subprocess import Popen, PIPE, STDOUT
import tempfile, shutil
from cogent.core.moltype import RNA, DNA
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.muscle_v38 import Muscle, muscle_seqs, aln_tree_seqs, \
align_unaligned_seqs, build_tree_from_alignment, \
align_and_build_tree, add_seqs_to_alignment, align_two_alignments
__author__ = "Catherine Lozupone"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Catherine Lozupone", "Rob Knight", "Daniel McDonald",
"Jai Ram Rideout"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Catherine Lozupone"
__email__ = "lozupone@colorado.edu"
__status__ = "Production"
class GeneralSetUp(TestCase):
def setUp(self):
"""Muscle general setUp method for all tests"""
# Check if muscle version is supported for this test
acceptable_version = (3,8)
command = "muscle -version"
proc = Popen(command,shell=True,universal_newlines=True,\
stdout=PIPE,stderr=STDOUT)
stdout = proc.stdout.read()
version_string = stdout.strip().split(' ')[1].strip()[1:]
try:
version = tuple(map(int,version_string.split('.')))
pass_test = version[:2] == acceptable_version
except ValueError:
pass_test = False
version_string = stdout
self.assertTrue(pass_test,\
"Unsupported muscle version. %s is required, but running %s." \
% ('.'.join(map(str,acceptable_version)), version_string))
self.seqs1 = ['ACUGCUAGCUAGUAGCGUACGUA','GCUACGUAGCUAC',
'GCGGCUAUUAGAUCGUA']
self.labels1 = ['>1','>2','>3']
self.lines1 = flatten(zip(self.labels1,self.seqs1))
self.seqs2=['UAGGCUCUGAUAUAAUAGCUCUC','UAUCGCUUCGACGAUUCUCUGAUAGAGA',
'UGACUACGCAU']
self.labels2=['>a','>b','>c']
self.lines2 = flatten(zip(self.labels2,self.seqs2))
self.temp_dir = tempfile.mkdtemp()
self.temp_dir_spaces = '/tmp/test for muscle/'
try:
mkdir(self.temp_dir_spaces)
except OSError:
pass
try:
#create sequence files
f = open(path.join(self.temp_dir, 'seq1.txt'),'w')
f.write('\n'.join(self.lines1))
f.close()
g = open(path.join(self.temp_dir, 'seq2.txt'),'w')
g.write('\n'.join(self.lines2))
g.close()
except OSError:
pass
def tearDown(self):
"""cleans up all files initially created"""
# remove the tempdir and contents
shutil.rmtree(self.temp_dir)
shutil.rmtree(self.temp_dir_spaces)
class MuscleTests(GeneralSetUp):
"""Tests for the Muscle application controller"""
def test_base_command(self):
"""Muscle BaseCommand should return the correct BaseCommand"""
c = Muscle()
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','muscle']))
c.Parameters['-in'].on('seq.txt')
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','muscle -in "seq.txt"']))
c.Parameters['-cluster2'].on('neighborjoining')
self.assertEqual(c.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','muscle -cluster2 neighborjoining' +
' -in "seq.txt"']))
def test_maxmb(self):
"""maxmb option should not break Muscle"""
app = Muscle()
app.Parameters['-maxmb'].on('250')
outfile = tempfile.NamedTemporaryFile()
app.Parameters['-out'].on(outfile.name)
infile = tempfile.NamedTemporaryFile()
infile.write(
">Seq1\nAAAGGGTTTCCCCT\n"
">Seq2\nAAAGGGGGTTTCCACT\n")
infile.flush()
result = app(infile.name)
observed = result['MuscleOut'].read()
expected = (
">Seq1\nAAA--GGGTTTCCCCT\n"
">Seq2\nAAAGGGGGTTTCCACT\n"
)
self.assertEqual(observed, expected)
def test_changing_working_dir(self):
"""Muscle BaseCommand should change according to WorkingDir"""
c = Muscle(WorkingDir='/tmp/muscle_test')
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/muscle_test','/"; ','muscle']))
c = Muscle()
c.WorkingDir = '/tmp/muscle_test2'
self.assertEqual(c.BaseCommand,\
''.join(['cd "','/tmp/muscle_test2','/"; ','muscle']))
#removing the dirs is proof that they were created at the same time
#if the dirs are not there, an OSError will be raised
rmdir('/tmp/muscle_test')
rmdir('/tmp/muscle_test2')
def test_aln_tree_seqs(self):
"aln_tree_seqs returns the muscle alignment and tree from iteration2"
tree, aln = aln_tree_seqs(path.join(self.temp_dir, 'seq1.txt'),
tree_type="neighborjoining",
WorkingDir=self.temp_dir,
clean_up=True)
self.assertEqual(str(tree), '((1:1.125,2:1.125):0.375,3:1.5);')
self.assertEqual(len(aln), 6)
self.assertEqual(aln[-2], '>3\n')
self.assertEqual(aln[-1], 'GCGGCUAUUAGAUCGUA------\n')
def test_aln_tree_seqs_spaces(self):
"aln_tree_seqs should work on filename with spaces"
try:
#create sequence files
f = open(path.join(self.temp_dir_spaces, 'muscle_test_seq1.txt'),'w')
f.write('\n'.join(self.lines1))
f.close()
except OSError:
pass
tree, aln = aln_tree_seqs(path.join(self.temp_dir_spaces,\
'muscle_test_seq1.txt'),
tree_type="neighborjoining",
WorkingDir=getcwd(),
clean_up=True)
self.assertEqual(str(tree), '((1:1.125,2:1.125):0.375,3:1.5);')
self.assertEqual(len(aln), 6)
self.assertEqual(aln[-2], '>3\n')
self.assertEqual(aln[-1], 'GCGGCUAUUAGAUCGUA------\n')
remove(self.temp_dir_spaces+'/muscle_test_seq1.txt')
def test_align_unaligned_seqs(self):
"""align_unaligned_seqs should work as expected"""
res = align_unaligned_seqs(self.seqs1, RNA)
self.assertEqual(res.toFasta(), align1)
def test_build_tree_from_alignment(self):
"""Muscle should return a tree built from the passed alignment"""
tree_short = build_tree_from_alignment(build_tree_seqs_short, DNA)
num_seqs = flatten(build_tree_seqs_short).count('>')
self.assertEqual(len(tree_short.tips()), num_seqs)
tree_long = build_tree_from_alignment(build_tree_seqs_long, DNA)
seq_names = []
for line in build_tree_seqs_long.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree_long.tips():
if node.Name not in seq_names:
self.fail()
def test_align_and_build_tree(self):
"""Should align and build a tree from a set of sequences"""
res = align_and_build_tree(self.seqs1, RNA)
self.assertEqual(res['Align'].toFasta(), align1)
tree = res['Tree']
seq_names = []
for line in align1.split('\n'):
if line.startswith('>'):
seq_names.append(line[1:])
for node in tree.tips():
if node.Name not in seq_names:
self.fail()
def test_add_seqs_to_alignment(self):
"""Should add sequences to an alignment"""
res = add_seqs_to_alignment(seqs_to_add, align1)
self.assertEqual(res.toFasta(), added_align_result)
def test_align_two_alignments(self):
"""Should align to multiple sequence alignments"""
res = align_two_alignments(align1, aln_to_merge)
self.assertEqual(res.toFasta(), merged_align_result)
align1 = ">seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n---GCUACGUAGCUAC-------\n>seq_2\nGCGGCUAUUAGAUCGUA------"
# for use in test_add_seqs_to_alignment()
seqs_to_add = ">foo\nGCUACGUAGCU\n>bar\nGCUACGUAGCC"
added_align_result = ">bar\n---GCUACGUAGCC---------\n>foo\n---GCUACGUAGCU---------\n>seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n---GCUACGUAGCUAC-------\n>seq_2\nGCGGCUAUUAGAUCGUA------"
# for use in test_align_two_alignments()
aln_to_merge = ">foo\nGCUACGUAGCU\n>bar\n--UACGUAGCC"
merged_align_result = ">bar\n-----UACGUAGCC---------\n>foo\n---GCUACGUAGCU---------\n>seq_0\nACUGCUAGCUAGUAGCGUACGUA\n>seq_1\n---GCUACGUAGCUAC-------\n>seq_2\nGCGGCUAUUAGAUCGUA------"
build_tree_seqs_short = """>muscle_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>muscle_test_seqs_1
GACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>muscle_test_seqs_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>muscle_test_seqs_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>muscle_test_seqs_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>muscle_test_seqs_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>muscle_test_seqs_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>muscle_test_seqs_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>muscle_test_seqs_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>muscle_test_seqs_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
build_tree_seqs_long = """>muscle_test_seqs_0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AGCTTTAAATCATGCCAGTG
>muscle_test_seqsaaaaaaaa_1
GACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
TGCTTTCAATAATGCCAGTG
>muscle_test_seqsaaaaaaaa_2
AACCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
TGCTTTGAATCATGCCAGTA
>muscle_test_seqsaaaaaaaa_3
AAACCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
TGCTTTACATCATGCAAGTG
>muscle_test_seqsaaaaaaaa_4
AACCGCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
TGCTTTAAATCATGCCAGTG
>muscle_test_seqsaaaaaaaa_5
AACCCCCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
TGCTTTAAATCATGCCAGTT
>muscle_test_seqsaaaaaaaa_6
GACCCCCGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
TACTTTAGATCATGCCGGTG
>muscle_test_seqsaaaaaaaa_7
AACCCCCACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
TGCTTTAAATCATGCCAGTG
>muscle_test_seqsaaaaaaaa_8
AACCCCCACGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
TGCATTAAATCATGCCAGTG
>muscle_test_seqsaaaaaaaa_9
AAGCCCCACGGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
TGCTTTAAATCCTGACAGCG
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_nupack.py 000644 000765 000024 00000005150 12024702176 022115 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.nupack import Nupack
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class NupackTest(TestCase):
"""Tests for Nupack application controller"""
def setUp(self):
self.input = nupack_input
def test_input_as_lines(self):
"""Test nupack input as lines"""
n = Nupack(InputHandler='_input_as_lines')
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in nupack_stdout])
res = n(self.input)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_input_as_string(self):
"""Test nupack input as string"""
n = Nupack()
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in nupack_stdout])
f = open('/tmp/single.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = n('/tmp/single.fasta')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('/tmp/single.fasta')
def test_get_result_path(self):
"""Tests nupack result path"""
n = Nupack(InputHandler='_input_as_lines')
res = n(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus',
'pair','ene'])
assert res['pair'] is not None
assert res['ene'] is not None
res.cleanUp()
nupack_input = ['>seq1\n',
'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n',
'\n']
nupack_stdout = ['****************************************************************\n',
'NUPACK 1.2\n', 'Copyright 2003, 2004 by Robert M. Dirks & Niles A. Pierce\n',
'California Institute of Technology\n', 'Pasadena, CA 91125 USA\n', '\n',
'Last Modified: 03/18/2004\n',
'****************************************************************\n',
'\n', '\n', 'Fold.out Version 1.2: Complexity O(N^5) (pseudoknots enabled)\n',
'Reading Input File...\n', 'Sequence Read.\n', 'Energy Parameters Loaded\n',
'SeqLength = 71\n', 'Sequence and a Minimum Energy Structure:\n',
'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n',
'.....((..((.((...{.{{{{{{.{.{{{{{{{{......)).))..))..}}}}}}}}}.}}}}}}.}\n',
'mfe = -23.30 kcal/mol\n', 'pseudoknotted!\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_parameters.py 000644 000765 000024 00000061276 12024702176 023012 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.app.parameters import Parameter, FlagParameter, ValuedParameter,\
MixedParameter,Parameters, _find_synonym, ParameterError, FilePath
__author__ = "Sandra Smit and Greg Caporaso"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Greg Caporaso", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Development"
class FlagParameterTests(TestCase):
""" Tests of the FlagParameter class """
def setUp(self):
"""Setup some variables for the tests to use """
self.p_modify_prefix = [FlagParameter(Name='d',Prefix='-'),\
FlagParameter(Name='d',Prefix='--'),\
FlagParameter(Name='d',Prefix='')]
self.p_modify_name = [FlagParameter(Name='d',Prefix='-'),\
FlagParameter(Name='D',Prefix='-'),\
FlagParameter(Name=4,Prefix='-'),\
FlagParameter(Name='abcdef',Prefix='-')]
self.p_On = [FlagParameter(Name='d',Prefix='-',Value=True),\
FlagParameter(Name='d',Prefix='-',Value=5),\
FlagParameter(Name='d',Prefix='-',Value=[1]),\
FlagParameter(Name='d',Prefix='-',Value='F')]
self.p_Off = [FlagParameter(Name='d',Prefix='-',Value=False),\
FlagParameter(Name='d',Prefix='-',Value=None),\
FlagParameter(Name='d',Prefix='-',Value=[]),\
FlagParameter(Name='d',Prefix='-',Value=0),\
FlagParameter(Name='d',Prefix='-',Value='')]
self.ID_tests = [FlagParameter(Name='d',Prefix='-'),\
FlagParameter(Name='d',Prefix=''),\
FlagParameter(Name='',Prefix='-'),\
FlagParameter(Name=4,Prefix='-'),\
FlagParameter(Name=None,Prefix='-'),\
FlagParameter(Name=4,Prefix=None),\
FlagParameter(Name='abcdef',Prefix='-')]
def test_init(self):
"""FlagParameter: init functions as expected """
param = FlagParameter(Name='a',Prefix='-',Value=42)
self.assertEqual(param.Name,'a')
self.assertEqual(param.Prefix,'-')
self.assertEqual(param.Value,42)
self.assertEqual(param.Delimiter,None)
self.assertEqual(param.Quote,None)
self.assertEqual(param.Id,'-a')
def test_init_defaults(self):
"""FlagParameter: init functions as expected with default values"""
p = FlagParameter(Name='a',Prefix='-')
self.assertEqual(p.Name,'a')
self.assertEqual(p.Prefix,'-')
self.assertEqual(p.Value,False)
self.assertEqual(p.Delimiter,None)
self.assertEqual(p.Quote,None)
self.assertEqual(p.Id,'-a')
def test_get_id(self):
"""FlagParameter: _get_id functions as expected """
expected_results = ['-d','d','-','-4','-','4','-abcdef']
for param,exp in zip(self.ID_tests,expected_results):
self.assertEqual(param._get_id(),exp)
def test_eq(self):
"""FlagParameter: eq functions as expected """
p1 = FlagParameter(Name='a',Prefix='-',Value=True)
p2 = FlagParameter(Name='a',Prefix='-',Value=True)
p3 = FlagParameter(Name='a',Prefix='-')
p4 = FlagParameter(Name='i',Prefix='-',Value=True)
p5 = FlagParameter(Name='a',Prefix='--',Value=True)
assert p1 == p2
assert not p1 == p3
assert not p1 == p4
assert not p1 == p5
assert not p3 == p4
assert not p3 == p5
assert not p4 == p5
def test_ne(self):
"""FlagParameter: ne functions as expected """
p1 = FlagParameter(Name='a',Prefix='-',Value=True)
p2 = FlagParameter(Name='a',Prefix='-',Value=True)
p3 = FlagParameter(Name='a',Prefix='-')
p4 = FlagParameter(Name='i',Prefix='-',Value=True)
p5 = FlagParameter(Name='a',Prefix='--',Value=True)
assert not p1 != p2
assert p1 != p3
assert p1 != p4
assert p1 != p5
assert p3 != p4
assert p3 != p5
assert p4 != p5
def test_isOn_True(self):
"""FlagParameter: isOn functions as expected with True Values """
for param in self.p_On:
assert param.isOn()
def test_isOn_False(self):
"""FlagParameter: isOn functions as expected with False Values """
for param in self.p_Off:
assert not param.isOn()
def test_isOff_True(self):
"""FlagParameter: isOff functions as expected with True values """
for param in self.p_Off:
assert param.isOff()
def test_isOff_False(self):
"""FlagParameter: isOff functions as expected with False values """
for param in self.p_On:
assert not param.isOff()
def test_on(self):
"""FlagParameter: on functions as expected """
for param in self.p_On + self.p_Off:
param.on()
assert param.isOn()
def test_off(self):
"""FlagParameter: off functions as expected """
for param in self.p_On + self.p_Off:
param.off()
assert param.isOff()
def test_str_modify_prefix(self):
"""FlagParameter: str functions as expected with different prefixes """
expected_results = ['-d','--d','d']
for param,exp in zip(self.p_modify_prefix,expected_results):
param.on()
self.assertEqual(str(param),exp)
def test_str_modify_name(self):
"""FlagParameter: str functions as expected with different names """
expected_results = ['-d','-D','-4','-abcdef']
for param,exp in zip(self.p_modify_name,expected_results):
param.on()
self.assertEqual(str(param),exp)
class ValuedParameterTests(TestCase):
""" Tests of the ValuedParameter class """
constructor = ValuedParameter
s = 'Valued'
def setUp(self):
"""Setup some variables for the tests to use """
self.p_modify_prefix = [self.constructor(Name='d',Prefix='-'),\
self.constructor(Name='d',Prefix='--'),\
self.constructor(Name='d',Prefix='')]
self.p_modify_name = [self.constructor(Name='d',Prefix='-'),\
self.constructor(Name='D',Prefix='-'),\
self.constructor(Name=4,Prefix='-'),\
self.constructor(Name='abcdef',Prefix='-')]
self.p_On = [self.constructor(Name='d',Prefix='-',Value=True),\
self.constructor(Name='d',Prefix='-',Value=5),\
self.constructor(Name='d',Prefix='-',Value=[1]),\
self.constructor(Name='d',Prefix='-',Value=False),\
self.constructor(Name='d',Prefix='-',Value='F')]
self.p_Off = [self.constructor(Name='d',Prefix='-',Value=None)]
self.p_full = [self.constructor(Name='a',Prefix='-',\
Value=42,Delimiter=' ',Quote='\'')]
self.p_default = [self.constructor(Name='a',Prefix='-')]
self.p_modified_prefix = [self.constructor(Name='d',Prefix='-'),\
self.constructor(Name='d',Prefix='--'),\
self.constructor(Name='d',Prefix='')]
self.p_modified_name = [self.constructor(Name='d',Prefix='-'),\
self.constructor(Name='D',Prefix='-'),\
self.constructor(Name=4,Prefix='-'),\
self.constructor(Name='abcdef',Prefix='-')]
self.p_modified_delimiter =\
[self.constructor(Name='d',Prefix='-',Value=42),\
self.constructor(Name='d',Prefix='-',Value=42,Delimiter=''),\
self.constructor(Name='d',Prefix='-',Value=42,Delimiter=' '),\
self.constructor(Name='d',Prefix='-',Value=42,Delimiter=9),\
self.constructor(Name='d',Prefix='-',Value=42,Delimiter='=')]
self.p_modified_value =\
[self.constructor(Name='d',Prefix='-',Value=42,Delimiter=' '),\
self.constructor(Name='d',Prefix='-',Value='pbl',Delimiter=' '),\
self.constructor(Name='d',Prefix='-',Value='2-2',Delimiter=' '),\
self.constructor(Name='d',Prefix='-',Value='evo/t.txt',\
Delimiter=' '),\
self.constructor(Name='d',Prefix='-',Value='\'',Delimiter=' ')]
self.p_modified_quote =\
[self.constructor(Name='d',Prefix='-',Value=42,Quote=''),\
self.constructor(Name='d',Prefix='-',Value=42),\
self.constructor(Name='d',Prefix='-',Value=42,Quote=' '),\
self.constructor(Name='d',Prefix='-',Value=42,Quote='\''),\
self.constructor(Name='d',Prefix='-',Value=42,Quote='\"'),\
self.constructor(Name='d',Prefix='-',Value=42,Quote='x')]
self.ID_tests = [self.constructor(Name='d',Prefix='-'),\
self.constructor(Name='d',Prefix=''),\
self.constructor(Name='',Prefix='-'),\
self.constructor(Name=4,Prefix='-'),\
self.constructor(Name=None,Prefix='-'),\
self.constructor(Name=4,Prefix=None),\
self.constructor(Name='abcdef',Prefix='-')]
self.p_modified_is_path =\
[self.constructor(Name='d',Prefix='-',Delimiter=' ',\
Value='test.txt',IsPath=True),\
self.constructor(Name='d',Prefix='-',Delimiter=' ',\
Value='test.txt',IsPath=False),\
self.constructor(Name='d',Prefix='-',Delimiter=' ',\
Value='test.txt',Quote='"',IsPath=True)]
def test_init(self):
"""Parameter: init functions as expected """
for param in self.p_full:
self.assertEqual(param.Name,'a')
self.assertEqual(param.Prefix,'-')
self.assertEqual(param.Value,42)
self.assertEqual(param.Delimiter,' ')
self.assertEqual(param.Quote,'\'')
self.assertEqual(param.Id,'-a')
def test_init_defaults(self):
"""Parameter: init functions as expected with default values"""
for p in self.p_default:
self.assertEqual(p.Name,'a')
self.assertEqual(p.Prefix,'-')
self.assertEqual(p.Value,None)
self.assertEqual(p.Delimiter,None)
self.assertEqual(p.Quote,None)
self.assertEqual(p.Id,'-a')
def test_get_id(self):
"""Parameter: _get_id functions as expected """
expected_results = ['-d','d','-','-4','-','4','-abcdef']
for param,exp in zip(self.ID_tests,expected_results):
self.assertEqual(param._get_id(),exp)
def test_eq(self):
"""Parameter: eq functions as expected """
p1 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='=')
p2 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='=')
p3 = self.constructor(Name='dsf',Prefix='-',Value=42,Quote='\'',\
Delimiter='=')
p4 = self.constructor(Name='a',Prefix='--',Value=42,Quote='\'',\
Delimiter='=')
p5 = self.constructor(Name='a',Prefix='-',Value=942,Quote='\'',\
Delimiter='=')
p6 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\"',\
Delimiter='=')
p7 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='!!!')
p8 = self.constructor(Name='wwwww',Prefix='-------')
p9 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='=',IsPath=True)
assert p1 == p2
assert not p1 == p3
assert not p1 == p4
assert not p1 == p5
assert not p1 == p6
assert not p1 == p7
assert not p1 == p8
assert not p1 == p9
# test default setting
p5.Value = 42
assert not p1 == p5
def test_ne(self):
"""Parameter: ne functions as expected """
p1 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='=')
p2 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='=')
p3 = self.constructor(Name='dsf',Prefix='-',Value=42,Quote='\'',\
Delimiter='=')
p4 = self.constructor(Name='a',Prefix='--',Value=42,Quote='\'',\
Delimiter='=')
p5 = self.constructor(Name='a',Prefix='-',Value=942,Quote='\'',\
Delimiter='=')
p6 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\"',\
Delimiter='=')
p7 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='!!!')
p8 = self.constructor(Name='wwwww',Prefix='-------')
p9 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='=',IsPath=True)
assert not p1 != p2
assert p1 != p3
assert p1 != p4
assert p1 != p5
assert p1 != p6
assert p1 != p7
assert p1 != p8
assert p1 != p9
# test default setting
p5.Value = 42
assert p1 != p5
def test_get_default(self):
"""Parameter: default behaves as expected """
p1 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='=')
self.assertEqual(p1._get_default(),42)
p1.Value = 43
self.assertEqual(p1._get_default(),42)
def test_get_default_w_IsPath(self):
"""Parameter: default is a FilePath object when IsPath is set """
p = self.constructor(Name='a',Prefix='-',Value='test.txt',Quote='\'',\
Delimiter='=',IsPath=True)
self.assertEqual(p._get_default(),'test.txt')
self.assertEqual(p.Default,'test.txt')
p.Value = 'test2.txt'
self.assertEqual(p._get_default(),'test.txt')
self.assertEqual(p.Default,'test.txt')
assert isinstance(p._get_default(),FilePath)
assert isinstance(p.Default,FilePath)
def test_reset(self):
"""Parameter: reset correctly set Value to _default """
p1 = self.constructor(Name='a',Prefix='-',Value=42,Quote='\'',\
Delimiter='=')
p1.Value=43
self.assertNotEqual(p1.Default,p1.Value)
p1.reset()
self.assertEqual(p1.Default,p1.Value)
def test_isOn_True(self):
"""Parameter: isOn functions as expected with True Values """
for param in self.p_On:
assert param.isOn()
def test_isOn_False(self):
"""Parameter: isOn functions as expected with False Values """
for param in self.p_Off:
assert not param.isOn()
def test_isOff_True(self):
"""Parameter: isOff functions as expected with True values """
for param in self.p_Off:
assert param.isOff()
def test_isOff_False(self):
"""Parameter: isOff functions as expected with False values """
for param in self.p_On:
assert not param.isOff()
def test_on(self):
"""Parameter: on functions as expected """
for param in self.p_On + self.p_Off:
param.on('a')
assert param.isOn()
p = self.p_On[0]
self.assertRaises(ParameterError,p.on,None)
def test_off(self):
"""Parameter: off functions as expected """
for param in self.p_On + self.p_Off:
param.off()
assert param.isOff()
def test_str_off(self):
"""Parameter: str() prints empty string when off """
for p in self.p_Off:
self.assertEqual(str(p),'')
def test_str_modify_prefix(self):
"""Parameter: str functions as expected with different prefixes """
expected_results = ['-d','--d','d']
for param,exp in zip(self.p_modified_prefix,expected_results):
param.on('')
self.assertEqual(str(param),exp)
def test_str_modify_name(self):
"""Parameter: str functions as expected with different names """
expected_results = ['-d','-D','-4','-abcdef']
for param,exp in zip(self.p_modified_name,expected_results):
param.on('')
self.assertEqual(str(param),exp)
def test_str_modify_delimiter(self):
"""Parameter: str functions as expected with different delimiter """
expected_results = ['-d42','-d42','-d 42','-d942', '-d=42']
for param,exp in zip(self.p_modified_delimiter,expected_results):
self.assertEqual(str(param),exp)
def test_str_modify_values(self):
"""Parameter: str functions as expected with different values """
expected_results = ['-d 42',\
'-d pbl','-d 2-2','-d evo/t.txt', '-d \'']
for param,exp in zip(self.p_modified_value,expected_results):
self.assertEqual(str(param),exp)
def test_str_modify_quotes(self):
"""Parameter: str functions as expected with different quotes """
expected_results = ['-d42','-d42','-d 42 ','-d\'42\'',\
'-d\"42\"','-dx42x']
for param,exp in zip(self.p_modified_quote,expected_results):
self.assertEqual(str(param),exp)
def test_str_modify_is_path(self):
"""Parameter: str functions as expected with different IsPath """
expected_results = ['-d "test.txt"','-d test.txt','-d "test.txt"']
for param,exp in zip(self.p_modified_is_path,expected_results):
self.assertEqual(str(param),exp)
def test_str_full(self):
"""Parameter: str functions as expected with all values non-default """
for p in self.p_full:
self.assertEqual(str(p),'-a \'42\'')
class MixedParameterTests(ValuedParameterTests):
""" Tests of the MixedParameter class """
constructor = MixedParameter
def setUp(self):
"""Setup some variables for the tests to use """
super(MixedParameterTests,self).setUp()
self.p_On = [self.constructor(Name='d',Prefix='-',Value=True),\
self.constructor(Name='d',Prefix='-',Value=5),\
self.constructor(Name='d',Prefix='-',Value=[1]),\
self.constructor(Name='d',Prefix='-',Value=None),\
self.constructor(Name='d',Prefix='-',Value='F')]
self.p_Off = [self.constructor(Name='d',Prefix='-',Value=False)]
# This is different from the superclass variable b/c we need to make
# sure that specifying IsPath with Value=None functions as expected
self.p_modified_is_path =\
[self.constructor(Name='d',Prefix='-',Delimiter=' ',\
Value='test.txt',IsPath=True),\
self.constructor(Name='d',Prefix='-',Delimiter=' ',\
Value='test.txt',Quote='"',IsPath=True),\
self.constructor(Name='d',Prefix='-',Delimiter=' ',\
Value='test.txt',IsPath=False),\
self.constructor(Name='d',Prefix='-',Delimiter=' ',\
Value=None,IsPath=True),\
self.constructor(Name='d',Prefix='-',Delimiter=' ',\
Value=None,IsPath=False)]
def test_on(self):
"""Parameter: on functions as expected """
for param in self.p_On + self.p_Off:
param.on('a')
assert param.isOn()
p = self.p_On[0]
self.assertRaises(ParameterError,p.on,False)
def test_init_defaults(self):
"""MixedParameter: init functions as expected with default values"""
for p in self.p_default:
self.assertEqual(p.Name,'a')
self.assertEqual(p.Prefix,'-')
self.assertEqual(p.Value,False)
self.assertEqual(p.Delimiter,None)
self.assertEqual(p.Quote,None)
self.assertEqual(p.Id,'-a')
self.assertEqual(p.IsPath,False)
def test_str_all_modes(self):
"""MixedParameter: str() functions in various modes """
p = MixedParameter(Prefix='-',Name='d',Delimiter='=',Quote=']')
self.assertEqual(str(p),'')
p.on()
self.assertEqual(str(p),'-d')
p.on('a')
self.assertEqual(str(p),'-d=]a]')
def test_str_modify_is_path(self):
"""MixedParameter: str functions as expected with different IsPath """
# This is different from the superclass test b/c we need to make
# sure that specifying IsPath with Value=None functions as expected
expected_results = ['-d "test.txt"','-d "test.txt"',\
'-d test.txt','-d','-d']
for param,exp in zip(self.p_modified_is_path,expected_results):
self.assertEqual(str(param),exp)
class ParametersTests(TestCase):
"""Tests of the Parameters class"""
def setUp(self):
self.fp = FlagParameter(Prefix='-',Name='d')
self.vp = ValuedParameter(Name='p',Prefix='-',Value=[1])
self.mp = MixedParameter(Prefix='--',Name='k',Delimiter=' ')
self.all_params = {self.fp.Id:self.fp, self.vp.Id:self.vp,
self.mp.Id:self.mp}
self.p1 = Parameters()
self.p2 = Parameters(self.all_params)
self._synonyms = {'Pino':'-p','K':'k'}
self.p3 = Parameters(self.all_params,self._synonyms)
def test_init(self):
"""Parameters: init functions as expected"""
self.assertEqualItems(self.p1,{})
self.assertEqualItems(self.p2,self.all_params)
self.assertEqualItems(self.p3,self.all_params)
def test_lookup(self):
"""Parameters: test ability to lookup """
self.assertEqual(self.p2['-p'],self.vp)
self.assertEqual(self.p3['Pino'],self.vp)
def test_immutability(self):
"""Parameters: attempt to modify object raises error """
self.assertRaises(NotImplementedError,self.p2.__setitem__,9)
self.assertRaises(NotImplementedError,self.p2.setdefault,9)
self.assertRaises(NotImplementedError,self.p2.update,{9:0})
self.assertRaises(NotImplementedError,self.p2.__delitem__,'-p')
def test_all_off(self):
"""Parameters: all_off() should turn all parametes off"""
p = self.p2
for v in p.values():
try:
v.on(3)
except TypeError:
v.on()
assert v.isOn()
p.all_off()
for v in p.values():
assert v.isOff()
def parametersTests(TestCase):
"""Tests of top-level functions """
def test_find_synonym(self):
"""_find_synonym() functions as expected """
f = _find_synonym({'a':'-a'})
self.assertEqual(f('a'),'-a')
class FilePathTests(TestCase):
""" Tests of the FilePath class """
def setUp(self):
""" Initialize variables to be used by tests """
self.filename = 'filename.txt'
self.relative_dir_path = 'a/relative/path/'
self.relative_dir_path_no_trailing_slash = 'a/relative/path'
self.relative_file_path = 'a/relative/filepath.txt'
self.absolute_dir_path = '/absolute/path/'
self.absolute_file_path = '/absolute/filepath.txt'
self.all_paths = [self.filename, self.relative_dir_path,\
self.relative_file_path, self.absolute_dir_path,\
self.absolute_file_path]
def test_init(self):
"""FilePath: initialization returns w/o error """
for p in self.all_paths:
self.assertEqual(FilePath(p),p)
self.assertEqual(FilePath(''),'')
def test_str(self):
"""FilePath: str wraps path in quotes """
# Do one explicit test (for sanity), then automatically run
# through the examples
self.assertEqual(str(FilePath(self.filename)),'"filename.txt"')
for p in self.all_paths:
self.assertEqual(str(FilePath(p)),'"' + p + '"')
def test_str_path_is_None(self):
"""FilePath: str return empty string when path is None """
self.assertEqual(str(FilePath(None)),'')
def test_add(self):
"""FilePath: add (or joining of paths) functions as expected """
actual = FilePath(self.relative_dir_path) + FilePath(self.filename)
expected = FilePath('a/relative/path/filename.txt')
self.assertEqual(actual,expected)
# result is a FilePath
assert isinstance(actual,FilePath)
# appending a string to a FilePath results in a FilePath
actual = FilePath(self.relative_dir_path) + 'filename.txt'
expected = FilePath('a/relative/path/filename.txt')
self.assertEqual(actual,expected)
# result is a FilePath
assert isinstance(actual,FilePath)
def test_FilePath_identity_preserved(self):
"""FilePath: trivial actions on FilePaths yeild original FilePath
"""
p = FilePath(self.filename)
# Creating FilePath from FilePath results in FilePath
# equal to original
self.assertEqual(FilePath(p),p)
for p in self.all_paths:
self.assertEqual(FilePath(p),p)
# Appending an empty FilePath to a FilePath results in FilePath
# equal to original
self.assertEqual(p+FilePath(''),p)
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_parsinsert.py 000644 000765 000024 00000010424 12024702176 023026 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for ParsInsert v1.03 application controller."""
__author__ = "Jesse Stombaugh"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jesse Stombaugh"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jesse Stombaugh"
__email__ = "jesse.stombaugh@colorado.edu"
__status__ = "Production"
from shutil import rmtree
from cogent.util.unit_test import TestCase, main
from cogent.app.parsinsert import ParsInsert, insert_sequences_into_tree
from cogent.core.alignment import Alignment
from cogent.parse.fasta import MinimalFastaParser
from cogent.parse.tree import DndParser
from cogent.core.moltype import DNA
from cogent.app.util import get_tmp_filename
from os.path import splitext
from os import getcwd, remove, rmdir, mkdir
class ParsInsertTests(TestCase):
def setUp(self):
# create a list of files to cleanup
self._paths_to_clean_up = []
self._dirs_to_clean_up = []
# load query seqs
self.seqs = Alignment(MinimalFastaParser(QUERY_SEQS.split()))
# generate temp filename
tmp_dir='/tmp'
self.outfile = get_tmp_filename(tmp_dir)
# create and write out reference sequence file
self.outfasta=splitext(self.outfile)[0]+'.fasta'
fastaout=open(self.outfasta,'w')
fastaout.write(REF_SEQS)
fastaout.close()
self._paths_to_clean_up.append(self.outfasta)
# create and write out starting tree file
self.outtree=splitext(self.outfile)[0]+'.tree'
treeout=open(self.outtree,'w')
treeout.write(REF_TREE)
treeout.close()
self._paths_to_clean_up.append(self.outtree)
def tearDown(self):
"""cleans up all files initially created"""
# remove the tempdir and contents
map(remove,self._paths_to_clean_up)
map(rmdir,self._dirs_to_clean_up)
def test_base_command(self):
"""Base command-calls"""
app = ParsInsert()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','ParsInsert']))
def test_change_working_dir(self):
"""Change working dir"""
app = ParsInsert(WorkingDir='/tmp/ParsInsertTest')
self.assertEqual(app.BaseCommand, \
''.join(['cd "','/tmp/ParsInsertTest',\
'/"; ','ParsInsert']))
rmtree('/tmp/ParsInsertTest')
def test_insert_sequences_into_tree(self):
"""Inserts sequences into Tree"""
# define log fp
log_fp='/tmp/parsinsert.log'
self._paths_to_clean_up.append(log_fp)
# define tax assignment values fp
tax_assign_fp='/tmp/tax_assignments.log'
self._paths_to_clean_up.append(tax_assign_fp)
# set the reference alignment and starting tree
param={
'-t':self.outtree,
'-s':self.outfasta,
'-l':log_fp,
'-o':tax_assign_fp
}
seqs, align_map = self.seqs.toPhylip()
# insert sequences into tree
tree = insert_sequences_into_tree(seqs, DNA, params=param)
# rename tips back to query names
for node in tree.tips():
if node.Name in align_map:
node.Name = align_map[node.Name]
self.assertEqual(tree.getNewick(with_distances=True),exp_tree)
QUERY_SEQS= """\
>6
TGCATGTCAGTATAGCTTTGGTGAAACTGCGAATGGCTCATTAAATCAGT
>7
TGCATGTCAGTATAACTTTGGTGAAACTGCGAATGGCTCATTAAATCAGT
"""
REF_SEQS= """\
>seq0000011
TGCATGTCAGTATAGCTTTAGTGAAACTGCGAATGGCTCATTAAATCAGT
>seq0000012
TGCATGTCAGTATAGCTTTAGTGAAACTGCGAATGGCTNNTTAAATCAGT
>seq0000013
TGCATGTCAGTATAGCATTAGTGAAACTGCGAATGGCTCATTAAATCAGT
>seq0000014
TCCATGTCAGTATAACTTTGGTGAAACTGCGAATGGCTCATTAAATCAGG
>seq0000015
NNNNNNNNNNTATATCTTATGTGAAACTTCGAATGCCTCATTAAATCAGT
"""
REF_TREE="""((seq0000014:0.08408,seq0000015:0.13713)0.609:0.00215,seq0000013:0.02032,(seq0000011:0.00014,seq0000012:0.00014)0.766:0.00015);
"""
exp_tree = """((seq0000014:0.08408,seq0000015:0.13713,7:0.02027):0.00215,seq0000013:0.02032,(seq0000011:0.00014,seq0000012:0.00014,6:0.02027):0.00015):0.0;"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_pfold.py 000644 000765 000024 00000036713 12024702176 021751 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Provides Tests for pfold application controller.
IMPORTANT!!!!!
'dir' variable must be set in pfold app controller file for application to work!
"""
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.pfold import fasta2col,findphyl,mltree,scfg
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class Fasta2colTest(TestCase):
"""Tests for fasta2col application controller"""
def setUp(self):
self.input = f2c_input
def test_stdout_input_as_lines(self):
"""Test fasta2col stdout input as lines"""
c = fasta2col(InputHandler='_input_as_lines')
res = c(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test fasta2col stdout input as string"""
c = fasta2col()
f = open('/tmp/single.col','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = c('/tmp/single.col')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/single.col')
def test_get_result_path(self):
"""Tests fasta2col result path"""
c = fasta2col(InputHandler='_input_as_lines')
res = c(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
class FindphylTest(TestCase):
"""Tests for findphyl application controller"""
def setUp(self):
self.input = fp_input
def test_input_as_lines(self):
"""Test findphyl input as lines"""
fp = findphyl(InputHandler='_input_as_lines')
res = fp(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test findphyl input as string"""
fp = findphyl()
f = open('/tmp/single.col','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = fp('/tmp/single.col')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/single.col')
def test_get_result_path(self):
"""Tests findphyl result path"""
fp = findphyl(InputHandler='_input_as_lines')
res = fp(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
class MltreeTest(TestCase):
"""Tests for Pfold application controller"""
def setUp(self):
self.input = ml_input
def test_input_as_lines(self):
"""Test mltree input as lines"""
m = mltree(InputHandler='_input_as_lines')
res = m(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test mltree input as string"""
m = mltree()
f = open('/tmp/single.col','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = m('/tmp/single.col')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/single.col')
def test_get_result_path(self):
"""Tests mltree result path"""
m = mltree(InputHandler='_input_as_lines')
res = m(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
class ScfgTest(TestCase):
"""Tests for scfg application controller"""
def setUp(self):
self.input = scfg_input
def test_input_as_lines(self):
"""Test scfg input as lines"""
s = scfg(InputHandler='_input_as_lines')
res = s(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test scfg input as string"""
s = scfg()
f = open('/tmp/single.col','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = s('/tmp/single.col')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/single.col')
def test_get_result_path(self):
"""Tests scfg result path"""
s = scfg(InputHandler='_input_as_lines')
res = s(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
f2c_input = ['>seq1\n',
'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n',
'\n']
f2c_stdout = ['; generated by fasta2col\n',
'; ============================================================\n',
'; TYPE RNA\n', '; COL 1 label\n',
'; COL 2 residue\n', '; COL 3 seqpos\n',
'; COL 4 alignpos\n', '; ENTRY seq1\n',
'; ----------\n', 'N G 1 1\n', 'N G 2 2\n',
'N C 3 3\n', 'N U 4 4\n', 'N A 5 5\n',
'N G 6 6\n', 'N A 7 7\n', 'N U 8 8\n',
'N A 9 9\n', 'N G 10 10\n', 'N C 11 11\n',
'N U 12 12\n', 'N C 13 13\n', 'N A 14 14\n',
'N G 15 15\n', 'N A 16 16\n', 'N U 17 17\n',
'N G 18 18\n', 'N G 19 19\n', 'N U 20 20\n',
'N A 21 21\n', 'N G 22 22\n', 'N A 23 23\n',
'N G 24 24\n', 'N C 25 25\n', 'N A 26 26\n',
'N G 27 27\n', 'N A 28 28\n', 'N G 29 29\n',
'N G 30 30\n', 'N A 31 31\n', 'N U 32 32\n',
'N U 33 33\n', 'N G 34 34\n', 'N A 35 35\n',
'N A 36 36\n', 'N G 37 37\n', 'N A 38 38\n',
'N U 39 39\n', 'N C 40 40\n', 'N C 41 41\n',
'N U 42 42\n', 'N U 43 43\n', 'N G 44 44\n',
'N U 45 45\n', 'N G 46 46\n', 'N U 47 47\n',
'N C 48 48\n', 'N G 49 49\n', 'N U 50 50\n',
'N C 51 51\n', 'N G 52 52\n', 'N G 53 53\n',
'N U 54 54\n', 'N U 55 55\n', 'N C 56 56\n',
'N G 57 57\n', 'N A 58 58\n', 'N U 59 59\n',
'N C 60 60\n', 'N C 61 61\n', 'N C 62 62\n',
'N G 63 63\n', 'N G 64 64\n', 'N C 65 65\n',
'N U 66 66\n', 'N C 67 67\n', 'N U 68 68\n',
'N G 69 69\n', 'N G 70 70\n', 'N C 71 71\n',
'; **********\n']
fp_input = f2c_stdout
fp_stdout = ['; generated by fasta2col\n',
'; ============================================================\n',
'; TYPE TREE\n', '; COL 1 label\n', '; COL 2 number\n', '; COL 3 name\n', '; COL 4 uplen\n',
'; COL 5 child\n', '; COL 6 brother\n',
'; ENTRY tree\n', '; root 1\n', '; ----------\n',
' N 1 seq1 0.000000 . .\n', '; **********\n',
'; TYPE RNA\n', '; COL 1 label\n',
'; COL 2 residue\n', '; COL 3 seqpos\n',
'; COL 4 alignpos\n', '; ENTRY seq1\n',
'; ----------\n', 'N G 1 1\n', 'N G 2 2\n',
'N C 3 3\n', 'N U 4 4\n', 'N A 5 5\n',
'N G 6 6\n', 'N A 7 7\n', 'N U 8 8\n',
'N A 9 9\n', 'N G 10 10\n', 'N C 11 11\n',
'N U 12 12\n', 'N C 13 13\n', 'N A 14 14\n',
'N G 15 15\n', 'N A 16 16\n', 'N U 17 17\n',
'N G 18 18\n', 'N G 19 19\n', 'N U 20 20\n',
'N A 21 21\n', 'N G 22 22\n', 'N A 23 23\n',
'N G 24 24\n', 'N C 25 25\n', 'N A 26 26\n',
'N G 27 27\n', 'N A 28 28\n', 'N G 29 29\n',
'N G 30 30\n', 'N A 31 31\n', 'N U 32 32\n',
'N U 33 33\n', 'N G 34 34\n', 'N A 35 35\n',
'N A 36 36\n', 'N G 37 37\n', 'N A 38 38\n',
'N U 39 39\n', 'N C 40 40\n', 'N C 41 41\n',
'N U 42 42\n', 'N U 43 43\n', 'N G 44 44\n',
'N U 45 45\n', 'N G 46 46\n', 'N U 47 47\n',
'N C 48 48\n', 'N G 49 49\n', 'N U 50 50\n',
'N C 51 51\n', 'N G 52 52\n', 'N G 53 53\n',
'N U 54 54\n', 'N U 55 55\n', 'N C 56 56\n',
'N G 57 57\n', 'N A 58 58\n', 'N U 59 59\n',
'N C 60 60\n', 'N C 61 61\n', 'N C 62 62\n',
'N G 63 63\n', 'N G 64 64\n', 'N C 65 65\n',
'N U 66 66\n', 'N C 67 67\n', 'N U 68 68\n',
'N G 69 69\n', 'N G 70 70\n', 'N C 71 71\n',
'; **********\n']
ml_input = fp_stdout
ml_stdout = ['; generated by fasta2col\n',
'; ============================================================\n',
'; TYPE TREE\n', '; COL 1 label\n',
'; COL 2 number\n', '; COL 3 name\n',
'; COL 4 uplen\n', '; COL 5 child\n',
'; COL 6 brother\n', '; ENTRY tree\n',
'; root 1\n', '; ----------\n',
' N 1 seq1 0.001000 . .\n', '; **********\n',
'; TYPE RNA\n', '; COL 1 label\n',
'; COL 2 residue\n', '; COL 3 seqpos\n',
'; COL 4 alignpos\n', '; ENTRY seq1\n',
'; ----------\n', 'N G 1 1\n', 'N G 2 2\n',
'N C 3 3\n', 'N U 4 4\n', 'N A 5 5\n',
'N G 6 6\n', 'N A 7 7\n', 'N U 8 8\n',
'N A 9 9\n', 'N G 10 10\n', 'N C 11 11\n',
'N U 12 12\n', 'N C 13 13\n', 'N A 14 14\n',
'N G 15 15\n', 'N A 16 16\n', 'N U 17 17\n',
'N G 18 18\n', 'N G 19 19\n', 'N U 20 20\n',
'N A 21 21\n', 'N G 22 22\n', 'N A 23 23\n',
'N G 24 24\n', 'N C 25 25\n', 'N A 26 26\n',
'N G 27 27\n', 'N A 28 28\n', 'N G 29 29\n',
'N G 30 30\n', 'N A 31 31\n', 'N U 32 32\n',
'N U 33 33\n', 'N G 34 34\n', 'N A 35 35\n',
'N A 36 36\n', 'N G 37 37\n', 'N A 38 38\n',
'N U 39 39\n', 'N C 40 40\n', 'N C 41 41\n',
'N U 42 42\n', 'N U 43 43\n', 'N G 44 44\n',
'N U 45 45\n', 'N G 46 46\n', 'N U 47 47\n',
'N C 48 48\n', 'N G 49 49\n', 'N U 50 50\n',
'N C 51 51\n', 'N G 52 52\n', 'N G 53 53\n',
'N U 54 54\n', 'N U 55 55\n', 'N C 56 56\n',
'N G 57 57\n', 'N A 58 58\n', 'N U 59 59\n',
'N C 60 60\n', 'N C 61 61\n', 'N C 62 62\n',
'N G 63 63\n', 'N G 64 64\n', 'N C 65 65\n',
'N U 66 66\n', 'N C 67 67\n', 'N U 68 68\n',
'N G 69 69\n', 'N G 70 70\n', 'N C 71 71\n',
'; **********\n']
scfg_input = ml_stdout
scfg_stdout = ['; generated by fasta2col\n',
'; ============================================================\n',
'; TYPE TREE\n', '; COL 1 label\n',
'; COL 2 number\n', '; COL 3 name\n',
'; COL 4 uplen\n', '; COL 5 child\n',
'; COL 6 brother\n', '; ENTRY tree\n',
'; root 1\n', '; ----------\n',
' N 1 seq1 0.001000 . .\n', '; **********\n',
'; TYPE RNA\n', '; COL 1 label\n',
'; COL 2 residue\n', '; COL 3 seqpos\n',
'; COL 4 alignpos\n', '; COL 5 align_bp\n',
'; COL 6 certainty\n', '; ENTRY seq1\n',
'; ----------\n', 'N G 1 1 . 0.8723\n',
'N G 2 2 71 0.5212\n', 'N C 3 3 70 0.5697\n',
'N U 4 4 69 0.5377\n', 'N A 5 5 68 0.5193\n',
'N G 6 6 67 0.4899\n', 'N A 7 7 . 0.6499\n',
'N U 8 8 . 0.9159\n', 'N A 9 9 . 0.7860\n',
'N G 10 10 . 0.4070\n', 'N C 11 11 . 0.3208\n',
'N U 12 12 . 0.4499\n', 'N C 13 13 . 0.5170\n',
'N A 14 14 . 0.8507\n', 'N G 15 15 . 0.8156\n',
'N A 16 16 . 0.8715\n', 'N U 17 17 . 0.8722\n',
'N G 18 18 . 0.7489\n', 'N G 19 19 . 0.7477\n',
'N U 20 20 . 0.7500\n', 'N A 21 21 . 0.7109\n',
'N G 22 22 . 0.3999\n', 'N A 23 23 . 0.3800\n',
'N G 24 24 . 0.3241\n', 'N C 25 25 . 0.3072\n',
'N A 26 26 . 0.7266\n', 'N G 27 27 . 0.5672\n',
'N A 28 28 . 0.4695\n', 'N G 29 29 41 0.5402\n',
'N G 30 30 40 0.5552\n', 'N A 31 31 39 0.5167\n',
'N U 32 32 38 0.4277\n', 'N U 33 33 . 0.4967\n',
'N G 34 34 . 0.7119\n', 'N A 35 35 . 0.7504\n',
'N A 36 36 . 0.8149\n', 'N G 37 37 . 0.6416\n',
'N A 38 38 32 0.4277\n', 'N U 39 39 31 0.5167\n',
'N C 40 40 30 0.5552\n', 'N C 41 41 29 0.5402\n',
'N U 42 42 . 0.4754\n', 'N U 43 43 . 0.6645\n',
'N G 44 44 . 0.7777\n', 'N U 45 45 . 0.8122\n',
'N G 46 46 . 0.6969\n', 'N U 47 47 . 0.6836\n',
'N C 48 48 . 0.5963\n', 'N G 49 49 . 0.4748\n',
'N U 50 50 . 0.5209\n', 'N C 51 51 . 0.4149\n',
'N G 52 52 . 0.3754\n', 'N G 53 53 . 0.4969\n',
'N U 54 54 . 0.7206\n', 'N U 55 55 . 0.7112\n',
'N C 56 56 . 0.5039\n', 'N G 57 57 . 0.5171\n',
'N A 58 58 . 0.5683\n', 'N U 59 59 . 0.6093\n',
'N C 60 60 . 0.5462\n', 'N C 61 61 . 0.3332\n',
'N C 62 62 . 0.3746\n', 'N G 63 63 . 0.3898\n',
'N G 64 64 . 0.3047\n', 'N C 65 65 . 0.2899\n',
'N U 66 66 . 0.3037\n', 'N C 67 67 6 0.4899\n',
'N U 68 68 5 0.5193\n', 'N G 69 69 4 0.5377\n',
'N G 70 70 3 0.5697\n', 'N C 71 71 2 0.5212\n',
'; **********\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_pknotsrg.py 000644 000765 000024 00000004057 12024702176 022510 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.pknotsrg import PknotsRG
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class PknotsrgTest(TestCase):
"""Tests for Pknotsrg application controller"""
def setUp(self):
self.input = pknotsrg_input
def test_stdout_input_as_lines(self):
"""Test pknotsrg stdout input as lines"""
p = PknotsRG(InputHandler='_input_as_lines')
exp= '%s\n' % '\n'.join([str(i).strip('\n') for i in pknotsrg_stdout])
res = p(self.input)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test pknotsrg stdout input as string"""
p = PknotsRG()
exp= '%s\n' % '\n'.join([str(i).strip('\n') for i in pknotsrg_stdout])
f = open('/tmp/single.plain','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = p('/tmp/single.plain')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('/tmp/single.plain')
def test_get_result_path(self):
"""Tests pknotsrg result path"""
p = PknotsRG(InputHandler='_input_as_lines')
res = p(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
pknotsrg_input = ['GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n']
pknotsrg_stdout = ['GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n', '.((((((..((((........)))).(((((((...))))))).....(((((.......))))))))))) (-22.40)\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_pplacer.py 000644 000765 000024 00000017363 12024702176 022273 0 ustar 00jrideout staff 000000 000000 #!/bin/env python
__author__ = "Jesse Stombaugh"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jesse Stombaugh"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jesse Stombaugh"
__email__ = "jesse.stombaugh@colorado.edu"
__status__ = "Production"
from os import getcwd, remove, rmdir, mkdir
from os.path import splitext
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from random import randint
from cogent.app.pplacer import Pplacer, insert_sequences_into_tree
from cogent.app.util import ApplicationError,get_tmp_filename
from cogent.parse.fasta import MinimalFastaParser
from cogent.core.tree import PhyloNode
from cogent.core.moltype import RNA,DNA
from StringIO import StringIO
from cogent.core.alignment import Alignment
class Genericpplacer(TestCase):
def setUp(self):
'''setup the files for testing pplacer'''
# create a list of files to cleanup
self._paths_to_clean_up = []
self._dirs_to_clean_up = []
# get a tmp filename to use
basename=splitext(get_tmp_filename())[0]
# create and write out RAxML stats file
self.stats_fname=basename+'.stats'
stats_out=open(self.stats_fname,'w')
stats_out.write(RAXML_STATS)
stats_out.close()
self._paths_to_clean_up.append(self.stats_fname)
# create and write out reference sequence file
self.refseq_fname=basename+'_refseqs.fasta'
refseq_out=open(self.refseq_fname,'w')
refseq_out.write(REF_SEQS)
refseq_out.close()
self._paths_to_clean_up.append(self.refseq_fname)
# create and write out query sequence file
self.query_fname=basename+'_queryseqs.fasta'
query_out=open(self.query_fname,'w')
query_out.write(QUERY_SEQS)
query_out.close()
self._paths_to_clean_up.append(self.query_fname)
# create and write out starting tree file
self.tree_fname=basename+'.tre'
tree_out=open(self.tree_fname,'w')
tree_out.write(REF_TREE)
tree_out.close()
self._paths_to_clean_up.append(self.tree_fname)
def writeTmp(self, outname):
"""Write data to temp file"""
t = open(outname, "w+")
t.write(PHYLIP_FILE)
t.close()
#
def tearDown(self):
"""cleans up all files initially created"""
# remove the tempdir and contents
map(remove,self._paths_to_clean_up)
map(rmdir,self._dirs_to_clean_up)
class pplacerTests(Genericpplacer):
"""Tests for the pplacer application controller"""
def test_pplacer(self):
"""Base command-calls"""
app=Pplacer()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','pplacer']))
app.Parameters['--help'].on()
self.assertEqual(app.BaseCommand, \
''.join(['cd "',getcwd(),'/"; ','pplacer --help']))
def test_change_working_dir(self):
"""Change working dir"""
working_dir='/tmp/Pplacer'
self._dirs_to_clean_up.append(working_dir)
# define working directory for output
app = Pplacer(WorkingDir=working_dir)
self.assertEqual(app.BaseCommand, \
''.join(['cd "','/tmp/Pplacer','/"; ','pplacer']))
def test_insert_sequences_into_tree(self):
"""Inserts sequences into Tree"""
params={}
# generate temp filename for output
params["-r"] = self.refseq_fname
params["-t"] = self.tree_fname
params["-s"] = self.stats_fname
params["--out-dir"] = "/tmp"
aln_ref_query=MinimalFastaParser(StringIO(QUERY_SEQS))
aln = Alignment(aln_ref_query)
seqs, align_map = aln.toPhylip()
tree = insert_sequences_into_tree(seqs, DNA, params=params,
write_log=False)
# rename tips back to query names
for node in tree.tips():
if node.Name in align_map:
node.Name = align_map[node.Name]
self.assertEqual(tree.getNewick(with_distances=True), RESULT_TREE)
JSON_RESULT="""\
{"tree":
"((seq0000004:0.08408[0],seq0000005:0.13713[1])0.609:0.00215[2],seq0000003:0.02032[3],(seq0000001:0.00014[4],seq0000002:0.00014[5])0.766:0.00015[6]):0[7];",
"placements":
[
{"p":
[[0, -113.210938, 0.713818, 0.064504, 0.000006],
[1, -114.929894, 0.127954, 0.137122, 0.000007],
[2, -114.932766, 0.127587, 0.000008, 0.000006],
[6, -117.743534, 0.007675, 0.000141, 0.027211],
[3, -117.743759, 0.007674, 0.020310, 0.027207],
[4, -117.747386, 0.007646, 0.000131, 0.027266],
[5, -117.747396, 0.007646, 0.000131, 0.027266]
], "n": ["seq0000006"]
},
{"p": [[0, -113.476305, 1.000000, 0.035395, 0.000006]], "n":
["seq0000007"]
}
], "metadata":
{"invocation":
"pplacer -t %s -r %s -s %s --out-dir \/tmp %s"
}, "version": 1, "fields":
["edge_num", "likelihood", "like_weight_ratio", "distal_length",
"pendant_length"
]
}
""".replace('\n','').replace(' ','')
QUERY_SEQS= """\
>6
TGCATGTCAGTATAGCTTTGGTGAAACTGCGAATGGCTCATTAAATCAGT
>7
TGCATGTCAGTATAACTTTGGTGAAACTGCGAATGGCTCATTAAATCAGT
"""
REF_SEQS= """\
>seq0000011
TGCATGTCAGTATAGCTTTAGTGAAACTGCGAATGGCTCATTAAATCAGT
>seq0000012
TGCATGTCAGTATAGCTTTAGTGAAACTGCGAATGGCTNNTTAAATCAGT
>seq0000013
TGCATGTCAGTATAGCATTAGTGAAACTGCGAATGGCTCATTAAATCAGT
>seq0000014
TCCATGTCAGTATAACTTTGGTGAAACTGCGAATGGCTCATTAAATCAGG
>seq0000015
NNNNNNNNNNTATATCTTATGTGAAACTTCGAATGCCTCATTAAATCAGT
"""
REF_TREE="""((seq0000014:0.08408,seq0000015:0.13713)0.609:0.00215,seq0000013:0.02032,(seq0000011:0.00014,seq0000012:0.00014)0.766:0.00015);
"""
RESULT_TREE="""((((seq0000014:0.0353946,7:6.11352e-06):0.0291093,6:6.11352e-06):0.019576,seq0000015:0.13713)0.609:0.00215,seq0000013:0.02032,(seq0000011:0.00014,seq0000012:0.00014)0.766:0.00015);"""
RAXML_STATS="""
This is RAxML version 7.2.6 released by Alexandros Stamatakis in February 2010.
With greatly appreciated code contributions by:
Andre Aberer (TUM)
Simon Berger (TUM)
John Cazes (TACC)
Michael Ott (TUM)
Nick Pattengale (UNM)
Wayne Pfeiffer (SDSC)
Alignment has 18 distinct alignment patterns
Proportion of gaps and completely undetermined characters in this alignment: 4.80%
RAxML rapid hill-climbing mode
Using 1 distinct models/data partitions with joint branch length optimization
Executing 1 inferences on the original alignment using 1 distinct randomized MP trees
All free model parameters will be estimated by RAxML
ML estimate of 25 per site rate categories
Likelihood of final tree will be evaluated and optimized under GAMMA
GAMMA Model parameters will be estimated up to an accuracy of 0.1000000000 Log Likelihood units
Partition: 0
Alignment Patterns: 18
Name: No Name Provided
DataType: DNA
Substitution Matrix: GTR
RAxML was called as follows:
raxmlHPC -m GTRCAT -s test_raxml.phy -n results
Inference[0]: Time 0.072128 CAT-based likelihood -85.425107, best rearrangement setting 2
alpha[0]: 1.000000 rates[0] ac ag at cg ct gt: 0.000017 0.037400 0.859448 1.304301 0.000017 1.000000
Conducting final model optimizations on all 1 trees under GAMMA-based models ....
Inference[0] final GAMMA-based Likelihood: -107.575676 tree written to file /home/RAxML_result.results
Starting final GAMMA-based thorough Optimization on tree 0 likelihood -107.575676 ....
Final GAMMA-based Score of best tree -107.575676
Program execution info written to /home/RAxML_info.results
Best-scoring ML tree written to: /home/RAxML_bestTree.results
Overall execution time: 0.078965 secs or 0.000022 hours or 0.000001 days
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_raxml.py 000644 000765 000024 00000013263 12024702176 021763 0 ustar 00jrideout staff 000000 000000 #!/bin/env python
from os import getcwd, remove, rmdir, mkdir
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from cogent.app.raxml import Raxml,raxml_alignment, build_tree_from_alignment
from cogent.app.util import ApplicationError
from cogent.parse.phylip import get_align_for_phylip
from cogent.core.tree import PhyloNode
from cogent.core.moltype import RNA
from StringIO import StringIO
from cogent.util.misc import app_path
from subprocess import Popen, PIPE, STDOUT
__author__ = "Micah Hamady"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Micah Hamady", "Rob Knight", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Micah Hamady"
__email__ = "Micah Hamady"
__status__ = "Development"
class GenericRaxml(TestCase):
def setUp(self):
"""Check if Raxml version is supported for this test"""
acceptable_version = (7,0,3)
self.assertTrue(app_path('raxmlHPC'),
"raxmlHPC not found. This may or may not be a problem depending on "+\
"which components of QIIME you plan to use.")
command = "raxmlHPC -v | grep version"
proc = Popen(command,shell=True,universal_newlines=True,\
stdout=PIPE,stderr=STDOUT)
stdout = proc.stdout.read()
version_string = stdout.strip().split(' ')[4].strip()
try:
version = tuple(map(int,version_string.split('.')))
pass_test = version == acceptable_version
except ValueError:
pass_test = False
version_string = stdout
self.assertTrue(pass_test,\
"Unsupported raxmlHPC version. %s is required, but running %s." \
% ('.'.join(map(str,acceptable_version)), version_string))
"""Setup data for raxml tests"""
self.seqs1 = ['ACUGCUAGCUAGUAGCGUACGUA','GCUACGUAGCUAC',
'GCGGCUAUUAGAUCGUA']
self.labels1 = ['>1','>2','>3']
self.lines1 = flatten(zip(self.labels1,self.seqs1))
self.test_model = "GTRCAT"
self.align1 = get_align_for_phylip(StringIO(PHYLIP_FILE))
self.test_fn1 = "/tmp/raxml_test1.txt"
self.test_fn2 = "raxml_test1.txt"
self.test_fn1_space = "/tmp/raxml test1.txt"
def writeTmp(self, outname):
"""Write data to temp file"""
t = open(outname, "w+")
t.write(PHYLIP_FILE)
t.close()
class RaxmlTests(GenericRaxml):
"""Tests for the Raxml application controller"""
def test_raxml(self):
"""raxml BaseCommand should return the correct BaseCommand"""
r = Raxml()
self.assertEqual(r.BaseCommand, \
''.join(['cd \"',getcwd(),'/\"; ','raxmlHPC -e 0.1 -f d -c 50']))
r.Parameters['-s'].on('seq.nexus')
self.assertEqual(r.BaseCommand,\
''.join(['cd \"',getcwd(),'/\"; ',\
'raxmlHPC -e 0.1 -f d -c 50 -s seq.nexus']))
def test_raxml_params(self):
"""raxml should raise exception if missing required params"""
r = Raxml(WorkingDir="/tmp")
r.SuppressStdout = True
r.SuppressStderr = True
# raise error by default
self.assertRaises(ValueError, r)
# specify output name
r.Parameters['-n'].on("test_name")
self.assertRaises(ApplicationError, r)
# specify model
r.Parameters['-m'].on("GTRCAT")
self.assertRaises(ApplicationError, r)
r.Parameters['-s'].on(self.test_fn1)
self.assertRaises(ApplicationError, r)
self.writeTmp(self.test_fn1)
o = r()
o.cleanUp()
remove(self.test_fn1)
def test_raxml_from_file(self):
"""raxml should run correctly using filename"""
r = Raxml(WorkingDir="/tmp")
r.Parameters['-s'].on(self.test_fn1)
r.Parameters['-m'].on("GTRCAT")
r.Parameters['-n'].on("test_me")
# test with abs filename
cur_out = self.test_fn1
self.writeTmp(cur_out)
out = r()
out.cleanUp()
remove(cur_out)
# test with rel + working dir
r.Parameters['-s'].on(self.test_fn2)
r.Parameters['-n'].on("test_me2")
r.Parameters['-w'].on("/tmp/")
self.writeTmp(self.test_fn1)
out = r()
out.cleanUp()
remove(self.test_fn1)
r.Parameters['-s'].on("\"%s\"" % self.test_fn1_space)
r.Parameters['-n'].on("test_me3")
r.Parameters['-w'].on("/tmp/")
#print r.BaseCommand
self.writeTmp(self.test_fn1_space)
out = r()
out.cleanUp()
remove(self.test_fn1_space)
def test_raxml_alignment(self):
"""raxml_alignment should work as expected"""
phy_node, parsimony_phy_node, log_likelihood, total_exec \
= raxml_alignment(self.align1)
def test_build_tree_from_alignment(self):
"""Builds a tree from an alignment"""
tree = build_tree_from_alignment(self.align1, RNA, False)
self.assertTrue(isinstance(tree, PhyloNode))
self.assertEqual(len(tree.tips()), 7)
self.assertRaises(NotImplementedError, build_tree_from_alignment, \
self.align1, RNA, True)
PHYLIP_FILE= """ 7 50
Species001 UGCAUGUCAG UAUAGCUUUA GUGAAACUGC GAAUGGCUCA UUAAAUCAGU
Species002 UGCAUGUCAG UAUAGCUUUA GUGAAACUGC GAAUGGCUNN UUAAAUCAGU
Species003 UGCAUGUCAG UAUAGCAUUA GUGAAACUGC GAAUGGCUCA UUAAAUCAGU
Species004 UCCAUGUCAG UAUAACUUUG GUGAAACUGC GAAUGGCUCA UUAAAUCAGG
Species005 NNNNNNNNNN UAUAUCUUAU GUGAAACUUC GAAUGCCUCA UUAAAUCAGU
Species006 UGCAUGUCAG UAUAGCUUUG GUGAAACUGC GAAUGGCUCA UUAAAUCAGU
Species007 UGCAUGUCAG UAUAACUUUG GUGAAACUGC GAAUGGCUCA UUAAAUCAGU
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_raxml_v730.py 000644 000765 000024 00000021231 12024702176 022534 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import getcwd, remove, rmdir, mkdir
from os.path import splitext
from cogent.util.unit_test import TestCase, main
from cogent.util.misc import flatten
from random import randint
from cogent.app.raxml_v730 import (Raxml,raxml_alignment,\
build_tree_from_alignment,\
insert_sequences_into_tree)
from cogent.app.util import ApplicationError,get_tmp_filename
from cogent.parse.phylip import get_align_for_phylip
from cogent.core.tree import PhyloNode
from cogent.core.moltype import RNA,DNA
from StringIO import StringIO
from cogent.util.misc import app_path
from subprocess import Popen, PIPE, STDOUT
from cogent.core.alignment import Alignment
import re
from random import choice, randint
__author__ = "Micah Hamady"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Micah Hamady", "Rob Knight", "Daniel McDonald","Jesse Stombaugh"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jesse Stombaugh"
__email__ = "jesse.stombaugh@colorado.edu"
__status__ = "Production"
class GenericRaxml(TestCase):
def setUp(self):
"""Check if Raxml version is supported for this test"""
acceptable_version = (7,3,0)
self.assertTrue(app_path('raxmlHPC'),
"raxmlHPC not found. This may or may not be a problem depending on "+\
"which components of QIIME you plan to use.")
command = "raxmlHPC -v | grep version"
proc = Popen(command,shell=True,universal_newlines=True,\
stdout=PIPE,stderr=STDOUT)
stdout = proc.stdout.read()
version_string = stdout.strip().split(' ')[4].strip()
try:
version = tuple(map(int,version_string.split('.')))
pass_test = version == acceptable_version
except ValueError:
pass_test = False
version_string = stdout
self.assertTrue(pass_test,\
"Unsupported raxmlHPC version. %s is required, but running %s." \
% ('.'.join(map(str,acceptable_version)), version_string))
"""Setup data for raxml tests"""
self.seqs1 = ['ACUGCUAGCUAGUAGCGUACGUA','GCUACGUAGCUAC',
'GCGGCUAUUAGAUCGUA']
self.labels1 = ['>1','>2','>3']
self.lines1 = flatten(zip(self.labels1,self.seqs1))
self.test_model = "GTRCAT"
self.align1 = get_align_for_phylip(StringIO(PHYLIP_FILE))
self.test_fn1 = "/tmp/raxml_test1.txt"
self.test_fn2 = "raxml_test1.txt"
self.test_fn1_space = "/tmp/raxml test1.txt"
def writeTmp(self, outname):
"""Write data to temp file"""
t = open(outname, "w+")
t.write(PHYLIP_FILE)
t.close()
class RaxmlTests(GenericRaxml):
"""Tests for the Raxml application controller"""
def test_raxml(self):
"""raxml BaseCommand should return the correct BaseCommand"""
r = Raxml()
self.assertEqual(r.BaseCommand, \
''.join(['cd \"',getcwd(),'/\"; ','raxmlHPC -f d -# 1']))
r.Parameters['-s'].on('seq.nexus')
self.assertEqual(r.BaseCommand,\
''.join(['cd \"',getcwd(),'/\"; ',\
'raxmlHPC -f d -s seq.nexus -# 1']))
def test_raxml_params(self):
"""raxml should raise exception if missing required params"""
r = Raxml(WorkingDir="/tmp")
r.SuppressStdout = True
r.SuppressStderr = True
# raise error by default
self.assertRaises(ValueError, r)
# specify output name
r.Parameters['-n'].on("test_name")
r.Parameters["-p"].on(randint(1,100000))
self.assertRaises(ApplicationError, r)
# specify model
r.Parameters['-m'].on("GTRCAT")
self.assertRaises(ApplicationError, r)
r.Parameters['-s'].on(self.test_fn1)
self.assertRaises(ApplicationError, r)
self.writeTmp(self.test_fn1)
o = r()
o.cleanUp()
remove(self.test_fn1)
def test_raxml_from_file(self):
"""raxml should run correctly using filename"""
r = Raxml(WorkingDir="/tmp")
r.Parameters['-s'].on(self.test_fn1)
r.Parameters['-m'].on("GTRCAT")
r.Parameters['-n'].on("test_me")
r.Parameters["-p"].on(randint(1,100000))
# test with abs filename
cur_out = self.test_fn1
self.writeTmp(cur_out)
out = r()
out.cleanUp()
remove(cur_out)
# test with rel + working dir
r.Parameters['-s'].on(self.test_fn2)
r.Parameters['-n'].on("test_me2")
r.Parameters['-w'].on("/tmp/")
r.Parameters["-p"].on(randint(1,100000))
self.writeTmp(self.test_fn1)
out = r()
out.cleanUp()
remove(self.test_fn1)
r.Parameters['-s'].on("\"%s\"" % self.test_fn1_space)
r.Parameters['-n'].on("test_me3")
r.Parameters['-w'].on("/tmp/")
r.Parameters["-p"].on(randint(1,100000))
#print r.BaseCommand
self.writeTmp(self.test_fn1_space)
out = r()
out.cleanUp()
remove(self.test_fn1_space)
def test_raxml_alignment(self):
"""raxml_alignment should work as expected"""
phy_node, parsimony_phy_node, log_likelihood, total_exec \
= raxml_alignment(self.align1)
def test_build_tree_from_alignment(self):
"""Builds a tree from an alignment"""
tree = build_tree_from_alignment(self.align1, RNA, False)
self.assertTrue(isinstance(tree, PhyloNode))
self.assertEqual(len(tree.tips()), 7)
self.assertRaises(NotImplementedError, build_tree_from_alignment, \
self.align1, RNA, True)
def test_insert_sequences_into_tree(self):
"""Inserts sequences into Tree using params - test handles tree-insertion"""
# generate temp filename for output
outfname=splitext(get_tmp_filename('/tmp/'))[0]
# create starting tree
outtreefname=outfname+'.tre'
outtree=open(outtreefname,'w')
outtree.write(REF_TREE)
outtree.close()
# set params for tree-insertion
params={}
params["-w"]="/tmp/"
params["-n"] = get_tmp_filename().split("/")[-1]
params["-f"] = 'v'
#params["-G"] = '0.25'
params["-t"] = outtreefname
params["-m"] = 'GTRGAMMA'
aln_ref_query=get_align_for_phylip(StringIO(PHYLIP_FILE_DNA_REF_QUERY))
aln = Alignment(aln_ref_query)
seqs, align_map = aln.toPhylip()
tree = insert_sequences_into_tree(seqs, DNA, params=params,
write_log=False)
for node in tree.tips():
removed_query_str=re.sub('QUERY___','',str(node.Name))
new_node_name=re.sub('___\d+','',str(removed_query_str))
if new_node_name in align_map:
node.Name = align_map[new_node_name]
self.assertTrue(isinstance(tree, PhyloNode))
self.assertEqual(tree.getNewick(with_distances=True),RESULT_TREE)
self.assertEqual(len(tree.tips()), 7)
self.assertRaises(NotImplementedError, build_tree_from_alignment, \
self.align1, RNA, True)
remove(outtreefname)
PHYLIP_FILE= """ 7 50
Species001 UGCAUGUCAG UAUAGCUUUA GUGAAACUGC GAAUGGCUCA UUAAAUCAGU
Species002 UGCAUGUCAG UAUAGCUUUA GUGAAACUGC GAAUGGCUNN UUAAAUCAGU
Species003 UGCAUGUCAG UAUAGCAUUA GUGAAACUGC GAAUGGCUCA UUAAAUCAGU
Species004 UCCAUGUCAG UAUAACUUUG GUGAAACUGC GAAUGGCUCA UUAAAUCAGG
Species005 NNNNNNNNNN UAUAUCUUAU GUGAAACUUC GAAUGCCUCA UUAAAUCAGU
Species006 UGCAUGUCAG UAUAGCUUUG GUGAAACUGC GAAUGGCUCA UUAAAUCAGU
Species007 UGCAUGUCAG UAUAACUUUG GUGAAACUGC GAAUGGCUCA UUAAAUCAGU
"""
PHYLIP_FILE_DNA_REF_QUERY= """ 7 50
Species001 TGCATGTCAG TATAGCTTTA GTGAAACTGC GAATGGCTCA TTAAATCAGT
Species002 TGCATGTCAG TATAGCTTTA GTGAAACTGC GAATGGCTNN TTAAATCAGT
Species003 TGCATGTCAG TATAGCATTA GTGAAACTGC GAATGGCTCA TTAAATCAGT
Species004 TCCATGTCAG TATAACTTTG GTGAAACTGC GAATGGCTCA TTAAATCAGG
Species005 NNNNNNNNNN TATATCTTAT GTGAAACTTC GAATGCCTCA TTAAATCAGT
Species006 TGCATGTCAG TATAGCTTTG GTGAAACTGC GAATGGCTCA TTAAATCAGT
Species007 TGCATGTCAG TATAACTTTG GTGAAACTGC GAATGGCTCA TTAAATCAGT
"""
REF_TREE="""((seq0000004:0.08408,seq0000005:0.13713)0.609:0.00215,seq0000003:0.02032,(seq0000001:0.00014,seq0000002:0.00014)0.766:0.00015);
"""
RESULT_TREE="""(Species003:0.0194919169324,(Species001:4.34281710439e-07,Species002:4.34281710439e-07):4.34281710439e-07,(((Species006:0.0,Species007:0.0):0.0,Species004:0.0438017433031):0.0438017433031,Species005:0.171345128781):0.00331197405878);"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_rdp_classifier.py 000644 000765 000024 00000054226 12024702176 023635 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for the rdp_classifier_2.0.1 application controller"""
import os
from cStringIO import StringIO
from os import getcwd, environ, remove, listdir
from shutil import rmtree
import tempfile
from cogent.app.util import ApplicationNotFoundError, ApplicationError,\
get_tmp_filename
from cogent.app.rdp_classifier import (
RdpClassifier, RdpTrainer, assign_taxonomy, train_rdp_classifier,
train_rdp_classifier_and_assign_taxonomy, parse_rdp_assignment
)
from cogent.util.unit_test import TestCase, main
__author__ = "Kyle Bittinger"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Kyle Bittinger"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Kyle Bittinger"
__email__ = "kylebittinger@gmail.com"
__status__ = "Prototype"
class RdpClassifierTests(TestCase):
def setUp(self):
# fetch user's RDP_JAR_PATH
if 'RDP_JAR_PATH' in environ:
self.user_rdp_jar_path = environ['RDP_JAR_PATH']
else:
self.user_rdp_jar_path = 'rdp_classifier-2.2.jar'
self.output_file = tempfile.NamedTemporaryFile()
def test_default_java_vm_parameters(self):
"""RdpClassifier should store default arguments to Java VM."""
a = RdpClassifier()
self.assertContains(a.Parameters, '-Xmx')
self.assertEqual(a.Parameters['-Xmx'].Value, '1000m')
def test_parameters_list(self):
a = RdpClassifier()
parameters = a.Parameters.keys()
parameters.sort()
self.assertEqual(parameters, ['-Xmx', '-f', '-o', '-t'])
def test_assign_jvm_parameters(self):
"""RdpCalssifier should pass alternate parameters to Java VM."""
app = RdpClassifier()
app.Parameters['-Xmx'].on('75M')
exp = ''.join([
'cd "', getcwd(), '/"; java -Xmx75M -jar "',
self.user_rdp_jar_path, '" -q'])
self.assertEqual(app.BaseCommand, exp)
def test_basecommand_property(self):
"""RdpClassifier BaseCommand property should use overridden method."""
app = RdpClassifier()
self.assertEqual(app.BaseCommand, app._get_base_command())
def test_base_command(self):
"""RdpClassifier should return expected shell command."""
app = RdpClassifier()
exp = ''.join([
'cd "', getcwd(), '/"; java -Xmx1000m -jar "',
self.user_rdp_jar_path, '" -q'])
self.assertEqual(app.BaseCommand, exp)
def test_change_working_dir(self):
"""RdpClassifier should run program in expected working directory."""
test_dir = '/tmp/RdpTest'
app = RdpClassifier(WorkingDir=test_dir)
exp = ''.join([
'cd "', test_dir, '/"; java -Xmx1000m -jar "',
self.user_rdp_jar_path, '" -q'])
self.assertEqual(app.BaseCommand, exp)
rmtree(test_dir)
def test_sample_fasta(self):
"""RdpClassifier should classify its own sample data correctly"""
test_dir = '/tmp/RdpTest'
app = RdpClassifier(WorkingDir=test_dir)
_, output_fp = tempfile.mkstemp(dir=test_dir)
app.Parameters['-o'].on(output_fp)
results = app(StringIO(rdp_sample_fasta))
assignment_toks = results['Assignments'].readline().split('\t')
self.assertEqual(assignment_toks[0], 'X67228')
lineage = [x.strip('"') for x in assignment_toks[2::3]]
self.assertEqual(lineage, [
'Root', 'Bacteria', 'Proteobacteria', 'Alphaproteobacteria',
'Rhizobiales', 'Rhizobiaceae', 'Rhizobium'])
rmtree(test_dir)
class RdpTrainerTests(TestCase):
"""Tests of the trainer for the RdpClassifier app
"""
def setUp(self):
self.reference_file = StringIO(rdp_training_sequences)
self.reference_file.seek(0)
self.taxonomy_file = tempfile.NamedTemporaryFile(
prefix="RdpTaxonomy", suffix=".txt")
self.taxonomy_file.write(rdp_training_taxonomy)
self.taxonomy_file.seek(0)
self.training_dir = tempfile.mkdtemp(prefix='RdpTrainer_output_')
def tearDown(self):
rmtree(self.training_dir)
def test_call(self):
app = RdpTrainer()
app.Parameters['taxonomy_file'].on(self.taxonomy_file.name)
app.Parameters['model_output_dir'].on(self.training_dir)
results = app(self.reference_file)
exp_file_list = [
'bergeyTrainingTree.xml', 'genus_wordConditionalProbList.txt',
'logWordPrior.txt', 'RdpClassifier.properties',
'wordConditionalProbIndexArr.txt',
]
obs_file_list = listdir(self.training_dir)
exp_file_list.sort()
obs_file_list.sort()
self.assertEqual(obs_file_list, exp_file_list)
autogenerated_headers = {
'bergeyTree': 'bergeyTrainingTree',
'probabilityList': 'genus_wordConditionalProbList',
'wordPrior': 'logWordPrior',
'probabilityIndex': 'wordConditionalProbIndexArr',
}
for id, basename in autogenerated_headers.iteritems():
obs_header = results[id].readline()
exp_header = exp_training_header_template % basename
self.assertEqual(exp_header, obs_header)
class RdpWrapperTests(TestCase):
""" Tests of RDP classifier wrapper functions
"""
def setUp(self):
self.num_trials = 10
self.test_input1 = rdp_test_fasta.split('\n')
self.expected_assignments1 = rdp_expected_out
# Files for training
self.reference_file = StringIO(rdp_training_sequences)
self.reference_file.seek(0)
self.taxonomy_file = StringIO(rdp_training_taxonomy)
self.taxonomy_file.seek(0)
self.training_dir = tempfile.mkdtemp(prefix='RdpTrainer_output_')
# Sequences for trained classifier
self.test_trained_input = rdp_trained_fasta.split("\n")
def tearDown(self):
rmtree(self.training_dir)
def test_parse_rdp_assignment(self):
seqid, direction, assignments = parse_rdp_assignment(
"X67228\t\t"
"Root\tnorank\t1.0\t"
"Bacteria\tdomain\t1.0\t"
"\"Proteobacteria\"\tphylum\t1.0\t"
"Alphaproteobacteria\tclass\t0.9\t"
"Rhizobiales\torder\t0.9\t"
"Rhizobiaceae\tfamily\t0.47\t"
"Rhizobium\tgenus\t0.46")
self.assertEqual(seqid, "X67228")
def test_assign_taxonomy_short_sequence(self):
"""assign_taxonomy should return Unclassifiable if sequence is too short
"""
assignments = assign_taxonomy([
'>MySeq 1',
'TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGA',
])
self.assertEqual(assignments, {'MySeq 1': ('Unassignable', 1.0)})
def test_assign_taxonomy(self):
"""assign_taxonomy wrapper functions as expected
This test may fail periodicially, but failure should be rare.
"""
unverified_seq_ids = set(self.expected_assignments1.keys())
for i in range(self.num_trials):
obs_assignments = assign_taxonomy(self.test_input1)
for seq_id in list(unverified_seq_ids):
obs_lineage, obs_confidence = obs_assignments[seq_id]
exp_lineage = self.expected_assignments1[seq_id]
if (obs_lineage == exp_lineage):
unverified_seq_ids.remove(seq_id)
if not unverified_seq_ids:
break
messages = []
for seq_id in unverified_seq_ids:
messages.append("Unable to verify %s trials" % self.num_trials)
messages.append(" Sequence ID: %s" % seq_id)
messages.append(" Expected: %s" % self.expected_assignments1[seq_id])
messages.append(" Observed: %s" % obs_assignments[seq_id][0])
messages.append(" Confidence: %s" % obs_assignments[seq_id][1])
# make sure all taxonomic results were correct at least once
self.assertFalse(unverified_seq_ids, msg='\n'.join(messages))
def test_assign_taxonomy_alt_confidence(self):
"""assign_taxonomy wrapper functions as expected with alt confidence
"""
obs_assignments = assign_taxonomy(
self.test_input1, min_confidence=0.95)
for seq_id, assignment in obs_assignments.items():
obs_lineage, obs_confidence = assignment
exp_lineage = self.expected_assignments1[seq_id]
message = "Sequence ID: %s, assignment: %s" % (seq_id, assignment)
self.assertTrue(
exp_lineage.startswith(obs_lineage) or \
(obs_lineage == "Unclassified"),
msg=message,
)
self.assertTrue(obs_confidence >= 0.95, msg=message)
def test_assign_taxonomy_file_output(self):
""" assign_taxonomy wrapper writes correct file output when requested
This function tests for sucessful completion of assign_taxonomy
when writing to file, that the lines in the file roughly look
correct by verifying how many are written (by zipping with
expected), and that each line starts with the correct seq id.
Actual testing of taxonomy data is performed elsewhere.
"""
output_fp = get_tmp_filename(\
prefix='RDPAssignTaxonomyTests',suffix='.txt')
# convert the expected dict to a list of lines to match
# file output
expected_file_headers = self.expected_assignments1.keys()
expected_file_headers.sort()
actual_return_value = assign_taxonomy(\
self.test_input1,min_confidence=0.95,output_fp=output_fp)
actual_file_output = list(open(output_fp))
actual_file_output.sort()
# remove the output_fp before running the tests, so if they
# fail the output file is still cleaned-up
remove(output_fp)
# None return value on write to file
self.assertEqual(actual_return_value,None)
# check that each line starts with the correct seq_id -- not
# checking the taxonomies or confidences here as these are variable and
# tested elsewhere
for a,e in zip(actual_file_output,expected_file_headers):
self.assertTrue(a.startswith(e))
def test_train_rdp_classifier(self):
results = train_rdp_classifier(
self.reference_file, self.taxonomy_file, self.training_dir)
exp_file_list = [
'bergeyTrainingTree.xml', 'genus_wordConditionalProbList.txt',
'logWordPrior.txt', 'RdpClassifier.properties',
'wordConditionalProbIndexArr.txt',
]
obs_file_list = listdir(self.training_dir)
exp_file_list.sort()
obs_file_list.sort()
self.assertEqual(obs_file_list, exp_file_list)
autogenerated_headers = {
'bergeyTree': 'bergeyTrainingTree',
'probabilityList': 'genus_wordConditionalProbList',
'wordPrior': 'logWordPrior',
'probabilityIndex': 'wordConditionalProbIndexArr',
}
for id, basename in autogenerated_headers.iteritems():
obs_header = results[id].readline()
exp_header = exp_training_header_template % basename
self.assertEqual(exp_header, obs_header)
def test_train_rdp_classifier_and_assign_taxonomy(self):
obs = train_rdp_classifier_and_assign_taxonomy(self.reference_file,
self.taxonomy_file, self.test_trained_input, min_confidence=0.80,
model_output_dir=self.training_dir)
exp = {'X67228': (
'Bacteria;Proteobacteria;Alphaproteobacteria;Rhizobiales;'
'Rhizobiaceae;Rhizobium', 1.0
)}
self.assertEqual(obs, exp)
# Sample data copied from rdp_classifier-2.0, which is licensed under
# the GPL 2.0 and Copyright 2008 Michigan State University Board of
# Trustees
rdp_training_sequences = """>X67228 Bacteria;Proteobacteria;Alphaproteobacteria;Rhizobiales;Rhizobiaceae;Rhizobium
aacgaacgctggcggcaggcttaacacatgcaagtcgaacgctccgcaaggagagtggcagacgggtgagtaacgcgtgggaatctacccaaccctgcggaatagctctgggaaactggaattaataccgcatacgccctacgggggaaagatttatcggggatggatgagcccgcgttggattagctagttggtggggtaaaggcctaccaaggcgacgatccatagctggtctgagaggatgatcagccacattgggactgagacacggcccaaa
>X73443 Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiaceae;Clostridium
nnnnnnngagatttgatcctggctcaggatgaacgctggccggccgtgcttacacatgcagtcgaacgaagcgcttaaactggatttcttcggattgaagtttttgctgactgagtggcggacgggtgagtaacgcgtgggtaacctgcctcatacagggggataacagttagaaatgactgctaataccnnataagcgcacagtgctgcatggcacagtgtaaaaactccggtggtatgagatggacccgcgtctgattagctagttggtggggt
>AB004750 Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Enterobacter
acgctggcggcaggcctaacacatgcaagtcgaacggtagcagaaagaagcttgcttctttgctgacgagtggcggacgggtgagtaatgtctgggaaactgcccgatggagggggataactactggaaacggtagctaataccgcataacgtcttcggaccaaagagggggaccttcgggcctcttgccatcggatgtgcccagatgggattagctagtaggtggggtaacggctcacctaggcgacgatccctagctggtctgagaggatgaccagccacactggaactgagacacggtccagactcctacgggaggcagcagtggggaatattgca
>xxxxxx Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Pseudomonadaceae;Pseudomonas
ttgaacgctggcggcaggcctaacacatgcaagtcgagcggcagcannnncttcgggaggctggcgagcggcggacgggtgagtaacgcatgggaacttacccagtagtgggggatagcccggggaaacccggattaataccgcatacgccctgagggggaaagcgggctccggtcgcgctattggatgggcccatgtcggattagttagttggtggggtaatggcctaccaaggcgacgatccgtagctggtctgagaggatgatcagccacaccgggactgagacacggcccggactcctacgggaggcagcagtggggaatattggacaatgggggcaaccctgatccagccatgccg
>AB004748 Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Enterobacter
acgctggcggcaggcctaacacatgcaagtcgaacggtagcagaaagaagcttgcttctttgctgacgagtggcggacgggtgagtaatgtctgggaaactgcccgatggagggggataactactggaaacggtagctaataccgcataacgtcttcggaccaaagagggggaccttcgggcctcttgccatcggatgtgcccagatgggattagctagtaggtggggtaacggctcacctaggcgacgatccctagctggtctgagaggatgaccagccacactggaactgagacacggtccagactcctacgggaggcagcagtggggaatattgcacaatgggcgcaagcctgatgcagccatgccgcgtgtatgaagaaggccttcgggttg
>AB000278 Bacteria;Proteobacteria;Gammaproteobacteria;Vibrionales;Vibrionaceae;Photobacterium
caggcctaacacatgcaagtcgaacggtaanagattgatagcttgctatcaatgctgacgancggcggacgggtgagtaatgcctgggaatataccctgatgtgggggataactattggaaacgatagctaataccgcataatctcttcggagcaaagagggggaccttcgggcctctcgcgtcaggattagcccaggtgggattagctagttggtggggtaatggctcaccaaggcgacgatccctagctggtctgagaggatgatcagccacactggaactgagacacggtccagactcctacgggaggcagcagtggggaatattgcacaatgggggaaaccctgatgcagccatgccgcgtgta
>AB000390 Bacteria;Proteobacteria;Gammaproteobacteria;Vibrionales;Vibrionaceae;Vibrio
tggctcagattgaacgctggcggcaggcctaacacatgcaagtcgagcggaaacgantnntntgaaccttcggggnacgatnacggcgtcgagcggcggacgggtgagtaatgcctgggaaattgccctgatgtgggggataactattggaaacgatagctaataccgcataatgtctacggaccaaagagggggaccttcgggcctctcgcttcaggatatgcccaggtgggattagctagttggtgaggtaatggctcaccaaggcgacgatccctagctggtctgagaggatgatcagccacactggaactgag
"""
rdp_training_taxonomy = """\
1*Bacteria*0*0*domain
765*Firmicutes*1*1*phylum
766*Clostridia*765*2*class
767*Clostridiales*766*3*order
768*Clostridiaceae*767*4*family
769*Clostridium*768*5*genus
160*Proteobacteria*1*1*phylum
433*Gammaproteobacteria*160*2*class
586*Vibrionales*433*3*order
587*Vibrionaceae*586*4*family
588*Vibrio*587*5*genus
592*Photobacterium*587*5*genus
552*Pseudomonadales*433*3*order
553*Pseudomonadaceae*552*4*family
554*Pseudomonas*553*5*genus
604*Enterobacteriales*433*3*order
605*Enterobacteriaceae*604*4*family
617*Enterobacter*605*5*genus
161*Alphaproteobacteria*160*2*class
260*Rhizobiales*161*3*order
261*Rhizobiaceae*260*4*family
262*Rhizobium*261*5*genus"""
exp_training_header_template = "1 version1 cogent %s \n"
rdp_trained_fasta = """>X67228
aacgaacgctggcggcaggcttaacacatgcaagtcgaacgctccgcaaggagagtggcagacgggtgagtaacgcgtgggaatctacccaaccctgcggaatagctctgggaaactggaattaataccgcatacgccctacgggggaaagatttatcggggatggatgagcccgcgttggattagctagttggtggggtaaaggcctaccaaggcgacgatccatagctggtctgagaggatgatcagccacattgggactgagacacggcccaaa
"""
rdp_sample_fasta = """>X67228 Bacteria;Proteobacteria;Alphaproteobacteria;Rhizobiales;Rhizobiaceae;Rhizobium
aacgaacgctggcggcaggcttaacacatgcaagtcgaacgctccgcaaggagagtggcagacgggtgagtaacgcgtgggaatctacccaaccctgcggaatagctctgggaaactggaattaataccgcatacgccctacgggggaaagatttatcggggatggatgagcccgcgttggattagctagttggtggggtaaaggcctaccaaggcgacgatccatagctggtctgagaggatgatcagccacattgggactgagacacggcccaaa
"""
rdp_sample_classification = """>X67228 reverse=false
Root; 1.0; Bacteria; 1.0; Proteobacteria; 1.0; Alphaproteobacteria; 1.0; Rhizobiales; 1.0; Rhizobiaceae; 1.0; Rhizobium; 0.95;
"""
rdp_test_fasta = """>AY800210 description field
TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGATGCGACTAAGCCATGCTAGTCTAACGGATCTTCGGATCCGTGGCATACCGCTCTGTAACACGTAGATAACCTACCCTGAGGTCGGGGAAACTCCCGGGAAACTGGGCCTAATCCCCGATAGATAATTTGTACTGGAATGTCTTTTTATTGAAACCTCCGAGGCCTCAGGATGGGTCTGCGCCAGATTATGGTCGTAGGTGGGGTAACGGCCCACCTAGCCTTTGATCTGTACCGGACATGAGAGTGTGTGCCGGGAGATGGCCACTGAGACAAGGGGCCAGGCCCTACGGGGCGCAGCAGGCGCGAAAACTTCACAATGCCCGCAAGGGTGATGAGGGTATCCGAGTGCTACCTTAGCCGGTAGCTTTTATTCAGTGTAAATAGCTAGATGAATAAGGGGAGGGCAAGGCTGGTGCCAGCCGCCGCGGTAAAACCAGCTCCCGAGTGGTCGGGATTTTTATTGGGCCTAAAGCGTCCGTAGCCGGGCGTGCAAGTCATTGGTTAAATATCGGGTCTTAAGCCCGAACCTGCTAGTGATACTACACGCCTTGGGACCGGAAGAGGCAAATGGTACGTTGAGGGTAGGGGTGAAATCCTGTAATCCCCAACGGACCACCGGTGGCGAAGCTTGTTCAGTCATGAACAACTCTACACAAGGCGATTTGCTGGGACGGATCCGACGGTGAGGGACGAAACCCAGGGGAGCGAGCGGGATTAGATACCCCGGTAGTCCTGGGCGTAAACGATGCGAACTAGGTGTTGGCGGAGCCACGAGCTCTGTCGGTGCCGAAGCGAAGGCGTTAAGTTCGCCGCCAGGGGAGTACGGCCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCAC
>EU883771
TGGCGTACGGCTCAGTAACACGTGGATAACTTACCCTTAGGACTGGGATAACTCTGGGAAACTGGGGATAATACTGGATATTAGGCTATGCCTGGAATGGTTTGCCTTTGAAATGTTTTTTTTCGCCTAAGGATAGGTCTGCGGCTGATTAGGTCGTTGGTGGGGTAATGGCCCACCAAGCCGATGATCGGTACGGGTTGTGAGAGCAAGGGCCCGGAGATGGAACCTGAGACAAGGTTCCAGACCCTACGGGGTGCAGCAGGCGCGAAACCTCCGCAATGTACGAAAGTGCGACGGGGGGATCCCAAGTGTTATGCTTTTTTGTATGACTTTTCATTAGTGTAAAAAGCTTTTAGAATAAGAGCTGGGCAAGACCGGTGCCAGCCGCCGCGGTAACACCGGCAGCTCGAGTGGTGACCACTTTTATTGGGCTTAAAGCGTTCGTAGCTTGATTTTTAAGTCTCTTGGGAAATCTCACGGCTTAACTGTGAGGCGTCTAAGAGATACTGGGAATCTAGGGACCGGGAGAGGTAAGAGGTACTTCAGGGGTAGAAGTGAAATTCTGTAATCCTTGAGGGACCACCGATGGCGAAGGCATCTTACCAGAACGGCTTCGACAGTGAGGAACGAAAGCTGGGGGAGCGAACGGGATTAGATACCCCGGTAGTCCCAGCCGTAAACTATGCGCGTTAGGTGTGCCTGTAACTACGAGTTACCGGGGTGCCGAAGTGAAAACGTGAAACGTGCCGCCTGGGAAGTACGGTCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCACCACAACGGGTGGAGCCTGCGGTTTAATTGGACTCAACGCCGGGCAGCTCACCGGATAGGACAGCGGAATGATAGCCGGGCTGAAGACCTTGCTTGACCAGCTGAGA
>EF503699
AAGAATGGGGATAGCATGCGAGTCACGCCGCAATGTGTGGCATACGGCTCAGTAACACGTAGTCAACATGCCCAGAGGACGTGGACACCTCGGGAAACTGAGGATAAACCGCGATAGGCCACTACTTCTGGAATGAGCCATGACCCAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGGAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCACGAAACCTCTGCAATAGGCGAAAGCTTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCCGCTTAACGGATGGGCTGCGGAGGATACTGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCTTTGATCTACTGAAGACCACCAGTGGTGAAGGCGGTTCGCCAGAACGCGCTCGAACGGTGAGGATGAAAGCTGGGGGAGCAAACCGGAATAGATACCCGAGTAATCCCAACTGTAAACGATGGCAACTCGGGGATGGGTTGGCCTCCAACCAACCCCATGGCCGCAGGGAAGCCGTTTAGCTCTCCCGCCTGGGGAATACGGTCCGCAGAATTGAACCTTAAAGGAATTTGGCGGGGAACCCCCACAAGGGGGAAAACCGTGCGGTTCAATTGGAATCCACCCCCCGGAAACTTTACCCGGGCGCG
>random_seq
AAGCTCCGTCGCGTGAGCTAAAAACCATGCTGACTTATGAGACCTAAAAGCGATGCGCCGACCTGACGATGCTCTGTTCAGTTTCATCACGATCACCGGTAGTCAGGGTACCCTCCAGACCGCGCATAGTGACTATGTTCCCGCACCTGTATATGTAATTCCCATTATACGTCTACGTTATGTAGTAAAGTTGCTCACGCCAGGCACAGTTTGTCTTGATACATAGGGTAGCTTAAGTCCCGTCCATTTCACCGCGATTGTAATAGACGAATCAGCAGTGGTGCAATCAAGTCCCAACAGTTATATTTCAAAAATCTTCCGATAGTCGTGGGCGAAGTTGTCAACCTACCTACCATGGCTATAAGGCCCAGTTTACTTCAGTTGAACGTGACGGTAACCCTACTGAGTGCACGATACCTGCTCAACAACGGCCCAAAACCCGTGCGACACATTGGGCACTACAATAATCTTAGAGGACCATGGATCTGGTGGGTGGACTGAAGCATATCCCAAAAGTGTCGTGAGTCCGTTATGCAATTGACTGAAACAGCCGTACCAGAGTTCGGATGACCTCTGGGTTGCTGCGGTACACACCCGGGTGCGGCTTCTGAAATAGAAAAGACTAAGCATCGGCCGCCTCACACGCCAC
>DQ260310
GATACCCCCGGAAACTGGGGATTATACCGGATATGTGGGGCTGCCTGGAATGGTACCTCATTGAAATGCTCCCGCGCCTAAAGATGGATCTGCCGCAGAATAAGTAGTTTGCGGGGTAAATGGCCACCCAGCCAGTAATCCGTACCGGTTGTGAAAACCAGAACCCCGAGATGGAAACTGAAACAAAGGTTCAAGGCCTACCGGGCACAACAAGCGCCAAAACTCCGCCATGCGAGCCATCGCGACGGGGGAAAACCAAGTACCACTCCTAACGGGGTGGTTTTTCCGAAGTGGAAAAAGCCTCCAGGAATAAGAACCTGGGCCAGAACCGTGGCCAGCCGCCGCCGTTACACCCGCCAGCTCGAGTTGTTGGCCGGTTTTATTGGGGCCTAAAGCCGGTCCGTAGCCCGTTTTGATAAGGTCTCTCTGGTGAAATTCTACAGCTTAACCTGTGGGAATTGCTGGAGGATACTATTCAAGCTTGAAGCCGGGAGAAGCCTGGAAGTACTCCCGGGGGTAAGGGGTGAAATTCTATTATCCCCGGAAGACCAACTGGTGCCGAAGCGGTCCAGCCTGGAACCGAACTTGACCGTGAGTTACGAAAAGCCAAGGGGCGCGGACCGGAATAAAATAACCAGGGTAGTCCTGGCCGTAAACGATGTGAACTTGGTGGTGGGAATGGCTTCGAACTGCCCAATTGCCGAAAGGAAGCTGTAAATTCACCCGCCTTGGAAGTACGGTCGCAAGACTGGAACCTAAAAGGAATTGGCGGGGGGACACCACAACGCGTGGAGCCTGGCGGTTTTATTGGGATTCCACGCAGACATCTCACTCAGGGGCGACAGCAGAAATGATGGGCAGGTTGATGACCTTGCTTGACAAGCTGAAAAGGAGGTGCAT
>EF503697
TAAAATGACTAGCCTGCGAGTCACGCCGTAAGGCGTGGCATACAGGCTCAGTAACACGTAGTCAACATGCCCAAAGGACGTGGATAACCTCGGGAAACTGAGGATAAACCGCGATAGGCCAAGGTTTCTGGAATGAGCTATGGCCGAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGTAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCGCGAAACCTCTGCAATAGGCGAAAGCCTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCTGCTCAACGGATGGGCTGCGGAGGATACCGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCATTGATCTACTGAAGACCACCAGTGGCGAAGGCGGTTTGCCAGAACGCGCTCGACGGTGAGGGATGAAAGCTGGGGGAGCAAACCGGATTAGATACCCGGGGTAGTCCCAGCTGTAAACGGATGCAGACTCGGGTGATGGGGTTGGCTTCCGGCCCAACCCCAATTGCCCCCAGGCGAAGCCCGTTAAGATCTTGCCGCCCTGTCAGATGTCAGGGCCGCCAATACTCGAAACCTTAAAAGGAAATTGGGCGCGGGAAAAGTCACCAAAAGGGGGTTGAAACCCTGCGGGTTATATATTGTAAACC
>short_seq
TAAAATGACTAGCCTGCGAGTCAC
"""
rdp_expected_out = {
'AY800210 description field': 'Archaea;Euryarchaeota',
'EU883771': 'Archaea;Euryarchaeota;Methanomicrobia;Methanomicrobiales;Methanomicrobiaceae;Methanomicrobium',
'EF503699': 'Archaea;Crenarchaeota;Thermoprotei',
'random_seq': 'Bacteria',
'DQ260310': 'Archaea;Euryarchaeota;Methanobacteria;Methanobacteriales;Methanobacteriaceae;Methanosphaera',
'EF503697': 'Archaea;Crenarchaeota;Thermoprotei',
'short_seq': 'Unassignable',
}
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_rdp_classifier20.py 000644 000765 000024 00000064642 12024702176 024002 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Tests for the rdp_classifier_2.0.1 application controller"""
from cStringIO import StringIO
from os import getcwd, environ, remove, listdir
from shutil import rmtree
from tempfile import mkdtemp
from cogent.app.util import (
ApplicationNotFoundError, ApplicationError, get_tmp_filename,
)
from cogent.app.rdp_classifier20 import (
RdpClassifier20, RdpTrainer20, assign_taxonomy, train_rdp_classifier,
train_rdp_classifier_and_assign_taxonomy,
)
from cogent.util.unit_test import TestCase, main
__author__ = "Kyle Bittinger"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Kyle Bittinger"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Kyle Bittinger"
__email__ = "kylebittinger@gmail.com"
__status__ = "Prototype"
class RdpClassifier20Tests(TestCase):
def setUp(self):
# fetch user's RDP_JAR_PATH
if 'RDP_JAR_PATH' in environ:
self.user_rdp_jar_path = environ['RDP_JAR_PATH']
else:
self.user_rdp_jar_path = 'rdp_classifier-2.0.jar'
def test_default_java_vm_parameters(self):
"""RdpClassifier should store default arguments to Java VM."""
a = RdpClassifier20()
self.assertContains(a.Parameters, '-Xmx')
self.assertEqual(a.Parameters['-Xmx'].Value, '1000m')
def test_parameters_list(self):
a = RdpClassifier20()
parameters = a.Parameters.keys()
parameters.sort()
self.assertEqual(parameters, ['-Xmx', '-training-data'])
def test_jvm_parameters_list(self):
a = RdpClassifier20()
parameters = a.JvmParameters.keys()
parameters.sort()
self.assertEqual(parameters, ['-Xmx'])
def test_positional_parameters_list(self):
a = RdpClassifier20()
parameters = a.PositionalParameters.keys()
parameters.sort()
self.assertEqual(parameters, ['-training-data'])
def test_default_positional_parameters(self):
"""RdpClassifier should store default positional arguments."""
a = RdpClassifier20()
self.assertContains(a.PositionalParameters, '-training-data')
self.assertEqual(a.PositionalParameters['-training-data'].Value, '')
def test_assign_jvm_parameters(self):
"""RdpCalssifier should pass alternate parameters to Java VM."""
app = RdpClassifier20()
app.Parameters['-Xmx'].on('75M')
exp = ''.join(['cd "', getcwd(), '/"; java -Xmx75M -jar "', self.user_rdp_jar_path, '"'])
self.assertEqual(app.BaseCommand, exp)
def test_basecommand_property(self):
"""RdpClassifier BaseCommand property should use overridden _get_base_command method."""
app = RdpClassifier20()
self.assertEqual(app.BaseCommand, app._get_base_command())
def test_base_command(self):
"""RdpClassifier should return expected shell command."""
app = RdpClassifier20()
exp = ''.join(['cd "', getcwd(), '/"; java -Xmx1000m -jar "', self.user_rdp_jar_path, '"'])
self.assertEqual(app.BaseCommand, exp)
def test_change_working_dir(self):
"""RdpClassifier should run program in expected working directory."""
test_dir = '/tmp/RdpTest'
app = RdpClassifier20(WorkingDir=test_dir)
exp = ''.join(['cd "', test_dir, '/"; java -Xmx1000m -jar "', self.user_rdp_jar_path, '"'])
self.assertEqual(app.BaseCommand, exp)
rmtree(test_dir)
def test_sample_fasta(self):
"""RdpClassifier should classify its own sample data correctly"""
test_dir = '/tmp/RdpTest'
app = RdpClassifier20(WorkingDir=test_dir)
results = app(rdp_sample_fasta)
results_file = results['Assignments']
id_line = results_file.readline()
self.failUnless(id_line.startswith('>X67228'))
classification_line = results_file.readline().strip()
obs = parse_rdp(classification_line)
exp = ['Root', 'Bacteria', 'Proteobacteria', 'Alphaproteobacteria', 'Rhizobiales', 'Rhizobiaceae', 'Rhizobium']
self.assertEqual(obs, exp)
rmtree(test_dir)
class RdpTrainer20Tests(TestCase):
"""Tests of the trainer for the RdpClassifier app
"""
def setUp(self):
self.reference_file = StringIO(rdp_training_sequences)
self.reference_file.seek(0)
self.taxonomy_file = StringIO(rdp_training_taxonomy)
self.taxonomy_file.seek(0)
self.training_dir = mkdtemp(prefix='RdpTrainer_output_')
def tearDown(self):
rmtree(self.training_dir)
def test_train_with_rdp_files(self):
app = RdpTrainer20()
results = app._train_with_rdp_files(
self.reference_file, self.taxonomy_file, self.training_dir)
exp_file_list = [
'bergeyTrainingTree.xml', 'genus_wordConditionalProbList.txt',
'logWordPrior.txt', 'RdpClassifier.properties',
'wordConditionalProbIndexArr.txt',
]
obs_file_list = listdir(self.training_dir)
exp_file_list.sort()
obs_file_list.sort()
self.assertEqual(obs_file_list, exp_file_list)
autogenerated_headers = {
'bergeyTree': 'bergeyTrainingTree',
'probabilityList': 'genus_wordConditionalProbList',
'wordPrior': 'logWordPrior',
'probabilityIndex': 'wordConditionalProbIndexArr',
}
for id, basename in autogenerated_headers.iteritems():
obs_header = results[id].readline()
exp_header = exp_training_header_template % basename
self.assertEqual(exp_header, obs_header)
class RdpWrapperTests(TestCase):
""" Tests of RDP classifier wrapper functions
"""
def setUp(self):
self.test_input1 = rdp_test_fasta.split('\n')
self.expected_assignments1 = rdp_expected_out
# Files for training
self.reference_file = StringIO(rdp_training_sequences)
self.reference_file.seek(0)
self.taxonomy_file = StringIO(rdp_training_taxonomy)
self.taxonomy_file.seek(0)
self.training_dir = mkdtemp(prefix='RdpTrainer_output_')
# Sequences for trained classifier
self.test_trained_input = rdp_trained_fasta.split("\n")
def tearDown(self):
rmtree(self.training_dir)
def test_assign_taxonomy_short_sequence(self):
"""assign_taxonomy should return Unclassifiable if sequence is too short
"""
assignments = assign_taxonomy([
'>MySeq 1',
'TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGA',
])
self.assertEqual(assignments, {'MySeq 1': ('Unassignable', 1.0)})
def test_assign_taxonomy(self):
"""assign_taxonomy wrapper functions as expected
This test may fail periodicially, but failure should be rare.
"""
# convert the expected dict to a list, so it's easier to
# handle the order
expected_assignments = \
[(k,v[0],v[1]) for k,v in self.expected_assignments1.items()]
expected_assignments.sort()
# Because there is some variation in the taxon assignments,
# I run the test several times (which can be quite slow) and
# each sequence was classified the same as expected at least once
taxon_assignment_results = [False] * len(expected_assignments)
all_assigned_correctly = False
for i in range(10):
actual_assignments = assign_taxonomy(self.test_input1)
# covert actual_assignments to a list so it's easier to handle
# the order
actual_assignments = \
[(k,v[0],v[1]) for k,v in actual_assignments.items()]
actual_assignments.sort()
for j in range(len(expected_assignments)):
a = actual_assignments[j]
e = expected_assignments[j]
# same description fields
self.assertEqual(a[0],e[0])
# same taxonomic assignment
r = a[1] == e[1]
if r and not taxon_assignment_results[j]:
taxon_assignment_results[j] = True
# confidence >= 0.80
self.assertTrue(a[2]>=0.80)
if False not in taxon_assignment_results:
# all sequences have been correctly assigned at
# least once -- bail out
all_assigned_correctly = True
break
# make sure all taxonomic results were correct at least once
self.assertTrue(all_assigned_correctly)
def test_assign_taxonomy_alt_confidence(self):
"""assign_taxonomy wrapper functions as expected with alt confidence
"""
actual_assignments = \
assign_taxonomy(self.test_input1,min_confidence=0.95)
# covert actual_assignments to a list so it's easier to handle
# the order
actual_assignments = \
[(k,v[0],v[1]) for k,v in actual_assignments.items()]
actual_assignments.sort()
# convert the expected dict to a list, so it's easier to
# handle the order
expected_assignments = \
[(k,v[0],v[1]) for k,v in self.expected_assignments1.items()]
expected_assignments.sort()
for a,e in zip(actual_assignments,expected_assignments):
# same description fields
self.assertEqual(a[0],e[0])
# confidence >= 0.95
self.assertTrue(a[2]>=0.95)
def test_assign_taxonomy_file_output(self):
""" assign_taxonomy wrapper writes correct file output when requested
This function tests for sucessful completion of assign_taxonomy
when writing to file, that the lines in the file roughly look
correct by verifying how many are written (by zipping with
expected), and that each line starts with the correct seq id.
Actual testing of taxonomy data is performed elsewhere.
"""
output_fp = get_tmp_filename(\
prefix='RDPAssignTaxonomyTests',suffix='.txt')
# convert the expected dict to a list of lines to match
# file output
expected_file_headers = self.expected_assignments1.keys()
expected_file_headers.sort()
actual_return_value = assign_taxonomy(\
self.test_input1,min_confidence=0.95,output_fp=output_fp)
actual_file_output = list(open(output_fp))
actual_file_output.sort()
# remove the output_fp before running the tests, so if they
# fail the output file is still cleaned-up
remove(output_fp)
# None return value on write to file
self.assertEqual(actual_return_value,None)
# check that each line starts with the correct seq_id -- not
# checking the taxonomies or confidences here as these are variable and
# tested elsewhere
for a,e in zip(actual_file_output,expected_file_headers):
self.assertTrue(a.startswith(e))
def test_train_rdp_classifier(self):
results = train_rdp_classifier(
self.reference_file, self.taxonomy_file, self.training_dir)
exp_file_list = [
'bergeyTrainingTree.xml', 'genus_wordConditionalProbList.txt',
'logWordPrior.txt', 'RdpClassifier.properties',
'wordConditionalProbIndexArr.txt',
]
obs_file_list = listdir(self.training_dir)
exp_file_list.sort()
obs_file_list.sort()
self.assertEqual(obs_file_list, exp_file_list)
autogenerated_headers = {
'bergeyTree': 'bergeyTrainingTree',
'probabilityList': 'genus_wordConditionalProbList',
'wordPrior': 'logWordPrior',
'probabilityIndex': 'wordConditionalProbIndexArr',
}
for id, basename in autogenerated_headers.iteritems():
obs_header = results[id].readline()
exp_header = exp_training_header_template % basename
self.assertEqual(exp_header, obs_header)
def test_train_rdp_classifier_and_assign_taxonomy(self):
obs = train_rdp_classifier_and_assign_taxonomy(self.reference_file,
self.taxonomy_file, self.test_trained_input, min_confidence=0.80,
model_output_dir=self.training_dir)
exp = {'X67228': ('Bacteria;Proteobacteria;Alphaproteobacteria;Rhizobiales;Rhizobiaceae;Rhizobium', 1.0)}
self.assertEqual(obs, exp)
def parse_rdp(line):
"""Returns a list of assigned taxa from an RDP classification line
"""
tokens = line.split('; ')
# Keep even-numbered tokens
return [t for (pos, t) in enumerate(tokens) if (pos % 2 == 0)]
# Sample data copied from rdp_classifier-2.0, which is licensed under
# the GPL 2.0 and Copyright 2008 Michigan State University Board of
# Trustees
rdp_training_sequences = """>X67228 Bacteria;Proteobacteria;Alphaproteobacteria;Rhizobiales;Rhizobiaceae;Rhizobium
aacgaacgctggcggcaggcttaacacatgcaagtcgaacgctccgcaaggagagtggcagacgggtgagtaacgcgtgggaatctacccaaccctgcggaatagctctgggaaactggaattaataccgcatacgccctacgggggaaagatttatcggggatggatgagcccgcgttggattagctagttggtggggtaaaggcctaccaaggcgacgatccatagctggtctgagaggatgatcagccacattgggactgagacacggcccaaa
>X73443 Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiaceae;Clostridium
nnnnnnngagatttgatcctggctcaggatgaacgctggccggccgtgcttacacatgcagtcgaacgaagcgcttaaactggatttcttcggattgaagtttttgctgactgagtggcggacgggtgagtaacgcgtgggtaacctgcctcatacagggggataacagttagaaatgactgctaataccnnataagcgcacagtgctgcatggcacagtgtaaaaactccggtggtatgagatggacccgcgtctgattagctagttggtggggt
>AB004750 Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Enterobacter
acgctggcggcaggcctaacacatgcaagtcgaacggtagcagaaagaagcttgcttctttgctgacgagtggcggacgggtgagtaatgtctgggaaactgcccgatggagggggataactactggaaacggtagctaataccgcataacgtcttcggaccaaagagggggaccttcgggcctcttgccatcggatgtgcccagatgggattagctagtaggtggggtaacggctcacctaggcgacgatccctagctggtctgagaggatgaccagccacactggaactgagacacggtccagactcctacgggaggcagcagtggggaatattgca
>xxxxxx Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Pseudomonadaceae;Pseudomonas
ttgaacgctggcggcaggcctaacacatgcaagtcgagcggcagcannnncttcgggaggctggcgagcggcggacgggtgagtaacgcatgggaacttacccagtagtgggggatagcccggggaaacccggattaataccgcatacgccctgagggggaaagcgggctccggtcgcgctattggatgggcccatgtcggattagttagttggtggggtaatggcctaccaaggcgacgatccgtagctggtctgagaggatgatcagccacaccgggactgagacacggcccggactcctacgggaggcagcagtggggaatattggacaatgggggcaaccctgatccagccatgccg
>AB004748 Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Enterobacter
acgctggcggcaggcctaacacatgcaagtcgaacggtagcagaaagaagcttgcttctttgctgacgagtggcggacgggtgagtaatgtctgggaaactgcccgatggagggggataactactggaaacggtagctaataccgcataacgtcttcggaccaaagagggggaccttcgggcctcttgccatcggatgtgcccagatgggattagctagtaggtggggtaacggctcacctaggcgacgatccctagctggtctgagaggatgaccagccacactggaactgagacacggtccagactcctacgggaggcagcagtggggaatattgcacaatgggcgcaagcctgatgcagccatgccgcgtgtatgaagaaggccttcgggttg
>AB000278 Bacteria;Proteobacteria;Gammaproteobacteria;Vibrionales;Vibrionaceae;Photobacterium
caggcctaacacatgcaagtcgaacggtaanagattgatagcttgctatcaatgctgacgancggcggacgggtgagtaatgcctgggaatataccctgatgtgggggataactattggaaacgatagctaataccgcataatctcttcggagcaaagagggggaccttcgggcctctcgcgtcaggattagcccaggtgggattagctagttggtggggtaatggctcaccaaggcgacgatccctagctggtctgagaggatgatcagccacactggaactgagacacggtccagactcctacgggaggcagcagtggggaatattgcacaatgggggaaaccctgatgcagccatgccgcgtgta
>AB000390 Bacteria;Proteobacteria;Gammaproteobacteria;Vibrionales;Vibrionaceae;Vibrio
tggctcagattgaacgctggcggcaggcctaacacatgcaagtcgagcggaaacgantnntntgaaccttcggggnacgatnacggcgtcgagcggcggacgggtgagtaatgcctgggaaattgccctgatgtgggggataactattggaaacgatagctaataccgcataatgtctacggaccaaagagggggaccttcgggcctctcgcttcaggatatgcccaggtgggattagctagttggtgaggtaatggctcaccaaggcgacgatccctagctggtctgagaggatgatcagccacactggaactgag
"""
rdp_training_taxonomy = """1*Bacteria*0*0*domain
765*Firmicutes*1*1*phylum
766*Clostridia*765*2*class
767*Clostridiales*766*3*order
768*Clostridiaceae*767*4*family
769*Clostridium*768*5*genus
160*Proteobacteria*1*1*phylum
433*Gammaproteobacteria*160*2*class
586*Vibrionales*433*3*order
587*Vibrionaceae*586*4*family
588*Vibrio*587*5*genus
592*Photobacterium*587*5*genus
552*Pseudomonadales*433*3*order
553*Pseudomonadaceae*552*4*family
554*Pseudomonas*553*5*genus
604*Enterobacteriales*433*3*order
605*Enterobacteriaceae*604*4*family
617*Enterobacter*605*5*genus
161*Alphaproteobacteria*160*2*class
260*Rhizobiales*161*3*order
261*Rhizobiaceae*260*4*family
262*Rhizobium*261*5*genus
"""
exp_training_header_template = "1 version1 cogent %s \n"
rdp_trained_fasta = """>X67228
aacgaacgctggcggcaggcttaacacatgcaagtcgaacgctccgcaaggagagtggcagacgggtgagtaacgcgtgggaatctacccaaccctgcggaatagctctgggaaactggaattaataccgcatacgccctacgggggaaagatttatcggggatggatgagcccgcgttggattagctagttggtggggtaaaggcctaccaaggcgacgatccatagctggtctgagaggatgatcagccacattgggactgagacacggcccaaa
"""
rdp_sample_fasta = """>X67228 Bacteria;Proteobacteria;Alphaproteobacteria;Rhizobiales;Rhizobiaceae;Rhizobium
aacgaacgctggcggcaggcttaacacatgcaagtcgaacgctccgcaaggagagtggcagacgggtgagtaacgcgtgggaatctacccaaccctgcggaatagctctgggaaactggaattaataccgcatacgccctacgggggaaagatttatcggggatggatgagcccgcgttggattagctagttggtggggtaaaggcctaccaaggcgacgatccatagctggtctgagaggatgatcagccacattgggactgagacacggcccaaa
"""
rdp_sample_classification = """>X67228 reverse=false
Root; 1.0; Bacteria; 1.0; Proteobacteria; 1.0; Alphaproteobacteria; 1.0; Rhizobiales; 1.0; Rhizobiaceae; 1.0; Rhizobium; 0.95;
"""
rdp_test_fasta = """>AY800210 description field
TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGATGCGACTAAGCCATGCTAGTCTAACGGATCTTCGGATCCGTGGCATACCGCTCTGTAACACGTAGATAACCTACCCTGAGGTCGGGGAAACTCCCGGGAAACTGGGCCTAATCCCCGATAGATAATTTGTACTGGAATGTCTTTTTATTGAAACCTCCGAGGCCTCAGGATGGGTCTGCGCCAGATTATGGTCGTAGGTGGGGTAACGGCCCACCTAGCCTTTGATCTGTACCGGACATGAGAGTGTGTGCCGGGAGATGGCCACTGAGACAAGGGGCCAGGCCCTACGGGGCGCAGCAGGCGCGAAAACTTCACAATGCCCGCAAGGGTGATGAGGGTATCCGAGTGCTACCTTAGCCGGTAGCTTTTATTCAGTGTAAATAGCTAGATGAATAAGGGGAGGGCAAGGCTGGTGCCAGCCGCCGCGGTAAAACCAGCTCCCGAGTGGTCGGGATTTTTATTGGGCCTAAAGCGTCCGTAGCCGGGCGTGCAAGTCATTGGTTAAATATCGGGTCTTAAGCCCGAACCTGCTAGTGATACTACACGCCTTGGGACCGGAAGAGGCAAATGGTACGTTGAGGGTAGGGGTGAAATCCTGTAATCCCCAACGGACCACCGGTGGCGAAGCTTGTTCAGTCATGAACAACTCTACACAAGGCGATTTGCTGGGACGGATCCGACGGTGAGGGACGAAACCCAGGGGAGCGAGCGGGATTAGATACCCCGGTAGTCCTGGGCGTAAACGATGCGAACTAGGTGTTGGCGGAGCCACGAGCTCTGTCGGTGCCGAAGCGAAGGCGTTAAGTTCGCCGCCAGGGGAGTACGGCCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCAC
>EU883771
TGGCGTACGGCTCAGTAACACGTGGATAACTTACCCTTAGGACTGGGATAACTCTGGGAAACTGGGGATAATACTGGATATTAGGCTATGCCTGGAATGGTTTGCCTTTGAAATGTTTTTTTTCGCCTAAGGATAGGTCTGCGGCTGATTAGGTCGTTGGTGGGGTAATGGCCCACCAAGCCGATGATCGGTACGGGTTGTGAGAGCAAGGGCCCGGAGATGGAACCTGAGACAAGGTTCCAGACCCTACGGGGTGCAGCAGGCGCGAAACCTCCGCAATGTACGAAAGTGCGACGGGGGGATCCCAAGTGTTATGCTTTTTTGTATGACTTTTCATTAGTGTAAAAAGCTTTTAGAATAAGAGCTGGGCAAGACCGGTGCCAGCCGCCGCGGTAACACCGGCAGCTCGAGTGGTGACCACTTTTATTGGGCTTAAAGCGTTCGTAGCTTGATTTTTAAGTCTCTTGGGAAATCTCACGGCTTAACTGTGAGGCGTCTAAGAGATACTGGGAATCTAGGGACCGGGAGAGGTAAGAGGTACTTCAGGGGTAGAAGTGAAATTCTGTAATCCTTGAGGGACCACCGATGGCGAAGGCATCTTACCAGAACGGCTTCGACAGTGAGGAACGAAAGCTGGGGGAGCGAACGGGATTAGATACCCCGGTAGTCCCAGCCGTAAACTATGCGCGTTAGGTGTGCCTGTAACTACGAGTTACCGGGGTGCCGAAGTGAAAACGTGAAACGTGCCGCCTGGGAAGTACGGTCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCACCACAACGGGTGGAGCCTGCGGTTTAATTGGACTCAACGCCGGGCAGCTCACCGGATAGGACAGCGGAATGATAGCCGGGCTGAAGACCTTGCTTGACCAGCTGAGA
>EF503699
AAGAATGGGGATAGCATGCGAGTCACGCCGCAATGTGTGGCATACGGCTCAGTAACACGTAGTCAACATGCCCAGAGGACGTGGACACCTCGGGAAACTGAGGATAAACCGCGATAGGCCACTACTTCTGGAATGAGCCATGACCCAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGGAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCACGAAACCTCTGCAATAGGCGAAAGCTTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCCGCTTAACGGATGGGCTGCGGAGGATACTGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCTTTGATCTACTGAAGACCACCAGTGGTGAAGGCGGTTCGCCAGAACGCGCTCGAACGGTGAGGATGAAAGCTGGGGGAGCAAACCGGAATAGATACCCGAGTAATCCCAACTGTAAACGATGGCAACTCGGGGATGGGTTGGCCTCCAACCAACCCCATGGCCGCAGGGAAGCCGTTTAGCTCTCCCGCCTGGGGAATACGGTCCGCAGAATTGAACCTTAAAGGAATTTGGCGGGGAACCCCCACAAGGGGGAAAACCGTGCGGTTCAATTGGAATCCACCCCCCGGAAACTTTACCCGGGCGCG
>random_seq
AAGCTCCGTCGCGTGAGCTAAAAACCATGCTGACTTATGAGACCTAAAAGCGATGCGCCGACCTGACGATGCTCTGTTCAGTTTCATCACGATCACCGGTAGTCAGGGTACCCTCCAGACCGCGCATAGTGACTATGTTCCCGCACCTGTATATGTAATTCCCATTATACGTCTACGTTATGTAGTAAAGTTGCTCACGCCAGGCACAGTTTGTCTTGATACATAGGGTAGCTTAAGTCCCGTCCATTTCACCGCGATTGTAATAGACGAATCAGCAGTGGTGCAATCAAGTCCCAACAGTTATATTTCAAAAATCTTCCGATAGTCGTGGGCGAAGTTGTCAACCTACCTACCATGGCTATAAGGCCCAGTTTACTTCAGTTGAACGTGACGGTAACCCTACTGAGTGCACGATACCTGCTCAACAACGGCCCAAAACCCGTGCGACACATTGGGCACTACAATAATCTTAGAGGACCATGGATCTGGTGGGTGGACTGAAGCATATCCCAAAAGTGTCGTGAGTCCGTTATGCAATTGACTGAAACAGCCGTACCAGAGTTCGGATGACCTCTGGGTTGCTGCGGTACACACCCGGGTGCGGCTTCTGAAATAGAAAAGACTAAGCATCGGCCGCCTCACACTTCAAGGGCCCTATGCCTAACAGTCTAGCAAATGCTTGAACCTTGTACCAAAGTTCAGACTTACCTTTACTTGGTTATCGCCCTTGAACCTGTAACCGTCACGTGGTCTACAATTCGTGGATTCCTGCATGAGGATGAACGGGTCCCTTCTCGTGCTACGTAGGCAGTATGTTCAACAACAAGAGGGTAATGCAATGGGGCTTAGAATCCCTTGACCGCAGAACACGTGGGGACTGCATTTCCACGTCGGTACTAATCCTCTGATTCTGTTCGTTATGTCCAAGACCATATCATCTTAATACCTATCAGACCTACGCTCTTCTGTCTGAACCCTAAAACGTTCGGAATAGCACGATCGTCCGGTTTGAACTGACGTGTAGGACTCTCGTTGCTCCCTGGTAATCATTCAGGCCCTGGCGTAATGCCCTTACTGACTACCACTGGCCTGGTTAGCAGCATCATTCTTAGGTGGAAGTGTTGGTCGCTGTTCTCCCATTGTGTCGAGTTTCCTCCGCGATCTCGTCACCGGGCGAGTTTTTAACTGCGACATCAACGTGTGGGTTTGACTTACCGCGCAGCATCGGGCCAACAGCCTTCGACAGCTAGAAGCTGGAAAATTAGTAAATAGTCCAGCACCGTTATATACATCTACTTGCTCGGAGGGGCACAGACGGCAGCGGACTCACGCCCGTTTTCAACCCTGGTAAAGAGGACGCGCGTTCATGAGGCGTAGGGATGCATTGCTCCTGATCCATGTTCTCAATTACGCTTCAATTCTGAGTATTAGACCTCACGCACGCAGTAAGCTTACTGGTCTCACTGCCATATTACTAGCTTAAAATAGCGGTCCAAAGACGCGGCATGATTAACGACAGCCCTTCACTTCACGGACCTCACGCCCGATATAGCGTACGTTCAGGGCTTGGAAAGGCGGACAATAATAAGCATGCAATAGCTAAGATTGTAGGAACTTCCATCCGCCGAACACAGCCCCTCGCCACAACGGTTGGAACCCGCGCTATGCCGTAAAGCGGCCAAAACGTCGCGCGCCACCACAAGATAGTGCTCAAAGCCCGCAGGGAGAGTCGGTGCTTGGTGCCTTCGCTACGGGGCCCAATAGCTTGCTTTTTCTTGCGCCGATTGACTCTAGGTAAACTCACCGTGACATACCGCATAAATCTGCAAGGGTGGTCCTGACTAAAGAGCTCTATAGCGATGATGGTGGCCTTAGACAGCACAAGCTGAACTTATTAATTCTTACCAGGTCCCGTGGGGTTCCGGAACATGAGTATGCTCTTTGGAACGGGCTTTGTCCACGTGTAAGGATGGTTACGTCCCGGGCGTATTGCACTACGTTCAAGTGGTGTAAGACAGAGTGACTAGAGACAGTGCCGTTATCACTATTGTGGGGCCCATCCTAAGGCTGAGGACACGGAACATGTCTCTTTATCATCGCACGAGCTGTATGCCACTGTATTCCTCTACCTTAGCCATCGCTCATTTAACGCCACGTGTAGCGGTGCAGGCTACGAGGCTTAAGTCTGCTCGGCTTGCTGAGCATATCCCTATAAATGAATGAGGAATAAAGGACATGACGCATTCCCGGCACCTGACAACAGGACGCAATTACTAAGTAGGCTTATGTAGTCTCGTGTAATGCAGACCGCTCTTAAGAGTCGGATCATAATTTGAGCAGAACAAAATTACTTATGCCCTTACAAGACGTGTGCAAACCTAAGTGTGAAGATTTAGGAGGCACCGCGTTTTATGGCTTCTGCGAATATATTGTGATTTCCTGAATAGTGGGGTGGGATGTAATGGACTGAAAAAGGTGAACATCTTAAGCCTACCAGTCATATTCCCGCCGGAACTTACTTAAATCAATGGACACTCAAAGAGACTTTGAAGCTCTTTATACCGATGTGCGCGCAAACCCCTCGAGTGCTGTCCTGCAACACCCTAAGTTGCAGTATGTTGGTTACAGCGATCATTTATAGGTTAAAATGGCTAAATGAGCTAGCGCCGCGGCCCGGAAGAACAGATTTCGTGAGGTGACCTGGCGAATGTGAATCCTGAAAATTTTCACACGACCACAGCAAAGCCGTTGGGCAAGTTCCGGCAACTAAGCCGAAGGTGACCCTGTACTGGCAGGGGTTTACCATGATGGAATGACCGGAATCAAGGCAAGGAAACACCGAGTACAGTTACGAGCAAACACGCGTAAATTAAATTACTGCAGTATAACTCGTTCACCAATTCGGGTCGGCCGACGTGCACGTCAACCAGGCATACGACACGTGAAATTCACTGCCGACACCACTGTTTCGATTACCATGTGTCTGGTCTTTCAAAGCACAGAGAGAGGCCCTCGCCGGTAAATTACGGACTCGTATGTGTTAACCGGGAATAGGTGGGACGGATCAACACTTAAGTTGGACAGACCAAAAACTAGCCGAAAACCTTCACAAAAAGAGTCATGAATGATCCGTCAAGGACAGCGCTCTCCCACCGCTGGATGGCAATCGCAAGGTATCAATCAATAGTGATGTCTACGAGTCTTACACAGGTGTCCTGGATGTAACTACTGTTGCCACGAGGAACGTATACACCCCAGCCTGCGTAATGTATGATCTTTTCGCGTTCTGAATCCAGAATATATTAGTGAAGGTCCCAAAGACACCTATTAATCGGTCCCAGTCGTTTGTCCTACATTTCTGTGTAGCCAGGGGTCCCCTATTACTCCTAATGAGGGATTGGCGCCGGGTAGAGTCTACGCCAAAGCGGCAAAGAGATTGATCACCGGCCGGGTACAATGCAGACTTTACATTCAGAGCGTGTTTGCCGCGTAATGCTTAATTCACTGCTGGCGCACCTCGCAGAATTACCTATATTTCCTCTTCCTCACTAAACTGGTGTTCAGAGATGGTCGATTTTCCGGTGTGGTTTATAGCAGGTCCCGCCACATGCAACACATACCGAACATCGCTATCAGTGTTGTTCTCGTCGCCGCGACTCCTGACTCGCGATTAGTTGGCTAGCTCCCAGCGCTAGCTCCGCCTCTGTCTGTATATCGCCAGTAATCAGTTTTCAATGACGTTGACTTATTTATAAACGAGCTGAAGCATCTCTCGCGCCCTAGCGTTACTACTATCAGGAACCGCCGTGTGGGAACTCCTCTACCTCACCACCCTGCCAGCTCCTATGACAACGTTTAGTCCGCGTACTGACAGGGAGAGAGAAGCGTTACGGGACCGTCTGAACAGTATGTTGGCAGAGGAAGGCCAGGGCTCCCTATGGTTTTAGGTT
>DQ260310
GATACCCCCGGAAACTGGGGATTATACCGGATATGTGGGGCTGCCTGGAATGGTACCTCATTGAAATGCTCCCGCGCCTAAAGATGGATCTGCCGCAGAATAAGTAGTTTGCGGGGTAAATGGCCACCCAGCCAGTAATCCGTACCGGTTGTGAAAACCAGAACCCCGAGATGGAAACTGAAACAAAGGTTCAAGGCCTACCGGGCACAACAAGCGCCAAAACTCCGCCATGCGAGCCATCGCGACGGGGGAAAACCAAGTACCACTCCTAACGGGGTGGTTTTTCCGAAGTGGAAAAAGCCTCCAGGAATAAGAACCTGGGCCAGAACCGTGGCCAGCCGCCGCCGTTACACCCGCCAGCTCGAGTTGTTGGCCGGTTTTATTGGGGCCTAAAGCCGGTCCGTAGCCCGTTTTGATAAGGTCTCTCTGGTGAAATTCTACAGCTTAACCTGTGGGAATTGCTGGAGGATACTATTCAAGCTTGAAGCCGGGAGAAGCCTGGAAGTACTCCCGGGGGTAAGGGGTGAAATTCTATTATCCCCGGAAGACCAACTGGTGCCGAAGCGGTCCAGCCTGGAACCGAACTTGACCGTGAGTTACGAAAAGCCAAGGGGCGCGGACCGGAATAAAATAACCAGGGTAGTCCTGGCCGTAAACGATGTGAACTTGGTGGTGGGAATGGCTTCGAACTGCCCAATTGCCGAAAGGAAGCTGTAAATTCACCCGCCTTGGAAGTACGGTCGCAAGACTGGAACCTAAAAGGAATTGGCGGGGGGACACCACAACGCGTGGAGCCTGGCGGTTTTATTGGGATTCCACGCAGACATCTCACTCAGGGGCGACAGCAGAAATGATGGGCAGGTTGATGACCTTGCTTGACAAGCTGAAAAGGAGGTGCAT
>EF503697
TAAAATGACTAGCCTGCGAGTCACGCCGTAAGGCGTGGCATACAGGCTCAGTAACACGTAGTCAACATGCCCAAAGGACGTGGATAACCTCGGGAAACTGAGGATAAACCGCGATAGGCCAAGGTTTCTGGAATGAGCTATGGCCGAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGTAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCGCGAAACCTCTGCAATAGGCGAAAGCCTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCTGCTCAACGGATGGGCTGCGGAGGATACCGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCATTGATCTACTGAAGACCACCAGTGGCGAAGGCGGTTTGCCAGAACGCGCTCGACGGTGAGGGATGAAAGCTGGGGGAGCAAACCGGATTAGATACCCGGGGTAGTCCCAGCTGTAAACGGATGCAGACTCGGGTGATGGGGTTGGCTTCCGGCCCAACCCCAATTGCCCCCAGGCGAAGCCCGTTAAGATCTTGCCGCCCTGTCAGATGTCAGGGCCGCCAATACTCGAAACCTTAAAAGGAAATTGGGCGCGGGAAAAGTCACCAAAAGGGGGTTGAAACCCTGCGGGTTATATATTGTAAACC
>short_seq
TAAAATGACTAGCCTGCGAGTCACGCCGTAAGGCGTGGC
"""
rdp_expected_out = {
'AY800210 description field': ('Root;Archaea;Euryarchaeota', 0.9),
'EU883771': ('Root;Archaea;Euryarchaeota;Methanobacteria;Methanobacteriales;Methanobacteriaceae;Methanosphaera', 0.92),
'EF503699': ('Root;Archaea;Crenarchaeota;Thermoprotei', 0.82),
'random_seq': ('Root', 1.0),
'DQ260310': ('Root;Archaea;Euryarchaeota;Methanobacteria;Methanobacteriales;Methanobacteriaceae', 0.93),
'EF503697': ('Root;Archaea;Crenarchaeota;Thermoprotei', 0.88),
'short_seq': ('Unassignable', 1.0)
}
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_rnaalifold.py 000644 000765 000024 00000006643 12024702176 022757 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.rnaalifold import RNAalifold, rnaalifold_from_alignment
from cogent.core.alignment import DataError
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman","Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class RnaalifoldTest(TestCase):
"""Tests for Rnaalifold application controller"""
def setUp(self):
self.input = RNAALIFOLD_INPUT
self.unaligned = \
{'seq_0': 'GGUAGGUCGCUGGACUUGUCUCCUUGACUGUCCGGAAGGAGCGGU',
'seq_1': 'GGUAGGUCGCUGGAUUGAUAUGAGUAUUGUCCGGAAGGAGCGGA',
'seq_2': 'GGUAGGACGCGGGACUUCUGUUCAGGACUGUCCCGAAGGUGCGGU',
'seq_3': 'GGUAGGUCGCCGCACGUCGCUUCAGGACUGUGCGGAAGGAGCGGU',
'seq_4': 'GGUAGGUCGCUGUACUUCUAUCAGGACUGUACGGAAGGAGCGGU',
}
self.alignment = \
{'seq_0': 'GGUAGGUCGCUGGAC-UUGUCUCCUUGACU-GUCCGGAAGGAGCGGU',
'seq_1': 'GGUAGGUCGCUGGAU-UGAUAUGAGUAUU--GUCCGGAAGGAGCGGA',
'seq_2': 'GGUAGGACGCGGGAC-UUCUGUUCAGGACU-GUCCCGAAGGUGCGGU',
'seq_3': 'GGUAGGUCGCCGCACGUCGCUUCAGGAC--UGUGCGGAAGGAGCGGU',
'seq_4': 'GGUAGGUCGCUGUAC-UUCUAUCAGGACU--GUACGGAAGGAGCGGU',
}
self.old_struct = '....(.((.((((((..(((....)))....))))))...)).)...'
#from version 1.4
self.new_struct = '....(.((.((((((................))))))...)).)...'
#from version 1.8 - no easy way to check version so putting both in
def test_input_as_lines(self):
"""Test rnaalifold stdout input as lines"""
r = RNAalifold(InputHandler='_input_as_lines')
res = r(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_input_as_string(self):
"""Test rnaalifold stdout input as string"""
r = RNAalifold()
f = open('/tmp/clustal','w')
f.write('\n'.join(self.input))
f.close()
res = r('/tmp/clustal')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/clustal')
def test_get_result_path(self):
"""Tests rnaalifold result path"""
r = RNAalifold(InputHandler='_input_as_lines')
res = r(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus','SS'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_rnaalifold_from_alignment_unaligned(self):
"""rnaalifold_from_alignment should handle unaligned seqs.
"""
self.assertRaises(DataError,rnaalifold_from_alignment,self.unaligned)
def test_rnaalifold_from_alignment(self):
"""rnaalifold_from_alignment should give correct result.
"""
[[seq, struct,energy]] = rnaalifold_from_alignment(aln=self.alignment)
try:
self.assertEqual(struct,self.old_struct)
except AssertionError:
self.assertEqual(struct,self.new_struct)
RNAALIFOLD_INPUT = ['CLUSTAL\n', '\n', 'seq1 GGCTAGATAGCTCAGATGGT-AGAGCAGAGGATTGAAGATCCTTGTGTCGTCGGTTCGATCCCGGCTCTGGCC----\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_rnaforester.py 000644 000765 000024 00000015257 12024702176 023177 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.app.rnaforester import RNAforester
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class RnaforesterTest(TestCase):
"""Tests for Rnaforester application controller"""
def setUp(self):
self.input = rnaforester_input
def test_stdout_input_as_lines(self):
"""Test rnaforester stdout input as lines"""
r = RNAforester(InputHandler='_input_as_lines')
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in rnaforester_stdout])
res = r(self.input)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test rnaforester stdout input as string"""
r = RNAforester()
exp = '%s\n' % '\n'.join([str(i).strip('\n') for i in rnaforester_stdout])
f = open('/tmp/input.fasta','w')
txt = '\n'.join([str(i).strip('\n') for i in self.input])
f.write(txt)
f.close()
res = r('/tmp/input.fasta')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('/tmp/input.fasta')
def test_get_result_path(self):
"""Tests rnaforester result path"""
r = RNAforester(InputHandler='_input_as_lines')
res = r(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus'])
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
rnaforester_input = ['>seq1\n',
'GGCCACGTAGCTCAGTCGGTAGAGCAAAGGACTGAAAATCCTTGTGTCGTTGGTTCAATTCCAACCGTGGCCACCA\n', '>seq2\n',
'GCCAGATAGCTCAGTCGGTAGAGCGTTCGCCTGAAAAGTGAAAGGTCGCCGGTTCGATCCCGGCTCTGGCCACCA\n']
rnaforester_stdout = ['*** Scoring parameters ***\n', '\n', 'Scoring type: similarity\n', 'Scoring parameters:\n', 'pm: 10\n', 'pd: -5\n', 'bm: 1\n', 'br: 0\n', 'bd: -10\n', '\n', '\n', 'Input string (upper or lower case); & to end for multiple alignments, @ to quit\n', '....,....1....,....2....,....3....,....4....,....5....,....6....,....7....,....8\n', '\n', '*** Calculation ***\n', '\n', 'clustering threshold is: 0.7\n', 'join clusters cutoff is: 0\n', '\n', 'Computing all pairwise similarities\n', '2,1: 0.74606\n', '\n', 'joining alignments:\n', '1,2: 0.74606 -> 1\n', 'Calculate similarities to other clusters\n', '\n', '\n', '*** Results ***\n', '\n', 'Minimum basepair probability for consensus structure (-cmin): 0.5\n', '\n', 'RNA Structure Cluster Nr: 1\n', 'Score: 264.25\n', 'Members: 2\n', '\n', 'seq1 ggccacguagcucagucgguagagcaaaggacugaaaauccuugugucguugguu\n', 'seq2 -gccagauagcucagucgguagagcguucgccugaaaagugaaaggucgccgguu\n', ' **** ****************** * ******* **** ****\n', '\n', 'seq1 caauuccaaccguggccacca\n', 'seq2 cgaucccggcucuggccacca\n', ' * ** ** * *********\n', '\n', 'seq1 (((((((..((((........)))).(((((.......))))).....(((((..\n', 'seq2 -((((((..((((........)))).((((.((....)))))).....(((((..\n', ' ***************************** **** *****************\n', '\n', 'seq1 .....))))))))))))....\n', 'seq2 .....))))))))))).....\n', ' **************** ****\n', '\n', '\n', 'Consensus sequence/structure:\n', ' 100% **** ****************** * ******* **** ****\n', ' 90% **** ****************** * ******* **** ****\n', ' 80% **** ****************** * ******* **** ****\n', ' 70% **** ****************** * ******* **** ****\n', ' 60% **** ****************** * ******* **** ****\n', ' 50% *******************************************************\n', ' 40% *******************************************************\n', ' 30% *******************************************************\n', ' 20% *******************************************************\n', ' 10% *******************************************************\n', ' ggccacauagcucagucgguagagcaaacgacugaaaagccaaaggucgccgguu\n', ' (((((((..((((........)))).((((.((....)))))).....(((((..\n', ' 10% *******************************************************\n', ' 20% *******************************************************\n', ' 30% *******************************************************\n', ' 40% *******************************************************\n', ' 50% *******************************************************\n', ' 60% *******************************************************\n', ' 70% ****************************** **** ****************\n', ' 80% ****************************** **** ****************\n', ' 90% ****************************** **** ****************\n', ' 100% ****************************** **** ****************\n', '\n', ' 100% * ** ** * *********\n', ' 90% * ** ** * *********\n', ' 80% * ** ** * *********\n', ' 70% * ** ** * *********\n', ' 60% * ** ** * *********\n', ' 50% *********************\n', ' 40% *********************\n', ' 30% *********************\n', ' 20% *********************\n', ' 10% *********************\n', ' caaucccaacccuggccacca\n', ' .....))))))))))))....\n', ' 10% *********************\n', ' 20% *********************\n', ' 30% *********************\n', ' 40% *********************\n', ' 50% *********************\n', ' 60% *********************\n', ' 70% **************** ****\n', ' 80% **************** ****\n', ' 90% **************** ****\n', ' 100% **************** ****\n', '\n', '\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_rnaview.py 000644 000765 000024 00001056324 12024702176 022321 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.app.rnaview import RnaView
from tempfile import mktemp, tempdir
from os import remove, system, getcwd
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Greg Caporaso", "Sandra Smit", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Greg Caporaso"
__email__ = "Greg Caporaso"
__status__ = "Production"
class test_rnaview(TestCase):
""" Tests of the rnaview application controller """
def setUp(self):
""" SetUp some objects for use by tests """
# Define the directory where mktemp creates files, this simplifies
# things b/c if ~/tmp exists files are created there, otherwise they
# are created in /tmp. For the case of tests, it's easier just to
# set it to a constant
self.fake_pdb_file = fake_pdb_file
self.fake_nmr_file = fake_nmr_file
self.r1 = RnaView(WorkingDir='/tmp')
self.r_input_as_lines = RnaView(WorkingDir='/tmp',\
InputHandler='_input_as_lines')
self.r2 = RnaView(params={'-v':None},WorkingDir='/tmp')
self.r3 = RnaView(params={'-c':'A'},WorkingDir='/tmp')
self.r4 = RnaView(params={'-x':None,'-p':None},WorkingDir='/tmp')
self.r5 = RnaView()
def test_base_command(self):
"""RnaView: BaseCommand is built correctly """
self.assertEqual(self.r1.BaseCommand, 'cd "/tmp/"; rnaview')
self.assertEqual(self.r2.BaseCommand, 'cd "/tmp/"; rnaview -v')
self.assertEqual(self.r3.BaseCommand, 'cd "/tmp/"; rnaview -c A')
assert (self.r4.BaseCommand == 'cd "/tmp/"; rnaview -x -p') or \
(self.r4.BaseCommand == 'cd "/tmp/"; rnaview -p -x')
self.assertEqual(self.r5.BaseCommand,\
'cd "' + getcwd() + '/'+ '"; rnaview')
def test_file_pointers_no_extras_input_as_file(self):
"""RnaView: pointers created only for minimal files w/ _input_as_lines
"""
written_files = {}.fromkeys(['bp_stats','base_pairs',\
'StdOut','StdErr','ExitStatus'])
res =self.r_input_as_lines(data=self.fake_pdb_file.split('\n'))
for f in res:
if f in written_files:
assert res[f] is not None
else:
assert res[f] is None
res.cleanUp()
def test_file_pointers_no_extras(self):
"""RnaView: pointers created only for minimal files
"""
filename = mktemp() + '.pdb'
f = open(filename,"w")
f.writelines(self.fake_pdb_file)
f.close()
written_files = {}.fromkeys(['bp_stats','base_pairs',\
'StdOut','StdErr','ExitStatus'])
res = self.r1(data=filename)
for f in res:
if f in written_files:
assert res[f] is not None
else:
assert res[f] is None
res.cleanUp()
remove(filename)
def test_file_pointers_w_vrml(self):
"""RnaView: pointers created for minimal files and files turned on
"""
# need to make a fake pdb file with base pairs so that wrl file will be
# created
filename = mktemp() + '.pdb'
f = open(filename,"w")
f.writelines(self.fake_pdb_file)
f.close()
written_files = {}.fromkeys(['bp_stats','base_pairs',\
'StdOut','StdErr','ExitStatus','vrml'])
res = self.r2(data=filename)
for f in res:
if f in written_files:
assert res[f] is not None
else:
assert res[f] is None
res.cleanUp()
remove(filename)
def test_base_pairs_out(self):
"""RnaView: output sanity check """
filename = mktemp()
f = open(filename,"w")
f.writelines(self.fake_pdb_file)
f.close()
res = self.r2(data=filename)
bp_file = list(res['base_pairs'])
self.assertEqual(bp_file[0],'PDB data file name: ' + filename + '\n')
res.cleanUp()
remove(filename)
def test_get_pdb_filename(self):
"""RnaView: _get_pdb_filename functions as expected """
#Test X-RAY CRYSTALLOGRAPHY file
f = open('/tmp/1EHZ.pdb',"w")
f.writelines(self.fake_pdb_file)
f.close()
self.assertEqual(self.r1._get_pdb_filename('/tmp/1EHZ.pdb'),'1EHZ.pdb')
remove('/tmp/1EHZ.pdb')
#Test NMR file
f = open('/tmp/pdb17.ent',"w")
f.writelines(self.fake_nmr_file)
f.close()
self.assertEqual(self.r1._get_pdb_filename('/tmp/pdb17.ent'),\
'pdb17.ent_nmr.pdb')
remove('/tmp/pdb17.ent')
#OLD TESTS BEFORE THE ACTUAL FILE HAD TO BE THERE
#self.assertEqual(self.r1._get_pdb_filename('/tmp/1EHZ.pdb'),'1EHZ.pdb')
#self.assertEqual(self.r1._get_pdb_filename('/tmp/duh/1EHZ.pdb'),\
# '1EHZ.pdb')
#self.assertEqual(self.r1._get_pdb_filename('1EHZ1.pdb'),'1EHZ1.pdb')
#self.assertEqual(self.r1._get_pdb_filename('/1'),'1')
#self.assertEqual(self.r1._get_pdb_filename('1EHZZZ.pdb'),'1EHZZZ.pdb')
#self.assertEqual(self.r1._get_pdb_filename('/tmp/tmpW3urtc'),\
# 'tmpW3urtc')
def test_get_out_path(self):
"""RnaView: _get_out_path functions as expected """
self.assertEqual(self.r1._get_out_path('1EHZ.pdb'),'')
self.assertEqual(self.r1._get_out_path('/tmp/1EHZ.pdb'),'/tmp/')
self.assertEqual(self.r1._get_out_path('/tmp/duh/1EHZ.pdb'),'/tmp/duh/')
self.assertEqual(self.r1._get_out_path('/1'),'/')
def test_accept_exit_status(self):
"""RnaView: _accept_exit_status functions as expected """
self.assertEqual(self.r1._accept_exit_status(0),True)
self.assertEqual(self.r1._accept_exit_status(1),False)
self.assertEqual(self.r1._accept_exit_status('0'),False)
self.assertEqual(self.r1._accept_exit_status(None),False)
self.assertEqual(self.r1._accept_exit_status(''),False)
fake_pdb_file = """ATOM 1 O3P G A 1 50.193 51.190 50.534 1.00 99.85 O
ATOM 2 P G A 1 50.626 49.730 50.573 1.00100.19 P
ATOM 3 O1P G A 1 49.854 48.893 49.562 1.00100.19 O
ATOM 4 O2P G A 1 52.137 49.542 50.511 1.00 99.21 O
ATOM 5 O5* G A 1 50.161 49.136 52.023 1.00 99.82 O
ATOM 6 C5* G A 1 50.216 49.948 53.210 1.00 98.63 C
ATOM 7 C4* G A 1 50.968 49.231 54.309 1.00 97.84 C
ATOM 8 O4* G A 1 50.450 47.888 54.472 1.00 97.10 O
ATOM 9 C3* G A 1 52.454 49.030 54.074 1.00 98.07 C
ATOM 10 O3* G A 1 53.203 50.177 54.425 1.00 99.39 O
ATOM 11 C2* G A 1 52.781 47.831 54.957 1.00 96.96 C
ATOM 12 O2* G A 1 53.018 48.156 56.313 1.00 96.77 O
ATOM 13 C1* G A 1 51.502 47.007 54.836 1.00 95.70 C
ATOM 14 N9 G A 1 51.628 45.992 53.798 1.00 93.67 N
ATOM 15 C8 G A 1 51.064 46.007 52.547 1.00 92.60 C
ATOM 16 N7 G A 1 51.379 44.966 51.831 1.00 91.19 N
ATOM 17 C5 G A 1 52.197 44.218 52.658 1.00 91.47 C
ATOM 18 C6 G A 1 52.848 42.992 52.425 1.00 90.68 C
ATOM 19 O6 G A 1 52.826 42.291 51.404 1.00 90.38 O
ATOM 20 N1 G A 1 53.588 42.588 53.534 1.00 90.71 N
ATOM 21 C2 G A 1 53.685 43.282 54.716 1.00 91.21 C
ATOM 22 N2 G A 1 54.452 42.733 55.671 1.00 91.23 N
ATOM 23 N3 G A 1 53.077 44.429 54.946 1.00 91.92 N
ATOM 24 C4 G A 1 52.356 44.836 53.879 1.00 92.62 C
ATOM 25 P C A 2 54.635 50.420 53.741 1.00100.19 P
ATOM 26 O1P C A 2 55.145 51.726 54.238 1.00100.19 O
ATOM 27 O2P C A 2 54.465 50.204 52.269 1.00100.19 O
ATOM 28 O5* C A 2 55.563 49.261 54.342 1.00 98.27 O
ATOM 29 C5* C A 2 55.925 49.246 55.742 1.00 95.40 C
ATOM 30 C4* C A 2 56.836 48.075 56.049 1.00 93.33 C
ATOM 31 O4* C A 2 56.122 46.828 55.830 1.00 92.18 O
ATOM 32 C3* C A 2 58.090 47.947 55.197 1.00 92.75 C
ATOM 33 O3* C A 2 59.174 48.753 55.651 1.00 92.89 O
ATOM 34 C2* C A 2 58.416 46.463 55.298 1.00 91.81 C
ATOM 35 O2* C A 2 59.140 46.136 56.466 1.00 91.36 O
ATOM 36 C1* C A 2 57.022 45.836 55.356 1.00 90.59 C
ATOM 37 N1 C A 2 56.570 45.364 54.029 1.00 88.84 N
ATOM 38 C2 C A 2 57.094 44.157 53.520 1.00 88.64 C
ATOM 39 O2 C A 2 57.921 43.516 54.198 1.00 88.97 O
ATOM 40 N3 C A 2 56.686 43.721 52.301 1.00 87.36 N
ATOM 41 C4 C A 2 55.802 44.437 51.597 1.00 87.11 C
ATOM 42 N4 C A 2 55.430 43.972 50.397 1.00 86.30 N
ATOM 43 C5 C A 2 55.259 45.660 52.089 1.00 86.87 C
ATOM 44 C6 C A 2 55.663 46.080 53.296 1.00 88.01 C
ATOM 45 P G A 3 60.184 49.419 54.574 1.00 92.31 P
ATOM 46 O1P G A 3 61.015 50.422 55.295 1.00 92.97 O
ATOM 47 O2P G A 3 59.371 49.857 53.404 1.00 91.56 O
ATOM 48 O5* G A 3 61.137 48.219 54.105 1.00 88.57 O
ATOM 49 C5* G A 3 62.175 47.724 54.969 1.00 83.44 C
ATOM 50 C4* G A 3 62.769 46.443 54.422 1.00 79.87 C
ATOM 51 O4* G A 3 61.734 45.427 54.299 1.00 78.36 O
ATOM 52 C3* G A 3 63.405 46.499 53.040 1.00 78.97 C
ATOM 53 O3* G A 3 64.741 47.029 53.060 1.00 79.76 O
ATOM 54 C2* G A 3 63.359 45.032 52.608 1.00 77.19 C
ATOM 55 O2* G A 3 64.411 44.256 53.155 1.00 77.80 O
ATOM 56 C1* G A 3 62.018 44.572 53.194 1.00 73.98 C
ATOM 57 N9 G A 3 60.934 44.675 52.202 1.00 68.20 N
ATOM 58 C8 G A 3 60.024 45.702 52.050 1.00 65.03 C
ATOM 59 N7 G A 3 59.252 45.556 51.003 1.00 62.99 N
ATOM 60 C5 G A 3 59.655 44.348 50.447 1.00 59.95 C
ATOM 61 C6 G A 3 59.189 43.675 49.292 1.00 55.65 C
ATOM 62 O6 G A 3 58.287 44.013 48.522 1.00 53.32 O
ATOM 63 N1 G A 3 59.893 42.491 49.072 1.00 54.00 N
ATOM 64 C2 G A 3 60.906 42.006 49.876 1.00 55.46 C
ATOM 65 N2 G A 3 61.512 40.873 49.479 1.00 48.16 N
ATOM 66 N3 G A 3 61.312 42.605 50.983 1.00 56.69 N
ATOM 67 C4 G A 3 60.666 43.774 51.193 1.00 61.76 C
ATOM 68 P G A 4 65.295 47.868 51.793 1.00 79.34 P
ATOM 69 O1P G A 4 66.538 48.562 52.246 1.00 80.87 O
ATOM 70 O2P G A 4 64.193 48.679 51.209 1.00 79.00 O
ATOM 71 O5* G A 4 65.720 46.752 50.724 1.00 75.17 O
ATOM 72 C5* G A 4 66.789 45.843 51.019 1.00 68.95 C
ATOM 73 C4* G A 4 66.749 44.634 50.114 1.00 65.13 C
ATOM 74 O4* G A 4 65.484 43.939 50.258 1.00 61.83 O
ATOM 75 C3* G A 4 66.881 44.840 48.611 1.00 62.79 C
ATOM 76 O3* G A 4 68.230 44.977 48.176 1.00 61.75 O
ATOM 77 C2* G A 4 66.318 43.538 48.064 1.00 60.58 C
ATOM 78 O2* G A 4 67.283 42.514 48.122 1.00 59.59 O
ATOM 79 C1* G A 4 65.192 43.241 49.051 1.00 58.29 C
ATOM 80 N9 G A 4 63.923 43.716 48.500 1.00 53.36 N
ATOM 81 C8 G A 4 63.204 44.843 48.842 1.00 49.19 C
ATOM 82 N7 G A 4 62.140 45.013 48.107 1.00 46.88 N
ATOM 83 C5 G A 4 62.144 43.926 47.243 1.00 45.95 C
ATOM 84 C6 G A 4 61.246 43.573 46.206 1.00 43.95 C
ATOM 85 O6 G A 4 60.182 44.136 45.874 1.00 42.46 O
ATOM 86 N1 G A 4 61.672 42.428 45.540 1.00 40.34 N
ATOM 87 C2 G A 4 62.788 41.686 45.867 1.00 42.60 C
ATOM 88 N2 G A 4 63.034 40.588 45.135 1.00 38.91 N
ATOM 89 N3 G A 4 63.612 41.994 46.850 1.00 44.40 N
ATOM 90 C4 G A 4 63.239 43.117 47.480 1.00 48.65 C
ATOM 91 P A A 5 68.530 45.722 46.789 1.00 59.03 P
ATOM 92 O1P A A 5 69.991 45.842 46.548 1.00 60.84 O
ATOM 93 O2P A A 5 67.685 46.959 46.834 1.00 60.64 O
ATOM 94 O5* A A 5 67.957 44.735 45.675 1.00 57.14 O
ATOM 95 C5* A A 5 68.648 43.529 45.323 1.00 53.41 C
ATOM 96 C4* A A 5 67.927 42.844 44.191 1.00 50.63 C
ATOM 97 O4* A A 5 66.589 42.480 44.646 1.00 48.70 O
ATOM 98 C3* A A 5 67.665 43.715 42.964 1.00 50.77 C
ATOM 99 O3* A A 5 68.747 43.769 42.051 1.00 52.86 O
ATOM 100 C2* A A 5 66.455 43.024 42.355 1.00 48.94 C
ATOM 101 O2* A A 5 66.864 41.798 41.731 1.00 48.54 O
ATOM 102 C1* A A 5 65.646 42.719 43.615 1.00 44.50 C
ATOM 103 N9 A A 5 64.779 43.843 44.021 1.00 42.01 N
ATOM 104 C8 A A 5 64.938 44.803 45.016 1.00 39.75 C
ATOM 105 N7 A A 5 63.925 45.649 45.113 1.00 41.58 N
ATOM 106 C5 A A 5 63.049 45.220 44.115 1.00 38.26 C
ATOM 107 C6 A A 5 61.796 45.688 43.683 1.00 35.83 C
ATOM 108 N6 A A 5 61.110 46.688 44.232 1.00 32.66 N
ATOM 109 N1 A A 5 61.233 45.057 42.644 1.00 35.14 N
ATOM 110 C2 A A 5 61.870 44.017 42.074 1.00 38.97 C
ATOM 111 N3 A A 5 63.024 43.467 42.399 1.00 36.02 N
ATOM 112 C4 A A 5 63.571 44.119 43.437 1.00 39.04 C
ATOM 113 P U A 6 69.150 45.179 41.392 1.00 55.09 P
ATOM 114 O1P U A 6 70.511 44.926 40.836 1.00 56.37 O
ATOM 115 O2P U A 6 68.953 46.283 42.381 1.00 51.00 O
ATOM 116 O5* U A 6 68.119 45.358 40.184 1.00 50.38 O
ATOM 117 C5* U A 6 67.912 44.271 39.258 1.00 48.10 C
ATOM 118 C4* U A 6 66.579 44.400 38.565 1.00 47.17 C
ATOM 119 O4* U A 6 65.486 44.324 39.513 1.00 46.61 O
ATOM 120 C3* U A 6 66.344 45.708 37.850 1.00 45.27 C
ATOM 121 O3* U A 6 66.964 45.696 36.590 1.00 45.77 O
ATOM 122 C2* U A 6 64.833 45.733 37.727 1.00 45.88 C
ATOM 123 O2* U A 6 64.431 44.864 36.684 1.00 44.33 O
ATOM 124 C1* U A 6 64.413 45.113 39.057 1.00 41.32 C
ATOM 125 N1 U A 6 64.065 46.111 40.079 1.00 39.88 N
ATOM 126 C2 U A 6 62.798 46.658 39.977 1.00 36.06 C
ATOM 127 O2 U A 6 62.021 46.333 39.099 1.00 38.25 O
ATOM 128 N3 U A 6 62.487 47.582 40.924 1.00 34.15 N
ATOM 129 C4 U A 6 63.272 48.002 41.975 1.00 37.36 C
ATOM 130 O4 U A 6 62.822 48.829 42.752 1.00 39.30 O
ATOM 131 C5 U A 6 64.583 47.395 42.032 1.00 39.23 C
ATOM 132 C6 U A 6 64.926 46.497 41.084 1.00 35.72 C
ATOM 133 P U A 7 67.463 47.074 35.969 1.00 44.37 P
ATOM 134 O1P U A 7 68.318 46.756 34.822 1.00 48.09 O
ATOM 135 O2P U A 7 67.945 47.948 37.077 1.00 45.68 O
ATOM 136 O5* U A 7 66.104 47.724 35.455 1.00 40.88 O
ATOM 137 C5* U A 7 65.285 47.024 34.459 1.00 37.89 C
ATOM 138 C4* U A 7 64.055 47.852 34.101 1.00 35.74 C
ATOM 139 O4* U A 7 63.297 48.107 35.326 1.00 38.13 O
ATOM 140 C3* U A 7 64.317 49.197 33.459 1.00 36.87 C
ATOM 141 O3* U A 7 63.402 49.394 32.378 1.00 37.45 O
ATOM 142 C2* U A 7 64.097 50.171 34.624 1.00 36.55 C
ATOM 143 O2* U A 7 63.595 51.417 34.246 1.00 35.54 O
ATOM 144 C1* U A 7 63.015 49.475 35.442 1.00 37.23 C
ATOM 145 N1 U A 7 63.056 49.858 36.864 1.00 36.91 N
ATOM 146 C2 U A 7 62.011 50.628 37.343 1.00 34.52 C
ATOM 147 O2 U A 7 61.087 50.966 36.653 1.00 34.65 O
ATOM 148 N3 U A 7 62.112 50.993 38.659 1.00 37.03 N
ATOM 149 C4 U A 7 63.131 50.684 39.541 1.00 40.15 C
ATOM 150 O4 U A 7 63.105 51.143 40.699 1.00 36.62 O
ATOM 151 C5 U A 7 64.179 49.865 38.971 1.00 36.52 C
ATOM 152 C6 U A 7 64.106 49.490 37.691 1.00 36.25 C
ATOM 153 P U A 8 63.884 49.282 30.858 1.00 36.77 P
ATOM 154 O1P U A 8 62.852 49.899 29.952 1.00 38.95 O
ATOM 155 O2P U A 8 64.442 47.955 30.547 1.00 38.70 O
ATOM 156 O5* U A 8 65.171 50.254 30.733 1.00 35.95 O
ATOM 157 C5* U A 8 64.994 51.676 30.500 1.00 33.53 C
ATOM 158 C4* U A 8 66.105 52.236 29.628 1.00 34.33 C
ATOM 159 O4* U A 8 67.428 52.119 30.261 1.00 31.81 O
ATOM 160 C3* U A 8 66.269 51.519 28.297 1.00 30.21 C
ATOM 161 O3* U A 8 65.321 51.887 27.314 1.00 32.41 O
ATOM 162 C2* U A 8 67.685 51.906 27.900 1.00 31.37 C
ATOM 163 O2* U A 8 67.743 53.224 27.433 1.00 27.02 O
ATOM 164 C1* U A 8 68.407 51.830 29.255 1.00 30.28 C
ATOM 165 N1 U A 8 68.914 50.469 29.501 1.00 28.11 N
ATOM 166 C2 U A 8 70.125 50.078 28.931 1.00 29.25 C
ATOM 167 O2 U A 8 70.835 50.819 28.278 1.00 27.81 O
ATOM 168 N3 U A 8 70.481 48.778 29.170 1.00 25.94 N
ATOM 169 C4 U A 8 69.808 47.856 29.922 1.00 27.37 C
ATOM 170 O4 U A 8 70.215 46.704 29.963 1.00 32.58 O
ATOM 171 C5 U A 8 68.612 48.328 30.490 1.00 29.58 C
ATOM 172 C6 U A 8 68.214 49.592 30.265 1.00 30.40 C
ATOM 173 P A A 9 64.755 50.731 26.311 1.00 32.05 P
ATOM 174 O1P A A 9 63.287 50.736 26.312 1.00 36.52 O
ATOM 175 O2P A A 9 65.447 49.415 26.519 1.00 31.33 O
ATOM 176 O5* A A 9 65.221 51.270 24.948 1.00 28.22 O
ATOM 177 C5* A A 9 64.646 52.433 24.369 1.00 32.91 C
ATOM 178 C4* A A 9 64.531 52.215 22.904 1.00 32.49 C
ATOM 179 O4* A A 9 65.887 52.090 22.406 1.00 35.09 O
ATOM 180 C3* A A 9 63.820 50.923 22.466 1.00 34.41 C
ATOM 181 O3* A A 9 63.140 51.180 21.236 1.00 36.11 O
ATOM 182 C2* A A 9 64.979 49.997 22.155 1.00 32.37 C
ATOM 183 O2* A A 9 64.686 49.016 21.194 1.00 35.87 O
ATOM 184 C1* A A 9 65.985 50.969 21.571 1.00 28.79 C
ATOM 185 N9 A A 9 67.376 50.497 21.585 1.00 23.84 N
ATOM 186 C8 A A 9 67.851 49.356 22.159 1.00 25.84 C
ATOM 187 N7 A A 9 69.149 49.195 22.010 1.00 26.83 N
ATOM 188 C5 A A 9 69.527 50.298 21.288 1.00 23.87 C
ATOM 189 C6 A A 9 70.730 50.663 20.793 1.00 30.26 C
ATOM 190 N6 A A 9 71.797 49.922 20.994 1.00 30.95 N
ATOM 191 N1 A A 9 70.817 51.794 20.072 1.00 28.29 N
ATOM 192 C2 A A 9 69.701 52.547 19.932 1.00 32.68 C
ATOM 193 N3 A A 9 68.469 52.287 20.369 1.00 25.13 N
ATOM 194 C4 A A 9 68.446 51.117 21.026 1.00 26.68 C
HETATM 195 P 2MG A 10 61.504 51.328 21.232 1.00 44.21 P
HETATM 196 O1P 2MG A 10 61.165 52.038 22.473 1.00 41.39 O
HETATM 197 O2P 2MG A 10 61.216 51.946 19.892 1.00 41.97 O
HETATM 198 O5* 2MG A 10 60.903 49.858 21.330 1.00 38.75 O
HETATM 199 C5* 2MG A 10 59.437 49.660 21.397 1.00 42.74 C
HETATM 200 C4* 2MG A 10 59.058 48.375 20.709 1.00 42.88 C
HETATM 201 O4* 2MG A 10 59.575 48.416 19.351 1.00 44.02 O
HETATM 202 C3* 2MG A 10 59.701 47.161 21.326 1.00 43.31 C
HETATM 203 O3* 2MG A 10 58.874 46.647 22.357 1.00 45.12 O
HETATM 204 C2* 2MG A 10 59.822 46.215 20.154 1.00 46.04 C
HETATM 205 O2* 2MG A 10 58.533 45.637 19.943 1.00 47.96 O
HETATM 206 C1* 2MG A 10 60.152 47.173 19.012 1.00 44.62 C
HETATM 207 N9 2MG A 10 61.581 47.402 18.752 1.00 42.14 N
HETATM 208 C8 2MG A 10 62.199 48.621 18.635 1.00 40.38 C
HETATM 209 N7 2MG A 10 63.494 48.534 18.422 1.00 40.70 N
HETATM 210 C5 2MG A 10 63.745 47.167 18.395 1.00 43.82 C
HETATM 211 C6 2MG A 10 64.965 46.449 18.205 1.00 43.45 C
HETATM 212 O6 2MG A 10 66.097 46.891 17.963 1.00 44.87 O
HETATM 213 N1 2MG A 10 64.767 45.086 18.293 1.00 44.71 N
HETATM 214 C2 2MG A 10 63.541 44.482 18.486 1.00 47.21 C
HETATM 215 N2 2MG A 10 63.532 43.164 18.551 1.00 49.27 N
HETATM 216 CM2 2MG A 10 62.220 42.454 18.591 1.00 52.10 C
HETATM 217 N3 2MG A 10 62.411 45.125 18.614 1.00 45.85 N
HETATM 218 C4 2MG A 10 62.574 46.451 18.582 1.00 43.27 C
ATOM 219 P C A 11 59.474 46.418 23.818 1.00 50.75 P
ATOM 220 O1P C A 11 58.367 46.417 24.802 1.00 49.46 O
ATOM 221 O2P C A 11 60.585 47.425 23.967 1.00 44.94 O
ATOM 222 O5* C A 11 60.064 44.937 23.797 1.00 49.65 O
ATOM 223 C5* C A 11 59.234 43.814 23.447 1.00 49.66 C
ATOM 224 C4* C A 11 60.091 42.608 23.221 1.00 50.13 C
ATOM 225 O4* C A 11 60.886 42.801 22.028 1.00 47.40 O
ATOM 226 C3* C A 11 61.091 42.406 24.335 1.00 52.64 C
ATOM 227 O3* C A 11 60.498 41.644 25.372 1.00 54.31 O
ATOM 228 C2* C A 11 62.252 41.701 23.640 1.00 51.51 C
ATOM 229 O2* C A 11 62.072 40.314 23.587 1.00 53.58 O
ATOM 230 C1* C A 11 62.189 42.294 22.230 1.00 48.88 C
ATOM 231 N1 C A 11 63.145 43.397 21.999 1.00 46.21 N
ATOM 232 C2 C A 11 64.484 43.091 21.738 1.00 45.74 C
ATOM 233 O2 C A 11 64.833 41.895 21.708 1.00 47.49 O
ATOM 234 N3 C A 11 65.365 44.106 21.527 1.00 42.07 N
ATOM 235 C4 C A 11 64.941 45.376 21.555 1.00 42.69 C
ATOM 236 N4 C A 11 65.829 46.353 21.301 1.00 38.00 N
ATOM 237 C5 C A 11 63.586 45.709 21.822 1.00 43.75 C
ATOM 238 C6 C A 11 62.732 44.698 22.035 1.00 45.15 C
ATOM 239 P U A 12 60.976 41.853 26.874 1.00 57.65 P
ATOM 240 O1P U A 12 60.123 41.039 27.783 1.00 59.26 O
ATOM 241 O2P U A 12 61.080 43.316 27.117 1.00 59.70 O
ATOM 242 O5* U A 12 62.441 41.244 26.886 1.00 55.93 O
ATOM 243 C5* U A 12 62.652 39.837 26.718 1.00 52.43 C
ATOM 244 C4* U A 12 64.121 39.544 26.594 1.00 48.54 C
ATOM 245 O4* U A 12 64.635 40.154 25.385 1.00 43.89 O
ATOM 246 C3* U A 12 65.015 40.119 27.684 1.00 50.30 C
ATOM 247 O3* U A 12 65.044 39.362 28.898 1.00 48.54 O
ATOM 248 C2* U A 12 66.384 40.159 27.007 1.00 48.05 C
ATOM 249 O2* U A 12 67.072 38.922 27.081 1.00 51.04 O
ATOM 250 C1* U A 12 66.013 40.478 25.565 1.00 47.40 C
ATOM 251 N1 U A 12 66.260 41.889 25.203 1.00 42.96 N
ATOM 252 C2 U A 12 67.565 42.250 24.872 1.00 43.65 C
ATOM 253 O2 U A 12 68.512 41.462 24.914 1.00 41.62 O
ATOM 254 N3 U A 12 67.736 43.577 24.520 1.00 45.49 N
ATOM 255 C4 U A 12 66.755 44.567 24.497 1.00 41.58 C
ATOM 256 O4 U A 12 67.069 45.722 24.203 1.00 41.28 O
ATOM 257 C5 U A 12 65.436 44.114 24.864 1.00 40.07 C
ATOM 258 C6 U A 12 65.241 42.831 25.193 1.00 44.32 C
ATOM 259 P C A 13 65.498 40.095 30.251 1.00 51.82 P
ATOM 260 O1P C A 13 65.477 39.159 31.399 1.00 52.57 O
ATOM 261 O2P C A 13 64.709 41.323 30.314 1.00 51.61 O
ATOM 262 O5* C A 13 67.010 40.399 29.846 1.00 48.38 O
ATOM 263 C5* C A 13 67.843 41.283 30.558 1.00 46.61 C
ATOM 264 C4* C A 13 69.102 41.516 29.762 1.00 43.48 C
ATOM 265 O4* C A 13 68.818 42.103 28.459 1.00 41.66 O
ATOM 266 C3* C A 13 70.084 42.477 30.389 1.00 46.01 C
ATOM 267 O3* C A 13 70.867 41.784 31.351 1.00 49.09 O
ATOM 268 C2* C A 13 70.925 42.922 29.204 1.00 42.77 C
ATOM 269 O2* C A 13 71.950 41.978 29.004 1.00 45.11 O
ATOM 270 C1* C A 13 69.909 42.919 28.054 1.00 39.03 C
ATOM 271 N1 C A 13 69.390 44.256 27.668 1.00 36.14 N
ATOM 272 C2 C A 13 70.236 45.162 26.999 1.00 31.39 C
ATOM 273 O2 C A 13 71.429 44.834 26.781 1.00 33.97 O
ATOM 274 N3 C A 13 69.736 46.376 26.604 1.00 30.71 N
ATOM 275 C4 C A 13 68.478 46.702 26.907 1.00 27.53 C
ATOM 276 N4 C A 13 68.050 47.913 26.576 1.00 29.33 N
ATOM 277 C5 C A 13 67.596 45.795 27.581 1.00 30.21 C
ATOM 278 C6 C A 13 68.085 44.602 27.937 1.00 31.74 C
ATOM 279 P A A 14 71.499 42.582 32.585 1.00 52.69 P
ATOM 280 O1P A A 14 71.592 41.647 33.723 1.00 56.81 O
ATOM 281 O2P A A 14 70.795 43.877 32.732 1.00 54.35 O
ATOM 282 O5* A A 14 72.996 42.894 32.143 1.00 52.44 O
ATOM 283 C5* A A 14 73.291 44.004 31.337 1.00 44.62 C
ATOM 284 C4* A A 14 74.612 43.815 30.626 1.00 38.21 C
ATOM 285 O4* A A 14 74.372 44.178 29.229 1.00 37.15 O
ATOM 286 C3* A A 14 75.617 44.841 31.120 1.00 39.31 C
ATOM 287 O3* A A 14 76.409 44.373 32.214 1.00 35.14 O
ATOM 288 C2* A A 14 76.410 45.187 29.878 1.00 35.42 C
ATOM 289 O2* A A 14 77.406 44.222 29.562 1.00 37.00 O
ATOM 290 C1* A A 14 75.325 45.147 28.805 1.00 32.12 C
ATOM 291 N9 A A 14 74.639 46.437 28.568 1.00 30.32 N
ATOM 292 C8 A A 14 73.332 46.800 28.850 1.00 28.83 C
ATOM 293 N7 A A 14 73.030 48.029 28.495 1.00 27.89 N
ATOM 294 C5 A A 14 74.205 48.496 27.963 1.00 28.40 C
ATOM 295 C6 A A 14 74.551 49.722 27.451 1.00 28.49 C
ATOM 296 N6 A A 14 73.715 50.778 27.422 1.00 27.62 N
ATOM 297 N1 A A 14 75.820 49.867 26.972 1.00 28.90 N
ATOM 298 C2 A A 14 76.658 48.824 27.058 1.00 26.09 C
ATOM 299 N3 A A 14 76.449 47.633 27.546 1.00 34.21 N
ATOM 300 C4 A A 14 75.194 47.523 27.993 1.00 28.42 C
ATOM 301 P G A 15 76.463 45.227 33.560 1.00 38.35 P
ATOM 302 O1P G A 15 77.577 44.561 34.373 1.00 36.34 O
ATOM 303 O2P G A 15 75.020 45.308 34.127 1.00 36.07 O
ATOM 304 O5* G A 15 76.977 46.682 33.179 1.00 34.17 O
ATOM 305 C5* G A 15 78.216 46.873 32.475 1.00 37.95 C
ATOM 306 C4* G A 15 78.274 48.248 31.867 1.00 34.05 C
ATOM 307 O4* G A 15 77.353 48.424 30.762 1.00 36.42 O
ATOM 308 C3* G A 15 77.992 49.400 32.793 1.00 41.25 C
ATOM 309 O3* G A 15 79.176 49.641 33.526 1.00 55.04 O
ATOM 310 C2* G A 15 77.696 50.528 31.803 1.00 37.22 C
ATOM 311 O2* G A 15 78.880 51.102 31.276 1.00 33.49 O
ATOM 312 C1* G A 15 76.941 49.779 30.686 1.00 33.07 C
ATOM 313 N9 G A 15 75.505 49.813 30.961 1.00 30.40 N
ATOM 314 C8 G A 15 74.775 48.836 31.612 1.00 30.39 C
ATOM 315 N7 G A 15 73.537 49.203 31.861 1.00 28.29 N
ATOM 316 C5 G A 15 73.439 50.464 31.298 1.00 27.38 C
ATOM 317 C6 G A 15 72.351 51.383 31.271 1.00 24.88 C
ATOM 318 O6 G A 15 71.261 51.260 31.756 1.00 26.54 O
ATOM 319 N1 G A 15 72.683 52.569 30.607 1.00 23.73 N
ATOM 320 C2 G A 15 73.896 52.858 30.094 1.00 29.75 C
ATOM 321 N2 G A 15 74.047 54.083 29.581 1.00 27.02 N
ATOM 322 N3 G A 15 74.925 52.008 30.089 1.00 28.46 N
ATOM 323 C4 G A 15 74.632 50.842 30.714 1.00 29.28 C
HETATM 324 P H2U A 16 79.106 49.914 35.099 1.00 64.01 P
HETATM 325 O1P H2U A 16 77.803 50.520 35.400 1.00 58.28 O
HETATM 326 O2P H2U A 16 79.533 48.676 35.816 1.00 67.91 O
HETATM 327 O5* H2U A 16 80.270 50.994 35.265 1.00 70.49 O
HETATM 328 C5* H2U A 16 81.110 51.317 34.115 1.00 77.82 C
HETATM 329 C4* H2U A 16 80.514 52.486 33.353 1.00 82.34 C
HETATM 330 O4* H2U A 16 79.081 52.313 33.356 1.00 85.70 O
HETATM 331 C3* H2U A 16 80.758 53.821 34.030 1.00 84.30 C
HETATM 332 O3* H2U A 16 81.907 54.422 33.414 1.00 84.12 O
HETATM 333 C1* H2U A 16 78.428 53.548 33.551 1.00 88.13 C
HETATM 334 C2* H2U A 16 79.505 54.639 33.690 1.00 86.71 C
HETATM 335 O2* H2U A 16 79.637 55.391 32.493 1.00 88.25 O
HETATM 336 N1 H2U A 16 77.347 53.323 34.582 1.00 91.19 N
HETATM 337 C2 H2U A 16 76.119 52.865 34.160 1.00 92.39 C
HETATM 338 O2 H2U A 16 75.885 52.463 33.033 1.00 92.20 O
HETATM 339 N3 H2U A 16 75.123 52.894 35.107 1.00 93.28 N
HETATM 340 C4 H2U A 16 75.289 52.711 36.458 1.00 93.34 C
HETATM 341 O4 H2U A 16 74.309 52.695 37.208 1.00 92.66 O
HETATM 342 C5 H2U A 16 76.696 52.479 36.909 1.00 93.77 C
HETATM 343 C6 H2U A 16 77.717 53.238 36.039 1.00 93.22 C
HETATM 344 P H2U A 17 83.371 53.708 33.472 1.00 82.84 P
HETATM 345 O1P H2U A 17 83.746 53.377 32.068 1.00 83.70 O
HETATM 346 O2P H2U A 17 83.498 52.655 34.529 1.00 83.82 O
HETATM 347 O5* H2U A 17 84.277 54.923 33.943 1.00 81.72 O
HETATM 348 C5* H2U A 17 83.692 55.978 34.736 1.00 76.14 C
HETATM 349 C4* H2U A 17 84.176 55.886 36.150 1.00 71.56 C
HETATM 350 O4* H2U A 17 85.622 55.872 36.137 1.00 71.61 O
HETATM 351 C3* H2U A 17 83.738 57.031 37.055 1.00 67.99 C
HETATM 352 O3* H2U A 17 82.553 56.582 37.718 1.00 60.02 O
HETATM 353 C1* H2U A 17 86.102 56.903 36.958 1.00 71.64 C
HETATM 354 C2* H2U A 17 84.964 57.213 37.948 1.00 71.27 C
HETATM 355 O2* H2U A 17 85.004 56.273 39.021 1.00 73.23 O
HETATM 356 N1 H2U A 17 86.579 57.954 36.004 1.00 72.27 N
HETATM 357 C2 H2U A 17 87.702 58.662 36.301 1.00 71.21 C
HETATM 358 O2 H2U A 17 87.834 59.359 37.287 1.00 72.68 O
HETATM 359 N3 H2U A 17 88.693 58.585 35.358 1.00 69.04 N
HETATM 360 C4 H2U A 17 88.711 57.779 34.244 1.00 68.89 C
HETATM 361 O4 H2U A 17 89.766 57.616 33.620 1.00 64.81 O
HETATM 362 C5 H2U A 17 87.401 57.154 33.864 1.00 69.36 C
HETATM 363 C6 H2U A 17 86.257 57.828 34.577 1.00 71.72 C
ATOM 364 P G A 18 81.804 57.491 38.803 1.00 53.35 P
ATOM 365 O1P G A 18 82.773 58.100 39.715 1.00 56.70 O
ATOM 366 O2P G A 18 80.724 56.638 39.368 1.00 56.95 O
ATOM 367 O5* G A 18 81.038 58.580 37.950 1.00 45.07 O
ATOM 368 C5* G A 18 80.288 58.201 36.778 1.00 37.17 C
ATOM 369 C4* G A 18 80.100 59.412 35.902 1.00 33.24 C
ATOM 370 O4* G A 18 79.417 60.430 36.705 1.00 29.49 O
ATOM 371 C3* G A 18 81.426 60.038 35.456 1.00 29.19 C
ATOM 372 O3* G A 18 81.313 60.691 34.173 1.00 27.98 O
ATOM 373 C2* G A 18 81.638 61.165 36.437 1.00 26.61 C
ATOM 374 O2* G A 18 82.417 62.205 35.773 1.00 31.88 O
ATOM 375 C1* G A 18 80.191 61.615 36.658 1.00 31.24 C
ATOM 376 N9 G A 18 79.893 62.457 37.818 1.00 25.73 N
ATOM 377 C8 G A 18 80.399 62.361 39.094 1.00 29.39 C
ATOM 378 N7 G A 18 79.992 63.332 39.883 1.00 29.66 N
ATOM 379 C5 G A 18 79.165 64.095 39.074 1.00 26.03 C
ATOM 380 C6 G A 18 78.469 65.259 39.359 1.00 29.73 C
ATOM 381 O6 G A 18 78.491 65.889 40.411 1.00 31.10 O
ATOM 382 N1 G A 18 77.698 65.711 38.257 1.00 25.44 N
ATOM 383 C2 G A 18 77.634 65.077 37.076 1.00 25.15 C
ATOM 384 N2 G A 18 76.850 65.605 36.127 1.00 28.06 N
ATOM 385 N3 G A 18 78.312 63.960 36.797 1.00 31.81 N
ATOM 386 C4 G A 18 79.053 63.539 37.817 1.00 27.46 C
ATOM 387 P G A 19 81.705 59.935 32.855 1.00 34.61 P
ATOM 388 O1P G A 19 80.751 58.780 32.632 1.00 31.49 O
ATOM 389 O2P G A 19 83.185 59.683 32.792 1.00 35.14 O
ATOM 390 O5* G A 19 81.429 61.065 31.780 1.00 30.92 O
ATOM 391 C5* G A 19 80.053 61.459 31.456 1.00 35.49 C
ATOM 392 C4* G A 19 80.105 62.508 30.407 1.00 32.28 C
ATOM 393 O4* G A 19 80.779 63.631 30.991 1.00 33.92 O
ATOM 394 C3* G A 19 80.907 62.116 29.171 1.00 34.56 C
ATOM 395 O3* G A 19 80.389 62.868 28.083 1.00 33.76 O
ATOM 396 C2* G A 19 82.305 62.679 29.462 1.00 35.83 C
ATOM 397 O2* G A 19 82.892 63.160 28.284 1.00 36.38 O
ATOM 398 C1* G A 19 81.965 63.912 30.283 1.00 31.26 C
ATOM 399 N9 G A 19 82.922 64.301 31.303 1.00 34.09 N
ATOM 400 C8 G A 19 83.808 63.510 32.002 1.00 34.35 C
ATOM 401 N7 G A 19 84.330 64.135 33.026 1.00 29.97 N
ATOM 402 C5 G A 19 83.803 65.412 32.954 1.00 30.15 C
ATOM 403 C6 G A 19 83.998 66.553 33.810 1.00 30.28 C
ATOM 404 O6 G A 19 84.715 66.645 34.861 1.00 30.49 O
ATOM 405 N1 G A 19 83.246 67.654 33.362 1.00 30.06 N
ATOM 406 C2 G A 19 82.438 67.667 32.262 1.00 28.68 C
ATOM 407 N2 G A 19 81.753 68.812 32.044 1.00 31.69 N
ATOM 408 N3 G A 19 82.279 66.621 31.443 1.00 33.35 N
ATOM 409 C4 G A 19 82.976 65.537 31.862 1.00 29.77 C
ATOM 410 P G A 20 79.212 62.270 27.169 1.00 37.57 P
ATOM 411 O1P G A 20 78.632 63.435 26.460 1.00 37.48 O
ATOM 412 O2P G A 20 78.418 61.535 28.129 1.00 34.93 O
ATOM 413 O5* G A 20 79.952 61.358 26.110 1.00 35.27 O
ATOM 414 C5* G A 20 80.561 61.904 24.945 1.00 34.78 C
ATOM 415 C4* G A 20 80.529 60.879 23.849 1.00 33.56 C
ATOM 416 O4* G A 20 81.420 59.808 24.203 1.00 34.69 O
ATOM 417 C3* G A 20 79.164 60.229 23.679 1.00 34.55 C
ATOM 418 O3* G A 20 78.373 60.964 22.748 1.00 32.07 O
ATOM 419 C2* G A 20 79.540 58.879 23.115 1.00 31.94 C
ATOM 420 O2* G A 20 79.935 59.005 21.776 1.00 29.14 O
ATOM 421 C1* G A 20 80.836 58.580 23.876 1.00 33.29 C
ATOM 422 N9 G A 20 80.557 57.879 25.128 1.00 28.16 N
ATOM 423 C8 G A 20 80.808 58.309 26.413 1.00 28.17 C
ATOM 424 N7 G A 20 80.362 57.471 27.316 1.00 27.62 N
ATOM 425 C5 G A 20 79.819 56.431 26.576 1.00 26.85 C
ATOM 426 C6 G A 20 79.214 55.251 26.985 1.00 29.07 C
ATOM 427 O6 G A 20 79.010 54.845 28.141 1.00 30.12 O
ATOM 428 N1 G A 20 78.811 54.474 25.894 1.00 26.18 N
ATOM 429 C2 G A 20 78.993 54.795 24.576 1.00 28.16 C
ATOM 430 N2 G A 20 78.546 53.879 23.648 1.00 24.71 N
ATOM 431 N3 G A 20 79.567 55.902 24.177 1.00 25.02 N
ATOM 432 C4 G A 20 79.951 56.671 25.225 1.00 27.86 C
ATOM 433 P A A 21 76.960 61.541 23.213 1.00 35.97 P
ATOM 434 O1P A A 21 76.324 62.054 21.989 1.00 35.07 O
ATOM 435 O2P A A 21 77.193 62.456 24.350 1.00 35.45 O
ATOM 436 O5* A A 21 76.166 60.289 23.790 1.00 34.57 O
ATOM 437 C5* A A 21 75.604 59.329 22.914 1.00 33.17 C
ATOM 438 C4* A A 21 75.622 58.001 23.580 1.00 34.52 C
ATOM 439 O4* A A 21 74.864 57.958 24.808 1.00 29.25 O
ATOM 440 C3* A A 21 75.125 56.852 22.735 1.00 33.11 C
ATOM 441 O3* A A 21 76.250 56.581 21.883 1.00 36.69 O
ATOM 442 C2* A A 21 74.815 55.806 23.788 1.00 33.65 C
ATOM 443 O2* A A 21 76.034 55.158 24.220 1.00 30.39 O
ATOM 444 C1* A A 21 74.304 56.666 24.955 1.00 30.28 C
ATOM 445 N9 A A 21 72.843 56.834 25.065 1.00 28.13 N
ATOM 446 C8 A A 21 72.122 57.968 24.720 1.00 24.90 C
ATOM 447 N7 A A 21 70.828 57.864 24.968 1.00 27.77 N
ATOM 448 C5 A A 21 70.695 56.581 25.516 1.00 25.63 C
ATOM 449 C6 A A 21 69.596 55.872 26.031 1.00 28.10 C
ATOM 450 N6 A A 21 68.327 56.341 26.073 1.00 24.98 N
ATOM 451 N1 A A 21 69.817 54.668 26.536 1.00 27.40 N
ATOM 452 C2 A A 21 71.064 54.186 26.531 1.00 26.83 C
ATOM 453 N3 A A 21 72.169 54.734 26.097 1.00 26.24 N
ATOM 454 C4 A A 21 71.927 55.948 25.580 1.00 28.94 C
ATOM 455 P G A 22 76.122 55.607 20.624 1.00 36.77 P
ATOM 456 O1P G A 22 77.347 55.811 19.853 1.00 34.15 O
ATOM 457 O2P G A 22 74.796 55.966 20.020 1.00 38.21 O
ATOM 458 O5* G A 22 76.107 54.255 21.420 1.00 39.67 O
ATOM 459 C5* G A 22 75.588 53.058 20.896 1.00 33.77 C
ATOM 460 C4* G A 22 76.292 51.916 21.581 1.00 33.57 C
ATOM 461 O4* G A 22 76.032 51.934 23.018 1.00 28.98 O
ATOM 462 C3* G A 22 75.794 50.585 21.102 1.00 31.27 C
ATOM 463 O3* G A 22 76.427 50.216 19.874 1.00 36.07 O
ATOM 464 C2* G A 22 75.986 49.707 22.315 1.00 30.09 C
ATOM 465 O2* G A 22 77.321 49.252 22.478 1.00 29.86 O
ATOM 466 C1* G A 22 75.605 50.671 23.444 1.00 25.75 C
ATOM 467 N9 G A 22 74.157 50.722 23.757 1.00 27.25 N
ATOM 468 C8 G A 22 73.306 51.785 23.618 1.00 27.24 C
ATOM 469 N7 G A 22 72.095 51.529 24.052 1.00 28.94 N
ATOM 470 C5 G A 22 72.147 50.220 24.476 1.00 28.23 C
ATOM 471 C6 G A 22 71.138 49.385 25.011 1.00 28.84 C
ATOM 472 O6 G A 22 69.936 49.648 25.252 1.00 29.10 O
ATOM 473 N1 G A 22 71.624 48.128 25.270 1.00 27.83 N
ATOM 474 C2 G A 22 72.899 47.703 25.050 1.00 30.21 C
ATOM 475 N2 G A 22 73.158 46.409 25.364 1.00 27.00 N
ATOM 476 N3 G A 22 73.837 48.454 24.566 1.00 29.25 N
ATOM 477 C4 G A 22 73.400 49.695 24.288 1.00 25.81 C
ATOM 478 P A A 23 75.571 49.404 18.784 1.00 38.64 P
ATOM 479 O1P A A 23 76.230 49.559 17.497 1.00 35.37 O
ATOM 480 O2P A A 23 74.080 49.759 18.881 1.00 35.35 O
ATOM 481 O5* A A 23 75.636 47.938 19.332 1.00 37.83 O
ATOM 482 C5* A A 23 76.912 47.318 19.633 1.00 37.02 C
ATOM 483 C4* A A 23 76.705 45.975 20.257 1.00 39.13 C
ATOM 484 O4* A A 23 76.089 46.103 21.547 1.00 38.15 O
ATOM 485 C3* A A 23 75.794 45.028 19.486 1.00 40.14 C
ATOM 486 O3* A A 23 76.500 44.368 18.446 1.00 42.27 O
ATOM 487 C2* A A 23 75.356 44.060 20.563 1.00 39.45 C
ATOM 488 O2* A A 23 76.423 43.125 20.754 1.00 42.00 O
ATOM 489 C1* A A 23 75.210 45.010 21.771 1.00 37.98 C
ATOM 490 N9 A A 23 73.858 45.578 21.885 1.00 35.38 N
ATOM 491 C8 A A 23 73.461 46.822 21.439 1.00 35.25 C
ATOM 492 N7 A A 23 72.234 47.140 21.772 1.00 33.59 N
ATOM 493 C5 A A 23 71.772 46.017 22.438 1.00 34.26 C
ATOM 494 C6 A A 23 70.529 45.710 23.019 1.00 32.33 C
ATOM 495 N6 A A 23 69.521 46.594 23.138 1.00 34.94 N
ATOM 496 N1 A A 23 70.368 44.470 23.517 1.00 35.35 N
ATOM 497 C2 A A 23 71.405 43.615 23.470 1.00 31.66 C
ATOM 498 N3 A A 23 72.643 43.811 23.008 1.00 32.48 N
ATOM 499 C4 A A 23 72.758 45.035 22.487 1.00 34.85 C
ATOM 500 P G A 24 75.691 43.814 17.170 1.00 44.02 P
ATOM 501 O1P G A 24 76.744 43.269 16.286 1.00 46.42 O
ATOM 502 O2P G A 24 74.752 44.889 16.691 1.00 43.05 O
ATOM 503 O5* G A 24 74.795 42.670 17.756 1.00 40.73 O
ATOM 504 C5* G A 24 75.378 41.492 18.218 1.00 46.30 C
ATOM 505 C4* G A 24 74.313 40.622 18.747 1.00 47.22 C
ATOM 506 O4* G A 24 73.799 41.198 19.975 1.00 46.23 O
ATOM 507 C3* G A 24 73.094 40.484 17.855 1.00 47.23 C
ATOM 508 O3* G A 24 73.287 39.486 16.850 1.00 51.92 O
ATOM 509 C2* G A 24 72.056 40.037 18.867 1.00 47.49 C
ATOM 510 O2* G A 24 72.324 38.676 19.169 1.00 46.29 O
ATOM 511 C1* G A 24 72.412 40.925 20.073 1.00 45.11 C
ATOM 512 N9 G A 24 71.687 42.195 20.013 1.00 42.04 N
ATOM 513 C8 G A 24 72.126 43.377 19.471 1.00 42.70 C
ATOM 514 N7 G A 24 71.218 44.315 19.472 1.00 40.83 N
ATOM 515 C5 G A 24 70.114 43.715 20.070 1.00 42.41 C
ATOM 516 C6 G A 24 68.831 44.242 20.336 1.00 44.36 C
ATOM 517 O6 G A 24 68.390 45.396 20.057 1.00 44.29 O
ATOM 518 N1 G A 24 68.011 43.299 20.965 1.00 42.61 N
ATOM 519 C2 G A 24 68.390 42.013 21.284 1.00 44.44 C
ATOM 520 N2 G A 24 67.446 41.234 21.843 1.00 42.33 N
ATOM 521 N3 G A 24 69.599 41.521 21.050 1.00 41.16 N
ATOM 522 C4 G A 24 70.396 42.419 20.435 1.00 42.35 C
ATOM 523 P C A 25 72.660 39.699 15.392 1.00 49.58 P
ATOM 524 O1P C A 25 73.082 38.530 14.539 1.00 54.65 O
ATOM 525 O2P C A 25 72.897 41.067 14.886 1.00 47.78 O
ATOM 526 O5* C A 25 71.110 39.469 15.645 1.00 48.69 O
ATOM 527 C5* C A 25 70.619 38.180 16.052 1.00 50.80 C
ATOM 528 C4* C A 25 69.170 38.275 16.491 1.00 50.78 C
ATOM 529 O4* C A 25 69.098 39.152 17.653 1.00 55.06 O
ATOM 530 C3* C A 25 68.156 38.899 15.531 1.00 53.87 C
ATOM 531 O3* C A 25 67.629 38.012 14.533 1.00 52.62 O
ATOM 532 C2* C A 25 67.045 39.336 16.481 1.00 54.24 C
ATOM 533 O2* C A 25 66.276 38.238 16.922 1.00 56.92 O
ATOM 534 C1* C A 25 67.844 39.818 17.685 1.00 51.93 C
ATOM 535 N1 C A 25 68.040 41.263 17.589 1.00 51.02 N
ATOM 536 C2 C A 25 67.005 42.092 18.016 1.00 51.02 C
ATOM 537 O2 C A 25 65.989 41.579 18.475 1.00 49.40 O
ATOM 538 N3 C A 25 67.136 43.428 17.897 1.00 50.42 N
ATOM 539 C4 C A 25 68.240 43.949 17.341 1.00 50.86 C
ATOM 540 N4 C A 25 68.316 45.287 17.212 1.00 46.56 N
ATOM 541 C5 C A 25 69.316 43.129 16.899 1.00 48.98 C
ATOM 542 C6 C A 25 69.185 41.802 17.062 1.00 50.79 C
HETATM 543 P M2G A 26 67.297 38.593 13.077 1.00 53.21 P
HETATM 544 O1P M2G A 26 68.469 39.430 12.691 1.00 53.23 O
HETATM 545 O2P M2G A 26 66.835 37.487 12.148 1.00 56.89 O
HETATM 546 O5* M2G A 26 66.058 39.572 13.258 1.00 49.44 O
HETATM 547 C5* M2G A 26 64.865 39.112 13.893 1.00 49.64 C
HETATM 548 C4* M2G A 26 63.938 40.267 14.143 1.00 49.36 C
HETATM 549 O4* M2G A 26 64.443 41.119 15.209 1.00 48.17 O
HETATM 550 C3* M2G A 26 63.719 41.196 12.968 1.00 48.54 C
HETATM 551 O3* M2G A 26 62.681 40.699 12.152 1.00 52.14 O
HETATM 552 C2* M2G A 26 63.273 42.477 13.644 1.00 47.40 C
HETATM 553 O2* M2G A 26 61.905 42.387 14.025 1.00 47.93 O
HETATM 554 C1* M2G A 26 64.147 42.470 14.901 1.00 46.92 C
HETATM 555 N9 M2G A 26 65.403 43.195 14.677 1.00 41.61 N
HETATM 556 C8 M2G A 26 66.657 42.687 14.400 1.00 45.40 C
HETATM 557 N7 M2G A 26 67.543 43.618 14.188 1.00 44.60 N
HETATM 558 C5 M2G A 26 66.836 44.807 14.371 1.00 43.23 C
HETATM 559 C6 M2G A 26 67.253 46.174 14.285 1.00 41.77 C
HETATM 560 O6 M2G A 26 68.372 46.637 14.008 1.00 45.23 O
HETATM 561 N1 M2G A 26 66.209 47.048 14.544 1.00 42.85 N
HETATM 562 C2 M2G A 26 64.926 46.678 14.840 1.00 42.16 C
HETATM 563 N2 M2G A 26 64.015 47.663 15.061 1.00 41.43 N
HETATM 564 N3 M2G A 26 64.531 45.410 14.927 1.00 42.18 N
HETATM 565 C4 M2G A 26 65.524 44.546 14.680 1.00 43.64 C
HETATM 566 CM1 M2G A 26 64.404 49.075 15.158 1.00 44.51 C
HETATM 567 CM2 M2G A 26 62.594 47.288 15.283 1.00 41.28 C
ATOM 568 P C A 27 62.860 40.709 10.569 1.00 53.96 P
ATOM 569 O1P C A 27 61.690 39.909 10.056 1.00 58.78 O
ATOM 570 O2P C A 27 64.244 40.343 10.165 1.00 54.14 O
ATOM 571 O5* C A 27 62.614 42.218 10.155 1.00 53.83 O
ATOM 572 C5* C A 27 61.437 42.899 10.561 1.00 51.71 C
ATOM 573 C4* C A 27 61.594 44.378 10.321 1.00 53.47 C
ATOM 574 O4* C A 27 62.476 44.955 11.330 1.00 51.31 O
ATOM 575 C3* C A 27 62.210 44.814 9.004 1.00 54.38 C
ATOM 576 O3* C A 27 61.256 44.865 7.943 1.00 60.47 O
ATOM 577 C2* C A 27 62.693 46.223 9.339 1.00 51.78 C
ATOM 578 O2* C A 27 61.640 47.167 9.301 1.00 51.18 O
ATOM 579 C1* C A 27 63.159 46.064 10.787 1.00 48.68 C
ATOM 580 N1 C A 27 64.612 45.818 10.877 1.00 42.59 N
ATOM 581 C2 C A 27 65.472 46.868 10.634 1.00 44.48 C
ATOM 582 O2 C A 27 64.981 47.978 10.348 1.00 42.73 O
ATOM 583 N3 C A 27 66.821 46.659 10.722 1.00 42.28 N
ATOM 584 C4 C A 27 67.275 45.452 11.056 1.00 43.75 C
ATOM 585 N4 C A 27 68.586 45.272 11.180 1.00 44.57 N
ATOM 586 C5 C A 27 66.402 44.364 11.291 1.00 44.20 C
ATOM 587 C6 C A 27 65.095 44.589 11.192 1.00 44.33 C
ATOM 588 P C A 28 61.715 44.551 6.429 1.00 61.60 P
ATOM 589 O1P C A 28 60.464 44.441 5.640 1.00 62.15 O
ATOM 590 O2P C A 28 62.648 43.401 6.479 1.00 61.61 O
ATOM 591 O5* C A 28 62.553 45.816 5.941 1.00 56.70 O
ATOM 592 C5* C A 28 61.910 47.047 5.647 1.00 57.75 C
ATOM 593 C4* C A 28 62.918 48.099 5.246 1.00 58.29 C
ATOM 594 O4* C A 28 63.719 48.476 6.402 1.00 56.80 O
ATOM 595 C3* C A 28 63.942 47.721 4.187 1.00 60.32 C
ATOM 596 O3* C A 28 63.466 47.779 2.838 1.00 64.19 O
ATOM 597 C2* C A 28 65.056 48.727 4.461 1.00 57.91 C
ATOM 598 O2* C A 28 64.774 50.025 3.952 1.00 56.60 O
ATOM 599 C1* C A 28 65.046 48.767 5.987 1.00 56.20 C
ATOM 600 N1 C A 28 65.958 47.725 6.532 1.00 51.41 N
ATOM 601 C2 C A 28 67.338 47.999 6.616 1.00 49.26 C
ATOM 602 O2 C A 28 67.761 49.119 6.240 1.00 45.60 O
ATOM 603 N3 C A 28 68.175 47.034 7.101 1.00 50.25 N
ATOM 604 C4 C A 28 67.676 45.854 7.493 1.00 50.21 C
ATOM 605 N4 C A 28 68.515 44.934 7.978 1.00 50.49 N
ATOM 606 C5 C A 28 66.284 45.560 7.412 1.00 50.83 C
ATOM 607 C6 C A 28 65.473 46.516 6.936 1.00 50.67 C
ATOM 608 P A A 29 64.134 46.810 1.715 1.00 65.77 P
ATOM 609 O1P A A 29 63.389 47.109 0.457 1.00 67.04 O
ATOM 610 O2P A A 29 64.179 45.395 2.219 1.00 63.95 O
ATOM 611 O5* A A 29 65.641 47.328 1.540 1.00 62.83 O
ATOM 612 C5* A A 29 65.903 48.647 0.972 1.00 63.87 C
ATOM 613 C4* A A 29 67.384 49.009 1.027 1.00 63.27 C
ATOM 614 O4* A A 29 67.815 49.121 2.412 1.00 62.56 O
ATOM 615 C3* A A 29 68.423 48.084 0.399 1.00 63.00 C
ATOM 616 O3* A A 29 68.576 48.226 -1.003 1.00 65.01 O
ATOM 617 C2* A A 29 69.702 48.526 1.092 1.00 61.38 C
ATOM 618 O2* A A 29 70.234 49.721 0.530 1.00 61.02 O
ATOM 619 C1* A A 29 69.196 48.789 2.509 1.00 59.63 C
ATOM 620 N9 A A 29 69.335 47.576 3.315 1.00 54.19 N
ATOM 621 C8 A A 29 68.378 46.647 3.653 1.00 54.48 C
ATOM 622 N7 A A 29 68.847 45.630 4.321 1.00 53.76 N
ATOM 623 C5 A A 29 70.198 45.923 4.448 1.00 52.14 C
ATOM 624 C6 A A 29 71.245 45.231 5.038 1.00 50.79 C
ATOM 625 N6 A A 29 71.082 44.066 5.687 1.00 50.54 N
ATOM 626 N1 A A 29 72.481 45.776 4.952 1.00 48.83 N
ATOM 627 C2 A A 29 72.620 46.942 4.329 1.00 48.49 C
ATOM 628 N3 A A 29 71.699 47.698 3.751 1.00 51.37 N
ATOM 629 C4 A A 29 70.502 47.119 3.845 1.00 50.75 C
ATOM 630 P G A 30 69.148 46.986 -1.875 1.00 63.15 P
ATOM 631 O1P G A 30 68.830 47.365 -3.277 1.00 64.99 O
ATOM 632 O2P G A 30 68.659 45.688 -1.323 1.00 61.44 O
ATOM 633 O5* G A 30 70.738 46.979 -1.648 1.00 64.00 O
ATOM 634 C5* G A 30 71.552 48.159 -1.889 1.00 63.25 C
ATOM 635 C4* G A 30 72.933 47.996 -1.281 1.00 63.56 C
ATOM 636 O4* G A 30 72.830 47.805 0.157 1.00 62.05 O
ATOM 637 C3* G A 30 73.716 46.785 -1.754 1.00 65.21 C
ATOM 638 O3* G A 30 74.380 47.055 -2.978 1.00 68.93 O
ATOM 639 C2* G A 30 74.690 46.532 -0.603 1.00 63.90 C
ATOM 640 O2* G A 30 75.815 47.379 -0.636 1.00 66.48 O
ATOM 641 C1* G A 30 73.839 46.903 0.605 1.00 60.48 C
ATOM 642 N9 G A 30 73.204 45.719 1.184 1.00 56.62 N
ATOM 643 C8 G A 30 71.872 45.376 1.155 1.00 55.59 C
ATOM 644 N7 G A 30 71.623 44.235 1.750 1.00 54.28 N
ATOM 645 C5 G A 30 72.868 43.798 2.203 1.00 52.26 C
ATOM 646 C6 G A 30 73.238 42.611 2.909 1.00 51.92 C
ATOM 647 O6 G A 30 72.512 41.677 3.315 1.00 48.72 O
ATOM 648 N1 G A 30 74.614 42.562 3.133 1.00 53.22 N
ATOM 649 C2 G A 30 75.513 43.524 2.738 1.00 52.55 C
ATOM 650 N2 G A 30 76.797 43.282 3.015 1.00 52.61 N
ATOM 651 N3 G A 30 75.180 44.635 2.106 1.00 52.73 N
ATOM 652 C4 G A 30 73.853 44.703 1.866 1.00 53.73 C
ATOM 653 P A A 31 74.530 45.886 -4.075 1.00 69.42 P
ATOM 654 O1P A A 31 75.319 46.471 -5.195 1.00 71.00 O
ATOM 655 O2P A A 31 73.193 45.303 -4.337 1.00 68.84 O
ATOM 656 O5* A A 31 75.405 44.785 -3.333 1.00 67.81 O
ATOM 657 C5* A A 31 76.782 45.018 -3.047 1.00 66.34 C
ATOM 658 C4* A A 31 77.346 43.848 -2.300 1.00 65.86 C
ATOM 659 O4* A A 31 76.688 43.760 -1.020 1.00 64.48 O
ATOM 660 C3* A A 31 77.123 42.485 -2.938 1.00 67.80 C
ATOM 661 O3* A A 31 78.102 42.185 -3.933 1.00 69.43 O
ATOM 662 C2* A A 31 77.166 41.543 -1.735 1.00 66.49 C
ATOM 663 O2* A A 31 78.476 41.202 -1.324 1.00 70.09 O
ATOM 664 C1* A A 31 76.518 42.403 -0.649 1.00 62.06 C
ATOM 665 N9 A A 31 75.083 42.164 -0.541 1.00 56.88 N
ATOM 666 C8 A A 31 74.083 42.881 -1.152 1.00 56.22 C
ATOM 667 N7 A A 31 72.877 42.454 -0.869 1.00 55.69 N
ATOM 668 C5 A A 31 73.093 41.379 -0.019 1.00 52.78 C
ATOM 669 C6 A A 31 72.210 40.498 0.642 1.00 53.56 C
ATOM 670 N6 A A 31 70.867 40.568 0.536 1.00 51.52 N
ATOM 671 N1 A A 31 72.757 39.533 1.428 1.00 53.95 N
ATOM 672 C2 A A 31 74.103 39.473 1.530 1.00 54.22 C
ATOM 673 N3 A A 31 75.027 40.244 0.958 1.00 53.01 N
ATOM 674 C4 A A 31 74.453 41.186 0.189 1.00 54.24 C
HETATM 675 N1 OMC A 32 74.486 38.301 -2.478 1.00 64.48 N
HETATM 676 C2 OMC A 32 73.347 37.833 -1.784 1.00 63.86 C
HETATM 677 N3 OMC A 32 72.174 38.492 -1.928 1.00 62.03 N
HETATM 678 C4 OMC A 32 72.103 39.570 -2.726 1.00 62.91 C
HETATM 679 C5 OMC A 32 73.242 40.067 -3.425 1.00 63.75 C
HETATM 680 C6 OMC A 32 74.401 39.413 -3.269 1.00 64.43 C
HETATM 681 O2 OMC A 32 73.450 36.817 -1.056 1.00 63.74 O
HETATM 682 N4 OMC A 32 70.914 40.189 -2.874 1.00 60.56 N
HETATM 683 C1* OMC A 32 75.756 37.560 -2.358 1.00 68.30 C
HETATM 684 C2* OMC A 32 75.912 36.485 -3.446 1.00 68.41 C
HETATM 685 O2* OMC A 32 76.521 35.341 -2.874 1.00 68.27 O
HETATM 686 CM2 OMC A 32 75.491 34.476 -2.439 1.00 68.09 C
HETATM 687 C3* OMC A 32 76.801 37.196 -4.464 1.00 69.68 C
HETATM 688 C4* OMC A 32 77.712 38.038 -3.579 1.00 69.87 C
HETATM 689 O4* OMC A 32 76.843 38.468 -2.493 1.00 69.46 O
HETATM 690 O3* OMC A 32 77.529 36.305 -5.304 1.00 71.71 O
HETATM 691 C5* OMC A 32 78.349 39.239 -4.237 1.00 68.92 C
HETATM 692 O5* OMC A 32 77.359 40.004 -4.930 1.00 69.40 O
HETATM 693 P OMC A 32 77.644 41.515 -5.330 1.00 70.88 P
HETATM 694 O1P OMC A 32 76.360 42.128 -5.750 1.00 69.87 O
HETATM 695 O2P OMC A 32 78.813 41.581 -6.239 1.00 71.33 O
ATOM 696 P U A 33 76.971 35.962 -6.783 1.00 72.91 P
ATOM 697 O1P U A 33 78.044 35.151 -7.420 1.00 73.35 O
ATOM 698 O2P U A 33 76.437 37.170 -7.490 1.00 71.97 O
ATOM 699 O5* U A 33 75.699 35.053 -6.505 1.00 71.09 O
ATOM 700 C5* U A 33 75.822 33.741 -5.951 1.00 71.16 C
ATOM 701 C4* U A 33 74.457 33.095 -5.870 1.00 72.48 C
ATOM 702 O4* U A 33 73.655 33.729 -4.828 1.00 73.47 O
ATOM 703 C3* U A 33 73.601 33.208 -7.129 1.00 72.70 C
ATOM 704 O3* U A 33 73.935 32.212 -8.110 1.00 70.79 O
ATOM 705 C2* U A 33 72.190 33.041 -6.575 1.00 72.85 C
ATOM 706 O2* U A 33 71.917 31.668 -6.340 1.00 73.80 O
ATOM 707 C1* U A 33 72.289 33.769 -5.226 1.00 72.04 C
ATOM 708 N1 U A 33 71.847 35.177 -5.291 1.00 69.22 N
ATOM 709 C2 U A 33 70.504 35.476 -4.990 1.00 67.66 C
ATOM 710 O2 U A 33 69.696 34.637 -4.613 1.00 66.73 O
ATOM 711 N3 U A 33 70.155 36.799 -5.139 1.00 64.32 N
ATOM 712 C4 U A 33 70.975 37.841 -5.535 1.00 64.94 C
ATOM 713 O4 U A 33 70.494 38.966 -5.720 1.00 60.96 O
ATOM 714 C5 U A 33 72.339 37.462 -5.787 1.00 65.88 C
ATOM 715 C6 U A 33 72.718 36.181 -5.660 1.00 68.66 C
HETATM 716 P OMG A 34 73.785 32.556 -9.678 1.00 71.12 P
HETATM 717 O1P OMG A 34 74.725 33.685 -10.014 1.00 67.66 O
HETATM 718 O2P OMG A 34 73.921 31.249 -10.387 1.00 68.06 O
HETATM 719 O5* OMG A 34 72.274 33.065 -9.810 1.00 65.26 O
HETATM 720 C5* OMG A 34 71.764 33.656 -11.016 1.00 64.26 C
HETATM 721 C4* OMG A 34 70.295 33.326 -11.163 1.00 64.62 C
HETATM 722 O4* OMG A 34 70.126 31.890 -11.328 1.00 63.80 O
HETATM 723 C3* OMG A 34 69.463 33.672 -9.939 1.00 65.81 C
HETATM 724 O3* OMG A 34 69.094 35.051 -9.965 1.00 67.70 O
HETATM 725 C2* OMG A 34 68.311 32.644 -9.969 1.00 64.60 C
HETATM 726 O2* OMG A 34 67.083 32.909 -10.666 1.00 63.66 O
HETATM 727 CM2 OMG A 34 67.294 33.412 -11.976 1.00 64.30 C
HETATM 728 C1* OMG A 34 68.999 31.433 -10.593 1.00 61.80 C
HETATM 729 N9 OMG A 34 69.429 30.396 -9.649 1.00 59.16 N
HETATM 730 C8 OMG A 34 70.718 29.977 -9.388 1.00 57.76 C
HETATM 731 N7 OMG A 34 70.774 28.948 -8.579 1.00 56.91 N
HETATM 732 C5 OMG A 34 69.441 28.691 -8.266 1.00 58.76 C
HETATM 733 C6 OMG A 34 68.866 27.676 -7.438 1.00 60.12 C
HETATM 734 O6 OMG A 34 69.451 26.785 -6.793 1.00 60.12 O
HETATM 735 N1 OMG A 34 67.469 27.777 -7.395 1.00 59.19 N
HETATM 736 C2 OMG A 34 66.720 28.751 -8.040 1.00 59.35 C
HETATM 737 N2 OMG A 34 65.376 28.719 -7.843 1.00 56.71 N
HETATM 738 N3 OMG A 34 67.250 29.698 -8.816 1.00 58.06 N
HETATM 739 C4 OMG A 34 68.602 29.600 -8.889 1.00 58.63 C
ATOM 740 P A A 35 69.287 35.959 -8.637 1.00 69.94 P
ATOM 741 O1P A A 35 68.963 37.372 -8.988 1.00 66.80 O
ATOM 742 O2P A A 35 70.613 35.629 -8.027 1.00 67.49 O
ATOM 743 O5* A A 35 68.138 35.409 -7.674 1.00 69.12 O
ATOM 744 C5* A A 35 66.791 35.233 -8.158 1.00 71.95 C
ATOM 745 C4* A A 35 65.999 34.348 -7.216 1.00 73.29 C
ATOM 746 O4* A A 35 66.330 32.957 -7.426 1.00 71.52 O
ATOM 747 C3* A A 35 66.228 34.575 -5.733 1.00 75.03 C
ATOM 748 O3* A A 35 65.477 35.689 -5.246 1.00 79.27 O
ATOM 749 C2* A A 35 65.806 33.241 -5.122 1.00 73.35 C
ATOM 750 O2* A A 35 64.415 33.130 -4.902 1.00 73.82 O
ATOM 751 C1* A A 35 66.202 32.251 -6.217 1.00 69.82 C
ATOM 752 N9 A A 35 67.458 31.568 -5.953 1.00 66.95 N
ATOM 753 C8 A A 35 68.714 31.908 -6.382 1.00 65.90 C
ATOM 754 N7 A A 35 69.650 31.095 -5.969 1.00 63.58 N
ATOM 755 C5 A A 35 68.964 30.158 -5.217 1.00 64.51 C
ATOM 756 C6 A A 35 69.394 29.030 -4.505 1.00 64.64 C
ATOM 757 N6 A A 35 70.676 28.646 -4.442 1.00 64.41 N
ATOM 758 N1 A A 35 68.454 28.302 -3.853 1.00 64.67 N
ATOM 759 C2 A A 35 67.173 28.694 -3.936 1.00 64.93 C
ATOM 760 N3 A A 35 66.650 29.737 -4.582 1.00 64.37 N
ATOM 761 C4 A A 35 67.612 30.435 -5.203 1.00 64.99 C
ATOM 762 P A A 36 66.113 36.647 -4.115 1.00 81.67 P
ATOM 763 O1P A A 36 65.045 37.623 -3.738 1.00 81.59 O
ATOM 764 O2P A A 36 67.432 37.156 -4.600 1.00 82.66 O
ATOM 765 O5* A A 36 66.374 35.639 -2.911 1.00 83.98 O
ATOM 766 C5* A A 36 65.302 34.813 -2.451 1.00 87.71 C
ATOM 767 C4* A A 36 65.801 33.698 -1.565 1.00 90.67 C
ATOM 768 O4* A A 36 66.568 32.696 -2.288 1.00 89.82 O
ATOM 769 C3* A A 36 66.712 33.999 -0.388 1.00 92.78 C
ATOM 770 O3* A A 36 66.031 34.644 0.701 1.00 97.07 O
ATOM 771 C2* A A 36 67.162 32.587 0.010 1.00 91.11 C
ATOM 772 O2* A A 36 66.278 31.932 0.896 1.00 92.17 O
ATOM 773 C1* A A 36 67.143 31.833 -1.328 1.00 88.90 C
ATOM 774 N9 A A 36 68.488 31.414 -1.719 1.00 85.94 N
ATOM 775 C8 A A 36 69.437 32.000 -2.530 1.00 84.74 C
ATOM 776 N7 A A 36 70.588 31.361 -2.537 1.00 83.82 N
ATOM 777 C5 A A 36 70.369 30.267 -1.700 1.00 84.29 C
ATOM 778 C6 A A 36 71.195 29.192 -1.278 1.00 84.05 C
ATOM 779 N6 A A 36 72.462 29.017 -1.673 1.00 85.59 N
ATOM 780 N1 A A 36 70.658 28.283 -0.430 1.00 83.44 N
ATOM 781 C2 A A 36 69.385 28.429 -0.052 1.00 82.14 C
ATOM 782 N3 A A 36 68.512 29.376 -0.383 1.00 82.89 N
ATOM 783 C4 A A 36 69.074 30.277 -1.213 1.00 84.44 C
HETATM 784 N1 YG A 37 73.405 29.912 1.754 1.00 91.04 N
HETATM 785 N2 YG A 37 73.444 28.355 3.405 1.00 90.89 N
HETATM 786 C2 YG A 37 72.723 29.290 2.751 1.00 90.80 C
HETATM 787 N3 YG A 37 71.471 29.563 3.082 1.00 90.20 N
HETATM 788 C3 YG A 37 70.758 28.811 4.134 1.00 89.88 C
HETATM 789 C4 YG A 37 70.959 30.583 2.344 1.00 90.19 C
HETATM 790 C5 YG A 37 71.580 31.301 1.340 1.00 89.89 C
HETATM 791 C6 YG A 37 72.913 30.962 0.974 1.00 90.32 C
HETATM 792 O6 YG A 37 73.618 31.473 0.097 1.00 89.77 O
HETATM 793 N7 YG A 37 70.739 32.287 0.844 1.00 89.86 N
HETATM 794 C8 YG A 37 69.640 32.153 1.532 1.00 89.85 C
HETATM 795 N9 YG A 37 69.698 31.144 2.464 1.00 90.90 N
HETATM 796 C10 YG A 37 75.897 27.876 3.472 1.00 91.27 C
HETATM 797 C11 YG A 37 74.717 28.526 2.928 1.00 92.18 C
HETATM 798 C12 YG A 37 74.703 29.466 1.794 1.00 92.82 C
HETATM 799 C13 YG A 37 75.894 29.679 0.821 1.00 95.17 C
HETATM 800 C14 YG A 37 75.821 28.497 -0.184 1.00 98.02 C
HETATM 801 C15 YG A 37 76.173 28.762 -1.668 1.00 99.84 C
HETATM 802 C16 YG A 37 75.991 27.380 -2.269 1.00 99.97 C
HETATM 803 O17 YG A 37 74.838 26.920 -2.376 1.00100.19 O
HETATM 804 O18 YG A 37 76.976 26.693 -2.657 1.00100.19 O
HETATM 805 C19 YG A 37 77.769 27.170 -3.764 1.00 99.79 C
HETATM 806 N20 YG A 37 75.234 29.792 -2.267 1.00100.19 N
HETATM 807 C21 YG A 37 75.173 30.151 -3.610 1.00100.19 C
HETATM 808 O22 YG A 37 74.112 30.084 -4.264 1.00100.19 O
HETATM 809 O23 YG A 37 76.221 30.547 -4.170 1.00100.19 O
HETATM 810 C24 YG A 37 76.863 31.711 -3.637 1.00 99.34 C
HETATM 811 C1* YG A 37 68.645 30.761 3.410 1.00 93.08 C
HETATM 812 C2* YG A 37 68.983 31.220 4.830 1.00 94.21 C
HETATM 813 O2* YG A 37 68.545 30.264 5.774 1.00 94.06 O
HETATM 814 C3* YG A 37 68.238 32.545 4.908 1.00 94.74 C
HETATM 815 O3* YG A 37 68.016 32.978 6.242 1.00 95.58 O
HETATM 816 C4* YG A 37 66.976 32.279 4.107 1.00 94.30 C
HETATM 817 O4* YG A 37 67.424 31.399 3.039 1.00 94.11 O
HETATM 818 C5* YG A 37 66.323 33.509 3.519 1.00 95.27 C
HETATM 819 O5* YG A 37 67.311 34.330 2.856 1.00 96.96 O
HETATM 820 P YG A 37 66.875 35.460 1.815 1.00 99.01 P
HETATM 821 O1P YG A 37 68.123 35.981 1.180 1.00 99.22 O
HETATM 822 O2P YG A 37 65.932 36.421 2.473 1.00 99.27 O
ATOM 823 P A A 38 69.075 33.984 6.915 1.00 95.95 P
ATOM 824 O1P A A 38 68.607 34.325 8.279 1.00 96.86 O
ATOM 825 O2P A A 38 69.344 35.071 5.940 1.00 96.06 O
ATOM 826 O5* A A 38 70.393 33.112 7.051 1.00 93.01 O
ATOM 827 C5* A A 38 70.417 31.929 7.859 1.00 91.33 C
ATOM 828 C4* A A 38 71.783 31.310 7.804 1.00 90.73 C
ATOM 829 O4* A A 38 72.019 30.786 6.472 1.00 89.61 O
ATOM 830 C3* A A 38 72.876 32.339 8.008 1.00 90.95 C
ATOM 831 O3* A A 38 73.107 32.623 9.369 1.00 92.09 O
ATOM 832 C2* A A 38 74.046 31.768 7.218 1.00 90.07 C
ATOM 833 O2* A A 38 74.791 30.775 7.903 1.00 89.63 O
ATOM 834 C1* A A 38 73.308 31.178 6.015 1.00 88.20 C
ATOM 835 N9 A A 38 73.101 32.188 4.971 1.00 84.93 N
ATOM 836 C8 A A 38 71.911 32.814 4.660 1.00 83.84 C
ATOM 837 N7 A A 38 72.004 33.675 3.679 1.00 82.59 N
ATOM 838 C5 A A 38 73.344 33.617 3.312 1.00 82.67 C
ATOM 839 C6 A A 38 74.081 34.292 2.315 1.00 81.67 C
ATOM 840 N6 A A 38 73.539 35.181 1.471 1.00 80.44 N
ATOM 841 N1 A A 38 75.404 34.015 2.214 1.00 80.84 N
ATOM 842 C2 A A 38 75.938 33.108 3.055 1.00 81.31 C
ATOM 843 N3 A A 38 75.346 32.402 4.026 1.00 82.09 N
ATOM 844 C4 A A 38 74.035 32.708 4.104 1.00 83.08 C
HETATM 845 N1 PSU A 39 74.080 36.066 5.459 1.00 75.82 N
HETATM 846 C2 PSU A 39 74.415 36.835 4.354 1.00 75.59 C
HETATM 847 N3 PSU A 39 75.735 36.769 3.984 1.00 76.29 N
HETATM 848 C4 PSU A 39 76.728 36.038 4.591 1.00 77.28 C
HETATM 849 C5 PSU A 39 76.307 35.280 5.732 1.00 77.93 C
HETATM 850 C6 PSU A 39 75.025 35.316 6.112 1.00 76.07 C
HETATM 851 O2 PSU A 39 73.605 37.525 3.749 1.00 75.80 O
HETATM 852 O4 PSU A 39 77.875 36.079 4.134 1.00 77.81 O
HETATM 853 C1* PSU A 39 77.325 34.455 6.488 1.00 79.85 C
HETATM 854 C2* PSU A 39 78.240 35.315 7.366 1.00 80.79 C
HETATM 855 O2* PSU A 39 79.550 34.775 7.399 1.00 79.82 O
HETATM 856 C3* PSU A 39 77.509 35.235 8.700 1.00 81.32 C
HETATM 857 C4* PSU A 39 77.034 33.800 8.726 1.00 83.30 C
HETATM 858 O3* PSU A 39 78.312 35.525 9.823 1.00 80.38 O
HETATM 859 O4* PSU A 39 76.648 33.545 7.349 1.00 81.10 O
HETATM 860 C5* PSU A 39 75.867 33.557 9.646 1.00 86.38 C
HETATM 861 O5* PSU A 39 74.796 34.470 9.341 1.00 90.31 O
HETATM 862 P PSU A 39 73.308 34.151 9.814 1.00 92.76 P
HETATM 863 O1P PSU A 39 73.270 34.200 11.303 1.00 93.12 O
HETATM 864 O2P PSU A 39 72.370 34.998 9.024 1.00 92.11 O
HETATM 865 P 5MC A 40 78.152 36.942 10.553 1.00 79.24 P
HETATM 866 O1P 5MC A 40 76.685 37.167 10.693 1.00 80.02 O
HETATM 867 O2P 5MC A 40 79.021 36.942 11.759 1.00 78.31 O
HETATM 868 O5* 5MC A 40 78.720 37.994 9.494 1.00 76.52 O
HETATM 869 C5* 5MC A 40 80.116 38.022 9.141 1.00 72.60 C
HETATM 870 C4* 5MC A 40 80.351 38.970 7.985 1.00 69.92 C
HETATM 871 O4* 5MC A 40 79.612 38.525 6.814 1.00 68.54 O
HETATM 872 C3* 5MC A 40 79.877 40.397 8.200 1.00 68.47 C
HETATM 873 O3* 5MC A 40 80.825 41.181 8.913 1.00 66.73 O
HETATM 874 C2* 5MC A 40 79.663 40.906 6.778 1.00 69.16 C
HETATM 875 O2* 5MC A 40 80.841 41.385 6.165 1.00 68.77 O
HETATM 876 C1* 5MC A 40 79.168 39.648 6.065 1.00 67.58 C
HETATM 877 N1 5MC A 40 77.695 39.634 6.019 1.00 65.59 N
HETATM 878 C2 5MC A 40 77.041 40.408 5.050 1.00 63.72 C
HETATM 879 O2 5MC A 40 77.718 41.074 4.247 1.00 61.25 O
HETATM 880 N3 5MC A 40 75.695 40.421 5.017 1.00 63.28 N
HETATM 881 C4 5MC A 40 74.995 39.705 5.898 1.00 62.84 C
HETATM 882 N4 5MC A 40 73.662 39.740 5.803 1.00 62.95 N
HETATM 883 C5 5MC A 40 75.630 38.920 6.903 1.00 63.44 C
HETATM 884 C6 5MC A 40 76.968 38.900 6.919 1.00 64.81 C
HETATM 885 CM5 5MC A 40 74.837 38.153 7.923 1.00 63.46 C
ATOM 886 P U A 41 80.313 42.447 9.767 1.00 63.29 P
ATOM 887 O1P U A 41 81.427 42.965 10.609 1.00 65.66 O
ATOM 888 O2P U A 41 79.049 42.016 10.412 1.00 63.65 O
ATOM 889 O5* U A 41 79.984 43.552 8.669 1.00 62.24 O
ATOM 890 C5* U A 41 81.036 44.143 7.918 1.00 56.79 C
ATOM 891 C4* U A 41 80.498 45.168 6.953 1.00 56.45 C
ATOM 892 O4* U A 41 79.680 44.526 5.942 1.00 53.37 O
ATOM 893 C3* U A 41 79.592 46.251 7.508 1.00 54.69 C
ATOM 894 O3* U A 41 80.283 47.292 8.160 1.00 55.80 O
ATOM 895 C2* U A 41 78.887 46.737 6.251 1.00 52.98 C
ATOM 896 O2* U A 41 79.686 47.539 5.407 1.00 54.28 O
ATOM 897 C1* U A 41 78.651 45.424 5.527 1.00 49.85 C
ATOM 898 N1 U A 41 77.358 44.851 5.928 1.00 45.19 N
ATOM 899 C2 U A 41 76.197 45.430 5.430 1.00 41.52 C
ATOM 900 O2 U A 41 76.190 46.418 4.723 1.00 42.41 O
ATOM 901 N3 U A 41 75.046 44.808 5.803 1.00 41.65 N
ATOM 902 C4 U A 41 74.928 43.710 6.596 1.00 40.75 C
ATOM 903 O4 U A 41 73.826 43.203 6.735 1.00 49.24 O
ATOM 904 C5 U A 41 76.154 43.186 7.099 1.00 43.67 C
ATOM 905 C6 U A 41 77.302 43.767 6.753 1.00 41.90 C
ATOM 906 P G A 42 79.705 47.861 9.545 1.00 53.54 P
ATOM 907 O1P G A 42 80.846 48.577 10.148 1.00 56.88 O
ATOM 908 O2P G A 42 79.060 46.769 10.292 1.00 47.65 O
ATOM 909 O5* G A 42 78.638 48.930 9.059 1.00 51.64 O
ATOM 910 C5* G A 42 79.001 49.877 8.054 1.00 51.41 C
ATOM 911 C4* G A 42 77.769 50.433 7.372 1.00 54.00 C
ATOM 912 O4* G A 42 77.032 49.365 6.704 1.00 51.14 O
ATOM 913 C3* G A 42 76.726 51.067 8.272 1.00 53.82 C
ATOM 914 O3* G A 42 77.060 52.389 8.660 1.00 57.90 O
ATOM 915 C2* G A 42 75.480 51.029 7.397 1.00 53.12 C
ATOM 916 O2* G A 42 75.444 52.122 6.489 1.00 55.26 O
ATOM 917 C1* G A 42 75.657 49.688 6.671 1.00 49.13 C
ATOM 918 N9 G A 42 74.906 48.601 7.302 1.00 44.46 N
ATOM 919 C8 G A 42 75.381 47.535 8.030 1.00 41.11 C
ATOM 920 N7 G A 42 74.431 46.730 8.433 1.00 41.58 N
ATOM 921 C5 G A 42 73.265 47.311 7.951 1.00 42.30 C
ATOM 922 C6 G A 42 71.901 46.887 8.049 1.00 39.56 C
ATOM 923 O6 G A 42 71.457 45.892 8.572 1.00 41.46 O
ATOM 924 N1 G A 42 71.044 47.776 7.421 1.00 40.73 N
ATOM 925 C2 G A 42 71.439 48.906 6.760 1.00 39.14 C
ATOM 926 N2 G A 42 70.481 49.648 6.204 1.00 43.75 N
ATOM 927 N3 G A 42 72.696 49.297 6.643 1.00 42.69 N
ATOM 928 C4 G A 42 73.544 48.463 7.263 1.00 41.15 C
ATOM 929 P G A 43 76.348 53.024 9.953 1.00 59.25 P
ATOM 930 O1P G A 43 76.997 54.350 10.246 1.00 56.83 O
ATOM 931 O2P G A 43 76.330 51.946 10.985 1.00 53.33 O
ATOM 932 O5* G A 43 74.844 53.245 9.472 1.00 55.31 O
ATOM 933 C5* G A 43 74.543 54.211 8.454 1.00 54.14 C
ATOM 934 C4* G A 43 73.059 54.264 8.204 1.00 51.95 C
ATOM 935 O4* G A 43 72.595 52.976 7.736 1.00 49.20 O
ATOM 936 C3* G A 43 72.190 54.541 9.414 1.00 53.09 C
ATOM 937 O3* G A 43 72.143 55.927 9.696 1.00 58.30 O
ATOM 938 C2* G A 43 70.852 53.982 8.963 1.00 50.69 C
ATOM 939 O2* G A 43 70.277 54.842 8.008 1.00 55.19 O
ATOM 940 C1* G A 43 71.295 52.730 8.219 1.00 46.94 C
ATOM 941 N9 G A 43 71.350 51.546 9.071 1.00 44.87 N
ATOM 942 C8 G A 43 72.451 50.993 9.658 1.00 41.57 C
ATOM 943 N7 G A 43 72.182 49.898 10.321 1.00 41.08 N
ATOM 944 C5 G A 43 70.826 49.729 10.161 1.00 40.57 C
ATOM 945 C6 G A 43 69.965 48.713 10.615 1.00 40.78 C
ATOM 946 O6 G A 43 70.230 47.688 11.221 1.00 38.22 O
ATOM 947 N1 G A 43 68.652 48.964 10.259 1.00 41.30 N
ATOM 948 C2 G A 43 68.217 50.037 9.555 1.00 42.51 C
ATOM 949 N2 G A 43 66.869 50.119 9.354 1.00 42.42 N
ATOM 950 N3 G A 43 69.008 50.969 9.090 1.00 44.65 N
ATOM 951 C4 G A 43 70.291 50.756 9.425 1.00 44.20 C
ATOM 952 P A A 44 71.830 56.434 11.191 1.00 59.72 P
ATOM 953 O1P A A 44 72.143 57.887 11.179 1.00 60.18 O
ATOM 954 O2P A A 44 72.477 55.542 12.203 1.00 59.03 O
ATOM 955 O5* A A 44 70.251 56.220 11.341 1.00 61.19 O
ATOM 956 C5* A A 44 69.317 56.879 10.465 1.00 59.15 C
ATOM 957 C4* A A 44 67.971 56.191 10.523 1.00 58.59 C
ATOM 958 O4* A A 44 68.135 54.794 10.173 1.00 58.70 O
ATOM 959 C3* A A 44 67.277 56.140 11.871 1.00 58.67 C
ATOM 960 O3* A A 44 66.523 57.316 12.123 1.00 60.86 O
ATOM 961 C2* A A 44 66.365 54.931 11.744 1.00 56.86 C
ATOM 962 O2* A A 44 65.162 55.206 11.061 1.00 56.94 O
ATOM 963 C1* A A 44 67.208 53.996 10.887 1.00 54.14 C
ATOM 964 N9 A A 44 67.970 53.042 11.685 1.00 47.88 N
ATOM 965 C8 A A 44 69.290 53.122 12.063 1.00 44.83 C
ATOM 966 N7 A A 44 69.697 52.091 12.767 1.00 43.37 N
ATOM 967 C5 A A 44 68.570 51.276 12.856 1.00 41.45 C
ATOM 968 C6 A A 44 68.345 50.029 13.433 1.00 42.09 C
ATOM 969 N6 A A 44 69.278 49.331 14.092 1.00 45.08 N
ATOM 970 N1 A A 44 67.101 49.482 13.313 1.00 42.78 N
ATOM 971 C2 A A 44 66.176 50.170 12.653 1.00 41.91 C
ATOM 972 N3 A A 44 66.268 51.351 12.075 1.00 40.34 N
ATOM 973 C4 A A 44 67.500 51.858 12.203 1.00 45.75 C
ATOM 974 P G A 45 66.470 57.914 13.620 1.00 58.58 P
ATOM 975 O1P G A 45 65.444 58.996 13.659 1.00 60.46 O
ATOM 976 O2P G A 45 67.862 58.228 14.011 1.00 57.19 O
ATOM 977 O5* G A 45 65.905 56.683 14.444 1.00 57.67 O
ATOM 978 C5* G A 45 64.533 56.287 14.311 1.00 52.30 C
ATOM 979 C4* G A 45 64.255 55.158 15.248 1.00 50.49 C
ATOM 980 O4* G A 45 65.017 54.002 14.829 1.00 50.44 O
ATOM 981 C3* G A 45 64.685 55.408 16.681 1.00 49.36 C
ATOM 982 O3* G A 45 63.616 56.059 17.359 1.00 51.42 O
ATOM 983 C2* G A 45 64.894 53.991 17.190 1.00 48.83 C
ATOM 984 O2* G A 45 63.645 53.382 17.453 1.00 45.60 O
ATOM 985 C1* G A 45 65.456 53.277 15.954 1.00 45.24 C
ATOM 986 N9 G A 45 66.920 53.202 15.909 1.00 41.15 N
ATOM 987 C8 G A 45 67.772 54.149 15.386 1.00 40.45 C
ATOM 988 N7 G A 45 69.031 53.833 15.507 1.00 39.19 N
ATOM 989 C5 G A 45 69.014 52.601 16.134 1.00 35.16 C
ATOM 990 C6 G A 45 70.070 51.816 16.551 1.00 38.09 C
ATOM 991 O6 G A 45 71.292 52.028 16.410 1.00 39.62 O
ATOM 992 N1 G A 45 69.636 50.685 17.196 1.00 37.05 N
ATOM 993 C2 G A 45 68.338 50.332 17.390 1.00 38.47 C
ATOM 994 N2 G A 45 68.164 49.150 17.996 1.00 39.48 N
ATOM 995 N3 G A 45 67.301 51.072 17.004 1.00 37.37 N
ATOM 996 C4 G A 45 67.719 52.193 16.390 1.00 36.46 C
HETATM 997 P 7MG A 46 63.905 57.326 18.310 1.00 53.01 P
HETATM 998 O1P 7MG A 46 64.951 58.232 17.766 1.00 52.60 O
HETATM 999 O2P 7MG A 46 62.558 57.883 18.619 1.00 54.84 O
HETATM 1000 O5* 7MG A 46 64.457 56.673 19.662 1.00 50.92 O
HETATM 1001 C5* 7MG A 46 63.673 55.697 20.380 1.00 47.09 C
HETATM 1002 C4* 7MG A 46 63.911 55.833 21.859 1.00 45.87 C
HETATM 1003 O4* 7MG A 46 65.276 55.388 22.160 1.00 44.37 O
HETATM 1004 C3* 7MG A 46 63.810 57.269 22.378 1.00 44.64 C
HETATM 1005 O3* 7MG A 46 63.177 57.259 23.652 1.00 47.38 O
HETATM 1006 C2* 7MG A 46 65.280 57.700 22.484 1.00 44.78 C
HETATM 1007 O2* 7MG A 46 65.577 58.744 23.387 1.00 43.73 O
HETATM 1008 C1* 7MG A 46 65.949 56.384 22.900 1.00 39.69 C
HETATM 1009 N9 7MG A 46 67.386 56.266 22.628 1.00 35.94 N
HETATM 1010 C8 7MG A 46 68.201 57.146 21.945 1.00 35.57 C
HETATM 1011 N7 7MG A 46 69.429 56.680 21.823 1.00 35.71 N
HETATM 1012 C5 7MG A 46 69.423 55.456 22.475 1.00 30.85 C
HETATM 1013 C6 7MG A 46 70.472 54.529 22.704 1.00 32.44 C
HETATM 1014 O6 7MG A 46 71.653 54.665 22.404 1.00 34.18 O
HETATM 1015 N1 7MG A 46 70.035 53.405 23.371 1.00 27.06 N
HETATM 1016 C2 7MG A 46 68.726 53.216 23.821 1.00 28.72 C
HETATM 1017 N2 7MG A 46 68.413 52.076 24.386 1.00 30.51 N
HETATM 1018 N3 7MG A 46 67.782 54.113 23.692 1.00 29.24 N
HETATM 1019 C4 7MG A 46 68.183 55.188 22.989 1.00 30.11 C
HETATM 1020 CM7 7MG A 46 70.529 57.362 21.130 1.00 35.54 C
ATOM 1021 P U A 47 61.607 57.698 23.777 1.00 47.19 P
ATOM 1022 O1P U A 47 60.804 56.464 23.970 1.00 48.54 O
ATOM 1023 O2P U A 47 61.264 58.639 22.661 1.00 50.14 O
ATOM 1024 O5* U A 47 61.587 58.598 25.089 1.00 45.96 O
ATOM 1025 C5* U A 47 62.341 59.800 25.124 1.00 48.85 C
ATOM 1026 C4* U A 47 62.482 60.255 26.545 1.00 50.43 C
ATOM 1027 O4* U A 47 61.241 60.814 27.040 1.00 50.06 O
ATOM 1028 C3* U A 47 62.833 59.116 27.493 1.00 49.46 C
ATOM 1029 O3* U A 47 63.658 59.705 28.465 1.00 50.38 O
ATOM 1030 C2* U A 47 61.488 58.710 28.088 1.00 48.84 C
ATOM 1031 O2* U A 47 61.620 58.065 29.342 1.00 41.07 O
ATOM 1032 C1* U A 47 60.798 60.075 28.167 1.00 50.55 C
ATOM 1033 N1 U A 47 59.332 60.087 28.149 1.00 54.98 N
ATOM 1034 C2 U A 47 58.686 60.797 29.157 1.00 56.81 C
ATOM 1035 O2 U A 47 59.281 61.400 30.035 1.00 56.24 O
ATOM 1036 N3 U A 47 57.319 60.784 29.079 1.00 58.14 N
ATOM 1037 C4 U A 47 56.552 60.165 28.123 1.00 58.07 C
ATOM 1038 O4 U A 47 55.332 60.325 28.140 1.00 59.44 O
ATOM 1039 C5 U A 47 57.289 59.452 27.121 1.00 57.49 C
ATOM 1040 C6 U A 47 58.613 59.436 27.164 1.00 55.97 C
ATOM 1041 P C A 48 65.235 59.648 28.260 1.00 51.91 P
ATOM 1042 O1P C A 48 65.823 60.627 29.208 1.00 48.27 O
ATOM 1043 O2P C A 48 65.455 59.769 26.780 1.00 53.23 O
ATOM 1044 O5* C A 48 65.585 58.155 28.696 1.00 48.16 O
ATOM 1045 C5* C A 48 65.553 57.821 30.068 1.00 37.25 C
ATOM 1046 C4* C A 48 66.046 56.424 30.251 1.00 33.96 C
ATOM 1047 O4* C A 48 67.242 56.203 29.430 1.00 33.29 O
ATOM 1048 C3* C A 48 66.457 56.168 31.682 1.00 32.27 C
ATOM 1049 O3* C A 48 66.149 54.821 32.011 1.00 29.89 O
ATOM 1050 C2* C A 48 67.972 56.366 31.634 1.00 27.98 C
ATOM 1051 O2* C A 48 68.646 55.696 32.665 1.00 27.27 O
ATOM 1052 C1* C A 48 68.291 55.799 30.245 1.00 27.98 C
ATOM 1053 N1 C A 48 69.554 56.279 29.660 1.00 23.61 N
ATOM 1054 C2 C A 48 70.690 55.421 29.693 1.00 24.90 C
ATOM 1055 O2 C A 48 70.567 54.326 30.181 1.00 24.38 O
ATOM 1056 N3 C A 48 71.884 55.875 29.215 1.00 23.05 N
ATOM 1057 C4 C A 48 71.964 57.127 28.722 1.00 24.65 C
ATOM 1058 N4 C A 48 73.163 57.592 28.288 1.00 21.79 N
ATOM 1059 C5 C A 48 70.843 57.978 28.653 1.00 27.10 C
ATOM 1060 C6 C A 48 69.665 57.518 29.131 1.00 23.05 C
HETATM 1061 P 5MC A 49 65.638 54.464 33.461 1.00 31.61 P
HETATM 1062 O1P 5MC A 49 65.643 52.989 33.540 1.00 33.43 O
HETATM 1063 O2P 5MC A 49 66.252 55.251 34.624 1.00 26.54 O
HETATM 1064 O5* 5MC A 49 64.126 54.972 33.441 1.00 31.88 O
HETATM 1065 C5* 5MC A 49 63.204 54.605 32.392 1.00 32.68 C
HETATM 1066 C4* 5MC A 49 61.796 55.006 32.810 1.00 30.80 C
HETATM 1067 O4* 5MC A 49 61.292 54.110 33.848 1.00 32.40 O
HETATM 1068 C3* 5MC A 49 61.745 56.381 33.468 1.00 31.44 C
HETATM 1069 O3* 5MC A 49 61.666 57.398 32.483 1.00 31.25 O
HETATM 1070 C2* 5MC A 49 60.485 56.287 34.312 1.00 34.62 C
HETATM 1071 O2* 5MC A 49 59.414 56.469 33.417 1.00 35.41 O
HETATM 1072 C1* 5MC A 49 60.568 54.849 34.825 1.00 33.10 C
HETATM 1073 N1 5MC A 49 61.331 54.787 36.102 1.00 32.34 N
HETATM 1074 C2 5MC A 49 60.737 55.340 37.271 1.00 32.42 C
HETATM 1075 O2 5MC A 49 59.568 55.832 37.197 1.00 28.24 O
HETATM 1076 N3 5MC A 49 61.420 55.348 38.428 1.00 29.50 N
HETATM 1077 C4 5MC A 49 62.626 54.785 38.503 1.00 32.97 C
HETATM 1078 N4 5MC A 49 63.188 54.744 39.702 1.00 28.75 N
HETATM 1079 C5 5MC A 49 63.270 54.215 37.358 1.00 34.81 C
HETATM 1080 C6 5MC A 49 62.583 54.243 36.161 1.00 33.69 C
HETATM 1081 CM5 5MC A 49 64.655 53.581 37.465 1.00 34.52 C
ATOM 1082 P U A 50 62.421 58.828 32.744 1.00 33.43 P
ATOM 1083 O1P U A 50 62.480 59.502 31.468 1.00 33.78 O
ATOM 1084 O2P U A 50 63.651 58.683 33.637 1.00 30.15 O
ATOM 1085 O5* U A 50 61.374 59.605 33.659 1.00 33.34 O
ATOM 1086 C5* U A 50 60.011 59.728 33.268 1.00 34.47 C
ATOM 1087 C4* U A 50 59.218 60.444 34.331 1.00 31.72 C
ATOM 1088 O4* U A 50 58.928 59.552 35.438 1.00 29.81 O
ATOM 1089 C3* U A 50 59.871 61.655 34.983 1.00 32.89 C
ATOM 1090 O3* U A 50 59.731 62.817 34.131 1.00 33.31 O
ATOM 1091 C2* U A 50 59.066 61.725 36.279 1.00 33.15 C
ATOM 1092 O2* U A 50 57.727 62.115 35.997 1.00 35.03 O
ATOM 1093 C1* U A 50 58.966 60.259 36.646 1.00 31.45 C
ATOM 1094 N1 U A 50 60.113 59.812 37.453 1.00 31.52 N
ATOM 1095 C2 U A 50 60.106 60.183 38.793 1.00 30.82 C
ATOM 1096 O2 U A 50 59.256 60.941 39.253 1.00 30.94 O
ATOM 1097 N3 U A 50 61.128 59.648 39.560 1.00 28.21 N
ATOM 1098 C4 U A 50 62.143 58.831 39.099 1.00 27.57 C
ATOM 1099 O4 U A 50 62.938 58.308 39.924 1.00 33.33 O
ATOM 1100 C5 U A 50 62.120 58.581 37.684 1.00 29.31 C
ATOM 1101 C6 U A 50 61.140 59.068 36.927 1.00 31.19 C
ATOM 1102 P G A 51 60.854 63.992 34.167 1.00 39.01 P
ATOM 1103 O1P G A 51 60.476 64.987 33.121 1.00 35.87 O
ATOM 1104 O2P G A 51 62.217 63.402 34.134 1.00 37.91 O
ATOM 1105 O5* G A 51 60.648 64.595 35.600 1.00 36.58 O
ATOM 1106 C5* G A 51 59.391 65.231 35.906 1.00 40.92 C
ATOM 1107 C4* G A 51 59.365 65.668 37.334 1.00 38.83 C
ATOM 1108 O4* G A 51 59.409 64.501 38.203 1.00 38.03 O
ATOM 1109 C3* G A 51 60.529 66.527 37.797 1.00 40.34 C
ATOM 1110 O3* G A 51 60.383 67.887 37.400 1.00 41.89 O
ATOM 1111 C2* G A 51 60.488 66.292 39.298 1.00 38.39 C
ATOM 1112 O2* G A 51 59.369 66.938 39.873 1.00 35.78 O
ATOM 1113 C1* G A 51 60.143 64.799 39.378 1.00 37.87 C
ATOM 1114 N9 G A 51 61.303 63.902 39.460 1.00 32.83 N
ATOM 1115 C8 G A 51 61.915 63.238 38.424 1.00 33.29 C
ATOM 1116 N7 G A 51 62.917 62.483 38.830 1.00 36.76 N
ATOM 1117 C5 G A 51 62.986 62.690 40.208 1.00 35.57 C
ATOM 1118 C6 G A 51 63.913 62.188 41.197 1.00 34.80 C
ATOM 1119 O6 G A 51 64.846 61.404 41.049 1.00 35.08 O
ATOM 1120 N1 G A 51 63.653 62.706 42.466 1.00 36.79 N
ATOM 1121 C2 G A 51 62.620 63.573 42.759 1.00 37.65 C
ATOM 1122 N2 G A 51 62.530 63.985 44.032 1.00 35.39 N
ATOM 1123 N3 G A 51 61.746 64.007 41.868 1.00 36.74 N
ATOM 1124 C4 G A 51 61.996 63.548 40.619 1.00 35.55 C
ATOM 1125 P U A 52 61.706 68.803 37.121 1.00 42.84 P
ATOM 1126 O1P U A 52 61.321 70.142 36.563 1.00 41.91 O
ATOM 1127 O2P U A 52 62.726 68.025 36.369 1.00 41.76 O
ATOM 1128 O5* U A 52 62.224 68.978 38.598 1.00 36.07 O
ATOM 1129 C5* U A 52 61.477 69.672 39.558 1.00 34.35 C
ATOM 1130 C4* U A 52 62.118 69.559 40.905 1.00 33.37 C
ATOM 1131 O4* U A 52 62.012 68.190 41.401 1.00 32.65 O
ATOM 1132 C3* U A 52 63.616 69.845 41.000 1.00 33.39 C
ATOM 1133 O3* U A 52 63.932 71.237 41.043 1.00 39.74 O
ATOM 1134 C2* U A 52 63.939 69.176 42.335 1.00 30.75 C
ATOM 1135 O2* U A 52 63.396 69.967 43.391 1.00 32.96 O
ATOM 1136 C1* U A 52 63.119 67.888 42.237 1.00 31.31 C
ATOM 1137 N1 U A 52 63.946 66.845 41.579 1.00 30.44 N
ATOM 1138 C2 U A 52 64.863 66.182 42.369 1.00 30.06 C
ATOM 1139 O2 U A 52 65.009 66.454 43.550 1.00 29.26 O
ATOM 1140 N3 U A 52 65.623 65.231 41.729 1.00 29.70 N
ATOM 1141 C4 U A 52 65.587 64.922 40.408 1.00 34.08 C
ATOM 1142 O4 U A 52 66.347 64.036 39.967 1.00 34.26 O
ATOM 1143 C5 U A 52 64.622 65.680 39.641 1.00 33.07 C
ATOM 1144 C6 U A 52 63.831 66.587 40.266 1.00 26.53 C
ATOM 1145 P G A 53 65.414 71.746 40.572 1.00 37.07 P
ATOM 1146 O1P G A 53 65.308 73.211 40.502 1.00 37.71 O
ATOM 1147 O2P G A 53 65.813 70.998 39.374 1.00 30.94 O
ATOM 1148 O5* G A 53 66.393 71.211 41.694 1.00 32.28 O
ATOM 1149 C5* G A 53 66.229 71.538 43.081 1.00 34.99 C
ATOM 1150 C4* G A 53 67.174 70.724 43.912 1.00 34.42 C
ATOM 1151 O4* G A 53 66.864 69.323 43.765 1.00 35.23 O
ATOM 1152 C3* G A 53 68.665 70.782 43.620 1.00 34.67 C
ATOM 1153 O3* G A 53 69.247 71.895 44.262 1.00 38.95 O
ATOM 1154 C2* G A 53 69.164 69.500 44.283 1.00 34.61 C
ATOM 1155 O2* G A 53 69.182 69.612 45.688 1.00 34.19 O
ATOM 1156 C1* G A 53 68.019 68.537 43.991 1.00 32.96 C
ATOM 1157 N9 G A 53 68.320 67.761 42.786 1.00 28.24 N
ATOM 1158 C8 G A 53 67.793 67.893 41.556 1.00 31.68 C
ATOM 1159 N7 G A 53 68.284 67.042 40.701 1.00 26.28 N
ATOM 1160 C5 G A 53 69.196 66.319 41.426 1.00 28.92 C
ATOM 1161 C6 G A 53 70.091 65.297 41.013 1.00 25.46 C
ATOM 1162 O6 G A 53 70.220 64.815 39.895 1.00 28.07 O
ATOM 1163 N1 G A 53 70.897 64.869 42.059 1.00 29.47 N
ATOM 1164 C2 G A 53 70.866 65.396 43.328 1.00 26.11 C
ATOM 1165 N2 G A 53 71.750 64.920 44.203 1.00 30.39 N
ATOM 1166 N3 G A 53 70.033 66.332 43.705 1.00 30.28 N
ATOM 1167 C4 G A 53 69.234 66.743 42.708 1.00 26.13 C
HETATM 1168 N1 5MU A 54 73.251 67.803 42.694 1.00 35.32 N
HETATM 1169 C2 5MU A 54 73.839 66.792 41.983 1.00 34.56 C
HETATM 1170 N3 5MU A 54 73.442 66.712 40.672 1.00 35.04 N
HETATM 1171 C4 5MU A 54 72.524 67.496 40.026 1.00 33.29 C
HETATM 1172 C5 5MU A 54 71.922 68.529 40.835 1.00 31.37 C
HETATM 1173 C5M 5MU A 54 70.918 69.466 40.203 1.00 28.02 C
HETATM 1174 C6 5MU A 54 72.301 68.618 42.113 1.00 33.12 C
HETATM 1175 O2 5MU A 54 74.649 66.016 42.473 1.00 42.24 O
HETATM 1176 O4 5MU A 54 72.257 67.283 38.828 1.00 36.52 O
HETATM 1177 C1* 5MU A 54 73.711 68.026 44.082 1.00 37.46 C
HETATM 1178 C2* 5MU A 54 75.024 68.864 44.109 1.00 40.51 C
HETATM 1179 O2* 5MU A 54 75.836 68.430 45.180 1.00 39.54 O
HETATM 1180 C3* 5MU A 54 74.485 70.281 44.321 1.00 42.37 C
HETATM 1181 C4* 5MU A 54 73.295 70.030 45.246 1.00 39.47 C
HETATM 1182 O3* 5MU A 54 75.448 71.209 44.879 1.00 44.31 O
HETATM 1183 O4* 5MU A 54 72.728 68.779 44.751 1.00 36.92 O
HETATM 1184 C5* 5MU A 54 72.225 71.084 45.312 1.00 38.24 C
HETATM 1185 O5* 5MU A 54 71.693 71.314 44.026 1.00 36.39 O
HETATM 1186 P 5MU A 54 70.668 72.485 43.743 1.00 37.08 P
HETATM 1187 O1P 5MU A 54 70.657 72.754 42.270 1.00 33.03 O
HETATM 1188 O2P 5MU A 54 70.866 73.636 44.695 1.00 39.97 O
HETATM 1189 N1 PSU A 55 74.158 70.927 39.519 1.00 35.82 N
HETATM 1190 C2 PSU A 55 73.717 70.455 38.323 1.00 38.30 C
HETATM 1191 N3 PSU A 55 74.479 69.441 37.783 1.00 35.34 N
HETATM 1192 C4 PSU A 55 75.687 68.934 38.291 1.00 36.07 C
HETATM 1193 C5 PSU A 55 76.107 69.537 39.499 1.00 33.56 C
HETATM 1194 C6 PSU A 55 75.337 70.458 40.076 1.00 35.52 C
HETATM 1195 O2 PSU A 55 72.728 70.924 37.738 1.00 37.13 O
HETATM 1196 O4 PSU A 55 76.304 68.043 37.675 1.00 32.17 O
HETATM 1197 C1* PSU A 55 77.461 69.118 40.100 1.00 34.24 C
HETATM 1198 C2* PSU A 55 78.634 70.014 39.665 1.00 37.02 C
HETATM 1199 O2* PSU A 55 79.793 69.181 39.668 1.00 37.99 O
HETATM 1200 C3* PSU A 55 78.650 71.033 40.796 1.00 38.47 C
HETATM 1201 C4* PSU A 55 78.398 70.137 41.999 1.00 35.54 C
HETATM 1202 O3* PSU A 55 79.864 71.807 40.930 1.00 37.81 O
HETATM 1203 O4* PSU A 55 77.424 69.161 41.505 1.00 34.94 O
HETATM 1204 C5* PSU A 55 77.870 70.849 43.223 1.00 36.16 C
HETATM 1205 O5* PSU A 55 76.820 71.796 42.859 1.00 39.91 O
HETATM 1206 P PSU A 55 75.925 72.471 43.991 1.00 43.83 P
HETATM 1207 O1P PSU A 55 74.766 73.172 43.306 1.00 46.32 O
HETATM 1208 O2P PSU A 55 76.844 73.293 44.834 1.00 45.38 O
ATOM 1209 P C A 56 79.893 73.323 40.427 1.00 37.81 P
ATOM 1210 O1P C A 56 81.372 73.714 40.748 1.00 37.74 O
ATOM 1211 O2P C A 56 78.768 74.121 41.003 1.00 35.29 O
ATOM 1212 O5* C A 56 79.825 73.304 38.871 1.00 33.59 O
ATOM 1213 C5* C A 56 79.545 74.494 38.135 1.00 33.82 C
ATOM 1214 C4* C A 56 79.735 74.239 36.678 1.00 32.83 C
ATOM 1215 O4* C A 56 81.120 73.946 36.360 1.00 33.52 O
ATOM 1216 C3* C A 56 78.954 73.036 36.142 1.00 30.99 C
ATOM 1217 O3* C A 56 77.596 73.405 35.829 1.00 31.77 O
ATOM 1218 C2* C A 56 79.739 72.659 34.901 1.00 31.94 C
ATOM 1219 O2* C A 56 79.480 73.400 33.725 1.00 29.83 O
ATOM 1220 C1* C A 56 81.174 72.955 35.333 1.00 33.49 C
ATOM 1221 N1 C A 56 81.800 71.739 35.857 1.00 29.51 N
ATOM 1222 C2 C A 56 82.298 70.818 34.956 1.00 28.07 C
ATOM 1223 O2 C A 56 82.160 71.013 33.755 1.00 29.82 O
ATOM 1224 N3 C A 56 82.907 69.716 35.412 1.00 27.72 N
ATOM 1225 C4 C A 56 83.035 69.503 36.720 1.00 32.68 C
ATOM 1226 N4 C A 56 83.675 68.399 37.102 1.00 29.93 N
ATOM 1227 C5 C A 56 82.515 70.397 37.674 1.00 30.58 C
ATOM 1228 C6 C A 56 81.894 71.503 37.204 1.00 29.09 C
ATOM 1229 P G A 57 76.379 72.458 36.349 1.00 32.12 P
ATOM 1230 O1P G A 57 75.189 73.231 35.952 1.00 34.27 O
ATOM 1231 O2P G A 57 76.558 72.064 37.745 1.00 22.22 O
ATOM 1232 O5* G A 57 76.529 71.173 35.451 1.00 28.84 O
ATOM 1233 C5* G A 57 76.321 71.233 34.052 1.00 30.38 C
ATOM 1234 C4* G A 57 76.829 69.964 33.385 1.00 32.75 C
ATOM 1235 O4* G A 57 78.284 69.786 33.566 1.00 34.57 O
ATOM 1236 C3* G A 57 76.221 68.672 33.883 1.00 29.11 C
ATOM 1237 O3* G A 57 74.937 68.457 33.239 1.00 27.73 O
ATOM 1238 C2* G A 57 77.251 67.650 33.423 1.00 28.35 C
ATOM 1239 O2* G A 57 77.136 67.492 32.013 1.00 34.71 O
ATOM 1240 C1* G A 57 78.571 68.404 33.655 1.00 32.37 C
ATOM 1241 N9 G A 57 79.153 68.106 34.968 1.00 26.80 N
ATOM 1242 C8 G A 57 79.113 68.840 36.137 1.00 26.67 C
ATOM 1243 N7 G A 57 79.792 68.266 37.110 1.00 27.09 N
ATOM 1244 C5 G A 57 80.280 67.087 36.529 1.00 28.66 C
ATOM 1245 C6 G A 57 81.103 66.037 37.080 1.00 28.50 C
ATOM 1246 O6 G A 57 81.588 65.974 38.203 1.00 28.04 O
ATOM 1247 N1 G A 57 81.358 65.033 36.153 1.00 27.23 N
ATOM 1248 C2 G A 57 80.910 65.036 34.858 1.00 27.75 C
ATOM 1249 N2 G A 57 81.215 63.982 34.112 1.00 25.22 N
ATOM 1250 N3 G A 57 80.185 66.017 34.328 1.00 27.62 N
ATOM 1251 C4 G A 57 79.901 66.989 35.227 1.00 25.05 C
HETATM 1252 P 1MA A 58 73.770 67.765 34.057 1.00 30.65 P
HETATM 1253 O1P 1MA A 58 73.621 68.229 35.450 1.00 29.49 O
HETATM 1254 O2P 1MA A 58 72.638 67.886 33.105 1.00 32.84 O
HETATM 1255 O5* 1MA A 58 74.315 66.273 34.254 1.00 28.81 O
HETATM 1256 C5* 1MA A 58 74.592 65.439 33.080 1.00 29.42 C
HETATM 1257 C4* 1MA A 58 74.279 63.972 33.383 1.00 33.42 C
HETATM 1258 O4* 1MA A 58 74.880 63.685 34.667 1.00 32.36 O
HETATM 1259 C3* 1MA A 58 72.789 63.573 33.509 1.00 35.13 C
HETATM 1260 O3* 1MA A 58 72.625 62.168 33.250 1.00 36.80 O
HETATM 1261 C2* 1MA A 58 72.560 63.667 35.012 1.00 34.80 C
HETATM 1262 O2* 1MA A 58 71.525 62.828 35.506 1.00 36.27 O
HETATM 1263 C1* 1MA A 58 73.908 63.150 35.551 1.00 33.62 C
HETATM 1264 N9 1MA A 58 74.284 63.494 36.930 1.00 30.36 N
HETATM 1265 C8 1MA A 58 73.887 64.574 37.688 1.00 34.55 C
HETATM 1266 N7 1MA A 58 74.415 64.610 38.899 1.00 33.32 N
HETATM 1267 C5 1MA A 58 75.204 63.469 38.953 1.00 33.37 C
HETATM 1268 C6 1MA A 58 76.031 62.941 39.948 1.00 33.58 C
HETATM 1269 N6 1MA A 58 76.184 63.488 41.134 1.00 41.19 N
HETATM 1270 N1 1MA A 58 76.708 61.803 39.669 1.00 34.48 N
HETATM 1271 CM1 1MA A 58 77.649 61.222 40.626 1.00 31.43 C
HETATM 1272 C2 1MA A 58 76.527 61.216 38.479 1.00 28.43 C
HETATM 1273 N3 1MA A 58 75.793 61.624 37.453 1.00 31.67 N
HETATM 1274 C4 1MA A 58 75.142 62.771 37.747 1.00 33.02 C
ATOM 1275 P U A 59 72.617 61.530 31.733 1.00 41.00 P
ATOM 1276 O1P U A 59 73.971 61.410 31.109 1.00 33.02 O
ATOM 1277 O2P U A 59 71.557 62.222 31.005 1.00 41.76 O
ATOM 1278 O5* U A 59 72.130 60.048 31.994 1.00 39.14 O
ATOM 1279 C5* U A 59 70.719 59.794 32.346 1.00 35.32 C
ATOM 1280 C4* U A 59 70.618 58.472 33.026 1.00 29.87 C
ATOM 1281 O4* U A 59 71.242 57.502 32.161 1.00 30.33 O
ATOM 1282 C3* U A 59 71.352 58.357 34.366 1.00 30.46 C
ATOM 1283 O3* U A 59 70.546 58.855 35.497 1.00 31.17 O
ATOM 1284 C2* U A 59 71.629 56.872 34.435 1.00 34.51 C
ATOM 1285 O2* U A 59 70.529 56.200 35.034 1.00 33.82 O
ATOM 1286 C1* U A 59 71.808 56.483 32.934 1.00 34.05 C
ATOM 1287 N1 U A 59 73.191 56.244 32.453 1.00 30.28 N
ATOM 1288 C2 U A 59 73.828 55.055 32.883 1.00 33.87 C
ATOM 1289 O2 U A 59 73.232 54.201 33.510 1.00 40.51 O
ATOM 1290 N3 U A 59 75.160 54.920 32.534 1.00 31.37 N
ATOM 1291 C4 U A 59 75.886 55.811 31.767 1.00 33.85 C
ATOM 1292 O4 U A 59 76.986 55.468 31.336 1.00 34.46 O
ATOM 1293 C5 U A 59 75.128 57.004 31.315 1.00 30.62 C
ATOM 1294 C6 U A 59 73.842 57.148 31.666 1.00 24.94 C
ATOM 1295 P C A 60 71.267 59.539 36.803 1.00 33.56 P
ATOM 1296 O1P C A 60 70.297 59.837 37.820 1.00 32.77 O
ATOM 1297 O2P C A 60 72.180 60.638 36.294 1.00 34.80 O
ATOM 1298 O5* C A 60 72.351 58.459 37.303 1.00 29.47 O
ATOM 1299 C5* C A 60 71.983 57.223 37.962 1.00 31.76 C
ATOM 1300 C4* C A 60 73.252 56.436 38.285 1.00 32.79 C
ATOM 1301 O4* C A 60 74.024 56.360 37.069 1.00 34.84 O
ATOM 1302 C3* C A 60 74.192 57.080 39.322 1.00 35.07 C
ATOM 1303 O3* C A 60 74.832 56.043 40.028 1.00 38.94 O
ATOM 1304 C2* C A 60 75.220 57.789 38.455 1.00 34.97 C
ATOM 1305 O2* C A 60 76.489 58.039 39.019 1.00 36.28 O
ATOM 1306 C1* C A 60 75.336 56.786 37.306 1.00 32.64 C
ATOM 1307 N1 C A 60 75.849 57.370 36.090 1.00 32.74 N
ATOM 1308 C2 C A 60 76.958 56.775 35.475 1.00 33.30 C
ATOM 1309 O2 C A 60 77.484 55.783 36.004 1.00 37.02 O
ATOM 1310 N3 C A 60 77.445 57.308 34.368 1.00 27.75 N
ATOM 1311 C4 C A 60 76.919 58.410 33.866 1.00 31.44 C
ATOM 1312 N4 C A 60 77.491 58.943 32.854 1.00 31.16 N
ATOM 1313 C5 C A 60 75.767 59.040 34.441 1.00 31.34 C
ATOM 1314 C6 C A 60 75.274 58.489 35.549 1.00 34.59 C
ATOM 1315 P C A 61 74.243 55.584 41.447 1.00 42.61 P
ATOM 1316 O1P C A 61 75.151 54.490 41.830 1.00 44.00 O
ATOM 1317 O2P C A 61 72.781 55.398 41.440 1.00 37.71 O
ATOM 1318 O5* C A 61 74.477 56.853 42.390 1.00 39.76 O
ATOM 1319 C5* C A 61 75.717 57.059 43.037 1.00 43.07 C
ATOM 1320 C4* C A 61 75.643 58.316 43.840 1.00 39.59 C
ATOM 1321 O4* C A 61 75.807 59.456 42.959 1.00 37.14 O
ATOM 1322 C3* C A 61 74.297 58.531 44.524 1.00 38.59 C
ATOM 1323 O3* C A 61 74.209 57.799 45.784 1.00 39.28 O
ATOM 1324 C2* C A 61 74.292 60.040 44.702 1.00 37.97 C
ATOM 1325 O2* C A 61 75.174 60.397 45.747 1.00 38.59 O
ATOM 1326 C1* C A 61 74.974 60.515 43.421 1.00 36.12 C
ATOM 1327 N1 C A 61 74.069 60.960 42.325 1.00 33.98 N
ATOM 1328 C2 C A 61 73.361 62.180 42.471 1.00 33.04 C
ATOM 1329 O2 C A 61 73.490 62.839 43.524 1.00 35.58 O
ATOM 1330 N3 C A 61 72.551 62.600 41.455 1.00 35.45 N
ATOM 1331 C4 C A 61 72.421 61.838 40.349 1.00 35.34 C
ATOM 1332 N4 C A 61 71.550 62.237 39.373 1.00 32.83 N
ATOM 1333 C5 C A 61 73.147 60.623 40.187 1.00 35.42 C
ATOM 1334 C6 C A 61 73.938 60.221 41.188 1.00 31.03 C
ATOM 1335 P A A 62 72.777 57.319 46.334 1.00 42.33 P
ATOM 1336 O1P A A 62 73.023 56.390 47.455 1.00 41.97 O
ATOM 1337 O2P A A 62 71.960 56.820 45.161 1.00 42.66 O
ATOM 1338 O5* A A 62 72.104 58.670 46.874 1.00 43.04 O
ATOM 1339 C5* A A 62 72.719 59.460 47.936 1.00 39.06 C
ATOM 1340 C4* A A 62 71.882 60.684 48.244 1.00 39.69 C
ATOM 1341 O4* A A 62 71.968 61.660 47.165 1.00 39.39 O
ATOM 1342 C3* A A 62 70.391 60.442 48.405 1.00 40.80 C
ATOM 1343 O3* A A 62 70.103 59.945 49.700 1.00 43.31 O
ATOM 1344 C2* A A 62 69.808 61.827 48.120 1.00 41.10 C
ATOM 1345 O2* A A 62 70.016 62.793 49.130 1.00 43.43 O
ATOM 1346 C1* A A 62 70.711 62.312 46.995 1.00 38.85 C
ATOM 1347 N9 A A 62 70.182 62.021 45.654 1.00 32.58 N
ATOM 1348 C8 A A 62 70.560 61.004 44.827 1.00 33.66 C
ATOM 1349 N7 A A 62 70.002 61.038 43.650 1.00 32.82 N
ATOM 1350 C5 A A 62 69.158 62.140 43.707 1.00 31.78 C
ATOM 1351 C6 A A 62 68.304 62.715 42.759 1.00 29.57 C
ATOM 1352 N6 A A 62 68.170 62.255 41.478 1.00 29.13 N
ATOM 1353 N1 A A 62 67.590 63.788 43.135 1.00 31.96 N
ATOM 1354 C2 A A 62 67.754 64.268 44.373 1.00 33.29 C
ATOM 1355 N3 A A 62 68.548 63.835 45.349 1.00 32.89 N
ATOM 1356 C4 A A 62 69.239 62.747 44.945 1.00 35.51 C
ATOM 1357 P C A 63 68.913 58.881 49.918 1.00 43.35 P
ATOM 1358 O1P C A 63 69.009 58.532 51.351 1.00 49.74 O
ATOM 1359 O2P C A 63 68.970 57.790 48.905 1.00 46.77 O
ATOM 1360 O5* C A 63 67.599 59.762 49.769 1.00 45.50 O
ATOM 1361 C5* C A 63 67.371 60.836 50.703 1.00 44.28 C
ATOM 1362 C4* C A 63 66.263 61.750 50.244 1.00 44.77 C
ATOM 1363 O4* C A 63 66.669 62.512 49.079 1.00 41.48 O
ATOM 1364 C3* C A 63 64.958 61.089 49.850 1.00 46.16 C
ATOM 1365 O3* C A 63 64.160 60.771 51.005 1.00 51.01 O
ATOM 1366 C2* C A 63 64.325 62.154 48.972 1.00 43.55 C
ATOM 1367 O2* C A 63 63.764 63.209 49.763 1.00 48.54 O
ATOM 1368 C1* C A 63 65.541 62.713 48.233 1.00 39.95 C
ATOM 1369 N1 C A 63 65.788 62.041 46.918 1.00 35.72 N
ATOM 1370 C2 C A 63 65.155 62.553 45.793 1.00 32.68 C
ATOM 1371 O2 C A 63 64.440 63.541 45.950 1.00 36.07 O
ATOM 1372 N3 C A 63 65.328 61.946 44.571 1.00 34.10 N
ATOM 1373 C4 C A 63 66.113 60.839 44.485 1.00 31.53 C
ATOM 1374 N4 C A 63 66.253 60.229 43.282 1.00 34.07 N
ATOM 1375 C5 C A 63 66.783 60.308 45.617 1.00 35.81 C
ATOM 1376 C6 C A 63 66.603 60.941 46.809 1.00 36.37 C
ATOM 1377 P A A 64 63.129 59.542 50.943 1.00 57.75 P
ATOM 1378 O1P A A 64 62.528 59.402 52.300 1.00 58.22 O
ATOM 1379 O2P A A 64 63.807 58.359 50.338 1.00 54.03 O
ATOM 1380 O5* A A 64 62.008 60.100 49.971 1.00 54.48 O
ATOM 1381 C5* A A 64 61.194 61.198 50.398 1.00 56.10 C
ATOM 1382 C4* A A 64 60.204 61.569 49.339 1.00 54.58 C
ATOM 1383 O4* A A 64 60.917 62.255 48.276 1.00 53.92 O
ATOM 1384 C3* A A 64 59.459 60.433 48.632 1.00 56.48 C
ATOM 1385 O3* A A 64 58.374 59.780 49.384 1.00 56.71 O
ATOM 1386 C2* A A 64 59.036 61.152 47.349 1.00 53.00 C
ATOM 1387 O2* A A 64 57.994 62.076 47.565 1.00 56.42 O
ATOM 1388 C1* A A 64 60.283 61.983 47.026 1.00 51.87 C
ATOM 1389 N9 A A 64 61.176 61.174 46.178 1.00 45.48 N
ATOM 1390 C8 A A 64 62.220 60.374 46.567 1.00 42.54 C
ATOM 1391 N7 A A 64 62.766 59.702 45.585 1.00 42.30 N
ATOM 1392 C5 A A 64 62.051 60.122 44.466 1.00 40.22 C
ATOM 1393 C6 A A 64 62.152 59.783 43.119 1.00 36.50 C
ATOM 1394 N6 A A 64 63.082 58.963 42.657 1.00 34.41 N
ATOM 1395 N1 A A 64 61.261 60.326 42.262 1.00 37.69 N
ATOM 1396 C2 A A 64 60.346 61.178 42.745 1.00 36.62 C
ATOM 1397 N3 A A 64 60.169 61.600 43.991 1.00 36.71 N
ATOM 1398 C4 A A 64 61.070 61.018 44.815 1.00 39.74 C
ATOM 1399 P G A 65 58.068 58.186 49.152 1.00 58.45 P
ATOM 1400 O1P G A 65 57.104 57.682 50.155 1.00 62.97 O
ATOM 1401 O2P G A 65 59.328 57.423 48.941 1.00 61.74 O
ATOM 1402 O5* G A 65 57.302 58.169 47.766 1.00 57.06 O
ATOM 1403 C5* G A 65 56.297 59.121 47.518 1.00 49.45 C
ATOM 1404 C4* G A 65 55.988 59.170 46.060 1.00 45.91 C
ATOM 1405 O4* G A 65 57.113 59.757 45.358 1.00 43.81 O
ATOM 1406 C3* G A 65 55.711 57.868 45.316 1.00 45.00 C
ATOM 1407 O3* G A 65 54.366 57.370 45.509 1.00 47.48 O
ATOM 1408 C2* G A 65 55.920 58.322 43.886 1.00 41.79 C
ATOM 1409 O2* G A 65 54.776 59.084 43.491 1.00 39.93 O
ATOM 1410 C1* G A 65 57.142 59.262 44.032 1.00 42.23 C
ATOM 1411 N9 G A 65 58.373 58.489 43.875 1.00 39.23 N
ATOM 1412 C8 G A 65 59.245 58.086 44.861 1.00 37.65 C
ATOM 1413 N7 G A 65 60.189 57.305 44.420 1.00 35.71 N
ATOM 1414 C5 G A 65 59.942 57.213 43.050 1.00 38.74 C
ATOM 1415 C6 G A 65 60.647 56.509 42.009 1.00 36.19 C
ATOM 1416 O6 G A 65 61.690 55.776 42.101 1.00 38.10 O
ATOM 1417 N1 G A 65 60.040 56.710 40.766 1.00 37.09 N
ATOM 1418 C2 G A 65 58.920 57.482 40.550 1.00 37.20 C
ATOM 1419 N2 G A 65 58.460 57.534 39.290 1.00 36.90 N
ATOM 1420 N3 G A 65 58.288 58.152 41.498 1.00 33.44 N
ATOM 1421 C4 G A 65 58.838 57.965 42.703 1.00 36.71 C
ATOM 1422 P A A 66 54.074 55.782 45.410 1.00 48.51 P
ATOM 1423 O1P A A 66 52.701 55.474 45.862 1.00 50.89 O
ATOM 1424 O2P A A 66 55.214 55.033 46.008 1.00 48.73 O
ATOM 1425 O5* A A 66 54.173 55.469 43.863 1.00 45.90 O
ATOM 1426 C5* A A 66 53.339 56.143 42.940 1.00 46.19 C
ATOM 1427 C4* A A 66 53.671 55.677 41.542 1.00 46.27 C
ATOM 1428 O4* A A 66 55.037 56.058 41.206 1.00 44.63 O
ATOM 1429 C3* A A 66 53.666 54.171 41.354 1.00 44.76 C
ATOM 1430 O3* A A 66 52.326 53.680 41.155 1.00 46.57 O
ATOM 1431 C2* A A 66 54.535 54.017 40.112 1.00 42.31 C
ATOM 1432 O2* A A 66 53.773 54.358 38.980 1.00 44.56 O
ATOM 1433 C1* A A 66 55.595 55.117 40.311 1.00 40.50 C
ATOM 1434 N9 A A 66 56.838 54.618 40.902 1.00 38.52 N
ATOM 1435 C8 A A 66 57.216 54.722 42.216 1.00 37.83 C
ATOM 1436 N7 A A 66 58.365 54.141 42.488 1.00 38.64 N
ATOM 1437 C5 A A 66 58.784 53.639 41.260 1.00 37.61 C
ATOM 1438 C6 A A 66 59.943 52.898 40.877 1.00 36.94 C
ATOM 1439 N6 A A 66 60.924 52.566 41.728 1.00 34.85 N
ATOM 1440 N1 A A 66 60.042 52.511 39.596 1.00 36.33 N
ATOM 1441 C2 A A 66 59.056 52.850 38.752 1.00 37.97 C
ATOM 1442 N3 A A 66 57.922 53.552 38.986 1.00 38.42 N
ATOM 1443 C4 A A 66 57.850 53.916 40.276 1.00 37.28 C
ATOM 1444 P A A 67 51.950 52.180 41.620 1.00 46.84 P
ATOM 1445 O1P A A 67 50.472 52.017 41.466 1.00 50.38 O
ATOM 1446 O2P A A 67 52.569 51.904 42.938 1.00 43.27 O
ATOM 1447 O5* A A 67 52.644 51.252 40.553 1.00 44.33 O
ATOM 1448 C5* A A 67 52.276 51.321 39.167 1.00 45.20 C
ATOM 1449 C4* A A 67 53.319 50.645 38.320 1.00 43.61 C
ATOM 1450 O4* A A 67 54.601 51.353 38.446 1.00 42.36 O
ATOM 1451 C3* A A 67 53.636 49.208 38.725 1.00 41.30 C
ATOM 1452 O3* A A 67 52.690 48.291 38.163 1.00 46.52 O
ATOM 1453 C2* A A 67 55.053 49.024 38.157 1.00 42.21 C
ATOM 1454 O2* A A 67 55.039 48.819 36.759 1.00 41.99 O
ATOM 1455 C1* A A 67 55.669 50.417 38.391 1.00 41.64 C
ATOM 1456 N9 A A 67 56.441 50.432 39.643 1.00 39.97 N
ATOM 1457 C8 A A 67 56.129 50.866 40.893 1.00 40.04 C
ATOM 1458 N7 A A 67 57.062 50.618 41.788 1.00 37.46 N
ATOM 1459 C5 A A 67 58.077 50.015 41.060 1.00 37.07 C
ATOM 1460 C6 A A 67 59.348 49.481 41.435 1.00 37.10 C
ATOM 1461 N6 A A 67 59.864 49.515 42.677 1.00 37.48 N
ATOM 1462 N1 A A 67 60.076 48.895 40.483 1.00 37.12 N
ATOM 1463 C2 A A 67 59.577 48.842 39.230 1.00 42.46 C
ATOM 1464 N3 A A 67 58.415 49.313 38.758 1.00 39.78 N
ATOM 1465 C4 A A 67 57.712 49.894 39.743 1.00 37.61 C
ATOM 1466 P U A 68 52.371 46.894 38.917 1.00 42.45 P
ATOM 1467 O1P U A 68 51.176 46.256 38.300 1.00 49.18 O
ATOM 1468 O2P U A 68 52.399 47.127 40.381 1.00 41.13 O
ATOM 1469 O5* U A 68 53.625 45.986 38.529 1.00 44.81 O
ATOM 1470 C5* U A 68 53.889 45.709 37.150 1.00 43.19 C
ATOM 1471 C4* U A 68 55.168 44.940 37.012 1.00 43.76 C
ATOM 1472 O4* U A 68 56.296 45.792 37.351 1.00 42.13 O
ATOM 1473 C3* U A 68 55.315 43.758 37.955 1.00 41.59 C
ATOM 1474 O3* U A 68 54.653 42.598 37.490 1.00 42.60 O
ATOM 1475 C2* U A 68 56.825 43.573 37.996 1.00 38.55 C
ATOM 1476 O2* U A 68 57.255 43.012 36.776 1.00 36.20 O
ATOM 1477 C1* U A 68 57.286 45.028 38.018 1.00 40.75 C
ATOM 1478 N1 U A 68 57.451 45.543 39.385 1.00 40.94 N
ATOM 1479 C2 U A 68 58.636 45.212 40.015 1.00 38.74 C
ATOM 1480 O2 U A 68 59.470 44.485 39.490 1.00 38.70 O
ATOM 1481 N3 U A 68 58.804 45.747 41.261 1.00 37.87 N
ATOM 1482 C4 U A 68 57.924 46.564 41.939 1.00 41.13 C
ATOM 1483 O4 U A 68 58.175 46.857 43.097 1.00 38.53 O
ATOM 1484 C5 U A 68 56.693 46.846 41.241 1.00 42.38 C
ATOM 1485 C6 U A 68 56.502 46.326 40.013 1.00 41.40 C
ATOM 1486 P U A 69 54.151 41.542 38.559 1.00 39.53 P
ATOM 1487 O1P U A 69 53.485 40.463 37.781 1.00 45.74 O
ATOM 1488 O2P U A 69 53.441 42.272 39.591 1.00 36.81 O
ATOM 1489 O5* U A 69 55.409 40.901 39.291 1.00 37.79 O
ATOM 1490 C5* U A 69 56.364 40.117 38.558 1.00 37.34 C
ATOM 1491 C4* U A 69 57.582 39.880 39.400 1.00 37.79 C
ATOM 1492 O4* U A 69 58.241 41.150 39.731 1.00 36.27 O
ATOM 1493 C3* U A 69 57.300 39.247 40.746 1.00 37.91 C
ATOM 1494 O3* U A 69 57.092 37.832 40.625 1.00 37.28 O
ATOM 1495 C2* U A 69 58.553 39.630 41.533 1.00 35.61 C
ATOM 1496 O2* U A 69 59.645 38.794 41.156 1.00 34.07 O
ATOM 1497 C1* U A 69 58.796 41.050 41.019 1.00 34.46 C
ATOM 1498 N1 U A 69 58.186 42.082 41.876 1.00 33.94 N
ATOM 1499 C2 U A 69 58.871 42.410 43.052 1.00 34.89 C
ATOM 1500 O2 U A 69 59.947 41.899 43.373 1.00 36.74 O
ATOM 1501 N3 U A 69 58.261 43.334 43.836 1.00 35.12 N
ATOM 1502 C4 U A 69 57.071 43.985 43.603 1.00 37.89 C
ATOM 1503 O4 U A 69 56.665 44.808 44.432 1.00 37.56 O
ATOM 1504 C5 U A 69 56.419 43.627 42.355 1.00 38.56 C
ATOM 1505 C6 U A 69 56.991 42.702 41.549 1.00 35.52 C
ATOM 1506 P C A 70 56.232 37.065 41.726 1.00 41.13 P
ATOM 1507 O1P C A 70 55.792 35.757 41.056 1.00 42.55 O
ATOM 1508 O2P C A 70 55.233 37.976 42.338 1.00 39.43 O
ATOM 1509 O5* C A 70 57.233 36.693 42.902 1.00 36.56 O
ATOM 1510 C5* C A 70 58.371 35.817 42.663 1.00 39.97 C
ATOM 1511 C4* C A 70 59.348 35.925 43.805 1.00 42.01 C
ATOM 1512 O4* C A 70 59.923 37.260 43.909 1.00 41.84 O
ATOM 1513 C3* C A 70 58.743 35.702 45.172 1.00 41.90 C
ATOM 1514 O3* C A 70 58.575 34.329 45.408 1.00 45.51 O
ATOM 1515 C2* C A 70 59.765 36.355 46.087 1.00 41.68 C
ATOM 1516 O2* C A 70 60.879 35.486 46.166 1.00 42.55 O
ATOM 1517 C1* C A 70 60.163 37.591 45.267 1.00 36.50 C
ATOM 1518 N1 C A 70 59.360 38.780 45.597 1.00 39.49 N
ATOM 1519 C2 C A 70 59.805 39.676 46.617 1.00 39.47 C
ATOM 1520 O2 C A 70 60.879 39.451 47.194 1.00 41.25 O
ATOM 1521 N3 C A 70 59.047 40.767 46.935 1.00 37.96 N
ATOM 1522 C4 C A 70 57.901 40.982 46.285 1.00 40.08 C
ATOM 1523 N4 C A 70 57.169 42.038 46.653 1.00 40.99 N
ATOM 1524 C5 C A 70 57.445 40.109 45.229 1.00 39.06 C
ATOM 1525 C6 C A 70 58.187 39.026 44.934 1.00 35.59 C
ATOM 1526 P G A 71 57.514 33.856 46.509 1.00 51.79 P
ATOM 1527 O1P G A 71 57.674 32.367 46.524 1.00 50.10 O
ATOM 1528 O2P G A 71 56.203 34.485 46.254 1.00 46.01 O
ATOM 1529 O5* G A 71 58.085 34.416 47.884 1.00 49.09 O
ATOM 1530 C5* G A 71 59.164 33.703 48.505 1.00 56.68 C
ATOM 1531 C4* G A 71 59.688 34.434 49.701 1.00 58.95 C
ATOM 1532 O4* G A 71 60.125 35.757 49.305 1.00 57.94 O
ATOM 1533 C3* G A 71 58.716 34.693 50.839 1.00 63.78 C
ATOM 1534 O3* G A 71 58.514 33.580 51.699 1.00 70.59 O
ATOM 1535 C2* G A 71 59.392 35.845 51.559 1.00 63.20 C
ATOM 1536 O2* G A 71 60.455 35.370 52.375 1.00 64.19 O
ATOM 1537 C1* G A 71 59.915 36.661 50.374 1.00 59.19 C
ATOM 1538 N9 G A 71 58.897 37.620 49.946 1.00 58.54 N
ATOM 1539 C8 G A 71 58.004 37.488 48.897 1.00 56.09 C
ATOM 1540 N7 G A 71 57.207 38.519 48.769 1.00 54.09 N
ATOM 1541 C5 G A 71 57.597 39.383 49.788 1.00 53.61 C
ATOM 1542 C6 G A 71 57.114 40.666 50.148 1.00 52.69 C
ATOM 1543 O6 G A 71 56.184 41.315 49.653 1.00 52.69 O
ATOM 1544 N1 G A 71 57.827 41.196 51.223 1.00 52.34 N
ATOM 1545 C2 G A 71 58.844 40.566 51.884 1.00 53.05 C
ATOM 1546 N2 G A 71 59.399 41.251 52.885 1.00 55.23 N
ATOM 1547 N3 G A 71 59.291 39.360 51.585 1.00 54.72 N
ATOM 1548 C4 G A 71 58.636 38.835 50.526 1.00 55.38 C
ATOM 1549 P C A 72 57.094 33.402 52.426 1.00 73.67 P
ATOM 1550 O1P C A 72 57.177 32.132 53.187 1.00 76.79 O
ATOM 1551 O2P C A 72 56.011 33.588 51.427 1.00 75.72 O
ATOM 1552 O5* C A 72 57.017 34.599 53.469 1.00 74.00 O
ATOM 1553 C5* C A 72 57.817 34.563 54.660 1.00 75.03 C
ATOM 1554 C4* C A 72 57.653 35.834 55.450 1.00 74.38 C
ATOM 1555 O4* C A 72 57.964 36.953 54.582 1.00 74.64 O
ATOM 1556 C3* C A 72 56.261 36.155 55.979 1.00 76.09 C
ATOM 1557 O3* C A 72 55.932 35.502 57.209 1.00 78.85 O
ATOM 1558 C2* C A 72 56.302 37.671 56.139 1.00 74.55 C
ATOM 1559 O2* C A 72 56.872 38.146 57.338 1.00 75.06 O
ATOM 1560 C1* C A 72 57.184 38.082 54.963 1.00 72.55 C
ATOM 1561 N1 C A 72 56.343 38.502 53.829 1.00 68.80 N
ATOM 1562 C2 C A 72 55.796 39.801 53.838 1.00 66.61 C
ATOM 1563 O2 C A 72 56.063 40.568 54.791 1.00 63.14 O
ATOM 1564 N3 C A 72 54.993 40.180 52.815 1.00 64.67 N
ATOM 1565 C4 C A 72 54.734 39.331 51.818 1.00 64.57 C
ATOM 1566 N4 C A 72 53.935 39.749 50.832 1.00 63.54 N
ATOM 1567 C5 C A 72 55.283 38.015 51.780 1.00 64.77 C
ATOM 1568 C6 C A 72 56.077 37.647 52.792 1.00 67.37 C
ATOM 1569 P A A 73 54.383 35.178 57.550 1.00 79.81 P
ATOM 1570 O1P A A 73 54.333 34.483 58.872 1.00 81.24 O
ATOM 1571 O2P A A 73 53.785 34.517 56.355 1.00 79.38 O
ATOM 1572 O5* A A 73 53.739 36.617 57.766 1.00 77.14 O
ATOM 1573 C5* A A 73 54.204 37.443 58.849 1.00 75.83 C
ATOM 1574 C4* A A 73 53.508 38.772 58.837 1.00 74.32 C
ATOM 1575 O4* A A 73 53.912 39.514 57.654 1.00 72.81 O
ATOM 1576 C3* A A 73 51.987 38.727 58.750 1.00 73.77 C
ATOM 1577 O3* A A 73 51.332 38.492 59.999 1.00 76.93 O
ATOM 1578 C2* A A 73 51.667 40.101 58.178 1.00 71.67 C
ATOM 1579 O2* A A 73 51.704 41.127 59.141 1.00 70.42 O
ATOM 1580 C1* A A 73 52.823 40.304 57.196 1.00 69.17 C
ATOM 1581 N9 A A 73 52.434 39.853 55.856 1.00 64.04 N
ATOM 1582 C8 A A 73 52.792 38.695 55.206 1.00 60.25 C
ATOM 1583 N7 A A 73 52.256 38.571 54.016 1.00 58.41 N
ATOM 1584 C5 A A 73 51.493 39.729 53.869 1.00 57.85 C
ATOM 1585 C6 A A 73 50.683 40.203 52.812 1.00 56.02 C
ATOM 1586 N6 A A 73 50.516 39.541 51.654 1.00 55.49 N
ATOM 1587 N1 A A 73 50.052 41.388 52.979 1.00 53.67 N
ATOM 1588 C2 A A 73 50.233 42.052 54.136 1.00 55.48 C
ATOM 1589 N3 A A 73 50.975 41.713 55.198 1.00 59.62 N
ATOM 1590 C4 A A 73 51.589 40.525 54.993 1.00 59.80 C
ATOM 1591 P C A 74 49.934 37.680 60.030 1.00 78.48 P
ATOM 1592 O1P C A 74 49.485 37.580 61.446 1.00 80.11 O
ATOM 1593 O2P C A 74 50.090 36.441 59.222 1.00 77.06 O
ATOM 1594 O5* C A 74 48.914 38.636 59.275 1.00 77.54 O
ATOM 1595 C5* C A 74 48.529 39.898 59.843 1.00 79.25 C
ATOM 1596 C4* C A 74 47.463 40.541 58.985 1.00 80.49 C
ATOM 1597 O4* C A 74 48.030 40.879 57.690 1.00 79.75 O
ATOM 1598 C3* C A 74 46.291 39.627 58.660 1.00 81.62 C
ATOM 1599 O3* C A 74 45.292 39.640 59.669 1.00 82.15 O
ATOM 1600 C2* C A 74 45.778 40.187 57.340 1.00 80.42 C
ATOM 1601 O2* C A 74 44.932 41.302 57.547 1.00 82.05 O
ATOM 1602 C1* C A 74 47.080 40.621 56.662 1.00 79.08 C
ATOM 1603 N1 C A 74 47.631 39.588 55.748 1.00 76.36 N
ATOM 1604 C2 C A 74 47.204 39.557 54.400 1.00 74.77 C
ATOM 1605 O2 C A 74 46.399 40.404 54.002 1.00 75.12 O
ATOM 1606 N3 C A 74 47.694 38.606 53.571 1.00 73.87 N
ATOM 1607 C4 C A 74 48.588 37.723 54.024 1.00 73.03 C
ATOM 1608 N4 C A 74 49.055 36.813 53.167 1.00 72.80 N
ATOM 1609 C5 C A 74 49.046 37.734 55.376 1.00 73.50 C
ATOM 1610 C6 C A 74 48.543 38.671 56.196 1.00 74.97 C
ATOM 1611 P C A 75 44.492 38.295 59.994 1.00 83.00 P
ATOM 1612 O1P C A 75 43.435 38.637 60.974 1.00 84.71 O
ATOM 1613 O2P C A 75 45.478 37.229 60.303 1.00 81.99 O
ATOM 1614 O5* C A 75 43.802 37.890 58.618 1.00 84.55 O
ATOM 1615 C5* C A 75 42.993 38.825 57.874 1.00 85.33 C
ATOM 1616 C4* C A 75 42.564 38.194 56.568 1.00 86.51 C
ATOM 1617 O4* C A 75 43.667 38.149 55.630 1.00 84.68 O
ATOM 1618 C3* C A 75 42.136 36.747 56.733 1.00 88.27 C
ATOM 1619 O3* C A 75 40.778 36.695 57.104 1.00 95.04 O
ATOM 1620 C2* C A 75 42.402 36.136 55.366 1.00 85.58 C
ATOM 1621 O2* C A 75 41.337 36.317 54.459 1.00 84.94 O
ATOM 1622 C1* C A 75 43.631 36.926 54.915 1.00 82.57 C
ATOM 1623 N1 C A 75 44.883 36.201 55.170 1.00 78.44 N
ATOM 1624 C2 C A 75 45.365 35.327 54.193 1.00 75.98 C
ATOM 1625 O2 C A 75 44.719 35.169 53.149 1.00 74.80 O
ATOM 1626 N3 C A 75 46.512 34.673 54.406 1.00 74.76 N
ATOM 1627 C4 C A 75 47.176 34.846 55.543 1.00 75.41 C
ATOM 1628 N4 C A 75 48.311 34.161 55.705 1.00 75.90 N
ATOM 1629 C5 C A 75 46.709 35.719 56.563 1.00 75.64 C
ATOM 1630 C6 C A 75 45.570 36.373 56.337 1.00 77.27 C
ATOM 1631 P A A 76 40.334 35.770 58.330 1.00 99.54 P
ATOM 1632 O1P A A 76 41.267 36.020 59.481 1.00 99.74 O
ATOM 1633 O2P A A 76 40.226 34.405 57.758 1.00 99.88 O
ATOM 1634 O5* A A 76 38.872 36.304 58.697 1.00100.19 O
ATOM 1635 C5* A A 76 38.666 37.596 59.323 1.00100.18 C
ATOM 1636 C4* A A 76 37.607 38.379 58.569 1.00100.19 C
ATOM 1637 O4* A A 76 36.479 37.500 58.278 1.00100.19 O
ATOM 1638 C3* A A 76 37.025 39.585 59.305 1.00100.19 C
ATOM 1639 O3* A A 76 36.428 40.400 58.274 1.00100.19 O
ATOM 1640 C2* A A 76 35.785 38.991 59.981 1.00100.19 C
ATOM 1641 O2* A A 76 34.780 39.945 60.283 1.00100.19 O
ATOM 1642 C1* A A 76 35.314 37.959 58.950 1.00100.19 C
ATOM 1643 N9 A A 76 34.598 36.785 59.488 1.00100.19 N
ATOM 1644 C8 A A 76 34.399 35.586 58.829 1.00100.19 C
ATOM 1645 N7 A A 76 33.715 34.701 59.522 1.00100.19 N
ATOM 1646 C5 A A 76 33.440 35.352 60.719 1.00100.19 C
ATOM 1647 C6 A A 76 32.739 34.948 61.881 1.00100.19 C
ATOM 1648 N6 A A 76 32.161 33.747 62.024 1.00100.19 N
ATOM 1649 N1 A A 76 32.652 35.835 62.902 1.00100.19 N
ATOM 1650 C2 A A 76 33.230 37.042 62.758 1.00100.19 C
ATOM 1651 N3 A A 76 33.911 37.538 61.720 1.00100.19 N
ATOM 1652 C4 A A 76 33.982 36.637 60.719 1.00100.19 C
TER 1653 A A 76
HETATM 1654 MG MG 590 70.566 35.530 1.665 1.00 65.44 MG
HETATM 1655 MN O4M 530 80.714 57.068 31.271 1.00 34.23 MN
HETATM 1656 O4 O4M 530 80.684 55.382 30.181 1.00 37.94 O
HETATM 1657 O3 O4M 530 81.503 58.060 29.728 1.00 34.54 O
HETATM 1658 O2 O4M 530 82.554 56.601 31.916 1.00 40.13 O
HETATM 1659 O1 O4M 530 78.882 57.524 30.607 1.00 37.65 O
HETATM 1660 MG MO5 510 57.346 47.575 47.279 1.00 62.77 MG
HETATM 1661 O1 MO5 510 59.121 46.716 46.939 1.00 61.12 O
HETATM 1662 O2 MO5 510 55.569 48.426 47.617 1.00 62.44 O
HETATM 1663 O3 MO5 510 57.139 47.928 45.318 1.00 62.18 O
HETATM 1664 O4 MO5 510 57.549 47.218 49.240 1.00 63.71 O
HETATM 1665 O5 MO5 510 56.451 45.796 47.050 1.00 64.69 O
HETATM 1666 MN MN5 520 49.923 44.427 50.131 1.00 89.20 MN
HETATM 1667 O1 MN5 520 50.566 42.548 49.894 1.00 90.06 O
HETATM 1668 O2 MN5 520 49.279 46.306 50.367 1.00 88.19 O
HETATM 1669 O3 MN5 520 48.828 43.854 51.702 1.00 89.34 O
HETATM 1670 O4 MN5 520 51.020 45.000 48.559 1.00 89.35 O
HETATM 1671 O5 MN5 520 48.379 44.049 48.917 1.00 88.93 O
HETATM 1672 MG MO3 540 77.110 64.307 25.357 1.00 40.08 MG
HETATM 1673 O1 MO3 540 75.884 64.949 23.911 1.00 42.31 O
HETATM 1674 O2 MO3 540 75.591 63.324 26.209 1.00 42.77 O
HETATM 1675 O3 MO3 540 78.628 65.295 24.504 1.00 43.67 O
HETATM 1676 MG MO6 560 62.649 46.629 27.595 1.00 47.02 MG
HETATM 1677 O1 MO6 560 63.354 44.755 27.511 1.00 43.55 O
HETATM 1678 O2 MO6 560 61.942 48.502 27.674 1.00 41.87 O
HETATM 1679 O3 MO6 560 62.352 46.432 29.566 1.00 44.71 O
HETATM 1680 O4 MO6 560 62.949 46.821 25.628 1.00 43.68 O
HETATM 1681 O5 MO6 560 64.498 47.320 27.946 1.00 41.71 O
HETATM 1682 O6 MO6 560 60.803 45.945 27.247 1.00 46.26 O
HETATM 1683 MG MO6 570 73.331 43.321 11.207 1.00 50.39 MG
HETATM 1684 O1 MO6 570 72.795 42.398 9.514 1.00 50.20 O
HETATM 1685 O2 MO6 570 73.865 44.246 12.908 1.00 49.37 O
HETATM 1686 O3 MO6 570 74.746 41.940 11.519 1.00 51.45 O
HETATM 1687 O4 MO6 570 71.918 44.704 10.896 1.00 48.14 O
HETATM 1688 O5 MO6 570 72.020 42.211 12.224 1.00 47.02 O
HETATM 1689 O6 MO6 570 74.644 44.433 10.185 1.00 47.69 O
HETATM 1690 MG MO1 580 69.222 44.815 33.339 1.00 61.74 MG
HETATM 1691 O1 MO1 580 68.372 45.072 31.544 1.00 46.52 O
HETATM 1692 MN MN5 550 72.301 48.513 33.894 1.00 56.51 MN
HETATM 1693 O1 MN5 550 70.576 49.247 33.191 1.00 58.54 O
HETATM 1694 O2 MN5 550 74.024 47.784 34.605 1.00 58.71 O
HETATM 1695 O3 MN5 550 71.834 46.713 33.168 1.00 61.51 O
HETATM 1696 O4 MN5 550 72.774 50.321 34.622 1.00 60.62 O
HETATM 1697 O5 MN5 550 71.401 48.057 35.619 1.00 60.95 O
HETATM 1698 O HOH 101 65.235 47.736 24.306 1.00 29.97 O
HETATM 1699 O HOH 102 74.678 53.324 26.387 1.00 29.43 O
HETATM 1700 O HOH 103 79.647 66.543 30.502 1.00 36.21 O
HETATM 1701 O HOH 104 69.474 53.115 32.762 1.00 35.08 O
HETATM 1702 O HOH 105 77.803 59.348 29.070 1.00 34.91 O
HETATM 1703 O HOH 106 86.312 62.508 34.397 1.00 36.87 O
HETATM 1704 O HOH 107 69.798 47.380 19.420 1.00 35.43 O
HETATM 1705 O HOH 108 77.715 51.787 26.254 1.00 25.88 O
HETATM 1706 O HOH 109 66.697 54.043 19.991 1.00 38.52 O
HETATM 1707 O HOH 110 73.012 72.799 41.306 1.00 35.46 O
HETATM 1708 O HOH 111 84.966 51.999 36.727 1.00 48.17 O
HETATM 1709 O HOH 112 75.699 47.326 15.656 1.00 43.55 O
HETATM 1710 O HOH 113 61.911 39.313 42.834 1.00 38.72 O
HETATM 1711 O HOH 114 72.538 65.567 46.811 1.00 39.71 O
HETATM 1712 O HOH 115 64.957 57.362 35.588 1.00 36.28 O
HETATM 1713 O HOH 116 88.913 61.884 36.666 1.00 33.38 O
HETATM 1714 O HOH 117 77.430 47.049 24.346 1.00 38.25 O
HETATM 1715 O HOH 118 85.080 55.471 30.753 1.00 42.06 O
HETATM 1716 O HOH 119 73.126 42.774 26.088 1.00 39.89 O
HETATM 1717 O HOH 120 79.541 54.130 20.639 1.00 41.26 O
HETATM 1718 O HOH 121 75.971 56.472 28.176 1.00 40.47 O
HETATM 1719 O HOH 123 78.750 74.856 43.549 1.00 41.10 O
HETATM 1720 O HOH 124 59.778 66.139 42.613 1.00 45.92 O
HETATM 1721 O HOH 125 72.198 49.756 14.319 1.00 52.62 O
HETATM 1722 O HOH 126 68.821 65.008 47.959 1.00 45.12 O
HETATM 1723 O HOH 127 67.849 57.944 43.472 1.00 49.89 O
HETATM 1724 O HOH 128 67.631 51.090 33.685 1.00 39.79 O
HETATM 1725 O HOH 129 72.804 72.294 34.649 1.00 52.66 O
HETATM 1726 O HOH 130 71.861 49.100 17.322 1.00 38.23 O
HETATM 1727 O HOH 131 65.908 53.779 40.692 1.00 47.68 O
HETATM 1728 O HOH 132 54.150 42.092 45.268 1.00 43.73 O
HETATM 1729 O HOH 133 89.825 58.582 38.826 1.00 50.13 O
HETATM 1730 O HOH 134 84.722 60.865 36.177 1.00 45.21 O
HETATM 1731 O HOH 135 76.181 73.948 39.594 1.00 36.60 O
HETATM 1732 O HOH 136 77.944 64.645 31.617 1.00 50.38 O
HETATM 1733 O HOH 137 63.795 30.172 -8.994 1.00 51.48 O
HETATM 1734 O HOH 138 79.187 54.860 37.993 1.00 53.51 O
HETATM 1735 O HOH 139 65.438 43.393 28.966 1.00 49.20 O
HETATM 1736 O HOH 140 76.458 61.362 31.941 1.00 41.25 O
HETATM 1737 O HOH 141 65.955 45.704 31.155 1.00 37.31 O
HETATM 1738 O HOH 142 76.497 48.574 12.986 1.00 52.62 O
HETATM 1739 O HOH 143 77.696 63.153 34.024 1.00 41.50 O
HETATM 1740 O HOH 144 83.868 72.752 40.256 1.00 49.29 O
HETATM 1741 O HOH 145 83.766 59.152 28.946 1.00 39.50 O
HETATM 1742 O HOH 146 80.216 39.612 12.437 1.00 58.96 O
HETATM 1743 O HOH 147 74.386 47.570 12.387 1.00 53.73 O
HETATM 1744 O HOH 148 76.514 45.163 13.466 1.00 52.76 O
HETATM 1745 O HOH 149 63.032 41.158 41.088 1.00 48.34 O
HETATM 1746 O HOH 150 71.118 68.217 36.794 1.00 51.89 O
HETATM 1747 O HOH 152 81.091 65.399 26.812 1.00 44.48 O
HETATM 1748 O HOH 153 77.519 52.631 29.605 1.00 48.97 O
HETATM 1749 O HOH 155 59.968 42.360 37.108 1.00 49.01 O
HETATM 1750 O HOH 156 65.613 68.667 37.929 1.00 45.40 O
HETATM 1751 O HOH 157 56.060 63.049 38.179 1.00 49.08 O
HETATM 1752 O HOH 158 65.177 33.333 7.613 1.00 55.31 O
HETATM 1753 O HOH 159 75.172 67.087 29.927 1.00 54.05 O
HETATM 1754 O HOH 160 84.839 64.460 36.543 1.00 47.37 O
HETATM 1755 O HOH 161 84.226 60.935 26.655 1.00 51.90 O
HETATM 1756 O HOH 162 65.528 66.128 32.712 1.00 58.08 O
HETATM 1757 O HOH 163 54.801 39.353 47.303 1.00 50.47 O
HETATM 1758 O HOH 164 82.124 69.432 40.965 1.00 44.14 O
HETATM 1759 O HOH 166 76.820 63.025 29.658 1.00 45.12 O
HETATM 1760 O HOH 167 66.938 41.242 10.226 1.00 51.21 O
HETATM 1761 O HOH 168 85.023 60.379 30.965 1.00 38.68 O
HETATM 1762 O HOH 170 81.568 67.018 41.474 1.00 54.90 O
HETATM 1763 O HOH 171 83.672 64.839 39.206 1.00 48.85 O
HETATM 1764 O HOH 172 69.358 59.813 40.447 1.00 56.32 O
HETATM 1765 O HOH 173 65.402 39.517 46.250 1.00 42.43 O
HETATM 1766 O HOH 174 78.025 56.354 40.203 1.00 44.75 O
HETATM 1767 O HOH 175 72.640 54.075 19.103 1.00 56.38 O
HETATM 1768 O HOH 178 62.561 49.577 9.243 1.00 59.11 O
HETATM 1769 O HOH 181 67.851 57.255 35.234 1.00 39.17 O
HETATM 1770 O HOH 183 65.609 57.383 39.390 1.00 56.16 O
HETATM 1771 O HOH 184 77.652 63.370 43.463 1.00 46.31 O
HETATM 1772 O HOH 185 56.156 59.761 40.881 1.00 54.01 O
HETATM 1773 O HOH 186 68.030 57.904 37.829 1.00 54.73 O
HETATM 1774 O HOH 189 64.948 50.726 18.484 1.00 45.40 O
HETATM 1775 O HOH 191 58.581 70.881 37.367 1.00 43.35 O
HETATM 1776 O HOH 195 69.329 73.815 40.546 1.00 45.81 O
HETATM 1777 O HOH 196 71.092 44.843 13.706 1.00 46.18 O
HETATM 1778 O HOH 197 63.773 67.421 46.112 1.00 52.13 O
HETATM 1779 O HOH 200 79.526 44.399 2.237 1.00 56.28 O
HETATM 1780 O HOH 204 61.159 66.141 44.876 1.00 49.57 O
HETATM 1781 O HOH 205 55.921 58.490 38.100 1.00 52.97 O
HETATM 1782 O HOH 206 61.370 44.287 30.748 1.00 53.06 O
HETATM 1783 O HOH 208 72.463 66.452 30.831 1.00 58.61 O
HETATM 1784 O HOH 210 60.953 51.071 33.259 1.00 44.43 O
HETATM 1785 O HOH 214 55.561 30.912 50.683 1.00 57.65 O
HETATM 1786 O HOH 219 72.422 43.667 15.579 1.00 52.11 O
HETATM 1787 O HOH 222 65.477 55.377 26.488 1.00 40.16 O
HETATM 1788 O HOH 223 62.090 56.194 45.841 1.00 48.80 O
HETATM 1789 O HOH 226 60.948 49.649 25.176 1.00 34.03 O
HETATM 1790 O HOH 228 69.381 66.644 35.818 1.00 46.90 O
HETATM 1791 O HOH 230 66.314 66.119 35.359 1.00 45.34 O
HETATM 1792 O HOH 231 69.248 64.196 37.425 1.00 39.82 O
HETATM 1793 O HOH 233 67.490 67.214 38.107 1.00 42.96 O
HETATM 1794 O HOH 591 70.315 63.256 32.948 1.00 48.78 O
HETATM 1795 O HOH 592 70.278 67.253 46.788 1.00 49.58 O
HETATM 1796 O HOH 593 59.221 51.476 25.337 1.00 53.13 O
HETATM 1797 O HOH 596 36.759 35.239 56.874 1.00 54.15 O
HETATM 1798 O HOH 598 72.226 76.169 43.785 1.00 56.77 O
HETATM 1799 O HOH 602 79.271 66.367 28.116 1.00 57.39 O
HETATM 1800 O HOH 603 68.045 43.077 4.648 1.00 58.94 O
HETATM 1801 O HOH 608 52.188 37.918 39.395 1.00 56.79 O
HETATM 1802 O HOH 610 53.895 62.874 28.494 1.00 55.33 O
HETATM 1803 O HOH 611 70.166 44.500 35.929 1.00 59.11 O
HETATM 1804 O HOH 612 65.815 56.418 41.681 1.00 63.02 O
HETATM 1805 O HOH 613 84.445 61.099 24.272 1.00 53.13 O
HETATM 1806 O HOH 616 62.869 55.003 26.332 1.00 48.50 O
HETATM 1807 O HOH 618 50.840 53.124 44.965 1.00 59.63 O
HETATM 1808 O HOH 626 59.036 51.116 45.301 1.00 57.70 O
HETATM 1809 O HOH 627 51.263 39.619 37.323 1.00 55.93 O
HETATM 1810 O HOH 633 59.499 57.746 20.958 1.00 59.69 O
HETATM 1811 O HOH 635 77.328 58.675 26.658 1.00 51.93 O
HETATM 1812 O HOH 644 72.884 27.349 -8.052 1.00 57.57 O
HETATM 1813 O HOH 648 63.777 65.450 36.414 1.00 42.27 O
HETATM 1814 O HOH 657 72.947 30.361 -12.545 1.00 50.16 O
HETATM 1815 O HOH 662 57.486 68.555 38.998 1.00 41.15 O
HETATM 1816 O HOH 670 72.917 73.923 36.977 1.00 53.90 O
HETATM 1817 O HOH 671 82.577 50.441 36.557 1.00 57.25 O
HETATM 1818 O HOH 675 68.361 55.414 38.613 1.00 58.70 O
HETATM 1819 O HOH 688 64.284 30.562 -4.413 1.00 56.07 O
HETATM 1820 O HOH 690 69.590 42.478 12.375 1.00 58.33 O
HETATM 1821 O HOH 693 83.889 61.714 39.991 1.00 53.01 O
HETATM 1822 O HOH 707 61.422 49.192 45.932 1.00 56.92 O
CONECT 181 195
CONECT 195 181 196 197 198
CONECT 196 195
CONECT 197 195
CONECT 198 195 199
CONECT 199 198 200
CONECT 200 199 201 202
CONECT 201 200 206
CONECT 202 200 203 204
CONECT 203 202 219
CONECT 204 202 205 206
CONECT 205 204
CONECT 206 201 204 207
CONECT 207 206 208 218
CONECT 208 207 209
CONECT 209 208 210
CONECT 210 209 211 218
CONECT 211 210 212 213
CONECT 212 211
CONECT 213 211 214
CONECT 214 213 215 217
CONECT 215 214 216
CONECT 216 215
CONECT 217 214 218
CONECT 218 207 210 217
CONECT 219 203
CONECT 309 324
CONECT 324 309 325 326 327
CONECT 325 324
CONECT 326 324
CONECT 327 324 328
CONECT 328 327 329
CONECT 329 328 330 331
CONECT 330 329 333
CONECT 331 329 332 334
CONECT 332 331 344
CONECT 333 330 334 336
CONECT 334 331 333 335
CONECT 335 334
CONECT 336 333 337 343
CONECT 337 336 338 339
CONECT 338 337
CONECT 339 337 340
CONECT 340 339 341 342
CONECT 341 340
CONECT 342 340 343
CONECT 343 336 342
CONECT 344 332 345 346 347
CONECT 345 344
CONECT 346 344
CONECT 347 344 348
CONECT 348 347 349
CONECT 349 348 350 351
CONECT 350 349 353
CONECT 351 349 352 354
CONECT 352 351 364
CONECT 353 350 354 356
CONECT 354 351 353 355
CONECT 355 354
CONECT 356 353 357 363
CONECT 357 356 358 359
CONECT 358 357
CONECT 359 357 360
CONECT 360 359 361 362
CONECT 361 360
CONECT 362 360 363
CONECT 363 356 362
CONECT 364 352
CONECT 531 543
CONECT 543 531 544 545 546
CONECT 544 543
CONECT 545 543
CONECT 546 543 547
CONECT 547 546 548
CONECT 548 547 549 550
CONECT 549 548 554
CONECT 550 548 551 552
CONECT 551 550 568
CONECT 552 550 553 554
CONECT 553 552
CONECT 554 549 552 555
CONECT 555 554 556 565
CONECT 556 555 557
CONECT 557 556 558
CONECT 558 557 559 565
CONECT 559 558 560 561
CONECT 560 559
CONECT 561 559 562
CONECT 562 561 563 564
CONECT 563 562 566 567
CONECT 564 562 565
CONECT 565 555 558 564
CONECT 566 563
CONECT 567 563
CONECT 568 551
CONECT 661 693
CONECT 675 676 680 683
CONECT 676 675 677 681
CONECT 677 676 678
CONECT 678 677 679 682
CONECT 679 678 680
CONECT 680 675 679
CONECT 681 676
CONECT 682 678
CONECT 683 675 684 689
CONECT 684 683 685 687
CONECT 685 684 686
CONECT 686 685
CONECT 687 684 688 690
CONECT 688 687 689 691
CONECT 689 683 688
CONECT 690 687 696
CONECT 691 688 692
CONECT 692 691 693
CONECT 693 661 692 694 695
CONECT 694 693
CONECT 695 693
CONECT 696 690
CONECT 704 716
CONECT 716 704 717 718 719
CONECT 717 716
CONECT 718 716
CONECT 719 716 720
CONECT 720 719 721
CONECT 721 720 722 723
CONECT 722 721 728
CONECT 723 721 724 725
CONECT 724 723 740
CONECT 725 723 726 728
CONECT 726 725 727
CONECT 727 726
CONECT 728 722 725 729
CONECT 729 728 730 739
CONECT 730 729 731
CONECT 731 730 732
CONECT 732 731 733 739
CONECT 733 732 734 735
CONECT 734 733
CONECT 735 733 736
CONECT 736 735 737 738
CONECT 737 736
CONECT 738 736 739
CONECT 739 729 732 738
CONECT 740 724
CONECT 770 820
CONECT 784 786 791 798
CONECT 785 786 797
CONECT 786 784 785 787
CONECT 787 786 788 789
CONECT 788 787
CONECT 789 787 790 795
CONECT 790 789 791 793
CONECT 791 784 790 792
CONECT 792 791
CONECT 793 790 794
CONECT 794 793 795
CONECT 795 789 794 811
CONECT 796 797
CONECT 797 785 796 798
CONECT 798 784 797 799
CONECT 799 798 800
CONECT 800 799 801
CONECT 801 800 802 806
CONECT 802 801 803 804
CONECT 803 802
CONECT 804 802 805
CONECT 805 804
CONECT 806 801 807
CONECT 807 806 808 809
CONECT 808 807
CONECT 809 807 810
CONECT 810 809
CONECT 811 795 812 817
CONECT 812 811 813 814
CONECT 813 812
CONECT 814 812 815 816
CONECT 815 814 823
CONECT 816 814 817 818
"""
fake_nmr_file="""HEADER RIBONUCLEIC ACID 04-AUG-98 17RA
TITLE BRANCHPOINT HELIX FROM YEAST AND BINDING SITE FOR PHAGE
TITLE 2 GA/MS2 COAT PROTEINS, NMR, 12 STRUCTURES
COMPND MOL_ID: 1;
COMPND 2 MOLECULE: RNA;
COMPND 3 CHAIN: NULL;
COMPND 4 FRAGMENT: RBS AND START SITE FOR PHAGE GA REPLICASE GENE;
COMPND 5 ENGINEERED: YES;
COMPND 6 MUTATION: A5U, A6U
SOURCE MOL_ID: 1;
SOURCE 2 SYNTHETIC: YES;
SOURCE 3 ORGANISM_SCIENTIFIC: SACCHAROMYCES CEREVISIAE;
SOURCE 4 ORGANISM_COMMON: BAKER'S YEAST;
SOURCE 5 CELLULAR_LOCATION: NUCLEUS;
SOURCE 6 GENE: REPLICASE;
SOURCE 7 OTHER_DETAILS: IN VITRO SYNTHESIS FROM DNA TEMPLATE USING
SOURCE 8 T7 RNA POLYMERASE. HAIRPIN CORRESPONDS TO NT -16 - +5 OF
SOURCE 9 PHAGE GA REPLICASE AND THE YEAST PRE-MRNA BRANCHPOINT HELIX
KEYWDS BRANCHPOINT HELIX, PHAGE MS2, BULGE, BASE TRIPLE,
KEYWDS 2 RIBONUCLEIC ACID
EXPDTA NMR, 12 STRUCTURES
AUTHOR E.P.NIKONOWICZ,J.S.SMITH
REVDAT 1 20-APR-99 17RA 0
JRNL AUTH J.S.SMITH,E.P.NIKONOWICZ
JRNL TITL NMR STRUCTURE AND DYNAMICS OF AN RNA MOTIF COMMON
JRNL TITL 2 TO THE SPLICEOSOME BRANCH-POINT HELIX AND THE
JRNL TITL 3 RNA-BINDING SITE FOR PHAGE GA COAT PROTEIN
JRNL REF BIOCHEMISTRY V. 37 13486 1998
JRNL REFN ASTM BICHAW US ISSN 0006-2960 0033
REMARK 1
REMARK 2
REMARK 2 RESOLUTION. NOT APPLICABLE.
REMARK 3
REMARK 3 REFINEMENT.
REMARK 3 PROGRAM : X-PLOR 3.1
REMARK 3 AUTHORS : BRUNGER
REMARK 3
REMARK 3 OTHER REFINEMENT REMARKS: REFINEMENT DETAILS CAN BE FOUND
REMARK 3 IN THE JRNL CITATION ABOVE.
REMARK 4
REMARK 4 17RA COMPLIES WITH FORMAT V. 2.3, 09-JULY-1998
REMARK 6
REMARK 6 CALCULATIONS PERFORMED WITHOUT PHOSPHATE ON 5' TERMINAL
REMARK 6 NUCLEOTIDE.
REMARK 210
REMARK 210 EXPERIMENTAL DETAILS
REMARK 210 EXPERIMENT TYPE : NMR
REMARK 210 TEMPERATURE (KELVIN) : 298
REMARK 210 PH : 6.8
REMARK 210 IONIC STRENGTH : 20 MM
REMARK 210 PRESSURE : 1 ATM
REMARK 210 SAMPLE CONTENTS : 10% H2O/90% D2O, 100% D2O
REMARK 210
REMARK 210 NMR EXPERIMENTS CONDUCTED : 2D/3D NOESY, COSY, HETCOR
REMARK 210 SPECTROMETER FIELD STRENGTH : 500 MHZ
REMARK 210 SPECTROMETER MODEL : AMX500
REMARK 210 SPECTROMETER MANUFACTURER : BRUKER
REMARK 210
REMARK 210 STRUCTURE DETERMINATION.
REMARK 210 SOFTWARE USED : FELIX 950
REMARK 210 METHOD USED : SIMULATED ANNEALING
REMARK 210
REMARK 210 CONFORMERS, NUMBER CALCULATED : 75
REMARK 210 CONFORMERS, NUMBER SUBMITTED : 12
REMARK 210 CONFORMERS, SELECTION CRITERIA : LEAST RESTRAINT VIOLATION
REMARK 210
REMARK 210 BEST REPRESENTATIVE CONFORMER IN THIS ENSEMBLE : NULL
REMARK 210
REMARK 210 REMARK: FURTHER DETAILS OF DATA ACQUISITION AND STRUCTURE
REMARK 210 CALCULATION CAN BE FOUND IN THE METHODS SECTION OF THE
REMARK 210 MANUSCRIPT LISTED ABOVE. MODELS 1-6 ARE MINIMIZED
REMARK 210 STRUCTURES CALCULATED WITHOUT BASE PAIR CONSTRAINTS FOR
REMARK 210 A6, A7, AND U16. MODELS 7-12 ARE MINIMIZED STRUCTURES
REMARK 210 CALCULATED USING A6-U16 BASE PAIR CONSTRAINTS AND AN A7
REMARK 210 N1H-U16 O2 HYDROGEN BOND.
REMARK 215
REMARK 215 NMR STUDY
REMARK 215 THE COORDINATES IN THIS ENTRY WERE GENERATED FROM SOLUTION
REMARK 215 NMR DATA. PROTEIN DATA BANK CONVENTIONS REQUIRE THAT
REMARK 215 CRYST1 AND SCALE RECORDS BE INCLUDED, BUT THE VALUES ON
REMARK 215 THESE RECORDS ARE MEANINGLESS.
REMARK 800
REMARK 800 SITE
REMARK 800 SITE_IDENTIFIER: AAU
REMARK 800 SITE_DESCRIPTION: (A-A)*U MOTIF. PKA OF A7~6.1 AND IS
REMARK 800 PARTIALLY PROTONATED AT PH 6.8, A7 NH1 MAY BE STABILIZED
REMARK 800 BY U16 O2 (MODELS 7-12).
REMARK 999
REMARK 999 SEQUENCE
REMARK 999 CORRESPONDS TO GB D10027, GROUP II RNA BASES 1733 1753
DBREF 17RA 1 21 PDB 17RA 17RA 1 21
SEQRES 1 21 G G C G U A A G G A U U A
SEQRES 2 21 C C U A U G C C
SITE 1 AAU 3 A 6 A 7 U 16
CRYST1 1.000 1.000 1.000 90.00 90.00 90.00 P 1 1
ORIGX1 1.000000 0.000000 0.000000 0.00000
ORIGX2 0.000000 1.000000 0.000000 0.00000
ORIGX3 0.000000 0.000000 1.000000 0.00000
SCALE1 1.000000 0.000000 0.000000 0.00000
SCALE2 0.000000 1.000000 0.000000 0.00000
SCALE3 0.000000 0.000000 1.000000 0.00000
MODEL 1
ATOM 1 O5* G 1 35.729 -4.043 -8.815 1.00 0.00 O
ATOM 2 C5* G 1 36.486 -5.197 -8.419 1.00 0.00 C
ATOM 3 C4* G 1 35.947 -6.491 -9.034 1.00 0.00 C
ATOM 4 O4* G 1 36.433 -7.650 -8.339 1.00 0.00 O
ATOM 5 C3* G 1 34.424 -6.588 -8.918 1.00 0.00 C
ATOM 6 O3* G 1 33.771 -5.934 -10.022 1.00 0.00 O
ATOM 7 C2* G 1 34.203 -8.095 -8.942 1.00 0.00 C
ATOM 8 O2* G 1 34.122 -8.584 -10.288 1.00 0.00 O
ATOM 9 C1* G 1 35.423 -8.665 -8.218 1.00 0.00 C
ATOM 10 N9 G 1 35.126 -8.972 -6.792 1.00 0.00 N
ATOM 11 C8 G 1 35.282 -8.197 -5.684 1.00 0.00 C
ATOM 12 N7 G 1 34.953 -8.707 -4.545 1.00 0.00 N
ATOM 13 C5 G 1 34.521 -9.985 -4.914 1.00 0.00 C
ATOM 14 C6 G 1 34.026 -11.046 -4.105 1.00 0.00 C
ATOM 15 O6 G 1 33.873 -11.066 -2.885 1.00 0.00 O
ATOM 16 N1 G 1 33.701 -12.162 -4.869 1.00 0.00 N
ATOM 17 C2 G 1 33.833 -12.251 -6.243 1.00 0.00 C
ATOM 18 N2 G 1 33.467 -13.405 -6.801 1.00 0.00 N
ATOM 19 N3 G 1 34.297 -11.256 -7.009 1.00 0.00 N
ATOM 20 C4 G 1 34.621 -10.158 -6.287 1.00 0.00 C
ATOM 21 1H5* G 1 36.434 -5.308 -7.345 1.00 0.00 H
ATOM 22 2H5* G 1 37.533 -5.043 -8.723 1.00 0.00 H
ATOM 23 H4* G 1 36.243 -6.549 -10.082 1.00 0.00 H
ATOM 24 H3* G 1 34.089 -6.173 -7.960 1.00 0.00 H
ATOM 25 1H2* G 1 33.294 -8.345 -8.391 1.00 0.00 H
ATOM 26 2HO* G 1 33.856 -9.506 -10.242 1.00 0.00 H
ATOM 27 H1* G 1 35.757 -9.572 -8.727 1.00 0.00 H
ATOM 28 H8 G 1 35.670 -7.179 -5.754 1.00 0.00 H
ATOM 29 H1 G 1 33.342 -12.958 -4.361 1.00 0.00 H
ATOM 30 1H2 G 1 33.541 -13.530 -7.800 1.00 0.00 H
ATOM 31 2H2 G 1 33.116 -14.156 -6.224 1.00 0.00 H
ATOM 32 H5T G 1 35.846 -3.936 -9.762 1.00 0.00 H
ATOM 33 P G 2 32.263 -5.363 -9.892 1.00 0.00 P
ATOM 34 O1P G 2 31.976 -4.551 -11.096 1.00 0.00 O
ATOM 35 O2P G 2 32.103 -4.764 -8.548 1.00 0.00 O
ATOM 36 O5* G 2 31.365 -6.705 -9.956 1.00 0.00 O
ATOM 37 C5* G 2 31.011 -7.307 -11.214 1.00 0.00 C
ATOM 38 C4* G 2 30.343 -8.676 -11.050 1.00 0.00 C
ATOM 39 O4* G 2 31.035 -9.497 -10.097 1.00 0.00 O
ATOM 40 C3* G 2 28.923 -8.561 -10.491 1.00 0.00 C
ATOM 41 O3* G 2 27.951 -8.310 -11.523 1.00 0.00 O
ATOM 42 C2* G 2 28.731 -9.940 -9.871 1.00 0.00 C
ATOM 43 O2* G 2 28.290 -10.893 -10.847 1.00 0.00 O
ATOM 44 C1* G 2 30.119 -10.301 -9.334 1.00 0.00 C
ATOM 45 N9 G 2 30.233 -10.024 -7.876 1.00 0.00 N
ATOM 46 C8 G 2 30.688 -8.915 -7.234 1.00 0.00 C
ATOM 47 N7 G 2 30.687 -8.928 -5.942 1.00 0.00 N
ATOM 48 C5 G 2 30.171 -10.196 -5.665 1.00 0.00 C
ATOM 49 C6 G 2 29.919 -10.822 -4.414 1.00 0.00 C
ATOM 50 O6 G 2 30.109 -10.370 -3.286 1.00 0.00 O
ATOM 51 N1 G 2 29.397 -12.100 -4.577 1.00 0.00 N
ATOM 52 C2 G 2 29.145 -12.706 -5.793 1.00 0.00 C
ATOM 53 N2 G 2 28.642 -13.941 -5.748 1.00 0.00 N
ATOM 54 N3 G 2 29.379 -12.124 -6.974 1.00 0.00 N
ATOM 55 C4 G 2 29.889 -10.878 -6.841 1.00 0.00 C
ATOM 56 1H5* G 2 31.908 -7.466 -11.801 1.00 0.00 H
ATOM 57 2H5* G 2 30.337 -6.621 -11.752 1.00 0.00 H
ATOM 58 H4* G 2 30.320 -9.189 -12.015 1.00 0.00 H
ATOM 59 H3* G 2 28.882 -7.791 -9.713 1.00 0.00 H
ATOM 60 1H2* G 2 28.016 -9.880 -9.045 1.00 0.00 H
ATOM 61 2HO* G 2 27.375 -10.684 -11.057 1.00 0.00 H
ATOM 62 H1* G 2 30.322 -11.357 -9.525 1.00 0.00 H
ATOM 63 H8 G 2 31.045 -8.046 -7.786 1.00 0.00 H
ATOM 64 H1 G 2 29.191 -12.607 -3.725 1.00 0.00 H
ATOM 65 1H2 G 2 28.437 -14.436 -6.605 1.00 0.00 H
ATOM 66 2H2 G 2 28.464 -14.382 -4.857 1.00 0.00 H
ATOM 67 P C 3 26.771 -7.224 -11.322 1.00 0.00 P
ATOM 68 O1P C 3 26.262 -6.847 -12.661 1.00 0.00 O
ATOM 69 O2P C 3 27.254 -6.170 -10.400 1.00 0.00 O
ATOM 70 O5* C 3 25.628 -8.075 -10.559 1.00 0.00 O
ATOM 71 C5* C 3 24.477 -8.572 -11.257 1.00 0.00 C
ATOM 72 C4* C 3 23.641 -9.523 -10.386 1.00 0.00 C
ATOM 73 O4* C 3 24.471 -10.338 -9.542 1.00 0.00 O
ATOM 74 C3* C 3 22.733 -8.770 -9.408 1.00 0.00 C
ATOM 75 O3* C 3 21.495 -8.361 -10.017 1.00 0.00 O
ATOM 76 C2* C 3 22.506 -9.840 -8.347 1.00 0.00 C
ATOM 77 O2* C 3 21.435 -10.719 -8.716 1.00 0.00 O
ATOM 78 C1* C 3 23.839 -10.592 -8.275 1.00 0.00 C
ATOM 79 N1 C 3 24.678 -10.136 -7.128 1.00 0.00 N
ATOM 80 C2 C 3 24.508 -10.789 -5.908 1.00 0.00 C
ATOM 81 O2 C 3 23.685 -11.698 -5.800 1.00 0.00 O
ATOM 82 N3 C 3 25.268 -10.395 -4.851 1.00 0.00 N
ATOM 83 C4 C 3 26.159 -9.403 -4.971 1.00 0.00 C
ATOM 84 N4 C 3 26.883 -9.048 -3.910 1.00 0.00 N
ATOM 85 C5 C 3 26.343 -8.725 -6.217 1.00 0.00 C
ATOM 86 C6 C 3 25.588 -9.118 -7.263 1.00 0.00 C
ATOM 87 1H5* C 3 24.807 -9.110 -12.148 1.00 0.00 H
ATOM 88 2H5* C 3 23.856 -7.730 -11.565 1.00 0.00 H
ATOM 89 H4* C 3 23.038 -10.170 -11.027 1.00 0.00 H
ATOM 90 H3* C 3 23.265 -7.915 -8.975 1.00 0.00 H
ATOM 91 1H2* C 3 22.294 -9.367 -7.384 1.00 0.00 H
ATOM 92 2HO* C 3 20.613 -10.251 -8.558 1.00 0.00 H
ATOM 93 H1* C 3 23.644 -11.663 -8.184 1.00 0.00 H
ATOM 94 1H4 C 3 27.559 -8.301 -3.985 1.00 0.00 H
ATOM 95 2H4 C 3 26.757 -9.525 -3.028 1.00 0.00 H
ATOM 96 H5 C 3 27.069 -7.917 -6.317 1.00 0.00 H
ATOM 97 H6 C 3 25.706 -8.619 -8.224 1.00 0.00 H
ATOM 98 P G 4 20.708 -7.037 -9.523 1.00 0.00 P
ATOM 99 O1P G 4 19.779 -6.624 -10.600 1.00 0.00 O
ATOM 100 O2P G 4 21.698 -6.069 -8.998 1.00 0.00 O
ATOM 101 O5* G 4 19.832 -7.583 -8.278 1.00 0.00 O
ATOM 102 C5* G 4 18.633 -8.350 -8.491 1.00 0.00 C
ATOM 103 C4* G 4 18.228 -9.169 -7.262 1.00 0.00 C
ATOM 104 O4* G 4 19.372 -9.689 -6.570 1.00 0.00 O
ATOM 105 C3* G 4 17.500 -8.321 -6.213 1.00 0.00 C
ATOM 106 O3* G 4 16.092 -8.212 -6.500 1.00 0.00 O
ATOM 107 C2* G 4 17.750 -9.137 -4.951 1.00 0.00 C
ATOM 108 O2* G 4 16.781 -10.184 -4.808 1.00 0.00 O
ATOM 109 C1* G 4 19.155 -9.706 -5.149 1.00 0.00 C
ATOM 110 N9 G 4 20.181 -8.913 -4.420 1.00 0.00 N
ATOM 111 C8 G 4 21.010 -7.930 -4.866 1.00 0.00 C
ATOM 112 N7 G 4 21.826 -7.403 -4.014 1.00 0.00 N
ATOM 113 C5 G 4 21.518 -8.108 -2.845 1.00 0.00 C
ATOM 114 C6 G 4 22.071 -7.993 -1.538 1.00 0.00 C
ATOM 115 O6 G 4 22.961 -7.238 -1.149 1.00 0.00 O
ATOM 116 N1 G 4 21.477 -8.887 -0.653 1.00 0.00 N
ATOM 117 C2 G 4 20.476 -9.781 -0.978 1.00 0.00 C
ATOM 118 N2 G 4 20.036 -10.563 0.009 1.00 0.00 N
ATOM 119 N3 G 4 19.952 -9.894 -2.202 1.00 0.00 N
ATOM 120 C4 G 4 20.513 -9.033 -3.084 1.00 0.00 C
ATOM 121 1H5* G 4 18.796 -9.055 -9.296 1.00 0.00 H
ATOM 122 2H5* G 4 17.821 -7.658 -8.769 1.00 0.00 H
ATOM 123 H4* G 4 17.590 -10.000 -7.571 1.00 0.00 H
ATOM 124 H3* G 4 17.968 -7.333 -6.126 1.00 0.00 H
ATOM 125 1H2* G 4 17.734 -8.483 -4.076 1.00 0.00 H
ATOM 126 2HO* G 4 16.922 -10.590 -3.948 1.00 0.00 H
ATOM 127 H1* G 4 19.178 -10.735 -4.796 1.00 0.00 H
ATOM 128 H8 G 4 20.986 -7.595 -5.904 1.00 0.00 H
ATOM 129 H1 G 4 21.814 -8.859 0.298 1.00 0.00 H
ATOM 130 1H2 G 4 20.432 -10.478 0.935 1.00 0.00 H
ATOM 131 2H2 G 4 19.309 -11.239 -0.169 1.00 0.00 H
ATOM 132 P U 5 15.233 -6.916 -6.060 1.00 0.00 P
ATOM 133 O1P U 5 13.850 -7.096 -6.556 1.00 0.00 O
ATOM 134 O2P U 5 15.992 -5.701 -6.434 1.00 0.00 O
ATOM 135 O5* U 5 15.217 -7.025 -4.446 1.00 0.00 O
ATOM 136 C5* U 5 13.987 -7.142 -3.713 1.00 0.00 C
ATOM 137 C4* U 5 14.174 -6.810 -2.224 1.00 0.00 C
ATOM 138 O4* U 5 15.442 -7.271 -1.730 1.00 0.00 O
ATOM 139 C3* U 5 14.196 -5.299 -1.970 1.00 0.00 C
ATOM 140 O3* U 5 12.866 -4.773 -1.798 1.00 0.00 O
ATOM 141 C2* U 5 15.006 -5.214 -0.682 1.00 0.00 C
ATOM 142 O2* U 5 14.170 -5.389 0.469 1.00 0.00 O
ATOM 143 C1* U 5 16.027 -6.347 -0.796 1.00 0.00 C
ATOM 144 N1 U 5 17.357 -5.858 -1.260 1.00 0.00 N
ATOM 145 C2 U 5 18.197 -5.285 -0.314 1.00 0.00 C
ATOM 146 O2 U 5 17.870 -5.156 0.866 1.00 0.00 O
ATOM 147 N3 U 5 19.433 -4.863 -0.773 1.00 0.00 N
ATOM 148 C4 U 5 19.901 -4.963 -2.073 1.00 0.00 C
ATOM 149 O4 U 5 21.023 -4.555 -2.368 1.00 0.00 O
ATOM 150 C5 U 5 18.963 -5.572 -2.991 1.00 0.00 C
ATOM 151 C6 U 5 17.746 -5.989 -2.569 1.00 0.00 C
ATOM 152 1H5* U 5 13.620 -8.166 -3.803 1.00 0.00 H
ATOM 153 2H5* U 5 13.248 -6.464 -4.143 1.00 0.00 H
ATOM 154 H4* U 5 13.372 -7.270 -1.643 1.00 0.00 H
ATOM 155 H3* U 5 14.723 -4.785 -2.783 1.00 0.00 H
ATOM 156 1H2* U 5 15.521 -4.251 -0.634 1.00 0.00 H
ATOM 157 2HO* U 5 14.701 -5.187 1.242 1.00 0.00 H
ATOM 158 H1* U 5 16.136 -6.836 0.175 1.00 0.00 H
ATOM 159 H3 U 5 20.051 -4.441 -0.096 1.00 0.00 H
ATOM 160 H5 U 5 19.246 -5.709 -4.036 1.00 0.00 H
ATOM 161 H6 U 5 17.062 -6.432 -3.288 1.00 0.00 H
ATOM 162 P A 6 12.565 -3.186 -1.896 1.00 0.00 P
ATOM 163 O1P A 6 11.096 -2.998 -1.909 1.00 0.00 O
ATOM 164 O2P A 6 13.385 -2.620 -2.991 1.00 0.00 O
ATOM 165 O5* A 6 13.139 -2.622 -0.494 1.00 0.00 O
ATOM 166 C5* A 6 12.398 -2.764 0.728 1.00 0.00 C
ATOM 167 C4* A 6 13.218 -2.316 1.947 1.00 0.00 C
ATOM 168 O4* A 6 14.583 -2.747 1.849 1.00 0.00 O
ATOM 169 C3* A 6 13.286 -0.789 2.053 1.00 0.00 C
ATOM 170 O3* A 6 12.314 -0.331 3.011 1.00 0.00 O
ATOM 171 C2* A 6 14.715 -0.482 2.497 1.00 0.00 C
ATOM 172 O2* A 6 14.736 0.082 3.814 1.00 0.00 O
ATOM 173 C1* A 6 15.474 -1.806 2.465 1.00 0.00 C
ATOM 174 N9 A 6 16.741 -1.676 1.704 1.00 0.00 N
ATOM 175 C8 A 6 16.951 -1.695 0.363 1.00 0.00 C
ATOM 176 N7 A 6 18.166 -1.554 -0.053 1.00 0.00 N
ATOM 177 C5 A 6 18.866 -1.420 1.150 1.00 0.00 C
ATOM 178 C6 A 6 20.222 -1.233 1.445 1.00 0.00 C
ATOM 179 N6 A 6 21.168 -1.143 0.507 1.00 0.00 N
ATOM 180 N1 A 6 20.569 -1.141 2.740 1.00 0.00 N
ATOM 181 C2 A 6 19.641 -1.226 3.696 1.00 0.00 C
ATOM 182 N3 A 6 18.333 -1.403 3.532 1.00 0.00 N
ATOM 183 C4 A 6 18.008 -1.492 2.225 1.00 0.00 C
ATOM 184 1H5* A 6 12.119 -3.812 0.856 1.00 0.00 H
ATOM 185 2H5* A 6 11.489 -2.162 0.668 1.00 0.00 H
ATOM 186 H4* A 6 12.776 -2.729 2.856 1.00 0.00 H
ATOM 187 H3* A 6 13.099 -0.339 1.074 1.00 0.00 H
ATOM 188 1H2* A 6 15.172 0.211 1.787 1.00 0.00 H
ATOM 189 2HO* A 6 14.285 -0.534 4.397 1.00 0.00 H
ATOM 190 H1* A 6 15.694 -2.126 3.485 1.00 0.00 H
ATOM 191 H8 A 6 16.123 -1.811 -0.335 1.00 0.00 H
ATOM 192 1H6 A 6 22.132 -1.008 0.774 1.00 0.00 H
ATOM 193 2H6 A 6 20.918 -1.210 -0.469 1.00 0.00 H
ATOM 194 H2 A 6 19.993 -1.143 4.724 1.00 0.00 H
ATOM 195 P A 7 11.860 1.219 3.079 1.00 0.00 P
ATOM 196 O1P A 7 10.531 1.280 3.729 1.00 0.00 O
ATOM 197 O2P A 7 12.051 1.826 1.741 1.00 0.00 O
ATOM 198 O5* A 7 12.943 1.858 4.095 1.00 0.00 O
ATOM 199 C5* A 7 13.656 3.061 3.772 1.00 0.00 C
ATOM 200 C4* A 7 14.906 3.224 4.652 1.00 0.00 C
ATOM 201 O4* A 7 15.883 2.209 4.374 1.00 0.00 O
ATOM 202 C3* A 7 15.639 4.540 4.375 1.00 0.00 C
ATOM 203 O3* A 7 15.112 5.625 5.160 1.00 0.00 O
ATOM 204 C2* A 7 17.066 4.195 4.787 1.00 0.00 C
ATOM 205 O2* A 7 17.264 4.395 6.194 1.00 0.00 O
ATOM 206 C1* A 7 17.224 2.721 4.409 1.00 0.00 C
ATOM 207 N9 A 7 17.905 2.560 3.096 1.00 0.00 N
ATOM 208 C8 A 7 17.377 2.501 1.843 1.00 0.00 C
ATOM 209 N7 A 7 18.197 2.371 0.854 1.00 0.00 N
ATOM 210 C5 A 7 19.433 2.334 1.510 1.00 0.00 C
ATOM 211 C6 A 7 20.748 2.208 1.046 1.00 0.00 C
ATOM 212 N6 A 7 21.058 2.096 -0.246 1.00 0.00 N
ATOM 213 N1 A 7 21.731 2.204 1.964 1.00 0.00 N
ATOM 214 C2 A 7 21.445 2.319 3.262 1.00 0.00 C
ATOM 215 N3 A 7 20.239 2.446 3.811 1.00 0.00 N
ATOM 216 C4 A 7 19.268 2.446 2.873 1.00 0.00 C
ATOM 217 1H5* A 7 12.996 3.918 3.924 1.00 0.00 H
ATOM 218 2H5* A 7 13.959 3.027 2.725 1.00 0.00 H
ATOM 219 H4* A 7 14.622 3.171 5.705 1.00 0.00 H
ATOM 220 H3* A 7 15.604 4.774 3.305 1.00 0.00 H
ATOM 221 1H2* A 7 17.771 4.801 4.215 1.00 0.00 H
ATOM 222 2HO* A 7 16.670 3.797 6.655 1.00 0.00 H
ATOM 223 H1* A 7 17.791 2.203 5.185 1.00 0.00 H
ATOM 224 H8 A 7 16.301 2.551 1.679 1.00 0.00 H
ATOM 225 1H6 A 7 22.024 2.006 -0.527 1.00 0.00 H
ATOM 226 2H6 A 7 20.327 2.100 -0.943 1.00 0.00 H
ATOM 227 H2 A 7 22.293 2.303 3.948 1.00 0.00 H
ATOM 228 P G 8 15.175 7.152 4.632 1.00 0.00 P
ATOM 229 O1P G 8 14.224 7.956 5.434 1.00 0.00 O
ATOM 230 O2P G 8 15.064 7.145 3.156 1.00 0.00 O
ATOM 231 O5* G 8 16.679 7.602 5.021 1.00 0.00 O
ATOM 232 C5* G 8 16.974 8.190 6.301 1.00 0.00 C
ATOM 233 C4* G 8 18.459 8.097 6.664 1.00 0.00 C
ATOM 234 O4* G 8 19.038 6.861 6.220 1.00 0.00 O
ATOM 235 C3* G 8 19.294 9.178 5.970 1.00 0.00 C
ATOM 236 O3* G 8 19.301 10.432 6.677 1.00 0.00 O
ATOM 237 C2* G 8 20.676 8.536 5.995 1.00 0.00 C
ATOM 238 O2* G 8 21.341 8.783 7.242 1.00 0.00 O
ATOM 239 C1* G 8 20.400 7.045 5.800 1.00 0.00 C
ATOM 240 N9 G 8 20.603 6.633 4.384 1.00 0.00 N
ATOM 241 C8 G 8 19.716 6.588 3.353 1.00 0.00 C
ATOM 242 N7 G 8 20.153 6.196 2.203 1.00 0.00 N
ATOM 243 C5 G 8 21.500 5.939 2.479 1.00 0.00 C
ATOM 244 C6 G 8 22.532 5.475 1.617 1.00 0.00 C
ATOM 245 O6 G 8 22.457 5.193 0.423 1.00 0.00 O
ATOM 246 N1 G 8 23.743 5.352 2.291 1.00 0.00 N
ATOM 247 C2 G 8 23.940 5.638 3.629 1.00 0.00 C
ATOM 248 N2 G 8 25.175 5.455 4.101 1.00 0.00 N
ATOM 249 N3 G 8 22.975 6.075 4.444 1.00 0.00 N
ATOM 250 C4 G 8 21.786 6.203 3.810 1.00 0.00 C
ATOM 251 1H5* G 8 16.430 7.661 7.074 1.00 0.00 H
ATOM 252 2H5* G 8 16.653 9.244 6.283 1.00 0.00 H
ATOM 253 H4* G 8 18.576 8.179 7.746 1.00 0.00 H
ATOM 254 H3* G 8 18.960 9.308 4.933 1.00 0.00 H
ATOM 255 1H2* G 8 21.274 8.913 5.164 1.00 0.00 H
ATOM 256 2HO* G 8 22.250 8.489 7.145 1.00 0.00 H
ATOM 257 H1* G 8 21.060 6.464 6.449 1.00 0.00 H
ATOM 258 H8 G 8 18.671 6.869 3.491 1.00 0.00 H
ATOM 259 H1 G 8 24.528 5.030 1.739 1.00 0.00 H
ATOM 260 1H2 G 8 25.377 5.646 5.072 1.00 0.00 H
ATOM 261 2H2 G 8 25.906 5.124 3.488 1.00 0.00 H
ATOM 262 P G 9 19.503 11.838 5.902 1.00 0.00 P
ATOM 263 O1P G 9 19.258 12.934 6.867 1.00 0.00 O
ATOM 264 O2P G 9 18.733 11.791 4.637 1.00 0.00 O
ATOM 265 O5* G 9 21.078 11.827 5.533 1.00 0.00 O
ATOM 266 C5* G 9 22.079 12.117 6.527 1.00 0.00 C
ATOM 267 C4* G 9 23.469 11.607 6.136 1.00 0.00 C
ATOM 268 O4* G 9 23.399 10.353 5.441 1.00 0.00 O
ATOM 269 C3* G 9 24.176 12.539 5.154 1.00 0.00 C
ATOM 270 O3* G 9 24.856 13.639 5.786 1.00 0.00 O
ATOM 271 C2* G 9 25.176 11.572 4.531 1.00 0.00 C
ATOM 272 O2* G 9 26.330 11.407 5.367 1.00 0.00 O
ATOM 273 C1* G 9 24.390 10.265 4.404 1.00 0.00 C
ATOM 274 N9 G 9 23.764 10.121 3.058 1.00 0.00 N
ATOM 275 C8 G 9 22.457 10.216 2.689 1.00 0.00 C
ATOM 276 N7 G 9 22.173 10.051 1.440 1.00 0.00 N
ATOM 277 C5 G 9 23.433 9.814 0.884 1.00 0.00 C
ATOM 278 C6 G 9 23.801 9.558 -0.468 1.00 0.00 C
ATOM 279 O6 G 9 23.073 9.498 -1.460 1.00 0.00 O
ATOM 280 N1 G 9 25.171 9.376 -0.598 1.00 0.00 N
ATOM 281 C2 G 9 26.084 9.433 0.440 1.00 0.00 C
ATOM 282 N2 G 9 27.363 9.241 0.117 1.00 0.00 N
ATOM 283 N3 G 9 25.747 9.673 1.710 1.00 0.00 N
ATOM 284 C4 G 9 24.415 9.854 1.864 1.00 0.00 C
ATOM 285 1H5* G 9 21.816 11.626 7.453 1.00 0.00 H
ATOM 286 2H5* G 9 22.106 13.208 6.687 1.00 0.00 H
ATOM 287 H4* G 9 24.079 11.487 7.029 1.00 0.00 H
ATOM 288 H3* G 9 23.471 12.891 4.392 1.00 0.00 H
ATOM 289 1H2* G 9 25.472 11.929 3.543 1.00 0.00 H
ATOM 290 2HO* G 9 26.061 10.888 6.129 1.00 0.00 H
ATOM 291 H1* G 9 25.050 9.416 4.600 1.00 0.00 H
ATOM 292 H8 G 9 21.675 10.422 3.420 1.00 0.00 H
ATOM 293 H1 G 9 25.505 9.184 -1.532 1.00 0.00 H
ATOM 294 1H2 G 9 28.075 9.277 0.832 1.00 0.00 H
ATOM 295 2H2 G 9 27.620 9.060 -0.844 1.00 0.00 H
ATOM 296 P A 10 24.574 15.170 5.346 1.00 0.00 P
ATOM 297 O1P A 10 25.088 16.058 6.414 1.00 0.00 O
ATOM 298 O2P A 10 23.160 15.284 4.920 1.00 0.00 O
ATOM 299 O5* A 10 25.509 15.351 4.040 1.00 0.00 O
ATOM 300 C5* A 10 26.926 15.558 4.158 1.00 0.00 C
ATOM 301 C4* A 10 27.695 14.893 3.010 1.00 0.00 C
ATOM 302 O4* A 10 27.088 13.644 2.639 1.00 0.00 O
ATOM 303 C3* A 10 27.666 15.734 1.730 1.00 0.00 C
ATOM 304 O3* A 10 28.738 16.681 1.557 1.00 0.00 O
ATOM 305 C2* A 10 27.848 14.655 0.676 1.00 0.00 C
ATOM 306 O2* A 10 29.235 14.386 0.433 1.00 0.00 O
ATOM 307 C1* A 10 27.132 13.433 1.221 1.00 0.00 C
ATOM 308 N9 A 10 25.782 13.325 0.619 1.00 0.00 N
ATOM 309 C8 A 10 24.567 13.233 1.208 1.00 0.00 C
ATOM 310 N7 A 10 23.531 13.159 0.438 1.00 0.00 N
ATOM 311 C5 A 10 24.118 13.212 -0.830 1.00 0.00 C
ATOM 312 C6 A 10 23.590 13.185 -2.128 1.00 0.00 C
ATOM 313 N6 A 10 22.285 13.087 -2.383 1.00 0.00 N
ATOM 314 N1 A 10 24.460 13.266 -3.151 1.00 0.00 N
ATOM 315 C2 A 10 25.772 13.368 -2.917 1.00 0.00 C
ATOM 316 N3 A 10 26.373 13.394 -1.738 1.00 0.00 N
ATOM 317 C4 A 10 25.485 13.314 -0.728 1.00 0.00 C
ATOM 318 1H5* A 10 27.271 15.137 5.101 1.00 0.00 H
ATOM 319 2H5* A 10 27.130 16.630 4.154 1.00 0.00 H
ATOM 320 H4* A 10 28.728 14.715 3.315 1.00 0.00 H
ATOM 321 H3* A 10 26.687 16.215 1.611 1.00 0.00 H
ATOM 322 1H2* A 10 27.356 14.965 -0.242 1.00 0.00 H
ATOM 323 2HO* A 10 29.611 14.051 1.250 1.00 0.00 H
ATOM 324 H1* A 10 27.712 12.533 0.999 1.00 0.00 H
ATOM 325 H8 A 10 24.467 13.253 2.288 1.00 0.00 H
ATOM 326 1H6 A 10 21.957 13.072 -3.339 1.00 0.00 H
ATOM 327 2H6 A 10 21.624 13.026 -1.622 1.00 0.00 H
ATOM 328 H2 A 10 26.420 13.467 -3.792 1.00 0.00 H
ATOM 329 P U 11 28.576 17.995 0.621 1.00 0.00 P
ATOM 330 O1P U 11 29.925 18.403 0.166 1.00 0.00 O
ATOM 331 O2P U 11 27.725 18.967 1.343 1.00 0.00 O
ATOM 332 O5* U 11 27.742 17.456 -0.660 1.00 0.00 O
ATOM 333 C5* U 11 28.394 16.929 -1.831 1.00 0.00 C
ATOM 334 C4* U 11 27.827 17.520 -3.137 1.00 0.00 C
ATOM 335 O4* U 11 26.520 17.016 -3.444 1.00 0.00 O
ATOM 336 C3* U 11 27.619 19.039 -3.065 1.00 0.00 C
ATOM 337 O3* U 11 27.694 19.750 -4.306 1.00 0.00 O
ATOM 338 C2* U 11 26.178 19.201 -2.604 1.00 0.00 C
ATOM 339 O2* U 11 25.622 20.454 -3.029 1.00 0.00 O
ATOM 340 C1* U 11 25.499 18.016 -3.297 1.00 0.00 C
ATOM 341 N1 U 11 24.332 17.511 -2.520 1.00 0.00 N
ATOM 342 C2 U 11 23.089 17.546 -3.137 1.00 0.00 C
ATOM 343 O2 U 11 22.939 17.962 -4.286 1.00 0.00 O
ATOM 344 N3 U 11 22.021 17.082 -2.388 1.00 0.00 N
ATOM 345 C4 U 11 22.082 16.594 -1.094 1.00 0.00 C
ATOM 346 O4 U 11 21.063 16.209 -0.521 1.00 0.00 O
ATOM 347 C5 U 11 23.411 16.592 -0.526 1.00 0.00 C
ATOM 348 C6 U 11 24.475 17.039 -1.237 1.00 0.00 C
ATOM 349 1H5* U 11 28.260 15.848 -1.848 1.00 0.00 H
ATOM 350 2H5* U 11 29.459 17.145 -1.780 1.00 0.00 H
ATOM 351 H4* U 11 28.499 17.279 -3.968 1.00 0.00 H
ATOM 352 H3* U 11 28.293 19.482 -2.333 1.00 0.00 H
ATOM 353 1H2* U 11 26.115 19.093 -1.518 1.00 0.00 H
ATOM 354 2HO* U 11 25.589 20.443 -3.989 1.00 0.00 H
ATOM 355 H1* U 11 25.169 18.324 -4.292 1.00 0.00 H
ATOM 356 H3 U 11 21.111 17.104 -2.827 1.00 0.00 H
ATOM 357 H5 U 11 23.559 16.227 0.491 1.00 0.00 H
ATOM 358 H6 U 11 25.464 17.021 -0.780 1.00 0.00 H
ATOM 359 P U 12 29.104 20.030 -5.029 1.00 0.00 P
ATOM 360 O1P U 12 30.182 19.371 -4.256 1.00 0.00 O
ATOM 361 O2P U 12 29.190 21.477 -5.328 1.00 0.00 O
ATOM 362 O5* U 12 28.904 19.242 -6.418 1.00 0.00 O
ATOM 363 C5* U 12 29.559 17.999 -6.687 1.00 0.00 C
ATOM 364 C4* U 12 28.656 17.042 -7.476 1.00 0.00 C
ATOM 365 O4* U 12 27.374 17.616 -7.774 1.00 0.00 O
ATOM 366 C3* U 12 29.275 16.676 -8.821 1.00 0.00 C
ATOM 367 O3* U 12 29.008 15.408 -9.437 1.00 0.00 O
ATOM 368 C2* U 12 28.653 17.722 -9.741 1.00 0.00 C
ATOM 369 O2* U 12 28.547 17.237 -11.086 1.00 0.00 O
ATOM 370 C1* U 12 27.274 18.004 -9.154 1.00 0.00 C
ATOM 371 N1 U 12 26.895 19.438 -9.299 1.00 0.00 N
ATOM 372 C2 U 12 26.259 19.820 -10.473 1.00 0.00 C
ATOM 373 O2 U 12 26.014 19.022 -11.377 1.00 0.00 O
ATOM 374 N3 U 12 25.916 21.158 -10.572 1.00 0.00 N
ATOM 375 C4 U 12 26.148 22.135 -9.619 1.00 0.00 C
ATOM 376 O4 U 12 25.799 23.298 -9.814 1.00 0.00 O
ATOM 377 C5 U 12 26.815 21.652 -8.430 1.00 0.00 C
ATOM 378 C6 U 12 27.161 20.347 -8.306 1.00 0.00 C
ATOM 379 1H5* U 12 29.833 17.528 -5.743 1.00 0.00 H
ATOM 380 2H5* U 12 30.462 18.191 -7.254 1.00 0.00 H
ATOM 381 H4* U 12 28.507 16.133 -6.892 1.00 0.00 H
ATOM 382 H3* U 12 30.355 16.846 -8.759 1.00 0.00 H
ATOM 383 1H2* U 12 29.243 18.624 -9.718 1.00 0.00 H
ATOM 384 2HO* U 12 28.308 17.983 -11.641 1.00 0.00 H
ATOM 385 H1* U 12 26.532 17.378 -9.652 1.00 0.00 H
ATOM 386 H3 U 12 25.452 21.448 -11.422 1.00 0.00 H
ATOM 387 H5 U 12 27.041 22.348 -7.621 1.00 0.00 H
ATOM 388 H6 U 12 27.668 20.016 -7.400 1.00 0.00 H
ATOM 389 P A 13 29.931 14.883 -10.657 1.00 0.00 P
ATOM 390 O1P A 13 30.926 15.931 -10.983 1.00 0.00 O
ATOM 391 O2P A 13 29.042 14.363 -11.721 1.00 0.00 O
ATOM 392 O5* A 13 30.717 13.645 -9.995 1.00 0.00 O
ATOM 393 C5* A 13 30.316 12.299 -10.252 1.00 0.00 C
ATOM 394 C4* A 13 29.638 11.672 -9.027 1.00 0.00 C
ATOM 395 O4* A 13 28.904 12.629 -8.255 1.00 0.00 O
ATOM 396 C3* A 13 28.602 10.612 -9.409 1.00 0.00 C
ATOM 397 O3* A 13 28.539 9.603 -8.396 1.00 0.00 O
ATOM 398 C2* A 13 27.285 11.373 -9.478 1.00 0.00 C
ATOM 399 O2* A 13 26.163 10.519 -9.217 1.00 0.00 O
ATOM 400 C1* A 13 27.494 12.395 -8.358 1.00 0.00 C
ATOM 401 N9 A 13 26.739 13.655 -8.572 1.00 0.00 N
ATOM 402 C8 A 13 26.342 14.278 -9.713 1.00 0.00 C
ATOM 403 N7 A 13 25.576 15.311 -9.592 1.00 0.00 N
ATOM 404 C5 A 13 25.456 15.411 -8.203 1.00 0.00 C
ATOM 405 C6 A 13 24.783 16.309 -7.365 1.00 0.00 C
ATOM 406 N6 A 13 24.048 17.324 -7.820 1.00 0.00 N
ATOM 407 N1 A 13 24.896 16.115 -6.041 1.00 0.00 N
ATOM 408 C2 A 13 25.627 15.104 -5.571 1.00 0.00 C
ATOM 409 N3 A 13 26.290 14.202 -6.269 1.00 0.00 N
ATOM 410 C4 A 13 26.166 14.412 -7.584 1.00 0.00 C
ATOM 411 1H5* A 13 31.198 11.713 -10.511 1.00 0.00 H
ATOM 412 2H5* A 13 29.625 12.287 -11.095 1.00 0.00 H
ATOM 413 H4* A 13 30.393 11.224 -8.384 1.00 0.00 H
ATOM 414 H3* A 13 28.839 10.174 -10.382 1.00 0.00 H
ATOM 415 1H2* A 13 27.187 11.875 -10.443 1.00 0.00 H
ATOM 416 2HO* A 13 26.029 9.977 -9.998 1.00 0.00 H
ATOM 417 H1* A 13 27.154 11.948 -7.421 1.00 0.00 H
ATOM 418 H8 A 13 26.726 13.980 -10.681 1.00 0.00 H
ATOM 419 1H6 A 13 23.582 17.942 -7.171 1.00 0.00 H
ATOM 420 2H6 A 13 23.957 17.476 -8.815 1.00 0.00 H
ATOM 421 H2 A 13 25.718 15.025 -4.491 1.00 0.00 H
ATOM 422 P C 14 28.746 8.040 -8.738 1.00 0.00 P
ATOM 423 O1P C 14 29.625 7.923 -9.924 1.00 0.00 O
ATOM 424 O2P C 14 27.417 7.388 -8.737 1.00 0.00 O
ATOM 425 O5* C 14 29.561 7.526 -7.444 1.00 0.00 O
ATOM 426 C5* C 14 30.941 7.870 -7.256 1.00 0.00 C
ATOM 427 C4* C 14 31.185 8.628 -5.942 1.00 0.00 C
ATOM 428 O4* C 14 30.361 9.798 -5.843 1.00 0.00 O
ATOM 429 C3* C 14 30.808 7.790 -4.720 1.00 0.00 C
ATOM 430 O3* C 14 31.916 6.964 -4.319 1.00 0.00 O
ATOM 431 C2* C 14 30.486 8.862 -3.686 1.00 0.00 C
ATOM 432 O2* C 14 31.671 9.303 -3.009 1.00 0.00 O
ATOM 433 C1* C 14 29.864 9.996 -4.509 1.00 0.00 C
ATOM 434 N1 C 14 28.377 9.960 -4.487 1.00 0.00 N
ATOM 435 C2 C 14 27.730 10.276 -3.297 1.00 0.00 C
ATOM 436 O2 C 14 28.380 10.549 -2.289 1.00 0.00 O
ATOM 437 N3 C 14 26.370 10.282 -3.285 1.00 0.00 N
ATOM 438 C4 C 14 25.667 10.000 -4.388 1.00 0.00 C
ATOM 439 N4 C 14 24.334 9.999 -4.323 1.00 0.00 N
ATOM 440 C5 C 14 26.326 9.681 -5.621 1.00 0.00 C
ATOM 441 C6 C 14 27.674 9.666 -5.621 1.00 0.00 C
ATOM 442 1H5* C 14 31.274 8.490 -8.090 1.00 0.00 H
ATOM 443 2H5* C 14 31.522 6.955 -7.247 1.00 0.00 H
ATOM 444 H4* C 14 32.234 8.923 -5.879 1.00 0.00 H
ATOM 445 H3* C 14 29.919 7.188 -4.929 1.00 0.00 H
ATOM 446 1H2* C 14 29.758 8.477 -2.969 1.00 0.00 H
ATOM 447 2HO* C 14 31.394 9.875 -2.291 1.00 0.00 H
ATOM 448 H1* C 14 30.211 10.959 -4.133 1.00 0.00 H
ATOM 449 1H4 C 14 23.788 9.774 -5.140 1.00 0.00 H
ATOM 450 2H4 C 14 23.870 10.216 -3.449 1.00 0.00 H
ATOM 451 H5 C 14 25.761 9.508 -6.542 1.00 0.00 H
ATOM 452 H6 C 14 28.212 9.392 -6.529 1.00 0.00 H
ATOM 453 P C 15 31.719 5.402 -3.957 1.00 0.00 P
ATOM 454 O1P C 15 33.013 4.715 -4.167 1.00 0.00 O
ATOM 455 O2P C 15 30.505 4.908 -4.646 1.00 0.00 O
ATOM 456 O5* C 15 31.415 5.441 -2.371 1.00 0.00 O
ATOM 457 C5* C 15 32.446 5.757 -1.422 1.00 0.00 C
ATOM 458 C4* C 15 31.871 6.019 -0.022 1.00 0.00 C
ATOM 459 O4* C 15 30.766 6.936 -0.065 1.00 0.00 O
ATOM 460 C3* C 15 31.284 4.752 0.604 1.00 0.00 C
ATOM 461 O3* C 15 32.277 3.986 1.310 1.00 0.00 O
ATOM 462 C2* C 15 30.252 5.327 1.564 1.00 0.00 C
ATOM 463 O2* C 15 30.848 5.659 2.826 1.00 0.00 O
ATOM 464 C1* C 15 29.722 6.578 0.856 1.00 0.00 C
ATOM 465 N1 C 15 28.433 6.316 0.152 1.00 0.00 N
ATOM 466 C2 C 15 27.307 6.054 0.933 1.00 0.00 C
ATOM 467 O2 C 15 27.389 6.058 2.160 1.00 0.00 O
ATOM 468 N3 C 15 26.125 5.807 0.305 1.00 0.00 N
ATOM 469 C4 C 15 26.039 5.814 -1.032 1.00 0.00 C
ATOM 470 N4 C 15 24.864 5.567 -1.612 1.00 0.00 N
ATOM 471 C5 C 15 27.188 6.085 -1.843 1.00 0.00 C
ATOM 472 C6 C 15 28.356 6.330 -1.216 1.00 0.00 C
ATOM 473 1H5* C 15 32.980 6.647 -1.757 1.00 0.00 H
ATOM 474 2H5* C 15 33.149 4.923 -1.368 1.00 0.00 H
ATOM 475 H4* C 15 32.651 6.426 0.625 1.00 0.00 H
ATOM 476 H3* C 15 30.788 4.145 -0.162 1.00 0.00 H
ATOM 477 1H2* C 15 29.443 4.608 1.705 1.00 0.00 H
ATOM 478 2HO* C 15 30.135 5.881 3.429 1.00 0.00 H
ATOM 479 H1* C 15 29.590 7.384 1.583 1.00 0.00 H
ATOM 480 1H4 C 15 24.787 5.570 -2.619 1.00 0.00 H
ATOM 481 2H4 C 15 24.052 5.375 -1.044 1.00 0.00 H
ATOM 482 H5 C 15 27.120 6.093 -2.932 1.00 0.00 H
ATOM 483 H6 C 15 29.245 6.553 -1.807 1.00 0.00 H
ATOM 484 P U 16 32.239 2.370 1.327 1.00 0.00 P
ATOM 485 O1P U 16 33.340 1.894 2.196 1.00 0.00 O
ATOM 486 O2P U 16 32.151 1.891 -0.072 1.00 0.00 O
ATOM 487 O5* U 16 30.835 2.048 2.060 1.00 0.00 O
ATOM 488 C5* U 16 30.717 2.070 3.491 1.00 0.00 C
ATOM 489 C4* U 16 29.251 1.992 3.949 1.00 0.00 C
ATOM 490 O4* U 16 28.384 2.751 3.092 1.00 0.00 O
ATOM 491 C3* U 16 28.697 0.566 3.878 1.00 0.00 C
ATOM 492 O3* U 16 29.025 -0.175 5.067 1.00 0.00 O
ATOM 493 C2* U 16 27.200 0.829 3.756 1.00 0.00 C
ATOM 494 O2* U 16 26.599 1.011 5.045 1.00 0.00 O
ATOM 495 C1* U 16 27.110 2.108 2.919 1.00 0.00 C
ATOM 496 N1 U 16 26.823 1.816 1.483 1.00 0.00 N
ATOM 497 C2 U 16 25.498 1.595 1.127 1.00 0.00 C
ATOM 498 O2 U 16 24.584 1.626 1.950 1.00 0.00 O
ATOM 499 N3 U 16 25.262 1.334 -0.212 1.00 0.00 N
ATOM 500 C4 U 16 26.213 1.273 -1.216 1.00 0.00 C
ATOM 501 O4 U 16 25.887 1.032 -2.377 1.00 0.00 O
ATOM 502 C5 U 16 27.564 1.513 -0.761 1.00 0.00 C
ATOM 503 C6 U 16 27.827 1.773 0.545 1.00 0.00 C
ATOM 504 1H5* U 16 31.156 2.996 3.868 1.00 0.00 H
ATOM 505 2H5* U 16 31.268 1.225 3.908 1.00 0.00 H
ATOM 506 H4* U 16 29.167 2.371 4.969 1.00 0.00 H
ATOM 507 H3* U 16 29.068 0.058 2.979 1.00 0.00 H
ATOM 508 1H2* U 16 26.719 0.003 3.226 1.00 0.00 H
ATOM 509 2HO* U 16 25.648 1.034 4.917 1.00 0.00 H
ATOM 510 H1* U 16 26.326 2.752 3.326 1.00 0.00 H
ATOM 511 H3 U 16 24.300 1.173 -0.483 1.00 0.00 H
ATOM 512 H5 U 16 28.385 1.485 -1.479 1.00 0.00 H
ATOM 513 H6 U 16 28.857 1.950 0.851 1.00 0.00 H
ATOM 514 P A 17 28.993 -1.792 5.089 1.00 0.00 P
ATOM 515 O1P A 17 29.952 -2.257 6.118 1.00 0.00 O
ATOM 516 O2P A 17 29.116 -2.284 3.697 1.00 0.00 O
ATOM 517 O5* A 17 27.495 -2.113 5.604 1.00 0.00 O
ATOM 518 C5* A 17 27.111 -1.892 6.970 1.00 0.00 C
ATOM 519 C4* A 17 25.653 -2.303 7.229 1.00 0.00 C
ATOM 520 O4* A 17 24.758 -1.701 6.281 1.00 0.00 O
ATOM 521 C3* A 17 25.445 -3.806 7.077 1.00 0.00 C
ATOM 522 O3* A 17 25.756 -4.478 8.311 1.00 0.00 O
ATOM 523 C2* A 17 23.962 -3.866 6.726 1.00 0.00 C
ATOM 524 O2* A 17 23.150 -3.848 7.907 1.00 0.00 O
ATOM 525 C1* A 17 23.728 -2.616 5.875 1.00 0.00 C
ATOM 526 N9 A 17 23.815 -2.914 4.421 1.00 0.00 N
ATOM 527 C8 A 17 24.831 -2.680 3.545 1.00 0.00 C
ATOM 528 N7 A 17 24.655 -3.039 2.318 1.00 0.00 N
ATOM 529 C5 A 17 23.368 -3.581 2.358 1.00 0.00 C
ATOM 530 C6 A 17 22.551 -4.157 1.377 1.00 0.00 C
ATOM 531 N6 A 17 22.927 -4.293 0.105 1.00 0.00 N
ATOM 532 N1 A 17 21.335 -4.587 1.757 1.00 0.00 N
ATOM 533 C2 A 17 20.941 -4.463 3.027 1.00 0.00 C
ATOM 534 N3 A 17 21.631 -3.936 4.035 1.00 0.00 N
ATOM 535 C4 A 17 22.846 -3.510 3.631 1.00 0.00 C
ATOM 536 1H5* A 17 27.226 -0.832 7.205 1.00 0.00 H
ATOM 537 2H5* A 17 27.766 -2.471 7.625 1.00 0.00 H
ATOM 538 H4* A 17 25.363 -2.005 8.231 1.00 0.00 H
ATOM 539 H3* A 17 26.048 -4.193 6.248 1.00 0.00 H
ATOM 540 1H2* A 17 23.755 -4.760 6.138 1.00 0.00 H
ATOM 541 2HO* A 17 22.244 -4.013 7.635 1.00 0.00 H
ATOM 542 H1* A 17 22.748 -2.193 6.109 1.00 0.00 H
ATOM 543 H8 A 17 25.758 -2.205 3.865 1.00 0.00 H
ATOM 544 1H6 A 17 22.300 -4.715 -0.565 1.00 0.00 H
ATOM 545 2H6 A 17 23.839 -3.974 -0.191 1.00 0.00 H
ATOM 546 H2 A 17 19.938 -4.827 3.262 1.00 0.00 H
ATOM 547 P U 18 26.538 -5.892 8.327 1.00 0.00 P
ATOM 548 O1P U 18 26.683 -6.322 9.737 1.00 0.00 O
ATOM 549 O2P U 18 27.740 -5.772 7.470 1.00 0.00 O
ATOM 550 O5* U 18 25.495 -6.886 7.598 1.00 0.00 O
ATOM 551 C5* U 18 24.294 -7.317 8.256 1.00 0.00 C
ATOM 552 C4* U 18 23.245 -7.824 7.257 1.00 0.00 C
ATOM 553 O4* U 18 23.032 -6.889 6.188 1.00 0.00 O
ATOM 554 C3* U 18 23.694 -9.107 6.552 1.00 0.00 C
ATOM 555 O3* U 18 23.374 -10.289 7.311 1.00 0.00 O
ATOM 556 C2* U 18 22.884 -9.044 5.263 1.00 0.00 C
ATOM 557 O2* U 18 21.575 -9.599 5.447 1.00 0.00 O
ATOM 558 C1* U 18 22.811 -7.551 4.933 1.00 0.00 C
ATOM 559 N1 U 18 23.820 -7.152 3.908 1.00 0.00 N
ATOM 560 C2 U 18 23.539 -7.458 2.581 1.00 0.00 C
ATOM 561 O2 U 18 22.503 -8.034 2.247 1.00 0.00 O
ATOM 562 N3 U 18 24.489 -7.077 1.651 1.00 0.00 N
ATOM 563 C4 U 18 25.681 -6.425 1.918 1.00 0.00 C
ATOM 564 O4 U 18 26.454 -6.134 1.007 1.00 0.00 O
ATOM 565 C5 U 18 25.897 -6.142 3.319 1.00 0.00 C
ATOM 566 C6 U 18 24.983 -6.503 4.256 1.00 0.00 C
ATOM 567 1H5* U 18 23.874 -6.478 8.815 1.00 0.00 H
ATOM 568 2H5* U 18 24.540 -8.119 8.955 1.00 0.00 H
ATOM 569 H4* U 18 22.300 -7.993 7.774 1.00 0.00 H
ATOM 570 H3* U 18 24.765 -9.062 6.325 1.00 0.00 H
ATOM 571 1H2* U 18 23.413 -9.576 4.470 1.00 0.00 H
ATOM 572 2HO* U 18 21.670 -10.555 5.471 1.00 0.00 H
ATOM 573 H1* U 18 21.807 -7.309 4.574 1.00 0.00 H
ATOM 574 H3 U 18 24.291 -7.293 0.681 1.00 0.00 H
ATOM 575 H5 U 18 26.810 -5.631 3.629 1.00 0.00 H
ATOM 576 H6 U 18 25.173 -6.258 5.304 1.00 0.00 H
ATOM 577 P G 19 24.346 -11.580 7.312 1.00 0.00 P
ATOM 578 O1P G 19 24.010 -12.406 8.495 1.00 0.00 O
ATOM 579 O2P G 19 25.739 -11.120 7.112 1.00 0.00 O
ATOM 580 O5* G 19 23.883 -12.376 5.982 1.00 0.00 O
ATOM 581 C5* G 19 23.221 -13.652 6.066 1.00 0.00 C
ATOM 582 C4* G 19 22.809 -14.197 4.694 1.00 0.00 C
ATOM 583 O4* G 19 22.387 -13.150 3.808 1.00 0.00 O
ATOM 584 C3* G 19 23.980 -14.852 3.954 1.00 0.00 C
ATOM 585 O3* G 19 24.213 -16.220 4.336 1.00 0.00 O
ATOM 586 C2* G 19 23.494 -14.774 2.513 1.00 0.00 C
ATOM 587 O2* G 19 22.622 -15.866 2.197 1.00 0.00 O
ATOM 588 C1* G 19 22.756 -13.437 2.447 1.00 0.00 C
ATOM 589 N9 G 19 23.620 -12.369 1.877 1.00 0.00 N
ATOM 590 C8 G 19 24.415 -11.464 2.507 1.00 0.00 C
ATOM 591 N7 G 19 25.082 -10.639 1.773 1.00 0.00 N
ATOM 592 C5 G 19 24.701 -11.024 0.485 1.00 0.00 C
ATOM 593 C6 G 19 25.095 -10.496 -0.775 1.00 0.00 C
ATOM 594 O6 G 19 25.871 -9.570 -1.004 1.00 0.00 O
ATOM 595 N1 G 19 24.481 -11.170 -1.824 1.00 0.00 N
ATOM 596 C2 G 19 23.594 -12.221 -1.685 1.00 0.00 C
ATOM 597 N2 G 19 23.107 -12.739 -2.815 1.00 0.00 N
ATOM 598 N3 G 19 23.218 -12.722 -0.504 1.00 0.00 N
ATOM 599 C4 G 19 23.805 -12.081 0.536 1.00 0.00 C
ATOM 600 1H5* G 19 22.311 -13.546 6.644 1.00 0.00 H
ATOM 601 2H5* G 19 23.894 -14.363 6.569 1.00 0.00 H
ATOM 602 H4* G 19 21.997 -14.916 4.812 1.00 0.00 H
ATOM 603 H3* G 19 24.887 -14.248 4.076 1.00 0.00 H
ATOM 604 1H2* G 19 24.350 -14.760 1.833 1.00 0.00 H
ATOM 605 2HO* G 19 22.486 -15.860 1.246 1.00 0.00 H
ATOM 606 H1* G 19 21.854 -13.544 1.842 1.00 0.00 H
ATOM 607 H8 G 19 24.490 -11.435 3.595 1.00 0.00 H
ATOM 608 H1 G 19 24.716 -10.852 -2.751 1.00 0.00 H
ATOM 609 1H2 G 19 22.456 -13.510 -2.777 1.00 0.00 H
ATOM 610 2H2 G 19 23.392 -12.361 -3.708 1.00 0.00 H
ATOM 611 P C 20 25.686 -16.880 4.233 1.00 0.00 P
ATOM 612 O1P C 20 25.634 -18.216 4.870 1.00 0.00 O
ATOM 613 O2P C 20 26.678 -15.885 4.698 1.00 0.00 O
ATOM 614 O5* C 20 25.882 -17.081 2.640 1.00 0.00 O
ATOM 615 C5* C 20 25.335 -18.223 1.964 1.00 0.00 C
ATOM 616 C4* C 20 25.611 -18.194 0.451 1.00 0.00 C
ATOM 617 O4* C 20 25.236 -16.940 -0.144 1.00 0.00 O
ATOM 618 C3* C 20 27.103 -18.328 0.127 1.00 0.00 C
ATOM 619 O3* C 20 27.549 -19.698 0.164 1.00 0.00 O
ATOM 620 C2* C 20 27.121 -17.766 -1.290 1.00 0.00 C
ATOM 621 O2* C 20 26.757 -18.765 -2.252 1.00 0.00 O
ATOM 622 C1* C 20 26.097 -16.627 -1.254 1.00 0.00 C
ATOM 623 N1 C 20 26.747 -15.292 -1.105 1.00 0.00 N
ATOM 624 C2 C 20 27.208 -14.670 -2.264 1.00 0.00 C
ATOM 625 O2 C 20 27.079 -15.220 -3.356 1.00 0.00 O
ATOM 626 N3 C 20 27.800 -13.449 -2.153 1.00 0.00 N
ATOM 627 C4 C 20 27.940 -12.856 -0.961 1.00 0.00 C
ATOM 628 N4 C 20 28.526 -11.659 -0.895 1.00 0.00 N
ATOM 629 C5 C 20 27.471 -13.484 0.235 1.00 0.00 C
ATOM 630 C6 C 20 26.885 -14.693 0.120 1.00 0.00 C
ATOM 631 1H5* C 20 24.256 -18.244 2.124 1.00 0.00 H
ATOM 632 2H5* C 20 25.771 -19.130 2.387 1.00 0.00 H
ATOM 633 H4* C 20 25.056 -18.999 -0.034 1.00 0.00 H
ATOM 634 H3* C 20 27.698 -17.695 0.796 1.00 0.00 H
ATOM 635 1H2* C 20 28.114 -17.367 -1.514 1.00 0.00 H
ATOM 636 2HO* C 20 25.840 -18.999 -2.091 1.00 0.00 H
ATOM 637 H1* C 20 25.508 -16.645 -2.175 1.00 0.00 H
ATOM 638 1H4 C 20 28.640 -11.200 -0.004 1.00 0.00 H
ATOM 639 2H4 C 20 28.858 -11.212 -1.738 1.00 0.00 H
ATOM 640 H5 C 20 27.584 -13.002 1.207 1.00 0.00 H
ATOM 641 H6 C 20 26.515 -15.194 1.013 1.00 0.00 H
ATOM 642 P C 21 29.106 -20.075 0.387 1.00 0.00 P
ATOM 643 O1P C 21 29.192 -21.528 0.664 1.00 0.00 O
ATOM 644 O2P C 21 29.688 -19.111 1.347 1.00 0.00 O
ATOM 645 O5* C 21 29.757 -19.794 -1.065 1.00 0.00 O
ATOM 646 C5* C 21 29.562 -20.704 -2.159 1.00 0.00 C
ATOM 647 C4* C 21 29.991 -20.090 -3.501 1.00 0.00 C
ATOM 648 O4* C 21 29.684 -18.689 -3.574 1.00 0.00 O
ATOM 649 C3* C 21 31.505 -20.153 -3.707 1.00 0.00 C
ATOM 650 O3* C 21 31.915 -21.419 -4.241 1.00 0.00 O
ATOM 651 C2* C 21 31.720 -19.028 -4.710 1.00 0.00 C
ATOM 652 O2* C 21 31.499 -19.481 -6.052 1.00 0.00 O
ATOM 653 C1* C 21 30.691 -17.968 -4.305 1.00 0.00 C
ATOM 654 N1 C 21 31.301 -16.871 -3.494 1.00 0.00 N
ATOM 655 C2 C 21 31.856 -15.796 -4.186 1.00 0.00 C
ATOM 656 O2 C 21 31.842 -15.776 -5.415 1.00 0.00 O
ATOM 657 N3 C 21 32.408 -14.779 -3.469 1.00 0.00 N
ATOM 658 C4 C 21 32.423 -14.807 -2.131 1.00 0.00 C
ATOM 659 N4 C 21 32.976 -13.791 -1.465 1.00 0.00 N
ATOM 660 C5 C 21 31.858 -15.906 -1.409 1.00 0.00 C
ATOM 661 C6 C 21 31.311 -16.910 -2.123 1.00 0.00 C
ATOM 662 1H5* C 21 28.504 -20.970 -2.214 1.00 0.00 H
ATOM 663 2H5* C 21 30.143 -21.610 -1.978 1.00 0.00 H
ATOM 664 H4* C 21 29.485 -20.610 -4.318 1.00 0.00 H
ATOM 665 H3* C 21 32.032 -19.932 -2.770 1.00 0.00 H
ATOM 666 1H2* C 21 32.733 -18.626 -4.605 1.00 0.00 H
ATOM 667 2HO* C 21 31.753 -18.767 -6.642 1.00 0.00 H
ATOM 668 H1* C 21 30.237 -17.545 -5.205 1.00 0.00 H
ATOM 669 1H4 C 21 32.994 -13.798 -0.455 1.00 0.00 H
ATOM 670 2H4 C 21 33.376 -13.013 -1.971 1.00 0.00 H
ATOM 671 H5 C 21 31.869 -15.929 -0.318 1.00 0.00 H
ATOM 672 H6 C 21 30.873 -17.760 -1.601 1.00 0.00 H
ATOM 673 H3T C 21 32.875 -21.422 -4.267 1.00 0.00 H
TER 674 C 21
ENDMDL
MODEL 2
ATOM 675 O5* G 1 37.008 -12.325 -11.644 1.00 0.00 O
ATOM 676 C5* G 1 35.778 -11.791 -11.135 1.00 0.00 C
ATOM 677 C4* G 1 34.582 -12.698 -11.437 1.00 0.00 C
ATOM 678 O4* G 1 34.720 -13.979 -10.804 1.00 0.00 O
ATOM 679 C3* G 1 33.275 -12.133 -10.875 1.00 0.00 C
ATOM 680 O3* G 1 32.656 -11.221 -11.801 1.00 0.00 O
ATOM 681 C2* G 1 32.443 -13.395 -10.683 1.00 0.00 C
ATOM 682 O2* G 1 31.758 -13.753 -11.891 1.00 0.00 O
ATOM 683 C1* G 1 33.467 -14.461 -10.291 1.00 0.00 C
ATOM 684 N9 G 1 33.522 -14.660 -8.818 1.00 0.00 N
ATOM 685 C8 G 1 34.370 -14.124 -7.898 1.00 0.00 C
ATOM 686 N7 G 1 34.209 -14.467 -6.663 1.00 0.00 N
ATOM 687 C5 G 1 33.121 -15.342 -6.745 1.00 0.00 C
ATOM 688 C6 G 1 32.453 -16.062 -5.716 1.00 0.00 C
ATOM 689 O6 G 1 32.698 -16.070 -4.511 1.00 0.00 O
ATOM 690 N1 G 1 31.408 -16.828 -6.223 1.00 0.00 N
ATOM 691 C2 G 1 31.047 -16.895 -7.556 1.00 0.00 C
ATOM 692 N2 G 1 30.014 -17.687 -7.852 1.00 0.00 N
ATOM 693 N3 G 1 31.669 -16.220 -8.527 1.00 0.00 N
ATOM 694 C4 G 1 32.692 -15.467 -8.059 1.00 0.00 C
ATOM 695 1H5* G 1 35.579 -10.837 -11.606 1.00 0.00 H
ATOM 696 2H5* G 1 35.887 -11.650 -10.048 1.00 0.00 H
ATOM 697 H4* G 1 34.492 -12.838 -12.516 1.00 0.00 H
ATOM 698 H3* G 1 33.455 -11.650 -9.907 1.00 0.00 H
ATOM 699 1H2* G 1 31.730 -13.248 -9.869 1.00 0.00 H
ATOM 700 2HO* G 1 30.920 -14.147 -11.638 1.00 0.00 H
ATOM 701 H1* G 1 33.214 -15.405 -10.780 1.00 0.00 H
ATOM 702 H8 G 1 35.160 -13.430 -8.191 1.00 0.00 H
ATOM 703 H1 G 1 30.887 -17.371 -5.548 1.00 0.00 H
ATOM 704 1H2 G 1 29.705 -17.775 -8.809 1.00 0.00 H
ATOM 705 2H2 G 1 29.543 -18.197 -7.120 1.00 0.00 H
ATOM 706 H5T G 1 36.972 -12.266 -12.601 1.00 0.00 H
ATOM 707 P G 2 31.597 -10.105 -11.305 1.00 0.00 P
ATOM 708 O1P G 2 31.385 -9.148 -12.416 1.00 0.00 O
ATOM 709 O2P G 2 32.027 -9.603 -9.980 1.00 0.00 O
ATOM 710 O5* G 2 30.241 -10.961 -11.103 1.00 0.00 O
ATOM 711 C5* G 2 29.403 -11.311 -12.220 1.00 0.00 C
ATOM 712 C4* G 2 28.254 -12.246 -11.831 1.00 0.00 C
ATOM 713 O4* G 2 28.692 -13.298 -10.958 1.00 0.00 O
ATOM 714 C3* G 2 27.167 -11.521 -11.033 1.00 0.00 C
ATOM 715 O3* G 2 26.224 -10.863 -11.900 1.00 0.00 O
ATOM 716 C2* G 2 26.527 -12.672 -10.268 1.00 0.00 C
ATOM 717 O2* G 2 25.523 -13.325 -11.057 1.00 0.00 O
ATOM 718 C1* G 2 27.697 -13.614 -9.968 1.00 0.00 C
ATOM 719 N9 G 2 28.219 -13.421 -8.588 1.00 0.00 N
ATOM 720 C8 G 2 29.283 -12.693 -8.154 1.00 0.00 C
ATOM 721 N7 G 2 29.533 -12.693 -6.887 1.00 0.00 N
ATOM 722 C5 G 2 28.519 -13.519 -6.392 1.00 0.00 C
ATOM 723 C6 G 2 28.244 -13.918 -5.055 1.00 0.00 C
ATOM 724 O6 G 2 28.853 -13.616 -4.030 1.00 0.00 O
ATOM 725 N1 G 2 27.135 -14.753 -4.989 1.00 0.00 N
ATOM 726 C2 G 2 26.378 -15.157 -6.074 1.00 0.00 C
ATOM 727 N2 G 2 25.346 -15.961 -5.811 1.00 0.00 N
ATOM 728 N3 G 2 26.631 -14.786 -7.334 1.00 0.00 N
ATOM 729 C4 G 2 27.709 -13.971 -7.423 1.00 0.00 C
ATOM 730 1H5* G 2 29.996 -11.836 -12.961 1.00 0.00 H
ATOM 731 2H5* G 2 29.003 -10.384 -12.662 1.00 0.00 H
ATOM 732 H4* G 2 27.820 -12.686 -12.731 1.00 0.00 H
ATOM 733 H3* G 2 27.622 -10.811 -10.332 1.00 0.00 H
ATOM 734 1H2* G 2 26.097 -12.302 -9.333 1.00 0.00 H
ATOM 735 2HO* G 2 25.111 -13.992 -10.501 1.00 0.00 H
ATOM 736 H1* G 2 27.375 -14.649 -10.099 1.00 0.00 H
ATOM 737 H8 G 2 29.908 -12.132 -8.849 1.00 0.00 H
ATOM 738 H1 G 2 26.879 -15.079 -4.068 1.00 0.00 H
ATOM 739 1H2 G 2 24.757 -16.290 -6.562 1.00 0.00 H
ATOM 740 2H2 G 2 25.155 -16.243 -4.859 1.00 0.00 H
ATOM 741 P C 3 25.601 -9.419 -11.527 1.00 0.00 P
ATOM 742 O1P C 3 25.067 -8.814 -12.769 1.00 0.00 O
ATOM 743 O2P C 3 26.592 -8.675 -10.717 1.00 0.00 O
ATOM 744 O5* C 3 24.357 -9.804 -10.570 1.00 0.00 O
ATOM 745 C5* C 3 23.094 -10.207 -11.119 1.00 0.00 C
ATOM 746 C4* C 3 22.246 -10.979 -10.096 1.00 0.00 C
ATOM 747 O4* C 3 23.056 -11.826 -9.267 1.00 0.00 O
ATOM 748 C3* C 3 21.535 -10.046 -9.110 1.00 0.00 C
ATOM 749 O3* C 3 20.295 -9.540 -9.639 1.00 0.00 O
ATOM 750 C2* C 3 21.302 -10.992 -7.937 1.00 0.00 C
ATOM 751 O2* C 3 20.101 -11.756 -8.115 1.00 0.00 O
ATOM 752 C1* C 3 22.538 -11.897 -7.928 1.00 0.00 C
ATOM 753 N1 C 3 23.542 -11.462 -6.911 1.00 0.00 N
ATOM 754 C2 C 3 23.422 -11.988 -5.627 1.00 0.00 C
ATOM 755 O2 C 3 22.515 -12.776 -5.364 1.00 0.00 O
ATOM 756 N3 C 3 24.325 -11.608 -4.684 1.00 0.00 N
ATOM 757 C4 C 3 25.310 -10.749 -4.974 1.00 0.00 C
ATOM 758 N4 C 3 26.172 -10.399 -4.019 1.00 0.00 N
ATOM 759 C5 C 3 25.444 -10.201 -6.290 1.00 0.00 C
ATOM 760 C6 C 3 24.547 -10.580 -7.223 1.00 0.00 C
ATOM 761 1H5* C 3 23.270 -10.847 -11.985 1.00 0.00 H
ATOM 762 2H5* C 3 22.547 -9.319 -11.442 1.00 0.00 H
ATOM 763 H4* C 3 21.509 -11.590 -10.621 1.00 0.00 H
ATOM 764 H3* C 3 22.202 -9.229 -8.810 1.00 0.00 H
ATOM 765 1H2* C 3 21.254 -10.421 -7.007 1.00 0.00 H
ATOM 766 2HO* C 3 20.243 -12.346 -8.859 1.00 0.00 H
ATOM 767 H1* C 3 22.232 -12.925 -7.721 1.00 0.00 H
ATOM 768 1H4 C 3 26.918 -9.750 -4.223 1.00 0.00 H
ATOM 769 2H4 C 3 26.078 -10.784 -3.088 1.00 0.00 H
ATOM 770 H5 C 3 26.246 -9.501 -6.530 1.00 0.00 H
ATOM 771 H6 C 3 24.625 -10.180 -8.233 1.00 0.00 H
ATOM 772 P G 4 19.644 -8.163 -9.094 1.00 0.00 P
ATOM 773 O1P G 4 18.604 -7.733 -10.057 1.00 0.00 O
ATOM 774 O2P G 4 20.741 -7.233 -8.737 1.00 0.00 O
ATOM 775 O5* G 4 18.912 -8.625 -7.728 1.00 0.00 O
ATOM 776 C5* G 4 17.694 -9.392 -7.759 1.00 0.00 C
ATOM 777 C4* G 4 17.404 -10.094 -6.429 1.00 0.00 C
ATOM 778 O4* G 4 18.608 -10.564 -5.802 1.00 0.00 O
ATOM 779 C3* G 4 16.784 -9.148 -5.396 1.00 0.00 C
ATOM 780 O3* G 4 15.354 -9.046 -5.548 1.00 0.00 O
ATOM 781 C2* G 4 17.148 -9.851 -4.094 1.00 0.00 C
ATOM 782 O2* G 4 16.192 -10.871 -3.771 1.00 0.00 O
ATOM 783 C1* G 4 18.527 -10.452 -4.372 1.00 0.00 C
ATOM 784 N9 G 4 19.622 -9.612 -3.818 1.00 0.00 N
ATOM 785 C8 G 4 20.416 -8.692 -4.429 1.00 0.00 C
ATOM 786 N7 G 4 21.319 -8.109 -3.711 1.00 0.00 N
ATOM 787 C5 G 4 21.118 -8.699 -2.458 1.00 0.00 C
ATOM 788 C6 G 4 21.800 -8.482 -1.229 1.00 0.00 C
ATOM 789 O6 G 4 22.733 -7.713 -0.997 1.00 0.00 O
ATOM 790 N1 G 4 21.285 -9.279 -0.212 1.00 0.00 N
ATOM 791 C2 G 4 20.244 -10.175 -0.356 1.00 0.00 C
ATOM 792 N2 G 4 19.892 -10.852 0.738 1.00 0.00 N
ATOM 793 N3 G 4 19.600 -10.385 -1.506 1.00 0.00 N
ATOM 794 C4 G 4 20.082 -9.620 -2.513 1.00 0.00 C
ATOM 795 1H5* G 4 17.777 -10.167 -8.510 1.00 0.00 H
ATOM 796 2H5* G 4 16.864 -8.717 -8.020 1.00 0.00 H
ATOM 797 H4* G 4 16.737 -10.941 -6.601 1.00 0.00 H
ATOM 798 H3* G 4 17.262 -8.163 -5.442 1.00 0.00 H
ATOM 799 1H2* G 4 17.216 -9.122 -3.284 1.00 0.00 H
ATOM 800 2HO* G 4 16.390 -11.175 -2.881 1.00 0.00 H
ATOM 801 H1* G 4 18.578 -11.447 -3.932 1.00 0.00 H
ATOM 802 H8 G 4 20.294 -8.449 -5.485 1.00 0.00 H
ATOM 803 H1 G 4 21.718 -9.178 0.693 1.00 0.00 H
ATOM 804 1H2 G 4 20.379 -10.694 1.610 1.00 0.00 H
ATOM 805 2H2 G 4 19.138 -11.524 0.697 1.00 0.00 H
ATOM 806 P U 5 14.561 -7.681 -5.200 1.00 0.00 P
ATOM 807 O1P U 5 13.126 -7.896 -5.497 1.00 0.00 O
ATOM 808 O2P U 5 15.277 -6.549 -5.832 1.00 0.00 O
ATOM 809 O5* U 5 14.740 -7.557 -3.598 1.00 0.00 O
ATOM 810 C5* U 5 13.691 -7.942 -2.694 1.00 0.00 C
ATOM 811 C4* U 5 13.954 -7.447 -1.263 1.00 0.00 C
ATOM 812 O4* U 5 15.270 -7.801 -0.808 1.00 0.00 O
ATOM 813 C3* U 5 13.921 -5.918 -1.168 1.00 0.00 C
ATOM 814 O3* U 5 12.578 -5.438 -0.963 1.00 0.00 O
ATOM 815 C2* U 5 14.806 -5.663 0.046 1.00 0.00 C
ATOM 816 O2* U 5 14.052 -5.744 1.264 1.00 0.00 O
ATOM 817 C1* U 5 15.869 -6.760 -0.017 1.00 0.00 C
ATOM 818 N1 U 5 17.145 -6.276 -0.615 1.00 0.00 N
ATOM 819 C2 U 5 18.017 -5.575 0.208 1.00 0.00 C
ATOM 820 O2 U 5 17.752 -5.322 1.383 1.00 0.00 O
ATOM 821 N3 U 5 19.208 -5.171 -0.369 1.00 0.00 N
ATOM 822 C4 U 5 19.604 -5.402 -1.677 1.00 0.00 C
ATOM 823 O4 U 5 20.693 -4.997 -2.083 1.00 0.00 O
ATOM 824 C5 U 5 18.638 -6.137 -2.463 1.00 0.00 C
ATOM 825 C6 U 5 17.463 -6.542 -1.923 1.00 0.00 C
ATOM 826 1H5* U 5 13.616 -9.031 -2.684 1.00 0.00 H
ATOM 827 2H5* U 5 12.744 -7.527 -3.047 1.00 0.00 H
ATOM 828 H4* U 5 13.212 -7.875 -0.585 1.00 0.00 H
ATOM 829 H3* U 5 14.368 -5.472 -2.063 1.00 0.00 H
ATOM 830 1H2* U 5 15.277 -4.682 -0.042 1.00 0.00 H
ATOM 831 2HO* U 5 13.710 -6.639 1.331 1.00 0.00 H
ATOM 832 H1* U 5 16.058 -7.137 0.990 1.00 0.00 H
ATOM 833 H3 U 5 19.849 -4.657 0.218 1.00 0.00 H
ATOM 834 H5 U 5 18.863 -6.384 -3.502 1.00 0.00 H
ATOM 835 H6 U 5 16.755 -7.083 -2.546 1.00 0.00 H
ATOM 836 P A 6 12.187 -3.888 -1.211 1.00 0.00 P
ATOM 837 O1P A 6 10.715 -3.766 -1.112 1.00 0.00 O
ATOM 838 O2P A 6 12.880 -3.421 -2.433 1.00 0.00 O
ATOM 839 O5* A 6 12.848 -3.140 0.060 1.00 0.00 O
ATOM 840 C5* A 6 12.211 -3.149 1.348 1.00 0.00 C
ATOM 841 C4* A 6 13.092 -2.495 2.425 1.00 0.00 C
ATOM 842 O4* A 6 14.452 -2.942 2.339 1.00 0.00 O
ATOM 843 C3* A 6 13.164 -0.974 2.252 1.00 0.00 C
ATOM 844 O3* A 6 12.183 -0.340 3.092 1.00 0.00 O
ATOM 845 C2* A 6 14.587 -0.603 2.659 1.00 0.00 C
ATOM 846 O2* A 6 14.605 0.044 3.937 1.00 0.00 O
ATOM 847 C1* A 6 15.381 -1.908 2.702 1.00 0.00 C
ATOM 848 N9 A 6 16.530 -1.858 1.766 1.00 0.00 N
ATOM 849 C8 A 6 16.552 -2.015 0.421 1.00 0.00 C
ATOM 850 N7 A 6 17.692 -1.914 -0.176 1.00 0.00 N
ATOM 851 C5 A 6 18.551 -1.655 0.899 1.00 0.00 C
ATOM 852 C6 A 6 19.931 -1.434 0.977 1.00 0.00 C
ATOM 853 N6 A 6 20.734 -1.440 -0.089 1.00 0.00 N
ATOM 854 N1 A 6 20.454 -1.205 2.195 1.00 0.00 N
ATOM 855 C2 A 6 19.670 -1.195 3.275 1.00 0.00 C
ATOM 856 N3 A 6 18.355 -1.391 3.316 1.00 0.00 N
ATOM 857 C4 A 6 17.854 -1.618 2.084 1.00 0.00 C
ATOM 858 1H5* A 6 12.007 -4.181 1.637 1.00 0.00 H
ATOM 859 2H5* A 6 11.265 -2.607 1.283 1.00 0.00 H
ATOM 860 H4* A 6 12.697 -2.734 3.414 1.00 0.00 H
ATOM 861 H3* A 6 12.998 -0.710 1.203 1.00 0.00 H
ATOM 862 1H2* A 6 15.020 0.055 1.901 1.00 0.00 H
ATOM 863 2HO* A 6 14.170 -0.543 4.561 1.00 0.00 H
ATOM 864 H1* A 6 15.744 -2.083 3.716 1.00 0.00 H
ATOM 865 H8 A 6 15.636 -2.206 -0.137 1.00 0.00 H
ATOM 866 1H6 A 6 21.723 -1.274 0.023 1.00 0.00 H
ATOM 867 2H6 A 6 20.351 -1.610 -1.008 1.00 0.00 H
ATOM 868 H2 A 6 20.162 -1.003 4.230 1.00 0.00 H
ATOM 869 P A 7 11.764 1.207 2.880 1.00 0.00 P
ATOM 870 O1P A 7 10.422 1.404 3.472 1.00 0.00 O
ATOM 871 O2P A 7 12.003 1.572 1.465 1.00 0.00 O
ATOM 872 O5* A 7 12.838 1.986 3.804 1.00 0.00 O
ATOM 873 C5* A 7 13.666 3.034 3.277 1.00 0.00 C
ATOM 874 C4* A 7 14.900 3.262 4.164 1.00 0.00 C
ATOM 875 O4* A 7 15.877 2.226 3.983 1.00 0.00 O
ATOM 876 C3* A 7 15.645 4.552 3.803 1.00 0.00 C
ATOM 877 O3* A 7 15.097 5.691 4.495 1.00 0.00 O
ATOM 878 C2* A 7 17.058 4.234 4.276 1.00 0.00 C
ATOM 879 O2* A 7 17.221 4.541 5.668 1.00 0.00 O
ATOM 880 C1* A 7 17.219 2.735 4.019 1.00 0.00 C
ATOM 881 N9 A 7 17.943 2.467 2.747 1.00 0.00 N
ATOM 882 C8 A 7 17.459 2.277 1.491 1.00 0.00 C
ATOM 883 N7 A 7 18.315 2.068 0.547 1.00 0.00 N
ATOM 884 C5 A 7 19.527 2.120 1.243 1.00 0.00 C
ATOM 885 C6 A 7 20.861 1.974 0.838 1.00 0.00 C
ATOM 886 N6 A 7 21.219 1.739 -0.425 1.00 0.00 N
ATOM 887 N1 A 7 21.811 2.082 1.784 1.00 0.00 N
ATOM 888 C2 A 7 21.477 2.318 3.055 1.00 0.00 C
ATOM 889 N3 A 7 20.250 2.473 3.547 1.00 0.00 N
ATOM 890 C4 A 7 19.313 2.361 2.580 1.00 0.00 C
ATOM 891 1H5* A 7 13.083 3.955 3.226 1.00 0.00 H
ATOM 892 2H5* A 7 13.992 2.762 2.272 1.00 0.00 H
ATOM 893 H4* A 7 14.597 3.291 5.212 1.00 0.00 H
ATOM 894 H3* A 7 15.635 4.706 2.717 1.00 0.00 H
ATOM 895 1H2* A 7 17.782 4.792 3.676 1.00 0.00 H
ATOM 896 2HO* A 7 16.609 3.987 6.157 1.00 0.00 H
ATOM 897 H1* A 7 17.756 2.278 4.851 1.00 0.00 H
ATOM 898 H8 A 7 16.387 2.290 1.287 1.00 0.00 H
ATOM 899 1H6 A 7 22.196 1.643 -0.663 1.00 0.00 H
ATOM 900 2H6 A 7 20.513 1.657 -1.143 1.00 0.00 H
ATOM 901 H2 A 7 22.299 2.386 3.768 1.00 0.00 H
ATOM 902 P G 8 15.447 7.203 4.041 1.00 0.00 P
ATOM 903 O1P G 8 14.403 8.100 4.587 1.00 0.00 O
ATOM 904 O2P G 8 15.726 7.206 2.587 1.00 0.00 O
ATOM 905 O5* G 8 16.832 7.501 4.820 1.00 0.00 O
ATOM 906 C5* G 8 16.850 7.784 6.232 1.00 0.00 C
ATOM 907 C4* G 8 18.238 7.596 6.853 1.00 0.00 C
ATOM 908 O4* G 8 18.934 6.484 6.270 1.00 0.00 O
ATOM 909 C3* G 8 19.154 8.797 6.596 1.00 0.00 C
ATOM 910 O3* G 8 18.995 9.830 7.589 1.00 0.00 O
ATOM 911 C2* G 8 20.534 8.156 6.693 1.00 0.00 C
ATOM 912 O2* G 8 20.992 8.107 8.051 1.00 0.00 O
ATOM 913 C1* G 8 20.338 6.751 6.124 1.00 0.00 C
ATOM 914 N9 G 8 20.771 6.671 4.703 1.00 0.00 N
ATOM 915 C8 G 8 20.045 6.813 3.561 1.00 0.00 C
ATOM 916 N7 G 8 20.673 6.707 2.436 1.00 0.00 N
ATOM 917 C5 G 8 21.984 6.462 2.858 1.00 0.00 C
ATOM 918 C6 G 8 23.163 6.253 2.090 1.00 0.00 C
ATOM 919 O6 G 8 23.284 6.243 0.867 1.00 0.00 O
ATOM 920 N1 G 8 24.271 6.042 2.904 1.00 0.00 N
ATOM 921 C2 G 8 24.251 6.032 4.287 1.00 0.00 C
ATOM 922 N2 G 8 25.415 5.807 4.898 1.00 0.00 N
ATOM 923 N3 G 8 23.147 6.230 5.013 1.00 0.00 N
ATOM 924 C4 G 8 22.054 6.438 4.243 1.00 0.00 C
ATOM 925 1H5* G 8 16.184 7.101 6.745 1.00 0.00 H
ATOM 926 2H5* G 8 16.503 8.818 6.385 1.00 0.00 H
ATOM 927 H4* G 8 18.138 7.432 7.928 1.00 0.00 H
ATOM 928 H3* G 8 18.991 9.190 5.586 1.00 0.00 H
ATOM 929 1H2* G 8 21.242 8.710 6.074 1.00 0.00 H
ATOM 930 2HO* G 8 20.386 7.545 8.538 1.00 0.00 H
ATOM 931 H1* G 8 20.907 6.036 6.721 1.00 0.00 H
ATOM 932 H8 G 8 18.973 7.005 3.590 1.00 0.00 H
ATOM 933 H1 G 8 25.150 5.891 2.427 1.00 0.00 H
ATOM 934 1H2 G 8 25.460 5.785 5.906 1.00 0.00 H
ATOM 935 2H2 G 8 26.250 5.655 4.351 1.00 0.00 H
ATOM 936 P G 9 19.371 11.371 7.273 1.00 0.00 P
ATOM 937 O1P G 9 18.904 12.198 8.410 1.00 0.00 O
ATOM 938 O2P G 9 18.919 11.692 5.901 1.00 0.00 O
ATOM 939 O5* G 9 20.988 11.363 7.282 1.00 0.00 O
ATOM 940 C5* G 9 21.729 11.337 8.516 1.00 0.00 C
ATOM 941 C4* G 9 23.200 10.954 8.316 1.00 0.00 C
ATOM 942 O4* G 9 23.358 9.961 7.292 1.00 0.00 O
ATOM 943 C3* G 9 24.044 12.132 7.832 1.00 0.00 C
ATOM 944 O3* G 9 24.504 12.988 8.895 1.00 0.00 O
ATOM 945 C2* G 9 25.211 11.387 7.193 1.00 0.00 C
ATOM 946 O2* G 9 26.160 10.963 8.181 1.00 0.00 O
ATOM 947 C1* G 9 24.545 10.187 6.512 1.00 0.00 C
ATOM 948 N9 G 9 24.217 10.466 5.085 1.00 0.00 N
ATOM 949 C8 G 9 23.010 10.681 4.496 1.00 0.00 C
ATOM 950 N7 G 9 22.992 10.916 3.226 1.00 0.00 N
ATOM 951 C5 G 9 24.352 10.856 2.902 1.00 0.00 C
ATOM 952 C6 G 9 24.996 11.033 1.646 1.00 0.00 C
ATOM 953 O6 G 9 24.487 11.290 0.555 1.00 0.00 O
ATOM 954 N1 G 9 26.374 10.890 1.755 1.00 0.00 N
ATOM 955 C2 G 9 27.054 10.612 2.927 1.00 0.00 C
ATOM 956 N2 G 9 28.381 10.509 2.832 1.00 0.00 N
ATOM 957 N3 G 9 26.456 10.446 4.111 1.00 0.00 N
ATOM 958 C4 G 9 25.111 10.580 4.031 1.00 0.00 C
ATOM 959 1H5* G 9 21.300 10.595 9.177 1.00 0.00 H
ATOM 960 2H5* G 9 21.657 12.330 8.987 1.00 0.00 H
ATOM 961 H4* G 9 23.608 10.573 9.251 1.00 0.00 H
ATOM 962 H3* G 9 23.499 12.701 7.070 1.00 0.00 H
ATOM 963 1H2* G 9 25.694 12.023 6.448 1.00 0.00 H
ATOM 964 2HO* G 9 26.943 10.661 7.715 1.00 0.00 H
ATOM 965 H1* G 9 25.200 9.313 6.581 1.00 0.00 H
ATOM 966 H8 G 9 22.084 10.649 5.073 1.00 0.00 H
ATOM 967 H1 G 9 26.900 11.006 0.898 1.00 0.00 H
ATOM 968 1H2 G 9 28.931 10.305 3.654 1.00 0.00 H
ATOM 969 2H2 G 9 28.835 10.632 1.939 1.00 0.00 H
ATOM 970 P A 10 24.210 14.578 8.885 1.00 0.00 P
ATOM 971 O1P A 10 24.448 15.101 10.250 1.00 0.00 O
ATOM 972 O2P A 10 22.901 14.810 8.231 1.00 0.00 O
ATOM 973 O5* A 10 25.366 15.154 7.911 1.00 0.00 O
ATOM 974 C5* A 10 26.711 15.341 8.379 1.00 0.00 C
ATOM 975 C4* A 10 27.739 15.068 7.275 1.00 0.00 C
ATOM 976 O4* A 10 27.319 13.980 6.439 1.00 0.00 O
ATOM 977 C3* A 10 27.893 16.256 6.319 1.00 0.00 C
ATOM 978 O3* A 10 28.901 17.233 6.647 1.00 0.00 O
ATOM 979 C2* A 10 28.363 15.549 5.059 1.00 0.00 C
ATOM 980 O2* A 10 29.788 15.390 5.046 1.00 0.00 O
ATOM 981 C1* A 10 27.655 14.208 5.062 1.00 0.00 C
ATOM 982 N9 A 10 26.458 14.265 4.188 1.00 0.00 N
ATOM 983 C8 A 10 25.159 14.007 4.467 1.00 0.00 C
ATOM 984 N7 A 10 24.302 14.150 3.511 1.00 0.00 N
ATOM 985 C5 A 10 25.123 14.559 2.455 1.00 0.00 C
ATOM 986 C6 A 10 24.862 14.897 1.121 1.00 0.00 C
ATOM 987 N6 A 10 23.641 14.870 0.585 1.00 0.00 N
ATOM 988 N1 A 10 25.910 15.265 0.361 1.00 0.00 N
ATOM 989 C2 A 10 27.141 15.300 0.879 1.00 0.00 C
ATOM 990 N3 A 10 27.497 14.996 2.117 1.00 0.00 N
ATOM 991 C4 A 10 26.434 14.632 2.860 1.00 0.00 C
ATOM 992 1H5* A 10 26.899 14.662 9.209 1.00 0.00 H
ATOM 993 2H5* A 10 26.825 16.367 8.730 1.00 0.00 H
ATOM 994 H4* A 10 28.704 14.825 7.725 1.00 0.00 H
ATOM 995 H3* A 10 26.920 16.733 6.143 1.00 0.00 H
ATOM 996 1H2* A 10 28.038 16.114 4.190 1.00 0.00 H
ATOM 997 2HO* A 10 30.022 14.832 5.791 1.00 0.00 H
ATOM 998 H1* A 10 28.334 13.427 4.714 1.00 0.00 H
ATOM 999 H8 A 10 24.848 13.720 5.467 1.00 0.00 H
ATOM 1000 1H6 A 10 23.509 15.125 -0.384 1.00 0.00 H
ATOM 1001 2H6 A 10 22.849 14.595 1.147 1.00 0.00 H
ATOM 1002 H2 A 10 27.943 15.645 0.219 1.00 0.00 H
ATOM 1003 P U 11 28.812 18.764 6.118 1.00 0.00 P
ATOM 1004 O1P U 11 30.180 19.331 6.126 1.00 0.00 O
ATOM 1005 O2P U 11 27.736 19.447 6.871 1.00 0.00 O
ATOM 1006 O5* U 11 28.328 18.615 4.578 1.00 0.00 O
ATOM 1007 C5* U 11 29.263 18.459 3.494 1.00 0.00 C
ATOM 1008 C4* U 11 28.940 19.378 2.299 1.00 0.00 C
ATOM 1009 O4* U 11 27.773 18.954 1.580 1.00 0.00 O
ATOM 1010 C3* U 11 28.599 20.813 2.722 1.00 0.00 C
ATOM 1011 O3* U 11 28.865 21.847 1.767 1.00 0.00 O
ATOM 1012 C2* U 11 27.084 20.814 2.869 1.00 0.00 C
ATOM 1013 O2* U 11 26.535 22.124 2.678 1.00 0.00 O
ATOM 1014 C1* U 11 26.667 19.857 1.751 1.00 0.00 C
ATOM 1015 N1 U 11 25.405 19.136 2.076 1.00 0.00 N
ATOM 1016 C2 U 11 24.329 19.311 1.216 1.00 0.00 C
ATOM 1017 O2 U 11 24.398 20.021 0.213 1.00 0.00 O
ATOM 1018 N3 U 11 23.165 18.639 1.550 1.00 0.00 N
ATOM 1019 C4 U 11 22.980 17.820 2.651 1.00 0.00 C
ATOM 1020 O4 U 11 21.896 17.271 2.850 1.00 0.00 O
ATOM 1021 C5 U 11 24.148 17.691 3.492 1.00 0.00 C
ATOM 1022 C6 U 11 25.302 18.336 3.190 1.00 0.00 C
ATOM 1023 1H5* U 11 29.236 17.423 3.156 1.00 0.00 H
ATOM 1024 2H5* U 11 30.267 18.682 3.849 1.00 0.00 H
ATOM 1025 H4* U 11 29.789 19.390 1.610 1.00 0.00 H
ATOM 1026 H3* U 11 29.063 21.050 3.677 1.00 0.00 H
ATOM 1027 1H2* U 11 26.799 20.406 3.842 1.00 0.00 H
ATOM 1028 2HO* U 11 25.592 22.066 2.848 1.00 0.00 H
ATOM 1029 H1* U 11 26.534 20.425 0.826 1.00 0.00 H
ATOM 1030 H3 U 11 22.374 18.759 0.931 1.00 0.00 H
ATOM 1031 H5 U 11 24.099 17.067 4.386 1.00 0.00 H
ATOM 1032 H6 U 11 26.165 18.216 3.844 1.00 0.00 H
ATOM 1033 P U 12 30.365 22.352 1.474 1.00 0.00 P
ATOM 1034 O1P U 12 31.310 21.554 2.289 1.00 0.00 O
ATOM 1035 O2P U 12 30.381 23.829 1.564 1.00 0.00 O
ATOM 1036 O5* U 12 30.538 21.941 -0.073 1.00 0.00 O
ATOM 1037 C5* U 12 31.344 20.830 -0.476 1.00 0.00 C
ATOM 1038 C4* U 12 30.748 20.111 -1.694 1.00 0.00 C
ATOM 1039 O4* U 12 29.536 20.722 -2.157 1.00 0.00 O
ATOM 1040 C3* U 12 31.705 20.135 -2.878 1.00 0.00 C
ATOM 1041 O3* U 12 31.712 19.032 -3.792 1.00 0.00 O
ATOM 1042 C2* U 12 31.243 21.382 -3.630 1.00 0.00 C
ATOM 1043 O2* U 12 31.513 21.273 -5.033 1.00 0.00 O
ATOM 1044 C1* U 12 29.743 21.469 -3.368 1.00 0.00 C
ATOM 1045 N1 U 12 29.291 22.881 -3.225 1.00 0.00 N
ATOM 1046 C2 U 12 28.934 23.562 -4.381 1.00 0.00 C
ATOM 1047 O2 U 12 28.991 23.041 -5.495 1.00 0.00 O
ATOM 1048 N3 U 12 28.512 24.870 -4.213 1.00 0.00 N
ATOM 1049 C4 U 12 28.414 25.550 -3.010 1.00 0.00 C
ATOM 1050 O4 U 12 28.024 26.716 -2.978 1.00 0.00 O
ATOM 1051 C5 U 12 28.805 24.768 -1.857 1.00 0.00 C
ATOM 1052 C6 U 12 29.223 23.486 -1.993 1.00 0.00 C
ATOM 1053 1H5* U 12 31.417 20.123 0.350 1.00 0.00 H
ATOM 1054 2H5* U 12 32.337 21.183 -0.719 1.00 0.00 H
ATOM 1055 H4* U 12 30.540 19.074 -1.425 1.00 0.00 H
ATOM 1056 H3* U 12 32.714 20.307 -2.500 1.00 0.00 H
ATOM 1057 1H2* U 12 31.729 22.258 -3.222 1.00 0.00 H
ATOM 1058 2HO* U 12 32.366 21.685 -5.193 1.00 0.00 H
ATOM 1059 H1* U 12 29.201 20.993 -4.184 1.00 0.00 H
ATOM 1060 H3 U 12 28.249 25.377 -5.047 1.00 0.00 H
ATOM 1061 H5 U 12 28.763 25.218 -0.864 1.00 0.00 H
ATOM 1062 H6 U 12 29.517 22.924 -1.105 1.00 0.00 H
ATOM 1063 P A 13 33.089 18.602 -4.523 1.00 0.00 P
ATOM 1064 O1P A 13 33.745 17.561 -3.700 1.00 0.00 O
ATOM 1065 O2P A 13 33.835 19.830 -4.881 1.00 0.00 O
ATOM 1066 O5* A 13 32.559 17.931 -5.890 1.00 0.00 O
ATOM 1067 C5* A 13 32.848 16.569 -6.220 1.00 0.00 C
ATOM 1068 C4* A 13 32.210 15.588 -5.224 1.00 0.00 C
ATOM 1069 O4* A 13 31.454 16.258 -4.215 1.00 0.00 O
ATOM 1070 C3* A 13 31.229 14.633 -5.904 1.00 0.00 C
ATOM 1071 O3* A 13 31.260 13.370 -5.229 1.00 0.00 O
ATOM 1072 C2* A 13 29.888 15.340 -5.756 1.00 0.00 C
ATOM 1073 O2* A 13 28.797 14.411 -5.753 1.00 0.00 O
ATOM 1074 C1* A 13 30.062 16.013 -4.393 1.00 0.00 C
ATOM 1075 N9 A 13 29.280 17.261 -4.260 1.00 0.00 N
ATOM 1076 C8 A 13 29.030 18.262 -5.142 1.00 0.00 C
ATOM 1077 N7 A 13 28.209 19.188 -4.770 1.00 0.00 N
ATOM 1078 C5 A 13 27.885 18.771 -3.476 1.00 0.00 C
ATOM 1079 C6 A 13 27.062 19.304 -2.476 1.00 0.00 C
ATOM 1080 N6 A 13 26.356 20.425 -2.629 1.00 0.00 N
ATOM 1081 N1 A 13 26.999 18.633 -1.315 1.00 0.00 N
ATOM 1082 C2 A 13 27.702 17.509 -1.151 1.00 0.00 C
ATOM 1083 N3 A 13 28.490 16.925 -2.024 1.00 0.00 N
ATOM 1084 C4 A 13 28.541 17.608 -3.169 1.00 0.00 C
ATOM 1085 1H5* A 13 33.931 16.424 -6.218 1.00 0.00 H
ATOM 1086 2H5* A 13 32.471 16.364 -7.221 1.00 0.00 H
ATOM 1087 H4* A 13 32.986 15.009 -4.730 1.00 0.00 H
ATOM 1088 H3* A 13 31.481 14.517 -6.962 1.00 0.00 H
ATOM 1089 1H2* A 13 29.767 16.088 -6.540 1.00 0.00 H
ATOM 1090 2HO* A 13 27.985 14.922 -5.797 1.00 0.00 H
ATOM 1091 H1* A 13 29.736 15.316 -3.619 1.00 0.00 H
ATOM 1092 H8 A 13 29.582 18.344 -6.068 1.00 0.00 H
ATOM 1093 1H6 A 13 25.778 20.764 -1.872 1.00 0.00 H
ATOM 1094 2H6 A 13 26.397 20.936 -3.499 1.00 0.00 H
ATOM 1095 H2 A 13 27.656 17.039 -0.178 1.00 0.00 H
ATOM 1096 P C 14 31.030 11.984 -6.021 1.00 0.00 P
ATOM 1097 O1P C 14 31.972 11.929 -7.163 1.00 0.00 O
ATOM 1098 O2P C 14 29.579 11.813 -6.253 1.00 0.00 O
ATOM 1099 O5* C 14 31.496 10.901 -4.923 1.00 0.00 O
ATOM 1100 C5* C 14 32.862 10.835 -4.492 1.00 0.00 C
ATOM 1101 C4* C 14 33.022 11.139 -2.994 1.00 0.00 C
ATOM 1102 O4* C 14 32.307 12.320 -2.612 1.00 0.00 O
ATOM 1103 C3* C 14 32.430 10.031 -2.122 1.00 0.00 C
ATOM 1104 O3* C 14 33.398 8.990 -1.904 1.00 0.00 O
ATOM 1105 C2* C 14 32.093 10.783 -0.841 1.00 0.00 C
ATOM 1106 O2* C 14 33.228 10.854 0.032 1.00 0.00 O
ATOM 1107 C1* C 14 31.678 12.176 -1.328 1.00 0.00 C
ATOM 1108 N1 C 14 30.202 12.319 -1.441 1.00 0.00 N
ATOM 1109 C2 C 14 29.447 12.280 -0.272 1.00 0.00 C
ATOM 1110 O2 C 14 29.995 12.119 0.819 1.00 0.00 O
ATOM 1111 N3 C 14 28.101 12.439 -0.369 1.00 0.00 N
ATOM 1112 C4 C 14 27.510 12.635 -1.555 1.00 0.00 C
ATOM 1113 N4 C 14 26.183 12.760 -1.603 1.00 0.00 N
ATOM 1114 C5 C 14 28.282 12.684 -2.763 1.00 0.00 C
ATOM 1115 C6 C 14 29.615 12.514 -2.658 1.00 0.00 C
ATOM 1116 1H5* C 14 33.452 11.553 -5.065 1.00 0.00 H
ATOM 1117 2H5* C 14 33.235 9.837 -4.691 1.00 0.00 H
ATOM 1118 H4* C 14 34.081 11.268 -2.759 1.00 0.00 H
ATOM 1119 H3* C 14 31.517 9.634 -2.579 1.00 0.00 H
ATOM 1120 1H2* C 14 31.254 10.295 -0.339 1.00 0.00 H
ATOM 1121 2HO* C 14 32.922 11.211 0.870 1.00 0.00 H
ATOM 1122 H1* C 14 32.066 12.937 -0.649 1.00 0.00 H
ATOM 1123 1H4 C 14 25.720 12.890 -2.489 1.00 0.00 H
ATOM 1124 2H4 C 14 25.640 12.718 -0.751 1.00 0.00 H
ATOM 1125 H5 C 14 27.815 12.905 -3.727 1.00 0.00 H
ATOM 1126 H6 C 14 30.233 12.508 -3.558 1.00 0.00 H
ATOM 1127 P C 15 32.984 7.429 -1.947 1.00 0.00 P
ATOM 1128 O1P C 15 34.217 6.631 -2.132 1.00 0.00 O
ATOM 1129 O2P C 15 31.858 7.267 -2.896 1.00 0.00 O
ATOM 1130 O5* C 15 32.426 7.167 -0.454 1.00 0.00 O
ATOM 1131 C5* C 15 33.306 7.165 0.681 1.00 0.00 C
ATOM 1132 C4* C 15 32.536 7.006 2.001 1.00 0.00 C
ATOM 1133 O4* C 15 31.494 7.986 2.129 1.00 0.00 O
ATOM 1134 C3* C 15 31.811 5.661 2.084 1.00 0.00 C
ATOM 1135 O3* C 15 32.663 4.622 2.598 1.00 0.00 O
ATOM 1136 C2* C 15 30.681 5.984 3.053 1.00 0.00 C
ATOM 1137 O2* C 15 31.107 5.831 4.414 1.00 0.00 O
ATOM 1138 C1* C 15 30.317 7.442 2.750 1.00 0.00 C
ATOM 1139 N1 C 15 29.122 7.547 1.862 1.00 0.00 N
ATOM 1140 C2 C 15 27.889 7.166 2.390 1.00 0.00 C
ATOM 1141 O2 C 15 27.809 6.774 3.552 1.00 0.00 O
ATOM 1142 N3 C 15 26.789 7.250 1.594 1.00 0.00 N
ATOM 1143 C4 C 15 26.881 7.689 0.333 1.00 0.00 C
ATOM 1144 N4 C 15 25.779 7.756 -0.416 1.00 0.00 N
ATOM 1145 C5 C 15 28.141 8.085 -0.219 1.00 0.00 C
ATOM 1146 C6 C 15 29.230 8.000 0.573 1.00 0.00 C
ATOM 1147 1H5* C 15 33.858 8.105 0.706 1.00 0.00 H
ATOM 1148 2H5* C 15 34.015 6.341 0.581 1.00 0.00 H
ATOM 1149 H4* C 15 33.227 7.106 2.841 1.00 0.00 H
ATOM 1150 H3* C 15 31.400 5.389 1.104 1.00 0.00 H
ATOM 1151 1H2* C 15 29.826 5.334 2.848 1.00 0.00 H
ATOM 1152 2HO* C 15 30.330 5.925 4.969 1.00 0.00 H
ATOM 1153 H1* C 15 30.127 7.972 3.687 1.00 0.00 H
ATOM 1154 1H4 C 15 25.835 8.084 -1.370 1.00 0.00 H
ATOM 1155 2H4 C 15 24.888 7.476 -0.031 1.00 0.00 H
ATOM 1156 H5 C 15 28.218 8.445 -1.247 1.00 0.00 H
ATOM 1157 H6 C 15 30.201 8.306 0.184 1.00 0.00 H
ATOM 1158 P U 16 32.481 3.079 2.148 1.00 0.00 P
ATOM 1159 O1P U 16 33.543 2.281 2.801 1.00 0.00 O
ATOM 1160 O2P U 16 32.335 3.037 0.675 1.00 0.00 O
ATOM 1161 O5* U 16 31.061 2.672 2.807 1.00 0.00 O
ATOM 1162 C5* U 16 30.943 2.388 4.209 1.00 0.00 C
ATOM 1163 C4* U 16 29.476 2.232 4.643 1.00 0.00 C
ATOM 1164 O4* U 16 28.611 3.142 3.944 1.00 0.00 O
ATOM 1165 C3* U 16 28.916 0.848 4.304 1.00 0.00 C
ATOM 1166 O3* U 16 29.263 -0.099 5.331 1.00 0.00 O
ATOM 1167 C2* U 16 27.419 1.134 4.239 1.00 0.00 C
ATOM 1168 O2* U 16 26.823 1.075 5.541 1.00 0.00 O
ATOM 1169 C1* U 16 27.333 2.547 3.658 1.00 0.00 C
ATOM 1170 N1 U 16 27.040 2.530 2.195 1.00 0.00 N
ATOM 1171 C2 U 16 25.709 2.427 1.812 1.00 0.00 C
ATOM 1172 O2 U 16 24.794 2.353 2.631 1.00 0.00 O
ATOM 1173 N3 U 16 25.464 2.408 0.449 1.00 0.00 N
ATOM 1174 C4 U 16 26.416 2.482 -0.553 1.00 0.00 C
ATOM 1175 O4 U 16 26.084 2.456 -1.738 1.00 0.00 O
ATOM 1176 C5 U 16 27.775 2.588 -0.069 1.00 0.00 C
ATOM 1177 C6 U 16 28.043 2.610 1.260 1.00 0.00 C
ATOM 1178 1H5* U 16 31.393 3.204 4.777 1.00 0.00 H
ATOM 1179 2H5* U 16 31.482 1.464 4.432 1.00 0.00 H
ATOM 1180 H4* U 16 29.391 2.412 5.717 1.00 0.00 H
ATOM 1181 H3* U 16 29.282 0.519 3.323 1.00 0.00 H
ATOM 1182 1H2* U 16 26.932 0.424 3.564 1.00 0.00 H
ATOM 1183 2HO* U 16 26.287 0.279 5.574 1.00 0.00 H
ATOM 1184 H1* U 16 26.554 3.105 4.182 1.00 0.00 H
ATOM 1185 H3 U 16 24.499 2.333 0.158 1.00 0.00 H
ATOM 1186 H5 U 16 28.596 2.645 -0.783 1.00 0.00 H
ATOM 1187 H6 U 16 29.078 2.699 1.589 1.00 0.00 H
ATOM 1188 P A 17 29.128 -1.691 5.090 1.00 0.00 P
ATOM 1189 O1P A 17 30.089 -2.375 5.985 1.00 0.00 O
ATOM 1190 O2P A 17 29.170 -1.952 3.633 1.00 0.00 O
ATOM 1191 O5* A 17 27.632 -2.003 5.614 1.00 0.00 O
ATOM 1192 C5* A 17 27.278 -1.850 6.998 1.00 0.00 C
ATOM 1193 C4* A 17 25.805 -2.202 7.251 1.00 0.00 C
ATOM 1194 O4* A 17 24.933 -1.552 6.313 1.00 0.00 O
ATOM 1195 C3* A 17 25.537 -3.691 7.076 1.00 0.00 C
ATOM 1196 O3* A 17 25.848 -4.377 8.302 1.00 0.00 O
ATOM 1197 C2* A 17 24.052 -3.687 6.737 1.00 0.00 C
ATOM 1198 O2* A 17 23.249 -3.687 7.926 1.00 0.00 O
ATOM 1199 C1* A 17 23.841 -2.405 5.932 1.00 0.00 C
ATOM 1200 N9 A 17 23.844 -2.667 4.467 1.00 0.00 N
ATOM 1201 C8 A 17 24.786 -2.368 3.532 1.00 0.00 C
ATOM 1202 N7 A 17 24.548 -2.718 2.311 1.00 0.00 N
ATOM 1203 C5 A 17 23.294 -3.330 2.427 1.00 0.00 C
ATOM 1204 C6 A 17 22.444 -3.936 1.494 1.00 0.00 C
ATOM 1205 N6 A 17 22.737 -4.034 0.196 1.00 0.00 N
ATOM 1206 N1 A 17 21.280 -4.436 1.948 1.00 0.00 N
ATOM 1207 C2 A 17 20.966 -4.348 3.242 1.00 0.00 C
ATOM 1208 N3 A 17 21.695 -3.799 4.210 1.00 0.00 N
ATOM 1209 C4 A 17 22.857 -3.304 3.734 1.00 0.00 C
ATOM 1210 1H5* A 17 27.451 -0.815 7.297 1.00 0.00 H
ATOM 1211 2H5* A 17 27.911 -2.502 7.603 1.00 0.00 H
ATOM 1212 H4* A 17 25.528 -1.907 8.258 1.00 0.00 H
ATOM 1213 H3* A 17 26.119 -4.088 6.237 1.00 0.00 H
ATOM 1214 1H2* A 17 23.812 -4.551 6.120 1.00 0.00 H
ATOM 1215 2HO* A 17 22.338 -3.821 7.656 1.00 0.00 H
ATOM 1216 H1* A 17 22.896 -1.943 6.222 1.00 0.00 H
ATOM 1217 H8 A 17 25.704 -1.843 3.798 1.00 0.00 H
ATOM 1218 1H6 A 17 22.086 -4.481 -0.435 1.00 0.00 H
ATOM 1219 2H6 A 17 23.607 -3.662 -0.156 1.00 0.00 H
ATOM 1220 H2 A 17 20.003 -4.767 3.538 1.00 0.00 H
ATOM 1221 P U 18 26.579 -5.817 8.301 1.00 0.00 P
ATOM 1222 O1P U 18 26.793 -6.227 9.708 1.00 0.00 O
ATOM 1223 O2P U 18 27.729 -5.760 7.371 1.00 0.00 O
ATOM 1224 O5* U 18 25.456 -6.782 7.657 1.00 0.00 O
ATOM 1225 C5* U 18 24.254 -7.102 8.372 1.00 0.00 C
ATOM 1226 C4* U 18 23.146 -7.595 7.431 1.00 0.00 C
ATOM 1227 O4* U 18 22.934 -6.690 6.339 1.00 0.00 O
ATOM 1228 C3* U 18 23.513 -8.921 6.759 1.00 0.00 C
ATOM 1229 O3* U 18 23.167 -10.054 7.578 1.00 0.00 O
ATOM 1230 C2* U 18 22.670 -8.867 5.493 1.00 0.00 C
ATOM 1231 O2* U 18 21.344 -9.360 5.732 1.00 0.00 O
ATOM 1232 C1* U 18 22.649 -7.384 5.114 1.00 0.00 C
ATOM 1233 N1 U 18 23.642 -7.059 4.047 1.00 0.00 N
ATOM 1234 C2 U 18 23.311 -7.401 2.742 1.00 0.00 C
ATOM 1235 O2 U 18 22.244 -7.945 2.458 1.00 0.00 O
ATOM 1236 N3 U 18 24.246 -7.089 1.771 1.00 0.00 N
ATOM 1237 C4 U 18 25.468 -6.473 1.981 1.00 0.00 C
ATOM 1238 O4 U 18 26.225 -6.242 1.039 1.00 0.00 O
ATOM 1239 C5 U 18 25.737 -6.149 3.366 1.00 0.00 C
ATOM 1240 C6 U 18 24.838 -6.444 4.339 1.00 0.00 C
ATOM 1241 1H5* U 18 23.903 -6.212 8.897 1.00 0.00 H
ATOM 1242 2H5* U 18 24.473 -7.881 9.105 1.00 0.00 H
ATOM 1243 H4* U 18 22.215 -7.704 7.990 1.00 0.00 H
ATOM 1244 H3* U 18 24.579 -8.932 6.500 1.00 0.00 H
ATOM 1245 1H2* U 18 23.153 -9.447 4.704 1.00 0.00 H
ATOM 1246 2HO* U 18 21.407 -10.312 5.833 1.00 0.00 H
ATOM 1247 H1* U 18 21.646 -7.113 4.775 1.00 0.00 H
ATOM 1248 H3 U 18 24.014 -7.334 0.818 1.00 0.00 H
ATOM 1249 H5 U 18 26.676 -5.662 3.631 1.00 0.00 H
ATOM 1250 H6 U 18 25.068 -6.171 5.372 1.00 0.00 H
ATOM 1251 P G 19 24.070 -11.395 7.584 1.00 0.00 P
ATOM 1252 O1P G 19 23.816 -12.113 8.853 1.00 0.00 O
ATOM 1253 O2P G 19 25.456 -11.030 7.213 1.00 0.00 O
ATOM 1254 O5* G 19 23.435 -12.255 6.371 1.00 0.00 O
ATOM 1255 C5* G 19 22.522 -13.339 6.622 1.00 0.00 C
ATOM 1256 C4* G 19 21.910 -13.906 5.338 1.00 0.00 C
ATOM 1257 O4* G 19 21.631 -12.876 4.378 1.00 0.00 O
ATOM 1258 C3* G 19 22.872 -14.848 4.607 1.00 0.00 C
ATOM 1259 O3* G 19 22.849 -16.193 5.123 1.00 0.00 O
ATOM 1260 C2* G 19 22.306 -14.797 3.194 1.00 0.00 C
ATOM 1261 O2* G 19 21.217 -15.718 3.035 1.00 0.00 O
ATOM 1262 C1* G 19 21.836 -13.351 3.036 1.00 0.00 C
ATOM 1263 N9 G 19 22.839 -12.528 2.309 1.00 0.00 N
ATOM 1264 C8 G 19 23.791 -11.684 2.790 1.00 0.00 C
ATOM 1265 N7 G 19 24.552 -11.088 1.933 1.00 0.00 N
ATOM 1266 C5 G 19 24.065 -11.583 0.719 1.00 0.00 C
ATOM 1267 C6 G 19 24.486 -11.309 -0.611 1.00 0.00 C
ATOM 1268 O6 G 19 25.390 -10.564 -0.986 1.00 0.00 O
ATOM 1269 N1 G 19 23.731 -12.014 -1.541 1.00 0.00 N
ATOM 1270 C2 G 19 22.696 -12.877 -1.236 1.00 0.00 C
ATOM 1271 N2 G 19 22.087 -13.463 -2.269 1.00 0.00 N
ATOM 1272 N3 G 19 22.295 -13.140 0.012 1.00 0.00 N
ATOM 1273 C4 G 19 23.016 -12.464 0.937 1.00 0.00 C
ATOM 1274 1H5* G 19 21.699 -12.982 7.229 1.00 0.00 H
ATOM 1275 2H5* G 19 23.061 -14.131 7.167 1.00 0.00 H
ATOM 1276 H4* G 19 20.985 -14.435 5.577 1.00 0.00 H
ATOM 1277 H3* G 19 23.888 -14.436 4.620 1.00 0.00 H
ATOM 1278 1H2* G 19 23.095 -15.012 2.471 1.00 0.00 H
ATOM 1279 2HO* G 19 20.988 -15.731 2.103 1.00 0.00 H
ATOM 1280 H1* G 19 20.886 -13.332 2.498 1.00 0.00 H
ATOM 1281 H8 G 19 23.908 -11.512 3.860 1.00 0.00 H
ATOM 1282 H1 G 19 23.976 -11.870 -2.509 1.00 0.00 H
ATOM 1283 1H2 G 19 21.324 -14.104 -2.107 1.00 0.00 H
ATOM 1284 2H2 G 19 22.390 -13.265 -3.212 1.00 0.00 H
ATOM 1285 P C 20 24.094 -17.201 4.902 1.00 0.00 P
ATOM 1286 O1P C 20 23.887 -18.383 5.769 1.00 0.00 O
ATOM 1287 O2P C 20 25.351 -16.425 5.009 1.00 0.00 O
ATOM 1288 O5* C 20 23.916 -17.661 3.361 1.00 0.00 O
ATOM 1289 C5* C 20 23.025 -18.728 3.003 1.00 0.00 C
ATOM 1290 C4* C 20 22.893 -18.887 1.479 1.00 0.00 C
ATOM 1291 O4* C 20 22.785 -17.619 0.811 1.00 0.00 O
ATOM 1292 C3* C 20 24.132 -19.534 0.852 1.00 0.00 C
ATOM 1293 O3* C 20 24.116 -20.969 0.981 1.00 0.00 O
ATOM 1294 C2* C 20 23.970 -19.088 -0.597 1.00 0.00 C
ATOM 1295 O2* C 20 23.083 -19.960 -1.314 1.00 0.00 O
ATOM 1296 C1* C 20 23.395 -17.672 -0.492 1.00 0.00 C
ATOM 1297 N1 C 20 24.448 -16.628 -0.664 1.00 0.00 N
ATOM 1298 C2 C 20 24.788 -16.267 -1.967 1.00 0.00 C
ATOM 1299 O2 C 20 24.233 -16.804 -2.926 1.00 0.00 O
ATOM 1300 N3 C 20 25.743 -15.314 -2.147 1.00 0.00 N
ATOM 1301 C4 C 20 26.346 -14.734 -1.103 1.00 0.00 C
ATOM 1302 N4 C 20 27.278 -13.806 -1.323 1.00 0.00 N
ATOM 1303 C5 C 20 26.005 -15.096 0.239 1.00 0.00 C
ATOM 1304 C6 C 20 25.058 -16.040 0.414 1.00 0.00 C
ATOM 1305 1H5* C 20 22.039 -18.520 3.422 1.00 0.00 H
ATOM 1306 2H5* C 20 23.399 -19.662 3.428 1.00 0.00 H
ATOM 1307 H4* C 20 22.009 -19.486 1.252 1.00 0.00 H
ATOM 1308 H3* C 20 25.046 -19.104 1.281 1.00 0.00 H
ATOM 1309 1H2* C 20 24.948 -19.058 -1.085 1.00 0.00 H
ATOM 1310 2HO* C 20 22.206 -19.849 -0.939 1.00 0.00 H
ATOM 1311 H1* C 20 22.621 -17.539 -1.252 1.00 0.00 H
ATOM 1312 1H4 C 20 27.743 -13.361 -0.545 1.00 0.00 H
ATOM 1313 2H4 C 20 27.521 -13.549 -2.269 1.00 0.00 H
ATOM 1314 H5 C 20 26.495 -14.624 1.092 1.00 0.00 H
ATOM 1315 H6 C 20 24.775 -16.334 1.424 1.00 0.00 H
ATOM 1316 P C 21 25.478 -21.837 0.913 1.00 0.00 P
ATOM 1317 O1P C 21 25.166 -23.216 1.355 1.00 0.00 O
ATOM 1318 O2P C 21 26.555 -21.078 1.590 1.00 0.00 O
ATOM 1319 O5* C 21 25.806 -21.872 -0.669 1.00 0.00 O
ATOM 1320 C5* C 21 25.064 -22.713 -1.566 1.00 0.00 C
ATOM 1321 C4* C 21 25.331 -22.359 -3.037 1.00 0.00 C
ATOM 1322 O4* C 21 25.492 -20.944 -3.228 1.00 0.00 O
ATOM 1323 C3* C 21 26.646 -22.955 -3.545 1.00 0.00 C
ATOM 1324 O3* C 21 26.476 -24.311 -3.980 1.00 0.00 O
ATOM 1325 C2* C 21 26.966 -22.031 -4.712 1.00 0.00 C
ATOM 1326 O2* C 21 26.289 -22.448 -5.905 1.00 0.00 O
ATOM 1327 C1* C 21 26.470 -20.658 -4.244 1.00 0.00 C
ATOM 1328 N1 C 21 27.584 -19.805 -3.730 1.00 0.00 N
ATOM 1329 C2 C 21 28.285 -19.039 -4.659 1.00 0.00 C
ATOM 1330 O2 C 21 27.988 -19.086 -5.851 1.00 0.00 O
ATOM 1331 N3 C 21 29.300 -18.247 -4.213 1.00 0.00 N
ATOM 1332 C4 C 21 29.619 -18.201 -2.914 1.00 0.00 C
ATOM 1333 N4 C 21 30.618 -17.412 -2.517 1.00 0.00 N
ATOM 1334 C5 C 21 28.906 -18.983 -1.951 1.00 0.00 C
ATOM 1335 C6 C 21 27.903 -19.767 -2.396 1.00 0.00 C
ATOM 1336 1H5* C 21 23.999 -22.597 -1.362 1.00 0.00 H
ATOM 1337 2H5* C 21 25.345 -23.754 -1.392 1.00 0.00 H
ATOM 1338 H4* C 21 24.502 -22.712 -3.654 1.00 0.00 H
ATOM 1339 H3* C 21 27.425 -22.882 -2.777 1.00 0.00 H
ATOM 1340 1H2* C 21 28.048 -22.003 -4.876 1.00 0.00 H
ATOM 1341 2HO* C 21 26.713 -23.255 -6.208 1.00 0.00 H
ATOM 1342 H1* C 21 25.977 -20.150 -5.077 1.00 0.00 H
ATOM 1343 1H4 C 21 30.870 -17.368 -1.539 1.00 0.00 H
ATOM 1344 2H4 C 21 31.124 -16.859 -3.193 1.00 0.00 H
ATOM 1345 H5 C 21 29.165 -18.946 -0.892 1.00 0.00 H
ATOM 1346 H6 C 21 27.342 -20.373 -1.686 1.00 0.00 H
ATOM 1347 H3T C 21 27.352 -24.670 -4.145 1.00 0.00 H
TER 1348 C 21
ENDMDL
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_rtax.py 000644 000765 000024 00000031410 12024702176 021610 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__author__ = "David Soergel"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["David Soergel"] #remember to add yourself
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "David Soergel"
__email__ = "soergel@cs.umass.edu"
__status__ = "Production"
from cogent.util.misc import remove_files
from unittest import TestCase, main
from cogent.app.rtax import Rtax, assign_taxonomy
from cogent.app.util import get_tmp_filename
class RtaxClassifierTests(TestCase):
""" Tests of the RTAX classifier module """
def setUp(self):
self.maxDiff = None
self.id_to_taxonomy_fp = get_tmp_filename(\
prefix='RtaxTaxonAssignerTests_',suffix='.txt')
self.input_seqs_fp = get_tmp_filename(\
prefix='RtaxTaxonAssignerTests_',suffix='.fasta')
self.reference_seqs_fp = get_tmp_filename(\
prefix='RtaxTaxonAssignerTests_',suffix='.fasta')
self.read_1_seqs_fp = get_tmp_filename(\
prefix='RtaxTaxonAssignerTests_',suffix='.fasta')
self.read_2_seqs_fp = get_tmp_filename(\
prefix='RtaxTaxonAssignerTests_',suffix='.fasta')
self._paths_to_clean_up = [self.id_to_taxonomy_fp,self.input_seqs_fp,self.reference_seqs_fp, self.read_1_seqs_fp,self.read_2_seqs_fp]
a = open(self.id_to_taxonomy_fp,'w')
a.write(rtax_reference_taxonomy)
a.close()
b = open(self.reference_seqs_fp,'w')
b.write(rtax_reference_fasta)
b.close()
c = open(self.input_seqs_fp,'w')
c.write(rtax_test_repset_fasta)
c.close()
d = open(self.read_1_seqs_fp,'w')
d.write(rtax_test_read1_fasta)
d.close()
e = open(self.read_2_seqs_fp,'w')
e.write(rtax_test_read2_fasta)
e.close()
def tearDown(self):
remove_files(set(self._paths_to_clean_up),error_on_missing=False)
def test_paired_end_classification(self):
self._paths_to_clean_up += cleanAll(self.read_1_seqs_fp)
self._paths_to_clean_up += cleanAll(self.read_2_seqs_fp)
result = assign_taxonomy(self.input_seqs_fp, self.reference_seqs_fp, self.id_to_taxonomy_fp, self.read_1_seqs_fp, self.read_2_seqs_fp,single_ok=False,header_id_regex="\\S+\\s+(\\S+?)\/")
self.assertEqual(result, rtax_expected_result_paired)
def test_paired_end_classification_with_fallback(self):
self._paths_to_clean_up += cleanAll(self.read_1_seqs_fp)
self._paths_to_clean_up += cleanAll(self.read_2_seqs_fp)
result = assign_taxonomy(self.input_seqs_fp, self.reference_seqs_fp, self.id_to_taxonomy_fp, self.read_1_seqs_fp, self.read_2_seqs_fp,single_ok=True,header_id_regex="\\S+\\s+(\\S+?)\/")
self.assertEqual(result, rtax_expected_result_paired_with_fallback)
def test_single_end_classification(self):
self._paths_to_clean_up += cleanAll(self.read_1_seqs_fp)
result = assign_taxonomy(self.input_seqs_fp, self.reference_seqs_fp, self.id_to_taxonomy_fp, self.read_1_seqs_fp, None ,header_id_regex="\\S+\\s+(\\S+?)\/")
self.assertEqual(result, rtax_expected_result_single)
# I'd like to add tests here that involve the TOOMANYHITS case. However, that requires either a reference
# database with >16,000 sequences, which we don't have handy for tests, or adjusting the maxMaxAccepts parameter to rtaxSearch.pl.
# However the "rtax" wrapper shell script currently doesn't allow setting that option, and I'd prefer to leave that as is
# unless someone actually wants to use it. Thus the TOOMANYHITS situation is not easily testable at the moment.
def cleanAll(path):
return [path, path + ".pos.db", path + ".pos.dir", path + ".pos.pag", path + ".lines.db", path + ".lines.dir", path + ".lines.pag"]
# sample data copied from GreenGenes
rtax_reference_taxonomy = """508720 99.0 k__Bacteria p__Actinobacteria c__Actinobacteria o__Actinomycetales f__Propionibacteriaceae g__Propionibacterium s__Propionibacterium acnes
508050 99.0 k__Bacteria p__Proteobacteria c__Betaproteobacteria o__Burkholderiales f__Comamonadaceae g__Diaphorobacter s__
502492 99.0 k__Bacteria p__Proteobacteria c__Betaproteobacteria o__Burkholderiales f__ g__Aquabacterium s__
"""
rtax_reference_fasta = """>508720
GACGAACGCTGGCGGCGTGCTTAACACATGCAAGTCGAACGGAAAGGCCCTGCTTTTGTGGGGTGCTCGAGTGGCGAACG
GGTGAGTAACACGTGAGTAACCTGCCCTTGACTTTGGGATAACTTCAGGAAACTGGGGCTAATACCGGATAGGAGCTCCT
GCTGCATGGTGGGGGTTGGAAAGTTTCGGCGGTTGGGGATGGACTCGCGGCTTATCAGCTTGTTGGTGGGGTAGTGGCTT
ACCAAGGCTTTGACGGGTAGCCGGCCTGAGAGGGTGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTACGGGA
GGCAGCAGTGGGGAATATTGCACAATGGGCGGAAGCCTGATGCAGCAACGCCGCGTGCGGGATGACGGCCTTCGGGTTGT
AAACCGCTTTCGCCTGTGACGAAGCGTGAGTGACGGTAATGGGTAAAGAAGCACCGGCTAACTACGTGCCAGCAGCCGCG
GTGATACGTAGGGTGCGAGCGTTGTCCGGATTTATTGGGCGTAAAGGGCTCGTAGGTGGTTGATCGCGTCGGAAGTGTAA
TCTTGGGGCTTAACCCTGAGCGTGCTTTCGATACGGGTTGACTTGAGGAAGGTAGGGGAGAATGGAATTCCTGGTGGAGC
GGTGGAATGCGCAGATATCAGGAGGAACACCAGTGGCGAAGGCGGTTCTCTGGGCCTTTCCTGACGCTGAGGAGCGAAAG
CGTGGGGAGCGAACAGGCTTAGATACCCTGGTAGTCCACGCTGTAAACGGTGGGTACTAGGTGTGGGGTCCATTCCACGG
GTTCCGTGCCGTAGCTAACGCTTTAAGTACCCCGCCTGGGGAGTACGGCCGCAAGGCTAAAACTCAAAGGAATTGACGGG
GCCCCGCACAAGCGGCGGAGCATGCGGATTAATTCGATGCAACGCGTAGAACCTTACCTGGGTTTGACATGGATCGGGAG
TGCTCAGAGATGGGTGTGCCTCTTTTGGGGTCGGTTCACAGGTGGTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTT
GGGTTAAGTCCCGCAACGAGCGCAACCCTTGTTCACTGTTGCCAGCACGTTATGGTGGGGACTCAGTGGAGACCGCCGGG
GTCAACTCGGAGGAAGGTGGGGATGACGTCAAGTCATCATGCCCCTTATGTCCAGGGCTTCACGCATGCTACAATGGCTG
GTACAGAGAGTGGCGAGCCTGTGAGGGTGAGCGAATCTCGGAAAGCCGGTCTCAGTTCGGATTGGGGTCTGCAACTCGAC
CTCATGAAGTCGGAGTCGCTAGTAATCGCAGATCAGCAACGCTGCGGTGAATACGTTCCCGGGGCT
>508050
ATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGTAACAGGTCTTCGGATGCTGACGAGTGGCGAACGGGTG
AGTAATACATCGGAACGTGCCCGATCGTGGGGGATAACGAGGCGAAAGCTTTGCTAATACCGCATACGATCTACGGATGA
AAGCGGGGGATCTTCGGACCTCGCGCGGACGGAGCGGCCGATGGCAGATTAGGTAGTTGGTGGGATAAAAGCTTACCAAG
CCGACGATCTGTAGCTGGTCTGAGAGGATGATCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGC
AGTGGGGAATTTTGGACAATGGGCGAAAGCCTGATCCAGCCATGCCGCGTGCAGGATGAAGGCCTTCGGGTTGTAAACTG
CTTTTGTACGGAACGAAAAGCCTCTTTCTAATAAAGAGGGGTCATGACGGTACCGTAAGAATAAGCACCGGCTAACTACG
TGCCAGCAGCCGCGGTAATACGTAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGTGCGCAGGCGGTTTTGTA
AGACAGAGGTGAAATCCCCGGGCTCAACCTGGGAACTGCCTTTGTGACTGCAAGGCTGGAGTGCGGCAGAGGGGGATGGA
ATTCCGCGTGTAGCAGTGAAATGCGTAGATATGCGGAGGAACACCGATGGCGAAGGCAATCCCCTGGGCCTGCACTGACG
CTCATGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCCTAAACGATGTCAACTGGTTGTTG
GGTCTTCACTGACTCAGTAACGAAGCTAACGCGTGAAGTTGACCGCCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAG
GAATTGACGGGGACCCGCACAAGCGGTGGATGATGTGGTTTAATTCGATGCAACGCGAAAAACCTTACCCACCTTTGACA
TGGCAGGAAGTTTCCAGAGATGGATTCGTGCCCGAAAGGGAACCTGCACACAGGTGCTGCATGGCTGTCGTCAGCTCGTG
TCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGCCATTAGTTGCTACGAAAGGGCACTCTAATGGGACTG
CCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAGTCCTCATGGCCCTTATAGGTGGGGCTACACACGTCATACAAT
GGCTGGTACAGAGGGTTGCCAACCCGCGAGGGGGAGCTAATCCCATAAAGCCAGTCGTAGTCCGGATCGCAGTCTGCAAC
TCGACTGCGTGAAGTCGGAATCGCTAGTAATCGCGGATCAGAATGTCGCGGTGAATACGTTCCCGGGTCT
>502492
ATTGAACGCTGGCGGCATGCCTTACACATGCAAGTCGAACGGTAACGGGTCCTTCGGGATGCCGACGAGTGGCGAACGGG
TGAGTAATATATCGGAACGTGCCCAGTAGTGGGGGATAACTGCTCGAAAGAGCAGCTAATACCGCATACGACCTGAGGGT
GAAAGGGGGGGATCGCAAGACCTCTCGCTATTGGAGCGGCCGATATCAGATTAGCTAGTTGGTGGGGTAAAGGCCTACCA
AGGCAACGATCTGTAGTTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCA
GCAGTGGGGAATTTTGGACAATGGGCGCAAGCCTGATCCAGCAATGCCGCGTGCAGGAAGAAGGCCTTCGGGTTGTAAAC
TGCTTTTGTCAGGGAAGAAATCTTCTGGGCTAATACCCCGGGAGGATGACGGTACCTGAAGAATAAGCACCGGCTAACTA
CGTGCCAGCAGCCGCGGTAATACGTAGGGTGCGAGCGTTAATCGGAATTACTGGGCGTAAAGCGTGCGCAGGCGGCTTTG
CAAGACAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATTTGTGACTGCAAGGCTAGAGTACGGCAGAGGGGGATG
GAATTCCGCGTGTAGCAGTGAAATGCGTAGATATGCGGAGGAACACCAATGGCGAAGGCAATCCCCTGGGCCTGTACTGA
CGCTCATGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCCTAAACGATGTCAACTGGTTGT
TGGACGGCTTGCTGTTCAGTAACGAAGCTAACGCGTGAAGTTGACCGCCTGGGGAGTACGGCCGCAAGGTTGAAACTCAA
AGGAATTGACGGGGACCCGCACAAGCGGTGGATGATGTGGTTTAATTCGATGCAACGCGAAAAACCTTACCTACCCTTGA
CATGTCAAGAATTCTGCAGAGATGTGGAAGTGCTCGAAAGAGAACTTGAACACAGGTGCTGCATGGCCGTCGTCAGCTCG
TGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGTCATTAGTTGCTACGCAAGAGCACTCTAATGAGAC
TGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAGGTCCTCATGGCCCTTATGGGTAGGGCTACACACGTCATACA
ATGGCCGGTACAGAGGGCTGCCAACCCGCGAGGGGGAGCCAATCCCAGAAAACCGGTCGTAGTCCGGATCGTAGTCTGCA
ACTCGACTGCGTGAAGTCGGAATCGCTAGTAATCGCGGATCAGCTTGCCGCGGTGAATACGTTCCCGGGTCT
"""
rtax_test_repset_fasta = """>clusterIdA splitRead1IdA
ACCAAGGCTTTGACGGGTAGCCGGCCTGAGTGGGTGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTACGGGA
>clusterIdB splitRead1IdB
CCGACGATCTGTAGCTGGTCTGAGAGGATGTTCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGC
>clusterIdC splitRead1IdC
AGGCAACGATCTGTAGTTGGTCTGAGAGGAGGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCA
>clusterIdD splitRead1IdD
AGGCAACGATCTGTAGTTGGTCTGAGAGGAGGACCAGCCACACTGGGACGGGGGGGGGGCCCAGACTCCTACGGGAGGCA
"""
# these reads are the 4th and 14th lines from the reference seqs
#rtax_test_read1_fasta = """>splitRead1IdA ampliconId_34563456/1
#ACCAAGGCTTTGACGGGTAGCCGGCCTGAGAGGGTGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTACGGGA
#>splitRead1IdB ampliconId_
#CCGACGATCTGTAGCTGGTCTGAGAGGATGATCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGC
#>splitRead1IdC ampliconId_
#AGGCAACGATCTGTAGTTGGTCTGAGAGGACGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCA
#"""
#
#rtax_test_read2_fasta = """>splitRead2IdA ampliconId_34563456/3
#GGGTTAAGTCCCGCAACGAGCGCAACCCTTGTTCACTGTTGCCAGCACGTTATGGTGGGGACTCAGTGGAGACCGCCGGG
#>splitRead2IdB ampliconId_
#TCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGCCATTAGTTGCTACGAAAGGGCACTCTAATGGGACTG
#>splitRead2IdC ampliconId_
#TGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGTCATTAGTTGCTACGCAAGAGCACTCTAATGAGAC
#"""
# these reads are the 4th and 14th lines from the reference seqs, with one nucleotide changed each
# except D and E, which are unique to one read or the other
# and F and G, which are just decoys
rtax_test_read1_fasta = """>splitRead1IdA ampliconId_34563456/1
ACCAAGGCTTTGACGGGTAGCCGGCCTGAGTGGGTGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTACGGGA
>splitRead1IdB ampliconId_12341234/1
CCGACGATCTGTAGCTGGTCTGAGAGGATGTTCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGC
>splitRead1IdC ampliconId_23452345/1
AGGCAACGATCTGTAGTTGGTCTGAGAGGAGGACCAGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCA
>splitRead1IdD ampliconId_45674567/1
AGGCAACGATCTGTAGTTGGTCTGAGAGGAGGACCAAAAAAAAAAAGACTGAGACACGGCCCAGACTCCTACGGGAGGCA
>splitRead1IdF ampliconId_56785678/1
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
"""
rtax_test_read2_fasta = """>splitRead2IdA ampliconId_34563456/3
GGGTTAAGTCCCGCAACGAGCGCAACCCTTATTCACTGTTGCCAGCACGTTATGGTGGGGACTCAGTGGAGACCGCCGGG
>splitRead2IdB ampliconId_12341234/3
TCGTGAGATGTTGGGTTAAGTCCCGCAACGTGCGCAACCCTTGCCATTAGTTGCTACGAAAGGGCACTCTAATGGGACTG
>splitRead2IdC ampliconId_23452345/3
TGTCGTGAGATGTTGGGTTAAGTCCCGCAAAGAGCGCAACCCTTGTCATTAGTTGCTACGCAAGAGCACTCTAATGAGAC
>splitRead2IdE ampliconId_67896789/3
TGTCGTGAGATGTTGGGTTAAAAAAAAAAAAAAACGCAACCCTTGTCATTAGTTGCTACGCAAGAGCACTCTAATGAGAC
>splitRead2IdG ampliconId_78907890/3
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT
"""
rtax_expected_result_paired = {
'clusterIdA splitRead1IdA': ('k__Bacteria; p__Actinobacteria; c__Actinobacteria; o__Actinomycetales; f__Propionibacteriaceae; g__Propionibacterium; s__Propionibacterium acnes', 1.0),
'clusterIdB splitRead1IdB': ('k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae; g__Diaphorobacter; s__', 1.0),
'clusterIdC splitRead1IdC': ('k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__; g__Aquabacterium; s__', 1.0),
}
rtax_expected_result_paired_with_fallback = {
'clusterIdA splitRead1IdA': ('k__Bacteria; p__Actinobacteria; c__Actinobacteria; o__Actinomycetales; f__Propionibacteriaceae; g__Propionibacterium; s__Propionibacterium acnes', 1.0),
'clusterIdB splitRead1IdB': ('k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae; g__Diaphorobacter; s__', 1.0),
'clusterIdC splitRead1IdC': ('k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__; g__Aquabacterium; s__', 1.0),
'clusterIdD splitRead1IdD': ('k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__; g__Aquabacterium; s__', 1.0),
}
rtax_expected_result_single = {
'clusterIdA splitRead1IdA': ('k__Bacteria; p__Actinobacteria; c__Actinobacteria; o__Actinomycetales; f__Propionibacteriaceae; g__Propionibacterium; s__Propionibacterium acnes', 1.0),
'clusterIdB splitRead1IdB': ('k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae; g__Diaphorobacter; s__', 1.0),
'clusterIdC splitRead1IdC': ('k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__; g__Aquabacterium; s__', 1.0),
'clusterIdD splitRead1IdD': ('k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__; g__Aquabacterium; s__', 1.0),
}
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_app/test_sfffile.py 000644 000765 000024 00000006047 12024702176 022260 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# test_sfffile.py
import os
import tempfile
from cogent.util.unit_test import TestCase, main
from cogent.parse.binary_sff import parse_binary_sff
from cogent.app.util import ApplicationError
from cogent.app.sfffile import Sfffile
__author__ = "Kyle Bittinger"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Kyle Bittinger"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Kyle Bittinger"
__email__ = "kylebittinger@gmail.com"
__status__ = "Prototype"
class SfffileTests(TestCase):
"""Test the Sfffile application controller.
"""
def setUp(self):
test_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
self.sff_fp = os.path.join(test_dir, 'data', 'test.sff')
def _check_unmodified_sff_contents(self, sff_file):
"""Extracting repeated code from sfffile tests"""
sff_file.seek(0)
header, reads_gen = parse_binary_sff(sff_file)
reads = list(reads_gen)
self.assertEqual(header["number_of_reads"], 1)
self.assertEqual(len(reads), 1)
self.assertEqual(reads[0]['Name'], 'FA6P1OK01CGMHQ')
def test_exit_status(self):
"""Sfffile should raise ApplicationError if exit status is nonzero."""
a = Sfffile()
self.assertRaises(ApplicationError, a, 'an_sff_file_that_does_not_exist.sff')
def test_call(self):
"""Simple sfffile call should produce expected output."""
a = Sfffile()
app_results = a(self.sff_fp)
self._check_unmodified_sff_contents(app_results['sff'])
app_results.cleanUp()
def test_call_with_output_path(self):
"""Sfffile should store output to specified filepath."""
_, output_fp = tempfile.mkstemp()
a = Sfffile()
a.Parameters['-o'].on(output_fp)
app_results = a(self.sff_fp)
self._check_unmodified_sff_contents(open(output_fp))
self._check_unmodified_sff_contents(app_results['sff'])
app_results.cleanUp()
def test_call_with_included_accession_numbers(self):
"""Sfffile should include specified accession numbers in output."""
accno_file = tempfile.NamedTemporaryFile()
accno_file.write('FA6P1OK01CGMHQ\n')
accno_file.seek(0)
a = Sfffile()
a.Parameters['-i'].on(accno_file.name)
app_results = a(self.sff_fp)
self._check_unmodified_sff_contents(app_results['sff'])
app_results.cleanUp()
def test_call_with_excluded_accession_numbers(self):
"""Sfffile should exclude specified accession numbers in output."""
accno_file = tempfile.NamedTemporaryFile()
accno_file.write('FA6P1OK01CGMHQ\n')
accno_file.seek(0)
a = Sfffile()
a.Parameters['-e'].on(accno_file.name)
app_results = a(self.sff_fp)
header, reads_gen = parse_binary_sff(app_results['sff'])
reads = list(reads_gen)
self.assertEqual(header["number_of_reads"], 0)
self.assertEqual(len(reads), 0)
app_results.cleanUp()
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_sffinfo.py 000644 000765 000024 00000027072 12024702176 022275 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# test_sffinfo.py
import os
import shutil
import tempfile
from cogent.util.unit_test import TestCase, main
from cogent.app.util import ApplicationError
from cogent.app.sffinfo import (
ManyValuedParameter, Sffinfo, sffinfo_from_file)
__author__ = "Kyle Bittinger"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Kyle Bittinger"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Kyle Bittinger"
__email__ = "kylebittinger@gmail.com"
__status__ = "Prototype"
class ManyValuedParameterTests(TestCase):
def test_init(self):
"""__init__() should set appropriate class variables."""
p = ManyValuedParameter(None, None)
self.assertEqual(p.Name, None)
self.assertEqual(p.Value, None)
self.assertEqual(p.Delimiter, None)
self.assertEqual(p.Quote, None)
p = ManyValuedParameter('-', 'a', Values=['abc'])
self.assertEqual(p.Value, ['abc'])
def test_append(self):
"""append() should append values to Value class attribute."""
p = ManyValuedParameter(None, None)
p.append('abc')
p.append(3)
self.assertEqual(p.Value, ['abc', 3])
def test_on(self):
"""on() should alias append()."""
p = ManyValuedParameter(None, None)
p.on('abc')
p.on(3)
self.assertEqual(p.Value, ['abc', 3])
def test_str(self):
"""__str__() should produce quoted, delimited string of parameter values."""
p = ManyValuedParameter(None, None)
p.append('abc')
p.append(3)
self.assertEqual(str(p), 'abc3')
p = ManyValuedParameter(None, None, Quote='"', ValueDelimiter=',')
p.append('abc')
p.append(3)
self.assertEqual(str(p), '"abc","3"')
class SffinfoTests(TestCase):
def setUp(self):
test_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
self.sff_fp = os.path.join(test_dir, 'data', 'test.sff')
def test_base_command(self):
"""BaseCommand should include non-positional parameters."""
s = Sffinfo()
expected = 'cd "%s/"; sffinfo' % os.getcwd()
self.assertEqual(s.BaseCommand, expected)
s.Parameters['-a'].on()
expected = 'cd "%s/"; sffinfo -a' % os.getcwd()
self.assertEqual(s.BaseCommand, expected)
# accession number parameters should not be included in base command
s.Parameters['-a'].off()
s.Parameters['accno'].on('12345ABC')
expected = 'cd "%s/"; sffinfo' % os.getcwd()
self.assertEqual(s.BaseCommand, expected)
def test_changing_working_dir(self):
"""WorkingDir should be created and included in BaseCommand."""
# Directory is not created, only filename is returned
working_dir = tempfile.mktemp()
self.assertRaises(OSError, os.rmdir, working_dir)
a = Sffinfo(WorkingDir=working_dir)
expected = 'cd "%s/"; sffinfo' % working_dir
self.assertEqual(a.BaseCommand, expected)
# Removing the directory is proof that it was created. If the
# directory is not there, an OSError will be raised.
os.rmdir(working_dir)
def test_input_handler(self):
"""Sffinfo should decorate input handler output with accession numbers"""
my_accno = '12345ABC'
a = Sffinfo()
a.Parameters['accno'].on(my_accno)
self.assertEqual(a.InputHandler, '_input_handler_decorator')
observed = getattr(a, a.InputHandler)(self.sff_fp)
expected = '"%s" %s' % (self.sff_fp, my_accno)
self.assertEqual(observed, expected)
def test_call(self):
"""Simple sffinfo call should produce expected output."""
a = Sffinfo()
app_results = a(self.sff_fp)
observed = app_results['StdOut'].read()
self.assertEqual(observed, sffinfo_output)
def test_call_with_accno(self):
"""Sffinfo accession number parameters should filter output."""
# Valid accession number
a = Sffinfo()
a.Parameters['accno'].on('FA6P1OK01CGMHQ')
app_results = a(self.sff_fp)
observed = app_results['StdOut'].read()
self.assertEqual(observed, sffinfo_output)
# Invalid accession number
a = Sffinfo()
a.Parameters['accno'].on('AAAAAAAAAAAAAA')
app_results = a(self.sff_fp)
observed = app_results['StdOut'].read()
self.assertEqual(observed, empty_sffinfo_output)
def test_call_with_flags(self):
"""Sffinfo flags should alter output as expected."""
# -a flag
a = Sffinfo()
a.Parameters['-a'].on()
app_results = a(self.sff_fp)
observed = app_results['StdOut'].read()
self.assertEqual(observed, 'FA6P1OK01CGMHQ\n')
# -s flag
a = Sffinfo()
a.Parameters['-s'].on()
app_results = a(self.sff_fp)
observed = app_results['StdOut'].read()
expected = (
'>FA6P1OK01CGMHQ length=48 xy=0892_1356 region=1 '
'run=R_2008_05_28_17_11_38_\n'
'ATCTGAGCTGGGTCATAGCTGCCTCCGTAGGAGGTGCCTCCCTACGGC\n'
)
self.assertEqual(observed, expected)
# -q flag
a = Sffinfo()
a.Parameters['-q'].on()
app_results = a(self.sff_fp)
observed = app_results['StdOut'].read()
expected = (
'>FA6P1OK01CGMHQ length=48 xy=0892_1356 region=1 '
'run=R_2008_05_28_17_11_38_\n'
'32 32 32 32 32 32 32 25 25 21 21 21 28 32 32 31 30 30 32 32 32 '
'33 31 25 18 18 20 18 32 30 28 23 22 22 24 28 18 19 18 16 16 16 '
'17 18 13 17 27 21\n')
self.assertEqual(observed, expected)
# -f flag
a = Sffinfo()
a.Parameters['-f'].on()
app_results = a(self.sff_fp)
observed = app_results['StdOut'].read()
expected = (
'>FA6P1OK01CGMHQ xy=0892_1356 region=1 run=R_2008_05_28_17_11_38_\n'
'A,1.02 C,0.00 G,0.00 T,0.99 A,0.00 C,1.00 G,0.00 T,1.00 A,0.00 C,0.00\n'
'G,1.00 T,0.00 A,1.10 C,0.00 G,1.08 T,0.00 A,0.00 C,1.46 G,0.00 T,0.88\n'
'A,0.18 C,0.00 G,2.69 T,1.01 A,0.08 C,0.96 G,0.00 T,0.02 A,0.92 C,0.08\n'
'G,0.00 T,0.98 A,0.68 C,0.00 G,0.89 T,0.00 A,0.00 C,1.15 G,0.00 T,1.13\n'
'A,0.00 C,0.02 G,1.12 T,0.05 A,0.15 C,1.84 G,0.00 T,1.10 A,0.00 C,2.47\n'
'G,0.96 T,0.86 A,1.06 C,0.00 G,1.96 T,0.12 A,0.93 C,0.13 G,1.65 T,1.06\n'
'A,0.06 C,0.00 G,0.99 T,0.00 A,0.00 C,1.87 G,0.44 T,1.08 A,0.00 C,3.25\n'
'G,0.09 T,0.97 A,0.50 C,1.00 G,1.72 T,0.07 A,0.00 C,0.92 \n')
self.assertEqual(observed, expected)
class SffinfoFunctionTests(TestCase):
def test_sffinfo_from_file(self):
"""sffinfo_from_file should return file object with sffinfo output."""
test_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sff_fp = os.path.join(test_dir, 'data', 'test.sff')
observed = sffinfo_from_file(sff_fp).read()
self.assertEqual(observed, sffinfo_output)
sffinfo_output = '''Common Header:
Magic Number: 0x2E736666
Version: 0001
Index Offset: 1504
Index Length: 706
# of Reads: 1
Header Length: 440
Key Length: 4
# of Flows: 400
Flowgram Code: 1
Flow Chars: TACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACG
Key Sequence: TCAG
>FA6P1OK01CGMHQ
Run Prefix: R_2008_05_28_17_11_38_
Region #: 1
XY Location: 0892_1356
Run Name: R_2008_05_28_17_11_38_FLX02070135_adminrig_KnightLauber
Analysis Name: /data/2008_05_28/R_2008_05_28_17_11_38_FLX02070135_adminrig_KnightLauber/D_2008_05_28_21_13_06_FLX02070135_KnightLauber_FullAnalysisAmplicons
Full Path: /data/2008_05_28/R_2008_05_28_17_11_38_FLX02070135_adminrig_KnightLauber/D_2008_05_28_21_13_06_FLX02070135_KnightLauber_FullAnalysisAmplicons/../D_2008_05_29_13_52_01_FLX02070135_Knight_Lauber_jones_SignalProcessingAmplicons
Read Header Len: 32
Name Length: 14
# of Bases: 77
Clip Qual Left: 5
Clip Qual Right: 52
Clip Adap Left: 0
Clip Adap Right: 0
Flowgram: 1.04 0.00 1.01 0.00 0.00 0.96 0.00 1.02 0.00 1.02 0.00 0.00 0.99 0.00 1.00 0.00 1.00 0.00 0.00 1.00 0.00 1.10 0.00 1.08 0.00 0.00 1.46 0.00 0.88 0.18 0.00 2.69 1.01 0.08 0.96 0.00 0.02 0.92 0.08 0.00 0.98 0.68 0.00 0.89 0.00 0.00 1.15 0.00 1.13 0.00 0.02 1.12 0.05 0.15 1.84 0.00 1.10 0.00 2.47 0.96 0.86 1.06 0.00 1.96 0.12 0.93 0.13 1.65 1.06 0.06 0.00 0.99 0.00 0.00 1.87 0.44 1.08 0.00 3.25 0.09 0.97 0.50 1.00 1.72 0.07 0.00 0.92 0.58 0.00 0.00 0.59 0.06 0.11 0.09 0.07 0.06 0.16 0.00 0.24 0.03 0.00 0.12 0.06 0.16 0.00 0.18 0.00 0.00 0.14 0.00 0.15 0.00 0.18 0.00 0.03 0.14 0.03 0.13 0.01 0.19 0.00 0.02 0.33 0.05 0.00 0.16 0.10 0.35 0.01 0.21 0.04 0.09 0.18 0.13 0.19 0.00 0.10 0.51 0.26 0.00 0.23 0.19 0.27 0.01 0.29 0.05 0.14 0.17 0.16 0.18 0.27 0.09 0.26 0.10 0.18 0.23 0.15 0.22 0.13 0.37 0.11 0.11 0.26 0.59 0.14 0.06 0.33 0.34 0.26 0.05 0.27 0.44 0.19 0.10 0.35 0.27 0.15 0.34 0.28 0.45 0.14 0.16 0.34 0.27 0.12 0.07 0.25 0.18 0.12 0.04 0.23 0.16 0.12 0.05 0.20 0.16 0.11 0.03 0.21 0.16 0.10 0.02 0.21 0.16 0.12 0.02 0.20 0.15 0.10 0.02 0.23 0.15 0.11 0.02 0.22 0.14 0.09 0.02 0.20 0.13 0.09 0.01 0.19 0.13 0.08 0.02 0.17 0.12 0.08 0.03 0.17 0.09 0.08 0.01 0.14 0.09 0.07 0.01 0.15 0.09 0.06 0.01 0.13 0.08 0.06 0.00 0.13 0.08 0.05 0.02 0.12 0.07 0.05 0.01 0.11 0.07 0.05 0.00 0.10 0.07 0.05 0.01 0.11 0.08 0.04 0.00 0.10 0.06 0.05 0.01 0.09 0.06 0.04 0.01 0.08 0.07 0.05 0.00 0.08 0.06 0.05 0.00 0.09 0.06 0.04 0.00 0.09 0.06 0.04 0.01 0.08 0.06 0.04 0.00 0.09 0.06 0.03 0.00 0.09 0.06 0.02 0.00 0.09 0.06 0.04 0.00 0.08 0.05 0.03 0.00 0.07 0.05 0.02 0.00 0.08 0.04 0.03 0.00 0.07 0.04 0.03 0.00 0.07 0.05 0.02 0.00 0.07 0.05 0.02 0.00 0.06 0.04 0.02 0.00 0.06 0.03 0.03 0.00 0.08 0.02 0.00 0.00 0.07 0.03 0.01 0.00 0.06 0.03 0.02 0.00 0.05 0.03 0.02 0.00 0.05 0.03 0.01 0.00 0.06 0.02 0.00 0.00 0.05 0.01 0.01 0.00 0.04 0.01 0.01 0.00 0.04 0.01 0.01 0.00 0.05 0.01 0.00 0.00 0.04 0.02 0.01 0.00 0.03 0.02 0.01 0.00 0.03 0.01 0.00 0.00 0.03 0.00 0.00 0.00 0.03 0.00 0.00 0.00 0.02 0.00
Flow Indexes: 1 3 6 8 10 13 15 17 20 22 24 27 29 32 32 32 33 35 38 41 42 44 47 49 52 55 55 57 59 59 60 61 62 64 64 66 68 68 69 72 75 75 77 79 79 79 81 82 83 84 84 87 88 91 102 126 130 138 140 145 153 157 161 164 166 171 175 179 183 187 191 195 199 203 211 215 219
Bases: tcagATCTGAGCTGGGTCATAGCTGCCTCCGTAGGAGGTGCCTCCCTACGGCgcnnnannnnngnnnnnnnnnnnnn
Quality Scores: 32 32 32 32 32 32 32 32 32 32 32 25 25 21 21 21 28 32 32 31 30 30 32 32 32 33 31 25 18 18 20 18 32 30 28 23 22 22 24 28 18 19 18 16 16 16 17 18 13 17 27 21 20 21 0 0 0 17 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 0 0
'''
empty_sffinfo_output = '''Common Header:
Magic Number: 0x2E736666
Version: 0001
Index Offset: 1504
Index Length: 706
# of Reads: 1
Header Length: 440
Key Length: 4
# of Flows: 400
Flowgram Code: 1
Flow Chars: TACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACG
Key Sequence: TCAG
'''
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_sfold.py 000644 000765 000024 00000005434 12024702176 021750 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""Provides Tests for Sfold application controller.
IMPORTANT!!! don't forget to set param_dir variable in sfold
application controller IMPORTANT!!!
"""
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.app.sfold import Sfold
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class SfoldTest(TestCase):
"""Tests for Sfold application controller"""
def setUp(self):
self.input = sfold_input
def test_stdout_input_as_lines(self):
"""Test Sfold stdout input as lines"""
s = Sfold(InputHandler='_input_as_lines')
res = s(self.input)
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test Sfold stdout input as string"""
s = Sfold()
f = open('/tmp/single.fasta','w')
f.write('\n'.join(self.input))
f.close()
res = s('/tmp/single.fasta')
self.assertEqual(res['ExitStatus'],0)
assert res['StdOut'] is not None
res.cleanUp()
remove('/tmp/single.fasta')
def test_get_result_path(self):
"""Tests sfold result path"""
s = Sfold(InputHandler='_input_as_lines')
res = s(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus',
'10structure','10structure_2','Dharmacon_thermo','bp',
'bprob','cdf','fe','loopr','oligo','oligo_f','pdf',
'sample','sample_1000','sirna','sirna_f','sirna_s',
'smfe','sstrand','stability'])
self.assertEqual(res['ExitStatus'],0)
assert res['10structure'] is not None
assert res['10structure_2'] is not None
assert res['Dharmacon_thermo'] is not None
assert res['bp'] is not None
assert res['cdf'] is not None
assert res['fe'] is not None
assert res['loopr'] is not None
assert res['oligo'] is not None
assert res['oligo_f'] is not None
assert res['pdf'] is not None
assert res['sample'] is not None
assert res['sample_1000'] is not None
assert res['sirna'] is not None
assert res['sirna_f'] is not None
assert res['sirna_s'] is not None
assert res['smfe'] is not None
assert res['sstrand'] is not None
assert res['stability'] is not None
res.cleanUp()
sfold_input = ['>seq1\n',
'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n',
'\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_stride.py 000644 000765 000024 00000004377 12024702176 022140 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
import os, tempfile
try:
from cogent.util.unit_test import TestCase, main
from cogent.parse.pdb import PDBParser
from cogent.app.stride import Stride
except ImportError:
from zenpdb.cogent.util.unit_test import TestCase, main
from zenpdb.cogent.parse.pdb import PDBParser
from zenpdb.cogent.app.stride import Stride
__author__ = "Marcin Cieslik"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Marcin Cieslik"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Marcin Cieslik"
__email__ = "mpc4p@virginia.edu"
__status__ = "Development"
class StrideTest(TestCase):
"""Tests for Stride application controller"""
def setUp(self):
self.input_file = os.path.join('data', '2E12.pdb')
self.input_structure = PDBParser(open(self.input_file))
def test_stdout_input_from_entity(self):
"""Test Stride when input is an entity"""
s = Stride()
res = s(self.input_structure)
self.assertEqual(res['ExitStatus'], 0)
assert res['StdOut'] is not None
self.assertTrue(res['StdOut'].readline().endswith('--------- 2E12\n'))
self.assertEquals(len(res['StdOut'].readlines()), 267)
res.cleanUp()
def test_stdout_input_from_path(self):
"""Test Stride when input is an entity"""
s = Stride(InputHandler='_input_as_path')
res = s(self.input_file)
self.assertEqual(res['ExitStatus'], 0)
assert res['StdOut'] is not None
self.assertTrue(res['StdOut'].readline().endswith('--------- 2E12\n'))
self.assertEquals(len(res['StdOut'].readlines()), 267)
res.cleanUp()
def test_get_result_path(self):
"""Tests stride result path"""
s = Stride()
fd, name = tempfile.mkstemp()
os.close(fd)
s.Parameters['-f'].on(name)
res = s(self.input_structure)
self.assertEqual(res['ExitStatus'], 0)
self.assertEqualItems(res.keys(), ['StdOut', 'StdErr', 'ExitStatus', 'File'])
self.assertTrue(res['File'].readline().endswith('--------- 2E12\n'))
self.assertEquals(len(res['File'].readlines()), 267)
res.cleanUp()
self.assertFalse(os.path.exists(name))
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_uclust.py 000755 000765 000024 00000073140 12024702176 022162 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""
: provides unit tests for the uclust.py module
Modified from Daniel McDonald's test_cd_hit.py code on Feb-4-2010 """
from os import getcwd, rmdir, remove
from subprocess import Popen, PIPE, STDOUT
from os.path import isfile
from cogent.util.misc import remove_files
from cogent.core.moltype import DNA
from cogent.util.unit_test import TestCase, main
from cogent.app.util import ApplicationError, get_tmp_filename
from cogent.app.uclust import (Uclust,
uclust_fasta_sort_from_filepath,
uclust_cluster_from_sorted_fasta_filepath,
get_output_filepaths,clusters_from_uc_file,
get_clusters_from_fasta_filepath,
uclust_search_and_align_from_fasta_filepath,
process_uclust_pw_alignment_results, UclustParseError)
__author__ = "William Walters"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Daniel McDonald","William Walters","Greg Caporaso"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "William Walters"
__email__ = "William.A.Walters@colorado.edu"
__status__ = "Production"
class UclustTests(TestCase):
def setUp(self):
self.tmp_unsorted_fasta_filepath = \
get_tmp_filename(prefix="uclust_test", suffix=".fasta")
tmp_unsorted_fasta = open(self.tmp_unsorted_fasta_filepath,"w")
tmp_unsorted_fasta.write('\n'.join(raw_dna_seqs))
tmp_unsorted_fasta.close()
self.tmp_sorted_fasta_filepath = \
get_tmp_filename(prefix = "uclust_test", suffix = ".fasta")
tmp_sorted_fasta = open(self.tmp_sorted_fasta_filepath,"w")
tmp_sorted_fasta.write('\n'.join(sorted_dna_seqs))
tmp_sorted_fasta.close()
self.tmp_uc_filepath = \
get_tmp_filename(prefix = "uclust_test", suffix = ".uc")
tmp_uc = open(self.tmp_uc_filepath,"w")
tmp_uc.write('\n'.join(uc_dna_clusters))
tmp_uc.close()
self.tmp_clstr_filepath = \
get_tmp_filename(prefix = "uclust_test", suffix = ".clstr")
self.WorkingDir = '/tmp/uclust_test'
self.tmpdir = '/tmp/'
self.files_to_remove = [self.tmp_unsorted_fasta_filepath,
self.tmp_sorted_fasta_filepath,
self.tmp_uc_filepath,
self.tmp_clstr_filepath]
def tearDown(self):
remove_files(self.files_to_remove,error_on_missing=False)
def test_fasta_sorting(self):
""" Should sort fasta seqs from largest to smallest in outfile
Since a fasta file has to be passed to the app controller for uclust,
a temporary fasta file is created, and the raw fasta seqs supplied
in this module are written to it. This file is sent to the app
controller, and the resulting sorted file is compared to the expected
results to ensure proper function of uclust as called by this app
controller."""
test_app = Uclust({'--tmpdir':self.tmpdir})
test_app_res = test_app(data = \
{'--mergesort':self.tmp_unsorted_fasta_filepath,\
'--output':self.tmp_sorted_fasta_filepath})
sorted_fasta_actual = [l.strip()
for l in open(test_app_res['Output'].name,"U")]
sorted_fasta_expected = [l.strip() for l in sorted_dna_seqs if l]
self.assertEqual(sorted_fasta_actual,sorted_fasta_expected)
test_app_res.cleanUp()
def test_clustering_fasta_filepath(self):
""" Should create clusters in uclust format from sorted fasta file
Since a fasta file has to be passed to the app controller for uclust,
a temporary fasta file is created, and the sorted seqs supplied
in this module are written to it. This file is sent to the app
controller, and the resulting uclust file is compared to the expected
results to ensure proper function of uclust as called by this app
controller."""
test_app = Uclust({'--id':0.9},HALT_EXEC=False)
test_app_res = test_app(data = \
{'--input':self.tmp_sorted_fasta_filepath,\
'--uc':self.tmp_uc_filepath})
uc_file = open(test_app_res['ClusterFile'].name,"U")
# compare the actual and expect uc files, ignoring comment lines
uc_file_actual = [l.strip() for l in uc_file
if not l.startswith('#')]
uc_file_expected = [l.strip() for l in uc_dna_clusters
if not l.startswith('#')]
self.assertEqual(uc_file_actual, uc_file_expected)
test_app_res.cleanUp()
class UclustConvenienceWrappers(TestCase):
""" Unit tests for uclust convenience wrappers """
def setUp(self):
self.tmp_unsorted_fasta_filepath = \
get_tmp_filename(prefix = "uclust_test", suffix = ".fasta")
tmp_unsorted_fasta = open(self.tmp_unsorted_fasta_filepath,"w")
tmp_unsorted_fasta.write('\n'.join(raw_dna_seqs))
tmp_unsorted_fasta.close()
self.tmp_raw_dna_seqs_rc_filepath = \
get_tmp_filename(prefix = "uclust_test", suffix = ".fasta")
tmp_rc_fasta = open(self.tmp_raw_dna_seqs_rc_filepath,"w")
tmp_rc_fasta.write('\n'.join(raw_dna_seqs_rc))
tmp_rc_fasta.close()
self.tmp_sorted_fasta_filepath = \
get_tmp_filename(prefix = "uclust_test", suffix = ".fasta")
tmp_sorted_fasta = open(self.tmp_sorted_fasta_filepath,"w")
tmp_sorted_fasta.write('\n'.join(sorted_dna_seqs))
tmp_sorted_fasta.close()
self.tmp_uc_filepath = \
get_tmp_filename(prefix = "uclust_test", suffix = ".uc")
tmp_uc = open(self.tmp_uc_filepath,"w")
tmp_uc.write('\n'.join(uc_dna_clusters))
tmp_uc.close()
self.tmp_clstr_filepath = \
get_tmp_filename(prefix = "uclust_test", suffix = ".clstr")
self.search_align_out1_expected = search_align_out1_expected
self.search_align_out_fasta_pairs1 = search_align_out_fasta_pairs1
self.search_align_out_uc1 = search_align_out_uc1
self.search_align_query1_fp = \
get_tmp_filename(prefix = "uclust_test", suffix = ".clstr")
open(self.search_align_query1_fp,'w').write(search_align_query1)
self.search_align_template1_fp = \
get_tmp_filename(prefix = "uclust_test", suffix = ".clstr")
open(self.search_align_template1_fp,'w').write(search_align_template1)
self.search_align_out2_expected = search_align_out2_expected
self.search_align_query2_fp = \
get_tmp_filename(prefix = "uclust_test", suffix = ".clstr")
open(self.search_align_query2_fp,'w').write(search_align_query2)
self.search_align_template2_fp = \
get_tmp_filename(prefix = "uclust_test", suffix = ".clstr")
open(self.search_align_template2_fp,'w').write(search_align_template2)
self.ref_dna_seqs_fp = get_tmp_filename(prefix = "uclust_test", suffix = ".fasta")
open(self.ref_dna_seqs_fp,'w').write(ref_dna_seqs)
self.files_to_remove = [self.tmp_unsorted_fasta_filepath,
self.tmp_raw_dna_seqs_rc_filepath,
self.tmp_sorted_fasta_filepath,
self.tmp_uc_filepath,
self.tmp_clstr_filepath,
self.search_align_query1_fp,
self.search_align_template1_fp,
self.search_align_query2_fp,
self.search_align_template2_fp,
self.ref_dna_seqs_fp]
self.ref_test_clusters1 = ref_test_clusters1
self.ref_test_failures1 = ref_test_failures1
self.ref_test_new_seeds1 = ref_test_new_seeds1
self.ref_test_clusters2 = ref_test_clusters2
self.ref_test_failures2 = ref_test_failures2
self.ref_test_new_seeds2 = ref_test_new_seeds2
self.uc_dna_clusters = uc_dna_clusters
self.uc_lines1 = uc_lines1
self.uc_lines_overlapping_lib_input_seq_ids = \
uc_lines_overlapping_lib_input_seq_ids
def tearDown(self):
remove_files(self.files_to_remove,error_on_missing=False)
def test_uclust_fasta_sort_from_filepath(self):
""" Given an unsorted fasta filepath, will return sorted file """
app_res = \
uclust_fasta_sort_from_filepath(self.tmp_unsorted_fasta_filepath)
sorted_fasta_actual = [l.strip()
for l in open(app_res['Output'].name,"U")]
sorted_fasta_expected = [l.strip() for l in sorted_dna_seqs if l]
self.assertEqual(sorted_fasta_actual,sorted_fasta_expected)
app_res.cleanUp()
def test_clusters_from_uc_file(self):
""" clusters_from_uc_file functions as expected """
expected_clusters = {'s2':['s2','s3']}
expected_failures = ['s1']
expected_new_seeds = ['s2']
self.assertEqual(clusters_from_uc_file(self.uc_lines1),
(expected_clusters,expected_failures,expected_new_seeds))
def test_clusters_from_uc_file_error(self):
""" clusters_from_uc_file raises error when lib/input seq ids overlap"""
self.assertRaises(UclustParseError,
clusters_from_uc_file,
self.uc_lines_overlapping_lib_input_seq_ids)
def test_uclust_cluster_from_sorted_fasta_filepath(self):
""" Given a sorted fasta filepath, will return uclust (.uc) file """
app_res = \
uclust_cluster_from_sorted_fasta_filepath(self.tmp_sorted_fasta_filepath, \
percent_ID = 0.90,HALT_EXEC=False)
uc_file = open(app_res['ClusterFile'].name,"U")
# compare the actual and expect uc files, ignoring comment lines
uc_file_actual = [l.strip() for l in uc_file
if not l.startswith('#')]
uc_file_expected = [l.strip() for l in uc_dna_clusters
if not l.startswith('#')]
self.assertEqual(uc_file_actual, uc_file_expected)
app_res.cleanUp()
def test_get_output_filepaths(self):
""" Properly generates output filepath names """
uc_res = \
get_output_filepaths("/tmp/","test_seqs.fasta")
self.assertEqual(uc_res, "/tmp/test_seqs_clusters.uc")
def test_get_clusters_from_fasta_filepath(self):
""" Tests for return of lists of OTUs from given fasta filepath """
clusters_res = \
get_clusters_from_fasta_filepath(self.tmp_unsorted_fasta_filepath, \
original_fasta_path = None, percent_ID = 0.90, save_uc_files=False)
expected_cluster_list.sort()
expected_failure_list.sort()
expected_new_seed_list.sort()
clusters_res[0].sort()
clusters_res[1].sort()
clusters_res[2].sort()
self.assertEqual(clusters_res,(expected_cluster_list,
expected_failure_list,
expected_new_seed_list))
def test_get_clusters_from_fasta_filepath_reference_db_only(self):
""" Correct clusters returned when clustering against a database only
"""
clusters_res = get_clusters_from_fasta_filepath(
self.tmp_unsorted_fasta_filepath,
original_fasta_path = None,
save_uc_files=False,
max_accepts=7,max_rejects=12,
percent_ID = 0.90,
subject_fasta_filepath=self.ref_dna_seqs_fp,
suppress_new_clusters=True,
HALT_EXEC=False)
self.ref_test_clusters1.sort()
self.ref_test_failures1.sort()
self.ref_test_new_seeds1.sort()
clusters_res[0].sort()
clusters_res[1].sort()
clusters_res[2].sort()
self.assertEqual(clusters_res,(self.ref_test_clusters1,
self.ref_test_failures1,
self.ref_test_new_seeds1))
def test_get_clusters_from_fasta_filepath_extending_reference_db(self):
""" Correct clusters when clustering against db and adding new clusters
"""
clusters_res = get_clusters_from_fasta_filepath(
self.tmp_unsorted_fasta_filepath,
original_fasta_path = None,
max_accepts=7,max_rejects=12,
percent_ID = 0.90,
subject_fasta_filepath=self.ref_dna_seqs_fp,
suppress_new_clusters=False,enable_rev_strand_matching=True,
HALT_EXEC=False,
save_uc_files=False)
self.ref_test_clusters2.sort()
self.ref_test_failures2.sort()
self.ref_test_new_seeds2.sort()
clusters_res[0].sort()
clusters_res[1].sort()
clusters_res[2].sort()
self.assertEqual(clusters_res,(self.ref_test_clusters2,
self.ref_test_failures2,
self.ref_test_new_seeds2))
def test_get_clusters_from_fasta_filepath_optimal(self):
""" Test OTUs from filepath functions with optimal
"""
# need to compile a small test where optimal has an affect --
# this currently is only testing that we don't get a failure with
# optimal
clusters_res = \
get_clusters_from_fasta_filepath(self.tmp_unsorted_fasta_filepath,
original_fasta_path = None, save_uc_files=False,
percent_ID = 0.90, optimal = True)
expected_cluster_list.sort()
expected_failure_list.sort()
expected_new_seed_list.sort()
clusters_res[0].sort()
clusters_res[1].sort()
clusters_res[2].sort()
self.assertEqual(clusters_res,(expected_cluster_list,
expected_failure_list,
expected_new_seed_list))
def test_get_clusters_from_fasta_filepath_suppress_sort(self):
""" Test OTUs from filepath functions with suppress sort
"""
expected = [['uclust_test_seqs_0'], ['uclust_test_seqs_1'],
['uclust_test_seqs_2'], ['uclust_test_seqs_3'],
['uclust_test_seqs_4'], ['uclust_test_seqs_5'],
['uclust_test_seqs_6', 'uclust_test_seqs_8'],
['uclust_test_seqs_7'], ['uclust_test_seqs_9']]
clusters_res = \
get_clusters_from_fasta_filepath(self.tmp_unsorted_fasta_filepath,
original_fasta_path = None,
percent_ID = 0.90, suppress_sort = True, save_uc_files=False)
expected_cluster_list.sort()
expected_failure_list.sort()
expected_new_seed_list.sort()
clusters_res[0].sort()
clusters_res[1].sort()
clusters_res[2].sort()
self.assertEqual(clusters_res,(expected_cluster_list,
expected_failure_list,
expected_new_seed_list))
def test_get_clusters_from_fasta_filepath_rev_strand_match(self):
""" Test OTUs from filepath functions with rev strand match
"""
# seq and its rc don't cluster when enable_rev_strand_matching = False
expected_cluster_list = [['uclust_test_seqs_0'], ['uclust_test_seqs_0_rc']]
expected_failure_list = []
expected_new_seed_list = ['uclust_test_seqs_0', 'uclust_test_seqs_0_rc']
clusters_res = \
get_clusters_from_fasta_filepath(self.tmp_raw_dna_seqs_rc_filepath,
original_fasta_path = None, save_uc_files=False,
percent_ID = 0.90, enable_rev_strand_matching = False)
expected_cluster_list.sort()
expected_failure_list.sort()
expected_new_seed_list.sort()
clusters_res[0].sort()
clusters_res[1].sort()
clusters_res[2].sort()
self.assertEqual(clusters_res,(expected_cluster_list,
expected_failure_list,
expected_new_seed_list))
# seq and its rc cluster when enable_rev_strand_matching = False
expected_cluster_list = [['uclust_test_seqs_0', 'uclust_test_seqs_0_rc']]
expected_failure_list = []
expected_new_seed_list = ['uclust_test_seqs_0']
clusters_res = \
get_clusters_from_fasta_filepath(self.tmp_raw_dna_seqs_rc_filepath,
original_fasta_path = None, save_uc_files=False,
percent_ID = 0.90, enable_rev_strand_matching = True)
expected_cluster_list.sort()
expected_failure_list.sort()
expected_new_seed_list.sort()
clusters_res[0].sort()
clusters_res[1].sort()
clusters_res[2].sort()
self.assertEqual(clusters_res,(expected_cluster_list,
expected_failure_list,
expected_new_seed_list))
def test_process_uclust_pw_alignment_results(self):
"""parsing of pairwise alignment fasta pairs file functions as expected
"""
actual = list(process_uclust_pw_alignment_results(\
self.search_align_out_fasta_pairs1,self.search_align_out_uc1))
expected = self.search_align_out1_expected
# iterate over results so error output will highlight the bad match
for a,e in zip(actual,expected):
self.assertEqual(a,e)
# make sure the full result objects are the same
self.assertEqual(actual,expected)
def test_uclust_search_and_align_from_fasta_filepath(self):
""" uclust_search_and_align_from_fasta_filepath functions as expected """
# rev comp matches allowed (default)
actual = list(uclust_search_and_align_from_fasta_filepath(
self.search_align_query1_fp,self.search_align_template1_fp))
self.assertEqual(actual,self.search_align_out1_expected)
# rev comp matches not allowed
actual = list(uclust_search_and_align_from_fasta_filepath(
self.search_align_query1_fp,self.search_align_template1_fp,
enable_rev_strand_matching=False))
self.assertEqual(actual,self.search_align_out1_expected[:2])
def test_uclust_search_and_align_from_fasta_filepath_protein(self):
""" uclust_search_and_align_from_fasta_filepath functions with protein """
# rev comp matches allowed (default)
actual = list(uclust_search_and_align_from_fasta_filepath(
self.search_align_query2_fp,self.search_align_template2_fp))
self.assertEqual(actual,self.search_align_out2_expected)
def test_uclust_supported_version(self):
"""uclust version is supported """
command = 'uclust --version'
proc = Popen(command,shell=True,universal_newlines=True,\
stdout=PIPE,stderr=STDOUT)
stdout = proc.stdout.read()
version_string = stdout.strip().split('v')[-1].strip('q')
try:
version = tuple(map(int,version_string.split('.')))
acceptable_version = version >= (1,2,22)
except ValueError:
acceptable_version = False
self.assertTrue(acceptable_version,\
"Unsupported uclust version. 1.2.22 or later "+\
"is required, but running %s." % version_string)
raw_dna_seqs = """>uclust_test_seqs_0
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
>uclust_test_seqs_1
GCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>uclust_test_seqs_2
CCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
>uclust_test_seqs_3
CCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
>uclust_test_seqs_4
ACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
>uclust_test_seqs_5
CCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
>uclust_test_seqs_6
CGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
>uclust_test_seqs_7
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>uclust_test_seqs_8
CGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
>uclust_test_seqs_9
GGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
""".split('\n')
ref_dna_seqs = """>ref1 25 random bases appended to uclust_test_seqs_0 and one mismatch
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATATTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCTATAGCAGCCCCAGCGTTTACTTCTA
>ref2 15 random bases prepended to uclust_test_seqs_1 and one mismatch
GCTGCGGCGTCCTGCGCCACGGTGGGTACAACACGTCCACTACATCTGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>ref3 5 random bases prepended and 10 random bases appended to uclust_test_seqs_2
ATAGGCCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACTGCCTGATTCA
>ref4 exact match to uclust_test_seqs_3
CCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
"""
ref_test_clusters1 = [['uclust_test_seqs_0'],['uclust_test_seqs_1'],
['uclust_test_seqs_2'],['uclust_test_seqs_3']]
ref_test_failures1 = ['uclust_test_seqs_4','uclust_test_seqs_5',
'uclust_test_seqs_6','uclust_test_seqs_7',
'uclust_test_seqs_8','uclust_test_seqs_9']
ref_test_new_seeds1 = []
ref_test_clusters2 = [['uclust_test_seqs_0'],['uclust_test_seqs_1'],
['uclust_test_seqs_2'],['uclust_test_seqs_3'],
['uclust_test_seqs_4'],['uclust_test_seqs_5'],
['uclust_test_seqs_6','uclust_test_seqs_8'],
['uclust_test_seqs_7'],['uclust_test_seqs_9']]
ref_test_failures2 = []
ref_test_new_seeds2 = ['uclust_test_seqs_4','uclust_test_seqs_5','uclust_test_seqs_6',
'uclust_test_seqs_7','uclust_test_seqs_9']
raw_dna_seqs_rc = """>uclust_test_seqs_0
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
>uclust_test_seqs_0_rc
AGCTCTGACACAAAACTGACGTGATGTGCCTTAAGTATCCAACCCGTTGGATGGGACGTCTTGTAGCCACCGT
""".split('\n')
sorted_dna_seqs=""">uclust_test_seqs_7
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>uclust_test_seqs_4
ACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
>uclust_test_seqs_2
CCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
>uclust_test_seqs_3
CCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
>uclust_test_seqs_1
GCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>uclust_test_seqs_5
CCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
>uclust_test_seqs_6
CGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
>uclust_test_seqs_0
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
>uclust_test_seqs_8
CGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
>uclust_test_seqs_9
GGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
""".split('\n')
# Clusters are created at a 0.90% identity
uc_dna_clusters= """# uclust --input /tmp/uclust_testBGwZvcikrbNefYGRTk0u.fasta --id 0.9 --uc /tmp/uclust_testrbcO0CyBVpV9AwH3OIK1.uc
# version=1.1.577
# Tab-separated fields:
# 1=Type, 2=ClusterNr, 3=SeqLength or ClusterSize, 4=PctId, 5=Strand, 6=QueryStart, 7=SeedStart, 8=Alignment, 9=QueryLabel, 10=TargetLabel
# Record types (field 1): L=LibSeed, S=NewSeed, H=Hit, R=Reject, D=LibCluster, C=NewCluster, N=NoHit
# For C and D types, PctId is average id with seed.
# QueryStart and SeedStart are zero-based relative to start of sequence.
# If minus strand, SeedStart is relative to reverse-complemented seed.
S 0 80 * * * * * uclust_test_seqs_7 *
S 1 79 * * * * * uclust_test_seqs_4 *
S 2 78 * * * * * uclust_test_seqs_2 *
S 3 77 * * * * * uclust_test_seqs_3 *
S 4 76 * * * * * uclust_test_seqs_1 *
S 5 75 * * * * * uclust_test_seqs_5 *
S 6 74 * * * * * uclust_test_seqs_6 *
S 7 73 * * * * * uclust_test_seqs_0 *
H 6 72 91.7 + 0 0 2I72M uclust_test_seqs_8 uclust_test_seqs_6
S 8 71 * * * * * uclust_test_seqs_9 *
C 0 1 * * * * * uclust_test_seqs_7 *
C 1 1 * * * * * uclust_test_seqs_4 *
C 2 1 * * * * * uclust_test_seqs_2 *
C 3 1 * * * * * uclust_test_seqs_3 *
C 4 1 * * * * * uclust_test_seqs_1 *
C 5 1 * * * * * uclust_test_seqs_5 *
C 6 2 91.7 * * * * uclust_test_seqs_6 *
C 7 1 * * * * * uclust_test_seqs_0 *
C 8 1 * * * * * uclust_test_seqs_9 *""".split('\n')
expected_cluster_list=[['uclust_test_seqs_7'], ['uclust_test_seqs_4'], ['uclust_test_seqs_2'], ['uclust_test_seqs_3'], ['uclust_test_seqs_1'], ['uclust_test_seqs_5'], ['uclust_test_seqs_6', 'uclust_test_seqs_8'], ['uclust_test_seqs_0'], ['uclust_test_seqs_9']]
expected_failure_list = []
expected_new_seed_list = ['uclust_test_seqs_7', 'uclust_test_seqs_4', 'uclust_test_seqs_2',
'uclust_test_seqs_3', 'uclust_test_seqs_1', 'uclust_test_seqs_5', 'uclust_test_seqs_6',
'uclust_test_seqs_0', 'uclust_test_seqs_9']
search_align_query1 = """>1_like
TACGGCTACCTTGTTACGACTTCATCCCAATCATTTGTTCCACCTTCGACGGCTA
>2_like
ATGATGATTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGGATGGCAACTAAG
>2_like_rc
CTTAGTTGCCATCCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCAT
>rand
TTGCGACGAGCGGACGGCCGGGTGTATGTCGTCATATATATGTGTCTGCCTATCGTTACGTACACTCGTCGTCT
"""
search_align_template1 = """>1
AGAAAGGAGGTGATCCAGCCGCACCTTCCGATACGGCTACCTTGTTACGACTTCACCCCAATCATTTGTTCCACCTTCGACGGCTAGCTCCAAATGGTTACTCCACCGGCTTCGGGTGTTACAAACTC
>2
AGCCCAAATCATAAGGGGCATGATGATTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGGATGGCAACTAAGCTTAAGGGTTGCGCT
"""
search_align_query2 = """>1_like
PRTEINACYYPL
>2_like
AGGYTPPLVN
>rand
GGTYPARREE
"""
search_align_template2 = """>1
PRTELNACYYPL
>2
AGGYTRPPLVN
"""
search_align_out2_expected = [
('1_like','1','PRTEINACYYPL','PRTELNACYYPL',91.70000),
('2_like','2','AGGYT-PPLVN','AGGYTRPPLVN',100.0)]
search_align_out_fasta_pairs1 = """>1_like
-------------------------------TACGGCTACCTTGTTACGACTTCATCCCAATCATTTGTTCCACCTTCGACGGCTA------------------------------------------
>1+
AGAAAGGAGGTGATCCAGCCGCACCTTCCGATACGGCTACCTTGTTACGACTTCACCCCAATCATTTGTTCCACCTTCGACGGCTAGCTCCAAATGGTTACTCCACCGGCTTCGGGTGTTACAAACTC
>2_like
-------------------ATGATGATTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGGATGGCAACTAAG---------------
>2+
AGCCCAAATCATAAGGGGCATGATGATTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGGATGGCAACTAAGCTTAAGGGTTGCGCT
>2_like_rc
---------------CTTAGTTGCCATCCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCAT-------------------
>2-
AGCGCAACCCTTAAGCTTAGTTGCCATCCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGATTTGGGCT
""".split('\n')
search_align_out_uc1 = """# uclust --input sm_query.fasta --lib sm_template.fasta --id 0.75 --libonly --rev --maxaccepts 8 --maxrejects 32 --fastapairs sm_pw.fasta --uc sm_result.uc
# version=1.1.577
# Tab-separated fields:
# 1=Type, 2=ClusterNr, 3=SeqLength or ClusterSize, 4=PctId, 5=Strand, 6=QueryStart, 7=SeedStart, 8=Alignment, 9=QueryLabel, 10=TargetLabel
# Record types (field 1): L=LibSeed, S=NewSeed, H=Hit, R=Reject, D=LibCluster, C=NewCluster, N=NoHit
# For C and D types, PctId is average id with seed.
# QueryStart and SeedStart are zero-based relative to start of sequence.
# If minus strand, SeedStart is relative to reverse-complemented seed.
L 0 128 * * * * * 1 *
H 0 55 98.2 + 0 0 31I55M42I 1_like 1
L 1 92 * * * * * 2 *
H 1 58 100.0 + 0 0 19I58M15I 2_like 2
H 1 58 100.0 - 0 0 15I58M19I 2_like_rc 2
N * 74 * * * * * rand *
D 0 2 * * * * 98.2 1 *
D 1 3 * * * * 100.0 2 *
""".split('\n')
search_align_out1_expected = [
('1_like','1','-------------------------------TACGGCTACCTTGTTACGACTTCATCCCAATCATTTGTTCCACCTTCGACGGCTA------------------------------------------','AGAAAGGAGGTGATCCAGCCGCACCTTCCGATACGGCTACCTTGTTACGACTTCACCCCAATCATTTGTTCCACCTTCGACGGCTAGCTCCAAATGGTTACTCCACCGGCTTCGGGTGTTACAAACTC',98.2),
('2_like','2','-------------------ATGATGATTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGGATGGCAACTAAG---------------','AGCCCAAATCATAAGGGGCATGATGATTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGGATGGCAACTAAGCTTAAGGGTTGCGCT',100.0),\
('2_like_rc RC','2','-------------------ATGATGATTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGGATGGCAACTAAG---------------','AGCCCAAATCATAAGGGGCATGATGATTTGACGTCATCCCCACCTTCCTCCGGTTTGTCACCGGGATGGCAACTAAGCTTAAGGGTTGCGCT',100.0)]
uc_lines1 = """# uclust --input q.fasta --lib r.fasta --uc results.uc --id 0.90 --libonly --rev
# version=1.1.579
# Tab-separated fields:
# 1=Type, 2=ClusterNr, 3=SeqLength or ClusterSize, 4=PctId, 5=Strand, 6=QueryStart, 7=SeedStart, 8=Alignment, 9=QueryLabel, 10=TargetLabel
# Record types (field 1): L=LibSeed, S=NewSeed, H=Hit, R=Reject, D=LibCluster, C=NewCluster, N=NoHit
# For C and D types, PctId is average id with seed.
# QueryStart and SeedStart are zero-based relative to start of sequence.
# If minus strand, SeedStart is relative to reverse-complemented seed.
N * 80 * * * * * s1 some comment *
S 4 80 * * * * * s2 some other comment *
H 2 78 100.0 + 0 0 5I78M10I s3 yet another comment s2""".split('\n')
uc_lines_overlapping_lib_input_seq_ids = """# uclust --maxrejects 32 --input /tmp/OtuPickerbb092OWRWLWqlBR2BmTZ.fasta --id 0.97 --uc /tmp/uclust_clustersLf5Oqv0SvGTZo1mVWBqK.uc --rev --usersort --maxaccepts 8 --lib r.fasta
# version=1.1.16
# Tab-separated fields:
# 1=Type, 2=ClusterNr, 3=SeqLength or ClusterSize, 4=PctId, 5=Strand, 6=QueryStart, 7=SeedStart, 8=Alignment, 9=QueryLabel, 10=TargetLabel
# Record types (field 1): L=LibSeed, S=NewSeed, H=Hit, R=Reject, D=LibCluster, C=NewCluster, N=NoHit
# For C and D types, PctId is average id with seed.
# QueryStart and SeedStart are zero-based relative to start of sequence.
# If minus strand, SeedStart is relative to reverse-complemented seed.
S 1 24 * * * * * 3 *
H 1 24 100.0 + 0 0 24M 4 3
L 0 54 * * * * * 3 *
H 0 54 100.0 + 0 0 54M 2 3
D 0 2 * * * * 100.0 3 *
C 1 2 100.0 * * * * 3 *
""".split('\n')
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_unafold.py 000644 000765 000024 00000004215 12024702176 022265 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import remove
from cogent.util.unit_test import TestCase, main
from cogent.core.info import Info
from cogent.app.unafold import hybrid_ss_min
__author__ = "Shandy Wikman"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__contributors__ = ["Shandy Wikman"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Shandy Wikman"
__email__ = "ens01svn@cs.umu.se"
__status__ = "Development"
class UnafoldTest(TestCase):
"""Tests for Unafold application controller"""
def setUp(self):
self.input = unafold_input
def test_stdout_input_as_lines(self):
"""Test Unafold stdout input as lines"""
u = hybrid_ss_min(InputHandler='_input_as_lines')
exp = '\n'.join(unafold_stdout)
res = u(self.input)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
def test_stdout_input_as_string(self):
"""Test Unafold stdout input as string"""
u = hybrid_ss_min()
exp = '\n'.join(unafold_stdout)
f = open('/tmp/single.fasta','w')
f.write('\n'.join(self.input))
f.close()
res = u('/tmp/single.fasta')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
remove('/tmp/single.fasta')
def test_get_result_path(self):
"""Tests unafold result path"""
u = hybrid_ss_min(InputHandler='_input_as_lines')
res = u(self.input)
self.assertEqualItems(res.keys(),['StdOut','StdErr','ExitStatus',\
'ct','dG','run','plot_37','ext_37'])
self.assertEqual(res['ExitStatus'],0)
assert res['ct'] is not None
assert res['dG'] is not None
assert res['run'] is not None
assert res['plot_37'] is not None
assert res['ext_37'] is not None
res.cleanUp()
unafold_input = ['>seq1\n',
'GGCUAGAUAGCUCAGAUGGUAGAGCAGAGGAUUGAAGAUCCUUGUGUCGUCGGUUCGAUCCCGGCUCUGGC\n',
'\n']
unafold_stdout = ['Calculating for seq1, t = 37\n']
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_usearch.py 000755 000765 000024 00000211443 12024702176 022275 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""
provides unit tests for the usearch.py module
"""
__author__ = "William Walters"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["William Walters",
"Jose Carlos Clemente Litran",
"Greg Caporaso"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "William Walters"
__email__ = "william.a.walters@colorado.edu"
__status__ = "Production"
from os.path import isfile, basename, join, exists
from shutil import rmtree
from glob import glob
from cogent.util.misc import remove_files
from cogent.util.unit_test import TestCase, main
from cogent.app.util import ApplicationError, get_tmp_filename
from cogent.util.misc import create_dir, get_random_directory_name
from cogent.app.usearch import (Usearch,
clusters_from_blast_uc_file, usearch_fasta_sort_from_filepath,
usearch_dereplicate_exact_subseqs, usearch_dereplicate_exact_seqs,
usearch_sort_by_abundance,
usearch_cluster_error_correction, usearch_chimera_filter_de_novo,
usearch_chimera_filter_ref_based, usearch_cluster_seqs,
enumerate_otus, assign_reads_to_otus, usearch_qf, concatenate_fastas,
get_retained_chimeras, assign_dna_reads_to_protein_database,
assign_dna_reads_to_dna_database,)
__author__ = "William Walters"
__copyright__ = "Copyright 2007-2009, The Cogent Project"
__credits__ = ["William Walters"]
__license__ = "GPL"
__version__ = "1.6.0.dev"
__maintainer__ = "William Walters"
__email__ = "William.A.Walters@colorado.edu"
__status__ = "Development"
class UsearchTests(TestCase):
def setUp(self):
# create the temporary input files
self.dna_seqs_1 = dna_seqs_1
self.dna_seqs_2 = dna_seqs_usearch
self.dna_seqs_3 = dna_seqs_3
self.dna_seqs_4 = dna_seqs_4
self.protein_ref_seqs1 = protein_ref_seqs1
self.ref_database = usearch_ref_seqs1
self.dna_seqs_with_abundance = dna_seqs_with_abundance
self.de_novo_chimera_seqs = de_novo_chimera_seqs
self.dna_seqs_with_dups = dna_seqs_with_dups
self.dna_seqs_reference_otu_picking = dna_seqs_reference_otu_picking
# Expected output files
self.uc_lines1 = uc_lines1
self.expected_otu_assignments = expected_otu_assignments
self.expected_enumerated_fasta = expected_enumerated_fasta
self.expected_enumerated_fasta_added_options =\
expected_enumerated_fasta_added_options
self.expected_clusters_w_abundance_default_settings =\
expected_clusters_w_abundance_default_settings
self.expected_clusters_w_abundance_low_setting =\
expected_clusters_w_abundance_low_setting
self.expected_reference_filtered_seqs =\
expected_reference_filtered_seqs
self.expected_de_novo_chimeras_default =\
expected_de_novo_chimeras_default
self.expected_de_novo_chimera_filtered_skew11 =\
expected_de_novo_chimera_filtered_skew11
self.expected_cluster_err_seqs =\
expected_cluster_err_seqs
self.expected_sorted_by_abundance_no_filter =\
expected_sorted_by_abundance_no_filter
self.expected_derep_seqs = expected_derep_seqs
self.expected_abundance_sort_filtered = expected_abundance_sort_filtered
self.expected_len_sorted_seqs = expected_len_sorted_seqs
self.expected_combined_dna_seqs_1_seqs_usearch =\
expected_combined_dna_seqs_1_seqs_usearch
self.retained_chimeras_seqs1 = retained_chimeras_seqs1
self.retained_chimeras_seqs2 = retained_chimeras_seqs2
self.expected_retained_chimeras_union =\
expected_retained_chimeras_union
self.expected_retained_chimeras_intersection =\
expected_retained_chimeras_intersection
self.expected_derep_seqs_full_len =\
expected_derep_seqs_full_len
# Create temporary files for use with unit tests
self.tmp_dir = '/tmp/'
self.tmp_seq_filepath1 = get_tmp_filename(\
prefix='UsearchOtuPickerTest_',\
suffix='.fasta')
seq_file = open(self.tmp_seq_filepath1,'w')
seq_file.write(self.dna_seqs_1)
seq_file.close()
self.tmp_seq_filepath2 = get_tmp_filename(\
prefix='UsearchOtuPickerTest_',\
suffix='.fasta')
seq_file = open(self.tmp_seq_filepath2,'w')
seq_file.write(self.dna_seqs_2)
seq_file.close()
self.dna_seqs3_filepath = get_tmp_filename(\
prefix='UsearchOtuPickerTest_',\
suffix='.fasta')
seq_file = open(self.dna_seqs3_filepath,'w')
seq_file.write(self.dna_seqs_3)
seq_file.close()
self.dna_seqs4_filepath = get_tmp_filename(\
prefix='UsearchOtuPickerTest_',\
suffix='.fasta')
seq_file = open(self.dna_seqs4_filepath,'w')
seq_file.write(self.dna_seqs_4)
seq_file.close()
self.protein_ref_seqs1_filepath = get_tmp_filename(\
prefix='UsearchOtuPickerTest_',\
suffix='.fasta')
seq_file = open(self.protein_ref_seqs1_filepath,'w')
seq_file.write(self.protein_ref_seqs1)
seq_file.close()
self.tmp_ref_database = get_tmp_filename(\
prefix='UsearchRefDatabase_',\
suffix='.fasta')
seq_file = open(self.tmp_ref_database, 'w')
seq_file.write(self.ref_database)
seq_file.close()
self.tmp_seqs_w_abundance = get_tmp_filename(\
prefix='UsearchSeqsAbundance_',\
suffix='.fasta')
seq_file = open(self.tmp_seqs_w_abundance, 'w')
seq_file.write(self.dna_seqs_with_abundance)
seq_file.close()
self.tmp_de_novo_chimera_seqs = get_tmp_filename(\
prefix='UsearchdenovoChimera_',\
suffix='.fasta')
seq_file = open(self.tmp_de_novo_chimera_seqs, 'w')
seq_file.write(self.de_novo_chimera_seqs)
seq_file.close()
self.tmp_dna_seqs_with_dups = get_tmp_filename(\
prefix='UsearchDupDNASeqs_',\
suffix='.fasta')
seq_file = open(self.tmp_dna_seqs_with_dups, 'w')
seq_file.write(self.dna_seqs_with_dups)
seq_file.close()
self.tmp_retained_chimeras_seqs1 = get_tmp_filename(\
prefix="UsearchRetainedChimeras1_",\
suffix=".fasta")
seq_file = open(self.tmp_retained_chimeras_seqs1, 'w')
seq_file.write(self.retained_chimeras_seqs1)
seq_file.close()
self.tmp_retained_chimeras_seqs2 = get_tmp_filename(\
prefix="UsearchRetainedChimeras1_",\
suffix=".fasta")
seq_file = open(self.tmp_retained_chimeras_seqs2, 'w')
seq_file.write(self.retained_chimeras_seqs2)
seq_file.close()
self.tmp_dna_seqs_ref_otu_picking = get_tmp_filename(\
prefix="UsearchRefOtuPicking_",\
suffix=".fasta")
seq_file = open(self.tmp_dna_seqs_ref_otu_picking, "w")
seq_file.write(self.dna_seqs_reference_otu_picking)
seq_file.close()
self._files_to_remove =\
[self.tmp_seq_filepath1, self.tmp_seq_filepath2,
self.tmp_ref_database, self.tmp_seqs_w_abundance,
self.tmp_de_novo_chimera_seqs, self.tmp_dna_seqs_with_dups,
self.tmp_retained_chimeras_seqs1, self.tmp_retained_chimeras_seqs2,
self.tmp_dna_seqs_ref_otu_picking, self.dna_seqs3_filepath,
self.protein_ref_seqs1_filepath, self.dna_seqs4_filepath]
self._dirs_to_remove = []
def tearDown(self):
remove_files(self._files_to_remove)
if self._dirs_to_remove:
for curr_dir in self._dirs_to_remove:
rmtree(curr_dir)
def test_usearch_qf(self):
""" Main program loop test, with default parameters """
# cluster size filtering set to 1 instead of default 4
clusters, failures = usearch_qf(self.tmp_seq_filepath2,
output_dir = self.tmp_dir,
db_filepath = self.tmp_ref_database,
minsize = 1,
remove_usearch_logs=True,
chimeras_retention = 'intersection')
expected_clusters = {'1': ['Solemya', 'Solemya_seq2'],
'0': ['usearch_ecoli_seq', 'usearch_ecoli_seq2']}
expected_failures = ['chimera']
self.assertEqual(clusters, expected_clusters)
self.assertEqual(failures, expected_failures)
def test_usearch_qf_minlen(self):
""" Main program loop test, with longer minlen """
# cluster size filtering set to 1 instead of default 4
clusters, failures = usearch_qf(self.tmp_seq_filepath2,
output_dir = self.tmp_dir,
db_filepath = self.tmp_ref_database,
minsize = 1,
remove_usearch_logs=True,
chimeras_retention = 'intersection',
minlen=110)
expected_clusters = {'0': ['usearch_ecoli_seq', 'usearch_ecoli_seq2']}
expected_failures = ['Solemya', 'Solemya_seq2', 'chimera']
self.assertEqual(clusters, expected_clusters)
self.assertEqual(failures, expected_failures)
def test_usearch_qf_reference_otu_picking(self):
""" Main program loop test, with reference + new clusters """
# cluster size filtering set to 1 instead of default 4
clusters, failures = usearch_qf(self.tmp_dna_seqs_ref_otu_picking,
output_dir = self.tmp_dir,
refseqs_fp = self.tmp_ref_database,
reference_chimera_detection=False,
minsize = 1,
remove_usearch_logs=True,
suppress_new_clusters=False)
# Will cluster everything including RandomCrap, as new clusters allowed.
expected_clusters = {'1': ['Solemya', 'Solemya_seq2'],
'0': ['usearch_ecoli_seq', 'usearch_ecoli_seq2'],
'2': ['RandomCrap']}
expected_failures = []
self.assertEqual(clusters, expected_clusters)
self.assertEqual(failures, expected_failures)
def test_usearch_qf_reference_otu_picking_no_new_clusters(self):
""" Main program loop test, with reference and no new clusters """
# cluster size filtering set to 1 instead of default 4
clusters, failures = usearch_qf(self.tmp_dna_seqs_ref_otu_picking,
output_dir = self.tmp_dir,
refseqs_fp = self.tmp_ref_database,
reference_chimera_detection=False,
minsize = 1,
remove_usearch_logs=True,
suppress_new_clusters=True)
# Will cluster everything but RandomCrap, as no new clusters allowed.
expected_clusters = {'1': ['Solemya', 'Solemya_seq2'],
'0': ['usearch_ecoli_seq', 'usearch_ecoli_seq2']}
expected_failures = ['RandomCrap']
self.assertEqual(clusters, expected_clusters)
self.assertEqual(failures, expected_failures)
def test_usearch_qf_no_ref_database(self):
""" Main program loop with no reference chimera testing """
# cluster size filtering set to 1 instead of default 4
clusters, failures = usearch_qf(self.tmp_seq_filepath2,
output_dir = self.tmp_dir,
reference_chimera_detection=False,
minsize = 1,
remove_usearch_logs=True)
# Chimera sequence should not be detected without reference test.
expected_clusters = {'1': ['Solemya', 'Solemya_seq2'],
'0': ['usearch_ecoli_seq', 'usearch_ecoli_seq2'],
'2': ['chimera']}
expected_failures = []
self.assertEqual(clusters, expected_clusters)
self.assertEqual(failures, expected_failures)
def test_usearch_qf_union(self):
""" Main program loop with union nonchimera retention """
# cluster size filtering set to 1 instead of default 4
clusters, failures = usearch_qf(self.tmp_seq_filepath2,
output_dir = self.tmp_dir,
reference_chimera_detection=False,
minsize = 1,
remove_usearch_logs=True,
chimeras_retention = 'union')
# Chimera sequence retained as passes de novo test
expected_clusters = {'1': ['Solemya', 'Solemya_seq2'],
'0': ['usearch_ecoli_seq', 'usearch_ecoli_seq2'],
'2': ['chimera']}
expected_failures = []
self.assertEqual(clusters, expected_clusters)
self.assertEqual(failures, expected_failures)
def test_usearch_qf_disabled_filters(self):
""" Returns expected clustering with no filtering """
# cluster size filtering set to 1 instead of default 4
clusters, failures = usearch_qf(self.tmp_seq_filepath2,
output_dir = self.tmp_dir,
de_novo_chimera_detection=False,
reference_chimera_detection=False,
cluster_size_filtering=False,
remove_usearch_logs=True)
# Chimera sequence should not be detected without reference test.
expected_clusters = {'1': ['Solemya', 'Solemya_seq2'],
'0': ['usearch_ecoli_seq', 'usearch_ecoli_seq2'],
'2': ['chimera']}
expected_failures = []
self.assertEqual(clusters, expected_clusters)
self.assertEqual(failures, expected_failures)
def test_usearch_qf_generates_logs(self):
""" Generates expected log files """
curr_output_dir = get_tmp_filename(prefix='/UsearchLogTest_',suffix='/')
create_dir(curr_output_dir)
self._dirs_to_remove.append(curr_output_dir)
# cluster size filtering set to 1 instead of default 4
clusters, failures = usearch_qf(self.tmp_seq_filepath2,
output_dir = curr_output_dir,
db_filepath = self.tmp_ref_database,
minsize = 1,
remove_usearch_logs=False,
chimeras_retention = 'intersection')
expected_clusters = {'1': ['Solemya', 'Solemya_seq2'],
'0': ['usearch_ecoli_seq', 'usearch_ecoli_seq2']}
expected_failures = ['chimera']
self.assertEqual(clusters, expected_clusters)
self.assertEqual(failures, expected_failures)
# Only checking for creation of files, as file contents contain
# tmp file names.
expected_log_names = ['assign_reads_to_otus.log',
'uchime_de_novo_chimera_filtering.log',
'derep.log',
'uchime_reference_chimera_filtering.log',
'minsize_0_abundance_sort.log',
'usearch_cluster_err_corrected.log',
'minsize_1_abundance_sort.log',
'usearch_cluster_seqs.log',
'sortlen.log']
actual_logs =\
[basename(curr_file) for curr_file in glob(curr_output_dir + "*.*")]
for log in expected_log_names:
self.assertContains(actual_logs, log)
def test_concatenate_fastas(self):
""" Properly concatenates two fasta files """
out_f =\
get_tmp_filename(prefix='UsearchConcatFileTest_',suffix='.fasta')
actual_concatenated_seqs = concatenate_fastas(self.tmp_seq_filepath1,
self.tmp_seq_filepath2, out_f)
self._files_to_remove.append(out_f)
actual_lines =\
[line.strip() for line in open(actual_concatenated_seqs, "U")]
self.assertEqual(actual_lines,
expected_combined_dna_seqs_1_seqs_usearch)
def test_assign_reads_to_otus(self):
""" Properly assigns reads back to original ID """
app_result, output_filepath =\
assign_reads_to_otus(original_fasta = self.tmp_ref_database,
filtered_fasta = self.tmp_seq_filepath2,
remove_usearch_logs = True,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
# Stripping off first line, which refers to the command using tmp
# file names, retaining other actual results.
actual_assignments =\
[line.strip() for line in open(output_filepath, "U")][2:]
self.assertEqual(actual_assignments, self.expected_otu_assignments)
def test_enumerate_otus(self):
""" Enumerates OTUs properly """
output_filepath = enumerate_otus(self.tmp_seq_filepath1)
self._files_to_remove.append(output_filepath)
actual_fasta = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_fasta, self.expected_enumerated_fasta)
def test_enumerate_otus_added_options(self):
""" Enumerates with all options properly """
output_filepath = enumerate_otus(self.tmp_seq_filepath1,
label_prefix = "Big",
label_suffix = "Ern",
retain_label_as_comment = True,
count_start = 255)
self._files_to_remove.append(output_filepath)
actual_fasta = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_fasta,
self.expected_enumerated_fasta_added_options)
def test_usearch_cluster_seqs(self):
""" Clusters sequences correctly """
# clusters all seqs with default 97% identity
app_result, output_filepath =\
usearch_cluster_seqs(self.tmp_seqs_w_abundance,
save_intermediate_files=False,
remove_usearch_logs=True,
percent_id = 0.97,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_clusters = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_clusters,
self.expected_clusters_w_abundance_default_settings)
def test_usearch_cluster_seqs_high_identity(self):
""" Clusters sequences correctly """
# Should get two clusters with 99.9% identity
app_result, output_filepath =\
usearch_cluster_seqs(self.tmp_seqs_w_abundance,
save_intermediate_files=False,
remove_usearch_logs=True,
percent_id = 0.999,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_clusters = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_clusters,
self.expected_clusters_w_abundance_low_setting)
def test_usearch_chimera_filter_ref_based(self):
""" Properly detects chimeras against reference database """
app_result, output_filepath =\
usearch_chimera_filter_ref_based(self.tmp_seq_filepath2,
self.tmp_ref_database,
remove_usearch_logs=True,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_filtered_chimeras =\
[line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_filtered_chimeras,
self.expected_reference_filtered_seqs)
def test_usearch_chimera_filter_de_novo(self):
""" Properly detects de novo chimeras """
app_result, output_filepath =\
usearch_chimera_filter_de_novo(self.tmp_de_novo_chimera_seqs,
remove_usearch_logs=True,
abundance_skew = 2,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_seqs = \
[line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_seqs, self.expected_de_novo_chimeras_default)
def test_usearch_chimera_filter_de_novo_abundance_skew(self):
""" Properly detects de novo chimeras with skew changes """
app_result, output_filepath =\
usearch_chimera_filter_de_novo(self.tmp_de_novo_chimera_seqs,
remove_usearch_logs=True,
abundance_skew = 11,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_seqs = \
[line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_seqs,
self.expected_de_novo_chimera_filtered_skew11)
def test_usearch_cluster_error_correction(self):
""" Properly clusters seqs for chimera testing/filtering """
# clusters all seqs with default 97% identity
app_result, output_filepath =\
usearch_cluster_error_correction(self.tmp_seqs_w_abundance,
save_intermediate_files=False,
remove_usearch_logs=True,
percent_id_err = 0.97,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_clusters = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_clusters,
self.expected_cluster_err_seqs)
def test_usearch_sort_by_abundance(self):
""" Properly sorts fasta by abundance """
app_result, output_filepath =\
usearch_sort_by_abundance(self.tmp_de_novo_chimera_seqs,
remove_usearch_logs=True,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_seqs = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_seqs,
self.expected_sorted_by_abundance_no_filter)
def test_usearch_sort_by_abundance_filter(self):
""" Properly sorts fasta by abundance, filters low count otus """
app_result, output_filepath =\
usearch_sort_by_abundance(self.tmp_de_novo_chimera_seqs,
remove_usearch_logs=True,
minsize = 40,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_seqs = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_seqs,
self.expected_abundance_sort_filtered)
def test_usearch_dereplicate_exact_subseqs(self):
""" Properly dereplicates fasta file """
app_result, output_filepath =\
usearch_dereplicate_exact_subseqs(self.tmp_dna_seqs_with_dups,
remove_usearch_logs=True,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_seqs = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_seqs, self.expected_derep_seqs)
def test_usearch_dereplicate_exact_seqs(self):
""" Properly dereplicates fasta file """
app_result, output_filepath =\
usearch_dereplicate_exact_seqs(self.tmp_dna_seqs_with_dups,
remove_usearch_logs=True,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_seqs = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_seqs, self.expected_derep_seqs_full_len)
def test_usearch_fasta_sort_from_filepath(self):
""" Properly sorts fasta according to seq length """
app_result, output_filepath =\
usearch_fasta_sort_from_filepath(self.tmp_seq_filepath2,
remove_usearch_logs=True,
working_dir=self.tmp_dir)
self._files_to_remove.append(output_filepath)
actual_seqs = [line.strip() for line in open(output_filepath, "U")]
self.assertEqual(actual_seqs, self.expected_len_sorted_seqs)
def test_clusters_from_blast_uc_file(self):
""" clusters_from_uc_file functions as expected """
expected_clusters = {'19': ['PC.634_4'], '42': ['PC.test2_1',
'PC.test1_2', 'PC.634_3'], '6': ['PC.269_5']}
expected_failures = ['PC.481_6']
self.assertEqual(clusters_from_blast_uc_file(self.uc_lines1),
(expected_clusters,expected_failures))
def test_get_retained_chimeras_union(self):
""" Properly returns union of two fastas """
out_f =\
get_tmp_filename(prefix='UsearchUnionTest_',suffix='.fasta')
actual_out_fp = get_retained_chimeras(self.tmp_retained_chimeras_seqs1,
self.tmp_retained_chimeras_seqs2, out_f, chimeras_retention = 'union')
self._files_to_remove.append(out_f)
actual_out_f = [line.strip() for line in open(actual_out_fp, "U")]
self.assertEqual(actual_out_f, self.expected_retained_chimeras_union)
def test_get_retained_chimeras_intersection(self):
""" Properly returns intersection of two fastas """
out_f =\
get_tmp_filename(prefix='UsearchIntersectionTest_',suffix='.fasta')
actual_out_fp = get_retained_chimeras(self.tmp_retained_chimeras_seqs1,
self.tmp_retained_chimeras_seqs2, out_f,
chimeras_retention = 'intersection')
self._files_to_remove.append(out_f)
actual_out_f = [line.strip() for line in open(actual_out_fp, "U")]
self.assertEqual(actual_out_f,
self.expected_retained_chimeras_intersection)
def test_assign_dna_reads_to_protein_database(self):
"""assign_dna_reads_to_protein_database wrapper functions as expected
"""
output_dir = get_random_directory_name(output_dir=self.tmp_dir)
self._dirs_to_remove.append(output_dir)
output_fp = join(output_dir,'out.uc')
assign_dna_reads_to_protein_database(self.dna_seqs3_filepath,
self.protein_ref_seqs1_filepath,
output_fp,
temp_dir = self.tmp_dir)
self.assertTrue(exists(output_fp))
self.assertTrue(exists(output_fp.replace('.uc','.bl6')))
# confirm that the clusters look like what we expect
expected_clusters = [['eco:b0015'],['eco:b0122','eco:b0122-like']]
expected_clusters.sort()
actual_clusters = clusters_from_blast_uc_file(open(output_fp))[0].values()
actual_clusters.sort()
self.assertEqual(actual_clusters,expected_clusters)
def test_assign_dna_reads_to_protein_database_alt_params(self):
"""assign_dna_reads_to_protein_database wrapper functions with alt params
"""
output_dir = get_random_directory_name(output_dir=self.tmp_dir)
self._dirs_to_remove.append(output_dir)
output_fp = join(output_dir,'out.uc')
assign_dna_reads_to_protein_database(self.dna_seqs3_filepath,
self.protein_ref_seqs1_filepath,
output_fp,
temp_dir = self.tmp_dir,
params={'--id':1.0})
self.assertTrue(exists(output_fp))
self.assertTrue(exists(output_fp.replace('.uc','.bl6')))
# confirm that the clusters look like what we expect
expected_clusters = [['eco:b0015'],['eco:b0122']]
expected_clusters.sort()
actual_clusters = clusters_from_blast_uc_file(open(output_fp))[0].values()
actual_clusters.sort()
self.assertEqual(actual_clusters,expected_clusters)
def test_assign_dna_reads_to_dna_database(self):
"""assign_dna_reads_to_protein_database wrapper functions as expected
"""
output_dir = get_random_directory_name(output_dir=self.tmp_dir)
self._dirs_to_remove.append(output_dir)
output_fp = join(output_dir,'out.uc')
assign_dna_reads_to_protein_database(self.dna_seqs3_filepath,
self.dna_seqs4_filepath,
output_fp,
temp_dir = self.tmp_dir)
self.assertTrue(exists(output_fp))
self.assertTrue(exists(output_fp.replace('.uc','.bl6')))
# confirm that the clusters look like what we expect
expected_clusters = [['eco:b0015'],['eco:b0122','eco:b0122-like']]
expected_clusters.sort()
actual_clusters = clusters_from_blast_uc_file(open(output_fp))[0].values()
actual_clusters.sort()
self.assertEqual(actual_clusters,expected_clusters)
# Long strings for test files, output, etc.
# *************************************************
retained_chimeras_seqs1 = """>seq1
ACAGGCC
>seq2
ACAGGCCCCC
>seq3
TTATCCATT"""
retained_chimeras_seqs2 = """>seq3
ACAGGCC
>seq4
ACAGGCCCCC
>seq5
TTATCCATT"""
dna_seqs_1 = """>uclust_test_seqs_0 some comment0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>uclust_test_seqs_1 some comment1
ACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
>uclust_test_seqs_2 some comment2
CCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
>uclust_test_seqs_3 some comment3
CCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
>uclust_test_seqs_4 some comment4
GCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>uclust_test_seqs_5 some comment4_again
CCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
>uclust_test_seqs_6 some comment6
CGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
>uclust_test_seqs_7 some comment7
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
>uclust_test_seqs_8 some comment8
CGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
>uclust_test_seqs_9 some comment9
GGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA"""
dna_seqs_3 = """>eco:b0001 thrL; thr operon leader peptide; K08278 thr operon leader peptide (N)
atgaaacgcattagcaccaccattaccaccaccatcaccattaccacaggtaacggtgcg
ggctga
>eco:b0015 dnaJ; chaperone Hsp40, co-chaperone with DnaK; K03686 molecular chaperone DnaJ (N)
atggctaagcaagattattacgagattttaggcgtttccaaaacagcggaagagcgtgaa
atcagaaaggcctacaaacgcctggccatgaaataccacccggaccgtaaccagggtgac
aaagaggccgaggcgaaatttaaagagatcaaggaagcttatgaagttctgaccgactcg
caaaaacgtgcggcatacgatcagtatggtcatgctgcgtttgagcaaggtggcatgggc
ggcggcggttttggcggcggcgcagacttcagcgatatttttggtgacgttttcggcgat
atttttggcggcggacgtggtcgtcaacgtgcggcgcgcggtgctgatttacgctataac
atggagctcaccctcgaagaagctgtacgtggcgtgaccaaagagatccgcattccgact
ctggaagagtgtgacgtttgccacggtagcggtgcaaaaccaggtacacagccgcagact
tgtccgacctgtcatggttctggtcaggtgcagatgcgccagggattcttcgctgtacag
cagacctgtccacactgtcagggccgcggtacgctgatcaaagatccgtgcaacaaatgt
catggtcatggtcgtgttgagcgcagcaaaacgctgtccgttaaaatcccggcaggggtg
gacactggagaccgcatccgtcttgcgggcgaaggtgaagcgggcgagcatggcgcaccg
gcaggcgatctgtacgttcaggttcaggttaaacagcacccgattttcgagcgtgaaggc
aacaacctgtattgcgaagtcccgatcaacttcgctatggcggcgctgggtggcgaaatc
gaagtaccgacccttgatggtcgcgtcaaactgaaagtgcctggcgaaacccagaccggt
aagctattccgtatgcgcggtaaaggcgtcaagtctgtccgcggtggcgcacagggtgat
ttgctgtgccgcgttgtcgtcgaaacaccggtaggcctgaacgaaaggcagaaacagctg
ctgcaagagctgcaagaaagcttcggtggcccaaccggcgagcacaacagcccgcgctca
aagagcttctttgatggtgtgaagaagttttttgacgacctgacccgctaa
>eco:b0122 yacC; conserved protein, PulS_OutS family (N)
atgaagacgtttttcagaacagtgttattcggcagcctgatggccgtctgcgcaaacagt
tacgcgctcagcgagtctgaagccgaagatatggccgatttaacggcagtttttgtcttt
ctgaagaacgattgtggttaccagaacttacctaacgggcaaattcgtcgcgcactggtc
tttttcgctcagcaaaaccagtgggacctcagtaattacgacaccttcgacatgaaagcc
ctcggtgaagacagctaccgcgatctcagcggcattggcattcccgtcgctaaaaaatgc
aaagccctggcccgcgattccttaagcctgcttgcctacgtcaaataa
>eco:b0122-like
atgaagaaaattttcagaacagtgttattcggcagcctgatggccgtctgcgcaaacagt
tacgcgctcagcgagtctgaagccgaagatatggccgatttaacggcagtttttgtcttt
ctgaagaacgattgtggttaccagaacttacctaacgggcaaattcgtcgcgcactggtc
tttttcgctcagcaaaaccagtgggacctcagtaattacgacaccttcgacatgaaagcc
ctcggtgaagacagctaccgcgatctcagcggcattggcattcccgtcgctaaaaaatgc
aaagccctggcccgcgattccttaagcctgcttgcctacgtcaaatcc"""
dna_seqs_4 = """>eco:b0015 dnaJ; chaperone Hsp40, co-chaperone with DnaK; K03686 molecular chaperone DnaJ (N)
atggctaagcaagattattacgagattttaggcgtttccaaaacagcggaagagcgtgaa
atcagaaaggcctacaaacgcctggccatgaaataccacccggaccgtaaccagggtgac
aaagaggccgaggcgaaatttaaagagatcaaggaagcttatgaagttctgaccgactcg
caaaaacgtgcggcatacgatcagtatggtcatgctgcgtttgagcaaggtggcatgggc
ggcggcggttttggcggcggcgcagacttcagcgatatttttggtgacgttttcggcgat
atttttggcggcggacgtggtcgtcaacgtgcggcgcgcggtgctgatttacgctataac
atggagctcaccctcgaagaagctgtacgtggcgtgaccaaagagatccgcattccgact
ctggaagagtgtgacgtttgccacggtagcggtgcaaaaccaggtacacagccgcagact
tgtccgacctgtcatggttctggtcaggtgcagatgcgccagggattcttcgctgtacag
cagacctgtccacactgtcagggccgcggtacgctgatcaaagatccgtgcaacaaatgt
catggtcatggtcgtgttgagcgcagcaaaacgctgtccgttaaaatcccggcaggggtg
gacactggagaccgcatccgtcttgcgggcgaaggtgaagcgggcgagcatggcgcaccg
gcaggcgatctgtacgttcaggttcaggttaaacagcacccgattttcgagcgtgaaggc
aacaacctgtattgcgaagtcccgatcaacttcgctatggcggcgctgggtggcgaaatc
gaagtaccgacccttgatggtcgcgtcaaactgaaagtgcctggcgaaacccagaccggt
aagctattccgtatgcgcggtaaaggcgtcaagtctgtccgcggtggcgcacagggtgat
ttgctgtgccgcgttgtcgtcgaaacaccggtaggcctgaacgaaaggcagaaacagctg
ctgcaagagctgcaagaaagcttcggtggcccaaccggcgagcacaacagcccgcgctca
aagagcttctttgatggtgtgaagaagttttttgacgacctgacccgctaa
>eco:b0122 yacC; conserved protein, PulS_OutS family (N)
atgaagacgtttttcagaacagtgttattcggcagcctgatggccgtctgcgcaaacagt
tacgcgctcagcgagtctgaagccgaagatatggccgatttaacggcagtttttgtcttt
ctgaagaacgattgtggttaccagaacttacctaacgggcaaattcgtcgcgcactggtc
tttttcgctcagcaaaaccagtgggacctcagtaattacgacaccttcgacatgaaagcc
ctcggtgaagacagctaccgcgatctcagcggcattggcattcccgtcgctaaaaaatgc
aaagccctggcccgcgattccttaagcctgcttgcctacgtcaaataa
>eco:b0122-like
atgaagacgtttttcagaacagtgttattcggcagcctgatggccgtctgcgcaaacagt
tacgcgctcagcgagtctgaagccgaagatatggccgatttaacggcagtttttgtcttt
ctgaagaacgattgtggttaccagaacttacctaacgggcaaattcgtcgcgcactggtc
tttttcgctcagcaaaaccagtgggacctcagtaattacgacaccttcgacatgaaagcc
ctcggtgaagacagctaccgcgatctcagcggcattggcattcccgtcgctaaaaaatgc
aaagccctggcccgcgattccttaagcctgcttgcctacgtcaaatcc"""
protein_ref_seqs1 = """>eco:b0001 thrL; thr operon leader peptide; K08278 thr operon leader peptide (A)
MKRISTTITTTITITTGNGAG
>eco:b0015 dnaJ; chaperone Hsp40, co-chaperone with DnaK; K03686 molecular chaperone DnaJ (A)
MAKQDYYEILGVSKTAEEREIRKAYKRLAMKYHPDRNQGDKEAEAKFKEIKEAYEVLTDS
QKRAAYDQYGHAAFEQGGMGGGGFGGGADFSDIFGDVFGDIFGGGRGRQRAARGADLRYN
MELTLEEAVRGVTKEIRIPTLEECDVCHGSGAKPGTQPQTCPTCHGSGQVQMRQGFFAVQ
QTCPHCQGRGTLIKDPCNKCHGHGRVERSKTLSVKIPAGVDTGDRIRLAGEGEAGEHGAP
AGDLYVQVQVKQHPIFEREGNNLYCEVPINFAMAALGGEIEVPTLDGRVKLKVPGETQTG
KLFRMRGKGVKSVRGGAQGDLLCRVVVETPVGLNERQKQLLQELQESFGGPTGEHNSPRS
KSFFDGVKKFFDDLTR
>eco:b0015:rep
MAKQDYYEILGVSKTAEEREIRKAYKRLAMKYHPDRNQGDKEAEAKFKEIKEAYEVLTDS
QKRAAYDQYGHAAFEQGGMGGGGFGGGADFSDIFGDVFGDIFGGGRGRQRAARGADLRYN
MELTLEEAVRGVTKEIRIPTLEECDVCHGSGAKPGTQPQTCPTCHGSGQVQMRQGFFAVQ
QTCPHCQGRGTLIKDPCNKCHGHGRVERSKTLSVKIPAGVDTGDRIRLAGEGEAGEHGAP
AGDLYVQVQVKQHPIFEREGNNLYCEVPINFAMAALGGEIEVPTLDGRVKLKVPGETQTG
KLFRMRGKGVKSVRGGAQGDLLCRVVVETPVGLNERQKQLLQELQESFGGPTGEHNSPRS
KSFFDGVKKFFDDLTR
>eco:b0122 yacC; conserved protein, PulS_OutS family (A)
MKTFFRTVLFGSLMAVCANSYALSESEAEDMADLTAVFVFLKNDCGYQNLPNGQIRRALV
FFAQQNQWDLSNYDTFDMKALGEDSYRDLSGIGIPVAKKCKALARDSLSLLAYVK"""
usearch_ref_seqs1 = """>ref1 ecoli sequence
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCA
>EU199232 1 1236 Bacteria/Deltaproteobacteria/Desulfurella - Hippea/uncultured
TACGCGCGGAAATCGAGCGAGATTGGGAACGCAAGTTCCTGAGTATTGCGGCGAACGGGTGAGTAAGACGTGGGTGATCTACCCCTAGGGTGGGAATAACCCGGGGAAACCCGGGCTAATACCGAATAAGACCACAGGAGGCGACTCCAGAGGGTCAAAGGGAGCCTTGGCCTCCCCC
>L07864 1 1200 Bacteria/Beta Gammaproteobacteria/Solemya symbiont
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTAATGCATGGGAATCTGCCATATAGTGGGGGACAACTGGGGAAACCCAGGCTAATACCGCATAATCTCTACGGAGGAAAGGCTTC
"""
dna_seqs_usearch = """>usearch_ecoli_seq
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGT
>Solemya seq
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTA
>usearch_ecoli_seq2
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTCCAT
>Solemya_seq2
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTATCAAG
>chimera
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACCCCTAGGGTGGGAATAACCCGGGGAAACCCGGGCTAATACCGAATAAGACCACAGGAGGCGACTCCAGAGGGTCAAAGGGAGCCTTGGCCTCCCCC
"""
dna_seqs_reference_otu_picking = """>usearch_ecoli_seq
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGT
>Solemya seq
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTA
>usearch_ecoli_seq2
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTCCAT
>Solemya_seq2
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTATCAAG
>RandomCrap
ACACAAACAGTATATTATATCCCCAGACAGGGACCGAGATTTACCACACCCAAAAAAAAAAAAAACACACCCCCCCCCCCCCCACACACACACTTATTTT
"""
dna_seqs_with_abundance = """>Cluster1;size=114
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>Cluster2;size=45
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCC
>Cluster0;size=37
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGAACATCGCGTCAGGTTTGTGTCAGGCCT
>Cluster7;size=33
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAAGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>Cluster6;size=32
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>Cluster5;size=25
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>Cluster11;size=22
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>Cluster12;size=15
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>Cluster13;size=2
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTGTGTCAGGCCT
>Cluster14;size=1
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTG"""
de_novo_chimera_seqs = """>Cluster1;size=52
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGGCTTGGTGGTCCGTTACAC
CGCCAACTACCTAATGCGACGCATGCCCATCCGCTACCGGATCGCTCCTTTGGAATCCCGGGGATGTCCCCGGAACTCGT
TATGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTAGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster0;size=50
TTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCC
CGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGCGGACTCATGATGCCA
TCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGG
>Cluster2;size=45
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCTGTTACCC
CGCCAACCAGCTAATCAGACGCGGATCCATCGTATACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTT
>Cluster10;size=43
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCGCCCTCTCAGGCCGGCTATGCATCATCGTCTTGGTGGGCCTTTACCC
CGCCAACCAACTAATGCACCGCAGGTCCATCCGCGCCCCATCCCCTAAAGGATGTTTCACAGAAAGAAGATGCCTCCTTC
CTGTACATCGGGATTTGTTCTCCGTTTCCAGAGCGTATTCCCGGTGCGCGGGCAGGTTCCCTACGTGTTACTCACCCG
>Cluster4;size=40
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGTCCCATGCAGGACCGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTGCAAGGCAGGTTACCCACGCGTTACTCACCCGTCCG
>Cluster6;size=40
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGGCCATCCGCAGCCGATAAATCTTTAAACATCGGGAGATGCCTCCCAACGTTGTTA
CGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTGCGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCGG
>Cluster3;size=30
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGATCAGTCTCTCAACTCGGCTATGCATCATTGCCTTGGTAAGCCGTTACCT
TACCAACTAGCTAATGCACCGCAGGTCCATCCAAGAGTGATAGCAGAACCATCTTTCAAACTCTAGACATGCGTCTAGTG
TTGTTATCCGGTATTAGCATCTGTTTCCAGGTGTTATCCCAGTCTCTTGGG
>Cluster12;size=19
TTGGTCCGTGTCTCAGTACCAATGTGGGGGGTTAACCTCTCAGTCCCCCTATGTATCGTGGTCTTGGTGAGCCGTTACCC
CACCAACTAACTAATACAACGCATGCCCATCCATTACCACCGGAGTTTTCAACCCAAGAAGATGCCTCCCTGGATGTTAT
GGGGTATTAGTACCGATTTCTCAGTGTTATCCCCCTGTAATGGGTAGGTTGCATACGCGTTACGCACCCGTGCGCCGGTC
GCCGACAAT
>Cluster30;size=18
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTTGGTGGGCCGTTACCC
CGCCAACTAGCTAATGCGCCGCATGGCCATCCGTAGCCGGTGTTACCCTTTAAACCCCAAGAGATGCCTCTCGGAGTTAT
TACGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTACGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster29;size=18
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGCCCATCCGCCACCGGTAATCCCTTTGGCGGCACCGGGATGCCCCGACGCCGCGTC
ACGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTGGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCGG
TCGCCGG
>Cluster16;size=16
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCGTTACCC
CTCCAACCAGCTAATCAGACGCGGGTCCATCCTGTACCACCGGAGTTTTTCACACTGTACCATGCGGTACTGTGCGCTTA
TGCGGTTTTAGCACCTATTTCTAAGTGTTATCCCCCTGTACAGGGCAGGTTACCCACGCGTTACTCACCCGTCCGCCACT
>Cluster222;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTAT
GCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTTACT
>Cluster221;size=1
CTGGGCCGTATCTCAGTCCCAATGTGGCCGTTCAACCTCTCAGTCCGGCTACTGATCGTCGCCTTGGTAGGCCGTTGCCC
CGCCAACTACCTAATCGGACGCGAGCCCATCTTTCAGCGGATTGCTCCTTTGATTATCTCACCATGCGGCAAAATAATGT
CATGCGGTATTAGCGTTCGTTTCCAAACGTTATCCCCCTCTGAAAGGCAGGTTGCTCACGCGTT
>Cluster218;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGGCCACCCTCTCAGGTCGGCTACTGATCGTCACCTTGGTAGGCCGTTACCC
CACCAACTAGCTAATCAGACGCAAGCCCATCTATCAGCGGATTGCTCCTTTTCTAGCTATATCATGCGATACTACTAGCT
TATGCGGTATTAGCAATGATTTCTCACTGTTATTCCCCTCTGATAGGCAGG
>Cluster217;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGAGTCCATCTCAGAGCGATAAATCTTTGATATCCAGAGCCATGCGACCCAGATATATT
ATGCGGTATTAGCAGCTGTTTCCAGCTGTTATTCCCCATCCAAGGCAGGTT
>Cluster216;size=1
CTGGGCCGTGTCTCAGTCCCAGTGTGGCCGTCCGCCCTCTCAGGTCAGCTACTGATCGTCGCCTTGGTAGGCCATTACCC
TACCAACTAGCTAATCAGACGCGAGGCCATCTCTCAGCGATAAATCTTTGATATATCTGCCATGCGACAAACATATATTA
TGCGGTATTAGCAGTCGTTTCCAACTGTTGTCCCCCTCTGAAAGGCAGGTT
>Cluster522;size=10
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTAT
GCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTTACT"""
dna_seqs_with_dups=""">seq1
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTAA
>seq2
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC
>seq3
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC
>seq4
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTT"""
# Expected output file data
uc_lines1 = """# usearch --id 0.97 --uc usearch_picked_otus/assign_reads_to_otus.uc --query seqs.fna --global --db usearch_picked_otus/enumerated_otus.fasta
# version=4.2.66
# Tab-separated fields:
# 1=Type, 2=ClusterNr, 3=SeqLength or ClusterSize, 4=PctId, 5=Strand, 6=QueryStart, 7=SeedStart, 8=Alignment, 9=QueryLabel, 10=TargetLabel
# Record types (field 1): L=LibSeed, S=NewSeed, H=Hit, R=Reject, D=LibCluster, C=NewCluster, N=NoHit
# For C and D types, PctId is average id with seed.
# QueryStart and SeedStart are zero-based relative to start of sequence.
# If minus strand, SeedStart is relative to reverse-complemented seed.
H\t42\t217\t99.1\t+\t0\t0\t217MI\tPC.test2_1 FLP3FBN02xELBSXx orig_bc=ACAGAGTCGGCG new_bc=ACAGAGTCGGCG,FLP3FBN02x bc_diffs=0\t42
H\t42\t217\t99.1\t+\t0\t0\t217MI\tPC.test1_2 FLP3FBN03ELBSXx orig_bc=ACAGAGTCGGCG new_bc=ACAGAGTCGGCG,FLP3FBN03 bc_diffs=0\t42
H\t42\t217\t99.1\t+\t0\t0\t217MI\tPC.634_3 FLP3FBN01ELBSX orig_bc=TCAGAGTCGGCT new_bc=ACAGAGTCGGCT,FLP3FBN01 bc_diffs=1\t42
H\t19\t243\t100.0\t+\t0\t0\t25MI218M\tPC.634_4 FLP3FBN01EG8AX orig_bc=ACAGAGTCGGCT new_bc=ACAGAGTCGGCT,FLP3FBN01 bc_diffs=0\t19
N\t*\t219\t*\t*\t*\t*\t*\tPC.481_6\tFLP3FBN01DEHK3 orig_bc=ACCAGCGACTAG new_bc=ACCAGCGACTAG,FLP3FBN01 bc_diffs=0\t*
H\t6\t211\t99.5\t+\t0\t0\t211M\tPC.269_5 FLP3FBN01EEWKD orig_bc=AGCACGAGCCTA new_bc=AGCACGAGCCTA,FLP3FBN01 bc_diffs=0\t6
""".split('\n')
expected_otu_assignments = """# Tab-separated fields:
# 1=Type, 2=ClusterNr, 3=SeqLength or ClusterSize, 4=PctId, 5=Strand, 6=QueryStart, 7=SeedStart, 8=Alignment, 9=QueryLabel, 10=TargetLabel
# Record types (field 1): L=LibSeed, S=NewSeed, H=Hit, R=Reject, D=LibCluster, C=NewCluster, N=NoHit
# For C and D types, PctId is average id with seed.
# QueryStart and SeedStart are zero-based relative to start of sequence.
# If minus strand, SeedStart is relative to reverse-complemented seed.
H\t2\t199\t97.5\t.\t0\t0\t119M80D\tref1 ecoli sequence\tusearch_ecoli_seq2
N\t*\t178\t*\t*\t*\t*\t*\tEU199232 1 1236 Bacteria/Deltaproteobacteria/Desulfurella - Hippea/uncultured\t*
H\t1\t180\t100.0\t.\t0\t0\t97M83D\tL07864 1 1200 Bacteria/Beta Gammaproteobacteria/Solemya symbiont\tSolemya seq""".split('\n')
expected_enumerated_fasta = """>0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>1
ACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
>2
CCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
>3
CCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
>4
GCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>5
CCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
>6
CGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
>7
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
>8
CGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
>9
GGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA""".split('\n')
expected_enumerated_fasta_added_options = """>Big255Ern\tuclust_test_seqs_0 some comment0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>Big256Ern\tuclust_test_seqs_1 some comment1
ACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
>Big257Ern\tuclust_test_seqs_2 some comment2
CCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
>Big258Ern\tuclust_test_seqs_3 some comment3
CCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
>Big259Ern\tuclust_test_seqs_4 some comment4
GCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>Big260Ern\tuclust_test_seqs_5 some comment4_again
CCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
>Big261Ern\tuclust_test_seqs_6 some comment6
CGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
>Big262Ern\tuclust_test_seqs_7 some comment7
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
>Big263Ern\tuclust_test_seqs_8 some comment8
CGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
>Big264Ern\tuclust_test_seqs_9 some comment9
GGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA""".split('\n')
expected_clusters_w_abundance_default_settings = """>Cluster1;size=326
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT""".split('\n')
expected_clusters_w_abundance_low_setting = """>Cluster1;size=304
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>Cluster11;size=22
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCTAACCC
CCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT""".split('\n')
expected_reference_filtered_seqs = """>usearch_ecoli_seq
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTG
ACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGT
>Solemya seq
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAG
TGGCGGACGGGTGAGTA
>usearch_ecoli_seq2
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTG
ACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTCCAT
>Solemya_seq2
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAG
TGGCGGACGGGTGAGTATCAAG""".split('\n')
expected_de_novo_chimeras_default = """>Cluster1;size=52
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGGCTTGGTGGTCCGTTACAC
CGCCAACTACCTAATGCGACGCATGCCCATCCGCTACCGGATCGCTCCTTTGGAATCCCGGGGATGTCCCCGGAACTCGT
TATGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTAGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster0;size=50
TTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCC
CGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGCGGACTCATGATGCCA
TCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGG
>Cluster2;size=45
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCTGTTACCC
CGCCAACCAGCTAATCAGACGCGGATCCATCGTATACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTT
>Cluster10;size=43
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCGCCCTCTCAGGCCGGCTATGCATCATCGTCTTGGTGGGCCTTTACCC
CGCCAACCAACTAATGCACCGCAGGTCCATCCGCGCCCCATCCCCTAAAGGATGTTTCACAGAAAGAAGATGCCTCCTTC
CTGTACATCGGGATTTGTTCTCCGTTTCCAGAGCGTATTCCCGGTGCGCGGGCAGGTTCCCTACGTGTTACTCACCCG
>Cluster4;size=40
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGTCCCATGCAGGACCGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTGCAAGGCAGGTTACCCACGCGTTACTCACCCGTCCG
>Cluster6;size=40
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGGCCATCCGCAGCCGATAAATCTTTAAACATCGGGAGATGCCTCCCAACGTTGTTA
CGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTGCGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCGG
>Cluster3;size=30
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGATCAGTCTCTCAACTCGGCTATGCATCATTGCCTTGGTAAGCCGTTACCT
TACCAACTAGCTAATGCACCGCAGGTCCATCCAAGAGTGATAGCAGAACCATCTTTCAAACTCTAGACATGCGTCTAGTG
TTGTTATCCGGTATTAGCATCTGTTTCCAGGTGTTATCCCAGTCTCTTGGG
>Cluster12;size=19
TTGGTCCGTGTCTCAGTACCAATGTGGGGGGTTAACCTCTCAGTCCCCCTATGTATCGTGGTCTTGGTGAGCCGTTACCC
CACCAACTAACTAATACAACGCATGCCCATCCATTACCACCGGAGTTTTCAACCCAAGAAGATGCCTCCCTGGATGTTAT
GGGGTATTAGTACCGATTTCTCAGTGTTATCCCCCTGTAATGGGTAGGTTGCATACGCGTTACGCACCCGTGCGCCGGTC
GCCGACAAT
>Cluster29;size=18
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGCCCATCCGCCACCGGTAATCCCTTTGGCGGCACCGGGATGCCCCGACGCCGCGTC
ACGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTGGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCGG
TCGCCGG
>Cluster30;size=18
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTTGGTGGGCCGTTACCC
CGCCAACTAGCTAATGCGCCGCATGGCCATCCGTAGCCGGTGTTACCCTTTAAACCCCAAGAGATGCCTCTCGGAGTTAT
TACGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTACGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster16;size=16
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCGTTACCC
CTCCAACCAGCTAATCAGACGCGGGTCCATCCTGTACCACCGGAGTTTTTCACACTGTACCATGCGGTACTGTGCGCTTA
TGCGGTTTTAGCACCTATTTCTAAGTGTTATCCCCCTGTACAGGGCAGGTTACCCACGCGTTACTCACCCGTCCGCCACT
>Cluster221;size=1
CTGGGCCGTATCTCAGTCCCAATGTGGCCGTTCAACCTCTCAGTCCGGCTACTGATCGTCGCCTTGGTAGGCCGTTGCCC
CGCCAACTACCTAATCGGACGCGAGCCCATCTTTCAGCGGATTGCTCCTTTGATTATCTCACCATGCGGCAAAATAATGT
CATGCGGTATTAGCGTTCGTTTCCAAACGTTATCCCCCTCTGAAAGGCAGGTTGCTCACGCGTT
>Cluster218;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGGCCACCCTCTCAGGTCGGCTACTGATCGTCACCTTGGTAGGCCGTTACCC
CACCAACTAGCTAATCAGACGCAAGCCCATCTATCAGCGGATTGCTCCTTTTCTAGCTATATCATGCGATACTACTAGCT
TATGCGGTATTAGCAATGATTTCTCACTGTTATTCCCCTCTGATAGGCAGG
>Cluster217;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGAGTCCATCTCAGAGCGATAAATCTTTGATATCCAGAGCCATGCGACCCAGATATATT
ATGCGGTATTAGCAGCTGTTTCCAGCTGTTATTCCCCATCCAAGGCAGGTT
>Cluster216;size=1
CTGGGCCGTGTCTCAGTCCCAGTGTGGCCGTCCGCCCTCTCAGGTCAGCTACTGATCGTCGCCTTGGTAGGCCATTACCC
TACCAACTAGCTAATCAGACGCGAGGCCATCTCTCAGCGATAAATCTTTGATATATCTGCCATGCGACAAACATATATTA
TGCGGTATTAGCAGTCGTTTCCAACTGTTGTCCCCCTCTGAAAGGCAGGTT""".split('\n')
expected_de_novo_chimera_filtered_skew11 = """>Cluster1;size=52
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGGCTTGGTGGTCCGTTACAC
CGCCAACTACCTAATGCGACGCATGCCCATCCGCTACCGGATCGCTCCTTTGGAATCCCGGGGATGTCCCCGGAACTCGT
TATGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTAGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster0;size=50
TTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCC
CGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGCGGACTCATGATGCCA
TCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGG
>Cluster2;size=45
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCTGTTACCC
CGCCAACCAGCTAATCAGACGCGGATCCATCGTATACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTT
>Cluster10;size=43
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCGCCCTCTCAGGCCGGCTATGCATCATCGTCTTGGTGGGCCTTTACCC
CGCCAACCAACTAATGCACCGCAGGTCCATCCGCGCCCCATCCCCTAAAGGATGTTTCACAGAAAGAAGATGCCTCCTTC
CTGTACATCGGGATTTGTTCTCCGTTTCCAGAGCGTATTCCCGGTGCGCGGGCAGGTTCCCTACGTGTTACTCACCCG
>Cluster4;size=40
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGTCCCATGCAGGACCGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTGCAAGGCAGGTTACCCACGCGTTACTCACCCGTCCG
>Cluster6;size=40
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGGCCATCCGCAGCCGATAAATCTTTAAACATCGGGAGATGCCTCCCAACGTTGTTA
CGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTGCGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCGG
>Cluster3;size=30
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGATCAGTCTCTCAACTCGGCTATGCATCATTGCCTTGGTAAGCCGTTACCT
TACCAACTAGCTAATGCACCGCAGGTCCATCCAAGAGTGATAGCAGAACCATCTTTCAAACTCTAGACATGCGTCTAGTG
TTGTTATCCGGTATTAGCATCTGTTTCCAGGTGTTATCCCAGTCTCTTGGG
>Cluster12;size=19
TTGGTCCGTGTCTCAGTACCAATGTGGGGGGTTAACCTCTCAGTCCCCCTATGTATCGTGGTCTTGGTGAGCCGTTACCC
CACCAACTAACTAATACAACGCATGCCCATCCATTACCACCGGAGTTTTCAACCCAAGAAGATGCCTCCCTGGATGTTAT
GGGGTATTAGTACCGATTTCTCAGTGTTATCCCCCTGTAATGGGTAGGTTGCATACGCGTTACGCACCCGTGCGCCGGTC
GCCGACAAT
>Cluster29;size=18
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGCCCATCCGCCACCGGTAATCCCTTTGGCGGCACCGGGATGCCCCGACGCCGCGTC
ACGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTGGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCGG
TCGCCGG
>Cluster30;size=18
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTTGGTGGGCCGTTACCC
CGCCAACTAGCTAATGCGCCGCATGGCCATCCGTAGCCGGTGTTACCCTTTAAACCCCAAGAGATGCCTCTCGGAGTTAT
TACGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTACGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster16;size=16
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCGTTACCC
CTCCAACCAGCTAATCAGACGCGGGTCCATCCTGTACCACCGGAGTTTTTCACACTGTACCATGCGGTACTGTGCGCTTA
TGCGGTTTTAGCACCTATTTCTAAGTGTTATCCCCCTGTACAGGGCAGGTTACCCACGCGTTACTCACCCGTCCGCCACT
>Cluster522;size=10
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTAT
GCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTTACT
>Cluster221;size=1
CTGGGCCGTATCTCAGTCCCAATGTGGCCGTTCAACCTCTCAGTCCGGCTACTGATCGTCGCCTTGGTAGGCCGTTGCCC
CGCCAACTACCTAATCGGACGCGAGCCCATCTTTCAGCGGATTGCTCCTTTGATTATCTCACCATGCGGCAAAATAATGT
CATGCGGTATTAGCGTTCGTTTCCAAACGTTATCCCCCTCTGAAAGGCAGGTTGCTCACGCGTT
>Cluster218;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGGCCACCCTCTCAGGTCGGCTACTGATCGTCACCTTGGTAGGCCGTTACCC
CACCAACTAGCTAATCAGACGCAAGCCCATCTATCAGCGGATTGCTCCTTTTCTAGCTATATCATGCGATACTACTAGCT
TATGCGGTATTAGCAATGATTTCTCACTGTTATTCCCCTCTGATAGGCAGG
>Cluster217;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGAGTCCATCTCAGAGCGATAAATCTTTGATATCCAGAGCCATGCGACCCAGATATATT
ATGCGGTATTAGCAGCTGTTTCCAGCTGTTATTCCCCATCCAAGGCAGGTT
>Cluster216;size=1
CTGGGCCGTGTCTCAGTCCCAGTGTGGCCGTCCGCCCTCTCAGGTCAGCTACTGATCGTCGCCTTGGTAGGCCATTACCC
TACCAACTAGCTAATCAGACGCGAGGCCATCTCTCAGCGATAAATCTTTGATATATCTGCCATGCGACAAACATATATTA
TGCGGTATTAGCAGTCGTTTCCAACTGTTGTCCCCCTCTGAAAGGCAGGTT""".split('\n')
expected_cluster_err_seqs = """>Cluster0;size=2
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT""".split('\n')
expected_sorted_by_abundance_no_filter = """>Cluster1;size=52
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGGCTTGGTGGTCCGTTACAC
CGCCAACTACCTAATGCGACGCATGCCCATCCGCTACCGGATCGCTCCTTTGGAATCCCGGGGATGTCCCCGGAACTCGT
TATGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTAGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster0;size=50
TTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCC
CGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGCGGACTCATGATGCCA
TCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGG
>Cluster2;size=45
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCTGTTACCC
CGCCAACCAGCTAATCAGACGCGGATCCATCGTATACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTT
>Cluster10;size=43
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCGCCCTCTCAGGCCGGCTATGCATCATCGTCTTGGTGGGCCTTTACCC
CGCCAACCAACTAATGCACCGCAGGTCCATCCGCGCCCCATCCCCTAAAGGATGTTTCACAGAAAGAAGATGCCTCCTTC
CTGTACATCGGGATTTGTTCTCCGTTTCCAGAGCGTATTCCCGGTGCGCGGGCAGGTTCCCTACGTGTTACTCACCCG
>Cluster4;size=40
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGTCCCATGCAGGACCGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTGCAAGGCAGGTTACCCACGCGTTACTCACCCGTCCG
>Cluster6;size=40
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGGCCATCCGCAGCCGATAAATCTTTAAACATCGGGAGATGCCTCCCAACGTTGTTA
CGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTGCGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCGG
>Cluster3;size=30
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGATCAGTCTCTCAACTCGGCTATGCATCATTGCCTTGGTAAGCCGTTACCT
TACCAACTAGCTAATGCACCGCAGGTCCATCCAAGAGTGATAGCAGAACCATCTTTCAAACTCTAGACATGCGTCTAGTG
TTGTTATCCGGTATTAGCATCTGTTTCCAGGTGTTATCCCAGTCTCTTGGG
>Cluster12;size=19
TTGGTCCGTGTCTCAGTACCAATGTGGGGGGTTAACCTCTCAGTCCCCCTATGTATCGTGGTCTTGGTGAGCCGTTACCC
CACCAACTAACTAATACAACGCATGCCCATCCATTACCACCGGAGTTTTCAACCCAAGAAGATGCCTCCCTGGATGTTAT
GGGGTATTAGTACCGATTTCTCAGTGTTATCCCCCTGTAATGGGTAGGTTGCATACGCGTTACGCACCCGTGCGCCGGTC
GCCGACAAT
>Cluster29;size=18
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGCCCATCCGCCACCGGTAATCCCTTTGGCGGCACCGGGATGCCCCGACGCCGCGTC
ACGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTGGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCGG
TCGCCGG
>Cluster30;size=18
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTTGGTGGGCCGTTACCC
CGCCAACTAGCTAATGCGCCGCATGGCCATCCGTAGCCGGTGTTACCCTTTAAACCCCAAGAGATGCCTCTCGGAGTTAT
TACGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTACGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster16;size=16
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCGTTACCC
CTCCAACCAGCTAATCAGACGCGGGTCCATCCTGTACCACCGGAGTTTTTCACACTGTACCATGCGGTACTGTGCGCTTA
TGCGGTTTTAGCACCTATTTCTAAGTGTTATCCCCCTGTACAGGGCAGGTTACCCACGCGTTACTCACCCGTCCGCCACT
>Cluster522;size=10
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTAT
GCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTTACT
>Cluster222;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTAT
GCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTTACT
>Cluster221;size=1
CTGGGCCGTATCTCAGTCCCAATGTGGCCGTTCAACCTCTCAGTCCGGCTACTGATCGTCGCCTTGGTAGGCCGTTGCCC
CGCCAACTACCTAATCGGACGCGAGCCCATCTTTCAGCGGATTGCTCCTTTGATTATCTCACCATGCGGCAAAATAATGT
CATGCGGTATTAGCGTTCGTTTCCAAACGTTATCCCCCTCTGAAAGGCAGGTTGCTCACGCGTT
>Cluster218;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGGCCACCCTCTCAGGTCGGCTACTGATCGTCACCTTGGTAGGCCGTTACCC
CACCAACTAGCTAATCAGACGCAAGCCCATCTATCAGCGGATTGCTCCTTTTCTAGCTATATCATGCGATACTACTAGCT
TATGCGGTATTAGCAATGATTTCTCACTGTTATTCCCCTCTGATAGGCAGG
>Cluster217;size=1
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGAGTCCATCTCAGAGCGATAAATCTTTGATATCCAGAGCCATGCGACCCAGATATATT
ATGCGGTATTAGCAGCTGTTTCCAGCTGTTATTCCCCATCCAAGGCAGGTT
>Cluster216;size=1
CTGGGCCGTGTCTCAGTCCCAGTGTGGCCGTCCGCCCTCTCAGGTCAGCTACTGATCGTCGCCTTGGTAGGCCATTACCC
TACCAACTAGCTAATCAGACGCGAGGCCATCTCTCAGCGATAAATCTTTGATATATCTGCCATGCGACAAACATATATTA
TGCGGTATTAGCAGTCGTTTCCAACTGTTGTCCCCCTCTGAAAGGCAGGTT""".split('\n')
expected_abundance_sort_filtered = """>Cluster1;size=52
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGGCTTGGTGGTCCGTTACAC
CGCCAACTACCTAATGCGACGCATGCCCATCCGCTACCGGATCGCTCCTTTGGAATCCCGGGGATGTCCCCGGAACTCGT
TATGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGTAGCGGGCAGGTTGCATACGTGTTACTCACCCGTGCGCCG
GTCGCCGG
>Cluster0;size=50
TTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCC
CGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGCGGACTCATGATGCCA
TCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGG
>Cluster2;size=45
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCTGTTACCC
CGCCAACCAGCTAATCAGACGCGGATCCATCGTATACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTATACGGCAGGTTCTCCACGCGTT
>Cluster10;size=43
CTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCGCCCTCTCAGGCCGGCTATGCATCATCGTCTTGGTGGGCCTTTACCC
CGCCAACCAACTAATGCACCGCAGGTCCATCCGCGCCCCATCCCCTAAAGGATGTTTCACAGAAAGAAGATGCCTCCTTC
CTGTACATCGGGATTTGTTCTCCGTTTCCAGAGCGTATTCCCGGTGCGCGGGCAGGTTCCCTACGTGTTACTCACCCG
>Cluster4;size=40
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCC
CGCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGTCCCATGCAGGACCGTGCGCTTA
TGCGGTATTAGCACCTATTTCTAAGTGTTATCCCCCAGTGCAAGGCAGGTTACCCACGCGTTACTCACCCGTCCG
>Cluster6;size=40
CTGGTCCGTGTCTCAGTACCAGTGTGGGGGACCTTCCTCTCAGAACCCCTACGCATCGTCGCCTCGGTGGGCCGTTACCC
CGCCGACTAGCTAATGCGCCGCATGGCCATCCGCAGCCGATAAATCTTTAAACATCGGGAGATGCCTCCCAACGTTGTTA
CGCGGTATTAGACGGAATTTCTTCCGCTTATCCCCCTGCTGCGGGCAGGTTCCATACGTGTTACTCACCCGTGCGCCGG""".split('\n')
expected_derep_seqs = """>seq1;size=2
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTAA
>seq2;size=2
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC""".split('\n')
expected_derep_seqs_full_len = """>Cluster0;size=1
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTTAA
>Cluster1;size=2
TTGGGCCGTGTCTCAGTCCCAATGTGGCCGTCACCCTCTCAGGCCGGCTACTGATCGTCGCCTTGGTGGGCCTTTACCCC
>Cluster2;size=1
GCCAACCAGCTAATCAGACGCGGGTCCATCTTGCACCACCGGAGTTTTTCACACTGCTTCATGCGAAGCTGTGCGCTT""".split('\n')
expected_len_sorted_seqs = """>chimera
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACCCCTAGGGTGGGAATAACCCGGGGAAACCCGGGCTAATACCGAATAAGACCACAGGAGGCGACTCCAGAGGGTCAAAGGGAGCCTTGGCCTCCCCC
>usearch_ecoli_seq2
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTCCAT
>usearch_ecoli_seq
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGT
>Solemya_seq2
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTATCAAG
>Solemya seq
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTA""".split('\n')
expected_combined_dna_seqs_1_seqs_usearch = """>uclust_test_seqs_0 some comment0
AACCCCCACGGTGGATGCCACACGCCCCATACAAAGGGTAGGATGCTTAAGACACATCGCGTCAGGTTTGTGTCAGGCCT
>uclust_test_seqs_1 some comment1
ACCCACACGGTGGATGCAACAGATCCCATACACCGAGTTGGATGCTTAAGACGCATCGCGTGAGTTTTGCGTCAAGGCT
>uclust_test_seqs_2 some comment2
CCCCCACGGTGGCAGCAACACGTCACATACAACGGGTTGGATTCTAAAGACAAACCGCGTCAAAGTTGTGTCAGAACT
>uclust_test_seqs_3 some comment3
CCCCACGGTAGCTGCAACACGTCCCATACCACGGGTAGGATGCTAAAGACACATCGGGTCTGTTTTGTGTCAGGGCT
>uclust_test_seqs_4 some comment4
GCCACGGTGGGTACAACACGTCCACTACATCGGCTTGGAAGGTAAAGACACGTCGCGTCAGTATTGCGTCAGGGCT
>uclust_test_seqs_5 some comment4_again
CCGCGGTAGGTGCAACACGTCCCATACAACGGGTTGGAAGGTTAAGACACAACGCGTTAATTTTGTGTCAGGGCA
>uclust_test_seqs_6 some comment6
CGCGGTGGCTGCAAGACGTCCCATACAACGGGTTGGATGCTTAAGACACATCGCAACAGTTTTGAGTCAGGGCT
>uclust_test_seqs_7 some comment7
ACGGTGGCTACAAGACGTCCCATCCAACGGGTTGGATACTTAAGGCACATCACGTCAGTTTTGTGTCAGAGCT
>uclust_test_seqs_8 some comment8
CGGTGGCTGCAACACGTGGCATACAACGGGTTGGATGCTTAAGACACATCGCCTCAGTTTTGTGTCAGGGCT
>uclust_test_seqs_9 some comment9
GGTGGCTGAAACACATCCCATACAACGGGTTGGATGCTTAAGACACATCGCATCAGTTTTATGTCAGGGGA
>usearch_ecoli_seq
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGT
>Solemya seq
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTA
>usearch_ecoli_seq2
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTCCAT
>Solemya_seq2
GGCTCAGATTGAACGCTGGCGGCATGCCTAACACATGCAAGTCGAACGGTAACAGGCGGAGCTTGCTCTGCGCTGACGAGTGGCGGACGGGTGAGTATCAAG
>chimera
CGCGTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAGGGAGTAAAGTTAATACCTTTGCTCATTGACCCCTAGGGTGGGAATAACCCGGGGAAACCCGGGCTAATACCGAATAAGACCACAGGAGGCGACTCCAGAGGGTCAAAGGGAGCCTTGGCCTCCCCC""".split('\n')
expected_retained_chimeras_union = """>seq1
ACAGGCC
>seq2
ACAGGCCCCC
>seq3
TTATCCATT
>seq4
ACAGGCCCCC
>seq5
TTATCCATT""".split('\n')
expected_retained_chimeras_intersection = """>seq3
TTATCCATT""".split('\n')
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_util.py 000644 000765 000024 00000147511 12024702176 021621 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from cogent.app.util import Application, CommandLineApplication, \
CommandLineAppResult, ResultPath, ApplicationError, ParameterIterBase,\
ParameterCombinations, cmdline_generator, ApplicationNotFoundError,\
get_tmp_filename, guess_input_handler
from cogent.app.parameters import *
from os import remove,system,mkdir,rmdir,removedirs,getcwd, walk
__author__ = "Greg Caporaso and Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Greg Caporaso", "Sandra Smit", "Gavin Huttley",
"Rob Knight", "Daniel McDonald"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Development"
class ParameterCombinationsTests(TestCase):
def setUp(self):
"""Setup for ParameterCombinations tests"""
self.mock_app = ParameterCombinationsApp
self.params = {'-flag1':True,
'--value1':range(0,5),
'-delim':range(0,2),
'-mix1':[None] + range(0,3)}
self.always_on = ['--value1']
self.param_iter = ParameterCombinations(self.mock_app, self.params,
self.always_on)
def test_init_generator(self):
"""Tests generator capabilities"""
all_params = list(self.param_iter)
self.assertEqual(len(all_params), 150)
params = {'-flag1':True,
'--value1':1,
'-delim':['choice1','choice2']}
always_on = ['-flag1','-delim']
param_iter = ParameterCombinations(self.mock_app, params, always_on)
exp = [self.mock_app._parameters.copy(),
self.mock_app._parameters.copy(),
self.mock_app._parameters.copy(),
self.mock_app._parameters.copy()]
# default is on in all these cases
exp[0]['-flag1'].on()
exp[0]['--value1'].on(1)
exp[0]['-delim'].on('choice1')
exp[1]['-flag1'].on()
exp[1]['--value1'].on(1)
exp[1]['-delim'].on('choice2')
exp[2]['-flag1'].on()
exp[2]['--value1'].off()
exp[2]['-delim'].on('choice1')
exp[3]['-flag1'].on()
exp[3]['--value1'].off()
exp[3]['-delim'].on('choice2')
obs = list(param_iter)
self.assertEqual(obs,exp)
def test_reset(self):
"""Resets the iterator"""
first = list(self.param_iter)
self.assertRaises(StopIteration, self.param_iter.next)
self.param_iter.reset()
second = list(self.param_iter)
self.assertEqual(first, second)
class ParameterIterBaseTests(TestCase):
def setUp(self):
"""Setup for ParameterIterBase tests"""
self.mock_app = ParameterCombinationsApp
self.params = {'-flag1':True,
'--value1':range(0,5),
'-delim':range(0,2),
'-mix1':[None] + range(0,3)}
self.always_on = ['--value1']
self.param_base = ParameterIterBase(self.mock_app, self.params,
self.always_on)
def test_init(self):
"""Test constructor"""
exp_params = {'-flag1':[True, False],
'--value1':range(0,5),
'-delim':range(0,2) + [False],
'-mix1':[None,0,1,2] + [False]}
exp_keys = exp_params.keys()
exp_values = exp_params.values()
self.assertEqual(sorted(self.param_base._keys), sorted(exp_keys))
self.assertEqual(sorted(self.param_base._values), sorted(exp_values))
self.params['asdasda'] = 5
self.assertRaises(ValueError, ParameterIterBase, self.mock_app, \
self.params, self.always_on)
self.params.pop('asdasda')
self.always_on.append('asdasd')
self.assertRaises(ValueError, ParameterIterBase, self.mock_app, \
self.params, self.always_on)
def test_make_app_params(self):
"""Returns app parameters with expected values set"""
values = [0,0,True,None]
exp = self.mock_app._parameters.copy()
exp['-flag1'].on()
exp['--value1'].on(0)
exp['-delim'].on(0)
exp['-mix1'].on(None)
obs = self.param_base._make_app_params(values)
self.assertEqual(obs, exp)
state = [4,False,False,False]
exp = self.mock_app._parameters.copy()
exp['-flag1'].off()
exp['--value1'].on(4)
exp['-delim'].off()
exp['-mix1'].off()
obs = self.param_base._make_app_params(values)
self.assertEqual(obs, exp)
class CommandLineGeneratorTests(TestCase):
def setUp(self):
self.abs_path_to_bin = '/bin/path'
self.abs_path_to_cmd = '/cmd/path'
self.abs_path_to_input = '/input/path'
self.abs_path_to_output = '/output/path'
self.abs_path_to_stdout = '/stdout/path'
self.abs_path_to_stderr = '/stderr/path'
self.app = ParameterCombinationsApp
params = {'-flag1':True,
'-delim':['choice1','choice2']}
always_on = ['-delim']
self.mock_app = ParameterCombinationsApp
self.param_iter = ParameterCombinations(self.mock_app,params, always_on)
def test_cmdline_generator_easy(self):
"""Returns parameter combinations commandlines"""
cmdgen = cmdline_generator(self.param_iter,
PathToBin=self.abs_path_to_bin,
PathToCmd=self.abs_path_to_cmd,
PathsToInputs=self.abs_path_to_input,
PathToOutput=self.abs_path_to_output,
PathToStdout=self.abs_path_to_stdout,
PathToStderr=self.abs_path_to_stderr,
UniqueOutputs=False,
InputParam='-input',
OutputParam='-output')
bin = self.abs_path_to_bin
cmd = self.abs_path_to_cmd
inputfile = self.abs_path_to_input
outputfile = self.abs_path_to_output
stdout = self.abs_path_to_stdout
stderr = self.abs_path_to_stderr
exp = [' '.join([bin, cmd, '-default=42', '-delimaaachoice1','-flag1',\
'-input="%s"' % inputfile,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr])]
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1', \
'-input="%s"' % inputfile,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42','-delimaaachoice2', \
'-flag1', '-input="%s"' % inputfile, \
'-output="%s"' % outputfile, '> "%s"' % stdout,\
'2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice2', \
'-input="%s"' % inputfile,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
cmdlines = list(cmdgen)
self.assertEqual(cmdlines, exp)
def test_cmdline_generator_hard(self):
"""Returns parameter combinations commandlines. Test stdin/stdout"""
cmdgen = cmdline_generator(self.param_iter,
PathToBin=self.abs_path_to_bin,
PathToCmd=self.abs_path_to_cmd,
PathsToInputs=self.abs_path_to_input,
PathToOutput=self.abs_path_to_output,
PathToStdout=self.abs_path_to_stdout,
PathToStderr=self.abs_path_to_stderr,
UniqueOutputs=True,
InputParam=None,
OutputParam=None)
bin = self.abs_path_to_bin
cmd = self.abs_path_to_cmd
inputfile = self.abs_path_to_input
outputfile = self.abs_path_to_output
stdout = self.abs_path_to_stdout
stderr = self.abs_path_to_stderr
# the extra '' is intentionally added. When stdout is used for actual
# output, the stdout_ param gets set to '' which results in an extra
# space being generated on the cmdline. this should be benign
# across operating systems
exp = [' '.join([bin, cmd, '-default=42', '-delimaaachoice1','-flag1',\
'< "%s"' % inputfile, '> "%s"0' % outputfile, '',\
'2> "%s"' % stderr])]
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1', \
'< "%s"' % inputfile,'> "%s"1' % outputfile, '',\
'2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42','-delimaaachoice2', \
'-flag1', '< "%s"' % inputfile, \
'> "%s"2' % outputfile, '', '2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice2', \
'< "%s"' % inputfile,'> "%s"3' % outputfile, '',\
'2> "%s"' % stderr]))
cmdlines = list(cmdgen)
self.assertEqual(cmdlines, exp)
def test_cmdline_generator_stdout_stderr_off(self):
"""Returns cmdlines with stdout and stderr disabled"""
cmdgen = cmdline_generator(self.param_iter,
PathToBin=self.abs_path_to_bin,
PathToCmd=self.abs_path_to_cmd,
PathsToInputs=self.abs_path_to_input,
PathToOutput=self.abs_path_to_output,
PathToStdout=None,
PathToStderr=None,
UniqueOutputs=False,
InputParam='-input',
OutputParam='-output')
bin = self.abs_path_to_bin
cmd = self.abs_path_to_cmd
inputfile = self.abs_path_to_input
outputfile = self.abs_path_to_output
stdout = self.abs_path_to_stdout
stderr = self.abs_path_to_stderr
exp = [' '.join([bin, cmd, '-default=42', '-delimaaachoice1','-flag1',\
'-input="%s"' % inputfile,'-output="%s"' % outputfile,\
'',''])]
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1', \
'-input="%s"' % inputfile,'-output="%s"' % outputfile,\
'','']))
exp.append(' '.join([bin, cmd, '-default=42','-delimaaachoice2', \
'-flag1', '-input="%s"' % inputfile, \
'-output="%s"' % outputfile,'','']))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice2', \
'-input="%s"' % inputfile,'-output="%s"' % outputfile,\
'','']))
cmdlines = list(cmdgen)
self.assertEqual(cmdlines, exp)
def test_cmdline_generator_multiple_inputs(self):
"""Tests the cmdline_generator for multiple input support"""
paths_to_inputs = ['/some/dir/a','/some/dir/b']
cmdgen = cmdline_generator(self.param_iter,
PathToBin=self.abs_path_to_bin,
PathToCmd=self.abs_path_to_cmd,
PathsToInputs=paths_to_inputs,
PathToOutput=self.abs_path_to_output,
PathToStdout=self.abs_path_to_stdout,
PathToStderr=self.abs_path_to_stderr,
UniqueOutputs=False,
InputParam='-input',
OutputParam='-output')
bin = self.abs_path_to_bin
cmd = self.abs_path_to_cmd
inputfile1 = paths_to_inputs[0]
inputfile2 = paths_to_inputs[1]
outputfile = self.abs_path_to_output
stdout = self.abs_path_to_stdout
stderr = self.abs_path_to_stderr
exp = [' '.join([bin, cmd, '-default=42', '-delimaaachoice1','-flag1',\
'-input="%s"' % inputfile1,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr])]
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1',\
'-flag1', '-input="%s"' % inputfile2,\
'-output="%s"' % outputfile, '> "%s"' % stdout, \
'2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1', \
'-input="%s"' % inputfile1,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1', \
'-input="%s"' % inputfile2,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42','-delimaaachoice2', \
'-flag1', '-input="%s"' % inputfile1, \
'-output="%s"' % outputfile, '> "%s"' % stdout,\
'2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42','-delimaaachoice2', \
'-flag1', '-input="%s"' % inputfile2, \
'-output="%s"' % outputfile, '> "%s"' % stdout,\
'2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice2', \
'-input="%s"' % inputfile1,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice2', \
'-input="%s"' % inputfile2,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
cmdlines = list(cmdgen)
self.assertEqual(cmdlines, exp)
def test_cmdline_generator_multiple_input_stdin(self):
"""Tests cmdline_generator for multiple inputs over stdin"""
paths_to_inputs = ['/some/dir/a','/some/dir/b']
cmdgen = cmdline_generator(self.param_iter,
PathToBin=self.abs_path_to_bin,
PathToCmd=self.abs_path_to_cmd,
PathsToInputs=paths_to_inputs,
PathToOutput=self.abs_path_to_output,
PathToStdout=self.abs_path_to_stdout,
PathToStderr=self.abs_path_to_stderr,
UniqueOutputs=False,
InputParam=None,
OutputParam='-output')
bin = self.abs_path_to_bin
cmd = self.abs_path_to_cmd
inputfile1 = paths_to_inputs[0]
inputfile2 = paths_to_inputs[1]
outputfile = self.abs_path_to_output
stdout = self.abs_path_to_stdout
stderr = self.abs_path_to_stderr
exp = [' '.join([bin, cmd, '-default=42', '-delimaaachoice1','-flag1',\
'< "%s"' % inputfile1,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr])]
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1',\
'-flag1', '< "%s"' % inputfile2,\
'-output="%s"' % outputfile, '> "%s"' % stdout, \
'2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1', \
'< "%s"' % inputfile1,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice1', \
'< "%s"' % inputfile2,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42','-delimaaachoice2', \
'-flag1', '< "%s"' % inputfile1, \
'-output="%s"' % outputfile, '> "%s"' % stdout,\
'2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42','-delimaaachoice2', \
'-flag1', '< "%s"' % inputfile2, \
'-output="%s"' % outputfile, '> "%s"' % stdout,\
'2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice2', \
'< "%s"' % inputfile1,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
exp.append(' '.join([bin, cmd, '-default=42', '-delimaaachoice2', \
'< "%s"' % inputfile2,'-output="%s"' % outputfile,\
'> "%s"' % stdout, '2> "%s"' % stderr]))
cmdlines = list(cmdgen)
self.assertEqual(cmdlines, exp)
class CommandLineApplicationTests(TestCase):
"""Tests for the CommandLineApplication class"""
def setUp(self):
"""setUp for all CommandLineApplication tests"""
f = open('/tmp/CLAppTester.py','w')
f.write(script)
f.close()
system('chmod 777 /tmp/CLAppTester.py')
# create a copy of the script with a space in the name
f = open('/tmp/CLApp Tester.py','w')
f.write(script)
f.close()
system('chmod 777 "/tmp/CLApp Tester.py"')
self.app_no_params = CLAppTester()
self.app_no_params_no_stderr = CLAppTester(SuppressStderr=True)
self.app_params =CLAppTester({'-F':'p_file.txt'})
self.app_params_space_in_command =\
CLAppTester_space_in_command({'-F':'p_file.txt'})
self.app_params_no_stderr =CLAppTester({'-F':'p_file.txt'},\
SuppressStderr=True)
self.app_params_no_stdout =CLAppTester({'-F':'p_file.txt'},\
SuppressStdout=True)
self.app_params_input_as_file =CLAppTester({'-F':'p_file.txt'},\
InputHandler='_input_as_lines')
self.app_params_WorkingDir =CLAppTester({'-F':'p_file.txt'},\
WorkingDir='/tmp/test')
self.app_params_WorkingDir_w_space =CLAppTester({'-F':'p_file.txt'},\
WorkingDir='/tmp/test space')
self.app_params_TmpDir =CLAppTester({'-F':'p_file.txt'},\
TmpDir='/tmp/tmp2')
self.app_params_TmpDir_w_space =CLAppTester({'-F':'p_file.txt'},\
TmpDir='/tmp/tmp space')
self.data = 42
def test_base_command(self):
"""CLAppTester: BaseCommand correctly composed """
# No parameters on
app = CLAppTester()
self.assertEqual(app.BaseCommand,'cd "/tmp/"; /tmp/CLAppTester.py')
# ValuedParameter on/off
app.Parameters['-F'].on('junk.txt')
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; /tmp/CLAppTester.py -F "junk.txt"')
app.Parameters['-F'].off()
self.assertEqual(app.BaseCommand,'cd "/tmp/"; /tmp/CLAppTester.py')
# ValuedParameter accessed by synonym turned on/off
app.Parameters['File'].on('junk.txt')
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; /tmp/CLAppTester.py -F "junk.txt"')
app.Parameters['File'].off()
self.assertEqual(app.BaseCommand,'cd "/tmp/"; /tmp/CLAppTester.py')
# Try multiple parameters, must check for a few different options
# because parameters are printed in arbitrary order
app.Parameters['-F'].on('junk.txt')
app.Parameters['--duh'].on()
self.failUnless(app.BaseCommand ==\
'cd "/tmp/"; /tmp/CLAppTester.py -F "junk.txt" --duh'\
or app.BaseCommand ==\
'cd "/tmp/"; /tmp/CLAppTester.py --duh -F "junk.txt"')
# Space in _command
app = CLAppTester_space_in_command()
self.assertEqual(app.BaseCommand,'cd "/tmp/"; "/tmp/CLApp Tester.py"')
def test_getHelp(self):
"""CLAppTester: getHelp() functions as expected """
app = CLAppTester()
self.assertEqual(app.getHelp(),'Duh')
def test_handle_app_result_build_failure(self):
"""_handle_app_result_build_failure called when CommandLineAppResult() fails
"""
app = CLAppTester_bad_fixed_file()
self.assertRaises(ApplicationError,app)
app = CLAppTester_bad_fixed_file_w_handler()
self.assertEqual(app(),"Called self._handle_app_result_build_failure")
def test_error_on_missing_executable(self):
"""CLAppTester: Useful error message on executable not found
"""
# fake command via self._command
class Blah(CLAppTester):
_command = 'fake_command_jasdlkfsadlkfskladfkladf'
self.assertRaises(ApplicationNotFoundError,Blah)
# real command but bad path via self._command
class Blah(CLAppTester):
_command = '/not/a/real/path/ls'
self.assertRaises(ApplicationNotFoundError,Blah)
# alt _error_on_missing_command function works as expected
class Blah(CLAppTester):
_command = 'ls'
def _error_on_missing_application(self,data):
raise ApplicationNotFoundError
self.assertRaises(ApplicationNotFoundError,Blah)
class Blah(CLAppTester):
_command = 'fake_app_asfasdasdasdasdasd'
def _error_on_missing_application(self,data):
pass
# no error raised
Blah()
def test_no_p_no_d(self):
"""CLAppTester: parameters turned off, no data"""
app = self.app_no_params
#test_init
assert app.Parameters['-F'].isOff()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
#test_command
self.assertEqual(app.BaseCommand,'cd "/tmp/"; /tmp/CLAppTester.py')
#test_result
result = app()
self.assertEqual(result['StdOut'].read(),'out\n')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
self.assertEqual(result['parameterized_file'],None)
result.cleanUp()
def test_no_p_data_as_str(self):
"""CLAppTester: parameters turned off, data as string"""
app = self.app_no_params
#test_init
assert app.Parameters['-F'].isOff()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
#test_command
self.assertEqual(app.BaseCommand,'cd "/tmp/"; /tmp/CLAppTester.py')
#test_result
result = app(self.data)
self.assertEqual(result['StdOut'].read(),'out 43\n')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
self.assertEqual(result['parameterized_file'],None)
result.cleanUp()
def test_p_data_as_str_suppress_stderr(self):
"""CLAppTester: parameters turned on, data as string, suppress stderr"""
app = self.app_params_no_stderr
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert app.SuppressStderr
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; /tmp/CLAppTester.py -F "p_file.txt"')
#test_result
result = app(self.data)
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'],None)
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
self.assertEqual(result['parameterized_file'].read(),\
'out 43 p_file.txt')
result.cleanUp()
def test_p_data_as_str_suppress_stdout(self):
"""CLAppTester: parameters turned on, data as string, suppress stdout"""
app = self.app_params_no_stdout
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert app.SuppressStdout
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; /tmp/CLAppTester.py -F "p_file.txt"')
#test_result
result = app(self.data)
self.assertEqual(result['StdOut'],None)
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
self.assertEqual(result['parameterized_file'].read(),\
'out 43 p_file.txt')
result.cleanUp()
def test_p_no_data(self):
"""CLAppTester: parameters turned on, no data"""
app = self.app_params
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; /tmp/CLAppTester.py -F "p_file.txt"')
#test_result
result = app()
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
self.assertEqual(result['parameterized_file'].read(),\
'out p_file.txt')
result.cleanUp()
def test_p_space_in_command(self):
"""CLAppTester: parameters turned on, no data, space in command"""
app = self.app_params_space_in_command
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; "/tmp/CLApp Tester.py" -F "p_file.txt"')
#test_result
result = app()
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
self.assertEqual(result['parameterized_file'].read(),\
'out p_file.txt')
result.cleanUp()
def test_p_data_as_str(self):
"""CLAppTester: parameters turned on, data as str"""
app = self.app_params
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; /tmp/CLAppTester.py -F "p_file.txt"')
#test_result
result = app(self.data)
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
self.assertEqual(result['parameterized_file'].read(),\
'out 43 p_file.txt')
result.cleanUp()
def test_p_data_as_file(self):
"""CLAppTester: parameters turned on, data as file"""
app = self.app_params_input_as_file
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_lines')
assert not app.SuppressStderr
#test_command
# we don't test the command in this case, because we don't know what
# the name of the input file is.
#test_result
result = app([self.data])
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
self.assertEqual(result['parameterized_file'].read(),\
'out 43 p_file.txt')
result.cleanUp()
def test_WorkingDir(self):
"""CLAppTester: WorkingDir functions as expected """
system('cp /tmp/CLAppTester.py /tmp/test/CLAppTester.py')
app = self.app_params_WorkingDir
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
# WorkingDir is what we expect
self.assertEqual(app.WorkingDir,'/tmp/test/')
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/test/"; /tmp/CLAppTester.py -F "p_file.txt"')
#test_result
result = app()
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
# Make sure that the parameterized file is in the correct place
self.assertEqual(result['parameterized_file'].name,\
'/tmp/test/p_file.txt')
self.assertEqual(result['parameterized_file'].read(),\
'out p_file.txt')
result.cleanUp()
def test_WorkingDir_w_space(self):
"""CLAppTester: WorkingDir w/ space in path functions as expected """
system('cp /tmp/CLAppTester.py "/tmp/test space/CLAppTester.py"')
app = self.app_params_WorkingDir_w_space
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
# WorkingDir is what we expect
self.assertEqual(app.WorkingDir,'/tmp/test space/')
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/test space/"; /tmp/CLAppTester.py -F "p_file.txt"')
#test_result
result = app()
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
# Make sure that the parameterized file is in the correct place
self.assertEqual(result['parameterized_file'].name,\
'/tmp/test space/p_file.txt')
self.assertEqual(result['parameterized_file'].read(),\
'out p_file.txt')
result.cleanUp()
def test_TmpDir(self):
"""CLAppTester: Alternative TmpDir functions as expected"""
app = self.app_params_TmpDir
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
# TmpDir is what we expect
self.assertEqual(app.TmpDir,'/tmp/tmp2')
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; /tmp/CLAppTester.py -F "p_file.txt"')
#test_result
result = app()
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
# Make sure that the parameterized file is in the correct place
self.assertEqual(result['parameterized_file'].name,\
'/tmp/p_file.txt')
self.assertEqual(result['parameterized_file'].read(),\
'out p_file.txt')
result.cleanUp()
def test_TmpDir_w_space(self):
"""CLAppTester: TmpDir functions as expected w space in name"""
app = self.app_params_TmpDir_w_space
#test_init
assert app.Parameters['-F'].isOn()
self.assertEqual(app.InputHandler,'_input_as_string')
assert not app.SuppressStderr
# TmpDir is what we expect
self.assertEqual(app.TmpDir,'/tmp/tmp space')
#test_command
self.assertEqual(app.BaseCommand,\
'cd "/tmp/"; /tmp/CLAppTester.py -F "p_file.txt"')
#test_result
result = app()
self.assertEqual(result['StdOut'].read(),'')
self.assertEqual(result['StdErr'].read(),'I am stderr\n')
self.assertEqual(result['ExitStatus'],0)
self.assertEqual(result['fixed_file'].read(),'I am fixed file')
self.assertEqual(result['base_dep_1'].read(),'base dependent 1')
self.assertEqual(result['base_dep_2'].read(),'base dependent 2')
# Make sure that the parameterized file is in the correct place
self.assertEqual(result['parameterized_file'].name,\
'/tmp/p_file.txt')
self.assertEqual(result['parameterized_file'].read(),\
'out p_file.txt')
result.cleanUp()
def test_input_as_string(self):
"""CLAppTester: _input_as_string functions as expected """
self.assertEqual(self.app_no_params._input_as_string('abcd'),'abcd')
self.assertEqual(self.app_no_params._input_as_string(42),'42')
self.assertEqual(self.app_no_params._input_as_string(None),'None')
self.assertEqual(self.app_no_params._input_as_string([1]),'[1]')
self.assertEqual(self.app_no_params._input_as_string({'a':1}),\
"{'a': 1}")
def test_input_as_lines_from_string(self):
"""CLAppTester: _input_as_lines functions as expected w/ data as str
"""
filename = self.app_no_params._input_as_lines('abcd')
self.assertEqual(filename[0],'/')
f = open(filename)
self.assertEqual(f.readline(),'a\n')
self.assertEqual(f.readline(),'b\n')
self.assertEqual(f.readline(),'c\n')
self.assertEqual(f.readline(),'d')
f.close()
remove(filename)
def test_input_as_lines_from_list(self):
"""CLAppTester: _input_as_lines functions as expected w/ data as list
"""
filename = self.app_no_params._input_as_lines(['line 1',None,3])
self.assertEqual(filename[0],'/')
f = open(filename)
self.assertEqual(f.readline(),'line 1\n')
self.assertEqual(f.readline(),'None\n')
self.assertEqual(f.readline(),'3')
f.close()
remove(filename)
def test_input_as_lines_from_list_w_newlines(self):
"""CLAppTester: _input_as_lines functions w/ data as list w/ newlines
"""
filename = self.app_no_params._input_as_lines(['line 1\n',None,3])
self.assertEqual(filename[0],'/')
f = open(filename)
self.assertEqual(f.readline(),'line 1\n')
self.assertEqual(f.readline(),'None\n')
self.assertEqual(f.readline(),'3')
f.close()
remove(filename)
def test_input_as_multiline_string(self):
"""CLAppTester: _input_as_multiline_string functions as expected
"""
filename = self.app_no_params._input_as_multiline_string(\
'line 1\nNone\n3')
self.assertEqual(filename[0],'/')
f = open(filename)
self.assertEqual(f.readline(),'line 1\n')
self.assertEqual(f.readline(),'None\n')
self.assertEqual(f.readline(),'3')
f.close()
remove(filename)
def test_input_as_lines_from_list_single_entry(self):
"""CLAppTester: _input_as_lines functions as expected w/ 1 element list
"""
filename = self.app_no_params._input_as_lines(['line 1'])
self.assertEqual(filename[0],'/')
f = open(filename)
self.assertEqual(f.readline(),'line 1')
f.close()
remove(filename)
def test_input_as_multiline_string_single_line(self):
"""CLAppTester: _input_as_multiline_string functions w/ single line
"""
# functions as expected with single line string
filename = self.app_no_params._input_as_multiline_string(\
'line 1')
self.assertEqual(filename[0],'/')
f = open(filename)
self.assertEqual(f.readline(),'line 1')
f.close()
remove(filename)
def test_getTmpFilename_non_default(self):
"""TmpFilename handles alt tmp_dir, prefix and suffix properly"""
app = CLAppTester()
obs = app.getTmpFilename(include_class_id=False)
self.assertTrue(obs.startswith('/tmp/tmp'))
self.assertTrue(obs.endswith('.txt'))
obs = app.getTmpFilename(tmp_dir="/tmp/blah",prefix="app_ctl_test",\
suffix='.test',include_class_id=False)
self.assertTrue(obs.startswith('/tmp/blah/app_ctl_test'))
self.assertTrue(obs.endswith('.test'))
def test_getTmpFilename_defaults_to_no_class_id(self):
"""CLAppTester: getTmpFilename doesn't include class id by default
"""
# I want to explicitly test for this so people don't forget to
# set the default to False if they change it for testing purposes
app = CLAppTester()
self.assertFalse(app.getTmpFilename().\
startswith('/tmp/tmpCLAppTester'))
self.assertTrue(app.getTmpFilename(include_class_id=True).\
startswith('/tmp/tmpCLAppTester'))
def test_input_as_path(self):
"""CLAppTester: _input_as_path casts data to FilePath"""
actual = self.app_no_params._input_as_path('test.pdb')
self.assertEqual(actual,'test.pdb')
self.assertEqual(str(actual),'"test.pdb"')
actual = self.app_no_params._input_as_path('te st.pdb')
self.assertEqual(actual,'te st.pdb')
self.assertEqual(str(actual),'"te st.pdb"')
actual = self.app_no_params._input_as_path('./test.pdb')
self.assertEqual(actual,'./test.pdb')
self.assertEqual(str(actual),'"./test.pdb"')
actual = self.app_no_params._input_as_path('/this/is/a/test.pdb')
self.assertEqual(actual,'/this/is/a/test.pdb')
self.assertEqual(str(actual),'"/this/is/a/test.pdb"')
actual = self.app_no_params._input_as_path('/this/i s/a/test.pdb')
self.assertEqual(actual,'/this/i s/a/test.pdb')
self.assertEqual(str(actual),'"/this/i s/a/test.pdb"')
def test_input_as_paths(self):
"""CLAppTester: _input_as_paths casts each input to FilePath """
input = ['test.pdb']
actual = self.app_no_params._input_as_paths(input)
expected = '"test.pdb"'
self.assertEqual(actual,expected)
input = ['test1.pdb','test2.pdb']
actual = self.app_no_params._input_as_paths(input)
expected = '"test1.pdb" "test2.pdb"'
self.assertEqual(actual,expected)
input = ['/path/to/test1.pdb','test2.pdb']
actual = self.app_no_params._input_as_paths(input)
expected = '"/path/to/test1.pdb" "test2.pdb"'
self.assertEqual(actual,expected)
input = ['test1.pdb','/path/to/test2.pdb']
actual = self.app_no_params._input_as_paths(input)
expected = '"test1.pdb" "/path/to/test2.pdb"'
self.assertEqual(actual,expected)
input = ['/path/to/test1.pdb','/path/to/test2.pdb']
actual = self.app_no_params._input_as_paths(input)
expected = '"/path/to/test1.pdb" "/path/to/test2.pdb"'
self.assertEqual(actual,expected)
input = ['/pa th/to/test1.pdb','/path/to/te st2.pdb']
actual = self.app_no_params._input_as_paths(input)
expected = '"/pa th/to/test1.pdb" "/path/to/te st2.pdb"'
self.assertEqual(actual,expected)
def test_absolute(self):
"""CLAppTester: _absolute converts relative paths to absolute paths
"""
absolute = self.app_no_params._absolute
self.assertEqual(absolute('/tmp/test.pdb'),'/tmp/test.pdb')
self.assertEqual(absolute('test.pdb'),'/tmp/test.pdb')
def test_working_dir_setting(self):
"""CLAppTester: WorkingDir is set correctly """
app = CLAppTester_no_working_dir()
self.assertEqual(app.WorkingDir,getcwd()+'/')
def test_error_raised_on_command_None(self):
"""CLAppTester: An error is raises when _command == None """
app = CLAppTester()
app._command = None
self.assertRaises(ApplicationError, app._get_base_command)
def test_rejected_exit_status(self):
"""CLAppTester_reject_exit_status results in useful error """
app = CLAppTester_reject_exit_status()
self.assertRaises(ApplicationError,app)
def test_getTmpFilename(self):
"""TmpFilename should return filename of correct length"""
app = CLAppTester()
obs = app.getTmpFilename(include_class_id=True)
# leaving the strings in this statement so it's clear where the expected
# length comes from
self.assertEqual(len(obs), len(app.TmpDir) + len('/') + app.TmpNameLen \
+ len('tmp') + len('CLAppTester') + len('.txt'))
assert obs.startswith(app.TmpDir)
chars = set(obs[18:])
assert len(chars) > 1
obs = app.getTmpFilename(include_class_id=False)
# leaving the strings in this statement so it's clear where the expected
# length comes from
self.assertEqual(len(obs), len(app.TmpDir) + len('/') + app.TmpNameLen \
+ len('tmp') + len('.txt'))
assert obs.startswith(app.TmpDir)
def test_getTmpFilename_prefix_suffix_result_constructor(self):
"""TmpFilename: result has correct prefix, suffix, type"""
app = CLAppTester()
obs = app.getTmpFilename(prefix='blah',include_class_id=False)
self.assertTrue(obs.startswith('/tmp/blah'))
obs = app.getTmpFilename(suffix='.blah',include_class_id=False)
self.assertTrue(obs.endswith('.blah'))
# Prefix defaults to not include the class name
obs = app.getTmpFilename(include_class_id=False)
self.assertFalse(obs.startswith('/tmp/tmpCLAppTester'))
self.assertTrue(obs.endswith('.txt'))
# including class id functions correctly
obs = app.getTmpFilename(include_class_id=True)
self.assertTrue(obs.startswith('/tmp/tmpCLAppTester'))
self.assertTrue(obs.endswith('.txt'))
# result as FilePath
obs = app.getTmpFilename(result_constructor=FilePath)
self.assertEqual(type(obs),FilePath)
# result as str (must check that result is a str and is not a FilePath
# since a FilePath is a str)
obs = app.getTmpFilename(result_constructor=str)
self.assertEqual(type(obs),str)
self.assertNotEqual(type(obs),FilePath)
class ConvenienceFunctionTests(TestCase):
"""
"""
def setUp(self):
"""
"""
self.tmp_dir = '/tmp'
self.tmp_name_len = 20
def test_guess_input_handler(self):
"""guess_input_handler should correctly identify input"""
gih = guess_input_handler
self.assertEqual(gih('abc.txt'), '_input_as_string')
self.assertEqual(gih('>ab\nTCAG'), '_input_as_multiline_string')
self.assertEqual(gih(['ACC','TGA'], True), '_input_as_seqs')
self.assertEqual(gih(['>a','ACC','>b','TGA']), '_input_as_lines')
self.assertEqual(gih([('a','ACC'),('b','TGA')]),\
'_input_as_seq_id_seq_pairs')
self.assertEqual(gih([]),'_input_as_lines')
def test_get_tmp_filename(self):
"""get_tmp_filename should return filename of correct length
Adapted from the CommandLineApplication tests of the member function
"""
obs = get_tmp_filename()
# leaving the strings in this statement so it's clear where the expected
# length comes from
self.assertEqual(len(obs), len(self.tmp_dir) + len('/') + self.tmp_name_len \
+ len('tmp') + len('.txt'))
self.assertTrue(obs.startswith('/tmp'))
# different results on different calls
self.assertNotEqual(get_tmp_filename(),get_tmp_filename())
obs = get_tmp_filename()
# leaving the strings in this statement so it's clear where the expected
# length comes from
self.assertEqual(len(obs), len(self.tmp_dir) + len('/') + self.tmp_name_len \
+ len('tmp') + len('.txt'))
assert obs.startswith(self.tmp_dir)
def test_get_tmp_filename_prefix_suffix_constructor(self):
"""get_tmp_filename: result has correct prefix, suffix, type
Adapted from the CommandLineApplication tests of the member function
"""
obs = get_tmp_filename(prefix='blah')
self.assertTrue(obs.startswith('/tmp/blah'))
obs = get_tmp_filename(suffix='.blah')
self.assertTrue(obs.endswith('.blah'))
# result as FilePath
obs = get_tmp_filename(result_constructor=FilePath)
self.assertEqual(type(obs),FilePath)
# result as str (must check that result is a str and is not a FilePath
# since a FilePath is a str)
obs = get_tmp_filename(result_constructor=str)
self.assertEqual(type(obs),str)
self.assertNotEqual(type(obs),FilePath)
class RemoveTests(TestCase):
def test_remove(self):
"""This will remove the test script. Not actually a test!"""
for dir, n, fnames in walk('/tmp/test/'):
for f in fnames:
try:
remove(dir + f)
except OSError, e:
pass
remove('/tmp/CLAppTester.py')
remove('/tmp/test space/CLAppTester.py')
remove('/tmp/CLApp Tester.py')
rmdir('/tmp/tmp space')
rmdir('/tmp/test')
rmdir('/tmp/test space')
rmdir('/tmp/tmp2')
rmdir('/tmp/blah')
#=====================END OF TESTS===================================
script = """#!/usr/bin/env python
#This is a test script intended to test the CommandLineApplication
#class and CommandLineAppResult class
from sys import argv, stderr,stdin
from os import isatty
out_file_name = None
input_arg = None
# parse input
try:
if argv[1] == '-F':
out_file_name = argv[2]
except IndexError:
pass
try:
if out_file_name:
input_arg = argv[3]
else:
input_arg = argv[1]
except IndexError:
pass
# Create the output string
out = 'out'
# get input
try:
f = open(str(input_arg))
data = int(f.readline().strip())
except IOError:
try:
data = int(input_arg)
except TypeError:
data = None
if data:
data = str(data + 1)
out = ' '.join([out,data])
# Write base dependent output files
base = 'BASE'
f = open('/tmp/' + base + '.1','w')
f.writelines(['base dependent 1'])
f.close()
f = open('/tmp/' + base + '.2','w')
f.writelines(['base dependent 2'])
f.close()
# If output to file, open the file and write output to it
if out_file_name:
filename = argv[2]
f = open(''.join([out_file_name]),'w')
out = ' '.join([out,out_file_name])
f.writelines(out)
f.close()
else:
print out
#generate some stderr
print >> stderr, 'I am stderr'
# Write the fixed file
f = open('/tmp/fixed.txt','w')
f.writelines(['I am fixed file'])
f.close()
"""
class CLAppTester(CommandLineApplication):
_parameters = {
'-F':ValuedParameter(Prefix='-',Name='F',Delimiter=' ',\
Value=None, Quote="\""),\
'--duh':FlagParameter(Prefix='--',Name='duh')}
_command = '/tmp/CLAppTester.py'
_synonyms = {'File':'-F','file':'-F'}
_working_dir = '/tmp'
def _get_result_paths(self,data):
if self.Parameters['-F'].isOn():
param_path = ''.join([self.WorkingDir,self.Parameters['-F'].Value])
else:
param_path = None
result = {}
result['fixed_file'] = ResultPath(Path='/tmp/fixed.txt')
result['parameterized_file'] = ResultPath(Path=param_path,\
IsWritten=self.Parameters['-F'].isOn())
result['base_dep_1'] = ResultPath(Path=self._build_name(suffix='.1'))
result['base_dep_2'] = ResultPath(Path=self._build_name(suffix='.2'))
return result
def _build_name(self,suffix):
return '/tmp/BASE' + suffix
def getHelp(self):
return """Duh"""
class CLAppTester_no_working_dir(CLAppTester):
_working_dir = None
class CLAppTester_reject_exit_status(CLAppTester):
def _accept_exit_status(self,exit_status):
return False
class CLAppTester_bad_fixed_file(CLAppTester):
def _get_result_paths(self,data):
if self.Parameters['-F'].isOn():
param_path = ''.join([self.WorkingDir,self.Parameters['-F'].Value])
else:
param_path = None
result = {}
result['fixed_file'] = ResultPath(Path='/tmp/fixed.txt')
result['fixed_file_bad'] = ResultPath(Path='/tmp/i_dont_exist.txt')
result['parameterized_file'] = ResultPath(Path=param_path,\
IsWritten=self.Parameters['-F'].isOn())
result['base_dep_1'] = ResultPath(Path=self._build_name(suffix='.1'))
result['base_dep_2'] = ResultPath(Path=self._build_name(suffix='.2'))
return result
class CLAppTester_bad_fixed_file_w_handler(CLAppTester_bad_fixed_file):
def _handle_app_result_build_failure(self,out,err,exit_status,result_paths):
return "Called self._handle_app_result_build_failure"
class CLAppTester_space_in_command(CLAppTester):
_command = '"/tmp/CLApp Tester.py"'
class ParameterCombinationsApp(CommandLineApplication):
"""ParameterCombinations mock application to wrap"""
_command = 'testcmd'
_parameters = {'-flag1':FlagParameter(Prefix='-',Name='flag1'),
'-flag2':FlagParameter(Prefix='-',Name='flag2'),
'--value1':ValuedParameter(Prefix='--',Name='value1'),
'-value2':ValuedParameter(Prefix='-',Name='value2'),
'-mix1':MixedParameter(Prefix='-',Name='mix1'),
'-mix2':MixedParameter(Prefix='-',Name='mix2'),
'-delim':ValuedParameter(Prefix='-',Name='delim',
Delimiter='aaa'),
'-default':ValuedParameter(Prefix='-',Name='default',
Value=42, Delimiter='='),
'-input':ValuedParameter(Prefix='-',Name='input',\
Delimiter='='),
'-output':ValuedParameter(Prefix='-',Name='output',
Delimiter='=')}
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_app/test_vienna_package.py 000644 000765 000024 00000054115 12024702176 023574 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from os import getcwd, remove, rmdir
import tempfile, shutil
from cogent.util.unit_test import TestCase, main
from cogent.app.vienna_package import RNAfold, RNAsubopt, RNAplot,\
plot_from_seq_and_struct, DataError, get_constrained_fold, \
get_secondary_structure
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Rob Knight", "Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Development"
class RNAfoldTests(TestCase):
"""Tests for the RNAfold application controller"""
def setUp(self):
self.unnamed_seq = ['AUAGCUAGCUAUGCGCUAGC','ACGGCUAUAGCUAGCGA',\
'gcuagcuauuauauaua']
self.named_seq = ['>namedseq1','AUAGCUAGCUAUGCGCUAGC','>namedseq2',\
'ACGGCUAUAGCUAGCGA']
self.mixed_seq = ['>namedseq1','AUAGCUAGCUAUGCGCUAGC',
'ACGGCUAUAGCUAGCGA','gcuagcuauuauauaua']
self.mixed_seq2 = ['>namedseq2','AUAGCUAGCUAUGCGCUAGC',
'ACGGCUAUAGCUAGCGA','gcuagcuauuauauaua']
self.temp_dir = '/tmp/test_rnafold'
def test_base_command(self):
"""RNAfold: BaseCommand should be ok for different parameter settings"""
r = RNAfold()
working_dir = getcwd()
obs = r.BaseCommand.split()
exp = ['cd','"%s/";' % getcwd(),'RNAfold','-d1','-T','37','-S','1.07']
self.assertEqualItems(obs, exp)
r.Parameters['-noLP'].on()
obs = r.BaseCommand.split()
exp = ['cd','"%s/";' % getcwd(),'RNAfold','-d1','-noLP','-T','37',\
'-S','1.07']
self.assertEqualItems(obs, exp)
r.Parameters['Temp'].on(15)
obs = r.BaseCommand.split()
exp = ['cd','"%s/";' % getcwd(),'RNAfold','-d1','-noLP','-T','15', \
'-S','1.07']
self.assertEqualItems(obs, exp)
r.Parameters['-d'].off()
obs = r.BaseCommand.split()
exp = ['cd','"%s/";' % getcwd(),'RNAfold','-noLP','-T','15','-S','1.07']
self.assertEqualItems(obs, exp)
def test_changing_working_dir(self):
"""RNAfold: BaseCommand should be ok after changing the working dir"""
#changing in initialization
temp_dir = tempfile.mkdtemp()
r = RNAfold(WorkingDir=temp_dir)
self.assertEqual(r.BaseCommand,\
'cd "%s/"; RNAfold -d1 -T 37 -S 1.07'%(temp_dir))
#changing afterwards
r = RNAfold()
r.WorkingDir = temp_dir
self.assertEqual(r.BaseCommand,\
'cd "%s/"; RNAfold -d1 -T 37 -S 1.07'%(temp_dir))
rmdir(temp_dir)
def test_stdout(self):
"""RNAfold: StdOut should be as expected"""
r = RNAfold()
exp = '\n'.join(['>namedseq1','AUAGCUAGCUAUGCGCUAGC',\
'...((((((.....)))))) ( -8.30)','ACGGCUAUAGCUAGCGA',\
'...((((....)))).. ( -3.20)','GCUAGCUAUUAUAUAUA',\
'................. ( 0.00)'])+'\n'
res = r(self.mixed_seq)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_stdout_input_as_path(self):
"""RNAfold: StdOut with input_as_path"""
r = RNAfold(InputHandler='_input_as_path')
f = open('/tmp/rnatestfile','w')
f.write('\n'.join(self.mixed_seq2))
f.close()
exp = '\n'.join(['>namedseq2','AUAGCUAGCUAUGCGCUAGC',\
'...((((((.....)))))) ( -8.30)','ACGGCUAUAGCUAGCGA',\
'...((((....)))).. ( -3.20)','GCUAGCUAUUAUAUAUA',\
'................. ( 0.00)'])+'\n'
res = r('/tmp/rnatestfile')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('/tmp/rnatestfile')
def test_stdout_input_as_path_space(self):
"""RNAfold: StdOut with input_as_path and space in filename"""
r = RNAfold(InputHandler='_input_as_path')
f = open('/tmp/rna test file','w')
f.write('\n'.join(self.mixed_seq2))
f.close()
exp = '\n'.join(['>namedseq2','AUAGCUAGCUAUGCGCUAGC',\
'...((((((.....)))))) ( -8.30)','ACGGCUAUAGCUAGCGA',\
'...((((....)))).. ( -3.20)','GCUAGCUAUUAUAUAUA',\
'................. ( 0.00)'])+'\n'
res = r('/tmp/rna test file')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('/tmp/rna test file')
def test_get_result_paths_unnamed_seq(self):
"""RNAfold: _get_result_paths() should work on unnamed seq"""
r = RNAfold()
res = r(self.unnamed_seq)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS','DP'])
self.failUnless(res['DP'] is None)
self.failUnless(res['SS'] is not None)
self.failUnless(res['StdOut'] is not None)
self.failUnless(res['StdErr'] is None)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
def test_get_result_paths_named_seq(self):
"""RNAfold: _get_result_paths() should work on named seq"""
r = RNAfold()
res = r(self.named_seq)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS','DP','namedseq1_ss',\
'namedseq2_ss','namedseq1_dp','namedseq2_dp'])
res.cleanUp()
def test_get_result_paths_mixed_seq(self):
"""RNAfold: _get_result_paths() should work on partly named seq"""
r = RNAfold()
res = r(self.mixed_seq)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS','DP','namedseq1_ss',\
'namedseq1_dp'])
res.cleanUp()
def test_get_result_paths_parameter(self):
"""RNAfold: _get_result_paths() should work with diff parameters"""
r = RNAfold()
r.Parameters['-p'].on()
res = r(self.unnamed_seq)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS','DP'])
self.failUnless(res['DP'] is not None)
self.failUnless(res['SS'] is not None)
self.failUnless(res['StdOut'] is not None)
self.failUnless(res['StdErr'] is None)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
def test_get_result_paths_working_dir(self):
"""RNAfold: _get_result_paths() should work with diff working dir"""
r = RNAfold(WorkingDir=self.temp_dir)
res = r(self.unnamed_seq)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS','DP'])
self.failUnless(res['DP'] is None)
self.failUnless(res['SS'] is not None)
self.failUnless(isinstance(res['SS'],file))
self.failUnless(res['StdOut'] is not None)
self.failUnless(res['StdErr'] is None)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
def test_get_constrained_fold_bad_data(self):
"""get_constrained_fold should handle bad data."""
test_seq = 'AAACCCGGGUUU'
constraint = '(((...)))'
#Test empty sequence.
self.assertRaises(ValueError, get_constrained_fold,\
'', constraint)
#Test empty constraint string.
self.assertRaises(ValueError, get_constrained_fold,\
test_seq, '')
#Test different length sequence and constraint.
self.assertRaises(ValueError, get_constrained_fold,\
test_seq, constraint)
def test_get_constrained_fold(self):
"""get_constrained_fold should give correct result."""
test_seq = 'AAACCCGGGUUU'
constraint = '(((......)))'
expected_struct = '((((....))))'
obs_seq, obs_struct, obs_energy = \
get_constrained_fold(test_seq,constraint)
#Test get back correct seq and struct
self.assertEqual(obs_seq, test_seq)
self.assertEqual(obs_struct, expected_struct)
def test_get_secondary_structure(self):
"""get_secondary_structure should give correct result."""
test_seq = 'AAACCCGGGUUU'
expected_struct = '((((....))))'
expected_energy = -0.80
obs_seq, obs_struct, obs_energy = \
get_secondary_structure(test_seq)
#Test get back correct seq and struct
self.assertEqual(obs_seq, test_seq)
self.assertEqual(obs_struct, expected_struct)
self.assertEqual(obs_energy, expected_energy)
def test_zzz_general_cleanup(self):
"""Executed last, clean up temp_dir"""
shutil.rmtree(self.temp_dir)
class RNAsuboptTests(TestCase):
"""Tests for the RNAsubopt application controller"""
def test_base_command(self):
"""RNAsubopt: BaseCommand should be ok for different parameter settings
"""
r = RNAsubopt()
obs = r.BaseCommand.split()
exp = ['cd','"%s/";' % getcwd(),'RNAsubopt','-e','1','-d2','-T','37']
self.assertEqualItems(obs, exp)
r.Parameters['-nsp'].on('GA')
obs = r.BaseCommand.split()
exp = ['cd','"%s/";' % getcwd(),'RNAsubopt','-e','1','-d2','-nsp','GA',\
'-T','37']
self.assertEqualItems(obs, exp)
r.Parameters['Temp'].on(15)
obs = r.BaseCommand.split()
exp = ['cd','"%s/";' % getcwd(),'RNAsubopt','-e','1','-d2','-nsp','GA',\
'-T','15']
self.assertEqualItems(obs, exp)
r.Parameters['-d'].off()
obs = r.BaseCommand.split()
exp = ['cd','"%s/";' % getcwd(),'RNAsubopt','-e','1','-nsp','GA','-T',\
'15']
self.assertEqualItems(obs, exp)
def test_changing_working_dir(self):
"""RNAsubopt: BaseCommand should be ok after changing the working dir
"""
temp_dir = tempfile.mkdtemp()
#changing in initialization
r = RNAsubopt(WorkingDir=temp_dir)
self.assertEqual(r.BaseCommand,\
'cd "%s/"; RNAsubopt -e 1 -d2 -T 37'%(temp_dir))
#changing afterwards
r = RNAsubopt()
r.WorkingDir = temp_dir
self.assertEqual(r.BaseCommand,\
'cd "%s/"; RNAsubopt -e 1 -d2 -T 37'%(temp_dir))
rmdir(temp_dir)
def test_stdout(self):
"""RNAsubopt: StdOut should be as expected"""
r = RNAsubopt()
seq = ['AUAGCUAGCUAUGCGCUAGCGGAUUAGCUAGCUAGCGA',\
'ucgaucgaucagcuagcuauuauauaua']
exp = '\n'.join(
['AUAGCUAGCUAUGCGCUAGCGGAUUAGCUAGCUAGCGA -1720 100',
'.(((((((((.(((....)))....))))))))).... -16.20',
'.(((((((((((.((....)).)).))))))))).... -17.20',
'.((((((((((..((....))...)))))))))).... -16.60',
'.((((((((((.((....))....)))))))))).... -16.40',
'.(((((((((((((....)))...)))))))))).... -16.90',
'.(((((((((((.((....)).).)))))))))).... -17.20',
'UCGAUCGAUCAGCUAGCUAUUAUAUAUA 0 100',
'......(((.((....)))))....... 0.70',
'..........((....)).......... 0.60',
'..((....)).................. 0.90',
'............................ 0.00']) + '\n'
res = r(seq)
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
def test_stdout_input_as_path_space(self):
"""RNAsubopt: StdOut with input_as_path and space in filename"""
mixed_seq2 = ['>namedseq2','AUAGCUAGCUAUGCGCUAGC',
'ACGGCUAUAGCUAGCGA','gcuagcuauuauauaua']
r = RNAsubopt(InputHandler='_input_as_path')
f = open('/tmp/rna test file','w')
f.write('\n'.join(mixed_seq2))
f.close()
exp = '\n'.join(['> namedseq2 [100]',
'AUAGCUAGCUAUGCGCUAGC -830 100',
'...((((((.....)))))) -8.30',
'ACGGCUAUAGCUAGCGA -320 100',
'...(((......))).. -2.30',
'...((((....)))).. -3.20',
'GCUAGCUAUUAUAUAUA 0 100',
'................. 0.00'])+'\n'
res = r('/tmp/rna test file')
obs = res['StdOut'].read()
self.assertEqual(obs,exp)
res.cleanUp()
remove('/tmp/rna test file')
def test_get_result_paths(self):
"""RNAsubopt: _get_result_paths() should create the right dict entries
"""
r = RNAsubopt()
seq = ['AUAGCUAGCUAUGCGCUAGCGGAUUAGCUAGCUAGCGA',\
'ucgaucgaucagcuagcuauuauauaua']
res = r(seq)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus'])
self.failUnless(res['StdOut'] is not None)
self.failUnless(res['StdErr'] is None)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
r = RNAsubopt({'-s':None,'-lodos':None,'-d':3,'-logML':None,\
'-noLP':None,'-4':None,'-noGU':None,'-noCloseGU':None})
res = r(seq)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus'])
self.failUnless(res['StdOut'] is not None)
self.failUnless(res['StdErr'] is None)
#self.assertEqual(res['ExitStatus'],0) #platform-dependent?
res.cleanUp()
class RNAplotTests(TestCase):
"""Tests for the RNAplot application controller"""
def setUp(self):
self.unnamed_seqs = ['AUAGCUAGCUAUGCGCUAGC','...((((((.....))))))',\
'ACGGCUAUAGCUAGCGA','...((((....))))..',\
'gcuagcuauuauauaua','.................']
self.named_seqs = \
['>namedseq1','AUAGCUAGCUAUGCGCUAGC','...((((((.....))))))',\
'>namedseq2','ACGGCUAUAGCUAGCGA','...((((....))))..']
self.mixed_seqs = \
['>namedseq1','AUAGCUAGCUAUGCGCUAGC','...((((((.....))))))',\
'ACGGCUAUAGCUAGCGA','...((((....))))..',\
'gcuagcuauuauauaua','.................']
self.named_seq = \
['>namedseq','AUAGCUAGCUAUGCGCUAGC','...((((((.....))))))']
self.standard_name = 'namedseq'
self.standard_seq = 'AUAGCUAGCUAUGCGCUAGC'
self.standard_struct = '...((((((.....))))))'
self.bad_pairing_struct = '...((((((.....)))...'
self.bad_chars_struct = '...((((((.....)xx)))'
self.short_struct = '...((((((..))))))'
self.temp_dir = '/tmp/test_rnaplot'
def test_base_command(self):
"""RNAplot: BaseCommand should be ok for different parameter settings"""
r = RNAplot()
working_dir = getcwd()
self.assertEqual(r.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','RNAplot']))
r.Parameters['-t'].on(0)
self.assertEqual(r.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','RNAplot -t 0']))
r.Parameters['-o'].on('svg')
self.assertEqual(r.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','RNAplot -t 0 -o svg']))
r.Parameters['-t'].off()
self.assertEqual(r.BaseCommand,\
''.join(['cd "',getcwd(),'/"; ','RNAplot -o svg']))
def test_changing_working_dir(self):
"""RNAplot: BaseCommand should be ok after changing the working dir"""
#changing in initialization
temp_dir = tempfile.mkdtemp()
r = RNAplot(WorkingDir=temp_dir)
self.assertEqual(r.BaseCommand,\
'cd "%s/"; RNAplot'%(temp_dir))
#changing afterwards
r = RNAplot()
r.WorkingDir = temp_dir
self.assertEqual(r.BaseCommand,\
'cd "%s/"; RNAplot'%(temp_dir))
rmdir(temp_dir)
def test_get_result_paths_unnamed_seq(self):
"""RNAplot: _get_result_paths() should work on unnamed seq"""
r = RNAplot()
res = r(self.unnamed_seqs)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS'])
self.failUnless(res['SS'] is not None)
self.failUnless(res['StdOut'] is not None)
self.failUnless(res['StdErr'] is None)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
def test_get_result_paths_named_seq(self):
"""RNAplot: _get_result_paths() should work on named seq"""
r = RNAplot()
res = r(self.named_seqs)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','namedseq1_ss',\
'namedseq2_ss'])
res.cleanUp()
def test_get_result_paths_mixed_seq(self):
"""RNAplot: _get_result_paths() should work on partly named seq"""
r = RNAplot()
res = r(self.mixed_seqs)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS','namedseq1_ss'])
res.cleanUp()
def test_get_result_paths_parameter(self):
"""RNAplot: _get_result_paths() should work with diff parameters"""
r = RNAplot()
r.Parameters['-t'].on(0)
res = r(self.unnamed_seqs)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS'])
self.failUnless(res['SS'] is not None)
self.failUnless(res['StdOut'] is not None)
self.failUnless(res['StdErr'] is None)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
def test_get_result_paths_working_dir(self):
"""RNAplot: _get_result_paths() should work with diff working dir"""
r = RNAplot(WorkingDir=self.temp_dir)
res = r(self.unnamed_seqs)
self.assertEqualItems(res.keys(),\
['StdOut','StdErr','ExitStatus','SS'])
self.failUnless(res['SS'] is not None)
self.failUnless(isinstance(res['SS'],file))
self.failUnless(res['StdOut'] is not None)
self.failUnless(res['StdErr'] is None)
self.assertEqual(res['ExitStatus'],0)
res.cleanUp()
def test_rnaplot_output(self):
"""RNAplot: calling RNAplot on data should give correct result."""
r = RNAplot(WorkingDir=self.temp_dir)
res = r(self.named_seq)
ps_plot = res['namedseq_ss'].read()
observed_lines = ps_plot.split('\n')
expected_lines = RNAPLOT_RES.split('\n')
#First 8 lines depend on the runtime. Check after.
self.assertEqual(observed_lines[8:],expected_lines[8:])
res.cleanUp()
def test_plot_from_seq_and_struct_bad_data(self):
"""plot_from_seq_and_struct helper function should handle bad data.
"""
#Check bad Vienna Structure pairing
self.assertRaises(IndexError, plot_from_seq_and_struct,\
self.standard_seq, self.bad_pairing_struct)
#Check bad characters in Vienna Structure
self.assertRaises(ValueError, plot_from_seq_and_struct,\
self.standard_seq, self.bad_chars_struct)
#Check different lengths of seq and struct
self.assertRaises(DataError, plot_from_seq_and_struct,\
self.standard_seq, self.short_struct)
def test_plot_from_seq_and_struct(self):
"""plot_from_seq_and_struct helper function should give correct result.
"""
ps_plot = plot_from_seq_and_struct(self.standard_seq,\
self.standard_struct, seqname=self.standard_name)
observed_lines = ps_plot.split('\n')
expected_lines = RNAPLOT_RES.split('\n')
#First 8 lines depend on the runtime. Check after.
self.assertEqual(observed_lines[8:],expected_lines[8:])
def test_zzz_general_cleanup(self):
"""Executed last, clean up temp_dir"""
shutil.rmtree(self.temp_dir)
RNAPLOT_RES = """%!PS-Adobe-3.0 EPSF-3.0
%%Creator: PS_dot.c,v 1.38 2007/02/02 15:18:13 ivo Exp $, ViennaRNA-1.7.1
%%CreationDate: Tue Oct 21 15:44:50 2008
%%Title: RNA Secondary Structure Plot
%%BoundingBox: 66 210 518 662
%%DocumentFonts: Helvetica
%%Pages: 1
%%EndComments
%Options:
% to switch off outline pairs of sequence comment or
% delete the appropriate line near the end of the file
%%BeginProlog
/RNAplot 100 dict def
RNAplot begin
/fsize 14 def
/outlinecolor {0.2 setgray} bind def
/paircolor {0.2 setgray} bind def
/seqcolor {0 setgray} bind def
/cshow { dup stringwidth pop -2 div fsize -3 div rmoveto show} bind def
/min { 2 copy gt { exch } if pop } bind def
/max { 2 copy lt { exch } if pop } bind def
/drawoutline {
gsave outlinecolor newpath
coor 0 get aload pop 0.8 0 360 arc % draw 5' circle of 1st sequence
currentdict /cutpoint known % check if cutpoint is defined
{coor 0 cutpoint getinterval
{aload pop lineto} forall % draw outline of 1st sequence
coor cutpoint 1 add get aload pop
2 copy moveto 0.8 0 360 arc % draw 5' circle of 2nd sequence
coor cutpoint 1 add coor length cutpoint 1 add sub getinterval
{aload pop lineto} forall} % draw outline of 2nd sequence
{coor {aload pop lineto} forall} % draw outline as a whole
ifelse
stroke grestore
} bind def
/drawpairs {
paircolor
0.7 setlinewidth
[9 3.01] 9 setdash
newpath
pairs {aload pop
coor exch 1 sub get aload pop moveto
coor exch 1 sub get aload pop lineto
} forall
stroke
} bind def
% draw bases
/drawbases {
[] 0 setdash
seqcolor
0
coor {
aload pop moveto
dup sequence exch 1 getinterval cshow
1 add
} forall
pop
} bind def
/init {
/Helvetica findfont fsize scalefont setfont
1 setlinejoin
1 setlinecap
0.8 setlinewidth
72 216 translate
% find the coordinate range
/xmax -1000 def /xmin 10000 def
/ymax -1000 def /ymin 10000 def
coor {
aload pop
dup ymin lt {dup /ymin exch def} if
dup ymax gt {/ymax exch def} {pop} ifelse
dup xmin lt {dup /xmin exch def} if
dup xmax gt {/xmax exch def} {pop} ifelse
} forall
/size {xmax xmin sub ymax ymin sub max} bind def
72 6 mul size div dup scale
size xmin sub xmax sub 2 div size ymin sub ymax sub 2 div
translate
} bind def
end
%%EndProlog
RNAplot begin
% data start here
/sequence (\\
AUAGCUAGCUAUGCGCUAGC\\
) def
/coor [
[100.992 114.290]
[88.210 108.134]
[86.994 93.999]
[98.538 85.751]
[105.046 72.236]
[111.554 58.722]
[118.062 45.207]
[124.571 31.693]
[131.079 18.178]
[127.159 2.622]
[136.992 -10.055]
[153.034 -10.127]
[162.981 2.461]
[159.200 18.052]
[144.593 24.686]
[138.085 38.201]
[131.577 51.716]
[125.069 65.230]
[118.560 78.745]
[112.052 92.259]
] def
/pairs [
[4 20]
[5 19]
[6 18]
[7 17]
[8 16]
[9 15]
] def
init
% switch off outline pairs or bases by removing these lines
drawoutline
drawpairs
drawbases
% show it
showpage
end
%%EOF
"""
if __name__ == '__main__':
main()
PyCogent-1.5.3/tests/test_align/__init__.py 000644 000765 000024 00000000554 12024702176 021651 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_algorithm', 'test_align', 'test_weights']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann", "Peter Maxwell", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Production"
PyCogent-1.5.3/tests/test_align/test_algorithm.py 000644 000765 000024 00000030045 12024702176 023135 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from __future__ import division
from cogent.util.unit_test import TestCase, main
from cogent.align.algorithm import ScoreCell, MatchScorer, equality_scorer,\
default_gap, default_gap_symbol, ScoreMatrix, NeedlemanWunschMatrix, \
SmithWatermanMatrix, nw_align, sw_align
from copy import copy, deepcopy
__author__ = "Jeremy Widmann"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Jeremy Widmann", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Jeremy Widmann"
__email__ = "jeremy.widmann@colorado.edu"
__status__ = "Production"
"""Tests of the cogent.align.algorithm module.
"""
class ScoreCellTests(TestCase):
"""Tests for ScoreCell class.
"""
def setUp(self):
"""Setup for ScoreCell tests."""
self.score_cell = ScoreCell()
def test_init(self):
"""Tests for ScoreCell __init__ function."""
#Test for empty score cell
self.assertEqual(self.score_cell.Score,0)
self.assertEqual(self.score_cell.Pointer,None)
def test_update(self):
"""Tests for ScoreCell update function."""
#Test tie up wins
self.score_cell.update(1,1,1)
self.assertEqual(self.score_cell.Score,1)
self.assertEqual(self.score_cell.Pointer,"up")
#Test tie diag wins
self.score_cell.update(3,1,3)
self.assertEqual(self.score_cell.Score,3)
self.assertEqual(self.score_cell.Pointer,"diag")
#Test up
self.score_cell.update(1,1,1)
self.assertEqual(self.score_cell.Score,1)
self.assertEqual(self.score_cell.Pointer,"up")
#Test diag
self.score_cell.update(3,1,2)
self.assertEqual(self.score_cell.Score,3)
self.assertEqual(self.score_cell.Pointer,"diag")
#Test left
self.score_cell.update(1,2,3)
self.assertEqual(self.score_cell.Score,3)
self.assertEqual(self.score_cell.Pointer,"left")
class MatchScorerTests(TestCase):
"""Tests for MatchScorer function.
"""
def setUp(self):
"""Setup for MatchScorer tests."""
self.equality_scorer = MatchScorer(1,-1)
self.mismatch_worse_scorer = MatchScorer(1,-2)
self.match_worse_scorer = MatchScorer(-1,1)
def test_scorer(self):
"""Tests for MatchScorer function."""
#Test equality_scorer
self.assertEqual(self.equality_scorer('A','A'),1)
self.assertEqual(self.equality_scorer('A','B'),-1)
#Test mismatch_worse_scorer
self.assertEqual(self.mismatch_worse_scorer('A','A'),1)
self.assertEqual(self.mismatch_worse_scorer('A','B'),-2)
#Test match_worse_scorer
self.assertEqual(self.match_worse_scorer('A','A'),-1)
self.assertEqual(self.match_worse_scorer('A','B'),1)
class ScoreMatrixTests(TestCase):
"""Tests for ScoreCell class.
"""
def setUp(self):
"""Setup for ScoreMatrix tests."""
self.score_matrix = ScoreMatrix('AACGU','ACAGU')
def fill():
pass
def traceback():
pass
self.score_matrix.fill = fill
self.score_matrix.traceback = traceback
self.empty_score_matrix = ScoreMatrix('','')
def test_init(self):
"""Tests for ScoreMatrix __init__ function."""
#Test empty ScoreMatrix
self.empty_score_matrix = ScoreMatrix('','')
self.assertEqual(self.empty_score_matrix.First,'')
self.assertEqual(self.empty_score_matrix.Second,'')
self.assertEqual(self.empty_score_matrix.Cols,1)
self.assertEqual(self.empty_score_matrix.Rows,1)
self.assertEqual(self.empty_score_matrix.GapScore,-1)
self.assertEqual(self.empty_score_matrix.GapSymbol,'-')
self.assertEqual(self.empty_score_matrix.FirstAlign,[])
self.assertEqual(self.empty_score_matrix.SecondAlign,[])
def test_str(self):
"""Tests for ScoreMatrix __str__ function."""
#Test empty ScoreMatrix
self.assertEqual(self.empty_score_matrix.__str__(),"Empty Score Matrix")
#Test full ScoreMatrix
self.assertEqual(self.score_matrix.__str__(),\
"""\t\tA\tA\tC\tG\tU\n\t0\t0\t0\t0\t0\t0\nA\t0\t0\t0\t0\t0\t0\nC\t0\t0\t0\t0\t0\t0\nA\t0\t0\t0\t0\t0\t0\nG\t0\t0\t0\t0\t0\t0\nU\t0\t0\t0\t0\t0\t0""")
def test_alignment(self):
"""Tests for ScoreMatrix alignment function."""
#Should not align since ScoreMatrix base object does not have fill()
#or traceback() methods. For testing purposes fill() and traceback()
#for self.score_matrix do nothing.
self.assertEqual(self.score_matrix.alignment(),('',''))
class NeedlemanWunschMatrixTests(TestCase):
"""Tests for NeedlemanWunschMatrix class.
"""
def setUp(self):
"""Setup for NeedlemanWunschMatrix tests."""
self.nw_matrix = NeedlemanWunschMatrix('ACGU','CAGU')
#Since _init_first_row, _init_first_col and _init_first_cell are
#automatically called when NeedlemanWunschMatrix is initialized,
#need to change all elements in nw_matrix_empty to 0 to test
#that each _init works.
self.nw_matrix_empty = \
NeedlemanWunschMatrix('ACGU','CAGU')
for i in range(len(self.nw_matrix_empty)):
for j in range(len(self.nw_matrix_empty[i])):
self.nw_matrix_empty[i][j]=ScoreCell(0)
def test_init_first_row(self):
"""Tests for NeedlemanWunschMatrix _init_first_row function."""
nw_matrix_empty = copy(self.nw_matrix_empty)
#Init first row
nw_matrix_empty._init_first_row()
#matrix after first row init
matrix_scores_first_row_init = [[0,-1,-2,-3,-4],
[0,0,0,0,0],
[0,0,0,0,0],
[0,0,0,0,0],
[0,0,0,0,0]]
for i in range(len(nw_matrix_empty)):
for j in range(len(nw_matrix_empty[i])):
self.assertEqual(nw_matrix_empty[i][j].Score,\
matrix_scores_first_row_init[i][j])
def test_init_first_col(self):
"""Tests for NeedlemanWunschMatrix _init_first_col function."""
nw_matrix_empty = copy(self.nw_matrix_empty)
#Init first row
nw_matrix_empty._init_first_col()
#matrix after first row init
matrix_scores_first_row_init = [[0,0,0,0,0],
[-1,0,0,0,0],
[-2,0,0,0,0],
[-3,0,0,0,0],
[-4,0,0,0,0]]
for i in range(len(nw_matrix_empty)):
for j in range(len(nw_matrix_empty[i])):
self.assertEqual(nw_matrix_empty[i][j].Score,\
matrix_scores_first_row_init[i][j])
def test_init_first_cell(self):
"""Tests for NeedlemanWunschMatrix _init_first_cell function."""
nw_matrix_empty = copy(self.nw_matrix_empty)
#Init first row
nw_matrix_empty._init_first_cell()
self.assertEqual(nw_matrix_empty[0][0].Score,0)
def test_initialized_matrix(self):
"""Tests for NeedlemanWunschMatrix after full initialization."""
matrix_scores_first_row_init = [[0,-1,-2,-3,-4],
[-1,0,0,0,0],
[-2,0,0,0,0],
[-3,0,0,0,0],
[-4,0,0,0,0]]
for i in range(len(self.nw_matrix)):
for j in range(len(self.nw_matrix[i])):
self.assertEqual(self.nw_matrix[i][j].Score,\
matrix_scores_first_row_init[i][j])
def test_fill(self):
"""Tests for NeedlemanWunschMatrix fill function."""
filled_nw_matrix = copy(self.nw_matrix)
filled_nw_matrix.fill()
matrix_scores_filled = [[0,-1,-2,-3,-4],
[-1,-1,0,-1,-2],
[-2,0,-1,-1,-2],
[-3,-1,-1,0,-1],
[-4,-2,-2,-1,1]]
matrix_pointers_filled = [[None,'left','left','left','left'],
['up','diag','diag','left','left'],
['up','diag','up','diag','diag'],
['up','up','diag','diag','left'],
['up','up','up','up','diag']]
self.assertEqual(filled_nw_matrix.Filled,True)
for i in range(len(filled_nw_matrix)):
for j in range(len(filled_nw_matrix[i])):
self.assertEqual(filled_nw_matrix[i][j].Score,\
matrix_scores_filled[i][j])
self.assertEqual(filled_nw_matrix[i][j].Pointer,\
matrix_pointers_filled[i][j])
self.assertEqual(filled_nw_matrix.MaxScore,(1,4,4))
def test_traceback(self):
"""Tests for NeedlemanWunschMatrix traceback function."""
self.nw_matrix.traceback()
self.assertEqual(self.nw_matrix.FirstAlign,['A','C','-','G','U'])
self.assertEqual(self.nw_matrix.SecondAlign,['-','C','A','G','U'])
class SmithWatermanMatrixTests(TestCase):
"""Tests for SmithWatermanMatrix class.
"""
def setUp(self):
"""Setup for SmithWatermanMatrix tests."""
self.sw_matrix = SmithWatermanMatrix('ACGU','CAGU')
def test_fill(self):
"""Tests for SmithWatermanMatrix fill function."""
filled_sw_matrix = copy(self.sw_matrix)
filled_sw_matrix.fill()
matrix_scores_filled = [[0,0,0,0,0],
[0,0,1,0,0],
[0,1,0,0,0],
[0,0,0,1,0],
[0,0,0,0,2]]
matrix_pointers_filled = [[None,None,None,None,None],
[None,None,'diag',None,None],
[None,'diag',None,None,None],
[None,None,None,'diag',None],
[None,None,None,None,'diag']]
for i in range(len(filled_sw_matrix)):
for j in range(len(filled_sw_matrix[i])):
self.assertEqual(filled_sw_matrix[i][j].Score,\
matrix_scores_filled[i][j])
self.assertEqual(filled_sw_matrix[i][j].Pointer,\
matrix_pointers_filled[i][j])
self.assertEqual(filled_sw_matrix.MaxScore,(2,4,4))
def test_traceback(self):
"""Tests for SmithWatermanMatrix traceback function."""
self.sw_matrix.fill()
self.sw_matrix.traceback()
self.assertEqual(self.sw_matrix.FirstAlign,['G','U'])
self.assertEqual(self.sw_matrix.SecondAlign,['G','U'])
class NwAlignTests(TestCase):
"""Tests for nw_align fuction.
"""
def test_nw_align_empty(self):
"""Tests for nw_align function."""
(first,second),score = nw_align('','',return_score=True)
self.assertEqual(first,'')
self.assertEqual(second,'')
self.assertEqual(score,0)
def test_nw_align(self):
"""Tests for nw_align function."""
(first,second),score = nw_align('ACGU','CAGU',return_score=True)
self.assertEqual(first,'AC-GU')
self.assertEqual(second,'-CAGU')
self.assertEqual(score,1)
class SwAlignTests(TestCase):
"""Tests for sw_align function.
"""
def test_sw_align_empty(self):
"""Tests for sw_align function."""
(first,second),score = sw_align('','',return_score=True)
self.assertEqual(first,'')
self.assertEqual(second,'')
self.assertEqual(score,0)
def test_sw_align(self):
"""Tests for sw_align function."""
(first,second),score = sw_align('ACGU','CAGU',return_score=True)
self.assertEqual(first,'GU')
self.assertEqual(second,'GU')
self.assertEqual(score,2)
#run if called from command-line
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_align/test_align.py 000644 000765 000024 00000022026 12024702176 022241 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent import DNA, LoadSeqs
from cogent.align.align import classic_align_pairwise, make_dna_scoring_dict,\
local_pairwise, global_pairwise
from cogent.evolve.models import HKY85
import cogent.evolve.substitution_model
dna_model = cogent.evolve.substitution_model.Nucleotide(
model_gaps=False, equal_motif_probs=True)
import cogent.align.progressive
import unittest
__author__ = "Peter Maxwell"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Peter Maxwell", "Gavin Huttley", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
def matchedColumns(align):
"""Count the matched columns in an alignment"""
def all_same(column):
consensus = None
for motif in column:
if consensus is None:
consensus = motif
elif motif != consensus:
return False
return True
return len(align.filtered(all_same))
seq1 = DNA.makeSequence('aaaccggacattacgtgcgta', Name='FAKE01')
seq2 = DNA.makeSequence( 'ccggtcaggttacgtacgtt', Name= 'FAKE02')
class AlignmentTestCase(unittest.TestCase):
def _aligned_both_ways(self, seq1, seq2, **kw):
S = make_dna_scoring_dict(10, -1, -8)
a1 = classic_align_pairwise(seq1, seq2, S, 10, 2, **kw)
a2 = classic_align_pairwise(seq2, seq1, S, 10, 2, **kw)
return [a1, a2]
def test_local(self):
for a in self._aligned_both_ways(seq1, seq2, local=True):
self.assertEqual(matchedColumns(a), 15)
self.assertEqual(len(a), 19)
def test_gap_at_one_end(self):
for a in self._aligned_both_ways(seq1, seq2, local=False):
self.assertEqual(matchedColumns(a), 15)
self.assertEqual(len(a), 23)
def test_gaps_at_both_ends(self):
s = 'aaaccggttt'
s1 = DNA.makeSequence(s[:-2], Name="A")
s2 = DNA.makeSequence(s[2:], Name="B")
for a in self._aligned_both_ways(s1, s2, local=False):
self.assertEqual(matchedColumns(a), 6)
self.assertEqual(len(a), 10)
def test_short(self):
s1 = DNA.makeSequence('tacagta', Name="A")
s2 = DNA.makeSequence('tacgtc', Name="B")
for a in self._aligned_both_ways(s1, s2, local=False):
self.assertEqual(matchedColumns(a), 5)
self.assertEqual(len(a), 7)
def test_pairwise_returns_score(self):
"""exercise pairwise local/global returns alignment score"""
S = make_dna_scoring_dict(10, -1, -8)
aln, score = local_pairwise(seq1, seq2, S, 10, 2, return_score=True)
self.assertTrue(score > 100)
aln, score = global_pairwise(seq1, seq2, S, 10, 2, return_score=True)
self.assertTrue(score > 100)
def test_codon(self):
s1 = DNA.makeSequence('tacgccgta', Name="A")
s2 = DNA.makeSequence('tacgta', Name="B")
codon_model = cogent.evolve.substitution_model.Codon(
model_gaps=False, equal_motif_probs=True,
mprob_model='conditional')
tree = cogent.LoadTree(tip_names=['A', 'B'])
lf = codon_model.makeLikelihoodFunction(tree, aligned=False)
lf.setSequences(dict(A=s1, B=s2))
(score, a) = lf.getLogLikelihood().edge.getViterbiScoreAndAlignment()
self.assertEqual(matchedColumns(a), 6)
self.assertEqual(len(a), 9)
def test_local_tiebreak(self):
"""Should pick the first best-equal hit rather than the last one"""
# so that the Pyrex and Python versions give the same result.
score_matrix = make_dna_scoring_dict(match=1, transition=-1,
transversion=-1)
pattern = DNA.makeSequence('cwc', Name='pattern')
two_hit = DNA.makeSequence( 'cactc', Name= 'target')
aln = local_pairwise(pattern, two_hit, score_matrix, 5, 2)
hit = aln.NamedSeqs['target']
self.assertEqual(str(hit).lower(), 'cac')
class UnalignedPairTestCase(unittest.TestCase):
def test_forward(self):
tree = cogent.LoadTree(tip_names='AB')
pc = dna_model.makeLikelihoodFunction(tree, aligned=False)
pc.setSequences({'A':seq1, 'B':seq2})
LnL = pc.getLogLikelihood()
assert isinstance(LnL, float)
class MultipleAlignmentTestCase(unittest.TestCase):
def _make_aln(self, orig, model=dna_model, param_vals=None,
indel_rate=0.1, indel_length=0.5, **kw):
kw['indel_rate'] = indel_rate
kw['indel_length'] = indel_length
seqs = dict((key, DNA.makeSequence(value))
for (key, value) in orig.items())
if len(seqs) == 2:
tree = cogent.LoadTree(tip_names=seqs.keys())
tree = cogent.LoadTree(treestring="(A:.1,B:.1)")
else:
tree = cogent.LoadTree(treestring="(((A:.1,B:.1):.1,C:.1):.1,D:.1)")
aln, tree = cogent.align.progressive.TreeAlign(model, seqs,
tree=tree, param_vals=param_vals, show_progress=False, **kw)
return aln
def _test_aln(self, seqs, model=dna_model, param_vals=None, **kw):
orig = dict((n,s.replace('-', '')) for (n,s) in seqs.items())
aln = self._make_aln(orig, model=model, param_vals=param_vals, **kw)
result = dict((n,s.lower()) for (n,s) in aln.todict().items())
# assert the alignment result is correct
self.assertEqual(seqs, result)
# assert the returned alignment has the correct parameter values in the
# align.Info object.
if param_vals:
for param, val in param_vals:
self.assertEqual(aln.Info.AlignParams[param], val)
def test_progressive1(self):
"""test progressive alignment, gaps in middle"""
self._test_aln({
'A': 'tacagta',
'B': 'tac-gtc',
'C': 'ta---ta',
'D': 'tac-gtc',
})
def test_progressive_est_tree(self):
"""excercise progressive alignment without a guide tree"""
seqs = LoadSeqs(data={'A': "TGTGGCACAAATGCTCATGCCAGCTCTTTACAGCATGAGAACA",
'B': "TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTT",
'C': "TGTGGCACAAGTACTCATGCCAGCTCAGTACAGCATGAGAACAGCAGTTT"}, aligned=False)
aln, tree = cogent.align.progressive.TreeAlign(HKY85(), seqs, show_progress=False,
param_vals={'kappa': 4.0})
expect = {'A': 'TGTGGCACAAATGCTCATGCCAGCTCTTTACAGCATGAGAACA-------',
'C': 'TGTGGCACAAGTACTCATGCCAGCTCAGTACAGCATGAGAACAGCAGTTT',
'B': 'TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTT'}
self.assertEqual(aln.todict(), expect)
def test_progressive_params(self):
"""excercise progressive alignment providing model params"""
self._test_aln({
'A': 'tacagta',
'B': 'tac-gtc',
'C': 'ta---ta',
'D': 'cac-cta',
}, model=HKY85(), param_vals=[('kappa',2.0)])
def test_TreeAlign_does_pairs(self):
"""test TreeAlign handles pairs of sequences"""
self._test_aln({
'A': 'acttgtac',
'B': 'ac--gtac',
})
def test_gap_at_start(self):
"""test progressive alignment, gaps at start"""
self._test_aln({
'A': '-ac',
'B': '-ac',
'C': '-ac',
'D': 'gac',
})
def test_gap_at_end(self):
"""test progressive alignment, gaps at end"""
self._test_aln({
'A': 'gt-',
'B': 'gt-',
'C': 'gt-',
'D': 'gta',
})
def test_gaps2(self):
"""Gaps have real costs, even end gaps"""
self._test_aln({
'A': 'g-',
'B': 'g-',
'C': 'ga',
'D': 'a-',
})
self._test_aln({
'A': '-g',
'B': '-g',
'C': 'ag',
'D': '-a',
})
def test_difficult_end_gaps(self):
self._test_aln({
'A': '--cctc',
'B': '--cctc',
'C': 'gacctc',
'D': 'ga----',
})
return
self._test_aln({
'A': 'gcctcgg------',
'B': 'gcctcgg------',
'C': 'gcctcggaaacgt',
'D': '-------aaacgt',
})
class HirschbergTestCase(MultipleAlignmentTestCase):
# Force use of linear space algorithm
def _test_aln(self, seqs, **kw):
tmp = cogent.align.pairwise.HIRSCHBERG_LIMIT
try:
cogent.align.pairwise.HIRSCHBERG_LIMIT = 100
result = MultipleAlignmentTestCase._test_aln(self, seqs, **kw)
finally:
cogent.align.pairwise.HIRSCHBERG_LIMIT = tmp
return result
if __name__ == '__main__':
unittest.main()
PyCogent-1.5.3/tests/test_align/test_weights/ 000755 000765 000024 00000000000 12024703632 022243 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/tests/test_align/test_weights/__init__.py 000644 000765 000024 00000000500 12024702176 024351 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
__all__ = ['test_methods', 'test_util']
__author__ = ""
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Development"
PyCogent-1.5.3/tests/test_align/test_weights/test_methods.py 000644 000765 000024 00000041223 12024702176 025323 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from __future__ import division
from numpy import array, zeros, float64 as Float64
from cogent.util.unit_test import TestCase, main
from cogent.parse.tree import DndParser
from cogent.parse.clustal import ClustalParser as MinimalClustalParser
from cogent.core.alignment import Alignment
from cogent.core.profile import Profile
from cogent.align.weights.util import DNA_ORDER, PROTEIN_ORDER
from cogent.align.weights.methods import VA, VOR, mVOR, pos_char_weights, PB,\
SS, ACL, GSC, _clip_branch_lengths, _set_branch_sum, _set_node_weight
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Rob Knight", "Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Development"
def ClustalParser(f):
return Alignment(list(MinimalClustalParser(f)))
class GeneralTests(TestCase):
"""General tests for all classes in this file, provides general setup"""
def setUp(self):
"""General setUp method for all tests in this file"""
#ALIGNMENTS
self.aln1 = Alignment(['ABC','BCC','BAC'])
#alignment from Henikoff 1994
self.aln2 = Alignment({'seq1':'GYVGS','seq2':'GFDGF','seq3':'GYDGF',\
'seq4':'GYQGG'},Names=['seq1','seq2','seq3','seq4'])
#alignment from Vingron & Sibbald 1993
self.aln3 = Alignment({'seq1':'AA', 'seq2':'AA', 'seq3':'BB'},\
Names=['seq1','seq2','seq3'])
#alignment from Vingron & Sibbald 1993
self.aln4 = Alignment({'seq1':'AA', 'seq2':'AA', 'seq3':'BB',\
'seq4':'BB','seq5':'CC'},Names=['seq1','seq2','seq3','seq4','seq5'])
self.aln5 = Alignment(['ABBA','ABCA','CBCB'])
#alignment 5S rRNA seqs from Hein 1990
self.aln6 = ClustalParser(FIVE_S_ALN.split('\n'))
#alignment from Vingron & Sibbald 1993
self.aln7 = Alignment({'seq1':'AGCTA', 'seq2':'AGGTA', 'seq3':'ACCTG',
'seq4':'TGCAA'},Names=['seq1','seq2','seq3','seq4'])
#TREES (SEE BOTTOM OF FILE FOR DESCRIPTION)
self.tree1 = DndParser(TREE_1)
self.tree2 = DndParser(TREE_2)
self.tree3 = DndParser(TREE_3)
self.tree4 = DndParser(TREE_4)
self.tree5 = DndParser(TREE_5)
self.tree6 = DndParser(TREE_6)
self.tree7 = DndParser(TREE_7)
self.tree8 = DndParser(TREE_8)
self.tree9 = DndParser(TREE_9)
class VoronoiTests(GeneralTests):
"""Tests for the voronoi sequence weighting module"""
def test_VA(self):
"""VA: should return expected results. Results don't vary with runs"""
err=1e-3
aln2_exp = {'seq1':.269, 'seq2':.269,'seq3':.192,'seq4':.269}
aln4_exp = {'seq1':.1875, 'seq2':.1875,'seq3':.1875,'seq4':.1875,\
'seq5':.25}
aln5_exp = {'seq_0':0.33333,'seq_1':0.25,'seq_2':0.4167}
aln6_exp = dict(zip(map(str,[1,2,3,4,5,6,7,8,9,10]),\
[0.0962,0.0925,0.1061,0.1007,0.0958,0.0977,0.0914,\
0.0934,0.1106,0.1156]))
self.assertFloatEqualAbs(VA(self.aln2).values(),aln2_exp.values(),
eps=err)
self.assertFloatEqualAbs(VA(self.aln4).values(),aln4_exp.values(),
eps=err)
self.assertFloatEqualAbs(VA(self.aln5).values(),aln5_exp.values(),
eps=err)
self.assertFloatEqualAbs(VA(self.aln6).values(),aln6_exp.values(),
eps=err)
results = []
for x in range(5):
results.append(VA(self.aln2))
if x > 0:
self.assertEqual(results[x], results[x-1])
def test_VOR_exact(self):
"""VOR: should give exact results when using pseudo_seqs_exact"""
err=1e-3
aln2_exp = {'seq1':.259, 'seq2':.315,'seq3':.167,'seq4':.259}
aln3_exp = {'seq1':.29167, 'seq2':.29167, 'seq3':.4167}
aln4_exp = {'seq1':.1851, 'seq2':.1851,'seq3':.1851,'seq4':.1851,\
'seq5':.259}
self.assertFloatEqualAbs(VOR(self.aln2).values(),aln2_exp.values(),
eps=err)
self.assertFloatEqualAbs(VOR(self.aln3).values(),aln3_exp.values(),\
eps=err)
self.assertFloatEqualAbs(VOR(self.aln4).values(),aln4_exp.values(),\
eps=err)
#this is the exact method, so the answer should be exactly the same
#every time (on the same alignment)
results = []
for x in range(5):
results.append(VOR(self.aln2))
if x > 0:
self.assertEqual(results[x], results[x-1])
def test_VOR_force_mc(self):
"""VOR: should result in good approximation when using monte carlo"""
err=9e-2
aln2_exp = {'seq1':.259, 'seq2':.315,'seq3':.167,'seq4':.259}
aln3_exp = {'seq1':.29167, 'seq2':.29167, 'seq3':.4167}
aln4_exp = {'seq1':.1851, 'seq2':.1851,'seq3':.1851,'seq4':.1851,\
'seq5':.259}
aln6_exp = dict(zip(map(str,[1,2,3,4,5,6,7,8,9,10]),\
[0.0840,0.0763,0.1155,0.1019,0.0932,0.0980,0.0864,\
0.0999,0.1121,0.1328]))
# the following assertSimilarMeans statements were added to replace
# stochastic assertFloatEqualAbs calls below
self.assertSimilarMeans(VOR(self.aln2,force_monte_carlo=True).values(),
aln2_exp.values())
self.assertSimilarMeans(VOR(self.aln3,force_monte_carlo=True).values(),
aln3_exp.values())
self.assertSimilarMeans(VOR(self.aln4,force_monte_carlo=True).values(),
aln4_exp.values())
self.assertSimilarMeans(VOR(self.aln6,n=1000).values(),
aln6_exp.values())
#self.assertFloatEqualAbs(VOR(self.aln2,force_monte_carlo=True)\
# .values(), aln2_exp.values(),eps=err)
#self.assertFloatEqualAbs(VOR(self.aln3,force_monte_carlo=True)\
# .values(), aln3_exp.values(),eps=err)
#self.assertFloatEqualAbs(VOR(self.aln4,force_monte_carlo=True)\
# .values(), aln4_exp.values(),eps=err)
#self.assertFloatEqualAbs(VOR(self.aln6,n=1000)\
# .values(), aln6_exp.values(),eps=err)
#make sure monte carlo is used
results = []
for x in range(5):
results.append(VOR(self.aln2,force_monte_carlo=True))
if x > 0:
self.assertNotEqual(results[x], results[x-1])
def test_VOR_mc_threshold(self):
"""VOR: should apply monte carlo when # of pseudo seqs > mc_threshold
"""
err=9e-2
aln2_exp = {'seq1':.259, 'seq2':.315,'seq3':.167,'seq4':.259}
# the following assertSimilarMeans statement was added to replace
# stochastic assertFloatEqualAbs call below
self.assertSimilarMeans(VOR(self.aln2, mc_threshold=15).values(),
aln2_exp.values())
#self.assertFloatEqual(VOR(self.aln2,mc_threshold=15).values(),\
# aln2_exp.values(),err)
#make sure monte carlo is used
results = []
for x in range(5):
results.append(VOR(self.aln2,mc_threshold=15))
if x > 0:
self.assertNotEqual(results[x], results[x-1])
def test_mVOR(self):
"""mVOR: should return weights closer to the 'True' weights"""
#err=5e-2 #original error value
# Raised the error value to prevent occasional failure of the test.
# The mVOR method takes a sample from a distribution and the outcome
# will depend on this sample. Every now and then, one of the weights
# was more than 0.05 away from the expected weight. Raised the
# allowed error value to prevent that. To use the method on real
# data, a larger sample should be taken (e.g. 10000?), but increasing
# the sample size here would make the test too slow.
err=0.075
aln3_exp = {'seq1':.25, 'seq2':.25, 'seq3':.5}
aln4_exp = {'seq1':.1667, 'seq2':.1667,'seq3':.1667,'seq4':.1667,\
'seq5':.3333}
aln6_exp = dict(zip(map(str,[1,2,3,4,5,6,7,8,9,10]),
[0.09021,0.08039,0.113560,0.10399,0.092370,0.097130,
0.09198,0.09538,0.10927,0.12572]))
# the following assertSimilarMeans statements were added to replace
# stochastic assertFloatEqualAbs calls below
self.assertSimilarMeans(mVOR(self.aln3,order="ABC").values(),
aln3_exp.values())
self.assertSimilarMeans(mVOR(self.aln4,order="ABC").values(),
aln4_exp.values())
self.assertSimilarMeans(mVOR(self.aln6,order=DNA_ORDER,n=3000)\
.values(), aln6_exp.values())
#self.assertFloatEqualAbs(mVOR(self.aln3,order="ABC").values(),\
# aln3_exp.values(),eps=err)
#self.assertFloatEqualAbs(mVOR(self.aln4,order="ABC").values(),\
# aln4_exp.values(),eps=err)
#self.assertFloatEqualAbs(mVOR(self.aln6,order=DNA_ORDER,n=3000)\
# .values(), aln6_exp.values(),eps=err)
#the results vary with runs, because the sample of random profiles
#is different each time
results = []
for x in range(5):
results.append(mVOR(self.aln4,order="ABC"))
if x > 0:
self.assertNotEqual(results[x], results[x-1])
class PositionBasedTests(GeneralTests):
"""Contains tests for PB (=position-based) method"""
def test_pos_char_weights(self):
"""pos_char_weights: should return correct contributions at each pos
"""
#build expected profile
exp_data = zeros([len(PROTEIN_ORDER),self.aln2.SeqLen],Float64)
exp = [{'G':1/4},{'Y':1/6,'F':1/2},{'V':1/3,'D':1/6,'Q':1/3},
{'G':1/4},{'G':1/3,'F':1/6,'S':1/3}]
for pos, weights in enumerate(exp):
for k,v in weights.items():
exp_data[PROTEIN_ORDER.index(k),pos] = v
exp_aln2 = Profile(exp_data,Alphabet=PROTEIN_ORDER)
#check observed against expected
self.assertEqual(pos_char_weights(self.aln2,PROTEIN_ORDER).Data,
exp_aln2.Data)
def test_PB(self):
"""PB: should return correct weights"""
err=1e-3
aln2_exp = {'seq3': 0.2, 'seq2': 0.267, 'seq1': 0.267, 'seq4': 0.267}
self.assertFloatEqualAbs(PB(self.aln2,PROTEIN_ORDER)\
.values(), aln2_exp.values(),eps=err)
class SsTests(GeneralTests):
"""Tests for SS function"""
def test_SS(self):
"""SS: should return the correct weights"""
err=1e-3
aln4_exp = {'seq1':.1910, 'seq2':.1910,'seq3':.1910,'seq4':.1910,\
'seq5':.2361}
aln6_exp = dict(zip(map(str,[1,2,3,4,5,6,7,8,9,10]),
[0.0977,0.0942,0.1045,0.0997,0.0968,0.0988,
0.0929,0.0950,0.1076,0.1122]))
aln7_exp = {'seq1':.1792, 'seq2':.2447,'seq3':.2880,'seq4':.2880}
self.assertFloatEqualAbs(SS(self.aln4).values(),aln4_exp.values(),
eps=err)
self.assertFloatEqualAbs(SS(self.aln6).values(),aln6_exp.values(),
eps=err)
self.assertFloatEqualAbs(SS(self.aln7).values(),aln7_exp.values(),
eps=err)
class AclTests(GeneralTests):
"""Contains tests for ACL functionality"""
def test_ACL(self):
"""ACL: should return correct weights"""
err=1e-3
tree1_exp = {'WMJ2': 0.035, 'HXB': 0.017, 'WMJ1': 0.039,\
'BH10': 0.013, 'CDC': 0.048, 'BRU': 0.014, 'SF2': 0.050,\
'BH8': 0.006, 'RF': 0.085, 'ELI': 0.068, 'PV22': 0.013,\
'Z6': 0.129, 'MAL': 0.115, 'WMJ3': 0.035, 'Z3': 0.333}
tree2_exp = {'agcta':0.7380,'aggta':0.0,'acctg':0.0,'tgcaa':0.2620}
tree3_exp = {'agcta':0.2857,'aggta':0.0,'acctg':0.2857,'tgcaa':0.4286}
tree4_exp = {'10': 0.1186, '1': 0.0627, '3': 0.1307, '2': 0.0627,
'5': 0.0919, '4': 0.1307, '7': 0.0958, '6': 0.0919,
'9': 0.1186, '8': 0.0958}
tree9_exp = {'A':.25,'B':.25,'C':.25,'D':.25}
self.assertFloatEqualAbs(ACL(self.tree1), tree1_exp, eps=err)
self.assertFloatEqualAbs(ACL(self.tree2), tree2_exp, eps=err)
self.assertFloatEqualAbs(ACL(self.tree3), tree3_exp, eps=err)
self.assertFloatEqualAbs(ACL(self.tree4), tree4_exp, eps=err)
#also works when branch lengths are zero
self.assertFloatEqualAbs(ACL(self.tree9), tree9_exp, eps=err)
w_tree8 = ACL(self.tree8)
self.assertFloatEqual(w_tree8['A'], w_tree8['B'],err)
self.assertFloatEqual(w_tree8['A'], w_tree8['C'],err)
self.assertFloatEqual(w_tree8['D'], w_tree8['E'],err)
self.assertFloatEqual(w_tree8['F'], w_tree8['G'],err)
self.assertGreaterThan(w_tree8['A'], w_tree8['D'])
self.assertGreaterThan(w_tree8['D'], w_tree8['H'])
self.assertGreaterThan(w_tree8['H'], w_tree8['F'])
class GscTests(GeneralTests):
"""Tests for GSC functionality"""
def test_gsc(self):
"""GSC: should return correct weights"""
err = 1e-3
tree6_exp = {'A': 0.19025, 'B': 0.19025, 'C': 0.2717, 'D': 0.3478}
tree7_exp = {'A':.25, 'B':.25, 'C':.25, 'D':.25}
tree8_exp = dict(zip('ABCDEFGH',[.1,.1,.2,.06,.06,.16,.16,.16]))
self.assertFloatEqualAbs(GSC(self.tree6).values(),\
tree6_exp.values(),eps=err)
self.assertFloatEqualAbs(GSC(self.tree7).values(),\
tree7_exp.values(),eps=err)
self.assertFloatEqualAbs(GSC(self.tree8).values(),\
tree8_exp.values(),eps=err)
#Rooted tree relating 15 HIV-1 isolates. From Altschul (1989) Fig 2.
TREE_1 = "(((((((((((BH8:0.7,PV22:0.3,BH10:0.3):0.1,BRU:0.5):0.1,HXB:0.7):2.4,SF2:3.3):0.1,CDC:3.7):0.5),((WMJ1:0.8,WMJ2:0.9,WMJ3:0.9):2.1)):0.4,RF:4.3):2.6),(((Z6:2.2,ELI:4.2):2.1,MAL:6.1):1.9)):2.7,Z3:9.3);"
#Model tree from Vingron and Sibbald (1993) Fig 3, distances estimated by Li.
TREE_2 = "(((((agcta:0.0,aggta:1.03):0.0),acctg:2.23):0.6),tgcaa:1.69);"
#Model tree from Vingron and Sibbald (1993) Fig 3 Actual # of substitutions
TREE_3 = "(((((agcta:0,aggta:1):1),acctg:1):1),tgcaa:2);"
#the ultrameric tree from Vingron and Sibbald (1993) Fig 3.
TREE_4 ="(((((((((2:6.0,1:6.0):12.9),((8:17.0,7:17.0):1.9)):5.3)),((6:8.5,5:8.5):15.7)):9.6),((((4:15.0,3:15.0):12.1),((9:11.0,10:11.0):16.1)):6.7)));"
#the additive tree from Vingron and Sibbald (1993) Fig 3.
#I don't trust the results they got for this tree (Table 3).
TREE_5 ="(((((((((2:7,1:7):19),((8:18,7:16):3)):12)),((6:10,5:10):28)):16),((((4:14,3:18):15),((9:8,10:14):24)):11)));"
TREE_6 = "(((A:20,B:20):30,C:50):30,D:80);"
TREE_7 = "((A:10,B:10):5,(C:10,D:10):5);"
TREE_8 = "((((A:5,B:5):5,C:15):10),((D:0,E:0):10,((F:5,G:5):10,H:10):10):10);"
TREE_9 = "(((A:0,B:0):5,C:10):5,D:25);"
FIVE_S_ALN =\
"""CLUSTAL W (1.81)
1 A----TCCACGGCCATAGGACTCTGAAAGCACTGCATCCCGT-CCGATCTGCAAAGTTAA
2 A----TCCACGGCCATAGGACTGTGAAAGCACCGCATCCCGT-CTGATCTGCGCAGTTAA
3 T----CTGGTGATGATGGCGGAGGGGACACACCCGTTCCCATACCGAACACGGCCGTTAA
4 T----CTGGTGGCGATAGCGAGAAGGTCACACCCGTTCCCATACCGAACACGGAAGTTAA
5 G---TGGTGCGGTCATACCAGCGCTAATGCACCGGATCCCAT-CAGAACTCCGCAGTTAA
6 G----GGTGCGATCATACCAGCGTTAATGCACCGGATCCCAT-CAGAACTCCGCAGTTAA
7 G----CTTACGACCATATCACGTTGAATGCACGCCATCCCGT-CCGATCTGGCAAGTTAA
8 G----CCTACGGCCATCCCACCCTGGTAACGCCCGATCTCGT-CTGATCTCGGAAGCTAA
9 T--T-CTGGTGTCTCAGGCGTGGAGGAACCACACCAATCCATCCCGAACTTGGTGGTGAA
10 TATT-CTGGTGTCCCAGGCGTAGAGGAACCACACCGATCCATCTCGAACTTGGTGGTGAA
. * .: . .: *.* : *.* **:*: * **
1 CCAGAGTACCGCCCAGT-TAGTACC-AC-GGTGGGGGACCACGCGGGAATCCTGGGTGCT
2 ACACAGTGCCGCCTAGT-TAGTACC-AT-GGTGGGGGACCACATGGGAATCCTGGGTGCT
3 GCCCTCCAGCGCC--AA-TGGTACT-TGCTC-CGCAGGGAG-CCGGGAGAGTAGGACGTC
4 GCTTCTCAGCGCC--GA-TGGTAGT-TA-GG-GGCTGTCCC-CTGTGAGAGTAGGACGCT
5 GCGCGCTTGGGCCAGAA-CAGTACT-GG-GATGGGTGACCTCCCGGGAAGTCCTGGTGCC
6 GCGCGCTTGGGTTGGAG-TAGTACT-AG-GATGGGTGACCTCCTGGGAAGTCCTAATATT
7 GCAACGTTGAGTCCAGT-TAGTACT-TG-GATCGGAGACGGCCTGGGAATCCTGGATGTT
8 GCAGGGTCGGGCCTGGT-TAGTACT-TG-GATGGGAGACCTCCTGGGAATACCGGGTGCT
9 ACTCTATTGCGGT--GA-CGATACTGTA-GG-GGAAGCCCG-ATGGAAAAATAGCTCGAC
10 ACTCTGCCGCGGT--AACCAATACT-CG-GG-GGGGGCCCT-GCGGAAAAATAGCTCGAT
* * . ..** * * * .*. . *
1 GT-GG-T--T-
2 GT-GG-T--T-
3 GCCAG-G--C-
4 GCCAG-G--C-
5 GCACC-C--C-
6 GCACC-C-TT-
7 GTAAG-C--T-
8 GTAGG-CT-T-
9 GCCAGGA--T-
10 GCCAGGA--TA
:
"""
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/test_align/test_weights/test_util.py 000644 000765 000024 00000022775 12024702176 024650 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from cogent.util.unit_test import TestCase, main
from numpy import array, float64 as Float64, zeros
from math import sqrt
from random import choice
from cogent.core.alignment import Alignment
from cogent.core.sequence import DnaSequence, RnaSequence
from cogent.core.moltype import DNA, RNA
from cogent.align.weights.util import Weights, number_of_pseudo_seqs,\
pseudo_seqs_exact, pseudo_seqs_monte_carlo, row_to_vote, distance_matrix,\
eigenvector_for_largest_eigenvalue, DNA_ORDER,RNA_ORDER,PROTEIN_ORDER,\
SeqToProfile,AlnToProfile, distance_to_closest
__author__ = "Sandra Smit"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Sandra Smit", "Rob Knight"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Sandra Smit"
__email__ = "sandra.smit@colorado.edu"
__status__ = "Development"
class WeightsTests(TestCase):
def test_weights(self):
"""Weights: should behave like a normal dict and can be normalized
"""
w = Weights({'seq1':2, 'seq2':3, 'seq3':10})
self.assertEqual(w['seq1'],2)
w.normalize()
exp = {'seq1':0.1333333, 'seq2':0.2, 'seq3':0.6666666}
self.assertFloatEqual(w.values(), exp.values())
class UtilTests(TestCase):
def setUp(self):
"""Set up for Voronoi tests"""
self.aln1 = Alignment(['ABC','BCC','BAC'])
self.aln2 = Alignment({'seq1':'GYVGS','seq2':'GFDGF','seq3':'GYDGF',\
'seq4':'GYQGG'},Names=['seq1','seq2','seq3','seq4'])
self.aln3 = Alignment({'seq1':'AA', 'seq2':'AA', 'seq3':'BB'},\
Names=['seq1','seq2','seq3'])
self.aln4 = Alignment({'seq1':'AA', 'seq2':'AA', 'seq3':'BB',\
'seq4':'BB','seq5':'CC'},Names=['seq1','seq2','seq3','seq4','seq5'])
self.aln5 = Alignment(['ABBA','ABCA','CBCB'])
def test_number_of_pseudo_seqs(self):
"""number_of_pseudo_seqs: should return # of pseudo seqs"""
self.assertEqual(number_of_pseudo_seqs(self.aln1),6)
self.assertEqual(number_of_pseudo_seqs(self.aln2),18)
self.assertEqual(number_of_pseudo_seqs(self.aln3),4)
self.assertEqual(number_of_pseudo_seqs(self.aln4),9)
def test_pseudo_seqs_exact(self):
"""pseudo_seqs_exact: should generate expected pseudo sequences"""
self.assertEqualItems(pseudo_seqs_exact(self.aln1),\
['AAC','ABC','ACC','BAC','BBC','BCC'])
self.assertEqualItems(pseudo_seqs_exact(self.aln3),\
['AA','AB','BA','BB'])
self.assertEqual(len(pseudo_seqs_exact(self.aln2)), 18)
def test_pseudo_seqs_monte_carlo(self):
"""pseudo_seqs_monte_carlo: random sample from all possible pseudo seqs
"""
self.assertEqual(len(list(pseudo_seqs_monte_carlo(self.aln1,n=100))),\
100)
for i in pseudo_seqs_monte_carlo(self.aln3,n=100):
self.assertContains(['AA','AB','BA','BB'], i)
def test_row_to_vote(self):
"""row_to_vote: should return correct votes for int and float distances
"""
self.assertEqual(row_to_vote(array([2,3,4,5])),array([1,0,0,0]))
self.assertEqual(row_to_vote(array([2,3,2,5])),array([.5,0,0.5,0]))
self.assertEqual(row_to_vote(array([2.3,3.5,2.1,5.8]))\
,array([0,0,1,0]))
def test_distance_matrix(self):
"""distance_matrix should obey Names of alignment"""
#Names=None
aln1_exp = array([[0,2,2],[2,0,1],[2,1,0]])
self.assertEqual(distance_matrix(self.aln1),aln1_exp)
a = Alignment(self.aln1.NamedSeqs)
a.Names=['seq_1','seq_2','seq_0']
a_exp = array([[0,1,2],[1,0,2],[2,2,0]])
self.assertEqual(distance_matrix(a),a_exp)
def test_eigenvector_for_largest_eigenvalue(self):
"""eigenvector_for_largest_eigenvalue: No idea how to test this"""
pass
def test_distance_to_closest(self):
"""distance_to_closest: should return closest distances"""
self.assertEqual(distance_to_closest(self.aln1),[2,1,1])
self.assertEqual(distance_to_closest(self.aln2),[2,1,1,2])
def test_SeqToProfile(self):
"""SequenceToProfile: should work with different parameter settings
"""
seq = DnaSequence("ATCGRYN-")
#Only non-degenerate bases in the char order, all other
#characters are ignored. In a sequence this means that
#several positions will contain only zeros in the profile.
exp = zeros([len(seq),4],Float64)
for x,y in zip(range(len(seq)),[2,0,1,3]):
exp[x,y] = 1
self.assertEqual(SeqToProfile(seq,char_order="TCAG",\
split_degenerates=False).Data.tolist(),exp.tolist())
#Same thing should work as well when the char order is not passed in
exp = zeros([len(seq),4],Float64)
for x,y in zip(range(len(seq)),[2,0,1,3]):
exp[x,y] = 1
self.assertEqual(SeqToProfile(seq, split_degenerates=False)\
.Data.tolist(),exp.tolist())
#All symbols in the sequence are in the char order, no row
#should contain only zeros. Degenerate symbols are not split.
exp = zeros([len(seq),8],Float64)
for x,y in zip(range(len(seq)),[2,0,1,3,4,5,6,7]):
exp[x,y] = 1
self.assertEqual(SeqToProfile(seq,char_order="TCAGRYN-",\
split_degenerates=False).Data.tolist(), exp.tolist())
#splitting all degenerate symbols, having only non-degenerate symbols
#in the character order (and -)
exp = array([[0,0,1,0,0],[1,0,0,0,0],[0,1,0,0,0],[0,0,0,1,0],
[0,0,.5,.5,0],[.5,.5,0,0,0],[.25,.25,.25,.25,0],[0,0,0,0,1]])
self.assertEqual(SeqToProfile(seq,char_order="TCAG-",\
split_degenerates=True).Data.tolist(),exp.tolist())
#splitting degenerates, but having one of the degenerate
#symbols in the character order. In that case the degenerate symbol
#is not split.
exp = array([[0,0,1,0,0,0],[1,0,0,0,0,0],[0,1,0,0,0,0],[0,0,0,1,0,0],
[0,0,.5,.5,0,0],[.5,.5,0,0,0,0],[0,0,0,0,1,0],[0,0,0,0,0,1]])
self.assertEqual(SeqToProfile(seq,char_order="TCAGN-",\
split_degenerates=True).Data.tolist(),exp.tolist())
def test_AlignmentToProfile_basic(self):
"""AlignmentToProfile: should work under basic conditions
"""
#sequences in the alignment are unweighted
#Alphabet is the alphabet of the sequences (RNA)
#CharOrder is set explicitly
#Degenerate bases are split up
#Gaps are ignored
#In all of the columns at least one character is in the CharOrder
a = Alignment({'a':RnaSequence('UCAGRYN-'),'b':RnaSequence('ACUGAAAA')})
exp =\
array([[.5,0,.5,0],
[0,1,0,0],
[.5,0,.5,0],
[0,0,0,1],
[0,0,.75,.25],
[.25,.25,.5,0],
[.125,.125,.625,.125],
[0,0,1,0]])
self.assertEqual(AlnToProfile(a,alphabet=RNA,\
split_degenerates=True).Data.tolist(),exp.tolist())
def test_AlignmentToProfile_ignore(self):
"""AlignmentToProfile: should raise an error if too many chars ignored
"""
#Same conditions as previous function, but in the last column
#there are only gaps, so normalization will fail at that position
a = Alignment({'a':RnaSequence('UCAGRYN-'),'b':RnaSequence('ACUGAAA-')})
exp =\
array([[.5,0,.5,0],
[0,1,0,0],
[.5,0,.5,0],
[0,0,0,1],
[0,0,.75,.25],
[.25,.25,.5,0],
[.125,.125,.625,.125],
[0,0,1,0]])
self.assertRaises(ValueError,AlnToProfile,a,alphabet=RNA,\
split_degenerates=True)
def test_AlignmentToProfile_weighted(self):
"""AlignmentToProfile: should work when sequences are weighted
"""
#Alignment: sequences are just strings and don't have an alphabet
#Weights: a normal dictionary (could be a real Weights object as well)
a = Alignment({'seq1':'TCAG','seq2':'TAR-','seq3':'YAG-'},\
Names=['seq1','seq2','seq3'])
w = {'seq1':0.5,'seq2':.25,'seq3':.25}
#Basic situation in which all letters in the sequences occur in the
#CharOrder, None have to be ignored. In that case it doesn't matter
#whether we set split_degenerates to True or False, because if it's
#True it's overwritten by the fact that the char is in the CharOrder.
exp = array([[0.75,0,0,0,0,.25,0],
[0,0.5,0.5,0,0,0,0],
[0,0.5,0,0.25,0.25,0,0],
[0,0,0,0.5,0,0,0.5]])
#split_degenerates = False
self.assertEqual(AlnToProfile(a,DNA, char_order="TACGRY-",\
weights=w, split_degenerates=False).Data.tolist(),exp.tolist())
#split_degenerates = True
self.assertEqual(AlnToProfile(a,DNA, char_order="TACGRY-",\
weights=w, split_degenerates=True).Data.tolist(),exp.tolist())
#Only non-degenerate symbols in the CharOrder. Degenerates are split.
#Gaps are ignored
exp = array([[0.875,0,0.125,0],
[0,0.5,0.5,0],
[0,0.625,0,0.375],
[0,0,0,1]])
self.assertEqual(AlnToProfile(a,DNA, char_order="TACG",\
weights=w, split_degenerates=True).Data.tolist(),exp.tolist())
#An Error is raised if all chars in an alignment column are ignored
#CharOrder=AT, degenerates are not split.
self.assertRaises(ValueError,AlnToProfile,a,DNA,\
char_order="AT",weights=w, split_degenerates=True)
if __name__ == "__main__":
main()
PyCogent-1.5.3/tests/data/1A1X.pdb 000644 000765 000024 00000302335 11305747275 017475 0 ustar 00jrideout staff 000000 000000 HEADER PROTO-ONCOGENE 18-DEC-97 1A1X
TITLE CRYSTAL STRUCTURE OF MTCP-1 INVOLVED IN T CELL MALIGNANCIES
COMPND MOL_ID: 1;
COMPND 2 MOLECULE: HMTCP-1;
COMPND 3 CHAIN: A;
COMPND 4 ENGINEERED: YES
SOURCE MOL_ID: 1;
SOURCE 2 ORGANISM_SCIENTIFIC: HOMO SAPIENS;
SOURCE 3 ORGANISM_COMMON: HUMAN;
SOURCE 4 ORGANISM_TAXID: 9606;
SOURCE 5 EXPRESSION_SYSTEM: ESCHERICHIA COLI;
SOURCE 6 EXPRESSION_SYSTEM_TAXID: 562
KEYWDS MTCP-1, CRYSTAL STRUCTURE, ONCOGENE INVOLVED IN T CELL
KEYWDS 2 MALIGNANCIES, PROTO-ONCOGENE
EXPDTA X-RAY DIFFRACTION
AUTHOR Z.Q.FU,G.C.DUBOIS,S.P.SONG,I.KULIKOVSKAYA,L.VIRGILIO,
AUTHOR 2 J.ROTHSTEIN,C.M.CROCE,I.T.WEBER,R.W.HARRISON
REVDAT 2 24-FEB-09 1A1X 1 VERSN
REVDAT 1 27-MAY-98 1A1X 0
JRNL AUTH Z.Q.FU,G.C.DU BOIS,S.P.SONG,I.KULIKOVSKAYA,
JRNL AUTH 2 L.VIRGILIO,J.L.ROTHSTEIN,C.M.CROCE,I.T.WEBER,
JRNL AUTH 3 R.W.HARRISON
JRNL TITL CRYSTAL STRUCTURE OF MTCP-1: IMPLICATIONS FOR ROLE
JRNL TITL 2 OF TCL-1 AND MTCP-1 IN T CELL MALIGNANCIES.
JRNL REF PROC.NATL.ACAD.SCI.USA V. 95 3413 1998
JRNL REFN ISSN 0027-8424
JRNL PMID 9520380
JRNL DOI 10.1073/PNAS.95.7.3413
REMARK 1
REMARK 2
REMARK 2 RESOLUTION. 2.00 ANGSTROMS.
REMARK 3
REMARK 3 REFINEMENT.
REMARK 3 PROGRAM : X-PLOR 3.8
REMARK 3 AUTHORS : BRUNGER
REMARK 3
REMARK 3 DATA USED IN REFINEMENT.
REMARK 3 RESOLUTION RANGE HIGH (ANGSTROMS) : 2.00
REMARK 3 RESOLUTION RANGE LOW (ANGSTROMS) : 6.50
REMARK 3 DATA CUTOFF (SIGMA(F)) : 2.000
REMARK 3 DATA CUTOFF HIGH (ABS(F)) : 1000000.000
REMARK 3 DATA CUTOFF LOW (ABS(F)) : 0.0010
REMARK 3 COMPLETENESS (WORKING+TEST) (%) : 99.7
REMARK 3 NUMBER OF REFLECTIONS : 6733
REMARK 3
REMARK 3 FIT TO DATA USED IN REFINEMENT.
REMARK 3 CROSS-VALIDATION METHOD : THROUGHOUT
REMARK 3 FREE R VALUE TEST SET SELECTION : RANDOM
REMARK 3 R VALUE (WORKING SET) : 0.211
REMARK 3 FREE R VALUE : 0.253
REMARK 3 FREE R VALUE TEST SET SIZE (%) : 8.600
REMARK 3 FREE R VALUE TEST SET COUNT : 582
REMARK 3 ESTIMATED ERROR OF FREE R VALUE : 0.010
REMARK 3
REMARK 3 FIT IN THE HIGHEST RESOLUTION BIN.
REMARK 3 TOTAL NUMBER OF BINS USED : 8
REMARK 3 BIN RESOLUTION RANGE HIGH (A) : 2.00
REMARK 3 BIN RESOLUTION RANGE LOW (A) : 2.09
REMARK 3 BIN COMPLETENESS (WORKING+TEST) (%) : 99.30
REMARK 3 REFLECTIONS IN BIN (WORKING SET) : 739
REMARK 3 BIN R VALUE (WORKING SET) : 0.2550
REMARK 3 BIN FREE R VALUE : 0.2680
REMARK 3 BIN FREE R VALUE TEST SET SIZE (%) : 8.70
REMARK 3 BIN FREE R VALUE TEST SET COUNT : 73
REMARK 3 ESTIMATED ERROR OF BIN FREE R VALUE : 0.031
REMARK 3
REMARK 3 NUMBER OF NON-HYDROGEN ATOMS USED IN REFINEMENT.
REMARK 3 PROTEIN ATOMS : 881
REMARK 3 NUCLEIC ACID ATOMS : 0
REMARK 3 HETEROGEN ATOMS : 0
REMARK 3 SOLVENT ATOMS : 24
REMARK 3
REMARK 3 B VALUES.
REMARK 3 FROM WILSON PLOT (A**2) : NULL
REMARK 3 MEAN B VALUE (OVERALL, A**2) : 22.01
REMARK 3 OVERALL ANISOTROPIC B VALUE.
REMARK 3 B11 (A**2) : NULL
REMARK 3 B22 (A**2) : NULL
REMARK 3 B33 (A**2) : NULL
REMARK 3 B12 (A**2) : NULL
REMARK 3 B13 (A**2) : NULL
REMARK 3 B23 (A**2) : NULL
REMARK 3
REMARK 3 ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM LUZZATI PLOT (A) : NULL
REMARK 3 ESD FROM SIGMAA (A) : NULL
REMARK 3 LOW RESOLUTION CUTOFF (A) : NULL
REMARK 3
REMARK 3 CROSS-VALIDATED ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM C-V LUZZATI PLOT (A) : NULL
REMARK 3 ESD FROM C-V SIGMAA (A) : NULL
REMARK 3
REMARK 3 RMS DEVIATIONS FROM IDEAL VALUES.
REMARK 3 BOND LENGTHS (A) : 0.007
REMARK 3 BOND ANGLES (DEGREES) : 1.40
REMARK 3 DIHEDRAL ANGLES (DEGREES) : 26.92
REMARK 3 IMPROPER ANGLES (DEGREES) : 1.19
REMARK 3
REMARK 3 ISOTROPIC THERMAL MODEL : RESTRAINED
REMARK 3
REMARK 3 ISOTROPIC THERMAL FACTOR RESTRAINTS. RMS SIGMA
REMARK 3 MAIN-CHAIN BOND (A**2) : 2.157 ; 1.500
REMARK 3 MAIN-CHAIN ANGLE (A**2) : 3.319 ; 2.000
REMARK 3 SIDE-CHAIN BOND (A**2) : 4.210 ; 2.000
REMARK 3 SIDE-CHAIN ANGLE (A**2) : 6.231 ; 2.500
REMARK 3
REMARK 3 NCS MODEL : NULL
REMARK 3
REMARK 3 NCS RESTRAINTS. RMS SIGMA/WEIGHT
REMARK 3 GROUP 1 POSITIONAL (A) : NULL ; NULL
REMARK 3 GROUP 1 B-FACTOR (A**2) : NULL ; NULL
REMARK 3
REMARK 3 PARAMETER FILE 1 : PARHCSDX.PRO
REMARK 3 PARAMETER FILE 2 : TIP3P.PARAMETER
REMARK 3 PARAMETER FILE 3 : NULL
REMARK 3 TOPOLOGY FILE 1 : TOPHCSDX.PRO
REMARK 3 TOPOLOGY FILE 2 : TIP3P.TOPOLOGY
REMARK 3 TOPOLOGY FILE 3 : NULL
REMARK 3
REMARK 3 OTHER REFINEMENT REMARKS: NULL
REMARK 4
REMARK 4 1A1X COMPLIES WITH FORMAT V. 3.15, 01-DEC-08
REMARK 100
REMARK 100 THIS ENTRY HAS BEEN PROCESSED BY BNL.
REMARK 200
REMARK 200 EXPERIMENTAL DETAILS
REMARK 200 EXPERIMENT TYPE : X-RAY DIFFRACTION
REMARK 200 DATE OF DATA COLLECTION : SEP-97
REMARK 200 TEMPERATURE (KELVIN) : 293
REMARK 200 PH : 7.8
REMARK 200 NUMBER OF CRYSTALS USED : 1
REMARK 200
REMARK 200 SYNCHROTRON (Y/N) : N
REMARK 200 RADIATION SOURCE : ROTATING ANODE
REMARK 200 BEAMLINE : NULL
REMARK 200 X-RAY GENERATOR MODEL : RIGAKU RUH2R
REMARK 200 MONOCHROMATIC OR LAUE (M/L) : M
REMARK 200 WAVELENGTH OR RANGE (A) : 1.5418
REMARK 200 MONOCHROMATOR : NI FILTER
REMARK 200 OPTICS : NULL
REMARK 200
REMARK 200 DETECTOR TYPE : IMAGE PLATE
REMARK 200 DETECTOR MANUFACTURER : RIGAKU
REMARK 200 INTENSITY-INTEGRATION SOFTWARE : DENZO
REMARK 200 DATA SCALING SOFTWARE : SCALEPACK
REMARK 200
REMARK 200 NUMBER OF UNIQUE REFLECTIONS : 7194
REMARK 200 RESOLUTION RANGE HIGH (A) : 2.000
REMARK 200 RESOLUTION RANGE LOW (A) : 21.000
REMARK 200 REJECTION CRITERIA (SIGMA(I)) : 0.000
REMARK 200
REMARK 200 OVERALL.
REMARK 200 COMPLETENESS FOR RANGE (%) : 99.7
REMARK 200 DATA REDUNDANCY : 5.900
REMARK 200 R MERGE (I) : NULL
REMARK 200 R SYM (I) : 0.04700
REMARK 200 FOR THE DATA SET : 15.1000
REMARK 200
REMARK 200 IN THE HIGHEST RESOLUTION SHELL.
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE HIGH (A) : 2.00
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE LOW (A) : 2.07
REMARK 200 COMPLETENESS FOR SHELL (%) : 99.3
REMARK 200 DATA REDUNDANCY IN SHELL : 5.40
REMARK 200 R MERGE FOR SHELL (I) : NULL
REMARK 200 R SYM FOR SHELL (I) : 0.14700
REMARK 200 FOR SHELL : 7.600
REMARK 200
REMARK 200 DIFFRACTION PROTOCOL: NULL
REMARK 200 METHOD USED TO DETERMINE THE STRUCTURE: MAD PHASING
REMARK 200 SOFTWARE USED: MADSYS, X-PLOR 3.8
REMARK 200 STARTING MODEL: NULL
REMARK 200
REMARK 200 REMARK: NULL
REMARK 280
REMARK 280 CRYSTAL
REMARK 280 SOLVENT CONTENT, VS (%): 37.00
REMARK 280 MATTHEWS COEFFICIENT, VM (ANGSTROMS**3/DA): 2.00
REMARK 280
REMARK 280 CRYSTALLIZATION CONDITIONS: PROTEIN WAS CRYSTALLIZED FROM 1.5M
REMARK 280 AMS WITH TRIZMA BUFFER AT PH 7.8
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY
REMARK 290 SYMMETRY OPERATORS FOR SPACE GROUP: P 62 2 2
REMARK 290
REMARK 290 SYMOP SYMMETRY
REMARK 290 NNNMMM OPERATOR
REMARK 290 1555 X,Y,Z
REMARK 290 2555 -Y,X-Y,Z+2/3
REMARK 290 3555 -X+Y,-X,Z+1/3
REMARK 290 4555 -X,-Y,Z
REMARK 290 5555 Y,-X+Y,Z+2/3
REMARK 290 6555 X-Y,X,Z+1/3
REMARK 290 7555 Y,X,-Z+2/3
REMARK 290 8555 X-Y,-Y,-Z
REMARK 290 9555 -X,-X+Y,-Z+1/3
REMARK 290 10555 -Y,-X,-Z+2/3
REMARK 290 11555 -X+Y,Y,-Z
REMARK 290 12555 X,X-Y,-Z+1/3
REMARK 290
REMARK 290 WHERE NNN -> OPERATOR NUMBER
REMARK 290 MMM -> TRANSLATION VECTOR
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY TRANSFORMATIONS
REMARK 290 THE FOLLOWING TRANSFORMATIONS OPERATE ON THE ATOM/HETATM
REMARK 290 RECORDS IN THIS ENTRY TO PRODUCE CRYSTALLOGRAPHICALLY
REMARK 290 RELATED MOLECULES.
REMARK 290 SMTRY1 1 1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 1 0.000000 1.000000 0.000000 0.00000
REMARK 290 SMTRY3 1 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 2 -0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 2 0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 2 0.000000 0.000000 1.000000 57.30800
REMARK 290 SMTRY1 3 -0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 3 -0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 3 0.000000 0.000000 1.000000 28.65400
REMARK 290 SMTRY1 4 -1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 4 0.000000 -1.000000 0.000000 0.00000
REMARK 290 SMTRY3 4 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 5 0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 5 -0.866025 0.500000 0.000000 0.00000
REMARK 290 SMTRY3 5 0.000000 0.000000 1.000000 57.30800
REMARK 290 SMTRY1 6 0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 6 0.866025 0.500000 0.000000 0.00000
REMARK 290 SMTRY3 6 0.000000 0.000000 1.000000 28.65400
REMARK 290 SMTRY1 7 -0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 7 0.866025 0.500000 0.000000 0.00000
REMARK 290 SMTRY3 7 0.000000 0.000000 -1.000000 57.30800
REMARK 290 SMTRY1 8 1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 8 0.000000 -1.000000 0.000000 0.00000
REMARK 290 SMTRY3 8 0.000000 0.000000 -1.000000 0.00000
REMARK 290 SMTRY1 9 -0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 9 -0.866025 0.500000 0.000000 0.00000
REMARK 290 SMTRY3 9 0.000000 0.000000 -1.000000 28.65400
REMARK 290 SMTRY1 10 0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 10 -0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 10 0.000000 0.000000 -1.000000 57.30800
REMARK 290 SMTRY1 11 -1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 11 0.000000 1.000000 0.000000 0.00000
REMARK 290 SMTRY3 11 0.000000 0.000000 -1.000000 0.00000
REMARK 290 SMTRY1 12 0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 12 0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 12 0.000000 0.000000 -1.000000 28.65400
REMARK 290
REMARK 290 REMARK: NULL
REMARK 300
REMARK 300 BIOMOLECULE: 1
REMARK 300 SEE REMARK 350 FOR THE AUTHOR PROVIDED AND/OR PROGRAM
REMARK 300 GENERATED ASSEMBLY INFORMATION FOR THE STRUCTURE IN
REMARK 300 THIS ENTRY. THE REMARK MAY ALSO PROVIDE INFORMATION ON
REMARK 300 BURIED SURFACE AREA.
REMARK 350
REMARK 350 COORDINATES FOR A COMPLETE MULTIMER REPRESENTING THE KNOWN
REMARK 350 BIOLOGICALLY SIGNIFICANT OLIGOMERIZATION STATE OF THE
REMARK 350 MOLECULE CAN BE GENERATED BY APPLYING BIOMT TRANSFORMATIONS
REMARK 350 GIVEN BELOW. BOTH NON-CRYSTALLOGRAPHIC AND
REMARK 350 CRYSTALLOGRAPHIC OPERATIONS ARE GIVEN.
REMARK 350
REMARK 350 BIOMOLECULE: 1
REMARK 350 AUTHOR DETERMINED BIOLOGICAL UNIT: DIMERIC
REMARK 350 APPLY THE FOLLOWING TO CHAINS: A
REMARK 350 BIOMT1 1 1.000000 0.000000 0.000000 0.00000
REMARK 350 BIOMT2 1 0.000000 1.000000 0.000000 0.00000
REMARK 350 BIOMT3 1 0.000000 0.000000 1.000000 0.00000
REMARK 350 BIOMT1 2 -1.000000 0.000000 0.000000 31.33250
REMARK 350 BIOMT2 2 0.000000 -1.000000 0.000000 54.26948
REMARK 350 BIOMT3 2 0.000000 0.000000 1.000000 0.00000
REMARK 465
REMARK 465 MISSING RESIDUES
REMARK 465 THE FOLLOWING RESIDUES WERE NOT LOCATED IN THE
REMARK 465 EXPERIMENT. (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN
REMARK 465 IDENTIFIER; SSSEQ=SEQUENCE NUMBER; I=INSERTION CODE.)
REMARK 465
REMARK 465 M RES C SSSEQI
REMARK 465 GLY A 1
REMARK 465 SER A 2
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: TORSION ANGLES
REMARK 500
REMARK 500 TORSION ANGLES OUTSIDE THE EXPECTED RAMACHANDRAN REGIONS:
REMARK 500 (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN IDENTIFIER;
REMARK 500 SSEQ=SEQUENCE NUMBER; I=INSERTION CODE).
REMARK 500
REMARK 500 STANDARD TABLE:
REMARK 500 FORMAT:(10X,I3,1X,A3,1X,A1,I4,A1,4X,F7.2,3X,F7.2)
REMARK 500
REMARK 500 EXPECTED VALUES: GJ KLEYWEGT AND TA JONES (1996). PHI/PSI-
REMARK 500 CHOLOGY: RAMACHANDRAN REVISITED. STRUCTURE 4, 1395 - 1400
REMARK 500
REMARK 500 M RES CSSEQI PSI PHI
REMARK 500 GLU A 75 37.60 76.92
REMARK 500
REMARK 500 REMARK: NULL
DBREF 1A1X A 3 108 UNP P56278 MTCPB_HUMAN 2 107
SEQRES 1 A 108 GLY SER ALA GLY GLU ASP VAL GLY ALA PRO PRO ASP HIS
SEQRES 2 A 108 LEU TRP VAL HIS GLN GLU GLY ILE TYR ARG ASP GLU TYR
SEQRES 3 A 108 GLN ARG THR TRP VAL ALA VAL VAL GLU GLU GLU THR SER
SEQRES 4 A 108 PHE LEU ARG ALA ARG VAL GLN GLN ILE GLN VAL PRO LEU
SEQRES 5 A 108 GLY ASP ALA ALA ARG PRO SER HIS LEU LEU THR SER GLN
SEQRES 6 A 108 LEU PRO LEU MET TRP GLN LEU TYR PRO GLU GLU ARG TYR
SEQRES 7 A 108 MET ASP ASN ASN SER ARG LEU TRP GLN ILE GLN HIS HIS
SEQRES 8 A 108 LEU MET VAL ARG GLY VAL GLN GLU LEU LEU LEU LYS LEU
SEQRES 9 A 108 LEU PRO ASP ASP
FORMUL 2 HOH *24(H2 O)
HELIX 1 1 PRO A 58 THR A 63 1 6
SHEET 1 A 9 HIS A 13 TRP A 15 0
SHEET 2 A 9 MET A 69 TYR A 73 -1 N TRP A 70 O LEU A 14
SHEET 3 A 9 ARG A 77 ASP A 80 -1 N MET A 79 O GLN A 71
SHEET 4 A 9 LEU A 85 VAL A 94 -1 N TRP A 86 O TYR A 78
SHEET 5 A 9 VAL A 97 LEU A 104 -1 N LYS A 103 O GLN A 87
SHEET 6 A 9 LEU A 41 GLN A 46 -1 N VAL A 45 O LEU A 100
SHEET 7 A 9 THR A 29 GLU A 36 -1 N GLU A 35 O ARG A 42
SHEET 8 A 9 ILE A 21 ASP A 24 -1 N TYR A 22 O TRP A 30
SHEET 9 A 9 LEU A 14 GLN A 18 -1 N GLN A 18 O ILE A 21
CRYST1 62.665 62.665 85.962 90.00 90.00 120.00 P 62 2 2 12
ORIGX1 1.000000 0.000000 0.000000 0.00000
ORIGX2 0.000000 1.000000 0.000000 0.00000
ORIGX3 0.000000 0.000000 1.000000 0.00000
SCALE1 0.015958 0.009213 0.000000 0.00000
SCALE2 0.000000 0.018427 0.000000 0.00000
SCALE3 0.000000 0.000000 0.011633 0.00000
ATOM 1 N ALA A 3 9.430 27.207 36.902 1.00 32.66 N
ATOM 2 CA ALA A 3 9.560 25.910 36.169 1.00 36.84 C
ATOM 3 C ALA A 3 8.771 24.851 36.930 1.00 35.55 C
ATOM 4 O ALA A 3 9.268 24.262 37.891 1.00 34.17 O
ATOM 5 CB ALA A 3 11.037 25.499 36.056 1.00 38.15 C
ATOM 6 N GLY A 4 7.541 24.611 36.486 1.00 34.63 N
ATOM 7 CA GLY A 4 6.682 23.653 37.152 1.00 32.01 C
ATOM 8 C GLY A 4 5.852 24.387 38.180 1.00 33.93 C
ATOM 9 O GLY A 4 5.178 23.764 38.988 1.00 34.34 O
ATOM 10 N GLU A 5 5.912 25.720 38.137 1.00 34.69 N
ATOM 11 CA GLU A 5 5.178 26.594 39.057 1.00 33.67 C
ATOM 12 C GLU A 5 4.090 27.381 38.346 1.00 36.27 C
ATOM 13 O GLU A 5 4.075 27.480 37.119 1.00 36.32 O
ATOM 14 CB GLU A 5 6.118 27.622 39.703 1.00 30.77 C
ATOM 15 CG GLU A 5 7.142 27.082 40.685 1.00 26.98 C
ATOM 16 CD GLU A 5 6.539 26.635 42.002 1.00 21.88 C
ATOM 17 OE1 GLU A 5 5.872 27.449 42.666 1.00 17.97 O
ATOM 18 OE2 GLU A 5 6.758 25.472 42.387 1.00 23.83 O
ATOM 19 N ASP A 6 3.211 27.969 39.153 1.00 39.47 N
ATOM 20 CA ASP A 6 2.109 28.817 38.696 1.00 43.46 C
ATOM 21 C ASP A 6 2.241 30.130 39.484 1.00 43.77 C
ATOM 22 O ASP A 6 1.246 30.733 39.884 1.00 47.03 O
ATOM 23 CB ASP A 6 0.747 28.163 39.003 1.00 47.84 C
ATOM 24 CG ASP A 6 0.395 27.031 38.041 1.00 51.43 C
ATOM 25 OD1 ASP A 6 -0.030 27.329 36.900 1.00 51.13 O
ATOM 26 OD2 ASP A 6 0.514 25.846 38.435 1.00 54.02 O
ATOM 27 N VAL A 7 3.485 30.551 39.715 1.00 43.28 N
ATOM 28 CA VAL A 7 3.794 31.769 40.475 1.00 38.90 C
ATOM 29 C VAL A 7 3.660 33.042 39.640 1.00 39.82 C
ATOM 30 O VAL A 7 3.479 34.133 40.182 1.00 42.59 O
ATOM 31 CB VAL A 7 5.221 31.694 41.099 1.00 34.86 C
ATOM 32 CG1 VAL A 7 6.279 31.737 40.015 1.00 29.95 C
ATOM 33 CG2 VAL A 7 5.433 32.803 42.110 1.00 30.38 C
ATOM 34 N GLY A 8 3.756 32.898 38.322 1.00 36.52 N
ATOM 35 CA GLY A 8 3.627 34.047 37.445 1.00 33.02 C
ATOM 36 C GLY A 8 4.917 34.810 37.234 1.00 33.14 C
ATOM 37 O GLY A 8 6.006 34.305 37.530 1.00 35.75 O
ATOM 38 N ALA A 9 4.783 36.045 36.753 1.00 28.39 N
ATOM 39 CA ALA A 9 5.935 36.896 36.465 1.00 23.88 C
ATOM 40 C ALA A 9 6.555 37.588 37.676 1.00 19.87 C
ATOM 41 O ALA A 9 5.860 37.951 38.633 1.00 18.30 O
ATOM 42 CB ALA A 9 5.568 37.933 35.408 1.00 23.25 C
ATOM 43 N PRO A 10 7.890 37.735 37.665 1.00 18.90 N
ATOM 44 CA PRO A 10 8.609 38.392 38.759 1.00 18.82 C
ATOM 45 C PRO A 10 8.400 39.897 38.649 1.00 16.65 C
ATOM 46 O PRO A 10 7.968 40.387 37.605 1.00 16.16 O
ATOM 47 CB PRO A 10 10.066 38.001 38.486 1.00 16.22 C
ATOM 48 CG PRO A 10 10.112 37.875 37.016 1.00 17.71 C
ATOM 49 CD PRO A 10 8.839 37.128 36.714 1.00 18.47 C
ATOM 50 N PRO A 11 8.648 40.644 39.738 1.00 17.77 N
ATOM 51 CA PRO A 11 8.460 42.095 39.656 1.00 17.80 C
ATOM 52 C PRO A 11 9.399 42.773 38.655 1.00 16.54 C
ATOM 53 O PRO A 11 10.559 42.395 38.513 1.00 16.67 O
ATOM 54 CB PRO A 11 8.721 42.560 41.095 1.00 15.87 C
ATOM 55 CG PRO A 11 9.636 41.536 41.635 1.00 13.61 C
ATOM 56 CD PRO A 11 9.046 40.248 41.100 1.00 15.18 C
ATOM 57 N ASP A 12 8.854 43.737 37.920 1.00 18.08 N
ATOM 58 CA ASP A 12 9.603 44.511 36.940 1.00 17.00 C
ATOM 59 C ASP A 12 10.733 45.280 37.635 1.00 15.91 C
ATOM 60 O ASP A 12 11.806 45.497 37.066 1.00 15.96 O
ATOM 61 CB ASP A 12 8.648 45.466 36.226 1.00 23.98 C
ATOM 62 CG ASP A 12 9.368 46.493 35.406 1.00 34.63 C
ATOM 63 OD1 ASP A 12 10.050 46.108 34.427 1.00 42.77 O
ATOM 64 OD2 ASP A 12 9.262 47.688 35.758 1.00 42.27 O
ATOM 65 N HIS A 13 10.470 45.715 38.860 1.00 16.48 N
ATOM 66 CA HIS A 13 11.475 46.421 39.641 1.00 17.19 C
ATOM 67 C HIS A 13 11.238 46.393 41.146 1.00 16.91 C
ATOM 68 O HIS A 13 10.117 46.152 41.627 1.00 15.83 O
ATOM 69 CB HIS A 13 11.674 47.856 39.139 1.00 25.37 C
ATOM 70 CG HIS A 13 10.460 48.722 39.244 1.00 29.62 C
ATOM 71 ND1 HIS A 13 9.757 49.149 38.137 1.00 33.44 N
ATOM 72 CD2 HIS A 13 9.865 49.299 40.316 1.00 32.29 C
ATOM 73 CE1 HIS A 13 8.785 49.958 38.523 1.00 34.91 C
ATOM 74 NE2 HIS A 13 8.829 50.067 39.840 1.00 32.19 N
ATOM 75 N LEU A 14 12.329 46.579 41.883 1.00 13.14 N
ATOM 76 CA LEU A 14 12.301 46.599 43.336 1.00 13.46 C
ATOM 77 C LEU A 14 13.125 47.791 43.804 1.00 16.02 C
ATOM 78 O LEU A 14 14.309 47.905 43.477 1.00 16.65 O
ATOM 79 CB LEU A 14 12.883 45.300 43.886 1.00 15.55 C
ATOM 80 CG LEU A 14 12.020 44.066 43.607 1.00 18.25 C
ATOM 81 CD1 LEU A 14 12.834 42.786 43.691 1.00 20.49 C
ATOM 82 CD2 LEU A 14 10.870 44.050 44.581 1.00 15.43 C
ATOM 83 N TRP A 15 12.472 48.712 44.506 1.00 17.72 N
ATOM 84 CA TRP A 15 13.135 49.902 45.014 1.00 14.75 C
ATOM 85 C TRP A 15 13.231 49.777 46.525 1.00 12.21 C
ATOM 86 O TRP A 15 12.233 49.528 47.190 1.00 13.12 O
ATOM 87 CB TRP A 15 12.339 51.172 44.677 1.00 21.09 C
ATOM 88 CG TRP A 15 12.285 51.581 43.224 1.00 31.43 C
ATOM 89 CD1 TRP A 15 11.213 51.476 42.387 1.00 38.00 C
ATOM 90 CD2 TRP A 15 13.305 52.258 42.478 1.00 38.37 C
ATOM 91 NE1 TRP A 15 11.495 52.056 41.173 1.00 40.79 N
ATOM 92 CE2 TRP A 15 12.773 52.543 41.203 1.00 40.40 C
ATOM 93 CE3 TRP A 15 14.618 52.658 42.767 1.00 45.21 C
ATOM 94 CZ2 TRP A 15 13.507 53.213 40.214 1.00 48.64 C
ATOM 95 CZ3 TRP A 15 15.353 53.329 41.778 1.00 48.47 C
ATOM 96 CH2 TRP A 15 14.792 53.598 40.522 1.00 50.70 C
ATOM 97 N VAL A 16 14.431 49.977 47.061 1.00 9.84 N
ATOM 98 CA VAL A 16 14.671 49.900 48.495 1.00 9.61 C
ATOM 99 C VAL A 16 13.919 51.007 49.246 1.00 11.80 C
ATOM 100 O VAL A 16 13.683 52.103 48.708 1.00 11.41 O
ATOM 101 CB VAL A 16 16.199 50.006 48.794 1.00 9.84 C
ATOM 102 CG1 VAL A 16 16.706 51.412 48.526 1.00 11.99 C
ATOM 103 CG2 VAL A 16 16.504 49.582 50.204 1.00 13.17 C
ATOM 104 N HIS A 17 13.464 50.686 50.451 1.00 11.23 N
ATOM 105 CA HIS A 17 12.779 51.667 51.289 1.00 12.50 C
ATOM 106 C HIS A 17 13.635 51.843 52.530 1.00 11.56 C
ATOM 107 O HIS A 17 14.045 52.952 52.892 1.00 15.66 O
ATOM 108 CB HIS A 17 11.392 51.190 51.693 1.00 8.81 C
ATOM 109 CG HIS A 17 10.611 52.228 52.424 1.00 12.32 C
ATOM 110 ND1 HIS A 17 10.009 53.286 51.782 1.00 16.44 N
ATOM 111 CD2 HIS A 17 10.406 52.422 53.745 1.00 12.87 C
ATOM 112 CE1 HIS A 17 9.470 54.092 52.677 1.00 16.27 C
ATOM 113 NE2 HIS A 17 9.698 53.590 53.877 1.00 18.21 N
ATOM 114 N GLN A 18 13.916 50.709 53.152 1.00 14.35 N
ATOM 115 CA GLN A 18 14.740 50.621 54.333 1.00 15.00 C
ATOM 116 C GLN A 18 15.655 49.445 54.024 1.00 14.65 C
ATOM 117 O GLN A 18 15.330 48.620 53.166 1.00 15.16 O
ATOM 118 CB GLN A 18 13.859 50.309 55.531 1.00 25.19 C
ATOM 119 CG GLN A 18 14.554 50.392 56.852 1.00 37.43 C
ATOM 120 CD GLN A 18 13.623 50.070 57.994 1.00 42.68 C
ATOM 121 OE1 GLN A 18 13.239 48.912 58.186 1.00 45.28 O
ATOM 122 NE2 GLN A 18 13.250 51.094 58.764 1.00 41.38 N
ATOM 123 N GLU A 19 16.794 49.366 54.701 1.00 12.93 N
ATOM 124 CA GLU A 19 17.742 48.280 54.469 1.00 16.07 C
ATOM 125 C GLU A 19 17.025 46.937 54.491 1.00 11.82 C
ATOM 126 O GLU A 19 16.378 46.601 55.475 1.00 13.21 O
ATOM 127 CB GLU A 19 18.836 48.293 55.548 1.00 19.28 C
ATOM 128 CG GLU A 19 20.275 48.282 55.018 1.00 31.93 C
ATOM 129 CD GLU A 19 20.785 46.893 54.672 1.00 36.30 C
ATOM 130 OE1 GLU A 19 20.530 46.406 53.549 1.00 43.02 O
ATOM 131 OE2 GLU A 19 21.462 46.292 55.527 1.00 41.71 O
ATOM 132 N GLY A 20 17.087 46.212 53.380 1.00 9.32 N
ATOM 133 CA GLY A 20 16.446 44.910 53.306 1.00 10.78 C
ATOM 134 C GLY A 20 14.967 44.868 52.953 1.00 12.37 C
ATOM 135 O GLY A 20 14.415 43.779 52.759 1.00 11.40 O
ATOM 136 N ILE A 21 14.310 46.028 52.900 1.00 11.21 N
ATOM 137 CA ILE A 21 12.892 46.071 52.553 1.00 11.81 C
ATOM 138 C ILE A 21 12.714 46.872 51.274 1.00 13.84 C
ATOM 139 O ILE A 21 13.095 48.043 51.192 1.00 12.70 O
ATOM 140 CB ILE A 21 12.025 46.652 53.693 1.00 11.59 C
ATOM 141 CG1 ILE A 21 12.224 45.832 54.967 1.00 15.04 C
ATOM 142 CG2 ILE A 21 10.528 46.603 53.308 1.00 16.33 C
ATOM 143 CD1 ILE A 21 11.451 46.351 56.168 1.00 22.83 C
ATOM 144 N TYR A 22 12.169 46.202 50.266 1.00 10.11 N
ATOM 145 CA TYR A 22 11.950 46.777 48.958 1.00 11.86 C
ATOM 146 C TYR A 22 10.471 46.880 48.634 1.00 14.44 C
ATOM 147 O TYR A 22 9.631 46.292 49.307 1.00 17.52 O
ATOM 148 CB TYR A 22 12.627 45.892 47.902 1.00 8.92 C
ATOM 149 CG TYR A 22 14.139 45.866 48.001 1.00 8.62 C
ATOM 150 CD1 TYR A 22 14.785 45.139 49.005 1.00 10.70 C
ATOM 151 CD2 TYR A 22 14.922 46.599 47.115 1.00 6.29 C
ATOM 152 CE1 TYR A 22 16.175 45.155 49.120 1.00 13.66 C
ATOM 153 CE2 TYR A 22 16.305 46.622 47.219 1.00 6.68 C
ATOM 154 CZ TYR A 22 16.925 45.902 48.221 1.00 8.01 C
ATOM 155 OH TYR A 22 18.292 45.938 48.326 1.00 14.82 O
ATOM 156 N ARG A 23 10.165 47.624 47.580 1.00 16.60 N
ATOM 157 CA ARG A 23 8.795 47.780 47.097 1.00 18.95 C
ATOM 158 C ARG A 23 8.796 47.633 45.575 1.00 15.47 C
ATOM 159 O ARG A 23 9.690 48.150 44.905 1.00 14.40 O
ATOM 160 CB ARG A 23 8.221 49.138 47.497 1.00 21.56 C
ATOM 161 CG ARG A 23 7.813 49.224 48.949 1.00 33.66 C
ATOM 162 CD ARG A 23 6.893 50.401 49.176 1.00 36.15 C
ATOM 163 NE ARG A 23 7.556 51.660 48.866 1.00 38.83 N
ATOM 164 CZ ARG A 23 7.224 52.829 49.402 1.00 45.05 C
ATOM 165 NH1 ARG A 23 6.229 52.903 50.282 1.00 46.49 N
ATOM 166 NH2 ARG A 23 7.899 53.923 49.069 1.00 46.39 N
ATOM 167 N ASP A 24 7.824 46.904 45.033 1.00 15.56 N
ATOM 168 CA ASP A 24 7.751 46.703 43.588 1.00 15.72 C
ATOM 169 C ASP A 24 6.818 47.714 42.934 1.00 14.47 C
ATOM 170 O ASP A 24 6.343 48.640 43.588 1.00 14.11 O
ATOM 171 CB ASP A 24 7.346 45.256 43.239 1.00 14.43 C
ATOM 172 CG ASP A 24 5.984 44.855 43.801 1.00 15.26 C
ATOM 173 OD1 ASP A 24 5.147 45.727 44.070 1.00 11.84 O
ATOM 174 OD2 ASP A 24 5.738 43.649 43.967 1.00 18.06 O
ATOM 175 N GLU A 25 6.554 47.529 41.650 1.00 14.92 N
ATOM 176 CA GLU A 25 5.680 48.429 40.904 1.00 17.73 C
ATOM 177 C GLU A 25 4.238 48.519 41.430 1.00 20.50 C
ATOM 178 O GLU A 25 3.505 49.436 41.066 1.00 22.81 O
ATOM 179 CB GLU A 25 5.652 48.021 39.435 1.00 18.41 C
ATOM 180 CG GLU A 25 5.109 46.612 39.187 1.00 19.84 C
ATOM 181 CD GLU A 25 6.198 45.564 39.068 1.00 21.17 C
ATOM 182 OE1 GLU A 25 7.249 45.697 39.736 1.00 16.47 O
ATOM 183 OE2 GLU A 25 5.994 44.602 38.298 1.00 18.38 O
ATOM 184 N TYR A 26 3.834 47.561 42.265 1.00 19.79 N
ATOM 185 CA TYR A 26 2.488 47.528 42.843 1.00 21.31 C
ATOM 186 C TYR A 26 2.441 48.038 44.276 1.00 22.08 C
ATOM 187 O TYR A 26 1.401 47.937 44.933 1.00 25.79 O
ATOM 188 CB TYR A 26 1.937 46.108 42.830 1.00 17.73 C
ATOM 189 CG TYR A 26 1.869 45.496 41.466 1.00 23.02 C
ATOM 190 CD1 TYR A 26 1.336 46.203 40.393 1.00 20.72 C
ATOM 191 CD2 TYR A 26 2.335 44.205 41.242 1.00 26.28 C
ATOM 192 CE1 TYR A 26 1.269 45.640 39.127 1.00 23.56 C
ATOM 193 CE2 TYR A 26 2.272 43.629 39.977 1.00 28.23 C
ATOM 194 CZ TYR A 26 1.740 44.353 38.927 1.00 26.06 C
ATOM 195 OH TYR A 26 1.681 43.801 37.672 1.00 30.94 O
ATOM 196 N GLN A 27 3.567 48.563 44.759 1.00 20.91 N
ATOM 197 CA GLN A 27 3.694 49.077 46.126 1.00 23.01 C
ATOM 198 C GLN A 27 3.722 47.972 47.180 1.00 20.14 C
ATOM 199 O GLN A 27 3.596 48.237 48.373 1.00 19.46 O
ATOM 200 CB GLN A 27 2.581 50.077 46.454 1.00 28.90 C
ATOM 201 CG GLN A 27 2.663 51.391 45.694 1.00 36.12 C
ATOM 202 CD GLN A 27 1.415 52.238 45.891 1.00 42.43 C
ATOM 203 OE1 GLN A 27 0.546 52.304 45.009 1.00 43.99 O
ATOM 204 NE2 GLN A 27 1.303 52.870 47.063 1.00 45.23 N
ATOM 205 N ARG A 28 3.878 46.731 46.735 1.00 17.12 N
ATOM 206 CA ARG A 28 3.953 45.605 47.650 1.00 15.88 C
ATOM 207 C ARG A 28 5.370 45.522 48.209 1.00 14.06 C
ATOM 208 O ARG A 28 6.345 45.813 47.514 1.00 11.98 O
ATOM 209 CB ARG A 28 3.613 44.308 46.925 1.00 15.62 C
ATOM 210 CG ARG A 28 2.188 44.240 46.440 1.00 15.16 C
ATOM 211 CD ARG A 28 1.945 42.941 45.743 1.00 18.63 C
ATOM 212 NE ARG A 28 2.935 42.734 44.697 1.00 21.42 N
ATOM 213 CZ ARG A 28 3.028 41.633 43.963 1.00 26.57 C
ATOM 214 NH1 ARG A 28 2.183 40.626 44.161 1.00 29.04 N
ATOM 215 NH2 ARG A 28 3.971 41.536 43.033 1.00 28.28 N
ATOM 216 N THR A 29 5.482 45.146 49.475 1.00 12.54 N
ATOM 217 CA THR A 29 6.791 45.039 50.098 1.00 14.08 C
ATOM 218 C THR A 29 7.409 43.646 49.966 1.00 13.70 C
ATOM 219 O THR A 29 6.709 42.630 49.943 1.00 11.99 O
ATOM 220 CB THR A 29 6.752 45.457 51.579 1.00 13.34 C
ATOM 221 OG1 THR A 29 5.743 44.712 52.259 1.00 12.89 O
ATOM 222 CG2 THR A 29 6.454 46.935 51.707 1.00 17.38 C
ATOM 223 N TRP A 30 8.729 43.627 49.823 1.00 12.04 N
ATOM 224 CA TRP A 30 9.507 42.404 49.701 1.00 8.73 C
ATOM 225 C TRP A 30 10.625 42.509 50.717 1.00 10.06 C
ATOM 226 O TRP A 30 11.212 43.577 50.872 1.00 12.46 O
ATOM 227 CB TRP A 30 10.117 42.310 48.314 1.00 9.80 C
ATOM 228 CG TRP A 30 9.145 42.015 47.236 1.00 11.47 C
ATOM 229 CD1 TRP A 30 8.245 42.881 46.681 1.00 13.90 C
ATOM 230 CD2 TRP A 30 8.989 40.772 46.543 1.00 10.96 C
ATOM 231 NE1 TRP A 30 7.542 42.254 45.683 1.00 13.05 N
ATOM 232 CE2 TRP A 30 7.978 40.958 45.575 1.00 12.91 C
ATOM 233 CE3 TRP A 30 9.607 39.518 46.643 1.00 8.88 C
ATOM 234 CZ2 TRP A 30 7.571 39.937 44.708 1.00 12.83 C
ATOM 235 CZ3 TRP A 30 9.203 38.501 45.776 1.00 8.59 C
ATOM 236 CH2 TRP A 30 8.195 38.720 44.823 1.00 10.12 C
ATOM 237 N VAL A 31 10.879 41.433 51.455 1.00 10.56 N
ATOM 238 CA VAL A 31 11.948 41.421 52.452 1.00 9.81 C
ATOM 239 C VAL A 31 13.123 40.644 51.863 1.00 13.48 C
ATOM 240 O VAL A 31 12.961 39.500 51.413 1.00 14.18 O
ATOM 241 CB VAL A 31 11.490 40.749 53.777 1.00 11.63 C
ATOM 242 CG1 VAL A 31 12.655 40.641 54.748 1.00 13.21 C
ATOM 243 CG2 VAL A 31 10.353 41.548 54.416 1.00 13.94 C
ATOM 244 N ALA A 32 14.295 41.272 51.842 1.00 12.15 N
ATOM 245 CA ALA A 32 15.483 40.632 51.293 1.00 11.67 C
ATOM 246 C ALA A 32 16.520 40.285 52.353 1.00 13.21 C
ATOM 247 O ALA A 32 16.853 41.109 53.202 1.00 12.93 O
ATOM 248 CB ALA A 32 16.105 41.507 50.209 1.00 9.35 C
ATOM 249 N VAL A 33 17.004 39.046 52.308 1.00 10.78 N
ATOM 250 CA VAL A 33 18.021 38.593 53.236 1.00 11.43 C
ATOM 251 C VAL A 33 19.234 38.106 52.451 1.00 13.65 C
ATOM 252 O VAL A 33 19.106 37.604 51.335 1.00 14.89 O
ATOM 253 CB VAL A 33 17.524 37.454 54.182 1.00 11.64 C
ATOM 254 CG1 VAL A 33 16.376 37.938 55.045 1.00 15.29 C
ATOM 255 CG2 VAL A 33 17.130 36.213 53.396 1.00 15.10 C
ATOM 256 N VAL A 34 20.414 38.291 53.033 1.00 14.86 N
ATOM 257 CA VAL A 34 21.646 37.861 52.398 1.00 14.07 C
ATOM 258 C VAL A 34 22.019 36.455 52.849 1.00 10.75 C
ATOM 259 O VAL A 34 21.917 36.128 54.024 1.00 12.88 O
ATOM 260 CB VAL A 34 22.833 38.825 52.725 1.00 13.34 C
ATOM 261 CG1 VAL A 34 24.138 38.293 52.108 1.00 17.43 C
ATOM 262 CG2 VAL A 34 22.546 40.230 52.203 1.00 10.34 C
ATOM 263 N GLU A 35 22.381 35.615 51.888 1.00 13.04 N
ATOM 264 CA GLU A 35 22.835 34.252 52.161 1.00 15.26 C
ATOM 265 C GLU A 35 24.138 34.116 51.384 1.00 15.10 C
ATOM 266 O GLU A 35 24.164 33.746 50.214 1.00 14.57 O
ATOM 267 CB GLU A 35 21.794 33.246 51.716 1.00 13.76 C
ATOM 268 CG GLU A 35 20.471 33.523 52.377 1.00 22.79 C
ATOM 269 CD GLU A 35 19.466 32.421 52.186 1.00 25.07 C
ATOM 270 OE1 GLU A 35 19.432 31.844 51.076 1.00 29.90 O
ATOM 271 OE2 GLU A 35 18.710 32.142 53.149 1.00 26.94 O
ATOM 272 N GLU A 36 25.219 34.495 52.045 1.00 18.73 N
ATOM 273 CA GLU A 36 26.538 34.495 51.446 1.00 23.19 C
ATOM 274 C GLU A 36 27.283 33.164 51.426 1.00 23.70 C
ATOM 275 O GLU A 36 27.430 32.499 52.452 1.00 27.43 O
ATOM 276 CB GLU A 36 27.376 35.547 52.148 1.00 22.75 C
ATOM 277 CG GLU A 36 28.673 35.866 51.466 1.00 31.51 C
ATOM 278 CD GLU A 36 29.457 36.917 52.210 1.00 34.90 C
ATOM 279 OE1 GLU A 36 28.839 37.748 52.915 1.00 40.64 O
ATOM 280 OE2 GLU A 36 30.698 36.904 52.094 1.00 37.73 O
ATOM 281 N GLU A 37 27.721 32.768 50.234 1.00 23.31 N
ATOM 282 CA GLU A 37 28.492 31.541 50.059 1.00 21.82 C
ATOM 283 C GLU A 37 29.966 31.943 50.125 1.00 23.97 C
ATOM 284 O GLU A 37 30.283 33.116 50.356 1.00 26.06 O
ATOM 285 CB GLU A 37 28.176 30.902 48.702 1.00 24.57 C
ATOM 286 CG GLU A 37 26.700 30.564 48.489 1.00 26.70 C
ATOM 287 CD GLU A 37 26.165 29.566 49.496 1.00 26.82 C
ATOM 288 OE1 GLU A 37 26.893 28.607 49.822 1.00 30.00 O
ATOM 289 OE2 GLU A 37 25.013 29.739 49.957 1.00 34.57 O
ATOM 290 N THR A 38 30.869 30.987 49.923 1.00 22.64 N
ATOM 291 CA THR A 38 32.303 31.288 49.966 1.00 21.52 C
ATOM 292 C THR A 38 32.760 32.121 48.760 1.00 19.63 C
ATOM 293 O THR A 38 33.459 33.131 48.899 1.00 19.04 O
ATOM 294 CB THR A 38 33.157 29.991 50.014 1.00 18.09 C
ATOM 295 OG1 THR A 38 32.874 29.271 51.216 1.00 21.23 O
ATOM 296 CG2 THR A 38 34.640 30.326 49.983 1.00 20.54 C
ATOM 297 N SER A 39 32.320 31.703 47.585 1.00 17.14 N
ATOM 298 CA SER A 39 32.705 32.346 46.353 1.00 20.78 C
ATOM 299 C SER A 39 31.734 33.376 45.810 1.00 21.63 C
ATOM 300 O SER A 39 32.076 34.109 44.886 1.00 19.37 O
ATOM 301 CB SER A 39 32.952 31.274 45.308 1.00 21.56 C
ATOM 302 OG SER A 39 33.744 30.251 45.882 1.00 26.38 O
ATOM 303 N PHE A 40 30.524 33.436 46.358 1.00 22.41 N
ATOM 304 CA PHE A 40 29.545 34.404 45.860 1.00 19.83 C
ATOM 305 C PHE A 40 28.464 34.754 46.864 1.00 17.95 C
ATOM 306 O PHE A 40 28.410 34.213 47.971 1.00 14.28 O
ATOM 307 CB PHE A 40 28.905 33.921 44.546 1.00 19.37 C
ATOM 308 CG PHE A 40 28.293 32.570 44.650 1.00 25.11 C
ATOM 309 CD1 PHE A 40 29.058 31.434 44.424 1.00 29.88 C
ATOM 310 CD2 PHE A 40 26.972 32.423 45.044 1.00 26.71 C
ATOM 311 CE1 PHE A 40 28.513 30.159 44.598 1.00 32.01 C
ATOM 312 CE2 PHE A 40 26.419 31.156 45.219 1.00 30.64 C
ATOM 313 CZ PHE A 40 27.193 30.021 44.997 1.00 28.16 C
ATOM 314 N LEU A 41 27.578 35.645 46.436 1.00 16.59 N
ATOM 315 CA LEU A 41 26.498 36.110 47.272 1.00 11.19 C
ATOM 316 C LEU A 41 25.134 35.890 46.639 1.00 10.44 C
ATOM 317 O LEU A 41 24.955 36.052 45.431 1.00 6.65 O
ATOM 318 CB LEU A 41 26.718 37.590 47.570 1.00 15.40 C
ATOM 319 CG LEU A 41 25.764 38.265 48.542 1.00 17.96 C
ATOM 320 CD1 LEU A 41 26.560 39.122 49.509 1.00 22.78 C
ATOM 321 CD2 LEU A 41 24.742 39.076 47.781 1.00 17.63 C
ATOM 322 N ARG A 42 24.189 35.475 47.472 1.00 9.43 N
ATOM 323 CA ARG A 42 22.810 35.248 47.058 1.00 12.78 C
ATOM 324 C ARG A 42 21.896 36.091 47.942 1.00 10.33 C
ATOM 325 O ARG A 42 22.240 36.417 49.077 1.00 13.14 O
ATOM 326 CB ARG A 42 22.407 33.772 47.218 1.00 10.56 C
ATOM 327 CG ARG A 42 22.983 32.814 46.171 1.00 13.78 C
ATOM 328 CD ARG A 42 22.105 31.557 46.035 1.00 15.67 C
ATOM 329 NE ARG A 42 22.758 30.495 45.267 1.00 15.51 N
ATOM 330 CZ ARG A 42 23.399 29.456 45.799 1.00 12.10 C
ATOM 331 NH1 ARG A 42 23.481 29.314 47.114 1.00 11.66 N
ATOM 332 NH2 ARG A 42 23.978 28.561 45.013 1.00 13.24 N
ATOM 333 N ALA A 43 20.754 36.483 47.396 1.00 10.52 N
ATOM 334 CA ALA A 43 19.769 37.244 48.148 1.00 9.84 C
ATOM 335 C ALA A 43 18.465 36.478 47.999 1.00 8.98 C
ATOM 336 O ALA A 43 18.105 36.083 46.903 1.00 12.92 O
ATOM 337 CB ALA A 43 19.622 38.647 47.585 1.00 8.83 C
ATOM 338 N ARG A 44 17.814 36.185 49.114 1.00 8.69 N
ATOM 339 CA ARG A 44 16.542 35.481 49.087 1.00 9.60 C
ATOM 340 C ARG A 44 15.524 36.573 49.385 1.00 8.62 C
ATOM 341 O ARG A 44 15.603 37.242 50.409 1.00 15.33 O
ATOM 342 CB ARG A 44 16.518 34.378 50.144 1.00 8.69 C
ATOM 343 CG ARG A 44 15.315 33.456 50.048 1.00 11.48 C
ATOM 344 CD ARG A 44 15.657 32.081 50.596 1.00 14.85 C
ATOM 345 NE ARG A 44 16.129 32.153 51.969 1.00 20.01 N
ATOM 346 CZ ARG A 44 15.340 32.179 53.038 1.00 25.11 C
ATOM 347 NH1 ARG A 44 14.021 32.138 52.904 1.00 28.22 N
ATOM 348 NH2 ARG A 44 15.878 32.232 54.246 1.00 25.52 N
ATOM 349 N VAL A 45 14.621 36.805 48.443 1.00 11.50 N
ATOM 350 CA VAL A 45 13.641 37.875 48.581 1.00 12.07 C
ATOM 351 C VAL A 45 12.228 37.313 48.583 1.00 12.67 C
ATOM 352 O VAL A 45 11.825 36.616 47.648 1.00 13.12 O
ATOM 353 CB VAL A 45 13.792 38.915 47.421 1.00 12.86 C
ATOM 354 CG1 VAL A 45 13.174 40.231 47.812 1.00 12.39 C
ATOM 355 CG2 VAL A 45 15.270 39.105 47.038 1.00 10.08 C
ATOM 356 N GLN A 46 11.487 37.623 49.644 1.00 9.87 N
ATOM 357 CA GLN A 46 10.119 37.152 49.799 1.00 12.52 C
ATOM 358 C GLN A 46 9.104 38.285 49.902 1.00 12.60 C
ATOM 359 O GLN A 46 9.328 39.284 50.596 1.00 10.34 O
ATOM 360 CB GLN A 46 10.004 36.250 51.033 1.00 12.62 C
ATOM 361 CG GLN A 46 10.774 34.950 50.921 1.00 16.77 C
ATOM 362 CD GLN A 46 10.550 34.052 52.113 1.00 19.44 C
ATOM 363 OE1 GLN A 46 9.951 34.464 53.097 1.00 17.87 O
ATOM 364 NE2 GLN A 46 11.032 32.813 52.031 1.00 14.24 N
ATOM 365 N GLN A 47 7.973 38.099 49.226 1.00 12.30 N
ATOM 366 CA GLN A 47 6.898 39.081 49.222 1.00 11.62 C
ATOM 367 C GLN A 47 6.063 38.904 50.483 1.00 13.03 C
ATOM 368 O GLN A 47 5.170 38.058 50.551 1.00 14.19 O
ATOM 369 CB GLN A 47 6.035 38.924 47.962 1.00 9.85 C
ATOM 370 CG GLN A 47 5.328 40.201 47.516 1.00 12.95 C
ATOM 371 CD GLN A 47 4.119 40.524 48.362 1.00 18.42 C
ATOM 372 OE1 GLN A 47 3.034 39.995 48.118 1.00 19.94 O
ATOM 373 NE2 GLN A 47 4.291 41.385 49.363 1.00 15.59 N
ATOM 374 N ILE A 48 6.416 39.681 51.496 1.00 12.27 N
ATOM 375 CA ILE A 48 5.734 39.664 52.776 1.00 11.76 C
ATOM 376 C ILE A 48 5.372 41.099 53.135 1.00 15.46 C
ATOM 377 O ILE A 48 6.188 42.016 52.976 1.00 15.44 O
ATOM 378 CB ILE A 48 6.644 39.064 53.879 1.00 15.37 C
ATOM 379 CG1 ILE A 48 7.000 37.610 53.527 1.00 14.45 C
ATOM 380 CG2 ILE A 48 5.959 39.148 55.258 1.00 16.12 C
ATOM 381 CD1 ILE A 48 7.998 36.954 54.484 1.00 19.15 C
ATOM 382 N GLN A 49 4.133 41.283 53.583 1.00 16.14 N
ATOM 383 CA GLN A 49 3.612 42.583 53.999 1.00 18.88 C
ATOM 384 C GLN A 49 4.245 42.997 55.334 1.00 16.77 C
ATOM 385 O GLN A 49 4.066 42.334 56.353 1.00 16.00 O
ATOM 386 CB GLN A 49 2.094 42.483 54.142 1.00 21.86 C
ATOM 387 CG GLN A 49 1.383 43.776 54.494 1.00 34.69 C
ATOM 388 CD GLN A 49 -0.130 43.613 54.473 1.00 42.01 C
ATOM 389 OE1 GLN A 49 -0.727 43.320 53.424 1.00 43.27 O
ATOM 390 NE2 GLN A 49 -0.758 43.780 55.634 1.00 41.30 N
ATOM 391 N VAL A 50 5.059 44.045 55.307 1.00 15.30 N
ATOM 392 CA VAL A 50 5.709 44.526 56.522 1.00 16.37 C
ATOM 393 C VAL A 50 5.416 46.010 56.671 1.00 18.04 C
ATOM 394 O VAL A 50 5.025 46.664 55.706 1.00 16.50 O
ATOM 395 CB VAL A 50 7.245 44.294 56.494 1.00 18.68 C
ATOM 396 CG1 VAL A 50 7.555 42.809 56.528 1.00 19.50 C
ATOM 397 CG2 VAL A 50 7.866 44.930 55.263 1.00 16.54 C
ATOM 398 N PRO A 51 5.549 46.553 57.891 1.00 18.12 N
ATOM 399 CA PRO A 51 5.277 47.980 58.078 1.00 19.86 C
ATOM 400 C PRO A 51 6.349 48.814 57.409 1.00 21.43 C
ATOM 401 O PRO A 51 7.467 48.344 57.174 1.00 19.19 O
ATOM 402 CB PRO A 51 5.325 48.138 59.598 1.00 24.01 C
ATOM 403 CG PRO A 51 6.338 47.123 60.009 1.00 25.48 C
ATOM 404 CD PRO A 51 5.949 45.926 59.163 1.00 18.27 C
ATOM 405 N LEU A 52 5.983 50.029 57.038 1.00 19.15 N
ATOM 406 CA LEU A 52 6.928 50.937 56.414 1.00 21.07 C
ATOM 407 C LEU A 52 6.986 52.187 57.266 1.00 22.46 C
ATOM 408 O LEU A 52 5.951 52.728 57.656 1.00 27.86 O
ATOM 409 CB LEU A 52 6.492 51.308 54.996 1.00 21.76 C
ATOM 410 CG LEU A 52 6.588 50.224 53.927 1.00 23.20 C
ATOM 411 CD1 LEU A 52 6.029 50.752 52.617 1.00 25.70 C
ATOM 412 CD2 LEU A 52 8.022 49.791 53.755 1.00 21.63 C
ATOM 413 N GLY A 53 8.200 52.592 57.613 1.00 19.61 N
ATOM 414 CA GLY A 53 8.381 53.797 58.394 1.00 18.06 C
ATOM 415 C GLY A 53 9.017 54.789 57.446 1.00 17.91 C
ATOM 416 O GLY A 53 8.639 54.856 56.269 1.00 16.04 O
ATOM 417 N ASP A 54 10.014 55.521 57.931 1.00 17.80 N
ATOM 418 CA ASP A 54 10.709 56.493 57.094 1.00 19.56 C
ATOM 419 C ASP A 54 11.629 55.784 56.099 1.00 18.53 C
ATOM 420 O ASP A 54 12.141 54.695 56.386 1.00 16.74 O
ATOM 421 CB ASP A 54 11.568 57.423 57.957 1.00 20.87 C
ATOM 422 CG ASP A 54 10.766 58.160 59.012 1.00 14.70 C
ATOM 423 OD1 ASP A 54 9.532 58.257 58.883 1.00 23.14 O
ATOM 424 OD2 ASP A 54 11.381 58.643 59.981 1.00 20.21 O
ATOM 425 N ALA A 55 11.813 56.387 54.926 1.00 15.45 N
ATOM 426 CA ALA A 55 12.722 55.826 53.934 1.00 15.62 C
ATOM 427 C ALA A 55 14.104 56.113 54.494 1.00 17.34 C
ATOM 428 O ALA A 55 14.335 57.181 55.062 1.00 18.82 O
ATOM 429 CB ALA A 55 12.547 56.516 52.607 1.00 12.76 C
ATOM 430 N ALA A 56 15.016 55.155 54.386 1.00 17.62 N
ATOM 431 CA ALA A 56 16.360 55.370 54.910 1.00 18.22 C
ATOM 432 C ALA A 56 17.145 56.353 54.038 1.00 18.86 C
ATOM 433 O ALA A 56 16.866 56.487 52.847 1.00 15.46 O
ATOM 434 CB ALA A 56 17.107 54.041 55.011 1.00 17.23 C
ATOM 435 N ARG A 57 18.103 57.057 54.642 1.00 21.08 N
ATOM 436 CA ARG A 57 18.942 57.998 53.903 1.00 23.00 C
ATOM 437 C ARG A 57 19.964 57.196 53.113 1.00 22.15 C
ATOM 438 O ARG A 57 20.508 56.211 53.616 1.00 22.87 O
ATOM 439 CB ARG A 57 19.699 58.929 54.848 1.00 24.04 C
ATOM 440 CG ARG A 57 18.830 59.726 55.791 1.00 32.51 C
ATOM 441 CD ARG A 57 17.841 60.612 55.062 1.00 34.98 C
ATOM 442 NE ARG A 57 17.109 61.457 56.006 1.00 41.64 N
ATOM 443 CZ ARG A 57 16.153 62.317 55.666 1.00 43.46 C
ATOM 444 NH1 ARG A 57 15.797 62.454 54.392 1.00 42.40 N
ATOM 445 NH2 ARG A 57 15.573 63.061 56.601 1.00 45.97 N
ATOM 446 N PRO A 58 20.232 57.602 51.860 1.00 21.73 N
ATOM 447 CA PRO A 58 21.203 56.906 51.007 1.00 20.52 C
ATOM 448 C PRO A 58 22.583 56.732 51.678 1.00 21.37 C
ATOM 449 O PRO A 58 23.298 55.760 51.413 1.00 20.72 O
ATOM 450 CB PRO A 58 21.269 57.812 49.773 1.00 22.99 C
ATOM 451 CG PRO A 58 19.873 58.352 49.690 1.00 20.91 C
ATOM 452 CD PRO A 58 19.573 58.698 51.122 1.00 22.61 C
ATOM 453 N SER A 59 22.935 57.668 52.556 1.00 20.39 N
ATOM 454 CA SER A 59 24.202 57.625 53.274 1.00 25.45 C
ATOM 455 C SER A 59 24.346 56.333 54.078 1.00 29.06 C
ATOM 456 O SER A 59 25.440 55.785 54.181 1.00 30.56 O
ATOM 457 CB SER A 59 24.348 58.852 54.183 1.00 23.85 C
ATOM 458 OG SER A 59 23.240 59.005 55.055 1.00 25.39 O
ATOM 459 N HIS A 60 23.237 55.849 54.633 1.00 32.05 N
ATOM 460 CA HIS A 60 23.228 54.605 55.405 1.00 34.52 C
ATOM 461 C HIS A 60 23.243 53.391 54.487 1.00 34.25 C
ATOM 462 O HIS A 60 23.776 52.339 54.839 1.00 37.45 O
ATOM 463 CB HIS A 60 21.975 54.515 56.272 1.00 39.39 C
ATOM 464 CG HIS A 60 22.088 55.229 57.581 1.00 50.07 C
ATOM 465 ND1 HIS A 60 21.246 56.260 57.940 1.00 53.27 N
ATOM 466 CD2 HIS A 60 22.919 55.035 58.633 1.00 53.22 C
ATOM 467 CE1 HIS A 60 21.550 56.667 59.160 1.00 55.62 C
ATOM 468 NE2 HIS A 60 22.561 55.941 59.602 1.00 56.55 N
ATOM 469 N LEU A 61 22.656 53.545 53.307 1.00 30.20 N
ATOM 470 CA LEU A 61 22.568 52.455 52.349 1.00 30.63 C
ATOM 471 C LEU A 61 23.822 52.203 51.502 1.00 32.64 C
ATOM 472 O LEU A 61 23.948 51.146 50.885 1.00 32.33 O
ATOM 473 CB LEU A 61 21.350 52.676 51.454 1.00 26.99 C
ATOM 474 CG LEU A 61 20.038 52.901 52.208 1.00 27.97 C
ATOM 475 CD1 LEU A 61 18.944 53.365 51.251 1.00 27.16 C
ATOM 476 CD2 LEU A 61 19.624 51.627 52.929 1.00 24.67 C
ATOM 477 N LEU A 62 24.751 53.157 51.488 1.00 35.49 N
ATOM 478 CA LEU A 62 25.981 53.029 50.699 1.00 37.77 C
ATOM 479 C LEU A 62 26.823 51.806 51.061 1.00 36.44 C
ATOM 480 O LEU A 62 27.501 51.233 50.210 1.00 36.53 O
ATOM 481 CB LEU A 62 26.862 54.280 50.847 1.00 40.27 C
ATOM 482 CG LEU A 62 26.436 55.666 50.344 1.00 42.29 C
ATOM 483 CD1 LEU A 62 27.501 56.659 50.766 1.00 39.59 C
ATOM 484 CD2 LEU A 62 26.260 55.696 48.833 1.00 40.03 C
ATOM 485 N THR A 63 26.773 51.413 52.324 1.00 34.57 N
ATOM 486 CA THR A 63 27.560 50.286 52.807 1.00 35.29 C
ATOM 487 C THR A 63 26.906 48.908 52.703 1.00 32.03 C
ATOM 488 O THR A 63 27.582 47.888 52.865 1.00 31.17 O
ATOM 489 CB THR A 63 27.969 50.516 54.267 1.00 37.75 C
ATOM 490 OG1 THR A 63 26.792 50.671 55.079 1.00 39.81 O
ATOM 491 CG2 THR A 63 28.842 51.767 54.375 1.00 40.91 C
ATOM 492 N SER A 64 25.604 48.885 52.429 1.00 28.60 N
ATOM 493 CA SER A 64 24.844 47.642 52.321 1.00 27.01 C
ATOM 494 C SER A 64 25.332 46.690 51.233 1.00 25.06 C
ATOM 495 O SER A 64 25.878 47.124 50.222 1.00 25.07 O
ATOM 496 CB SER A 64 23.367 47.964 52.083 1.00 25.98 C
ATOM 497 OG SER A 64 22.601 46.778 51.968 1.00 30.64 O
ATOM 498 N GLN A 65 25.130 45.392 51.447 1.00 20.79 N
ATOM 499 CA GLN A 65 25.515 44.375 50.460 1.00 20.97 C
ATOM 500 C GLN A 65 24.467 44.286 49.334 1.00 17.84 C
ATOM 501 O GLN A 65 24.751 43.814 48.230 1.00 18.22 O
ATOM 502 CB GLN A 65 25.677 43.007 51.133 1.00 20.52 C
ATOM 503 CG GLN A 65 26.826 42.940 52.130 1.00 20.61 C
ATOM 504 CD GLN A 65 26.974 41.562 52.736 1.00 24.18 C
ATOM 505 OE1 GLN A 65 26.248 41.201 53.656 1.00 27.16 O
ATOM 506 NE2 GLN A 65 27.902 40.777 52.210 1.00 22.39 N
ATOM 507 N LEU A 66 23.253 44.724 49.645 1.00 16.91 N
ATOM 508 CA LEU A 66 22.130 44.737 48.707 1.00 17.29 C
ATOM 509 C LEU A 66 22.064 46.105 48.015 1.00 15.83 C
ATOM 510 O LEU A 66 22.441 47.130 48.600 1.00 14.50 O
ATOM 511 CB LEU A 66 20.820 44.452 49.456 1.00 19.92 C
ATOM 512 CG LEU A 66 20.328 43.007 49.592 1.00 21.14 C
ATOM 513 CD1 LEU A 66 21.390 42.007 49.168 1.00 21.08 C
ATOM 514 CD2 LEU A 66 19.859 42.758 51.017 1.00 20.36 C
ATOM 515 N PRO A 67 21.540 46.143 46.781 1.00 14.35 N
ATOM 516 CA PRO A 67 21.435 47.390 46.018 1.00 14.67 C
ATOM 517 C PRO A 67 20.246 48.281 46.335 1.00 14.26 C
ATOM 518 O PRO A 67 19.308 47.880 47.030 1.00 13.77 O
ATOM 519 CB PRO A 67 21.381 46.889 44.578 1.00 12.70 C
ATOM 520 CG PRO A 67 20.557 45.647 44.709 1.00 16.82 C
ATOM 521 CD PRO A 67 21.094 44.991 45.974 1.00 14.43 C
ATOM 522 N LEU A 68 20.311 49.507 45.820 1.00 13.52 N
ATOM 523 CA LEU A 68 19.244 50.487 45.992 1.00 13.91 C
ATOM 524 C LEU A 68 18.056 50.078 45.127 1.00 12.87 C
ATOM 525 O LEU A 68 16.908 50.374 45.456 1.00 11.98 O
ATOM 526 CB LEU A 68 19.706 51.881 45.554 1.00 12.66 C
ATOM 527 CG LEU A 68 20.839 52.587 46.293 1.00 17.85 C
ATOM 528 CD1 LEU A 68 21.091 53.928 45.628 1.00 17.81 C
ATOM 529 CD2 LEU A 68 20.488 52.786 47.751 1.00 18.03 C
ATOM 530 N MET A 69 18.335 49.396 44.022 1.00 11.64 N
ATOM 531 CA MET A 69 17.273 48.972 43.126 1.00 16.65 C
ATOM 532 C MET A 69 17.660 47.825 42.209 1.00 16.10 C
ATOM 533 O MET A 69 18.827 47.655 41.858 1.00 15.01 O
ATOM 534 CB MET A 69 16.830 50.141 42.254 1.00 20.53 C
ATOM 535 CG MET A 69 17.926 50.645 41.336 1.00 29.19 C
ATOM 536 SD MET A 69 17.354 50.897 39.654 1.00 46.93 S
ATOM 537 CE MET A 69 17.759 49.335 38.933 1.00 38.88 C
ATOM 538 N TRP A 70 16.645 47.067 41.805 1.00 13.15 N
ATOM 539 CA TRP A 70 16.792 45.946 40.886 1.00 10.26 C
ATOM 540 C TRP A 70 15.776 46.214 39.790 1.00 10.68 C
ATOM 541 O TRP A 70 14.647 46.593 40.084 1.00 12.34 O
ATOM 542 CB TRP A 70 16.435 44.623 41.568 1.00 12.59 C
ATOM 543 CG TRP A 70 17.559 43.937 42.265 1.00 10.88 C
ATOM 544 CD1 TRP A 70 18.712 43.479 41.705 1.00 8.84 C
ATOM 545 CD2 TRP A 70 17.578 43.509 43.632 1.00 8.55 C
ATOM 546 NE1 TRP A 70 19.441 42.777 42.636 1.00 7.96 N
ATOM 547 CE2 TRP A 70 18.767 42.778 43.826 1.00 9.30 C
ATOM 548 CE3 TRP A 70 16.696 43.666 44.712 1.00 6.59 C
ATOM 549 CZ2 TRP A 70 19.102 42.199 45.059 1.00 9.37 C
ATOM 550 CZ3 TRP A 70 17.027 43.094 45.939 1.00 10.38 C
ATOM 551 CH2 TRP A 70 18.225 42.366 46.100 1.00 9.72 C
ATOM 552 N GLN A 71 16.174 46.013 38.541 1.00 11.12 N
ATOM 553 CA GLN A 71 15.301 46.222 37.396 1.00 10.97 C
ATOM 554 C GLN A 71 15.336 44.944 36.568 1.00 12.14 C
ATOM 555 O GLN A 71 16.413 44.460 36.228 1.00 13.62 O
ATOM 556 CB GLN A 71 15.830 47.397 36.577 1.00 19.11 C
ATOM 557 CG GLN A 71 14.997 47.784 35.375 1.00 21.02 C
ATOM 558 CD GLN A 71 15.593 48.978 34.637 1.00 27.76 C
ATOM 559 OE1 GLN A 71 16.383 48.820 33.703 1.00 29.53 O
ATOM 560 NE2 GLN A 71 15.234 50.181 35.072 1.00 28.11 N
ATOM 561 N LEU A 72 14.166 44.383 36.263 1.00 14.29 N
ATOM 562 CA LEU A 72 14.100 43.156 35.471 1.00 16.97 C
ATOM 563 C LEU A 72 14.845 43.327 34.141 1.00 20.03 C
ATOM 564 O LEU A 72 14.626 44.284 33.392 1.00 19.06 O
ATOM 565 CB LEU A 72 12.646 42.729 35.264 1.00 18.95 C
ATOM 566 CG LEU A 72 12.350 41.309 34.775 1.00 20.18 C
ATOM 567 CD1 LEU A 72 13.084 40.265 35.619 1.00 20.20 C
ATOM 568 CD2 LEU A 72 10.837 41.075 34.822 1.00 21.11 C
ATOM 569 N TYR A 73 15.745 42.386 33.880 1.00 22.95 N
ATOM 570 CA TYR A 73 16.596 42.389 32.699 1.00 24.81 C
ATOM 571 C TYR A 73 16.362 41.085 31.914 1.00 27.98 C
ATOM 572 O TYR A 73 15.983 40.076 32.504 1.00 27.51 O
ATOM 573 CB TYR A 73 18.043 42.478 33.193 1.00 24.82 C
ATOM 574 CG TYR A 73 19.042 42.916 32.167 1.00 28.69 C
ATOM 575 CD1 TYR A 73 19.069 44.230 31.709 1.00 29.31 C
ATOM 576 CD2 TYR A 73 19.947 42.008 31.630 1.00 29.76 C
ATOM 577 CE1 TYR A 73 19.972 44.625 30.731 1.00 32.02 C
ATOM 578 CE2 TYR A 73 20.850 42.389 30.658 1.00 32.56 C
ATOM 579 CZ TYR A 73 20.859 43.696 30.209 1.00 31.82 C
ATOM 580 OH TYR A 73 21.752 44.053 29.225 1.00 36.68 O
ATOM 581 N PRO A 74 16.575 41.091 30.576 1.00 32.74 N
ATOM 582 CA PRO A 74 16.377 39.890 29.742 1.00 31.54 C
ATOM 583 C PRO A 74 17.170 38.682 30.227 1.00 31.66 C
ATOM 584 O PRO A 74 18.256 38.835 30.790 1.00 33.95 O
ATOM 585 CB PRO A 74 16.889 40.336 28.369 1.00 33.02 C
ATOM 586 CG PRO A 74 16.586 41.790 28.349 1.00 36.16 C
ATOM 587 CD PRO A 74 16.999 42.231 29.738 1.00 32.78 C
ATOM 588 N GLU A 75 16.627 37.489 29.985 1.00 30.64 N
ATOM 589 CA GLU A 75 17.267 36.230 30.374 1.00 31.65 C
ATOM 590 C GLU A 75 17.123 35.937 31.869 1.00 28.27 C
ATOM 591 O GLU A 75 18.040 35.413 32.506 1.00 29.39 O
ATOM 592 CB GLU A 75 18.755 36.226 29.985 1.00 37.57 C
ATOM 593 CG GLU A 75 19.041 36.580 28.533 1.00 43.26 C
ATOM 594 CD GLU A 75 18.389 35.620 27.568 1.00 50.20 C
ATOM 595 OE1 GLU A 75 18.661 34.406 27.665 1.00 53.62 O
ATOM 596 OE2 GLU A 75 17.600 36.075 26.714 1.00 54.09 O
ATOM 597 N GLU A 76 15.962 36.274 32.420 1.00 24.07 N
ATOM 598 CA GLU A 76 15.662 36.051 33.826 1.00 24.29 C
ATOM 599 C GLU A 76 16.752 36.433 34.804 1.00 20.63 C
ATOM 600 O GLU A 76 17.379 35.592 35.444 1.00 18.08 O
ATOM 601 CB GLU A 76 15.188 34.617 34.064 1.00 32.67 C
ATOM 602 CG GLU A 76 13.797 34.360 33.492 1.00 44.16 C
ATOM 603 CD GLU A 76 12.806 35.480 33.831 1.00 51.92 C
ATOM 604 OE1 GLU A 76 12.156 35.403 34.900 1.00 56.04 O
ATOM 605 OE2 GLU A 76 12.683 36.442 33.032 1.00 52.76 O
ATOM 606 N ARG A 77 16.972 37.729 34.901 1.00 18.61 N
ATOM 607 CA ARG A 77 17.950 38.278 35.813 1.00 17.16 C
ATOM 608 C ARG A 77 17.631 39.742 36.036 1.00 15.52 C
ATOM 609 O ARG A 77 16.783 40.308 35.347 1.00 18.04 O
ATOM 610 CB ARG A 77 19.376 38.070 35.291 1.00 17.74 C
ATOM 611 CG ARG A 77 19.594 38.482 33.882 1.00 24.36 C
ATOM 612 CD ARG A 77 20.725 37.675 33.271 1.00 29.77 C
ATOM 613 NE ARG A 77 21.072 38.219 31.964 1.00 36.45 N
ATOM 614 CZ ARG A 77 22.233 38.023 31.351 1.00 41.91 C
ATOM 615 NH1 ARG A 77 23.176 37.276 31.920 1.00 41.81 N
ATOM 616 NH2 ARG A 77 22.475 38.638 30.201 1.00 42.87 N
ATOM 617 N TYR A 78 18.234 40.318 37.069 1.00 14.26 N
ATOM 618 CA TYR A 78 18.013 41.716 37.409 1.00 12.21 C
ATOM 619 C TYR A 78 19.294 42.511 37.311 1.00 12.38 C
ATOM 620 O TYR A 78 20.374 42.003 37.613 1.00 13.31 O
ATOM 621 CB TYR A 78 17.502 41.844 38.841 1.00 11.37 C
ATOM 622 CG TYR A 78 16.055 41.478 39.041 1.00 13.61 C
ATOM 623 CD1 TYR A 78 15.052 42.438 38.917 1.00 11.56 C
ATOM 624 CD2 TYR A 78 15.688 40.179 39.378 1.00 10.08 C
ATOM 625 CE1 TYR A 78 13.717 42.113 39.124 1.00 13.82 C
ATOM 626 CE2 TYR A 78 14.362 39.845 39.587 1.00 13.45 C
ATOM 627 CZ TYR A 78 13.380 40.812 39.458 1.00 16.37 C
ATOM 628 OH TYR A 78 12.061 40.470 39.649 1.00 15.20 O
ATOM 629 N MET A 79 19.174 43.752 36.857 1.00 12.71 N
ATOM 630 CA MET A 79 20.323 44.633 36.799 1.00 13.56 C
ATOM 631 C MET A 79 20.093 45.642 37.920 1.00 12.04 C
ATOM 632 O MET A 79 19.008 46.210 38.020 1.00 14.41 O
ATOM 633 CB MET A 79 20.427 45.361 35.456 1.00 11.12 C
ATOM 634 CG MET A 79 21.640 46.295 35.409 1.00 14.73 C
ATOM 635 SD MET A 79 21.887 47.165 33.869 1.00 19.00 S
ATOM 636 CE MET A 79 22.924 46.026 33.010 1.00 15.38 C
ATOM 637 N ASP A 80 21.082 45.816 38.793 1.00 10.24 N
ATOM 638 CA ASP A 80 20.959 46.760 39.892 1.00 10.68 C
ATOM 639 C ASP A 80 21.429 48.162 39.503 1.00 13.19 C
ATOM 640 O ASP A 80 21.760 48.416 38.338 1.00 16.65 O
ATOM 641 CB ASP A 80 21.680 46.255 41.153 1.00 11.02 C
ATOM 642 CG ASP A 80 23.199 46.088 40.978 1.00 13.93 C
ATOM 643 OD1 ASP A 80 23.816 46.744 40.114 1.00 13.00 O
ATOM 644 OD2 ASP A 80 23.790 45.297 41.751 1.00 15.93 O
ATOM 645 N ASN A 81 21.484 49.057 40.483 1.00 16.40 N
ATOM 646 CA ASN A 81 21.905 50.434 40.246 1.00 18.10 C
ATOM 647 C ASN A 81 23.389 50.603 39.909 1.00 16.47 C
ATOM 648 O ASN A 81 23.788 51.644 39.391 1.00 17.21 O
ATOM 649 CB ASN A 81 21.526 51.305 41.435 1.00 13.98 C
ATOM 650 CG ASN A 81 21.991 50.723 42.724 1.00 14.03 C
ATOM 651 OD1 ASN A 81 21.436 49.738 43.206 1.00 13.53 O
ATOM 652 ND2 ASN A 81 23.053 51.290 43.274 1.00 16.16 N
ATOM 653 N ASN A 82 24.194 49.578 40.180 1.00 17.77 N
ATOM 654 CA ASN A 82 25.628 49.607 39.870 1.00 16.10 C
ATOM 655 C ASN A 82 25.939 48.889 38.549 1.00 16.16 C
ATOM 656 O ASN A 82 27.103 48.668 38.224 1.00 19.80 O
ATOM 657 CB ASN A 82 26.429 48.935 40.984 1.00 18.78 C
ATOM 658 CG ASN A 82 26.283 49.633 42.310 1.00 22.33 C
ATOM 659 OD1 ASN A 82 26.200 48.993 43.358 1.00 23.21 O
ATOM 660 ND2 ASN A 82 26.255 50.954 42.277 1.00 27.16 N
ATOM 661 N SER A 83 24.894 48.509 37.814 1.00 17.04 N
ATOM 662 CA SER A 83 25.002 47.789 36.536 1.00 17.78 C
ATOM 663 C SER A 83 25.355 46.311 36.666 1.00 17.32 C
ATOM 664 O SER A 83 25.639 45.654 35.662 1.00 21.76 O
ATOM 665 CB SER A 83 25.990 48.457 35.570 1.00 18.73 C
ATOM 666 OG SER A 83 25.409 49.585 34.952 1.00 31.03 O
ATOM 667 N ARG A 84 25.345 45.789 37.889 1.00 16.34 N
ATOM 668 CA ARG A 84 25.653 44.383 38.109 1.00 15.27 C
ATOM 669 C ARG A 84 24.418 43.542 37.833 1.00 14.93 C
ATOM 670 O ARG A 84 23.296 44.020 37.982 1.00 12.68 O
ATOM 671 CB ARG A 84 26.122 44.164 39.535 1.00 17.72 C
ATOM 672 CG ARG A 84 27.335 44.970 39.878 1.00 25.25 C
ATOM 673 CD ARG A 84 27.646 44.857 41.347 1.00 34.69 C
ATOM 674 NE ARG A 84 28.765 45.714 41.732 1.00 42.42 N
ATOM 675 CZ ARG A 84 28.833 46.373 42.884 1.00 45.31 C
ATOM 676 NH1 ARG A 84 27.842 46.273 43.764 1.00 47.22 N
ATOM 677 NH2 ARG A 84 29.890 47.130 43.156 1.00 47.36 N
ATOM 678 N LEU A 85 24.636 42.297 37.416 1.00 14.33 N
ATOM 679 CA LEU A 85 23.558 41.366 37.100 1.00 17.03 C
ATOM 680 C LEU A 85 23.364 40.325 38.182 1.00 15.42 C
ATOM 681 O LEU A 85 24.326 39.823 38.760 1.00 15.71 O
ATOM 682 CB LEU A 85 23.819 40.668 35.765 1.00 20.80 C
ATOM 683 CG LEU A 85 23.215 41.272 34.496 1.00 24.06 C
ATOM 684 CD1 LEU A 85 23.410 42.767 34.468 1.00 25.84 C
ATOM 685 CD2 LEU A 85 23.847 40.627 33.280 1.00 31.93 C
ATOM 686 N TRP A 86 22.101 40.032 38.465 1.00 14.08 N
ATOM 687 CA TRP A 86 21.722 39.051 39.471 1.00 10.66 C
ATOM 688 C TRP A 86 20.869 38.005 38.776 1.00 12.64 C
ATOM 689 O TRP A 86 19.828 38.327 38.217 1.00 13.85 O
ATOM 690 CB TRP A 86 20.908 39.703 40.588 1.00 7.24 C
ATOM 691 CG TRP A 86 21.665 40.716 41.382 1.00 9.74 C
ATOM 692 CD1 TRP A 86 22.097 41.940 40.948 1.00 10.12 C
ATOM 693 CD2 TRP A 86 22.058 40.616 42.757 1.00 8.32 C
ATOM 694 NE1 TRP A 86 22.731 42.604 41.966 1.00 12.02 N
ATOM 695 CE2 TRP A 86 22.723 41.819 43.089 1.00 8.47 C
ATOM 696 CE3 TRP A 86 21.910 39.630 43.744 1.00 9.41 C
ATOM 697 CZ2 TRP A 86 23.244 42.066 44.367 1.00 11.95 C
ATOM 698 CZ3 TRP A 86 22.422 39.875 45.016 1.00 8.69 C
ATOM 699 CH2 TRP A 86 23.082 41.083 45.315 1.00 15.01 C
ATOM 700 N GLN A 87 21.326 36.761 38.792 1.00 11.88 N
ATOM 701 CA GLN A 87 20.610 35.667 38.151 1.00 11.39 C
ATOM 702 C GLN A 87 19.438 35.195 39.000 1.00 12.00 C
ATOM 703 O GLN A 87 19.589 35.006 40.201 1.00 11.24 O
ATOM 704 CB GLN A 87 21.570 34.485 37.940 1.00 14.49 C
ATOM 705 CG GLN A 87 20.954 33.287 37.231 1.00 18.40 C
ATOM 706 CD GLN A 87 20.598 33.589 35.784 1.00 23.31 C
ATOM 707 OE1 GLN A 87 21.462 33.972 34.990 1.00 27.67 O
ATOM 708 NE2 GLN A 87 19.325 33.418 35.432 1.00 26.80 N
ATOM 709 N ILE A 88 18.263 35.037 38.399 1.00 11.31 N
ATOM 710 CA ILE A 88 17.126 34.520 39.155 1.00 12.62 C
ATOM 711 C ILE A 88 17.322 33.004 39.123 1.00 11.88 C
ATOM 712 O ILE A 88 17.188 32.386 38.070 1.00 14.98 O
ATOM 713 CB ILE A 88 15.767 34.870 38.502 1.00 15.22 C
ATOM 714 CG1 ILE A 88 15.512 36.380 38.547 1.00 17.20 C
ATOM 715 CG2 ILE A 88 14.629 34.147 39.226 1.00 12.57 C
ATOM 716 CD1 ILE A 88 14.292 36.818 37.728 1.00 13.83 C
ATOM 717 N GLN A 89 17.731 32.421 40.247 1.00 15.00 N
ATOM 718 CA GLN A 89 17.951 30.974 40.311 1.00 16.39 C
ATOM 719 C GLN A 89 16.646 30.218 40.495 1.00 16.88 C
ATOM 720 O GLN A 89 16.505 29.078 40.045 1.00 19.34 O
ATOM 721 CB GLN A 89 18.974 30.628 41.379 1.00 12.14 C
ATOM 722 CG GLN A 89 20.292 31.319 41.124 1.00 13.54 C
ATOM 723 CD GLN A 89 21.419 30.665 41.868 1.00 9.67 C
ATOM 724 OE1 GLN A 89 21.586 30.871 43.061 1.00 12.98 O
ATOM 725 NE2 GLN A 89 22.198 29.858 41.165 1.00 13.21 N
ATOM 726 N HIS A 90 15.710 30.839 41.205 1.00 15.39 N
ATOM 727 CA HIS A 90 14.376 30.269 41.348 1.00 12.39 C
ATOM 728 C HIS A 90 13.342 31.307 41.775 1.00 11.51 C
ATOM 729 O HIS A 90 13.672 32.323 42.393 1.00 9.32 O
ATOM 730 CB HIS A 90 14.344 28.958 42.166 1.00 11.57 C
ATOM 731 CG HIS A 90 14.323 29.134 43.652 1.00 11.82 C
ATOM 732 ND1 HIS A 90 13.547 30.079 44.288 1.00 15.98 N
ATOM 733 CD2 HIS A 90 14.933 28.431 44.632 1.00 5.68 C
ATOM 734 CE1 HIS A 90 13.681 29.950 45.594 1.00 5.12 C
ATOM 735 NE2 HIS A 90 14.518 28.958 45.829 1.00 9.37 N
ATOM 736 N HIS A 91 12.115 31.088 41.323 1.00 12.42 N
ATOM 737 CA HIS A 91 10.985 31.956 41.612 1.00 13.33 C
ATOM 738 C HIS A 91 9.830 31.011 41.883 1.00 14.22 C
ATOM 739 O HIS A 91 9.227 30.461 40.965 1.00 14.55 O
ATOM 740 CB HIS A 91 10.677 32.837 40.398 1.00 14.49 C
ATOM 741 CG HIS A 91 9.508 33.757 40.588 1.00 11.65 C
ATOM 742 ND1 HIS A 91 8.830 34.320 39.529 1.00 10.13 N
ATOM 743 CD2 HIS A 91 8.919 34.236 41.709 1.00 12.17 C
ATOM 744 CE1 HIS A 91 7.875 35.108 39.990 1.00 11.37 C
ATOM 745 NE2 HIS A 91 7.908 35.075 41.309 1.00 11.03 N
ATOM 746 N LEU A 92 9.536 30.818 43.160 1.00 14.20 N
ATOM 747 CA LEU A 92 8.483 29.908 43.549 1.00 16.13 C
ATOM 748 C LEU A 92 7.706 30.337 44.773 1.00 15.61 C
ATOM 749 O LEU A 92 7.994 31.364 45.392 1.00 13.18 O
ATOM 750 CB LEU A 92 9.052 28.491 43.741 1.00 21.91 C
ATOM 751 CG LEU A 92 10.522 28.319 44.137 1.00 19.48 C
ATOM 752 CD1 LEU A 92 10.697 28.548 45.601 1.00 21.10 C
ATOM 753 CD2 LEU A 92 11.003 26.940 43.775 1.00 24.03 C
ATOM 754 N MET A 93 6.655 29.576 45.046 1.00 15.85 N
ATOM 755 CA MET A 93 5.782 29.789 46.182 1.00 20.41 C
ATOM 756 C MET A 93 6.280 28.825 47.251 1.00 22.02 C
ATOM 757 O MET A 93 6.350 27.612 47.013 1.00 19.65 O
ATOM 758 CB MET A 93 4.354 29.422 45.787 1.00 26.24 C
ATOM 759 CG MET A 93 3.275 30.079 46.628 1.00 34.92 C
ATOM 760 SD MET A 93 3.241 31.869 46.373 1.00 41.75 S
ATOM 761 CE MET A 93 3.437 31.974 44.624 1.00 34.79 C
ATOM 762 N VAL A 94 6.703 29.364 48.390 1.00 22.33 N
ATOM 763 CA VAL A 94 7.194 28.536 49.487 1.00 24.39 C
ATOM 764 C VAL A 94 6.368 28.825 50.730 1.00 26.64 C
ATOM 765 O VAL A 94 6.375 29.938 51.244 1.00 26.50 O
ATOM 766 CB VAL A 94 8.668 28.806 49.799 1.00 25.47 C
ATOM 767 CG1 VAL A 94 9.120 27.943 50.956 1.00 26.45 C
ATOM 768 CG2 VAL A 94 9.513 28.518 48.600 1.00 25.45 C
ATOM 769 N ARG A 95 5.656 27.812 51.206 1.00 28.59 N
ATOM 770 CA ARG A 95 4.801 27.950 52.377 1.00 30.86 C
ATOM 771 C ARG A 95 3.795 29.092 52.197 1.00 28.49 C
ATOM 772 O ARG A 95 3.442 29.785 53.150 1.00 31.14 O
ATOM 773 CB ARG A 95 5.643 28.127 53.648 1.00 35.29 C
ATOM 774 CG ARG A 95 6.193 26.814 54.231 1.00 43.27 C
ATOM 775 CD ARG A 95 7.128 26.076 53.271 1.00 50.53 C
ATOM 776 NE ARG A 95 7.570 24.779 53.793 1.00 54.79 N
ATOM 777 CZ ARG A 95 8.841 24.378 53.845 1.00 56.28 C
ATOM 778 NH1 ARG A 95 9.818 25.167 53.407 1.00 52.45 N
ATOM 779 NH2 ARG A 95 9.140 23.184 54.347 1.00 59.62 N
ATOM 780 N GLY A 96 3.352 29.283 50.955 1.00 26.49 N
ATOM 781 CA GLY A 96 2.376 30.317 50.646 1.00 24.62 C
ATOM 782 C GLY A 96 2.914 31.701 50.337 1.00 24.27 C
ATOM 783 O GLY A 96 2.137 32.605 50.018 1.00 26.98 O
ATOM 784 N VAL A 97 4.233 31.864 50.405 1.00 20.29 N
ATOM 785 CA VAL A 97 4.881 33.147 50.136 1.00 18.13 C
ATOM 786 C VAL A 97 5.712 33.086 48.863 1.00 16.61 C
ATOM 787 O VAL A 97 6.472 32.136 48.653 1.00 18.26 O
ATOM 788 CB VAL A 97 5.802 33.548 51.310 1.00 21.27 C
ATOM 789 CG1 VAL A 97 6.535 34.843 51.013 1.00 21.18 C
ATOM 790 CG2 VAL A 97 4.988 33.696 52.572 1.00 24.93 C
ATOM 791 N GLN A 98 5.568 34.104 48.019 1.00 11.13 N
ATOM 792 CA GLN A 98 6.322 34.187 46.770 1.00 9.24 C
ATOM 793 C GLN A 98 7.790 34.470 47.113 1.00 11.25 C
ATOM 794 O GLN A 98 8.095 35.368 47.912 1.00 9.57 O
ATOM 795 CB GLN A 98 5.759 35.290 45.876 1.00 11.50 C
ATOM 796 CG GLN A 98 6.286 35.263 44.460 1.00 20.05 C
ATOM 797 CD GLN A 98 5.622 36.297 43.574 1.00 21.93 C
ATOM 798 OE1 GLN A 98 6.127 36.628 42.500 1.00 24.81 O
ATOM 799 NE2 GLN A 98 4.479 36.814 44.020 1.00 24.35 N
ATOM 800 N GLU A 99 8.692 33.711 46.498 1.00 12.43 N
ATOM 801 CA GLU A 99 10.110 33.859 46.782 1.00 11.35 C
ATOM 802 C GLU A 99 11.027 33.912 45.563 1.00 10.20 C
ATOM 803 O GLU A 99 10.893 33.119 44.635 1.00 9.87 O
ATOM 804 CB GLU A 99 10.563 32.723 47.708 1.00 9.36 C
ATOM 805 CG GLU A 99 12.063 32.672 47.920 1.00 14.16 C
ATOM 806 CD GLU A 99 12.491 31.512 48.781 1.00 13.26 C
ATOM 807 OE1 GLU A 99 12.259 31.552 50.003 1.00 18.35 O
ATOM 808 OE2 GLU A 99 13.081 30.565 48.244 1.00 13.98 O
ATOM 809 N LEU A 100 11.960 34.861 45.581 1.00 10.42 N
ATOM 810 CA LEU A 100 12.947 34.997 44.515 1.00 8.12 C
ATOM 811 C LEU A 100 14.276 34.636 45.128 1.00 7.89 C
ATOM 812 O LEU A 100 14.535 34.988 46.278 1.00 8.59 O
ATOM 813 CB LEU A 100 13.038 36.438 44.014 1.00 10.38 C
ATOM 814 CG LEU A 100 11.968 37.005 43.083 1.00 8.57 C
ATOM 815 CD1 LEU A 100 12.180 38.503 42.937 1.00 12.70 C
ATOM 816 CD2 LEU A 100 12.034 36.317 41.734 1.00 11.56 C
ATOM 817 N LEU A 101 15.069 33.849 44.405 1.00 8.76 N
ATOM 818 CA LEU A 101 16.406 33.497 44.861 1.00 10.93 C
ATOM 819 C LEU A 101 17.342 34.076 43.806 1.00 12.06 C
ATOM 820 O LEU A 101 17.403 33.584 42.671 1.00 13.11 O
ATOM 821 CB LEU A 101 16.609 31.982 44.998 1.00 9.65 C
ATOM 822 CG LEU A 101 18.001 31.673 45.574 1.00 11.27 C
ATOM 823 CD1 LEU A 101 18.099 32.208 46.995 1.00 11.25 C
ATOM 824 CD2 LEU A 101 18.299 30.176 45.524 1.00 12.23 C
ATOM 825 N LEU A 102 18.030 35.153 44.188 1.00 12.14 N
ATOM 826 CA LEU A 102 18.950 35.881 43.312 1.00 12.70 C
ATOM 827 C LEU A 102 20.417 35.604 43.596 1.00 11.45 C
ATOM 828 O LEU A 102 20.832 35.526 44.747 1.00 14.27 O
ATOM 829 CB LEU A 102 18.713 37.388 43.454 1.00 9.65 C
ATOM 830 CG LEU A 102 17.294 37.898 43.228 1.00 12.23 C
ATOM 831 CD1 LEU A 102 17.230 39.413 43.442 1.00 11.94 C
ATOM 832 CD2 LEU A 102 16.856 37.527 41.826 1.00 11.88 C
ATOM 833 N LYS A 103 21.210 35.532 42.536 1.00 10.60 N
ATOM 834 CA LYS A 103 22.630 35.284 42.677 1.00 10.78 C
ATOM 835 C LYS A 103 23.414 36.371 41.960 1.00 8.25 C
ATOM 836 O LYS A 103 23.250 36.566 40.756 1.00 9.80 O
ATOM 837 CB LYS A 103 22.990 33.913 42.093 1.00 14.08 C
ATOM 838 CG LYS A 103 24.456 33.517 42.291 1.00 12.97 C
ATOM 839 CD LYS A 103 24.750 32.164 41.689 1.00 18.27 C
ATOM 840 CE LYS A 103 26.194 31.801 41.902 1.00 19.25 C
ATOM 841 NZ LYS A 103 26.495 30.426 41.441 1.00 26.24 N
ATOM 842 N LEU A 104 24.260 37.077 42.703 1.00 8.70 N
ATOM 843 CA LEU A 104 25.077 38.140 42.119 1.00 10.28 C
ATOM 844 C LEU A 104 26.169 37.528 41.256 1.00 9.18 C
ATOM 845 O LEU A 104 26.997 36.763 41.743 1.00 11.41 O
ATOM 846 CB LEU A 104 25.698 39.012 43.212 1.00 10.80 C
ATOM 847 CG LEU A 104 26.633 40.102 42.701 1.00 10.58 C
ATOM 848 CD1 LEU A 104 25.905 41.017 41.723 1.00 10.79 C
ATOM 849 CD2 LEU A 104 27.181 40.879 43.872 1.00 11.82 C
ATOM 850 N LEU A 105 26.133 37.843 39.969 1.00 6.87 N
ATOM 851 CA LEU A 105 27.095 37.332 39.008 1.00 9.92 C
ATOM 852 C LEU A 105 28.296 38.268 38.875 1.00 15.63 C
ATOM 853 O LEU A 105 28.194 39.464 39.163 1.00 14.69 O
ATOM 854 CB LEU A 105 26.414 37.171 37.649 1.00 10.09 C
ATOM 855 CG LEU A 105 25.218 36.216 37.594 1.00 8.13 C
ATOM 856 CD1 LEU A 105 24.583 36.276 36.208 1.00 12.90 C
ATOM 857 CD2 LEU A 105 25.660 34.808 37.910 1.00 12.11 C
ATOM 858 N PRO A 106 29.457 37.731 38.457 1.00 19.64 N
ATOM 859 CA PRO A 106 30.660 38.558 38.297 1.00 22.67 C
ATOM 860 C PRO A 106 30.432 39.539 37.164 1.00 25.96 C
ATOM 861 O PRO A 106 29.753 39.206 36.190 1.00 29.22 O
ATOM 862 CB PRO A 106 31.742 37.532 37.956 1.00 20.17 C
ATOM 863 CG PRO A 106 30.980 36.424 37.296 1.00 18.51 C
ATOM 864 CD PRO A 106 29.735 36.320 38.137 1.00 19.87 C
ATOM 865 N ASP A 107 30.943 40.758 37.296 1.00 30.85 N
ATOM 866 CA ASP A 107 30.739 41.746 36.238 1.00 37.83 C
ATOM 867 C ASP A 107 31.469 41.340 34.971 1.00 41.65 C
ATOM 868 O ASP A 107 32.653 41.016 35.014 1.00 40.17 O
ATOM 869 CB ASP A 107 31.196 43.140 36.671 1.00 43.05 C
ATOM 870 CG ASP A 107 30.820 44.219 35.654 1.00 51.89 C
ATOM 871 OD1 ASP A 107 31.520 44.348 34.618 1.00 53.03 O
ATOM 872 OD2 ASP A 107 29.815 44.933 35.892 1.00 54.46 O
ATOM 873 N ASP A 108 30.750 41.325 33.853 1.00 46.19 N
ATOM 874 CA ASP A 108 31.352 40.962 32.577 1.00 50.93 C
ATOM 875 C ASP A 108 31.279 42.138 31.608 1.00 51.95 C
ATOM 876 O ASP A 108 31.867 43.180 31.964 1.00 53.18 O
ATOM 877 CB ASP A 108 30.661 39.731 31.977 1.00 51.88 C
ATOM 878 CG ASP A 108 31.404 39.166 30.761 1.00 52.53 C
ATOM 879 OD1 ASP A 108 32.547 39.602 30.477 1.00 50.50 O
ATOM 880 OD2 ASP A 108 30.842 38.271 30.092 1.00 55.16 O
ATOM 881 OXT ASP A 108 30.861 41.990 30.465 1.00 53.01 O
TER 882 ASP A 108
HETATM 883 O HOH A 201 10.790 54.362 49.155 1.00 40.18 O
HETATM 884 O HOH A 202 2.542 44.383 50.633 1.00 23.32 O
HETATM 885 O HOH A 203 25.202 45.116 45.802 1.00 43.48 O
HETATM 886 O HOH A 204 13.390 60.000 54.870 1.00 43.75 O
HETATM 887 O HOH A 205 27.374 41.457 37.460 1.00 17.49 O
HETATM 888 O HOH A 206 27.812 34.370 40.842 1.00 50.30 O
HETATM 889 O HOH A 207 3.611 36.208 48.759 1.00 23.32 O
HETATM 890 O HOH A 208 23.300 44.010 53.130 1.00 43.87 O
HETATM 891 O HOH A 209 13.307 31.217 55.633 1.00 42.65 O
HETATM 892 O HOH A 210 10.639 51.975 47.659 1.00 46.65 O
HETATM 893 O HOH A 211 2.400 38.324 41.933 1.00 42.89 O
HETATM 894 O HOH A 212 18.750 47.014 51.139 1.00 20.60 O
HETATM 895 O HOH A 213 29.420 41.990 40.390 1.00 35.57 O
HETATM 896 O HOH A 214 19.260 32.730 32.410 1.00 47.68 O
HETATM 897 O HOH A 215 15.685 48.995 59.961 1.00 46.82 O
HETATM 898 O HOH A 216 -1.220 40.340 55.790 1.00 58.68 O
HETATM 899 O HOH A 217 7.303 41.722 35.036 1.00 44.43 O
HETATM 900 O HOH A 218 28.604 49.559 48.327 1.00 56.72 O
HETATM 901 O HOH A 219 23.770 46.990 57.770 1.00 39.86 O
HETATM 902 O HOH A 220 2.957 37.206 52.169 1.00 51.92 O
HETATM 903 O HOH A 221 30.110 49.910 43.900 1.00 57.81 O
HETATM 904 O HOH A 222 29.812 49.633 38.182 1.00 45.35 O
HETATM 905 O HOH A 223 28.242 50.610 57.743 1.00 50.83 O
HETATM 906 O HOH A 224 7.227 31.975 36.634 1.00 29.20 O
MASTER 265 0 0 1 9 0 0 6 905 1 0 9
END
PyCogent-1.5.3/tests/data/1LJO.pdb 000644 000765 000024 00000243331 11305747275 017530 0 ustar 00jrideout staff 000000 000000 HEADER UNKNOWN FUNCTION 22-APR-02 1LJO
TITLE CRYSTAL STRUCTURE OF AN SM-LIKE PROTEIN (AF-SM2) FROM
TITLE 2 ARCHAEOGLOBUS FULGIDUS AT 1.95A RESOLUTION
COMPND MOL_ID: 1;
COMPND 2 MOLECULE: ARCHAEAL SM-LIKE PROTEIN AF-SM2;
COMPND 3 CHAIN: A;
COMPND 4 ENGINEERED: YES;
COMPND 5 MUTATION: YES
SOURCE MOL_ID: 1;
SOURCE 2 ORGANISM_SCIENTIFIC: ARCHAEOGLOBUS FULGIDUS;
SOURCE 3 ORGANISM_TAXID: 2234;
SOURCE 4 GENE: AF0362;
SOURCE 5 EXPRESSION_SYSTEM: ESCHERICHIA COLI BL21(DE3);
SOURCE 6 EXPRESSION_SYSTEM_TAXID: 469008;
SOURCE 7 EXPRESSION_SYSTEM_STRAIN: BL21(DE3);
SOURCE 8 EXPRESSION_SYSTEM_VECTOR_TYPE: PLASMID;
SOURCE 9 EXPRESSION_SYSTEM_PLASMID: MODIFIED PET24D
KEYWDS SNRNP, SM, CORE SNRNP DOMAIN, RNA BINDING PROTEIN, UNKNOWN
KEYWDS 2 FUNCTION
EXPDTA X-RAY DIFFRACTION
AUTHOR I.TORO,J.BASQUIN,H.TEO-DREHER,D.SUCK
REVDAT 3 24-FEB-09 1LJO 1 VERSN
REVDAT 2 12-AUG-03 1LJO 1 DBREF SEQADV
REVDAT 1 03-JUL-02 1LJO 0
JRNL AUTH I.TORO,J.BASQUIN,H.TEO-DREHER,D.SUCK
JRNL TITL ARCHAEAL SM PROTEINS FORM HEPTAMERIC AND HEXAMERIC
JRNL TITL 2 COMPLEXES: CRYSTAL STRUCTURES OF THE SM1 AND SM2
JRNL TITL 3 PROTEINS FROM THE HYPERTHERMOPHILE ARCHAEOGLOBUS
JRNL TITL 4 FULGIDUS.
JRNL REF J.MOL.BIOL. V. 320 129 2002
JRNL REFN ISSN 0022-2836
JRNL PMID 12079339
JRNL DOI 10.1016/S0022-2836(02)00406-0
REMARK 1
REMARK 1 REFERENCE 1
REMARK 1 AUTH I.TORO,S.THORE,C.MAYER,J.BASQUIN,B.SRAPHIN,D.SUCK
REMARK 1 TITL RNA BINDING IN AN SM CORE DOMAIN: X-RAY STRUCTURE
REMARK 1 TITL 2 AND FUNCTIONAL ANALYSIS OF AN ARCHAEAL SM PROTEIN
REMARK 1 TITL 3 COMPLEX.
REMARK 1 REF EMBO J. V. 20 2293 2001
REMARK 1 REFN ISSN 0261-4189
REMARK 1 DOI 10.1093/EMBOJ/20.9.2293
REMARK 2
REMARK 2 RESOLUTION. 1.95 ANGSTROMS.
REMARK 3
REMARK 3 REFINEMENT.
REMARK 3 PROGRAM : CNS
REMARK 3 AUTHORS : BRUNGER,ADAMS,CLORE,DELANO,GROS,GROSSE-
REMARK 3 : KUNSTLEVE,JIANG,KUSZEWSKI,NILGES, PANNU,
REMARK 3 : READ,RICE,SIMONSON,WARREN
REMARK 3
REMARK 3 REFINEMENT TARGET : ENGH & HUBER
REMARK 3
REMARK 3 DATA USED IN REFINEMENT.
REMARK 3 RESOLUTION RANGE HIGH (ANGSTROMS) : 1.95
REMARK 3 RESOLUTION RANGE LOW (ANGSTROMS) : 27.10
REMARK 3 DATA CUTOFF (SIGMA(F)) : 0.000
REMARK 3 DATA CUTOFF HIGH (ABS(F)) : NULL
REMARK 3 DATA CUTOFF LOW (ABS(F)) : NULL
REMARK 3 COMPLETENESS (WORKING+TEST) (%) : 96.6
REMARK 3 NUMBER OF REFLECTIONS : 4521
REMARK 3
REMARK 3 FIT TO DATA USED IN REFINEMENT.
REMARK 3 CROSS-VALIDATION METHOD : THROUGHOUT
REMARK 3 FREE R VALUE TEST SET SELECTION : RANDOM
REMARK 3 R VALUE (WORKING SET) : 0.194
REMARK 3 FREE R VALUE : 0.211
REMARK 3 FREE R VALUE TEST SET SIZE (%) : 5.000
REMARK 3 FREE R VALUE TEST SET COUNT : 226
REMARK 3 ESTIMATED ERROR OF FREE R VALUE : 0.014
REMARK 3
REMARK 3 FIT IN THE HIGHEST RESOLUTION BIN.
REMARK 3 TOTAL NUMBER OF BINS USED : 6
REMARK 3 BIN RESOLUTION RANGE HIGH (A) : 1.95
REMARK 3 BIN RESOLUTION RANGE LOW (A) : 2.07
REMARK 3 BIN COMPLETENESS (WORKING+TEST) (%) : 91.50
REMARK 3 REFLECTIONS IN BIN (WORKING SET) : 670
REMARK 3 BIN R VALUE (WORKING SET) : 0.1990
REMARK 3 BIN FREE R VALUE : 0.2940
REMARK 3 BIN FREE R VALUE TEST SET SIZE (%) : 5.40
REMARK 3 BIN FREE R VALUE TEST SET COUNT : 38
REMARK 3 ESTIMATED ERROR OF BIN FREE R VALUE : 0.048
REMARK 3
REMARK 3 NUMBER OF NON-HYDROGEN ATOMS USED IN REFINEMENT.
REMARK 3 PROTEIN ATOMS : 578
REMARK 3 NUCLEIC ACID ATOMS : 0
REMARK 3 HETEROGEN ATOMS : 1
REMARK 3 SOLVENT ATOMS : 45
REMARK 3
REMARK 3 B VALUES.
REMARK 3 FROM WILSON PLOT (A**2) : 18.57
REMARK 3 MEAN B VALUE (OVERALL, A**2) : 25.00
REMARK 3 OVERALL ANISOTROPIC B VALUE.
REMARK 3 B11 (A**2) : -5.74000
REMARK 3 B22 (A**2) : -5.74000
REMARK 3 B33 (A**2) : 11.48000
REMARK 3 B12 (A**2) : -1.46000
REMARK 3 B13 (A**2) : 0.00000
REMARK 3 B23 (A**2) : 0.00000
REMARK 3
REMARK 3 ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM LUZZATI PLOT (A) : 0.20
REMARK 3 ESD FROM SIGMAA (A) : 0.11
REMARK 3 LOW RESOLUTION CUTOFF (A) : 5.00
REMARK 3
REMARK 3 CROSS-VALIDATED ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM C-V LUZZATI PLOT (A) : 0.24
REMARK 3 ESD FROM C-V SIGMAA (A) : 0.24
REMARK 3
REMARK 3 RMS DEVIATIONS FROM IDEAL VALUES.
REMARK 3 BOND LENGTHS (A) : 0.005
REMARK 3 BOND ANGLES (DEGREES) : 1.32
REMARK 3 DIHEDRAL ANGLES (DEGREES) : 25.48
REMARK 3 IMPROPER ANGLES (DEGREES) : 0.73
REMARK 3
REMARK 3 ISOTROPIC THERMAL MODEL : ISOTROPIC
REMARK 3
REMARK 3 ISOTROPIC THERMAL FACTOR RESTRAINTS. RMS SIGMA
REMARK 3 MAIN-CHAIN BOND (A**2) : 2.255 ; NULL
REMARK 3 MAIN-CHAIN ANGLE (A**2) : 3.363 ; NULL
REMARK 3 SIDE-CHAIN BOND (A**2) : 3.077 ; NULL
REMARK 3 SIDE-CHAIN ANGLE (A**2) : 4.729 ; NULL
REMARK 3
REMARK 3 BULK SOLVENT MODELING.
REMARK 3 METHOD USED : FLAT MODEL
REMARK 3 KSOL : 0.38
REMARK 3 BSOL : 56.13
REMARK 3
REMARK 3 NCS MODEL : NULL
REMARK 3
REMARK 3 NCS RESTRAINTS. RMS SIGMA/WEIGHT
REMARK 3 GROUP 1 POSITIONAL (A) : NULL ; NULL
REMARK 3 GROUP 1 B-FACTOR (A**2) : NULL ; NULL
REMARK 3
REMARK 3 PARAMETER FILE 1 : PROTEIN_REP.PARAM
REMARK 3 PARAMETER FILE 2 : WATER_REP.PARAM
REMARK 3 PARAMETER FILE 3 : ION.PARAM
REMARK 3 PARAMETER FILE 4 : ACY.PAR
REMARK 3 PARAMETER FILE 5 : NULL
REMARK 3 TOPOLOGY FILE 1 : PROTEIN.TOP
REMARK 3 TOPOLOGY FILE 2 : WATER.TOP
REMARK 3 TOPOLOGY FILE 3 : ION.TOP
REMARK 3 TOPOLOGY FILE 4 : ACY.TOP
REMARK 3 TOPOLOGY FILE 5 : NULL
REMARK 3
REMARK 3 OTHER REFINEMENT REMARKS: MAXIMUM LIKELIHOOD TARGET
REMARK 4
REMARK 4 1LJO COMPLIES WITH FORMAT V. 3.15, 01-DEC-08
REMARK 100
REMARK 100 THIS ENTRY HAS BEEN PROCESSED BY RCSB ON 24-APR-02.
REMARK 100 THE RCSB ID CODE IS RCSB016002.
REMARK 200
REMARK 200 EXPERIMENTAL DETAILS
REMARK 200 EXPERIMENT TYPE : X-RAY DIFFRACTION
REMARK 200 DATE OF DATA COLLECTION : 29-APR-99; 20-APR-99
REMARK 200 TEMPERATURE (KELVIN) : 100; 100
REMARK 200 PH : 3.6
REMARK 200 NUMBER OF CRYSTALS USED : 1
REMARK 200
REMARK 200 SYNCHROTRON (Y/N) : Y; N
REMARK 200 RADIATION SOURCE : ESRF; ROTATING ANODE
REMARK 200 BEAMLINE : BM14; NULL
REMARK 200 X-RAY GENERATOR MODEL : NULL; ELLIOTT GX-21
REMARK 200 MONOCHROMATIC OR LAUE (M/L) : M; M
REMARK 200 WAVELENGTH OR RANGE (A) : 1; 1.5418
REMARK 200 MONOCHROMATOR : SI 111; NI MIRROR + NI FILTER
REMARK 200 OPTICS : NULL; NULL
REMARK 200
REMARK 200 DETECTOR TYPE : CCD; IMAGE PLATE
REMARK 200 DETECTOR MANUFACTURER : MARRESEARCH; MARRESEARCH
REMARK 200 INTENSITY-INTEGRATION SOFTWARE : MAR
REMARK 200 DATA SCALING SOFTWARE : XDS
REMARK 200
REMARK 200 NUMBER OF UNIQUE REFLECTIONS : 4522
REMARK 200 RESOLUTION RANGE HIGH (A) : 1.950
REMARK 200 RESOLUTION RANGE LOW (A) : 27.100
REMARK 200 REJECTION CRITERIA (SIGMA(I)) : 0.000
REMARK 200
REMARK 200 OVERALL.
REMARK 200 COMPLETENESS FOR RANGE (%) : 97.6
REMARK 200 DATA REDUNDANCY : 2.700
REMARK 200 R MERGE (I) : 0.05100
REMARK 200 R SYM (I) : 0.05100
REMARK 200 FOR THE DATA SET : 10.5000
REMARK 200
REMARK 200 IN THE HIGHEST RESOLUTION SHELL.
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE HIGH (A) : 1.95
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE LOW (A) : 2.06
REMARK 200 COMPLETENESS FOR SHELL (%) : 90.9
REMARK 200 DATA REDUNDANCY IN SHELL : 2.00
REMARK 200 R MERGE FOR SHELL (I) : 0.17300
REMARK 200 R SYM FOR SHELL (I) : 0.17300
REMARK 200 FOR SHELL : 4.200
REMARK 200
REMARK 200 DIFFRACTION PROTOCOL: SINGLE WAVELENGTH; SINGLE WAVELENGTH
REMARK 200 METHOD USED TO DETERMINE THE STRUCTURE: SIRAS
REMARK 200 SOFTWARE USED: SHARP
REMARK 200 STARTING MODEL: BUILT BY ARP/WARP (68 RESIDUES)
REMARK 200
REMARK 200 REMARK: NULL
REMARK 280
REMARK 280 CRYSTAL
REMARK 280 SOLVENT CONTENT, VS (%): 32.92
REMARK 280 MATTHEWS COEFFICIENT, VM (ANGSTROMS**3/DA): 1.83
REMARK 280
REMARK 280 CRYSTALLIZATION CONDITIONS: AMMONIUM SULPHATE, LITHIUM
REMARK 280 SULPHATE, SODIUM SULPHATE, PH 3.6, VAPOR DIFFUSION, HANGING
REMARK 280 DROP, TEMPERATURE 293K
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY
REMARK 290 SYMMETRY OPERATORS FOR SPACE GROUP: P 6
REMARK 290
REMARK 290 SYMOP SYMMETRY
REMARK 290 NNNMMM OPERATOR
REMARK 290 1555 X,Y,Z
REMARK 290 2555 -Y,X-Y,Z
REMARK 290 3555 -X+Y,-X,Z
REMARK 290 4555 -X,-Y,Z
REMARK 290 5555 Y,-X+Y,Z
REMARK 290 6555 X-Y,X,Z
REMARK 290
REMARK 290 WHERE NNN -> OPERATOR NUMBER
REMARK 290 MMM -> TRANSLATION VECTOR
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY TRANSFORMATIONS
REMARK 290 THE FOLLOWING TRANSFORMATIONS OPERATE ON THE ATOM/HETATM
REMARK 290 RECORDS IN THIS ENTRY TO PRODUCE CRYSTALLOGRAPHICALLY
REMARK 290 RELATED MOLECULES.
REMARK 290 SMTRY1 1 1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 1 0.000000 1.000000 0.000000 0.00000
REMARK 290 SMTRY3 1 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 2 -0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 2 0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 2 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 3 -0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 3 -0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 3 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 4 -1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 4 0.000000 -1.000000 0.000000 0.00000
REMARK 290 SMTRY3 4 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 5 0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 5 -0.866025 0.500000 0.000000 0.00000
REMARK 290 SMTRY3 5 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 6 0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 6 0.866025 0.500000 0.000000 0.00000
REMARK 290 SMTRY3 6 0.000000 0.000000 1.000000 0.00000
REMARK 290
REMARK 290 REMARK: NULL
REMARK 300
REMARK 300 BIOMOLECULE: 1
REMARK 300 SEE REMARK 350 FOR THE AUTHOR PROVIDED AND/OR PROGRAM
REMARK 300 GENERATED ASSEMBLY INFORMATION FOR THE STRUCTURE IN
REMARK 300 THIS ENTRY. THE REMARK MAY ALSO PROVIDE INFORMATION ON
REMARK 300 BURIED SURFACE AREA.
REMARK 300 REMARK: THE BIOLOGICAL ASSEMBLY IS A HEXAMER GENERATED FROM THE
REMARK 300 MONOMER IN THE ASYMMETRIC UNIT BY THE OPERATIONS: -Y,X-Y,Z; Y-X,
REMARK 300 -X,Z; -X,-Y,Z; Y,Y-X,Z AND X-Y,X,Z
REMARK 350
REMARK 350 COORDINATES FOR A COMPLETE MULTIMER REPRESENTING THE KNOWN
REMARK 350 BIOLOGICALLY SIGNIFICANT OLIGOMERIZATION STATE OF THE
REMARK 350 MOLECULE CAN BE GENERATED BY APPLYING BIOMT TRANSFORMATIONS
REMARK 350 GIVEN BELOW. BOTH NON-CRYSTALLOGRAPHIC AND
REMARK 350 CRYSTALLOGRAPHIC OPERATIONS ARE GIVEN.
REMARK 350
REMARK 350 BIOMOLECULE: 1
REMARK 350 AUTHOR DETERMINED BIOLOGICAL UNIT: HEXAMERIC
REMARK 350 APPLY THE FOLLOWING TO CHAINS: A
REMARK 350 BIOMT1 1 1.000000 0.000000 0.000000 0.00000
REMARK 350 BIOMT2 1 0.000000 1.000000 0.000000 0.00000
REMARK 350 BIOMT3 1 0.000000 0.000000 1.000000 0.00000
REMARK 350 BIOMT1 2 -0.500000 -0.866025 0.000000 0.00000
REMARK 350 BIOMT2 2 0.866025 -0.500000 0.000000 0.00000
REMARK 350 BIOMT3 2 0.000000 0.000000 1.000000 0.00000
REMARK 350 BIOMT1 3 -0.500000 0.866025 0.000000 0.00000
REMARK 350 BIOMT2 3 -0.866025 -0.500000 0.000000 0.00000
REMARK 350 BIOMT3 3 0.000000 0.000000 1.000000 0.00000
REMARK 350 BIOMT1 4 -1.000000 0.000000 0.000000 0.00000
REMARK 350 BIOMT2 4 0.000000 -1.000000 0.000000 0.00000
REMARK 350 BIOMT3 4 0.000000 0.000000 1.000000 0.00000
REMARK 350 BIOMT1 5 0.500000 0.866025 0.000000 0.00000
REMARK 350 BIOMT2 5 -0.866025 0.500000 0.000000 0.00000
REMARK 350 BIOMT3 5 0.000000 0.000000 1.000000 0.00000
REMARK 350 BIOMT1 6 0.500000 -0.866025 0.000000 0.00000
REMARK 350 BIOMT2 6 0.866025 0.500000 0.000000 0.00000
REMARK 350 BIOMT3 6 0.000000 0.000000 1.000000 0.00000
REMARK 375
REMARK 375 SPECIAL POSITION
REMARK 375 THE FOLLOWING ATOMS ARE FOUND TO BE WITHIN 0.15 ANGSTROMS
REMARK 375 OF A SYMMETRY RELATED ATOM AND ARE ASSUMED TO BE ON SPECIAL
REMARK 375 POSITIONS.
REMARK 375
REMARK 375 ATOM RES CSSEQI
REMARK 375 CD CD A 78 LIES ON A SPECIAL POSITION.
REMARK 375 HOH A 307 LIES ON A SPECIAL POSITION.
REMARK 375 HOH A 309 LIES ON A SPECIAL POSITION.
REMARK 375 HOH A 398 LIES ON A SPECIAL POSITION.
REMARK 375 HOH A 442 LIES ON A SPECIAL POSITION.
REMARK 375 HOH A 444 LIES ON A SPECIAL POSITION.
REMARK 465
REMARK 465 MISSING RESIDUES
REMARK 465 THE FOLLOWING RESIDUES WERE NOT LOCATED IN THE
REMARK 465 EXPERIMENT. (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN
REMARK 465 IDENTIFIER; SSSEQ=SEQUENCE NUMBER; I=INSERTION CODE.)
REMARK 465
REMARK 465 M RES C SSSEQI
REMARK 465 GLU A 76
REMARK 465 GLU A 77
REMARK 525
REMARK 525 SOLVENT
REMARK 525
REMARK 525 THE SOLVENT MOLECULES HAVE CHAIN IDENTIFIERS THAT
REMARK 525 INDICATE THE POLYMER CHAIN WITH WHICH THEY ARE MOST
REMARK 525 CLOSELY ASSOCIATED. THE REMARK LISTS ALL THE SOLVENT
REMARK 525 MOLECULES WHICH ARE MORE THAN 5A AWAY FROM THE
REMARK 525 NEAREST POLYMER CHAIN (M = MODEL NUMBER;
REMARK 525 RES=RESIDUE NAME; C=CHAIN IDENTIFIER; SSEQ=SEQUENCE
REMARK 525 NUMBER; I=INSERTION CODE):
REMARK 525
REMARK 525 M RES CSSEQI
REMARK 525 HOH A 444 DISTANCE = 6.77 ANGSTROMS
REMARK 600
REMARK 600 HETEROGEN
REMARK 600 CD ION SITTING ON SIX-FOLD AXIS IS MODELLING A
REMARK 600 SULPHATE ION
REMARK 800
REMARK 800 SITE
REMARK 800 SITE_IDENTIFIER: AC1
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE ACY A 201
REMARK 800 SITE_IDENTIFIER: AC2
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE ACY A 202
REMARK 800 SITE_IDENTIFIER: AC3
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE ACY A 203
REMARK 900
REMARK 900 RELATED ENTRIES
REMARK 900 RELATED ID: 1D3B RELATED DB: PDB
REMARK 900 CRYSTAL STRUCTURE OF THE D3B SUBCOMPLEX OF THE HUMAN CORE
REMARK 900 SNRNP DOMAIN AT 2.0A RESOLUTION
REMARK 900 RELATED ID: 1B34 RELATED DB: PDB
REMARK 900 CRYSTAL STRUCTURE OF THE D1D2 SUB-COMPLEX FROM THE HUMAN
REMARK 900 SNRNP CORE DOMAIN
REMARK 900 RELATED ID: 1I81 RELATED DB: PDB
REMARK 900 CRYSTAL STRUCTURE OF A HEPTAMERIC LSM PROTEIN FROM
REMARK 900 METHANOBACTERIUM THERMOAUTOTROPHICUM
REMARK 900 RELATED ID: 1I8F RELATED DB: PDB
REMARK 900 THE CRYSTAL STRUCTURE OF A HEPTAMERIC ARCHAEAL SM PROTEIN:
REMARK 900 IMPLICATIONS FOR THE EUKARYOTIC SNRNP CORE
REMARK 900 RELATED ID: 1I5L RELATED DB: PDB
REMARK 900 CRYSTAL STRUCTURE OF AN SM-LIKE PROTEIN (AF-SM1) FROM
REMARK 900 ARCHAEOGLOBUS FULGIDUS COMPLEXED WITH SHORT POLY-U RNA
REMARK 900 RELATED ID: 1I4K RELATED DB: PDB
REMARK 900 CRYSTAL STRUCTURE OF AN SM-LIKE PROTEIN (AF-SM1) FROM
REMARK 900 ARCHAEOGLOBUS FULGIDUS AT 2.5A RESOLUTION
REMARK 900 RELATED ID: 1JRI RELATED DB: PDB
REMARK 900 THE CRYSTAL STRUCTURE OF AN SM-LIKE ARCHAEAL PROTEIN WITH
REMARK 900 TWO HEPTAMERS IN THE ASYMMETRIC UNIT.
DBREF 1LJO A 1 77 UNP O29885 O29885_ARCFU 1 75
SEQADV 1LJO GLY A 1 UNP O29885 CLONING ARTIFACT
SEQADV 1LJO ALA A 2 UNP O29885 CLONING ARTIFACT
SEQRES 1 A 77 GLY ALA MET VAL LEU PRO ASN GLN MET VAL LYS SER MET
SEQRES 2 A 77 VAL GLY LYS ILE ILE ARG VAL GLU MET LYS GLY GLU GLU
SEQRES 3 A 77 ASN GLN LEU VAL GLY LYS LEU GLU GLY VAL ASP ASP TYR
SEQRES 4 A 77 MET ASN LEU TYR LEU THR ASN ALA MET GLU CYS LYS GLY
SEQRES 5 A 77 GLU GLU LYS VAL ARG SER LEU GLY GLU ILE VAL LEU ARG
SEQRES 6 A 77 GLY ASN ASN VAL VAL LEU ILE GLN PRO GLN GLU GLU
HET CD A 78 1
HET ACY A 201 4
HET ACY A 202 4
HET ACY A 203 4
HETNAM CD CADMIUM ION
HETNAM ACY ACETIC ACID
FORMUL 2 CD CD 2+
FORMUL 3 ACY 3(C2 H4 O2)
FORMUL 6 HOH *33(H2 O)
HELIX 1 1 LEU A 5 MET A 13 1 9
HELIX 2 2 ARG A 65 ASN A 67 5 3
SHEET 1 A 5 GLU A 54 LEU A 64 0
SHEET 2 A 5 LEU A 42 LYS A 51 -1 N LEU A 42 O LEU A 64
SHEET 3 A 5 GLN A 28 VAL A 36 -1 N GLN A 28 O CYS A 50
SHEET 4 A 5 ILE A 17 MET A 22 -1 N VAL A 20 O LEU A 29
SHEET 5 A 5 VAL A 69 PRO A 74 -1 O VAL A 70 N GLU A 21
SITE 1 AC1 3 GLN A 28 ASP A 38 LYS A 51
SITE 1 AC2 2 LYS A 55 SER A 58
SITE 1 AC3 5 ILE A 17 ASN A 46 GLY A 60 GLU A 61
SITE 2 AC3 5 HOH A 385
CRYST1 58.420 58.420 32.084 90.00 90.00 120.00 P 6 6
ORIGX1 1.000000 0.000000 0.000000 0.00000
ORIGX2 0.000000 1.000000 0.000000 0.00000
ORIGX3 0.000000 0.000000 1.000000 0.00000
SCALE1 0.017117 0.009883 0.000000 0.00000
SCALE2 0.000000 0.019766 0.000000 0.00000
SCALE3 0.000000 0.000000 0.031168 0.00000
ATOM 1 N GLY A 1 22.149 18.199 41.790 1.00 43.67 N
ATOM 2 CA GLY A 1 21.635 19.597 41.827 1.00 42.53 C
ATOM 3 C GLY A 1 20.136 19.663 42.046 1.00 41.28 C
ATOM 4 O GLY A 1 19.647 19.354 43.133 1.00 41.86 O
ATOM 5 N ALA A 2 19.405 20.067 41.012 1.00 38.71 N
ATOM 6 CA ALA A 2 17.953 20.175 41.087 1.00 35.37 C
ATOM 7 C ALA A 2 17.313 19.817 39.753 1.00 34.90 C
ATOM 8 O ALA A 2 17.981 19.797 38.715 1.00 34.91 O
ATOM 9 CB ALA A 2 17.554 21.588 41.489 1.00 33.87 C
ATOM 10 N MET A 3 16.017 19.528 39.783 1.00 31.49 N
ATOM 11 CA MET A 3 15.297 19.186 38.567 1.00 30.05 C
ATOM 12 C MET A 3 13.809 19.434 38.748 1.00 28.55 C
ATOM 13 O MET A 3 13.313 19.490 39.872 1.00 28.05 O
ATOM 14 CB MET A 3 15.540 17.721 38.185 1.00 30.48 C
ATOM 15 CG MET A 3 14.879 16.691 39.089 1.00 29.18 C
ATOM 16 SD MET A 3 15.038 15.018 38.409 1.00 29.49 S
ATOM 17 CE MET A 3 15.024 14.014 39.898 1.00 31.84 C
ATOM 18 N VAL A 4 13.105 19.593 37.633 1.00 25.64 N
ATOM 19 CA VAL A 4 11.667 19.833 37.661 1.00 23.81 C
ATOM 20 C VAL A 4 10.933 18.550 37.289 1.00 21.83 C
ATOM 21 O VAL A 4 11.119 18.016 36.195 1.00 23.25 O
ATOM 22 CB VAL A 4 11.273 20.948 36.667 1.00 21.95 C
ATOM 23 CG1 VAL A 4 9.778 21.227 36.753 1.00 23.10 C
ATOM 24 CG2 VAL A 4 12.064 22.208 36.971 1.00 22.74 C
ATOM 25 N LEU A 5 10.107 18.054 38.204 1.00 18.90 N
ATOM 26 CA LEU A 5 9.355 16.829 37.958 1.00 20.29 C
ATOM 27 C LEU A 5 8.330 17.012 36.843 1.00 16.15 C
ATOM 28 O LEU A 5 7.695 18.058 36.732 1.00 17.31 O
ATOM 29 CB LEU A 5 8.647 16.373 39.234 1.00 19.85 C
ATOM 30 CG LEU A 5 9.564 15.895 40.366 1.00 24.33 C
ATOM 31 CD1 LEU A 5 8.751 15.672 41.634 1.00 23.59 C
ATOM 32 CD2 LEU A 5 10.274 14.612 39.943 1.00 24.78 C
ATOM 33 N PRO A 6 8.176 15.996 35.982 1.00 15.96 N
ATOM 34 CA PRO A 6 7.209 16.085 34.889 1.00 14.51 C
ATOM 35 C PRO A 6 5.810 16.470 35.384 1.00 14.71 C
ATOM 36 O PRO A 6 5.177 17.359 34.824 1.00 13.33 O
ATOM 37 CB PRO A 6 7.265 14.691 34.279 1.00 14.95 C
ATOM 38 CG PRO A 6 8.724 14.351 34.418 1.00 12.33 C
ATOM 39 CD PRO A 6 9.005 14.782 35.851 1.00 15.51 C
ATOM 40 N ASN A 7 5.331 15.809 36.436 1.00 19.33 N
ATOM 41 CA ASN A 7 4.010 16.127 36.980 1.00 23.08 C
ATOM 42 C ASN A 7 3.946 17.585 37.430 1.00 23.25 C
ATOM 43 O ASN A 7 2.900 18.225 37.318 1.00 22.91 O
ATOM 44 CB ASN A 7 3.666 15.213 38.163 1.00 23.44 C
ATOM 45 CG ASN A 7 3.219 13.828 37.726 1.00 25.02 C
ATOM 46 OD1 ASN A 7 3.030 12.937 38.554 1.00 28.45 O
ATOM 47 ND2 ASN A 7 3.040 13.644 36.425 1.00 22.14 N
ATOM 48 N GLN A 8 5.058 18.105 37.946 1.00 23.39 N
ATOM 49 CA GLN A 8 5.104 19.499 38.390 1.00 23.53 C
ATOM 50 C GLN A 8 4.946 20.401 37.170 1.00 21.36 C
ATOM 51 O GLN A 8 4.220 21.395 37.200 1.00 19.26 O
ATOM 52 CB GLN A 8 6.445 19.828 39.069 1.00 28.13 C
ATOM 53 CG GLN A 8 6.714 19.118 40.390 1.00 30.41 C
ATOM 54 CD GLN A 8 7.978 19.629 41.082 1.00 32.59 C
ATOM 55 OE1 GLN A 8 9.078 19.573 40.527 1.00 30.42 O
ATOM 56 NE2 GLN A 8 7.820 20.125 42.304 1.00 34.48 N
ATOM 57 N MET A 9 5.645 20.049 36.097 1.00 17.49 N
ATOM 58 CA MET A 9 5.588 20.829 34.870 1.00 15.33 C
ATOM 59 C MET A 9 4.172 20.833 34.292 1.00 14.63 C
ATOM 60 O MET A 9 3.637 21.889 33.961 1.00 15.62 O
ATOM 61 CB MET A 9 6.581 20.268 33.842 1.00 15.69 C
ATOM 62 CG MET A 9 6.667 21.070 32.549 1.00 21.37 C
ATOM 63 SD MET A 9 7.046 22.822 32.836 1.00 27.63 S
ATOM 64 CE MET A 9 6.588 23.523 31.263 1.00 23.80 C
ATOM 65 N VAL A 10 3.559 19.658 34.189 1.00 13.76 N
ATOM 66 CA VAL A 10 2.210 19.569 33.635 1.00 15.31 C
ATOM 67 C VAL A 10 1.199 20.364 34.454 1.00 16.49 C
ATOM 68 O VAL A 10 0.324 21.023 33.893 1.00 13.31 O
ATOM 69 CB VAL A 10 1.731 18.098 33.526 1.00 14.85 C
ATOM 70 CG1 VAL A 10 0.304 18.049 32.982 1.00 16.89 C
ATOM 71 CG2 VAL A 10 2.665 17.310 32.615 1.00 13.51 C
ATOM 72 N LYS A 11 1.318 20.312 35.778 1.00 14.56 N
ATOM 73 CA LYS A 11 0.385 21.047 36.618 1.00 18.34 C
ATOM 74 C LYS A 11 0.537 22.551 36.405 1.00 16.58 C
ATOM 75 O LYS A 11 -0.438 23.290 36.478 1.00 18.09 O
ATOM 76 CB LYS A 11 0.587 20.695 38.099 1.00 18.98 C
ATOM 77 CG LYS A 11 -0.494 21.271 39.011 1.00 26.61 C
ATOM 78 CD LYS A 11 -0.424 20.707 40.429 1.00 27.09 C
ATOM 79 CE LYS A 11 0.851 21.122 41.149 1.00 31.24 C
ATOM 80 NZ LYS A 11 0.946 22.601 41.317 1.00 34.46 N
ATOM 81 N SER A 12 1.756 23.001 36.123 1.00 16.69 N
ATOM 82 CA SER A 12 1.996 24.420 35.892 1.00 16.02 C
ATOM 83 C SER A 12 1.320 24.893 34.603 1.00 17.10 C
ATOM 84 O SER A 12 1.155 26.089 34.392 1.00 14.71 O
ATOM 85 CB SER A 12 3.500 24.708 35.813 1.00 19.31 C
ATOM 86 OG SER A 12 4.058 24.248 34.595 1.00 21.19 O
ATOM 87 N MET A 13 0.929 23.949 33.750 1.00 16.32 N
ATOM 88 CA MET A 13 0.266 24.281 32.487 1.00 18.39 C
ATOM 89 C MET A 13 -1.244 24.463 32.645 1.00 16.18 C
ATOM 90 O MET A 13 -1.930 24.841 31.693 1.00 15.91 O
ATOM 91 CB MET A 13 0.524 23.188 31.445 1.00 18.87 C
ATOM 92 CG MET A 13 1.942 23.124 30.905 1.00 21.81 C
ATOM 93 SD MET A 13 2.139 21.753 29.723 1.00 26.67 S
ATOM 94 CE MET A 13 3.236 20.689 30.628 1.00 28.82 C
ATOM 95 N VAL A 14 -1.764 24.188 33.838 1.00 17.68 N
ATOM 96 CA VAL A 14 -3.196 24.328 34.075 1.00 16.93 C
ATOM 97 C VAL A 14 -3.634 25.772 33.864 1.00 17.33 C
ATOM 98 O VAL A 14 -2.969 26.707 34.309 1.00 15.19 O
ATOM 99 CB VAL A 14 -3.579 23.890 35.502 1.00 17.94 C
ATOM 100 CG1 VAL A 14 -5.011 24.305 35.808 1.00 18.77 C
ATOM 101 CG2 VAL A 14 -3.433 22.381 35.634 1.00 18.66 C
ATOM 102 N GLY A 15 -4.758 25.950 33.185 1.00 15.79 N
ATOM 103 CA GLY A 15 -5.245 27.291 32.922 1.00 16.38 C
ATOM 104 C GLY A 15 -4.672 27.859 31.634 1.00 16.56 C
ATOM 105 O GLY A 15 -5.079 28.922 31.182 1.00 17.25 O
ATOM 106 N LYS A 16 -3.731 27.144 31.033 1.00 16.77 N
ATOM 107 CA LYS A 16 -3.111 27.605 29.796 1.00 16.86 C
ATOM 108 C LYS A 16 -3.387 26.661 28.634 1.00 12.79 C
ATOM 109 O LYS A 16 -3.864 25.549 28.832 1.00 12.68 O
ATOM 110 CB LYS A 16 -1.602 27.766 29.999 1.00 21.71 C
ATOM 111 CG LYS A 16 -1.265 28.678 31.175 1.00 26.90 C
ATOM 112 CD LYS A 16 0.207 29.049 31.229 1.00 32.02 C
ATOM 113 CE LYS A 16 0.461 30.032 32.363 1.00 35.30 C
ATOM 114 NZ LYS A 16 1.866 30.520 32.389 1.00 38.44 N
ATOM 115 N ILE A 17 -3.081 27.124 27.424 1.00 12.25 N
ATOM 116 CA ILE A 17 -3.285 26.353 26.201 1.00 12.39 C
ATOM 117 C ILE A 17 -2.129 25.391 25.954 1.00 11.21 C
ATOM 118 O ILE A 17 -0.964 25.787 25.987 1.00 11.91 O
ATOM 119 CB ILE A 17 -3.378 27.273 24.962 1.00 14.96 C
ATOM 120 CG1 ILE A 17 -4.437 28.356 25.183 1.00 17.81 C
ATOM 121 CG2 ILE A 17 -3.688 26.442 23.718 1.00 14.38 C
ATOM 122 CD1 ILE A 17 -5.817 27.820 25.475 1.00 19.62 C
ATOM 123 N ILE A 18 -2.457 24.130 25.691 1.00 9.41 N
ATOM 124 CA ILE A 18 -1.435 23.126 25.433 1.00 11.75 C
ATOM 125 C ILE A 18 -1.767 22.340 24.172 1.00 13.26 C
ATOM 126 O ILE A 18 -2.911 22.345 23.714 1.00 12.21 O
ATOM 127 CB ILE A 18 -1.308 22.130 26.613 1.00 11.15 C
ATOM 128 CG1 ILE A 18 -2.599 21.318 26.765 1.00 12.77 C
ATOM 129 CG2 ILE A 18 -1.035 22.893 27.908 1.00 13.70 C
ATOM 130 CD1 ILE A 18 -2.487 20.155 27.757 1.00 9.49 C
ATOM 131 N ARG A 19 -0.753 21.679 23.615 1.00 10.70 N
ATOM 132 CA ARG A 19 -0.910 20.856 22.425 1.00 12.91 C
ATOM 133 C ARG A 19 -0.537 19.450 22.869 1.00 11.65 C
ATOM 134 O ARG A 19 0.501 19.255 23.502 1.00 11.52 O
ATOM 135 CB ARG A 19 0.032 21.332 21.307 1.00 14.90 C
ATOM 136 CG ARG A 19 0.014 20.466 20.049 1.00 22.71 C
ATOM 137 CD ARG A 19 0.933 21.036 18.965 1.00 26.27 C
ATOM 138 NE ARG A 19 0.463 22.329 18.478 1.00 30.98 N
ATOM 139 CZ ARG A 19 -0.461 22.488 17.533 1.00 33.47 C
ATOM 140 NH1 ARG A 19 -1.017 21.431 16.957 1.00 35.05 N
ATOM 141 NH2 ARG A 19 -0.838 23.707 17.172 1.00 32.94 N
ATOM 142 N VAL A 20 -1.381 18.478 22.536 1.00 12.81 N
ATOM 143 CA VAL A 20 -1.159 17.090 22.938 1.00 12.18 C
ATOM 144 C VAL A 20 -1.174 16.088 21.795 1.00 14.25 C
ATOM 145 O VAL A 20 -2.064 16.118 20.950 1.00 13.93 O
ATOM 146 CB VAL A 20 -2.244 16.624 23.935 1.00 12.11 C
ATOM 147 CG1 VAL A 20 -1.934 15.208 24.425 1.00 11.83 C
ATOM 148 CG2 VAL A 20 -2.337 17.597 25.091 1.00 11.98 C
ATOM 149 N GLU A 21 -0.188 15.197 21.779 1.00 10.98 N
ATOM 150 CA GLU A 21 -0.146 14.157 20.760 1.00 18.04 C
ATOM 151 C GLU A 21 -0.542 12.861 21.461 1.00 16.71 C
ATOM 152 O GLU A 21 0.068 12.483 22.463 1.00 13.57 O
ATOM 153 CB GLU A 21 1.256 14.026 20.164 1.00 21.82 C
ATOM 154 CG GLU A 21 1.402 12.823 19.248 1.00 29.30 C
ATOM 155 CD GLU A 21 2.719 12.814 18.503 1.00 33.96 C
ATOM 156 OE1 GLU A 21 3.773 12.974 19.154 1.00 36.33 O
ATOM 157 OE2 GLU A 21 2.697 12.641 17.265 1.00 38.97 O
ATOM 158 N MET A 22 -1.573 12.199 20.942 1.00 15.57 N
ATOM 159 CA MET A 22 -2.064 10.952 21.522 1.00 16.49 C
ATOM 160 C MET A 22 -1.633 9.762 20.684 1.00 18.10 C
ATOM 161 O MET A 22 -1.534 9.854 19.458 1.00 19.18 O
ATOM 162 CB MET A 22 -3.595 10.958 21.609 1.00 15.35 C
ATOM 163 CG MET A 22 -4.195 12.065 22.452 1.00 14.61 C
ATOM 164 SD MET A 22 -3.732 11.959 24.195 1.00 14.83 S
ATOM 165 CE MET A 22 -4.691 10.534 24.725 1.00 12.83 C
ATOM 166 N LYS A 23 -1.402 8.638 21.348 1.00 17.43 N
ATOM 167 CA LYS A 23 -0.980 7.423 20.668 1.00 24.78 C
ATOM 168 C LYS A 23 -2.037 6.928 19.680 1.00 30.60 C
ATOM 169 O LYS A 23 -1.712 6.543 18.555 1.00 36.89 O
ATOM 170 CB LYS A 23 -0.663 6.341 21.704 1.00 25.61 C
ATOM 171 CG LYS A 23 -0.090 5.065 21.129 1.00 29.18 C
ATOM 172 CD LYS A 23 0.576 4.231 22.215 1.00 30.69 C
ATOM 173 CE LYS A 23 -0.386 3.902 23.347 1.00 31.48 C
ATOM 174 NZ LYS A 23 0.292 3.202 24.472 1.00 29.40 N
ATOM 175 N GLY A 24 -3.301 6.948 20.093 1.00 34.18 N
ATOM 176 CA GLY A 24 -4.371 6.497 19.217 1.00 42.56 C
ATOM 177 C GLY A 24 -5.054 7.622 18.456 1.00 47.45 C
ATOM 178 O GLY A 24 -6.264 7.576 18.217 1.00 47.89 O
ATOM 179 N GLU A 25 -4.276 8.630 18.070 1.00 48.95 N
ATOM 180 CA GLU A 25 -4.796 9.781 17.332 1.00 49.42 C
ATOM 181 C GLU A 25 -3.753 10.296 16.341 1.00 48.97 C
ATOM 182 O GLU A 25 -2.587 10.469 16.691 1.00 49.84 O
ATOM 183 CB GLU A 25 -5.181 10.893 18.311 1.00 51.57 C
ATOM 184 CG GLU A 25 -6.673 11.190 18.375 1.00 54.39 C
ATOM 185 CD GLU A 25 -7.124 12.157 17.296 1.00 55.59 C
ATOM 186 OE1 GLU A 25 -6.700 13.331 17.340 1.00 56.74 O
ATOM 187 OE2 GLU A 25 -7.898 11.747 16.404 1.00 56.01 O
ATOM 188 N GLU A 26 -4.173 10.543 15.104 1.00 47.72 N
ATOM 189 CA GLU A 26 -3.259 11.031 14.075 1.00 45.76 C
ATOM 190 C GLU A 26 -3.114 12.555 14.071 1.00 42.11 C
ATOM 191 O GLU A 26 -2.105 13.091 13.610 1.00 41.70 O
ATOM 192 CB GLU A 26 -3.716 10.530 12.700 1.00 50.25 C
ATOM 193 CG GLU A 26 -5.198 10.720 12.422 1.00 54.51 C
ATOM 194 CD GLU A 26 -5.687 9.868 11.263 1.00 57.55 C
ATOM 195 OE1 GLU A 26 -5.561 8.627 11.343 1.00 58.81 O
ATOM 196 OE2 GLU A 26 -6.200 10.434 10.273 1.00 59.03 O
ATOM 197 N ASN A 27 -4.122 13.249 14.587 1.00 37.10 N
ATOM 198 CA ASN A 27 -4.090 14.707 14.657 1.00 32.16 C
ATOM 199 C ASN A 27 -3.868 15.104 16.111 1.00 29.56 C
ATOM 200 O ASN A 27 -4.240 14.359 17.014 1.00 28.35 O
ATOM 201 CB ASN A 27 -5.414 15.288 14.166 1.00 31.78 C
ATOM 202 CG ASN A 27 -5.765 14.828 12.771 1.00 33.56 C
ATOM 203 OD1 ASN A 27 -4.942 14.899 11.863 1.00 36.50 O
ATOM 204 ND2 ASN A 27 -6.991 14.358 12.592 1.00 32.62 N
ATOM 205 N GLN A 28 -3.271 16.270 16.338 1.00 25.00 N
ATOM 206 CA GLN A 28 -3.024 16.724 17.701 1.00 24.08 C
ATOM 207 C GLN A 28 -4.244 17.414 18.293 1.00 22.39 C
ATOM 208 O GLN A 28 -5.125 17.875 17.565 1.00 18.75 O
ATOM 209 CB GLN A 28 -1.844 17.701 17.750 1.00 26.69 C
ATOM 210 CG GLN A 28 -0.543 17.179 17.159 1.00 29.60 C
ATOM 211 CD GLN A 28 -0.368 17.579 15.703 1.00 30.51 C
ATOM 212 OE1 GLN A 28 -0.385 18.767 15.369 1.00 28.00 O
ATOM 213 NE2 GLN A 28 -0.194 16.590 14.831 1.00 30.38 N
ATOM 214 N LEU A 29 -4.286 17.478 19.621 1.00 17.60 N
ATOM 215 CA LEU A 29 -5.372 18.146 20.321 1.00 13.82 C
ATOM 216 C LEU A 29 -4.816 19.420 20.934 1.00 14.73 C
ATOM 217 O LEU A 29 -3.747 19.409 21.547 1.00 13.40 O
ATOM 218 CB LEU A 29 -5.950 17.260 21.432 1.00 15.61 C
ATOM 219 CG LEU A 29 -6.698 15.992 21.014 1.00 17.65 C
ATOM 220 CD1 LEU A 29 -7.637 16.309 19.853 1.00 19.13 C
ATOM 221 CD2 LEU A 29 -5.708 14.928 20.603 1.00 23.43 C
ATOM 222 N VAL A 30 -5.537 20.519 20.751 1.00 11.03 N
ATOM 223 CA VAL A 30 -5.125 21.802 21.293 1.00 13.27 C
ATOM 224 C VAL A 30 -6.293 22.362 22.092 1.00 15.06 C
ATOM 225 O VAL A 30 -7.416 22.434 21.589 1.00 13.80 O
ATOM 226 CB VAL A 30 -4.774 22.797 20.169 1.00 17.35 C
ATOM 227 CG1 VAL A 30 -4.356 24.128 20.765 1.00 15.22 C
ATOM 228 CG2 VAL A 30 -3.675 22.222 19.288 1.00 17.67 C
ATOM 229 N GLY A 31 -6.032 22.747 23.338 1.00 13.60 N
ATOM 230 CA GLY A 31 -7.095 23.295 24.163 1.00 12.93 C
ATOM 231 C GLY A 31 -6.592 23.796 25.499 1.00 12.34 C
ATOM 232 O GLY A 31 -5.400 23.721 25.788 1.00 13.21 O
ATOM 233 N LYS A 32 -7.501 24.316 26.314 1.00 13.56 N
ATOM 234 CA LYS A 32 -7.133 24.830 27.624 1.00 11.92 C
ATOM 235 C LYS A 32 -7.103 23.687 28.626 1.00 13.67 C
ATOM 236 O LYS A 32 -8.075 22.929 28.757 1.00 9.82 O
ATOM 237 CB LYS A 32 -8.137 25.890 28.086 1.00 13.57 C
ATOM 238 CG LYS A 32 -7.804 26.518 29.444 1.00 13.10 C
ATOM 239 CD LYS A 32 -8.978 27.341 29.956 1.00 16.44 C
ATOM 240 CE LYS A 32 -8.706 27.900 31.342 1.00 21.19 C
ATOM 241 NZ LYS A 32 -9.960 28.358 32.014 1.00 24.62 N
ATOM 242 N LEU A 33 -5.983 23.561 29.332 1.00 12.31 N
ATOM 243 CA LEU A 33 -5.846 22.507 30.325 1.00 12.95 C
ATOM 244 C LEU A 33 -6.594 22.929 31.583 1.00 14.89 C
ATOM 245 O LEU A 33 -6.157 23.824 32.303 1.00 13.36 O
ATOM 246 CB LEU A 33 -4.368 22.254 30.652 1.00 11.35 C
ATOM 247 CG LEU A 33 -4.109 21.145 31.683 1.00 10.95 C
ATOM 248 CD1 LEU A 33 -4.696 19.834 31.196 1.00 7.68 C
ATOM 249 CD2 LEU A 33 -2.610 21.009 31.924 1.00 10.06 C
ATOM 250 N GLU A 34 -7.733 22.287 31.827 1.00 14.72 N
ATOM 251 CA GLU A 34 -8.561 22.591 32.990 1.00 16.11 C
ATOM 252 C GLU A 34 -8.275 21.677 34.168 1.00 16.23 C
ATOM 253 O GLU A 34 -8.586 22.013 35.309 1.00 17.12 O
ATOM 254 CB GLU A 34 -10.043 22.493 32.618 1.00 20.73 C
ATOM 255 CG GLU A 34 -10.575 23.735 31.939 1.00 29.40 C
ATOM 256 CD GLU A 34 -10.723 24.893 32.901 1.00 33.30 C
ATOM 257 OE1 GLU A 34 -11.617 24.835 33.772 1.00 35.00 O
ATOM 258 OE2 GLU A 34 -9.937 25.855 32.795 1.00 38.23 O
ATOM 259 N GLY A 35 -7.688 20.518 33.893 1.00 14.92 N
ATOM 260 CA GLY A 35 -7.382 19.591 34.966 1.00 17.13 C
ATOM 261 C GLY A 35 -6.471 18.455 34.545 1.00 14.75 C
ATOM 262 O GLY A 35 -6.456 18.053 33.382 1.00 14.72 O
ATOM 263 N VAL A 36 -5.709 17.942 35.503 1.00 14.61 N
ATOM 264 CA VAL A 36 -4.787 16.843 35.263 1.00 14.03 C
ATOM 265 C VAL A 36 -4.567 16.091 36.578 1.00 16.53 C
ATOM 266 O VAL A 36 -4.746 16.663 37.653 1.00 17.71 O
ATOM 267 CB VAL A 36 -3.422 17.370 34.733 1.00 16.01 C
ATOM 268 CG1 VAL A 36 -2.842 18.390 35.704 1.00 17.38 C
ATOM 269 CG2 VAL A 36 -2.449 16.216 34.535 1.00 16.33 C
ATOM 270 N ASP A 37 -4.216 14.808 36.492 1.00 17.00 N
ATOM 271 CA ASP A 37 -3.944 14.013 37.692 1.00 17.81 C
ATOM 272 C ASP A 37 -2.570 13.358 37.589 1.00 18.30 C
ATOM 273 O ASP A 37 -1.870 13.532 36.591 1.00 16.80 O
ATOM 274 CB ASP A 37 -5.022 12.946 37.924 1.00 17.10 C
ATOM 275 CG ASP A 37 -5.245 12.058 36.718 1.00 17.69 C
ATOM 276 OD1 ASP A 37 -4.266 11.760 36.008 1.00 18.62 O
ATOM 277 OD2 ASP A 37 -6.408 11.647 36.494 1.00 17.45 O
ATOM 278 N ASP A 38 -2.190 12.598 38.614 1.00 21.26 N
ATOM 279 CA ASP A 38 -0.882 11.951 38.631 1.00 22.33 C
ATOM 280 C ASP A 38 -0.642 10.929 37.526 1.00 19.90 C
ATOM 281 O ASP A 38 0.502 10.593 37.235 1.00 21.89 O
ATOM 282 CB ASP A 38 -0.621 11.303 39.995 1.00 26.36 C
ATOM 283 CG ASP A 38 -0.423 12.329 41.099 1.00 31.39 C
ATOM 284 OD1 ASP A 38 0.134 13.414 40.815 1.00 31.56 O
ATOM 285 OD2 ASP A 38 -0.809 12.047 42.252 1.00 35.31 O
ATOM 286 N TYR A 39 -1.706 10.428 36.912 1.00 19.47 N
ATOM 287 CA TYR A 39 -1.542 9.463 35.834 1.00 20.09 C
ATOM 288 C TYR A 39 -1.522 10.208 34.503 1.00 17.99 C
ATOM 289 O TYR A 39 -1.531 9.605 33.428 1.00 16.32 O
ATOM 290 CB TYR A 39 -2.682 8.442 35.854 1.00 28.34 C
ATOM 291 CG TYR A 39 -2.775 7.679 37.155 1.00 36.83 C
ATOM 292 CD1 TYR A 39 -3.422 8.226 38.263 1.00 40.12 C
ATOM 293 CD2 TYR A 39 -2.193 6.419 37.288 1.00 39.62 C
ATOM 294 CE1 TYR A 39 -3.487 7.536 39.474 1.00 42.98 C
ATOM 295 CE2 TYR A 39 -2.251 5.721 38.492 1.00 42.48 C
ATOM 296 CZ TYR A 39 -2.899 6.284 39.579 1.00 43.68 C
ATOM 297 OH TYR A 39 -2.962 5.594 40.768 1.00 46.23 O
ATOM 298 N MET A 40 -1.491 11.532 34.598 1.00 16.11 N
ATOM 299 CA MET A 40 -1.483 12.407 33.433 1.00 17.01 C
ATOM 300 C MET A 40 -2.741 12.349 32.568 1.00 17.68 C
ATOM 301 O MET A 40 -2.688 12.578 31.353 1.00 15.78 O
ATOM 302 CB MET A 40 -0.226 12.170 32.586 1.00 19.38 C
ATOM 303 CG MET A 40 1.000 12.863 33.187 1.00 24.63 C
ATOM 304 SD MET A 40 2.492 12.824 32.172 1.00 31.38 S
ATOM 305 CE MET A 40 1.901 13.540 30.713 1.00 16.88 C
ATOM 306 N ASN A 41 -3.871 12.015 33.187 1.00 14.05 N
ATOM 307 CA ASN A 41 -5.131 12.050 32.457 1.00 14.62 C
ATOM 308 C ASN A 41 -5.283 13.557 32.283 1.00 14.43 C
ATOM 309 O ASN A 41 -4.855 14.316 33.150 1.00 12.23 O
ATOM 310 CB ASN A 41 -6.285 11.512 33.302 1.00 11.91 C
ATOM 311 CG ASN A 41 -6.206 10.016 33.501 1.00 15.14 C
ATOM 312 OD1 ASN A 41 -5.977 9.271 32.549 1.00 11.61 O
ATOM 313 ND2 ASN A 41 -6.396 9.566 34.740 1.00 11.10 N
ATOM 314 N LEU A 42 -5.866 13.998 31.175 1.00 12.68 N
ATOM 315 CA LEU A 42 -6.015 15.426 30.943 1.00 14.27 C
ATOM 316 C LEU A 42 -7.451 15.820 30.626 1.00 14.90 C
ATOM 317 O LEU A 42 -8.157 15.116 29.904 1.00 14.11 O
ATOM 318 CB LEU A 42 -5.123 15.869 29.773 1.00 14.12 C
ATOM 319 CG LEU A 42 -3.650 15.452 29.772 1.00 15.28 C
ATOM 320 CD1 LEU A 42 -3.026 15.828 28.435 1.00 14.57 C
ATOM 321 CD2 LEU A 42 -2.908 16.116 30.928 1.00 15.18 C
ATOM 322 N TYR A 43 -7.873 16.954 31.172 1.00 14.49 N
ATOM 323 CA TYR A 43 -9.199 17.480 30.902 1.00 11.72 C
ATOM 324 C TYR A 43 -9.006 18.834 30.233 1.00 12.35 C
ATOM 325 O TYR A 43 -8.531 19.786 30.853 1.00 12.43 O
ATOM 326 CB TYR A 43 -10.020 17.622 32.189 1.00 8.99 C
ATOM 327 CG TYR A 43 -11.322 18.386 32.012 1.00 12.05 C
ATOM 328 CD1 TYR A 43 -12.067 18.279 30.837 1.00 13.25 C
ATOM 329 CD2 TYR A 43 -11.810 19.213 33.022 1.00 13.38 C
ATOM 330 CE1 TYR A 43 -13.260 18.977 30.670 1.00 17.56 C
ATOM 331 CE2 TYR A 43 -13.002 19.915 32.866 1.00 15.44 C
ATOM 332 CZ TYR A 43 -13.720 19.795 31.686 1.00 17.83 C
ATOM 333 OH TYR A 43 -14.884 20.509 31.510 1.00 17.24 O
ATOM 334 N LEU A 44 -9.356 18.895 28.953 1.00 11.88 N
ATOM 335 CA LEU A 44 -9.228 20.117 28.171 1.00 12.68 C
ATOM 336 C LEU A 44 -10.600 20.695 27.867 1.00 10.41 C
ATOM 337 O LEU A 44 -11.572 19.956 27.722 1.00 14.24 O
ATOM 338 CB LEU A 44 -8.525 19.831 26.839 1.00 14.22 C
ATOM 339 CG LEU A 44 -7.134 19.195 26.857 1.00 17.86 C
ATOM 340 CD1 LEU A 44 -6.603 19.100 25.431 1.00 15.18 C
ATOM 341 CD2 LEU A 44 -6.204 20.031 27.714 1.00 18.92 C
ATOM 342 N THR A 45 -10.673 22.016 27.779 1.00 9.36 N
ATOM 343 CA THR A 45 -11.917 22.690 27.442 1.00 9.49 C
ATOM 344 C THR A 45 -11.607 23.551 26.227 1.00 12.47 C
ATOM 345 O THR A 45 -10.441 23.869 25.979 1.00 13.56 O
ATOM 346 CB THR A 45 -12.421 23.591 28.585 1.00 10.31 C
ATOM 347 OG1 THR A 45 -11.404 24.534 28.936 1.00 13.74 O
ATOM 348 CG2 THR A 45 -12.791 22.743 29.815 1.00 12.90 C
ATOM 349 N ASN A 46 -12.640 23.905 25.467 1.00 11.09 N
ATOM 350 CA ASN A 46 -12.470 24.728 24.275 1.00 11.16 C
ATOM 351 C ASN A 46 -11.446 24.076 23.339 1.00 12.84 C
ATOM 352 O ASN A 46 -10.719 24.758 22.618 1.00 14.48 O
ATOM 353 CB ASN A 46 -11.995 26.122 24.698 1.00 12.47 C
ATOM 354 CG ASN A 46 -12.845 26.703 25.819 1.00 13.81 C
ATOM 355 OD1 ASN A 46 -13.993 27.073 25.607 1.00 12.92 O
ATOM 356 ND2 ASN A 46 -12.286 26.760 27.026 1.00 15.15 N
ATOM 357 N ALA A 47 -11.417 22.749 23.343 1.00 12.36 N
ATOM 358 CA ALA A 47 -10.466 21.994 22.540 1.00 11.04 C
ATOM 359 C ALA A 47 -10.793 21.868 21.060 1.00 13.51 C
ATOM 360 O ALA A 47 -11.946 21.978 20.642 1.00 14.67 O
ATOM 361 CB ALA A 47 -10.285 20.612 23.133 1.00 13.09 C
ATOM 362 N MET A 48 -9.754 21.616 20.276 1.00 14.15 N
ATOM 363 CA MET A 48 -9.897 21.439 18.840 1.00 20.38 C
ATOM 364 C MET A 48 -8.875 20.424 18.353 1.00 19.08 C
ATOM 365 O MET A 48 -7.837 20.216 18.979 1.00 16.15 O
ATOM 366 CB MET A 48 -9.684 22.766 18.111 1.00 25.54 C
ATOM 367 CG MET A 48 -8.323 23.386 18.339 1.00 32.64 C
ATOM 368 SD MET A 48 -8.117 24.935 17.445 1.00 41.02 S
ATOM 369 CE MET A 48 -8.810 26.109 18.624 1.00 40.25 C
ATOM 370 N GLU A 49 -9.182 19.789 17.232 1.00 17.46 N
ATOM 371 CA GLU A 49 -8.283 18.816 16.643 1.00 19.10 C
ATOM 372 C GLU A 49 -7.502 19.618 15.608 1.00 19.95 C
ATOM 373 O GLU A 49 -8.097 20.329 14.794 1.00 18.79 O
ATOM 374 CB GLU A 49 -9.096 17.710 15.975 1.00 20.68 C
ATOM 375 CG GLU A 49 -8.314 16.481 15.592 1.00 28.05 C
ATOM 376 CD GLU A 49 -9.216 15.390 15.050 1.00 31.22 C
ATOM 377 OE1 GLU A 49 -10.199 15.036 15.734 1.00 33.97 O
ATOM 378 OE2 GLU A 49 -8.944 14.888 13.943 1.00 35.11 O
ATOM 379 N CYS A 50 -6.177 19.517 15.648 1.00 18.43 N
ATOM 380 CA CYS A 50 -5.336 20.259 14.724 1.00 23.55 C
ATOM 381 C CYS A 50 -4.248 19.405 14.085 1.00 24.85 C
ATOM 382 O CYS A 50 -3.914 18.326 14.566 1.00 24.75 O
ATOM 383 CB CYS A 50 -4.657 21.435 15.446 1.00 23.56 C
ATOM 384 SG CYS A 50 -5.758 22.646 16.233 1.00 27.18 S
ATOM 385 N LYS A 51 -3.717 19.914 12.981 1.00 27.16 N
ATOM 386 CA LYS A 51 -2.622 19.288 12.251 1.00 32.30 C
ATOM 387 C LYS A 51 -1.641 20.440 12.102 1.00 34.33 C
ATOM 388 O LYS A 51 -1.568 21.084 11.056 1.00 36.68 O
ATOM 389 CB LYS A 51 -3.077 18.808 10.872 1.00 33.18 C
ATOM 390 CG LYS A 51 -3.635 17.397 10.855 1.00 35.44 C
ATOM 391 CD LYS A 51 -4.003 16.983 9.438 1.00 37.00 C
ATOM 392 CE LYS A 51 -3.826 15.491 9.244 1.00 37.26 C
ATOM 393 NZ LYS A 51 -2.402 15.109 9.430 1.00 37.82 N
ATOM 394 N GLY A 52 -0.899 20.709 13.168 1.00 36.17 N
ATOM 395 CA GLY A 52 0.026 21.821 13.143 1.00 36.07 C
ATOM 396 C GLY A 52 -0.820 23.043 13.431 1.00 37.69 C
ATOM 397 O GLY A 52 -1.597 23.048 14.389 1.00 37.36 O
ATOM 398 N GLU A 53 -0.701 24.072 12.601 1.00 36.96 N
ATOM 399 CA GLU A 53 -1.482 25.283 12.804 1.00 38.00 C
ATOM 400 C GLU A 53 -2.834 25.198 12.096 1.00 35.81 C
ATOM 401 O GLU A 53 -3.601 26.161 12.088 1.00 36.99 O
ATOM 402 CB GLU A 53 -0.702 26.498 12.300 1.00 40.98 C
ATOM 403 CG GLU A 53 0.684 26.638 12.912 1.00 46.00 C
ATOM 404 CD GLU A 53 0.650 26.740 14.428 1.00 49.17 C
ATOM 405 OE1 GLU A 53 0.021 27.685 14.948 1.00 51.39 O
ATOM 406 OE2 GLU A 53 1.254 25.876 15.099 1.00 50.07 O
ATOM 407 N GLU A 54 -3.127 24.039 11.514 1.00 32.81 N
ATOM 408 CA GLU A 54 -4.384 23.836 10.800 1.00 30.87 C
ATOM 409 C GLU A 54 -5.459 23.148 11.636 1.00 27.61 C
ATOM 410 O GLU A 54 -5.292 22.012 12.073 1.00 29.24 O
ATOM 411 CB GLU A 54 -4.142 23.017 9.529 1.00 34.29 C
ATOM 412 CG GLU A 54 -3.244 23.695 8.508 1.00 37.10 C
ATOM 413 CD GLU A 54 -3.822 25.003 8.002 1.00 39.05 C
ATOM 414 OE1 GLU A 54 -4.943 24.988 7.450 1.00 39.81 O
ATOM 415 OE2 GLU A 54 -3.154 26.046 8.156 1.00 41.42 O
ATOM 416 N LYS A 55 -6.568 23.850 11.838 1.00 26.15 N
ATOM 417 CA LYS A 55 -7.711 23.348 12.596 1.00 24.91 C
ATOM 418 C LYS A 55 -8.569 22.444 11.706 1.00 26.12 C
ATOM 419 O LYS A 55 -8.917 22.822 10.583 1.00 24.82 O
ATOM 420 CB LYS A 55 -8.534 24.541 13.092 1.00 28.30 C
ATOM 421 CG LYS A 55 -9.994 24.267 13.404 1.00 31.15 C
ATOM 422 CD LYS A 55 -10.182 23.525 14.709 1.00 35.12 C
ATOM 423 CE LYS A 55 -11.247 24.205 15.559 1.00 34.85 C
ATOM 424 NZ LYS A 55 -12.498 24.462 14.793 1.00 38.47 N
ATOM 425 N VAL A 56 -8.909 21.254 12.201 1.00 22.26 N
ATOM 426 CA VAL A 56 -9.725 20.323 11.428 1.00 22.11 C
ATOM 427 C VAL A 56 -11.068 19.976 12.069 1.00 22.94 C
ATOM 428 O VAL A 56 -12.012 19.634 11.368 1.00 20.13 O
ATOM 429 CB VAL A 56 -8.961 19.009 11.139 1.00 24.28 C
ATOM 430 CG1 VAL A 56 -7.697 19.310 10.350 1.00 24.86 C
ATOM 431 CG2 VAL A 56 -8.621 18.301 12.432 1.00 22.83 C
ATOM 432 N ARG A 57 -11.157 20.058 13.397 1.00 21.31 N
ATOM 433 CA ARG A 57 -12.406 19.756 14.099 1.00 21.32 C
ATOM 434 C ARG A 57 -12.516 20.484 15.434 1.00 22.16 C
ATOM 435 O ARG A 57 -11.537 20.594 16.164 1.00 19.00 O
ATOM 436 CB ARG A 57 -12.530 18.257 14.400 1.00 26.83 C
ATOM 437 CG ARG A 57 -12.853 17.346 13.238 1.00 32.40 C
ATOM 438 CD ARG A 57 -13.407 16.027 13.777 1.00 34.30 C
ATOM 439 NE ARG A 57 -13.641 15.028 12.739 1.00 38.31 N
ATOM 440 CZ ARG A 57 -12.696 14.251 12.217 1.00 40.20 C
ATOM 441 NH1 ARG A 57 -11.440 14.353 12.635 1.00 38.65 N
ATOM 442 NH2 ARG A 57 -13.010 13.365 11.280 1.00 41.69 N
ATOM 443 N SER A 58 -13.711 20.975 15.747 1.00 22.24 N
ATOM 444 CA SER A 58 -13.959 21.637 17.027 1.00 21.16 C
ATOM 445 C SER A 58 -14.431 20.522 17.951 1.00 20.11 C
ATOM 446 O SER A 58 -15.267 19.706 17.557 1.00 23.47 O
ATOM 447 CB SER A 58 -15.055 22.702 16.895 1.00 22.39 C
ATOM 448 OG SER A 58 -14.558 23.866 16.265 1.00 25.78 O
ATOM 449 N LEU A 59 -13.906 20.479 19.170 1.00 16.60 N
ATOM 450 CA LEU A 59 -14.273 19.428 20.106 1.00 18.57 C
ATOM 451 C LEU A 59 -14.919 19.913 21.403 1.00 18.10 C
ATOM 452 O LEU A 59 -15.794 19.246 21.941 1.00 21.22 O
ATOM 453 CB LEU A 59 -13.037 18.589 20.446 1.00 21.78 C
ATOM 454 CG LEU A 59 -12.288 17.936 19.281 1.00 20.89 C
ATOM 455 CD1 LEU A 59 -11.063 17.204 19.813 1.00 25.63 C
ATOM 456 CD2 LEU A 59 -13.200 16.972 18.550 1.00 21.80 C
ATOM 457 N GLY A 60 -14.483 21.061 21.909 1.00 13.34 N
ATOM 458 CA GLY A 60 -15.051 21.564 23.146 1.00 14.81 C
ATOM 459 C GLY A 60 -14.425 20.861 24.338 1.00 12.11 C
ATOM 460 O GLY A 60 -13.203 20.834 24.474 1.00 13.49 O
ATOM 461 N GLU A 61 -15.255 20.281 25.194 1.00 11.35 N
ATOM 462 CA GLU A 61 -14.761 19.579 26.375 1.00 14.34 C
ATOM 463 C GLU A 61 -14.358 18.139 26.064 1.00 12.24 C
ATOM 464 O GLU A 61 -15.143 17.382 25.498 1.00 10.89 O
ATOM 465 CB GLU A 61 -15.832 19.547 27.468 1.00 16.30 C
ATOM 466 CG GLU A 61 -16.337 20.899 27.920 1.00 17.55 C
ATOM 467 CD GLU A 61 -17.277 20.783 29.106 1.00 22.60 C
ATOM 468 OE1 GLU A 61 -18.254 20.011 29.021 1.00 20.88 O
ATOM 469 OE2 GLU A 61 -17.042 21.465 30.123 1.00 25.49 O
ATOM 470 N ILE A 62 -13.140 17.755 26.433 1.00 11.62 N
ATOM 471 CA ILE A 62 -12.694 16.378 26.207 1.00 11.62 C
ATOM 472 C ILE A 62 -11.768 15.915 27.320 1.00 12.85 C
ATOM 473 O ILE A 62 -11.080 16.717 27.941 1.00 11.49 O
ATOM 474 CB ILE A 62 -11.921 16.204 24.875 1.00 11.98 C
ATOM 475 CG1 ILE A 62 -10.708 17.137 24.853 1.00 15.00 C
ATOM 476 CG2 ILE A 62 -12.838 16.470 23.683 1.00 15.73 C
ATOM 477 CD1 ILE A 62 -9.795 16.919 23.657 1.00 15.99 C
ATOM 478 N VAL A 63 -11.756 14.611 27.559 1.00 12.59 N
ATOM 479 CA VAL A 63 -10.890 14.023 28.568 1.00 12.70 C
ATOM 480 C VAL A 63 -9.946 13.064 27.851 1.00 12.11 C
ATOM 481 O VAL A 63 -10.392 12.168 27.128 1.00 12.86 O
ATOM 482 CB VAL A 63 -11.705 13.247 29.623 1.00 13.16 C
ATOM 483 CG1 VAL A 63 -10.774 12.438 30.511 1.00 12.01 C
ATOM 484 CG2 VAL A 63 -12.537 14.224 30.454 1.00 11.50 C
ATOM 485 N LEU A 64 -8.645 13.262 28.040 1.00 11.28 N
ATOM 486 CA LEU A 64 -7.641 12.411 27.405 1.00 10.77 C
ATOM 487 C LEU A 64 -7.077 11.410 28.416 1.00 13.62 C
ATOM 488 O LEU A 64 -6.724 11.779 29.537 1.00 14.37 O
ATOM 489 CB LEU A 64 -6.514 13.275 26.826 1.00 13.71 C
ATOM 490 CG LEU A 64 -6.967 14.372 25.845 1.00 15.56 C
ATOM 491 CD1 LEU A 64 -5.759 15.158 25.332 1.00 14.13 C
ATOM 492 CD2 LEU A 64 -7.717 13.741 24.688 1.00 15.63 C
ATOM 493 N ARG A 65 -7.007 10.141 28.019 1.00 12.50 N
ATOM 494 CA ARG A 65 -6.492 9.094 28.896 1.00 12.04 C
ATOM 495 C ARG A 65 -4.972 9.202 29.001 1.00 12.71 C
ATOM 496 O ARG A 65 -4.270 9.150 27.998 1.00 9.50 O
ATOM 497 CB ARG A 65 -6.879 7.719 28.354 1.00 11.52 C
ATOM 498 CG ARG A 65 -6.501 6.560 29.249 1.00 15.06 C
ATOM 499 CD ARG A 65 -7.298 6.591 30.545 1.00 16.75 C
ATOM 500 NE ARG A 65 -7.021 5.426 31.378 1.00 21.45 N
ATOM 501 CZ ARG A 65 -6.017 5.340 32.243 1.00 24.46 C
ATOM 502 NH1 ARG A 65 -5.181 6.360 32.397 1.00 27.58 N
ATOM 503 NH2 ARG A 65 -5.853 4.232 32.956 1.00 24.35 N
ATOM 504 N GLY A 66 -4.481 9.339 30.229 1.00 9.02 N
ATOM 505 CA GLY A 66 -3.054 9.482 30.466 1.00 9.34 C
ATOM 506 C GLY A 66 -2.092 8.480 29.847 1.00 11.68 C
ATOM 507 O GLY A 66 -1.059 8.875 29.302 1.00 13.98 O
ATOM 508 N ASN A 67 -2.394 7.190 29.909 1.00 12.26 N
ATOM 509 CA ASN A 67 -1.444 6.242 29.343 1.00 17.65 C
ATOM 510 C ASN A 67 -1.398 6.276 27.821 1.00 14.32 C
ATOM 511 O ASN A 67 -0.567 5.610 27.219 1.00 14.19 O
ATOM 512 CB ASN A 67 -1.708 4.816 29.832 1.00 24.07 C
ATOM 513 CG ASN A 67 -3.043 4.293 29.402 1.00 26.78 C
ATOM 514 OD1 ASN A 67 -4.078 4.703 29.922 1.00 32.41 O
ATOM 515 ND2 ASN A 67 -3.034 3.378 28.438 1.00 30.24 N
ATOM 516 N ASN A 68 -2.284 7.046 27.198 1.00 12.47 N
ATOM 517 CA ASN A 68 -2.265 7.155 25.740 1.00 12.98 C
ATOM 518 C ASN A 68 -1.764 8.517 25.275 1.00 14.35 C
ATOM 519 O ASN A 68 -1.749 8.832 24.074 1.00 12.18 O
ATOM 520 CB ASN A 68 -3.638 6.821 25.157 1.00 12.57 C
ATOM 521 CG ASN A 68 -3.929 5.332 25.237 1.00 14.23 C
ATOM 522 OD1 ASN A 68 -3.059 4.516 24.941 1.00 14.44 O
ATOM 523 ND2 ASN A 68 -5.137 4.973 25.642 1.00 12.25 N
ATOM 524 N VAL A 69 -1.334 9.320 26.242 1.00 11.13 N
ATOM 525 CA VAL A 69 -0.759 10.627 25.944 1.00 12.90 C
ATOM 526 C VAL A 69 0.683 10.334 25.549 1.00 12.03 C
ATOM 527 O VAL A 69 1.358 9.544 26.210 1.00 13.49 O
ATOM 528 CB VAL A 69 -0.727 11.547 27.188 1.00 12.99 C
ATOM 529 CG1 VAL A 69 0.153 12.762 26.911 1.00 10.85 C
ATOM 530 CG2 VAL A 69 -2.139 12.001 27.542 1.00 13.91 C
ATOM 531 N VAL A 70 1.151 10.943 24.467 1.00 10.26 N
ATOM 532 CA VAL A 70 2.528 10.731 24.033 1.00 9.03 C
ATOM 533 C VAL A 70 3.400 11.924 24.404 1.00 10.37 C
ATOM 534 O VAL A 70 4.432 11.780 25.068 1.00 13.74 O
ATOM 535 CB VAL A 70 2.615 10.514 22.497 1.00 12.59 C
ATOM 536 CG1 VAL A 70 4.081 10.428 22.062 1.00 11.93 C
ATOM 537 CG2 VAL A 70 1.873 9.233 22.111 1.00 12.95 C
ATOM 538 N LEU A 71 2.961 13.107 23.998 1.00 10.76 N
ATOM 539 CA LEU A 71 3.715 14.326 24.240 1.00 14.37 C
ATOM 540 C LEU A 71 2.794 15.503 24.555 1.00 13.59 C
ATOM 541 O LEU A 71 1.719 15.630 23.971 1.00 14.87 O
ATOM 542 CB LEU A 71 4.570 14.624 22.996 1.00 15.71 C
ATOM 543 CG LEU A 71 5.461 15.868 22.896 1.00 19.18 C
ATOM 544 CD1 LEU A 71 6.419 15.707 21.707 1.00 18.54 C
ATOM 545 CD2 LEU A 71 4.608 17.112 22.718 1.00 19.07 C
ATOM 546 N ILE A 72 3.222 16.352 25.486 1.00 11.85 N
ATOM 547 CA ILE A 72 2.462 17.539 25.873 1.00 12.14 C
ATOM 548 C ILE A 72 3.381 18.733 25.675 1.00 13.51 C
ATOM 549 O ILE A 72 4.530 18.713 26.100 1.00 13.00 O
ATOM 550 CB ILE A 72 2.034 17.504 27.358 1.00 15.00 C
ATOM 551 CG1 ILE A 72 1.160 16.279 27.625 1.00 13.31 C
ATOM 552 CG2 ILE A 72 1.271 18.792 27.709 1.00 15.75 C
ATOM 553 CD1 ILE A 72 0.729 16.143 29.089 1.00 16.07 C
ATOM 554 N GLN A 73 2.873 19.771 25.025 1.00 15.97 N
ATOM 555 CA GLN A 73 3.672 20.956 24.757 1.00 17.94 C
ATOM 556 C GLN A 73 2.888 22.228 25.027 1.00 19.26 C
ATOM 557 O GLN A 73 1.786 22.403 24.510 1.00 19.75 O
ATOM 558 CB GLN A 73 4.131 20.945 23.291 1.00 20.01 C
ATOM 559 CG GLN A 73 4.765 22.245 22.814 1.00 22.80 C
ATOM 560 CD GLN A 73 5.007 22.264 21.314 1.00 24.83 C
ATOM 561 OE1 GLN A 73 4.101 21.995 20.524 1.00 25.58 O
ATOM 562 NE2 GLN A 73 6.231 22.590 20.914 1.00 24.85 N
ATOM 563 N PRO A 74 3.439 23.128 25.855 1.00 21.71 N
ATOM 564 CA PRO A 74 2.730 24.378 26.139 1.00 23.39 C
ATOM 565 C PRO A 74 2.545 25.060 24.787 1.00 28.88 C
ATOM 566 O PRO A 74 3.427 24.976 23.930 1.00 28.01 O
ATOM 567 CB PRO A 74 3.710 25.137 27.030 1.00 25.69 C
ATOM 568 CG PRO A 74 4.464 24.033 27.726 1.00 25.64 C
ATOM 569 CD PRO A 74 4.709 23.061 26.601 1.00 23.40 C
ATOM 570 N GLN A 75 1.410 25.712 24.577 1.00 32.73 N
ATOM 571 CA GLN A 75 1.186 26.375 23.301 1.00 39.17 C
ATOM 572 C GLN A 75 1.552 27.849 23.402 1.00 42.29 C
ATOM 573 O GLN A 75 1.661 28.347 24.543 1.00 44.20 O
ATOM 574 CB GLN A 75 -0.274 26.223 22.874 1.00 41.26 C
ATOM 575 CG GLN A 75 -0.555 26.679 21.451 1.00 46.85 C
ATOM 576 CD GLN A 75 0.276 25.931 20.423 1.00 49.37 C
ATOM 577 OE1 GLN A 75 1.504 26.035 20.403 1.00 50.93 O
ATOM 578 NE2 GLN A 75 -0.392 25.169 19.565 1.00 50.14 N
TER 579 GLN A 75
HETATM 580 CD CD A 78 0.000 0.000 21.937 0.17 61.72 CD
HETATM 581 C ACY A 201 0.588 16.434 11.242 1.00 51.60 C
HETATM 582 O ACY A 201 1.289 16.199 10.168 1.00 52.86 O
HETATM 583 OXT ACY A 201 -0.447 15.802 11.650 1.00 51.61 O
HETATM 584 CH3 ACY A 201 1.113 17.604 12.057 1.00 51.74 C
HETATM 585 C ACY A 202 -16.124 22.064 13.139 1.00 44.74 C
HETATM 586 O ACY A 202 -15.330 23.087 13.303 1.00 45.43 O
HETATM 587 OXT ACY A 202 -15.878 20.837 13.406 1.00 44.17 O
HETATM 588 CH3 ACY A 202 -17.478 22.439 12.565 1.00 45.13 C
HETATM 589 C ACY A 203 -19.085 20.723 25.138 1.00 30.72 C
HETATM 590 O ACY A 203 -17.820 21.006 25.001 1.00 27.32 O
HETATM 591 OXT ACY A 203 -19.656 19.592 24.937 1.00 34.61 O
HETATM 592 CH3 ACY A 203 -19.920 21.909 25.585 1.00 26.21 C
HETATM 593 O HOH A 307 0.000 33.729 35.203 0.50 44.16 O
HETATM 594 O HOH A 309 -14.605 25.297 32.084 0.50 32.50 O
HETATM 595 O HOH A 316 -2.773 12.841 18.475 1.00 32.51 O
HETATM 596 O HOH A 317 -8.600 26.641 22.997 1.00 29.31 O
HETATM 597 O HOH A 319 -1.318 26.677 36.680 1.00 37.58 O
HETATM 598 O HOH A 320 3.352 22.733 39.368 1.00 37.01 O
HETATM 599 O HOH A 323 -1.196 24.784 6.603 1.00 47.79 O
HETATM 600 O HOH A 324 18.373 22.770 36.334 1.00 44.77 O
HETATM 601 O HOH A 330 -6.553 30.933 32.628 1.00 36.16 O
HETATM 602 O HOH A 377 -8.617 12.457 37.852 1.00 7.32 O
HETATM 603 O HOH A 382 -16.313 23.846 30.081 1.00 19.10 O
HETATM 604 O HOH A 385 -17.288 18.182 24.062 1.00 26.97 O
HETATM 605 O HOH A 387 -1.722 29.817 27.238 1.00 27.14 O
HETATM 606 O HOH A 398 -14.605 25.297 20.944 0.50 48.63 O
HETATM 607 O HOH A 401 -5.952 12.980 9.790 1.00 29.37 O
HETATM 608 O HOH A 404 -15.906 21.840 33.538 1.00 46.91 O
HETATM 609 O HOH A 405 -2.397 2.618 19.050 1.00 42.44 O
HETATM 610 O HOH A 409 3.734 21.614 43.710 1.00 46.20 O
HETATM 611 O HOH A 411 -8.261 10.755 12.821 1.00 46.00 O
HETATM 612 O HOH A 415 -1.265 16.103 6.863 1.00 36.28 O
HETATM 613 O HOH A 421 0.067 16.574 4.720 1.00 35.13 O
HETATM 614 O HOH A 422 17.588 19.870 35.658 1.00 39.78 O
HETATM 615 O HOH A 424 -17.449 17.800 18.055 1.00 41.00 O
HETATM 616 O HOH A 426 -3.858 31.887 30.436 1.00 36.03 O
HETATM 617 O HOH A 428 0.993 25.088 8.070 1.00 40.80 O
HETATM 618 O HOH A 430 -4.072 7.167 15.867 1.00 40.07 O
HETATM 619 O HOH A 431 -1.597 30.443 23.424 1.00 37.68 O
HETATM 620 O HOH A 436 -0.387 9.278 42.936 1.00 45.52 O
HETATM 621 O HOH A 442 0.000 0.000 27.450 0.17 44.43 O
HETATM 622 O HOH A 443 -8.569 12.038 40.572 1.00 31.79 O
HETATM 623 O HOH A 444 0.000 0.000 18.270 0.17 39.19 O
HETATM 624 O HOH A 445 -5.372 5.610 36.213 1.00 54.10 O
HETATM 625 O HOH A 446 -3.541 12.178 8.896 1.00 33.30 O
CONECT 581 582 583 584
CONECT 582 581
CONECT 583 581
CONECT 584 581
CONECT 585 586 587 588
CONECT 586 585
CONECT 587 585
CONECT 588 585
CONECT 589 590 591 592
CONECT 590 589
CONECT 591 589
CONECT 592 589
MASTER 325 0 4 2 5 0 4 6 624 1 12 6
END
PyCogent-1.5.3/tests/data/2E12.pdb 000644 000765 000024 00000476355 11305747275 017452 0 ustar 00jrideout staff 000000 000000 HEADER TRANSLATION 17-OCT-06 2E12
TITLE THE CRYSTAL STRUCTURE OF XC5848 FROM XANTHOMONAS CAMPESTRIS
TITLE 2 ADOPTING A NOVEL VARIANT OF SM-LIKE MOTIF
COMPND MOL_ID: 1;
COMPND 2 MOLECULE: HYPOTHETICAL PROTEIN XCC3642;
COMPND 3 CHAIN: A, B;
COMPND 4 SYNONYM: SM-LIKE MOTIF;
COMPND 5 ENGINEERED: YES
SOURCE MOL_ID: 1;
SOURCE 2 ORGANISM_SCIENTIFIC: XANTHOMONAS CAMPESTRIS PV. CAMPESTRIS;
SOURCE 3 ORGANISM_TAXID: 340;
SOURCE 4 STRAIN: PV. CAMPESTRIS;
SOURCE 5 EXPRESSION_SYSTEM: ESCHERICHIA COLI;
SOURCE 6 EXPRESSION_SYSTEM_TAXID: 562
KEYWDS NOVEL SM-LIKE MOTIF, LSM MOTIF, XANTHOMONAS CAMPESTRIS, X-
KEYWDS 2 RAY CRYSTALLOGRAPHY, TRANSLATION
EXPDTA X-RAY DIFFRACTION
AUTHOR K.-H.CHIN,S.-K.RUAN,A.H.-J.WANG,S.-H.CHOU
REVDAT 2 24-FEB-09 2E12 1 VERSN
REVDAT 1 30-OCT-07 2E12 0
JRNL AUTH K.-H.CHIN,S.-K.RUAN,A.H.-J.WANG,S.-H.CHOU
JRNL TITL XC5848, AN ORFAN PROTEIN FROM XANTHOMONAS
JRNL TITL 2 CAMPESTRIS, ADOPTS A NOVEL VARIANT OF SM-LIKE MOTIF
JRNL REF PROTEINS V. 68 1006 2007
JRNL REFN ISSN 0887-3585
JRNL PMID 17546661
JRNL DOI 10.1002/PROT.21375
REMARK 1
REMARK 2
REMARK 2 RESOLUTION. 1.70 ANGSTROMS.
REMARK 3
REMARK 3 REFINEMENT.
REMARK 3 PROGRAM : CNS
REMARK 3 AUTHORS : BRUNGER,ADAMS,CLORE,DELANO,GROS,GROSSE-
REMARK 3 : KUNSTLEVE,JIANG,KUSZEWSKI,NILGES, PANNU,
REMARK 3 : READ,RICE,SIMONSON,WARREN
REMARK 3
REMARK 3 REFINEMENT TARGET : NULL
REMARK 3
REMARK 3 DATA USED IN REFINEMENT.
REMARK 3 RESOLUTION RANGE HIGH (ANGSTROMS) : 1.70
REMARK 3 RESOLUTION RANGE LOW (ANGSTROMS) : 30.00
REMARK 3 DATA CUTOFF (SIGMA(F)) : 5.000
REMARK 3 DATA CUTOFF HIGH (ABS(F)) : NULL
REMARK 3 DATA CUTOFF LOW (ABS(F)) : NULL
REMARK 3 COMPLETENESS (WORKING+TEST) (%) : 99.1
REMARK 3 NUMBER OF REFLECTIONS : 6937
REMARK 3
REMARK 3 FIT TO DATA USED IN REFINEMENT.
REMARK 3 CROSS-VALIDATION METHOD : THROUGHOUT
REMARK 3 FREE R VALUE TEST SET SELECTION : RANDOM
REMARK 3 R VALUE (WORKING SET) : 0.220
REMARK 3 FREE R VALUE : 0.280
REMARK 3 FREE R VALUE TEST SET SIZE (%) : NULL
REMARK 3 FREE R VALUE TEST SET COUNT : NULL
REMARK 3 ESTIMATED ERROR OF FREE R VALUE : NULL
REMARK 3
REMARK 3 FIT IN THE HIGHEST RESOLUTION BIN.
REMARK 3 TOTAL NUMBER OF BINS USED : NULL
REMARK 3 BIN RESOLUTION RANGE HIGH (A) : 1.70
REMARK 3 BIN RESOLUTION RANGE LOW (A) : 1.75
REMARK 3 BIN COMPLETENESS (WORKING+TEST) (%) : 97.00
REMARK 3 REFLECTIONS IN BIN (WORKING SET) : NULL
REMARK 3 BIN R VALUE (WORKING SET) : 0.2400
REMARK 3 BIN FREE R VALUE : 0.2200
REMARK 3 BIN FREE R VALUE TEST SET SIZE (%) : NULL
REMARK 3 BIN FREE R VALUE TEST SET COUNT : NULL
REMARK 3 ESTIMATED ERROR OF BIN FREE R VALUE : 0.012
REMARK 3
REMARK 3 NUMBER OF NON-HYDROGEN ATOMS USED IN REFINEMENT.
REMARK 3 PROTEIN ATOMS : 1512
REMARK 3 NUCLEIC ACID ATOMS : 0
REMARK 3 HETEROGEN ATOMS : 0
REMARK 3 SOLVENT ATOMS : 122
REMARK 3
REMARK 3 B VALUES.
REMARK 3 FROM WILSON PLOT (A**2) : 24.00
REMARK 3 MEAN B VALUE (OVERALL, A**2) : NULL
REMARK 3 OVERALL ANISOTROPIC B VALUE.
REMARK 3 B11 (A**2) : NULL
REMARK 3 B22 (A**2) : NULL
REMARK 3 B33 (A**2) : NULL
REMARK 3 B12 (A**2) : NULL
REMARK 3 B13 (A**2) : NULL
REMARK 3 B23 (A**2) : NULL
REMARK 3
REMARK 3 ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM LUZZATI PLOT (A) : NULL
REMARK 3 ESD FROM SIGMAA (A) : NULL
REMARK 3 LOW RESOLUTION CUTOFF (A) : NULL
REMARK 3
REMARK 3 CROSS-VALIDATED ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM C-V LUZZATI PLOT (A) : NULL
REMARK 3 ESD FROM C-V SIGMAA (A) : NULL
REMARK 3
REMARK 3 RMS DEVIATIONS FROM IDEAL VALUES.
REMARK 3 BOND LENGTHS (A) : 0.007
REMARK 3 BOND ANGLES (DEGREES) : 1.32
REMARK 3 DIHEDRAL ANGLES (DEGREES) : NULL
REMARK 3 IMPROPER ANGLES (DEGREES) : NULL
REMARK 3
REMARK 3 ISOTROPIC THERMAL MODEL : NULL
REMARK 3
REMARK 3 ISOTROPIC THERMAL FACTOR RESTRAINTS. RMS SIGMA
REMARK 3 MAIN-CHAIN BOND (A**2) : NULL ; NULL
REMARK 3 MAIN-CHAIN ANGLE (A**2) : NULL ; NULL
REMARK 3 SIDE-CHAIN BOND (A**2) : NULL ; NULL
REMARK 3 SIDE-CHAIN ANGLE (A**2) : NULL ; NULL
REMARK 3
REMARK 3 BULK SOLVENT MODELING.
REMARK 3 METHOD USED : NULL
REMARK 3 KSOL : NULL
REMARK 3 BSOL : NULL
REMARK 3
REMARK 3 NCS MODEL : NULL
REMARK 3
REMARK 3 NCS RESTRAINTS. RMS SIGMA/WEIGHT
REMARK 3 GROUP 1 POSITIONAL (A) : NULL ; NULL
REMARK 3 GROUP 1 B-FACTOR (A**2) : NULL ; NULL
REMARK 3
REMARK 3 PARAMETER FILE 1 : NULL
REMARK 3 TOPOLOGY FILE 1 : NULL
REMARK 3
REMARK 3 OTHER REFINEMENT REMARKS: NULL
REMARK 4
REMARK 4 2E12 COMPLIES WITH FORMAT V. 3.15, 01-DEC-08
REMARK 100
REMARK 100 THIS ENTRY HAS BEEN PROCESSED BY PDBJ ON 19-OCT-06.
REMARK 100 THE RCSB ID CODE IS RCSB026092.
REMARK 200
REMARK 200 EXPERIMENTAL DETAILS
REMARK 200 EXPERIMENT TYPE : X-RAY DIFFRACTION
REMARK 200 DATE OF DATA COLLECTION : 28-JUL-06
REMARK 200 TEMPERATURE (KELVIN) : 100
REMARK 200 PH : 8.0
REMARK 200 NUMBER OF CRYSTALS USED : 10
REMARK 200
REMARK 200 SYNCHROTRON (Y/N) : Y
REMARK 200 RADIATION SOURCE : NSRRC
REMARK 200 BEAMLINE : BL13B1
REMARK 200 X-RAY GENERATOR MODEL : NULL
REMARK 200 MONOCHROMATIC OR LAUE (M/L) : M
REMARK 200 WAVELENGTH OR RANGE (A) : 0.96437, 0.97983
REMARK 200 MONOCHROMATOR : NULL
REMARK 200 OPTICS : NULL
REMARK 200
REMARK 200 DETECTOR TYPE : CCD
REMARK 200 DETECTOR MANUFACTURER : ADSC QUANTUM 315
REMARK 200 INTENSITY-INTEGRATION SOFTWARE : DENZO
REMARK 200 DATA SCALING SOFTWARE : HKL-2000
REMARK 200
REMARK 200 NUMBER OF UNIQUE REFLECTIONS : 6937
REMARK 200 RESOLUTION RANGE HIGH (A) : 1.700
REMARK 200 RESOLUTION RANGE LOW (A) : 30.000
REMARK 200 REJECTION CRITERIA (SIGMA(I)) : 2.000
REMARK 200
REMARK 200 OVERALL.
REMARK 200 COMPLETENESS FOR RANGE (%) : 99.7
REMARK 200 DATA REDUNDANCY : 4.500
REMARK 200 R MERGE (I) : 0.24000
REMARK 200 R SYM (I) : 0.06000
REMARK 200 FOR THE DATA SET : 8.0000
REMARK 200
REMARK 200 IN THE HIGHEST RESOLUTION SHELL.
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE HIGH (A) : 1.70
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE LOW (A) : NULL
REMARK 200 COMPLETENESS FOR SHELL (%) : 97.5
REMARK 200 DATA REDUNDANCY IN SHELL : 4.50
REMARK 200 R MERGE FOR SHELL (I) : 0.06000
REMARK 200 R SYM FOR SHELL (I) : 0.24000
REMARK 200 FOR SHELL : 7.900
REMARK 200
REMARK 200 DIFFRACTION PROTOCOL: MAD
REMARK 200 METHOD USED TO DETERMINE THE STRUCTURE: MAD
REMARK 200 SOFTWARE USED: AMORE
REMARK 200 STARTING MODEL: NULL
REMARK 200
REMARK 200 REMARK: NULL
REMARK 280
REMARK 280 CRYSTAL
REMARK 280 SOLVENT CONTENT, VS (%): 46.26
REMARK 280 MATTHEWS COEFFICIENT, VM (ANGSTROMS**3/DA): 2.29
REMARK 280
REMARK 280 CRYSTALLIZATION CONDITIONS: PH 8.0, VAPOR DIFFUSION, SITTING
REMARK 280 DROP, TEMPERATURE 298K
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY
REMARK 290 SYMMETRY OPERATORS FOR SPACE GROUP: P 21 21 21
REMARK 290
REMARK 290 SYMOP SYMMETRY
REMARK 290 NNNMMM OPERATOR
REMARK 290 1555 X,Y,Z
REMARK 290 2555 -X+1/2,-Y,Z+1/2
REMARK 290 3555 -X,Y+1/2,-Z+1/2
REMARK 290 4555 X+1/2,-Y+1/2,-Z
REMARK 290
REMARK 290 WHERE NNN -> OPERATOR NUMBER
REMARK 290 MMM -> TRANSLATION VECTOR
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY TRANSFORMATIONS
REMARK 290 THE FOLLOWING TRANSFORMATIONS OPERATE ON THE ATOM/HETATM
REMARK 290 RECORDS IN THIS ENTRY TO PRODUCE CRYSTALLOGRAPHICALLY
REMARK 290 RELATED MOLECULES.
REMARK 290 SMTRY1 1 1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 1 0.000000 1.000000 0.000000 0.00000
REMARK 290 SMTRY3 1 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 2 -1.000000 0.000000 0.000000 24.97100
REMARK 290 SMTRY2 2 0.000000 -1.000000 0.000000 0.00000
REMARK 290 SMTRY3 2 0.000000 0.000000 1.000000 41.06000
REMARK 290 SMTRY1 3 -1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 3 0.000000 1.000000 0.000000 25.84950
REMARK 290 SMTRY3 3 0.000000 0.000000 -1.000000 41.06000
REMARK 290 SMTRY1 4 1.000000 0.000000 0.000000 24.97100
REMARK 290 SMTRY2 4 0.000000 -1.000000 0.000000 25.84950
REMARK 290 SMTRY3 4 0.000000 0.000000 -1.000000 0.00000
REMARK 290
REMARK 290 REMARK: NULL
REMARK 300
REMARK 300 BIOMOLECULE: 1
REMARK 300 SEE REMARK 350 FOR THE AUTHOR PROVIDED AND/OR PROGRAM
REMARK 300 GENERATED ASSEMBLY INFORMATION FOR THE STRUCTURE IN
REMARK 300 THIS ENTRY. THE REMARK MAY ALSO PROVIDE INFORMATION ON
REMARK 300 BURIED SURFACE AREA.
REMARK 350
REMARK 350 COORDINATES FOR A COMPLETE MULTIMER REPRESENTING THE KNOWN
REMARK 350 BIOLOGICALLY SIGNIFICANT OLIGOMERIZATION STATE OF THE
REMARK 350 MOLECULE CAN BE GENERATED BY APPLYING BIOMT TRANSFORMATIONS
REMARK 350 GIVEN BELOW. BOTH NON-CRYSTALLOGRAPHIC AND
REMARK 350 CRYSTALLOGRAPHIC OPERATIONS ARE GIVEN.
REMARK 350
REMARK 350 BIOMOLECULE: 1
REMARK 350 AUTHOR DETERMINED BIOLOGICAL UNIT: DIMERIC
REMARK 350 APPLY THE FOLLOWING TO CHAINS: A, B
REMARK 350 BIOMT1 1 1.000000 0.000000 0.000000 0.00000
REMARK 350 BIOMT2 1 0.000000 1.000000 0.000000 0.00000
REMARK 350 BIOMT3 1 0.000000 0.000000 1.000000 0.00000
REMARK 465
REMARK 465 MISSING RESIDUES
REMARK 465 THE FOLLOWING RESIDUES WERE NOT LOCATED IN THE
REMARK 465 EXPERIMENT. (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN
REMARK 465 IDENTIFIER; SSSEQ=SEQUENCE NUMBER; I=INSERTION CODE.)
REMARK 465
REMARK 465 M RES C SSSEQI
REMARK 465 LEU A 94
REMARK 465 GLY A 95
REMARK 465 ALA A 96
REMARK 465 PRO A 97
REMARK 465 GLN A 98
REMARK 465 VAL A 99
REMARK 465 MET A 100
REMARK 465 PRO A 101
REMARK 465 LEU B 94
REMARK 465 GLY B 95
REMARK 465 ALA B 96
REMARK 465 PRO B 97
REMARK 465 GLN B 98
REMARK 465 VAL B 99
REMARK 465 MET B 100
REMARK 465 PRO B 101
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: CLOSE CONTACTS IN SAME ASYMMETRIC UNIT
REMARK 500
REMARK 500 THE FOLLOWING ATOMS ARE IN CLOSE CONTACT.
REMARK 500
REMARK 500 ATM1 RES C SSEQI ATM2 RES C SSEQI DISTANCE
REMARK 500 O HOH A 127 O HOH A 149 2.05
REMARK 500
REMARK 500 REMARK: NULL
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: TORSION ANGLES
REMARK 500
REMARK 500 TORSION ANGLES OUTSIDE THE EXPECTED RAMACHANDRAN REGIONS:
REMARK 500 (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN IDENTIFIER;
REMARK 500 SSEQ=SEQUENCE NUMBER; I=INSERTION CODE).
REMARK 500
REMARK 500 STANDARD TABLE:
REMARK 500 FORMAT:(10X,I3,1X,A3,1X,A1,I4,A1,4X,F7.2,3X,F7.2)
REMARK 500
REMARK 500 EXPECTED VALUES: GJ KLEYWEGT AND TA JONES (1996). PHI/PSI-
REMARK 500 CHOLOGY: RAMACHANDRAN REVISITED. STRUCTURE 4, 1395 - 1400
REMARK 500
REMARK 500 M RES CSSEQI PSI PHI
REMARK 500 ASN A 64 -175.84 -178.56
REMARK 500 HIS A 71 -156.72 -164.33
REMARK 500 LEU A 72 -70.52 -135.73
REMARK 500 ALA A 74 -75.47 -29.45
REMARK 500 SER A 75 -5.54 -145.62
REMARK 500 GLN A 76 -178.36 65.32
REMARK 500 GLU A 77 115.33 61.52
REMARK 500 MET A 92 -36.89 93.21
REMARK 500 LEU B 25 37.31 -77.89
REMARK 500 GLN B 28 37.09 32.85
REMARK 500 ARG B 30 132.20 -36.84
REMARK 500 ASN B 64 -172.78 -175.93
REMARK 500 GLN B 76 67.64 34.46
REMARK 500 PRO B 91 -156.99 -48.61
REMARK 500 MET B 92 -37.52 -160.44
REMARK 500
REMARK 500 REMARK: NULL
REMARK 525
REMARK 525 SOLVENT
REMARK 525
REMARK 525 THE SOLVENT MOLECULES HAVE CHAIN IDENTIFIERS THAT
REMARK 525 INDICATE THE POLYMER CHAIN WITH WHICH THEY ARE MOST
REMARK 525 CLOSELY ASSOCIATED. THE REMARK LISTS ALL THE SOLVENT
REMARK 525 MOLECULES WHICH ARE MORE THAN 5A AWAY FROM THE
REMARK 525 NEAREST POLYMER CHAIN (M = MODEL NUMBER;
REMARK 525 RES=RESIDUE NAME; C=CHAIN IDENTIFIER; SSEQ=SEQUENCE
REMARK 525 NUMBER; I=INSERTION CODE):
REMARK 525
REMARK 525 M RES CSSEQI
REMARK 525 HOH B 115 DISTANCE = 6.82 ANGSTROMS
REMARK 525 HOH A 116 DISTANCE = 6.52 ANGSTROMS
REMARK 525 HOH B 119 DISTANCE = 5.12 ANGSTROMS
REMARK 525 HOH B 121 DISTANCE = 5.21 ANGSTROMS
REMARK 525 HOH B 123 DISTANCE = 5.18 ANGSTROMS
REMARK 525 HOH A 124 DISTANCE = 6.99 ANGSTROMS
REMARK 525 HOH B 124 DISTANCE = 5.13 ANGSTROMS
REMARK 525 HOH B 134 DISTANCE = 7.25 ANGSTROMS
REMARK 525 HOH B 140 DISTANCE = 5.54 ANGSTROMS
REMARK 525 HOH B 141 DISTANCE = 5.94 ANGSTROMS
REMARK 525 HOH B 142 DISTANCE = 6.60 ANGSTROMS
REMARK 525 HOH B 143 DISTANCE = 7.39 ANGSTROMS
REMARK 525 HOH A 145 DISTANCE = 9.25 ANGSTROMS
REMARK 525 HOH A 150 DISTANCE = 6.01 ANGSTROMS
REMARK 525 HOH B 152 DISTANCE = 5.46 ANGSTROMS
REMARK 525 HOH B 153 DISTANCE = 9.74 ANGSTROMS
REMARK 525 HOH B 154 DISTANCE = 9.32 ANGSTROMS
REMARK 525 HOH B 155 DISTANCE = 5.41 ANGSTROMS
REMARK 525 HOH B 163 DISTANCE = 5.16 ANGSTROMS
DBREF 2E12 A 1 101 UNP Q8P4R5 Q8P4R5_XANCP 1 101
DBREF 2E12 B 1 101 UNP Q8P4R5 Q8P4R5_XANCP 1 101
SEQRES 1 A 101 MET PRO LYS TYR ALA PRO HIS VAL TYR THR GLU GLN ALA
SEQRES 2 A 101 GLN ILE ALA THR LEU GLU HIS TRP VAL LYS LEU LEU ASP
SEQRES 3 A 101 GLY GLN GLU ARG VAL ARG ILE GLU LEU ASP ASP GLY SER
SEQRES 4 A 101 MET ILE ALA GLY THR VAL ALA VAL ARG PRO THR ILE GLN
SEQRES 5 A 101 THR TYR ARG ASP GLU GLN GLU ARG GLU GLY SER ASN GLY
SEQRES 6 A 101 GLN LEU ARG ILE ASP HIS LEU ASP ALA SER GLN GLU PRO
SEQRES 7 A 101 GLN TRP ILE TRP MET ASP ARG ILE VAL ALA VAL HIS PRO
SEQRES 8 A 101 MET PRO LEU GLY ALA PRO GLN VAL MET PRO
SEQRES 1 B 101 MET PRO LYS TYR ALA PRO HIS VAL TYR THR GLU GLN ALA
SEQRES 2 B 101 GLN ILE ALA THR LEU GLU HIS TRP VAL LYS LEU LEU ASP
SEQRES 3 B 101 GLY GLN GLU ARG VAL ARG ILE GLU LEU ASP ASP GLY SER
SEQRES 4 B 101 MET ILE ALA GLY THR VAL ALA VAL ARG PRO THR ILE GLN
SEQRES 5 B 101 THR TYR ARG ASP GLU GLN GLU ARG GLU GLY SER ASN GLY
SEQRES 6 B 101 GLN LEU ARG ILE ASP HIS LEU ASP ALA SER GLN GLU PRO
SEQRES 7 B 101 GLN TRP ILE TRP MET ASP ARG ILE VAL ALA VAL HIS PRO
SEQRES 8 B 101 MET PRO LEU GLY ALA PRO GLN VAL MET PRO
FORMUL 3 HOH *122(H2 O)
HELIX 1 1 GLU A 11 LEU A 24 1 14
HELIX 2 2 GLU B 11 LEU B 25 1 15
SHEET 1 A 3 ILE A 51 ARG A 55 0
SHEET 2 A 3 GLU A 61 ASP A 70 -1 O ASN A 64 N GLN A 52
SHEET 3 A 3 GLN A 79 TRP A 82 -1 O ILE A 81 N LEU A 67
SHEET 1 B 5 ILE A 51 ARG A 55 0
SHEET 2 B 5 GLU A 61 ASP A 70 -1 O ASN A 64 N GLN A 52
SHEET 3 B 5 MET A 40 VAL A 45 -1 N THR A 44 O ASP A 70
SHEET 4 B 5 ARG A 30 LEU A 35 -1 N ILE A 33 O ILE A 41
SHEET 5 B 5 ILE A 86 PRO A 91 -1 O VAL A 87 N GLU A 34
SHEET 1 C 5 PRO B 78 TRP B 82 0
SHEET 2 C 5 GLN B 66 ASP B 70 -1 N ILE B 69 O GLN B 79
SHEET 3 C 5 MET B 40 VAL B 47 -1 N ALA B 46 O ARG B 68
SHEET 4 C 5 VAL B 31 LEU B 35 -1 N ILE B 33 O ILE B 41
SHEET 5 C 5 ILE B 86 HIS B 90 -1 O VAL B 87 N GLU B 34
SHEET 1 D 2 GLN B 52 ARG B 55 0
SHEET 2 D 2 GLU B 61 ASN B 64 -1 O ASN B 64 N GLN B 52
CRYST1 49.942 51.699 82.120 90.00 90.00 90.00 P 21 21 21 8
ORIGX1 1.000000 0.000000 0.000000 0.00000
ORIGX2 0.000000 1.000000 0.000000 0.00000
ORIGX3 0.000000 0.000000 1.000000 0.00000
SCALE1 0.020023 0.000000 0.000000 0.00000
SCALE2 0.000000 0.019343 0.000000 0.00000
SCALE3 0.000000 0.000000 0.012177 0.00000
ATOM 1 N MET A 1 53.045 42.225 33.724 1.00 2.75 N
ATOM 2 CA MET A 1 53.628 40.900 33.321 1.00 2.75 C
ATOM 3 C MET A 1 52.484 39.953 32.944 1.00 2.75 C
ATOM 4 O MET A 1 51.460 39.918 33.620 1.00 2.75 O
ATOM 5 CB MET A 1 54.438 40.316 34.481 1.00 2.75 C
ATOM 6 CG MET A 1 55.168 39.017 34.162 1.00 2.75 C
ATOM 7 SD MET A 1 56.025 38.339 35.612 1.00 2.75 S
ATOM 8 CE MET A 1 57.693 38.808 35.263 1.00 2.75 C
ATOM 9 N PRO A 2 52.639 39.190 31.852 1.00 6.58 N
ATOM 10 CA PRO A 2 51.588 38.262 31.417 1.00 6.58 C
ATOM 11 C PRO A 2 51.672 36.859 32.016 1.00 6.58 C
ATOM 12 O PRO A 2 52.754 36.306 32.174 1.00 6.58 O
ATOM 13 CB PRO A 2 51.762 38.212 29.890 1.00 6.58 C
ATOM 14 CG PRO A 2 52.746 39.341 29.567 1.00 17.56 C
ATOM 15 CD PRO A 2 53.627 39.381 30.780 1.00 28.54 C
ATOM 16 N LYS A 3 50.524 36.287 32.352 1.00 6.58 N
ATOM 17 CA LYS A 3 50.484 34.928 32.870 1.00 6.58 C
ATOM 18 C LYS A 3 50.086 34.114 31.642 1.00 6.58 C
ATOM 19 O LYS A 3 49.199 34.526 30.894 1.00 6.58 O
ATOM 20 CB LYS A 3 49.430 34.799 33.972 1.00 6.58 C
ATOM 21 CG LYS A 3 49.622 35.779 35.119 1.00 17.56 C
ATOM 22 CD LYS A 3 48.606 35.530 36.216 1.00 28.54 C
ATOM 23 CE LYS A 3 48.810 36.475 37.389 1.00 39.52 C
ATOM 24 NZ LYS A 3 47.845 36.196 38.491 1.00 50.50 N
ATOM 25 N TYR A 4 50.760 32.992 31.414 1.00 2.75 N
ATOM 26 CA TYR A 4 50.475 32.153 30.246 1.00 2.75 C
ATOM 27 C TYR A 4 49.716 30.873 30.590 1.00 2.75 C
ATOM 28 O TYR A 4 49.948 30.254 31.629 1.00 6.58 O
ATOM 29 CB TYR A 4 51.779 31.798 29.515 1.00 2.75 C
ATOM 30 CG TYR A 4 52.453 32.994 28.860 1.00 2.75 C
ATOM 31 CD1 TYR A 4 53.107 33.965 29.627 1.00 2.75 C
ATOM 32 CD2 TYR A 4 52.382 33.190 27.474 1.00 2.75 C
ATOM 33 CE1 TYR A 4 53.664 35.112 29.028 1.00 2.75 C
ATOM 34 CE2 TYR A 4 52.943 34.330 26.868 1.00 2.75 C
ATOM 35 CZ TYR A 4 53.576 35.287 27.649 1.00 2.75 C
ATOM 36 OH TYR A 4 54.090 36.431 27.057 1.00 2.75 O
ATOM 37 N ALA A 5 48.784 30.502 29.719 1.00 6.58 N
ATOM 38 CA ALA A 5 47.984 29.298 29.911 1.00 6.58 C
ATOM 39 C ALA A 5 48.010 28.497 28.621 1.00 6.58 C
ATOM 40 O ALA A 5 48.174 29.058 27.541 1.00 6.58 O
ATOM 41 CB ALA A 5 46.540 29.667 30.281 1.00 6.58 C
ATOM 42 N PRO A 6 47.873 27.171 28.723 1.00 2.75 N
ATOM 43 CA PRO A 6 47.873 26.279 27.562 1.00 2.75 C
ATOM 44 C PRO A 6 46.806 26.625 26.505 1.00 2.75 C
ATOM 45 O PRO A 6 47.047 26.448 25.314 1.00 6.58 O
ATOM 46 CB PRO A 6 47.682 24.887 28.186 1.00 2.75 C
ATOM 47 CG PRO A 6 47.204 25.169 29.610 1.00 2.75 C
ATOM 48 CD PRO A 6 47.957 26.398 29.972 1.00 2.75 C
ATOM 49 N HIS A 7 45.641 27.109 26.944 1.00 6.58 N
ATOM 50 CA HIS A 7 44.553 27.501 26.031 1.00 6.58 C
ATOM 51 C HIS A 7 43.788 28.682 26.635 1.00 6.58 C
ATOM 52 O HIS A 7 43.749 28.823 27.855 1.00 6.58 O
ATOM 53 CB HIS A 7 43.549 26.351 25.817 1.00 6.58 C
ATOM 54 CG HIS A 7 44.171 25.053 25.402 1.00 17.56 C
ATOM 55 ND1 HIS A 7 44.791 24.206 26.296 1.00 28.54 N
ATOM 56 CD2 HIS A 7 44.249 24.448 24.193 1.00 28.54 C
ATOM 57 CE1 HIS A 7 45.222 23.133 25.656 1.00 39.52 C
ATOM 58 NE2 HIS A 7 44.906 23.256 24.380 1.00 39.52 N
ATOM 59 N VAL A 8 43.190 29.529 25.791 1.00 6.58 N
ATOM 60 CA VAL A 8 42.399 30.686 26.264 1.00 6.58 C
ATOM 61 C VAL A 8 41.139 30.865 25.388 1.00 6.58 C
ATOM 62 O VAL A 8 41.162 30.538 24.202 1.00 6.58 O
ATOM 63 CB VAL A 8 43.231 32.013 26.272 1.00 6.58 C
ATOM 64 CG1 VAL A 8 44.314 31.951 27.342 1.00 17.56 C
ATOM 65 CG2 VAL A 8 43.857 32.253 24.902 1.00 17.56 C
ATOM 66 N TYR A 9 40.064 31.405 25.968 1.00 6.58 N
ATOM 67 CA TYR A 9 38.773 31.561 25.260 1.00 6.58 C
ATOM 68 C TYR A 9 38.145 32.966 25.195 1.00 6.58 C
ATOM 69 O TYR A 9 38.157 33.712 26.171 1.00 6.58 O
ATOM 70 CB TYR A 9 37.755 30.602 25.888 1.00 6.58 C
ATOM 71 CG TYR A 9 38.240 29.170 25.920 1.00 17.56 C
ATOM 72 CD1 TYR A 9 38.045 28.322 24.828 1.00 28.54 C
ATOM 73 CD2 TYR A 9 38.961 28.686 27.010 1.00 28.54 C
ATOM 74 CE1 TYR A 9 38.559 27.031 24.819 1.00 39.52 C
ATOM 75 CE2 TYR A 9 39.481 27.400 27.009 1.00 39.52 C
ATOM 76 CZ TYR A 9 39.277 26.577 25.911 1.00 50.50 C
ATOM 77 OH TYR A 9 39.797 25.302 25.901 1.00 61.48 O
ATOM 78 N THR A 10 37.555 33.294 24.047 1.00 6.58 N
ATOM 79 CA THR A 10 36.938 34.606 23.834 1.00 6.58 C
ATOM 80 C THR A 10 35.470 34.561 23.400 1.00 6.58 C
ATOM 81 O THR A 10 34.818 35.600 23.302 1.00 6.58 O
ATOM 82 CB THR A 10 37.710 35.414 22.763 1.00 6.58 C
ATOM 83 OG1 THR A 10 37.602 34.759 21.494 1.00 17.56 O
ATOM 84 CG2 THR A 10 39.181 35.523 23.135 1.00 17.56 C
ATOM 85 N GLU A 11 34.952 33.368 23.138 1.00 6.58 N
ATOM 86 CA GLU A 11 33.562 33.228 22.698 1.00 6.58 C
ATOM 87 C GLU A 11 32.609 33.191 23.900 1.00 6.58 C
ATOM 88 O GLU A 11 32.825 32.439 24.851 1.00 6.58 O
ATOM 89 CB GLU A 11 33.409 31.955 21.860 1.00 6.58 C
ATOM 90 CG GLU A 11 32.145 31.906 21.007 1.00 17.56 C
ATOM 91 CD GLU A 11 32.180 32.899 19.855 1.00 28.54 C
ATOM 92 OE1 GLU A 11 33.222 32.977 19.167 1.00 39.52 O
ATOM 93 OE2 GLU A 11 31.163 33.590 19.630 1.00 39.52 O
ATOM 94 N GLN A 12 31.555 34.004 23.844 1.00 6.58 N
ATOM 95 CA GLN A 12 30.586 34.098 24.931 1.00 6.58 C
ATOM 96 C GLN A 12 29.975 32.785 25.415 1.00 6.58 C
ATOM 97 O GLN A 12 29.537 32.694 26.564 1.00 6.58 O
ATOM 98 CB GLN A 12 29.479 35.093 24.565 1.00 6.58 C
ATOM 99 CG GLN A 12 30.005 36.518 24.420 1.00 17.56 C
ATOM 100 CD GLN A 12 30.952 36.896 25.552 1.00 28.54 C
ATOM 101 OE1 GLN A 12 30.536 37.055 26.703 1.00 39.52 O
ATOM 102 NE2 GLN A 12 32.236 37.027 25.228 1.00 39.52 N
ATOM 103 N ALA A 13 29.952 31.768 24.558 1.00 6.58 N
ATOM 104 CA ALA A 13 29.405 30.476 24.948 1.00 6.58 C
ATOM 105 C ALA A 13 30.357 29.750 25.894 1.00 6.58 C
ATOM 106 O ALA A 13 29.918 29.074 26.823 1.00 6.58 O
ATOM 107 CB ALA A 13 29.142 29.620 23.723 1.00 6.58 C
ATOM 108 N GLN A 14 31.660 29.883 25.645 1.00 6.58 N
ATOM 109 CA GLN A 14 32.674 29.247 26.475 1.00 6.58 C
ATOM 110 C GLN A 14 32.864 30.020 27.770 1.00 6.58 C
ATOM 111 O GLN A 14 33.198 29.439 28.797 1.00 6.58 O
ATOM 112 CB GLN A 14 34.019 29.149 25.739 1.00 6.58 C
ATOM 113 CG GLN A 14 34.141 28.000 24.748 1.00 17.56 C
ATOM 114 CD GLN A 14 33.025 27.982 23.720 1.00 28.54 C
ATOM 115 OE1 GLN A 14 31.896 27.591 24.019 1.00 39.52 O
ATOM 116 NE2 GLN A 14 33.335 28.413 22.501 1.00 39.52 N
ATOM 117 N ILE A 15 32.663 31.332 27.720 1.00 6.58 N
ATOM 118 CA ILE A 15 32.798 32.133 28.920 1.00 6.58 C
ATOM 119 C ILE A 15 31.600 31.819 29.811 1.00 6.58 C
ATOM 120 O ILE A 15 31.727 31.754 31.044 1.00 6.58 O
ATOM 121 CB ILE A 15 32.826 33.635 28.602 1.00 6.58 C
ATOM 122 CG1 ILE A 15 34.036 33.962 27.724 1.00 17.56 C
ATOM 123 CG2 ILE A 15 32.934 34.427 29.889 1.00 17.56 C
ATOM 124 CD1 ILE A 15 34.139 35.417 27.365 1.00 28.54 C
ATOM 125 N ALA A 16 30.436 31.616 29.191 1.00 6.58 N
ATOM 126 CA ALA A 16 29.221 31.282 29.941 1.00 6.58 C
ATOM 127 C ALA A 16 29.416 29.948 30.664 1.00 6.58 C
ATOM 128 O ALA A 16 29.005 29.787 31.814 1.00 6.58 O
ATOM 129 CB ALA A 16 28.018 31.198 28.997 1.00 6.58 C
ATOM 130 N THR A 17 30.047 28.996 29.984 1.00 6.58 N
ATOM 131 CA THR A 17 30.317 27.690 30.573 1.00 6.58 C
ATOM 132 C THR A 17 31.305 27.861 31.732 1.00 6.58 C
ATOM 133 O THR A 17 31.047 27.402 32.844 1.00 6.58 O
ATOM 134 CB THR A 17 30.914 26.708 29.530 1.00 6.58 C
ATOM 135 OG1 THR A 17 32.126 27.249 28.999 1.00 17.56 O
ATOM 136 CG2 THR A 17 29.944 26.499 28.383 1.00 17.56 C
ATOM 137 N LEU A 18 32.419 28.544 31.472 1.00 6.58 N
ATOM 138 CA LEU A 18 33.430 28.774 32.498 1.00 6.58 C
ATOM 139 C LEU A 18 32.868 29.412 33.765 1.00 6.58 C
ATOM 140 O LEU A 18 33.285 29.069 34.872 1.00 6.58 O
ATOM 141 CB LEU A 18 34.560 29.652 31.942 1.00 6.58 C
ATOM 142 CG LEU A 18 35.487 29.006 30.907 1.00 17.56 C
ATOM 143 CD1 LEU A 18 36.392 30.058 30.282 1.00 28.54 C
ATOM 144 CD2 LEU A 18 36.317 27.922 31.580 1.00 28.54 C
ATOM 145 N GLU A 19 31.922 30.335 33.608 1.00 6.58 N
ATOM 146 CA GLU A 19 31.335 31.017 34.760 1.00 6.58 C
ATOM 147 C GLU A 19 30.371 30.150 35.560 1.00 6.58 C
ATOM 148 O GLU A 19 30.310 30.256 36.785 1.00 6.58 O
ATOM 149 CB GLU A 19 30.644 32.316 34.308 1.00 6.58 C
ATOM 150 CG GLU A 19 31.636 33.396 33.881 1.00 17.56 C
ATOM 151 CD GLU A 19 30.969 34.633 33.303 1.00 28.54 C
ATOM 152 OE1 GLU A 19 30.217 34.502 32.315 1.00 39.52 O
ATOM 153 OE2 GLU A 19 31.206 35.741 33.830 1.00 39.52 O
ATOM 154 N HIS A 20 29.621 29.289 34.874 1.00 6.58 N
ATOM 155 CA HIS A 20 28.678 28.406 35.560 1.00 6.58 C
ATOM 156 C HIS A 20 29.426 27.414 36.463 1.00 6.58 C
ATOM 157 O HIS A 20 28.944 27.068 37.531 1.00 6.58 O
ATOM 158 CB HIS A 20 27.823 27.637 34.545 1.00 6.58 C
ATOM 159 CG HIS A 20 26.814 26.725 35.171 1.00 17.56 C
ATOM 160 ND1 HIS A 20 25.792 27.184 35.973 1.00 28.54 N
ATOM 161 CD2 HIS A 20 26.676 25.379 35.118 1.00 28.54 C
ATOM 162 CE1 HIS A 20 25.068 26.159 36.390 1.00 39.52 C
ATOM 163 NE2 HIS A 20 25.584 25.053 35.885 1.00 39.52 N
ATOM 164 N TRP A 21 30.608 26.975 36.028 1.00 6.58 N
ATOM 165 CA TRP A 21 31.416 26.027 36.799 1.00 6.58 C
ATOM 166 C TRP A 21 31.830 26.606 38.143 1.00 6.58 C
ATOM 167 O TRP A 21 31.872 25.895 39.150 1.00 6.58 O
ATOM 168 CB TRP A 21 32.679 25.629 36.021 1.00 6.58 C
ATOM 169 CG TRP A 21 32.440 24.737 34.824 1.00 17.56 C
ATOM 170 CD1 TRP A 21 33.259 24.592 33.740 1.00 28.54 C
ATOM 171 CD2 TRP A 21 31.327 23.857 34.604 1.00 28.54 C
ATOM 172 NE1 TRP A 21 32.728 23.683 32.861 1.00 39.52 N
ATOM 173 CE2 TRP A 21 31.543 23.215 33.365 1.00 39.52 C
ATOM 174 CE3 TRP A 21 30.169 23.549 35.333 1.00 39.52 C
ATOM 175 CZ2 TRP A 21 30.644 22.283 32.837 1.00 50.50 C
ATOM 176 CZ3 TRP A 21 29.275 22.623 34.807 1.00 50.50 C
ATOM 177 CH2 TRP A 21 29.520 22.001 33.570 1.00 61.48 C
ATOM 178 N VAL A 22 32.156 27.895 38.154 1.00 6.58 N
ATOM 179 CA VAL A 22 32.554 28.557 39.391 1.00 6.58 C
ATOM 180 C VAL A 22 31.392 28.493 40.386 1.00 6.58 C
ATOM 181 O VAL A 22 31.580 28.181 41.551 1.00 6.58 O
ATOM 182 CB VAL A 22 32.951 30.034 39.125 1.00 6.58 C
ATOM 183 CG1 VAL A 22 33.343 30.730 40.426 1.00 17.56 C
ATOM 184 CG2 VAL A 22 34.112 30.078 38.131 1.00 17.56 C
ATOM 185 N LYS A 23 30.191 28.776 39.893 1.00 6.58 N
ATOM 186 CA LYS A 23 28.977 28.742 40.699 1.00 6.58 C
ATOM 187 C LYS A 23 28.775 27.375 41.351 1.00 6.58 C
ATOM 188 O LYS A 23 28.181 27.267 42.423 1.00 6.58 O
ATOM 189 CB LYS A 23 27.764 29.067 39.819 1.00 6.58 C
ATOM 190 CG LYS A 23 27.639 30.528 39.416 1.00 17.56 C
ATOM 191 CD LYS A 23 27.106 31.370 40.562 1.00 28.54 C
ATOM 192 CE LYS A 23 25.840 30.742 41.131 1.00 39.52 C
ATOM 193 NZ LYS A 23 24.916 30.311 40.043 1.00 50.50 N
ATOM 194 N LEU A 24 29.264 26.331 40.692 1.00 6.58 N
ATOM 195 CA LEU A 24 29.131 24.979 41.207 1.00 6.58 C
ATOM 196 C LEU A 24 30.387 24.503 41.944 1.00 6.58 C
ATOM 197 O LEU A 24 30.421 23.392 42.461 1.00 6.58 O
ATOM 198 CB LEU A 24 28.810 24.023 40.061 1.00 6.58 C
ATOM 199 CG LEU A 24 27.567 24.381 39.240 1.00 17.56 C
ATOM 200 CD1 LEU A 24 27.409 23.373 38.107 1.00 28.54 C
ATOM 201 CD2 LEU A 24 26.331 24.393 40.128 1.00 28.54 C
ATOM 202 N LEU A 25 31.416 25.341 41.995 1.00 6.58 N
ATOM 203 CA LEU A 25 32.658 24.969 42.669 1.00 6.58 C
ATOM 204 C LEU A 25 33.010 25.943 43.784 1.00 6.58 C
ATOM 205 O LEU A 25 34.124 26.475 43.828 1.00 6.58 O
ATOM 206 CB LEU A 25 33.818 24.922 41.665 1.00 6.58 C
ATOM 207 CG LEU A 25 33.829 23.785 40.641 1.00 17.56 C
ATOM 208 CD1 LEU A 25 34.858 24.061 39.555 1.00 28.54 C
ATOM 209 CD2 LEU A 25 34.134 22.478 41.348 1.00 28.54 C
ATOM 210 N ASP A 26 32.069 26.175 44.690 1.00 2.75 N
ATOM 211 CA ASP A 26 32.325 27.100 45.777 1.00 2.75 C
ATOM 212 C ASP A 26 33.445 26.600 46.704 1.00 2.75 C
ATOM 213 O ASP A 26 33.659 25.394 46.864 1.00 2.75 O
ATOM 214 CB ASP A 26 31.043 27.349 46.577 1.00 2.75 C
ATOM 215 CG ASP A 26 31.174 28.526 47.521 1.00 2.75 C
ATOM 216 OD1 ASP A 26 30.323 28.657 48.431 1.00 2.75 O
ATOM 217 OD2 ASP A 26 32.126 29.333 47.354 1.00 2.75 O
ATOM 218 N GLY A 27 34.162 27.543 47.309 1.00 2.75 N
ATOM 219 CA GLY A 27 35.245 27.182 48.207 1.00 2.75 C
ATOM 220 C GLY A 27 34.850 26.148 49.249 1.00 2.75 C
ATOM 221 O GLY A 27 33.798 26.272 49.896 1.00 2.75 O
ATOM 222 N GLN A 28 35.691 25.116 49.379 1.00 2.75 N
ATOM 223 CA GLN A 28 35.525 24.020 50.344 1.00 2.75 C
ATOM 224 C GLN A 28 34.394 23.025 50.087 1.00 2.75 C
ATOM 225 O GLN A 28 34.154 22.150 50.911 1.00 2.75 O
ATOM 226 CB GLN A 28 35.385 24.582 51.773 1.00 2.75 C
ATOM 227 CG GLN A 28 36.645 25.245 52.319 1.00 2.75 C
ATOM 228 CD GLN A 28 37.835 24.295 52.390 1.00 2.75 C
ATOM 229 OE1 GLN A 28 37.859 23.373 53.197 1.00 2.75 O
ATOM 230 NE2 GLN A 28 38.827 24.521 51.539 1.00 2.75 N
ATOM 231 N GLU A 29 33.703 23.141 48.953 1.00 2.75 N
ATOM 232 CA GLU A 29 32.606 22.224 48.651 1.00 2.75 C
ATOM 233 C GLU A 29 33.156 20.908 48.112 1.00 2.75 C
ATOM 234 O GLU A 29 34.122 20.893 47.346 1.00 2.75 O
ATOM 235 CB GLU A 29 31.663 22.859 47.622 1.00 2.75 C
ATOM 236 CG GLU A 29 30.332 22.146 47.421 1.00 2.75 C
ATOM 237 CD GLU A 29 29.298 22.461 48.496 1.00 2.75 C
ATOM 238 OE1 GLU A 29 28.934 21.526 49.252 1.00 2.75 O
ATOM 239 OE2 GLU A 29 28.838 23.629 48.589 1.00 2.75 O
ATOM 240 N ARG A 30 32.548 19.804 48.524 1.00 2.75 N
ATOM 241 CA ARG A 30 32.983 18.485 48.070 1.00 2.75 C
ATOM 242 C ARG A 30 32.229 18.140 46.798 1.00 2.75 C
ATOM 243 O ARG A 30 30.995 18.173 46.768 1.00 2.75 O
ATOM 244 CB ARG A 30 32.708 17.446 49.148 1.00 2.75 C
ATOM 245 CG ARG A 30 33.678 17.503 50.319 1.00 2.75 C
ATOM 246 CD ARG A 30 33.196 16.634 51.464 1.00 2.75 C
ATOM 247 NE ARG A 30 33.169 15.211 51.129 1.00 2.75 N
ATOM 248 CZ ARG A 30 32.354 14.339 51.707 1.00 2.75 C
ATOM 249 NH1 ARG A 30 31.509 14.756 52.639 1.00 2.75 N
ATOM 250 NH2 ARG A 30 32.382 13.059 51.355 1.00 2.75 N
ATOM 251 N VAL A 31 32.969 17.827 45.740 1.00 6.58 N
ATOM 252 CA VAL A 31 32.339 17.513 44.470 1.00 6.58 C
ATOM 253 C VAL A 31 33.095 16.443 43.700 1.00 6.58 C
ATOM 254 O VAL A 31 34.211 16.063 44.063 1.00 6.58 O
ATOM 255 CB VAL A 31 32.263 18.770 43.580 1.00 6.58 C
ATOM 256 CG1 VAL A 31 31.510 19.879 44.295 1.00 17.56 C
ATOM 257 CG2 VAL A 31 33.669 19.236 43.236 1.00 17.56 C
ATOM 258 N ARG A 32 32.456 15.940 42.654 1.00 6.58 N
ATOM 259 CA ARG A 32 33.070 14.951 41.777 1.00 6.58 C
ATOM 260 C ARG A 32 33.007 15.667 40.441 1.00 6.58 C
ATOM 261 O ARG A 32 31.963 16.217 40.080 1.00 6.58 O
ATOM 262 CB ARG A 32 32.253 13.665 41.725 1.00 6.58 C
ATOM 263 CG ARG A 32 33.072 12.405 41.464 1.00 17.56 C
ATOM 264 CD ARG A 32 32.308 11.169 41.939 1.00 28.54 C
ATOM 265 NE ARG A 32 30.906 11.193 41.524 1.00 39.52 N
ATOM 266 CZ ARG A 32 30.494 11.171 40.259 1.00 50.50 C
ATOM 267 NH1 ARG A 32 31.376 11.121 39.269 1.00 61.48 N
ATOM 268 NH2 ARG A 32 29.199 11.210 39.983 1.00 61.48 N
ATOM 269 N ILE A 33 34.120 15.665 39.719 1.00 6.58 N
ATOM 270 CA ILE A 33 34.210 16.366 38.447 1.00 6.58 C
ATOM 271 C ILE A 33 34.430 15.472 37.237 1.00 6.58 C
ATOM 272 O ILE A 33 35.204 14.525 37.299 1.00 6.58 O
ATOM 273 CB ILE A 33 35.367 17.377 38.506 1.00 6.58 C
ATOM 274 CG1 ILE A 33 35.173 18.297 39.716 1.00 17.56 C
ATOM 275 CG2 ILE A 33 35.443 18.176 37.210 1.00 17.56 C
ATOM 276 CD1 ILE A 33 36.352 19.210 39.990 1.00 28.54 C
ATOM 277 N GLU A 34 33.740 15.785 36.142 1.00 6.58 N
ATOM 278 CA GLU A 34 33.897 15.045 34.893 1.00 6.58 C
ATOM 279 C GLU A 34 34.785 15.897 33.977 1.00 6.58 C
ATOM 280 O GLU A 34 34.471 17.060 33.713 1.00 6.58 O
ATOM 281 CB GLU A 34 32.542 14.794 34.216 1.00 6.58 C
ATOM 282 CG GLU A 34 31.610 13.862 34.986 1.00 17.56 C
ATOM 283 CD GLU A 34 30.434 13.382 34.143 1.00 28.54 C
ATOM 284 OE1 GLU A 34 29.525 12.721 34.694 1.00 39.52 O
ATOM 285 OE2 GLU A 34 30.424 13.662 32.924 1.00 39.52 O
ATOM 286 N LEU A 35 35.885 15.308 33.503 1.00 6.58 N
ATOM 287 CA LEU A 35 36.852 15.980 32.627 1.00 6.58 C
ATOM 288 C LEU A 35 36.719 15.504 31.179 1.00 6.58 C
ATOM 289 O LEU A 35 36.297 14.379 30.938 1.00 6.58 O
ATOM 290 CB LEU A 35 38.273 15.705 33.123 1.00 6.58 C
ATOM 291 CG LEU A 35 38.619 16.198 34.532 1.00 17.56 C
ATOM 292 CD1 LEU A 35 39.872 15.507 35.024 1.00 28.54 C
ATOM 293 CD2 LEU A 35 38.793 17.708 34.522 1.00 28.54 C
ATOM 294 N ASP A 36 37.115 16.349 30.225 1.00 6.58 N
ATOM 295 CA ASP A 36 37.004 16.013 28.797 1.00 6.58 C
ATOM 296 C ASP A 36 37.945 14.938 28.245 1.00 6.58 C
ATOM 297 O ASP A 36 37.946 14.673 27.045 1.00 6.58 O
ATOM 298 CB ASP A 36 37.122 17.287 27.941 1.00 6.58 C
ATOM 299 CG ASP A 36 38.504 17.921 27.999 1.00 17.56 C
ATOM 300 OD1 ASP A 36 39.416 17.334 28.609 1.00 28.54 O
ATOM 301 OD2 ASP A 36 38.678 19.014 27.420 1.00 28.54 O
ATOM 302 N ASP A 37 38.739 14.321 29.118 1.00 6.58 N
ATOM 303 CA ASP A 37 39.658 13.258 28.710 1.00 6.58 C
ATOM 304 C ASP A 37 39.108 11.907 29.186 1.00 6.58 C
ATOM 305 O ASP A 37 39.765 10.868 29.067 1.00 6.58 O
ATOM 306 CB ASP A 37 41.033 13.499 29.321 1.00 6.58 C
ATOM 307 CG ASP A 37 41.061 13.216 30.801 1.00 17.56 C
ATOM 308 OD1 ASP A 37 40.058 13.532 31.477 1.00 28.54 O
ATOM 309 OD2 ASP A 37 42.087 12.688 31.281 1.00 28.54 O
ATOM 310 N GLY A 38 37.892 11.937 29.726 1.00 6.58 N
ATOM 311 CA GLY A 38 37.248 10.734 30.211 1.00 6.58 C
ATOM 312 C GLY A 38 37.481 10.496 31.693 1.00 6.58 C
ATOM 313 O GLY A 38 36.758 9.731 32.334 1.00 6.58 O
ATOM 314 N SER A 39 38.493 11.155 32.243 1.00 6.58 N
ATOM 315 CA SER A 39 38.815 10.988 33.653 1.00 6.58 C
ATOM 316 C SER A 39 37.890 11.800 34.557 1.00 6.58 C
ATOM 317 O SER A 39 37.053 12.585 34.099 1.00 6.58 O
ATOM 318 CB SER A 39 40.277 11.371 33.912 1.00 6.58 C
ATOM 319 OG SER A 39 40.487 12.754 33.679 1.00 17.56 O
ATOM 320 N MET A 40 38.050 11.597 35.856 1.00 6.58 N
ATOM 321 CA MET A 40 37.233 12.285 36.832 1.00 6.58 C
ATOM 322 C MET A 40 37.985 12.348 38.140 1.00 6.58 C
ATOM 323 O MET A 40 38.601 11.372 38.562 1.00 6.58 O
ATOM 324 CB MET A 40 35.899 11.554 37.006 1.00 6.58 C
ATOM 325 CG MET A 40 36.002 10.039 37.107 1.00 17.56 C
ATOM 326 SD MET A 40 36.695 9.434 38.663 1.00 28.54 S
ATOM 327 CE MET A 40 35.193 9.171 39.631 1.00 39.52 C
ATOM 328 N ILE A 41 37.956 13.521 38.760 1.00 6.58 N
ATOM 329 CA ILE A 41 38.626 13.734 40.035 1.00 6.58 C
ATOM 330 C ILE A 41 37.588 14.131 41.067 1.00 6.58 C
ATOM 331 O ILE A 41 36.634 14.841 40.760 1.00 6.58 O
ATOM 332 CB ILE A 41 39.698 14.847 39.930 1.00 6.58 C
ATOM 333 CG1 ILE A 41 40.390 15.028 41.284 1.00 17.56 C
ATOM 334 CG2 ILE A 41 39.053 16.159 39.486 1.00 17.56 C
ATOM 335 CD1 ILE A 41 41.615 15.922 41.246 1.00 28.54 C
ATOM 336 N ALA A 42 37.766 13.660 42.291 1.00 6.58 N
ATOM 337 CA ALA A 42 36.836 13.978 43.360 1.00 6.58 C
ATOM 338 C ALA A 42 37.634 14.504 44.534 1.00 6.58 C
ATOM 339 O ALA A 42 38.774 14.097 44.742 1.00 6.58 O
ATOM 340 CB ALA A 42 36.071 12.749 43.766 1.00 6.58 C
ATOM 341 N GLY A 43 37.037 15.419 45.287 1.00 6.58 N
ATOM 342 CA GLY A 43 37.728 15.971 46.428 1.00 6.58 C
ATOM 343 C GLY A 43 37.130 17.262 46.912 1.00 6.58 C
ATOM 344 O GLY A 43 35.950 17.552 46.662 1.00 6.58 O
ATOM 345 N THR A 44 37.944 18.050 47.604 1.00 2.75 N
ATOM 346 CA THR A 44 37.469 19.325 48.114 1.00 2.75 C
ATOM 347 C THR A 44 38.065 20.509 47.359 1.00 2.75 C
ATOM 348 O THR A 44 39.271 20.567 47.114 1.00 2.75 O
ATOM 349 CB THR A 44 37.797 19.483 49.615 1.00 2.75 C
ATOM 350 OG1 THR A 44 37.466 18.279 50.314 1.00 2.75 O
ATOM 351 CG2 THR A 44 36.975 20.619 50.213 1.00 2.75 C
ATOM 352 N VAL A 45 37.196 21.436 46.968 1.00 2.75 N
ATOM 353 CA VAL A 45 37.608 22.664 46.288 1.00 2.75 C
ATOM 354 C VAL A 45 38.435 23.444 47.314 1.00 2.75 C
ATOM 355 O VAL A 45 37.888 23.937 48.291 1.00 2.75 O
ATOM 356 CB VAL A 45 36.388 23.534 45.910 1.00 2.75 C
ATOM 357 CG1 VAL A 45 36.858 24.819 45.199 1.00 2.75 C
ATOM 358 CG2 VAL A 45 35.433 22.744 45.015 1.00 2.75 C
ATOM 359 N ALA A 46 39.743 23.561 47.088 1.00 2.75 N
ATOM 360 CA ALA A 46 40.609 24.277 48.028 1.00 2.75 C
ATOM 361 C ALA A 46 40.193 25.733 48.224 1.00 2.75 C
ATOM 362 O ALA A 46 40.119 26.219 49.343 1.00 2.75 O
ATOM 363 CB ALA A 46 42.066 24.210 47.557 1.00 2.75 C
ATOM 364 N VAL A 47 39.921 26.428 47.126 1.00 2.75 N
ATOM 365 CA VAL A 47 39.525 27.827 47.191 1.00 2.75 C
ATOM 366 C VAL A 47 38.636 28.117 45.976 1.00 2.75 C
ATOM 367 O VAL A 47 38.873 27.569 44.901 1.00 2.75 O
ATOM 368 CB VAL A 47 40.782 28.736 47.192 1.00 2.75 C
ATOM 369 CG1 VAL A 47 41.524 28.615 45.863 1.00 2.75 C
ATOM 370 CG2 VAL A 47 40.401 30.177 47.472 1.00 2.75 C
ATOM 371 N ARG A 48 37.605 28.948 46.141 1.00 6.58 N
ATOM 372 CA ARG A 48 36.722 29.256 45.014 1.00 6.58 C
ATOM 373 C ARG A 48 37.595 29.782 43.884 1.00 6.58 C
ATOM 374 O ARG A 48 38.360 30.727 44.074 1.00 6.58 O
ATOM 375 CB ARG A 48 35.674 30.313 45.392 1.00 6.58 C
ATOM 376 CG ARG A 48 34.751 30.691 44.227 1.00 17.56 C
ATOM 377 CD ARG A 48 33.809 31.848 44.571 1.00 28.54 C
ATOM 378 NE ARG A 48 32.778 31.472 45.535 1.00 39.52 N
ATOM 379 CZ ARG A 48 31.814 32.286 45.956 1.00 50.50 C
ATOM 380 NH1 ARG A 48 31.742 33.528 45.500 1.00 61.48 N
ATOM 381 NH2 ARG A 48 30.919 31.858 46.836 1.00 61.48 N
ATOM 382 N PRO A 49 37.507 29.162 42.696 1.00 6.58 N
ATOM 383 CA PRO A 49 38.319 29.607 41.558 1.00 6.58 C
ATOM 384 C PRO A 49 37.776 30.880 40.921 1.00 6.58 C
ATOM 385 O PRO A 49 36.635 31.274 41.170 1.00 6.58 O
ATOM 386 CB PRO A 49 38.263 28.414 40.614 1.00 6.58 C
ATOM 387 CG PRO A 49 36.890 27.875 40.853 1.00 17.56 C
ATOM 388 CD PRO A 49 36.769 27.929 42.363 1.00 28.54 C
ATOM 389 N THR A 50 38.604 31.520 40.101 1.00 6.58 N
ATOM 390 CA THR A 50 38.206 32.754 39.433 1.00 6.58 C
ATOM 391 C THR A 50 38.573 32.681 37.959 1.00 6.58 C
ATOM 392 O THR A 50 39.582 32.073 37.598 1.00 6.58 O
ATOM 393 CB THR A 50 38.931 33.963 40.049 1.00 6.58 C
ATOM 394 OG1 THR A 50 40.337 33.847 39.802 1.00 17.56 O
ATOM 395 CG2 THR A 50 38.694 34.014 41.553 1.00 17.56 C
ATOM 396 N ILE A 51 37.751 33.282 37.108 1.00 6.58 N
ATOM 397 CA ILE A 51 38.036 33.292 35.676 1.00 6.58 C
ATOM 398 C ILE A 51 38.876 34.539 35.412 1.00 6.58 C
ATOM 399 O ILE A 51 38.528 35.631 35.875 1.00 6.58 O
ATOM 400 CB ILE A 51 36.733 33.355 34.840 1.00 6.58 C
ATOM 401 CG1 ILE A 51 35.838 32.158 35.182 1.00 17.56 C
ATOM 402 CG2 ILE A 51 37.063 33.354 33.357 1.00 17.56 C
ATOM 403 CD1 ILE A 51 36.490 30.797 34.969 1.00 28.54 C
ATOM 404 N GLN A 52 39.991 34.372 34.700 1.00 6.58 N
ATOM 405 CA GLN A 52 40.891 35.486 34.406 1.00 6.58 C
ATOM 406 C GLN A 52 41.364 35.523 32.958 1.00 6.58 C
ATOM 407 O GLN A 52 41.000 34.676 32.141 1.00 6.58 O
ATOM 408 CB GLN A 52 42.131 35.411 35.296 1.00 6.58 C
ATOM 409 CG GLN A 52 41.862 35.283 36.779 1.00 17.56 C
ATOM 410 CD GLN A 52 43.097 34.864 37.554 1.00 28.54 C
ATOM 411 OE1 GLN A 52 44.168 35.450 37.403 1.00 39.52 O
ATOM 412 NE2 GLN A 52 42.951 33.848 38.393 1.00 39.52 N
ATOM 413 N THR A 53 42.198 36.518 32.665 1.00 6.58 N
ATOM 414 CA THR A 53 42.784 36.708 31.335 1.00 6.58 C
ATOM 415 C THR A 53 44.222 36.172 31.290 1.00 6.58 C
ATOM 416 O THR A 53 45.039 36.458 32.173 1.00 6.58 O
ATOM 417 CB THR A 53 42.822 38.199 30.954 1.00 6.58 C
ATOM 418 OG1 THR A 53 41.497 38.745 31.002 1.00 17.56 O
ATOM 419 CG2 THR A 53 43.394 38.368 29.555 1.00 17.56 C
ATOM 420 N TYR A 54 44.537 35.418 30.244 1.00 6.58 N
ATOM 421 CA TYR A 54 45.881 34.843 30.080 1.00 6.58 C
ATOM 422 C TYR A 54 46.313 34.975 28.624 1.00 6.58 C
ATOM 423 O TYR A 54 45.550 35.463 27.797 1.00 6.58 O
ATOM 424 CB TYR A 54 45.871 33.352 30.440 1.00 6.58 C
ATOM 425 CG TYR A 54 45.516 33.023 31.878 1.00 17.56 C
ATOM 426 CD1 TYR A 54 46.472 33.103 32.889 1.00 28.54 C
ATOM 427 CD2 TYR A 54 44.231 32.599 32.219 1.00 28.54 C
ATOM 428 CE1 TYR A 54 46.158 32.763 34.202 1.00 39.52 C
ATOM 429 CE2 TYR A 54 43.908 32.260 33.525 1.00 39.52 C
ATOM 430 CZ TYR A 54 44.875 32.343 34.512 1.00 50.50 C
ATOM 431 OH TYR A 54 44.559 32.000 35.806 1.00 61.48 O
ATOM 432 N ARG A 55 47.541 34.545 28.335 1.00 2.75 N
ATOM 433 CA ARG A 55 48.108 34.533 26.980 1.00 2.75 C
ATOM 434 C ARG A 55 48.536 33.107 26.654 1.00 2.75 C
ATOM 435 O ARG A 55 49.060 32.393 27.524 1.00 2.75 O
ATOM 436 CB ARG A 55 49.388 35.374 26.850 1.00 2.75 C
ATOM 437 CG ARG A 55 49.234 36.863 26.771 1.00 2.75 C
ATOM 438 CD ARG A 55 50.560 37.443 26.279 1.00 2.75 C
ATOM 439 NE ARG A 55 50.656 38.887 26.450 1.00 2.75 N
ATOM 440 CZ ARG A 55 51.751 39.595 26.207 1.00 2.75 C
ATOM 441 NH1 ARG A 55 52.850 38.995 25.769 1.00 2.75 N
ATOM 442 NH2 ARG A 55 51.763 40.901 26.445 1.00 2.75 N
ATOM 443 N ASP A 56 48.338 32.695 25.406 1.00 2.75 N
ATOM 444 CA ASP A 56 48.802 31.376 24.999 1.00 2.75 C
ATOM 445 C ASP A 56 50.175 31.571 24.343 1.00 2.75 C
ATOM 446 O ASP A 56 50.692 32.693 24.283 1.00 2.75 O
ATOM 447 CB ASP A 56 47.828 30.692 24.029 1.00 2.75 C
ATOM 448 CG ASP A 56 47.463 31.558 22.828 1.00 2.75 C
ATOM 449 OD1 ASP A 56 48.277 32.392 22.382 1.00 2.75 O
ATOM 450 OD2 ASP A 56 46.346 31.373 22.303 1.00 2.75 O
ATOM 451 N GLU A 57 50.764 30.485 23.857 1.00 2.75 N
ATOM 452 CA GLU A 57 52.074 30.553 23.240 1.00 2.75 C
ATOM 453 C GLU A 57 52.174 31.476 22.030 1.00 2.75 C
ATOM 454 O GLU A 57 53.229 32.067 21.800 1.00 2.75 O
ATOM 455 CB GLU A 57 52.540 29.159 22.842 1.00 2.75 C
ATOM 456 CG GLU A 57 53.986 29.147 22.410 1.00 2.75 C
ATOM 457 CD GLU A 57 54.443 27.799 21.954 1.00 2.75 C
ATOM 458 OE1 GLU A 57 54.101 26.799 22.626 1.00 2.75 O
ATOM 459 OE2 GLU A 57 55.166 27.739 20.928 1.00 2.75 O
ATOM 460 N GLN A 58 51.102 31.569 21.242 1.00 2.75 N
ATOM 461 CA GLN A 58 51.072 32.429 20.056 1.00 2.75 C
ATOM 462 C GLN A 58 50.853 33.879 20.475 1.00 2.75 C
ATOM 463 O GLN A 58 50.757 34.766 19.635 1.00 2.75 O
ATOM 464 CB GLN A 58 49.948 31.986 19.102 1.00 2.75 C
ATOM 465 CG GLN A 58 50.322 30.826 18.180 1.00 2.75 C
ATOM 466 CD GLN A 58 49.116 30.184 17.489 1.00 2.75 C
ATOM 467 OE1 GLN A 58 48.243 30.876 16.942 1.00 2.75 O
ATOM 468 NE2 GLN A 58 49.074 28.854 17.498 1.00 2.75 N
ATOM 469 N GLU A 59 50.767 34.093 21.788 1.00 2.75 N
ATOM 470 CA GLU A 59 50.568 35.405 22.400 1.00 2.75 C
ATOM 471 C GLU A 59 49.160 36.017 22.289 1.00 2.75 C
ATOM 472 O GLU A 59 49.020 37.232 22.351 1.00 2.75 O
ATOM 473 CB GLU A 59 51.594 36.407 21.858 1.00 2.75 C
ATOM 474 CG GLU A 59 53.050 35.958 21.945 1.00 2.75 C
ATOM 475 CD GLU A 59 53.569 35.861 23.369 1.00 2.75 C
ATOM 476 OE1 GLU A 59 53.031 36.548 24.253 1.00 2.75 O
ATOM 477 OE2 GLU A 59 54.536 35.108 23.603 1.00 2.75 O
ATOM 478 N ARG A 60 48.134 35.179 22.139 1.00 2.75 N
ATOM 479 CA ARG A 60 46.741 35.630 22.052 1.00 2.75 C
ATOM 480 C ARG A 60 46.102 35.633 23.461 1.00 2.75 C
ATOM 481 O ARG A 60 46.320 34.704 24.242 1.00 2.75 O
ATOM 482 CB ARG A 60 45.932 34.699 21.121 1.00 2.75 C
ATOM 483 CG ARG A 60 46.589 34.384 19.760 1.00 2.75 C
ATOM 484 CD ARG A 60 45.768 33.320 18.998 1.00 2.75 C
ATOM 485 NE ARG A 60 46.277 32.993 17.657 1.00 2.75 N
ATOM 486 CZ ARG A 60 46.263 33.827 16.623 1.00 2.75 C
ATOM 487 NH1 ARG A 60 45.764 35.052 16.755 1.00 2.75 N
ATOM 488 NH2 ARG A 60 46.767 33.446 15.457 1.00 2.75 N
ATOM 489 N GLU A 61 45.316 36.663 23.777 1.00 2.75 N
ATOM 490 CA GLU A 61 44.659 36.788 25.092 1.00 2.75 C
ATOM 491 C GLU A 61 43.226 36.234 25.142 1.00 2.75 C
ATOM 492 O GLU A 61 42.454 36.385 24.189 1.00 2.75 O
ATOM 493 CB GLU A 61 44.632 38.253 25.526 1.00 2.75 C
ATOM 494 CG GLU A 61 45.997 38.851 25.745 1.00 2.75 C
ATOM 495 CD GLU A 61 45.940 40.168 26.502 1.00 2.75 C
ATOM 496 OE1 GLU A 61 46.927 40.463 27.203 1.00 2.75 O
ATOM 497 OE2 GLU A 61 44.923 40.900 26.401 1.00 2.75 O
ATOM 498 N GLY A 62 42.871 35.615 26.266 1.00 2.75 N
ATOM 499 CA GLY A 62 41.536 35.043 26.409 1.00 2.75 C
ATOM 500 C GLY A 62 41.231 34.629 27.842 1.00 2.75 C
ATOM 501 O GLY A 62 42.041 34.849 28.741 1.00 2.75 O
ATOM 502 N SER A 63 40.070 34.019 28.063 1.00 2.75 N
ATOM 503 CA SER A 63 39.688 33.613 29.409 1.00 2.75 C
ATOM 504 C SER A 63 39.919 32.142 29.725 1.00 2.75 C
ATOM 505 O SER A 63 39.943 31.295 28.840 1.00 2.75 O
ATOM 506 CB SER A 63 38.220 33.956 29.657 1.00 2.75 C
ATOM 507 OG SER A 63 38.035 35.358 29.654 1.00 2.75 O
ATOM 508 N ASN A 64 40.094 31.863 31.014 1.00 2.75 N
ATOM 509 CA ASN A 64 40.303 30.513 31.527 1.00 2.75 C
ATOM 510 C ASN A 64 40.424 30.614 33.048 1.00 2.75 C
ATOM 511 O ASN A 64 40.265 31.694 33.611 1.00 2.75 O
ATOM 512 CB ASN A 64 41.580 29.908 30.953 1.00 2.75 C
ATOM 513 CG ASN A 64 41.529 28.393 30.893 1.00 2.75 C
ATOM 514 OD1 ASN A 64 40.803 27.751 31.651 1.00 2.75 O
ATOM 515 ND2 ASN A 64 42.319 27.816 30.008 1.00 2.75 N
ATOM 516 N GLY A 65 40.705 29.492 33.705 1.00 2.75 N
ATOM 517 CA GLY A 65 40.845 29.498 35.155 1.00 2.75 C
ATOM 518 C GLY A 65 41.566 28.271 35.690 1.00 2.75 C
ATOM 519 O GLY A 65 41.647 27.239 35.020 1.00 2.75 O
ATOM 520 N GLN A 66 42.092 28.382 36.908 1.00 2.75 N
ATOM 521 CA GLN A 66 42.811 27.283 37.531 1.00 2.75 C
ATOM 522 C GLN A 66 42.101 26.858 38.800 1.00 2.75 C
ATOM 523 O GLN A 66 41.749 27.693 39.630 1.00 6.58 O
ATOM 524 CB GLN A 66 44.256 27.702 37.838 1.00 2.75 C
ATOM 525 CG GLN A 66 45.061 28.035 36.572 1.00 2.75 C
ATOM 526 CD GLN A 66 46.476 28.504 36.870 1.00 2.75 C
ATOM 527 OE1 GLN A 66 47.325 27.715 37.271 1.00 2.75 O
ATOM 528 NE2 GLN A 66 46.727 29.796 36.687 1.00 2.75 N
ATOM 529 N LEU A 67 41.903 25.548 38.930 1.00 2.75 N
ATOM 530 CA LEU A 67 41.223 24.933 40.070 1.00 2.75 C
ATOM 531 C LEU A 67 42.171 24.013 40.831 1.00 2.75 C
ATOM 532 O LEU A 67 42.919 23.239 40.230 1.00 6.58 O
ATOM 533 CB LEU A 67 40.034 24.111 39.572 1.00 2.75 C
ATOM 534 CG LEU A 67 39.229 23.238 40.536 1.00 2.75 C
ATOM 535 CD1 LEU A 67 38.464 24.107 41.506 1.00 2.75 C
ATOM 536 CD2 LEU A 67 38.260 22.374 39.742 1.00 2.75 C
ATOM 537 N ARG A 68 42.142 24.130 42.154 1.00 2.75 N
ATOM 538 CA ARG A 68 42.956 23.307 43.035 1.00 2.75 C
ATOM 539 C ARG A 68 42.006 22.437 43.854 1.00 2.75 C
ATOM 540 O ARG A 68 41.051 22.939 44.457 1.00 6.58 O
ATOM 541 CB ARG A 68 43.788 24.178 43.982 1.00 2.75 C
ATOM 542 CG ARG A 68 44.669 23.384 44.943 1.00 2.75 C
ATOM 543 CD ARG A 68 45.297 24.302 45.998 1.00 2.75 C
ATOM 544 NE ARG A 68 45.248 23.716 47.330 1.00 2.75 N
ATOM 545 CZ ARG A 68 45.555 24.357 48.452 1.00 2.75 C
ATOM 546 NH1 ARG A 68 45.949 25.629 48.424 1.00 2.75 N
ATOM 547 NH2 ARG A 68 45.437 23.733 49.612 1.00 2.75 N
ATOM 548 N ILE A 69 42.260 21.134 43.859 1.00 2.75 N
ATOM 549 CA ILE A 69 41.440 20.188 44.602 1.00 2.75 C
ATOM 550 C ILE A 69 42.374 19.491 45.581 1.00 2.75 C
ATOM 551 O ILE A 69 43.463 19.076 45.199 1.00 6.58 O
ATOM 552 CB ILE A 69 40.838 19.103 43.667 1.00 2.75 C
ATOM 553 CG1 ILE A 69 40.102 19.765 42.512 1.00 2.75 C
ATOM 554 CG2 ILE A 69 39.885 18.189 44.442 1.00 2.75 C
ATOM 555 CD1 ILE A 69 39.009 20.704 42.973 1.00 2.75 C
ATOM 556 N ASP A 70 41.956 19.379 46.834 1.00 2.75 N
ATOM 557 CA ASP A 70 42.754 18.684 47.827 1.00 2.75 C
ATOM 558 C ASP A 70 41.903 17.541 48.340 1.00 2.75 C
ATOM 559 O ASP A 70 40.713 17.454 48.057 1.00 6.58 O
ATOM 560 CB ASP A 70 43.090 19.555 49.037 1.00 2.75 C
ATOM 561 CG ASP A 70 43.571 20.936 48.675 1.00 2.75 C
ATOM 562 OD1 ASP A 70 44.169 21.129 47.592 1.00 2.75 O
ATOM 563 OD2 ASP A 70 43.355 21.841 49.509 1.00 2.75 O
ATOM 564 N HIS A 71 42.524 16.653 49.098 1.00 2.75 N
ATOM 565 CA HIS A 71 41.800 15.555 49.712 1.00 2.75 C
ATOM 566 C HIS A 71 42.616 14.918 50.808 1.00 2.75 C
ATOM 567 O HIS A 71 43.510 15.558 51.382 1.00 2.75 O
ATOM 568 CB HIS A 71 41.337 14.470 48.715 1.00 2.75 C
ATOM 569 CG HIS A 71 42.063 14.457 47.405 1.00 2.75 C
ATOM 570 ND1 HIS A 71 43.370 14.872 47.260 1.00 2.75 N
ATOM 571 CD2 HIS A 71 41.666 14.036 46.179 1.00 2.75 C
ATOM 572 CE1 HIS A 71 43.745 14.713 46.004 1.00 2.75 C
ATOM 573 NE2 HIS A 71 42.729 14.209 45.326 1.00 2.75 N
ATOM 574 N LEU A 72 42.305 13.664 51.108 1.00 6.58 N
ATOM 575 CA LEU A 72 43.013 12.947 52.145 1.00 6.58 C
ATOM 576 C LEU A 72 43.370 11.530 51.722 1.00 6.58 C
ATOM 577 O LEU A 72 44.543 11.219 51.486 1.00 6.58 O
ATOM 578 CB LEU A 72 42.159 12.903 53.413 1.00 6.58 C
ATOM 579 CG LEU A 72 42.824 12.362 54.688 1.00 17.56 C
ATOM 580 CD1 LEU A 72 42.887 10.839 54.669 1.00 28.54 C
ATOM 581 CD2 LEU A 72 44.214 12.974 54.820 1.00 28.54 C
ATOM 582 N ASP A 73 42.336 10.695 51.626 1.00 6.58 N
ATOM 583 CA ASP A 73 42.438 9.274 51.268 1.00 6.58 C
ATOM 584 C ASP A 73 42.532 9.014 49.757 1.00 6.58 C
ATOM 585 O ASP A 73 43.367 8.217 49.317 1.00 6.58 O
ATOM 586 CB ASP A 73 41.232 8.536 51.890 1.00 6.58 C
ATOM 587 CG ASP A 73 41.061 7.104 51.385 1.00 17.56 C
ATOM 588 OD1 ASP A 73 42.021 6.314 51.454 1.00 28.54 O
ATOM 589 OD2 ASP A 73 39.944 6.763 50.933 1.00 28.54 O
ATOM 590 N ALA A 74 41.696 9.704 48.984 1.00 6.58 N
ATOM 591 CA ALA A 74 41.639 9.584 47.520 1.00 6.58 C
ATOM 592 C ALA A 74 42.966 9.206 46.872 1.00 6.58 C
ATOM 593 O ALA A 74 43.158 8.059 46.440 1.00 6.58 O
ATOM 594 CB ALA A 74 41.134 10.884 46.923 1.00 6.58 C
ATOM 595 N SER A 75 43.873 10.179 46.793 1.00 6.58 N
ATOM 596 CA SER A 75 45.194 9.978 46.208 1.00 6.58 C
ATOM 597 C SER A 75 46.268 10.802 46.906 1.00 6.58 C
ATOM 598 O SER A 75 47.454 10.676 46.598 1.00 6.58 O
ATOM 599 CB SER A 75 45.177 10.361 44.724 1.00 6.58 C
ATOM 600 OG SER A 75 46.477 10.711 44.261 1.00 17.56 O
ATOM 601 N GLN A 76 45.859 11.650 47.841 1.00 6.58 N
ATOM 602 CA GLN A 76 46.815 12.516 48.516 1.00 6.58 C
ATOM 603 C GLN A 76 47.342 13.452 47.426 1.00 6.58 C
ATOM 604 O GLN A 76 46.906 13.372 46.274 1.00 6.58 O
ATOM 605 CB GLN A 76 47.979 11.717 49.106 1.00 6.58 C
ATOM 606 CG GLN A 76 47.628 10.833 50.279 1.00 17.56 C
ATOM 607 CD GLN A 76 48.865 10.302 50.963 1.00 28.54 C
ATOM 608 OE1 GLN A 76 49.658 11.069 51.505 1.00 39.52 O
ATOM 609 NE2 GLN A 76 49.044 8.987 50.936 1.00 39.52 N
ATOM 610 N GLU A 77 48.269 14.334 47.780 1.00 2.75 N
ATOM 611 CA GLU A 77 48.827 15.275 46.804 1.00 2.75 C
ATOM 612 C GLU A 77 47.784 16.210 46.213 1.00 2.75 C
ATOM 613 O GLU A 77 46.863 15.762 45.512 1.00 2.75 O
ATOM 614 CB GLU A 77 49.487 14.540 45.645 1.00 2.75 C
ATOM 615 CG GLU A 77 50.748 13.777 45.989 1.00 2.75 C
ATOM 616 CD GLU A 77 51.640 13.565 44.770 1.00 2.75 C
ATOM 617 OE1 GLU A 77 51.111 13.485 43.635 1.00 2.75 O
ATOM 618 OE2 GLU A 77 52.875 13.465 44.948 1.00 2.75 O
ATOM 619 N PRO A 78 47.910 17.522 46.480 1.00 2.75 N
ATOM 620 CA PRO A 78 46.923 18.451 45.917 1.00 2.75 C
ATOM 621 C PRO A 78 47.045 18.472 44.387 1.00 2.75 C
ATOM 622 O PRO A 78 48.130 18.259 43.850 1.00 2.75 O
ATOM 623 CB PRO A 78 47.299 19.775 46.571 1.00 2.75 C
ATOM 624 CG PRO A 78 48.806 19.658 46.712 1.00 2.75 C
ATOM 625 CD PRO A 78 48.950 18.245 47.236 1.00 2.75 C
ATOM 626 N GLN A 79 45.945 18.732 43.685 1.00 2.75 N
ATOM 627 CA GLN A 79 45.965 18.738 42.221 1.00 2.75 C
ATOM 628 C GLN A 79 45.442 20.046 41.637 1.00 2.75 C
ATOM 629 O GLN A 79 44.452 20.577 42.120 1.00 2.75 O
ATOM 630 CB GLN A 79 45.104 17.582 41.690 1.00 2.75 C
ATOM 631 CG GLN A 79 44.758 16.545 42.743 1.00 2.75 C
ATOM 632 CD GLN A 79 45.138 15.144 42.314 1.00 2.75 C
ATOM 633 OE1 GLN A 79 45.167 14.212 43.125 1.00 2.75 O
ATOM 634 NE2 GLN A 79 45.433 14.986 41.027 1.00 2.75 N
ATOM 635 N TRP A 80 46.122 20.558 40.611 1.00 6.58 N
ATOM 636 CA TRP A 80 45.714 21.784 39.925 1.00 6.58 C
ATOM 637 C TRP A 80 45.298 21.416 38.512 1.00 6.58 C
ATOM 638 O TRP A 80 46.007 20.680 37.823 1.00 6.58 O
ATOM 639 CB TRP A 80 46.863 22.798 39.850 1.00 6.58 C
ATOM 640 CG TRP A 80 47.138 23.513 41.135 1.00 17.56 C
ATOM 641 CD1 TRP A 80 47.869 23.052 42.193 1.00 28.54 C
ATOM 642 CD2 TRP A 80 46.689 24.822 41.497 1.00 28.54 C
ATOM 643 NE1 TRP A 80 47.906 23.996 43.190 1.00 39.52 N
ATOM 644 CE2 TRP A 80 47.189 25.093 42.789 1.00 39.52 C
ATOM 645 CE3 TRP A 80 45.912 25.795 40.856 1.00 39.52 C
ATOM 646 CZ2 TRP A 80 46.936 26.300 43.452 1.00 50.50 C
ATOM 647 CZ3 TRP A 80 45.661 26.995 41.517 1.00 50.50 C
ATOM 648 CH2 TRP A 80 46.173 27.235 42.800 1.00 61.48 C
ATOM 649 N ILE A 81 44.149 21.932 38.082 1.00 6.58 N
ATOM 650 CA ILE A 81 43.639 21.647 36.747 1.00 6.58 C
ATOM 651 C ILE A 81 43.137 22.923 36.083 1.00 6.58 C
ATOM 652 O ILE A 81 42.666 23.830 36.765 1.00 6.58 O
ATOM 653 CB ILE A 81 42.460 20.657 36.814 1.00 6.58 C
ATOM 654 CG1 ILE A 81 42.919 19.333 37.427 1.00 17.56 C
ATOM 655 CG2 ILE A 81 41.877 20.441 35.426 1.00 17.56 C
ATOM 656 CD1 ILE A 81 41.820 18.285 37.524 1.00 28.54 C
ATOM 657 N TRP A 82 43.252 23.004 34.763 1.00 6.58 N
ATOM 658 CA TRP A 82 42.733 24.167 34.059 1.00 6.58 C
ATOM 659 C TRP A 82 41.257 23.846 33.845 1.00 6.58 C
ATOM 660 O TRP A 82 40.907 22.739 33.429 1.00 6.58 O
ATOM 661 CB TRP A 82 43.457 24.389 32.726 1.00 6.58 C
ATOM 662 CG TRP A 82 44.872 24.851 32.906 1.00 17.56 C
ATOM 663 CD1 TRP A 82 45.985 24.069 32.988 1.00 28.54 C
ATOM 664 CD2 TRP A 82 45.315 26.199 33.103 1.00 28.54 C
ATOM 665 NE1 TRP A 82 47.096 24.843 33.225 1.00 39.52 N
ATOM 666 CE2 TRP A 82 46.714 26.156 33.300 1.00 39.52 C
ATOM 667 CE3 TRP A 82 44.666 27.441 33.134 1.00 39.52 C
ATOM 668 CZ2 TRP A 82 47.478 27.308 33.527 1.00 50.50 C
ATOM 669 CZ3 TRP A 82 45.426 28.590 33.361 1.00 50.50 C
ATOM 670 CH2 TRP A 82 46.819 28.511 33.554 1.00 61.48 C
ATOM 671 N MET A 83 40.396 24.812 34.149 1.00 6.58 N
ATOM 672 CA MET A 83 38.952 24.614 34.064 1.00 6.58 C
ATOM 673 C MET A 83 38.299 24.360 32.704 1.00 6.58 C
ATOM 674 O MET A 83 37.179 23.854 32.657 1.00 6.58 O
ATOM 675 CB MET A 83 38.249 25.768 34.785 1.00 6.58 C
ATOM 676 CG MET A 83 38.328 25.644 36.306 1.00 17.56 C
ATOM 677 SD MET A 83 38.012 27.184 37.202 1.00 28.54 S
ATOM 678 CE MET A 83 36.223 27.187 37.257 1.00 39.52 C
ATOM 679 N ASP A 84 38.971 24.689 31.604 1.00 6.58 N
ATOM 680 CA ASP A 84 38.383 24.432 30.286 1.00 6.58 C
ATOM 681 C ASP A 84 38.278 22.929 30.000 1.00 6.58 C
ATOM 682 O ASP A 84 37.691 22.512 29.001 1.00 6.58 O
ATOM 683 CB ASP A 84 39.209 25.094 29.177 1.00 6.58 C
ATOM 684 CG ASP A 84 40.675 24.686 29.203 1.00 17.56 C
ATOM 685 OD1 ASP A 84 41.367 24.906 28.186 1.00 28.54 O
ATOM 686 OD2 ASP A 84 41.137 24.157 30.233 1.00 28.54 O
ATOM 687 N ARG A 85 38.846 22.119 30.883 1.00 6.58 N
ATOM 688 CA ARG A 85 38.827 20.665 30.725 1.00 6.58 C
ATOM 689 C ARG A 85 37.592 20.012 31.361 1.00 6.58 C
ATOM 690 O ARG A 85 37.367 18.809 31.205 1.00 6.58 O
ATOM 691 CB ARG A 85 40.089 20.062 31.348 1.00 6.58 C
ATOM 692 CG ARG A 85 41.395 20.729 30.918 1.00 17.56 C
ATOM 693 CD ARG A 85 41.800 20.392 29.478 1.00 28.54 C
ATOM 694 NE ARG A 85 40.870 20.912 28.477 1.00 39.52 N
ATOM 695 CZ ARG A 85 41.024 20.762 27.164 1.00 50.50 C
ATOM 696 NH1 ARG A 85 42.074 20.107 26.687 1.00 61.48 N
ATOM 697 NH2 ARG A 85 40.128 21.265 26.327 1.00 61.48 N
ATOM 698 N ILE A 86 36.791 20.802 32.070 1.00 2.75 N
ATOM 699 CA ILE A 86 35.601 20.281 32.751 1.00 2.75 C
ATOM 700 C ILE A 86 34.364 20.109 31.889 1.00 2.75 C
ATOM 701 O ILE A 86 34.032 20.976 31.093 1.00 6.58 O
ATOM 702 CB ILE A 86 35.220 21.168 33.954 1.00 2.75 C
ATOM 703 CG1 ILE A 86 36.316 21.051 35.018 1.00 2.75 C
ATOM 704 CG2 ILE A 86 33.830 20.772 34.484 1.00 2.75 C
ATOM 705 CD1 ILE A 86 36.167 21.980 36.205 1.00 2.75 C
ATOM 706 N VAL A 87 33.673 18.990 32.100 1.00 6.58 N
ATOM 707 CA VAL A 87 32.456 18.642 31.368 1.00 6.58 C
ATOM 708 C VAL A 87 31.228 18.574 32.288 1.00 6.58 C
ATOM 709 O VAL A 87 30.091 18.768 31.847 1.00 6.58 O
ATOM 710 CB VAL A 87 32.635 17.278 30.669 1.00 6.58 C
ATOM 711 CG1 VAL A 87 31.420 16.951 29.831 1.00 17.56 C
ATOM 712 CG2 VAL A 87 33.881 17.305 29.814 1.00 17.56 C
ATOM 713 N ALA A 88 31.454 18.301 33.568 1.00 6.58 N
ATOM 714 CA ALA A 88 30.349 18.213 34.517 1.00 6.58 C
ATOM 715 C ALA A 88 30.841 18.331 35.957 1.00 6.58 C
ATOM 716 O ALA A 88 31.971 17.964 36.263 1.00 6.58 O
ATOM 717 CB ALA A 88 29.605 16.888 34.329 1.00 6.58 C
ATOM 718 N VAL A 89 29.980 18.845 36.830 1.00 6.58 N
ATOM 719 CA VAL A 89 30.305 19.005 38.242 1.00 6.58 C
ATOM 720 C VAL A 89 29.085 18.623 39.064 1.00 6.58 C
ATOM 721 O VAL A 89 28.040 19.262 38.954 1.00 6.58 O
ATOM 722 CB VAL A 89 30.676 20.465 38.584 1.00 6.58 C
ATOM 723 CG1 VAL A 89 30.915 20.598 40.079 1.00 17.56 C
ATOM 724 CG2 VAL A 89 31.916 20.894 37.805 1.00 17.56 C
ATOM 725 N HIS A 90 29.211 17.578 39.878 1.00 6.58 N
ATOM 726 CA HIS A 90 28.100 17.137 40.714 1.00 6.58 C
ATOM 727 C HIS A 90 28.487 17.151 42.194 1.00 6.58 C
ATOM 728 O HIS A 90 29.606 16.795 42.558 1.00 6.58 O
ATOM 729 CB HIS A 90 27.646 15.748 40.263 1.00 6.58 C
ATOM 730 CG HIS A 90 27.053 15.737 38.886 1.00 17.56 C
ATOM 731 ND1 HIS A 90 25.859 16.357 38.586 1.00 28.54 N
ATOM 732 CD2 HIS A 90 27.515 15.231 37.719 1.00 28.54 C
ATOM 733 CE1 HIS A 90 25.612 16.234 37.295 1.00 39.52 C
ATOM 734 NE2 HIS A 90 26.602 15.554 36.745 1.00 39.52 N
ATOM 735 N PRO A 91 27.567 17.581 43.065 1.00 6.58 N
ATOM 736 CA PRO A 91 27.811 17.652 44.510 1.00 6.58 C
ATOM 737 C PRO A 91 27.701 16.304 45.227 1.00 6.58 C
ATOM 738 O PRO A 91 27.305 15.316 44.619 1.00 6.58 O
ATOM 739 CB PRO A 91 26.738 18.617 44.971 1.00 6.58 C
ATOM 740 CG PRO A 91 25.575 18.186 44.121 1.00 17.56 C
ATOM 741 CD PRO A 91 26.200 18.031 42.746 1.00 28.54 C
ATOM 742 N MET A 92 28.075 16.288 46.512 1.00 2.75 N
ATOM 743 CA MET A 92 28.001 15.116 47.400 1.00 2.75 C
ATOM 744 C MET A 92 29.240 14.214 47.533 1.00 2.75 C
ATOM 745 O MET A 92 29.518 13.693 48.624 1.00 2.75 O
ATOM 746 CB MET A 92 26.772 14.261 47.054 1.00 2.75 C
ATOM 747 CG MET A 92 26.441 13.184 48.082 1.00 2.75 C
ATOM 748 SD MET A 92 26.160 13.829 49.736 1.00 2.75 S
ATOM 749 CE MET A 92 24.402 13.775 49.827 1.00 2.75 C
ATOM 750 N PRO A 93 29.996 13.996 46.443 1.00 1.02 N
ATOM 751 CA PRO A 93 31.176 13.137 46.583 1.00 1.02 C
ATOM 752 C PRO A 93 32.396 13.910 47.080 1.00 1.02 C
ATOM 753 O PRO A 93 33.506 13.658 46.572 1.00 1.02 O
ATOM 754 CB PRO A 93 31.369 12.597 45.173 1.00 1.02 C
ATOM 755 CG PRO A 93 30.915 13.739 44.343 1.00 1.02 C
ATOM 756 CD PRO A 93 29.657 14.172 45.020 1.00 1.02 C
TER 757 PRO A 93
ATOM 758 N MET B 1 -0.631 29.877 42.866 1.00 2.75 N
ATOM 759 CA MET B 1 -0.995 29.262 41.562 1.00 2.75 C
ATOM 760 C MET B 1 0.286 28.899 40.811 1.00 2.75 C
ATOM 761 O MET B 1 1.216 29.701 40.724 1.00 2.75 O
ATOM 762 CB MET B 1 -1.844 30.260 40.745 1.00 2.75 C
ATOM 763 CG MET B 1 -3.198 29.715 40.246 1.00 2.75 C
ATOM 764 SD MET B 1 -4.537 30.952 40.018 1.00 2.75 S
ATOM 765 CE MET B 1 -3.845 31.930 38.718 1.00 2.75 C
ATOM 766 N PRO B 2 0.365 27.664 40.285 1.00 6.58 N
ATOM 767 CA PRO B 2 1.563 27.256 39.548 1.00 6.58 C
ATOM 768 C PRO B 2 1.684 28.116 38.298 1.00 6.58 C
ATOM 769 O PRO B 2 0.673 28.422 37.654 1.00 6.58 O
ATOM 770 CB PRO B 2 1.280 25.794 39.214 1.00 6.58 C
ATOM 771 CG PRO B 2 0.419 25.349 40.353 1.00 17.56 C
ATOM 772 CD PRO B 2 -0.533 26.513 40.491 1.00 28.54 C
ATOM 773 N LYS B 3 2.911 28.510 37.962 1.00 6.58 N
ATOM 774 CA LYS B 3 3.157 29.337 36.781 1.00 6.58 C
ATOM 775 C LYS B 3 3.480 28.475 35.573 1.00 6.58 C
ATOM 776 O LYS B 3 4.410 27.669 35.604 1.00 6.58 O
ATOM 777 CB LYS B 3 4.316 30.309 37.024 1.00 6.58 C
ATOM 778 CG LYS B 3 4.053 31.350 38.103 1.00 17.56 C
ATOM 779 CD LYS B 3 5.227 32.302 38.249 1.00 28.54 C
ATOM 780 CE LYS B 3 4.916 33.416 39.238 1.00 39.52 C
ATOM 781 NZ LYS B 3 6.037 34.397 39.360 1.00 50.50 N
ATOM 782 N TYR B 4 2.702 28.644 34.510 1.00 2.75 N
ATOM 783 CA TYR B 4 2.905 27.887 33.276 1.00 2.75 C
ATOM 784 C TYR B 4 3.900 28.588 32.348 1.00 2.75 C
ATOM 785 O TYR B 4 4.089 29.798 32.423 1.00 6.58 O
ATOM 786 CB TYR B 4 1.557 27.718 32.559 1.00 2.75 C
ATOM 787 CG TYR B 4 1.645 27.281 31.111 1.00 2.75 C
ATOM 788 CD1 TYR B 4 1.661 25.925 30.762 1.00 2.75 C
ATOM 789 CD2 TYR B 4 1.721 28.226 30.084 1.00 2.75 C
ATOM 790 CE1 TYR B 4 1.747 25.523 29.421 1.00 2.75 C
ATOM 791 CE2 TYR B 4 1.812 27.836 28.748 1.00 2.75 C
ATOM 792 CZ TYR B 4 1.821 26.477 28.426 1.00 2.75 C
ATOM 793 OH TYR B 4 1.898 26.086 27.098 1.00 2.75 O
ATOM 794 N ALA B 5 4.527 27.807 31.472 1.00 6.58 N
ATOM 795 CA ALA B 5 5.478 28.321 30.504 1.00 6.58 C
ATOM 796 C ALA B 5 5.495 27.369 29.324 1.00 6.58 C
ATOM 797 O ALA B 5 5.460 26.157 29.498 1.00 6.58 O
ATOM 798 CB ALA B 5 6.868 28.412 31.117 1.00 6.58 C
ATOM 799 N PRO B 6 5.528 27.904 28.096 1.00 2.75 N
ATOM 800 CA PRO B 6 5.548 27.021 26.929 1.00 2.75 C
ATOM 801 C PRO B 6 6.721 26.028 26.897 1.00 2.75 C
ATOM 802 O PRO B 6 6.604 24.962 26.301 1.00 6.58 O
ATOM 803 CB PRO B 6 5.572 28.007 25.761 1.00 2.75 C
ATOM 804 CG PRO B 6 4.764 29.155 26.286 1.00 2.75 C
ATOM 805 CD PRO B 6 5.282 29.306 27.698 1.00 2.75 C
ATOM 806 N HIS B 7 7.843 26.377 27.528 1.00 6.58 N
ATOM 807 CA HIS B 7 9.018 25.489 27.561 1.00 6.58 C
ATOM 808 C HIS B 7 9.853 25.669 28.834 1.00 6.58 C
ATOM 809 O HIS B 7 9.948 26.773 29.362 1.00 6.58 O
ATOM 810 CB HIS B 7 9.941 25.739 26.356 1.00 6.58 C
ATOM 811 CG HIS B 7 9.275 25.574 25.025 1.00 17.56 C
ATOM 812 ND1 HIS B 7 8.385 26.494 24.518 1.00 28.54 N
ATOM 813 CD2 HIS B 7 9.386 24.602 24.090 1.00 28.54 C
ATOM 814 CE1 HIS B 7 7.976 26.098 23.325 1.00 39.52 C
ATOM 815 NE2 HIS B 7 8.570 24.953 23.043 1.00 39.52 N
ATOM 816 N VAL B 8 10.467 24.582 29.307 1.00 6.58 N
ATOM 817 CA VAL B 8 11.310 24.610 30.508 1.00 6.58 C
ATOM 818 C VAL B 8 12.621 23.845 30.259 1.00 6.58 C
ATOM 819 O VAL B 8 12.716 23.083 29.294 1.00 6.58 O
ATOM 820 CB VAL B 8 10.581 23.984 31.730 1.00 6.58 C
ATOM 821 CG1 VAL B 8 9.362 24.840 32.107 1.00 17.56 C
ATOM 822 CG2 VAL B 8 10.150 22.560 31.418 1.00 17.56 C
ATOM 823 N TYR B 9 13.618 24.037 31.127 1.00 6.58 N
ATOM 824 CA TYR B 9 14.922 23.375 30.961 1.00 6.58 C
ATOM 825 C TYR B 9 15.644 23.034 32.271 1.00 6.58 C
ATOM 826 O TYR B 9 15.576 23.790 33.238 1.00 6.58 O
ATOM 827 CB TYR B 9 15.844 24.268 30.126 1.00 6.58 C
ATOM 828 CG TYR B 9 15.261 24.675 28.794 1.00 17.56 C
ATOM 829 CD1 TYR B 9 15.352 23.838 27.682 1.00 28.54 C
ATOM 830 CD2 TYR B 9 14.593 25.890 28.653 1.00 28.54 C
ATOM 831 CE1 TYR B 9 14.793 24.206 26.459 1.00 39.52 C
ATOM 832 CE2 TYR B 9 14.030 26.263 27.442 1.00 39.52 C
ATOM 833 CZ TYR B 9 14.132 25.422 26.349 1.00 50.50 C
ATOM 834 OH TYR B 9 13.580 25.807 25.149 1.00 61.48 O
ATOM 835 N THR B 10 16.355 21.902 32.294 1.00 6.58 N
ATOM 836 CA THR B 10 17.098 21.494 33.495 1.00 6.58 C
ATOM 837 C THR B 10 18.550 21.056 33.262 1.00 6.58 C
ATOM 838 O THR B 10 19.232 20.699 34.209 1.00 6.58 O
ATOM 839 CB THR B 10 16.390 20.338 34.252 1.00 6.58 C
ATOM 840 OG1 THR B 10 16.313 19.190 33.403 1.00 17.56 O
ATOM 841 CG2 THR B 10 14.983 20.751 34.673 1.00 17.56 C
ATOM 842 N GLU B 11 19.039 21.089 32.026 1.00 6.58 N
ATOM 843 CA GLU B 11 20.423 20.666 31.779 1.00 6.58 C
ATOM 844 C GLU B 11 21.426 21.753 32.164 1.00 6.58 C
ATOM 845 O GLU B 11 21.222 22.907 31.840 1.00 6.58 O
ATOM 846 CB GLU B 11 20.613 20.282 30.308 1.00 6.58 C
ATOM 847 CG GLU B 11 20.139 18.877 29.963 1.00 17.56 C
ATOM 848 CD GLU B 11 20.561 18.450 28.572 1.00 28.54 C
ATOM 849 OE1 GLU B 11 19.995 18.969 27.587 1.00 39.52 O
ATOM 850 OE2 GLU B 11 21.471 17.599 28.465 1.00 39.52 O
ATOM 851 N GLN B 12 22.508 21.381 32.850 1.00 6.58 N
ATOM 852 CA GLN B 12 23.524 22.352 33.278 1.00 6.58 C
ATOM 853 C GLN B 12 23.988 23.330 32.193 1.00 6.58 C
ATOM 854 O GLN B 12 24.135 24.528 32.459 1.00 6.58 O
ATOM 855 CB GLN B 12 24.746 21.622 33.853 1.00 6.58 C
ATOM 856 CG GLN B 12 24.447 20.816 35.106 1.00 17.56 C
ATOM 857 CD GLN B 12 23.857 21.674 36.206 1.00 28.54 C
ATOM 858 OE1 GLN B 12 24.459 22.661 36.626 1.00 39.52 O
ATOM 859 NE2 GLN B 12 22.673 21.303 36.678 1.00 39.52 N
ATOM 860 N ALA B 13 24.247 22.827 30.986 1.00 6.58 N
ATOM 861 CA ALA B 13 24.679 23.689 29.885 1.00 6.58 C
ATOM 862 C ALA B 13 23.573 24.695 29.606 1.00 6.58 C
ATOM 863 O ALA B 13 23.834 25.882 29.429 1.00 6.58 O
ATOM 864 CB ALA B 13 24.955 22.863 28.638 1.00 6.58 C
ATOM 865 N GLN B 14 22.334 24.211 29.574 1.00 6.58 N
ATOM 866 CA GLN B 14 21.193 25.087 29.337 1.00 6.58 C
ATOM 867 C GLN B 14 21.134 26.162 30.411 1.00 6.58 C
ATOM 868 O GLN B 14 20.944 27.333 30.108 1.00 6.58 O
ATOM 869 CB GLN B 14 19.892 24.292 29.344 1.00 6.58 C
ATOM 870 CG GLN B 14 19.866 23.151 28.342 1.00 17.56 C
ATOM 871 CD GLN B 14 18.547 22.409 28.349 1.00 28.54 C
ATOM 872 OE1 GLN B 14 18.052 22.005 29.404 1.00 39.52 O
ATOM 873 NE2 GLN B 14 17.970 22.220 27.167 1.00 39.52 N
ATOM 874 N ILE B 15 21.283 25.746 31.663 1.00 6.58 N
ATOM 875 CA ILE B 15 21.269 26.667 32.789 1.00 6.58 C
ATOM 876 C ILE B 15 22.388 27.697 32.595 1.00 6.58 C
ATOM 877 O ILE B 15 22.180 28.892 32.790 1.00 6.58 O
ATOM 878 CB ILE B 15 21.485 25.909 34.133 1.00 6.58 C
ATOM 879 CG1 ILE B 15 20.329 24.939 34.383 1.00 17.56 C
ATOM 880 CG2 ILE B 15 21.603 26.900 35.284 1.00 17.56 C
ATOM 881 CD1 ILE B 15 20.456 24.137 35.678 1.00 28.54 C
ATOM 882 N ALA B 16 23.566 27.215 32.198 1.00 6.58 N
ATOM 883 CA ALA B 16 24.737 28.060 31.963 1.00 6.58 C
ATOM 884 C ALA B 16 24.404 29.206 31.017 1.00 6.58 C
ATOM 885 O ALA B 16 24.794 30.346 31.249 1.00 6.58 O
ATOM 886 CB ALA B 16 25.884 27.216 31.380 1.00 6.58 C
ATOM 887 N THR B 17 23.681 28.877 29.952 1.00 6.58 N
ATOM 888 CA THR B 17 23.259 29.839 28.937 1.00 6.58 C
ATOM 889 C THR B 17 22.311 30.896 29.510 1.00 6.58 C
ATOM 890 O THR B 17 22.491 32.099 29.286 1.00 6.58 O
ATOM 891 CB THR B 17 22.524 29.121 27.768 1.00 6.58 C
ATOM 892 OG1 THR B 17 23.424 28.224 27.102 1.00 17.56 O
ATOM 893 CG2 THR B 17 21.978 30.139 26.761 1.00 17.56 C
ATOM 894 N LEU B 18 21.305 30.442 30.251 1.00 6.58 N
ATOM 895 CA LEU B 18 20.319 31.349 30.835 1.00 6.58 C
ATOM 896 C LEU B 18 20.939 32.313 31.834 1.00 6.58 C
ATOM 897 O LEU B 18 20.583 33.486 31.885 1.00 6.58 O
ATOM 898 CB LEU B 18 19.186 30.553 31.502 1.00 6.58 C
ATOM 899 CG LEU B 18 18.293 29.728 30.570 1.00 17.56 C
ATOM 900 CD1 LEU B 18 17.182 29.084 31.380 1.00 28.54 C
ATOM 901 CD2 LEU B 18 17.703 30.610 29.485 1.00 28.54 C
ATOM 902 N GLU B 19 21.877 31.812 32.628 1.00 6.58 N
ATOM 903 CA GLU B 19 22.548 32.626 33.623 1.00 6.58 C
ATOM 904 C GLU B 19 23.476 33.635 32.955 1.00 6.58 C
ATOM 905 O GLU B 19 23.745 34.693 33.513 1.00 6.58 O
ATOM 906 CB GLU B 19 23.368 31.741 34.566 1.00 6.58 C
ATOM 907 CG GLU B 19 22.568 30.706 35.350 1.00 17.56 C
ATOM 908 CD GLU B 19 23.462 29.774 36.161 1.00 28.54 C
ATOM 909 OE1 GLU B 19 22.925 28.956 36.939 1.00 39.52 O
ATOM 910 OE2 GLU B 19 24.701 29.853 36.016 1.00 39.52 O
ATOM 911 N HIS B 20 23.990 33.302 31.774 1.00 6.58 N
ATOM 912 CA HIS B 20 24.890 34.224 31.098 1.00 6.58 C
ATOM 913 C HIS B 20 24.075 35.346 30.478 1.00 6.58 C
ATOM 914 O HIS B 20 24.542 36.483 30.370 1.00 6.58 O
ATOM 915 CB HIS B 20 25.712 33.501 30.031 1.00 6.58 C
ATOM 916 CG HIS B 20 26.754 34.364 29.389 1.00 17.56 C
ATOM 917 ND1 HIS B 20 27.742 34.997 30.111 1.00 28.54 N
ATOM 918 CD2 HIS B 20 26.958 34.704 28.094 1.00 28.54 C
ATOM 919 CE1 HIS B 20 28.509 35.691 29.289 1.00 39.52 C
ATOM 920 NE2 HIS B 20 28.055 35.529 28.059 1.00 39.52 N
ATOM 921 N TRP B 21 22.843 35.022 30.098 1.00 6.58 N
ATOM 922 CA TRP B 21 21.941 35.996 29.503 1.00 6.58 C
ATOM 923 C TRP B 21 21.543 37.024 30.552 1.00 6.58 C
ATOM 924 O TRP B 21 21.513 38.216 30.275 1.00 6.58 O
ATOM 925 CB TRP B 21 20.693 35.304 28.948 1.00 6.58 C
ATOM 926 CG TRP B 21 20.884 34.669 27.611 1.00 17.56 C
ATOM 927 CD1 TRP B 21 20.154 33.646 27.081 1.00 28.54 C
ATOM 928 CD2 TRP B 21 21.840 35.042 26.610 1.00 28.54 C
ATOM 929 NE1 TRP B 21 20.595 33.357 25.812 1.00 39.52 N
ATOM 930 CE2 TRP B 21 21.630 34.199 25.499 1.00 39.52 C
ATOM 931 CE3 TRP B 21 22.856 36.008 26.543 1.00 39.52 C
ATOM 932 CZ2 TRP B 21 22.397 34.291 24.332 1.00 50.50 C
ATOM 933 CZ3 TRP B 21 23.618 36.101 25.385 1.00 50.50 C
ATOM 934 CH2 TRP B 21 23.384 35.246 24.295 1.00 61.48 C
ATOM 935 N VAL B 22 21.251 36.548 31.757 1.00 6.58 N
ATOM 936 CA VAL B 22 20.871 37.423 32.856 1.00 6.58 C
ATOM 937 C VAL B 22 22.016 38.368 33.205 1.00 6.58 C
ATOM 938 O VAL B 22 21.794 39.456 33.740 1.00 6.58 O
ATOM 939 CB VAL B 22 20.504 36.615 34.124 1.00 6.58 C
ATOM 940 CG1 VAL B 22 20.199 37.565 35.280 1.00 17.56 C
ATOM 941 CG2 VAL B 22 19.299 35.720 33.844 1.00 17.56 C
ATOM 942 N LYS B 23 23.242 37.952 32.906 1.00 6.58 N
ATOM 943 CA LYS B 23 24.402 38.779 33.203 1.00 6.58 C
ATOM 944 C LYS B 23 24.563 39.904 32.180 1.00 6.58 C
ATOM 945 O LYS B 23 24.783 41.057 32.559 1.00 6.58 O
ATOM 946 CB LYS B 23 25.666 37.916 33.243 1.00 6.58 C
ATOM 947 CG LYS B 23 26.913 38.650 33.735 1.00 17.56 C
ATOM 948 CD LYS B 23 28.070 37.687 33.976 1.00 28.54 C
ATOM 949 CE LYS B 23 27.716 36.664 35.046 1.00 39.52 C
ATOM 950 NZ LYS B 23 28.860 35.776 35.385 1.00 50.50 N
ATOM 951 N LEU B 24 24.459 39.581 30.891 1.00 6.58 N
ATOM 952 CA LEU B 24 24.602 40.605 29.851 1.00 6.58 C
ATOM 953 C LEU B 24 23.462 41.614 29.935 1.00 6.58 C
ATOM 954 O LEU B 24 23.687 42.828 29.971 1.00 6.58 O
ATOM 955 CB LEU B 24 24.625 39.982 28.448 1.00 6.58 C
ATOM 956 CG LEU B 24 25.777 39.047 28.088 1.00 17.56 C
ATOM 957 CD1 LEU B 24 25.708 38.726 26.608 1.00 28.54 C
ATOM 958 CD2 LEU B 24 27.115 39.699 28.432 1.00 28.54 C
ATOM 959 N LEU B 25 22.236 41.106 29.957 1.00 6.58 N
ATOM 960 CA LEU B 25 21.062 41.958 30.056 1.00 6.58 C
ATOM 961 C LEU B 25 20.922 42.398 31.516 1.00 6.58 C
ATOM 962 O LEU B 25 19.808 42.493 32.037 1.00 6.58 O
ATOM 963 CB LEU B 25 19.817 41.177 29.644 1.00 6.58 C
ATOM 964 CG LEU B 25 19.863 40.486 28.281 1.00 17.56 C
ATOM 965 CD1 LEU B 25 18.618 39.629 28.125 1.00 28.54 C
ATOM 966 CD2 LEU B 25 19.953 41.517 27.166 1.00 28.54 C
ATOM 967 N ASP B 26 22.061 42.649 32.158 1.00 2.75 N
ATOM 968 CA ASP B 26 22.128 43.057 33.566 1.00 2.75 C
ATOM 969 C ASP B 26 22.523 44.514 33.726 1.00 2.75 C
ATOM 970 O ASP B 26 22.004 45.215 34.611 1.00 2.75 O
ATOM 971 CB ASP B 26 23.130 42.171 34.326 1.00 2.75 C
ATOM 972 CG ASP B 26 23.997 42.956 35.308 1.00 2.75 C
ATOM 973 OD1 ASP B 26 23.455 43.524 36.279 1.00 2.75 O
ATOM 974 OD2 ASP B 26 25.233 43.011 35.107 1.00 2.75 O
ATOM 975 N GLY B 27 23.455 44.965 32.890 1.00 2.75 N
ATOM 976 CA GLY B 27 23.875 46.348 32.949 1.00 2.75 C
ATOM 977 C GLY B 27 22.767 47.212 32.378 1.00 2.75 C
ATOM 978 O GLY B 27 22.985 48.369 32.029 1.00 2.75 O
ATOM 979 N GLN B 28 21.574 46.631 32.285 1.00 2.75 N
ATOM 980 CA GLN B 28 20.410 47.326 31.758 1.00 2.75 C
ATOM 981 C GLN B 28 20.784 48.327 30.672 1.00 2.75 C
ATOM 982 O GLN B 28 20.196 49.406 30.577 1.00 2.75 O
ATOM 983 CB GLN B 28 19.680 48.034 32.902 1.00 2.75 C
ATOM 984 CG GLN B 28 18.260 48.531 32.581 1.00 2.75 C
ATOM 985 CD GLN B 28 18.223 49.944 32.023 1.00 2.75 C
ATOM 986 OE1 GLN B 28 18.831 50.868 32.583 1.00 2.75 O
ATOM 987 NE2 GLN B 28 17.501 50.127 30.928 1.00 2.75 N
ATOM 988 N GLU B 29 21.761 47.984 29.842 1.00 2.75 N
ATOM 989 CA GLU B 29 22.166 48.909 28.788 1.00 2.75 C
ATOM 990 C GLU B 29 21.594 48.521 27.414 1.00 2.75 C
ATOM 991 O GLU B 29 21.555 47.337 27.064 1.00 2.75 O
ATOM 992 CB GLU B 29 23.691 49.009 28.766 1.00 2.75 C
ATOM 993 CG GLU B 29 24.269 49.642 27.536 1.00 2.75 C
ATOM 994 CD GLU B 29 24.648 48.604 26.511 1.00 2.75 C
ATOM 995 OE1 GLU B 29 23.812 47.700 26.271 1.00 2.75 O
ATOM 996 OE2 GLU B 29 25.777 48.678 25.957 1.00 2.75 O
ATOM 997 N ARG B 30 21.163 49.513 26.636 1.00 2.75 N
ATOM 998 CA ARG B 30 20.545 49.258 25.326 1.00 2.75 C
ATOM 999 C ARG B 30 21.165 48.103 24.565 1.00 2.75 C
ATOM 1000 O ARG B 30 22.384 48.014 24.437 1.00 2.75 O
ATOM 1001 CB ARG B 30 20.562 50.517 24.453 1.00 2.75 C
ATOM 1002 CG ARG B 30 21.842 51.315 24.545 1.00 2.75 C
ATOM 1003 CD ARG B 30 21.629 52.494 25.479 1.00 2.75 C
ATOM 1004 NE ARG B 30 20.661 53.440 24.919 1.00 2.75 N
ATOM 1005 CZ ARG B 30 20.173 54.494 25.566 1.00 2.75 C
ATOM 1006 NH1 ARG B 30 20.561 54.749 26.808 1.00 2.75 N
ATOM 1007 NH2 ARG B 30 19.287 55.285 24.969 1.00 2.75 N
ATOM 1008 N VAL B 31 20.303 47.225 24.051 1.00 6.58 N
ATOM 1009 CA VAL B 31 20.750 46.036 23.338 1.00 6.58 C
ATOM 1010 C VAL B 31 19.934 45.674 22.111 1.00 6.58 C
ATOM 1011 O VAL B 31 18.881 46.262 21.837 1.00 6.58 O
ATOM 1012 CB VAL B 31 20.740 44.801 24.268 1.00 6.58 C
ATOM 1013 CG1 VAL B 31 21.809 44.938 25.344 1.00 17.56 C
ATOM 1014 CG2 VAL B 31 19.362 44.636 24.882 1.00 17.56 C
ATOM 1015 N ARG B 32 20.442 44.675 21.392 1.00 6.58 N
ATOM 1016 CA ARG B 32 19.821 44.154 20.183 1.00 6.58 C
ATOM 1017 C ARG B 32 19.753 42.629 20.299 1.00 6.58 C
ATOM 1018 O ARG B 32 20.716 41.928 19.969 1.00 6.58 O
ATOM 1019 CB ARG B 32 20.656 44.547 18.961 1.00 6.58 C
ATOM 1020 CG ARG B 32 20.011 44.208 17.628 1.00 17.56 C
ATOM 1021 CD ARG B 32 20.841 44.748 16.476 1.00 28.54 C
ATOM 1022 NE ARG B 32 20.180 44.577 15.186 1.00 39.52 N
ATOM 1023 CZ ARG B 32 20.662 45.039 14.035 1.00 50.50 C
ATOM 1024 NH1 ARG B 32 21.812 45.703 14.014 1.00 61.48 N
ATOM 1025 NH2 ARG B 32 19.995 44.840 12.907 1.00 61.48 N
ATOM 1026 N ILE B 33 18.613 42.123 20.759 1.00 6.58 N
ATOM 1027 CA ILE B 33 18.420 40.687 20.943 1.00 6.58 C
ATOM 1028 C ILE B 33 17.983 39.923 19.687 1.00 6.58 C
ATOM 1029 O ILE B 33 17.061 40.330 18.981 1.00 6.58 O
ATOM 1030 CB ILE B 33 17.378 40.434 22.077 1.00 6.58 C
ATOM 1031 CG1 ILE B 33 17.822 41.155 23.357 1.00 17.56 C
ATOM 1032 CG2 ILE B 33 17.207 38.933 22.321 1.00 17.56 C
ATOM 1033 CD1 ILE B 33 16.846 41.042 24.509 1.00 28.54 C
ATOM 1034 N GLU B 34 18.652 38.804 19.417 1.00 6.58 N
ATOM 1035 CA GLU B 34 18.310 37.968 18.271 1.00 6.58 C
ATOM 1036 C GLU B 34 17.743 36.653 18.811 1.00 6.58 C
ATOM 1037 O GLU B 34 18.360 36.031 19.684 1.00 6.58 O
ATOM 1038 CB GLU B 34 19.553 37.678 17.423 1.00 6.58 C
ATOM 1039 CG GLU B 34 19.238 36.976 16.098 1.00 17.56 C
ATOM 1040 CD GLU B 34 20.474 36.485 15.355 1.00 28.54 C
ATOM 1041 OE1 GLU B 34 20.320 36.008 14.211 1.00 39.52 O
ATOM 1042 OE2 GLU B 34 21.592 36.567 15.909 1.00 39.52 O
ATOM 1043 N LEU B 35 16.589 36.230 18.293 1.00 6.58 N
ATOM 1044 CA LEU B 35 15.945 34.997 18.744 1.00 6.58 C
ATOM 1045 C LEU B 35 16.135 33.829 17.783 1.00 6.58 C
ATOM 1046 O LEU B 35 16.818 33.957 16.762 1.00 6.58 O
ATOM 1047 CB LEU B 35 14.447 35.223 18.965 1.00 6.58 C
ATOM 1048 CG LEU B 35 14.019 36.470 19.741 1.00 17.56 C
ATOM 1049 CD1 LEU B 35 12.520 36.400 20.012 1.00 28.54 C
ATOM 1050 CD2 LEU B 35 14.790 36.573 21.048 1.00 28.54 C
ATOM 1051 N ASP B 36 15.506 32.700 18.119 1.00 6.58 N
ATOM 1052 CA ASP B 36 15.601 31.481 17.320 1.00 6.58 C
ATOM 1053 C ASP B 36 15.067 31.569 15.900 1.00 6.58 C
ATOM 1054 O ASP B 36 15.740 31.126 14.965 1.00 6.58 O
ATOM 1055 CB ASP B 36 14.925 30.308 18.042 1.00 6.58 C
ATOM 1056 CG ASP B 36 13.460 30.562 18.330 1.00 17.56 C
ATOM 1057 OD1 ASP B 36 13.161 31.389 19.216 1.00 28.54 O
ATOM 1058 OD2 ASP B 36 12.605 29.938 17.663 1.00 28.54 O
ATOM 1059 N ASP B 37 13.871 32.130 15.722 1.00 6.58 N
ATOM 1060 CA ASP B 37 13.284 32.234 14.385 1.00 6.58 C
ATOM 1061 C ASP B 37 13.967 33.262 13.477 1.00 6.58 C
ATOM 1062 O ASP B 37 13.640 33.360 12.294 1.00 6.58 O
ATOM 1063 CB ASP B 37 11.782 32.538 14.484 1.00 6.58 C
ATOM 1064 CG ASP B 37 11.483 33.725 15.380 1.00 17.56 C
ATOM 1065 OD1 ASP B 37 12.436 34.426 15.778 1.00 28.54 O
ATOM 1066 OD2 ASP B 37 10.291 33.957 15.679 1.00 28.54 O
ATOM 1067 N GLY B 38 14.926 34.006 14.021 1.00 6.58 N
ATOM 1068 CA GLY B 38 15.634 35.009 13.241 1.00 6.58 C
ATOM 1069 C GLY B 38 15.147 36.411 13.556 1.00 6.58 C
ATOM 1070 O GLY B 38 15.657 37.410 13.024 1.00 6.58 O
ATOM 1071 N SER B 39 14.150 36.488 14.428 1.00 6.58 N
ATOM 1072 CA SER B 39 13.596 37.774 14.816 1.00 6.58 C
ATOM 1073 C SER B 39 14.714 38.598 15.441 1.00 6.58 C
ATOM 1074 O SER B 39 15.689 38.061 15.974 1.00 6.58 O
ATOM 1075 CB SER B 39 12.472 37.598 15.833 1.00 6.58 C
ATOM 1076 OG SER B 39 12.970 37.747 17.150 1.00 17.56 O
ATOM 1077 N MET B 40 14.573 39.911 15.345 1.00 6.58 N
ATOM 1078 CA MET B 40 15.534 40.834 15.909 1.00 6.58 C
ATOM 1079 C MET B 40 14.738 41.846 16.716 1.00 6.58 C
ATOM 1080 O MET B 40 13.819 42.488 16.198 1.00 6.58 O
ATOM 1081 CB MET B 40 16.326 41.533 14.797 1.00 6.58 C
ATOM 1082 CG MET B 40 17.305 40.629 14.058 1.00 17.56 C
ATOM 1083 SD MET B 40 18.636 40.080 15.132 1.00 28.54 S
ATOM 1084 CE MET B 40 19.536 41.606 15.341 1.00 39.52 C
ATOM 1085 N ILE B 41 15.084 41.964 17.992 1.00 6.58 N
ATOM 1086 CA ILE B 41 14.417 42.882 18.900 1.00 6.58 C
ATOM 1087 C ILE B 41 15.434 43.823 19.548 1.00 6.58 C
ATOM 1088 O ILE B 41 16.316 43.389 20.284 1.00 6.58 O
ATOM 1089 CB ILE B 41 13.639 42.094 19.998 1.00 6.58 C
ATOM 1090 CG1 ILE B 41 13.134 43.042 21.090 1.00 17.56 C
ATOM 1091 CG2 ILE B 41 14.544 41.037 20.613 1.00 17.56 C
ATOM 1092 CD1 ILE B 41 12.281 44.171 20.593 1.00 28.54 C
ATOM 1093 N ALA B 42 15.311 45.112 19.252 1.00 6.58 N
ATOM 1094 CA ALA B 42 16.207 46.120 19.807 1.00 6.58 C
ATOM 1095 C ALA B 42 15.459 47.068 20.737 1.00 6.58 C
ATOM 1096 O ALA B 42 14.265 47.344 20.548 1.00 6.58 O
ATOM 1097 CB ALA B 42 16.865 46.914 18.685 1.00 6.58 C
ATOM 1098 N GLY B 43 16.167 47.565 21.746 1.00 6.58 N
ATOM 1099 CA GLY B 43 15.549 48.488 22.675 1.00 6.58 C
ATOM 1100 C GLY B 43 16.218 48.543 24.033 1.00 6.58 C
ATOM 1101 O GLY B 43 17.363 48.129 24.202 1.00 6.58 O
ATOM 1102 N THR B 44 15.480 49.052 25.012 1.00 2.75 N
ATOM 1103 CA THR B 44 15.964 49.183 26.374 1.00 2.75 C
ATOM 1104 C THR B 44 15.438 48.065 27.287 1.00 2.75 C
ATOM 1105 O THR B 44 14.273 47.690 27.215 1.00 2.75 O
ATOM 1106 CB THR B 44 15.527 50.540 26.959 1.00 2.75 C
ATOM 1107 OG1 THR B 44 15.744 51.569 25.980 1.00 2.75 O
ATOM 1108 CG2 THR B 44 16.311 50.856 28.204 1.00 2.75 C
ATOM 1109 N VAL B 45 16.304 47.533 28.139 1.00 2.75 N
ATOM 1110 CA VAL B 45 15.899 46.486 29.078 1.00 2.75 C
ATOM 1111 C VAL B 45 15.065 47.194 30.146 1.00 2.75 C
ATOM 1112 O VAL B 45 15.599 47.887 31.006 1.00 2.75 O
ATOM 1113 CB VAL B 45 17.121 45.814 29.737 1.00 2.75 C
ATOM 1114 CG1 VAL B 45 16.660 44.796 30.779 1.00 2.75 C
ATOM 1115 CG2 VAL B 45 17.980 45.121 28.662 1.00 2.75 C
ATOM 1116 N ALA B 46 13.751 47.016 30.086 1.00 2.75 N
ATOM 1117 CA ALA B 46 12.836 47.691 31.010 1.00 2.75 C
ATOM 1118 C ALA B 46 12.469 46.896 32.258 1.00 2.75 C
ATOM 1119 O ALA B 46 12.144 47.460 33.299 1.00 2.75 O
ATOM 1120 CB ALA B 46 11.569 48.114 30.250 1.00 2.75 C
ATOM 1121 N VAL B 47 12.488 45.581 32.134 1.00 2.75 N
ATOM 1122 CA VAL B 47 12.211 44.693 33.255 1.00 2.75 C
ATOM 1123 C VAL B 47 13.268 43.629 33.047 1.00 2.75 C
ATOM 1124 O VAL B 47 13.247 42.935 32.034 1.00 2.75 O
ATOM 1125 CB VAL B 47 10.785 44.079 33.182 1.00 2.75 C
ATOM 1126 CG1 VAL B 47 10.574 43.106 34.320 1.00 2.75 C
ATOM 1127 CG2 VAL B 47 9.738 45.186 33.231 1.00 2.75 C
ATOM 1128 N ARG B 48 14.206 43.531 33.986 1.00 6.58 N
ATOM 1129 CA ARG B 48 15.313 42.584 33.895 1.00 6.58 C
ATOM 1130 C ARG B 48 14.898 41.137 33.998 1.00 6.58 C
ATOM 1131 O ARG B 48 13.934 40.802 34.690 1.00 6.58 O
ATOM 1132 CB ARG B 48 16.352 42.885 34.981 1.00 6.58 C
ATOM 1133 CG ARG B 48 17.321 43.997 34.611 1.00 17.56 C
ATOM 1134 CD ARG B 48 18.158 44.434 35.802 1.00 28.54 C
ATOM 1135 NE ARG B 48 17.319 44.918 36.894 1.00 39.52 N
ATOM 1136 CZ ARG B 48 17.754 45.670 37.899 1.00 50.50 C
ATOM 1137 NH1 ARG B 48 19.028 46.032 37.954 1.00 61.48 N
ATOM 1138 NH2 ARG B 48 16.915 46.058 38.850 1.00 61.48 N
ATOM 1139 N PRO B 49 15.629 40.246 33.310 1.00 6.58 N
ATOM 1140 CA PRO B 49 15.308 38.820 33.354 1.00 6.58 C
ATOM 1141 C PRO B 49 15.716 38.196 34.688 1.00 6.58 C
ATOM 1142 O PRO B 49 16.727 38.579 35.291 1.00 6.58 O
ATOM 1143 CB PRO B 49 16.112 38.258 32.182 1.00 6.58 C
ATOM 1144 CG PRO B 49 17.333 39.095 32.209 1.00 17.56 C
ATOM 1145 CD PRO B 49 16.780 40.492 32.422 1.00 28.54 C
ATOM 1146 N THR B 50 14.911 37.257 35.162 1.00 6.58 N
ATOM 1147 CA THR B 50 15.210 36.561 36.404 1.00 6.58 C
ATOM 1148 C THR B 50 14.796 35.130 36.158 1.00 6.58 C
ATOM 1149 O THR B 50 13.668 34.890 35.742 1.00 6.58 O
ATOM 1150 CB THR B 50 14.381 37.078 37.593 1.00 6.58 C
ATOM 1151 OG1 THR B 50 13.011 36.700 37.421 1.00 17.56 O
ATOM 1152 CG2 THR B 50 14.482 38.594 37.702 1.00 17.56 C
ATOM 1153 N ILE B 51 15.684 34.182 36.420 1.00 6.58 N
ATOM 1154 CA ILE B 51 15.337 32.787 36.193 1.00 6.58 C
ATOM 1155 C ILE B 51 14.367 32.328 37.277 1.00 6.58 C
ATOM 1156 O ILE B 51 14.527 32.676 38.444 1.00 6.58 O
ATOM 1157 CB ILE B 51 16.589 31.890 36.205 1.00 6.58 C
ATOM 1158 CG1 ILE B 51 17.621 32.421 35.202 1.00 17.56 C
ATOM 1159 CG2 ILE B 51 16.202 30.461 35.827 1.00 17.56 C
ATOM 1160 CD1 ILE B 51 18.923 31.646 35.177 1.00 28.54 C
ATOM 1161 N GLN B 52 13.348 31.568 36.887 1.00 6.58 N
ATOM 1162 CA GLN B 52 12.362 31.068 37.846 1.00 6.58 C
ATOM 1163 C GLN B 52 11.901 29.652 37.506 1.00 6.58 C
ATOM 1164 O GLN B 52 12.246 29.116 36.447 1.00 6.58 O
ATOM 1165 CB GLN B 52 11.158 32.014 37.892 1.00 6.58 C
ATOM 1166 CG GLN B 52 11.441 33.352 38.566 1.00 17.56 C
ATOM 1167 CD GLN B 52 10.191 34.211 38.710 1.00 28.54 C
ATOM 1168 OE1 GLN B 52 9.204 33.791 39.311 1.00 39.52 O
ATOM 1169 NE2 GLN B 52 10.232 35.417 38.160 1.00 39.52 N
ATOM 1170 N THR B 53 11.139 29.030 38.406 1.00 6.58 N
ATOM 1171 CA THR B 53 10.641 27.678 38.151 1.00 6.58 C
ATOM 1172 C THR B 53 9.254 27.726 37.503 1.00 6.58 C
ATOM 1173 O THR B 53 8.380 28.492 37.920 1.00 6.58 O
ATOM 1174 CB THR B 53 10.576 26.845 39.446 1.00 6.58 C
ATOM 1175 OG1 THR B 53 9.712 27.490 40.388 1.00 17.56 O
ATOM 1176 CG2 THR B 53 11.971 26.702 40.060 1.00 17.56 C
ATOM 1177 N TYR B 54 9.075 26.909 36.468 1.00 6.58 N
ATOM 1178 CA TYR B 54 7.825 26.837 35.710 1.00 6.58 C
ATOM 1179 C TYR B 54 7.459 25.387 35.405 1.00 6.58 C
ATOM 1180 O TYR B 54 8.239 24.471 35.642 1.00 6.58 O
ATOM 1181 CB TYR B 54 7.959 27.579 34.381 1.00 6.58 C
ATOM 1182 CG TYR B 54 8.169 29.069 34.500 1.00 17.56 C
ATOM 1183 CD1 TYR B 54 7.105 29.924 34.784 1.00 28.54 C
ATOM 1184 CD2 TYR B 54 9.433 29.627 34.308 1.00 28.54 C
ATOM 1185 CE1 TYR B 54 7.295 31.301 34.868 1.00 39.52 C
ATOM 1186 CE2 TYR B 54 9.634 30.999 34.391 1.00 39.52 C
ATOM 1187 CZ TYR B 54 8.562 31.831 34.670 1.00 50.50 C
ATOM 1188 OH TYR B 54 8.760 33.190 34.745 1.00 61.48 O
ATOM 1189 N ARG B 55 6.262 25.203 34.866 1.00 2.75 N
ATOM 1190 CA ARG B 55 5.745 23.892 34.501 1.00 2.75 C
ATOM 1191 C ARG B 55 5.178 24.061 33.090 1.00 2.75 C
ATOM 1192 O ARG B 55 4.663 25.129 32.768 1.00 2.75 O
ATOM 1193 CB ARG B 55 4.618 23.490 35.464 1.00 2.75 C
ATOM 1194 CG ARG B 55 5.036 23.429 36.939 1.00 2.75 C
ATOM 1195 CD ARG B 55 3.858 23.448 37.904 1.00 2.75 C
ATOM 1196 NE ARG B 55 2.904 22.370 37.654 1.00 2.75 N
ATOM 1197 CZ ARG B 55 2.071 21.887 38.570 1.00 2.75 C
ATOM 1198 NH1 ARG B 55 2.066 22.374 39.810 1.00 2.75 N
ATOM 1199 NH2 ARG B 55 1.238 20.909 38.247 1.00 2.75 N
ATOM 1200 N ASP B 56 5.260 23.022 32.258 1.00 2.75 N
ATOM 1201 CA ASP B 56 4.725 23.121 30.899 1.00 2.75 C
ATOM 1202 C ASP B 56 3.407 22.354 30.799 1.00 2.75 C
ATOM 1203 O ASP B 56 2.945 21.798 31.786 1.00 2.75 O
ATOM 1204 CB ASP B 56 5.752 22.625 29.861 1.00 2.75 C
ATOM 1205 CG ASP B 56 6.180 21.175 30.076 1.00 2.75 C
ATOM 1206 OD1 ASP B 56 5.549 20.471 30.888 1.00 2.75 O
ATOM 1207 OD2 ASP B 56 7.152 20.744 29.423 1.00 2.75 O
ATOM 1208 N GLU B 57 2.794 22.339 29.620 1.00 2.75 N
ATOM 1209 CA GLU B 57 1.517 21.655 29.439 1.00 2.75 C
ATOM 1210 C GLU B 57 1.593 20.165 29.728 1.00 2.75 C
ATOM 1211 O GLU B 57 0.579 19.527 30.011 1.00 2.75 O
ATOM 1212 CB GLU B 57 0.991 21.846 28.015 1.00 2.75 C
ATOM 1213 CG GLU B 57 -0.419 21.291 27.860 1.00 2.75 C
ATOM 1214 CD GLU B 57 -0.875 21.205 26.428 1.00 2.75 C
ATOM 1215 OE1 GLU B 57 -0.048 20.835 25.565 1.00 2.75 O
ATOM 1216 OE2 GLU B 57 -2.068 21.484 26.176 1.00 2.75 O
ATOM 1217 N GLN B 58 2.794 19.610 29.629 1.00 2.75 N
ATOM 1218 CA GLN B 58 2.990 18.197 29.887 1.00 2.75 C
ATOM 1219 C GLN B 58 3.354 18.035 31.366 1.00 2.75 C
ATOM 1220 O GLN B 58 3.759 16.956 31.819 1.00 2.75 O
ATOM 1221 CB GLN B 58 4.098 17.648 28.987 1.00 2.75 C
ATOM 1222 CG GLN B 58 3.982 18.057 27.494 1.00 2.75 C
ATOM 1223 CD GLN B 58 2.608 17.776 26.882 1.00 2.75 C
ATOM 1224 OE1 GLN B 58 1.621 18.407 27.241 1.00 2.75 O
ATOM 1225 NE2 GLN B 58 2.548 16.819 25.957 1.00 2.75 N
ATOM 1226 N GLU B 59 3.208 19.124 32.115 1.00 2.75 N
ATOM 1227 CA GLU B 59 3.485 19.130 33.552 1.00 2.75 C
ATOM 1228 C GLU B 59 4.927 18.894 33.999 1.00 2.75 C
ATOM 1229 O GLU B 59 5.165 18.511 35.153 1.00 2.75 O
ATOM 1230 CB GLU B 59 2.575 18.123 34.244 1.00 2.75 C
ATOM 1231 CG GLU B 59 1.112 18.451 34.092 1.00 2.75 C
ATOM 1232 CD GLU B 59 0.527 19.000 35.368 1.00 2.75 C
ATOM 1233 OE1 GLU B 59 1.058 19.997 35.904 1.00 2.75 O
ATOM 1234 OE2 GLU B 59 -0.468 18.425 35.839 1.00 2.75 O
ATOM 1235 N ARG B 60 5.881 19.107 33.091 1.00 2.75 N
ATOM 1236 CA ARG B 60 7.303 18.953 33.401 1.00 2.75 C
ATOM 1237 C ARG B 60 7.743 20.231 34.113 1.00 2.75 C
ATOM 1238 O ARG B 60 7.262 21.317 33.783 1.00 2.75 O
ATOM 1239 CB ARG B 60 8.131 18.787 32.124 1.00 2.75 C
ATOM 1240 CG ARG B 60 8.299 17.370 31.617 1.00 2.75 C
ATOM 1241 CD ARG B 60 9.172 17.363 30.362 1.00 2.75 C
ATOM 1242 NE ARG B 60 9.520 16.018 29.899 1.00 2.75 N
ATOM 1243 CZ ARG B 60 10.584 15.327 30.305 1.00 2.75 C
ATOM 1244 NH1 ARG B 60 11.434 15.845 31.186 1.00 2.75 N
ATOM 1245 NH2 ARG B 60 10.785 14.105 29.843 1.00 2.75 N
ATOM 1246 N GLU B 61 8.643 20.095 35.086 1.00 2.75 N
ATOM 1247 CA GLU B 61 9.144 21.249 35.838 1.00 2.75 C
ATOM 1248 C GLU B 61 10.583 21.614 35.437 1.00 2.75 C
ATOM 1249 O GLU B 61 11.456 20.744 35.328 1.00 2.75 O
ATOM 1250 CB GLU B 61 9.073 20.972 37.342 1.00 2.75 C
ATOM 1251 CG GLU B 61 9.641 22.100 38.212 1.00 2.75 C
ATOM 1252 CD GLU B 61 9.414 21.892 39.716 1.00 2.75 C
ATOM 1253 OE1 GLU B 61 8.395 22.396 40.264 1.00 2.75 O
ATOM 1254 OE2 GLU B 61 10.258 21.218 40.350 1.00 2.75 O
ATOM 1255 N GLY B 62 10.820 22.903 35.205 1.00 2.75 N
ATOM 1256 CA GLY B 62 12.149 23.344 34.805 1.00 2.75 C
ATOM 1257 C GLY B 62 12.364 24.845 34.933 1.00 2.75 C
ATOM 1258 O GLY B 62 11.504 25.558 35.442 1.00 2.75 O
ATOM 1259 N SER B 63 13.521 25.319 34.473 1.00 2.75 N
ATOM 1260 CA SER B 63 13.880 26.737 34.536 1.00 2.75 C
ATOM 1261 C SER B 63 13.639 27.483 33.217 1.00 2.75 C
ATOM 1262 O SER B 63 13.699 26.903 32.127 1.00 2.75 O
ATOM 1263 CB SER B 63 15.359 26.890 34.904 1.00 2.75 C
ATOM 1264 OG SER B 63 15.691 26.241 36.121 1.00 2.75 O
ATOM 1265 N ASN B 64 13.398 28.786 33.340 1.00 2.75 N
ATOM 1266 CA ASN B 64 13.164 29.670 32.203 1.00 2.75 C
ATOM 1267 C ASN B 64 13.040 31.065 32.809 1.00 2.75 C
ATOM 1268 O ASN B 64 13.274 31.258 34.007 1.00 2.75 O
ATOM 1269 CB ASN B 64 11.854 29.304 31.498 1.00 2.75 C
ATOM 1270 CG ASN B 64 11.842 29.708 30.050 1.00 2.75 C
ATOM 1271 OD1 ASN B 64 12.538 30.639 29.640 1.00 2.75 O
ATOM 1272 ND2 ASN B 64 11.033 29.014 29.252 1.00 2.75 N
ATOM 1273 N GLY B 65 12.676 32.045 31.996 1.00 2.75 N
ATOM 1274 CA GLY B 65 12.514 33.388 32.516 1.00 2.75 C
ATOM 1275 C GLY B 65 12.014 34.352 31.456 1.00 2.75 C
ATOM 1276 O GLY B 65 12.081 34.062 30.269 1.00 2.75 O
ATOM 1277 N GLN B 66 11.521 35.506 31.885 1.00 2.75 N
ATOM 1278 CA GLN B 66 11.004 36.507 30.958 1.00 2.75 C
ATOM 1279 C GLN B 66 11.604 37.879 31.268 1.00 2.75 C
ATOM 1280 O GLN B 66 11.946 38.169 32.416 1.00 6.58 O
ATOM 1281 CB GLN B 66 9.471 36.589 31.082 1.00 2.75 C
ATOM 1282 CG GLN B 66 8.771 35.236 31.210 1.00 2.75 C
ATOM 1283 CD GLN B 66 7.275 35.331 31.557 1.00 2.75 C
ATOM 1284 OE1 GLN B 66 6.449 35.774 30.752 1.00 2.75 O
ATOM 1285 NE2 GLN B 66 6.928 34.895 32.760 1.00 2.75 N
ATOM 1286 N LEU B 67 11.746 38.711 30.237 1.00 2.75 N
ATOM 1287 CA LEU B 67 12.246 40.081 30.403 1.00 2.75 C
ATOM 1288 C LEU B 67 11.375 40.929 29.487 1.00 2.75 C
ATOM 1289 O LEU B 67 10.763 40.410 28.545 1.00 6.58 O
ATOM 1290 CB LEU B 67 13.723 40.226 29.990 1.00 2.75 C
ATOM 1291 CG LEU B 67 14.064 40.266 28.490 1.00 2.75 C
ATOM 1292 CD1 LEU B 67 15.109 41.342 28.186 1.00 2.75 C
ATOM 1293 CD2 LEU B 67 14.572 38.897 28.061 1.00 2.75 C
ATOM 1294 N ARG B 68 11.284 42.222 29.769 1.00 2.75 N
ATOM 1295 CA ARG B 68 10.484 43.091 28.918 1.00 2.75 C
ATOM 1296 C ARG B 68 11.432 44.088 28.290 1.00 2.75 C
ATOM 1297 O ARG B 68 12.258 44.696 28.980 1.00 6.58 O
ATOM 1298 CB ARG B 68 9.411 43.837 29.715 1.00 2.75 C
ATOM 1299 CG ARG B 68 8.269 44.413 28.850 1.00 2.75 C
ATOM 1300 CD ARG B 68 7.342 45.325 29.650 1.00 2.75 C
ATOM 1301 NE ARG B 68 7.885 46.665 29.858 1.00 2.75 N
ATOM 1302 CZ ARG B 68 7.533 47.457 30.867 1.00 2.75 C
ATOM 1303 NH1 ARG B 68 6.642 47.034 31.754 1.00 2.75 N
ATOM 1304 NH2 ARG B 68 8.071 48.668 30.992 1.00 2.75 N
ATOM 1305 N ILE B 69 11.341 44.215 26.972 1.00 2.75 N
ATOM 1306 CA ILE B 69 12.158 45.162 26.242 1.00 2.75 C
ATOM 1307 C ILE B 69 11.195 46.180 25.645 1.00 2.75 C
ATOM 1308 O ILE B 69 10.234 45.816 24.964 1.00 6.58 O
ATOM 1309 CB ILE B 69 12.966 44.477 25.105 1.00 2.75 C
ATOM 1310 CG1 ILE B 69 13.825 45.516 24.373 1.00 2.75 C
ATOM 1311 CG2 ILE B 69 12.021 43.826 24.100 1.00 2.75 C
ATOM 1312 CD1 ILE B 69 14.837 44.895 23.427 1.00 2.75 C
ATOM 1313 N ASP B 70 11.436 47.456 25.924 1.00 2.75 N
ATOM 1314 CA ASP B 70 10.595 48.519 25.392 1.00 2.75 C
ATOM 1315 C ASP B 70 11.278 49.017 24.127 1.00 2.75 C
ATOM 1316 O ASP B 70 12.442 49.426 24.158 1.00 6.58 O
ATOM 1317 CB ASP B 70 10.449 49.657 26.414 1.00 2.75 C
ATOM 1318 CG ASP B 70 9.565 49.273 27.603 1.00 2.75 C
ATOM 1319 OD1 ASP B 70 9.427 50.090 28.536 1.00 2.75 O
ATOM 1320 OD2 ASP B 70 8.993 48.164 27.600 1.00 2.75 O
ATOM 1321 N HIS B 71 10.560 48.967 23.010 1.00 6.58 N
ATOM 1322 CA HIS B 71 11.126 49.383 21.731 1.00 6.58 C
ATOM 1323 C HIS B 71 11.585 50.833 21.729 1.00 6.58 C
ATOM 1324 O HIS B 71 11.250 51.606 22.622 1.00 6.58 O
ATOM 1325 CB HIS B 71 10.120 49.140 20.610 1.00 6.58 C
ATOM 1326 CG HIS B 71 9.883 47.689 20.317 1.00 17.56 C
ATOM 1327 ND1 HIS B 71 10.311 47.087 19.154 1.00 28.54 N
ATOM 1328 CD2 HIS B 71 9.260 46.723 21.032 1.00 28.54 C
ATOM 1329 CE1 HIS B 71 9.960 45.814 19.163 1.00 39.52 C
ATOM 1330 NE2 HIS B 71 9.321 45.567 20.292 1.00 39.52 N
ATOM 1331 N LEU B 72 12.348 51.195 20.703 1.00 6.58 N
ATOM 1332 CA LEU B 72 12.900 52.536 20.592 1.00 6.58 C
ATOM 1333 C LEU B 72 12.025 53.563 19.881 1.00 6.58 C
ATOM 1334 O LEU B 72 12.510 54.613 19.444 1.00 6.58 O
ATOM 1335 CB LEU B 72 14.280 52.453 19.924 1.00 6.58 C
ATOM 1336 CG LEU B 72 15.251 51.508 20.649 1.00 17.56 C
ATOM 1337 CD1 LEU B 72 16.484 51.256 19.801 1.00 28.54 C
ATOM 1338 CD2 LEU B 72 15.634 52.104 21.993 1.00 28.54 C
ATOM 1339 N ASP B 73 10.732 53.277 19.777 1.00 6.58 N
ATOM 1340 CA ASP B 73 9.816 54.209 19.133 1.00 6.58 C
ATOM 1341 C ASP B 73 9.310 55.196 20.179 1.00 6.58 C
ATOM 1342 O ASP B 73 9.482 54.985 21.384 1.00 6.58 O
ATOM 1343 CB ASP B 73 8.635 53.477 18.463 1.00 6.58 C
ATOM 1344 CG ASP B 73 7.749 52.743 19.454 1.00 17.56 C
ATOM 1345 OD1 ASP B 73 8.180 51.704 19.994 1.00 28.54 O
ATOM 1346 OD2 ASP B 73 6.618 53.213 19.692 1.00 28.54 O
ATOM 1347 N ALA B 74 8.697 56.277 19.712 1.00 6.58 N
ATOM 1348 CA ALA B 74 8.186 57.329 20.597 1.00 6.58 C
ATOM 1349 C ALA B 74 7.301 56.841 21.743 1.00 6.58 C
ATOM 1350 O ALA B 74 7.404 57.345 22.868 1.00 6.58 O
ATOM 1351 CB ALA B 74 7.437 58.377 19.765 1.00 6.58 C
ATOM 1352 N SER B 75 6.430 55.873 21.472 1.00 6.58 N
ATOM 1353 CA SER B 75 5.536 55.372 22.516 1.00 6.58 C
ATOM 1354 C SER B 75 6.066 54.104 23.193 1.00 6.58 C
ATOM 1355 O SER B 75 5.320 53.397 23.868 1.00 6.58 O
ATOM 1356 CB SER B 75 4.130 55.132 21.947 1.00 6.58 C
ATOM 1357 OG SER B 75 3.590 56.335 21.420 1.00 17.56 O
ATOM 1358 N GLN B 76 7.361 53.848 23.013 1.00 6.58 N
ATOM 1359 CA GLN B 76 8.062 52.698 23.606 1.00 6.58 C
ATOM 1360 C GLN B 76 7.242 51.418 23.739 1.00 6.58 C
ATOM 1361 O GLN B 76 6.942 50.972 24.844 1.00 6.58 O
ATOM 1362 CB GLN B 76 8.628 53.088 24.979 1.00 6.58 C
ATOM 1363 CG GLN B 76 9.744 54.135 24.912 1.00 17.56 C
ATOM 1364 CD GLN B 76 10.260 54.538 26.278 1.00 28.54 C
ATOM 1365 OE1 GLN B 76 9.565 55.200 27.046 1.00 39.52 O
ATOM 1366 NE2 GLN B 76 11.485 54.136 26.588 1.00 39.52 N
ATOM 1367 N GLU B 77 6.901 50.822 22.601 1.00 6.58 N
ATOM 1368 CA GLU B 77 6.105 49.604 22.581 1.00 6.58 C
ATOM 1369 C GLU B 77 6.715 48.527 23.460 1.00 6.58 C
ATOM 1370 O GLU B 77 7.874 48.165 23.282 1.00 6.58 O
ATOM 1371 CB GLU B 77 5.978 49.089 21.148 1.00 6.58 C
ATOM 1372 CG GLU B 77 5.091 47.872 21.014 1.00 17.56 C
ATOM 1373 CD GLU B 77 4.703 47.590 19.577 1.00 28.54 C
ATOM 1374 OE1 GLU B 77 3.995 48.428 18.981 1.00 39.52 O
ATOM 1375 OE2 GLU B 77 5.105 46.533 19.048 1.00 39.52 O
ATOM 1376 N PRO B 78 5.936 48.002 24.423 1.00 6.58 N
ATOM 1377 CA PRO B 78 6.391 46.957 25.343 1.00 6.58 C
ATOM 1378 C PRO B 78 6.335 45.567 24.725 1.00 6.58 C
ATOM 1379 O PRO B 78 5.356 45.213 24.061 1.00 6.58 O
ATOM 1380 CB PRO B 78 5.427 47.094 26.513 1.00 6.58 C
ATOM 1381 CG PRO B 78 4.153 47.425 25.814 1.00 17.56 C
ATOM 1382 CD PRO B 78 4.586 48.464 24.795 1.00 28.54 C
ATOM 1383 N GLN B 79 7.392 44.787 24.938 1.00 2.75 N
ATOM 1384 CA GLN B 79 7.446 43.426 24.414 1.00 2.75 C
ATOM 1385 C GLN B 79 8.108 42.471 25.386 1.00 2.75 C
ATOM 1386 O GLN B 79 9.292 42.610 25.705 1.00 2.75 O
ATOM 1387 CB GLN B 79 8.191 43.376 23.067 1.00 2.75 C
ATOM 1388 CG GLN B 79 8.383 41.954 22.507 1.00 2.75 C
ATOM 1389 CD GLN B 79 8.772 41.943 21.037 1.00 2.75 C
ATOM 1390 OE1 GLN B 79 9.524 42.804 20.573 1.00 2.75 O
ATOM 1391 NE2 GLN B 79 8.270 40.951 20.295 1.00 2.75 N
ATOM 1392 N TRP B 80 7.327 41.502 25.855 1.00 6.58 N
ATOM 1393 CA TRP B 80 7.833 40.493 26.769 1.00 6.58 C
ATOM 1394 C TRP B 80 8.361 39.348 25.920 1.00 6.58 C
ATOM 1395 O TRP B 80 7.761 38.994 24.899 1.00 6.58 O
ATOM 1396 CB TRP B 80 6.720 39.992 27.696 1.00 6.58 C
ATOM 1397 CG TRP B 80 6.186 41.056 28.617 1.00 17.56 C
ATOM 1398 CD1 TRP B 80 5.272 42.023 28.311 1.00 28.54 C
ATOM 1399 CD2 TRP B 80 6.565 41.282 29.982 1.00 28.54 C
ATOM 1400 NE1 TRP B 80 5.058 42.838 29.398 1.00 39.52 N
ATOM 1401 CE2 TRP B 80 5.839 42.406 30.437 1.00 39.52 C
ATOM 1402 CE3 TRP B 80 7.449 40.646 30.865 1.00 39.52 C
ATOM 1403 CZ2 TRP B 80 5.970 42.909 31.737 1.00 50.50 C
ATOM 1404 CZ3 TRP B 80 7.579 41.148 32.159 1.00 50.50 C
ATOM 1405 CH2 TRP B 80 6.841 42.269 32.580 1.00 61.48 C
ATOM 1406 N ILE B 81 9.495 38.790 26.334 1.00 6.58 N
ATOM 1407 CA ILE B 81 10.117 37.686 25.618 1.00 6.58 C
ATOM 1408 C ILE B 81 10.552 36.585 26.602 1.00 6.58 C
ATOM 1409 O ILE B 81 10.823 36.859 27.768 1.00 6.58 O
ATOM 1410 CB ILE B 81 11.363 38.180 24.849 1.00 6.58 C
ATOM 1411 CG1 ILE B 81 10.980 39.340 23.931 1.00 17.56 C
ATOM 1412 CG2 ILE B 81 11.963 37.041 24.029 1.00 17.56 C
ATOM 1413 CD1 ILE B 81 12.138 39.905 23.133 1.00 28.54 C
ATOM 1414 N TRP B 82 10.607 35.347 26.122 1.00 6.58 N
ATOM 1415 CA TRP B 82 11.044 34.219 26.928 1.00 6.58 C
ATOM 1416 C TRP B 82 12.536 34.024 26.653 1.00 6.58 C
ATOM 1417 O TRP B 82 12.957 34.029 25.497 1.00 6.58 O
ATOM 1418 CB TRP B 82 10.279 32.943 26.545 1.00 6.58 C
ATOM 1419 CG TRP B 82 8.860 32.907 27.039 1.00 17.56 C
ATOM 1420 CD1 TRP B 82 7.741 33.270 26.351 1.00 28.54 C
ATOM 1421 CD2 TRP B 82 8.418 32.487 28.334 1.00 28.54 C
ATOM 1422 NE1 TRP B 82 6.625 33.098 27.135 1.00 39.52 N
ATOM 1423 CE2 TRP B 82 7.011 32.619 28.358 1.00 39.52 C
ATOM 1424 CE3 TRP B 82 9.074 32.010 29.478 1.00 39.52 C
ATOM 1425 CZ2 TRP B 82 6.245 32.292 29.484 1.00 50.50 C
ATOM 1426 CZ3 TRP B 82 8.312 31.683 30.599 1.00 50.50 C
ATOM 1427 CH2 TRP B 82 6.911 31.827 30.591 1.00 61.48 C
ATOM 1428 N MET B 83 13.323 33.828 27.711 1.00 6.58 N
ATOM 1429 CA MET B 83 14.769 33.660 27.582 1.00 6.58 C
ATOM 1430 C MET B 83 15.256 32.493 26.734 1.00 6.58 C
ATOM 1431 O MET B 83 16.308 32.584 26.103 1.00 6.58 O
ATOM 1432 CB MET B 83 15.424 33.558 28.961 1.00 6.58 C
ATOM 1433 CG MET B 83 15.555 34.879 29.710 1.00 17.56 C
ATOM 1434 SD MET B 83 16.809 34.800 31.027 1.00 28.54 S
ATOM 1435 CE MET B 83 17.992 35.915 30.400 1.00 39.52 C
ATOM 1436 N ASP B 84 14.506 31.398 26.711 1.00 6.58 N
ATOM 1437 CA ASP B 84 14.933 30.244 25.933 1.00 6.58 C
ATOM 1438 C ASP B 84 14.997 30.546 24.438 1.00 6.58 C
ATOM 1439 O ASP B 84 15.714 29.890 23.690 1.00 6.58 O
ATOM 1440 CB ASP B 84 14.007 29.056 26.199 1.00 6.58 C
ATOM 1441 CG ASP B 84 12.574 29.325 25.798 1.00 17.56 C
ATOM 1442 OD1 ASP B 84 11.982 30.293 26.311 1.00 28.54 O
ATOM 1443 OD2 ASP B 84 12.040 28.554 24.974 1.00 28.54 O
ATOM 1444 N ARG B 85 14.272 31.572 24.015 1.00 6.58 N
ATOM 1445 CA ARG B 85 14.233 31.963 22.614 1.00 6.58 C
ATOM 1446 C ARG B 85 15.462 32.732 22.128 1.00 6.58 C
ATOM 1447 O ARG B 85 15.637 32.911 20.926 1.00 6.58 O
ATOM 1448 CB ARG B 85 12.984 32.817 22.368 1.00 6.58 C
ATOM 1449 CG ARG B 85 11.689 32.126 22.760 1.00 17.56 C
ATOM 1450 CD ARG B 85 11.570 30.776 22.073 1.00 28.54 C
ATOM 1451 NE ARG B 85 10.306 30.109 22.368 1.00 39.52 N
ATOM 1452 CZ ARG B 85 9.114 30.556 21.982 1.00 50.50 C
ATOM 1453 NH1 ARG B 85 9.016 31.677 21.278 1.00 61.48 N
ATOM 1454 NH2 ARG B 85 8.018 29.881 22.300 1.00 61.48 N
ATOM 1455 N ILE B 86 16.315 33.163 23.053 1.00 2.75 N
ATOM 1456 CA ILE B 86 17.482 33.971 22.701 1.00 2.75 C
ATOM 1457 C ILE B 86 18.731 33.228 22.253 1.00 2.75 C
ATOM 1458 O ILE B 86 19.178 32.298 22.914 1.00 6.58 O
ATOM 1459 CB ILE B 86 17.873 34.872 23.878 1.00 2.75 C
ATOM 1460 CG1 ILE B 86 16.657 35.683 24.331 1.00 2.75 C
ATOM 1461 CG2 ILE B 86 19.037 35.785 23.487 1.00 2.75 C
ATOM 1462 CD1 ILE B 86 16.854 36.372 25.652 1.00 2.75 C
ATOM 1463 N VAL B 87 19.305 33.655 21.134 1.00 6.58 N
ATOM 1464 CA VAL B 87 20.518 33.019 20.637 1.00 6.58 C
ATOM 1465 C VAL B 87 21.725 33.962 20.657 1.00 6.58 C
ATOM 1466 O VAL B 87 22.863 33.526 20.461 1.00 6.58 O
ATOM 1467 CB VAL B 87 20.318 32.464 19.205 1.00 6.58 C
ATOM 1468 CG1 VAL B 87 19.211 31.429 19.213 1.00 17.56 C
ATOM 1469 CG2 VAL B 87 19.973 33.596 18.240 1.00 17.56 C
ATOM 1470 N ALA B 88 21.483 35.251 20.896 1.00 6.58 N
ATOM 1471 CA ALA B 88 22.564 36.227 20.954 1.00 6.58 C
ATOM 1472 C ALA B 88 22.097 37.581 21.494 1.00 6.58 C
ATOM 1473 O ALA B 88 20.906 37.916 21.451 1.00 6.58 O
ATOM 1474 CB ALA B 88 23.188 36.409 19.574 1.00 6.58 C
ATOM 1475 N VAL B 89 23.054 38.359 21.991 1.00 6.58 N
ATOM 1476 CA VAL B 89 22.781 39.685 22.542 1.00 6.58 C
ATOM 1477 C VAL B 89 23.994 40.593 22.303 1.00 6.58 C
ATOM 1478 O VAL B 89 25.045 40.405 22.904 1.00 6.58 O
ATOM 1479 CB VAL B 89 22.504 39.618 24.069 1.00 6.58 C
ATOM 1480 CG1 VAL B 89 22.213 41.014 24.608 1.00 17.56 C
ATOM 1481 CG2 VAL B 89 21.335 38.684 24.349 1.00 17.56 C
ATOM 1482 N HIS B 90 23.849 41.563 21.409 1.00 6.58 N
ATOM 1483 CA HIS B 90 24.940 42.493 21.114 1.00 6.58 C
ATOM 1484 C HIS B 90 24.516 43.895 21.577 1.00 6.58 C
ATOM 1485 O HIS B 90 23.328 44.191 21.645 1.00 6.58 O
ATOM 1486 CB HIS B 90 25.234 42.495 19.610 1.00 6.58 C
ATOM 1487 CG HIS B 90 24.976 41.180 18.935 1.00 17.56 C
ATOM 1488 ND1 HIS B 90 23.706 40.685 18.729 1.00 28.54 N
ATOM 1489 CD2 HIS B 90 25.825 40.263 18.412 1.00 28.54 C
ATOM 1490 CE1 HIS B 90 23.784 39.521 18.109 1.00 39.52 C
ATOM 1491 NE2 HIS B 90 25.059 39.241 17.905 1.00 39.52 N
ATOM 1492 N PRO B 91 25.479 44.772 21.905 1.00 6.58 N
ATOM 1493 CA PRO B 91 25.155 46.131 22.360 1.00 6.58 C
ATOM 1494 C PRO B 91 24.146 46.915 21.507 1.00 6.58 C
ATOM 1495 O PRO B 91 23.319 46.349 20.784 1.00 6.58 O
ATOM 1496 CB PRO B 91 26.516 46.815 22.397 1.00 6.58 C
ATOM 1497 CG PRO B 91 27.430 45.689 22.786 1.00 17.56 C
ATOM 1498 CD PRO B 91 26.935 44.550 21.909 1.00 28.54 C
ATOM 1499 N MET B 92 24.226 48.232 21.630 1.00 6.58 N
ATOM 1500 CA MET B 92 23.373 49.183 20.917 1.00 6.58 C
ATOM 1501 C MET B 92 24.021 50.563 20.904 1.00 6.58 C
ATOM 1502 O MET B 92 23.922 51.283 19.904 1.00 6.58 O
ATOM 1503 CB MET B 92 22.005 49.304 21.584 1.00 6.58 C
ATOM 1504 CG MET B 92 20.961 48.349 21.051 1.00 17.56 C
ATOM 1505 SD MET B 92 20.639 48.596 19.289 1.00 28.54 S
ATOM 1506 CE MET B 92 19.668 50.108 19.308 1.00 39.52 C
ATOM 1507 N PRO B 93 24.688 50.950 22.019 1.00 1.02 N
ATOM 1508 CA PRO B 93 25.360 52.250 22.166 1.00 1.02 C
ATOM 1509 C PRO B 93 25.878 52.907 20.883 1.00 1.02 C
ATOM 1510 O PRO B 93 25.289 53.937 20.472 1.00 1.02 O
ATOM 1511 CB PRO B 93 26.484 51.935 23.138 1.00 1.02 C
ATOM 1512 CG PRO B 93 25.829 50.975 24.071 1.00 1.02 C
ATOM 1513 CD PRO B 93 25.080 50.051 23.125 1.00 1.02 C
TER 1514 PRO B 93
HETATM 1515 O HOH A 102 55.426 32.989 21.912 1.00 1.02 O
HETATM 1516 O HOH A 103 40.901 26.749 43.055 1.00 2.13 O
HETATM 1517 O HOH A 104 35.349 33.788 41.580 1.00 2.13 O
HETATM 1518 O HOH A 105 38.978 10.519 41.005 1.00 2.13 O
HETATM 1519 O HOH A 106 25.923 8.913 38.903 1.00 2.13 O
HETATM 1520 O HOH A 107 40.775 10.844 37.633 1.00 2.13 O
HETATM 1521 O HOH A 108 46.016 24.167 52.453 1.00 2.13 O
HETATM 1522 O HOH A 109 34.530 20.517 53.061 1.00 2.13 O
HETATM 1523 O HOH A 110 39.762 16.152 30.467 1.00 2.13 O
HETATM 1524 O HOH A 111 30.722 35.109 21.328 1.00 2.13 O
HETATM 1525 O HOH A 112 48.099 39.721 22.618 1.00 2.13 O
HETATM 1526 O HOH A 113 29.251 24.535 24.931 1.00 2.13 O
HETATM 1527 O HOH A 114 33.272 36.664 19.585 1.00 2.13 O
HETATM 1528 O HOH A 115 36.183 37.056 26.418 1.00 2.13 O
HETATM 1529 O HOH A 116 49.838 45.352 38.462 1.00 2.13 O
HETATM 1530 O HOH A 117 46.800 25.050 36.459 1.00 2.13 O
HETATM 1531 O HOH A 118 40.302 38.406 23.407 1.00 2.13 O
HETATM 1532 O HOH A 119 37.692 32.576 19.258 1.00 2.13 O
HETATM 1533 O HOH A 120 33.794 37.488 17.152 1.00 2.13 O
HETATM 1534 O HOH A 121 43.449 39.198 39.150 1.00 2.13 O
HETATM 1535 O HOH A 122 49.640 41.488 20.852 1.00 2.13 O
HETATM 1536 O HOH A 123 32.173 35.770 17.262 1.00 2.13 O
HETATM 1537 O HOH A 124 22.494 21.386 46.541 1.00 2.13 O
HETATM 1538 O HOH A 125 28.032 25.047 29.712 1.00 2.13 O
HETATM 1539 O HOH A 126 28.233 21.667 43.224 1.00 2.13 O
HETATM 1540 O HOH A 127 39.084 12.357 48.850 1.00 2.13 O
HETATM 1541 O HOH A 128 34.475 39.410 27.398 1.00 2.13 O
HETATM 1542 O HOH A 129 47.708 22.629 31.427 1.00 2.13 O
HETATM 1543 O HOH A 130 46.418 42.566 23.669 1.00 2.13 O
HETATM 1544 O HOH A 131 30.155 30.338 44.630 1.00 2.13 O
HETATM 1545 O HOH A 132 28.721 25.660 44.704 1.00 2.13 O
HETATM 1546 O HOH A 133 28.302 16.476 50.387 1.00 2.13 O
HETATM 1547 O HOH A 134 41.695 30.391 40.467 1.00 2.13 O
HETATM 1548 O HOH A 135 56.669 36.377 24.355 1.00 2.13 O
HETATM 1549 O HOH A 136 41.693 16.469 44.730 1.00 2.13 O
HETATM 1550 O HOH A 137 42.409 31.118 37.804 1.00 1.02 O
HETATM 1551 O HOH A 138 49.137 31.195 36.402 1.00 1.02 O
HETATM 1552 O HOH A 139 47.098 27.230 22.246 1.00 1.02 O
HETATM 1553 O HOH A 140 44.417 29.341 23.097 1.00 1.02 O
HETATM 1554 O HOH A 141 44.503 21.646 30.042 1.00 1.02 O
HETATM 1555 O HOH A 142 50.120 24.010 34.435 1.00 1.02 O
HETATM 1556 O HOH A 143 42.119 23.323 26.144 1.00 1.02 O
HETATM 1557 O HOH A 144 37.316 21.543 24.530 1.00 1.02 O
HETATM 1558 O HOH A 145 48.258 50.129 33.383 1.00 1.02 O
HETATM 1559 O HOH A 146 44.850 39.402 22.317 1.00 1.02 O
HETATM 1560 O HOH A 147 29.120 25.401 32.390 1.00 1.02 O
HETATM 1561 O HOH A 148 32.874 12.977 56.281 1.00 1.02 O
HETATM 1562 O HOH A 149 38.535 14.185 48.108 1.00 1.02 O
HETATM 1563 O HOH A 150 53.534 41.286 39.637 1.00 1.02 O
HETATM 1564 O HOH A 151 36.940 23.510 22.201 1.00 1.02 O
HETATM 1565 O HOH A 152 34.988 24.620 28.470 1.00 1.02 O
HETATM 1566 O HOH A 153 40.101 21.420 51.543 1.00 1.02 O
HETATM 1567 O HOH A 154 28.368 9.624 37.268 1.00 1.02 O
HETATM 1568 O HOH A 155 35.088 36.660 31.676 1.00 1.02 O
HETATM 1569 O HOH A 156 47.916 37.455 31.986 1.00 1.02 O
HETATM 1570 O HOH A 157 54.542 41.201 24.879 1.00 1.02 O
HETATM 1571 O HOH B 102 7.289 36.553 28.720 1.00 1.02 O
HETATM 1572 O HOH B 103 16.717 54.179 24.047 1.00 1.02 O
HETATM 1573 O HOH B 104 9.248 42.123 17.733 1.00 1.02 O
HETATM 1574 O HOH B 105 14.412 28.147 38.194 1.00 1.02 O
HETATM 1575 O HOH B 106 12.750 20.065 38.258 1.00 1.02 O
HETATM 1576 O HOH B 107 2.862 19.364 41.232 1.00 1.02 O
HETATM 1577 O HOH B 108 4.268 47.290 30.459 1.00 2.13 O
HETATM 1578 O HOH B 109 -2.769 31.767 43.156 1.00 2.13 O
HETATM 1579 O HOH B 110 12.902 52.548 24.732 1.00 2.13 O
HETATM 1580 O HOH B 111 26.359 26.707 27.712 1.00 2.13 O
HETATM 1581 O HOH B 112 22.639 23.783 37.663 1.00 2.13 O
HETATM 1582 O HOH B 113 5.670 27.728 39.182 1.00 2.13 O
HETATM 1583 O HOH B 114 18.823 27.871 20.886 1.00 2.13 O
HETATM 1584 O HOH B 115 6.968 22.085 46.925 1.00 2.13 O
HETATM 1585 O HOH B 116 20.608 59.410 25.117 1.00 2.13 O
HETATM 1586 O HOH B 117 9.544 22.077 28.354 1.00 2.13 O
HETATM 1587 O HOH B 118 9.058 35.190 23.766 1.00 2.13 O
HETATM 1588 O HOH B 119 20.838 33.579 37.615 1.00 2.13 O
HETATM 1589 O HOH B 120 29.520 41.743 35.507 1.00 2.13 O
HETATM 1590 O HOH B 121 30.129 41.166 22.082 1.00 2.13 O
HETATM 1591 O HOH B 122 27.747 54.704 18.906 1.00 2.13 O
HETATM 1592 O HOH B 123 28.438 46.176 32.160 1.00 2.13 O
HETATM 1593 O HOH B 124 1.534 49.415 26.654 1.00 2.13 O
HETATM 1594 O HOH B 125 27.355 55.392 22.150 1.00 2.13 O
HETATM 1595 O HOH B 126 4.705 14.287 32.912 1.00 2.13 O
HETATM 1596 O HOH B 127 12.883 20.283 43.923 1.00 2.13 O
HETATM 1597 O HOH B 128 2.632 45.033 28.330 1.00 2.13 O
HETATM 1598 O HOH B 129 1.635 21.917 23.452 1.00 2.13 O
HETATM 1599 O HOH B 130 4.297 24.108 27.700 1.00 2.13 O
HETATM 1600 O HOH B 131 17.004 27.437 25.729 1.00 2.13 O
HETATM 1601 O HOH B 132 2.460 23.310 21.287 1.00 2.13 O
HETATM 1602 O HOH B 133 11.278 39.168 35.156 1.00 2.13 O
HETATM 1603 O HOH B 134 27.898 50.589 36.883 1.00 2.13 O
HETATM 1604 O HOH B 135 -1.156 19.299 39.714 1.00 2.13 O
HETATM 1605 O HOH B 136 8.539 41.213 15.785 1.00 2.13 O
HETATM 1606 O HOH B 137 26.268 43.473 15.966 1.00 2.13 O
HETATM 1607 O HOH B 138 5.065 41.947 19.954 1.00 2.13 O
HETATM 1608 O HOH B 139 7.697 38.140 21.957 1.00 2.13 O
HETATM 1609 O HOH B 140 14.774 22.019 21.284 1.00 2.13 O
HETATM 1610 O HOH B 141 15.624 24.668 41.850 1.00 2.13 O
HETATM 1611 O HOH B 142 21.241 28.333 12.634 1.00 2.13 O
HETATM 1612 O HOH B 143 3.423 26.956 48.307 1.00 2.13 O
HETATM 1613 O HOH B 144 27.900 42.522 31.320 1.00 2.13 O
HETATM 1614 O HOH B 145 9.389 30.775 39.658 1.00 2.13 O
HETATM 1615 O HOH B 146 26.148 37.301 22.575 1.00 2.13 O
HETATM 1616 O HOH B 147 9.155 17.660 36.448 1.00 2.13 O
HETATM 1617 O HOH B 148 18.137 33.019 13.730 1.00 2.13 O
HETATM 1618 O HOH B 149 11.313 27.060 15.206 1.00 2.13 O
HETATM 1619 O HOH B 150 4.056 17.989 38.825 1.00 2.13 O
HETATM 1620 O HOH B 151 7.416 35.656 43.886 1.00 2.13 O
HETATM 1621 O HOH B 152 12.541 27.907 11.923 1.00 2.13 O
HETATM 1622 O HOH B 153 6.329 26.333 11.082 1.00 2.13 O
HETATM 1623 O HOH B 154 26.283 56.895 33.844 1.00 2.13 O
HETATM 1624 O HOH B 155 5.366 21.950 19.886 1.00 2.13 O
HETATM 1625 O HOH B 156 13.512 42.231 37.121 1.00 2.13 O
HETATM 1626 O HOH B 157 -0.309 28.369 45.779 1.00 1.02 O
HETATM 1627 O HOH B 158 25.446 48.828 33.125 1.00 1.02 O
HETATM 1628 O HOH B 159 18.755 48.751 27.967 1.00 1.02 O
HETATM 1629 O HOH B 160 17.792 30.870 15.719 1.00 1.02 O
HETATM 1630 O HOH B 161 14.024 55.209 23.929 1.00 1.02 O
HETATM 1631 O HOH B 162 5.358 54.257 26.690 1.00 1.02 O
HETATM 1632 O HOH B 163 20.975 21.968 22.981 1.00 1.02 O
HETATM 1633 O HOH B 164 17.979 35.529 38.171 1.00 1.02 O
HETATM 1634 O HOH B 165 24.624 33.158 26.880 1.00 1.02 O
HETATM 1635 O HOH B 166 1.944 14.011 24.536 1.00 1.02 O
HETATM 1636 O HOH B 167 24.800 20.135 30.685 1.00 1.02 O
MASTER 305 0 0 2 15 0 0 6 1634 2 0 16
END
PyCogent-1.5.3/tests/data/bowtie_output.map 000644 000765 000024 00000001526 11533073176 021735 0 ustar 00jrideout staff 000000 000000 GAPC_0015:6:1:1283:11957#0/1 - Mus 66047927 TGTATATATAAACATATATGGAAACTGAATATATATACATTATGTATGTATATATGTATATGTTATATATACATA IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 0 55:A>G,64:C>A
GAPC_0015:6:1:1394:18813#0/1 + Mus 77785518 ATGAAATTCCTAGCCAAATGGATGGACCTGGAGGGCATCATC IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 447
GAPC_0015:6:1:1560:18056#0/1 + Mus 178806665 TAGATAAAGGCTCTGTTTTTCATCATTGAGAAATTGTTATTTTTCTGATGTTATA IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 0 9:T>G
GAPC_0015:6:1:1565:19849#0/1 + Mus 116516430 ACCATTTGCTTGGAAAATTGTTTTCCAGCCTTTCACTCTGAG IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 141
GAPC_0015:6:1:1591:17397#0/1 - Mus 120440696 TCTAAATCTGTTCATTAATTAAGCCTGTTTCCATGTCCTTGGTCTTAAGACCAATCTGTTATGCGGGTGTGA IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII 0 70:A>C,71:G>T PyCogent-1.5.3/tests/data/brca1.fasta 000644 000765 000024 00000510250 10665667404 020344 0 ustar 00jrideout staff 000000 000000 >FlyingFox
TGTGGCACAAATGCTCATGCCAGCTCTTTACAGCATGAGAAC---AGTTTATTATACACTAAAGACAGAATGAATGTAGA
AAAGACTGACTTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACAGAACAGATGGGTTGAAACTAAGGAAA
CATGTAACGAT---ATGCAGACTTCCAGCACAGAGAAAAAGGTAGTTCTGAATGCTGATCCCCTGAATGGGAGAATAGAA
CTGAATAAGCAGAAACCTCCATGCTCTGACAGTCCTAGAGAT---TCTCAAGAT---ATTTCTTGGATAACACGGAATAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCCAGACGTGATGAAATATTAACTTCTGATGTCTCACCTGATGGGAGGTCTG
AATCAAATGTG---------------GTAGAAGTTCCAAAT------GAAGTAGATGGATACTCTGGTGCTTCAGAGAAA
ATAGCTTTAAAGGCCAATGATCCTCATGGTGCTTTAATGTGC------GAAAGAGTTCACTCCAAACTGGTAGAAAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACATATCGGAGGAAAGCAAGCCTCCCTAACTTGAGCCACATAACTGAAAATC
TAATTACAGGAGCATCTGCTATAGAACCTCAGATAACACAA---------------------------------------
---------------------GAGTATCCCCTCACAAATAAACTAAAGCGTAAAAGGAGAACTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAATAGATTTGGCAGTTGTTCAGAAAACTCCGGAAAACATAATTGAGGAAACTGACCAAATAG
AGCAGAAT---------GGTCATGTGATGAATAGTACTAATAATGGTCATGAGAATGAAACAAAAGGTGATTAT---GTT
CAGAAGAAGAAAAATACAAACCCAACAGAA------TCATTGGAAAAAGAATCTACTTTCAAAACTAAAGCTGAACCTAT
ATGCAGCAGCATAAGCAATATGGAACTAGAATTAAATATCCACAGTTCAAAAGCAGTTAAGAAGAATAGGCTGAGGAGGA
AGTCCTCTACCAGGCATATTCATGCACTTGAACTAGTAGTCAATAGAAATCCAAGCCCACCTAATCATACTGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---CTGAAGGAAAAA---AATTCTGACCAAATGCCAGTCAGACACAGCAAAAA
ACTTCAATTCATAGAAGATAAAGAATCTTCAACTGGAGCCAAGAAGAATAACAAGCCAAATGAGACAATCAATAAAAGAC
TTGCCAGTGATGCTTTTCCAGAATTAAATATAACAAACATACCTGGTTTTTTTACTAATGGTTCAAGTTCTAATAAACTT
CAAGAGTTTGTCAATCCTAGCCTTCAAAGAGAAGAAATAAAAGAGAAC---CTAGGAACAATTCAAGTGTCTAATAGTAC
CAAGGACCCCAAAATTTTGATCTTCGGTGAAGGAAGA---GGTTCACAA---ACTGATCGATCTACAGAGAGTACCAGTA
TTTTATTGGTGCCTGAAACGGATTATGGCACTCAAGATAGTATCTCATTACTGGAACCTGACATCCCAGAG---AGGGTA
AAG---ACAGCACCAAACCATCAT------------GCAGCAATTAAAAACCCCAGAGAACTTATTCATGGTTGT---TC
TGAAGATACTAGAAATGATGCAGAGGGCTTTAAAGATCCATTGAGACGTGAAGTTAAC---TACANNNNNNNNNNN----
-----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
NNTTCAAACCCAGGAAATCTAGAAAAGGAATGTGCAACAGGCTATGCCCACTCCAAGTCCTTGAGGAAACAAAGTCCAAA
AGTCACTCTTGAATGTGACCGAAAAGAA---AATCAGGGAAAGAAAGAGTCTAACGTCAAGCATGTGCAGGCAGTTTATA
CAACTGTAGGCTTTCCTGTGGTTTGTGAGAAAGAAAAAAAGCCAGGAGATTATGCTAAATATGGCATAAAAGAAGTCTCT
AGGCTTTGTCAGTCATTTCAGTTCAGA---GAAAATGAAACTGAACTCACTATTGCAAATAAACTTGGAATTTCACAAAA
CCCATATCATATGCCATCCATTCCTCCCATCAAGTCATCTGTTAAAACTACATGTAAGAAAAAT---CTGTCAGAGGAAA
AGTTTGAAGAACATTCAATATCCCCTGAAAGAACAATAGGAAATGAGACCATCATTCAAAGTACAGTGGGCACAATTAGC
CAAAATAACATTAGAGAAAGCACTTTTAAAGAAGGCAGCTCAAGCAGTATTTATGAAGCAGGTTCCAGTACTAACGAACT
AGGCTCTAGTGTCAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAGAACTAAGTA
GAAACAGAGGACCACAATTAAATGCTGTGCTTCAATTGGGTCTCATGCAGCCTGAAGTCTATAAGCAAAGCCTT---CCT
CTAAGTAATTGTAAACATCCTGAAATAAAAAGGCAAGGAGAAAATGAAGGAGTAGTTCAGGCTGTTAATGCAGATGTCTC
TCTACGTCAGATTTCAGATAACTTAGAGCAA---CCTATGGGAAACAGTAATGCTTCTCAGGTTTGTTCTGAGACACCGG
ATGACCTGTTAAATGATGACAAAATAAAAGAGAATATCGGCTTTGATGAAAGTGGCATTAAGGAAAGATCTGCTGTTTTT
AGCAAAAGTGTCCAGAAAGGAGAATTCAAAAGGAGCCCTAGTCCCTTAGCCCAT---ACAAGTTTGTCTCAAGGTCGCCG
AAGAGGGGCTAGGAAATTAGAGTCCTCAGAAGAGGA-------------
>DogFaced
TGTGGCACAAATACTCATGCCAACTCATTACAGCATGAGAACAGCAGTTTATTATACACTAAAGACAGAATGAATGTAGA
AAAGACTGACTTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAGCAGAACAGATGGGTTGAAACTAAGGAAA
CATGTAATGAT---AGGCAGACTTCCAGCANAGAGAAAAAGGTAGTTCTGAATGCTGATCCCCTGAATGGAAGAATAAAA
CTGAATAAGCAGAAACCTCCATGCTCTGACAGTCCTAGAGAT---TCCAAAGAT---ATTCCTTGGATAACACGGAATAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCCAGACGTGATGAAACATTAACTTCTGATGTCTTACTTGATGAGAGGTCTG
AATCAAATGTG---------------GTAGAAGTTCCAAAT------GAAGTAGATGGATACTCTGGTGCTTCAGAGGAA
ATAGCCTTAAAGGCCAGTGATCCTCATGGTGCTTTAATATGT------GAAAGAGTTCACTCCAAATTGATAGAAAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACATATCGGAGGAAAGCAAGCCTCCCTAACTTAAGCCACATAACTGAAAATC
TAATTACAAGAGCATCTGCTACAGAACCTCAGATAACACAA---------------------------------------
---------------------GAGTGCCCCCTCACAAATAAACTAAAACGTAAAAGAAGAACTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAATAGATTTGACAACTGTTCAAAAAACTTCTGAAAATATAATTGAGGGAACTGACCAAATAG
AGCAGAAT---------GGTCATGTGATGAATAGTTCTAATGATGGTCATGAGAATGAAACAAAAGGTGATTAT---GTT
CAGAAGAAGAAAAATACAAACCCAACAGAA------TCATTGGAAAAAGAATCTGCTTTCAGAACTAAAGTTGAGTCTGT
ACCCAACAACATAAGCAATGTGGAACTAGAATTAAATATTCACGGTTCAAAAGCACTCAAGAAGAATAGNCTGAGGAGGA
AGTCCTNTACCAGGCATATTCATGCACTTGAACTAGTAGTCAATAGAAATTCAAGCCCACCTAATCATACTGAACTACAA
ATTGATAGTTGTTCCAGCAGTGAAGAA---CTGAAGGAAAAA---AATTCTGACCGAATGCCAGACAGACACAGCAAAAA
ACTTCAGTTCGTAGAAGATAAAGAATCTGCAACTGGAGCCAAGAAGAATAACATGCCAAATGAGGCAATAAATAAAAGAC
TTTCCAGTGAAGCTTTTCCCGAATTAAATATAACAAACGTACCTGGTTTTTTTACTAATGGTTCAAGTTCTAATAAACGT
CAAGAGTTTGTCAATCCTAGCCTTCAAGGAGAAGAAATAAAAGAGAAT---CTACGAACAATTCAAGTGTCTAATAGCAC
CAAAGACCCCAAAATTCTAATCTTTGGTGAAGGAAGA---GGTTCACAA---ACTGATCGATCTACAGAGAGTACCAGTA
TTTTATTGGGACCTGAAACGGATTATGGCACTCAAGATAGTATCTCATTACTGGAATCTGACATCCCAGGG---AGGGCA
AAG---ACAGCACCAAACCAACATGCAGATCTGTGTGCAGCAATTGAAAACCCCAGAGAACTTATTCATGATTGT---TT
TAAAGAAACTAGAAATGACACAGAGAGCTTTAAAGATCCATTGAGACATGAAGTTAAC---TCCACNNNNNNNNNN----
-----NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
NNTTCAGACCCAGGAAATCTAGAAAAGGAATGTGCAACAGGCTATGCCCACTCCAGGTCCTTGATAAAACAAAGTCCAAA
AGTCACTCTTGAATGTGACCGAAAAGGA---AATCAGGGAAAGAAAGAGTCTAACATNGAGCATGTGCAGGCAGTTTATA
CAACTATAGGCTTTCCTGGGGTTTCTGAGAAAGACAAAAAGCCAGGAGATTATGCCAGATATGGCATAAAAGAAGTCTCT
AGGCTTTGTCAGTCATTTCAGTCTAGA---AGAAATGAAACTGAGCTCACTATTGCAAATAAACTTGGACTTTCACAAAA
CCCATATCATATGCCATCCATTTCTCCCATCAAGTCATCTGTTAAAACTATATGTAAGAAAAAT---CTGTCAGAGGAAA
AGTTTGAAGAACATTCAATATTCCCTGAAAGAGCAATAGGAAATGAGACCATCATTCAAAGTACAGTGGGCACAATTAGC
CAAAATAACATTAGAGAAAGCACTTTTAAAGAAGGCAGCTCAAGCGGTATTTATGAAGCAGGTTCCAGTACCAATGAACT
AGGCTCTAGTGTCAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAGAACTAAGTA
GAAACAGAGGACCAAAATTAAATGCTGTGCTTCAGTTGGGTCTCATGCAGCCTGAAGTCTATGAGCAAAGCCTT---CCT
CTAAGTAATTGTAAACATTCTGAAATAAAAAGGCAAGGAGAAAATGAAGGAGTGGTTCAGGCTGTTAATGCAGATGTCTC
TCCANGTCAAATTTCAGATAACTTAGAGCAA---CCTATGGGAAACAGTAATATTTCTCAGGTTTGTTCTGAGACACCGG
ATGACCTGTTAAATGATGACAAAATAAAGGACAATATCAGCTTTGATGAAAGTGGCATTCAGGAAAGATCTGCTGTTTTT
AGCAAAAATGTCCAGAAAGGAGAATTCAGAAGGAGCCCTAGTCCCTTAGCCCAT---GCAAGTTTGTCTCAAGGTCGCCC
AAGAAGGGC----------------------------------------
>FreeTaile
TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTACTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAGCAGCCTGGCTTAGCAAAGAGCCAGCAGAGCAGATGGGCTGAAAGTAAAGAAA
CATGTAATGAT---AGGCAGACTCTCAGCACAGAGAAAAGGGTAGTTCTGAATGCTGATCCTCTGAATAGG---------
------AGAAAAGAACCTCCAGGCTCTAACTATCCTAGAGAT---TCCCAAGAT---GTTCCTTGGATAACACGGAGTAG
TAGCATACAGAAAGTTAATGAGTGGTTCTCCAGACGTGATGAAATACTAACTACTGGTGGCTCACATAACGGTAGATTTG
AATCAAATGTTGAAGTAGCTGGTGCAGTAGAAGTTCCAAAT------GAAGTAGATGGATATTCTGGTTCTCCAGAGAAA
ATAGCCTTAATGGCCTGTGATCCTCCTGATGCTTTAATATGT------GAAAGAGTCTCCTCTAAACCACTAGAAAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGAAAGGCAAGCTTCCCTAACTTGAGCCACATAAGTGAAAATC
TAATTATAGGAGCATCTGCTATAGAACCCCAGGTAACAAAA---------------------------------------
---------------------GAATGTCCCCTCACAAATAAACTAAAGCGTAAAAGAAGA---ACATCAAGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGGCAGTTGTTCAAAAGACTCTTGAAAAGGTAATTGAGGGAACTGACCAAATAG
AACAGAAT---------GGTCATGTGATGAGTATTACTAGTAATTGTCATGAGAATAAAACAAAAGGTGATTAT---GTT
CAGAAAGAGAAAAATTCTAACCCAACAGAA------TCATTGGAAAAAGAATCTGCTTTCACAACTAAAGCTGAACCTAT
AAGCAGCAGCATAAGCAATATGGAACTAGAGTTAAATATCCACAGTTCAAAAGCACCTAAGAAGAATAGGCTGAAGAGGA
AGTCCTCTACCAGGCACATTTATGCACTTGAACTAGTAGTCAATAGAAATCCAAGCCCACCTAATCACACTGAACTACAA
ATTGATAGCTGTTCTAGCAGTGAAGAG---GTGAAGGAAAAA---AATTCTGACCAAATACCAGTCAGACACAGCAAAAA
GCTTCAACTCATGGAAGGTAAAGAACCTGCAACTGGAGCCAAGAAGAGTAACAAATCAAATGAACAAATAAATAAAAAAC
TTGCCAGTGATGTTTTTCCAGAACTAAACTTAACAAACATACCTGGTTTTTTAAGTAATGATTCAAGTTCTAATAAACTT
AAAGAGTTTGTCAATCCTAACCTTCAAAGAGAAGAAATAACAGAGAAC---CTAGGAACAGTTCACATGTCTAATAGTAC
CAAAGACCTCAAAGATCTGATATTAAGTGGAGGAAGA---AGTTTGCAA---ACTGATAGATCTATGGAGAGTACCAATA
TTTTATTGGTACCTGAAACTGATTATGGCACGCAGGATAGTATCTCATTACTGGAACCTGACACCCCAGGG---AAGGCA
AAA---AAAGCTCCAAATCAATATGCGGGTCTGTGTGCAGAAATTAAAAACCNCAAGGAACTTATCCATGGTTGT---TC
TAACGATAATAGAAATGACAGAGAGGACATTAAGGATCTATTGAGACCTGAAGTTAAC---CACANNNNNNNNNNNNNNN
NNNNNNNGGAAGAGAGTGAACTTGATACACAGTATTTACAGAATACATTCAAGGTTTCAAAACGTCAGTCGTTTGCTCTG
TTTTCAAATCCA---------GAAAAGGAATATGCAACAGTCTATGGCCACTCCAGGTCCTTAAGGAAACAAAGTCCAAA
AGTCACTCTTGAATGTGGACAAAAAGAAGAAAATCAGGGAGAGAAAGAATCTGAAATCAAGTATGTACGGGGAGTTCACA
CAACTGCAGGCTTTCCTGTGGTTTGTGAGAAAGACGAAAAGCCAGAAGAATATGCCAAATGTAGCATAAAAGGAACCTCT
AGCCTTTGTCAGCCACCTCAGTTCAGA---GGCAACGAAACTGAACTCACTATTGCAAATAAACCCGGAATTTCACGAAA
CCCATATCATATACCATGCATTTCTCCCATCAGGTCCTTTGTTAAAACTATAAATAAGAAAAAC---CTGTCAGAGGAAA
AGTTTGAGGAACATTCAGTGTCACCTGAAAGAGCAATGAGAAATGAGAAT---ATTCTAAGTACAGTGAGCCCAATTAGC
CTAAATAAC---AGAGAAAGCACTTTTAAAGAAGGCAGCTCAAGC---------------------AGTACTAATGAAGT
AGGCTCTAGTACCAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAGAACTAGGTA
GAAACAGAGGATCAAAAATAAATGCTATGCTCAGATCAGGTCTCATGCAACCTGAAGTCTATAAGCCAAGCCTT---TCT
GTAAGTAATTGTGAACATCCTGAAATAAAAAGGCAAGGAGAAAATGAAGGAGTAGTTCAGGCTGTTAATGCAGATTTCTC
TCCATGTCAAATTTCAGATAACTTAGAACAA---TCTATGGGAAGTACTCCTGCTTCTCAGGTTTGTTCTGAGACACCAG
ATGACCTGTTAAATGATGACAAAATAAAGGAGAATAGCAGCTTTGCTGGAAGTGGCATTAAGGAAAGATCTGCTATTTTT
AGCAAAAGTGTCAAGAAAGAAAAATTCAGAAGGAGCCCTAGCCCCTTTGCCCAT---ACACATTTGACTCATACTCGCCA
AAGAGGGGCCAGGAAATTAGAGTCCTCAG--------------------
>LittleBro
TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTACTACTCACCAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAGCAGCCTGGCTTAGCAAGGAGCCAGCAGAGCAGATGGGCTGAAAGTAAAGAAA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAGAAAAGGGTAATTCTGGATGCTGATCCTCTGAATGGG---------
------GAAAAAGAACTTCCACGCTCTGACCATCCCAGAGAT---TCCCAAGAT---GTGCCTTGGATAACACGGAGCAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCCAGGCGTGATGAAATACTAACTTCTGATGGCTCACATAATGGCAAGTCTG
AGTCAAATGCTGAAGTAGCTGGTGCAGTGGAAGTTGCAAAT------GAAGTAGATGGGTATTCTGGTTCTCCAGGGAAA
ATAACCTTAATGGCCCATGATCCTCATGGTGCTTTAACCTGTGAAAGTGAAAGAGTTCACTCCAAACCAGTAGAAAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCAAACTTGAGCCACATAACTAAAAATC
TAATTGTAGGAGCATCTGCTATAGAACCTCAGATAGCACAA---------------------------------------
---------------------GAGTGTCCCCTCACAAATAAACTAAAGCGTAAAAGGAGAAGTACATCNGGCCTTCATCC
TGAGGATTTTATTAAGAAAGTAGATTTGGCAGTTGTTCAAAAGACTCCTGAAGAGATAATTAAGGGAACTGACCGAATAG
AACAGAAT---------GGTCATGAGATGAATATTACTAATAATGATCATGAGAATGAAACAAAAGGTGATTGT---GTT
CAGAAAGAGAAAAATGCTAACCTAACAGAA------TCACTGGAAAAAGAATCTGCGTTCACAAGTAAAGCTGAACCTAT
AAGCAGCAGCATAAGCAATATGGAACTAGAATTAAATGTCCACAGTTCAAAAGCACCTAAGAAGAATAGGCTGAAGAGGA
AGTCCTCTACCAGGCCTATTCATGCACTTGAACTAGTAGTCAATAGAAATCCGAGCCCATCTAACCATACTGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---GTGAAGGAAAAA---AATTCTGACCAAATACCAGTCAGACACAGCAAGAA
GCTTCAACTCATGGAAGGTAAAGAACCTGCAGCTGGAGCCAAGAAGAGTAATAAGTCAGATGAACAAATAAATAAAAAAC
TTGCCAGTGATGCTTTTCTAGAACAAAACTTAACAAACATGCCTGGTGTTTTTACTAATGGTTTAAGCTCTAATAAGCTT
AACGAGTTTGTCGATCCTAACCTACAAAGAGAAGAAACAGAAGAGAAC---CTAGGAGCAGTTCAAATGTCTAATAGTAC
CAAAGACCTCGAAGATCTGACATTAAGTGGAGGAAGA---AGTGTGCAA---ATTGATAGATCTAAAGAGAGTACCAATA
TTGTATTGGTACCTGAAACTGATTATGGCACACAGGATAGTGTCTCATTACTGGAACCTGACATCCCAGGG---AAGGCA
AAA---ACAGCTCCAAATCAATGTGGGGATCTGTGTGCAGCAGTTAAAAATCCTAAAGAACTTATTCGTGGTTGT---TC
TAAAGATATTAGAAATGACAGAGAGGGCTTTAAGGATCTATTGAGATGTGAAGTTAAC---CACACGCAGGAGACAAGCA
TAGAAGTGGAAGAGAGTGAACTTGATACACAGGAATTACAGAATACATTCAAGGTGTCAAAGCGCCAGTCATTTGCTCTG
TTTTCAAATCCA---------GAAAAGGAATGTGCAACAGCCTATGCTCACTCCCAGTCTTTAAGGAAACAAAGTCCAAA
AGTCACTCTTGAATGTGGACAAAAAGAAGAAAATCAGGGAAAGAAAGAATCTAAAATCAAGCATGTACAGGCAGTTCACA
CAGCTGTAGGCTTTCCTGTGGTTTGTGAGAAAGACAGAAAGCCAGGAGAGTATGCCAAATACAGCATAAAAGGAACCTCT
ATGCATTGCCNGTCCTCTCAGTTCAGA---GGCAACAAAACTGAACTCACTATTACAGATAAATATGGACTTTCCCCAAA
CCCATATCATATACCATCCATTTCTCCCATCAAGTCATTTGTTAAAACTGTAAGTAAGAAAAAC---CTGTCAAAGGAAA
AGTTTGAGGAACATTTAGTGTCACCTGAAAGAGCAATGGGAAATGAGAAC---ATTCAAAGTACAGTGAGCCCAATTAGC
CTAAGTAACATTAGAGAAAGCGCTTTTAAAGAAAGCAGCTCAAGC---------------------AGTACTAATGAAGG
GGGCTCTAGTATCAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCATGCAGAACTAGATA
TAAACAAAGGATCAAAATTAACTGCTATGCTCAGATTAGGTCTCATGCAACCCGAAGTCTATAAGCCAAGCCTT---CCT
GTAAGTAATTGTAAACATCCTGAAGTAAAAAGGCAAGGAGACAACGAAGGACTAGTTCAGGCTGTTAATGCAGACTTCCC
TCCATGTCAAATTTCAGATAACCTAGAACAA---CCTATGGGAAGTAGTCCTGTTTCTCAGGTTTGTTCTGCGACACCGG
ATGACTTGTTAACTGATGATGAAATAAAGGAGAATAGCGGCTTTGATGAAAGTGGCATTAANGAAAGATCTGCTGTTTTT
AGCAAAGATGTTCAGAAAGAAGAATTCAGAGGGAGCCCTAGCCCCTTAGCCCAT---ACATATTTGACTCGGAGTTGCCA
AAGAAGGGCCAGGAAATTAGAGTCCTCAGAAGAGGA-------------
>TombBat
TGTGGCACAAGTACTCATGCCAGCTCAGTACAGCATGAGAACAGCAGTTTACTACTCACTAAAGACAGAATGAACGTAGA
AAAGCTTGACTTCTGTAATAAAAGCAAGCAGCCTGGCTTAGCAAGGAGCCAGCAGAGCAGATGGGCTGAAAGTAAAGAAA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAGAAAAGGGTAGTTGTGAATGCTGATACCCTGGATGGG---------
------AGAAAAGAACCTCCATACTCTGACTGTCCTAATGAT---TCCCAAGAT---GTCCCTTGGATAACAGGGAATAG
TAGCATACAGAAAGTTAGTGAGTGGTTTTCCAGGCGTGATGAAATATTAACTTCTGATGGATCACATGATGGGAGATCTG
AATCAAATATGGAAGTAGCTGGTGCAGTAGAAGTTCCATAT------GAAGTAGATGGATATTCTGATTCTCCAGAGAAA
ATAGGCTTAATGGCCAGTGATCCTCTTGGTGCTTTACTATGTGAAAGTGAAAGAATCCACTCCAAACCAGTAGAAAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGAGCCATATAACTGAAAATC
TAATTATAGGAGCACCTACTATACAATCTCAGATAACACAA---------------------------------------
---------------------AATTGTCCCCTCACAGATAAACTAAAGCATAAAAGAAGAACTACATCAGGCCTTCGTCC
TGAGGATTTTATCAAGAAGGTAGATTTGGCAGCTGTTCAGAAGACTCCTGAAAAGATAATTGAGGGAACTGATCAAACAG
AACAGAAT---------GGTTCTGTGATGAATATTACTGATAATGGTCATGAGGATGAAACAAAATGTGATTAT---GGT
CAGAAAGAGAAAAATGCTAACCCAGCAGAA------TCATTGGAAAAAGAATCTGCTTTCAGAACTAAAGCTGAACCTAT
AAGCAGCAGCATAAGCAACATGGAACTAGAGTTAAATATCAACAGTTCAAAAGCACCTAAGAAGAATAGACTGAGGAGGA
AGTCCTCTACCAGGCATATTTATGCACTTGAACTGGTAGTCAATAGAAATCCAAGCCCACCTAATCATATTGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---GTGAAGAAAAGA---AATTCTGACCAAATACCAGTCAGGCACAGCAAAGA
GCCTCAACTCGTGGAAGGTGAAGAACCTACGACTAGAGCCAAGAAG---AATAAGTCAAATGAACAAATAAATAAAAGAC
TTGCCAGTGATACTTTTCCAGAACTAAATTTAAAAAACATACCTGGTTTTTTTACTAATGGTTCAAGTTCTAATAAACTT
CAAGAGTTTGTTGATCCTAACCTTCGAAGAGAAGAAGTGGAAGAGAAC---CTAGGAACAATTCAAGTGTCTGATAGTAC
CAAAGACCTCAAAGATCTGATATTAAGTGGAGGAAGA---AGTTTGCAA---ACTGATAGATCTATGGAGAGTACCAATA
TTTTATTGGTACCTGAAACTGATTATGACACTCAGTATAGTATCTCATTACTGGAACCTGACACCCCAGGG---AAGGCA
AAA---ACAGCACCAAGTCAACATGCGAGTCTGTGTGCAGCAATTGAAAACCCCAAGGAGTTTAACCATGGTTGT---TC
TAAAGATACTAGAAGTGACACAGAGGGTGTTAAGGATCTACTGAGATGTGAAATTAAC---CNCACNNNNNNNNNNNNNN
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNGAATACATTCNNGNTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATTCAGAAAATCCAGAAAAGGAATGTGCAACAGTCTATGCCCACTCCAAGTCCTTAAGGAAACACAGTCCAAA
AGTCACTCTTGGATGTGGTCAAAAAGAAGAAAATCAGGAAGAGAAAGAATCTAAAATCAAGCATGTACAGGCTGTTCACA
CAGCTGCAGGCCTTCCTGCCATTTGTGAGAAAGACAAGAAGCCAGGAGAATATGACAGATACAATATAAAAGGAATCTCT
AGGCTTTGTCAGTTATCTCAGTTCAGA---GGCAATGAAACTGAACTCACTATTGAAAATAAACACAGAATTTTACAAAA
CCCATATCATATATCACCCATCTCTCCCATCAGGTCATCTGTTAAAACGATAAGTAAGAAAAAC---CTGTCAGAGGAAA
AGTTTGAGAAACAGTCAGTGTCACCTGAAAAAGCAATGGGAAATGAGAACATCATTCAAAGTACAGTGAGCACAATTAGC
CAAAATAATGTTAGAGAAAGAGCTGTTAAAGAAGGCAGCTCAAGC---------------------AGTACTAACGAAGT
AGGCTCTAGTATCGATGAAGCAGGTTCCAGT---------------------GGTAAAAACATTGGAGCAGAACTAGATA
GAAACAGAGGATCAAAATTAAGTGCTGTTCTCAGATTAGGTCTCATGCAACCCGAAGTCTATAAGCCAAGCCTT---CCT
ATAAGTAATTGTAAACACTCTGAAATAGAAAGGCAAGGAGAAAATGAAGTAGTAGTTCAGGCTGTTAATGCA--------
----TGTCAAATTTCAGATAACTTAGAACAG---CCTATGGGAAGTAGTCCTGTTTCTCAGGCTTGTTCTGAGACACCAG
ATGACCTATTAGATGATGACAAAATAAAGGAGAATAGCAGCTTTGCTGAAAGTGGCATTAAGGAAAGATCTGCTATTTTT
AGCAAAAGTGCCCAGGAA---GAACTCAGCAGGAGCCCTAGCCCCTTAACCCAT---ACACATTTGGCTCAGGGTCAGCA
GAGAAGGGCCGGGAAATTAGAGCC-------------------------
>RoundEare
---------------------NGCTCATTANAGCNTGAGAACAGCAGTTTACTGCTCACTGAGGACCAGATGAGTGTGGG
AAAGGCTGAATTCCGTCATGAAAGCAAGCAGCCCGGCTTAGCGAGGAGCCAGCAGAGCAGATGGGCTGAAAGTAAAGAAA
CATGTGACGAT---AGGCAGGCTCCCAGCGCAGAGGAAAGGGCAGTTCTGAATGCTGATCCCCAGAATGGG---------
------AGGGAAGAATCTCCATCCTCTGACCACCCTAGAGAT---TCCCAAGAT---GTTCCTTGGATAACACGGAATAG
CAGCATACAGAAAGTTAATGAGTGGTTTTCCAGACGTGATGAAACACGGACTTCCAACGGCTCCCACGGTGGGAGGCCTG
AGTCAGACACGGAAGGAGCCGACACGGTAGAAGCTCCGGAC------GAAGTGCGTGGATGCCCTGGCTCTCCAGAGAAC
ACAGCCTCGCCGGCCGGCGAGCCTCATGGCGCTTTAATGTGCGGAAGTGAAAGCGTCCACTCCAAACCAGTGGAGAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGAGCCACGTAACTGACAGGC
TAACTACGGGACTGTCCGCTCCAGACCCTCAGATAACACGA---------------------------------------
---------------------GAGCGTCCCTTCACCAACAAACTAAAGCGTAAAAGGAGAACTACACCGGGCCTTCACCC
AGAGGATTTTATCAAGACAGTGGATTTGACCGTTGTCCAGAAGACTCCTGAGAAGACCATTGAGGGAACTGACCAAACAG
AACAGAAC---------GGTCGTGTGATGGATATTGCTAACAGTGGTCACGGGAATGAAGCAAAAGGTGATTAT---GTT
CAGAATGAGAAGAGTTCTGACCCAACAGAA------TCACTGGGAGAAGAACCCGCTTTCAGAACTAAAGCTGGACCTAT
AAGCAGCAGCATAAGCACCGTGGGACTAGAATTGAATGTCCACGGTTCAAAAGCGCCCAGGAAGACTAAGCGGAGGGAGA
AGACTGCTGCCGAGCATACTTATGCACCTGGACTCGGGGTCAGCAAGAGCCCGAGCCCCCCTGCTCACGCCGGACTGCGG
ACGGACGGTTGTTCTGGCGGCGAGGAG---GCAAAGATCGGG---AATTCTGGGCAGAGGCCAGCCAGGCGGAGCAGCAA
GCTTCCGCTCGAGGAGGGTCAGGAGCCTGCAGCTGGGGCCAGCAAGGGTGACCGGTCAGATGCACCGATGAATAAGAGAC
TTGCCAATGATGCTTTTCCGGAACTAAATTTAACAAGCGTATCTGCCGTTTTTACTAATGGTTCAGGTTCTACTAAACTT
AAAGAGTGTGTCGATTCTAACCCTCAAGGAGAAGACACAGAAGAGAAC---CGAGGAACAGTTCAAGTGTCTAGTAGCAC
CAAAGACCTCAAAGATCTGATATTCAGTGGGGGAAGA---AGTTTGCAA---ACTGACAGATCTGTGGAGAGTCCCAATA
TTGNATTGGTACCTGAAACTGACTGTGACACTCAGGATAGCGTCTCCCTGCTGGCACCTGACACCCCAGGG---AAGGCA
GAA---ACAGCACCAGGCCAACGTGTGGGTGGGTGCGCAGCTGCTGGAAGCCCGAAGGAACTTATCCGTGATTGT---TC
GAAG------------GACACAGAGGGCGTTAAGGATCTCCCGAGATGTGAAGTTCAG---GAGACNNNNNNNNNNNNNN
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNTGCTCTG
TGTTCAAATCCAGGNAATCCAGGAAAGGAATGTGCAACCATGTATTCCCACTCCAGGTCCACAAGGAAACGAAGTCCAAA
AGTTACTCTTGAATGTGGACGAAAAGAA---CATCAGGGAGAGAAGGAATTTAATATGGAGCGTGCGCAGCCACCTTACA
CAACAGCAGGCTTTCCTAAGGGTTGTGAGAAAGACAAAACGCCAGGAGAGTGTGCCACATATACTATGAAAGGAATCTCT
AAGCCTTGTCAGTCATCTTCGTTCAGA---GGCAATGAAACTAAACTCACTATTGAAAATAAATATGGGATTTCACAAAA
CCCCTATCACATACCACCCATTTCTCCCGTCAGGTCATCTGTTAAAACTACAAGTAAGAAGAAC---CTGTCAGAGGAGA
AGTGTGAGGAACATTCAGTGTCACCTGCCAGAGCCGTGGGACGTGAGAACATCATTCAGAGTACAGCGGGCACTCCTAGC
CAGAACAAAACCAGGGAAAGTGCCGCCAGAGAAGGCAGCTCGAGC---------------------GGCACTAACGAAGT
AGGCTCCAGT------------------------------------------GGTGAAAACGGTCAAGCAGAGCCAGGCA
CAAACAGAGCATCAAAATTAAGCGCTCTTCTCAGATCAGGGCTCATGCAACCTGAAGTCTGTAAGCCGAGTCTT---CCT
CTGAGTAATTGTGAAGATCCTGAAATAAAAAGGCAA---GAAGATGGGGGAGTAGTGCAGGCTGTTAATGCAGATTTCTC
TCCGTGTCAAATTTTAGATAACCTAGAACAA---CCTCTGGGAAGCAGTCCCGCTTCTCGGGTTTGTTCCGAGACCCCAG
ACGACCTGTTAAATGATGACAAGGTAAAGGAGGATAACAGCTTTGCTGAAGGCGGCATGAAGGACAGATCTGCTGTTTTT
AGCAAAAGCGTCCTGAAA---GAATTCAGAAGGAGCCCCAGTCCCTTAGCCCAC---ACANTCTTGGCTCGGGGTCACCC
CAGAAGGGCCAGGAAACTCGAGTCCTCAGAAGAGGA-------------
>FalseVamp
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAATTTATTACTGACTGAAGACATAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGTGTTAGCAAGGAGCCAGCAGAGCAGATGGGCTAACAGTAAAGAAA
TATGTAATGAT---AGGCAGACTCCCAACACAGAGAAAAGGGTAGTTCTGAATGCTGATCCCTTGAATGAGAGAAAAGAA
CTGAATAATCAGAAACCTCTATGCTCTGACAGTCCTAGAGAT---TCCCAAGAC---GTTCCTTGGATAACACGTAATAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCCAGACGTGATGAAATACTAACTTCTCATGGTTCACATGATGGGACAGGTG
GATCAAATACAGAAGAAGCTGGTGCAGCAGAAATTCTAAAT------GAAGTAGATGGATATTCTGGTTCTTCAGAGAAA
ATAGCTTTAATGGCCAGTGATCCTCCTGGTGCTTCAATTTGTGAAAGTGAAAGAGTCTACTCCAAACCAGTAGAAAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTACAGGAGGAAGGCAAGCCTCCCTAACTTGGGCCACAGAGCTGAAAATC
TAATTATAGGAGCATCTGCTGTAGAACCTCAGATAATACAA---------------------------------------
---------------------GAGTGTCTCCTCATAAATAAACTAAAGCGTAAAAGGAGAACTACATCAGCCCTCCATCC
TGAGGATTTTATCAAGAAAGTAGATGTGGCAGTTGTTGAAAAGATTCCTGGAGATAGAATCAAGGGAACTGACCAAATAG
AGCAGCAT---------GGTCATGTGATGAATATTACTAATTATGGTCATGAGAATGAAACA------------------
------------AATGCTCACTCAACAGAA------TCACTGGACAAAGAATCTGCTTTTAGAACTAAAGCTGAACCTAT
AAGCAGCAGTATAAGTAATATGGAACTAGAATTAAATATCCACAGTTTAAAAGCACCTAAGAAGAATAGGCTGAGGAGGA
AGTCCTCTACAAGGCATATTCATGCACTTGAACTA---GTCAGTAGAAATCCAAGCCCACCTAATCATACTGAACTACAG
ATTGATAGTTGTTCTAGCAATGAAGAG---GTGGAGAAGAAA---AACTCTGACCAAATGCCAGCCAGACACAACAAAAA
TCTTCAACTTATAGAAGATAAAGAACCTGCAACTAGAGCTAAGAAGAGTAACAAGCCAGATGAACAAATAAATAAGAGAC
TTACCAGTGATGCTTTTTCAGAACTAAATTTAACAAACACACCTGGTTTTGTTACCAACAGTTCAAATTCTGATAAACTT
AAAGAGTTTGTCAATCCTAGCCTTCAAAGAGAAGAAATAGAAGAGCAT---CTGGGAACGATTAAAGTGTCTAATAGTAC
CAAAGACCCCAAAGATCTGATACTAAGTGGAGGAAGA---GGTTTGCAA---ACCGATCGTTCTATGGAGAGTACCAGTA
TTTCATTGGTACCTGATACTGATTATGGCACTCAGGCTAGTATGTCATTACTGGAACCTGACACCCCAGGG---AAGGTA
AAA---ACAGCACCAAATCGACGTGCAGGTGTGTGTGCTGCAATTGAAAACCCCAAGGAAATTATCCATGGTTGT---TC
TAAAGATACTAGAAATGACACAGGGGACTTTAAGGATCCACTAAGAGGTGAAGTTAAC---CACACNNNNNNNNNNNNNN
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN
NTTTCAAATCCAGGAAATCCAGAAAAGGAATGTGCAACAGTCTGTGCCCACTCCAGTTCCTTAAGGAACGAAAGTCCAAA
GGTCACTCTTGAATGTGGACAAAAAGAAGAAAATCACGGAAAGAAAGAGTCCAAAATCAAGCATGTGCAGGCAGTTCCAA
CAACTGCAGGCTTTCCTGTGGTTTGTGAGAAAGAAAAAAATCCAGGAGATTATGCCAAATATACCAAAAAAGGAGTCTCT
AGGCTTCGTCAGTCATCTCAGATCAGA---GGCAACAAAACCGAACTCACTGTTACAAATAAACATGGAATTTCTCAAAA
CCCATATCATATACCACCCATTTCTTCCATCAGGTCATCTGTTAAAACTATATGTAAGGAAAAC---CTGTCAGAGGAAA
ACCTTGAGGCATATTTGGTGTCACCTGAAAGAGCAATGGGAAATGAGAGCATTGTTCAAAGTACAGTGAGCACAGTTAGC
CAAAGTAACATTAGAGAAAGCACTTTTAAAGAGGGCAGCTCCAGCAATATTTATGAAGCAGATTCCAGTGCTAATGAAGT
AGGCTCTAGTATCAGTGAGGTAAGTTCCAGT---------------------GGTGAGAACATTCAAACAGAACTGGGTA
GAAACCAAGGACCAAAATTAAATGCTGTGCTCAGATTAGGTCTCATGCAACCTCAAGTCTATGTGCAAAGCCTT---CCT
GTAAGCAATTGTGAACATTCTGAAATAAAAAGGCAAGGAGAAAATGAAGGAGTAGTTGAGGCTGTTAATGCAGAATTCTC
TCCATGTCAAACTTCAGATAACCTGGAACAA---CCTATGGGAAGTAGTCATGCTTCTCAAATTTGTTCTGAGACACCGG
ATGACCTGTTAAACGATTATGAAATAAAGGAAAATGTTAGCTTT---------------AAGGAAAGATCTGCTGTTTTT
AGCAAAAGTGTCCAAAAAGAAGAATTGAGTAGAAGCCCTAGCCCCTTAATCCAT---ACATGTTTAGCTCAGGGTCACCG
AAGA---------------------------------------------
>LeafNose
TGTGGCACAAATACTCATGCCAGCTCTTTACATTATGAGCACAGCAGTTTATTACTCACTGAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAGCAGCCTGGCTTAGCAAGGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAGGAAAATGTAGTTCTGAATACTGATCCCCTGAATGGGAGAAAAGAA
CTGAATAAGCAGAAACCTCCATGCTCTGACAGTCCTAGGGAT---TCCCAAGTT---GTTGCATGGATAACACAGAATAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCCAGACGTGATGAAATATTAACTTCTCATAGCTCATGTTATGGGAGAGCTG
AATCAAATACAGAAGTATCTGGTGCAGTAGAAGTTCCACTT------GAAGTAGATGGATTTTCTGGCTCTACAGAGAAA
ATAACCTTAATGACCAGTGATCCTCATGATGCTGTAATATGTGAAAGTGGAAGAGTCCACTCCAAACCATTGGAAAGTAC
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTCAGCCACACAACTGAAAACA
TAATTATAGGAGCATCTGCTGTAGAACCTCAGATAACACAA---------------------------------------
---------------------GAGTGTCCCCTCACAAACAAACTAAGGCGTAAGAGGCGAACTACGTCAGGCCTTCATCC
TGAGGATTTCATCAAGAAAGTAGATTTGACAGTTGTTCAAAAGACTCCTGAAAAGATAATTGAGAGAACTCACCAAACAG
AACAGAAT---------GGTCATGTGATGAACATTACTGATAATGGTCATGGGAATGAAACAAAAGGTGATTAT---GTT
CAGAAAGAGGATAATGCTAACCCAACAGAA------TCATTGGAAAAAGAATCTGCTTTCAGAACTACAGCTGAACCTAT
AAGCAGCAGTATAAGCCATATGGAACTAGAATTAAATATCCATAGTTCAAAAGCACCTAAGAAAAATAGGCTGAGGAGGA
AGTCCTCTACCAGGCCTATTCATGCACTTGAACTAGTAGTCAGTGGAAATCCACGCCCACCTAGTCAGACTGAGCTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---GTGAAGAAAAAA---ATTTCTGACCAAGTGCCAGTCACACACAGCAAAAC
GCTTGAACTCATAGAAGATCAAGAACCTGCAAATGGAGTCAAGAAGAGGAACAAGCCAAATGAACAAATAAATAAGAGAC
TTACCAGTAATGCTTTTCCAGAACTAAATTTAACAAACATACCTGGTATATTG---AACCGTTCAAGTTCAAATAAACTT
CAAGAGTTTGTCAATCCTAGCCTTCAAAGAGAAGAAATAGAAGAGAGC---CTAGGAACAATTCAAGTGTCTAATAGTAC
CAAAGGCCTCAAAGATTTGATATCAAATGGGGGAAGA---GGCTTGCAA---ACTGGTCAATCTATGGAAAGTACCAGTA
TTTTATTGGTACCTGATACTGATTATGGCAGTCAGGATAGTATGTCATTACTCGAACCTGACACCCCAGGG---AAGGCA
AAG---ACTGCACCAAATCAACATGTGGGTGTATGTACAGCAGTTGAAAACCCCGAGGAACTTATCCATGGTGGT---TC
TAATGATACTAGAAATGACACAGAGAGCTTTAAGGATTCATTGAGACATGAAGTTAAC---CACGGTCAGGAGACAAGCA
TAGAAATGGAAGAGAGTGAACTTGATACACAGTATTTACAGGAAACATTCAAGGTTTCAAAGCGTCAATCATTTGCTCTG
TTTTCAAATCCAAGAAATCAAAGAAAGGAATGTGCAACAATCCAGTCCAGGTCC------TTAAGGAAACAAAGTGCAAA
AGTCACTCTTGAATGTGGACAAAAAGAAGAAAATCAGGGAAAGAAAGATTCTAAAATCAAGCTTGTACAGGCAGTTCATA
CAACTGCAGGCTATCCTGTGGTTTGTGAGAAAGATGAAAATCCAGGAGATTATGCCAAATACAGCACAAAAGGAGTCTCT
AGGCTTTGTCAATCATCTCTGTTCAGA---AGCAACGAAACTGAACTCACTATTGCAAATAAACATGGAATTTCTCAAAA
CCCACATAATATACCACATATTTCTCCCATCAGGTCATCTGTTAAAACTGTATGTAAGAAAAAC---CTGTCAGAGGAAA
ACTTGGAGGAATATCCAGTGTCACCTGAAAGAGCAATGGGAAATGAGAGCATCATTCAAAGTACAGTGAGCACAATTAGC
CAAAATAACATTAGAGAAAGCACTTTTAAAGAAAGCAGCTCAAGCAATNTTTATGAAGCAGATTCCAGTACTAATGAAGT
AGGCTCTAGTATCAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAGAACTCGGCA
GAAACAGAGGACCGAAATTAAATGCTGTGCTCGGATTAGGTCTCGTGCAACCTGAAGTCTATAGGCAAAGCCTT---CCT
GTAAGTAATTGTCAACATCCAGAAATAAAAAGGCAGGGAGAAAATGAAGGAATAGTTCAGGCTGTTAGTGCAGACTTCTC
TCCATGTCAAATTTCAGATAACCTAGAACAA---CCTACGGGAAGTAGTCATGCTTCTCAGGTTTGTCCTGAGACACCGG
ATGACCTGTTAAATGATAACGAAATAAAGGAAAATGACAGCTTTGCTGAAAGTGACATTAAGGAAAGATCTGCTGTTTTT
AGCAAAAGTGTCCAGAAAGGAGAATTCAGAAGGAGCCCTAGCCCCGTAGCTCAC---ACACGTTTGGCTCAGGGTCACCA
AAGACGGGCCAGGAAATTAGAGTCCTCAGAAGAGGA-------------
>Horse
TGTGGCACAAATACTCATGCCAGCTCATTGCAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAAGAGCCAACAGAGCAGACGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGGCCCCCAACTCAGAGGAAAAGCTAGTTCTGAATGCTGATCCGCTGTATGGGAGAGAAGAA
CTGAATAAGCAGAAACCTCCACGCTCTGACAGTCCTAGAGAC---TCCCAAGAT---GTTCCTTGGATAACACTGAATAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCCAGAAGTGAGGAAATGTTAACTTCTGATGACTCATGTGACGGAGGGCCTG
AATCAAATACAGAAGTAGCTGGTGCAGTAGAAGTTCCAAAT------GAAGTACGTGGATATTCTGGTTCTTCAGAGAAA
ATAGACTTAATGGCCGGTGATCCTTCTAGTGCTTTAATATGTGAAAGTGAAAGAGTCCGCTCCAAACCAGTAGAGAATAA
T---ATTGAAGATAGAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCTTCCCTAACTTGAGCCACATAACTGAAGATC
TAATTATAGGGGCATCTGCTATAGAACCTCAGATTACACAA---------------------------------------
---------------------GAGCGTCCACTCACAAATAGAGTGAAGCATAAAAGGAGAACGTCATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGGCAGTTGTCCAAAAGACTCCTGAAAAGATAATTGAGGGAACTGACCAAATAG
AGCAGAAC---------AGTCATGTGATGAATATTACTCCTAATGGTCATGGGAATGAAACAAAAGGCGATTAT---GTT
CAGAATGAGAAAAACGCTTACCTAACAGAA------TCATTGGAGACAGAATCTGCTTTCAGAACTAAAGCTGAACCTAT
AAGCAGCAGCATAGGCAATCTGGAACTGGAATTAAATATCCACAGTTCAAAAGCACCTAAGAAGAATAGGCTGAGGAGGA
AGTCTTGTACCAAGCAGATTCATGCACTTGAACTAGTAGTCAGTAAAAATCCAAGCCCACCTAATCATACTGAACTACAA
ATCGATAGTTGTTCTAGTAGTGAAGAG---ATGAAGAAAAAA---AATTCTGACCAAATGCCGGTCAGACACAGCAAAAA
GCTTCAACTCATGGAAGATAAAGAACCTGCCACTGGAGCCAAAAAGAGTAACAAGCCAAATGAACAAATAAATAAAAGAC
TTGCCAGTGATGCTTTTCCAGAGCTAAAATTAACAAACATACCTGGTTTTTTTACTAACTGTTCAAGTTCTAATAAACTT
CATGAGTTTGTCAATCCTAGCCTTCAAAGAGAAGAAATAGAACAGAAC---CTAGGAGCAAATCGACTGTCTAATAGTGC
CAAAGACCCCAAAGATCTGATATTAAGTGGAGGAAAA---TGTTTGCAA---GCTGAAAGATCTGTAGAGAGTTCCGGTA
TTTCATTGGTACCTGATACTGATTATGGGACTCAGGATAGTATCTCACTGCTGGAAGCTGACACCCTAGGG---AAGGCA
AAA---ACAGCACCAAATCAATGTGCAAATCTATGCGCAGCAATTGAAAACCCCAAGGAACTTACCCATGATTGT---TC
TAAGGATACTAGAAATGATACACAGGGCGTTAAGGATCCATTGAGACGTGAAGTTAAC---CACACTCAGGAGACAAGCA
TAGAAATGGAAGAGAGTGAATTTGATACGCAGTATCTACAGAATATGTTCAAGGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATCCAGGAAGTCCAGAAAAGAAGTGTGCAACAGTCAGTGCCCACTCCAGGTCCTTAAGGAAACAAAGTCCAAA
AGTCACTCTTAAATGTGGACAAAAAGAAGGAAAGGAGGGAAAGAAAGAGTCTAAAATCAAGAATGTGCAGTCAGTTCACA
CAACTGTGGGCTTTCCTGTGATTTGTCAGAAAGATAAGAAGCCAGGTGACTATGTCAAATGTAGCACAAAAGAAGCCTCT
AGGCTTTGTCAGTCATCTCAGTTCAGA---GGCAACGAAACNGAACTTATTACTGCAAATAAACATGGAATTTCACAAAA
CCCATATTATATACCATCACTTTCTCCCATCAGGTCATCTGTTAAAACTGTATGTCAGAAAAAC---CTGCCAGAGGGAA
AGCTTGAGGAACAGTCACTGTCACCTGAAAGAGCAATGGGAAATGAGAGCATTGTTCAAAGTACAGTGAGCACAATTAGC
CAAAATAACATTAGAGAAAGCACATTGAAAGAAGTCAGCTCAAGC---------------------AGTATTAATGAAGT
AGGCTCTAGTATTAATGAAGTAGGTTCCAGT---------------------GGTGAACACATTCAAGCAGAACTAGGCA
GAAACAGAGGACCTAAATTAAATGCTATTCTCAGATTAGGTCTTATGCAACCTGAAGTCTATAAGCAAAGTCTT---CCT
ATAAGTAATTGTAAACATCTGGAAATAAAAAGGCAAGGAGAAAAGGAA---GTAGTTCAGGCTGTTAACGCAGACTTTTC
TCCGTGTCTAATTTCAGATAACCTAGAACAA---CCTATGGGAAGTAGTTGTGCTTCTCAGGTTTGTTCTGAGACACCTG
ATGACCTGTTAAATGATGACGAAATAAAGGAAAATATCAGCTTTGCTGAAAGTGGCGTTAAGGAAAGATCTGCCGTTTTT
AGCAAAAGCGTCCAGAAAGGAAAGTTCAGAAGGAGTCCTAGCCCTATAGGCCGT---ACGTGTTTGGCTCAGGGTCACCA
AAGACGGGCCAGGAAATTAGAGTCCTCAGAAGAGAACACGTCTAGTGAG
>Rhino
TGTGGCACGAATACTCATGCCAGCTCATTGCAGCATGAGAACAGCAGTGTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGTGAACAGCCTGGTTTAGCCAAGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCCAACTCAGAGAAAAAGCTAGTTCTGAACGCTGATCCYCTGTATGGGAGAAAAGAA
CTGAATAAGCAGAAACCTCCATGTTCTGACAGTCCTAGAGAT---TCCCAAGAT---ATTCCTTGGATAACACGGAATAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAAATATTAACTTCTGATGACTCACATGATGGGGGGCCTG
AATCAAATACTGAAGTAGCTGGTGCAGTAGAAGTTCAAAAT------GAAGTAGATGGATATTCTGGTTCTTCAGAGAAA
ATAGGCTTAATGGCCAGTGATCCTCCTGGTGCTTTAATATGTGAAAGTGAAAGAGTCCACTCCAAACCAGTAGAGAATAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCTTAACTTGAGCCACATAACTGAAGATC
TAATTATAGGAGCATCTGCTATAGAATCTCAGATTACACAG---------------------------------------
---------------------GAGCGTCCCCTCACAAATAAACTGAAGCATAAAAGGAGAACTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGGCAGTTGTCCAAAAGACTCCTGAAAAGATAATTGAGGGAACTGACCAAATAG
AGCAGAAC---------GGTCGTGTGATGAGTATTGCTAATAATGGTCATGAGAATGAAACAAAAGGTGATTAT---GTT
CAGAAAGAGAAAAATGCTAACCCAACAGAA------TCATTGGAGAAAGAATCTGCTTTCAGAACGAAAGCTGAACCTAT
AAGCAGCAGCATAAGCAATCTGGAACTGGAATTAAATATCCACAGTTCAAAAGCACCTAAGAAGAATAGGCTGAGGAGGA
AATCCTCTACCAGGCATATTCATGCACTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAATCATACTGAACTACAG
GTTGATAGTTGTTCTAGCAGTGAGGAG---ATGAAGAAGAAA---AGTCCCAGCCAGGTGCCAGTCAGACATAGCAGAAA
GCTTCAACTCACMGAAGATAAAGAACCCGCAGCTGGAGCCAAGAAAAGTAACAAGCCAAATGAACAGATAAATAAAAGAC
TCGCCAGTGATGCTTTTCCAGAACTAAAATTAACAAACGTACCTGGTTTTTTTGCTAACTGTTCAAGTTCTAATAAACTT
CAAGAGTTTGTCAATCCTAGCCTTCAAAGAGAAGACATAGAACGGAAC---CTAGGAGCAATTCAAGTGTCTAATAGTAC
CAAAGACCCCGAAGATCTGATATTAAGTGGAGGAAGA---GGTTTGCAR---GCTGAAAGATCTGTAGAGAGCACCAGTA
TTTCATTGGTACCTGATACTGATTATGGCACTCAGGGTAGTATCTCATTACTGGAAGCTGACACCCTAGGG---AAGGCA
AAA---ACAGCACCAGATCAACGTGCAAGTCTATGTGCAGCAATTGAAAACCCCAAGGAACTTATCCATGATTGT---TC
TAAAGATACTAGAAATGACACAGAGGGCCTTAAGGATCCATTGAGATGTGAAGTTAAC---CACACTCAGGAGACAAGCA
TAGAAATGGAAGAGAGTGAACTTGATACACAGTATCTACAGAATACGTTCAAGGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATTCAGGAAATCCAGAAAAGGATTGTGCAGCAGTCTCTGCCCACACCAGGTCTTTAAGGAAACCAAGTCCGAA
AGTCACTCTTGAATGTGGACAAAAAGAAGAAAATCAGGGAAAGAAAGAGTCTAAAGTCAAGCATGTGCAGTCAGTTCATA
CAACTGTGGACTTTCCTGTGGTTTGTCAGAAAGATAAGAAACCAGGTGATCATGTCAAATATAGCATAAAAGAACTCTCT
AGGCTTTGTCAGTCATCTCAGTTCAGA---GGCAATGAAACTGAACTCATTACTGCAAATAAACGTGAACTTTCACAAAA
CCTGTGTTATATACCATCACTTTCTCCCATCAGGTCATCTGTTAAAACTATATGTAAGAAAAAT---GTGTCAGAGGAAA
AGCTTGAGGAACATTCAGTGTCCCCTGAAAGAGCACTGGGAAACAAGAGCGTCATTCAAAGTACAGTGAGCACAATTAGC
CAAAATAACATTAGAGAAAGCACTTTTAAAGAAGTCGGCTCAAGCAGTATTAATGAAGTAGATTCCAGTACTAATGAAGT
AGGCTCTAGTATTAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTGAAGCAGAGCTAGGCA
GAAACAGAGGACCTAAATTAAATGCTATTCTCAGATTAGGTCTTATGCAACCTGAAGTCTATAAGCAAAGTCTT---CCA
ATAAGTAATTGTAAACATCCGGAAATAAAAAGGCGAGGAGAAAATGAAGGAGTAGTTCAGCCTGTTAATGCAGATTTCTC
TCCGTGTCCAATTTCAGATAACCTAGAACAA---CCTGTGGGAATTAGTTGTGCTTCTCAGGTTTGTTCTGAGACACCTG
ATGACCTATTAAATGACAACGAAATAAAGGAAAATATCAGCTTTACTGAAAGTGGCATTAAGGAAAGATCTGCTATTTTT
AGCAAAAGCGTCCAGAAAGGAGAATTCAGAAGGAGCCCTAGCCCTTTAGCCCGT---ACATGTTTGGCT---------CA
AAGAGGGGCCAGGAAATTAGAGTCCTCAGAAGAGAACATGTCTAGTGAG
>Pangolin
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATAAATGTAGA
AAAGACTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCTGCAAAGCAGATGGGCTGAATGTAAAGAAA
CATGTAACGAT---AGGCAGGCTCTCAGCACAGGGAAAAAGGTAGTTCTGAATGCTGATCCCCTGTGTGGGAGAAAAGAA
CTGAATAAGCAGAAACCTTCATGCTCTGACAGTCCTAGAGTT---TCTCAAGAC---GTTCCTTGGATAACACTAAATAG
TAGCATACRGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAAATGTTAACTTCTGATGATCCATGTGATGGGAGGTCTG
AATCAAATACTGAAGTAGCTGGTGCAGTAGAAGTTCCAAAT------GAAGTAGATGAAAATTGTGGTTCTTCAGAGAAA
AAAGACTTAATGGCCAGTGATCCTCATGATGCTTTAATACGTGAAAGTAAAAGAGGCCACTCCAAACCAGTAGAGAGTAA
T---ACTGAAGATAAAATATTTGGGAAAACCTATCGGAAGAAGGCAAGTCTCTCTCACTTGAGCCACGTAACTGAAAATC
TAATTATTGGAGCATTTGCAGTAGAACCTCAGATAACACAA---------------------------------------
---------------------GAGCGTCCCCTCAGAAATAGAGTAAAGCGTAAAAGGAGAACTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGGAAGTTGTTCAAAAGACTCCTGAAAAGATAATTGAGGGAACCGACCAAATAG
AGCAGAAT---------GCTCTTCTGATGAATAGAACAAATAACGGTCATAAGAATGAAACAAAAGGTGATTAT---GTT
CAGAAAGAGAAAAATGCTAACCCAACAGAA------TCATTGAAAAAAGAACCTGCTTTCAGAACTAGAGCTGAACCTAT
AACCAGCAATATAAGCAATATGGAGCTAGAATTAAATATCCATAGTTCAAAAGTACTTAAGAAGAATAGGCTGAGGAGGA
AGTCTTCTACCAGGCACATTCATGCACTTGAACTAGTAGTCAATAGAAATCCAAGCCCCCCTAAACATACTGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAGTTGATGAAA---------------AACCAAATACCAGTCAAACATNCCAAAAA
GCTTCAACTCAAGGAAGATAGAGAACCTGCATCTAGAGCCAAGAAGAGTAACAAGCCAAATGAACAAATAAATAAAAGAT
TTACCAGTGACACTTTTCCAGAACTAAATTTAACAAACATACCTGGTTTTTTTAGTAAATGTTCAAGTTCTAATAAACTT
CAAGAGTTTGTTGACCCTAGCCTTCAAAGAGAAGAAATAGAAAATAAT---CTAGAAACAATTCTA------------AC
CAAAGACCCCAAAGATGTGATATTACATAGAGGA------GGTTTGCAA---ACTGAAAGATGTGTAGAGAGTAACAGTA
TTTCATTGGTACCTGATACTGATTACGGCACTCAGGATAGTATCTCATTACTGGAAGCTGACACACTAGGG---AAGACA
AAA---ACAGCACCAAATCAATGTGCAAGTCTGTGTGCAGCAATTGAAAACCCCAAGGAACTTACCCATTGTTGT---GC
TAAAGATATTAGAAATGACACAGAGAGCTTTAAGGATCTATTGAGACATGAAGATAAC---CACACTCAGGAGACAAGCA
TAGGAACGGAAGAGAATAAACTTGATAAGCAGTACTTACAGAATACTTTCAGGGTTTCAAAGCATCAGTCATTTGCTCAG
TTTTCAAATATGGGAAATCCAGAAAAAGAATGTGCAGCAGTCAGTGCCCACTCTGGGTCCTTAAGGAAACAAAGTCCAAA
AGTCACTCTTGCATATGGACAAAAAGAAGAAAATGAGGGAAAGAAAGAGTCTGAAATCAAGCATGTTCAAACAATTCATA
CAACTGCAGGCCCTCTTGTGGTTAGTCAGAAAGATGAGAAGCCAGGTGATTATGTAAAATTTGGCATAAAAGGAGTCTCT
ACGCATTGTCAGTCATCTCAGTTCAGA---GGCAATAAAACTGAACTTATTTTTGCAAATAAACCTGGAATTTCACAATA
CCCATATCATATATCATCAATTTCTCCCATCAGGTCATCTGTTAAAATAATATGTAAGGAAAAC---CTGTCAGAGGAAA
AGTCTGTGGAACATTCGATGTCATTGGAAAAAGCAGTGGGAAACAAGAGCATCATTCAAAGTACTGTGAGCACAATTAGC
CAAAATAACATTAAAGGAAACAATTTTAAAGATGGCAGCTCCAGCAGCATTAATGAAATAGGTTCCAGTACTAATGAAGT
AGGCTCTAGTATTAATGAAGTAGGTTCCAGT---------------------GGTGAAAAAATTCAAGCAGAACTAGGTA
GAAACAGAGGACCTAAATTAAGTGCTGTGCTCAGATTAGGTCTTATGCAACCTGAGGCCTATAAGCAAAATCTT---CTT
ATAGGTAATCGTAAACACCCTGAAATTAAAAGACAAGGAGAAAAAGAAGGAGTAGTTCAGGTTGTTAATGCTGATTTCTC
TCCATGTCTAATTTCAGATAACCTAGAACAA---CCTATGGGAAGTAGTCATGCTTCTCAGGTTTGTTCTGAGACACCTG
AGGACATATTAAATGGTGATGAAATAAAGGAAAATATCGGCTTTGCTGAAAGTGGTATTAAGGAAAGATCTGCTGTTTCT
AGCAAAAGTGTCCAGAAAGGAGAATTCAGAAAGAGCCCAAGCCCTGTAGTCCAT---ATGAGTTTGTCTCAGAGTCACCA
AAGAAGAGCTGGGATAATAGAGTCTTCAGAAGAGAACATGTTTAGTGAG
>Cat
TGTGCCACAAATACTCGTGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGGCAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATGAAAGCAAACAGCCTGGCGTAGCAAGGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAGAAAAAGGTAGTTCTGAATGCTGATCCCCTGTGTAGGAGAAAA---
CTGAGTAAGCAGAAATCTCCATGCTCTGACAGTCCTAGAGAT---TCCCAAGAT---GTACCTTGGATAACACTGAATAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAAATGTTAACTTCTGATGACTCACATGATGAGGGATCTG
AATCGAATCCTGGAGTAGCTGGTGCA---GAAGTTCCAAAT------GTAGTGGATGGATATTCTGGTTCTTCTGAGAAA
ATAGACTTAATGGCCAGTGATCCTCATGATGCTTTGATATGTGAAAGTGAAAGAGTTCACACCAAACCAGTAGAGAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTTCCTAACTTGAGCCACACAAGTGAAGATC
TCATTATAGGAGCATGTGCTATAGAACCTCAGATAACGCAA---------------------------------------
---------------------GCCTATCCCCTCACAAATAAAACAAAGCGTAAAAGGAGATCTACCGCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGGCCATTGTTCAAAAGACTCCTGAAAAGCTAATTGAGGGAACCGATCGAATAG
GGCAAAAT---------GGCCATGTGATGAATAGAACAAATAATGGTCCTGAGAATGGGACAAAAGGTGATTAT---GTT
CAGAAAGAGAAAAATGCTAAGCCAACAGAA------TCATTGGAAAAAGAATCTGCTTTTAGAACCAAAGCTGAACCAAT
AAGCAGCAATATAAGTAATATGGAATCAGAATTAAATAGCCACAGTTCAAGGGCACCTAAGGAGAACAGGCTGAGGAGGA
AGTCCTCTACCAGGCACATGCGTGCGCTGGAATTAGTAGTCAATAGAAATCCAAGCCCACCTGATCATACCGAACTACAG
ATTGATAGTTGTTCTAGCAGTGAAGAGATGGTGAAAAGAAAA---AGTTCGGAACAAATGCTAGTCAGACACAGCAAAAC
ACTTCAACTCGTGGAAAATAAAGAACCTGCACCTGGAGCCAAGAAGCGTAACAAGCCAAGTAAACAAATAAATAAAAGAC
TTGCCAGTAACACTTTTCCAGAGCTAAATTTAACAAACATACCTGGGGTTTTTACTAACTGTTCAAGTTCTAATACACTT
CAAGAGTTTGTCAACCCTGGCATTCAAAGAGAAGAACTAGAAGAGAGC---CGAGGAACGATTCACGTGTCTGATAGGAC
CAGAGATCCCAAAGCGCTGGTATCGAGTGGAGGAAGA---AGTTTGCAA---ACTGAAAGATCTGTAGAGAGTACCAGTA
TTTCATTGGTACCTGATGCCGATTATGGCACTCAGGATAGTATCTCATTACTGGAAGCTGACACCCTAGGG---AAGGCA
AAA---ACAGCACCAAATCAACGTGTGAGTCTGTGTGCAGCAATTGAAAACCCCAAGGAAGCTATCCGTGGTTGT---TC
CAAAGATACTAGAAATGGCACAGAGAGTTTTACAGATCCTCTGAGACGTGAAGATANC---CATACTCAGGAGACAAGTA
TAGAAATGGAAGAGAATGAACTTGATACGCAGTGGTTATACAATACGTTCAAGGGTTCAAAACGTCAGTCATTTGCTCTG
TTTTCAAATCCAGGAAACCCAGAAAAGGAATGTGCTACAGCCTGGGCCCGTTCCACGTCCTTAAGGAAACAAAGTCCAAA
AGTCGCTCTTGAATATGAACAAAAAGAAGAAAATCAGGGAAAGAATCAGTCTGAAATCAAGCATGTGCAGGCAGTCCGTG
CAACTGCAGGCTTTTCTGCAGTCAGTCAGAAAGTGGAGAAGCCAGGTGATTATGCCAAATGTAGCATAAAAGGAGTCCCT
GGGCTCTGTCAGTCATCTCAGTTCAGA---GGCAATGAAACTGAACTCTTTATTGCAAATAACCATGACATTTCAAAAAA
CCCTTATCATATACCACCACTTTCTCCCATCAGATCATCTGTTAATGCTGTATGTAAGAAAAAC---CTGTCAGAGGAAA
AGTTTGAGCAGCGTTCAATGTCACCTGAAAGAGCAGTGGGAAATGAGAGCGTCATTCAAAGTACAGTGAACACAATTAGC
CAAAATAACATTAGAGAAAACACTTTTAAAGAAGTTAGCTCAAGCAGTGTTAATGAAGTAGGTTCCAGTGCTAATGAAGT
AGGCTCTAGCATTAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAACAGAACTGGGTA
GAAACCGAGGACCTAAGTTAAGTGCTATGCTCAGGTTAGGTCTTATGCAACCTGAAGTCTATGAGCAAAGTCTT---CCT
ATAAGTAATTGTAAATGTCCAGAAATGAAAAGGCAAGGAGAAAATGAAGGAGTAGTTCAGTCTGTTAATGCAGATTTTTC
TCCATGTCTAATTTCCGATAATGTAGAACAA---CCTATGGAAAGTAGCCGTGCTTCTCAGGTTTGTTCTGAGACACCCA
ATGACCTATTAAATGGTGATGAAATAAAGGGAAAAATCAGCTTTGCTGAAAGT---GCTAAGGAAAGATCTGCTGTTTTT
GGCAAGAGTGTCCAGAAAGGAGAATTCAGAAGGAGCCCTAGCCCTTTAGACCAT---ACACATCTGGCTCAGGGTCACCA
AACAGAGACCAGGAAGTTAGAGTCCTCAGAAGAGAACGTGTCTAGTGAG
>Dog
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAACACAGAATGAATGTAGA
AAAGGCTGAAATCTGTAATAACAGCAAACAGCCTGGCTTAGCAAGGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGATTCCCAGCACAGAGAAAAAGGTAGTTGTGAATGCTGATCTCCTGTGTGGGAGAAAAGAA
CTGAATAAACAGAAACCTCCACACTCTGATAGTCCTAGAGAT---TCCCAAGAT---GTTCCTTGGATAACACTGAATAG
TAGCATACGGAAAGTTAATGAGTGGTTTTCCAGAAGTGACGAAATATTAACTTCTGATGATTCACATGACAGAGGATCTG
AATTGAATACTGAAGTAGGTGGTGCAGTAGAAGTTCCAAAT------GAAGTGGGTGAATATTCTGGTTCTTCTGAGAAA
ATAGACTTAATGGCCAGTGATCCTCAGGATGCTTTCATATGTGAAAGTGAAAGAGTCCACACCAAGCCAGTAGGAGGTAA
T---ATCGAAGATAAAATATTTGGAAAAACCTATCGGAGGAAGGCAAGCCTCCCTAAGGTGAGCCACACAACTGAAGTTC
TAACTATAGGAGCGTGTGCTATAGAACCTCAGACAATGCAA---------------------------------------
---------------------ACCCATCCCTTCATGAATAAAGCAGAGCATAAAAGGAGAACTACATCTAGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGAGTTAGGCATTGTTCCAAAGACTCCTGAAAAGCTAATTGAGGGAATCAACCAAATCA
AGCGAGAT---------GGTCATGTGATAAATATTACAAATAATGGTCCTGAGAATGAAACAGAAGGTGATTAT---GTT
CAGAAAGAGAAAAATGCTAACCCAACAGAA------TCATTGGAAAAAGAATCTGCTTTTAGAACCAAAACTGAACCAAT
GAGCAGCAGGATAAGCAATATGGAACTGGAATTAAATAGCTCCAGTTCAAAAGCACCTAAGAAGAACAGGCTGAGGAGGA
AGTCCTCTGCCAGGCACACTTGTGCCCTTGAATTCGTAGTCAATAGAAATCTAAACCCACCTGATCATAGTGAACTACAG
ATTGAAAGTTGTTCTAGCAGTGAAGAG---ATGAAGAAACAG---CATCTGGACCAAGTACCAGTCAGACACAACAAAAC
ACTTCAGCTCATGCAAGATAAAGAACCTGCAGGTAGAGCTAAGAAAAGTAGTAAGCCAGGAGAACAAATAAATAAGAGAC
TCGCCAGCCATGCTTTTCCAGAGCTAACTTTAACAAATGTATCTGGTTTTTTTGCTAACTATTCAAGTTCTAGTAAGCCT
CAAGAGTGCATCAACCCTGGCCTTCGAAGAGAAGAAATAGAAGAGAGC---CGAAGAATGACTCAAGTGTCTGATAGTAC
CAGAGATCCCAAAGAGCTGGTATTGAGTGGAGGAAGA---GGTTTGCAA---ACTGAGAGATCTGTAGAGAGTACCAGTA
TTTCATTGGTACTTGATACTGATTATGGTACACAGGACAGTATCTCATTACTGGAAGCTGACACCCTGAGG---AAGGCA
AAA---ACAGTATCAAATCAACAGGCGAATCTGTGTGCAACAATTGAGAACCCCAAGGAACCTATCCATGGTTGT---TC
TAAGGACACTAGAAATGACACAGAGGGTTTTGTAGTTCCATTGACGTGCAAAGATAAC---CACACTCAAGAGACAAGCA
TAGAAATGGAAGAGAGTGAACTTGACACGCAGTGCTTACGCAATATGTTCAAGGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCATATCCAAGAGATCCGGAAGAGGACTGTGTAACAGTCTGTCCCCGCTCTGGGGCCTTTGGAAAACAAGGTCCAAA
AGTCACTCTAGAATGTGGACAGAAAGAAGAAAGTCAGGGAAAGAAAGAGTCTGAAATCAGACATGTGCAGGCAGTTCATA
CAAATGCAGGCTTTTCTGCAGTTAGTCAGAAAGCTAAGAAGCCAGGCGATTTTGCCAAATGTAGCATAAAGGGAGTCTCT
CGGCTTTGTCTGTCATCTCAGTTCAAA---GGCAAGGAAACTGAACTCCTTATTGCAAATTACCATGGAATTTCCCAAAA
CCCTTATCATATACCACCACTTTCTCCCATCAGATCATGTGTTAAAACTCTATGTCAGGAAAAC---CTGTCAGAGGAAA
AGTTTGAGCAACATTCAATGTCACCCGAAAGAGCAGTGGGAAATGAGAGAGTCATTCAAAGTACAGTGAGCACAATTAGC
CAAAATAACATTAGAGAATGTGCTTCTAAAGAAGTCGGCTCAAGCAGTGTTAATGAAGTAGTTTCCAGTACTAATGAAGT
AGGCTCTAGTGTTAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAGAACTAGGTA
GAAACCGAGGACCTAAATTAAATGCTATGCTCAGATTAGGTCTTATGCAACCTGAAGTCTGTAAGCAAAGCCTT---TCT
TTAAGTAATTGTAAACATCCAGAAATGAAATGGCAAGGACAAAGTGAAGGAGCAGTTCTGTCTGTTAGTGCAGATTTCTC
TCCATGTCTGATTTCAGATAACCCAGAACAA---CCTATGGGAAGTAGTCGGTCTTCTCAGGTTTGTTCTGAGACACCTG
ATGACCTATTAAATGGTGACAAAATAAAGGGAAAAGTCAGCTTTGCTGAAAGTGACATTAAGGAAAAATCTGCTGTGTTT
AGCAAAAGTGTCCAGAGTGGAGAGTTCAGCAGAAGCCCTAGCCCTTCAGACCAT---ACACGTTTGGCCCAGGGTTACCA
GAGAGGGACCAAGAAATTAGAGTCCTCAGAAGAGAACATGTCTAGTGAG
>Llama
TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAGGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGTCTTAGCAAGGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGACA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAGAAAAAGGTGGCTCTGAATGCCGATCGCTTATATGGGAGCGAAGAA
CTGAATAAGCAGAAACCTGCATGCTCTGACAGTCCTAGAGAT---TCCCAAGAT---GTTCCTTGGATAACACTGAATAG
TAGCATACAGAAAGTGAATGAGTGGTTTTCCAGAAGCGACGAAATGTTACCTTCTGATGACTCACATGAAGTGGGGCCTG
AATCAAATACTGAAGTAGCTGGTGCAGTGGAAGTTCCAAAT------GAAGTAGATGGCTATTCAGGCTCTTCAGAGAAA
ATAGACTTAATGGCCAGTGATCCTCATGGTGCTTTAAAATGTGAAAATGAAAAAGTCCACGCCAAACCAGTAGGGAGTAA
C---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGACCCACAGAGCTGAAGATC
TAATTCTAGGAGCATCTGTTCTAGAGCCTCAGATAACACAA---------------------------------------
---------------------GAGCGCCCCTTCACAAATAAACTAAAGCGTAAAAGGAGAACTCTACCAGGTCTTCATCC
TGAGGATTTTATCAAGAAAGTCGATTTGGCCGTTGTTCAAAAGTCTCCTGAAAAGATAATTGAGCGAACAGACCAAACAG
AGCAGAAT---------GGTCATGGGATGAATATTACTAGTAATGGTCATGAGAATGAAACAAACGACGATTAT---GTT
CAGAAAGAGAAAAATGCTAACCCAACAGAA------TCATTGGAAAAAGAATCTGCTTTCAAAACTAAGGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTGAATACCCATAGTTCAAAAGCACCTAAG---AATAGGCCGAGGAGGA
AGTCCTCTACCAGGCAGATTCATGCACTTGAACTAATAGTCAGTAGAAACCCAAGCCCACCTAATCACACTGAACTACAG
ATTGAGAGTTGTTCCAGCAGTGAAGAG---ATGAAGGAAAAA---CATTCTGACCAAATGCCAGTCAGGCACCGCAAAAA
GCTTCAGCTCACGGGAGATAAAGAACCTACGACTGGAACCAAGAAGAGTAACAAGCCACATCAACAAATAAATAAAAGAC
TTGTCGGTAACACTTTTCCAGAACTAAATTTAACAAACACACCTGGTTTTTTTACTAAGTGTTCAAGTTCTAATAAACTT
CAAGAGTTTGCCAATCCTAGCCTTCAAAGAGAA---------GAGAAC---CCAGGAGCAATTCAAGTATCGAACAGTAC
CAAAGACCCCAAAGTTCTGATATTAAGTGGAGGGAGA---GGTTTACAA---ATTGAAAGATCTGTAGAGAATACCAGTA
TTTCCTTGGTACCTGAAACTGATTATGACACTCAGGACAGTGTCTCATTACTGGAAGCTGACACCCTAGGG---AAGGCA
AAA---ACAGCACCAAATCAATGTGTGAGTCTCTGTGCAGCAACTGAAAACCCCAAGGAACTTATCCATAGTTGT---TC
TAAAGATACTAGAAATGGCACAGCAGGCTTTAAGGATCCATTGGGATGTGATGTTAAT---CACACTCAGGAGGCAAGCA
TGGAAGTGGAAGAGAGTGAACTTGATACTCAGTATTTGCAGAATACGTTCAAGGTTTCAAAGCGTCAGACATTTGCTCTG
TTTTCAAATCCAGGAGATTCAGAAAAGGAATGTGCAACGATCTATGCCCACTCTGGGCCCTTAAGGGAACAAAGTCCAAA
AATCACTCTTGAATGTGGACAAAAAGAAGAAAATCAGAGAAAGAGCAAGTCTGAAATCAAGCATATGCAGGCAGTTCATA
CAACTTTGAACTTTCCTGTGGTTGGTCAAAAAGATAAG---CCGAGTGATTATGCCAAATATAGCCCAAAAGGAATATCT
AGGCTTTGTTGGCCATCACAGCTCAGA---GGCAATGAATCTGAGTTCATTATTGCAAATAAACATGGGATTTTACAAAA
CCCATATCTTATAACATCACTTTCTCCTAACAGGTCATCTGTTAAAACTATGTGTAAGAAAAAC---CCGTCCGAGGAAA
AGCTTGAGAAATGTGTCATATCACCTAAAAGAGTGATGGGAAACGAGAGCACCATTCAAAGTATAGTGAGTGCAATGAGC
CAAAATAACATTAGAGAAAGCACTTTTAAAGAAGTCAGCTCAAGCAGTGTCAATGAAGTAGGTTCCAGTACTAATGAAGT
AGGTTCTAGTATTAATGAAGTAGGTTCCAGT---------------------GGCGAAAACATTCAAGCAGAACTAGGTA
GAAACATGGGACCTAAATTAAATGCTATGCTCAGATTAGGTCTTTTGCAACCTGAAGTCTGTAAGCAAAGTCTT---CCT
GTAAGTAATTGTAAACAACCTGAAATAAAAAGGCAAGGAGAAAATGAAGGCATCTTTCAGGCTGTTAATACCGACTTCTC
TCCATGTCTAATTTCAGATAACCTAGAACAA---CCTATGGGAAGCAGTCATGCTTCTCAGGTTTGTTCTGAGACACCTG
ATGACCTGTTATATGATGACGAAATAAAGGAAAATACCAGCTTTGCTGAAAGTGACATTAAGGAAAGATCTGCTGTTTTT
AGCAAAAGTGTCCAAAAA---GAATTCAGAAGGAGCCCTAGCCCTTTAGTGCAT---ACGCATTTGGCTCAGGGTCACCA
AAGAGGGGCTAGGAAATTAGAGTCCTCAGAAGAGAATGTGTCTAGTGAG
>Pig
TGTGGCACAGATACTCATGCCAGCTCGTTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTTTGTAATAAAAGCAAGCAGCCTGTCTTAGCAAAGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGGCA
CATGTAATGAT---AGGCAGACTCCTAACACAGAGAAAAAGGTAGTTCTGAATACTGATCTCCTGTATGGGAGAAACGAA
CTGAATAAGCAGAAACCTGCGTGCTCTGACAGTCCTAGAGAT---TCCCAAGAT---GTTCCTTGGATAACATTGAATAG
TAGCATACAGAAAGTTAATGAGTGGTTTTCTAGAAGCGATGAAATGTTAACTTCTGACGACTCACAGGACAGGAGGTCTG
AATCAAATACTGGGGTAGCTGGTGCAGCAGAGGTTCCAAAT------GAAGCAGATGGACATTTGGGTTCTTCAGAGAAA
ATAGACTTAATGGCCAGTGACCCTCATGGTGCTTTAATACGTGAACGTGAAAGAGGGCACTCCAAACCAGCAGAGAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGAGCCACGTAATTGAAGATC
TAATTTTAGGAGCATCTGCTGTAGAGCCTCAAATAACACAA---------------------------------------
---------------------GAGCGCCCCCTCACAAATAAACTAAAGCGGAAAAGGAGAGGTACATCAGGCCTTGATCC
CGAGGATTTTATCAAGAGAGCCGATTCGGCAGTTGTTCCAAAAACTCCTGAAAAGACAATTGAGGGAACTGATGAGACAG
AGCAGAAT---------GGTCAGGGGATGAATATTACCAGTAAAGGTCATGAGAATGAAACAAAAAGTGGTAAT---GTT
CAGAAAGAGAAAAATGTTAACCCAACTGCA------TCGTTGGGAAAAGAACCTGCTTTCAGAGCTAGGGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTGAATATCCATGGTTCGAAAGCACCAAAG---AACAGGCTGAGGAGGA
AGTCCTCTACCAGGCAGATCCATGCACTTGAACTAGTAGTCAATAGAAACCCAAGCCCACCTAGTCATACTGAGTTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATGAAGAAGAGA---AATTCCGACCAAGTGCCAGTCAGGCACAGCAAAAA
GCTTCACCTCAGGGGAGATAAAGAACCTACAACTGGAGCCAAGAAGAATAATAGGCCACATGAACAAGTAAATAAAAGAC
CTATCAGTGATGCTTTTCCAGAACTAAATTTAACAAATGTACCTGTTTCTATTACTAACTGTTCAAATTCTAATAAGCTT
CAAGAATCTGTCAGTCCTAACCTTCAAAGAGAA---------GAGAAC---CTAGGGACAATTCAAGTGTCGAATAGTAA
CAAAGACCCCAAAGATGTGATGTTAAGTGGAGGAAAA---GGTTTTCAA---ATTGAAAGATCTGTAGAGAATACCAGTA
TTTCCCTGGTACCTGATACTGATTATGGCACTCAGGACAGTATCTCATTACTGGAAACTGACACCCTAGGA---AAGGCA
AAA---ACAACACCCAATCAACATGTGAGGCTGTGTGCAGCAACTGAAAACCCCAAAGAACTTAGCCTTGGTTGT---TC
TAAAGGTGTTAGAAACGACACAGGGGACTTTAAGGATCCCCTGGCTCATGATGTTAAC---CACACTCAGGAAGCAAGCA
TAGAAGTGGAAGAGAATGAACTTGATACACAGTATTTGCAGAGTATGTTCAAGGTTTCAAAGCGTCAGACATTTGCTCTG
TTTTCAAATCCAGCAAATCCAGAAAAGGAATGTACAACCGTCCATGCCCACTCCAAGTCCTTAAGAGAACAAAGTCCAAA
AGTCACTCATGAAGGTGGACAAAAAGATGAAAATCAGGGAAAGAGTGAGTCTAAAGTCAAGCATGGGCAGTCAGTTCATA
CAACTGTGGACTTTCTAGTGGTTGGTCAAAAGGATAAGAAGCCGAGTGATTTTGCCAAATGTGGTGCAAAAGGAGTAACT
GGGCTTTATCAGACATCACAGTTCAGA---GGCCACAAAACTGAGTTCATTAATGCAAATAAACCTGGGATTTCACAAAA
CCCATATGTCATACCATCCCTTTCTCCCATCAGGTCGTCTGTTAAAACTATATGTAAGAAAAAC---CTGTCAGAGGAAA
AGTTTGAGGAACCTAAAATGTCACCCGAAAGAACAATGGGAAACGAGAGCATCATTCCAAATACAGAGAGCACAGTTAGC
CAAAATAACATTCAAGAGAGAACTTTTAAAGAAGGCAGCTCAGGCAGTCCTAATGAAGTCGGGTCCAGTACCAACGAAGT
AGGCTCTAGTATTAATGAAGTAGGTTCCAGC---------------------GGTGAAAACGTTCGAGCAGAACCAGGTA
GAAACAGAGGACCTAAATTAAGTGCAATGCTCAGATTAGGTCTCATGCAACCCGAAGTTTATAAGCAAAGTCTT---CCT
GTAAGTAATTGTAACCACACAGAAATAAAAAGGCAAGGAGAAAATGAAGGCATATTTCAGGCTGTTAATGCAGATTTCTC
CCCATATCTAATTTCAGATAACCCCGAACAA---CCTATGGGAAGTAGTCATGCTTCTCAGATTTGTTCTGAGACACCTG
ATGACCTGTTAAATGATGACAAAATAAAGGAAAATCTCAACTTTGCTGAAAGTGACGTTAAGGAAAGATCTGCTGTTTTT
AGCAAAAGTGCCCAAGAAGGGGAATTTAAAAGGAGCCCTAGCCCTTTAGCCCAC---AGACGTTTGGCTCAGGGTCACCA
AAGATGGGCTAGGAAATTAGAGTCTTCAGAAGAGAGTGGGTCTAGTGAG
>Cow
TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTGCTCACTGAAAACAGACTGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGTCTTAGTAAAGAGCCAGCAGAGCAGATGGGCTGAAAGTAAGGGCA
CATGTAAGGAT---AGGCAGATTCCCAGCACTGAGAAAAAGATAGTTCTGAATACTGATCCCCTGTACAGAAGAAAAGAA
CTGCGTAAGCAGAAACCTGCATGCCCTGACAGTCCTGGAGAT---TCCCAAGAT---GTTCCTTGGGTAACCCTGAATAA
TAGCATACAGAAAGTTAATGACTGGTTTTCCAGAAGTGATGAAATATTAACTTCTGATGACTCGTGCGATGGGGGGTYTG
AATCAAATAATGAAGTAGCTGGTGCAGTGGAAATTCCAAAT------AAAGTAGATGGATATTCAGGTTCTTCAGAGAAA
ATCAACTTAATGGCCAGTGATCCTCATGGTACTTTAATACAC------GAAAGAGTCCACTCCAAACCCGTAGAGAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGTCAAGTCTCCCTAACTTCAGCCACATAGCTGAAGATC
TAATTCTAGGCGCATTTACTGTAGAACCTCAGATAACACAA---------------------------------------
---------------------GAGCAGCCCCTCACAAATAAACTAAAATGTAAAAGGAGAGGTACATCAGGCCTTCAGCC
TGAGGATTTTATCAAGAAAGTCGATTTGACAATTGTTCCAAAGACTCCTGAAAAGATGACGGAGGGAACTGACCAAACAG
AGCAGAAA---------TGTCATGGGATGAATATTACTAGTGATGGTCATGAGAATAAAACAAAACGTGATTAT---GTT
CAGAAAGAGCAAAACGCTAACCCAGCAGAA------TCATTGGAAAAAGAATCTGTTTTCAGAACTGAGGCTGAACCTAT
AAGCATCAGTATAAGCAATATGGAACTAGAATTGAATATCCACCGTTCAAAAGCACCTAAG---AATAGGCTGAAGAGAA
AGTCCTCTACCAGGAAAATTCCTGAACTTGAACTAGTAGTCAGTAGAAACCCAAGTCTACCTAATCATACTGAGCTACCA
ATTGATAGCAGTTCTAGCAATGAAGAG---ATGAAGAAAAAA---CATTCTAGCCAAATGCCAGTCAGGCAGAGCCAAAA
GCTTCAACTCATTGGAGATAAAGAACTTACTGCTGGAGCC---AAGAATAACAAAACATATGAACAAATAAATAAAAGAC
TTGCTAGTGATGCTTTTCCAGAACTAAAGTTAACAAACACACCTGGTTATTTTACTAACTGTTCTAGT------AAACCT
GAAGAGTTTGTTCATCCTAGCCTTCAAAGAGAG---------GAGAAC---CTAGGAACAATTCAAGTGTCGAATAGTAC
CAAAGACCCCAAAGATCTGATATTAAGAGAAGGAAAA---GCTTTGCAA---ATTGAAAGATCTGTAGAGAGTACCAATA
TTTCCTTGGTTCCTGATACTGATTATAGCACTCAGGATAGTATCTCATTACTAGAAGCTAAAACCCCAGAA---AAGGCA
AAG---ACTGCACCAAATCCATGTGTGAGTCTGTGTACAGCAACCAAAAACCTCAAGGAACTTATCCATAGGGAT---TT
TAAAGATACCAAAAACAACACAGAGGGCTTTCAGGATCTACTGGGACATGACATTAACTACGTCATTCAGGAGACAAGCA
GAGAAATGGAAGACAGTGAACTTGATACACAGTATTTGCAGAATACATTCAAGGCTTCAAAGCGTCAGACATTTGCTCTG
TTTTCCAATCCAGGAAATCCACAAAAGGAATGTGCCACAGTCTTTGCCCACTCGGGGTCCTTAAGGGATCAAAGTCCAAG
AGACCCCCTCAAATGCAGACAAAAAGAAGACAGTCAGGGAAAGAGTGAGTCTAAAAGCCAGCACGTGCAGGCCATTTGTA
CAACAGTGCACTTTCCTGTGGCTGATCAGCAAGATAGGACGCCAGGTGACGATGCCAAATGTAGCGCAAAAGAAGTAACT
AGGGTTTGTCAGTCATCACAGTTGAGA---GGCCACAAAACTGAACTTGTTTTTGCAAATAAACAAGGGGTTTCAGAAAA
ACCAAATCTTATACCATCACTTTCTCCCATCAAGTCATCTGTTAAAACCATATGTAAGAAAAGC---CCATCAGAG---A
AGTTTGAGGAACCTGTAACGTCACCTGAAAAAACATTGGGGAGTGAGAGCATCATTCAAAGTGCAGTGAGCACAATCAGC
CAAAATAACATTCAAGAAAGCACTTTTAAAGAAGTCAGCTCAAACAGTGTAAATGAAGTAGGTTCCAGTACTAATGAAGT
AGGCTCTAGTGTTAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAGAACCAGGTA
GAAACAGAGAACCTAAATTAAGAGCTTTACTCGGATTAGGTCTTACGCAACCTGAAGTCTATAAGCAAAGTCTT---CCT
GTAAGTAACTGTCACCATCCTGAAATAAAAAGGCAAGGAGAAAATGAGGACATGCCTCAGGCTGTTAAGGCAGATTTCTC
CCCATGTCTAATTTCAGATAACCTCGAACAA---CCTACGGGAAGCCGTCATGCTTCTCAGGTTTGTTCTGAGACACCTG
ACAACTTGTTAAATGATGATGAAATAAAAGAAAATAGCCACTTTGCTGAAAGTGACATTAAGGAAAGATCTGCTGTTTTT
AGTGAAAGTGTCCAAAAAGGAGAATTCAGAGGGAGCCCTGGCCCTTTCACCCAT---ACACATTTGGCTCAGGGTCACCA
AAGAGGGGCTGGCAAACTAGAG---TCAGAAGAGACTGTGTCTAGTGAG
>Hippo
TGTGGCACAGATACTCGTGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGCAGA
AAAGGCTGAATTCTGTAATAAAAGCNAACAGCCTCTCTTAGCAAAGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGACA
CATGTAATGAT---AGACAGACTCCCAGCACAGAGAAAAAGGTAGTTCTGAACGCTGATCCCCTATACGGGAGAAAAGAA
CTGAATAAGCAGAAACGTGCATGCTCTGACGGCCCTAGCGAT---TCCCAAGAT---GTTCCTTGGATAACACTGAATAG
TAGCATACAGAAAGTTAATGAATGGTTTTCCAGGAGTGGCGAGATGTTAACTTCTGACGACTTATGTGTTAAGGGGTGTG
AATCAAATACTGAAGTAGCTGGTGCAGCGGAAGTTCCAAAT------GAAATTGATGGGTGTTTGGGTTCTTCAGAGAAA
ATAGATTTAATGGCCCGTGACCCTCGTGGTGCCTTAATACGTGAAAGTGAAAGAGTCCACGCCAAACCAGTAGAGAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGAGCCACATAGCTGAAGATC
TAATTAAAGGAGCATCTGCTGTAGGACCTCAGATAACACAA---------------------------------------
---------------------GAGCGCCCCCTCACAAATAAACTAAAGCGTAAAAGGAGGCGGACATCGGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTCGATGCGGCAGTTGTTCCAAAGACTCCTGAAAAGATAATTGAGGGAACTGATCAAACAG
AGCAGAAT------------------------------------GGTCATGAGAATGAAATGAAAGGTGATTAT---GTT
CAGAAAGAAAAAAATGCTAACCCAACAGAA------TCTTTGGAAAAAGAATCTGCTTTCAGAACTAAGGCTGAACCTAT
AAGCATCAGTATAAGCAATATGGAACTAGAATTGAATATCCACAGTTCAAAAGCACCTAAG---AGTACGCTGAGAAGGA
AGTCCTCTACCAGGCAGATTCATGCACTTGAACTAGTAGTCAGTAGAAACCCGAGCCCACCTAATCGTACTGAACTACAA
ATCGATAGTTGTTCTAGCAGTGAAGAG---ATGAAGAAAAAA---CATTCCTGCCAAATGCCAGTCAGGCACAGCAAAAA
GCTTCAATTCATGGGATATAAAGAACCCGCAACTGGAGTCAGGAAGAGTAATAAACCACACGAACAAATAAATAAAACAC
TTGCCAGTGGTGCTTTTCCAGAACTAAATGTAACAAACATACCTGGTTTTTTTACTAACTGTTCTAGTTCTAGTAAACTT
CAAGAGGTTGTTAATCCTGGCCTTCCAAGAGAG---------GAGAAC---CTAGGAACAATTCAAGTGTCAAATAGTAC
CAAAGACCCCAAAAATCTGATATTAAGTAGAGGAAAA---GGTTTGCAA---ATTGAAAGATCTATAGAGAGCACCAGTA
TTTCCTTGGTACCTGATACTGATTATGGCACTCAGGACAGTATCTCATTACTGGAAGCTGACACCCTAGGG---AAGGCA
AAG---ACAGCAACAAATCAACGTGTGGGTCTGTGTGCAGCAACTGAAAACCCCAAGGAACTTATCCATGGTTAT---TC
CAAAGATACTAGAAACGACATGGACGGCGTCCAGCATCCATTGGGACAGGATGTTAAC---CACACTCAGGATGCAAGCA
TAGAAGTGGAAGACAGTGAACTTGATACACAGTATTTGCAGAATACATTCAGGGTTTCAAAGCGTCAGACATTTGCCCTG
TTTTCAAATCCAGGAAATCCAGGAAAGGAACGTGCAACAGTCTGTGCTCATTCCGGGTCCTTAAGGGAACAAAGTCCAAG
AGTCCCTCTTGAATGCGGACAAAAAGAAGAAAATCAGGGCAAGAGTGAATCTAAA---------ATGCAGGCAATTTATA
CAACTGTGGACTTTGCTGTGGCTGGTCAAAATGATAGGAAGCCGAGTGATTACACCAAATGTAGCACTAAAGGAGTAACT
AGGCTTTGTCCCTCATCACAGTTTGGA---AGCAACAAAACTGAGCACATTATTGCAAATAAATATGGAATTTCACAAAA
CCCATATGTTATACCATCACTTTCTCCCATCAGGTCATCTGTTAAAACTATACGGAAGAAAAAC---CTGTCAGAGGAAA
AGTTTGAGGAACCTGTAGTGTCAGCTGAAAGAGCAATGGCAAATGAGAGCATCCTTCAAAGTACAGTGAACACAATTAGC
CAAAATAACATTCGAGAAAACACTTTTAAAGAAGTCAGTTCAAGCAGTATTAATGAAGTAGTTTCCAGTACTAATGAAGT
AGGCTCTAGTATCAGTGAAGTAGGTTCTAGT---------------------GGTGGAAACATTCAAGCAGAACTAGACA
GAAAGAGAGGACCTAAACTAAGTGCTTTGCTTAGATTAGGTCTTATGCAACCTGAAGTATATAAGCAAAGTCTT---CCT
GTAAGTAATTGTCAACATCCTGAAATAAAAAGGCAAGGAGAAAATGAAGGCATACTTCAGGCTGTTAATGCAGATTTCTC
CCCGTGTCTAATTTCAGATAACCTAGAACAA---CCTATGGGAAGCAGTCATGCTTCTCAGGTTTGTTCTGAAACACCTG
ATGATTTGTTAAATGATGACGGAATAAAGGAAAATAGCAACTTTGCTGAAAGTGACATTAAGGAAAGATCTGCTGTTTTT
AGCAAAAATGTCCAAAAAGGAGAATTCAGAAGGAGCCCTGGCCCTTTAGCCCAT---ACACGTTTGGCTCAGGGTCACCA
AAGAAGGGCTGGGAAATTGGAGTCCTCAGAAGA----------------
>SpermWhale
TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAAAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGTCTTAGCAAAGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGACA
CATGTAATGAT---AGGCAGACTCCCAGTACAGAGAAAAAGGTAGTTCTGAATGCTGATCCCCTATATGGGAGAAAAGAA
CTGAATAAGCAGAAATCTGCATGCTCTGACAGTCCTAGAGAT---TCCCAAGAG---TTTCCTTGGATAGCAGTGAATAG
TAGCATACAGAAAGTTAATGAATGGTTTTCCAGAAGTGATGAAATGTTAACTTCTAACGACTTACGTGATGGGGGATTTG
AATCAAACCCTGAAGTAGCTCGTGCAGTGGAAGTTCCACAG------GAAGTTGATGGATATTTGGGTTCTTCAGAGAAA
ATAGACTTAATGGCCAGTGATCCTCATGGTGCTTTAATACGTGAAAGTGAAAGAGTCCACTCCAAACCAGTAGAGAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGAGCCACGTAGCTGAAAATC
TAATTATAGGAGCATCTACTGTAGGACCTCAGATTACACAA---------------------------------------
---------------------GAGCGCCCCCTCACAAATAAACTAAAGCGTAAAAGGAGAAGTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTCGATTTGGCAGTTATTCCAAAGACTCCTGAAAAAATAATTGAGGGAACTGACCAAACAG
AGCAGAAT---------GGTCATGGGGTGAATATTACTAGTAATGGTCATGAGACTGAAATGAAAGGTGATTGT---GTT
CAGAAAGAGAAAAATGCTAACCTAACAGAA------TCATTGGAAAAAGAATCTGCTTTCAGAACTAAGGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTGAATATCCATAGTTCAAAAGCACCTAAA---AATAGGCTGGGGNGGA
TGTCCTCTTCCAGGAAGATTCATGCACTTGAACTAGTAGTCAGTAGAAACCCAAGCCCACCTAATCATACTGAACTACAA
ATTGATAGTTGTTCTAGCACTGAAGAG---ATGAAGAAAAAA---CATTCCAGCCAAATGCCAGTCAGGTGCGGCAAAAA
GCTTCAATTCATTGGAGATAAAGAACCTACAACTGGAGCCAAGAAGAGTAACAAGCCACATGAACAAATAAATAAAAGAC
TTGACAGTGACACTTATCCAGAACTAAATTTAACAAACATACCTGTTTTTTTTACTCACTGTTCTAGTTCTAATAAACTT
CAAGAGTTTGTTAATCCTAGCCTTCAAAGAGAG---------GAGAAC---CTAGGAACAATTCAAGTGTCGAATAGTAC
TGAAGACCCCAAAGATCTGACATTAAGTGGAGGAAAA---GGTTTGCAA---ATTGAAAGATCTGTAGAGAGTTCCAGTA
TTTCCTTGGTACCTGATACTGATTATGGCACTCAGGATAGTATCTCATTACTGGAAGCTGACACCCTAGGG---AAGGCA
AAG---ACAGCACCAAATCAACATGTGAGTCTGTGTGCAGCAATTGAAAGCCCCAAGGAACTTATCCACGGTTGT---TC
TAAAGATATTAGAAACGACACAGAGGACTTTAAGGATCCACTGGGACATCACGTTAAC---CACATTCAGGAGGCGAGCA
CAGNNNNNNNNNNNNNNNNACTTGATACTCAGTTTTTGCAGAATATGTTCAAGGTTTCAAAGCGTCAGACGTTTGCTCTG
TTTTCAAATCCAGAAAATCCAGAAAAGGAATGTGCAACAGTCTGTGCCCACTCTGGGTCCTTAAGAGAACAAAGTCCAAG
AGTCCCTCTTGAATGCAGACAAAAAGAAGAAAATCAGGGAAAGAGTGAGTCTAAAATCAAGCATGTGTGGGCAATTAATA
CAACTGTGGACTTCCCTGTTGCTGGTCAAAAAGATAAG---CCGAGCGATCATGCCAAACGTAGCCCCAAAAGAGTAACT
AGGCTTTGTCAGTCATCACAGTTCAGA---AGCAACAAAACTGAGCTCATTATTGCAAATAAACATGGGATTTCACAAAA
CCCATATCTTATACCATCACTTTCTCCCATCAGGTCATCTGTTAAAACTATATGTAAGAAAAAC---CTGTCAGAGGAAA
AGTTTGCGGAACCTGTAATGTCACCTGAAAGAGCAATGGAAAACGAGAGCATCATTCAAAGTACAGTGAGCACAATCAGC
CAAAATAACATTCGAGAAAGCACTTTTAAAGAAGTCAGCTCAAGCAGTACTAATGAAGTAGGTTCCAGTACCAATGAAGT
AGGCTCTAGTATTAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAAAACTAGATA
GAAACAGAGGACCTAAATTAAGTGCTTTGCTCAGATTAGGTCTCATGCAACCCGAAGTCTATAAGCAAAGTCTT---CCT
GTAAGTAACTGTCAACTTCCTGAAATAAAAAGGCAAGGAGAAAATGAAGGCACACTTCAGGCTGTTAATGCAGATTTCTC
CCCATGTCTAGTTTCAGATAACCTAGAACAA---CCTATGGGAAGAAGCCATGCTTCTCAGGTTTGCTCTGAGACATCTG
ATGAGTTGTTAAATGATGACAAAATAAAGGAAAATAGCAACTTTGCTGAAAGTGACATTAAGGAAAGATCT---GTTTTT
AGCAAAAGTGTCCAAAAAGGAGAATTCAGAAAGAGCACTGGCCCTTTAGCCCATCATACATGTTTGGCTCAGGGTCACGA
AAGAGGGGCT---------GAGTCCTCAGAAGAGAAAGTGTCTAGTGAG
>HumpbackW
TGTGGCACAGATACTCATGCCAGCTCATTACAACATGAAAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGTCTCAGCAAAGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGACA
CATGTAATGAT---AGGCAGACTCCCAGTACAGAGAAAAAGGTAGTTCTGAATGCTGATCCCCTGTATGGGAGAAAAGAA
CTGAATAAGCAGAAACCTGCATGCTCTGACAGTCCTAGAGAT---TCCCAAGAG---TTTCCTTGGATAACAGTGAATAG
TCGCATACAGAAAGTTAATGAATGGTTTTCCAGAAGTGATGAAATGTTAACTTCTAACGACTCACGTGATGGGGGATTTG
AATCAAACACTGAAGTAGCTTGTGCAGTGGAAGTTCCAAAG------GAAGTTGATGGATATTTGGGTTCTTCAGAGAAA
ATAGACTTAATGGCCAGTGATCCTCATGGTGCTTTAATACGTGAAAGTGAAAGAGTCCACTCCAAACCAGTAGAGAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGAGCCACATAGCTGAACATC
TAATTATAGGAGCATCTACTGTAGAACCTCAGATAACACAA---------------------------------------
---------------------GAGCGCCCCCTCACAAATAAACTAAAGCGTAAAAGGAGAAGTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTCGATTTGGCAGTTATTGCAAAGACTCCTGAAAAAATAACTGAGGGAACTGACCAAACAG
AGCAGAAT---------GGTCATGGGATGCATGTTACTAGTAATGGTCCTGAGACTGAAATGAAAGATGATTAT---GTT
CAGAAAGAGAAAAATGCTAACCTAACAGAG------TCATTGGAAAAACAATCTGCTTTCAGAACTAAGCCTGAACCTAT
AAGCAGCAGTATAGGCAATATGGAACTAGAATTGAATATCCATAGTTCAAAAGCACCTAAA---AATAGGCTGAGGAGGA
AGTCCTCTACCAGGAAGATTCATGCACTTGAACTAGTAGTCAGTAGAAACCCAAGCCCACCTAATCATACTGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATGAAGAAAAAA---CATTCCAGCCAAATGCCAGTCAGGCACGGCAAAAA
GCTTCAATTCATGGGAGATAAAGCACCTACAACTGGAGCCAAGAAGAGTAACAAGCCACACGAACAAATAAATAAAAGAC
TTACCAGTGACGCTTATCCAGAACTAAATTTAACAAACATACCTGGTTTTTTTACTCACTGTTCTAGTTCTAATAAACTT
CAAGAGTTTGTTAATCCTAGCCTTCAAAGAGAG---------GAGAAC---CTAGGAAAAATTCAAGTGTCGAATAGTAC
CAAAGACCCCAAAGATCTGACATTAAGTGGAGGAAAA---GGTTTGCAA---ATTGAAAGATCTGTAGAGAGTACCGGTA
TTTCCTTGGTACCTGATACTGATTATGGCACTCAGGATAGTATCTCATTACTGGAAGCTGACACCCTAGGG---AAGGCA
AAG---ACAGCACCAAATCAACATGTGAGTCTGTGTGCAGCAATTGAAAGCCCCAAGGAACTTATCCATGGTTGT---TC
TAAAGATATTAGAAACGACACAGAGGACTTTCAGGATCCACTGGGACATCACGTTAAC---CACATTCAGGAGGCGAGCG
CAGAAATGGAAGAGAATGAACTTGATACACAGTATTTGCAGAATATGTTCAGGGTTTCAAAGCGTCAGACGTTTGTTCTG
TTTTCAAATCCA---------GAAAAGGAATGTGCAACAGTCTGTGCCCGCTCTGGGTCCTTAAGAGAACAAAGTCCAAG
AGTCCCTCTTGAATGCAGACAAAAAGAAGAAAATCAGGGAAAGAGTGAGTCTAAAATCAAGCATGTGCGGGCAATTAATA
CAACTGTGGACTTCCCTGTTGCTGGTCAAAAAGATAAGAAGCCGAGCGATCATGCCAAACGTAGCCCAAAAAGAGTAACT
AGGCTTTGTCAGTCATCACAGTTCAGA---AGCAACAAAACTGAGCTCATTATTGCAAATAAACATGGGATTTCACAAAA
CCCATATCTTATACCATCACTTTCTCCCATCAGGTCATCTGTTAAAACTATATGTAAGAAAAAC---CTGTCAGAGGAAA
AGTTTGAGGAACCTGTAAGGTCACCTGAAAGAGCAATGGAAAACGAGAGCATCATTCAAAGTACAGTGAGCACAATTAGC
CAAAATAACATTCGAGAAAGCACTTTTAAAGAAGTCAGCTCAAGCAGTATTAATGAAGTAGGTTCCAGTACTAATGAAGT
AGGCTCTAGTATTAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAAAACTAGRTA
GAAACAGAGGACCTAAATTAAGTGCTTTGCTCAGATTAGGTCTTATGCAACCCGAAGTCTATAAGCAAAGTCTT---CCT
ATAAGTAACTGTCAACTTCCTGAAATAAAAAGGCAAGGAGAAAGTGAAGGCACACTTCAGGCTGTTAATGCAGATTTCTC
CCCAAGTCTAATTTCAGATAACCTAGAACAA---CCTATGGGAAGAAGCCATGCTTCTCAGGTTTGTTCTGAGACATCTG
ACGAGTTTTTAAATGATGACAAAATAAGGGAAAATAGCAACTTTGCTGAAAGTGACATTAAGGAAAGATCT---GTTTTT
AGCAAAAGTGTCCAAAAAGGAGAATTCAGAAGGAGCCCTGGCCCTTTAGCCCATCATACATGTTTGGCTCAGGGTCACGA
AAGAGGGGCT---------GAGTCCTCAGAAGAGAATGTGTCTAGTGAG
>Mole
TGTGGCATAAATACTCATGCCAGCTTATTACAGCATGAAAACAGCAGTTTATTACTCACTGAAAACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGACTTAGCAAAGAGCCAGCAGAACAGATGGGCTGAAAGTAAAGAAA
CATGTAATGAT---AGGCAGACTTCCAGCCCAGAGAAAAGGGTAGACCCGAATGCTGATCCCATGTATGGGAGAAAAGAA
CTGAATAAGCAGAAACCTCCATGCTCTGACAGCCCCAGAAAT---TCCCAAGGT---GTTGCCTGGATAACACTGAACAG
TAGCATTCGAAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAAATATTAACTTCTGATGAATCTCGTGATGGGGAGTCCC
CATCAAATATTGAAATGACTGGTGAAGTAGAAGTTCCAAAC------ACAGTAGATGGATTTTCTGGTTCTTCAGAGAAA
ATAGACTTAATGGCCAGCGATCCTCCC---GCTTTAATGTGTAAAAGTGAAAGAGTCCGCACCAAACCAGTAGAAAGTAA
T---ATTGAAGATAAGATATTTGGGAAAACCTATCGGAGGAAGACAAGCCTCCCAAACTTGAGCCACGTGGCTGAATATT
TAATTACAGGGACATCTGTCACAGAACCTCAGATAGTTCAA---------------------------------------
---------------------GAGCGTCCCTTCACAAATAGATTAAAACGTAAAAGGAGAACTCTACCAGGCCTTTGTCC
TGAGGATTTTATCAAGAAAGTAGATTTGGAAGTTGTTCAGAACACCCCTGAAAAGATAAGTGCGGGAACTGATCAAATGG
ATCAGAGT---------GGTCAAGTGATGGATGTTGCTTATAATGGTCATGGGAATGAAACAAAACGTGATTAT---GTT
CAGAAAGAGAAAAGTGCTAACCCAGCCGAA------TCTTTAGAAAAAGAATCTACCTTCAGAATTAAAGCTAAGCCCAT
AAGTAGCAGTATAAGCAATATGGAACTAGAATTAAATATCCACTCTTCAAAAGCACCTAAGAAGAACAGGCTGAGGAGGA
AGTCTTCTACCAAGCATATTCATGCACTTGAACTGGTGGTCAAAAGAAATCCAAGCCCACCTAATCATACAGAACTACAA
ATTGATAGCTGTTCTAGCAGTGAAGAG---ATGAAGGAAAGA---AATTCCAACCAAATGCCAGTAAGACACAGCAAAAG
GCTTCAACTCATGGAAGATAAAGACCCCGCAACTGAAGCCGTCAAGAGTAACAAGCCAAAAGAACAAATT---AAAAGAT
TTGCCAGTGATACTTTGCCAGAACTAAATTCAACACATGTACCTGGCTTTCTTAGCAACTATTCAAGTTCTAATAACCTT
GAAGAGTTTTCCAATCCTAGCCTTCAAAGAGAAGAACTAGAAGAGAAC---CTAGGAACAAATCAAGTGTCAAATAATAC
CAAAGACCCCAAAGATCCGATACTTAGTGGACAAAGA---GATTTGCAA---GCTGAAAGATCTGGCGAGAGTACCAATA
TTTCATTGGTACCTGAGACTGATTTTGGCAGTCAGGATAGTGTCTCATTACTGGAAATTGACATCCTAGGC---AAGGCA
AAA---AAAGTGCCGAATCAGTGTGCAAGTCTGTGTACAAAAATTGAAAACTCTAAGGAACTTATTCATAGTTGT---TC
TAAAGATACTAGAAATGACACACAGGGCTGTAAGGATCCACTGAAATACGAAGTTAAC---CACACTCAGGAGATAAGGA
TAGAGATGGAAGAGAATGAACTTGATACACAGTATTTACAGTCTACGTTCAAAGCTTCAAAGCGTCAATCATTTGCTCTG
TCTTCACATCCGGGAAATTCAGAAAAGAAATATCCCCCAGTCTCTGCCCCTTCCAGGTCCTTGAAGAGACAAACTCCAAA
AATCACTCTGGAATGTGAACTGAAAGAAGAAAATCAAGGGAAGAAAGAGTCTAAAACCGAGCATGTACAGGCAGTACATA
GAATTGCAGACTTAACTCTGGCTTGTCAGAACGATAAG---CCACATGATTCTGCCAAATGTAGCATAAAAGGAGTCTCT
AGGCTTTGTCAGTCATCTCAGTTCAGA---GGCAACGAAACAGAAGTCATTGTTGCAAATAAACGTTTAATCTTACAAAA
CCCATATCTTATTCCACCACTTTCTTCAATTCAGTCATCTGTTAAAAGTGCTTGTAAGAAAAAC---CTGGCGGAGGAAA
AGCTTGAGGAACACTCATGGTCACCCGAAAGAGAAACAGGAAACGGGAGCATCATTGAAAGTACAGTGAGCAGGGTTAGC
CAAAATAACAATAGAGAAAATGCTTTTAAGGAAGTCAGCTCAAGTAGTATTAACGAAGTAGGTTCCAGTACTAACGAAGC
TGACTCTAGTATTAATGAAGTAGGTTCCAGT---------------------GGTGAAAATATTCAAGCTGAACTAGATG
GAAGCAGAGGACCTAAATTAAATGCTATGCTCAGATTGGGTCTTATGCAACCTGAAGTCTATAAGCAAAGTCTT---CCT
AAAAGTACTTGTAAACATCCTGAAGTTAAAAGGCAAGGAGAAAATGAAGGCATAGTTCAGGCTGTTCATACAGATTTCTT
TCCATGTCTGATTTCAGATAACCAAGAACAA---CCTATGGGAAGTAGTCATGCTTCTCAGGTTTGTTCTGAGACGCCTG
AGGACCTGTTAAATGACGAAATAAAGGATAATAACATCAGCTTTGCTGACAGTGGCATTAAGGAAAGATCTGCTGTTTTT
AGCAAAAGTTTCCAGAAAGGAGAATTC---AGGAGCCCTAGCCTTTTAGACCAT---ACATGTTTGGCTCAGGACCACGA
AAGTGGG------AAATTGGAGTCCCCAGAAGAGACTATGTCTAGTGAG
>Hedgehog
---------------------------------CGTGAGAACAGCAGTTTATTACTCACTAAAGGCAAAATGAATGTAGA
AAAGGCTGAATTCTGTAGTAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACAGAGCAGATGGGCTGAAAATATGGAAA
CATGTAATGAT---AGGCAGACTCCTAGCCCAGACAAAGAAGTAGATCTGAATGCTGATTCCTTATATGAGAGAAAAGAA
CTAAACGAGCAGATCTCTTCATACTCCAGCAGTCCTAAAGAT---TCCAAAGAC---ATTTCTTGGGTAGCACTGAAT--
-AGCATACAGAAAGTGAATGAATGGCTTTCCAGAAGTGATGAACTGTTAACTTCTGATGACTCATATGATAAGGGATCTA
AATCAAAAACTGAAGTAACTGTAACAACAGAAGTTCCAAAT------GCAATAGATAGRTTTTTTGGTTCTTCAGAGAAA
ATAAACTTAACAGCCAGTGATCCTCATGTTGCTTTAATACGTGAAGGTGAAGGAGTCCACTTCAAACCAGTAAAGAATAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATGGGAGGAAGGCAAGCCTTCTTAATTTGAGCCACGTAACTGAAGATG
TAATTATAAGG------------GAACCTCAGGTAGCCAAA---------------------------------------
---------------------GAGCCTCTCCTTGCAACTAAATTAAAACGTAAAAGGAGAACTGATGTAGGTCTTTGTCC
TGAGGATTTTATCAAGAAAGTAGATGTGGCAATTGTTCAGAAGACTCCTGAAAAGATAATCAAGAGACCTGGCCAACTGG
ATCAAAGT---------GACCAAGTAATGAATATTGCTACTAATGGTCATGAAACTGAAACAAAGAGTGATTAT---GTT
CAGAAGGAGAAAAATGCTAACCCAGCAGAA------TCACCAGACAAAGAATCTGCTTTTAGAAATAAACCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATGTCCACAGTTCAAAAGCACCTAAGAAGAATAAACTCAGGAGAA
AGTCATCTGCCAGGCATATTCATGCACTTGAAGTAGTAGTCAATAAAAACTCAAGCCCACCTAGCCATACAGAACTACAA
ATTGATAGCTGTTCTAGCAATGAAGAG---ATGAGGGGGGTG---AAAGCTGATCAAATGCCAGTCAGGCACAGCAAACA
ACTTCCACTCATTGAAGACAAAGAACCTGCAACTAGAGCCTTTAGTAGTAGCAAGTCAAATGAACAAATAAGTAAACAGT
TTGTTGGTGAGACTTTTTCAGACCTAAATTTAACAAACATCCCTGGTTTTCTTACCAGCTGTTCAAGTTCCAATAAACAT
CAGGAATGTATTAATCCTAACCTACAAAGAGAGGTATTAGGAGAAAGC---CGTGGGACTATTCAAGTGTGTAATAATAC
CAAAAACCCTAAAGATCTGATAGTAAGTGGAAAGAGA---GGTTTACAA---ATTGAAAGATCTGTAGAGAGTCCT----
--------GTAGAGAACACTGACTATGGCAGTCAGGATAGTATCTCATTACTGGAAACTGATACTCTAGGG---AAGGCA
AAA---AAGACACCAAATCAATGTGTAAGTCTGTGTGTAGCAACTGAAACCCCCAAAGAACTTAGCCATAGTTGT---TC
TAAAGATACTAGAAATGACACTGAAGGCTTTAGGGATTCACTCAGATGTGAAGTTGAT---CACACGCAGGAGACAAGCA
CAGAACTGGAGGAGAGTGAACTTGATACACAGTATTTACAGAATACCTTCAAGGTTTCAAAACGTCGGTCATTTGCTCTG
TTTTCAAGTCCAGAGAATTCAGAAAAGGCATGTACAAGAGGCTCTGTCCATTCTAAGTCTTTAAGGAAACAAAGTCCAAA
AGTTATTCTGGACTGTGAACAAAAAGAAGAAAATCAAGGAGAGAAAGCATCTGAAATCAAGTATTTGCCATCAGAACATA
CAACTACAGGCTTTCCTGTGGTGTGTTATAAAGATACA---TCAGGTGATTATGCCAAATGTAGCGTAAAAGGAGTCTCC
AGGCATTGTCAGCCATCTCGGTTCAGA---GGCAGTGAACCTGAACTCATTGTTGCAAATAAAAATTTAATTTTACAAAA
CCTATATCATATACCAACACTTCCTACCATCATGTCATCTACTAAGAGTATATGCAAGAAAAAC---CTGTCTGAGGAAA
AT------------TCACTGTCGCCTGAAAGAGCAGTGACAAACAAAAGCATCATCCAAAGTACAGTGAACACCATTAGC
CAGACTAATGCCAGTGAAAATGCTCTTAAAGATGTCAGTTCAAGCAGTGTTAATGATATGGGTTCCAGTACTAATGAAGT
AGGTTCCAGT------------------------------------------AGTGAAAACATTCAAGCTAAACTATGTA
GAAACAGAGGACCCAGATTAAATGCTACTCTTAGAGCAAGTCTTATGCAACCTGAAGTCTTTGAGCAGTGTCTT---CTG
ATGAGTAACTGTAAACATTCTGAAATGAAAAGACAAGGAGAAAATGAAGGTGTTATTCAGACTGTTAATATAGAATCCGA
TTCATGCCCAAGACCAGATAACTTAGAACAA---CCGGTGGAAACTAGTCAT---------GTTTGTTCTGAAACACCTG
ACGATCTGTTAAATGACGATGAAATGAAGGAAAATACAAGCTTTACTGAAAGTGGCATTAAGGAACAATCTGCTGTTTTT
GGCAAAAGTACCCAGAAAGGT---TTCAGAAGGAGCCCTAGCCCTTTAGGCCAC---ACATGTTTGAGACAGGATCAGCA
AAGAGGGGCACAAAAATCAGAGCCCTCTGAAGATTTCATGTCTAGTGAG
>TreeShrew
TGTGGCATAAATACTTATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAGGACAGAATGAATGTAGA
AAAGGCTGAATTGTGTAATAAAAGCCAACAACCTGACTTAGCAAGGAGCCAGCAGAGCAGATGGACTGAAAATAAGGAAA
CATGTAATGAT---AGGCAGATTCCCAGCACAGAAAAAAAGGTAGATCTAAATGCTGATCCCCTGTGTGGGAAGAAAAAA
CAAGCTAAGCAGAAACYGCTATGTTCTAACAGTCCTAGAGAT---GACCAAGAT---TCTCCTTGGATAACTCTAAATAG
TAGCATTCAGAAAGTTAATGAATGGTTTTCCAGAAGTGATGAAATGTTAACTTCTAACGACTCACATGATGGTGAGTCTG
AA------------ATAGCTGGTGCATTYGAAGYTCCAAAT------AAAGTAGATGAATATTCTGGTTCTTCAGAAAAA
ATAGACTTAATGGCCAACAATCTTCATGATGCTTTAATAAGTAAAAGTGAAGGAATCTACTCCAAACCAGTAGAGGGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAAGCAAGTCTTCCTAACTTGAGCCGTGTAACTGATGATC
TAATTAGAGGGGCATTTGTTACAGAGCCTGAGATAACTCGA---------------------------------------
---------------------GAGCGTCCCTTCACAAATAAATTAAAGCGGAAAAGGAGAACTATATCAGGCCTTCATCC
TGAAGATTTTATCAAGAAAACAGATTTGGCAGTTGTTCAAAAGACTCCTGAAAAGATAAATCAGAGAACTGACCAAATAG
AGCATAAT---------GGTCAGGTGATGAGTATTGCTAATAGTGGTCATGAGAATGAAACAAAAGGTGATTAT---ATT
TCGAAAGAGAAAAATGCTAACCCAATGGAA------TCATTAGAAAAAGAATCTGCTCTCAGAACTAAAGCTGAGCCCAT
AAGCAGCAGTGTAAGCAATATGGAACTAGAAATAAATAACCACAGTTCAGAAGCACCTAAGAAGAATAGGCTGAGGAGAA
AGTTTTCTGCTAGGCATATTCGCACACTTGAACTAGTAGACAATAAAAGTCCAAGCCCACCTAATCGTACTGAACTACAA
ATTGACAGTTATTCTAGCGGTGAAGAG---AGAAAGAAAAAG---GGT---GAGCAAATGCCAGTTGGACACAGCAGAAA
GTTTCAACTTGAGGAAGAGAAAGAACCTACAACTGGAGCCAAGAAAAATAACCAGCCAAATACAGAAATAAGTGAAAGAC
ATGCCAGTGGTGTTATCCCAGATCTGAAGTTAACAAACATACCTGGTTTTTTCACAAACTCTTCGAGTTCTAATAAACTT
CCAGAATTTGTCCATCGTAGCCTTCAAAGAGAAAAA---GAAGAGAAC---CGAGAAACAATTCAAATATCCAGTAGTAC
C---------AAAGATCTGGTATTAAGGGGAGAAAGG---GGTTTGCAA---GATGTAAGGTCTGCAGAGAGTACCAGTA
TTTCTTTGGTACCTGATACTGATGATAACACCCAGGATAGCATCTCATTACTAGATGCTAACCCCCTAGCTAGGAAGGCA
AAA---ACAGCACCAAATCAATGTGTAAATCAGAGTGCAACAACTGAAAACCCCAAGGAACTTATACACAGTTGT---TC
TAAAACTACTAGGAAT------GAAGGCTTCAAGGATCCATTGAAAAGTGAAGTTAAT---CATATTCAGGAGATGAGTG
TAGAAATGGAGGAGAGTGAACTTGATACTCAGTATTTACAGAATACATTCAGGAGTTCAAAGCGTCAGTCATTTGCTCTG
TCTTCAAATCCAGGAAATCCAGAAAAGGAACATGTCTGTGTT--------------------------------------
-------------------------------AAAGAAAGTCTGAAAGAGTCTAACATCCAACATATACAGGCAGTTAGTA
CC---------------ATGGTTTTTCAGAAAGATAAG---CTAGGTGATTTTGCTACATCTGGCATTAAAGAAGTCCCT
AGACTTTGTCCATCATCTCAGTTCAGA---GGCAATGAAACTGATCTCATTACTGCAAATAAACCTGAAGTTTCACAAAA
CCCGTATCATATGCCATTACTTTATCCTGTCAAGTCACCTATTATAACTAAAAGTAAGAAAAGC---CTGTCAGAGGAAG
GGTTTGAGGAACAGGCAATGTCACTTGAAAGAGCAATGGAAAATGAGAACATCATTCAAAGTACAGTGAGCACAATTAGC
CAAGATAACATTAGAGAAGGTGCTTTTAAAGAAGCCAGCTCAAGCAGTATTAATGAAATAGGTCCTAGTACTAATGAAGG
AAGCTCTAGTATTAATGAGGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAGAACTAGGTA
AAAAGAGAGGATCCAAATTAAATGCTGTGCTTAGATTAGGTCTTATGCAACCCGAAGTCTATAAGCAAAGTCTT---CCT
TTAAGTAATCATAATGATCCTGAAATGAAAAGACAAGAAAAAAATGAAGGAGGAGTTCAGGCTATTAAA---GATTTACC
TCCATGTCTAATTTCAGATAATCAAGAGCAT------ATGGGAAGTAGCCATGCTTCTCAGATTTGTTCTGAGACACCTG
ATGATCTGTTAGATGATGATGAAGGAAAAGAAAAT---AGCTTTGCTGAGGTTGATGTTAAGGAAAGATCTGCTGTTTTT
GGCAAAACTGTCCAGAGAAGAGAGTTAAGAAGGAGCTCTAGCCCTTTAACTCGT---GCATGTTTGACTGAGGGTCAGCA
AACAGGAGCCCAGAAATTAGATTCATCAGAAGAGAACCTATCTAGTGAG
>FlyingLem
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACGCACTAAAGACAGAATAAATGTTGA
AAAGACTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAGGAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACGCCCAGCACAGAGAAAAAGATAGATCTAAATGCTGATTCCCAGCATGGGAGAAAAGAA
CGGAATATGCAGAAACCTCCATACCCTGAGAGTCCTAGAGAT---ACCCAAGAT---GTTCCTTGGATAACACTAAACAG
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAAATTTTAGCTTCTGATGACTCACGTGACAGGGTGTCTG
AATCAAATGCCAAAGTAGCTGGTGCATTAGAAGTTCCAAAT------GATGTAGATGGATATTCTGATTCTTCAGAGAAA
GTTGATTTAATGGCCAGTGATCCTCATGATGCTTTAATATGTAAAAGTGAAAGAATCCACTCCAGACCAGTAGAGAGTAA
T---ATCAAAGATAAAATATTTGGGAAAACCTATCAGAGGAAGACAAGCCTCCCTAACTTGAGCCACGTAAATGAAGATC
TAATTATAGGAGCATTTGTTACAGAACCACAGATAACACAA---------------------------------------
---------------------GAGCGTCCCCTCACAAATAAGGTAAAGCCTAAAAGGAGAACTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGCAGACTTGGCAGTTGTTCAAAAAACTCCTGAAAAGATAAATCAGGGAATTGACCAAATGG
AGCAGAAT---------GATCGAGTGATGAATATTATTAATAGTGGTCATGAGAATGAAACAAAGGATGATTAT---GTT
CAGAAAGAGAAAAATGCTAACCCAACAGAA------TCATTGGAAAAAGAATCTGCTTTCAGAACTAAAGCAGAACCTAT
AAGCAGCAGTATAAGCAATATGGAAATAGAATTAAATATCCACAATTCAAAACCATCTAAGAAGAATAGGCTGAGGAAGA
TGTCCTCTACTAGGCATATTCATGCACTTGAACTAGTAGTCAATAGAAATCCAAGCCCACCTAATTATACTGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAA---ATAGAGAAAAAA---AATTCCAGCCAAATGCCAGTCAGGCACAGCAGAAA
GCTTCAACTCATGGAAAATAAAGAACCTGCAACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAAATAAGTAGAAGAC
ATTCCAGTAATGCTTTCCCAGAACTGCGGTTAACAAATGTACCTGTTTTTTTTGCTAACTGTTCAAGTTCTAATAAACTT
CAAGAATTTATCGATCCTAGCCTTCAAAGAGAAGAAATAGAAGAGAAC---CTAGAAACAATTCATGTGTCTAATAGTGC
CAAAGACCCCAAAGATTTGGTGTTAAGTGGGGAGAAG---GGTTTGCAA---ACTGAAAGATCTGTAGAGAGTACCAGTA
TTTCATTAGTACCTGATACTGATTATGGCACTCAAGACAGTATCTCAATATTAGAAGCTAACATCCTAGGG---AAGGCA
AAA---ACAGCACCAAGTCAACATGCAAATCAGTGTGCAGCAATTGAAAACCCCAAAGAACTTATCCATGGTTGT---CC
TAAAGGTACTAGAAATGACACAGAGGATTTTAAGGATCCATTGAGATGTGGAGTTGAC---CACATTCAGAAGACAAGCA
TAGAAATGCAAGAGAGTGAACTTGATACTCAGTATTTACAAAATATATTCAAGGTTTCAAAACGTCAGTCATTTGCTCTC
TTTTCAAATCCAGGAAATCCAGAAAAGGAGTGTGCAACAGTCTATGCCCACTCCAGGTTGTTAAGGAAACAAAGTCCAAA
AGTCACTCCTGAATGTGAACAAAAAGAAGAAAATGAGGGAAATAAAGAGTCTAAAATCAAGCACATACAGGCAGTTAATA
CCACTGTGGGCTTTTCTGTCCTTTGTCAGAATGTTAAGAAGCCAGGTGATTATGCCAAATTTAGCATTAAAGGAGTCTCT
AGGCATTGTTCATCATCTCAGTTCAGA---GGCAATGAAACTGAACTCATTACTGCAAATAAACATGGAATTTTACAAAA
CTCATGTCATATGTCATCACTTTCCCCCATCAGGTCATCTGTTAAAATTAAATGTAAGAAGAAC---CTGTCAGAGGAAA
GGTTTGAGGAACATTCAGTGTCACCTGAAAGAGCAATGGCAAACAAGAGAATCATTCAAAGTACAGTGAACACAATTAGC
CAAAATAACATTAGAGACAGTGCTTCTAAAGAAGCCAGCTCAAGCAGTATTAATGAAGTAGGTTCCAGTACTAATGAAGT
AGGCTCCAGTATTAATGAAGTAGGTCCCAGT---------------------GGTGAAAACATTCAAGCAGAACTAGGTA
GAAACAGAGGACCTAAATTAAGTGCTATGCTTAGATTAGGCCTCATGCAACCTGAAGTTTACAAGCAAAATCTT---CCT
TTAGGTAATTGTAAACATCCTGAAATA---AGGCAAGAAGAAAATGAAGGAATAGTTCAGGCTGTTAATACAAATCTGTC
TCTGTGCCTAATTTCACATAACCTCGAACAA---CCTATGGAAAGTAGTCATGCTTCCCAGGTTTGTTCTGAGACACCTG
ATGACCTGTTAGATGGTGATGAGATAAAGGAAAACACCAGCTTTGCTGAAAGTGACAGTAAGGAAAGATCTGCTGTTTTT
AGCAAAAGTGTCCAGAGAGGAGAGTTAAGCAGGAGCCCTAGCCCTTTTGCCCAA---ACATGTTTGGCTCAGGGTCACCA
AAGAGGAGCCAGGAAATTAGAGTCTTCTGAAGAGAACGTATCTAGTGAG
>Galago
TGTGGCAAAAATACTCATGCCAGCTCATTACAGCATGAGAGCAGCAGTTTATTACTCACTAAAGACAAAATGAATGTAGA
AAAGGCTGAATTTTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACAGAGCAGATCGGCTCAAAGTAAGGAAA
CATGCAATGAT---AGGCACACTTGCAGCCCTGAGCAAAAGGTAGATCTGAATACTGCTCCCCCATATGGGAGAAAAGAA
CAGAATAAGGAGAAACTTCTATGCTCCAAGAATCCTAGAGAT---AGCCAAGAT---GTTCCTTGGATAACACTAAATAG
CAGCATTCAGAAAGTTAATGAATGGTTTTCTAGAAGTGATGAAATGTTAACTTCTGATGACTCACATGATGAGGGTTCTG
AATCACATGCTGAAGTAGCTGGAGCCTTAGAAGTTCCAAGT------GAAGTAGATGGATATTCCAGTTCCTCAGAGAAA
ATAGACTTACTGGCCAGTGATCCTCATTATCCTATAATATGTAAAAGTGAAAGAGTTCACTCCAAACCAATAAAGAGTAA
A---GTTGAAGATAAAATATTTGGGAAAACTTATCGGAGGAAGGCAAGCCTCCCTAACTTAAGCCATGTAACTGAAAATC
TAATTATAAGAGCAGCTGCTACTGAGCCACAGATAACACAA---------------------------------------
---------------------GAGTGTTCCCTCACAAATAAATTAAAACGTAAAAGGAGAACTACATCAGGTCTTTGTCC
TGAGGATTTTATCAAGAAGGCAGATTTGGCAGTTGTTCAAAAGACACCTGAAAAGAGAATTCAGGGAACTAACCAAGTGG
ATCAGAAT---------AGTCACGTGGTAAATATTACTAATAGTGGTTATGAGAATGAAACAAAAGGTGATTAT---GTT
CAGAATGAAAAAAATGCTAACTCAACAGAA------TCATTGGAAAAAGAATCTTCTCTCGGAACTAAAGCTGAACCTAT
AAGCAGCAGTATAAGTAATATGAAATTAGAATTAAATATTCACAATTCAAAAGCAAGTAAAAAGAAAAGGCTGAGGAAGA
AGTCTTCTAGCAGGCATATTCGTGCACTTGAACTAGTAGTCAATAAAAATCCAAGCCCTCCTAATCATACCAACCTACAA
ATTGACAGTTGTTCTAGCAGTGAAGAA---ATAAAGGATAAA---AGTTCTGACCAAATACCAGTCAGGCATAGCAGAAA
GCCTGGACTCATGGAAGATAGAGAACCTGCAACTGGAGCCAAGAAAAGTAACAAGCCAAATGAGCAAATAAGTAAAAGAC
ATGTCAGTGATACTTTCCCAGAAGTGGCATTAACAAATATATCTAGTTTTTTTACTAACTGTTCAGGTTCTAATAGACTT
AAAGAATTTGTCAATCCTAGCCTTCAAAGAAAAAAAACAGAAGAGAACTTAGAAGAAACAATTCAAGTGTCTAATAGTAC
CAAAGGTCCGGTGTTAAGTGGAGAAAGGGTTTTGCAA---ATTGAAAGT---GAAGAAAGATCTATAAAAAGCACCAGTA
TTTCATTGGTACCTGATACTGATTATGGTACTCAGGACAGTAACTCGTTACTGAAAGTTAAAGTCTTACGG---AAGGTG
AAA---ACAGCACCAAATAAACATGCAAGTCAGGGTACAGCCACTGAAAACCCCAAGGAACTAATCCATGGTTGC---TC
TAAAGATACTGGAAATGACACAGAGGGCTATAAGGATCCATTGAGACATGAAATTAAC---CACATTCAGAAGATAAGCA
TGGAAATGGAAGACAGTGAACTTGATACTCAGTATTTACAGAATACATTCAAGTTTTCAAAGCGTCAGTCGTTTGCTCTG
TTTTCAAACCTAGGA---------AAGGAATGTGCAACAGTCTGTGCCCAGTCTCTCTCTGCGTCCTTAAGAAAAGGTTC
AAAAGTCATTCTTGAATGTGAACAAATAGAAAATCCAGGAATGAAAGAGCCTAAAATCAAGCATATACAGGGAAATAATA
TCAATACAGGCTTCTCTGTAGTTTGTCAGAAAGATAAGAAAACAGATGATTATGCCAAATACAGCATCAAAGAAGCATCT
AGGTTTTGTTTGTCAAATCAGTTTCGA---GACAATGAAACTGAATCCATTACTGTAAATAAACTTGGAATTTTACAAAA
CCTCTATCATATACCACCACTTTCTCCTATCAGGCTATTTGATAAAACTAAATGTAATACAAAC---CTGTTAGAGGAAA
GGTTTGAAGAACATTCAGTGTTACCTGAAAAAGCAGTAGGAAACGAGAACACCGTTCCAAGTACAATGAATACAATTAAC
CAAAATAAC---AGAGAAAGTGCTTATAAAGAAGCCAGTTCAAGCAGTATCAATGAAGTAAGCTCGAGTACTAATGAAGT
GGGCTCCAGTGTTAACGAAGTAGGCCCCAGT---------------------AGTGAAAACATTCAAGCAGAACTAGATA
AAAACAGAGGACCTAAGTTGAATGCTGTGCTTAGATTAGGTCTTATGCAACCTGAAGTCTATAAACAAAATCTT---CCT
ATAAGTAATTGTGAACATCCTAAAATAAAAGGGCAAGAAGAAAATGGA---GTAGTTCAACCTGTTAATCCAGATTTTTC
TTCATGTCTAATTTCAGATAACCTAGAACAA---CCTACGAGAAGTAGTCATGCTTCTCAGCTTTGTTCTGAGACACCTG
ATGACTTATTAGTTGATGATGAACTAAAGGAAAATACCAGTTTTGCTGAAAATAACATTAAGGAAAGATCTGCTGTTTTT
AGCAAAAATGTCATGAGAAGAGAGATTAGCAGGAGCCCTAGCCCTTTAGCCCAT---ATACATTTGACTCAGGCTCACCA
AAGAGAGGTTAGGAAATTAGAGTCCTCAGAAGAGAACATGTCTAGTGAA
>HowlerMon
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTGTTACTCACTAAAGACACACTGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACATAACAGATGGGCTGAAAGTGAGGAAA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAGAAAAAGGTAGATGTGGATGCTGATCCCCTGCATGGGAGAAAAGAA
TGGAATAAGCAGAAACCTCCGTGCTCTGAGAATCCTAGAGATGATACTGAAGAT---GTTGCTTGGATAATGCTAAATAG
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAACTTCTGATGACTCACATGATGGGGGGTCTG
AATCAAATGCCAAAGTAGCTGAAGCATTGGAAGTTCTAAAT------GAGGTAGATGGATATTCTAGTTCTTCAGAGAAA
ATAGACTTACTGGCCAGTGATCCTCATGATCATTTGATATGTAAAAGTGAAAGAGTTCACTGCAAATCAGTAGAGAGTAG
T---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGAGCCACGTAACTGAAAATC
TAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA---------------------------------------
---------------------GAGCATCCTCTCACAAATAAATTAAAGCGTAAAAGGAGAGTTACATCAGGACTTCATCC
TGAGGATTTTATCAAGAAAGCAGATTTGGCAGTT---CAAAAGACTCCTGAAAAGATAAATCAGGGAACTAACCAAACAG
AGCGGAAT---------GATCAAGTGATGAATATTACTAACAGTGGTCATGAGAATAAAACAAAAGGTGATTCT---ATT
CAGAATGAGAACAATCCTAACCCAGTAGAA------TCACTGGAAAAAGAATCA---TTCAAAAGTAAAGCTGAACCTAT
AAGCAGTAGTATAAGCAATATGGAATTAGAATTGAATGTCCACAATTCCAAAGCATCTAAAAAGAATAGGCTGAGAAGGA
AGTCTTCTACCAGGCATATTCATGAGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAATTATACTGAAGTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATAAAGAAAAAA---AATTACAACCAAATGCCAGTCAGGCACAGCAGAAA
GCTACAACTCATGGAAGATAAAGAACGTGCAGCTAGAGCCAAAAAGAGTAGCAAGCCAAATGAACAAACAAGTAAAAGAC
ATGCCAGTGATACTTTCCCAGAACTGAGGTTAACAAACATACCTGGTTCTTTTACTAACTGTTCAAATACTAATGAATTT
AAAGAATTTGTCAATCCTAGCCTTCCAAGAGAACAAACAGAAGAGAAA---CTAGAAACAGTTAAACTGTCTAATAATGC
CAAAGACCCCAAAGATCTCATGTTAAGTGGAGAAAGT---GTTTTGCAA---ATTGAAAGATCTGTAGAGAGTAGCAGTA
TTTTGTTGATACCTGGTACTGATTATGGCACTCAGGAAAGTATCTCATTACTGGAAGTTAGCACTCTGGGG---AAGGCA
AAA---ACAGAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGAACTAATTCATGGTTGT---TC
TAAAGATACTAGAAATGGCACAGAAGGCTTGAAGTATCCATTGGGACCTGAAGTTAAC---TACAGTCAGGAAACAAGCA
TAGATATGAGAGAAAGTGAACTTGATACTCAATATTTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCTG
TTTTCAAATCCAGGAAATCCAGAAAAGGAATGTGCAACATTCTCTGCCTGCTCTAGGTCCTTAAAGAAACAAAGTCCAAA
GGTCACTCCTGAATGTGAACAAAAGGAAGAAAATCAAGGAGAGAAAGAGTCTAATATCGAGCTTGTAGAGACAGTTAATA
CCACTGCAGGCTTTCCTATGGTTTGTCAGAAAGATAAG---CCAGTTGATTATGCCAGATGT---ATCGAAGGAGGCTCT
AGGCTTTGTCTATCATCTCAGTTCAGA---GGCAACGAAACTGGACTCATTATTCCAAATAAACATGGACTTTTACAGAA
CCCATATCATATGTCACCGCTTATTCCCACCAGGTCATTTGTTAAAACTAAATGTAAGAAAAAC---CTGCTAGAAGAAA
ACTCTGAGGAACATTCAATGTCACCTGAAAGAGCAATGGGAAACAAGAACATCATTCCAAGTACAGTGAGCACAATTAGC
CATAATAAC---AGAGAAAATGCTTTTAAAGAAACCAGCTCAAGCAGTATTTATGAAGTAGGTTCCAGTACTAATGAAGC
AGGTTCTAGTACTAATGAAGTAGGCTCCAGTATTAATGAAGTAGGTTCCAGTGATGAAAACATTCAAGCAGAGCTAGGTA
GAAACAGAAGGCCAAAATTGAATGCTATGCTTAGATTAGGGCTTCTGCAACCTGAGATTTGTAAGCAAAGTCTT---CCT
ATAAGTGATTGTAAACATCCTGAAATTAAAAAGCAAGAACATGAAGAA---GTAGTTCAGACTGTTAATACAGACGTCTC
TCTATGTCTGATTTCATATAACCTAGAACAG---CATATGGGAAGCAGTCATACATCTCAGGTTTGTTCTGAGACACCTG
ACAACCTGTTAGATGATGGTGAAATAAAGGAAGATACTAGTTTTGCTGAATATGGCATTAAGGAGACTTCTACTGTTTTT
AGCAAAAGTGTCCAGAGAGGAGAGCTCAGCAGGAGCCCTAGCCCTTTCACCCAT---ACACATTTGGCTCAGGTTTACCA
AAGAGGGGCCAAGAAATTAGAGTCCTCGGAAGAGAATTTATCTAGTGAG
>Rhesus
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAAC---AGTTTGTTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTGGCAAGGAGCCAACATAACAGATGGACTGGAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAGAAAAAGGTAGATCTGAATGCTAATGCCCTGTATGAGAGAAAAGAA
TGGAATAAGCAAAAACTGCCATGCTCTGAGAATCCTAGAGAC---ACTGAAGAT---GTTCCTTGGATAACACTAAATAG
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAAGTTCTGATGACTCACATGATGGGGGGTCTG
AATCAAATGCCAAAGTAGCTGATGTATTGGACGTTCTAAAT------GAGGTAGATGAATATTCTGGTTCTTCAGAGAAA
ATAGACTTACTGGCCAGTGATCCTCATGAGCCTTTAATATGTAAAAGTGAAAGAGTTCACTCCAGTTCAGTAGAGAGTAA
T---ATTAAAGACAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAACCTTCCCAATTTAAGCCATGTAACTGAAAATC
TAATTATAGGAGCACTTGTTACTGAGTCACAGATAATGCAA---------------------------------------
---------------------GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGAACTACATCAGGTCTTCATCC
TGAGGATTTTATAAAGAAAGCAGATTTGGCAGTT---CAAAAGACTCCTGAAATAATAAATCAGGGAACTAACCAAATGG
AGCAGAAT---------GGTCAAGTGATGAATATTACTAATAGTGCTCATGAGAATAAAACAAAAGGTGATTCT---ATT
CAGAATGAGAAAAATCCTAACCCAATAGAA------TCACTGGAAGAAGAATCTGCTTTCAAAACTAAAGCTGAACCTAT
AAGCAGCAGTATAAACAATATGGAACTAGAATTAAATATCCACAATTCAAAAGCACCTAAAAAAAATAGGCTGAGGAGGA
AGTCTTCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAACTGTACTGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATAAAGAAAAAA---AATTACAACCAAATGCCAGTCAGGCACAGCAGAAA
CCTACAACTCATGGAAGATAAAGAATCTGCAACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGAC
ATGCCAGTGATACTTTCCCAGAACTGAAGTTAACAAAGGTACCTGGTTCTTTTACTAACTGTTCAAATACTAGTGAA---
AAAGAATTTGTCAATCCTAGCCTTTCAAGAGAAGAAAAAGAAGAGAAA---CTAGAAACAGTTAAAGTGTCTAATAATGC
CAAAGACCCCAAAGATCTCATCTTAAGTGGAGAAAGG---GTTTTACAA---ACTGAAAGATCTGTAGAGAGTAGCAGTA
TTTCATTGGTACCTGGTACCGATTATGGCACTCAGGAAAGTATCTCATTACTGGAAGTTAGCACTCTAGGG---AAGGCA
AAA---ACAGAACGAAATAAATGTATGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGAACTAATTCATGGTTGT---TC
TGAAGATACTAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGAAGTGAAGTTAAC---CACAGTCAGGAAACAAGCA
TAGAAATAGAAGAAAGTGAACTTGATACTCAGTATTTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCCTTTGCTCTG
TTTTCAAATCCAGGAAATCCAGAAGAGGAATGTGCAACATTCTCTGCCCACTCTAGGTCCTTAAAGAAACAAAGTCCAAA
AGTTACTTCTGAATGTGAACAAAAGGAAGAAAATCAAGGAAAGAAACAGTCTAATATCAAGCCTGTACAGACAGTTAATA
TCACTGCAGGCTTTTCTGTGGTTTGTCAGAAAGATAAG---CCAGTTGATAATGCCAAATGTAGTATCAAAGGAGGCTCT
AGGTTTTGTCTATCATCTCAGTTCAGA---GGCAACGAAACTGGACTCATTACTCCAAATAAACATGGACTGTTACAAAA
CCCATACCATATACCACCACTTTTTCCTGTCAAGTCATTTGTTAAAACTAAATGTAACAAAAAC---CTGCTAGAGGAAA
ACTCTGAGGAACATTCAGTGTCACCTGAAAGAGCAGTGGGAAACAAGAACATCATTCCAAGTACAGTGAGCACAATTAGC
CATAATAACATTAGAGAAAATGCTTTTAAAGAAGCCAGCTCGAGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGT
GGGCTCCAGTATTAATGAAGTAGGTTCCAGT---------------------GATGAAAACATTCAAGCAGAACTAGGTA
GAAACAGAGGGCCAAAATTGAATGCTGTGCTTAGATTAGGGCTTTTGCAACCTGAGGTCTGTAAACAAAGTCTT---CCT
ATAAGTAATTGTAAGCATCCTGAAATAAAAAAGCAAGAACATGAAGAA---TTAGTTCAGACTGTTAATACAGACTTCTC
TCCATGTCTGATTTCAGATAACCTAGAACAG---CCTATGGGAAGTAGTCATGCGTCTGAGGTTTGTTCTGAGACTCCTG
ATGATCTGTTAGATGATGGTGAAATAAAGGAAGATACTAGTTTTGCTGAAAATGACATTAAGGAGAGTTCTGCTGTTTTT
AGCAAAAGCATCCAGAGAGGAGAGCTCAGCAGGAGCCCTAGCCCTTTCACCCAT---ACACATTTAGCTCAGGGTTACCG
AAAAGAGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Orangutan
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAAAAAAAGGTAGACCTGAATGCTGATCCCCTGTGTGAGAGAAAAGAA
TGGAATAAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGAT---ACTGAAGAT---GTTCCTTGGATAACACTAAATAG
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGACGAACTGTTAGGTTCTGATGACTCACATGATGGGAGGTCTG
AATCAAATGCCAAAGTAGCGGATGTATTGGACGTTCTAAAT------GAGGTAGATGAATATTCTGGTTCTTCAGAGAAA
ATAGACTTACTGGCCAGTGATCCTCATGAGGCTTTAATTTGTAAAAGTGAAAGAGTTCACTCCAAATCAGTAGAGAGTAA
T---ATTGAAGACAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCCAACTTAAGCCATGTAACTGAAAATC
TAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA---------------------------------------
---------------------GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGAGCTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGCAGATTTGGCAGTT---CAAAAGACTCCTGAAATGATAAATCAGGGAACTAACCAAATGG
AGCAGAAT---------GGTCAAGTGATGAATATTACTAATAGTGGTCATGAGAATAAAACAAAAGGTGATTCT---ATT
CAGAATGAGAAAAATCCTAACCCAATAGAA------TCACTCGAAAAAGAATCTGCTTTCAAAACAAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTCGAATTAAATATCCATAATTCAAAAGCACCTAAAAAGAATAGGCTGAGGAGGA
AGTCTTCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAATTGTACTGAATTGCAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATAAAGAAAAAA---AAATACAACCAAATGCCAGTCAGGCACAGCAGAAA
CCTACAACTCATGGAAGATAAAGAACCTGCAACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGAC
ATGACAGCGATACTTTCCCAGAGCTGAAGTTAACAAATGCACCTGGTTCTTTTACTAACTGTTCAAATACCAGTGAGCTT
AAAGAATTTGTCAATCCTAGCCTTCCAAGAGAAGAAAAAGAAGAGAAA---CTAGGAACAGTTAAAGTGTCTAATAATGC
CAAAGACCCCAAAGATCTCATGTTAAGTGGAGGAAGG---GTTTTGCAA---ACTGAAAGATCTGTAGAGAGTAGCAGTA
TTTCATTGGTACCTGGTACTGATTATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGG---AAGGCA
AAA---ACAGAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGAACTAATTCATGGTTGT---TT
CAAAGATACTAGAAATGACACAGAAGGGTTTAAGTATCCATTGGGACATGAAGTTAAC---CACAGTCAGGAAACAAGCA
TAGAAATGGAAGAAAGTGAACTTGATACTCAGTATTTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCTG
TTTTCAAATCCAGGAAATCCAGAAGAGGAATGTGCAACATTCTCTGCCCACTCTAGGTCCTTAAAGAAACAAAGTCCAAA
AGTCACTTTTGAATGTGAACAAAAGGAAGAAAATCAAGGAAAGAATGAGTCTAATATCAAGCCTGTACAGACAGCTAATA
TCACTGCAGGCTTTCCTGTGGTTTGTCAGAAAGATAAG---CCAGTTGATTATGCCAAATGTAGTATCAAAGGAGGCTCT
AGGTTTTGTCTATCATCTCAGTTCAGA---GGCAACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTCACAAAA
CCCATATCATATACCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAAC---CTGCTAGAGGAAA
ACTCTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAACGAGAAC---ATTCCAAGTACAGTGAGCATAATTAGC
CGTAATAACATTAGAGAAAATGTTTTTAAAGAAGCCAGCTCAAGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGT
GGGCTCCAGTATTAATGAAGTAGGTTCCAGT---------------------GATGAAAACATTCAAGCAGAACTAGGTA
GAAGCAGAGGGCCAAAATTGAATGCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTATAAACAAAGTTTT---CCT
GGAAGTAATGGTAAGCATCCTGAAATAAAAAAGCAAGAATATGAAGAA---GTACTTCAGACTGTTAATACAGACTTCTC
TCCATGTCTGATTTCAGATAACCTAGAACAG---CCTATGAGAAGTAGTCATGCATCTCAGGTTTGTTCTGAGACACCTA
ATGACCTGTTAGATGATGGTGAAATAAAGGAAGATACTAGTTTTGCTGAAAATGACATTAAGGAAAGTTCTGCTGTTTTT
AGCAAAAGCGTCCAGAGAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCAT---ACACATTTGGCTCAGGGTTACCG
AAGAGGGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Gorilla
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAACAAACAGCCTGGCTTAGCAAGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAA
CATGTAATGAT---AGGCGGACTCCCAGCACAGAAAAAAAGGTAGATCTGAATGCTGATCCCCTGTGTGAGAGAAACGAA
TGGAATAAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGAT---ACTGAAGAT---GTTCCTTGGATAACACTAAATAG
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAGGTTCTGATGACTCACATGATGGGGGGTCTG
AATCAAATGCCAAAGTAGCTGATGTATTGGACGTTCTAAAT------GAGGTAGATGAATATTCTGGTTCTTCAGAGAAA
ATAGACTTACTGGCCAGTGATCCTCATGAGGCTTTAATATGTAAAAGTGAAAGAGTTCACTCCAAATCAGTAGAGAGTAA
T---ATTGAAGACAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCCAGCTTAAGCCATGTAACTGAAAATC
TAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA---------------------------------------
---------------------GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGAGCTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGCAGATTTGGCAGTT---CAAAAGACTCCTGAAATGATAAATCAGGGAACTAACCAAATGG
AGCAGAAT---------GGTCAAGTGATGAATATTACTAATAGTGGTCATGAGAATAAAACAAAAGGTGATTCT---ATT
CAGAATGAGAAAAATCCTAACCCAATAGAA------TCACTAGAAAAAGAATCTGCTTTCAAAACGAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTCGAATTAAATATCCACAATTCAAAAGCGCCTAAAAAGAATAGGCTGAGGAGGA
AGTCTTCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAATTGTACTGAATTGCAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATAAAGAAAAAA---AAGTACAACCAAATGCCAGTCAGGCACAGCAGAAA
CCTACAGCTCATGGAAGATAAAGAACCTGCAACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGAC
ATGACAGCGATACTTTCCCAGAGCTGAAGTTAACAAATGCACCTGGTTCTTTTACTAACTGTTCAAATACCAGTGAACTT
AAAGAATTTGTCAATCCTAGCCTTCCAAGAGAAGAAAAAGAAGAGAAA---CTAGAAACAGTTAAAGTGTCTAATAATGC
CGAAGACCCCAAAGATCTCATGTTAAGTGGAGAAAGG---GTTTTGCAA---ACTGAAAGATCTGTAGAGAGTAGCAGTA
TTTCATTGGTACCTGGTACTGATTATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGG---AAGGCA
AAA---ACAGAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGGACTAATTCATGGTTGT---TC
CAAAGATACTAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGACATGAAGTTAAC---CACAGTCGGGAAACAAGCA
TAGAAATGGAAGAAAGTGAACTTGATGCTCAGTATTTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCTG
TTTTCAAATCCAGGAAATCCAGAAGAGGAATGTGCAACATTCTCTGCCCACTCTAGGTCCTTAAAGAAACAAAGTCCAAA
AGTCACTTTTGAATGTGAACAAAAGGAAGAAAATCAAGGAAAGAATGAGTCTAATATCAAGCCTGTACAGACAGTTAATA
TCACTGCAGGCTTTCCTGTGGTTTGTCAGAAAGATAAG---CCAGTTGATTATGCCAAATGTAGTATCAAAGGAGGCTCT
AGGTTTTGTCTATCATCTCAGTTCAGA---GGCAACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTTACAAAA
CCCATATCATATACCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAAC---CTGCTAGAGGAAA
ACTTTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAATGAGAAC---ATTCCAAGTACAGTGAGCACAATTAGC
CGTAATAACATTAGAGAAAATGTTTTTAAAGAAGCCAGCTCAAGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGT
GGGCTCCAGTATTAATGAAGTAGGTTCCAGT---------------------GATGAAAACATTCAAGCAGAACTAGGTA
GAAACAGAGGGCCAAAATTGAATGCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTATAAACAAAGTCTT---CCT
GGAAGTAATTGTAAGCATCCTGAAATAAAAAAGCAAGAATATGAAGAA---GTAGTTCAGACTGTTAATACAGATTTCTC
TCCATGTCTGATTTCAGATAACTTAGAACAG---CCTATGGGAAGTAGTCATGCATCTCAGGTTTGTTCTGAGACACCTG
ATGACCTGTTAGATGATGGTGAAATAAAGGAAGATACTAGTTTTGCTAAAAATGACATTAAGGAAAGTTCTGCTGTTTTT
AGCAAAAGCGTCCAGAGAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCAT---ACACATTTGGCTCAGGGTTACCG
AAGAGGGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Human
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAA
CATGTAATGAT---AGGCGGACTCCCAGCACAGAAAAAAAGGTAGATCTGAATGCTGATCCCCTGTGTGAGAGAAAAGAA
TGGAATAAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGAT---ACTGAAGAT---GTTCCTTGGATAACACTAAATAG
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAGGTTCTGATGACTCACATGATGGGGAGTCTG
AATCAAATGCCAAAGTAGCTGATGTATTGGACGTTCTAAAT------GAGGTAGATGAATATTCTGGTTCTTCAGAGAAA
ATAGACTTACTGGCCAGTGATCCTCATGAGGCTTTAATATGTAAAAGTGAAAGAGTTCACTCCAAATCAGTAGAGAGTAA
T---ATTGAAGACAAAATATTTGGGAAAACCTATCGGAAGAAGGCAAGCCTCCCCAACTTAAGCCATGTAACTGAAAATC
TAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA---------------------------------------
---------------------GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGACCTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGCAGATTTGGCAGTT---CAAAAGACTCCTGAAATGATAAATCAGGGAACTAACCAAACGG
AGCAGAAT---------GGTCAAGTGATGAATATTACTAATAGTGGTCATGAGAATAAAACAAAAGGTGATTCT---ATT
CAGAATGAGAAAAATCCTAACCCAATAGAA------TCACTCGAAAAAGAATCTGCTTTCAAAACGAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTCGAATTAAATATCCACAATTCAAAAGCACCTAAAAAGAATAGGCTGAGGAGGA
AGTCTTCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAATTGTACTGAATTGCAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATAAAGAAAAAA---AAGTACAACCAAATGCCAGTCAGGCACAGCAGAAA
CCTACAACTCATGGAAGGTAAAGAACCTGCAACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGAC
ATGACAGCGATACTTTCCCAGAGCTGAAGTTAACAAATGCACCTGGTTCTTTTACTAAGTGTTCAAATACCAGTGAACTT
AAAGAATTTGTCAATCCTAGCCTTCCAAGAGAAGAAAAAGAAGAGAAA---CTAGAAACAGTTAAAGTGTCTAATAATGC
TGAAGACCCCAAAGATCTCATGTTAAGTGGAGAAAGG---GTTTTGCAA---ACTGAAAGATCTGTAGAGAGTAGCAGTA
TTTCATTGGTACCTGGTACTGATTATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGG---AAGGCA
AAA---ACAGAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGGACTAATTCATGGTTGT---TC
CAAAGATAATAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGACATGAAGTTAAC---CACAGTCGGGAAACAAGCA
TAGAAATGGAAGAAAGTGAACTTGATGCTCAGTATTTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCCG
TTTTCAAATCCAGGAAATGCAGAAGAGGAATGTGCAACATTCTCTGCCCACTCTGGGTCCTTAAAGAAACAAAGTCCAAA
AGTCACTTTTGAATGTGAACAAAAGGAAGAAAATCAAGGAAAGAATGAGTCTAATATCAAGCCTGTACAGACAGTTAATA
TCACTGCAGGCTTTCCTGTGGTTGGTCAGAAAGATAAG---CCAGTTGATAATGCCAAATGTAGTATCAAAGGAGGCTCT
AGGTTTTGTCTATCATCTCAGTTCAGA---GGCAACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTTACAAAA
CCCATATCGTATACCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAAT---CTGCTAGAGGAAA
ACTTTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAATGAGAAC---ATTCCAAGTACAGTGAGCACAATTAGC
CGTAATAACATTAGAGAAAATGTTTTTAAAGAAGCCAGCTCAAGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGT
GGGCTCCAGTATTAATGAAATAGGTTCCAGT---------------------GATGAAAACATTCAAGCAGAACTAGGTA
GAAACAGAGGGCCAAAATTGAATGCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTATAAACAAAGTCTT---CCT
GGAAGTAATTGTAAGCATCCTGAAATAAAAAAGCAAGAATATGAAGAA---GTAGTTCAGACTGTTAATACAGATTTCTC
TCCATATCTGATTTCAGATAACTTAGAACAG---CCTATGGGAAGTAGTCATGCATCTCAGGTTTGTTCTGAGACACCTG
ATGACCTGTTAGATGATGGTGAAATAAAGGAAGATACTAGTTTTGCTGAAAATGACATTAAGGAAAGTTCTGCTGTTTTT
AGCAAAAGCGTCCAGAAAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCAT---ACACATTTGGCTCAGGGTTACCG
AAGAGGGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Chimpanzee
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAA
CATGTAATGAT---AGGCGGACTCCCAGCACAGAAAAAAAGGTAGATCTGAATGCTGATCCCCTGTGTGAGAGAAAAGAA
TGGAATAAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGAT---ACTGAAGAT---GTTCCTTGGATAACACTAAATAG
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAGGTTCTGATGACTCACATGATGGGGGGTCTG
AATCAAATGCCAAAGTAGCTGATGTATTGGACGTTCTAAAT------GAGGTAGATGAATATTCTGGTTCTTCAGAGAAA
ATAGACTTACTGGCCAGCGATCCTCATGAGGCTTTAATATGTAAAAGTGAAAGAGTTCACTCCAAATCAGTAGAGAGTAA
T---ACTGAAGACAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCCAACTTAAGCCATGTAACTGAAAATC
TAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA---------------------------------------
---------------------GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGAGCTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGCAGATTTGGCAGTT---CAAAAGACTCCTGAAATGATAAATCAGGGAACTAACCAAATGG
AGCAGAAT---------GGTCAAGTGATGAATATTACTAATAGTGGTCATGAGAATAAAACAAAAGGTGATTCT---ATT
CAGAATGAGAAAAATCCTAACCCAATAGAA------TCACTCGAAAAAGAATCTGCTTTCAAAACGAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTCGAATTAAATATCCACAATTCAAAAGCACCTAAAAAGAATAGGCTGAGGAGGA
AGTCTTCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAATTGTACTGAATTGCAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATAAAGAAAAAA---AAGTACAACCAAATGCCAGTCAGGCACAGCAGAAA
CCTACAACTCATGGAAGATAAAGAACCTGCAACTGGAGTCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGAC
ATGACAGCGATACTTTCCCAGAGCTGAAGTTAACAAATGCACCTGGTTCTTTTACTAACTGTTCAAATACCAGTGAACTT
AAAGAATTTGTCAATCCTAGCCTTCCAAGAGAAGAAGAAGAAGAGAAA---CTAGAAACAGTTAAAGTGTCTAATAATGC
CGAAGACCCCAAAGATCTCATGTTAAGTGGAGAAAGG---GTTTTGCAA---ACTGAAAGATCTGTAGAGAGTAGCAGTA
TTTCATTGGTACCTGGTACTGATTATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGG---AAGGCA
AAA---ACAGAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGGACTAATTCATGGTTGT---TC
CAAAGATACTAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGACATGAAGTTAAC---CACAGTCGGGAAACAAGCA
TAGAAATGGAAGAAAGTGAACTTGATGCTCAGTATTTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCTG
TTTTCAAATCCAGGAAATCCAGAAGAGGAATGTGCAACATTCTCTGCCCACTGTAGGTCCTTAAAGAAACAAAGTCCAAA
AGTCACTTTTGAACGTGAACAAAAGGAACAAAATCAAGGAAAGAATGAGTCTAATATCAAGCCTGTACAGACAGTTAATA
TCACTGCAGGCTTTCCTGTGGTTTGTCAGAAAGATAAG---CCAGTTGATTATGCCAAATGTAGTATCAAAGGAGGCTCT
AGGTTTTGTCTATCATCTCAGTTCAGA---GGCAACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTTACAAAA
CCCATATCATATACCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAAC---CTGCTAGAGGAAA
ACTTTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAATGAGAAC---ATTCCAAGTACAGTGAGCACAATTAGC
CGTAATAACATTAGAGAAAATGTTTTTAAAGAAGCCAGCTCAAGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGT
GGGCTCCAGTATTAATGAAGTAGGTTCCAGT---------------------GATGAAAACATTCAAGCAGAACTAGGTA
GAAACAGAGGGCCAAAATTGAATGCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTATAAACAAAGTCTT---CCT
GAAAGTAATTGTAAGCATCCTGAAATAAAAAAGCAAGAATATGAAGAA---GTAGTTCAGACTGTTAATACAGATTTCTC
TCCATGTCTGATTTCAGATAACTTAGAACAG---CCTATGGGAAGTAGTCATGCATCTCAGGTTTGTTCTGAGACACCTG
ATGACCTGTTAGATGATGGTGAAATAAAGGAAGATACTAGTTTTGCTGAAAATGACATTAAGGAAAGTTCTGCTGTTTTT
AGCAAAAGCGTCCAGAGAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCAT---ACACATTTGGCTCAGGGTTACCG
AAGAGGGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Jackrabbit
--------------------------------------------------------------------------------
-AAGGCTGAATTCTGTAATAAGAGCAAACAGCCTGGCTTAGCAAGAAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCCAGCACAGAGAAAAAGGTAGTTCTGAATGTTGACTGCCTGTATGGGAGAAAACAA
CAGGATAAGCAGAAACCTCCATGCCCTGAGACCTCTGGAGAT---AACCAAGAT---GTTTCTTGGATAACAGTAAATAG
CAGCATTCGGAAAGTTAACGAGTGGTTCTCCAGAAGTAATGAAATGTTAACTCCTGATGACTCACTTGACCGGCGGTCTG
AATCAAATGCCAAAGTGGCTGGTGCATTAGAAGTCCCAAAG------GAGGTAGATGGATATTCTGGTTCTACAGAGAAA
ATAGACTTACTGGCCAGTGATTCCCATAATGCTTTAATATGTGAAAGCAAAAGAGTCCATTCCAAACCAGTAGAGAATAA
T---ATCAAAGATAAAATATTTGGGAAAACCTACCACAGGAAGACAAGCCTCCCTAACTTGAGCCACATAACTGAAGATC
TAACTATAGGAGCATTTGCTGCGGAACCACTGGTA---------------------------------------------
---------------------CCATGTCCCCCCGCAAATAAATTAAAGCGTAAAAGAAGAACTTCTTCAGGCCTTCAACC
TGAAGATTTTATCAAGAAGGTAGATTTGGCAGTTGTTCCAAAAACCACTGCACAGATAAATCAGGGAACTGATCAAACGG
TGGACAGT---------GATCAGGTGATGAATATTACTAATTGTGGTAATGAGAATGAAACAGAAGGTGACTAT---ATT
CAGAAAGAGACAAATGCTAACCCAACAGAA------TCCCTAGAAAAAGACTCTTCCTTCAGAACTAAAGTTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATGTCCATAATTCAAAAAAACCCAAGAAGAATAGGCTGAGGAGGA
AGTCCTCTACCAGGCGTGTTCATGCACTTGAACTAGTAGTCAATAAGAAACCGAGCCCACCTAATCATGCTGAACTACAA
ATTGACAGTTGTACTAGCAGTGAAGAA---ATG------------AATTTTGACCAAATACCAGTCAGTCACAGCAGACA
GGCTCAAGTCATAGAAGATACAGAACCTCCAACTGGAGCTAGGAAG---AACAAGCCAAGTGAACAAATAAGTAAAAGAC
ATGCCAGTGATGTTTTCCCAGAAGTCAAATTAACAAACATACCTGGTGTTTTTACAAACTGTTCAAGTTCTAATAAACTT
CAAGAATCTGTCGATCCTAGCCTTCAAAGAAGGGAAATAGAAGAGAAC---CTAGACACAGTTCAAGTGCCTAACAGTGC
CATAGACCCCAAAGATCTCCTGTTATGTGGAGAAAGG---GGCTTGCAA---ACTGAAAGGTCTGCGGAGAGTACCAGTA
TTTCACTGGTACCTGATACTGAATATGGTACCCAGGACAGCATCTCATTACTGGGCGCTAACACCCTTGGG---AAGGCA
AAA---ACAGCAGCAAATGGACATGTGAGTGAGAGCACAACAATTGGAAATCCCAAGGAACTTAGCCATGATTGT---TT
GAAAGATACTGGAAATGACCCAGACAACTGTAAGGATCCACTGAGAAGTGAAGTTGAC---------CAAGAGACAAGCG
TAGAAATGGAAGAGAGTGAGTTTGATACTCAGTATTTACAGAATACATTCATGGGTTCAAAGCGTCGTTCATTTGCTCTG
TGTTCAAAACCAGGAGATCCAGAAAAGGAATGTGCAGCAGTCTGTACCCGCTCCAACTCCTCAAGGAAACAAAGTCCAGA
AGTCACTCTTGAACGTGAACAAAAAGAA---AGTCAGAGAAAGGAAGAGTGGAAAATCAGTCATGTCCAGGCAGCTGATA
GCACTGTGGGCTTTCCTGTGGTGTGTCAGAAAGAAAAG---GCAGGTGATTGTGCCAAATGGAGCACTAAAGAGATCTCT
AGGCTTTGTCTGTCATCTCAGTCCAAA---GGCAGTGAAACTGAGCTCATTGCTGTAAGTAAACATGGGATGTCACAAAA
CCCATATCATATACCACCAATTTCTCCCATCAAGACATCTGTTAAAGCCACACGCCAGGTACAC---CTGTCAGGGGAAA
GGTCTGAGGAGCATTCCGTGTCATCTGAAAGAGCAGTGGGAAGCGAGAGCATCATTCAAAGCACAGTGAGCACAATTAGC
CAAGAGTACATTAGAGAAAGTGCTTTGAAAGGATTCAGCTCAAGCAGTATTAATGAAGGGGGCTCTAGTGCTAACGAAGT
ATGCTCCAGTGTGAATGAAGTAGGATCCAGT---------------------GGTGAAAACATGCAAGCACAACCAGGCA
GAAGCAGAGCACCTGAGTTAAATGCTGTGCTGAGAATAGGTCTTCTGCAGCCTGAAGTCTCTGAGCAAAGCCTT---CCT
ATAAGTAATTCTGAACTTCCCAAACTACAAAGGCAAGGAGAAAACGAAGGAGTAGTTCAGGCTGTGAATAGAGATTTCTC
TTCGTATCTGGTTCCTGATAGCCAAGAGCAG---TCTATGGGAGGAAGGCATGCTTCTCAGATTTGTTCTGAGACACCTG
ATGACCTGTTAGATATTTATGAAATAAAGGAAAATACCAGCTTTGCTGAGAGCGGCATTAAGGAAAGATCTGCTGTGTTT
AGTAAAAGTGTTCAGAGGGGAGAGTGCAGTAGAACCCCTAGCCCTTCAGGCCAT---GCATGTTTGGCTCAGAGTCA---
-------------------------------------------------
>FlyingSqu
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAGCAGAGCAGATGGGCTAAAAGTAAGGAAA
CCTGTAATGAT---AGGCAAATTCCCAGCTCAGAGAAAAAGGTAGATTTGAATGCTGATCCCCAATATGAGAAAAAAGAA
CCAAGTAAGCAGAAACATCCATGCTCTGAGAATTCCAGAGAT---ACCCAAGAT---GTTCCTTGGATAACACTAAATAG
CAGCATTCGGAAAGTTAACGAGTGGTTTTCCAGAAGTGACGAAATGTTAACTTCTGATGACTCAGATGATGGGGGTTCTG
AATCAAATGCTGAAATAGCTGGTATATTAGAAATTCCAAAT------GAAGTAGATGGATTTTCTGGTTCTTCGGAGAAA
ATAGACTTGTTGGCCACTGATCCGCATAATGCTTTAATTTCTAAATGTAAAAGAGTCTGCTCCAAAGCAGTCAAGAGTAA
T---ATTGAAGATAAAATATTTGGGAAAACCTATCAGAGGAAGGCAAGCCTCCCTAACTTGAGCCATATAACTGAAAATC
TAATTATAGGAGCATTTGCCAGAGAACCACAAATAACACAAGAGCTTGCCAGAGAACCACAAATAACACAACAGCTTGCC
AGAGAACCACAAATAACACAAGAGCGTCCCCTCACAAATAAATTAAGACGTAAAAGGAGAACTACATCATGCCTTCATCC
TGAGGACTTTATCAAGAAAACAGATTTGGCAATTGTTCAAAAGACTCCTGAAAAGATAAATCAGGGAACTGACCAAATGG
AACACAAT---------GATCAAGTAATGAATATTACTAATAGTGGTCAAGAGAATGAAACAAAAGTTGATTAT---GTT
CAGAAAGAGAAAAATGCTAACCCAGTTGAA------TCATTGGAAAAAGAGTCTGCTTTCAGAACTAAAGCTGAACCTAT
AAGCAGTAGTATAAGCAACATGGAACTAGAATTAAATATCCACAATTCAAAAGCACCTAAGAAAAATAGGCTGAGGAGGA
AGTCTTCTACTAGGTACATTCATGTGCTTGAACCAGTAGTTAATAGAAATACAAGTCCACCTCATCACACTGAATTGCAA
ATTGATAGTTGTACTAGTAGTGAAGAA---ATAAAGACAAGA---AATTCCAACCAAATGTCAGTCAGGCATGGCAAAAA
GCTTCAGTTCATGGAAGATGCAGAACCTGCAACTGATGTCAGAAAAAGTAACAAGCCAAATGAACAAGTAAATAAGAGAC
ATACCAATGATGCTTTCCCAGGACTGAAGTTAACAGGCATATCTGGTATTTTTACTAACTGCTCAAGTTCTAGTAAAGTT
GAAGAATTTATCAATCCTAACCTTCAGAAAGAAGGAACAGAAGAGAAC---ATAGAAATAATTCAAGTGTCTGATAATAC
CCAAGACCCCAAAGATACGGTGTTAAGTGGAGAAAGG---GTTTTGCAA---ACTGAGAGATCTGTAGAGAGTACCAGTA
TTTCATTGGTACCTGATACTGATTATGGCACTCAGGACAGTATCTCATTACTGGAAGCTAACACCTTTGGA---AAAGCA
AGA---ACAGCATCAAATCAACATGTTACTCAGTATGTGGCAATTGAAAATCCCAAAGAATTTGTCCATGGTCAT---TC
TAAAGATACTAAAAATGACCCAGAGGGTTTCAAGGATTCATTGAGATGTGAAGTTAAC---CACATTCAAGAGACAAATG
TAGAAATGGAAGAAAGTGAACTTGATACTCAGTCTTTAGAGAATACATTCCAAGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATCCAGGAAATCTAGAAAAGGAATGTGCAGCCAACTATACCTCTTCCAAGTCCTTACGGAAACAAAGCCCAGA
CATGACTCTTGAATGTGAGCAAGAAGAAGAAAATTGGGGAAAGAAAGAGTCTAAAATTAGGCATGTACAGGCAATTAATG
CTACT------------ATGGTTTGTCAGAAAAGTAAG---CCAGATGATGATGCCCAATGTAGTGTTACAGAAGTCTCT
AGAATTTTTCCATCATTTCAGTTCAGA---GACAATCTAACTAAACTCATAACTGCAGATAAACATGGAATTTCACAAAA
CCCATATCATATGCCATCCATTTCTCCCAGCAGGTCATCTGTTAACACTAAATGTAGGAGAAAC---CTATCAGAAGAAA
AGTTTGAGAAAGATTCAAGGTCACCTAAAGAAGCGGTGGGATATAAGAGAATCATTCAAAGTACAGTGAGCACAATTAGC
CAAAATAACATTAGACAAAGTGCCTTTAAAGAAGCGAACTCAGGCAGTATTAATGAAGTAGGCTCTAGTACTAATGAAGT
AGGCTCCAGTATTAATGAAGTAGGTTCCAGT---------------------GGTGAAAACATTCAAGCAGAACTAGGTA
GAAACAGAGGACCCAAATTAAATGCTGTGCTTAGATTAGGTCTTATGCAACCTGAAGCCTGTAAACAAAATCTT------
CTAAGTAATTGTAAATACCCTGAAATAAAAAGACAAGGAGAAGATGAA---GTAGTTCAAGTTGTTAATGCAGATTTCTC
TCCATGTCTAATTTCAGATGACTTAGAACAA---CCTATGGGAAATAGTCATGTCACTCAGGTTTGTTCTGAGACTCCTG
ATGACCTGTTAGATGATGATGAAATACAGGAAAATACCAGCTTTGCTGAAGGTGGTATTAAGGAAAGATCTGCTGTTTTT
AGTAAGAGTGTCCAAAGAGGAGAGTTTAGCAGGAGCCCGAGTCCTTTATCCCAT---ACGTCTTTGGCTCGGAGTCATCA
AAAAGGGGCCAGGAAATTAGAGTCCTCAGAAGAGAGCATCTGTAGTGAG
>OldWorld
--------------------------------------------------------------------------------
----------------------------------------------AGCCAACAGAGCAGGTGGGCTGAGAGCAAGGAGA
GGTGCCATGAC---AGGCAGGCTCCTGGCACAGAGCAGAAGGTAGAGCTGACTGCTGAGCCCCTCCACGAGAGAAAAAGA
CGGAAAAAGCAGAACCCTCCGAGCTCCGAGGCTCATGGAGGG---ACCCAGGAT---GTTCCTTGGATCACACTAAATAG
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGACAAAGCAGTGACTTCTGACAGCACCTGTGACAGGGAGTCCA
AGTCAGATGCTGAAGAAGCTGGTGTGGCAGAAGATCCAAAA------GGCCTAGAT---------GGCTCTTCAGAGAAA
GTAGGCTTGCTGACCAGCAGTCCTCAAAAAGCTATAATCTGTGCCAGGGAGAGGGTCTGCTCCAAAGCACTGAAGAGTGA
C---ATGGAAGATAAAGTATTTGGGAAAACCTATCAGAGGAGGGTGAGCCTCCGCAGCTCAAGCCACGGAGCTGAAAGTC
TGACCGTGGGAGCGTTTGTTAGAGAGCCGCAGCTGACACTG---------------------------------------
---------------------GAGCGCTCCTTCACAAATAAAATAAAGCGCAAGAGGAGAACCACATCGTGCCTTCATCC
TGAGGACTTTGTCAAGAAAGCAGATTTGACAGTGGCTCAAAAGACTCCTGAAAAGGTAAATCAGGGAACGAAGCAAATGG
AGGAGAGT---------AGTCAAGTGACAAATACTACTAATAACAGTCATGAGAATGAGACAAAAATGGGCAAT---GTT
CAG------AGAAACCCTAACCCAGTACTA------TCAGTGGAAAAAGAGTCTGCTTCTGGTACTAACGCAGAGCCCTC
GAGCAGCAGCATAAACAACAGGGAACTAGAATTAAACACCCCTCTTGCAAAAGAACCTAAGGAAGACAGGCTGAGGGGGA
CGTCCTCAAGCAGACACAGACCT------------------------AATCCACACCTGCTGGATCACACAGAGCTGCAA
AGTGGCAATTCTATCAGCAGTGAAGAA---ATAAAGGAAAAA---AGCTCCCCCCAAATGCCCATCAGGCACAGCAGGAC
GCTGCACCTCACAGGGGCTGTGGAAGCTTCTATTGGAGCCAGGGAGAGTAAGAAGCCAGCTGGACAAGTAAGGGAGAGAC
ATGCCGGGGACTCTTTCCTAGAACCAAGATTAGCAAGACTACCTGCT---TTTACTAACAGTTCAAGCCCTGATAACCTT
AAAGAATTTGTCAACCTTAGTGCACAGACAGAAGAGATGGAAGAGAAC---CCAGAAACAGTACAAGTGTCCGAAAGTAC
CAGAGACTCCAAAGGTCCTGTGTTAAGTGGGGAAAAG---GGAGTGCAA---ACCGAGAGGTCTATGGAGAGCACTAGCA
TTTCACTAGTCCCTGACACTGACTGTGGCACTCAGGACAGTGTCTCCTTACTGGAAGCCGACAGCCTCAGG---AAGGCA
CGG---AGAGCATCGCATCAGTGTATGGCTCAATATGTGGCGGTTGCGAAGCCCAAGGAACTTCTGCCTGCTTGT---TC
TGAAGACACTGGAAACGGCACAGACAGCTTAAATGATCCATTGAGATGTGGAGGGAGC---CACATCCAGGAGGCAAATA
TAGAAATGGAAGATAGTGAACTCGACACTCAGTATTTACAGAATACATTCCAGGCTTCAAAGCGTCAGTCATTTGCTCTC
TTTTCAAATCCAGGAAACTCAAAAAAGGAATCAACAACAGTCTGTGCCCACTCTGAGTCCTTTAAGAAACAAAATCCAGA
AGTCATTCCTGAATGTGAACAAACAGAAGAAAATTGGGGCAAGAAAGTGCCTAAAATTAGTTGTGTGCAAGAGAGCGCC-
--------------CCTCTGGTTTCTCAGAGGGATCAG---CCAGGCACCAGCATCATATGTAGCGGCACAGGAGTCTCG
AGGCTCTGTCTCTCGTCTTGGTTCACA---GGCAGCAAAACTGAACTCGTCACAGCTGACAAACATGGAATTTCACAAAA
TCCATATCACATGCCATCAATTTCTCCCATCAGGCCATTTGTTAAAACTCCATGTAAGAAAACC----------------
-----------CGTTCCTCATCACCTGGAGAAGCCACAGGTAACCAGATCATCCTTCAGAGCACC---------------
------------AGCCATCGCGCTTGCAGAGAAGCCAGCTTGGGCAGTGGGAACGAAGGGGGCTCCAGT-----------
----------------------------------------------------GGGGAGCACATTCAAGCAGAACCCAGTA
GACACCAAGAGCCTGAACTA------------AGATTAGGTCTGACGCAGCCCGAAGTCTACCAGCAAAGTCTT---CCT
GTAGGTGACTGTAGACATCCCGAAATACAAACACGAGGAGAAAATGGAGTGGTAGCTCAGGCTGTCCATGCAGATTTCTC
TCCGTGTCTAATTTTAGATAACGTGGAACAG---CCTATGGGAAATAATCCTGCTTCTCAGATCTGTTCTGAGACGCCCG
ATGACCTGTTAGATGATGAGAACAAAAAGGAAGATGCCAGCTTTGCCGAAGGTGGCATTAAGGAAACTTCTGCCATTTTT
AGCAAGAGTGTCCAGACAAGACGATTCAGCAGGAGCCCCAGCCCTGTAACCAAT---ACCACTTTGGCTCAGGGTCACCG
AAGAAGGGCGAGAAAACTCGAGTCTTCTGAGGAGAGCATGTCAAGTGAG
>Mouse
TGTGGCACAGATGCTCATGCCAGCTCATTACAGCCTGAGACCAGCAGTTTATTGCTCATTGAAGACAGAATGAATGCAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCATAGCAGTGAGCCAGCAGAGCAGATGGGCTGCAAGTAAAGGAA
CATGTAACGAC---AGGCAGGTTCCCAGCACTGGGGAAAAGGTAGGTCCAAACGCTGACTCCCTTAGTGATAGAGAGAAG
TGGACTCACCCGCAAAGTCTGTGCCCTGAGAATTCTGGAGCT---ACCACCGAT---GTTCCTTGGATAACACTAAATAG
CAGCGTTCAGAAAGTTAATGAGTGGTTTTCCAGAACTGGTGAAATGTTAACTTCTGACAGCGCATCTGCCAGGAGGCACG
AGTCAAATGCTGAAGCAGCTGTTGTGTTGGAAGTTTCAAAC------GAAGTGGATGGGGGTTTTAGTTCTTCAAGGAAA
ACAGACTTAGTAACCCCCGACCCCCATCATACTTTAATGTGTAAAAGTGGAAGAGACTTCTCCAAACCAGTAGAGGATAA
T---ATCAGTGATAAAATATTTGGGAAATCCTATCAGAGAAAGGGAAGCCGCCCTCACCTGAACCATGTGACTGAA----
--ATTATAGGCACATTTATTACAGAACCACAGATAACACAA---------------------------------------
---------------------GAGCAGCCCTTCACAAATAAATTAAAACGTAAGAGA------AGTACATCCCTTCAACC
TGAGGACTTCATCAAGAAAGCAGATTCAGCAGGTGTTCAAAGGACTCCTGACAACATAAATCAGGGAACTGACCTAATGG
AGCCAAAT---------GAGCAAGCAGTGAGTACTACCAGTAACTGTCAGGAGAACAAAATAGCAGGTAGTAAT---CTC
CAGAAAGAGAAAAGCGCTCATCCAACTGAA------TCATTGAGAAAGGAACCTGCTTCCACAGCAGGAGCCAAATCTAT
AAGCAACAGTGTAAGTGATTTGGAGGTAGAATTAAACGTCCACAGTTCAAAAGCACCTAAGAAAAATAGGCTGAGGAGGA
AGTCTTCTATCAGGTGTGCTCTTCCACTTGAACCA---ATCAGTAGAAATCCAAGCCCACCTACTTGTGCTGAGCTTCAA
ATCGATAGTTGTGGTAGCAGTGAAGAA---ACAAAGAAAAAC---CATTCCAACCAACAGCCAGCCGGGCACCTTAGAGA
GCCTCAACTCATCGAAGACACTGAACCTGCAGCGGATGCCAAGAAG---AACGAGCCAAATGAACACATAAGGAAGAGAC
GTGCCAGCGATGCTTTCCCAGAAGAGAAATTAATGAACAAAGCTGGTTTATTAACTAGCTGTTCAAGTCCTAGAAAATCT
CAAGGGCCTGTCAATCCCAGCCCTCAGAGAACAGGAACA---GAGCAA---CTTGAAACACGCCAAATGTCTGACAGTGC
CAAAGAACTCGGGGATCGGGTCCTAGGAGGAGAGCCC---AGTGGCAAAACCACTGACCGATCTGAGGAGAGCACCAGCG
TATCCTTGGTACCTGACACTGACTACGACACTCAGAACAGTGTCTCAGTCCTGGACGCTCACACTGTCAGA---TATGCA
AGA---ACAGGATCCGCTCAGTGTATGACTCAGTTTGTAGCAAGCGAAAACCCCAAGGAACTCGTCCATGGC------TC
TAACAATGCTGGGAGTGGCACAGAGGGTCTCAAGCCCCCCTTGAGACACGCGCTTAAC---CTCAGTCAGGAGAAA---G
TAGAAATGGAAGACAGTGAACTTGATACTCAGTATTTGCAGAATACATTTCAAGTTTCAAAGCGTCAGTCATTTGCTTTA
TTTTCAAAACCTAGAAGTCCCCAAAAGGACTGTGCT------------CACTCTGTGCCCTCAAAGGAACTGAGTCCAAA
GGTGACAGCTAAAGGTAAACAAAAAGAA---CGTCAGGGACAGGAAGAATTTGAAATCAGTCACGTACAAGCAGTTGCGG
CCACAGTGGGCTTACCTGTGCCCTGTCAAGAAGGTAAG---CTAGCTGCTGATACAATGTGT------GATAGAGGTTGT
AGGCTTTGTCCATCATCTCATTACAGA---AGCGGGGAGAATGGACTCAGCGCCACAGGTAAATCAGGAATTTCACAAAA
CTCACATTTTAAACAATCAGTTTCTCCCATCAGGTCATCTATAAAAACTGACAATAGGAAACCT---CTGACAGAGGGAC
GATTTGAGAGACATACATCATCAACTGAGATGGCGGTGGGAAATGAGAACATTCTTCAGAGTACAGTGCACACAGTTAGC
CTGAATAAC---AGAGGAAATGCTTGTCAAGAAGCCGGCTCGGGCAGTATTCATGAAGTATGTTCCACT-----------
----------------------------------------------------GGTGACTCCTTCCCAGGACAACTAGGTA
GAAACAGAGGGCCTAAGGTGAACACTGTGCCTCCATTAGATAGTATGCAGCCTGGTGTCTGTCAGCAAAGTGTT---CCT
GTAAGTGAT---AAGTATCTTGAAATAAAAAAGCAGGAG---------------GGTGAGGCTGTCTGTGCAGACTTCTC
TCCATGTCTATTCTCAGACCATCTTGAGCAA---TCTATG---AGTGGTAAGGTTTTTCAGGTTTGCTCTGAGACACCTG
ATGACCTGCTGGATGATGTTGAAATACAGGGACATACTAGCTTTGGTGAAGGTGACATAATGGAGAGATCTGCTGTCTTT
AACGGAAGCATCCTGAGAAGGGAGTCCAGTAGGAGCCCTAGTCCTGTAACCCAT---GCATCGAAGTCTCAGAGTCTCCA
CAGAGCGTCTAGGAAATTAGAATCGTCAGAAGAGAGCGACTCCACTGAG
>Rat
TGTGGCACAGATGCTCGTGCCAGCTCATTACAGCGTGGGACCCGCAGTTTATTGTTCACTGAGGACAGACTGGATGCAGA
AAAGGCTGAATTCTGTGATAGAAGCAAACAGTCTGGCGCAGCAGTGAGCCAGCAGAGCAGATGGGCTGACAGTAAAGAAA
CATGTAATGGC---AGGCCGGTTCCCCGCACTGAGGGAAAGGCAGATCCAAATGTGGATTCCCTCTGTGGTAGAAAGCAG
TGGAATCATCCGAAAAGCCTGTGCCCTGAGAATTCTGGAGCT---ACCACTGAC---GTTCCTTGGATAACACTGAATAG
CAGCATTCAGAAAGTGAATGAGTGGTTTTCCAGAACTGGTGAAATGTTAACTTCTGACAATGCATCTGACAGGAGGCCTG
CGTCAAATGCAGAAGCTGCTGTTGTGTTAGAAGTTTCAAAT------GAAGTGGATGGATGTTTCAGTTCTTCAAAGAAA
ATAGACTTAGTTGCCCCTGATCCCGATAATGCTGTAATGTGTACAAGTGGAAGAGACTTCTCCAAGCCAGTAGAGAATAT
T---ATCAACGATAAAATATTTGGGAAAACCTATCAGAGAAAGGGAAGCCGCCCTCACTTGAACCATGTGACTGAA----
--ATTATAGGCACATTTACTACAGAACCACAGATTATACAA---------------------------------------
---------------------GAGCAGCCCTTCACAAATAAATTAAAACGCAAAAGA------AGTACATGCCTTCATCC
TGAGGACTTTATCAAGAAAGCAGATTTAACAGTTGTTCAAAGGATTTCTGAAAATTTAAATCAGGGAACTGACCAAATGG
AGCCAAAT---------GACCAAGCAATGAGTATTACCAGTAACGGTCAGGAGAACAGAGCAACAGGTAATGAT---CTT
CAGAGAGGGAGAAATGCTCATCCAATAGAA------TCATTGAGAAAGGAACCTGCTTTCACAGCTAAAGCCAAATCTAT
AAGCAACAGTATAAGTGATTTGGAGGTAGAATTAAATGTTCACAGTTCAAAAGCACCTAAGAAAAATAGGCTGAGGAGGA
AGTCT---ACCAGGTGTGTTCTTCCACTCGAACCA---ATCAGTAGAAATCCGAGCCCACCTACTTGTGCTGAACTTCAG
ATCGAGAGTTGTGGTAGCAGTGAAGAA---ACAAAGAAAAAC---AATTCCAACCAAACCCCAGCCGGGCACATTAGAGA
GCCTCAACTCATCGAAGACACAGAACCCGCAGCTGATGCCAAGAAG---AACGAGCCAAATGAACACATAAGGAAGAGAA
GTGCCAGTGATGCGTTCCCAGAAGAGAAATTAATGAACAAAGCTGGTTTATTAACTAGCTGTTCAAGTCCTAGAAAGCCT
CAAGGACCTGTCAATCCTAGCCCTGAGAGAAAAGGAATA---GAGCAA---CTTGAAATGTGCCAGATGCCTGATAATAA
CAAAGAACTCGGGGATTTGGTCCTGGGAGGAGAGCCC---AGTGGGAAACCTACTGAACCATCTGAGGAGAGCACCAGTG
TGTCCTTGGTACCCGACACAGACTACGACACCCAGAACAGTGTCTCAATACTGGAAGCGAACACTGTCAGA---TATGCA
AGA---ACAGGATCAGTTCAGTGTATGACTCAGTTTGTCGCAAGTGAAAACCCCAAGGAACTTGTCCATGGT------TC
TAACAATGCTGGAAGTGGCTCGGAGTGCTTCAAGCACCCATTGAGACATGAACTTAAC---CACAATCAAGAGACA---A
TAGAAATGGAAGACAGTGAACTTGATACTCAGTATTTGCAGAATACATTTCAAGTTTCAAAGCGTCAGTCATTTGCTTTA
TTTTCAAAACTTAGAAGTCCCCAAAAGGACTGTACTCTGGTAGGTGCCCGCTCTGTGCCCTCAAGGGAACCAAGTCCAAA
GGTGACTTCTAGAGGTGAACAAAAAGAA---CGTCAGGGACAAGAAGAGTCTGAAATCAGTCATGTACAGGCAGTCACAG
TCACAGTAGGCTTACCTGTGCCCTGTCAGGAAGGTAAG---CCAGGTGCTGTTACAATGTGT------GCTGATGTTTCT
AGGCTTTGTCCGTCATCTCATTATAGA---AGCTGTGAGAATGGACTCAACACCACAGATAAATCTGGAATTTCACAAAA
CTCACATTTTAGACAATCAGTTTCTCCCCTCAGGTCATCTATAAAAACTGACAATAGAAAAACT---CTGACAGAGGGNC
GATTTGAGAAACAT---------ACTGAAAGGGGRATGGGAAATGAGACTGCTGTTCAAAGTACAATACACACAATTAGT
CTAAATAAC---AGAGGAGATGCTTGTCTAGAAGCCAGCTCAGGCAGTGTTATTGAAGTACATTCCACT-----------
----------------------------------------------------GGTGAAAACGTCCAGGGGCAACTAGATA
GAAACAGAGGGCCTAAGGTAAACACCGTGTCTCTATTAGATAGTACACAGCCTGGTGTCTCTAAGCAGAGTGCT---CCT
GTAAGTGAT---AAGTATCTTGAAATA---AAGCAGGAG---------------AGTAAGGCTGTCAGTGCAGACTTCTC
TCCATGTCTGTTCTCAGATCATCTTGAAAAA---CCTATGAGAAGTGATAAGACTTTTCAGGTTTGCTCTGAGACACCTG
ATGACCTGTTGGATGATGTTGAAATACAGGAAAATGCTAGCTTCGGTGAAGGTGGCATAACGGAAAAGTCTGCTATTTTT
AATGGAAGTGTCCTGAGAAGAGAGTCCAGTAGGAGCCCTAGCCCTGTAACCCAT---GCATCGAAGTCGCGGAGTCTCCA
CAGAGGGTCTAGGAAATTAGAATTCTCAGAAGAGAGCGACTCCACTGAG
>NineBande
TGTGGCACAAATACTCATGCCAACTTATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGCGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCCAGCATAGAGAAAAAGGTAGATGTGGATGCTGATCCCCTGTATGGGCGAAAAGAA
CTGAATAAGCAGAAACCTCCATGCTCTGAGAGTCATAGAGAT---ACCCAAGAT---ATTCCTTGGATAATGCTGAATAG
TAGCATTCAGAAAGTTAACGAGTGGTTTTCCAGAGGTGATGACATATTAACTTCTGATGACTCACACGATAGGGGGTCTG
AATTAAATGCAGAAGTAGCTGGTGCATTGAAAGTTTCAAAA------GAAGTAGATGAATATTCTAGTTTTTCAGAGAAG
ATAGACTTAATGGCCATTAATCCTCATGATACTTTACAATTTGCAAGTGAAAGAGTCCAATTGAAACCAGCAGAGAGTAA
C---ATCAAAGATAAAATATTTGGGAAAACCTATCATAGGAAGGCAAGCCTCCCTAACTTGAGCCACATAACCCGAAACC
TTTTTATAGGAGCTATTGCTGCAGAGCCCAAGATAACACAA---------------------------------------
---------------------GAGCATTCCCTCCAAAATAAAATAAAGCGTAAAAGGAGAACTGCATCAGGCCTTCGTCC
TGAGGATTTATCCAAGAAAGTAGATTTGACAGTTGTTCAAAAAACCCCTGAAAAGATAAATCAGGGAACTGACCAAATGG
AGCAGAAT---------GATCCAGTGATGAATATTGCTAATAGTGGTCATGAGAATGAAACAAAAGGTGATTGT---GTT
CAGAAAGAGAAAAATGCTAATCCGACAGAA------TCATTGGGAAAAGAATCTGCTTTCAGAACTAAAGGCGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATATTTTAAATTCAAAAGCATCTAAGAAGAATAGGCCGAAGAGGA
TGTCCTCTACCAGGCATATTCATGCACTTGAACTAGTCGGCAGTAGAAATCCAAGCCCACCTAATCATACTGAACTACAA
ATTGATAGTTGTTCTAGCATTGAAGAG---ATAGAGAAAATA---AATTCTAACCAAAAGCCAATCAGACACAACAGAAT
GCTTCAACTCACGAAAGAAAAAGAAACCACAACTGGAGCCAAAAAGAACAATAAGCCAAATGAACAAATAAGTGAAAGAC
ATGCCAGTGATGCTTTCCTAGAACTTAAA------AATGTAACTGATTTTCTTCCTAAATGTTCAAGTTCTGATAAACTT
CAAAAATTT---AATTCTAGCCTGCAAGGAGAAGTAGCA---GAGAAC---CTAGAAACAATTCAAGTGTCTGATAGTAC
CAGGGACCCTGAAGATCTGGTGGTAAGTGGAGAAAAG---TGTTTGCAA---ACTGAAAGATCTGCAGAGAGTACCGGTA
TTTCAGTGGTACCTGATACTGATTATGGCACTCAAGACAGTATCTCATTACTGGAAGCTGACACCCTGGGG---AAGGCA
AAA---ACAGCACTAAATCAACATGTGAGTCAGTATGTAGCAATTAGAAATGCCACTGAACTTTCCCATGGTTGT---TC
TAAAGACACTAGAAATGACACTGAAGATTTTAAGGATTCATTGAGACATGAAGTTAAC---CACACTCAGGGGACAAATG
TTGAAATAGAAGAGAGTGAACTTGATACTCAGTATTTGCAGAATACATTCAAGATTTCAAAGCGCCAGTCATTTGCTCTG
TTTTCGAATCCA---------GAAAATGAATGTGCAACAGTCTGTGCCCACTCCAGGTTCTTAGGGAAACAAAGTCCAAA
AGTCACCTTTGAATGTAGACATAAAGAAGAAAATCAGGGGAAGAAAGAGTCTAAAATCAAACATGTGCAGGTAATTCACA
CAACTGCAGGCTTTCCTATAGTTTGTCAGAAAGATAAG---CCAGGTGATTATGCCAAAGGTAGCATTCAAGGAGTCTCT
AGGCTTTGTCAGTCCTCTCAGGCCAGA---GGCAATGAATCTGAACTCATTAATTCAAATGAACATGAAATTTCACAAAA
CCCAGATCAAATGCCATCACTTTCTCACATGAAGTCATCTGTTAAAACTAAATGTAAGGAAAAC---CTGTCAGAGGAAA
AGTTTGAGGAACTTACAGTGTCACTTGAAAGAACAATGGTAAATGAGAACATCATTCAAAGTACAGTAAGCACAATTAGC
CACAGTAACATTAGAGAAAACACTTTTAAAGAAGCCAGCTCAAGCAGTATTAATGAAGTAGGGTCCAGT-----------
----------------------------------------------------GATGAGAACATTCAAGCAGAAGTAGGTA
GAAACAGAGCACCTAAATTAAATGCTATGCTCAGATTAGGTCTTATGCAACCTGAAGTCTATAAGCAAAGTCTT---CCT
ATAACCAATTGTAAATATCCTGAAATAAAAAGTCAAGGAGAAAATGAAGAAGCAATTCGGGCTGTTGATATAGACTTCTC
TCCATGTCTAATTTCAGATAACCTACAACTA---CCTATGGGAAATAGTTGTGCTTCCCAGATTTGTTCTGAGACACCTG
ATGACTTGTTAGATGATGATGAAATAAAGGAAAATAACTGCTTTGCTGAAAGTGACATTAAGGAAAGATCTGCTATTTTT
AGCAAAACTGTCCAGAAAAGAGAGTTCAGAAGGAGCCCTAGCCCTTTAGTCCAT---ACAAGTTTTGCTCAGGGTCACCA
AAGAAAGCCCAGGAAATTAGACTCCTCAGAAGAGGACGTATCTAGTGAG
>HairyArma
TGTGGCACAAATACTCATGCCAACTTATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAGTGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGCGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCCAACACAGAGAAAAAGGTAGATGTGGCTGCTGATTCCCTGTATGGGCGAAAAGAA
CTGAATAAGCAGAAACTTCCATGCTCTGAGAGTCCTAGAGAT---ACCCAAGAT---ATTCCTTGGATAACGCTGAATAG
TAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGACCTATTAACTTCTGATGACTCACACGATGGGGGGTCTG
AATCAAAAGCAGAAGTAGCTGGTGCATTAAAAGTTCCAAAT------GAAGTAAATGGATATTCTAGTTCTTCAGAGAAG
ATAGACTTATTGGCCAGTGATCCTCATAATGCTTTAATATTTGCAAGTGAAAGAGTCCAATCCAAACCAGCAGAGAGTAA
C---ATCAAAGATAAAATATTTGGGAAAACCTATCACAGGAAGGCAAGCTTTCCTAACTTGAGCCACATAACTGAGGATC
TTTTTATAGGAGCTATTGCTACAGAACCCAAGATAATACAA---------------------------------------
---------------------GAGCATTCCCTCACAAATAAAATAAAGCGTAAAAGGAGAACTACGTCATGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGACAGTTGTTCAAAAGACGCCTGAAAAGATAAATCAGGGAACTGACCAAATGG
AGCAGAAT---------GATCAAGTGATGAATAGTGCTAATAGTGGTCATGAAAATGAAACAAAAGGTGATTAT---GTT
CAGAAAGAGGAAAATGCTAACCCAATAGAA------TCATTGGAAAAAGAATCTGCTTTCAGAACTAAAGGTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATATCTATAATTCAAAAGCATCTAAGAAGAATAGGCTGAGGAGGA
TGTCCTCTACCAGGCATATTCATGCACTTGAACTAGTAGGCAATAGAAATCCAAGCCCACCTAAACATACTGAACTACAA
ATTGATAGTTGTTCTAGCACTGAAGAG---ATAGAGAAAATA---AATTCTAACCAAAAACCAATCAGACACAACAGAAT
GCTTCAACTCATGAAAGAAAAAGAAAACACAACTGGAGCTAAAAAGAATAACAAGCCAAATGAACAAATAAGTGAAAGAC
ATGCCAGTGATGTTTTCCCAGAACTAAAATTAACAAATGTAACCGATTTTCTTCCTAAATGTTCAAATCCTGATAAACTT
CAAGAATTTGTTAATTCTAGCCTGCAAGGGGAAGTAGCA---GAGAAC---CTAGAAACAATTCAAGTGTCTGATACTAC
CAGGAATCCTGAAGATCTGGTGTTAAGTGAAGGAAAG---AGTTTGCAA---ACTCAAAGGTCTGCAGAGAGTACCAGTA
TTTCAGTGGTACCTGATACTGATTATGGCACTCAAGACAGTGTCTCATTACTGGAAGCTGACACCCTGGGG---AAGGCA
AAA---ACAGCACTAAATCAACCTATGAGTCAGTATGCAGCAATTAAAAATGCCACTGAACTCTCCCATGGTTGT---GC
TAAAGACACTAGAAATGACACTGAGGATTTTAAGGATCCGTTGAGACATGAAGTTACC---CACACTCAGGAGACTAGTG
TAGAAATGGAAGAGAGTGAACTTGATACTCAGTATTTACAGAATACATTCAAGATTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCGAATCCA---------GAAAATGAATGCGCAACAGTGTGTGCCCACTCCAGGTTCTTAGGCAAACAAAGTCCAAA
AGTCATTTTTGAATGTAGGCAAAAAGAAGAAAATCAGGGGAAGAAAGAGTCTAAAATCAAACATGTGCAGGCAGTTCATA
CAACTGCAGGCTTTCCTGTAGTTTGTCAGAAAGATAAG---CCAGGTGATTATGCCAAATGTAGCATTCAAGAAGTCTCT
AGGCTTTGTCAGTCCTCTCAGTTCAGA---GGCAATGAATCTGAACTCATTACTGCAAATGAACATGAAATTTCACAAAA
CCCAGATCAAATGCCATCACTTTCTCACATCAGGTCATCTGTTAAAACTAAATGTAAGGAAAAC---CTGTCAGAGGAAA
AGTTTGAGGAACTTACAATATCACTTGAAAGAACAGTGGGAAATGAGAACATCGTTCAAAGTACAGTAAGCACAATTAGC
CACAATAACATTAGAGAAAACGCTTTTAAAGAAGCCAGCTCAAGCAGTATTAATGAAGTAGGTTCTAGT-----------
----------------------------------------------------GGTGAAAACATTCAAGCAGAACTAGGTA
GAAACAGAGCACCTAAATTAAATGCTATGCTCAGATTAGGTCTTATGCAACCTGAAGTCTATAAGCAAAGTCTT---CCT
ATAACTAGTTGTAAACATCCTGAAATAAAAAGGCAAGGAGAAAATGAAGAAGCAATTCAGGCTGTTGATACTGATTTCTC
TCCACATCTAATTTCAGATAACCTAGAACTA---CCTATGGGAAATAGTCATGTTTCTCAGATTTGTTCTGAGACGCCTG
ATGATTTGTTAGATGATGATGAAATAAAGGAAAATAACAGCTTTGCTGAARATGGCATTAAGGAAAGATCTGCTGTTTTT
AGCAAAAGTGTCCAGAAAAGAGAGTTCAGAAGGAGTCCTAGCCCTTTAGGCCAT---ACAAGTTTGGCTCAGGGTCACCA
AAGAAGGGCCAGGAAATTAGACTCCTCAGAAGAGGACGTATCTAGTGAG
>Anteater
TGTGGCACAAATATTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAAAGAATGTAGA
AAAGGCTGAATTCTGTGATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAGCAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCACACTACCAGCACAGAGAAAAAAGTAGATGTGGATGCTGATCCCCTGCATCGGAGAAAAGAA
CTGAAGAAGTGGAAATCTCCATACTCTGAGAATCCTAGAGGT---ACCCAAGAT---ATTCCTTGGATAACACTGAATAG
TAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGACATATTGACTTCTAATGACTCATGCAATGAGGGGTCTG
AATTAAATGCAGAAGTAGCTGATGCATCAAAAGTTCCAAAT------GACGTAGATAGATATTCTGGTTCTTCAGAGAAA
ATAGACTTAATAGCCAGTGACCCTCATAATGCTTTAATATGTGCAAGTGAAAAAGTCCAGTCCAAACCAACAGAGAGTAA
T---ATCAAAGATAAAATATTTGGGAAAACCTATCACAGGAAGGCAAGCCTCCCTAACTTGAGCCGTATAGCTAAAGATC
TTTTTATAGGAGCTGTTGCTGCAGAACCTAAGATAACACAA---------------------------------------
---------------------GAGCTCCCCCTGACAAATGAAATGAAGCTTAAAAGGAGGACTACATCAGGACTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGACAGTTGTTCAAAAGAAGCCTAAAATGATAAATCAGGGAACTAACCAAATAG
AGCAGAAT---------TGTCAACTGATGAATATTGCCAATAGTGGTAATGAAAATGAAACAAAAGGTGATTTT---GTT
CAGAAGGAGAAAAGTGCTAACCCAACAGAA------TCATCAGAAAAAGAATCTGCTTTCAGAACTAAAGGTGAACCTAT
AAGTAGTAGTATAAGCAATATGAAACTAGAATTAAATACCTGCAATTCAAAAGCATCTAAGAAGAATAGGCTGAGGAGAA
TGTCCTCTACCAGGCATATGCATGCACTTGAACTAGTAGCCAATAGAAAGCCAAGCCAGCCTAATCACACTGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAA---ATAAAGAAAAAA---AAATCTGACCAAAAGCCAATAAGACACAGCAGAAC
AGTTCAATTCATGAAAGATAAAGAAACTGCAATTGGAGCCAAGAAGAGTAACAAGCGAAATGAACAAATAAATAAAAGAC
ATGCCAGTGATGCTTTCCCAGAACTAAATTTAACAAACGTAACTGGTTTTCCTACTAAATGTTCAAATTCTGATAAACTT
CAAGAATTTGTCAATTCTAGCCTGCAAGGAGAAGCAGCA---GAGAAC---CTAGAAACAATACAAGTGTCTGATACTAC
CATGGACCCTGAAGGTCTGGTATTAAGTGAAGGAAAG---AATTTGCAA---ACTGAAAGATCTGTAGAGAGCACCAGTA
TTTCATTGGTGCCTGACACTGATTATGGCACTCAAGATAGTATCTCATTACTAGAAGCTGCTACCCTAGGG---AAAGCA
AAA---GCAGCACCAAATCAACATGTGAGTCTGTGTGCAGCAGTTGGAAATGCCACTGAACTTGTCCATGGTTGT---TC
TAAAGATACTAGAAATGACACTGAAGATTTTAAGGATTCATTGAGACATGAAGTTAAC---CACACACAAGGGACAGTCA
TAGAAAAGGAAGAGAGTGAACTTGATACTCAGTATTTNNNNNNNNNNTACAAGATTTCAAAGCGTCAGTCATTTGCTCTG
TATTCAAATTCT---------GAAAAGGAATGTGTAACAATCTGTGCCCACTCCAGGTCCGTACGGAAACAAAGTCCAAA
AGTAACTTTTGACTATAGACAAAAAGAAGAAAATCAAGGAAAGAAAGAGTCTAAGATCAAACATGTGCAGGCAGTTCATA
CAACCGCAGGCTTCTCTGTAGTTTGTCAGAAAGATAAGAAGCCCCATGATTATGCCAAGTGTAGCATTCAGGGAGTCTCT
AAGCTTTGTGAGTCATCTCAGTTCAGA---GGCAATGAATCTGAACTCATTACTGCAAACGAACATGGAATTTCCCCAAA
TCCAGATCAAATGCCATCACTTTCTCCCAACAGGTCATCTGTTAAAACTAAATATAAGAAAAAC---TTGTCAGAAGAAA
GGTTTGAGGAACATACAGTGTCACTTGATAGAGCAGTGGGAAATGAGAGCATCATTCAAAGTACAGTAAGCACAATTAGC
CAAAATAACATTAGAGAAAGCACTTTTAAAGAAGCCAGCTCAAGCAGTATTAATGAAGTAGGTTCCAGTATTAATGAAGT
GGGTTCCAGTATTAATGAAGTGGGTTCCAGT---------------------GGTGAGAACGTTCAAGCAGAGCTAGGTA
GAAACAGA---CCTAAGCTAAATGCTATGCTCAGATTAGGTCTTATGCAACCTGAAGTCTATGAGCAAAATCTT---CCT
ATAACTAATTTTAAACTTTCTGAAATTAAAAAACAAGGAGAAAATGAAGAAGTAGTTCAGGCTGTTAATACAGATTTCTC
CCCATGTCTAATTTCAGATAACCTAGAACTG---CCTATGGGAAGTAGTCGTGTTTCTCAGATTTGTTCTGAGACACCTG
ATGACCTGTTAGATGATGATGAAATAAAGGAAAATAACAGCTTTGCTGAAAGTGGCGTTAAGGAAAGATCTGCTGTTTTT
AGCAAAAGTGTCCAGAGAAGAGAATTCAGAAGGAGCCCTAGCCCTTTAGCCCAA---ACAAGTGTGGCTCAGGGTCACCA
AAGAGGGGCCAGGAAATTAGCCTCCTCAGAAGNGGACNAGTCTAGNGAG
>Sloth
TGTGGCACATATACTCATGCCAGCTCATTACAGCGTGAGAACAGCAGTTTATTACTCACTAAAAACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAGCAGCCTGGCTTAGCAAGGAGCCAACAGAACAGATGGGCTGAAAGTAAGGAAA
CACGTAATGAT---AGGCAGACTCCCAGCACAGAGAAAAAGGTAGATGTGGATGCTGATCCCCTGTATGGGCGAAAAGAA
CTGAATAAGCAGAAACCTCCATGCTCTGAGAGTCCTCAAAAT---ACCCAAGAT---ATTCCTTGGATAACACTGAATAG
TAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGACATACTAACTTCTGATGACTCACACAATGGGGGGTCTG
AATCAAATGCAGAAGTAGTTGGTGCATTGAAAGTTCCAAAT------GAAGTAGATGGATATTCTGGTTCTTCAGAGAAG
ATAGACTTAATAGCCAGTGATCCTCACAATGCTTTAATATTTGCAGGTGAAAGAGTCCAGTCCAAACCAACAGAGACTAA
C---ATTGAAGATAAAATATTTGGGAAAACCTATCACAGGAAGGCAAGCCTCCCTAACTTGAGCCACATAGCTGAAAATC
TTTTTATAGGAGCCATTGCTACAAAACCTAAGATAACACAA---------------------------------------
---------------------GAGCACCCCCTGACAAAGAAAATAAAGCATAAAAGTAGGACTACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTCGATTTGACAGTTGTTCAAAAGATGCCTGAAAAGATAAATCAGGGAACTGACCAAATGG
AGCAGAAG------AATAGTCAAGTGATAAATATTGCTAATAGTGGTCATGAGAATGAAACAAAAGATGATTAT---GTT
CAGAAAGAGAAAAATGCTAACCCAACAGAA------TCATTGGAAAAAGAATCTGCTTTCAGAACTGAAGGTGAACCCAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATATCTTCAATTCAAAAGTATCTAAGAAGAATAGGCTGAAGAGGA
TGTCCTCTACCAGGCATATTCATGCACTTGAACTAGTAGCCAATAGAAATCCAAGCCAACCTAATCATAATGAACTACAA
ATTGATAGTTGTTCTAGCAGTGAAGAG---ATAAAGAAAGAA---AATTCTGTCCAAAAGCCAATAAGGCACAGCAGAAT
GCTTCAACTCCTGAAAGGTAAAGAAACTCCAACCGTAACCAAGAAGAGTAACAAGCGAAATGAACAAATAAGTAAAAGGC
ATTCCAGTGATGCTTTCCCAGAACTAAATTTAACAAATGTAACTGGTTTTCTTACTAAATGTTCAAGTTCTGATAAACTT
CAAGAATTTGTCAATTCTAGCCTGCAAGGAGAAGTAGCA---GAGAAC---CTAGAAACAATTCAAGTGTCTGATAGTAC
CAGAGACCCCGGAGCTCTGGTGTTAAGTGGAGGAAAG---GGTTTGCAA---ACTGAAAGATCTCTAGAGAGTACCAGTA
TTACAATGATACCTGAAACTGATTATGACACTCAAGACAGTATCTCCTTACTGGAAGCTGACACCCTAGGG---AAAGCA
AAA---GCAGCACCAAATCAACATGTGAGTCAGTATGCAGCAATTGGAAATGCCACTAAACTTTTCCATGGTTGT---TC
TAAAGATACTAGAAGTGACACTGAGAATTTTAAGGATCCATTGAGACATGAAGTTAAC---CACACACAGGAGACATTTG
TAGAAATGGAAGAGAGTGAACTTGATACTCAGTATTTACAGAATACATTCAAGATTTCAAAGCGTCAATCATTTGCTCTG
TTTTCAAATCCA---------GAAAAGGAATGCGCAACAGTCTCTGCCCACTCCAGGCCCTTAGGAAAACAAAGTCCAAA
AGTCACTTTTGACTGTAGACAAAAAGAA---GATCAGGAGAAGAAGGAGTCTAAAATCAAACACGTGCAGGCAGTTCATA
CAACTGCAGACTTTCCTGTAGTTTGTCAGAAAGATAAG---CCAGGTGATTATGCTAAATGTAGCATTCAAGGAGTCTCT
AAGCTTTGTCAGTTATTTCAGTTCAGA---GGCAATGAATCTGAACCCATTACTGCAGATGAACATGAAATTTCACAAAA
TCCAGATCAGATGCCATCACTTTCTCCCATGAAGTCATCTGTTAAAAGTAAATTTAAGGAAAAC---CTGTCAGAGGAAA
GATTTGAGGAACATACAGTATCACTTGAAAGAGCAGTGGGAAAGGAGCACATCATTCAAAGGACAGTGAGTCCAATTAGC
CAAAATAACATTAGAGAAAGCGCTTTTAAAGAAGCCAGCTCAAGCAGTATCAATGAAGTAGGTTCCAGTGTTAATGAAGT
AGGTTCCAGTGTTAATGAAGTAGGTTCCAGT---------------------GGTGAGAACACTCAAGCAGAGCTAGGTA
GAAACAGAGGATCTAAATTAAGTGCTATGCTCAGATTAAGTCTTATGCAACCTGAAGTCTATAAGCAAAGTCTT---CCT
ATAACTAATTGTAAGCATCCTGAAATTAAAAAGCAAGGAGAAAATGAAGAAGTAGTTCAGGCTGTTAAAACA--------
----TGTCTAATTTCAGATAACCTAGAACTA---CCTATGGGAAGTAGTCATGCTTCTCAGATTTGTTCTGAGACACCTG
ATGATCTGTTAGATGATGGTGAAATAAAGGAAAATAACAGCTTTGCTGAAAGTGGCATTAAGGAAAGATCTGCTGTTTTT
ACCAAAAGTGTCCAGAAAAGAGAGTTCAGAAGGAGCCCGAGCCCGTTAGCCCAA---ACAAGGGTCACC---------AA
AAGACGGGCCAGGAAATTAGACTCCTCAGAAGAGGATGTGTCTAGTGAG
>Dugong
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAATAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTCATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAGCAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCTAGCACAGAGAAAAAGGTAGATATGAATGCTAATCCATTGTATGAGAGAAAAGAA
GTGAATAAGCAGAAACCTCCATGCTCCGAGAGTGTTAGAGAT---ACACAGGAT---ATTCCTTGGCTAACACTGAATAG
TAGCATTCAGAAAGTTAATGAGTGGTTTTTCAGAAGTGATGGCCTG---------GATGACTTGCATGATAAGGGGTCTG
AGTCAAATGCAGAAGTAGCTGGTGCTTTAGAAGTTCCAGAA------GAAGTACATGGATATTCTAGTTCTTCAGAGAAA
ATAGACTTAATGGCTAGTGATCCTCATAGTGCTTTAATATGTGAAAGTGAAAGAGTCCTCTTCAAACCAGCAGAAAGTAA
C---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAATTCTCCCTCATTTGAGCCATGTAACTGAAGATC
TAATTATAGGAGCTGTTGCTACAGAACCTCAGATAGCACAA---------------------------------------
---------------------GAACGTCCTCTTACAAATAAATTAAAGCGTAAAAGGAGA---ACATCAGGCCTTCATCC
TGAGGATTTCATCAAGAAAGTAGATTTGGCAGTTGTTCAAAAGACTCCTGAAAAGATAAATCAAGAAACTGACCAAGTGG
AGCAGAAT---------GGTCAAGTGATGAATATTGCTAATGGTGGTCATGGAAATGAAACAAAAGATGATTAT---GTT
CAGAAAGAGAAGAATGCTAACCCAACAGAA------TCACTGACAAAGGAATCTGCTTTCAGAACTAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATATGCATAATTCAAAAGCACCGAAGAAGAACAGGCTGAGGAGGA
AGTCCTCTACCAGGCATATTCATGCACTTGAACTAGTAGTCAATAGAAATCCAAGTCCACCTACTCATACTGAACTACAA
ATTGATAGTTGGTCTAGCAGTGAAGAG---ATAAAGAAA------AGTTCTGAGCAAAAGCCAGTCAGACACAACAGAAA
CCTTCAACTCATGAAAAACCAAGAAACCACAACTGGAGCCAAGAAAAGTAACAAGCCAAAGGAACAAATAAGTAAAAGAC
ATGCCAGTGACGCTTACCCAGAACTAAATTTAACAAGCACAACTGGCTTAATTACTAACTGTTCAAGTTCTCATAATTAT
CAAGAATTT---AATCCTAGCCTTCAGGGAGAAGAAATAGAAGAAAAT---CTGGGAACAATTCAAGTGTCTAATAGAAC
CAGAGACCCCGAGGATCTAGTGTTAAATGGAGGAAGA---GGTTTGCAA---ACTGAAATATCTGTTGAGAGTACCAGTA
TCTCAGTGATACCTGATACTGACTATGGCAGTCAGAACAGCATCTCATTACTGGAAGCTGACACCCTCAGG---AAGGCA
AAA---ACAGCACCAAATCAATGTGCAAGTCAGTGTGCAGCAATTGAAAACCCCAATGAACTTATCCATGGTTGT---CC
TAAAGATACTAGAAATGACACAGAGGATTTTAAGGATCTGTTGAGATGTGAAGTTAAC---CACATTCAGGAGACGTGCG
TAGAAATGGAAGACAGNGAACTTGATACTCAGTATTTGCAGAGTACATTCAAGGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATCCA---------GAAAAGGAATGTGCAACAATTTGTGCCCACTCCAAGTCCTTAAGGAAACAAAGTCCAAA
AGTCACTCCTGAGTATGGAGAAGAAGAAGAAAATCAAGGGAACAAAGAGTCTAAAATCAAGCATGAGCAGGCAGTTCATA
CGACTGCGGGCTATCCTGAGGATTGTCAGAAAGAGAAGAAGCCAAGTGATTATACCAAAAGTAGCATCAAAGGAGTCTCT
AGGCTTTGTCAGTCATCTCAGTTCAGA---GGCAGTGAATCCCAACACATTACTGCAGGTGAACATGGAATTTCACAAAA
TCCAGATCAAATGCCATTGCTTTCTCCCATCAGGGCATCTGTTAAAAGT------AAGAAAAAC---TTGTCAGAAGAAA
GGTTTGAGGAACATACAATATCACTTGAAAGAGCAGTAGGAAATGAGAGCATCGTTCAAAGTACAGTGAGCACAGTTAGC
CAAAATGACATTAAGGAAAGTGCTTCTAAAGAAGCCAGCTCAAGCAGTATTAATGAAGTAGGTTCTAGT-----------
----------------------------------------------------GGCGAAAACATTCGAGCAGAGCTAGGTA
GGAACAGAGGACCTAAATTAAATGCTGTGCTCAGATTAGGTCTTATGCAACCTGAAGTCTATAAACAAAGTCTT---CCT
GTAAGTAACTGTAAACGTCCTGAAATAAAAAGGCAAGGAGAAAATGAAGGAGTAGTTCAGGATGTTAATATGGATTTCTC
TCCATGTCTAATTTCAGATAACCTAGAACAA---CCTATGGGAAGTAGTCGTGCTTCTCAGATTTGTTCTGAGACTCCTG
ATGACCTGTTAGATGATGATGAAATAAAGGAAAATATCAGCTTTGCTGAAAGTGGCATTAAGGAAAGATCTGCTGTTTTT
AGTAAA---GACCAGAGAAGAGAGTTCAGAAGGAACCCAAGCCCTTTATCCCAT---TCAGGTTTGGCTCAGGGTCACCT
AAGAGGGGCCAGGGAATTAGAGTCCTCAGACGAGAACATATCTAGTGAG
>Manatee
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAATAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTCATAAAAGCAAACAGCCTGGCTTAACAAGGAGCCAGCAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCTAGCACAGAGAAAAAGGTAGATATGAATGCTAATCCATTGTATGAGAGAAAAGAA
GTGAATAAGCAGAAACCTCCATGCTCCGAGAGTGTTAGAGAT---ACACAAGAT---ATTCCTTGGCTGACACTGAATAG
TAGCATTCAGAAAGTTAATGAGTGGTTTTTCAGAAGTGATGGCCTG---------GATGACTTGCATGATAAGGGGTCTG
AATCAAATGCAGAAGTAGCTGGTGCATTAGAAGTTCCAGAA------GAAGTACATGGATATTCTAGTTCTTCAGAGAAA
ATAGACTTAATGGCCAGTGATCCTCATAGTGCTTTAATATGTGAAAGTGAAAGAGTCCTCTCCAAACCAGCAGAAAGTAA
C---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAATTCTCCCTCATTTGAGCCATGTAACTGAAGATC
TAATTATAGGAGCTGTTGCTACAGAACCTCAGATAGCACAA---------------------------------------
---------------------GAACGTCCCCTTACAAATAAATTAAAGCGTAAAAGGAGA---ACATCAGGCCTTCATCC
TGAGGATTTCATCAAGAAAGTAGATTTGGCAGTTGTTCAAAAGACTCCTGAAAAGATAAATCAGGAAACTGACCAAGTGG
AGCAGAAT---------GGTCAAGTGATGAATATTGCTAATGGTGGTCATGAAAATGAAACAAAAGATGATTAT---GTT
CAGAAGGAGAAGAATGCTAACCCAACAGAA------TCACTGACAAAGGAATCTGCTTTCAGAACTAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATATGCATAATTCAAAAGCACTGAAGAAGAATCGGCTGAGGAGGA
AGTCCTCTACCAGGCATATTCATGCACTTGAACTAGTAGTCAATAGAAATCCAAGTCCACCTACTCATACTGAACTACAA
ATTGATAGTTGGTCTAGCAGTGACGAG---ATAAAGAAA------AGTTCTGAGCAAAAGCCAGTCAGACACAACAGAAA
CCTTCAACTCATGAAAAACCAAGAAACCACAACTGGAGCCAAGAAAAGTAACAAGCCAAAGGAACAAATAAGTAAAAGAC
ATGCCAGTGACACTTACCCAGAACTAAATTTAACAAGCACAACTGGCTTAATTACTAACTGTTCAAGTTCTCATAATTAT
CAAAAATTTGTTAATCCTAGCCTTCAGGGAGAAGAAATAGAAGAAAAT---CTGGGAGCAACTCAAGTGTCTAATAGAAC
CAGAGACCCCGAGGATCTAGTGTTAAATGGAGGAAGA---GGTTTGCAA---ACTGAAATATCTGTTGAGAGTACCAGTA
TCTCAGTGATACCTGATACTGATTATGGCAGTCAGAACAGCATCTCATTACTGGAAGCTGACACCCTCAGG---AAGGCA
AAA---ACAGCACCAAATCACTGTGCAAGTCAGTGTGCAGCAATTGAAAACCCCAATGAACTTATCCATGGTTGT---CC
TAAAGATACTAGAAATGACACAGAGGATTTTAAGGATCTGTTGAGATGTGAAGTTAAC---CACGTTCAGGAGACATGCA
TAGAAATGGAAGACAGTGAACTTGATACTCAGTATTTGCAGAGTACATTCAAGGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATCCA---------GAAAAGGAATGTGCAACAATTTGTGCCCACTCCAAGTCCTTAAGGAAACAAAGTCCAAA
AGTCACTCCTGAGTATGGAGAAAAAGAAGAAAATCAAGGGAACAAAGAGTCTAAAATCAAGCATGAGCAGGCAGTTCATA
CAACTGCTGGCTATCCTGAGGATTGTCAGAAAGAGAAGAAGCCAAGTGATTATACCAAATGTAGCACTAAAGGAGTCTCT
AGGCTTTGTCAGTCATCTCAGTTCAGA---GGCAGTGAATCCGAACACATT---ACAGGTGAACATGGAATTTCACAAAA
TCCAGATCAAATGCCATTGCTTTCTCCCATCAGGGCATCTGTTAAAAGT------AAGAAAAAC---TTGTCAGAAGAAA
GGTTTGAGGAACATACAATATCACTTGAAAGAGCAGTAGGAAATGAGAGCATCGTTCAAAGTACAGTGAGCACAGTTAGC
CAAAATAACATTAAGGAAAGTGCTTCTAAAGAAGCCAGCTCAAGCAGTATTAATGAAGTAGGTTCCAGTGTTAATGAAGT
AGGTTCTAGT------------------------------------------GGCGAAAACATTGAAGCAGAGCTAGGTA
GGAACAGAGGACCTAAATTAAATGCTGTGCTCAGATTAGGTCTTATGCAACCTGAAGTGTATAAACAAAGTCTT---CCT
GTAAGTAACTGTAAACATCCTGAAATAAAAAGGCAAGGAGAAAATGAAGGAGTCGTTGAGGATGTTAATATGGATTTCTC
TCCATGTCTAATTTCAGATAACCTAGAACAA---CCTATGGGAAGTAGTCGTGCTTCTCAGATTTGTTCTGAGACTCCTG
ATGACCTGTTAGATGATGATGAAATAAAGGAAAATATCAGCTTTGCTGAAAGTGGCATTAAGGAAAGATCTGCTGTTTTT
AGTAAA---GACCAGAGAAGAGAGTTCAGAAGGAACCCAAGCCCTTTATCCCGT---TCAGGTTTGGCTCAGGGTCACCT
AAGAGGGGCCAGGGAATTAGAGTCCTCAGAAGAGAACATATCTAGTGAG
>AfricanEl
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATAAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAACAAAAGCAAACAGCCTGGCTTAGCAAGAAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCTAGCACAGAGAAAAAGGTAGATGTGAATGCTGATCCCTTGTATGAGAGAAAAGAA
GTGAATAAGCAGAAACCTCCACGCTCTGAGAATCTTAGAGAC---ACCCAAGAT---ATTCCTTGGATAACACTGAATAG
TAGCATTCAGAAAGTTAATGAGTGGTTTTTCAGAAGTGACGGCCTG---------GATGTCTTAAATGATGAGGGGCCTG
AATCCAGTGCAGAAGTAGCTGGTGCATTAGAAGTTCCAAAT------GAAGTACAT------TCTAATTCTTCAGAGAAA
ATAGACCTAATGGCCAGTGATCTGCATGGTGCTTTAATATGTGAAAGTGAAAGAGTCCCCTCCAAACCAGCAGAAAGTAA
C---ATCGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAGGTATGTCTCATTTGAGCCACATAACTGAAGATC
TGATTATGGGAGCTATTGCTTCAGAACCTCAGATAGCACGA---------------------------------------
---------------------GAACATCCTTTTACAAATAAATTAAAGCGTAAAAGGAGA---ACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGGCAGTTGTTCAAAAGATCCCTGAAAAGATAAATCAGGAAACTGACCATGTGG
AGCAGAAC---------GGTCAAGTGATGAATATTGCTAATGGTGGTCGTGAGAATGAAACAAAAGGTGATTAT---GTT
CAGAAAGAGAAGAATGCTATCCCAACAGAA------TCATTGGCAAAAGAATCTGCTTTCAGAACTAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATATGCATAATTCAAAAGCACCAAAGAAGAATAGGCTGAGGAGGA
AGTCGTCAACCAGACATATTCATGCACTTGAACTAGTAGTCAATAGAAATCCAAGTCCACCTACTCATACTGAACTACAA
ATTGACAGTTGGTCTAGCAGTGAAGAG---ACAAAGAAAAAA---AGTTCTGAGCAAAAGCCAATCAGACACAACAGAAA
CCTTCAACTCATGAAAAATCAAGAAACCGCAACTGGAGCCAAGAAGAGTAACAAGCCAAAGGAACAAATAAGTAAAAGAC
ATGGCGCTGACTCTTACCCAGAACTACATTTAACAACCACAGCTGGCTTTATTACTAAGTGTTCAAGTTCTGATAATCTT
CAAGAATTTGTCAATCCTAGCCTTCAAGGAGAGAAAACAGAAGAAAAC---CTGGAAACAATTCAAGTGTCTAATATTAC
CAAAGAGCCCAAGGATCTAGTGTTAAATGGAGGAAGA---GATTTGCAA---ACCAAAAAATCTATTGAGAGTACCAATA
TCTCAGTGATACCTGATACTGTTTATGGCACTCAGGACAGCGTCTCATTGCTGGGAGCTGACACCCCAGGG---AAGGCA
AAA---ACAGCACCAAATCGATGTGCAAGTCAGTGTACAGCAATTGAAAACCCAAGTGAACTTACCAACAGTTGT---CC
TAAAGATACTAGAAATGACACAGAGGGTTTTAAGGATCTATTGAGATGTGAAGCTAGC---CACATTCAGGAGACATGCA
TAGAAATAGAAGAGAGTGAACTTGATACTCAGTATTTGCAGAGTACATTCAAGGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATCCA---------GAAAAGAAATGTGCAACAATTTGTGCCCACTCCAAGTCCTTAAGGAAGCAAAGCCCAAA
AGTCACTCTTGTGTGTGGAGAAAAAGAAGAAAATCAAGGGAACAGAGAGCCTAAAATCAAGCATGAGCAGGCAGTTCATA
TGCCTACAGGCTATCCTGAGGCTTGTCAGAAAGAGAAG---CCAAGTGACTATACCAAATATAGCATTAAAGGAGTCTCT
GGGCTTTGTCAGTCATCTCAGTTCAGA---GGCAGTGAATCTGAACTCATTACTGCAGATGGACATGGAATCTCACAAAA
CCCAGATCAAATACCATCACTTTCTCCCACCAGGTCATCTGTTAAAACTAAATGTAAGACAAAC---CTGTTGGAAGAAA
GGTTTGAGGAACATACAATATCACTTGAAAGAGCAATGAGAAATGAGAACGTCATTCAAAGTACAGTGAGCACAGTTAGC
CAAAATAACATTAGGGAAAGTGCTTCTAAAGAAGCCAGCTCAAGCAGTATTAATGAAGTATGTTCCAGTATTAATGAAGT
AGGTTCTAGT------------------------------------------GGTGAAAACATTCAAGCAGAAATAAGTA
GGAAGAGAGGACCTAAATTAAATGCTGTGCTCAGATTAGGTCTTATGCAACCTGAAGTTTATAAACAAAGTCTT---CCT
ATAAGTGACTGTAAACATCCTGGAATAAAAACGCAAGGAGAAAATGAAGGAGTAGTTCAGGCTGTTAATACAGATTTCTC
CCCATGTCTAATTTCAGATAACCTAGAACAA---CCTGTGGGAACTAGTCGTGCTTCTCAGGTTTGTTCTGAGACTCCCG
ACGACCTGTTAGATGATGATGAAATAAAGGAAAATATCAGCTTTGCTGAAAACGGCATTAAGGAAAGATCT---GTTTTT
ATTAAAGATGACCAGAGAAGAGAGTTCAGAAGGAACCCAAGCCCTTTATCCCAT---TCAGGTTTGGCTCAGGGTTGCCT
AAGAGGGGCCAGGGAATTGGAGCCCTCACAAGAGAACATATCTAG----
>AsianElep
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATAAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAACAAAAGCAAACAGCCTGGCTTAGCAAGAAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCTAGCACAGAGAAAAAGGTAGATGTGAATGCTAATCCCTTGTATGAGAGAAAAGAA
GTGAATAAGCAGAAACCTCCACGCTCTGAGAATCTTAGAGAC---ACCCAAGAT---ATTCCTTGGATAACACTGAATAG
TAGCATTCAGAAAGTTAATGAGTGGTTTTTCAGAAGTGACGGCCTG---------GATGTCTTAAATGATGAGGGGCCTG
AATCCAGTGCAGAAGTAGCTGGTGCATTAGAAGTTCCAAAT------GAAGTACAT------TCTAATTCTTCAGAGAAA
ATAGACCTAATGGCCAGTGATCTGCGTGGTGCTTTAATATGTGAAAGTGAAAGAGTCCCCTCCAAACCAGCAGAAAGTAA
C---ATCGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAGGTATCTCTCATTTGAGCCACATAACTGAAGATC
TGATTATGGGAGCTATTGCTTCAGAACCTCAGATAGCACGA---------------------------------------
---------------------GAACATCCTTTTACAAATAAATTAAAGCGTAAAAGGAGA---ACATCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGTAGATTTGGCAGTTGTTCAAAAGATCCCTGAAAAGATAAATCAGGAAACTGACCATGTGG
AGCAGAAC---------GGTCAAGTGATGAATATTGCTAATGGTGGTCGTGAGAATGAAACAAAAGGTGATTAT---GTT
CAGAAAGAGAAGAATGCTATCCCAACAGAA------TCATTGGCAAAAGAATCTGCTTTCAGAACTAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATATGGAGGTAGAATTAAATATGCATAATTCAAAAGCCCCAAAGAAGAATAGGCTGAGGAGGA
AGTCGTCAACCAGGCATATTCATGCACTTGAACTAGTAGTCAATAGAAATCTAAGTCCACCTACTCATACTGAACTACAA
ATTGACAGTTGGTCTAGCAGTGAAGAG---ACAAAGAAAAAA---AGTTCTGAGCAAAAGCCAATCAGACACAACAGAAA
CCTTCAACTCATGAAAAATCAAGAAACCGCAACTGGAGCCAAGAAGAGTAACAAGCCAAAGGAACAAATAAGTAAAAGAC
ATGGCGCTGACTCTTACCCAGAACTACATTTAACAACCACAGCTGGCTTTATTACTAAGTGTTCAAGTTCTGATAATCTT
CAAGAATTTGTCAATCCTAGCCTTCAAGGAGAGAAAACAGAAGAAAAC---CTGGAAACAATTCAAGTGTCTAATATTAC
CAAAGAGCCCAAGGATCTAGTGTTAAATGGAGGAAGA---GATTTGCAA---ACCAAAAAATCTATTGAGAGTACCAATA
TCTCAGTGATACCTGATACTGTTTATGGCACTCAGGACAGCGTCTCATTGCTGGGAGCTGACACCCCAGGG---AAGGCA
AAA---ACAGCACCAAATCAATGTGCAAGTCAGTGTACAGCAATTGAAAACCCAAGTGAACTTACCAACAGTTGT---CC
TAAAGATACTAGAAATGACACAGAGGGTTTTAAGGATCTATTGAGATGTGAAGCTAGC---CACATTCAGGAGACATGCA
TAGAAATAGAAGAGAGTGAACTTGATACTCAGTATTTACAGAGTACATTCAAGGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATCCA---------GAAAAGAAATGTGCAACAATTTGTGCCCACTCCAAGTCCTTAAGGAAGCAAAGCCCAAA
AGTCACTCTTGTGTGTGGAGAAAAAGAAGAAAATCAAGGGAACAGAGAGCCTAAAATCAAGCATGAGCAGGCAGTTCATA
TGCCTGCAGGCTATCCTGAGGCTTGTCAGAAAGAGAAG---CCAAGTGACTATACCAAATATAGCATTAAAGGAGTCTCT
GGGCTTTGTCAGTCATCTCAGTTCAGA---GGCAGTGAATCTGAACTCATTACTGCAGATGGACATGGAATCTCACAAAA
CCCAGATCAAATACCATCACTTTCTCCCACCAGGTCATCTGTTAAAACTAAATGTAAGACAAAC---CTGTTGGAAGAAA
GGTTTGAGGAACATACAATATCACTTGAAAGAGCAATGAGAAATGAGAACGTCATTCAAAGTACAGTGAGCACAGTTAGC
CAAAATAACATTAGGGAAAGTGCTTCTAAAGAAGCCAGCTCAAGCAGTATTAATGAAGTATGTTCCAGTATTAATGAAGT
AGGTTCTAGT------------------------------------------GGTGAAAACATTCAAGCAGAAATAAGTA
GGAAGAGAGGACCTAAATTAAATGCTGTGCTCAGATTAGGTCTTATGCAACCTGAAGTTTATAAACAAAGTCTT---CCT
ATAAGTGACTGTAAACATCCTGGAATAAAAACGCAAGGAGAAAATGAAGGAGTAGTTCAGGCTGTTAATACAGATTTCTC
CCCATGTCTAATTTCAGATAACCTAGAACAA---CCTGTGGGAACTAGTCGTGCTTCTCAGGTTTGTTCTGAGACTCCCG
ACGACCTGTTAGATGATGATGAAATAAAGGAAAATATCAGCTTTGCTGAAAACAGCATTAAGGAAAGATCT---GTTTTT
ATTAAAGATGACCAGAGAAGAGAGTTCAGAAGGAACCCAAGCCCTTTATCCCAT---TCAGGTTTGGCTCAGGGTTGCCT
AAGAGGGGCCAGGGAATTGGAGCCCTCACAAGAGAACA-----------
>RockHyrax
TGTGGCACAGATACTTGTGCCAGCTCGTTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGGATGTAGA
AAAGGCTGAATTCTGTAGTAAGAGCAAACAGCCTGGCTTAGCAAGGAGCCAACAGAGCAGATGGGCTGAGAGTACGGAAA
CATGTAATGGT---AGGCAGATTCTTAGAACAGAGAAAAAGGTAGAAACGAATGCTGATCCTTTGTATGGGAAAAAAGAA
GGGAATAAGCAGAAACCTCCATGCTCTGAGAGTCGCACAGAT---ACGCAAGAT---ATTCCTTGGGTAACACTGAATAA
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGACAACCTA---------AGTGATTCACCTAGTGAGGGGTCTG
AATTAAATGGAAAAGTGGCTGGTCCAGTAAAACTTCCAGGT------GAAGTACATAGATATTCTAGTTTTCCAGAGAAC
ATAGATTTAATGGCCAGTGGTCCTCCTGGT------------------GAAAGAATCCCCTGCAAACCACCAAAAAGTAA
C---ATCAAAGATAAAATATTTGGGAAAACCTATCAGAGGAAGGGAAGTCTCCCTCACCTGAGCCACATAACCGAAGATC
TAGTTAAAGGCGCCATTGCTACACAACCACAGATAGCACGA---------------------------------------
---------------------GAACATCCTCTTACAAATAAGTTACAGCATAAAAGGAGA---ACATCAGGCCTTCATCC
TGAGGATTTTATCAAAAAAGCAGATTTGACAGTTGTTCAGAAGGCATCTGAGAAGATAAATCAGGAAACTGACAAAGTGG
AGCAGAGT---------GGTCAAGTGATAAATATTGGTAATGGTGGTCATGAGAATGAAACAAAAGATGATTAT---GTT
CTGAAAGAGAAGAATGGTAACCCAGCAGAA------TCACTGAAAAAAGAATCTGTGTTCAAAACTAAAGCTGAACCTAT
AAGCAACAGTATAAGCAATATGGAACTAGAATTAAATACACATAATTCAAAATCACTGAAGAAGAACAGGCTGAGGAAGA
AGTCCTCCTCCAGACATGTTCATGCCCTTGAACTGGTAGTCAATAGAAATCCAAGTTCACCACCTCATACTGGGCTACAA
ATTGATAGCTGGTCTGGCAGTGAAGAA---ATGAAGAAAACA---AGTTCTGAGCAAAAGCCAGTCAGACACAACATAAA
CCTCCAACTCATGAAAAACCAAGAAACCACAACTGGAGCCAAGAAGAGTAACAAGCCAAAGGAACAAATAAATAAAAGAC
ACACTAGTAATCCTTACCCAGAACTAAATTTAACAAGCACAGCTGGCTTTATTACTGTATGTTCAAGTTCTGATAATCTT
CAAGAACCTGTCAACCCCAGCCTTCAAGGAGAGGAAATAGAAGAAAAC---TTGGCAACAGTCCAAATGTCTAATACTGC
CAAAGAACCTGAGGATCTAGAGTTAAATGGAGGGAGA---GTTTTGCAA---ACCAAAAGATCTGTTGAAAGTACTAGTA
CCTCAGTGATACCTGATGCTGACTGTGGTGCTCAGGACAGCATCTCGTTACTGGAAGCTGACACTCTAGGG---AAGGCA
AAA---ACAGCACCAAATCAAGGGGCAGGTCAATGTTCGGCAATCGAAAACCCCAACGAACTTATTCATGGTAGT---CC
TAAAGACACTAGAAATGATATAGAGGGTTTTAAGGATCCACTGAGATGCAAAGTTAAC---CCTATTCAGGAGATATGTG
TAGAAATGGATGAAAATGAACTTGATACTCAGTATATACAGAGTACATTCAAGGTTTCAAAGCGTCATTCTTTTGCTCTG
TTTTCAAATCCG---------GAAAAGGAGTGTGCGACAAGTTATACCCACTCCAAGTCGTTAAGGAAAGAAAATCCCAA
AGTCACTCTTCAGCGTGGAGAAGAAGAAGAAAATCAAGGGAACAAAGAATCTAAAATCAAGCAT---------GTTCATA
CAACTGCAAGCTGTCCTGAGGTTTGTCAGGAAGACACAAAGCCTAGTGATCGTACTAACTGTAGTGTTAAAGGACTCCCT
AGGCTTTGTCACTCATCTCAATTCAAA---GGTAGTGAGTCTGAACTCATTACTGAAGGTGAACATGGAATTGCACAAAA
CCCGGATCAGATGCCATCATCTTCTCCCATCAGATCATCTGTTAACTCTAAGTGTAACAAAAAC---CTGTCAGAAGAGC
GATTTAAGGAACATAAAATATTACTTGAAAGAACAACAGGAAATGAAACCATTGTCCAAAGTACAGTGAGCACAGGTAGC
CAAGATAACATTAGGGGAAGTGCTTCGAAAGAAACCAGCTCAAGCAGTATTAATGAAGTAGGTTCTAGT-----------
----------------------------------------------------AGCGAAAACATTCAAGCAGAAATAAGTA
GGAACAGAGAACCTAGATTAAATGCTGTGCTCAGGTTAGGTGTTATGCAACCTGAAGTGTATAAACAAAGTCTT---TCT
ATAAGTAACTGTAAACAGCCAGAAATAAAAAAGCGAGGAGAAAATGAAGGAGTAGTTCAGGCTGTTAGTACAGATTTCTC
TGCATGTCCCATTTCAGAAAACCTAGAACAA---CCTGTGAGAAGTAGTCACACTTCTCAGGTTTGTTCTCAGACTCCTG
ATAACCTGTTAGATGATGATGAAATAAAGGGAAAGACTGACTTTGCTGGAAGTAGCATTAAGGACAGACCT---GTCTTT
AGTAAAGATGACCAGGGAAGAGAGTTCAGAAGGAACCCAAGCCCTTTATCCCAT---TCAGGTTTGGCTCAGGGCCACCT
GATAGGGGCCAGGGAATTAGAGGCCTCACAAGAGAACACATCTAGCGG-
>TreeHyrax
------NCAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGGATGTAGA
AAAGGCTGAATTCTGTAGTAAGAGCAAACAGCCTGGCTTAGCAAGGAGCCAACAGAGCAGATGGGCTGAGAGTACGGAAA
CATGTAATGAT---AGGCAGATTCTTAGAACAGAGAAAAAGGTAGATACAAATGCTGATCCTTTGTATGGTAAAAAAGAA
GGGAATAAGCAGAAACCTCCATGCTCTGAGAGTCGCACAGAT---ACGCAAGAT---ATTCCTTGGGTAACACTGAATAA
CAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGACAACCTA---------AGTGATTCACCTAGTGAGGGGTCTG
AATTAAATGGAAAAGTGGCTGGTCCAGTAAAGCTTCCAGGT------GAAGTACATAGATATTCTAGTTTTCCAGAGAAC
ATAGATTTAATGGCCAGTGGTCCTCCTGGTGATTTAATATGTGAAAGTGAAAGAATCCCCTGCAAACCACCAAAAAGTAA
C---ATCAAAGATAAAATATTTGGGAAAACCTATCAGAGGAAGGGAAGTCTCCCTCACCTGAGCCACATAACTGAAGATC
TAGTTAAAGGCGCCATTACTACACAACCACAGATAGCACGA---------------------------------------
---------------------GAACATCCTCTTACAAATAAGTTACAGCATAAAAGGAGA---ACATCAGGCCTTCATCC
TGAGGATTTTATCAAAAAAGCAGATTTGACAGTTGTTCAGAAGGCATCTGAGAAGATAAATCAGGAAACTGACAAAGTGG
AGCAGAGT---------GGTCAAGTGATAAATATTGCTAATGGTGGTCATGAGAAGGAAACAAAAGATGATTAT---GTT
CTGAAAGAGAAGAATGGTAACCCAGCAGAA------TCACTGAAAAAAGAATCTGTGTTCAAAACTAAAGCTGAACCTAT
AAGCAACAGTATAAGCAATATGGAACTAGAATTAAATACACATAATTCAAAATCACTGAAGAAGAACAGACTGAGGAAGA
AGTCCTCCTCCAGACATGTTCATGCCCTTGAACTGGTAGTCAATAGAAATCCAAGTTCACCACCTCATACTGGGCTACAA
ATTGATAGTTGGTCTGGCAGTGAAGAA---ATGAAGAAAACA---AGTTCTGAGCAAAAGCCAGTCAGACACAACATAAA
CCTCCAACTCATGAAAAACCAAGAAACCACAACTGGAGCCAAGAAGAGTAACAAGCCAAAGGAACAAATAAATAAAAGAC
ACACTAGTAATCCTTACCCAGAACTAAATTTAACAAGCACAGCTGGCTTTATTACTGCGTGTTCAAGTTCTGATAATCTT
CAAGAACCTGTCAACCCCAGCCTTCAAGGAGAGGAAATAGAAAAAAAC---TTGGCAACAGTCCAAATGTCTAATACTGC
CAAAGAACCTGAGGATCTAGAGTTAAATGGAGGGGGA---GTTTTGCAA---ACCAAAAGATCTGTTGAAAGTACCAGTA
CCTCAGTGATACCTGATGCTGACTGTGGTGCTCAGGACAGTATCTCGTTACTGGAAGCTGACACTCTAGGG---AAGGCA
AAA---ACAGCACCAAATCAAGGGGCAGGTCAATGTTCAGCAATCGAAAACCCCAACGAACTTATTCATGGTAGT---CC
TAAAGACACTAGAAATGATATAGAGGGTTTTAAGGATCCACTGAGATGCGAAGTTAAC---CCTATTCAGGAGATATGTG
TAGAAATGGATGAAAATGAACTTGATACTCAGTATATACAGAGTACATTCAAGGTTTCAAAGCGTCATTCTTTTGCTCTG
TTTTCAAATCCA---------GAAAAGGAGTGTGTGAAAAGTTATACCCACTCCAAGTCGTTAAGGAAAGAAAATCCCAA
AGTCACTCTTCAGCGTGGAGAAGAAGAAGAAAATCAAGGGAACAAAGAATCTAAAATCAAGCAT---------GTTCATA
CAACTGCAAGCTGTCCTAAGGTTTGTCAGGAAGACGCAAAGCCTAGTGATCGTACCAACTGTAGTGTTAAAGGACTCCCT
AGGCTTTGTCACTCATCTCAATTCAAA---GGTAGTGAGTCTGAACTCATTACTGAAGGTGAACATGGAATTGCACAAAA
CCCAGATCAGATGCCATCATCTTCTCCCATCAGATCATCTGTTAACTCTAAGTGTAACAAAAAC---CTGTCAGAAGAGC
GATTTAAGGAACATAAAATATTATTTGAAAGAACAACAGGAAATGAAACCATTGTCCAAAGTACAGTGAGCACAGGTAGC
CAAGATAACATTAGGGGAAGTGCTTCGAAAGAAACCAGCTCAAGCAGTATTAATGAAGTAGGTTCTAGT-----------
----------------------------------------------------AGCGAAAACATTCAAGCAGAAATAAGTA
GGAACAGAGAACCTAGATTAAATGCTGTGCTCAGGTTAGGTGTTATGCAACCTGAAGTGTATAAGCAAAGTCTT---TCT
ATAAGTAACTGTAAACAGCCAGAAATAAAAAAGCAAGGAGAAAATGAAGGAGTAGTTCAGGCTGTTAGTACGGATTTCTC
TGCATGTCCCATTTCAGAAAACCTAGAACAA---CCTGTGAGAAGTAGTCACACTTCTCAGGTTTGTTCTCAGACTCCTG
ATAACCTGTTAGATGATGATGAAATAAAGGGAAAGACTGACTTTGCTGGAAGTAGCATTAAGGACAGACCT---GTCTTT
AGTAAAGATGACCAGGGAAGAGAGTTCAGAAGGAACCCAAGCCCTTTGTCCCAT---TCAGGTTTGGCTCAGGGCCACCT
GATAGGGGCCAGGGAATTAGAGNCCTCACAAGAGAACACATCTAGCAA-
>Aardvark
TGTGGCACAAATACTCATGCCAGCTCGTTACAGCATGAGAACAGCAGTTTATCACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGTGAGGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCTTAGCACAGGGGAAAAGGTAGATATGAAGGCTGATCCCTTGTATGGGAGAAAAGAA
GTGAATAAGCAGAAACCTCCATGCTCTGAGAATCCTAGAGAT---ACTGAAGAT---ATTCCTTGGATAACACTGAATAG
TAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGGCCTG---------GATGGCTCACATGATGAAGGGTCTG
AATCAAATGCAGAAATAGGTGGTGCATTAGAAGTTTCAAAT------GAAGTACATAGTTACTCTGGTTCTTCAGAGAAA
ATAGACTTAATGGCCAGTGAACCTCATGTTGCTTTAATATGTGAAAGTGAAAGAGTCCTCTCCAAACCAGCAGAAAGTAA
C---ATCGAAGATAAGATATTTGGGAAAACCTATCGGAGGAAGTCGAGTCTCCCTAACATAAGCCATATAACTGAAGATC
TAATTTTAGGAGCTATTGCTACAGAACCTCAGGTTGCACGA---------------------------------------
---------------------GAATGTCCTCTTGGAAATAAATTAAAGCGTAAAAGGAGA---ACATCAGGCCTTCATCC
TGAGGATTTTATTAAGAAAGTAGATTTGGCAGTT---CAAAAGACTCCTGAAAAGATAAATCAGGAAAATGACCAAATGG
AACAAAAT---------GGTCAGGAGGAGAATATTGCTGATGGCTGTCATGAGAATGCAACAAAAGGTGAATAC---ATG
CAGAAAAAGAAGAGTGCAAATCCAACAGAA------TCATTGGCAACAGAATCTGTTTTCAGAACTAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAATTTGGAACTAGAATTAAATACACACAATTCAAAGGCATCCAAGAAGAATAAGCTGAGGAGGA
AATCCTCTACCAGGCATATTCATGCACTTGAACTAGTAGTCAATAGGAATCCAAGTCCCCCTAGTCATACTGAGTTACAG
ATTGATAGCTGGCCTAGCAGTGAAGAG---TTAAAGAAAAAA---AGTTCTGAGCACAAGCCAATCAGACAGAATACAAA
CCTGCAACTCATGAAAGATCAAGAGGCCACAACTGGGGCCAAGAAGAGTAACAAGCCAAATGAACAAATAAGTACAGGAC
ACGCCTCTGACATTTTCCCAAAATTGAATTTAACAAACATAACTGGTTTTATTACTAATTGTTCAAGTTCTGATAATCTT
CAAGAATTTGTCAATCCTAGCCTTCAAGAAGAGGAAATAAAAGAGAAC---CTGGGAACAATTCAAGTGTCTGATAGTAC
CAGAGATCCTACGGATGAGGTGTTAAAC---AGAAGA---GGTTTGCAA---ACTGAAAGATCTGTGGAGAATACCAGTA
TTTCAGTGAAACCTGATACTGATTATAGCACTCAGGACAGCATCTTATTACTGAAAGCTAACTCCCTAAGG---AAGGCA
AAA---ACAGCACCA------------AGTCAGTGTGCAGCAATTGAAAATCCTAACAAACTTAGCCATGGTTTT---CC
TAAAGATACCAGAAATGACATAGAGGGTTTTAAGGATCTATTTAGAGGTGAAGATAAC---CACGTTCAGGAGACATACA
TAGAAATGGAAGAGAGTGAACTTGATACTCAGTATTTACAGAATACATTCAAGGTTTCAAAGCGTCAGTCATTTGCTCTG
TTTTCAAATCCA---------GAAAAGGAATTTGCAACAGTCCATGCCCACTCCAGGTCCTTGAGGAAACAAAGTCCAAA
CATCACTCTTGAGTGTGGAGAAAAAGAAGAAAATCAGGGGAACGAGGAATCTAAAATCAAGTGCGTACAGCTAGTTCTTT
CAACTACAGGCTATGCTGGAGCTTGTCAGAAAGAGAAG---CCAAGTGATTATGCCAAATGTAGCATTAAAGGAGTCTCT
AGACTTTGTCAGTCATCTCAATTCAGA---GGCAATGAATCTGAAATCATTACTGCAAATGAACATGGAGTCTCACAAAA
CCTGGATCAGACACCATCACTTTCTCCCACTAGGTCATCTGTTAAAGCTAAATGTAAGACAAAT---CTGTCCAAAGAAA
GATTTGAGCAACAGAAAATATCACATGAAAGAGTAATGGGAAATGAGAGCACCATTCAGAGTACAGTGGGCACAGTTAGC
CAAAGTAACATTAGGGAAAGTGCTTTTAAAGAAGCTAGCTCAAGCAGTATTAATGAGGTAGGTTCCAGTGTTAATGAAAT
AGGTTCTAGT------------------------------------------GGTGAAAACATTCAAGCAGAACTAGGTA
AGAACAGAGGACCTAAATTGAATGCTGTGCTCAAATTATGTCTTATGCAACCTGAAGAGTATAAACAAAGTCCT---CCT
ATAAGTAATTGTAAACATCCTTCAATAAAAACCCAAGGACAAAATGAAGGAGTAGTTCAGGCTGTTAATACAGGTTTTTC
TTCATGTCTGATTTCAGATAACCTAGGACAA---CCTATGGGAAGCAGTCATGCTTCTCAGATTTGTTCTGAGACACCTG
ATGACCTGTTAGATGATGACAAAATAAAGGAAAATACCAGCTTTGCTGTAAGTGGCATTAAGGAAAGATCTGCTGTTTTT
AGTAAAGATGACCAGGAAAGAGAGTTCAGAAGGAGCCTGAGCCGTTTCTCCCAT---TCAAGTTTGGCTCAGGTTCACGT
AAGAGGTGCCAGGGAATTAGAGTCCTCAGAAGAGAACATATCTAGTGAG
>GoldenMol
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTGTAATAAAAACAAACAGTCTGGCTTAGCGAGGAGCCAGCAGAGCAGATGGGCTGGAAGTAAGGCAG
CGTGCAATGAC---AAGCAGACTCCTAGCACACAGACAGAGCTATATAGGAGTGCTGGTCCCATGCACAGGAGAAAAGAA
GTAAATAAGCTGAAATCTCCATGGTCTGAGAGTCCTGGAGCT---ACCCAAGAG---ATTCCTTGGATAACACTGAATAG
TAGCATTCGGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGGCCTG---------GATGAGTCACATGATGAGGGGTCTG
AATCAAATGCAGAGGTTGCTTGTAAATTCGAATTTCCCAAG------GAAGTACAAGGATATTCTAGTTCTTCAGAGAAA
ATGGACTTAATGGCCAATGATCCTCATGATGCTTTAATATGTGAAAATGAGAGAATCCTCTCCAAACCAGCTGTAAGTAA
C---ATTGAAGATAAAATTTTTGGGAAAACCTATCGGAGGAAGACAAGTCTCCCTAACTTGAGCCATGTAACTAAAGACC
TAATGATAGGAGCTGTTGCTACAGAAGCTCAGATGGCACAA---------------------------------------
---------------------GAACGTCCTCTTACAAATAAATTAAAGCGCAAAAGGAGA---ACCTCAGGCCTTCATCC
TGAGGATTTTATCAAGAAAGCAGGCATGAAAGTTGTTCAAAAGACTCCTGAAAAGATAAATCAAGAAACTAACCAAATGG
AGCAGAAT---------GATCAAGTGAGGAATATTGTTGATGGTGGTCATGAAAATGATACAAAAAGTGATTAT---GTT
CAGAAAGAGAAGAGTGCTAACCCAGCCAAA------TCATTGGCAAAAGAGTCCGCTTTCACAACTAAAGCGGAACCTAT
AAGCAGTAGTATAAGCAATATGGAACTAGAATTAAATATGTACAATTCTAAAGCACTGAGGAAGAATAGGTTGAGGAGGA
AGTCCTCTTCCAGGCATATTCACACACTTGACTTGGTAGTCAATAGAAATCCAAGTCCACCTCCTTACACTGAACTACAG
ATTGATAGTTGGCCTAGCAGTGAAGAA---ATAAACGAAACA---AGTTCTGAACAAAAGCCAACCAGACACAGCAGAAA
CCTTCACCTCATGAAAGAACAGGAAACTGCAACTGGAACCAAGAACAGTAACAAGCCAAATGAACAAATAAGTAAAAGAC
ATGCCACTTACACTTTTTCAGAACTAAACATAACAAATAGAACTGACTTTATTACTAACTGCCCACGTTCTGATAATCTT
CAAGAACTTGTCAATCCTAGCCTTCAAGGAGAGGAAAGGGAAGAGAAA---TCGGAAACAATGCAAGTATATGATAACAC
CAAAGAACCTGAGGATCAGGTGTTAAGTGGAAGAAGG---GATTTGCAA---ATGGAAAGATCTGTTGAGAGTACCAGTG
TTTCAGTGATACCCGATACTGATCATGGCACTCAGAACCACACCTCATTACCGGAAGCTGGCACCCTCGGG---AAGGCA
GAA---ACAGCACCAAATCAATGTACAAGTCAGTGTAAAGCAATTGAAAATCCCAACCAACTTATCCATGGTTGT---CC
T---------AGAAATGACACAGAGGGCTTTAAGGATCTATTGAAACATGAAGTTAAA---CACAATCAGGAGACATGCA
TAGAAATGGAAGAGGGTGAGCTTGATATTCAGTATTTACAGAATACATTCAAGGTTTCAAAGCGTCGGTCATTTGCTCTG
TTTTCAAATCCA---------GAAAAGGAATGTGCAACAGTCAGTGCCCACTCTAGGTCCTTCAGGAAACAAAGTCCAAA
AGCCACTCTTGAATGTGGCGAAAAAGAAGAAAATCAGGGGCACAAAGAGTCTAAAGTCAAGCATGTACAGGCAGTTCATA
CAAGTGTGGGCTATCCTGGACTCTGTCAGAAAGAGAAG---CCAAGTGATTATACCAAAGGTAGCATTCAGGGGGCCTCT
AGGCTTCATCAGTCATCTCAGTTCAGT---GGCAATGAATCTGAACAAATTACTGCAAATGAAAATGGAATTTCACAAAG
CCCAGATCAAACAGCATTGCTTTCT------------------------AAATGTAAGAAAAAC---TTGTCTGAAGAAA
GATTTGAAGAACGTGCAGTATCACTCGAAAAAGCAGTGGGAAATGAGAGCATCATTCAAAGTACAGTGAGCACAGTTAGC
CACAATAACATTAGGGAAAGGGCTTTTAAGGAAACCAGCTCAAGTAGTACTAATGAAGTAGGTTCCAGTATTAATGAAGT
AGGTTCTAGT------------------------------------------AACGAAAACATCCAAGCAGAGGTAGGTA
GGAACAGAGGACCTAAGTTAAATGCTATGCTCACATTAGGTTTTATGCAACCTGAAGTCTATAAACAAAATCTT---ACT
CTAAGTAATTGTAAACATCCTGAAATAACAAAGCAGGGAGACAATGAAGAAAGAGTTCAAGCTGCTGACCCAGGTTTCTC
TCCGTGTCTAATTTCAGATAACCTAGAACCA---CCTATGGGAAGTAATCATGCTTCTCAGATTTGTTCTGAGACACCTG
ATGACCTGTTAGATGATGATGAAATCAAAGAAAATATCAGCTTTGCTGAAAGTGGCATTAACGAAAGATCTGCAGTTTTT
AGTAAAGATGACCATAGAAGACAATTCAGAAGGAACCTAAGCCCTTTATCCCAT---TTAGGTTTGACTCAGGGTCACTT
AAGAGGTACCAGAGAATTAGAGTCTTCAGAAGAGAACCTGTCTAGTGAG
>Madagascar
TGTGGAACAAATACGCTTGCCAACTCATTACAGCGTGAGAACTACAGTTTATTACTCACTAAAGACAGACTGAATGTAGA
AAAGGCTGGATTCTGTAATGAAAGCAAACAGCCCGGCTTAGCAAGGAGCCAACATAACAGATGGGCTGAAAGTAAGGAGA
CATGTAATGAC---AAGCCGACTCCTAGCACAGAGAAAAAGGTAGATAAGAATGCTGACCCCGTGCATGGGAGAAAAGGA
GTGCCTAAGCAGAAACCTCCGTGCCATGGAAGTCCTAGAAAG---AGCCACGAT---GTGCCTTGGAAAACACGGAAGAG
TAGCATTTGGAAAGTCAATGAGTGGTTTTCCAAAAGCGATGGCCTG---------GGTGACTCGCATGATGAGCGGCCTG
AATCAGATGCAGACGTCGCTGGGGCCTTCGAAGTTCCAGAT------GAAGCACGCGAATCTTCTAGTTCACCAGAGAAA
ACAGACTTGATGGTCAGTGATCCTCATGTTCCTTTACTGCCTAAAAGTGAAATAGTCCTTTCCAAACCAGTAGAAAGTAA
C---ATCGAAGACAAAATATTTGGGAAAACGTATCGGAGGAAGTCAAGTCTCCTTAACTCGAGCCATGTAACCGAAGATC
TAATGGTAGGAGCTGCTGCTGCTGTAGCACCTCCGATAGCG---------------------------------------
------------------CAAGAGCACCTTCTTACCAGTAAATTAAAACGC---AGAAGA---TCATCCGTCCTCCACCC
TGAGGACTTTATCAAGAAAGCAGATTTGGCAGTTGTTGAAAAG------------ATCAACCAGGGAACTGACCAAACAC
GGCCGAAG---------GGTCAAGTGGAGCATACTCCCGATGGTGGTCACGGGCATGGAACAAAAGGCGGGAAT---TGT
GTTCAGAAGGAGAGTGCTGACCTGGCAGAA------TCATCGGCCAAAGAATCTGCCTTTCGAACTGTAGCTGAGCCTTT
GAGCAGTAGGAAAAGCGGTATGGAACTGGAACCGACTGTGTTCAATGCAAAAGCACAN---AAGAACAGGCTGAGGAGGA
AGCCCTCTGCCAGGCACATCCACCCCCTGGAACTA---GTCAACAGACAGCCAAGCCCGACGAGGCACACAGAACTGCAA
ATCAGTAGCTGGCCTAGCAGTGAAGAG---CTAAAGAAAGAA---GAATCTGAGCCAAAGCCAGTCAGACGGAGCCGGAA
CTTACAGCTCACGAAAGACCAAGAAATGGCCATCGGAGCCAAGAAGAATGACAAACCAAATGAAGAAAGGGGCAAAAAAC
ACGCCCCTGACACTTTCCCAGAACGAAATTTAACAGACACAACTGACCTAATTACTACCTGTTCGTTTTCTGGTAATCTT
CAAGCATCTGTCTGTCCTAGCCTTCCAGGGGCAAACCTGAAAGAGAAA---CTGGGAACAGTGCAGGTGTCTAATGGTAC
CAGAGACCCCAAAGGTGAGGTGTTGGGTAGAGCAAGG---GGCCTGCAA---ACCGCAAGATCTGTTGAGAGTACCAGTG
TTTCACTGATACCTGATGCTGATGATGGCCCTCAGGGTACCATCTCAATCATGGAAGCAGGCAACCGAGGG---GAGGCA
CAA---ACAGCACCAGGTGAATGTGCAAGGCAGTGTGCAGCAACTGAAAACCCCAACAGGAGTGTCCAGGGTCTT---TC
CAAAGACACTAGAAATAACAGGGAGGGCTCTGAGGATCTCTTGACACACGACGTTAAC---CACCTTCAAGAGACATGCA
CAGAAATGGAAGAGAGTGAACTTGATATTCAATCCTTACAGAATACATTCAAAGTCTCAAAGCGTCAGTCATTTGCTCTG
TCTTCAAATCCA---------GAAAAGGAGTGTGCCTCGCTCGGTGCCCGCCCT---------------------CCAAA
CATTGCTCTTGAGTGTGGGGAA---GAAGGGACTGAGGAGAACAAAGAGTCTGCAGTTCGACCTGTGCAGGCAGTTCCTG
CAACTGTGGGCGGTGCTGGAGGTAGTCCAACAGAGCAACAGCCACGTGATTATACCAAAAGTCACCTTCAAGGAGTGTCC
AGGCTTGGTCAGGCAGCTCCATTCAGA---GGCAGTGAATCTGACCCCAGTACCTCAGTTGAACATGGGATTGTGCAGAC
CTCGGAGCNTGCCCCACCACTCGCTCCCATCAGGTCATCTGTTAACAGTGAACGTAAG------------------GAAA
GACTGGAGGATCATGCAGAATCACTTGAAAGAGCCTCAGAAAACGAGAGTATCATTCCAAGTACAGTGAGCACAATTAGC
CAAAATACCCCGAGAGAAAATGCTTTCAAAGGAACCAGCTCAAGCAGTCTTAATGAAGTAGGTTCTAGC-----------
----------------------------------------------------AGCGAAAACATTCAAGCAGAGCTAGCTA
GGAACAGAGAACCTAAATTGGATGCTGTGCTCAGGTTGGGTCTTGTGCAACCTGAAGTCTGTAAGGAAAGTCTT---CCT
ATGAGGAAATGTAAGCATTCTGAAGTAAAAAGGCAAAAAGGCAATGGAGGACTAGTTCCAGCTGTTCATCCAGATTTCTC
TCGCTATCTAATGTCACATAACCCAGAGCAG---CCTATGGAGGACAAT---GATCCTCAGATTTGTTCTGAGACACCTG
AAGACCTGTTAGATGACAGTGAAATAAATAAAAACAGCCACTTGGTTCAAAGTGACATTAGGGAAAGATCTGCTGTTTTT
AGCAAAGATAACCAGAGAAGAGATTTCAGAAGGAGCCCTGGGCCTACATCCCAT---TTAGGTTTGTCTTGGGGTCACCC
NAGAGGTGCTGAAGAGTTAGAGTCCTTAG--------------------
>Tenrec
TGTGGCACACGTACGCTTGCCAGCTCGGCACAGCGCGAGGACTGCAGCTTATTACTCACCGAAGACAGACTGGATGGAGA
AAAGGCTGGATTCTGCAAGGAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAGCATAGCAGATGGGCTGAAAGTAGGGGAA
CGGGTAATGAC---AAGCCGACTCGTAACACAGAGGAAGAGGTAGTTGTGAGCGCTGACTCCGCGCATGGGAGGAAAGGA
GTGTCTAAGCAGAAACCTCCGCGCCAGAAAAGGCCCAGAAAG---AGCCATGAT---GTGCCTTGGAAAACACGGAAGAG
CAGCATTTCGAAGGTTAACGAGTGGTTTTCCAAAAGCCACGGCCTG---------GGTGACTCTCGCGATGGGCGGCCTG
AGTCAGGCGCAGACGTAGCTGTAGCCTTCGAAGTTCCAGAC------GAAGCATGTGAATCTTATAGTTCTCCAGAGAAA
ACAGACCTGATGGCCAGGGACCCTCCTATTCCCTTACTGCATAAAAGCGCAAGAGTCTTTTCCAAACCAGTAGAAAGTAA
C---ATCGAAGACAAAATATTTGGGAAAACGTATCGGAGGAAGTCAAGCCTCCTTAACTCGAGCCATGTAACTGAAGATC
TGGTGCTAGGAGCTGCGGCTGCCGTAGCGCCTCCGGTAGCA---------------------------------------
------------------CAAGAGCAGCTTCTTACCAGTAAATTAAAGCGCAAGAGGAGA---TCCTTCGTCCTGCACCC
TGAGGACTTCATCAAGAAAGCAGATTTGGCTGTCGTTCAAAAGACTCCTGAAACGATCCATCAGGGACCTGACCCAATGC
AGCCGAAG---------GGGCCAGTGCAGAAGATTCCCGATGGTGGTCCCGGGCGAGGGACAAAAGGCGGGGATCGTGTT
CCGAAGGAGAAGAGTGCTAACCTGGCAGAA------ACATCGGCCAAAGAATCTGCCTTTCGAACTGTAGCTGAACCTTT
GAGCAGCCGGAAAAGCAGTATGGAACTGGAGTTGCCTGTGTTCAGTTCAAGAGCGCAG---AAGAACAGGCTGAGGAGGA
AGCCCTCTGCCAGGCACATCCATCCGCTGGAACTA---GTCAACAGACAACCAAGCCCGACTACGCACACGGAGCTGCAA
ATCAGCAGTTGGCCTAGCAGTGAGGAG---CTAAAGAAAGAA---GAATCCGAGCCAAAGCCAATCAGACGGAGCCGGCA
CTTAAAGCGGGAAAGA---------------------GCCAAGAAGAATGACAAGCCAAACGGAGAAAGGGGCAAAAAAC
ACGCCCCTGACACATTCCCAGACCGAAAGTCAACAAGCACAACGGACTTAATTGCTAACTGTTCCGTTTCTGGCAGTCTT
CATGGAGCTGTCTGTCCTGGCCTTCCAGGGGCAAAGCAAACAGAGAAA---CGGGGAGCAGTGCAGGTGTCTAATAGCGC
CAGAGACCCCAAAGATGAGGTGTTGGGTAGAGCAAGG---GGCCTGCAA---ACTGCAAGATCTGTTGAGAGCACCAGTT
TTTCACTGATACCTGCTGCTGCTGACGGCACCCCGGGTGGCGTCTCAATAATGGAAGCAGGCAGCCGAGGA---CAGGCA
CAA---ACAGCACCAGATCCATGTGCAAGGCAGTGTACAGCAACGGACAACCCCAGCGAAAGTGCCCACGGTCTT---TC
CAGAGATACTAGAAACAGCACGGAGGGCTTTGCGGATCTATTGACACATGGCGTTCCC---CACATCCAAGAGACATGCA
CAGAAATGGAAGAGAGTGAACTTGATATTCAGTCTCTACAGAATATGTTCAAAGTCTCCAAGCGTCAGTCATTTGCTCTC
TCTTCAAATCCA---------GAAAAGGAGTGTGCCACACTCTGTGCCCATCCTAGCGCCTTCAGGAAACAGAATCCAAA
CGATGCTCTTGAGGGTGGAGAA---GAAGGGACTCGGGAGAACAAAGAGTCTACAATTAAGCCTGTGCGGGCAGTTCATA
CCACCGTGGGC------------------ACGGAGAAGCAGCCAAGTGATTACACCAACAGTAGCTTTCAAGGAGTTTCT
AGGCGTGGTCAGGCATCTCAATTCAGA---GCCAGTGAATCTGACCCCGGTACCTCAGTCGAACACGGAAGTTTGCAAAC
CACAGAGCATACCCCACCACTCTCTCCCATCAGATCCTCCCTTAAAAGTAAATGTAAGGAAAAG---CTGTCAGAAGAAA
GATTGGAGGATCAGGCAGAATCCCTTGAAAGAGCCTCGGGGAATGAGAGCATCATTCAAAGTACAGTGAGCACAATTAGC
CAAAATACGCTTAGAGAAAATGCTTTTAAAGGAACCAGCTCAAGCAGTCTTAATGAAGTAGGTTCTAGC-----------
----------------------------------------------------AGCGAAAACATTCAGGCAGAACTAGCTA
GGAACAGAGAACCTAAATTGGATGCTGTGCTCAGACTAGGACTTGTGCAGCCTGAAGGCTGTAAGGAGGAAAGTCTTCCC
CTAAGGAAATGCAAGCATCCTGAAGTAAGAAGGCAAAAAGGCAATGGAGGACTAGTTCCAGCTGTCAATCCGGATCTCTC
CCGCTATCTAATGTCACGTAACCCGGAGCAA---CCGATGGAGAGCAAC---GGTTCTCAGATTTGCTCGGAGACACCTG
AAGACCTGTTAGATGACAGTGAAATAAAAAATAACAGCTACTTTGTTCAAAGTGACGTTAAGGAAAGGTCTGCAGTTTTT
GGCAAAGATAACCAGAGAAGAGATTTCAGAAGGAGCCCTGGGCCTACATCCCAT---TTAGGTTTGACTTGGGGTCACCC
AAGGGGTGCGGAAGAATTAGAGTCCTTAGAAGAAAGCGAAGCCAGTGAG
>LesserEle
TGTGGCACAGATCCTCATGCCAGCTCATTACAGCATGAGAGCAGCAGTTTATTACTCACTAAAGACAGAATGAATGTAGA
AAAGGCTGAATTCTATAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAA
CATGTAATGAT---AGGCAGACTCCTAGCACAGAAAAAAAGGTAGCTGTGAGTGCTGATCTTTATTATGGGATAAAAGAA
GTGAATAAGCAGAAATCTCCGCACTCTGAGAGTCCAAACAAT---AACCAGAAT---ACTCCTTGGATGACATTGAACAG
TAGCATTCGGAAAGTTAATGACTGGTTTTCCAGAAGCGGTGGCCTG---------GATGGCTGCCATGAT---AGATCTG
AATCGAATGTAGTAATAGCTGGTGAAGTGGAAGTTCCAAAT------GAAGTACACGGATATTCTATTTATTCAGAGAAA
TTAGACTTAATGCCCAACAATCCTCATGATACTTCACTGTATGAAAGTGAAAGAACCCTCTCCAAACCAGCTGAAAACAA
C---ATTGAAGATAAAATATTTGGGAAAACCTATCGGAAGAAGGCAAGTCTCTCTAACTTGAGCCATGTGACTCAAGATC
TCATTACAGGAGCTGTTGCTACAGAATGTCAAACAGCACAA---------------------------------------
---------------------GAACGCCCTCTTACAAATAAATTAAAGCGTAAAAGAAGA---ACATCAGGCCTTCAGCC
TGAGGATTTTATCAAGAAGGTAGATTTGACAGTTGTTCAAAAGATTCCTGAAAAGACAAATCAGGAAACTGAACAAATGG
TGCAGAAT------GGTCAAGTGAAGAATAAGATTGCTAGTGGTGGTCATGAGAGTGATACAAAAGGTGATTAT---GTT
CAGGAAGAGAAGAATACTAACCCAACAGAG------TCACTGGTAAGAGAATCTGATTTCAGAAATAAAGCTGAACCTAT
AAGCAGCAGTATAAGCAAAATGGAGCTAGATTTAAATACACACAGTTCGGTAGCACCAAAGGAGAACAGGCTGAGGAGGA
TGTCCTCAACCGGGCATGTTCACGCACTTGAACTAGTAGTCAATATAAGTCCAAGGTCACCTATCCATACTGAAGTACAG
ATTGATGGTTGGTCTAGCAGTGAAGAG---AAAACGAAAAAA---CATTCCGAGCATAAGCCAGTCAGACCTAGCAGAAA
CGTTTCAGTTACAACAAATCAAGAAACTGAAACTGGGTCCAAGAAGAATAACAAGCCAAATGAACAAATGAGTAAAAGAC
ATGCCACTGACACTTCCCCAGGGCAC---------AACATAACTGGCTTCATTACTGACTGTTCAAATACCAGCAGTCTT
CAAGAATGTTTTAATCCTAGACTTCAGGGAGAGGCAGTAGAAGACAAC---TTTGGACCAGTTCAAGTGTCTAATAGTAT
CAAAGATCCCAAGGATCAAGTATTAAATAGAGGAAGG---AGTTTGCAGCACACTGGAAAATGTGTTGAGAGTACCAGTA
TTTCAGTGTTATCTGATACTGATTATGGCACTCAGAATAGCATCTCATTACTGGAGGCTGGCACCCTAGGG---AAGGCA
GAA---ACAGCACCAGATCAATGTGCAAGTCACTGTGCAGCAATGGAAAACTCCAAGAAACATGTTCATGACTTT---CC
TAAAGATACTGGAAATGATACAAAGGGTTTAAAGGACTCATTGAAATGTGATGCTAGC---CACAGTAAGGATACGTACA
TGGAAATGGAAGATAGTGAACTTGATACTCAGTATTTACAGCATACATTCAAGGTTTCAAAGCGTCAGTCATTTTCTCTG
TTTCCAAATCCA---------GAAAGGGACTATACA--------------------------------------------
----------------------------------------------------------AAGCTAGTGCAGCTAGTTCATA
CCACTGCGAGCTATCCTGGAGCCTGTGAGGAAAAGAAA---CCAAATGATTTTACCAAATGTAGCATTAAAGGAGTCACT
AGACTCTCTCATTCATCTCCATTGAGA---GGCAATGAATCTGAACTCATTACCGCAAATGAACATGAAATGTCACATAG
CCCAGATCAGACACCGTCACTTTCTCCCACCAAGGTTCCTGTTAAAATGACATGGAAGAAAAACCACCTGTCAGAAGAAA
ACTTTGAGGAACATACAATA------------ACAATGGGAAATGAGAGCATCGTTTATAGTCCAGTGAGCACAGTTAGC
CAAAGTAATGTTAAGGGA------TATGCTCAGGCCAGTTCAAGCAGTATTAACGAAGTAGGTTCCAGTACTAATGAAGG
AGGTTCCAGTATTAATGAAGTAGGTTCTAGT---------------------GGTGAAAACATCCAAGCAGAGCTCGATA
GGAACAGAGGACCTGCATTAAATGCTGTACTCAGATTAGGTCTTGTGCAACCTGAAGTCTATGAACAAAGTCTT---CCT
GCAGGAAATTGTAAACATCCTGAAATGACAAGGCCAGGAGACAGTGAAGGAGAAAAAAAGACTGTTAATCCAGATTTCTC
TCCATGTCTACTCTCAGATAATTTAGAACAA---CCTAGGGGAAGTTGTCATGCTTCTCAGATTTGTTCTGAGACACCAG
ATGACCTGTTTGGTGATGATGAAATAAAGGAAAATAGCAGCTTTGGTGAAATCAGCTTTAAAGAGAGATCTGCTGTTTTT
AGTAAAGATGAGCAGGCCAGAGAGTTCAATAGGAACTCAAGCCGTTCATCTCGT---TCAGATTTGGCTCCCAGTCATCT
AAGACGCGATAGGGAATTAGAGTCCTCAGAAGAGAATGTATGTA-----
>GiantElep
TGTGCCACAAGTATTCATGCCAGCTCATTACTGCATGAGAACAGCAGGTTATTGCTCAGTAAAGACAGAATGGATGTAGA
AAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGGAGCCAACAGAGCAGATGGACTGAAAATAAGGAAA
CATGTAATCAT---AGGCAGACTCCTAGTATAGAGAAAAAATTAGATATGAATGCTGATCCCTCTTATGGGCGAAAAGAA
GTGAATAAGCAGAAATATGAATGCTCTGAAAGCCCTCAAGAT---ACCCAAGAT---ATTCCTTGGATGACACTGAATAG
TAGCGTTCAGAAAGTTAATGCATGGTTTTCCAGAAGTGATGGCCTC---------GATGATGCCCCTGATGTAGGGTCTG
AATCAAATACAGCAATAACTGGTGCACTGGAAGTTTCAAAG------GAAGTACATGGATATTCTAGTTCTTCAGAGAAA
GTACACACAATGACTGGTGATCCTCAGGGTGCTTCAGTATGTGAAAGTGAAAGAGTCTTCTCTAAACCAGCAGAAAATAA
C---GTTGAAGATAAAATATTTGGGAAAACCTATCGGAGAAAGTCAAGTCTCCCTAACTTGAACCATATAACGCAAGATC
TCATTGTAGGAGCTGTTGCTACAGGACCTCAGACAGCACAA---------------------------------------
---------------------GAACACCCTCTTATAAATAAACTAAAGCGTAAAAGGAGA---ATATCTGGCCTTCGTCC
TGAAGATTTTATCAAGAAGGTAGATTTGACT---AGTCAGAAGACTCCTGAAAAGAGAAATCAGACCATTTACCAAGTGG
AC------------------------AGTAGTATTGCTGGCGGTGGTCATGAGCATGAAACGAAAGGTGACTGT---GTT
CAGAAAGAGAAGAATGTTAGCCCAGCAGAA------TCATTGACAAAAGCTTCTGCTTTCAGAACTAAGGATGAACCTAT
AAGCAGCAGTGTGAGCAGTATGGAACTAGAATTAAATATGTACAGTTCGATAGCACCAAAGAAGAACAGGCTGAGAAGGA
AGTCCTCTACTAAGCGTATTTGTGCACTTGAACTAGTAGTCGATAGAAATCCAACTTCACCTACCCATGCTGAGCTAGAG
ATTGATAGTTGGCCTAGCAGTGAAGAG---AGAAGGGAAAAA---TGTTCAGAGTTTAACTCCGTCAGACACAGCAGAAC
CTTTCAGCTTATGAAAGGTCAAGAAACTGAAATTGGAGACCAAAAGAATAATGACAAGCAAAATGAACAAATAAGTAAAA
AACATGCCACTGACACTTCTCCAAAACGA------AACATAACTGGCTTTATCACAAACTGTTCAAATACTGATAATCTT
CAAGAATTTGTTAATCCTAGATTTGAAGGAGAGGAAATAGCC---------GTGGGACCAATTCAAGTGTTGAATAGTAC
CAAGGACCCTGGAACTCAAGTGTTAAGTAAGGAAAGG---GGTTTGCAC---ACTGGGAATTATGTTGAGAGTACCAGTA
TTTCAGTAATACCTGATACTGATGATGGTATTCAAAATAGCACCTCATTACTGGAAGCTGGCACATTAGAA---AAGGCA
GAAGAAACAGCATTGACTCAATGTGCAAGTCACTGTGCAACAATTTTAAACCCCAACACACATGTTCATGGCTTT---CC
TAAAGATCCTGCAAATGACACAGAGGGTGTTAAGGATCTGTTGAAATGTAATCCTAAC---CACCTTCAGGATACGTGCA
TAGAAATGGAAGATAGTGAACTAGATACTCAGTATTTACAGAATACATTCAAAGTTTCAAAACGTCAGTCATTTACCCTG
TTTCCAAATCCA---------GAAAAAGAATGTACAACAGTCTGTGCCCACTCCAGGCTCTCAAAGAAACAAAATCCAAG
TGTCACTCTTGAGTGTAGAGAAAAAAAAGAAAATCAGGGGAATGAAGAGTCTAAAATGAAACATGTGCAGGTCGTTCATA
CATCTGTGCACTATCCGGGAGTTTGTGAAGAAGAGAAGATACCAGATGATCACACCAAAGTTAGCATTAAAGGGATCTCT
AGGCTTTGTCAGTCATCTCCTTTCAGG---AGCAATGAATCTGAACGCATTACTGAAAATGAATGTAAAATGTCACATAG
CCCAAACCAGACACCATCATTTTCTCCCACCAAGCCATCAGTTAGAACCAAATATAAGCAATTCTACTTGTCAGAAGAAG
AGTTGGAGGAACATGCACTATCACCTGAAAGAGCAATGGAAAATGAGAGTTTCATTCACAGTACAGTGAACGCAGTTAGC
CAAAATAACCTTAGGGGAAGTGTCTTTAAAGAAGGCAGCTCAAGCAGTATTAATGAAGCAGGATCCAGTACTAATGAAGT
AAGTTCCAGTATTAATGAAGTATGTTCTAGT---------------------GATGAAAACATCCAAGCCGAACTAGATA
GGAACAGAAGACCTGAATTAAATGCTGTACTCAGGTTAGGTCTTATGCAACCTGAAGTGTATCAACCAAGTCTT---CCA
ACAAATAACTGTGAATATCTTGAAATTAGTGGGCCAGGAAAAAATGAAGGCATAATTCAGGCTGTTAATCCAGATTTTAC
TCCGTGTCTGATTTCAGATAACTTAGAACAACAGCCTATGGGAAGTAATCATGCTTCTCAGATTTGTTCTGAAACACCTG
ATGACCTGTTAAATGATGAGAAAAGAAATGAGAATATCAGCTTTGCTCAAATCAGCATTAAGGAACGATCCACTGTTTTT
AGTAAA---GACCAGGCAAGAGAATTCAGAGGAAACCCAAACCCTTTATCCCAT---TCAGATTTGACTCAGAGTCATCT
AAGAAGTGGTAGGGAATTAGAGTCATCAGAAGANAA-------------
>Caenolest
---------------------NGCTCATTACTGCCTGAGATCACCAGTTTATTGCCCAACACAGACAGAATGAATGTAGA
AAAGGCTGAACTCTGTAATAAAAGCAAACAGCCTGGCTTAGCAAGCAACCAGCAGAGCAATCTGGATGAAAGTAAGGAAA
TATGTAGTGCTAGCAAGACCCCAGGTGCAGAGGAA---CAGCCTGAGCTGAATGCCAATCATCTGTGTGAGAGGAAAGAA
CTAGAGGAG---AAGCTGCAGTGCCCTGAGAGCCCCAGAGGTGATTCTGGGGACTGCCTGTCTGGAACCAAAGTGAAAAA
CAGTATTCAGAAAGTTAATGAGTGGTTATTCAGAAGTAATGACGTTTTAGCCCCAGATTACTCAAGTGTTAGGAGCCATG
AACAGAATGCAGAGGCAACCAATGCTTTAGAATATGGGCATGTAGAG---ACAGATGGAAATTCTAGCATTTCTGAAAAG
ACTGATATGGTGGCTGACAGTACTGATGGTTCCTGGCTACATGCACCTGAAAAAAACTGCCCCAGACCGGCAGAGAGCAA
CAATATTGAAGATAAAATATTTGGAAAAACCTATCGAAGAAAGTCGGTTCACCCTGTTTTGAATTACGTAACTGAAAACT
TGATTGTTGAAACCATTGCTCCTGATTCTGTGATCCCTCCA---------------------------------------
---------------------GAGCCTCTCAAAAAAACCAAATTAAAGCGTAAAAGAAAGACCATATGTRACCTGCAGCC
TGAGGATTTCATCAAAAAGACAAACATTCCAGTTATTCCCAAAACCCCTGAAAAGAAAAATCACCCTGTTGACCAGATCC
TTGAAAAAGAACAAAATGGCCAGGTGATGAGCACAGCTGATGGTCAGTCCAAGCAGAAAGCACCCGGTTGTCAT---GTG
GGGGAACTGAAAGAGGCTCAGGCATCAGAACCATCCTCTGTAGAGAAAGGATCCACTTTCAAAACTGGATCCGAGCCTGC
AGCTGGTAGCACAAACCAGAGGGAACTTGAATTAAATGGTAGAGATGCAAAAATGACAAAAAAAGACAGACCAAGGAAGA
GGCCTTCAGTTAGGACTGTCTGTGCTCTGGAGCTCGTGACTGATAGACACCCAGGCTCTTCTAATGAGACAGAACTACAG
ATCGATAGCTATCCCAGCAGTGAAGAG---ATAAGGAAAGGAAATAATTCTGAGCAAAAGCAAGTCAGACGCAGCAGAAG
ACTTCAGATGCTGTCAGAA---GAAATTGCAGCAGGAGCCAAGAAGGCCCATAAGCCAGATGAAGAAGTGGAAGAGAATT
GTGTCAATGAAGTTTCCCCAGAACTAAAAATAGGAAAAGTATCTGCCTGTTCTACTGACAGTCTAGCTACTGATAGTGAT
CTGGTATTAGCTAGCTGCAGTTTCACAGAA---GGAGATGAAAAGAGC---CTGGAAGCCTTCCAG---------CCCAG
CAGAGACCAAGAC---AGCCTGGCAGTAAGCAGAGGAGAGAAGTTGCAA---GGGAAAAGAACCAAAGGAAACATGGAGG
TTTTGGAGGTTGCCAGTACTGATTGGGACACTCAGGACAGCACCTCATTGTTTCCAACCGATGTTCCCCCA---AATCCA
ACA---GCAGACTCTGGCCCACACAGAAATCAACATGAGGTCATAGAAACCCCCAAGGAACTCTTTGATGATTGCTCATC
CAAAAACACCGGAAGTGGTAAAGAAGATTTG---------ACAAGACAAGAAGTCAAA---AATACCTCAGAGACAACCA
CAGAGATAGAGGACAGTGAACTTGATACCCAATATTTACAGAATACCTTCAAACGTTCAAAACGCCAATCATTTGCTCTG
TGTCCCAGTCCAAGG------CAGACAAGTATGAAACTCCGGTCCATCCCTAGAGCTCTAAGTCATCAGAGCCCAGATAA
AGCCACGAATCATGGGGGGCAGGAAAAAAAAAAGCAGGGAAGCAGAGAATCAGACAAGGCTGTGCAGCCAGAACTTGCAG
TCATGAGTTCAGCTGCGGTTTGTCAGACAAAGGAGAAAAAGCCAGGTGATTATGCCAAATGTAGCACA------GTCTCT
AGGCTTTGTCACATAGCTCCATTACATGATGACAATGACTGTGACCACAGTGCTGAAAACAACAAGGGAATTTCACAAGT
TCCTGATCAAAAGCAATCTGTCTCTCCAGCAAAGTCATCAGCTGGTAGATCTATATACACAAAAAGCCTCCTGGAGGAAA
GACTTGATGAACAGACCACATGTCCCGAAACAGTGATGGGAAATGAAAGCTTAGTCCACAGTAGCTTAAGCCTGGTTAGC
CAAAGTAACAGCGGAGAATATATTTCTAAAGCAACTGACTCAAACAGATTTGTTGGTGTAGACTCTAGC-----------
----------------------------------------------------GGAGAAGGTAGTCAGGAAGAAAAAGGTG
AAAACAAATTAAATCAGTCCCAAGTCTGTCAACAAAGCTT----------------------------------------
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
-------------------------------------------------
>Phascogale
---------------------NGCTCATTACTGCCTGAAACCTCCAGTTTATTGCCCAACACAGACAGAATGTCT---GA
AAAAGCTGAGCTCAGTAATAAAAGCAAACAGTCTGGCTTAGCAAGGAACCAACAGAGCAGACTGGATGAAAGTAAGGGAA
TATGTAGTACTGGGAAGACCCCCAGTGTAGGAGAG---CAGCCTGAGTTGAATGCCCATCATCTGTGTGAGAAGCAAGAA
CTAAAGGAG---AAGCCACAAGGTCCTGAAGGCCCCAGAGGAAATCCTCAGAATTGCCTATCTGGAACCAAACTGAAAAG
CAGTATTCAGAAAGTTAATGAGTGGTTATCCAGGAGTAATGACATTTTAGCCTCCGATTGCTCCCTTGACAAGAATCATA
AGCAGAATGCAGAGATAGCTAGTGCCTTAGAAGATGGGCATCCAGATAACTCTGATGGAAATTCTAGCATTTCTGAGAAG
ACTGACGTTGTGGCTGACACTGCCGATGGAGCCTGGCTACATGTGCCTAAAAGAACTTACACCAGGCCAGCAGAAAACAA
CAATATTAAAGATAAAATATTTGGAAAAACCTATCGGAGAAAGTCGGGTCACCCTAATTTGAATCACATAACTGAAAATT
TGATTGTTGAGACAGTTGTTCCTGATTCTTTGGTTCCTCCA---------------------------------------
---------------------GAACCTCTGAAAAATACCAAGTTAAAGCGTAAAAGAAAGACTATATGTGACTTGCAGCC
TGAGGATTTCATTAAGAAGACG---GTTCCAGTTACTCACAAAACCCCTGAAAAGAAACATCACGCTGCTGACCAAACCC
TTGAAAGAGAACAAAATGACCAAGTGATGAACATGGATAATGGTCATCCTGAACAGAAAGCACTAAATGGTCAT---GTA
GGGGAAATTAAAGAAGCTCAGACATCGGAACTGTTCTCTGCAGAGAAAGAATCCACTTTCAGAACTGGAACAGAGCCTGC
AGCTAGC------------------------TTAAATGGTGAAGAAACCAACATAACAAAAAAAGACAAGCTGAGGAAGC
AGCCTTCATTCAAGATTGTCTGTGCTCTTGAGCTTGGAGTTGATGGAAGCCCAAGCTCTTCTAATGAGACTGAACTACAG
ATCGATAGCTATCCCAGCAGTGAAGAG---ATAAGGAGAAAAAATAATTCTGAACAGAAGCAACTTAGACGCAGCAGAAG
ACTTCAGCAGGTGTCAGAA---GAGATTGCAATTGGAGCCAAGAAAGCCCATAAGCCAGATGATCAAGCAGAAGAAAGTT
GTATCACTGAAGTTGTCTCAGAACTAAAATTAGGAAATCTACCTGCCTGTGCTCCTGACAATGTCAGTACTGATAAGGAT
CAAGTATTAGCTAGTTGCAGTTTCACA------GGAGATGAAAGGAGT---CTGGAAGTAATCCCT---------AGCAG
CCAAGACCAAGAT------TTGGCATTGAGTGGAAAGGAAGGGTTGCAA---GGTGAAATATCTCAAGGAAGCCTGGGGA
CTGTGGAGGTTCCTGATACTGCTTGGGACACTCAGGACAGTACCTCGTTGTTTCCAGCTGATACTCCTCAA---AATTCA
AAA---CCAGGTCCCAGTCCTCACAGAAATCACTGTGAAATAATGGAAACCCCCAAGGAACTCTTAGAAAGTAGTTCATC
CAAAAACACTGAAAGTAGTGTAGAAGATTTAAGGAGCCTGATGAAACAAGAAGTTAAA---AATGCCTCCAAGACAATCA
CAGAAATGGAGGATAGTGAACTTGACACCCAGTATTTACAGAATACTTTCAAGCGTTCAAAGCGCCAGTCATTTGCACTG
TGTTCTAGCCCAAGG------CAAGAATATGTGAAAACCTGTGCTGTCCCTGGGGCTATAAGTCAGCAAAGT--------
----ACAGTTCGTAGGTACCAGGAAAAAGAAAAGCAAGAAAACAGAGAATCAAACAAGCCTGTGCAGCCAAAGCCTGCTG
TTGTG---------------------ATAGAGAAGGGGAAGCCAGGTGATCATGCCAAATGGAGCACCAGAGAAGTCTCC
AGGCTTTGTCACATAGCTTCATTAAATAGTGGCAATGACTGTGAACCCATTGCTGAAATCAACCAGGGAATTTCACAAGT
TCCTGATCAAAACCAATCAGTTTCTCCAGCAAGGTCATCTGATAGTAAAACCATATATGCAAAAAACTTCCTGGAGGAAA
GGCTTGATGAGCAAACCACGTGCCCTGAAACAACTATGGGAAATGAAAGCTTAGCCCAAAGCAGCATTAGTTTAGTTAGT
CAAAGTAATAGCAGAGAATATGTTTCTAACCCAATTGACTTAATT------ATCAGCGTAGGCTCCAGT-----------
----------------------------------------------------GGAGAAGGCACTCAGGCAGAAAAAAGTG
AAAACAAAGAATCTGAATTAAATACACCACCCAAATTAAAGCTTATGCAACCCCAAGTCTCTCAACAGACCTTT---CCT
CAGAATAATTGCAAA-----------------------------------------------------------------
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
-------------------------------------------------
>Wombat
---------------NNTGCCAGTTCATTACTTCCTAAAACCAGCAGTTTATTGCCCAACACAGACAGAATGAATGTAGA
AAAGGCTGAACTCTGCCATAAAAACAAACAGCCTGCCTTAGGAAGGAACCAAGAGAGCAGTCTCGATGAAAGTAAGGAAA
TATGTAGCCCTGGGAAGACCCCAGGTGCCTGTGAG---CGGCATGAGCTGAATGACCATCATCTGTGTGAGAGGCAAGGC
CTAGAGGAG---AAGCCGCAGCACCCTGAGAGCCCTAGAGGTAATCCTCAGAACTGCCTGTCTGGAACCAAACTGAAAAG
CAGCATTCAGAAAGTTAATGAGTGGTTATCCAGAAGTAGTGACATTTTAGCCTCTGATAACTCCAACGGTAGGAGCCATG
AGCAGAGCGCAGAGGTGCCTAGTGCCTTAGAAGATGGGCATCCAGATACCGCAGAGGGAAATTCTAGCGTTTCTGAGAAG
ACTGACCCAGTGGCTGACAGCACTGATGATGCCTGGCTACATGTGCCTAAAAGAAGCTGTCTCAGGCCTGCAGAAAAC--
-AATATTGAAGATAAAATATTTGGAAAAACCTATCGGAGAAAGTCAGGTCACCCTAATTTGAATTATGTAACTGAAAACT
TGTTTGCTGAAGCTGTGGCTCCTGATTCCTTGATCCCTCTA---------------------------------------
---------------------GAGGCTCCCAAAAACACCAGGTTAAAGCGTAAAGGAAGGAGCATAGCTGACCTGCAGCC
TGAGGATTTCATCAGGAAGACGGACGTTCCAGTTATTCACAAAACCCCTGAAAAGAAAAATCACTCTGTTGACCAAATTC
TCAAAAGAGAACAAAGTGACCAAGTGATGAACACGGCTAACAGTCTTCCTGAGCAGAAAGCCCTAGGTGGTCAT---GTA
GGGGAAGTGAAAGATGTTCAGGTATTAGAGCTGTTCTCTGCGGAGAAAGAATCCACTTTCAGAACTGGAACAGAGCCTGT
AGCTGGCAGCACAAACCATGGGGAGCTTGAATTAAATAGTAGAAATGCCAAAATGACAAGAAAAGACAGGCTGAGGAAGA
AGCCTTCAGCCAGGATCGTCCGTGCTCTTGAGCTCGTAGTTGATAGAAACCCAAGCTCTTCTAATGAGAGTGAACTGCAG
ATCGATAGCTATCCCAGCAGTGAAGAG---ATAAGGAAAGGAACTAATTCTGAACAGAAGCAAATCAGACGCAGCAGAAG
GCTTCGGCTGCTATCAGAA---GAAATTGTGGTTGGAGCCAAGAAGGCCCATAAGCCAGATGACCAAGCAGAAGAAAGTT
GTATCAGTGAAGTTTTCCCAGAACTAAAAATAGGAAACGTGCCTGCCTGTGCTACTGACAGTCTAACTACTGATAGGGAT
CAAGTGTTAGCTAGCTGCAGTTTCACAGAAGAAAGAGATGAAAGGAGC---CTGGAAGCAATCCCA---------AGCAG
CAAAGACCAAGAT------CTGCCCTTGAATGGAGGGGAGGGGTTGCAA---GGTGAAAGAGCCCCAGGAAGCCTGGAGG
CTTTGGAGGTTCCTGATACTGATTGGGACACTCAGGACAGTACCTCATTGTTTCCAGCTGATACTCCCCAA---AATTCA
AAA---GCAGGACCCAGTCCTCACAGAAGCCACAGTGAAATAATGGAAACCCCCAAGGAACTCTTAGATGGTTGTTCATC
CAAAAACACTGAAAGTGACGAAGAAGATTTGAGGAGCCTGATGAGACAGGAAGTTAAA---AATGCCTCCAAGACAACCA
CAGAAATGGAGGATAGTGAACTCGACACCCAGTATTTACAAAATACCTTCAAACGTTCAAAGCGCCAGTCATTTGCTCTG
CGTTCTAGCCCAAGG------CAGGAATGTAGGAAACCCTCTGCTGTCCCTGGGACTGTAAATCAGCAGAGTCCAGATAA
CACCACAGATTGTGGGGGCCAGGAAAAAGAAAAGCAGGGAAACAGAGAATCAAACAAGCCTGTGTGGCCAAAGTCTGCAG
TCATGAGCTTAGCTGCGGCTTGTCAGACAGAGGAGAGGAAGCCAGGTGTTTATGCCAAATGTAGCACCACAGAAGTGTCC
AGGCTTTGTCACATAGCTCCATTACATGGTGTCATTGACTGTGAACACATTGCTGGAAACAACCAGGGAATTTCGCAAGT
TCCTGATCAAAAACCATCAGTTTCTCCAGCAAGGTCATCTGCTAGTAAAACTATAAATACAAAAAACCTCCTGGAGGAAA
GGCTTGATGAACAGACCACATGTCCTGAAACAGCTATGGGAAATGAAAGCTTAGCCCAAAGCAGCTTAAGTCCAGTAAGC
CAAAGTAATAGCAGAGAATATATTTCTAAAGCAACTGACTTAAATAGATTTATCAGCATAGGCTCTAGT-----------
----------------------------------------------------GGAGAAGGCAGTCAGGCACAAAAAGGTG
AAAACAAAGAATCTGAATTAAATACACAACCCAAATTAAAGCTTGTGCAACCCCAAATCTGTCAACAAAGCTTT---CCT
CAGGATAATTGCAAAGAGTCTAAAAGAAAAGGGAAGGGAGGAAATGGAAAATTAGCTCAGGCCATCAGTACAGATTCATC
TCCATGTTTAGAACAA------------------ACTAAAGAGAGTACACATTCTTCTCAGGTTTGTTCTGAGACACCTG
ATGACCT-------------------------------------------------------------------------
--------------------------------------------------------------------------------
-------------------------------------------------
>Bandicoot
---------------------NACTCATTAATGCTTGAAACCAGCAGTTTATTGTCCAACATAGACAGAATGACTACAAA
AAAGGCTGAACTCTGTAATAAAAGTAAAGATCCTGGCTTAGCAAGGAACCAACAGGACTGTTTGGGTGAAAGTAAAGAAA
TAAGTAGCACTGTGAAGACCCCAGCTGCAGGGGAG---CAGCATAAGCTGAATGCCCACCATCTGTGTGAGAAGCAAGAA
CTAGAGGTA---AAGTCACAGCACCCTGAGAGCCCCAAAGGTAGTCCTCGGAGGTGCCGGTCTGGAACCAAACTGAAAAG
CAGTATTCAGAAAGTCAGTGAGTGGTTGTCTAGAAGTAATGACATTTTAAACTCTGATTATTCCCATGAGAGAAGCCAGG
AGCAGAATGCAGAGATTGCTATTGCCTTAGAAGATGGGCATCTGAATACTGCTGATGGAAATTCTAGCATTTCTGAGAAG
ACTGNCCTGGTGGCTGNCACCACTGAT---------------GTGCTGGAAACTAGCTTNTCCAGGCCAGCTAAAAGC--
-AATATTGAAGATAAAATATTTGGGAAGACCTATCGGAGAAAGTCANGTCACTCTAATTTGAATTATCTAACTGAAAACC
TCCTTGTTGAAACTATTGCTCCTGATTCTTTGATCCCTCCA---------------------------------------
---------------------GAATCTCTCAAGAACATCAAGTTAAAGCGAAAAAGAAAAACTATATCTGACCTGCAGCC
TGAAGATTTCATCAGGAAGACAGATGTTCCAGTTAGTCACAAAACCCCTGAAAAGAAAAATCCTGCTGTTGACCAGATTC
TTGAAAGAGAACAAAATGACCAAGTGATGAACACAGCTAATGGTCATCTTAAACAGAAAGCACTGGGTGATCAT---GTC
AAGGAAGTGAAAGATGCTCAGGCAGCAGAACTGTTCTCTACAGAGAAAGAATCAACATTCAGGACTAGAACAGAGCCTAA
AGCTGGCAGCATAGTCCACGGGGAGCTCGAATTAAATGGGAGAGGTGCCAAAATGACAAAAAAGGACAGGTTGAGGAAAA
AGCCTTCAGCCAGGATTGTCCGTGCTCTTGAGCTTGTGGCTGATAAAAACTCAGGCTCTTCTAATGAGGCTGAATTACAG
ATCGATAGTTATCCCAGCAGTGATGAG---ATAAGGAAAGGAAATAATTCTGAACAGAAGCAAATCAGACGCAGCAGAAG
ACTTCAGCTACTGTCAGAA---GAAATTGCAGTTGGAACCAAGAAGGCCCATGAGCCATATGACCAAGCAGAAGAAAGAT
GTGTCAAGAAGGTTTTCCCAGAATTGGAAATGGGAACTGTGTCTGCTGGTGCTACTGACAGCCTATCTACTGATAGGGAT
GAAGTGTTAGCTAGTTGCAGTTTCACAGAT---GGAGAGGAAAGGAAC---CTGGAAGTAATCCCA---------AGCAG
CAAAGACCAAGACCAAGATCTGGCATTAAGTGAAAGGGAAAGGTTGCAA---GAAAAAAGAACCCAAGGAAACCTGGAGC
TTCTGGAGGTTCCAGATACTTATTGGGAAACTCAAGACAGTACTTCACTGTTTCCAGCTGAAACTCCCCAG---AATTCA
AAA---GCAGGACCCAGTCCTCACAGAAGTAACTGTGAAATAATGGAATCCTCCAAAGAACTCTTCGATGCTTATTCATC
CAAAAACACTGACAGTGGCACTGAAGGTTTG---------ATAAGACAGGAAATTAAA---TATGGCTCTGAGACATCTT
CAGTAATGGAGGATAGTGAACTTGACACCCAGTATTTGCAGAATACCTTCAAACGTTCTAAGCGCCAAACATTTGCTCTG
TGTTCCAACCCAAAG------CAGGAACAGATAAAACCCTGCTCTGTTCCTAGGGCTGTCAGCCACCAGAGTTCAGATAA
TGCCTCAGACTGTGGGGGCCAAGAAAAAGAAAAGCAAGGAAACAGAGAATCAAATAAACCTGGCCAACTAGCATCTGCAG
TCAGGAGCTCAGCTGCCACTTGTCAGACA---GAGAGGAAGCCAGGTGATCCTGACAAATGTAGCGCCACAGGAGTTTCC
AGACTTTGTCACATAGCTCCATTACAAGAAGGCAATGACTGTGAATACATTGCTGGAAAAAAACAGGGAATTTCACAAGT
TCCTAATCAAAAACAATCAGTTTCTCCGACAAGGTCATCAGTTAGTAAA---ATATATACAAAAAACCTCTTGAAAGATA
GACTT---GAACAGACCACATGCCCTGAAACAGTTATGGGAAATGAAAGCTTAGGCCAAAGCAGCTTAAGTCCAGTTAGC
CAAAATAACAGCAGAGAATATATTTCTAAAGCAACTGACTTAAATAGATTTATTAGCAGGGACTCTAGT-----------
----------------------------------------------------GGAGAAGACAGTCGGGCAGAAAAAGGTA
AAATCAAAGAATCTGAATTAAATACACCAACCAAATTCAAACTTGTGCAACCACAAGTATGTCAACTAAGCTTT---TCT
CAGGATAATTGCAAAGAGCCAAAAAGAAAAGGGAAAGGAGGAAATGGAATATTAGCTCTGGCCACCAGTACAGATTCATC
TCCATGTTTAAAAGAA------------------ACTAAAGAGAGTACACATTCTTCTCAGG------------------
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
-------------------------------------------------
PyCogent-1.5.3/tests/data/brca1_5.250.paml 000644 000765 000024 00000002453 10665667404 020731 0 ustar 00jrideout staff 000000 000000 5 250
NineBande
tgtggcacaaatactcatgccaacttattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggcgccaacagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cccagcatagagaaaaaggtagatgtggatgctgatcccctgtatgggcgaaaagaactg
aataagcaga
Mouse
tgtggcacagatgctcatgccagctcattacagcctgagaccagcagtttattgctcatt
gaagacagaatgaatgcagaaaaggctgaattctgtaataaaagcaaacagcctggcata
gcagtgagccagcagagcagatgggctgcaagtaaaggaacatgtaacgacaggcaggtt
cccagcactggggaaaaggtaggtccaaacgctgactcccttagtgatagagagaagtgg
actcacccgc
Human
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
cccagcacagaaaaaaaggtagatctgaatgctgatcccctgtgtgagagaaaagaatgg
aataagcaga
HowlerMon
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttgttactcact
aaagacacactgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctgaaagtgaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagatgtggatgctgatcccctgcatgggagaaaagaatgg
aataagcaga
DogFaced
tgtggcacaaatactcatgccaactcattacagcatgagaacagcagtttattatacact
aaagacagaatgaatgtagaaaagactgacttctgtaataaaagcaaacagcctggctta
gcaaggagccagcagaacagatgggttgaaactaaggaaacatgtaatgataggcagact
tccagca?agagaaaaaggtagttctgaatgctgatcccctgaatggaagaataaaactg
aataagcaga
PyCogent-1.5.3/tests/data/brca1_5.paml 000644 000765 000024 00000000540 10665667404 020417 0 ustar 00jrideout staff 000000 000000 5 60
NineBande
gcaaggcgccaacagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
Mouse
gcagtgagccagcagagcagatgggctgcaagtaaaggaacatgtaacgacaggcaggtt
Human
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
HowlerMon
gcaaggagccaacataacagatgggctgaaagtgaggaaacatgtaatgataggcagact
DogFaced
gcaaggagccagcagaacagatgggttgaaactaaggaaacatgtaatgataggcagact
PyCogent-1.5.3/tests/data/brca1_5.tree 000644 000765 000024 00000000057 10665667404 020430 0 ustar 00jrideout staff 000000 000000 (((Human,HowlerMon),Mouse),NineBande,DogFaced); PyCogent-1.5.3/tests/data/F6AVWTA01.sff 000644 000765 000024 00000103100 11446435255 020236 0 ustar 00jrideout staff 000000 000000 .sff ‚¸ „ ¸ TACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTCAG GA202I001ER3QL e b h _ a n f f n c e à f ` _ e b ¾ É Â e k h Æ
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^ k Ê a _ ^ T W' l e ` V ^ ° º g t q TCAGCAGTCAGTCTGCTGCCTTCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTACTGATCGTTGCCTTGGTGGGCCGTTACCCCGCCAACAAGCTAATCAGACGCATCCCCATCCATCACCGATAAATCTTTAATCTCTTTCAGATGTCTTCTAGAGATATCATTGGGTATTAGTCTTACTTTCGCAAGGTTATCCCCAAGTGGTGGCAGGTTGGATACGCGTTACTCACCCGTGCGCCGGTCG%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%%!!!""%%%%%%%%%%%%%%%""""%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&%%%%%%%%%%%%%%%%%%%%%%%((((((&&(&&& $&&$$$$&&&(( & % GA202I001EEVFW h g a i b l f i g g e e b d b h g h Ê g . j g g È c a+ Ä
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O X Z% m z L j P Í ¾ x y m TCAGCATCGTAGCTGCTGCCTTCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTACTGATCGTTGCCTTGGTGGGCCGTTACCCCGCCAACAAGCTAATCAGACGCATCCCCATCCATCACCGATAAATCTTTAATCTCTTTCAGATGTCTTCTAGAGATATCATTGGGTATTAGTCTTACTTTCGCAAGGTTATCCCCAAGTGGTCGGGCAGGTTGGATACGCGTTACTCACCCGTGCGCCGGTCG###################### ########$$$$&&'(''('(((&########"""""############# """###########""! ########################################### ################################### "###### !# ## #####!!!# GA202I001DA5ZC g g ` f e p h g j g m d d c b c d c
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l h l j Í c Y p h ] [ ^ l e j i i Ó 1 m e Ì b f h q » g U b j _ Ç
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i M TCAGCATCGTAGCTGCTGCCTCCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTACTGATCGTTGCCTTGGTGGGCCGTTACCCCGCCAACAAGCTAATCAGACGCATCCCCATCCATCACCGATAAATCTTTAATCTCTTTCAGATGTCTTCTAGAGATATCATTGGGTATTAGTCTTACTTTCGCAAGGTTATCCCCAAGTGGTGGGCAGGTTGGATACGCGTTACTCACCCGTGCGCCGGTCG%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%&& (%%%%%%%%%%%%%%&&&&%%%%%%%%%%%%%%%%%%%&&&%%%%%%!!!!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&%%%%%%%%%$$ !!&&$$$ !%&&$$$$$&&& GA202I001B9RKV c b j d ^ p g c c d l a b c ` d g c È
i " h e m É
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S( m i W „ y TCAGCATCGTAGCTGCTGCCTCCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCCCGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGCGGACTCATGATGCCATCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGTGCG%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%% (%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&%%%%%%&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&(((&&&&&&&& GA202I001E1SL6 h g ` g g n f g g g k d d _ d f e d Î È Å g c f à a ` d f d Ê f Í g c d f e b d d f i g Ð a f f g d
8 Í Ì Ã X c ` f c e f Ð
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h Y i k e d ¼ c q [
l
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k ¬ d TCAGCATCGTAGCTGCTGCCTTCCGTAGGAGTCTGGTCCGTGTCTCAGTACCAGTGTGGGGGGTTAACCTCTCAGTCCCCCTATGTATCGTCGCCTTGGTGAGCCGTTACCCCACCAACTAGCTAATACAACGCATGCCCATCCCTAACCATCGGAATTTTCAACCATAAAAGATGCCTTCTATGATATTATGGGGTATTAGTACCAATTTCTCAGTGTTACTCCCCCTGTTAAAGGTAGGTTGCATACGCGTTACGCACCCGTGCGCCGGTCGCCACCA%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%% !!%%%%%%%%%%& !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%""""&%%%%%%%%%%%%%%%%%%%%%%& $ !!$$$$$$ þ GA202I001EGORF d d h d b c ` m c a c k d e e c f e Ì i $ h e k É g ` h `
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^ a Í g y TCAGCTGACTGACTGCTGCCTCCCGTAGGAGTCTGGGCCGTGTCTCAGTCCCAATGTGGCCGGTCACCCTCTCAGGTCGGCTACTGATCGTCGCCTTGGTGGGCTGTTATCTCACCAACTAGCTAATCAGACGCGGGTCCATCTTATACCACCGGAGTTTTTCACACCATGTCATGCAACATTGTGCGCTTATGCGGTATTACCAGCCGTTTCCAGCTGCTATCCCCCAGTACAAGGCAGGTTACCCACGCGTTAC%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%"""""%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%((((((&&&&&&&((&&&(&&(&&&&&!! GA202I001DRQUB e e g e c f f o e e c m e e c e f e » Ê ¾ \ g h
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d h a w e ] c È g g O N `$ o k Y ~ { TCAGCTGACTGACTGCTGCCTTCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCCCGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGCGGACTCATGATGCCATCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGTGCG%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%% &%%%%%%%%%%%%%%""""%%%%%%%%%%%%%%%%%%%%%%%%%%%&!!!!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%(&&&&&&&&&&$$$&$$$%%&!!!!&&&& GA202I001COCJJ g g a f f e g i h f f h e f a f c d
Î Ê È g f i Ë a d f g c . Î e e
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Y
a? € TCAGCTGACTGACTGCTGCCTTCCGTAGGAGTCTGGGCCGTGTCTCAGTCCCAGTGTGGCTGGTCGTCCTCTCAGACCAGCTACCGATCGTCGCCTTGGTGAGCCTTTACCTCACCAACTAGCTAATCGGACATCGGCCGCTCTTCCAGCGCGAGGTCTTGCGATCCCCCGCTTTCACCCTCAGGTCTCATGCGGTATTAGCTGCCCTTTCGGGCAGTTATCCCCCCATAGAAGACACGTTCCGATGTATTACTCACCCG%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%"""%&&!""%%%%%% !#% !!!!$$!!!!$%$$$$ GA202I001EK5WE g g b d e h e j f e c i e e b e h d Ê
Ï Ä h g f Ç
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1 r TCAGCTGACTGACTGCTGCCTTCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGTTGGTTTGGTGGGCCGTTACCCCGCCAACTGCCTAATGGAACGCATCCCCATCGACAACCGAAATTCTTTAATAATTATCCCATGCGGGAAAACTATGCCATCCGGTATTAATCTTTCTTTCGAAAGGCTATCCCAGTGTTGTCGGCAGGTTGGATACGTGTTACTCACCCGTGCGCCGGTCGCCATCCATCAAAG%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%%!!!!!%%%%%%%%%%%%%%%""""%%%%%%%%%%%%%%%%%%%!!!%%%%%%!!!!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&%%%%(&&&&&(((&&&&&((((&&&&&&&&&&& GA202I001C3FPU b d j c o c m c e c ^ c e d b e g e É i $ g g k
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d
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l g j Í Õ i Q g q a ^ X h Ï ` e Ë Ü ¼ \
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P [ W m g ^ y TCAGAGACTCTGCTGCTGCCTCCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCCCGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGTGAACTCATGATGCCATCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGTGCG%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%%"""""%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&!!!!&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%(((((&&&&&&&&&&&&&&&&&&&&&&&& GA202I001C31UY h f a g n f l g h e e d c d d e f e Æ f ' g h f É f b) Æ e Á c e
e d b e c
g
g Ð Å Ê g i e Ý e Ç Ä » b b g g f f
Æ… h \ e Ì
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g
g g Î
a _ h h h Ê h " Ì d Ï lz k º c g i a \
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b ¿ g l P
V `" l m Z ‰ ~ TCAGAGACTCTGCTGCTGCCTCCCGTAGGAGTTTGGACCGTGTCTCAGTTCCAATGTGGGGGACCTTCCTCTCAGAACCCCTATCCATCGAAGACTAGGTGGGCCGTTACCCCGCCTACTATCTAATGGAACGCATCCCCATCGTCTACCGGAATACCTTTAATCATGTGAACATGCGGACTCATGATGCCATCTTGTATTAATCTTCCTTTCAGAAGGCTGTCCAAGAGTAGACGGCAGGTTGGATACGTGTTACTCACCCGTGCG%%%%%%%%%%%%%%%%%%%%%%(((((((((((((((((((((((((((%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%& &%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&((&&&&&&&&&&&&&&$&&&&&&&&%$$
GA202I001CXAFL a c k f n d l e d a c a a d d b c e Æ
g h e j
Å
e a Á g  b h c c e e a f e Î
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f e e g b
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Ç a d b e f d b À n
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454
GA202I001
R_2010_01_22_13_28_56_FLX02080328_adminrig_Bushman_CaFE
D_2010_01_22_13_30_28_FLX02080328_fullProcessingAmplicons
/data/R_2010_01_22_13_28_56_FLX02080328_adminrig_Bushman_CaFE/D_2010_01_22_13_30_28_FLX02080328_fullProcessingAmplicons/
1.1.03
GA202I001B35KA o÷ÿGA202I001B9RKV BâÿGA202I001C31UY vfÿGA202I001C3FPU i‘ÿGA202I001COCJJ \”ÿGA202I001CXAFL |ÔÿGA202I001D4EKM %ÿGA202I001D7W79 ›ÿGA202I001DA5ZC Rhesus with extra words
tgtggcacaaatactcatgccagctcattacagcatgagaac---agtttgttactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggcttg
gcaaggagccaacataacagatggactggaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagatctgaatgctaatgccctgtatgagagaaaagaatgg
aataagcaaaaactgccatgctctgagaatcctagagacactgaagatgttccttgg
>Manatee
tgtggcacaaatactcatgccagctcattacagcatgagaatagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtcataaaagcaaacagcctggctta
acaaggagccagcagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cctagcacagagaaaaaggtagatatgaatgctaatccattgtatgagagaaaagaagtg
aataagcagaaacctccatgctccgagagtgttagagatacacaagatattccttgg
>Pig
tgtggcacagatactcatgccagctcgttacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattttgtaataaaagcaagcagcctgtctta
gcaaagagccaacagagcagatgggctgaaagtaagggcacatgtaatgataggcagact
cctaacacagagaaaaaggtagttctgaatactgatctcctgtatgggagaaacgaactg
aataagcagaaacctgcgtgctctgacagtcctagagattcccaagatgttccttgg
>GoldenMol
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaaacaaacagtctggctta
gcgaggagccagcagagcagatgggctggaagtaaggcagcgtgcaatgacaagcagact
cctagcacacagacagagctatataggagtgctggtcccatgcacaggagaaaagaagta
aataagctgaaatctccatggtctgagagtcctggagctacccaagagattccttgg
>Rat
tgtggcacagatgctcgtgccagctcattacagcgtgggacccgcagtttattgttcact
gaggacagactggatgcagaaaaggctgaattctgtgatagaagcaaacagtctggcgca
gcagtgagccagcagagcagatgggctgacagtaaagaaacatgtaatggcaggccggtt
ccccgcactgagggaaaggcagatccaaatgtggattccctctgtggtagaaagcagtgg
aatcatccgaaaagcctgtgccctgagaattctggagctaccactgacgttccttgg
>Human
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
cccagcacagaaaaaaaggtagatctgaatgctgatcccctgtgtgagagaaaagaatgg
aataagcagaaactgccatgctcagagaatcctagagatactgaagatgttccttgg
>Jackrabbit
------------------------------------------------------------
---------------------aaggctgaattctgtaataagagcaaacagcctggctta
gcaagaagccaacagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagttctgaatgttgactgcctgtatgggagaaaacaacag
gataagcagaaacctccatgccctgagacctctggagataaccaagatgtttcttgg
>FlyingSqu
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccagcagagcagatgggctaaaagtaaggaaacctgtaatgataggcaaatt
cccagctcagagaaaaaggtagatttgaatgctgatccccaatatgagaaaaaagaacca
agtaagcagaaacatccatgctctgagaattccagagatacccaagatgttccttgg
>FreeTaile
tgtggcacagatactcatgccagctcattacagcatgagaacagcagtttactactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaagcagcctggctta
gcaaagagccagcagagcagatgggctgaaagtaaagaaacatgtaatgataggcagact
ctcagcacagagaaaagggtagttctgaatgctgatcctctgaat---------------
aggagaaaagaacctccaggctctaactatcctagagattcccaagatgttccttgg
>Mole
tgtggcataaatactcatgccagcttattacagcatgaaaacagcagtttattactcact
gaaaacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctgactta
gcaaagagccagcagaacagatgggctgaaagtaaagaaacatgtaatgataggcagact
tccagcccagagaaaagggtagacccgaatgctgatcccatgtatgggagaaaagaactg
aataagcagaaacctccatgctctgacagccccagaaattcccaaggtgttgcctgg
PyCogent-1.5.3/tests/data/formattest.gde 000644 000765 000024 00000006041 10665667404 021203 0 ustar 00jrideout staff 000000 000000 %Rhesus
tgtggcacaaatactcatgccagctcattacagcatgagaac---agtttgttactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggcttg
gcaaggagccaacataacagatggactggaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagatctgaatgctaatgccctgtatgagagaaaagaatgg
aataagcaaaaactgccatgctctgagaatcctagagacactgaagatgttccttgg
%Manatee
tgtggcacaaatactcatgccagctcattacagcatgagaatagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtcataaaagcaaacagcctggctta
acaaggagccagcagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cctagcacagagaaaaaggtagatatgaatgctaatccattgtatgagagaaaagaagtg
aataagcagaaacctccatgctccgagagtgttagagatacacaagatattccttgg
%Pig
tgtggcacagatactcatgccagctcgttacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattttgtaataaaagcaagcagcctgtctta
gcaaagagccaacagagcagatgggctgaaagtaagggcacatgtaatgataggcagact
cctaacacagagaaaaaggtagttctgaatactgatctcctgtatgggagaaacgaactg
aataagcagaaacctgcgtgctctgacagtcctagagattcccaagatgttccttgg
%GoldenMol
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaaacaaacagtctggctta
gcgaggagccagcagagcagatgggctggaagtaaggcagcgtgcaatgacaagcagact
cctagcacacagacagagctatataggagtgctggtcccatgcacaggagaaaagaagta
aataagctgaaatctccatggtctgagagtcctggagctacccaagagattccttgg
%Rat
tgtggcacagatgctcgtgccagctcattacagcgtgggacccgcagtttattgttcact
gaggacagactggatgcagaaaaggctgaattctgtgatagaagcaaacagtctggcgca
gcagtgagccagcagagcagatgggctgacagtaaagaaacatgtaatggcaggccggtt
ccccgcactgagggaaaggcagatccaaatgtggattccctctgtggtagaaagcagtgg
aatcatccgaaaagcctgtgccctgagaattctggagctaccactgacgttccttgg
%Human
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
cccagcacagaaaaaaaggtagatctgaatgctgatcccctgtgtgagagaaaagaatgg
aataagcagaaactgccatgctcagagaatcctagagatactgaagatgttccttgg
%Jackrabbit
------------------------------------------------------------
---------------------aaggctgaattctgtaataagagcaaacagcctggctta
gcaagaagccaacagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagttctgaatgttgactgcctgtatgggagaaaacaacag
gataagcagaaacctccatgccctgagacctctggagataaccaagatgtttcttgg
%FlyingSqu
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccagcagagcagatgggctaaaagtaaggaaacctgtaatgataggcaaatt
cccagctcagagaaaaaggtagatttgaatgctgatccccaatatgagaaaaaagaacca
agtaagcagaaacatccatgctctgagaattccagagatacccaagatgttccttgg
%FreeTaile
tgtggcacagatactcatgccagctcattacagcatgagaacagcagtttactactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaagcagcctggctta
gcaaagagccagcagagcagatgggctgaaagtaaagaaacatgtaatgataggcagact
ctcagcacagagaaaagggtagttctgaatgctgatcctctgaat---------------
aggagaaaagaacctccaggctctaactatcctagagattcccaagatgttccttgg
%Mole
tgtggcataaatactcatgccagcttattacagcatgaaaacagcagtttattactcact
gaaaacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctgactta
gcaaagagccagcagaacagatgggctgaaagtaaagaaacatgtaatgataggcagact
tccagcccagagaaaagggtagacccgaatgctgatcccatgtatgggagaaaagaactg
aataagcagaaacctccatgctctgacagccccagaaattcccaaggtgttgcctgg
PyCogent-1.5.3/tests/data/formattest.msf 000644 000765 000024 00000006653 10665667404 021242 0 ustar 00jrideout staff 000000 000000
This file is an example of the sort of broken MSF many programs produce
Features that cannot be relied on are the header !!AA_MULTIPLE_ALIGNMENT 1.0
that should be on the first line, checksum, date type etc.
The other main variance is position numbers on the line above the sequence
which is on only the second block in this test
D:\MHC.msf MSF: 184 Type: N January 01, 1776 12:00 Check: 0 ..
Name: TrvuDRB2 Len: 184 Check: 0 Weight: 1.00
Name: TrvuDRB3 Len: 184 Check: 0 Weight: 1.00
Name: MaruDAB1 Len: 184 Check: 0 Weight: 1.00
Name: ModoDAB1 Len: 184 Check: 0 Weight: 1.00
Name: MaruDBB Len: 184 Check: 0 Weight: 1.00
Name: TvMHC2_5 Len: 184 Check: 0 Weight: 1.00
Name: HosaDOB Len: 184 Check: 0 Weight: 1.00
Name: PatrDOB Len: 184 Check: 0 Weight: 1.00
Name: OrcuDOB Len: 184 Check: 0 Weight: 1.00
//
TrvuDRB2 ---MLSVLLP KGVWIEVLAV TLLVLASQVA AGRHA-PEHF TEQGKSECHF
TrvuDRB3 ---MPCVLLP KGIWIEVLAV TLLVLTSQVA SGRHA-PEHF TGQFKYECHF
MaruDAB1 ---------- --------AV ILLVLTSQVA AGRHA-PKDF LWQAKSECHF
ModoDAB1 ---MVSAQPL GGIWMEVLVV TLLVLTAQVA ADRRP-PKHF TEYSTSECYF
MaruDBB ---MVDVRIS AGCWKIGLLM TSMLLSLSAS WARDI-PEDF VYQYKAECYF
TvMHC2_5 ---MVDVWIS ADYWKIGLLM TLTVLSLSAS WARDI-PEDF MRQHKAECYF
HosaDOB ------MGSG WVPWVVALLV NLTQLDSSMT QGTDS-PEDF VIQAKADCYF
PatrDOB ------MGSG WVPWVVALLV NLTRLDSSMT QGTDS-PEDF VIQAKADCYF
OrcuDOB ------MDSK WVPWVVALLV NLIRLDYSMT Q-GDS-PEDF VIQAKADCYF
51 100
TrvuDRB2 VNGTETVRFV ERHVYNREEF MRFDSDVGEY VALTELGRRQ AEYYNS-QKD
TrvuDRB3 VNGTEHVRFV ERHIYNREEF MRFDSAVGEF VALTELGRRH AELWNS-RKE
MaruDAB1 ENGTQHVRFM DRYFYNRQEA LRFDSDVGEY VAVSELGRLQ AELWNK-REE
ModoDAB1 INGTDQVRLI ERYIYNREEY VRFDSNVGVY EAVTELGRGI AEHLNS-QKE
MaruDBB TNGSERVRFV VRDIYNGEEF ARFDSDVGVY VPVTELGRPD AEYWNS-QEE
TvMHC2_5 TNGTERVRFV ERYIYNDQED VRFDSEVGEY VAVTELGRPD AEYWNS-QKE
HosaDOB TNGTEKVQFV VRFIFNLEEY VRFDSDVGMF VALTKLGQPD AEQWNS-RLD
PatrDOB TNGTEKVQFV VRFIFNLEEY VRFDSDVGMF VALTKLGQPD AEQWNS-RLD
OrcuDOB TNGTEQVRVV VRFIFNLEEY AHFDSDVGMF VALTELGQPD AESWNN-RPD
TrvuDRB2 YMESRRGQVD NYCRHNYE-V IEPFSVRRRV EPEVTVYPSK TAPLGHHNLL
TrvuDRB3 ILEGRRAQVD -TCRHNYE-V IEPFSVRRRV EPEVTVYPSK TAPLGHHNLL
MaruDAB1 ILEDARAAVD TLCRHNYE-I LERFLVPRRV EPEVTVYPSK LAPLGHHNLL
ModoDAB1 RLDYLLAAVD TYCRHNYE-I SEPFLVRRRV EPEVLVYPSK TAPVGHHNLL
MaruDBB ILEKERAYVD TLCRHNYE-A AKPFTLDRRV QPRVTISPSK --TDALQHLL
TvMHC2_5 LLEEKRAEVD TLCRHNYE-A GKSFTVDRRV QPRVTISPSR --TEALQHLL
HosaDOB LLERSRQAVD GVCRHNYR-L GAPFTVGRKV QPEVTVYPER TPLLHQHNLL
PatrDOB LLERSRQAVD GVCRHNYR-L GAPFTVGRKV QPEVTVYPER TPLLHQHNLL
OrcuDOB ILERSRRSVD FLCRRNYR-L GAPFTVGRKV PPEGTVIPER TPVCGQQPAA
TrvuDRB2 GVGLIVHRRS QKGNRGSQPT GLLS------ ----
TrvuDRB3 GVGLVVHRRS QKGNRGSQPT GLLS------ ----
MaruDAB1 GVGLIVYKRN QKGNRGSQPT GLLS------ ----
ModoDAB1 GGGLIVHMRS QKANRGSQPA GLLS------ ----
MaruDBB SVGLIIHLKN KKGHTGPQPT GLLG------ ----
TvMHC2_5 GVGLIIHLKN QKGRTGPQPA GLLR------ ----
HosaDOB LVGIVIQLRA QKGYVRTQMS GNEVSRAVLL PQSC
PatrDOB LVGIVIQLRA QKGYVRTQMS GNEVSRAVLL PQSC
OrcuDOB LVGTIIHIRA WKICGDTALC CC-------- ----
PyCogent-1.5.3/tests/data/formattest.paml 000644 000765 000024 00000006037 10665667404 021402 0 ustar 00jrideout staff 000000 000000 10 297
Rhesus
tgtggcacaaatactcatgccagctcattacagcatgagaac---agtttgttactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggcttg
gcaaggagccaacataacagatggactggaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagatctgaatgctaatgccctgtatgagagaaaagaatgg
aataagcaaaaactgccatgctctgagaatcctagagacactgaagatgttccttgg
Manatee
tgtggcacaaatactcatgccagctcattacagcatgagaatagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtcataaaagcaaacagcctggctta
acaaggagccagcagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cctagcacagagaaaaaggtagatatgaatgctaatccattgtatgagagaaaagaagtg
aataagcagaaacctccatgctccgagagtgttagagatacacaagatattccttgg
Pig
tgtggcacagatactcatgccagctcgttacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattttgtaataaaagcaagcagcctgtctta
gcaaagagccaacagagcagatgggctgaaagtaagggcacatgtaatgataggcagact
cctaacacagagaaaaaggtagttctgaatactgatctcctgtatgggagaaacgaactg
aataagcagaaacctgcgtgctctgacagtcctagagattcccaagatgttccttgg
GoldenMol
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaaacaaacagtctggctta
gcgaggagccagcagagcagatgggctggaagtaaggcagcgtgcaatgacaagcagact
cctagcacacagacagagctatataggagtgctggtcccatgcacaggagaaaagaagta
aataagctgaaatctccatggtctgagagtcctggagctacccaagagattccttgg
Rat
tgtggcacagatgctcgtgccagctcattacagcgtgggacccgcagtttattgttcact
gaggacagactggatgcagaaaaggctgaattctgtgatagaagcaaacagtctggcgca
gcagtgagccagcagagcagatgggctgacagtaaagaaacatgtaatggcaggccggtt
ccccgcactgagggaaaggcagatccaaatgtggattccctctgtggtagaaagcagtgg
aatcatccgaaaagcctgtgccctgagaattctggagctaccactgacgttccttgg
Human
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
cccagcacagaaaaaaaggtagatctgaatgctgatcccctgtgtgagagaaaagaatgg
aataagcagaaactgccatgctcagagaatcctagagatactgaagatgttccttgg
Jackrabbit
------------------------------------------------------------
---------------------aaggctgaattctgtaataagagcaaacagcctggctta
gcaagaagccaacagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagttctgaatgttgactgcctgtatgggagaaaacaacag
gataagcagaaacctccatgccctgagacctctggagataaccaagatgtttcttgg
FlyingSqu
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccagcagagcagatgggctaaaagtaaggaaacctgtaatgataggcaaatt
cccagctcagagaaaaaggtagatttgaatgctgatccccaatatgagaaaaaagaacca
agtaagcagaaacatccatgctctgagaattccagagatacccaagatgttccttgg
FreeTaile
tgtggcacagatactcatgccagctcattacagcatgagaacagcagtttactactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaagcagcctggctta
gcaaagagccagcagagcagatgggctgaaagtaaagaaacatgtaatgataggcagact
ctcagcacagagaaaagggtagttctgaatgctgatcctctgaat---------------
aggagaaaagaacctccaggctctaactatcctagagattcccaagatgttccttgg
Mole
tgtggcataaatactcatgccagcttattacagcatgaaaacagcagtttattactcact
gaaaacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctgactta
gcaaagagccagcagaacagatgggctgaaagtaaagaaacatgtaatgataggcagact
tccagcccagagaaaagggtagacccgaatgctgatcccatgtatgggagaaaagaactg
aataagcagaaacctccatgctctgacagccccagaaattcccaaggtgttgcctgg
PyCogent-1.5.3/tests/data/formattest.phylip 000644 000765 000024 00000006710 10665667404 021754 0 ustar 00jrideout staff 000000 000000 10 297
Rhesus tgtggcacaaatactcatgccagctcattacagcatgagaac---agtttgttactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggcttg
gcaaggagccaacataacagatggactggaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagatctgaatgctaatgccctgtatgagagaaaagaatgg
aataagcaaaaactgccatgctctgagaatcctagagacactgaagatgttccttgg
Manatee tgtggcacaaatactcatgccagctcattacagcatgagaatagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtcataaaagcaaacagcctggctta
acaaggagccagcagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cctagcacagagaaaaaggtagatatgaatgctaatccattgtatgagagaaaagaagtg
aataagcagaaacctccatgctccgagagtgttagagatacacaagatattccttgg
Pig tgtggcacagatactcatgccagctcgttacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattttgtaataaaagcaagcagcctgtctta
gcaaagagccaacagagcagatgggctgaaagtaagggcacatgtaatgataggcagact
cctaacacagagaaaaaggtagttctgaatactgatctcctgtatgggagaaacgaactg
aataagcagaaacctgcgtgctctgacagtcctagagattcccaagatgttccttgg
GoldenMo tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaaacaaacagtctggctta
gcgaggagccagcagagcagatgggctggaagtaaggcagcgtgcaatgacaagcagact
cctagcacacagacagagctatataggagtgctggtcccatgcacaggagaaaagaagta
aataagctgaaatctccatggtctgagagtcctggagctacccaagagattccttgg
Rat tgtggcacagatgctcgtgccagctcattacagcgtgggacccgcagtttattgttcact
gaggacagactggatgcagaaaaggctgaattctgtgatagaagcaaacagtctggcgca
gcagtgagccagcagagcagatgggctgacagtaaagaaacatgtaatggcaggccggtt
ccccgcactgagggaaaggcagatccaaatgtggattccctctgtggtagaaagcagtgg
aatcatccgaaaagcctgtgccctgagaattctggagctaccactgacgttccttgg
Human tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
cccagcacagaaaaaaaggtagatctgaatgctgatcccctgtgtgagagaaaagaatgg
aataagcagaaactgccatgctcagagaatcctagagatactgaagatgttccttgg
Jackrabb ------------------------------------------------------------
---------------------aaggctgaattctgtaataagagcaaacagcctggctta
gcaagaagccaacagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagttctgaatgttgactgcctgtatgggagaaaacaacag
gataagcagaaacctccatgccctgagacctctggagataaccaagatgtttcttgg
FlyingSq tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccagcagagcagatgggctaaaagtaaggaaacctgtaatgataggcaaatt
cccagctcagagaaaaaggtagatttgaatgctgatccccaatatgagaaaaaagaacca
agtaagcagaaacatccatgctctgagaattccagagatacccaagatgttccttgg
FreeTail tgtggcacagatactcatgccagctcattacagcatgagaacagcagtttactactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaagcagcctggctta
gcaaagagccagcagagcagatgggctgaaagtaaagaaacatgtaatgataggcagact
ctcagcacagagaaaagggtagttctgaatgctgatcctctgaat---------------
aggagaaaagaacctccaggctctaactatcctagagattcccaagatgttccttgg
Mole tgtggcataaatactcatgccagcttattacagcatgaaaacagcagtttattactcact
gaaaacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctgactta
gcaaagagccagcagaacagatgggctgaaagtaaagaaacatgtaatgataggcagact
tccagcccagagaaaagggtagacccgaatgctgatcccatgtatgggagaaaagaactg
aataagcagaaacctccatgctctgacagccccagaaattcccaaggtgttgcctgg
PyCogent-1.5.3/tests/data/Homo_sapiens_codon_usage.pri 000644 000765 000024 00001606061 10665667404 024051 0 ustar 00jrideout staff 000000 000000 >BX649449#3\BX649449\join(44979..45265,45932..46513,48260..48821)\1431\CAH71689.1\Homo sapiens\Human DNA sequence from clone RP11-248D7 on chromosome 1 Containstwo genes for novel proteins similar to preferentially expressedantigen in melanoma (PRAME) and a preferentially expressed antigenin melanoma (PRAME) pseudogene.\n\, complete sequence./locus_tag="RP11-248D7.3-001"/standard_name="OTTHUMP00000011089"/codon_start=1/product="novel protein similar to preferentially expressed antigen in melanoma (PRAME)"/protein_id="CAH71689.1"/db_xref="GI:55666023"/db_xref="InterPro:IPR001611"/db_xref="UniProt/TrEMBL:Q5TYX0"
0 6 3 0 7 15 6 19 37 11 6 6 2 6 1 5 9 5 4 12 0 7 6 11 1 7 4 13 0 5 3 5 4 1 2 5 12 7 8 19 11 6 10 14 6 3 8 17 12 12 5 3 14 13 15 4 4 12 4 15 8 0 0 1
>BC002704\BC002704\307..2445\2139\AAH02704.1\Homo sapiens\Homo sapiens signal transducer and activator of transcription 1,91kDa, transcript variant beta, mRNA (cDNA clone MGC:3493IMAGE:3627218), complete cds./gene="STAT1"/codon_start=1/product="signal transducer and activator of transcription 1, isoform beta"/protein_id="AAH02704.1"/db_xref="GI:12803735"/db_xref="GeneID:6772"/db_xref="MIM:600555"
2 3 6 3 11 7 3 11 29 18 7 19 4 8 2 9 12 10 7 12 6 8 8 9 5 10 4 10 4 9 6 6 7 7 3 9 19 10 30 25 13 30 9 44 9 6 35 26 19 16 9 9 5 5 17 15 6 15 15 16 15 1 0 0
>HS445C9#3\Z95115\57994..58629\636\CAB62951.1\Homo sapiens\Human DNA sequence from clone CTA-445C9 on chromosome 22q12.1,complete sequence./locus_tag="CTA-445C9.2-001"/standard_name="OTTHUMP00000028722"/codon_start=1/protein_id="CAB62951.1"/db_xref="GI:6572242"/db_xref="Genew:4994"/db_xref="GOA:Q9UGV6"/db_xref="HSSP:1NHN"/db_xref="InterPro:IPR000135"/db_xref="InterPro:IPR000910"/db_xref="InterPro:IPR009071"/db_xref="UniProt/Swiss-Prot:Q9UGV6"
1 1 1 0 2 2 0 1 5 0 0 0 5 1 1 3 2 0 1 2 0 3 2 2 1 6 7 3 5 6 6 2 2 1 0 2 0 2 16 27 2 2 1 1 1 4 19 13 2 16 2 4 2 1 4 4 0 2 2 6 2 1 0 0
>BC037529\BC037529\240..560\321\AAH37529.2\Homo sapiens\Homo sapiens methylenetetrahydrofolate dehydrogenase (NADP+dependent) 2-like, mRNA (cDNA clone IMAGE:4794959), complete cds./gene="MTHFD2L"/codon_start=1/product="MTHFD2L protein"/protein_id="AAH37529.2"/db_xref="GI:34191218"/db_xref="GeneID:441024"
1 0 0 0 4 1 2 3 0 3 3 2 2 1 0 2 2 2 1 0 0 1 4 0 0 2 1 2 0 3 3 0 1 3 2 2 3 3 2 3 2 2 2 4 1 2 6 1 2 3 0 1 0 2 0 1 5 1 3 3 1 1 0 0
>BT019976\BT019976\1..579\579\AAV38779.1\Homo sapiens\Homo sapiens phosphomevalonate kinase mRNA, complete cds./codon_start=1/product="phosphomevalonate kinase"/protein_id="AAV38779.1"/db_xref="GI:54696814"
1 5 6 0 4 2 0 4 10 2 0 3 1 3 0 2 4 1 1 3 3 0 3 1 2 0 0 5 2 5 4 7 4 1 2 4 6 2 2 6 4 0 0 13 0 2 3 14 10 2 1 2 1 2 6 5 1 6 1 3 5 0 1 0
>BC006354\BC006354\268..945\678\AAH06354.1\Homo sapiens\Homo sapiens Coenzyme A synthase, mRNA (cDNA clone IMAGE:4123850),complete cds./gene="COASY"/codon_start=1/product="COASY protein"/protein_id="AAH06354.1"/db_xref="GI:13623499"/db_xref="GeneID:80347"
2 3 5 1 1 3 1 8 9 3 0 4 1 0 0 1 7 3 2 2 1 4 5 2 1 3 1 11 2 7 2 8 6 2 2 4 13 0 2 10 3 1 2 12 2 5 4 11 4 5 1 3 0 2 0 3 2 6 8 4 5 0 0 1
>AL136089#5\AL136089\complement(join(4948..5708,8394..8514,10823..10933, 11451..11563,11876..11987,12333..12394,14627..14791, 24237..24393))\1602\CAI20011.1\Homo sapiens\Human DNA sequence from clone RP1-278E11 on chromosome 6 Containsthe 3' end of the novel gene KIAA0381, the MOCS1 gene formolybdenum cofactor synthesis 1, a pseudogene similar to 60Sribosomal protein L23 (RPL23) and a pseudogene similar to tubulinbeta chain (TUBB), complete sequence./gene="MOCS1"/locus_tag="RP1-278E11.2-002"/standard_name="OTTHUMP00000016354"/codon_start=1/protein_id="CAI20011.1"/db_xref="GI:56204710"/db_xref="GOA:Q5TCE2"/db_xref="InterPro:IPR002820"/db_xref="InterPro:IPR007197"/db_xref="InterPro:IPR010505"/db_xref="UniProt/TrEMBL:Q5TCE2"
3 4 15 1 5 5 7 14 29 5 2 3 5 9 1 7 12 2 7 14 0 6 7 11 5 6 6 26 1 15 8 14 9 7 3 11 27 2 5 25 13 3 2 26 7 6 6 27 14 8 2 3 7 2 12 8 2 19 5 12 5 0 1 0
>HUMXE7A#2\L03426\join(167..928,929..1077,1078..1318,1319..1324)\1158\AAA61303.1\Homo sapiens\Human XE7 mRNA, complete alternate coding regions./gene="XE7"/codon_start=1/protein_id="AAA61303.1"/db_xref="GI:340387"
2 10 6 3 4 8 0 6 30 2 0 3 1 8 2 3 7 2 0 10 3 0 0 6 4 1 2 14 5 2 0 9 8 0 0 3 11 1 4 38 8 2 3 20 7 0 7 41 15 2 6 1 4 0 15 3 0 16 2 12 3 0 0 1
>AY623111\AY623111\join(2465..2513,3272..3362,27057..27132,40243..40335, 73734..73813,89444..89510,92446..92508,104917..105004, 112167..112397,117471..117609,133807..133966, 144333..144445,145517..145564,147600..147722, 148444..148777,167766..167795)\1785\AAT38107.1\Homo sapiens\Homo sapiens CDC14 cell division cycle 14 homolog A (S. cerevisiae)(CDC14A) gene, complete cds./gene="CDC14A"/codon_start=1/product="CDC14 cell division cycle 14 homolog A (S. cerevisiae)"/protein_id="AAT38107.1"/db_xref="GI:47777659"
6 1 4 3 16 7 8 7 10 7 8 10 12 15 2 14 12 8 14 12 1 7 13 7 2 8 19 13 2 8 16 9 7 7 4 2 8 6 25 13 21 18 6 10 9 7 17 15 9 17 11 16 5 6 16 17 9 10 11 8 3 1 0 0
>AK027045\AK027045\98..1822\1725\BAB15636.1\Homo sapiens\Homo sapiens cDNA: FLJ23392 fis, clone HEP17418./codon_start=1/protein_id="BAB15636.1"/db_xref="GI:10440063"
4 5 11 4 4 3 4 3 25 12 0 8 12 8 4 14 10 10 9 11 3 9 33 9 0 22 17 20 0 17 12 11 14 8 2 6 20 7 8 12 3 3 3 20 8 8 13 29 14 13 11 5 6 4 12 9 0 5 4 7 6 1 0 0
>AF238378#2\AF238378\complement(join(20771..20880,21461..21635))\285\AAT68884.1\Homo sapiens\Homo sapiens chromosome 8 clone SCb-561b17 map p23.1, completesequence./gene="Em:AF200455.14"/codon_start=1/product="defensin, alpha 1, myeloid-related sequence"/protein_id="AAT68884.1"/db_xref="GI:50057848"
0 1 0 1 3 2 0 4 2 2 0 1 1 1 0 0 1 0 0 2 0 0 5 0 1 0 6 6 2 5 3 1 0 0 0 0 2 3 1 1 1 0 0 5 0 1 3 3 2 1 1 2 6 0 1 0 1 3 3 2 2 0 0 1
>BC071876\BC071876\330..1262\933\AAH71876.1\Homo sapiens\Homo sapiens chromosome 19 open reading frame 27, mRNA (cDNA cloneMGC:88549 IMAGE:6672380), complete cds./gene="C19orf27"/codon_start=1/product="C19orf27 protein"/protein_id="AAH71876.1"/db_xref="GI:47939594"/db_xref="GeneID:81926"
0 14 0 2 1 4 0 10 19 0 0 1 0 9 8 1 10 1 0 9 5 0 0 11 7 5 1 22 3 1 0 14 9 3 0 4 12 1 0 8 5 2 0 8 7 0 0 18 13 0 14 2 10 1 12 0 0 15 1 4 3 0 1 0
>HSP2X4PC\Y07684\28..1194\1167\CAA68948.1\Homo sapiens\H.sapiens mRNA for P2X4 purinoceptor./codon_start=1/product="P2X4 purinoceptor"/protein_id="CAA68948.1"/db_xref="GI:1781009"/db_xref="GOA:Q99571"/db_xref="UniProt/Swiss-Prot:Q99571"
0 8 3 1 3 4 1 11 11 5 1 2 2 7 1 4 5 2 5 8 4 8 3 7 2 2 4 12 7 8 4 16 5 1 2 8 20 3 10 13 17 3 2 9 4 0 5 12 12 9 11 7 10 4 13 6 4 19 3 9 6 0 0 1
>BX664739#1\BX664739\complement(join(5483..5615,5756..5802,5924..6132, 6381..6486,6690..6737))\543\CAI43234.1\Homo sapiens\Human DNA sequence from clone WI2-89031B12 on chromosome X Containsthe FAM3A gene for family with sequence similarity, the SLC10A3 3gene for solute carrier family 10 (sodium/bile acid cotransporterfamily) member 3, the UBL4 gene for ubiquitin-like 4 and three CpGislands, complete sequence./gene="UBL4"/locus_tag="XX-FW89031B12.1-002"/standard_name="OTTHUMP00000015408"/codon_start=1/product="ubiquitin-like 4"/protein_id="CAI43234.1"/db_xref="GI:57284174"/db_xref="GOA:Q5HY81"/db_xref="UniProt/TrEMBL:Q5HY81"
2 4 2 2 2 5 5 3 17 0 0 2 0 6 1 1 5 2 0 2 3 1 3 3 2 2 3 5 2 1 1 6 2 0 1 6 7 1 3 7 3 0 0 14 4 4 4 8 4 4 1 1 2 0 3 0 0 3 0 1 4 0 0 1
>AL627311#1\AL627311 AC027632\join(complement(AL672037.5:31607..31619), complement(142067..142127),complement(119882..119957), complement(81610..81738),complement(33457..33552), complement(28345..28377),complement(11792..11971), complement(11078..11192),complement(3746..3843), complement(AL358392.19:76459..76581), complement(AL358392.19:56988..57096), complement(AL358392.19:48476..49315), complement(AL358392.19:48361..48380))\-67197\CAI14552.1\Homo sapiens\Human DNA sequence from clone RP11-487E1 on chromosome 1 Containspart of the EIF4G3 gene for eukaryotic translation initiationfactor 4 gamma, 3, a ribosomal protein S15a (RPS15A) pseudogene anda pseudogene similar to part of ribosomal protein L34 (RPL34),complete sequence./gene="EIF4G3"/locus_tag="RP11-190H11.1-002"/standard_name="OTTHUMP00000002723"/codon_start=1/product="eukaryotic translation initiation factor 4 gamma, 3"/protein_id="CAI14552.1"/db_xref="GI:55962100"/db_xref="GOA:Q5SVN3"/db_xref="UniProt/TrEMBL:Q5SVN3"
2 6 3 3 14 9 7 8 15 16 10 12 11 11 2 10 11 13 9 16 3 9 14 15 6 20 13 8 2 6 8 11 9 6 6 6 8 6 15 5 12 14 10 24 11 15 5 10 6 7 10 9 7 11 9 28 10 13 16 12 7 2 8 11
>BC001734\BC001734\77..367\291\AAH01734.1\Homo sapiens\Homo sapiens Sec61 beta subunit, mRNA (cDNA clone MGC:1255IMAGE:3502133), complete cds./gene="SEC61B"/codon_start=1/product="protein translocation complex beta"/protein_id="AAH01734.1"/db_xref="GI:12804623"/db_xref="GeneID:10952"
1 2 2 1 0 2 0 1 1 1 0 2 2 2 2 2 2 3 3 3 0 3 1 2 1 3 3 3 2 1 2 5 5 1 2 1 2 3 3 1 1 1 0 1 1 0 1 0 0 1 2 0 0 1 2 1 0 1 1 4 2 0 1 0
>AC004410\AC004410\join(278..413,523..643,1344..1460,3657..3738,4411..4485, 4808..4870,4999..5098,5699..5776,11880..12040, 13392..13655)\1197\AAC05601.1\Homo sapiens\Homo sapiens chromosome 19, fosmid 39554, complete sequence./codon_start=1/evidence=not_experimental/product="fos39554_1"/protein_id="AAC05601.1"/db_xref="GI:2959559"
0 5 6 4 0 3 1 15 32 1 0 1 3 12 3 3 9 2 2 8 9 1 8 16 9 7 4 25 5 5 2 12 7 2 3 6 27 1 3 9 4 0 0 14 3 0 3 13 12 3 10 2 12 2 17 3 0 10 1 11 7 0 1 0
>AC073283#1\AC073283\complement(join(73603..73672,73873..73937,94935..95192, 96634..96693,98848..98928))\534\AAY24084.1\Homo sapiens\Homo sapiens BAC clone RP11-761B3 from 2, complete sequence./gene="FLJ40172"/codon_start=1/product="unknown"/protein_id="AAY24084.1"/db_xref="GI:62988697"
0 1 1 0 4 3 3 0 3 5 3 1 5 4 1 2 3 1 5 4 0 5 9 3 2 6 3 3 0 4 3 1 1 1 2 2 5 3 8 4 3 4 5 4 1 0 7 0 6 3 4 3 0 1 4 5 5 1 2 3 2 0 1 0
>HUMTYROPHO\L18983\74..3013\2940\AAA90974.1\Homo sapiens\Homo sapiens tyrosine phosphatase (IA-2/PTP) mRNA, complete cds./gene="IA-2/PTP"/EC_number="3.1.3.48"/codon_start=1/transl_except=(pos:80..82,aa:Arg)/product="tyrosine phosphatase"/protein_id="AAA90974.1"/db_xref="GI:499630"
1 20 21 5 5 12 4 25 64 10 2 10 8 29 1 10 29 7 9 19 8 7 24 28 12 27 22 42 7 20 18 25 24 12 3 16 39 4 7 23 13 4 15 46 20 9 10 50 26 13 14 7 11 6 12 9 3 22 5 17 8 0 0 1
>HS934G17#9\AL021155\33197..33562\366\CAI23399.1\Homo sapiens\Human DNA sequence from clone RP5-934G17 on chromosome 1p36.21Contains the 3' end of the CLCN6 gene for chloride channel 6, twonovel genes, the NPPA gene for natriuretic peptide precursor A, theNPPB gene for natriuretic peptide precursor B, a pseudogene similarto part of SET binding factor 1 (SBF1) and the 3' end of a novelgene, complete sequence./locus_tag="RP5-934G17.3-001"/standard_name="OTTHUMP00000002487"/codon_start=1/product="novel protein"/protein_id="CAI23399.1"/db_xref="GI:56202429"/db_xref="UniProt/TrEMBL:Q5JZE0"
0 3 0 0 2 3 0 5 8 4 2 1 4 3 1 7 5 2 1 2 1 3 5 8 0 3 4 5 1 5 1 0 0 1 0 2 2 1 0 5 0 1 2 2 1 0 0 2 1 2 0 1 1 1 0 1 1 0 2 1 2 0 0 1
>BC007891\BC007891\17..1354\1338\AAH07891.1\Homo sapiens\Homo sapiens selenocysteine lyase, mRNA (cDNA clone MGC:14083IMAGE:4126478), complete cds./gene="SCLY"/codon_start=1/product="selenocysteine lyase"/protein_id="AAH07891.1"/db_xref="GI:14043901"/db_xref="GeneID:51540"
2 6 8 0 2 8 2 8 16 7 1 1 3 6 3 1 10 3 5 12 2 5 6 11 7 6 10 17 13 6 7 9 15 6 1 8 28 2 5 13 8 9 4 18 13 4 13 15 14 5 3 6 4 1 7 6 4 11 6 11 2 0 1 0
>AK094438\AK094438\97..2373\2277\BAC04356.1\Homo sapiens\Homo sapiens cDNA FLJ37119 fis, clone BRACE2022333./codon_start=1/protein_id="BAC04356.1"/db_xref="GI:21753501"
1 12 22 4 7 23 2 28 71 5 0 5 3 11 8 3 20 3 3 6 8 2 13 18 9 6 14 44 12 14 3 21 16 5 2 15 34 5 3 22 7 1 3 57 22 3 6 35 34 4 9 1 13 6 10 5 0 9 4 15 11 0 0 1
>AY366246\AY366246\8..727\720\AAR16204.1\Homo sapiens\Homo sapiens natural killer cell inhibitory receptor (KIR2DS4)mRNA, KIR2DS4*004 allele, complete cds./gene="KIR2DS4"/allele="KIR2DS4*004"/codon_start=1/product="natural killer cell inhibitory receptor"/protein_id="AAR16204.1"/db_xref="GI:38305400"
1 0 0 0 3 3 1 6 9 5 0 5 4 11 3 2 1 3 2 4 5 3 7 6 4 7 4 5 1 4 5 3 6 4 2 5 5 5 4 2 5 1 4 7 9 2 3 8 3 3 3 3 4 2 7 3 2 6 2 9 3 0 0 1
>AB060284\AB060284\6..1064\1059\BAB61052.1\Homo sapiens\Homo sapiens mRNA for WNT3A, complete cds./gene="WNT3A"/codon_start=1/product="WNT3A"/protein_id="BAB61052.1"/db_xref="GI:14530679"
1 18 8 0 0 2 0 6 13 0 1 0 4 4 8 1 13 0 2 7 5 0 4 8 3 1 2 20 2 4 1 20 5 4 0 7 13 1 1 14 10 0 1 10 13 0 1 21 13 1 10 1 21 4 11 3 0 12 2 6 9 0 1 0
>BC014534\BC014534\313..1002\690\AAH14534.1\Homo sapiens\Homo sapiens methyl-CpG binding domain protein 5, mRNA (cDNA cloneIMAGE:3996924), complete cds./gene="MBD5"/codon_start=1/product="MBD5 protein"/protein_id="AAH14534.1"/db_xref="GI:15778911"/db_xref="GeneID:55777"
1 0 1 0 5 2 3 3 2 3 7 6 5 3 1 9 6 14 4 2 2 4 6 4 1 9 7 3 0 4 2 1 5 7 0 1 3 5 5 2 10 7 7 12 5 3 4 0 2 3 1 1 2 3 1 3 3 1 3 10 0 1 0 0
>HUMPRPHOS1\M63960\30..1022\993\AAA36508.1\Homo sapiens\Human protein phosphatase-1 catalytic subunit mRNA, complete cds./EC_number="3.1.3.16"/codon_start=1/product="protein phosphatase-1"/protein_id="AAA36508.1"/db_xref="GI:190516"
3 5 6 2 1 1 1 8 25 3 0 2 1 5 2 4 4 2 3 5 0 1 1 10 1 5 2 10 1 2 3 15 5 4 2 1 10 0 5 17 12 3 0 13 6 0 3 18 21 2 8 5 10 3 12 7 2 15 3 6 3 0 1 0
>AL627230#6\AL627230\complement(join(96963..97088,97647..97724))\204\CAH70358.1\Homo sapiens\Human DNA sequence from clone RP11-12A20 on chromosome 9 Containssix novel pseudogenes, the FAM27B gene for family with sequencesimilarity 27, member B, a pseudogene similar to part of ribosomalprotein L10 (RPL10) and four CpG islands, complete sequence./gene="FAM27B"/locus_tag="RP11-12A20.3-001"/standard_name="OTTHUMP00000015366"/codon_start=1/product="family with sequence similarity 27, member B"/protein_id="CAH70358.1"/db_xref="GI:55666401"/db_xref="UniProt/TrEMBL:Q9BU53"
0 0 4 0 2 2 0 2 0 1 0 1 1 0 0 1 2 0 1 0 2 2 0 4 0 1 3 3 1 1 2 0 3 0 0 0 1 1 2 1 1 0 1 2 1 0 2 4 0 4 1 0 0 2 1 1 0 2 0 1 0 0 0 1
>AY757363\AY757363\15..1406\1392\AAV52330.1\Homo sapiens\Homo sapiens putative L-2-hydroxyglutarate dehydrogenase (L2HGDH)mRNA, complete cds./gene="L2HGDH"/EC_number="1.1.99.2"/function="catalyzes the FAD dependent conversion of L-2-hydroxyglutarate to alpha-ketoglutarate"/codon_start=1/product="putative L-2-hydroxyglutarate dehydrogenase"/protein_id="AAV52330.1"/db_xref="GI:55469290"
4 3 4 2 9 5 4 4 11 13 3 6 6 5 0 8 5 9 5 2 0 6 11 2 3 10 12 14 3 8 18 11 7 13 9 5 7 12 14 10 1 10 8 12 2 5 15 9 3 19 5 14 3 10 8 11 8 6 22 8 1 1 0 0
>CR456744\CR456744\1..1299\1299\CAG33025.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834B0611D forgene TRIP13, thyroid hormone receptor interactor 13; complete cds,incl. stopcodon./gene="TRIP13"/codon_start=1/protein_id="CAG33025.1"/db_xref="GI:48145605"
3 3 2 0 6 5 3 12 19 7 4 9 6 3 2 7 11 5 7 10 1 6 3 6 0 5 10 12 4 5 1 10 3 2 2 8 20 5 11 16 11 9 2 16 5 6 15 15 13 12 7 3 2 4 7 9 5 9 18 5 5 1 0 0
>AL391595#2\AL391595\join(20166..20361,41019..41096,42633..42701,81150..81283, 82347..82502,83283..83306)\657\CAI15050.1\Homo sapiens\Human DNA sequence from clone RP11-51I15 on chromosome 6 Containsthe 5' part of the BCKDHB gene for branched chain keto aciddehydrogenase E1, beta polypeptide (maple syrup urine disease) andone CpG island, complete sequence./gene="BCKDHB"/locus_tag="RP1-279A18.1-002"/standard_name="OTTHUMP00000018047"/codon_start=1/product="branched chain keto acid dehydrogenase E1, beta polypeptide (maple syrup urine disease)"/protein_id="CAI15050.1"/db_xref="GI:55959445"/db_xref="GOA:Q5T2J3"/db_xref="InterPro:IPR005475"/db_xref="UniProt/TrEMBL:Q5T2J3"
1 2 5 1 2 3 1 4 1 3 1 5 1 1 0 4 2 2 1 1 0 8 3 2 1 5 5 9 10 6 9 5 6 3 3 3 1 8 5 2 2 3 2 8 2 4 5 4 1 9 1 5 2 3 3 12 2 4 6 2 3 0 1 0
>HUMIFI16A\M63838\265..2454\2190\AAA58683.1\Homo sapiens\Human interferon-gamma induced protein (IFI 16) gene, complete cds./gene="IFI 16"/codon_start=1/product="interferon-gamma induced protein"/protein_id="AAA58683.1"/db_xref="GI:184569"
5 2 1 2 13 4 8 6 11 10 7 9 16 8 0 6 14 16 21 13 3 19 20 11 4 14 9 9 0 14 17 4 9 4 14 5 19 8 48 38 15 22 6 21 4 13 38 22 12 15 2 12 3 4 19 15 12 16 13 24 0 1 0 0
>AY048673\AY048673\101..478\378\AAL07514.1\Homo sapiens\Homo sapiens SSTK-interacting protein variant mRNA, complete cds,alternatively spliced./function="interacts with protein kinase SSTK deposited with GenBank Accession Number AF329483"/codon_start=1/product="SSTK-interacting protein variant"/protein_id="AAL07514.1"/db_xref="GI:15822788"
0 0 1 0 2 1 1 5 5 2 3 2 0 2 1 4 2 3 3 1 0 2 5 5 0 4 4 4 0 4 2 0 1 0 0 0 2 3 4 3 4 5 5 6 3 2 4 2 0 1 0 2 1 2 1 1 0 1 1 3 0 0 0 1
>AF000574\AF000574\1..1797\1797\AAB88119.1\Homo sapiens\Homo sapiens clone 1 immunoglobulin-like transcript 4 mRNA,complete cds./codon_start=1/product="immunoglobulin-like transcript 4"/protein_id="AAB88119.1"/db_xref="GI:2264427"
4 5 6 6 6 9 3 27 27 4 0 3 14 13 5 10 11 8 12 22 0 4 14 31 2 14 8 19 2 12 9 17 16 7 0 10 25 3 4 11 8 1 3 31 14 3 15 17 13 8 13 9 5 7 10 2 2 17 2 6 9 0 1 0
>AB040801\AB040801\1..1122\1122\BAA96647.1\Homo sapiens\Homo sapiens mRNA for SREB3, complete cds./gene="sreb3"/codon_start=1/product="SREB3"/protein_id="BAA96647.1"/db_xref="GI:8467970"
1 9 4 3 1 1 1 12 27 1 0 2 3 3 0 4 7 1 5 8 1 3 7 8 2 3 4 27 4 14 3 12 3 5 1 9 17 1 1 15 6 2 0 7 7 5 2 9 6 1 12 2 13 2 15 9 1 10 4 18 9 0 0 1
>BC002718\BC002718\58..447\390\AAH02718.1\Homo sapiens\Homo sapiens tumor necrosis factor receptor superfamily, member12A, mRNA (cDNA clone MGC:3386 IMAGE:3632233), complete cds./gene="TNFRSF12A"/codon_start=1/product="type I transmembrane protein Fn14"/protein_id="AAH02718.1"/db_xref="GI:12803761"/db_xref="GeneID:51330"/db_xref="MIM:605914"
2 4 4 0 2 2 0 3 13 3 0 3 0 3 1 2 4 0 0 5 0 0 2 4 1 2 2 3 6 4 1 8 4 0 0 1 4 0 0 2 0 0 1 1 1 0 0 5 4 0 0 0 8 0 4 1 1 2 0 2 4 0 0 1
>AB018001\AB018001\31..1143\1113\BAA88063.1\Homo sapiens\Homo sapiens mRNA for Death-associated protein kinase 2, completecds./gene="DAPK2"/codon_start=1/product="Death-associated protein kinase 2"/protein_id="BAA88063.1"/db_xref="GI:6521210"
0 5 12 0 1 10 1 8 20 5 2 1 2 4 1 2 12 6 4 6 6 1 6 3 3 1 4 9 1 5 6 2 4 3 0 5 16 3 4 22 9 5 2 12 11 0 8 29 14 6 4 4 2 1 11 9 2 16 9 7 3 1 0 0
>BC005024\BC005024\48..425\378\AAH05024.1\Homo sapiens\Homo sapiens mitochondria-associated protein involved ingranulocyte-macrophage colony-stimulating factor signaltransduction, mRNA (cDNA clone MGC:12559 IMAGE:3955475), completecds./gene="Magmas"/codon_start=1/product="mitochondria-associated granulocyte macrophage CSF signaling molecule"/protein_id="AAH05024.1"/db_xref="GI:13477135"/db_xref="GeneID:51025"
1 3 4 0 1 1 0 5 4 0 1 1 1 5 0 1 3 0 0 0 1 0 0 1 0 1 6 9 0 3 2 4 1 1 0 2 8 0 3 6 3 1 0 11 2 1 3 7 1 3 2 1 0 0 1 3 0 2 2 3 0 0 0 1
>HUMDIKI\D73409\81..3590\3510\BAA11134.1\Homo sapiens\Homo sapiens mRNA for diacylglycerol kinase delta, complete cds./EC_number="2.7.1.107"/function="phosphorylaton of diacylglycerol"/codon_start=1/product="diacylglycerol kinase delta"/protein_id="BAA11134.1"/db_xref="GI:1181079"
9 14 15 4 11 13 6 28 55 13 5 11 12 29 11 15 27 16 11 33 10 4 15 18 14 8 18 40 3 18 15 26 25 6 3 31 31 7 26 56 32 11 1 47 28 3 23 61 38 25 11 9 22 16 24 13 6 26 15 29 17 0 1 0
>BC070387\BC070387\50..997\948\AAH70387.1\Homo sapiens\Homo sapiens T cell receptor beta variable 3-1, mRNA (cDNA cloneMGC:88400 IMAGE:30325415), complete cds./gene="TRBV3-1"/codon_start=1/product="TRBV3-1 protein"/protein_id="AAH70387.1"/db_xref="GI:47125017"/db_xref="GeneID:28619"/db_xref="IMGT/GENE-DB:TRBV3-1"
0 4 1 0 4 3 2 11 13 2 2 2 2 9 2 5 8 3 8 8 0 2 6 7 2 1 4 13 0 4 2 5 7 3 1 11 10 2 8 10 4 11 5 11 6 1 3 15 11 3 7 5 5 5 11 3 2 6 2 6 6 0 1 0
>BC090038\BC090038\124..1098\975\AAH90038.1\Homo sapiens\Homo sapiens nuclease sensitive element binding protein 1, mRNA(cDNA clone MGC:110976 IMAGE:6526492), complete cds./gene="NSEP1"/codon_start=1/product="nuclease sensitive element binding protein 1"/protein_id="AAH90038.1"/db_xref="GI:58477789"/db_xref="GeneID:4904"/db_xref="MIM:154030"
4 11 4 5 7 8 0 2 0 1 0 1 0 2 3 0 5 5 4 4 2 3 12 10 2 11 8 12 3 6 10 13 5 11 5 1 4 6 6 10 9 12 10 14 1 1 11 16 6 7 8 8 0 0 5 2 1 2 0 4 1 1 0 0
>AY279531\AY279531\1..852\852\AAP34399.1\Homo sapiens\Homo sapiens small CTD phosphatase 2 mRNA, complete cds./codon_start=1/product="small CTD phosphatase 2"/protein_id="AAP34399.1"/db_xref="GI:31074179"
1 4 4 3 2 4 1 11 14 3 1 1 1 9 2 3 5 1 2 8 0 4 5 2 0 8 5 8 3 6 3 5 6 0 0 4 13 2 0 13 5 2 2 11 4 2 7 13 12 5 5 4 5 5 10 5 3 9 3 3 1 0 1 0
>AL589862#3\AL589862\join(127383..127425,130868..131036,131816..132013, 160620..160705,162368..162487,AL138762.20:2451..2626, AL138762.20:5131..5257,AL138762.20:20669..20770, AL138762.20:23030..23116,AL138762.20:23564..23640)\-693189\CAI17856.1\Homo sapiens\Human DNA sequence from clone GS1-165F21 on chromosome 10 Containsthe 5' end of the PAX2 gene for paired box gene 2 and fifteen CpGislands, complete sequence./gene="PAX2"/locus_tag="RP11-179B2.1-001"/standard_name="OTTHUMP00000020286"/codon_start=1/product="paired box gene 2"/protein_id="CAI17856.1"/db_xref="GI:55960623"/db_xref="GOA:Q5W0L6"/db_xref="InterPro:IPR001523"/db_xref="UniProt/TrEMBL:Q5W0L6"
2 4 8 2 6 11 2 5 10 2 1 7 1 14 2 5 8 0 3 6 3 1 6 15 5 12 6 10 5 5 11 10 17 7 2 8 19 5 9 10 5 7 4 12 8 0 6 15 10 6 5 0 2 3 7 6 0 12 6 9 4 1 0 2
>AB015718\AB015718\51..2957\2907\BAA35073.1\Homo sapiens\Homo sapiens lok mRNA for protein kinase, complete cds./gene="lok"/codon_start=1/product="protein kinase"/protein_id="BAA35073.1"/db_xref="GI:4001688"
7 18 24 4 6 11 3 25 63 5 1 2 3 15 3 11 25 9 1 23 10 3 10 21 5 8 6 39 6 13 4 15 8 6 4 6 28 3 18 73 26 9 10 63 15 8 21 95 38 13 13 3 8 4 17 7 3 26 6 31 7 1 0 0
>BC030267\BC030267\178..3654\3477\AAH30267.1\Homo sapiens\Homo sapiens ATPase type 13A2, mRNA (cDNA clone MGC:40082IMAGE:5240813), complete cds./gene="ATP13A2"/codon_start=1/product="ATP13A2 protein"/protein_id="AAH30267.1"/db_xref="GI:20988435"/db_xref="GeneID:23400"
5 18 23 4 8 11 6 37 90 4 1 8 9 22 4 8 37 5 17 25 12 14 24 45 16 19 23 48 14 18 9 34 29 6 3 33 69 6 4 24 17 4 8 47 18 4 7 44 31 6 26 8 17 9 29 3 4 33 6 28 17 0 1 0
>AF241254\AF241254\104..2521\2418\AAF78220.1\Homo sapiens\Homo sapiens angiotensin converting enzyme-like protein mRNA,complete cds./codon_start=1/product="angiotensin converting enzyme-like protein"/protein_id="AAF78220.1"/db_xref="GI:8650466"
4 1 3 2 10 11 7 9 21 19 10 10 11 11 0 14 11 7 17 9 2 11 15 9 0 13 21 11 0 19 19 6 13 5 7 8 17 18 27 20 16 38 15 23 2 14 38 18 23 20 12 21 4 4 17 22 9 15 16 27 23 0 1 0
>HSGCSAB\X66533\89..1948\1860\CAA47144.1\Homo sapiens\H.sapiens soluble guanylate cyclase small subunit mRNA./EC_number="4.6.1.2"/codon_start=1/product="guanylate cyclase"/protein_id="CAA47144.1"/db_xref="GI:31686"/db_xref="GOA:Q02153"/db_xref="InterPro:IPR001054"/db_xref="UniProt/Swiss-Prot:Q02153"
3 3 4 5 15 3 6 15 16 13 7 12 5 6 1 10 8 5 17 6 2 13 11 2 1 9 8 7 0 9 16 10 7 7 3 13 13 13 18 15 6 17 12 14 11 8 37 16 17 23 11 11 7 7 7 21 12 18 10 15 2 0 0 1
>BC014594\BC014594\96..449\354\AAH14594.1\Homo sapiens\Homo sapiens GABA(A) receptor-associated protein-like 2, mRNA (cDNAclone MGC:26328 IMAGE:4821535), complete cds./gene="GABARAPL2"/codon_start=1/product="GABA(A) receptor-associated protein-like 2"/protein_id="AAH14594.1"/db_xref="GI:15779041"/db_xref="GeneID:11345"/db_xref="MIM:607452"
1 0 1 0 1 3 1 0 2 2 1 1 1 2 1 3 2 0 1 0 0 3 2 1 1 1 0 1 3 1 3 2 0 0 0 2 6 3 4 8 1 0 0 5 2 0 5 4 4 4 3 2 1 0 5 2 0 5 4 4 2 0 0 1
>HUMSSR2\D37991\25..576\552\BAA07206.1\Homo sapiens\Human SSR2 mRNA for beta-signal sequence receptor, complete cds./gene="SSR2"/codon_start=1/product="beta-signal sequence receptor"/protein_id="BAA07206.1"/db_xref="GI:1736880"
2 1 2 0 1 4 3 2 10 2 1 4 3 6 1 3 2 2 1 4 1 4 1 4 0 5 5 5 0 7 6 4 2 1 0 5 7 2 4 4 4 3 1 4 1 1 3 4 7 3 5 2 0 0 4 6 0 4 4 3 3 0 0 1
>AF214737\AF214737\26..3235\3210\AAF72866.1\Homo sapiens\Homo sapiens C9orf10a (C9orf10) mRNA, complete cds, alternativelyspliced./gene="C9orf10"/codon_start=1/product="C9orf10a"/protein_id="AAF72866.1"/db_xref="GI:8118021"
4 9 15 7 16 13 8 26 40 7 4 7 13 13 7 18 28 7 8 13 8 8 26 22 22 28 22 39 11 21 27 42 20 11 6 20 24 14 16 37 27 6 8 44 22 14 26 26 24 17 21 14 15 4 25 15 3 16 20 22 13 0 0 1
>BC014521\BC014521\58..726\669\AAH14521.1\Homo sapiens\Homo sapiens PDZ and LIM domain 7 (enigma), transcript variant 4,mRNA (cDNA clone IMAGE:3690154), complete cds./gene="PDLIM7"/codon_start=1/product="enigma protein, isoform 4"/protein_id="AAH14521.1"/db_xref="GI:15778884"/db_xref="GeneID:9260"/db_xref="MIM:605903"
1 5 9 1 0 2 0 10 9 1 0 0 1 6 2 1 9 0 4 3 1 1 3 6 10 3 2 12 5 2 2 7 6 2 1 3 7 1 4 7 4 3 2 13 6 0 2 9 7 4 2 1 1 0 5 2 0 4 1 3 4 0 1 0
>BC030227\BC030227\66..1145\1080\AAH30227.1\Homo sapiens\Homo sapiens CD72 antigen, mRNA (cDNA clone MGC:34615IMAGE:5226648), complete cds./gene="CD72"/codon_start=1/product="CD72 antigen"/protein_id="AAH30227.1"/db_xref="GI:20987445"/db_xref="GeneID:971"/db_xref="MIM:107272"
1 4 2 0 5 9 4 9 20 2 3 5 13 4 2 7 10 5 6 7 4 9 6 6 1 0 7 7 4 8 5 3 8 2 2 4 8 2 6 13 6 5 8 25 1 3 7 14 4 9 6 5 8 5 5 3 2 6 2 4 8 0 1 0
>AY449689\AY449689\1..2493\2493\AAS19705.1\Homo sapiens\Homo sapiens prominin 1 isoform s3 (PROM1) mRNA, complete cds./gene="PROM1"/codon_start=1/product="prominin 1 isoform s3"/protein_id="AAS19705.1"/db_xref="GI:42556032"
6 2 4 4 12 8 11 13 36 16 8 26 11 13 2 9 19 15 12 15 2 21 5 8 3 13 19 4 4 13 16 15 10 8 10 13 17 13 25 18 20 29 14 20 6 7 26 13 16 24 16 20 11 12 14 23 14 23 24 11 8 0 0 1
>AL157392#1\AL157392\join(13445..13510,23816..23893,26602..26706,31989..32102, 36397..36543,37973..38041,40099..40239,40373..40444, 42756..42911,56618..56698)\1029\CAI13123.1\Homo sapiens\Human DNA sequence from clone RP11-295P9 on chromosome 10 Containsthe PRPF18 gene for PRP18 pre-mRNA processing factor 18 homolog(yeast), a ribosomal protein L6 (RPL6)(TAXREB107) pseudogene, twonovel genes, the 5' end of a novel gene, the 3' end of the gene fora novel protein (FLJ10210) and two CpG islands, complete sequence./gene="PRPF18"/locus_tag="RP11-295P9.7-001"/standard_name="OTTHUMP00000019146"/codon_start=1/product="PRP18 pre-mRNA processing factor 18 homolog (yeast)(PRPF18)"/protein_id="CAI13123.1"/db_xref="GI:55957682"/db_xref="InterPro:IPR003648"/db_xref="InterPro:IPR004098"
0 1 4 2 12 6 3 3 9 9 8 7 3 4 1 1 0 3 4 5 2 5 7 1 0 5 6 5 3 4 7 5 1 4 0 3 7 6 24 11 4 11 2 15 1 5 20 18 8 12 5 6 1 2 3 7 3 9 10 7 2 0 0 1
>HUMSRTR2A\M21985\127..1578\1452\AAA36650.1\Homo sapiens\Human steroid receptor TR2 mRNA, complete cds./codon_start=1/protein_id="AAA36650.1"/db_xref="GI:338486"
6 1 0 2 5 5 3 4 10 14 11 3 17 3 1 12 10 6 15 7 0 16 8 1 1 6 17 8 3 6 17 4 4 3 12 4 6 5 16 8 5 19 16 13 8 6 18 7 6 19 5 3 5 11 7 11 4 6 17 14 3 1 0 0
>AL359706#3\AL359706\join(38993..39022,39371..39535,44269..44367,51724..51942)\513\CAI12868.1\Homo sapiens\Human DNA sequence from clone RP11-245H20 on chromosome 13 Containsthe 5' end of the NUFIP1 gene for nuclear fragile X mentalretardation protein interacting protein 1, the gene forlipopolysaccharide specific response-7 protein (LSR7) and a CpGisland, complete sequence./gene="RP11-245H20.2"/locus_tag="RP11-245H20.2-001"/standard_name="OTTHUMP00000018339"/codon_start=1/protein_id="CAI12868.1"/db_xref="GI:55959531"/db_xref="UniProt/TrEMBL:Q5T3Z3"
1 0 1 1 9 4 2 1 2 3 3 0 9 1 0 5 0 2 3 2 0 3 4 1 0 2 1 1 0 7 3 2 1 1 2 0 0 1 16 10 1 4 2 2 1 3 13 3 5 12 1 0 0 0 0 6 4 1 1 5 2 1 0 0
>AL137140#2\AL137140\join(97009..97051,97729..97846,100937..100996, 104964..105032,108813..108881,109428..109466, 110504..110584,113257..113322,130277..130357, 132528..132593,138678..138722,140462..140521, 140822..140881,143198..143257,143787..143846, 144209..144268,145489..145548,149189..149248, 150191..150250,151180..151239,154024..154074, 155026..155088,158732..158791,158936..158995, 159137..159193,169080..169142,175512..175583, 178253..178327,181809..181917,183839..183941, 185391..185407)\2007\CAH70475.1\Homo sapiens\Human DNA sequence from clone RP11-137M6 on chromosome13q21.33-22.3 Contains the SCEL gene for sciellin, a novel gene anda CpG island, complete sequence./gene="SCEL"/locus_tag="RP11-137M6.1-001"/standard_name="OTTHUMP00000018525"/codon_start=1/protein_id="CAH70475.1"/db_xref="GI:55661725"/db_xref="GOA:Q5W0S9"/db_xref="InterPro:IPR001781"/db_xref="UniProt/TrEMBL:Q5W0S9"
3 1 4 0 24 13 2 10 3 14 4 12 7 8 1 16 13 16 14 12 2 21 12 7 2 18 7 6 1 10 15 4 3 10 11 3 15 7 43 18 25 41 18 16 3 7 35 7 13 28 7 8 7 2 4 4 8 12 16 11 4 1 0 0
>AF168611\AF168611\1..1101\1101\AAD50823.1\Homo sapiens\Homo sapiens HLA-C class I antigen (HLA-C) mRNA, HLA-Cw*05DZallele, complete cds./gene="HLA-C"/allele="HLA-Cw*05DZ"/codon_start=1/product="HLA-C class I antigen"/protein_id="AAD50823.1"/db_xref="GI:5758662"
2 10 7 1 5 6 2 8 19 1 0 0 1 6 1 7 5 2 3 15 4 2 5 9 3 2 4 14 10 10 8 11 10 1 0 5 16 2 3 10 5 1 1 21 5 3 1 24 15 4 11 4 6 2 7 0 0 10 0 6 10 0 0 1
>BC019008\BC019008\57..1451\1395\AAH19008.1\Homo sapiens\Homo sapiens Williams-Beuren syndrome chromosome region 16,transcript variant 1, mRNA (cDNA clone MGC:20807 IMAGE:4330507),complete cds./gene="WBSCR16"/codon_start=1/product="RCC1-like G exchanging factor-like, isoform 1"/protein_id="AAH19008.1"/db_xref="GI:17512067"/db_xref="GeneID:81554"
6 12 7 0 3 6 1 3 25 4 2 4 4 9 3 7 8 4 4 5 7 4 4 11 2 6 5 13 8 9 20 14 17 10 1 14 28 5 7 7 9 4 4 14 9 2 11 12 10 9 6 7 7 6 11 7 0 8 4 7 8 1 0 0
>AK056091\AK056091\477..1367\891\BAB71092.1\Homo sapiens\Homo sapiens cDNA FLJ31529 fis, clone NT2RI2000421, moderatelysimilar to ZINC FINGER PROTEIN 75./codon_start=1/protein_id="BAB71092.1"/db_xref="GI:16551403"
0 0 2 1 10 3 2 5 2 8 5 2 6 4 0 5 5 4 9 3 0 6 4 5 1 4 5 3 0 0 5 2 4 1 3 2 5 3 26 12 4 6 10 10 13 5 11 9 3 9 1 5 1 11 5 7 4 2 3 4 6 0 0 1
>AK000805\AK000805\145..1398\1254\BAA91382.1\Homo sapiens\Homo sapiens cDNA FLJ20798 fis, clone ADSU02031./codon_start=1/protein_id="BAA91382.1"/db_xref="GI:7021111"
1 5 8 3 2 7 2 17 20 4 2 6 7 25 0 9 27 9 1 9 1 7 16 26 2 8 7 21 1 11 6 9 7 6 1 7 7 2 2 5 3 4 4 11 3 3 2 17 12 6 1 2 6 3 4 4 1 5 0 4 6 0 0 1
>BC040279\BC040279\18..1541\1524\AAH40279.1\Homo sapiens\Homo sapiens lactate dehydrogenase D, transcript variant 1, mRNA(cDNA clone MGC:34649 IMAGE:5162826), complete cds./gene="LDHD"/codon_start=1/product="D-lactate dehydrogenase, isoform 1 precursor"/protein_id="AAH40279.1"/db_xref="GI:54611260"/db_xref="GeneID:197257"/db_xref="MIM:607490"
4 9 12 1 0 8 1 15 33 2 1 0 2 9 2 4 6 2 7 11 9 2 6 10 1 7 10 27 8 8 7 30 9 4 3 12 33 1 2 11 12 4 2 19 11 6 5 29 13 7 7 1 10 5 14 2 1 10 2 9 9 0 0 1
>HUMGAB3R#1\L04311\join(96..175,1044..1135,1347..1414)\240\AAA52507.1\Homo sapiens\Human GABA-A receptor beta-3 subunit (GABRB3) gene, 5' end./gene="GABRB3"/codon_start=1/product="GABA-alpha receptor beta-3 subunit"/protein_id="AAA52507.1"/db_xref="GI:292040"/db_xref="GDB:G00-127-549"
1 2 0 0 1 0 1 3 5 0 0 1 0 4 0 1 1 1 0 2 1 0 0 5 1 0 0 1 0 0 0 2 5 1 0 2 4 1 1 2 4 0 0 0 0 0 1 3 5 1 1 0 2 0 1 1 0 4 1 5 2 0 0 0
>AF106685\AF106685\81..1724\1644\AAD43038.1\Homo sapiens\Homo sapiens myelin gene expression factor 2 mRNA, complete cds./codon_start=1/product="myelin gene expression factor 2"/protein_id="AAD43038.1"/db_xref="GI:5410336"
5 2 1 7 17 3 4 2 4 6 8 6 8 7 2 8 11 12 8 0 0 8 12 0 1 10 9 5 3 7 44 14 6 27 4 3 8 12 27 13 8 19 5 8 0 6 20 14 9 21 3 4 1 3 7 19 12 4 15 32 3 1 0 0
>AB065730\AB065730\join(201..344,1572..1717,3449..3582,3901..4104,4714..4885, 5312..5476,6698..6805,7669..7849,8533..8697)\1419\BAC05951.1\Homo sapiens\Homo sapiens gene for seven transmembrane helix receptor, completecds, isolate:CBRC7TM_293./codon_start=1/evidence=not_experimental/product="seven transmembrane helix receptor"/protein_id="BAC05951.1"/db_xref="GI:21928729"
1 8 8 3 3 5 0 21 29 5 0 2 1 18 3 3 18 5 9 16 6 2 10 17 3 10 5 27 4 8 4 11 11 3 2 9 13 5 0 8 6 2 3 11 9 1 0 10 6 1 13 7 11 1 18 5 1 23 4 12 12 0 0 1
>BC001861\BC001861\309..1112\804\AAH01861.2\Homo sapiens\Homo sapiens testis expressed sequence 101, mRNA (cDNA cloneMGC:4766 IMAGE:3538494), complete cds./gene="TEX101"/codon_start=1/product="testis expressed sequence 101"/protein_id="AAH01861.2"/db_xref="GI:33876506"/db_xref="GeneID:83639"
2 0 0 1 0 2 4 4 13 4 2 4 3 8 2 6 2 3 7 12 1 8 6 5 1 5 4 8 2 3 6 6 7 3 1 3 7 1 5 3 2 4 3 9 2 3 8 12 3 2 2 2 5 10 3 5 3 7 7 8 3 1 0 0
>AK058093\AK058093\170..640\471\BAB71662.1\Homo sapiens\Homo sapiens cDNA FLJ25364 fis, clone TST01761, highly similar toLEUKOCYTE ANTIGEN CD37./codon_start=1/protein_id="BAB71662.1"/db_xref="GI:16554123"
0 1 1 0 1 2 0 13 11 0 0 1 2 3 0 0 4 0 4 5 0 2 0 0 2 1 0 8 0 0 3 5 3 1 0 2 4 1 6 5 1 0 2 6 1 1 4 6 4 0 1 2 3 1 11 3 1 12 0 3 3 0 1 0
>BC036067\BC036067\84..512\429\AAH36067.1\Homo sapiens\Homo sapiens chromosome 1 open reading frame 115, mRNA (cDNA cloneMGC:33695 IMAGE:5274863), complete cds./gene="C1orf115"/codon_start=1/product="hypothetical protein LOC79762"/protein_id="AAH36067.1"/db_xref="GI:23271283"/db_xref="GeneID:79762"
4 5 4 0 0 5 0 3 7 0 0 0 0 2 0 0 7 0 0 3 2 0 1 3 4 0 1 8 11 1 2 5 7 0 2 3 5 0 1 7 0 1 1 1 2 0 0 15 3 0 6 0 1 0 3 1 0 4 0 1 0 1 0 0
>HUMSNAP25A\L19760\89..709\621\AAC37545.1\Homo sapiens\Human nerve-terminal protein (isoform SNAP25A) mRNA, complete cds./gene="SNAP"/codon_start=1/product="nerve terminal protein"/protein_id="AAC37545.1"/db_xref="GI:307426"
2 3 1 6 1 4 1 2 6 2 2 3 1 1 1 0 3 4 3 2 0 1 0 0 0 2 2 7 0 7 3 7 2 2 2 1 4 2 8 4 7 8 5 8 1 1 11 12 6 13 1 0 1 3 2 0 1 9 1 13 1 1 0 0
>AF154001\AF154001\872..1729\858\AAD38185.1\Homo sapiens\Homo sapiens MRP3s1 protein (MRP3s1) mRNA, splice variant, completecds./gene="MRP3s1"/codon_start=1/product="MRP3s1 protein"/protein_id="AAD38185.1"/db_xref="GI:5031476"
2 10 3 1 3 3 1 7 21 3 1 2 3 4 1 5 5 1 3 8 1 4 2 5 3 1 5 7 2 8 2 12 6 3 2 4 14 1 1 6 5 3 0 8 4 2 5 15 13 5 5 1 4 0 6 3 1 15 3 7 4 1 0 0
>BT007073\BT007073\1..717\717\AAP35736.1\Homo sapiens\Homo sapiens CD63 antigen (melanoma 1 antigen) mRNA, complete cds./codon_start=1/product="CD63 antigen (melanoma 1 antigen)"/protein_id="AAP35736.1"/db_xref="GI:30582985"
1 0 1 0 2 2 0 4 10 4 0 4 1 2 2 2 0 3 1 2 1 2 1 1 1 2 7 9 2 8 5 7 6 2 1 8 18 2 4 9 8 5 0 6 1 1 1 10 2 3 4 2 9 6 5 9 1 10 7 9 2 0 1 0
>AK027627\AK027627\167..1525\1359\BAB55244.1\Homo sapiens\Homo sapiens cDNA FLJ14721 fis, clone NT2RP3001608./codon_start=1/protein_id="BAB55244.1"/db_xref="GI:14042435"
0 5 8 2 1 1 2 8 31 1 0 3 3 10 3 0 24 4 3 9 5 3 12 29 14 8 10 38 8 8 1 22 10 3 1 5 18 1 3 16 10 1 2 19 8 3 1 13 7 2 16 4 8 2 3 1 0 9 3 5 2 1 0 0
>HSM806474\BX538239\99..644\546\CAD98077.1\Homo sapiens\Homo sapiens mRNA; cDNA DKFZp686P0948 (from clone DKFZp686P0948);complete cds./gene="DKFZp686P0948"/codon_start=1/product="hypothetical protein"/protein_id="CAD98077.1"/db_xref="GI:31874712"
0 0 0 1 3 1 2 1 0 1 3 2 6 6 0 11 3 4 2 0 0 6 5 1 1 4 2 2 0 6 3 3 0 3 2 3 0 4 9 2 3 2 5 5 1 5 19 5 6 11 0 3 1 3 2 1 1 2 1 3 0 0 0 1
>AB090811\AB090811\336..1964\1629\BAC55936.1\Homo sapiens\Homo sapiens ChGn-2 mRNA for chondroitin beta1,4N-acetylgalactosaminyltransferase-2, complete cds./gene="ChGn-2"/codon_start=1/product="chondroitin beta1,4 N-acetylgalactosaminyltransferase-2"/protein_id="BAC55936.1"/db_xref="GI:27923015"
5 6 4 2 8 5 5 10 12 13 6 10 5 2 0 8 3 10 3 10 2 7 5 5 1 11 6 10 1 8 12 7 4 14 5 7 14 12 19 13 5 17 13 13 7 11 36 20 9 16 7 15 3 5 10 20 4 5 16 15 5 0 0 1
>AF252611\AF252611\302..1033\732\AAK37429.1\Homo sapiens\Homo sapiens WBS15 protein (WBSCR5) mRNA, complete cds./gene="WBSCR5"/codon_start=1/product="WBS15 protein"/protein_id="AAK37429.1"/db_xref="GI:13649483"
0 3 2 1 4 4 0 5 13 0 0 3 4 8 3 4 7 2 4 2 1 3 5 8 3 1 9 9 2 0 4 4 10 4 0 2 7 0 3 7 3 3 3 11 1 1 9 14 7 7 8 2 3 2 3 1 2 2 2 4 4 0 1 0
>HSU44103\U44103\1..606\606\AAC51200.1\Homo sapiens\Homo sapiens small GTP binding protein Rab9 mRNA, complete cds./codon_start=1/product="small GTP binding protein Rab9"/protein_id="AAC51200.1"/db_xref="GI:1174147"
4 0 1 0 3 3 0 2 3 6 2 2 5 0 0 4 5 4 7 3 1 2 1 1 0 4 6 3 1 2 4 1 1 5 2 2 6 4 6 6 5 4 2 6 1 3 8 5 6 10 1 5 4 1 4 10 3 0 5 3 3 0 0 1
>HS88J8#1\AL035402\complement(12652..13614)\963\CAB42853.1\Homo sapiens\Human DNA sequence from clone RP1-88J8 on chromosome 6p21.31-21.33Contains the OR2W1 gene for olfactory receptor 2W1, olfactoryreceptor 2P1 pseudogene OR2P1P and a GTP binding proteinpseudogene. Contains ESTs, an STS and GSS, complete sequence./locus_tag="RP1-88J8.2-001"/standard_name="OTTHUMP00000017732"/codon_start=1/product="olfactory receptor, family 2, subfamily W, member 1"/protein_id="CAB42853.1"/db_xref="GI:4826521"/db_xref="Genew:8281"/db_xref="GOA:Q9Y3N9"/db_xref="InterPro:IPR000276"/db_xref="InterPro:IPR000725"/db_xref="UniProt/Swiss-Prot:Q9Y3N9"
1 0 0 1 4 2 4 11 12 7 6 8 4 4 0 9 4 4 11 7 1 4 6 2 1 3 3 5 0 7 5 5 0 4 5 6 4 6 8 11 8 7 3 4 2 7 1 3 4 6 8 7 2 9 9 6 5 13 12 16 3 0 1 0
>BC010935\BC010935\90..638\549\AAH10935.1\Homo sapiens\Homo sapiens casein kappa, mRNA (cDNA clone MGC:13553IMAGE:4279903), complete cds./gene="CSN3"/codon_start=1/product="casein kappa"/protein_id="AAH10935.1"/db_xref="GI:15012070"/db_xref="GeneID:1448"/db_xref="MIM:601695"
0 2 1 2 2 1 1 0 4 1 1 2 2 1 0 0 3 2 5 6 3 5 18 2 0 9 6 4 0 7 1 0 0 0 3 3 5 6 5 1 3 8 5 4 1 3 4 4 1 2 2 9 1 1 1 4 2 6 5 2 0 1 0 0
>BC014017\BC014017\9..1220\1212\AAH14017.1\Homo sapiens\Homo sapiens ribosomal protein L3, mRNA (cDNA clone MGC:20304IMAGE:4128023), complete cds./gene="RPL3"/codon_start=1/product="ribosomal protein L3"/protein_id="AAH14017.1"/db_xref="GI:15559314"/db_xref="GeneID:6122"/db_xref="MIM:604163"
3 10 6 5 2 4 1 5 15 4 0 1 0 7 0 4 6 2 2 15 1 5 3 3 2 7 4 9 0 8 6 18 7 2 3 9 22 1 8 48 6 3 2 12 10 6 6 15 13 5 7 4 3 2 11 6 0 10 9 10 5 1 0 0
>BC025719\BC025719\30..1202\1173\AAH25719.1\Homo sapiens\Homo sapiens matrix metalloproteinase 23B, mRNA (cDNA cloneMGC:34412 IMAGE:5228894), complete cds./gene="MMP23B"/codon_start=1/product="matrix metalloproteinase 23B"/protein_id="AAH25719.1"/db_xref="GI:19343598"/db_xref="GeneID:8510"/db_xref="MIM:603321"
1 16 13 2 1 8 1 13 30 1 0 1 1 7 2 0 10 0 0 11 8 1 3 19 9 0 2 21 14 3 3 21 6 0 0 10 16 0 4 6 6 1 1 7 16 0 1 14 14 0 13 0 11 0 17 0 1 7 0 5 12 0 0 1
>AC011298#2\AC011298\93404..93637\234\AAX93238.1\Homo sapiens\Homo sapiens BAC clone RP11-118M12 from 2, complete sequence./gene="tmp_locus_27"/codon_start=1/product="unknown"/protein_id="AAX93238.1"/db_xref="GI:62702314"
0 0 0 2 0 2 1 0 7 0 1 0 1 2 0 0 3 0 1 2 1 1 1 5 2 3 1 0 1 3 2 4 2 2 0 5 1 1 0 0 0 0 0 2 3 0 0 0 3 1 1 0 2 3 2 0 0 0 0 1 2 0 1 0
>AF289203S1#3\AF289203\32875..33747\873\AAG42366.1\Homo sapiens\Homo sapiens odorant receptor HOR3'beta1, odorant receptorHOR3'beta2, and odorant receptor HOR3'beta3 genes, complete cds./codon_start=1/product="odorant receptor HOR3'beta3"/protein_id="AAG42366.1"/db_xref="GI:11991865"
1 6 2 1 0 3 2 10 15 9 3 4 3 5 1 8 5 3 8 5 1 3 3 7 2 4 3 8 0 5 5 3 2 6 2 7 10 4 3 1 4 4 1 3 8 2 3 2 4 2 6 5 4 4 9 12 5 12 12 13 2 1 0 0
>AF262240\AF262240\20..739\720\AAF87716.1\Homo sapiens\Homo sapiens Smac mRNA, complete cds; nuclear gene formitochondrial product./function="binds IAPs and neutralizes their inhibition on caspase activation and activity"/codon_start=1/product="Smac"/protein_id="AAF87716.1"/db_xref="GI:9454219"
1 1 3 2 4 3 0 3 8 4 2 6 6 2 2 5 2 4 4 8 1 9 1 0 0 3 11 4 3 7 2 2 2 1 3 0 8 5 7 6 1 2 3 12 4 1 13 15 0 4 4 5 0 4 3 3 4 1 5 6 4 0 0 1
>AF386492\AF386492\join(2804..3074,4831..5064,6291..6485,8115..8313, 9912..10012,10133..10219,11418..11501,11821..11858)\1209\AAK60338.1\Homo sapiens\Homo sapiens serine-cysteine proteinase inhibitor clade E member 1(SERPINE1) gene, complete cds./gene="SERPINE1"/codon_start=1/product="serine-cysteine proteinase inhibitor clade E member 1"/protein_id="AAK60338.1"/db_xref="GI:14326588"
0 5 5 0 4 4 2 14 20 4 0 2 7 6 1 4 7 3 9 10 4 4 3 16 0 3 1 18 4 6 6 9 6 2 0 12 21 2 6 13 11 2 4 18 10 3 6 13 16 4 6 3 1 0 20 5 1 10 4 18 4 0 0 1
>AK055353\AK055353\530..2140\1611\BAB70908.1\Homo sapiens\Homo sapiens cDNA FLJ30791 fis, clone FEBRA2000972, moderatelysimilar to ZINC FINGER PROTEIN 184./codon_start=1/protein_id="BAB70908.1"/db_xref="GI:16550064"
3 0 0 1 18 6 3 0 7 19 3 7 8 8 1 3 10 8 6 3 1 14 6 12 0 4 8 8 1 10 16 3 6 1 5 5 5 9 31 18 5 10 18 22 8 26 33 22 4 5 9 13 3 28 9 12 8 4 10 5 5 0 1 0
>AB001895\AB001895\288..3716\3429\BAA23269.1\Homo sapiens\Homo sapiens mRNA for B120, complete cds./codon_start=1/product="B120"/protein_id="BAA23269.1"/db_xref="GI:2588991"
6 6 10 5 3 12 3 11 9 4 3 7 18 43 8 24 25 20 16 19 4 17 53 45 12 57 14 34 5 23 30 49 34 16 2 4 12 5 9 22 30 24 33 122 8 8 10 15 15 17 21 37 1 1 8 6 5 12 6 60 4 0 0 1
>S82745\S82745\1..330\330\AAD14415.1\Homo sapiens\Ig VH=IgM monoclonal antibody heavy chain variable region {VH-D-JHjunctions, clone B4E7} [human, hybrid cells, splenic lymphocytesfused to lymphoblastoid B cell line GM4672, Genomic, 330 nt]./gene="Ig VH"/codon_start=1/protein_id="AAD14415.1"/db_xref="GI:4262115"
1 1 1 2 2 0 0 1 5 0 0 0 1 5 0 1 2 3 0 4 3 0 1 0 1 0 4 2 1 3 3 2 4 1 0 4 3 0 2 3 2 2 2 1 1 0 0 2 4 2 7 5 0 2 3 1 2 1 1 3 3 0 0 0
>BC010674\BC010674\428..3208\2781\AAH10674.1\Homo sapiens\Homo sapiens protein tyrosine phosphatase, non-receptor type 4(megakaryocyte), mRNA (cDNA clone MGC:9204 IMAGE:3853914), completecds./gene="PTPN4"/codon_start=1/product="protein tyrosine phosphatase, non-receptor type 4"/protein_id="AAH10674.1"/db_xref="GI:14715027"/db_xref="GeneID:5775"/db_xref="MIM:176878"
11 0 7 5 23 10 12 6 10 12 17 18 22 8 3 20 4 14 24 9 1 17 25 8 2 25 14 9 1 16 22 9 9 7 20 12 9 21 32 18 16 35 27 28 7 22 47 10 16 34 14 21 6 13 12 28 6 10 30 23 9 1 0 0
>BC002715\BC002715\259..1344\1086\AAH02715.1\Homo sapiens\Homo sapiens peroxisome proliferative activated receptor, delta,transcript variant 2, mRNA (cDNA clone MGC:3931 IMAGE:3630487),complete cds./gene="PPARD"/codon_start=1/product="peroxisome proliferative activated receptor, delta, isoform 2"/protein_id="AAH02715.1"/db_xref="GI:12803755"/db_xref="GeneID:5467"/db_xref="MIM:600409"
0 8 5 4 0 1 1 9 19 3 0 2 3 4 2 1 14 3 3 6 2 2 5 5 1 4 9 16 2 3 3 10 8 3 1 5 11 2 5 23 11 4 1 13 7 2 6 27 10 2 9 1 10 4 15 5 0 12 4 8 2 0 0 1
>AF073312\AF073312\125..1561\1437\AAC25673.1\Homo sapiens\Homo sapiens peanut-like 2 (PNUTL2) mRNA, complete cds./gene="PNUTL2"/codon_start=1/product="peanut-like 2"/protein_id="AAC25673.1"/db_xref="GI:3290200"
6 4 15 3 2 8 2 9 18 5 0 2 3 5 1 6 8 2 9 8 1 7 14 12 2 6 9 7 1 5 5 9 7 5 4 7 18 2 10 22 13 4 8 14 7 5 13 28 22 17 6 7 6 2 13 8 2 15 4 10 5 1 0 0
>BT007076\BT007076\1..507\507\AAP35739.1\Homo sapiens\Homo sapiens protein phosphatase 1, regulatory (inhibitor) subunit1B (dopamine and cAMP regulated phosphoprotein, DARPP-32) mRNA,complete cds./codon_start=1/product="protein phosphatase 1, regulatory (inhibitor) subunit 1B (dopamine and cAMP regulated phosphoprotein, DARPP-32)"/protein_id="AAP35739.1"/db_xref="GI:30582991"
0 3 2 0 4 1 1 2 8 1 0 1 4 4 2 5 2 1 3 1 0 0 5 6 0 6 1 4 0 4 2 3 5 2 0 2 2 0 1 4 2 2 2 8 4 1 12 26 3 6 1 1 0 2 1 0 0 2 1 1 1 0 1 0
>AK126499\AK126499\718..1095\378\BAC86567.1\Homo sapiens\Homo sapiens cDNA FLJ44535 fis, clone UTERU3004709./codon_start=1/protein_id="BAC86567.1"/db_xref="GI:34532998"
0 1 2 2 4 4 0 0 4 1 0 4 0 2 3 2 2 1 2 1 0 0 2 1 0 5 6 10 1 5 2 8 5 4 0 1 4 1 2 0 0 0 2 3 3 0 3 7 1 1 2 0 1 1 3 0 0 0 0 3 3 0 0 1
>AL772202#4\AL772202\40993..41253\261\CAI16742.1\Homo sapiens\Human DNA sequence from clone RP11-791O21 on chromosome 9 Containsa PEST-containing nuclear protein (PEST) pseudogene, a novel gene(FLJ37523), a novel gene, the EDG3 gene for endothelialdifferentiation, sphingolipid G-protein-coupled receptor, 3 and aCpG island, complete sequence./locus_tag="RP11-791O21.3-001"/standard_name="OTTHUMP00000021613"/codon_start=1/protein_id="CAI16742.1"/db_xref="GI:55962810"/db_xref="UniProt/TrEMBL:Q5SQD5"
0 0 1 0 1 2 2 2 0 1 0 0 0 1 0 3 2 0 4 0 0 1 1 4 2 3 2 1 0 0 0 2 1 0 0 1 3 0 4 2 0 3 0 8 1 2 1 1 2 0 1 0 3 1 3 3 1 2 1 4 3 0 0 1
>HUMMTMMP\D26512\112..1860\1749\BAA05519.1\Homo sapiens\Homo sapiens MT-MMP mRNA for membrane-type matrixmetalloproteinase, comlete cds./gene="MT-MMP"/codon_start=1/product="membrane-type matrix metalloproteinase"/protein_id="BAA05519.1"/db_xref="GI:793763"
5 10 5 6 3 9 2 14 24 3 0 1 6 7 3 4 8 2 4 12 4 6 6 28 2 9 4 24 8 7 8 25 16 4 2 7 19 3 9 24 12 9 7 12 4 8 7 30 18 13 20 5 3 3 28 9 0 16 7 15 13 0 0 1
>AL732442#6\AL732442\join(4469..4575,5043..5103,5219..5310,5434..5494, 5615..5728,5912..6013,17958..18003,18116..18184, 19757..19828,20349..20596)\972\CAI17752.1\Homo sapiens\Human DNA sequence from clone XXbac-48F10 on chromosome 6 containsthe 3' end of the MRPS18B gene for mitochondrial ribosomal proteinS18B, two novel proteins, a prothymosin, alpha (PTMA) pseudogene,the DDX16 gene for DEAD/H box polypeptide 16 , the gene forKIAA1949 protein, the NRM gene for nurim and four CpG islands,complete sequence./locus_tag="XXbac-BCX48F10.5-001"/standard_name="OTTHUMP00000029755"/codon_start=1/product="chromosome 6 open reading frame 134"/protein_id="CAI17752.1"/db_xref="GI:55962472"/db_xref="InterPro:IPR007965"/db_xref="UniProt/TrEMBL:Q9H8X5"
8 10 2 6 1 6 2 5 18 3 0 3 4 4 0 5 3 4 3 5 3 2 12 14 5 8 6 11 1 13 6 4 2 2 3 2 8 4 4 11 5 4 5 10 6 7 7 11 8 6 4 2 2 0 7 7 1 7 6 4 1 1 0 0
>BC013376\BC013376\45..1250\1206\AAH13376.1\Homo sapiens\Homo sapiens MARVEL domain containing 3, mRNA (cDNA clone MGC:16443IMAGE:3946889), complete cds./gene="MARVELD3"/codon_start=1/product="MARVEL domain containing 3"/protein_id="AAH13376.1"/db_xref="GI:15426530"/db_xref="GeneID:91862"
7 10 15 0 7 10 2 7 16 0 0 7 1 1 3 4 7 5 3 5 2 2 3 12 14 6 5 16 7 6 12 13 15 4 0 6 6 4 7 8 4 0 5 9 7 1 13 15 21 5 15 4 9 3 7 5 2 5 2 7 4 1 0 0
>AK000530\AK000530\236..607\372\BAA91234.1\Homo sapiens\Homo sapiens cDNA FLJ20523 fis, clone KAT10456./codon_start=1/protein_id="BAA91234.1"/db_xref="GI:7020688"
0 1 1 0 1 3 1 1 6 0 2 3 2 4 0 4 2 1 1 2 0 4 4 11 0 6 0 6 0 2 2 2 5 2 0 5 1 0 0 3 0 4 0 3 1 1 1 4 2 2 0 2 2 0 0 3 0 1 1 2 6 0 0 1
>BC003521\BC003521\241..711\471\AAH03521.1\Homo sapiens\Homo sapiens calpain 3, (p94), transcript variant 5, mRNA (cDNAclone IMAGE:3606623), complete cds./gene="CAPN3"/codon_start=1/product="calpain 3, isoform e"/protein_id="AAH03521.1"/db_xref="GI:13097609"/db_xref="GeneID:825"/db_xref="MIM:114240"
1 0 1 1 1 1 0 8 6 1 0 0 0 2 0 1 2 1 5 3 0 0 0 0 0 0 5 2 1 1 3 3 1 1 0 3 1 2 4 9 10 1 0 5 7 1 0 7 9 5 2 3 3 1 7 3 0 7 4 8 3 0 0 1
>AF118108\AF118108\91..1059\969\AAD42764.1\Homo sapiens\Homo sapiens lymphatic endothelium-specific hyaluronan receptorLYVE-1 mRNA, complete cds./codon_start=1/product="lymphatic endothelium-specific hyaluronan receptor LYVE-1"/protein_id="AAD42764.1"/db_xref="GI:5359673"
2 1 1 1 2 5 2 4 8 5 0 5 3 5 2 6 9 4 9 7 2 15 8 3 0 7 6 8 1 11 6 3 4 4 2 7 10 6 12 13 8 7 4 6 0 0 17 6 3 5 3 4 5 4 7 9 2 6 8 5 4 0 1 0
>AB037972\AB037972\24..227\204\BAB40572.1\Homo sapiens\Homo sapiens mRNA for defensin like protein, complete cds./codon_start=1/product="defensin like protein"/protein_id="BAB40572.1"/db_xref="GI:13516833"
2 0 1 1 3 1 0 2 2 2 1 2 0 0 1 0 1 0 1 0 1 0 2 0 0 1 0 0 0 2 2 4 0 1 0 1 2 1 3 3 1 0 0 2 0 2 1 1 0 0 0 3 5 1 1 2 1 3 0 1 0 1 0 0
>BC096061\BC096061\40..522\483\AAH96061.1\Homo sapiens\Homo sapiens ribonuclease, RNase A family, 3 (eosinophil cationicprotein), mRNA (cDNA clone MGC:116696 IMAGE:40000110), completecds./gene="RNASE3"/codon_start=1/product="ribonuclease, RNase A family, 3 (eosinophil cationic protein)"/protein_id="AAH96061.1"/db_xref="GI:64654615"/db_xref="GeneID:6037"/db_xref="MIM:131398"
2 1 5 2 5 4 0 4 5 4 1 1 2 1 0 1 0 3 1 3 1 4 7 2 0 4 5 2 0 2 1 1 1 3 2 0 3 6 2 0 8 7 3 4 3 3 0 1 3 3 0 4 4 5 3 4 2 3 4 3 2 1 0 0
>AF527764\AF527764\160..1257\1098\AAQ09011.1\Homo sapiens\Homo sapiens tissue-type brain LIM-like protein 2A mRNA, completecds./codon_start=1/product="LIM-like protein 2A"/protein_id="AAQ09011.1"/db_xref="GI:33327362"
1 9 11 1 0 3 0 8 22 0 0 1 0 5 4 1 6 0 2 4 1 1 2 9 5 2 0 23 4 2 1 13 7 3 0 7 12 0 1 26 14 3 1 10 14 4 3 23 10 2 10 2 25 8 15 5 0 6 3 7 3 0 0 1
>BC094732\BC094732\148..393\246\AAH94732.1\Homo sapiens\Homo sapiens A kinase (PRKA) anchor protein 7, transcript variantalpha, mRNA (cDNA clone IMAGE:5275622), complete cds./gene="AKAP7"/codon_start=1/product="A-kinase anchor protein 7, isoform alpha"/protein_id="AAH94732.1"/db_xref="GI:63100300"/db_xref="GeneID:9465"/db_xref="MIM:604693"
0 0 0 0 1 3 1 2 2 1 0 0 1 0 0 1 1 2 1 1 0 0 0 1 1 1 1 0 1 3 2 2 3 0 1 1 3 0 4 4 5 4 0 5 0 0 5 5 2 3 0 1 2 0 1 1 0 1 0 1 0 0 0 1
>HSA269537\AJ269537\68..1126\1059\CAB87380.1\Homo sapiens\Homo sapiens mRNA for chondroitin-4-sulfotransferase (C4ST gene)./gene="C4ST"/codon_start=1/product="chondroitin-4-sulfotransferase"/protein_id="CAB87380.1"/db_xref="GI:7572958"/db_xref="GOA:Q9NPF2"/db_xref="UniProt/Swiss-Prot:Q9NPF2"
2 4 12 1 2 4 1 8 20 0 1 5 4 5 0 2 9 1 4 11 3 4 6 8 1 1 3 10 1 1 2 3 4 1 0 9 14 0 6 17 15 3 3 12 12 1 9 15 9 5 17 4 9 0 13 5 0 15 0 13 2 1 0 0
>CR533546\CR533546\1..927\927\CAG38577.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834H0819D forgene PPT2, palmitoyl-protein thioesterase 2; complete cds, incl.stopcodon./gene="PPT2"/codon_start=1/protein_id="CAG38577.1"/db_xref="GI:49065518"
2 2 7 2 2 1 1 9 20 5 0 6 0 9 2 5 8 1 4 4 1 3 2 12 2 4 3 9 4 2 2 4 13 3 1 5 13 2 0 6 5 5 3 7 9 4 5 8 5 11 7 6 6 1 11 3 1 9 3 8 10 0 0 1
>AF109355\AF109355\62..718\657\AAQ13503.1\Homo sapiens\Homo sapiens MSTP001 mRNA, complete cds./codon_start=1/product="MSTP001"/protein_id="AAQ13503.1"/db_xref="GI:33337733"
2 2 1 0 1 1 1 5 15 0 0 4 0 3 2 1 5 2 1 6 2 2 2 1 1 1 1 13 1 1 0 3 3 3 1 3 5 1 2 10 7 2 3 12 2 3 8 9 10 4 5 2 4 1 6 5 1 9 5 8 4 1 0 0
>BC017355\BC017355\25..1590\1566\AAH17355.1\Homo sapiens\Homo sapiens karyopherin alpha 3 (importin alpha 4), mRNA (cDNAclone MGC:29709 IMAGE:5020312), complete cds./gene="KPNA3"/codon_start=1/product="karyopherin alpha 3"/protein_id="AAH17355.1"/db_xref="GI:16878323"/db_xref="GeneID:3839"/db_xref="MIM:601892"
1 2 2 1 10 2 6 6 10 12 13 8 10 4 0 5 5 6 15 5 0 5 10 8 3 7 16 5 0 15 9 5 2 8 7 11 12 18 16 9 15 19 15 20 4 6 25 9 6 28 4 3 2 7 7 9 21 6 14 6 6 1 0 0
>AK097034\AK097034\293..655\363\BAC04932.1\Homo sapiens\Homo sapiens cDNA FLJ39715 fis, clone SMINT2013228./codon_start=1/protein_id="BAC04932.1"/db_xref="GI:21756673"
0 1 0 1 1 2 2 7 4 0 4 0 1 1 1 2 1 3 8 2 0 0 3 0 2 2 3 3 0 2 0 3 3 2 1 1 2 1 0 1 2 3 0 4 8 2 0 2 1 1 3 4 4 2 0 5 1 0 1 4 3 0 0 1
>AK097954\AK097954\117..488\372\BAC05204.1\Homo sapiens\Homo sapiens cDNA FLJ40635 fis, clone THYMU2015825./codon_start=1/protein_id="BAC05204.1"/db_xref="GI:21757865"
1 0 2 1 5 2 1 1 7 4 1 5 4 4 1 1 1 1 2 2 0 2 4 2 0 0 2 1 0 1 2 4 4 6 1 1 3 1 4 0 0 2 3 1 4 2 0 4 3 2 0 0 5 1 0 2 0 2 0 4 4 0 0 1
>HSIGKLV40\X72461\1..366\366\CAA51129.1\Homo sapiens\H.sapiens mRNA for rearranged Ig kappa light chain variable region(I.27)./codon_start=1/product="Ig kappa light chain (VJC)"/protein_id="CAA51129.1"/db_xref="GI:441391"
1 0 1 0 1 3 0 7 6 0 1 1 1 1 0 4 3 3 1 7 1 3 3 1 0 2 2 3 1 2 2 2 5 2 0 4 2 1 4 2 0 2 3 6 0 2 2 1 2 2 1 3 2 1 3 1 0 4 0 1 3 0 0 0
>BC042558\BC042558\473..1270\798\AAH42558.1\Homo sapiens\Homo sapiens zinc finger, DHHC-type containing 21, mRNA (cDNA cloneMGC:42917 IMAGE:4837003), complete cds./gene="ZDHHC21"/codon_start=1/product="zinc finger, DHHC domain containing 21"/protein_id="AAH42558.1"/db_xref="GI:27503777"/db_xref="GeneID:340481"
2 1 1 3 5 6 3 6 5 3 6 5 2 3 1 2 1 0 3 1 0 7 9 4 0 3 2 5 0 0 5 6 0 4 0 3 2 10 2 7 4 6 2 4 7 8 10 2 2 5 6 4 6 9 8 12 9 4 12 9 8 1 0 0
>AY009107\AY009107\582..2021\1440\AAG49398.1\Homo sapiens\Homo sapiens PRTD-NY3 mRNA, complete cds./codon_start=1/product="PRTD-NY3"/protein_id="AAG49398.1"/db_xref="GI:12330998"
0 1 1 0 3 3 5 10 15 5 1 12 2 5 1 3 11 8 6 6 4 12 2 9 0 6 10 8 3 5 7 15 8 8 5 7 13 3 12 32 15 9 8 14 8 5 8 21 10 10 9 5 2 5 11 7 6 21 11 19 8 0 0 1
>AF203910\AF203910\125..1042\918\AAG23728.1\Homo sapiens\Homo sapiens serine/threonine kinase KRCT mRNA, complete cds./codon_start=1/product="serine/threonine kinase KRCT"/protein_id="AAG23728.1"/db_xref="GI:10834569"
3 4 6 1 3 3 4 9 18 5 2 4 1 4 1 3 3 3 0 6 1 3 5 4 1 4 3 11 2 5 3 7 6 6 0 4 10 1 2 8 4 5 7 14 7 8 5 13 11 5 4 4 5 4 9 1 2 11 3 9 5 0 0 1
>AY509035\AY509035\193..4353\4161\AAS91662.1\Homo sapiens\Homo sapiens roundabout-like protein 3 (ROBO3) mRNA, complete cds./gene="ROBO3"/codon_start=1/product="roundabout-like protein 3"/protein_id="AAS91662.1"/db_xref="GI:46395048"
12 21 20 11 12 22 7 29 70 13 0 10 12 34 4 21 48 28 17 21 13 13 41 66 18 38 27 48 25 22 29 51 41 10 7 22 63 2 10 21 24 9 12 57 14 6 28 61 22 21 19 8 16 4 21 3 3 20 5 23 31 0 0 1
>AK027159\AK027159\88..1692\1605\BAB15677.1\Homo sapiens\Homo sapiens cDNA: FLJ23506 fis, clone LNG03055./codon_start=1/protein_id="BAB15677.1"/db_xref="GI:10440218"
6 3 6 2 15 15 2 10 10 14 2 4 5 7 1 10 16 7 9 3 2 9 7 5 2 7 6 11 3 7 16 7 13 6 6 6 12 7 23 12 4 3 6 20 24 7 19 23 10 9 5 10 9 19 12 13 2 5 6 8 6 1 0 0
>AY007112\AY007112\429..1001\573\AAG01989.1\Homo sapiens\Homo sapiens clone TCCCTA00141 mRNA sequence./codon_start=1/protein_id="AAG01989.1"/db_xref="GI:9956007"
2 1 2 0 2 3 5 3 4 7 1 3 1 5 0 3 2 2 3 2 1 2 2 1 1 2 5 2 1 4 1 4 2 1 2 0 2 1 8 5 5 5 2 9 1 5 15 7 3 4 0 5 3 2 2 5 2 6 6 4 1 1 0 0
>BC031632\BC031632\494..1387\894\AAH31632.1\Homo sapiens\Homo sapiens KIAA1257, mRNA (cDNA clone MGC:35174 IMAGE:5170293),complete cds./gene="KIAA1257"/codon_start=1/product="KIAA1257 protein"/protein_id="AAH31632.1"/db_xref="GI:21594958"/db_xref="GeneID:57501"
1 0 1 2 9 5 1 4 6 4 8 7 6 5 2 7 4 3 6 4 2 6 6 5 4 1 5 5 0 2 5 3 1 3 2 4 6 3 16 14 5 4 6 9 6 4 17 12 9 3 2 3 1 1 4 5 3 5 7 7 6 1 0 0
>AF043045\AF043045\166..7974\7809\AAC33845.1\Homo sapiens\Homo sapiens actin-binding protein homolog ABP-278 mRNA, completecds./codon_start=1/product="actin-binding protein homolog ABP-278"/protein_id="AAC33845.1"/db_xref="GI:3282771"
12 17 20 7 11 17 6 38 68 10 5 13 15 33 14 26 63 27 44 69 23 32 41 75 24 60 37 89 12 44 53 91 79 54 12 78 131 42 68 104 59 29 15 57 45 13 71 93 84 72 55 34 29 9 54 32 9 80 45 37 16 1 0 0
>BC044658\BC044658\111..1505\1395\AAH44658.1\Homo sapiens\Homo sapiens FKSG44 gene, mRNA (cDNA clone MGC:47564IMAGE:5759383), complete cds./gene="FKSG44"/codon_start=1/product="FKSG44 protein"/protein_id="AAH44658.1"/db_xref="GI:27881616"/db_xref="GeneID:83786"
5 11 11 1 1 5 1 14 38 2 0 3 1 12 4 1 13 8 3 6 1 1 4 16 7 5 3 21 6 8 2 22 11 2 1 9 22 3 1 17 5 0 1 24 10 4 4 32 20 6 10 3 7 2 13 3 0 10 1 3 4 0 0 1
>HS223H9#1\AL008582\complement(37838..38872)\1035\CAB62938.1\Homo sapiens\Human DNA sequence from clone CTA-223H9 on chromosome 22q12.3-13.2,complete sequence./locus_tag="CTA-223H9.1-001"/standard_name="OTTHUMP00000028652"/codon_start=1/protein_id="CAB62938.1"/db_xref="GI:6572197"/db_xref="Genew:11980"/db_xref="GOA:Q14106"/db_xref="InterPro:IPR002087"/db_xref="UniProt/Swiss-Prot:Q14106"
0 5 5 0 0 0 2 5 18 1 0 2 5 10 1 3 16 6 1 9 1 1 7 13 2 6 3 17 3 4 3 17 7 10 2 1 16 1 6 14 13 2 0 18 3 1 3 16 7 5 7 2 2 1 12 9 0 6 5 7 2 0 0 1
>HSVATPA\X69151\167..1315\1149\CAA48903.1\Homo sapiens\H.sapiens mRNA for subunit C of vacuolar proton-ATPase V1 domain./codon_start=1/product="vacuolar proton-ATPase"/protein_id="CAA48903.1"/db_xref="GI:37643"/db_xref="GOA:P21283"/db_xref="UniProt/Swiss-Prot:P21283"
2 0 2 1 4 5 5 1 12 8 7 14 4 2 0 7 3 6 4 2 1 8 5 3 0 3 14 4 1 8 6 3 1 1 9 4 7 14 21 17 9 16 8 8 3 3 17 9 12 14 7 8 1 2 9 6 3 1 13 8 6 0 0 1
>AF357881\AF357881\25..3117\3093\AAK70402.1\Homo sapiens\Homo sapiens transcriptional coactivator MMS19 (MMS19) mRNA,complete cds./gene="MMS19"/codon_start=1/product="transcriptional coactivator MMS19"/protein_id="AAK70402.1"/db_xref="GI:14586956"
6 7 15 5 11 6 14 31 74 25 5 23 9 18 0 21 26 12 16 15 2 9 14 21 4 25 22 30 6 37 7 17 10 10 11 13 50 7 11 26 12 12 10 46 18 14 24 35 27 21 6 8 18 12 28 14 2 18 7 19 8 0 0 1
>BT009921\BT009921\1..1029\1029\AAP88923.1\Homo sapiens\Homo sapiens homeo box C10 mRNA, complete cds./codon_start=1/product="homeo box C10"/protein_id="AAP88923.1"/db_xref="GI:32880185"
2 8 5 0 2 6 0 8 12 2 0 4 0 12 6 2 17 5 4 8 4 2 2 15 6 7 5 10 7 3 4 9 7 0 2 3 3 1 11 13 8 10 3 7 4 1 11 21 10 1 8 6 8 1 6 3 1 3 2 8 3 0 1 0
>AB061822\AB061822\join(1094..1096,1623..1724,2375..2469,5142..5241, 5343..5396,5674..5982)\663\BAB79460.1\Homo sapiens\Homo sapiens RPL14 gene for ribosomal protein L14, complete cds andsequence./gene="RPL14"/codon_start=1/product="ribosomal protein L14"/protein_id="BAB79460.1"/db_xref="GI:17932938"
2 1 1 1 3 5 0 3 1 1 0 2 0 1 0 2 0 2 4 1 0 4 5 1 1 7 10 14 3 23 3 3 0 3 1 4 4 6 17 20 2 2 4 10 2 1 3 1 1 6 0 2 2 0 4 4 1 4 3 6 3 1 0 0
>BC036027\BC036027\205..3483\3279\AAH36027.1\Homo sapiens\Homo sapiens chromosome 13 open reading frame 22, mRNA (cDNA cloneMGC:33089 IMAGE:5271146), complete cds./gene="C13orf22"/codon_start=1/product="chromosome 13 open reading frame 22"/protein_id="AAH36027.1"/db_xref="GI:23273907"/db_xref="GeneID:10208"
3 0 2 5 11 6 11 8 18 21 32 22 34 11 7 33 12 22 31 12 0 27 32 7 3 23 15 11 1 35 19 9 9 17 18 5 13 23 48 33 14 52 21 30 14 19 56 20 20 35 2 20 8 23 8 27 18 7 25 15 9 0 0 1
>HSTCRGSA\X72500\1..825\825\CAA51165.1\Homo sapiens\H.sapiens mRNA for soluble gamma TCR./codon_start=1/product="gamma-delta T-cell receptor"/protein_id="CAA51165.1"/db_xref="GI:298107"
1 1 0 0 4 1 2 3 11 7 1 2 8 6 0 4 2 1 12 3 5 5 2 4 1 6 6 3 0 4 5 4 2 4 4 5 5 3 13 12 3 6 5 6 4 2 10 9 5 10 4 4 0 6 2 6 6 5 11 4 4 1 0 0
>AF193054\AF193054\286..1224\939\AAG22482.1\Homo sapiens\Homo sapiens PP3241 mRNA, complete cds./gene="PP3241"/codon_start=1/product="unknown"/protein_id="AAG22482.1"/db_xref="GI:10732632"
2 5 10 4 2 2 2 10 16 5 0 7 2 5 1 3 2 0 3 11 3 4 2 3 1 7 5 15 2 6 2 7 5 3 0 4 15 1 4 11 5 2 2 15 9 2 4 13 9 6 1 1 4 4 7 4 2 16 4 10 0 1 0 0
>HSCALB\X65869\55..294\240\CAA46699.1\Homo sapiens\H.sapiens mRNA for calbindin D9k, a calcium binding protein./function="calcium-binding protein"/codon_start=1/product="calbindin-D9k"/protein_id="CAA46699.1"/db_xref="GI:29602"/db_xref="GOA:P29377"/db_xref="UniProt/Swiss-Prot:P29377"
0 0 0 0 0 1 2 2 3 0 2 2 1 1 0 1 0 3 0 1 0 1 2 1 0 1 1 1 0 1 2 0 0 2 2 0 0 1 5 6 1 1 2 3 0 0 9 1 2 5 0 1 0 0 2 3 1 0 2 1 0 0 0 1
>AB110940\AB110940\join(801..1145,9755..9850,10833..10970,11281..11303, 11486..11573)\690\BAD13706.1\Homo sapiens\Homo sapiens TRIM40 gene for TRIM40 protein, complete cds,cell_line: LKT3./gene="TRIM40"/codon_start=1/product="TRIM40 protein"/protein_id="BAD13706.1"/db_xref="GI:46091155"
2 1 3 0 4 6 2 8 12 6 3 3 1 2 0 3 6 2 4 3 1 0 2 6 0 3 3 6 1 4 2 2 2 2 1 4 7 1 3 13 5 3 0 17 4 4 10 13 5 1 1 2 10 4 3 0 0 5 4 3 1 0 0 1
>AK023667\AK023667\638..1090\453\BAB14631.1\Homo sapiens\Homo sapiens cDNA FLJ13605 fis, clone PLACE1010562./codon_start=1/protein_id="BAB14631.1"/db_xref="GI:10435659"
0 2 1 0 1 6 0 4 17 2 1 0 2 4 0 1 3 4 1 3 0 1 2 3 0 0 2 7 2 2 1 2 1 4 0 2 3 1 0 4 1 0 4 5 3 1 1 8 3 4 5 4 5 1 4 1 1 1 1 5 3 0 0 1
>BC017221\BC017221\105..1736\1632\AAH17221.1\Homo sapiens\Homo sapiens chromosome 12 open reading frame 22, mRNA (cDNA cloneMGC:13118 IMAGE:4100454), complete cds./gene="C12orf22"/codon_start=1/product="TGF-beta induced apotosis protein 12"/protein_id="AAH17221.1"/db_xref="GI:16878013"/db_xref="GeneID:81566"
4 8 13 2 0 4 3 12 28 2 1 3 11 14 3 9 18 7 9 10 5 5 12 13 1 11 8 15 1 11 4 12 7 7 3 7 22 2 7 16 8 10 3 20 6 4 23 33 11 24 5 4 8 12 10 8 0 7 8 8 1 0 0 1
>AL591668#3\AL591668\join(79309..79446,79696..79797,95192..95325,95600..95643, 115179..115348,115514..115657,116707..116913)\939\CAI41601.1\Homo sapiens\Human DNA sequence from clone RP13-546E3 on chromosome X Containsthe 5' end of the PHF6 gene for PHD finger protein 6 and a CpGisland, complete sequence./gene="PHF6"/locus_tag="AC004383.6-003"/standard_name="OTTHUMP00000024064"/codon_start=1/product="PHD finger protein 6"/protein_id="CAI41601.1"/db_xref="GI:57209487"
4 2 0 0 9 5 1 2 4 2 4 5 13 5 0 8 3 8 11 2 1 3 2 2 0 6 9 2 1 4 10 3 3 2 4 4 2 1 22 12 2 7 3 7 8 10 19 4 3 9 3 5 7 11 0 14 3 1 8 7 0 0 1 0
>AB032928\AB032928\112..1677\1566\BAA89344.1\Homo sapiens\Homo sapiens mRNA for hMYHgamma3, complete cds./gene="hMYH"/codon_start=1/product="hMYHgamma3"/protein_id="BAA89344.1"/db_xref="GI:6691537"
3 7 12 5 5 8 7 7 31 4 1 2 5 9 2 8 11 6 6 16 2 3 12 11 3 7 13 27 0 12 7 11 14 7 6 8 21 6 4 13 9 2 7 39 10 2 9 23 9 7 5 6 7 5 8 3 0 4 3 9 12 0 0 1
>BC031976\BC031976\682..804\123\AAH31976.1\Homo sapiens\Homo sapiens cDNA clone MGC:42850 IMAGE:4830480, complete cds./codon_start=1/product="Unknown (protein for MGC:42850)"/protein_id="AAH31976.1"/db_xref="GI:71297011"
1 0 0 0 3 0 1 2 1 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 1 1 2 4 1 3 0 0 0 2 0 2 3 0 0 0 0 0 0 1 2 0 2 0 1 0 0
>BC005385\BC005385\43..834\792\AAH05385.1\Homo sapiens\Homo sapiens similar to Chymotrypsinogen B precursor, mRNA (cDNAclone MGC:12508 IMAGE:3950220), complete cds./gene="LOC440387"/codon_start=1/product="similar to Chymotrypsinogen B precursor"/protein_id="AAH05385.1"/db_xref="GI:13529251"/db_xref="GeneID:440387"
0 1 0 1 0 4 0 8 16 0 0 0 0 15 0 2 6 1 4 15 0 0 0 8 0 5 1 18 1 4 1 15 7 2 0 10 14 0 1 14 6 3 1 8 3 0 1 5 14 1 2 0 9 2 8 1 1 9 2 3 10 0 0 1
>CR456776\CR456776\1..1020\1020\CAG33057.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834F024D forgene TBP, TATA box binding protein; complete cds, incl. stopcodon./gene="TBP"/codon_start=1/protein_id="CAG33057.1"/db_xref="GI:48145669"
2 0 1 1 7 4 2 4 7 5 4 5 3 5 1 4 2 7 5 8 4 8 9 8 2 9 12 7 1 7 6 5 3 5 5 1 6 5 6 9 5 5 11 49 2 0 8 5 2 2 3 6 1 2 5 8 2 7 11 10 0 1 0 0
>D86043\D86043\3..1514\1512\BAA12974.1\Homo sapiens\Homo sapiens mRNA for SHPS-1, complete cds./codon_start=1/product="SHPS-1"/protein_id="BAA12974.1"/db_xref="GI:1864011"
2 2 6 2 6 6 2 10 17 1 1 6 9 10 3 9 12 1 11 21 3 7 4 18 7 8 5 24 8 6 8 9 8 3 5 9 25 6 7 18 14 10 3 22 11 3 6 28 15 5 8 4 8 1 9 2 1 13 4 5 6 0 0 1
>AF022728\AF022728\162..2045\1884\AAC05082.1\Homo sapiens\Homo sapiens beta-dystrobrevin (BDTN) mRNA, complete cds./gene="BDTN"/codon_start=1/product="beta-dystrobrevin"/protein_id="AAC05082.1"/db_xref="GI:2935183"
8 8 6 7 8 8 3 10 30 10 5 7 7 14 3 8 10 8 7 13 5 7 8 13 2 14 17 14 1 10 6 10 6 6 3 8 10 9 11 20 15 11 9 32 12 13 20 29 16 8 5 7 9 6 6 15 8 7 7 28 4 0 1 0
>BC013996\BC013996\41..1033\993\AAH13996.1\Homo sapiens\Homo sapiens aldo-keto reductase family 7, member A2 (aflatoxinaldehyde reductase), mRNA (cDNA clone MGC:20271 IMAGE:3625337),complete cds./gene="AKR7A2"/codon_start=1/product="AKR7A2 protein"/protein_id="AAH13996.1"/db_xref="GI:15559276"/db_xref="GeneID:8574"/db_xref="MIM:603418"
0 7 6 0 1 4 2 7 21 1 0 4 3 5 2 0 7 2 1 10 4 2 2 7 4 5 4 21 4 6 2 17 8 2 0 4 13 1 3 10 6 4 2 13 11 2 6 18 10 2 9 4 4 3 9 4 0 4 2 8 7 0 1 0
>S68252\S68252\4..627\624\AAD14009.1\Homo sapiens\TIMP-1=metalloproteinase inhibitor [human, keratoconus keratocytes,mRNA, 636 nt]./gene="TIMP-1"/codon_start=1/protein_id="AAD14009.1"/db_xref="GI:4261709"
0 2 4 2 0 3 0 5 10 1 4 4 0 6 0 2 4 3 2 9 2 3 4 8 0 1 0 10 0 5 3 6 4 0 0 5 3 1 3 5 3 1 2 10 5 1 3 7 3 2 4 2 9 3 7 4 2 6 1 4 4 0 0 1
>BC101124\BC101124\123..251\129\AAI01125.1\Homo sapiens\Homo sapiens cDNA clone MGC:119771 IMAGE:40014007, complete cds./codon_start=1/product="Unknown (protein for MGC:119771)"/protein_id="AAI01125.1"/db_xref="GI:71682794"
0 3 1 0 1 0 0 1 0 0 0 0 0 1 1 0 1 1 0 0 0 0 1 1 0 1 0 0 0 0 1 0 1 0 0 0 1 0 1 3 3 0 1 0 0 1 1 1 1 1 1 0 3 2 2 0 0 2 0 1 2 0 0 1
>BC078662\BC078662\130..756\627\AAH78662.1\Homo sapiens\Homo sapiens RAB6B, member RAS oncogene family, mRNA (cDNA cloneMGC:88263 IMAGE:6450986), complete cds./gene="RAB6B"/codon_start=1/product="RAB6B protein"/protein_id="AAH78662.1"/db_xref="GI:50927456"/db_xref="GeneID:51560"
2 3 1 1 1 5 1 2 8 1 0 4 1 4 1 2 7 2 4 5 5 1 1 4 1 0 2 2 3 4 2 5 7 1 0 4 8 1 6 8 4 3 1 10 0 0 2 12 12 3 6 0 2 0 8 2 1 9 4 7 2 1 0 0
>AK027060\AK027060\7..636\630\BAB15643.1\Homo sapiens\Homo sapiens cDNA: FLJ23407 fis, clone HEP19601./codon_start=1/protein_id="BAB15643.1"/db_xref="GI:10440085"
3 2 4 1 8 3 0 7 1 4 0 2 3 1 0 2 8 5 2 0 0 9 3 2 0 0 3 4 0 1 4 2 8 1 2 1 1 1 11 11 0 4 2 11 9 6 10 9 1 3 1 5 5 9 6 1 1 3 2 1 0 1 0 0
>AC093674\AC093674\join(21995..22131,27668..27720,58421..58528,59567..59697, 62635..62728,71278..71633)\879\AAY24212.1\Homo sapiens\Homo sapiens BAC clone RP11-592G8 from 2, complete sequence./gene="HNMT"/codon_start=1/product="unknown"/protein_id="AAY24212.1"/db_xref="GI:62988825"
0 1 1 0 2 3 3 8 7 8 1 4 5 4 1 5 3 6 5 4 1 3 5 1 0 2 5 3 0 6 7 3 4 4 3 0 2 7 11 14 6 7 7 6 2 4 11 11 12 8 4 6 5 1 5 10 5 3 12 10 5 1 0 0
>HSARSD\X83572\77..1858\1782\CAA58555.1\Homo sapiens\Homo sapiens ARSD gene, complete CDS./gene="ARSD"/codon_start=1/protein_id="CAA58555.1"/db_xref="GI:791002"/db_xref="GOA:P51689"/db_xref="InterPro:IPR000917"/db_xref="UniProt/Swiss-Prot:P51689"
5 5 5 0 9 8 5 15 26 8 5 6 4 11 2 6 7 5 5 14 9 5 4 19 9 5 16 19 10 5 17 19 15 13 2 5 21 4 6 9 10 9 1 21 17 16 9 18 17 9 9 5 9 6 19 10 3 9 7 12 14 0 0 1
>AL391384#1\AL391384\join(complement(1897..2124),complement(1138..1295), complement(AL138695.13:66652..66845), complement(AL138695.13:65885..65958), complement(AL138695.13:64390..64557), complement(AL138695.13:63676..63840), complement(AL138695.13:62411..62524), complement(AL138695.13:62149..62286), complement(AL138695.13:61158..61304), complement(AL138695.13:60624..60740), complement(AL138695.13:60260..60361), complement(AL138695.13:59546..59610), complement(AL138695.13:59369..59453), complement(AL138695.13:57250..57377), complement(AL138695.13:54437..54523), complement(AL138695.13:51916..52072), complement(AL138695.13:50388..50602), complement(AL138695.13:50111..50279), complement(AL138695.13:49828..49986), complement(AL138695.13:48994..49116), complement(AL138695.13:48260..48343))\228\CAI15670.1\Homo sapiens\Human DNA sequence from clone RP11-555G22 on chromosome 13 Containsthe 5' end of the gene for mitotic control protein (DIS3,KIAA1008),the 5' end of the gene for progesterone-induced blocking factor 1(PIBF1) and a CpG island, complete sequence./gene="RP11-342J4.3"/locus_tag="RP11-342J4.3-003"/standard_name="OTTHUMP00000018498"/codon_start=1/protein_id="CAI15670.1"/db_xref="GI:55959542"/db_xref="GOA:Q5W0P7"/db_xref="InterPro:IPR001900"/db_xref="InterPro:IPR006596"/db_xref="UniProt/TrEMBL:Q5W0P7"
2 1 2 1 29 14 17 13 23 8 26 10 23 10 4 16 11 15 28 10 4 14 25 10 7 12 17 8 7 8 12 11 8 9 10 9 7 11 49 27 17 31 19 21 25 17 17 13 15 15 22 15 19 15 17 24 23 16 16 13 9 29 8 15
>AF289485\AF289485\21..1151\1131\AAG17847.1\Homo sapiens\Homo sapiens MYG1 homolog mRNA, complete cds./codon_start=1/product="MYG1 homolog"/protein_id="AAG17847.1"/db_xref="GI:10444289"
9 6 9 2 2 1 0 9 25 4 2 4 2 8 0 2 8 5 1 11 2 3 9 9 7 7 12 11 2 4 5 7 9 5 0 3 13 3 4 7 2 3 5 12 13 3 5 22 14 5 6 6 3 3 11 3 1 9 3 8 7 0 1 0
>HUMHVDC\L29384\166..6921\6756\AAA59204.1\Homo sapiens\Homo sapiens (clone pcDNA-alpha1E-1) voltage-dependent calciumchannel alpha-1E-1 subunit mRNA, complete cds./codon_start=1/product="voltage-dependent calcium channel alpha-1E-1"/protein_id="AAA59204.1"/db_xref="GI:495868"
21 33 39 13 16 36 18 54 97 20 7 30 25 62 7 27 42 29 17 61 15 20 21 42 15 30 28 81 9 34 26 52 41 12 8 48 72 12 26 75 60 34 11 75 38 15 44 106 61 33 35 27 21 14 68 53 12 84 33 77 29 0 1 0
>AF039843\AF039843\391..1338\948\AAC04258.1\Homo sapiens\Homo sapiens Sprouty 2 (SPRY2) mRNA, complete cds./gene="SPRY2"/codon_start=1/product="Sprouty 2"/protein_id="AAC04258.1"/db_xref="GI:2809400"
3 3 3 2 8 6 1 7 8 4 1 5 5 8 4 8 8 3 5 4 3 4 8 8 0 13 1 8 0 4 1 5 8 7 2 7 3 4 8 8 9 2 1 16 8 2 3 11 10 5 4 3 12 14 2 2 2 4 1 3 3 0 1 0
>AL512785#3\AL512785\complement(join(84515..84550,86158..86322,89974..90037, 99118..99251))\399\CAI15780.1\Homo sapiens\Human DNA sequence from clone RP11-565P22 on chromosome 1 Containstwo novel genes, the 3' end of the gene for C-terminal PDZ domainligand of neuronal nitric oxide synthase (CAPON), a novel gene(LOC284680), the EAT2 gene for SH2 domain-containing molecule EAT2and a CpG island, complete sequence./gene="EAT2"/locus_tag="RP11-565P22.5-001"/standard_name="OTTHUMP00000029531"/codon_start=1/product="SH2 domain-containing molecule EAT2"/protein_id="CAI15780.1"/db_xref="GI:55960297"/db_xref="InterPro:IPR000980"
1 0 0 1 5 1 1 2 5 2 3 5 0 1 2 1 5 1 2 3 0 1 5 1 0 2 1 0 0 0 3 1 3 1 0 5 4 1 6 5 3 2 1 3 2 1 5 4 2 4 5 2 1 2 1 5 3 2 1 2 1 0 0 1
>AF091871#1\AF091871\17..283\267\AAD14598.1\Homo sapiens\Homo sapiens molybdopterin-synthase small and large subunit (MOCS2)bicistronic mRNA, complete cds./gene="MOCS2"/function="molybdenum cofactor biosynthesis"/codon_start=1/product="molybdopterin-synthase small subunit"/protein_id="AAD14598.1"/db_xref="GI:4262372"
1 0 0 2 1 0 0 2 2 2 0 3 1 0 0 1 0 2 1 1 0 1 0 2 1 3 1 1 1 3 6 0 0 0 1 1 3 5 2 1 0 1 2 5 0 1 6 3 1 2 0 2 1 0 0 2 5 1 3 1 1 0 1 0
>BC009743\BC009743\104..1699\1596\AAH09743.1\Homo sapiens\Homo sapiens coiled-coil domain containing 9, mRNA (cDNA cloneMGC:10357 IMAGE:3832697), complete cds./gene="CCDC9"/codon_start=1/product="coiled-coil domain containing 9"/protein_id="AAH09743.1"/db_xref="GI:14602475"/db_xref="GeneID:26093"
6 17 25 3 2 9 0 4 11 4 0 3 5 11 3 5 10 7 4 5 3 7 12 23 3 18 7 21 1 12 9 22 14 5 1 4 8 1 5 21 7 4 2 19 11 2 16 67 16 11 3 2 1 1 6 2 1 8 2 8 11 0 0 1
>HS889N15#8\AL031177\join(44805..44814,79055..79165,81759..81830,84238..84336, 87035..87136,87317..87389,90069..90148,90782..90969, 91091..91169,103130..103275,104780..104836,105957..106065, 106620..106690)\1197\CAI43137.1\Homo sapiens\Human DNA sequence from clone RP5-889N15 on chromosome Xq22.1-22.3Contains the 3' end of a novel gene (MGC44287), the PSMD10 gene forproteasome (prosome, macropain) 26S subunit, non-ATPase, 10 (p28),the AUTL2 gene for AUT-like 2, cysteine endopeptidase (S.cerevisiae) (APG4A, MGC43691), the 3' end of the COL4A6 gene forcollagen, type IV, alpha 6 and a CpG island, complete sequence./gene="APG4A"/locus_tag="RP5-889N15.2-001"/standard_name="OTTHUMP00000023821"/codon_start=1/product="APG4 autophagy 4 homolog A (S. cerevisiae)"/protein_id="CAI43137.1"/db_xref="GI:57284015"/db_xref="GOA:Q8WYN0"/db_xref="InterPro:IPR005078"/db_xref="UniProt/Swiss-Prot:Q8WYN0"
1 3 0 2 3 4 6 3 11 6 11 6 10 3 0 7 2 4 8 4 2 7 9 6 0 7 6 4 1 8 12 3 4 5 3 3 5 10 18 8 7 7 8 13 2 5 18 12 11 15 5 6 6 6 9 12 3 8 9 11 10 0 1 0
>HUMCACNL1E\L29534\14..6448\6435\AAA51900.1\Homo sapiens\Homo sapiens cardiac L-type voltage-dependent calcium channel a1subunit (CACNL1A1) mRNA, complete cds./gene="CACNL1A1"/function="calcium channel"/codon_start=1/evidence=experimental/product="cardiac L-type voltage-dependent calcium channel a1 subunit"/protein_id="AAA51900.1"/db_xref="GI:463079"/db_xref="GDB:G00-126-094"
14 25 36 4 7 35 9 69 117 9 7 13 7 56 4 19 58 12 17 58 22 12 26 55 10 17 25 90 21 29 18 54 41 18 4 48 67 12 20 81 74 25 12 69 30 9 41 103 53 34 42 14 28 15 80 47 6 107 30 53 26 0 1 0
>BC063652\BC063652\282..1055\774\AAH63652.1\Homo sapiens\Homo sapiens potassium channel tetramerisation domain containing 1,mRNA (cDNA clone MGC:75559 IMAGE:4802987), complete cds./gene="KCTD1"/codon_start=1/product="KCTD1 protein"/protein_id="AAH63652.1"/db_xref="GI:39645903"/db_xref="GeneID:284252"
2 0 4 2 9 5 3 9 5 3 1 7 3 8 2 2 4 1 3 3 3 4 5 5 0 7 5 2 0 0 6 7 1 3 3 8 5 1 6 3 4 5 4 8 6 0 10 7 10 5 5 4 1 4 4 7 2 9 4 6 2 1 0 0
>AY358607\AY358607\68..508\441\AAQ88970.1\Homo sapiens\Homo sapiens clone DNA77303 SRSR846 (UNQ846) mRNA, complete cds./locus_tag="UNQ846"/codon_start=1/product="SRSR846"/protein_id="AAQ88970.1"/db_xref="GI:37182336"
1 1 0 0 3 2 3 5 4 3 1 5 3 2 1 2 0 2 2 4 1 2 5 1 1 6 3 0 1 5 3 3 2 0 2 2 4 5 1 0 0 3 3 2 3 0 6 0 5 2 0 5 3 4 2 2 1 4 4 3 3 0 0 1
>AL669918#7\AL669918\complement(join(43384..43472,43956..44160,44559..44688, 45097..45208,45367..45514,46275..46421))\831\CAI18138.1\Homo sapiens\Human DNA sequence from clone XXbac-246D15 on chromosome 6 containsthe HLA-DOB gene for major histocompatibility complex, class II, DObeta, the TAP2 gene for transporter 2, ATP-binding cassette,subfamily B (MDR/TAP), the PSMB8 gene for proteasome (prosome,macropain) subunit, beta type, 8 (large multifunctional protease7), the TAP1 gene for transporter 1, ATP-binding cassette,sub-family B (MDR/TAP), the PSMB9 gene for proteasome (prosome,macropain) subunit, beta type, 9 (large multifunctional protease2), a novel protein similar to protein phosphatase 1, regulatory(inhibitor) subunit 2 and two CpG islands, complete sequence./gene="PSMB8"/locus_tag="XXbac-BPG246D15.6-002"/standard_name="OTTHUMP00000029420"/codon_start=1/product="proteasome (prosome, macropain) subunit, beta type, 8 (large multifunctional protease 7)"/protein_id="CAI18138.1"/db_xref="GI:55961477"/db_xref="GOA:Q5QNR8"/db_xref="InterPro:IPR000243"/db_xref="InterPro:IPR001353"/db_xref="UniProt/TrEMBL:Q5QNR8"
3 3 8 2 1 3 2 6 10 3 2 0 3 5 3 6 3 7 2 3 2 3 2 3 2 4 5 11 2 5 10 10 7 4 2 3 7 3 1 7 5 5 1 8 4 3 10 5 7 6 11 6 3 3 6 0 0 1 7 14 3 1 0 0
>AL513164#2\AL513164\join(97905..98060,144971..145099,AL033378.12:19328..19378, AL033378.12:19502..19551,AL033378.12:47689..47729, AL033378.12:50561..50647,AL033378.12:53254..53366, AL033378.12:66758..66859,AL033378.12:93468..93600, AL033378.12:98691..99037,AL033378.12:104435..104509, AL033378.12:106597..106740,AL033378.12:110670..110805, AL033378.12:111941..112110,AL033378.12:112915..113124, AL033378.12:113895..114045,AL033378.12:119587..119700, AL033378.12:122824..123962,AL033378.12:125159..125290, AL033378.12:127439..127702)\-600465\CAH73449.1\Homo sapiens\Human DNA sequence from clone RP11-400P17 on chromosome 6 Containsthe 5' part of a novel gene, the 5' part of the gene for KIAA0790protein (KIAA0790) and a CpG island, complete sequence./gene="RP3-323M4.1"/locus_tag="RP3-323M4.1-001"/standard_name="OTTHUMP00000017386"/codon_start=1/protein_id="CAH73449.1"/db_xref="GI:55665282"/db_xref="InterPro:IPR001452"/db_xref="InterPro:IPR001660"/db_xref="InterPro:IPR011510"/db_xref="InterPro:IPR011511"/db_xref="UniProt/TrEMBL:Q5VUX1"
3 4 5 2 17 25 9 20 35 24 22 40 29 20 0 26 20 22 26 13 2 22 20 17 8 20 16 12 7 15 22 15 16 11 13 11 20 31 45 30 14 27 18 28 19 17 16 27 14 21 15 28 21 26 21 52 21 9 24 24 31 17 14 29
>AF411849S2\AF456925\complement(2643..3659)\1017\AAL47764.1\Homo sapiens\Homo sapiens USH3 region, partial sequence./codon_start=1/product="KIAA0001"/protein_id="AAL47764.1"/db_xref="GI:17901946"/IGNORED_CODON=2
0 1 3 0 3 3 5 9 8 8 3 5 8 5 1 6 9 6 7 3 0 7 3 3 1 6 2 3 0 6 5 1 1 2 4 6 14 5 13 11 7 7 1 11 3 2 8 1 6 2 9 6 5 4 13 14 5 19 14 7 6 0 0 1
>BC075842\BC075842\23..1432\1410\AAH75842.1\Homo sapiens\Homo sapiens immunoglobulin heavy constant gamma 1 (G1m marker),mRNA (cDNA clone MGC:88778 IMAGE:6215815), complete cds./gene="IGHG1"/codon_start=1/product="IGHG1 protein"/protein_id="AAH75842.1"/db_xref="GI:49904194"/db_xref="GeneID:3500"/db_xref="IMGT/GENE-DB:IGHG1"/db_xref="MIM:147100"
2 0 4 1 2 1 1 15 23 0 0 1 6 22 4 7 19 4 5 25 5 3 8 16 7 5 4 9 2 4 6 13 9 2 2 19 26 1 11 23 14 4 1 17 9 2 4 17 15 1 15 4 9 2 12 2 2 6 2 3 11 0 0 1
>HUMMGPHB\J03544\80..2671\2592\AAA59597.1\Homo sapiens\Human brain glycogen phosphorylase mRNA, complete cds./gene="PYGB"/codon_start=1/protein_id="AAA59597.1"/db_xref="GI:307200"/db_xref="GDB:G00-120-326"
2 17 19 1 2 12 1 10 54 8 1 10 3 14 6 2 5 3 3 20 11 4 8 21 6 4 10 32 9 10 5 27 14 6 1 16 47 2 7 47 29 11 0 29 21 5 11 54 44 10 22 12 10 4 28 11 2 38 6 22 14 0 1 0
>AF461041\AF461041\146..7096\6951\AAL67803.1\Homo sapiens\Homo sapiens AF15q14 isoform 2 mRNA, complete cds; alternativelyspliced./codon_start=1/product="AF15q14 isoform 2"/protein_id="AAL67803.1"/db_xref="GI:18308012"
6 2 3 7 44 16 22 20 36 35 38 42 45 21 1 61 26 60 56 39 5 71 36 16 4 41 28 21 1 44 37 8 14 17 37 20 20 40 117 72 44 122 64 54 22 39 131 73 46 104 13 34 10 40 23 53 66 18 64 54 13 0 1 0
>AK056900\AK056900\94..483\390\BAB71305.1\Homo sapiens\Homo sapiens cDNA FLJ32338 fis, clone PROST2005919, moderatelysimilar to Human breast cancer, estrogen regulated LIV-1 protein(LIV-1) mRNA./codon_start=1/protein_id="BAB71305.1"/db_xref="GI:16552425"
0 2 1 0 1 2 0 5 15 0 0 2 0 4 1 0 3 0 0 3 1 1 1 0 0 0 4 13 5 4 3 4 6 1 1 2 6 1 0 1 2 0 1 1 4 0 0 7 4 0 2 0 2 0 6 0 0 2 0 3 2 0 0 1
>BC025784\BC025784\1..1404\1404\AAH25784.1\Homo sapiens\Homo sapiens pancreatic lipase-related protein 1, mRNA (cDNA cloneMGC:34434 IMAGE:5226231), complete cds./gene="PNLIPRP1"/codon_start=1/product="pancreatic lipase-related protein 1"/protein_id="AAH25784.1"/db_xref="GI:19343958"/db_xref="GeneID:5407"/db_xref="MIM:604422"
2 2 3 0 4 4 2 13 14 4 0 6 3 6 0 6 12 3 15 9 4 7 8 11 2 4 8 9 1 11 18 10 6 5 1 1 18 6 12 17 11 11 6 10 7 3 9 18 14 14 8 7 11 2 16 12 2 16 8 7 8 1 0 0
>HSU49187\U49187\465..2075\1611\AAC51134.1\Homo sapiens\Human placenta (Diff48) mRNA, complete cds./gene="Diff48"/codon_start=1/protein_id="AAC51134.1"/db_xref="GI:1293561"
3 5 4 0 6 6 6 10 26 7 5 4 7 14 3 9 11 3 11 12 4 2 9 5 1 10 13 14 1 10 9 9 5 10 5 5 7 5 22 17 10 15 6 15 8 2 25 34 15 14 4 8 4 3 9 11 3 12 6 14 3 0 1 0
>BC011786\BC011786\76..417\342\AAH11786.1\Homo sapiens\Homo sapiens putative insulin-like growth factor II associatedprotein, mRNA (cDNA clone MGC:19839 IMAGE:4100006), complete cds./gene="LOC492304"/codon_start=1/product="putative insulin-like growth factor II associated protein"/protein_id="AAH11786.1"/db_xref="GI:15080002"/db_xref="GeneID:492304"
2 0 2 2 1 2 0 3 3 1 0 0 0 1 1 1 0 2 0 4 1 2 4 7 3 4 1 6 1 1 3 5 2 1 0 4 1 2 2 1 2 3 1 4 3 2 0 2 2 0 1 0 4 3 1 1 1 0 4 1 2 0 1 0
>HUMPECAM1\M28526\142..2358\2217\AAA36429.1\Homo sapiens\Human platelet endothelial cell adhesion molecule (PECAM-1) mRNA,complete cds./codon_start=1/protein_id="AAA36429.1"/db_xref="GI:189776"
2 2 2 1 10 8 3 4 25 9 3 4 12 17 2 15 12 14 14 18 8 8 10 12 3 7 8 21 4 9 14 4 6 6 3 24 32 8 26 33 24 13 12 24 11 7 33 24 17 14 12 10 8 8 14 9 11 22 18 19 5 0 1 0
>AF151100\AF151100\320..703\384\AAD42081.1\Homo sapiens\Homo sapiens TDAG51/Ipl homologue 1 (TIH1) mRNA, complete cds./gene="TIH1"/codon_start=1/product="TDAG51/Ipl homologue 1"/protein_id="AAD42081.1"/db_xref="GI:5326878"
0 6 4 0 0 0 1 6 8 0 0 0 0 1 0 0 4 0 1 7 4 0 0 3 0 0 0 6 3 1 0 9 6 0 0 2 7 0 0 9 2 0 0 7 1 0 3 7 1 1 1 0 3 0 5 0 0 5 0 1 2 1 0 0
>HSU38805\U38805\72..2276\2205\AAD04206.1\Homo sapiens\Homo sapiens fertilin beta mRNA, complete cds./codon_start=1/product="fertilin beta"/protein_id="AAD04206.1"/db_xref="GI:4151119"
0 2 2 1 13 5 3 6 11 9 18 7 22 6 1 10 7 19 12 3 1 13 13 3 2 14 17 7 0 11 19 7 12 12 10 3 10 22 30 14 11 25 20 14 8 12 33 13 12 25 9 20 17 26 10 28 15 3 32 16 8 0 1 0
>AY495333\AY495333\190..726\537\AAS80145.1\Homo sapiens\Homo sapiens tumor necrosis factor alpha-inducing factor deltaisoform (TAIF) mRNA, complete cds, alternatively spliced./gene="TAIF"/codon_start=1/product="tumor necrosis factor alpha-inducing factor delta isoform"/protein_id="AAS80145.1"/db_xref="GI:46095220"
2 0 3 1 4 0 1 3 10 1 1 0 3 4 1 3 2 1 2 2 0 1 2 3 1 3 4 7 1 1 4 2 3 0 0 3 6 2 5 8 1 1 2 11 3 1 5 15 4 4 2 3 4 1 6 2 1 0 0 7 5 0 0 1
>AC009957\AC009957\complement(120698..120949)\252\AAX93056.1\Homo sapiens\Homo sapiens BAC clone RP11-285H23 from 2, complete sequence./gene="PRO0159"/codon_start=1/product="unknown"/protein_id="AAX93056.1"/db_xref="GI:62702129"
0 0 0 0 1 0 1 1 3 4 0 1 1 3 0 3 0 1 1 0 0 1 0 0 0 0 2 1 1 0 1 1 0 0 1 4 1 0 2 3 0 3 1 1 1 4 1 1 0 2 0 4 0 1 2 8 1 2 9 2 2 1 0 0
>HUMHYMEGLA\L07033 S55700\15..992\978\AAA92733.1\Homo sapiens\Human hydroxymethylglutaryl-CoA lyase mRNA, complete cds./EC_number="4.1.3.4"/standard_name="3-hydroxy-3-methylglutaryl CoA; HMG CoA Lyase"/codon_start=1/evidence=experimental/product="hydroxymethylglutaryl-CoA lyase"/protein_id="AAA92733.1"/db_xref="GI:184503"
2 0 4 0 1 2 3 5 12 5 1 6 5 6 0 9 3 2 1 12 1 4 6 3 1 4 9 8 4 13 9 11 5 5 3 10 13 4 8 15 6 6 3 9 3 1 10 7 8 1 6 2 3 5 3 6 3 10 5 12 1 0 0 1
>BC010397\BC010397\7..699\693\AAH10397.1\Homo sapiens\Homo sapiens lysophospholipase I, mRNA (cDNA clone MGC:13688IMAGE:4109335), complete cds./gene="LYPLA1"/codon_start=1/product="lysophospholipase I"/protein_id="AAH10397.1"/db_xref="GI:14714526"/db_xref="GeneID:10434"/db_xref="MIM:605599"
0 0 2 0 3 1 2 3 4 5 3 5 5 1 1 6 0 3 3 5 1 3 5 3 2 7 6 7 2 6 6 2 5 7 0 2 7 3 8 3 3 7 3 8 3 3 7 1 1 10 0 3 4 2 2 6 1 5 12 9 3 0 0 1
>BC036370\BC036370\32..1447\1416\AAH36370.1\Homo sapiens\Homo sapiens stress 70 protein chaperone, microsome-associated,60kDa, mRNA (cDNA clone MGC:26248 IMAGE:4837136), complete cds./gene="STCH"/codon_start=1/product="stress 70 protein chaperone, microsome-associated, 60kDa, precursor"/protein_id="AAH36370.1"/db_xref="GI:22137780"/db_xref="GeneID:6782"/db_xref="MIM:601100"
2 1 2 3 7 3 6 5 8 9 12 14 5 3 1 11 3 7 9 7 3 8 7 6 0 8 13 5 0 11 17 12 6 2 11 6 15 9 18 11 8 14 12 11 5 4 20 13 11 13 2 12 0 1 6 14 7 7 14 10 1 0 0 1
>AL589765#13\AL589765\complement(join(96827..96879,97085..97181,97440..97541, 97767..97918,98195..98259,98471..98643,98814..98974, 101060..101381,101478..101582,102426..102515, 103856..103962,105274..105397))\1551\CAI17175.1\Homo sapiens\Human DNA sequence from clone RP11-98D18 on chromosome 1 Containsthe 3' end of the SNX27 gene for sorting nexin family member 27,the TNRC4 gene for trinucleotide repeat containing 4, five novelgenes, a ribosomal protein S11 (RPS11) pseudogene, the MRPL9 genefor mitochondrial ribosomal protein L9, the OAZ3 gene for ornithinedecarboxylase antizyme 3, a novel gene (FLJ36032) the TDRKH genefor tudor and KH domain containing, the RORC gene for RAR-relatedorphan receptor C and four CpG islands, complete sequence./gene="TDRKH"/locus_tag="RP11-98D18.8-004"/standard_name="OTTHUMP00000015262"/codon_start=1/product="tudor and KH domain containing"/protein_id="CAI17175.1"/db_xref="GI:55960562"/db_xref="GOA:Q5SZR5"/db_xref="InterPro:IPR002999"/db_xref="InterPro:IPR004087"/db_xref="InterPro:IPR004088"/db_xref="InterPro:IPR008191"/db_xref="UniProt/TrEMBL:Q5SZR5"
2 3 9 0 7 5 6 10 12 9 7 8 8 6 0 12 11 10 12 8 1 10 11 6 1 10 12 12 0 14 12 6 7 7 6 6 10 8 15 13 5 7 3 13 4 6 27 22 19 18 6 7 2 3 3 9 7 13 11 11 8 0 0 1
>AK055094\AK055094\71..1444\1374\BAB70853.1\Homo sapiens\Homo sapiens cDNA FLJ30532 fis, clone BRAWH2001129, weakly similarto OCCLUDIN./codon_start=1/protein_id="BAB70853.1"/db_xref="GI:16549750"
3 3 7 2 11 6 4 8 12 4 5 8 9 7 3 4 3 9 7 12 0 2 19 10 3 5 9 6 1 11 13 9 5 5 5 6 11 9 8 10 7 9 5 4 6 3 12 13 13 14 13 13 4 3 6 15 7 5 9 14 8 0 0 1
>HS187N21\Z98036\join(complement(AL355855.23:6892..6990), complement(59373..59483),complement(13152..13196), complement(10962..11046),complement(6264..6442))\-355851\CAI19715.1\Homo sapiens\Human DNA sequence from clone RP1-187N21 on chromosome 6p21.2-21.33Contains part of a novel gene and the 3' end of the NUDT3 gene fornudix (nucleoside diphosphate linked moiety X)-type motif 3,complete sequence./gene="NUDT3"/locus_tag="RP1-187N21.3-001"/standard_name="OTTHUMP00000016227"/codon_start=1/protein_id="CAI19715.1"/db_xref="GI:56208216"/db_xref="Genew:8050"/db_xref="GOA:O95989"/db_xref="InterPro:IPR000086"/db_xref="UniProt/TrEMBL:O95989"
1 1 1 2 7 3 2 4 3 0 3 5 3 2 1 1 4 4 5 1 1 3 9 2 1 1 4 0 0 4 8 2 3 2 1 2 3 3 3 6 1 2 0 4 2 5 3 8 2 1 1 0 6 5 0 4 0 1 5 5 4 1 1 1
>AL670886#18\AL670886\join(19489..19560,20525..20627,21196..21353)\333\CAI17797.1\Homo sapiens\Human DNA sequence from clone XXbac-88C14 on chromosome 6 containsthe 5' end of the BAT3 gene for HLA-B associated transcript 3, theAPOM gene for apolipoprotein M, the gene for chromosome 6, openreading frame 47, the BAT4 gene for HLA-B associated transcript 4,the CSNK2B gene for casein kinase 2, beta polypeptide, the LY6G5Bgene for lymphocyte antigen 6 complex, locus 5B , the gene for G5cprotein, the BAT5 gene for HLA-B associated transcript 5, theLY6G6F gene for lymphocyte antigen 6 complex, locus G6f, the LY6G6Egene for lymphocyte antigen 6 complex, locus G6E, the LY6G6C genefor lymphocyte antigen 6 complex, locus G6C, the gene forchromosome 6 open reading frame 25, the DDAH gene fordimethylarginine dimethylaminohydrolase 2, the CLIC1 gene forchloride intracellular channel 1 and seven CpG islands, completesequence./gene="CSNK2B"/locus_tag="XXbac-BCX88C14.4-006"/standard_name="OTTHUMP00000029469"/codon_start=1/product="casein kinase 2, beta polypeptide"/protein_id="CAI17797.1"/db_xref="GI:55961590"/db_xref="GOA:Q5SRQ7"/db_xref="InterPro:IPR000704"/db_xref="UniProt/TrEMBL:Q5SRQ7"
1 1 0 2 0 1 1 3 4 3 0 2 1 3 0 1 2 1 0 1 0 1 0 1 0 5 1 3 0 1 2 2 1 0 0 1 3 0 1 0 3 3 1 6 2 0 6 7 6 2 3 2 1 2 3 1 0 5 2 4 2 1 0 0
>AY358109\AY358109\14..361\348\AAQ88476.1\Homo sapiens\Homo sapiens clone DNA129563 ACAH3104 (UNQ3104) mRNA, complete cds./locus_tag="UNQ3104"/codon_start=1/product="ACAH3104"/protein_id="AAQ88476.1"/db_xref="GI:37181324"
0 0 1 0 0 0 2 6 4 8 2 6 0 4 0 6 1 1 0 2 0 1 3 3 0 5 1 3 1 7 0 2 1 0 0 0 1 0 0 0 2 1 1 2 3 3 1 2 1 2 2 0 3 4 5 3 3 1 2 2 1 1 0 0
>BC032690\BC032690\90..1775\1686\AAH32690.1\Homo sapiens\Homo sapiens tudor and KH domain containing protein, mRNA (cDNAclone MGC:45166 IMAGE:5241008), complete cds./gene="TDRKH"/codon_start=1/product="TDRKH protein"/protein_id="AAH32690.1"/db_xref="GI:21595812"/db_xref="GeneID:11022"
2 3 9 1 10 5 6 10 13 9 7 8 9 6 0 15 11 10 14 9 1 10 12 7 1 10 15 13 0 14 11 9 8 7 6 6 13 9 16 15 5 8 3 16 4 7 27 25 19 18 6 7 3 4 3 10 8 17 12 11 8 0 0 1
>MMPLNHR\X16070\129..1247\1119\CAA34203.1\Homo sapiens\Human mRNA for pln homing receptor homologue (peripheral lymphnode)./codon_start=1/product="pln homing receptor"/protein_id="CAA34203.1"/db_xref="GI:38093"/db_xref="GOA:P14151"/db_xref="UniProt/Swiss-Prot:P14151"/IGNORED_CODON=1
1 0 1 1 5 3 2 4 6 1 5 5 8 1 0 9 7 5 4 11 1 7 9 8 0 3 10 6 1 2 13 3 7 3 1 1 6 2 12 14 16 5 4 7 3 5 12 12 7 8 7 6 9 17 12 5 6 10 9 8 15 1 0 0
>HS20I3#4\AL035423\join(36844..36909,41747..41840,43109..43256,45816..45910, 47211..47296,55205..55300,61193..61317,62106..62241, 68129..68209,69474..69515)\969\CAI42441.1\Homo sapiens\Human DNA sequence from clone RP1-20I3 on chromosome Xq25-26Contains a SNRPN upstream reading frame (SNURF) pseudogene, theSLC25A14 gene for solute carrier family 25 (mitochondrial carrier,brain),member 14 (UCP5, BMCP1), the gene for G-protein coupledreceptor 2 (GPCR2), the gene for CGI-79 protein and a CpG island,complete sequence./gene="SLC25A14"/locus_tag="RP1-20I3.5-002"/standard_name="OTTHUMP00000024013"/codon_start=1/product="solute carrier family 25 (mitochondrial carrier, brain), member 14"/protein_id="CAI42441.1"/db_xref="GI:57471622"/db_xref="GOA:O95258"/db_xref="UniProt/Swiss-Prot:O95258"
3 3 1 3 2 5 6 3 4 7 6 6 4 3 0 3 6 2 4 5 1 9 3 4 1 2 4 6 3 8 10 8 6 7 7 1 10 8 9 8 4 3 9 6 2 5 5 7 1 9 3 7 0 3 6 13 6 10 15 11 6 1 0 0
>AK125630\AK125630\854..1285\432\BAC86224.1\Homo sapiens\Homo sapiens cDNA FLJ43642 fis, clone STOMA2004925./codon_start=1/protein_id="BAC86224.1"/db_xref="GI:34531786"
0 2 1 0 0 7 7 4 7 2 1 5 0 6 1 2 1 0 1 5 1 1 3 4 0 3 1 4 0 2 3 7 3 4 0 1 4 0 1 3 2 3 1 3 2 1 4 2 4 2 0 1 5 1 2 2 2 2 0 2 5 0 0 1
>HSA488947\AJ488947\1..2568\2568\CAD35759.1\Homo sapiens\Homo sapiens mRNA for polyserase-IB protein./codon_start=1/product="polyserase-IB protein"/protein_id="CAD35759.1"/db_xref="GI:33341912"/db_xref="GOA:Q7Z410"/db_xref="UniProt/Swiss-Prot:Q7Z410"
5 6 19 2 4 13 5 16 52 5 1 6 5 17 6 8 25 5 12 33 14 7 8 29 11 18 9 47 10 18 12 36 25 5 2 18 39 4 7 23 12 3 4 26 18 2 8 35 29 2 10 4 20 12 18 7 1 24 3 13 17 0 1 0
>BC044952\BC044952\107..1729\1623\AAH44952.1\Homo sapiens\Homo sapiens KIAA1271 protein, mRNA (cDNA clone MGC:50830IMAGE:5751684), complete cds./gene="KIAA1271"/codon_start=1/product="KIAA1271 protein"/protein_id="AAH44952.1"/db_xref="GI:27924145"/db_xref="GeneID:57506"
1 2 8 5 4 8 2 13 21 4 0 6 9 20 3 10 21 6 13 19 1 5 22 22 4 21 15 19 7 9 3 18 14 5 4 6 22 3 5 10 8 11 2 14 5 3 3 31 14 6 7 3 9 1 8 4 0 9 2 6 4 0 1 0
>AY775789\AY775789\234..1013\780\AAW66851.1\Homo sapiens\Homo sapiens thymic stromal-derived lymphopoietin receptortranscript variant 2 (TSLPR) mRNA, complete cds, alternativelyspliced./gene="TSLPR"/codon_start=1/product="thymic stromal-derived lymphopoietin receptor transcript variant 2"/protein_id="AAW66851.1"/db_xref="GI:58201460"
0 1 2 0 3 3 0 9 8 3 3 3 1 9 1 5 4 2 5 6 3 1 6 9 2 2 4 7 1 1 2 3 6 3 1 4 13 2 7 7 3 2 3 11 5 1 3 16 9 6 6 3 2 3 5 5 2 4 4 6 8 0 0 1
>BC069117\BC069117\1..987\987\AAH69117.1\Homo sapiens\Homo sapiens G protein-coupled receptor 7, mRNA (cDNA cloneMGC:95396 IMAGE:7216971), complete cds./gene="GPR7"/codon_start=1/product="G protein-coupled receptor 7"/protein_id="AAH69117.1"/db_xref="GI:46575749"/db_xref="GeneID:2831"/db_xref="MIM:600730"
0 12 8 0 0 1 2 17 29 0 0 2 0 5 5 0 12 0 1 13 4 3 1 10 8 0 4 24 15 2 0 5 2 1 1 9 22 1 0 5 11 0 0 7 2 1 0 7 11 0 11 1 9 1 16 1 1 14 0 5 6 0 0 1
>S77906\S77906\161..1024\864\AAB34218.2\Homo sapiens\Pax (PAX8e)=paired box {alternatively spliced} [human, thyroid,kidney and Wilms' tumors, mRNA Partial, 1031 nt]./gene="PAX8"/codon_start=1/product="paired box protein 8 isoform 3"/protein_id="AAB34218.2"/db_xref="GI:7524546"
3 6 4 0 3 4 1 6 10 2 0 0 3 9 1 2 15 3 2 6 2 6 5 11 3 11 1 9 1 5 5 11 6 1 3 5 10 0 4 8 4 5 1 13 8 2 2 10 10 5 5 1 6 1 2 3 1 11 3 6 1 0 0 1
>BC051847\BC051847\162..1847\1686\AAH51847.1\Homo sapiens\Homo sapiens zinc finger protein 394, mRNA (cDNA clone MGC:60166IMAGE:6007172), complete cds./gene="ZNF394"/codon_start=1/product="zinc finger protein 99"/protein_id="AAH51847.1"/db_xref="GI:30354282"/db_xref="GeneID:84124"
5 9 4 4 15 10 6 10 18 8 1 7 5 12 2 8 10 16 5 11 2 5 4 15 7 4 4 6 10 7 9 5 17 4 0 2 16 2 20 17 8 10 13 23 20 10 27 33 17 3 3 5 6 16 11 8 1 7 6 5 7 1 0 0
>AC097173\AC097173 AC007512\complement(join(131051..131223,131807..131910, 132908..133028,136605..136751,137595..137667))\618\AAY40945.1\Homo sapiens\Homo sapiens BAC clone RP11-96A1 from 4, complete sequence./gene="tmp_locus_1"/codon_start=1/product="unknown"/protein_id="AAY40945.1"/db_xref="GI:63991993"
1 2 1 3 3 0 1 3 9 3 2 3 6 1 1 4 3 2 4 4 1 6 3 1 0 2 2 3 1 2 3 2 1 1 4 3 7 5 10 3 1 6 1 10 1 0 11 7 4 7 4 3 0 3 3 6 2 9 6 2 3 0 0 1
>HUMCMYBLA\M15024\114..2036\1923\AAA52032.1\Homo sapiens\Human c-myb mRNA, complete cds./gene="MYB"/codon_start=1/protein_id="AAA52032.1"/db_xref="GI:180660"/db_xref="GDB:G00-119-441"
6 0 4 4 11 6 8 8 15 4 9 8 8 12 2 14 11 8 17 13 2 12 15 9 4 19 17 11 3 9 11 3 6 6 6 6 10 12 23 21 14 18 10 26 18 10 35 16 14 18 7 7 4 5 7 9 5 8 12 12 12 0 0 1
>AF150100\AF150100\218..487\270\AAD40006.1\Homo sapiens\Homo sapiens small zinc finger-like protein (TIM9a) mRNA, completecds./gene="TIM9a"/codon_start=1/product="small zinc finger-like protein"/protein_id="AAD40006.1"/db_xref="GI:5107188"
1 0 0 0 3 0 0 1 2 2 2 1 1 1 0 1 0 0 4 4 0 0 2 0 0 1 3 2 0 1 1 1 1 0 1 0 0 1 7 1 0 2 3 6 0 2 7 2 2 1 1 2 2 2 1 4 3 0 1 3 0 0 1 0
>BC008833\BC008833\154..1431\1278\AAH08833.1\Homo sapiens\Homo sapiens hypothetical protein FLJ20291, mRNA (cDNA cloneMGC:12612 IMAGE:4304656), complete cds./gene="FLJ20291"/codon_start=1/product="hypothetical protein FLJ20291"/protein_id="AAH08833.1"/db_xref="GI:14250728"/db_xref="GeneID:54883"
5 3 12 3 14 12 1 5 14 5 4 4 5 15 2 9 10 5 3 3 0 3 7 4 1 5 7 8 1 4 4 6 9 5 2 4 6 3 21 38 9 7 5 11 7 7 11 39 9 6 5 3 1 0 2 3 0 8 2 14 4 0 0 1
>BC018538\BC018538\52..537\486\AAH18538.1\Homo sapiens\Homo sapiens arachidonate 5-lipoxygenase-activating protein, mRNA(cDNA clone MGC:17120 IMAGE:4342203), complete cds./gene="ALOX5AP"/codon_start=1/product="arachidonate 5-lipoxygenase-activating protein"/protein_id="AAH18538.1"/db_xref="GI:17391275"/db_xref="GeneID:241"/db_xref="MIM:603700"
0 1 1 0 1 4 3 7 3 3 0 2 0 3 0 1 5 1 1 6 2 3 0 2 0 3 0 4 3 4 5 3 3 1 2 5 4 3 2 2 4 3 3 5 1 1 3 3 1 2 8 1 1 1 8 8 4 5 2 3 1 1 0 0
>BC008250\BC008250\30..794\765\AAH08250.1\Homo sapiens\Homo sapiens ethylmalonic encephalopathy 1, mRNA (cDNA cloneMGC:9282 IMAGE:3872059), complete cds./gene="ETHE1"/codon_start=1/product="ETHE1 protein"/protein_id="AAH08250.1"/db_xref="GI:14198377"/db_xref="GeneID:23474"/db_xref="MIM:608451"
0 5 8 2 1 3 0 7 17 2 1 4 0 5 2 2 5 1 6 8 1 3 4 2 0 8 0 11 4 5 4 7 9 1 1 7 5 2 2 3 4 2 1 10 8 2 2 12 9 4 4 1 3 6 9 2 1 9 2 5 0 0 0 1
>HS337O184\AL591562\69..1190\1122\CAC39140.1\Homo sapiens\Novel human gene mapping to chomosome 20./codon_start=1/product="hypothetical protein"/protein_id="CAC39140.1"/db_xref="GI:14149068"/db_xref="GOA:Q969T3"/db_xref="UniProt/Swiss-Prot:Q969T3"
2 6 18 6 0 0 0 16 32 2 0 5 3 7 1 2 9 3 1 10 2 2 8 12 5 5 9 22 3 6 3 13 7 2 0 2 7 1 2 8 3 2 4 20 7 2 5 27 22 4 3 1 3 2 7 6 0 4 1 3 5 1 0 0
>HUMDV\L23768\1..1128\1128\AAA35778.1\Homo sapiens\Human Gal beta1,3(4)GlcNAc alpha2,3-sialyltransferase mRNA,complete cds./codon_start=1/product="Gal beta 1,3 (4)GlcNAc alpha 2, 3-sialyltranferase"/protein_id="AAA35778.1"/db_xref="GI:388015"
4 10 6 0 3 0 5 11 17 3 2 7 7 6 1 5 4 3 3 8 3 2 3 8 1 7 10 13 1 6 6 17 3 1 2 5 15 3 11 12 6 8 2 6 4 0 1 19 13 5 7 8 4 1 10 12 0 16 4 8 7 0 0 1
>AL731797#1\AL731797\join(5853..6928,18235..18358,20120..20239,21032..21118, 22096..22280,22593..22755,23535..23760,27786..27907, 28856..28990,31599..31741,33235..33417,33911..34117, 35425..35666,37293..37423,38493..38981)\3633\CAI22793.1\Homo sapiens\Human DNA sequence from clone RP4-786G8 on chromosome 1 Containsthe 3' end of the HIPK1 gene for homeodomain interacting proteinkinase 1 and the gene for HNOEL-iso protein (HNOEL-iso), completesequence./gene="HIPK1"/locus_tag="RP4-786G8.2-001"/standard_name="OTTHUMP00000013763"/codon_start=1/product="homeodomain interacting protein kinase 1"/protein_id="CAI22793.1"/db_xref="GI:56206712"/db_xref="InterPro:IPR000719"/db_xref="InterPro:IPR002290"/db_xref="InterPro:IPR008271"/db_xref="InterPro:IPR011009"
7 6 4 3 10 10 15 21 32 17 6 20 26 23 7 28 37 29 32 29 2 34 34 17 7 33 20 30 7 46 21 15 17 10 10 18 28 25 17 31 20 25 26 66 20 18 21 19 15 25 21 22 12 7 12 19 5 21 24 20 8 0 1 0
>HSTRAN\X72215\1..876\876\CAA51017.1\Homo sapiens\H.sapiens mRNA for variant of transcription factor./gene="Pit-1/GHF-1 variant"/codon_start=1/product="transcription factor"/protein_id="CAA51017.1"/db_xref="GI:311926"/db_xref="GOA:P28069"/db_xref="UniProt/Swiss-Prot:P28069"
4 0 3 0 8 4 1 2 12 5 4 3 1 3 1 10 2 8 8 6 0 3 4 1 0 9 8 5 0 12 8 1 1 1 3 1 7 3 17 3 3 11 3 8 4 7 17 10 4 3 2 5 5 3 2 11 6 3 3 7 2 1 0 0
>AK057899\AK057899\406..906\501\BAB71611.1\Homo sapiens\Homo sapiens cDNA FLJ25170 fis, clone CBR08752./codon_start=1/protein_id="BAB71611.1"/db_xref="GI:16553878"
0 1 3 0 2 2 0 7 8 1 1 3 2 5 1 2 6 0 3 3 3 2 6 7 1 7 5 8 2 5 1 3 4 1 0 2 9 3 1 2 0 4 1 8 5 0 0 4 2 1 0 0 2 2 4 5 1 1 0 2 2 1 0 0
>BC026154\BC026154\280..1755\1476\AAH26154.1\Homo sapiens\Homo sapiens chromosome 9 open reading frame 12, mRNA (cDNA cloneMGC:26027 IMAGE:4839268), complete cds./gene="C9orf12"/codon_start=1/product="chromosome 9 open reading frame 12"/protein_id="AAH26154.1"/db_xref="GI:20072840"/db_xref="GeneID:64768"
3 6 7 1 4 7 2 9 24 9 6 5 3 5 6 5 9 7 4 7 2 6 4 7 5 11 7 12 2 3 3 10 13 2 3 11 16 4 11 28 10 6 6 17 12 4 10 23 15 10 14 6 9 8 7 14 5 6 6 11 3 1 0 0
>AL590423#3\AL590423\complement(join(3991..4221,5371..5422,6162..6271))\393\CAI41542.1\Homo sapiens\Human DNA sequence from clone RP13-364K23 on chromosome Xq22.1-23Contains the DSIPI gene for delta sleep inducing peptide,immunoreactor (DIP, GILZ, TSC-22R), the 5' end of a novel gene andtwo CpG islands, complete sequence./gene="DSIPI"/locus_tag="RP13-364K23.1-001"/standard_name="OTTHUMP00000023810"/codon_start=1/product="delta sleep inducing peptide, immunoreactor"/protein_id="CAI41542.1"/db_xref="GI:57209361"/db_xref="GOA:Q5JRJ1"/db_xref="UniProt/TrEMBL:Q5JRJ1"
1 0 0 1 1 0 1 0 11 1 0 1 0 7 0 3 3 1 0 3 0 0 3 3 0 2 1 5 2 2 2 0 1 2 0 1 10 2 0 7 4 2 1 7 1 1 3 13 2 2 1 2 0 1 4 0 1 4 0 4 0 1 0 0
>BC101154\BC101154\1..900\900\AAI01155.1\Homo sapiens\Homo sapiens cDNA clone MGC:119923 IMAGE:40015678, complete cds./codon_start=1/product="Unknown (protein for MGC:119923)"/protein_id="AAI01155.1"/db_xref="GI:71681910"
0 1 0 1 4 3 4 6 10 5 8 11 5 6 0 5 4 4 2 5 1 11 1 3 1 3 3 3 2 8 5 3 1 1 10 6 8 7 6 13 7 9 6 2 3 4 4 1 1 2 3 5 1 6 8 14 8 6 10 9 10 0 0 1
>BC013943\BC013943\73..1011\939\AAH13943.1\Homo sapiens\Homo sapiens hypothetical protein MGC24381, mRNA (cDNA cloneMGC:24381 IMAGE:4064325), complete cds./gene="MGC24381"/codon_start=1/product="hypothetical protein MGC24381"/protein_id="AAH13943.1"/db_xref="GI:15530296"/db_xref="GeneID:115939"
1 12 7 0 5 5 0 2 20 2 0 6 1 5 1 2 8 1 1 2 4 1 3 11 7 3 2 18 12 6 5 19 10 1 1 4 11 1 3 8 5 1 0 11 4 0 3 22 12 5 4 1 9 1 6 5 0 4 1 3 4 0 0 1
>BC001917\BC001917\29..1045\1017\AAH01917.1\Homo sapiens\Homo sapiens malate dehydrogenase 2, NAD (mitochondrial), mRNA(cDNA clone MGC:3559 IMAGE:2823443), complete cds./gene="MDH2"/codon_start=1/product="mitochondrial malate dehydrogenase, precursor"/protein_id="AAH01917.1"/db_xref="GI:12804929"/db_xref="GeneID:4191"/db_xref="MIM:154100"
1 4 3 0 2 0 1 8 16 4 0 2 2 8 2 4 6 0 4 15 4 1 3 9 4 4 6 20 2 10 7 11 6 4 2 10 13 6 8 18 8 5 0 9 3 2 8 8 6 7 3 2 4 4 8 4 0 17 4 6 0 0 0 1
>HSM805997\BX537890\105..914\810\CAD97885.1\Homo sapiens\Homo sapiens mRNA; cDNA DKFZp313F0536 (from clone DKFZp313F0536);complete cds./gene="DKFZp313F0536"/codon_start=1/product="hypothetical protein"/protein_id="CAD97885.1"/db_xref="GI:31873903"/db_xref="GOA:Q7Z3H8"/db_xref="InterPro:IPR007087"/db_xref="UniProt/TrEMBL:Q7Z3H8"
1 4 3 2 1 7 4 11 4 2 3 5 4 5 2 6 10 2 6 4 6 2 1 7 2 3 8 10 2 6 4 1 5 3 1 3 8 3 6 13 5 0 2 7 9 3 6 11 10 2 3 2 7 6 3 4 0 4 1 2 2 1 0 0
>AL590708#20\AL590708\complement(join(158372..158586,158674..158830, 158906..159012,159095..159197,159285..159503, 159760..159875,160312..160387,160472..160696, 161381..161494,161770..162107,162477..162564, 162759..162866,162973..163062,163868..164009, 164339..164397,166890..166996,167093..167186, 167275..167325,167592..167630,168499..168579, 168763..168822,169239..169302,169422..169465, 169725..169829,175155..175277,177198..177245))\2973\CAI13841.1\Homo sapiens\Human DNA sequence from clone RP11-395P17 on chromosome 9 Containsthe PCSCL gene for likely ortholog of rat peroxisomal Ca-dependentsolute carrier-like protein (KIAA1896), the PTGES2 gene forprostaglandin E synthase 2 (GBF1, GBF-1, C9orf15, FLJ14038), theLCN2 gene for lipocalin 2 (oncogene 24p3) (NGAL), the C9orf16 genefor chromosome 9 open reading frame 16 (MGC4639, EST00098,FLJ12823), the CIZ1 gene for Cip1-interacting zinc finger protein(LSFR1), the DNM1 gene for dynamin 1 (DNM), the GOLGA2 gene forgolgi autoantigen, golgin subfamily a, 2 (GM130, MGC20672), thegene for a novel protein and seven CpG islands, complete sequence./gene="GOLGA2"/locus_tag="RP11-395P17.5-004"/standard_name="OTTHUMP00000022234"/codon_start=1/product="golgi autoantigen, golgin subfamily a, 2"/protein_id="CAI13841.1"/db_xref="GI:55961118"/db_xref="InterPro:IPR003345"
3 13 23 4 6 16 9 17 60 10 8 14 9 7 5 11 25 7 8 18 6 11 8 12 2 16 20 36 12 25 14 12 13 10 9 8 21 4 16 41 20 16 24 87 13 5 30 111 19 15 8 6 6 5 3 6 3 11 5 25 3 1 0 0
>BC012354\BC012354\7..888\882\AAH12354.1\Homo sapiens\Homo sapiens ribosomal protein S2, mRNA (cDNA clone MGC:20390IMAGE:4564801), complete cds./gene="RPS2"/codon_start=1/product="ribosomal protein S2"/protein_id="AAH12354.1"/db_xref="GI:15214457"/db_xref="GeneID:6187"/db_xref="MIM:603624"
1 10 6 3 2 2 0 7 9 0 0 3 2 6 0 4 1 1 3 12 0 6 2 8 0 6 4 13 2 6 5 22 8 8 2 8 8 3 0 24 3 1 0 6 4 0 1 9 6 6 5 2 5 0 9 2 0 12 5 7 3 0 1 0
>BC002854\BC002854\177..1994\1818\AAH02854.1\Homo sapiens\Homo sapiens ubiquitin specific protease 2, transcript variant 1,mRNA (cDNA clone MGC:4176 IMAGE:3635143), complete cds./gene="USP2"/codon_start=1/product="ubiquitin specific protease 2, isoform a"/protein_id="AAH02854.1"/db_xref="GI:12804005"/db_xref="GeneID:9099"/db_xref="MIM:604725"
9 13 13 2 9 6 5 19 28 7 4 2 8 22 3 4 23 5 12 20 6 6 6 18 4 10 5 18 0 6 7 15 11 12 0 5 14 3 6 20 17 7 2 21 7 4 12 16 19 14 18 13 9 6 16 6 3 9 4 11 5 0 1 0
>AY189940\AY189940\21..563\543\AAO39000.1\Homo sapiens\Homo sapiens HOMER1F (HOMER1) mRNA, complete cds, alternativelyspliced./gene="HOMER1"/codon_start=1/product="HOMER1F"/protein_id="AAO39000.1"/db_xref="GI:28396185"
1 1 2 2 1 2 5 3 12 2 5 2 1 1 0 2 3 2 5 1 0 5 0 0 0 0 5 6 0 4 3 0 0 1 2 0 2 1 10 6 3 8 10 6 1 3 22 8 2 4 0 1 1 1 0 2 3 1 3 1 2 1 0 0
>HS111C20#4\AL035530\join(73239..73354,78863..78950,86368..86509,88982..89127, 90101..90304,91853..92015,94443..94529,94941..95251)\1257\CAI19235.1\Homo sapiens\Human DNA sequence from clone RP1-111C20 on chromosome 6q25.3-27Contains the gene for radial spoke protein 3 (RSP3), the TAGP genefor T-cell activation GTPase activating protein, a novel gene and aCpG island, complete sequence./gene="RSHL2"/locus_tag="RP1-111C20.2-002"/standard_name="OTTHUMP00000017517"/codon_start=1/product="radial spokehead-like 2"/protein_id="CAI19235.1"/db_xref="GI:56202997"/db_xref="InterPro:IPR009290"/db_xref="UniProt/TrEMBL:Q9BX75"
6 3 9 6 11 9 5 9 12 9 5 4 6 2 0 6 7 3 14 6 1 3 9 4 2 7 7 10 1 6 7 5 5 3 2 1 8 7 8 8 4 2 12 14 3 4 40 21 8 15 7 8 2 1 1 9 6 2 6 15 2 0 1 0
>AB042029\AB042029\407..1267\861\BAB70508.1\Homo sapiens\Homo sapiens DEPC-1 mRNA for prostate cancer antigen-1, completecds./gene="DEPC-1"/codon_start=1/product="prostate cancer antigen-1"/protein_id="BAB70508.1"/db_xref="GI:16326129"
5 4 2 1 11 3 3 3 3 4 2 4 4 1 0 3 4 2 8 6 0 5 8 7 1 9 2 5 1 8 4 4 3 3 3 2 10 4 7 8 5 4 3 11 6 5 14 10 9 5 3 8 2 2 2 5 3 4 5 4 9 0 0 1
>AB055225\AB055225\80..622\543\BAB97211.1\Homo sapiens\Homo sapiens IMAA mRNA for hLAT1-3TM, complete cds./gene="IMAA"/codon_start=1/product="hLAT1-3TM"/protein_id="BAB97211.1"/db_xref="GI:21320896"
0 2 3 0 0 0 2 9 9 0 0 0 1 3 5 0 0 0 0 5 3 0 0 4 6 1 3 13 12 0 0 16 2 1 1 5 12 0 1 9 1 0 0 2 1 1 1 11 3 0 6 0 4 0 5 0 1 10 0 4 2 0 0 1
>BC067286\BC067286\150..1373\1224\AAH67286.1\Homo sapiens\Homo sapiens melanoma antigen family B, 6, mRNA (cDNA cloneMGC:75411 IMAGE:30386334), complete cds./gene="MAGEB6"/codon_start=1/product="melanoma antigen, family B, 6 protein"/protein_id="AAH67286.1"/db_xref="GI:45501360"/db_xref="GeneID:158809"/db_xref="MIM:300467"
1 4 3 4 6 1 1 6 14 1 2 9 12 13 3 10 7 9 0 8 2 7 6 7 1 9 6 12 3 11 4 10 4 13 3 5 10 10 10 18 7 2 6 14 2 4 10 21 3 22 6 8 3 5 5 3 2 6 5 6 2 1 0 0
>HUMEPI\D14582\96..995\900\BAA03436.1\Homo sapiens\Homo sapiens mRNA for epimorphin, complete cds./codon_start=1/product="epimorphin"/protein_id="BAA03436.1"/db_xref="GI:303605"
2 3 7 2 6 2 2 1 10 3 1 3 5 2 2 3 5 4 4 4 1 8 4 0 1 0 4 4 3 7 3 2 4 1 3 1 8 8 14 11 7 7 4 8 3 4 16 17 9 11 1 5 0 1 5 5 7 9 9 11 2 0 0 1
>HUMIGHWD\M36530\join(87..132,236..546)\357\AAA36064.1\Homo sapiens\Human Ig germline heavy-chain gene V region./codon_start=1/protein_id="AAA36064.1"/db_xref="GI:185628"
0 1 0 0 5 0 1 1 6 2 2 4 3 0 0 4 4 2 1 3 2 0 0 0 0 1 0 2 1 6 2 2 5 3 1 3 3 2 5 1 3 0 2 4 1 0 1 6 2 1 3 3 0 3 3 1 1 1 1 3 2 0 0 0
>BC038971\BC038971\205..1176\972\AAH38971.1\Homo sapiens\Homo sapiens family with sequence similarity 49, member A, mRNA(cDNA clone MGC:47569 IMAGE:5200807), complete cds./gene="FAM49A"/codon_start=1/product="family with sequence similarity 49, member A"/protein_id="AAH38971.1"/db_xref="GI:24658571"/db_xref="GeneID:81553"
4 2 0 0 6 7 4 5 12 9 2 3 1 4 0 3 5 6 9 6 2 5 7 2 2 3 6 8 1 6 4 3 1 0 0 8 6 2 10 7 10 11 3 11 6 2 17 13 7 6 6 3 5 2 7 8 2 9 8 14 2 0 1 0
>BC098164\BC098164\70..513\444\AAH98164.1\Homo sapiens\Homo sapiens family with sequence similarity 12, member A, mRNA(cDNA clone MGC:119848 IMAGE:40014621), complete cds./gene="FAM12A"/codon_start=1/product="human epididymis-specific 3 alpha, precursor"/protein_id="AAH98164.1"/db_xref="GI:68532413"/db_xref="GeneID:10876"
2 0 0 1 4 3 1 4 4 3 2 1 0 1 0 1 7 3 2 0 0 0 2 0 0 1 2 3 0 1 1 3 1 1 4 1 0 1 7 4 5 3 0 1 1 3 6 6 2 3 7 4 3 4 6 1 4 4 5 3 5 0 1 0
>BC010858\BC010858\123..2378\2256\AAH10858.1\Homo sapiens\Homo sapiens enhancer of zeste homolog 2 (Drosophila), transcriptvariant 1, mRNA (cDNA clone MGC:9169 IMAGE:3901250), complete cds./gene="EZH2"/codon_start=1/product="enhancer of zeste 2, isoform a"/protein_id="AAH10858.1"/db_xref="GI:14790029"/db_xref="GeneID:2146"/db_xref="MIM:601573"
6 6 9 5 17 10 6 6 11 5 6 8 8 7 4 13 9 10 8 10 3 13 18 9 2 16 15 8 0 18 12 10 10 6 5 5 17 8 32 29 18 22 10 23 7 10 43 19 15 38 9 14 13 22 7 24 11 9 17 13 7 0 0 1
>AK001783\AK001783\111..842\732\BAA91908.1\Homo sapiens\Homo sapiens cDNA FLJ10921 fis, clone OVARC1000411./codon_start=1/protein_id="BAA91908.1"/db_xref="GI:7023271"
2 0 0 0 4 3 0 3 5 2 5 5 3 1 0 8 1 4 7 1 0 6 7 0 1 4 7 1 0 3 4 0 1 2 6 4 6 7 13 6 1 6 4 5 6 2 24 14 2 8 3 3 1 2 5 3 5 1 8 6 2 1 0 0
>HSU78576\U78576\422..2110\1689\AAC50911.1\Homo sapiens\Human 68 kDa type I phosphatidylinositol-4-phosphate 5-kinase alphamRNA, clone PIP5KIa2, complete cds./EC_number="2.7.1.68"/codon_start=1/product="68 kDa type I phosphatidylinositol-4-phosphate 5-kinase alpha"/protein_id="AAC50911.1"/db_xref="GI:1743873"
5 3 11 4 5 2 6 7 12 8 5 14 13 15 6 13 7 12 12 11 0 9 7 10 3 17 10 9 3 9 8 13 5 10 3 7 11 9 15 20 9 4 7 14 5 10 13 20 13 15 15 9 3 5 16 11 3 13 12 15 1 1 0 0
>AF075171\AF075171\928..1233\306\AAC69326.1\Homo sapiens\Homo sapiens nonsyndromic hearing impairment protein (DFNA5) mRNA,short form, complete cds./gene="DFNA5"/codon_start=1/product="nonsyndromic hearing impairment protein"/protein_id="AAC69326.1"/db_xref="GI:3777547"
0 1 0 1 2 1 0 2 10 4 1 3 3 0 0 4 1 1 2 2 0 2 3 2 0 0 2 1 0 5 2 2 1 0 1 2 2 0 4 2 0 1 0 2 1 1 3 1 3 5 0 0 3 2 1 2 1 1 4 1 0 0 0 1
>AL158151#2\AL158151\complement(join(2878..3093,3479..3616,4731..4793, 5494..5629,5730..5852,6012..6131,7347..7447,7992..8170, 9364..9538,9881..10046,10494..10547,11669..11787, 15295..15558,17964..17990))\1881\CAI12869.1\Homo sapiens\Human DNA sequence from clone RP11-247A12 on chromosome 9 Containsthe CRAT gene for carnitine acetyltransferase (CAT1), the PPP2R4gene for protein phosphatase 2A, regulatory subunit B' (PR 53)(PTPA), the IER5L gene for immediate early response 5-like, a novelgene and three CpG islands, complete sequence./gene="CRAT"/locus_tag="RP11-247A12.5-001"/standard_name="OTTHUMP00000022327"/codon_start=1/product="carnitine acetyltransferase"/protein_id="CAI12869.1"/db_xref="GI:55958023"/db_xref="GOA:Q5T952"/db_xref="InterPro:IPR000542"/db_xref="UniProt/TrEMBL:Q5T952"
4 12 8 2 0 5 4 14 40 3 1 4 4 17 4 2 16 3 3 22 5 1 4 23 1 7 8 28 6 6 3 13 10 4 2 12 30 0 4 37 19 0 0 32 17 4 3 28 23 12 20 4 5 3 19 9 0 26 3 20 7 0 0 1
>AK027309\AK027309\13..984\972\BAB55032.1\Homo sapiens\Homo sapiens cDNA FLJ14403 fis, clone HEMBA1003805, highly similarto Mus musculus KH domain RNA binding protein QKI-5A mRNA./codon_start=1/protein_id="BAB55032.1"/db_xref="GI:14041905"
3 0 2 2 8 5 2 3 8 8 6 5 3 0 0 1 4 3 7 6 1 6 10 5 1 14 11 8 3 11 6 7 4 3 5 3 6 6 13 8 7 7 5 6 3 3 15 9 6 7 6 4 1 1 2 3 3 9 7 11 1 1 0 0
>AL590808#2\AL590808\join(67396..68038,77966..78108,80405..80597,87940..88048, 88247..88338,88445..88567,91858..91962,93075..93239, 94842..95002,95867..96036,AL606833.8:3444..3517, AL606833.8:17146..17436,AL606833.8:24294..24461, AL606833.8:33259..33389)\-240792\CAI41594.1\Homo sapiens\Human DNA sequence from clone RP13-483F6 on chromosome X Contains aserine or cysteine proteinase inhibitor clade A (alpha-1antiproteinase, antitrypsin) member 7 (SERPINA7) pseudogene and the5' end of gene FLJ10178, complete sequence./gene="RP11-647M7.1"/locus_tag="RP11-647M7.1-002"/standard_name="OTTHUMP00000023784"/codon_start=1/product="novel protein"/protein_id="CAI41594.1"/db_xref="GI:57209435"/db_xref="GOA:Q5JQS1"/db_xref="UniProt/TrEMBL:Q5JQS1"
4 4 5 3 22 15 5 4 18 17 15 16 22 9 6 18 9 16 17 9 3 14 23 21 4 16 10 5 3 12 9 9 13 10 8 9 19 15 33 27 14 30 20 20 9 12 30 20 12 21 10 22 8 9 6 20 15 13 31 14 14 4 1 4
>HSA271671\AJ271671\88..1062\975\CAB82784.1\Homo sapiens\Homo sapiens mRNA for IRT1 protein./gene="Irt1"/function="unknown"/codon_start=1/product="IRT1 protein"/protein_id="CAB82784.1"/db_xref="GI:7330679"/db_xref="GOA:Q9NY26"/db_xref="UniProt/TrEMBL:Q9NY26"
1 3 4 1 0 3 4 14 43 1 0 6 6 4 1 2 5 2 4 4 1 2 7 5 2 6 8 15 4 12 5 10 12 2 4 5 16 0 1 4 1 1 3 12 5 3 3 16 3 2 2 1 3 5 9 4 1 11 1 6 3 0 1 0
>AK128756\AK128756\747..1292\546\BAC87601.1\Homo sapiens\Homo sapiens cDNA FLJ44869 fis, clone BRAMY2015516./codon_start=1/protein_id="BAC87601.1"/db_xref="GI:34536289"
0 0 0 1 0 1 4 3 18 6 0 8 1 5 0 5 1 0 0 5 0 1 4 14 1 25 2 16 1 1 0 6 0 4 0 2 0 2 1 0 0 0 0 0 2 1 0 1 1 0 2 1 9 2 1 3 1 2 0 3 14 0 0 1
>AK027269\AK027269\44..1396\1353\BAB55010.1\Homo sapiens\Homo sapiens cDNA FLJ14363 fis, clone HEMBA1000719./codon_start=1/protein_id="BAB55010.1"/db_xref="GI:14041843"
2 26 7 1 0 3 3 9 37 6 0 2 3 8 8 4 9 1 2 7 3 1 3 15 8 3 2 20 19 7 2 22 10 2 1 12 20 2 3 7 8 1 1 12 20 2 3 24 25 3 16 0 6 1 8 2 0 8 0 3 7 0 0 1
>BC026167\BC026167\43..621\579\AAH26167.1\Homo sapiens\Homo sapiens similar to CG9643-PA, mRNA (cDNA clone MGC:26857IMAGE:4823003), complete cds./gene="LOC399818"/codon_start=1/product="LOC399818 protein"/protein_id="AAH26167.1"/db_xref="GI:20071183"/db_xref="GeneID:399818"
2 1 1 0 1 3 1 2 5 4 2 2 1 2 3 8 2 3 2 1 0 4 1 1 1 2 3 1 4 4 7 6 3 6 2 3 4 2 7 6 2 7 2 3 1 2 8 5 6 6 1 3 0 1 4 7 3 1 10 4 3 1 0 0
>HSAB5104\Z15143\1..1089\1089\CAA78849.1\Homo sapiens\H.sapiens mRNA for MHC class I HLA-B*5104./codon_start=1/product="MCH class I HLA-B*5104"/protein_id="CAA78849.1"/db_xref="GI:28235"/db_xref="GOA:P30489"/db_xref="UniProt/Swiss-Prot:P30489"
2 8 6 1 6 7 1 8 17 1 0 0 1 7 0 7 6 2 6 16 3 4 4 8 4 2 5 12 12 8 5 11 10 1 1 6 16 2 2 7 7 0 1 19 6 4 1 24 15 4 12 3 4 1 7 0 1 10 2 5 11 0 0 1
>AY590469\AY590469\join(1898..3116,3346..3569,6609..6687,7047..7191, 9500..9690,11892..12031,13632..13829,14388..14656, 16654..16816,20076..20236,21052..21293,21695..21897, 23002..23102,25808..25939,26313..26426,28128..28280, 30249..30446,32391..32459,32709..32843,35555..35708, 40384..40642,40866..40963,42074..42464,43549..43806, 44340..44469,46254..46460,50292..50442,51846..52004)\5943\AAS89300.1\Homo sapiens\Homo sapiens MCM3 minichromosome maintenance deficient 3 (S.cerevisiae) associated protein (MCM3AP) gene, complete cds./gene="MCM3AP"/codon_start=1/product="MCM3 minichromosome maintenance deficient 3 (S. cerevisiae) associated protein"/protein_id="AAS89300.1"/db_xref="GI:46361510"
7 13 22 10 25 36 14 37 96 29 12 26 28 36 10 52 44 42 24 35 12 23 36 41 8 45 33 37 23 50 30 36 31 21 14 22 71 26 37 64 33 26 19 86 30 18 53 100 51 39 19 5 18 24 35 53 11 24 23 36 19 0 0 1
>AY598792\AY598792\1..690\690\AAT09203.1\Homo sapiens\Homo sapiens HBV X-transactivated protein 12 mRNA, complete cds./codon_start=1/product="HBV X-transactivated protein 12"/protein_id="AAT09203.1"/db_xref="GI:47054187"
2 1 2 2 4 3 3 6 6 4 2 2 2 4 0 5 3 1 2 2 0 3 5 0 0 6 2 2 0 5 1 2 1 2 4 3 4 4 11 11 5 5 1 13 3 4 9 8 6 7 1 6 2 2 5 9 2 5 5 6 3 0 1 0
>HSDJ559A3#5\AL117348\complement(join(73022..73171,74203..74211,74425..74646, 74771..74947))\558\CAI21800.1\Homo sapiens\Human DNA sequence from clone RP4-559A3 on chromosome 1q41-42.2Contains the 5' end of a novel gene (KIAA0792), the LEFTB gene forleft-right determination, factor B, the PYCR2 gene forpyrroline-5-carboxylate reductase family, member 2, the EBAF genefor endometrial bleeding associated factor (left-rightdetermination, factor A; transforming growth factor betasuperfamily), a novel gene, an NADH dehydrogenase (ubiquinone) 1alpha subcomplex, 3, 9kDa (NDUFA3) pseudogene and two CpG islands,complete sequence./gene="PYCR2"/locus_tag="RP4-559A3.4-003"/standard_name="OTTHUMP00000035615"/codon_start=1/product="pyrroline-5-carboxylate reductase family, member 2"/protein_id="CAI21800.1"/db_xref="GI:56203953"/db_xref="GOA:Q5TE93"/db_xref="InterPro:IPR000304"/db_xref="UniProt/TrEMBL:Q5TE93"
0 2 0 0 3 0 0 7 11 1 1 0 0 5 0 1 8 1 6 5 3 1 4 4 0 2 2 10 1 4 1 5 5 2 1 5 14 0 1 12 3 0 2 4 2 2 4 7 6 3 1 1 2 1 4 1 0 7 2 5 0 1 0 0
>HSU96759\U96759\319..801\483\AAC23907.1\Homo sapiens\Homo sapiens von Hippel-Lindau binding protein (VBP-1) mRNA,complete cds./gene="VBP-1"/codon_start=1/product="von Hippel-Lindau binding protein"/protein_id="AAC23907.1"/db_xref="GI:2738244"
1 0 0 0 4 2 2 1 5 5 2 5 2 2 1 1 0 0 3 5 0 4 0 0 0 4 4 2 0 4 0 0 2 1 3 1 1 2 11 10 5 6 2 7 0 0 9 4 3 10 2 4 1 1 1 3 0 0 4 6 2 1 0 0
>HSA133005\AJ133005\5..2212\2208\CAB40813.1\Homo sapiens\Homo sapiens mRNA for fertilin beta sperm protein./gene="fertilin beta"/function="sperm surface protein"/codon_start=1/product="fertilin beta protein"/protein_id="CAB40813.1"/db_xref="GI:4585655"/db_xref="GOA:Q99965"/db_xref="InterPro:IPR001590"/db_xref="InterPro:IPR001762"/db_xref="InterPro:IPR002870"/db_xref="InterPro:IPR006025"/db_xref="InterPro:IPR006209"/db_xref="InterPro:IPR006586"/db_xref="UniProt/Swiss-Prot:Q99965"
0 3 2 1 13 5 3 6 11 9 18 7 22 6 1 10 7 19 12 3 1 13 13 3 2 14 16 7 0 11 19 7 12 12 11 3 10 22 30 14 11 25 20 14 8 12 33 13 12 25 9 20 17 26 10 28 15 3 32 16 8 0 1 0
>AY255768\AY255768\1..1113\1113\AAP13479.1\Homo sapiens\Homo sapiens NADPH oxidase regulatory protein (NOXO1) mRNA,complete cds./gene="NOXO1"/codon_start=1/product="NADPH oxidase regulatory protein"/protein_id="AAP13479.1"/db_xref="GI:30102430"
3 21 13 1 1 7 3 8 27 2 0 3 4 5 1 5 12 2 1 11 8 2 7 16 9 6 7 11 13 4 4 18 8 2 0 1 17 2 0 4 1 0 4 16 3 0 6 17 13 3 4 1 5 2 10 3 0 5 0 1 7 0 0 1
>HSA010119\AJ010119\66..2384\2319\CAA09009.1\Homo sapiens\Homo sapiens mRNA for Ribosomal protein kinase B (RSK-B)./gene="rsk-b"/function="CREB-Kinase"/codon_start=1/evidence=experimental/product="Ribosomal protein kinase B (RSK-B)"/protein_id="CAA09009.1"/db_xref="GI:3452409"/db_xref="GOA:O75676"/db_xref="InterPro:IPR000719"/db_xref="InterPro:IPR000961"/db_xref="InterPro:IPR008271"/db_xref="InterPro:IPR011009"/db_xref="UniProt/Swiss-Prot:O75676"
7 24 25 1 0 4 0 17 66 2 0 3 3 14 9 4 20 2 1 10 16 1 5 31 5 9 9 31 18 10 4 30 26 5 1 10 38 0 5 31 14 3 2 36 18 3 9 51 26 6 15 2 7 3 31 5 0 20 5 13 6 1 0 0
>AF248484\AF248484\complement(124276..127752)\3477\AAF62185.1\Homo sapiens\Homo sapiens chromosome 21 PAC 30P13 map 21q11.2, completesequence, containing gene for nuclear factor RIP140./gene="nuclear factor RIP140"/codon_start=1/product="nuclear factor RIP140"/protein_id="AAF62185.1"/db_xref="GI:7407669"
5 1 2 1 22 12 12 11 24 26 25 22 30 12 1 40 33 46 22 8 5 27 25 10 3 31 30 15 1 26 21 11 11 15 8 8 19 20 61 31 28 54 27 32 20 14 54 23 15 37 7 15 5 9 7 17 10 8 11 26 6 1 0 0
>BC042047\BC042047\60..3128\3069\AAH42047.2\Homo sapiens\Homo sapiens hect domain and RLD 6, transcript variant 1, mRNA(cDNA clone MGC:50367 IMAGE:5531519), complete cds./gene="HERC6"/codon_start=1/product="hect domain and RLD 6, isoform a"/protein_id="AAH42047.2"/db_xref="GI:66840150"/db_xref="GeneID:55008"/db_xref="MIM:609249"
3 8 3 4 22 9 10 19 40 13 15 10 14 16 5 19 15 19 14 12 3 20 20 7 3 20 19 12 5 25 28 8 18 9 6 10 21 17 36 34 21 17 21 28 18 15 46 20 16 31 7 16 8 18 24 31 23 9 22 28 12 1 0 0
>BC051856\BC051856\311..1246\936\AAH51856.1\Homo sapiens\Homo sapiens hypothetical protein FLJ12505, mRNA (cDNA cloneMGC:60211 IMAGE:6067012), complete cds./gene="FLJ12505"/codon_start=1/product="hypothetical protein FLJ12505"/protein_id="AAH51856.1"/db_xref="GI:30354003"/db_xref="GeneID:79805"
2 4 7 0 4 9 1 5 15 0 1 3 5 5 2 2 12 2 1 8 1 4 3 10 2 7 4 9 3 3 3 12 6 0 0 7 9 1 8 17 5 4 2 7 12 2 3 12 11 1 9 3 2 0 6 5 2 8 5 11 4 0 1 0
>AK056449\AK056449\58..480\423\BAB71185.1\Homo sapiens\Homo sapiens cDNA FLJ31887 fis, clone NT2RP7003050./codon_start=1/protein_id="BAB71185.1"/db_xref="GI:16551854"
3 2 4 2 0 5 0 2 4 2 0 0 1 4 1 1 6 2 2 2 1 3 5 7 2 4 4 4 8 2 6 3 8 4 0 1 4 1 0 2 0 0 0 1 4 0 1 4 1 0 0 0 3 2 1 0 0 0 0 2 9 0 1 0
>AY358204\AY358204\111..590\480\AAQ88571.1\Homo sapiens\Homo sapiens clone DNA131647 SQAW5801 (UNQ5801) mRNA, complete cds./locus_tag="UNQ5801"/codon_start=1/product="SQAW5801"/protein_id="AAQ88571.1"/db_xref="GI:37181520"
0 1 1 0 2 4 0 3 10 2 0 1 0 4 0 1 5 1 1 2 0 1 6 15 2 3 1 3 2 3 1 6 2 2 1 5 3 0 3 3 3 0 2 2 0 0 3 7 3 2 2 1 8 4 8 1 0 8 3 1 1 0 0 1
>HSU71092\U71092\382..1590\1209\AAC14587.1\Homo sapiens\Homo sapiens somatostatin receptor-like protein (GPR24) gene,complete cds./gene="GPR24"/codon_start=1/product="somatostatin receptor-like protein"/protein_id="AAC14587.1"/db_xref="GI:1737179"
0 11 3 0 3 7 1 16 19 2 1 5 5 10 4 3 12 2 5 14 7 3 3 10 1 7 5 19 2 4 4 9 10 4 2 9 16 1 3 10 12 4 1 12 6 2 4 7 6 3 10 3 7 3 13 8 1 27 3 12 6 0 0 1
>AF431970\AF431970\43..1308\1266\AAM44214.1\Homo sapiens\Homo sapiens putative nucleoporin protein SEH1B (SEH1) mRNA,complete cds./gene="SEH1"/codon_start=1/product="putative nucleoporin protein SEH1B"/protein_id="AAM44214.1"/db_xref="GI:21239233"
4 2 4 2 7 4 4 5 5 5 4 5 7 8 1 16 11 10 9 6 1 9 6 4 0 16 9 5 3 14 10 1 7 7 7 5 9 7 9 10 4 16 0 13 7 9 11 4 6 19 0 8 2 8 6 8 5 7 7 9 14 1 0 0
>AB009589\AB009589\join(8540..9479,10624..10949)\1266\BAA23982.1\Homo sapiens\Homo sapiens gene for Osteomodulin, complete cds./codon_start=1/product="Osteomodulin"/protein_id="BAA23982.1"/db_xref="GI:2696502"
1 1 0 2 5 1 13 8 4 15 6 4 8 1 0 8 4 5 6 1 0 9 15 2 1 9 4 1 0 4 5 1 2 6 4 2 4 4 18 6 9 24 17 6 9 12 26 4 10 16 10 15 4 5 12 13 6 6 14 12 1 0 1 0
>AK131376\AK131376\220..585\366\BAD18527.1\Homo sapiens\Homo sapiens cDNA FLJ16434 fis, clone BRACE3015829./codon_start=1/protein_id="BAD18527.1"/db_xref="GI:47077213"
0 0 0 1 1 1 0 2 2 4 3 2 1 6 0 4 3 3 0 1 1 2 5 1 0 5 3 3 1 0 2 3 1 1 3 2 3 0 10 4 0 1 2 5 1 2 2 3 0 3 0 2 1 2 1 1 3 0 0 5 3 0 0 1
>BC002618\BC002618\127..1044\918\AAH02618.1\Homo sapiens\Homo sapiens serine/threonine kinase 16, transcript variant 2, mRNA(cDNA clone MGC:1953 IMAGE:3143105), complete cds./gene="STK16"/codon_start=1/product="serine/threonine kinase 16"/protein_id="AAH02618.1"/db_xref="GI:12803571"/db_xref="GeneID:8576"/db_xref="MIM:604719"
3 4 5 1 3 3 4 9 18 5 2 4 1 4 1 3 3 3 0 6 1 3 5 4 1 4 3 11 2 5 3 7 6 6 0 4 10 1 2 8 4 5 7 14 7 8 5 13 11 5 4 4 5 4 9 1 2 11 3 9 6 0 0 1
>BC020750\BC020750\122..778\657\AAH20750.1\Homo sapiens\Homo sapiens serine dehydratase, mRNA (cDNA clone MGC:22597IMAGE:4662951), complete cds./gene="SDS"/codon_start=1/product="SDS protein"/protein_id="AAH20750.1"/db_xref="GI:18088452"/db_xref="GeneID:10993"/db_xref="MIM:182128"
0 1 1 1 0 3 1 5 10 1 1 1 1 6 1 1 4 1 3 8 0 1 0 9 2 2 4 14 5 4 2 13 5 4 0 8 10 0 3 12 3 1 2 3 5 1 5 7 4 2 2 1 2 2 4 3 0 8 3 7 5 0 0 1
>AK075142\AK075142\300..2600\2301\BAC11431.1\Homo sapiens\Homo sapiens cDNA FLJ90661 fis, clone PLACE1005003, weakly similarto PROSTASIN PRECURSOR (EC 3.4.21.-)./codon_start=1/protein_id="BAC11431.1"/db_xref="GI:22761041"
4 19 11 2 3 6 5 20 60 2 1 6 6 12 7 3 19 3 6 13 4 10 15 40 12 15 12 38 13 14 13 34 21 6 3 13 31 2 1 4 10 3 4 30 15 6 11 39 19 4 9 4 19 13 8 7 2 15 3 7 29 0 0 1
>HSLTKM\X52213\259..1653\1395\CAA36460.1\Homo sapiens\H.sapiens ltk mRNA./gene="ltk"/codon_start=1/protein_id="CAA36460.1"/db_xref="GI:34422"/db_xref="GOA:P29376"/db_xref="UniProt/Swiss-Prot:P29376"
3 7 7 3 3 9 2 17 40 7 0 4 5 9 1 6 10 5 5 8 1 4 14 13 3 15 3 17 0 2 6 15 16 4 2 5 13 5 2 14 5 5 2 19 7 2 5 21 10 7 6 6 7 3 7 5 1 10 6 16 9 0 0 1
>AF159174\AF159174\37..831\795\AAL25998.1\Homo sapiens\Homo sapiens small intestine aquaporin mRNA, complete cds./codon_start=1/product="small intestine aquaporin"/protein_id="AAL25998.1"/db_xref="GI:16564853"
0 2 4 1 1 1 1 14 19 1 1 3 2 6 1 5 1 1 5 8 1 2 3 4 1 8 2 17 1 9 5 10 8 8 1 7 10 4 1 4 8 2 1 6 3 1 3 4 3 2 4 4 4 1 8 4 2 6 4 8 3 1 0 0
>BC056402\BC056402\237..1382\1146\AAH56402.1\Homo sapiens\Homo sapiens hypothetical protein BC007540, mRNA (cDNA cloneMGC:50858 IMAGE:5764461), complete cds./gene="LOC144097"/codon_start=1/product="hypothetical protein LOC144097"/protein_id="AAH56402.1"/db_xref="GI:33880045"/db_xref="GeneID:144097"
1 4 5 2 8 6 2 12 9 3 0 4 4 5 5 4 12 2 4 8 2 3 18 18 8 9 9 15 2 6 6 13 8 2 1 6 14 3 6 11 4 3 3 12 7 0 9 29 20 4 0 0 3 2 7 0 0 5 1 7 5 1 0 0
>AK026909\AK026909\149..1588\1440\BAB15588.1\Homo sapiens\Homo sapiens cDNA: FLJ23256 fis, clone COL05534./codon_start=1/protein_id="BAB15588.1"/db_xref="GI:10439879"
5 3 6 5 13 7 4 3 11 7 4 13 5 8 2 6 5 6 4 6 2 3 9 6 0 3 12 11 2 14 10 5 6 6 4 5 11 10 23 27 3 10 11 11 1 4 23 38 11 27 8 7 1 1 1 5 3 5 10 3 4 0 0 1
>BC009393\BC009393\136..603\468\AAH09393.1\Homo sapiens\Homo sapiens HIV-1 Rev binding protein-like, mRNA (cDNA cloneIMAGE:4135946), complete cds./gene="HRBL"/codon_start=1/product="HRBL protein"/protein_id="AAH09393.1"/db_xref="GI:14424764"/db_xref="GeneID:3268"/db_xref="MIM:604019"
0 2 4 3 2 3 0 2 5 2 1 1 1 4 1 1 3 0 2 5 0 2 3 1 2 3 0 3 5 1 1 8 5 2 3 3 7 1 2 8 2 1 2 4 1 1 2 9 1 4 1 1 8 0 5 2 0 2 1 3 3 0 0 1
>HSU34625\U34625\121..1908\1788\AAA86419.1\Homo sapiens\Human T cell surface glycoprotein CD-6 mRNA, complete cds./codon_start=1/product="T cell surface glycoprotein CD6"/protein_id="AAA86419.1"/db_xref="GI:1015968"
2 8 10 2 1 8 1 20 23 3 0 9 9 20 5 7 18 8 7 10 3 7 15 17 9 11 11 27 9 5 7 20 21 2 2 9 19 3 4 4 17 5 2 22 13 4 6 41 18 6 9 1 23 4 11 3 3 8 3 5 15 0 1 0
>HUMFERL\M11147\152..679\528\AAA52439.1\Homo sapiens\Human ferritin L chain mRNA, complete cds./gene="FTL"/codon_start=1/protein_id="AAA52439.1"/db_xref="GI:182514"/db_xref="GDB:G00-119-234"
0 5 0 3 0 2 1 8 13 3 0 2 0 3 0 2 3 0 0 4 1 2 2 1 1 0 1 9 0 5 0 7 1 4 0 2 4 0 3 9 4 2 1 6 5 2 5 11 8 5 4 3 0 1 8 0 0 2 1 5 1 1 0 0
>AF527578\AF527578\1..1413\1413\AAN37810.1\Homo sapiens\Homo sapiens mutant desmin mRNA, complete cds./codon_start=1/product="mutant desmin"/protein_id="AAN37810.1"/db_xref="GI:23506465"
5 20 13 1 1 3 1 16 26 2 0 4 2 11 7 6 7 3 2 13 6 4 1 3 5 1 4 24 8 7 1 12 6 2 0 6 21 0 1 21 17 3 1 31 2 4 12 45 18 5 13 1 1 0 10 2 0 11 7 10 1 1 0 0
>CR456941\CR456941\1..996\996\CAG33222.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834A075D forgene RABGGTB, Rab geranylgeranyltransferase, beta subunit; completecds, incl. stopcodon./gene="RABGGTB"/codon_start=1/protein_id="CAG33222.1"/db_xref="GI:48145999"
1 1 0 1 7 2 3 2 6 10 8 9 5 4 0 6 0 7 4 1 2 4 4 1 2 6 8 0 1 9 14 5 4 7 4 3 7 7 7 8 1 9 5 8 0 9 16 6 6 16 3 8 5 7 2 11 2 6 15 9 7 1 0 0
>HSJ244F24#1\AL096865\join(complement(121800..121937), complement(121476..121599),complement(27303..27667), complement(18241..18397),complement(12209..12313), AL358135.19:34471..34644,AL161907.17:5353..5514, AL161907.17:38324..38389,AL161907.17:39934..40412)\138\CAI19932.1\Homo sapiens\Human DNA sequence from clone RP1-244F24 on chromosome 6p12.3-21.2Contains the 5' end of the RUNX2 gene for runt-relatedtranscription factor 2, the 3' end of the SUPT3H gene forsuppressor of Ty 3 homolog (S. cerevisiae) and three CpG islands,complete sequence./gene="RUNX2"/locus_tag="RP1-166H4.1-002"/standard_name="OTTHUMP00000016533"/codon_start=1/protein_id="CAI19932.1"/db_xref="GI:56203978"/db_xref="GOA:Q5T802"/db_xref="InterPro:IPR000040"/db_xref="UniProt/TrEMBL:Q5T802"
3 3 16 2 12 11 8 6 21 12 6 2 10 12 5 8 30 8 15 7 6 7 12 5 7 6 12 7 1 4 13 8 4 8 8 5 8 8 16 17 15 7 13 13 9 7 11 13 5 7 4 6 13 8 6 13 5 7 11 16 20 6 5 11
>BX248519#1\BX248519\join(5137..5235,5322..5427,5675..6087)\618\CAI41939.1\Homo sapiens\Human DNA sequence from clone DASS-280D8 on chromosome 6 Containsthe LTA gene for lymphotoxin alpha (TNF superfamily, member 1), theTNF gene for tumor necrosis factor (TNF superfamily, member 2), theLTB gene for lymphotoxin beta (TNF superfamily, member 3), the LST1gene for leukocyte specific transcript 1, the NCR3 gene for naturalcytotoxicity triggering receptor 3, and 1 CpG island, completesequence./locus_tag="DASS-280D8.1-001"/standard_name="OTTHUMP00000037612"/codon_start=1/product="lymphotoxin alpha (TNF superfamily, member 1)"/protein_id="CAI41939.1"/db_xref="GI:57209822"/db_xref="InterPro:IPR003636"/db_xref="InterPro:IPR006052"/db_xref="InterPro:IPR006053"/db_xref="InterPro:IPR008983"
0 0 0 3 1 1 3 17 12 2 0 1 2 8 1 3 5 2 3 7 1 2 4 7 0 7 1 9 1 5 3 4 6 2 0 6 4 2 2 4 3 1 0 13 8 3 2 1 3 2 6 1 0 1 10 1 0 2 1 4 2 0 1 0
>HSGLTSY\X76013\6..2333\2328\CAA53600.1\Homo sapiens\H.sapiens QRSHs mRNA for glutaminyl-tRNA synthetase./gene="QRSHs"/codon_start=1/product="glutaminyl-tRNA synthetase"/protein_id="CAA53600.1"/db_xref="GI:558586"/db_xref="GOA:P47897"/db_xref="InterPro:IPR000924"/db_xref="InterPro:IPR001412"/db_xref="InterPro:IPR004514"/db_xref="InterPro:IPR007638"/db_xref="InterPro:IPR007639"/db_xref="InterPro:IPR011035"/db_xref="UniProt/Swiss-Prot:P47897"
8 9 17 7 2 7 12 18 35 9 3 5 7 8 2 5 6 5 12 16 4 14 15 14 1 13 14 24 4 23 11 21 5 8 6 13 34 4 9 37 15 9 1 26 17 9 11 48 28 13 9 16 8 8 22 14 1 17 10 16 10 0 0 1
>AC018463#1\AC018463\join(4628..4770,9547..9629,9706..9775,13285..13342, 21006..21126,24049..24090,26818..26909)\609\AAX93048.1\Homo sapiens\Homo sapiens BAC clone RP11-295J19 from 2, complete sequence./gene="MGC33602"/codon_start=1/product="unknown"/protein_id="AAX93048.1"/db_xref="GI:62702121"
0 2 3 1 2 0 3 6 18 5 3 1 1 2 0 3 5 3 5 6 2 4 0 1 4 1 3 5 9 5 2 2 3 0 3 1 8 0 0 7 3 3 1 6 0 1 1 3 2 2 6 3 1 6 3 6 4 11 1 4 6 0 0 1
>S61511\S61511\1..225\225\AAB26807.1\Homo sapiens\PAX3=HuP2 {exon 2} [human, Genomic Mutant, 229 nt]./gene="PAX3"/codon_start=1/product="HuP2"/protein_id="AAB26807.1"/db_xref="GI:300503"
0 4 3 0 0 2 0 2 3 0 0 0 0 3 1 0 0 0 0 0 1 0 0 2 1 0 1 3 0 0 0 7 0 1 0 3 2 1 0 2 4 0 2 4 5 2 0 1 1 0 0 0 4 0 0 1 0 6 0 1 1 0 0 1
>AF060500\AF060500\1..2076\2076\AAD38323.1\Homo sapiens\Homo sapiens liver specific transporter mRNA, complete cds./codon_start=1/product="liver specific transporter"/protein_id="AAD38323.1"/db_xref="GI:5051630"
2 0 1 2 8 5 9 4 11 12 16 21 27 10 1 21 6 8 13 10 2 14 11 4 0 9 16 4 0 14 29 5 6 15 6 9 12 12 31 10 10 33 14 4 1 11 19 7 3 15 13 18 6 14 17 26 20 10 29 19 6 1 0 0
>BC065533\BC065533\179..1459\1281\AAH65533.1\Homo sapiens\Homo sapiens inositol hexaphosphate kinase 2, transcript variant 1,mRNA (cDNA clone MGC:75016 IMAGE:6162048), complete cds./gene="IHPK2"/codon_start=1/product="inositol hexaphosphate kinase 2, isoform a"/protein_id="AAH65533.1"/db_xref="GI:41350931"/db_xref="GeneID:51447"/db_xref="MIM:606992"
3 8 4 4 1 5 4 9 14 4 4 5 7 4 1 5 7 5 7 6 0 4 4 6 0 5 8 7 0 6 2 11 7 4 4 11 17 0 15 20 7 5 3 19 7 9 15 28 11 11 12 6 3 6 11 5 4 5 5 11 5 0 0 1
>HSTRHREC\X72089\20..1216\1197\CAA50979.1\Homo sapiens\H.sapiens mRNA for TRH receptor./codon_start=1/product="TRH receptor"/protein_id="CAA50979.1"/db_xref="GI:440156"/db_xref="GOA:P34981"/db_xref="UniProt/Swiss-Prot:P34981"
1 0 0 1 6 5 3 14 11 6 4 5 7 8 0 8 6 6 13 10 0 5 3 5 1 5 7 10 0 7 3 6 0 2 8 13 12 5 8 10 13 12 3 9 2 2 5 6 5 8 16 6 9 6 10 12 5 13 15 11 6 0 0 1
>AL162590#5\AL162590\join(26407..26538,26735..26912,29807..29911,30362..30589, 34138..34252,36496..36611,36937..37037,38607..38825)\1194\CAI15553.1\Homo sapiens\Human DNA sequence from clone RP11-54K16 on chromosome 9p13.3-21.1Contains a cancer/testis antigen 1 (CTAG1) (LAGE2B) pseudogene, theDNAJA1 gene for DnaJ (Hsp40) homolog, subfamily A, member 1, thegene for homolog of C. elegans smu-1 (SMU-1) (FLJ10805), the 5' endof the APTX gene for aprataxin and 3 CpG islands, completesequence./gene="DNAJA1"/locus_tag="RP11-54K16.1-001"/standard_name="OTTHUMP00000021193"/codon_start=1/product="DnaJ (Hsp40) homolog, subfamily A, member 1"/protein_id="CAI15553.1"/db_xref="GI:55958015"/db_xref="InterPro:IPR001305"/db_xref="InterPro:IPR001623"/db_xref="InterPro:IPR002939"/db_xref="InterPro:IPR003095"/db_xref="InterPro:IPR008971"
5 2 2 1 9 6 4 5 8 2 4 4 1 1 0 8 1 1 3 4 0 6 8 5 0 5 7 0 0 6 19 9 2 13 6 3 6 9 19 17 4 10 6 17 1 11 25 12 12 14 5 6 5 8 3 10 6 8 11 12 0 1 0 0
>HSJ000882\AJ000882\202..4401\4200\CAA04372.1\Homo sapiens\Homo sapiens mRNA for steroid receptor coactivator 1e./codon_start=1/product="steroid receptor coactivator 1e"/protein_id="CAA04372.1"/db_xref="GI:2924311"/db_xref="GOA:Q15788"/db_xref="UniProt/Swiss-Prot:Q15788"
9 4 7 5 23 16 19 12 25 23 24 18 41 24 4 38 34 30 34 17 7 27 45 24 3 46 24 22 2 29 38 19 14 16 19 10 21 13 36 19 45 45 45 77 9 12 40 29 29 38 9 12 10 12 17 18 16 17 24 50 4 0 1 0
>AB020982\AB020982\12..1898\1887\BAA35127.1\Homo sapiens\Homo sapiens ASH2L mRNA, complete cds, similar to Drosophila ash2sequence./gene="ASH2L"/codon_start=1/protein_id="BAA35127.1"/db_xref="GI:4009336"
4 4 7 0 5 2 5 3 9 7 4 15 6 8 0 9 8 14 17 10 2 7 13 9 6 17 13 14 6 17 23 15 16 10 6 6 12 6 23 23 11 10 5 16 8 7 20 23 14 28 12 15 8 3 9 14 5 4 12 13 10 0 0 1
>AF202635\AF202635\707..1039\333\AAG22489.1\Homo sapiens\Homo sapiens PP1200 mRNA, complete cds./codon_start=1/product="PP1200"/protein_id="AAG22489.1"/db_xref="GI:10732646"
0 1 0 0 1 1 3 2 2 3 1 4 1 4 0 3 1 3 2 3 1 2 1 2 1 2 2 1 2 3 1 1 1 3 1 0 2 1 4 2 2 1 1 2 2 0 3 2 1 0 1 2 2 1 1 10 1 3 3 2 2 0 1 0
>BC013579\BC013579\219..2222\2004\AAH13579.1\Homo sapiens\Homo sapiens calpastatin, mRNA (cDNA clone MGC:9402 IMAGE:3878564),complete cds./gene="CAST"/codon_start=1/product="CAST protein"/protein_id="AAH13579.1"/db_xref="GI:15488898"/db_xref="GeneID:831"/db_xref="MIM:114090"
0 1 4 2 9 2 5 9 7 7 6 9 23 8 6 16 4 10 20 12 3 10 33 10 3 19 14 8 1 37 16 4 6 8 3 5 8 6 49 42 3 6 9 11 1 2 55 24 22 45 3 3 1 6 3 2 6 5 6 9 0 1 0 0
>AL353135#3\AL353135\12579..12785\207\CAI16245.1\Homo sapiens\Human DNA sequence from clone RP11-63L7 on chromosome 6 Containsthe PROL2 gene for proline rich 2 (proline-rich protein withnuclear targeting signal), the gene for NB4apoptosis/differentiation related protein (PNAS-145), the gene forserine-arginine repressor protein (35kDa) (SRrp35), the gene for anovel protein similar to putative amidohydrolase, the 3' end of theGABRR1 gene for gamma-aminobutyric acid (GABA) receptor, rho 1 and3 CpG islands, complete sequence./gene="RP11-63L7.5"/locus_tag="RP11-63L7.5-001"/standard_name="OTTHUMP00000016848"/codon_start=1/protein_id="CAI16245.1"/db_xref="GI:55958302"/db_xref="UniProt/TrEMBL:Q9BXV2"
0 0 0 0 2 0 0 1 0 0 4 6 1 1 0 0 1 0 2 0 0 1 0 0 0 1 1 1 0 0 1 0 0 1 6 0 0 0 7 0 1 2 1 1 0 5 0 1 0 1 2 4 0 3 0 4 1 1 2 1 1 0 1 0
>BC096078\BC096078\74..1489\1416\AAH96078.1\Homo sapiens\Homo sapiens 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1,mRNA (cDNA clone MGC:116716 IMAGE:40000711), complete cds./gene="PFKFB1"/codon_start=1/product="6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase 1"/protein_id="AAH96078.1"/db_xref="GI:64654628"/db_xref="GeneID:5207"/db_xref="MIM:311790"
9 7 6 1 4 6 2 11 22 4 2 2 4 10 0 2 10 3 10 10 0 4 8 5 0 8 5 13 2 4 4 13 0 6 1 7 18 6 7 17 11 8 6 16 9 7 19 24 10 11 12 16 7 3 5 8 5 19 7 11 4 0 0 1
>BC055419\BC055419\453..1040\588\AAH55419.1\Homo sapiens\Homo sapiens integrin, alpha 4 (antigen CD49D, alpha 4 subunit ofVLA-4 receptor), mRNA (cDNA clone IMAGE:4805867), complete cds./gene="ITGA4"/codon_start=1/product="ITGA4 protein"/protein_id="AAH55419.1"/db_xref="GI:33392763"/db_xref="GeneID:3676"/db_xref="MIM:192975"
3 2 1 0 6 4 1 4 8 2 1 3 1 2 1 0 5 1 3 1 3 5 1 9 2 3 0 4 5 4 6 5 5 5 0 4 7 0 2 5 5 8 1 6 3 1 8 3 2 1 6 2 4 4 1 1 3 4 1 2 5 1 0 0
>BC009300\BC009300\116..616\501\AAH09300.1\Homo sapiens\Homo sapiens mitochondrial protein 18 kDa, transcript variant 1,mRNA (cDNA clone MGC:15180 IMAGE:4126237), complete cds./gene="MTP18"/codon_start=1/product="mitochondrial protein 18 kDa, isoform a"/protein_id="AAH09300.1"/db_xref="GI:31455234"/db_xref="GeneID:51537"
1 7 2 0 0 2 1 4 8 2 0 1 1 4 1 3 6 0 1 8 1 1 2 5 3 1 2 8 4 6 1 8 2 0 1 2 16 0 1 5 1 1 0 2 1 0 1 5 5 3 4 3 0 1 3 1 0 4 4 1 5 0 0 1
>AL353602#5\AL353602\complement(join(28535..28711,28924..29088,29554..29725, 30658..30716,30854..30989,31431..31650,31809..31983, 32284..32481,32677..32785,33147..33331,33843..33869, 35898..36083))\1809\CAC36269.1\Homo sapiens\Human DNA sequence from clone RP11-22I24 on chromosome 6 Containsthe 3' part of the POLH gene for DNA directed polymerase eta, theGTPBP2 gene for GTP binding protein 2 and one CpG island, completesequence./gene="GTPBP2"/locus_tag="RP11-22I24.2-011"/standard_name="OTTHUMP00000016486"/codon_start=1/product="GTP binding protein 2"/protein_id="CAC36269.1"/db_xref="GI:13561007"/db_xref="Genew:4670"/db_xref="GOA:Q9BX10"/db_xref="InterPro:IPR000795"/db_xref="InterPro:IPR004160"/db_xref="InterPro:IPR004161"/db_xref="UniProt/TrEMBL:Q9BX10"
8 7 12 7 2 4 4 13 37 6 1 3 4 5 4 5 14 4 13 18 3 5 5 11 4 3 9 19 1 11 14 23 18 3 10 15 28 4 8 25 13 8 3 21 8 6 10 33 17 9 7 3 10 3 17 7 2 15 7 12 1 0 0 1
>AY551299\AY551299\1..1545\1545\AAS58460.1\Homo sapiens\Homo sapiens protein kinase Chk2 transcript variant del9 (CHK2)mRNA, complete cds./gene="CHK2"/codon_start=1/product="protein kinase Chk2 transcript variant del9"/protein_id="AAS58460.1"/db_xref="GI:45356842"
3 3 3 4 7 5 4 5 11 10 6 10 8 13 1 13 11 7 10 11 2 7 6 5 1 13 8 10 1 14 10 5 10 4 6 4 11 11 19 18 7 11 5 16 5 4 27 18 9 16 9 8 5 7 4 17 4 7 12 7 6 0 0 1
>HSU10690\U10690\3075..3449\375\AAA68874.1\Homo sapiens\Human MAGE-5b antigen (MAGE5b) gene, complete cds./gene="MAGE5b"/codon_start=1/product="MAGE-5b antigen"/protein_id="AAA68874.1"/db_xref="GI:533521"
1 0 0 0 0 1 1 4 5 2 0 1 1 7 0 3 2 3 0 3 0 4 4 1 0 6 2 5 0 5 1 4 3 2 0 1 6 0 0 7 1 0 3 5 1 1 3 10 3 1 0 1 1 0 2 1 0 2 2 1 1 1 0 0
>HSU28164\U28164\232..1794\1563\AAD28324.1\Homo sapiens\Homo sapiens spermatogenesis associated PD1 mRNA, complete cds./codon_start=1/product="spermatogenesis associated PD1"/protein_id="AAD28324.1"/db_xref="GI:4730927"
3 11 15 1 4 3 1 20 28 3 2 2 8 21 8 4 25 4 3 16 5 6 6 16 5 7 7 22 1 4 0 15 4 1 0 4 21 1 7 30 8 0 2 14 11 4 4 23 16 16 18 6 10 7 11 5 0 8 1 9 3 0 1 0
>AL139287#21\AL139287\complement(join(73754..73855,73953..74398,74658..74709))\600\CAI23191.1\Homo sapiens\Human DNA sequence from clone RP5-890O3 on chromosome 1 Containsthe AKIP gene for aurora-A kinase interacting protein, a novel gene(FLJ90811) a NADH dehydrogenase (ubiquinone) 1 beta subcomplex 415kDa (NDUFB4) pseudogene, a novel gene (MGC3047), the DVL1 genefor dishevelled dsh homolog 1 (Drosophila), the TAS1R3 gene fortaste receptor type 1 member 3, a novel gene (MGC10334), a novelgene (FLJ20542), a novel gene and five CpG islands, completesequence./gene="AKIP"/locus_tag="RP5-890O3.1-002"/standard_name="OTTHUMP00000003014"/codon_start=1/product="aurora-A kinase interacting protein"/protein_id="CAI23191.1"/db_xref="GI:56204969"
0 8 7 0 2 5 1 3 17 1 0 1 0 3 1 2 5 0 1 3 2 2 2 8 4 4 2 7 4 1 2 7 9 1 0 6 4 1 3 14 2 0 2 9 2 0 4 7 1 3 4 0 3 1 3 0 1 4 1 4 5 0 0 1
>S78433\S78433\1..18\18\AAB21197.1\Homo sapiens\isovaleryl-CoA dehydrogenase presursor {exon 2} [human, mRNAPartial Mutant, 18 nt]./gene="isovaleryl-CoA dehydrogenase presursor"/codon_start=1/product="isovaleryl-CoA dehydrogenase presursor"/protein_id="AAB21197.1"/db_xref="GI:243926"
0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0
>BC046199\BC046199\423..752\330\AAH46199.1\Homo sapiens\Homo sapiens family with sequence similarity 72, member A, mRNA(cDNA clone MGC:57827 IMAGE:6064384), complete cds./gene="FAM72A"/codon_start=1/product="FAM72A protein"/protein_id="AAH46199.1"/db_xref="GI:28278563"/db_xref="GeneID:389835"
0 0 0 0 3 0 2 0 1 2 2 1 1 3 0 1 2 3 2 2 0 1 2 0 0 1 4 0 0 0 2 1 1 2 2 0 3 2 4 2 7 1 0 1 2 1 2 4 4 3 0 3 3 7 4 1 1 4 5 2 2 1 0 0
>BT007312\BT007312\1..1416\1416\AAP35976.1\Homo sapiens\Homo sapiens G protein-coupled receptor kinase-interactor 2 mRNA,complete cds./codon_start=1/product="G protein-coupled receptor kinase-interactor 2"/protein_id="AAP35976.1"/db_xref="GI:30583463"
2 3 6 1 8 6 7 8 10 8 8 11 7 3 3 9 12 10 8 6 6 4 6 5 3 6 12 12 3 10 9 4 6 2 5 9 9 5 19 10 12 13 8 19 6 12 12 16 16 19 2 7 5 3 5 7 6 3 5 10 4 0 1 0
>BC013937\BC013937\94..660\567\AAH13937.1\Homo sapiens\Homo sapiens chromosome 7 open reading frame 24, mRNA (cDNA cloneMGC:24311 IMAGE:3997629), complete cds./gene="C7orf24"/codon_start=1/product="chromosome 7 open reading frame 24"/protein_id="AAH13937.1"/db_xref="GI:15530290"/db_xref="GeneID:79017"
2 1 0 0 0 1 0 1 7 2 2 1 1 2 2 1 2 6 5 2 1 3 4 2 1 1 3 4 2 1 5 5 3 3 3 2 2 4 10 6 4 6 6 3 1 1 12 6 4 4 3 5 2 2 2 5 4 3 4 5 3 0 1 0
>BC052563\BC052563\434..2734\2301\AAH52563.1\Homo sapiens\Homo sapiens zyg-11 homolog B (C. elegans)-like, mRNA (cDNA cloneMGC:59807 IMAGE:6303965), complete cds./gene="ZYG11BL"/codon_start=1/product="zyg-11 homolog B (C. elegans)-like"/protein_id="AAH52563.1"/db_xref="GI:30851198"/db_xref="GeneID:10444"
2 16 17 3 2 7 6 30 58 5 0 8 3 18 3 7 25 4 6 13 9 6 5 10 4 8 3 25 3 5 3 15 8 1 2 15 26 3 6 30 31 10 2 31 15 2 14 50 33 7 16 4 17 7 26 8 3 30 10 21 9 0 1 0
>AY619692\AY619692\84..1025\942\AAU88048.1\Homo sapiens\Homo sapiens intelectin 1 (ITLN1) mRNA, complete cds./gene="ITLN1"/codon_start=1/product="intelectin 1"/protein_id="AAU88048.1"/db_xref="GI:52843235"
0 3 1 2 3 4 1 4 10 1 0 1 1 3 1 7 9 5 4 8 3 7 4 5 1 4 6 8 3 3 14 13 3 5 1 3 8 3 5 7 10 6 1 12 5 2 5 10 10 7 12 8 3 7 7 11 2 6 1 5 9 0 0 1
>BC034046\BC034046\179..3787\3609\AAH34046.1\Homo sapiens\Homo sapiens protein tyrosine phosphatase, receptor type, fpolypeptide (PTPRF), interacting protein (liprin), alpha 1, mRNA(cDNA clone MGC:26800 IMAGE:4794300), complete cds./gene="PPFIA1"/codon_start=1/product="PPFIA1 protein"/protein_id="AAH34046.1"/db_xref="GI:21707845"/db_xref="GeneID:8500"
14 10 11 9 30 28 10 16 43 36 20 21 13 29 5 19 24 21 22 13 8 14 14 13 7 12 34 25 5 24 14 24 13 12 8 12 22 11 42 30 24 20 21 47 21 14 82 44 34 36 6 4 7 3 9 10 6 16 16 34 10 1 0 0
>AL627107#1\AL627107\join(36278..36304,37516..37860)\372\CAI23611.1\Homo sapiens\Human DNA sequence from clone XXyac-R12DG2 on chromosome 13Contains 2 novel genes, a calumenin (CALU) pseudogene, a novel gene(possible ortholog of RIKEN cDNA 4933433D23 gene) and a CpG island,complete sequence./locus_tag="XXyac-R12DG2.2-001"/standard_name="OTTHUMP00000018349"/codon_start=1/protein_id="CAI23611.1"/db_xref="GI:56207198"/db_xref="UniProt/TrEMBL:Q8WYW1"
1 8 2 0 3 4 0 3 0 1 0 7 5 7 8 1 9 0 4 4 1 0 4 4 3 1 0 5 0 1 1 4 4 0 1 1 3 2 0 4 1 0 0 0 0 0 0 3 0 0 2 1 0 0 3 0 0 2 1 1 3 0 0 1
>AY956764\AY956764\1..1794\1794\AAX38251.1\Homo sapiens\Homo sapiens heat shock protein 90Bc (HSP90Bc) mRNA, complete cds./gene="HSP90Bc"/codon_start=1/product="heat shock protein 90Bc"/protein_id="AAX38251.1"/db_xref="GI:61104913"
2 3 5 3 2 3 5 10 15 9 2 11 4 9 1 13 9 5 7 14 1 6 1 13 0 7 10 10 1 11 3 8 1 14 4 5 20 7 22 35 12 8 2 19 10 6 30 53 18 27 5 13 4 2 9 11 4 23 10 17 3 0 1 0
>HSTIF\X79538\74..1309\1236\CAA56074.1\Homo sapiens\H.sapiens nuk_34 mRNA for translation initiation factor./codon_start=1/product="translation initiation factor"/protein_id="CAA56074.1"/db_xref="GI:496902"/db_xref="GOA:P38919"/db_xref="UniProt/Swiss-Prot:P38919"
3 3 6 5 8 6 1 8 13 3 0 11 5 5 3 2 3 2 7 11 5 8 4 3 1 3 4 9 5 8 4 10 5 5 3 7 12 7 13 10 7 5 4 17 2 3 11 18 13 15 11 2 3 2 9 5 1 23 10 16 3 0 0 1
>HSNUCPP\Z34289\55..2154\2100\CAA84063.1\Homo sapiens\H.sapiens mRNA for nucleolar phosphoprotein p130./function="nucleologenesis"/codon_start=1/product="nucleolar phosphoprotein p130"/protein_id="CAA84063.1"/db_xref="GI:663008"/db_xref="GOA:Q14978"/db_xref="UniProt/Swiss-Prot:Q14978"
7 3 5 0 3 5 1 6 7 2 3 1 16 15 0 28 35 21 7 15 1 8 23 14 1 24 29 33 5 22 11 10 2 9 5 8 14 9 31 80 6 12 8 20 0 1 17 50 20 19 3 2 0 0 5 4 3 2 3 3 2 0 0 1
>HSRPS3AGE\X87373\join(387..448,1212..1315,1702..1889,3598..3806,4911..5020, 5209..5330)\795\CAA60827.1\Homo sapiens\Homo sapiens RPS3a gene for ribosomal protein S3a./gene="RPS3a"/codon_start=1/product="ribosomal protein S3a"/protein_id="CAA60827.1"/db_xref="GI:854179"/db_xref="GOA:P49241"/db_xref="UniProt/Swiss-Prot:P49241"
2 3 2 3 3 1 0 4 4 5 0 5 0 1 0 6 1 3 3 7 2 5 4 1 0 2 3 2 1 7 7 5 1 7 1 7 6 9 20 18 4 6 5 7 2 3 12 3 5 12 1 4 2 2 5 5 3 2 7 11 2 1 0 0
>AF167473\AF167473\1..570\570\AAF89618.1\Homo sapiens\Homo sapiens heme-binding protein mRNA, complete cds./codon_start=1/product="heme-binding protein"/protein_id="AAF89618.1"/db_xref="GI:9622095"
0 1 5 2 0 1 2 0 5 0 1 2 0 2 1 1 4 1 5 3 2 1 3 5 0 4 4 7 1 4 3 6 6 3 3 5 3 2 5 11 2 3 3 3 0 0 11 5 7 3 4 5 1 1 4 4 0 4 4 7 4 0 0 1
>BA000025#2\BA000025 AP000502-AP000521\42521..43900\1380\BAB63293.1\Homo sapiens\Homo sapiens genomic DNA, chromosome 6p21.3, HLA Class I region./gene="NG35"/function="Zn finger"/codon_start=1/protein_id="BAB63293.1"/db_xref="GI:15277208"
1 7 13 1 0 3 2 14 25 4 1 5 3 7 6 2 16 3 2 7 3 1 9 14 3 8 7 27 5 3 7 19 11 5 1 9 23 2 5 19 13 1 1 12 17 1 8 25 10 6 5 1 14 1 15 1 1 10 6 8 0 0 1 0
>AY337001\AY337001\1..1035\1035\AAQ76789.1\Homo sapiens\Homo sapiens chemokine receptor-like 2 mRNA, complete cds./codon_start=1/product="chemokine receptor-like 2"/protein_id="AAQ76789.1"/db_xref="GI:34596212"
0 2 0 1 2 9 4 11 20 10 1 5 3 3 2 3 6 5 8 5 1 6 5 7 0 3 8 8 2 4 2 5 3 2 3 5 12 6 12 6 6 6 5 6 4 4 10 7 7 6 9 8 6 6 14 13 2 7 7 7 4 1 0 0
>AK022909\AK022909\1..2223\2223\BAB14304.1\Homo sapiens\Homo sapiens cDNA FLJ12847 fis, clone NT2RP2003347./codon_start=1/protein_id="BAB14304.1"/db_xref="GI:10434574"
1 3 2 5 15 12 7 6 15 13 12 14 24 11 3 26 15 15 14 13 3 9 14 9 4 19 12 9 3 8 16 13 6 8 5 13 9 8 37 26 9 22 8 20 15 9 36 22 11 23 6 7 10 15 4 18 6 7 16 14 5 0 0 1
>BC007226\BC007226\42..2006\1965\AAH07226.1\Homo sapiens\Homo sapiens N-glycanase 1, mRNA (cDNA clone MGC:15182IMAGE:2963554), complete cds./gene="NGLY1"/codon_start=1/product="N-glycanase 1"/protein_id="AAH07226.1"/db_xref="GI:13938211"/db_xref="GeneID:55768"
8 1 3 3 22 6 4 8 14 16 7 15 17 9 2 16 8 9 14 8 1 8 5 4 3 10 8 12 5 16 12 9 7 7 8 9 10 13 26 15 12 18 11 19 9 6 37 19 9 23 3 13 6 14 4 20 10 4 18 5 16 0 0 1
>HSA550516\AJ550516\1..297\297\CAD79455.1\Homo sapiens\Homo sapiens mRNA for HDM2-HD1 protein (HDM2 gene)./gene="HDM2"/function="oncogene"/codon_start=1/product="HDM2-HD1 protein"/protein_id="CAD79455.1"/db_xref="GI:29125741"
1 0 0 0 1 1 2 0 0 2 0 1 1 0 1 2 0 2 2 4 0 2 3 3 0 3 1 2 0 2 1 1 0 3 3 1 3 0 4 4 1 4 5 1 0 2 4 2 1 1 0 1 4 4 1 1 0 0 6 4 0 0 1 0
>BC063017\BC063017\11..691\681\AAH63017.1\Homo sapiens\Homo sapiens fumarylacetoacetate hydrolase domain containing 1,mRNA (cDNA clone MGC:74876 IMAGE:5226963), complete cds./gene="FAHD1"/codon_start=1/product="FAHD1 protein"/protein_id="AAH63017.1"/db_xref="GI:38648928"/db_xref="GeneID:81889"
0 5 1 0 2 3 1 4 11 1 0 4 1 8 1 1 5 0 2 2 3 3 2 9 3 3 4 4 8 2 5 7 4 1 0 6 9 3 2 14 5 0 0 3 5 0 5 13 5 3 5 2 5 0 4 1 2 10 2 8 4 0 0 1
>HSY17999#1\Y17999\281..2170\1890\CAA76991.1\Homo sapiens\Homo sapiens mRNA for protein kinase Dyrk1B./gene="Dyrk1B"/codon_start=1/product="Dyrk1B protein kinase"/protein_id="CAA76991.1"/db_xref="GI:4379097"/db_xref="GOA:Q9Y463"/db_xref="InterPro:IPR000719"/db_xref="InterPro:IPR008271"/db_xref="InterPro:IPR011009"/db_xref="UniProt/Swiss-Prot:Q9Y463"
3 16 18 4 0 4 2 16 43 4 1 2 6 14 6 5 15 6 5 14 8 3 12 30 9 16 5 28 7 5 3 28 13 7 5 5 17 0 4 23 17 2 1 30 14 6 4 23 21 9 16 7 8 2 13 4 1 16 7 12 4 0 0 1
>BC013748\BC013748\153..812\660\AAH13748.1\Homo sapiens\Homo sapiens px19-like protein, mRNA (cDNA clone MGC:9879IMAGE:3867564), complete cds./gene="PX19"/codon_start=1/product="px19-like protein"/protein_id="AAH13748.1"/db_xref="GI:15489294"/db_xref="GeneID:27166"/db_xref="MIM:605733"
3 2 7 0 1 1 1 3 8 2 1 2 0 5 1 3 5 2 3 8 2 3 2 1 1 3 3 13 1 4 0 3 0 3 1 5 11 3 4 14 6 3 3 11 3 1 7 9 7 0 3 3 0 2 5 5 1 3 1 5 6 0 1 0
>AL353671#8\AL353671\105019..105606\588\CAH71256.1\Homo sapiens\Human DNA sequence from clone RP11-205M20 on chromosome 9 Containsthe 5' end of the gene for DEAD/H (Asp-Glu-Ala-Asp/His) boxpolypeptide (RIG-I), the gene for tumor protein p53-binding protein(TP53BPL), a novel gene, a DNA fragmentation factor, 40kDa, betapolypeptide (caspase-activated DNase) (DFFB) (CAD, CPAN, DFF40)pseudogene, a novel gene (FLJ25547), the NDUFB6 gene for NADHdehydrogenase (ubiquinone) 1 beta subcomplex, 6, 17kDa (B17), and aCpG island, complete sequence./locus_tag="RP11-205M20.5-001"/standard_name="OTTHUMP00000021184"/codon_start=1/protein_id="CAH71256.1"/db_xref="GI:55662288"/db_xref="UniProt/TrEMBL:Q8N7I0"
0 2 1 1 2 5 1 8 4 3 2 4 9 3 0 5 9 3 3 2 0 4 5 7 3 3 2 5 0 6 1 5 4 3 2 2 3 1 1 1 4 3 3 6 5 3 3 1 1 4 1 2 6 2 6 5 0 1 3 4 7 1 0 0
>AL590385#2\AL590385 AC013307\join(62127..62211,62646..62666,62996..63250,66479..66733, 67493..67615,70554..70591,74634..74807)\951\CAI16119.1\Homo sapiens\Human DNA sequence from clone RP11-5K23 on chromosome 1 Containsthe FCGR2A gene for Fc fragment of IgG low affinity IIa receptorfor (CD32), the HSPA6 gene for heat shock 70kDa protein 6(HSP70B'), a ribosomal protein S23 (RPS23) pseudogene, the FCGR3Agene for Fc fragment of IgG low affinity IIIa receptor for (CD16),a novel gene and three CpG islands, complete sequence./gene="FCGR2A"/locus_tag="RP11-5K23.6-002"/standard_name="OTTHUMP00000032377"/codon_start=1/product="Fc fragment of IgG, low affinity IIa, receptor for (CD32)"/protein_id="CAI16119.1"/db_xref="GI:55960610"
0 1 1 1 3 4 0 4 15 5 0 4 3 7 0 4 9 4 5 8 3 10 5 9 1 9 4 6 1 11 4 5 4 1 3 5 12 2 5 9 12 8 8 11 7 3 5 8 10 5 7 1 5 1 8 1 1 8 7 8 5 1 0 0
>BC067422\BC067422\29..1156\1128\AAH67422.1\Homo sapiens\Homo sapiens alcohol dehydrogenase 1C (class I), gamma polypeptide,mRNA (cDNA clone MGC:79242 IMAGE:7002194), complete cds./gene="ADH1C"/codon_start=1/product="class I alcohol dehydrogenase, gamma subunit"/protein_id="AAH67422.1"/db_xref="GI:45768580"/db_xref="GeneID:126"/db_xref="MIM:103730"
0 3 2 2 2 2 5 3 10 4 5 2 3 4 3 5 4 5 4 9 3 6 3 6 1 10 13 6 0 11 13 12 7 5 4 12 15 7 20 13 7 5 1 5 2 4 11 10 6 10 3 1 6 9 3 14 3 10 11 8 2 0 0 1
>HSU18803\U18803\1..642\642\AAC50879.1\Homo sapiens\Human myelin/oligodendrocyte glycoprotein MOG beta 2 isoform (MOG)mRNA, complete cds./gene="MOG"/codon_start=1/product="myelin/oligodendrocyte glycoprotein beta 2 isoform"/protein_id="AAC50879.1"/db_xref="GI:1688063"
2 2 5 0 6 3 1 18 10 2 1 2 1 2 1 6 4 0 2 1 0 3 2 5 0 5 6 1 1 3 6 5 5 2 2 2 10 3 3 3 1 3 4 4 3 2 8 8 2 6 5 2 4 1 11 1 3 3 1 3 2 1 0 0
>AK074396\AK074396\255..917\663\BAB85069.1\Homo sapiens\Homo sapiens cDNA FLJ23816 fis, clone HSI02685./codon_start=1/protein_id="BAB85069.1"/db_xref="GI:18676987"
0 11 5 5 0 2 0 7 12 2 0 1 0 2 1 1 9 1 2 7 3 1 0 12 3 5 1 11 5 1 2 14 2 1 0 6 7 0 0 1 7 0 1 9 4 0 0 10 7 0 9 0 12 4 6 0 0 4 0 3 1 1 0 0
>AK098557\AK098557\281..1384\1104\BAC05332.1\Homo sapiens\Homo sapiens cDNA FLJ25691 fis, clone TST04456./codon_start=1/protein_id="BAC05332.1"/db_xref="GI:21758596"
1 1 2 0 2 9 5 11 5 5 6 1 7 3 0 7 10 7 11 1 1 7 9 6 2 11 7 5 0 7 7 4 5 5 3 1 5 8 10 7 9 14 7 8 5 9 13 9 7 3 6 12 4 3 5 13 7 9 6 10 4 1 0 0
>AF040639\AF040639\85..1080\996\AAD02195.1\Homo sapiens\Homo sapiens aflatoxin B1-aldehyde reductase mRNA, complete cds./codon_start=1/product="aflatoxin B1-aldehyde reductase"/protein_id="AAD02195.1"/db_xref="GI:4104867"
1 7 8 1 1 3 0 8 25 2 0 2 2 5 2 0 8 1 1 11 5 1 3 7 2 3 5 21 4 3 1 17 8 1 0 3 11 1 2 10 6 4 1 14 11 2 5 19 10 2 9 4 4 3 10 5 1 5 3 11 6 0 1 0
>BC069360\BC069360\1..345\345\AAH69360.1\Homo sapiens\Homo sapiens chemokine (C motif) ligand 2, mRNA (cDNA cloneMGC:97475 IMAGE:7262751), complete cds./gene="XCL2"/codon_start=1/product="chemokine (C motif) ligand 2"/protein_id="AAH69360.1"/db_xref="GI:47479837"/db_xref="GeneID:6846"/db_xref="MIM:604828"
1 0 0 1 5 4 1 4 3 2 0 1 1 2 1 1 3 1 2 10 2 3 3 0 0 0 2 2 0 2 1 4 1 1 2 3 5 1 3 2 2 2 2 3 0 1 3 0 2 1 2 0 1 2 0 1 0 5 3 3 1 0 1 0
>BC026319\BC026319\23..1870\1848\AAH26319.1\Homo sapiens\Homo sapiens hypothetical protein FLJ11078, mRNA (cDNA cloneMGC:26163 IMAGE:4799495), complete cds./gene="FLJ11078"/codon_start=1/product="hypothetical protein LOC55295"/protein_id="AAH26319.1"/db_xref="GI:20071160"/db_xref="GeneID:55295"
2 27 12 3 1 4 1 13 46 0 0 1 3 4 10 1 25 0 1 14 9 2 1 14 9 2 5 42 6 6 1 36 9 6 2 11 35 1 0 11 12 3 0 28 15 2 2 36 27 4 19 3 18 1 25 2 1 14 2 17 8 0 1 0
>AF155811\AF155811\1..969\969\AAG29584.1\Homo sapiens\Homo sapiens mitochondrial uncoupling protein 5 short form mRNA,complete cds; nuclear gene for mitochondrial product./function="reduces mitochondrial membrane potential in mammalian cells"/codon_start=1/product="mitochondrial uncoupling protein 5 short form"/protein_id="AAG29584.1"/db_xref="GI:11094339"
3 3 1 3 2 5 6 3 4 7 6 6 4 3 0 3 6 2 4 5 1 9 3 4 1 2 4 6 3 8 10 8 6 7 7 1 10 8 9 8 4 3 9 6 2 5 5 7 1 9 3 7 0 3 6 13 6 10 15 11 6 1 0 0
>AF520533S2\AF520534\284..1900\1617\AAQ17589.1\Homo sapiens\Homo sapiens individual 80 allele A, envelope glycoprotein gene,complete cds, and 3' long terminal repeat, complete sequence./codon_start=1/product="envelope glycoprotein"/protein_id="AAQ17589.1"/db_xref="GI:33411037"
5 6 3 4 8 3 16 17 5 10 8 4 9 10 2 12 8 5 6 23 0 21 4 19 0 17 11 7 0 6 18 6 5 6 11 11 2 10 12 5 14 12 18 4 2 10 16 7 5 8 9 9 8 10 9 12 10 11 7 13 9 0 1 0
>HS1120P11#2\AL109615\complement(join(138779..139145,141477..141547))\438\CAI19245.1\Homo sapiens\Human DNA sequence from clone RP5-1120P11 on chromosome6p12.3-21.2, complete sequence./locus_tag="RP5-1120P11.5-001"/standard_name="OTTHUMP00000016500"/codon_start=1/protein_id="CAI19245.1"/db_xref="GI:56204136"/db_xref="GOA:Q6P1L8"/db_xref="InterPro:IPR000218"/db_xref="UniProt/TrEMBL:Q6P1L8"
3 2 3 0 2 0 1 3 6 0 0 0 0 2 0 0 5 3 2 4 1 2 1 5 0 3 0 3 2 3 2 5 6 0 2 2 10 0 1 10 7 1 0 4 2 3 1 2 4 0 1 2 2 2 4 2 1 3 5 4 1 0 0 1
>BC008999\BC008999\320..1255\936\AAH08999.1\Homo sapiens\Homo sapiens KIAA0157, mRNA (cDNA clone MGC:17346 IMAGE:2900632),complete cds./gene="KIAA0157"/codon_start=1/product="KIAA0157 protein"/protein_id="AAH08999.1"/db_xref="GI:14290468"/db_xref="GeneID:23172"
3 2 1 0 10 6 1 6 1 5 3 4 5 7 1 10 5 11 2 3 0 8 4 7 2 11 9 4 2 7 6 3 2 2 0 2 10 6 7 6 4 12 6 15 4 3 14 8 12 8 4 8 0 2 4 6 1 4 5 7 0 1 0 0
>HSAJ3317\AJ223317\133..1560\1428\CAA11257.1\Homo sapiens\Homo sapiens mRNA for sarcosine dehydrogenase, complete cds./codon_start=1/product="sarcosine dehydrogenase"/protein_id="CAA11257.1"/db_xref="GI:4454259"/db_xref="GOA:O96023"/db_xref="UniProt/TrEMBL:O96023"/IGNORED_CODON=1
6 7 13 5 0 4 3 9 28 2 0 2 2 8 3 3 10 4 3 16 8 3 5 13 5 4 8 19 4 7 8 22 12 8 1 12 27 0 0 12 8 4 3 13 12 8 4 27 13 5 6 6 5 4 8 4 0 11 5 13 9 0 0 1
>BC007315\BC007315\262..1002\741\AAH07315.1\Homo sapiens\Homo sapiens CCR4-NOT transcription complex, subunit 7, mRNA (cDNAclone MGC:1092 IMAGE:2989585), complete cds./gene="CNOT7"/codon_start=1/product="CNOT7 protein"/protein_id="AAH07315.1"/db_xref="GI:13938366"/db_xref="GeneID:29883"/db_xref="MIM:604913"
2 0 2 1 2 1 5 4 2 4 4 8 4 0 0 5 4 0 4 3 1 3 4 1 0 3 6 2 1 3 9 1 2 4 2 3 4 4 9 5 4 8 6 9 0 4 15 11 7 4 7 5 2 3 2 12 3 5 7 7 3 0 0 1
>AC016776#2\AC016776\join(82753..82870,97608..97637,104389..104454, 126211..126278,134986..135056,140200..140257, 141866..141898,145522..145584,150932..150982)\558\AAY24220.1\Homo sapiens\Homo sapiens BAC clone RP11-574K22 from 2, complete sequence./gene="NCE2"/codon_start=1/product="unknown"/protein_id="AAY24220.1"/db_xref="GI:62988833"
0 0 4 2 4 1 3 1 4 4 4 5 1 2 1 2 0 2 7 2 2 4 3 4 0 3 4 2 2 3 2 2 2 3 1 1 5 5 10 5 4 4 0 3 1 5 8 4 6 10 4 1 1 4 1 6 1 3 2 2 3 0 0 1
>AK097248\AK097248\283..2055\1773\BAC04985.1\Homo sapiens\Homo sapiens cDNA FLJ39929 fis, clone SPLEN2021295./codon_start=1/protein_id="BAC04985.1"/db_xref="GI:21756940"
4 3 0 6 12 8 4 6 9 11 8 10 11 4 2 10 4 6 11 13 5 11 20 16 4 21 4 6 0 7 9 6 3 10 5 5 4 8 25 17 11 16 12 14 11 10 29 17 14 16 10 21 3 9 11 12 10 4 14 10 8 0 0 1
>AK126055\AK126055\1285..4461\3177\BAC86417.1\Homo sapiens\Homo sapiens cDNA FLJ44067 fis, clone TESTI4037066./codon_start=1/protein_id="BAC86417.1"/db_xref="GI:34532404"
3 1 1 4 18 10 21 10 16 25 29 26 37 10 3 32 9 20 24 11 1 23 18 4 4 17 24 6 1 12 16 5 4 14 15 10 13 10 56 20 20 33 31 26 8 18 66 16 22 33 10 21 8 19 12 33 22 8 41 15 13 0 0 1
>D86062\D86062\19..732\714\BAA12985.1\Homo sapiens\Homo sapiens mRNA for KNP-Ib, complete cds./gene="KNP-I"/codon_start=1/product="KNP-Ib"/protein_id="BAA12985.1"/db_xref="GI:1545815"
0 2 1 2 1 6 0 8 9 1 0 2 0 5 2 3 2 1 1 5 4 2 2 2 2 5 7 16 8 7 7 7 5 3 0 8 15 1 3 9 4 1 0 6 9 2 6 9 4 3 2 1 5 0 2 3 0 9 2 4 1 0 0 1
>AL591845#3\AL591845\complement(join(58531..58961,59207..59273))\498\CAH71861.1\Homo sapiens\Human DNA sequence from clone RP11-268J15 on chromosome 1 Containsthe 3' end of a novel gene for thyroid hormone receptor-associatedprotein, 150 kDa subunit (TRAP150) (FLJ22082), a novel transcript(FLJ22938), a gene for a novel protein (FLJ10647), the 3' end of agene for Ser/Thr-like kinase (MGC4796) and two CpG islands,complete sequence./gene="RP11-268J15.2"/locus_tag="RP11-268J15.2-001"/standard_name="OTTHUMP00000009598"/codon_start=1/product="novel protein"/protein_id="CAH71861.1"/db_xref="GI:55665952"/db_xref="UniProt/TrEMBL:Q9NVM1"
1 7 8 0 0 1 0 6 16 0 0 1 0 1 2 0 7 0 1 4 6 1 0 10 6 0 1 4 4 2 0 10 3 0 0 4 2 0 0 0 4 0 0 3 2 0 1 15 11 1 3 1 2 0 4 0 0 5 0 3 2 0 0 1
>HSRBPRL7A\X57959\11..757\747\CAA41027.1\Homo sapiens\H.sapiens mRNA for ribosomal protein L7./gene="humL7-14"/codon_start=1/product="ribosomal protein L7"/protein_id="CAA41027.1"/db_xref="GI:35903"/db_xref="GOA:P18124"/db_xref="UniProt/Swiss-Prot:P18124"
7 3 0 1 7 8 1 1 5 9 0 6 1 0 1 3 1 0 1 4 0 2 4 3 0 2 7 1 2 7 5 4 1 6 5 1 4 3 10 24 8 7 2 3 2 2 8 9 1 3 4 7 1 0 6 4 0 12 8 9 2 1 0 0
>CR456738\CR456738\1..627\627\CAG33019.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834F046D forgene FADD, Fas (TNFRSF6)-associated via death domain; complete cds,incl. stopcodon./gene="FADD"/codon_start=1/protein_id="CAG33019.1"/db_xref="GI:48145593"
0 7 3 3 3 3 2 8 21 0 0 0 4 6 3 2 5 1 3 4 0 0 0 2 2 1 4 6 5 3 0 2 8 0 1 3 9 1 2 6 8 1 1 7 4 0 3 14 13 2 1 0 2 2 4 1 1 3 0 5 3 1 0 0
>S81868\S81868\1327..1350\24\AAD14378.1\Homo sapiens\adenosine A3 receptor {5' region} [human, HepG2 cells, Genomic,1350 nt]./gene="adenosine A3 receptor"/codon_start=1/protein_id="AAD14378.1"/db_xref="GI:4262078"
0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
>BC014661\BC014661\3..794\792\AAH14661.1\Homo sapiens\Homo sapiens hypothetical protein FLJ12448, mRNA (cDNA cloneMGC:22955 IMAGE:4860511), complete cds./gene="FLJ12448"/codon_start=1/product="hypothetical protein FLJ12448"/protein_id="AAH14661.1"/db_xref="GI:15779204"/db_xref="GeneID:64897"
3 4 4 1 1 2 1 2 4 3 0 4 4 4 4 3 11 8 3 9 0 2 5 5 3 4 11 10 5 9 3 4 3 3 2 5 7 0 7 23 4 2 4 8 3 2 5 20 6 5 0 0 2 0 6 0 1 2 2 3 2 0 0 1
>BC010505\BC010505\104..1069\966\AAH10505.1\Homo sapiens\Homo sapiens secretory carrier membrane protein 3, transcriptvariant 2, mRNA (cDNA clone MGC:17478 IMAGE:3452347), complete cds./gene="SCAMP3"/codon_start=1/product="secretory carrier membrane protein 3, isoform 2"/protein_id="AAH10505.1"/db_xref="GI:14714725"/db_xref="GeneID:10067"/db_xref="MIM:606913"
4 3 4 0 2 1 2 11 12 4 1 3 4 7 1 3 7 3 5 3 1 5 8 11 3 7 7 17 1 16 3 8 3 4 2 7 7 2 2 8 9 5 2 14 1 1 5 11 5 1 5 3 5 2 18 9 0 6 4 7 6 0 0 1
>AK074662\AK074662\212..580\369\BAC11120.1\Homo sapiens\Homo sapiens cDNA FLJ90181 fis, clone MAMMA1000706./codon_start=1/protein_id="BAC11120.1"/db_xref="GI:22760248"
0 5 1 3 0 4 1 5 8 1 0 1 1 2 0 1 3 0 9 1 0 4 4 9 0 4 5 4 0 0 1 3 2 1 1 1 1 1 0 0 1 0 0 3 9 2 0 1 1 0 0 1 5 3 1 0 0 2 0 1 5 0 0 1
>BC003674\BC003674\48..347\300\AAH03674.1\Homo sapiens\Homo sapiens NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 2,8kDa, mRNA (cDNA clone MGC:12315 IMAGE:4044385), complete cds./gene="NDUFA2"/codon_start=1/product="NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 2, 8kDa"/protein_id="AAH03674.1"/db_xref="GI:13277540"/db_xref="GeneID:4695"/db_xref="MIM:602137"
1 5 0 1 1 1 3 1 4 0 1 1 0 1 1 0 1 3 0 1 1 0 0 4 0 1 4 4 3 1 1 4 1 1 1 3 2 1 2 4 3 2 1 4 1 0 1 5 2 2 2 0 1 1 2 1 0 3 2 1 1 0 0 1
>HSU14971\U14971\36..620\585\AAA85659.1\Homo sapiens\Human ribosomal protein S9 mRNA, complete cds./codon_start=1/product="ribosomal protein S9"/protein_id="AAA85659.1"/db_xref="GI:550023"
1 11 7 3 2 3 0 2 18 1 1 2 0 3 0 3 1 0 0 3 2 1 2 1 3 1 0 7 0 3 1 8 5 1 0 6 7 2 4 15 3 1 1 6 3 1 2 11 5 6 1 2 0 1 6 1 1 7 2 2 2 1 0 0
>BC000881\BC000881\130..474\345\AAH00881.1\Homo sapiens\Homo sapiens centromere protein A, 17kDa, mRNA (cDNA clone MGC:5165IMAGE:3461992), complete cds./gene="CENPA"/codon_start=1/product="CENPA protein"/protein_id="AAH00881.1"/db_xref="GI:12654133"/db_xref="GeneID:1058"/db_xref="MIM:117139"
3 4 7 0 1 4 2 6 3 2 2 1 0 4 0 0 5 1 1 3 0 1 1 5 5 0 4 3 0 1 1 7 0 1 0 0 1 2 0 6 0 0 3 1 2 3 1 5 1 1 0 1 0 0 2 2 1 2 0 1 1 0 0 1
>HSRH4\X63098\20..1084\1065\CAA44812.1\Homo sapiens\H.sapiens mRNA for rhesus polypeptide (Rh4)./codon_start=1/product="Rhesus polypeptide Rh4"/protein_id="CAA44812.1"/db_xref="GI:36020"/db_xref="GOA:P18577"/db_xref="UniProt/Swiss-Prot:P18577"
0 1 4 1 3 5 2 8 22 6 2 8 5 4 2 8 7 9 5 8 2 3 4 4 3 8 7 12 5 11 4 8 7 6 1 9 21 0 1 9 6 5 6 6 8 2 2 3 4 5 4 6 5 2 14 4 1 11 2 14 9 1 0 0
>HSU81031#1\U81031 AC000028\join(5284..5501,5659..5794,5911..6078,6236..6345, 7501..7551,7688..7823,8388..8480)\912\AAC39521.2\Homo sapiens\Homo sapiens CDK4, SAS, and KIAA0167 genes, complete cds; and OS9gene, partial cds; from cosmid 6E5, complete sequence./codon_start=1/product="CDK4"/protein_id="AAC39521.2"/db_xref="GI:17986211"
9 2 2 4 4 2 4 3 19 4 1 2 0 3 2 4 2 4 10 2 1 2 8 11 1 5 5 10 0 7 9 7 3 5 4 5 11 7 1 10 3 4 0 8 5 4 6 13 10 7 4 5 1 3 2 11 0 8 3 8 3 0 0 1
>BC094744\BC094744\75..2924\2850\AAH94744.1\Homo sapiens\Homo sapiens multimerin 2, mRNA (cDNA clone MGC:104596IMAGE:30343159), complete cds./gene="MMRN2"/codon_start=1/product="multimerin 2"/protein_id="AAH94744.1"/db_xref="GI:63101264"/db_xref="GeneID:79812"/db_xref="MIM:608925"
4 11 19 4 5 13 3 23 71 7 3 9 4 12 7 5 31 4 9 21 11 7 10 10 7 16 16 55 18 14 9 24 25 9 1 16 40 3 11 28 19 6 7 61 28 5 12 70 35 11 12 2 10 2 18 12 3 14 2 15 10 0 0 1
>AK127042\AK127042\1326..4424\3099\BAC86800.1\Homo sapiens\Homo sapiens cDNA FLJ45099 fis, clone BRAWH3031710, highly similarto Homo sapiens serologically defined colon cancer antigen 33(SDCCAG33)./codon_start=1/protein_id="BAC86800.1"/db_xref="GI:34533774"
1 7 7 2 2 7 3 18 49 4 3 13 6 43 12 11 50 9 11 38 19 9 13 33 20 12 12 33 15 12 5 30 14 3 0 16 31 4 26 69 28 10 2 46 24 5 10 63 36 12 23 7 11 6 15 7 2 23 4 19 7 0 1 0
>AK074906\AK074906\92..2332\2241\BAC11282.1\Homo sapiens\Homo sapiens cDNA FLJ90425 fis, clone NT2RP3000444./codon_start=1/protein_id="BAC11282.1"/db_xref="GI:22760656"
3 11 30 6 8 10 6 21 63 4 0 6 6 21 5 9 22 6 5 8 2 5 8 27 8 14 9 31 8 9 9 22 20 7 1 5 31 4 2 25 6 6 4 39 8 5 15 53 27 4 8 2 16 4 8 1 0 17 3 8 15 0 0 1
>BC101263\BC101263\101..1048\948\AAI01264.1\Homo sapiens\Homo sapiens hypothetical protein DKFZp547E052, mRNA (cDNA cloneMGC:120278 IMAGE:40023930), complete cds./gene="DKFZp547E052"/codon_start=1/product="hypothetical protein LOC84236"/protein_id="AAI01264.1"/db_xref="GI:71682034"/db_xref="GeneID:84236"
1 0 3 1 10 4 4 8 7 9 3 7 5 5 0 4 6 5 1 3 1 5 8 3 2 6 8 4 0 8 11 5 7 3 4 3 3 7 5 3 8 7 7 7 3 8 12 2 4 6 8 9 2 4 9 11 2 5 5 7 7 0 0 1
>HSA418064\AJ418064\join(195..214,1642..1849,10482..10648,12181..12314, 13207..13304,14872..14946,15086..15277,18194..18289, 21663..21738,23005..23098,25671..25750,25842..25886, 26722..26811,31129..31226,36154..36297,37528..37666, 38366..38501,40270..40449,44239..44363,44861..45039, 46373..46498,46836..46948,47300..47480,51531..51611, 54157..54309)\3030\CAD10805.1\Homo sapiens\Homo sapiens SMARCA3 gene for SWI/SNF related, matrix associated,actin dependent regulator of chromatin, subfamily a, member 3,exons 1-26./gene="SMARCA3"/function="transcription factor"/codon_start=1/product="SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 3"/protein_id="CAD10805.1"/db_xref="GI:16943790"/db_xref="GOA:Q14527"/db_xref="UniProt/Swiss-Prot:Q14527"
5 4 2 7 30 6 8 1 16 25 30 22 17 9 0 23 9 14 27 4 3 23 26 5 3 17 27 10 3 18 33 8 3 15 12 7 13 26 55 32 12 41 15 24 3 22 58 13 16 38 5 16 7 11 8 28 15 11 30 24 14 1 0 0
>BC029125\BC029125\15..1070\1056\AAH29125.1\Homo sapiens\Homo sapiens formyl peptide receptor-like 1, mRNA (cDNA cloneMGC:34599 IMAGE:5180065), complete cds./gene="FPRL1"/codon_start=1/product="formyl peptide receptor-like 1"/protein_id="AAH29125.1"/db_xref="GI:20809658"/db_xref="GeneID:2358"/db_xref="MIM:136538"
1 3 4 1 2 2 1 9 20 6 4 6 2 8 0 5 4 3 6 9 3 9 7 4 1 6 5 14 0 8 4 9 6 2 1 14 13 5 5 6 8 5 2 2 4 1 5 9 8 0 5 4 3 5 15 11 0 13 14 11 8 0 0 1
>HS885L7#2\AL035669\join(45701..45848,46287..46408,47764..47845,48152..48226, 48633..48820)\615\CAC12748.1\Homo sapiens\Human DNA sequence from clone RP5-885L7 on chromosome 20q13.2-13.33Contains the 3' end of the NTSR1 gene for high affinity neurotensinreceptor 1, the C20orf20 gene, the OGFR gene for opioid growthfactor receptor, the COL9A3 gene for collagen IX alpha 3, theC20orf143 gene, the TCFL5 gene for basic helix-loop-helixtranscription factor-like 5, the ARF4P2 gene for ADP-ribosylationfactor 4 pseudogene 2, the 3' end of the DATF1 gene for deathassociated transcription factor 1, two novel genes and seven CpGislands, complete sequence./gene="C20orf20"/locus_tag="RP5-885L7.13-001"/standard_name="OTTHUMP00000031512"/codon_start=1/protein_id="CAC12748.1"/db_xref="GI:12313998"/db_xref="Genew:15866"/db_xref="GOA:Q9NV56"/db_xref="UniProt/Swiss-Prot:Q9NV56"
2 3 5 0 0 1 0 1 4 2 0 2 4 4 0 2 7 3 1 4 1 0 4 4 3 1 4 5 3 2 2 7 7 1 0 7 8 1 8 9 6 2 0 4 5 2 6 17 11 1 1 0 2 1 5 1 1 3 4 8 2 0 1 0
>D13641\D13641\102..539\438\BAA02804.1\Homo sapiens\Human mRNA for KIAA0016 gene, complete cds./gene="KIAA0016"/codon_start=1/product="mitochondrial outer membrane protein 19"/protein_id="BAA02804.1"/db_xref="GI:285987"
3 1 1 0 4 1 1 1 3 9 4 1 0 1 0 0 2 3 2 0 0 2 5 1 0 1 1 5 0 7 1 1 3 4 3 1 4 1 3 8 3 1 2 11 0 1 8 3 4 3 2 1 2 1 6 0 1 2 4 2 0 0 0 1
>AK127827\AK127827\728..1117\390\BAC87150.1\Homo sapiens\Homo sapiens cDNA FLJ45930 fis, clone PLACE7000707./codon_start=1/protein_id="BAC87150.1"/db_xref="GI:34534909"
2 1 2 1 0 4 0 4 5 1 0 2 3 1 1 3 5 1 1 1 0 1 4 1 1 6 1 1 2 2 6 1 5 1 0 1 5 3 0 1 0 1 1 3 2 0 1 4 2 5 1 2 3 1 3 8 2 0 2 2 6 0 1 0
>AF213668\AF213668\54..950\897\AAG40147.1\Homo sapiens\Homo sapiens bHLHZip transcription factor BIGMAX gamma mRNA,complete cds./codon_start=1/product="bHLHZip transcription factor BIGMAX gamma"/protein_id="AAG40147.1"/db_xref="GI:11761696"
1 3 6 2 4 4 2 3 6 3 1 2 2 13 0 5 9 3 1 6 3 2 1 9 1 2 4 12 4 4 1 8 6 2 2 8 10 1 5 17 6 2 4 17 8 1 3 18 13 6 6 3 2 3 6 3 0 8 6 3 2 0 0 1
>BC069110\BC069110\31..774\744\AAH69110.1\Homo sapiens\Homo sapiens chymase 1, mast cell, mRNA (cDNA clone MGC:95388IMAGE:7216927), complete cds./gene="CMA1"/codon_start=1/product="chymase 1, mast cell, preproprotein"/protein_id="AAH69110.1"/db_xref="GI:46575745"/db_xref="GeneID:1215"/db_xref="MIM:118938"
1 1 4 1 6 2 1 5 12 8 1 3 3 5 1 4 2 0 7 3 1 4 4 8 1 4 4 5 0 8 5 6 6 4 2 3 7 1 4 10 6 3 3 6 4 5 5 5 5 3 3 2 4 4 6 6 4 7 1 5 3 1 0 0
>AK091742\AK091742\132..2195\2064\BAC03738.1\Homo sapiens\Homo sapiens cDNA FLJ34423 fis, clone HHDPC2008123, highly similarto NUCLEOLIN./codon_start=1/protein_id="BAC03738.1"/db_xref="GI:21750187"
7 0 3 1 10 5 2 5 6 3 5 7 7 8 0 6 7 8 11 5 2 16 10 4 1 13 20 17 5 23 26 20 10 22 5 9 8 13 47 37 7 14 6 8 1 0 58 44 26 47 3 5 0 1 5 21 3 6 8 8 2 0 1 0
>BC035311\BC035311\178..1608\1431\AAH35311.1\Homo sapiens\Homo sapiens dermokine, mRNA (cDNA clone MGC:21664 IMAGE:4752921),complete cds./gene="ZD52F10"/codon_start=1/product="dermokine"/protein_id="AAH35311.1"/db_xref="GI:54035054"/db_xref="GeneID:93099"
3 2 1 1 5 2 0 6 13 3 0 1 8 11 2 9 25 12 1 5 2 9 6 9 2 9 11 15 3 9 25 46 24 15 0 9 6 2 7 10 20 13 4 19 5 5 10 10 5 6 5 3 3 1 6 8 1 2 7 3 11 0 1 0
>BC027583\BC027583\153..209\57\AAH27583.1\Homo sapiens\Homo sapiens microtubule-associated protein 2, mRNA (cDNA cloneIMAGE:4837202), complete cds./gene="MAP2"/codon_start=1/product="MAP2 protein"/protein_id="AAH27583.1"/db_xref="GI:71052145"/db_xref="GeneID:4133"/db_xref="MIM:157130"
0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 2 0 0 2 0 0 0 0 0 0 0 0 0 1 1 1 0 0
>BT007282\BT007282\1..1938\1938\AAP35946.1\Homo sapiens\Homo sapiens eukaryotic translation initiation factor 4 gamma, 1mRNA, complete cds./codon_start=1/product="eukaryotic translation initiation factor 4 gamma, 1"/protein_id="AAP35946.1"/db_xref="GI:30583403"
13 9 13 8 3 4 5 17 34 7 3 8 7 8 1 7 18 10 7 7 6 4 4 18 1 11 11 16 7 19 8 15 14 9 5 5 21 3 13 29 10 4 3 30 4 6 24 42 22 11 6 6 3 2 11 6 2 13 11 12 9 0 1 0
>AF311312\AF311312 S58544\199..2979\2781\AAG23967.1\Homo sapiens\Homo sapiens infertility-related sperm protein mRNA, complete cds./codon_start=1/product="infertility-related sperm protein"/protein_id="AAG23967.1"/db_xref="GI:10863768"
3 3 8 4 13 13 14 12 18 22 11 14 15 3 1 10 14 13 19 8 3 13 16 4 9 14 25 27 17 19 18 24 9 6 8 3 10 8 60 38 21 21 10 26 1 15 62 33 12 40 8 21 7 13 9 15 10 8 24 14 7 1 0 0
>AF151808\AF151808\70..1386\1317\AAD34045.1\Homo sapiens\Homo sapiens CGI-50 protein mRNA, complete cds./codon_start=1/product="CGI-50 protein"/protein_id="AAD34045.1"/db_xref="GI:4929569"
1 3 5 0 6 8 3 9 22 4 2 6 2 10 3 2 13 3 5 12 8 6 6 11 4 4 8 17 4 8 6 11 5 3 5 3 19 2 10 11 13 2 2 9 9 4 4 21 15 4 12 0 13 4 11 8 1 12 10 12 2 0 0 1
>BC067765\BC067765\343..963\621\AAH67765.1\Homo sapiens\Homo sapiens SPFH domain family, member 2, mRNA (cDNA cloneMGC:87072 IMAGE:5296776), complete cds./gene="SPFH2"/codon_start=1/product="SPFH2 protein"/protein_id="AAH67765.1"/db_xref="GI:45709604"/db_xref="GeneID:11160"
0 0 0 0 3 2 1 7 7 3 1 1 4 2 1 4 2 4 3 2 1 4 0 1 1 6 3 3 1 6 3 3 2 7 2 4 14 1 1 10 6 2 4 7 5 3 4 5 3 3 3 6 3 2 7 3 3 4 3 7 3 0 1 0
>HSU19D8\Z70689\complement(join(4824..5056,6232..6395,7157..7338, 7437..7657,7904..8040,8807..8997,9761..9856))\1224\CAI41980.1\Homo sapiens\Human DNA sequence from clone LL0XNC01-19D8 on chromosome XContains the 5' end of the NXF2 gene for nuclear RNA export factor2, complete sequence./gene="NXF2"/locus_tag="GHc-618H1.1-001"/standard_name="OTTHUMP00000023709"/codon_start=1/product="nuclear RNA export factor 2"/protein_id="CAI41980.1"/db_xref="GI:57210044"/db_xref="UniProt/TrEMBL:Q5H9J9"
2 1 1 3 6 2 14 17 18 9 3 6 5 4 0 6 7 7 7 7 0 9 6 4 2 9 8 6 2 6 1 10 2 2 2 4 8 5 12 7 11 6 6 19 3 9 23 12 7 11 6 4 4 5 6 9 3 11 5 12 5 0 0 1
>AF222043\AF222043\173..1681\1509\AAF37827.2\Homo sapiens\Homo sapiens ubiquitin-associated protein (NAG20) mRNA, completecds./gene="NAG20"/codon_start=1/product="ubiquitin-associated protein"/protein_id="AAF37827.2"/db_xref="GI:7948993"
0 1 5 0 3 1 4 11 12 9 7 14 7 13 1 11 15 8 10 6 4 8 10 11 0 14 8 10 3 10 7 11 4 3 3 7 9 5 18 20 8 16 2 18 6 5 21 24 14 11 3 3 3 8 12 9 3 4 11 17 1 0 0 1
>HUMLFERR\M83202\8..2143\2136\AAA59511.1\Homo sapiens\Human lactoferrin (HLF1) mRNA, complete cds./gene="HLF1"/codon_start=1/product="lactoferrin"/protein_id="AAA59511.1"/db_xref="GI:187122"
3 5 7 4 13 13 0 13 32 10 2 9 5 13 2 10 12 8 8 9 2 12 6 10 6 13 12 27 8 18 12 23 12 8 2 11 32 5 23 23 17 15 8 21 4 5 19 23 22 16 12 9 17 16 21 11 4 7 5 6 10 1 0 0
>BC005279\BC005279\23..1282\1260\AAH05279.1\Homo sapiens\Homo sapiens carboxypeptidase A1 (pancreatic), mRNA (cDNA cloneMGC:12328 IMAGE:3949850), complete cds./gene="CPA1"/codon_start=1/product="pancreatic carboxypeptidase A1, precursor"/protein_id="AAH05279.1"/db_xref="GI:13528975"/db_xref="GeneID:1357"/db_xref="MIM:114850"
2 5 7 2 0 1 0 7 22 3 0 5 0 15 2 2 10 5 4 14 5 6 3 9 1 4 4 17 4 5 2 16 11 0 3 10 12 0 1 19 9 3 2 16 10 3 3 22 20 5 11 8 1 1 14 9 0 23 7 6 8 0 0 1
>HUMPTS4\U63383\join(U63380.1:17..99,U63381.1:11..90,U63382.1:11..33, U63382.1:429..485,11..81,280..403)\-25149\AAC16970.1\Homo sapiens\Homo sapiens 6-pyruvoyl-tetrahydropterin synthase gene, exon 5,exon 6, and complete cds./codon_start=1/product="6-pyruvoyl-tetrahydropterin synthase"/protein_id="AAC16970.1"/db_xref="GI:3142325"
2 0 0 0 1 2 0 1 5 4 1 5 0 0 0 0 2 1 0 0 1 3 2 5 0 2 4 1 1 1 2 1 1 1 4 1 8 4 5 3 1 5 0 4 0 3 4 2 2 9 3 6 2 1 1 3 2 4 4 6 6 1 1 2
>AK093122\AK093122\203..1336\1134\BAC04063.1\Homo sapiens\Homo sapiens cDNA FLJ35803 fis, clone TESTI2005979./codon_start=1/protein_id="BAC04063.1"/db_xref="GI:21751892"
4 10 13 3 2 10 1 12 24 3 1 3 5 8 6 3 7 3 4 10 2 1 7 18 10 6 2 15 10 6 5 12 13 3 1 6 7 0 2 14 5 0 4 15 7 1 3 17 13 2 3 0 5 4 11 1 0 1 3 2 8 0 1 0
>AF168954\AF168954\133..1071\939\AAM88911.1\Homo sapiens\Homo sapiens LFIRE1 (LFIRE1) mRNA, complete cds./gene="LFIRE1"/codon_start=1/product="LFIRE1"/protein_id="AAM88911.1"/db_xref="GI:22023090"
1 1 2 1 5 4 0 4 5 8 1 3 1 2 1 7 5 4 2 5 2 4 3 1 0 2 7 2 2 4 11 6 6 2 3 6 4 5 14 7 6 16 5 13 3 4 13 8 8 13 7 10 1 4 8 9 1 4 8 6 12 1 0 0
>AF022813\AF022813\105..821\717\AAC51864.1\Homo sapiens\Homo sapiens tetraspan (NAG-2) mRNA, complete cds./gene="NAG-2"/codon_start=1/product="tetraspan"/protein_id="AAC51864.1"/db_xref="GI:2586350"
0 2 1 0 0 1 0 8 25 1 0 2 0 5 1 1 3 1 1 8 6 2 0 1 2 1 1 18 4 2 1 14 3 2 1 5 10 0 1 8 8 0 2 7 2 0 0 7 7 0 8 1 10 3 15 2 0 11 1 5 7 0 1 0
>BC045759\BC045759\752..952\201\AAH45759.1\Homo sapiens\Homo sapiens microtubule-associated protein 1 light chain 3 beta,mRNA (cDNA clone MGC:48651 IMAGE:4828857), complete cds./gene="MAP1LC3B"/codon_start=1/product="MAP1LC3B protein"/protein_id="AAH45759.1"/db_xref="GI:71297332"/db_xref="GeneID:81631"
0 1 0 0 1 1 0 2 2 0 1 2 2 2 0 0 2 2 1 0 1 0 1 0 0 0 0 2 0 1 2 0 1 0 0 3 3 0 2 1 1 2 0 3 1 0 1 5 0 2 1 2 0 0 4 0 1 2 1 4 0 1 0 0
>AF151980\AF151980\1..1149\1149\AAD37802.2\Homo sapiens\Homo sapiens connexin 43 (CX43) gene, complete cds./gene="CX43"/codon_start=1/product="connexin 43"/protein_id="AAD37802.2"/db_xref="GI:6563408"
6 3 2 2 4 0 2 7 14 2 2 7 5 4 1 12 9 6 2 5 1 5 4 5 0 10 3 11 4 8 6 4 7 6 2 3 13 8 10 18 7 9 7 11 1 7 8 10 10 8 10 6 5 4 17 4 2 15 5 7 6 0 1 0
>AK023746\AK023746\162..947\786\BAB14665.1\Homo sapiens\Homo sapiens cDNA FLJ13684 fis, clone PLACE2000021, moderatelysimilar to Homo sapiens TRF1-interacting ankyrin-related ADP-ribosepolymerase mRNA./codon_start=1/protein_id="BAB14665.1"/db_xref="GI:10435772"
2 0 2 0 8 4 4 2 4 3 3 3 1 2 0 9 1 4 2 2 0 5 3 1 1 4 5 1 1 5 13 3 3 9 4 2 2 6 9 6 7 6 4 5 9 7 11 10 1 7 5 8 2 3 3 8 3 5 10 7 1 1 0 0
>AF303084\AF303084\43..534\492\AAQ14494.1\Homo sapiens\Homo sapiens epididymal-specific lipocalin LCN6 mRNA, complete cds./codon_start=1/product="epididymal-specific lipocalin LCN6"/protein_id="AAQ14494.1"/db_xref="GI:33340037"
1 0 2 0 2 2 0 3 16 3 0 2 2 3 1 1 3 2 1 4 2 2 1 4 0 1 0 8 1 3 3 5 6 0 0 3 12 0 0 5 6 1 0 7 1 0 2 9 6 0 2 1 0 1 6 3 2 2 0 5 5 0 1 0
>AL158839#4\AL158839\join(28627..28883,40119..40206)\345\CAH70972.1\Homo sapiens\Human DNA sequence from clone RP11-180O5 on chromosome 1 Containsthe 5' end of gene DKFZP566D1346, the HHLA3 gene for HERV-HLTR-associating 3 and a novel gene, complete sequence./gene="HHLA3"/locus_tag="RP11-180O5.1-002"/standard_name="OTTHUMP00000010943"/codon_start=1/product="HERV-H LTR-associating 3"/protein_id="CAH70972.1"/db_xref="GI:55661699"/db_xref="UniProt/TrEMBL:Q5VZP2"
0 0 2 1 4 3 2 1 0 2 1 0 0 1 0 4 1 2 1 3 2 2 5 2 0 2 4 2 3 0 3 0 2 1 1 2 0 0 6 3 0 2 4 2 2 2 2 8 0 2 1 1 3 5 1 2 1 2 0 5 1 0 1 0
>AL135927#24\AL135927\complement(join(131817..132091,132449..132599, 132830..132926,133223..133349,133470..133675, 133811..133917))\963\CAI15543.1\Homo sapiens\Human DNA sequence from clone RP11-54H19 on chromosome 1 Containsthe 3' end of the LMNA gene for lamin A/C, the gene for a novelprotein similar to semaphorins (FLJ12287), a novel gene (KIAA0446),the PMF1 gene for polyamine-modulated factor 1, the BGLAP gene forbone gamma-carboxyglutamate (gla) protein (osteocalcin), the genefor progestin and adipoQ receptor family member VI (PAQR6) and the3' end of the gene for Est1p-like protein B (EST1B), completesequence./gene="PAQR6"/locus_tag="RP11-54H19.6-002"/standard_name="OTTHUMP00000018882"/codon_start=1/product="progestin and adipoQ receptor family member VI"/protein_id="CAI15543.1"/db_xref="GI:55957519"/db_xref="GOA:Q5TCK8"/db_xref="UniProt/TrEMBL:Q5TCK8"
0 7 3 2 1 2 1 17 31 1 1 2 1 8 3 1 8 3 6 9 1 2 4 8 3 5 6 18 7 6 3 18 5 2 0 5 4 0 1 1 5 0 1 9 13 2 3 6 3 2 11 3 10 3 21 3 0 4 2 6 7 0 0 1
>HS1039K5#4\AL031587\join(43475..43590,83147..83425,83552..83588)\432\CAI18967.1\Homo sapiens\Human DNA sequence from clone RP5-1039K5 on chromosome22q12.3-13.2, complete sequence./locus_tag="RP5-1039K5.7-007"/standard_name="OTTHUMP00000028518"/codon_start=1/protein_id="CAI18967.1"/db_xref="GI:56202770"/db_xref="UniProt/TrEMBL:Q5JYU7"
0 1 1 0 4 1 1 5 4 3 0 4 3 5 1 8 1 2 0 2 2 1 2 7 3 5 1 5 1 4 2 4 4 1 1 2 4 1 0 3 2 4 1 1 1 2 3 4 8 1 0 0 6 2 1 0 0 2 0 3 3 0 0 1
>CR456751\CR456751\1..261\261\CAG33032.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834C1216D forgene SNRPF, small nuclear ribonucleoprotein polypeptide F; completecds, incl. stopcodon./gene="SNRPF"/codon_start=1/protein_id="CAG33032.1"/db_xref="GI:48145619"
0 0 0 0 2 1 1 2 2 3 2 1 0 0 0 2 0 1 2 0 0 0 1 2 0 1 1 0 0 1 5 2 1 2 2 1 3 1 2 3 1 5 0 1 0 1 8 2 0 4 3 2 0 1 1 0 2 1 0 6 1 1 0 0
>BC003557\BC003557\46..999\954\AAH03557.1\Homo sapiens\Homo sapiens apolipoprotein E, mRNA (cDNA clone MGC:1571IMAGE:3355712), complete cds./gene="APOE"/codon_start=1/product="apolipoprotein E precursor"/protein_id="AAH03557.1"/db_xref="GI:13097699"/db_xref="GeneID:348"/db_xref="MIM:107741"
0 22 10 1 0 1 1 7 31 0 0 2 0 4 1 1 8 0 3 7 1 1 0 4 3 1 4 24 9 2 1 13 3 1 0 2 21 1 1 12 0 1 2 30 2 0 6 34 8 3 4 0 2 0 3 1 1 1 0 8 8 0 0 1
>BC074940\BC074940\41..796\756\AAH74940.1\Homo sapiens\Homo sapiens tumor necrosis factor (ligand) superfamily, member 15,mRNA (cDNA clone MGC:104048 IMAGE:30915494), complete cds./gene="TNFSF15"/codon_start=1/product="tumor necrosis factor (ligand) superfamily, member 15"/protein_id="AAH74940.1"/db_xref="GI:49902479"/db_xref="GeneID:9966"/db_xref="MIM:604052"
2 1 1 1 3 3 4 7 10 3 1 3 1 3 1 3 8 3 7 9 0 2 7 4 0 3 7 8 0 3 8 3 4 1 3 4 7 2 5 7 6 1 4 11 4 2 8 7 6 4 6 2 5 1 11 4 0 6 1 7 3 0 1 0
>AK074216\AK074216\79..708\630\BAB85019.1\Homo sapiens\Homo sapiens cDNA FLJ23636 fis, clone CAS07176./codon_start=1/protein_id="BAB85019.1"/db_xref="GI:18676757"
0 1 0 0 6 3 8 2 5 4 1 2 2 2 1 5 3 1 2 0 1 2 4 5 1 5 7 2 0 3 6 1 2 1 5 2 5 8 11 12 4 3 4 1 3 0 10 7 3 3 3 3 3 1 5 11 3 4 3 1 3 0 0 1
>HSM800550\AL050393\1729..2511\783\CAB43687.2\Homo sapiens\Homo sapiens mRNA; cDNA DKFZp586F0420 (from clone DKFZp586F0420);partial cds./gene="DKFZp586F0420"/codon_start=1/product="hypothetical protein"/protein_id="CAB43687.2"/db_xref="GI:6562171"/db_xref="UniProt/TrEMBL:Q9UG54"
2 2 0 3 5 3 4 0 3 3 5 6 6 6 0 7 5 10 8 6 1 8 7 2 1 4 7 3 0 4 6 3 1 1 2 2 3 3 11 7 5 6 11 14 1 3 15 4 6 8 2 2 2 1 0 1 1 4 4 9 1 0 0 1
>BC039174\BC039174\82..3282\3201\AAH39174.1\Homo sapiens\Homo sapiens vinculin, mRNA (cDNA clone MGC:21734 IMAGE:4520338),complete cds./gene="VCL"/codon_start=1/product="VCL protein"/protein_id="AAH39174.1"/db_xref="GI:24657579"/db_xref="GeneID:7414"/db_xref="MIM:193065"
11 7 16 10 15 7 7 20 33 15 8 12 16 12 2 12 10 6 17 20 6 18 17 7 7 23 26 48 6 53 19 10 15 11 7 9 40 14 37 39 23 15 12 50 6 5 39 50 24 40 3 5 5 5 7 8 7 20 29 36 9 0 1 0
>BC010464\BC010464\96..368\273\AAH10464.1\Homo sapiens\Homo sapiens mitogen-activated protein kinase kinase kinase 3, mRNA(cDNA clone IMAGE:4179950), complete cds./gene="MAP3K3"/codon_start=1/product="MAP3K3 protein"/protein_id="AAH10464.1"/db_xref="GI:14714649"/db_xref="GeneID:4215"
1 0 0 0 0 1 1 2 6 1 1 2 1 1 0 2 1 2 0 2 0 4 2 0 1 5 2 3 0 3 3 5 2 0 0 5 2 4 1 2 0 3 1 0 0 0 2 4 0 0 1 1 1 2 0 1 0 0 1 4 1 0 0 1
>AY258289\AY258289\join(5573..5728,6880..7017,8678..8734,11369..11530, 13337..13438,13967..13996)\645\AAP14648.1\Homo sapiens\Homo sapiens membrane-spanning 4-domains subfamily A member 3(MS4A3) gene, complete cds./gene="MS4A3"/codon_start=1/product="membrane-spanning 4-domains subfamily A member 3"/protein_id="AAP14648.1"/db_xref="GI:30144639"
0 0 0 0 2 1 4 2 8 1 3 4 11 4 0 7 0 5 4 5 0 3 4 3 2 1 8 6 1 4 4 4 4 4 2 2 4 4 3 1 3 10 3 5 4 1 4 5 1 3 6 1 4 3 6 5 6 4 6 6 3 1 0 0
>AF126021\AF126021\186..1085\900\AAF17231.1\Homo sapiens\Homo sapiens B-cell receptor-associated protein BAP37 mRNA,complete cds./codon_start=1/evidence=not_experimental/product="B-cell receptor-associated protein BAP37"/protein_id="AAF17231.1"/db_xref="GI:6563274"
6 4 8 1 2 3 3 4 14 5 0 7 2 7 0 2 6 3 6 3 2 1 0 4 1 5 3 23 1 5 4 7 4 4 3 1 15 0 7 12 5 6 2 20 2 0 8 12 8 3 6 2 0 0 9 1 0 16 5 5 1 0 0 1
>AK126160\AK126160\2311..2922\612\BAC86466.1\Homo sapiens\Homo sapiens cDNA FLJ44172 fis, clone THYMU2036085./codon_start=1/protein_id="BAC86466.1"/db_xref="GI:34532558"
0 0 0 1 1 2 4 18 10 6 1 2 3 7 0 21 1 2 1 0 0 4 0 3 0 6 0 3 0 7 0 1 0 3 2 10 3 4 2 0 0 4 3 2 3 1 2 1 0 1 1 6 3 9 10 14 0 2 8 2 3 0 0 1
>BC036724\BC036724\572..1588\1017\AAH36724.1\Homo sapiens\Homo sapiens FBJ murine osteosarcoma viral oncogene homolog B, mRNA(cDNA clone MGC:39968 IMAGE:5212854), complete cds./gene="FOSB"/codon_start=1/product="FBJ murine osteosarcoma viral oncogene homolog B"/protein_id="AAH36724.1"/db_xref="GI:54673701"/db_xref="GeneID:2354"/db_xref="MIM:164772"
5 3 5 1 2 4 1 11 13 1 0 2 2 14 5 6 8 8 4 12 3 2 7 20 11 6 5 13 6 5 4 13 7 3 0 6 7 3 4 5 4 1 6 12 2 0 9 19 10 4 6 1 5 0 7 4 0 4 0 5 2 0 0 1
>AY242134\AY242134\1..1161\1161\AAO92301.1\Homo sapiens\Homo sapiens prostaglandin I2 (prostacyclin) receptor (PTGIR) mRNA,complete cds./gene="PTGIR"/codon_start=1/product="prostaglandin I2 (prostacyclin) receptor"/protein_id="AAO92301.1"/db_xref="GI:29825395"
3 14 3 0 0 4 0 17 34 3 0 2 1 7 8 2 14 1 3 10 2 0 3 12 5 6 2 35 10 5 5 18 8 2 0 8 19 0 1 4 5 0 1 14 5 0 1 7 9 2 8 1 18 0 20 1 0 8 0 10 5 0 0 1
>AB049824\AB049824\203..934\732\BAC06820.1\Homo sapiens\Homo sapiens mRNA for JC7, complete cds./gene="JC7"/codon_start=1/product="JC7"/protein_id="BAC06820.1"/db_xref="GI:22090467"
3 2 2 0 5 2 2 1 0 0 0 0 7 2 3 11 3 6 4 1 1 2 5 8 2 5 6 1 1 4 2 5 4 1 0 1 6 3 21 17 1 4 3 6 1 1 25 11 4 25 1 2 0 0 2 1 0 0 1 6 0 1 0 0
>AB102799\AB102799\1..168\168\BAD89390.1\Homo sapiens\Homo sapiens IL6ST mRNA for IL6ST nirs variant 1, complete cds./gene="IL6ST"/codon_start=1/product="IL6ST nirs variant 1"/protein_id="BAD89390.1"/db_xref="GI:58736963"
0 0 0 0 0 0 2 1 3 0 0 7 1 0 0 2 0 1 4 1 1 2 1 1 0 1 2 1 0 0 0 0 2 0 0 0 2 0 0 2 1 0 3 1 1 1 1 0 0 0 0 0 0 1 1 1 0 0 5 1 1 0 1 0
>HSDJ261K5#3\AL050350\join(27067..27146,29147..29322,34171..34279,37663..37839, 49271..49838)\1110\CAI42510.1\Homo sapiens\Human DNA sequence from clone RP1-261K5 on chromosome 6q21-22.1Contains the 3' end of the SLC22A16 gene for solute carrier family22 (organic cation transporter) member 16, the DDO gene forD-aspartate oxidase, the 5' part of a novel gene and two CpGislands, complete sequence./gene="DDO"/locus_tag="RP1-261K5.2-001"/standard_name="OTTHUMP00000017001"/codon_start=1/protein_id="CAI42510.1"/db_xref="GI:57208416"/db_xref="GOA:Q5JXM5"/db_xref="InterPro:IPR006076"/db_xref="InterPro:IPR006181"/db_xref="UniProt/TrEMBL:Q5JXM5"
7 0 2 0 6 12 1 9 13 6 0 3 6 8 0 1 4 4 8 7 2 8 5 8 4 5 8 9 1 9 10 10 6 8 4 5 14 5 5 8 3 4 4 10 8 6 9 10 9 8 2 5 6 4 6 12 3 6 9 4 10 0 1 0
>BT006799\BT006799\1..273\273\AAP35445.1\Homo sapiens\Homo sapiens ALL1-fused gene from chromosome 1q mRNA, complete cds./codon_start=1/product="ALL1-fused gene from chromosome 1q"/protein_id="AAP35445.1"/db_xref="GI:30582437"
0 0 0 0 1 2 0 2 6 2 0 1 1 2 1 0 5 2 1 2 0 1 1 2 0 2 3 2 0 1 0 3 1 2 0 1 1 1 3 1 2 0 1 2 1 0 4 3 4 3 3 0 0 0 4 1 0 3 1 3 2 0 1 0
>HSUBA80R\X63237\26..496\471\CAA44911.1\Homo sapiens\H.sapiens Uba80 mRNA for ubiquitin./gene="UbA80"/codon_start=1/product="ubiquitin"/protein_id="CAA44911.1"/db_xref="GI:37571"
1 1 0 3 4 1 0 1 5 5 0 2 0 0 1 4 0 2 0 4 2 4 1 2 0 3 1 1 0 4 2 3 2 3 1 1 4 2 6 19 1 4 1 5 2 2 6 4 3 6 3 3 1 5 2 3 1 3 4 2 0 1 0 0
>AY064485\AY064485\1..1536\1536\AAL57720.1\Homo sapiens\Homo sapiens cytochrome P450 (CYP4B1) mRNA, CYP4B1*3 allele,complete cds./gene="CYP4B1"/allele="CYP4B1*3"/codon_start=1/product="cytochrome P450"/protein_id="AAL57720.1"/db_xref="GI:18086502"
0 11 9 3 3 6 2 18 32 5 1 6 2 10 0 8 10 3 6 9 2 4 5 12 1 11 5 15 1 8 5 13 11 4 1 8 17 1 7 20 5 3 0 21 11 11 4 18 23 11 9 8 7 1 21 15 0 16 4 16 12 0 1 0
>AF099935\AF099935\85..681\597\AAC72975.1\Homo sapiens\Homo sapiens MDC-3.13 isoform 2 mRNA, complete cds./codon_start=1/product="MDC-3.13 isoform 2"/protein_id="AAC72975.1"/db_xref="GI:3860093"
0 1 2 0 2 3 2 3 5 2 4 5 2 6 0 0 0 3 3 6 0 1 0 1 0 1 4 6 0 2 1 0 1 2 0 3 8 3 8 12 5 10 5 5 4 4 7 9 3 8 2 3 1 2 1 9 2 8 2 6 0 0 0 1
>BC013724\BC013724\189..740\552\AAH13724.1\Homo sapiens\Homo sapiens ferritin, heavy polypeptide 1, mRNA (cDNA cloneMGC:17255 IMAGE:3857790), complete cds./gene="FTH1"/codon_start=1/product="ferritin, heavy polypeptide 1"/protein_id="AAH13724.1"/db_xref="GI:15489239"/db_xref="GeneID:2495"/db_xref="MIM:134770"
2 4 0 0 0 1 1 2 10 2 1 6 2 3 1 3 2 1 1 4 1 1 1 2 0 0 2 6 3 2 2 2 1 2 0 0 5 1 8 5 6 6 2 8 5 5 7 9 10 5 8 1 0 3 2 4 0 5 1 5 1 1 0 0
>HUAC002550#3\AC002550\complement(join(43656..43754,44484..44630,52661..52779, 61742..61907,74833..74922))\621\AAC05806.1\Homo sapiens\Human Chromosome 16 BAC clone CIT987SK-A-101F10, complete sequence./gene="101F10.2"/codon_start=1/product="Unknown gene product"/protein_id="AAC05806.1"/db_xref="GI:2911265"
1 3 1 0 1 3 3 9 13 5 2 2 0 5 3 1 6 0 1 6 4 2 2 0 1 2 3 5 0 1 1 2 4 0 0 3 4 2 5 8 10 2 3 6 3 6 5 8 10 3 6 0 2 2 5 3 2 6 2 6 2 0 0 1
>BC017441\BC017441\266..622\357\AAH17441.1\Homo sapiens\Homo sapiens solute carrier family 30 (zinc transporter), member 5,mRNA (cDNA clone IMAGE:3630637), complete cds./gene="SLC30A5"/codon_start=1/product="zinc transporter ZTL1"/protein_id="AAH17441.1"/db_xref="GI:16924303"/db_xref="GeneID:64924"/db_xref="MIM:607819"
1 0 0 0 1 1 4 1 1 3 4 2 2 0 0 2 1 0 1 1 0 3 1 2 1 2 1 1 0 3 3 7 4 1 1 0 5 3 12 3 1 1 1 2 2 0 2 2 3 2 1 2 0 1 3 7 2 0 6 2 0 0 0 1
>S72008\S72008\49..1305\1257\AAB31337.1\Homo sapiens\hCDC10=CDC10 homolog [human, fetal lung, mRNA, 2314 nt]./gene="hCDC10"/codon_start=1/protein_id="AAB31337.1"/db_xref="GI:560623"
1 1 1 6 11 4 2 5 4 7 6 9 4 1 2 5 2 3 8 2 1 5 8 0 0 7 7 2 0 8 9 2 2 8 6 3 11 10 28 19 10 16 11 16 3 7 30 15 6 13 6 6 2 3 4 10 5 9 9 14 3 1 0 0
>AK126695\AK126695\64..1260\1197\BAC86646.1\Homo sapiens\Homo sapiens cDNA FLJ44741 fis, clone BRACE3027931./codon_start=1/protein_id="BAC86646.1"/db_xref="GI:34533273"
0 12 0 9 2 1 3 27 19 5 0 3 14 6 11 7 11 0 4 1 0 32 3 5 0 3 23 6 13 11 0 3 1 0 14 2 1 0 1 1 19 2 20 9 10 4 2 2 2 1 1 15 32 4 4 1 2 0 1 13 0 0 0 1
>AY358759\AY358759\286..1902\1617\AAQ89119.1\Homo sapiens\Homo sapiens clone DNA97003 TREC2422 (UNQ2422) mRNA, complete cds./locus_tag="UNQ2422"/codon_start=1/product="TREC2422"/protein_id="AAQ89119.1"/db_xref="GI:37182637"
5 8 6 1 1 2 7 21 40 8 1 11 4 10 3 7 10 6 6 13 0 11 7 9 4 6 10 23 4 6 9 9 9 11 10 13 28 2 1 11 6 3 1 14 8 0 5 10 11 2 12 8 7 2 21 11 3 27 8 16 10 0 1 0
>BC014946\BC014946\187..1113\927\AAH14946.1\Homo sapiens\Homo sapiens translocase of outer mitochondrial membrane 40homolog-like (yeast), mRNA (cDNA clone MGC:22951 IMAGE:4872309),complete cds./gene="TOMM40L"/codon_start=1/product="TOMM40L protein"/protein_id="AAH14946.1"/db_xref="GI:15928956"/db_xref="GeneID:84134"
2 3 6 1 2 2 5 8 17 1 0 8 1 1 2 0 8 5 8 2 1 8 3 8 1 4 7 10 2 7 9 9 9 2 6 4 11 6 1 7 8 4 1 12 10 5 3 12 4 7 5 4 1 2 11 4 1 3 1 8 5 0 0 1
>AF015185\AF015185\354..1547\1194\AAB92496.1\Homo sapiens\Homo sapiens clone ET10 ET putative translation product (ET) mRNA,alternatively spliced complete cds./gene="ET"/codon_start=1/product="ET putative translation product"/protein_id="AAB92496.1"/db_xref="GI:2708503"
2 1 1 1 2 2 4 8 10 10 6 4 2 3 0 15 12 8 10 4 1 7 3 0 4 4 5 16 1 12 16 8 2 6 4 5 11 9 8 7 6 9 4 5 3 0 11 5 7 6 7 6 3 3 17 24 3 10 21 10 3 0 0 1
>BC017034\BC017034\87..782\696\AAH17034.1\Homo sapiens\Homo sapiens lysophospholipase II, mRNA (cDNA clone MGC:9106IMAGE:3845764), complete cds./gene="LYPLA2"/codon_start=1/product="lysophospholipase II"/protein_id="AAH17034.1"/db_xref="GI:16877568"/db_xref="GeneID:11313"
1 0 5 0 0 2 0 8 13 2 1 2 1 4 0 3 3 2 3 6 3 0 2 7 1 10 4 13 3 8 4 5 6 2 1 6 7 2 0 11 4 2 0 5 5 4 3 9 6 2 3 0 3 3 2 5 1 8 2 10 3 1 0 0
>HSA245821\AJ245821\85..1827\1743\CAB57951.1\Homo sapiens\Homo sapiens mRNA for putative secreted molecule (psk-2 gene)./gene="psk-2"/function="putative role in seizures"/codon_start=1/product="putative secreted molecule"/protein_id="CAB57951.1"/db_xref="GI:6018462"/db_xref="UniProt/TrEMBL:Q9UJ46"
3 10 10 1 0 7 2 14 45 7 1 5 4 9 5 4 14 3 5 17 10 6 17 28 9 13 6 21 0 4 12 21 21 7 2 12 16 3 2 2 9 9 3 18 11 4 13 34 17 7 7 6 9 7 10 5 2 14 3 8 6 0 1 0
>HSMSHR\X65634\462..1415\954\CAA46588.1\Homo sapiens\H.sapiens MSH-R gene for melanocyte stimulating hormone receptor./gene="MSH-R"/codon_start=1/evidence=experimental/product="melanocyte stimulating hormone receptor"/protein_id="CAA46588.1"/db_xref="GI:34791"/db_xref="GOA:Q01726"/db_xref="UniProt/Swiss-Prot:Q01726"
1 4 6 0 2 2 0 20 31 2 0 2 1 8 1 1 8 1 4 6 5 0 0 7 3 0 2 24 4 5 2 9 4 1 0 10 19 1 1 4 8 2 0 11 9 1 0 7 7 0 8 0 14 0 15 2 0 21 2 6 3 0 0 1
>AK000922\AK000922\273..1619\1347\BAA91427.1\Homo sapiens\Homo sapiens cDNA FLJ10060 fis, clone HEMBA1001407./codon_start=1/protein_id="BAA91427.1"/db_xref="GI:7021891"
0 2 4 2 1 2 4 9 52 8 1 8 6 6 1 8 9 4 2 12 1 5 11 15 3 12 15 28 2 7 3 19 10 13 5 4 37 2 1 4 3 3 4 9 7 3 4 12 5 0 4 2 4 8 16 5 0 6 0 8 7 0 0 1
>BC047021\BC047021\130..1293\1164\AAH47021.1\Homo sapiens\Homo sapiens mRNA similar to immunoglobulin superfamily, member 4(cDNA clone MGC:51880 IMAGE:5248100), complete cds./codon_start=1/product="Similar to immunoglobulin superfamily, member 4"/protein_id="AAH47021.1"/db_xref="GI:28422552"
1 2 4 1 4 6 6 6 18 2 2 5 4 4 3 6 4 6 8 9 2 7 5 7 1 7 4 8 14 3 4 5 9 5 6 9 20 1 9 8 9 7 4 15 5 2 13 10 9 11 5 8 5 3 6 6 2 13 6 10 3 0 0 1
>AF165519\AF165519\25..579\555\AAF86649.1\Homo sapiens\Homo sapiens mitogen-activated protein kinase phosphatase x (MKPX)mRNA, complete cds./gene="MKPX"/codon_start=1/product="mitogen-activated protein kinase phosphatase x"/protein_id="AAF86649.1"/db_xref="GI:9294745"
0 1 2 1 6 2 0 3 12 1 0 3 1 2 0 2 4 2 3 2 0 1 3 2 0 2 3 8 2 2 3 4 4 1 1 4 5 1 5 6 7 1 2 6 4 4 6 8 2 5 3 2 4 1 5 3 0 5 5 4 3 1 0 0
>BC021708\BC021708\88..1104\1017\AAH21708.1\Homo sapiens\Homo sapiens HLA-G histocompatibility antigen, class I, G, mRNA(cDNA clone MGC:26146 IMAGE:4822521), complete cds./gene="HLA-G"/codon_start=1/product="HLA-G protein"/protein_id="AAH21708.1"/db_xref="GI:18203847"/db_xref="GeneID:3135"/db_xref="MIM:142871"
1 8 6 0 5 5 1 9 19 1 0 0 1 7 2 3 5 1 2 15 3 3 1 8 4 4 6 12 9 8 4 7 9 2 1 5 15 2 0 11 5 1 1 15 6 3 3 24 13 5 9 5 4 2 7 1 1 6 1 10 11 0 0 1
>BC093736\BC093736\36..1139\1104\AAH93736.1\Homo sapiens\Homo sapiens heparan sulfate (glucosamine) 3-O-sulfotransferase 2,mRNA (cDNA clone MGC:120771 IMAGE:7939581), complete cds./gene="HS3ST2"/codon_start=1/product="heparan sulfate D-glucosaminyl 3-O-sulfotransferase 2"/protein_id="AAH93736.1"/db_xref="GI:62739479"/db_xref="GeneID:9956"/db_xref="MIM:604056"
7 12 6 1 3 7 1 15 18 1 0 4 3 9 2 1 11 1 2 9 7 4 1 14 7 8 0 12 5 3 1 17 7 3 2 4 12 2 7 12 7 1 2 11 6 1 6 9 12 4 8 5 7 2 14 6 1 11 4 5 4 1 0 0
>AY055383\AY055383\join(242..267,363..565,5232..5365,7066..7133,7691..7875, 8189..8230,13999..14203,17362..17498,18942..19054, 19377..19486,28501..28646,29073..29171,30136..30249, 32749..32865,33129..33297,34437..34708,36819..36955, 37543..37701)\2436\AAL16413.1\Homo sapiens\Homo sapiens type II transmembrane serine protease 6 (TMPRSS6)gene, complete cds./gene="TMPRSS6"/codon_start=1/product="type II transmembrane serine protease 6"/protein_id="AAL16413.1"/db_xref="GI:23428409"
2 22 11 1 3 10 3 29 49 1 1 8 3 20 9 3 23 5 6 16 9 1 4 28 8 6 5 32 8 8 7 33 19 10 1 16 49 4 7 21 14 3 3 38 17 1 9 35 28 12 25 7 20 18 23 3 2 19 3 11 19 0 0 1
>AK094247\AK094247\20..1024\1005\BAC04317.1\Homo sapiens\Homo sapiens cDNA FLJ36928 fis, clone BRACE2005216, weakly similarto Xenopus laevis bicaudal-C (Bic-C) mRNA./codon_start=1/protein_id="BAC04317.1"/db_xref="GI:21753271"
1 2 5 1 4 6 1 5 9 5 3 4 7 16 3 10 16 6 5 8 2 7 7 14 3 8 8 8 4 3 7 14 9 5 0 3 5 2 10 10 9 2 3 9 7 3 5 13 7 4 0 1 0 1 3 5 2 4 6 3 1 0 0 1
>AL136128#4\AL136128\join(127425..127443,AL121938.10:41776..41891, AL121938.10:50816..50964,AL121938.10:69980..70081, AL121938.10:75415..75453,AL121938.10:84532..84541)\-609666\CAI23002.1\Homo sapiens\Human DNA sequence from clone RP1-84N20 on chromosome 6 Contains anovel gene, the 5' end of the TPD52L1 gene encoding two variants oftumor protein D52-like 1 protein and two CpG islands, completesequence./gene="TPD52L1"/locus_tag="RP1-167O5.1-003"/standard_name="OTTHUMP00000017135"/codon_start=1/protein_id="CAI23002.1"/db_xref="GI:56204340"/db_xref="InterPro:IPR007327"/db_xref="UniProt/TrEMBL:Q9BUQ6"
0 0 0 0 2 2 1 5 5 5 7 0 3 1 0 3 1 3 3 2 0 1 4 4 0 1 2 1 1 2 3 1 0 0 3 2 2 2 2 3 1 6 3 4 3 4 3 2 0 3 2 2 1 0 4 11 3 0 3 5 0 5 1 2
>AF390031\AF390031\join(2492..2558,3337..3505,4348..4540)\429\AAM73649.1\Homo sapiens\Homo sapiens trans-activated by hepatitis C virus core protein 2(TAHCCP2) gene, complete cds./gene="TAHCCP2"/codon_start=1/product="trans-activated by hepatitis C virus core protein 2"/protein_id="AAM73649.1"/db_xref="GI:21666302"
0 1 6 1 2 4 1 5 4 0 0 1 0 6 0 2 3 1 1 3 2 0 1 3 2 3 1 6 4 7 2 5 4 1 1 1 5 1 1 9 5 1 1 5 1 1 4 5 2 1 1 1 0 1 3 0 0 3 2 4 1 0 0 1
>BC016395\BC016395\126..806\681\AAH16395.1\Homo sapiens\Homo sapiens hepatocellularcarcinoma-associated antigen HCA557a,transcript variant 1, mRNA (cDNA clone MGC:16818 IMAGE:3882414),complete cds./gene="DKFZP586D0919"/codon_start=1/product="hepatocellularcarcinoma-associated antigen HCA557a, isoform a"/protein_id="AAH16395.1"/db_xref="GI:16741082"/db_xref="GeneID:25895"
1 2 2 1 2 4 1 4 18 0 0 2 0 3 3 2 3 1 2 5 1 1 3 6 1 3 3 7 6 4 1 6 12 1 0 4 11 1 0 5 4 4 3 11 3 6 7 8 6 6 2 4 2 2 9 3 0 9 1 2 2 0 0 1
>BC046367\BC046367\238..1713\1476\AAH46367.1\Homo sapiens\Homo sapiens synaptotagmin IX, mRNA (cDNA clone MGC:50869IMAGE:5770087), complete cds./gene="SYT9"/codon_start=1/product="synaptotagmin IX"/protein_id="AAH46367.1"/db_xref="GI:28204903"/db_xref="GeneID:143425"
5 3 7 4 7 9 2 10 18 8 6 9 7 8 3 6 5 3 5 11 3 4 4 13 3 9 6 10 2 6 3 9 6 4 3 10 15 4 14 14 15 10 6 15 13 4 7 18 26 14 5 9 5 8 9 8 5 12 10 8 6 0 0 1
>AY358239\AY358239\37..345\309\AAQ88606.1\Homo sapiens\Homo sapiens clone DNA147246 KLIA6249 (UNQ6249) mRNA, complete cds./locus_tag="UNQ6249"/codon_start=1/product="KLIA6249"/protein_id="AAQ88606.1"/db_xref="GI:37181594"
0 0 0 0 0 0 0 4 5 0 1 0 0 1 1 1 1 1 2 10 1 3 2 0 2 8 3 10 5 4 0 2 2 0 1 1 0 1 3 2 0 1 1 4 0 0 3 7 1 1 0 0 0 1 2 1 0 2 0 1 0 0 0 1
>HSJ469A13#4\AL132768\complement(join(51898..52007,53873..53960,54792..54939, 57197..57271,57668..57727,61571..61658,65879..65951, 67079..67152,70535..70568))\750\CAI21468.1\Homo sapiens\Human DNA sequence from clone RP3-469A13 on chromosome 20 Containsthe 3' end of a novel gene, the C20orf172 gene for chromosome 20open reading frame 172, the 5' end of the NDRG3 gene for NDRGfamily member 3 (N-myc downstream-regulated gene 3, FLJ13556) andfour CpG islands, complete sequence./gene="C20orf172"/locus_tag="RP3-469A13.1-009"/standard_name="OTTHUMP00000030880"/codon_start=1/protein_id="CAI21468.1"/db_xref="GI:56204753"/db_xref="UniProt/TrEMBL:Q5JW55"
1 0 2 1 4 1 3 4 5 9 4 6 8 2 0 13 4 5 3 1 0 8 2 1 0 4 5 4 0 3 9 2 1 0 1 3 6 1 14 6 2 3 4 18 1 2 14 8 4 9 3 1 1 4 5 7 5 2 2 7 1 0 0 1
>S82917\S82917\51..335\285\AAB46802.1\Homo sapiens\dopamine D4 receptor {exon 1} [human, leukocytes, Genomic, 350 nt]./gene="dopamine D4 receptor"/codon_start=1/product="dopamine D4 receptor"/protein_id="AAB46802.1"/db_xref="GI:1835971"
0 3 1 0 0 0 0 8 9 0 0 0 0 2 1 2 3 0 0 3 1 0 0 1 2 0 2 5 11 3 0 3 9 0 0 1 8 0 0 0 3 0 0 2 0 0 0 2 3 0 1 0 1 0 2 0 0 2 0 1 0 0 0 0
>AK057511\AK057511\153..2429\2277\BAB71515.1\Homo sapiens\Homo sapiens cDNA FLJ32949 fis, clone TESTI2008020, weakly similarto DPY-19 PROTEIN./codon_start=1/protein_id="BAB71515.1"/db_xref="GI:16553246"
3 6 8 7 12 10 8 13 16 22 22 18 12 12 2 14 9 11 21 11 1 12 6 7 4 12 14 13 3 11 17 10 5 6 11 5 14 17 18 16 7 19 10 15 5 9 28 15 6 11 9 21 6 9 16 33 15 13 26 30 16 0 0 1
>AK024983\AK024983\366..833\468\BAB15049.1\Homo sapiens\Homo sapiens cDNA: FLJ21330 fis, clone COL02466./codon_start=1/protein_id="BAB15049.1"/db_xref="GI:10437414"
0 0 1 2 2 5 2 2 13 0 0 1 0 4 0 2 2 0 1 5 0 2 2 5 0 3 1 7 0 5 4 3 5 0 0 4 4 1 0 3 3 2 2 8 4 5 5 4 3 4 1 3 1 1 4 1 0 6 1 4 2 0 0 1
>CR457379\CR457379\1..1842\1842\CAG33660.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834B0621D forgene PDCD8, programmed cell death 8 (apoptosis-inducing factor);complete cds, incl. stopcodon./gene="PDCD8"/codon_start=1/protein_id="CAG33660.1"/db_xref="GI:48146875"
8 1 8 0 13 9 5 8 15 8 5 11 13 3 0 10 8 9 12 4 2 9 8 10 4 10 14 12 4 22 17 17 9 16 9 11 20 11 18 23 9 12 6 16 3 7 22 20 13 16 8 5 3 2 14 6 6 9 20 12 8 1 0 0
>HUMTFPC\M27436\100..987\888\AAA36734.1\Homo sapiens\Human tissue factor gene, complete cds, with a Alu repetitivesequence in the 3' untranslated region./codon_start=1/protein_id="AAA36734.1"/db_xref="GI:339508"
1 1 6 0 3 1 2 5 5 2 3 3 6 4 0 3 6 4 14 5 2 9 3 5 3 3 6 5 0 5 7 5 4 1 3 9 13 5 10 10 8 8 3 7 1 0 7 14 5 6 7 5 1 4 8 5 3 5 7 2 7 1 0 0
>AY527412\AY527412\join(18626..18709,20398..20499,21575..21668,21833..21900, 24457..24575,26195..26270,34900..35081,35237..35376, 37188..37289,37599..37826,38268..38329)\1257\AAS00097.1\Homo sapiens\Homo sapiens RAD52 homolog (S. cerevisiae) (RAD52) gene, completecds./gene="RAD52"/codon_start=1/product="RAD52 homolog (S. cerevisiae)"/protein_id="AAS00097.1"/db_xref="GI:41324138"
4 3 5 1 5 8 1 6 12 7 5 3 6 7 1 10 12 4 5 3 4 9 8 3 5 7 12 10 4 8 10 9 4 6 2 5 16 5 7 20 9 7 5 27 6 5 11 16 14 8 8 4 6 2 3 5 2 3 4 7 4 1 0 0
>AF035119\AF035119\325..3600\3276\AAB87700.1\Homo sapiens\Homo sapiens deleted in liver cancer-1 (DLC-1) mRNA, complete cds./gene="DLC-1"/codon_start=1/product="deleted in liver cancer-1"/protein_id="AAB87700.1"/db_xref="GI:2654198"
8 12 14 3 10 20 14 24 44 8 8 13 11 33 8 18 50 13 8 19 10 13 13 29 7 17 9 21 7 14 9 21 15 5 6 19 28 13 30 43 35 16 13 37 17 10 32 36 40 29 18 10 11 10 22 13 3 25 10 25 12 0 0 1
>AY226382\AY226382\1..3102\3102\AAO59428.1\Homo sapiens\Homo sapiens NOD protein family member 17 (NOD17) mRNA, completecds./gene="NOD17"/codon_start=1/product="NOD protein family member 17"/protein_id="AAO59428.1"/db_xref="GI:29372853"
4 6 4 8 19 13 13 22 47 31 12 32 13 6 7 23 26 14 16 11 8 19 12 14 4 4 15 17 3 18 13 9 9 11 8 12 17 13 29 27 22 32 14 24 10 14 29 30 25 21 15 16 19 21 19 33 18 21 18 32 11 0 0 1
>BC011934\BC011934\3..686\684\AAH11934.1\Homo sapiens\Homo sapiens sperm associated antigen 7, mRNA (cDNA clone MGC:20134IMAGE:4330461), complete cds./gene="SPAG7"/codon_start=1/product="SPAG7 protein"/protein_id="AAH11934.1"/db_xref="GI:15080361"/db_xref="GeneID:9552"
1 4 3 4 1 4 5 2 7 0 0 1 2 6 0 1 6 2 2 2 0 1 3 4 1 2 4 11 1 3 2 4 4 1 0 1 10 0 7 19 1 3 5 11 2 1 7 20 10 5 4 1 0 2 3 4 1 6 2 7 1 0 1 0
>HSP0071\X81889\142..3777\3636\CAA57478.1\Homo sapiens\H.sapiens mRNA for p0071 protein./codon_start=1/product="p0071 protein"/protein_id="CAA57478.1"/db_xref="GI:1702924"/db_xref="GOA:Q99569"/db_xref="UniProt/Swiss-Prot:Q99569"
14 6 15 4 27 23 10 14 38 14 9 21 36 31 7 34 21 17 29 31 6 16 33 18 5 24 28 26 4 18 23 21 20 11 10 8 31 24 27 23 37 22 27 48 10 16 25 35 29 29 20 30 8 6 7 15 10 13 16 20 11 0 0 1
>HUMA2CIIA\D13538\3..1379\1377\BAA02737.1\Homo sapiens\Human alpha2CII-adrenergic receptor gene, complete cds./codon_start=1/product="alpha2CII-adrenergic receptor"/protein_id="BAA02737.1"/db_xref="GI:219406"
4 23 12 0 1 6 0 13 25 0 0 2 0 11 15 0 13 0 1 8 5 1 2 11 12 0 5 25 31 4 0 28 13 4 0 11 29 1 0 8 10 2 0 11 2 1 1 14 8 2 15 0 11 1 24 3 0 16 0 5 8 0 0 1
>AK126497\AK126497\1109..3427\2319\BAC86566.1\Homo sapiens\Homo sapiens cDNA FLJ44533 fis, clone UTERU3004523./codon_start=1/protein_id="BAC86566.1"/db_xref="GI:34532995"
3 3 0 4 18 23 6 13 17 14 4 13 25 26 1 30 16 20 13 13 1 18 24 19 2 28 10 13 0 14 10 13 17 14 4 7 11 9 5 19 11 9 22 26 17 19 16 31 10 26 7 5 6 9 11 8 3 5 4 12 15 1 0 0
>HSU09412\U09412\522..1568\1047\AAC50253.1\Homo sapiens\Human zinc finger protein ZNF134 mRNA, complete cds./codon_start=1/product="zinc finger protein ZNF134"/protein_id="AAC50253.1"/db_xref="GI:488553"
4 2 1 0 8 9 1 2 1 7 2 1 3 4 0 2 9 14 6 3 1 10 1 2 2 7 4 4 0 3 7 4 9 3 1 3 2 8 19 14 4 5 5 15 20 10 14 13 4 5 5 8 13 10 6 8 1 4 9 4 2 0 1 0
>AL136231#1\AL136231\join(AL162587.20:72938..73028,AL162587.20:126825..126965, 379..471,3274..3388,4977..5019,6599..6697,11134..11318, 12837..12944,14931..15053,15499..15693,21968..22102, 24242..24488)\-323829\CAI41264.1\Homo sapiens\Human DNA sequence from clone RP11-6J24 on chromosome 9p24.1-24.3Contains the 3' end of the SLC1A1 gene for solute carrier family 1(neuronal/epithelial high affinity glutamate transporter, systemXag), the 5' end of a novel gene (FLJ10058), the gene forHsp90-associating relative of Cdc37 (HARC) (FLJ20639), the 3' endof the AK3L1 gene for adenylate kinase 3 like 1 (AK3), a ribosomalprotein S6 (RPS6) pseudogene and 3 CpG islands, complete sequence./gene="SLC1A1"/locus_tag="RP11-6J24.1-001"/standard_name="OTTHUMP00000021006"/codon_start=1/product="solute carrier family 1 (neuronal\/epithelial high affinity glutamate transporter, system Xag), member 1"/protein_id="CAI41264.1"/db_xref="GI:57208640"/db_xref="InterPro:IPR001991"
3 3 1 2 3 5 5 9 20 9 6 8 6 8 0 6 5 6 11 13 3 6 4 5 1 7 10 10 3 14 8 11 6 7 4 18 20 11 14 18 13 7 1 14 3 1 17 7 12 11 5 13 1 6 16 13 6 18 25 21 3 1 2 0
>BC009915\BC009915\68..1240\1173\AAH09915.1\Homo sapiens\Homo sapiens brain protein 16, mRNA (cDNA clone MGC:2733IMAGE:2822563), complete cds./gene="LOC51236"/codon_start=1/product="brain protein 16"/protein_id="AAH09915.1"/db_xref="GI:14602823"/db_xref="GeneID:51236"
3 10 12 1 0 4 3 8 37 5 0 9 0 3 2 2 3 1 4 2 3 1 6 14 11 7 6 22 30 4 4 11 9 1 1 2 17 1 0 4 5 1 1 19 6 1 6 31 16 4 5 0 6 2 4 1 0 4 2 8 5 0 0 1
>BC050272\BC050272\696..1799\1104\AAH50272.1\Homo sapiens\Homo sapiens zinc finger, DHHC-type containing 2, mRNA (cDNA cloneMGC:21181 IMAGE:4398300), complete cds./gene="ZDHHC2"/codon_start=1/product="rec"/protein_id="AAH50272.1"/db_xref="GI:30044999"/db_xref="GeneID:51201"
4 1 4 0 5 3 5 6 7 9 5 8 4 6 1 10 9 3 6 4 1 7 8 3 2 6 10 8 2 5 6 7 1 4 1 4 6 5 12 8 6 10 5 7 2 10 8 8 1 12 8 7 10 6 9 17 3 7 4 12 9 1 0 0
>AF450008\AF450008\243..1607\1365\AAL47160.1\Homo sapiens\Homo sapiens CFTR-associated ligand (CAL) mRNA, complete cds./gene="CAL"/codon_start=1/product="CFTR-associated ligand"/protein_id="AAL47160.1"/db_xref="GI:17865154"
4 0 1 5 8 2 5 5 15 11 5 11 2 5 1 9 3 5 5 3 0 8 9 0 2 5 13 7 3 15 13 8 11 11 8 2 10 9 24 13 7 4 13 12 6 14 26 16 10 21 3 6 7 0 2 4 3 8 8 6 2 1 0 0
>AY032594\AY032594\1..570\570\AAK51136.1\Homo sapiens\Homo sapiens hepatitis C virus core-binding protein 6 (HCBP6) mRNA,complete cds./gene="HCBP6"/codon_start=1/product="hepatitis C virus core-binding protein 6"/protein_id="AAK51136.1"/db_xref="GI:20384691"
2 2 0 4 0 1 2 2 5 4 0 1 3 4 1 2 4 1 4 2 0 5 2 0 0 3 6 5 5 4 11 2 3 3 1 2 9 3 4 13 2 3 3 7 1 1 5 7 4 1 2 1 1 0 5 8 2 2 1 4 4 1 0 0
>HUMKAP1A\L27711\52..690\639\AAA66496.1\Homo sapiens\Human protein phosphatase (KAP1) mRNA, complete cds./gene="KAP1"/function="interaction with cyclin dependent kinases"/standard_name="dual specificity protein phosphatase"/codon_start=1/product="protein phosphatase"/protein_id="AAA66496.1"/db_xref="GI:443669"
3 0 1 0 9 0 6 3 4 7 3 1 12 1 0 5 3 2 4 5 0 2 5 1 1 2 3 2 0 4 5 0 4 3 2 2 1 2 7 3 1 4 7 4 1 6 8 5 7 7 4 3 4 8 1 5 10 3 3 2 1 1 0 0
>BT006684\BT006684\1..1476\1476\AAP35330.1\Homo sapiens\Homo sapiens ferredoxin reductase mRNA, complete cds./codon_start=1/product="ferredoxin reductase"/protein_id="AAP35330.1"/db_xref="GI:30582207"
4 11 14 3 3 5 4 9 30 4 1 3 2 4 3 3 13 2 7 9 9 2 9 16 5 13 8 24 3 6 4 20 13 8 1 10 32 1 1 17 5 2 2 18 8 3 4 26 15 8 7 1 4 4 10 5 1 8 6 7 11 0 1 0
>BC022003\BC022003\42..1691\1650\AAH22003.1\Homo sapiens\Homo sapiens myotubularin related protein 9, mRNA (cDNA cloneMGC:26187 IMAGE:4825583), complete cds./gene="MTMR9"/codon_start=1/product="myotubularin-related protein 9"/protein_id="AAH22003.1"/db_xref="GI:18314567"/db_xref="GeneID:66036"/db_xref="MIM:606260"
8 2 4 5 5 9 4 12 20 9 3 12 7 12 0 7 4 9 9 10 3 7 7 6 3 8 6 10 2 15 9 6 4 7 5 6 9 3 12 14 10 15 5 22 8 7 25 24 12 7 7 9 6 7 9 18 5 18 17 11 14 0 0 1
>HUMDEF5A\M97925\join(1399..1570,2550..2662)\285\AAA35754.1\Homo sapiens\H.sapiens defensin 5 gene, complete cds./codon_start=1/product="defensin 5"/protein_id="AAA35754.1"/db_xref="GI:181533"
1 2 0 2 4 1 0 6 2 3 0 0 2 3 0 3 0 1 1 6 0 0 0 0 0 0 2 5 0 7 2 2 2 1 0 0 2 0 0 1 1 1 0 7 0 0 3 3 2 1 1 1 3 3 0 1 0 4 1 1 0 0 0 1
>BC068976\BC068976\79..3303\3225\AAH68976.1\Homo sapiens\Homo sapiens phospholipase D1, phophatidylcholine-specific, mRNA(cDNA clone MGC:70810 IMAGE:6068382), complete cds./gene="PLD1"/codon_start=1/product="phospholipase D1, phophatidylcholine-specific"/protein_id="AAH68976.1"/db_xref="GI:46362479"/db_xref="GeneID:5337"/db_xref="MIM:602382"
7 6 10 8 26 15 7 15 23 20 13 13 13 13 1 19 13 15 19 10 5 10 15 17 3 11 14 17 1 29 29 11 11 10 10 13 27 14 43 31 20 26 20 19 23 21 37 37 28 29 16 25 8 4 28 25 25 26 28 23 19 1 0 0
>AF022152\AF022152\32..3280\3249\AAB71894.1\Homo sapiens\Homo sapiens AP-3 complex beta3B subunit mRNA, complete cds./codon_start=1/product="AP-3 complex beta3B subunit"/protein_id="AAB71894.1"/db_xref="GI:2460298"
5 16 14 7 4 7 7 18 69 7 2 4 13 28 7 15 27 20 13 31 4 8 12 29 3 17 15 45 15 17 9 28 12 6 7 20 44 6 22 50 23 9 5 41 14 5 21 71 39 20 20 7 4 7 21 7 4 30 19 27 5 0 0 1
>AK022907\AK022907\163..2031\1869\BAB14302.1\Homo sapiens\Homo sapiens cDNA FLJ12845 fis, clone NT2RP2003307, moderatelysimilar to KINESIN LIGHT CHAIN./codon_start=1/protein_id="BAB14302.1"/db_xref="GI:10434570"
3 17 17 6 0 5 3 16 46 1 0 9 3 10 2 5 22 5 9 11 1 2 6 11 3 10 9 27 5 14 6 22 17 5 5 7 17 2 7 36 17 5 1 31 10 3 11 48 19 15 12 7 5 2 3 3 0 13 1 10 4 1 0 0
>AK172809\AK172809\215..1033\819\BAD18779.1\Homo sapiens\Homo sapiens cDNA FLJ23970 fis, clone HEP17024./codon_start=1/protein_id="BAD18779.1"/db_xref="GI:47077816"
0 1 1 1 9 5 0 7 7 3 16 0 3 0 0 0 4 0 12 1 2 2 1 1 0 13 4 1 0 3 6 1 1 1 12 8 19 1 5 6 14 16 0 3 1 3 9 3 4 1 1 4 0 0 17 3 11 16 2 7 0 0 1 0
>BC027937\BC027937\418..2010\1593\AAH27937.1\Homo sapiens\Homo sapiens retinoic acid induced 2, mRNA (cDNA clone MGC:34677IMAGE:5201821), complete cds./gene="RAI2"/codon_start=1/product="RAI2 protein"/protein_id="AAH27937.1"/db_xref="GI:20379790"/db_xref="GeneID:10742"/db_xref="MIM:300217"
0 1 3 0 3 2 1 16 22 3 1 7 5 24 0 5 13 10 2 14 2 5 17 30 5 19 5 19 3 9 4 14 4 3 2 12 24 0 12 16 15 8 3 28 11 1 13 23 13 6 2 4 2 2 9 9 3 14 7 18 2 1 0 0
>AB062430\AB062430\225..2243\2019\BAB93493.1\Homo sapiens\Homo sapiens OK/SW-cl.100 mRNA, complete cds./gene="OK/SW-cl.100"/codon_start=1/protein_id="BAB93493.1"/db_xref="GI:21104446"
5 19 21 3 3 2 2 8 43 1 0 5 10 19 10 6 27 8 6 13 12 5 17 48 17 10 15 45 9 7 4 23 15 4 0 9 35 0 7 22 4 3 1 15 12 3 6 40 25 4 4 1 8 2 8 3 0 6 0 9 3 0 1 0
>HUMTRHYAL\L09190\join(1507..1644,2512..8070)\5697\AAA65582.1\Homo sapiens\Human trichohyalin (TRHY) gene, complete cds./gene="TRHY"/codon_start=1/product="trichohyalin"/protein_id="AAA65582.1"/db_xref="GI:292836"
15 151 59 31 57 105 14 36 120 9 5 6 0 5 1 4 12 8 4 0 7 4 9 4 11 4 7 14 3 7 10 9 8 2 1 5 9 2 48 57 4 4 75 262 16 7 151 361 41 18 11 8 2 5 33 6 1 7 3 2 18 1 0 0
>BT019657\BT019657\1..1011\1011\AAV38463.1\Homo sapiens\Homo sapiens TATA box binding protein mRNA, complete cds./codon_start=1/product="TATA box binding protein"/protein_id="AAV38463.1"/db_xref="GI:54696182"
2 0 1 1 7 4 2 4 7 4 4 5 3 5 1 4 2 7 5 8 5 7 9 8 2 10 12 7 1 7 6 5 3 5 5 1 6 5 6 9 6 4 11 46 2 0 8 5 2 2 3 6 1 2 5 8 2 7 11 10 0 0 1 0
>AF026005\AF026005\1..2577\2577\AAB88808.1\Homo sapiens\Homo sapiens delayed rectifier potassium channel Kv2.1 (DRK1) mRNA,complete cds./gene="DRK1"/codon_start=1/product="delayed rectifier potassium channel Kv2.1"/protein_id="AAB88808.1"/db_xref="GI:2570866"
6 15 11 3 5 8 4 30 27 10 2 12 4 26 5 11 31 14 14 19 7 10 8 24 4 15 12 26 7 12 11 16 14 7 4 14 14 5 21 37 23 10 5 22 15 3 15 48 27 11 16 3 12 3 31 7 2 27 17 26 10 0 0 1
>AF153978\AF153978\246..1097\852\AAF75588.1\Homo sapiens\Homo sapiens CD40-like protein precusor mRNA, complete cds./codon_start=1/product="CD40-like protein precusor"/protein_id="AAF75588.1"/db_xref="GI:8489097"
0 2 2 1 4 5 2 4 11 0 0 1 2 8 0 1 9 2 5 12 4 0 8 8 4 6 1 13 2 3 4 9 8 4 2 9 11 2 3 9 4 2 1 11 6 0 3 14 8 1 4 2 16 7 4 1 2 4 3 3 6 0 0 1
>AK001753\AK001753\128..1525\1398\BAA91884.1\Homo sapiens\Homo sapiens cDNA FLJ10891 fis, clone NT2RP4002078, weakly similarto ZINC FINGER PROTEIN 91./codon_start=1/protein_id="BAA91884.1"/db_xref="GI:7023216"
4 1 1 6 9 7 2 4 8 10 4 2 14 4 1 7 2 6 11 2 0 12 2 1 0 9 8 4 0 5 12 9 2 4 4 3 5 10 29 21 6 22 12 9 13 26 17 17 7 8 9 3 5 18 10 10 4 3 11 8 2 0 1 0
>AL450310\AL450310\complement(join(33273..33364,34830..34891,38748..38872, 53976..54116,55402..55608,60637..60719,62653..62812, 66293..66370,70972..71063,73447..73612,84113..84282, 88802..88865,93154..93389,96576..96756))\1857\CAH72298.1\Homo sapiens\Human DNA sequence from clone RP11-307O14 on chromosome 6 Containsthe 5' end of a novel gene and the gene for MacGAP protein,complete sequence./gene="ARHGAP18"/locus_tag="RP11-307O14.1-001"/standard_name="OTTHUMP00000017190"/codon_start=1/product="Rho GTPase activating protein 18"/protein_id="CAH72298.1"/db_xref="GI:55665388"/db_xref="GOA:Q96S64"/db_xref="InterPro:IPR000198"/db_xref="UniProt/TrEMBL:Q96S64"
7 1 3 0 9 6 9 13 11 15 8 17 6 6 2 7 7 8 14 7 5 6 11 5 1 10 13 16 1 12 11 3 4 8 9 8 7 12 36 26 12 15 18 25 1 5 38 22 12 22 4 8 4 1 3 15 6 10 16 16 5 0 1 0
>AF395536\AF395536\1..1887\1887\AAK82415.1\Homo sapiens\Homo sapiens sorting nexin 18 (SNX18) mRNA, complete cds./gene="SNX18"/codon_start=1/product="sorting nexin 18"/protein_id="AAK82415.1"/db_xref="GI:15042691"
1 17 2 0 2 5 3 10 33 3 3 4 4 13 11 4 20 1 4 12 7 1 4 23 19 5 4 28 19 4 4 38 11 3 3 8 24 3 5 28 10 3 2 34 11 2 1 34 35 5 13 7 8 1 32 3 2 11 1 8 12 0 1 0
>HS1000E10#4\AL096773\join(65219..65417,67037..67146,67546..67638,68254..68351, 70586..70667,70992..71120,71252..71377,72293..72505, 74461..74601,74687..74851,78019..78126,78723..78898, 79776..79888,81107..81226,84392..84570,85367..85530, 86364..86496,86893..86940)\2397\CAI18825.1\Homo sapiens\Human DNA sequence from clone RP5-1000E10 on chromosome 1p12-13.3Contains the 5' end of the gene for a novel protein (FLJ37099), theAMPD1 gene for adenosine monophosphate deaminase 1 (isoform M), theNRAS gene for neuroblastoma RAS viral (v-ras) oncogene homolog, thegene for NRAS-related gene (D1S155E) and the gene for a novelprotein (FLJ44339), complete sequence./gene="RP5-1000E10.3"/locus_tag="RP5-1000E10.3-003"/standard_name="OTTHUMP00000013881"/codon_start=1/product="NRAS-related gene (D1S155E)"/protein_id="CAI18825.1"/db_xref="GI:56203365"/db_xref="InterPro:IPR002059"/db_xref="InterPro:IPR008994"
8 8 2 10 7 7 3 6 21 7 7 8 11 5 1 8 8 13 11 8 3 20 11 8 1 14 13 12 0 18 18 18 13 16 13 11 21 25 39 21 17 25 14 19 7 11 41 21 14 39 8 8 4 11 15 29 5 12 28 15 1 1 0 0
>BC022993\BC022993\127..837\711\AAH22993.1\Homo sapiens\Homo sapiens reticulon 3, transcript variant 1, mRNA (cDNA cloneIMAGE:4940867), complete cds./gene="RTN3"/codon_start=1/product="reticulon 3, isoform a"/protein_id="AAH22993.1"/db_xref="GI:18606175"/db_xref="GeneID:10313"/db_xref="MIM:604249"
1 0 0 1 1 2 1 6 14 4 0 1 3 11 3 2 4 3 0 6 2 3 2 2 3 1 3 9 4 8 4 6 3 1 3 7 4 6 5 11 2 2 2 4 3 3 7 3 3 5 5 3 2 1 8 4 0 12 9 6 2 1 0 0
>AF093415\AF093415\30..770\741\AAF22488.1\Homo sapiens\Homo sapiens cell division protein FtsJ (FJH1) mRNA, complete cds./gene="FJH1"/codon_start=1/product="cell division protein FtsJ"/protein_id="AAF22488.1"/db_xref="GI:6652820"
2 1 6 2 4 8 0 6 12 7 2 2 3 1 0 1 7 4 6 5 0 4 2 4 1 6 4 6 4 5 3 6 9 0 2 1 14 3 3 8 2 3 3 9 5 2 4 7 8 4 4 0 3 4 8 3 1 5 2 2 3 0 0 1
>AL359764#4\AL359764\join(complement(6483..6560),AL512307.12:153863..153959, complement(AL590682.9:65938..65988), complement(AL590682.9:19459..19565), complement(AL590682.9:13576..13627), complement(AL365184.12:142467..142531), complement(AL365184.12:141188..141264), complement(AL365184.12:140999..141080), complement(AL365184.12:99510..99584), complement(AL365184.12:88729..88827), complement(AL365184.12:87128..87189), complement(AL365184.12:86030..86140), complement(AL365184.12:84330..84455), complement(AL365184.12:78552..78738), complement(AL365184.12:75316..75405), complement(AL365184.12:73059..73133))\78\CAI15142.1\Homo sapiens\Human DNA sequence from clone RP11-527D7 on chromosome 1 Containsthe 5' end of the RGS7 gene for regulator of G-protein signalling7, a novel gene, the 5' end of the FH gene for fumarate hydrataseand two CpG islands, complete sequence./gene="RGS7"/locus_tag="RP11-80B9.3-004"/standard_name="OTTHUMP00000037996"/codon_start=1/product="regulator of G-protein signalling 7"/protein_id="CAI15142.1"/db_xref="GI:55959534"/db_xref="GOA:P49802"/db_xref="UniProt/Swiss-Prot:P49802"
2 1 1 2 23 13 3 5 4 5 7 7 3 5 1 10 7 9 4 3 1 8 10 5 2 5 4 8 0 10 11 5 8 3 8 5 11 9 26 16 7 11 8 11 6 6 16 5 2 13 6 10 3 7 7 17 13 8 11 8 7 6 7 13
>AF155095\AF155095\151..1863\1713\AAD42861.1\Homo sapiens\Homo sapiens NY-REN-2 antigen mRNA, complete cds./codon_start=1/product="NY-REN-2 antigen"/protein_id="AAD42861.1"/db_xref="GI:5360085"
1 3 3 4 5 3 3 2 7 5 5 9 9 11 1 16 16 12 5 7 1 10 20 13 2 15 17 10 0 19 17 8 11 19 7 3 11 9 15 18 18 21 10 29 7 6 7 9 10 16 9 10 1 3 9 10 4 2 17 10 10 1 0 0
>AF077961\AF077961\1..1317\1317\AAD51483.1\Homo sapiens\Homo sapiens clone 327 CLN3 protein (CLN3) mRNA, complete cds./gene="CLN3"/codon_start=1/product="CLN3 protein"/protein_id="AAD51483.1"/db_xref="GI:5801841"
1 5 7 1 1 3 0 21 38 7 0 7 5 14 5 9 12 4 5 10 2 3 4 8 3 7 6 19 4 10 7 14 12 3 1 10 12 4 1 4 11 0 1 13 7 5 5 14 9 2 10 4 6 4 16 9 1 13 4 5 10 0 0 1
>D87953\D87953\123..1307\1185\BAA13505.1\Homo sapiens\Human mRNA for RTP, complete cds./gene="GC4"/codon_start=1/product="RTP"/protein_id="BAA13505.1"/db_xref="GI:1596167"
3 9 4 0 0 0 2 8 13 5 1 3 2 11 4 4 12 1 4 18 1 5 2 8 4 8 4 13 2 9 7 16 9 2 1 10 15 2 4 9 15 2 3 15 13 2 5 19 14 5 10 0 5 3 5 5 0 11 4 20 3 0 1 0
>AY372211\AY372211\1..879\879\AAQ75759.1\Homo sapiens\Homo sapiens unknown mRNA./codon_start=1/product="unknown"/protein_id="AAQ75759.1"/db_xref="GI:34577163"
3 1 3 3 2 1 0 4 12 6 1 1 5 1 1 4 1 1 7 5 1 8 12 4 3 17 11 9 1 12 3 3 3 6 1 2 3 5 6 8 7 10 6 12 6 5 4 6 0 5 4 1 7 2 5 5 2 3 6 16 0 0 0 1
>BC093690\BC093690\50..1489\1440\AAH93690.1\Homo sapiens\Homo sapiens carbohydrate (chondroitin 6) sulfotransferase 3, mRNA(cDNA clone MGC:120725 IMAGE:7939535), complete cds./gene="CHST3"/codon_start=1/product="carbohydrate (chondroitin 6) sulfotransferase 3"/protein_id="AAH93690.1"/db_xref="GI:62739448"/db_xref="GeneID:9469"/db_xref="MIM:603799"
0 25 9 1 3 3 1 13 36 2 1 4 4 9 4 1 11 0 1 7 7 2 2 13 8 1 5 30 6 2 1 19 5 0 0 8 22 2 4 21 12 1 2 24 8 0 6 34 18 2 10 1 8 1 23 3 2 12 1 11 7 0 1 0
>HSU17838\U17838\856..6015\5160\AAC50820.2\Homo sapiens\Homo sapiens zinc finger protein RIZ mRNA, complete cds./function="zinc finger protein"/codon_start=1/product="zinc finger protein RIZ"/protein_id="AAC50820.2"/db_xref="GI:9955379"
13 6 18 4 15 15 6 17 26 30 24 22 32 38 7 63 37 30 33 26 5 33 54 40 15 53 31 41 10 35 16 15 24 18 16 15 32 28 100 51 30 46 17 54 17 27 76 74 25 50 15 11 16 25 21 27 17 14 24 27 12 0 1 0
>CR457417\CR457417\1..930\930\CAG33698.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834A1014D forgene PPP2CA, protein phosphatase 2 (formerly 2A), catalyticsubunit, alpha isoform; complete cds, incl. stopcodon./gene="PPP2CA"/codon_start=1/protein_id="CAG33698.1"/db_xref="GI:48146951"/db_xref="GOA:Q6I9T8"/db_xref="InterPro:IPR004843"/db_xref="InterPro:IPR006186"/db_xref="UniProt/TrEMBL:Q6I9T8"
3 2 1 7 6 0 3 5 8 8 1 5 3 3 1 5 2 1 8 4 2 4 10 1 0 3 4 2 0 6 6 3 4 10 3 2 6 10 7 6 5 7 6 8 1 9 8 12 10 14 5 11 3 7 6 8 2 7 4 6 5 1 0 0
>BC038838\BC038838\232..936\705\AAH38838.1\Homo sapiens\Homo sapiens mesenchymal stem cell protein DSC54, mRNA (cDNA cloneMGC:47873 IMAGE:5170587), complete cds./gene="LOC51334"/codon_start=1/product="LOC51334 protein"/protein_id="AAH38838.1"/db_xref="GI:24416469"/db_xref="GeneID:51334"
3 0 2 0 4 4 3 3 3 3 2 3 2 2 0 1 5 5 6 5 4 5 13 8 2 20 5 2 0 3 6 5 2 1 2 4 5 2 10 7 7 8 1 5 6 3 6 2 6 2 1 2 2 4 2 1 3 5 3 3 0 0 0 1
>BC030830\BC030830\133..750\618\AAH30830.1\Homo sapiens\Homo sapiens CD83 antigen (activated B lymphocytes, immunoglobulinsuperfamily), mRNA (cDNA clone MGC:26322 IMAGE:4818856), completecds./gene="CD83"/codon_start=1/product="CD83 antigen (activated B lymphocytes, immunoglobulin superfamily)"/protein_id="AAH30830.1"/db_xref="GI:21410827"/db_xref="GeneID:9308"/db_xref="MIM:604534"
2 1 1 1 3 4 3 5 10 1 3 3 0 4 2 2 3 2 5 3 2 5 3 7 3 2 2 3 2 5 2 3 4 3 1 3 6 3 3 9 3 3 1 9 3 2 7 6 4 4 5 2 6 1 4 4 0 4 3 3 2 0 0 1
>HSM806071\BX537946\80..2989\2910\CAD97914.1\Homo sapiens\Homo sapiens mRNA; cDNA DKFZp686C0686 (from clone DKFZp686C0686);complete cds./gene="DKFZp686C0686"/codon_start=1/product="hypothetical protein"/protein_id="CAD97914.1"/db_xref="GI:31873988"/db_xref="GOA:Q7Z3F2"/db_xref="InterPro:IPR000719"/db_xref="InterPro:IPR001090"/db_xref="InterPro:IPR001245"/db_xref="InterPro:IPR001426"/db_xref="InterPro:IPR001660"/db_xref="InterPro:IPR003961"/db_xref="InterPro:IPR006209"/db_xref="InterPro:IPR008266"/db_xref="UniProt/TrEMBL:Q7Z3F2"
5 1 8 7 19 6 8 6 18 15 6 15 11 10 0 23 17 15 14 24 2 11 22 12 1 14 24 12 1 25 27 16 12 14 15 16 36 14 36 22 18 25 16 14 9 12 43 30 12 32 13 24 18 14 11 20 7 27 23 27 14 1 0 0
>AB055421\AB055421\7..960\954\BAB21756.1\Homo sapiens\Homo sapiens mRNA for ChM1L, complete cds./gene="ChM1L"/codon_start=1/product="ChM1L"/protein_id="BAB21756.1"/db_xref="GI:12698293"
3 4 0 3 4 1 5 0 6 5 2 1 3 2 0 2 3 1 2 4 0 9 6 3 1 8 4 5 0 1 8 4 3 3 3 7 9 1 14 9 6 11 6 3 6 0 24 14 5 8 9 6 3 11 5 11 6 6 14 7 7 1 0 0
>CR456454\CR456454\61..840\780\CAG30340.1\Homo sapiens\Homo sapiens dJ186O1.2 full length open reading frame (ORF) cDNAclone (cDNA clone C22ORF:pGEM.dJ186O1.2.V2)./gene="dJ186O1.2"/codon_start=1/protein_id="CAG30340.1"/db_xref="GI:47678439"/db_xref="InterPro:IPR001849"/db_xref="UniProt/TrEMBL:Q6ICB4"
2 9 3 0 1 4 2 5 16 0 0 5 2 7 0 3 12 3 1 5 0 1 5 5 2 6 5 11 4 6 1 15 7 0 2 1 11 2 1 8 3 1 1 12 6 1 6 16 5 2 1 2 5 3 3 6 0 2 0 3 8 1 0 0
>BC020818\BC020818\108..1334\1227\AAH20818.1\Homo sapiens\Homo sapiens Sjogren syndrome antigen B (autoantigen La), mRNA(cDNA clone MGC:23872 IMAGE:4338551), complete cds./gene="SSB"/codon_start=1/product="autoantigen La"/protein_id="AAH20818.1"/db_xref="GI:18089160"/db_xref="GeneID:6741"/db_xref="MIM:109090"
0 0 1 2 11 3 10 1 5 3 6 7 3 3 1 5 3 2 6 2 1 6 3 1 0 6 12 6 0 9 9 5 2 11 7 1 7 2 46 15 6 14 9 10 1 5 41 8 10 20 2 4 1 2 6 13 11 3 8 6 5 0 1 0
>AK092263\AK092263\306..674\369\BAC03841.1\Homo sapiens\Homo sapiens cDNA FLJ34944 fis, clone NT2RP7008015./codon_start=1/protein_id="BAC03841.1"/db_xref="GI:21750811"
1 0 6 1 2 3 1 7 1 1 0 1 0 2 3 2 1 3 0 5 1 1 1 5 2 3 1 3 4 1 4 7 3 2 1 2 0 0 2 3 0 0 2 2 1 1 4 1 5 1 1 1 4 2 1 0 0 1 0 6 3 0 1 0
>AY038182\AY038182\69..308\240\AAK72469.1\Homo sapiens\Homo sapiens probable protease inhibitor WAP10 precursor, mRNA,complete cds./codon_start=1/product="probable protease inhibitor WAP10 precursor"/protein_id="AAK72469.1"/db_xref="GI:21654721"
1 0 0 1 0 1 3 1 7 0 1 0 0 1 0 2 1 0 1 1 0 1 1 1 0 2 2 1 0 0 2 0 1 0 0 2 1 2 4 2 1 2 1 8 2 0 2 0 1 1 2 1 4 5 0 0 1 2 0 3 0 0 0 1
>HUMMLCAB\M20642\44..628\585\AAA59854.1\Homo sapiens\Human alkali myosin light chain 1 mRNA, complete cds./gene="MYL1"/codon_start=1/product="myosin light chain"/protein_id="AAA59854.1"/db_xref="GI:188592"/db_xref="GDB:G00-120-217"
1 1 0 1 1 1 1 4 7 1 1 0 0 3 0 3 2 0 3 4 0 0 3 3 2 5 7 12 2 5 1 4 0 6 0 6 3 3 8 11 4 6 3 4 1 1 15 7 7 3 1 1 1 0 2 7 0 5 4 7 0 0 0 1
>AY177201\AY177201\1..705\705\AAO27703.1\Homo sapiens\Homo sapiens ubiquitin-specific protease otubain 2 mRNA, completecds./codon_start=1/product="ubiquitin-specific protease otubain 2"/protein_id="AAO27703.1"/db_xref="GI:28628209"
1 3 3 0 1 6 2 3 14 3 0 2 2 6 3 1 4 3 2 5 3 1 1 1 0 3 2 11 1 3 0 3 3 0 3 0 8 1 8 6 8 2 1 5 8 2 7 13 11 4 7 3 2 2 16 2 1 9 5 4 0 0 0 1
>HS86C11#3\AL021807\56377..56769\393\CAA16948.1\Homo sapiens\Human DNA sequence from clone RP1-86C11 on chromosome 6p21.31-22.1Contains a vomeronasal olfactory 1 receptor chromosome 6-2(VN1R6-2P) pseudogene, histone genes H2BFN and H2AFA, the gene fora novel protein identical to H2B histone family member A (H2BFA),the gene for a novel protein identical to H2A histone family memberI (H2AFI), a novel histone gene similar to H4F2 and three CpGislands, complete sequence./gene="RP1-86C11.5"/locus_tag="RP1-86C11.5-001"/standard_name="OTTHUMP00000016174"/codon_start=1/protein_id="CAA16948.1"/db_xref="GI:3928696"
1 7 1 2 0 1 1 4 11 0 0 0 0 0 0 3 1 0 0 3 0 2 0 3 2 0 2 9 5 1 2 9 1 2 0 3 5 0 4 10 6 0 1 4 3 1 1 6 2 0 1 2 0 0 1 0 0 5 1 1 0 1 0 0
>BC073784\BC073784\25..732\708\AAH73784.1\Homo sapiens\Homo sapiens cDNA clone MGC:88801 IMAGE:4297904, complete cds./codon_start=1/product="Unknown (protein for MGC:88801)"/protein_id="AAH73784.1"/db_xref="GI:49257468"
1 0 2 0 2 1 2 9 7 0 0 0 4 7 0 9 12 3 4 8 4 7 2 12 3 1 2 11 3 2 5 4 8 3 0 8 8 0 2 9 6 2 1 10 2 2 2 7 3 4 6 2 1 5 6 0 0 5 0 1 5 0 1 0
>AL157935#12\AL157935\complement(join(109055..109113,109886..109988, 110767..110856,111151..111153))\255\CAI12615.1\Homo sapiens\Human DNA sequence from clone RP11-203J24 on chromosome 9 Containsthe 5' end of the ENG gene for endoglin (Osler-Rendu-Weber syndrome1) (END, ORW, HHT1, ORW1, CD105), the AK1 gene for adenylate kinase1, the ST6GALNAC6 gene for CMP-NeuAC:(beta)-N-acetylgalactosaminide(alpha)2,6-sialyltransferase member VI (ST6GALNACVI), the SIAT7Dgene for sialyltransferase 7D((alpha-N-acetylneuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase) (SIAT3C, ST6GALNAC4,ST6GALNACIV), the DPM2 gene for dolichyl-phosphatemannosyltransferase polypeptide 2, regulatory subunit (MGC21559),the gene for a novel protien containing FLJ00179, a novel gene andten CpG islands, complete sequence./gene="DPM2"/locus_tag="RP11-203J24.2-001"/standard_name="OTTHUMP00000022224"/codon_start=1/product="dolichyl-phosphate mannosyltransferase polypeptide 2, regulatory subunit"/protein_id="CAI12615.1"/db_xref="GI:55958264"
1 0 0 0 1 0 0 5 8 0 0 1 0 1 0 0 1 1 1 4 1 0 2 1 0 0 1 5 0 3 2 2 1 0 0 3 6 1 0 5 0 0 0 3 1 1 0 0 2 0 2 3 0 0 4 1 0 6 1 2 1 0 0 1
>AF327066\AF327066\1..1431\1431\AAK11227.1\Homo sapiens\Homo sapiens Ewings sarcoma EWS-Fli1 (type 1) oncogene mRNA,complete cds./codon_start=1/product="Ewings sarcoma EWS-Fli1 (type 1) oncogene"/protein_id="AAK11227.1"/db_xref="GI:12963355"
0 3 3 1 2 1 2 3 6 1 1 0 2 14 1 6 27 13 5 23 4 19 10 19 6 18 13 14 2 10 13 7 15 4 1 7 4 0 6 6 13 2 17 43 5 4 0 7 5 8 23 29 0 1 4 3 0 6 2 8 4 0 1 0
>AK023335\AK023335\252..1637\1386\BAB14532.1\Homo sapiens\Homo sapiens cDNA FLJ13273 fis, clone OVARC1001010./codon_start=1/protein_id="BAB14532.1"/db_xref="GI:10435228"
2 1 1 0 10 6 6 10 10 11 8 13 6 5 0 12 5 7 9 6 0 9 13 5 0 14 11 6 0 7 7 2 5 4 12 6 9 7 17 21 4 6 6 16 5 8 27 9 8 12 5 3 6 9 4 16 7 9 9 5 4 0 1 0
>AY740522\AY740522\1..177\177\AAU89079.1\Homo sapiens\Homo sapiens HCV F-transactivated protein 2 mRNA, complete cds./codon_start=1/product="HCV F-transactivated protein 2"/protein_id="AAU89079.1"/db_xref="GI:52857652"
0 0 0 0 1 1 0 1 1 0 2 1 0 1 0 1 1 1 3 0 0 3 2 0 0 0 3 1 1 1 1 0 0 3 1 1 1 0 5 1 2 0 1 1 0 0 1 0 0 1 1 4 0 1 3 0 0 0 3 2 0 1 0 0
>BC012858\BC012858\71..613\543\AAH12858.1\Homo sapiens\Homo sapiens pituitary tumor-transforming 1 interacting protein,mRNA (cDNA clone MGC:9271 IMAGE:3857505), complete cds./gene="PTTG1IP"/codon_start=1/product="pituitary tumor-transforming gene 1 protein-interacting protein, precursor"/protein_id="AAH12858.1"/db_xref="GI:15277511"/db_xref="GeneID:754"/db_xref="MIM:603784"
0 3 5 1 4 6 0 5 8 2 0 3 0 2 1 2 3 1 3 3 1 1 2 2 6 1 2 6 4 5 4 3 2 1 1 3 3 2 5 6 9 0 0 3 0 1 6 10 2 1 2 2 8 6 0 3 1 5 1 4 4 1 0 0
>HUMPLCA\M34667\77..3949\3873\AAA36452.1\Homo sapiens\Human phospholipase C-gamma mRNA, complete cds./codon_start=1/protein_id="AAA36452.1"/db_xref="GI:190038"
15 23 25 11 4 10 5 33 54 13 2 12 14 28 6 9 26 13 13 24 10 8 14 25 9 21 10 44 5 19 9 32 28 2 4 21 36 6 10 62 38 12 6 53 22 9 20 93 54 20 39 12 15 8 44 22 2 37 18 32 19 0 1 0
>AY305302\AY305302\15..1766\1752\AAP72167.1\Homo sapiens\Homo sapiens kin of irregular chiasm 2 splice variant B (KIRREL2)mRNA, complete cds; alternatively spliced./gene="KIRREL2"/codon_start=1/product="kin of irregular chiasm 2 splice variant B"/protein_id="AAP72167.1"/db_xref="GI:32186868"
4 11 13 4 6 5 3 11 37 3 2 4 6 8 6 13 16 6 12 15 0 10 13 15 6 13 8 32 6 11 10 19 21 8 2 14 30 4 1 8 8 3 4 15 8 3 9 26 16 10 5 2 9 3 15 4 2 5 5 4 11 1 0 0
>BC030532\BC030532\118..2685\2568\AAH30532.1\Homo sapiens\Homo sapiens suppression of tumorigenicity 14 (colon carcinoma,matriptase, epithin), mRNA (cDNA clone MGC:40392 IMAGE:5213189),complete cds./gene="ST14"/codon_start=1/product="matriptase"/protein_id="AAH30532.1"/db_xref="GI:20988875"/db_xref="GeneID:6768"/db_xref="MIM:606797"
0 21 13 3 2 9 0 16 41 1 2 7 6 24 2 3 31 4 7 21 13 5 6 23 10 8 3 26 9 8 11 40 21 5 5 20 35 3 9 29 28 9 1 33 16 7 3 41 42 11 26 2 29 11 36 7 1 23 2 10 15 0 1 0
>BC034410\BC034410\154..1977\1824\AAH34410.1\Homo sapiens\Homo sapiens engulfment and cell motility 3 (ced-12 homolog, C.elegans), mRNA (cDNA clone MGC:34167 IMAGE:5171412), complete cds./gene="ELMO3"/codon_start=1/product="engulfment and cell motility 3"/protein_id="AAH34410.1"/db_xref="GI:21706711"/db_xref="GeneID:79767"/db_xref="MIM:606422"
2 14 16 6 1 6 5 19 61 4 0 8 3 9 1 2 21 6 7 9 3 5 6 24 2 7 4 23 4 7 2 15 13 2 1 5 25 1 1 22 16 3 3 31 9 2 5 48 20 5 8 6 8 4 19 5 2 14 2 20 5 0 0 1
>AF312923\AF312923\18..296\279\AAK28486.1\Homo sapiens\Homo sapiens prostin 1 short isoform mRNA, complete cds./codon_start=1/product="prostin 1 short isoform"/protein_id="AAK28486.1"/db_xref="GI:13507169"
1 3 0 1 0 1 1 0 10 1 2 3 0 3 0 0 1 0 0 2 2 2 1 2 0 0 1 10 2 0 2 5 1 0 0 1 4 0 1 0 0 0 0 5 0 1 1 4 3 0 1 2 3 0 1 1 1 1 0 1 4 0 0 1
>AY358306\AY358306\214..2064\1851\AAQ88673.1\Homo sapiens\Homo sapiens clone DNA57254 GPR125 (UNQ556) mRNA, complete cds./locus_tag="UNQ556"/codon_start=1/product="GPR125"/protein_id="AAQ88673.1"/db_xref="GI:37181732"
5 8 9 3 10 7 6 7 29 11 6 12 11 2 5 14 4 11 8 12 5 11 8 9 5 4 13 12 10 12 14 18 9 6 5 7 15 10 10 15 16 18 6 21 3 4 15 12 10 22 6 14 7 12 7 15 8 3 17 13 9 1 0 0
>BC042755\BC042755\2463..2558\96\AAH42755.1\Homo sapiens\Homo sapiens regulator of G-protein signalling 2, 24kDa, mRNA (cDNAclone IMAGE:4830785), complete cds./gene="RGS2"/codon_start=1/product="RGS2 protein"/protein_id="AAH42755.1"/db_xref="GI:71297280"/db_xref="GeneID:5997"/db_xref="MIM:600861"
0 0 0 1 0 0 0 0 0 0 0 2 1 0 0 1 0 0 2 1 0 0 1 0 0 2 0 0 0 1 0 0 0 0 0 0 0 0 1 1 2 0 1 1 0 1 1 3 1 0 1 1 0 1 2 0 0 1 0 1 0 0 0 1
>AF069734\AF069734\1..954\954\AAC39904.1\Homo sapiens\Homo sapiens SPT3-like protein mRNA, complete cds./codon_start=1/product="SPT3-like protein"/protein_id="AAC39904.1"/db_xref="GI:3335557"
5 3 1 0 8 6 2 2 5 8 9 4 3 3 0 7 7 9 5 2 1 7 3 3 0 2 14 6 2 11 3 3 3 2 4 2 4 5 13 5 3 8 7 9 5 2 16 6 9 12 4 5 3 2 6 6 2 6 10 13 1 0 0 1
>S66427\S66427\115..3888\3774\AAB28543.1\Homo sapiens\RBP1=retinoblastoma binding protein 1 [human, Nalm-6 pre-B cellleukemia, mRNA, 4834 nt]./gene="RBP1"/codon_start=1/product="retinoblastoma binding protein 1"/protein_id="AAB28543.1"/db_xref="GI:435776"
11 1 2 4 27 19 13 15 9 19 24 16 30 6 3 39 14 35 24 14 4 19 23 4 5 24 22 10 2 22 34 5 5 11 26 4 14 20 83 55 13 46 23 21 4 14 118 51 28 67 6 19 5 12 6 18 17 12 32 20 8 0 0 1
>HSA413230\AJ413230\209..2200\1992\CAC88372.1\Homo sapiens\Homo sapiens mRNA for anion transporter (SUT2/SLC26A7 gene),isoform 2./gene="SUT2/SLC26A7"/function="putative sulfate transporter"/codon_start=1/product="anion transporter"/protein_id="CAC88372.1"/db_xref="GI:18643952"/db_xref="GOA:Q8TE53"/db_xref="UniProt/TrEMBL:Q8TE53"
3 1 1 0 3 6 4 6 19 17 10 17 12 10 1 10 9 10 17 9 2 6 12 5 3 7 16 18 2 18 23 8 3 4 7 9 26 19 25 11 15 16 9 15 2 10 20 5 8 13 4 20 7 11 10 25 21 12 18 26 7 0 0 1
>HUMGLIA1F\M64979\1..1128\1128\AAA58611.1\Homo sapiens\Human glial factor-1 (which interacts with a polyomavirus (JC)B-domain) mRNA, partial cds./gene="glial factor-1"/codon_start=1/product="glial factor-1"/protein_id="AAA58611.1"/db_xref="GI:183250"
4 3 5 4 5 13 0 6 14 5 0 3 1 10 2 4 10 2 2 8 3 2 10 7 2 11 5 15 3 10 7 10 11 5 1 11 14 2 6 12 9 1 3 25 11 3 8 23 11 4 1 3 1 1 6 5 3 5 2 3 0 0 0 0
>BC070085\BC070085\218..2887\2670\AAH70085.1\Homo sapiens\Homo sapiens colony stimulating factor 2 receptor, beta,low-affinity (granulocyte-macrophage), mRNA (cDNA clone MGC:87425IMAGE:30344148), complete cds./gene="CSF2RB"/codon_start=1/product="CSF2RB protein"/protein_id="AAH70085.1"/db_xref="GI:47123336"/db_xref="GeneID:1439"/db_xref="MIM:138981"
2 13 8 1 3 19 6 27 42 5 1 1 11 26 5 11 34 9 5 28 3 5 31 42 9 32 10 35 3 9 13 20 33 4 3 21 36 5 7 18 14 3 6 40 16 3 7 44 34 9 16 3 12 6 16 8 4 15 5 13 19 0 0 1
>DQ023504\DQ023504\960..3143\2184\AAY89635.1\Homo sapiens\Homo sapiens prolyl endopeptidase-like variant C2 (PREPL) mRNA,complete cds, alternatively spliced./gene="PREPL"/codon_start=1/product="prolyl endopeptidase-like variant C2"/protein_id="AAY89635.1"/db_xref="GI:68303897"
3 4 4 6 9 3 8 11 11 19 15 13 5 2 0 12 7 9 16 10 2 14 14 7 1 17 11 6 3 14 12 9 4 9 10 2 12 18 36 27 11 24 8 17 11 12 42 15 16 33 14 19 6 11 17 16 13 7 17 15 8 0 0 1
>HUMDCKATPB\M60527\160..942\783\AAA35752.1\Homo sapiens\Human deoxycytidine kinase mRNA, complete cds./EC_number="2.7.1.74"/codon_start=1/product="deoxycytidine kinase"/protein_id="AAA35752.1"/db_xref="GI:181510"
3 1 1 0 5 2 0 3 5 9 5 5 2 1 0 8 4 5 8 4 0 3 1 1 2 6 3 6 0 2 2 3 4 1 1 1 4 6 11 6 3 10 10 3 0 5 17 11 5 6 0 12 4 2 3 9 2 7 4 6 7 0 0 1
>BC020228\BC020228\7..864\858\AAH20228.1\Homo sapiens\Homo sapiens dodecenoyl-Coenzyme A delta isomerase (3,2trans-enoyl-Coenzyme A isomerase), mRNA (cDNA clone MGC:31929IMAGE:4541779), complete cds./gene="DCI"/codon_start=1/product="DCI protein"/protein_id="AAH20228.1"/db_xref="GI:18044954"/db_xref="GeneID:1632"/db_xref="MIM:600305"
3 8 7 1 0 3 0 5 28 0 1 2 1 5 2 1 9 0 0 5 5 1 2 4 7 0 1 16 14 5 3 9 8 2 0 9 13 2 5 7 7 1 0 14 2 1 2 14 12 1 5 0 2 2 7 1 2 6 2 7 3 1 0 0
>BC033212\BC033212\31..2487\2457\AAH33212.1\Homo sapiens\Homo sapiens KIAA1914, transcript variant 1, mRNA (cDNA cloneMGC:45872 IMAGE:4909140), complete cds./gene="KIAA1914"/codon_start=1/product="KIAA1914 protein, isoform 1"/protein_id="AAH33212.1"/db_xref="GI:21620069"/db_xref="GeneID:84632"
0 9 13 1 4 10 5 23 46 8 2 4 6 21 5 13 30 6 14 20 4 3 20 13 8 17 11 25 5 11 6 24 4 3 1 15 31 1 20 52 17 10 4 34 12 1 22 66 34 14 17 6 11 5 7 2 2 15 7 9 9 0 1 0
>HUMMOXYII\M83772\137..1738\1602\AAA86284.1\Homo sapiens\Human flavin-containing monooxygenase form II (FMO2) mRNA, completecds./gene="FMO2"/codon_start=1/product="flavoprotein"/protein_id="AAA86284.1"/db_xref="GI:188631"/db_xref="GDB:G00-127-981"
2 2 3 1 5 6 3 9 14 5 5 9 3 12 4 3 11 6 11 11 0 6 9 10 1 10 13 11 0 6 9 16 12 5 10 9 11 6 20 19 12 12 2 11 3 6 11 18 11 12 6 8 3 8 15 26 6 12 17 16 10 1 0 0
>BC002973\BC002973\71..931\861\AAH02973.1\Homo sapiens\Homo sapiens ribonuclease H1, mRNA (cDNA clone MGC:2019IMAGE:3537074), complete cds./gene="RNASEH1"/codon_start=1/product="ribonuclease H1"/protein_id="AAH02973.1"/db_xref="GI:12804229"/db_xref="GeneID:246243"/db_xref="MIM:604123"
2 4 2 2 9 5 0 1 7 3 2 2 1 2 3 2 6 3 4 3 2 3 3 1 5 5 9 13 3 3 7 7 10 3 1 6 5 6 8 9 4 8 7 4 2 7 11 10 8 4 3 3 5 0 4 9 3 3 4 7 8 0 0 1
>AF304464\AF304464\350..2539\2190\AAL04015.1\Homo sapiens\Homo sapiens calcium transport protein CaT2 mRNA, complete cds./codon_start=1/product="calcium transport protein CaT2"/protein_id="AAL04015.1"/db_xref="GI:15625297"
7 11 7 6 4 10 8 18 51 15 1 9 1 17 0 9 7 7 8 21 4 8 8 15 1 6 7 28 4 12 13 6 20 7 1 11 29 7 5 15 19 7 8 26 13 7 7 37 24 8 11 10 10 4 24 16 1 29 11 22 11 0 0 1
>AK024329\AK024329\70..1860\1791\BAB14888.1\Homo sapiens\Homo sapiens cDNA FLJ14267 fis, clone PLACE1002665, highly similarto Mus musculus enhancer of polycomb (Epc1) mRNA./codon_start=1/protein_id="BAB14888.1"/db_xref="GI:10436688"
10 2 4 1 9 8 5 6 12 7 12 7 19 9 3 17 3 22 15 6 4 17 14 5 1 14 21 13 1 16 9 6 5 5 8 7 8 11 22 13 10 21 18 23 7 10 19 7 13 16 6 8 2 5 5 11 6 7 9 13 3 0 1 0
>BC009679\BC009679\18..995\978\AAH09679.1\Homo sapiens\Homo sapiens DKFZP566O084 protein, mRNA (cDNA clone MGC:8916IMAGE:3878039), complete cds./gene="DKFZp566O084"/codon_start=1/product="DKFZP566O084 protein"/protein_id="AAH09679.1"/db_xref="GI:16307180"/db_xref="GeneID:25979"
3 1 4 2 2 6 2 9 16 3 1 2 2 7 0 5 7 1 7 14 1 1 1 3 2 5 8 15 2 14 2 12 7 3 1 8 15 5 7 14 4 4 1 8 4 1 5 7 9 4 5 6 2 3 9 4 2 14 3 9 1 0 1 0
>AY223901\AY223901\272..652\381\AAO73604.1\Homo sapiens\Homo sapiens putative schizophrenia protein variant 4 (G72) mRNA,complete cds, alternatively spliced./gene="G72"/codon_start=1/product="putative schizophrenia protein variant 4"/protein_id="AAO73604.1"/db_xref="GI:29423472"
0 0 0 0 6 4 2 1 3 3 2 3 1 2 0 6 2 0 3 0 1 1 0 1 0 2 3 0 0 3 3 2 1 3 1 1 1 0 4 4 2 2 1 5 2 4 8 4 2 1 2 3 0 2 2 4 2 1 4 4 2 0 0 1
>HSMH3C2R\X04481 K01236\37..2295\2259\CAA28169.1\Homo sapiens\Human mRNA for complement component C2./codon_start=1/protein_id="CAA28169.1"/db_xref="GI:34628"/db_xref="GOA:P06681"/db_xref="UniProt/Swiss-Prot:P06681"
3 10 10 3 4 11 2 15 40 11 2 4 4 20 7 10 17 6 12 16 4 5 10 20 2 10 6 23 3 11 11 23 18 10 1 18 23 6 13 23 24 19 7 23 6 13 13 26 23 15 6 10 17 7 17 14 2 23 7 20 13 0 1 0
>BC004492\BC004492\6..740\735\AAH04492.1\Homo sapiens\Homo sapiens DKFZP586A0522 protein, mRNA (cDNA clone MGC:11081IMAGE:3689692), complete cds./gene="DKFZP586A0522"/codon_start=1/product="DKFZP586A0522 protein"/protein_id="AAH04492.1"/db_xref="GI:13325370"/db_xref="GeneID:25840"
1 3 3 0 4 2 0 3 20 2 0 5 0 3 1 3 5 1 1 4 1 2 2 5 1 3 3 7 1 5 2 5 6 0 1 2 16 0 4 9 10 1 2 7 4 2 2 14 1 4 6 3 6 3 10 9 2 6 4 4 8 0 1 0
>HSU94586\U94586\91..336\246\AAB52726.1\Homo sapiens\Homo sapiens NADH:ubiquinone oxidoreductase MLRQ subunit mRNA,complete cds./codon_start=1/product="NADH:ubiquinone oxidoreductase MLRQ subunit"/protein_id="AAB52726.1"/db_xref="GI:1946692"
0 1 0 2 1 0 0 3 4 0 0 3 1 0 0 0 2 0 1 0 0 2 4 3 0 0 2 1 0 1 3 0 0 2 1 0 2 1 1 6 2 4 1 2 0 1 1 1 1 4 3 1 0 1 3 2 0 3 1 1 2 1 0 0
>BC093838\BC093838\64..627\564\AAH93838.1\Homo sapiens\Homo sapiens hypothetical protein BC011880, mRNA (cDNA cloneMGC:120873 IMAGE:7939683), complete cds./gene="LOC113444"/codon_start=1/product="hypothetical protein LOC113444"/protein_id="AAH93838.1"/db_xref="GI:62740001"/db_xref="GeneID:113444"
0 0 0 1 0 5 3 3 7 5 1 2 2 4 0 6 2 5 2 3 0 2 6 2 0 4 7 5 0 3 4 9 2 1 0 2 8 4 3 3 2 1 2 4 6 3 5 5 3 3 1 4 2 4 2 6 0 1 3 5 9 0 0 1
>AF221069\AF221069\10..795\786\AAF26448.1\Homo sapiens\Homo sapiens Claudin-18 mRNA, complete cds./codon_start=1/product="Claudin-18"/protein_id="AAF26448.1"/db_xref="GI:6715518"
1 2 1 0 0 4 1 4 14 2 0 0 3 8 0 4 4 2 6 12 0 3 2 2 0 2 3 15 3 4 5 12 7 6 3 4 12 3 4 5 8 0 2 6 2 1 4 3 6 1 7 4 7 1 8 4 1 9 5 15 4 1 0 0
>AF012629\AF012629\1..780\780\AAB67110.1\Homo sapiens\Homo sapiens antagonist decoy receptor for TRAIL/Apo-2L (TRID)mRNA, complete cds./gene="TRID"/codon_start=1/product="antagonist decoy receptor for TRAIL/Apo-2L"/protein_id="AAB67110.1"/db_xref="GI:2338431"
0 0 4 0 2 2 3 1 3 1 0 0 3 4 0 5 7 3 9 16 1 8 11 2 5 7 1 12 1 12 2 1 8 2 1 8 6 5 4 4 6 4 3 7 1 4 14 10 1 4 3 0 6 9 4 2 1 5 2 8 1 0 0 1
>BT007015\BT007015\1..1251\1251\AAP35661.1\Homo sapiens\Homo sapiens cyclin G associated kinase mRNA, complete cds./codon_start=1/product="cyclin G associated kinase"/protein_id="AAP35661.1"/db_xref="GI:30582869"
0 5 7 0 1 3 0 10 25 2 0 2 3 14 7 9 13 3 5 6 7 1 15 17 11 9 5 21 6 10 6 19 9 3 0 3 12 0 6 14 9 4 4 16 6 0 4 15 20 3 1 2 3 1 12 6 0 3 3 6 9 0 1 0
>BC002631\BC002631\248..1429\1182\AAH02631.1\Homo sapiens\Homo sapiens matrix metalloproteinase 28, transcript variant 2,mRNA (cDNA clone MGC:4164 IMAGE:3610296), complete cds./gene="MMP28"/codon_start=1/product="matrix metalloproteinase 28, preproprotein isoform 2"/protein_id="AAH02631.1"/db_xref="GI:12803593"/db_xref="GeneID:79148"/db_xref="MIM:608417"
1 20 3 3 3 5 4 8 25 1 0 4 4 7 1 1 8 2 2 7 2 4 4 13 3 4 5 16 14 6 5 15 9 2 1 8 12 3 7 8 8 3 7 14 10 2 4 16 12 9 10 2 2 0 15 6 0 5 2 4 12 0 0 1
>AL354750#4\AL354750\join(127998..128040,AL356053.14:42950..43060, AL356053.14:46033..46143,AL356053.14:51859..51972, AL356053.14:68600..68710,AL356053.14:83714..83812, AL356053.14:85867..85977,AL356053.14:86312..86437, AL356053.14:161995..162078,AL356053.14:171350..171433, AL591850.4:7143..7229,AL591850.4:17440..17523, AL591850.4:28168..28251,AL591850.4:28501..28584, AL591850.4:29001..29084,AL365203.19:2001..2030, AL365203.19:2710..2832,AL365203.19:5921..6046, AL365203.19:8514..8603,AL365203.19:30461..30507)\-5326254\CAI39705.1\Homo sapiens\Human DNA sequence from clone RP11-195O1 on chromosome 10 Containsthe 3' end of a novel gene novel protein (FLJ32762) (FLJ25419), anuclear DNA-binding protein (C1D) pseudogene, the 5' end of a novelgene (FLJ13031) and two CpG islands, complete sequence./gene="RP11-479G22.1"/locus_tag="RP11-479G22.1-001"/standard_name="OTTHUMP00000019424"/codon_start=1/product="novel protein"/protein_id="CAI39705.1"/db_xref="GI:57162332"/db_xref="UniProt/TrEMBL:Q5VTK2"
1 0 0 2 10 4 7 13 11 20 21 21 6 8 1 16 6 6 6 9 0 18 10 12 0 10 6 7 1 4 11 3 5 4 5 2 10 10 20 7 3 15 12 15 6 12 7 4 3 11 2 25 10 18 15 39 11 8 24 14 13 12 7 12
>HS108K11#3\Z85986\join(83137..83267,97697..97748,98876..98998, 101522..101605,105499..105622,107847..108001, 115737..115839,116695..116756,123349..123466, 124853..124976,125464..125559,126534..126628, 127425..127555)\1398\CAB39180.1\Homo sapiens\Human DNA sequence from clone RP1-108K11 on chromosome 6p21Contains the SFRS3 for splicing factor arginine/serine-rich(SRP20), the STK38 gene for serine/threonine protein kinase (NDR),the 3' end of a gene for a novel protein (2410004NRIK) and a CpGisland, complete sequence./gene="STK38"/locus_tag="RP1-108K11.2-001"/standard_name="OTTHUMP00000016293"/codon_start=1/product="serine\/threonine kinase 38"/protein_id="CAB39180.1"/db_xref="GI:4495062"/db_xref="GOA:Q15208"/db_xref="InterPro:IPR000719"/db_xref="InterPro:IPR000961"/db_xref="InterPro:IPR001245"/db_xref="InterPro:IPR002290"/db_xref="InterPro:IPR008271"/db_xref="InterPro:IPR011009"/db_xref="UniProt/Swiss-Prot:Q15208"
2 1 3 5 11 6 6 6 6 12 3 8 4 5 1 7 4 6 15 6 2 8 5 2 0 11 14 4 1 5 8 9 4 2 4 1 11 6 25 16 11 6 4 7 5 8 24 22 13 12 8 7 3 3 11 13 7 10 9 19 8 0 1 0
>CR457017\CR457017\1..414\414\CAG33298.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834H055D forgene CRABP1, cellular retinoic acid binding protein 1; completecds, incl. stopcodon./gene="CRABP1"/codon_start=1/protein_id="CAG33298.1"/db_xref="GI:48146151"/db_xref="GOA:P29762"/db_xref="UniProt/Swiss-Prot:P29762"
0 4 1 1 1 2 0 0 6 3 1 0 0 2 0 0 2 1 1 7 3 3 0 2 1 0 1 6 2 1 2 4 2 1 1 3 6 0 2 7 5 2 1 2 2 0 3 10 5 4 2 1 3 0 4 2 0 5 1 3 3 1 0 0
>BC036298\BC036298\79..1335\1257\AAH36298.2\Homo sapiens\Homo sapiens serine (or cysteine) proteinase inhibitor, clade H(heat shock protein 47), member 1, (collagen binding protein 1),mRNA (cDNA clone MGC:25195 IMAGE:4748644), complete cds./gene="SERPINH1"/codon_start=1/product="serine (or cysteine) proteinase inhibitor, clade H, member 1, precursor"/protein_id="AAH36298.2"/db_xref="GI:37589973"/db_xref="GeneID:871"/db_xref="MIM:600943"
2 14 4 1 0 0 3 10 31 3 2 5 5 8 4 0 16 0 2 10 4 3 1 10 0 4 5 26 8 4 1 15 5 3 0 4 23 1 4 30 11 0 2 11 12 2 2 25 21 3 9 1 2 0 14 2 0 10 2 14 4 0 1 0
>BC063793\BC063793\10..936\927\AAH63793.1\Homo sapiens\Homo sapiens transcriptional regulator protein, mRNA (cDNA cloneMGC:70553 IMAGE:6502502), complete cds./gene="HCNGP"/codon_start=1/product="transcriptional regulator protein"/protein_id="AAH63793.1"/db_xref="GI:39795356"/db_xref="GeneID:29115"
3 0 2 1 4 1 1 3 3 2 1 3 3 4 4 7 6 1 5 16 5 3 5 5 1 4 4 12 4 8 3 10 3 2 1 3 6 5 9 22 6 3 2 8 1 1 17 18 8 17 5 4 0 2 1 5 2 10 5 6 2 0 0 1
>AF152514\AF152514\1..2454\2454\AAD43774.1\Homo sapiens\Homo sapiens protocadherin gamma A7 short form protein(PCDH-gamma-A7) variable region sequence, complete cds./gene="PCDH-gamma-A7"/function="cell-cell adhesion"/codon_start=1/product="protocadherin gamma A7 short form protein"/protein_id="AAD43774.1"/db_xref="GI:5457076"
1 8 12 1 10 5 6 20 44 9 8 12 11 21 3 10 17 8 18 14 10 14 12 18 7 15 7 21 11 16 12 13 13 10 9 18 37 6 13 10 21 15 6 26 12 4 27 27 35 22 16 12 3 3 16 11 11 18 6 12 4 0 0 1
>HSM805396\AL834156\join(890..2041,2041..2295)\1407\CAD38862.1\Homo sapiens\Homo sapiens mRNA; cDNA DKFZp761P2012 (from clone DKFZp761P2012)./gene="DKFZp761P2012"/codon_start=1/product="hypothetical protein"/protein_id="CAD38862.1"/db_xref="GI:21739633"/db_xref="UniProt/TrEMBL:Q8N3H9"
3 17 17 5 0 2 1 4 41 0 0 6 4 7 2 3 8 4 1 17 2 3 9 16 6 6 8 12 8 8 6 16 9 2 1 1 19 3 1 12 9 3 1 30 11 7 2 24 13 8 16 3 5 0 10 3 2 7 5 13 6 0 0 1
>AF121855\AF121855\181..1395\1215\AAD27828.1\Homo sapiens\Homo sapiens sorting nexin 5 (SNX5) mRNA, complete cds./gene="SNX5"/codon_start=1/product="sorting nexin 5"/protein_id="AAD27828.1"/db_xref="GI:4689250"
3 3 4 0 6 5 7 8 11 9 4 6 3 4 1 10 5 5 8 5 2 4 2 5 0 5 5 7 2 12 2 1 2 4 3 6 9 10 24 19 8 8 4 12 4 7 22 18 14 14 5 6 3 2 7 15 3 3 9 8 1 0 0 1
>BC029796\BC029796\322..681\360\AAH29796.1\Homo sapiens\Homo sapiens hypothetical protein BC014011, mRNA (cDNA cloneMGC:35369 IMAGE:5183143), complete cds./gene="LOC116349"/codon_start=1/product="LOC116349 protein"/protein_id="AAH29796.1"/db_xref="GI:20987520"/db_xref="GeneID:116349"
1 2 3 2 3 1 0 2 2 0 0 3 2 3 2 1 1 2 0 4 1 2 1 2 2 4 3 4 3 3 0 7 6 2 1 4 1 1 1 1 2 3 3 4 2 2 3 5 0 0 0 0 0 2 1 2 1 0 0 4 2 0 0 1
>BC053592\BC053592\488..799\312\AAH53592.1\Homo sapiens\Homo sapiens uridine phosphorylase 1, mRNA (cDNA cloneIMAGE:5724026), complete cds./gene="UPP1"/codon_start=1/product="UPP1 protein"/protein_id="AAH53592.1"/db_xref="GI:31566145"/db_xref="GeneID:7378"/db_xref="MIM:191730"
0 3 1 1 0 1 0 4 6 0 0 1 0 2 1 0 6 0 0 2 1 0 0 0 1 1 2 7 2 1 0 3 3 0 0 2 5 0 1 5 1 2 2 5 0 0 2 5 3 1 3 3 4 1 2 1 0 3 0 3 0 0 0 1
>AY459291\AY459291\1..240\240\AAR23236.1\Homo sapiens\Homo sapiens HCV-NS5ATP5 binding protein 1 mRNA, complete cds./codon_start=1/product="HCV-NS5ATP5 binding protein 1"/protein_id="AAR23236.1"/db_xref="GI:38505469"
0 0 0 0 2 0 0 1 1 1 2 0 3 3 0 2 1 0 1 3 0 3 5 1 0 5 2 2 0 0 2 0 2 2 1 2 2 0 1 0 1 2 1 2 3 2 0 0 2 0 0 1 0 0 4 4 1 0 1 3 2 0 0 1
>AY230251\AY230251\1..873\873\AAO73561.1\Homo sapiens\Homo sapiens N-acetyltransferase 2 (NAT2) gene, NAT2*12D allele,complete cds./gene="NAT2"/allele="NAT2*12D"/codon_start=1/product="N-acetyltransferase 2"/protein_id="AAO73561.1"/db_xref="GI:29423786"
1 0 2 0 8 3 1 6 8 7 5 7 2 5 0 7 2 0 10 6 2 5 4 2 0 6 1 1 0 4 4 5 7 3 1 3 5 5 9 5 7 9 4 11 4 2 12 10 6 5 8 6 2 4 3 12 3 6 13 7 4 0 1 0
>AY663396#2\AY663396\complement(join(37566..37720,38077..38358,38772..39020, 42791..42872))\768\AAU87981.1\Homo sapiens\Homo sapiens voucher Coriell Cell Repository DNA sample NA14660 MHCclass II antigen (HLA-DQB1) gene, HLA-DQB1-DQB1*050101 allele andMHC class II antigen (HLA-DQA1) gene, complete cds; and MHC classII antigen (HLA-DRB1) gene, partial cds./gene="HLA-DQA1"/codon_start=1/product="MHC class II antigen"/protein_id="AAU87981.1"/db_xref="GI:52840181"
0 1 1 1 2 1 1 7 12 2 0 4 3 4 0 7 4 2 5 8 0 3 2 4 1 8 2 5 0 8 3 7 4 8 1 5 13 4 5 5 9 2 2 6 5 2 3 14 6 4 6 1 2 3 7 6 0 7 6 6 5 0 0 1
>BC062746\BC062746\47..538\492\AAH62746.1\Homo sapiens\Homo sapiens lipocalin 6, mRNA (cDNA clone MGC:72111IMAGE:6452008), complete cds./gene="LCN6"/codon_start=1/product="lipocalin 6"/protein_id="AAH62746.1"/db_xref="GI:38540969"/db_xref="GeneID:158062"/db_xref="MIM:609379"
1 0 2 0 2 2 0 3 16 3 0 2 2 3 1 1 3 2 1 4 1 3 1 4 0 1 0 8 1 3 3 5 6 0 0 3 12 0 0 5 6 1 0 7 1 0 2 9 6 0 2 1 0 1 6 3 2 2 0 5 5 0 1 0
>HSPMP35HM\Y12860\122..1045\924\CAA73367.1\Homo sapiens\Homo sapiens mRNA for peroxisomal integral membrane protein./codon_start=1/product="peroxisomal integral membrane protein"/protein_id="CAA73367.1"/db_xref="GI:2808531"/db_xref="GOA:O43808"/db_xref="UniProt/Swiss-Prot:O43808"
3 1 3 3 6 2 2 11 13 10 3 5 2 6 1 2 3 2 11 5 2 5 5 3 0 1 7 8 1 7 10 2 4 4 6 5 12 6 15 4 4 7 4 7 5 3 8 3 1 6 4 6 2 0 6 12 1 6 9 8 4 0 0 1
>BC012803\BC012803\84..1583\1500\AAH12803.1\Homo sapiens\Homo sapiens CDC20 cell division cycle 20 homolog (S. cerevisiae),mRNA (cDNA clone MGC:2777 IMAGE:2959588), complete cds./gene="CDC20"/codon_start=1/product="cell division cycle 20"/protein_id="AAH12803.1"/db_xref="GI:15215409"/db_xref="GeneID:991"/db_xref="MIM:603618"
7 8 10 3 1 2 4 7 22 5 0 6 3 13 1 7 15 17 5 10 1 4 6 9 2 13 15 25 5 7 4 16 7 9 5 4 17 4 10 13 12 9 5 22 11 9 9 14 7 12 7 5 3 4 4 3 1 14 3 7 16 0 0 1
>AL355987#23\AL355987\complement(join(140941..140981,141391..141484, 141773..141933,142305..142356,144666..144743))\426\CAI12698.1\Homo sapiens\Human DNA sequence from clone RP11-216L13 on chromosome 9 Containsthe 3' end of the gene for a novel protein similar to mousepancreatitis-induced protein 49 (PIP49), the 5' end of a novelgene (FLJ30346), five novel genes (containing LOC158062, KIAA1984,FLJ35320, FLJ36901, FLJ30985, FLJ10101, FLJ37063 FLJ13045,FLJ40767), a nucleolin (NCL) pseudogene, the gene for a novelprotein similar to mouse lipocalin 8 (EP17, Lcn5), a 13kD lysosomalH+ transporting ATPase V1 subunit G isoform 1 (ATP6V1G1)pseudogene, the gene for phosphohistidine phosphatase (PHP14), thegene for a novel protein similar to rat apical early endosomalglycoprotein (LOC252882), the EDF1 gene for endothelialdifferentiation-related factor 1 (MBF1, EDF-1), the 5' end of theTRAF2 gene for TNF receptor-associated factor 2 (TRAP, TRAP3) andten CpG islands, complete sequence./gene="EDF1"/locus_tag="RP11-216L13.1-003"/standard_name="OTTHUMP00000022618"/codon_start=1/product="endothelial differentiation-related factor 1"/protein_id="CAI12698.1"/db_xref="GI:55958759"/db_xref="GOA:O60869"/db_xref="GOA:Q5T5T2"/db_xref="UniProt/Swiss-Prot:O60869"
1 1 4 1 2 2 0 0 6 2 1 0 0 2 0 1 3 1 1 3 6 1 1 1 0 1 1 9 2 4 3 4 1 1 0 0 10 0 5 10 3 2 2 10 1 2 1 9 6 2 0 1 0 0 0 0 1 5 2 1 2 0 0 1
>AP001748#1\AP001748 AL163293 BA000005\join(160243..160290,163349..163476,165911..166082, 168926..169096,172766..172865,173991..174088, 177161..177289,180729..180805,184560..184732, 185748..185959)\1308\BAA95533.1\Homo sapiens\Homo sapiens genomic DNA, chromosome 21q, section 92/105./gene="PKNOX1"/codon_start=1/product="homeobox-containing protein"/protein_id="BAA95533.1"/db_xref="GI:7768746"
2 1 2 0 3 4 2 5 10 5 7 9 5 6 3 9 10 8 17 7 4 5 10 6 5 9 6 10 5 7 7 6 7 3 6 10 14 4 11 9 14 4 12 30 2 5 14 14 8 15 3 3 3 4 4 6 1 10 9 12 3 0 1 0
>AF401998\AF401998\1..1149\1149\AAK94915.1\Homo sapiens\Homo sapiens muscleblind 41kD isoform (MBNL) mRNA, complete cds./gene="MBNL"/codon_start=1/product="muscleblind 41kD isoform"/protein_id="AAK94915.1"/db_xref="GI:15290633"
4 1 4 2 3 3 3 1 4 4 7 7 5 2 1 4 5 3 15 6 3 6 14 9 3 9 19 20 0 18 5 3 3 5 5 6 4 9 10 6 10 10 11 14 2 8 7 6 6 3 5 3 9 5 3 8 5 4 5 16 1 0 1 0
>AY166584\AY166584\1..2022\2022\AAO27704.1\Homo sapiens\Homo sapiens vasorin mRNA, complete cds./codon_start=1/product="vasorin"/protein_id="AAO27704.1"/db_xref="GI:37725933"
4 20 18 2 0 5 3 30 73 2 0 6 2 10 3 3 22 0 13 16 10 6 17 32 13 13 8 36 7 9 2 29 25 3 1 13 25 0 1 7 20 2 0 29 11 2 3 32 19 3 9 1 15 4 10 4 0 9 2 6 3 1 0 0
>BC021988\BC021988\95..823\729\AAH21988.1\Homo sapiens\Homo sapiens Nedd4 family interacting protein 2, mRNA (cDNA cloneMGC:23729 IMAGE:4101140), complete cds./gene="NDFIP2"/codon_start=1/product="NDFIP2 protein"/protein_id="AAH21988.1"/db_xref="GI:18314412"/db_xref="GeneID:54602"
0 1 0 0 6 3 1 2 2 11 2 2 5 3 1 6 1 4 5 3 0 6 8 2 2 5 12 0 1 12 6 3 3 2 2 2 5 3 3 1 4 5 1 8 2 1 9 6 3 8 3 9 1 3 10 9 3 4 6 6 5 0 1 0
>HUMC1A1\M20789\join(120..222,1678..1872,2011..2045,2148..2183,2274..2375, 3099..3170,3405..3449,3598..3651,3813..3866,4359..4412, 4529..4582,4856..4909,4999..5043,5160..5213,5328..5372, 5551..5604,5864..5962,6023..6067,6170..6268,6396..6449, 6666..6773,6870..6923,7048..7146,7308..7361,7450..7548)\1767\AAB59373.1\Homo sapiens\Human, alpha 1 collagen type I gene, exons 1-25, clone RMS-8./gene="COL1A1"/codon_start=1/product="alpha-1 type I collagen"/protein_id="AAB59373.1"/db_xref="GI:179594"/db_xref="GDB:G00-119-061"
9 2 2 10 2 2 0 9 8 1 1 3 4 1 0 6 7 1 1 8 1 6 8 54 0 62 3 11 1 37 43 45 5 75 1 6 6 4 8 13 6 4 10 8 2 1 15 17 12 12 1 2 8 2 7 2 0 5 2 6 1 0 0 0
>AF490768\AF490768\89..4792\4704\AAM18046.1\Homo sapiens\Homo sapiens KIAA0184 protein mRNA, complete cds./codon_start=1/product="KIAA0184 protein"/protein_id="AAM18046.1"/db_xref="GI:20269774"
6 14 25 7 18 22 10 31 95 14 8 16 13 25 16 21 30 17 25 51 12 23 22 35 20 32 36 54 15 34 28 33 34 15 5 47 76 20 27 42 21 10 7 45 31 9 22 56 45 28 26 13 18 19 28 12 8 34 13 30 18 0 0 1
>BC007537\BC007537\342..2690\2349\AAH07537.1\Homo sapiens\Homo sapiens CSRP2 binding protein, transcript variant 1, mRNA(cDNA clone MGC:15388 IMAGE:3350378), complete cds./gene="CSRP2BP"/codon_start=1/product="CSRP2 binding protein, isoform a"/protein_id="AAH07537.1"/db_xref="GI:14043103"/db_xref="GeneID:57325"
5 5 6 4 14 19 2 8 28 11 7 15 12 11 3 20 12 16 12 12 7 11 18 12 5 18 13 15 1 15 19 10 8 7 6 11 14 11 28 23 6 6 8 23 10 6 33 27 25 27 14 14 4 9 13 18 5 13 17 18 12 0 0 1
>BC034737\BC034737\225..2123\1899\AAH34737.1\Homo sapiens\Homo sapiens ligand of numb-protein X, mRNA (cDNA clone MGC:34086IMAGE:5194423), complete cds./gene="LNX"/codon_start=1/product="multi-PDZ-domain-containing protein"/protein_id="AAH34737.1"/db_xref="GI:21961543"/db_xref="GeneID:84708"
8 4 8 5 16 9 4 10 21 8 6 11 6 12 2 6 21 12 10 6 1 9 16 12 1 12 13 15 3 10 16 15 9 10 5 14 18 9 16 9 17 15 3 13 7 10 21 16 18 16 8 8 5 6 6 7 6 16 19 8 9 0 1 0
>BC071982\BC071982\116..676\561\AAH71982.1\Homo sapiens\Homo sapiens cDNA clone MGC:88679 IMAGE:5477638, complete cds./codon_start=1/product="Unknown (protein for MGC:88679)"/protein_id="AAH71982.1"/db_xref="GI:47938380"
1 1 2 1 2 2 0 2 12 7 2 1 6 3 0 6 3 1 4 2 2 3 3 0 0 2 5 4 1 1 2 1 2 2 0 4 4 6 4 8 4 3 2 7 2 4 4 3 1 6 6 2 4 1 5 7 0 5 3 3 2 1 0 0
>CR536527\CR536527\1..783\783\CAG38764.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834F0322D forgene DCK, deoxycytidine kinase; complete cds, incl. stopcodon./gene="DCK"/codon_start=1/protein_id="CAG38764.1"/db_xref="GI:49168538"
3 1 1 0 5 2 0 3 5 9 5 5 2 1 0 8 4 5 8 4 0 3 1 1 2 6 3 6 0 2 2 3 4 1 1 1 4 6 11 6 3 10 10 3 0 5 17 11 5 6 0 12 4 2 3 9 2 7 4 6 7 0 0 1
>AF026445\AF026445\266..3865\3600\AAC02966.1\Homo sapiens\Homo sapiens cofactor of initiator function (CIF150) mRNA, completecds./gene="CIF150"/codon_start=1/product="cofactor of initiator function"/protein_id="AAC02966.1"/db_xref="GI:2739087"
4 2 5 3 21 17 11 9 16 30 21 30 21 20 1 24 14 26 25 8 0 26 28 14 5 18 26 14 2 29 21 9 5 10 16 12 22 28 49 37 21 38 13 29 18 34 45 28 18 37 14 26 4 22 18 41 20 11 27 39 17 0 0 1
>BC057777\BC057777\42..1121\1080\AAH57777.1\Homo sapiens\Homo sapiens guanine nucleotide binding protein (G protein), qpolypeptide, mRNA (cDNA clone MGC:71577 IMAGE:30337698), completecds./gene="GNAQ"/codon_start=1/product="guanine nucleotide binding protein (G protein), q polypeptide"/protein_id="AAH57777.1"/db_xref="GI:35505494"/db_xref="GeneID:2776"/db_xref="MIM:600998"
6 4 5 0 9 3 3 7 12 4 5 2 3 4 1 5 2 6 6 6 4 1 4 4 0 3 3 11 2 5 4 3 4 0 4 8 6 5 6 16 7 8 7 9 3 3 11 18 16 12 9 9 5 0 9 8 2 18 5 11 3 1 0 0
>AY720432\AY720432\1..3858\3858\AAU14134.1\Homo sapiens\Homo sapiens crumbs-like protein 2 precursor (CRB2) mRNA, completecds./gene="CRB2"/codon_start=1/product="crumbs-like protein 2 precursor"/protein_id="AAU14134.1"/db_xref="GI:51921989"
6 35 16 8 4 7 5 45 82 8 0 10 8 16 10 13 20 9 6 33 12 10 21 45 25 29 17 67 27 25 8 82 39 25 3 16 47 1 0 5 13 11 1 40 30 12 9 60 38 20 10 3 74 35 33 10 1 11 2 8 19 0 1 0
>CR456765\CR456765\1..930\930\CAG33046.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834D054D forgene TOMM34, translocase of outer mitochondrial membrane 34;complete cds, incl. stopcodon./gene="TOMM34"/codon_start=1/protein_id="CAG33046.1"/db_xref="GI:48145647"
2 4 4 0 7 2 2 9 13 2 0 7 5 5 2 5 6 4 4 2 2 2 2 5 0 7 10 12 3 9 3 5 2 2 2 1 10 5 10 20 12 5 2 9 3 2 12 13 8 6 8 5 5 2 4 1 0 4 4 5 2 1 0 0
>AK075407\AK075407\73..699\627\BAC11600.1\Homo sapiens\Homo sapiens cDNA PSEC0098 fis, clone NT2RP2002695, highly similarto Mesenchymal stem cell protein DSCD75./codon_start=1/protein_id="BAC11600.1"/db_xref="GI:22761475"
0 22 3 1 0 2 1 4 34 1 0 4 1 1 3 0 3 2 0 4 1 0 0 5 3 1 0 5 13 3 0 4 5 1 0 7 10 0 0 1 3 0 0 8 7 0 0 11 8 2 4 0 5 0 5 3 0 1 0 3 3 0 0 1
>BC006401\BC006401\145..1317\1173\AAH06401.1\Homo sapiens\Homo sapiens Fas apoptotic inhibitory molecule 3, mRNA (cDNA cloneMGC:12770 IMAGE:4308958), complete cds./gene="FAIM3"/codon_start=1/product="Fas apoptotic inhibitory molecule 3"/protein_id="AAH06401.1"/db_xref="GI:13623573"/db_xref="GeneID:9214"/db_xref="MIM:606015"
5 7 4 1 3 12 1 5 24 5 0 2 7 9 2 7 6 4 7 15 1 3 12 12 6 7 7 16 3 5 9 9 7 2 7 4 9 7 6 11 5 3 5 10 9 3 10 11 8 2 9 5 4 2 8 2 1 10 0 9 5 0 0 1
>BC002357\BC002357\211..1644\1434\AAH02357.1\Homo sapiens\Homo sapiens protoporphyrinogen oxidase, mRNA (cDNA clone MGC:8485IMAGE:2821983), complete cds./gene="PPOX"/codon_start=1/product="protoporphyrinogen oxidase"/protein_id="AAH02357.1"/db_xref="GI:12803107"/db_xref="GeneID:5498"/db_xref="MIM:600923"
1 8 8 6 2 9 10 14 29 5 4 8 8 6 0 6 11 14 4 6 0 7 7 10 2 15 8 19 2 19 18 16 10 5 2 11 17 7 3 5 4 3 7 17 9 5 6 22 8 3 3 3 5 3 5 7 2 5 6 5 7 0 0 1
>BC069499\BC069499\267..1526\1260\AAH69499.1\Homo sapiens\Homo sapiens potassium inwardly-rectifying channel, subfamily J,member 5, mRNA (cDNA clone MGC:97076 IMAGE:7262288), complete cds./gene="KCNJ5"/codon_start=1/product="potassium inwardly-rectifying channel J5"/protein_id="AAH69499.1"/db_xref="GI:46854375"/db_xref="GeneID:3762"/db_xref="MIM:600734"
2 7 8 1 1 4 1 17 18 0 0 3 0 11 1 3 6 2 8 14 2 2 5 9 0 3 4 12 1 6 1 18 9 2 0 12 13 4 2 19 13 3 2 13 5 3 11 26 15 6 7 5 5 4 18 4 1 14 10 15 8 0 0 1
>HSGDF5\X80915\640..2145\1506\CAA56874.1\Homo sapiens\H.sapiens Gdf5 gene./gene="Gdf5"/codon_start=1/protein_id="CAA56874.1"/db_xref="GI:671525"/db_xref="GOA:P43026"/db_xref="InterPro:IPR001111"/db_xref="InterPro:IPR001839"/db_xref="InterPro:IPR002400"/db_xref="UniProt/Swiss-Prot:P43026"
5 8 14 1 4 11 0 7 33 4 0 8 0 8 4 4 10 3 6 10 4 4 12 30 3 3 7 26 1 7 10 20 11 4 0 7 15 0 8 30 10 4 2 16 6 2 4 23 19 6 6 4 8 2 14 6 0 10 4 6 7 0 1 0
>HUMFKMKA\M69148\1..432\432\AAA58478.1\Homo sapiens\Human midkine mRNA, complete cds./gene="hMK-1"/codon_start=1/product="midkine"/protein_id="AAA58478.1"/db_xref="GI:182651"
1 5 1 0 0 1 0 6 3 0 0 0 0 1 0 0 3 0 1 11 0 0 0 5 1 0 1 7 4 2 2 8 5 2 0 3 3 0 6 17 2 1 1 5 1 0 0 6 2 3 2 0 9 1 2 2 0 2 0 1 4 0 1 0
>AL606537\AL606537\join(complement(AC011700.5:23459..25185), complement(AC011700.5:16449..16554), complement(AC011700.5:10004..10200),96915..97122)\-1164\CAI15309.1\Homo sapiens\Human DNA sequence from clone RP11-53A1 on chromosome 1 Containsthe 3' end of the PROX1 gene for prospero-related homeobox protein1, complete sequence./gene="PROX1"/locus_tag="RP11-53A1.1-001"/standard_name="OTTHUMP00000035023"/codon_start=1/product="prospero-related homeobox 1"/protein_id="CAI15309.1"/db_xref="GI:55961898"/db_xref="GOA:Q5SW76"/db_xref="InterPro:IPR007738"/db_xref="UniProt/TrEMBL:Q5SW76"
1 1 1 0 22 11 13 16 9 15 14 14 18 10 1 26 6 16 11 9 0 15 13 10 1 15 11 5 0 10 9 5 8 3 9 8 8 10 37 18 10 19 10 19 5 17 28 12 6 12 4 16 9 18 17 23 17 13 21 15 9 17 9 11
>BC099842\BC099842\31..405\375\AAH99842.1\Homo sapiens\Homo sapiens TP53TG3 protein, transcript variant 2, mRNA (cDNAclone MGC:119886 IMAGE:40015192), complete cds./gene="TP53TG3"/codon_start=1/product="hypothetical protein LOC24150, isoform 2"/protein_id="AAH99842.1"/db_xref="GI:71122422"/db_xref="GeneID:24150"
3 2 2 0 3 0 2 1 2 0 0 3 5 3 1 3 3 2 3 2 1 2 3 7 0 7 4 6 1 4 3 1 3 4 0 0 0 4 0 1 0 1 1 1 0 2 2 4 3 0 0 1 4 4 1 3 1 2 0 1 2 1 0 0
>AL357033#1\AL357033\complement(join(5687..6079,6733..6774))\435\CAI17067.1\Homo sapiens\Human DNA sequence from clone RP11-93B14 on chromosome 20 Containsthe SLC21A12 gene for solute carrier family 21 (organic aniontransporter) member 12, the 5' end of the NTSR1 gene encoding thehigh affinity neurotensin receptor 1, three novel genes, the genefor a novel protein (FLJ32154) and four CpG islands, completesequence./gene="RP11-93B14.6"/locus_tag="RP11-93B14.6-001"/standard_name="OTTHUMP00000031495"/codon_start=1/protein_id="CAI17067.1"/db_xref="GI:55959056"/db_xref="UniProt/TrEMBL:Q5JT57"
2 7 9 1 0 2 0 5 5 1 0 1 0 5 2 2 1 1 1 0 5 2 1 3 12 2 2 7 4 1 5 10 5 3 0 1 2 1 1 2 1 0 1 9 2 0 3 2 2 1 0 0 2 0 2 1 0 0 0 1 3 0 0 1
>AF053318\AF053318\245..1123\879\AAD02685.1\Homo sapiens\Homo sapiens CCR4-associated factor 1 (POP2) mRNA, complete cds./gene="POP2"/codon_start=1/product="CCR4-associated factor 1"/protein_id="AAD02685.1"/db_xref="GI:4106061"
2 0 2 2 0 4 2 3 9 12 3 5 5 5 0 3 4 5 9 0 0 1 4 1 0 2 4 5 1 3 8 6 2 3 1 1 9 5 6 9 5 9 1 17 2 4 12 12 8 11 5 7 2 3 6 10 2 7 9 11 3 0 0 1
>S74499\S74499\25..342\318\AAB33275.1\Homo sapiens\Ig VH4=Ig heavy chain variable region {clone D21} [human, systemiclupus erythematosus, mRNA Partial, 343 nt]./gene="Ig VH4"/codon_start=1/product="Ig heavy chain variable region"/protein_id="AAB33275.1"/db_xref="GI:807018"
1 0 1 1 1 0 0 4 5 0 1 0 3 5 1 1 3 4 0 5 3 1 1 1 1 1 0 4 2 0 2 2 4 2 1 2 2 0 0 4 3 0 0 4 0 0 0 6 3 0 4 2 1 1 3 0 0 2 1 3 4 0 0 0
>BC012303\BC012303\81..425\345\AAH12303.1\Homo sapiens\Homo sapiens PDZK1 interacting protein 1, mRNA (cDNA cloneMGC:21224 IMAGE:4469903), complete cds./gene="PDZK1IP1"/codon_start=1/product="PDZK1 interacting protein 1"/protein_id="AAH12303.1"/db_xref="GI:15126763"/db_xref="GeneID:10158"/db_xref="MIM:607178"
0 1 0 0 0 2 0 5 6 2 0 0 0 1 2 1 3 2 1 2 0 0 1 2 2 2 5 6 2 0 4 4 1 0 0 5 5 1 1 2 2 2 1 4 2 1 1 8 0 2 1 1 1 1 3 1 0 3 1 6 2 1 0 0
>AF121775\AF121775\219..1319\1101\AAF24125.1\Homo sapiens\Homo sapiens nasopharyngeal carcinoma susceptibility protein LZ16mRNA, complete cds./codon_start=1/product="nasopharyngeal carcinoma susceptibility protein LZ16"/protein_id="AAF24125.1"/db_xref="GI:6690397"
3 4 8 2 3 8 2 6 15 2 1 2 5 7 2 5 13 3 7 9 12 3 7 8 3 5 6 14 4 2 4 14 11 2 0 5 10 1 13 21 15 1 0 14 6 0 4 24 14 5 6 1 1 2 5 1 0 4 1 8 2 0 0 1
>HSU77396\U77396\234..920\687\AAB36550.1\Homo sapiens\Homo sapiens LPS-Induced TNF-Alpha Factor (LITAF) mRNA, completecds./gene="LITAF"/codon_start=1/product="LPS-Induced TNF-Alpha Factor"/protein_id="AAB36550.1"/db_xref="GI:1684872"
0 1 0 3 0 1 2 4 12 4 1 1 3 8 2 2 5 4 3 5 5 2 9 6 1 15 6 5 3 5 7 1 11 4 1 4 7 2 1 2 4 4 4 8 4 3 3 2 1 1 4 5 4 2 3 3 0 4 2 5 4 0 1 0
>AL591543#2\AL591543\join(54020..54195,54662..54953)\468\CAI17286.1\Homo sapiens\Human DNA sequence from clone RP13-198D9 on chromosome 9 Contains anovel gene (KIAA2015), a novel gene, a tyrosine3-monooxygenase/tryptophan 5-monooxygenase activation protein, betapolypeptide (YWHAB) pseudogene and two CpG islands, completesequence./locus_tag="RP13-198D9.2-003"/standard_name="OTTHUMP00000021401"/codon_start=1/protein_id="CAI17286.1"/db_xref="GI:55961130"/db_xref="UniProt/TrEMBL:Q5SY85"
0 5 7 1 2 3 2 5 11 0 0 2 1 3 0 1 3 0 3 2 0 0 1 2 6 4 6 6 5 2 5 11 5 2 0 1 2 1 0 0 0 0 1 10 6 1 5 2 5 1 0 0 6 1 0 0 0 0 1 1 5 1 0 0
>AL138690\AL138690\join(157463..157756,AL161902.12:69081..69312, AL161902.12:73095..73195,AL161902.12:73454..73549, AL161902.12:76711..76832,AL161902.12:78417..78543, AL161902.12:84158..84277,AL161902.12:86865..87011, AL161902.12:98056..98253,AL161902.12:98867..99000, AL356430.19:21907..22015,AL356430.19:32900..33052, AL356430.19:34420..34588,AL356430.19:41024..41103, AL356430.19:41838..41900,AL356430.19:41987..42084, AL356430.19:47092..47184,AL356430.19:65879..65987, AL356430.19:79384..79465,AL356430.19:79693..79816, AL356430.19:80688..80880,AL356430.19:82626..83642, AL356430.19:85360..85577,AL356430.19:87966..88119, AL356430.19:94882..95062,AL356430.19:97074..97204, AL356430.19:100606..100713,AL356430.19:105970..106138, AL356430.19:107586..107681,AL356430.19:119474..119912, AL356430.19:132310..132464,AL356430.19:134663..134789, AL356430.19:156102..156229,AL357083.19:45114..45175, AL357083.19:64253..64317,AL357083.19:103833..103941, AL357083.19:106882..107048,AL161718.14:52938..53062, AL390071.9:14325..14468,AL390071.9:34633..34769, AL390071.9:112710..112827,AL390071.9:113163..113265, AL390071.9:117220..117335,AL390071.9:129138..129250, AL390071.9:146131..146271,AL390071.9:155561..155680, AL390071.9:168659..168811,AL139083.15:19322..19489, AL139083.15:37500..37589,AL139083.15:40896..41088, AL139083.15:43046..43117,AL139083.15:46096..46251, AL139083.15:46820..46990,AL139083.15:56326..56427, AL139083.15:58615..58811,AL139083.15:59609..59760, AL139083.15:62142..62232)\-12986205\CAH72296.1\Homo sapiens\Human DNA sequence from clone RP11-307O13 on chromosome13q12.3-14.2 Contains the 5' end of the NBEA gene for neurobeachin(BCL8B FLJ10197 KIAA1544) and a CpG island, complete sequence./gene="NBEA"/locus_tag="RP11-270C18.1-001"/standard_name="OTTHUMP00000018239"/codon_start=1/product="neurobeachin"/protein_id="CAH72296.1"/db_xref="GI:55662138"/db_xref="InterPro:IPR000409"/db_xref="InterPro:IPR001680"/db_xref="InterPro:IPR010508"/db_xref="UniProt/TrEMBL:Q5W0E7"
7 6 9 1 72 57 32 49 53 51 72 50 59 52 13 80 37 36 74 35 7 43 52 38 12 40 35 39 6 41 47 35 35 29 33 27 46 37 123 80 53 74 52 54 46 52 63 65 34 41 24 55 46 53 59 91 57 51 68 53 47 61 37 58
>AF536216\AF536216\364..2196\1833\AAP46193.1\Homo sapiens\Homo sapiens sodium solute symporter family 5 member 8 protein(SLC5A8) mRNA, complete cds./gene="SLC5A8"/codon_start=1/product="sodium solute symporter family 5 member 8 protein"/protein_id="AAP46193.1"/db_xref="GI:31249543"
1 1 1 3 9 3 4 11 19 11 11 14 9 10 2 7 13 6 18 14 2 11 9 4 1 10 12 16 6 12 24 14 9 9 5 11 26 13 11 6 9 13 12 10 3 3 6 6 8 13 16 14 3 8 19 19 6 14 23 16 11 0 0 1
>HSU13665\U13665\106..1095\990\AAA65233.1\Homo sapiens\Human cathepsin O (CTSO) mRNA, complete cds./gene="CTSO"/codon_start=1/product="cathepsin O"/protein_id="AAA65233.1"/db_xref="GI:606923"
3 1 2 1 3 2 3 5 14 3 2 1 0 4 0 8 8 4 2 6 0 3 4 4 0 4 4 10 1 6 11 6 5 7 1 4 14 4 11 17 16 9 3 8 4 4 10 11 6 7 6 12 2 6 3 3 2 6 6 8 9 0 0 1
>AL157935#4\AL157935\complement(join(41341..41409,41654..41845,45156..45272, 46023..46186,46359..46394,46727..46781))\633\CAI12607.1\Homo sapiens\Human DNA sequence from clone RP11-203J24 on chromosome 9 Containsthe 5' end of the ENG gene for endoglin (Osler-Rendu-Weber syndrome1) (END, ORW, HHT1, ORW1, CD105), the AK1 gene for adenylate kinase1, the ST6GALNAC6 gene for CMP-NeuAC:(beta)-N-acetylgalactosaminide(alpha)2,6-sialyltransferase member VI (ST6GALNACVI), the SIAT7Dgene for sialyltransferase 7D((alpha-N-acetylneuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase) (SIAT3C, ST6GALNAC4,ST6GALNACIV), the DPM2 gene for dolichyl-phosphatemannosyltransferase polypeptide 2, regulatory subunit (MGC21559),the gene for a novel protien containing FLJ00179, a novel gene andten CpG islands, complete sequence./gene="AK1"/locus_tag="RP11-203J24.1-009"/standard_name="OTTHUMP00000022219"/codon_start=1/product="adenylate kinase 1"/protein_id="CAI12607.1"/db_xref="GI:55958256"/db_xref="GOA:Q5T9B7"/db_xref="InterPro:IPR000850"/db_xref="InterPro:IPR006267"/db_xref="InterPro:IPR011769"/db_xref="UniProt/TrEMBL:Q5T9B7"
1 2 6 3 3 1 1 4 12 0 0 2 2 6 3 0 2 2 3 10 0 1 1 2 1 3 1 7 0 1 3 11 5 1 0 6 10 1 6 13 1 2 1 7 2 0 4 15 9 3 3 4 3 1 3 2 0 6 3 5 0 0 1 0
>BC027463\BC027463\38..673\636\AAH27463.1\Homo sapiens\Homo sapiens ribosomal protein L13, transcript variant 1, mRNA(cDNA clone MGC:34920 IMAGE:5111302), complete cds./gene="RPL13"/codon_start=1/product="ribosomal protein L13"/protein_id="AAH27463.1"/db_xref="GI:20071962"/db_xref="GeneID:6137"/db_xref="MIM:113703"
1 9 12 3 2 4 0 5 6 0 0 1 0 3 2 2 2 2 0 3 4 1 0 10 4 0 2 16 3 4 2 6 0 1 0 5 7 2 7 18 5 2 1 6 4 0 6 7 2 2 2 1 1 0 7 0 1 7 2 4 2 1 0 0
>HSU07151\U07151\16..564\549\AAA21654.1\Homo sapiens\Human GTP binding protein (ARL3) mRNA, complete cds./gene="ARL3"/function="GTP binding protein"/standard_name="ARF-like 3"/codon_start=1/evidence=experimental/product="ARL3"/protein_id="AAA21654.1"/db_xref="GI:460625"
1 2 0 0 4 1 2 5 6 4 1 5 3 0 0 3 1 4 4 3 1 1 3 0 0 2 6 2 1 3 3 5 0 4 3 3 3 1 8 7 3 7 2 9 1 1 9 4 6 4 1 2 2 1 1 4 2 8 4 2 4 1 0 0
>AL365181#10\AL365181\join(134628..134712,134944..135297,135488..135604, 135738..135920,136238..136521)\1023\CAI13055.1\Homo sapiens\Human DNA sequence from clone RP11-284F21 on chromosome 1 Containsthe 5' end of the MEF2D gene for MADS box transcription enhancerfactor 2 polypeptide D (myocyte enhancer factor 2D), the IQGAP3gene for IQ motif containing GTPase activating protein 3, a novelgene, the APOA1BP gene for apolipoprotein A-I binding protein, anovel gene (FLJ20249), a novel gene, the gene for brain linkprotein-1 (BRAL1), a novel gene, the 5' end of the BCAN gene forbrevican, the 3' end of a novel gene and three CpG islands,complete sequence./gene="HAPLN2"/locus_tag="RP11-284F21.6-001"/standard_name="OTTHUMP00000031987"/codon_start=1/product="hyaluronan and proteoglycan link protein 2"/protein_id="CAI13055.1"/db_xref="GI:55959666"/db_xref="InterPro:IPR000538"/db_xref="InterPro:IPR003599"/db_xref="InterPro:IPR007110"
3 16 10 1 0 4 2 12 16 2 0 2 0 5 1 2 6 2 1 11 6 0 3 14 6 3 3 17 9 2 6 18 13 2 0 3 14 1 1 5 3 2 4 7 8 2 2 15 12 1 15 2 10 1 11 2 0 9 1 3 8 0 1 0
>HUMCATS\M90696 S39127\137..1132\996\AAC37592.1\Homo sapiens\Homo sapiens cathepsin S (CTSS) mRNA, complete cds./gene="CTSS"/codon_start=1/product="cathepsin S"/protein_id="AAC37592.1"/db_xref="GI:179957"
1 0 3 3 6 0 1 5 13 5 0 4 7 4 0 8 3 5 4 3 1 4 3 3 0 5 5 5 1 8 6 9 4 8 3 2 15 5 17 10 8 11 3 7 6 6 17 2 5 10 9 11 4 7 5 3 1 5 3 11 8 0 1 0
>D63705\D63705\84..719\636\BAA23620.1\Homo sapiens\Homo sapiens mRNA for TFIID subunit p30beta, complete cds./codon_start=1/product="TFIID subunit p30beta"/protein_id="BAA23620.1"/db_xref="GI:2645175"
0 2 0 1 1 4 1 1 5 1 3 1 5 3 3 6 0 1 3 4 1 2 3 3 1 3 5 5 1 5 5 2 4 2 2 2 5 6 14 8 2 2 2 7 2 1 12 14 8 10 0 2 0 1 4 1 1 9 2 6 1 0 1 0
>HOSA18281\Y18281\22..579\558\CAB50728.1\Homo sapiens\Homo sapiens mRNA for mannose binding lectin-associated serineprotease-2, alternatively spliced transcript (clone phl-5)./gene="MASP-2"/codon_start=1/product="mannose binding lectin-associated serine protease-2 related protein, MAp19 (19kDa)"/protein_id="CAB50728.1"/db_xref="GI:5459315"/db_xref="GOA:O00187"/db_xref="UniProt/Swiss-Prot:O00187"
0 7 2 1 0 1 0 5 15 1 1 0 1 6 3 0 4 0 1 7 3 2 1 5 3 3 4 8 1 0 1 9 5 1 0 2 4 0 0 6 3 1 0 4 7 0 1 12 10 0 7 2 8 1 10 1 0 0 2 1 2 0 1 0
>AL136373#7\AL136373\join(complement(AL593856.8:21752..22017), complement(AL593856.8:18951..19059), complement(AL593856.8:12382..12432), complement(AL593856.8:11822..11884), complement(AL593856.8:7512..7562), complement(AL593856.8:6276..6323), complement(117968..118063),complement(116001..116108), complement(108583..108777))\-59376\CAI14761.1\Homo sapiens\Human DNA sequence from clone RP11-49P4 on chromosome 1p32.2-33Contains two novel genes (FLJ40412, FLJ32011), the MKNK1 gene forMAP kinase-interacting serine/threonine kinase 1, the gene forMOB3C protein (MOB3C) and the 3' end of the ATPAF1 gene for ATPsynthase mitochondrial F1 complex assembly factor 1, completesequence./gene="ATPAF1"/locus_tag="RP11-49P4.5-002"/standard_name="OTTHUMP00000009681"/codon_start=1/product="ATP synthase mitochondrial F1 complex assembly factor 1"/protein_id="CAI14761.1"/db_xref="GI:55957743"/db_xref="GOA:Q5SXB7"/db_xref="InterPro:IPR010591"/db_xref="UniProt/TrEMBL:Q5SXB7"
4 2 1 0 8 3 4 11 10 4 4 3 2 5 2 6 4 2 4 6 3 8 7 6 3 3 8 10 0 11 6 7 6 6 4 2 4 5 6 6 6 8 6 9 8 3 11 11 4 2 2 4 5 4 7 16 2 5 5 5 4 1 2 3
>HS330O12#4\AL031731\join(29996..30260,32427..32553,32693..32788,32896..33031, 35290..35433)\768\CAI20211.1\Homo sapiens\Human DNA sequence from clone RP3-330O12 on chromosome1p36.11-36.23 Contains the FBXO2 gene for F-box only protein 2, thegene for F-box protein FBX30, the FBXO6 gene for F-box only protein6, the MAD2L2 gene for MAD2 mitotic arrest deficient-like 2(yeast), the 5' end of a novel gene and three CpG islands, completesequence./gene="FBXO44"/locus_tag="RP3-330O12.5-001"/standard_name="OTTHUMP00000002063"/codon_start=1/product="F-box protein 44"/protein_id="CAI20211.1"/db_xref="GI:56203289"/db_xref="GOA:Q9H4M3"/db_xref="InterPro:IPR001810"/db_xref="InterPro:IPR007397"/db_xref="UniProt/Swiss-Prot:Q9H4M3"
2 4 3 0 0 5 0 9 17 0 1 0 1 5 1 1 6 0 2 7 1 3 2 7 6 1 1 6 3 2 1 7 6 0 0 6 9 2 2 11 8 2 0 11 6 1 3 13 12 6 8 2 7 0 11 1 0 10 0 2 12 0 0 1
>HSA306634\AJ306634\join(217..289,420..689,931..1206,1786..1826)\660\CAC36395.1\Homo sapiens\Homo sapiens HLA-A gene for MHC class I antigen, A*23N allele,exons 1-7./gene="HLA-A"/function="MHC class I antigen"/codon_start=1/product="HLA-A protein"/protein_id="CAC36395.1"/db_xref="GI:13620230"/db_xref="GOA:Q9BCN1"/db_xref="InterPro:IPR001039"/db_xref="UniProt/TrEMBL:Q9BCN1"
2 9 4 1 2 2 1 7 9 0 0 1 1 5 2 2 3 0 3 6 4 1 2 6 3 0 1 11 9 1 0 6 9 1 0 2 8 0 2 4 3 0 1 12 4 1 0 15 15 1 9 3 2 0 5 1 1 4 0 7 5 0 0 1
>HS333A15#4\AL031429\join(complement(123019..123915),complement(88643..88822), complement(30101..30127), complement(AL158087.12:96271..96346), complement(AL158087.12:89396..89424))\897\CAI20231.1\Homo sapiens\Human DNA sequence from clone RP3-333A15 on chromosome 1p31.1-31.3Contains the 5' end of the PTGER3 gene for prostaglandin E receptor3 (subtype EP3), part of a novel gene and a CpG island, completesequence./gene="PTGER3"/locus_tag="RP5-952N6.2-007"/standard_name="OTTHUMP00000011029"/codon_start=1/product="prostaglandin E receptor 3 (subtype EP3)"/protein_id="CAI20231.1"/db_xref="GI:56417800"/db_xref="GOA:O00325"/db_xref="InterPro:IPR000265"/db_xref="InterPro:IPR000276"/db_xref="InterPro:IPR001244"/db_xref="InterPro:IPR001481"/db_xref="InterPro:IPR008365"/db_xref="UniProt/TrEMBL:O00325"
2 10 8 3 7 1 0 15 25 5 4 4 2 9 6 5 6 1 5 14 7 3 3 3 6 3 2 21 7 3 2 12 13 1 3 9 12 5 5 12 11 1 1 12 6 4 3 12 2 3 6 1 12 0 15 5 2 12 3 15 12 1 0 0
>AB012723\AB012723\join(10753..10844,11940..12014,15049..15198,19720..19896, 21232..21383,23136..23318,23728..23882,25740..25910)\1155\BAA36418.1\Homo sapiens\Homo sapiens gene for kinesin-like protein, complete cds./codon_start=1/product="kinesin-like protein"/protein_id="BAA36418.1"/db_xref="GI:4115553"
4 3 3 3 3 13 3 13 17 5 2 7 2 5 4 9 14 2 5 8 4 3 5 6 4 5 9 16 9 7 12 9 10 5 0 7 13 10 2 11 2 4 5 16 6 4 3 15 13 7 3 3 7 1 3 2 2 3 7 5 1 0 0 1
>AF069291#1\AF069291\join(68735..68801,73157..73293,73635..73826,80160..80251, 83583..84612)\1518\AAC62231.1\Homo sapiens\Homo sapiens BAC clone 255A7 from 8q21 containing NBS1 gene,complete sequence./gene="hT41"/codon_start=1/product="hT41"/protein_id="AAC62231.1"/db_xref="GI:3687829"
6 3 0 2 10 2 3 3 10 14 14 9 14 6 2 12 6 4 8 2 1 8 10 4 1 12 8 3 2 11 14 6 8 11 13 2 9 13 17 16 5 13 5 8 3 17 19 9 8 21 7 15 2 7 4 19 13 6 9 11 5 1 0 0
>HSDJ319M7#1\AL079341\join(60503..60687,64270..64633,65757..66021,78160..78379, 80878..80997,complement(AL031905.7:20931..21040), complement(AL355345.13:18948..19137), AL033518.14:12909..13016,AL033518.14:76828..76906, AL033518.14:94243..94440)\-2028\CAI20151.1\Homo sapiens\Human DNA sequence from clone RP1-319M7 on chromosome 6p21.1-21.3Contains the 5' end of the gene for a novel protein (containsKIAA1880 and FLJ32945), a TRK-fused gene (TFG) pseudogene and a CpGisland, complete sequence./locus_tag="RP3-322I12.1-004"/standard_name="OTTHUMP00000016337"/codon_start=1/protein_id="CAI20151.1"/db_xref="GI:56203781"/db_xref="InterPro:IPR000210"/db_xref="InterPro:IPR000421"/db_xref="InterPro:IPR008979"
2 1 1 2 11 11 3 16 14 13 6 6 4 10 6 10 7 8 7 6 7 13 10 14 4 9 9 4 1 8 5 11 10 4 6 9 7 9 16 12 9 17 8 15 13 19 8 14 10 7 6 10 12 13 21 14 14 22 15 11 9 15 7 12
>BC066294\BC066294\14..598\585\AAH66294.1\Homo sapiens\Homo sapiens lysozyme-like 2, mRNA (cDNA clone MGC:86984IMAGE:4374284), complete cds./gene="LYZL2"/codon_start=1/product="LYZL2 protein"/protein_id="AAH66294.1"/db_xref="GI:42542634"/db_xref="GeneID:119180"
0 1 1 1 2 3 0 3 10 1 0 2 4 4 1 2 6 1 4 3 1 4 0 1 1 1 3 6 5 4 3 10 1 0 0 4 0 3 8 7 5 3 2 5 3 0 0 7 9 3 4 3 7 4 5 1 1 6 4 4 7 1 0 0
>BC009073\BC009073\330..1208\879\AAH09073.1\Homo sapiens\Homo sapiens chromosome 14 open reading frame 152, mRNA (cDNA cloneMGC:9764 IMAGE:3856004), complete cds./gene="C14orf152"/codon_start=1/product="C14orf152 protein"/protein_id="AAH09073.1"/db_xref="GI:14290588"/db_xref="GeneID:90050"
0 5 3 0 2 12 0 7 21 3 0 3 0 10 0 2 5 3 0 3 0 1 7 21 3 8 4 6 2 6 4 13 9 2 0 4 13 0 4 18 3 3 0 13 2 4 4 13 5 5 6 3 7 1 5 2 0 4 0 5 3 0 1 0
>AE006463#8\AE006463 AE005175\119356..119826\471\AAK61228.1\Homo sapiens\Homo sapiens 16p13.3 sequence section 2 of 8./gene="RPL23AL"/codon_start=1/product="60S ribosomal protein L23A like"/protein_id="AAK61228.1"/db_xref="GI:14336695"/db_xref="MIM:602326"/db_xref="UniProt/Swiss-Prot:P29316"
2 2 3 0 1 3 0 2 5 2 1 3 1 0 1 1 2 0 2 6 3 1 0 2 2 6 3 8 4 5 1 1 1 2 0 3 4 3 7 18 5 0 0 3 4 0 6 3 1 6 1 3 0 1 2 1 1 4 2 1 1 1 0 0
>BC004372\BC004372\132..2231\2100\AAH04372.1\Homo sapiens\Homo sapiens CD44 antigen (homing function and Indian blood groupsystem), transcript variant 2, mRNA (cDNA clone MGC:10468IMAGE:3638681), complete cds./gene="CD44"/codon_start=1/product="CD44 antigen, isoform 2 precursor"/protein_id="AAH04372.1"/db_xref="GI:13325118"/db_xref="GeneID:960"/db_xref="MIM:107269"
2 4 3 2 12 11 2 8 8 4 2 10 19 14 2 14 19 15 34 23 7 18 20 12 2 9 15 7 1 15 22 9 10 9 3 5 15 5 6 11 20 20 6 19 12 20 33 14 25 20 7 7 6 3 9 12 4 19 10 12 12 1 0 0
>AY486331\AY486331\10..558\549\AAS57906.1\Homo sapiens\Homo sapiens BCL10-associated protein variant 1 (BAG) mRNA,complete cds, alternatively spliced./gene="BAG"/codon_start=1/product="BCL10-associated protein variant 1"/protein_id="AAS57906.1"/db_xref="GI:45331268"
0 3 1 0 1 4 1 3 2 2 0 1 3 1 2 2 5 1 0 3 2 3 7 0 7 8 4 1 6 3 2 3 2 1 2 2 1 0 8 14 4 4 0 2 1 1 5 20 6 7 3 3 0 1 1 3 4 1 0 2 3 0 1 0
>AK075017\AK075017\169..948\780\BAC11355.1\Homo sapiens\Homo sapiens cDNA FLJ90536 fis, clone OVARC1000105, highly similarto Ubiquitin conjugating enzyme E2./codon_start=1/protein_id="BAC11355.1"/db_xref="GI:22760840"
1 1 1 0 3 5 1 10 10 2 2 3 0 2 2 2 5 5 0 7 7 3 4 7 5 6 6 6 3 2 2 5 8 2 0 8 7 2 9 6 9 2 3 10 5 2 5 9 7 2 4 5 1 3 3 9 2 6 5 4 3 0 0 1
>BC023981\BC023981\131..1195\1065\AAH23981.1\Homo sapiens\Homo sapiens carbonic anhydrase XII, transcript variant 1, mRNA(cDNA clone MGC:22865 IMAGE:4042589), complete cds./gene="CA12"/codon_start=1/product="carbonic anhydrase XII, isoform 1 precursor"/protein_id="AAH23981.1"/db_xref="GI:18645129"/db_xref="GeneID:771"/db_xref="MIM:603263"
1 3 3 0 2 3 0 10 24 5 1 1 4 12 2 3 7 5 4 6 2 5 2 8 7 5 2 13 3 6 4 11 4 3 2 7 11 2 3 14 13 5 5 13 12 3 6 12 10 3 9 6 2 3 11 2 1 9 8 6 5 0 0 1
>BC098269\BC098269\49..1875\1827\AAH98269.1\Homo sapiens\Homo sapiens RAP1, GTP-GDP dissociation stimulator 1, mRNA (cDNAclone MGC:118860 IMAGE:40001059), complete cds./gene="RAP1GDS1"/codon_start=1/product="RAP1, GTP-GDP dissociation stimulator 1"/protein_id="AAH98269.1"/db_xref="GI:67514265"/db_xref="GeneID:5910"/db_xref="MIM:179502"
2 1 0 1 10 3 14 8 19 21 16 13 8 4 1 6 4 19 9 4 2 8 6 1 0 4 26 12 0 23 13 7 3 8 17 4 10 15 28 13 8 22 12 21 4 11 31 17 7 25 1 2 4 10 2 11 12 7 17 19 2 0 0 1
>BC010087\BC010087\14..1852\1839\AAH10087.1\Homo sapiens\Homo sapiens phosphoglucomutase 2, mRNA (cDNA clone MGC:19508IMAGE:2964390), complete cds./gene="PGM2"/codon_start=1/product="phosphoglucomutase 2"/protein_id="AAH10087.1"/db_xref="GI:14603253"/db_xref="GeneID:55276"/db_xref="MIM:172000"
6 3 2 1 6 5 7 6 10 9 8 12 3 7 0 12 11 14 10 13 2 9 10 5 5 12 10 15 1 28 10 10 11 8 1 7 14 6 28 20 7 18 8 18 5 8 24 16 19 18 11 8 4 5 7 27 5 12 15 10 10 1 0 0
>BC000954\BC000954\112..663\552\AAH00954.1\Homo sapiens\Homo sapiens chromobox homolog 3 (HP1 gamma homolog, Drosophila),transcript variant 1, mRNA (cDNA clone MGC:4912 IMAGE:3450099),complete cds./gene="CBX3"/codon_start=1/product="chromobox homolog 3"/protein_id="AAH00954.1"/db_xref="GI:12654267"/db_xref="GeneID:11335"/db_xref="MIM:604477"
1 0 0 1 6 0 2 1 2 2 2 4 2 1 0 5 2 3 4 0 0 3 3 0 0 4 3 3 2 6 5 1 1 3 3 1 4 1 19 6 2 5 3 2 0 1 17 5 6 10 0 2 0 3 1 6 1 0 4 5 4 1 0 0
>AY651137\AY651137\534..1526\993\AAW70050.1\Homo sapiens\Homo sapiens clone KHC33 MRGX2 (MRGX2) gene, complete cds./gene="MRGX2"/codon_start=1/product="MRGX2"/protein_id="AAW70050.1"/db_xref="GI:58294240"/IGNORED_CODON=3
0 6 1 1 2 6 2 14 33 6 4 1 3 6 1 4 8 7 5 10 0 2 3 4 4 1 2 10 2 3 4 9 5 3 1 11 10 3 0 5 4 3 1 9 2 2 3 4 4 6 5 1 6 9 21 7 2 12 7 6 11 0 1 0
>AY359040\AY359040\161..457\297\AAQ89399.1\Homo sapiens\Homo sapiens clone DNA52758 SCRG1 (UNQ390) mRNA, complete cds./locus_tag="UNQ390"/codon_start=1/product="SCRG1"/protein_id="AAQ89399.1"/db_xref="GI:37183198"
0 1 0 0 1 0 3 2 3 2 0 2 0 0 0 2 1 0 1 1 0 1 2 0 1 2 1 1 0 1 4 0 2 0 2 2 1 3 3 3 4 3 2 2 2 1 2 1 2 4 2 0 5 3 5 1 1 2 3 4 1 0 0 1
>AY663423#2\AY663423\join(48096..48116,48596..49585)\1011\AAU47296.1\Homo sapiens\Homo sapiens isolate fa0141 immunoglobulin superfamily member 4B(IGSF4B) gene, complete cds; and Duffy blood group (FY) genes,complete cds, alternatively spliced./gene="FY"/codon_start=1/product="Duffy blood group"/protein_id="AAU47296.1"/db_xref="GI:52426524"
0 3 0 0 2 2 6 13 36 3 0 12 4 7 0 7 8 4 3 7 2 5 5 8 0 6 7 19 1 9 8 8 7 8 2 8 9 1 1 5 5 3 0 9 6 3 4 3 5 6 2 3 5 7 11 4 1 4 4 4 11 0 1 0
>HSU70439\U70439\211..966\756\AAB37579.1\Homo sapiens\Human silver-stainable protein SSP29 mRNA, complete cds./codon_start=1/product="silver-stainable protein SSP29"/protein_id="AAB37579.1"/db_xref="GI:1698783"
3 0 1 0 2 4 1 6 9 5 6 6 4 0 0 0 2 5 3 4 0 0 1 2 1 3 2 1 0 3 6 3 2 5 2 3 3 3 10 7 5 8 0 2 1 1 34 22 13 25 2 1 1 2 2 5 1 4 1 3 0 1 0 0
>HSU66867\U66867\807..1283\477\AAC50716.1\Homo sapiens\Human ubiquitin conjugating enzyme 9 (hUBC9) mRNA, complete cds./gene="hUBC9"/codon_start=1/product="ubiquitin conjugating enzyme 9"/protein_id="AAC50716.1"/db_xref="GI:1561759"
1 0 1 0 2 4 3 3 1 2 3 1 1 1 3 1 1 0 3 0 2 1 11 2 2 1 3 6 1 2 3 2 3 1 0 2 4 0 10 4 3 4 4 3 2 0 4 7 4 3 4 1 3 1 3 4 1 6 2 4 4 1 0 0
>HSIL15MR1\X94222\223..630\408\CAA63913.1\Homo sapiens\H.sapiens mRNA for interleukin-15 (cell line NCIH69)./codon_start=1/product="interleukin-15 (IL-15)"/protein_id="CAA63913.1"/db_xref="GI:1495460"/db_xref="GOA:P40933"/db_xref="UniProt/Swiss-Prot:P40933"
0 0 0 0 0 0 1 1 2 3 2 6 1 1 0 5 1 7 4 1 1 2 0 1 0 1 4 1 0 1 3 0 2 0 6 1 1 2 7 1 4 5 3 1 1 3 9 4 0 7 0 1 4 2 2 3 2 3 7 4 1 0 0 1
>BC054049\BC054049\83..997\915\AAH54049.1\Homo sapiens\Homo sapiens zinc finger protein 364, mRNA (cDNA clone MGC:65162IMAGE:6157275), complete cds./gene="ZNF364"/codon_start=1/product="Rabring 7"/protein_id="AAH54049.1"/db_xref="GI:32450454"/db_xref="GeneID:27246"
2 0 6 1 8 2 5 0 4 4 5 3 1 3 2 8 9 7 11 2 1 6 8 4 2 8 5 9 3 4 6 7 4 7 5 2 3 2 2 4 3 7 6 7 10 4 13 7 11 8 2 2 4 6 5 14 3 2 5 4 6 0 0 1
>AY297044\AY297044\219..3341\3123\AAP44473.1\Homo sapiens\Homo sapiens transient receptor potential cation channel subfamilyM member 4 splice variant A (TRPM4) mRNA, complete cds;alternatively spliced./gene="TRPM4"/codon_start=1/product="transient receptor potential cation channel subfamily M member 4 splice variant A"/protein_id="AAP44473.1"/db_xref="GI:31335331"
4 32 22 8 1 14 5 49 76 9 0 14 6 17 12 7 22 7 6 15 10 6 10 22 16 13 10 49 15 15 8 36 38 8 3 19 35 6 10 22 17 4 5 35 13 5 12 45 38 12 19 6 19 4 41 10 2 22 8 24 22 0 0 1
>BC018272\BC018272\82..906\825\AAH18272.1\Homo sapiens\Homo sapiens toll interacting protein, mRNA (cDNA clone MGC:16867IMAGE:3452585), complete cds./gene="TOLLIP"/codon_start=1/product="toll interacting protein"/protein_id="AAH18272.1"/db_xref="GI:17390641"/db_xref="GeneID:54472"/db_xref="MIM:606277"
3 8 1 0 1 2 0 4 14 1 0 1 0 5 0 1 5 0 3 6 5 1 5 14 4 0 3 15 4 2 1 12 6 1 1 6 17 1 1 8 6 4 0 22 3 0 1 12 12 2 9 2 2 2 5 0 0 12 1 14 3 0 1 0
>AY174122\AY174122\128..313\186\AAN73231.1\Homo sapiens\Homo sapiens chemokine-like factor super family 1 isoform 5(CKLFSF1) mRNA, complete cds; alternatively spliced./gene="CKLFSF1"/codon_start=1/product="chemokine-like factor super family 1 isoform 5"/protein_id="AAN73231.1"/db_xref="GI:25361699"
0 0 1 0 1 1 0 1 1 2 1 2 3 1 0 0 0 1 1 1 0 1 0 0 1 3 2 5 0 1 0 0 3 0 1 1 1 1 3 1 2 0 2 0 1 1 2 3 0 2 0 1 0 0 1 0 0 2 1 2 0 1 0 0
>BC046149\BC046149\60..791\732\AAH46149.1\Homo sapiens\Homo sapiens nitrilase 1, mRNA (cDNA clone MGC:57670IMAGE:5764281), complete cds./gene="NIT1"/codon_start=1/product="NIT1 protein"/protein_id="AAH46149.1"/db_xref="GI:28279801"/db_xref="GeneID:4817"/db_xref="MIM:604618"
1 0 3 1 3 4 2 4 16 6 0 3 3 7 1 5 3 1 5 4 2 2 5 6 0 11 7 5 0 10 4 4 5 5 4 3 4 1 4 3 3 1 4 7 4 2 7 10 6 0 3 2 4 7 6 3 2 3 4 5 3 0 0 1
>AK125005\AK125005\76..1527\1452\BAC86022.1\Homo sapiens\Homo sapiens cDNA FLJ43015 fis, clone BRTHA2016496, moderatelysimilar to Vacuolar processing enzyme precursor (EC 3.4.22.-)./codon_start=1/protein_id="BAC86022.1"/db_xref="GI:34530959"
2 2 1 3 2 8 4 10 7 10 4 6 6 8 0 11 5 13 7 3 1 8 5 4 2 13 14 6 1 15 11 7 7 18 3 7 7 10 14 10 10 17 11 3 6 10 19 9 9 18 8 14 4 4 6 15 7 6 12 13 7 1 0 0
>AF020918\AF020918\71..739\669\AAD04711.1\Homo sapiens\Homo sapiens glutathione transferase (GSTA4) mRNA, complete cds./gene="GSTA4"/EC_number="2.5.1.18"/codon_start=1/product="glutathione transferase"/protein_id="AAD04711.1"/db_xref="GI:2738933"
1 0 1 0 6 3 2 6 10 4 5 3 0 1 0 1 4 1 4 4 0 0 2 4 0 8 5 3 0 3 3 3 2 3 1 2 8 4 4 13 5 4 5 7 5 1 12 5 3 7 6 2 0 0 4 8 2 4 10 7 1 1 0 0
>AF035360\AF035360\88..2091\2004\AAB99951.1\Homo sapiens\Homo sapiens ring finger protein (FXY) mRNA, complete cds./gene="FXY"/codon_start=1/product="ring finger protein"/protein_id="AAB99951.1"/db_xref="GI:2827994"
4 9 8 5 4 3 7 16 21 7 3 10 10 14 1 7 14 7 13 26 2 6 3 12 4 10 9 17 5 13 5 6 9 3 5 11 17 5 14 25 25 10 8 23 13 12 16 30 17 17 9 7 16 14 10 11 3 23 17 8 8 0 0 1
>AY038048\AY038048\180..3170\2991\AAK71497.1\Homo sapiens\Homo sapiens SEZ6 (SEZ6) mRNA, complete cds./gene="SEZ6"/codon_start=1/product="SEZ6"/protein_id="AAK71497.1"/db_xref="GI:20143985"
6 18 5 4 2 8 7 24 45 6 1 4 8 20 6 10 30 10 19 38 1 15 28 43 9 26 14 36 5 15 14 39 22 13 6 16 33 8 5 18 10 10 6 35 22 9 9 50 26 21 19 10 14 12 25 13 5 31 5 12 15 0 0 1
>AK057590\AK057590\42..410\369\BAB71530.1\Homo sapiens\Homo sapiens cDNA FLJ33028 fis, clone THYMU2000140./codon_start=1/protein_id="BAB71530.1"/db_xref="GI:16553340"
1 2 4 0 5 4 0 3 5 6 1 3 2 3 1 3 1 2 0 1 0 1 2 5 1 3 0 2 0 4 2 4 2 1 1 4 2 4 3 2 0 3 1 2 1 2 5 0 1 1 0 0 2 0 1 2 1 1 3 4 2 0 1 0
>HSMTMMPPR\X90925\113..1861\1749\CAA62432.1\Homo sapiens\H.sapiens mRNA for MT-MMP protein./codon_start=1/product="MT-MMP protein"/protein_id="CAA62432.1"/db_xref="GI:1495995"/db_xref="GOA:P50281"/db_xref="UniProt/Swiss-Prot:P50281"
5 10 5 6 3 9 2 14 25 2 0 1 5 7 3 4 8 2 4 12 4 6 7 28 2 9 4 24 8 7 8 26 15 4 2 7 19 3 9 23 12 9 7 12 4 8 7 31 18 13 20 5 3 3 28 9 0 17 6 15 13 0 0 1
>BC096703\BC096703\1..255\255\AAH96703.1\Homo sapiens\Homo sapiens CDC42 small effector 2, mRNA (cDNA clone MGC:120071IMAGE:40021506), complete cds./gene="CDC42SE2"/codon_start=1/product="CDC42 small effector 2"/protein_id="AAH96703.1"/db_xref="GI:68532498"/db_xref="GeneID:56990"
1 0 2 0 1 1 0 1 1 0 0 1 2 2 0 0 1 3 2 0 1 0 0 1 0 3 1 1 1 1 8 0 0 2 0 1 2 2 1 2 3 2 1 6 0 2 2 1 2 1 0 1 1 2 3 1 0 0 4 6 1 0 1 0
>AF121141\AF121141\357..6656\6300\AAD17298.1\Homo sapiens\Homo sapiens endocrine regulator mRNA, complete cds./codon_start=1/product="endocrine regulator"/protein_id="AAD17298.1"/db_xref="GI:4325209"/IGNORED_CODON=1
22 13 17 12 22 27 24 28 36 24 24 43 47 43 3 69 36 54 41 26 0 38 80 33 5 71 31 36 2 53 33 20 33 22 27 11 38 34 81 86 37 30 33 48 27 24 91 111 53 58 13 23 13 15 21 32 23 23 37 30 11 1 0 0
>BC012476\BC012476\59..1465\1407\AAH12476.2\Homo sapiens\Homo sapiens hypothetical protein LOC116236, mRNA (cDNA cloneMGC:21749 IMAGE:4537124), complete cds./gene="LOC116236"/codon_start=1/product="hypothetical protein LOC116236"/protein_id="AAH12476.2"/db_xref="GI:54035278"/db_xref="GeneID:116236"
6 16 11 4 2 7 1 19 32 7 0 7 2 11 4 2 14 2 5 6 1 4 4 13 13 6 1 25 13 3 8 21 13 2 2 8 13 2 2 4 5 1 1 8 11 2 3 27 17 4 11 1 11 4 19 3 0 11 1 1 11 0 0 1
>AL670886#17\AL670886\join(19489..19560,20525..20627,21196..21311,21754..21840)\378\CAI17798.1\Homo sapiens\Human DNA sequence from clone XXbac-88C14 on chromosome 6 containsthe 5' end of the BAT3 gene for HLA-B associated transcript 3, theAPOM gene for apolipoprotein M, the gene for chromosome 6, openreading frame 47, the BAT4 gene for HLA-B associated transcript 4,the CSNK2B gene for casein kinase 2, beta polypeptide, the LY6G5Bgene for lymphocyte antigen 6 complex, locus 5B , the gene for G5cprotein, the BAT5 gene for HLA-B associated transcript 5, theLY6G6F gene for lymphocyte antigen 6 complex, locus G6f, the LY6G6Egene for lymphocyte antigen 6 complex, locus G6E, the LY6G6C genefor lymphocyte antigen 6 complex, locus G6C, the gene forchromosome 6 open reading frame 25, the DDAH gene fordimethylarginine dimethylaminohydrolase 2, the CLIC1 gene forchloride intracellular channel 1 and seven CpG islands, completesequence./gene="CSNK2B"/locus_tag="XXbac-BCX88C14.4-004"/standard_name="OTTHUMP00000029470"/codon_start=1/product="casein kinase 2, beta polypeptide"/protein_id="CAI17798.1"/db_xref="GI:55961591"/db_xref="GOA:Q5SRQ6"/db_xref="InterPro:IPR000704"/db_xref="UniProt/TrEMBL:Q5SRQ6"
1 1 0 3 0 0 1 2 3 4 0 3 1 2 0 0 2 1 0 1 0 1 1 2 0 3 1 3 0 1 3 2 1 2 0 1 3 0 1 1 4 3 2 7 2 0 7 8 7 2 5 2 0 5 3 2 0 5 3 5 2 0 0 1
>AK000710\AK000710\377..970\594\BAA91335.1\Homo sapiens\Homo sapiens cDNA FLJ20703 fis, clone KAIA1965./codon_start=1/protein_id="BAA91335.1"/db_xref="GI:7020969"
1 6 5 0 0 3 0 3 12 2 0 1 1 2 1 3 6 1 2 6 2 4 1 2 5 1 2 6 3 4 2 2 4 0 0 2 2 0 2 7 4 0 1 9 2 1 1 29 9 6 1 3 2 1 3 1 1 3 2 10 2 0 0 1
>AF126426\AF126426\265..1299\1035\AAF37591.1\Homo sapiens\Homo sapiens neurotrimin (HNT) mRNA, complete cds./gene="HNT"/codon_start=1/product="neurotrimin"/protein_id="AAF37591.1"/db_xref="GI:7158998"
0 3 5 0 5 5 2 9 13 4 0 2 6 3 2 6 9 2 4 11 4 4 5 9 0 5 4 10 2 2 4 7 9 4 5 13 20 2 8 9 12 6 3 8 5 1 11 7 10 5 8 4 8 2 7 3 1 8 9 3 6 0 0 1
>AY044836\AY044836\6..1583\1578\AAK98782.1\Homo sapiens\Homo sapiens vesicular inhibitory amino acid transporter mRNA,complete cds./codon_start=1/product="vesicular inhibitory amino acid transporter"/protein_id="AAK98782.1"/db_xref="GI:17975777"
3 11 2 0 0 1 2 21 35 1 0 4 0 15 5 1 11 2 0 7 12 1 2 10 5 4 2 33 13 3 4 32 6 3 1 14 28 1 2 20 13 3 1 13 10 2 5 21 16 2 13 3 15 2 26 7 2 28 3 13 10 0 1 0
>BC034952\BC034952\184..2733\2550\AAH34952.1\Homo sapiens\Homo sapiens diaphanous homolog 3 (Drosophila), mRNA (cDNA cloneMGC:26208 IMAGE:4830888), complete cds./gene="DIAPH3"/codon_start=1/product="diaphanous homolog 3"/protein_id="AAH34952.1"/db_xref="GI:54114914"/db_xref="GeneID:81624"
3 3 8 3 21 7 8 8 17 26 20 23 7 6 2 15 11 10 13 5 2 8 19 6 4 27 13 8 1 14 14 4 4 7 11 5 18 11 47 31 13 24 20 21 6 9 58 33 12 33 7 10 5 12 13 28 13 13 20 26 3 1 0 0
>BC011350\BC011350\54..1979\1926\AAH11350.1\Homo sapiens\Homo sapiens chromosome 14 open reading frame 169, mRNA (cDNA cloneMGC:16815 IMAGE:4340013), complete cds./gene="C14orf169"/codon_start=1/product="chromosome 14 open reading frame 169"/protein_id="AAH11350.1"/db_xref="GI:15030188"/db_xref="GeneID:79697"
10 19 14 3 2 10 5 11 43 5 2 15 1 13 11 6 6 5 5 12 8 4 7 21 13 10 9 29 19 14 7 8 17 8 3 8 27 6 2 8 11 3 4 28 11 5 15 28 19 15 14 5 4 2 11 9 4 4 3 12 8 0 1 0
>BC022481\BC022481\199..1347\1149\AAH22481.1\Homo sapiens\Homo sapiens neurogenic differentiation 2, mRNA (cDNA cloneMGC:26304 IMAGE:4816285), complete cds./gene="NEUROD2"/codon_start=1/product="neurogenic differentiation 2"/protein_id="AAH22481.1"/db_xref="GI:18490286"/db_xref="GeneID:4761"/db_xref="MIM:601725"
0 13 9 1 0 1 3 11 19 3 0 3 1 7 11 3 7 0 0 5 7 1 6 13 11 2 4 14 17 2 3 30 8 4 0 4 7 0 1 20 10 4 1 8 13 1 6 29 15 1 13 2 5 2 7 2 0 3 0 7 2 0 0 1
>AK126907\AK126907\1195..1809\615\BAC86746.1\Homo sapiens\Homo sapiens cDNA FLJ44959 fis, clone BRAWH2012054./codon_start=1/protein_id="BAC86746.1"/db_xref="GI:34533585"
0 3 2 1 2 1 3 6 8 7 2 6 5 11 2 11 2 1 0 4 0 3 4 9 0 6 2 3 0 2 1 2 0 0 1 1 5 1 2 0 5 4 4 9 5 5 2 5 2 1 0 1 1 7 11 6 1 6 3 5 2 0 0 1
>BC032549\BC032549\83..853\771\AAH32549.1\Homo sapiens\Homo sapiens POU domain, class 2, associating factor 1, mRNA (cDNAclone MGC:45211 IMAGE:5554134), complete cds./gene="POU2AF1"/codon_start=1/product="POU2AF1 protein"/protein_id="AAH32549.1"/db_xref="GI:21619723"/db_xref="GeneID:5450"/db_xref="MIM:601206"
1 0 1 1 3 2 2 6 11 4 0 3 2 6 1 5 6 1 6 11 4 1 9 18 7 7 6 15 3 4 0 5 4 2 0 5 15 0 1 4 1 1 2 12 3 2 6 10 6 1 6 5 3 1 1 2 0 4 0 4 4 0 1 0
>AF044333\AF044333\1..1545\1545\AAD09407.1\Homo sapiens\Homo sapiens pleiotropic regulator 1 (PLRG1) mRNA, complete cds./gene="PLRG1"/codon_start=1/product="pleiotropic regulator 1"/protein_id="AAD09407.1"/db_xref="GI:2832296"
6 0 3 3 11 5 1 2 4 7 10 11 8 2 1 12 4 13 19 7 2 13 13 1 2 15 14 5 2 20 15 6 5 6 9 3 18 11 23 11 3 17 6 13 7 18 16 7 9 18 9 5 1 5 4 8 5 6 12 10 12 1 0 0
>HUMTROMOD\M77016\35..1114\1080\AAA61224.1\Homo sapiens\Human tropomodulin mRNA, complete cds./gene="TMOD"/codon_start=1/product="tropomodulin"/protein_id="AAA61224.1"/db_xref="GI:339948"/db_xref="GDB:G00-127-386"
3 1 6 1 2 5 2 9 23 7 0 5 3 3 1 2 7 4 7 5 4 2 4 12 1 5 11 6 4 3 4 5 5 1 2 3 13 2 10 19 16 10 3 9 3 0 25 15 11 9 8 3 1 1 3 3 1 8 7 10 1 0 1 0
>HS1119A7#5\AL022313\complement(join(63285..63298,63801..64084,64758..64900, 68776..68905,69003..69088,69599..69729,71061..71208, 71703..71835,72874..72986,75507..75579,76193..76278, 76894..77030,77962..78007,78297..78419))\1647\CAA18440.1\Homo sapiens\Human DNA sequence from clone RP5-1119A7 on chromosome22q12.2-12.3, complete sequence./locus_tag="RP5-1119A7.9-001"/standard_name="OTTHUMP00000028733"/codon_start=1/protein_id="CAA18440.1"/db_xref="GI:4200328"/db_xref="Genew:3278"/db_xref="GOA:O15371"/db_xref="InterPro:IPR007783"/db_xref="UniProt/Swiss-Prot:O15371"
4 12 7 6 7 6 3 8 15 3 1 6 7 8 0 8 9 6 9 8 4 6 3 10 2 6 4 17 3 4 7 7 7 5 1 11 11 8 15 24 16 12 4 28 6 1 20 27 21 20 17 4 4 7 14 11 0 16 8 14 10 1 0 0
>HSCD59R\X17198\73..459\387\CAA35059.1\Homo sapiens\Human mRNA for CD59 antigen./codon_start=1/product="CD59 antigen precursor"/protein_id="CAA35059.1"/db_xref="GI:29815"/db_xref="GOA:P13987"/db_xref="UniProt/Swiss-Prot:P13987"
0 1 0 0 0 1 1 2 9 3 2 1 3 1 0 2 2 0 4 2 1 2 2 1 0 1 2 2 1 3 2 0 4 2 0 5 2 1 3 4 6 4 2 2 0 4 3 3 3 2 3 1 6 5 3 4 0 1 1 1 2 1 0 0
>DQ054788\DQ054788\1..1902\1902\AAY88246.1\Homo sapiens\Homo sapiens interleukin-1 receptor associated-kinase 1 splicevariant c (IRAK1) mRNA, complete cds, alternatively spliced./gene="IRAK1"/codon_start=1/product="interleukin-1 receptor associated-kinase 1 splice variant c"/protein_id="AAY88246.1"/db_xref="GI:68235820"
2 8 10 4 2 11 4 14 40 4 0 6 6 21 5 6 24 6 6 12 7 4 19 24 10 12 11 38 4 12 8 23 16 4 1 4 27 1 1 14 12 0 0 33 10 4 6 32 19 3 11 2 10 3 10 10 0 14 4 6 13 0 0 1
>HSRIBIR\Y00281\138..1961\1824\CAA68392.1\Homo sapiens\Human mRNA for ribophorin I./codon_start=1/protein_id="CAA68392.1"/db_xref="GI:36053"/db_xref="GOA:P04843"/db_xref="UniProt/Swiss-Prot:P04843"
3 7 5 5 5 4 2 11 37 8 1 8 4 10 1 10 11 6 8 21 6 4 9 4 4 11 5 19 6 10 5 14 8 3 6 12 28 7 6 34 10 10 3 17 12 6 17 30 14 19 15 14 2 0 13 10 3 19 14 8 3 0 1 0
>AL160163#4\AL160163\complement(join(101513..101680,102132..102268, 102808..102967,105943..106158,106525..106572))\729\CAI23490.1\Homo sapiens\Human DNA sequence from clone RP5-973N23 on chromosome 6p12.3-21.2Contains the TRFP gene for TRF-proximal protein, the BYSL gene forbystin-like protein, the CCDN3 gene for cyclin D3, the 5' end ofUSP49 gene for ubiquitin specific protease 49 and 3 CpG islands,complete sequence./gene="CCND3"/locus_tag="RP5-973N23.3-002"/standard_name="OTTHUMP00000016391"/codon_start=1/product="cyclin D3"/protein_id="CAI23490.1"/db_xref="GI:56204980"/db_xref="GOA:Q5T8J1"/db_xref="InterPro:IPR004367"/db_xref="InterPro:IPR006670"/db_xref="InterPro:IPR006671"/db_xref="UniProt/TrEMBL:Q5T8J1"
2 4 5 1 0 3 1 9 19 0 0 4 0 7 0 4 10 1 4 8 2 3 2 8 1 3 5 13 3 6 1 6 5 2 1 7 4 0 4 5 1 0 2 10 3 2 5 10 5 5 4 1 5 4 3 2 1 5 3 6 2 0 1 0
>AK075391\AK075391\131..649\519\BAC11590.1\Homo sapiens\Homo sapiens cDNA PSEC0081 fis, clone NT2RP2004130./codon_start=1/protein_id="BAC11590.1"/db_xref="GI:22761449"
0 3 2 0 0 5 0 4 6 2 0 1 1 5 0 0 0 1 1 4 1 0 7 8 8 4 1 7 3 1 5 4 5 0 1 2 6 0 1 4 3 3 0 8 0 1 3 4 2 0 7 5 9 2 8 0 2 2 0 7 3 0 1 0
>AY550027\AY550027\1..378\378\AAS55642.1\Homo sapiens\Homo sapiens augmenter of liver regeneration mRNA, complete cds./codon_start=1/product="augmenter of liver regeneration"/protein_id="AAS55642.1"/db_xref="GI:45239054"
0 6 3 0 1 3 1 1 7 0 1 0 1 1 0 1 1 0 1 5 1 0 2 3 2 1 1 3 0 2 0 4 0 0 0 1 2 0 2 6 2 1 1 6 5 1 4 5 10 3 3 0 5 3 3 3 1 0 0 2 4 0 1 0
>AF451977\AF451977\99..4394\4296\AAL49758.1\Homo sapiens\Homo sapiens cask-interacting protein 1 (CASKIN1) mRNA, completecds./gene="CASKIN1"/codon_start=1/product="cask-interacting protein 1"/protein_id="AAL49758.1"/db_xref="GI:17940758"
10 24 38 0 0 14 4 22 85 4 0 6 7 24 16 14 51 5 10 30 20 10 25 88 54 32 16 95 40 17 7 72 35 16 1 21 55 1 8 71 23 8 1 59 30 6 12 74 45 13 12 7 9 1 12 4 0 35 6 19 7 0 0 1
>BC031427\BC031427\33..851\819\AAH31427.1\Homo sapiens\Homo sapiens phosphatidylinositol transfer protein, beta, mRNA(cDNA clone MGC:17010 IMAGE:4341137), complete cds./gene="PITPNB"/codon_start=1/product="PITPNB protein"/protein_id="AAH31427.1"/db_xref="GI:21594294"/db_xref="GeneID:23760"/db_xref="MIM:606876"
0 1 1 2 4 3 2 1 4 2 5 4 1 1 0 2 4 3 7 2 3 3 5 4 0 4 7 3 1 3 8 2 1 4 3 3 7 6 12 14 5 6 6 8 3 4 18 8 7 9 4 6 0 5 8 3 2 4 10 6 8 0 0 1
>HSA544583\AJ544583\1..882\882\CAD67566.1\Homo sapiens\Homo sapiens mRNA for testis serine protease 2 precursor (TESSP2gene)./gene="TESSP2"/codon_start=1/product="testis serine protease 2 precursor"/protein_id="CAD67566.1"/db_xref="GI:32562977"/db_xref="GOA:Q7Z5A4"/db_xref="InterPro:IPR001254"/db_xref="UniProt/TrEMBL:Q7Z5A4"
3 3 2 1 2 5 0 8 8 6 0 2 7 5 0 4 4 3 5 8 3 1 5 5 2 7 2 4 7 2 7 18 5 3 2 8 12 1 5 6 4 7 5 10 3 2 10 7 5 5 2 4 5 6 3 4 4 7 4 5 10 0 0 1
>BC096088\BC096088\295..1206\912\AAH96088.1\Homo sapiens\Homo sapiens DPH1 homolog (S. cerevisiae), mRNA (cDNA cloneMGC:116728 IMAGE:40000799), complete cds./gene="DPH1"/codon_start=1/product="DPH1 protein"/protein_id="AAH96088.1"/db_xref="GI:64654638"/db_xref="GeneID:1801"/db_xref="MIM:603527"
3 7 5 4 1 3 2 6 17 6 0 4 1 10 3 4 6 2 3 4 1 4 4 14 4 4 2 17 4 8 2 11 3 0 0 6 16 1 3 7 2 1 2 12 6 1 3 13 13 2 4 6 5 1 5 4 3 4 5 4 5 0 0 1
>HSM804399\AL833088\3029..3571\543\CAD89931.1\Homo sapiens\Homo sapiens mRNA; cDNA DKFZp451M2119 (from clone DKFZp451M2119);complete cds./gene="DKFZp451M2119"/codon_start=1/product="hypothetical protein"/protein_id="CAD89931.1"/db_xref="GI:30268378"
0 0 0 0 3 2 3 5 4 8 3 5 1 7 0 9 1 2 2 2 0 2 8 2 2 6 2 4 0 1 2 3 7 5 1 2 4 2 2 5 0 1 3 3 3 4 4 4 1 2 2 2 5 5 5 5 4 0 4 4 2 0 0 1
>AK074264\AK074264\251..1537\1287\BAB85033.1\Homo sapiens\Homo sapiens cDNA FLJ23684 fis, clone HEP09821./codon_start=1/protein_id="BAB85033.1"/db_xref="GI:18676819"
2 6 3 1 4 5 3 3 14 2 4 5 5 8 1 11 4 4 5 6 8 4 3 7 9 8 12 6 4 11 10 12 11 3 7 7 18 9 11 5 8 12 11 6 6 7 16 11 9 9 2 6 8 4 6 8 4 8 13 5 8 1 0 0
>AF098534\AF098534\259..2013\1755\AAC97951.1\Homo sapiens\Homo sapiens RAD17 isoform 4 (RAD17) mRNA, complete cds./gene="RAD17"/function="cell cycle checkpoint regulation"/codon_start=1/product="RAD17 isoform 4"/protein_id="AAC97951.1"/db_xref="GI:4050044"
6 1 5 0 10 9 11 8 10 10 20 8 12 1 1 18 5 12 9 4 2 10 8 7 1 16 9 7 1 12 22 1 3 9 3 3 8 8 27 12 10 16 16 15 4 11 32 10 12 20 3 10 4 6 9 19 16 5 17 15 5 0 1 0
>HSU79303\U79303\289..750\462\AAB50227.1\Homo sapiens\Human clone 23882 mRNA, complete cds./codon_start=1/product="unknown"/protein_id="AAB50227.1"/db_xref="GI:1710290"
0 1 9 1 1 6 1 1 9 0 0 0 1 7 1 3 5 4 1 2 0 0 1 4 1 3 3 4 2 5 1 2 4 1 0 1 0 0 1 4 3 1 0 4 3 0 3 16 9 2 1 0 2 0 5 1 0 4 1 7 1 0 1 0
>AB065474\AB065474\join(201..287,1173..1227,3684..3835,5306..5557,6747..8126, 9755..9796,10241..10300,10652..10714)\2091\BAC45257.1\Homo sapiens\Homo sapiens gene for seven transmembrane helix receptor, completecds, isolate:CBRC7TM_37./codon_start=1/evidence=not_experimental/product="seven transmembrane helix receptor"/protein_id="BAC45257.1"/db_xref="GI:27348191"
3 3 1 3 9 12 5 14 16 9 6 16 12 16 3 16 12 5 14 13 2 10 9 8 1 4 13 19 2 16 13 8 6 4 6 7 24 12 25 17 14 24 11 12 13 5 17 14 10 10 6 5 12 9 15 21 15 23 28 25 13 0 1 0
>AK096295\AK096295\124..2169\2046\BAC04752.1\Homo sapiens\Homo sapiens cDNA FLJ38976 fis, clone NT2RI2004099, weakly similarto ANKYRIN 2./codon_start=1/protein_id="BAC04752.1"/db_xref="GI:21755754"
0 23 19 3 1 11 4 12 56 3 0 2 1 8 4 1 15 3 3 16 11 1 5 19 10 1 5 44 22 12 4 32 17 6 1 11 49 1 3 14 21 0 5 31 20 6 2 37 32 3 5 0 18 4 12 2 1 17 2 5 5 0 0 1
>AK091496\AK091496\561..3035\2475\BAC03677.1\Homo sapiens\Homo sapiens cDNA FLJ34177 fis, clone FCBBF3016451, highly similarto RETINAL-CADHERIN PRECURSOR./codon_start=1/protein_id="BAC03677.1"/db_xref="GI:21749880"
4 13 12 2 3 6 0 17 34 1 0 1 7 21 2 5 17 2 12 29 13 1 10 33 15 6 11 25 9 14 11 24 18 7 1 27 36 3 7 21 41 11 3 28 14 0 7 35 54 11 22 8 4 2 15 5 1 45 5 26 7 0 0 1
>AY221751\AY221751\474..1970\1497\AAO67709.1\Homo sapiens\Homo sapiens myocardial ischemic preconditioning upregulatedprotein 2 (MIP2) mRNA, complete cds./gene="MIP2"/codon_start=1/product="myocardial ischemic preconditioning upregulated protein 2"/protein_id="AAO67709.1"/db_xref="GI:37900894"
4 3 4 6 4 6 11 2 14 14 10 7 7 3 0 10 5 11 17 3 3 7 11 1 2 5 10 2 2 8 10 10 7 3 6 2 10 13 15 9 5 16 10 16 7 14 21 9 14 22 4 11 5 11 7 6 6 3 10 10 14 0 0 1
>HSM806319\BX537603\1119..4055\2937\CAD97793.1\Homo sapiens\Homo sapiens mRNA; cDNA DKFZp686L04115 (from clone DKFZp686L04115)./gene="DKFZp686L04115"/codon_start=1/product="hypothetical protein"/protein_id="CAD97793.1"/db_xref="GI:31874445"
6 7 7 2 10 12 9 21 33 13 8 11 11 10 1 14 29 17 20 17 5 18 12 19 3 18 15 17 7 17 17 15 11 13 9 20 32 9 20 16 36 20 14 20 30 14 31 20 34 24 21 16 14 14 15 15 11 17 23 32 6 1 0 0
>BC035657\BC035657\62..1102\1041\AAH35657.1\Homo sapiens\Homo sapiens G protein-coupled receptor 41, mRNA (cDNA cloneMGC:46158 IMAGE:5588752), complete cds./gene="GPR41"/codon_start=1/product="G protein-coupled receptor 41"/protein_id="AAH35657.1"/db_xref="GI:23272749"/db_xref="GeneID:2865"/db_xref="MIM:603821"
1 6 4 0 3 6 1 16 30 3 0 3 2 8 2 2 11 3 1 10 2 2 3 7 4 1 3 12 4 5 3 11 10 3 0 10 22 0 0 6 5 3 1 13 7 2 6 9 8 1 11 2 7 4 18 4 1 10 1 5 8 0 1 0
>BC001484\BC001484\57..1061\1005\AAH01484.1\Homo sapiens\Homo sapiens malate dehydrogenase 1, NAD (soluble), mRNA (cDNAclone MGC:1375 IMAGE:3505345), complete cds./gene="MDH1"/codon_start=1/product="cytosolic malate dehydrogenase"/protein_id="AAH01484.1"/db_xref="GI:16306622"/db_xref="GeneID:4190"/db_xref="MIM:154200"
2 0 0 3 3 2 2 4 12 8 2 4 5 9 1 5 1 4 2 4 1 7 6 3 0 4 7 10 0 13 8 4 0 11 2 10 10 10 16 15 6 8 4 5 2 2 13 5 7 16 3 4 2 2 5 7 1 11 8 9 4 0 0 1
>AF078835\AF078835\1..840\840\AAG12174.1\Homo sapiens\Homo sapiens p33ING1 (ING1) mRNA, complete cds./gene="ING1"/codon_start=1/product="p33ING1"/protein_id="AAG12174.1"/db_xref="GI:10039545"
1 8 7 1 1 3 1 3 13 0 0 2 1 8 3 0 6 2 3 2 2 0 0 9 0 3 1 6 11 3 0 10 5 0 0 2 9 0 7 20 15 2 1 13 6 1 1 29 19 0 6 2 6 3 5 0 0 9 0 6 2 0 1 0
>HSNRASR\X02751\727..1296\570\CAA26529.1\Homo sapiens\Human N-ras mRNA and flanking regions./codon_start=1/protein_id="CAA26529.1"/db_xref="GI:35103"/db_xref="GOA:P01111"/db_xref="InterPro:IPR001806"/db_xref="InterPro:IPR005225"/db_xref="UniProt/Swiss-Prot:P01111"
2 1 0 0 4 3 2 3 5 0 0 4 2 0 1 1 3 3 7 4 0 2 3 1 0 1 2 5 1 2 4 2 3 5 5 0 7 5 7 5 4 2 4 6 2 0 8 4 3 13 8 1 0 5 2 4 4 3 4 7 0 1 0 0
>BC061912\BC061912\18..338\321\AAH61912.1\Homo sapiens\Homo sapiens PTD008 protein, mRNA (cDNA clone MGC:70730IMAGE:4444565), complete cds./gene="PTD008"/codon_start=1/product="PTD008 protein"/protein_id="AAH61912.1"/db_xref="GI:38541370"/db_xref="GeneID:51398"
0 0 2 0 0 2 0 1 6 1 0 1 0 4 2 2 5 1 0 0 3 1 2 3 6 1 0 3 0 2 0 2 0 0 0 2 3 0 1 4 5 2 1 2 0 0 1 1 5 0 3 1 2 2 3 1 0 3 0 11 3 0 0 1
>BC010418\BC010418\62..949\888\AAH10418.1\Homo sapiens\Homo sapiens ribosomal protein SA, mRNA (cDNA clone MGC:16557IMAGE:4079845), complete cds./gene="RPSA"/codon_start=1/product="ribosomal protein SA"/protein_id="AAH10418.1"/db_xref="GI:14714564"/db_xref="GeneID:3921"/db_xref="MIM:150370"
0 3 3 3 1 5 1 2 9 7 1 1 1 4 0 6 1 2 1 8 2 13 4 4 0 12 10 8 1 18 6 5 0 4 2 4 7 6 3 8 6 3 2 13 4 0 13 12 8 7 3 4 1 1 8 2 2 5 8 7 10 1 0 0
>BC094839\BC094839\63..1121\1059\AAH94839.1\Homo sapiens\Homo sapiens ADP-ribosylation-like factor 6 interacting protein 4,transcript variant 3, mRNA (cDNA clone MGC:104844 IMAGE:6339167),complete cds./gene="ARL6IP4"/codon_start=1/product="SRp25 nuclear protein, isoform 3"/protein_id="AAH94839.1"/db_xref="GI:63100339"/db_xref="GeneID:51329"/db_xref="MIM:607668"
7 11 12 0 6 12 1 1 8 7 0 2 1 20 8 8 9 3 3 6 4 0 3 8 7 3 7 18 10 6 6 18 12 4 1 4 6 0 3 32 2 0 2 9 3 0 7 19 7 5 1 0 4 0 1 0 0 5 1 5 4 0 0 1
>BT006647\BT006647\1..792\792\AAP35293.1\Homo sapiens\Homo sapiens proteasome (prosome, macropain) subunit, alpha type, 1mRNA, complete cds./codon_start=1/product="proteasome (prosome, macropain) subunit, alpha type, 1"/protein_id="AAP35293.1"/db_xref="GI:30582133"
2 0 1 5 9 2 2 2 6 6 3 5 5 4 0 5 2 0 4 2 1 5 7 1 0 6 7 4 2 10 3 3 1 8 2 1 2 11 8 4 2 6 7 8 1 8 12 6 5 12 1 7 1 4 3 6 1 2 11 8 1 0 1 0
>BC045619\BC045619\617..2110\1494\AAH45619.1\Homo sapiens\Homo sapiens protein phosphatase 2, regulatory subunit B (B56),beta isoform, mRNA (cDNA clone MGC:39486 IMAGE:5294756), completecds./gene="PPP2R5B"/codon_start=1/product="PPP2R5B protein"/protein_id="AAH45619.1"/db_xref="GI:28374383"/db_xref="GeneID:5526"/db_xref="MIM:601644"
0 10 14 4 2 0 5 16 37 4 1 2 2 12 3 3 11 3 4 9 2 4 5 20 3 6 4 14 1 5 1 3 11 5 2 9 22 3 4 24 7 7 5 26 11 2 5 41 9 8 8 7 3 5 18 11 0 19 2 8 5 0 1 0
>BC039146\BC039146\45..1166\1122\AAH39146.1\Homo sapiens\Homo sapiens CD34 antigen, mRNA (cDNA clone MGC:21247IMAGE:4746591), complete cds./gene="CD34"/codon_start=1/product="CD34 protein"/protein_id="AAH39146.1"/db_xref="GI:24657613"/db_xref="GeneID:947"/db_xref="MIM:142230"
2 2 1 0 4 3 3 2 18 7 1 7 11 7 1 13 12 6 16 19 2 9 3 3 1 11 5 9 2 8 10 12 7 2 3 5 9 5 7 9 11 6 8 13 4 2 10 11 6 5 2 6 3 4 5 2 1 9 2 4 2 0 0 1
>BC075054\BC075054\50..736\687\AAH75054.1\Homo sapiens\Homo sapiens ephrin-A5, mRNA (cDNA clone MGC:103964IMAGE:30915365), complete cds./gene="EFNA5"/codon_start=1/product="ephrin-A5"/protein_id="AAH75054.1"/db_xref="GI:50960213"/db_xref="GeneID:1946"/db_xref="MIM:601535"
1 4 1 1 4 4 3 5 6 2 2 4 2 6 0 4 5 1 3 1 1 4 8 3 2 2 4 4 2 1 3 4 1 2 2 6 6 4 5 5 6 5 1 3 4 3 7 6 8 8 7 3 2 5 11 5 2 4 1 6 3 0 1 0
>AF336793\AF336793\104..943\840\AAL71993.1\Homo sapiens\Homo sapiens SSC1/ELOVL1 mRNA, complete cds./codon_start=1/product="SSC1/ELOVL1"/protein_id="AAL71993.1"/db_xref="GI:18461755"
1 2 4 2 0 1 2 8 12 6 1 2 3 9 1 5 4 0 2 7 0 0 2 6 1 5 5 7 0 3 4 7 4 1 1 8 11 3 2 10 7 2 3 8 7 4 0 5 4 1 13 6 0 2 15 4 2 7 10 16 11 0 0 1
>AY360171\AY360171\26..1978\1953\AAQ98856.1\Homo sapiens\Homo sapiens transducer of regulated CREB protein 1 (TORC1) mRNA,complete cds./gene="TORC1"/codon_start=1/product="transducer of regulated CREB protein 1"/protein_id="AAQ98856.1"/db_xref="GI:37693041"
1 5 10 3 2 5 0 14 46 2 2 1 4 30 8 9 32 3 10 23 8 6 18 39 19 7 7 25 15 5 8 25 14 2 2 11 7 1 6 8 17 5 6 43 15 1 5 20 29 0 10 3 1 1 13 4 0 15 0 17 2 0 0 1
>BC019043\BC019043\46..1479\1434\AAH19043.1\Homo sapiens\Homo sapiens solute carrier family 2, (facilitated glucosetransporter) member 8, mRNA (cDNA clone MGC:20634 IMAGE:4641145),complete cds./gene="SLC2A8"/codon_start=1/product="solute carrier family 2, (facilitated glucose transporter) member 8"/protein_id="AAH19043.1"/db_xref="GI:17512130"/db_xref="GeneID:29988"/db_xref="MIM:605245"
1 11 4 0 1 3 2 20 36 4 0 4 2 11 4 1 13 2 3 9 2 4 3 14 6 8 5 39 10 7 3 27 12 5 0 22 22 2 1 8 3 0 1 14 3 2 6 13 8 1 6 2 7 2 25 6 0 19 0 15 13 0 0 1
>AY322547\AY322547\1..1062\1062\AAP84360.1\Homo sapiens\Homo sapiens endothelial differentiation G-protein-coupled receptor7 mRNA, complete cds./codon_start=1/product="endothelial differentiation G-protein-coupled receptor 7"/protein_id="AAP84360.1"/db_xref="GI:32482015"
0 3 3 2 1 11 1 10 18 4 2 7 2 8 0 7 9 5 10 5 2 7 2 7 2 0 2 8 4 5 2 7 5 1 2 12 14 7 7 9 13 6 1 5 3 4 0 6 8 4 10 4 9 3 10 11 1 13 7 15 7 1 0 0
>BC037881\BC037881\148..960\813\AAH37881.2\Homo sapiens\Homo sapiens monocyte to macrophage differentiation-associated 2,mRNA (cDNA clone MGC:43879 IMAGE:5274201), complete cds./gene="MMD2"/codon_start=1/product="MMD2 protein"/protein_id="AAH37881.2"/db_xref="GI:71052022"/db_xref="GeneID:221938"
2 1 3 1 0 6 1 9 12 5 0 1 0 8 1 1 5 1 2 9 2 1 0 9 0 3 3 12 3 5 1 10 4 2 2 8 8 0 2 8 5 0 0 4 8 5 2 8 4 2 10 5 3 5 17 5 1 13 1 10 11 0 0 1
>HSU59299\U59299\61..1578\1518\AAC52013.1\Homo sapiens\Homo sapiens putative monocarboxylate transporter MCT mRNA,complete cds./codon_start=1/product="MCT"/protein_id="AAC52013.1"/db_xref="GI:2463630"
1 5 7 3 1 4 1 22 40 6 1 2 3 13 1 3 19 2 4 13 4 3 9 9 3 8 9 26 6 8 5 27 8 5 1 9 21 2 2 8 9 3 5 15 7 2 3 11 7 4 10 2 11 4 31 4 2 22 0 16 13 0 0 1
>AF159456\AF159456\107..7348\7242\AAD49696.1\Homo sapiens\Homo sapiens gp-340 variant protein (DMBT1) mRNA, complete cds./gene="DMBT1"/codon_start=1/product="gp-340 variant protein"/protein_id="AAD49696.1"/db_xref="GI:5733598"
33 22 22 8 8 51 18 23 83 7 6 33 82 90 14 34 35 36 34 67 15 22 43 54 15 16 28 78 1 39 71 128 14 46 12 60 84 15 4 6 42 82 12 67 39 36 46 41 79 77 50 24 65 66 25 26 7 37 29 17 89 0 1 0
>AK000814\AK000814\245..952\708\BAA91385.1\Homo sapiens\Homo sapiens cDNA FLJ20807 fis, clone ADSE01784./codon_start=1/protein_id="BAA91385.1"/db_xref="GI:7021123"
0 3 5 0 0 0 2 6 18 2 0 2 2 5 0 1 4 3 0 4 2 2 3 14 3 3 4 7 2 5 4 4 1 1 0 3 12 0 0 8 3 1 0 12 5 3 5 12 9 4 9 7 4 0 9 1 0 4 0 7 5 0 0 1
>AK026092\AK026092\63..1556\1494\BAB15357.1\Homo sapiens\Homo sapiens cDNA: FLJ22439 fis, clone HRC09236./codon_start=1/protein_id="BAB15357.1"/db_xref="GI:10438831"
0 10 11 1 1 0 1 14 39 1 1 3 3 16 4 4 23 2 1 18 6 4 3 14 5 5 1 20 13 4 0 11 8 6 2 3 23 0 2 29 8 1 1 28 11 2 2 33 19 2 16 3 8 1 13 3 0 13 2 18 1 0 0 1
>BC099711\BC099711\278..2668\2391\AAH99711.1\Homo sapiens\Homo sapiens solute carrier family 4 (anion exchanger), member 1,adaptor protein, mRNA (cDNA clone MGC:120646 IMAGE:40026923),complete cds./gene="SLC4A1AP"/codon_start=1/product="solute carrier family 4 (anion exchanger), member 1, adaptor protein"/protein_id="AAH99711.1"/db_xref="GI:71043487"/db_xref="GeneID:22950"/db_xref="MIM:602655"
3 6 10 4 8 14 6 10 14 14 12 17 15 7 6 15 15 9 14 14 1 17 23 11 6 20 14 11 7 12 20 17 11 12 8 3 11 7 34 35 10 6 12 22 7 7 55 42 23 28 8 8 9 4 5 15 5 5 10 15 7 0 0 1
>AK095693\AK095693\669..1133\465\BAC04609.1\Homo sapiens\Homo sapiens cDNA FLJ38374 fis, clone FEBRA2002552./codon_start=1/protein_id="BAC04609.1"/db_xref="GI:21755009"
0 0 1 0 4 1 0 1 4 3 1 2 1 3 3 3 1 4 0 0 1 4 4 3 0 4 4 0 1 3 3 1 4 4 0 2 8 2 3 6 2 2 3 5 4 5 6 6 1 4 0 0 3 2 2 2 2 3 2 5 6 0 1 0
>AF019039\AF019039\125..2815\2691\AAB83973.1\Homo sapiens\Homo sapiens transportin2 mRNA, complete cds./codon_start=1/product="transportin2"/protein_id="AAB83973.1"/db_xref="GI:2589204"/IGNORED_CODON=1
2 12 9 1 1 7 2 33 66 7 0 8 8 11 8 4 9 7 8 17 7 2 9 30 6 9 6 40 5 12 3 21 7 6 4 19 25 4 10 32 31 7 7 48 19 3 15 45 38 21 13 8 19 8 28 9 0 43 15 29 12 0 1 0
>AK126036\AK126036\3..3041\3039\BAC86406.1\Homo sapiens\Homo sapiens cDNA FLJ44048 fis, clone TESTI4030669./codon_start=1/protein_id="BAC86406.1"/db_xref="GI:34532374"
3 0 0 1 20 2 11 5 11 15 29 19 42 16 1 36 12 22 27 9 2 20 19 7 0 17 15 10 0 20 14 4 1 3 14 10 17 37 62 38 13 39 33 16 8 12 69 24 8 43 4 14 1 14 7 21 31 10 39 13 2 0 0 1
>HSU86529\U86529\104..754\651\AAB96392.1\Homo sapiens\Human glutathione transferase Zeta 1 (GSTZ1) mRNA, complete cds./gene="GSTZ1"/EC_number="2.5.1.18"/codon_start=1/product="glutathione transferase Zeta 1"/protein_id="AAB96392.1"/db_xref="GI:2228731"
3 0 1 2 2 4 2 4 14 1 0 3 2 3 0 4 4 0 2 6 2 3 3 7 1 4 2 8 2 4 3 5 1 1 1 2 9 1 1 11 4 3 2 15 2 0 1 9 5 5 3 3 3 2 4 2 2 11 5 5 2 0 1 0
>AF272884\AF272884\55..3129\3075\AAK77662.1\Homo sapiens\Homo sapiens gamma-tubulin complex component GCP5 (GCP5) mRNA,complete cds./gene="GCP5"/codon_start=1/product="gamma-tubulin complex component GCP5"/protein_id="AAK77662.1"/db_xref="GI:15021369"
8 2 8 4 18 10 9 19 31 19 18 21 11 12 2 20 15 24 14 13 6 17 15 8 3 12 19 13 5 16 16 9 6 7 11 16 25 19 30 30 18 19 20 35 15 22 58 24 26 36 15 18 6 9 18 26 17 12 21 28 20 1 0 0
>AK097353\AK097353\25..735\711\BAC05011.1\Homo sapiens\Homo sapiens cDNA FLJ40034 fis, clone SYNOV2000152, highly similarto Homo sapiens kappa 1 immunoglobulin light chain mRNA./codon_start=1/protein_id="BAC05011.1"/db_xref="GI:21757071"
2 1 1 0 4 3 1 7 10 2 1 1 2 3 2 8 8 6 4 8 1 4 4 2 2 4 3 6 2 2 6 4 3 3 1 8 4 2 8 5 7 2 4 12 3 1 4 6 7 5 5 3 3 3 6 5 0 5 1 3 3 0 1 0
>AK123305\AK123305\1306..2115\810\BAC85577.1\Homo sapiens\Homo sapiens cDNA FLJ41311 fis, clone BRAMY2042760./codon_start=1/protein_id="BAC85577.1"/db_xref="GI:34528814"
3 3 4 0 2 2 2 6 18 4 0 0 7 11 2 5 9 4 1 8 4 3 1 10 3 4 0 6 1 2 2 9 7 3 3 5 5 2 5 15 1 0 3 9 3 2 1 12 9 5 11 1 4 1 2 3 1 7 2 6 5 1 0 0
>AB183548\AB183548\402..4154\3753\BAD27573.1\Homo sapiens\Homo sapiens DREG mRNA for developmentally regulatedG-protein-coupled receptor beta 1, complete cds./gene="DREG"/codon_start=1/product="developmentally regulated G-protein-coupled receptor beta 1"/protein_id="BAD27573.1"/db_xref="GI:50251168"
6 3 6 1 18 8 16 20 25 18 25 24 30 23 1 25 28 25 24 24 3 21 18 11 1 17 24 19 3 27 23 14 13 12 14 17 25 26 48 20 42 57 15 24 10 14 34 15 21 34 18 20 13 22 33 39 10 32 42 24 25 1 0 0
>AY355461\AY355461\1..1044\1044\AAQ84219.1\Homo sapiens\Homo sapiens MNK1-like kinase 1b (MNK1B) mRNA, complete cds./gene="MNK1B"/codon_start=1/product="MNK1-like kinase 1b"/protein_id="AAQ84219.1"/db_xref="GI:35187115"
4 2 5 1 1 7 1 3 13 5 1 8 0 5 0 6 7 6 3 6 2 1 8 4 0 4 5 14 0 4 6 11 4 4 2 5 13 3 11 16 5 4 6 12 7 2 14 15 16 5 6 4 3 7 6 8 3 10 3 6 4 0 0 1
>BC014256\BC014256\84..1037\954\AAH14256.1\Homo sapiens\Homo sapiens guanine nucleotide binding protein (G protein), betapolypeptide 2-like 1, mRNA (cDNA clone MGC:20686 IMAGE:4765908),complete cds./gene="GNB2L1"/codon_start=1/product="guanine nucleotide binding protein (G protein), beta polypeptide 2-like 1"/protein_id="AAH14256.1"/db_xref="GI:15559817"/db_xref="GeneID:10399"/db_xref="MIM:176981"
4 4 2 2 0 2 2 7 15 2 2 0 3 8 1 8 7 3 4 17 5 5 3 3 2 2 1 7 0 7 6 17 1 3 3 6 10 3 4 13 13 1 1 11 7 1 4 5 5 16 4 2 4 4 4 4 0 14 5 5 13 0 1 0
>HUMSP4040A\L00974\join(520..931,1460..1564,5852..6081,7221..7396,7605..7614)\933\AAA60567.1\Homo sapiens\Homo sapiens SP40,40 gene, exons 5-9./gene="SP40,40"/codon_start=1/product="'SP40,40'"/protein_id="AAA60567.1"/db_xref="GI:338305"
1 6 12 0 0 5 1 6 15 2 0 4 0 14 2 4 6 0 1 7 5 4 1 10 3 4 1 3 3 4 0 3 0 2 1 8 8 1 4 9 12 1 1 18 13 0 6 20 17 4 8 1 3 2 17 4 3 7 0 10 3 0 0 1
>AK124881\AK124881\2679..3668\990\BAC85978.1\Homo sapiens\Homo sapiens cDNA FLJ42891 fis, clone BRHIP3008405, highly similarto Dynamin 2 (EC 3.6.1.50)./codon_start=1/protein_id="BAC85978.1"/db_xref="GI:34530791"
1 2 2 2 3 7 2 7 15 4 0 3 6 8 1 5 9 5 3 2 3 1 8 11 1 10 2 8 3 8 6 14 8 3 1 6 7 2 4 13 6 1 3 13 5 4 5 15 9 2 6 1 5 7 10 6 0 8 1 7 9 0 1 0
>AK126012\AK126012\744..2759\2016\BAC86391.1\Homo sapiens\Homo sapiens cDNA FLJ44024 fis, clone TESTI4026524, moderatelysimilar to Chromodomain helicase-DNA-binding protein 4./codon_start=1/protein_id="BAC86391.1"/db_xref="GI:34532335"
7 16 14 1 6 9 1 10 44 5 0 6 3 15 2 5 13 4 2 7 5 0 15 18 11 7 3 31 6 6 1 17 16 3 1 8 20 3 5 40 22 4 2 34 17 3 11 67 33 10 12 3 1 1 12 7 1 19 3 15 8 0 1 0
>BC093694\BC093694\49..1269\1221\AAH93694.1\Homo sapiens\Homo sapiens uronyl-2-sulfotransferase, mRNA (cDNA clone MGC:120729IMAGE:7939539), complete cds./gene="UST"/codon_start=1/product="uronyl-2-sulfotransferase"/protein_id="AAH93694.1"/db_xref="GI:62739710"/db_xref="GeneID:10090"
1 6 5 3 7 9 1 9 22 7 5 6 2 5 1 2 6 3 1 4 1 8 7 14 2 11 1 5 1 1 10 10 6 1 2 8 11 1 5 18 11 7 3 12 8 7 15 15 9 8 15 5 4 3 15 10 1 10 7 8 5 0 0 1
>BC030579\BC030579\108..1301\1194\AAH30579.1\Homo sapiens\Homo sapiens UDP-GlcNAc:betaGalbeta-1,3-N-acetylglucosaminyltransferase 1, mRNA (cDNA cloneMGC:26071 IMAGE:4828158), complete cds./gene="B3GNT1"/codon_start=1/product="B3GNT1 protein"/protein_id="AAH30579.1"/db_xref="GI:21040509"/db_xref="GeneID:10678"/db_xref="MIM:605581"
3 1 3 1 6 6 0 9 21 4 3 9 2 8 1 4 5 7 2 4 4 6 6 7 2 5 6 3 2 2 5 8 6 3 4 5 6 8 16 14 15 8 7 8 6 8 8 13 11 12 12 6 6 1 10 10 7 9 7 10 6 1 0 0
>AY707088\AY707088\1..1269\1269\AAU12168.1\Homo sapiens\Homo sapiens paired box gene 6 isoform a mRNA, complete cds./codon_start=1/product="paired box gene 6 isoform a"/protein_id="AAU12168.1"/db_xref="GI:51872083"
6 2 6 0 14 5 4 3 12 2 2 2 6 15 3 3 13 11 9 17 1 4 12 8 7 10 5 8 1 5 8 10 8 6 4 5 8 6 8 5 14 7 13 17 3 3 10 11 5 9 6 6 4 2 3 6 5 6 8 14 6 1 0 0
>HSHEPSH\X07732\826..2079\1254\CAA30558.1\Homo sapiens\Human hepatoma mRNA for serine protease hepsin./codon_start=1/product="hepsin"/protein_id="CAA30558.1"/db_xref="GI:32064"/db_xref="GOA:P05981"/db_xref="UniProt/Swiss-Prot:P05981"
4 4 11 2 2 6 1 13 21 3 0 2 0 11 2 3 10 4 3 7 7 4 5 13 3 1 4 22 5 8 5 24 9 6 2 11 20 1 1 9 7 3 3 17 8 0 3 14 14 6 6 4 10 9 9 4 2 10 4 5 10 0 0 1
>AK022532\AK022532\89..3016\2928\BAB14081.1\Homo sapiens\Homo sapiens cDNA FLJ12470 fis, clone NT2RM1000885, weakly similarto HYPOTHETICAL 97.1 KD PROTEIN R05D3.4 IN CHROMOSOME III./codon_start=1/protein_id="BAB14081.1"/db_xref="GI:10433974"
16 14 13 11 12 13 17 14 31 17 5 24 10 14 0 18 7 13 14 13 1 11 8 2 1 6 24 22 2 15 9 9 6 6 4 12 18 10 40 62 14 21 14 54 8 9 63 80 18 41 5 10 3 8 9 10 4 15 18 25 2 0 0 1
>AK027310\AK027310\101..1150\1050\BAB55033.1\Homo sapiens\Homo sapiens cDNA FLJ14404 fis, clone HEMBA1004055./codon_start=1/protein_id="BAB55033.1"/db_xref="GI:14041907"
4 1 2 0 5 3 1 9 17 4 3 6 2 5 2 2 8 1 4 6 0 6 3 4 1 10 3 8 2 6 5 4 6 3 3 2 13 5 12 10 11 8 5 6 9 6 14 6 12 9 2 10 2 2 7 7 5 11 9 8 9 0 0 1
>HSA302580\AJ302580\1..939\939\CAC20500.1\Homo sapiens\Homo sapiens 6M1-6*02 gene for olfactory receptor, cell line SA./gene="6M1-6*02"/codon_start=1/product="olfactory receptor"/protein_id="CAC20500.1"/db_xref="GI:12054385"/db_xref="GOA:O76002"/db_xref="UniProt/Swiss-Prot:O76002"
0 1 2 3 3 1 5 15 12 10 1 6 7 4 3 5 3 2 5 7 0 7 5 1 2 7 7 4 2 4 5 2 4 3 7 5 8 10 4 5 3 6 2 5 4 7 5 3 3 4 7 6 4 6 11 11 1 10 9 13 5 0 0 1
>AK074849\AK074849\125..1726\1602\BAC11243.1\Homo sapiens\Homo sapiens cDNA FLJ90368 fis, clone NT2RP2004205, highly similarto B7 homolog 3./codon_start=1/protein_id="BAC11243.1"/db_xref="GI:22760560"
0 7 10 3 2 2 1 8 43 0 0 2 0 9 4 4 26 1 8 21 7 2 4 14 4 10 12 21 5 10 5 26 7 7 0 10 41 0 6 6 14 3 1 34 7 1 4 22 16 12 8 2 11 2 18 3 0 10 1 8 8 0 0 1
>HUMAARE\D38441\20..2218\2199\BAA07476.1\Homo sapiens\Human mRNA for acylamino acid-releasing enzyme, complete cds./EC_number="3.4.19.1"/codon_start=1/product="acylamino acid-releasing enzyme"/protein_id="BAA07476.1"/db_xref="GI:556514"
1 10 13 4 3 5 6 16 36 6 2 11 11 15 5 7 22 5 7 14 3 4 12 18 1 18 9 17 4 13 8 28 15 6 2 11 49 6 7 20 10 6 7 30 11 7 9 38 27 12 11 11 14 3 13 18 1 16 6 16 16 0 0 1
>HSDJ144C9#1\AL096774\complement(join(3258..3264,3806..3950,5535..5579, 6083..6154,6255..6422,6907..6994))\525\CAI19568.1\Homo sapiens\Human DNA sequence from clone RP1-144C9 on chromosome 1p34.3-36.11Contains the gene for a novel protein, a ribosomal protein S24(RPS24) pseudogene, the GPR3 gene for G protein-coupled receptor 3and the 3' end of the WASF2 gene for WAS protein family, member 2,complete sequence./locus_tag="RP1-144C9.1-001"/standard_name="OTTHUMP00000003472"/codon_start=1/product="novel protein"/protein_id="CAI19568.1"/db_xref="GI:56203462"/db_xref="UniProt/TrEMBL:Q5JXD6"
1 4 2 0 1 1 3 5 6 0 0 2 1 2 0 1 6 0 3 2 1 1 4 3 3 2 1 8 4 7 7 3 4 3 0 6 8 0 2 4 1 2 2 5 7 0 2 10 3 0 2 1 7 6 2 4 0 5 0 2 2 0 0 1
>AK027665\AK027665\72..1163\1092\BAB55277.1\Homo sapiens\Homo sapiens cDNA FLJ14759 fis, clone NT2RP3003290, moderatelysimilar to Mus musculus mRNA for Ndr1 related protein Ndr3./codon_start=1/protein_id="BAB55277.1"/db_xref="GI:14042511"
2 2 2 0 7 0 4 10 13 5 4 4 4 8 2 6 7 2 8 9 0 6 6 6 0 7 5 6 1 8 10 9 5 2 2 6 8 8 8 5 9 11 6 14 6 8 11 11 11 10 6 2 3 5 5 6 6 7 8 9 2 1 0 0
>S55843\S55843\1..60\60\AAB25673.1\Homo sapiens\rhodopsin {exon 5} [human, peripheral blood, Genomic Mutant, 60nt]./gene="rhodopsin"/codon_start=1/product="rhodopsin"/protein_id="AAB25673.1"/db_xref="GI:266288"
2 0 1 0 1 2 2 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0
>AK027466\AK027466\1..687\687\BAB55131.1\Homo sapiens\Homo sapiens cDNA FLJ14560 fis, clone NT2RM2002049./codon_start=1/protein_id="BAB55131.1"/db_xref="GI:14042161"
2 1 6 2 1 2 3 8 14 3 1 3 3 6 2 1 4 0 3 7 0 1 4 4 0 3 4 10 1 5 3 10 2 1 0 6 11 2 3 6 4 1 1 2 4 2 2 6 12 2 3 2 0 1 10 7 0 4 5 7 5 0 0 1
>AF150733\AF150733\94..261\168\AAF67473.1\Homo sapiens\Homo sapiens AD-014 protein mRNA, complete cds./codon_start=1/product="AD-014 protein"/protein_id="AAF67473.1"/db_xref="GI:7688665"
0 1 0 0 1 1 2 1 2 2 0 1 0 0 0 0 3 0 0 0 0 1 1 1 0 2 1 2 0 0 3 1 1 1 0 0 2 1 1 4 0 0 0 4 0 0 1 1 0 1 1 0 0 0 1 3 0 1 2 2 2 1 0 0
>AB075876\AB075876\429..1238\810\BAD38658.1\Homo sapiens\Homo sapiens mRNA for putative protein product of HMFN2567,complete cds./gene="HMFN2567"/codon_start=1/product="putative protein product of HMFN2567"/protein_id="BAD38658.1"/db_xref="GI:51555806"
2 3 1 1 6 4 3 2 13 9 1 11 7 3 1 6 1 2 2 8 0 5 2 5 0 3 6 4 1 6 4 4 3 4 6 5 8 4 6 2 6 6 2 7 1 3 5 6 4 2 1 2 3 4 10 9 9 7 5 5 8 0 1 0
>AL662870#1\AL662870\join(42188..42272,42366..42468,42660..42888,44431..44578, 44838..44937,45460..45646,45754..46000,46526..46621, 46730..46881,47964..48129,48862..48972,50079..50323, 50472..50599,50837..51055,51531..51765,52346..52495, 52614..52754)\2742\CAI18442.1\Homo sapiens\Human DNA sequence from clone XXbac-70P20 on chromosome 6 containsthe DDR1 gene for discoidin domain receptor family, member 1, aputative novel transcript and two CpG islands, complete sequence./gene="DDR1"/locus_tag="XXbac-BPG70P20.1-005"/standard_name="OTTHUMP00000029346"/codon_start=1/product="discoidin domain receptor family, member 1"/protein_id="CAI18442.1"/db_xref="GI:55962110"/db_xref="InterPro:IPR000421"/db_xref="InterPro:IPR000719"/db_xref="InterPro:IPR001245"/db_xref="InterPro:IPR002011"/db_xref="InterPro:IPR008266"/db_xref="InterPro:IPR008979"/db_xref="InterPro:IPR011009"
6 16 27 8 4 9 4 29 55 8 4 7 4 14 2 10 17 9 3 18 5 5 15 35 10 19 12 42 5 14 12 35 31 6 3 13 38 6 3 19 21 9 2 33 12 7 5 44 32 17 14 15 10 7 20 13 0 22 4 24 20 0 0 1
>AF144477\AF144477\281..1777\1497\AAD44754.1\Homo sapiens\Homo sapiens myotilin mRNA, complete cds./codon_start=1/product="myotilin"/protein_id="AAD44754.1"/db_xref="GI:5532485"
3 2 1 5 16 2 4 3 6 8 7 7 14 14 3 8 9 5 9 8 1 9 21 3 0 11 14 4 1 20 14 4 3 3 5 2 10 9 20 10 13 14 21 21 4 6 19 6 6 18 4 9 3 4 11 8 8 9 4 9 3 1 0 0
>AK097588\AK097588\258..1961\1704\BAC05111.1\Homo sapiens\Homo sapiens cDNA FLJ40269 fis, clone TESTI2026597./codon_start=1/protein_id="BAC05111.1"/db_xref="GI:21757406"
6 2 3 5 4 4 6 8 14 5 12 9 7 8 0 11 11 5 4 11 1 10 10 5 2 8 15 15 1 13 15 11 7 12 3 3 13 14 9 25 10 6 11 22 7 6 21 16 10 20 5 16 5 6 20 13 4 8 14 15 5 0 1 0
>AL136131#14\AL136131\join(136965..137030,140059..140110,143187..143383, 144178..144254,144607..144636,150259..150280)\444\CAC19515.1\Homo sapiens\Human DNA sequence from clone RP1-261G23 on chromosome 6p12.2-21.1Contains the KIAA0110 gene, the FLJ30845 gene, the MRPS18A gene formitochondrial ribosomal protein S18A, a pseudogene similar toOPA-interacting protein (OIP21) a novel gene, the VEGF gene forvascular endothelial growth factor and two CpG islands, completesequence./gene="VEGF"/locus_tag="RP1-261G23.1-003"/standard_name="OTTHUMP00000016488"/codon_start=1/product="vascular endothelial growth factor"/protein_id="CAC19515.1"/db_xref="GI:11989985"/db_xref="Genew:12680"/db_xref="GOA:P15692"/db_xref="InterPro:IPR000072"/db_xref="InterPro:IPR002400"/db_xref="UniProt/Swiss-Prot:P15692"
1 1 2 0 3 1 1 2 6 1 0 1 0 3 0 1 3 0 0 2 0 1 3 3 1 2 3 2 0 1 3 3 2 0 0 1 6 0 4 5 3 2 2 7 5 4 4 9 3 3 4 1 5 4 4 1 1 6 1 7 3 0 0 1
>AF218421\AF218421\28..897\870\AAF37561.1\Homo sapiens\Homo sapiens hepatocellular carcinoma-associated antigen 59 mRNA,complete cds./codon_start=1/product="hepatocellular carcinoma-associated antigen 59"/protein_id="AAF37561.1"/db_xref="GI:7158847"
2 3 6 4 4 6 2 1 9 3 1 3 3 5 2 1 1 3 3 6 2 2 3 5 1 6 6 4 1 4 1 5 3 2 3 2 10 3 10 23 12 4 1 8 2 3 9 32 9 10 2 5 0 1 3 3 2 5 4 10 0 0 0 1
>AK128288\AK128288\1550..1981\432\BAC87369.1\Homo sapiens\Homo sapiens cDNA FLJ46426 fis, clone THYMU3013897./codon_start=1/protein_id="BAC87369.1"/db_xref="GI:34535589"
0 1 1 1 0 0 1 7 4 3 2 7 1 5 1 5 4 0 3 4 0 2 5 4 2 8 1 7 0 2 1 1 2 1 2 3 0 3 0 0 1 1 1 5 4 2 1 2 1 1 1 0 6 4 5 3 0 5 0 5 1 0 0 1
>BC025255\BC025255\9..2417\2409\AAH25255.1\Homo sapiens\Homo sapiens spermatogenesis associated 20, mRNA (cDNA cloneMGC:39131 IMAGE:5019010), complete cds./gene="SPATA20"/codon_start=1/product="sperm protein SSP411"/protein_id="AAH25255.1"/db_xref="GI:19263653"/db_xref="GeneID:64847"
7 15 19 6 1 7 5 22 48 1 1 11 12 11 4 6 18 11 5 20 5 8 4 26 7 12 6 37 5 14 7 34 13 9 1 16 35 1 7 26 12 11 3 42 15 8 10 35 30 11 17 10 10 4 21 9 1 10 4 18 18 0 0 1
>BC017583\BC017583\193..372\180\AAH17583.1\Homo sapiens\Homo sapiens cDNA clone MGC:26468 IMAGE:4828130, complete cds./codon_start=1/product="Unknown (protein for MGC:26468)"/protein_id="AAH17583.1"/db_xref="GI:17068408"
0 1 0 0 1 0 3 1 3 2 0 1 0 0 0 1 0 0 1 1 0 1 0 0 1 1 1 1 0 1 2 0 1 0 2 2 0 2 2 1 2 2 1 2 2 1 1 0 1 3 1 0 1 1 2 0 1 0 2 3 0 1 0 0
>BC070333\BC070333\59..421\363\AAH70333.1\Homo sapiens\Homo sapiens immunoglobulin heavy variable 1-69, mRNA (cDNA cloneMGC:88338 IMAGE:6557369), complete cds./gene="IGHV1-69"/codon_start=1/product="IGHV1-69 protein"/protein_id="AAH70333.1"/db_xref="GI:47124252"/db_xref="GeneID:28461"/db_xref="IMGT/GENE-DB:IGHV1-69"
1 0 0 0 3 1 0 1 3 1 0 0 1 4 0 3 6 0 5 2 5 0 0 0 0 3 3 3 1 4 3 2 4 2 0 4 8 0 0 6 1 0 1 7 0 0 1 3 4 0 3 2 1 1 3 2 0 4 1 3 4 0 0 1
>BC026288\BC026288\167..679\513\AAH26288.1\Homo sapiens\Homo sapiens ubiquitin-conjugating enzyme E2G 1 (UBC7 homolog, C.elegans), transcript variant 1, mRNA (cDNA clone MGC:23926IMAGE:4806647), complete cds./gene="UBE2G1"/codon_start=1/product="ubiquitin-conjugating enzyme E2G 1, isoform 1"/protein_id="AAH26288.1"/db_xref="GI:20070812"/db_xref="GeneID:7326"/db_xref="MIM:601569"
3 2 0 0 4 1 1 4 5 4 1 0 1 0 1 3 1 1 2 1 1 3 5 1 0 7 4 1 1 4 2 2 1 5 1 2 3 4 9 3 1 7 1 2 2 2 12 5 3 9 1 4 1 1 2 4 1 3 7 4 4 0 0 1
>AF397395\AF397395\90..737\648\AAK97476.1\Homo sapiens\Homo sapiens NOE3-4 (NOE3) mRNA, complete cds, alternativelyspliced./gene="NOE3"/codon_start=1/product="NOE3-4"/protein_id="AAK97476.1"/db_xref="GI:15420834"
1 1 3 1 5 3 3 4 10 4 5 5 1 4 0 3 3 1 4 3 1 3 1 1 0 4 2 3 1 4 2 0 3 2 0 2 3 4 13 9 5 1 7 13 1 1 15 6 3 9 3 2 3 1 2 3 1 2 7 7 1 1 0 0
>HSU43292\U43292\308..817\510\AAB05839.1\Homo sapiens\Human MDS1B (MDS1) mRNA, complete cds./gene="MDS1"/codon_start=1/product="MDS1B"/protein_id="AAB05839.1"/db_xref="GI:1294815"
1 0 1 0 2 6 1 2 3 2 0 3 3 3 1 5 3 2 2 1 0 2 4 4 0 9 4 6 0 2 7 2 3 2 6 1 1 1 5 4 2 4 1 3 1 1 7 7 2 5 4 4 1 2 3 2 3 4 2 4 3 0 1 0
>BC008200\BC008200\331..1170\840\AAH08200.1\Homo sapiens\Homo sapiens keratin 8, mRNA (cDNA clone MGC:5377 IMAGE:3445666),complete cds./gene="KRT8"/codon_start=1/product="KRT8 protein"/protein_id="AAH08200.1"/db_xref="GI:14198278"/db_xref="GeneID:3856"/db_xref="MIM:148060"
0 5 8 3 0 4 1 5 24 0 0 1 0 11 2 7 16 1 4 5 1 1 0 2 0 0 3 14 2 6 1 10 6 2 1 3 5 1 1 15 9 0 0 14 1 1 2 30 9 5 5 4 0 0 2 1 0 10 6 9 0 0 0 1
>HS34B20#16\AL031777\complement(76356..76766)\411\CAC03421.1\Homo sapiens\Human DNA sequence from clone RP1-34B20 on chromosome 6p21.31-22.2Contains seventeen histone (pseudo)genes and gene RPS10P1 (40SRibosomal protein S10 pseudogene 1), three CpG islands, ESTs, STSsand GSSs, complete sequence./gene="HIST1H3G"/locus_tag="RP1-34B20.1-001"/standard_name="OTTHUMP00000016152"/codon_start=1/protein_id="CAC03421.1"/db_xref="GI:10198618"/db_xref="GOA:P16106"/db_xref="GOA:P68431"/db_xref="InterPro:IPR000164"/db_xref="InterPro:IPR007124"/db_xref="InterPro:IPR007125"/db_xref="UniProt/Swiss-Prot:P68431"
2 12 1 2 1 0 0 2 8 0 0 2 0 2 1 0 1 1 1 5 0 4 0 2 2 2 1 7 5 5 0 4 2 1 0 0 6 0 3 10 1 0 1 7 0 2 1 6 2 2 2 1 1 1 2 2 0 4 3 3 0 0 1 0
>HSU11870\U11870\2057..3109\1053\AAA64378.1\Homo sapiens\Human interleukin-8 receptor type A (IL8RBA) gene, promoter andcomplete cds./gene="IL8RA"/codon_start=1/evidence=experimental/product="interleukin-8 receptor type A"/protein_id="AAA64378.1"/db_xref="GI:511805"
1 6 3 5 0 3 4 9 34 3 1 6 2 7 1 4 6 3 7 7 0 5 4 5 1 2 4 15 0 3 6 10 1 0 0 17 9 4 1 10 10 8 1 6 4 6 3 6 4 8 9 4 7 3 14 10 0 16 4 12 6 0 0 1
>AB065748\AB065748\201..1151\951\BAC05968.1\Homo sapiens\Homo sapiens gene for seven transmembrane helix receptor, completecds, isolate:CBRC7TM_311./codon_start=1/evidence=not_experimental/product="seven transmembrane helix receptor"/protein_id="BAC05968.1"/db_xref="GI:21928764"
2 1 2 0 1 3 3 9 17 3 5 8 6 3 1 17 2 2 9 8 1 6 2 4 0 5 5 4 0 8 2 2 4 3 6 7 11 7 6 5 5 10 3 3 0 4 4 3 2 6 7 10 4 7 10 12 4 5 13 14 0 1 0 0
>AF055460\AF055460\123..1031\909\AAC27036.1\Homo sapiens\Homo sapiens stanniocalcin-2 (STC-2) mRNA, complete cds./gene="STC-2"/codon_start=1/product="stanniocalcin-2"/protein_id="AAC27036.1"/db_xref="GI:3335144"
3 2 8 0 2 6 0 4 12 1 1 8 1 6 1 3 10 1 1 9 1 2 3 8 2 2 1 14 4 6 5 10 7 4 0 2 11 1 4 10 9 1 1 17 11 4 7 17 9 3 2 1 7 8 6 4 2 8 2 5 2 0 0 1
>BT007434\BT007434\1..2253\2253\AAP36102.1\Homo sapiens\Homo sapiens methylmalonyl Coenzyme A mutase mRNA, complete cds./codon_start=1/product="methylmalonyl Coenzyme A mutase"/protein_id="AAP36102.1"/db_xref="GI:30583707"
9 3 2 8 12 8 6 7 11 23 8 9 11 7 0 14 4 5 13 9 0 16 14 5 1 16 20 10 3 35 29 7 6 16 13 2 16 17 29 20 7 18 10 24 7 8 47 8 9 31 7 12 0 8 7 21 14 10 27 24 7 0 1 0
>HUMANTN\M60618 M34541\32..1474\1443\AAA35537.1\Homo sapiens\Human nuclear autoantigen (SP-100) mRNA, complete cds./gene="Sp-100"/codon_start=1/product="nuclear autoantigen"/protein_id="AAA35537.1"/db_xref="GI:178689"
3 0 0 3 15 8 4 7 12 4 4 3 12 6 2 12 12 12 10 4 1 7 10 9 2 8 12 3 1 6 8 6 4 7 6 5 8 4 12 13 8 18 16 7 7 7 32 24 14 18 2 2 5 6 9 9 7 6 8 8 2 0 1 0
>AK058150\AK058150\119..757\639\BAB71688.1\Homo sapiens\Homo sapiens cDNA FLJ25421 fis, clone TST03713./codon_start=1/protein_id="BAB71688.1"/db_xref="GI:16554206"
0 0 1 1 1 2 1 3 7 3 5 2 7 10 0 17 5 6 4 4 0 2 4 2 0 5 2 3 1 5 3 1 2 1 3 2 2 2 5 6 2 9 4 8 3 4 6 6 2 10 0 0 0 1 3 5 2 7 4 4 2 1 0 0
>AF193339\AF193339\303..3650\3348\AAF61199.1\Homo sapiens\Homo sapiens eukaryotic translation initiation factor 2 alphakinase PEK mRNA, complete cds./codon_start=1/product="eukaryotic translation initiation factor 2 alpha kinase PEK"/protein_id="AAF61199.1"/db_xref="GI:7341091"
9 9 4 5 20 17 5 18 28 16 14 17 24 14 2 30 20 23 22 11 7 19 30 9 8 21 16 19 14 23 26 13 12 8 15 8 20 22 37 25 16 25 11 24 10 15 57 36 29 39 8 25 4 14 15 27 13 18 28 25 16 0 1 0
>AF110763\AF110763\join(22..177,604..778,1380..1549,2043..2229,3457..3611)\843\AAD21579.1\Homo sapiens\Homo sapiens skeletal muscle LIM-protein 1 (FHL1) gene, completecds./gene="FHL1"/codon_start=1/product="skeletal muscle LIM-protein 1"/protein_id="AAD21579.1"/db_xref="GI:4512028"
0 4 1 1 1 1 0 0 4 1 0 2 0 5 0 2 1 2 1 9 0 5 0 7 0 1 2 11 2 3 7 3 7 2 0 2 15 2 7 26 8 2 8 7 9 4 2 9 10 6 7 5 25 10 12 8 0 5 1 1 4 1 0 0
>AK128139\AK128139\162..1736\1575\BAC87293.1\Homo sapiens\Homo sapiens cDNA FLJ46260 fis, clone TESTI4024494, weakly similarto Homo sapiens zinc-binding protein Rbcc728./codon_start=1/protein_id="BAC87293.1"/db_xref="GI:34535364"
6 10 12 3 4 8 2 14 34 7 0 6 4 10 2 3 12 6 10 15 2 3 10 17 3 8 8 24 0 7 10 16 10 9 3 1 21 0 0 24 8 1 6 29 13 3 10 26 9 2 7 1 22 7 9 2 2 8 3 9 3 0 0 1
>BC030509\BC030509\291..530\240\AAH30509.1\Homo sapiens\Homo sapiens DKFZp434A0131 protein, mRNA (cDNA cloneIMAGE:4400104), complete cds./gene="DKFZP434A0131"/codon_start=1/product="DKFZP434A0131 protein"/protein_id="AAH30509.1"/db_xref="GI:20988121"/db_xref="GeneID:54441"
0 1 0 0 1 1 1 2 8 1 1 0 0 1 0 0 4 0 1 1 1 2 3 0 0 0 1 1 0 2 1 0 4 3 1 0 1 0 0 3 1 0 1 5 4 0 0 5 5 0 1 0 1 1 4 1 0 0 0 2 2 0 0 1
>D87062\D87062\1..501\501\BAB46918.1\Homo sapiens\Homo sapiens hucep-3 mRNA for cerebral protein-3, complete cds./gene="hucep-3"/codon_start=1/evidence=not_experimental/product="cerebral protein-3"/protein_id="BAB46918.1"/db_xref="GI:13874423"
2 0 3 0 4 6 2 4 10 4 0 2 1 5 1 5 8 1 3 7 0 0 3 2 0 1 1 5 0 1 5 7 10 3 0 1 5 0 3 1 0 0 0 6 3 1 2 6 1 1 2 0 5 5 3 3 0 1 1 4 6 0 0 1
>HUMNKEFA\L19184\68..667\600\AAA50464.1\Homo sapiens\Human natural killer cell enhancing factor (NKEFA) mRNA, completecds./gene="NKEFA"/codon_start=1/product="enhancer protein"/protein_id="AAA50464.1"/db_xref="GI:440306"
0 2 1 0 1 2 2 1 2 3 1 2 2 1 1 5 1 2 2 4 1 3 3 4 1 7 2 3 0 7 5 4 3 3 2 3 6 3 10 9 3 3 2 6 2 2 5 2 5 11 2 3 4 2 10 5 0 6 7 3 2 0 0 1
>BC068477\BC068477\345..1376\1032\AAH68477.1\Homo sapiens\Homo sapiens Rap guanine nucleotide exchange factor (GEF) 3, mRNA(cDNA clone IMAGE:4813268), complete cds./gene="RAPGEF3"/codon_start=1/product="RAPGEF3 protein"/protein_id="AAH68477.1"/db_xref="GI:46250001"/db_xref="GeneID:10411"/db_xref="MIM:606057"
8 2 11 3 2 5 0 10 28 3 1 4 0 7 2 3 9 0 2 9 1 3 5 8 1 2 5 13 1 5 6 6 10 2 0 2 21 2 2 12 7 1 2 13 7 8 8 19 9 10 4 1 7 1 7 3 0 11 1 4 4 1 0 0
>HSY14768#9\Y14768\join(26891..26933,29486..29637,29713..29830,29979..30086, 30224..30300)\498\CAA75068.1\Homo sapiens\Homo sapiens DNA, cosmid clones TN62 and TN82./gene="1C7"/codon_start=1/product="1C7f"/protein_id="CAA75068.1"/db_xref="GI:3805809"/db_xref="GOA:O14931"/db_xref="UniProt/Swiss-Prot:O14931"
3 0 3 1 3 0 1 5 7 2 0 2 1 6 0 2 4 0 3 2 1 1 3 5 0 2 0 6 0 5 5 5 7 2 0 6 11 1 2 1 0 2 1 3 5 3 2 7 2 2 2 2 4 3 4 1 0 4 3 4 3 0 1 0
>HSJ1103B4#2\AL121998\complement(join(48522..48673,53613..53835,58125..58282, 59446..59571,80071..80311,82557..82757,84604..84793, 90029..90176,91145..91289,98536..98629,111260..111336))\1755\CAI19172.1\Homo sapiens\Human DNA sequence from clone RP5-1103B4 on chromosome 1 Containsthe C8A gene for complement component 8 alpha polypeptide, the C8Bgene for complement component 8 beta polypeptide and a novel gene,complete sequence./gene="C8A"/locus_tag="RP5-1103B4.1-001"/standard_name="OTTHUMP00000010016"/codon_start=1/product="complement component 8, alpha polypeptide"/protein_id="CAI19172.1"/db_xref="GI:56203387"/db_xref="GOA:P07357"/db_xref="InterPro:IPR000884"/db_xref="InterPro:IPR001862"/db_xref="InterPro:IPR002172"/db_xref="InterPro:IPR006209"/db_xref="InterPro:IPR008085"/db_xref="InterPro:IPR008957"/db_xref="UniProt/Swiss-Prot:P07357"
4 6 6 2 7 10 0 3 14 7 5 10 9 10 1 8 13 6 12 9 3 7 7 3 1 7 14 15 0 6 15 16 12 13 8 1 11 7 16 16 9 14 5 28 6 3 17 16 21 18 11 15 16 14 10 12 2 15 11 12 9 0 0 1
>AY357727\AY357727\198..2042\1845\AAR29466.1\Homo sapiens\Homo sapiens progerin mRNA, complete cds./codon_start=1/product="progerin"/protein_id="AAR29466.1"/db_xref="GI:39653934"
2 29 15 9 0 5 2 9 50 6 0 3 6 12 6 6 24 2 1 19 4 8 2 6 2 3 9 28 7 14 4 11 14 3 1 4 20 1 4 36 12 7 1 38 9 4 7 64 23 12 7 2 5 0 4 3 1 13 1 10 4 1 0 0
>HSA249976\AJ249976\91..1800\1710\CAB65116.1\Homo sapiens\Homo sapiens mRNA for AMP-activated protein kinase gamma2 subunit(AMPK gamma2 gene)./gene="AMPK gamma2"/function="AMP-activated protein kinase regulatory subunit"/codon_start=1/evidence=experimental/product="AMP-activated protein kinase gamma2 subunit"/protein_id="CAB65116.1"/db_xref="GI:6688199"/db_xref="GOA:Q9UGJ0"/db_xref="UniProt/Swiss-Prot:Q9UGJ0"
5 6 3 2 8 7 3 6 18 8 5 5 9 27 4 9 12 7 11 12 4 2 8 19 10 10 8 13 7 9 8 10 6 6 9 3 14 10 21 20 7 10 6 12 9 5 15 18 13 12 6 10 2 1 19 10 10 13 12 13 2 0 0 1
>BC015803\BC015803\8..1057\1050\AAH15803.1\Homo sapiens\Homo sapiens interferon regulatory factor 2, mRNA (cDNA cloneMGC:9260 IMAGE:3920890), complete cds./gene="IRF2"/codon_start=1/product="interferon regulatory factor 2"/protein_id="AAH15803.1"/db_xref="GI:16041826"/db_xref="GeneID:3660"/db_xref="MIM:147576"
2 3 6 0 3 3 1 6 8 4 0 1 3 12 1 5 14 6 4 6 3 6 8 8 7 7 4 5 4 1 6 3 5 0 4 9 8 4 14 16 9 10 5 8 2 5 14 15 7 11 5 2 2 1 3 3 4 9 6 10 8 1 0 0
>HUMHAHLABW\M83193\1..1017\1017\AAA58628.1\Homo sapiens\Homo sapiens (isolate HA) HLA-Bw62 antigen (HLA-Bw62.3 IEF variant,B*1501 allele) mRNA, 3'end./gene="HLA-Bw62.3"/codon_start=1/product="HLA-Bw62 antigen"/protein_id="AAA58628.1"/db_xref="GI:183777"
1 8 5 1 6 7 1 6 14 1 0 0 1 9 0 7 7 2 6 14 2 3 4 7 4 2 4 10 11 8 5 12 9 1 1 3 15 2 1 8 5 0 1 19 4 5 1 23 16 4 13 2 4 1 6 0 1 9 1 5 10 0 0 1
>AF487652\AF487652\join(2955..3328,7168..7693)\900\AAL96666.1\Homo sapiens\Homo sapiens fibrinogen silencer binding protein (FSBP) gene,complete cds./gene="FSBP"/codon_start=1/product="fibrinogen silencer binding protein"/protein_id="AAL96666.1"/db_xref="GI:19744802"
1 3 2 0 9 6 9 3 4 4 7 8 5 5 2 7 1 6 3 5 0 2 6 1 0 8 7 1 0 3 4 1 1 2 7 0 5 7 14 9 4 8 8 12 4 7 16 15 3 12 0 7 1 1 0 7 4 2 11 8 1 1 0 0
>AF226604\AF226604\1..579\579\AAF64280.1\Homo sapiens\Homo sapiens sigma 1 receptor beta variant mRNA, complete cds,alternatively spliced./codon_start=1/product="sigma 1 receptor beta variant"/protein_id="AAF64280.1"/db_xref="GI:7582320"
0 3 8 1 0 0 0 8 16 3 0 2 0 4 2 1 2 0 2 7 2 2 3 1 0 2 2 8 7 4 0 11 4 3 2 6 9 0 0 0 1 1 0 9 6 0 1 11 5 0 3 3 1 0 9 1 1 2 0 4 9 0 0 1
>BC065530\BC065530\225..3236\3012\AAH65530.1\Homo sapiens\Homo sapiens methyl-CpG binding domain protein 6, mRNA (cDNA cloneMGC:70424 IMAGE:6152748), complete cds./gene="MBD6"/codon_start=1/product="methyl-CpG binding domain protein 6"/protein_id="AAH65530.1"/db_xref="GI:41351092"/db_xref="GeneID:114785"
7 6 12 11 10 13 10 29 47 22 5 13 21 23 2 27 32 17 8 19 2 11 47 79 8 80 15 47 3 26 27 29 44 15 3 11 15 4 7 10 10 13 10 20 12 6 9 28 13 7 5 0 6 6 12 7 1 5 3 9 4 0 1 0
>AF033095\AF033095\63..776\714\AAB87479.1\Homo sapiens\Homo sapiens testis enhanced gene transcript protein (TEGT) mRNA,complete cds./gene="TEGT"/codon_start=1/product="testis enhanced gene transcript protein"/protein_id="AAB87479.1"/db_xref="GI:2645729"
1 1 0 1 2 1 0 6 14 9 2 6 2 3 0 3 4 2 3 3 1 5 0 2 1 2 7 8 2 5 7 6 2 1 0 7 3 2 5 8 4 2 2 5 2 6 5 2 0 8 1 5 2 3 10 11 3 6 8 12 3 0 0 1
>BC028237\BC028237\429..1295\867\AAH28237.1\Homo sapiens\Homo sapiens growth differentiation factor 10, mRNA (cDNA cloneMGC:39897 IMAGE:5245100), complete cds./gene="GDF10"/codon_start=1/product="GDF10 protein"/protein_id="AAH28237.1"/db_xref="GI:20380935"/db_xref="GeneID:2662"/db_xref="MIM:601361"
1 8 8 1 1 7 1 4 14 1 0 0 2 6 2 2 4 0 0 2 2 1 4 20 7 3 5 17 7 1 2 6 5 0 0 4 12 3 4 11 8 3 0 12 4 1 1 13 12 8 6 2 4 3 7 2 1 11 1 6 5 0 0 1
>AB044786\AB044786\211..780\570\BAD29732.1\Homo sapiens\Homo sapiens Si-1-2 mRNA for zinc finger protein, complete cds./gene="Si-1-2"/codon_start=1/product="zinc finger protein"/protein_id="BAD29732.1"/db_xref="GI:50300079"
0 6 4 1 1 3 0 1 20 0 0 1 0 6 1 0 4 3 2 3 5 1 4 12 5 5 1 9 3 1 2 3 3 2 0 4 5 2 1 7 1 0 0 8 3 0 0 10 7 3 3 1 7 2 4 0 0 2 0 4 3 1 0 0
>AL355315#4\AL355315\join(13479..13689,30632..30765,40285..40434)\495\CAI15455.1\Homo sapiens\Human DNA sequence from clone RP11-548K23 on chromosome 10 Containsthe ANKRD2 gene for ankyrin repeat domain 2 (stretch responsivemuscle), six novel genes, the gene for phosphatidylinositol4-kinase type II (PI4KII) and four CpG islands, complete sequence./gene="C10orf65"/locus_tag="RP11-548K23.9-001"/standard_name="OTTHUMP00000020215"/codon_start=1/product="chromosome 10 open reading frame 65"/protein_id="CAI15455.1"/db_xref="GI:55958616"/db_xref="GOA:Q96EV5"/db_xref="InterPro:IPR002220"/db_xref="UniProt/TrEMBL:Q96EV5"
2 4 1 0 0 3 1 2 12 0 0 2 1 1 0 2 4 0 0 5 1 2 2 7 0 1 2 6 2 4 2 5 10 2 0 4 8 0 4 3 2 3 2 6 2 0 1 10 3 2 2 2 5 0 4 2 0 3 2 3 5 0 0 1
>AL355145#2\AL355145\join(12011..12137,14114..14179,14563..14667,15064..15274, 15671..15861,16440..16522,16904..17157,17987..18185, 18328..18449,18979..19774,20643..20657)\2169\CAI22937.1\Homo sapiens\Human DNA sequence from clone RP5-831G13 on chromosome 1 Containsthe 3' end of the gene for a novel protein (possible ortholog ofmouse mitsugumin 29), genes MGC46534 and FLJ39035, theamphoterin-induced gene (KIAA1161) (AMIGO) and the 5' end of theGPR61 gene for G protein-coupled receptor 61, complete sequence./gene="ATXN7L2"/locus_tag="RP5-831G13.2-001"/standard_name="OTTHUMP00000012702"/codon_start=1/product="ataxin 7-like 1"/protein_id="CAI22937.1"/db_xref="GI:56206276"/db_xref="UniProt/TrEMBL:Q5T6C5"
1 10 23 4 5 6 0 14 24 6 2 4 6 25 2 13 25 7 7 21 3 4 28 29 6 25 12 31 8 19 6 19 22 6 4 5 20 4 17 40 12 3 3 21 14 6 12 34 18 7 4 4 19 10 10 4 1 9 1 13 4 1 0 0
>BC040555\BC040555\725..1099\375\AAH40555.1\Homo sapiens\Homo sapiens thiamin pyrophosphokinase 1, mRNA (cDNA cloneMGC:41789 IMAGE:5269277), complete cds./gene="TPK1"/codon_start=1/product="TPK1 protein"/protein_id="AAH40555.1"/db_xref="GI:71296864"/db_xref="GeneID:27010"/db_xref="MIM:606370"
0 0 0 1 4 2 1 3 3 4 1 2 0 0 1 1 0 0 3 4 0 5 3 1 0 4 1 2 1 1 4 3 1 1 1 1 3 4 2 3 1 3 3 3 3 1 1 2 3 3 2 0 0 4 1 2 3 8 3 4 3 0 0 1
>AK056984\AK056984\96..752\657\BAB71332.1\Homo sapiens\Homo sapiens cDNA FLJ32422 fis, clone SKMUS2000933, weakly similarto RNA polymerase III subunit./codon_start=1/protein_id="BAB71332.1"/db_xref="GI:16552536"
2 1 8 3 1 2 5 3 5 0 0 4 5 0 0 1 1 1 3 4 0 2 4 9 1 5 1 4 0 3 2 5 4 5 2 2 4 0 4 11 2 3 1 6 0 1 21 20 7 9 3 5 0 0 4 2 2 4 4 5 2 0 0 1
>BT019526\BT019526\1..930\930\AAV38333.1\Homo sapiens\Homo sapiens protein phosphatase 2 (formerly 2A), catalyticsubunit, beta isoform mRNA, complete cds./codon_start=1/product="protein phosphatase 2 (formerly 2A), catalytic subunit, beta isoform"/protein_id="AAV38333.1"/db_xref="GI:54695922"
2 2 3 9 4 0 1 5 9 7 8 1 5 2 0 3 1 1 9 6 1 4 9 1 1 3 3 3 2 4 8 4 2 9 5 2 7 7 4 7 7 7 7 7 2 8 9 10 10 15 5 11 3 7 6 8 4 1 7 6 5 0 1 0
>BT006840\BT006840\1..1113\1113\AAP35486.1\Homo sapiens\Homo sapiens phosphoserine aminotransferase mRNA, complete cds./codon_start=1/product="phosphoserine aminotransferase"/protein_id="AAP35486.1"/db_xref="GI:30582519"
1 1 2 1 2 4 2 4 10 6 5 8 5 7 1 5 5 4 5 2 2 1 8 6 1 3 4 14 2 10 10 7 7 6 1 8 16 10 12 15 10 12 5 6 3 3 9 10 8 10 6 7 3 4 6 11 3 4 15 9 3 0 1 0
>AF498921\AF498921\1..642\642\AAM18130.1\Homo sapiens\Homo sapiens purinergic receptor P2RY11 (P2RY11) mRNA, completecds./gene="P2RY11"/codon_start=1/product="purinergic receptor P2RY11"/protein_id="AAM18130.1"/db_xref="GI:20269977"
1 3 5 2 1 3 2 8 16 0 0 2 1 3 0 0 11 1 4 1 1 2 2 9 4 2 6 20 5 1 0 10 6 1 0 1 13 0 1 4 3 1 2 5 5 0 0 6 4 1 8 2 8 2 2 1 1 2 0 6 2 0 0 1
>AK002033\AK002033\135..2447\2313\BAA92047.1\Homo sapiens\Homo sapiens cDNA FLJ11171 fis, clone PLACE1007317, weakly similarto Drosophila melanogaster Adrift mRNA./codon_start=1/protein_id="BAA92047.1"/db_xref="GI:7023671"
2 0 3 3 9 7 13 10 17 25 12 24 7 9 1 19 11 14 8 6 0 23 16 7 1 7 10 7 3 19 14 3 7 9 11 5 7 16 28 21 15 29 11 20 9 25 34 16 9 21 7 11 10 22 12 39 7 7 21 18 13 0 0 1
>BC003134\BC003134\554..1264\711\AAH03134.1\Homo sapiens\Homo sapiens achaete-scute complex-like 1 (Drosophila), mRNA (cDNAclone MGC:3624 IMAGE:2821173), complete cds./gene="ASCL1"/codon_start=1/product="achaete-scute complex homolog-like 1"/protein_id="AAH03134.1"/db_xref="GI:13111927"/db_xref="GeneID:429"/db_xref="MIM:100790"
1 10 2 0 1 0 0 3 10 2 0 2 3 4 7 3 7 1 1 3 1 0 0 11 8 0 6 17 13 0 0 12 1 1 0 7 3 0 1 8 10 0 1 29 2 1 2 11 7 0 5 0 1 1 6 3 0 2 0 5 1 0 0 1
>BC066907\BC066907\23..1381\1359\AAH66907.1\Homo sapiens\Homo sapiens ethanolamine kinase 1, mRNA (cDNA clone MGC:87084IMAGE:5260109), complete cds./gene="ETNK1"/codon_start=1/product="ethanolamine kinase 1"/protein_id="AAH66907.1"/db_xref="GI:45219773"/db_xref="GeneID:55500"
4 4 5 4 3 3 6 11 12 7 3 5 2 8 1 6 3 8 3 6 1 6 7 9 4 6 9 16 2 10 10 8 7 2 6 14 11 6 9 11 8 15 6 14 4 8 14 16 5 14 10 9 5 4 10 12 4 7 14 7 8 1 0 0
>HSA512835\AJ512835\108..1424\1317\CAD55563.1\Homo sapiens\Homo sapiens mRNA for putative calcium binding transporter (ORF1)./codon_start=1/product="putative calcium binding transporter"/protein_id="CAD55563.1"/db_xref="GI:28551967"/db_xref="GOA:Q86Y43"/db_xref="InterPro:IPR001993"/db_xref="InterPro:IPR002048"/db_xref="InterPro:IPR002067"/db_xref="InterPro:IPR002167"/db_xref="UniProt/TrEMBL:Q86Y43"
3 13 11 3 1 5 1 9 34 5 0 4 6 7 3 2 5 4 6 8 7 1 3 6 3 2 4 17 2 6 2 22 9 8 1 8 15 0 3 14 7 5 6 19 6 4 5 23 20 6 7 5 4 0 10 2 3 14 8 11 10 1 0 0
>BC033082\BC033082\741..1604\864\AAH33082.1\Homo sapiens\Homo sapiens KIAA1922 protein, mRNA (cDNA clone MGC:45647IMAGE:2960715), complete cds./gene="KIAA1922"/codon_start=1/product="KIAA1922 protein"/protein_id="AAH33082.1"/db_xref="GI:23138751"/db_xref="GeneID:114819"
2 12 15 1 3 17 1 3 21 2 0 0 2 1 0 1 20 3 1 4 0 0 3 3 1 5 4 16 3 4 4 9 4 2 0 2 8 1 2 12 2 0 5 21 5 1 4 27 7 1 1 2 5 1 0 0 0 1 0 4 8 0 1 0
>BC009404\BC009404\15..809\795\AAH09404.1\Homo sapiens\Homo sapiens ribosomal protein S3A, mRNA (cDNA clone MGC:15425IMAGE:4308955), complete cds./gene="RPS3A"/codon_start=1/product="ribosomal protein S3a"/protein_id="AAH09404.1"/db_xref="GI:14424796"/db_xref="GeneID:6189"/db_xref="MIM:180478"
2 3 2 3 3 1 0 4 4 5 0 5 0 1 0 6 1 3 3 7 2 5 4 1 0 2 3 2 1 7 7 5 1 7 1 7 6 9 20 18 4 6 5 7 2 3 12 3 5 12 1 4 2 2 5 5 3 2 7 11 2 1 0 0
>AK126051\AK126051\1..2937\2937\BAC86413.1\Homo sapiens\Homo sapiens cDNA FLJ44063 fis, clone TESTI4035637./codon_start=1/protein_id="BAC86413.1"/db_xref="GI:34532396"
2 0 0 0 14 7 10 6 8 9 26 19 35 16 3 32 13 20 31 6 1 25 22 5 0 17 13 7 0 14 11 4 5 5 18 7 17 31 72 30 14 44 35 12 5 9 58 27 10 48 0 21 2 11 10 21 27 9 39 14 1 0 0 1
>HUMPRPC\K03204\38..1033\996\AAA60185.1\Homo sapiens\Human PRB1 locus salivary proline-rich protein mRNA, clone cP3,complete cds./gene="PRB1"/codon_start=1/protein_id="AAA60185.1"/db_xref="GI:190486"/db_xref="GDB:G00-119-511"
5 1 0 0 3 0 1 0 5 0 1 2 2 7 0 4 3 4 0 0 0 0 60 31 0 30 4 3 0 3 40 11 2 10 0 1 1 0 4 16 10 4 40 12 0 0 4 0 3 1 0 0 0 0 0 0 1 0 1 1 0 0 0 1
>AB020592\AB020592\166..1245\1080\BAB18742.1\Homo sapiens\Homo sapiens HspBP mRNA for heat shock protein binding protein,complete cds./gene="HspBP"/codon_start=1/product="heat shock protein binding protein"/protein_id="BAB18742.1"/db_xref="GI:11559220"
4 8 9 2 0 3 1 8 41 1 0 2 5 6 3 4 6 2 2 3 2 1 4 7 4 3 4 17 7 5 2 18 9 3 0 4 14 0 2 6 4 2 2 29 7 1 6 28 13 1 2 0 7 6 9 1 0 4 0 13 2 0 0 1
>AF259792\AF259792\193..4653\4461\AAG36928.1\Homo sapiens\Homo sapiens p250R mRNA, complete cds./codon_start=1/product="p250R"/protein_id="AAG36928.1"/db_xref="GI:11527189"/IGNORED_CODON=1
10 13 4 8 14 18 5 13 41 15 5 23 18 35 13 23 54 25 10 19 10 17 51 52 22 40 34 25 12 22 27 40 34 15 4 21 25 10 28 42 43 16 21 93 19 9 30 56 42 27 28 17 9 7 14 20 7 28 16 74 12 0 0 1
>BT020103\BT020103\1..900\900\AAV38906.1\Homo sapiens\Homo sapiens F11 receptor mRNA, complete cds./codon_start=1/product="F11 receptor"/protein_id="AAV38906.1"/db_xref="GI:54697068"
2 1 5 2 3 1 0 4 10 2 0 7 4 8 3 9 6 4 11 9 1 6 3 6 0 8 4 7 2 3 5 6 9 2 1 9 15 4 5 11 5 8 3 2 2 0 10 9 5 4 5 6 4 3 7 6 2 8 4 5 3 0 1 0
>AB062402\AB062402\189..740\552\BAB93489.1\Homo sapiens\Homo sapiens OK/SW-cl.84 mRNA for ferritin-heavy polypeptide 1,complete cds./gene="OK/SW-cl.84"/codon_start=1/product="ferritin-heavy polypeptide 1"/protein_id="BAB93489.1"/db_xref="GI:21104438"
2 4 0 0 0 1 1 2 10 2 1 6 2 3 1 3 2 1 1 4 1 1 1 2 0 0 2 6 3 2 2 2 1 2 0 0 5 1 8 5 6 6 2 8 5 5 7 9 10 5 8 1 0 3 1 5 0 5 1 5 1 1 0 0
>AL356356#6\AL356356\join(15278..15316,16226..16250,17936..17987,19673..19751, 24792..25009,25764..25926,26159..26296,26478..26555, 31597..31697,31894..31995,32168..32240,32853..32967, 34178..34326)\1332\CAI15490.1\Homo sapiens\Human DNA sequence from clone RP11-54A4 on chromosome 1 Containsthe 3' end of the gene for a novel protein (KIAA0460), the gene forthreonyl-tRNA synthetase (FLJ12528), the ECM1 gene forextracellular matrix protein 1, the TSRC1 gene for thrombospondinrepeat containing 1, two novel genes, the MCL1 gene for myeloidcell leukemia sequence 1 (BCL2-related), the ENSA gene forendosulfine alpha, the 3' end of the gene for GPP34-related protein(GPP34R) and two CpG islands, complete sequence./gene="TARSL1"/locus_tag="RP11-54A4.9-012"/standard_name="OTTHUMP00000014941"/codon_start=1/product="threonyl-tRNA synthetase-like 1"/protein_id="CAI15490.1"/db_xref="GI:55958998"/db_xref="GOA:Q5T5E9"/db_xref="InterPro:IPR002314"/db_xref="InterPro:IPR002320"/db_xref="InterPro:IPR004154"/db_xref="InterPro:IPR006195"/db_xref="UniProt/TrEMBL:Q5T5E9"
5 3 11 4 6 4 5 10 28 9 0 3 1 7 1 8 6 6 9 4 2 5 8 9 2 7 9 16 1 6 11 9 10 7 0 6 13 3 5 8 6 3 4 25 11 6 15 13 15 11 4 6 7 4 15 8 0 5 6 4 8 0 0 1
>HUMENOA\M14328\95..1399\1305\AAA52387.1\Homo sapiens\Human alpha enolase mRNA, complete cds./gene="ENO1"/codon_start=1/protein_id="AAA52387.1"/db_xref="GI:182114"
1 5 1 1 3 6 1 10 20 2 0 3 3 5 2 11 3 2 4 5 0 9 4 8 1 3 4 19 5 15 4 11 13 10 2 12 12 7 11 27 14 10 1 10 3 3 9 20 14 12 7 4 6 0 12 5 0 19 8 9 3 1 0 0
>AL359553#2\AL359553\join(5268..5398,7097..7248,8958..9235,10804..11013, 16292..16450,16800..16869,17967..18022)\1056\CAC19798.1\Homo sapiens\Human DNA sequence from clone RP5-871G17 on chromosome 1 Containsthe 3' end of the HAO2 gene for hydroxyacid oxidase 2 (long chain),the HSD3B2 gene for hydroxy-delta-5-steroid dehydrogenase 3 beta-and steroid delta-isomerase 2, two glyceraldehyde-3-phosphatedehydrogenase (GAPD) pseudogenes and two hydroxy-delta-5-steroiddehydrogenase 3 beta- and steroid delta-isomerase family (HSD3B)pseudogenes, complete sequence./gene="HAO2"/locus_tag="RP5-871G17.1-002"/standard_name="OTTHUMP00000014486"/codon_start=1/product="hydroxyacid oxidase 2 (long chain)"/protein_id="CAC19798.1"/db_xref="GI:12043434"/db_xref="Genew:4810"/db_xref="GOA:Q9NYQ3"/db_xref="HSSP:1GOX"/db_xref="InterPro:IPR000262"/db_xref="InterPro:IPR003009"/db_xref="InterPro:IPR008259"/db_xref="UniProt/Swiss-Prot:Q9NYQ3"
7 1 4 1 5 6 3 5 9 9 3 11 3 6 1 3 7 1 12 3 1 7 2 3 1 6 8 7 2 12 3 6 8 7 4 7 8 4 7 8 8 6 4 11 3 5 9 9 7 13 3 2 6 4 5 7 3 13 13 4 5 1 0 0
>AF343078\AF343078\67..1803\1737\AAK38647.1\Homo sapiens\Homo sapiens TOB3 mRNA, complete cds./codon_start=1/product="TOB3"/protein_id="AAK38647.1"/db_xref="GI:13752411"
4 15 19 4 2 8 1 11 36 6 1 6 2 8 5 1 11 2 5 11 10 2 2 12 8 2 5 38 13 8 4 16 16 2 0 9 17 3 6 31 8 8 6 33 11 1 7 43 24 2 6 4 2 2 11 6 2 13 2 18 7 0 0 1
>BC011855\BC011855\2..1444\1443\AAH11855.1\Homo sapiens\Homo sapiens DnaJ (Hsp40) homolog, subfamily A, member 3, mRNA(cDNA clone MGC:20326 IMAGE:4139881), complete cds./gene="DNAJA3"/codon_start=1/product="DnaJ (Hsp40) homolog, subfamily A, member 3"/protein_id="AAH11855.1"/db_xref="GI:15080163"/db_xref="GeneID:9093"/db_xref="MIM:608382"
4 4 7 2 4 11 1 3 12 5 1 5 3 12 2 6 15 2 10 11 8 3 1 10 3 13 8 16 3 7 12 22 11 5 0 6 21 3 11 22 8 3 2 19 6 3 5 21 10 11 11 6 5 6 14 7 5 14 6 10 3 0 0 1
>BC026307\BC026307\157..2136\1980\AAH26307.1\Homo sapiens\Homo sapiens chromosome 18 open reading frame 9, mRNA (cDNA cloneMGC:26034 IMAGE:4792211), complete cds./gene="C18orf9"/codon_start=1/product="hypothetical protein LOC79959"/protein_id="AAH26307.1"/db_xref="GI:20072843"/db_xref="GeneID:79959"
12 1 3 8 13 6 1 7 16 22 15 10 13 7 4 9 3 7 18 4 3 16 16 5 1 19 16 9 1 15 18 5 4 10 12 4 10 19 23 7 7 13 14 15 7 10 38 12 7 22 5 13 3 20 5 23 10 9 12 13 9 0 1 0
>AF149722\AF149722\199..831\633\AAF37422.1\Homo sapiens\Homo sapiens ING1 tumor suppressor, variant B (ING1) mRNA, completecds./gene="ING1"/codon_start=1/product="ING1 tumor suppressor, variant B"/protein_id="AAF37422.1"/db_xref="GI:7158367"
1 6 4 1 0 3 0 2 8 0 0 0 1 6 2 1 6 0 2 2 2 0 0 9 0 1 0 5 8 1 0 10 3 0 1 1 8 1 5 18 13 2 0 10 5 1 1 19 13 1 3 1 5 3 3 0 0 6 0 4 2 0 1 0
>HSU43784\U43784\23..1171\1149\AAC50428.1\Homo sapiens\Human mitogen activated protein kinase activated protein kinase-3mRNA, complete cds./codon_start=1/product="mitogen activated protein kinase activated protein kinase-3"/protein_id="AAC50428.1"/db_xref="GI:1256005"
2 4 7 1 2 5 1 10 16 2 0 5 3 5 1 5 4 1 5 8 2 6 5 12 3 4 6 12 0 5 2 18 4 7 3 6 11 1 4 22 12 2 2 20 7 5 7 20 15 6 7 6 5 4 7 3 1 11 5 12 5 0 1 0
>AF369951\AF369951\83..442\360\AAM21294.1\Homo sapiens\Homo sapiens lung cancer oncogene 1 mRNA, complete cds./codon_start=1/product="lung cancer oncogene 1"/protein_id="AAM21294.1"/db_xref="GI:20385454"
0 1 7 3 0 2 1 2 5 2 2 2 0 1 0 0 1 0 1 1 2 0 3 3 4 1 1 2 1 3 2 3 0 2 1 0 2 0 4 2 2 0 0 1 0 3 7 2 3 4 3 6 1 0 2 7 1 4 3 3 0 0 0 1
>AK131264\AK131264\538..2541\2004\BAD18442.1\Homo sapiens\Homo sapiens cDNA FLJ16197 fis, clone CTONG1000113, highly similarto ZINC FINGER PROTEIN 184./codon_start=1/protein_id="BAD18442.1"/db_xref="GI:47077016"
3 2 3 1 17 4 4 6 6 12 2 3 12 7 0 13 12 13 13 11 1 25 14 6 1 10 2 11 2 7 17 7 11 5 5 2 8 3 45 17 12 18 15 30 9 36 44 21 6 13 5 14 4 32 10 15 8 4 18 4 6 0 0 1
>BC060810\BC060810\674..2020\1347\AAH60810.1\Homo sapiens\Homo sapiens G protein-coupled receptor 172B, mRNA (cDNA cloneMGC:71649 IMAGE:30348722), complete cds./gene="GPR172B"/codon_start=1/product="G protein-coupled receptor 172B"/protein_id="AAH60810.1"/db_xref="GI:38511970"/db_xref="GeneID:55065"/db_xref="MIM:607883"
0 2 4 2 1 2 4 9 52 8 1 8 6 6 1 8 9 4 2 12 1 5 11 15 3 12 15 27 2 7 3 19 10 13 5 5 37 2 1 4 3 3 4 9 7 3 4 12 5 0 4 2 4 8 16 5 0 6 0 8 7 0 0 1
>BC016914\BC016914\88..705\618\AAH16914.1\Homo sapiens\Homo sapiens zinc finger, CCHC domain containing 4, mRNA (cDNAclone MGC:21108 IMAGE:4423672), complete cds./gene="ZCCHC4"/codon_start=1/product="ZCCHC4 protein"/protein_id="AAH16914.1"/db_xref="GI:16877315"/db_xref="GeneID:29063"
3 0 3 0 8 4 0 2 8 6 4 11 3 2 0 2 2 2 4 2 1 3 3 5 1 4 1 7 0 4 4 0 2 2 3 1 5 2 3 9 3 3 4 10 1 4 7 4 4 7 1 3 1 9 2 8 0 1 4 1 2 0 1 0
>AF006740\AF006740\57..1709\1653\AAC39545.1\Homo sapiens\Homo sapiens Coch-5B2 mRNA, complete cds./gene="Coch-5B2"/codon_start=1/protein_id="AAC39545.1"/db_xref="GI:2801413"
4 4 1 0 10 3 6 4 10 4 3 5 4 9 2 13 10 6 16 4 2 10 5 7 3 10 11 14 1 20 15 15 10 11 15 11 13 11 21 14 11 13 6 11 2 7 14 12 7 21 3 9 4 7 17 18 8 14 14 10 5 1 0 0
>AF516142\AF516142\16..1446\1431\AAP47194.1\Homo sapiens\Homo sapiens proton-coupled amino acid transporter (PAT1) mRNA,complete cds./gene="PAT1"/codon_start=1/product="proton-coupled amino acid transporter"/protein_id="AAP47194.1"/db_xref="GI:31324239"
3 4 3 1 2 3 1 20 39 1 2 6 3 16 2 0 17 0 6 15 4 1 4 11 4 6 3 10 4 6 7 14 8 4 0 10 21 5 6 5 12 10 3 10 10 0 6 10 10 3 14 5 8 5 19 14 4 33 6 12 5 0 1 0
>AY823524\AY823524\12..1391\1380\AAW22617.1\Homo sapiens\Homo sapiens protection of telomeres protein 1 variant 5 mRNA,complete cds, alternatively spliced./codon_start=1/product="protection of telomeres protein 1 variant 5"/protein_id="AAW22617.1"/db_xref="GI:56693613"
2 3 2 1 6 5 10 3 9 14 10 13 14 0 0 12 7 5 13 6 1 12 11 3 2 5 10 5 0 2 11 4 0 9 8 6 6 14 20 11 4 15 14 11 3 13 11 8 8 16 4 14 3 7 2 15 8 8 9 6 5 1 0 0
>BC007775\BC007775\15..899\885\AAH07775.1\Homo sapiens\Homo sapiens zinc finger protein 346, mRNA (cDNA clone MGC:12633IMAGE:4301820), complete cds./gene="ZNF346"/codon_start=1/product="zinc finger protein 346"/protein_id="AAH07775.1"/db_xref="GI:14043595"/db_xref="GeneID:23567"/db_xref="MIM:605308"
0 5 1 0 5 2 3 3 8 1 2 4 4 7 2 1 8 0 3 7 2 3 4 4 3 4 6 9 5 4 3 6 5 2 0 4 11 1 11 20 9 1 6 18 6 6 6 11 12 1 6 3 7 4 4 3 3 3 3 8 1 0 1 0
>AF059252\AF059252\130..1320\1191\AAC78603.1\Homo sapiens\Homo sapiens clone 1 HLA class III protein Dom3z (DOM3Z) mRNA,complete cds./gene="DOM3Z"/codon_start=1/product="HLA class III protein Dom3z"/protein_id="AAC78603.1"/db_xref="GI:3372630"
3 5 10 3 3 6 3 13 18 3 0 1 3 6 1 8 7 2 8 7 3 4 12 17 5 12 5 12 0 8 7 10 7 3 3 6 8 5 6 8 8 3 4 13 7 2 6 17 14 6 12 5 6 2 12 7 2 0 0 9 10 0 1 0
>HSA400854\AJ400854\72..3716\3645\CAC14139.1\Homo sapiens\Homo sapiens mRNA for MUC4 protein splice variant sv17 (MUC4 gene)./gene="MUC4"/codon_start=1/product="MUC4 protein splice variant sv17"/protein_id="CAC14139.1"/db_xref="GI:10944947"/db_xref="UniProt/TrEMBL:Q9H485"
3 3 8 2 9 18 8 20 17 15 3 1 69 52 4 42 29 22 108 75 11 41 40 25 9 27 25 35 7 23 31 16 21 15 10 19 15 12 9 12 15 8 21 35 20 11 22 27 24 7 4 3 3 2 23 8 13 15 9 21 12 0 1 0
>BT007295\BT007295\1..828\828\AAP35959.1\Homo sapiens\Homo sapiens zinc finger protein 339 mRNA, complete cds./codon_start=1/product="zinc finger protein 339"/protein_id="AAP35959.1"/db_xref="GI:30583429"
0 7 2 3 2 5 1 5 17 1 0 0 0 3 5 2 17 2 5 9 2 0 1 9 4 1 4 7 2 0 3 18 3 0 0 7 6 1 10 13 5 2 0 11 12 2 1 16 11 4 5 2 10 2 7 1 0 3 1 2 1 0 1 0
>AK023886\AK023886\306..2129\1824\BAB14712.1\Homo sapiens\Homo sapiens cDNA FLJ13824 fis, clone THYRO1000505./codon_start=1/protein_id="BAB14712.1"/db_xref="GI:10435959"
2 14 16 6 1 6 5 19 61 4 0 8 3 9 1 2 21 6 7 9 3 5 6 24 2 7 4 23 4 7 2 15 13 2 1 5 25 1 1 22 16 3 4 30 9 2 5 48 20 5 8 6 8 4 19 5 2 14 2 20 5 0 0 1
>BC025305\BC025305\48..1664\1617\AAH25305.1\Homo sapiens\Homo sapiens cisplatin resistance related protein CRR9p, mRNA (cDNAclone MGC:39275 IMAGE:3051368), complete cds./gene="CRR9"/codon_start=1/product="cisplatin resistance related protein CRR9p"/protein_id="AAH25305.1"/db_xref="GI:19263702"/db_xref="GeneID:81037"
1 7 9 0 3 3 0 10 41 2 2 5 5 13 0 4 11 3 2 19 9 3 3 10 5 4 4 14 8 5 2 7 11 4 2 19 28 3 10 24 15 5 0 15 9 5 6 18 16 11 23 5 5 1 21 18 1 17 4 15 13 0 0 1
>BC040152\BC040152\208..501\294\AAH40152.1\Homo sapiens\Homo sapiens dolichyl pyrophosphate phosphatase 1, mRNA (cDNA cloneIMAGE:5752769), complete cds./gene="DOLPP1"/codon_start=1/product="DOLPP1 protein"/protein_id="AAH40152.1"/db_xref="GI:25304089"/db_xref="GeneID:57171"
1 1 1 0 2 4 2 5 6 1 1 1 0 7 0 0 3 0 2 1 2 0 0 2 0 1 1 3 0 1 1 0 1 0 2 3 2 0 1 1 4 0 2 2 2 1 1 2 2 0 2 2 0 0 8 2 0 1 1 3 3 0 0 1
>AL356280#2\AL356280\join(complement(150364..150432), complement(AL359760.10:67552..67698), complement(AL359760.10:61345..61500), complement(AL359760.10:55699..55918), complement(AL359760.10:36749..36855), complement(AL359760.10:34911..35588))\69\CAI16873.1\Homo sapiens\Human DNA sequence from clone RP11-82O2 on chromosome 1 Containsthe 5' end of the OLFM3 gene for olfactomedin 3 and a DNAJ familypseudogene, complete sequence./gene="OLFM3"/locus_tag="RP11-556K13.2-003"/standard_name="OTTHUMP00000012614"/codon_start=1/product="olfactomedin 3"/protein_id="CAI16873.1"/db_xref="GI:55959089"
1 1 0 0 14 6 14 6 13 9 16 5 10 6 1 10 2 10 7 1 1 11 10 3 0 11 2 4 1 3 6 4 2 4 2 5 7 8 29 10 6 13 15 8 3 2 7 4 3 5 8 16 4 7 7 27 11 5 8 6 9 10 7 13
>AK057341\AK057341\81..1547\1467\BAB71436.1\Homo sapiens\Homo sapiens cDNA FLJ32779 fis, clone TESTI2002090./codon_start=1/protein_id="BAB71436.1"/db_xref="GI:16552997"
1 0 0 1 11 3 7 3 5 14 17 15 14 3 0 6 6 12 14 5 2 8 15 1 3 8 7 0 0 6 6 0 1 0 7 5 10 9 23 10 8 16 14 5 3 6 33 17 5 20 7 9 2 12 9 19 9 4 16 11 5 0 0 1
>HS323M22A\AL096886\90..1361\1272\CAB51469.1\Homo sapiens\Novel human gene mapping to chomosome 22./codon_start=1/product="hypothetical protein"/protein_id="CAB51469.1"/db_xref="GI:5596697"/db_xref="GOA:O95922"/db_xref="UniProt/Swiss-Prot:O95922"
3 3 7 2 6 2 1 11 22 2 1 2 3 6 4 6 8 5 4 12 2 2 5 3 6 3 3 6 3 4 4 8 9 3 2 8 15 4 10 26 17 11 4 7 5 3 13 14 20 4 15 7 5 2 7 8 1 21 4 8 11 0 0 1
>AB065858\AB065858\201..1208\1008\BAC06076.1\Homo sapiens\Homo sapiens gene for seven transmembrane helix receptor, completecds, isolate:CBRC7TM_421./codon_start=1/evidence=not_experimental/product="seven transmembrane helix receptor"/protein_id="BAC06076.1"/db_xref="GI:21928981"
1 5 0 0 1 3 4 14 17 7 1 3 1 11 0 9 7 2 4 5 0 6 3 4 0 5 6 16 1 8 3 7 5 3 0 13 3 3 3 6 4 5 3 5 8 6 2 4 3 4 5 8 6 5 10 10 4 24 12 14 3 1 0 0
>BC008316\BC008316\68..1045\978\AAH08316.1\Homo sapiens\Homo sapiens LRP16 protein, mRNA (cDNA clone MGC:15615IMAGE:3342973), complete cds./gene="LRP16"/codon_start=1/product="LRP16 protein"/protein_id="AAH08316.1"/db_xref="GI:14249877"/db_xref="GeneID:28992"
2 9 11 1 0 3 1 9 24 1 0 1 0 6 2 1 12 2 3 9 3 2 0 13 4 0 1 18 16 2 3 13 8 3 0 4 16 1 4 19 2 1 0 8 5 2 1 17 14 0 7 2 7 2 6 3 0 12 1 3 5 0 0 1
>BC002683\BC002683\130..558\429\AAH02683.1\Homo sapiens\Homo sapiens neuritin 1, mRNA (cDNA clone MGC:3391 IMAGE:3605775),complete cds./gene="NRN1"/codon_start=1/product="neuritin, precursor"/protein_id="AAH02683.1"/db_xref="GI:12803695"/db_xref="GeneID:51299"/db_xref="MIM:607409"
0 0 0 0 3 0 0 7 7 3 2 2 1 3 2 1 4 0 2 2 3 0 0 0 3 0 2 3 9 1 1 8 3 0 0 2 6 0 4 6 6 0 2 3 1 0 3 1 4 5 2 2 5 1 5 1 1 3 1 3 3 0 0 1
>HUMRASAD\M31470\1..642\642\AAA36547.1\Homo sapiens\Human ras-like protein mRNA, complete cds, clone TC10./codon_start=1/protein_id="AAA36547.1"/db_xref="GI:190881"
1 1 0 1 3 1 3 5 3 2 7 1 3 0 1 1 4 0 0 4 3 5 4 5 2 2 5 6 2 3 8 5 3 0 4 5 9 1 9 7 2 4 2 5 3 0 6 6 7 5 5 4 5 5 4 3 7 1 3 6 1 0 0 1
>AF302493\AF302493\71..2092\2022\AAQ14492.1\Homo sapiens\Homo sapiens endocrine transmitter regulatory protein mRNA,complete cds./codon_start=1/product="endocrine transmitter regulatory protein"/protein_id="AAQ14492.1"/db_xref="GI:33340033"
3 8 9 4 9 14 7 10 27 7 5 9 6 13 3 10 14 19 5 10 3 15 11 4 1 8 7 15 0 8 13 12 12 13 4 6 24 6 27 36 7 12 6 24 6 11 28 28 18 18 10 6 7 4 5 12 6 14 6 17 11 0 0 1
>AL671561#7\AL671561\join(41671..41676,42468..42549,42679..42948,43175..43450, 44050..44325,44448..44564,45010..45014)\1032\CAI17562.1\Homo sapiens\Human DNA sequence from clone XXbac-209H21 on chromosome 6 containsa HLA (MHC) class 1 pseudogene, a putative novel MHC class 1 (HLA)protein (fragment), a 60S ribosomal protein L7A (RPL7A) pseudogene,a P5-1 pseudogene, the HLA-G gene for histompatibility antigen,class I, G, a major histocompatibility complex, class I, Hpseudogene (HLA-H, HLAHP) and five CpG islands, complete sequence./gene="HLA-G"/locus_tag="XXbac-BCX209H21.15-001"/standard_name="OTTHUMP00000029630"/codon_start=1/product="HLA-G histocompatibility antigen, class I, G"/protein_id="CAI17562.1"/db_xref="GI:55961745"/db_xref="GOA:Q5RIS3"/db_xref="InterPro:IPR001039"/db_xref="InterPro:IPR003006"/db_xref="InterPro:IPR003597"/db_xref="InterPro:IPR007110"/db_xref="UniProt/TrEMBL:Q5RIS3"
1 8 5 0 5 7 1 9 19 1 0 0 1 7 2 3 4 1 2 15 4 3 2 8 4 4 6 12 9 8 4 8 9 2 1 5 15 2 0 11 5 1 1 16 6 3 3 24 13 5 9 5 4 2 7 1 1 6 1 11 11 0 0 1
>BC007515\BC007515\47..277\231\AAH07515.1\Homo sapiens\Homo sapiens heat shock factor binding protein 1, mRNA (cDNA cloneMGC:4536 IMAGE:3010737), complete cds./gene="HSBP1"/codon_start=1/product="heat shock factor binding protein 1"/protein_id="AAH07515.1"/db_xref="GI:13960151"/db_xref="GeneID:3281"/db_xref="MIM:604553"
0 1 0 0 1 0 0 3 3 0 0 0 0 0 1 1 0 4 2 3 1 1 0 1 0 1 0 2 1 1 0 0 2 0 0 0 4 0 1 4 1 1 2 7 0 0 5 1 4 5 0 0 0 0 0 1 1 2 3 5 0 0 0 1
>AF104938\AF104938\217..3588\3372\AAD54676.1\Homo sapiens\Homo sapiens lectomedin-1 beta (LEC1) mRNA, complete cds./gene="LEC1"/codon_start=1/product="lectomedin-1 beta"/protein_id="AAD54676.1"/db_xref="GI:5880492"
14 2 3 4 14 11 9 11 23 25 13 14 26 9 0 15 18 16 32 23 4 26 21 10 1 20 27 11 2 36 27 16 9 13 10 13 30 21 33 22 25 34 13 23 11 7 43 13 21 31 20 31 20 14 29 32 16 18 46 23 19 0 0 1
>AF277194\AF277194\46..495\450\AAK07549.1\Homo sapiens\Homo sapiens PNAS-136 mRNA, complete cds./codon_start=1/product="PNAS-136"/protein_id="AAK07549.1"/db_xref="GI:12751113"/IGNORED_CODON=1
3 0 0 0 4 1 2 4 8 2 0 1 2 3 0 2 1 1 4 3 1 3 0 0 0 3 3 1 1 3 3 1 0 2 0 1 4 3 7 9 2 3 3 2 0 1 5 4 4 3 3 1 1 2 4 6 4 3 3 7 1 0 0 1
>AY804140\AY804140\39..815\777\AAW78745.1\Homo sapiens\Homo sapiens MHC class II antigen (HLA-DPB1) mRNA,HLA-DPB1-DPB1*1401 allele, complete cds./gene="HLA-DPB1"/allele="DPB1*1401"/codon_start=1/product="MHC class II antigen"/protein_id="AAW78745.1"/db_xref="GI:58532285"
3 3 7 1 2 4 0 3 17 1 2 1 0 3 0 5 5 2 6 6 3 1 2 4 1 3 3 4 4 3 6 4 7 0 1 7 17 4 1 8 6 4 3 14 7 0 3 14 9 3 8 0 4 1 9 1 0 7 1 6 4 1 0 0
>AF525416\AF525416\132..1646\1515\AAP80792.1\Homo sapiens\Homo sapiens unnamed C1q domain protein mRNA, complete cds./codon_start=1/product="unnamed C1q domain protein"/protein_id="AAP80792.1"/db_xref="GI:32401237"
4 0 2 3 9 2 2 3 11 10 5 1 13 7 1 20 11 11 8 9 3 17 19 6 3 19 20 8 0 8 16 6 3 11 7 5 9 7 6 5 8 22 20 20 3 5 12 8 8 11 4 15 3 4 6 17 5 0 10 9 4 0 0 1
>S65701\S65701\14..85\72\AAB28213.1\Homo sapiens\CRK=proto-oncogene {intron/exon junction} [human, Genomic, 85 nt]./gene="CRK"/codon_start=1/protein_id="AAB28213.1"/db_xref="GI:430793"
1 0 0 0 1 0 0 1 1 0 1 1 1 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 1 1 0 2 1 0 0 0 1 1 1 0 0 0 0 0 0 0
>BC093046\BC093046\81..1859\1779\AAH93046.1\Homo sapiens\Homo sapiens signal peptide peptidase-like 2B, mRNA (cDNA cloneMGC:111084 IMAGE:30395602), complete cds./gene="SPPL2B"/codon_start=1/product="signal peptide peptidase-like 2B"/protein_id="AAH93046.1"/db_xref="GI:62202483"/db_xref="GeneID:56928"/db_xref="MIM:608239"
0 8 9 6 0 9 1 23 43 3 0 2 3 15 2 3 14 2 2 10 12 1 8 21 13 7 6 35 16 7 3 23 12 2 3 11 38 1 7 14 9 1 0 21 5 1 4 17 20 3 18 4 16 3 24 4 0 18 3 16 10 0 1 0
>BT019813\BT019813\1..732\732\AAV38616.1\Homo sapiens\Homo sapiens CD48 antigen (B-cell membrane protein) mRNA, completecds./codon_start=1/product="CD48 antigen (B-cell membrane protein)"/protein_id="AAV38616.1"/db_xref="GI:54696488"
0 0 1 0 3 4 3 3 14 6 1 3 2 6 1 5 7 4 0 10 2 4 3 4 0 6 2 1 0 1 1 5 2 3 5 7 10 0 9 10 7 4 5 4 1 2 7 7 6 4 6 4 3 5 2 4 2 5 5 5 7 0 1 0
>HSU63289\U63289\138..1586\1449\AAC50895.1\Homo sapiens\Human RNA-binding protein CUG-BP/hNab50 (NAB50) mRNA, complete cds./gene="NAB50"/function="binds to (CUG)n triplet repeats"/codon_start=1/product="CUG-BP/hNab50"/protein_id="AAC50895.1"/db_xref="GI:1518802"
2 0 4 2 2 4 3 13 13 9 5 5 5 6 4 8 16 9 9 8 2 8 7 8 1 6 15 11 1 25 10 11 7 12 2 5 9 5 8 16 14 15 6 36 6 1 11 5 11 6 6 4 4 3 4 14 4 8 5 21 2 0 0 1
>BC042426\BC042426\431..907\477\AAH42426.1\Homo sapiens\Homo sapiens LIM domain only 2 (rhombotin-like 1), mRNA (cDNA cloneMGC:34396 IMAGE:5188482), complete cds./gene="LMO2"/codon_start=1/product="LMO2 protein"/protein_id="AAH42426.1"/db_xref="GI:27502791"/db_xref="GeneID:4005"/db_xref="MIM:180385"
0 2 6 1 2 2 0 7 9 1 0 0 1 3 1 1 2 0 2 0 0 1 2 1 0 1 1 5 0 0 0 4 4 3 1 0 6 0 4 6 2 1 1 6 2 1 4 6 12 1 6 3 9 5 3 1 2 7 1 4 2 0 1 0
>AY359018\AY359018\151..597\447\AAQ89377.1\Homo sapiens\Homo sapiens clone DNA73746 TKAL754 (UNQ754) mRNA, complete cds./locus_tag="UNQ754"/codon_start=1/product="TKAL754"/protein_id="AAQ89377.1"/db_xref="GI:37183154"
0 2 2 0 1 2 2 4 9 4 0 4 2 3 1 0 6 3 2 0 0 0 1 1 0 0 3 3 2 1 3 3 2 1 2 1 3 0 1 4 7 4 1 4 4 0 4 2 5 4 4 3 5 3 2 4 2 4 1 2 5 0 0 1
>BC014533\BC014533\7..642\636\AAH14533.3\Homo sapiens\Homo sapiens myelin expression factor 2, mRNA (cDNA cloneIMAGE:4133844), complete cds./gene="MYEF2"/codon_start=1/product="MYEF2 protein"/protein_id="AAH14533.3"/db_xref="GI:32425486"/db_xref="GeneID:50804"
4 1 1 3 9 1 2 0 4 1 1 2 2 4 1 0 6 5 1 0 0 3 4 0 0 1 3 1 1 2 24 7 2 13 1 2 1 2 8 1 2 7 0 3 0 1 6 5 3 9 1 0 1 2 1 12 9 2 3 19 1 1 0 0
>BC034296\BC034296\50..751\702\AAH34296.1\Homo sapiens\Homo sapiens hypothetical protein MGC35043, mRNA (cDNA cloneMGC:35043 IMAGE:5165558), complete cds./gene="MGC35043"/codon_start=1/product="hypothetical protein MGC35043"/protein_id="AAH34296.1"/db_xref="GI:21706729"/db_xref="GeneID:255119"
1 2 0 1 11 5 4 1 9 4 1 3 2 2 1 2 1 5 3 1 3 8 4 1 0 1 3 6 2 7 4 2 3 2 0 3 6 1 8 5 4 7 6 5 2 1 12 6 12 9 8 3 0 0 3 7 4 5 8 2 1 1 0 0
>AK128830\AK128830\1266..2633\1368\BAC87630.1\Homo sapiens\Homo sapiens cDNA FLJ46317 fis, clone TESTI4041832./codon_start=1/protein_id="BAC87630.1"/db_xref="GI:34536392"
3 1 2 14 28 17 1 1 20 0 0 0 0 15 0 0 1 16 3 0 0 1 3 29 0 17 2 7 16 1 24 23 34 1 0 16 30 1 0 17 0 0 1 8 0 1 15 36 2 0 0 1 0 15 1 0 0 0 0 1 30 0 1 0
>AY518541\AY518541\join(1953..2016,2351..2507,3966..4088,5361..5459, 7052..7145)\537\AAR89914.1\Homo sapiens\Homo sapiens endothelin 2 (EDN2) gene, complete cds./gene="EDN2"/codon_start=1/product="endothelin 2"/protein_id="AAR89914.1"/db_xref="GI:40786807"
2 5 5 1 2 7 1 4 6 4 0 1 1 11 0 1 3 1 5 5 0 4 4 2 1 5 2 11 2 3 2 4 3 0 0 4 4 1 0 7 2 0 3 6 2 3 3 5 5 0 2 0 7 2 3 1 0 2 1 2 5 0 1 0
>HUMCYCD3A\M92287\166..1044\879\AAA52137.1\Homo sapiens\Homo sapiens cyclin D3 (CCND3) mRNA, complete cds./gene="CCND3"/codon_start=1/product="cyclin D3"/protein_id="AAA52137.1"/db_xref="GI:181247"/db_xref="GDB:G00-128-969"
2 7 9 2 0 2 1 8 28 0 0 4 0 7 0 4 9 0 4 9 2 3 2 10 4 1 4 15 4 7 0 5 7 2 2 8 5 0 3 7 1 0 2 14 5 2 6 15 7 5 7 1 7 5 4 2 1 6 3 9 3 0 1 0
>AF242523\AF242523\6..725\720\AAF99603.1\Homo sapiens\Homo sapiens hypothetical transmembrane protein SBBI53 mRNA,complete cds./codon_start=1/product="hypothetical transmembrane protein SBBI53"/protein_id="AAF99603.1"/db_xref="GI:9802044"
3 2 4 1 2 1 3 4 5 5 6 11 1 1 0 2 4 0 5 5 0 1 7 4 1 4 2 7 1 1 7 5 2 7 2 4 5 3 3 0 6 5 2 7 2 0 6 4 2 4 6 4 1 1 12 19 4 5 6 8 4 1 0 0
>AB097031\AB097031\13..741\729\BAC77384.1\Homo sapiens\Homo sapiens mRNA for putative MAPK activating protein, completecds, clone: PM07./codon_start=1/product="putative MAPK activating protein"/protein_id="BAC77384.1"/db_xref="GI:31455517"
0 1 0 0 6 3 1 2 2 11 2 2 5 3 1 6 1 4 5 3 0 6 8 2 2 5 12 0 0 12 6 3 3 2 2 2 6 3 3 1 4 5 1 8 2 1 9 6 3 8 3 9 1 3 10 9 3 4 6 6 5 0 1 0
>HSA218C14#6\AL121894\complement(join(103487..103570,104825..104938, 107191..107433))\441\CAC05424.1\Homo sapiens\Human DNA sequence from clone RP11-218C14 on chromosome 20 Containsthe 3' end of a novel gene, two genes for novel proteins similar tocystatin 9-like (mouse) (CST9L), the CST9L gene for cystatin 9-like(mouse), a cystatin 9-like (mouse) pseudogene, the CST3 gene forcystatin C, a novel gene and a CpG island, complete sequence./gene="CST3"/locus_tag="RP11-218C14.4-001"/standard_name="OTTHUMP00000030440"/codon_start=1/protein_id="CAC05424.1"/db_xref="GI:9944241"/db_xref="Genew:2475"/db_xref="GOA:P01034"/db_xref="InterPro:IPR000010"/db_xref="UniProt/Swiss-Prot:P01034"
1 5 1 1 0 1 1 1 10 0 0 3 0 2 1 1 4 1 1 5 1 0 1 6 3 1 2 12 2 2 1 6 2 1 1 1 10 0 4 3 5 0 0 7 1 2 0 5 7 0 4 0 2 2 4 1 0 3 0 4 1 0 1 0
>HSY14768#14\Y14768\join(73051..73132,73401..73501,74029..74202)\357\CAA75073.1\Homo sapiens\Homo sapiens DNA, cosmid clones TN62 and TN82./gene="ATP6G"/codon_start=1/product="V-ATPase G-subunit like protein"/protein_id="CAA75073.1"/db_xref="GI:3805814"/db_xref="GOA:O95670"/db_xref="InterPro:IPR005124"/db_xref="UniProt/Swiss-Prot:O95670"
3 2 3 1 3 3 0 0 4 3 0 0 0 3 0 2 2 1 1 0 0 0 0 2 0 0 4 6 1 4 0 3 1 1 0 4 4 0 0 7 3 0 3 17 2 0 1 11 1 1 2 0 1 0 1 0 0 1 1 5 0 0 1 0
>HUMHBGFBV\M63888\1..1989\1989\AAA35959.1\Homo sapiens\Human heparin-binding growth factor receptor (HBGF-R-alpha-a2)mRNA, complete cds./gene="HBGF-R"/codon_start=1/product="heparin-binding growth factor receptor"/protein_id="AAA35959.1"/db_xref="GI:183881"
2 7 10 3 7 3 4 9 33 4 2 12 6 21 5 8 14 7 13 16 3 2 9 18 8 12 10 17 2 12 7 12 16 6 3 11 33 5 13 28 18 7 3 17 11 6 14 30 25 13 12 10 13 4 8 2 1 21 3 18 13 1 0 0
>HSH12\X57129\526..1167\642\CAA40408.1\Homo sapiens\H.sapiens H1.2 gene for histone H1./gene="H1.2"/codon_start=1/product="histone H1"/protein_id="CAA40408.1"/db_xref="GI:31968"/db_xref="GOA:P16403"/db_xref="UniProt/Swiss-Prot:P16403"
0 0 0 3 0 0 0 3 4 1 0 1 1 4 0 3 6 1 1 4 2 4 2 8 4 7 3 16 12 17 2 7 3 4 2 1 7 5 16 43 3 0 1 0 0 0 1 5 0 1 0 1 0 0 0 1 0 2 0 1 0 0 1 0
>AF230929\AF230929\227..1264\1038\AAG16780.1\Homo sapiens\Homo sapiens keratinocyte annexin-like protein pemphaxin mRNA,complete cds./function="may be involved in the regulation of keratinocyte cell adhesion"/codon_start=1/product="keratinocyte annexin-like protein pemphaxin"/protein_id="AAG16780.1"/db_xref="GI:10436074"
5 3 3 2 3 8 3 10 22 5 0 6 3 3 1 8 7 3 5 9 0 7 2 3 2 2 9 13 2 11 3 10 6 0 0 6 14 0 4 9 6 4 7 23 3 2 8 14 12 8 6 1 3 1 7 4 0 10 7 5 2 0 0 1
>BC062353\BC062353\27..908\882\AAH62353.1\Homo sapiens\Homo sapiens chromosome 1 open reading frame 131, mRNA (cDNA cloneMGC:71140 IMAGE:4648754), complete cds./gene="C1orf131"/codon_start=1/product="hypothetical protein LOC128061"/protein_id="AAH62353.1"/db_xref="GI:38565958"/db_xref="GeneID:128061"
0 0 3 2 8 6 3 2 6 4 2 4 2 7 3 6 4 4 9 1 3 0 4 6 2 7 5 4 1 11 9 2 3 5 2 0 6 7 17 23 6 7 5 9 2 2 19 8 4 7 2 2 0 1 4 4 3 5 6 4 0 0 0 1
>AF213041\AF213041\1..639\639\AAK06373.1\Homo sapiens\Homo sapiens isolate NT1 cyclin-dependent kinase associated proteinphosphatase mRNA, complete cds./codon_start=1/product="cyclin-dependent kinase associated protein phosphatase"/protein_id="AAK06373.1"/db_xref="GI:12734660"
3 0 1 0 9 0 6 3 4 7 3 1 12 1 0 5 3 2 4 5 0 2 5 1 1 2 3 2 0 4 5 0 4 3 2 2 1 3 7 3 1 4 7 4 1 6 8 5 7 6 4 3 4 8 1 5 10 3 3 2 1 1 0 0
>BC023995\BC023995\120..1010\891\AAH23995.1\Homo sapiens\Homo sapiens chromosome 2 open reading frame 25, mRNA (cDNA cloneMGC:24534 IMAGE:4103877), complete cds./gene="C2orf25"/codon_start=1/product="chromosome 2 open reading frame 25"/protein_id="AAH23995.1"/db_xref="GI:18645170"/db_xref="GeneID:27249"
4 1 0 1 5 2 2 4 5 5 5 3 6 1 2 5 2 7 5 1 0 11 7 2 0 7 9 4 0 8 8 1 3 7 6 1 7 9 9 5 5 10 5 4 1 7 20 4 4 11 2 5 4 5 4 13 3 2 7 6 4 0 1 0
>BC013795\BC013795\393..848\456\AAH13795.1\Homo sapiens\Homo sapiens hypothetical protein FLJ23560, mRNA (cDNA cloneIMAGE:3919095), complete cds./gene="FLJ23560"/codon_start=1/product="FLJ23560 protein"/protein_id="AAH13795.1"/db_xref="GI:15489408"/db_xref="GeneID:79738"
0 0 0 0 2 0 3 1 1 5 5 5 5 2 0 2 3 3 4 3 0 3 4 2 1 1 2 1 0 3 1 1 0 6 4 2 1 5 8 3 0 6 4 5 2 4 5 1 1 2 4 4 1 3 0 2 4 2 2 7 0 1 0 0
>AF038461\AF038461\260..2365\2106\AAC39770.1\Homo sapiens\Homo sapiens 12R-lipoxygenase mRNA, complete cds./function="converts arachidonic acid to 12R-HPETE (12R-hydroperoxyeicosatetraenoic acid)"/codon_start=1/product="12R-lipoxygenase"/protein_id="AAC39770.1"/db_xref="GI:3220166"
5 15 13 2 3 8 1 25 40 2 1 8 3 6 4 6 12 3 9 20 8 4 5 24 10 11 7 24 6 7 8 20 13 2 2 14 22 1 8 22 17 6 2 20 18 4 3 39 26 7 26 10 15 1 24 9 3 26 14 14 13 0 1 0
>AB011406\AB011406\177..1751\1575\BAA32129.1\Homo sapiens\Homo sapiens mRNA for alkalin phosphatase, complete cds./function="hydrolyze a variety of monophosphate esters with high pH optima"/standard_name="tissue non-specific alkalin phosphatase"/codon_start=1/evidence=experimental/product="alkalin phosphatase"/protein_id="BAA32129.1"/db_xref="GI:3401945"
2 4 5 2 3 5 1 11 26 4 2 4 3 11 3 3 9 2 4 19 6 6 3 15 2 6 5 29 6 8 4 22 12 7 2 11 25 1 10 18 20 7 2 12 18 5 5 24 27 2 16 5 3 3 14 2 0 13 5 15 5 0 0 1
>AF182422\AF182422\336..1019\684\AAG14958.1\Homo sapiens\Homo sapiens MDS023 (MDS023) mRNA, complete cds./gene="MDS023"/codon_start=1/product="MDS023"/protein_id="AAG14958.1"/db_xref="GI:10197644"
2 0 1 0 4 3 4 2 3 8 7 2 4 3 0 4 2 4 4 2 1 6 3 2 0 2 7 2 0 2 3 0 0 1 5 1 5 4 14 11 1 13 0 3 2 3 18 12 4 7 5 4 3 2 0 3 2 2 7 4 4 0 0 1
>HUMHBBPA6G#2\L48216\join(217..308,420..438)\111\AAA88064.1\Homo sapiens\Homo sapiens beta-globin (HBB) gene, with a to g mutation in thepoly-A signal, (J00179 bases 61971-63802)./gene="HBB"/codon_start=1/product="beta-globin"/protein_id="AAA88064.1"/db_xref="GI:1066776"/db_xref="GDB:G00-119-297"
0 0 0 0 0 0 1 0 3 0 0 0 0 1 0 1 0 1 0 0 0 2 0 0 0 2 0 3 0 0 0 2 0 2 0 0 3 2 0 2 1 0 0 0 2 0 1 3 0 1 0 0 0 0 0 1 0 0 0 1 1 0 1 0
>BC040061\BC040061\166..2994\2829\AAH40061.1\Homo sapiens\Homo sapiens protein kinase N1, transcript variant 2, mRNA (cDNAclone MGC:46204 IMAGE:5752583), complete cds./gene="PKN1"/codon_start=1/product="protein kinase C-like 1, isoform 2"/protein_id="AAH40061.1"/db_xref="GI:25304069"/db_xref="GeneID:5585"/db_xref="MIM:601032"
7 20 32 2 4 11 2 21 83 6 0 10 3 15 10 4 33 7 9 27 9 6 11 29 9 15 9 44 15 13 6 30 24 9 4 9 35 2 6 35 16 5 3 36 15 2 16 62 39 11 9 2 9 5 31 7 2 18 6 13 9 0 1 0
>HSA276674\AJ276674\join(10303..10421,11044..11172,11329..11429,11515..11736, 11896..12073,12951..13195,13572..13679,17109..17239)\1233\CAB82769.1\Homo sapiens\Homo sapiens PNR gene for photoreceptor-specific nuclear receptor,exons 1-8./gene="PNR"/function="unknown"/codon_start=1/product="photoreceptor-specific nuclear receptor"/protein_id="CAB82769.1"/db_xref="GI:7329721"/db_xref="GOA:Q9Y5X4"/db_xref="InterPro:IPR000003"/db_xref="InterPro:IPR000536"/db_xref="InterPro:IPR001628"/db_xref="InterPro:IPR001723"/db_xref="InterPro:IPR008946"/db_xref="UniProt/Swiss-Prot:Q9Y5X4"
1 7 10 1 3 6 1 14 22 2 0 5 0 11 2 8 19 1 6 5 4 4 7 13 6 6 7 21 5 11 1 11 10 2 2 5 12 0 2 15 7 3 1 17 9 1 5 21 9 7 2 2 11 3 11 5 2 8 1 13 4 0 1 0
>AF107292\AF107292\44..4483\4440\AAF14192.1\Homo sapiens\Homo sapiens urokinase receptor-associated protein uPARAP mRNA,complete cds./codon_start=1/product="urokinase receptor-associated protein uPARAP"/protein_id="AAF14192.1"/db_xref="GI:6492130"
7 29 27 8 6 6 4 27 85 8 1 10 7 29 7 9 64 12 10 44 18 12 13 48 18 15 10 57 17 9 8 67 33 14 2 23 32 1 8 38 48 10 6 84 33 7 14 82 60 12 32 8 37 19 42 9 3 39 5 19 67 0 1 0
>AL358075#6\AL358075\join(AL603888.9:87702..87856,AL603888.9:129709..129800, AL645480.8:11485..11560,AL645480.8:16566..16644, AL645480.8:20002..20156,AL645480.8:22057..22132, AL645480.8:24491..24700,complement(126523..126624), complement(124138..124270),complement(123249..123310), complement(122902..122987),complement(122240..122448), complement(120405..120543),complement(118357..118489), complement(117287..117452),complement(116653..116754), complement(116267..116389),complement(115982..116091), complement(115461..115613),complement(110308..110325))\-443349\CAI21706.1\Homo sapiens\Human DNA sequence from clone RP4-533D7 on chromosome 1p34.1-35.1Contains the 3' end of the gene for microtubule associated testisspecific serine/threonine protein kinase (MAST205), the PIK3R3 genefor phosphoinositide-3-kinase regulatory subunit polypeptide 3(p55, gamma), a cytochrome c oxidase subunit VIIb (COX7B)pseudogene, two novel genes and a CpG island, complete sequence./gene="MAST2"/locus_tag="RP4-533D7.1-003"/standard_name="OTTHUMP00000009698"/codon_start=1/product="microtubule associated serine/threonine kinase 2"/protein_id="CAI21706.1"/db_xref="GI:56205429"/db_xref="GOA:Q5VT07"/db_xref="GOA:Q6P0Q8"/db_xref="UniProt/Swiss-Prot:Q6P0Q8"
3 10 9 5 13 22 10 16 24 9 10 10 11 13 1 12 14 12 15 10 2 17 15 15 4 17 12 20 3 17 22 11 13 9 6 4 23 9 22 25 7 12 16 20 14 14 8 23 17 8 10 7 10 7 10 16 8 10 12 14 17 14 6 18
>AF325830\AF325830\1..1119\1119\AAK49911.1\Homo sapiens\Homo sapiens calponin-like integrin-linked kinase binding proteinmRNA, complete cds./codon_start=1/product="calponin-like integrin-linked kinase binding protein"/protein_id="AAK49911.1"/db_xref="GI:13936722"
4 3 3 2 1 3 3 10 25 4 2 7 2 7 2 6 5 2 5 8 1 4 7 10 4 2 2 9 0 5 6 1 6 1 1 9 18 5 12 20 9 8 7 11 3 4 12 21 12 10 4 2 0 1 8 7 2 9 6 7 2 0 0 1
>BC028581\BC028581\69..2654\2586\AAH28581.1\Homo sapiens\Homo sapiens piwi-like 1 (Drosophila), mRNA (cDNA clone MGC:26748IMAGE:4827445), complete cds./gene="PIWIL1"/codon_start=1/product="piwi-like 1"/protein_id="AAH28581.1"/db_xref="GI:20306782"/db_xref="GeneID:9271"/db_xref="MIM:605571"
7 6 7 8 26 15 11 10 18 14 16 14 12 8 1 5 12 10 24 11 4 14 21 6 2 15 9 19 2 12 23 13 8 14 5 11 20 20 24 21 19 23 20 34 8 11 22 15 19 26 20 16 9 7 9 23 10 16 26 19 11 1 0 0
>AF301470\AF301470\219..422\204\AAG22030.1\Homo sapiens\Homo sapiens beta-defensin 3 mRNA, complete cds./codon_start=1/product="beta-defensin 3"/protein_id="AAG22030.1"/db_xref="GI:10717136"
2 0 1 1 3 1 0 2 2 2 1 2 0 0 1 0 1 0 1 0 1 0 2 0 0 1 0 0 0 2 2 4 0 1 0 1 2 1 3 3 1 0 0 2 0 2 1 1 0 0 0 3 5 1 1 2 1 3 0 1 0 1 0 0
>AK057788\AK057788\197..697\501\BAB71573.1\Homo sapiens\Homo sapiens cDNA FLJ25059 fis, clone CBL04610./codon_start=1/protein_id="BAB71573.1"/db_xref="GI:16553729"
3 0 0 2 4 1 2 1 2 3 2 1 4 1 0 3 3 5 2 2 0 2 6 0 0 4 2 1 0 2 6 3 1 8 1 2 2 5 6 1 0 6 3 1 1 4 4 1 3 7 1 6 1 4 2 9 2 3 9 4 2 0 1 0
>AF270513\AF270513\160..3321\3162\AAK37963.1\Homo sapiens\Homo sapiens extracellular glycoprotein EMILIN-2 precursor, mRNA,complete cds./codon_start=1/product="extracellular glycoprotein EMILIN-2 precursor"/protein_id="AAK37963.1"/db_xref="GI:13661556"
5 8 11 1 16 20 4 24 41 13 3 11 9 11 5 15 22 14 14 20 11 14 14 35 17 15 22 23 10 17 18 27 30 12 3 20 36 14 17 40 27 17 13 51 13 10 39 38 31 24 15 9 14 8 13 13 6 14 7 18 11 1 0 0
>BC001767\BC001767\98..499\402\AAH01767.1\Homo sapiens\Homo sapiens LSM1 homolog, U6 small nuclear RNA associated (S.cerevisiae), mRNA (cDNA clone MGC:1352 IMAGE:3353833), completecds./gene="LSM1"/codon_start=1/product="Lsm1 protein"/protein_id="AAH01767.1"/db_xref="GI:12804683"/db_xref="GeneID:27257"/db_xref="MIM:607281"
4 0 0 1 2 2 4 2 3 4 2 3 0 2 0 0 2 1 2 2 0 2 0 1 0 3 3 2 0 0 3 3 1 2 1 2 7 1 4 5 2 1 3 5 1 2 9 5 5 5 2 1 0 0 0 3 2 1 8 2 0 1 0 0
>BC050677\BC050677\259..2016\1758\AAH50677.1\Homo sapiens\Homo sapiens hypothetical protein MGC3121, mRNA (cDNA cloneMGC:60225 IMAGE:6053861), complete cds./gene="MGC3121"/codon_start=1/product="hypothetical protein MGC3121"/protein_id="AAH50677.1"/db_xref="GI:29791770"/db_xref="GeneID:78994"
10 10 20 4 6 13 4 12 21 5 2 9 10 16 3 10 15 2 7 21 3 7 30 34 12 28 7 20 1 11 6 10 11 4 1 8 13 4 4 15 5 4 4 21 8 1 14 24 11 8 4 0 4 3 10 4 3 10 3 9 6 0 1 0
>HUMFKBP\M34539\79..405\327\AAA35844.1\Homo sapiens\Human FK506-binding protein (FKBP) mRNA, complete cds./codon_start=1/protein_id="AAA35844.1"/db_xref="GI:182628"
1 2 1 0 2 0 2 1 2 2 0 0 0 3 0 1 0 1 0 4 0 3 5 2 0 0 0 5 0 0 3 4 4 2 0 1 7 1 3 5 1 0 0 5 2 1 5 2 2 4 1 2 1 0 2 3 1 4 0 4 1 0 0 1
>BC093885\BC093885\74..919\846\AAH93885.1\Homo sapiens\Homo sapiens SH3 and multiple ankyrin repeat domains 2, transcriptvariant 2, mRNA (cDNA clone IMAGE:7939730), complete cds./gene="SHANK2"/codon_start=1/product="SH3 and multiple ankyrin repeat domains 2, isoform 2"/protein_id="AAH93885.1"/db_xref="GI:62739586"/db_xref="GeneID:22941"/db_xref="MIM:603290"
3 4 6 0 0 6 2 3 8 2 0 2 2 5 2 2 3 1 5 7 5 2 5 11 7 4 1 10 5 6 6 8 5 4 0 8 14 3 9 13 5 8 3 8 2 0 5 12 8 3 4 0 2 2 5 3 2 4 4 11 1 0 1 0
>AK129649\AK129649\214..642\429\BAC85207.1\Homo sapiens\Homo sapiens cDNA FLJ26138 fis, clone TMS04622./codon_start=1/protein_id="BAC85207.1"/db_xref="GI:34526237"
2 0 0 0 2 2 0 5 9 1 0 1 3 4 2 4 4 7 2 6 0 5 3 3 0 1 3 6 0 0 1 1 3 3 0 1 1 1 1 7 2 4 2 5 1 0 4 16 1 2 1 1 0 1 1 2 0 1 0 4 0 0 1 0
>HSU84744\U84744\553..5148\4596\AAB87737.1\Homo sapiens\Human Chediak-Higashi syndrome protein short isoform (LYST) mRNA,complete cds./gene="LYST"/codon_start=1/product="Chediak-Higashi syndrome protein short isoform"/protein_id="AAB87737.1"/db_xref="GI:2654474"
12 3 5 4 32 11 21 17 36 42 53 41 38 13 5 37 20 51 23 14 1 26 19 10 3 28 37 24 0 29 21 6 11 20 19 8 21 35 59 33 26 38 32 51 12 45 76 41 23 49 7 17 15 28 13 45 31 14 38 31 11 1 0 0
>BC014445\BC014445\162..1793\1632\AAH14445.1\Homo sapiens\Homo sapiens EH-domain containing 2, mRNA (cDNA clone MGC:22994IMAGE:4908085), complete cds./gene="EHD2"/codon_start=1/product="EH-domain containing 2"/protein_id="AAH14445.1"/db_xref="GI:15680192"/db_xref="GeneID:30846"/db_xref="MIM:605890"
2 18 8 1 1 2 0 19 44 0 0 2 2 8 6 1 11 0 0 13 6 1 1 17 7 7 4 23 9 2 2 27 10 2 0 6 30 1 4 34 11 1 0 19 13 3 3 41 30 5 11 0 2 1 17 9 0 22 1 16 7 0 0 1
>AL139281#1\AL139281\join(13755..13872,22290..22390,28388..28464,37450..37597, 38904..39008)\549\CAI12665.1\Homo sapiens\Human DNA sequence from clone RP11-215C7 on chromosome 10 Containsthe gene for pilin-like transcription factor (PILB) (CGI-131), atyrosine 3-monooxygenase/tryptophan 5-monooxygenase activationprotein zeta polypeptide (YWHAZ) pseudogene, the gene for a novelprotein similar to bHLH protein Ptf1-p48 (PTF1A) (possible orthologof rodent pancreas specific transcription factor 1a (Ptf1a)), anovel gene, a novel pseudogene and five CpG islands, completesequence./gene="MSRB2"/locus_tag="RP11-215C7.1-001"/standard_name="OTTHUMP00000019305"/codon_start=1/product="methionine sulfoxide reductase B2"/protein_id="CAI12665.1"/db_xref="GI:55957250"
0 1 5 1 2 2 2 5 6 2 1 2 1 1 2 5 1 5 3 4 3 2 2 2 3 6 3 1 4 4 6 8 8 3 0 2 4 1 4 7 2 2 2 3 3 3 5 7 1 3 3 1 6 2 4 3 0 3 0 2 3 0 0 1
>AB158468\AB158468\50..1411\1362\BAD07014.1\Homo sapiens\Homo sapiens gdf7 mRNA for growth differentiation factor 7,complete cds./gene="gdf7"/codon_start=1/product="growth differentiation factor 7"/protein_id="BAD07014.1"/db_xref="GI:40786371"
3 23 12 3 1 9 2 7 22 5 1 6 1 8 8 3 14 0 3 5 6 2 8 8 16 1 10 32 27 7 3 38 12 3 0 8 15 2 1 3 6 0 2 8 7 2 4 16 19 0 7 0 10 1 11 0 0 8 2 6 6 0 1 0
>BC047733\BC047733\8..1183\1176\AAH47733.1\Homo sapiens\Homo sapiens DNA (cytosine-5-)-methyltransferase 2, transcriptvariant a, mRNA (cDNA clone MGC:54074 IMAGE:6473993), complete cds./gene="DNMT2"/codon_start=1/product="DNA methyltransferase 2, isoform a"/protein_id="AAH47733.1"/db_xref="GI:29126973"/db_xref="GeneID:1787"/db_xref="MIM:602478"
3 1 2 1 5 5 7 6 7 15 13 4 5 2 0 9 7 2 9 3 1 7 11 5 0 7 6 4 1 4 6 8 2 3 7 2 11 4 16 9 4 13 10 13 4 2 20 10 5 13 5 11 2 4 6 13 9 3 16 8 0 1 0 0
>AY061755\AY061755\121..10086\9966\AAL33798.1\Homo sapiens\Homo sapiens nesprin-1 beta mRNA, complete cds./codon_start=1/product="nesprin-1 beta"/protein_id="AAL33798.1"/db_xref="GI:17861386"
22 28 31 20 32 35 39 103 155 57 39 72 39 59 12 70 63 52 44 43 16 38 30 22 6 20 57 78 8 72 41 29 24 25 17 31 57 33 114 110 47 61 97 207 40 40 171 183 88 96 30 24 17 30 28 35 34 52 69 77 52 0 0 1
>BC028040\BC028040\106..1371\1266\AAH28040.1\Homo sapiens\Homo sapiens 2',3'-cyclic nucleotide 3' phosphodiesterase, mRNA(cDNA clone MGC:40095 IMAGE:5248370), complete cds./gene="CNP"/codon_start=1/product="CNP protein"/protein_id="AAH28040.1"/db_xref="GI:20380838"/db_xref="GeneID:1267"/db_xref="MIM:123830"
4 7 11 1 3 2 2 10 26 4 3 5 3 7 2 3 8 1 4 11 9 2 2 10 3 4 3 16 1 8 3 17 13 1 1 5 15 0 5 34 6 1 5 15 4 1 4 26 17 8 13 1 4 3 15 5 1 9 2 7 5 0 0 1
>Z93322\Z93322\8..778\771\CAB07532.1\Homo sapiens\H.sapiens mRNA; IMAGE cDNA clone 308937./codon_start=1/product="c21ORF-HumF09G8.5"/protein_id="CAB07532.1"/db_xref="GI:2425155"/db_xref="GOA:O43822"/db_xref="UniProt/Swiss-Prot:O43822"
1 8 8 4 1 4 2 6 31 0 0 0 1 7 2 0 14 3 2 6 3 4 1 4 5 3 3 11 1 4 1 12 3 0 0 2 9 1 0 8 6 0 0 10 5 0 2 25 3 4 3 0 7 0 1 1 1 6 1 4 2 0 0 1
>HS179D312\AL049704\25..1005\981\CAB41268.1\Homo sapiens\Human gene from PAC 179D3, chromosome X, isoform of mitochondrialapoptosis inducing factor, AIF, AF100928./codon_start=1/product="hypothetical protein"/protein_id="CAB41268.1"/db_xref="GI:4678809"/db_xref="GOA:O95831"/db_xref="UniProt/Swiss-Prot:O95831"
5 1 5 0 2 7 3 6 5 2 1 8 5 2 0 2 4 6 4 3 0 6 3 10 3 1 10 5 2 11 10 10 3 8 4 6 14 8 8 12 7 6 4 7 3 4 11 13 9 7 5 1 2 1 7 3 4 7 8 7 5 0 0 1
>AF077820\AF077820\89..4936\4848\AAC72791.1\Homo sapiens\Homo sapiens LDL receptor member LR3 mRNA, complete cds./codon_start=1/product="LDL receptor member LR3"/protein_id="AAC72791.1"/db_xref="GI:3831748"
5 33 34 6 3 17 3 39 100 4 0 7 12 29 13 6 46 4 17 46 26 9 9 51 36 7 12 80 18 4 11 55 42 10 1 31 62 3 5 47 50 12 3 53 33 6 5 65 122 16 43 7 35 22 40 8 1 73 14 29 35 0 0 1
>HSJ154G14#4\AL121964\join(complement(AL121837.33:1025..1144),14033..14143, 17217..17282,24173..24218,25626..25764,29216..29340, 32254..32382,33661..33791,35291..35372,37663..37793, 38453..38582,41208..41288,49439..49503,62057..62162, 66521..66582,69159..69191)\-121833\CAI19610.1\Homo sapiens\Human DNA sequence from clone RP1-154G14 on chromosome 6q15-16.3Contains the 3' end of the MAP3K7 gene for mitogen-activatedprotein kinase kinase kinase 7 (TGF-beta activated kinase 1, TAK1),complete sequence./gene="MAP3K7"/locus_tag="RP1-154G14.1-003"/standard_name="OTTHUMP00000016872"/codon_start=1/protein_id="CAI19610.1"/db_xref="GI:56203690"
0 3 0 3 9 11 0 10 12 9 1 8 2 15 3 7 17 14 8 7 7 16 10 5 4 5 4 7 2 8 9 9 5 8 5 8 7 9 9 8 10 17 10 9 9 19 5 0 5 5 4 6 8 10 17 18 11 13 14 4 17 10 3 11
>HUMHLABC\L38504\1..1089\1089\AAA69724.1\Homo sapiens\Homo sapiens (clones 18.1, 18.2, 19.2) MHC class I HLA-B*2702 mRNA,complete cds./gene="HLA-B*2702"/codon_start=1/product="major histocompatibility complex"/protein_id="AAA69724.1"/db_xref="GI:896271"
2 8 6 1 7 5 1 10 17 1 0 0 1 7 0 7 6 2 5 15 4 3 2 7 7 2 5 12 11 10 5 11 10 1 1 5 18 2 1 9 4 1 1 18 7 3 1 26 17 4 11 3 6 1 6 0 1 9 1 4 11 0 0 1
>AY337264\AY337264\102..1184\1083\AAR00269.1\Homo sapiens\Homo sapiens protein phosphatase 2C epsilon (PP2CE) mRNA, completecds./gene="PP2CE"/codon_start=1/product="protein phosphatase 2C epsilon"/protein_id="AAR00269.1"/db_xref="GI:37700518"
4 5 3 0 6 2 3 7 14 6 2 10 4 7 1 5 6 3 4 5 4 4 3 1 2 5 5 8 1 5 2 5 9 5 4 4 12 3 9 16 7 6 0 12 7 2 12 14 16 12 7 3 2 2 14 4 4 14 4 10 4 0 0 1
>BC014549\BC014549\51..1097\1047\AAH14549.1\Homo sapiens\Homo sapiens capping protein (actin filament), gelsolin-like, mRNA(cDNA clone MGC:13643 IMAGE:4108934), complete cds./gene="CAPG"/codon_start=1/product="gelsolin-like capping protein"/protein_id="AAH14549.1"/db_xref="GI:15778939"/db_xref="GeneID:822"/db_xref="MIM:153615"
2 3 7 2 0 1 1 6 23 1 0 0 3 6 2 4 3 3 3 3 1 4 7 3 2 6 5 17 3 7 4 15 7 3 0 4 17 1 3 21 12 4 2 21 5 2 5 21 13 5 6 2 2 3 11 4 2 11 3 5 6 0 0 1
>BC012176\BC012176\97..1032\936\AAH12176.1\Homo sapiens\Homo sapiens naked cuticle homolog 2 (Drosophila), mRNA (cDNA cloneMGC:20432 IMAGE:4649935), complete cds./gene="NKD2"/codon_start=1/product="NKD2 protein"/protein_id="AAH12176.1"/db_xref="GI:15082530"/db_xref="GeneID:85409"/db_xref="MIM:607852"
1 8 6 2 5 11 2 9 7 1 0 1 1 6 5 2 11 2 1 5 4 1 3 12 4 6 8 7 6 6 4 10 11 3 0 8 8 0 3 11 7 1 1 12 8 0 3 28 17 3 4 2 7 1 5 1 0 1 2 4 3 0 0 1
>AF020920\AF020920\311..1345\1035\AAG50147.1\Homo sapiens\Homo sapiens chromosome 3 beta-1,4-galactosyltransferase mRNA,complete cds./codon_start=1/evidence=experimental/product="beta-1,4-galactosyltransferase"/protein_id="AAG50147.1"/db_xref="GI:12275809"
3 2 4 1 8 5 2 10 14 3 6 7 1 4 0 5 3 4 4 2 1 8 1 6 0 6 5 6 0 3 5 8 5 5 4 4 13 5 13 12 10 10 3 8 8 5 14 11 7 6 9 7 3 3 12 7 1 5 5 6 6 0 0 1
>BC000218\BC000218\8..1864\1857\AAH00218.1\Homo sapiens\Homo sapiens delta-like 3 (Drosophila), transcript variant 1, mRNA(cDNA clone MGC:652 IMAGE:3508262), complete cds./gene="DLL3"/codon_start=1/product="delta-like 3 protein, isoform 1 precursor"/protein_id="AAH00218.1"/db_xref="GI:12652923"/db_xref="GeneID:10683"/db_xref="MIM:602768"
2 29 12 3 2 7 4 20 23 4 1 7 2 17 4 6 12 2 3 9 5 3 6 26 22 17 9 23 21 14 13 37 20 8 3 13 13 0 1 2 6 3 2 14 13 1 6 23 18 7 9 1 36 12 18 2 1 6 5 3 7 0 0 1
>BC064548\BC064548\66..332\267\AAH64548.1\Homo sapiens\Homo sapiens cytochrome c oxidase subunit VIb polypeptide 2(testis), mRNA (cDNA clone MGC:74620 IMAGE:5744705), complete cds./gene="COX6B2"/codon_start=1/product="cytochrome c oxidase subunit VIb, testis-specific isoform"/protein_id="AAH64548.1"/db_xref="GI:40353035"/db_xref="GeneID:125965"
0 5 0 1 0 1 0 1 2 0 0 1 0 0 2 0 4 0 0 2 2 0 0 6 2 0 0 2 0 0 0 1 3 0 0 0 3 0 2 4 5 0 0 6 2 0 1 4 2 1 4 1 4 0 5 0 0 4 1 1 3 0 0 1
>AL845353#28\AL845353\complement(join(127057..127089,127265..127426, 127539..127748))\405\CAI41898.1\Homo sapiens\Human DNA sequence from clone DAQB-47P19 on chromosome 6 Containsthe 3' end of the MRPS18B gene for mitochondrial ribosomal proteinS18B, the C6orf134 gene for chromosome 6 open reading frame 134,the C6orf136 gene for chromosome 6 open reading frame 136, theDHX16 gene for DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 16, theKIAA1949 gene, the NRM gene for nurim (nuclear envelope membraneprotein), the RPL7P4 pseudogene for ribosomal protein L7 pseudogene4, the MDC1 gene for mediator of DNA damage checkpoint 1, the TUBBgene for tubulin, beta polypeptide, the FLOT1 gene for flotillin 1,the IER3 gene for immediate early response 3 and 8 CpG islands,complete sequence./gene="IER3"/locus_tag="DAQB-47P19.3-003"/standard_name="OTTHUMP00000014832"/codon_start=1/product="immediate early response 3"/protein_id="CAI41898.1"/db_xref="GI:57209818"/db_xref="UniProt/TrEMBL:Q5JP65"
2 6 3 0 0 2 0 4 7 1 0 0 0 5 0 2 3 0 0 7 0 3 4 6 7 7 3 8 3 1 1 1 3 2 1 3 2 1 1 1 2 0 0 3 3 0 2 6 2 0 1 0 2 1 3 1 0 5 0 3 0 0 0 1
>AY335944\AY335944\join(101..349,1400..1805,1982..2775)\1449\AAQ16550.1\Homo sapiens\Homo sapiens homeodomain protein IRXB2 (IRX5) gene, complete cds./gene="IRX5"/codon_start=1/product="homeodomain protein IRXB2"/protein_id="AAQ16550.1"/db_xref="GI:33356607"
1 9 8 0 0 1 2 11 9 2 1 7 1 10 20 8 7 0 4 12 8 1 8 31 22 10 3 22 25 7 7 30 14 3 0 2 6 1 7 17 12 2 1 12 6 5 4 23 20 2 19 4 4 2 7 2 1 5 3 7 4 1 0 0
>BC009676\BC009676\10..1053\1044\AAH09676.1\Homo sapiens\Homo sapiens histone deacetylase 11, mRNA (cDNA clone MGC:8894IMAGE:3906049), complete cds./gene="HDAC11"/codon_start=1/product="histone deacetylase 11"/protein_id="AAH09676.1"/db_xref="GI:16307174"/db_xref="GeneID:79885"/db_xref="MIM:607226"
2 9 6 4 0 6 2 6 18 9 0 0 3 7 2 1 4 0 7 8 2 0 4 10 2 2 3 9 4 5 3 14 11 1 1 3 21 2 4 13 6 5 0 9 6 4 2 21 13 8 9 2 1 1 8 6 2 20 3 8 5 0 0 1
>AK074766\AK074766\171..1382\1212\BAC11192.1\Homo sapiens\Homo sapiens cDNA FLJ90285 fis, clone NT2RP1000679./codon_start=1/protein_id="BAC11192.1"/db_xref="GI:22760424"
7 0 11 1 4 5 0 5 8 6 2 5 4 10 1 8 8 9 8 7 2 5 14 22 1 19 9 9 2 10 6 5 14 4 2 4 7 2 8 24 3 0 2 7 2 2 19 21 13 13 2 2 4 4 4 6 0 5 4 8 4 0 0 1
>HSU49379\U49379\88..1791\1704\AAC50497.1\Homo sapiens\Human diacylglycerol kinase epsilon DGK mRNA, complete cds./EC_number="2.7.1.107"/codon_start=1/product="diacylglycerol kinase epsilon DGK"/protein_id="AAC50497.1"/db_xref="GI:1289445"
5 6 4 3 3 7 8 8 22 5 7 10 1 4 4 8 5 5 11 6 2 10 9 8 3 7 7 8 7 7 18 9 11 7 9 6 8 14 18 21 8 13 10 16 8 6 18 10 14 21 9 9 18 10 11 8 5 10 13 17 12 0 1 0
>AC069281#2\AC069281\complement(join(7546..7592,8626..8784,10150..10384, 11265..11500,12852..12993,13092..13190,16503..16541))\957\AAP21862.1\Homo sapiens\Homo sapiens BAC clone RP11-44M6 from 7, complete sequence./gene="FBXO24"/codon_start=1/product="unknown"/protein_id="AAP21862.1"/db_xref="GI:30141998"
1 11 6 2 4 6 4 12 11 4 0 7 2 5 2 4 7 2 4 10 2 2 5 3 3 6 1 11 1 1 5 8 5 3 1 8 13 7 3 12 1 3 2 16 7 1 5 10 7 5 10 3 5 8 11 2 0 6 3 5 4 0 0 1
>AF050080\AF050080\1..354\354\AAC69520.1\Homo sapiens\Homo sapiens C16orf3 small protein mRNA, complete cds./codon_start=1/product="C16orf3 small protein"/protein_id="AAC69520.1"/db_xref="GI:3818471"
0 0 0 1 2 2 0 0 3 1 0 0 2 6 0 6 5 1 2 2 2 1 5 9 0 2 1 7 3 3 0 5 2 1 6 0 1 0 1 2 0 0 3 3 1 4 2 3 1 0 0 0 8 1 0 0 1 1 0 3 2 0 0 1
>HSJ836N17#2\AL049539\join(AL353092.6:21133..21252,AL353092.6:22789..22831, AL353092.6:23186..23288,AL353092.6:24093..24191, 4334..4437,8454..8603,8951..9103,11188..11367, 13128..13204,18423..18576,23564..23695,25877..26079)\-140055\CAI22966.1\Homo sapiens\Human DNA sequence from clone RP5-836N17 on chromosome20q11.1-11.21 Contains the 3' end of the HCK for hemopoietic cellkinase, the gene for novel protein (KIAA0255), the RPL24P1 gene forribosomal protein L24 pseudogene 1 and two CpG Islands, completesequence./gene="HCK"/locus_tag="RP5-836N17.3-002"/standard_name="OTTHUMP00000030578"/codon_start=1/protein_id="CAI22966.1"/db_xref="GI:56203175"
5 4 12 3 3 5 1 7 28 2 0 8 3 10 5 6 10 3 2 12 4 4 7 10 2 17 6 16 1 9 9 9 8 2 1 10 15 0 14 21 15 2 4 18 4 4 7 25 15 5 17 1 5 1 15 10 2 20 4 19 8 1 5 5
>HUMP45C17\M19489\join(1839..2135,3804..3942,4176..4405,5068..5154, 5849..6064,6297..6466,7364..7467,7986..8269)\1527\AAA36405.1\Homo sapiens\Human P450XVIIA-1 (steroid 17-alpha-hydroxylase/17,20 lyase) gene,complete cds./gene="CYP17"/codon_start=1/protein_id="AAA36405.1"/db_xref="GI:386992"
3 5 2 5 2 5 3 13 34 5 1 8 5 9 0 6 9 3 5 17 0 3 5 12 2 8 3 15 5 7 3 14 6 6 2 6 17 5 10 27 12 16 3 17 9 6 7 19 17 11 5 4 1 3 18 6 7 23 6 12 10 1 0 0
>HUMIFNAJ1\M34913\41..610\570\AAA36039.1\Homo sapiens\Human interferon-alpha-J1 (IFN-alpha-J1) mRNA, complete cds./codon_start=1/protein_id="AAA36039.1"/db_xref="GI:184615"
0 0 1 1 6 5 2 5 10 2 2 3 2 5 0 6 5 0 3 2 0 4 0 1 1 3 3 5 0 3 2 2 1 0 1 2 4 2 6 4 1 4 4 8 2 2 7 10 4 3 4 1 2 3 9 4 2 7 0 6 2 0 0 1
>AB093575\AB093575\252..953\702\BAC76997.1\Homo sapiens\Homo sapiens ERas mRNA for small GTPase protein E-Ras, completecds./gene="ERas"/codon_start=1/product="small GTPase protein E-Ras"/protein_id="BAC76997.1"/db_xref="GI:31158278"
0 2 3 1 0 6 0 3 16 2 0 1 0 4 2 2 2 3 4 10 0 1 1 5 0 4 5 14 2 8 1 11 4 1 0 5 12 1 1 8 2 1 1 15 8 3 1 11 9 5 2 0 5 4 5 1 1 5 1 3 5 0 0 1
>BC053851\BC053851\394..4056\3663\AAH53851.1\Homo sapiens\Homo sapiens bromodomain and PHD finger containing, 1, transcriptvariant 1, mRNA (cDNA clone MGC:61492 IMAGE:6140996), complete cds./gene="BRPF1"/codon_start=1/product="bromodomain and PHD finger-containing protein 1, isoform 1"/protein_id="AAH53851.1"/db_xref="GI:31753086"/db_xref="GeneID:7862"/db_xref="MIM:602410"
9 25 35 10 2 11 7 18 47 9 1 11 24 14 3 9 40 20 17 20 7 12 27 35 8 17 17 33 4 18 6 36 10 16 7 15 35 7 22 66 30 13 10 46 29 13 18 88 43 28 25 8 22 7 20 9 0 33 7 28 13 0 0 1
>BC046366\BC046366\395..1096\702\AAH46366.1\Homo sapiens\Homo sapiens copine VIII, mRNA (cDNA clone IMAGE:5764002), completecds./gene="LOC144402"/codon_start=1/product="LOC144402 protein"/protein_id="AAH46366.1"/db_xref="GI:28204828"/db_xref="GeneID:144402"
1 0 0 0 7 3 4 1 5 2 1 3 4 4 0 5 1 3 2 2 0 2 8 3 0 8 6 4 1 9 8 2 3 4 6 4 5 5 7 3 3 6 5 5 2 2 5 5 3 13 4 9 0 1 1 8 6 3 7 9 0 0 0 1
>HSFLA1A\Y00796\89..3601\3513\CAA68747.1\Homo sapiens\Human mRNA for leukocyte-associated molecule-1 alpha subunit (LFA-1alpha subunit)./codon_start=1/protein_id="CAA68747.1"/db_xref="GI:31422"/db_xref="GOA:P20701"/db_xref="UniProt/Swiss-Prot:P20701"
3 9 12 1 14 11 2 26 73 7 1 15 9 29 9 14 30 10 19 23 2 13 15 26 8 15 14 24 7 20 22 28 42 12 7 19 42 13 15 36 22 15 11 48 19 11 21 53 39 23 20 14 11 11 34 24 6 46 10 25 10 0 0 1
>AF151905\AF151905\128..667\540\AAD34142.1\Homo sapiens\Homo sapiens CGI-147 protein mRNA, complete cds./codon_start=1/product="CGI-147 protein"/protein_id="AAD34142.1"/db_xref="GI:4929763"
2 0 0 1 2 0 3 3 4 3 3 5 1 2 0 2 5 3 3 1 1 5 3 4 0 2 5 3 0 8 6 5 5 1 2 3 4 5 9 6 0 2 4 4 2 3 7 1 4 3 4 1 3 2 0 1 0 1 7 8 2 0 1 0
>BC001689\BC001689\72..977\906\AAH01689.1\Homo sapiens\Homo sapiens solute carrier family 25 (carnitine/acylcarnitinetranslocase), member 20, mRNA (cDNA clone MGC:1207 IMAGE:3050073),complete cds./gene="SLC25A20"/codon_start=1/product="carnitine/acylcarnitine translocase"/protein_id="AAH01689.1"/db_xref="GI:12804553"/db_xref="GeneID:788"/db_xref="MIM:212138"
5 0 5 0 2 2 2 4 9 6 3 6 1 1 0 4 3 4 4 5 2 7 6 6 3 9 6 10 1 6 8 9 12 4 1 7 10 1 7 11 3 5 2 9 2 0 6 5 4 5 5 5 3 3 13 9 0 14 2 11 3 0 0 1
>AB035863\AB035863\58..1449\1392\BAA92873.1\Homo sapiens\Homo sapiens SCS-betaA mRNA for ATP specific succinyl CoAsynthetase beta subunit precursor, complete cds./gene="SCS-betaA"/codon_start=1/product="ATP specific succinyl CoA synthetase beta subunit precursor"/protein_id="BAA92873.1"/db_xref="GI:7328935"
2 2 5 0 4 5 4 7 5 9 6 9 10 2 0 6 1 5 6 5 2 2 6 2 0 6 17 8 3 21 17 6 2 14 10 9 11 10 21 16 7 10 13 12 1 6 26 2 6 21 7 4 2 4 3 12 17 5 12 16 1 0 0 1
>AL391357#1\AL391357\complement(join(5456..5526,7021..7186))\237\CAH73469.1\Homo sapiens\Human DNA sequence from clone RP11-401M16 on chromosome 1 Containsthe gene for calcium/calmodulin-dependent protein kinase II(CaMKIINalpha), the gene for a novel protein (FLJ12875), aribosomal protein S4 X-linked (RPS4X) pseudogene, the CDA gene forcytidine deaminase, the PINK1 gene for PTEN induced putative kinase1, a novel gene (FLJ00387), the DDOST gene fordolichyl-diphosphooligosaccharide-protein glycosyltransferase andthe 3' end of the KIF17 gene for kinesin family member 17, completesequence./gene="RP11-401M16.1"/locus_tag="RP11-401M16.1-001"/standard_name="OTTHUMP00000002879"/codon_start=1/product="calcium/calmodulin-dependent protein kinase II (CaMKIINalpha)"/protein_id="CAH73469.1"/db_xref="GI:55664520"/db_xref="GOA:Q7Z7J9"/db_xref="UniProt/TrEMBL:Q7Z7J9"
0 1 3 0 0 1 0 0 5 0 0 0 0 1 1 0 2 0 0 2 0 0 0 3 1 2 1 1 0 0 0 8 1 1 0 1 3 2 1 5 3 1 0 4 0 0 1 2 6 3 2 0 1 0 3 0 0 2 2 2 0 1 0 0
>CR536498\CR536498\1..1221\1221\CAG38737.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834A0620D forgene REN, renin; complete cds, incl. stopcodon./gene="REN"/codon_start=1/protein_id="CAG38737.1"/db_xref="GI:49168484"/db_xref="InterPro:IPR001461"/db_xref="InterPro:IPR001969"/db_xref="InterPro:IPR009007"
3 4 2 2 3 5 1 14 15 2 1 4 4 15 3 4 8 3 8 20 3 4 2 11 2 3 2 13 1 1 11 14 7 8 2 8 12 2 5 14 8 4 4 9 5 1 8 11 12 8 11 6 3 4 13 9 1 17 6 13 7 0 0 1
>AF063601\AF063601\194..2137\1944\AAG43160.1\Homo sapiens\Homo sapiens brain my043 protein mRNA, complete cds./codon_start=1/product="brain my043 protein"/protein_id="AAG43160.1"/db_xref="GI:12002034"
0 2 1 0 3 4 7 14 11 10 11 22 29 4 0 21 8 14 13 3 2 13 17 5 2 19 15 8 0 22 7 2 2 7 7 0 14 27 32 20 4 12 8 12 2 7 47 21 11 27 4 14 3 1 9 14 16 7 16 12 2 0 0 1
>AY281131\AY281131\1..3750\3750\AAP37612.1\Homo sapiens\Homo sapiens AIDA-1b mRNA, complete cds./codon_start=1/product="AIDA-1b"/protein_id="AAP37612.1"/db_xref="GI:31746739"
8 5 4 2 24 13 11 21 28 21 14 23 24 24 5 33 17 17 38 17 2 25 24 19 4 31 28 20 2 23 35 15 19 8 12 15 21 17 48 28 26 42 18 32 26 20 67 29 24 40 14 15 6 16 5 23 10 20 38 22 11 0 0 1
>HSA406932\AJ406932\34..330\297\CAC27571.1\Homo sapiens\Homo sapiens mRNA for keratin associated protein 3.2 (KRTAP3.2gene)./gene="KRTAP3.2"/function="structural protein"/standard_name="KAP3.2"/codon_start=1/product="keratin associated protein 3.2"/protein_id="CAC27571.1"/db_xref="GI:12655438"/db_xref="UniProt/TrEMBL:Q9BYR7"
0 2 0 0 1 0 0 4 4 0 1 0 0 4 0 1 2 1 1 7 0 3 4 9 1 2 0 2 0 0 1 2 1 0 0 2 1 1 1 0 3 0 0 3 2 0 0 3 2 1 0 0 14 5 2 0 0 2 1 1 1 0 0 1
>AY358984\AY358984\51..1697\1647\AAQ89343.1\Homo sapiens\Homo sapiens clone DNA82307 aminyltransferase (UNQ906) mRNA,complete cds./locus_tag="UNQ906"/codon_start=1/product="aminyltransferase"/protein_id="AAQ89343.1"/db_xref="GI:37183086"
3 16 11 0 2 5 2 18 45 0 0 3 6 12 9 2 11 2 3 10 5 5 3 12 6 8 7 14 8 2 5 17 4 1 1 5 26 2 10 24 12 2 1 23 14 4 2 35 29 4 16 0 4 1 32 3 0 19 5 8 9 1 0 0
>BC008988\BC008988\58..1194\1137\AAH08988.1\Homo sapiens\Homo sapiens T-cell immunoglobulin and mucin domain containing 4,mRNA (cDNA clone MGC:17333 IMAGE:4184237), complete cds./gene="TIMD4"/codon_start=1/product="T-cell immunoglobulin and mucin domain containing 4"/protein_id="AAH08988.1"/db_xref="GI:14290446"/db_xref="GeneID:91937"
1 4 1 0 7 3 4 13 9 7 1 5 10 10 1 8 5 7 26 17 4 10 6 11 2 6 8 4 2 3 8 2 4 5 1 7 12 4 11 5 7 4 2 9 5 1 11 9 7 10 5 2 6 2 3 5 3 7 4 13 9 1 0 0
>AK126120\AK126120\1301..1741\441\BAC86449.1\Homo sapiens\Homo sapiens cDNA FLJ44132 fis, clone THYMU2008282./codon_start=1/protein_id="BAC86449.1"/db_xref="GI:34532501"
0 2 2 0 2 7 3 4 5 1 4 1 3 4 1 1 3 5 2 2 0 2 4 1 0 3 1 7 0 5 2 5 4 5 4 0 3 1 1 0 2 0 3 4 4 2 2 6 2 2 0 0 4 1 0 6 1 0 4 3 0 0 0 1
>AF147709\AF147709\26..4012\3987\AAF33021.1\Homo sapiens\Homo sapiens MYB-binding protein 1A (MYBBP1A) mRNA, complete cds./gene="MYBBP1A"/codon_start=1/product="MYB-binding protein 1A"/protein_id="AAF33021.1"/db_xref="GI:6959304"
6 22 31 7 2 14 10 38 106 5 1 27 7 25 7 6 40 14 11 32 16 7 12 38 13 17 21 60 12 16 10 26 21 8 1 18 56 3 19 82 21 7 7 92 28 9 13 82 42 14 11 5 13 4 36 12 3 24 4 23 11 0 0 1
>S76984\S76984\1..39\39\AAD14243.1\Homo sapiens\HEXA {HEXA4bpDeltass mutation, exon 11} [human, Tay-Sachs diseasepatient, mRNA Partial Mutant, 84 nt]./gene="HEXA"/codon_start=1/protein_id="AAD14243.1"/db_xref="GI:4261943"
0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 2 0 0 1
>AY152724\AY152724\1..957\957\AAN73210.1\Homo sapiens\Homo sapiens X-linked ectodermal dysplasia receptor long isoform(XEDAR) mRNA, complete cds, alternatively spliced./gene="XEDAR"/codon_start=1/product="X-linked ectodermal dysplasia receptor long isoform"/protein_id="AAN73210.1"/db_xref="GI:25140979"
1 2 2 2 2 3 2 6 10 2 1 5 1 7 1 5 13 4 9 11 1 3 4 10 1 7 5 7 0 7 9 3 3 4 1 6 9 4 3 8 5 5 7 13 5 1 6 19 7 6 5 2 13 8 10 7 1 6 3 1 4 1 0 0
>AL359513#1\AL359513\complement(join(12614..13992,21231..21389,32435..33397, 37746..37803))\2559\CAH71657.1\Homo sapiens\Human DNA sequence from clone RP11-245D16 on chromosome 13 Containsthe gene for TMTSP for transmembrane molecule with thrombospondinmodule (LOC55901), the gene fpr CGI-145 protein (LOC51028), theCKAP2 gene for cytoskeleton associated protein 2 (LB1, FLJ10749)and 3 CpG islands, complete sequence./gene="THSD1"/locus_tag="RP11-245D16.1-001"/standard_name="OTTHUMP00000018448"/codon_start=1/product="thrombospondin, type I, domain 1"/protein_id="CAH71657.1"/db_xref="GI:55663986"/db_xref="Genew:17754"/db_xref="GOA:Q9NS62"/db_xref="InterPro:IPR000884"/db_xref="InterPro:IPR003067"/db_xref="UniProt/TrEMBL:Q9NS62"
5 4 8 3 14 24 6 9 31 9 4 15 7 21 3 10 27 17 19 16 5 20 21 23 8 20 13 27 3 12 14 11 18 9 7 14 25 3 15 24 17 12 6 34 11 6 21 37 20 13 10 9 10 12 24 20 5 13 9 10 9 0 1 0
>AK128007\AK128007\1041..1484\444\BAC87229.1\Homo sapiens\Homo sapiens cDNA FLJ46126 fis, clone TESTI2041362./codon_start=1/protein_id="BAC87229.1"/db_xref="GI:34535168"
0 0 0 0 5 8 1 3 1 2 1 3 1 5 0 3 1 4 5 6 0 2 5 2 0 2 5 4 0 7 1 5 9 1 1 1 4 1 2 2 1 1 2 3 2 1 4 1 2 2 2 0 3 1 4 3 1 1 2 3 5 0 0 1
>AF049259\AF049259\join(512..1006,2331..2413,2613..2769,2960..3121, 3246..3371,3464..3684,4694..4712)\1263\AAC35754.1\Homo sapiens\Homo sapiens keratin 13 gene, complete cds./codon_start=1/product="keratin 13"/protein_id="AAC35754.1"/db_xref="GI:3603253"
0 11 6 4 0 5 1 12 31 2 0 0 2 3 0 6 16 3 2 10 4 5 2 2 1 1 4 16 1 9 12 20 6 16 0 4 12 1 1 18 14 4 2 21 2 1 6 40 14 4 8 6 3 3 3 8 0 12 6 12 2 0 1 0
>HSRNASMG\X85373\84..314\231\CAA59689.1\Homo sapiens\H.sapiens mRNA for Sm protein G./gene="pBSCF"/codon_start=1/evidence=experimental/product="Sm protein G"/protein_id="CAA59689.1"/db_xref="GI:806566"/db_xref="GOA:Q15357"/db_xref="UniProt/Swiss-Prot:Q15357"
2 0 1 0 1 0 0 0 0 1 3 4 1 0 0 0 1 2 0 0 0 1 0 2 0 1 0 1 1 1 5 1 0 1 2 1 3 0 4 2 2 3 2 1 1 1 3 2 1 2 0 0 0 1 0 3 3 2 1 6 0 1 0 0
>AY532090\AY532090\3712..3792\81\AAT09392.1\Homo sapiens\Homo sapiens isolate YCC26 truncated 5-aminoevulinate synthase 2(ALAS2) gene, exons 2 and 3 and complete cds./gene="ALAS2"/codon_start=1/product="truncated 5-aminoevulinate synthase 2"/protein_id="AAT09392.1"/db_xref="GI:47059411"
0 0 0 0 0 1 1 0 2 0 0 1 0 0 0 0 0 1 0 0 0 1 0 2 1 2 1 1 0 1 0 0 1 2 0 0 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 1 0 0
>BT006838\BT006838\1..1410\1410\AAP35484.1\Homo sapiens\Homo sapiens v-ets erythroblastosis virus E26 oncogene homolog 2(avian) mRNA, complete cds./codon_start=1/product="v-ets erythroblastosis virus E26 oncogene homolog 2 (avian)"/protein_id="AAP35484.1"/db_xref="GI:30582515"
0 7 5 0 1 3 2 15 20 2 4 7 4 12 2 8 15 8 9 8 4 1 6 10 3 9 2 10 2 5 7 14 5 3 3 4 12 4 8 18 14 13 10 21 4 3 13 19 20 8 9 3 7 3 15 10 1 7 5 11 11 0 1 0
>HUMTHYP\M24398\301..609\309\AAA61185.1\Homo sapiens\Human parathymosin mRNA, complete cds./gene="PTMS"/codon_start=1/protein_id="AAA61185.1"/db_xref="GI:339699"/db_xref="GDB:G00-125-555"
1 0 2 0 1 0 0 0 2 0 0 1 0 0 2 0 3 0 1 0 0 1 0 2 0 0 3 4 4 2 1 0 4 0 0 0 4 0 4 9 1 1 0 1 0 0 18 21 1 7 0 0 0 0 0 0 0 0 0 1 0 0 0 1
>AB107883\AB107883\1..1209\1209\BAC79077.1\Homo sapiens\Homo sapiens BRAL2 mRNA for brain link protein-2, complete cds./gene="BRAL2"/codon_start=1/product="brain link protein-2"/protein_id="BAC79077.1"/db_xref="GI:32480475"
4 18 8 5 0 1 2 7 24 0 0 2 1 3 2 1 3 2 3 8 2 0 1 10 7 8 9 19 21 7 4 35 15 7 4 12 16 0 0 9 8 1 2 10 9 1 5 10 15 5 11 3 10 1 12 1 0 3 0 2 13 0 1 0
>HSB29IGBV\X83539\1..378\378\CAA58522.1\Homo sapiens\H.sapiens B29 mRNA for Ig-beta, splice variant./gene="B29, alternative-spliced form"/codon_start=1/product="Ig-beta, variant"/protein_id="CAA58522.1"/db_xref="GI:620078"/db_xref="GOA:P40259"/db_xref="UniProt/Swiss-Prot:P40259"
0 0 3 0 1 2 0 2 13 0 0 3 1 0 1 2 3 0 2 3 3 0 3 2 0 2 2 3 2 2 1 3 1 2 2 0 5 0 1 5 1 1 0 5 3 0 2 7 6 3 2 1 0 0 3 0 1 8 1 4 2 0 0 1
>AF165281\AF165281\121..6726\6606\AAD49849.1\Homo sapiens\Homo sapiens ATP cassette binding transporter 1 (ABC1) mRNA,complete cds./gene="ABC1"/codon_start=1/product="ATP cassette binding transporter 1"/protein_id="AAD49849.1"/db_xref="GI:5734101"
12 12 22 3 26 24 14 44 109 32 14 29 25 36 3 38 46 30 40 46 10 23 26 32 8 36 27 49 5 40 40 49 42 16 11 44 86 25 47 78 57 44 19 65 18 20 54 71 60 55 40 27 19 17 60 54 13 72 39 61 37 0 0 1
>HSU03907\U03907\1..1098\1098\AAA03605.1\Homo sapiens\Human MHC Class I HLA-B-3201 mRNA, complete cds./codon_start=1/product="Class I HLA-B-3201"/protein_id="AAA03605.1"/db_xref="GI:432996"
2 9 6 1 5 7 2 10 13 1 0 3 2 5 0 9 8 2 4 14 6 2 0 8 5 3 2 15 12 10 5 9 10 2 0 3 17 1 2 8 3 1 0 24 5 4 0 23 17 5 11 3 4 1 7 2 1 9 1 10 11 0 0 1
>BC039033\BC039033\89..478\390\AAH39033.1\Homo sapiens\Homo sapiens HLA class II region expressed gene KE2, mRNA (cDNAclone MGC:47665 IMAGE:5748799), complete cds./gene="HKE2"/codon_start=1/product="HLA class II region expressed gene KE2"/protein_id="AAH39033.1"/db_xref="GI:24658611"/db_xref="GeneID:10471"/db_xref="MIM:605660"
1 0 4 0 0 3 4 0 8 5 1 0 1 3 1 0 0 1 3 1 0 0 0 0 1 1 4 4 1 4 1 1 5 1 1 2 4 0 6 7 1 2 3 14 0 0 6 9 2 2 1 2 0 0 1 1 0 3 1 2 0 0 0 1
>BC015761\BC015761\145..1902\1758\AAH15761.1\Homo sapiens\Homo sapiens lectin, galactoside-binding, soluble, 3 bindingprotein, mRNA (cDNA clone MGC:23157 IMAGE:4858122), complete cds./gene="LGALS3BP"/codon_start=1/product="galectin 3 binding protein"/protein_id="AAH15761.1"/db_xref="GI:16041761"/db_xref="GeneID:3959"/db_xref="MIM:600626"
1 5 7 1 5 10 2 18 46 2 0 4 6 16 6 5 15 6 3 23 4 6 1 20 3 4 6 35 2 5 3 24 8 3 0 15 19 1 3 16 14 3 6 23 8 1 4 27 25 8 17 5 13 3 26 4 0 10 4 9 16 0 1 0
>BC034393\BC034393\26..562\537\AAH34393.1\Homo sapiens\Homo sapiens endothelin 2, mRNA (cDNA clone MGC:34606IMAGE:5185394), complete cds./gene="EDN2"/codon_start=1/product="endothelin 2"/protein_id="AAH34393.1"/db_xref="GI:21706719"/db_xref="GeneID:1907"/db_xref="MIM:131241"
2 5 5 1 2 7 1 4 6 4 0 1 1 11 0 1 3 1 5 5 0 4 4 2 1 5 2 11 2 3 2 4 3 0 0 4 4 1 0 7 2 0 3 6 2 3 3 5 5 0 2 0 7 2 3 1 0 2 1 2 5 0 1 0
>AK025764\AK025764\42..455\414\BAB15235.1\Homo sapiens\Homo sapiens cDNA: FLJ22111 fis, clone HEP18290./codon_start=1/protein_id="BAB15235.1"/db_xref="GI:10438381"
2 1 0 0 1 0 2 0 0 4 6 3 1 0 0 1 1 2 4 0 1 2 3 1 0 2 4 3 0 1 6 1 1 0 0 0 3 1 8 4 1 6 3 2 0 2 10 0 6 6 2 1 0 1 2 9 3 0 4 6 4 0 1 0
>AB035340#2\AB035340\3243..3461\219\BAA96378.1\Homo sapiens\Homo sapiens TCL6f1 mRNA for T-cell leukemia/lymphoma 6 ORF141,T-cell leukemia/lymphoma 6 ORF72, complete cds, clone:pDG1./gene="TCL6f1"/codon_start=1/product="T-cell leukemia/lymphoma 6 ORF72"/protein_id="BAA96378.1"/db_xref="GI:8176583"
1 0 0 0 1 2 0 0 1 1 2 1 2 1 0 3 1 4 0 1 0 1 1 0 1 2 4 3 0 4 7 1 1 1 0 0 2 0 0 0 0 1 1 2 1 0 0 2 1 2 1 0 3 1 2 1 0 1 0 2 2 0 0 1
>AK002011\AK002011\314..802\489\BAA92033.1\Homo sapiens\Homo sapiens cDNA FLJ11149 fis, clone PLACE1006731, weakly similarto RIBOFLAVIN KINASE (EC 2.7.1.26)/ FMN ADENYLYLTRANSFERASE (EC2.7.7.2)./codon_start=1/protein_id="BAA92033.1"/db_xref="GI:7023634"
2 1 2 0 1 1 1 1 3 2 2 1 2 2 0 3 2 3 2 1 1 1 4 2 0 2 1 2 1 3 3 6 1 4 1 1 6 3 6 7 2 5 3 2 2 4 7 4 3 5 4 3 2 0 6 2 3 4 6 6 2 0 0 1
>CR456983\CR456983\1..1245\1245\CAG33264.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834D025D forgene STAF65(gamma), SPTF-associated factor 65 gamma; complete cds,incl. stopcodon./gene="STAF65(gamma)"/codon_start=1/protein_id="CAG33264.1"/db_xref="GI:48146083"
1 4 5 4 2 3 2 11 14 7 1 3 10 7 1 5 8 14 4 4 1 7 8 7 1 20 4 8 1 11 4 5 7 4 3 6 13 2 5 13 6 9 4 21 8 6 17 21 14 8 3 5 3 4 8 6 2 7 8 10 4 1 0 0
>AK021843\AK021843\164..589\426\BAB13908.1\Homo sapiens\Homo sapiens cDNA FLJ11781 fis, clone HEMBA1005963./codon_start=1/protein_id="BAB13908.1"/db_xref="GI:10433112"
0 1 1 1 5 4 3 2 3 0 4 3 9 6 0 3 0 1 6 1 0 2 2 4 0 4 1 3 0 4 0 2 3 0 1 0 2 1 6 3 1 4 3 4 1 3 2 2 1 1 2 3 0 3 3 1 4 2 4 4 2 1 0 0
>AK022850\AK022850\10..867\858\BAB14272.1\Homo sapiens\Homo sapiens cDNA FLJ12788 fis, clone NT2RP2001946./codon_start=1/protein_id="BAB14272.1"/db_xref="GI:10434483"
3 5 6 2 1 2 3 6 15 3 0 3 4 3 0 6 10 4 1 3 0 5 7 12 1 5 2 8 1 6 6 6 7 5 0 2 8 2 5 16 2 1 5 12 3 2 9 23 5 11 4 1 5 3 3 2 1 2 1 4 2 0 0 1
>HUMGPMIVI\M60710\join(38..136,844..936,1870..1908)\231\AAA35929.1\Homo sapiens\Human glycophorin (HGpMiVI) gene, exons 2-4./gene="HGpMiVI"/codon_start=3/product="glycophorin MiVI"/protein_id="AAA35929.1"/db_xref="GI:553319"
0 0 1 0 2 2 1 2 5 3 1 2 2 1 0 1 1 0 4 1 0 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 0 2 4 2 2 0 5 6 1 3 0 1 1 0 1 1 1 0 0 3 2 2 0 2 1 1 0 1
>AY341953\AY341953\342..599\258\AAQ76866.1\Homo sapiens\Homo sapiens chromosome 20 F379 retina specific protein (F379)mRNA, complete cds./gene="F379"/codon_start=1/product="F379 retina specific protein"/protein_id="AAQ76866.1"/db_xref="GI:34596537"
0 0 0 0 2 0 0 2 3 1 3 3 2 1 1 2 2 0 3 4 1 1 1 2 1 3 0 3 0 2 0 1 2 2 0 0 0 2 3 3 1 1 1 1 2 1 2 1 1 3 0 1 1 1 3 1 2 1 2 2 1 1 0 0
>BC008753\BC008753\222..764\543\AAH08753.1\Homo sapiens\Homo sapiens ADP-ribosylation factor 4, mRNA (cDNA clone MGC:1097IMAGE:3346199), complete cds./gene="ARF4"/codon_start=1/product="ADP-ribosylation factor 4"/protein_id="AAH08753.1"/db_xref="GI:14250597"/db_xref="GeneID:378"/db_xref="MIM:601177"
1 1 0 3 4 1 3 3 7 7 1 4 2 3 0 1 1 1 6 5 0 3 1 0 0 2 4 2 0 3 3 3 2 5 5 1 3 3 5 6 4 4 3 7 0 1 7 3 1 10 1 4 0 2 3 4 1 2 8 6 4 1 0 0
>AF117210\AF117210\13..2391\2379\AAD27814.1\Homo sapiens\Homo sapiens host cell factor 2 (HCF-2) mRNA, complete cds./gene="HCF-2"/codon_start=1/product="host cell factor 2"/protein_id="AAD27814.1"/db_xref="GI:4689221"
5 3 4 2 14 7 7 2 12 14 10 12 22 8 0 19 13 17 26 9 6 18 23 5 3 24 23 10 4 17 22 10 10 17 12 7 15 22 33 13 12 32 15 11 8 12 24 13 6 27 9 18 5 12 7 17 8 15 12 13 16 0 0 1
>AK074518\AK074518\497..1435\939\BAC11035.1\Homo sapiens\Homo sapiens cDNA FLJ90037 fis, clone HEMBA1002048, moderatelysimilar to ODD-SKIPPED PROTEIN./codon_start=1/protein_id="BAC11035.1"/db_xref="GI:22760013"
2 3 6 1 6 5 2 8 15 1 1 4 0 5 2 3 7 2 2 12 7 5 4 11 8 2 1 9 7 2 5 5 4 2 1 1 6 1 13 9 3 6 2 12 20 3 2 8 10 4 6 1 4 7 9 8 0 9 1 6 1 0 1 0
>BC008953\BC008953\55..573\519\AAH08953.1\Homo sapiens\Homo sapiens thioredoxin domain containing 12 (endoplasmicreticulum), mRNA (cDNA clone MGC:3735 IMAGE:2959502), complete cds./gene="TXNDC12"/codon_start=1/product="endoplasmic reticulum thioredoxin superfamily member, 18 kDa"/protein_id="AAH08953.1"/db_xref="GI:14286304"/db_xref="GeneID:51060"
1 0 1 1 1 2 1 4 7 4 0 2 1 2 0 3 2 4 1 1 3 0 1 5 0 3 2 4 0 4 6 2 5 3 1 2 2 3 6 7 1 5 1 2 0 7 13 5 1 9 1 3 1 2 4 5 0 4 5 4 2 1 0 0
>BC012163\BC012163\7..345\339\AAH12163.1\Homo sapiens\Homo sapiens mitochondrial ribosomal protein L53, mRNA (cDNA cloneMGC:20402 IMAGE:4622995), complete cds./gene="MRPL53"/codon_start=1/product="mitochondrial ribosomal protein L53"/protein_id="AAH12163.1"/db_xref="GI:15082500"/db_xref="GeneID:116540"
0 4 4 0 0 3 0 3 5 1 0 1 1 3 1 0 2 1 0 3 2 2 0 2 1 1 1 4 3 5 1 4 2 2 0 2 6 2 2 2 2 1 0 3 1 3 2 3 6 1 0 0 2 1 5 0 0 1 2 3 0 0 0 1
>AB041018\AB041018\418..1311\894\BAD74066.1\Homo sapiens\Homo sapiens C2orf4a mRNA for chromosome 2 open reading frame 4a,complete cds./gene="C2orf4"/codon_start=1/product="chromosome 2 open reading frame 4 long form"/protein_id="BAD74066.1"/db_xref="GI:56377669"
3 1 1 2 6 2 3 5 6 4 3 3 4 4 2 9 4 11 7 2 2 1 0 3 2 7 5 8 1 7 9 0 5 3 3 2 7 2 8 5 2 8 6 9 3 10 13 4 4 9 7 10 2 5 5 6 3 2 13 9 5 0 0 1
>BC015887\BC015887\54..1268\1215\AAH15887.1\Homo sapiens\Homo sapiens WD repeat and SOCS box-containing 2, mRNA (cDNA cloneMGC:10210 IMAGE:3910968), complete cds./gene="WSB2"/codon_start=1/product="WD SOCS-box protein 2"/protein_id="AAH15887.1"/db_xref="GI:16198433"/db_xref="GeneID:55884"
2 3 4 0 4 7 4 8 20 8 3 5 4 11 2 8 12 6 8 5 6 4 7 12 3 4 5 11 1 6 5 9 8 3 0 14 7 4 12 10 1 5 6 9 12 2 7 10 10 11 7 0 9 4 9 8 0 9 8 7 15 1 0 0
>HS125H231\AL035291\220..3984\3765\CAA22894.1\Homo sapiens\H.sapiens gene from PACs 125H23 and 105D12./codon_start=1/product="hypothetical protein"/protein_id="CAA22894.1"/db_xref="GI:4200228"/db_xref="GOA:Q9UBS9"/db_xref="UniProt/TrEMBL:Q9UBS9"
7 4 6 3 13 6 10 5 18 29 19 23 50 10 3 50 17 26 33 10 2 31 34 11 4 22 20 18 2 22 26 7 2 16 24 9 15 30 62 32 7 54 25 32 8 14 85 40 16 51 7 28 8 14 7 24 27 12 32 25 7 1 0 0
>AF144412\AF144412\2490..2675\186\AAD38378.1\Homo sapiens\Homo sapiens lens epithelial cell protein (LEP503) gene, completecds./gene="LEP503"/codon_start=1/product="lens epithelial cell protein"/protein_id="AAD38378.1"/db_xref="GI:5051958"
1 0 3 0 0 0 2 3 4 0 0 0 0 0 0 0 0 0 2 2 0 1 0 3 0 2 0 3 0 0 1 2 3 0 0 2 1 0 0 3 0 0 1 3 0 0 2 1 1 1 1 0 2 1 3 0 0 2 1 2 2 1 0 0
>AF120274\AF120274\783..1445\663\AAD21075.1\Homo sapiens\Homo sapiens pre-pro-neublastin mRNA, complete cds./codon_start=1/product="pre-pro-neublastin"/protein_id="AAD21075.1"/db_xref="GI:4455085"
2 17 8 1 2 1 1 4 17 3 0 0 0 10 1 3 9 1 0 4 3 0 2 14 11 6 3 12 10 5 4 15 5 0 0 5 4 0 0 0 1 0 0 4 4 0 3 2 4 0 1 0 9 0 3 0 0 0 0 2 4 0 0 1
>BC047365\BC047365\523..903\381\AAH47365.1\Homo sapiens\Homo sapiens hypothetical protein LOC130355, mRNA (cDNA cloneMGC:35431 IMAGE:5189916), complete cds./gene="LOC130355"/codon_start=1/product="hypothetical protein LOC130355"/protein_id="AAH47365.1"/db_xref="GI:66840145"/db_xref="GeneID:130355"
0 2 0 1 2 2 2 2 4 1 1 3 2 2 0 0 1 2 2 2 0 3 3 1 0 3 4 1 0 3 3 0 0 0 3 1 4 1 6 4 2 5 3 0 1 3 11 0 3 4 1 4 0 1 4 3 0 4 4 1 1 0 0 1
>BT006931\BT006931\1..999\999\AAP35577.1\Homo sapiens\Homo sapiens dystonia 1, torsion (autosomal dominant; torsin A)mRNA, complete cds./codon_start=1/product="dystonia 1, torsion (autosomal dominant; torsin A)"/protein_id="AAP35577.1"/db_xref="GI:30582701"
3 0 4 1 2 4 1 12 16 2 4 5 2 5 1 1 8 4 4 4 2 0 2 5 2 2 5 9 4 4 4 11 3 3 1 4 13 3 10 14 9 5 0 9 7 3 8 9 8 14 9 6 4 2 13 8 4 12 7 7 4 0 1 0
>AY358899\AY358899\62..1393\1332\AAQ89258.1\Homo sapiens\Homo sapiens clone DNA33460 EFEMP2 (UNQ200) mRNA, complete cds./locus_tag="UNQ200"/codon_start=1/product="EFEMP2"/protein_id="AAQ89258.1"/db_xref="GI:37182916"
1 16 6 2 0 2 5 9 16 0 0 4 2 14 2 6 10 1 2 11 2 0 8 15 4 9 0 15 3 5 3 12 10 4 2 10 13 1 0 3 18 2 4 21 9 4 3 24 17 11 19 5 28 14 9 3 1 9 4 8 2 0 0 1
>AL590559#4\AL590559\complement(join(2366..2422,4325..4498,9168..9345, 13359..13481,14047..14136,14242..14382,15294..15444, 19147..19459))\1227\CAH73323.1\Homo sapiens\Human DNA sequence from clone RP11-393N21 on chromosome 1 Containsthe 5' end of the gene for PAI-1 mRNA-binding protein (PAI-RBP1), apoly(A) binding protein, cytoplasmic 4 (PABPC4) pseudogene, a novelgene and a CpG island, complete sequence./gene="RP11-102M16.2"/locus_tag="RP11-393N21.3-006"/standard_name="OTTHUMP00000010978"/codon_start=1/product="PAI-1 mRNA-binding protein (PAI-RBP1)"/protein_id="CAH73323.1"/db_xref="GI:55665493"/db_xref="InterPro:IPR006861"
10 4 2 11 9 4 0 0 6 6 3 2 5 3 2 7 4 6 2 3 2 4 11 5 3 7 8 4 3 9 18 17 9 12 2 2 7 8 17 18 7 9 5 11 3 8 25 17 16 14 3 1 1 0 6 8 4 2 6 4 3 1 0 0
>AF365928\AF365928\148..1821\1674\AAM00356.1\Homo sapiens\Homo sapiens calcium transport protein CaT1 mRNA, complete cds,alternatively spliced./codon_start=1/product="calcium transport protein CaT1"/protein_id="AAM00356.1"/db_xref="GI:19880486"
4 9 15 1 4 6 6 18 40 6 2 3 5 8 1 2 9 3 4 21 4 5 4 15 2 5 2 18 0 6 7 11 13 5 2 6 20 1 4 15 12 3 3 22 9 3 6 21 21 6 13 8 11 1 23 7 2 31 6 25 12 0 0 1
>BC069235\BC069235\224..1957\1734\AAH69235.1\Homo sapiens\Homo sapiens THAP domain containing 4, mRNA (cDNA clone MGC:78456IMAGE:6645198), complete cds./gene="THAP4"/codon_start=1/product="THAP domain containing 4"/protein_id="AAH69235.1"/db_xref="GI:46623323"/db_xref="GeneID:51078"
2 9 8 1 4 13 3 3 27 4 1 1 8 22 7 7 21 8 8 15 6 5 13 20 6 5 5 28 6 7 11 17 8 3 1 9 21 2 8 33 13 1 4 27 13 5 9 28 13 9 5 2 9 3 14 4 0 13 3 11 5 1 0 0
>AY074877\AY074877\249..2990\2742\AAL79676.1\Homo sapiens\Homo sapiens pVHL-interacting deubiquitinating enzyme 2 (VDU2)mRNA, complete cds./gene="VDU2"/codon_start=1/product="pVHL-interacting deubiquitinating enzyme 2"/protein_id="AAL79676.1"/db_xref="GI:23262727"
6 12 22 3 1 7 3 16 44 6 2 8 8 23 9 9 26 6 5 20 11 2 12 24 11 8 9 38 5 12 11 26 17 6 5 21 31 3 11 37 24 4 2 42 22 6 8 62 38 12 26 4 19 13 26 6 1 25 11 13 13 0 0 1
>HSA400877#6\AJ400877\complement(join(190479..190622,192592..192672, 195028..195132,197427..197507,198287..198508))\633\CAB92290.1\Homo sapiens\Homo sapiens ASCL3 gene, CEGP1 gene, C11orf14 gene, C11orf15 gene,C11orf16 gene and C11orf17 gene./gene="C11orf17"/codon_start=1/product="C11orf17 protein"/protein_id="CAB92290.1"/db_xref="GI:8052242"/db_xref="UniProt/Swiss-Prot:Q9NQ31"
1 1 1 4 6 3 2 2 7 3 1 2 5 4 1 4 2 2 2 4 0 3 4 3 3 3 6 5 4 5 4 5 6 2 2 4 8 2 5 7 2 3 2 6 3 4 5 11 9 1 1 8 2 2 3 0 3 1 0 5 1 0 0 1
>AL451062#4\AL451062 AC026934\join(53597..53759,AL592548.10:7818..7865, AL592548.10:30608..30650,AL592548.10:53936..54028, AL357079.24:14444..14538,AL357079.24:50193..50263)\-2491626\CAH71026.1\Homo sapiens\Human DNA sequence from clone RP11-184I16 on chromosome 1 Containsthe 3' end of the JMJD2 gene for jumonji domain containing 2, twonovel genes, the 5' end of the SIAT6 gene for sialyltransferase 6(N-acetyllacosaminide alpha 2,3-sialyltransferase), a SMT3suppressor of mif two 3 (yeast) family pseudogene and a CpG island,complete sequence./gene="SIAT6"/locus_tag="RP11-7O11.1-007"/standard_name="OTTHUMP00000008817"/codon_start=1/product="sialyltransferase 6 (N-acetyllacosaminide alpha 2,3-sialyltransferase)"/protein_id="CAH71026.1"/db_xref="GI:55665241"
2 2 0 0 1 2 6 6 4 3 1 6 3 3 1 5 3 4 3 1 0 2 2 2 0 2 1 3 1 1 5 2 3 1 2 1 3 3 4 5 3 2 2 6 4 5 2 3 1 1 1 4 2 6 3 6 5 0 4 3 5 1 2 1
>AF417920\AF417920\264..1553\1290\AAL59159.1\Homo sapiens\Homo sapiens ASB-10 mRNA, complete cds./codon_start=1/product="ASB-10"/protein_id="AAL59159.1"/db_xref="GI:18092200"
3 14 7 5 5 7 1 17 39 5 0 4 2 9 1 4 8 3 2 12 2 2 8 14 2 6 10 25 6 13 7 14 9 2 0 9 13 2 2 5 4 1 1 13 10 9 6 20 12 11 4 1 6 10 5 3 0 5 0 3 6 0 1 0
>BC017318\BC017318\252..677\426\AAH17318.1\Homo sapiens\Homo sapiens hypothetical protein MGC29643, mRNA (cDNA cloneMGC:29643 IMAGE:3641660), complete cds./gene="MGC29643"/codon_start=1/product="hypothetical protein MGC29643"/protein_id="AAH17318.1"/db_xref="GI:16878240"/db_xref="GeneID:116372"
0 2 0 0 0 3 1 5 4 2 1 2 3 5 2 2 1 2 0 3 1 1 4 2 0 1 3 7 3 0 2 2 5 0 0 1 3 2 4 2 6 1 3 5 1 0 3 2 2 0 3 0 9 5 6 2 0 6 1 4 1 0 0 1
>HSHHA2GEN\X90761\join(4581..5048,5730..5812,5977..6133,7463..7624, 7703..7828,8856..9076,11662..11791)\1347\CAA62284.1\Homo sapiens\Homo sapiens hHa2 gene./gene="hHa2"/codon_start=1/product="HHa2 hair keratin type I intermediate filament"/protein_id="CAA62284.1"/db_xref="GI:3757666"/db_xref="GOA:Q14532"/db_xref="InterPro:IPR001664"/db_xref="InterPro:IPR002957"/db_xref="UniProt/Swiss-Prot:Q14532"
1 9 11 0 1 9 1 6 35 6 0 1 2 16 2 4 11 4 2 14 6 4 4 9 1 6 5 22 1 5 0 11 2 1 0 8 15 4 3 9 15 8 3 29 2 2 5 39 15 4 10 2 19 7 6 0 0 10 4 15 2 0 0 1
>HSA539427#2\AJ539427\311..1045\735\CAD62383.1\Homo sapiens\Homo sapiens mRNA for IKIP3 (IKIP gene)./gene="IKIP"/codon_start=1/product="IKIP3"/protein_id="CAD62383.1"/db_xref="GI:41529139"/db_xref="UniProt/TrEMBL:Q6ZWH4"
3 1 1 2 5 1 10 2 3 3 8 3 5 3 0 6 2 6 12 2 4 5 2 0 0 0 5 1 0 3 0 0 1 4 8 1 3 4 15 12 3 11 8 2 1 2 14 4 7 13 0 1 0 0 2 4 10 0 12 3 1 0 1 0
>AY049737\AY049737\16..552\537\AAL12172.1\Homo sapiens\Homo sapiens nucleophosmin/nucleoplasmin 3 (NPM3) mRNA, completecds./gene="NPM3"/codon_start=1/product="nucleophosmin/nucleoplasmin 3"/protein_id="AAL12172.1"/db_xref="GI:16118247"
1 2 5 0 0 1 2 6 5 1 1 1 0 3 1 2 3 4 0 5 2 3 1 3 2 4 3 9 2 1 1 6 4 2 3 4 5 4 2 4 2 2 2 5 3 2 6 16 5 5 0 0 3 2 5 3 0 3 1 5 0 0 1 0
>AF428136\AF428136\1..1173\1173\AAQ04219.1\Homo sapiens\Homo sapiens cell line PE/CA-PJ15 SCCA1/SCCA2 fusion protein mRNA,complete cds./codon_start=1/product="SCCA1/SCCA2 fusion protein"/protein_id="AAQ04219.1"/db_xref="GI:33313307"
1 0 1 0 4 3 5 9 6 4 7 5 9 5 1 4 6 5 9 8 3 7 5 0 0 5 8 8 0 6 6 4 3 3 5 7 7 5 20 17 12 15 7 10 6 3 20 14 5 11 4 8 0 3 16 10 3 9 6 12 5 0 1 0
>AL161645#3\AL161645\complement(join(138931..138969,139992..140079, 140238..140348,140421..140544,140622..140688, 141400..141463,141708..141797,142505..142559, 142808..142855,143518..143592,143942..144001, 144732..144759))\849\CAH70048.1\Homo sapiens\Human DNA sequence from clone RP11-108K14 on chromosome 10 Containsthe 3' end of a novel gene (LOC92170) (FLJ90495, FLJ39553), threenovel genes, the CYP2E1 gene for family 2 subfamily E polypeptide 1cytochrome P450, a novel gene (LOC93426), the 3' end of a olfactoryreceptor protein pseudogene and eight CpG islands, completesequence./gene="RP11-108K14.6"/locus_tag="RP11-108K14.6-001"/standard_name="OTTHUMP00000020812"/codon_start=1/product="novel protein"/protein_id="CAH70048.1"/db_xref="GI:55661922"/db_xref="UniProt/TrEMBL:Q9BWU4"
1 2 5 0 4 5 3 6 23 1 0 4 0 2 1 1 6 2 4 4 0 0 4 3 0 1 6 9 1 7 6 3 1 1 1 4 6 1 8 20 3 2 8 25 7 4 14 26 6 3 0 0 4 3 2 2 0 3 5 6 3 0 0 1
>HSU79262\U79262\96..1205\1110\AAB50208.1\Homo sapiens\Human deoxyhypusine synthase mRNA, complete cds./codon_start=1/product="deoxyhypusine synthase"/protein_id="AAB50208.1"/db_xref="GI:1710220"
1 6 6 1 0 3 1 6 21 4 0 3 3 6 2 2 5 2 7 10 2 1 5 7 2 2 4 16 5 6 2 15 7 4 3 8 13 2 0 17 16 6 2 13 6 2 7 19 16 4 9 3 4 0 9 6 0 16 5 12 4 0 0 1
>AF153341\AF153341\233..1441\1209\AAF75586.1\Homo sapiens\Homo sapiens winged helix/forkhead transcription factor (HFH1)gene, complete cds./gene="HFH1"/codon_start=1/product="winged helix/forkhead transcription factor"/protein_id="AAF75586.1"/db_xref="GI:8489093"/IGNORED_CODON=1
1 22 6 2 1 2 1 14 17 3 1 2 1 6 8 0 10 2 0 2 8 0 4 27 20 3 6 25 39 3 2 32 10 1 0 5 7 0 0 12 7 0 0 6 5 0 1 18 14 2 9 1 6 0 10 1 0 7 0 5 4 0 0 1
>BC011775\BC011775\287..1369\1083\AAH11775.1\Homo sapiens\Homo sapiens non imprinted in Prader-Willi/Angelman syndrome 2,transcript variant 3, mRNA (cDNA clone MGC:19609 IMAGE:3640970),complete cds./gene="NIPA2"/codon_start=1/product="non imprinted in Prader-Willi/Angelman syndrome 2, isoform a"/protein_id="AAH11775.1"/db_xref="GI:15079979"/db_xref="GeneID:81614"/db_xref="MIM:608146"
3 1 1 1 3 2 8 5 13 10 4 8 5 4 0 7 7 6 8 2 0 8 5 1 0 4 7 7 3 10 11 9 5 9 3 8 15 4 8 8 3 14 3 3 2 6 9 7 4 4 3 7 1 5 9 13 5 7 18 9 5 1 0 0
>AY369207\AY369207\253..882\630\AAQ73311.1\Homo sapiens\Homo sapiens RNA-binding protein with multiple splicing 2 (RBPMS2)mRNA, complete cds./gene="RBPMS2"/codon_start=1/product="RNA-binding protein with multiple splicing 2"/protein_id="AAQ73311.1"/db_xref="GI:34485858"
0 2 3 2 2 1 3 5 9 0 0 2 0 6 0 1 6 0 2 8 0 5 5 6 2 5 7 14 4 5 3 10 3 2 0 2 4 1 2 8 4 3 1 5 4 1 4 7 6 1 6 2 0 1 5 5 0 5 2 4 3 0 1 0
>BT019487\BT019487\1..648\648\AAV38294.1\Homo sapiens\Homo sapiens sodium channel, voltage-gated, type II, beta mRNA,complete cds./codon_start=1/product="sodium channel, voltage-gated, type II, beta"/protein_id="AAV38294.1"/db_xref="GI:54695844"
0 5 3 1 3 1 1 7 10 0 0 2 1 4 1 3 4 1 3 3 3 1 2 4 2 5 0 7 0 1 1 7 4 2 1 6 13 0 3 9 12 1 1 6 3 2 2 14 6 6 5 0 5 1 8 2 0 4 3 8 2 0 1 0
>AY129018\AY129018\58..411\354\AAM98761.1\Homo sapiens\Homo sapiens clone FP18376 unknown mRNA./codon_start=1/product="unknown"/protein_id="AAM98761.1"/db_xref="GI:37547445"
1 1 1 1 2 1 0 5 3 1 3 3 2 3 0 2 6 1 1 5 0 5 3 3 1 3 2 3 0 1 2 2 1 3 2 1 2 0 3 1 1 2 2 5 2 4 0 1 0 0 1 0 2 1 3 1 0 1 2 2 7 1 0 0
>AY040554\AY040554\1..1008\1008\AAK77968.1\Homo sapiens\Homo sapiens SLAM mRNA, complete cds./codon_start=1/product="SLAM"/protein_id="AAK77968.1"/db_xref="GI:15072538"
0 3 2 1 3 4 2 9 14 7 2 5 3 9 0 3 12 3 12 12 2 1 11 5 1 4 4 3 1 7 5 4 8 4 1 9 10 4 12 9 11 6 1 13 3 3 8 12 5 4 6 8 7 0 3 4 6 8 4 8 4 0 0 1
>HSGALT2\Y15060\1..1269\1269\CAA75344.1\Homo sapiens\Homo sapiens mRNA for GalT2 protein./gene="galT2"/codon_start=1/product="GalT2 protein"/protein_id="CAA75344.1"/db_xref="GI:3256001"/db_xref="GOA:O43825"/db_xref="InterPro:IPR002659"/db_xref="UniProt/Swiss-Prot:O43825"
4 3 3 4 9 4 9 1 10 8 7 7 2 1 1 9 5 9 11 4 1 9 9 4 0 12 11 5 0 5 10 7 1 5 4 4 3 5 16 9 11 17 12 4 7 11 14 7 5 7 12 12 3 5 9 12 7 4 14 9 9 1 0 0
>HS5O6#1\AL020993\join(complement(24348..24539),complement(22513..22678), complement(7822..7912),complement(7247..7322), complement(3358..3449),complement(2003..2172), complement(1364..1558), complement(AL021977.10:40844..41085))\192\CAI21955.1\Homo sapiens\Human DNA sequence from clone RP1-5O6 on chromosome 22q12, completesequence./locus_tag="CTA-447C4.2-001"/standard_name="OTTHUMP00000028772"/codon_start=1/protein_id="CAI21955.1"/db_xref="GI:56202405"/db_xref="GOA:Q9Y519"/db_xref="InterPro:IPR005178"/db_xref="UniProt/Swiss-Prot:Q9Y519"
1 2 4 2 1 5 5 11 16 8 1 5 9 8 6 9 10 3 10 10 6 8 8 12 5 14 7 15 4 8 9 16 7 6 2 9 10 3 2 3 1 3 8 7 7 8 6 10 2 3 7 4 11 4 12 1 0 10 2 7 11 0 1 3
>HSA302551\AJ302551\1..936\936\CAC20476.1\Homo sapiens\Homo sapiens 6M1-3*01 gene for olfactory receptor, cell line OLGA./gene="6M1-3*01"/codon_start=1/product="olfactory receptor"/protein_id="CAC20476.1"/db_xref="GI:12054343"/db_xref="GOA:O76001"/db_xref="UniProt/Swiss-Prot:O76001"
2 1 0 2 4 1 3 14 16 7 2 4 6 5 1 8 3 2 6 10 0 4 4 0 2 8 5 3 0 8 8 2 4 3 7 8 7 9 3 3 5 6 4 4 5 6 4 3 2 6 8 6 4 6 10 11 4 11 5 11 5 0 0 1
>AK128511\AK128511\252..1412\1161\BAC87473.1\Homo sapiens\Homo sapiens cDNA FLJ46666 fis, clone TRACH3007625./codon_start=1/protein_id="BAC87473.1"/db_xref="GI:34535916"
3 2 6 1 4 2 3 10 12 4 5 7 3 4 1 10 5 4 7 3 0 1 6 2 0 12 4 11 0 7 10 10 7 6 4 7 6 5 6 5 4 4 6 5 9 11 12 11 5 10 5 7 6 6 14 18 6 11 10 12 9 0 0 1
>AF101264\AF101264\1..1254\1254\AAD04566.1\Homo sapiens\Homo sapiens Ca2+/calmodulin-dependent kinase kinase mRNA, completecds./codon_start=1/product="Ca2+/calmodulin-dependent kinase kinase"/protein_id="AAD04566.1"/db_xref="GI:4151803"
1 5 8 5 0 4 1 9 21 0 2 6 4 10 4 5 4 3 2 12 4 1 8 16 6 5 3 8 3 3 5 10 5 4 0 12 18 1 8 21 9 7 1 14 9 2 14 20 15 6 9 3 6 3 8 6 2 19 4 11 2 0 1 0
>BC008734\BC008734\167..1264\1098\AAH08734.1\Homo sapiens\Homo sapiens Fc fragment of IgG, receptor, transporter, alpha, mRNA(cDNA clone MGC:1506 IMAGE:3163446), complete cds./gene="FCGRT"/codon_start=1/product="Fc fragment of IgG, receptor, transporter, alpha"/protein_id="AAH08734.1"/db_xref="GI:14250561"/db_xref="GeneID:2217"/db_xref="MIM:601437"
1 3 6 1 1 5 3 12 28 5 0 4 1 12 4 1 7 4 2 11 1 2 4 11 5 8 2 15 7 8 8 15 11 4 2 6 11 0 4 10 6 4 1 14 8 0 5 17 8 5 6 1 4 2 12 3 0 5 2 4 13 0 0 1
>AJ938058\AJ938058\6..1238\1233\CAI79393.1\Homo sapiens\Homo sapiens mRNA for killer cell immunoglobulin-like receptor(KIR3DL3 gene), variant 44b TM3./gene="KIR3DL3"/codon_start=1/product="killer cell immunoglobulin-like receptor"/protein_id="CAI79393.1"/db_xref="GI:62700724"
0 5 2 2 9 6 2 12 13 6 1 6 6 9 3 9 6 4 9 7 2 7 6 16 2 13 8 8 4 4 7 5 12 9 2 13 16 6 6 3 10 5 4 11 11 5 5 13 11 4 7 3 5 5 12 7 1 8 2 9 6 1 0 0
>AL954664#2\AL954664\join(18932..19085,20954..21072,21140..21246,25333..25483)\531\CAI41962.1\Homo sapiens\Human DNA sequence from clone LL0YNC03-56G10 on chromosome XContains the 3' end of the gene for protein phosphatase 2A 48 kDaregulatory subunit (PR48), a novel gene and five CpG islands,complete sequence./gene="PPP2R3B"/locus_tag="LL0YNC03-56G10.1-007"/standard_name="OTTHUMP00000022820"/codon_start=1/product="protein phosphatase 2 (formerly 2A), regulatory subunit B'', beta"/protein_id="CAI41962.1"/db_xref="GI:57209895"/db_xref="GOA:Q96H01"/db_xref="InterPro:IPR002048"/db_xref="UniProt/TrEMBL:Q96H01"
1 2 0 0 0 4 0 6 18 0 0 0 1 3 1 0 3 1 0 1 1 2 0 5 4 1 1 8 4 1 1 4 4 1 0 2 3 0 1 7 2 0 0 8 1 0 1 23 17 0 7 0 5 0 10 0 0 5 0 4 2 0 0 1
>BC021886\BC021886\21..443\423\AAH21886.1\Homo sapiens\Homo sapiens ribosomal protein L27, mRNA (cDNA clone MGC:5383IMAGE:3445930), complete cds./gene="RPL27"/codon_start=1/product="RPL27 protein"/protein_id="AAH21886.1"/db_xref="GI:18255173"/db_xref="GeneID:6155"/db_xref="MIM:607526"
1 6 2 0 3 1 2 0 4 2 0 1 2 1 0 2 1 0 4 1 0 1 1 4 1 1 0 4 0 6 3 3 0 0 0 6 6 0 9 14 3 2 0 2 1 2 3 2 2 6 6 1 0 0 3 4 1 4 2 3 1 0 1 0
>AY422212\AY422212\105..3401\3297\AAR31184.1\Homo sapiens\Homo sapiens putative non-ribosomal peptide synthetase NRPS1098mRNA, complete cds./codon_start=1/product="putative non-ribosomal peptide synthetase NRPS1098"/protein_id="AAR31184.1"/db_xref="GI:39841348"
4 0 3 2 15 9 7 19 20 29 27 25 30 15 1 34 8 18 29 8 0 29 23 2 8 13 13 10 2 19 28 14 14 12 22 11 24 32 50 24 16 31 19 22 9 24 44 21 13 32 12 23 8 27 11 39 12 15 37 15 15 1 0 0
>BC074966\BC074966\21..590\570\AAH74966.1\Homo sapiens\Homo sapiens interferon, alpha 4, mRNA (cDNA clone MGC:103901IMAGE:30915288), complete cds./gene="IFNA4"/codon_start=1/product="interferon, alpha 4"/protein_id="AAH74966.1"/db_xref="GI:49901646"/db_xref="GeneID:3441"/db_xref="MIM:147564"
0 0 0 0 6 5 2 6 12 2 2 2 2 6 1 5 5 0 3 2 0 4 0 2 0 2 3 5 0 3 2 2 1 1 0 2 5 2 5 4 1 4 5 8 2 3 6 10 4 4 4 1 1 4 7 4 2 7 0 6 2 0 0 1
>AF054821\AF054821\32..1594\1563\AAC08589.1\Homo sapiens\Homo sapiens cytochrome P-450 mRNA, complete cds./codon_start=1/product="cytochrome P-450"/protein_id="AAC08589.1"/db_xref="GI:2997737"
0 14 8 5 2 6 0 16 43 4 0 5 4 5 1 3 10 7 3 13 3 2 7 17 6 8 6 21 3 4 2 9 9 4 2 16 9 3 7 21 8 2 5 15 10 6 6 21 21 8 5 8 10 3 19 10 2 17 10 13 13 0 0 1
>AB084279\AB084279\85..4392\4308\BAD00086.1\Homo sapiens\Homo sapiens ASXH2 mRNA for polycomb group protein, complete cds./gene="ASXH2"/codon_start=1/product="polycomb group protein"/protein_id="BAD00086.1"/db_xref="GI:37998953"
5 2 3 5 30 21 14 19 24 24 17 13 39 28 6 34 48 31 36 32 5 33 48 35 8 37 39 25 5 33 29 28 13 27 13 24 20 24 52 50 20 28 29 67 11 15 50 50 16 29 7 7 14 9 14 14 9 21 15 25 6 1 0 0
>HSU60266\U60266\15..3050\3036\AAC34130.1\Homo sapiens\Homo sapiens lysosomal alpha-mannosidase (manB) mRNA, complete cds./gene="manB"/EC_number="3.2.1.24"/function="necessary for the catabolism of N-linked carbohydrates released during glycoprotein turnover"/codon_start=1/product="lysosomal alpha-mannosidase"/protein_id="AAC34130.1"/db_xref="GI:3522867"
5 29 18 5 5 8 4 21 67 8 1 8 10 13 9 2 21 5 18 24 8 7 6 30 18 14 11 44 18 11 14 28 17 11 8 12 46 9 7 17 31 17 7 50 23 4 7 38 33 18 25 9 9 3 32 12 3 20 5 21 27 0 1 0
>BC034761\BC034761\220..1434\1215\AAH34761.1\Homo sapiens\Homo sapiens adrenomedullin receptor, mRNA (cDNA clone MGC:34399IMAGE:5185932), complete cds./gene="ADMR"/codon_start=1/product="adrenomedullin receptor"/protein_id="AAH34761.1"/db_xref="GI:21961320"/db_xref="GeneID:11318"/db_xref="MIM:605307"
1 5 8 1 0 0 0 18 33 6 0 2 2 12 2 4 14 2 5 15 2 4 4 13 1 10 7 13 3 2 2 10 5 1 1 17 16 1 1 5 9 3 1 10 15 5 1 11 7 2 11 4 12 3 14 7 1 17 2 11 10 0 0 1
>BC095509\BC095509\431..1399\969\AAH95509.1\Homo sapiens\Homo sapiens MAS-related GPR, member X4, mRNA (cDNA cloneMGC:111722 IMAGE:30706615), complete cds./gene="MRGPRX4"/codon_start=1/product="G protein-coupled receptor MRGX4"/protein_id="AAH95509.1"/db_xref="GI:63100789"/db_xref="GeneID:117196"/db_xref="MIM:607230"
0 8 1 3 1 8 2 15 35 2 3 2 2 8 2 4 8 6 6 6 3 1 6 5 1 3 2 4 3 3 5 6 3 3 1 11 9 7 3 3 7 4 1 7 2 2 4 7 3 4 8 2 6 7 12 6 1 14 6 8 7 0 0 1
>AF282882\AF282882\1..273\273\AAM52248.1\Homo sapiens\Homo sapiens plasminogen/activator kringle mRNA, complete cds./codon_start=1/product="plasminogen/activator kringle"/protein_id="AAM52248.1"/db_xref="GI:21425749"
0 0 1 1 1 0 0 2 3 1 0 0 1 3 1 0 1 2 2 1 2 0 1 2 1 2 2 5 1 0 1 4 3 1 0 1 0 1 2 2 2 5 0 3 1 1 0 2 2 3 7 0 4 2 0 1 1 1 0 2 2 1 0 0
>HSLIPOC\X67647\44..574\531\CAA47889.1\Homo sapiens\H.sapiens mRNA for tear lipocalin./codon_start=1/product="lipocalin precursor"/protein_id="CAA47889.1"/db_xref="GI:313856"/db_xref="GOA:P31025"/db_xref="UniProt/Swiss-Prot:P31025"
1 1 1 0 1 3 0 7 12 1 0 1 2 0 2 1 5 1 1 4 4 2 1 4 2 1 2 10 0 2 3 6 6 0 0 4 8 0 3 9 3 1 0 4 6 0 5 12 7 2 4 1 2 1 1 2 1 5 2 5 1 0 1 0
>AF480304\AF480304\1..642\642\AAL89654.1\Homo sapiens\Homo sapiens START domain-containing 5 protein (STARD5) mRNA,complete cds./gene="STARD5"/codon_start=1/product="START domain-containing 5 protein"/protein_id="AAL89654.1"/db_xref="GI:19525702"
2 1 4 0 4 1 3 4 4 2 1 1 1 5 0 2 5 1 3 9 0 2 6 5 3 2 3 5 1 3 4 4 4 4 2 2 13 3 1 9 6 2 2 4 0 5 5 9 7 3 3 3 2 5 6 6 0 3 4 5 4 1 0 0
>BC022475\BC022475\207..884\678\AAH22475.1\Homo sapiens\Homo sapiens insulin induced gene 2, mRNA (cDNA clone MGC:26273IMAGE:4794938), complete cds./gene="INSIG2"/codon_start=1/product="insulin induced protein 2"/protein_id="AAH22475.1"/db_xref="GI:18490895"/db_xref="GeneID:51141"/db_xref="MIM:608660"
2 0 1 1 5 0 4 3 4 3 6 3 3 2 0 8 2 4 4 0 2 4 6 3 0 2 9 2 0 5 9 4 2 4 7 3 8 4 6 1 4 4 3 5 0 4 5 3 1 5 3 4 2 5 3 11 4 2 10 5 6 0 0 1
>AK122653\AK122653\108..3179\3072\BAC85501.1\Homo sapiens\Homo sapiens cDNA FLJ16086 fis, clone NT2RP7005118, moderatelysimilar to RAS GTPASE-ACTIVATING-LIKE PROTEIN IQGAP1./codon_start=1/protein_id="BAC85501.1"/db_xref="GI:34527841"
12 13 16 6 8 14 10 33 65 11 4 10 6 11 2 7 17 4 12 18 4 10 10 13 4 11 23 50 1 24 5 12 16 9 4 21 37 8 14 56 25 10 12 66 25 12 16 45 34 16 20 15 5 2 25 13 3 32 10 17 9 0 0 1
>AF328864\AF328864\31..594\564\AAK15708.1\Homo sapiens\Homo sapiens hypothetical protein SBBI8 mRNA, complete cds./codon_start=1/product="hypothetical protein SBBI8"/protein_id="AAK15708.1"/db_xref="GI:13195462"
3 3 4 0 5 3 2 1 10 3 1 3 2 5 1 4 2 2 0 3 1 1 0 1 3 5 2 4 3 7 8 5 2 2 0 3 3 4 10 6 1 2 6 5 1 1 14 5 4 1 3 2 2 0 2 1 0 2 1 4 3 0 0 1
>AF152525\AF152525\1..2616\2616\AAD43785.1\Homo sapiens\Homo sapiens protocadherin gamma C4 short form protein(PCDH-gamma-C4) variable region sequence, complete cds./gene="PCDH-gamma-C4"/function="cell-cell adhesion"/codon_start=1/product="protocadherin gamma C4 short form protein"/protein_id="AAD43785.1"/db_xref="GI:5457098"
11 9 10 8 8 9 10 27 31 16 3 15 17 14 2 21 20 16 8 14 2 16 27 18 6 20 18 18 2 28 12 14 19 12 13 15 38 11 1 15 15 19 9 20 9 8 13 32 27 32 11 10 6 10 14 21 1 17 9 9 5 1 0 0
>HSA010228\AJ010228\297..1163\867\CAA09043.1\Homo sapiens\Homo sapiens mRNA for RET finger protein-like 1, long variant./gene="rfpl1l"/standard_name="RET finger protein-like 1, long variant"/codon_start=1/evidence=experimental/product="RFPL1L"/protein_id="CAA09043.1"/db_xref="GI:3417312"/db_xref="GOA:O75677"/db_xref="UniProt/Swiss-Prot:O75677"
2 5 2 1 2 7 3 6 12 2 1 4 2 7 0 5 6 7 6 3 1 4 6 4 2 5 2 5 0 7 5 4 5 3 1 9 8 2 4 10 6 3 3 7 4 4 5 12 9 8 1 2 9 6 8 7 1 7 4 8 4 1 0 0
>AL160175#10\AL160175\join(114367..114418,114912..115332,116225..116523, 118263..118368,119045..119138,121391..121500, 121583..121724,125605..125675,125799..125927, 126489..126641,126790..126922,128503..128583)\1791\CAC10006.1\Homo sapiens\Human DNA sequence from clone RP11-243J16 on chromosome 20 Containsthe BCL2L1 gene for the apoptosis regulator BCL2-like 1, theC20orf1 gene encoding the targeting protein for XKLP2 (FLS353), theMYLK gene for myosin light chain kinase 2 (skeletal muscle), theFKHL18 gene for forkhead-like 18 (Drosophila)(FREAC10), an ATPsynthase H+ transporting mitochondrial F0 complex subunit f isoform2 (ATP5J2) pseudogene, the DUSP15 gene for dual specificityphosphatase-like 15, the 3' end of a novel gene, the 5' end of theC20orf125 gene and seven CpG islands, complete sequence./locus_tag="RP11-243J16.2-001"/standard_name="OTTHUMP00000030560"/codon_start=1/protein_id="CAC10006.1"/db_xref="GI:10279705"/db_xref="Genew:16243"/db_xref="GOA:Q9H1R3"/db_xref="HSSP:2BBM"/db_xref="UniProt/Swiss-Prot:Q9H1R3"
1 6 2 0 1 14 2 13 28 2 0 5 9 7 2 2 14 5 8 17 1 4 10 22 5 10 16 24 5 11 10 16 17 5 1 12 14 4 17 35 20 4 5 18 5 5 9 39 18 12 5 3 3 7 11 9 0 17 7 18 4 0 0 1
>AF151830\AF151830\70..1401\1332\AAD34067.1\Homo sapiens\Homo sapiens CGI-72 protein mRNA, complete cds./codon_start=1/product="CGI-72 protein"/protein_id="AAD34067.1"/db_xref="GI:4929613"
2 1 1 3 7 3 2 1 5 9 8 6 15 7 3 20 8 11 10 2 1 7 17 8 1 16 15 7 1 15 9 1 6 4 8 3 5 6 28 19 8 10 5 13 1 5 16 14 6 17 2 1 1 7 3 5 8 4 4 8 4 0 0 1
>D87258\D87258\49..1491\1443\BAA13322.1\Homo sapiens\Homo sapiens mRNA for serin protease with IGF-binding motif,complete cds./codon_start=1/product="serin protease with IGF-binding motif"/protein_id="BAA13322.1"/db_xref="GI:1513059"
4 14 10 0 0 3 0 7 23 4 1 4 4 9 5 3 10 2 4 10 3 2 6 5 15 4 4 27 11 4 11 17 8 6 2 11 25 2 14 13 14 4 2 14 6 3 12 18 17 8 3 4 15 1 4 6 2 23 11 6 0 0 1 0
>HSJ976O13#4\AL117354\join(complement(AC093577.2:49381..49385), complement(AC093577.2:18484..18682), complement(AC093577.2:18286..18367), complement(AC093577.2:14129..14224), complement(AC093577.2:13824..13924), complement(AC093577.2:13294..13442), complement(AC093577.2:10472..10567), complement(AC093577.2:9511..9579), complement(AC093577.2:8240..8363), complement(AC093577.2:1613..1680), complement(37326..37496),complement(32966..33071), complement(32794..32846),complement(32579..32683), complement(29747..30104))\-9354\CAI23502.1\Homo sapiens\Human DNA sequence from clone RP5-976O13 on chromosome 1p21.2-22.2Contains the 3' end of the M96 gene for likely ortholog of mousemetal response element binding transcription factor 2 and the 3'end of the CGI-100 gene for CGI-100 protein, complete sequence./gene="RP5-976O13.1"/locus_tag="RP5-976O13.1-002"/standard_name="OTTHUMP00000011846"/codon_start=1/product="likely ortholog of mouse metal response element binding transcription factor 2 (M96)"/protein_id="CAI23502.1"/db_xref="GI:56203558"/db_xref="GOA:Q5TE74"/db_xref="InterPro:IPR001965"/db_xref="InterPro:IPR002999"/db_xref="UniProt/TrEMBL:Q5TE74"
2 0 2 2 21 16 4 6 9 6 16 7 12 7 3 10 7 5 9 10 2 10 13 2 2 7 10 8 2 2 13 5 3 6 7 4 7 6 24 28 8 16 13 11 4 13 19 6 5 9 12 10 17 9 10 23 16 9 16 11 10 14 3 15
>AK125205\AK125205\181..588\408\BAC86085.1\Homo sapiens\Homo sapiens cDNA FLJ43215 fis, clone FEBRA2021908./codon_start=1/protein_id="BAC86085.1"/db_xref="GI:34531222"
4 3 5 1 1 3 0 2 2 1 1 0 1 3 0 1 3 0 0 6 3 0 3 8 7 4 0 5 3 2 2 5 8 0 1 1 2 1 2 2 1 1 1 3 10 1 0 5 1 0 1 0 3 1 2 3 0 0 1 4 1 0 1 0
>AK123553\AK123553\194..2326\2133\BAC85644.1\Homo sapiens\Homo sapiens cDNA FLJ41559 fis, clone CTONG1000087./codon_start=1/protein_id="BAC85644.1"/db_xref="GI:34529129"
3 3 1 1 14 5 10 6 12 23 15 19 23 5 0 14 12 16 22 4 2 18 8 1 1 10 19 8 3 8 15 9 4 7 21 6 18 18 22 8 16 26 18 18 8 13 36 10 10 17 8 10 6 16 8 19 11 11 17 10 8 0 1 0
>BC000591\BC000591\132..1814\1683\AAH00591.1\Homo sapiens\Homo sapiens apoptosis antagonizing transcription factor, mRNA(cDNA clone MGC:815 IMAGE:3346769), complete cds./gene="AATF"/codon_start=1/product="apoptosis antagonizing transcription factor"/protein_id="AAH00591.1"/db_xref="GI:12653627"/db_xref="GeneID:26574"/db_xref="MIM:608463"
6 5 2 0 8 15 4 5 19 14 2 14 4 4 1 11 11 14 7 9 1 5 9 6 4 9 11 11 6 9 10 9 10 10 5 7 7 3 24 19 6 5 6 20 8 5 32 32 25 29 4 5 1 1 8 12 3 8 5 10 5 0 0 1
>AK125596\AK125596\1077..1784\708\BAC86214.1\Homo sapiens\Homo sapiens cDNA FLJ43608 fis, clone SPLEN2012624./codon_start=1/protein_id="BAC86214.1"/db_xref="GI:34531742"
2 3 1 1 4 2 6 9 13 7 3 5 1 2 0 5 4 3 5 2 0 3 5 4 2 2 6 7 0 11 6 5 2 1 1 6 7 3 5 4 6 7 1 4 4 0 4 12 3 8 2 6 2 4 0 4 2 3 0 3 2 0 1 0
>BC060796\BC060796\146..2200\2055\AAH60796.1\Homo sapiens\Homo sapiens testis-specific protein TSP-NY, mRNA (cDNA cloneMGC:71605 IMAGE:5284906), complete cds./gene="TSP-NY"/codon_start=1/product="TSP-NY protein"/protein_id="AAH60796.1"/db_xref="GI:38173788"/db_xref="GeneID:84660"
3 4 2 4 7 5 8 12 19 14 9 11 21 12 2 15 8 12 11 6 9 9 7 6 3 4 9 11 3 9 5 7 5 3 7 6 9 6 38 34 12 21 21 28 10 8 48 27 15 22 2 4 11 10 7 7 5 11 19 17 4 0 0 1
>S77435\S77435\1..57\57\AAD14255.1\Homo sapiens\V beta 3=T-cell receptor beta 3 chain variable region {VDJjunction} [human, colorectal carcinoma patient, colonicintraepithelial T lymphocytes, mRNA Partial, 57 nt]./gene="V3"/codon_start=1/protein_id="AAD14255.1"/db_xref="GI:4261955"
0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 2 0 0 1 2 0 0 1 0 1 0 0 0 0
>HUMIGHWE1\M36852\join(311..356,439..494)\102\AAA58803.1\Homo sapiens\Human Ig germline gamma-3 heavy-chain gene V region, partial cds./gene="IGHG3"/codon_start=1/map="14q32.33"/protein_id="AAA58803.1"/db_xref="GI:185632"/db_xref="GDB:G00-119-339"
0 0 0 0 1 0 0 1 5 1 0 0 0 1 1 0 0 0 0 0 0 0 2 1 0 1 1 0 0 1 1 1 1 0 0 1 2 0 1 1 0 0 0 2 1 1 0 1 0 0 0 0 0 0 2 0 0 0 0 1 2 0 0 0
>BC001370\BC001370\157..282\126\AAH01370.1\Homo sapiens\Homo sapiens LIM and senescent cell antigen-like domains 2, mRNA(cDNA clone IMAGE:3051392), complete cds./gene="LIMS2"/codon_start=1/product="LIMS2 protein"/protein_id="AAH01370.1"/db_xref="GI:12655041"/db_xref="GeneID:55679"/db_xref="MIM:607908"
0 1 1 0 0 1 0 1 5 0 0 0 0 1 1 1 0 0 1 1 0 0 0 2 1 0 0 3 0 0 0 0 0 0 0 0 1 0 0 9 1 0 0 1 0 0 0 3 1 0 1 0 1 1 1 0 0 0 0 1 0 0 0 1
>CR457390\CR457390\1..1041\1041\CAG33671.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834B0414D forgene TMEFF2, transmembrane protein with EGF-like and twofollistatin-like domains 2; complete cds, incl. stopcodon./gene="TMEFF2"/codon_start=1/protein_id="CAG33671.1"/db_xref="GI:48146897"/db_xref="InterPro:IPR000742"/db_xref="InterPro:IPR002350"/db_xref="InterPro:IPR006209"/db_xref="InterPro:IPR006210"/db_xref="UniProt/TrEMBL:Q9NSS5"
3 1 1 0 4 2 2 6 6 3 4 1 3 4 1 10 3 5 8 6 1 7 1 4 3 4 8 5 0 8 9 5 5 5 3 8 10 3 9 6 5 11 6 12 3 5 15 11 8 14 5 7 14 19 5 4 2 6 7 5 5 1 0 0
>CR457086\CR457086\1..2052\2052\CAG33367.1\Homo sapiens\Homo sapiens full open reading frame cDNA clone RZPDo834E0814D forgene SV2B, synaptic vesicle glycoprotein 2B; complete cds, incl.stopcodon./gene="SV2B"/codon_start=1/protein_id="CAG33367.1"/db_xref="GI:48146289"
5 4 3 0 9 3 4 13 34 4 2 6 4 11 0 12 9 9 13 15 2 3 7 9 1 2 8 25 2 11 12 25 13 7 2 16 17 6 11 20 11 12 6 16 8 8 16 26 13 21 18 12 8 7 30 22 2 26 15 33 14 1 0 0
>BC071930\BC071930\62..460\399\AAH71930.1\Homo sapiens\Homo sapiens ribosomal protein S12, mRNA (cDNA clone MGC:88615IMAGE:6295016), complete cds./gene="RPS12"/codon_start=1/product="ribosomal protein S12"/protein_id="AAH71930.1"/db_xref="GI:47940604"/db_xref="GeneID:6206"/db_xref="MIM:603660"
0 2 0 2 1 0 3 1 1 4 2 1 0 1 0 1 0 1 0 0 0 2 0 1 0 1 2 7 0 5 3 4 1 2 4 2 3 5 7 9 3 1 3 1 2 1 5 7 5 4 0 3 2 5 1 0 0 2 5 3 1 0 0 1
>HSY17392\Y17392\48..416\369\CAA76759.1\Homo sapiens\Homo sapiens mRNA for prefoldin subunit 1./gene="pfd1hu"/codon_start=1/product="prefoldin subunit 1"/protein_id="CAA76759.1"/db_xref="GI:3212110"/db_xref="GOA:O60925"/db_xref="UniProt/Swiss-Prot:O60925"
2 0 1 0 2 2 3 1 4 3 2 1 0 2 0 0 0 1 3 0 1 3 0 1 0 0 5 5 0 1 1 0 0 1 2 0 2 1 6 9 3 0 2 8 1 2 8 8 3 3 1 1 0 0 1 1 2 2 5 6 0 0 1 0
>AC092610#1\AC092610 AC024380\complement(join(54535..54640,54787..54926,55328..55467, 56810..57152,58703..58911,60723..60873,70435..70607, 71385..71622,72396..72508,77551..77711,87298..87335, 89764..89916))\1965\AAS07559.1\Homo sapiens\Homo sapiens BAC clone RP11-160E17 from 7, complete sequence./gene="FLJ10324"/codon_start=1/product="unknown"/protein_id="AAS07559.1"/db_xref="GI:41474573"
1 9 8 5 3 10 1 28 51 7 0 5 1 18 9 3 25 1 6 7 9 4 12 31 10 9 10 34 8 8 5 25 17 4 0 9 16 2 4 11 6 1 2 34 16 2 9 35 23 2 14 1 16 1 21 2 1 16 1 15 10 0 1 0
>AF502942\AF502942\141..3248\3108\AAP30832.1\Homo sapiens\Homo sapiens ubiquitin-specific protease 31 (USP31) mRNA, completecds./gene="USP31"/codon_start=1/product="ubiquitin-specific protease 31"/protein_id="AAP30832.1"/db_xref="GI:30315217"
6 8 7 7 17 7 8 14 24 17 16 22 14 7 3 19 10 15 11 8 4 17 16 9 5 13 15 13 2 20 22 14 8 12 8 9 20 19 44 40 20 30 32 28 9 15 60 42 12 43 13 22 14 23 5 30 12 11 27 21 16 1 0 0
>AL355310#4\AL355310\join(81322..81331,86356..86486,86715..86845,87213..87281, 87372..87480,87779..87965,88228..88369,88482..88571, 88827..88956,89136..89330,89417..89548,89696..89859, 90162..90288,90380..90543,90849..90969,91286..91459, 91736..91846,91996..92205)\2397\CAI19305.1\Homo sapiens\Human DNA sequence from clone RP5-1160K1 on chromosome 1 Containsthe GPR61 gene for G protein-coupled receptor 61, the GNAI3 genefor guanine nucleotide binding protein (G protein) alpha inhibitingactivity polypeptide 3, two novel genes, the GNAT2 gene for guaninenucleotide binding protein (G protein) alpha transducing activitypolypeptide 2, the AMPD2 gene for adenosine monophosphate deaminase2 (isoform L) and the 5' end of a ribosomal protein L7 (RPL7)pseudogene, complete sequence./gene="AMPD2"/locus_tag="RP5-1160K1.5-001"/standard_name="OTTHUMP00000013369"/codon_start=1/product="adenosine monophosphate deaminase 2 (isoform L)"/protein_id="CAI19305.1"/db_xref="GI:56206059"
3 22 21 4 0 7 3 19 64 2 1 3 6 13 4 6 21 5 1 19 8 3 10 17 12 12 4 29 7 8 1 13 13 8 2 11 35 0 4 31 18 9 2 33 25 8 11 63 24 16 25 6 8 4 24 10 1 23 6 24 6 0 0 1
>AF284421\AF284421\91..2277\2187\AAK84071.1\Homo sapiens\Homo sapiens complement factor MASP-3 mRNA, complete cds./codon_start=1/product="complement factor MASP-3"/protein_id="AAK84071.1"/db_xref="GI:15088517"
4 5 5 2 4 10 3 12 28 6 2 6 7 21 5 5 14 8 13 15 4 9 14 17 2 14 4 12 1 10 9 25 13 6 3 20 35 4 12 18 19 13 7 20 13 6 10 43 27 13 22 14 15 12 21 8 5 21 6 13 13 0 0 1
>S60073\S60073\1..81\81\AAB20039.1\Homo sapiens\T-cell antigen receptor VJ junction alpha chain Valpha8.1/Jalphaunassigned [human, cytotoxic T lymphocyte cell line B1b, mRNAPartial, 81 nt]./gene="T-cell antigen receptor VJ junction alpha chain Valpha8.1/Jalpha unassigned"/codon_start=1/product="T-cell antigen receptor VJ junction alpha chain Valpha8.1/Jalpha unassigned"/protein_id="AAB20039.1"/db_xref="GI:237179"
0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 2 0 0 0 4 1 0 1 0 0 0 1 3 0 0 2 1 0 0 0 0 0 0 0 1 0 0 1 1 1 0 1 0 0 0 0 0 0
>BC007641\BC007641\336..563\228\AAH07641.1\Homo sapiens\Homo sapiens hypothetical protein MGC15912, mRNA (cDNA cloneMGC:15912 IMAGE:3534121), complete cds./gene="MGC15912"/codon_start=1/product="hypothetical protein MGC15912"/protein_id="AAH07641.1"/db_xref="GI:14043293"/db_xref="GeneID:84972"
1 0 0 1 0 1 2 2 1 6 2 2 0 0 1 0 1 1 1 0 0 2 0 0 0 2 0 2 0 2 3 1 2 2 1 2 4 2 1 2 1 0 3 0 1 2 2 1 1 2 0 1 1 0 2 1 0 3 0 1 3 0 0 1
>BC000259\BC000259\188..1366\1179\AAH00259.1\Homo sapiens\Homo sapiens family with sequence similarity 53, member C, mRNA(cDNA clone MGC:821 IMAGE:3357346), complete cds./gene="FAM53C"/codon_start=1/product="FAM53C protein"/protein_id="AAH00259.1"/db_xref="GI:12652997"/db_xref="GeneID:51307"
4 10 13 1 3 3 2 8 20 4 0 6 7 18 1 10 17 8 3 1 0 5 12 24 3 15 3 12 1 7 3 6 7 7 0 3 8 0 3 10 6 2 6 16 7 2 7 15 9 7 3 0 6 7 11 2 2 4 1 3 8 1 0 0
>BC019864\BC019864\185..2128\1944\AAH19864.1\Homo sapiens\Homo sapiens phosphodiesterase 4A, cAMP-specific (phosphodiesteraseE2 dunce homolog, Drosophila), mRNA (cDNA clone MGC:30168IMAGE:4942336), complete cds./gene="PDE4A"/codon_start=1/product="phosphodiesterase 4A, cAMP-specific (phosphodiesterase E2 dunce homolog, Drosophila)"/protein_id="AAH19864.1"/db_xref="GI:18043809"/db_xref="GeneID:5141"/db_xref="MIM:600126"
5 8 6 2 1 5 3 17 35 3 1 11 10 15 5 6 14 3 11 14 8 3 10 14 10 10 13 24 6 13 5 10 9 4 3 7 24 3 6 17 19 3 7 29 18 3 14 44 25 12 12 1 8 2 16 5 4 14 5 22 10 0 0 1
>AL445931#6\AL445931 AC041022\complement(join(149770..149797,153240..153475, 154966..155157,158499..158627,161289..161660, 163580..163794,164768..164915,165512..165649, 166471..166683))\1671\CAI13727.1\Homo sapiens\Human DNA sequence from clone RP11-374P20 on chromosome 9 Containsthe 5' end of the VAV2 gene for vav 2 oncogene, a novel gene(FLJ35348), the 3' end of the BRD3 gene for bromodomain containing3, a novel gene and five CpG islands, complete sequence./gene="BRD3"/locus_tag="RP11-374P20.3-002"/standard_name="OTTHUMP00000022725"/codon_start=1/product="bromodomain containing 3"/protein_id="CAI13727.1"/db_xref="GI:55960169"
1 3 8 1 2 4 5 4 13 0 3 3 2 6 8 3 14 4 6 13 9 4 14 28 11 13 8 35 9 11 2 13 2 3 2 13 24 3 14 51 10 6 4 22 10 2 5 33 17 8 10 4 2 3 6 6 2 10 4 16 4 0 0 1
>AC004510#2\AC004510\complement(join(16764..17053,18531..18558))\318\AAC08455.1\Homo sapiens\Homo sapiens chromosome 19, cosmid R30385, complete sequence./codon_start=1/product="R30385_2"/protein_id="AAC08455.1"/db_xref="GI:2996653"
0 2 0 1 2 3 0 1 1 2 0 0 2 2 0 0 2 2 1 0 1 2 4 2 0 4 1 2 0 0 5 2 1 2 1 1 2 0 3 4 1 3 1 3 6 2 8 1 0 1 1 4 0 7 1 3 1 1 1 1 1 0 1 0
>BC044920\BC044920\1597..2445\849\AAH44920.1\Homo sapiens\Homo sapiens seven in absentia homolog 1 (Drosophila), mRNA (cDNAclone MGC:44340 IMAGE:5295925), complete cds./gene="SIAH1"/codon_start=1/product="SIAH1 protein"/protein_id="AAH44920.1"/db_xref="GI:71297497"/db_xref="GeneID:6477"/db_xref="MIM:602212"
4 3 1 1 0 3 3 2 5 8 5 4 1 8 1 4 4 2 8 4 0 8 6 3 2 7 7 2 3 9 5 7 0 5 4 3 4 3 6 4 3 9 3 11 3 7 8 7 7 3 2 3 3 15 4 9 3 2 9 9 3 0 0 1
>AF307096\AF307096\778..2214\1437\AAL29190.1\Homo sapiens\Homo sapiens ZNF317-3 protein mRNA, complete cds, alternativelyspliced./codon_start=1/product="ZNF317-3 protein"/protein_id="AAL29190.1"/db_xref="GI:16797864"
4 4 9 0 6 17 0 14 5 7 1 2 7 11 1 2 12 3 1 9 10 10 3 8 2 4 4 11 4 5 6 9 17 3 2 4 9 3 21 25 10 4 2 12 37 3 12 18 9 6 13 3 17 10 13 6 2 6 3 13 4 0 0 1
>BC007781\BC007781\4..753\750\AAH07781.1\Homo sapiens\Homo sapiens inhibitor of growth family, member 4, transcriptvariant 1, mRNA (cDNA clone MGC:12557 IMAGE:4309278), complete cds./gene="ING4"/codon_start=1/product="inhibitor of growth family, member 4, isoform 1"/protein_id="AAH07781.1"/db_xref="GI:14043612"/db_xref="GeneID:51147"/db_xref="MIM:608524"
0 3 5 3 2 1 1 4 6 4 2 4 2 6 1 2 4 6 4 4 0 3 1 6 0 4 0 9 1 6 1 5 5 1 0 2 7 0 12 16 5 0 3 9 3 2 11 11 13 6 0 9 4 4 1 7 0 1 6 9 2 0 1 0
>AY769950\AY769950\join(3285..3427,26236..26357,28741..28863,32688..32900, 38531..38599,41033..41149,56284..56505,59149..59410, 59695..59866,64668..64761,68665..68879,71794..71944, 77929..78138,94160..97265,119263..119416,120813..121025, 121312..121540,121748..121930,123669..123785, 124394..124465,125885..125970,129624..129779, 162629..162773,163990..164138,165248..165424, 188104..188259)\7056\AAV85964.1\Homo sapiens\Homo sapiens coagulation factor VIII, procoagulant component(hemophilia A) (F8) gene, complete cds./gene="F8"/codon_start=1/product="coagulation factor VIII, procoagulant component (hemophilia A)"/protein_id="AAV85964.1"/db_xref="GI:56385012"
12 10 6 8 37 31 25 30 49 39 33 46 54 29 4 52 39 41 53 36 4 62 57 25 3 43 40 26 3 41 49 30 24 26 31 31 35 28 95 63 43 82 54 56 31 44 90 58 42 79 29 50 18 8 47 62 29 28 53 61 37 0 0 1
>BC071926\BC071926\25..417\393\AAH71926.1\Homo sapiens\Homo sapiens ribosomal protein S24, transcript variant 1, mRNA(cDNA clone MGC:88611 IMAGE:5556377), complete cds./gene="RPS24"/codon_start=1/product="ribosomal protein S24, isoform a"/protein_id="AAH71926.1"/db_xref="GI:48734994"/db_xref="GeneID:6229"/db_xref="MIM:602412"
2 2 1 0 6 2 2 0 2 3 0 0 1 1 0 0 0 0 4 4 0 5 0 2 1 1 3 2 1 1 1 5 2 3 2 4 1 1 8 14 3 2 2 1 1 3 4 1 1 4 1 3 0 0 2 4 0 2 3 6 0 0 0 1
>HSG115G20#1\AL078645\join(82987..83080,113065..113159,196216..196292, 203878..203938,AL358152.9:20859..20897)\-35478\CAI17842.1\Homo sapiens\Human DNA sequence from clone GS1-115G20 on chromosome 1 Containspart of the C1orf21 gene for chromosome 1 open reading frame 21, anovel pseudogene and a novel transcript, complete sequence./gene="C1orf21"/locus_tag="RP4-768P8.1-001"/standard_name="OTTHUMP00000033397"/codon_start=1/product="chromosome 1 open reading frame 21"/protein_id="CAI17842.1"/db_xref="GI:55957216"/db_xref="Genew:15494"/db_xref="UniProt/TrEMBL:Q9H246"
0 0 0 0 3 2 0 0 1 1 1 1 1 1 0 1 2 1 1 0 0 2 1 1 1 1 4 6 0 0 2 2 3 0 1 1 2 5 10 3 5 4 5 4 1 2 12 5 0 3 3 1 0 1 2 2 2 2 2 4 0 1 0 0
>BC006012\BC006012\76..663\588\AAH06012.2\Homo sapiens\Homo sapiens selenoprotein T, mRNA (cDNA clone MGC:14845IMAGE:4333083), complete cds./gene="SELT"/codon_start=1/transl_except=(pos:220..222,aa:Sec)/product="selenoprotein T"/protein_id="AAH06012.2"/db_xref="GI:45766671"/db_xref="GeneID:51714"/db_xref="MIM:607912"
1 1 4 0 2 2 2 4 6 5 4 1 4 2 1 4 5 0 1 0 1 1 4 1 1 4 3 3 3 2 1 6 1 3 2 2 5 6 1 7 2 6 6 5 3 2 4 6 2 3 4 3 0 3 6 4 5 3 6 12 3 0 1 1
>AY663420#3\AY663420\48577..49593\1017\AAU47288.1\Homo sapiens\Homo sapiens isolate fa0138 immunoglobulin superfamily member 4B(IGSF4B) gene, complete cds; and Duffy blood group (FY) genes,complete cds, alternatively spliced./gene="FY"/codon_start=1/product="Duffy blood group"/protein_id="AAU47288.1"/db_xref="GI:52426513"
0 3 0 0 2 1 6 14 35 3 0 12 4 8 0 8 8 4 3 7 2 5 5 8 0 6 7 20 1 9 8 8 7 8 2 9 9 1 1 5 4 3 0 10 5 3 4 3 5 6 2 4 5 6 11 4 1 4 4 4 11 0 1 0
>AK001944\AK001944\111..1691\1581\BAA91992.1\Homo sapiens\Homo sapiens cDNA FLJ11082 fis, clone PLACE1005206./codon_start=1/protein_id="BAA91992.1"/db_xref="GI:7023523"
4 2 2 3 8 3 6 8 16 25 11 14 7 5 2 11 3 14 5 2 1 7 11 2 0 18 13 5 0 18 10 2 2 6 6 4 13 10 18 10 5 13 13 14 1 10 29 10 5 16 8 16 2 3 9 20 8 7 14 9 7 0 0 1
>BC001342\BC001342\105..1481\1377\AAH01342.2\Homo sapiens\Homo sapiens Huntingtin interacting protein E, mRNA (cDNA cloneMGC:5623 IMAGE:3462741), complete cds./gene="HYPE"/codon_start=1/product="Huntingtin interacting protein E"/protein_id="AAH01342.2"/db_xref="GI:45945855"/db_xref="GeneID:11153"
0 8 5 1 2 10 0 16 28 3 1 5 3 8 5 2 9 0 5 17 5 4 4 8 7 5 5 21 7 6 1 12 6 1 1 9 22 2 7 19 12 0 2 14 11 6 12 23 14 3 15 2 2 1 9 5 2 23 2 16 4 1 0 0
>BC007846\BC007846\23..1357\1335\AAH07846.1\Homo sapiens\Homo sapiens fatty acid desaturase 1, mRNA (cDNA clone MGC:14118IMAGE:4129208), complete cds./gene="FADS1"/codon_start=1/product="fatty acid desaturase 1"/protein_id="AAH07846.1"/db_xref="GI:14043780"/db_xref="GeneID:3992"/db_xref="MIM:606148"
2 5 7 1 0 1 6 12 22 6 0 7 6 5 1 4 5 3 4 9 3 1 4 13 3 3 2 24 2 3 3 6 12 1 0 7 16 3 8 17 13 4 1 19 18 12 2 15 11 6 10 6 3 2 27 10 2 10 8 12 16 1 0 0
>AF494057\AF494057\join(2220..2323,4103..4333,4745..5610,7917..7991, 8069..8203,8806..8955,9447..9550,10475..10552)\1743\AAM00008.1\Homo sapiens\Homo sapiens methyl-CpG binding domain protein 4 (MBD4) gene,complete cds./gene="MBD4"/codon_start=1/product="methyl-CpG binding domain protein 4"/protein_id="AAM00008.1"/db_xref="GI:19852107"
4 3 3 3 15 7 4 8 8 17 5 8 16 4 0 14 11 16 9 11 1 13 11 5 3 8 10 4 0 11 14 5 4 8 4 6 11 9 39 22 13 12 11 6 4 8 35 15 12 19 4 9 5 9 4 20 6 8 8 8 10 1 0 0
>AB016901\AB016901\281..454\174\BAA78636.1\Homo sapiens\Homo sapiens HGC6.2 mRNA, complete cds./gene="HGC6.2"/codon_start=1/protein_id="BAA78636.1"/db_xref="GI:5006259"
1 0 0 0 0 1 0 2 1 0 1 0 1 2 0 1 0 2 1 0 1 2 2 1 1 3 0 1 0 3 2 2 0 1 1 0 2 0 1 0 0 0 2 1 1 3 1 1 3 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0
>BC015308\BC015308\31..915\885\AAH15308.1\Homo sapiens\Homo sapiens survival of motor neuron 1, telomeric, transcriptvariant d, mRNA (cDNA clone MGC:20996 IMAGE:4427000), complete cds./gene="SMN1"/codon_start=1/product="survival of motor neuron 1, telomeric, isoform d"/protein_id="AAH15308.1"/db_xref="GI:15929774"/db_xref="GeneID:6606"/db_xref="MIM:600354"
0 1 1 0 5 2 4 1 5 2 4 1 8 6 1 7 5 4 4 3 0 4 23 6 3 7 3 1 1 12 8 9 2 6 1 1 3 4 13 9 3 14 7 4 1 3 9 6 4 14 3 5 3 5 2 5 4 2 8 6 6 1 0 0
>AF116538\AF116538\383..958\576\AAD41262.2\Homo sapiens\Homo sapiens pituitary tumor transforming gene protein 2 (PTTG2)gene, complete cds./gene="PTTG2"/codon_start=1/product="pituitary tumor transforming gene protein 2"/protein_id="AAD41262.2"/db_xref="GI:27414489"
0 1 0 2 4 0 1 2 7 3 3 2 5 1 0 6 1 3 4 4 0 3 7 5 0 8 3 5 0 6 5 4 1 0 1 3 4 4 10 10 1 3 2 3 1 1 8 7 4 6 2 1 1 1 3 7 2 3 2 4 1 0 0 1
>BC069529\BC069529\53..607\555\AAH69529.1\Homo sapiens\Homo sapiens paired-like homeobox protein OTEX, mRNA (cDNA cloneMGC:96960 IMAGE:7262169), complete cds./gene="OTEX"/codon_start=1/product="paired-like homeobox protein OTEX"/protein_id="AAH69529.1"/db_xref="GI:46854685"/db_xref="GeneID:158800"/db_xref="MIM:300447"
3 2 3 2 3 3 1 3 4 1 2 1 1 0 1 0 2 2 2 1 2 3 3 5 5 4 3 5 2 2 2 9 1 5 2 3 7 3 3 2 7 3 2 11 3 2 7 10 6 2 4 0 1 2 3 1 1 2 0 8 1 0 1 0
>HUMORFI\L40399\451..1248\798\AAC42005.1\Homo sapiens\Homo sapiens (clone S240ii117/zap112) mRNA, complete cds./codon_start=1/protein_id="AAC42005.1"/db_xref="GI:887372"/IGNORED_CODON=5
1 2 2 3 5 2 4 5 14 5 5 4 1 4 0 6 3 4 5 3 0 7 6 2 2 4 4 6 0 4 3 5 4 2 3 2 8 2 9 5 2 4 7 16 4 2 13 11 3 6 2 0 3 5 1 6 2 3 6 5 3 0 0 1
>AY676494\AY676494\621..1301\681\AAT78423.1\Homo sapiens\Homo sapiens claudin-like protein 24 (CLP24) mRNA, complete cds./gene="CLP24"/codon_start=1/product="claudin-like protein 24"/protein_id="AAT78423.1"/db_xref="GI:50541903"
1 6 2 1 3 4 0 9 21 1 0 0 3 7 0 0 3 1 1 7 3 1 2 3 2 1 5 17 7 1 1 9 7 0 0 5 14 0 1 1 7 1 1 6 1 1 0 8 8 1 4 0 8 1 6 2 0 4 4 6 7 0 0 1
>BC003103\BC003103\178..1104\927\AAH03103.1\Homo sapiens\Homo sapiens regulating synaptic membrane exocytosis 3, mRNA (cDNAclone MGC:1884 IMAGE:3503630), complete cds./gene="RIMS3"/codon_start=1/product="RIMS3 protein"/protein_id="AAH03103.1"/db_xref="GI:13111871"/db_xref="GeneID:9783"
1 5 10 0 0 2 1 7 17 1 0 1 3 12 0 3 18 2 7 15 2 2 5 7 1 2 2 14 2 5 6 12 11 3 0 3 12 1 3 15 4 2 1 15 2 0 5 9 8 5 3 2 4 1 6 2 0 9 4 10 3 1 0 0
>BC025963\BC025963\48..1286\1239\AAH25963.1\Homo sapiens\Homo sapiens acyl-Coenzyme A dehydrogenase, C-2 to C-3 short chain,mRNA (cDNA clone MGC:39242 IMAGE:4842286), complete cds./gene="ACADS"/codon_start=1/product="acyl-Coenzyme A dehydrogenase, C-2 to C-3 short chain, precursor"/protein_id="AAH25963.1"/db_xref="GI:19684166"/db_xref="GeneID:35"/db_xref="MIM:606885"
0 7 9 1 2 2 0 13 21 3 1 5 2 5 3 2 9 5 3 13 5 1 4 7 1 5 5 42 6 9 3 19 10 2 0 6 8 1 3 19 7 3 2 15 4 2 5 20 11 5 9 0 3 3 7 6 1 22 3 16 6 0 0 1
>BC029378\BC029378\9..1268\1260\AAH29378.1\Homo sapiens\Homo sapiens telomeric repeat binding factor (NIMA-interacting) 1,transcript variant 2, mRNA (cDNA clone MGC:32568 IMAGE:4724068),complete cds./gene="TERF1"/codon_start=1/product="telomeric repeat binding factor 1, isoform 2"/protein_id="AAH29378.1"/db_xref="GI:20810196"/db_xref="GeneID:7013"/db_xref="MIM:600951"
3 4 2 0 15 6 5 4 5 7 3 8 7 5 0 8 8 7 10 5 1 6 1 2 3 6 9 9 5 8 6 6 1 4 4 2 7 4 25 10 7 10 6 14 3 8 27 21 11 11 2 4 5 3 8 9 9 1 10 13 6 0 0 1
>AK122906\AK122906\313..1104\792\BAC85513.1\Homo sapiens\Homo sapiens cDNA FLJ16581 fis, clone TESTI2050987, weakly similarto RET finger protein-like 1./codon_start=1/protein_id="BAC85513.1"/db_xref="GI:34528351"
2 3 2 1 4 3 3 5 11 6 2 6 1 8 0 3 7 2 4 4 0 2 3 3 1 4 5 4 1 5 4 4 2 2 1 6 9 3 2 8 3 5 4 4 6 6 7 12 4 12 1 2 7 8 11 6 1 7 3 4 4 0 0 1
>BC010003\BC010003\136..753\618\AAH10003.2\Homo sapiens\Homo sapiens chromosome 6 open reading frame 117, mRNA (cDNA cloneMGC:16762 IMAGE:4134852), complete cds./gene="C6orf117"/codon_start=1/product="chromosome 6 open reading frame 117"/protein_id="AAH10003.2"/db_xref="GI:33872596"/db_xref="GeneID:112609"
0 2 0 0 6 3 0 3 8 4 1 2 3 7 1 6 2 2 3 6 0 1 6 1 0 2 3 5 0 2 5 1 2 1 1 2 6 3 4 5 7 3 4 7 4 1 7 11 8 5 3 4 1 1 2 12 0 3 7 4 2 0 0 1
>HSA131730#2\AJ131730\229..873\645\CAB56836.1\Homo sapiens\Homo sapiens mRNA for DREAM protein./gene="dream"/function="transcriptional repressor"/codon_start=1/evidence=experimental/product="DREAM protein"/protein_id="CAB56836.1"/db_xref="GI:6006496"/db_xref="GOA:Q9Y2W7"/db_xref="UniProt/Swiss-Prot:Q9Y2W7"
0 2 2 0 1 2 0 6 14 0 0 0 1 5 0 1 4 1 2 8 2 0 2 2 1 1 1 8 4 0 1 7 4 0 1 4 5 1 3 10 5 3 0 12 6 0 2 17 10 6 5 2 2 2 9 6 0 8 3 8 2 0 1 0
>HSTROPONC\X54163\90..722\633\CAA38102.1\Homo sapiens\Human mRNA for cardiac troponin I./codon_start=1/protein_id="CAA38102.1"/db_xref="GI:37428"/db_xref="GOA:P19429"/db_xref="UniProt/Swiss-Prot:P19429"
3 8 7 1 4 2 0 2 16 1 0 3 0 4 1 2 4 1 0 5 2 2 2 1 2 2 6 8 5 4 3 3 4 0 0 1 5 0 5 18 4 0 1 8 3 0 3 18 7 6 2 1 2 0 1 3 1 6 2 4 1 0 0 1
>AF110798#3\AF110798\join(1163..1184,1523..1729,2373..2496,2577..2817)\594\AAD17189.1\Homo sapiens\Homo sapiens interleukin-18 binding protein precursor (IL18BP)gene, alternative splice products, complete cds./gene="IL18BP"/codon_start=1/product="interleukin-18 binding protein c precursor"/protein_id="AAD17189.1"/db_xref="GI:4324926"
1 1 1 2 4 2 0 10 13 0 1 3 1 4 1 0 12 0 5 6 2 2 8 4 0 4 2 8 0 2 3 3 3 3 0 8 9 2 0 4 3 2 0 11 5 1 5 6 3 0 1 0 5 4 6 0 0 1 1 2 7 0 0 1
>HSU00803\U00803\448..1965\1518\AAA18284.1\Homo sapiens\Human SRC-like tyrosine kinase (FRK) mRNA, complete cds./gene="FRK"/codon_start=1/product="SRC-like tyrosine kinase"/protein_id="AAA18284.1"/db_xref="GI:392888"
5 1 2 2 17 3 6 5 14 11 5 10 11 6 1 8 6 6 8 5 2 8 11 4 3 4 12 8 2 8 11 7 3 8 8 3 7 7 15 13 12 10 12 16 6 6 21 15 14 13 10 14 4 4 6 17 5 13 10 10 11 0 0 1
>BC013975\BC013975\73..2319\2247\AAH13975.1\Homo sapiens\Homo sapiens sema domain, immunoglobulin domain (Ig), short basicdomain, secreted, (semaphorin) 3B, transcript variant 2, mRNA (cDNAclone MGC:12697 IMAGE:4121913), complete cds./gene="SEMA3B"/codon_start=1/product="semaphorin 3B, isoform 2 precursor"/protein_id="AAH13975.1"/db_xref="GI:15559241"/db_xref="GeneID:7869"/db_xref="MIM:601281"
5 26 26 7 1 8 4 15 44 2 0 9 3 13 10 4 17 7 3 16 11 5 8 22 12 6 12 38 18 8 11 25 16 5 4 14 33 4 2 20 14 3 7 22 18 5 5 39 28 5 13 3 16 4 20 15 1 10 4 9 13 0 0 1
>HSJ136O14#9\AL121963\join(106104..106447,complement(AL357141.8:70100..70221), complement(AL357141.8:34799..34962), complement(AL357141.8:33774..33942), complement(AL357141.8:22675..22833), complement(AL357141.8:10467..10648), complement(AL357141.8:9243..9408), complement(AL357141.8:8637..8848))\-35361\CAB87592.2\Homo sapiens\Human DNA sequence from clone RP1-136O14 on chromosome 6q21-22.3Contains a pseudogene similar to various (hypothetical) genes, theCOL10A1 gene for collagen, type X, alpha 1 (Schmid metaphysealchondrodysplasia) (collagen X, alpha-1 polypeptide; collagen, typeX, alpha 1 (Schmid metaphyseal chondrodysplasia)), the 5' end of anovel gene and the 5' end of the FRK gene for fyn-related kinase(GTK, RAK). Contains a CpG island, complete sequence./gene="FRK"/locus_tag="RP11-702N8.1-001"/standard_name="OTTHUMP00000017048"/codon_start=1/product="fyn-related kinase"/protein_id="CAB87592.2"/db_xref="GI:56203498"/db_xref="GOA:Q9NTR5"/db_xref="HSSP:1BU1"/db_xref="InterPro:IPR000719"/db_xref="InterPro:IPR000980"/db_xref="InterPro:IPR001245"/db_xref="InterPro:IPR001452"/db_xref="InterPro:IPR002290"/db_xref="InterPro:IPR008266"/db_xref="InterPro:IPR011009"/db_xref="InterPro:IPR011511"/db_xref="UniProt/TrEMBL:Q9NTR5"
0 1 0 1 10 4 4 12 11 8 8 15 4 4 2 6 8 9 15 2 0 8 7 7 1 9 5 7 1 4 11 4 11 6 9 10 6 8 21 11 5 12 10 11 7 9 10 8 4 4 5 14 10 14 9 31 11 5 15 11 6 8 10 7
>AF264014\AF264014\26..4387\4362\AAF91396.1\Homo sapiens\Homo sapiens scavenger receptor cysteine-rich type 1 protein M160precursor, mRNA, complete cds, alternatively spliced./codon_start=1/product="scavenger receptor cysteine-rich type 1 protein M160 precursor"/protein_id="AAF91396.1"/db_xref="GI:9652087"
8 7 4 9 30 26 11 20 38 23 13 20 24 19 7 37 21 19 28 18 3 21 10 11 3 12 24 27 2 30 72 29 35 17 13 19 50 27 26 14 26 39 17 29 24 28 38 40 40 57 4 12 46 58 16 22 9 26 21 17 57 0 0 1
>BC011686\BC011686\74..3496\3423\AAH11686.1\Homo sapiens\Homo sapiens damage-specific DNA binding protein 1, 127kDa, mRNA(cDNA clone MGC:19563 IMAGE:3845478), complete cds./gene="DDB1"/codon_start=1/product="damage-specific DNA binding protein 1"/protein_id="AAH11686.1"/db_xref="GI:15079750"/db_xref="GeneID:1642"/db_xref="MIM:600045"
6 13 12 6 4 7 7 28 46 17 8 19 9 16 6 15 28 11 13 29 9 19 7 19 0 15 7 29 4 19 17 33 18 14 9 26 48 8 15 39 27 27 8 39 18 10 36 55 35 20 18 17 15 7 21 25 1 40 31 27 8 0 1 0
>HSIL4SV\X81851\1..414\414\CAA57444.1\Homo sapiens\H. sapiens IL-4 gene splice variant./gene="IL-4"/codon_start=1/product="interleukin-4"/protein_id="CAA57444.1"/db_xref="GI:673419"/db_xref="GOA:P05112"/db_xref="UniProt/Swiss-Prot:P05112"
1 1 2 0 1 4 2 5 7 1 1 4 1 2 1 0 3 1 2 3 2 5 0 1 0 2 2 2 3 1 1 3 0 2 0 1 2 0 3 8 6 1 1 7 5 1 4 5 2 1 1 1 3 3 7 1 0 5 0 2 1 0 0 1
>HSPSANLZP\Z50781\136..369\234\CAA90644.1\Homo sapiens\H.sapiens mRNA for leucine zipper protein./codon_start=1/evidence=experimental/product="leucine zipper protein"/protein_id="CAA90644.1"/db_xref="GI:1834507"/db_xref="GOA:Q99576"/db_xref="UniProt/Swiss-Prot:Q99576"
1 0 0 1 1 0 1 0 8 0 0 1 0 3 0 1 2 0 0 2 0 0 3 2 0 2 1 1 1 2 0 0 0 2 0 0 6 0 0 5 2 1 1 4 0 1 2 12 0 1 0 1 0 1 1 0 0 2 0 2 0 1 0 0
>AL513327#5\AL513327\complement(join(122695..122849,126700..126976, 127901..128042,129178..129292,130105..130234, 131920..132072))\972\CAI13955.1\Homo sapiens\Human DNA sequence from clone RP11-415J8 on chromosome 1 Containsthe gene for a novel protein (FLJ35476), the gene for a novelprotein similar to ABO family protein, two novel genes, the PHC2gene for polyhomeotic-like 2 (Drosophila) and two CpG islands,complete sequence./gene="PHC2"/locus_tag="RP11-415J8.4-003"/standard_name="OTTHUMP00000004294"/codon_start=1/product="polyhomeotic-like 2 (Drosophila)"/protein_id="CAI13955.1"/db_xref="GI:55960661"/db_xref="InterPro:IPR001660"/db_xref="UniProt/TrEMBL:Q8N306"
1 6 7 4 0 1 1 7 17 4 0 2 7 8 3 3 9 2 2 9 1 5 8 10 1 2 4 13 2 5 6 6 7 2 1 1 9 2 7 18 6 4 4 13 7 2 8 16 11 3 3 4 3 4 8 2 1 10 1 9 1 0 1 0
>BC028712\BC028712\245..1039\795\AAH28712.1\Homo sapiens\Homo sapiens ankyrin repeat domain 19, mRNA (cDNA clone MGC:27029IMAGE:4837806), complete cds./gene="ANKRD19"/codon_start=1/product="ANKRD19 protein"/protein_id="AAH28712.1"/db_xref="GI:71052207"/db_xref="GeneID:138649"
0 3 4 1 9 6 3 8 10 6 2 6 3 2 0 2 5 2 2 2 1 5 2 0 0 1 5 9 2 8 1 5 3 1 2 2 5 2 4 8 8 10 8 7 5 9 8 7 10 3 3 5 3 3 5 4 4 7 8 4 1 0 0 1
>AF067513\AF067513\620..2200\1581\AAC72078.1\Homo sapiens\Homo sapiens PITSLRE protein kinase alpha SV4 isoform (CDC2L1)mRNA, complete cds./gene="CDC2L1"/codon_start=1/product="PITSLRE protein kinase alpha SV4 isoform"/protein_id="AAC72078.1"/db_xref="GI:3850306"
2 4 5 3 2 7 1 13 34 2 1 1 9 8 4 4 18 5 2 17 7 1 4 16 5 5 5 14 2 3 4 17 11 6 1 5 17 3 5 29 14 1 0 16 8 2 27 57 21 5 11 4 3 0 18 0 0 18 2 12 5 0 0 1
>BC060782\BC060782\450..2861\2412\AAH60782.1\Homo sapiens\Homo sapiens leucine rich repeat containing 8 family, member B,mRNA (cDNA clone MGC:71558 IMAGE:5298560), complete cds./gene="LRRC8B"/codon_start=1/product="LRRC8B protein"/protein_id="AAH60782.1"/db_xref="GI:38174504"/db_xref="GeneID:23507"
2 7 2 2 3 6 15 23 42 26 13 24 14 20 2 8 16 9 10 8 3 11 14 6 2 14 8 13 1 10 5 4 5 6 4 15 20 10 33 22 18 27 2 33 10 14 24 29 19 11 12 20 9 12 10 23 8 23 17 12 12 0 0 1
>AY531265\AY531265\1..429\429\AAT00461.1\Homo sapiens\Homo sapiens biogenesis of lysosome-related organelles complex 1subunit 2 mRNA, complete cds./codon_start=1/product="biogenesis of lysosome-related organelles complex 1 subunit 2"/protein_id="AAT00461.1"/db_xref="GI:46558847"
2 0 2 0 0 1 0 3 8 2 2 2 1 1 0 0 1 3 1 3 1 3 0 1 0 2 6 6 3 7 1 1 1 0 2 1 1 0 6 9 3 3 0 5 0 0 8 9 5 5 3 5 1 0 1 0 1 2 3 5 0 0 0 1
>S66400#2\S66400\join(51..819,1114..1532)\1188\AAB27919.1\Homo sapiens\CD44=CD44SP {alternatively spliced} [human, breast carcinoma cellline MCF-7, mRNA Partial, 1586 nt]./gene="CD44"/codon_start=1/product="CD44R5"/protein_id="AAB27919.1"/db_xref="GI:435700"
2 3 2 1 4 6 1 6 6 3 0 9 7 8 1 5 11 9 16 11 4 7 7 9 1 7 9 6 1 9 12 3 8 6 2 3 13 2 4 8 13 10 3 9 6 6 13 8 17 9 6 4 6 3 5 7 4 14 7 8 5 1 0 0
>AK126047\AK126047\1418..1927\510\BAC86411.1\Homo sapiens\Homo sapiens cDNA FLJ44059 fis, clone TESTI4035065./codon_start=1/protein_id="BAC86411.1"/db_xref="GI:34532390"
0 1 2 1 5 8 0 2 6 2 0 5 5 3 0 4 5 3 6 3 0 2 8 4 1 3 3 4 0 3 7 4 4 5 1 1 3 3 0 1 1 1 2 7 8 1 2 2 1 0 2 0 0 2 4 1 1 2 1 4 9 0 0 1
>S73837\S73837\1..66\66\AAD14137.1\Homo sapiens\TCR V delta 2 D delta J delta=T cell receptor delta chain variableregion [human, systemic lupus erythematosus patient, peripheralblood, lymphocytes, mRNA Partial, 66 nt]./gene="TCR V delta 2 D delta J delta"/codon_start=1/protein_id="AAD14137.1"/db_xref="GI:4261837"
1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 1 0 0 0 0 0 0 2 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 2 1 2 0 0 2 0 0 0 0 0 1 1 0 0 0
>BC000148\BC000148\55..690\636\AAH00148.1\Homo sapiens\Homo sapiens synaptosomal-associated protein, 23kDa, transcriptvariant 1, mRNA (cDNA clone MGC:5325 IMAGE:2900640), complete cds./gene="SNAP23"/codon_start=1/product="synaptosomal-associated protein 23, isoform SNAP23A"/protein_id="AAH00148.1"/db_xref="GI:12652793"/db_xref="GeneID:8773"/db_xref="MIM:602534"
1 2 0 1 7 1 2 2 7 2 2 1 3 0 0 4 1 3 9 2 1 5 4 0 1 1 3 6 0 4 6 6 0 4 2 1 2 0 6 9 7 10 8 6 1 0 12 7 6 10 1 1 3 3 0 1 5 5 8 5 1 1 0 0
PyCogent-1.5.3/tests/data/interleaved.phylip 000644 000765 000024 00000015602 10665667404 022066 0 ustar 00jrideout staff 000000 000000 3 1758 I
human ATGGGCCAAG GGGACGAGAG CGAGCGCATC GTGATCAACG TGGGCGGCAC
chimp ?????????? ?????????? ?????????? ?????????? ??????????
mouse ATGGGCCAAG GGGACGAGAG CGAGCGCATC GTGATCAACG TGGGCGGCAC
GCGCCACCAG ACGTACCGCT CGACCCTGCG CACGCTGCCC GGCACGCGGC
?????????? ?????????? ?????????? ?????????? ??????????
GCGCCACCAG ACGTACCGCT CGACGCTGCG CACGCTGCCC GGCACGCGGC
TCGCCTGGCT GGCGGAGCCC GACGCCCACA GCCACTTCGA CTATGACCCG
?????????? ?????????? ?????????? ?????????? ??????????
TTGCCTGGCT GGCAGAGCCG GACGCCCACA GCCACTTCGA CTATGACCCG
CGTGCTGACG AGTTCTTCTT CGACCGCCAC CCCGGCGTCT TCGCGCACAT
?????????? ?????????? ?????????? ?????????? ??????????
CGTGCCGACG AGTTCTTCTT CGACCGCCAC CCGGGCGTCT TCGCTCACAT
CCTGAACTAC TACCGCACGG GCAAGCTGCA CTGCCCAGCC GACGTGTGCG
?????????? ??CCGCACGG GCAAGCTGCA CTGCCCAGCC GACGTGTGCG
CCTGAACTAT TACCGCACCG GCAAGCTTCA CTGCCCGGCC GACGTGTGCG
GGCCGCTCTA CGAGGAGGAG CTGGCCTTCT GGGGCATCGA CGAGACCGAC
GGCCGCTCTA CGAGGAGGAG CTGGCCTTCT GGGGCATCGA CG???C?GAC
GGCCGCTCTA CGAGGAGGAG CTGGCCTTCT GGGGCATCGA CGAGACGGAC
GTGGAGCCCT GCTGCTGGAT GACGTACCGC CAGCACCGCG ACGCCGAGGA
GTGGAGCCCT GCTGCTGGAT GACGTACCG? ?AGCACCGCG ACGCCGAGGA
GTGGAGCCCT GCTGCTGGAT GACCTATCGC CAGCACCGAG ACGCTGAGGA
GGCTCTGGAC AGCTTCGGCG GCGCTCCTCT GGACAACAGC GCCGACGACG
GGCGCTGGAC AGCTTCGGCG GCGCTCCTCT GGACAACAGC GCCGACG???
GGCGCTGGAC AGCTTTGGCG GTGCGCCCTT GGACAACAGC GCCGACGACG
CGGACGCCGA CGGCCCTGGC GACTCGGGCG ACGGCGAGGA CGAGCTGGAG
?????????? ?????????? ??????GGCG ACGGCGAGGA CGAGCTGGAG
CGGACGCCGA CGGCCCCGGC GACTCGGGCG ACGGCGAGGA CGAGCTGGAG
ATGACCAAGC GCCTGGCGCT CAGTGACTCC CCGGATGGCC GGCCTGGCGG
ATGACCAAGC GC??????CT CAGTGACTCC CCGGATGGCC GGCCTGGC??
ATGACCAAGA GATTGGCACT CAGTGACTCC CCAGATGGCC GGCCTGGCGG
CTTTTGGCGC CGCTGGCAGC CGCGCATCTG GGCGCTCTTC GAGGACCCGT
CTTT?GGCGC C????????? ?????????? ?????????? ??????????
CTTCTGGCGC CGCTGGCAAC CGCGCATCTG GGCGCTGTTC GAGGACCCCT
ACTCGTCCCG CTACGCGCGG TATGTGGCCT TCGCTTCCCT CTTCTTCATC
?????????? ?????????? TATGTGGCCT TCGCTTCCCT CTTCTTCATC
ACTCATCCCG CTACGCGCGG TATGTGGCCT TTGCCTCCCT CTTCTTCATC
CTGGTCTCCA TCACCACCTT CTGCCTGGAG ACCCACGAGC GCTTCAACCC
CTGGTCTCCA TCACCACCTT CTGCCTGGAG ACCCACGAGC GCTTCAACCC
CTGGTCTCCA TCACAACCTT CTGTCTGGAG ACTCACGAGC GCTTCAACCC
CATCGTGAAC AAGACGGAGA TCGAGAACGT TCGCAATGGC ACGCAAGTGC
CATCGTGAAC AAGACGGAGA TTGAGAACGT TCGCAATGGC ACGCAAGTGC
CATCGTGAAC AAGACCGAAA TCGAGAACGT TCGAAACGGC ACCCAAGTGC
GCTACTACCG GGAGGCCGAG ACGGAGGCCT TCCTTACCTA CATCGAGGGC
GCTACTACCG GGAGGCCGAG ACGGAGGCCT TCCTTACCTA CATCGAGGGC
GGTACTACCG GGAAGCAGAG ACGGAGGCCT TCCTCACCTA CATCGAGGGC
GTCTGTGTGG TCTGGTTCAC CTTCGAGTTC CTCATGCGTG TCATCTTCTG
GTCTGTGTGG TCTGGTTCAC CTT???GTTC CTCATGCGT? TCATCTTCTG
GTCTGCGTGG TCTGGTTCAC CTTCGAGTTC CTCATGCGTG TCGTCTTCTG
CCCCAACAAG GTAGAGTTCA TCAAGAACTC GCTCAACATC ATTGACTTTG
CCCCAACAAG GTAGAGTTCA TCAAGAACTC GCTCAACATC ATTGACTTTG
CCCCAACAAG GTGGAATTCA TCAAGAACTC CCTCAATATC ATTGACTTTG
TGGCCATCCT GCCCTTCTAC CTGGAGGTGG GGCTGAGCGG CCTGTCCTCC
TGGCCATCCT GCCCTTCTAC CTGGAGGTGG GGCTGAGCGG CCTGTCCTCC
TGGCCATTCT CCCCTTCTAC CTGGAGGTGG GCCTAAGCGG CCTGTCCTCA
AAGGCAGCCA AGGACGTGCT GGGCTTCCTG CGCGTCGTCC GCTTCGTGCG
AAGGCAGCCA AGGACGTGCT GGGCTTCCTG CGCGTCGTCC GCTTCGTGCG
AAAGCCGCCA AGGACGTTCT GGGCTTCCTG CGCGTCGTCC GCTTCGTGCG
CATCTTGCGC ATCTTTAAGC TGACCCGCCA CTTTGTGGGC CTGCGGGTCC
CATCTTGCGC ATCTTTAAGC TGACCCGCCA CTTTGTGGGC CTGCGGGTCC
CATCCTGCGC ATCTTCAAGC TGACCCGCCA CTTCGTGGGC CTGAGGGTCC
TGGGCCACAC GCTCCGAGCC AGCACCAACG AGTTCCTGCT GCTCATCATC
TGGGCCACAC GCTCCGAGCC AGCACCAACG AGTTCCTGCT GCTCATCATC
TGGGCCACAC GCTCCGTGCC AGCACCAACG AGTTCCTGCT GCTTATCATC
TTCCTGGCCT TGGGCGTGCT GATCTTCGCC ACCATGATCT ACTACGCCGA
TTCCTGGCCT TGGGCGTGCT GATCTTCGCC ACCATGATCT ACTATGCCGA
TTCCTGGCCC TGGGAGTGCT CATCTTTGCC ACCATGATCT ACTACGCCGA
GAGGATAGGG GCACAGCCCA ATGACCCCAG CGCCAGTGAG CACACGCACT
GAGGATAGGG GCACAGCCCA ATGACCCCAG CGCCAGTGAG CACACGCACT
GAGGATAGGG GCACAGCCCA ATGACCCCAG CGCCAGCGAA CACACACACT
TTAAGAACAT CCCCATCGGC TTCTGGTGGG CCGTGGTCAC CATGACGACC
TTAAGAACAT CCCCATCGGC TTCTG?TGGG CCGTGGTCAC CATGACGACC
TTAAAAACAT CCCCATCGGC TTCTGGTGGG CTGTGGTCAC CATGACGACA
CTGGGCTATG GAGACATGTA CCCGCAGACG TGGTCCGGCA TGCTGGTGGG
CTGGGCTATG GAGACATGTA CC???AGACG TGGTCCGGCA TGCTGGTGGG
CTGGGCTATG GAGACATGTA TCCCCAGACG TGGTCTGGAA TGCTGGTGGG
GGCTCTGTGT GCGCTGGCGG GCGTGCTCAC CATCGCCATG CCCGTGCCCG
GGCTCTGTGT GCGCTGGCGG GCGTGCTCAC CATCGCCATG CCCGTGCCCG
AGCCTTGTGT GCTCTGGCTG GTGTGCTGAC CATTGCCATG CCGGTGCCTG
TCATCGTGAA CAATTTCGGG ATGTATTACT CCTTAGCCAT GGCTAAGCAG
TCATCGTGAA CAATTTCGGG ATGTATTACT CCTTAGCCAT GGCTAAGCAG
TCATCGTGAA CAATTTTGGG ATGTACTACT CTTTAGCCAT GGCTAAGCAG
AAACTACCAA AGAAAAAAAA GAAGCATATT CCGCGGCCAC CGCAGCTGGG
AAACTACCAA AGAAAAAAAA GAAGCATATT CCGCGGCCAC CGCAGCTGGG
AAACTACCAA AGAAAAAAAA GAAGCATATT CCGCGGCCAC CACAGCTGGG
ATCTCCCAAT TATTGTAAAT CTGTCGTAAA CTCTCCACAC CACAGTACTC
ATCTCCCAAT TATTGTAAAT CTGTCGTAAA CTCTCCACAC CACAGTACTC
ATCTCCCAAT TATTGTAAAT CTGTCGTAAA CTCTCCACAC CACAGTACTC
AGAGTGACAC ATGTCCGCTG GCCCAGGAAG AAATTTTAGA AATTAACAGA
AGAGTGACAC ATGTCCGCTG GCCCAGGAAG AAATTTTAGA AATTAACAGA
AGAGTGACAC ATGCCCGCTG GCCCAGGAAG AAATTTTAGA AATTAACAGA
GCAGATTCCA AACTGAATGG GGAGGTGGCG AAGGCCGCGC TGGCGAACGA
GCAGATTCCA AACTGAATGG GGAGGTGGCG AAGGCCG??? TGGCGAAC??
GCAGATTCCA AACTGAATGG GGAGGTGGCG AAGGCCGCGC TGGCGAACGA
AGACTGCCCC CACATAGACC AGGCCCTCAC TCCCGATGAG GGCCTGCCCT
AGA??GCCCC CACATAGACC AGGCC???AC TCCCGATGAG GGCCTGCCCT
AGACTGCCCC CACATAGACC AGGCCCTCAC TCCCGATGAG GGCCTGCCCT
TTACGCGCTC GGGCACCCGC GAGAGATACG GACCCTGCTT CCTCTTATCA
TTACGCG??C GGGCAC??GC GAGAGATACG GACCCTGCTT CCTCTTATCA
TTACCCGCTC GGGCACCCGC GAGAGATACG GACCCTGCTT CCTCTTATCA
ACCGGGGAGT ACGCGTGCCC ACCTGGTGGA GGAATGAGAA AGGATCTTTG
ACCGGGGAGT ACGCG????? ?????????? ?????????? ???ATCTTTG
ACCGGGGAGT ACGCGTGCCC ACCTGGTGGA GGAATGAGAA AGGATCTTTG
CAAAGAAAGC CCTGTCATTG CTAAGTATAT GCCGACAGAG GCTGTGAGAG
CAAAGAAAGC CCTGTCATTG CTAAGTATAT GCCGACAGAG GCTGTGAGAG
CAAAGAAAGC CCTGTCATTG CTAAGTATAT GCCGACAGAG GCTGTGAGAG
TGACTTGA
TGACTTGA
TGACTTGA
PyCogent-1.5.3/tests/data/murphy.tree 000644 000765 000024 00000001103 10665667404 020531 0 ustar 00jrideout staff 000000 000000 (Chook,((((((((FlyingFox,DogFaced),((FreeTaile,LittleBro),(TombBat,RoundEare))),(FalseVamp,LeafNose)),(((Horse,Rhino),(Pangolin,(Cat,Dog))),(Llama,(Pig,(Cow,(Hippo,(SpermWhale,HumpbackW))))))),(Mole,Hedgehog)),(((TreeShrew,FlyingLem),(Galago,(HowlerMon,(Rhesus,(Orangutan,(Gorilla,(Human,Chimpanzee))))))),(Jackrabbit,(FlyingSqu,(OldWorld,(Mouse,Rat)))))),((NineBande,HairyArma),(Anteater,Sloth))),(((Dugong,Manatee),((AfricanEl,AsianElep),(RockHyrax,TreeHyrax))),(Aardvark,((GoldenMol,(Madagascar,Tenrec)),(LesserEle,GiantElep))))),(Caenolest,(Phascogale,(Wombat,Bandicoot))));
PyCogent-1.5.3/tests/data/primates_brca1.fasta 000644 000765 000024 00000071347 10665667404 022261 0 ustar 00jrideout staff 000000 000000 >TreeShrew
tgtggcataaatacttatgccagctcattacagcatgagaacagcagtttattactcact
aaggacagaatgaatgtagaaaaggctgaattgtgtaataaaagccaacaacctgactta
gcaaggagccagcagagcagatggactgaaaataaggaaacatgtaatgataggcagatt
cccagcacagaaaaaaaggtagatctaaatgctgatcccctgtgtgggaagaaaaaacaa
gctaagcagaaacygctatgttctaacagtcctagagatnnngaccaagattctccttgg
ataactctaaatagtagcattcagaaagttaatgaatggttttccagaagtgatgaaatg
ttaacttctaacgactcacatgatggtgagtctgaannnnnnnnnnnnatagctggtgca
ttygaagytccaaataaagtagatgaatattctggttcttcagaaaaaatagacttaatg
gccaacaatcttcatgatgctttaataagtaaaagtgaaggaatctactccaaaccagta
gagggtaatattgaagataaaatatttgggaaaacctatcggaggaaagcaagtcttcct
aacttgagccgtgtaactgatgatctaattagaggggcatttgttacagagcctgagata
actcgagagcgtcccttcacaaataaattaaagcggaaaaggagaactatatcaggcctt
catcctgaagattttatcaagaaaacagatttggcagttgttcaaaagactcctgaaaag
ataaatcagagaactgaccaaatagagcataatggtcaggtgatgagtattgctaatagt
ggtcatgagaatgaaacaaaaggtgattatatttcgaaagagaaaaatgctaacccaatg
gaatcattagaaaaagaatctgctctcagaactaaagctgagcccataagcagcagtgta
agcaatatggaactagaaataaataaccacagttcagaagcacctaagaagaataggctg
aggagaaagttttctgctaggcatattcgcacacttgaactagtagacaataaaagtcca
agcccacctaatcgtactgaactacaaattgacagttattctagcggtgaagagagaaag
aaaaagnnnggtgagcaaatgccagttggacacagcagaaagtttcaacttgaggaagag
aaagaacctacaactggagccaagaaaaataaccagccaaatacagaaataagtgaaaga
catgccagtggtgttatcccagatctgaagttaacaaacatacctggttttttcacaaac
tcttcgagttctaataaacttccagaatttgtccatcgtagccttcaaagagaannnaaa
gaagagaacnnncgagaaacaattcaaatatccagtagtaccaaannnnnnnnngatctg
gtattaaggggagaannnaggggtttgcaagatgtaaggtctgcagagagtaccagtatt
tctttggtacctgatactgatgataacacccaggatagcatctcattactagatgctaac
cccctagctaggaaggcaaaaacagcaccaaatcaatgtgtaaatcagagtgcaacaact
gaaaaccccaaggaacttatacacagttgttctaaaactactaggaatnnnnnngaaggc
ttcaaggatccattgaaaagtgaagttaatcatattcaggagatgagtgtagaaatggag
gagagtgaacttgatactcagtatttacagaatacattcaggagttcaaagcgtcagtca
tttgctctgtcttcaaatccaggaaatccagaaaaggaacatgtctgtgttnnnnnnnnn
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn
aaagaaagtctgaaagagtctaacatccaacatatacaggcagttagtaccatggttnnn
nnnnnnnnnnnntttcagaaagataagnnnctaggtgattttgctacatctggcattaaa
gaagtccctagactttgtccatcatctcagttcagaggcaatgaaactgatctcattact
gcaaataaacctgaagtttcacaaaacccgtatcatatgccattactttatcctgtcaag
tcacctattataactaaaagtaagaaaagcctgtcagaggaagggtttgaggaacaggca
atgtcacttgaaagagcaatggaaaatgagaacatcattcaaagtacagtgagcacaatt
agccaagataacattagagaaggtgcttttaaagaagccagctcaagcagtattaatgaa
ataggtcctagtactaatgaaggaagctctagtattaatgaggtaggttccagtnnnnnn
nnnnnnnnnnnnnnnggtgaaaacattcaagcagaactaggtaaaaagagaggatccaaa
ttaaatgctgtgcttagattaggtcttatgcaacccgaagtctataagcaaagtcttcct
ttaagtaatcataatgatcctgaaatgaaaagacaagaaaaaaatgaaggaggagttcag
gctattaaannngatttacctccatgtctaatttcagataatcaagagcatnnnatggga
agtagccatgcttctcagatttgttctgagacacctgatgatctgttagatgatgatgaa
ggaaaagaaaatnnnagctttgctgaggttgatgttaaggaaagatctgctgtttttggc
aaaactgtccagagaagagagttaagaaggagctctagccctttaactcgtgcatgtttg
actgagggtcagcaaacaggagcccagaaattagattcatcagaagagaacctatctagt
gag
>Orangutan
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcagact
cccagcacagaaaaaaaggtagacctgaatgctgatcccctgtgtgagagaaaagaatgg
aataagcagaaactgccatgctcagagaatcctagagatnnnactgaagatgttccttgg
ataacactaaatagcagcattcagaaagttaatgagtggttttccagaagtgacgaactg
ttaggttctgatgactcacatgatgggaggtctgaatcaaatgccaaagtagcggatgta
ttggacgttctaaatgaggtagatgaatattctggttcttcagagaaaatagacttactg
gccagtgatcctcatgaggctttaatttgtaaaagtgaaagagttcactccaaatcagta
gagagtaatattgaagacaaaatatttgggaaaacctatcggaggaaggcaagcctcccc
aacttaagccatgtaactgaaaatctaattataggagcatttgttactgagccacagata
atacaagagcgtcccctcacaaataaattaaagcgtaaaaggagagctacatcaggcctt
catcctgaggattttatcaagaaagcagatttggcagttnnncaaaagactcctgaaatg
ataaatcagggaactaaccaaatggagcagaatggtcaagtgatgaatattactaatagt
ggtcatgagaataaaacaaaaggtgattctattcagaatgagaaaaatcctaacccaata
gaatcactcgaaaaagaatctgctttcaaaacaaaagctgaacctataagcagcagtata
agcaatatggaactcgaattaaatatccataattcaaaagcacctaaaaagaataggctg
aggaggaagtcttctaccaggcatattcatgcgcttgaactagtagtcagtagaaatcta
agcccacctaattgtactgaattgcaaattgatagttgttctagcagtgaagagataaag
aaaaaaaaatacaaccaaatgccagtcaggcacagcagaaacctacaactcatggaagat
aaagaacctgcaactggagccaagaagagtaacaagccaaatgaacagacaagtaaaaga
catgacagcgatactttcccagagctgaagttaacaaatgcacctggttcttttactaac
tgttcaaataccagtgagcttaaagaatttgtcaatcctagccttccaagagaagaaaaa
gaagagaaannnctaggaacagttaaagtgtctaataatgccaaagaccccaaagatctc
atgttaagtggaggannnagggttttgcaaactgaaagatctgtagagagtagcagtatt
tcattggtacctggtactgattatggcactcaggaaagtatctcgttactggaagttagc
actctagggnnnaaggcaaaaacagaaccaaataaatgtgtgagtcagtgtgcagcattt
gaaaaccccaaggaactaattcatggttgtttcaaagatactagaaatgacacagaaggg
tttaagtatccattgggacatgaagttaaccacagtcaggaaacaagcatagaaatggaa
gaaagtgaacttgatactcagtatttgcagaatacattcaaggtttcaaagcgccagtca
tttgctctgttttcaaatccaggaaatccagaagaggaatgtgcaacattctctgcccac
tctaggtccttaaagaaacaaagtccaaaagtcacttttgaatgtgaacaaaaggaagaa
aatcaaggaaagaatgagtctaatatcaagcctgtacagacagctaatatcactgcaggc
tttcctgtggtttgtcagaaagataagnnnccagttgattatgccaaatgtagtatcaaa
ggaggctctaggttttgtctatcatctcagttcagaggcaacgaaactggactcattact
ccaaataaacatggactttcacaaaacccatatcatataccaccactttttcccatcaag
tcatttgttaaaactaaatgtaagaaaaacctgctagaggaaaactctgaggaacattca
atgtcacctgaaagagaaatgggaaacgagaacnnnattccaagtacagtgagcataatt
agccgtaataacattagagaaaatgtttttaaagaagccagctcaagcaatattaatgaa
gtaggttccagtactaatgaagtgggctccagtattaatgaagtaggttccagtnnnnnn
nnnnnnnnnnnnnnngatgaaaacattcaagcagaactaggtagaagcagagggccaaaa
ttgaatgctatgcttagattaggggttttgcaacctgaggtctataaacaaagttttcct
ggaagtaatggtaagcatcctgaaataaaaaagcaagaatatgaagaannngtacttcag
actgttaatacagacttctctccatgtctgatttcagataacctagaacagcctatgaga
agtagtcatgcatctcaggtttgttctgagacacctaatgacctgttagatgatggtgaa
ataaaggaagatactagttttgctgaaaatgacattaaggaaagttctgctgtttttagc
aaaagcgtccagagaggagagcttagcaggagtcctagccctttcacccatacacatttg
gctcagggttaccgaagaggggccaagaaattagagtcctcagaagagaacttatctagt
gag
>Rhesus
tgtggcacaaatactcatgccagctcattacagcatgagaacnnnagtttgttactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggcttg
gcaaggagccaacataacagatggactggaagtaaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagatctgaatgctaatgccctgtatgagagaaaagaatgg
aataagcaaaaactgccatgctctgagaatcctagagacnnnactgaagatgttccttgg
ataacactaaatagcagcattcagaaagttaatgagtggttttccagaagtgatgaactg
ttaagttctgatgactcacatgatggggggtctgaatcaaatgccaaagtagctgatgta
ttggacgttctaaatgaggtagatgaatattctggttcttcagagaaaatagacttactg
gccagtgatcctcatgagcctttaatatgtaaaagtgaaagagttcactccagttcagta
gagagtaatattaaagacaaaatatttgggaaaacctatcggaggaaggcaaaccttccc
aatttaagccatgtaactgaaaatctaattataggagcacttgttactgagtcacagata
atgcaagagcgtcccctcacaaataaattaaagcgtaaaaggagaactacatcaggtctt
catcctgaggattttataaagaaagcagatttggcagttnnncaaaagactcctgaaata
ataaatcagggaactaaccaaatggagcagaatggtcaagtgatgaatattactaatagt
gctcatgagaataaaacaaaaggtgattctattcagaatgagaaaaatcctaacccaata
gaatcactggaagaagaatctgctttcaaaactaaagctgaacctataagcagcagtata
aacaatatggaactagaattaaatatccacaattcaaaagcacctaaaaaaaataggctg
aggaggaagtcttctaccaggcatattcatgcgcttgaactagtagtcagtagaaatcta
agcccacctaactgtactgaactacaaattgatagttgttctagcagtgaagagataaag
aaaaaaaattacaaccaaatgccagtcaggcacagcagaaacctacaactcatggaagat
aaagaatctgcaactggagccaagaagagtaacaagccaaatgaacagacaagtaaaaga
catgccagtgatactttcccagaactgaagttaacaaaggtacctggttcttttactaac
tgttcannnaatactagtgaaaaagaatttgtcaatcctagcctttcaagagaagaaaaa
gaagagaaannnctagaaacagttaaagtgtctaataatgccaaagaccccaaagatctc
atcttaagtggagaannnagggttttacaaactgaaagatctgtagagagtagcagtatt
tcattggtacctggtaccgattatggcactcaggaaagtatctcattactggaagttagc
actctagggnnnaaggcaaaaacagaacgaaataaatgtatgagtcagtgtgcagcattt
gaaaaccccaaggaactaattcatggttgttctgaagatactagaaatgacacagaaggc
tttaagtatccattgggaagtgaagttaaccacagtcaggaaacaagcatagaaatagaa
gaaagtgaacttgatactcagtatttgcagaatacattcaaggtttcaaagcgccagtcc
tttgctctgttttcaaatccaggaaatccagaagaggaatgtgcaacattctctgcccac
tctaggtccttaaagaaacaaagtccaaaagttacttctgaatgtgaacaaaaggaagaa
aatcaaggaaagaaacagtctaatatcaagcctgtacagacagttaatatcactgcaggc
ttttctgtggtttgtcagaaagataagnnnccagttgataatgccaaatgtagtatcaaa
ggaggctctaggttttgtctatcatctcagttcagaggcaacgaaactggactcattact
ccaaataaacatggactgttacaaaacccataccatataccaccactttttcctgtcaag
tcatttgttaaaactaaatgtaacaaaaacctgctagaggaaaactctgaggaacattca
gtgtcacctgaaagagcagtgggaaacaagaacatcattccaagtacagtgagcacaatt
agccataataacattagagaaaatgcttttaaagaagccagctcgagcaatattaatgaa
gtaggttccagtactaatgaagtgggctccagtattaatgaagtaggttccagtnnnnnn
nnnnnnnnnnnnnnngatgaaaacattcaagcagaactaggtagaaacagagggccaaaa
ttgaatgctgtgcttagattagggcttttgcaacctgaggtctgtaaacaaagtcttcct
ataagtaattgtaagcatcctgaaataaaaaagcaagaacatgaagaannnttagttcag
actgttaatacagacttctctccatgtctgatttcagataacctagaacagcctatggga
agtagtcatgcgtctgaggtttgttctgagactcctgatgatctgttagatgatggtgaa
ataaaggaagatactagttttgctgaaaatgacattaaggagagttctgctgtttttagc
aaaagcatccagagaggagagctcagcaggagccctagccctttcacccatacacattta
gctcagggttaccgaaaagaggccaagaaattagagtcctcagaagagaacttatctagt
gag
>Chimpanzee
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
cccagcacagaaaaaaaggtagatctgaatgctgatcccctgtgtgagagaaaagaatgg
aataagcagaaactgccatgctcagagaatcctagagatnnnactgaagatgttccttgg
ataacactaaatagcagcattcagaaagttaatgagtggttttccagaagtgatgaactg
ttaggttctgatgactcacatgatggggggtctgaatcaaatgccaaagtagctgatgta
ttggacgttctaaatgaggtagatgaatattctggttcttcagagaaaatagacttactg
gccagcgatcctcatgaggctttaatatgtaaaagtgaaagagttcactccaaatcagta
gagagtaatactgaagacaaaatatttgggaaaacctatcggaggaaggcaagcctcccc
aacttaagccatgtaactgaaaatctaattataggagcatttgttactgagccacagata
atacaagagcgtcccctcacaaataaattaaagcgtaaaaggagagctacatcaggcctt
catcctgaggattttatcaagaaagcagatttggcagttnnncaaaagactcctgaaatg
ataaatcagggaactaaccaaatggagcagaatggtcaagtgatgaatattactaatagt
ggtcatgagaataaaacaaaaggtgattctattcagaatgagaaaaatcctaacccaata
gaatcactcgaaaaagaatctgctttcaaaacgaaagctgaacctataagcagcagtata
agcaatatggaactcgaattaaatatccacaattcaaaagcacctaaaaagaataggctg
aggaggaagtcttctaccaggcatattcatgcgcttgaactagtagtcagtagaaatcta
agcccacctaattgtactgaattgcaaattgatagttgttctagcagtgaagagataaag
aaaaaaaagtacaaccaaatgccagtcaggcacagcagaaacctacaactcatggaagat
aaagaacctgcaactggagtcaagaagagtaacaagccaaatgaacagacaagtaaaaga
catgacagcgatactttcccagagctgaagttaacaaatgcacctggttcttttactaac
tgttcaaataccagtgaacttaaagaatttgtcaatcctagccttccaagagaagaagaa
gaagagaaannnctagaaacagttaaagtgtctaataatgccgaagaccccaaagatctc
atgttaagtggagaannnagggttttgcaaactgaaagatctgtagagagtagcagtatt
tcattggtacctggtactgattatggcactcaggaaagtatctcgttactggaagttagc
actctagggnnnaaggcaaaaacagaaccaaataaatgtgtgagtcagtgtgcagcattt
gaaaaccccaagggactaattcatggttgttccaaagatactagaaatgacacagaaggc
tttaagtatccattgggacatgaagttaaccacagtcgggaaacaagcatagaaatggaa
gaaagtgaacttgatgctcagtatttgcagaatacattcaaggtttcaaagcgccagtca
tttgctctgttttcaaatccaggaaatccagaagaggaatgtgcaacattctctgcccac
tgtaggtccttaaagaaacaaagtccaaaagtcacttttgaacgtgaacaaaaggaacaa
aatcaaggaaagaatgagtctaatatcaagcctgtacagacagttaatatcactgcaggc
tttcctgtggtttgtcagaaagataagnnnccagttgattatgccaaatgtagtatcaaa
ggaggctctaggttttgtctatcatctcagttcagaggcaacgaaactggactcattact
ccaaataaacatggacttttacaaaacccatatcatataccaccactttttcccatcaag
tcatttgttaaaactaaatgtaagaaaaacctgctagaggaaaactttgaggaacattca
atgtcacctgaaagagaaatgggaaatgagaacnnnattccaagtacagtgagcacaatt
agccgtaataacattagagaaaatgtttttaaagaagccagctcaagcaatattaatgaa
gtaggttccagtactaatgaagtgggctccagtattaatgaagtaggttccagtnnnnnn
nnnnnnnnnnnnnnngatgaaaacattcaagcagaactaggtagaaacagagggccaaaa
ttgaatgctatgcttagattaggggttttgcaacctgaggtctataaacaaagtcttcct
gaaagtaattgtaagcatcctgaaataaaaaagcaagaatatgaagaannngtagttcag
actgttaatacagatttctctccatgtctgatttcagataacttagaacagcctatggga
agtagtcatgcatctcaggtttgttctgagacacctgatgacctgttagatgatggtgaa
ataaaggaagatactagttttgctgaaaatgacattaaggaaagttctgctgtttttagc
aaaagcgtccagagaggagagcttagcaggagtcctagccctttcacccatacacatttg
gctcagggttaccgaagaggggccaagaaattagagtcctcagaagagaacttatctagt
gag
>Gorilla
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaaacaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
cccagcacagaaaaaaaggtagatctgaatgctgatcccctgtgtgagagaaacgaatgg
aataagcagaaactgccatgctcagagaatcctagagatnnnactgaagatgttccttgg
ataacactaaatagcagcattcagaaagttaatgagtggttttccagaagtgatgaactg
ttaggttctgatgactcacatgatggggggtctgaatcaaatgccaaagtagctgatgta
ttggacgttctaaatgaggtagatgaatattctggttcttcagagaaaatagacttactg
gccagtgatcctcatgaggctttaatatgtaaaagtgaaagagttcactccaaatcagta
gagagtaatattgaagacaaaatatttgggaaaacctatcggaggaaggcaagcctcccc
agcttaagccatgtaactgaaaatctaattataggagcatttgttactgagccacagata
atacaagagcgtcccctcacaaataaattaaagcgtaaaaggagagctacatcaggcctt
catcctgaggattttatcaagaaagcagatttggcagttnnncaaaagactcctgaaatg
ataaatcagggaactaaccaaatggagcagaatggtcaagtgatgaatattactaatagt
ggtcatgagaataaaacaaaaggtgattctattcagaatgagaaaaatcctaacccaata
gaatcactagaaaaagaatctgctttcaaaacgaaagctgaacctataagcagcagtata
agcaatatggaactcgaattaaatatccacaattcaaaagcgcctaaaaagaataggctg
aggaggaagtcttctaccaggcatattcatgcgcttgaactagtagtcagtagaaatcta
agcccacctaattgtactgaattgcaaattgatagttgttctagcagtgaagagataaag
aaaaaaaagtacaaccaaatgccagtcaggcacagcagaaacctacagctcatggaagat
aaagaacctgcaactggagccaagaagagtaacaagccaaatgaacagacaagtaaaaga
catgacagcgatactttcccagagctgaagttaacaaatgcacctggttcttttactaac
tgttcaaataccagtgaacttaaagaatttgtcaatcctagccttccaagagaagaaaaa
gaagagaaannnctagaaacagttaaagtgtctaataatgccgaagaccccaaagatctc
atgttaagtggagaannnagggttttgcaaactgaaagatctgtagagagtagcagtatt
tcattggtacctggtactgattatggcactcaggaaagtatctcgttactggaagttagc
actctagggnnnaaggcaaaaacagaaccaaataaatgtgtgagtcagtgtgcagcattt
gaaaaccccaagggactaattcatggttgttccaaagatactagaaatgacacagaaggc
tttaagtatccattgggacatgaagttaaccacagtcgggaaacaagcatagaaatggaa
gaaagtgaacttgatgctcagtatttgcagaatacattcaaggtttcaaagcgccagtca
tttgctctgttttcaaatccaggaaatccagaagaggaatgtgcaacattctctgcccac
tctaggtccttaaagaaacaaagtccaaaagtcacttttgaatgtgaacaaaaggaagaa
aatcaaggaaagaatgagtctaatatcaagcctgtacagacagttaatatcactgcaggc
tttcctgtggtttgtcagaaagataagnnnccagttgattatgccaaatgtagtatcaaa
ggaggctctaggttttgtctatcatctcagttcagaggcaacgaaactggactcattact
ccaaataaacatggacttttacaaaacccatatcatataccaccactttttcccatcaag
tcatttgttaaaactaaatgtaagaaaaacctgctagaggaaaactttgaggaacattca
atgtcacctgaaagagaaatgggaaatgagaacnnnattccaagtacagtgagcacaatt
agccgtaataacattagagaaaatgtttttaaagaagccagctcaagcaatattaatgaa
gtaggttccagtactaatgaagtgggctccagtattaatgaagtaggttccagtnnnnnn
nnnnnnnnnnnnnnngatgaaaacattcaagcagaactaggtagaaacagagggccaaaa
ttgaatgctatgcttagattaggggttttgcaacctgaggtctataaacaaagtcttcct
ggaagtaattgtaagcatcctgaaataaaaaagcaagaatatgaagaannngtagttcag
actgttaatacagatttctctccatgtctgatttcagataacttagaacagcctatggga
agtagtcatgcatctcaggtttgttctgagacacctgatgacctgttagatgatggtgaa
ataaaggaagatactagttttgctaaaaatgacattaaggaaagttctgctgtttttagc
aaaagcgtccagagaggagagcttagcaggagtcctagccctttcacccatacacatttg
gctcagggttaccgaagaggggccaagaaattagagtcctcagaagagaacttatctagt
gag
>FlyingLem
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattacgcact
aaagacagaataaatgttgaaaagactgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaggagagcagatgggctgaaagtaaggaaacatgtaatgataggcagacg
cccagcacagagaaaaagatagatctaaatgctgattcccagcatgggagaaaagaacgg
aatatgcagaaacctccataccctgagagtcctagagatnnnacccaagatgttccttgg
ataacactaaacagcagcattcagaaagttaatgagtggttttccagaagtgatgaaatt
ttagcttctgatgactcacgtgacagggtgtctgaatcaaatgccaaagtagctggtgca
ttagaagttccaaatgatgtagatggatattctgattcttcagagaaagttgatttaatg
gccagtgatcctcatgatgctttaatatgtaaaagtgaaagaatccactccagaccagta
gagagtaatatcaaagataaaatatttgggaaaacctatcagaggaagacaagcctccct
aacttgagccacgtaaatgaagatctaattataggagcatttgttacagaaccacagata
acacaagagcgtcccctcacaaataaggtaaagcctaaaaggagaactacatcaggcctt
catcctgaggattttatcaagaaagcagacttggcagttgttcaaaaaactcctgaaaag
ataaatcagggaattgaccaaatggagcagaatgatcgagtgatgaatattattaatagt
ggtcatgagaatgaaacaaaggatgattatgttcagaaagagaaaaatgctaacccaaca
gaatcattggaaaaagaatctgctttcagaactaaagcagaacctataagcagcagtata
agcaatatggaaatagaattaaatatccacaattcaaaaccatctaagaagaataggctg
aggaagatgtcctctactaggcatattcatgcacttgaactagtagtcaatagaaatcca
agcccacctaattatactgaactacaaattgatagttgttctagcagtgaagaaatagag
aaaaaaaattccagccaaatgccagtcaggcacagcagaaagcttcaactcatggaaaat
aaagaacctgcaactggagccaagaagagtaacaagccaaatgaacaaataagtagaaga
cattccagtaatgctttcccagaactgcggttaacaaatgtacctgttttttttgctaac
tgttcaagttctaataaacttcaagaatttatcgatcctagccttcaaagagaagaaata
gaagagaacnnnctagaaacaattcatgtgtctaatagtgccaaagaccccaaagatttg
gtgttaagtggggagnnnaagggtttgcaaactgaaagatctgtagagagtaccagtatt
tcattagtacctgatactgattatggcactcaagacagtatctcaatattagaagctaac
atcctagggnnnaaggcaaaaacagcaccaagtcaacatgcaaatcagtgtgcagcaatt
gaaaaccccaaagaacttatccatggttgtcctaaaggtactagaaatgacacagaggat
tttaaggatccattgagatgtggagttgaccacattcagaagacaagcatagaaatgcaa
gagagtgaacttgatactcagtatttacaaaatatattcaaggtttcaaaacgtcagtca
tttgctctcttttcaaatccaggaaatccagaaaaggagtgtgcaacagtctatgcccac
tccaggttgttaaggaaacaaagtccaaaagtcactcctgaatgtgaacaaaaagaagaa
aatgagggaaataaagagtctaaaatcaagcacatacaggcagttaataccactgtgggc
ttttctgtcctttgtcagaatgttaagaagccaggtgattatgccaaatttagcattaaa
ggagtctctaggcattgttcatcatctcagttcagaggcaatgaaactgaactcattact
gcaaataaacatggaattttacaaaactcatgtcatatgtcatcactttcccccatcagg
tcatctgttaaaattaaatgtaagaagaacctgtcagaggaaaggtttgaggaacattca
gtgtcacctgaaagagcaatggcaaacaagagaatcattcaaagtacagtgaacacaatt
agccaaaataacattagagacagtgcttctaaagaagccagctcaagcagtattaatgaa
gtaggttccagtactaatgaagtaggctccagtattaatgaagtaggtcccagtnnnnnn
nnnnnnnnnnnnnnnggtgaaaacattcaagcagaactaggtagaaacagaggacctaaa
ttaagtgctatgcttagattaggcctcatgcaacctgaagtttacaagcaaaatcttcct
ttaggtaattgtaaacatcctgaaataaggnnncaagaagaaaatgaaggaatagttcag
gctgttaatacaaatctgtctctgtgcctaatttcacataacctcgaacaacctatggaa
agtagtcatgcttcccaggtttgttctgagacacctgatgacctgttagatggtgatgag
ataaaggaaaacaccagctttgctgaaagtgacagtaaggaaagatctgctgtttttagc
aaaagtgtccagagaggagagttaagcaggagccctagcccttttgcccaaacatgtttg
gctcagggtcaccaaagaggagccaggaaattagagtcttctgaagagaacgtatctagt
gag
>Galago
tgtggcaaaaatactcatgccagctcattacagcatgagagcagcagtttattactcact
aaagacaaaatgaatgtagaaaaggctgaattttgtaataaaagcaaacagcctggctta
gcaaggagccaacagagcagatcggctcaaagtaaggaaacatgcaatgataggcacact
tgcagccctgagcaaaaggtagatctgaatactgctcccccatatgggagaaaagaacag
aataaggagaaacttctatgctccaagaatcctagagatnnnagccaagatgttccttgg
ataacactaaatagcagcattcagaaagttaatgaatggttttctagaagtgatgaaatg
ttaacttctgatgactcacatgatgagggttctgaatcacatgctgaagtagctggagcc
ttagaagttccaagtgaagtagatggatattccagttcctcagagaaaatagacttactg
gccagtgatcctcattatcctataatatgtaaaagtgaaagagttcactccaaaccaata
aagagtaaagttgaagataaaatatttgggaaaacttatcggaggaaggcaagcctccct
aacttaagccatgtaactgaaaatctaattataagagcagctgctactgagccacagata
acacaagagtgttccctcacaaataaattaaaacgtaaaaggagaactacatcaggtctt
tgtcctgaggattttatcaagaaggcagatttggcagttgttcaaaagacacctgaaaag
agaattcagggaactaaccaagtggatcagaatagtcacgtggtaaatattactaatagt
ggttatgagaatgaaacaaaaggtgattatgttcagaatgaaaaaaatgctaactcaaca
gaatcattggaaaaagaatcttctctcggaactaaagctgaacctataagcagcagtata
agtaatatgaaattagaattaaatattcacaattcaaaagcaagtaaaaagaaaaggctg
aggaagaagtcttctagcaggcatattcgtgcacttgaactagtagtcaataaaaatcca
agccctcctaatcataccaacctacaaattgacagttgttctagcagtgaagaaataaag
gataaaagttctgaccaaataccagtcaggcatagcagaaagcctggactcatggaagat
agagaacctgcaactggagccaagaaaagtaacaagccaaatgagcaaataagtaaaaga
catgtcagtgatactttcccagaagtggcattaacaaatatatctagtttttttactaac
tgttcaggttctaatagacttaaagaatttgtcaatcctagccttcaaagaaaaaaaaca
gaagagaacttagaagaaacaattcaagtgtctaatagtaccaaaggtccggtgttaagt
ggagaaagggttttgnnncaaattgaaagtgaagaaagatctataaaaagcaccagtatt
tcattggtacctgatactgattatggtactcaggacagtaactcgttactgaaagttaaa
gtcttacggnnnaaggtgaaaacagcaccaaataaacatgcaagtcagggtacagccact
gaaaaccccaaggaactaatccatggttgctctaaagatactggaaatgacacagagggc
tataaggatccattgagacatgaaattaaccacattcagaagataagcatggaaatggaa
gacagtgaacttgatactcagtatttacagaatacattcaagttttcaaagcgtcagtcg
tttgctctgttttcaaacctannnnnnnnnggaaaggaatgtgcaacagtctgtgcccag
tctctctctgcgtccttaagaaaaggttcaaaagtcattcttgaatgtgaacaaatagaa
aatccaggaatgaaagagcctaaaatcaagcatatacagggaaataatatcaatacaggc
ttctctgtagtttgtcagaaagataagaaaacagatgattatgccaaatacagcatcaaa
gaagcatctaggttttgtttgtcaaatcagtttcgagacaatgaaactgaatccattact
gtaaataaacttggaattttacaaaacctctatcatataccaccactttctcctatcagg
ctatttgataaaactaaatgtaatacaaacctgttagaggaaaggtttgaagaacattca
gtgttacctgaaaaagcagtaggaaacgagaacaccgttccaagtacaatgaatacaatt
aaccaaaataacnnnagagaaagtgcttataaagaagccagttcaagcagtatcaatgaa
gtaagctcgagtactaatgaagtgggctccagtgttaacgaagtaggccccagtnnnnnn
nnnnnnnnnnnnnnnagtgaaaacattcaagcagaactagataaaaacagaggacctaag
ttgaatgctgtgcttagattaggtcttatgcaacctgaagtctataaacaaaatcttcct
ataagtaattgtgaacatcctaaaataaaagggcaagaagaaaatggannngtagttcaa
cctgttaatccagatttttcttcatgtctaatttcagataacctagaacaacctacgaga
agtagtcatgcttctcagctttgttctgagacacctgatgacttattagttgatgatgaa
ctaaaggaaaataccagttttgctgaaaataacattaaggaaagatctgctgtttttagc
aaaaatgtcatgagaagagagattagcaggagccctagccctttagcccatatacatttg
actcaggctcaccaaagagaggttaggaaattagagtcctcagaagagaacatgtctagt
gaa
>Human
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttattactcact
aaagacagaatgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
cccagcacagaaaaaaaggtagatctgaatgctgatcccctgtgtgagagaaaagaatgg
aataagcagaaactgccatgctcagagaatcctagagatnnnactgaagatgttccttgg
ataacactaaatagcagcattcagaaagttaatgagtggttttccagaagtgatgaactg
ttaggttctgatgactcacatgatggggagtctgaatcaaatgccaaagtagctgatgta
ttggacgttctaaatgaggtagatgaatattctggttcttcagagaaaatagacttactg
gccagtgatcctcatgaggctttaatatgtaaaagtgaaagagttcactccaaatcagta
gagagtaatattgaagacaaaatatttgggaaaacctatcggaagaaggcaagcctcccc
aacttaagccatgtaactgaaaatctaattataggagcatttgttactgagccacagata
atacaagagcgtcccctcacaaataaattaaagcgtaaaaggagacctacatcaggcctt
catcctgaggattttatcaagaaagcagatttggcagttnnncaaaagactcctgaaatg
ataaatcagggaactaaccaaacggagcagaatggtcaagtgatgaatattactaatagt
ggtcatgagaataaaacaaaaggtgattctattcagaatgagaaaaatcctaacccaata
gaatcactcgaaaaagaatctgctttcaaaacgaaagctgaacctataagcagcagtata
agcaatatggaactcgaattaaatatccacaattcaaaagcacctaaaaagaataggctg
aggaggaagtcttctaccaggcatattcatgcgcttgaactagtagtcagtagaaatcta
agcccacctaattgtactgaattgcaaattgatagttgttctagcagtgaagagataaag
aaaaaaaagtacaaccaaatgccagtcaggcacagcagaaacctacaactcatggaaggt
aaagaacctgcaactggagccaagaagagtaacaagccaaatgaacagacaagtaaaaga
catgacagcgatactttcccagagctgaagttaacaaatgcacctggttcttttactaag
tgttcaaataccagtgaacttaaagaatttgtcaatcctagccttccaagagaagaaaaa
gaagagaaannnctagaaacagttaaagtgtctaataatgctgaagaccccaaagatctc
atgttaagtggagaannnagggttttgcaaactgaaagatctgtagagagtagcagtatt
tcattggtacctggtactgattatggcactcaggaaagtatctcgttactggaagttagc
actctagggnnnaaggcaaaaacagaaccaaataaatgtgtgagtcagtgtgcagcattt
gaaaaccccaagggactaattcatggttgttccaaagataatagaaatgacacagaaggc
tttaagtatccattgggacatgaagttaaccacagtcgggaaacaagcatagaaatggaa
gaaagtgaacttgatgctcagtatttgcagaatacattcaaggtttcaaagcgccagtca
tttgctccgttttcaaatccaggaaatgcagaagaggaatgtgcaacattctctgcccac
tctgggtccttaaagaaacaaagtccaaaagtcacttttgaatgtgaacaaaaggaagaa
aatcaaggaaagaatgagtctaatatcaagcctgtacagacagttaatatcactgcaggc
tttcctgtggttggtcagaaagataagnnnccagttgataatgccaaatgtagtatcaaa
ggaggctctaggttttgtctatcatctcagttcagaggcaacgaaactggactcattact
ccaaataaacatggacttttacaaaacccatatcgtataccaccactttttcccatcaag
tcatttgttaaaactaaatgtaagaaaaatctgctagaggaaaactttgaggaacattca
atgtcacctgaaagagaaatgggaaatgagaacnnnattccaagtacagtgagcacaatt
agccgtaataacattagagaaaatgtttttaaagaagccagctcaagcaatattaatgaa
gtaggttccagtactaatgaagtgggctccagtattaatgaaataggttccagtnnnnnn
nnnnnnnnnnnnnnngatgaaaacattcaagcagaactaggtagaaacagagggccaaaa
ttgaatgctatgcttagattaggggttttgcaacctgaggtctataaacaaagtcttcct
ggaagtaattgtaagcatcctgaaataaaaaagcaagaatatgaagaannngtagttcag
actgttaatacagatttctctccatatctgatttcagataacttagaacagcctatggga
agtagtcatgcatctcaggtttgttctgagacacctgatgacctgttagatgatggtgaa
ataaaggaagatactagttttgctgaaaatgacattaaggaaagttctgctgtttttagc
aaaagcgtccagaaaggagagcttagcaggagtcctagccctttcacccatacacatttg
gctcagggttaccgaagaggggccaagaaattagagtcctcagaagagaacttatctagt
gag
>Mouse
tgtggcacagatgctcatgccagctcattacagcctgagaccagcagtttattgctcatt
gaagacagaatgaatgcagaaaaggctgaattctgtaataaaagcaaacagcctggcata
gcagtgagccagcagagcagatgggctgcaagtaaaggaacatgtaacgacaggcaggtt
cccagcactggggaaaaggtaggtccaaacgctgactcccttagtgatagagagaagtgg
actcacccgcaaagtctgtgccctgagaattctggagctnnnaccaccgatgttccttgg
ataacactaaatagcagcgttcagaaagttaatgagtggttttccagaactggtgaaatg
ttaacttctgacagcgcatctgccaggaggcacgagtcaaatgctgaagcagctgttgtg
ttggaagtttcaaacgaagtggatgggggttttagttcttcaaggaaaacagacttagta
acccccgacccccatcatactttaatgtgtaaaagtggaagagacttctccaaaccagta
gaggataatatcagtgataaaatatttgggaaatcctatcagagaaagggaagccgccct
cacctgaaccatgtgactgaaattataggcacannnnnntttattacagaaccacagata
acacaagagcagcccttcacaaataaattaaaacgtaagagannnnnnagtacatccctt
caacctgaggacttcatcaagaaagcagattcagcaggtgttcaaaggactcctgacaac
ataaatcagggaactgacctaatggagccaaatgagcaagcagtgagtactaccagtaac
tgtcaggagaacaaaatagcaggtagtaatctccagaaagagaaaagcgctcatccaact
gaatcattgagaaaggaacctgcttccacagcaggagccaaatctataagcaacagtgta
agtgatttggaggtagaattaaacgtccacagttcaaaagcacctaagaaaaataggctg
aggaggaagtcttctatcaggtgtgctcttccacttgaaccannnatcagtagaaatcca
agcccacctacttgtgctgagcttcaaatcgatagttgtggtagcagtgaagaaacaaag
aaaaaccattccaaccaacagccagccgggcaccttagagagcctcaactcatcgaagac
actgaacctgcagcggatgccaagaagaacgagnnnccaaatgaacacataaggaagaga
cgtgccagcgatgctttcccagaagagaaattaatgaacaaagctggtttattaactagc
tgttcaagtcctagaaaatctcaagggcctgtcaatcccagccctcagagaacaggaaca
gagcaannnnnncttgaaacacgccaaatgtctgacagtgccaaagaactcggggatcgg
gtcctaggaggagagcccagtggcaaaaccactgaccgatctgaggagagcaccagcgta
tccttggtacctgacactgactacgacactcagaacagtgtctcagtcctggacgctcac
actgtcagannntatgcaagaacaggatccgctcagtgtatgactcagtttgtagcaagc
gaaaaccccaaggaactcgtccatggctctaacaatgctgggnnnagtggcacagagggt
ctcaagccccccttgagacacgcgcttaacctcagtcaggagaaannngtagaaatggaa
gacagtgaacttgatactcagtatttgcagaatacatttcaagtttcaaagcgtcagtca
tttgctttattttcaaaacctagaagtccccaaaaggactgtnnnnnnnnnnnngctcac
tctgtgccctcaaaggaactgagtccaaaggtgacagctaaaggtaaacaaaaagaacgt
cagggacaggaagaatttgaaatcagtcacgtacaagcagttgcggccacagtgggcnnn
ttacctgtgccctgtcaagaaggtaagnnnctagctgctgatacaatgtgtnnnnnngat
agaggttgtaggctttgtccatcatctcattacagaagcggggagaatggactcagcgcc
acaggtaaatcaggaatttcacaaaactcacattttaaacaatcagtttctcccatcagg
tcatctataaaaactgacaataggaaacctctgacagagggacgatttgagagacataca
tcatcaactgagatggcggtgggaaatgagaacattcttcagagtacagtgcacacagtt
agcctgaataacnnnagaggaaatgctnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn
nnnnnnnnntgtcaagaagccggctcgggcagtattcatgaagtatgttccactnnnnnn
nnnnnnnnnnnnnnnggtgactccttcccaggacaactaggtagaaacagagggcctaag
gtgaacactgtgcctccattagatagtatgcagcctggtgtctgtcagcaaagtgttcct
gtaagtgatnnnaagtatcttgaaataaaaaagnnnnnnnnnnnnnnncaggagggtgag
gctgtctgtgcagacttctctccatgtctattctcagaccatcttgagcaatctatgagt
ggtnnnaaggtttttcaggtttgctctgagacacctgatgacctgctggatgatgttgaa
atacagggacatactagctttggtgaaggtgacataatggagagatctgctgtctttaac
ggaagcatcctgagaagggagtccagtaggagccctagtcctgtaacccatgcatcgaag
tctcagagtctccacagagcgtctaggaaattagaatcgtcagaagagagcgactccact
gag
>HowlerMon
tgtggcacaaatactcatgccagctcattacagcatgagaacagcagtttgttactcact
aaagacacactgaatgtagaaaaggctgaattctgtaataaaagcaaacagcctggctta
gcaaggagccaacataacagatgggctgaaagtgaggaaacatgtaatgataggcagact
cccagcacagagaaaaaggtagatgtggatgctgatcccctgcatgggagaaaagaatgg
aataagcagaaacctccgtgctctgagaatcctagagatgatactgaagatgttgcttgg
ataatgctaaatagcagcattcagaaagttaatgagtggttttccagaagtgatgaactg
ttaacttctgatgactcacatgatggggggtctgaatcaaatgccaaagtagctgaagca
ttggaagttctaaatgaggtagatggatattctagttcttcagagaaaatagacttactg
gccagtgatcctcatgatcatttgatatgtaaaagtgaaagagttcactgcaaatcagta
gagagtagtattgaagataaaatatttgggaaaacctatcggaggaaggcaagcctccct
aacttgagccacgtaactgaaaatctaattataggagcatttgttactgagccacagata
atacaagagcatcctctcacaaataaattaaagcgtaaaaggagagttacatcaggactt
catcctgaggattttatcaagaaagcagatttggcagttnnncaaaagactcctgaaaag
ataaatcagggaactaaccaaacagagcggaatgatcaagtgatgaatattactaacagt
ggtcatgagaataaaacaaaaggtgattctattcagaatgagaacaatcctaacccagta
gaatcactggaaaaagaannntcattcaaaagtaaagctgaacctataagcagtagtata
agcaatatggaattagaattgaatgtccacaattccaaagcatctaaaaagaataggctg
agaaggaagtcttctaccaggcatattcatgagcttgaactagtagtcagtagaaatcta
agcccacctaattatactgaagtacaaattgatagttgttctagcagtgaagagataaag
aaaaaaaattacaaccaaatgccagtcaggcacagcagaaagctacaactcatggaagat
aaagaacgtgcagctagagccaaaaagagtagcaagccaaatgaacaaacaagtaaaaga
catgccagtgatactttcccagaactgaggttaacaaacatacctggttcttttactaac
tgttcaaatactaatgaatttaaagaatttgtcaatcctagccttccaagagaacaaaca
gaagagaaannnctagaaacagttaaactgtctaataatgccaaagaccccaaagatctc
atgttaagtggagaannnagtgttttgcaaattgaaagatctgtagagagtagcagtatt
ttgttgatacctggtactgattatggcactcaggaaagtatctcattactggaagttagc
actctggggnnnaaggcaaaaacagaaccaaataaatgtgtgagtcagtgtgcagcattt
gaaaaccccaaggaactaattcatggttgttctaaagatactagaaatggcacagaaggc
ttgaagtatccattgggacctgaagttaactacagtcaggaaacaagcatagatatgaga
gaaagtgaacttgatactcaatatttgcagaatacattcaaggtttcaaagcgccagtca
tttgctctgttttcaaatccaggaaatccagaaaaggaatgtgcaacattctctgcctgc
tctaggtccttaaagaaacaaagtccaaaggtcactcctgaatgtgaacaaaaggaagaa
aatcaaggagagaaagagtctaatatcgagcttgtagagacagttaataccactgcaggc
tttcctatggtttgtcagaaagataagnnnccagttgattatgccagatgtatcgaannn
ggaggctctaggctttgtctatcatctcagttcagaggcaacgaaactggactcattatt
ccaaataaacatggacttttacagaacccatatcatatgtcaccgcttattcccaccagg
tcatttgttaaaactaaatgtaagaaaaacctgctagaagaaaactctgaggaacattca
atgtcacctgaaagagcaatgggaaacaagaacatcattccaagtacagtgagcacaatt
agccataataacnnnagagaaaatgcttttaaagaaaccagctcaagcagtatttatgaa
gtaggttccagtactaatgaagcaggttctagtactaatgaagtaggctccagtattaat
gaagtaggttccagtgatgaaaacattcaagcagagctaggtagaaacagaaggccaaaa
ttgaatgctatgcttagattagggcttctgcaacctgagatttgtaagcaaagtcttcct
ataagtgattgtaaacatcctgaaattaaaaagcaagaacatgaagaannngtagttcag
actgttaatacagacgtctctctatgtctgatttcatataacctagaacagcatatggga
agcagtcatacatctcaggtttgttctgagacacctgacaacctgttagatgatggtgaa
ataaaggaagatactagttttgctgaatatggcattaaggagacttctactgtttttagc
aaaagtgtccagagaggagagctcagcaggagccctagccctttcacccatacacatttg
gctcaggtttaccaaagaggggccaagaaattagagtcctcggaagagaatttatctagt
gag
PyCogent-1.5.3/tests/data/primates_brca1.tree 000644 000765 000024 00000000145 10665667404 022106 0 ustar 00jrideout staff 000000 000000 ((TreeShrew,FlyingLem),Mouse,(Galago,(HowlerMon,(Rhesus,(Orangutan,(Gorilla,(Human,Chimpanzee))))))); PyCogent-1.5.3/tests/data/test.psl 000644 000765 000024 00000001377 11533073176 020030 0 ustar 00jrideout staff 000000 000000 psLayout version 3
match mis- rep. N's Q gap Q gap T gap T gap strand Q Q Q Q T T T T block blockSizes qStarts tStarts
match match count bases count bases name size start end name size start end count
---------------------------------------------------------------------------------------------------------------------------------------------------------------
33 0 0 0 0 0 0 0 + q1 33 0 33 83 35 0 33 1 33, 0, 0,
32 0 0 0 0 0 0 0 + q1 33 0 32 314 35 0 32 1 32, 0, 0,
33 0 0 0 0 0 0 0 + q1 33 0 33 279 35 0 33 1 33, 0, 0,
33 0 0 0 0 0 0 0 + q1 33 0 33 260 35 0 33 1 33, 0, 0,
33 0 0 0 0 0 0 0 + q1 33 0 33 257 35 0 33 1 33, 0, 0,
33 0 0 0 0 0 0 0 - q2 33 0 33 501-Rev-Primer-Match 33 0 33 1 33, 0, 0,
PyCogent-1.5.3/tests/data/test.sff 000644 000765 000024 00000004250 11347461377 020010 0 ustar 00jrideout staff 000000 000000 .sff à Â ¸ TACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTCAG M 4 FA6P1OK01CGMHQ h e ` f f c d d d n l ’ X
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TCAGATCTGAGCTGGGTCATAGCTGCCTCCGTAGGAGGTGCCTCCCTACGGCGCNNNANNNNNGNNNNNNNNNNNNN !
.mft1.00 ž
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FA6P1OK
R_2008_05_28_17_11_38_FLX02070135_adminrig_KnightLauber
/data/2008_05_28/R_2008_05_28_17_11_38_FLX02070135_adminrig_KnightLauber/D_2008_05_28_21_13_06_FLX02070135_KnightLauber_FullAnalysisAmplicons
/data/2008_05_28/R_2008_05_28_17_11_38_FLX02070135_adminrig_KnightLauber/D_2008_05_28_21_13_06_FLX02070135_KnightLauber_FullAnalysisAmplicons/../D_2008_05_29_13_52_01_FLX02070135_Knight_Lauber_jones_SignalProcessingAmplicons
1.1.03
FA6P1OK01CGMHQ ¹ÿ PyCogent-1.5.3/misc/boring 000644 000765 000024 00000001167 10665667404 016421 0 ustar 00jrideout staff 000000 000000 # Boring file regexps for darcs:
\.hi$
\.o$
\.o\.cmd$
# *.ko files aren't boring by default because they might
# be Korean translations rather than kernel modules.
# \.ko$
\.ko\.cmd$
\.mod\.c$
(^|/)\.tmp_versions($|/)
(^|/)CVS($|/)
(^|/)RCS($|/)
~$
#(^|/)\.[^/]
(^|/)_darcs($|/)
\.bak$
\.BAK$
\.orig$
(^|/)vssver\.scc$
\.swp$
(^|/)MT($|/)
(^|/)\{arch\}($|/)
(^|/).arch-ids($|/)
(^|/),
\.class$
\.prof$
(^|/)\.DS_Store$
(^|/)BitKeeper($|/)
(^|/)ChangeSet($|/)
(^|/)\.svn($|/)
\.py[co]$
\#
\.cvsignore$
(^|/)Thumbs\.db$
#
# Cogent specific entries start here
#
^build($|/)
\.pdf$
\.so$
_.*.c$
^doc/examples/.*\.py$
doctest_.*\.py$
PyCogent-1.5.3/include/array_interface.h 000644 000765 000024 00000000632 12024702176 021174 0 ustar 00jrideout staff 000000 000000 #include "Python.h"
#define PYCOGENT_VERSION "1.5.3"
/* Array Interface flags */
#define CONTIGUOUS 0x001
#define FORTRAN 0x002
#define ALIGNED 0x100
#define NOTSWAPPED 0x200
#define WRITEABLE 0x400
typedef struct PyArrayInterface {
int version;
int nd;
char typekind;
int itemsize;
int flags;
Py_intptr_t *shape;
Py_intptr_t *strides;
void *data;
} PyArrayInterface;
PyCogent-1.5.3/include/numerical_pyrex.pyx 000644 000765 000024 00000011047 12024702176 021637 0 ustar 00jrideout staff 000000 000000 # Array checking functions for Pyrex code that takes NumPy arrays
#
# The idea here is that many array functions:
# - Need to know the dimensions of their array inputs.
# - Require some dimensions of different arrays to match.
# - Don't ever need to consider a dimension of length 0.
#
# eg: x = y = z = 0
# dataA = checkArrayDouble2D(A, &x, &y)
# dataB = checkArrayDouble2D(B, &z, &x) # x must match
#
__version__ = "('1', '5', '3')"
cdef extern from "Python.h":
void *PyCObject_AsVoidPtr(object)
cdef extern from "array_interface.h":
struct PyArrayInterface:
int version
int nd
char typekind
int itemsize
int flags
int *shape, *strides
void *data
int CONTIGUOUS
ctypedef object ArrayType
cdef double *uncheckedArrayDouble(ArrayType A):
cdef PyArrayInterface *a
cobj = A.__array_struct__
a = PyCObject_AsVoidPtr(cobj)
return a.data
cdef void *checkArray(ArrayType A, char typecode, int itemsize,
int nd, int **dims) except NULL:
cdef PyArrayInterface *a
cdef int length, size
cdef char kind
if A is None:
raise TypeError("Array required, got None")
cobj = A.__array_struct__
a = PyCObject_AsVoidPtr(cobj)
if a.version != 2:
raise ValueError(
"Unexpected array interface version %s" % str(a.version))
cdef char typecode2
typecode2 = a.typekind
if typecode2 != typecode:
raise TypeError("'%s' type array required, got '%s'" %
(chr(typecode), chr(typecode2)))
if a.itemsize != itemsize:
raise TypeError("'%s%s' type array required, got '%s%s'" %
(chr(typecode), itemsize, chr(typecode2), a.itemsize))
if a.nd != nd:
raise ValueError("%s dimensional array required, got %s" %
(nd, a.nd))
if not a.flags & CONTIGUOUS:
raise ValueError ('Noncontiguous array')
cdef int dimension, val
cdef int *var
for dimension from 0 <= dimension < nd:
val = a.shape[dimension]
var = dims[dimension]
if var[0] == 0:
# Length unspecified, take it from the provided array
var[0] = val
elif var[0] != val:
# Length already specified, but not the same
raise ValueError("Dimension %s is %s, expected %s" %
(dimension, val, var[0]))
else:
# Length matches what was expected
pass
return a.data
cdef void *checkArray1D(ArrayType a, char typecode, int size,
int *x) except NULL:
cdef int *dims[1]
dims[0] = x
return checkArray(a, typecode, size, 1, dims)
cdef void *checkArray2D(ArrayType a, char typecode, int size,
int *x, int *y) except NULL:
cdef int *dims[2]
dims[0] = x
dims[1] = y
return checkArray(a, typecode, size, 2, dims)
cdef void *checkArray3D(ArrayType a, char typecode, int size,
int *x, int *y, int *z) except NULL:
cdef int *dims[3]
dims[0] = x
dims[1] = y
dims[2] = z
return checkArray(a, typecode, size, 3, dims)
cdef void *checkArray4D(ArrayType a, char typecode, int size,
int *w, int *x, int *y, int *z) except NULL:
cdef int *dims[4]
dims[0] = w
dims[1] = x
dims[2] = y
dims[3] = z
return checkArray(a, typecode, size, 4, dims)
cdef double * checkArrayDouble1D(ArrayType a, int *x) except NULL:
return checkArray1D(a, c'f', sizeof(double), x)
cdef double * checkArrayDouble2D(ArrayType a, int *x, int *y) except NULL:
return checkArray2D(a, c'f', sizeof(double), x, y)
cdef double * checkArrayDouble3D(ArrayType a, int *x, int *y, int *z) except NULL:
return checkArray3D(a, c'f', sizeof(double), x, y, z)
cdef double * checkArrayDouble4D(ArrayType a, int *w, int *x, int *y, int *z) except NULL:
return checkArray4D(a, c'f', sizeof(double), w, x, y, z)
cdef long * checkArrayLong1D(ArrayType a, int *x) except NULL:
return checkArray1D(a, c'i', sizeof(long), x)
cdef long * checkArrayLong2D(ArrayType a, int *x, int *y) except NULL:
return checkArray2D(a, c'i', sizeof(long), x, y)
cdef long * checkArrayLong3D(ArrayType a, int *x, int *y, int *z) except NULL:
return checkArray3D(a, c'i', sizeof(long), x, y, z)
cdef long * checkArrayLong4D(ArrayType a, int *w, int *x, int *y, int *z) except NULL:
return checkArray4D(a, c'i', sizeof(long), w, x, y, z)
PyCogent-1.5.3/doc/_static/ 000755 000765 000024 00000000000 12024703636 016436 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/doc/ChangeLog.rst 000755 000765 000024 00000000000 12024703636 021347 2../ChangeLog ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/doc/coding_guidelines.rst 000644 000765 000024 00000062332 11305663627 021231 0 ustar 00jrideout staff 000000 000000 Coding guidelines
=================
As project size increases, consistency increases in importance. Unit testing and a consistent style are critical to having trusted code to integrate. Also, guesses about names and interfaces will be correct more often.
What should I call my variables?
--------------------------------
- *Choose the name that people will most likely guess.* Make it descriptive, but not too long: ``curr_record`` is better than ``c``, or ``curr``, or ``current_genbank_record_from_database``.
- *Good names are hard to find.* Don't be afraid to change names except when they are part of interfaces that other people are also using. It may take some time working with the code to come up with reasonable names for everything: if you have unit tests, it's easy to change them, especially with global search and replace.
- *Use singular names for individual things, plural names for collections.* For example, you'd expect ``self.Name`` to hold something like a single string, but ``self.Names`` to hold something that you could loop through like a list or dict. Sometimes the decision can be tricky: is ``self.Index`` an int holding a positon, or a dict holding records keyed by name for easy lookup? If you find yourself wondering these things, the name should probably be changed to avoid the problem: try ``self.Position`` or ``self.LookUp``.
- *Don't make the type part of the name.* You might want to change the implementation later. Use ``Records`` rather than ``RecordDict`` or ``RecordList``, etc. Don't use Hungarian Notation either (i.e. where you prefix the name with the type).
- *Make the name as precise as possible.* If the variable is the name of the input file, call it ``infile_name``, not ``input`` or ``file`` (which you shouldn't use anyway, since they're keywords), and not ``infile`` (because that looks like it should be a file object, not just its name).
- *Use* ``result`` *to store the value that will be returned from a method or function.* Use ``data`` for input in cases where the function or method acts on arbitrary data (e.g. sequence data, or a list of numbers, etc.) unless a more descriptive name is appropriate.
- *One-letter variable names should only occur in math functions or as loop iterators with limited scope.* Limited scope covers things like ``for k in keys: print k``, where ``k`` survives only a line or two. Loop iterators should refer to the variable that they're looping through: ``for k in keys, i in items``, or ``for key in keys, item in items``. If the loop is long or there are several 1-letter variables active in the same scope, rename them.
- *Limit your use of abbreviations.* A few well-known abbreviations are OK, but you don't want to come back to your code in 6 months and have to figure out what ``sptxck2`` is. It's worth it to spend the extra time typing ``species_taxon_check_2``, but that's still a horrible name: what's check number 1? Far better to go with something like ``taxon_is_species_rank`` that needs no explanation, especially if the variable is only used once or twice.
Acceptable abbreviations
^^^^^^^^^^^^^^^^^^^^^^^^
The following list of abbreviations can be considered well-known and used with impunity within mixed name variables, but some should not be used by themselves as they would conflict with common functions, python built-in's, or raise an exception. Do not use the following by themselves as variable names: ``dir``, ``exp`` (a common ``math`` module function), ``in``, ``max``, and ``min``. They can, however, be used as part of a name, eg ``matrix_exp``.
+--------------------+--------------+
| Full | Abbreviated |
+====================+==============+
| alignment | aln |
+--------------------+--------------+
| archaeal | arch |
+--------------------+--------------+
| auxillary | aux |
+--------------------+--------------+
| bacterial | bact |
+--------------------+--------------+
| citation | cite |
+--------------------+--------------+
| current | curr |
+--------------------+--------------+
| database | db |
+--------------------+--------------+
| dictionary | dict |
+--------------------+--------------+
| directory | dir |
+--------------------+--------------+
| end of file | eof |
+--------------------+--------------+
| eukaryotic | euk |
+--------------------+--------------+
| frequency | freq |
+--------------------+--------------+
| expected | exp |
+--------------------+--------------+
| index | idx |
+--------------------+--------------+
| input | in |
+--------------------+--------------+
| maximum | max |
+--------------------+--------------+
| minimum | min |
+--------------------+--------------+
| mitochondrial | mt |
+--------------------+--------------+
| number | num |
+--------------------+--------------+
| observed | obs |
+--------------------+--------------+
| original | orig |
+--------------------+--------------+
| output | out |
+--------------------+--------------+
| parameter | param |
+--------------------+--------------+
| phylogeny | phylo |
+--------------------+--------------+
| previous | prev |
+--------------------+--------------+
| probability | prob |
+--------------------+--------------+
| protein | prot |
+--------------------+--------------+
| record | rec |
+--------------------+--------------+
| reference | ref |
+--------------------+--------------+
| sequence | seq |
+--------------------+--------------+
| standard deviation | stdev |
+--------------------+--------------+
| statistics | stats |
+--------------------+--------------+
| string | str |
+--------------------+--------------+
| structure | struct |
+--------------------+--------------+
| temporary | temp |
+--------------------+--------------+
| taxonomic | tax |
+--------------------+--------------+
| variance | var |
+--------------------+--------------+
What are the naming conventions?
--------------------------------
.. tabularcolumns:: |p{3.4cm}|p{6cm}|p{5cm}|
.. csv-table::
:header: Type , Convention , Example
function , ``verb_with_underscores`` , ``find_all``
variable , ``noun_with_underscores`` , ``curr_index``
constant , ``NOUN_ALL_CAPS`` , ``ALLOWED_RNA_PAIRS``
class , ``MixedCaseNoun`` , ``RnaSequence``
public property , ``MixedCaseNoun`` , ``IsPaired``
private property , ``_noun_with_leading_underscore`` , ``_is_updated``
public method , ``mixedCaseExceptFirstWordVerb`` , ``stripDegenerate``
private method , ``_verb_with_leading_underscore`` , ``_check_if_paired``
really private data , ``__two_leading_underscores`` , ``__delegator_object_ref``
parameters that match properties , ``SameAsProperty`` , "``def __init__(data, Alphabet=None)``"
factory function , ``MixedCase`` , ``InverseDict``
module , ``lowercase_with_underscores`` , ``unit_test``
global variables , ``gMixedCaseWithLeadingG`` , no examples - should be rare!
- *It is important to follow the naming conventions because they make it much easier to guess what a name refers to*. In particular, it should be easy to guess what scope a name is defined in, what it refers to, whether it's OK to change its value, and whether its referent is callable. The following rules provide these distinctions.
- ``lowercase_with_underscores`` *for modules and internal variables (including function/method parameters).*
- ``MixedCase`` for *classes* and *public properties*, and for *factory functions* that act like additional constructors for a class.
- ``mixedCaseExceptFirstWord`` for *public methods and functions*.
- ``_lowercase_with_leading_underscore`` for *private* functions, methods, and properties.
- ``__lowercase_with_two_leading_underscores`` for *private* properties and functions that *must not be overwritten* by a subclass.
- ``CAPS_WITH_UNDERSCORES`` for named *constants*.
- ``gMixedCase`` (i.e. mixed case prefixed with 'g') for *globals*. Globals should be used extremely rarely and with caution, even if you sneak them in using the Singleton pattern or some similar system.
- *Underscores can be left out if the words read OK run together.* ``infile`` and ``outfile`` rather than ``in_file`` and ``out_file``; ``infile_name`` and ``outfile_name`` rather than ``in_file_name`` and ``out_file_name`` or ``infilename`` and ``outfilename`` (getting too long to read effortlessly).
How do I organize my modules (source files)?
--------------------------------------------
- *Have a docstring with a description of the module's functions*. If the description is long, the first line should be a short summary that makes sense on its own, separated from the rest by a newline.
- *All code, including import statements, should follow the docstring.* Otherwise, the docstring will not be recognized by the interpreter, and you will not have access to it in interactive sessions (i.e. through ``obj.__doc__``) or when generating documentation with automated tools.
- *Import built-in modules first, followed by third-party modules, followed by any changes to the path and your own modules.* Especially, additions to the path and names of your modules are likely to change rapidly: keeping them in one place makes them easier to find.
- *Don't use* ``from module import *``, *instead use* ``from module import Name, Name2, Name3...`` *or possibly* ``import module``. This makes it *much* easier to see name collisions and to replace implementations.
Example of module structure
^^^^^^^^^^^^^^^^^^^^^^^^^^^
::
#!/usr/bin/env python
"""Provides NumberList and FrequencyDistribution, classes for statistics.
NumberList holds a sequence of numbers, and defines several statistical
operations (mean, stdev, etc.) FrequencyDistribution holds a mapping from
items (not necessarily numbers) to counts, and defines operations such as
Shannon entropy and frequency normalization.
"""
from math import sqrt, log, e
from random import choice, random
from Utils import indices
class NumberList(list):
pass # much code deleted
class FrequencyDistribution(dict):
pass # much code deleted
# use the following when the module can meaningfully be called as a script.
if __name__ == '__main__': # code to execute if called from command-line
pass # do nothing - code deleted
How should I write comments?
----------------------------
- *Always update the comments when the code changes.* Incorrect comments are far worse than no comments, since they are actively misleading.
- *Comments should say more than the code itself.* Examine your comments carefully: they may indicate that you'd be better off rewriting your code (especially, *renaming your variables* and getting rid of the comment.) In particular, don't scatter magic numbers and other constants that have to be explained through your code. It's far better to use variables whose names are self-documenting, especially if you use the same constant more than once. Also, think about making constants into class or instance data, since it's all too common for 'constants' to need to change or to be needed in several methods.
+-------+------------------------------------------------------------+
| Wrong | ``win_size -= 20 # decrement win_size by 20`` |
+-------+------------------------------------------------------------+
| OK | ``win_size -= 20 # leave space for the scroll bar`` |
+-------+------------------------------------------------------------+
| Right | ``self._scroll_bar_size = 20`` |
+-------+------------------------------------------------------------+
| | ``win_size -= self._scroll_bar_size`` |
+-------+------------------------------------------------------------+
- *Use comments starting with #, not strings, inside blocks of code.* Python ignores real comments, but must allocate storage for strings (which can be a performance disaster inside an inner loop).
- *Start each method, class and function with a docstring using triple double quotes (""").* The docstring should start with a 1-line description that makes sense by itself (many automated formatting tools, and the IDE, use this). This should be followed by a blank line, followed by descriptions of the parameters (if any). Finally, add any more detailed information, such as a longer description, notes about the algorithm, detailed notes about the parameters, etc. If there is a usage example, it should appear at the end. Make sure any descriptions of parameters have the correct spelling, case, etc. For example: ::
def __init__(self, data, name='', alphabet=None):
"""Returns new Sequence object with specified data, name, alphabet.
Arguments:
- data: The sequence data. Should be a sequence of characters.
- name: Arbitrary label for the sequence. Should be string-like.
- alphabet: Set of allowed characters. Should support 'for x in y'
syntax. None by default.
Note: if alphabet is None, performs no validation.
"""
- *Always update the docstring when the code changes.* Like outdated comments, outdated docstrings can waste a lot of time. "Correct examples are priceless, but incorrect examples are worse than worthless." `Jim Fulton`_.
How should I format my code?
----------------------------
- *Use 4 spaces for indentation.* Do not use tabs (set your editor to convert tabs to spaces). The behaviour of tabs is not predictable across platforms, and will cause syntax errors. If we all use the same indentation, collaboration is much easier.
- *Lines should not be longer than 79 characters.* Long lines are inconvenient in some editors. Use \\ for line continuation. Note that there cannot be whitespace after the \\.
- *Blank lines should be used to highlight class and method definitions.* Separate class definitions by two blank lines. Separate methods by one blank line.
- *Be consistent with the use of whitespace around operators.* Inconsistent whitespace makes it harder to see at a glance what is grouped together.
+------+--------------------------+
| Good | ``((a+b)*(c+d))`` |
+------+--------------------------+
| OK | ``((a + b) * (c + d))`` |
+------+--------------------------+
| Bad | ``( (a+ b) *(c +d ))`` |
+------+--------------------------+
- *Don't put whitespace after delimiters or inside slicing delimiters.* Whitespace here makes it harder to see what's associated.
+------+-------------+------------------+
| Good | ``(a+b)`` | ``d[k]`` |
+------+-------------+------------------+
| Bad | ``( a+b )`` | ``d [k], d[ k]`` |
+------+-------------+------------------+
How should I test my code ?
---------------------------
There are two basic approaches for testing code in python: unit testing and doc testing. Their purpose is the same, to check that execution of code given some input produces a specified output. The cases to which the two approaches lend themselves are different.
An excellent discourse on testing code and the pros and cons of these alternatives is provided in a presentation by `Jim Fulton`_, which is recommended reading. A significant change since that presentation is that ``doctest`` can now read content that is not contained within docstrings. A another comparison of these two approaches, along with a third (``py.test``) is also available_. To see examples of both styles of testing look in ``PyCogent/tests``: files ending in .rst are using ``doctest``, those ending in .py are using ``unittest``.
.. _`Jim Fulton`: http://www.python.org/pycon/dc2004/papers/4/PyCon2004DocTestUnit.pdf
.. _available: http://agiletesting.blogspot.com/2005/11/articles-and-tutorials-page-updated.html
In general, it's easier to start writing ``doctest``'s, as you don't need to learn the ``unittest`` API but the latter give's much greater control.
Whatever approach is employed, the general principle is every line of code should be tested. It is critical that your code be fully tested before you draw conclusions from results it produces. For scientific work, bugs don't just mean unhappy users who you'll never actually meet: they may mean retracted publications.
Tests are an opportunity to invent the interface(s) you want. Write the test for a method before you write the method: often, this helps you figure out what you would want to call it and what parameters it should take. It's OK to write the tests a few methods at a time, and to change them as your ideas about the interface change. However, you shouldn't change them once you've told other people what the interface is.
Never treat prototypes as production code. It's fine to write prototype code without tests to try things out, but when you've figured out the algorithm and interfaces you must rewrite it *with tests* to consider it finished. Often, this helps you decide what interfaces and functionality you actually need and what you can get rid of.
"Code a little test a little". For production code, write a couple of tests, then a couple of methods, then a couple more tests, then a couple more methods, then maybe change some of the names or generalize some of the functionality. If you have a huge amount of code where 'all you have to do is write the tests', you're probably closer to 30% done than 90%. Testing vastly reduces the time spent debugging, since whatever went wrong has to be in the code you wrote since the last test suite. And remember to use python's interactive interpreter for quick checks of syntax and ideas.
Run the test suite when you change `anything`. Even if a change seems trivial, it will only take a couple of seconds to run the tests and then you'll be sure. This can eliminate long and frustrating debugging sessions where the change turned out to have been made long ago, but didn't seem significant at the time.
Some ``unittest`` pointers
^^^^^^^^^^^^^^^^^^^^^^^^^^
- *Use the* ``unittest`` *framework with tests in a separate file for each module.* Name the test file ``test_module_name.py``. Keeping the tests separate from the code reduces the temptation to change the tests when the code doesn't work, and makes it easy to verify that a completely new implementation presents the same interface (behaves the same) as the old.
- *Use* ``evo.unit_test`` *if you are doing anything with floating point numbers or permutations* (use ``assertFloatEqual``). Do *not* try to compare floating point numbers using ``assertEqual`` if you value your sanity. ``assertFloatEqualAbs`` and ``assertFloatEqualRel`` can specifically test for absolute and relative differences if the default behavior is not giving you what you want. Similarly, ``assertEqualItems``, ``assertSameItems``, etc. can be useful when testing permutations.
- *Test the interface of each class in your code by defining at least one* ``TestCase`` *with the name* ``ClassNameTests``. This should contain tests for everything in the public interface.
- *If the class is complicated, you may want to define additional tests with names* ``ClassNameTests_test_type``. These might subclass ``ClassNameTests`` in order to share ``setUp`` methods, etc.
- *Tests of private methods should be in a separate* ``TestCase`` *called* ``ClassNameTests_private``. Private methods may change if you change the implementation. It is not required that test cases for private methods pass when you change things (that's why they're private, after all), though it is often useful to have these tests for debugging.
- *Test `all` the methods in your class.* You should assume that any method you haven't tested has bugs. The convention for naming tests is ``test_method_name``. Any leading and trailing underscores on the method name can be ignored for the purposes of the test; however, *all tests must start with the literal substring* ``test`` *for* ``unittest`` *to find them.* If the method is particularly complex, or has several discretely different cases you need to check, use ``test_method_name_suffix``, e.g. ``test_init_empty``, ``test_init_single``, ``test_init_wrong_type``, etc. for testing ``__init__``.
- *Write good docstrings for all your test methods.* When you run the test with the ``-v`` command-line switch for verbose output, the docstring for each test will be printed along with ``...OK`` or ``...FAILED`` on a single line. It is thus important that your docstring is short and descriptive, and makes sense in this context.
**Good docstrings:** ::
NumberList.var should raise ValueError on empty or 1-item list
NumberList.var should match values from R if list has >2 items
NumberList.__init__ should raise error on values that fail float()
FrequencyDistribution.var should match corresponding NumberList var
**Bad docstrings:** ::
var should calculate variance # lacks class name, not descriptive
Check initialization of a NumberList # doesn't say what's expected
Tests of the NumberList initialization. # ditto
- *Module-level functions should be tested in their own* ``TestCase``\ *, called* ``modulenameTests``. Even if these functions are simple, it's important to check that they work as advertised.
- *It is much more important to test several small cases that you can check by hand than a single large case that requires a calculator.* Don't trust spreadsheets for numerical calculations -- use R instead!
- *Make sure you test all the edge cases: what happens when the input is None, or '', or 0, or negative?* What happens at values that cause a conditional to go one way or the other? Does incorrect input raise the right exceptions? Can your code accept subclasses or superclasses of the types it expects? What happens with very large input?
- *To test permutations, check that the original and shuffled version are different, but that the sorted original and sorted shuffled version are the same.* Make sure that you get *different* permutations on repeated runs and when starting from different points.
- *To test random choices, figure out how many of each choice you expect in a large sample (say, 1000 or a million) using the binomial distribution or its normal approximation.* Run the test several times and check that you're within, say, 3 standard deviations of the mean.
Example of a ``unittest`` test module structure
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
::
#!/usr/bin/env python
"""Tests NumberList and FrequencyDistribution, classes for statistics."""
from cogent.util.unit_test import TestCase, main # for floating point test use unittestfp
from statistics import NumberList, FrequencyDistribution
class NumberListTests(TestCase): # remember to subclass TestCase
"""Tests of the NumberList class."""
def setUp(self):
"""Define a few standard NumberLists."""
self.Null = NumberList() # test empty init
self.Empty = NumberList([]) # test init with empty sequence
self.Single = NumberList([5]) # single item
self.Zero = NumberList([0]) # single, False item
self.Three = NumberList([1,2,3]) # multiple items
self.ZeroMean = NumberList([1,-1]) # items nonzero, mean zero
self.ZeroVar = NumberList([1,1,1]) # items nonzero, mean nonzero, variance zero
# etc. These objects shared by all tests, and created new each time a method
# starting with the string 'test' is called (i.e. the same object does not
# persist between tests: rather, you get separate copies).
def test_mean_empty(self):
"""NumberList.mean() should raise ValueError on empty object"""
for empty in (self.Null, self.Empty):
self.assertRaises(ValueError, empty.mean)
def test_mean_single(self):
"""NumberList.mean() should return item if only 1 item in list"""
for single in (self.Single, self.Zero):
self.assertEqual(single.mean(), single[0])
# other tests of mean
def test_var_failures(self):
"""NumberList.var() should raise ZeroDivisionError if <2 items"""
for small in (self.Null, self.Empty, self.Single, self.Zero):
self.assertRaises(ZeroDivisionError, small.var)
# other tests of var
# tests of other methods
class FrequencyDistributionTests(TestCase):
pass # much code deleted
# tests of other classes
if __name__ == '__main__': # run tests if called from command-line
main()
PyCogent-1.5.3/doc/COGENT_LICENSE.rst 000644 000765 000024 00000045504 11204372323 017665 0 ustar 00jrideout staff 000000 000000 .. _cogent_license:
PyCogent License
================
::
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FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN
OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED
OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS
TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE
PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING,
REPAIR OR CORRECTION.
12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED
TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER
PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
POSSIBILITY OF SUCH DAMAGES.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
convey the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
Copyright 2007-2009 (C)
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
Also add information on how to contact you by electronic and paper mail.
If the program is interactive, make it output a short notice like this
when it starts in an interactive mode:
Gnomovision version 69, Copyright 2007-2009 (C) year name of author
Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, the commands you use may
be called something other than `show w' and `show c'; they could even be
mouse-clicks or menu items--whatever suits your program.
You should also get your employer (if you work as a programmer) or your
school, if any, to sign a "copyright disclaimer" for the program, if
necessary. Here is a sample; alter the names:
Yoyodyne, Inc., hereby disclaims all copyright interest in the program
`Gnomovision' (which makes passes at compilers) written by James Hacker.
, 1 April 1989
Ty Coon, President of Vice
This General Public License does not permit incorporating your program into
proprietary programs. If your program is a subroutine library, you may
consider it more useful to permit linking proprietary applications with the
library. If this is what you want to do, use the GNU Library General
Public License instead of this License.
PyCogent-1.5.3/doc/conf.py 000644 000765 000024 00000014721 12024702176 016312 0 ustar 00jrideout staff 000000 000000 # -*- coding: utf-8 -*-
#
# PyCogent documentation build configuration file, created by
# sphinx-quickstart on Wed May 13 12:28:51 2009.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import sys, os
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#sys.path.append(os.path.abspath('.'))
# -- General configuration -----------------------------------------------------
# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = ['sphinx.ext.todo', 'sphinx.ext.doctest', 'sphinx.ext.pngmath']
# todo_include_todos=True # to expose the TODOs, uncomment this line
# Add any paths that contain templates here, relative to this directory.
templates_path = ['templates']
# The suffix of source filenames.
source_suffix = '.rst'
# ignore the cookbook/ensembl.rst file as it's specifically imported
exclude_patterns = ['cookbook/ensembl.rst']
# The encoding of source files.
#source_encoding = 'utf-8'
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = u'PyCogent'
copyright = u'2009, PyCogent Team'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = "1.5"
# The full version, including alpha/beta/rc tags.
release = "1.5.3"
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = '%B %d, %Y'
# List of documents that shouldn't be included in the build.
#unused_docs = []
# List of directories, relative to source directory, that shouldn't be searched
# for source files.
exclude_trees = ['_build']
#exclude_trees = ['_build', 'cookbook'] # comment out after release
# The reST default role (used for this markup: `text`) to use for all documents.
#default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
#add_function_parentheses = True
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
#add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
show_authors = True
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# -- Options for HTML output ---------------------------------------------------
# The theme to use for HTML and HTML Help pages. Major themes that come with
# Sphinx are currently 'default' and 'sphinxdoc'.
html_theme = 'default'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
#html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
#html_theme_path = []
# The name for this set of Sphinx documents. If None, it defaults to
# " v documentation".
#html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
#html_short_title = None
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
#html_logo = None
# The name of an image file (within the carry path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
#html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
#html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
#html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
#html_additional_pages = {}
# If false, no module index is generated.
#html_use_modindex = True
# If false, no index is generated.
#html_use_index = True
# If true, the index is split into individual pages for each letter.
#html_split_index = False
# If true, links to the reST sources are added to the pages.
#html_show_sourcelink = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a `
:download:`abglobin_aa.phylip `
:download:`dists_for_phylo.pickle `
:download:`long_testseqs.fasta `
:download:`motif_example.fasta `
:download:`motif_example_meme_results.txt `
:download:`primate_brca1.fasta `
:download:`primate_brca1.tree `
:download:`primate_cdx2_promoter.fasta `
:download:`test.paml `
:download:`test.tree `
:download:`test2.fasta `
:download:`trna_profile.fasta `
:download:`refseqs.fasta `
:download:`refseqs_protein.fasta `
:download:`inseqs.fasta `
:download:`inseqs_protein.fasta `
PyCogent-1.5.3/doc/developer_notes.rst 000644 000765 000024 00000013563 12014704335 020743 0 ustar 00jrideout staff 000000 000000 For Developers
==============
Anyone can contribute to the development of PyCogent, not just registered developers. If you figure out a solution to something using PyCogent that you'd like to share please post comments on the forums_ page at sourceforge and we'll look at including your tips! If you have ideas for improving the current documentation, then we want to hear from you so please post on the tracker_ page!
.. _forums: http://sourceforge.net/forum/?group_id=186234
.. _tracker: http://sourceforge.net/tracker2/?group_id=186234
Grabbing from the subversion repository
---------------------------------------
To grab PyCogent from the sourceforge subversion repository, do the following::
$ svn co https://pycogent.svn.sourceforge.net/svnroot/pycogent/trunk PyCogent
Building/testing the documentation
----------------------------------
To build the documentation or ``doctest`` the contents, you'll need to install Sphinx. Assuming you have ``easy_install`` configured on your machine (and if not, download ``setuptools`` from http://pypi.python.org/pypi/setuptools and follow the instructions). Then grab Sphinx::
$ sudo easy_install -U sphinx
Generating the html form of the documentation requires changing into the ``doc`` directory and executing a ``make`` command::
$ cd path/to/PyCogent/doc
$ make html
... # bunch of output
Build finished. The HTML pages are in _build/html.
This prints a bunch of output to screen and creates a directory ``PyCogent/doc/_build`` and within that ``html``. The index file ``PyCogent/doc/_build/html/index.html`` is the root of the documentation.
One can also generate a pdf file, using the Sphinx latex generation capacity. This is slightly more involved. (It also requires that you have an installation of TeTex_.)
.. _TeTex: http://www.tug.org/texlive/
First generate the latex ::
$ make latex
... # bunch of output
Build finished; the LaTeX files are in _build/latex.
Run `make all-pdf' or `make all-ps' in that directory to run these through (pdf)latex.
then change into the ``latex`` dir and build the pdf ::
$ cd _build/latex
$ make all-pdf
You can now open ``PyCogent.pdf``.
To actually test the documentation, you need to be in the ``doc`` directory and then execute another ``make`` command::
$ cd path/to/PyCogent/doc
$ make doctest
The results are in ``_build/doctest/output.txt``.
.. note:: The documentation does not test for presence of 3rd party dependencies (such as applications or python modules) like the PyCogent ``unittest`` test suite. If you don't have all the 3rd party applications installed you will see failures. At this point **no effort** is being expended to hide such failures.
Adding to the documentation
---------------------------
You can maximise the cogent user experience for yourself and others by contributing to the documentation. If you solve a problem that you think might prove useful to others then add it into the documentation. If you can think of ways to improve the existing documents let us know.
For guidance on adding documentation, look at any of the existing examples. The restructured text format is pretty easy to write (for overview see the Sphinx `rest overview`_). The conventions adopted by PyCogent are to use heading levels to be consistent with the Python.org standard (taken from `Sphinx headings`_). They are
- # with overline, for parts
- \* with overline, for chapters
- =, for sections
- -, for subsections
- ^, for subsubsections
- ", for paragraphs
- +, added for sub-paragraphs (non-standard)
If it's a use-case, create your file in the ``examples`` directory, giving it a ``.rst`` suffix. Link it into the documentation tree, adding a line into the ``examples/index.rst`` file. If it's something you think should be added into the cookbook, add it into the appropriate cookbook document.
The new documentation checklist
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Things you should check before committing your new document:
- Add a line at the beginning with yourself as author (``.. sectionauthor:: My Name``) so people can contact you with feedback.
- Add any data files used in your documentation under ``PyCogent/doc/data/``
- Add a download link to those files to ``PyCogent/doc/data_file_links.rst`` following the style employed in that file.
- Spellcheck!!
- Check what you wrote is valid restructured text by building the documents for both html and latex. If your document isn't connected into the table of contents, Sphinx will print a warning to screen.
- Check you have correctly marked up the content and that it looks OK. Make sure that python code and shell commands are correctly highlighted and that literals are marked up as literals. In particular, check the latex build since it is common for text to span beyond the page margins. If the latter happens, revise your document!
- Check that it works (rather than testing the entire suite, you can use the convenience script within doc). For instance, the following is a single test of one file::
$ cd path/to/PyCogent/doc
$ python doctest_rsts.py examples/reverse_complement.rst
Adding TODOs
^^^^^^^^^^^^
Add todo's into the rst files using the ``todo`` directive as in
::
.. todo::
some task
To see the list of todo's in the project, uncomment the line that sets ``todo_include_todos=True`` in ``doc/conf.py``, then cd into the ``doc/`` and make the html docs again. The todo's are listed on the main page.
.. warning:: Be sure to revert the conf.py file back to it's original state so you don't accidentally commit the change as this affects everyone else's documentation too!
Developing C-extensions
-----------------------
Extensions for PyCogent should be written in `Cython `_.
******
Search
******
* :ref:`search`
.. _`Nature 2009 457:480-4`: http://www.ncbi.nlm.nih.gov/pubmed/19043404?ordinalpos=6&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum
.. _`PNAS 2008 105:17994-9`: http://www.ncbi.nlm.nih.gov/pubmed/19004758?ordinalpos=7&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum
.. _`Science 2008 320:1647-51`: http://www.ncbi.nlm.nih.gov/pubmed/18497261?ordinalpos=12&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum
.. _`Nature 2008 453: 175-83`: http://www.ncbi.nlm.nih.gov/pubmed/18464734?dopt=Citation
.. _`Nat Genet 2007 39: 1261-5`: http://www.ncbi.nlm.nih.gov/pubmed/17828264?dopt=Citation
**********************
News and Announcements
**********************
PyCogent News and Annoucements are available via the News and Announcements Blog at http://pycogent.wordpress.com.
`Subscribe to the News and Annoucements RSS Feed `_
PyCogent-1.5.3/doc/install.rst 000644 000765 000024 00000007714 12024703343 017214 0 ustar 00jrideout staff 000000 000000 .. _quick-install:
Quick installation
==================
PyCogent.app for OSX 10.6
-------------------------
`Download PyCogent.app `_.
Please, note that this is the only installation method supported for Windows and that natively Windows does not support gz files properly so to uncompress a gz file in Windows use `7-zip `_ to your hard drive and replace the first line of the :download:`requirements file <../cogent-requirements.txt>` with the full path to the tarball, e.g. ``/Users/my_user_name/Downloads/cogent-1.5.3.tgz``.
Optional installs
^^^^^^^^^^^^^^^^^
To use the Ensembl querying code
""""""""""""""""""""""""""""""""
Add the following lines to the requirements file ::
MySQL-python>=1.2.2
SQLAlchemy>=0.5
.. note:: The MySQL-python module requires that you have MySQL installed.
To use the parallel capabilities
""""""""""""""""""""""""""""""""
Add the following to the requirements file ::
mpi4py>=1.0
To build the documentation
""""""""""""""""""""""""""
Add the following to the requirements file ::
Sphinx>=0.6
To use the development version of PyCogent
""""""""""""""""""""""""""""""""""""""""""
Just replace the first line of the requirements file with ``https://pycogent.svn.sourceforge.net/svnroot/pycogent/trunk``.
To use the graphics capabilities
""""""""""""""""""""""""""""""""
You need to install matplotlib_ (version 1.1.0+) to use the drawing code. However, compiling matplotlib can be a challenge. We therefore suggest you obtain a prebuilt binary for your platform from the matplotlib_ project page rather than modify the requirements file. For OSX, we suggest reading the following instructions on `compiling matplotlib`_.
.. _pip: http://pypi.python.org/pypi/pip
.. _matplotlib: http://matplotlib.sourceforge.net/
.. _`compiling matplotlib`: http://sourceforge.net/projects/pycogent/forums/forum/651121/topic/5635916
.. todo::
**FOR RELEASE:** update the tarball name for the version.
Installing ``easy_install``
---------------------------
If your system doesn't have ``easy_install``, you can execute the following::
$ sudo curl http://peak.telecommunity.com/dist/ez_setup.py | python
or, if you are on a linux system that has a package manager, you may only need to do something like::
$ sudo apt-get install python-setuptools
Use the approach to getting ``easy_install`` that best suites your system, then follow the (above) instructions for the ``pip`` based installation.
PyCogent-1.5.3/doc/licenses.rst 000644 000765 000024 00000001633 11523377514 017357 0 ustar 00jrideout staff 000000 000000 Licenses and disclaimer
=======================
.. toctree::
:maxdepth: 1
:hidden:
COGENT_LICENSE
PyCogent is released under the GPL license, a copy of which is included in the distribution (see :ref:`cogent_license`). Licenses for other code sources are left in place.
This software is provided "as-is". There are no expressed or implied warranties of any kind, including, but not limited to, the warranties of merchantability and fitness for a given application. In no event shall the authors be liable for any direct, indirect, incidental, special, exemplary or consequential damages (including, but not limited to, loss of use, data or profits, or business interruption) however caused and on any theory of liability, whether in contract, strict liability or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.
PyCogent-1.5.3/doc/Makefile 000644 000765 000024 00000005665 11204372323 016456 0 ustar 00jrideout staff 000000 000000 # Makefile for Sphinx documentation
#
# You can set these variables from the command line.
SPHINXOPTS =
SPHINXBUILD = sphinx-build
PAPER =
# Internal variables.
PAPEROPT_a4 = -D latex_paper_size=a4
PAPEROPT_letter = -D latex_paper_size=letter
ALLSPHINXOPTS = -d _build/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) .
.PHONY: help clean html dirhtml pickle json htmlhelp qthelp latex changes linkcheck doctest
help:
@echo "Please use \`make ' where is one of"
@echo " html to make standalone HTML files"
@echo " dirhtml to make HTML files named index.html in directories"
@echo " pickle to make pickle files"
@echo " json to make JSON files"
@echo " htmlhelp to make HTML files and a HTML help project"
@echo " qthelp to make HTML files and a qthelp project"
@echo " latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter"
@echo " changes to make an overview of all changed/added/deprecated items"
@echo " linkcheck to check all external links for integrity"
@echo " doctest to run all doctests embedded in the documentation (if enabled)"
clean:
-rm -rf _build/*
html:
$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) _build/html
@echo
@echo "Build finished. The HTML pages are in _build/html."
dirhtml:
$(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) _build/dirhtml
@echo
@echo "Build finished. The HTML pages are in _build/dirhtml."
pickle:
$(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) _build/pickle
@echo
@echo "Build finished; now you can process the pickle files."
json:
$(SPHINXBUILD) -b json $(ALLSPHINXOPTS) _build/json
@echo
@echo "Build finished; now you can process the JSON files."
htmlhelp:
$(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) _build/htmlhelp
@echo
@echo "Build finished; now you can run HTML Help Workshop with the" \
".hhp project file in _build/htmlhelp."
qthelp:
$(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) _build/qthelp
@echo
@echo "Build finished; now you can run "qcollectiongenerator" with the" \
".qhcp project file in _build/qthelp, like this:"
@echo "# qcollectiongenerator _build/qthelp/PyCogent.qhcp"
@echo "To view the help file:"
@echo "# assistant -collectionFile _build/qthelp/PyCogent.qhc"
latex:
$(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) _build/latex
@echo
@echo "Build finished; the LaTeX files are in _build/latex."
@echo "Run \`make all-pdf' or \`make all-ps' in that directory to" \
"run these through (pdf)latex."
changes:
$(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) _build/changes
@echo
@echo "The overview file is in _build/changes."
linkcheck:
$(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) _build/linkcheck
@echo
@echo "Link check complete; look for any errors in the above output " \
"or in _build/linkcheck/output.txt."
doctest:
$(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) _build/doctest
@echo "Testing of doctests in the sources finished, look at the " \
"results in _build/doctest/output.txt."
PyCogent-1.5.3/doc/README.rst 000755 000765 000024 00000000000 12024703636 017563 2../README ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/doc/scripting_guidelines.rst 000644 000765 000024 00000067553 11730414735 021776 0 ustar 00jrideout staff 000000 000000 Scripting guidelines
====================
Developing command line interfaces for your scripts is a convenient way to create easily reproducible analyses with PyCogent. This document covers the support for developing standardized interfaces in PyCogent. In addition to making your code easier to distribute (or to return to months after it was originally written), several GUI generators that are currently in development make use of the PyCogent ``option_parsing`` module -- this means that defining your interfaces with PyCogent's ``option_parsing`` module will allow your code to be easily wrapped in graphical interfaces.
PyCogent command line interfaces are based on the ``optparse`` module in the Python Standard Library, using ``cogent.util.option_parsing.parse_command_line_parameters`` as a convenience wrapper for defining interfaces based on certain information provided by the script developer. A fully functional `example script <./scripting_guidelines.html#countseqs>`_ and a `script template <./scripting_guidelines.html#scripttemplate>`_ are provided below.
This page will help you develop your command line interfaces after you've familiarized yourself with ``optparse``, but will not be a replacement to a general understanding of how to interact with ``optparse``. You should therefore refer both to the `optparse documentation `_ as well as the `PyCogent Scripting Guidelines <./scripting_guidelines.html>`_. As support for optparse will not continue into Python 3.0, we will be switching to ``argparse`` when we transition PyCogent to Python 3. We'll do our best to minimize the work in transitioning from ``optparse`` to ``argparse`` for PyCogent scripts by changing the interface to ``cogent.util.option_parsing.parse_command_line_parameters`` as little as possible.
This document starts with a basic example of creating a script. It then covers guidelines for defining scripts which all PyCogent developers must adhere to, and which we suggest all PyCogent script developers adhere to. Finally it covers some details of the ``script_info`` object and custom command line option types defined in PyCogent.
You should also review the PyCogent `coding guidelines <./coding_guidelines.html>`_. The scripting guidelines presented here are an extension of those.
Quickstart : how to create your first PyCogent script in 5 minutes
------------------------------------------------------------------
These steps show you how to quickly create a working PyCogent script from the PyCogent script template. Some very basic familiarity with python will help here (e.g., identifying the ``main()`` function and adding to it with the correct indentation).
1. Copy and paste the `script template <./scripting_guidelines.html#scripttemplate>`_ to a new file on your system. The next steps will assume that you're saving that file as ``/path/to/home/pycogent_user/pycogent_script_template.py``.
2. Open a command terminal and enter the following command::
chmod 755 /path/to/home/pycogent_user/pycogent_script_template.py
3. Open ``pycogent_script_template.py`` with a text editor (such as emacs, pico, or TextWrangler) and add the following to the bottom of the main() function (be sure you have proper indentation)::
print "Hello World!"
Next, after the line::
script_info['version'] = __version__
add the following line::
script_info['help_on_no_arguments'] = False
4. Run and print help text::
python /home/pycogent_user/pycogent_script_template.py -h
5. Run script -- ``Hello World!`` will be printed to the terminal::
python /home/pycogent_user/pycogent_script_template.py
You've now got a working PyCogent script. You can continue working with this script to add the functionality you're interested in. See the `optparse documentation `_ documentation for discussion of how to create options, as well as the `example script <./scripting_guidelines.html#countseqs>`_ provided below.
General notes on designing command line interfaces
--------------------------------------------------
**Design convenient command line interfaces.** The goal of your interface is to make things easy for the user (who is often you). This section covers some guidelines for how to do that.
**Have people who are better programmers than you interact with your command line interface and give you feedback on it.** If your script is difficult to work with, or has requirements that are not intuitive for users who frequently work with command line applications, people won't use your code.
**If there are tasks that are automatable, automate them.** For example, if you can make a good guess at what an output file should be named from an input file and a parameter choice, do that and use it as the default output path (but allow the user to overwrite it with a command line option).
**Define sensible default values for your command line options.** If most of the time that a script is used it will require a parameter to be set to a certain value, make that value the default to simplify the interface.
**Have the user specify named options rather than positional arguments.** The latter are more difficult to work with as users need to remember the order that they need to be passed. PyCogent scripts do not allow positional arguments by default, but if you must use them you can override this behavior by setting ``script_info['disallow_positional_arguments'] = False``. Note that this contradicts what the ``optparse`` docs say - we disagree with their comment that all required options should be passed as positional arguments.
**Avoid making assumptions about how a script will be run.** Perhaps most importantly, don't assume that the script will be run from the same directory that the script lives in. Users often want to copy executables into a centralized directory on their system (e.g., ``/usr/local/bin``). Facilitate that by not requiring that the script is run from a specific location. If you rely on data files, you have other options such as having users set an environment variable that defines where data files live on the system. Test your script from multiple locations on the file system!
Designing PyCogent command line interfaces
------------------------------------------
This section covers guidelines for how to build PyCogent command line interfaces using the ``script_info`` dictionary and the ``cogent.util.option_parsing.parse_command_line_parameters`` function. Some of this is general to ``optparse`` and some is specific to PyCogent.
Flag options
^^^^^^^^^^^^
Flags are boolean options to your script. ``optparse`` supports these directly, so you should never have to define an option that explicitly takes ``True`` or ``False`` on the command line.
Flags to your script should always be either ``action='store_true'`` or ``action='store_false'``, and do not need to define a type. The names of these options should suggest whether the option enables something (e.g., ``--print_to_stdout``) which would be defined with ``action='store_true'`` (i.e., default is False), or whether the option disables something (e.g., ``--suppress_stdout``) which would be defined with ``action='store_false'`` (i.e., the default is True). A bad name for a flag is ``--stdout`` as it's not clear what this option does.
Always define ``default`` for boolean options to set the default option for your script. If ``action='store_true'`` you should *always* pass ``default=False``. If ``action='store_false'`` you should *always* pass ``default=True``.
Choice options
^^^^^^^^^^^^^^
Use ``type=choice`` when an option is passed as a string and can be one of several acceptable values. This saves you from having to check that the user passed an acceptable value. This is done by ``optparse``, so saves you lines of code that you'd need to test, and standardizes how errors are handled. The acceptable choices are defined with ``choices=``. An example choice option definition is::
alignment_method_choices = ['pynast','mafft','muscle']
o = make_option('-m','--alignment_method',type='choice',
help='Method for aligning sequences. Valid choices are: '+\
', '.join(alignment_method_choices) + ' [default: %default]',
choices=alignment_method_choices, default='pynast')
Note that the help text here includes the list of acceptable options. This is generally a good idea as it's convenient for the user. It's not a good idea however if this is a big list (say, more than 5 or so options). If the user passes something invalid (such as ``raxml`` in this example) the list of acceptable options will be included in the error text.
Defining where output will be stored
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If a single file is created, allow the user to define that file name. If multiple files are created, allow the user to define a directory name and store all of the output files in that directory. Use the ``new_filepath`` and ``new_dirpath``, respectively, to define these output types. These will raise errors if the file or directory already exists, which is generally good as it avoids overwriting results that may have taken a long time to generate.
Defining options
----------------
Use ``make_option`` (`described here `_) to create options. As in that example, you'll define these in lists that get set as ``script_info['required_options']`` and ``script_info['optional_options']``.
Use the PyCogent custom option types when specifying input file or directory paths. These standardize error handling in the case of input files which don't exist or aren't readable and output files which already exist.
Don't define ``dest=``. By default this gets set to the long-form parameter option (e.g. ``dest='input_fp'`` is implied if your option is ``--input_fp``). Defining this as something else will confuse other people who may end up doing maintenance work on your scripts in the future.
Always define ``default=`` for optional options, and never define ``default=`` for required options. The default value for all options is ``None``, but it's convenient to explicitly define that for readability.
Always define ``help=``, and provide useful information in this string. Include ``[default: %default]`` for optional options, but not for required options (as there can be no default for a required option, or it'd be optional). The ``%default`` gets replaced with the value provided for ``default=``. It sometimes makes sense to include additional information in the ``[default:%default]`` text if the option on it's own is not informative. For example::
make_option("--output_fp",default=None,help="output filepath [default:%default; print to stdout]")
``action=store`` and ``type=string`` are defaults, and therefore do not need to be included. Leave these values out to keep your code cleaner.
If you need to pass multiple paths or strings to a single option, do this by passing a comma-separated string. The ``existing_filepaths`` option type expects strings in this format and takes care of splitting them on commas and returning a list, so if you're passing multiple input filepaths set ``type='existing_filepaths'``.
Naming options
--------------
``optparse`` allows for users to define short-form (e.g., ``-i``) and long-form (``--input_fp``) option names. For options that are commonly used, define both a long-form and a short-form parameter name::
make_option('-i','--input_dir',type="existing_filepath",help='the input directory')
For options that are infrequently used define only a long-form parameter name::
make_option('--output_file_type',help='the file type for graphical output',default='pdf')
This helps with reducing clutter and saving convenient short-form parameter names for future options that may be added.
Make paths to files end with ``_fp`` and paths to directories end with ``_dir``. This helps users understand exactly what must be passed to a script.
Some standard names for common options are listed below. You should use these whenever possible.
+-------------------------------+----------------------------------------------------------------------------------------------------+
| Description | Option name |
+===============================+====================================================================================================+
| path to an input file | ``-i``, ``--input_fp`` |
+-------------------------------+----------------------------------------------------------------------------------------------------+
| path to an output file | ``-o``, ``--output_fp`` |
+-------------------------------+----------------------------------------------------------------------------------------------------+
| path to an input directory | ``-i``, ``--input_dir`` |
+-------------------------------+----------------------------------------------------------------------------------------------------+
| path to an output dir | ``-o``, ``--output_dir`` |
+-------------------------------+----------------------------------------------------------------------------------------------------+
| path to a log file | ``-l``, ``--log_fp`` |
+-------------------------------+----------------------------------------------------------------------------------------------------+
What documentation should be included in my scripts?
----------------------------------------------------
The ``script_documentation`` entry in ``script_info`` should describe the basic functionality of your script. This entry is typically one to several sentences. Be sure not to add line breaks yourself - ``optparse`` will take care of this for you, and the formatting will look better than if you try to do it yourself.
The ``usage_examples`` entry in ``script_info`` should list one or more examples of commands that need to be run to execute your script. These should be actual calls to commands. A user should be able to copy this and paste it on the command line and have the script run (provided they put the right input files in place). See the `example script <./scripting_guidelines.html#countseqs>`_ for instances of what good usage examples look like. ``script_info['usage_examples']`` must be a list of tuples with three string entries each where the first entry is a concise title for the example, the second entry is a description of the example and why certain parameter settings are being made, and the third entry should be the exact command that needs to be run. Start these examples with ``%prog`` - this gets replaced with the name of your script and is convenient so you don't have to remember to update the usage examples if the name of your script changes.
The ``output_description`` entry in ``script_info`` should describe the output generated by the script. This entry is typically one to several sentences. Again, don't add line breaks yourself.
The script_info dictionary
--------------------------
The ``script_info`` dictionary is the central piece of information required to define a cogent script. ``script_info`` is passed to ``parse_command_line_parameters`` to define the command line interface for your script. Additionally several tools have been developed to import and use this object to define other types of interfaces (e.g., script form in the PyCogent beta GUI) or to auto-generate script documentation (e.g., for the QIIME project). This section covers the values that can be defined in your ``script_info`` dictionaries, what they do, and their default values.
Core values defined in PyCogent command line interfaces
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
These are the core values defined in the ``script_info`` dictionary used by the PyCogent ``option_parsing`` module.
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| key | Description | Default |
+===============================+====================================================================================================+==============+
| script_description | a paragraph description of the script's functionality | REQUIRED |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| script_usage | a list of tuples illustrating example usages of the script | [] |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| output_description | a paragraph description of the script's output | "" |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| version | a version number for the script | REQUIRED |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| required_options | a list of optparse Option objects that are required for the script to run | [] |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| optional_options | a list of optparse Option objects that are optional for the script to run | [] |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| disallow_positional_arguments | do not allow positional arguments to be passed to the script | True |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| help_on_no_arguments | print help text if the script is called with no options or arguments | True |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
| suppress_verbose | do not auto-generate a verbose option for the script | False |
+-------------------------------+----------------------------------------------------------------------------------------------------+--------------+
Values known to be used by the tools outside of the PyCogent codebase
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
These values are known to be used by tools outside of the PyCogent code base in ``script_info`` objects. It's best to not name new values with these names to avoid conflicts.
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
| key | Description | Used by |
+===============================+=======================================================================================================+==============+
| brief_description | a one-sentence description of the script, used by some document generators | Q,T |
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
| script_type | a definition of the type of script, used by some graphical interfaces | Q,PG |
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
| optional_options_groups | a list grouping related options under a heading [['section heading string', section_option_list], ...]| PG |
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
| authors | string of author names | PG |
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
| script_name | a brief "human readable" name for the script, used in some graphical interfaces | Q,PG |
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
| output_type | a list of tuples noting the type (in a controlled vocabulary) of each possible output | Q |
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
| option_label | a dictionary matching option names to "human readable" names, used in some graphical interfaces | Q |
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
| script_usage_output_to_remove | a list of output dirs/files that must be cleaned up if running script_usage examples multiple times | Q |
+-------------------------------+-------------------------------------------------------------------------------------------------------+--------------+
* "Used by" key : Q: `QIIME `_; PG: PyCogent beta GUI; T: tax2tree.
Setting values in script_info
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The ``script_info`` object is simply a dict, so the standard method for setting and working with dict entries applies. Some examples are::
script_info['brief_description'] = "Count sequences in one or more fasta files."
script_info['required_options'] = [
make_option('-i','--input_fps',
help='the input filepaths (comma-separated)'),
]
Custom command line option types
--------------------------------
Several custom option types are defined in PyCogent. These are:
* ``existing_path`` : Specify a path to a directory or file. Path must exist or an error is raised.
* ``new_path`` : Specify a path to a directory or file. Path must not exist or an error is raised.
* ``existing_filepath`` : Specify a path to a file. Path must exist or an error is raised.
* ``existing_filepaths`` : Specify a comma-separated list of file paths. All paths must exist or an error is raised. These are returned as a list split on commas.
* ``new_filepath`` : Specify a path to a file. Path must not exist or an error is raised.
* ``existing_dirpath`` : Specify a path to a directory. Path must exist or an error is raised.
* ``new_dirpath`` : Specify a path to a directory. Path must not exist or an error is raised.
.. _scripttemplate:
Template for a new PyCogent script
----------------------------------
The following is a template for a PyCogent script. You can download this from :download:`here ` to form the basis of your new script. This script is also embedded here for documentation purposes. This template forms a fully functional PyCogent script, so on copying this you should be able to run the script to confirm that it is working::
python pycogent_script_template.py
This will print help text and exit.
You can rename this script and use it define your new PyCogent script.
PyCogent script template::
#!/usr/bin/env python
# File created on 15 Jul 2011
from __future__ import division
__author__ = "AUTHOR_NAME"
__copyright__ = "COPYRIGHT_INFORMATION"
__credits__ = ["AUTHOR_NAME"]
__license__ = "GPL"
__version__ = "1.6.0dev"
__maintainer__ = "AUTHOR_NAME"
__email__ = "AUTHOR_EMAIL"
__status__ = "Development"
from cogent.util.option_parsing import parse_command_line_parameters, make_option
script_info = {}
script_info['brief_description'] = ""
script_info['script_description'] = ""
script_info['script_usage'] = [("","","")]
script_info['output_description']= ""
script_info['required_options'] = [\
# Example required option
#make_option('-i','--input_dir',type="existing_filepath",help='the input directory'),\
]
script_info['optional_options'] = [\
# Example optional option
#make_option('-o','--output_dir',type="new_dirpath",help='the output directory [default: %default]'),\
]
script_info['version'] = __version__
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
if __name__ == "__main__":
main()
.. _countseqs:
Example of a simple PyCogent script
-----------------------------------
You can download an example PyCogent script for counting the number of sequences in one or more fasta files :download:`here `. This script is also embedded here for documentation purposes.
::
#!/usr/bin/env python
from __future__ import division
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2011, The PyCogent project"
__credits__ = ["Greg Caporaso"]
__license__ = "GPL"
__version__ = "1.6.0dev"
__maintainer__ = "Greg Caporaso"
__email__ = "gregcaporaso@gmail.com"
__status__ = "Development"
from glob import glob
from cogent.util.option_parsing import (
parse_command_line_parameters,
make_option)
from cogent.parse.fasta import MinimalFastaParser
script_info = {}
script_info['brief_description'] = "Count sequences in one or more fasta files."
script_info['script_description'] = "This script counts the number of sequences in one or more fasta files and prints the results to stdout."
script_info['script_usage'] = [\
("Count sequences in one file",
"Count the sequences in a fasta file and write results to stdout.",
"%prog -i in.fasta"),
("Count sequences in two file",
"Count the sequences in two fasta files and write results to stdout.",
"%prog -i in1.fasta,in2.fasta"),
("Count the sequences in many fasta files",
"Count the sequences all .fasta files in current directory and write results to stdout. Note that -i option must be quoted.",
"%prog -i \"*.fasta\"")]
script_info['output_description']= "Tabular data is written to stdout."
script_info['required_options'] = [
make_option('-i','--input_fps',
help='the input filepaths (comma-separated)'),
]
script_info['optional_options'] = [
make_option('--suppress_errors',action='store_true',\
help='Suppress warnings about missing files [default: %default]',
default=False)
]
script_info['version'] = __version__
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
suppress_errors = opts.suppress_errors
input_fps = []
for input_fp in opts.input_fps.split(','):
input_fps.extend(glob(input_fp))
for input_fp in input_fps:
i = 0
try:
input_f = open(input_fp,'U')
except IOError,e:
if suppress_errors:
continue
else:
print input_fp, e
for s in MinimalFastaParser(input_f):
i += 1
print input_fp, i
if __name__ == "__main__":
main()
PyCogent-1.5.3/doc/templates/ 000755 000765 000024 00000000000 12024703636 017006 5 ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/doc/templates/layout.html 000644 000765 000024 00000001035 11361423150 021201 0 ustar 00jrideout staff 000000 000000 {% extends "!layout.html" %}
{% block extrahead %}
\
{% endblock %}
{% block sidebartoc %}
{{ super() }}
{% endblock %}
PyCogent-1.5.3/doc/images/tol_entropy_gap_filtered.png 000644 000765 000024 00000124411 11611026400 024035 0 ustar 00jrideout staff 000000 000000 ‰PNG
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H|9ÜeyRRRR—œ¤¾än‰ìÔ€Ô€Ô€ÔÀå ÿÓ€&z1ß´å IEND®B`‚ PyCogent-1.5.3/doc/examples/align_codons_to_protein.rst 000644 000765 000024 00000006316 11213034174 024260 0 ustar 00jrideout staff 000000 000000 Map protein alignment gaps to DNA alignment gaps
================================================
.. sectionauthor:: Gavin Huttley
Although PyCogent provides a means for directly aligning codon sequences, you may want to use a different approach based on the translate-align-introduce gaps into the original paradigm. After you've translated your codon sequences, and aligned the resulting amino acid sequences, you want to introduce the gaps from the aligned protein sequences back into the original codon sequences. Here's how.
.. doctest::
>>> from cogent import LoadSeqs, DNA, PROTEIN
First I'm going to construct an artificial example, using the seqs dict as a means to get the data into the Alignment object. The basic idea, however, is that you should already have a set of DNA sequences that are in frame (i.e. position 0 is the 1st codon position), you've translated those sequences and aligned these translated sequences. The result is an alignment of aa sequences and a set of unaligned DNA sequences from which the aa seqs were derived. If your sequences are not in frame you can adjust it by either slicing, or adding N's to the beginning of the raw string.
.. doctest::
>>> seqs = {
... 'hum': 'AAGCAGATCCAGGAAAGCAGCGAGAATGGCAGCCTGGCCGCGCGCCAGGAGAGGCAGGCCCAGGTCAACCTCACT',
... 'mus': 'AAGCAGATCCAGGAGAGCGGCGAGAGCGGCAGCCTGGCCGCGCGGCAGGAGAGGCAGGCCCAAGTCAACCTCACG',
... 'rat': 'CTGAACAAGCAGCCACTTTCAAACAAGAAA'}
>>> unaligned_DNA = LoadSeqs(data=seqs, moltype = DNA, aligned = False)
>>> print unaligned_DNA.toFasta()
>hum
AAGCAGATCCAGGAAAGCAGCGAGAATGGCAGCCTGGCCGCGCGCCAGGAGAGGCAGGCCCAGGTCAACCTCACT
>mus
AAGCAGATCCAGGAGAGCGGCGAGAGCGGCAGCCTGGCCGCGCGGCAGGAGAGGCAGGCCCAAGTCAACCTCACG
>rat
CTGAACAAGCAGCCACTTTCAAACAAGAAA
In order to ensure the alignment algorithm preserves the coding frame, we align the translation of the sequences. We need to translate them first, but note that because the seqs are unaligned they we have to set ``aligned = False``, or we'll get an error.
.. doctest::
>>> unaligned_aa = unaligned_DNA.getTranslation()
>>> print unaligned_aa.toFasta()
>hum
KQIQESSENGSLAARQERQAQVNLT
>mus
KQIQESGESGSLAARQERQAQVNLT
>rat
LNKQPLSNKK
The translated seqs can then be written to file, using the method ``writeToFile``. That file then serves as input for an alignment program. The resulting alignment file can be read back in. (We won't write to file in this example.) For this example we will specify the aligned sequences in the dict, rather than from file.
.. doctest::
>>> aligned_aa_seqs = {'hum': 'KQIQESSENGSLAARQERQAQVNLT',
... 'mus': 'KQIQESGESGSLAARQERQAQVNLT',
... 'rat': 'LNKQ------PLS---------NKK'}
>>> aligned_aa = LoadSeqs(data = aligned_aa_seqs, moltype = PROTEIN)
>>> aligned_DNA = aligned_aa.replaceSeqs(unaligned_DNA)
Just to be sure, we'll check that the DNA sequence has gaps in the right place.
.. doctest::
>>> print aligned_DNA
>hum
AAGCAGATCCAGGAAAGCAGCGAGAATGGCAGCCTGGCCGCGCGCCAGGAGAGGCAGGCCCAGGTCAACCTCACT
>rat
CTGAACAAGCAG------------------CCACTTTCA---------------------------AACAAGAAA
>mus
AAGCAGATCCAGGAGAGCGGCGAGAGCGGCAGCCTGGCCGCGCGGCAGGAGAGGCAGGCCCAAGTCAACCTCACG
PyCogent-1.5.3/doc/examples/alignment_app_controllers.rst 000644 000765 000024 00000004432 11444532333 024626 0 ustar 00jrideout staff 000000 000000 .. _alignment-controllers:
Using alignment application controllers to align unaligned sequences
====================================================================
.. sectionauthor:: Daniel McDonald
This document provides examples of how to align sequences using the alignment application controllers. Each alignment application controller module provides the support method ``align_unaligned_seqs``. This method takes as input a ``SequenceCollection`` object or a dict mapping sequence ids to sequences, the ``MolType`` of the sequences, and an option dict containing specific parameter settings. As output, the method returns an ``Alignment`` object.
First, lets import all of the ``align_unaligned_seqs`` methods:
.. doctest::
>>> from cogent.app.clustalw import align_unaligned_seqs as clustalw_align_unaligned_seqs
>>> from cogent.app.muscle import align_unaligned_seqs as muscle_align_unaligned_seqs
>>> from cogent.app.mafft import align_unaligned_seqs as mafft_align_unaligned_seqs
Next, we'll load our test data. We will be using DNA sequences for this example:
.. doctest::
>>> from cogent.core.moltype import DNA
>>> from cogent import LoadSeqs
>>> unaligned_seqs = LoadSeqs(filename='data/test2.fasta', aligned=False)
Lets align some sequences using default parameters!
.. note:: Output is truncated for document formatting
.. doctest::
>>> clustalw_aln = clustalw_align_unaligned_seqs(unaligned_seqs, DNA)
>>> muscle_aln = muscle_align_unaligned_seqs(unaligned_seqs, DNA)
>>> mafft_aln = mafft_align_unaligned_seqs(unaligned_seqs, DNA)
>>> clustalw_aln
5 x 60 dna alignment: NineBande[------CGCCA...], Mouse[GCAGTGAGCCA...], ...
>>> muscle_aln
5 x 60 dna alignment: NineBande[------CGCCA...], Mouse[GCAGTGAGCCA...], ...
>>> mafft_aln
5 x 60 dna alignment: NineBande[------CGCCA...], Mouse[GCAGTGAGCCA...], ...
To change specific parameters, simply specify the parameters in a dict and pass it in:
.. note:: Output is truncated for document formatting
.. doctest::
>>> clustalw_params = {'-gapopen':-3, '-quicktree':True}
>>> clustalw_aln = clustalw_align_unaligned_seqs(unaligned_seqs, DNA, params=clustalw_params)
>>> clustalw_aln
5 x 60 dna alignment: NineBande[------CGCCA...], Mouse[GCAGTGAGCCA...], ...
PyCogent-1.5.3/doc/examples/aln_profile.rst 000644 000765 000024 00000012237 11214023773 021654 0 ustar 00jrideout staff 000000 000000 Creating and manipulating alignment profiles
============================================
.. sectionauthor:: Sandra Smit
This is an example of how to create a profile from an alignment and how to do particular tricks with it. First, import the necessary stuff.
.. doctest::
>>> from cogent.core.profile import Profile
>>> from cogent import LoadSeqs, RNA
Then load an example alignment of 20 phe-tRNA sequences which we will use to create the profile
.. doctest::
>>> aln = LoadSeqs("data/trna_profile.fasta", moltype=RNA)
Examine the number of sequences in the alignment and the alignment length
.. doctest::
>>> print len(aln.Seqs)
20
>>> print len(aln)
77
Create a profile containing the counts of each base at each alignment position
.. doctest::
>>> pf = aln.getPosFreqs()
>>> print pf.prettyPrint(include_header=True, column_limit=6, col_sep=' ')
U C A G - B
0 0 0 20 0 0
0 12 0 8 0 0
1 18 0 1 0 0
7 9 0 4 0 0...
Normalize the positions to get the relative frequencies at each position
.. doctest::
>>> pf.normalizePositions()
>>> print pf.prettyPrint(include_header=True, column_limit=6, col_sep=' ')
U C A G - B
0.0000 0.0000 0.0000 1.0000 0.0000 0.0000
0.0000 0.6000 0.0000 0.4000 0.0000 0.0000
0.0500 0.9000 0.0000 0.0500 0.0000 0.0000
0.3500 0.4500 0.0000 0.2000 0.0000 0.0000...
Make sure the data in the profile is valid. The method isValid checks whether all rows add up to one and whether the profile has a valid Alphabet and CharacterOrder.
.. doctest::
>>> print pf.isValid()
True
A profile can be used to calculate consensus sequences from the alignment. To illustrate the different options for consensus calculation, let's examine the frequency data at the fifth position of the alignment (index=4)
.. doctest::
>>> print '\n'.join(['%s: %.3f'%(c,f) for (c,f) in\
... zip(pf.CharOrder, pf.dataAt(4)) if f!=0])
U: 0.050
C: 0.400
A: 0.250
G: 0.300
The easiest consensus calculation will simply take the most frequent character at each position.
.. doctest::
>>> print pf.toConsensus(fully_degenerate=False)
GCCCCGGUAGCUCAGU--GGUAGAGCAGGGGACUGAAAAUCCCCGUGUCGGCGGUUCGAUUCCGUCCCGGGGCACCA
You can also specify to use the degenerate character needed to cover all symbols occurring at a certain alignment position (fully_degenerate=True). At index 4 in the alignment U, C, A, and G occur, thus the fully degenerate symbol needed is 'N'. Alternatively, using the cutoff value, you can ask for the degenerate symbol needed to cover a certain frequency. At a cutoff of 0.8, we need both C, G, and A at index 4 to cover this value, which results in the degenerate character 'V'. For the lower cutoff of 0.6, C and G suffice, and thus the character in the consensus sequence is 'S'.
.. doctest::
>>> pf.Alphabet=RNA
>>> print pf.toConsensus(fully_degenerate=True)
GSBBNNDUAGCUCAGH??GGKAGAGCRBNVGRYUGAARAYCBNVNKGUCVBBDGWUCRAWHCHSNBHNNNVSC?CHM
>>> print pf.toConsensus(cutoff=0.8)
GSCYVBRUAGCUCAGU??GGUAGAGCASVSGAYUGAAAAUCYBSRUGUCSSYGGUUCGAUUCCGBSYSBRGSCACCA
>>> print pf.toConsensus(cutoff=0.6)
GCCYSGRUAGCUCAGU??GGUAGAGCAGRGGACUGAAAAUCCYCGUGUCGGYGGUUCGAUUCCGYCYCKRGGCACCA
A profile could also function as the description of a certain motif. As an example, let's create a profile description for the T-pseudouridine-C-loop which starts at index 54 and ends at index 59 (based on the reference structure matching the alignment).
.. doctest::
>>> loop_profile = Profile(pf.Data[54:60,:], Alphabet=RNA, CharOrder=pf.CharOrder)
>>> print loop_profile.prettyPrint(include_header=True, column_limit=6, col_sep=' ')
U C A G - B
0.9500 0.0000 0.0500 0.0000 0.0000 0.0000
1.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 1.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0500 0.9500 0.0000 0.0000
0.0000 0.0000 1.0000 0.0000 0.0000 0.0000
0.8500 0.0000 0.1500 0.0000 0.0000 0.0000
We can calculate how well this profile matches in a certain sequence (or profile) by using the score method. As an example we see where the loop profile best fits into the yeast phe-tRNA sequence. As expected, we find the best hit at index 54 (with a score of 5.75).
.. doctest::
>>> yeast = RNA.Sequence(\
... 'GCGGAUUUAGCUCAGUU-GGGAGAGCGCCAGACUGAAGAUCUGGAGGUCCUGUGUUCGAUCCACAGAAUUCGCACCA')
>>> scores = loop_profile.score(yeast)
>>> print scores
[ 2.8 0.9 0.85 0.15 2.05 2. 3.75 0.95 1.2 1. 2.9 2.75
0. 0.05 1. 2.9 2.05 1.95 0.2 1.95 0.05 1. 0. 2.
0.15 2. 1.2 1.95 0.9 0.05 1.15 2.15 2.05 1.15 2.8 0.1
0.9 0. 2.05 2.05 2.95 1. 1.8 0.95 0.05 0.85 2. 2.8
0.95 1.85 2.75 1. 0.95 1.15 5.75 1. 0. 0.15 3.05 2.15
1. 1.2 2.15 1.9 0.95 0. 0.05 1.05 4.05 1.95 1.05 0.15]
>>> print max(scores)
5.75
>>> print scores.argmax()
54
PyCogent-1.5.3/doc/examples/application_controller_framework.rst 000644 000765 000024 00000162015 11361411300 026173 0 ustar 00jrideout staff 000000 000000 ********************************************************
Application Controller Documentation
********************************************************
.. sectionauthor:: Greg Caporaso, Sandra Smit
About this document
===================
The purpose of this document is
to serve as a guideline for new users who want to implement application
controllers. It should also be helpful as a reference document for more
experienced coders. To meet the different needs of these people, this document
is split up into multiple sections that discuss the framework in different
levels of detail. We first provide a summary, then documentation for application
controller users, then documentation for application controller developers, and
finally a developer's reference detailing the underlying objects.
An addition example of building and applying a new application controller is provided `here <./building_and_using_an_application_controller.html>`_.
Feedback from users of this document will help us to improve it, so please don't
hesitate to contact us: gregcaporaso@gmail.com or sandra_smit at users.sourceforge.net.
.. % ============================================================================
The application controller framework: brief overview
====================================================
Summary
-------
An application performs a certain task. It uses parameters to give the user
control over the possible settings. In general an application requires some
input data and produces some output. To run RNAfold on (i.e. predict an RNA
secondary structure for) the sequence in seqs.txt, using some settings for
temperature and GU pairs), and to save the output in the file result.txt, the
following command would have to be executed::
RNAfold -T 25 -noGU result.txt
Suppose you want to fold the sequences at two different temperatures (25 and 37
degrees Celcius) and investigate the difference between the structures. This
would require a lot of manual work (run RNA fold twice, store all the files, use
python to read in the files, parse the output, and calculate the difference).
This task becomes a lot easier if we can control the application RNAfold from
within the python environment. The following example folds two sequences at two
different temperatures and reports the symmetric difference between the
resulting structures. It works by creating a single application controller, and
running it with different settings on the same input. The output is parsed and
compared. The code snippet doesn't leave any files on the system.
.. % This command would run RNAfold on (i.e. predict an RNA secondary structure for) the sequences in seqs.txt. It would write the output to the file result.txt. And it would use the specified settings (for temperature and GU pairs).
::
seqs = ['GCCCGGAUAGCUCAGUUAAAAUCCCCGUGUCGGUGGUUCAAUUCCGCCUCCGGGCCCA',\
'CCCCUGGUGGCCAUAGCGGGGAUUAACCCGGCCUGUGCCGGCAGCGGCACGGGAGGUCGCUGCCAGGGG']
r = RNAfold(WorkingDir="/tmp")
r.Parameters['-T'].on(25)
print "COMMAND AT 25C:", r.BaseCommand
res = r(seqs)
fold_25 = just_seqs_parser(res['StdOut'].readlines())
res.cleanUp()
r.Parameters['-T'].on(37)
print "COMMAND AT 37C:", r.BaseCommand
res = r(seqs)
fold_37 = just_seqs_parser(res['StdOut'].readlines())
res.cleanUp()
for seq_25, struct_25 in fold_25:
for seq_37, struct_37 in fold_37:
if seq_25 == seq_37:
print 'SEQ:', seq_25
print '25C:', struct_25
print '37C:', struct_37
print 'BASE PAIR SIMILARITY: %.3f'%\
(compare_pairs(struct_25.toPairs(), struct_37.toPairs()))
Running the script results in the following output::
COMMAND AT 25C: cd "/tmp/"; RNAfold -d1 -T 25 -S 1.07
COMMAND AT 37C: cd "/tmp/"; RNAfold -d1 -T 37 -S 1.07
SEQ: GCCCGGAUAGCUCAGUUAAAAUCCCCGUGUCGGUGGUUCAAUUCCGCCUCCGGGCCCA
25C: (((((((..((..((((.....(((((...))).))...))))..)).)))))))... (-26.25)
37C: ((((((.((((...)))).............(((((.......))))).))))))... (-19.6)
BASE PAIR SIMILARITY: 0.222
SEQ: CCCCUGGUGGCCAUAGCGGGGAUUAACCCGGCCUGUGCCGGCAGCGGCACGGGAGGUCGCUGCCAGGGG
25C: (((((((((((.((..((((......)))).(((((((((....)))))))))..)).))))))))))) (-55.52)
37C: (((((((..((.....((((......)))).(((((((((....))))))))).....))..))))))) (-46.3)
BASE PAIR SIMILARITY: 0.846
It has tremendous benefits to have the capability to run an application in an
integrative fashion from the Python environment, using Python object as input,
catching and directly using the output in a downstream analysis. It is
timesaving and allows for the full automation of an analysis (prevents manual
intervention). This is extremely convenient, for example, if you wish to perform
a comparison of a large variety of parameters passed to a single application.
Rather than manually running the application many times from the command line,
you can script the runs and automatically process the output. A piece of python
code that handles this is called an application controller (APPC). The purpose
of the application controller framework is to support various application
controllers in general. The framework is generic and supports actions that all
applications have in common. Each application requires a specific APPC that
defines all the variables and methods for that unique application.
At the moment the framework supports only one type of application: the command
line application. In the (near) future we want to support web applications as
well.
This section addresses the different components of an application and how these
components are represented in the framework. The framework is set up in two
files: cogent/app/util.py and cogent/app/parameters.py
Command line applications
-------------------------
Every application requires a base command (such as RNAfold, muscle, or clustalw)
and some parameters. These two properties are stored in the high level class
Application.
The class CommandlineApplication inherits from Application and has additional
features. It deals with the working directory, input, and output. The central
method is the __call__ method in which the full command-to-execute is built up
and executed. The result of running the application controller is returned to
the user.
The util.py file contains one other class: ApplicationError. This class is used
to raise exceptions for application controllers.
Parameters
----------
Most applications allow you to specify a certain set of parameters to control
how the program runs. Parameters can control many different features of an
application, such as the temperature at which RNA is folded, the number of gaps
allowed in an alignment, or the name of an output file. They come in many forms
as well, some are simply flags, some always require a value, some can have
optional values.
.. % Parameter
.. % -- FlagParameter
.. % -- ValuedParameter
.. % -- MixedParameter
.. % Parameters
.. % ParameterError
.. % FilePath
The application controller framework supports three types of parameters, which
will be discussed below. Subclassing to specify new types of parameters or to
make certain attributes fixed, is very easy.
The abstract Parameter class defines the basic functionality of a parameter: it
initializes all the Parameter attributes and it defines a Parameter ID which is
a unique identifier for each parameter. In general a parameter has a prefix
(usually a dash) and a name. Some parameters have values. The Parameter object
is discussed in more detail in section :ref:`sec:build`.
There are three subclasses from the class Parameter. FlagParameter is used for
parameters that don't have values (e.g. allow GU pairs or not). ValuedParameters
are used for paramaters that specify some value (e.g. the temperature or some
input file). MixedParameters are parameters that might or might not have a value
(e.g. the -d parameter in RNAfold). All parameters of an application are grouped
in a Paramters object. The class Parameters is a special type of dictionary that
allows lookups by parameter ID or synonyms.
The parameters.py file contains two more classes. ParameterError is used to
raise exceptions in the parameter framework. The class FilePath defines paths on
a system, it can print itself in a special way and add other parts of a path.
Input
-----
Input can be very diverse between applications. Most often it requires a file or
some data directly from the command line. Application input is handled by "input
handlers". There are a few generic input handlers in CommandLineApplication
object. Specific APPCs can use these methods directly or overwrite them. The
methods process the input data for the application. They might for example write
a certain Python object to a temporary file, and change some application
parameters to use this file.
Output
------
All applications produce some form of output. It can be limited to information
on "standard output" (stdout) and "standard error" (stderr). Many applications
produce additional output files. Most (unfortunately not all) applications
report a meaningful exit status that inform the user on whether the execution of
the program was succesful. The class CommandLineAppResult handles all aspects of
application output: stdout, stderr, exit status, and the additional output
files. Access to all the available files is handles by the class ResultPath.
More technical aspect of these classes is discussed in section :ref:`sec:build`.
.. % ResultPath
.. % CommandLineAppResult
.. % ============================================================================
.. % \newpage
Using an application controller
===============================
Summary
-------
#. Create an instance of some app controller
#. Turn parameters on and off
#. Optionally change the working directory
#. Optionally check the base command which is built-up from the above
information
#. Set the input handler
#. Possibly redirect StdOut and StdErr
#. Apply the instance to the input data, store the results
#. Use the results as you like
#. Possibly clean up files created by the program and the APPC
Creating an instance with basic settings (parameters, working directory)
------------------------------------------------------------------------
The first step toward running an application is creating an instance of the
APPC. Two basic settings are the parameters and the working directory. Below are
some examples on how to do this. Note that the working directory must be an
absolute path.
All parameters have the methods isOn and isOff to check whether the parameter is
active or not. Parameters can be turned on and off (with or without a value)
with the on() and off() methods. The values can also be set during
initialization of the APPC. When specifying the parameters upon initialization
the __init__ parameter params should be a dictionary of parameters that should
be turned on, keyed by either the Parameter ID or a synonym. The values in
params should be the values to turn the parameters on with for Valued or Mixed
Parameters, or None for Flag or Mixed Parameters.
It is useful to check the BaseCommand to see if all the parameters have the
correct settings and if the working directory is correct. During debugging it is
useful to check whether the command runs on the normal command line.
.. % \subsection{Setting/changing parameters}
.. % \subsection{Changing the working directory}
::
Initialization without params, only defaults are on.
>>> from cogent.app.vienna_package import RNAfold
>>> r = RNAfold()
Initialization with params, set new values for this instance
>>> r = RNAfold(params={'-T':25,'-d':None,'-4':None,'-S':1.2})
Initialization changing the Working directory (must be absolute path!)
>>> r = RNAfold(WorkingDir='/tmp')
>>> print r.BaseCommand
cd "/tmp/"; RNAfold -d1 -T 37 -S 1.07
Changing the working directory after initialization (must be absolute path!)
>>> r = RNAfold()
>>> r.WorkingDir = '/tmp'
>>> print r.BaseCommand
cd "/tmp/"; RNAfold -d1 -T 37 -S 1.07
Checking the parameters
>>> r = RNAfold()
>>> print r.Parameters['-P'].isOn()
False
>>> print r.Parameters['-P']
>>> print r.Parameters['-T'].isOn()
True
>>> print r.Parameters['-T']
-T 37
Other settings on initialization
--------------------------------
The input handler could be set (if not, the default is used) ::
On initialization
>>> r = RNAfold(InputHandler="_input_as_string")
>>> print r.InputHandler
_input_as_string
After initialization
>>> r = RNAfold()
>>> print r.InputHandler # default
_input_as_lines
>>> r.InputHandler = "_input_as_path"
>>> print r.InputHandler
_input_as_path
Standard out and standard error can be suppressed. If SuppressStderr or
SuppressStdout are set to True, stdout and stderr will be routed to /dev/null.
The default is to store these results in a temporary file. Redirecting StdErr
might be useful for programs that write a lot of useless information to this
filestream.
.. % input handler
Some parameters concerning the creation of temporary files can be changed.
TmpDir: default is /tmp. TmpNameLen is the length of the filenames, default is
20.
HALT_EXEC is a parameter that can be set to True for debugging purposes. It
stops the process right before execution of the system call, it leaves all the
input files (incl. temporary) in place. This allows the user to check whether
the input is generated correctly. See Section :ref:`sec:haltexec` for more
details.
Running the application, using the output, and cleaning up
----------------------------------------------------------
When calling the instance of the APPC on some data the __call__ method is
invoked. The call method has to optional parameters: data (the input data) and
remove_tmp (if True the temporary files are removed). The call method returns a
CommandLineAppResult object, containing all the application output information.
The output dictionary can be used to access the resulting files. All the
information can be incorporated in a downstream analysis. In the example below
the aligned sequences in clustalw format are parsed and printed.
Additionally CommandLineAppResult contains one public method: cleanUp() which
takes no parameters. The method cleanUp() should be used when you want to
delete the files that were created by the CommandLineApplication from disk. Note
that after cleanUp() you may still have access to your files, but these are not
reliable. You will only have access to what has already been loaded into memory
(ie. only a fraction of your file typically), so you should only run cleanUp()
after you are done accessing you files. Also note that running cleanUp() is not
required. If you want the result files to remain on disc you should not run
cleanUp() and they will be left in place. This is useful for running an
application for later analysis of results. ::
>>> from cogent import PROTEIN
>>> from cogent.app.clustalw import Clustalw
>>> from cogent.parse.clustal import ClustalParser
>>> s1 = PROTEIN.Sequence('MHSSIVLATVLFVAIASASKTRELCMKSL')
>>> s2 = PROTEIN.Sequence('MALAEADDGAVVFGEEQEALVLKSWAVMKKDA')
>>> s3 = PROTEIN.Sequence('MSTVEGREFSEDQEALVVKSWTVMKLNAGELALKF')
>>> c = Clustalw(InputHandler="_input_as_seqs")
>>> result = c([s1,s2,s3])
>>> print result['ExitStatus']
0
>>> aln_txt = result['Align'].readlines()
>>> for label, seq in ClustalParser(aln_txt): print "%s: %s"%(label, seq)
2: MALAEADDGAVVFGEEQEALVLKSWAVMKKDA-------
3: MSTVEGRE----FSEDQEALVVKSWTVMKLNAGELALKF
1: MHSSIVLAT-VLFVAIASASKTRELCMKSL---------
>>> result.cleanUp()
.. % ============================================================================
.. % \newpage
.. _sec:build:
Designing and implementing a new type of application controller
===============================================================
Each specific application that you wish to control through PyCogent requires an
application controller, i.e., a subclass of CommandLineApplication. Building the
new application controller consists of three steps:
#. Creating the application controller class: Overwrite CommandLineApplication
to define your new application controller, and define the class data. (Section
:ref:`sec:step1`.)
#. Input handing: Determine whether the built-in input handlers (in
CommandLineApplication) are sufficient. If not, write one or more input handling
methods. (Section :ref:`sec:step2`.)
#. Output handling: Determine whether the program writes any output files to
disk. If so, implement the _get_result_paths method. (Section :ref:`sec:step3`.)
.. _sec:step1:
Step 1: Creating the application controller class and defining class data
-------------------------------------------------------------------------
All of these class variables are discussed in detail in Sections
:ref:`sec:application` and :ref:`sec:commandlineapplication`. ---
**The following class data must be overwritten:**
_command:
The command used to run the command (a string).
**The following class data can be overwritten:**
_parameters:
A dictionary of Parameter objects. Keys should be the identifiers of the
parameters, and values should be the Parameter objects.
_command_delimiter:
String that specifies the delimiter between the components of a full command,
e.g. the command, parameters, and arguments.
_synonyms:
A dictionary of parameter synonyms. Keys should be the alternative keys to
lookup a parameter, and values should be the identifiers used in the _parameters
dictionary.
_input_handler:
The name of the input handler method that should be used by default. The value
should be a string (see CommandLineApplication.__call__ for how it's used).
_working_dir:
Specifies where the command should be run (string). Default is current working
directory.
_suppress_stdout:
Boolean value that specifies what happens with standard output (stdout) by
default.
_suppress_stderr:
Boolean value that specifies what happens with standard error (stderr) by
default.
Defining parameters
^^^^^^^^^^^^^^^^^^^
All parameters should be one of the three built-in types: FlagParamater,
ValuedParameter, or MixedParameter. (We don't know of any types that wouldn't
fit into this framework, but if you come across any, please let us know.)
Examples illustrating how to define the three different parameter types can be
found in Section :ref:`sec:parameters`. The _parameters dict is a mapping of
parameter identifiers, or Prefix and Name joined by the empty string, to
parameter objects. All parameters which can be passed to an application should
be defined in the parameters dict. Usually you can get this list by reviewing
the application's documentation. See Section :ref:`sec:rnafoldexample` for an
example including the definition of the _parameters dict. Note: if for a given
ValuedParameter or MixedParameter, the value is intended to be a path to a
directory or file, ``IsPath=True`` must be passed when initializing those
parameters. --- **Defining a new Parameter type** --- If the application
you're working with uses a type of parameter that is not supported by the
framework yet, you might want to write your own subclass. To subclass Parameter,
the following methods will need to be implemented: __str__, isOn(), isOff(),
on(), off(). These methods cover the two important characteristics of each
parameter: knowing how to print itself, based on its status, and knowing how to
be turned on or off. It is unlikely that you will need to subclass parameter if
working with CommandLineApplication subclasses. If you think you do, please let
us know. --- **Writing constructor functions/wrappers** --- There might be
several reasons, such as to make some attribute of the parameter fixed, to write
a wrapper around or constructor function for a parameter. For example to fixate
the prefix of the FlagParameter, one might write this::
>>> from cogent.app.parameters import FlagParameter
>>> def DashedFlag(name):
... return FlagParameter('-',name)
...
>>> tree = DashedFlag('tree')
>>> tree
>> tree.on()
>>> print tree
-tree
.. _sec:rnafoldexample:
A complete Command-LineApplication subclass example
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
A subclass of CommandLineApplication might look something like this::
class RNAfold(CommandLineApplication):
"""Application controller for RNAfold (in the Vienna RNA package)
"""
_command = 'RNAfold'
_parameters = {
'-p':MixedParameter(Prefix='-',Name='p',Delimiter='',Value=False),
'-C':FlagParameter(Prefix='-',Name='C'),
'-T':ValuedParameter(Prefix='-',Name='T',Value=37,Delimiter=' '),
'-4':FlagParameter(Prefix='-',Name=4),
'-d':MixedParameter(Prefix='-',Name='d',Delimiter='',Value=1),
'-noLP':FlagParameter(Prefix='-',Name='noLP'),
'-noGU':FlagParameter(Prefix='-',Name='noGU'),
'-noCloseGU':FlagParameter(Prefix='-',Name='noCloseGU'),
'-e':ValuedParameter(Prefix='-',Name='e',Delimiter=' '),
'-P':ValuedParameter(Prefix='-',Name='P',Delimiter=' '),
'-nsp':ValuedParameter(Prefix='-',Name='nsp',Delimiter=' '),
'-S':ValuedParameter(Prefix='-',Name='S',Value=1.07,Delimiter=' ')}
_synonyms = {'Temperature':'-T','Temp':'-T','Scale':'-S'}
_input_handler = '_input_as_lines'
_suppress_stderr = True
If the built-in input handlers are sufficient, and no output to disk is written
by the program, this would complete the application controller.
.. _sec:step2:
Step 2: Input handling
----------------------
Not all applications handle their input in the same way. The input might be
specified as a filename on the command line, as a list of values on the command
line, or an input file might be specified through parameters. Some input data
might also require processing before it is used by the application.
To give the user control over how input is handled without having to overwrite
__call__(), small input handling methods can be specified in the application
controller. In most cases, the CommandLineApplication input handlers can
probably be used (e.g., passing data via stdin or a temp file), but for more
complicated input formats, custom input handlers may need to be written for a
CommandLineApplication subclass. Every input handling method should take one
parameter, data, and return a string that will be appended to the command, e.g.
``/path/to/input/file.txt``, if a path is passed to the application. (In this
example, you would want to use CommandLineApplication._input_as_path as the
input handler.)
By writing multiple input handling methods, multiple types of input can be
handled by one application. The user can specify which one they want to use in a
certain instance by setting the _input_handler class variable, or the
InputHandler initialization variable.
For example, RNAfold takes a list of sequences from stdin. In this case, none of
the built-in input handlers provides this functionaloty. The following input
handler (from cogent.app.rnafold.Rnafold) writes the sequences (data) to a
temporary file and redirects them to stdin. ::
def _input_as_lines(self,data):
"""Returns 'name' above it in
your input file (or list of sequences). The ss and dp files for
named sequences will be written to name_ss.ps and name_dp.ps
"""
result = {}
name_counter = 0
seq_counter = 0
if not isinstance(data,list):
#means data is file
data = open(data).readlines()
for item in data:
if item.startswith('>'):
name_counter += 1
name = item.strip('>\n')
result[(name+'_ss')] =\
ResultPath(Path=(self.WorkingDir+name+'_ss.ps'))
result[(name+'_dp')] =\
ResultPath(Path=(self.WorkingDir+name+'_dp.ps'),\
IsWritten=self.Parameters['-p'].isOn())
else:
seq_counter += 1
result['SS'] = ResultPath(Path=self.WorkingDir+'rna.ps',\
IsWritten=seq_counter - name_counter > 0) #Secondary Structure
result['DP'] = ResultPath(Path=self.WorkingDir+'dot.ps',
IsWritten=(self.Parameters['-p'].isOn() and\
seq_counter - name_counter > 0)) #DotPlot
return result
Tips and tricks for creating application controllers
----------------------------------------------------
.. _sec:haltexec:
HALT_EXEC is your friend
^^^^^^^^^^^^^^^^^^^^^^^^
The __init__ method takes a boolean parameter, HALT_EXEC, which is False by
default. Setting HALT_EXEC=True will cause __call__ to exit before the system
call, print out the complete command that was about to be run, and leave all
temporary files in place. This is extremely useful for debugging, because it
allows you to run the application directly with the input that was generated by
the application controller. You can therefore run the command and look directly
at stdout and stderr, debug any temporary files that were created, etc. If the
application you are controlling is slow, this can also allow you to debug
earlier steps without having to wait for the application to run. HALT_EXEC is
your friend.
.. % ============================================================================
.. % \newpage
Application controller base classes: Developer's reference
==========================================================
Command line applications
-------------------------
.. _sec:application:
Application: cogent.app. util.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Application is an abstract class that contains some data used by for all
application handlers that could be written. Private class data of Application
consists of:
_command:
The command used to run the command (a string). If the command is in your path
(in a directory listed in the environment variable ``$PATH``, or found by typing
``which`` followed by the command) you can provide only the command, e.g.
``RNAfold``. If the command is not in your path, you must specify the absolute
path it, e.g. ``/some/other/bin/rnaview``. The use of absolute paths here is
*not* recommended, because the location of the installation might be different
on every machine. Instead, consider setting your ``$PATH`` environment variable
to include the directory where the application is installed.
For example if you are writing an application controller for ``ls`` where you
might run: --- ls -al \*.jpg --- _command should be set to ``ls``.
_parameters:
A dictionary of Parameter objects. Keys should be the identifiers of the
parameters, and values should be the Parameter objects. This dictionary defines
which parameters are available to the application. No values are specified,
except for occasional default values. The default value for _parameters is the
empty dictionary. If the application takes any command line parameters, this
must be overwritten. This is almost always the case. See
cogent.app.clustalw.Clustalw._parameters for an example of when parameters is
overwritten. ::
_parameters = {'-T':ValuedParameter('-','T',Delimiter='=')}
_synonyms:
A dictionary of parameter synonyms. Keys should be the alternative keys to
lookup a parameter, and values should be the identifiers used in the _parameters
dictionary. It probably a good idea to comment on the available synonyms in the
docstring of the application controller, so users that haven't read the manual
know what they can use to control the parameters. The default value for
_synonyms is the empty dictionary. See
cogent.app.vienna_package.ViennaPackage._synonyms for an example of this being
overwritten. ::
_synonyms = {'Temperature':'-T', 'Temp':'-T'}
_command_delimiter:
String that specifies the delimiter between the components of a full command,
e.g. the command, parameters, and arguments. The default value is ' ' (a single
space). This delimiter will work for any Unix application, so it is usually not
overwritten. (We are interested in hearing about any circumstances where this
might be overwritten. Please let us know if you come across any. One example
might be if the command being constructed is a URL.)
In the above 'ls' example, a single space (' ') spearates the command
componenets: the base command ``ls``, the parameters ``-al``, and the argument
``*.jpg``.
The only method that is defined by Application is __init__, which takes one
optional argument, params. The value of params should be a dictionary of
parameters that should be turned on. Keys should be either the Parameter ID or a
synonym. The values in params should be the values to turn the parameters on
with for Valued or Mixed Parameters, or None for Flag or Mixed Parameters.
Application is never directly instantiated, but is instead inherited (either
directly or indirectly) by all application controllers. It is necessary that
Application.__init__() be called somewhere during the initialization of your
class, but if you are inheriting from a higher level class (such as
CommandLineApplication) this should already be handled.
.. _sec:commandlineapplication:
Command-LineApplication: cogent.app.util.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
CommandLineApplication is an abstract class for command line application
controllers. Several variables are class data to facilitate subclassing
CommandLineApplication and to allow definition of defaults for Application
Controller subclasses. This class was designed to be easily and minimally
subclassed.
CommandLineApplication inherits from Application. CommandLineApplication
contains the following additional class data:
_input_handler:
The name of the input handler method that should be used by default. The value
should be a string (see CommandLineApplication.__call__ for how it's used). The
input handling methods are private, so they should start with an underscore. The
default value for _input_handler is '_input_as_string'. The input handler can be
changed on instance level via the InputHandler initialization parameter.
_working_dir:
Specifies the default working directory (string). The working_dir is where many
applications write out their output. Setting this value gives you control over
where output is written. The value of _working_dir should be an *absolute* path.
If the value of _working_dir is None (the default) the current working directory
will be used. The working directory can be changed at instance level via the
WorkingDir initialization parameter.
_suppress_stdout:
Boolean value that specifies what happens with standard output (stdout) by
default. If the value is False (default), stdout is caught and accessible in the
result object. If the value is True, stdout is routed to /dev/null and won't be
accessible. Suppression of stdout can also be controlled at instance level via
the SuppressStdout initialization parameter.
_suppress_stderr:
Boolean value that specifies what happens with standard error (stderr) by
default. Some programs write a lot to stderr which you might want to ignore. If
the value is False (default), stderr is caught and accessible in the result
object. If the value is True, stderr is routed to /dev/null and won't be
accessible. Suppression of stderr can also be controlled at instance level via
the SuppressStderr initialization parameter.
Class data can be overruled on the instance level by passing alternate data in
as parameters to __init__(). These parameters are InputHandler, SupressStderr,
and WorkingDir. Note that _working_dir and WorkingDir must always be an
absolute path, although no explicit checking is done for this. You *will* get
weird results in many cases if you use relative paths. WorkingDir, InputHandler,
and SupressStderr are all public attributes of CommandLineApplication, and can
be modified at anytime. You should (obviously) not modify the private versions
of these attributes. Note that if WorkingDir does not exist on the system it
will be created, and it will not be removed after the program runs.
There is an additional private variable _input_filename. This is set to the
string containing the absolute path to an input file when the input file is a
python generated temporary file. This should not be accessed from outside of the
program, but may be useful at times when subclassing.
CommandLineApplication defines several methods. These include::
__init__(), __call__(), _input_as_string(), _input_as_multiline_string(),
_input_as_lines(), _input_as_path(), _input_as_paths(), _absolute(),
_get_base_command(), _get_WorkingDir(), _set_WorkingDir(), _accept_exit_status(),
_get_result_paths(), getTmpFilename()
We will go over these in differing depths, because for most cases, these are
background methods that should never be called directly, or overwritten.
__init__():
Initializes the object, taking as parameters params (see Application),
InputHandler, WorkingDir, SupressStderr (discussed above). This method *must* be
called by subclasses in their __init__() if they have one. For most purposes,
you will never need to overwrite this method.
__call__():
This is the method that does most of the work in the CommandLineApplication.
Most of a users interaction with CommandLineApplications will be through this
method, which takes data as a parameter. data is the data that should be passed
as input to the application when it is called, default is None. Note that before
data is appended to the command the InputHandler function is called on it. If
data=None, no data is passed into the function, and the input handler will not
be called. You should at all costs avoid overwriting __call__() as a lot is
going on here.
_input_as_string():
The default input handler. This acts on one parameter, data, that is passed in.
It type casts data to a string, and returns the string.
_input_as_lines():
An alternate input handler. In this case, data is a a sequence of lines to be
written in a temporary file. This allows you interact with programs which only
takes files as input, when you have created a data file on the fly. The return
value of this function is a string representing the absolute path to the
filename, which will be created with in self.WorkingDir.
_input_as_multiline_string():
Input handler, similar to _input_as_lines, except data is a single string which
should be written to a temporary file. The temporary file's path is passed as
input to the application as input.
_input_as_path():
Another alternate input handler. This is similar to _input_as_string, but casts
the input to a FilePath object rather than a string. If the input is a path,
this input handler should be used.
_input_as_paths():
Yet another alternate input handler. This is similar to _input_as_path, but
operates on a list of paths.
_absolute():
Converts a filename to an absolute path if it is not already. The path that is
appended is self.WorkingDir. The result is a FilePath object.
_get_base_command():
Appends the necessary parameters to self._command and returns the full command
as a string (without input and output).
_get_WorkingDir() and _set_WorkingDir():
accessor methods for the WorkingDir attribute.
_accept_exit_status():
This function takes a string containing the return value of the application that
was run. It is meant to be overwritten when necessary. It's purpose is to
analyze the exit_status of the application being run to determine if an
ApplicationError should be raised. By default, no ApplicationError is raised
regardless of the exit_status. In a subclass this is handy because you can
customize what exit statuses are acceptable to you, and which are not, or you
can not define the function in your subclass and accept all exit statuses.
_get_result_paths():
This method is used to initialize the CommandLineAppResult class (see Section
:ref:`sec:commandlineappresult`). This method should be overwritten if the
application creates output other than stdout and stderr. A dict should be
returned with ResultPath objects keyed by the names that you'd like to access
their data by in the CommandLineAppResult object. When building the ResultPath
objects, you will need to construct the names of all of the files that are being
created. For this reason, you will need access to all of the data that the
application has access to in the case of dynamic filenames. In order to
construct these file name you have access to the Parameters object, data (which
is passed in to the function) in the case where, for example, the output
filename is specified as input to the program. The name of the input filename,
when generated as a temporary file is available as self._input_filename, for
cases where the output file name is based on the name of the input filename.
This, in addition to system calls if necessary, should provide all of the
information needed to build the names and paths of output files.
getTmpFilename():
Generates a random filename using ``TmpLenName`` random alphanumeric (upper and
lowercase) characters. The result will be an absolute path (presuming that
``TmpDir`` is absolute, which it should be), and the filename will begin with
``prefix``, end with ``suffix``, and be in
``tmp_dir`` or ``TmpDir``. The ``tmp_dir`` parameter
overrides the class/object-level default. Note that this function does not
actually created the file, just the filename. The result is a ``FilePath``
object.
Two module level functions are also implemented::
get_tmp_filename, guess_input_handler
get_tmp_filename:
A module level implementation of ``CommandLineApplication.getTmpFilename().``
guess_input_handler:
This is a module-level function intended to pick the right input_handler in case
the input is a set of sequences. It will return one of four input handlers: ---
_input_as_multiline_string, _input_as_path, _input_as_seqs, _input_as_lines.
Parameters
----------
Parameter: cogent.app. parameters.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The class Parameter is an abstract class. Every Parameter object has six
attributes: Prefix, Name, Value, Delimiter, Quote, and IsPath. All attributes
may have any value, as long as it can be type casted into a string.
The Prefix of a parameter specifies the character that precedes the name of the
parameter. It is mandatory to specify a prefix for a parameter, although it may
be the empty string. For example: '-' is the prefix in '-T=37', and '\*' is the
prefix in '\*d'. Note that some characters may have to be escaped (e.g.
`\backslash`).
Name is the second mandatory attribute of Parameter. The combination of the
prefix and name of a parameter should form a unique combination that identifies
the parameter. This ID is a public property of Parameter and will function later
on as the key in the dictionary of parameters.
The attribute Value specifies the value of a parameter. It will be clear that
not all parameters, such as flags, require a value. Therefore this field is
optional in the __init__ method. For example, the value in '-T=37' is 37, the
value in '-d1' is 1.
The Delimiter specifies what separates the name from the value when a parameter
is printed. For example: '=' in 'T=37' or ' ' (single space) in '#r 14'.
The Quote is an optional attribute that determines which characters will
surround the value when the parameter is printed. Be alert on escaping quotes,
since most quote-values will have a special meaning in python. At the moment
only symmetrical quotes are supported, such as " ' " (single quote) in " -p='a'
". Asymmetrical quotes are not possible, e.g. 'd=[4]'. *Is this something that
should get supported?*
IsPath should be set to true if the Value of the Parameter object is intended to
be a path to a directory or file. Paths require special handling when printing,
and Value is therefore cast to a cogent.app.parameters.FilePath object. IsPath
is only used by ValuedParameter and MixedParameter objects, and has no effect on
FlagParameters.
Every type of parameter prints itself differently. A flag will only print a
combination of its prefix and name; another parameter may include everything.
Therefore, the __str__ has to be specified in each specific subclass of
Parameter. Whether a parameter is printed is determined by its value. This is
also subclass specific and will be explained in the following sections.
FlagParameter: cogent.app. parameters.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
FlagParameter inherits from Parameter. A flag can't have a value, it is just on
or off. For example: if '-tree' is set, a dendrogram is calculated; if '-tree'
is not set, the tree is not calculated. Since a flag can never have a value, we
can easily use the value to specify whether the flag will be printed or not. If
Value=True, the parameter will print itself; if Value=False, it won't.
A FlagParameter can be initialized with three things. Prefix, Name (mandatory),
and Value (optional). The default for Value is False to indicate that the
parameter is off (i.e. not printed) by default. The only thing that counts for a
flag is whether its value evaluates to True or to False.
If a FlagParameter has to print itself, it checks first whether it is on or off
(Value=True or Value=False). If it is off, it will return the empty string. If
it is on it will return the combination of its prefix and name.
The methods isOn() and isOff() will return True or False depending on the Value
of the FlagParameter. These methods can be used to see whether the parameter
will be printed on the command line or not. With the methods on() and off() the
parameter can be turned on or off. These methods don't take a value, because a
flag can't have a value. Internally, they'll set parameter.Value to True or
False.
.. % Example can be removed (b/c is in section 2?)?
::
>>> from cogent.app.parameters import FlagParameter
>>> tree = FlagParameter(Prefix='-',Name='tree')
>>> tree.isOn()
False
>>> print tree
>>> tree.on()
>>> print tree
-tree
ValuedParameter: cogent.app. parameters.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValuedParameter also inherits from Parameter. In addition to setting all
attributes of the parameter during initialization, a default value is set. This
is a private property of a ValuedParameter and will be set to the value with
which the parameter.Value is initialized. The Default value is available for
inspection through parameter.Default. The default value should not be changed by
the user. With the method reset() the Value of the parameter will be reset to
the default value.
Like in FlagParameter, the value is used to control whether the parameter will
print itself or not. If the Value is None, the parameter is off and __str__ will
return the empty string. If the Value is anything else, the parameter will be
printed in full glory: prefix, name, value and optionally delimiter and quotes.
If IsPath is True, the value will be wrapped in double quotes when printed
allowing for spaces in paths.
The methods isOn() and isOff() can be used to check whether the parameter will
be printed or not. If parameter.Value is not None, the parameter is on and will
be printed. If parameter.Value is None the parameter is off and won't be
printed. By using the method on(value) the Value of the parameter is set to the
specified value. If you accidentally try to turn the parameter on with the value
None, an error will be raised. Calling off() will set the Value of the parameter
to None.
.. % Example can be removed (b/c is in section 2?)?
::
>>> from cogent.app.parameters import ValuedParameter
>>> temp = ValuedParameter(Prefix='-',Name='T',Delimiter="=")
>>> temp.isOn()
False
>>> print temp
>>> temp.on(37)
>>> print temp
-T=37
>>> temp_def = ValuedParameter(Prefix='-',Name='T',Value=100,Delimiter="=")
>>> temp_def.Default
100
>>> print temp_def
-T=100
>>> temp_def.on(15)
>>> print temp_def
-T=15
>>> temp_def.reset()
>>> print temp_def
-T=100
MixedParameter: cogent.app. parameters.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
MixedParameter is a subclass of ValuedParameter, because they share many
features. A MixedParameter is a parameter that has an optional value; sometimes
it behaves like a FlagParameter, sometimes like a ValuedParameter. An example
is: '-d[0\ `\mid`\ 1\ `\mid`\ 2]'.
During initialization the Default value is set like in ValuedParameter. The
method reset() is available to reset the parameter value to the default.
This type of Parameter has the most complicated control over 'on' or 'off'. If
the Value is False, the parameter is off. If the Value is None, the parameter is
on, but behaves like a flag (only prefix and name will be printed), if the Value
is anything else, the parameter is on and behaves like a ValuedParameter.
The methods isOn() and isOff() have the same functionality as in the other
parameter types. When using on(val=None) it is optional to specify the value. If
a MixedParameter is turned on without a value it will behave like flag. When
turned on with a value, it will behave like a ValuedParameter. The method off()
sets the Value to False, which indicates that the parameter should not be
printed.
.. % Example can be removed (b/c is in section 2?)?
::
>>> from cogent.app.parameters import MixedParameter
>>> d = MixedParameter(Prefix='-',Name='d',Delimiter='')
>>> d.isOff()
True
>>> d.on()
>>> print d
-d
>>> d.on(2)
>>> print d
-d2
FilePath: cogent.app. parameters.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The FilePath object inherits from string, and should be used to wrap all strings
that represent paths. Examples inlcude::
my_file.txt
/path/to/my/file.txt
/path/to/my/dir/
Wrapping paths in a FilePath object wraps the path in quotes when it should be,
for example when passed to a system call, and doesn't wrap it in quotes when it
shouldn't be, for example when performing operations on strings. The following
example illustrates how this fails with a simple string, but performs as it
should with a FilePath. In this example, p1 and p2 are simple strings, and p3,
p4, p5, and p6 are FilePath objects. Since the example path contains spaces, a
system call would not generate the desired result if the path is not wrapped in
quotes. The FilePath object will wrap it in quotes when it is cast to a string,
but will not wrap it in quotes when performing other string operations. The
string object, on the other hand, does not differentiate, and joining p1 and p2
results in quotes placed in the middle of the string. ::
>>> p1 = '"/path to/"'
>>> p2 = '"my_file.txt"'
>>> print str(p1 + p2)
"/path to/""my_file.txt"
>>> from cogent.app.parameters import FilePath
>>> p3 = FilePath("/path to/")
>>> p4 = FilePath("my_file.txt")
>>> print str(p3+p4)
"/path to/my_file.txt"
>>> p5 = FilePath("/path to/")
>>> p6 = FilePath("my_file.txt")
>>> print str(p5+p6)
"/path to/my_file.txt"
The FilePath object is used by MixedParameter and ValuedParameter when their
IsPath attribute is set to True. This causes the Value attribute to be cast to a
FilePath object, and it is wrapped in quotes when used in a system call. The
_input_as_path input handler also casts the input to a FilePath object. In
general, if you are working with a string in an application controller that
represents a path to a file or directory, for example in a custom input handler,
that string should be cast to a FilePath object. Failure to do this will result
in errors if users pass a path that contains spaces.
.. _sec:parameters:
Parameters: cogent.app. parameters.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
For most applications multiple parameters can be set. An application controller
should have a set of known parameters with optional default values. All
parameters of an application are organized in a dictionary where keys are
parameter identifiers (combination of prefix and name) and values are Parameter
objects.
Sometimes it might be hard to remember what the identifiers of the parameters in
a specific application are. Lets look at an example. Suppose the user knows that
the temperature can be set in three applications. In application *A* with '-T',
in application *B* with '\*temp', and in application *C* with '--t'. It is very
likely that he/she doesn't remember what parameter is used in which application.
If every application controller has an synonyms dictionary which maps 'temp' to
the identifier of the application specific parameter, the user can always lookup
the temperature with parameters['temp'].
To support the lookup of parameters by synonyms, the class Parameters is not a
simple dictionary, but a MappedDict (in cogent.util.misc). A MappedDict is a
dictionary that can apply some function to a lookup value, before it looks it up
in the dictionary. This function is called a mask. In the Parameters object the
mask allows users to look up parameters in the dictionary by synonyms.
The Parameters object uses the private function _find_synonym() internally to
determine by what key the parameter will be looked up. If the key, given by the
user, appears in the synonyms dictionary the key to use for the parameters
dictionary is looked up. Otherwise, it is assumed that the user used an existing
key in the parameters dictionary. ::
>>> from cogent.app.parameters import FlagParameter
>>> a = FlagParameter('-','a')
>>> from cogent.app.parameters import ValuedParameter
>>> b = ValuedParameter('-','T',Value=37,Delimiter='=')
>>> from cogent.app.parameters import MixedParameter
>>> c = MixedParameter('-','d',Value=0)
>>> params = {'-a':a,'-T':b,'-d':c}
>>> synonyms = {'temp':'-T','distance':'-d'}
>>> from cogent.app.parameters import Parameters
>>> p = Parameters(params,synonyms)
>>> p['-a'].isOn()
False
>>> print p['temp']
-T=37
>>> p['distance'].on(2)
>>> print p['-d']
-d2
Input
-----
CommandLineApplication subclasses are called using the __call__ method with a
single variable, data. This is the value passed to the application on the
command line. The value of data will differ based on the application you are
interfacing. Controlling for this without having to overwrite __call__ for every
CommandLineApplication is the purpose of the _input_handlers discussed in
Section :ref:`sec:commandlineapplication`.
Some examples of data that might be passed to CommandLineApplications are
strings, via the _input_as_string input handler, a list of lines that should be
written to file and then passed to the application, via the _input_as_lines
input handler, or a path to a file or directory, via the _input_as_path input
handler. To define the input handler that should be used, the class data
_input_handler should be set. If one of the default input handlers is not
applicable for a new CommandLineApplication, you will need to write a custom
input handler. See ``cogent.app.raxml.Raxml._input_as_seqs`` for an example of a
custom input handler.
For a discussion of the predefined input handlers, see Section
:ref:`sec:commandlineapplication`. For a discussion on defining custom input
handlers, see Section :ref:`sec:step2`.
.. % I think we're better off just pointing to the relevant discussion, rather than including there here.
.. % Is there a good example that we could put here? I hesitate to put a real example, b/c if we're going to
.. % rewrite this as executable documentation, it will fail on any system that didn't have the application
.. % we use as an example.
Output
------
ResultPath: cogent.app.util.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The ResultPath object is intended to hold the important information pertaining
to output files created by an application, namely the path to where the file can
be found, and whether the file was written or not. ResultPath is a very simple
container class. It has no methods aside from __init__().
To initialize a ResultPath object you must specify the path to the output file
by setting the Path parameter. This must be a string, and it is *highly*
recommended that this be an absolute path, though relative paths will also work
in many cases. You can also optionally specify a boolean value specifying
whether the file has been written or not by setting the IsWritten parameter.
This is True by default. ::
>>> from cogent.app.util import ResultPath
>>> rp = ResultPath(Path='/tmp/my_output.txt',IsWritten=True)
>>> rp.Path
'/tmp/my_output.txt'
>>> rp.IsWritten
True
>>> rp
`_. (Note this is what NCBI now refers to as *legacy BLAST*, not BLAST+.)
This document was developed in the process of writing the full ``formatdb`` application controller in PyCogent. You can find that file in your PyCogent directory at: ``cogent/app/formatdb.py``. After you work through this example, you should refer to that file to see what the full application controller and convenience wrappers look like.
A more complete reference on `PyCogent Application Controllers can be found here <./application_controller_framework.html>`_.
Building a formatdb application controller
==========================================
Step 0. Decide which application you want to support, and which version.
------------------------------------------------------------------------
Decide what version of the program you want to support and install the application. Check out the features, and decide what functionality you want to support::
formatdb --help
For the sake of brevity in this example, we'll support only the basic functionality: creating nucleic acid or protein blast databases in the default format, and with default names (i.e., named based on the names of the input file).
So, we'll support the ``-i``, ``-o``, and ``-p`` parameters.
Step 1. Define the class and the class variables.
-------------------------------------------------
First, create a new file called ``minimal_formatdb.py``. Open this in a text editor, and add the following header lines::
#!/usr/bin/python
from cogent.app.util import CommandLineApplication, ResultPath
from cogent.app.parameters import ValuedParameter
This imports some classes that we'll be using from PyCogent. For this to function correctly, ``cogent`` must be in your ``$PYTHONPATH``. Next define your class, ``MinimalFormatDb``::
class MinimalFormatDb(CommandLineApplication):
""" Example APPC for the formatdb program in the blast package """
Note that you're defining this class to inherit from ``CommandLineApplication``. This is where most of the heavy lifting is done.
We'll next want to define the following class variables:
* ``_command``: the command called to start the application
* ``_parameters``: the parameters to be passed (we'll select a few that we're going to support)
* ``_input_handler``: function describing how to convert a single parameter passed to the app controller object into input for the function
* ``_suppress_stdout``: (if other than False)
* ``_suppress_stderr``: (if other than False)
This is done by adding the following lines::
_command = "formatdb"
_parameters = {\
'-i':ValuedParameter(Prefix='-',Name='i',Delimiter=' ',IsPath=True),
'-o':ValuedParameter(Prefix='-',Name='o',Delimiter=' ',Value='T'),
'-p':ValuedParameter(Prefix='-',Name='p',Delimiter=' ',Value='F')
}
_input_handler = "_input_as_parameter"
You'll see here that we're only defining the ``-i``, ``-o``, and ``-p`` parameters, hence the name of this call being ``MinimalFormatDb``. An important variable to note here is ``_input_handler``. We'll come back to that next.
An addition thing to note here is that I'm setting Value for ``-p`` to ``F`` instead of the default of ``T``. This is because I usually build nucleotide databases (specified by ``-p F``), not protein databases (which is the default, and specified by ``-p T``).
Step 2. Overwrite methods as necessary.
---------------------------------------
We'll next create a non-default input handler. The input handler takes the input that you'll eventually provide when calling an instance of ``MinimalFormatDb``, and prepares it be passed to the actual command line application that you're calling. ``formatdb`` requires that you pass a fasta files via the ``-i`` parameters, so we'll define a new function ``_input_as_parameter``, here::
def _input_as_parameter(self,data):
""" Set -i to data
"""
self.Parameters['-i'].on(data)
return ''
Input handlers return a string that gets appended to the command, but turning parameters on also caused them to be added to the command. For that reason, this input handler returns an empty string -- otherwise ``-i`` would end up being passed twice to ``formatdb``.
Finally, we'll define the ``_get_result_paths``, which is the function that tells the application controller what files it should expect to be written, and under what circumstances. Our ``MinimalFormatDb`` application controller writes a log file under all circumstances, and nucleotide databases when ``-p`` is set to ``F`` or protein databases when ``-p`` is set to ``T``. We return the resulting files as a dict of ResultPath objects::
def _get_result_paths(self,data):
"""
"""
result = {}
result['log'] = ResultPath(\
Path=self.WorkingDir+'formatdb.log',IsWritten=True)
if self.Parameters['-p'].Value == 'F':
extensions = ['nhr','nin','nsi','nsq','nsd']
else:
extensions = ['phr','pin','psi','psq','psd']
for extension in extensions:
result[extension] = ResultPath(\
Path=data + '.' + extension,\
IsWritten=True)
return result
At this stage, you've created an application controller which supports interacting with a few features of the ``formatdb`` command line application controller. In the next step, we'll look at how to use your new application controller.
Using the new formatdb application controller
=============================================
Next we'll import the new ``minimal_formatdb`` application controller, and test it out. For the following examples, you need to access some files that are in your ``cogent/doc/data`` directory. For simplicity, we'll assume that on your system this directory is ``/home/pycogent_user/PyCogent/cogent/doc/data``. You should always replace this directory with the path as it exists on your machine.
Open a python interpreter in the directory where you created your ``minimal_formatdb.py`` and enter the following commands::
>>> import minimal_formatdb
>>> fdb = minimal_formatdb.MinimalFormatDb()
>>> res = fdb('/home/pycogent_user/PyCogent/doc/data/refseqs.fasta')
>>> res
You'll see that you've created a new protein BLAST database -- you can tell because you have the nucleotide database files in the result object (i.e., they begin with ``n``).
Next clean up your the files that were created::
>>> res.cleanUp()
Next we'll change some parameters settings, and confirm the changes::
>>> fdb = minimal_formatdb.MinimalFormatDb()
>>> fdb.Parameters['-p'].on('T')
>>> fdb.Parameters['-p'].isOn()
True
>>> fdb.Parameters['-p'].Value
'T'
>>> str(fdb.Parameters['-p'])
'-p T'
We've just set the -p parameter to F, indicating that a protein database should be built instead of a nucleotide database. Note that the database files now begin with ``p``. Run the appc and investigate the results::
>>> res = fdb('/home/pycogent_user/PyCogent/doc/data/refseqs.fasta')
>>> res
Next clean up your the files that were created::
>>> res.cleanUp()
Tips and tricks when writing applications controllers
=======================================================
One of the most useful features of application controller object when building and debugging is the HALT_EXEC parameter that can be passed to the constructor. This will cause the program to halt just before executing, and print the command that would have been run. For example:
>>> fdb = minimal_formatdb.MinimalFormatDb(HALT_EXEC=True)
>>> res = fdb('/home/pycogent_user/PyCogent/doc/data/refseqs.fasta')
[Traceback omitted]
Halted exec with command:
cd "/home/pycogent_user/"; formatdb -o T -i "/home/pycogent_user/PyCogent/doc/data/refseqs.fasta" -p F > "/tmp/tmpBpMUXE0ksEhzIZA1SSbS.txt" 2> "/tmp/tmpSKc0PRhTl47SZfkxY0g1.txt"
You can then leave the interpreter and paste this command onto the command line, and see directly what happens if this command is called. It's usually useful to remove the stdout and stderr redirects (i.e., everything after and including the first ``>``). For example::
cd "/home/pycogent_user/"; formatdb -o T -i "/home/pycogent_user/PyCogent/doc/data/refseqs.fasta"
.. rubric:: Footnotes
.. [#attribution] This document was modified from Greg Caporaso's PyCogent lecture. You can also grab the `full lecture materials `_.
PyCogent-1.5.3/doc/examples/calculate_neigbourjoining_tree.rst 000644 000765 000024 00000002470 11425201333 025576 0 ustar 00jrideout staff 000000 000000 Make a neighbor joining tree
============================
.. sectionauthor:: Gavin Huttley
An example of how to calculate the pairwise distances for a set of sequences.
.. doctest::
>>> from cogent import LoadSeqs
>>> from cogent.phylo import distance, nj
Import a substitution model (or create your own)
.. doctest::
>>> from cogent.evolve.models import HKY85
Load the alignment.
.. doctest::
>>> al = LoadSeqs("data/long_testseqs.fasta")
Create a pairwise distances object calculator for the alignment, providing a substitution model instance.
.. doctest::
>>> d = distance.EstimateDistances(al, submodel= HKY85())
>>> d.run()
Now use this matrix to build a neighbour joining tree.
.. doctest::
>>> mytree = nj.nj(d.getPairwiseDistances())
We can visualise this tree by ``print mytree.asciiArt()``, which generates the equivalent of:
.. code-block:: python
/-Human
/edge.0--|
| \-HowlerMon
|
-root----| /-NineBande
|-edge.1--|
| \-DogFaced
|
\-Mouse
We can save this tree to file.
.. doctest::
>>> mytree.writeToFile('test_nj.tree')
.. clean up
.. doctest::
:hide:
>>> import os
>>> os.remove('test_nj.tree')
PyCogent-1.5.3/doc/examples/calculate_pairwise_distances.rst 000644 000765 000024 00000005612 11425201333 025250 0 ustar 00jrideout staff 000000 000000 .. _calculating-pairwise-distances:
Calculate pairwise distances between sequences
==============================================
.. sectionauthor:: Gavin Huttley
An example of how to calculate the pairwise distances for a set of sequences.
.. doctest::
>>> from cogent import LoadSeqs
>>> from cogent.phylo import distance
Import a substitution model (or create your own)
.. doctest::
>>> from cogent.evolve.models import HKY85
Load my alignment
.. doctest::
>>> al = LoadSeqs("data/long_testseqs.fasta")
Create a pairwise distances object with your alignment and substitution model
.. doctest::
>>> d = distance.EstimateDistances(al, submodel= HKY85())
Printing ``d`` before execution shows its status.
.. doctest::
>>> print d
=========================================================================
Seq1 \ Seq2 Human HowlerMon Mouse NineBande DogFaced
-------------------------------------------------------------------------
Human * Not Done Not Done Not Done Not Done
HowlerMon Not Done * Not Done Not Done Not Done
Mouse Not Done Not Done * Not Done Not Done
NineBande Not Done Not Done Not Done * Not Done
DogFaced Not Done Not Done Not Done Not Done *
-------------------------------------------------------------------------
Which in this case is to simply indicate nothing has been done.
.. doctest::
>>> d.run()
>>> print d
=====================================================================
Seq1 \ Seq2 Human HowlerMon Mouse NineBande DogFaced
---------------------------------------------------------------------
Human * 0.0730 0.3363 0.1804 0.1972
HowlerMon 0.0730 * 0.3487 0.1865 0.2078
Mouse 0.3363 0.3487 * 0.3813 0.4022
NineBande 0.1804 0.1865 0.3813 * 0.2019
DogFaced 0.1972 0.2078 0.4022 0.2019 *
---------------------------------------------------------------------
Note that pairwise distances can be distributed for computation across multiple CPU's. In this case, when statistics (like distances) are requested only the master CPU returns data.
We'll write a phylip formatted distance matrix.
.. doctest::
>>> d.writeToFile('dists_for_phylo.phylip', format="phylip")
We'll also save the distances to file in Python's pickle format.
.. doctest::
>>> import cPickle
>>> f = open('dists_for_phylo.pickle', "w")
>>> cPickle.dump(d.getPairwiseDistances(), f)
>>> f.close()
.. clean up
.. doctest::
:hide:
>>> import os
>>> for file_name in 'dists_for_phylo.phylip', 'dists_for_phylo.pickle':
... os.remove(file_name)
PyCogent-1.5.3/doc/examples/calculate_UPGMA_cluster.rst 000644 000765 000024 00000003006 11425201333 023775 0 ustar 00jrideout staff 000000 000000 Make a UPGMA cluster
====================
.. sectionauthor:: Catherine Lozupone
An example of how to calculate the pairwise distances for a set of sequences.
**NOTE:** UPGMA should not be used for phylogenetic reconstruction.
.. doctest::
>>> from cogent import LoadSeqs
>>> from cogent.phylo import distance
>>> from cogent.cluster.UPGMA import upgma
Import a substitution model (or create your own)
.. doctest::
>>> from cogent.evolve.models import HKY85
Load the alignment.
.. doctest::
>>> al = LoadSeqs("data/test.paml")
Create a pairwise distances object calculator for the alignment, providing a substitution model instance.
.. doctest::
>>> d = distance.EstimateDistances(al, submodel= HKY85())
>>> d.run()
Now use this matrix to build a UPGMA cluster.
.. doctest::
>>> mycluster = upgma(d.getPairwiseDistances())
>>> print mycluster.asciiArt()
/-NineBande
/edge.1--|
| | /-HowlerMon
/edge.0--| \edge.2--|
| | \-Human
-root----| |
| \-DogFaced
|
\-Mouse
We demonstrate saving this UPGMA cluster to a file.
.. doctest::
>>> mycluster.writeToFile('test_upgma.tree')
..
We don't actually want to keep that file now, so I'm importing the ``os`` module to delete it.
.. doctest::
:hide:
>>> import os
>>> os.remove('test_upgma.tree')
PyCogent-1.5.3/doc/examples/codon_models.rst 000644 000765 000024 00000043435 11473355707 022047 0 ustar 00jrideout staff 000000 000000 Using codon models
==================
.. sectionauthor:: Gavin Huttley
The basic paradigm for evolutionary modelling is:
#. construct the codon substitution model
#. constructing likelihood function
#. modify likelihood function (setting rules)
#. providing the alignment(s)
#. optimisation
#. get results out
.. note:: In the following, a result followed by '...' just means the output has been truncated for the sake of a succinct presentation.
Constructing the codon substitution model
-----------------------------------------
PyCogent implements 4 basic rate matrices, described in a recently accepted manuscript: i) NF models, these are nucleotide frequency weighted rate matrices and were initially described by Muse and Gaut (1994); ii) a variant of (i) where position specific nucleotide frequencies are used; iii) TF models, these are tuple (codon in this case) frequency weighted rate matrices and were initially described by Goldman and Yang (1994); iv) CNF, these use the conditional nucleotide frequency and have developed by Yap, Lindsay, Easteal and Huttley. These different models can be created using provided convenience functions which will be the case here, or specified by directly calling the ``Codon`` substitution model class and setting the argument ``mprob_model`` equal to:
- NF, ``mprob_model='monomer'``
- NF with position specific nucleotide frequencies, ``mprob_model='monomers'``
- TF, ``mprob_model=None``
- CNF, ``mprob_model='conditional'``
.. warning:: The TF form is the currently the default, but this will be changed in the near future.
In the following I will construct GTR variants of i and iv and a HKY variant of iii.
We import these explicitly from the ``cogent.evolve.models`` module.
.. doctest::
>>> from cogent.evolve.models import CNFGTR, MG94GTR, GY94
These are functions and calling them returns the indicated substitution model with default behaviour of recoding gap characters into N's.
.. doctest::
>>> tf = GY94()
>>> nf = MG94GTR()
>>> cnf = CNFGTR()
In the following demonstration I will use only the CNF form (``cnf``).
For our example we load a sample alignment and tree as per usual. To reduce the computational overhead for this example we will limit the number of sampled taxa.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree, DNA
>>> aln = LoadSeqs('data/primate_brca1.fasta', moltype=DNA)
>>> tree = LoadTree('data/primate_brca1.tree')
Standard test of neutrality
---------------------------
We construct a likelihood function and constrain omega parameter (the ratio of nonsynonymous to synonymous substitutions) to equal 1. We also set some display formatting parameters.
.. doctest::
>>> lf = cnf.makeLikelihoodFunction(tree, digits=2, space=3)
>>> lf.setParamRule('omega', is_constant=True, value=1.0)
We then provide an alignment and optimise the model. In the current case we just use the local optimiser (hiding progress to keep this document succinct). We then print the results.
.. note:: I'm going to specify a set of conditions that will be used for all optimiser steps. For those new to python, one can construct a dictionary with the following form ``{'argument_name': argument_value}``, or alternatively ``dict(argument_name=argument_value)``. I'm doing the latter. This dictionary is then passed to functions/methods by prefacing it with ``**``.
.. doctest::
>>> optimiser_args = dict(local=True, max_restarts=5, tolerance=1e-8)
>>> lf.setAlignment(aln)
>>> lf.optimise(**optimiser_args)
>>> print lf
Likelihood Function Table
========================================
A/C A/G A/T C/G C/T omega
----------------------------------------
1.10 4.07 0.84 1.95 4.58 1.00
----------------------------------------
============================
edge parent length
----------------------------
Galago root 0.53
HowlerMon root 0.14
Rhesus edge.3 0.07
Orangutan edge.2 0.02
Gorilla edge.1 0.01
Human edge.0 0.02
Chimpanzee edge.0 0.01
edge.0 edge.1 0.00
edge.1 edge.2 0.01
edge.2 edge.3 0.04
edge.3 root 0.02
----------------------------
==============
motif mprobs
--------------
CTT 0.01
ACC 0.00...
In the above output, the first table shows the maximum likelihood estimates (MLEs) for the substitution model parameters that are 'global' in scope. For instance, the ``C/T=4.58`` MLE indicates that the relative rate of substitutions between C and T is nearly 5 times the background substitution rate.
The above function has been fit using the default counting procedure for estimating the motif frequencies, i.e. codon frequencies are estimated as the average of the observed codon frequencies. If you wanted to numerically optimise the motif probabilities, then modify the likelihood function creation line to
.. code-block:: python
lf = cnf.makeLikelihoodFunction(tree,optimise_motif_probs=True)
We can then free up the omega parameter, but before we do that we'll store the log-likelihood and number of free parameters for the current model form for reuse later.
.. doctest::
>>> neutral_lnL = lf.getLogLikelihood()
>>> neutral_nfp = lf.getNumFreeParams()
>>> lf.setParamRule('omega', is_constant=False)
>>> lf.optimise(**optimiser_args)
>>> print lf
Likelihood Function Table
========================================
A/C A/G A/T C/G C/T omega
----------------------------------------
1.08 3.86 0.78 1.96 4.08 0.75
----------------------------------------
============================
edge parent length
----------------------------
Galago root 0.53
HowlerMon root 0.14...
>>> non_neutral_lnL = lf.getLogLikelihood()
>>> non_neutral_nfp = lf.getNumFreeParams()
We then conduct a likelihood ratio test whether the MLE of omega significantly improves the fit over the constraint it equals 1. We import the convenience function from the cogent stats module.
>>> from cogent.maths.stats import chisqprob
>>> LR = 2*(non_neutral_lnL-neutral_lnL)
>>> df = non_neutral_nfp - neutral_nfp
>>> print chisqprob(LR, df)
0.0026...
Not surprisingly, this is significant. We then ask whether the Human and Chimpanzee edges have a value of omega that is significantly different from the rest of the tree.
.. doctest::
>>> lf.setParamRule('omega', tip_names=['Chimpanzee', 'Human'],
... outgroup_name='Galago', is_clade=True)
>>> lf.optimise(**optimiser_args)
>>> print lf
Likelihood Function Table
================================
A/C A/G A/T C/G C/T
--------------------------------
1.08 3.86 0.78 1.96 4.07
--------------------------------
====================================
edge parent length omega
------------------------------------
Galago root 0.53 0.73
HowlerMon root 0.14 0.73
Rhesus edge.3 0.07 0.73
Orangutan edge.2 0.02 0.73
Gorilla edge.1 0.01 0.73
Human edge.0 0.02 2.39
Chimpanzee edge.0 0.01 2.39
edge.0 edge.1 0.00 0.73...
>>> chimp_human_clade_lnL = lf.getLogLikelihood()
>>> chimp_human_clade_nfp = lf.getNumFreeParams()
>>> LR = 2*(chimp_human_clade_lnL-non_neutral_lnL)
>>> df = chimp_human_clade_nfp-non_neutral_nfp
>>> print chisqprob(LR, df)
0.028...
This is basically a replication of the original Huttley et al (2000) result for *BRCA1*.
Rate-heterogeneity model variants
---------------------------------
It is also possible to specify rate-heterogeneity variants of these models. In the first instance we'll create a likelihood function where these rate-classes are global across the entire tree. Because fitting these models can be time consuming I'm going to recreate the non-neutral likelihood function from above first, fit it, and then construct the rate-heterogeneity likelihood function. By doing this I can ensure that the richer model starts with parameter values that produce a log-likelihood the same as the null model, ensuring the subsequent optimisation step improves the likelihood over the null.
.. doctest::
>>> lf = cnf.makeLikelihoodFunction(tree, digits=2, space=3)
>>> lf.setAlignment(aln)
>>> lf.optimise(**optimiser_args)
>>> non_neutral_lnL = lf.getLogLikelihood()
>>> non_neutral_nfp = lf.getNumFreeParams()
Now, we have a null model which we know (from having fit it above) has a MLE < 1. We will construct a rate-heterogeneity model with just 2 rate-classes (neutral and adaptive) that are separated by the boundary of omega=1. These rate-classes are specified as discrete bins in PyCogent and the model configuration steps for a bin or bins are done using the ``setParamRule`` method. To ensure the alternate model starts with a likelihood at least as good as the previous we need to make the probability of the neutral site-class bin ~= 1 (these are referenced by the ``bprobs`` parameter type) and assign the null model omega MLE to this class.
To get all the parameter MLEs (branch lengths, GTR terms, etc ..) into the alternate model we get an annotated tree from the null model which will have these values associated with it.
.. doctest::
>>> annot_tree = lf.getAnnotatedTree()
>>> omega_mle = lf.getParamValue('omega')
We can then construct a new likelihood function, specifying the rate-class properties.
.. doctest::
>>> rate_lf = cnf.makeLikelihoodFunction(annot_tree,
... bins = ['neutral', 'adaptive'], digits=2, space=3)
We define a very small value (``epsilon``) that is used to specify the starting values.
.. doctest::
>>> epsilon=1e-6
We now provide starting parameter values for ``omega`` for the two bins, setting the boundary
.. doctest::
>>> rate_lf.setParamRule('omega', bin='neutral', upper=1, init=omega_mle)
>>> rate_lf.setParamRule('omega', bin='adaptive', lower=1+epsilon,
... upper=100, init=1+2*epsilon)
and provide the starting values for the bin probabilities (``bprobs``).
.. doctest::
>>> rate_lf.setParamRule('bprobs', init=[1-epsilon, epsilon])
The above statement essentially assigns a probability of nearly 1 to the 'neutral' bin. We now set the alignment and fit the model.
.. doctest::
>>> rate_lf.setAlignment(aln)
>>> rate_lf.optimise(**optimiser_args)
>>> rate_lnL = rate_lf.getLogLikelihood()
>>> rate_nfp = rate_lf.getNumFreeParams()
>>> LR = 2*(rate_lnL-non_neutral_lnL)
>>> df = rate_nfp-non_neutral_nfp
>>> print rate_lf
Likelihood Function Table
============================
edge parent length
----------------------------
Galago root 0.56
HowlerMon root 0.14
Rhesus edge.3 0.07
Orangutan edge.2 0.02
Gorilla edge.1 0.01
Human edge.0 0.02
Chimpanzee edge.0 0.01
edge.0 edge.1 0.00
edge.1 edge.2 0.01
edge.2 edge.3 0.03
edge.3 root 0.02
----------------------------
=========================
bin bprobs omega
-------------------------
neutral 0.14 0.01
adaptive 0.86 1.17
-------------------------
================================
A/C A/G A/T C/G C/T
--------------------------------
1.07 3.96 0.78 1.96 4.20
--------------------------------
==============
motif mprobs
--------------
CTT 0.01...
>>> print chisqprob(LR, df)
0.000...
We can get the posterior probabilities of site-classifications out of this model as
.. doctest::
>>> pp = rate_lf.getBinProbs()
This is a ``DictArray`` class which stores the probabilities as a ``numpy.array``.
Mixing branch and site-heterogeneity
------------------------------------
The following implements a modification of the approach of Zhang, Nielsen and Yang (Mol Biol Evol, 22:2472–9, 2005). For this model class, there are groups of branches for which all positions are evolving neutrally but some proportion of those neutrally evolving sites change to adaptively evolving on so-called foreground edges. For the current example, we'll define the Chimpanzee and Human branches as foreground and everything else as background. The following table defines the parameter scopes.
+--------------+----------------+----------------------+---------------------+
| Site class | Proportion | Background edges | Foreground edges |
+==============+================+======================+=====================+
| 0 | p_0 | 0 < omega_0 < 1 | 0 < omega_0 < 1 |
+--------------+----------------+----------------------+---------------------+
| 1 | p_1 | omega_1=1 | omega_1=1 |
+--------------+----------------+----------------------+---------------------+
| 2a | p_2 | 0 < omega_0 < 1 | omega_2 > 1 |
+--------------+----------------+----------------------+---------------------+
| 2b | p_3 | omega_1=1 | omega_2 > 1 |
+--------------+----------------+----------------------+---------------------+
.. note:: Our implementation is not as parametrically succinct as that of Zhang et al, we have 1 additional bin probability.
After Zhang et al, we first define a null model that has 2 rate classes '0' and '1'. We also get all the MLEs out using ``getStatistics``, just printing out the bin parameters table in the current case.
.. doctest::
>>> rate_lf = cnf.makeLikelihoodFunction(tree, bins = ['0', '1'],
... digits=2, space=3)
>>> rate_lf.setParamRule('omega', bin='0', upper=1.0-epsilon,
... init=1-epsilon)
>>> rate_lf.setParamRule('omega', bins='1', is_constant=True, value=1.0)
>>> rate_lf.setAlignment(aln)
>>> rate_lf.optimise(**optimiser_args)
>>> tables = rate_lf.getStatistics(with_titles=True)
>>> for table in tables:
... if 'bin' in table.Title:
... print table
bin params
====================
bin bprobs omega
--------------------
0 0.11 0.00
1 0.89 1.00
--------------------
We're also going to use the MLEs from the ``rate_lf`` model, since that nests within the more complex branch by rate-class model. This is unfortunately quite ugly compared with just using the annotated tree approach described above. It is currently necessary, however, due to a bug in constructing annotated trees for models with binned parameters.
.. doctest::
>>> globals = [t for t in tables if 'global' in t.Title][0]
>>> globals = dict(zip(globals.Header, globals.getRawData()[0]))
>>> bin_params = [t for t in tables if 'bin' in t.Title][0]
>>> rate_class_omegas = dict(bin_params.getRawData(['bin', 'omega']))
>>> rate_class_probs = dict(bin_params.getRawData(['bin', 'bprobs']))
>>> lengths = [t for t in tables if 'edge' in t.Title][0]
>>> lengths = dict(lengths.getRawData(['edge', 'length']))
We now create the more complex model,
.. doctest::
>>> rate_branch_lf = cnf.makeLikelihoodFunction(tree,
... bins = ['0', '1', '2a', '2b'], digits=2, space=3)
and set from the nested null model the branch lengths,
.. doctest::
>>> for branch, length in lengths.items():
... rate_branch_lf.setParamRule('length', edge=branch, init=length)
GTR term MLES,
.. doctest::
>>> for param, mle in globals.items():
... rate_branch_lf.setParamRule(param, init=mle)
binned parameter values,
.. doctest::
>>> rate_branch_lf.setParamRule('omega', bins=['0', '2a'], upper=1.0,
... init=rate_class_omegas['0'])
>>> rate_branch_lf.setParamRule('omega', bins=['1', '2b'], is_constant=True,
... value=1.0)
>>> rate_branch_lf.setParamRule('omega', bins=['2a', '2b'],
... edges=['Chimpanzee', 'Human'], init=99,
... lower=1.0, upper=100.0, is_constant=False)
and the bin probabilities.
.. doctest::
>>> rate_branch_lf.setParamRule('bprobs',
... init=[rate_class_probs['0']-epsilon,
... rate_class_probs['1']-epsilon, epsilon, epsilon])
The result of these steps is to create a rate/branch model with initial parameter values that result in likelihood the same as the null.
.. doctest::
>>> rate_branch_lf.setAlignment(aln)
This function can then be optimised as before. The results of one such optimisation are shown below. As you can see, the ``omega`` value for the '2a' and '2b' bins is at the upper bounds, indicating the model is not maximised in this case.
.. code-block:: python
rate_branch_lf.optimise(**optimiser_args)
print rate_branch_lf
Likelihood Function Table
=========================
edge bin omega
-------------------------
Galago 0 0.00
Galago 1 1.00
Galago 2a 0.00
Galago 2b 1.00
HowlerMon 0 0.00
HowlerMon 1 1.00
HowlerMon 2a 0.00
HowlerMon 2b 1.00
Rhesus 0 0.00
Rhesus 1 1.00
Rhesus 2a 0.00
Rhesus 2b 1.00
Orangutan 0 0.00
Orangutan 1 1.00
Orangutan 2a 0.00
Orangutan 2b 1.00
Gorilla 0 0.00
Gorilla 1 1.00
Gorilla 2a 0.00
Gorilla 2b 1.00
Human 0 0.00
Human 1 1.00
Human 2a 100.00
Human 2b 100.00
Chimpanzee 0 0.00
Chimpanzee 1 1.00
Chimpanzee 2a 100.00
Chimpanzee 2b 100.00...
PyCogent-1.5.3/doc/examples/coevolution.rst 000644 000765 000024 00000011756 12014672260 021735 0 ustar 00jrideout staff 000000 000000 Perform a coevolutionary analysis on biological sequence alignments
===================================================================
.. sectionauthor:: Greg Caporaso
This document describes how to perform a coevolutionary analysis on a ``DenseAlignment`` object. Coevolutionary analyses identify correlated substitution patterns between ``DenseAlignment`` positions (columns). Several coevolution detection methods are currently provided via the PyCogent coevolution module. ``DenseAlignment`` objects must always be used as input to these functions.
Before using an alignment in a coevolutionary analysis, you should be confident in the alignment. Poorly aligned sequences can yield very misleading results. There can be no ambiguous residue/base codes (e.g., B/Z/X in protein alignments) -- while some of the algorithms could tolerate them (e.g. Mutual Information), others which rely on information such as background residue frequencies (e.g. Statistical Coupling Analysis) cannot handle them. Some recoded amino acid alphabets will also not handle ambiguous residues. The best strategy is just to exclude ambiguous codes all together. To test for invalid characters before starting an analysis you can do the following:
.. doctest::
>>> from cogent import LoadSeqs, PROTEIN, DNA, RNA
>>> from cogent.core.alignment import DenseAlignment
>>> from cogent.evolve.coevolution import validate_alignment
>>> aln = LoadSeqs(data={'1':'GAA','2':'CTA', '3':'CTC','4':'-TC'},moltype=PROTEIN,aligned=DenseAlignment)
>>> validate_alignment(aln)
To run a coevolutionary analysis, first create a ``DenseAlignment``:
.. doctest::
>>> from cogent import LoadSeqs, PROTEIN, DNA, RNA
>>> from cogent.core.alignment import DenseAlignment
>>> aln = LoadSeqs(data={'1':'AAA','2':'CTA', '3':'CTC','4':'-TC'},moltype=PROTEIN,aligned=DenseAlignment)
Perform a coevolutionary analysis on a pair of positions in the alignment using mutual information (``mi``):
.. doctest::
>>> from cogent.evolve.coevolution import coevolve_pair_functions, coevolve_pair
>>> coevolve_pair(coevolve_pair_functions['mi'],aln,pos1=1,pos2=2)
0.31127...
Perform a coevolutionary analysis on a pair of positions in the alignment using statistical coupling analysis (``sca``):
.. doctest::
>>> from cogent.evolve.coevolution import coevolve_pair_functions, coevolve_pair
>>> coevolve_pair(coevolve_pair_functions['sca'],aln,pos1=1,pos2=2,cutoff=0.5)
0.98053...
Perform a coevolutionary analysis on one position and all other positions in the alignment using mutual information (``mi``):
.. doctest::
>>> from cogent.evolve.coevolution import coevolve_position_functions, coevolve_position
>>> coevolve_position(coevolve_position_functions['mi'],aln,position=1)
array([ nan, 0.81127812, 0.31127812])
Perform a coevolutionary analysis on all pairs of positions in the alignment using mutual information (``mi``):
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> from cogent.evolve.coevolution import coevolve_alignment_functions, coevolve_alignment
>>> coevolve_alignment(coevolve_alignment_functions['mi'],aln)
array([[ nan, nan, nan],
[ nan, 0.81127812, 0.31127812],
[ nan, 0.31127812, 1. ]])
View the available algorithms for computing coevolution values:
.. doctest::
>>> print coevolve_pair_functions.keys()
['mi', 'sca', 'an', 'gctmpca', 'rmi', 'nmi']
Perform an intermolecular coevolutionary analysis using mutual information (``mi``). Note that there are strict requirements on the sequence identifiers for intermolecular analyses, and some important considerations involved in preparing alignments for these analyses. See the coevolve_alignments docstring (i.e., ``help(coevolve_alignments)`` from the python interpreter) for information. Briefly, sequence identifiers are split on ``+`` symbols. The ids before the + must match perfectly between the two alignments as these are used to match the sequences between alignments. In the following example, these are common species names: human, chicken, echidna, and pig. The text after the ``+`` can be anything, and should probably be the original database identifiers of the sequences.
.. doctest::
>>> from cogent.evolve.coevolution import coevolve_alignment_functions,\
... coevolve_alignments
>>> aln1 = LoadSeqs(data={'human+protein1':'AAA','pig+protein1':'CTA',
... 'chicken+protein1':'CTC','echidna+weird_db_identifier':'-TC'},
... moltype=PROTEIN,aligned=DenseAlignment)
>>> aln2 = LoadSeqs(data={'pig+protein2':'AAAY','chicken+protein2':'CTAY',
... 'echidna+protein2':'CTCF','human+protein2':'-TCF'},
... moltype=PROTEIN,aligned=DenseAlignment)
>>> coevolve_alignments(coevolve_alignment_functions['mi'],aln1,aln2)
array([[ nan, nan, nan],
[ nan, 0.12255625, 0.31127812],
[ nan, 0.31127812, 0. ],
[ nan, 0.31127812, 0. ]])
PyCogent-1.5.3/doc/examples/complete_seq_features.rst 000755 000765 000024 00000000000 12024703642 033112 2../../tests/test_core/test_features.rst ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/doc/examples/DisplayPolicy_key.pdf 000644 000765 000024 00000013361 11204372323 022754 0 ustar 00jrideout staff 000000 000000 %PDF-1.3
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PyCogent-1.5.3/doc/examples/draw_dendrogram.rst 000644 000765 000024 00000005354 11425201333 022515 0 ustar 00jrideout staff 000000 000000 .. _draw-trees:
Drawing dendrograms and saving to PDF
=====================================
.. sectionauthor:: Gavin Huttley
From cogent import all the components we need.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree
>>> from cogent.evolve.models import MG94HKY
>>> from cogent.draw import dendrogram
Do a model, see the neutral test example for more details of this
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> aln = LoadSeqs("data/long_testseqs.fasta")
>>> t = LoadTree("data/test.tree")
>>> sm = MG94HKY()
>>> nonneutral_lf = sm.makeLikelihoodFunction(t)
>>> nonneutral_lf.setParamRule("omega", is_independent = True)
>>> nonneutral_lf.setAlignment(aln)
>>> nonneutral_lf.optimise()
We will draw two different dendrograms -- one with branch lengths contemporaneous, the other where length is scaled.
Specify the dimensions of the canvas in pixels
.. doctest::
>>> height, width = 500, 700
Dendrogram with branch lengths not proportional
-----------------------------------------------
.. doctest::
>>> np = dendrogram.ContemporaneousDendrogram(nonneutral_lf.tree)
>>> np.drawToPDF('tree-unscaled.pdf' , width, height, stroke_width=2.0,
... show_params = ['r'], label_template = "%(r).2g", shade_param = 'r',
... max_value = 1.0, show_internal_labels=False, font_size = 10,
... scale_bar = None, use_lengths=False)
Dendrogram with branch lengths proportional
-------------------------------------------
.. doctest::
>>> p = dendrogram.SquareDendrogram(nonneutral_lf.tree)
>>> p.drawToPDF('tree-scaled.pdf', width, height, stroke_width=2.0,
... shade_param = 'r', max_value = 1.0, show_internal_labels=False,
... font_size = 10)
Separating the analysis and visualisation steps
-----------------------------------------------
It's typically better to not have the analysis and drawing code in the same script, since drawing involves frequent iterations. This requires saving a tree for later reuse. This can be done using an annotated tree, which looks just like a tree, but has the maximum-likelihood parameter estimates attached to each tree edge. The tree must be saved in xml format to preserve the parameter estimates. The annotated tree is obtained from the likelihood function and saved to file specifying the format with the .xml suffix. This file can then be loaded using the standard ``LoadTree`` method in a separate script and used for drawing.
.. doctest::
>>> at = nonneutral_lf.getAnnotatedTree()
>>> at.writeToFile('annotated_tree.xml')
.. we clean up after ourselves, deleting the file
.. doctest::
:hide:
>>> import os
>>> for file_name in 'tree-scaled.pdf', 'tree-unscaled.pdf', 'annotated_tree.xml':
... os.remove(file_name)
PyCogent-1.5.3/doc/examples/draw_dotplot.rst 000644 000765 000024 00000002072 11444532333 022062 0 ustar 00jrideout staff 000000 000000 Drawing a dotplot
=================
.. sectionauthor:: Gavin Huttley
.. doctest::
>>> from cogent import LoadSeqs, DNA
>>> from cogent.core import annotation
>>> from cogent.draw import dotplot
Load the alignment for illustrative purposes, I'll make one sequence a different length than the other and introduce a custom sequence annotation for a miscellaneous feature. Normally, those annotations would be on the unaligned sequences.
.. doctest::
>>> aln = LoadSeqs("data/test.paml", moltype=DNA)
>>> feature = aln.addAnnotation(annotation.Feature, "misc_feature",
... "pprobs", [(38, 55)])
>>> seq1 = aln.getSeq('NineBande')[10:-3]
>>> seq2 = aln.getSeq('DogFaced')
Write out the dotplot as a pdf file in the current directory note that seq1 will be the x-axis, and seq2 the y-axis.
.. doctest::
>>> dp = dotplot.Display2D(seq1,seq2)
>>> filename = 'dotplot_example.pdf'
>>> dp.drawToPDF(filename)
.. clean up
.. doctest::
:hide:
>>> import os
>>> os.remove('dotplot_example.pdf')
PyCogent-1.5.3/doc/examples/empirical_protein_models.rst 000644 000765 000024 00000005466 11425201333 024432 0 ustar 00jrideout staff 000000 000000 Use an empirical protein substitution model
===========================================
.. sectionauthor:: Gavin Huttley
This file contains an example of importing an empirically determined protein substitution matrix such as Dayhoff et al 1978 and using it to create a substitution model. The globin alignment is from the PAML distribution.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree, PROTEIN
>>> from cogent.evolve.substitution_model import EmpiricalProteinMatrix
>>> from cogent.parse.paml_matrix import PamlMatrixParser
Make a tree object. In this case from a string.
.. doctest::
>>> treestring="(((rabbit,rat),human),goat-cow,marsupial);"
>>> t = LoadTree(treestring=treestring)
Import the alignment, explicitly setting the ``moltype`` to be protein
.. doctest::
>>> al = LoadSeqs('data/abglobin_aa.phylip',
... interleaved=True,
... moltype=PROTEIN,
... )
Open the file that contains the empirical matrix and parse the matrix and frequencies.
.. doctest::
>>> matrix_file = open('data/dayhoff.dat')
The ``PamlMatrixParser`` will import the matrix and frequency from files designed for Yang's PAML package. This format is the lower half of the matrix in three letter amino acid name order white space delineated followed by motif frequencies in the same order.
.. doctest::
>>> empirical_matrix, empirical_frequencies = PamlMatrixParser(matrix_file)
Create an Empirical Protein Matrix Substitution model object. This will take the unscaled empirical matrix and use it and the motif frequencies to create a scaled Q matrix.
.. doctest::
>>> sm = EmpiricalProteinMatrix(empirical_matrix, empirical_frequencies)
Make a parameter controller, likelihood function object and optimise.
.. doctest::
>>> lf = sm.makeLikelihoodFunction(t)
>>> lf.setAlignment(al)
>>> lf.optimise()
>>> print lf.getLogLikelihood()
-1706...
>>> print lf
Likelihood Function Table
=============================
edge parent length
-----------------------------
rabbit edge.0 0.0785
rat edge.0 0.1750
edge.0 edge.1 0.0324
human edge.1 0.0545
edge.1 root 0.0269
goat-cow root 0.0972
marsupial root 0.2424
-----------------------------
===============
motif mprobs
---------------
A 0.0871
C 0.0335
D 0.0469
E 0.0495
F 0.0398
G 0.0886
H 0.0336
I 0.0369
K 0.0805
L 0.0854
M 0.0148
N 0.0404
P 0.0507
Q 0.0383
R 0.0409
S 0.0696
T 0.0585
V 0.0647
W 0.0105
Y 0.0299
---------------
PyCogent-1.5.3/doc/examples/entity_selection.rst 000644 000765 000024 00000011651 11307154323 022741 0 ustar 00jrideout staff 000000 000000 Selecting and grouping entities
===============================
.. sectionauthor:: Marcin Cieslik
The feature, which distinguishes PyCogent's approach to the handling of macromolecular structures is the flexible and concise way of selecting, grouping and retrieving data from entities. The concepts of entity and hierarchy are similar.
Overview of methods and functions covered.
------------------------------------------
The methods covered in this section of the manual deal with selecting entities for purposes like: "select all hydrogen atoms from chain B", "mask all hetero atoms", "remove all water molecules" etc. We start with the high-level functions first, which are concise and standard to low-level methods for fine grained manipulations
Selection based on hierarchy.
-----------------------------
Let's start by accessing a PDB file and creating a structure entity. We establish a connection to the PDB file server download a file and parse it.
.. doctest::
>>> from cogent.parse.pdb import PDBParser
>>> from cogent.db.pdb import Pdb
>>> pdb = Pdb()
>>> socket_handle = pdb['2E1F']
>>> structure = PDBParser(socket_handle)
Let's see what we got
.. doctest::
>>> print structure.header['name']
HYDROLASE
>>> print structure.header['experiment_type']
X-RAY DIFFRACTION
WOW, thats descriptive. At least we know it is an X-Ray structure. Now how many chains does it have?
.. doctest::
>>> structure[(0,)].getChildren()
[]
We found the 'A' chain of the first (0-based indexing) model. We can dig deeper
.. doctest::
>>> structure[(0,)][('A',)].sortedkeys()[0:2]
[(('H_HOH', 1, ' '),), (('H_HOH', 2, ' '),)]
Only waters? Probably not. You can see what is inside a chain by looking inside the dictionary to get the list of short ids and child entities:
.. doctest::
>>> chain_A = structure[(0,)][('A',)]
>>> # chain_A.keys() # get the short_ids
>>> # chain_A.values() # get the children
>>> len(chain_A)
147
This number is too high because we counted water molecules not only amino acids. But typing ``structure[(0,)][('A',)]`` is pretty boring and it requires to inspect the number of models and chain ids first. The function which allows to select entities from the hierarchy based on their identity is called ``einput``
.. doctest::
>>> from cogent.struct.selection import einput
>>> all_residues = einput(structure, 'R', 'my_residues')
>>> all_atoms = einput(structure, 'A')
>>> len(all_residues)
147
Still waters are included.
Selection based on properties.
------------------------------
We already have a collection of entities ``all_residues`` which contains all residues in the structure regardless of the number of chains and models. Our task is to determine the number of non-water residues. The property which allows us to distinguish a water molecule from an amino acid is the name, which is stored as the ``name`` attribute.
.. doctest::
>>> chain_A.name
'A'
>>> first_child = chain_A.sortedvalues()[0]
>>> first_child.name
'H_HOH'
We could write a loop to select those residues we can either loop over the residues in ``chain_A`` or ``all_residues`` as they are the same:
.. doctest::
>>> non_water = []
>>> for residue in chain_A:
... if residue.name != 'H_HOH':
... non_water.append(residue)
...
>>> len(non_water)
95
To make this more convenient each entity e.g. a ``Chain`` instance has a method to select children based on a property ``selectChildren``. The equivalent of the above expression is:
.. doctest::
>>> non_water = chain_A.selectChildren('H_HOH', 'ne', 'name').values()
or
.. doctest::
>>> non_water = all_residues.selectChildren('H_HOH', 'ne', 'name').values()
>>> len(non_water)
95
The first argument is a value, the second an operator name from the ``operator`` module, here 'ne' is for 'Not Equal'. The last argument 'name' is resolved by the ``data_children`` method which allows the user to retrieve data from a child entities attributes, xtra dictionary or methods. Here we get the data from the 'name' attribute. The ``selectChildren`` method returns a dictionary, where keys are the short ids and values are the child entities. The result can be put into a new entity holder.
.. doctest::
>>> non_water_holder = einput(non_water, 'R')
But having to first group the entities via ``einput`` then select them only to put them into a new container seems awkward. It can be done in one step using the ``select`` function.
.. doctest::
>>> from cogent.struct.selection import select
>>> non_water_holder = select(structure, 'R', 'H_HOH', 'ne', 'name')
>>> len(non_water_holder)
95
Is there a serine(s) in the sequence?
.. doctest::
>>> serines = select(structure, 'R', 'SER', 'eq', 'name')
>>> serines.sortedkeys()[0]
('2E1F', 0, 'A', ('SER', 1146, ' '))
The function raises a ``ValueError`` if no entities can be selected.
PyCogent-1.5.3/doc/examples/estimate_startingpoint.rst 000644 000765 000024 00000004533 11425201333 024154 0 ustar 00jrideout staff 000000 000000 Estimate parameter values using a sampling from a dataset
=========================================================
.. sectionauthor:: Gavin Huttley
This script uses the ``sample`` method of the alignment class to provide an estimate for a two stage optimisation. This allows rapid optimisation of long alignments and complex models with a good chance of arriving at the global maximum for the model and data. Local optimisation of the full alignment may end up in local maximum and for this reason results from this strategy my be inaccurate.
From cogent import all the components we need.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree
>>> from cogent.evolve import substitution_model
Load your alignment, note that if your file ends with a suffix that is the same as it's format (assuming it's a supported format) then you can just give the filename. Otherwise you can specify the format using the format argument.
.. doctest::
>>> aln = LoadSeqs(filename = "data/long_testseqs.fasta")
Get your tree
.. doctest::
>>> t = LoadTree(filename = "data/test.tree")
Get the substitution model (defaults to Felsensteins 1981 model)
.. doctest::
>>> sm = substitution_model.Nucleotide()
Make a likelihood function from a sample of the alignment the ``sample`` method selects the chosen number of bases at random.
.. doctest::
>>> lf = sm.makeLikelihoodFunction(t)
>>> lf.setMotifProbsFromData(aln)
>>> lf.setAlignment(aln.sample(20))
Optimise with the local optimiser
.. doctest::
>>> lf.optimise(local=True)
Next use the whole alignment
.. doctest::
>>> lf.setAlignment(aln)
and the faster Powell optimiser that will only find the best result near the provided starting point
.. doctest::
>>> lf.optimise(local=True)
.. doctest::
>>> print lf
Likelihood Function Table
=============================
edge parent length
-----------------------------
Human edge.0 0.0309
HowlerMon edge.0 0.0412
edge.0 edge.1 0.0359
Mouse edge.1 0.2666
edge.1 root 0.0226
NineBande root 0.0895
DogFaced root 0.1095
-----------------------------
===============
motif mprobs
---------------
T 0.2317
C 0.1878
A 0.3681
G 0.2125
---------------
PyCogent-1.5.3/doc/examples/generating_app_commandlines.rst 000644 000765 000024 00000007727 11213303017 025075 0 ustar 00jrideout staff 000000 000000 Generating application commandlines
===================================
.. sectionauthor:: Daniel McDonald
In this example we will generate application command lines. This tool is useful for creating jobs scripts in a cluster or supercomputer environment, as well as when varying parameters. First, we must create a ``ParameterIterBase`` subclass instance. For this example, we will use the ``ParameterCombinations`` object and will vary parameters from the ``Clustalw`` application controller.
.. doctest::
>>> from cogent.app.clustalw import Clustalw
>>> from cogent.app.util import ParameterCombinations
Lets go ahead and vary the parameters ``-gapdist`` and ``-kimura``, specifying that we always want a value for the ``-gapdist`` parameter. ``-gapdist`` is a ``ValuedParameter``, so we must specify a list of values we wish to use. ``-kimura`` is a ``FlagParameter``, so we only need to say that we would like it on (``True``). If the parameter is not specified in ``AlwaysOn`` then the off state will be added to the range of possible values for the parameter.
.. doctest::
>>> params_to_vary = {'-gapdist':[1,2,3], '-kimura':True}
>>> always_on = ['-gapdist']
>>> param_comb = ParameterCombinations(Clustalw, params_to_vary, always_on)
The returned instance is a generator that will yield parameter dictionaries that can be passed to the application controller. For this example, we will instead use the generator to construct command line strings.
.. doctest::
>>> from cogent.app.util import cmdline_generator
To generate command lines, you must specify a ``ParameterIterBase`` subclass instance, the full path to the application, an optional initial binary (such as Python), how to handle inputs and outputs, specify the actual inputs, how to handle ``stdin/stdout/stderr``, and if you would like unique outputs to be created. This sounds like a lot, but not all applications support by PyCogent work the same. This generator is designed to handle every application supported by PyCogent. In this example, we are not specifying how to handle ``stderr`` and ``stdout``. They are by default thrown to ``/dev/null``.
.. note:: Output from printing ``cmd`` is truncated for document formatting
.. doctest::
>>> path_to_bin = '' # we do not need an initial binary
>>> path_to_cmd = '/usr/bin/clustalw'
>>> paths_to_inputs = ['/home/user/input1','/home/user/input2']
>>> path_to_output = '/home/user/output'
>>> unique_outputs = True
>>> input_param = '-infile'
>>> output_param = '-outfile'
>>> cmd_gen = cmdline_generator(param_comb, PathToBin=path_to_bin, \
... PathToCmd=path_to_cmd, PathsToInputs=paths_to_inputs, \
... PathToOutput=path_to_output, UniqueOutputs=unique_outputs,\
... InputParam=input_param, OutputParam=output_param)
>>> for cmd in cmd_gen:
... print cmd
...
/usr/bin/clustalw -align -gapdist=1 -kimura -infile="/home/user/input1" -outfile="/home/...
/usr/bin/clustalw -align -gapdist=1 -kimura -infile="/home/user/input2" -outfile="/home/...
/usr/bin/clustalw -align -gapdist=1 -infile="/home/user/input1" -outfile="/home/user/out...
/usr/bin/clustalw -align -gapdist=1 -infile="/home/user/input2" -outfile="/home/user/out...
/usr/bin/clustalw -align -gapdist=2 -kimura -infile="/home/user/input1" -outfile="/home/...
/usr/bin/clustalw -align -gapdist=2 -kimura -infile="/home/user/input2" -outfile="/home/...
/usr/bin/clustalw -align -gapdist=2 -infile="/home/user/input1" -outfile="/home/user/out...
/usr/bin/clustalw -align -gapdist=2 -infile="/home/user/input2" -outfile="/home/user/out...
/usr/bin/clustalw -align -gapdist=3 -kimura -infile="/home/user/input1" -outfile="/home/...
/usr/bin/clustalw -align -gapdist=3 -kimura -infile="/home/user/input2" -outfile="/home/...
/usr/bin/clustalw -align -gapdist=3 -infile="/home/user/input1" -outfile="/home/user/out...
/usr/bin/clustalw -align -gapdist=3 -infile="/home/user/input2" -outfile="/home/user/out...
PyCogent-1.5.3/doc/examples/genetic_code_aa_index.rst 000644 000765 000024 00000006067 11444532333 023630 0 ustar 00jrideout staff 000000 000000 Compute the effect of a nucleotide substitution on residue polarity in two different genetic codes using GeneticCode and AAIndex
================================================================================================================================
.. sectionauthor:: Greg Caporaso
This document illustrates how to work with a genetic code object, and compare two different genetic codes. Here we compare the change in residue polarity, as judged by the Woese Polarity Requirement index (Woese 1973), resulting from a nucleotide substitution if the sequence is translated with the standard nuclear genetic code, or the vertebrate mitochondrial genetic code.
First, we load the genetic code objects and look at how they differ from one another.
.. doctest::
>>> from cogent.core.genetic_code import GeneticCode
>>> code = 'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'
>>> standard_nuclear_genetic_code = GeneticCode(code)
>>> code = 'FFLLSSSSYY**CCWWLLLLPPPPHHQQRRRRIIMMTTTTNNKKSS**VVVVAAAADDEEGGGG'
>>> vertebrate_mitochondrial_genetic_code = GeneticCode(code)
>>> standard_nuclear_genetic_code == vertebrate_mitochondrial_genetic_code
False
We'll make some synonyms for the objects for simplicity, and then look at the differences between the two codes:
.. doctest::
>>> ngc = standard_nuclear_genetic_code
>>> mgc = vertebrate_mitochondrial_genetic_code
>>> differences = ngc.changes(mgc).items()
>>> differences.sort()
>>> differences
[('AGA', 'R*'), ('AGG', 'R*'), ('ATA', 'IM'), ('TGA', '*W')]
Next, let's load the Woese Polar Requirement ``AAIndex`` data, and find the effect of an ATA to ATG substitution with each of the two ``GeneticCode`` objects.
.. doctest::
>>> from cogent.parse.aaindex import getWoeseDistanceMatrix
>>> woese_distance_matrix = getWoeseDistanceMatrix()
>>> woese_distance_matrix[ngc['ATA']][ngc['ATG']]
0.39999999999999947
>>> woese_distance_matrix[mgc['ATA']][mgc['ATG']]
0.0
This illustrates that there is a difference in residue polarity associated with substitution only in the standard nuclear code (where ATA to ATG translates to an isoleucine to methionine substitution). In the vertebrate mitochondrial code, ATA to ATG is a synonymous substitution. Calculations of this type were central to [1]_ which presents the study that these modules were initially developed for.
``GeneticCode`` objects can also be used to translate DNA sequences (where asterisks in the results refer to stop-translation characters):
.. doctest::
>>> dna = "AAACGCTGTGTGTGAGATGAAAAA"
>>> ngc.translate(dna)
'KRCV*DEK'
>>> mgc.translate(dna)
'KRCVWDEK'
The standard nuclear genetic code can also be loaded as ``DEFAULT``:
.. doctest::
>>> from cogent.core.genetic_code import DEFAULT
>>> DEFAULT == standard_nuclear_genetic_code
True
**Citations**
.. [1] Caporaso, Yarus, and Knight. *Error minimization and coding triplet/binding site associations are independent features of the canonical genetic code.* J Mol Evol, 61(5):597-607, 2005.
PyCogent-1.5.3/doc/examples/goodness_of_fit.rst 000644 000765 000024 00000006543 11305663710 022536 0 ustar 00jrideout staff 000000 000000 The ``goodness_of_fit`` module
==============================
.. sectionauthor:: Andreas Wilm
This is a short example of how to use the goodness_of_fit module.
``goodness_of_fit`` will measure the degree of correspondence (or goodness of fit) between a multidimensional scaling (i.e. a lower dimensional representation of distances between objects) and the input distance matrix.
Let's setup some example data:
.. doctest::
>>> import numpy
>>> import cogent.cluster.goodness_of_fit as goodness_of_fit
>>> distmat = numpy.array([
... [ 0. , 0.039806, 0.056853, 0.21595 , 0.056853, 0.0138 ,
... 0.203862, 0.219002, 0.056853, 0.064283],
... [ 0.039806, 0. , 0.025505, 0.203862, 0.0208 , 0.039806,
... 0.194917, 0.21291 , 0.0208 , 0.027869],
... [ 0.056853, 0.025505, 0. , 0.197887, 0.018459, 0.056853,
... 0.191958, 0.203862, 0.018459, 0.025505],
... [ 0.21595 , 0.203862, 0.197887, 0. , 0.206866, 0.206866,
... 0.07956 , 0.066935, 0.203862, 0.206866],
... [ 0.056853, 0.0208 , 0.018459, 0.206866, 0. , 0.056853,
... 0.203862, 0.21595 , 0.0138 , 0.0208 ],
... [ 0.0138 , 0.039806, 0.056853, 0.206866, 0.056853, 0. ,
... 0.197887, 0.209882, 0.056853, 0.064283],
... [ 0.203862, 0.194917, 0.191958, 0.07956 , 0.203862, 0.197887,
... 0. , 0.030311, 0.200869, 0.206866],
... [ 0.219002, 0.21291 , 0.203862, 0.066935, 0.21595 , 0.209882,
... 0.030311, 0. , 0.21291 , 0.219002],
... [ 0.056853, 0.0208 , 0.018459, 0.203862, 0.0138 , 0.056853,
... 0.200869, 0.21291 , 0. , 0.011481],
... [ 0.064283, 0.027869, 0.025505, 0.206866, 0.0208 , 0.064283,
... 0.206866, 0.219002, 0.011481, 0. ]])
>>> mds_coords = numpy.array([
... [ 0.065233, 0.035019, 0.015413],
... [ 0.059604, 0.00168 , -0.003254],
... [ 0.052371, -0.010959, -0.014047],
... [-0.13804 , -0.036031, 0.031628],
... [ 0.063703, -0.015483, -0.00751 ],
... [ 0.056803, 0.031762, 0.021767],
... [-0.135082, 0.023552, -0.021006],
... [-0.150323, 0.011935, -0.010013],
... [ 0.06072 , -0.01622 , -0.007721],
... [ 0.065009, -0.025254, -0.005257]])
You are now good to compute stress values as shown in the following.
``Stress.calcKruskalStress()``
------------------------------
This computes Kruskal's Stress AKA Stress Formula 1 (Kruskal, 1964).
Kruskal gives the following numbers as guideline:
========== ===============
Stress [%] Goodness of fit
========== ===============
20 Poor
10 Fair
5 Good
2.5 Excellent
0 Perfect
========== ===============
Our example data gives a very good stress value:
.. doctest::
>>> stress = goodness_of_fit.Stress(distmat, mds_coords)
>>> print stress.calcKruskalStress()
0.02255...
``Stress.calcSstress()``
------------------------
This computes S-Stress (Takane, 1977). S-Stress emphasises larger dissimilarities more than smaller ones. S-Stress values behave nicer then Stress-1 values:
- The value of S-Stress is always between 0 and 1
- Values less then 0.1 mean good representation.
Using the example data again:
.. doctest::
>>> stress = goodness_of_fit.Stress(distmat, mds_coords)
>>> print stress.calcSstress()
0.00883...
PyCogent-1.5.3/doc/examples/handling_3dstructures.rst 000644 000765 000024 00000031671 11444532333 023705 0 ustar 00jrideout staff 000000 000000 Working with macromolecular structures
======================================
.. sectionauthor:: Marcin Cieslik
This part of the documentation presents examples on how to work with macromolecular structures i.e. coordinate files. This functionality has originates from ZenPDB.
At the current stage of development the input and output is limited to PDB files and some derivatives, but the "internal" representation and construction is file-format agnostic and other parsers can be easily added.
Hierarchy and identity
----------------------
A common way to describe macromolecular structures is the hierarchical representation. The hierarchy is made from entities (atoms, residues, chains, models, structures and crystals). In this hierarchical representation models are within structures (e.g. several NMR models of one protein structure or residues which are a collection of atoms). Hierarchical representations are unique i.e. each entity has to be uniquely identified for a given structure, which means that it has a unique identifier. We will refer to this identifier as the *full_id* in contrast with the *short_id* or just *id* which defines an entity uniquely only within it's parent. Each entity has only a single parent, but can have multiple children e.g. a residue is part of only one peptide chain, but it will contain multiple atoms.
An example of a *full_id*:
::
# for an atom
('4TSV', 0, 'A', ('ARG', 131, ' '), ('O', ' '))
# for a residue
('4TSV', 0, 'A', ('ARG', 131, ' '))
# for a chain
('4TSV', 0, 'A')
The first is the identifier for the oxygen atom from the peptide bond of the ARG131 residue in the 'A' chain of the first model (0) in the structure available from the PDB as '4TSV'. A short version of an *id* which is specific only within a parent (i.e. for an atom within a residue) looks similar. In the example below we see the short id of the same atom. Of course this information is not enough to pin-point an atom in the structure but it is enough to identify different atoms within the same residue.
::
(('O', ' '),)
As you can see the *full_id* is a linear tuple of short id's which can be either a tuple (e.g. ('O', ' ') for an oxygen atom) or a string (e.g. 'A' for chain A). All strings within a short id have some special meaning for example the id of a residue has the following structure ('three letter AA name', residue_id, 'insertion code'). It should be noted that according to the RCSB the ``residue_id`` is the integer number which should be 1 for the first natural residue in a protein. Residues can have negative ``residue_ids`` e.g. residues of a N-terminal affinity tag.
What is an Entity?
------------------
``Entity`` is the most basic class to provide methods specific to macromolecular structures. The ``Atom``, ``Residue``, ``Chain``, ``Model`` and ``Structure`` classes all inherit from the ``Entity`` class, yet there is some distinction between them. Only the ``Atom`` entity cannot contain other entities e.g. an instance of the ``Residue`` class can (and should) contain some ``Atom`` instances. The methods common to container entities are within the ``MultiEntity`` class which they all inherit from. The ``MultiEntity`` is also a subclass of the ``Entity`` class. It is important not to use the ``Entity`` and ``MultiEntity`` classes directly as some attributes (e.g. their position within the SMCRA hierarchy) have to be provided. In fact each entity is just a Python dictionary with almost all dictionary methods left untouched.
Parsing a macromolecular structure e.g. a PDB file means to create a ``Structure`` entity or in other words to recursively fill it with atoms, residues and chains.
Working with entities
---------------------
Our first task will be to parse and write a structure in a PDB file into an ``Entity`` hierarchy. This is quite easy and if you are familiar with the internals of PyCogent I hope it will also be obvious. You can use any PDB file the examples use the ``4TSV.pdb`` file in the doc/data directory.
The easy way, but implicit way:
.. doctest::
>>> import cogent
>>> structure = cogent.LoadStructure('data/4TSV.pdb')
This code involves quite a bit of magic, so let's do everything manually.
The ``cogent.LoadStructure`` method is a convenience method to get a structure object from a file in any of the supported formats. Right now PyCogent supports only the PDB file-format. Now let's read and write the same PDB file by using the ``PDBParser`` and ``PDBWriter`` function directly. The new_structure argument can be any ``Entity`` (e.g. a ``Structure`` entity) or a container of entities (e.g. a list of ``Atom`` and ``Residue`` entities):
.. doctest::
>>> from cogent.parse.pdb import PDBParser
>>> from cogent.format.pdb import PDBWriter
>>> import tempfile, os
>>> pdb_file = open('data/4TSV.pdb')
>>> new_structure = PDBParser(pdb_file)
>>> open_handle, file_name = tempfile.mkstemp()
>>> os.close(open_handle)
>>> new_pdb_file = open(file_name,'wb')
>>> PDBWriter(new_pdb_file, new_structure)
>>> new_structure
In this code-listing we first import the PDB parser and PDB writer, open a PDB file and parse the structure. You can verify that the ``PDBParser`` does not close the open ``pdb_file``:
.. doctest::
>>> assert not pdb_file.closed
>>> assert not new_pdb_file.closed
Currently the ``PDBParser`` parses quite a lot information from the header of the PDB file and the atomic coordinates. It omits the anisotropic b-factors. Additional information is stored in the ``header`` attribute which is a dictionary.
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> structure.id # the static id tuple.
('4TSV',)
>>> structure.getId() # the dynamic id tuple, use calls to get_id whenever possible.
('4TSV',)
>>> structure.getFull_id() # only for the structure entity is the full_id identical to the id.
('4TSV',)
>>> structure.header.keys() # the pdb header is parsed in to a dictionary as the header attribute
['bio_cmx', 'uc_mxs',...
>>> structure.header['id'] # this is the 4-char PDB ID parsed from the header and used to construct the structure.id
'4TSV'
>>> structure.header['expdta'] # if this is 'X-RAY' we probably deal with a x-ray structre and thus a lot crystallografic data is store in the header.
'X-RAY'
Not all information from the PDB header is currently parsed, If you are interested in some special data you can access the unparsed header through the ``raw_header`` attribute, the same is true for the trailer. If you manage to extract the data from the ``raw_header`` you are ready to modify the modular code of the ``PDBParser`` class, please submit a patch!
.. code-block:: python
structure.raw_header
structure.raw_trailer
The structure entity is a container for model entities, as you already know the structure is just a dictionary of models.
.. doctest::
>>> structure.items()
[((0,), )]
>>> structure.values()
[]
>>> structure.keys()
[(0,)]
>>> first_model = structure.values()[0] # we name the first(and only) model in the structure
>>> first_model_id = first_model.getId()
But PyCogent provides more specific methods to work with entities. The one which is useful to access the contents of an entity is ``getChildren``. The optional argument to the ``getChildren`` methods is a list of ids (e.g. to access only a subset of children) more concise and sophisticated methods to work with children will be introduced later
.. doctest::
>>> structure.getChildren() # the output should be the same as structure.values()
[]
>>> children_list = structure.getChildren([first_model_id])
A typical way to change a property of all children in a MultiEntity would be to write a loop. In this example we change the name of every residue to 'UNK'.
.. doctest::
>>> some_model = structure.values()[0]
>>> some_chain = some_model.values()[0]
>>> for residue in some_chain.values():
... residue.setName('UNK')
...
Pycogent allows to make it much shorter. Whenever a structure is created the top-level entity(i.e. the structure) gets pointer list to all the entities it contains stored as the ``table`` attribute. For example the structure entity will have a table with a list of all models, chains, residues and atoms that it contains. The keys of this table are *full_ids* the values the actual entities. The table is divided into sections based on the hierarchy i.e. there is a separate dictionary for residues, atoms, chains and models.
.. doctest::
>>> sorted(structure.table.keys()) # all the different entity levels in the table (which is a normal dictionary)
['A', 'C', 'M', 'R']
>>> structure.table['C'] # this is a full_id to entity mapping for all chains inside the structures
{('4TSV', 0, ' '): , ('4TSV', 0, 'A'): }
The creation of such a table is quite expensive so it is created for the structure entity, but there is no reason why you should not create a table for e.g. a chain if you need it.
.. doctest::
>>> some_model = structure.values()[0]
>>> some_chain = some_model.values()[0]
>>> some_chain.setTable()
>>> # some_chain.table['R'] # all the residues
There is however a catch. Tables are not dynamic, this means that they are not magically updated whenever a child changes it's id. This can be easily seen in following example where a new chain is created a residue moved into it. A table is created for the chain, but it does not update the key after the child changes it's name.
.. doctest::
>>> from cogent.core.entity import Chain # the chain entity
>>> new_chain = Chain('J') # an ampty chain named 'J'
>>> new_chain.getId()
('J',)
>>> some_residue = structure.table['R'].values()[0] # a semi-random residue from structure
>>> # a possible output:
>>> some_residue.setName('001') # change the name to '001'
>>> # some_residue.getId() # should return e.g. (('001', 39, ' '),)
>>> # some_residue.getFull_id() # should return ('4TSV', 0, 'A', ('001', 39, ' '))
>>> new_chain.addChild(some_residue) # move from chain 'A' in 4TSV into chain 'J'
>>> # new_chain.keys() # should return: [(('001', 39, ' '),)]
>>> new_chain.setTable()
>>> # new_chain.table['R'].keys() # should return: [('J', ('001', 39, ' '))]
>>> some_residue.setName('002') # change the name to '002'
>>> # new_chain.keys() # should return: [(('002', 39, ' '),)] # updated!
>>> # new_chain.table['R'].keys() # should return [('J', ('001', 39, ' '))] not updated
>>> new_chain.setTable(force =True) # update table
>>> # new_chain.table['R'].keys() # should return [('J', ('002', 39, ' '))] updated
It is important to realize that Python dictionaries are not sorted so the order of two equal dictionaries is not the same. Each time a child is changed in a way that affects the parent e.g. a part of it's id changes the parent dictionary will be updated and the order might also. You should **never** assume that an entity has a particular order.
.. doctest::
>>> some_residue = some_chain.values()[0]
>>> old_id = some_residue.getId() # e.g. (('ILE', 154, ' '),)
>>> some_residue.setName('VAL')
>>> new_id = some_residue.getId() # e.g. (('VAL', 154, ' '),)
>>> some_chain.getChildren([old_id]) # nothin... not valid anymore
[]
>>> # some_chain.getChildren([new_id]) # e.g. []
But the the table of an entity is static and does not get updated.
.. doctest::
>>> some_full_id = some_residue.getFull_id() # entities in tables are stored using their full ids!!
>>> # some_chain.table['R'][some_full_id] # should raise a KeyError
>>> some_chain.setTable() # we make a new table
>>> some_chain.table['R'][some_full_id]
It is important to note that the table is a simple dictionary and the entity specific methods like ``getChildren`` are not available. You can figure out whether the table is up-to-date (or at least I hope I managed to code it right) using the ``modified`` attribute.
.. doctest::
>>> some_chain.modified
False
If the result were ``True`` the residue has been modified and might require to use the ``setTable``, or in some cases ``updateIds()`` methods.
.. doctest::
>>> some_chain.setTable()
>>> some_chain.updateIds()
Do not run those methods if you do not need to as they take some time.
The loop to run a child method can be implicitly omitted by using the dispatch method. It calls the method for every child.
.. doctest::
>>> some_model = structure.values()[0]
>>> some_chain = some_model.values()[1]
>>> some_chain.dispatch('setName', 'UNK')
>>> some_chain.modified
True
The above method has exactly the same effect as the loop. All residues within the chain will have the name set to 'UNK'. You can verify that the id's and dictionary keys got updated.:
.. code-block:: python
some_chain.keys()[0] # output random e.g. (('UNK', 260, ' '),)
some_chain.values()[0] # e.g.
PyCogent-1.5.3/doc/examples/handling_tabular_data.rst 000755 000765 000024 00000000000 12024703642 032321 2../../tests/test_util/test_table.rst ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/doc/examples/hmm_par_heterogeneity.rst 000644 000765 000024 00000025533 11473355707 023757 0 ustar 00jrideout staff 000000 000000 .. _rate-heterogeneity-hmm:
Evaluate process heterogeneity using a Hidden Markov Model
==========================================================
.. sectionauthor:: Gavin Huttley
The existence of rate heterogeneity in the evolution of biological sequences is well known. Typically such an evolutionary property is evaluated using so-called site-heterogeneity models. These models postulate the existence of discrete classes of sites, where sites within a class evolve according to a specific rate that is distinct from the rates of the other classes. These models retain the assumption that alignment columns evolve independently. One can naturally ask the question of whether rate classes occur randomly throughout the sequence or whether they are in fact auto-correlated - meaning sites of a class tend to cluster together. Because we do not have, *a priori*, a basis for classifying the sites the models are specified such that each column can belong to any of the designated site classes and the likelihood is computed across all possible classifications. Post numerical optimisation we can calculate the posterior probability a site column belongs to a specific site class. In ``cogent``, site classes are referred to as ``bins`` and so we refer to bin probabilities etc ...
To illustrate how to evaluate these hypotheses formally we specify 3 nested hypotheses: (i) Ho: no rate heterogeneity; (ii) Ha(1): two classes of sites - fast and slow, but independent sites; (iii) Ha(2): fast and slowly evolving sites are auto-correlated (meaning a sites class is correlated with that of its' immediate neighbours).
It is also possible to apply these models to different types of changes and we illustrate this with a single parameterisation at the end.
First import standard components necessary for all of the following calculations. As the likelihood ratio tests (LRT) involve nested hypotheses we will employ the chi-square approximation for assessing statistical significance.
.. doctest::
>>> from cogent.evolve.substitution_model import Nucleotide, predicate
>>> from cogent import LoadSeqs, LoadTree
>>> from cogent.maths.stats import chisqprob
Load the alignment and tree.
.. doctest::
>>> aln = LoadSeqs("data/long_testseqs.fasta")
>>> tree = LoadTree("data/test.tree")
Model Ho: no rate heterogeneity
-------------------------------
We define a HKY model of nucleotide substitution, which has a transition parameter. This is defined using the ``MotifChange`` class, by specifying a transition as **not** a transversion (``~MotifChange('R','Y')``).
.. doctest::
>>> MotifChange = predicate.MotifChange
>>> treat_gap = dict(recode_gaps=True, model_gaps=False)
>>> kappa = (~MotifChange('R', 'Y')).aliased('kappa')
>>> model = Nucleotide(predicates=[kappa], **treat_gap)
We specify a null model with no bins, and optimise it.
.. doctest::
>>> lf_one = model.makeLikelihoodFunction(tree, digits=2, space=3)
>>> lf_one.setAlignment(aln)
>>> lf_one.optimise()
>>> lnL_one = lf_one.getLogLikelihood()
>>> df_one = lf_one.getNumFreeParams()
>>> print lf_one
Likelihood Function Table
=====
kappa
-----
4.10
-----
===========================
edge parent length
---------------------------
Human edge.0 0.03
HowlerMon edge.0 0.04
edge.0 edge.1 0.04
Mouse edge.1 0.28
edge.1 root 0.02
NineBande root 0.09
DogFaced root 0.11
---------------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
Model Ha(1): two classes of gamma distributed but independent sites
-------------------------------------------------------------------
Our next hypothesis is that there are two rate classes, or bins, with rates gamma distributed. We will restrict the bin probabilities to be equal.
.. doctest::
>>> bin_submod = Nucleotide(predicates=[kappa], ordered_param='rate',
... distribution='gamma', **treat_gap)
>>> lf_bins = bin_submod.makeLikelihoodFunction(tree, bins=2,
... sites_independent=True, digits=2, space=3)
>>> lf_bins.setParamRule('bprobs', is_constant=True)
>>> lf_bins.setAlignment(aln)
>>> lf_bins.optimise(local=True)
>>> lnL_bins = lf_bins.getLogLikelihood()
>>> df_bins = lf_bins.getNumFreeParams()
>>> assert df_bins == 9
>>> print lf_bins
Likelihood Function Table
==================
kappa rate_shape
------------------
4.38 1.26
------------------
===========================
edge parent length
---------------------------
Human edge.0 0.03
HowlerMon edge.0 0.04
edge.0 edge.1 0.04
Mouse edge.1 0.31
edge.1 root 0.02
NineBande root 0.10
DogFaced root 0.12
---------------------------
====================
bin bprobs rate
--------------------
bin0 0.50 0.41
bin1 0.50 1.59
--------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
Model Ha(2): fast and slowly evolving sites are auto-correlated
---------------------------------------------------------------
We then specify a model with switches for changing between site-classes, the HMM part. The setup is almost identical to that for above with the sole difference being setting the ``sites_independent=False``.
.. doctest::
>>> lf_patches = bin_submod.makeLikelihoodFunction(tree, bins=2,
... sites_independent=False, digits=2, space=3)
>>> lf_patches.setParamRule('bprobs', is_constant=True)
>>> lf_patches.setAlignment(aln)
>>> lf_patches.optimise(local=True)
>>> lnL_patches = lf_patches.getLogLikelihood()
>>> df_patches = lf_patches.getNumFreeParams()
>>> print lf_patches
Likelihood Function Table
===============================
bin_switch kappa rate_shape
-------------------------------
0.56 4.42 1.16
-------------------------------
===========================
edge parent length
---------------------------
Human edge.0 0.03
HowlerMon edge.0 0.04
edge.0 edge.1 0.04
Mouse edge.1 0.31
edge.1 root 0.02
NineBande root 0.10
DogFaced root 0.12
---------------------------
====================
bin bprobs rate
--------------------
bin0 0.50 0.39
bin1 0.50 1.61
--------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
We use the following short function to compute the LR test statistic.
.. doctest::
>>> LR = lambda alt, null: 2 * (alt - null)
We conduct the test between the sequentially nested models.
.. doctest::
>>> lr = LR(lnL_bins, lnL_one)
>>> print lr
22...
>>> print "%.4f" % chisqprob(lr, df_patches-df_bins)
0.0000
The stationary bin probabilities are labelled as ``bprobs`` and can be obtained as follows.
.. doctest::
>>> bprobs = lf_patches.getParamValue('bprobs')
>>> print "%.1f : %.1f" % tuple(bprobs)
0.5 : 0.5
Of greater interest here (given the model was set up so the bin probabilities were equal, i.e. ``is_constant=True``) are the posterior probabilities as those allow classification of sites. The result is a ``DictArray`` class instance, which behaves like a dictionary.
.. doctest::
>>> pp = lf_patches.getBinProbs()
If we want to know the posterior probability the 21st position belongs to ``bin0``, we can determine it as:
.. doctest::
>>> print pp['bin0'][20]
0.8...
A model with patches of ``kappa``
---------------------------------
In this example we model sequence evolution where there are 2 classes of sites distinguished by their ``kappa`` parameters. We need to know what value of ``kappa`` to specify the delineation of the bin boundaries. We can determine this from the null model (``lf_one``). For this use case, we also need to use a ``numpy.array``, so we'll import that.
.. todo::
**FOR RELEASE** did we fix this silliness of requiring a nump.array?
.. doctest::
>>> from numpy import array
>>> single_kappa = lf_one.getParamValue('kappa')
We then construct the substitution model in a different way to that when evaluating generic rate heterogeneity (above).
.. doctest::
>>> kappa_bin_submod = Nucleotide(predicates=[kappa], **treat_gap)
>>> lf_kappa = kappa_bin_submod.makeLikelihoodFunction(tree,
... bins = ['slow', 'fast'], sites_independent=False, digits=1,
... space=3)
To improve the likelihood fitting it is desirable to set starting values in the model that result in it's initial likelihood being that of the null model (or as close as possible). To do this, we're going to define an arbitrarily small value (``epsilon``) which we use to provide the starting value to the two bins as slightly smaller/greater than ``single_kappa`` for the slow/fast bins respectively. At the same time we set the upper/lower bin boundaries.
.. doctest::
>>> epsilon = 1e-6
>>> lf_kappa.setParamRule(kappa, init=single_kappa-epsilon,
... upper=single_kappa, bin='slow')
>>> lf_kappa.setParamRule(kappa, init=single_kappa+epsilon,
... lower=single_kappa, bin='fast')
We then illustrate how to adjust the bin probabilities, here doing it so that one of them is nearly 1, the other nearly 0. This ensures the likelihood will be near identical to that of ``lf_one`` and as a result the optimisation step will actually improve fit over the simpler model.
.. doctest::
>>> lf_kappa.setParamRule('bprobs',
... init=array([1.0-epsilon, 0.0+epsilon]))
>>> lf_kappa.setAlignment(aln)
>>> lf_kappa.optimise(local=True)
>>> print lf_kappa
Likelihood Function Table
==========
bin_switch
----------
0.6
----------
=====================
bin bprobs kappa
---------------------
slow 0.8 3.0
fast 0.2 23.3
---------------------
===========================
edge parent length
---------------------------
Human edge.0 0.0
HowlerMon edge.0 0.0
edge.0 edge.1 0.0
Mouse edge.1 0.3
edge.1 root 0.0
NineBande root 0.1
DogFaced root 0.1
---------------------------
==============
motif mprobs
--------------
T 0.2
C 0.2
A 0.4
G 0.2
--------------
>>> print lf_kappa.getLogLikelihood()
-8749.3...
PyCogent-1.5.3/doc/examples/index.rst 000644 000765 000024 00000004075 11443272207 020474 0 ustar 00jrideout staff 000000 000000 #####################
Cogent Usage Examples
#####################
**************************************
A Note on the Computable Documentation
**************************************
The following examples are all available as standalone text files which can be computed using the Python doctest module.
*****************
Data manipulation
*****************
.. toctree::
:maxdepth: 1
translate_dna
seq_features
complete_seq_features
reverse_complement
align_codons_to_protein
aln_profile
genetic_code_aa_index
handling_tabular_data
handling_3dstructures
entity_selection
query_ncbi
query_ensembl
manipulating_tree_nodes
**********************************
Controlling 3rd party applications
**********************************
.. toctree::
:maxdepth: 1
application_controller_framework
building_and_using_an_application_controller
alignment_app_controllers
phylogeny_app_controllers
generating_app_commandlines
*********************
General data analysis
*********************
.. toctree::
:maxdepth: 1
goodness_of_fit
perform_PCoA_analysis
perform_nmds
motif_results
unifrac
period_estimation
******************
Data Visualisation
******************
.. toctree::
:maxdepth: 1
draw_dendrogram
draw_dotplot
*******************
Modelling Evolution
*******************
.. toctree::
:maxdepth: 1
simple
relative_rate
neutral_test
scope_model_params_on_trees
codon_models
empirical_protein_models
testing_multi_loci
reuse_results
unrestricted_nucleotide
simulate_alignment
parametric_bootstrap
estimate_startingpoint
coevolution
rate_heterogeneity
hmm_par_heterogeneity
seqsim_alignment_simulation
seqsim_aln_sim_user_alphabet
seqsim_tree_sim
***************************
Phylogenetic Reconstruction
***************************
.. toctree::
:maxdepth: 1
calculate_pairwise_distances
calculate_neigbourjoining_tree
calculate_UPGMA_cluster
phylo_by_ls
maketree_from_proteinseqs
PyCogent-1.5.3/doc/examples/maketree_from_proteinseqs.rst 000644 000765 000024 00000004304 11425201333 024624 0 ustar 00jrideout staff 000000 000000 Making a phylogenetic tree from a protein sequence alignment
============================================================
.. sectionauthor:: Gavin Huttley
In this example we pull together the distance calculation and tree building with the additional twist of using an empirical protein substitution matrix. We will therefore be computing the tree from a protein sequence alignment. We will first do the standard cogent import for ``LoadSeqs``.
.. doctest::
>>> from cogent import LoadSeqs, PROTEIN
We will use an empirical protein substitution matrix.
.. doctest::
>>> from cogent.evolve.models import JTT92
The next components we need are for computing the matrix of pairwise sequence distances and then for estimating a neighbour joining tree from those distances.
.. doctest::
>>> from cogent.phylo import nj, distance
Now load our sequence alignment, explicitly setting the alphabet to be protein.
.. doctest::
>>> aln = LoadSeqs('data/abglobin_aa.phylip', interleaved=True,
... moltype=PROTEIN)
Create an Empirical Protein Matrix Substitution model object. This will take the unscaled empirical matrix and use it and the motif frequencies to create a scaled Q matrix.
.. doctest::
>>> sm = JTT92()
We now use this and the alignment to construct a distance calculator.
.. doctest::
>>> d = distance.EstimateDistances(aln, submodel = sm)
>>> d.run()
The resulting distances are passed to the nj function.
.. doctest::
>>> mytree = nj.nj(d.getPairwiseDistances())
The shape of the resulting tree can be readily view by printing ``mytree.asciiArt()``. The result will be equivalent to.
.. code-block:: python
/-human
|
| /-rabbit
-root----|-edge.1--|
| \-rat
|
| /-goat-cow
\edge.0--|
\-marsupial
This tree can be saved to file, the ``with_distances`` argument specifies that branch lengths are to be included in the newick formatted output.
.. doctest::
>>> mytree.writeToFile('test_nj.tree', with_distances=True)
.. clean up
.. doctest::
:hide:
>>> import os
>>> os.remove('test_nj.tree')
PyCogent-1.5.3/doc/examples/manipulating_tree_nodes.rst 000644 000765 000024 00000020323 11213036343 024250 0 ustar 00jrideout staff 000000 000000 Manipulation of Tree Node Objects
=================================
.. sectionauthor:: Tony Walters
Examples of how to initialize and manipulate various tree node objects.
.. doctest ::
>>> from cogent.core.tree import PhyloNode
>>> from cogent import LoadTree
>>> from cogent.parse.tree import DndParser
The general method to initialize a tree is ``LoadTree``, however, for exceptionally large trees or if one needs to specify the node objects (``TreeNode``, ``PhyloNode``, or ``RangeNode``), ``DndParser`` should be used. ``LoadTree`` uses ``PhyloNode`` objects by default.
The basic properties of the tree node objects are:
* ``TreeNode`` objects are general purpose in nature, and lack phylogenetic distance values.
* ``PhyloNode`` objects inherit the methods of the ``TreeNode`` class and in addition contain phylogenetic distances.
* ``RangeNode`` objects contain evolution simulation methods in addition to the standard features of a ``PhyloNode``.
The following demonstrates the two methods for initializing a phylogenetic tree object.
.. doctest ::
>>> simple_tree_string="(B:0.2,(C:0.3,D:0.4)E:0.5)F;"
>>> complex_tree_string="(((363564 AB294167.1 Alkalibacterium putridalgicola:0.0028006,55874 AB083411.1 Marinilactibacillus psychrotolerans:0.0022089):0.40998,(15050 Y10772.1 Facklamia hominis:0.32304,(132509 AY707780.1 Aerococcus viridans:0.58815,((143063 AY879307.1 Abiotrophia defectiva:0.5807,83619 AB042060.1 Bacillus schlegelii:0.23569):0.03586,169722 AB275483.1 Fibrobacter succinogenes:0.38272):0.06516):0.03492):0.14265):0.63594,(3589 M62687.1 Fibrobacter intestinalis:0.65866,314063 CP001146.1 Dictyoglomus thermophilum:0.38791):0.32147,276579 EU652053.1 Thermus scotoductus:0.57336);"
>>> simple_tree=LoadTree(treestring=simple_tree_string)
>>> complex_tree=DndParser(complex_tree_string, PhyloNode)
Now to displaying, creating, deleting, and inserting a node in simple_tree. Note that simple_tree has three tips, one internal node 'E', and the root 'F.' For this example, we will create a node named 'A', with a distance of 0.1, delete the node 'C' through its parent, the internal node 'E', and finally we will insert 'A' where 'C' once was.
Display the original tree.
.. doctest ::
>>> print simple_tree.asciiArt()
/-B
-F-------|
| /-C
\E-------|
\-D
Create a new node object.
.. doctest ::
>>> A_node=PhyloNode(Name='A',Length=0.1)
Display the children of the root node, one of which is the parent of the tip we wish to alter. To add or remove a node, we need to use the parent of the target node, which in this case is the internal node 'E.'
.. doctest ::
>>> print simple_tree.Children
[Tree("B;"), Tree("(C,D)E;")]
Remove the 'C' tip. **Note:** ``remove()`` and ``removeNode()`` return 'True' if a node is removed, 'False' if they cannot remove a node.
.. doctest ::
>>> simple_tree.Children[1].remove('C')
True
Insert the new 'A' tip where 'C' was previously.
.. doctest ::
>>> simple_tree.Children[1].insert(0,A_node)
Finally, display the modified tree.
.. doctest ::
>>> print simple_tree.asciiArt()
/-B
-F-------|
| /-A
\E-------|
\-D
When deleting tree nodes, it is often desirable to clean up any unbranched internal nodes that may have resulted from removal of tips. For example, if we wanted to delete the node 'A' that was previously added, the resulting tree would have an unbranched internal node 'E.'
.. doctest ::
>>> simple_tree.Children[1].remove('A')
True
>>> print simple_tree.asciiArt()
/-B
-F-------|
\E------- /-D
With the ``prune()`` method, internal nodes with only a single branch are removed.
.. doctest ::
>>> simple_tree.prune()
>>> print simple_tree.asciiArt()
/-B
-F-------|
\-D
An Example of Conditional Tree Node Modifications
=================================================
Now to look at the more complex and realistic tree. In complex_tree, there are no internal nodes or a defined root. In order to display this tree in a more succinct manner, we can rename these tips to only contain the genus and species names. To step through the tips only, we can use the ``iterTips()`` iterator, and rename each node. The ``asciiArt()`` function, by default, will attempt to display internal nodes; this can be suppressed by the parameter ``show_internal=False``.
First, let's split the ungainly name string for each tip and only preserve the genus and species component, separated by a space.
.. doctest ::
>>> for n in complex_tree.iterTips():
... n.Name=n.Name.split()[2]+" "+n.Name.split()[3]
Now we display the tree with ``asciiArt()``.
.. doctest ::
>>> print complex_tree.asciiArt(show_internal=False)
/-Alkalibacterium putridalgicola
/--------|
| \-Marinilactibacillus psychrotolerans
/--------|
| | /-Facklamia hominis
| | |
| \--------| /-Aerococcus viridans
| | |
| \--------| /-Abiotrophia defectiva
| | /--------|
---------| \--------| \-Bacillus schlegelii
| |
| \-Fibrobacter succinogenes
|
| /-Fibrobacter intestinalis
|---------|
| \-Dictyoglomus thermophilum
|
\-Thermus scotoductus
For another example of manipulating a phylogenetic tree, let us suppose that we want to remove any species in the tree that are not closely related to *Aerococcus viridans*. To do this, we will delete any nodes that have a greater phylogenetic distance than 1.8 from *Aerococcus viridans*. The best method to remove a large number of nodes from a tree is to first create a list of nodes to delete, followed by the actual removal process. It is important that the ``prune()`` function be called after deletion of each node to ensure that internal nodes whose tips are deleted are removed instead of becoming tips. Alternatively, one could test for internal nodes whose children are deleted in the procedure and flag these nodes to be deleted as well.
First, generate a list of tip nodes.
.. doctest ::
>>> tips=complex_tree.tips()
Next, iterate through this list, compare the distances to *Aerococcus*, and append to the deletion list if greater than 1.8.
.. doctest ::
>>> tips_to_delete=[]
>>> AEROCOCCUS_INDEX=3
>>> for n in tips:
... if tips[AEROCOCCUS_INDEX].distance(n)>1.8:
... tips_to_delete.append(n)
Now for the actual deletion process. We can simply use the parent of each node in the deletion list to remove itself. Pruning is necessary to prevent internal nodes from being left as tips. **Note:** ``remove()`` and ``removeNode()`` return 'True' if a node is successfully removed, 'False' otherwise.
.. doctest ::
>>> for n in tips_to_delete:
... n.Parent.remove(n)
... complex_tree.prune()
True
True
True
Finally, print the modified complex_tree.
.. doctest ::
>>> print complex_tree.asciiArt(show_internal=False)
/-Alkalibacterium putridalgicola
/--------|
| \-Marinilactibacillus psychrotolerans
--------- /--------|
| /-Facklamia hominis
| |
\--------| /-Aerococcus viridans
| |
\--------| /-Abiotrophia defectiva
| /--------|
\--------| \-Bacillus schlegelii
|
\-Fibrobacter succinogenes
PyCogent-1.5.3/doc/examples/motif_results.rst 000644 000765 000024 00000013225 11357233473 022267 0 ustar 00jrideout staff 000000 000000 Motif results example
=====================
.. sectionauthor:: Jeremy Widmann
In this example we will be parsing a motif results file and doing some basic operations highlighting the features of the various core motif handling objects. We first want to import the necessary modules.
.. doctest::
>>> from cogent import LoadSeqs
>>> from cogent.parse.meme import MemeParser
Now we want to parse the MEME (http://meme.sdsc.edu) motif results file and the fasta file that we passed to MEME originally. This will construct a ``MotifResults`` object and a ``SequenceCollection`` object respectively, then add the ``SequenceCollection`` to the ``MotifResults``.
.. doctest::
>>> results = MemeParser(open('data/motif_example_meme_results.txt','U'))
>>> seqs = LoadSeqs('data/motif_example.fasta',aligned=False)
>>> results.Alignment = seqs
Lets quickly look at an overview of the ``MotifResults``. First, we can check the ``MolType`` of the sequences, how many sequences were searched, and how many distinct motifs were found.
.. doctest::
>>> results.MolType.label
'protein'
>>> len(results.Alignment.NamedSeqs)
96
>>> len(results.Motifs)
10
Here 10 unique motifs were found searching 96 protein sequences. Now lets look in more detail at the motifs that were found by MEME. The ``MotifResults`` object has a list of ``Motif`` objects. Each ``Motif`` object contains a list of ``Module`` objects that make up the motif. In this example, each ``Motif`` has only one ``Module``. Show the module ID, Evalue, and number of instances of the module in the set of sequences.
.. doctest::
>>> for motif in results.Motifs:
... module = motif.Modules[0]
... print module.ID, module.Evalue, len(module.NamedSeqs)
...
1 0.0 50
2 7.3e-239 41
3 2.2e-254 45
4 7.8e-153 37
5 2.9e-120 13
6 2e-99 29
7 4.2e-54 20
8 6.1e-41 29
9 3.5e-15 9
10 5.3e-14 7
Module 1 has the smallest Evalue and the most instances, so we'll look at this one in more detail. The ``Module`` object is a subclass of the core ``Alignment`` object, so it shares much of this functionality. We can look at the consensus sequence for Module 1 calculated in different ways. Lets compare the consensus that MEME provides, the calculated majority consensus, and the calculated IUPAC consensus.
.. doctest::
>>> module_1 = results.Motifs[0].Modules[0]
>>> module_1.ID
'1'
>>> module_1.ConsensusSequence
'GKPVVVDFWATWCGPCRxEAPILEELAKE'
>>> module_1.majorityConsensus(transform=str)
'GKPVVVDFWATWCGPCRAEAPILEELAKE'
>>> module_1.IUPACConsensus()
'XXXXXXXXXXXXCXXCXXXXXXXXXXXXX'
Here we can see that the consensus sequences provided by MEME and the calculated majority consensus are about the same. The IUPAC consensus is an easy way to see if any positions in the module are absolutely conserved. To get a better idea of the conservation of the module, we can calculate the uncertainties for every position in the module.
.. doctest::
>>> iupac = module_1.IUPACConsensus()
>>> majority = module_1.majorityConsensus()
>>> uncertainty = module_1.uncertainties()
>>> for i,m,u in zip(iupac,majority,uncertainty):
... print i,m,u
...
X G 2.69585768303
X K 2.29582593843
X P 2.96578451217
X V 1.61117952123
X V 1.91067699662
X V 2.01512726036
X D 1.57769736083
X F 0.777268500731
X W 2.0045407601
X A 0.522179190202
X T 2.70369216641
X W 0.282292189082
C C 0.0
X G 1.96072818839
X P 0.937268500731
C C 0.0
X R 2.03875770182
X A 3.68637013016
X E 2.60359082041
X A 2.9672863748
X P 0.282292189082
X I 3.49915032218
X L 2.19664948376
X E 2.71346937346
X E 2.49058231553
X L 1.94895812367
X A 2.71230564207
X K 2.85533775047
X E 2.36191706121
The first column is the IUPAC consensus symbol, the second column is the majority consensus symbol, and the third column is the uncertainty at a given position in the module. The smaller the number, the less uncertainty, and therefore the more conserved the majority residue is at that position. Now that we have examined Module 1 in some detail, lets do some more simple tasks. How many different sequences is Module 1 located in?
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> module_1.LocationDict
{'18309723': [284], '15614085': [58], '15966937': [59], ...
>>> len(module_1.LocationDict)
49
The ``LocationDict`` property of the ``Module`` object is a dictionary of sequences IDs and indices in the sequence where the module was found. Here we see that Module 1 was found in 49 different sequences, which means that it was found twice in one sequence. We can find what other modules were found to have more than one instance in a given sequence.
.. doctest::
>>> for motif in results.Motifs:
... module = motif.Modules[0]
... for seq_id, indices in module.LocationDict.items():
... if len(indices) > 1:
... print module.ID, seq_id, indices
...
1 18406743 [42, 362]
3 18406743 [104, 264, 424]
We see that Module 1 and Module 3 have more than one instance in sequence 18406743. Since this sequence is the only one to contain multiple instances of the same module, lets quickly examine some statistics of the alignment.
.. doctest::
>>> len(results.Alignment.NamedSeqs['18406743'])
578
>>> lengths = [len(seq) for seq in results.Alignment.Seqs]
>>> min(lengths)
89
>>> max(lengths)
578
>>> sum(lengths)/float(len(lengths))
169.86458333333334
This sequence is the longest of all the sequences searched and more than 3 times longer than the average sequence.
PyCogent-1.5.3/doc/examples/neutral_test.rst 000644 000765 000024 00000010760 11425201333 022064 0 ustar 00jrideout staff 000000 000000 A test of the neutral theory
============================
.. sectionauthor:: Gavin Huttley
This file contains an example for performing a likelihood ratio test of neutrality. The test compares a model where the codon model parameter omega is constrained to be the same for all edges against one where each edge has its' own omega. From cogent import all the components we need.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree
>>> from cogent.evolve.models import MG94GTR
>>> from cogent.maths import stats
Get your alignment and tree.
.. doctest::
>>> al = LoadSeqs("data/long_testseqs.fasta")
>>> t = LoadTree("data/test.tree")
We use a Goldman Yang 1994 model.
.. doctest::
>>> sm = MG94GTR()
Make the controller object
.. doctest::
>>> lf = sm.makeLikelihoodFunction(t, digits=2, space=2)
Get the likelihood function object this object performs the actual likelihood calculation.
.. doctest::
>>> lf.setAlignment(al)
By default, parameters other than branch lengths are treated as global in scope, so we don't need to do anything special here. We can influence how rigorous the optimisation will be, and switch between the global and local optimisers provided in the toolkit using arguments to the optimise method. The ``global_tolerance=1.0`` argument specifies conditions for an early break from simulated annealing which will be automatically followed by the Powell local optimiser. .. note:: the 'results' are of course nonsense.
.. doctest::
>>> lf.optimise(global_tolerance = 1.0)
View the resulting maximum-likelihood parameter values
.. doctest::
>>> print lf
Likelihood Function Table
===================================
A/C A/G A/T C/G C/T omega
-----------------------------------
1.02 3.36 0.73 0.95 3.71 0.90
-----------------------------------
=========================
edge parent length
-------------------------
Human edge.0 0.09
HowlerMon edge.0 0.12
edge.0 edge.1 0.12
Mouse edge.1 0.84
edge.1 root 0.06
NineBande root 0.28
DogFaced root 0.34
-------------------------
=============
motif mprobs
-------------
T 0.23
C 0.19
A 0.37
G 0.21
-------------
We'll get the lnL and number of free parameters for later use.
.. doctest::
>>> null_lnL = lf.getLogLikelihood()
>>> null_nfp = lf.getNumFreeParams()
Specify each edge has it's own omega by just modifying the existing ``lf``. This means the new function will start with the above values.
.. doctest::
>>> lf.setParamRule("omega", is_independent = True)
Optimise the likelihood function, this time just using the local optimiser.
.. doctest::
>>> lf.optimise(local = True)
View the resulting maximum-likelihood parameter values.
.. doctest::
>>> print lf
Likelihood Function Table
============================
A/C A/G A/T C/G C/T
----------------------------
1.03 3.38 0.73 0.95 3.72
----------------------------
================================
edge parent length omega
--------------------------------
Human edge.0 0.09 0.59
HowlerMon edge.0 0.12 0.96
edge.0 edge.1 0.11 1.13
Mouse edge.1 0.83 0.92
edge.1 root 0.06 0.39
NineBande root 0.28 1.28
DogFaced root 0.34 0.84
--------------------------------
=============
motif mprobs
-------------
T 0.23
C 0.19
A 0.37
G 0.21
-------------
Get out an annotated tree, it looks just like a tree, but has the maximum-likelihood parameter estimates attached to each tree edge. This object can be used for plotting, or to provide starting estimates to a related model.
.. doctest::
>>> at = lf.getAnnotatedTree()
The lnL's from the two models are now used to calculate the likelihood ratio statistic (``LR``) it's degrees-of-freedom (``df``) and the probability (``P``) of observing the LR.
.. doctest::
>>> LR = 2 * (lf.getLogLikelihood() - null_lnL)
>>> df = lf.getNumFreeParams() - null_nfp
>>> P = stats.chisqprob(LR, df)
Print this and look up a chi-sq with number of edges - 1 degrees of freedom.
.. doctest::
>>> print "Likelihood ratio statistic = ", LR
Likelihood ratio statistic = 8...
>>> print "degrees-of-freedom = ", df
degrees-of-freedom = 6
>>> print "probability = ", P
probability = 0.2...
PyCogent-1.5.3/doc/examples/parametric_bootstrap.rst 000644 000765 000024 00000004613 11425201333 023577 0 ustar 00jrideout staff 000000 000000 .. _parametric-bootstrap:
Performing a parametric bootstrap
=================================
.. sectionauthor:: Gavin Huttley
This file contains an example for estimating the probability of a Likelihood ratio statistic obtained from a relative rate test. The bootstrap classes can take advantage of parallel architectures.
From cogent import all the components we need.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree
>>> from cogent.evolve import bootstrap
>>> from cogent.evolve.models import HKY85
>>> from cogent.maths import stats
Define the null model that takes an alignment object and returns a likelihood function properly assembled for optimising the likelihood under the null hypothesis. The sample distribution is generated using this model.
We will use a HKY model.
.. doctest::
>>> def create_alt_function():
... t = LoadTree("data/test.tree")
... sm = HKY85()
... return sm.makeLikelihoodFunction(t)
Define a function that takes an alignment object and returns an appropriately assembled function for the alternative model. Since the two models are identical bar the constraint on the branch lengths, we'll use the same code to generate the basic likelihood function as for the alt model, and then apply the constraint here
.. doctest::
>>> def create_null_function():
... lf = create_alt_function()
... # set the local clock for humans & howler monkey
... lf.setLocalClock("Human", "HowlerMon")
... return lf
Get our observed data alignment
.. doctest::
>>> aln = LoadSeqs(filename = "data/long_testseqs.fasta")
Create a ``EstimateProbability`` bootstrap instance
.. doctest::
>>> estimateP = bootstrap.EstimateProbability(create_null_function(),
... create_alt_function(),
... aln)
Specify how many random samples we want it to generate. Here we use a very small number of replicates only for the purpose of testing.
.. doctest::
>>> estimateP.setNumReplicates(5)
Run it.
.. doctest::
>>> estimateP.run()
Get the estimated probability.
.. doctest::
>>> p = estimateP.getEstimatedProb()
``p`` is a floating point value, as you'd expect. Grab the estimated likelihoods (null and alternate) for the observed data.
.. doctest::
>>> print '%.2f, %.2f' % estimateP.getObservedlnL()
-8751.94, -8750.59
PyCogent-1.5.3/doc/examples/perform_nmds.rst 000644 000765 000024 00000003031 11213034174 022041 0 ustar 00jrideout staff 000000 000000 Perform Nonmetric Multidimensional Scaling
==========================================
.. sectionauthor:: Justin Kuczynski
An example of how to use nmds.
.. doctest::
>>> from cogent.cluster.nmds import NMDS
>>> from cogent.maths.distance_transform import dist_euclidean
>>> from numpy import array
We start with an abundance matrix, samples (rows) by sequences/species (cols)
.. doctest::
>>> abundance = array(
... [[7,1,0,0,0,0,0,0,0],
... [4,2,0,0,0,1,0,0,0],
... [2,4,0,0,0,1,0,0,0],
... [1,7,0,0,0,0,0,0,0],
... [0,8,0,0,0,0,0,0,0],
... [0,7,1,0,0,0,0,0,0],#idx 5
... [0,4,2,0,0,0,2,0,0],
... [0,2,4,0,0,0,1,0,0],
... [0,1,7,0,0,0,0,0,0],
... [0,0,8,0,0,0,0,0,0],
... [0,0,7,1,0,0,0,0,0],#idx 10
... [0,0,4,2,0,0,0,3,0],
... [0,0,2,4,0,0,0,1,0],
... [0,0,1,7,0,0,0,0,0],
... [0,0,0,8,0,0,0,0,0],
... [0,0,0,7,1,0,0,0,0],#idx 15
... [0,0,0,4,2,0,0,0,4],
... [0,0,0,2,4,0,0,0,1],
... [0,0,0,1,7,0,0,0,0]], 'float')
Then compute a distance matrix of your choosing, and perform nmds on that matrix
.. doctest::
>>> distmtx = dist_euclidean(abundance)
>>> nm = NMDS(distmtx, verbosity=0)
The NMDS object provides a list of points, which can be plotted if desired
.. doctest::
>>> pts = nm.getPoints()
>>> stress = nm.getStress()
With matplotlib installed, we could then do ``plt.plot(pts[:,0], pts[:,1])``
PyCogent-1.5.3/doc/examples/perform_PCoA_analysis.rst 000644 000765 000024 00000004502 11572751111 023576 0 ustar 00jrideout staff 000000 000000 Perform Principal Coordinates Analysis
======================================
.. sectionauthor:: Cathy Lozupone
An example of how to calculate the pairwise distances for a set of sequences.
.. doctest::
>>> from cogent import LoadSeqs
>>> from cogent.phylo import distance
>>> from cogent.cluster.metric_scaling import PCoA
Import a substitution model (or create your own)
.. doctest::
>>> from cogent.evolve.models import HKY85
Load the alignment.
.. doctest::
>>> al = LoadSeqs("data/test.paml")
Create a pairwise distances object calculator for the alignment, providing a substitution model instance.
.. doctest::
>>> d = distance.EstimateDistances(al, submodel= HKY85())
>>> d.run()
Now use this matrix to perform principal coordinates analysis.
.. doctest::
>>> PCoA_result = PCoA(d.getPairwiseDistances())
>>> print PCoA_result
======================================================================================
Type Label vec_num-0 vec_num-1 vec_num-2 vec_num-3 vec_num-4
--------------------------------------------------------------------------------------
Eigenvectors NineBande -0.02 0.01 0.04 0.01 0.00
Eigenvectors DogFaced -0.04 -0.06 -0.01 0.00 0.00
Eigenvectors HowlerMon -0.07 0.01 0.01 -0.02 0.00
Eigenvectors Mouse 0.20 0.01 -0.01 -0.00 0.00
Eigenvectors Human -0.07 0.04 -0.03 0.01 0.00
Eigenvalues eigenvalues 0.05 0.01 0.00 0.00 0.00
Eigenvalues var explained (%) 85.71 9.60 3.73 0.95 0.00
--------------------------------------------------------------------------------------
We can save these results to a file in a delimited format (we'll use tab here) that can be opened up in any data analysis program, like R or Excel. Here the principal coordinates can be plotted against each other for visualization.
.. doctest::
>>> PCoA_result.writeToFile('PCoA_results.txt',sep='\t')
..
We don't actually want to keep that file now, so I'm importing the ``os`` module to delete it.
.. doctest::
>>> import os
>>> os.remove('PCoA_results.txt')
PyCogent-1.5.3/doc/examples/period_estimation.rst 000644 000765 000024 00000021314 12014672411 023072 0 ustar 00jrideout staff 000000 000000 ***************************
Estimating periodic signals
***************************
.. sectionauthor:: Gavin Huttley, Julien Epps, Hua Ying
We consider two different scenarios:
- estimating the periods in a signal
- estimating the power for a given period
- measuring statistical significance for the latter case
Estimating the periods in a signal
==================================
For numerical (continuous) data
-------------------------------
We first make some sample data. A periodic signal and some noise.
..
We set a seed for the random number generator so that we can get
consistent generation of the same series. This makes the document
robust for doctesting.
.. doctest::
:hide:
>>> import numpy
>>> numpy.random.seed(11)
.. doctest::
>>> import numpy
>>> t = numpy.arange(0, 10, 0.1)
>>> n = numpy.random.randn(len(t))
>>> nse = numpy.convolve(n, numpy.exp(-t/0.05))*0.1
>>> nse = nse[:len(t)]
>>> sig = numpy.sin(2*numpy.pi*t) + nse
Discrete Fourier transform
^^^^^^^^^^^^^^^^^^^^^^^^^^
We now use the discrete Fourier transform to estimate periodicity in this signal. Given we set the period to equal 10, we expect the maximum power for that index.
.. doctest::
>>> from cogent.maths.period import dft
>>> pwr, period = dft(sig)
>>> print period
[ 2. 2.04081633 2.08333333 2.12765957 2.17391304
2.22222222 2.27272727 2.3255814 2.38095238 2.43902439
2.5 2.56410256 2.63157895 2.7027027 2.77777778
2.85714286 2.94117647 3.03030303 3.125 3.22580645...
>>> print pwr
[ 1.06015801 +0.00000000e+00j 0.74686707 -1.93971914e-02j
0.36784793 -2.66370366e-02j 0.04384413 +2.86970840e-02j
1.54473269 -2.43777386e-02j 0.28522968 -2.33602932e-01j...
The power (``pwr``) is returned as an array of complex numbers, so we convert into real numbers using ``abs``. We then zip the power and corresponding periods and sort to identify the period with maximum signal.
>>> pwr = abs(pwr)
>>> max_pwr, max_period = sorted(zip(pwr,period))[-1]
>>> print max_pwr, max_period
50.7685934719 10.0
Auto-correlation
^^^^^^^^^^^^^^^^
We now use auto-correlation.
.. doctest::
>>> from cogent.maths.period import auto_corr
>>> pwr, period = auto_corr(sig)
>>> print period
[ 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24...
>>> print pwr
[ 1.63366075e+01 -1.47309007e+01 -3.99310414e+01 -4.94779387e+01...
We then zip the power and corresponding periods and sort to identify the period with maximum signal.
.. doctest::
>>> max_pwr, max_period = sorted(zip(pwr,period))[-1]
>>> print max_pwr, max_period
46.7917300733 10
For symbolic data
-----------------
We create a sequence as just a string
.. doctest::
>>> s = 'ATCGTTGGGACCGGTTCAAGTTTTGGAACTCGCAAGGGGTGAATGGTCTTCGTCTAACGCTGG'\
... 'GGAACCCTGAATCGTTGTAACGCTGGGGTCTTTAACCGTTCTAATTTAACGCTGGGGGGTTCT'\
... 'AATTTTTAACCGCGGAATTGCGTC'
We then specify the motifs whose occurrences will be converted into 1, with all other motifs converted into 0. As we might want to do this in batches for many sequences we use a factory function.
.. doctest::
>>> from cogent.maths.stats.period import SeqToSymbols
>>> seq_to_symbols = SeqToSymbols(['AA', 'TT', 'AT'])
>>> symbols = seq_to_symbols(s)
>>> len(symbols) == len(s)
True
>>> symbols
array([1, 0, 0, 0, 1, 0, 0, 0, 0, 0...
We then estimate the integer discrete Fourier transform for the full data. To do this, we need to pass in the symbols from full conversion of the sequence. The returned values are the powers and periods.
.. doctest::
>>> from cogent.maths.period import ipdft
>>> powers, periods = ipdft(symbols)
>>> powers #doctest: +SKIP
array([ 3.22082108e-14, 4.00000000e+00, 9.48683298e+00,
6.74585634e+00, 3.46410162e+00, 3.20674669e+00,...
>>> periods
array([ 2, 3, 4...
We can also compute the auto-correlation statistic, and the hybrid (which combines IPDFT and auto-correlation).
.. doctest::
>>> from cogent.maths.period import auto_corr, hybrid
>>> powers, periods = auto_corr(symbols)
>>> powers
array([ 11., 9., 11., 9., 6...
>>> periods
array([ 2, 3, 4...
>>> powers, periods = hybrid(symbols)
>>> powers #doctest: +SKIP
array([ 3.54290319e-13, 3.60000000e+01, 1.04355163e+02,
6.07127071e+01, 2.07846097e+01, 2.88607202e+01,...
>>> periods
array([ 2, 3, 4...
Estimating power for specified period
=====================================
For numerical (continuous) data
-------------------------------
We just use ``sig`` created above. The Goertzel algorithm gives the same result as the ``dft``.
.. doctest::
>>> from cogent.maths.period import goertzel
>>> pwr = goertzel(sig, 10)
>>> print pwr
50.7685934719
For symbolic data
-----------------
.. take example above and show how to compute it using autocorrelation
We use the symbols from the above example. For the ``ipdft``, ``auto_corr`` and ``hybrid`` functions we just need to identify the array index containing the period of interest and slice the corresponding value from the returned powers. The reported periods start at ``llim``, which defaults to 2, but indexes start at 0, the index for a period-5 is simply 5-``llim``.
.. doctest::
>>> powers, periods = auto_corr(symbols)
>>> llim = 2
>>> period5 = 5-llim
>>> periods[period5]
5
>>> powers[period5]
9.0
For Fourier techniques, we can compute the power for a specific period more efficiently using Goertzel algorithm.
.. doctest::
>>> from cogent.maths.period import goertzel
>>> period = 4
>>> power = goertzel(symbols, period)
>>> ipdft_powers, periods = ipdft(symbols)
>>> ipdft_power = abs(ipdft_powers[period-llim])
>>> round(power, 6) == round(ipdft_power, 6)
True
>>> power
9.4868...
It's also possible to specify a period to the stand-alone functions. As per the ``goertzel`` function, just the power is returned.
.. doctest::
>>> power = hybrid(symbols, period=period)
>>> power
104.355...
Measuring statistical significance of periodic signals
======================================================
For numerical (continuous data)
-------------------------------
We use the signal provided above. Because significance testing is being done using a resampling approach, we define a calculator which precomputes some values to improve compute performance. For a continuous signal, we'll use the Goertzel algorithm.
.. doctest::
>>> from cogent.maths.period import Goertzel
>>> goertzel_calc = Goertzel(len(sig), period=10)
Having defined this, we then just pass this calculator to the ``blockwise_bootstrap`` function. The other critical settings are the ``block_size`` which specifies the size of segments of contiguous sequence positions to use for sampling and ``num_reps`` which is the number of permuted replicate sequences to generate.
.. doctest::
>>> from cogent.maths.stats.period import blockwise_bootstrap
>>> obs_stat, p = blockwise_bootstrap(sig, calc=goertzel_calc, block_size=10,
... num_reps=1000)
>>> print obs_stat
50.7685934719
>>> print p
0.0
For symbolic data
-----------------
Permutation testing
^^^^^^^^^^^^^^^^^^^
The very notion of permutation testing for periods, applied to a genome, requires the compute performance be as quick as possible. This means providing as much information up front as possible. We have made the implementation flexible by not assuming how the user will convert sequences to symbols. It's also the case that numerous windows of exactly the same size are being assessed. Accordingly, we use a class to construct a fixed signal length evaluator. We do this for the hybrid metric first.
.. doctest::
>>> from cogent.maths.period import Hybrid
>>> len(s)
150
>>> hybrid_calculator = Hybrid(len(s), period = 4)
.. note:: We defined the period length of interest in defining this calculator because we're interested in dinucleotide motifs.
We then construct a seq-to-symbol convertor.
.. doctest::
>>> from cogent.maths.stats.period import SeqToSymbols
>>> seq_to_symbols = SeqToSymbols(['AA', 'TT', 'AT'], length=len(s))
The rest is as per the analysis using ``Goertzel`` above.
.. doctest::
>>> from cogent.maths.stats.period import blockwise_bootstrap
>>> stat, p = blockwise_bootstrap(s, calc=hybrid_calculator,
... block_size=10, num_reps=1000, seq_to_symbols=seq_to_symbols)
...
>>> print stat
104.35...
>>> p < 0.1
True
PyCogent-1.5.3/doc/examples/phylo_by_ls.rst 000644 000765 000024 00000014674 11444532333 021716 0 ustar 00jrideout staff 000000 000000 Phylogenetic reconstruction by least squares
============================================
.. sectionauthor:: Gavin Huttley
We will load some pre-computed pairwise distance data. To see how that data was computed see the :ref:`calculating-pairwise-distances` example. That data is saved in a format called ``pickle`` which is native to python. As per usual, we import the basic components we need.
.. recompute the data matrix and then delete file at end
.. doctest::
:hide:
>>> from cogent import LoadSeqs
>>> from cogent.phylo import distance
>>> from cogent.evolve.models import HKY85
>>> al = LoadSeqs("data/long_testseqs.fasta")
>>> d = distance.EstimateDistances(al, submodel= HKY85())
>>> d.run()
>>> import cPickle
>>> f = open('dists_for_phylo.pickle', "w")
>>> cPickle.dump(d.getPairwiseDistances(), f)
>>> f.close()
.. doctest::
>>> import cPickle
>>> from cogent.phylo import distance, least_squares
Now load the distance data.
.. doctest::
>>> f = file('dists_for_phylo.pickle', 'r')
>>> dists = cPickle.load(f)
>>> f.close()
If there are extremely small distances, they can cause an error in the least squares calculation. Since such estimates are between extremely closely related sequences we could simply drop all distances for one of the sequences. We won't do that here, we'll leave that as exercise.
We make the ls calculator.
.. doctest::
>>> ls = least_squares.WLS(dists)
We will search tree space for the collection of best trees using the advanced stepwise addition algorithm (hereafter *asaa*).
Look for the single best tree
-----------------------------
In this use case we are after just 1 tree. We specify up to what taxa size all possible trees for the sample will be computed. Here we are specifying ``a=5``. This means 5 sequences will be picked randomly and all possible trees relating them will be evaluated. ``k=1`` means only the best tree will be kept at the end of each such round of evaluation. For every remaining sequence it is grafted onto every possible branch of this tree. The best ``k`` results are then taken to the next round, when another sequence is randomly selected for addition. This proceeds until all sequences have been added. The result with following arguments is a single wls score and a single ``Tree`` which can be saved etc ..
.. doctest::
>>> score, tree = ls.trex(a = 5, k = 1)
>>> assert score < 1e-4
We won't display this tree, because we are doing more below.
A more rigourous tree space search
----------------------------------
We change the asaa settings, so we keep more trees and then look at the distribution of the statistics for the last collection of trees. We could also change ``a`` to be larger, but in the current case we just adjust ``k``. We also set the argument ``return_all = True``, the effect of which is to return the complete set of saved trees. These, and their support statistic, can then be inspected.
.. doctest::
>>> trees = ls.trex(a = 5, k = 5, return_all = True)
Remember the sum-of-squares statistic will be smaller for 'good' trees. The order of the trees returned is from good to bad. The number of returned ``trees`` is the same as the number requested to be retained at each step.
.. doctest::
>>> print len(trees)
5
Lets inspect the resulting statistics. First, the object ``trees`` is a list of ``(wls, Tree)`` tuples. We will therefore loop over the list to generate a separate list of just the wls statistics. The following syntax is called a list comprehension - basically just a very succinct ``for`` loop.
.. doctest::
>>> wls_stats = [tree[0] for tree in trees]
The ``wls_stats`` is a list which, if printed, looks like
.. code-block:: python
[1.3308768548934439e-05, 0.0015588630350439783, ...
From this you'll see that the first 5 results are very similar to each other and would probably reasonably be considered equivalently supported topologies. I'll just print the first two of the these trees after balancing them (in order to make their representations as equal as possible).
.. doctest::
>>> t1 = trees[0][1].balanced()
>>> t2 = trees[1][1].balanced()
>>> print t1.asciiArt()
/-Human
/edge.0--|
| \-HowlerMon
|
-root----|--Mouse
|
| /-NineBande
\edge.1--|
\-DogFaced
>>> print t2.asciiArt()
/-DogFaced
|
| /-Human
-root----|-edge.0--|
| \-HowlerMon
|
| /-NineBande
\edge.1--|
\-Mouse
You can see the difference involves the Jackrabbit, TreeShrew, Gorilla, Rat clade.
Assessing the fit for a pre-specified tree topology
---------------------------------------------------
In some instances we may have a tree from the literature or elsewhere whose fit to the data we seek to evaluate. In this case I'm going load a tree as follows.
.. doctest::
>>> from cogent import LoadTree
>>> query_tree = LoadTree(
... treestring="((Human:.2,DogFaced:.2):.3,(NineBande:.1, Mouse:.5):.2,HowlerMon:.1)")
We now just use the ``ls`` object created above. The following evaluates the query using it's associated branch lengths, returning only the wls statistic.
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> ls.evaluateTree(query_tree)
2.8...
We can also evaluate just the tree's topology, returning both the wls statistic and the tree with best fit branch lengths.
.. doctest::
>>> wls, t = ls.evaluateTopology(query_tree)
>>> assert "%.4f" % wls == '0.0084'
Using maximum likelihood for measuring tree fit
-----------------------------------------------
This is a much slower algorithm and the interface largely mirrors that for the above. The difference is you import ``maximum_likelihood`` instead of ``least_squares``, and use the ``ML`` instead of ``WLS`` classes. The ``ML`` class requires a substitution model (like a HKY85 for DNA or JTT92 for protein), and an alignment. It also optionally takes a distance matrix, such as that used here, computed for the same sequences. These distances are then used to obtain estimates of branch lengths by the WLS method for each evaluated tree topology which are then used as starting values for the likelihood optimisation.
.. clean up
.. doctest::
:hide:
>>> import os
>>> os.remove('dists_for_phylo.pickle')
PyCogent-1.5.3/doc/examples/phylogeny_app_controllers.rst 000644 000765 000024 00000006170 11361531512 024663 0 ustar 00jrideout staff 000000 000000 .. _appcontroller-phylogeny:
Using phylogeny application controllers to construct phylogenetic trees from alignments
=======================================================================================
.. sectionauthor:: Daniel McDonald
This document provides a few use case examples of how to use the phylogeny application controllers available in PyCogent. Each phylogeny application controller provides the support method ``build_tree_from_alignment``. This method takes as input an ``Alignment`` object, a ``SequenceColleciton`` object or a dict mapping sequence IDs to sequences. The ``MolType`` must also be specified. Optionally, you can indicate if you would like the "best_tree$", as well as any additional application parameters. These methods return a ``PhyloNode`` object.
To start, lets import all of our ``build_tree_from_alignment`` methods and our ``MolType``:
.. doctest::
>>> from cogent.core.moltype import DNA
>>> from cogent.app.clearcut import build_tree_from_alignment as clearcut_build_tree
>>> from cogent.app.clustalw import build_tree_from_alignment as clustalw_build_tree
>>> from cogent.app.fasttree import build_tree_from_alignment as fasttree_build_tree
>>> from cogent.app.muscle import build_tree_from_alignment as muscle_build_tree
>>> from cogent.app.raxml import build_tree_from_alignment as raxml_build_tree
Next, we'll load up a test set of sequences and construct an ``Alignment``:
.. doctest::
>>> from cogent import LoadSeqs
>>> from cogent.app.muscle import align_unaligned_seqs
>>> unaligned = LoadSeqs(filename='data/test2.fasta', aligned=False)
>>> aln = align_unaligned_seqs(unaligned, DNA)
Now, let's construct some trees with default parameters!
.. note:: We are explicitly seeding Clearcut and RAxML to ensure reproducible results, and FastTree's output depends slightly on which version of FastTree is installed
.. doctest::
>>> clearcut_tree = clearcut_build_tree(aln, DNA, params={'-s':42})
>>> clustalw_tree = clustalw_build_tree(aln, DNA)
>>> fasttree_tree = fasttree_build_tree(aln, DNA)
>>> muscle_tree = muscle_build_tree(aln, DNA)
>>> raxml_tree = raxml_build_tree(aln, DNA, params={'-p':42})
>>> clearcut_tree
Tree("(Mouse,(((HowlerMon,Human),DogFaced),NineBande));")
>>> clustalw_tree
Tree("((DogFaced,(HowlerMon,Human)),Mouse,NineBande);")
>>> muscle_tree
Tree("(Mouse,(DogFaced,(Human,(HowlerMon,NineBande))));")
>>> raxml_tree
Tree("((HowlerMon,Human),(DogFaced,Mouse),NineBande);")
.. code-block:: python
>>> fasttree_tree
Tree("(Mouse,NineBande,(DogFaced,(HowlerMon,Human)0.752)0.508);")
These methods allow the programmer to specify any of the applications parameters. Let's look at an example where we tell Clearcut to use traditional neighbor-joining, shuffle the distance matrix, use Kimura distance correction and explicitly seed the random number generator:
.. doctest::
>>> clearcut_params = {'-N':True,'-k':True,'-S':True,'-s':42}
>>> clearcut_tree = clearcut_build_tree(aln, DNA, params=clearcut_params)
>>> clearcut_tree
Tree("(((HowlerMon,Human),(NineBande,Mouse)),DogFaced);")
PyCogent-1.5.3/doc/examples/query_ensembl.rst 000644 000765 000024 00000067574 12003174737 022256 0 ustar 00jrideout staff 000000 000000 .. _query-ensembl:
Querying Ensembl
================
.. sectionauthor:: Gavin Huttley, Hua Ying
We begin this documentation with a note on dependencies, performance and code status. Ensembl_ makes their data available via MySQL servers, so the ``cogent.db.ensembl`` module has additional dependencies of `MySQL-python`_ and SQLAlchemy_. You can use ``easy_install`` to install the latter, but the former is more involved. If you experience trouble, please post to the PyCogent help forums. Regarding performance, significant queries to the UK servers from Australia are very slow. The examples in this documentation, for instance, take ~15 minutes to run when pointed at the UK servers. Running against a local installation, however, is ~50 times faster. On status, the ``cogent.db.ensembl`` module should be considered beta level code. We still strongly advise users to check results for a subset of their analyses against the data from the UK Ensembl web site.
.. _`MySQL-python`: http://sourceforge.net/projects/mysql-python
.. _SQLAlchemy: http://www.sqlalchemy.org/
The major components of Ensembl_ are compara and individual genomes. In all cases extracting data requires connecting to MySQL databases on a server and the server may be located remotely or locally. For convenience, the critical objects you'll need to query a database are provided in the top-level module import, ie immediately under ``cogent.db.ensembl``.
.. _Ensembl: http://www.ensembl.org
Specifying a Host and Account
-----------------------------
So the first step is to specify what host and account are to be used. On my lab's machines, I have set an environment variable with the username and password for our local installation of the Ensembl_ MySQL databases, e.g. ``ENSEMBL_ACCOUNT="username password"``. So I'll check for that (since the documentation runs much quicker when this is true) and if it's absent, we just set ``account=None`` and the account used defaults to the UK Ensembl_ service. I also define which release of ensembl we'll use in one place to allow easier updating of this documentation.
.. doctest::
>>> import os
>>> Release = 67
>>> from cogent.db.ensembl import HostAccount
>>> if 'ENSEMBL_ACCOUNT' in os.environ:
... host, username, password = os.environ['ENSEMBL_ACCOUNT'].split()
... account = HostAccount(host, username, password)
... else:
... account = None
What Species Are Available?
---------------------------
Another key element, of course, is the species available. Included as part of ``cogent.db.ensembl`` is the module ``species``. This module contains a class that translates between latin names, common names and ensembl database prefixes. The species listed are guaranteed to be incomplete, given Ensembl's update schedule, so it's possible to dynamically add to this listing, or even change the common name for a given latin name.
.. doctest::
>>> from cogent.db.ensembl import Species
>>> print Species
================================================================================
Common Name Species Name Ensembl Db Prefix
--------------------------------------------------------------------------------
A.aegypti Aedes aegypti aedes_aegypti
A.clavatus Aspergillus clavatus aspergillus_clavatus...
In Australia, the common name for *Gallus gallus* is chook, so I'll modify that.
.. doctest::
>>> Species.amendSpecies('Gallus gallus', 'chook')
>>> assert Species.getCommonName('Gallus gallus') == 'chook'
You can also add new species for when they become available using ``Species.amendSpecies``.
Species common names are used to construct attributes on PyCogent ``Compara`` instances). You can get the name that will be using the ``getComparaName`` method. For species with a real common name
.. doctest::
>>> Species.getComparaName('Procavia capensis')
'RockHyrax'
or with a shortened species name
.. doctest::
>>> Species.getComparaName('Caenorhabditis remanei')
'Cremanei'
The ``Species`` class is basically used to translate between latin names and ensembl's database naming scheme. It also serves to allow the user to simply enter the common name for a species in order to reference it's genome databases. The queries are case-insensitive.
Interrogating a Genome
----------------------
As implied above, Ensembl databases are versioned, hence you must explicitly state what release you want. Aside from that, getting an object for querying a genome is simply a matter of importing the ``HostAccount`` and ``Genome`` classes. Here I'm going to use the ``cogent.db.ensembl`` level imports.
.. doctest::
>>> from cogent.db.ensembl import HostAccount, Genome
>>> human = Genome(Species='human', Release=Release, account=account)
>>> print human
Genome(Species='Homo sapiens'; Release='67')
Notice I used the common name rather than full name. The ``Genome`` provides an interface to obtaining different attributes. It's primary role is to allow selection of genomic regions according to some search criteria. The type of region is presently limited to ``Gene``, ``Est``, ``CpGisland``, ``Repeat`` and ``Variation``. There's also a ``GenericRegion``. The specific types are also capable of identifying information related to themselves, as we will demonstrate below.
A Note on Coordinate Systems
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The positions employed on Ensembl's web-site, and in their MySQL database differ from those used internally by ``cogent.db.ensembl``. In all cases where you are querying ``cogent.db.ensembl`` objects directly inputting nucleotide positions you can indicate you are using Ensembl coordinates by setting ``ensembl_coord=True``. If you are explicitly passing in a ``cogent.db.ensembl`` region, that argument has no effect.
Selecting Gene's
^^^^^^^^^^^^^^^^
The genome can be queried for gene's in a number of ways. You can search for genes using the ``Genome.getGeneByStableId`` method which requires you know the Ensembl stable id.
.. doctest::
>>> brca1 = human.getGeneByStableId(StableId='ENSG00000012048')
>>> print brca1.Description
breast cancer 1, early onset...
Alternatively, you can query using the ``Genome.getGenesMatching`` method. This method allows querying for gene(s) by the following identifiers: HGNC symbol; Ensembl ``stable_id``; description; or coding type.
.. note:: When querying by description, you can specify that the exact words in the query must be present in the description by setting the argument ``like=True``. The default is ``like=False``.
In general for such queries, case shouldn't matter. For instance, find the *BRCA2* gene by it's HGNC symbol.
.. doctest::
>>> genes = human.getGenesMatching(Symbol='brca2')
Because there can be multiple hits from a ``getGenesMatching`` query, and because we wish to not spend time doing things (like talking to the database) unnecessarily, the result of the query is a python generator. This acts like a series and allows you to iterate over the database hits until you find the one you want and then terminate the record collection.
.. doctest::
>>> for gene in genes:
... if gene.Symbol.lower() == 'brca2':
... break
...
>>> brca2 = gene # so we keep track of this reference for later on
>>> print brca2.Symbol
BRCA2
>>> print brca2.Description
breast cancer 2...
>>> print brca2
Gene(Species='Homo sapiens'; BioType='protein_coding'; Description='breast...
This code serves to illustrate a few things. First, the sorts of properties that exist on the object. These can be directly accessed as illustrated above. Secondly, that the argument names to ``getGenesMatching`` match the properties.
Gene's also have a location. The length of a gene is the difference between its start and end location.
.. note:: Unfortunately all gene coordinates can vary between genome builds. So start, end and length can all differ between Ensembl releases for the same gene.
.. doctest::
>>> print brca2.Location
Homo sapiens:chromosome:13:32889610...
>>> print len(brca2)
84195
Each location is directly tied to the parent genome and the coordinate above also shows the coordinates' *type* (chromosome in this case), name (13), start, end and strand. The start and end positions are python indices and will differ from the Ensembl indices in that start will be the Ensembl index - 1. This is because python counts from 0, not 1. In querying for regions using a specific set of coordinates, it is possible to put in the Ensembl coordinates (demonstrated below).
``Gene`` has several useful properties, including the ability to directly get their own DNA sequence and their ``CanonicalTranscript`` and ``Transcripts``. ``CanonicalTranscript`` is the characteristic transcript for a gene, as defined by Ensembl. ``Transcripts`` is a tuple attribute containing individual region instances of type ``Transcript``. A ``Transcript`` has ``Exons``, ``Introns``, a ``Cds`` and, if the ``BioType`` is protein coding, a protein sequence. In the following we grab the cannonical transcript from ``brca2``
.. doctest::
>>> print brca2.BioType
protein_coding
>>> print brca2.Seq
GGGCTTGTGGCGC...
>>> print brca2.CanonicalTranscript.Cds
ATGCCTATTGGATC...
>>> print brca2.CanonicalTranscript.ProteinSeq
MPIGSKERPTF...
It is also possible to iterate over a transcript's exons, over their translated exons, or to obtain their coding DNA sequence. We grab the second transcript for this.
.. doctest::
>>> transcript = brca2.Transcripts[0]
>>> for exon in transcript.Exons:
... print exon, exon.Location
Exon(StableId=ENSE00001184784, Rank=1) Homo sapiens:chromosome:13:...
>>> for exon in transcript.TranslatedExons:
... print exon, exon.Location
Exon(StableId=ENSE00001484009, Rank=2) Homo sapiens:chromosome:13:...
>>> print transcript.Cds
ATGCCTATTGGATCCAAA...
The ``Cds`` sequence includes the stop-codon, if present. The reason for this is there are many annotated transcripts in the Ensembl database the length of whose transcribed exons are not divisible by 3. Hence we leave it to the user to decide how to deal with that, but mention here that determining the number of complete codons is trivial and you can slice the ``Cds`` so that it's length is divisible by 3.
The ``Exons`` and ``TranslatedExons`` properties are tuples that are evaluated on demand and can be sliced. Each ``Exon/TranslatedExon`` is itself a region, with all of the properties of generic regions (like having a ``Seq`` attribute). Similar descriptions apply to the ``Introns`` property and ``Intron`` class. We show just for the canonical transcript.
.. doctest::
>>> for intron in brca2.CanonicalTranscript.Introns:
... print intron
Intron(TranscriptId=ENST00000380152, Rank=1)
Intron(TranscriptId=ENST00000380152, Rank=2)
Intron(TranscriptId=ENST00000380152, Rank=3)...
The ``Gene`` region also has convenience methods for examining properties of it's transcripts, in presenting the ``Cds`` lengths and getting the ``Transcript`` encoding the longest ``Cds``.
.. doctest::
>>> print brca2.getCdsLengths()
[10257, 1807, 10257]
>>> longest = brca2.getLongestCdsTranscript()
>>> print longest.Cds
ATGCCTATTGGATCCAAA...
All Regions have a ``getFeatures`` method which differs from that on genome only in that the genomic coordinates are automatically entered for you. Regions also have the ability to return their sequence as an annotated ``cogent`` sequence. The method on ``Gene`` simply queries the parent genome using the gene's own location as the coordinate for the currently supported region types. We will query ``brca2`` asking for gene features, the end-result will be a ``cogent`` sequence that can be used to obtain the CDS, for instance, using the standard ``cogent`` annotation capabilities.
.. doctest::
>>> annot_brca2 = brca2.getAnnotatedSeq(feature_types='gene')
>>> cds = annot_brca2.getAnnotationsMatching('CDS')[0].getSlice()
>>> print cds
ATGCCTATTGGATCCAAA...
Those are the properties of a ``Gene``, at present, of direct interest to end-users.
There are obviously different types of genes, and the ``Genome`` object provides an ability to establish exactly what distinct types are defined in Ensembl.
.. doctest::
>>> print human.getDistinct('BioType')
['rRNA', 'lincRNA', 'IG_C_pseudogene', ...
The genome can be queried for any of these types, for instance we'll query for ``rRNA``. We'll get the first few records and then exit.
.. doctest::
>>> rRNA_genes = human.getGenesMatching(BioType='rRNA')
>>> count = 0
>>> for gene in rRNA_genes:
... print gene
... count += 1
... if count == 1:
... break
...
Gene(Species='Homo sapiens'; BioType='Mt_rRNA'; ...
This has the effect of returning any gene whose ``BioType`` includes the phrase ``rRNA``. If a gene is not a protein coding gene, as in the current case, then it's ``Transcripts`` will have ``ProteinSeq==None`` and ``TranslatedExons==None``, but it will have ``Exons`` and a ``Cds``.
.. doctest::
>>> transcript = gene.Transcripts[0]
>>> assert transcript.ProteinSeq == None
>>> assert transcript.TranslatedExons == None
>>> assert transcript.Cds != None
Getting ESTs
^^^^^^^^^^^^
Ensembl's ``otherfeatures`` database mirrors the structure of the ``core`` database and contains EST information. Hence, the ``Est`` region inherits directly from ``Gene`` (ie has many of the same properties). ``est`` is a supported ``feature_types`` for the ``getFeatures`` method. You can also directly query for an EST using Ensembl's ``StableID``. Here, however, we'll just query for ``Est`` that map to the ``brca2`` region.
.. doctest::
>>> ests = human.getFeatures(feature_types='est', region=brca2)
>>> for est in ests:
... print est
Est(Species='Homo sapiens'; BioType='protein_coding'; Description='None';...
Getting Variation
^^^^^^^^^^^^^^^^^
``Variation`` regions also have distinctive properties worthy of additional mention. As for genes, there are distinct types stored in Ensembl that may be of interest. Those types can likewise be discovered from the genome,
.. doctest::
>>> print human.getDistinct('Effect')
['3_prime_UTR_variant', 'splice_acceptor_variant', 'intergenic_variant'...
and that information can be used to query the genome for all variation of that effect.
.. note:: What we term ``effect``, Ensembl terms consequence. We use ``effect`` because it's shorter.
We allow the query to be an inexact match by setting ``like=True``. Again we'll just iterate over the first few.
.. doctest::
>>> nsyn_variants = human.getVariation(Effect='non_synonymous_codon',
... like=True)
...
>>> for nsyn_variant in nsyn_variants:
... break
...
>>> print nsyn_variant
Variation(Symbol='rs180965628'; Effect='non_synonymous_codon'; Alleles='G/A')
>>> print nsyn_variant.AlleleFreqs
=============================
allele freq sample_id
-----------------------------
A 0.0000 113559
G 1.0000 113559
A 0.0013 113560
G 0.9987 113560
A 0.0000 113561
G 1.0000 113561
A 0.0005 113562
G 0.9995 113562
A 0.0000 113563
G 1.0000 113563
-----------------------------
``Variation`` objects also have other useful properties, such as a location, the number of alleles and the allele frequencies. The length of a ``Variation`` instance is the length of it's longest allele.
.. doctest::
>>> assert len(nsyn_variant) == 1
>>> print nsyn_variant.Location
Homo sapiens:chromosome:17:6068-6069:1
>>> assert nsyn_variant.NumAlleles == 2
``Variation`` objects have ``FlankingSeq`` and ``Seq`` attributes which, of course, in the case of a SNP is a single nucleotide long and should correspond to one of the alleles. In the latter case, this property is a tuple with the 0th entry being the 5'- 300 nucleotides and the 1st entry being the 3' nucleotides.
.. doctest::
>>> print nsyn_variant.FlankingSeq[0]
ACTAATACCTG...
>>> print nsyn_variant.FlankingSeq[1]
CACGATGCCTA...
>>> assert str(nsyn_variant.Seq) in nsyn_variant.Alleles, str(nsyn_variant.Seq)
As a standard feature, ``Variation`` within a specific interval can also be obtained. Using the ``brca2`` gene region instance created above, we can find all the genetic variants using the ``Variants`` property of genome regions. We use this example to also demonstrate the ``PeptideAlleles`` and ``TranslationLocation`` attributes. ``PeptideAlleles`` is the amino-acid variation resulting from the nucleotide variation while ``TranslationLocation`` is the position in the translated peptide of the variant. If a variant does not affect protein coding sequence (either it's not exonic or it's a synonymous variant) then these properties have the value ``None``.
We illustrate their use.
.. doctest::
>>> for variant in brca2.Variants:
... if variant.PeptideAlleles is None:
... continue
... print variant.PeptideAlleles, variant.TranslationLocation
P/L 1...
.. note:: These are Python coordinates, add 1 to get the Ensembl value.
We can also use a slightly more involved query to find all variants within the gene of a specific type. (Of course, you could also simply iterate over the ``Variants`` attribute to grab these out too.)
.. doctest::
>>> brca2_snps = human.getFeatures(feature_types='variation',
... region=brca2)
>>> for snp in brca2_snps:
... if 'non_synonymous_codon' in snp.Effect:
... break
>>> print snp
Variation(Symbol='rs80358836'; Effect=['2KB_upstream_variant', '5KB_upstream_variant', 'non_synonymous_codon']; Alleles='C/T')
>>> print snp.Location
Homo sapiens:chromosome:13:32890601-32890602:1
Other Region Types
^^^^^^^^^^^^^^^^^^
These can be obtained from the genome instance using the genomes ``getFeatures`` method. At present, only repeats, CpG islands, variation, EST's and genes can be obtained through this method. There's also ``GenericRegion``, which is precisely that.
In Ensembl's databases, each type of feature may be recorded at multiple coordinate levels. Accordingly, each level is checked to obtain full information of that feature.
.. doctest::
>>> chicken = Genome(Species='chook', Release=Release, account=account)
>>> print chicken.FeatureCoordLevels
Gallus gallus
============================================
Type Levels
--------------------------------------------
gene chromosome
repeat contig
est chromosome
variation chromosome
cpg chromosome, supercontig, contig
--------------------------------------------
Comparative Analyses
--------------------
The Ensembl compara database is represented by ``cogent.db.ensembl.compara.Compara``. This object provides a means for querying for relationships among genomes and obtaining multiple alignments. For convenience the class is made available through the top-level module for importing (i.e. ``cogent.db.ensembl.Compara``). Instantiating ``Compara`` requires, as before, the ensembl release, the series of species of interest and optionally an account (we also use our local account for speed). For the purpose of illustration we'll use the human, mouse and rat genomes.
.. note:: Any queries on this instance of compara will only return results for the indicated species. If you want to query about other species, create another instance.
.. doctest::
>>> from cogent.db.ensembl import Compara
>>> compara = Compara(['human', 'mouse', 'rat'], account=account,
... Release=Release)
>>> print compara
Compara(Species=('Homo sapiens', 'Mus musculus', 'Rattus norvegicus'); Release=67...
The ``Compara`` object loads the corresponding ``Genome``'s and attaches them to itself as named attributes (use ``Species.getComparaName`` to find out what the attribute will be). The genome instances are named according to their common name in CamelCase, or Scase. For instance, if we had created a ``Compara`` instance with the American pika species included, then that genome would be accessed as ``compara.AmericanPika``. Common names containing a '.' are treated differently. For instance, the common name for *Caenorhabditis remanei* is ``C.remanei`` which becomes ``compara.Cremanei``. We access the human genome in this ``Compara`` instance and conduct a gene search.
.. doctest::
>>> brca2 = compara.Human.getGeneByStableId(StableId='ENSG00000139618')
>>> print brca2
Gene(Species='Homo sapiens'; BioType='protein_coding'; Description='breast...
We can now use this result to search compara for related genes. We note here that like ``Genome``, ``Compara`` has the ``getDistinct`` method to assist in identifying appropriate search criteria. What are the distinct types of gene relationships recorded in Ensembl, for instance?
.. doctest::
>>> relationships = compara.getDistinct('relationship')
>>> print relationships
[u'ortholog_one2many', u'contiguous_gene_split', u'ortholog_one2one',...
So we use the ``brca2`` instance above and search for orthologs among the human, mouse, rat genomes.
.. doctest::
>>> orthologs = compara.getRelatedGenes(gene_region=brca2,
... Relationship='ortholog_one2one')
>>> print orthologs
RelatedGenes:
Relationships=ortholog_one2one
Gene(Species='Rattus norvegicus'; BioType='protein_coding'; Description='Breast cancer ...
I could also have done that query using a ``StableId``, which I now do using the Ensembl mouse identifier for *Brca2*.
.. doctest::
>>> orthologs = compara.getRelatedGenes(StableId='ENSMUSG00000041147',
... Relationship='ortholog_one2one')
>>> print orthologs
RelatedGenes:
Relationships=ortholog_one2one
Gene(Species='Rattus norvegicus'; BioType='protein_coding'; Description='Breast cancer...
The ``RelatedGenes`` object has a number of properties allowing you to get access to data. A ``Members`` attribute holds each of the ``Gene`` instances displayed above. The length of this attribute tells you how many hits there were, while each member has all of the capabilities described for ``Gene`` above, eg. a ``Cds`` property. There is also a ``getSeqLengths`` method which returns the vector of sequence lengths for the members. This method returns just the lengths of the individual genes.
.. doctest::
>>> print orthologs.Members
(Gene(Species='Rattus norvegicus'; BioType='protein_coding'; Descr...
>>> print orthologs.getSeqLengths()
[40742, 47117, 84195]
In addition there's a ``getMaxCdsLengths`` method for returning the lengths of the longest ``Cds`` from each member.
.. doctest::
>>> print orthologs.getMaxCdsLengths()
[10032, 9990, 10257]
You can also obtain the sequences as a ``cogent`` ``SequenceCollection`` (unaligned), with the ability to have those sequences annotated as described above. The sequences are named in accordance with their genomic coordinates.
.. doctest::
>>> seqs = orthologs.getSeqCollection(feature_types='gene')
>>> print seqs.Names
['Rattus norvegicus:chromosome:12:428...
We can also search for other relationship types, which we do here for a histone.
.. doctest::
>>> paralogs = compara.getRelatedGenes(StableId='ENSG00000164032',
... Relationship='within_species_paralog')
>>> print paralogs
RelatedGenes:
Relationships=within_species_paralog
Gene(Species='Homo sapiens'; BioType='protein_coding'; Description='H2A...
Getting Comparative Alignments
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Ensembl stores multiple sequence alignments for selected species. For a given group of species, you can examine what alignments are available by printing the ``method_species_links`` attribute of ``Compara``. This will return something like
>>> print compara.method_species_links
Align Methods/Clades
=============================================================================...
method_link_species_set_id method_link_id species_set_id align_method ...
-----------------------------------------------------------------------------...
580 10 34468 PECAN ...
578 13 34466 EPO ...
582 14 34697 EPO_LOW_COVERAGE ...
-----------------------------------------------------------------------------...
The ``align_method`` and ``align_clade`` columns can be used as arguments to ``getSyntenicRegions``. This method is responsible for returning ``SyntenicRegions`` instances for a given coordinate from a species. As it's possible that multiple records may be found from the multiple alignment for a given set of coordinates, the result of calling this method is a python generator. The returned regions have a length, defined by the full set of aligned sequences. If the ``omit_redundant`` argument is used, then positions with gaps in all sampled species will be removed in the alignment to be returned. The length of the syntenic region, however, is the length of the unfiltered alignment.
.. note:: It's important to realise that multiple alignments are from these clades. Hence, sequence regions that you might expect would result in a contiguous alignment in the species subset of interest may be returned as separate ``SyntenicRegions`` due to the influence on the alignment of the other species.
.. doctest::
>>> syntenic_regions = compara.getSyntenicRegions(region=brca2,
... align_method='EPO', align_clade='eutherian')
>>> for syntenic_region in syntenic_regions:
... print syntenic_region
... print len(syntenic_region)
... print repr(syntenic_region.getAlignment(omit_redundant=False))
SyntenicRegions:
Coordinate(Human,chro...,13,32889610-32907347,1)
Coordinate(Mouse,chro...,5,151325195-151339535,-1)
Coordinate(Rat,chro...,12,4313281-4324025,1)
54774
3 x 54774 dna alignment: Homo sapiens:chromosome:13:32889610-32907347...
We consider a species for which pairwise alignments are available -- the bush baby.
.. doctest::
>>> compara_pair = Compara(['Human', 'Bushbaby'], Release=Release,
... account=account)
>>> print compara_pair
Compara(Species=('Homo sapiens', 'Otolemur garnettii'); Release=67; connected=True)
Printing the ``method_species_links`` table provides all the necessary information for specifying selection conditions.
>>> print compara_pair.method_species_links
Align Methods/Clades
============================================================================...
method_link_species_set_id method_link_id species_set_id align_method...
----------------------------------------------------------------------------...
582 14 34697 EPO_LOW_COVERAGE...
545 16 34112 LASTZ_NET...
----------------------------------------------------------------------------...
.. doctest::
>>> gene = compara_pair.Bushbaby.getGeneByStableId(
... StableId='ENSOGAG00000003166'
... )
...
>>> print gene
Gene(Species='Otolemur garnettii'; BioType='protein_coding'...
>>> syntenic = compara_pair.getSyntenicRegions(region=gene,
... align_method='LASTZ_NET', align_clade='H.sap-O.gar')
...
>>> for region in syntenic:
... print region
... break
SyntenicRegions:
Coordinate(Bushbaby,scaf...,GL87...,8624867-8626121,1)
Coordinate(Human,chro...,7,135410894-135412244,1)
PyCogent-1.5.3/doc/examples/query_ncbi.rst 000644 000765 000024 00000012636 11464420767 021540 0 ustar 00jrideout staff 000000 000000 Querying NCBI for VWF
=====================
.. sectionauthor:: Gavin Huttley
This example is taken from the PyCogent paper (Knight et al. Genome Biol, 8(8):R171, 2007).
.. note:: Due to changes by NCBI in the structure of there records, it is no longer easy (but not impossible) to use the Sequences ``Info`` attribute to restrict sequences to Swissprot entries as we had done previously.
We query the NCBI protein data base for von Willebrand Factor (VWF), a 2813 amino acid glycoprotein required for platelet adhesion in blood coagulation. Missense mutations in this molecule have been associated with von Willebrand disease, a heterogeneous disorder characterized by prolonged bleeding.
We import ``EUtils`` for querying NCBI and search the protein data-base, restricting our search to mammal sequences.
.. doctest::
>>> from cogent.db.ncbi import EUtils
>>> db = EUtils(db="protein", rettype="gp")
>>> query = '"VWf"[gene] AND Mammalia[orgn]'
>>> records = db[query].readlines()
We have requested the GenBank record format. We use the ``RichGenbankParser`` to grab features from the feature annotations of this format. We illustrate grabbing additional content from the feature tables by extracting the locations of SNPs and whether those SNPs have a disease association. An inspection of the feature tables for human entries reveals that the Swissprot entry had the most complete and accessible content regarding the SNP data: region features with ``region_name="Variant"`` and a note field that contains the indicated amino acid difference along with an indication of whether the SNP was associated with von Willebrand disease (denoted by the symbol VWD). Finally, we seek to extract the protein domain locations for presentation purposes.
We simply limit our attention to large, relatively complete sequences. From the human record we extract annotation data. We use regular expressions to assist with extracting data regarding the amino acid change and the domain names. We also name sequences based on their [G]enus [spe]cies and accession.
The selected species are accumulated in a ``seqs`` dictionary, keyed by their name. The feature data are accumulated in a list.
.. doctest::
>>> import re
>>> from cogent.parse.genbank import RichGenbankParser
>>> parser = RichGenbankParser(records)
>>> seqs = {}
>>> rows = []
>>> for accession, seq in parser:
... if len(seq) < 2800:
... continue
... # we extract annotation data only from the human record
... if "Homo" in seq.Info.species:
... for feature in seq.Info.features:
... if "region_name" not in feature:
... continue # ignore this one, go to the next feature
... if "Variant" in feature["region_name"]:
... note = feature["note"][0]
... variant = " ".join(re.findall("[A-Z] *-> *[A-Z]",
... note))
... disease = "VWD" in note
... lo = feature["location"].first() - 1
... hi = feature["location"].last()
... rows.append(["SNP", lo, hi, variant.strip(), disease])
... else:
... region_name = feature["region_name"][0]
... if region_name == "Domain":
... note = [field.strip() \
... for field in re.split("[.;]", feature["note"][0]) if field]
... if len(note) == 1:
... note += [""]
... lo = feature["location"].first() - 1
... hi = feature["location"].last()
... rows.append(["Domain", lo, hi, ' '.join(note).strip(), None])
... species = seq.Info.species.split()
... seq_name = "%s.%s" % (species[0][0] + species[1][:3], accession)
... seqs[seq_name] = seq
We convert the sequences to a ``SequenceCollection`` using ``LoadSeqs`` and then save to a fasta formatted file.
.. doctest::
>>> from cogent import LoadSeqs
>>> seqs = LoadSeqs(data=seqs, aligned=False)
>>> print seqs.NamedSeqs['Clup.VWF_CANFA'].toFasta()
>Clup.VWF_CANFA
MSPTRLVRVLLALALI...
We convert the features into a PyCogent ``Table`` object, which requires we specify column headings. This can be saved to file if desired, but we don't do that here. For display purposes, we just print the first 10 records.
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> from cogent import LoadTable
>>> feature_table = LoadTable(header=["Type", "Start", "Stop", "Note",
... "Disease"], rows=rows)
Printing ``feature_table[:10]`` should result in something like:
.. code-block:: python
============================================
Type Start Stop Note Disease
--------------------------------------------
Domain 33 240 VWFD 1
SNP 272 273 R -> W True
Domain 294 348 TIL 1
SNP 317 318 N -> K False
SNP 376 377 W -> C True
Domain 386 598 VWFD 2
SNP 483 484 H -> R False
SNP 527 528 N -> S True
SNP 549 550 G -> R True
Domain 651 707 TIL 2
--------------------------------------------
PyCogent-1.5.3/doc/examples/rate_heterogeneity.rst 000644 000765 000024 00000004370 11473355707 023263 0 ustar 00jrideout staff 000000 000000 .. _rate-heterogeneity:
Analysis of rate heterogeneity
==============================
.. sectionauthor:: Gavin Huttley
A simple example for analyses involving rate heterogeneity among sites. In this case we will simulate an alignment with two rate categories and then try to recover the rates from the alignment.
.. doctest::
>>> from cogent.evolve.substitution_model import Nucleotide
>>> from cogent import LoadTree
Make an alignment with equal split between rates 0.6 and 0.2, and then concatenate them to create a new alignment.
.. doctest::
>>> model = Nucleotide(equal_motif_probs=True)
>>> tree = LoadTree("data/test.tree")
>>> lf = model.makeLikelihoodFunction(tree)
>>> lf.setParamRule('length', value=0.6, is_constant=True)
>>> aln1 = lf.simulateAlignment(sequence_length=10000)
>>> lf.setParamRule('length', value=0.2, is_constant=True)
>>> aln2 = lf.simulateAlignment(sequence_length=10000)
>>> aln3 = aln1 + aln2
Start from scratch, optimising only rates and the rate probability ratio.
.. doctest::
>>> model = Nucleotide(equal_motif_probs=True, ordered_param="rate",
... distribution="free")
>>> lf = model.makeLikelihoodFunction(tree, bins=2, digits=2, space=3)
>>> lf.setAlignment(aln3)
>>> lf.optimise(local=True, max_restarts=2)
We want to know the bin probabilities and the posterior probabilities.
.. doctest::
>>> bprobs = [t for t in lf.getStatistics() if 'bin' in t.Title][0]
Print the ``bprobs`` sorted by ``'rate'`` will generate a table like
.. code-block:: python
bin params
====================
bin bprobs rate
--------------------
bin0 0.49 0.49
bin1 0.51 1.48
--------------------
We'll now use a gamma distribution on the sample alignment, specifying the number of bins as 4. We specify that the bins have equal density using the ``lf.setParamRule('bprobs', is_constant=True)`` command.
.. doctest::
>>> model = Nucleotide(equal_motif_probs=True, ordered_param="rate",
... distribution="gamma")
>>> lf = model.makeLikelihoodFunction(tree, bins=4)
>>> lf.setParamRule('bprobs', is_constant=True)
>>> lf.setAlignment(aln3)
>>> lf.optimise(local=True, max_restarts=2)
PyCogent-1.5.3/doc/examples/relative_rate.rst 000644 000765 000024 00000007040 11425201333 022176 0 ustar 00jrideout staff 000000 000000 Performing a relative rate test
===============================
.. sectionauthor:: Gavin Huttley
From cogent import all the components we need
.. doctest::
>>> from cogent import LoadSeqs, LoadTree
>>> from cogent.evolve.models import HKY85
>>> from cogent.maths import stats
Get your alignment and tree.
.. doctest::
>>> aln = LoadSeqs(filename = "data/long_testseqs.fasta")
>>> t = LoadTree(filename = "data/test.tree")
Create a HKY85 model.
.. doctest::
>>> sm = HKY85()
Make the controller object and limit the display precision (to decrease the chance that small differences in estimates cause tests of the documentation to fail).
.. doctest::
>>> lf = sm.makeLikelihoodFunction(t, digits=2, space=3)
Set the local clock for humans & Howler Monkey. This method is just a special interface to the more general ``setParamRules`` method.
.. doctest::
>>> lf.setLocalClock("Human", "HowlerMon")
Get the likelihood function object this object performs the actual likelihood calculation.
.. doctest::
>>> lf.setAlignment(aln)
Optimise the function capturing the return optimised lnL, and parameter value vector.
.. doctest::
>>> lf.optimise()
View the resulting maximum-likelihood parameter values.
.. doctest::
>>> lf.setName("clock")
>>> print lf
clock
=====
kappa
-----
4.10
-----
===========================
edge parent length
---------------------------
Human edge.0 0.04
HowlerMon edge.0 0.04
edge.0 edge.1 0.04
Mouse edge.1 0.28
edge.1 root 0.02
NineBande root 0.09
DogFaced root 0.11
---------------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
We extract the log-likelihood and number of free parameters for later use.
.. doctest::
>>> null_lnL = lf.getLogLikelihood()
>>> null_nfp = lf.getNumFreeParams()
Clear the local clock constraint, freeing up the branch lengths.
.. doctest::
>>> lf.setParamRule('length', is_independent=True)
Run the optimiser capturing the return optimised lnL, and parameter value vector.
.. doctest::
>>> lf.optimise()
View the resulting maximum-likelihood parameter values.
.. doctest::
>>> lf.setName("non clock")
>>> print lf
non clock
=====
kappa
-----
4.10
-----
===========================
edge parent length
---------------------------
Human edge.0 0.03
HowlerMon edge.0 0.04
edge.0 edge.1 0.04
Mouse edge.1 0.28
edge.1 root 0.02
NineBande root 0.09
DogFaced root 0.11
---------------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
These two lnL's are now used to calculate the likelihood ratio statistic it's degrees-of-freedom and the probability of observing the LR.
.. doctest::
>>> LR = 2 * (lf.getLogLikelihood() - null_lnL)
>>> df = lf.getNumFreeParams() - null_nfp
>>> P = stats.chisqprob(LR, df)
Print this and look up a :math:`$\chi^2$` with number of edges - 1 degrees of freedom.
.. doctest::
>>> print "Likelihood ratio statistic = ", LR
Likelihood ratio statistic = 2.7...
>>> print "degrees-of-freedom = ", df
degrees-of-freedom = 1
>>> print "probability = ", P
probability = 0.09...
PyCogent-1.5.3/doc/examples/reuse_results.rst 000644 000765 000024 00000006231 11425201333 022255 0 ustar 00jrideout staff 000000 000000 Reusing results to speed up optimisation
========================================
.. sectionauthor:: Gavin Huttley
An example of how to use the maximum-likelihood parameter estimates from one model as starting values for another model. In this file we do something silly, by saving a result and then reloading it. This is silly because the analyses are run consecutively. A better approach when running consecutively is to simply use the annotated tree directly.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree
>>> from cogent.evolve.models import MG94HKY
We'll create a simple model, optimise it and save it for later reuse
.. doctest::
>>> aln = LoadSeqs("data/long_testseqs.fasta")
>>> t = LoadTree("data/test.tree")
>>> sm = MG94HKY()
>>> lf = sm.makeLikelihoodFunction(t, digits=2, space=2)
>>> lf.setAlignment(aln)
>>> lf.optimise(local=True)
>>> print lf
Likelihood Function Table
============
kappa omega
------------
3.85 0.90
------------
=========================
edge parent length
-------------------------
Human edge.0 0.09
HowlerMon edge.0 0.12
edge.0 edge.1 0.12
Mouse edge.1 0.84
edge.1 root 0.06
NineBande root 0.28
DogFaced root 0.34
-------------------------
=============
motif mprobs
-------------
T 0.23
C 0.19
A 0.37
G 0.21
-------------
The essential object for reuse is an annotated tree these capture the parameter estimates from the above optimisation we can either use this directly in the same run, or we can save the tree to file in ``xml`` format and reload the tree at a later time for use. In this example I'll illustrate the latter scenario.
.. doctest::
>>> at=lf.getAnnotatedTree()
>>> at.writeToFile('tree.xml')
We load the tree as per usual
.. doctest::
>>> nt = LoadTree('tree.xml')
Now create a more parameter rich model, in this case by allowing the ``Human`` edge to have a different value of ``omega``. By providing the annotated tree, the parameter estimates from the above run will be used as starting values for the new model.
.. doctest::
>>> new_lf = sm.makeLikelihoodFunction(nt, digits=2, space=2)
>>> new_lf.setParamRule('omega', edge='Human',
... is_independent=True)
>>> new_lf.setAlignment(aln)
>>> new_lf.optimise(local=True)
>>> print new_lf
Likelihood Function Table
=====
kappa
-----
3.85
-----
================================
edge parent length omega
--------------------------------
Human edge.0 0.09 0.59
HowlerMon edge.0 0.12 0.92
edge.0 edge.1 0.12 0.92
Mouse edge.1 0.84 0.92
edge.1 root 0.06 0.92
NineBande root 0.28 0.92
DogFaced root 0.34 0.92
--------------------------------
=============
motif mprobs
-------------
T 0.23
C 0.19
A 0.37
G 0.21
-------------
.. clean up
.. doctest::
:hide:
>>> import os
>>> os.remove('tree.xml')
PyCogent-1.5.3/doc/examples/reverse_complement.rst 000644 000765 000024 00000002560 12014672513 023257 0 ustar 00jrideout staff 000000 000000 Getting the reverse complement
==============================
.. sectionauthor:: Gavin Huttley
This is a property of DNA, and hence alignments need to be created with the appropriate ``MolType``. In the following example, the alignment is truncated to just 50 bases for the sake of simplifying the presentation.
.. doctest::
>>> from cogent import LoadSeqs, DNA
>>> aln = LoadSeqs("data/long_testseqs.fasta", moltype=DNA)[:50]
The original alignment looks like this.
.. doctest::
>>> print aln
>Human
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTT
>HowlerMon
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTT
>Mouse
TGTGGCACAGATGCTCATGCCAGCTCATTACAGCCTGAGACCAGCAGTTT
>NineBande
TGTGGCACAAATACTCATGCCAACTTATTACAGCATGAGAACAGCAGTTT
>DogFaced
TGTGGCACAAATACTCATGCCAACTCATTACAGCATGAGAACAGCAGTTT
We do reverse complement very simply.
.. doctest::
>>> naln = aln.rc()
The reverse complemented alignment looks like this.
.. doctest::
>>> print naln
>Human
AAACTGCTGTTCTCATGCTGTAATGAGCTGGCATGAGTATTTGTGCCACA
>HowlerMon
AAACTGCTGTTCTCATGCTGTAATGAGCTGGCATGAGTATTTGTGCCACA
>Mouse
AAACTGCTGGTCTCAGGCTGTAATGAGCTGGCATGAGCATCTGTGCCACA
>NineBande
AAACTGCTGTTCTCATGCTGTAATAAGTTGGCATGAGTATTTGTGCCACA
>DogFaced
AAACTGCTGTTCTCATGCTGTAATGAGTTGGCATGAGTATTTGTGCCACA
PyCogent-1.5.3/doc/examples/scope_model_params_on_trees.rst 000644 000765 000024 00000027413 11473355707 025132 0 ustar 00jrideout staff 000000 000000 .. _scope-params-on-trees:
Allowing substitution model parameters to differ between branches
=================================================================
.. sectionauthor:: Gavin Huttley
A common task concerns assessing how substitution model exchangeability parameters differ between evolutionary lineages. This is most commonly of interest for the case of testing for natural selection. Here I'll demonstrate the different ways of scoping parameters across trees for the codon model case and how these can be used for evolutionary modelling.
We start with the standard imports, plus using a canned codon substitution model and then load the sample data set.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree
>>> from cogent.evolve.models import MG94HKY
>>> aln = LoadSeqs("data/long_testseqs.fasta")
>>> tree = LoadTree("data/test.tree")
We construct the substitution model and likelihood function and set the alignment.
.. doctest::
>>> sm = MG94HKY()
>>> lf = sm.makeLikelihoodFunction(tree, digits=2, space=3)
>>> lf.setAlignment(aln)
At this point we have a likelihood function with two exchangeability parameters from the substitution model (``kappa`` the transition/transversion ratio; ``omega`` the nonsynonymous/synonymous ratio) plus branch lengths for all tree edges. To facilitate subsequent discussion I now display the tree
.. doctest::
>>> print tree.asciiArt()
/-Human
/edge.0--|
/edge.1--| \-HowlerMon
| |
| \-Mouse
-root----|
|--NineBande
|
\-DogFaced
In order to scope a parameter on a tree (meaning specifying a subset of edges for which the parameter is to be treated differently to the remainder of the tree) requires uniquely identifying the edges. We do this using the following arguments to the likelihood function ``setParamRule`` method:
- ``tip_names``: the name of two tips
- ``outgroup_name``: the name of a tip that is not part of the clade of interest
- ``is_clade``: if ``True``, all lineages descended from the tree node identified by the ``tip_names`` and ``outgroup_name`` argument are affected by the other arguments. If ``False``, then the ``is_stem`` argument must apply.
- ``is_stem``: Whether the edge leading to the node is included.
The next concepts include exactly what can be scoped and how. In the case of testing for distinctive periods of natural selection it is common to specify distinct values for ``omega`` for an edge. I'll first illustrate some possible uses for the arguments above by setting ``omega`` to be distinctive for specific edges. I will set a value for omega so that printing the likelihood function illustrates what edges have been effected, but I won't actually do any model fitting.
Specifying a clade
------------------
I'm going to cause ``omega`` to attain a different value for all branches aside from the primate clade and stem (``HowlerMon``, ``Human``, ``edge.0``).
.. doctest::
>>> lf.setParamRule('omega', tip_names=['DogFaced', 'Mouse'],
... outgroup_name='Human', init=2.0, is_clade=True)
>>> print lf
Likelihood Function Table
=====
kappa
-----
1.00
-----
===================================
edge parent length omega
-----------------------------------
Human edge.0 0.03 1.00
HowlerMon edge.0 0.04 1.00
edge.0 edge.1 0.04 1.00
Mouse edge.1 0.28 2.00
edge.1 root 0.02 2.00
NineBande root 0.09 2.00
DogFaced root 0.11 2.00
-----------------------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
As you can see ``omega`` for the primate edges I listed above have the default parameter value (1.0), while the others have what I've assigned. In fact, you could omit the ``is_clade`` argument as this is the default, but I think for readability of scripts it's best to be explicit.
Specifying a stem
-----------------
This time I'll specify the stem leading to the primates as the edge of interest.
.. note:: I need to reset the ``lf`` so all edges have the default value again. I'll show this only for this example, but rest assured I'm doing it for all others too.
.. doctest::
>>> lf.setParamRule('omega', init=1.0)
>>> lf.setParamRule('omega', tip_names=['Human', 'HowlerMon'],
... outgroup_name='Mouse', init=2.0, is_stem=True, is_clade=False)
>>> print lf
Likelihood Function Table
=====
kappa
-----
1.00
-----
===================================
edge parent length omega
-----------------------------------
Human edge.0 0.03 1.00
HowlerMon edge.0 0.04 1.00
edge.0 edge.1 0.04 2.00
Mouse edge.1 0.28 1.00
edge.1 root 0.02 1.00
NineBande root 0.09 1.00
DogFaced root 0.11 1.00
-----------------------------------...
Specifying clade and stem
-------------------------
I'll specify that both the primates and their stem are to be considered.
.. doctest::
:hide:
>>> lf.setParamRule('omega', init=1.0)
.. doctest::
>>> lf.setParamRule('omega', tip_names=['Human', 'HowlerMon'],
... outgroup_name='Mouse', init=2.0, is_stem=True, is_clade=True)
>>> print lf
Likelihood Function Table
=====
kappa
-----
1.00
-----
===================================
edge parent length omega
-----------------------------------
Human edge.0 0.03 2.00
HowlerMon edge.0 0.04 2.00
edge.0 edge.1 0.04 2.00
Mouse edge.1 0.28 1.00
edge.1 root 0.02 1.00
NineBande root 0.09 1.00
DogFaced root 0.11 1.00
-----------------------------------...
Alternate arguments for specifying edges
----------------------------------------
The likelihood function ``setParamRule`` method also has the arguments of ``edge`` and ``edges``. These allow specific naming of the tree edge(s) to be affected by a rule. In general, however, the ``tip_names`` + ``outgroup_name`` combo is more robust.
Applications of scoped parameters
---------------------------------
The general use-cases for which a tree scope can be applied are:
1. constraining all edges identified by a rule to have a specific value which is constant and not modifiable
>>> lf.setParamRule('omega', tip_names=['Human', 'HowlerMon'],
... outgroup_name='Mouse', is_clade=True, is_constant=True)
2. all edges identified by a rule have the same but different value to the rest of the tree
>>> lf.setParamRule('omega', tip_names=['Human', 'HowlerMon'],
... outgroup_name='Mouse', is_clade=True)
3. allowing all edges identified by a rule to have different values of the parameter with the remaining tree edges having the same value
>>> lf.setParamRule('omega', tip_names=['Human', 'HowlerMon'],
... outgroup_name='Mouse', is_clade=True, is_independent=True)
4. allowing all edges to have a different value
>>> lf.setParamRule('omega', is_independent=True)
I'll demonstrate these cases sequentially as they involve gradually increasing the degrees of freedom in the model. First we'll constrain ``omega`` to equal 1 on the primate edges. I'll then optimise the model.
.. note:: here I'm specifying a constant value for the parameter and so I **must** use the argument ``value`` to set it. This not to be confused with the argument ``init`` that is used for providing initial (starting) values for fitting.
.. doctest::
:hide:
>>> lf.setParamRule('omega', init=1.0)
.. doctest::
>>> lf.setParamRule('omega', tip_names=['Human', 'HowlerMon'],
... outgroup_name='Mouse', is_clade=True, value=1.0, is_constant=True)
>>> lf.optimise(local=True)
>>> print lf
Likelihood Function Table
=====
kappa
-----
3.87
-----
===================================
edge parent length omega
-----------------------------------
Human edge.0 0.09 1.00
HowlerMon edge.0 0.12 1.00
edge.0 edge.1 0.12 0.92
Mouse edge.1 0.84 0.92
edge.1 root 0.06 0.92
NineBande root 0.28 0.92
DogFaced root 0.34 0.92
-----------------------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
>>> print lf.getLogLikelihood()
-8640.9...
>>> print lf.getNumFreeParams()
9
I'll now free up ``omega`` on the primate clade, but making it a single value shared by all primate lineages.
.. doctest::
>>> lf.setParamRule('omega', tip_names=['Human', 'HowlerMon'],
... outgroup_name='Mouse', is_clade=True, is_constant=False)
>>> lf.optimise(local=True)
>>> print lf
Likelihood Function Table
=====
kappa
-----
3.85
-----
===================================
edge parent length omega
-----------------------------------
Human edge.0 0.09 0.77
HowlerMon edge.0 0.12 0.77
edge.0 edge.1 0.12 0.92
Mouse edge.1 0.84 0.92
edge.1 root 0.06 0.92
NineBande root 0.28 0.92
DogFaced root 0.34 0.92
-----------------------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
>>> print lf.getLogLikelihood()
-8639.7...
>>> print lf.getNumFreeParams()
10
Finally I'll allow all primate edges to have different values of ``omega``.
.. doctest::
>>> lf.setParamRule('omega', tip_names=['Human', 'HowlerMon'],
... outgroup_name='Mouse', is_clade=True, is_independent=True)
>>> lf.optimise(local=True)
>>> print lf
Likelihood Function Table
=====
kappa
-----
3.85
-----
===================================
edge parent length omega
-----------------------------------
Human edge.0 0.09 0.59
HowlerMon edge.0 0.12 0.95
edge.0 edge.1 0.12 0.92
Mouse edge.1 0.84 0.92
edge.1 root 0.06 0.92
NineBande root 0.28 0.92
DogFaced root 0.34 0.92
-----------------------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
>>> print lf.getLogLikelihood()
-8638.9...
>>> print lf.getNumFreeParams()
11
We now allow ``omega`` to be different on all edges.
.. doctest::
>>> lf.setParamRule('omega', is_independent=True)
>>> lf.optimise(local=True)
>>> print lf
Likelihood Function Table
=====
kappa
-----
3.85
-----
===================================
edge parent length omega
-----------------------------------
Human edge.0 0.09 0.59
HowlerMon edge.0 0.12 0.95
edge.0 edge.1 0.12 1.13
Mouse edge.1 0.84 0.92
edge.1 root 0.06 0.38
NineBande root 0.28 1.27
DogFaced root 0.34 0.84
-----------------------------------
==============
motif mprobs
--------------
T 0.23
C 0.19
A 0.37
G 0.21
--------------
>>> print lf.getLogLikelihood()
-8636.1...
>>> print lf.getNumFreeParams()
15
PyCogent-1.5.3/doc/examples/seq_features.rst 000644 000765 000024 00000006254 11350301455 022047 0 ustar 00jrideout staff 000000 000000 .. _seq-annotations:
Advanced sequence handling
==========================
.. sectionauthor:: Gavin Huttley
Individual sequences and alignments can be manipulated by annotations. Most value in the genome sequences arises from sequence annotations regarding specific sequence feature types, e.g. genes with introns / exons, repeat sequences. These can be applied to an alignment either using data formats available from genome portals (e.g. GFF, or GenBank annotation formats) or by custom assignments.
Annotations can be added in two ways: using either the ``addAnnotation`` or the ``addFeature`` method. The distinction between these two is that ``addFeatures`` is more specialised. Features can be thought of as a type of annotation representing standard sequence properties eg introns/exons. Annotations are the more general case, such as a computed property which has, say a numerical value and a span.
For illustrative purposes we define a sequence with 2 exons and grab the 1\ :sup:`st` \ exon:
.. doctest::
>>> from cogent import DNA
>>> s = DNA.makeSequence("aagaagaagacccccaaaaaaaaaattttttttttaaaaaaaaaaaaa",
... Name="Orig")
>>> exon1 = s.addFeature('exon', 'exon1', [(10,15)])
>>> exon2 = s.addFeature('exon', 'exon2', [(30,40)])
Here, '``exon``' is the feature type, and '``exon#``' the feature name. The feature type is used for the display formatting, which won't be illustrated here, and also for selecting all features of the same type, shown below.
We could also have created an annotation using the ``addAnnotation`` method:
.. doctest::
>>> from cogent.core.annotation import Feature
>>> s2=DNA.makeSequence("aagaagaagacccccaaaaaaaaaattttttttttaaaaaaaaaaaaa",
... Name="Orig2")
>>> exon3 = s2.addAnnotation(Feature, 'exon', 'exon1', [(35,40)])
We can use the features (eg ``exon1``) to get the corresponding sequence region.
.. doctest::
>>> s[exon1]
DnaSequence(CCCCC)
You can query annotations by type and optionally by label, receiving a list of features:
.. doctest::
>>> exons = s.getAnnotationsMatching('exon')
>>> print exons
[exon "exon1" at [10:15]/48, exon "exon2" at [30:40]/48]
We can use this list to construct a pseudo-feature covering (or excluding) multiple features using ``getRegionCoveringAll``. For instance, getting all exons,
.. doctest::
>>> print s.getRegionCoveringAll(exons)
region "exon" at [10:15, 30:40]/48
>>> s.getRegionCoveringAll(exons).getSlice()
DnaSequence(CCCCCTT... 15)
or not exons (the exon *shadow*):
.. doctest::
>>> print s.getRegionCoveringAll(exons).getShadow().getSlice()
AAGAAGAAGAAAAAAAAAAATTTTTAAAAAAAA
The first of these essentially returns the CDS of the gene.
Features are themselves sliceable:
.. doctest::
>>> exon1[0:3].getSlice()
DnaSequence(CCC)
This approach to sequence / alignment handling allows the user to manipulate them according to things they know about such as genes or repeat elements. Most of this annotation data can be obtained from genome portals.
The toolkit can perform standard sequence / alignment manipulations such as getting a subset of sequences or aligned columns, translating sequences, reading and writing standard formats.
PyCogent-1.5.3/doc/examples/seqsim_alignment_simulation.rst 000644 000765 000024 00000006736 11361433354 025177 0 ustar 00jrideout staff 000000 000000 Seqsim Simple Alignment Simulation Example
==========================================
.. sectionauthor:: Julia Goodrich
This is a very simple example of how to use the ``seqsim`` module to simulate
an alignment for a tree starting with a random sequence and substitution rate
matrix (q). The rate matrix gives the rate constant of going from one character
in the sequence to another character in the sequence, the Q matrix determines
the rate of change of the sequence.
First we will perform the necessary imports:
* ``Rates`` is an object that stores the rate matrix data, it can also be used
to generate a random rate matrix given an ``Alphabet``.
* ``DnaUsage`` is a ``Usage`` object that stores the usage of each nucleotide.
* ``DnaPairs`` is an Alphabet it stores the DNA pairs (AA,AT,AC,...), it can
be passed into the ``Rates`` object, defining the rate matrix pairs for DNA.
* ``DNA`` is a ``MolType`` object for DNA.
* ``RangeNode`` is the main ``seqsim`` Node object, it allows for the easy
evolution of sequences.
* ``DndParser`` is a parser for a newick format tree.
.. doctest::
>>> from cogent.seqsim.usage import Rates, DnaUsage
>>> from cogent.core.usage import DnaPairs
>>> from cogent.core.moltype import DNA
>>> from cogent.core.alignment import Alignment
>>> from cogent.seqsim.tree import RangeNode
>>> from cogent.parse.tree import DndParser
Now, lets specify a 4 taxon tree:
.. doctest::
>>> t = DndParser('(a:0.4,b:0.3,(c:0.15,d:0.2)edge.0:0.1);',
... constructor = RangeNode)
To generate a random DNA sequence, we first specify nucleotide frequencies
with the ``DnaUsage`` object. Then we create a random DNA sequence that is
five bases long.
.. doctest::
>>> u = DnaUsage({'A':0.5,'T':0.2,'C':0.15,'G':0.25})
>>> s = DNA.ModelSeq(u.randomIndices(5))
>>> q = Rates.random(DnaPairs)
Set q at the base of the tree and propagate it to all nodes in the tree,
.. doctest::
>>> t.Q = q
>>> t.propagateAttr('Q')
Set a P matrix (probability matrix) from every Q matrix on each node:
P(t) = e^(Qt),
.. doctest::
>>> t.assignP()
Use ``evolve`` to evolve sequences for each tip, Note: must evolve sequence
data, not sequence object itself (for speed)
.. doctest::
>>> t.evolve(s._data)
Build alignment,
.. doctest::
>>> seqs = {}
>>> for n in t.tips():
... seqs[n.Name] = DNA.ModelSeq(n.Sequence)
>>> aln = Alignment(seqs)
The result is a Cogent ``Alignment`` object, which can be used the same way as
any other alignment object.
``evolveSeqs`` can be used instead of evolve to evolve multiple sequences
according to the same tree (can model either different genes, or different rate
categories within a gene that you then combine, etc...),
.. doctest::
>>> from numpy import concatenate
First you need to use ``assignPs`` to assign the proper P matricies given rates:
.. doctest::
>>> t.assignPs([.5, .75, 1])
There needs to be the same number of random sequences as there are rate
catigories so we create a list of 3 random sequences,
.. doctest::
>>> s = [DNA.ModelSeq(u.randomIndices(5))._data for i in range(0,3)]
Then use ``evolveSeqs`` to evolve a sequence for every tip with every rate.
.. doctest::
>>> t.evolveSeqs(s)
Now to concatenate the sequences,
.. doctest::
>>> seqs = {}
>>> for n in t.tips():
... for s in n.Sequences:
... seqs[n.Name] = DNA.ModelSeq(concatenate(tuple(n.Sequences)))
>>> aln = Alignment(seqs)
PyCogent-1.5.3/doc/examples/seqsim_aln_sim_user_alphabet.rst 000644 000765 000024 00000004245 11361433354 025266 0 ustar 00jrideout staff 000000 000000 Seqsim Alignment Simulation Example with Non-standard alphabet
==============================================================
.. sectionauthor:: Julia Goodrich
This is an example of how to use PyCogent's ``seqsim`` module to simulate an
alignment where the alphabet is defined by the user for a simple tree starting
with a random sequence and a random substitution rate matrix.
First we will perform the necessary imports.
.. doctest::
>>> from cogent.seqsim.usage import Rates
>>> from cogent.core.alignment import DenseAlignment
>>> from cogent.seqsim.tree import RangeNode
>>> from cogent.parse.tree import DndParser
>>> from cogent.core.alphabet import CharAlphabet
>>> from cogent.seqsim.usage import Usage
>>> from cogent.core.sequence import ModelSequence
Now, lets specify a 4 taxon tree:
.. doctest::
>>> t = DndParser('(a:0.4,b:0.3,(c:0.15,d:0.2)edge.0:0.1);',
... constructor = RangeNode)
Create the alphabet by passing in the characters to ``CharAlphabet`` then create
tuples of all the possible pairs using ** operator
.. doctest::
>>> Bases = CharAlphabet('ABCD')
>>> Pairs = Bases**2
Generate a random sequence with the new alphabet and a random rate matrix,
``Usage`` is being used to define character frequencies for the random
sequence. Then we create a random sequence of length five.
.. doctest::
>>> u = Usage({'A':0.5,'B':0.2,'C':0.15,'D':0.25}, Alphabet = Bases)
>>> s = ModelSequence(u.randomIndices(5))
>>> q = Rates.random(Pairs)
Set q at the base of the tree and propagate it to all nodes in the tree,
.. doctest::
>>> t.Q = q
>>> t.propagateAttr('Q')
Set a P matrix from every Q matrix on each node,
.. doctest::
>>> t.assignP()
Use ``evolve`` to evolve sequences for each tip, Note: must evolve sequence
data, not sequence object itself (for speed)
.. doctest::
>>> t.evolve(s._data)
Build alignment,
.. doctest::
>>> seqs = {}
>>> for n in t.tips():
... seqs[n.Name] = ModelSequence(n.Sequence,Bases)
>>> aln = DenseAlignment(seqs,Alphabet=Bases)
The result is a Cogent ``Alignment`` object, which can be used the same way as
any other alignment object.
PyCogent-1.5.3/doc/examples/seqsim_tree_sim.rst 000644 000765 000024 00000002503 11361433354 022550 0 ustar 00jrideout staff 000000 000000 Seqsim Simple Tree Simulation
=============================
.. sectionauthor:: Julia Goodrich
This is an example of how to use the birth-death model in cogent to simulate
a tree.
.. doctest::
>>> from cogent.seqsim.birth_death import BirthDeathModel, ExtinctionError,\
... TooManyTaxaError
Create a model with specific death probabilities per timestep using
``BirthProb`` and ``DeathProb``, and ``TimePerStep``. The desired maximum
number of taxa on the tree can be set using ``MaxTaxa``.
.. doctest::
>>> b = BirthDeathModel(BirthProb=0.2, DeathProb=0.1, TimePerStep=0.03,
... MaxTaxa=20)
To simulate a tree with an exact number of taxa, use the following loop.
The ``exact`` flag raises a ``TooManyTaxaError`` exception if the call produces
the wrong number of taxa (e.g. because too many things died in the same
timestep). An ``ExtinctionError`` is raised if the ancestral node dies off, or
all the nodes die off.
.. doctest::
>>> while True:
... try:
... t = b(exact=True)
... except (ExtinctionError, TooManyTaxaError):
... pass
... else:
... break
t now contains a ``RangeNode`` tree object that was returned, and can be used
the same ways any other tree object in cogent is used. For instance, ``seqsim``
can be used to evolve alignments.
PyCogent-1.5.3/doc/examples/simple.rst 000644 000765 000024 00000002234 11425201333 020641 0 ustar 00jrideout staff 000000 000000 The simplest script
===================
.. sectionauthor:: Gavin Huttley
This is just about the simplest possible Cogent script for evolutionary modelling. We use a canned nucleotide substitution model (the ``HKY85`` model) on just three primate species. As there is only unrooted tree possible, the sequence names are all that's required to make the tree.
.. doctest::
>>> from cogent.evolve.models import HKY85
>>> from cogent import LoadSeqs, LoadTree
>>> model = HKY85()
>>> aln = LoadSeqs("data/primate_cdx2_promoter.fasta")
>>> tree = LoadTree(tip_names=aln.Names)
>>> lf = model.makeLikelihoodFunction(tree)
>>> lf.setAlignment(aln)
>>> lf.optimise()
>>> print lf
Likelihood Function Table
======
kappa
------
5.9589
------
===========================
edge parent length
---------------------------
human root 0.0040
macaque root 0.0384
chimp root 0.0061
---------------------------
===============
motif mprobs
---------------
T 0.2552
C 0.2581
A 0.2439
G 0.2428
---------------
PyCogent-1.5.3/doc/examples/simulate_alignment.rst 000644 000765 000024 00000003150 11213034174 023231 0 ustar 00jrideout staff 000000 000000 Simulate an alignment
=====================
.. sectionauthor:: Gavin Huttley
How to simulate an alignment. For this example we just create a simple model using a four taxon tree with very different branch lengths, a Felsenstein model with very different nucleotide frequencies and a long alignment.
See the other examples for how to define other substitution models.
.. doctest::
>>> import sys
>>> from cogent import LoadTree
>>> from cogent.evolve import substitution_model
Specify the 4 taxon tree,
.. doctest::
>>> t = LoadTree(treestring='(a:0.4,b:0.3,(c:0.15,d:0.2)edge.0:0.1);')
Define our Felsenstein 1981 substitution model.
.. doctest::
>>> sm = substitution_model.Nucleotide(motif_probs = {'A': 0.5, 'C': 0.2,
... 'G': 0.2, 'T': 0.1}, model_gaps=False)
>>> lf = sm.makeLikelihoodFunction(t)
>>> lf.setConstantLengths()
>>> lf.setName('F81 model')
>>> print lf
F81 model
==========================
edge parent length
--------------------------
a root 0.4000
b root 0.3000
c edge.0 0.1500
d edge.0 0.2000
edge.0 root 0.1000
--------------------------
===============
motif mprobs
---------------
T 0.1000
C 0.2000
A 0.5000
G 0.2000
---------------
We'll now create a simulated alignment of length 1000 nucleotides.
.. doctest::
>>> simulated = lf.simulateAlignment(sequence_length=1000)
The result is a normal ``Cogent`` alignment object, which can be used in the same way as any other alignment object.
PyCogent-1.5.3/doc/examples/testing_multi_loci.rst 000644 000765 000024 00000006412 11425201333 023247 0 ustar 00jrideout staff 000000 000000 Likelihood analysis of multiple loci
====================================
.. sectionauthor:: Gavin Huttley
We want to know whether an exchangeability parameter is different between alignments. We will specify a null model, under which each alignment get's it's own motif probabilities and all alignments share branch lengths and the exchangeability parameter kappa (the transition / transversion ratio). We'll split the example alignment into two-pieces.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree, LoadTable
>>> from cogent.evolve.models import HKY85
>>> from cogent.recalculation.scope import EACH, ALL
>>> from cogent.maths.stats import chisqprob
>>> aln = LoadSeqs("data/long_testseqs.fasta")
>>> half = len(aln)/2
>>> aln1 = aln[:half]
>>> aln2 = aln[half:]
We provide names for those alignments, then construct the tree, model instances.
.. doctest::
>>> loci_names = ["1st-half", "2nd-half"]
>>> loci = [aln1, aln2]
>>> tree = LoadTree(tip_names=aln.getSeqNames())
>>> mod = HKY85()
To make a likelihood function with multiple alignments we provide the list of loci names. We can then specify a parameter (other than length) to be the same across the loci (using the imported ``ALL``) or different for each locus (using ``EACH``). We conduct a LR test as before.
.. doctest::
>>> lf = mod.makeLikelihoodFunction(tree,loci=loci_names,digits=2,space=3)
>>> lf.setParamRule("length", is_independent=False)
>>> lf.setParamRule('kappa', loci = ALL)
>>> lf.setAlignment(loci)
>>> lf.optimise(local=True)
>>> print lf
Likelihood Function Table
=========================
locus motif mprobs
-------------------------
1st-half T 0.22
1st-half C 0.18
1st-half A 0.38
1st-half G 0.21
2nd-half T 0.24
2nd-half C 0.19
2nd-half A 0.35
2nd-half G 0.22
-------------------------
==============
kappa length
--------------
3.98 0.13
--------------
>>> all_lnL = lf.getLogLikelihood()
>>> all_nfp = lf.getNumFreeParams()
>>> lf.setParamRule('kappa', loci = EACH)
>>> lf.optimise(local=True)
>>> print lf
Likelihood Function Table
================
locus kappa
----------------
1st-half 4.33
2nd-half 3.74
----------------
=========================
locus motif mprobs
-------------------------
1st-half T 0.22
1st-half C 0.18
1st-half A 0.38
1st-half G 0.21
2nd-half T 0.24
2nd-half C 0.19
2nd-half A 0.35
2nd-half G 0.22
-------------------------
======
length
------
0.13
------
>>> each_lnL = lf.getLogLikelihood()
>>> each_nfp = lf.getNumFreeParams()
>>> LR = 2 * (each_lnL - all_lnL)
>>> df = each_nfp - all_nfp
Just to pretty up the result display, I'll print a table consisting of the test statistics created on the fly.
>>> print LoadTable(header=['LR', 'df', 'p'],
... rows=[[LR, df, chisqprob(LR, df)]], digits=2, space=3)
================
LR df p
----------------
1.59 1 0.21
----------------
PyCogent-1.5.3/doc/examples/translate_dna.rst 000644 000765 000024 00000001371 11213034174 022172 0 ustar 00jrideout staff 000000 000000 Translating DNA into protein
============================
.. sectionauthor:: Gavin Huttley
To translate a DNA alignment, read it in assigning the DNA alphabet. Note setting ``aligned = False`` is critical for loading sequences of unequal length. Different genetic codes are available in ``cogent.core.genetic_code``
.. doctest::
>>> from cogent import LoadSeqs, DNA
>>> al = LoadSeqs('data/test2.fasta', moltype=DNA, aligned = False)
>>> pal = al.getTranslation()
>>> print pal.toFasta()
>DogFaced
ARSQQNRWVETKETCNDRQT
>HowlerMon
ARSQHNRWAESEETCNDRQT
>Human
ARSQHNRWAGSKETCNDRRT
>Mouse
AVSQQSRWAASKGTCNDRQV
>NineBande
RQQSRWAESKETCNDRQT
To save this result to a file, use the ``writeToFile`` method.
PyCogent-1.5.3/doc/examples/unifrac.rst 000644 000765 000024 00000003121 11215636452 021006 0 ustar 00jrideout staff 000000 000000 Run a Fast Unifrac community analysis
=====================================
.. sectionauthor:: Justin Kuczynski
Below is a simple example of using the fast unifrac function.
first we import some tools
.. doctest::
>>> from cogent.parse.tree import DndParser
>>> from cogent.maths.unifrac.fast_unifrac import fast_unifrac
>>> from cogent.maths.unifrac.fast_tree import UniFracTreeNode
then we make a small example tree with tips B, C, D representing the relationship
between species B, C, and D
.. doctest::
>>> tree_str = "(B:0.2,(C:0.3,D:0.4)E:0.6)F;"
>>> tr = DndParser(tree_str, UniFracTreeNode)
>>> print tr.asciiArt() # doctest: +SKIP
/-B
-F-------|
| /-C
\E-------|
\-D
here's what the sample (rows) by sequence (cols) abundance matrix looks like::
... [10,11,0]
... [2,0,9]
... [2,2,2]
and here it is in dict format for unifrac
.. doctest::
>>> envs = {'B':{'sample1':10, 'sample2':2, 'sample3':2},
... 'C':{'sample1':11,'sample2':0, 'sample3':2},
... 'D':{'sample1':0, 'sample2':9, 'sample3':2}
... }
now we run unifrac::
>>> res = fast_unifrac(tr, envs)
>>> print res['distance_matrix'] # doctest: +SKIP
(array([[ 0. , 0.46666667, 0.26666667],
[ 0.46666667, 0. , 0.2 ],
[ 0.26666667, 0.2 , 0. ]]),
['sample1', 'sample2', 'sample3'])
the pcoa results are misleading for such a small dataset, but the distance
matrix is accurate
PyCogent-1.5.3/doc/examples/unrestricted_nucleotide.rst 000644 000765 000024 00000007064 11425201333 024304 0 ustar 00jrideout staff 000000 000000 Specifying and using an unrestricted nucleotide substitution model
==================================================================
.. sectionauthor:: Gavin Huttley
Do standard ``cogent`` imports.
.. doctest::
>>> from cogent import LoadSeqs, LoadTree, DNA
>>> from cogent.evolve.predicate import MotifChange
>>> from cogent.evolve.substitution_model import Nucleotide
.. don't pollute screen during execution with uninteresting warning
.. doctest::
:hide:
>>> import warnings
>>> warnings.filterwarnings("ignore", "Model not reversible")
To specify substitution models we use the ``MotifChange`` class from predicates. In the case of an unrestricted nucleotide model, we specify 11 such ``MotifChanges``, the last possible change being ignored (with the result it is constrained to equal 1, thus calibrating the matrix). Also note that this is a non-reversible model and thus we can't assume the nucleotide frequencies estimated from the alignments are reasonable estimates for the root frequencies. We therefore specify they are to be optimised using ``optimise_motif_probs`` argument.
.. doctest::
>>> ACTG = list('ACTG')
>>> preds = [MotifChange(i, j, forward_only=True) for i in ACTG for j in ACTG if i != j]
>>> del(preds[-1])
>>> preds
[A>C, A>T, A>G, C>A, C>T, C>G, T>A, T>C, T>G, G>A, G>C]
>>> sm = Nucleotide(predicates=preds, recode_gaps=True,
... optimise_motif_probs=True)
>>> print sm
Nucleotide ( name = ''; type = 'None'; params = ['A>T', 'C>G', 'T>G',...
We'll illustrate this with a sample alignment and tree in ``data/primate_cdx2_promoter.fasta``.
.. doctest::
>>> al = LoadSeqs("data/primate_cdx2_promoter.fasta", moltype=DNA)
>>> al
3 x 1525 dna alignment: human[AGCGCCCGCGG...], macaque[AGC...
>>> tr = LoadTree(tip_names=al.Names)
>>> print tr
(human,macaque,chimp)root;
We now construct the parameter controller with each predicate constant across the tree, get the likelihood function calculator and optimise the function.
.. doctest::
>>> lf = sm.makeLikelihoodFunction(tr, digits=2, space=3)
>>> lf.setAlignment(al)
>>> lf.setName('Unrestricted model')
>>> lf.optimise(local=True)
We just used the Powell optimiser, as this works quite well.
.. doctest::
>>> print lf
Unrestricted model
==========================================================================
A>C A>G A>T C>A C>G C>T G>A G>C T>A T>C T>G
--------------------------------------------------------------------------
0.49 4.88 1.04 2.04 0.99 7.89 9.00 1.55 0.48 5.53 1.57
--------------------------------------------------------------------------
=========================
edge parent length
-------------------------
human root 0.00
macaque root 0.04
chimp root 0.01
-------------------------
==============
motif mprobs
--------------
T 0.26
C 0.26
A 0.24
G 0.24
--------------
This data set consists of species that are relatively close for a modest length alignment. As a result, doing something like allowing the parameters to differ between edges is not particularly well supported. If you have lots of data it makes sense to allow parameters to differ between edges, which can be specified by modifying the ``lf`` as follows.
.. doctest::
>>> for pred in preds:
... lf.setParamRule(pred, is_independent=True)
You would then re-optimise the model as above.
PyCogent-1.5.3/doc/examples/using_parallel.py 000644 000765 000024 00000002036 11502775461 022207 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
"""An example of how to distribute jobs across multiple cpu's. Note that this example works even if on a single cpu since the parallel assigns a `fake` communicator in that instance.
"""
from cogent.util import parallel
__author__ = "Gavin Huttleu"
__copyright__ = "Copyright 2007-2011, The Cogent Project"
__contributors__ = ["Gavin Huttley", "Peter Maxwell"]
__license__ = "GPL"
__version__ = "1.3.0.dev"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
JOBS = range(12) # nonsense jobs, just a list of numbers to be printed.
# we divide up the CPUs into (at most) 12 groups of (at least) 1 CPU.
(comm, leftover) = parallel.getSplitCommunicators(len(JOBS))
# and set the cpu's available to lower levels
parallel.push(leftover)
try:
for job in JOBS:
if not job % comm.size == comm.rank:
continue
print "My ID=%d, my message=%s" % (comm.rank, JOBS[job])
finally:
# always restore the original parallel context
parallel.pop(leftover)
PyCogent-1.5.3/doc/data/1HQF.pdb 000644 000765 000024 00002374042 11361362322 017117 0 ustar 00jrideout staff 000000 000000 HEADER HYDROLASE 16-DEC-00 1HQF
TITLE CRYSTAL STRUCTURE OF THE BINUCLEAR MANGANESE METALLOENZYME
TITLE 2 ARGINASE COMPLEXED WITH N-HYDROXY-L-ARGININE
COMPND MOL_ID: 1;
COMPND 2 MOLECULE: ARGINASE 1;
COMPND 3 CHAIN: A, B, C;
COMPND 4 EC: 3.5.3.1;
COMPND 5 ENGINEERED: YES
SOURCE MOL_ID: 1;
SOURCE 2 ORGANISM_SCIENTIFIC: RATTUS NORVEGICUS;
SOURCE 3 ORGANISM_COMMON: NORWAY RAT;
SOURCE 4 ORGANISM_TAXID: 10116;
SOURCE 5 EXPRESSION_SYSTEM: ESCHERICHIA COLI;
SOURCE 6 EXPRESSION_SYSTEM_TAXID: 562
KEYWDS ARGINASE, N-HYDROXY-L-ARGININE (NOHA), BINUCLEAR MANGANESE
KEYWDS 2 CLUSTER, METALLOENZYME, HYDROLASE
EXPDTA X-RAY DIFFRACTION
AUTHOR J.D.COX,E.CAMA,D.M.COLLELUORI,D.E.ASH,D.W.CHRISTIANSON
REVDAT 3 24-FEB-09 1HQF 1 VERSN
REVDAT 2 01-APR-03 1HQF 1 JRNL
REVDAT 1 04-APR-01 1HQF 0
JRNL AUTH J.D.COX,E.CAMA,D.M.COLLELUORI,S.PETHE,J.L.BOUCHER,
JRNL AUTH 2 D.MANSUY,D.E.ASH,D.W.CHRISTIANSON
JRNL TITL MECHANISTIC AND METABOLIC INFERENCES FROM THE
JRNL TITL 2 BINDING OF SUBSTRATE ANALOGUES AND PRODUCTS TO
JRNL TITL 3 ARGINASE.
JRNL REF BIOCHEMISTRY V. 40 2689 2001
JRNL REFN ISSN 0006-2960
JRNL PMID 11258880
JRNL DOI 10.1021/BI002318+
REMARK 1
REMARK 2
REMARK 2 RESOLUTION. 2.90 ANGSTROMS.
REMARK 3
REMARK 3 REFINEMENT.
REMARK 3 PROGRAM : CNS
REMARK 3 AUTHORS : BRUNGER,ADAMS,CLORE,DELANO,GROS,GROSSE-
REMARK 3 : KUNSTLEVE,JIANG,KUSZEWSKI,NILGES, PANNU,
REMARK 3 : READ,RICE,SIMONSON,WARREN
REMARK 3
REMARK 3 REFINEMENT TARGET : ENGH & HUBER
REMARK 3
REMARK 3 DATA USED IN REFINEMENT.
REMARK 3 RESOLUTION RANGE HIGH (ANGSTROMS) : 2.90
REMARK 3 RESOLUTION RANGE LOW (ANGSTROMS) : 30.00
REMARK 3 DATA CUTOFF (SIGMA(F)) : 2.000
REMARK 3 DATA CUTOFF HIGH (ABS(F)) : NULL
REMARK 3 DATA CUTOFF LOW (ABS(F)) : NULL
REMARK 3 COMPLETENESS (WORKING+TEST) (%) : NULL
REMARK 3 NUMBER OF REFLECTIONS : 17125
REMARK 3
REMARK 3 FIT TO DATA USED IN REFINEMENT.
REMARK 3 CROSS-VALIDATION METHOD : NULL
REMARK 3 FREE R VALUE TEST SET SELECTION : RANDOM
REMARK 3 R VALUE (WORKING SET) : 0.265
REMARK 3 FREE R VALUE : 0.289
REMARK 3 FREE R VALUE TEST SET SIZE (%) : NULL
REMARK 3 FREE R VALUE TEST SET COUNT : 781
REMARK 3 ESTIMATED ERROR OF FREE R VALUE : NULL
REMARK 3
REMARK 3 FIT IN THE HIGHEST RESOLUTION BIN.
REMARK 3 TOTAL NUMBER OF BINS USED : NULL
REMARK 3 BIN RESOLUTION RANGE HIGH (A) : NULL
REMARK 3 BIN RESOLUTION RANGE LOW (A) : NULL
REMARK 3 BIN COMPLETENESS (WORKING+TEST) (%) : NULL
REMARK 3 REFLECTIONS IN BIN (WORKING SET) : NULL
REMARK 3 BIN R VALUE (WORKING SET) : NULL
REMARK 3 BIN FREE R VALUE : NULL
REMARK 3 BIN FREE R VALUE TEST SET SIZE (%) : NULL
REMARK 3 BIN FREE R VALUE TEST SET COUNT : NULL
REMARK 3 ESTIMATED ERROR OF BIN FREE R VALUE : NULL
REMARK 3
REMARK 3 NUMBER OF NON-HYDROGEN ATOMS USED IN REFINEMENT.
REMARK 3 PROTEIN ATOMS : 7185
REMARK 3 NUCLEIC ACID ATOMS : 0
REMARK 3 HETEROGEN ATOMS : 45
REMARK 3 SOLVENT ATOMS : 15
REMARK 3
REMARK 3 B VALUES.
REMARK 3 FROM WILSON PLOT (A**2) : NULL
REMARK 3 MEAN B VALUE (OVERALL, A**2) : NULL
REMARK 3 OVERALL ANISOTROPIC B VALUE.
REMARK 3 B11 (A**2) : NULL
REMARK 3 B22 (A**2) : NULL
REMARK 3 B33 (A**2) : NULL
REMARK 3 B12 (A**2) : NULL
REMARK 3 B13 (A**2) : NULL
REMARK 3 B23 (A**2) : NULL
REMARK 3
REMARK 3 ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM LUZZATI PLOT (A) : NULL
REMARK 3 ESD FROM SIGMAA (A) : NULL
REMARK 3 LOW RESOLUTION CUTOFF (A) : NULL
REMARK 3
REMARK 3 CROSS-VALIDATED ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM C-V LUZZATI PLOT (A) : NULL
REMARK 3 ESD FROM C-V SIGMAA (A) : NULL
REMARK 3
REMARK 3 RMS DEVIATIONS FROM IDEAL VALUES.
REMARK 3 BOND LENGTHS (A) : 0.008
REMARK 3 BOND ANGLES (DEGREES) : 1.50
REMARK 3 DIHEDRAL ANGLES (DEGREES) : NULL
REMARK 3 IMPROPER ANGLES (DEGREES) : NULL
REMARK 3
REMARK 3 ISOTROPIC THERMAL MODEL : NULL
REMARK 3
REMARK 3 ISOTROPIC THERMAL FACTOR RESTRAINTS. RMS SIGMA
REMARK 3 MAIN-CHAIN BOND (A**2) : NULL ; NULL
REMARK 3 MAIN-CHAIN ANGLE (A**2) : NULL ; NULL
REMARK 3 SIDE-CHAIN BOND (A**2) : NULL ; NULL
REMARK 3 SIDE-CHAIN ANGLE (A**2) : NULL ; NULL
REMARK 3
REMARK 3 BULK SOLVENT MODELING.
REMARK 3 METHOD USED : NULL
REMARK 3 KSOL : NULL
REMARK 3 BSOL : NULL
REMARK 3
REMARK 3 NCS MODEL : NULL
REMARK 3
REMARK 3 NCS RESTRAINTS. RMS SIGMA/WEIGHT
REMARK 3 GROUP 1 POSITIONAL (A) : NULL ; NULL
REMARK 3 GROUP 1 B-FACTOR (A**2) : NULL ; NULL
REMARK 3
REMARK 3 PARAMETER FILE 1 : NULL
REMARK 3 TOPOLOGY FILE 1 : NULL
REMARK 3
REMARK 3 OTHER REFINEMENT REMARKS: NULL
REMARK 4
REMARK 4 1HQF COMPLIES WITH FORMAT V. 3.15, 01-DEC-08
REMARK 100
REMARK 100 THIS ENTRY HAS BEEN PROCESSED BY RCSB ON 18-DEC-00.
REMARK 100 THE RCSB ID CODE IS RCSB012517.
REMARK 200
REMARK 200 EXPERIMENTAL DETAILS
REMARK 200 EXPERIMENT TYPE : X-RAY DIFFRACTION
REMARK 200 DATE OF DATA COLLECTION : 20-JUN-00
REMARK 200 TEMPERATURE (KELVIN) : 100
REMARK 200 PH : 8.5
REMARK 200 NUMBER OF CRYSTALS USED : 2
REMARK 200
REMARK 200 SYNCHROTRON (Y/N) : Y
REMARK 200 RADIATION SOURCE : SSRL
REMARK 200 BEAMLINE : BL7-1
REMARK 200 X-RAY GENERATOR MODEL : NULL
REMARK 200 MONOCHROMATIC OR LAUE (M/L) : M
REMARK 200 WAVELENGTH OR RANGE (A) : 1.08
REMARK 200 MONOCHROMATOR : FILTER
REMARK 200 OPTICS : NULL
REMARK 200
REMARK 200 DETECTOR TYPE : IMAGE PLATE
REMARK 200 DETECTOR MANUFACTURER : MAR SCANNER 345 MM PLATE
REMARK 200 INTENSITY-INTEGRATION SOFTWARE : DENZO
REMARK 200 DATA SCALING SOFTWARE : SCALEPACK
REMARK 200
REMARK 200 NUMBER OF UNIQUE REFLECTIONS : 17424
REMARK 200 RESOLUTION RANGE HIGH (A) : 2.900
REMARK 200 RESOLUTION RANGE LOW (A) : 30.000
REMARK 200 REJECTION CRITERIA (SIGMA(I)) : 2.000
REMARK 200
REMARK 200 OVERALL.
REMARK 200 COMPLETENESS FOR RANGE (%) : 83.7
REMARK 200 DATA REDUNDANCY : 1.800
REMARK 200 R MERGE (I) : 0.06400
REMARK 200 R SYM (I) : NULL
REMARK 200 FOR THE DATA SET : 11.4000
REMARK 200
REMARK 200 IN THE HIGHEST RESOLUTION SHELL.
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE HIGH (A) : 2.90
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE LOW (A) : 3.00
REMARK 200 COMPLETENESS FOR SHELL (%) : 86.7
REMARK 200 DATA REDUNDANCY IN SHELL : 1.80
REMARK 200 R MERGE FOR SHELL (I) : 0.30200
REMARK 200 R SYM FOR SHELL (I) : NULL
REMARK 200 FOR SHELL : NULL
REMARK 200
REMARK 200 DIFFRACTION PROTOCOL: SINGLE WAVELENGTH
REMARK 200 METHOD USED TO DETERMINE THE STRUCTURE: MOLECULAR REPLACEMENT
REMARK 200 SOFTWARE USED: AMORE
REMARK 200 STARTING MODEL: NULL
REMARK 200
REMARK 200 REMARK: NULL
REMARK 280
REMARK 280 CRYSTAL
REMARK 280 SOLVENT CONTENT, VS (%): 48.35
REMARK 280 MATTHEWS COEFFICIENT, VM (ANGSTROMS**3/DA): 2.38
REMARK 280
REMARK 280 CRYSTALLIZATION CONDITIONS: PEG 8000, BICINE, MANGANESE
REMARK 280 CHLORIDE, PH 8.5, VAPOR DIFFUSION, HANGING DROP, TEMPERATURE
REMARK 280 277K
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY
REMARK 290 SYMMETRY OPERATORS FOR SPACE GROUP: P 32
REMARK 290
REMARK 290 SYMOP SYMMETRY
REMARK 290 NNNMMM OPERATOR
REMARK 290 1555 X,Y,Z
REMARK 290 2555 -Y,X-Y,Z+2/3
REMARK 290 3555 -X+Y,-X,Z+1/3
REMARK 290
REMARK 290 WHERE NNN -> OPERATOR NUMBER
REMARK 290 MMM -> TRANSLATION VECTOR
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY TRANSFORMATIONS
REMARK 290 THE FOLLOWING TRANSFORMATIONS OPERATE ON THE ATOM/HETATM
REMARK 290 RECORDS IN THIS ENTRY TO PRODUCE CRYSTALLOGRAPHICALLY
REMARK 290 RELATED MOLECULES.
REMARK 290 SMTRY1 1 1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 1 0.000000 1.000000 0.000000 0.00000
REMARK 290 SMTRY3 1 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 2 -0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 2 0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 2 0.000000 0.000000 1.000000 74.66667
REMARK 290 SMTRY1 3 -0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 3 -0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 3 0.000000 0.000000 1.000000 37.33333
REMARK 290
REMARK 290 REMARK: NULL
REMARK 300
REMARK 300 BIOMOLECULE: 1
REMARK 300 SEE REMARK 350 FOR THE AUTHOR PROVIDED AND/OR PROGRAM
REMARK 300 GENERATED ASSEMBLY INFORMATION FOR THE STRUCTURE IN
REMARK 300 THIS ENTRY. THE REMARK MAY ALSO PROVIDE INFORMATION ON
REMARK 300 BURIED SURFACE AREA.
REMARK 300 REMARK: THE BIOLOGICAL ASSEMBLY IS A TRIMER
REMARK 350
REMARK 350 COORDINATES FOR A COMPLETE MULTIMER REPRESENTING THE KNOWN
REMARK 350 BIOLOGICALLY SIGNIFICANT OLIGOMERIZATION STATE OF THE
REMARK 350 MOLECULE CAN BE GENERATED BY APPLYING BIOMT TRANSFORMATIONS
REMARK 350 GIVEN BELOW. BOTH NON-CRYSTALLOGRAPHIC AND
REMARK 350 CRYSTALLOGRAPHIC OPERATIONS ARE GIVEN.
REMARK 350
REMARK 350 BIOMOLECULE: 1
REMARK 350 AUTHOR DETERMINED BIOLOGICAL UNIT: TRIMERIC
REMARK 350 SOFTWARE DETERMINED QUATERNARY STRUCTURE: TRIMERIC
REMARK 350 SOFTWARE USED: PISA
REMARK 350 TOTAL BURIED SURFACE AREA: 6090 ANGSTROM**2
REMARK 350 SURFACE AREA OF THE COMPLEX: 34170 ANGSTROM**2
REMARK 350 CHANGE IN SOLVENT FREE ENERGY: -42.0 KCAL/MOL
REMARK 350 APPLY THE FOLLOWING TO CHAINS: A, B, C
REMARK 350 BIOMT1 1 1.000000 0.000000 0.000000 0.00000
REMARK 350 BIOMT2 1 0.000000 1.000000 0.000000 0.00000
REMARK 350 BIOMT3 1 0.000000 0.000000 1.000000 0.00000
REMARK 465
REMARK 465 MISSING RESIDUES
REMARK 465 THE FOLLOWING RESIDUES WERE NOT LOCATED IN THE
REMARK 465 EXPERIMENT. (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN
REMARK 465 IDENTIFIER; SSSEQ=SEQUENCE NUMBER; I=INSERTION CODE.)
REMARK 465
REMARK 465 M RES C SSSEQI
REMARK 465 MET A 1
REMARK 465 SER A 2
REMARK 465 SER A 3
REMARK 465 LYS A 4
REMARK 465 PRO A 5
REMARK 465 LYS A 320
REMARK 465 PRO A 321
REMARK 465 PRO A 322
REMARK 465 LYS A 323
REMARK 465 MET B 1
REMARK 465 SER B 2
REMARK 465 SER B 3
REMARK 465 LYS B 4
REMARK 465 PRO B 5
REMARK 465 LYS B 320
REMARK 465 PRO B 321
REMARK 465 PRO B 322
REMARK 465 LYS B 323
REMARK 465 MET C 1
REMARK 465 SER C 2
REMARK 465 SER C 3
REMARK 465 LYS C 4
REMARK 465 PRO C 5
REMARK 465 LYS C 320
REMARK 465 PRO C 321
REMARK 465 PRO C 322
REMARK 465 LYS C 323
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: COVALENT BOND ANGLES
REMARK 500
REMARK 500 THE STEREOCHEMICAL PARAMETERS OF THE FOLLOWING RESIDUES
REMARK 500 HAVE VALUES WHICH DEVIATE FROM EXPECTED VALUES BY MORE
REMARK 500 THAN 6*RMSD (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN
REMARK 500 IDENTIFIER; SSEQ=SEQUENCE NUMBER; I=INSERTION CODE).
REMARK 500
REMARK 500 STANDARD TABLE:
REMARK 500 FORMAT: (10X,I3,1X,A3,1X,A1,I4,A1,3(1X,A4,2X),12X,F5.1)
REMARK 500
REMARK 500 EXPECTED VALUES PROTEIN: ENGH AND HUBER, 1999
REMARK 500 EXPECTED VALUES NUCLEIC ACID: CLOWNEY ET AL 1996
REMARK 500
REMARK 500 M RES CSSEQI ATM1 ATM2 ATM3
REMARK 500 GLY A 99 N - CA - C ANGL. DEV. = -16.9 DEGREES
REMARK 500 GLY B 99 N - CA - C ANGL. DEV. = -16.9 DEGREES
REMARK 500 GLY C 99 N - CA - C ANGL. DEV. = -16.9 DEGREES
REMARK 500
REMARK 500 REMARK: NULL
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: TORSION ANGLES
REMARK 500
REMARK 500 TORSION ANGLES OUTSIDE THE EXPECTED RAMACHANDRAN REGIONS:
REMARK 500 (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN IDENTIFIER;
REMARK 500 SSEQ=SEQUENCE NUMBER; I=INSERTION CODE).
REMARK 500
REMARK 500 STANDARD TABLE:
REMARK 500 FORMAT:(10X,I3,1X,A3,1X,A1,I4,A1,4X,F7.2,3X,F7.2)
REMARK 500
REMARK 500 EXPECTED VALUES: GJ KLEYWEGT AND TA JONES (1996). PHI/PSI-
REMARK 500 CHOLOGY: RAMACHANDRAN REVISITED. STRUCTURE 4, 1395 - 1400
REMARK 500
REMARK 500 M RES CSSEQI PSI PHI
REMARK 500 PRO A 14 85.88 -48.72
REMARK 500 SER A 16 -5.78 -165.06
REMARK 500 LEU A 53 103.77 -51.24
REMARK 500 ASN A 60 75.10 50.01
REMARK 500 PRO A 63 81.46 -69.84
REMARK 500 PHE A 64 83.60 -41.96
REMARK 500 GLN A 65 -85.83 73.46
REMARK 500 ASN A 69 45.42 29.26
REMARK 500 GLN A 88 -35.97 -39.68
REMARK 500 HIS A 101 7.39 -69.68
REMARK 500 THR A 135 134.44 -30.16
REMARK 500 SER A 136 30.35 -99.07
REMARK 500 SER A 137 147.43 -171.80
REMARK 500 LEU A 140 -7.95 -56.98
REMARK 500 GLN A 143 -17.02 -140.95
REMARK 500 PRO A 144 -39.73 -27.56
REMARK 500 GLU A 151 0.66 -58.92
REMARK 500 ASP A 158 133.47 -39.00
REMARK 500 PRO A 160 90.93 -57.05
REMARK 500 PRO A 167 108.91 -46.32
REMARK 500 ARG A 180 -2.77 -154.05
REMARK 500 PRO A 184 -73.06 -43.78
REMARK 500 GLU A 214 -75.17 -61.77
REMARK 500 THR A 215 -37.19 -28.53
REMARK 500 ARG A 222 -84.88 -85.02
REMARK 500 VAL A 233 -25.58 -28.46
REMARK 500 LYS A 266 2.48 -56.69
REMARK 500 ASN A 279 79.63 -113.91
REMARK 500 PRO A 280 0.83 -43.08
REMARK 500 VAL A 289 -70.82 -63.14
REMARK 500 LEU A 301 -12.50 -49.38
REMARK 500 THR A 306 126.95 -33.68
REMARK 500 PRO B 14 85.85 -48.65
REMARK 500 SER B 16 -5.73 -165.10
REMARK 500 LEU B 53 103.76 -51.23
REMARK 500 ASN B 60 75.07 50.02
REMARK 500 PRO B 63 81.46 -69.86
REMARK 500 PHE B 64 83.61 -41.96
REMARK 500 GLN B 65 -85.84 73.46
REMARK 500 ASN B 69 45.41 29.29
REMARK 500 GLN B 88 -35.81 -39.74
REMARK 500 HIS B 101 7.29 -69.59
REMARK 500 THR B 135 134.44 -30.13
REMARK 500 SER B 136 30.33 -99.04
REMARK 500 SER B 137 147.42 -171.82
REMARK 500 LEU B 140 -7.94 -56.99
REMARK 500 GLN B 143 -17.05 -140.95
REMARK 500 PRO B 144 -39.71 -27.55
REMARK 500 GLU B 151 0.66 -58.93
REMARK 500 ASP B 158 133.44 -38.97
REMARK 500 PRO B 160 90.85 -56.98
REMARK 500 PRO B 167 108.92 -46.33
REMARK 500 ARG B 180 -2.74 -154.05
REMARK 500 PRO B 184 -73.14 -43.72
REMARK 500 GLU B 214 -75.16 -61.81
REMARK 500 THR B 215 -37.16 -28.54
REMARK 500 ARG B 222 -84.88 -84.96
REMARK 500 VAL B 233 -25.55 -28.51
REMARK 500 LYS B 266 2.55 -56.75
REMARK 500 ASN B 279 79.62 -113.87
REMARK 500 PRO B 280 0.78 -43.02
REMARK 500 VAL B 289 -70.76 -63.19
REMARK 500 LEU B 301 -12.54 -49.31
REMARK 500 THR B 306 126.94 -33.71
REMARK 500 PRO C 14 85.85 -48.68
REMARK 500 SER C 16 -5.79 -165.09
REMARK 500 LEU C 53 103.78 -51.23
REMARK 500 ASN C 60 75.10 50.02
REMARK 500 PRO C 63 81.43 -69.79
REMARK 500 PHE C 64 83.59 -41.92
REMARK 500 GLN C 65 -85.86 73.49
REMARK 500 ASN C 69 45.43 29.21
REMARK 500 GLN C 88 -36.05 -39.63
REMARK 500 HIS C 101 7.37 -69.69
REMARK 500 THR C 135 134.44 -30.07
REMARK 500 SER C 136 30.32 -99.11
REMARK 500 SER C 137 147.43 -171.81
REMARK 500 LEU C 140 -7.99 -56.95
REMARK 500 GLN C 143 -17.05 -140.94
REMARK 500 PRO C 144 -39.76 -27.49
REMARK 500 GLU C 151 0.69 -58.91
REMARK 500 ASP C 158 133.48 -39.02
REMARK 500 PRO C 160 90.90 -57.03
REMARK 500 PRO C 167 108.93 -46.31
REMARK 500 ARG C 180 -2.76 -154.04
REMARK 500 PRO C 184 -73.09 -43.76
REMARK 500 GLU C 214 -75.17 -61.77
REMARK 500 THR C 215 -37.13 -28.58
REMARK 500 ARG C 222 -84.82 -85.02
REMARK 500 VAL C 233 -25.63 -28.42
REMARK 500 LYS C 266 2.48 -56.66
REMARK 500 ASN C 279 79.62 -113.88
REMARK 500 PRO C 280 0.85 -43.07
REMARK 500 VAL C 289 -70.88 -63.14
REMARK 500 LEU C 301 -12.51 -49.33
REMARK 500 THR C 306 126.95 -33.67
REMARK 500
REMARK 500 REMARK: NULL
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: PLANAR GROUPS
REMARK 500
REMARK 500 PLANAR GROUPS IN THE FOLLOWING RESIDUES HAVE A TOTAL
REMARK 500 RMS DISTANCE OF ALL ATOMS FROM THE BEST-FIT PLANE
REMARK 500 BY MORE THAN AN EXPECTED VALUE OF 6*RMSD, WITH AN
REMARK 500 RMSD 0.02 ANGSTROMS, OR AT LEAST ONE ATOM HAS
REMARK 500 AN RMSD GREATER THAN THIS VALUE
REMARK 500 (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN IDENTIFIER;
REMARK 500 SSEQ=SEQUENCE NUMBER; I=INSERTION CODE).
REMARK 500
REMARK 500 M RES CSSEQI RMS TYPE
REMARK 500 TYR A 176 0.07 SIDE_CHAIN
REMARK 500 TYR B 176 0.07 SIDE_CHAIN
REMARK 500 TYR C 176 0.07 SIDE_CHAIN
REMARK 500
REMARK 500 REMARK: NULL
REMARK 620
REMARK 620 METAL COORDINATION
REMARK 620 (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN IDENTIFIER;
REMARK 620 SSEQ=SEQUENCE NUMBER; I=INSERTION CODE):
REMARK 620
REMARK 620 COORDINATION ANGLES FOR: M RES CSSEQI METAL
REMARK 620 MN A 500 MN
REMARK 620 N RES CSSEQI ATOM
REMARK 620 1 ASP A 124 OD2
REMARK 620 2 HAR A 906 OH1 87.5
REMARK 620 3 ASP A 128 OD2 77.2 119.9
REMARK 620 4 HIS A 101 ND1 78.9 114.6 118.5
REMARK 620 N 1 2 3
REMARK 620
REMARK 620 COORDINATION ANGLES FOR: M RES CSSEQI METAL
REMARK 620 MN A 501 MN
REMARK 620 N RES CSSEQI ATOM
REMARK 620 1 ASP A 124 OD1
REMARK 620 2 ASP A 232 OD2 74.9
REMARK 620 3 ASP A 234 OD1 91.6 75.8
REMARK 620 4 ASP A 234 OD2 130.8 61.4 57.9
REMARK 620 5 HAR A 906 OH1 106.8 58.3 122.1 69.3
REMARK 620 6 HIS A 126 ND1 87.5 157.2 119.8 140.0 115.6
REMARK 620 7 HAR A 906 NH1 108.5 90.6 152.0 94.1 34.3 81.3
REMARK 620 N 1 2 3 4 5 6
REMARK 620
REMARK 620 COORDINATION ANGLES FOR: M RES CSSEQI METAL
REMARK 620 MN B 502 MN
REMARK 620 N RES CSSEQI ATOM
REMARK 620 1 HIS B 101 ND1
REMARK 620 2 ASP B 124 OD2 78.9
REMARK 620 3 HAR B 907 OH1 114.6 87.5
REMARK 620 4 ASP B 128 OD2 118.5 77.2 119.9
REMARK 620 N 1 2 3
REMARK 620
REMARK 620 COORDINATION ANGLES FOR: M RES CSSEQI METAL
REMARK 620 MN B 503 MN
REMARK 620 N RES CSSEQI ATOM
REMARK 620 1 ASP B 232 OD2
REMARK 620 2 HAR B 907 OH1 58.3
REMARK 620 3 ASP B 124 OD1 74.9 106.8
REMARK 620 4 ASP B 234 OD1 75.7 123.6 89.1
REMARK 620 5 ASP B 234 OD2 58.4 71.2 126.3 56.8
REMARK 620 6 HIS B 126 ND1 157.2 115.5 87.5 119.0 143.6
REMARK 620 7 HAR B 907 NH1 90.6 34.3 108.4 154.3 97.5 81.3
REMARK 620 N 1 2 3 4 5 6
REMARK 620
REMARK 620 COORDINATION ANGLES FOR: M RES CSSEQI METAL
REMARK 620 MN C 504 MN
REMARK 620 N RES CSSEQI ATOM
REMARK 620 1 HAR C 908 OH1
REMARK 620 2 HIS C 101 ND1 114.6
REMARK 620 3 ASP C 124 OD2 87.5 78.9
REMARK 620 4 ASP C 128 OD2 119.9 118.5 77.2
REMARK 620 N 1 2 3
REMARK 620
REMARK 620 COORDINATION ANGLES FOR: M RES CSSEQI METAL
REMARK 620 MN C 505 MN
REMARK 620 N RES CSSEQI ATOM
REMARK 620 1 HAR C 908 OH1
REMARK 620 2 ASP C 124 OD1 106.8
REMARK 620 3 HIS C 126 ND1 115.6 87.5
REMARK 620 4 ASP C 234 OD1 123.4 89.0 119.2
REMARK 620 5 ASP C 234 OD2 71.2 126.5 143.3 56.8
REMARK 620 6 ASP C 232 OD2 58.3 74.8 157.2 75.5 58.6
REMARK 620 7 HAR C 908 NH1 34.3 108.5 81.3 154.2 97.5 90.6
REMARK 620 N 1 2 3 4 5 6
REMARK 800
REMARK 800 SITE
REMARK 800 SITE_IDENTIFIER: AC1
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE MN A 500
REMARK 800 SITE_IDENTIFIER: AC2
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE MN A 501
REMARK 800 SITE_IDENTIFIER: AC3
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE MN B 502
REMARK 800 SITE_IDENTIFIER: AC4
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE MN B 503
REMARK 800 SITE_IDENTIFIER: AC5
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE MN C 504
REMARK 800 SITE_IDENTIFIER: AC6
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE MN C 505
REMARK 800 SITE_IDENTIFIER: AC7
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE HAR A 906
REMARK 800 SITE_IDENTIFIER: AC8
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE HAR B 907
REMARK 800 SITE_IDENTIFIER: AC9
REMARK 800 EVIDENCE_CODE: SOFTWARE
REMARK 800 SITE_DESCRIPTION: BINDING SITE FOR RESIDUE HAR C 908
REMARK 900
REMARK 900 RELATED ENTRIES
REMARK 900 RELATED ID: 1RLA RELATED DB: PDB
REMARK 900 NATIVE ARGINASE
DBREF 1HQF A 1 323 UNP P07824 ARGI1_RAT 1 323
DBREF 1HQF B 1 323 UNP P07824 ARGI1_RAT 1 323
DBREF 1HQF C 1 323 UNP P07824 ARGI1_RAT 1 323
SEQRES 1 A 323 MET SER SER LYS PRO LYS PRO ILE GLU ILE ILE GLY ALA
SEQRES 2 A 323 PRO PHE SER LYS GLY GLN PRO ARG GLY GLY VAL GLU LYS
SEQRES 3 A 323 GLY PRO ALA ALA LEU ARG LYS ALA GLY LEU VAL GLU LYS
SEQRES 4 A 323 LEU LYS GLU THR GLU TYR ASN VAL ARG ASP HIS GLY ASP
SEQRES 5 A 323 LEU ALA PHE VAL ASP VAL PRO ASN ASP SER PRO PHE GLN
SEQRES 6 A 323 ILE VAL LYS ASN PRO ARG SER VAL GLY LYS ALA ASN GLU
SEQRES 7 A 323 GLN LEU ALA ALA VAL VAL ALA GLU THR GLN LYS ASN GLY
SEQRES 8 A 323 THR ILE SER VAL VAL LEU GLY GLY ASP HIS SER MET ALA
SEQRES 9 A 323 ILE GLY SER ILE SER GLY HIS ALA ARG VAL HIS PRO ASP
SEQRES 10 A 323 LEU CYS VAL ILE TRP VAL ASP ALA HIS THR ASP ILE ASN
SEQRES 11 A 323 THR PRO LEU THR THR SER SER GLY ASN LEU HIS GLY GLN
SEQRES 12 A 323 PRO VAL ALA PHE LEU LEU LYS GLU LEU LYS GLY LYS PHE
SEQRES 13 A 323 PRO ASP VAL PRO GLY PHE SER TRP VAL THR PRO CYS ILE
SEQRES 14 A 323 SER ALA LYS ASP ILE VAL TYR ILE GLY LEU ARG ASP VAL
SEQRES 15 A 323 ASP PRO GLY GLU HIS TYR ILE ILE LYS THR LEU GLY ILE
SEQRES 16 A 323 LYS TYR PHE SER MET THR GLU VAL ASP LYS LEU GLY ILE
SEQRES 17 A 323 GLY LYS VAL MET GLU GLU THR PHE SER TYR LEU LEU GLY
SEQRES 18 A 323 ARG LYS LYS ARG PRO ILE HIS LEU SER PHE ASP VAL ASP
SEQRES 19 A 323 GLY LEU ASP PRO VAL PHE THR PRO ALA THR GLY THR PRO
SEQRES 20 A 323 VAL VAL GLY GLY LEU SER TYR ARG GLU GLY LEU TYR ILE
SEQRES 21 A 323 THR GLU GLU ILE TYR LYS THR GLY LEU LEU SER GLY LEU
SEQRES 22 A 323 ASP ILE MET GLU VAL ASN PRO THR LEU GLY LYS THR PRO
SEQRES 23 A 323 GLU GLU VAL THR ARG THR VAL ASN THR ALA VAL ALA LEU
SEQRES 24 A 323 THR LEU SER CYS PHE GLY THR LYS ARG GLU GLY ASN HIS
SEQRES 25 A 323 LYS PRO GLU THR ASP TYR LEU LYS PRO PRO LYS
SEQRES 1 B 323 MET SER SER LYS PRO LYS PRO ILE GLU ILE ILE GLY ALA
SEQRES 2 B 323 PRO PHE SER LYS GLY GLN PRO ARG GLY GLY VAL GLU LYS
SEQRES 3 B 323 GLY PRO ALA ALA LEU ARG LYS ALA GLY LEU VAL GLU LYS
SEQRES 4 B 323 LEU LYS GLU THR GLU TYR ASN VAL ARG ASP HIS GLY ASP
SEQRES 5 B 323 LEU ALA PHE VAL ASP VAL PRO ASN ASP SER PRO PHE GLN
SEQRES 6 B 323 ILE VAL LYS ASN PRO ARG SER VAL GLY LYS ALA ASN GLU
SEQRES 7 B 323 GLN LEU ALA ALA VAL VAL ALA GLU THR GLN LYS ASN GLY
SEQRES 8 B 323 THR ILE SER VAL VAL LEU GLY GLY ASP HIS SER MET ALA
SEQRES 9 B 323 ILE GLY SER ILE SER GLY HIS ALA ARG VAL HIS PRO ASP
SEQRES 10 B 323 LEU CYS VAL ILE TRP VAL ASP ALA HIS THR ASP ILE ASN
SEQRES 11 B 323 THR PRO LEU THR THR SER SER GLY ASN LEU HIS GLY GLN
SEQRES 12 B 323 PRO VAL ALA PHE LEU LEU LYS GLU LEU LYS GLY LYS PHE
SEQRES 13 B 323 PRO ASP VAL PRO GLY PHE SER TRP VAL THR PRO CYS ILE
SEQRES 14 B 323 SER ALA LYS ASP ILE VAL TYR ILE GLY LEU ARG ASP VAL
SEQRES 15 B 323 ASP PRO GLY GLU HIS TYR ILE ILE LYS THR LEU GLY ILE
SEQRES 16 B 323 LYS TYR PHE SER MET THR GLU VAL ASP LYS LEU GLY ILE
SEQRES 17 B 323 GLY LYS VAL MET GLU GLU THR PHE SER TYR LEU LEU GLY
SEQRES 18 B 323 ARG LYS LYS ARG PRO ILE HIS LEU SER PHE ASP VAL ASP
SEQRES 19 B 323 GLY LEU ASP PRO VAL PHE THR PRO ALA THR GLY THR PRO
SEQRES 20 B 323 VAL VAL GLY GLY LEU SER TYR ARG GLU GLY LEU TYR ILE
SEQRES 21 B 323 THR GLU GLU ILE TYR LYS THR GLY LEU LEU SER GLY LEU
SEQRES 22 B 323 ASP ILE MET GLU VAL ASN PRO THR LEU GLY LYS THR PRO
SEQRES 23 B 323 GLU GLU VAL THR ARG THR VAL ASN THR ALA VAL ALA LEU
SEQRES 24 B 323 THR LEU SER CYS PHE GLY THR LYS ARG GLU GLY ASN HIS
SEQRES 25 B 323 LYS PRO GLU THR ASP TYR LEU LYS PRO PRO LYS
SEQRES 1 C 323 MET SER SER LYS PRO LYS PRO ILE GLU ILE ILE GLY ALA
SEQRES 2 C 323 PRO PHE SER LYS GLY GLN PRO ARG GLY GLY VAL GLU LYS
SEQRES 3 C 323 GLY PRO ALA ALA LEU ARG LYS ALA GLY LEU VAL GLU LYS
SEQRES 4 C 323 LEU LYS GLU THR GLU TYR ASN VAL ARG ASP HIS GLY ASP
SEQRES 5 C 323 LEU ALA PHE VAL ASP VAL PRO ASN ASP SER PRO PHE GLN
SEQRES 6 C 323 ILE VAL LYS ASN PRO ARG SER VAL GLY LYS ALA ASN GLU
SEQRES 7 C 323 GLN LEU ALA ALA VAL VAL ALA GLU THR GLN LYS ASN GLY
SEQRES 8 C 323 THR ILE SER VAL VAL LEU GLY GLY ASP HIS SER MET ALA
SEQRES 9 C 323 ILE GLY SER ILE SER GLY HIS ALA ARG VAL HIS PRO ASP
SEQRES 10 C 323 LEU CYS VAL ILE TRP VAL ASP ALA HIS THR ASP ILE ASN
SEQRES 11 C 323 THR PRO LEU THR THR SER SER GLY ASN LEU HIS GLY GLN
SEQRES 12 C 323 PRO VAL ALA PHE LEU LEU LYS GLU LEU LYS GLY LYS PHE
SEQRES 13 C 323 PRO ASP VAL PRO GLY PHE SER TRP VAL THR PRO CYS ILE
SEQRES 14 C 323 SER ALA LYS ASP ILE VAL TYR ILE GLY LEU ARG ASP VAL
SEQRES 15 C 323 ASP PRO GLY GLU HIS TYR ILE ILE LYS THR LEU GLY ILE
SEQRES 16 C 323 LYS TYR PHE SER MET THR GLU VAL ASP LYS LEU GLY ILE
SEQRES 17 C 323 GLY LYS VAL MET GLU GLU THR PHE SER TYR LEU LEU GLY
SEQRES 18 C 323 ARG LYS LYS ARG PRO ILE HIS LEU SER PHE ASP VAL ASP
SEQRES 19 C 323 GLY LEU ASP PRO VAL PHE THR PRO ALA THR GLY THR PRO
SEQRES 20 C 323 VAL VAL GLY GLY LEU SER TYR ARG GLU GLY LEU TYR ILE
SEQRES 21 C 323 THR GLU GLU ILE TYR LYS THR GLY LEU LEU SER GLY LEU
SEQRES 22 C 323 ASP ILE MET GLU VAL ASN PRO THR LEU GLY LYS THR PRO
SEQRES 23 C 323 GLU GLU VAL THR ARG THR VAL ASN THR ALA VAL ALA LEU
SEQRES 24 C 323 THR LEU SER CYS PHE GLY THR LYS ARG GLU GLY ASN HIS
SEQRES 25 C 323 LYS PRO GLU THR ASP TYR LEU LYS PRO PRO LYS
HET MN A 500 1
HET MN A 501 1
HET MN B 502 1
HET MN B 503 1
HET MN C 504 1
HET MN C 505 1
HET HAR A 906 13
HET HAR B 907 13
HET HAR C 908 13
HETNAM MN MANGANESE (II) ION
HETNAM HAR N-OMEGA-HYDROXY-L-ARGININE
FORMUL 4 MN 6(MN 2+)
FORMUL 10 HAR 3(C6 H14 N4 O3)
FORMUL 13 HOH *15(H2 O)
HELIX 1 1 GLY A 23 GLU A 25 5 3
HELIX 2 2 LYS A 26 ALA A 34 1 9
HELIX 3 3 GLY A 35 GLU A 42 1 8
HELIX 4 4 ASN A 69 GLY A 91 1 23
HELIX 5 5 SER A 102 HIS A 115 1 14
HELIX 6 6 ASN A 139 GLY A 142 5 4
HELIX 7 7 GLN A 143 LEU A 149 1 7
HELIX 8 8 ASP A 183 LEU A 193 1 11
HELIX 9 9 SER A 199 GLY A 207 1 9
HELIX 10 10 GLY A 207 GLY A 221 1 15
HELIX 11 11 SER A 253 LYS A 266 1 14
HELIX 12 12 THR A 285 PHE A 304 1 20
HELIX 13 13 GLY B 23 GLU B 25 5 3
HELIX 14 14 LYS B 26 ALA B 34 1 9
HELIX 15 15 GLY B 35 GLU B 42 1 8
HELIX 16 16 ASN B 69 GLY B 91 1 23
HELIX 17 17 SER B 102 HIS B 115 1 14
HELIX 18 18 ASN B 139 GLY B 142 5 4
HELIX 19 19 GLN B 143 LEU B 149 1 7
HELIX 20 20 ASP B 183 LEU B 193 1 11
HELIX 21 21 SER B 199 GLY B 207 1 9
HELIX 22 22 GLY B 207 GLY B 221 1 15
HELIX 23 23 SER B 253 LYS B 266 1 14
HELIX 24 24 THR B 285 PHE B 304 1 20
HELIX 25 25 GLY C 23 GLU C 25 5 3
HELIX 26 26 LYS C 26 ALA C 34 1 9
HELIX 27 27 GLY C 35 GLU C 42 1 8
HELIX 28 28 ASN C 69 GLY C 91 1 23
HELIX 29 29 SER C 102 HIS C 115 1 14
HELIX 30 30 ASN C 139 GLY C 142 5 4
HELIX 31 31 GLN C 143 LEU C 149 1 7
HELIX 32 32 ASP C 183 LEU C 193 1 11
HELIX 33 33 SER C 199 GLY C 207 1 9
HELIX 34 34 GLY C 207 GLY C 221 1 15
HELIX 35 35 SER C 253 LYS C 266 1 14
HELIX 36 36 THR C 285 PHE C 304 1 20
SHEET 1 A 8 ASN A 46 ASP A 52 0
SHEET 2 A 8 PRO A 7 GLY A 12 1 N ILE A 8 O ASN A 46
SHEET 3 A 8 ILE A 93 LEU A 97 1 N ILE A 93 O PRO A 7
SHEET 4 A 8 LEU A 270 MET A 276 1 O SER A 271 N SER A 94
SHEET 5 A 8 ILE A 227 ASP A 232 1 O ILE A 227 N SER A 271
SHEET 6 A 8 VAL A 120 VAL A 123 1 O ILE A 121 N SER A 230
SHEET 7 A 8 ILE A 174 ILE A 177 1 O VAL A 175 N TRP A 122
SHEET 8 A 8 TYR A 197 PHE A 198 1 N PHE A 198 O TYR A 176
SHEET 1 B 8 ASN B 46 ASP B 52 0
SHEET 2 B 8 PRO B 7 GLY B 12 1 N ILE B 8 O ASN B 46
SHEET 3 B 8 ILE B 93 LEU B 97 1 N ILE B 93 O PRO B 7
SHEET 4 B 8 LEU B 270 MET B 276 1 O SER B 271 N SER B 94
SHEET 5 B 8 ILE B 227 ASP B 232 1 O ILE B 227 N SER B 271
SHEET 6 B 8 VAL B 120 VAL B 123 1 O ILE B 121 N SER B 230
SHEET 7 B 8 ILE B 174 ILE B 177 1 O VAL B 175 N TRP B 122
SHEET 8 B 8 TYR B 197 PHE B 198 1 N PHE B 198 O TYR B 176
SHEET 1 C 8 ASN C 46 ASP C 52 0
SHEET 2 C 8 PRO C 7 GLY C 12 1 N ILE C 8 O ASN C 46
SHEET 3 C 8 ILE C 93 LEU C 97 1 N ILE C 93 O PRO C 7
SHEET 4 C 8 LEU C 270 MET C 276 1 O SER C 271 N SER C 94
SHEET 5 C 8 ILE C 227 ASP C 232 1 O ILE C 227 N SER C 271
SHEET 6 C 8 VAL C 120 VAL C 123 1 O ILE C 121 N SER C 230
SHEET 7 C 8 ILE C 174 ILE C 177 1 O VAL C 175 N TRP C 122
SHEET 8 C 8 TYR C 197 PHE C 198 1 N PHE C 198 O TYR C 176
LINK MN MN A 500 OD2 ASP A 124 1555 1555 2.03
LINK MN MN A 500 OH1 HAR A 906 1555 1555 2.64
LINK MN MN A 500 OD2 ASP A 128 1555 1555 2.08
LINK MN MN A 500 ND1 HIS A 101 1555 1555 2.35
LINK MN MN A 501 OD1 ASP A 124 1555 1555 2.19
LINK MN MN A 501 OD2 ASP A 232 1555 1555 2.49
LINK MN MN A 501 OD1 ASP A 234 1555 1555 2.48
LINK MN MN A 501 OD2 ASP A 234 1555 1555 2.01
LINK MN MN A 501 OH1 HAR A 906 1555 1555 2.21
LINK MN MN A 501 ND1 HIS A 126 1555 1555 1.99
LINK MN MN A 501 NH1 HAR A 906 1555 1555 2.34
LINK MN MN B 502 ND1 HIS B 101 1555 1555 2.35
LINK MN MN B 502 OD2 ASP B 124 1555 1555 2.03
LINK MN MN B 502 OH1 HAR B 907 1555 1555 2.64
LINK MN MN B 502 OD2 ASP B 128 1555 1555 2.08
LINK MN MN B 503 OD2 ASP B 232 1555 1555 2.49
LINK MN MN B 503 OH1 HAR B 907 1555 1555 2.21
LINK MN MN B 503 OD1 ASP B 124 1555 1555 2.19
LINK MN MN B 503 OD1 ASP B 234 1555 1555 2.58
LINK MN MN B 503 OD2 ASP B 234 1555 1555 1.89
LINK MN MN B 503 ND1 HIS B 126 1555 1555 1.99
LINK MN MN B 503 NH1 HAR B 907 1555 1555 2.34
LINK MN MN C 504 OH1 HAR C 908 1555 1555 2.64
LINK MN MN C 504 ND1 HIS C 101 1555 1555 2.35
LINK MN MN C 504 OD2 ASP C 124 1555 1555 2.03
LINK MN MN C 504 OD2 ASP C 128 1555 1555 2.08
LINK MN MN C 505 OH1 HAR C 908 1555 1555 2.21
LINK MN MN C 505 OD1 ASP C 124 1555 1555 2.19
LINK MN MN C 505 ND1 HIS C 126 1555 1555 1.99
LINK MN MN C 505 OD1 ASP C 234 1555 1555 2.59
LINK MN MN C 505 OD2 ASP C 234 1555 1555 1.88
LINK MN MN C 505 OD2 ASP C 232 1555 1555 2.49
LINK MN MN C 505 NH1 HAR C 908 1555 1555 2.34
SITE 1 AC1 5 HIS A 101 ASP A 124 ASP A 128 ASP A 232
SITE 2 AC1 5 HAR A 906
SITE 1 AC2 5 ASP A 124 HIS A 126 ASP A 232 ASP A 234
SITE 2 AC2 5 HAR A 906
SITE 1 AC3 5 HIS B 101 ASP B 124 ASP B 128 ASP B 232
SITE 2 AC3 5 HAR B 907
SITE 1 AC4 5 ASP B 124 HIS B 126 ASP B 232 ASP B 234
SITE 2 AC4 5 HAR B 907
SITE 1 AC5 5 HIS C 101 ASP C 124 ASP C 128 ASP C 232
SITE 2 AC5 5 HAR C 908
SITE 1 AC6 5 ASP C 124 HIS C 126 ASP C 232 ASP C 234
SITE 2 AC6 5 HAR C 908
SITE 1 AC7 13 ASP A 124 HIS A 126 ASP A 128 SER A 137
SITE 2 AC7 13 HIS A 141 GLY A 142 ASP A 183 GLU A 186
SITE 3 AC7 13 ASP A 232 ASP A 234 GLU A 277 MN A 500
SITE 4 AC7 13 MN A 501
SITE 1 AC8 13 ASP B 124 HIS B 126 ASP B 128 SER B 137
SITE 2 AC8 13 HIS B 141 GLY B 142 ASP B 183 GLU B 186
SITE 3 AC8 13 ASP B 232 ASP B 234 GLU B 277 MN B 502
SITE 4 AC8 13 MN B 503
SITE 1 AC9 13 ASP C 124 HIS C 126 ASP C 128 SER C 137
SITE 2 AC9 13 HIS C 141 GLY C 142 ASP C 183 GLU C 186
SITE 3 AC9 13 ASP C 232 ASP C 234 GLU C 277 MN C 504
SITE 4 AC9 13 MN C 505
CRYST1 88.000 88.000 112.000 90.00 90.00 120.00 P 32 9
ORIGX1 1.000000 0.000000 0.000000 0.00000
ORIGX2 0.000000 1.000000 0.000000 0.00000
ORIGX3 0.000000 0.000000 1.000000 0.00000
SCALE1 0.011364 0.006561 0.000000 0.00000
SCALE2 0.000000 0.013122 0.000000 0.00000
SCALE3 0.000000 0.000000 0.008929 0.00000
ATOM 1 N LYS A 6 20.150 24.280 -3.804 1.00 99.08 N
ATOM 2 CA LYS A 6 20.016 25.666 -3.251 1.00 99.00 C
ATOM 3 C LYS A 6 20.110 25.692 -1.713 1.00 98.40 C
ATOM 4 O LYS A 6 19.950 24.661 -1.046 1.00 97.61 O
ATOM 5 CB LYS A 6 18.690 26.275 -3.726 1.00 99.66 C
ATOM 6 CG LYS A 6 18.835 27.475 -4.668 1.00 99.85 C
ATOM 7 CD LYS A 6 19.049 28.777 -3.884 1.00100.73 C
ATOM 8 CE LYS A 6 19.103 30.010 -4.789 1.00101.23 C
ATOM 9 NZ LYS A 6 19.115 31.289 -4.008 1.00100.75 N
ATOM 10 N PRO A 7 20.388 26.877 -1.135 1.00 97.80 N
ATOM 11 CA PRO A 7 20.507 27.023 0.316 1.00 97.15 C
ATOM 12 C PRO A 7 19.380 27.825 0.940 1.00 96.32 C
ATOM 13 O PRO A 7 18.846 28.746 0.325 1.00 96.22 O
ATOM 14 CB PRO A 7 21.827 27.749 0.457 1.00 97.20 C
ATOM 15 CG PRO A 7 21.693 28.770 -0.642 1.00 97.43 C
ATOM 16 CD PRO A 7 21.026 28.026 -1.803 1.00 97.47 C
ATOM 17 N ILE A 8 19.053 27.481 2.180 1.00 95.57 N
ATOM 18 CA ILE A 8 17.996 28.154 2.922 1.00 94.69 C
ATOM 19 C ILE A 8 18.514 28.607 4.269 1.00 94.01 C
ATOM 20 O ILE A 8 19.133 27.814 4.985 1.00 93.77 O
ATOM 21 CB ILE A 8 16.792 27.204 3.226 1.00 94.64 C
ATOM 22 CG1 ILE A 8 16.130 26.722 1.935 1.00 93.94 C
ATOM 23 CG2 ILE A 8 15.771 27.916 4.108 1.00 93.66 C
ATOM 24 CD1 ILE A 8 15.647 27.841 1.065 1.00 94.03 C
ATOM 25 N GLU A 9 18.293 29.874 4.608 1.00 92.63 N
ATOM 26 CA GLU A 9 18.681 30.319 5.937 1.00 91.96 C
ATOM 27 C GLU A 9 17.423 30.890 6.573 1.00 91.79 C
ATOM 28 O GLU A 9 16.719 31.703 5.962 1.00 91.03 O
ATOM 29 CB GLU A 9 19.783 31.383 5.946 1.00 91.63 C
ATOM 30 CG GLU A 9 20.487 31.410 7.322 1.00 91.26 C
ATOM 31 CD GLU A 9 21.121 32.739 7.707 1.00 91.17 C
ATOM 32 OE1 GLU A 9 21.711 32.810 8.808 1.00 89.98 O
ATOM 33 OE2 GLU A 9 21.029 33.705 6.926 1.00 91.53 O
ATOM 34 N ILE A 10 17.132 30.438 7.790 1.00 91.97 N
ATOM 35 CA ILE A 10 15.947 30.883 8.514 1.00 92.34 C
ATOM 36 C ILE A 10 16.288 31.950 9.541 1.00 91.65 C
ATOM 37 O ILE A 10 17.227 31.793 10.319 1.00 91.67 O
ATOM 38 CB ILE A 10 15.268 29.705 9.249 1.00 93.05 C
ATOM 39 CG1 ILE A 10 14.834 28.654 8.224 1.00 93.78 C
ATOM 40 CG2 ILE A 10 14.079 30.216 10.082 1.00 91.79 C
ATOM 41 CD1 ILE A 10 14.226 27.398 8.817 1.00 92.99 C
ATOM 42 N ILE A 11 15.516 33.032 9.539 1.00 90.86 N
ATOM 43 CA ILE A 11 15.715 34.133 10.475 1.00 89.22 C
ATOM 44 C ILE A 11 14.465 34.241 11.331 1.00 88.75 C
ATOM 45 O ILE A 11 13.350 34.222 10.816 1.00 87.87 O
ATOM 46 CB ILE A 11 15.906 35.491 9.751 1.00 88.97 C
ATOM 47 CG1 ILE A 11 17.018 35.381 8.714 1.00 87.62 C
ATOM 48 CG2 ILE A 11 16.223 36.582 10.758 1.00 88.11 C
ATOM 49 CD1 ILE A 11 18.340 34.985 9.283 1.00 88.39 C
ATOM 50 N GLY A 12 14.659 34.346 12.638 1.00 88.08 N
ATOM 51 CA GLY A 12 13.529 34.477 13.530 1.00 86.84 C
ATOM 52 C GLY A 12 13.402 35.940 13.891 1.00 85.81 C
ATOM 53 O GLY A 12 14.381 36.556 14.305 1.00 86.11 O
ATOM 54 N ALA A 13 12.207 36.501 13.731 1.00 84.95 N
ATOM 55 CA ALA A 13 11.973 37.908 14.041 1.00 83.69 C
ATOM 56 C ALA A 13 11.024 38.075 15.226 1.00 83.14 C
ATOM 57 O ALA A 13 10.099 38.884 15.166 1.00 83.23 O
ATOM 58 CB ALA A 13 11.399 38.627 12.801 1.00 82.18 C
ATOM 59 N PRO A 14 11.251 37.329 16.323 1.00 82.39 N
ATOM 60 CA PRO A 14 10.376 37.435 17.495 1.00 82.40 C
ATOM 61 C PRO A 14 10.136 38.880 17.911 1.00 83.87 C
ATOM 62 O PRO A 14 10.828 39.401 18.776 1.00 84.25 O
ATOM 63 CB PRO A 14 11.132 36.648 18.552 1.00 81.00 C
ATOM 64 CG PRO A 14 12.562 36.848 18.154 1.00 80.99 C
ATOM 65 CD PRO A 14 12.493 36.624 16.677 1.00 81.10 C
ATOM 66 N PHE A 15 9.144 39.516 17.296 1.00 86.12 N
ATOM 67 CA PHE A 15 8.819 40.913 17.578 1.00 87.98 C
ATOM 68 C PHE A 15 7.305 41.081 17.715 1.00 88.21 C
ATOM 69 O PHE A 15 6.548 40.163 17.386 1.00 88.51 O
ATOM 70 CB PHE A 15 9.349 41.793 16.443 1.00 88.79 C
ATOM 71 CG PHE A 15 9.326 43.256 16.746 1.00 91.15 C
ATOM 72 CD1 PHE A 15 9.860 43.739 17.938 1.00 92.70 C
ATOM 73 CD2 PHE A 15 8.802 44.161 15.827 1.00 91.85 C
ATOM 74 CE1 PHE A 15 9.883 45.108 18.207 1.00 93.41 C
ATOM 75 CE2 PHE A 15 8.820 45.531 16.083 1.00 93.06 C
ATOM 76 CZ PHE A 15 9.359 46.008 17.276 1.00 93.27 C
ATOM 77 N SER A 16 6.850 42.237 18.190 1.00 87.82 N
ATOM 78 CA SER A 16 5.413 42.425 18.338 1.00 88.48 C
ATOM 79 C SER A 16 4.935 43.859 18.544 1.00 90.22 C
ATOM 80 O SER A 16 3.734 44.108 18.571 1.00 90.56 O
ATOM 81 CB SER A 16 4.896 41.562 19.492 1.00 86.82 C
ATOM 82 OG SER A 16 5.377 42.010 20.739 1.00 83.07 O
ATOM 83 N LYS A 17 5.856 44.801 18.690 1.00 92.02 N
ATOM 84 CA LYS A 17 5.466 46.191 18.913 1.00 93.42 C
ATOM 85 C LYS A 17 4.714 46.797 17.725 1.00 93.24 C
ATOM 86 O LYS A 17 4.114 47.874 17.829 1.00 92.98 O
ATOM 87 CB LYS A 17 6.704 47.033 19.255 1.00 95.56 C
ATOM 88 CG LYS A 17 6.807 47.487 20.727 1.00 96.54 C
ATOM 89 CD LYS A 17 6.616 46.336 21.709 1.00 97.30 C
ATOM 90 CE LYS A 17 7.113 46.705 23.100 1.00 97.15 C
ATOM 91 NZ LYS A 17 8.596 46.859 23.109 1.00 96.57 N
ATOM 92 N GLY A 18 4.739 46.107 16.593 1.00 92.44 N
ATOM 93 CA GLY A 18 4.026 46.619 15.441 1.00 92.27 C
ATOM 94 C GLY A 18 2.538 46.700 15.749 1.00 92.53 C
ATOM 95 O GLY A 18 1.793 47.378 15.040 1.00 92.29 O
ATOM 96 N GLN A 19 2.113 46.009 16.811 1.00 92.65 N
ATOM 97 CA GLN A 19 0.713 45.969 17.238 1.00 92.73 C
ATOM 98 C GLN A 19 0.574 45.619 18.727 1.00 94.03 C
ATOM 99 O GLN A 19 1.526 45.154 19.355 1.00 93.82 O
ATOM 100 CB GLN A 19 -0.067 44.967 16.379 1.00 92.02 C
ATOM 101 CG GLN A 19 0.542 43.575 16.280 1.00 91.29 C
ATOM 102 CD GLN A 19 0.385 42.780 17.553 1.00 91.08 C
ATOM 103 OE1 GLN A 19 -0.703 42.725 18.118 1.00 91.96 O
ATOM 104 NE2 GLN A 19 1.464 42.152 18.009 1.00 89.85 N
ATOM 105 N PRO A 20 -0.628 45.825 19.303 1.00 95.05 N
ATOM 106 CA PRO A 20 -0.989 45.576 20.709 1.00 95.93 C
ATOM 107 C PRO A 20 -0.967 44.147 21.273 1.00 96.49 C
ATOM 108 O PRO A 20 -0.271 43.872 22.256 1.00 97.00 O
ATOM 109 CB PRO A 20 -2.377 46.203 20.814 1.00 95.49 C
ATOM 110 CG PRO A 20 -2.943 45.941 19.473 1.00 95.38 C
ATOM 111 CD PRO A 20 -1.801 46.322 18.562 1.00 94.96 C
ATOM 112 N ARG A 21 -1.748 43.255 20.670 1.00 96.79 N
ATOM 113 CA ARG A 21 -1.837 41.861 21.116 1.00 96.91 C
ATOM 114 C ARG A 21 -0.463 41.184 21.226 1.00 94.86 C
ATOM 115 O ARG A 21 0.288 41.101 20.247 1.00 94.86 O
ATOM 116 CB ARG A 21 -2.729 41.064 20.155 1.00 99.34 C
ATOM 117 CG ARG A 21 -3.809 41.896 19.475 1.00102.34 C
ATOM 118 CD ARG A 21 -4.595 41.057 18.483 1.00106.42 C
ATOM 119 NE ARG A 21 -5.547 40.179 19.152 1.00109.60 N
ATOM 120 CZ ARG A 21 -6.649 40.607 19.757 1.00111.63 C
ATOM 121 NH1 ARG A 21 -6.939 41.902 19.773 1.00112.45 N
ATOM 122 NH2 ARG A 21 -7.461 39.741 20.347 1.00112.44 N
ATOM 123 N GLY A 22 -0.149 40.683 22.417 1.00 92.20 N
ATOM 124 CA GLY A 22 1.137 40.041 22.627 1.00 89.96 C
ATOM 125 C GLY A 22 1.196 38.544 22.385 1.00 88.10 C
ATOM 126 O GLY A 22 0.241 37.821 22.653 1.00 87.82 O
ATOM 127 N GLY A 23 2.337 38.080 21.888 1.00 86.64 N
ATOM 128 CA GLY A 23 2.507 36.667 21.623 1.00 85.01 C
ATOM 129 C GLY A 23 3.205 36.439 20.299 1.00 84.30 C
ATOM 130 O GLY A 23 4.015 35.522 20.165 1.00 84.52 O
ATOM 131 N VAL A 24 2.900 37.285 19.320 1.00 83.77 N
ATOM 132 CA VAL A 24 3.489 37.174 17.986 1.00 83.44 C
ATOM 133 C VAL A 24 5.004 36.944 17.935 1.00 84.55 C
ATOM 134 O VAL A 24 5.517 36.393 16.954 1.00 83.80 O
ATOM 135 CB VAL A 24 3.121 38.408 17.120 1.00 82.02 C
ATOM 136 CG1 VAL A 24 1.875 38.107 16.303 1.00 82.66 C
ATOM 137 CG2 VAL A 24 2.861 39.604 18.004 1.00 80.13 C
ATOM 138 N GLU A 25 5.722 37.363 18.977 1.00 85.75 N
ATOM 139 CA GLU A 25 7.168 37.163 18.997 1.00 86.17 C
ATOM 140 C GLU A 25 7.437 35.699 19.323 1.00 85.93 C
ATOM 141 O GLU A 25 8.528 35.175 19.057 1.00 86.45 O
ATOM 142 CB GLU A 25 7.854 38.071 20.026 1.00 86.78 C
ATOM 143 CG GLU A 25 7.688 37.675 21.482 1.00 88.34 C
ATOM 144 CD GLU A 25 6.301 37.957 22.014 1.00 90.53 C
ATOM 145 OE1 GLU A 25 5.594 38.809 21.422 1.00 91.06 O
ATOM 146 OE2 GLU A 25 5.927 37.340 23.037 1.00 91.16 O
ATOM 147 N LYS A 26 6.434 35.040 19.899 1.00 84.12 N
ATOM 148 CA LYS A 26 6.551 33.628 20.218 1.00 82.19 C
ATOM 149 C LYS A 26 6.378 32.864 18.908 1.00 80.51 C
ATOM 150 O LYS A 26 6.492 31.641 18.870 1.00 80.34 O
ATOM 151 CB LYS A 26 5.472 33.211 21.212 1.00 82.12 C
ATOM 152 CG LYS A 26 5.627 33.832 22.583 1.00 84.38 C
ATOM 153 CD LYS A 26 4.535 33.336 23.539 1.00 86.61 C
ATOM 154 CE LYS A 26 4.701 33.921 24.947 1.00 86.85 C
ATOM 155 NZ LYS A 26 3.645 33.481 25.915 1.00 86.67 N
ATOM 156 N GLY A 27 6.106 33.608 17.838 1.00 78.69 N
ATOM 157 CA GLY A 27 5.916 33.013 16.527 1.00 76.08 C
ATOM 158 C GLY A 27 6.996 32.022 16.144 1.00 74.71 C
ATOM 159 O GLY A 27 6.727 30.821 16.068 1.00 74.43 O
ATOM 160 N PRO A 28 8.231 32.489 15.882 1.00 74.00 N
ATOM 161 CA PRO A 28 9.330 31.591 15.505 1.00 74.28 C
ATOM 162 C PRO A 28 9.599 30.518 16.560 1.00 75.07 C
ATOM 163 O PRO A 28 10.172 29.466 16.277 1.00 74.60 O
ATOM 164 CB PRO A 28 10.503 32.550 15.323 1.00 73.18 C
ATOM 165 CG PRO A 28 9.838 33.786 14.807 1.00 71.70 C
ATOM 166 CD PRO A 28 8.635 33.898 15.722 1.00 72.82 C
ATOM 167 N ALA A 29 9.166 30.796 17.781 1.00 77.64 N
ATOM 168 CA ALA A 29 9.346 29.871 18.891 1.00 79.22 C
ATOM 169 C ALA A 29 8.468 28.636 18.726 1.00 79.71 C
ATOM 170 O ALA A 29 8.883 27.519 19.062 1.00 81.37 O
ATOM 171 CB ALA A 29 9.025 30.574 20.214 1.00 79.86 C
ATOM 172 N ALA A 30 7.259 28.839 18.210 1.00 78.80 N
ATOM 173 CA ALA A 30 6.329 27.735 18.005 1.00 78.62 C
ATOM 174 C ALA A 30 6.643 27.029 16.693 1.00 78.68 C
ATOM 175 O ALA A 30 6.593 25.798 16.600 1.00 78.63 O
ATOM 176 CB ALA A 30 4.897 28.254 17.989 1.00 78.52 C
ATOM 177 N LEU A 31 6.982 27.819 15.682 1.00 78.19 N
ATOM 178 CA LEU A 31 7.291 27.274 14.369 1.00 77.40 C
ATOM 179 C LEU A 31 8.457 26.302 14.400 1.00 77.67 C
ATOM 180 O LEU A 31 8.397 25.251 13.774 1.00 77.84 O
ATOM 181 CB LEU A 31 7.565 28.410 13.378 1.00 75.60 C
ATOM 182 CG LEU A 31 6.306 29.077 12.813 1.00 73.01 C
ATOM 183 CD1 LEU A 31 6.521 30.549 12.633 1.00 70.89 C
ATOM 184 CD2 LEU A 31 5.949 28.417 11.504 1.00 71.89 C
ATOM 185 N ARG A 32 9.522 26.639 15.116 1.00 78.94 N
ATOM 186 CA ARG A 32 10.656 25.726 15.177 1.00 80.72 C
ATOM 187 C ARG A 32 10.224 24.490 15.946 1.00 81.47 C
ATOM 188 O ARG A 32 10.589 23.375 15.588 1.00 80.36 O
ATOM 189 CB ARG A 32 11.863 26.363 15.879 1.00 82.03 C
ATOM 190 CG ARG A 32 12.700 27.320 15.032 1.00 82.49 C
ATOM 191 CD ARG A 32 14.092 27.523 15.652 1.00 84.29 C
ATOM 192 NE ARG A 32 14.834 28.634 15.057 1.00 85.70 N
ATOM 193 CZ ARG A 32 14.491 29.915 15.180 1.00 86.70 C
ATOM 194 NH1 ARG A 32 13.416 30.251 15.882 1.00 87.41 N
ATOM 195 NH2 ARG A 32 15.219 30.863 14.602 1.00 86.01 N
ATOM 196 N LYS A 33 9.449 24.714 17.007 1.00 82.85 N
ATOM 197 CA LYS A 33 8.938 23.647 17.855 1.00 84.50 C
ATOM 198 C LYS A 33 8.052 22.707 17.041 1.00 85.48 C
ATOM 199 O LYS A 33 7.895 21.534 17.380 1.00 85.93 O
ATOM 200 CB LYS A 33 8.147 24.240 19.024 1.00 85.61 C
ATOM 201 CG LYS A 33 7.295 23.228 19.779 1.00 88.84 C
ATOM 202 CD LYS A 33 8.130 22.161 20.495 1.00 91.56 C
ATOM 203 CE LYS A 33 8.497 22.583 21.921 1.00 93.10 C
ATOM 204 NZ LYS A 33 7.288 22.874 22.767 1.00 93.72 N
ATOM 205 N ALA A 34 7.461 23.221 15.969 1.00 86.44 N
ATOM 206 CA ALA A 34 6.622 22.388 15.113 1.00 86.60 C
ATOM 207 C ALA A 34 7.563 21.654 14.151 1.00 86.88 C
ATOM 208 O ALA A 34 7.138 21.028 13.177 1.00 85.52 O
ATOM 209 CB ALA A 34 5.629 23.254 14.346 1.00 87.03 C
ATOM 210 N GLY A 35 8.856 21.764 14.444 1.00 88.26 N
ATOM 211 CA GLY A 35 9.883 21.112 13.652 1.00 89.33 C
ATOM 212 C GLY A 35 10.115 21.685 12.275 1.00 89.25 C
ATOM 213 O GLY A 35 10.597 20.985 11.385 1.00 89.47 O
ATOM 214 N LEU A 36 9.793 22.956 12.090 1.00 89.38 N
ATOM 215 CA LEU A 36 9.969 23.569 10.782 1.00 90.16 C
ATOM 216 C LEU A 36 11.369 23.377 10.197 1.00 90.88 C
ATOM 217 O LEU A 36 11.522 23.101 9.003 1.00 90.76 O
ATOM 218 CB LEU A 36 9.621 25.062 10.845 1.00 89.73 C
ATOM 219 CG LEU A 36 9.749 25.890 9.559 1.00 89.10 C
ATOM 220 CD1 LEU A 36 9.245 25.116 8.351 1.00 89.09 C
ATOM 221 CD2 LEU A 36 8.967 27.180 9.735 1.00 88.91 C
ATOM 222 N VAL A 37 12.393 23.495 11.033 1.00 91.52 N
ATOM 223 CA VAL A 37 13.756 23.352 10.537 1.00 92.05 C
ATOM 224 C VAL A 37 14.023 21.993 9.871 1.00 93.18 C
ATOM 225 O VAL A 37 14.330 21.929 8.676 1.00 93.84 O
ATOM 226 CB VAL A 37 14.779 23.576 11.663 1.00 90.22 C
ATOM 227 CG1 VAL A 37 16.099 24.015 11.067 1.00 88.34 C
ATOM 228 CG2 VAL A 37 14.258 24.610 12.643 1.00 89.51 C
ATOM 229 N GLU A 38 13.893 20.915 10.641 1.00 93.67 N
ATOM 230 CA GLU A 38 14.133 19.558 10.141 1.00 93.22 C
ATOM 231 C GLU A 38 13.368 19.216 8.861 1.00 91.50 C
ATOM 232 O GLU A 38 13.967 18.795 7.867 1.00 89.54 O
ATOM 233 CB GLU A 38 13.786 18.524 11.227 1.00 95.27 C
ATOM 234 CG GLU A 38 14.485 18.751 12.567 1.00 97.90 C
ATOM 235 CD GLU A 38 13.809 19.818 13.416 1.00 98.72 C
ATOM 236 OE1 GLU A 38 12.801 19.504 14.088 1.00 98.61 O
ATOM 237 OE2 GLU A 38 14.281 20.973 13.402 1.00100.35 O
ATOM 238 N LYS A 39 12.049 19.387 8.888 1.00 89.99 N
ATOM 239 CA LYS A 39 11.242 19.076 7.719 1.00 89.24 C
ATOM 240 C LYS A 39 11.836 19.778 6.517 1.00 89.66 C
ATOM 241 O LYS A 39 11.944 19.197 5.436 1.00 90.45 O
ATOM 242 CB LYS A 39 9.803 19.529 7.917 1.00 87.39 C
ATOM 243 CG LYS A 39 9.108 18.851 9.057 1.00 86.93 C
ATOM 244 CD LYS A 39 7.701 19.373 9.197 1.00 87.74 C
ATOM 245 CE LYS A 39 7.034 18.791 10.426 1.00 88.21 C
ATOM 246 NZ LYS A 39 6.956 17.314 10.322 1.00 89.64 N
ATOM 247 N LEU A 40 12.235 21.030 6.708 1.00 89.66 N
ATOM 248 CA LEU A 40 12.824 21.787 5.614 1.00 89.32 C
ATOM 249 C LEU A 40 14.053 21.052 5.093 1.00 90.45 C
ATOM 250 O LEU A 40 14.258 20.950 3.884 1.00 89.95 O
ATOM 251 CB LEU A 40 13.184 23.209 6.072 1.00 85.82 C
ATOM 252 CG LEU A 40 12.106 24.275 5.815 1.00 82.28 C
ATOM 253 CD1 LEU A 40 12.438 25.534 6.573 1.00 82.14 C
ATOM 254 CD2 LEU A 40 12.009 24.560 4.332 1.00 80.23 C
ATOM 255 N LYS A 41 14.856 20.516 6.007 1.00 92.70 N
ATOM 256 CA LYS A 41 16.063 19.793 5.617 1.00 95.26 C
ATOM 257 C LYS A 41 15.711 18.612 4.719 1.00 96.02 C
ATOM 258 O LYS A 41 16.482 18.238 3.833 1.00 96.02 O
ATOM 259 CB LYS A 41 16.817 19.307 6.857 1.00 95.44 C
ATOM 260 CG LYS A 41 17.342 20.436 7.740 1.00 97.67 C
ATOM 261 CD LYS A 41 17.803 19.917 9.099 1.00 98.54 C
ATOM 262 CE LYS A 41 18.078 21.056 10.072 1.00 97.92 C
ATOM 263 NZ LYS A 41 18.379 20.550 11.440 1.00 96.37 N
ATOM 264 N GLU A 42 14.535 18.041 4.943 1.00 97.23 N
ATOM 265 CA GLU A 42 14.074 16.906 4.162 1.00 99.27 C
ATOM 266 C GLU A 42 13.934 17.193 2.673 1.00100.29 C
ATOM 267 O GLU A 42 13.638 16.292 1.889 1.00 99.46 O
ATOM 268 CB GLU A 42 12.738 16.421 4.698 1.00100.72 C
ATOM 269 CG GLU A 42 12.835 15.631 5.974 1.00104.56 C
ATOM 270 CD GLU A 42 11.464 15.245 6.501 1.00107.81 C
ATOM 271 OE1 GLU A 42 10.562 14.990 5.666 1.00108.24 O
ATOM 272 OE2 GLU A 42 11.295 15.187 7.742 1.00110.21 O
ATOM 273 N THR A 43 14.128 18.442 2.275 1.00102.51 N
ATOM 274 CA THR A 43 14.010 18.786 0.863 1.00104.86 C
ATOM 275 C THR A 43 15.364 18.735 0.165 1.00106.85 C
ATOM 276 O THR A 43 16.342 18.194 0.701 1.00107.03 O
ATOM 277 CB THR A 43 13.422 20.203 0.661 1.00104.47 C
ATOM 278 OG1 THR A 43 14.244 21.165 1.336 1.00104.26 O
ATOM 279 CG2 THR A 43 12.005 20.273 1.201 1.00103.94 C
ATOM 280 N GLU A 44 15.399 19.298 -1.042 1.00108.54 N
ATOM 281 CA GLU A 44 16.611 19.362 -1.854 1.00109.37 C
ATOM 282 C GLU A 44 17.418 20.626 -1.505 1.00109.21 C
ATOM 283 O GLU A 44 18.448 20.918 -2.123 1.00109.70 O
ATOM 284 CB GLU A 44 16.231 19.361 -3.340 1.00109.72 C
ATOM 285 CG GLU A 44 14.952 20.135 -3.644 1.00111.43 C
ATOM 286 CD GLU A 44 14.707 20.311 -5.135 1.00112.66 C
ATOM 287 OE1 GLU A 44 14.820 19.312 -5.881 1.00113.58 O
ATOM 288 OE2 GLU A 44 14.395 21.448 -5.561 1.00112.10 O
ATOM 289 N TYR A 45 16.939 21.362 -0.502 1.00108.44 N
ATOM 290 CA TYR A 45 17.582 22.592 -0.046 1.00107.04 C
ATOM 291 C TYR A 45 18.379 22.374 1.243 1.00106.43 C
ATOM 292 O TYR A 45 17.982 21.584 2.109 1.00106.41 O
ATOM 293 CB TYR A 45 16.533 23.676 0.219 1.00106.81 C
ATOM 294 CG TYR A 45 15.777 24.176 -0.992 1.00106.18 C
ATOM 295 CD1 TYR A 45 14.900 23.350 -1.694 1.00106.02 C
ATOM 296 CD2 TYR A 45 15.920 25.492 -1.420 1.00106.09 C
ATOM 297 CE1 TYR A 45 14.182 23.833 -2.797 1.00106.12 C
ATOM 298 CE2 TYR A 45 15.214 25.982 -2.515 1.00105.75 C
ATOM 299 CZ TYR A 45 14.348 25.153 -3.198 1.00105.62 C
ATOM 300 OH TYR A 45 13.661 25.649 -4.283 1.00104.68 O
ATOM 301 N ASN A 46 19.504 23.075 1.362 1.00105.11 N
ATOM 302 CA ASN A 46 20.331 22.988 2.559 1.00103.37 C
ATOM 303 C ASN A 46 19.779 24.079 3.446 1.00101.06 C
ATOM 304 O ASN A 46 19.540 25.194 2.984 1.00 99.33 O
ATOM 305 CB ASN A 46 21.797 23.279 2.243 1.00106.07 C
ATOM 306 CG ASN A 46 22.368 22.335 1.211 1.00108.03 C
ATOM 307 OD1 ASN A 46 22.276 21.113 1.352 1.00109.57 O
ATOM 308 ND2 ASN A 46 22.967 22.897 0.164 1.00108.96 N
ATOM 309 N VAL A 47 19.586 23.775 4.720 1.00 99.24 N
ATOM 310 CA VAL A 47 19.012 24.767 5.611 1.00 98.07 C
ATOM 311 C VAL A 47 19.908 25.157 6.774 1.00 96.62 C
ATOM 312 O VAL A 47 20.481 24.300 7.443 1.00 96.63 O
ATOM 313 CB VAL A 47 17.657 24.270 6.181 1.00 98.47 C
ATOM 314 CG1 VAL A 47 16.828 25.451 6.665 1.00 97.35 C
ATOM 315 CG2 VAL A 47 16.901 23.481 5.123 1.00 98.39 C
ATOM 316 N ARG A 48 20.019 26.461 7.004 1.00 94.83 N
ATOM 317 CA ARG A 48 20.809 26.981 8.102 1.00 93.46 C
ATOM 318 C ARG A 48 19.889 27.851 8.932 1.00 92.09 C
ATOM 319 O ARG A 48 19.276 28.783 8.413 1.00 90.53 O
ATOM 320 CB ARG A 48 21.985 27.813 7.583 1.00 95.23 C
ATOM 321 CG ARG A 48 22.812 28.488 8.686 1.00 96.76 C
ATOM 322 CD ARG A 48 23.895 29.396 8.107 1.00 98.94 C
ATOM 323 NE ARG A 48 23.997 30.689 8.800 1.00102.01 N
ATOM 324 CZ ARG A 48 24.580 30.887 9.984 1.00102.83 C
ATOM 325 NH1 ARG A 48 25.135 29.874 10.641 1.00103.67 N
ATOM 326 NH2 ARG A 48 24.609 32.108 10.510 1.00103.04 N
ATOM 327 N ASP A 49 19.772 27.520 10.215 1.00 91.94 N
ATOM 328 CA ASP A 49 18.934 28.283 11.129 1.00 92.13 C
ATOM 329 C ASP A 49 19.848 29.349 11.727 1.00 92.71 C
ATOM 330 O ASP A 49 20.878 29.032 12.322 1.00 93.23 O
ATOM 331 CB ASP A 49 18.379 27.373 12.229 1.00 92.41 C
ATOM 332 CG ASP A 49 17.266 28.034 13.031 1.00 93.21 C
ATOM 333 OD1 ASP A 49 17.523 29.074 13.676 1.00 93.93 O
ATOM 334 OD2 ASP A 49 16.125 27.518 13.022 1.00 94.25 O
ATOM 335 N HIS A 50 19.467 30.611 11.549 1.00 93.35 N
ATOM 336 CA HIS A 50 20.234 31.766 12.027 1.00 93.56 C
ATOM 337 C HIS A 50 19.871 32.135 13.481 1.00 93.08 C
ATOM 338 O HIS A 50 20.577 32.907 14.135 1.00 92.89 O
ATOM 339 CB HIS A 50 19.971 32.936 11.056 1.00 94.71 C
ATOM 340 CG HIS A 50 20.757 34.184 11.326 1.00 95.99 C
ATOM 341 ND1 HIS A 50 20.652 34.899 12.506 1.00 97.39 N
ATOM 342 CD2 HIS A 50 21.584 34.905 10.531 1.00 95.59 C
ATOM 343 CE1 HIS A 50 21.373 36.001 12.422 1.00 96.73 C
ATOM 344 NE2 HIS A 50 21.950 36.030 11.231 1.00 96.87 N
ATOM 345 N GLY A 51 18.785 31.562 13.990 1.00 92.46 N
ATOM 346 CA GLY A 51 18.378 31.860 15.348 1.00 92.91 C
ATOM 347 C GLY A 51 17.452 33.059 15.378 1.00 93.76 C
ATOM 348 O GLY A 51 16.974 33.509 14.334 1.00 93.36 O
ATOM 349 N ASP A 52 17.206 33.590 16.574 1.00 94.72 N
ATOM 350 CA ASP A 52 16.319 34.741 16.732 1.00 95.39 C
ATOM 351 C ASP A 52 16.987 36.067 17.009 1.00 95.22 C
ATOM 352 O ASP A 52 17.501 36.296 18.097 1.00 94.37 O
ATOM 353 CB ASP A 52 15.301 34.504 17.847 1.00 96.23 C
ATOM 354 CG ASP A 52 14.153 33.647 17.402 1.00 96.65 C
ATOM 355 OD1 ASP A 52 13.689 33.838 16.258 1.00 97.76 O
ATOM 356 OD2 ASP A 52 13.712 32.792 18.197 1.00 97.38 O
ATOM 357 N LEU A 53 16.947 36.951 16.025 1.00 96.11 N
ATOM 358 CA LEU A 53 17.517 38.270 16.191 1.00 97.52 C
ATOM 359 C LEU A 53 16.959 38.885 17.482 1.00 99.27 C
ATOM 360 O LEU A 53 15.805 39.311 17.520 1.00100.25 O
ATOM 361 CB LEU A 53 17.147 39.162 14.997 1.00 95.74 C
ATOM 362 CG LEU A 53 17.582 38.737 13.593 1.00 94.64 C
ATOM 363 CD1 LEU A 53 17.245 39.855 12.624 1.00 93.53 C
ATOM 364 CD2 LEU A 53 19.080 38.450 13.563 1.00 94.55 C
ATOM 365 N ALA A 54 17.763 38.910 18.543 1.00101.13 N
ATOM 366 CA ALA A 54 17.321 39.507 19.799 1.00102.37 C
ATOM 367 C ALA A 54 17.209 40.996 19.509 1.00103.74 C
ATOM 368 O ALA A 54 18.091 41.581 18.881 1.00102.75 O
ATOM 369 CB ALA A 54 18.342 39.251 20.898 1.00101.69 C
ATOM 370 N PHE A 55 16.121 41.611 19.948 1.00106.29 N
ATOM 371 CA PHE A 55 15.936 43.025 19.676 1.00109.42 C
ATOM 372 C PHE A 55 16.023 43.908 20.908 1.00111.23 C
ATOM 373 O PHE A 55 15.192 43.821 21.815 1.00111.53 O
ATOM 374 CB PHE A 55 14.599 43.256 18.962 1.00110.05 C
ATOM 375 CG PHE A 55 14.493 42.564 17.628 1.00109.86 C
ATOM 376 CD1 PHE A 55 15.416 42.824 16.616 1.00109.98 C
ATOM 377 CD2 PHE A 55 13.481 41.643 17.389 1.00109.37 C
ATOM 378 CE1 PHE A 55 15.332 42.177 15.387 1.00109.69 C
ATOM 379 CE2 PHE A 55 13.388 40.992 16.166 1.00109.52 C
ATOM 380 CZ PHE A 55 14.318 41.260 15.163 1.00109.89 C
ATOM 381 N VAL A 56 17.048 44.756 20.917 1.00113.41 N
ATOM 382 CA VAL A 56 17.305 45.703 21.998 1.00114.90 C
ATOM 383 C VAL A 56 16.120 46.662 22.079 1.00115.83 C
ATOM 384 O VAL A 56 15.704 47.222 21.061 1.00115.87 O
ATOM 385 CB VAL A 56 18.596 46.508 21.711 1.00115.37 C
ATOM 386 CG1 VAL A 56 19.799 45.566 21.643 1.00114.66 C
ATOM 387 CG2 VAL A 56 18.454 47.269 20.392 1.00115.29 C
ATOM 388 N ASP A 57 15.581 46.866 23.278 1.00116.87 N
ATOM 389 CA ASP A 57 14.423 47.741 23.408 1.00118.41 C
ATOM 390 C ASP A 57 14.740 49.223 23.575 1.00119.01 C
ATOM 391 O ASP A 57 15.558 49.606 24.414 1.00118.81 O
ATOM 392 CB ASP A 57 13.528 47.274 24.555 1.00118.79 C
ATOM 393 CG ASP A 57 12.051 47.475 24.250 1.00119.33 C
ATOM 394 OD1 ASP A 57 11.647 48.632 23.999 1.00118.72 O
ATOM 395 OD2 ASP A 57 11.301 46.472 24.251 1.00119.85 O
ATOM 396 N VAL A 58 14.068 50.042 22.765 1.00119.62 N
ATOM 397 CA VAL A 58 14.237 51.494 22.771 1.00119.95 C
ATOM 398 C VAL A 58 13.555 52.159 23.967 1.00120.08 C
ATOM 399 O VAL A 58 12.341 52.397 23.958 1.00120.20 O
ATOM 400 CB VAL A 58 13.678 52.127 21.470 1.00120.15 C
ATOM 401 CG1 VAL A 58 13.733 53.652 21.554 1.00119.13 C
ATOM 402 CG2 VAL A 58 14.476 51.630 20.273 1.00120.11 C
ATOM 403 N PRO A 59 14.340 52.481 25.010 1.00119.88 N
ATOM 404 CA PRO A 59 13.798 53.124 26.210 1.00118.69 C
ATOM 405 C PRO A 59 13.081 54.412 25.852 1.00117.26 C
ATOM 406 O PRO A 59 13.558 55.197 25.034 1.00116.68 O
ATOM 407 CB PRO A 59 15.039 53.359 27.066 1.00119.27 C
ATOM 408 CG PRO A 59 16.130 53.533 26.038 1.00119.94 C
ATOM 409 CD PRO A 59 15.814 52.431 25.062 1.00119.85 C
ATOM 410 N ASN A 60 11.928 54.620 26.469 1.00116.37 N
ATOM 411 CA ASN A 60 11.132 55.808 26.210 1.00116.10 C
ATOM 412 C ASN A 60 10.935 56.022 24.707 1.00115.83 C
ATOM 413 O ASN A 60 11.570 56.886 24.093 1.00115.68 O
ATOM 414 CB ASN A 60 11.791 57.042 26.844 1.00115.54 C
ATOM 415 CG ASN A 60 10.939 58.301 26.704 1.00115.47 C
ATOM 416 OD1 ASN A 60 9.751 58.304 27.031 1.00114.68 O
ATOM 417 ND2 ASN A 60 11.550 59.379 26.221 1.00115.65 N
ATOM 418 N ASP A 61 10.061 55.209 24.122 1.00115.14 N
ATOM 419 CA ASP A 61 9.735 55.306 22.706 1.00114.13 C
ATOM 420 C ASP A 61 8.441 56.131 22.669 1.00113.89 C
ATOM 421 O ASP A 61 7.418 55.724 23.229 1.00113.46 O
ATOM 422 CB ASP A 61 9.504 53.904 22.129 1.00113.36 C
ATOM 423 CG ASP A 61 9.587 53.874 20.621 1.00112.30 C
ATOM 424 OD1 ASP A 61 9.116 54.835 19.986 1.00111.35 O
ATOM 425 OD2 ASP A 61 10.113 52.885 20.071 1.00111.82 O
ATOM 426 N SER A 62 8.491 57.292 22.023 1.00113.79 N
ATOM 427 CA SER A 62 7.330 58.184 21.961 1.00113.65 C
ATOM 428 C SER A 62 6.397 57.976 20.759 1.00112.82 C
ATOM 429 O SER A 62 6.847 57.735 19.635 1.00112.49 O
ATOM 430 CB SER A 62 7.805 59.644 21.995 1.00114.15 C
ATOM 431 OG SER A 62 8.621 59.890 23.131 1.00113.73 O
ATOM 432 N PRO A 63 5.074 58.072 20.993 1.00111.99 N
ATOM 433 CA PRO A 63 4.026 57.905 19.973 1.00111.53 C
ATOM 434 C PRO A 63 3.924 59.018 18.918 1.00110.84 C
ATOM 435 O PRO A 63 3.075 59.901 19.031 1.00111.39 O
ATOM 436 CB PRO A 63 2.746 57.801 20.808 1.00111.29 C
ATOM 437 CG PRO A 63 3.230 57.204 22.091 1.00111.54 C
ATOM 438 CD PRO A 63 4.488 58.000 22.343 1.00111.51 C
ATOM 439 N PHE A 64 4.779 58.956 17.898 1.00109.81 N
ATOM 440 CA PHE A 64 4.801 59.925 16.794 1.00109.33 C
ATOM 441 C PHE A 64 3.376 60.280 16.332 1.00108.56 C
ATOM 442 O PHE A 64 2.874 59.711 15.364 1.00108.37 O
ATOM 443 CB PHE A 64 5.604 59.318 15.630 1.00110.08 C
ATOM 444 CG PHE A 64 5.743 60.216 14.419 1.00110.63 C
ATOM 445 CD1 PHE A 64 6.603 61.309 14.433 1.00110.93 C
ATOM 446 CD2 PHE A 64 5.060 59.926 13.240 1.00110.60 C
ATOM 447 CE1 PHE A 64 6.786 62.091 13.289 1.00110.88 C
ATOM 448 CE2 PHE A 64 5.237 60.703 12.094 1.00110.13 C
ATOM 449 CZ PHE A 64 6.101 61.784 12.120 1.00110.58 C
ATOM 450 N GLN A 65 2.738 61.226 17.023 1.00108.06 N
ATOM 451 CA GLN A 65 1.367 61.655 16.719 1.00107.81 C
ATOM 452 C GLN A 65 0.369 60.580 17.162 1.00107.14 C
ATOM 453 O GLN A 65 -0.174 60.636 18.268 1.00107.01 O
ATOM 454 CB GLN A 65 1.184 61.907 15.219 1.00108.70 C
ATOM 455 CG GLN A 65 2.222 62.822 14.589 1.00110.56 C
ATOM 456 CD GLN A 65 1.912 63.139 13.131 1.00110.91 C
ATOM 457 OE1 GLN A 65 0.874 63.726 12.822 1.00110.88 O
ATOM 458 NE2 GLN A 65 2.812 62.748 12.230 1.00110.95 N
ATOM 459 N ILE A 66 0.137 59.608 16.277 1.00106.12 N
ATOM 460 CA ILE A 66 -0.770 58.482 16.523 1.00103.69 C
ATOM 461 C ILE A 66 0.058 57.190 16.548 1.00101.94 C
ATOM 462 O ILE A 66 -0.175 56.307 17.382 1.00100.49 O
ATOM 463 CB ILE A 66 -1.866 58.389 15.410 1.00103.32 C
ATOM 464 CG1 ILE A 66 -3.243 58.685 16.002 1.00102.53 C
ATOM 465 CG2 ILE A 66 -1.858 57.025 14.758 1.00103.34 C
ATOM 466 CD1 ILE A 66 -3.438 60.137 16.393 1.00102.55 C
ATOM 467 N VAL A 67 1.027 57.107 15.631 1.00100.15 N
ATOM 468 CA VAL A 67 1.922 55.956 15.510 1.00 98.05 C
ATOM 469 C VAL A 67 2.641 55.642 16.816 1.00 97.96 C
ATOM 470 O VAL A 67 3.259 56.515 17.419 1.00 98.49 O
ATOM 471 CB VAL A 67 2.977 56.184 14.415 1.00 96.47 C
ATOM 472 CG1 VAL A 67 3.852 54.939 14.274 1.00 95.16 C
ATOM 473 CG2 VAL A 67 2.290 56.542 13.105 1.00 94.29 C
ATOM 474 N LYS A 68 2.578 54.386 17.237 1.00 97.30 N
ATOM 475 CA LYS A 68 3.192 53.985 18.491 1.00 97.06 C
ATOM 476 C LYS A 68 4.474 53.211 18.291 1.00 97.44 C
ATOM 477 O LYS A 68 4.824 52.871 17.162 1.00 97.46 O
ATOM 478 CB LYS A 68 2.185 53.164 19.286 1.00 95.66 C
ATOM 479 CG LYS A 68 0.822 53.788 19.193 1.00 94.66 C
ATOM 480 CD LYS A 68 -0.213 53.089 20.021 1.00 94.77 C
ATOM 481 CE LYS A 68 -1.570 53.725 19.751 1.00 95.37 C
ATOM 482 NZ LYS A 68 -1.485 55.223 19.734 1.00 93.99 N
ATOM 483 N ASN A 69 5.174 52.968 19.398 1.00 98.69 N
ATOM 484 CA ASN A 69 6.444 52.231 19.423 1.00100.55 C
ATOM 485 C ASN A 69 7.261 52.365 18.126 1.00101.33 C
ATOM 486 O ASN A 69 7.800 51.377 17.622 1.00100.98 O
ATOM 487 CB ASN A 69 6.162 50.747 19.694 1.00101.27 C
ATOM 488 CG ASN A 69 5.332 50.520 20.957 1.00101.35 C
ATOM 489 OD1 ASN A 69 5.877 50.330 22.049 1.00101.81 O
ATOM 490 ND2 ASN A 69 4.006 50.543 20.808 1.00100.63 N
ATOM 491 N PRO A 70 7.387 53.596 17.593 1.00102.26 N
ATOM 492 CA PRO A 70 8.126 53.865 16.353 1.00102.62 C
ATOM 493 C PRO A 70 9.597 53.482 16.341 1.00102.96 C
ATOM 494 O PRO A 70 10.024 52.663 15.526 1.00103.01 O
ATOM 495 CB PRO A 70 7.916 55.362 16.150 1.00103.21 C
ATOM 496 CG PRO A 70 7.868 55.873 17.545 1.00103.31 C
ATOM 497 CD PRO A 70 6.984 54.861 18.235 1.00102.72 C
ATOM 498 N ARG A 71 10.372 54.090 17.230 1.00103.42 N
ATOM 499 CA ARG A 71 11.798 53.808 17.313 1.00104.26 C
ATOM 500 C ARG A 71 12.048 52.304 17.415 1.00104.02 C
ATOM 501 O ARG A 71 12.987 51.771 16.809 1.00104.32 O
ATOM 502 CB ARG A 71 12.389 54.536 18.518 1.00105.61 C
ATOM 503 CG ARG A 71 12.195 56.037 18.437 1.00107.38 C
ATOM 504 CD ARG A 71 12.640 56.742 19.702 1.00109.01 C
ATOM 505 NE ARG A 71 12.465 58.188 19.588 1.00109.72 N
ATOM 506 CZ ARG A 71 11.288 58.789 19.442 1.00110.10 C
ATOM 507 NH1 ARG A 71 10.173 58.068 19.395 1.00110.13 N
ATOM 508 NH2 ARG A 71 11.228 60.110 19.335 1.00109.92 N
ATOM 509 N SER A 72 11.200 51.624 18.180 1.00103.10 N
ATOM 510 CA SER A 72 11.313 50.180 18.346 1.00101.82 C
ATOM 511 C SER A 72 11.311 49.516 16.957 1.00101.36 C
ATOM 512 O SER A 72 12.310 48.923 16.527 1.00100.77 O
ATOM 513 CB SER A 72 10.135 49.655 19.185 1.00101.15 C
ATOM 514 OG SER A 72 10.120 50.217 20.488 1.00 99.62 O
ATOM 515 N VAL A 73 10.179 49.648 16.265 1.00100.71 N
ATOM 516 CA VAL A 73 9.971 49.085 14.934 1.00 99.43 C
ATOM 517 C VAL A 73 10.957 49.604 13.891 1.00 98.74 C
ATOM 518 O VAL A 73 11.145 48.989 12.844 1.00 98.50 O
ATOM 519 CB VAL A 73 8.543 49.389 14.435 1.00 99.57 C
ATOM 520 CG1 VAL A 73 8.318 48.724 13.093 1.00 99.47 C
ATOM 521 CG2 VAL A 73 7.511 48.919 15.462 1.00 98.64 C
ATOM 522 N GLY A 74 11.576 50.742 14.170 1.00 98.05 N
ATOM 523 CA GLY A 74 12.532 51.287 13.230 1.00 98.09 C
ATOM 524 C GLY A 74 13.882 50.608 13.367 1.00 98.36 C
ATOM 525 O GLY A 74 14.550 50.310 12.372 1.00 97.94 O
ATOM 526 N LYS A 75 14.290 50.358 14.607 1.00 98.26 N
ATOM 527 CA LYS A 75 15.571 49.719 14.853 1.00 98.70 C
ATOM 528 C LYS A 75 15.504 48.202 14.721 1.00 98.41 C
ATOM 529 O LYS A 75 16.486 47.558 14.324 1.00 98.11 O
ATOM 530 CB LYS A 75 16.101 50.088 16.238 1.00 99.64 C
ATOM 531 CG LYS A 75 17.410 49.371 16.591 1.00101.06 C
ATOM 532 CD LYS A 75 18.475 49.577 15.507 1.00101.25 C
ATOM 533 CE LYS A 75 19.682 48.675 15.721 1.00100.94 C
ATOM 534 NZ LYS A 75 20.639 48.782 14.585 1.00100.45 N
ATOM 535 N ALA A 76 14.350 47.632 15.064 1.00 98.25 N
ATOM 536 CA ALA A 76 14.159 46.187 14.972 1.00 97.31 C
ATOM 537 C ALA A 76 14.169 45.777 13.506 1.00 96.60 C
ATOM 538 O ALA A 76 14.733 44.743 13.149 1.00 95.57 O
ATOM 539 CB ALA A 76 12.836 45.788 15.619 1.00 96.93 C
ATOM 540 N ASN A 77 13.542 46.608 12.671 1.00 97.00 N
ATOM 541 CA ASN A 77 13.452 46.380 11.229 1.00 97.74 C
ATOM 542 C ASN A 77 14.752 46.753 10.531 1.00 98.75 C
ATOM 543 O ASN A 77 15.021 46.296 9.420 1.00 98.91 O
ATOM 544 CB ASN A 77 12.290 47.184 10.631 1.00 97.23 C
ATOM 545 CG ASN A 77 10.975 46.405 10.622 1.00 97.89 C
ATOM 546 OD1 ASN A 77 10.757 45.538 9.771 1.00 96.57 O
ATOM 547 ND2 ASN A 77 10.097 46.708 11.580 1.00 97.76 N
ATOM 548 N GLU A 78 15.550 47.597 11.181 1.00 99.93 N
ATOM 549 CA GLU A 78 16.837 47.996 10.624 1.00100.34 C
ATOM 550 C GLU A 78 17.804 46.831 10.805 1.00 99.33 C
ATOM 551 O GLU A 78 18.568 46.486 9.902 1.00 99.02 O
ATOM 552 CB GLU A 78 17.383 49.231 11.342 1.00101.86 C
ATOM 553 CG GLU A 78 18.810 49.574 10.935 1.00103.76 C
ATOM 554 CD GLU A 78 19.304 50.857 11.561 1.00104.81 C
ATOM 555 OE1 GLU A 78 19.254 50.962 12.806 1.00105.01 O
ATOM 556 OE2 GLU A 78 19.742 51.752 10.803 1.00105.37 O
ATOM 557 N GLN A 79 17.761 46.226 11.985 1.00 98.33 N
ATOM 558 CA GLN A 79 18.615 45.093 12.284 1.00 98.14 C
ATOM 559 C GLN A 79 18.317 43.920 11.350 1.00 98.36 C
ATOM 560 O GLN A 79 19.233 43.197 10.938 1.00 99.37 O
ATOM 561 CB GLN A 79 18.415 44.657 13.735 1.00 98.02 C
ATOM 562 CG GLN A 79 19.077 43.327 14.072 1.00 98.51 C
ATOM 563 CD GLN A 79 18.936 42.961 15.536 1.00 99.74 C
ATOM 564 OE1 GLN A 79 19.382 41.894 15.968 1.00100.42 O
ATOM 565 NE2 GLN A 79 18.318 43.849 16.312 1.00 99.69 N
ATOM 566 N LEU A 80 17.038 43.744 11.015 1.00 97.08 N
ATOM 567 CA LEU A 80 16.596 42.648 10.154 1.00 96.12 C
ATOM 568 C LEU A 80 17.004 42.802 8.698 1.00 95.39 C
ATOM 569 O LEU A 80 17.694 41.942 8.155 1.00 94.88 O
ATOM 570 CB LEU A 80 15.068 42.475 10.256 1.00 96.94 C
ATOM 571 CG LEU A 80 14.318 41.481 9.348 1.00 96.90 C
ATOM 572 CD1 LEU A 80 14.882 40.069 9.459 1.00 96.64 C
ATOM 573 CD2 LEU A 80 12.853 41.486 9.744 1.00 97.01 C
ATOM 574 N ALA A 81 16.570 43.888 8.064 1.00 95.38 N
ATOM 575 CA ALA A 81 16.904 44.132 6.660 1.00 95.32 C
ATOM 576 C ALA A 81 18.365 43.748 6.453 1.00 95.15 C
ATOM 577 O ALA A 81 18.707 43.034 5.505 1.00 95.06 O
ATOM 578 CB ALA A 81 16.680 45.610 6.301 1.00 94.39 C
ATOM 579 N ALA A 82 19.210 44.217 7.371 1.00 94.53 N
ATOM 580 CA ALA A 82 20.639 43.944 7.352 1.00 92.86 C
ATOM 581 C ALA A 82 20.925 42.450 7.167 1.00 92.77 C
ATOM 582 O ALA A 82 21.511 42.040 6.158 1.00 94.08 O
ATOM 583 CB ALA A 82 21.259 44.430 8.641 1.00 91.55 C
ATOM 584 N VAL A 83 20.508 41.631 8.131 1.00 90.57 N
ATOM 585 CA VAL A 83 20.750 40.196 8.036 1.00 87.86 C
ATOM 586 C VAL A 83 20.245 39.634 6.717 1.00 87.81 C
ATOM 587 O VAL A 83 20.903 38.810 6.101 1.00 87.85 O
ATOM 588 CB VAL A 83 20.081 39.426 9.183 1.00 85.44 C
ATOM 589 CG1 VAL A 83 20.562 37.977 9.171 1.00 83.17 C
ATOM 590 CG2 VAL A 83 20.389 40.107 10.519 1.00 84.36 C
ATOM 591 N VAL A 84 19.078 40.094 6.284 1.00 88.67 N
ATOM 592 CA VAL A 84 18.480 39.633 5.030 1.00 89.97 C
ATOM 593 C VAL A 84 19.382 39.901 3.816 1.00 90.78 C
ATOM 594 O VAL A 84 19.658 39.005 3.014 1.00 89.94 O
ATOM 595 CB VAL A 84 17.105 40.312 4.804 1.00 89.27 C
ATOM 596 CG1 VAL A 84 16.498 39.842 3.488 1.00 88.30 C
ATOM 597 CG2 VAL A 84 16.175 40.007 5.973 1.00 88.68 C
ATOM 598 N ALA A 85 19.833 41.142 3.681 1.00 92.01 N
ATOM 599 CA ALA A 85 20.704 41.498 2.574 1.00 93.16 C
ATOM 600 C ALA A 85 21.971 40.673 2.738 1.00 93.76 C
ATOM 601 O ALA A 85 22.607 40.268 1.754 1.00 92.85 O
ATOM 602 CB ALA A 85 21.032 42.996 2.616 1.00 92.48 C
ATOM 603 N GLU A 86 22.305 40.414 4.002 1.00 94.93 N
ATOM 604 CA GLU A 86 23.492 39.655 4.383 1.00 96.65 C
ATOM 605 C GLU A 86 23.513 38.245 3.808 1.00 97.30 C
ATOM 606 O GLU A 86 24.541 37.767 3.317 1.00 96.34 O
ATOM 607 CB GLU A 86 23.585 39.587 5.907 1.00 97.43 C
ATOM 608 CG GLU A 86 25.000 39.631 6.397 1.00101.11 C
ATOM 609 CD GLU A 86 25.795 40.709 5.681 1.00103.56 C
ATOM 610 OE1 GLU A 86 25.361 41.887 5.705 1.00104.28 O
ATOM 611 OE2 GLU A 86 26.847 40.374 5.090 1.00104.59 O
ATOM 612 N THR A 87 22.363 37.587 3.884 1.00 98.79 N
ATOM 613 CA THR A 87 22.207 36.236 3.382 1.00 99.86 C
ATOM 614 C THR A 87 22.033 36.335 1.888 1.00101.87 C
ATOM 615 O THR A 87 22.756 35.697 1.133 1.00102.78 O
ATOM 616 CB THR A 87 20.963 35.572 3.962 1.00 99.41 C
ATOM 617 OG1 THR A 87 20.789 35.983 5.324 1.00 99.80 O
ATOM 618 CG2 THR A 87 21.117 34.075 3.930 1.00 99.73 C
ATOM 619 N GLN A 88 21.065 37.147 1.471 1.00104.27 N
ATOM 620 CA GLN A 88 20.771 37.362 0.053 1.00107.00 C
ATOM 621 C GLN A 88 22.018 37.455 -0.834 1.00107.90 C
ATOM 622 O GLN A 88 22.007 36.996 -1.983 1.00107.08 O
ATOM 623 CB GLN A 88 19.939 38.638 -0.121 1.00107.91 C
ATOM 624 CG GLN A 88 18.444 38.450 0.060 1.00109.47 C
ATOM 625 CD GLN A 88 17.885 37.366 -0.847 1.00110.31 C
ATOM 626 OE1 GLN A 88 18.415 37.111 -1.932 1.00110.06 O
ATOM 627 NE2 GLN A 88 16.799 36.730 -0.410 1.00110.80 N
ATOM 628 N LYS A 89 23.078 38.057 -0.293 1.00109.56 N
ATOM 629 CA LYS A 89 24.342 38.227 -1.008 1.00110.90 C
ATOM 630 C LYS A 89 25.078 36.891 -1.153 1.00111.00 C
ATOM 631 O LYS A 89 25.699 36.618 -2.185 1.00110.95 O
ATOM 632 CB LYS A 89 25.228 39.228 -0.266 1.00111.68 C
ATOM 633 CG LYS A 89 26.458 39.658 -1.047 1.00113.68 C
ATOM 634 CD LYS A 89 27.348 40.596 -0.230 1.00116.52 C
ATOM 635 CE LYS A 89 26.614 41.873 0.203 1.00117.23 C
ATOM 636 NZ LYS A 89 27.492 42.813 0.971 1.00117.27 N
ATOM 637 N ASN A 90 25.005 36.068 -0.110 1.00110.80 N
ATOM 638 CA ASN A 90 25.634 34.751 -0.112 1.00110.60 C
ATOM 639 C ASN A 90 24.921 33.851 -1.108 1.00110.46 C
ATOM 640 O ASN A 90 25.410 32.775 -1.460 1.00110.57 O
ATOM 641 CB ASN A 90 25.551 34.132 1.280 1.00110.18 C
ATOM 642 CG ASN A 90 26.339 34.909 2.299 1.00109.88 C
ATOM 643 OD1 ASN A 90 27.566 34.892 2.280 1.00110.06 O
ATOM 644 ND2 ASN A 90 25.644 35.611 3.186 1.00109.05 N
ATOM 645 N GLY A 91 23.747 34.300 -1.543 1.00110.39 N
ATOM 646 CA GLY A 91 22.968 33.548 -2.507 1.00109.77 C
ATOM 647 C GLY A 91 21.861 32.669 -1.944 1.00109.04 C
ATOM 648 O GLY A 91 21.079 32.108 -2.715 1.00109.23 O
ATOM 649 N THR A 92 21.770 32.546 -0.620 1.00107.90 N
ATOM 650 CA THR A 92 20.741 31.697 -0.019 1.00106.35 C
ATOM 651 C THR A 92 19.375 32.383 0.037 1.00105.86 C
ATOM 652 O THR A 92 19.283 33.615 -0.047 1.00105.70 O
ATOM 653 CB THR A 92 21.144 31.233 1.418 1.00105.45 C
ATOM 654 OG1 THR A 92 20.501 32.048 2.402 1.00103.68 O
ATOM 655 CG2 THR A 92 22.655 31.319 1.611 1.00104.19 C
ATOM 656 N ILE A 93 18.318 31.573 0.154 1.00104.70 N
ATOM 657 CA ILE A 93 16.942 32.070 0.239 1.00101.94 C
ATOM 658 C ILE A 93 16.600 32.413 1.684 1.00100.46 C
ATOM 659 O ILE A 93 16.758 31.584 2.587 1.00100.27 O
ATOM 660 CB ILE A 93 15.925 31.023 -0.247 1.00101.61 C
ATOM 661 CG1 ILE A 93 16.257 30.580 -1.670 1.00101.79 C
ATOM 662 CG2 ILE A 93 14.523 31.606 -0.191 1.00101.59 C
ATOM 663 CD1 ILE A 93 16.287 31.716 -2.664 1.00102.89 C
ATOM 664 N SER A 94 16.138 33.641 1.890 1.00 98.22 N
ATOM 665 CA SER A 94 15.780 34.113 3.217 1.00 96.48 C
ATOM 666 C SER A 94 14.339 33.749 3.568 1.00 95.30 C
ATOM 667 O SER A 94 13.420 33.963 2.763 1.00 94.98 O
ATOM 668 CB SER A 94 15.962 35.631 3.300 1.00 96.70 C
ATOM 669 OG SER A 94 15.296 36.288 2.230 1.00 96.79 O
ATOM 670 N VAL A 95 14.146 33.182 4.761 1.00 92.94 N
ATOM 671 CA VAL A 95 12.814 32.794 5.229 1.00 89.32 C
ATOM 672 C VAL A 95 12.596 33.325 6.642 1.00 87.17 C
ATOM 673 O VAL A 95 13.033 32.723 7.628 1.00 86.40 O
ATOM 674 CB VAL A 95 12.642 31.274 5.229 1.00 88.54 C
ATOM 675 CG1 VAL A 95 11.154 30.936 5.278 1.00 88.25 C
ATOM 676 CG2 VAL A 95 13.293 30.680 3.992 1.00 87.16 C
ATOM 677 N VAL A 96 11.893 34.450 6.716 1.00 85.04 N
ATOM 678 CA VAL A 96 11.627 35.137 7.968 1.00 83.33 C
ATOM 679 C VAL A 96 10.424 34.694 8.789 1.00 81.90 C
ATOM 680 O VAL A 96 9.293 35.094 8.510 1.00 81.87 O
ATOM 681 CB VAL A 96 11.480 36.654 7.724 1.00 83.38 C
ATOM 682 CG1 VAL A 96 11.342 37.391 9.051 1.00 83.72 C
ATOM 683 CG2 VAL A 96 12.672 37.163 6.947 1.00 83.57 C
ATOM 684 N LEU A 97 10.675 33.868 9.803 1.00 80.03 N
ATOM 685 CA LEU A 97 9.618 33.440 10.711 1.00 76.82 C
ATOM 686 C LEU A 97 9.375 34.744 11.444 1.00 75.41 C
ATOM 687 O LEU A 97 10.333 35.449 11.745 1.00 74.63 O
ATOM 688 CB LEU A 97 10.131 32.399 11.703 1.00 75.09 C
ATOM 689 CG LEU A 97 10.749 31.133 11.112 1.00 75.32 C
ATOM 690 CD1 LEU A 97 10.932 30.113 12.220 1.00 72.55 C
ATOM 691 CD2 LEU A 97 9.851 30.584 10.014 1.00 74.86 C
ATOM 692 N GLY A 98 8.127 35.087 11.736 1.00 74.85 N
ATOM 693 CA GLY A 98 7.936 36.354 12.400 1.00 74.16 C
ATOM 694 C GLY A 98 6.970 36.569 13.541 1.00 74.60 C
ATOM 695 O GLY A 98 6.400 35.656 14.137 1.00 73.56 O
ATOM 696 N GLY A 99 6.865 37.850 13.856 1.00 75.85 N
ATOM 697 CA GLY A 99 6.008 38.352 14.897 1.00 78.40 C
ATOM 698 C GLY A 99 5.122 39.171 13.996 1.00 80.54 C
ATOM 699 O GLY A 99 4.904 38.753 12.856 1.00 80.94 O
ATOM 700 N ASP A 100 4.655 40.334 14.440 1.00 82.59 N
ATOM 701 CA ASP A 100 3.780 41.140 13.590 1.00 84.85 C
ATOM 702 C ASP A 100 4.372 41.386 12.192 1.00 84.58 C
ATOM 703 O ASP A 100 5.584 41.315 11.987 1.00 84.05 O
ATOM 704 CB ASP A 100 3.422 42.461 14.284 1.00 87.56 C
ATOM 705 CG ASP A 100 4.395 43.572 13.978 1.00 90.13 C
ATOM 706 OD1 ASP A 100 4.435 44.009 12.808 1.00 89.63 O
ATOM 707 OD2 ASP A 100 5.107 44.006 14.912 1.00 92.61 O
ATOM 708 N HIS A 101 3.489 41.668 11.242 1.00 84.89 N
ATOM 709 CA HIS A 101 3.840 41.873 9.843 1.00 85.65 C
ATOM 710 C HIS A 101 4.618 43.144 9.530 1.00 85.99 C
ATOM 711 O HIS A 101 4.839 43.459 8.360 1.00 85.93 O
ATOM 712 CB HIS A 101 2.551 41.832 9.009 1.00 86.72 C
ATOM 713 CG HIS A 101 2.738 41.366 7.596 1.00 86.60 C
ATOM 714 ND1 HIS A 101 1.693 40.872 6.839 1.00 85.54 N
ATOM 715 CD2 HIS A 101 3.825 41.355 6.788 1.00 86.26 C
ATOM 716 CE1 HIS A 101 2.131 40.580 5.630 1.00 86.39 C
ATOM 717 NE2 HIS A 101 3.422 40.865 5.570 1.00 86.65 N
ATOM 718 N SER A 102 5.042 43.878 10.552 1.00 86.24 N
ATOM 719 CA SER A 102 5.796 45.103 10.301 1.00 86.63 C
ATOM 720 C SER A 102 7.276 44.785 10.119 1.00 85.62 C
ATOM 721 O SER A 102 8.092 45.676 9.898 1.00 84.65 O
ATOM 722 CB SER A 102 5.615 46.088 11.448 1.00 87.71 C
ATOM 723 OG SER A 102 6.280 45.619 12.605 1.00 91.99 O
ATOM 724 N MET A 103 7.622 43.507 10.229 1.00 85.08 N
ATOM 725 CA MET A 103 9.000 43.095 10.039 1.00 84.48 C
ATOM 726 C MET A 103 9.164 42.876 8.549 1.00 83.76 C
ATOM 727 O MET A 103 10.190 42.378 8.086 1.00 83.39 O
ATOM 728 CB MET A 103 9.302 41.805 10.799 1.00 84.83 C
ATOM 729 CG MET A 103 9.126 41.927 12.302 1.00 87.32 C
ATOM 730 SD MET A 103 9.968 43.364 13.016 1.00 88.58 S
ATOM 731 CE MET A 103 11.677 42.836 12.847 1.00 87.63 C
ATOM 732 N ALA A 104 8.130 43.251 7.802 1.00 83.38 N
ATOM 733 CA ALA A 104 8.143 43.122 6.352 1.00 83.07 C
ATOM 734 C ALA A 104 9.080 44.180 5.763 1.00 82.42 C
ATOM 735 O ALA A 104 9.838 43.900 4.829 1.00 82.21 O
ATOM 736 CB ALA A 104 6.734 43.289 5.799 1.00 84.51 C
ATOM 737 N ILE A 105 9.028 45.398 6.304 1.00 80.53 N
ATOM 738 CA ILE A 105 9.922 46.451 5.829 1.00 78.98 C
ATOM 739 C ILE A 105 11.346 45.892 5.938 1.00 77.86 C
ATOM 740 O ILE A 105 12.063 45.791 4.940 1.00 76.47 O
ATOM 741 CB ILE A 105 9.807 47.765 6.675 1.00 78.15 C
ATOM 742 CG1 ILE A 105 8.926 47.559 7.904 1.00 77.60 C
ATOM 743 CG2 ILE A 105 9.183 48.868 5.831 1.00 78.93 C
ATOM 744 CD1 ILE A 105 8.669 48.857 8.658 1.00 74.53 C
ATOM 745 N GLY A 106 11.737 45.509 7.151 1.00 76.94 N
ATOM 746 CA GLY A 106 13.053 44.943 7.349 1.00 76.15 C
ATOM 747 C GLY A 106 13.354 43.920 6.274 1.00 76.23 C
ATOM 748 O GLY A 106 14.188 44.167 5.407 1.00 77.43 O
ATOM 749 N SER A 107 12.668 42.781 6.316 1.00 75.72 N
ATOM 750 CA SER A 107 12.872 41.711 5.337 1.00 75.71 C
ATOM 751 C SER A 107 12.956 42.222 3.896 1.00 75.75 C
ATOM 752 O SER A 107 13.975 42.051 3.218 1.00 74.82 O
ATOM 753 CB SER A 107 11.735 40.681 5.444 1.00 76.72 C
ATOM 754 OG SER A 107 11.782 39.698 4.408 1.00 75.74 O
ATOM 755 N ILE A 108 11.879 42.853 3.438 1.00 75.95 N
ATOM 756 CA ILE A 108 11.809 43.362 2.079 1.00 75.58 C
ATOM 757 C ILE A 108 12.978 44.277 1.736 1.00 76.75 C
ATOM 758 O ILE A 108 13.625 44.092 0.706 1.00 77.19 O
ATOM 759 CB ILE A 108 10.467 44.079 1.836 1.00 74.49 C
ATOM 760 CG1 ILE A 108 9.315 43.104 2.090 1.00 73.59 C
ATOM 761 CG2 ILE A 108 10.397 44.577 0.409 1.00 75.30 C
ATOM 762 CD1 ILE A 108 7.962 43.605 1.678 1.00 71.41 C
ATOM 763 N SER A 109 13.258 45.253 2.597 1.00 77.84 N
ATOM 764 CA SER A 109 14.378 46.168 2.371 1.00 78.47 C
ATOM 765 C SER A 109 15.657 45.368 2.182 1.00 78.55 C
ATOM 766 O SER A 109 16.288 45.427 1.131 1.00 77.36 O
ATOM 767 CB SER A 109 14.550 47.114 3.564 1.00 78.95 C
ATOM 768 OG SER A 109 13.625 48.183 3.502 1.00 81.14 O
ATOM 769 N GLY A 110 16.026 44.623 3.219 1.00 79.20 N
ATOM 770 CA GLY A 110 17.219 43.812 3.160 1.00 81.12 C
ATOM 771 C GLY A 110 17.305 43.071 1.845 1.00 83.10 C
ATOM 772 O GLY A 110 18.372 42.994 1.240 1.00 83.47 O
ATOM 773 N HIS A 111 16.178 42.536 1.391 1.00 85.03 N
ATOM 774 CA HIS A 111 16.137 41.791 0.135 1.00 87.81 C
ATOM 775 C HIS A 111 16.484 42.651 -1.098 1.00 88.96 C
ATOM 776 O HIS A 111 17.319 42.261 -1.923 1.00 87.29 O
ATOM 777 CB HIS A 111 14.747 41.155 -0.039 1.00 88.57 C
ATOM 778 CG HIS A 111 14.669 40.158 -1.158 1.00 89.32 C
ATOM 779 ND1 HIS A 111 13.495 39.528 -1.509 1.00 89.05 N
ATOM 780 CD2 HIS A 111 15.616 39.692 -2.009 1.00 88.94 C
ATOM 781 CE1 HIS A 111 13.721 38.718 -2.530 1.00 89.41 C
ATOM 782 NE2 HIS A 111 14.999 38.799 -2.852 1.00 88.73 N
ATOM 783 N ALA A 112 15.835 43.814 -1.204 1.00 90.99 N
ATOM 784 CA ALA A 112 16.021 44.756 -2.318 1.00 92.37 C
ATOM 785 C ALA A 112 17.465 45.227 -2.488 1.00 93.72 C
ATOM 786 O ALA A 112 17.876 45.643 -3.579 1.00 93.91 O
ATOM 787 CB ALA A 112 15.101 45.969 -2.131 1.00 91.27 C
ATOM 788 N ARG A 113 18.226 45.175 -1.402 1.00 94.50 N
ATOM 789 CA ARG A 113 19.616 45.589 -1.435 1.00 94.94 C
ATOM 790 C ARG A 113 20.414 44.713 -2.395 1.00 95.62 C
ATOM 791 O ARG A 113 21.213 45.215 -3.184 1.00 96.16 O
ATOM 792 CB ARG A 113 20.202 45.547 -0.015 1.00 94.28 C
ATOM 793 CG ARG A 113 19.745 46.736 0.825 1.00 94.48 C
ATOM 794 CD ARG A 113 20.114 46.645 2.300 1.00 95.26 C
ATOM 795 NE ARG A 113 19.785 47.894 2.999 1.00 96.22 N
ATOM 796 CZ ARG A 113 19.727 48.043 4.326 1.00 96.89 C
ATOM 797 NH1 ARG A 113 19.972 47.015 5.138 1.00 96.87 N
ATOM 798 NH2 ARG A 113 19.422 49.229 4.847 1.00 96.57 N
ATOM 799 N VAL A 114 20.173 43.408 -2.348 1.00 96.02 N
ATOM 800 CA VAL A 114 20.883 42.473 -3.210 1.00 96.73 C
ATOM 801 C VAL A 114 20.171 42.238 -4.546 1.00 97.56 C
ATOM 802 O VAL A 114 20.814 41.949 -5.557 1.00 97.44 O
ATOM 803 CB VAL A 114 21.084 41.130 -2.486 1.00 97.09 C
ATOM 804 CG1 VAL A 114 21.944 40.206 -3.331 1.00 97.30 C
ATOM 805 CG2 VAL A 114 21.724 41.372 -1.117 1.00 96.77 C
ATOM 806 N HIS A 115 18.845 42.363 -4.540 1.00 99.09 N
ATOM 807 CA HIS A 115 18.026 42.179 -5.744 1.00100.13 C
ATOM 808 C HIS A 115 16.963 43.274 -5.811 1.00100.23 C
ATOM 809 O HIS A 115 15.808 43.052 -5.459 1.00100.81 O
ATOM 810 CB HIS A 115 17.325 40.818 -5.730 1.00100.57 C
ATOM 811 CG HIS A 115 18.257 39.649 -5.655 1.00101.28 C
ATOM 812 ND1 HIS A 115 18.888 39.273 -4.490 1.00101.75 N
ATOM 813 CD2 HIS A 115 18.635 38.752 -6.596 1.00101.64 C
ATOM 814 CE1 HIS A 115 19.612 38.189 -4.714 1.00102.42 C
ATOM 815 NE2 HIS A 115 19.475 37.853 -5.983 1.00102.31 N
ATOM 816 N PRO A 116 17.343 44.465 -6.280 1.00100.42 N
ATOM 817 CA PRO A 116 16.471 45.634 -6.410 1.00100.72 C
ATOM 818 C PRO A 116 15.457 45.524 -7.536 1.00100.87 C
ATOM 819 O PRO A 116 14.693 46.461 -7.787 1.00100.56 O
ATOM 820 CB PRO A 116 17.460 46.752 -6.660 1.00101.70 C
ATOM 821 CG PRO A 116 18.451 46.063 -7.564 1.00102.18 C
ATOM 822 CD PRO A 116 18.674 44.745 -6.847 1.00101.10 C
ATOM 823 N ASP A 117 15.461 44.389 -8.225 1.00101.28 N
ATOM 824 CA ASP A 117 14.530 44.175 -9.332 1.00102.06 C
ATOM 825 C ASP A 117 13.382 43.237 -8.950 1.00101.05 C
ATOM 826 O ASP A 117 12.539 42.902 -9.786 1.00101.44 O
ATOM 827 CB ASP A 117 15.281 43.618 -10.550 1.00103.66 C
ATOM 828 CG ASP A 117 16.057 42.344 -10.234 1.00105.43 C
ATOM 829 OD1 ASP A 117 16.826 42.338 -9.244 1.00106.09 O
ATOM 830 OD2 ASP A 117 15.904 41.353 -10.985 1.00106.50 O
ATOM 831 N LEU A 118 13.350 42.835 -7.679 1.00 98.82 N
ATOM 832 CA LEU A 118 12.324 41.926 -7.167 1.00 95.55 C
ATOM 833 C LEU A 118 10.892 42.471 -7.232 1.00 93.68 C
ATOM 834 O LEU A 118 10.659 43.681 -7.348 1.00 93.41 O
ATOM 835 CB LEU A 118 12.644 41.524 -5.709 1.00 93.59 C
ATOM 836 CG LEU A 118 12.657 42.592 -4.599 1.00 92.16 C
ATOM 837 CD1 LEU A 118 11.272 43.181 -4.388 1.00 92.08 C
ATOM 838 CD2 LEU A 118 13.134 41.963 -3.313 1.00 90.84 C
ATOM 839 N CYS A 119 9.940 41.546 -7.176 1.00 90.59 N
ATOM 840 CA CYS A 119 8.525 41.875 -7.169 1.00 86.30 C
ATOM 841 C CYS A 119 8.109 41.414 -5.793 1.00 83.38 C
ATOM 842 O CYS A 119 8.946 40.981 -5.007 1.00 83.17 O
ATOM 843 CB CYS A 119 7.782 41.080 -8.234 1.00 85.90 C
ATOM 844 SG CYS A 119 8.373 39.392 -8.362 1.00 85.58 S
ATOM 845 N VAL A 120 6.824 41.488 -5.497 1.00 80.52 N
ATOM 846 CA VAL A 120 6.353 41.078 -4.187 1.00 76.40 C
ATOM 847 C VAL A 120 4.922 40.565 -4.220 1.00 73.42 C
ATOM 848 O VAL A 120 4.020 41.248 -4.695 1.00 72.14 O
ATOM 849 CB VAL A 120 6.446 42.262 -3.173 1.00 75.95 C
ATOM 850 CG1 VAL A 120 5.674 41.930 -1.902 1.00 74.91 C
ATOM 851 CG2 VAL A 120 7.915 42.554 -2.842 1.00 73.63 C
ATOM 852 N ILE A 121 4.727 39.350 -3.723 1.00 71.26 N
ATOM 853 CA ILE A 121 3.390 38.758 -3.640 1.00 69.79 C
ATOM 854 C ILE A 121 2.987 38.893 -2.166 1.00 66.24 C
ATOM 855 O ILE A 121 3.645 38.354 -1.273 1.00 65.09 O
ATOM 856 CB ILE A 121 3.382 37.252 -4.078 1.00 71.19 C
ATOM 857 CG1 ILE A 121 3.643 37.117 -5.584 1.00 71.26 C
ATOM 858 CG2 ILE A 121 2.023 36.637 -3.802 1.00 71.09 C
ATOM 859 CD1 ILE A 121 4.863 37.861 -6.072 1.00 72.36 C
ATOM 860 N TRP A 122 1.916 39.631 -1.918 1.00 62.73 N
ATOM 861 CA TRP A 122 1.471 39.872 -0.556 1.00 60.62 C
ATOM 862 C TRP A 122 0.147 39.186 -0.203 1.00 60.19 C
ATOM 863 O TRP A 122 -0.941 39.704 -0.490 1.00 59.32 O
ATOM 864 CB TRP A 122 1.378 41.391 -0.344 1.00 58.94 C
ATOM 865 CG TRP A 122 1.153 41.853 1.077 1.00 56.58 C
ATOM 866 CD1 TRP A 122 -0.029 41.851 1.766 1.00 55.86 C
ATOM 867 CD2 TRP A 122 2.126 42.438 1.956 1.00 55.45 C
ATOM 868 NE1 TRP A 122 0.144 42.402 3.018 1.00 55.24 N
ATOM 869 CE2 TRP A 122 1.460 42.762 3.167 1.00 55.02 C
ATOM 870 CE3 TRP A 122 3.500 42.703 1.851 1.00 54.23 C
ATOM 871 CZ2 TRP A 122 2.111 43.359 4.250 1.00 54.64 C
ATOM 872 CZ3 TRP A 122 4.157 43.297 2.934 1.00 54.27 C
ATOM 873 CH2 TRP A 122 3.461 43.610 4.120 1.00 55.66 C
ATOM 874 N VAL A 123 0.254 38.010 0.414 1.00 59.72 N
ATOM 875 CA VAL A 123 -0.925 37.257 0.851 1.00 59.40 C
ATOM 876 C VAL A 123 -1.212 37.675 2.307 1.00 57.38 C
ATOM 877 O VAL A 123 -0.516 37.275 3.244 1.00 55.82 O
ATOM 878 CB VAL A 123 -0.697 35.723 0.789 1.00 59.65 C
ATOM 879 CG1 VAL A 123 -2.017 35.003 0.936 1.00 58.94 C
ATOM 880 CG2 VAL A 123 -0.043 35.336 -0.519 1.00 58.72 C
ATOM 881 N ASP A 124 -2.245 38.497 2.465 1.00 55.40 N
ATOM 882 CA ASP A 124 -2.649 39.052 3.755 1.00 54.22 C
ATOM 883 C ASP A 124 -4.128 39.331 3.553 1.00 55.31 C
ATOM 884 O ASP A 124 -4.581 39.455 2.405 1.00 55.23 O
ATOM 885 CB ASP A 124 -1.889 40.375 3.985 1.00 50.71 C
ATOM 886 CG ASP A 124 -2.005 40.899 5.388 1.00 47.58 C
ATOM 887 OD1 ASP A 124 -3.129 41.084 5.879 1.00 46.94 O
ATOM 888 OD2 ASP A 124 -0.959 41.157 6.016 1.00 46.77 O
ATOM 889 N ALA A 125 -4.884 39.407 4.645 1.00 56.37 N
ATOM 890 CA ALA A 125 -6.307 39.725 4.538 1.00 57.62 C
ATOM 891 C ALA A 125 -6.360 41.236 4.271 1.00 58.34 C
ATOM 892 O ALA A 125 -7.222 41.739 3.546 1.00 56.62 O
ATOM 893 CB ALA A 125 -7.033 39.393 5.843 1.00 56.07 C
ATOM 894 N HIS A 126 -5.381 41.932 4.849 1.00 59.92 N
ATOM 895 CA HIS A 126 -5.241 43.374 4.762 1.00 61.14 C
ATOM 896 C HIS A 126 -4.154 43.830 3.807 1.00 64.86 C
ATOM 897 O HIS A 126 -3.182 43.103 3.556 1.00 65.54 O
ATOM 898 CB HIS A 126 -4.914 43.930 6.141 1.00 58.52 C
ATOM 899 CG HIS A 126 -5.564 43.177 7.247 1.00 57.04 C
ATOM 900 ND1 HIS A 126 -4.956 42.112 7.877 1.00 59.20 N
ATOM 901 CD2 HIS A 126 -6.815 43.256 7.755 1.00 55.86 C
ATOM 902 CE1 HIS A 126 -5.810 41.557 8.720 1.00 58.98 C
ATOM 903 NE2 HIS A 126 -6.946 42.232 8.664 1.00 58.70 N
ATOM 904 N THR A 127 -4.329 45.052 3.298 1.00 67.28 N
ATOM 905 CA THR A 127 -3.372 45.686 2.402 1.00 69.38 C
ATOM 906 C THR A 127 -2.215 46.169 3.285 1.00 70.18 C
ATOM 907 O THR A 127 -1.039 46.062 2.916 1.00 68.18 O
ATOM 908 CB THR A 127 -4.006 46.902 1.677 1.00 71.32 C
ATOM 909 OG1 THR A 127 -4.933 47.547 2.561 1.00 72.91 O
ATOM 910 CG2 THR A 127 -4.729 46.470 0.401 1.00 70.67 C
ATOM 911 N ASP A 128 -2.568 46.686 4.463 1.00 72.64 N
ATOM 912 CA ASP A 128 -1.585 47.192 5.423 1.00 76.54 C
ATOM 913 C ASP A 128 -0.800 48.353 4.786 1.00 78.32 C
ATOM 914 O ASP A 128 0.327 48.659 5.186 1.00 77.37 O
ATOM 915 CB ASP A 128 -0.598 46.070 5.845 1.00 76.13 C
ATOM 916 CG ASP A 128 -1.299 44.825 6.405 1.00 74.37 C
ATOM 917 OD1 ASP A 128 -2.361 44.968 7.056 1.00 74.66 O
ATOM 918 OD2 ASP A 128 -0.774 43.706 6.199 1.00 71.25 O
ATOM 919 N ILE A 129 -1.422 48.988 3.791 1.00 81.57 N
ATOM 920 CA ILE A 129 -0.837 50.099 3.029 1.00 82.62 C
ATOM 921 C ILE A 129 -1.206 51.494 3.574 1.00 83.95 C
ATOM 922 O ILE A 129 -1.137 52.497 2.855 1.00 83.15 O
ATOM 923 CB ILE A 129 -1.235 49.968 1.503 1.00 81.91 C
ATOM 924 CG1 ILE A 129 -0.529 51.027 0.673 1.00 81.40 C
ATOM 925 CG2 ILE A 129 -2.752 50.058 1.333 1.00 80.22 C
ATOM 926 CD1 ILE A 129 0.960 50.999 0.830 1.00 82.11 C
ATOM 927 N ASN A 130 -1.572 51.546 4.856 1.00 85.83 N
ATOM 928 CA ASN A 130 -1.923 52.800 5.508 1.00 86.95 C
ATOM 929 C ASN A 130 -0.667 53.553 5.927 1.00 87.55 C
ATOM 930 O ASN A 130 0.391 52.965 6.148 1.00 87.00 O
ATOM 931 CB ASN A 130 -2.805 52.564 6.746 1.00 88.13 C
ATOM 932 CG ASN A 130 -4.294 52.509 6.412 1.00 90.24 C
ATOM 933 OD1 ASN A 130 -4.780 53.246 5.550 1.00 91.56 O
ATOM 934 ND2 ASN A 130 -5.027 51.645 7.110 1.00 91.70 N
ATOM 935 N THR A 131 -0.802 54.867 6.029 1.00 88.52 N
ATOM 936 CA THR A 131 0.291 55.733 6.415 1.00 88.78 C
ATOM 937 C THR A 131 0.007 56.312 7.797 1.00 90.67 C
ATOM 938 O THR A 131 -1.112 56.202 8.317 1.00 89.83 O
ATOM 939 CB THR A 131 0.424 56.874 5.420 1.00 87.72 C
ATOM 940 OG1 THR A 131 -0.777 57.660 5.439 1.00 86.20 O
ATOM 941 CG2 THR A 131 0.637 56.319 4.025 1.00 87.64 C
ATOM 942 N PRO A 132 1.025 56.933 8.414 1.00 92.13 N
ATOM 943 CA PRO A 132 0.924 57.549 9.745 1.00 92.76 C
ATOM 944 C PRO A 132 -0.234 58.548 9.786 1.00 92.59 C
ATOM 945 O PRO A 132 -0.730 58.927 10.857 1.00 91.94 O
ATOM 946 CB PRO A 132 2.282 58.237 9.905 1.00 93.72 C
ATOM 947 CG PRO A 132 3.208 57.353 9.106 1.00 92.98 C
ATOM 948 CD PRO A 132 2.391 57.075 7.872 1.00 92.38 C
ATOM 949 N LEU A 133 -0.639 58.957 8.586 1.00 92.49 N
ATOM 950 CA LEU A 133 -1.714 59.917 8.361 1.00 92.47 C
ATOM 951 C LEU A 133 -3.065 59.221 8.373 1.00 92.31 C
ATOM 952 O LEU A 133 -4.014 59.671 9.023 1.00 92.59 O
ATOM 953 CB LEU A 133 -1.520 60.587 6.998 1.00 92.42 C
ATOM 954 CG LEU A 133 -0.109 61.073 6.657 1.00 93.22 C
ATOM 955 CD1 LEU A 133 -0.103 61.677 5.255 1.00 92.74 C
ATOM 956 CD2 LEU A 133 0.353 62.091 7.701 1.00 93.47 C
ATOM 957 N THR A 134 -3.132 58.117 7.636 1.00 91.80 N
ATOM 958 CA THR A 134 -4.345 57.319 7.500 1.00 90.29 C
ATOM 959 C THR A 134 -4.710 56.484 8.733 1.00 88.61 C
ATOM 960 O THR A 134 -5.751 56.700 9.348 1.00 87.36 O
ATOM 961 CB THR A 134 -4.198 56.378 6.309 1.00 90.62 C
ATOM 962 OG1 THR A 134 -3.074 55.523 6.533 1.00 91.28 O
ATOM 963 CG2 THR A 134 -3.958 57.166 5.034 1.00 89.53 C
ATOM 964 N THR A 135 -3.847 55.533 9.077 1.00 87.08 N
ATOM 965 CA THR A 135 -4.072 54.647 10.216 1.00 87.00 C
ATOM 966 C THR A 135 -4.872 55.242 11.360 1.00 86.71 C
ATOM 967 O THR A 135 -4.628 56.368 11.774 1.00 86.97 O
ATOM 968 CB THR A 135 -2.758 54.158 10.829 1.00 86.89 C
ATOM 969 OG1 THR A 135 -1.822 55.239 10.867 1.00 85.36 O
ATOM 970 CG2 THR A 135 -2.193 52.990 10.039 1.00 87.48 C
ATOM 971 N SER A 136 -5.832 54.468 11.858 1.00 86.78 N
ATOM 972 CA SER A 136 -6.647 54.865 12.995 1.00 87.04 C
ATOM 973 C SER A 136 -5.993 54.146 14.152 1.00 88.13 C
ATOM 974 O SER A 136 -6.646 53.752 15.117 1.00 88.17 O
ATOM 975 CB SER A 136 -8.091 54.388 12.852 1.00 86.80 C
ATOM 976 OG SER A 136 -8.852 55.273 12.056 1.00 87.18 O
ATOM 977 N SER A 137 -4.685 53.956 14.018 1.00 89.21 N
ATOM 978 CA SER A 137 -3.887 53.287 15.033 1.00 91.19 C
ATOM 979 C SER A 137 -2.428 53.435 14.636 1.00 91.93 C
ATOM 980 O SER A 137 -2.101 53.474 13.448 1.00 90.67 O
ATOM 981 CB SER A 137 -4.264 51.807 15.110 1.00 92.06 C
ATOM 982 OG SER A 137 -4.001 51.158 13.867 1.00 93.47 O
ATOM 983 N GLY A 138 -1.558 53.524 15.636 1.00 93.57 N
ATOM 984 CA GLY A 138 -0.141 53.687 15.371 1.00 95.55 C
ATOM 985 C GLY A 138 0.554 52.360 15.168 1.00 96.50 C
ATOM 986 O GLY A 138 1.789 52.254 15.210 1.00 97.48 O
ATOM 987 N ASN A 139 -0.268 51.343 14.938 1.00 96.37 N
ATOM 988 CA ASN A 139 0.183 49.976 14.723 1.00 95.32 C
ATOM 989 C ASN A 139 0.837 49.866 13.345 1.00 94.83 C
ATOM 990 O ASN A 139 0.184 49.586 12.334 1.00 94.93 O
ATOM 991 CB ASN A 139 -1.026 49.053 14.835 1.00 95.07 C
ATOM 992 CG ASN A 139 -1.940 49.439 15.992 1.00 95.16 C
ATOM 993 OD1 ASN A 139 -2.119 50.625 16.297 1.00 96.11 O
ATOM 994 ND2 ASN A 139 -2.534 48.443 16.632 1.00 95.53 N
ATOM 995 N LEU A 140 2.139 50.098 13.318 1.00 93.89 N
ATOM 996 CA LEU A 140 2.893 50.044 12.082 1.00 94.05 C
ATOM 997 C LEU A 140 2.804 48.717 11.327 1.00 94.50 C
ATOM 998 O LEU A 140 3.292 48.621 10.198 1.00 94.62 O
ATOM 999 CB LEU A 140 4.355 50.390 12.361 1.00 93.18 C
ATOM 1000 CG LEU A 140 4.604 51.860 12.677 1.00 91.51 C
ATOM 1001 CD1 LEU A 140 5.785 51.977 13.604 1.00 91.57 C
ATOM 1002 CD2 LEU A 140 4.818 52.636 11.386 1.00 89.96 C
ATOM 1003 N HIS A 141 2.194 47.695 11.933 1.00 94.12 N
ATOM 1004 CA HIS A 141 2.063 46.408 11.245 1.00 93.21 C
ATOM 1005 C HIS A 141 1.018 46.568 10.147 1.00 93.53 C
ATOM 1006 O HIS A 141 0.728 45.629 9.403 1.00 93.63 O
ATOM 1007 CB HIS A 141 1.656 45.276 12.212 1.00 90.47 C
ATOM 1008 CG HIS A 141 0.212 45.299 12.629 1.00 88.47 C
ATOM 1009 ND1 HIS A 141 -0.345 44.306 13.404 1.00 86.91 N
ATOM 1010 CD2 HIS A 141 -0.782 46.186 12.379 1.00 87.52 C
ATOM 1011 CE1 HIS A 141 -1.623 44.579 13.614 1.00 86.12 C
ATOM 1012 NE2 HIS A 141 -1.913 45.713 13.003 1.00 85.96 N
ATOM 1013 N GLY A 142 0.452 47.771 10.069 1.00 93.98 N
ATOM 1014 CA GLY A 142 -0.557 48.070 9.069 1.00 95.37 C
ATOM 1015 C GLY A 142 -0.125 49.206 8.156 1.00 96.23 C
ATOM 1016 O GLY A 142 -0.963 49.945 7.631 1.00 95.98 O
ATOM 1017 N GLN A 143 1.191 49.327 7.974 1.00 96.91 N
ATOM 1018 CA GLN A 143 1.811 50.358 7.142 1.00 97.13 C
ATOM 1019 C GLN A 143 3.025 49.890 6.307 1.00 97.15 C
ATOM 1020 O GLN A 143 3.407 50.548 5.343 1.00 96.46 O
ATOM 1021 CB GLN A 143 2.230 51.526 8.036 1.00 97.37 C
ATOM 1022 CG GLN A 143 1.063 52.120 8.811 1.00 98.88 C
ATOM 1023 CD GLN A 143 1.478 53.200 9.796 1.00 99.70 C
ATOM 1024 OE1 GLN A 143 2.157 54.162 9.437 1.00 98.74 O
ATOM 1025 NE2 GLN A 143 1.054 53.048 11.047 1.00100.53 N
ATOM 1026 N PRO A 144 3.625 48.735 6.650 1.00 97.65 N
ATOM 1027 CA PRO A 144 4.790 48.193 5.943 1.00 97.32 C
ATOM 1028 C PRO A 144 4.994 48.534 4.473 1.00 96.74 C
ATOM 1029 O PRO A 144 6.123 48.758 4.041 1.00 96.95 O
ATOM 1030 CB PRO A 144 4.650 46.692 6.165 1.00 97.93 C
ATOM 1031 CG PRO A 144 4.144 46.639 7.556 1.00 98.75 C
ATOM 1032 CD PRO A 144 3.063 47.702 7.544 1.00 98.52 C
ATOM 1033 N VAL A 145 3.921 48.563 3.696 1.00 96.76 N
ATOM 1034 CA VAL A 145 4.065 48.860 2.273 1.00 96.67 C
ATOM 1035 C VAL A 145 4.311 50.351 2.045 1.00 95.18 C
ATOM 1036 O VAL A 145 5.050 50.740 1.134 1.00 94.04 O
ATOM 1037 CB VAL A 145 2.810 48.396 1.468 1.00 97.80 C
ATOM 1038 CG1 VAL A 145 3.019 48.650 -0.017 1.00 97.24 C
ATOM 1039 CG2 VAL A 145 2.546 46.908 1.707 1.00 97.02 C
ATOM 1040 N ALA A 146 3.695 51.173 2.890 1.00 94.06 N
ATOM 1041 CA ALA A 146 3.824 52.623 2.809 1.00 93.54 C
ATOM 1042 C ALA A 146 5.271 53.092 3.027 1.00 93.29 C
ATOM 1043 O ALA A 146 5.635 54.217 2.661 1.00 93.69 O
ATOM 1044 CB ALA A 146 2.891 53.281 3.829 1.00 92.75 C
ATOM 1045 N PHE A 147 6.090 52.232 3.624 1.00 91.80 N
ATOM 1046 CA PHE A 147 7.489 52.559 3.868 1.00 89.97 C
ATOM 1047 C PHE A 147 8.362 52.054 2.742 1.00 88.94 C
ATOM 1048 O PHE A 147 9.413 52.620 2.452 1.00 88.67 O
ATOM 1049 CB PHE A 147 7.965 51.932 5.169 1.00 90.00 C
ATOM 1050 CG PHE A 147 7.492 52.648 6.376 1.00 90.95 C
ATOM 1051 CD1 PHE A 147 6.164 52.572 6.766 1.00 91.17 C
ATOM 1052 CD2 PHE A 147 8.367 53.446 7.104 1.00 91.91 C
ATOM 1053 CE1 PHE A 147 5.706 53.284 7.872 1.00 92.42 C
ATOM 1054 CE2 PHE A 147 7.926 54.164 8.209 1.00 92.68 C
ATOM 1055 CZ PHE A 147 6.590 54.085 8.596 1.00 92.65 C
ATOM 1056 N LEU A 148 7.912 50.980 2.110 1.00 88.06 N
ATOM 1057 CA LEU A 148 8.653 50.362 1.031 1.00 87.82 C
ATOM 1058 C LEU A 148 8.317 50.979 -0.318 1.00 89.07 C
ATOM 1059 O LEU A 148 9.104 50.915 -1.266 1.00 88.06 O
ATOM 1060 CB LEU A 148 8.359 48.865 1.034 1.00 85.29 C
ATOM 1061 CG LEU A 148 8.597 48.243 2.410 1.00 82.72 C
ATOM 1062 CD1 LEU A 148 8.166 46.797 2.422 1.00 81.84 C
ATOM 1063 CD2 LEU A 148 10.062 48.368 2.754 1.00 82.23 C
ATOM 1064 N LEU A 149 7.142 51.587 -0.397 1.00 91.44 N
ATOM 1065 CA LEU A 149 6.710 52.211 -1.635 1.00 94.48 C
ATOM 1066 C LEU A 149 7.375 53.555 -1.883 1.00 96.57 C
ATOM 1067 O LEU A 149 7.557 54.362 -0.962 1.00 96.50 O
ATOM 1068 CB LEU A 149 5.191 52.402 -1.644 1.00 93.94 C
ATOM 1069 CG LEU A 149 4.316 51.275 -2.184 1.00 93.30 C
ATOM 1070 CD1 LEU A 149 2.880 51.756 -2.177 1.00 92.84 C
ATOM 1071 CD2 LEU A 149 4.740 50.889 -3.606 1.00 93.57 C
ATOM 1072 N LYS A 150 7.725 53.782 -3.146 1.00 98.82 N
ATOM 1073 CA LYS A 150 8.348 55.028 -3.573 1.00100.82 C
ATOM 1074 C LYS A 150 7.237 56.063 -3.792 1.00101.32 C
ATOM 1075 O LYS A 150 7.333 57.201 -3.325 1.00101.72 O
ATOM 1076 CB LYS A 150 9.128 54.806 -4.876 1.00101.79 C
ATOM 1077 CG LYS A 150 10.171 53.691 -4.801 1.00102.99 C
ATOM 1078 CD LYS A 150 10.869 53.472 -6.144 1.00103.99 C
ATOM 1079 CE LYS A 150 11.922 52.363 -6.049 1.00104.51 C
ATOM 1080 NZ LYS A 150 12.661 52.130 -7.331 1.00104.60 N
ATOM 1081 N GLU A 151 6.178 55.651 -4.488 1.00101.60 N
ATOM 1082 CA GLU A 151 5.044 56.523 -4.775 1.00102.29 C
ATOM 1083 C GLU A 151 4.399 57.045 -3.504 1.00102.54 C
ATOM 1084 O GLU A 151 3.419 57.787 -3.554 1.00102.16 O
ATOM 1085 CB GLU A 151 3.987 55.780 -5.590 1.00102.95 C
ATOM 1086 CG GLU A 151 4.448 55.312 -6.956 1.00104.96 C
ATOM 1087 CD GLU A 151 5.045 53.920 -6.934 1.00106.23 C
ATOM 1088 OE1 GLU A 151 6.035 53.701 -6.206 1.00107.34 O
ATOM 1089 OE2 GLU A 151 4.521 53.043 -7.653 1.00107.33 O
ATOM 1090 N LEU A 152 4.951 56.656 -2.365 1.00102.97 N
ATOM 1091 CA LEU A 152 4.411 57.085 -1.092 1.00104.39 C
ATOM 1092 C LEU A 152 5.438 57.865 -0.290 1.00105.77 C
ATOM 1093 O LEU A 152 5.131 58.404 0.777 1.00105.76 O
ATOM 1094 CB LEU A 152 3.943 55.867 -0.303 1.00104.29 C
ATOM 1095 CG LEU A 152 2.452 55.801 0.033 1.00104.15 C
ATOM 1096 CD1 LEU A 152 1.607 56.346 -1.103 1.00103.71 C
ATOM 1097 CD2 LEU A 152 2.100 54.358 0.323 1.00104.71 C
ATOM 1098 N LYS A 153 6.661 57.921 -0.809 1.00107.04 N
ATOM 1099 CA LYS A 153 7.735 58.642 -0.139 1.00107.67 C
ATOM 1100 C LYS A 153 7.369 60.121 -0.057 1.00107.92 C
ATOM 1101 O LYS A 153 6.763 60.678 -0.980 1.00108.76 O
ATOM 1102 CB LYS A 153 9.052 58.465 -0.902 1.00107.80 C
ATOM 1103 CG LYS A 153 10.260 59.095 -0.221 1.00108.64 C
ATOM 1104 CD LYS A 153 11.552 58.800 -0.980 1.00109.46 C
ATOM 1105 CE LYS A 153 12.752 59.546 -0.386 1.00110.70 C
ATOM 1106 NZ LYS A 153 13.062 59.158 1.028 1.00111.92 N
ATOM 1107 N GLY A 154 7.727 60.747 1.059 1.00107.54 N
ATOM 1108 CA GLY A 154 7.425 62.151 1.240 1.00107.33 C
ATOM 1109 C GLY A 154 5.937 62.414 1.149 1.00107.30 C
ATOM 1110 O GLY A 154 5.514 63.533 0.860 1.00108.46 O
ATOM 1111 N LYS A 155 5.140 61.376 1.377 1.00106.64 N
ATOM 1112 CA LYS A 155 3.690 61.508 1.344 1.00105.81 C
ATOM 1113 C LYS A 155 3.193 61.505 2.789 1.00105.92 C
ATOM 1114 O LYS A 155 1.988 61.497 3.054 1.00105.68 O
ATOM 1115 CB LYS A 155 3.070 60.355 0.551 1.00104.96 C
ATOM 1116 CG LYS A 155 3.441 60.354 -0.921 1.00103.47 C
ATOM 1117 CD LYS A 155 2.896 61.590 -1.612 1.00104.34 C
ATOM 1118 CE LYS A 155 3.337 61.663 -3.069 1.00104.97 C
ATOM 1119 NZ LYS A 155 2.769 62.855 -3.775 1.00103.63 N
ATOM 1120 N PHE A 156 4.152 61.515 3.713 1.00106.22 N
ATOM 1121 CA PHE A 156 3.886 61.528 5.149 1.00106.40 C
ATOM 1122 C PHE A 156 5.148 61.912 5.943 1.00106.38 C
ATOM 1123 O PHE A 156 6.276 61.702 5.481 1.00105.46 O
ATOM 1124 CB PHE A 156 3.342 60.161 5.615 1.00107.04 C
ATOM 1125 CG PHE A 156 4.223 58.980 5.263 1.00107.71 C
ATOM 1126 CD1 PHE A 156 4.511 58.667 3.930 1.00107.58 C
ATOM 1127 CD2 PHE A 156 4.748 58.168 6.269 1.00106.90 C
ATOM 1128 CE1 PHE A 156 5.304 57.565 3.608 1.00106.82 C
ATOM 1129 CE2 PHE A 156 5.537 57.067 5.960 1.00106.77 C
ATOM 1130 CZ PHE A 156 5.818 56.764 4.625 1.00107.12 C
ATOM 1131 N PRO A 157 4.967 62.492 7.147 1.00106.61 N
ATOM 1132 CA PRO A 157 6.081 62.912 8.008 1.00106.37 C
ATOM 1133 C PRO A 157 7.055 61.801 8.371 1.00106.46 C
ATOM 1134 O PRO A 157 6.682 60.823 9.020 1.00106.53 O
ATOM 1135 CB PRO A 157 5.373 63.485 9.237 1.00106.35 C
ATOM 1136 CG PRO A 157 4.089 62.704 9.290 1.00106.43 C
ATOM 1137 CD PRO A 157 3.678 62.699 7.835 1.00106.79 C
ATOM 1138 N ASP A 158 8.306 61.966 7.949 1.00106.90 N
ATOM 1139 CA ASP A 158 9.351 60.987 8.231 1.00106.90 C
ATOM 1140 C ASP A 158 9.153 60.469 9.652 1.00107.41 C
ATOM 1141 O ASP A 158 8.930 61.241 10.592 1.00107.55 O
ATOM 1142 CB ASP A 158 10.728 61.632 8.063 1.00104.94 C
ATOM 1143 CG ASP A 158 10.847 62.391 6.757 1.00104.15 C
ATOM 1144 OD1 ASP A 158 10.567 61.794 5.692 1.00103.27 O
ATOM 1145 OD2 ASP A 158 11.210 63.585 6.789 1.00103.26 O
ATOM 1146 N VAL A 159 9.222 59.154 9.804 1.00107.49 N
ATOM 1147 CA VAL A 159 8.997 58.547 11.102 1.00107.43 C
ATOM 1148 C VAL A 159 10.257 58.215 11.896 1.00105.92 C
ATOM 1149 O VAL A 159 11.246 57.713 11.349 1.00105.41 O
ATOM 1150 CB VAL A 159 8.126 57.274 10.952 1.00108.72 C
ATOM 1151 CG1 VAL A 159 7.778 56.703 12.326 1.00109.55 C
ATOM 1152 CG2 VAL A 159 6.855 57.610 10.170 1.00109.32 C
ATOM 1153 N PRO A 160 10.224 58.507 13.209 1.00104.72 N
ATOM 1154 CA PRO A 160 11.282 58.294 14.198 1.00104.41 C
ATOM 1155 C PRO A 160 11.765 56.853 14.321 1.00103.98 C
ATOM 1156 O PRO A 160 11.224 56.076 15.111 1.00103.74 O
ATOM 1157 CB PRO A 160 10.643 58.789 15.490 1.00103.93 C
ATOM 1158 CG PRO A 160 9.783 59.892 15.014 1.00103.63 C
ATOM 1159 CD PRO A 160 9.125 59.287 13.805 1.00104.02 C
ATOM 1160 N GLY A 161 12.789 56.512 13.542 1.00103.53 N
ATOM 1161 CA GLY A 161 13.352 55.177 13.594 1.00103.26 C
ATOM 1162 C GLY A 161 13.464 54.493 12.249 1.00103.11 C
ATOM 1163 O GLY A 161 14.166 53.489 12.114 1.00102.78 O
ATOM 1164 N PHE A 162 12.795 55.046 11.244 1.00102.76 N
ATOM 1165 CA PHE A 162 12.803 54.445 9.919 1.00102.25 C
ATOM 1166 C PHE A 162 13.581 55.262 8.904 1.00101.97 C
ATOM 1167 O PHE A 162 13.363 55.150 7.700 1.00101.94 O
ATOM 1168 CB PHE A 162 11.362 54.247 9.459 1.00101.45 C
ATOM 1169 CG PHE A 162 10.484 53.644 10.514 1.00101.08 C
ATOM 1170 CD1 PHE A 162 10.144 54.372 11.653 1.00100.76 C
ATOM 1171 CD2 PHE A 162 10.036 52.334 10.399 1.00101.58 C
ATOM 1172 CE1 PHE A 162 9.378 53.806 12.663 1.00100.12 C
ATOM 1173 CE2 PHE A 162 9.267 51.756 11.408 1.00101.83 C
ATOM 1174 CZ PHE A 162 8.939 52.497 12.543 1.00101.45 C
ATOM 1175 N SER A 163 14.494 56.084 9.403 1.00102.29 N
ATOM 1176 CA SER A 163 15.325 56.918 8.545 1.00102.63 C
ATOM 1177 C SER A 163 16.013 56.038 7.495 1.00102.57 C
ATOM 1178 O SER A 163 15.851 56.247 6.290 1.00102.59 O
ATOM 1179 CB SER A 163 16.367 57.644 9.397 1.00102.37 C
ATOM 1180 OG SER A 163 15.741 58.319 10.479 1.00101.02 O
ATOM 1181 N TRP A 164 16.761 55.047 7.979 1.00102.49 N
ATOM 1182 CA TRP A 164 17.503 54.075 7.160 1.00101.47 C
ATOM 1183 C TRP A 164 16.656 53.402 6.074 1.00 99.77 C
ATOM 1184 O TRP A 164 17.186 52.783 5.149 1.00 98.35 O
ATOM 1185 CB TRP A 164 18.070 52.988 8.072 1.00103.47 C
ATOM 1186 CG TRP A 164 16.996 52.353 8.921 1.00106.13 C
ATOM 1187 CD1 TRP A 164 16.552 52.772 10.150 1.00106.71 C
ATOM 1188 CD2 TRP A 164 16.174 51.236 8.556 1.00106.44 C
ATOM 1189 NE1 TRP A 164 15.506 51.979 10.569 1.00106.48 N
ATOM 1190 CE2 TRP A 164 15.261 51.033 9.622 1.00106.26 C
ATOM 1191 CE3 TRP A 164 16.134 50.386 7.447 1.00106.62 C
ATOM 1192 CZ2 TRP A 164 14.305 50.016 9.584 1.00106.64 C
ATOM 1193 CZ3 TRP A 164 15.184 49.378 7.417 1.00106.79 C
ATOM 1194 CH2 TRP A 164 14.287 49.197 8.486 1.00107.31 C
ATOM 1195 N VAL A 165 15.339 53.510 6.208 1.00 98.45 N
ATOM 1196 CA VAL A 165 14.422 52.917 5.251 1.00 97.02 C
ATOM 1197 C VAL A 165 14.417 53.689 3.940 1.00 96.57 C
ATOM 1198 O VAL A 165 14.342 54.917 3.926 1.00 95.58 O
ATOM 1199 CB VAL A 165 12.998 52.882 5.808 1.00 96.60 C
ATOM 1200 CG1 VAL A 165 12.066 52.232 4.806 1.00 96.25 C
ATOM 1201 CG2 VAL A 165 12.987 52.136 7.127 1.00 95.83 C
ATOM 1202 N THR A 166 14.485 52.950 2.838 1.00 96.74 N
ATOM 1203 CA THR A 166 14.498 53.543 1.508 1.00 96.80 C
ATOM 1204 C THR A 166 13.397 52.949 0.632 1.00 96.74 C
ATOM 1205 O THR A 166 13.451 51.771 0.273 1.00 96.41 O
ATOM 1206 CB THR A 166 15.846 53.288 0.803 1.00 96.99 C
ATOM 1207 OG1 THR A 166 16.918 53.566 1.710 1.00 97.70 O
ATOM 1208 CG2 THR A 166 15.985 54.176 -0.436 1.00 96.21 C
ATOM 1209 N PRO A 167 12.378 53.757 0.288 1.00 96.68 N
ATOM 1210 CA PRO A 167 11.284 53.266 -0.558 1.00 97.04 C
ATOM 1211 C PRO A 167 11.915 52.513 -1.724 1.00 97.98 C
ATOM 1212 O PRO A 167 12.517 53.123 -2.606 1.00 98.54 O
ATOM 1213 CB PRO A 167 10.596 54.552 -0.983 1.00 96.70 C
ATOM 1214 CG PRO A 167 10.740 55.410 0.259 1.00 96.21 C
ATOM 1215 CD PRO A 167 12.175 55.170 0.661 1.00 95.91 C
ATOM 1216 N CYS A 168 11.774 51.189 -1.719 1.00 99.21 N
ATOM 1217 CA CYS A 168 12.392 50.335 -2.736 1.00100.39 C
ATOM 1218 C CYS A 168 11.594 49.807 -3.935 1.00100.22 C
ATOM 1219 O CYS A 168 12.197 49.377 -4.916 1.00100.36 O
ATOM 1220 CB CYS A 168 13.074 49.150 -2.039 1.00101.41 C
ATOM 1221 SG CYS A 168 12.045 48.309 -0.814 1.00102.86 S
ATOM 1222 N ILE A 169 10.266 49.802 -3.879 1.00100.14 N
ATOM 1223 CA ILE A 169 9.507 49.311 -5.033 1.00 99.43 C
ATOM 1224 C ILE A 169 8.256 50.124 -5.324 1.00100.06 C
ATOM 1225 O ILE A 169 7.630 50.689 -4.423 1.00 99.94 O
ATOM 1226 CB ILE A 169 9.094 47.819 -4.886 1.00 97.80 C
ATOM 1227 CG1 ILE A 169 8.135 47.643 -3.706 1.00 97.02 C
ATOM 1228 CG2 ILE A 169 10.326 46.950 -4.727 1.00 97.30 C
ATOM 1229 CD1 ILE A 169 8.689 48.068 -2.363 1.00 96.20 C
ATOM 1230 N SER A 170 7.911 50.194 -6.603 1.00100.49 N
ATOM 1231 CA SER A 170 6.731 50.922 -7.033 1.00101.32 C
ATOM 1232 C SER A 170 5.529 49.970 -7.023 1.00101.91 C
ATOM 1233 O SER A 170 5.684 48.768 -6.782 1.00102.46 O
ATOM 1234 CB SER A 170 6.969 51.513 -8.428 1.00100.78 C
ATOM 1235 OG SER A 170 7.596 50.585 -9.289 1.00100.26 O
ATOM 1236 N ALA A 171 4.336 50.503 -7.274 1.00101.63 N
ATOM 1237 CA ALA A 171 3.120 49.692 -7.275 1.00101.52 C
ATOM 1238 C ALA A 171 3.060 48.733 -8.465 1.00101.47 C
ATOM 1239 O ALA A 171 2.149 47.907 -8.577 1.00101.00 O
ATOM 1240 CB ALA A 171 1.899 50.604 -7.273 1.00101.29 C
ATOM 1241 N LYS A 172 4.045 48.841 -9.345 1.00101.77 N
ATOM 1242 CA LYS A 172 4.097 47.997 -10.524 1.00102.19 C
ATOM 1243 C LYS A 172 4.808 46.675 -10.265 1.00100.80 C
ATOM 1244 O LYS A 172 4.860 45.807 -11.139 1.00100.93 O
ATOM 1245 CB LYS A 172 4.782 48.760 -11.665 1.00104.75 C
ATOM 1246 CG LYS A 172 3.806 49.323 -12.708 1.00107.35 C
ATOM 1247 CD LYS A 172 2.609 50.052 -12.073 1.00107.90 C
ATOM 1248 CE LYS A 172 1.503 50.295 -13.105 1.00108.26 C
ATOM 1249 NZ LYS A 172 0.237 50.819 -12.513 1.00107.62 N
ATOM 1250 N ASP A 173 5.342 46.518 -9.058 1.00 98.57 N
ATOM 1251 CA ASP A 173 6.053 45.296 -8.709 1.00 95.87 C
ATOM 1252 C ASP A 173 5.427 44.539 -7.534 1.00 92.84 C
ATOM 1253 O ASP A 173 5.845 43.421 -7.219 1.00 92.74 O
ATOM 1254 CB ASP A 173 7.522 45.612 -8.392 1.00 97.37 C
ATOM 1255 CG ASP A 173 8.215 46.378 -9.511 1.00 97.26 C
ATOM 1256 OD1 ASP A 173 8.154 45.935 -10.681 1.00 95.86 O
ATOM 1257 OD2 ASP A 173 8.828 47.426 -9.208 1.00 98.11 O
ATOM 1258 N ILE A 174 4.428 45.149 -6.895 1.00 89.13 N
ATOM 1259 CA ILE A 174 3.728 44.540 -5.757 1.00 83.93 C
ATOM 1260 C ILE A 174 2.394 43.916 -6.166 1.00 80.70 C
ATOM 1261 O ILE A 174 1.697 44.451 -7.019 1.00 80.98 O
ATOM 1262 CB ILE A 174 3.431 45.585 -4.651 1.00 82.90 C
ATOM 1263 CG1 ILE A 174 2.612 44.946 -3.535 1.00 81.94 C
ATOM 1264 CG2 ILE A 174 2.650 46.744 -5.218 1.00 82.20 C
ATOM 1265 CD1 ILE A 174 3.299 43.772 -2.898 1.00 82.59 C
ATOM 1266 N VAL A 175 2.049 42.779 -5.565 1.00 77.49 N
ATOM 1267 CA VAL A 175 0.775 42.106 -5.848 1.00 74.17 C
ATOM 1268 C VAL A 175 0.166 41.524 -4.562 1.00 71.60 C
ATOM 1269 O VAL A 175 0.789 40.719 -3.862 1.00 70.28 O
ATOM 1270 CB VAL A 175 0.926 40.972 -6.916 1.00 73.83 C
ATOM 1271 CG1 VAL A 175 -0.418 40.295 -7.158 1.00 72.13 C
ATOM 1272 CG2 VAL A 175 1.439 41.549 -8.215 1.00 71.71 C
ATOM 1273 N TYR A 176 -1.059 41.955 -4.270 1.00 68.81 N
ATOM 1274 CA TYR A 176 -1.805 41.530 -3.090 1.00 65.95 C
ATOM 1275 C TYR A 176 -2.750 40.394 -3.411 1.00 66.00 C
ATOM 1276 O TYR A 176 -3.431 40.435 -4.435 1.00 66.47 O
ATOM 1277 CB TYR A 176 -2.655 42.676 -2.583 1.00 63.07 C
ATOM 1278 CG TYR A 176 -1.935 43.714 -1.775 1.00 62.07 C
ATOM 1279 CD1 TYR A 176 -1.578 43.465 -0.461 1.00 61.02 C
ATOM 1280 CD2 TYR A 176 -1.750 45.001 -2.273 1.00 62.56 C
ATOM 1281 CE1 TYR A 176 -1.074 44.479 0.355 1.00 60.83 C
ATOM 1282 CE2 TYR A 176 -1.247 46.026 -1.465 1.00 62.19 C
ATOM 1283 CZ TYR A 176 -0.919 45.757 -0.145 1.00 61.80 C
ATOM 1284 OH TYR A 176 -0.503 46.774 0.689 1.00 61.14 O
ATOM 1285 N ILE A 177 -2.796 39.383 -2.547 1.00 66.80 N
ATOM 1286 CA ILE A 177 -3.723 38.263 -2.745 1.00 67.11 C
ATOM 1287 C ILE A 177 -4.374 37.942 -1.391 1.00 68.56 C
ATOM 1288 O ILE A 177 -3.677 37.766 -0.378 1.00 69.41 O
ATOM 1289 CB ILE A 177 -3.027 36.961 -3.285 1.00 65.54 C
ATOM 1290 CG1 ILE A 177 -1.803 37.302 -4.140 1.00 65.06 C
ATOM 1291 CG2 ILE A 177 -4.002 36.172 -4.153 1.00 61.44 C
ATOM 1292 CD1 ILE A 177 -1.131 36.090 -4.755 1.00 62.70 C
ATOM 1293 N GLY A 178 -5.709 37.906 -1.374 1.00 68.46 N
ATOM 1294 CA GLY A 178 -6.437 37.587 -0.158 1.00 68.24 C
ATOM 1295 C GLY A 178 -7.071 38.757 0.576 1.00 68.59 C
ATOM 1296 O GLY A 178 -7.617 38.570 1.675 1.00 68.65 O
ATOM 1297 N LEU A 179 -7.024 39.950 -0.019 1.00 67.99 N
ATOM 1298 CA LEU A 179 -7.595 41.145 0.615 1.00 65.97 C
ATOM 1299 C LEU A 179 -9.106 41.016 0.846 1.00 64.84 C
ATOM 1300 O LEU A 179 -9.873 40.646 -0.043 1.00 62.84 O
ATOM 1301 CB LEU A 179 -7.281 42.397 -0.222 1.00 63.88 C
ATOM 1302 CG LEU A 179 -5.791 42.594 -0.553 1.00 61.65 C
ATOM 1303 CD1 LEU A 179 -5.604 43.843 -1.400 1.00 60.43 C
ATOM 1304 CD2 LEU A 179 -4.984 42.673 0.731 1.00 58.38 C
ATOM 1305 N ARG A 180 -9.524 41.323 2.065 1.00 64.18 N
ATOM 1306 CA ARG A 180 -10.921 41.216 2.409 1.00 63.57 C
ATOM 1307 C ARG A 180 -11.282 42.163 3.546 1.00 65.71 C
ATOM 1308 O ARG A 180 -12.437 42.243 3.945 1.00 67.12 O
ATOM 1309 CB ARG A 180 -11.242 39.767 2.782 1.00 60.48 C
ATOM 1310 CG ARG A 180 -11.048 39.448 4.247 1.00 58.48 C
ATOM 1311 CD ARG A 180 -11.227 37.978 4.543 1.00 55.45 C
ATOM 1312 NE ARG A 180 -10.080 37.260 4.032 1.00 58.34 N
ATOM 1313 CZ ARG A 180 -9.295 36.469 4.754 1.00 60.04 C
ATOM 1314 NH1 ARG A 180 -9.534 36.271 6.046 1.00 58.90 N
ATOM 1315 NH2 ARG A 180 -8.237 35.902 4.179 1.00 60.12 N
ATOM 1316 N ASP A 181 -10.298 42.876 4.075 1.00 68.57 N
ATOM 1317 CA ASP A 181 -10.562 43.844 5.141 1.00 72.38 C
ATOM 1318 C ASP A 181 -9.692 45.095 4.939 1.00 73.65 C
ATOM 1319 O ASP A 181 -8.701 45.331 5.650 1.00 72.86 O
ATOM 1320 CB ASP A 181 -10.312 43.209 6.516 1.00 74.74 C
ATOM 1321 CG ASP A 181 -10.261 44.242 7.637 1.00 76.50 C
ATOM 1322 OD1 ASP A 181 -10.962 45.273 7.524 1.00 76.76 O
ATOM 1323 OD2 ASP A 181 -9.526 44.012 8.628 1.00 77.76 O
ATOM 1324 N VAL A 182 -10.082 45.905 3.960 1.00 75.62 N
ATOM 1325 CA VAL A 182 -9.323 47.104 3.636 1.00 77.84 C
ATOM 1326 C VAL A 182 -9.941 48.416 4.069 1.00 78.44 C
ATOM 1327 O VAL A 182 -11.098 48.689 3.755 1.00 79.02 O
ATOM 1328 CB VAL A 182 -9.038 47.173 2.125 1.00 78.31 C
ATOM 1329 CG1 VAL A 182 -8.948 48.621 1.662 1.00 79.03 C
ATOM 1330 CG2 VAL A 182 -7.730 46.458 1.826 1.00 79.08 C
ATOM 1331 N ASP A 183 -9.138 49.229 4.763 1.00 79.14 N
ATOM 1332 CA ASP A 183 -9.550 50.543 5.256 1.00 78.94 C
ATOM 1333 C ASP A 183 -9.732 51.569 4.143 1.00 79.30 C
ATOM 1334 O ASP A 183 -9.102 51.476 3.086 1.00 79.36 O
ATOM 1335 CB ASP A 183 -8.535 51.077 6.266 1.00 78.05 C
ATOM 1336 CG ASP A 183 -8.649 50.399 7.612 1.00 79.06 C
ATOM 1337 OD1 ASP A 183 -9.726 50.506 8.236 1.00 78.74 O
ATOM 1338 OD2 ASP A 183 -7.668 49.757 8.049 1.00 80.08 O
ATOM 1339 N PRO A 184 -10.600 52.569 4.375 1.00 79.74 N
ATOM 1340 CA PRO A 184 -10.875 53.625 3.395 1.00 80.29 C
ATOM 1341 C PRO A 184 -9.567 54.111 2.773 1.00 81.42 C
ATOM 1342 O PRO A 184 -9.262 53.803 1.617 1.00 81.63 O
ATOM 1343 CB PRO A 184 -11.543 54.708 4.237 1.00 78.84 C
ATOM 1344 CG PRO A 184 -12.233 53.934 5.285 1.00 78.62 C
ATOM 1345 CD PRO A 184 -11.208 52.900 5.674 1.00 78.97 C
ATOM 1346 N GLY A 185 -8.800 54.859 3.566 1.00 81.81 N
ATOM 1347 CA GLY A 185 -7.530 55.393 3.115 1.00 82.31 C
ATOM 1348 C GLY A 185 -6.772 54.417 2.249 1.00 82.89 C
ATOM 1349 O GLY A 185 -6.291 54.770 1.175 1.00 82.84 O
ATOM 1350 N GLU A 186 -6.668 53.180 2.716 1.00 83.40 N
ATOM 1351 CA GLU A 186 -5.970 52.157 1.963 1.00 84.01 C
ATOM 1352 C GLU A 186 -6.583 51.938 0.577 1.00 85.43 C
ATOM 1353 O GLU A 186 -5.851 51.826 -0.412 1.00 85.30 O
ATOM 1354 CB GLU A 186 -5.946 50.852 2.760 1.00 82.52 C
ATOM 1355 CG GLU A 186 -4.753 50.735 3.683 1.00 80.01 C
ATOM 1356 CD GLU A 186 -4.936 49.662 4.723 1.00 80.52 C
ATOM 1357 OE1 GLU A 186 -5.894 49.797 5.507 1.00 82.23 O
ATOM 1358 OE2 GLU A 186 -4.137 48.697 4.765 1.00 79.04 O
ATOM 1359 N HIS A 187 -7.914 51.889 0.493 1.00 87.43 N
ATOM 1360 CA HIS A 187 -8.569 51.681 -0.799 1.00 89.34 C
ATOM 1361 C HIS A 187 -8.171 52.807 -1.743 1.00 91.26 C
ATOM 1362 O HIS A 187 -7.855 52.580 -2.916 1.00 91.25 O
ATOM 1363 CB HIS A 187 -10.094 51.647 -0.658 1.00 88.09 C
ATOM 1364 CG HIS A 187 -10.794 51.084 -1.862 1.00 87.99 C
ATOM 1365 ND1 HIS A 187 -12.162 51.021 -1.972 1.00 88.58 N
ATOM 1366 CD2 HIS A 187 -10.298 50.526 -2.993 1.00 87.65 C
ATOM 1367 CE1 HIS A 187 -12.486 50.445 -3.121 1.00 87.86 C
ATOM 1368 NE2 HIS A 187 -11.374 50.136 -3.756 1.00 86.86 N
ATOM 1369 N TYR A 188 -8.195 54.024 -1.210 1.00 93.24 N
ATOM 1370 CA TYR A 188 -7.825 55.219 -1.958 1.00 94.52 C
ATOM 1371 C TYR A 188 -6.466 54.951 -2.594 1.00 93.43 C
ATOM 1372 O TYR A 188 -6.332 54.876 -3.814 1.00 93.13 O
ATOM 1373 CB TYR A 188 -7.722 56.402 -0.992 1.00 97.75 C
ATOM 1374 CG TYR A 188 -7.504 57.742 -1.651 1.00101.26 C
ATOM 1375 CD1 TYR A 188 -8.513 58.337 -2.400 1.00102.84 C
ATOM 1376 CD2 TYR A 188 -6.291 58.417 -1.518 1.00103.00 C
ATOM 1377 CE1 TYR A 188 -8.326 59.570 -3.003 1.00105.63 C
ATOM 1378 CE2 TYR A 188 -6.089 59.656 -2.118 1.00105.61 C
ATOM 1379 CZ TYR A 188 -7.112 60.227 -2.861 1.00106.52 C
ATOM 1380 OH TYR A 188 -6.934 61.449 -3.473 1.00107.84 O
ATOM 1381 N ILE A 189 -5.474 54.790 -1.728 1.00 91.82 N
ATOM 1382 CA ILE A 189 -4.102 54.532 -2.112 1.00 89.96 C
ATOM 1383 C ILE A 189 -3.932 53.468 -3.194 1.00 89.45 C
ATOM 1384 O ILE A 189 -3.338 53.744 -4.231 1.00 90.11 O
ATOM 1385 CB ILE A 189 -3.284 54.129 -0.879 1.00 89.42 C
ATOM 1386 CG1 ILE A 189 -3.574 55.113 0.256 1.00 89.61 C
ATOM 1387 CG2 ILE A 189 -1.808 54.133 -1.210 1.00 88.40 C
ATOM 1388 CD1 ILE A 189 -2.982 54.739 1.613 1.00 90.14 C
ATOM 1389 N ILE A 190 -4.448 52.260 -2.976 1.00 88.36 N
ATOM 1390 CA ILE A 190 -4.299 51.199 -3.978 1.00 87.98 C
ATOM 1391 C ILE A 190 -4.921 51.518 -5.338 1.00 87.97 C
ATOM 1392 O ILE A 190 -4.393 51.115 -6.377 1.00 87.59 O
ATOM 1393 CB ILE A 190 -4.886 49.852 -3.495 1.00 87.07 C
ATOM 1394 CG1 ILE A 190 -6.258 50.080 -2.869 1.00 86.15 C
ATOM 1395 CG2 ILE A 190 -3.929 49.181 -2.528 1.00 86.59 C
ATOM 1396 CD1 ILE A 190 -6.891 48.815 -2.363 1.00 85.40 C
ATOM 1397 N LYS A 191 -6.046 52.225 -5.331 1.00 88.65 N
ATOM 1398 CA LYS A 191 -6.717 52.595 -6.575 1.00 88.53 C
ATOM 1399 C LYS A 191 -5.889 53.672 -7.267 1.00 88.10 C
ATOM 1400 O LYS A 191 -5.494 53.532 -8.429 1.00 88.34 O
ATOM 1401 CB LYS A 191 -8.110 53.149 -6.280 1.00 88.47 C
ATOM 1402 CG LYS A 191 -8.988 52.221 -5.477 1.00 88.98 C
ATOM 1403 CD LYS A 191 -9.185 50.891 -6.187 1.00 90.42 C
ATOM 1404 CE LYS A 191 -9.988 51.044 -7.473 1.00 91.22 C
ATOM 1405 NZ LYS A 191 -10.220 49.740 -8.165 1.00 91.30 N
ATOM 1406 N THR A 192 -5.636 54.745 -6.519 1.00 87.39 N
ATOM 1407 CA THR A 192 -4.868 55.890 -6.984 1.00 86.37 C
ATOM 1408 C THR A 192 -3.532 55.479 -7.562 1.00 85.11 C
ATOM 1409 O THR A 192 -3.254 55.733 -8.730 1.00 85.30 O
ATOM 1410 CB THR A 192 -4.598 56.877 -5.836 1.00 86.84 C
ATOM 1411 OG1 THR A 192 -5.818 57.538 -5.471 1.00 87.24 O
ATOM 1412 CG2 THR A 192 -3.562 57.910 -6.259 1.00 87.53 C
ATOM 1413 N LEU A 193 -2.708 54.854 -6.731 1.00 83.59 N
ATOM 1414 CA LEU A 193 -1.389 54.415 -7.147 1.00 81.81 C
ATOM 1415 C LEU A 193 -1.444 53.211 -8.054 1.00 81.47 C
ATOM 1416 O LEU A 193 -0.412 52.626 -8.362 1.00 82.12 O
ATOM 1417 CB LEU A 193 -0.532 54.075 -5.936 1.00 81.24 C
ATOM 1418 CG LEU A 193 -0.121 55.238 -5.039 1.00 80.57 C
ATOM 1419 CD1 LEU A 193 -1.349 55.886 -4.409 1.00 80.60 C
ATOM 1420 CD2 LEU A 193 0.820 54.710 -3.971 1.00 80.83 C
ATOM 1421 N GLY A 194 -2.642 52.836 -8.480 1.00 80.95 N
ATOM 1422 CA GLY A 194 -2.771 51.690 -9.360 1.00 80.89 C
ATOM 1423 C GLY A 194 -1.932 50.498 -8.924 1.00 80.68 C
ATOM 1424 O GLY A 194 -0.863 50.246 -9.475 1.00 79.93 O
ATOM 1425 N ILE A 195 -2.427 49.767 -7.930 1.00 81.64 N
ATOM 1426 CA ILE A 195 -1.751 48.590 -7.395 1.00 81.78 C
ATOM 1427 C ILE A 195 -2.522 47.339 -7.791 1.00 82.29 C
ATOM 1428 O ILE A 195 -3.706 47.219 -7.461 1.00 82.81 O
ATOM 1429 CB ILE A 195 -1.695 48.647 -5.861 1.00 81.34 C
ATOM 1430 CG1 ILE A 195 -0.708 49.722 -5.426 1.00 81.48 C
ATOM 1431 CG2 ILE A 195 -1.339 47.282 -5.301 1.00 81.33 C
ATOM 1432 CD1 ILE A 195 -0.732 50.003 -3.942 1.00 82.56 C
ATOM 1433 N LYS A 196 -1.860 46.417 -8.490 1.00 82.10 N
ATOM 1434 CA LYS A 196 -2.514 45.176 -8.909 1.00 82.86 C
ATOM 1435 C LYS A 196 -2.798 44.312 -7.678 1.00 83.44 C
ATOM 1436 O LYS A 196 -1.899 44.024 -6.879 1.00 82.76 O
ATOM 1437 CB LYS A 196 -1.639 44.410 -9.901 1.00 82.66 C
ATOM 1438 CG LYS A 196 -2.238 43.111 -10.409 1.00 82.46 C
ATOM 1439 CD LYS A 196 -3.449 43.330 -11.304 1.00 83.91 C
ATOM 1440 CE LYS A 196 -3.835 42.017 -12.016 1.00 86.21 C
ATOM 1441 NZ LYS A 196 -5.105 42.029 -12.829 1.00 85.46 N
ATOM 1442 N TYR A 197 -4.062 43.915 -7.531 1.00 83.30 N
ATOM 1443 CA TYR A 197 -4.503 43.112 -6.393 1.00 82.70 C
ATOM 1444 C TYR A 197 -5.560 42.092 -6.796 1.00 82.58 C
ATOM 1445 O TYR A 197 -6.019 42.067 -7.939 1.00 83.40 O
ATOM 1446 CB TYR A 197 -5.081 44.023 -5.293 1.00 82.50 C
ATOM 1447 CG TYR A 197 -6.277 44.862 -5.730 1.00 82.72 C
ATOM 1448 CD1 TYR A 197 -7.410 44.261 -6.297 1.00 82.81 C
ATOM 1449 CD2 TYR A 197 -6.275 46.257 -5.587 1.00 82.18 C
ATOM 1450 CE1 TYR A 197 -8.507 45.017 -6.716 1.00 82.44 C
ATOM 1451 CE2 TYR A 197 -7.376 47.031 -6.001 1.00 82.21 C
ATOM 1452 CZ TYR A 197 -8.491 46.398 -6.572 1.00 82.80 C
ATOM 1453 OH TYR A 197 -9.579 47.124 -7.026 1.00 80.90 O
ATOM 1454 N PHE A 198 -5.954 41.259 -5.839 1.00 81.74 N
ATOM 1455 CA PHE A 198 -6.971 40.240 -6.071 1.00 79.29 C
ATOM 1456 C PHE A 198 -7.743 40.012 -4.790 1.00 75.97 C
ATOM 1457 O PHE A 198 -7.411 39.119 -4.018 1.00 76.68 O
ATOM 1458 CB PHE A 198 -6.344 38.908 -6.486 1.00 81.72 C
ATOM 1459 CG PHE A 198 -5.749 38.909 -7.860 1.00 84.47 C
ATOM 1460 CD1 PHE A 198 -4.495 39.466 -8.092 1.00 85.88 C
ATOM 1461 CD2 PHE A 198 -6.430 38.314 -8.923 1.00 85.59 C
ATOM 1462 CE1 PHE A 198 -3.924 39.425 -9.364 1.00 87.07 C
ATOM 1463 CE2 PHE A 198 -5.868 38.267 -10.195 1.00 86.78 C
ATOM 1464 CZ PHE A 198 -4.610 38.822 -10.418 1.00 86.99 C
ATOM 1465 N SER A 199 -8.773 40.808 -4.554 1.00 71.87 N
ATOM 1466 CA SER A 199 -9.547 40.623 -3.345 1.00 67.84 C
ATOM 1467 C SER A 199 -10.272 39.287 -3.420 1.00 66.10 C
ATOM 1468 O SER A 199 -10.403 38.698 -4.502 1.00 64.20 O
ATOM 1469 CB SER A 199 -10.556 41.746 -3.185 1.00 66.46 C
ATOM 1470 OG SER A 199 -11.427 41.759 -4.287 1.00 65.39 O
ATOM 1471 N MET A 200 -10.728 38.817 -2.259 1.00 64.09 N
ATOM 1472 CA MET A 200 -11.450 37.562 -2.156 1.00 61.01 C
ATOM 1473 C MET A 200 -12.449 37.465 -3.292 1.00 62.42 C
ATOM 1474 O MET A 200 -12.649 36.388 -3.860 1.00 62.06 O
ATOM 1475 CB MET A 200 -12.172 37.476 -0.811 1.00 56.33 C
ATOM 1476 CG MET A 200 -11.247 37.266 0.372 1.00 53.16 C
ATOM 1477 SD MET A 200 -10.171 35.801 0.200 1.00 46.37 S
ATOM 1478 CE MET A 200 -11.362 34.537 0.043 1.00 48.10 C
ATOM 1479 N THR A 201 -13.063 38.595 -3.634 1.00 62.97 N
ATOM 1480 CA THR A 201 -14.033 38.611 -4.719 1.00 64.97 C
ATOM 1481 C THR A 201 -13.363 38.205 -6.045 1.00 66.10 C
ATOM 1482 O THR A 201 -13.991 37.542 -6.896 1.00 65.58 O
ATOM 1483 CB THR A 201 -14.736 40.006 -4.834 1.00 65.68 C
ATOM 1484 OG1 THR A 201 -14.545 40.550 -6.148 1.00 65.66 O
ATOM 1485 CG2 THR A 201 -14.196 40.972 -3.783 1.00 65.96 C
ATOM 1486 N GLU A 202 -12.091 38.576 -6.214 1.00 66.73 N
ATOM 1487 CA GLU A 202 -11.362 38.219 -7.431 1.00 67.80 C
ATOM 1488 C GLU A 202 -11.004 36.765 -7.373 1.00 68.66 C
ATOM 1489 O GLU A 202 -11.062 36.059 -8.385 1.00 70.18 O
ATOM 1490 CB GLU A 202 -10.095 39.031 -7.584 1.00 67.72 C
ATOM 1491 CG GLU A 202 -10.303 40.210 -8.494 1.00 72.08 C
ATOM 1492 CD GLU A 202 -11.396 41.136 -7.989 1.00 74.23 C
ATOM 1493 OE1 GLU A 202 -11.155 41.809 -6.957 1.00 73.29 O
ATOM 1494 OE2 GLU A 202 -12.488 41.178 -8.619 1.00 75.62 O
ATOM 1495 N VAL A 203 -10.619 36.324 -6.180 1.00 67.55 N
ATOM 1496 CA VAL A 203 -10.287 34.929 -5.968 1.00 65.53 C
ATOM 1497 C VAL A 203 -11.555 34.211 -6.431 1.00 64.91 C
ATOM 1498 O VAL A 203 -11.525 33.354 -7.323 1.00 64.87 O
ATOM 1499 CB VAL A 203 -10.070 34.620 -4.453 1.00 65.75 C
ATOM 1500 CG1 VAL A 203 -9.491 33.222 -4.279 1.00 65.81 C
ATOM 1501 CG2 VAL A 203 -9.166 35.660 -3.816 1.00 66.78 C
ATOM 1502 N ASP A 204 -12.674 34.608 -5.820 1.00 62.79 N
ATOM 1503 CA ASP A 204 -13.977 34.030 -6.103 1.00 61.49 C
ATOM 1504 C ASP A 204 -14.282 33.960 -7.571 1.00 62.37 C
ATOM 1505 O ASP A 204 -14.775 32.946 -8.056 1.00 61.65 O
ATOM 1506 CB ASP A 204 -15.070 34.836 -5.411 1.00 59.70 C
ATOM 1507 CG ASP A 204 -15.247 34.446 -3.965 1.00 56.79 C
ATOM 1508 OD1 ASP A 204 -14.278 33.900 -3.398 1.00 52.71 O
ATOM 1509 OD2 ASP A 204 -16.342 34.694 -3.405 1.00 54.02 O
ATOM 1510 N LYS A 205 -13.989 35.043 -8.280 1.00 64.38 N
ATOM 1511 CA LYS A 205 -14.264 35.101 -9.707 1.00 65.17 C
ATOM 1512 C LYS A 205 -13.389 34.196 -10.567 1.00 64.26 C
ATOM 1513 O LYS A 205 -13.889 33.307 -11.239 1.00 63.15 O
ATOM 1514 CB LYS A 205 -14.143 36.536 -10.208 1.00 66.18 C
ATOM 1515 CG LYS A 205 -14.584 36.687 -11.649 1.00 69.34 C
ATOM 1516 CD LYS A 205 -14.486 38.132 -12.116 1.00 73.83 C
ATOM 1517 CE LYS A 205 -15.071 38.343 -13.519 1.00 76.14 C
ATOM 1518 NZ LYS A 205 -16.559 38.137 -13.597 1.00 77.46 N
ATOM 1519 N LEU A 206 -12.083 34.413 -10.533 1.00 64.81 N
ATOM 1520 CA LEU A 206 -11.153 33.640 -11.356 1.00 67.28 C
ATOM 1521 C LEU A 206 -10.807 32.234 -10.887 1.00 68.71 C
ATOM 1522 O LEU A 206 -10.696 31.311 -11.698 1.00 69.72 O
ATOM 1523 CB LEU A 206 -9.840 34.408 -11.503 1.00 68.10 C
ATOM 1524 CG LEU A 206 -9.968 35.909 -11.740 1.00 67.44 C
ATOM 1525 CD1 LEU A 206 -8.586 36.565 -11.699 1.00 63.42 C
ATOM 1526 CD2 LEU A 206 -10.678 36.126 -13.072 1.00 67.18 C
ATOM 1527 N GLY A 207 -10.608 32.078 -9.583 1.00 69.83 N
ATOM 1528 CA GLY A 207 -10.222 30.785 -9.053 1.00 70.69 C
ATOM 1529 C GLY A 207 -8.722 30.866 -8.870 1.00 70.94 C
ATOM 1530 O GLY A 207 -8.001 31.200 -9.805 1.00 70.79 O
ATOM 1531 N ILE A 208 -8.259 30.574 -7.660 1.00 70.50 N
ATOM 1532 CA ILE A 208 -6.844 30.654 -7.332 1.00 70.18 C
ATOM 1533 C ILE A 208 -5.917 30.335 -8.513 1.00 72.13 C
ATOM 1534 O ILE A 208 -4.913 31.025 -8.717 1.00 71.07 O
ATOM 1535 CB ILE A 208 -6.513 29.751 -6.106 1.00 68.19 C
ATOM 1536 CG1 ILE A 208 -5.824 30.574 -5.018 1.00 66.86 C
ATOM 1537 CG2 ILE A 208 -5.685 28.558 -6.528 1.00 65.59 C
ATOM 1538 CD1 ILE A 208 -4.600 31.335 -5.457 1.00 63.60 C
ATOM 1539 N GLY A 209 -6.257 29.317 -9.301 1.00 74.55 N
ATOM 1540 CA GLY A 209 -5.420 28.963 -10.440 1.00 78.13 C
ATOM 1541 C GLY A 209 -5.107 30.133 -11.365 1.00 79.78 C
ATOM 1542 O GLY A 209 -3.941 30.474 -11.573 1.00 79.81 O
ATOM 1543 N LYS A 210 -6.161 30.737 -11.916 1.00 81.12 N
ATOM 1544 CA LYS A 210 -6.073 31.890 -12.815 1.00 81.72 C
ATOM 1545 C LYS A 210 -5.481 33.085 -12.060 1.00 81.92 C
ATOM 1546 O LYS A 210 -4.704 33.864 -12.612 1.00 82.06 O
ATOM 1547 CB LYS A 210 -7.480 32.223 -13.339 1.00 83.49 C
ATOM 1548 CG LYS A 210 -7.630 33.543 -14.084 1.00 86.80 C
ATOM 1549 CD LYS A 210 -6.745 33.615 -15.328 1.00 89.98 C
ATOM 1550 CE LYS A 210 -6.904 34.963 -16.055 1.00 90.59 C
ATOM 1551 NZ LYS A 210 -5.832 35.226 -17.079 1.00 91.17 N
ATOM 1552 N VAL A 211 -5.850 33.222 -10.792 1.00 81.88 N
ATOM 1553 CA VAL A 211 -5.343 34.310 -9.969 1.00 81.43 C
ATOM 1554 C VAL A 211 -3.816 34.290 -9.966 1.00 82.60 C
ATOM 1555 O VAL A 211 -3.186 35.338 -10.093 1.00 82.44 O
ATOM 1556 CB VAL A 211 -5.848 34.193 -8.512 1.00 80.75 C
ATOM 1557 CG1 VAL A 211 -5.199 35.253 -7.643 1.00 79.53 C
ATOM 1558 CG2 VAL A 211 -7.359 34.332 -8.472 1.00 80.56 C
ATOM 1559 N MET A 212 -3.226 33.101 -9.817 1.00 83.85 N
ATOM 1560 CA MET A 212 -1.767 32.958 -9.796 1.00 85.06 C
ATOM 1561 C MET A 212 -1.206 33.105 -11.202 1.00 87.35 C
ATOM 1562 O MET A 212 -0.223 33.813 -11.432 1.00 87.24 O
ATOM 1563 CB MET A 212 -1.358 31.595 -9.230 1.00 82.29 C
ATOM 1564 CG MET A 212 -1.708 31.386 -7.757 1.00 80.30 C
ATOM 1565 SD MET A 212 -0.942 32.561 -6.600 1.00 73.97 S
ATOM 1566 CE MET A 212 0.638 31.866 -6.471 1.00 75.37 C
ATOM 1567 N GLU A 213 -1.846 32.416 -12.137 1.00 90.13 N
ATOM 1568 CA GLU A 213 -1.472 32.447 -13.541 1.00 92.16 C
ATOM 1569 C GLU A 213 -1.314 33.912 -13.969 1.00 92.77 C
ATOM 1570 O GLU A 213 -0.294 34.293 -14.549 1.00 94.09 O
ATOM 1571 CB GLU A 213 -2.571 31.752 -14.344 1.00 94.04 C
ATOM 1572 CG GLU A 213 -2.244 31.404 -15.778 1.00 99.07 C
ATOM 1573 CD GLU A 213 -3.352 30.571 -16.421 1.00102.30 C
ATOM 1574 OE1 GLU A 213 -3.623 29.457 -15.914 1.00103.12 O
ATOM 1575 OE2 GLU A 213 -3.952 31.026 -17.425 1.00104.92 O
ATOM 1576 N GLU A 214 -2.317 34.733 -13.668 1.00 92.07 N
ATOM 1577 CA GLU A 214 -2.267 36.148 -14.013 1.00 91.63 C
ATOM 1578 C GLU A 214 -1.102 36.818 -13.305 1.00 91.32 C
ATOM 1579 O GLU A 214 -0.086 37.111 -13.925 1.00 91.52 O
ATOM 1580 CB GLU A 214 -3.567 36.853 -13.615 1.00 92.05 C
ATOM 1581 CG GLU A 214 -4.652 36.808 -14.668 1.00 92.73 C
ATOM 1582 CD GLU A 214 -5.872 37.625 -14.279 1.00 93.79 C
ATOM 1583 OE1 GLU A 214 -5.727 38.851 -14.051 1.00 93.91 O
ATOM 1584 OE2 GLU A 214 -6.973 37.037 -14.208 1.00 93.93 O
ATOM 1585 N THR A 215 -1.263 37.053 -12.004 1.00 91.31 N
ATOM 1586 CA THR A 215 -0.238 37.696 -11.177 1.00 90.84 C
ATOM 1587 C THR A 215 1.180 37.460 -11.668 1.00 90.63 C
ATOM 1588 O THR A 215 2.030 38.349 -11.575 1.00 89.71 O
ATOM 1589 CB THR A 215 -0.297 37.213 -9.714 1.00 91.00 C
ATOM 1590 OG1 THR A 215 -0.442 35.788 -9.687 1.00 91.70 O
ATOM 1591 CG2 THR A 215 -1.443 37.843 -8.986 1.00 90.94 C
ATOM 1592 N PHE A 216 1.444 36.256 -12.173 1.00 90.43 N
ATOM 1593 CA PHE A 216 2.776 35.948 -12.666 1.00 90.26 C
ATOM 1594 C PHE A 216 3.088 36.749 -13.916 1.00 91.62 C
ATOM 1595 O PHE A 216 3.964 37.615 -13.887 1.00 92.03 O
ATOM 1596 CB PHE A 216 2.932 34.447 -12.916 1.00 86.72 C
ATOM 1597 CG PHE A 216 3.158 33.653 -11.659 1.00 83.81 C
ATOM 1598 CD1 PHE A 216 3.357 34.296 -10.439 1.00 82.90 C
ATOM 1599 CD2 PHE A 216 3.158 32.267 -11.687 1.00 82.83 C
ATOM 1600 CE1 PHE A 216 3.527 33.571 -9.263 1.00 82.23 C
ATOM 1601 CE2 PHE A 216 3.328 31.531 -10.513 1.00 82.56 C
ATOM 1602 CZ PHE A 216 3.520 32.184 -9.299 1.00 81.79 C
ATOM 1603 N SER A 217 2.380 36.483 -15.008 1.00 92.18 N
ATOM 1604 CA SER A 217 2.625 37.240 -16.227 1.00 92.47 C
ATOM 1605 C SER A 217 2.780 38.726 -15.865 1.00 92.71 C
ATOM 1606 O SER A 217 3.797 39.340 -16.181 1.00 93.44 O
ATOM 1607 CB SER A 217 1.465 37.069 -17.205 1.00 92.57 C
ATOM 1608 OG SER A 217 0.345 37.830 -16.789 1.00 92.76 O
ATOM 1609 N TYR A 218 1.781 39.290 -15.189 1.00 92.44 N
ATOM 1610 CA TYR A 218 1.810 40.694 -14.787 1.00 93.21 C
ATOM 1611 C TYR A 218 3.135 41.144 -14.148 1.00 94.61 C
ATOM 1612 O TYR A 218 3.512 42.314 -14.246 1.00 93.90 O
ATOM 1613 CB TYR A 218 0.666 40.981 -13.811 1.00 92.46 C
ATOM 1614 CG TYR A 218 0.769 42.342 -13.149 1.00 92.79 C
ATOM 1615 CD1 TYR A 218 0.179 43.472 -13.721 1.00 93.36 C
ATOM 1616 CD2 TYR A 218 1.504 42.512 -11.975 1.00 91.95 C
ATOM 1617 CE1 TYR A 218 0.324 44.743 -13.139 1.00 92.39 C
ATOM 1618 CE2 TYR A 218 1.658 43.770 -11.387 1.00 92.17 C
ATOM 1619 CZ TYR A 218 1.067 44.886 -11.973 1.00 92.07 C
ATOM 1620 OH TYR A 218 1.240 46.137 -11.403 1.00 91.03 O
ATOM 1621 N LEU A 219 3.831 40.221 -13.490 1.00 96.79 N
ATOM 1622 CA LEU A 219 5.098 40.537 -12.825 1.00 99.53 C
ATOM 1623 C LEU A 219 6.348 40.001 -13.535 1.00102.10 C
ATOM 1624 O LEU A 219 7.370 40.687 -13.624 1.00102.34 O
ATOM 1625 CB LEU A 219 5.086 39.997 -11.389 1.00 98.47 C
ATOM 1626 CG LEU A 219 4.218 40.679 -10.335 1.00 97.30 C
ATOM 1627 CD1 LEU A 219 4.155 39.802 -9.108 1.00 97.75 C
ATOM 1628 CD2 LEU A 219 4.787 42.041 -9.981 1.00 96.22 C
ATOM 1629 N LEU A 220 6.263 38.772 -14.032 1.00104.81 N
ATOM 1630 CA LEU A 220 7.391 38.133 -14.705 1.00107.29 C
ATOM 1631 C LEU A 220 7.161 38.026 -16.216 1.00109.31 C
ATOM 1632 O LEU A 220 7.805 37.223 -16.894 1.00109.84 O
ATOM 1633 CB LEU A 220 7.614 36.731 -14.110 1.00106.72 C
ATOM 1634 CG LEU A 220 7.339 36.524 -12.609 1.00105.67 C
ATOM 1635 CD1 LEU A 220 7.545 35.055 -12.248 1.00104.74 C
ATOM 1636 CD2 LEU A 220 8.241 37.424 -11.769 1.00104.50 C
ATOM 1637 N GLY A 221 6.242 38.836 -16.738 1.00111.26 N
ATOM 1638 CA GLY A 221 5.947 38.801 -18.161 1.00113.38 C
ATOM 1639 C GLY A 221 7.136 39.205 -19.008 1.00114.74 C
ATOM 1640 O GLY A 221 7.529 38.487 -19.928 1.00114.30 O
ATOM 1641 N ARG A 222 7.709 40.361 -18.692 1.00116.28 N
ATOM 1642 CA ARG A 222 8.864 40.875 -19.414 1.00117.84 C
ATOM 1643 C ARG A 222 10.164 40.292 -18.855 1.00117.49 C
ATOM 1644 O ARG A 222 10.689 39.293 -19.358 1.00117.04 O
ATOM 1645 CB ARG A 222 8.887 42.406 -19.323 1.00120.30 C
ATOM 1646 CG ARG A 222 7.796 43.093 -20.148 1.00124.08 C
ATOM 1647 CD ARG A 222 7.560 44.553 -19.730 1.00127.28 C
ATOM 1648 NE ARG A 222 6.905 44.666 -18.423 1.00129.65 N
ATOM 1649 CZ ARG A 222 6.365 45.785 -17.939 1.00130.39 C
ATOM 1650 NH1 ARG A 222 6.397 46.906 -18.651 1.00131.75 N
ATOM 1651 NH2 ARG A 222 5.786 45.786 -16.743 1.00130.10 N
ATOM 1652 N LYS A 223 10.681 40.917 -17.805 1.00117.21 N
ATOM 1653 CA LYS A 223 11.917 40.456 -17.187 1.00116.89 C
ATOM 1654 C LYS A 223 11.651 39.571 -15.969 1.00115.74 C
ATOM 1655 O LYS A 223 11.094 40.024 -14.967 1.00116.07 O
ATOM 1656 CB LYS A 223 12.775 41.655 -16.755 1.00118.12 C
ATOM 1657 CG LYS A 223 13.327 42.530 -17.885 1.00119.48 C
ATOM 1658 CD LYS A 223 14.481 41.865 -18.637 1.00120.20 C
ATOM 1659 CE LYS A 223 15.289 42.887 -19.446 1.00119.96 C
ATOM 1660 NZ LYS A 223 14.485 43.612 -20.473 1.00120.32 N
ATOM 1661 N LYS A 224 12.047 38.307 -16.064 1.00113.56 N
ATOM 1662 CA LYS A 224 11.892 37.378 -14.951 1.00110.71 C
ATOM 1663 C LYS A 224 12.793 37.876 -13.819 1.00108.17 C
ATOM 1664 O LYS A 224 14.006 37.988 -13.994 1.00107.92 O
ATOM 1665 CB LYS A 224 12.333 35.968 -15.363 1.00111.33 C
ATOM 1666 CG LYS A 224 11.350 35.221 -16.242 1.00111.67 C
ATOM 1667 CD LYS A 224 10.994 36.002 -17.491 1.00113.19 C
ATOM 1668 CE LYS A 224 10.010 35.226 -18.354 1.00114.15 C
ATOM 1669 NZ LYS A 224 9.515 36.039 -19.504 1.00114.36 N
ATOM 1670 N ARG A 225 12.208 38.191 -12.668 1.00104.97 N
ATOM 1671 CA ARG A 225 12.998 38.661 -11.531 1.00102.05 C
ATOM 1672 C ARG A 225 12.814 37.760 -10.306 1.00 99.65 C
ATOM 1673 O ARG A 225 12.153 36.720 -10.381 1.00100.15 O
ATOM 1674 CB ARG A 225 12.637 40.114 -11.169 1.00101.03 C
ATOM 1675 CG ARG A 225 11.188 40.374 -10.782 1.00 99.54 C
ATOM 1676 CD ARG A 225 10.295 40.355 -12.005 1.00 99.50 C
ATOM 1677 NE ARG A 225 9.100 41.185 -11.851 1.00 98.90 N
ATOM 1678 CZ ARG A 225 9.122 42.495 -11.614 1.00 99.29 C
ATOM 1679 NH1 ARG A 225 10.278 43.136 -11.492 1.00 99.63 N
ATOM 1680 NH2 ARG A 225 7.986 43.171 -11.518 1.00 99.36 N
ATOM 1681 N PRO A 226 13.446 38.118 -9.177 1.00 96.61 N
ATOM 1682 CA PRO A 226 13.282 37.282 -7.984 1.00 93.91 C
ATOM 1683 C PRO A 226 11.969 37.635 -7.301 1.00 90.68 C
ATOM 1684 O PRO A 226 11.476 38.760 -7.434 1.00 90.41 O
ATOM 1685 CB PRO A 226 14.489 37.654 -7.130 1.00 94.90 C
ATOM 1686 CG PRO A 226 15.508 38.067 -8.157 1.00 96.02 C
ATOM 1687 CD PRO A 226 14.679 38.914 -9.076 1.00 95.93 C
ATOM 1688 N ILE A 227 11.409 36.666 -6.580 1.00 86.58 N
ATOM 1689 CA ILE A 227 10.142 36.848 -5.872 1.00 81.66 C
ATOM 1690 C ILE A 227 10.332 36.979 -4.367 1.00 78.57 C
ATOM 1691 O ILE A 227 11.235 36.372 -3.774 1.00 78.91 O
ATOM 1692 CB ILE A 227 9.152 35.647 -6.119 1.00 81.09 C
ATOM 1693 CG1 ILE A 227 8.302 35.897 -7.367 1.00 79.71 C
ATOM 1694 CG2 ILE A 227 8.243 35.436 -4.902 1.00 79.22 C
ATOM 1695 CD1 ILE A 227 9.024 35.678 -8.673 1.00 79.96 C
ATOM 1696 N HIS A 228 9.481 37.793 -3.761 1.00 73.48 N
ATOM 1697 CA HIS A 228 9.500 37.948 -2.331 1.00 69.84 C
ATOM 1698 C HIS A 228 8.062 37.720 -1.886 1.00 67.82 C
ATOM 1699 O HIS A 228 7.209 38.610 -1.983 1.00 66.60 O
ATOM 1700 CB HIS A 228 9.940 39.338 -1.915 1.00 70.56 C
ATOM 1701 CG HIS A 228 10.037 39.499 -0.432 1.00 73.54 C
ATOM 1702 ND1 HIS A 228 11.058 38.940 0.312 1.00 75.85 N
ATOM 1703 CD2 HIS A 228 9.211 40.096 0.459 1.00 74.60 C
ATOM 1704 CE1 HIS A 228 10.856 39.185 1.594 1.00 75.11 C
ATOM 1705 NE2 HIS A 228 9.740 39.884 1.712 1.00 76.27 N
ATOM 1706 N LEU A 229 7.784 36.509 -1.428 1.00 65.08 N
ATOM 1707 CA LEU A 229 6.450 36.177 -0.963 1.00 62.32 C
ATOM 1708 C LEU A 229 6.312 36.516 0.518 1.00 61.53 C
ATOM 1709 O LEU A 229 6.847 35.814 1.378 1.00 62.14 O
ATOM 1710 CB LEU A 229 6.175 34.691 -1.152 1.00 59.30 C
ATOM 1711 CG LEU A 229 4.861 34.239 -0.512 1.00 57.40 C
ATOM 1712 CD1 LEU A 229 3.687 34.835 -1.274 1.00 54.44 C
ATOM 1713 CD2 LEU A 229 4.810 32.730 -0.508 1.00 56.40 C
ATOM 1714 N SER A 230 5.612 37.600 0.818 1.00 59.36 N
ATOM 1715 CA SER A 230 5.401 37.985 2.203 1.00 58.06 C
ATOM 1716 C SER A 230 4.041 37.362 2.534 1.00 57.34 C
ATOM 1717 O SER A 230 2.983 37.879 2.151 1.00 57.15 O
ATOM 1718 CB SER A 230 5.363 39.518 2.334 1.00 58.58 C
ATOM 1719 OG SER A 230 5.725 39.967 3.634 1.00 57.12 O
ATOM 1720 N PHE A 231 4.070 36.228 3.222 1.00 55.66 N
ATOM 1721 CA PHE A 231 2.831 35.547 3.565 1.00 54.53 C
ATOM 1722 C PHE A 231 2.368 35.851 4.973 1.00 53.57 C
ATOM 1723 O PHE A 231 3.101 35.671 5.947 1.00 52.54 O
ATOM 1724 CB PHE A 231 2.981 34.034 3.403 1.00 52.60 C
ATOM 1725 CG PHE A 231 1.687 33.330 3.169 1.00 46.80 C
ATOM 1726 CD1 PHE A 231 0.620 33.522 4.025 1.00 44.29 C
ATOM 1727 CD2 PHE A 231 1.549 32.461 2.094 1.00 46.49 C
ATOM 1728 CE1 PHE A 231 -0.555 32.862 3.824 1.00 44.81 C
ATOM 1729 CE2 PHE A 231 0.377 31.787 1.876 1.00 46.31 C
ATOM 1730 CZ PHE A 231 -0.687 31.987 2.745 1.00 47.96 C
ATOM 1731 N ASP A 232 1.122 36.294 5.064 1.00 54.56 N
ATOM 1732 CA ASP A 232 0.522 36.642 6.340 1.00 54.94 C
ATOM 1733 C ASP A 232 -0.489 35.610 6.764 1.00 54.45 C
ATOM 1734 O ASP A 232 -1.644 35.688 6.386 1.00 53.16 O
ATOM 1735 CB ASP A 232 -0.160 37.998 6.250 1.00 53.83 C
ATOM 1736 CG ASP A 232 -0.888 38.357 7.507 1.00 54.18 C
ATOM 1737 OD1 ASP A 232 -0.905 37.546 8.459 1.00 51.22 O
ATOM 1738 OD2 ASP A 232 -1.464 39.462 7.541 1.00 54.39 O
ATOM 1739 N VAL A 233 -0.036 34.658 7.569 1.00 55.37 N
ATOM 1740 CA VAL A 233 -0.863 33.588 8.093 1.00 56.07 C
ATOM 1741 C VAL A 233 -2.342 33.943 8.253 1.00 56.17 C
ATOM 1742 O VAL A 233 -3.197 33.057 8.238 1.00 57.17 O
ATOM 1743 CB VAL A 233 -0.348 33.147 9.452 1.00 58.18 C
ATOM 1744 CG1 VAL A 233 -0.651 34.238 10.495 1.00 57.95 C
ATOM 1745 CG2 VAL A 233 -0.986 31.836 9.835 1.00 59.10 C
ATOM 1746 N ASP A 234 -2.657 35.226 8.420 1.00 55.85 N
ATOM 1747 CA ASP A 234 -4.063 35.628 8.557 1.00 55.47 C
ATOM 1748 C ASP A 234 -4.843 35.763 7.236 1.00 52.10 C
ATOM 1749 O ASP A 234 -6.055 35.812 7.247 1.00 52.05 O
ATOM 1750 CB ASP A 234 -4.183 36.937 9.370 1.00 59.03 C
ATOM 1751 CG ASP A 234 -3.841 38.191 8.563 1.00 63.96 C
ATOM 1752 OD1 ASP A 234 -4.294 38.323 7.392 1.00 65.02 O
ATOM 1753 OD2 ASP A 234 -3.136 39.067 9.126 1.00 66.85 O
ATOM 1754 N GLY A 235 -4.148 35.832 6.109 1.00 50.06 N
ATOM 1755 CA GLY A 235 -4.876 35.746 4.823 1.00 49.84 C
ATOM 1756 C GLY A 235 -5.652 34.477 4.460 1.00 49.59 C
ATOM 1757 O GLY A 235 -6.279 34.383 3.392 1.00 47.09 O
ATOM 1758 N LEU A 236 -5.575 33.478 5.331 1.00 50.09 N
ATOM 1759 CA LEU A 236 -6.306 32.249 5.122 1.00 50.76 C
ATOM 1760 C LEU A 236 -7.566 32.466 5.926 1.00 51.57 C
ATOM 1761 O LEU A 236 -7.662 33.445 6.670 1.00 52.88 O
ATOM 1762 CB LEU A 236 -5.522 31.073 5.678 1.00 52.43 C
ATOM 1763 CG LEU A 236 -4.915 30.163 4.613 1.00 54.89 C
ATOM 1764 CD1 LEU A 236 -4.292 31.006 3.512 1.00 55.00 C
ATOM 1765 CD2 LEU A 236 -3.884 29.252 5.259 1.00 55.89 C
ATOM 1766 N ASP A 237 -8.548 31.589 5.794 1.00 52.93 N
ATOM 1767 CA ASP A 237 -9.758 31.791 6.582 1.00 57.18 C
ATOM 1768 C ASP A 237 -9.499 31.487 8.068 1.00 58.88 C
ATOM 1769 O ASP A 237 -8.649 30.651 8.401 1.00 59.95 O
ATOM 1770 CB ASP A 237 -10.897 30.922 6.071 1.00 58.63 C
ATOM 1771 CG ASP A 237 -12.202 31.231 6.770 1.00 60.03 C
ATOM 1772 OD1 ASP A 237 -12.355 30.816 7.944 1.00 60.59 O
ATOM 1773 OD2 ASP A 237 -13.052 31.916 6.154 1.00 60.31 O
ATOM 1774 N PRO A 238 -10.223 32.165 8.983 1.00 57.68 N
ATOM 1775 CA PRO A 238 -9.992 31.897 10.402 1.00 56.57 C
ATOM 1776 C PRO A 238 -10.134 30.441 10.850 1.00 56.08 C
ATOM 1777 O PRO A 238 -9.540 30.041 11.858 1.00 56.48 O
ATOM 1778 CB PRO A 238 -10.977 32.841 11.083 1.00 57.23 C
ATOM 1779 CG PRO A 238 -10.912 34.037 10.192 1.00 57.07 C
ATOM 1780 CD PRO A 238 -11.054 33.372 8.828 1.00 57.93 C
ATOM 1781 N VAL A 239 -10.895 29.643 10.103 1.00 53.68 N
ATOM 1782 CA VAL A 239 -11.077 28.233 10.452 1.00 52.34 C
ATOM 1783 C VAL A 239 -9.754 27.459 10.296 1.00 52.10 C
ATOM 1784 O VAL A 239 -9.516 26.447 10.960 1.00 50.40 O
ATOM 1785 CB VAL A 239 -12.145 27.579 9.545 1.00 51.91 C
ATOM 1786 CG1 VAL A 239 -11.492 26.911 8.356 1.00 51.39 C
ATOM 1787 CG2 VAL A 239 -12.960 26.587 10.335 1.00 51.86 C
ATOM 1788 N PHE A 240 -8.892 27.966 9.423 1.00 52.61 N
ATOM 1789 CA PHE A 240 -7.615 27.331 9.133 1.00 51.13 C
ATOM 1790 C PHE A 240 -6.452 27.840 9.963 1.00 50.55 C
ATOM 1791 O PHE A 240 -5.648 27.050 10.443 1.00 52.43 O
ATOM 1792 CB PHE A 240 -7.293 27.504 7.645 1.00 49.52 C
ATOM 1793 CG PHE A 240 -8.305 26.865 6.717 1.00 46.38 C
ATOM 1794 CD1 PHE A 240 -8.323 25.483 6.533 1.00 43.52 C
ATOM 1795 CD2 PHE A 240 -9.216 27.647 6.012 1.00 44.12 C
ATOM 1796 CE1 PHE A 240 -9.207 24.900 5.664 1.00 40.93 C
ATOM 1797 CE2 PHE A 240 -10.108 27.063 5.138 1.00 41.80 C
ATOM 1798 CZ PHE A 240 -10.105 25.688 4.964 1.00 40.90 C
ATOM 1799 N THR A 241 -6.361 29.150 10.134 1.00 49.79 N
ATOM 1800 CA THR A 241 -5.267 29.742 10.890 1.00 50.83 C
ATOM 1801 C THR A 241 -5.824 30.632 11.974 1.00 52.55 C
ATOM 1802 O THR A 241 -5.576 31.840 11.988 1.00 51.99 O
ATOM 1803 CB THR A 241 -4.391 30.608 9.988 1.00 51.65 C
ATOM 1804 OG1 THR A 241 -5.214 31.587 9.324 1.00 53.02 O
ATOM 1805 CG2 THR A 241 -3.681 29.744 8.961 1.00 50.87 C
ATOM 1806 N PRO A 242 -6.594 30.052 12.899 1.00 54.97 N
ATOM 1807 CA PRO A 242 -7.200 30.812 13.998 1.00 57.22 C
ATOM 1808 C PRO A 242 -6.294 31.627 14.928 1.00 56.87 C
ATOM 1809 O PRO A 242 -6.674 32.720 15.333 1.00 57.12 O
ATOM 1810 CB PRO A 242 -8.027 29.751 14.736 1.00 57.28 C
ATOM 1811 CG PRO A 242 -7.408 28.439 14.312 1.00 57.06 C
ATOM 1812 CD PRO A 242 -7.114 28.676 12.868 1.00 56.17 C
ATOM 1813 N ALA A 243 -5.113 31.110 15.263 1.00 58.31 N
ATOM 1814 CA ALA A 243 -4.190 31.822 16.156 1.00 58.19 C
ATOM 1815 C ALA A 243 -3.535 33.043 15.514 1.00 58.24 C
ATOM 1816 O ALA A 243 -2.363 32.982 15.136 1.00 57.68 O
ATOM 1817 CB ALA A 243 -3.103 30.864 16.666 1.00 56.37 C
ATOM 1818 N THR A 244 -4.287 34.141 15.404 1.00 59.71 N
ATOM 1819 CA THR A 244 -3.787 35.390 14.807 1.00 62.49 C
ATOM 1820 C THR A 244 -4.247 36.642 15.561 1.00 64.13 C
ATOM 1821 O THR A 244 -5.001 36.564 16.534 1.00 66.01 O
ATOM 1822 CB THR A 244 -4.264 35.586 13.343 1.00 60.93 C
ATOM 1823 OG1 THR A 244 -4.306 34.328 12.665 1.00 62.57 O
ATOM 1824 CG2 THR A 244 -3.297 36.495 12.600 1.00 62.79 C
ATOM 1825 N GLY A 245 -3.779 37.799 15.094 1.00 65.60 N
ATOM 1826 CA GLY A 245 -4.167 39.064 15.688 1.00 65.27 C
ATOM 1827 C GLY A 245 -5.541 39.394 15.154 1.00 65.53 C
ATOM 1828 O GLY A 245 -6.518 39.319 15.883 1.00 65.18 O
ATOM 1829 N THR A 246 -5.626 39.725 13.870 1.00 67.51 N
ATOM 1830 CA THR A 246 -6.916 40.048 13.268 1.00 69.03 C
ATOM 1831 C THR A 246 -7.500 38.944 12.405 1.00 70.69 C
ATOM 1832 O THR A 246 -6.942 38.642 11.349 1.00 72.99 O
ATOM 1833 CB THR A 246 -6.865 41.219 12.287 1.00 68.81 C
ATOM 1834 OG1 THR A 246 -5.709 42.029 12.523 1.00 70.16 O
ATOM 1835 CG2 THR A 246 -8.156 42.024 12.391 1.00 67.59 C
ATOM 1836 N PRO A 247 -8.605 38.303 12.838 1.00 69.84 N
ATOM 1837 CA PRO A 247 -9.103 37.282 11.913 1.00 67.28 C
ATOM 1838 C PRO A 247 -10.160 38.016 11.050 1.00 65.99 C
ATOM 1839 O PRO A 247 -10.721 39.037 11.478 1.00 64.86 O
ATOM 1840 CB PRO A 247 -9.698 36.226 12.847 1.00 66.52 C
ATOM 1841 CG PRO A 247 -10.233 37.044 13.965 1.00 67.42 C
ATOM 1842 CD PRO A 247 -9.140 38.085 14.199 1.00 69.14 C
ATOM 1843 N VAL A 248 -10.396 37.535 9.831 1.00 64.07 N
ATOM 1844 CA VAL A 248 -11.391 38.147 8.939 1.00 60.46 C
ATOM 1845 C VAL A 248 -12.065 37.005 8.146 1.00 58.21 C
ATOM 1846 O VAL A 248 -11.449 36.399 7.273 1.00 58.79 O
ATOM 1847 CB VAL A 248 -10.718 39.175 7.979 1.00 59.13 C
ATOM 1848 CG1 VAL A 248 -11.756 39.918 7.216 1.00 59.22 C
ATOM 1849 CG2 VAL A 248 -9.914 40.178 8.764 1.00 60.23 C
ATOM 1850 N VAL A 249 -13.321 36.697 8.457 1.00 54.05 N
ATOM 1851 CA VAL A 249 -13.998 35.592 7.779 1.00 51.52 C
ATOM 1852 C VAL A 249 -13.996 35.692 6.269 1.00 49.68 C
ATOM 1853 O VAL A 249 -13.816 36.775 5.715 1.00 50.93 O
ATOM 1854 CB VAL A 249 -15.445 35.489 8.209 1.00 50.57 C
ATOM 1855 CG1 VAL A 249 -15.511 35.113 9.657 1.00 50.72 C
ATOM 1856 CG2 VAL A 249 -16.138 36.803 7.956 1.00 48.35 C
ATOM 1857 N GLY A 250 -14.209 34.562 5.604 1.00 45.28 N
ATOM 1858 CA GLY A 250 -14.256 34.567 4.153 1.00 44.16 C
ATOM 1859 C GLY A 250 -12.943 34.831 3.427 1.00 45.03 C
ATOM 1860 O GLY A 250 -12.876 35.650 2.491 1.00 43.44 O
ATOM 1861 N GLY A 251 -11.906 34.112 3.859 1.00 45.14 N
ATOM 1862 CA GLY A 251 -10.591 34.236 3.268 1.00 44.15 C
ATOM 1863 C GLY A 251 -10.099 32.957 2.610 1.00 44.72 C
ATOM 1864 O GLY A 251 -10.820 31.956 2.525 1.00 45.93 O
ATOM 1865 N LEU A 252 -8.859 33.012 2.135 1.00 43.77 N
ATOM 1866 CA LEU A 252 -8.196 31.911 1.462 1.00 44.97 C
ATOM 1867 C LEU A 252 -8.312 30.572 2.190 1.00 47.83 C
ATOM 1868 O LEU A 252 -8.208 30.488 3.431 1.00 51.38 O
ATOM 1869 CB LEU A 252 -6.719 32.272 1.271 1.00 43.84 C
ATOM 1870 CG LEU A 252 -6.527 33.479 0.355 1.00 43.55 C
ATOM 1871 CD1 LEU A 252 -5.193 34.166 0.599 1.00 41.47 C
ATOM 1872 CD2 LEU A 252 -6.668 33.014 -1.076 1.00 41.53 C
ATOM 1873 N SER A 253 -8.512 29.509 1.426 1.00 46.62 N
ATOM 1874 CA SER A 253 -8.615 28.197 2.034 1.00 46.70 C
ATOM 1875 C SER A 253 -7.223 27.599 2.160 1.00 47.40 C
ATOM 1876 O SER A 253 -6.295 28.043 1.482 1.00 48.44 O
ATOM 1877 CB SER A 253 -9.459 27.323 1.148 1.00 45.90 C
ATOM 1878 OG SER A 253 -9.056 27.527 -0.191 1.00 46.47 O
ATOM 1879 N TYR A 254 -7.077 26.603 3.031 1.00 47.39 N
ATOM 1880 CA TYR A 254 -5.799 25.926 3.211 1.00 47.44 C
ATOM 1881 C TYR A 254 -5.393 25.585 1.790 1.00 49.11 C
ATOM 1882 O TYR A 254 -4.339 26.021 1.326 1.00 49.44 O
ATOM 1883 CB TYR A 254 -5.987 24.647 4.028 1.00 46.22 C
ATOM 1884 CG TYR A 254 -4.726 23.843 4.337 1.00 47.21 C
ATOM 1885 CD1 TYR A 254 -3.759 24.322 5.216 1.00 48.90 C
ATOM 1886 CD2 TYR A 254 -4.556 22.556 3.828 1.00 47.33 C
ATOM 1887 CE1 TYR A 254 -2.656 23.535 5.593 1.00 49.41 C
ATOM 1888 CE2 TYR A 254 -3.467 21.758 4.190 1.00 49.47 C
ATOM 1889 CZ TYR A 254 -2.519 22.250 5.077 1.00 51.72 C
ATOM 1890 OH TYR A 254 -1.459 21.442 5.467 1.00 53.13 O
ATOM 1891 N ARG A 255 -6.256 24.836 1.096 1.00 49.81 N
ATOM 1892 CA ARG A 255 -6.033 24.439 -0.299 1.00 50.99 C
ATOM 1893 C ARG A 255 -5.559 25.608 -1.174 1.00 52.53 C
ATOM 1894 O ARG A 255 -4.471 25.551 -1.767 1.00 53.55 O
ATOM 1895 CB ARG A 255 -7.321 23.851 -0.894 1.00 51.35 C
ATOM 1896 CG ARG A 255 -7.507 22.365 -0.629 1.00 54.18 C
ATOM 1897 CD ARG A 255 -8.900 21.851 -0.994 1.00 55.20 C
ATOM 1898 NE ARG A 255 -9.164 21.927 -2.429 1.00 59.63 N
ATOM 1899 CZ ARG A 255 -10.322 21.587 -3.002 1.00 62.22 C
ATOM 1900 NH1 ARG A 255 -11.333 21.140 -2.253 1.00 63.52 N
ATOM 1901 NH2 ARG A 255 -10.478 21.704 -4.322 1.00 60.66 N
ATOM 1902 N GLU A 256 -6.371 26.659 -1.262 1.00 52.25 N
ATOM 1903 CA GLU A 256 -5.995 27.820 -2.056 1.00 54.48 C
ATOM 1904 C GLU A 256 -4.634 28.384 -1.630 1.00 55.70 C
ATOM 1905 O GLU A 256 -3.847 28.835 -2.469 1.00 56.74 O
ATOM 1906 CB GLU A 256 -7.040 28.926 -1.931 1.00 55.00 C
ATOM 1907 CG GLU A 256 -8.374 28.616 -2.564 1.00 55.21 C
ATOM 1908 CD GLU A 256 -9.322 29.777 -2.450 1.00 56.50 C
ATOM 1909 OE1 GLU A 256 -9.391 30.358 -1.341 1.00 57.48 O
ATOM 1910 OE2 GLU A 256 -9.995 30.103 -3.459 1.00 57.60 O
ATOM 1911 N GLY A 257 -4.366 28.365 -0.327 1.00 55.23 N
ATOM 1912 CA GLY A 257 -3.106 28.885 0.176 1.00 54.94 C
ATOM 1913 C GLY A 257 -1.943 27.990 -0.184 1.00 54.60 C
ATOM 1914 O GLY A 257 -0.830 28.448 -0.460 1.00 52.82 O
ATOM 1915 N LEU A 258 -2.204 26.693 -0.154 1.00 54.63 N
ATOM 1916 CA LEU A 258 -1.184 25.749 -0.509 1.00 55.19 C
ATOM 1917 C LEU A 258 -1.045 25.800 -2.014 1.00 56.88 C
ATOM 1918 O LEU A 258 0.022 25.496 -2.551 1.00 58.61 O
ATOM 1919 CB LEU A 258 -1.548 24.341 -0.048 1.00 53.48 C
ATOM 1920 CG LEU A 258 -1.260 24.113 1.433 1.00 51.43 C
ATOM 1921 CD1 LEU A 258 -1.343 22.639 1.771 1.00 50.84 C
ATOM 1922 CD2 LEU A 258 0.129 24.614 1.732 1.00 52.56 C
ATOM 1923 N TYR A 259 -2.098 26.201 -2.717 1.00 56.63 N
ATOM 1924 CA TYR A 259 -1.946 26.265 -4.157 1.00 58.61 C
ATOM 1925 C TYR A 259 -1.007 27.400 -4.533 1.00 59.71 C
ATOM 1926 O TYR A 259 -0.194 27.268 -5.453 1.00 61.48 O
ATOM 1927 CB TYR A 259 -3.260 26.481 -4.871 1.00 58.79 C
ATOM 1928 CG TYR A 259 -3.096 26.308 -6.365 1.00 59.56 C
ATOM 1929 CD1 TYR A 259 -3.250 25.047 -6.958 1.00 58.31 C
ATOM 1930 CD2 TYR A 259 -2.808 27.409 -7.190 1.00 57.95 C
ATOM 1931 CE1 TYR A 259 -3.135 24.888 -8.339 1.00 60.55 C
ATOM 1932 CE2 TYR A 259 -2.689 27.268 -8.568 1.00 58.97 C
ATOM 1933 CZ TYR A 259 -2.860 26.006 -9.140 1.00 61.35 C
ATOM 1934 OH TYR A 259 -2.800 25.859 -10.506 1.00 61.49 O
ATOM 1935 N ILE A 260 -1.124 28.518 -3.823 1.00 59.36 N
ATOM 1936 CA ILE A 260 -0.268 29.665 -4.081 1.00 59.47 C
ATOM 1937 C ILE A 260 1.206 29.284 -3.906 1.00 59.59 C
ATOM 1938 O ILE A 260 1.950 29.221 -4.884 1.00 57.54 O
ATOM 1939 CB ILE A 260 -0.639 30.842 -3.149 1.00 60.43 C
ATOM 1940 CG1 ILE A 260 -2.014 31.402 -3.544 1.00 60.99 C
ATOM 1941 CG2 ILE A 260 0.408 31.934 -3.232 1.00 61.05 C
ATOM 1942 CD1 ILE A 260 -2.496 32.527 -2.661 1.00 60.66 C
ATOM 1943 N THR A 261 1.630 29.018 -2.672 1.00 61.59 N
ATOM 1944 CA THR A 261 3.026 28.639 -2.421 1.00 63.51 C
ATOM 1945 C THR A 261 3.491 27.573 -3.428 1.00 67.33 C
ATOM 1946 O THR A 261 4.677 27.526 -3.797 1.00 68.11 O
ATOM 1947 CB THR A 261 3.219 28.056 -1.011 1.00 60.27 C
ATOM 1948 OG1 THR A 261 2.313 26.970 -0.842 1.00 57.46 O
ATOM 1949 CG2 THR A 261 2.976 29.100 0.071 1.00 57.45 C
ATOM 1950 N GLU A 262 2.559 26.717 -3.857 1.00 69.10 N
ATOM 1951 CA GLU A 262 2.869 25.664 -4.825 1.00 71.64 C
ATOM 1952 C GLU A 262 3.235 26.208 -6.211 1.00 74.49 C
ATOM 1953 O GLU A 262 4.229 25.784 -6.805 1.00 73.82 O
ATOM 1954 CB GLU A 262 1.701 24.685 -4.951 1.00 70.03 C
ATOM 1955 CG GLU A 262 1.614 23.697 -3.809 1.00 66.23 C
ATOM 1956 CD GLU A 262 0.732 22.508 -4.137 1.00 64.16 C
ATOM 1957 OE1 GLU A 262 -0.269 22.686 -4.872 1.00 61.75 O
ATOM 1958 OE2 GLU A 262 1.037 21.400 -3.645 1.00 61.96 O
ATOM 1959 N GLU A 263 2.431 27.132 -6.732 1.00 77.10 N
ATOM 1960 CA GLU A 263 2.726 27.732 -8.030 1.00 80.64 C
ATOM 1961 C GLU A 263 3.936 28.663 -7.914 1.00 82.90 C
ATOM 1962 O GLU A 263 4.634 28.920 -8.900 1.00 83.65 O
ATOM 1963 CB GLU A 263 1.526 28.512 -8.546 1.00 81.10 C
ATOM 1964 CG GLU A 263 0.500 27.618 -9.180 1.00 85.33 C
ATOM 1965 CD GLU A 263 1.108 26.753 -10.278 1.00 87.53 C
ATOM 1966 OE1 GLU A 263 1.628 27.336 -11.255 1.00 89.71 O
ATOM 1967 OE2 GLU A 263 1.071 25.502 -10.164 1.00 87.81 O
ATOM 1968 N ILE A 264 4.171 29.165 -6.705 1.00 83.91 N
ATOM 1969 CA ILE A 264 5.305 30.034 -6.437 1.00 86.02 C
ATOM 1970 C ILE A 264 6.570 29.202 -6.627 1.00 87.43 C
ATOM 1971 O ILE A 264 7.491 29.568 -7.370 1.00 86.72 O
ATOM 1972 CB ILE A 264 5.268 30.567 -4.974 1.00 86.67 C
ATOM 1973 CG1 ILE A 264 4.251 31.702 -4.849 1.00 87.39 C
ATOM 1974 CG2 ILE A 264 6.664 31.006 -4.531 1.00 86.51 C
ATOM 1975 CD1 ILE A 264 4.502 32.885 -5.768 1.00 86.98 C
ATOM 1976 N TYR A 265 6.593 28.071 -5.933 1.00 88.88 N
ATOM 1977 CA TYR A 265 7.713 27.153 -5.989 1.00 89.33 C
ATOM 1978 C TYR A 265 7.995 26.706 -7.423 1.00 89.27 C
ATOM 1979 O TYR A 265 9.127 26.772 -7.890 1.00 89.51 O
ATOM 1980 CB TYR A 265 7.423 25.932 -5.117 1.00 89.38 C
ATOM 1981 CG TYR A 265 8.366 24.809 -5.387 1.00 89.34 C
ATOM 1982 CD1 TYR A 265 9.695 24.896 -5.002 1.00 90.14 C
ATOM 1983 CD2 TYR A 265 7.956 23.698 -6.121 1.00 90.59 C
ATOM 1984 CE1 TYR A 265 10.611 23.906 -5.349 1.00 92.33 C
ATOM 1985 CE2 TYR A 265 8.859 22.699 -6.475 1.00 92.63 C
ATOM 1986 CZ TYR A 265 10.190 22.810 -6.088 1.00 92.95 C
ATOM 1987 OH TYR A 265 11.096 21.835 -6.454 1.00 93.11 O
ATOM 1988 N LYS A 266 6.956 26.254 -8.116 1.00 89.51 N
ATOM 1989 CA LYS A 266 7.077 25.781 -9.491 1.00 90.13 C
ATOM 1990 C LYS A 266 7.669 26.789 -10.482 1.00 89.83 C
ATOM 1991 O LYS A 266 7.777 26.502 -11.676 1.00 89.92 O
ATOM 1992 CB LYS A 266 5.706 25.305 -9.989 1.00 91.98 C
ATOM 1993 CG LYS A 266 5.231 24.003 -9.345 1.00 93.52 C
ATOM 1994 CD LYS A 266 3.758 23.699 -9.637 1.00 94.83 C
ATOM 1995 CE LYS A 266 3.479 23.466 -11.124 1.00 95.81 C
ATOM 1996 NZ LYS A 266 3.436 24.720 -11.944 1.00 96.25 N
ATOM 1997 N THR A 267 8.059 27.963 -9.998 1.00 89.07 N
ATOM 1998 CA THR A 267 8.639 28.978 -10.874 1.00 87.97 C
ATOM 1999 C THR A 267 10.108 29.224 -10.527 1.00 88.38 C
ATOM 2000 O THR A 267 10.786 30.045 -11.151 1.00 88.04 O
ATOM 2001 CB THR A 267 7.875 30.291 -10.758 1.00 86.90 C
ATOM 2002 OG1 THR A 267 8.122 30.872 -9.470 1.00 86.88 O
ATOM 2003 CG2 THR A 267 6.390 30.034 -10.937 1.00 84.42 C
ATOM 2004 N GLY A 268 10.581 28.501 -9.519 1.00 88.84 N
ATOM 2005 CA GLY A 268 11.958 28.617 -9.082 1.00 88.87 C
ATOM 2006 C GLY A 268 12.450 30.028 -8.819 1.00 89.07 C
ATOM 2007 O GLY A 268 13.644 30.237 -8.603 1.00 90.27 O
ATOM 2008 N LEU A 269 11.550 31.001 -8.810 1.00 87.70 N
ATOM 2009 CA LEU A 269 11.970 32.374 -8.586 1.00 87.22 C
ATOM 2010 C LEU A 269 11.823 32.887 -7.162 1.00 86.80 C
ATOM 2011 O LEU A 269 11.817 34.102 -6.941 1.00 84.64 O
ATOM 2012 CB LEU A 269 11.209 33.302 -9.524 1.00 88.82 C
ATOM 2013 CG LEU A 269 11.463 33.107 -11.014 1.00 89.57 C
ATOM 2014 CD1 LEU A 269 10.770 34.232 -11.768 1.00 89.71 C
ATOM 2015 CD2 LEU A 269 12.965 33.121 -11.302 1.00 89.67 C
ATOM 2016 N LEU A 270 11.712 31.977 -6.195 1.00 87.46 N
ATOM 2017 CA LEU A 270 11.554 32.392 -4.801 1.00 88.00 C
ATOM 2018 C LEU A 270 12.877 32.861 -4.230 1.00 87.09 C
ATOM 2019 O LEU A 270 13.886 32.161 -4.316 1.00 87.38 O
ATOM 2020 CB LEU A 270 11.010 31.256 -3.923 1.00 88.45 C
ATOM 2021 CG LEU A 270 10.779 31.677 -2.457 1.00 88.79 C
ATOM 2022 CD1 LEU A 270 9.553 32.581 -2.368 1.00 86.57 C
ATOM 2023 CD2 LEU A 270 10.605 30.447 -1.576 1.00 88.64 C
ATOM 2024 N SER A 271 12.869 34.046 -3.635 1.00 85.87 N
ATOM 2025 CA SER A 271 14.089 34.581 -3.071 1.00 85.51 C
ATOM 2026 C SER A 271 13.921 34.895 -1.581 1.00 83.98 C
ATOM 2027 O SER A 271 14.785 34.556 -0.763 1.00 83.61 O
ATOM 2028 CB SER A 271 14.494 35.831 -3.857 1.00 86.30 C
ATOM 2029 OG SER A 271 15.902 35.972 -3.874 1.00 87.42 O
ATOM 2030 N GLY A 272 12.802 35.529 -1.238 1.00 81.96 N
ATOM 2031 CA GLY A 272 12.534 35.881 0.145 1.00 78.89 C
ATOM 2032 C GLY A 272 11.132 35.468 0.550 1.00 76.86 C
ATOM 2033 O GLY A 272 10.173 35.697 -0.191 1.00 75.55 O
ATOM 2034 N LEU A 273 11.012 34.872 1.733 1.00 74.99 N
ATOM 2035 CA LEU A 273 9.722 34.399 2.228 1.00 72.30 C
ATOM 2036 C LEU A 273 9.376 34.947 3.614 1.00 70.78 C
ATOM 2037 O LEU A 273 10.217 34.986 4.511 1.00 69.89 O
ATOM 2038 CB LEU A 273 9.731 32.866 2.286 1.00 71.11 C
ATOM 2039 CG LEU A 273 8.464 32.038 2.033 1.00 69.91 C
ATOM 2040 CD1 LEU A 273 8.551 30.790 2.895 1.00 68.42 C
ATOM 2041 CD2 LEU A 273 7.194 32.820 2.360 1.00 68.44 C
ATOM 2042 N ASP A 274 8.129 35.365 3.784 1.00 70.14 N
ATOM 2043 CA ASP A 274 7.682 35.879 5.072 1.00 69.92 C
ATOM 2044 C ASP A 274 6.468 35.115 5.619 1.00 68.55 C
ATOM 2045 O ASP A 274 5.438 34.987 4.960 1.00 68.14 O
ATOM 2046 CB ASP A 274 7.371 37.384 4.978 1.00 69.92 C
ATOM 2047 CG ASP A 274 8.631 38.241 4.843 1.00 70.83 C
ATOM 2048 OD1 ASP A 274 9.631 37.966 5.546 1.00 69.82 O
ATOM 2049 OD2 ASP A 274 8.617 39.199 4.044 1.00 71.83 O
ATOM 2050 N ILE A 275 6.624 34.578 6.823 1.00 67.15 N
ATOM 2051 CA ILE A 275 5.559 33.848 7.496 1.00 65.60 C
ATOM 2052 C ILE A 275 5.306 34.638 8.774 1.00 65.13 C
ATOM 2053 O ILE A 275 5.889 34.352 9.834 1.00 63.76 O
ATOM 2054 CB ILE A 275 5.988 32.398 7.824 1.00 65.55 C
ATOM 2055 CG1 ILE A 275 5.988 31.558 6.547 1.00 65.04 C
ATOM 2056 CG2 ILE A 275 5.059 31.781 8.847 1.00 65.82 C
ATOM 2057 CD1 ILE A 275 7.140 31.856 5.621 1.00 67.21 C
ATOM 2058 N MET A 276 4.428 35.637 8.637 1.00 63.90 N
ATOM 2059 CA MET A 276 4.074 36.565 9.705 1.00 62.24 C
ATOM 2060 C MET A 276 2.698 36.347 10.298 1.00 61.84 C
ATOM 2061 O MET A 276 1.913 35.538 9.799 1.00 60.99 O
ATOM 2062 CB MET A 276 4.106 37.998 9.176 1.00 62.85 C
ATOM 2063 CG MET A 276 5.187 38.271 8.162 1.00 66.01 C
ATOM 2064 SD MET A 276 6.803 37.805 8.780 1.00 70.21 S
ATOM 2065 CE MET A 276 6.810 38.752 10.336 1.00 69.59 C
ATOM 2066 N GLU A 277 2.439 37.114 11.366 1.00 61.47 N
ATOM 2067 CA GLU A 277 1.174 37.177 12.130 1.00 61.13 C
ATOM 2068 C GLU A 277 0.691 35.965 12.914 1.00 60.56 C
ATOM 2069 O GLU A 277 -0.500 35.861 13.211 1.00 58.86 O
ATOM 2070 CB GLU A 277 0.011 37.647 11.230 1.00 60.57 C
ATOM 2071 CG GLU A 277 0.103 39.091 10.703 1.00 59.95 C
ATOM 2072 CD GLU A 277 0.285 40.120 11.796 1.00 60.38 C
ATOM 2073 OE1 GLU A 277 -0.072 39.859 12.963 1.00 60.82 O
ATOM 2074 OE2 GLU A 277 0.809 41.207 11.509 1.00 63.05 O
ATOM 2075 N VAL A 278 1.590 35.052 13.255 1.00 60.40 N
ATOM 2076 CA VAL A 278 1.173 33.886 14.012 1.00 61.42 C
ATOM 2077 C VAL A 278 1.278 34.192 15.485 1.00 61.69 C
ATOM 2078 O VAL A 278 2.370 34.465 15.957 1.00 62.84 O
ATOM 2079 CB VAL A 278 2.059 32.687 13.749 1.00 61.62 C
ATOM 2080 CG1 VAL A 278 1.773 31.632 14.795 1.00 60.45 C
ATOM 2081 CG2 VAL A 278 1.792 32.131 12.358 1.00 63.02 C
ATOM 2082 N ASN A 279 0.161 34.120 16.211 1.00 62.09 N
ATOM 2083 CA ASN A 279 0.160 34.415 17.646 1.00 62.05 C
ATOM 2084 C ASN A 279 -0.152 33.207 18.511 1.00 62.56 C
ATOM 2085 O ASN A 279 -1.275 33.074 18.980 1.00 62.08 O
ATOM 2086 CB ASN A 279 -0.866 35.500 17.964 1.00 61.37 C
ATOM 2087 CG ASN A 279 -0.414 36.409 19.091 1.00 60.61 C
ATOM 2088 OD1 ASN A 279 0.356 35.997 19.964 1.00 58.30 O
ATOM 2089 ND2 ASN A 279 -0.893 37.654 19.080 1.00 57.50 N
ATOM 2090 N PRO A 280 0.841 32.323 18.751 1.00 64.39 N
ATOM 2091 CA PRO A 280 0.758 31.089 19.553 1.00 67.08 C
ATOM 2092 C PRO A 280 0.000 31.187 20.874 1.00 69.58 C
ATOM 2093 O PRO A 280 -0.114 30.209 21.614 1.00 69.61 O
ATOM 2094 CB PRO A 280 2.225 30.718 19.757 1.00 65.11 C
ATOM 2095 CG PRO A 280 2.812 31.096 18.477 1.00 64.36 C
ATOM 2096 CD PRO A 280 2.204 32.473 18.217 1.00 64.19 C
ATOM 2097 N THR A 281 -0.520 32.374 21.152 1.00 72.57 N
ATOM 2098 CA THR A 281 -1.262 32.626 22.371 1.00 75.80 C
ATOM 2099 C THR A 281 -2.721 32.934 22.061 1.00 76.44 C
ATOM 2100 O THR A 281 -3.609 32.663 22.867 1.00 76.53 O
ATOM 2101 CB THR A 281 -0.631 33.801 23.132 1.00 76.94 C
ATOM 2102 OG1 THR A 281 -0.277 34.831 22.201 1.00 79.55 O
ATOM 2103 CG2 THR A 281 0.622 33.350 23.862 1.00 77.78 C
ATOM 2104 N LEU A 282 -2.967 33.500 20.888 1.00 78.33 N
ATOM 2105 CA LEU A 282 -4.326 33.830 20.498 1.00 80.29 C
ATOM 2106 C LEU A 282 -5.054 32.603 19.979 1.00 83.19 C
ATOM 2107 O LEU A 282 -5.489 32.566 18.831 1.00 85.02 O
ATOM 2108 CB LEU A 282 -4.333 34.936 19.439 1.00 77.40 C
ATOM 2109 CG LEU A 282 -3.728 36.239 19.952 1.00 75.93 C
ATOM 2110 CD1 LEU A 282 -3.933 37.352 18.951 1.00 75.40 C
ATOM 2111 CD2 LEU A 282 -4.375 36.586 21.269 1.00 75.90 C
ATOM 2112 N GLY A 283 -5.172 31.592 20.833 1.00 85.07 N
ATOM 2113 CA GLY A 283 -5.877 30.382 20.451 1.00 86.60 C
ATOM 2114 C GLY A 283 -7.068 30.132 21.368 1.00 87.56 C
ATOM 2115 O GLY A 283 -6.903 30.043 22.593 1.00 88.62 O
ATOM 2116 N LYS A 284 -8.264 30.039 20.780 1.00 86.77 N
ATOM 2117 CA LYS A 284 -9.495 29.789 21.537 1.00 85.88 C
ATOM 2118 C LYS A 284 -9.302 28.474 22.283 1.00 85.02 C
ATOM 2119 O LYS A 284 -9.770 28.309 23.414 1.00 84.12 O
ATOM 2120 CB LYS A 284 -10.695 29.664 20.588 1.00 87.29 C
ATOM 2121 CG LYS A 284 -12.009 30.266 21.094 1.00 87.71 C
ATOM 2122 CD LYS A 284 -12.186 31.714 20.625 1.00 87.88 C
ATOM 2123 CE LYS A 284 -11.075 32.619 21.155 1.00 88.18 C
ATOM 2124 NZ LYS A 284 -11.107 33.997 20.599 1.00 87.29 N
ATOM 2125 N THR A 285 -8.608 27.547 21.620 1.00 84.15 N
ATOM 2126 CA THR A 285 -8.289 26.234 22.164 1.00 83.26 C
ATOM 2127 C THR A 285 -6.926 25.820 21.623 1.00 82.99 C
ATOM 2128 O THR A 285 -6.533 26.209 20.521 1.00 81.31 O
ATOM 2129 CB THR A 285 -9.291 25.159 21.725 1.00 83.35 C
ATOM 2130 OG1 THR A 285 -9.041 24.798 20.359 1.00 84.05 O
ATOM 2131 CG2 THR A 285 -10.711 25.672 21.857 1.00 84.61 C
ATOM 2132 N PRO A 286 -6.188 25.019 22.399 1.00 83.41 N
ATOM 2133 CA PRO A 286 -4.861 24.527 22.027 1.00 82.95 C
ATOM 2134 C PRO A 286 -4.768 24.008 20.593 1.00 82.76 C
ATOM 2135 O PRO A 286 -3.768 24.247 19.910 1.00 83.94 O
ATOM 2136 CB PRO A 286 -4.607 23.447 23.067 1.00 83.43 C
ATOM 2137 CG PRO A 286 -5.219 24.065 24.297 1.00 83.83 C
ATOM 2138 CD PRO A 286 -6.545 24.579 23.762 1.00 84.08 C
ATOM 2139 N GLU A 287 -5.797 23.293 20.145 1.00 81.54 N
ATOM 2140 CA GLU A 287 -5.823 22.768 18.781 1.00 80.48 C
ATOM 2141 C GLU A 287 -5.679 23.922 17.777 1.00 79.49 C
ATOM 2142 O GLU A 287 -4.760 23.928 16.949 1.00 78.67 O
ATOM 2143 CB GLU A 287 -7.139 22.008 18.546 1.00 82.25 C
ATOM 2144 CG GLU A 287 -7.899 22.331 17.237 1.00 83.83 C
ATOM 2145 CD GLU A 287 -7.189 21.856 15.960 1.00 84.57 C
ATOM 2146 OE1 GLU A 287 -6.168 22.465 15.578 1.00 85.56 O
ATOM 2147 OE2 GLU A 287 -7.652 20.873 15.332 1.00 84.28 O
ATOM 2148 N GLU A 288 -6.590 24.893 17.864 1.00 77.25 N
ATOM 2149 CA GLU A 288 -6.578 26.060 16.985 1.00 73.95 C
ATOM 2150 C GLU A 288 -5.168 26.565 16.751 1.00 72.69 C
ATOM 2151 O GLU A 288 -4.801 26.892 15.627 1.00 72.64 O
ATOM 2152 CB GLU A 288 -7.408 27.186 17.583 1.00 72.46 C
ATOM 2153 CG GLU A 288 -8.867 26.839 17.761 1.00 70.50 C
ATOM 2154 CD GLU A 288 -9.740 28.075 17.833 1.00 69.40 C
ATOM 2155 OE1 GLU A 288 -9.176 29.195 17.863 1.00 68.54 O
ATOM 2156 OE2 GLU A 288 -10.986 27.930 17.862 1.00 68.62 O
ATOM 2157 N VAL A 289 -4.385 26.652 17.823 1.00 71.45 N
ATOM 2158 CA VAL A 289 -2.999 27.094 17.707 1.00 70.18 C
ATOM 2159 C VAL A 289 -2.322 26.039 16.841 1.00 69.20 C
ATOM 2160 O VAL A 289 -1.995 26.299 15.684 1.00 68.99 O
ATOM 2161 CB VAL A 289 -2.278 27.180 19.102 1.00 69.79 C
ATOM 2162 CG1 VAL A 289 -0.841 27.657 18.928 1.00 67.62 C
ATOM 2163 CG2 VAL A 289 -3.021 28.149 20.022 1.00 69.71 C
ATOM 2164 N THR A 290 -2.133 24.846 17.401 1.00 68.00 N
ATOM 2165 CA THR A 290 -1.509 23.739 16.676 1.00 66.88 C
ATOM 2166 C THR A 290 -1.893 23.766 15.194 1.00 66.56 C
ATOM 2167 O THR A 290 -1.036 23.653 14.309 1.00 66.19 O
ATOM 2168 CB THR A 290 -1.936 22.390 17.275 1.00 65.35 C
ATOM 2169 OG1 THR A 290 -1.423 22.294 18.604 1.00 63.64 O
ATOM 2170 CG2 THR A 290 -1.408 21.238 16.442 1.00 64.85 C
ATOM 2171 N ARG A 291 -3.191 23.909 14.942 1.00 65.26 N
ATOM 2172 CA ARG A 291 -3.718 23.973 13.580 1.00 64.06 C
ATOM 2173 C ARG A 291 -2.921 25.057 12.869 1.00 63.34 C
ATOM 2174 O ARG A 291 -2.143 24.797 11.946 1.00 64.70 O
ATOM 2175 CB ARG A 291 -5.196 24.367 13.622 1.00 61.65 C
ATOM 2176 CG ARG A 291 -5.919 24.347 12.298 1.00 58.64 C
ATOM 2177 CD ARG A 291 -7.379 24.710 12.527 1.00 56.90 C
ATOM 2178 NE ARG A 291 -7.893 24.016 13.704 1.00 57.01 N
ATOM 2179 CZ ARG A 291 -9.040 24.296 14.320 1.00 57.06 C
ATOM 2180 NH1 ARG A 291 -9.827 25.272 13.868 1.00 57.97 N
ATOM 2181 NH2 ARG A 291 -9.387 23.621 15.413 1.00 55.48 N
ATOM 2182 N THR A 292 -3.121 26.277 13.346 1.00 61.05 N
ATOM 2183 CA THR A 292 -2.471 27.461 12.829 1.00 58.67 C
ATOM 2184 C THR A 292 -0.985 27.235 12.589 1.00 58.47 C
ATOM 2185 O THR A 292 -0.430 27.647 11.576 1.00 57.49 O
ATOM 2186 CB THR A 292 -2.650 28.609 13.828 1.00 58.81 C
ATOM 2187 OG1 THR A 292 -4.053 28.792 14.112 1.00 56.48 O
ATOM 2188 CG2 THR A 292 -2.042 29.895 13.267 1.00 59.71 C
ATOM 2189 N VAL A 293 -0.349 26.560 13.533 1.00 59.78 N
ATOM 2190 CA VAL A 293 1.075 26.284 13.456 1.00 58.82 C
ATOM 2191 C VAL A 293 1.489 25.365 12.320 1.00 58.73 C
ATOM 2192 O VAL A 293 2.366 25.709 11.539 1.00 60.24 O
ATOM 2193 CB VAL A 293 1.566 25.700 14.777 1.00 57.64 C
ATOM 2194 CG1 VAL A 293 2.892 25.021 14.587 1.00 59.61 C
ATOM 2195 CG2 VAL A 293 1.690 26.812 15.794 1.00 56.78 C
ATOM 2196 N ASN A 294 0.873 24.199 12.216 1.00 59.01 N
ATOM 2197 CA ASN A 294 1.245 23.271 11.151 1.00 59.52 C
ATOM 2198 C ASN A 294 0.933 23.817 9.764 1.00 57.04 C
ATOM 2199 O ASN A 294 1.787 23.810 8.886 1.00 56.04 O
ATOM 2200 CB ASN A 294 0.550 21.929 11.369 1.00 62.65 C
ATOM 2201 CG ASN A 294 0.814 21.364 12.757 1.00 65.74 C
ATOM 2202 OD1 ASN A 294 1.973 21.114 13.136 1.00 65.73 O
ATOM 2203 ND2 ASN A 294 -0.259 21.172 13.531 1.00 65.75 N
ATOM 2204 N THR A 295 -0.290 24.296 9.572 1.00 55.78 N
ATOM 2205 CA THR A 295 -0.697 24.869 8.289 1.00 53.42 C
ATOM 2206 C THR A 295 0.335 25.924 7.851 1.00 51.63 C
ATOM 2207 O THR A 295 0.690 26.035 6.669 1.00 51.32 O
ATOM 2208 CB THR A 295 -2.105 25.511 8.402 1.00 51.74 C
ATOM 2209 OG1 THR A 295 -2.468 26.108 7.156 1.00 51.03 O
ATOM 2210 CG2 THR A 295 -2.114 26.581 9.471 1.00 52.14 C
ATOM 2211 N ALA A 296 0.814 26.693 8.817 1.00 48.87 N
ATOM 2212 CA ALA A 296 1.816 27.692 8.537 1.00 48.83 C
ATOM 2213 C ALA A 296 3.061 26.934 8.066 1.00 49.86 C
ATOM 2214 O ALA A 296 3.551 27.129 6.951 1.00 48.11 O
ATOM 2215 CB ALA A 296 2.108 28.464 9.788 1.00 48.98 C
ATOM 2216 N VAL A 297 3.542 26.049 8.934 1.00 51.36 N
ATOM 2217 CA VAL A 297 4.700 25.199 8.665 1.00 53.60 C
ATOM 2218 C VAL A 297 4.558 24.572 7.285 1.00 55.78 C
ATOM 2219 O VAL A 297 5.479 24.606 6.459 1.00 58.28 O
ATOM 2220 CB VAL A 297 4.783 24.044 9.699 1.00 53.14 C
ATOM 2221 CG1 VAL A 297 5.801 23.003 9.267 1.00 50.59 C
ATOM 2222 CG2 VAL A 297 5.142 24.600 11.063 1.00 54.44 C
ATOM 2223 N ALA A 298 3.393 23.989 7.051 1.00 56.73 N
ATOM 2224 CA ALA A 298 3.102 23.335 5.798 1.00 58.92 C
ATOM 2225 C ALA A 298 3.282 24.318 4.654 1.00 61.14 C
ATOM 2226 O ALA A 298 3.875 23.975 3.628 1.00 62.85 O
ATOM 2227 CB ALA A 298 1.671 22.798 5.820 1.00 58.61 C
ATOM 2228 N LEU A 299 2.770 25.537 4.819 1.00 60.82 N
ATOM 2229 CA LEU A 299 2.892 26.527 3.759 1.00 61.09 C
ATOM 2230 C LEU A 299 4.352 26.834 3.418 1.00 62.91 C
ATOM 2231 O LEU A 299 4.652 27.247 2.300 1.00 65.11 O
ATOM 2232 CB LEU A 299 2.187 27.830 4.139 1.00 57.81 C
ATOM 2233 CG LEU A 299 0.665 27.992 4.080 1.00 55.38 C
ATOM 2234 CD1 LEU A 299 0.377 29.446 4.314 1.00 53.96 C
ATOM 2235 CD2 LEU A 299 0.075 27.601 2.741 1.00 51.97 C
ATOM 2236 N THR A 300 5.260 26.643 4.369 1.00 62.76 N
ATOM 2237 CA THR A 300 6.666 26.925 4.104 1.00 62.65 C
ATOM 2238 C THR A 300 7.231 25.849 3.206 1.00 61.32 C
ATOM 2239 O THR A 300 7.636 26.123 2.081 1.00 59.77 O
ATOM 2240 CB THR A 300 7.494 26.957 5.399 1.00 63.73 C
ATOM 2241 OG1 THR A 300 6.782 27.679 6.410 1.00 65.35 O
ATOM 2242 CG2 THR A 300 8.831 27.658 5.157 1.00 63.25 C
ATOM 2243 N LEU A 301 7.252 24.628 3.727 1.00 60.60 N
ATOM 2244 CA LEU A 301 7.730 23.460 2.996 1.00 62.25 C
ATOM 2245 C LEU A 301 7.095 23.374 1.615 1.00 62.75 C
ATOM 2246 O LEU A 301 7.509 22.579 0.779 1.00 61.14 O
ATOM 2247 CB LEU A 301 7.377 22.186 3.763 1.00 62.64 C
ATOM 2248 CG LEU A 301 7.940 22.064 5.174 1.00 63.60 C
ATOM 2249 CD1 LEU A 301 7.288 20.909 5.926 1.00 64.16 C
ATOM 2250 CD2 LEU A 301 9.434 21.856 5.060 1.00 64.47 C
ATOM 2251 N SER A 302 6.060 24.173 1.393 1.00 65.66 N
ATOM 2252 CA SER A 302 5.378 24.177 0.108 1.00 67.63 C
ATOM 2253 C SER A 302 6.240 24.982 -0.849 1.00 69.13 C
ATOM 2254 O SER A 302 6.601 24.513 -1.931 1.00 70.32 O
ATOM 2255 CB SER A 302 3.994 24.810 0.247 1.00 67.19 C
ATOM 2256 OG SER A 302 3.224 24.576 -0.915 1.00 69.11 O
ATOM 2257 N CYS A 303 6.587 26.189 -0.414 1.00 70.31 N
ATOM 2258 CA CYS A 303 7.433 27.101 -1.173 1.00 71.32 C
ATOM 2259 C CYS A 303 8.792 26.478 -1.479 1.00 72.31 C
ATOM 2260 O CYS A 303 9.553 26.990 -2.303 1.00 72.83 O
ATOM 2261 CB CYS A 303 7.672 28.363 -0.358 1.00 71.03 C
ATOM 2262 SG CYS A 303 6.178 29.094 0.236 1.00 72.69 S
ATOM 2263 N PHE A 304 9.096 25.372 -0.811 1.00 73.09 N
ATOM 2264 CA PHE A 304 10.379 24.725 -0.991 1.00 72.61 C
ATOM 2265 C PHE A 304 10.356 23.314 -1.551 1.00 73.36 C
ATOM 2266 O PHE A 304 11.192 22.488 -1.180 1.00 74.39 O
ATOM 2267 CB PHE A 304 11.119 24.742 0.336 1.00 71.80 C
ATOM 2268 CG PHE A 304 11.378 26.121 0.851 1.00 71.95 C
ATOM 2269 CD1 PHE A 304 12.400 26.896 0.314 1.00 72.36 C
ATOM 2270 CD2 PHE A 304 10.584 26.662 1.850 1.00 72.11 C
ATOM 2271 CE1 PHE A 304 12.627 28.193 0.766 1.00 71.54 C
ATOM 2272 CE2 PHE A 304 10.804 27.957 2.308 1.00 72.05 C
ATOM 2273 CZ PHE A 304 11.829 28.723 1.763 1.00 71.30 C
ATOM 2274 N GLY A 305 9.409 23.026 -2.438 1.00 72.86 N
ATOM 2275 CA GLY A 305 9.389 21.703 -3.027 1.00 72.03 C
ATOM 2276 C GLY A 305 8.143 20.866 -2.864 1.00 71.73 C
ATOM 2277 O GLY A 305 7.430 20.623 -3.845 1.00 72.28 O
ATOM 2278 N THR A 306 7.891 20.412 -1.636 1.00 70.88 N
ATOM 2279 CA THR A 306 6.731 19.577 -1.347 1.00 69.05 C
ATOM 2280 C THR A 306 5.539 19.961 -2.227 1.00 69.72 C
ATOM 2281 O THR A 306 5.135 21.137 -2.311 1.00 68.72 O
ATOM 2282 CB THR A 306 6.312 19.672 0.117 1.00 66.56 C
ATOM 2283 OG1 THR A 306 7.471 19.823 0.936 1.00 65.69 O
ATOM 2284 CG2 THR A 306 5.598 18.407 0.527 1.00 65.22 C
ATOM 2285 N LYS A 307 5.001 18.946 -2.895 1.00 69.29 N
ATOM 2286 CA LYS A 307 3.871 19.089 -3.799 1.00 69.35 C
ATOM 2287 C LYS A 307 2.765 18.223 -3.215 1.00 68.64 C
ATOM 2288 O LYS A 307 3.046 17.325 -2.434 1.00 68.97 O
ATOM 2289 CB LYS A 307 4.298 18.609 -5.190 1.00 69.94 C
ATOM 2290 CG LYS A 307 5.658 19.203 -5.601 1.00 71.55 C
ATOM 2291 CD LYS A 307 6.367 18.403 -6.698 1.00 75.08 C
ATOM 2292 CE LYS A 307 5.767 18.656 -8.069 1.00 76.43 C
ATOM 2293 NZ LYS A 307 5.923 20.091 -8.461 1.00 77.73 N
ATOM 2294 N ARG A 308 1.512 18.493 -3.552 1.00 68.82 N
ATOM 2295 CA ARG A 308 0.440 17.684 -2.995 1.00 69.63 C
ATOM 2296 C ARG A 308 0.226 16.403 -3.799 1.00 73.65 C
ATOM 2297 O ARG A 308 -0.750 15.659 -3.593 1.00 74.33 O
ATOM 2298 CB ARG A 308 -0.853 18.501 -2.898 1.00 65.67 C
ATOM 2299 CG ARG A 308 -1.047 19.134 -1.519 1.00 61.84 C
ATOM 2300 CD ARG A 308 -2.286 19.993 -1.437 1.00 56.86 C
ATOM 2301 NE ARG A 308 -2.127 21.204 -2.225 1.00 51.40 N
ATOM 2302 CZ ARG A 308 -3.122 21.812 -2.855 1.00 51.56 C
ATOM 2303 NH1 ARG A 308 -4.353 21.317 -2.790 1.00 50.69 N
ATOM 2304 NH2 ARG A 308 -2.887 22.911 -3.554 1.00 53.11 N
ATOM 2305 N GLU A 309 1.156 16.140 -4.711 1.00 76.34 N
ATOM 2306 CA GLU A 309 1.076 14.947 -5.524 1.00 78.81 C
ATOM 2307 C GLU A 309 2.193 13.998 -5.129 1.00 81.14 C
ATOM 2308 O GLU A 309 2.209 12.835 -5.537 1.00 80.97 O
ATOM 2309 CB GLU A 309 1.179 15.304 -7.003 1.00 78.42 C
ATOM 2310 CG GLU A 309 2.482 15.938 -7.395 1.00 79.83 C
ATOM 2311 CD GLU A 309 2.793 15.708 -8.856 1.00 80.70 C
ATOM 2312 OE1 GLU A 309 2.001 16.166 -9.715 1.00 79.92 O
ATOM 2313 OE2 GLU A 309 3.827 15.059 -9.143 1.00 80.64 O
ATOM 2314 N GLY A 310 3.125 14.500 -4.327 1.00 84.23 N
ATOM 2315 CA GLY A 310 4.237 13.681 -3.880 1.00 88.85 C
ATOM 2316 C GLY A 310 5.613 14.225 -4.234 1.00 92.10 C
ATOM 2317 O GLY A 310 5.745 15.212 -4.951 1.00 91.07 O
ATOM 2318 N ASN A 311 6.641 13.555 -3.726 1.00 97.12 N
ATOM 2319 CA ASN A 311 8.038 13.912 -3.960 1.00102.29 C
ATOM 2320 C ASN A 311 8.864 12.631 -3.775 1.00106.18 C
ATOM 2321 O ASN A 311 8.584 11.834 -2.871 1.00107.49 O
ATOM 2322 CB ASN A 311 8.512 14.969 -2.946 1.00102.14 C
ATOM 2323 CG ASN A 311 7.845 16.330 -3.141 1.00102.71 C
ATOM 2324 OD1 ASN A 311 8.009 16.972 -4.178 1.00103.04 O
ATOM 2325 ND2 ASN A 311 7.093 16.775 -2.135 1.00102.31 N
ATOM 2326 N HIS A 312 9.863 12.426 -4.634 1.00109.68 N
ATOM 2327 CA HIS A 312 10.730 11.247 -4.548 1.00112.52 C
ATOM 2328 C HIS A 312 12.149 11.606 -5.000 1.00113.52 C
ATOM 2329 O HIS A 312 12.341 12.169 -6.084 1.00113.20 O
ATOM 2330 CB HIS A 312 10.179 10.102 -5.414 1.00114.32 C
ATOM 2331 CG HIS A 312 10.305 10.339 -6.891 1.00117.06 C
ATOM 2332 ND1 HIS A 312 9.493 11.212 -7.578 1.00118.23 N
ATOM 2333 CD2 HIS A 312 11.180 9.839 -7.798 1.00118.21 C
ATOM 2334 CE1 HIS A 312 9.862 11.245 -8.850 1.00118.99 C
ATOM 2335 NE2 HIS A 312 10.882 10.422 -9.008 1.00119.29 N
ATOM 2336 N LYS A 313 13.139 11.291 -4.168 1.00114.77 N
ATOM 2337 CA LYS A 313 14.533 11.590 -4.494 1.00116.23 C
ATOM 2338 C LYS A 313 14.857 11.036 -5.879 1.00117.88 C
ATOM 2339 O LYS A 313 14.705 9.838 -6.127 1.00118.20 O
ATOM 2340 CB LYS A 313 15.458 10.969 -3.447 1.00115.55 C
ATOM 2341 CG LYS A 313 15.169 11.415 -2.019 1.00114.52 C
ATOM 2342 CD LYS A 313 16.016 10.625 -1.029 1.00113.62 C
ATOM 2343 CE LYS A 313 15.671 10.946 0.417 1.00111.93 C
ATOM 2344 NZ LYS A 313 16.459 10.099 1.360 1.00109.72 N
ATOM 2345 N PRO A 314 15.298 11.907 -6.806 1.00119.02 N
ATOM 2346 CA PRO A 314 15.635 11.490 -8.170 1.00119.57 C
ATOM 2347 C PRO A 314 16.822 10.538 -8.246 1.00120.29 C
ATOM 2348 O PRO A 314 17.581 10.378 -7.281 1.00119.94 O
ATOM 2349 CB PRO A 314 15.931 12.812 -8.877 1.00119.10 C
ATOM 2350 CG PRO A 314 15.115 13.800 -8.115 1.00119.32 C
ATOM 2351 CD PRO A 314 15.368 13.373 -6.690 1.00119.29 C
ATOM 2352 N GLU A 315 16.966 9.913 -9.411 1.00120.71 N
ATOM 2353 CA GLU A 315 18.051 8.979 -9.682 1.00120.73 C
ATOM 2354 C GLU A 315 18.044 7.734 -8.807 1.00119.42 C
ATOM 2355 O GLU A 315 18.984 6.937 -8.841 1.00119.59 O
ATOM 2356 CB GLU A 315 19.399 9.698 -9.559 1.00122.78 C
ATOM 2357 CG GLU A 315 19.665 10.686 -10.692 1.00124.50 C
ATOM 2358 CD GLU A 315 20.924 11.503 -10.482 1.00125.58 C
ATOM 2359 OE1 GLU A 315 21.290 12.260 -11.404 1.00125.94 O
ATOM 2360 OE2 GLU A 315 21.541 11.395 -9.399 1.00126.86 O
ATOM 2361 N THR A 316 16.990 7.569 -8.017 1.00117.54 N
ATOM 2362 CA THR A 316 16.881 6.392 -7.168 1.00115.78 C
ATOM 2363 C THR A 316 15.745 5.555 -7.728 1.00113.97 C
ATOM 2364 O THR A 316 14.675 6.080 -8.034 1.00113.84 O
ATOM 2365 CB THR A 316 16.575 6.758 -5.686 1.00116.09 C
ATOM 2366 OG1 THR A 316 17.638 7.566 -5.163 1.00116.18 O
ATOM 2367 CG2 THR A 316 16.447 5.489 -4.831 1.00115.05 C
ATOM 2368 N ASP A 317 16.003 4.260 -7.894 1.00111.82 N
ATOM 2369 CA ASP A 317 15.007 3.326 -8.405 1.00109.43 C
ATOM 2370 C ASP A 317 14.309 2.721 -7.186 1.00109.27 C
ATOM 2371 O ASP A 317 14.869 1.865 -6.488 1.00109.58 O
ATOM 2372 CB ASP A 317 15.689 2.242 -9.262 1.00106.72 C
ATOM 2373 CG ASP A 317 14.713 1.202 -9.810 1.00104.53 C
ATOM 2374 OD1 ASP A 317 13.709 1.574 -10.452 1.00103.22 O
ATOM 2375 OD2 ASP A 317 14.961 -0.004 -9.607 1.00102.42 O
ATOM 2376 N TYR A 318 13.093 3.207 -6.922 1.00108.87 N
ATOM 2377 CA TYR A 318 12.279 2.750 -5.798 1.00108.47 C
ATOM 2378 C TYR A 318 11.649 1.403 -6.125 1.00109.21 C
ATOM 2379 O TYR A 318 10.792 0.918 -5.399 1.00108.22 O
ATOM 2380 CB TYR A 318 11.181 3.775 -5.486 1.00107.18 C
ATOM 2381 CG TYR A 318 11.632 5.027 -4.738 1.00105.92 C
ATOM 2382 CD1 TYR A 318 11.945 4.983 -3.370 1.00104.92 C
ATOM 2383 CD2 TYR A 318 11.713 6.264 -5.387 1.00104.89 C
ATOM 2384 CE1 TYR A 318 12.323 6.145 -2.669 1.00103.58 C
ATOM 2385 CE2 TYR A 318 12.091 7.430 -4.696 1.00104.05 C
ATOM 2386 CZ TYR A 318 12.392 7.362 -3.341 1.00103.64 C
ATOM 2387 OH TYR A 318 12.761 8.507 -2.670 1.00102.85 O
ATOM 2388 N LEU A 319 12.089 0.814 -7.232 1.00111.27 N
ATOM 2389 CA LEU A 319 11.612 -0.493 -7.690 1.00112.79 C
ATOM 2390 C LEU A 319 12.650 -1.591 -7.385 1.00113.76 C
ATOM 2391 O LEU A 319 12.326 -2.521 -6.602 1.00114.70 O
ATOM 2392 CB LEU A 319 11.341 -0.461 -9.203 1.00111.81 C
ATOM 2393 CG LEU A 319 10.062 0.223 -9.681 1.00110.60 C
ATOM 2394 CD1 LEU A 319 10.039 0.280 -11.202 1.00109.61 C
ATOM 2395 CD2 LEU A 319 8.861 -0.550 -9.149 1.00109.90 C
TER 2396 LEU A 319
ATOM 2397 N LYS B 6 -32.819 -1.014 -13.478 1.00 99.08 N
ATOM 2398 CA LYS B 6 -31.536 -1.722 -13.166 1.00 99.00 C
ATOM 2399 C LYS B 6 -31.542 -2.347 -11.758 1.00 98.40 C
ATOM 2400 O LYS B 6 -32.358 -1.982 -10.901 1.00 97.61 O
ATOM 2401 CB LYS B 6 -30.365 -0.743 -13.323 1.00 99.66 C
ATOM 2402 CG LYS B 6 -29.397 -1.076 -14.463 1.00 99.85 C
ATOM 2403 CD LYS B 6 -28.354 -2.113 -14.025 1.00100.73 C
ATOM 2404 CE LYS B 6 -27.313 -2.399 -15.109 1.00101.23 C
ATOM 2405 NZ LYS B 6 -26.192 -3.258 -14.609 1.00100.75 N
ATOM 2406 N PRO B 7 -30.634 -3.312 -11.510 1.00 97.80 N
ATOM 2407 CA PRO B 7 -30.548 -3.981 -10.212 1.00 97.15 C
ATOM 2408 C PRO B 7 -29.293 -3.635 -9.433 1.00 96.32 C
ATOM 2409 O PRO B 7 -28.236 -3.398 -10.013 1.00 96.22 O
ATOM 2410 CB PRO B 7 -30.553 -5.442 -10.605 1.00 97.20 C
ATOM 2411 CG PRO B 7 -29.608 -5.411 -11.777 1.00 97.43 C
ATOM 2412 CD PRO B 7 -29.947 -4.122 -12.532 1.00 97.47 C
ATOM 2413 N ILE B 8 -29.421 -3.643 -8.111 1.00 95.57 N
ATOM 2414 CA ILE B 8 -28.311 -3.337 -7.219 1.00 94.69 C
ATOM 2415 C ILE B 8 -28.152 -4.437 -6.193 1.00 94.01 C
ATOM 2416 O ILE B 8 -29.137 -4.836 -5.565 1.00 93.77 O
ATOM 2417 CB ILE B 8 -28.554 -2.025 -6.404 1.00 94.64 C
ATOM 2418 CG1 ILE B 8 -28.668 -0.814 -7.330 1.00 93.94 C
ATOM 2419 CG2 ILE B 8 -27.426 -1.816 -5.399 1.00 93.66 C
ATOM 2420 CD1 ILE B 8 -27.465 -0.620 -8.200 1.00 94.03 C
ATOM 2421 N GLU B 9 -26.933 -4.946 -6.035 1.00 92.63 N
ATOM 2422 CA GLU B 9 -26.718 -5.928 -4.984 1.00 91.96 C
ATOM 2423 C GLU B 9 -25.601 -5.375 -4.113 1.00 91.79 C
ATOM 2424 O GLU B 9 -24.555 -4.951 -4.620 1.00 91.03 O
ATOM 2425 CB GLU B 9 -26.322 -7.317 -5.496 1.00 91.63 C
ATOM 2426 CG GLU B 9 -26.625 -8.387 -4.422 1.00 91.26 C
ATOM 2427 CD GLU B 9 -25.767 -9.642 -4.488 1.00 91.17 C
ATOM 2428 OE1 GLU B 9 -25.979 -10.542 -3.645 1.00 89.98 O
ATOM 2429 OE2 GLU B 9 -24.886 -9.731 -5.364 1.00 91.53 O
ATOM 2430 N ILE B 10 -25.841 -5.355 -2.805 1.00 91.97 N
ATOM 2431 CA ILE B 10 -24.868 -4.835 -1.851 1.00 92.34 C
ATOM 2432 C ILE B 10 -24.090 -5.955 -1.181 1.00 91.65 C
ATOM 2433 O ILE B 10 -24.674 -6.926 -0.705 1.00 91.67 O
ATOM 2434 CB ILE B 10 -25.560 -4.002 -0.749 1.00 93.05 C
ATOM 2435 CG1 ILE B 10 -26.280 -2.813 -1.392 1.00 93.78 C
ATOM 2436 CG2 ILE B 10 -24.527 -3.546 0.297 1.00 91.79 C
ATOM 2437 CD1 ILE B 10 -27.076 -1.953 -0.430 1.00 92.99 C
ATOM 2438 N ILE B 11 -22.769 -5.809 -1.144 1.00 90.86 N
ATOM 2439 CA ILE B 11 -21.893 -6.796 -0.523 1.00 89.22 C
ATOM 2440 C ILE B 11 -21.182 -6.116 0.634 1.00 88.75 C
ATOM 2441 O ILE B 11 -20.663 -5.012 0.489 1.00 87.87 O
ATOM 2442 CB ILE B 11 -20.806 -7.314 -1.501 1.00 88.97 C
ATOM 2443 CG1 ILE B 11 -21.454 -7.816 -2.786 1.00 87.62 C
ATOM 2444 CG2 ILE B 11 -19.995 -8.418 -0.847 1.00 88.11 C
ATOM 2445 CD1 ILE B 11 -22.436 -8.922 -2.578 1.00 88.39 C
ATOM 2446 N GLY B 12 -21.170 -6.778 1.783 1.00 88.08 N
ATOM 2447 CA GLY B 12 -20.496 -6.220 2.934 1.00 86.84 C
ATOM 2448 C GLY B 12 -19.152 -6.902 3.049 1.00 85.81 C
ATOM 2449 O GLY B 12 -19.084 -8.129 3.034 1.00 86.11 O
ATOM 2450 N ALA B 13 -18.083 -6.118 3.157 1.00 84.95 N
ATOM 2451 CA ALA B 13 -16.736 -6.670 3.267 1.00 83.69 C
ATOM 2452 C ALA B 13 -16.116 -6.379 4.632 1.00 83.14 C
ATOM 2453 O ALA B 13 -14.960 -5.963 4.708 1.00 83.23 O
ATOM 2454 CB ALA B 13 -15.843 -6.091 2.148 1.00 82.18 C
ATOM 2455 N PRO B 14 -16.866 -6.610 5.725 1.00 82.39 N
ATOM 2456 CA PRO B 14 -16.335 -6.348 7.067 1.00 82.40 C
ATOM 2457 C PRO B 14 -14.951 -6.948 7.271 1.00 83.87 C
ATOM 2458 O PRO B 14 -14.822 -8.053 7.782 1.00 84.25 O
ATOM 2459 CB PRO B 14 -17.379 -6.981 7.972 1.00 81.00 C
ATOM 2460 CG PRO B 14 -17.903 -8.108 7.135 1.00 80.99 C
ATOM 2461 CD PRO B 14 -18.081 -7.435 5.811 1.00 81.10 C
ATOM 2462 N PHE B 15 -13.920 -6.206 6.878 1.00 86.12 N
ATOM 2463 CA PHE B 15 -12.538 -6.669 6.991 1.00 87.98 C
ATOM 2464 C PHE B 15 -11.655 -5.549 7.543 1.00 88.21 C
ATOM 2465 O PHE B 15 -12.094 -4.398 7.625 1.00 88.51 O
ATOM 2466 CB PHE B 15 -12.039 -7.106 5.611 1.00 88.79 C
ATOM 2467 CG PHE B 15 -10.746 -7.854 5.641 1.00 91.15 C
ATOM 2468 CD1 PHE B 15 -10.569 -8.926 6.512 1.00 92.70 C
ATOM 2469 CD2 PHE B 15 -9.710 -7.512 4.775 1.00 91.85 C
ATOM 2470 CE1 PHE B 15 -9.381 -9.657 6.514 1.00 93.41 C
ATOM 2471 CE2 PHE B 15 -8.519 -8.235 4.766 1.00 93.06 C
ATOM 2472 CZ PHE B 15 -8.350 -9.308 5.637 1.00 93.27 C
ATOM 2473 N SER B 16 -10.418 -5.863 7.918 1.00 87.82 N
ATOM 2474 CA SER B 16 -9.554 -4.819 8.453 1.00 88.48 C
ATOM 2475 C SER B 16 -8.067 -5.146 8.534 1.00 90.22 C
ATOM 2476 O SER B 16 -7.265 -4.281 8.874 1.00 90.56 O
ATOM 2477 CB SER B 16 -10.045 -4.407 9.844 1.00 86.82 C
ATOM 2478 OG SER B 16 -9.873 -5.438 10.789 1.00 83.07 O
ATOM 2479 N LYS B 17 -7.689 -6.379 8.227 1.00 92.02 N
ATOM 2480 CA LYS B 17 -6.282 -6.764 8.305 1.00 93.42 C
ATOM 2481 C LYS B 17 -5.400 -6.006 7.309 1.00 93.24 C
ATOM 2482 O LYS B 17 -4.166 -6.036 7.394 1.00 92.98 O
ATOM 2483 CB LYS B 17 -6.143 -8.280 8.105 1.00 95.56 C
ATOM 2484 CG LYS B 17 -5.779 -9.083 9.372 1.00 96.54 C
ATOM 2485 CD LYS B 17 -6.682 -8.748 10.555 1.00 97.30 C
ATOM 2486 CE LYS B 17 -6.585 -9.807 11.644 1.00 97.15 C
ATOM 2487 NZ LYS B 17 -7.170 -11.098 11.181 1.00 96.57 N
ATOM 2488 N GLY B 18 -6.028 -5.321 6.363 1.00 92.44 N
ATOM 2489 CA GLY B 18 -5.247 -4.565 5.406 1.00 92.27 C
ATOM 2490 C GLY B 18 -4.451 -3.487 6.125 1.00 92.53 C
ATOM 2491 O GLY B 18 -3.504 -2.934 5.563 1.00 92.29 O
ATOM 2492 N GLN B 19 -4.836 -3.195 7.371 1.00 92.65 N
ATOM 2493 CA GLN B 19 -4.187 -2.176 8.198 1.00 92.73 C
ATOM 2494 C GLN B 19 -4.409 -2.423 9.698 1.00 94.03 C
ATOM 2495 O GLN B 19 -5.270 -3.213 10.084 1.00 93.82 O
ATOM 2496 CB GLN B 19 -4.694 -0.784 7.805 1.00 92.02 C
ATOM 2497 CG GLN B 19 -6.207 -0.621 7.778 1.00 91.29 C
ATOM 2498 CD GLN B 19 -6.812 -0.576 9.160 1.00 91.08 C
ATOM 2499 OE1 GLN B 19 -6.325 0.146 10.025 1.00 91.96 O
ATOM 2500 NE2 GLN B 19 -7.880 -1.338 9.376 1.00 89.85 N
ATOM 2501 N PRO B 20 -3.639 -1.729 10.561 1.00 95.05 N
ATOM 2502 CA PRO B 20 -3.665 -1.810 12.031 1.00 95.93 C
ATOM 2503 C PRO B 20 -4.919 -1.379 12.808 1.00 96.49 C
ATOM 2504 O PRO B 20 -5.486 -2.169 13.570 1.00 97.00 O
ATOM 2505 CB PRO B 20 -2.442 -0.990 12.433 1.00 95.49 C
ATOM 2506 CG PRO B 20 -2.411 0.061 11.393 1.00 95.38 C
ATOM 2507 CD PRO B 20 -2.643 -0.732 10.129 1.00 94.96 C
ATOM 2508 N ARG B 21 -5.326 -0.125 12.636 1.00 96.79 N
ATOM 2509 CA ARG B 21 -6.497 0.423 13.329 1.00 96.91 C
ATOM 2510 C ARG B 21 -7.754 -0.438 13.141 1.00 94.86 C
ATOM 2511 O ARG B 21 -8.202 -0.677 12.014 1.00 94.86 O
ATOM 2512 CB ARG B 21 -6.771 1.850 12.837 1.00 99.34 C
ATOM 2513 CG ARG B 21 -5.527 2.598 12.375 1.00102.34 C
ATOM 2514 CD ARG B 21 -5.890 3.968 11.830 1.00106.42 C
ATOM 2515 NE ARG B 21 -6.188 4.914 12.899 1.00109.60 N
ATOM 2516 CZ ARG B 21 -5.272 5.415 13.720 1.00111.63 C
ATOM 2517 NH1 ARG B 21 -3.999 5.063 13.591 1.00112.45 N
ATOM 2518 NH2 ARG B 21 -5.628 6.268 14.670 1.00112.44 N
ATOM 2519 N GLY B 22 -8.331 -0.885 14.253 1.00 92.20 N
ATOM 2520 CA GLY B 22 -9.514 -1.724 14.179 1.00 89.96 C
ATOM 2521 C GLY B 22 -10.854 -1.012 14.202 1.00 88.10 C
ATOM 2522 O GLY B 22 -11.020 0.005 14.868 1.00 87.82 O
ATOM 2523 N GLY B 23 -11.820 -1.567 13.477 1.00 86.64 N
ATOM 2524 CA GLY B 23 -13.140 -0.976 13.429 1.00 85.01 C
ATOM 2525 C GLY B 23 -13.693 -0.985 12.020 1.00 84.30 C
ATOM 2526 O GLY B 23 -14.890 -1.189 11.816 1.00 84.52 O
ATOM 2527 N VAL B 24 -12.817 -0.775 11.043 1.00 83.77 N
ATOM 2528 CA VAL B 24 -13.215 -0.744 9.636 1.00 83.44 C
ATOM 2529 C VAL B 24 -14.152 -1.867 9.176 1.00 84.55 C
ATOM 2530 O VAL B 24 -14.893 -1.698 8.201 1.00 83.80 O
ATOM 2531 CB VAL B 24 -11.967 -0.698 8.715 1.00 82.02 C
ATOM 2532 CG1 VAL B 24 -11.634 0.746 8.376 1.00 82.66 C
ATOM 2533 CG2 VAL B 24 -10.785 -1.332 9.408 1.00 80.13 C
ATOM 2534 N GLU B 25 -14.122 -3.009 9.863 1.00 85.75 N
ATOM 2535 CA GLU B 25 -14.999 -4.113 9.484 1.00 86.17 C
ATOM 2536 C GLU B 25 -16.406 -3.786 9.970 1.00 85.93 C
ATOM 2537 O GLU B 25 -17.396 -4.353 9.487 1.00 86.45 O
ATOM 2538 CB GLU B 25 -14.527 -5.445 10.081 1.00 86.78 C
ATOM 2539 CG GLU B 25 -14.776 -5.637 11.566 1.00 88.34 C
ATOM 2540 CD GLU B 25 -13.850 -4.811 12.430 1.00 90.53 C
ATOM 2541 OE1 GLU B 25 -12.769 -4.409 11.935 1.00 91.06 O
ATOM 2542 OE2 GLU B 25 -14.197 -4.581 13.611 1.00 91.16 O
ATOM 2543 N LYS B 26 -16.488 -2.866 10.928 1.00 84.12 N
ATOM 2544 CA LYS B 26 -17.776 -2.435 11.443 1.00 82.19 C
ATOM 2545 C LYS B 26 -18.375 -1.492 10.404 1.00 80.51 C
ATOM 2546 O LYS B 26 -19.499 -1.020 10.552 1.00 80.34 O
ATOM 2547 CB LYS B 26 -17.606 -1.707 12.773 1.00 82.12 C
ATOM 2548 CG LYS B 26 -17.123 -2.592 13.901 1.00 84.38 C
ATOM 2549 CD LYS B 26 -17.015 -1.804 15.212 1.00 86.61 C
ATOM 2550 CE LYS B 26 -16.569 -2.695 16.378 1.00 86.85 C
ATOM 2551 NZ LYS B 26 -16.430 -1.967 17.680 1.00 86.67 N
ATOM 2552 N GLY B 27 -17.604 -1.231 9.350 1.00 78.69 N
ATOM 2553 CA GLY B 27 -18.047 -0.350 8.284 1.00 76.08 C
ATOM 2554 C GLY B 27 -19.442 -0.656 7.778 1.00 74.71 C
ATOM 2555 O GLY B 27 -20.362 0.134 8.002 1.00 74.43 O
ATOM 2556 N PRO B 28 -19.636 -1.790 7.079 1.00 74.00 N
ATOM 2557 CA PRO B 28 -20.959 -2.156 6.557 1.00 74.28 C
ATOM 2558 C PRO B 28 -22.015 -2.259 7.657 1.00 75.07 C
ATOM 2559 O PRO B 28 -23.216 -2.156 7.407 1.00 74.60 O
ATOM 2560 CB PRO B 28 -20.692 -3.489 5.864 1.00 73.18 C
ATOM 2561 CG PRO B 28 -19.294 -3.321 5.359 1.00 71.70 C
ATOM 2562 CD PRO B 28 -18.602 -2.702 6.557 1.00 72.82 C
ATOM 2563 N ALA B 29 -21.548 -2.455 8.881 1.00 77.64 N
ATOM 2564 CA ALA B 29 -22.432 -2.571 10.033 1.00 79.22 C
ATOM 2565 C ALA B 29 -23.087 -1.235 10.361 1.00 79.71 C
ATOM 2566 O ALA B 29 -24.261 -1.188 10.751 1.00 81.37 O
ATOM 2567 CB ALA B 29 -21.647 -3.086 11.243 1.00 79.86 C
ATOM 2568 N ALA B 30 -22.329 -0.154 10.203 1.00 78.80 N
ATOM 2569 CA ALA B 30 -22.844 1.180 10.487 1.00 78.62 C
ATOM 2570 C ALA B 30 -23.629 1.698 9.289 1.00 78.68 C
ATOM 2571 O ALA B 30 -24.682 2.328 9.436 1.00 78.63 O
ATOM 2572 CB ALA B 30 -21.696 2.127 10.808 1.00 78.52 C
ATOM 2573 N LEU B 31 -23.114 1.415 8.099 1.00 78.19 N
ATOM 2574 CA LEU B 31 -23.755 1.865 6.873 1.00 77.40 C
ATOM 2575 C LEU B 31 -25.171 1.335 6.726 1.00 77.67 C
ATOM 2576 O LEU B 31 -26.067 2.077 6.345 1.00 77.84 O
ATOM 2577 CB LEU B 31 -22.906 1.472 5.659 1.00 75.60 C
ATOM 2578 CG LEU B 31 -21.718 2.401 5.388 1.00 73.01 C
ATOM 2579 CD1 LEU B 31 -20.538 1.623 4.892 1.00 70.89 C
ATOM 2580 CD2 LEU B 31 -22.137 3.449 4.386 1.00 71.89 C
ATOM 2581 N ARG B 32 -25.385 0.059 7.018 1.00 78.94 N
ATOM 2582 CA ARG B 32 -26.733 -0.481 6.898 1.00 80.72 C
ATOM 2583 C ARG B 32 -27.595 0.164 7.969 1.00 81.47 C
ATOM 2584 O ARG B 32 -28.751 0.492 7.723 1.00 80.36 O
ATOM 2585 CB ARG B 32 -26.754 -2.005 7.081 1.00 82.03 C
ATOM 2586 CG ARG B 32 -26.334 -2.830 5.866 1.00 82.49 C
ATOM 2587 CD ARG B 32 -26.825 -4.281 5.994 1.00 84.29 C
ATOM 2588 NE ARG B 32 -26.221 -5.185 5.016 1.00 85.70 N
ATOM 2589 CZ ARG B 32 -24.933 -5.524 5.006 1.00 86.70 C
ATOM 2590 NH1 ARG B 32 -24.109 -5.038 5.926 1.00 87.41 N
ATOM 2591 NH2 ARG B 32 -24.464 -6.349 4.077 1.00 86.01 N
ATOM 2592 N LYS B 33 -27.011 0.330 9.156 1.00 82.85 N
ATOM 2593 CA LYS B 33 -27.686 0.936 10.294 1.00 84.50 C
ATOM 2594 C LYS B 33 -28.087 2.372 9.964 1.00 85.48 C
ATOM 2595 O LYS B 33 -29.032 2.912 10.538 1.00 85.93 O
ATOM 2596 CB LYS B 33 -26.771 0.910 11.521 1.00 85.61 C
ATOM 2597 CG LYS B 33 -27.233 1.804 12.664 1.00 88.84 C
ATOM 2598 CD LYS B 33 -28.564 1.351 13.275 1.00 91.56 C
ATOM 2599 CE LYS B 33 -28.357 0.362 14.427 1.00 93.10 C
ATOM 2600 NZ LYS B 33 -27.506 0.929 15.530 1.00 93.72 N
ATOM 2601 N ALA B 34 -27.363 2.998 9.044 1.00 86.44 N
ATOM 2602 CA ALA B 34 -27.693 4.362 8.642 1.00 86.60 C
ATOM 2603 C ALA B 34 -28.803 4.256 7.589 1.00 86.88 C
ATOM 2604 O ALA B 34 -29.154 5.227 6.915 1.00 85.52 O
ATOM 2605 CB ALA B 34 -26.463 5.054 8.066 1.00 87.03 C
ATOM 2606 N GLY B 35 -29.331 3.042 7.457 1.00 88.26 N
ATOM 2607 CA GLY B 35 -30.408 2.769 6.523 1.00 89.33 C
ATOM 2608 C GLY B 35 -30.035 2.799 5.061 1.00 89.25 C
ATOM 2609 O GLY B 35 -30.891 3.030 4.207 1.00 89.47 O
ATOM 2610 N LEU B 36 -28.770 2.554 4.757 1.00 89.38 N
ATOM 2611 CA LEU B 36 -28.334 2.588 3.369 1.00 90.16 C
ATOM 2612 C LEU B 36 -29.188 1.729 2.436 1.00 90.88 C
ATOM 2613 O LEU B 36 -29.517 2.144 1.320 1.00 90.76 O
ATOM 2614 CB LEU B 36 -26.860 2.178 3.266 1.00 89.73 C
ATOM 2615 CG LEU B 36 -26.212 2.147 1.875 1.00 89.10 C
ATOM 2616 CD1 LEU B 36 -26.658 3.331 1.032 1.00 89.09 C
ATOM 2617 CD2 LEU B 36 -24.703 2.145 2.044 1.00 88.91 C
ATOM 2618 N VAL B 37 -29.573 0.543 2.892 1.00 91.52 N
ATOM 2619 CA VAL B 37 -30.365 -0.339 2.044 1.00 92.05 C
ATOM 2620 C VAL B 37 -31.690 0.288 1.583 1.00 93.18 C
ATOM 2621 O VAL B 37 -31.909 0.481 0.382 1.00 93.84 O
ATOM 2622 CB VAL B 37 -30.654 -1.672 2.754 1.00 90.22 C
ATOM 2623 CG1 VAL B 37 -30.917 -2.747 1.721 1.00 88.34 C
ATOM 2624 CG2 VAL B 37 -29.486 -2.053 3.644 1.00 89.51 C
ATOM 2625 N GLU B 38 -32.561 0.613 2.535 1.00 93.67 N
ATOM 2626 CA GLU B 38 -33.869 1.203 2.237 1.00 93.22 C
ATOM 2627 C GLU B 38 -33.811 2.432 1.327 1.00 91.50 C
ATOM 2628 O GLU B 38 -34.481 2.476 0.291 1.00 89.54 O
ATOM 2629 CB GLU B 38 -34.593 1.577 3.543 1.00 95.27 C
ATOM 2630 CG GLU B 38 -34.719 0.433 4.549 1.00 97.90 C
ATOM 2631 CD GLU B 38 -33.448 0.211 5.357 1.00 98.72 C
ATOM 2632 OE1 GLU B 38 -33.226 0.947 6.345 1.00 98.61 O
ATOM 2633 OE2 GLU B 38 -32.668 -0.694 4.997 1.00100.35 O
ATOM 2634 N LYS B 39 -33.021 3.429 1.717 1.00 89.99 N
ATOM 2635 CA LYS B 39 -32.914 4.639 0.919 1.00 89.24 C
ATOM 2636 C LYS B 39 -32.602 4.253 -0.511 1.00 89.66 C
ATOM 2637 O LYS B 39 -33.175 4.803 -1.453 1.00 90.45 O
ATOM 2638 CB LYS B 39 -31.817 5.548 1.454 1.00 87.39 C
ATOM 2639 CG LYS B 39 -32.060 6.027 2.852 1.00 86.93 C
ATOM 2640 CD LYS B 39 -30.919 6.899 3.311 1.00 87.74 C
ATOM 2641 CE LYS B 39 -31.090 7.281 4.767 1.00 88.21 C
ATOM 2642 NZ LYS B 39 -32.345 8.049 4.956 1.00 89.64 N
ATOM 2643 N LEU B 40 -31.700 3.293 -0.675 1.00 89.66 N
ATOM 2644 CA LEU B 40 -31.336 2.849 -2.012 1.00 89.32 C
ATOM 2645 C LEU B 40 -32.581 2.353 -2.737 1.00 90.45 C
ATOM 2646 O LEU B 40 -32.783 2.652 -3.913 1.00 89.95 O
ATOM 2647 CB LEU B 40 -30.263 1.751 -1.944 1.00 85.82 C
ATOM 2648 CG LEU B 40 -28.810 2.245 -2.052 1.00 82.28 C
ATOM 2649 CD1 LEU B 40 -27.862 1.139 -1.665 1.00 82.14 C
ATOM 2650 CD2 LEU B 40 -28.531 2.712 -3.464 1.00 80.23 C
ATOM 2651 N LYS B 41 -33.429 1.617 -2.025 1.00 92.70 N
ATOM 2652 CA LYS B 41 -34.652 1.088 -2.623 1.00 95.26 C
ATOM 2653 C LYS B 41 -35.523 2.223 -3.149 1.00 96.02 C
ATOM 2654 O LYS B 41 -36.234 2.068 -4.144 1.00 96.02 O
ATOM 2655 CB LYS B 41 -35.429 0.256 -1.600 1.00 95.44 C
ATOM 2656 CG LYS B 41 -34.687 -0.993 -1.131 1.00 97.67 C
ATOM 2657 CD LYS B 41 -35.349 -1.610 0.097 1.00 98.54 C
ATOM 2658 CE LYS B 41 -34.476 -2.690 0.724 1.00 97.92 C
ATOM 2659 NZ LYS B 41 -35.049 -3.185 2.006 1.00 96.37 N
ATOM 2660 N GLU B 42 -35.449 3.369 -2.485 1.00 97.23 N
ATOM 2661 CA GLU B 42 -36.226 4.532 -2.877 1.00 99.27 C
ATOM 2662 C GLU B 42 -35.924 5.037 -4.281 1.00100.29 C
ATOM 2663 O GLU B 42 -36.577 5.960 -4.767 1.00 99.46 O
ATOM 2664 CB GLU B 42 -35.995 5.662 -1.888 1.00100.72 C
ATOM 2665 CG GLU B 42 -36.719 5.495 -0.580 1.00104.56 C
ATOM 2666 CD GLU B 42 -36.385 6.612 0.394 1.00107.81 C
ATOM 2667 OE1 GLU B 42 -36.179 7.759 -0.073 1.00108.24 O
ATOM 2668 OE2 GLU B 42 -36.339 6.344 1.618 1.00110.21 O
ATOM 2669 N THR B 43 -34.931 4.452 -4.935 1.00102.51 N
ATOM 2670 CA THR B 43 -34.588 4.885 -6.285 1.00104.86 C
ATOM 2671 C THR B 43 -35.298 4.039 -7.335 1.00106.85 C
ATOM 2672 O THR B 43 -36.240 3.294 -7.029 1.00107.03 O
ATOM 2673 CB THR B 43 -33.067 4.798 -6.551 1.00104.47 C
ATOM 2674 OG1 THR B 43 -32.617 3.454 -6.336 1.00104.26 O
ATOM 2675 CG2 THR B 43 -32.311 5.743 -5.633 1.00103.94 C
ATOM 2676 N GLU B 44 -34.837 4.177 -8.578 1.00108.54 N
ATOM 2677 CA GLU B 44 -35.378 3.435 -9.713 1.00109.37 C
ATOM 2678 C GLU B 44 -34.661 2.080 -9.853 1.00109.21 C
ATOM 2679 O GLU B 44 -34.913 1.317 -10.793 1.00109.70 O
ATOM 2680 CB GLU B 44 -35.211 4.265 -10.992 1.00109.72 C
ATOM 2681 CG GLU B 44 -33.917 5.072 -11.032 1.00111.43 C
ATOM 2682 CD GLU B 44 -33.661 5.713 -12.387 1.00112.66 C
ATOM 2683 OE1 GLU B 44 -34.597 6.332 -12.942 1.00113.58 O
ATOM 2684 OE2 GLU B 44 -32.520 5.604 -12.896 1.00112.10 O
ATOM 2685 N TYR B 45 -33.774 1.791 -8.901 1.00108.44 N
ATOM 2686 CA TYR B 45 -33.006 0.549 -8.885 1.00107.04 C
ATOM 2687 C TYR B 45 -33.569 -0.456 -7.877 1.00106.43 C
ATOM 2688 O TYR B 45 -34.057 -0.075 -6.805 1.00106.41 O
ATOM 2689 CB TYR B 45 -31.546 0.828 -8.516 1.00106.81 C
ATOM 2690 CG TYR B 45 -30.755 1.645 -9.514 1.00106.18 C
ATOM 2691 CD1 TYR B 45 -31.059 2.983 -9.762 1.00106.02 C
ATOM 2692 CD2 TYR B 45 -29.679 1.083 -10.192 1.00106.09 C
ATOM 2693 CE1 TYR B 45 -30.301 3.739 -10.667 1.00106.12 C
ATOM 2694 CE2 TYR B 45 -28.920 1.823 -11.095 1.00105.75 C
ATOM 2695 CZ TYR B 45 -29.232 3.146 -11.328 1.00105.62 C
ATOM 2696 OH TYR B 45 -28.477 3.865 -12.227 1.00104.68 O
ATOM 2697 N ASN B 46 -33.501 -1.738 -8.227 1.00105.11 N
ATOM 2698 CA ASN B 46 -33.965 -2.795 -7.337 1.00103.37 C
ATOM 2699 C ASN B 46 -32.733 -3.144 -6.535 1.00101.06 C
ATOM 2700 O ASN B 46 -31.648 -3.290 -7.096 1.00 99.33 O
ATOM 2701 CB ASN B 46 -34.426 -4.021 -8.124 1.00106.07 C
ATOM 2702 CG ASN B 46 -35.540 -3.704 -9.094 1.00108.03 C
ATOM 2703 OD1 ASN B 46 -36.562 -3.126 -8.717 1.00109.57 O
ATOM 2704 ND2 ASN B 46 -35.351 -4.085 -10.355 1.00108.96 N
ATOM 2705 N VAL B 47 -32.891 -3.292 -5.229 1.00 99.24 N
ATOM 2706 CA VAL B 47 -31.735 -3.579 -4.399 1.00 98.07 C
ATOM 2707 C VAL B 47 -31.816 -4.896 -3.647 1.00 96.62 C
ATOM 2708 O VAL B 47 -32.836 -5.213 -3.039 1.00 96.63 O
ATOM 2709 CB VAL B 47 -31.506 -2.440 -3.370 1.00 98.47 C
ATOM 2710 CG1 VAL B 47 -30.065 -2.461 -2.879 1.00 97.35 C
ATOM 2711 CG2 VAL B 47 -31.840 -1.094 -3.995 1.00 98.39 C
ATOM 2712 N ARG B 48 -30.728 -5.656 -3.697 1.00 94.83 N
ATOM 2713 CA ARG B 48 -30.644 -6.923 -2.997 1.00 93.46 C
ATOM 2714 C ARG B 48 -29.428 -6.849 -2.099 1.00 92.09 C
ATOM 2715 O ARG B 48 -28.321 -6.586 -2.568 1.00 90.53 O
ATOM 2716 CB ARG B 48 -30.494 -8.084 -3.984 1.00 95.23 C
ATOM 2717 CG ARG B 48 -30.293 -9.452 -3.318 1.00 96.76 C
ATOM 2718 CD ARG B 48 -30.031 -10.550 -4.347 1.00 98.94 C
ATOM 2719 NE ARG B 48 -28.943 -11.459 -3.959 1.00102.01 N
ATOM 2720 CZ ARG B 48 -29.040 -12.440 -3.059 1.00102.83 C
ATOM 2721 NH1 ARG B 48 -30.187 -12.667 -2.429 1.00103.67 N
ATOM 2722 NH2 ARG B 48 -27.980 -13.198 -2.792 1.00103.04 N
ATOM 2723 N ASP B 49 -29.646 -7.051 -0.802 1.00 91.94 N
ATOM 2724 CA ASP B 49 -28.562 -7.025 0.169 1.00 92.13 C
ATOM 2725 C ASP B 49 -28.067 -8.466 0.266 1.00 92.71 C
ATOM 2726 O ASP B 49 -28.838 -9.376 0.572 1.00 93.23 O
ATOM 2727 CB ASP B 49 -29.076 -6.542 1.529 1.00 92.41 C
ATOM 2728 CG ASP B 49 -27.949 -6.205 2.496 1.00 93.21 C
ATOM 2729 OD1 ASP B 49 -27.157 -7.111 2.838 1.00 93.93 O
ATOM 2730 OD2 ASP B 49 -27.846 -5.032 2.921 1.00 94.25 O
ATOM 2731 N HIS B 50 -26.781 -8.661 -0.012 1.00 93.35 N
ATOM 2732 CA HIS B 50 -26.138 -9.979 0.001 1.00 93.56 C
ATOM 2733 C HIS B 50 -25.623 -10.354 1.406 1.00 93.08 C
ATOM 2734 O HIS B 50 -25.284 -11.511 1.670 1.00 92.89 O
ATOM 2735 CB HIS B 50 -24.999 -9.953 -1.039 1.00 94.71 C
ATOM 2736 CG HIS B 50 -24.286 -11.257 -1.244 1.00 95.99 C
ATOM 2737 ND1 HIS B 50 -23.597 -11.904 -0.234 1.00 97.39 N
ATOM 2738 CD2 HIS B 50 -24.067 -11.985 -2.366 1.00 95.59 C
ATOM 2739 CE1 HIS B 50 -22.985 -12.965 -0.726 1.00 96.73 C
ATOM 2740 NE2 HIS B 50 -23.253 -13.037 -2.020 1.00 96.87 N
ATOM 2741 N GLY B 51 -25.591 -9.381 2.311 1.00 92.46 N
ATOM 2742 CA GLY B 51 -25.118 -9.654 3.652 1.00 92.91 C
ATOM 2743 C GLY B 51 -23.620 -9.446 3.744 1.00 93.76 C
ATOM 2744 O GLY B 51 -23.006 -8.892 2.828 1.00 93.36 O
ATOM 2745 N ASP B 52 -23.023 -9.900 4.844 1.00 94.72 N
ATOM 2746 CA ASP B 52 -21.584 -9.746 5.052 1.00 95.39 C
ATOM 2747 C ASP B 52 -20.746 -10.990 4.876 1.00 95.22 C
ATOM 2748 O ASP B 52 -20.784 -11.895 5.701 1.00 94.37 O
ATOM 2749 CB ASP B 52 -21.285 -9.192 6.445 1.00 96.23 C
ATOM 2750 CG ASP B 52 -21.482 -7.707 6.524 1.00 96.65 C
ATOM 2751 OD1 ASP B 52 -21.102 -7.013 5.557 1.00 97.76 O
ATOM 2752 OD2 ASP B 52 -22.006 -7.235 7.554 1.00 97.38 O
ATOM 2753 N LEU B 53 -19.965 -11.014 3.808 1.00 96.11 N
ATOM 2754 CA LEU B 53 -19.087 -12.136 3.557 1.00 97.52 C
ATOM 2755 C LEU B 53 -18.264 -12.405 4.825 1.00 99.27 C
ATOM 2756 O LEU B 53 -17.331 -11.663 5.130 1.00100.25 O
ATOM 2757 CB LEU B 53 -18.141 -11.819 2.390 1.00 95.74 C
ATOM 2758 CG LEU B 53 -18.739 -11.495 1.019 1.00 94.64 C
ATOM 2759 CD1 LEU B 53 -17.609 -11.386 0.013 1.00 93.53 C
ATOM 2760 CD2 LEU B 53 -19.718 -12.585 0.594 1.00 94.55 C
ATOM 2761 N ALA B 54 -18.621 -13.446 5.574 1.00101.13 N
ATOM 2762 CA ALA B 54 -17.870 -13.791 6.777 1.00102.37 C
ATOM 2763 C ALA B 54 -16.517 -14.270 6.273 1.00103.74 C
ATOM 2764 O ALA B 54 -16.441 -15.040 5.316 1.00102.75 O
ATOM 2765 CB ALA B 54 -18.577 -14.896 7.547 1.00101.69 C
ATOM 2766 N PHE B 55 -15.447 -13.807 6.901 1.00106.29 N
ATOM 2767 CA PHE B 55 -14.124 -14.199 6.449 1.00109.42 C
ATOM 2768 C PHE B 55 -13.380 -15.099 7.420 1.00111.23 C
ATOM 2769 O PHE B 55 -13.043 -14.693 8.535 1.00111.53 O
ATOM 2770 CB PHE B 55 -13.281 -12.957 6.139 1.00110.05 C
ATOM 2771 CG PHE B 55 -13.849 -12.092 5.044 1.00109.86 C
ATOM 2772 CD1 PHE B 55 -14.081 -12.615 3.773 1.00109.98 C
ATOM 2773 CD2 PHE B 55 -14.166 -10.762 5.287 1.00109.37 C
ATOM 2774 CE1 PHE B 55 -14.620 -11.826 2.761 1.00109.69 C
ATOM 2775 CE2 PHE B 55 -14.703 -9.965 4.285 1.00109.52 C
ATOM 2776 CZ PHE B 55 -14.932 -10.501 3.018 1.00109.89 C
ATOM 2777 N VAL B 56 -13.137 -16.327 6.971 1.00113.41 N
ATOM 2778 CA VAL B 56 -12.421 -17.342 7.738 1.00114.90 C
ATOM 2779 C VAL B 56 -11.007 -16.830 7.998 1.00115.83 C
ATOM 2780 O VAL B 56 -10.327 -16.387 7.068 1.00115.87 O
ATOM 2781 CB VAL B 56 -12.348 -18.666 6.939 1.00115.37 C
ATOM 2782 CG1 VAL B 56 -13.756 -19.205 6.683 1.00114.66 C
ATOM 2783 CG2 VAL B 56 -11.628 -18.434 5.609 1.00115.29 C
ATOM 2784 N ASP B 57 -10.553 -16.897 9.247 1.00116.87 N
ATOM 2785 CA ASP B 57 -9.225 -16.387 9.559 1.00118.41 C
ATOM 2786 C ASP B 57 -8.081 -17.375 9.357 1.00119.01 C
ATOM 2787 O ASP B 57 -8.134 -18.512 9.830 1.00118.81 O
ATOM 2788 CB ASP B 57 -9.186 -15.840 10.986 1.00118.79 C
ATOM 2789 CG ASP B 57 -8.296 -14.612 11.106 1.00119.33 C
ATOM 2790 OD1 ASP B 57 -7.092 -14.715 10.786 1.00118.72 O
ATOM 2791 OD2 ASP B 57 -8.809 -13.543 11.511 1.00119.85 O
ATOM 2792 N VAL B 58 -7.048 -16.911 8.653 1.00119.62 N
ATOM 2793 CA VAL B 58 -5.861 -17.707 8.349 1.00119.95 C
ATOM 2794 C VAL B 58 -4.935 -17.864 9.555 1.00120.08 C
ATOM 2795 O VAL B 58 -4.138 -16.971 9.868 1.00120.20 O
ATOM 2796 CB VAL B 58 -5.051 -17.081 7.184 1.00120.15 C
ATOM 2797 CG1 VAL B 58 -3.743 -17.844 6.974 1.00119.13 C
ATOM 2798 CG2 VAL B 58 -5.886 -17.095 5.911 1.00120.11 C
ATOM 2799 N PRO B 59 -5.023 -19.018 10.240 1.00119.88 N
ATOM 2800 CA PRO B 59 -4.184 -19.281 11.413 1.00118.69 C
ATOM 2801 C PRO B 59 -2.714 -19.149 11.062 1.00117.26 C
ATOM 2802 O PRO B 59 -2.269 -19.611 10.013 1.00116.68 O
ATOM 2803 CB PRO B 59 -4.572 -20.705 11.802 1.00119.27 C
ATOM 2804 CG PRO B 59 -4.961 -21.321 10.480 1.00119.94 C
ATOM 2805 CD PRO B 59 -5.782 -20.224 9.857 1.00119.85 C
ATOM 2806 N ASN B 60 -1.966 -18.511 11.949 1.00116.37 N
ATOM 2807 CA ASN B 60 -0.544 -18.304 11.733 1.00116.10 C
ATOM 2808 C ASN B 60 -0.278 -17.715 10.345 1.00115.83 C
ATOM 2809 O ASN B 60 0.162 -18.413 9.425 1.00115.68 O
ATOM 2810 CB ASN B 60 0.222 -19.623 11.909 1.00115.54 C
ATOM 2811 CG ASN B 60 1.735 -19.443 11.809 1.00115.47 C
ATOM 2812 OD1 ASN B 60 2.318 -18.583 12.470 1.00114.68 O
ATOM 2813 ND2 ASN B 60 2.375 -20.264 10.981 1.00115.65 N
ATOM 2814 N ASP B 61 -0.571 -16.426 10.203 1.00115.14 N
ATOM 2815 CA ASP B 61 -0.344 -15.709 8.956 1.00114.13 C
ATOM 2816 C ASP B 61 1.005 -15.006 9.162 1.00113.89 C
ATOM 2817 O ASP B 61 1.153 -14.177 10.066 1.00113.46 O
ATOM 2818 CB ASP B 61 -1.464 -14.685 8.734 1.00113.36 C
ATOM 2819 CG ASP B 61 -1.547 -14.214 7.302 1.00112.30 C
ATOM 2820 OD1 ASP B 61 -0.485 -14.040 6.676 1.00111.35 O
ATOM 2821 OD2 ASP B 61 -2.673 -14.008 6.805 1.00111.82 O
ATOM 2822 N SER B 62 1.989 -15.346 8.334 1.00113.79 N
ATOM 2823 CA SER B 62 3.331 -14.774 8.465 1.00113.65 C
ATOM 2824 C SER B 62 3.589 -13.495 7.655 1.00112.82 C
ATOM 2825 O SER B 62 3.147 -13.364 6.509 1.00112.49 O
ATOM 2826 CB SER B 62 4.378 -15.835 8.094 1.00114.15 C
ATOM 2827 OG SER B 62 4.209 -17.012 8.871 1.00113.73 O
ATOM 2828 N PRO B 63 4.318 -12.533 8.253 1.00111.99 N
ATOM 2829 CA PRO B 63 4.669 -11.242 7.641 1.00111.53 C
ATOM 2830 C PRO B 63 5.680 -11.293 6.484 1.00110.84 C
ATOM 2831 O PRO B 63 6.865 -11.034 6.687 1.00111.39 O
ATOM 2832 CB PRO B 63 5.209 -10.434 8.825 1.00111.29 C
ATOM 2833 CG PRO B 63 4.467 -11.009 9.989 1.00111.54 C
ATOM 2834 CD PRO B 63 4.555 -12.490 9.707 1.00111.51 C
ATOM 2835 N PHE B 64 5.199 -11.612 5.283 1.00109.81 N
ATOM 2836 CA PHE B 64 6.023 -11.683 4.069 1.00109.33 C
ATOM 2837 C PHE B 64 7.020 -10.512 3.999 1.00108.56 C
ATOM 2838 O PHE B 64 6.756 -9.505 3.344 1.00108.37 O
ATOM 2839 CB PHE B 64 5.090 -11.663 2.846 1.00110.08 C
ATOM 2840 CG PHE B 64 5.794 -11.761 1.509 1.00110.63 C
ATOM 2841 CD1 PHE B 64 6.332 -12.966 1.069 1.00110.93 C
ATOM 2842 CD2 PHE B 64 5.859 -10.658 0.660 1.00110.60 C
ATOM 2843 CE1 PHE B 64 6.914 -13.071 -0.197 1.00110.88 C
ATOM 2844 CE2 PHE B 64 6.439 -10.755 -0.606 1.00110.13 C
ATOM 2845 CZ PHE B 64 6.965 -11.962 -1.033 1.00110.58 C
ATOM 2846 N GLN B 65 8.165 -10.656 4.669 1.00108.06 N
ATOM 2847 CA GLN B 65 9.202 -9.618 4.718 1.00107.81 C
ATOM 2848 C GLN B 65 8.752 -8.467 5.624 1.00107.14 C
ATOM 2849 O GLN B 65 9.077 -8.431 6.813 1.00107.01 O
ATOM 2850 CB GLN B 65 9.494 -9.059 3.322 1.00108.70 C
ATOM 2851 CG GLN B 65 9.783 -10.105 2.258 1.00110.56 C
ATOM 2852 CD GLN B 65 10.194 -9.486 0.927 1.00110.91 C
ATOM 2853 OE1 GLN B 65 11.208 -8.791 0.844 1.00110.88 O
ATOM 2854 NE2 GLN B 65 9.406 -9.735 -0.117 1.00110.95 N
ATOM 2855 N ILE B 66 8.005 -7.529 5.037 1.00106.12 N
ATOM 2856 CA ILE B 66 7.464 -6.361 5.740 1.00103.69 C
ATOM 2857 C ILE B 66 5.932 -6.466 5.746 1.00101.94 C
ATOM 2858 O ILE B 66 5.283 -6.167 6.755 1.00100.49 O
ATOM 2859 CB ILE B 66 7.902 -5.031 5.042 1.00103.32 C
ATOM 2860 CG1 ILE B 66 8.836 -4.240 5.956 1.00102.53 C
ATOM 2861 CG2 ILE B 66 6.698 -4.194 4.672 1.00103.34 C
ATOM 2862 CD1 ILE B 66 10.204 -4.872 6.122 1.00102.55 C
ATOM 2863 N VAL B 67 5.379 -6.905 4.611 1.00100.15 N
ATOM 2864 CA VAL B 67 3.937 -7.078 4.435 1.00 98.05 C
ATOM 2865 C VAL B 67 3.328 -7.982 5.500 1.00 97.96 C
ATOM 2866 O VAL B 67 3.798 -9.094 5.724 1.00 98.49 O
ATOM 2867 CB VAL B 67 3.612 -7.666 3.052 1.00 96.47 C
ATOM 2868 CG1 VAL B 67 2.097 -7.774 2.880 1.00 95.16 C
ATOM 2869 CG2 VAL B 67 4.244 -6.807 1.966 1.00 94.29 C
ATOM 2870 N LYS B 68 2.266 -7.510 6.137 1.00 97.30 N
ATOM 2871 CA LYS B 68 1.631 -8.270 7.200 1.00 97.06 C
ATOM 2872 C LYS B 68 0.330 -8.903 6.767 1.00 97.44 C
ATOM 2873 O LYS B 68 -0.150 -8.644 5.665 1.00 97.46 O
ATOM 2874 CB LYS B 68 1.411 -7.349 8.394 1.00 95.66 C
ATOM 2875 CG LYS B 68 2.617 -6.479 8.603 1.00 94.66 C
ATOM 2876 CD LYS B 68 2.518 -5.601 9.814 1.00 94.77 C
ATOM 2877 CE LYS B 68 3.730 -4.680 9.854 1.00 95.37 C
ATOM 2878 NZ LYS B 68 4.998 -5.420 9.545 1.00 93.99 N
ATOM 2879 N ASN B 69 -0.210 -9.754 7.638 1.00 98.69 N
ATOM 2880 CA ASN B 69 -1.471 -10.473 7.413 1.00100.55 C
ATOM 2881 C ASN B 69 -1.765 -10.753 5.929 1.00101.33 C
ATOM 2882 O ASN B 69 -2.896 -10.574 5.471 1.00100.98 O
ATOM 2883 CB ASN B 69 -2.628 -9.666 8.016 1.00101.27 C
ATOM 2884 CG ASN B 69 -2.409 -9.321 9.489 1.00101.35 C
ATOM 2885 OD1 ASN B 69 -2.828 -10.064 10.383 1.00101.81 O
ATOM 2886 ND2 ASN B 69 -1.747 -8.191 9.742 1.00100.63 N
ATOM 2887 N PRO B 70 -0.756 -11.227 5.172 1.00102.26 N
ATOM 2888 CA PRO B 70 -0.893 -11.523 3.740 1.00102.62 C
ATOM 2889 C PRO B 70 -1.942 -12.554 3.357 1.00102.96 C
ATOM 2890 O PRO B 70 -2.875 -12.251 2.611 1.00103.01 O
ATOM 2891 CB PRO B 70 0.515 -11.956 3.346 1.00103.21 C
ATOM 2892 CG PRO B 70 1.001 -12.633 4.577 1.00103.31 C
ATOM 2893 CD PRO B 70 0.553 -11.691 5.669 1.00102.72 C
ATOM 2894 N ARG B 71 -1.777 -13.775 3.850 1.00103.42 N
ATOM 2895 CA ARG B 71 -2.715 -14.848 3.551 1.00104.26 C
ATOM 2896 C ARG B 71 -4.150 -14.409 3.840 1.00104.02 C
ATOM 2897 O ARG B 71 -5.079 -14.729 3.085 1.00104.32 O
ATOM 2898 CB ARG B 71 -2.352 -16.082 4.373 1.00105.61 C
ATOM 2899 CG ARG B 71 -0.947 -16.572 4.088 1.00107.38 C
ATOM 2900 CD ARG B 71 -0.532 -17.697 5.014 1.00109.01 C
ATOM 2901 NE ARG B 71 0.815 -18.167 4.702 1.00109.72 N
ATOM 2902 CZ ARG B 71 1.911 -17.420 4.811 1.00110.10 C
ATOM 2903 NH1 ARG B 71 1.821 -16.163 5.229 1.00110.13 N
ATOM 2904 NH2 ARG B 71 3.093 -17.931 4.493 1.00109.92 N
ATOM 2905 N SER B 72 -4.324 -13.672 4.932 1.00103.10 N
ATOM 2906 CA SER B 72 -5.640 -13.171 5.311 1.00101.82 C
ATOM 2907 C SER B 72 -6.235 -12.385 4.128 1.00101.36 C
ATOM 2908 O SER B 72 -7.243 -12.788 3.532 1.00100.77 O
ATOM 2909 CB SER B 72 -5.517 -12.258 6.544 1.00101.15 C
ATOM 2910 OG SER B 72 -5.004 -12.954 7.669 1.00 99.62 O
ATOM 2911 N VAL B 73 -5.577 -11.274 3.795 1.00100.71 N
ATOM 2912 CA VAL B 73 -5.983 -10.385 2.710 1.00 99.43 C
ATOM 2913 C VAL B 73 -6.020 -11.066 1.345 1.00 98.74 C
ATOM 2914 O VAL B 73 -6.661 -10.578 0.417 1.00 98.50 O
ATOM 2915 CB VAL B 73 -5.030 -9.176 2.616 1.00 99.57 C
ATOM 2916 CG1 VAL B 73 -5.517 -8.223 1.544 1.00 99.47 C
ATOM 2917 CG2 VAL B 73 -4.928 -8.474 3.971 1.00 98.64 C
ATOM 2918 N GLY B 74 -5.323 -12.186 1.218 1.00 98.05 N
ATOM 2919 CA GLY B 74 -5.321 -12.890 -0.047 1.00 98.09 C
ATOM 2920 C GLY B 74 -6.568 -13.739 -0.201 1.00 98.36 C
ATOM 2921 O GLY B 74 -7.164 -13.807 -1.281 1.00 97.94 O
ATOM 2922 N LYS B 75 -6.971 -14.394 0.883 1.00 98.26 N
ATOM 2923 CA LYS B 75 -8.149 -15.243 0.844 1.00 98.70 C
ATOM 2924 C LYS B 75 -9.444 -14.457 1.011 1.00 98.41 C
ATOM 2925 O LYS B 75 -10.488 -14.834 0.460 1.00 98.11 O
ATOM 2926 CB LYS B 75 -8.068 -16.327 1.918 1.00 99.64 C
ATOM 2927 CG LYS B 75 -9.326 -17.202 1.985 1.00101.06 C
ATOM 2928 CD LYS B 75 -9.676 -17.792 0.613 1.00101.25 C
ATOM 2929 CE LYS B 75 -11.048 -18.450 0.613 1.00100.94 C
ATOM 2930 NZ LYS B 75 -11.431 -18.889 -0.758 1.00100.45 N
ATOM 2931 N ALA B 76 -9.378 -13.371 1.780 1.00 98.25 N
ATOM 2932 CA ALA B 76 -10.550 -12.529 2.008 1.00 97.31 C
ATOM 2933 C ALA B 76 -10.929 -11.841 0.705 1.00 96.60 C
ATOM 2934 O ALA B 76 -12.111 -11.713 0.385 1.00 95.57 O
ATOM 2935 CB ALA B 76 -10.249 -11.488 3.082 1.00 96.93 C
ATOM 2936 N ASN B 77 -9.908 -11.411 -0.039 1.00 97.00 N
ATOM 2937 CA ASN B 77 -10.080 -10.732 -1.323 1.00 97.74 C
ATOM 2938 C ASN B 77 -10.392 -11.725 -2.433 1.00 98.75 C
ATOM 2939 O ASN B 77 -10.935 -11.352 -3.473 1.00 98.91 O
ATOM 2940 CB ASN B 77 -8.819 -9.932 -1.678 1.00 97.23 C
ATOM 2941 CG ASN B 77 -8.862 -8.497 -1.154 1.00 97.89 C
ATOM 2942 OD1 ASN B 77 -9.524 -7.630 -1.732 1.00 96.57 O
ATOM 2943 ND2 ASN B 77 -8.160 -8.246 -0.047 1.00 97.76 N
ATOM 2944 N GLU B 78 -10.035 -12.988 -2.213 1.00 99.93 N
ATOM 2945 CA GLU B 78 -10.317 -14.031 -3.191 1.00100.34 C
ATOM 2946 C GLU B 78 -11.803 -14.362 -3.104 1.00 99.33 C
ATOM 2947 O GLU B 78 -12.486 -14.519 -4.117 1.00 99.02 O
ATOM 2948 CB GLU B 78 -9.495 -15.288 -2.902 1.00101.86 C
ATOM 2949 CG GLU B 78 -9.892 -16.473 -3.772 1.00103.76 C
ATOM 2950 CD GLU B 78 -9.003 -17.676 -3.562 1.00104.81 C
ATOM 2951 OE1 GLU B 78 -8.873 -18.116 -2.399 1.00105.01 O
ATOM 2952 OE2 GLU B 78 -8.442 -18.176 -4.563 1.00105.37 O
ATOM 2953 N GLN B 79 -12.298 -14.465 -1.877 1.00 98.33 N
ATOM 2954 CA GLN B 79 -13.699 -14.759 -1.650 1.00 98.14 C
ATOM 2955 C GLN B 79 -14.591 -13.659 -2.227 1.00 98.36 C
ATOM 2956 O GLN B 79 -15.672 -13.941 -2.759 1.00 99.37 O
ATOM 2957 CB GLN B 79 -13.967 -14.903 -0.153 1.00 98.02 C
ATOM 2958 CG GLN B 79 -15.447 -14.963 0.202 1.00 98.51 C
ATOM 2959 CD GLN B 79 -15.683 -15.192 1.682 1.00 99.74 C
ATOM 2960 OE1 GLN B 79 -16.827 -15.227 2.143 1.00100.42 O
ATOM 2961 NE2 GLN B 79 -14.598 -15.356 2.436 1.00 99.69 N
ATOM 2962 N LEU B 80 -14.127 -12.412 -2.127 1.00 97.08 N
ATOM 2963 CA LEU B 80 -14.880 -11.254 -2.606 1.00 96.12 C
ATOM 2964 C LEU B 80 -14.960 -11.151 -4.120 1.00 95.39 C
ATOM 2965 O LEU B 80 -16.053 -11.140 -4.683 1.00 94.88 O
ATOM 2966 CB LEU B 80 -14.289 -9.956 -2.022 1.00 96.94 C
ATOM 2967 CG LEU B 80 -14.804 -8.575 -2.471 1.00 96.90 C
ATOM 2968 CD1 LEU B 80 -16.311 -8.439 -2.284 1.00 96.64 C
ATOM 2969 CD2 LEU B 80 -14.084 -7.512 -1.662 1.00 97.01 C
ATOM 2970 N ALA B 81 -13.807 -11.064 -4.778 1.00 95.38 N
ATOM 2971 CA ALA B 81 -13.772 -10.960 -6.238 1.00 95.32 C
ATOM 2972 C ALA B 81 -14.819 -11.914 -6.801 1.00 95.15 C
ATOM 2973 O ALA B 81 -15.620 -11.542 -7.665 1.00 95.06 O
ATOM 2974 CB ALA B 81 -12.375 -11.318 -6.771 1.00 94.39 C
ATOM 2975 N ALA B 82 -14.809 -13.140 -6.277 1.00 94.53 N
ATOM 2976 CA ALA B 82 -15.742 -14.184 -6.674 1.00 92.86 C
ATOM 2977 C ALA B 82 -17.189 -13.679 -6.667 1.00 92.77 C
ATOM 2978 O ALA B 82 -17.843 -13.624 -7.715 1.00 94.08 O
ATOM 2979 CB ALA B 82 -15.603 -15.362 -5.738 1.00 91.55 C
ATOM 2980 N VAL B 83 -17.691 -13.303 -5.492 1.00 90.57 N
ATOM 2981 CA VAL B 83 -19.064 -12.820 -5.398 1.00 87.86 C
ATOM 2982 C VAL B 83 -19.325 -11.692 -6.383 1.00 87.81 C
ATOM 2983 O VAL B 83 -20.372 -11.646 -7.010 1.00 87.85 O
ATOM 2984 CB VAL B 83 -19.400 -12.323 -3.985 1.00 85.44 C
ATOM 2985 CG1 VAL B 83 -20.900 -12.059 -3.882 1.00 83.17 C
ATOM 2986 CG2 VAL B 83 -18.939 -13.349 -2.947 1.00 84.36 C
ATOM 2987 N VAL B 84 -18.361 -10.791 -6.521 1.00 88.67 N
ATOM 2988 CA VAL B 84 -18.488 -9.654 -7.435 1.00 89.97 C
ATOM 2989 C VAL B 84 -18.705 -10.093 -8.891 1.00 90.78 C
ATOM 2990 O VAL B 84 -19.632 -9.636 -9.566 1.00 89.94 O
ATOM 2991 CB VAL B 84 -17.230 -8.753 -7.356 1.00 89.27 C
ATOM 2992 CG1 VAL B 84 -17.360 -7.584 -8.324 1.00 88.30 C
ATOM 2993 CG2 VAL B 84 -17.032 -8.259 -5.928 1.00 88.68 C
ATOM 2994 N ALA B 85 -17.841 -10.977 -9.374 1.00 92.01 N
ATOM 2995 CA ALA B 85 -17.965 -11.468 -10.736 1.00 93.16 C
ATOM 2996 C ALA B 85 -19.299 -12.193 -10.815 1.00 93.76 C
ATOM 2997 O ALA B 85 -19.973 -12.190 -11.855 1.00 92.85 O
ATOM 2998 CB ALA B 85 -16.814 -12.428 -11.062 1.00 92.48 C
ATOM 2999 N GLU B 86 -19.690 -12.783 -9.687 1.00 94.93 N
ATOM 3000 CA GLU B 86 -20.908 -13.570 -9.543 1.00 96.65 C
ATOM 3001 C GLU B 86 -22.144 -12.729 -9.841 1.00 97.30 C
ATOM 3002 O GLU B 86 -23.081 -13.193 -10.523 1.00 96.34 O
ATOM 3003 CB GLU B 86 -20.996 -14.169 -8.138 1.00 97.43 C
ATOM 3004 CG GLU B 86 -19.848 -15.102 -7.788 1.00101.11 C
ATOM 3005 CD GLU B 86 -19.766 -16.298 -8.716 1.00103.56 C
ATOM 3006 OE1 GLU B 86 -20.617 -16.405 -9.625 1.00104.28 O
ATOM 3007 OE2 GLU B 86 -18.851 -17.129 -8.535 1.00104.59 O
ATOM 3008 N THR B 87 -22.175 -11.520 -9.307 1.00 98.79 N
ATOM 3009 CA THR B 87 -23.286 -10.607 -9.490 1.00 99.86 C
ATOM 3010 C THR B 87 -23.131 -9.988 -10.856 1.00101.87 C
ATOM 3011 O THR B 87 -24.048 -10.031 -11.667 1.00102.78 O
ATOM 3012 CB THR B 87 -23.256 -9.487 -8.456 1.00 99.41 C
ATOM 3013 OG1 THR B 87 -22.797 -10.005 -7.200 1.00 99.80 O
ATOM 3014 CG2 THR B 87 -24.639 -8.927 -8.265 1.00 99.73 C
ATOM 3015 N GLN B 88 -21.956 -9.415 -11.102 1.00104.27 N
ATOM 3016 CA GLN B 88 -21.641 -8.776 -12.381 1.00107.00 C
ATOM 3017 C GLN B 88 -22.175 -9.534 -13.603 1.00107.90 C
ATOM 3018 O GLN B 88 -22.584 -8.917 -14.595 1.00107.08 O
ATOM 3019 CB GLN B 88 -20.124 -8.609 -12.523 1.00107.91 C
ATOM 3020 CG GLN B 88 -19.560 -7.359 -11.872 1.00109.47 C
ATOM 3021 CD GLN B 88 -20.247 -6.094 -12.361 1.00110.31 C
ATOM 3022 OE1 GLN B 88 -20.739 -6.036 -13.492 1.00110.06 O
ATOM 3023 NE2 GLN B 88 -20.271 -5.067 -11.513 1.00110.80 N
ATOM 3024 N LYS B 89 -22.162 -10.868 -13.524 1.00109.56 N
ATOM 3025 CA LYS B 89 -22.634 -11.730 -14.598 1.00110.90 C
ATOM 3026 C LYS B 89 -24.151 -11.680 -14.716 1.00111.00 C
ATOM 3027 O LYS B 89 -24.709 -11.708 -15.822 1.00110.95 O
ATOM 3028 CB LYS B 89 -22.165 -13.168 -14.376 1.00111.68 C
ATOM 3029 CG LYS B 89 -22.853 -13.872 -13.216 1.00113.68 C
ATOM 3030 CD LYS B 89 -22.332 -15.289 -13.043 1.00116.52 C
ATOM 3031 CE LYS B 89 -23.013 -15.990 -11.878 1.00117.23 C
ATOM 3032 NZ LYS B 89 -22.513 -17.381 -11.697 1.00117.27 N
ATOM 3033 N ASN B 90 -24.830 -11.613 -13.571 1.00110.80 N
ATOM 3034 CA ASN B 90 -26.287 -11.534 -13.527 1.00110.60 C
ATOM 3035 C ASN B 90 -26.738 -10.195 -14.086 1.00110.46 C
ATOM 3036 O ASN B 90 -27.920 -9.988 -14.371 1.00110.57 O
ATOM 3037 CB ASN B 90 -26.772 -11.671 -12.087 1.00110.18 C
ATOM 3038 CG ASN B 90 -26.464 -13.024 -11.506 1.00109.88 C
ATOM 3039 OD1 ASN B 90 -27.074 -14.018 -11.888 1.00110.06 O
ATOM 3040 ND2 ASN B 90 -25.503 -13.079 -10.592 1.00109.05 N
ATOM 3041 N GLY B 91 -25.781 -9.282 -14.222 1.00110.39 N
ATOM 3042 CA GLY B 91 -26.071 -7.966 -14.759 1.00109.77 C
ATOM 3043 C GLY B 91 -26.295 -6.856 -13.743 1.00109.04 C
ATOM 3044 O GLY B 91 -26.415 -5.692 -14.131 1.00109.23 O
ATOM 3045 N THR B 92 -26.344 -7.187 -12.452 1.00107.90 N
ATOM 3046 CA THR B 92 -26.580 -6.168 -11.430 1.00106.35 C
ATOM 3047 C THR B 92 -25.316 -5.375 -11.090 1.00105.86 C
ATOM 3048 O THR B 92 -24.196 -5.827 -11.361 1.00105.70 O
ATOM 3049 CB THR B 92 -27.165 -6.790 -10.121 1.00105.45 C
ATOM 3050 OG1 THR B 92 -26.129 -6.973 -9.151 1.00103.68 O
ATOM 3051 CG2 THR B 92 -27.821 -8.137 -10.408 1.00104.19 C
ATOM 3052 N ILE B 93 -25.510 -4.182 -10.520 1.00104.70 N
ATOM 3053 CA ILE B 93 -24.406 -3.306 -10.117 1.00101.94 C
ATOM 3054 C ILE B 93 -23.924 -3.683 -8.721 1.00100.46 C
ATOM 3055 O ILE B 93 -24.716 -3.753 -7.774 1.00100.27 O
ATOM 3056 CB ILE B 93 -24.833 -1.828 -10.081 1.00101.61 C
ATOM 3057 CG1 ILE B 93 -25.398 -1.405 -11.435 1.00101.79 C
ATOM 3058 CG2 ILE B 93 -23.642 -0.960 -9.712 1.00101.59 C
ATOM 3059 CD1 ILE B 93 -24.430 -1.597 -12.578 1.00102.89 C
ATOM 3060 N SER B 94 -22.624 -3.930 -8.608 1.00 98.22 N
ATOM 3061 CA SER B 94 -22.023 -4.312 -7.342 1.00 96.48 C
ATOM 3062 C SER B 94 -21.638 -3.086 -6.516 1.00 95.30 C
ATOM 3063 O SER B 94 -21.013 -2.147 -7.034 1.00 94.98 O
ATOM 3064 CB SER B 94 -20.783 -5.176 -7.589 1.00 96.70 C
ATOM 3065 OG SER B 94 -19.898 -4.553 -8.510 1.00 96.79 O
ATOM 3066 N VAL B 95 -22.026 -3.087 -5.239 1.00 92.94 N
ATOM 3067 CA VAL B 95 -21.714 -1.981 -4.332 1.00 89.32 C
ATOM 3068 C VAL B 95 -21.128 -2.534 -3.037 1.00 87.17 C
ATOM 3069 O VAL B 95 -21.855 -2.964 -2.137 1.00 86.40 O
ATOM 3070 CB VAL B 95 -22.959 -1.153 -4.010 1.00 88.54 C
ATOM 3071 CG1 VAL B 95 -22.531 0.205 -3.458 1.00 88.25 C
ATOM 3072 CG2 VAL B 95 -23.808 -0.988 -5.258 1.00 87.16 C
ATOM 3073 N VAL B 96 -19.802 -2.490 -2.958 1.00 85.04 N
ATOM 3074 CA VAL B 96 -19.058 -3.018 -1.828 1.00 83.33 C
ATOM 3075 C VAL B 96 -18.852 -2.116 -0.619 1.00 81.90 C
ATOM 3076 O VAL B 96 -17.957 -1.271 -0.613 1.00 81.87 O
ATOM 3077 CB VAL B 96 -17.664 -3.498 -2.283 1.00 83.38 C
ATOM 3078 CG1 VAL B 96 -16.938 -4.180 -1.129 1.00 83.72 C
ATOM 3079 CG2 VAL B 96 -17.806 -4.436 -3.459 1.00 83.57 C
ATOM 3080 N LEU B 97 -19.685 -2.302 0.404 1.00 80.03 N
ATOM 3081 CA LEU B 97 -19.536 -1.557 1.648 1.00 76.82 C
ATOM 3082 C LEU B 97 -18.270 -2.202 2.175 1.00 75.41 C
ATOM 3083 O LEU B 97 -18.115 -3.412 2.044 1.00 74.63 O
ATOM 3084 CB LEU B 97 -20.684 -1.854 2.610 1.00 75.09 C
ATOM 3085 CG LEU B 97 -22.097 -1.584 2.096 1.00 75.32 C
ATOM 3086 CD1 LEU B 97 -23.065 -1.659 3.262 1.00 72.55 C
ATOM 3087 CD2 LEU B 97 -22.153 -0.216 1.434 1.00 74.86 C
ATOM 3088 N GLY B 98 -17.361 -1.434 2.761 1.00 74.85 N
ATOM 3089 CA GLY B 98 -16.153 -2.080 3.215 1.00 74.16 C
ATOM 3090 C GLY B 98 -15.483 -1.782 4.535 1.00 74.60 C
ATOM 3091 O GLY B 98 -15.998 -1.109 5.427 1.00 73.56 O
ATOM 3092 N GLY B 99 -14.309 -2.384 4.634 1.00 75.85 N
ATOM 3093 CA GLY B 99 -13.442 -2.269 5.776 1.00 78.40 C
ATOM 3094 C GLY B 99 -12.306 -1.598 5.051 1.00 80.54 C
ATOM 3095 O GLY B 99 -12.579 -0.833 4.122 1.00 80.94 O
ATOM 3096 N ASP B 100 -11.058 -1.894 5.400 1.00 82.59 N
ATOM 3097 CA ASP B 100 -9.938 -1.243 4.721 1.00 84.85 C
ATOM 3098 C ASP B 100 -10.026 -1.354 3.190 1.00 84.58 C
ATOM 3099 O ASP B 100 -10.679 -2.246 2.647 1.00 84.05 O
ATOM 3100 CB ASP B 100 -8.602 -1.788 5.243 1.00 87.56 C
ATOM 3101 CG ASP B 100 -8.106 -2.982 4.467 1.00 90.13 C
ATOM 3102 OD1 ASP B 100 -7.757 -2.805 3.281 1.00 89.63 O
ATOM 3103 OD2 ASP B 100 -8.062 -4.088 5.052 1.00 92.61 O
ATOM 3104 N HIS B 101 -9.362 -0.425 2.514 1.00 84.89 N
ATOM 3105 CA HIS B 101 -9.368 -0.318 1.061 1.00 85.65 C
ATOM 3106 C HIS B 101 -8.639 -1.422 0.308 1.00 85.99 C
ATOM 3107 O HIS B 101 -8.484 -1.339 -0.911 1.00 85.93 O
ATOM 3108 CB HIS B 101 -8.788 1.050 0.672 1.00 86.72 C
ATOM 3109 CG HIS B 101 -9.302 1.599 -0.625 1.00 86.60 C
ATOM 3110 ND1 HIS B 101 -9.235 2.944 -0.934 1.00 85.54 N
ATOM 3111 CD2 HIS B 101 -9.848 0.992 -1.706 1.00 86.26 C
ATOM 3112 CE1 HIS B 101 -9.716 3.137 -2.146 1.00 86.39 C
ATOM 3113 NE2 HIS B 101 -10.095 1.969 -2.639 1.00 86.65 N
ATOM 3114 N SER B 102 -8.191 -2.458 1.008 1.00 86.24 N
ATOM 3115 CA SER B 102 -7.489 -3.543 0.328 1.00 86.63 C
ATOM 3116 C SER B 102 -8.488 -4.552 -0.229 1.00 85.62 C
ATOM 3117 O SER B 102 -8.108 -5.548 -0.839 1.00 84.65 O
ATOM 3118 CB SER B 102 -6.528 -4.239 1.282 1.00 87.71 C
ATOM 3119 OG SER B 102 -7.247 -4.977 2.251 1.00 91.99 O
ATOM 3120 N MET B 103 -9.772 -4.297 -0.002 1.00 85.08 N
ATOM 3121 CA MET B 103 -10.803 -5.177 -0.519 1.00 84.48 C
ATOM 3122 C MET B 103 -11.091 -4.693 -1.925 1.00 83.76 C
ATOM 3123 O MET B 103 -12.030 -5.150 -2.578 1.00 83.39 O
ATOM 3124 CB MET B 103 -12.069 -5.107 0.333 1.00 84.83 C
ATOM 3125 CG MET B 103 -11.860 -5.541 1.773 1.00 87.32 C
ATOM 3126 SD MET B 103 -11.005 -7.130 1.934 1.00 88.58 S
ATOM 3127 CE MET B 103 -12.298 -8.237 1.358 1.00 87.63 C
ATOM 3128 N ALA B 104 -10.269 -3.753 -2.383 1.00 83.38 N
ATOM 3129 CA ALA B 104 -10.405 -3.201 -3.723 1.00 83.07 C
ATOM 3130 C ALA B 104 -9.941 -4.243 -4.744 1.00 82.42 C
ATOM 3131 O ALA B 104 -10.565 -4.414 -5.797 1.00 82.21 O
ATOM 3132 CB ALA B 104 -9.581 -1.926 -3.849 1.00 84.51 C
ATOM 3133 N ILE B 105 -8.845 -4.939 -4.439 1.00 80.53 N
ATOM 3134 CA ILE B 105 -8.364 -5.983 -5.339 1.00 78.98 C
ATOM 3135 C ILE B 105 -9.543 -6.938 -5.564 1.00 77.86 C
ATOM 3136 O ILE B 105 -9.991 -7.134 -6.696 1.00 76.47 O
ATOM 3137 CB ILE B 105 -7.150 -6.777 -4.746 1.00 78.15 C
ATOM 3138 CG1 ILE B 105 -6.889 -6.388 -3.294 1.00 77.60 C
ATOM 3139 CG2 ILE B 105 -5.893 -6.469 -5.547 1.00 78.93 C
ATOM 3140 CD1 ILE B 105 -5.621 -7.026 -2.742 1.00 74.53 C
ATOM 3141 N GLY B 106 -10.054 -7.509 -4.476 1.00 76.94 N
ATOM 3142 CA GLY B 106 -11.186 -8.403 -4.583 1.00 76.15 C
ATOM 3143 C GLY B 106 -12.238 -7.814 -5.499 1.00 76.23 C
ATOM 3144 O GLY B 106 -12.437 -8.308 -6.605 1.00 77.43 O
ATOM 3145 N SER B 107 -12.900 -6.751 -5.051 1.00 75.72 N
ATOM 3146 CA SER B 107 -13.945 -6.094 -5.839 1.00 75.71 C
ATOM 3147 C SER B 107 -13.556 -5.892 -7.306 1.00 75.75 C
ATOM 3148 O SER B 107 -14.208 -6.415 -8.216 1.00 74.82 O
ATOM 3149 CB SER B 107 -14.293 -4.732 -5.214 1.00 76.72 C
ATOM 3150 OG SER B 107 -15.186 -3.966 -6.024 1.00 75.74 O
ATOM 3151 N ILE B 108 -12.486 -5.132 -7.525 1.00 75.95 N
ATOM 3152 CA ILE B 108 -12.023 -4.831 -8.868 1.00 75.58 C
ATOM 3153 C ILE B 108 -11.794 -6.085 -9.703 1.00 76.75 C
ATOM 3154 O ILE B 108 -12.282 -6.174 -10.829 1.00 77.19 O
ATOM 3155 CB ILE B 108 -10.747 -3.968 -8.822 1.00 74.49 C
ATOM 3156 CG1 ILE B 108 -11.037 -2.670 -8.065 1.00 73.59 C
ATOM 3157 CG2 ILE B 108 -10.294 -3.639 -10.228 1.00 75.30 C
ATOM 3158 CD1 ILE B 108 -9.947 -1.642 -8.136 1.00 71.41 C
ATOM 3159 N SER B 109 -11.067 -7.056 -9.154 1.00 77.84 N
ATOM 3160 CA SER B 109 -10.814 -8.311 -9.865 1.00 78.47 C
ATOM 3161 C SER B 109 -12.136 -8.934 -10.282 1.00 78.55 C
ATOM 3162 O SER B 109 -12.403 -9.113 -11.467 1.00 77.36 O
ATOM 3163 CB SER B 109 -10.057 -9.295 -8.967 1.00 78.95 C
ATOM 3164 OG SER B 109 -8.674 -8.996 -8.938 1.00 81.14 O
ATOM 3165 N GLY B 110 -12.955 -9.262 -9.288 1.00 79.20 N
ATOM 3166 CA GLY B 110 -14.244 -9.855 -9.556 1.00 81.12 C
ATOM 3167 C GLY B 110 -14.948 -9.133 -10.682 1.00 83.10 C
ATOM 3168 O GLY B 110 -15.540 -9.763 -11.555 1.00 83.47 O
ATOM 3169 N HIS B 111 -14.874 -7.807 -10.674 1.00 85.03 N
ATOM 3170 CA HIS B 111 -15.519 -6.999 -11.707 1.00 87.81 C
ATOM 3171 C HIS B 111 -14.949 -7.243 -13.119 1.00 88.96 C
ATOM 3172 O HIS B 111 -15.705 -7.466 -14.073 1.00 87.29 O
ATOM 3173 CB HIS B 111 -15.402 -5.510 -11.340 1.00 88.57 C
ATOM 3174 CG HIS B 111 -16.248 -4.606 -12.188 1.00 89.32 C
ATOM 3175 ND1 HIS B 111 -16.233 -3.234 -12.053 1.00 89.05 N
ATOM 3176 CD2 HIS B 111 -17.125 -4.876 -13.186 1.00 88.94 C
ATOM 3177 CE1 HIS B 111 -17.062 -2.699 -12.933 1.00 89.41 C
ATOM 3178 NE2 HIS B 111 -17.615 -3.673 -13.632 1.00 88.73 N
ATOM 3179 N ALA B 112 -13.619 -7.199 -13.232 1.00 90.99 N
ATOM 3180 CA ALA B 112 -12.898 -7.389 -14.500 1.00 92.37 C
ATOM 3181 C ALA B 112 -13.189 -8.728 -15.175 1.00 93.72 C
ATOM 3182 O ALA B 112 -13.038 -8.874 -16.395 1.00 93.91 O
ATOM 3183 CB ALA B 112 -11.389 -7.246 -14.265 1.00 91.27 C
ATOM 3184 N ARG B 113 -13.592 -9.708 -14.376 1.00 94.50 N
ATOM 3185 CA ARG B 113 -13.905 -11.025 -14.897 1.00 94.94 C
ATOM 3186 C ARG B 113 -15.069 -10.951 -15.880 1.00 95.62 C
ATOM 3187 O ARG B 113 -15.027 -11.559 -16.948 1.00 96.16 O
ATOM 3188 CB ARG B 113 -14.211 -11.982 -13.734 1.00 94.28 C
ATOM 3189 CG ARG B 113 -12.940 -12.437 -13.022 1.00 94.48 C
ATOM 3190 CD ARG B 113 -13.182 -13.213 -11.734 1.00 95.26 C
ATOM 3191 NE ARG B 113 -11.923 -13.750 -11.203 1.00 96.22 N
ATOM 3192 CZ ARG B 113 -11.750 -14.232 -9.968 1.00 96.89 C
ATOM 3193 NH1 ARG B 113 -12.758 -14.252 -9.097 1.00 96.87 N
ATOM 3194 NH2 ARG B 113 -10.559 -14.699 -9.600 1.00 96.57 N
ATOM 3195 N VAL B 114 -16.093 -10.180 -15.531 1.00 96.02 N
ATOM 3196 CA VAL B 114 -17.264 -10.040 -16.385 1.00 96.73 C
ATOM 3197 C VAL B 114 -17.139 -8.884 -17.382 1.00 97.56 C
ATOM 3198 O VAL B 114 -17.715 -8.929 -18.470 1.00 97.44 O
ATOM 3199 CB VAL B 114 -18.528 -9.851 -15.527 1.00 97.09 C
ATOM 3200 CG1 VAL B 114 -19.763 -9.846 -16.412 1.00 97.30 C
ATOM 3201 CG2 VAL B 114 -18.612 -10.963 -14.478 1.00 96.77 C
ATOM 3202 N HIS B 115 -16.386 -7.853 -17.001 1.00 99.09 N
ATOM 3203 CA HIS B 115 -16.163 -6.678 -17.852 1.00100.13 C
ATOM 3204 C HIS B 115 -14.690 -6.276 -17.791 1.00100.23 C
ATOM 3205 O HIS B 115 -14.320 -5.350 -17.076 1.00100.81 O
ATOM 3206 CB HIS B 115 -17.012 -5.492 -17.386 1.00100.57 C
ATOM 3207 CG HIS B 115 -18.486 -5.756 -17.386 1.00101.28 C
ATOM 3208 ND1 HIS B 115 -19.107 -6.510 -16.416 1.00101.75 N
ATOM 3209 CD2 HIS B 115 -19.464 -5.334 -18.222 1.00101.64 C
ATOM 3210 CE1 HIS B 115 -20.409 -6.537 -16.650 1.00102.42 C
ATOM 3211 NE2 HIS B 115 -20.651 -5.831 -17.738 1.00102.31 N
ATOM 3212 N PRO B 116 -13.839 -6.963 -18.557 1.00100.42 N
ATOM 3213 CA PRO B 116 -12.395 -6.729 -18.626 1.00100.72 C
ATOM 3214 C PRO B 116 -12.011 -5.455 -19.359 1.00100.87 C
ATOM 3215 O PRO B 116 -10.824 -5.163 -19.532 1.00100.56 O
ATOM 3216 CB PRO B 116 -11.901 -7.960 -19.356 1.00101.70 C
ATOM 3217 CG PRO B 116 -12.994 -8.148 -20.378 1.00102.18 C
ATOM 3218 CD PRO B 116 -14.247 -7.985 -19.537 1.00101.10 C
ATOM 3219 N ASP B 117 -13.013 -4.705 -19.803 1.00101.28 N
ATOM 3220 CA ASP B 117 -12.761 -3.458 -20.524 1.00102.06 C
ATOM 3221 C ASP B 117 -13.019 -2.225 -19.655 1.00101.05 C
ATOM 3222 O ASP B 117 -12.912 -1.090 -20.126 1.00101.44 O
ATOM 3223 CB ASP B 117 -13.626 -3.399 -21.791 1.00103.66 C
ATOM 3224 CG ASP B 117 -15.113 -3.571 -21.500 1.00105.43 C
ATOM 3225 OD1 ASP B 117 -15.480 -4.545 -20.801 1.00106.09 O
ATOM 3226 OD2 ASP B 117 -15.913 -2.736 -21.981 1.00106.50 O
ATOM 3227 N LEU B 118 -13.341 -2.460 -18.382 1.00 98.82 N
ATOM 3228 CA LEU B 118 -13.632 -1.385 -17.433 1.00 95.55 C
ATOM 3229 C LEU B 118 -12.461 -0.432 -17.162 1.00 93.68 C
ATOM 3230 O LEU B 118 -11.291 -0.747 -17.417 1.00 93.41 O
ATOM 3231 CB LEU B 118 -14.122 -1.974 -16.090 1.00 93.59 C
ATOM 3232 CG LEU B 118 -13.182 -2.854 -15.244 1.00 92.16 C
ATOM 3233 CD1 LEU B 118 -11.993 -2.056 -14.737 1.00 92.08 C
ATOM 3234 CD2 LEU B 118 -13.949 -3.409 -14.070 1.00 90.84 C
ATOM 3235 N CYS B 119 -12.806 0.748 -16.660 1.00 90.59 N
ATOM 3236 CA CYS B 119 -11.832 1.759 -16.288 1.00 86.30 C
ATOM 3237 C CYS B 119 -12.017 1.830 -14.791 1.00 83.38 C
ATOM 3238 O CYS B 119 -12.793 1.064 -14.228 1.00 83.17 O
ATOM 3239 CB CYS B 119 -12.178 3.100 -16.922 1.00 85.90 C
ATOM 3240 SG CYS B 119 -13.942 3.421 -16.918 1.00 85.58 S
ATOM 3241 N VAL B 120 -11.326 2.749 -14.142 1.00 80.52 N
ATOM 3242 CA VAL B 120 -11.441 2.864 -12.700 1.00 76.40 C
ATOM 3243 C VAL B 120 -11.195 4.283 -12.211 1.00 73.42 C
ATOM 3244 O VAL B 120 -10.165 4.881 -12.508 1.00 72.14 O
ATOM 3245 CB VAL B 120 -10.439 1.900 -11.989 1.00 75.95 C
ATOM 3246 CG1 VAL B 120 -10.341 2.241 -10.507 1.00 74.91 C
ATOM 3247 CG2 VAL B 120 -10.894 0.446 -12.171 1.00 73.63 C
ATOM 3248 N ILE B 121 -12.157 4.819 -11.470 1.00 71.26 N
ATOM 3249 CA ILE B 121 -12.024 6.155 -10.887 1.00 69.79 C
ATOM 3250 C ILE B 121 -11.694 5.912 -9.408 1.00 66.24 C
ATOM 3251 O ILE B 121 -12.475 5.304 -8.672 1.00 65.09 O
ATOM 3252 CB ILE B 121 -13.342 6.995 -11.026 1.00 71.19 C
ATOM 3253 CG1 ILE B 121 -13.603 7.366 -12.492 1.00 71.26 C
ATOM 3254 CG2 ILE B 121 -13.216 8.293 -10.251 1.00 71.09 C
ATOM 3255 CD1 ILE B 121 -13.551 6.198 -13.447 1.00 72.36 C
ATOM 3256 N TRP B 122 -10.526 6.372 -8.987 1.00 62.73 N
ATOM 3257 CA TRP B 122 -10.084 6.154 -7.620 1.00 60.62 C
ATOM 3258 C TRP B 122 -10.037 7.428 -6.770 1.00 60.19 C
ATOM 3259 O TRP B 122 -9.059 8.188 -6.806 1.00 59.32 O
ATOM 3260 CB TRP B 122 -8.709 5.470 -7.664 1.00 58.94 C
ATOM 3261 CG TRP B 122 -8.180 4.952 -6.347 1.00 56.58 C
ATOM 3262 CD1 TRP B 122 -7.600 5.683 -5.347 1.00 55.86 C
ATOM 3263 CD2 TRP B 122 -8.131 3.582 -5.919 1.00 55.45 C
ATOM 3264 NE1 TRP B 122 -7.188 4.856 -4.324 1.00 55.24 N
ATOM 3265 CE2 TRP B 122 -7.511 3.561 -4.643 1.00 55.02 C
ATOM 3266 CE3 TRP B 122 -8.567 2.370 -6.476 1.00 54.23 C
ATOM 3267 CZ2 TRP B 122 -7.293 2.379 -3.929 1.00 54.64 C
ATOM 3268 CZ3 TRP B 122 -8.355 1.185 -5.764 1.00 54.27 C
ATOM 3269 CH2 TRP B 122 -7.730 1.202 -4.500 1.00 55.66 C
ATOM 3270 N VAL B 123 -11.110 7.657 -6.014 1.00 59.72 N
ATOM 3271 CA VAL B 123 -11.191 8.813 -5.117 1.00 59.40 C
ATOM 3272 C VAL B 123 -10.670 8.353 -3.741 1.00 57.38 C
ATOM 3273 O VAL B 123 -11.347 7.635 -3.000 1.00 55.82 O
ATOM 3274 CB VAL B 123 -12.643 9.340 -4.970 1.00 59.65 C
ATOM 3275 CG1 VAL B 123 -12.630 10.698 -4.309 1.00 58.94 C
ATOM 3276 CG2 VAL B 123 -13.314 9.434 -6.323 1.00 58.72 C
ATOM 3277 N ASP B 124 -9.448 8.775 -3.430 1.00 55.40 N
ATOM 3278 CA ASP B 124 -8.752 8.407 -2.199 1.00 54.22 C
ATOM 3279 C ASP B 124 -7.793 9.566 -1.995 1.00 55.31 C
ATOM 3280 O ASP B 124 -7.477 10.282 -2.958 1.00 55.23 O
ATOM 3281 CB ASP B 124 -7.962 7.105 -2.447 1.00 50.71 C
ATOM 3282 CG ASP B 124 -7.432 6.474 -1.191 1.00 47.58 C
ATOM 3283 OD1 ASP B 124 -6.719 7.143 -0.427 1.00 46.94 O
ATOM 3284 OD2 ASP B 124 -7.707 5.280 -0.962 1.00 46.77 O
ATOM 3285 N ALA B 125 -7.347 9.772 -0.759 1.00 56.37 N
ATOM 3286 CA ALA B 125 -6.379 10.834 -0.490 1.00 57.62 C
ATOM 3287 C ALA B 125 -5.036 10.288 -0.994 1.00 58.34 C
ATOM 3288 O ALA B 125 -4.186 11.022 -1.505 1.00 56.62 O
ATOM 3289 CB ALA B 125 -6.302 11.126 1.010 1.00 56.07 C
ATOM 3290 N HIS B 126 -4.896 8.969 -0.869 1.00 59.92 N
ATOM 3291 CA HIS B 126 -3.705 8.232 -1.250 1.00 61.14 C
ATOM 3292 C HIS B 126 -3.844 7.466 -2.552 1.00 64.86 C
ATOM 3293 O HIS B 126 -4.955 7.084 -2.949 1.00 65.54 O
ATOM 3294 CB HIS B 126 -3.362 7.232 -0.154 1.00 58.52 C
ATOM 3295 CG HIS B 126 -3.692 7.721 1.211 1.00 57.04 C
ATOM 3296 ND1 HIS B 126 -4.911 7.483 1.809 1.00 59.20 N
ATOM 3297 CD2 HIS B 126 -3.010 8.536 2.048 1.00 55.86 C
ATOM 3298 CE1 HIS B 126 -4.972 8.142 2.954 1.00 58.98 C
ATOM 3299 NE2 HIS B 126 -3.831 8.789 3.122 1.00 58.70 N
ATOM 3300 N THR B 127 -2.697 7.236 -3.194 1.00 67.28 N
ATOM 3301 CA THR B 127 -2.617 6.475 -4.434 1.00 69.38 C
ATOM 3302 C THR B 127 -2.747 4.999 -4.039 1.00 70.18 C
ATOM 3303 O THR B 127 -3.415 4.210 -4.718 1.00 68.18 O
ATOM 3304 CB THR B 127 -1.255 6.699 -5.140 1.00 71.32 C
ATOM 3305 OG1 THR B 127 -0.231 6.861 -4.149 1.00 72.91 O
ATOM 3306 CG2 THR B 127 -1.295 7.933 -6.043 1.00 70.67 C
ATOM 3307 N ASP B 128 -2.110 4.645 -2.921 1.00 72.64 N
ATOM 3308 CA ASP B 128 -2.134 3.275 -2.406 1.00 76.54 C
ATOM 3309 C ASP B 128 -1.508 2.328 -3.445 1.00 78.32 C
ATOM 3310 O ASP B 128 -1.783 1.124 -3.462 1.00 77.37 O
ATOM 3311 CB ASP B 128 -3.590 2.824 -2.106 1.00 76.13 C
ATOM 3312 CG ASP B 128 -4.331 3.767 -1.149 1.00 74.37 C
ATOM 3313 OD1 ASP B 128 -3.684 4.348 -0.247 1.00 74.66 O
ATOM 3314 OD2 ASP B 128 -5.567 3.913 -1.300 1.00 71.25 O
ATOM 3315 N ILE B 129 -0.662 2.898 -4.305 1.00 81.57 N
ATOM 3316 CA ILE B 129 0.017 2.181 -5.392 1.00 82.62 C
ATOM 3317 C ILE B 129 1.421 1.664 -5.020 1.00 83.95 C
ATOM 3318 O ILE B 129 2.257 1.405 -5.893 1.00 83.15 O
ATOM 3319 CB ILE B 129 0.078 3.099 -6.680 1.00 81.91 C
ATOM 3320 CG1 ILE B 129 0.652 2.330 -7.858 1.00 81.40 C
ATOM 3321 CG2 ILE B 129 0.892 4.364 -6.401 1.00 80.22 C
ATOM 3322 CD1 ILE B 129 -0.094 1.065 -8.152 1.00 82.11 C
ATOM 3323 N ASN B 130 1.659 1.495 -3.718 1.00 85.83 N
ATOM 3324 CA ASN B 130 2.933 0.990 -3.225 1.00 86.95 C
ATOM 3325 C ASN B 130 2.986 -0.528 -3.343 1.00 87.55 C
ATOM 3326 O ASN B 130 1.961 -1.208 -3.348 1.00 87.00 O
ATOM 3327 CB ASN B 130 3.169 1.389 -1.759 1.00 88.13 C
ATOM 3328 CG ASN B 130 3.840 2.754 -1.616 1.00 90.24 C
ATOM 3329 OD1 ASN B 130 4.710 3.120 -2.410 1.00 91.56 O
ATOM 3330 ND2 ASN B 130 3.448 3.503 -0.588 1.00 91.70 N
ATOM 3331 N THR B 131 4.201 -1.046 -3.441 1.00 88.52 N
ATOM 3332 CA THR B 131 4.432 -2.470 -3.561 1.00 88.78 C
ATOM 3333 C THR B 131 5.092 -2.979 -2.284 1.00 90.67 C
ATOM 3334 O THR B 131 5.545 -2.192 -1.442 1.00 89.83 O
ATOM 3335 CB THR B 131 5.354 -2.747 -4.737 1.00 87.72 C
ATOM 3336 OG1 THR B 131 6.624 -2.123 -4.500 1.00 86.20 O
ATOM 3337 CG2 THR B 131 4.750 -2.186 -6.009 1.00 87.64 C
ATOM 3338 N PRO B 132 5.147 -4.311 -2.121 1.00 92.13 N
ATOM 3339 CA PRO B 132 5.750 -4.970 -0.953 1.00 92.76 C
ATOM 3340 C PRO B 132 7.186 -4.484 -0.746 1.00 92.59 C
ATOM 3341 O PRO B 132 7.770 -4.621 0.338 1.00 91.94 O
ATOM 3342 CB PRO B 132 5.694 -6.452 -1.333 1.00 93.72 C
ATOM 3343 CG PRO B 132 4.462 -6.535 -2.201 1.00 92.98 C
ATOM 3344 CD PRO B 132 4.602 -5.308 -3.064 1.00 92.38 C
ATOM 3345 N LEU B 133 7.726 -3.918 -1.823 1.00 92.49 N
ATOM 3346 CA LEU B 133 9.085 -3.391 -1.883 1.00 92.47 C
ATOM 3347 C LEU B 133 9.132 -1.971 -1.343 1.00 92.31 C
ATOM 3348 O LEU B 133 9.994 -1.621 -0.530 1.00 92.59 O
ATOM 3349 CB LEU B 133 9.561 -3.378 -3.338 1.00 92.42 C
ATOM 3350 CG LEU B 133 9.297 -4.637 -4.167 1.00 93.22 C
ATOM 3351 CD1 LEU B 133 9.806 -4.427 -5.590 1.00 92.74 C
ATOM 3352 CD2 LEU B 133 9.974 -5.840 -3.508 1.00 93.47 C
ATOM 3353 N THR B 134 8.192 -1.160 -1.817 1.00 91.80 N
ATOM 3354 CA THR B 134 8.081 0.244 -1.439 1.00 90.29 C
ATOM 3355 C THR B 134 7.543 0.491 -0.025 1.00 88.61 C
ATOM 3356 O THR B 134 8.244 1.035 0.825 1.00 87.36 O
ATOM 3357 CB THR B 134 7.174 0.963 -2.431 1.00 90.62 C
ATOM 3358 OG1 THR B 134 5.884 0.348 -2.405 1.00 91.28 O
ATOM 3359 CG2 THR B 134 7.732 0.854 -3.839 1.00 89.53 C
ATOM 3360 N THR B 135 6.296 0.092 0.209 1.00 87.08 N
ATOM 3361 CA THR B 135 5.644 0.280 1.502 1.00 87.00 C
ATOM 3362 C THR B 135 6.565 0.270 2.707 1.00 86.71 C
ATOM 3363 O THR B 135 7.435 -0.583 2.822 1.00 86.97 O
ATOM 3364 CB THR B 135 4.585 -0.792 1.770 1.00 86.89 C
ATOM 3365 OG1 THR B 135 5.076 -2.062 1.332 1.00 85.36 O
ATOM 3366 CG2 THR B 135 3.281 -0.453 1.069 1.00 87.48 C
ATOM 3367 N SER B 136 6.360 1.235 3.600 1.00 86.78 N
ATOM 3368 CA SER B 136 7.115 1.329 4.839 1.00 87.04 C
ATOM 3369 C SER B 136 6.182 0.713 5.855 1.00 88.13 C
ATOM 3370 O SER B 136 6.166 1.091 7.026 1.00 88.17 O
ATOM 3371 CB SER B 136 7.398 2.780 5.222 1.00 86.80 C
ATOM 3372 OG SER B 136 8.532 3.283 4.546 1.00 87.18 O
ATOM 3373 N SER B 137 5.380 -0.228 5.372 1.00 89.21 N
ATOM 3374 CA SER B 137 4.419 -0.935 6.204 1.00 91.19 C
ATOM 3375 C SER B 137 3.835 -2.062 5.368 1.00 91.93 C
ATOM 3376 O SER B 137 3.697 -1.935 4.150 1.00 90.67 O
ATOM 3377 CB SER B 137 3.309 0.016 6.653 1.00 92.06 C
ATOM 3378 OG SER B 137 2.600 0.526 5.525 1.00 93.47 O
ATOM 3379 N GLY B 138 3.502 -3.165 6.029 1.00 93.57 N
ATOM 3380 CA GLY B 138 2.954 -4.311 5.327 1.00 95.55 C
ATOM 3381 C GLY B 138 1.454 -4.211 5.166 1.00 96.50 C
ATOM 3382 O GLY B 138 0.762 -5.192 4.854 1.00 97.48 O
ATOM 3383 N ASN B 139 0.961 -2.997 5.378 1.00 96.37 N
ATOM 3384 CA ASN B 139 -0.455 -2.675 5.285 1.00 95.32 C
ATOM 3385 C ASN B 139 -0.884 -2.682 3.817 1.00 94.83 C
ATOM 3386 O ASN B 139 -0.823 -1.667 3.115 1.00 94.93 O
ATOM 3387 CB ASN B 139 -0.674 -1.304 5.916 1.00 95.07 C
ATOM 3388 CG ASN B 139 0.121 -1.130 7.206 1.00 95.16 C
ATOM 3389 OD1 ASN B 139 1.248 -1.625 7.334 1.00 96.11 O
ATOM 3390 ND2 ASN B 139 -0.455 -0.416 8.161 1.00 95.53 N
ATOM 3391 N LEU B 140 -1.314 -3.847 3.360 1.00 93.89 N
ATOM 3392 CA LEU B 140 -1.741 -4.011 1.986 1.00 94.05 C
ATOM 3393 C LEU B 140 -2.866 -3.076 1.541 1.00 94.50 C
ATOM 3394 O LEU B 140 -3.200 -3.040 0.354 1.00 94.62 O
ATOM 3395 CB LEU B 140 -2.145 -5.466 1.748 1.00 93.18 C
ATOM 3396 CG LEU B 140 -0.977 -6.444 1.707 1.00 91.51 C
ATOM 3397 CD1 LEU B 140 -1.438 -7.790 2.201 1.00 91.57 C
ATOM 3398 CD2 LEU B 140 -0.417 -6.521 0.295 1.00 89.96 C
ATOM 3399 N HIS B 141 -3.457 -2.324 2.474 1.00 94.12 N
ATOM 3400 CA HIS B 141 -4.526 -1.396 2.098 1.00 93.21 C
ATOM 3401 C HIS B 141 -3.891 -0.227 1.353 1.00 93.53 C
ATOM 3402 O HIS B 141 -4.579 0.695 0.910 1.00 93.63 O
ATOM 3403 CB HIS B 141 -5.307 -0.887 3.328 1.00 90.47 C
ATOM 3404 CG HIS B 141 -4.581 0.144 4.147 1.00 88.47 C
ATOM 3405 ND1 HIS B 141 -5.170 0.780 5.218 1.00 86.91 N
ATOM 3406 CD2 HIS B 141 -3.326 0.646 4.053 1.00 87.52 C
ATOM 3407 CE1 HIS B 141 -4.308 1.633 5.749 1.00 86.12 C
ATOM 3408 NE2 HIS B 141 -3.183 1.572 5.061 1.00 85.96 N
ATOM 3409 N GLY B 142 -2.565 -0.278 1.235 1.00 93.98 N
ATOM 3410 CA GLY B 142 -1.825 0.764 0.547 1.00 95.37 C
ATOM 3411 C GLY B 142 -1.052 0.214 -0.641 1.00 96.23 C
ATOM 3412 O GLY B 142 -0.005 0.751 -1.014 1.00 95.98 O
ATOM 3413 N GLN B 143 -1.587 -0.858 -1.227 1.00 96.91 N
ATOM 3414 CA GLN B 143 -0.996 -1.543 -2.376 1.00 97.13 C
ATOM 3415 C GLN B 143 -2.004 -2.038 -3.439 1.00 97.15 C
ATOM 3416 O GLN B 143 -1.625 -2.313 -4.575 1.00 96.46 O
ATOM 3417 CB GLN B 143 -0.169 -2.727 -1.872 1.00 97.37 C
ATOM 3418 CG GLN B 143 0.926 -2.306 -0.902 1.00 98.88 C
ATOM 3419 CD GLN B 143 1.679 -3.478 -0.296 1.00 99.70 C
ATOM 3420 OE1 GLN B 143 2.187 -4.345 -1.007 1.00 98.74 O
ATOM 3421 NE2 GLN B 143 1.766 -3.497 1.031 1.00100.53 N
ATOM 3422 N PRO B 144 -3.301 -2.129 -3.091 1.00 97.65 N
ATOM 3423 CA PRO B 144 -4.349 -2.595 -4.006 1.00 97.32 C
ATOM 3424 C PRO B 144 -4.166 -2.404 -5.506 1.00 96.74 C
ATOM 3425 O PRO B 144 -4.523 -3.282 -6.289 1.00 96.95 O
ATOM 3426 CB PRO B 144 -5.590 -1.879 -3.489 1.00 97.93 C
ATOM 3427 CG PRO B 144 -5.375 -1.924 -2.024 1.00 98.75 C
ATOM 3428 CD PRO B 144 -3.921 -1.512 -1.901 1.00 98.52 C
ATOM 3429 N VAL B 145 -3.628 -1.265 -5.918 1.00 96.76 N
ATOM 3430 CA VAL B 145 -3.455 -1.022 -7.348 1.00 96.67 C
ATOM 3431 C VAL B 145 -2.273 -1.818 -7.901 1.00 95.18 C
ATOM 3432 O VAL B 145 -2.302 -2.283 -9.046 1.00 94.04 O
ATOM 3433 CB VAL B 145 -3.260 0.499 -7.644 1.00 97.80 C
ATOM 3434 CG1 VAL B 145 -3.156 0.730 -9.144 1.00 97.24 C
ATOM 3435 CG2 VAL B 145 -4.430 1.305 -7.076 1.00 97.02 C
ATOM 3436 N ALA B 146 -1.246 -1.978 -7.071 1.00 94.06 N
ATOM 3437 CA ALA B 146 -0.042 -2.710 -7.445 1.00 93.54 C
ATOM 3438 C ALA B 146 -0.332 -4.187 -7.757 1.00 93.29 C
ATOM 3439 O ALA B 146 0.470 -4.866 -8.410 1.00 93.69 O
ATOM 3440 CB ALA B 146 0.997 -2.597 -6.326 1.00 92.75 C
ATOM 3441 N PHE B 147 -1.475 -4.679 -7.289 1.00 91.80 N
ATOM 3442 CA PHE B 147 -1.866 -6.061 -7.538 1.00 89.97 C
ATOM 3443 C PHE B 147 -2.743 -6.157 -8.765 1.00 88.94 C
ATOM 3444 O PHE B 147 -2.762 -7.175 -9.452 1.00 88.67 O
ATOM 3445 CB PHE B 147 -2.630 -6.622 -6.349 1.00 90.00 C
ATOM 3446 CG PHE B 147 -1.761 -6.977 -5.204 1.00 90.95 C
ATOM 3447 CD1 PHE B 147 -1.178 -5.988 -4.427 1.00 91.17 C
ATOM 3448 CD2 PHE B 147 -1.480 -8.310 -4.926 1.00 91.91 C
ATOM 3449 CE1 PHE B 147 -0.321 -6.319 -3.380 1.00 92.42 C
ATOM 3450 CE2 PHE B 147 -0.626 -8.657 -3.886 1.00 92.68 C
ATOM 3451 CZ PHE B 147 -0.042 -7.659 -3.109 1.00 92.65 C
ATOM 3452 N LEU B 148 -3.471 -5.082 -9.031 1.00 88.06 N
ATOM 3453 CA LEU B 148 -4.383 -5.036 -10.154 1.00 87.82 C
ATOM 3454 C LEU B 148 -3.696 -4.569 -11.428 1.00 89.07 C
ATOM 3455 O LEU B 148 -4.144 -4.856 -12.541 1.00 88.06 O
ATOM 3456 CB LEU B 148 -5.549 -4.119 -9.796 1.00 85.29 C
ATOM 3457 CG LEU B 148 -6.193 -4.513 -8.467 1.00 82.72 C
ATOM 3458 CD1 LEU B 148 -7.247 -3.510 -8.069 1.00 81.84 C
ATOM 3459 CD2 LEU B 148 -6.791 -5.893 -8.605 1.00 82.23 C
ATOM 3460 N LEU B 149 -2.595 -3.851 -11.258 1.00 91.44 N
ATOM 3461 CA LEU B 149 -1.853 -3.347 -12.401 1.00 94.48 C
ATOM 3462 C LEU B 149 -1.004 -4.413 -13.072 1.00 96.57 C
ATOM 3463 O LEU B 149 -0.377 -5.248 -12.407 1.00 96.50 O
ATOM 3464 CB LEU B 149 -0.949 -2.182 -11.988 1.00 93.94 C
ATOM 3465 CG LEU B 149 -1.515 -0.766 -12.031 1.00 93.30 C
ATOM 3466 CD1 LEU B 149 -0.398 0.194 -11.681 1.00 92.84 C
ATOM 3467 CD2 LEU B 149 -2.075 -0.445 -13.422 1.00 93.57 C
ATOM 3468 N LYS B 150 -0.990 -4.363 -14.401 1.00 98.82 N
ATOM 3469 CA LYS B 150 -0.208 -5.289 -15.210 1.00100.82 C
ATOM 3470 C LYS B 150 1.234 -4.768 -15.267 1.00101.32 C
ATOM 3471 O LYS B 150 2.188 -5.523 -15.061 1.00101.72 O
ATOM 3472 CB LYS B 150 -0.795 -5.376 -16.625 1.00101.79 C
ATOM 3473 CG LYS B 150 -2.275 -5.755 -16.668 1.00102.99 C
ATOM 3474 CD LYS B 150 -2.821 -5.761 -18.097 1.00103.99 C
ATOM 3475 CE LYS B 150 -4.300 -6.158 -18.126 1.00104.51 C
ATOM 3476 NZ LYS B 150 -4.877 -6.213 -19.507 1.00104.60 N
ATOM 3477 N GLU B 151 1.380 -3.469 -15.529 1.00101.60 N
ATOM 3478 CA GLU B 151 2.690 -2.832 -15.614 1.00102.29 C
ATOM 3479 C GLU B 151 3.474 -2.981 -14.322 1.00102.54 C
ATOM 3480 O GLU B 151 4.597 -2.494 -14.208 1.00102.16 O
ATOM 3481 CB GLU B 151 2.544 -1.344 -15.929 1.00102.95 C
ATOM 3482 CG GLU B 151 1.896 -1.036 -17.264 1.00104.96 C
ATOM 3483 CD GLU B 151 0.390 -0.905 -17.173 1.00106.23 C
ATOM 3484 OE1 GLU B 151 -0.274 -1.873 -16.749 1.00107.34 O
ATOM 3485 OE2 GLU B 151 -0.131 0.172 -17.534 1.00107.33 O
ATOM 3486 N LEU B 152 2.878 -3.655 -13.351 1.00102.97 N
ATOM 3487 CA LEU B 152 3.530 -3.849 -12.072 1.00104.39 C
ATOM 3488 C LEU B 152 3.722 -5.324 -11.767 1.00105.77 C
ATOM 3489 O LEU B 152 4.354 -5.687 -10.771 1.00105.76 O
ATOM 3490 CB LEU B 152 2.701 -3.189 -10.976 1.00104.29 C
ATOM 3491 CG LEU B 152 3.371 -2.052 -10.202 1.00104.15 C
ATOM 3492 CD1 LEU B 152 4.245 -1.208 -11.111 1.00103.71 C
ATOM 3493 CD2 LEU B 152 2.284 -1.212 -9.568 1.00104.71 C
ATOM 3494 N LYS B 153 3.171 -6.173 -12.630 1.00107.04 N
ATOM 3495 CA LYS B 153 3.288 -7.614 -12.452 1.00107.67 C
ATOM 3496 C LYS B 153 4.759 -8.010 -12.530 1.00107.92 C
ATOM 3497 O LYS B 153 5.530 -7.443 -13.312 1.00108.76 O
ATOM 3498 CB LYS B 153 2.485 -8.350 -13.530 1.00107.80 C
ATOM 3499 CG LYS B 153 2.457 -9.864 -13.366 1.00108.64 C
ATOM 3500 CD LYS B 153 1.563 -10.528 -14.412 1.00109.46 C
ATOM 3501 CE LYS B 153 1.639 -12.057 -14.347 1.00110.70 C
ATOM 3502 NZ LYS B 153 1.166 -12.629 -13.046 1.00111.92 N
ATOM 3503 N GLY B 154 5.145 -8.976 -11.702 1.00107.54 N
ATOM 3504 CA GLY B 154 6.521 -9.425 -11.693 1.00107.33 C
ATOM 3505 C GLY B 154 7.472 -8.290 -11.379 1.00107.30 C
ATOM 3506 O GLY B 154 8.653 -8.347 -11.723 1.00108.46 O
ATOM 3507 N LYS B 155 6.955 -7.246 -10.742 1.00106.64 N
ATOM 3508 CA LYS B 155 7.773 -6.103 -10.362 1.00105.81 C
ATOM 3509 C LYS B 155 8.028 -6.197 -8.858 1.00105.92 C
ATOM 3510 O LYS B 155 8.609 -5.296 -8.248 1.00105.68 O
ATOM 3511 CB LYS B 155 7.058 -4.797 -10.714 1.00104.96 C
ATOM 3512 CG LYS B 155 6.860 -4.588 -12.205 1.00103.47 C
ATOM 3513 CD LYS B 155 8.198 -4.458 -12.909 1.00104.34 C
ATOM 3514 CE LYS B 155 8.031 -4.346 -14.420 1.00104.97 C
ATOM 3515 NZ LYS B 155 9.341 -4.172 -15.124 1.00103.63 N
ATOM 3516 N PHE B 156 7.582 -7.311 -8.281 1.00106.22 N
ATOM 3517 CA PHE B 156 7.738 -7.599 -6.858 1.00106.40 C
ATOM 3518 C PHE B 156 7.470 -9.085 -6.560 1.00106.38 C
ATOM 3519 O PHE B 156 6.734 -9.756 -7.293 1.00105.46 O
ATOM 3520 CB PHE B 156 6.813 -6.697 -6.014 1.00107.04 C
ATOM 3521 CG PHE B 156 5.349 -6.764 -6.398 1.00107.71 C
ATOM 3522 CD1 PHE B 156 4.920 -6.395 -7.677 1.00107.58 C
ATOM 3523 CD2 PHE B 156 4.395 -7.179 -5.467 1.00106.90 C
ATOM 3524 CE1 PHE B 156 3.568 -6.437 -8.020 1.00106.82 C
ATOM 3525 CE2 PHE B 156 3.046 -7.222 -5.797 1.00106.77 C
ATOM 3526 CZ PHE B 156 2.630 -6.851 -7.078 1.00107.12 C
ATOM 3527 N PRO B 157 8.079 -9.618 -5.481 1.00106.61 N
ATOM 3528 CA PRO B 157 7.915 -11.023 -5.082 1.00106.37 C
ATOM 3529 C PRO B 157 6.475 -11.447 -4.836 1.00106.46 C
ATOM 3530 O PRO B 157 5.808 -10.925 -3.941 1.00106.53 O
ATOM 3531 CB PRO B 157 8.773 -11.128 -3.821 1.00106.35 C
ATOM 3532 CG PRO B 157 8.714 -9.739 -3.247 1.00106.43 C
ATOM 3533 CD PRO B 157 8.893 -8.893 -4.487 1.00106.79 C
ATOM 3534 N ASP B 158 6.007 -12.402 -5.635 1.00106.90 N
ATOM 3535 CA ASP B 158 4.647 -12.917 -5.509 1.00106.90 C
ATOM 3536 C ASP B 158 4.306 -13.015 -4.026 1.00107.41 C
ATOM 3537 O ASP B 158 5.100 -13.508 -3.216 1.00107.55 O
ATOM 3538 CB ASP B 158 4.540 -14.281 -6.194 1.00104.94 C
ATOM 3539 CG ASP B 158 5.131 -14.266 -7.589 1.00104.15 C
ATOM 3540 OD1 ASP B 158 4.733 -13.396 -8.397 1.00103.27 O
ATOM 3541 OD2 ASP B 158 5.999 -15.115 -7.881 1.00103.26 O
ATOM 3542 N VAL B 159 3.125 -12.531 -3.669 1.00107.49 N
ATOM 3543 CA VAL B 159 2.718 -12.524 -2.277 1.00107.43 C
ATOM 3544 C VAL B 159 1.825 -13.686 -1.851 1.00105.92 C
ATOM 3545 O VAL B 159 0.900 -14.081 -2.570 1.00105.41 O
ATOM 3546 CB VAL B 159 2.026 -11.181 -1.930 1.00108.72 C
ATOM 3547 CG1 VAL B 159 1.711 -11.116 -0.436 1.00109.55 C
ATOM 3548 CG2 VAL B 159 2.928 -10.017 -2.342 1.00109.32 C
ATOM 3549 N PRO B 160 2.111 -14.248 -0.663 1.00104.72 N
ATOM 3550 CA PRO B 160 1.422 -15.365 -0.014 1.00104.41 C
ATOM 3551 C PRO B 160 -0.071 -15.154 0.213 1.00103.98 C
ATOM 3552 O PRO B 160 -0.478 -14.634 1.254 1.00103.74 O
ATOM 3553 CB PRO B 160 2.179 -15.514 1.300 1.00103.93 C
ATOM 3554 CG PRO B 160 3.556 -15.140 0.914 1.00103.63 C
ATOM 3555 CD PRO B 160 3.333 -13.905 0.086 1.00104.02 C
ATOM 3556 N GLY B 161 -0.875 -15.569 -0.763 1.00103.53 N
ATOM 3557 CA GLY B 161 -2.314 -15.447 -0.645 1.00103.26 C
ATOM 3558 C GLY B 161 -2.982 -14.761 -1.817 1.00103.11 C
ATOM 3559 O GLY B 161 -4.202 -14.838 -1.975 1.00102.78 O
ATOM 3560 N PHE B 162 -2.185 -14.112 -2.657 1.00102.76 N
ATOM 3561 CA PHE B 162 -2.729 -13.385 -3.794 1.00102.25 C
ATOM 3562 C PHE B 162 -2.404 -14.040 -5.124 1.00101.97 C
ATOM 3563 O PHE B 162 -2.409 -13.391 -6.168 1.00101.94 O
ATOM 3564 CB PHE B 162 -2.208 -11.952 -3.759 1.00101.45 C
ATOM 3565 CG PHE B 162 -2.297 -11.326 -2.399 1.00101.08 C
ATOM 3566 CD1 PHE B 162 -1.482 -11.772 -1.360 1.00100.76 C
ATOM 3567 CD2 PHE B 162 -3.226 -10.326 -2.139 1.00101.58 C
ATOM 3568 CE1 PHE B 162 -1.594 -11.239 -0.083 1.00100.12 C
ATOM 3569 CE2 PHE B 162 -3.346 -9.785 -0.860 1.00101.83 C
ATOM 3570 CZ PHE B 162 -2.527 -10.246 0.170 1.00101.45 C
ATOM 3571 N SER B 163 -2.123 -15.335 -5.077 1.00102.29 N
ATOM 3572 CA SER B 163 -1.807 -16.095 -6.278 1.00102.63 C
ATOM 3573 C SER B 163 -2.922 -15.897 -7.312 1.00102.57 C
ATOM 3574 O SER B 163 -2.674 -15.438 -8.430 1.00102.59 O
ATOM 3575 CB SER B 163 -1.669 -17.576 -5.921 1.00102.37 C
ATOM 3576 OG SER B 163 -0.763 -17.743 -4.840 1.00101.02 O
ATOM 3577 N TRP B 164 -4.146 -16.232 -6.905 1.00102.49 N
ATOM 3578 CA TRP B 164 -5.365 -16.117 -7.722 1.00101.47 C
ATOM 3579 C TRP B 164 -5.554 -14.739 -8.366 1.00 99.77 C
ATOM 3580 O TRP B 164 -6.363 -14.573 -9.281 1.00 98.35 O
ATOM 3581 CB TRP B 164 -6.580 -16.410 -6.843 1.00103.47 C
ATOM 3582 CG TRP B 164 -6.605 -15.536 -5.612 1.00106.13 C
ATOM 3583 CD1 TRP B 164 -6.009 -15.789 -4.402 1.00106.71 C
ATOM 3584 CD2 TRP B 164 -7.186 -14.230 -5.509 1.00106.44 C
ATOM 3585 NE1 TRP B 164 -6.190 -14.718 -3.555 1.00106.48 N
ATOM 3586 CE2 TRP B 164 -6.908 -13.759 -4.200 1.00106.26 C
ATOM 3587 CE3 TRP B 164 -7.922 -13.426 -6.385 1.00106.62 C
ATOM 3588 CZ2 TRP B 164 -7.334 -12.502 -3.768 1.00106.64 C
ATOM 3589 CZ3 TRP B 164 -8.342 -12.180 -5.949 1.00106.79 C
ATOM 3590 CH2 TRP B 164 -8.053 -11.734 -4.646 1.00107.31 C
ATOM 3591 N VAL B 165 -4.819 -13.753 -7.865 1.00 98.45 N
ATOM 3592 CA VAL B 165 -4.903 -12.399 -8.382 1.00 97.02 C
ATOM 3593 C VAL B 165 -4.240 -12.286 -9.747 1.00 96.57 C
ATOM 3594 O VAL B 165 -3.131 -12.775 -9.956 1.00 95.58 O
ATOM 3595 CB VAL B 165 -4.236 -11.407 -7.427 1.00 96.60 C
ATOM 3596 CG1 VAL B 165 -4.363 -9.999 -7.971 1.00 96.25 C
ATOM 3597 CG2 VAL B 165 -4.868 -11.521 -6.054 1.00 95.83 C
ATOM 3598 N THR B 166 -4.932 -11.625 -10.668 1.00 96.74 N
ATOM 3599 CA THR B 166 -4.435 -11.440 -12.025 1.00 96.80 C
ATOM 3600 C THR B 166 -4.429 -9.962 -12.410 1.00 96.74 C
ATOM 3601 O THR B 166 -5.489 -9.349 -12.553 1.00 96.41 O
ATOM 3602 CB THR B 166 -5.320 -12.186 -13.044 1.00 96.99 C
ATOM 3603 OG1 THR B 166 -5.587 -13.508 -12.564 1.00 97.70 O
ATOM 3604 CG2 THR B 166 -4.625 -12.270 -14.405 1.00 96.21 C
ATOM 3605 N PRO B 167 -3.232 -9.370 -12.571 1.00 96.68 N
ATOM 3606 CA PRO B 167 -3.140 -7.955 -12.949 1.00 97.04 C
ATOM 3607 C PRO B 167 -4.117 -7.727 -14.097 1.00 97.98 C
ATOM 3608 O PRO B 167 -3.886 -8.190 -15.212 1.00 98.54 O
ATOM 3609 CB PRO B 167 -1.686 -7.823 -13.371 1.00 96.70 C
ATOM 3610 CG PRO B 167 -0.992 -8.761 -12.403 1.00 96.21 C
ATOM 3611 CD PRO B 167 -1.894 -9.972 -12.413 1.00 95.91 C
ATOM 3612 N CYS B 168 -5.206 -7.015 -13.814 1.00 99.21 N
ATOM 3613 CA CYS B 168 -6.264 -6.783 -14.800 1.00100.39 C
ATOM 3614 C CYS B 168 -6.352 -5.471 -15.590 1.00100.22 C
ATOM 3615 O CYS B 168 -7.031 -5.430 -16.614 1.00100.36 O
ATOM 3616 CB CYS B 168 -7.623 -7.050 -14.139 1.00101.41 C
ATOM 3617 SG CYS B 168 -7.845 -6.252 -12.533 1.00102.86 S
ATOM 3618 N ILE B 169 -5.711 -4.397 -15.139 1.00100.14 N
ATOM 3619 CA ILE B 169 -5.784 -3.150 -15.906 1.00 99.43 C
ATOM 3620 C ILE B 169 -4.469 -2.389 -15.949 1.00100.06 C
ATOM 3621 O ILE B 169 -3.662 -2.443 -15.018 1.00 99.94 O
ATOM 3622 CB ILE B 169 -6.886 -2.188 -15.378 1.00 97.80 C
ATOM 3623 CG1 ILE B 169 -6.561 -1.732 -13.954 1.00 97.02 C
ATOM 3624 CG2 ILE B 169 -8.242 -2.863 -15.443 1.00 97.30 C
ATOM 3625 CD1 ILE B 169 -6.444 -2.847 -12.937 1.00 96.20 C
ATOM 3626 N SER B 170 -4.255 -1.691 -17.057 1.00100.49 N
ATOM 3627 CA SER B 170 -3.051 -0.901 -17.237 1.00101.32 C
ATOM 3628 C SER B 170 -3.299 0.513 -16.697 1.00101.91 C
ATOM 3629 O SER B 170 -4.423 0.844 -16.304 1.00102.46 O
ATOM 3630 CB SER B 170 -2.665 -0.877 -18.721 1.00100.78 C
ATOM 3631 OG SER B 170 -3.790 -0.673 -19.550 1.00100.26 O
ATOM 3632 N ALA B 171 -2.257 1.339 -16.670 1.00101.63 N
ATOM 3633 CA ALA B 171 -2.375 2.705 -16.163 1.00101.52 C
ATOM 3634 C ALA B 171 -3.198 3.602 -17.089 1.00101.47 C
ATOM 3635 O ALA B 171 -3.479 4.762 -16.774 1.00101.00 O
ATOM 3636 CB ALA B 171 -0.985 3.295 -15.958 1.00101.29 C
ATOM 3637 N LYS B 172 -3.592 3.051 -18.228 1.00101.77 N
ATOM 3638 CA LYS B 172 -4.368 3.800 -19.198 1.00102.19 C
ATOM 3639 C LYS B 172 -5.866 3.723 -18.933 1.00100.80 C
ATOM 3640 O LYS B 172 -6.660 4.377 -19.613 1.00100.93 O
ATOM 3641 CB LYS B 172 -4.046 3.290 -20.609 1.00104.75 C
ATOM 3642 CG LYS B 172 -3.092 4.201 -21.395 1.00107.35 C
ATOM 3643 CD LYS B 172 -1.866 4.633 -20.571 1.00107.90 C
ATOM 3644 CE LYS B 172 -1.129 5.791 -21.250 1.00108.26 C
ATOM 3645 NZ LYS B 172 -0.049 6.388 -20.410 1.00107.62 N
ATOM 3646 N ASP B 173 -6.249 2.935 -17.933 1.00 98.57 N
ATOM 3647 CA ASP B 173 -7.658 2.781 -17.601 1.00 95.87 C
ATOM 3648 C ASP B 173 -8.003 3.228 -16.177 1.00 92.84 C
ATOM 3649 O ASP B 173 -9.180 3.280 -15.808 1.00 92.74 O
ATOM 3650 CB ASP B 173 -8.092 1.321 -17.800 1.00 97.37 C
ATOM 3651 CG ASP B 173 -7.771 0.796 -19.193 1.00 97.26 C
ATOM 3652 OD1 ASP B 173 -8.142 1.454 -20.193 1.00 95.86 O
ATOM 3653 OD2 ASP B 173 -7.149 -0.287 -19.280 1.00 98.11 O
ATOM 3654 N ILE B 174 -6.978 3.550 -15.388 1.00 89.13 N
ATOM 3655 CA ILE B 174 -7.157 4.004 -14.003 1.00 83.93 C
ATOM 3656 C ILE B 174 -7.060 5.524 -13.876 1.00 80.70 C
ATOM 3657 O ILE B 174 -6.263 6.152 -14.562 1.00 80.98 O
ATOM 3658 CB ILE B 174 -6.087 3.390 -13.064 1.00 82.90 C
ATOM 3659 CG1 ILE B 174 -6.236 3.963 -11.659 1.00 81.94 C
ATOM 3660 CG2 ILE B 174 -4.701 3.706 -13.568 1.00 82.20 C
ATOM 3661 CD1 ILE B 174 -7.588 3.707 -11.058 1.00 82.59 C
ATOM 3662 N VAL B 175 -7.880 6.111 -13.006 1.00 77.49 N
ATOM 3663 CA VAL B 175 -7.853 7.560 -12.770 1.00 74.17 C
ATOM 3664 C VAL B 175 -8.051 7.875 -11.279 1.00 71.60 C
ATOM 3665 O VAL B 175 -9.050 7.483 -10.665 1.00 70.28 O
ATOM 3666 CB VAL B 175 -8.929 8.320 -13.614 1.00 73.83 C
ATOM 3667 CG1 VAL B 175 -8.871 9.814 -13.318 1.00 72.13 C
ATOM 3668 CG2 VAL B 175 -8.688 8.091 -15.088 1.00 71.71 C
ATOM 3669 N TYR B 176 -7.076 8.585 -10.715 1.00 68.81 N
ATOM 3670 CA TYR B 176 -7.073 8.979 -9.310 1.00 65.95 C
ATOM 3671 C TYR B 176 -7.610 10.380 -9.125 1.00 66.00 C
ATOM 3672 O TYR B 176 -7.255 11.277 -9.888 1.00 66.47 O
ATOM 3673 CB TYR B 176 -5.652 8.983 -8.784 1.00 63.07 C
ATOM 3674 CG TYR B 176 -5.086 7.641 -8.428 1.00 62.07 C
ATOM 3675 CD1 TYR B 176 -5.462 7.002 -7.259 1.00 61.02 C
ATOM 3676 CD2 TYR B 176 -4.056 7.081 -9.179 1.00 62.56 C
ATOM 3677 CE1 TYR B 176 -4.811 5.846 -6.826 1.00 60.83 C
ATOM 3678 CE2 TYR B 176 -3.395 5.923 -8.755 1.00 62.19 C
ATOM 3679 CZ TYR B 176 -3.775 5.316 -7.568 1.00 61.80 C
ATOM 3680 OH TYR B 176 -3.078 4.224 -7.093 1.00 61.14 O
ATOM 3681 N ILE B 177 -8.462 10.573 -8.121 1.00 66.80 N
ATOM 3682 CA ILE B 177 -8.993 11.909 -7.829 1.00 67.11 C
ATOM 3683 C ILE B 177 -8.943 12.117 -6.308 1.00 68.56 C
ATOM 3684 O ILE B 177 -9.424 11.272 -5.536 1.00 69.41 O
ATOM 3685 CB ILE B 177 -10.476 12.114 -8.312 1.00 65.54 C
ATOM 3686 CG1 ILE B 177 -10.781 11.253 -9.540 1.00 65.06 C
ATOM 3687 CG2 ILE B 177 -10.702 13.574 -8.693 1.00 61.44 C
ATOM 3688 CD1 ILE B 177 -12.174 11.462 -10.102 1.00 62.70 C
ATOM 3689 N GLY B 178 -8.326 13.224 -5.886 1.00 68.46 N
ATOM 3690 CA GLY B 178 -8.238 13.543 -4.471 1.00 68.24 C
ATOM 3691 C GLY B 178 -6.899 13.279 -3.802 1.00 68.59 C
ATOM 3692 O GLY B 178 -6.785 13.429 -2.575 1.00 68.65 O
ATOM 3693 N LEU B 179 -5.886 12.909 -4.587 1.00 67.99 N
ATOM 3694 CA LEU B 179 -4.557 12.617 -4.034 1.00 65.97 C
ATOM 3695 C LEU B 179 -3.933 13.836 -3.342 1.00 64.84 C
ATOM 3696 O LEU B 179 -3.894 14.943 -3.880 1.00 62.84 O
ATOM 3697 CB LEU B 179 -3.624 12.086 -5.136 1.00 63.88 C
ATOM 3698 CG LEU B 179 -4.179 10.888 -5.928 1.00 61.65 C
ATOM 3699 CD1 LEU B 179 -3.187 10.465 -7.000 1.00 60.43 C
ATOM 3700 CD2 LEU B 179 -4.487 9.742 -4.980 1.00 58.38 C
ATOM 3701 N ARG B 180 -3.448 13.616 -2.129 1.00 64.18 N
ATOM 3702 CA ARG B 180 -2.860 14.692 -1.370 1.00 63.57 C
ATOM 3703 C ARG B 180 -1.844 14.165 -0.365 1.00 65.71 C
ATOM 3704 O ARG B 180 -1.209 14.938 0.341 1.00 67.12 O
ATOM 3705 CB ARG B 180 -3.966 15.480 -0.665 1.00 60.48 C
ATOM 3706 CG ARG B 180 -4.323 14.955 0.707 1.00 58.48 C
ATOM 3707 CD ARG B 180 -5.518 15.663 1.300 1.00 55.45 C
ATOM 3708 NE ARG B 180 -6.708 15.223 0.605 1.00 58.34 N
ATOM 3709 CZ ARG B 180 -7.773 14.684 1.188 1.00 60.04 C
ATOM 3710 NH1 ARG B 180 -7.815 14.520 2.506 1.00 58.90 N
ATOM 3711 NH2 ARG B 180 -8.788 14.271 0.433 1.00 60.12 N
ATOM 3712 N ASP B 181 -1.692 12.850 -0.291 1.00 68.57 N
ATOM 3713 CA ASP B 181 -0.706 12.259 0.615 1.00 72.38 C
ATOM 3714 C ASP B 181 -0.037 11.049 -0.058 1.00 73.65 C
ATOM 3715 O ASP B 181 -0.304 9.881 0.270 1.00 72.86 O
ATOM 3716 CB ASP B 181 -1.367 11.861 1.942 1.00 74.74 C
ATOM 3717 CG ASP B 181 -0.476 10.962 2.793 1.00 76.50 C
ATOM 3718 OD1 ASP B 181 0.764 11.111 2.713 1.00 76.76 O
ATOM 3719 OD2 ASP B 181 -1.023 10.117 3.543 1.00 77.76 O
ATOM 3720 N VAL B 182 0.849 11.345 -1.003 1.00 75.62 N
ATOM 3721 CA VAL B 182 1.525 10.293 -1.748 1.00 77.84 C
ATOM 3722 C VAL B 182 2.977 10.057 -1.391 1.00 78.44 C
ATOM 3723 O VAL B 182 3.774 10.993 -1.388 1.00 79.02 O
ATOM 3724 CB VAL B 182 1.430 10.554 -3.262 1.00 78.31 C
ATOM 3725 CG1 VAL B 182 2.647 9.987 -3.981 1.00 79.03 C
ATOM 3726 CG2 VAL B 182 0.167 9.907 -3.806 1.00 79.08 C
ATOM 3727 N ASP B 183 3.306 8.788 -1.126 1.00 79.14 N
ATOM 3728 CA ASP B 183 4.660 8.361 -0.775 1.00 78.94 C
ATOM 3729 C ASP B 183 5.633 8.435 -1.947 1.00 79.30 C
ATOM 3730 O ASP B 183 5.234 8.328 -3.109 1.00 79.36 O
ATOM 3731 CB ASP B 183 4.645 6.935 -0.227 1.00 78.05 C
ATOM 3732 CG ASP B 183 4.123 6.866 1.189 1.00 79.06 C
ATOM 3733 OD1 ASP B 183 4.746 7.485 2.078 1.00 78.74 O
ATOM 3734 OD2 ASP B 183 3.090 6.198 1.419 1.00 80.08 O
ATOM 3735 N PRO B 184 6.931 8.616 -1.648 1.00 79.74 N
ATOM 3736 CA PRO B 184 7.977 8.706 -2.672 1.00 80.29 C
ATOM 3737 C PRO B 184 7.759 7.629 -3.733 1.00 81.42 C
ATOM 3738 O PRO B 184 7.329 7.920 -4.853 1.00 81.63 O
ATOM 3739 CB PRO B 184 9.257 8.472 -1.876 1.00 78.84 C
ATOM 3740 CG PRO B 184 8.927 9.023 -0.549 1.00 78.62 C
ATOM 3741 CD PRO B 184 7.530 8.513 -0.307 1.00 78.97 C
ATOM 3742 N GLY B 185 8.050 6.385 -3.353 1.00 81.81 N
ATOM 3743 CA GLY B 185 7.895 5.257 -4.251 1.00 82.31 C
ATOM 3744 C GLY B 185 6.664 5.377 -5.116 1.00 82.89 C
ATOM 3745 O GLY B 185 6.727 5.197 -6.330 1.00 82.84 O
ATOM 3746 N GLU B 186 5.537 5.688 -4.489 1.00 83.40 N
ATOM 3747 CA GLU B 186 4.296 5.839 -5.221 1.00 84.01 C
ATOM 3748 C GLU B 186 4.387 6.924 -6.298 1.00 85.43 C
ATOM 3749 O GLU B 186 3.922 6.718 -7.424 1.00 85.30 O
ATOM 3750 CB GLU B 186 3.152 6.131 -4.249 1.00 82.52 C
ATOM 3751 CG GLU B 186 2.481 4.883 -3.720 1.00 80.01 C
ATOM 3752 CD GLU B 186 1.644 5.155 -2.499 1.00 80.52 C
ATOM 3753 OE1 GLU B 186 2.236 5.608 -1.501 1.00 82.23 O
ATOM 3754 OE2 GLU B 186 0.413 4.920 -2.527 1.00 79.04 O
ATOM 3755 N HIS B 187 4.989 8.069 -5.969 1.00 87.43 N
ATOM 3756 CA HIS B 187 5.111 9.151 -6.947 1.00 89.34 C
ATOM 3757 C HIS B 187 5.891 8.644 -8.152 1.00 91.26 C
ATOM 3758 O HIS B 187 5.526 8.896 -9.305 1.00 91.25 O
ATOM 3759 CB HIS B 187 5.823 10.370 -6.352 1.00 88.09 C
ATOM 3760 CG HIS B 187 5.657 11.619 -7.170 1.00 87.99 C
ATOM 3761 ND1 HIS B 187 6.265 12.809 -6.853 1.00 88.58 N
ATOM 3762 CD2 HIS B 187 4.916 11.857 -8.280 1.00 87.65 C
ATOM 3763 CE1 HIS B 187 5.906 13.735 -7.730 1.00 87.86 C
ATOM 3764 NE2 HIS B 187 5.089 13.183 -8.603 1.00 86.86 N
ATOM 3765 N TYR B 188 6.973 7.929 -7.862 1.00 93.24 N
ATOM 3766 CA TYR B 188 7.829 7.346 -8.887 1.00 94.52 C
ATOM 3767 C TYR B 188 6.928 6.572 -9.842 1.00 93.43 C
ATOM 3768 O TYR B 188 6.784 6.921 -11.013 1.00 93.13 O
ATOM 3769 CB TYR B 188 8.824 6.390 -8.223 1.00 97.75 C
ATOM 3770 CG TYR B 188 9.882 5.835 -9.145 1.00101.26 C
ATOM 3771 CD1 TYR B 188 10.884 6.656 -9.651 1.00102.84 C
ATOM 3772 CD2 TYR B 188 9.885 4.488 -9.504 1.00103.00 C
ATOM 3773 CE1 TYR B 188 11.864 6.156 -10.492 1.00105.63 C
ATOM 3774 CE2 TYR B 188 10.863 3.971 -10.348 1.00105.61 C
ATOM 3775 CZ TYR B 188 11.851 4.813 -10.840 1.00106.52 C
ATOM 3776 OH TYR B 188 12.826 4.328 -11.685 1.00107.84 O
ATOM 3777 N ILE B 189 6.315 5.528 -9.299 1.00 91.82 N
ATOM 3778 CA ILE B 189 5.420 4.652 -10.024 1.00 89.96 C
ATOM 3779 C ILE B 189 4.395 5.370 -10.899 1.00 89.45 C
ATOM 3780 O ILE B 189 4.336 5.118 -12.098 1.00 90.11 O
ATOM 3781 CB ILE B 189 4.684 3.732 -9.041 1.00 89.42 C
ATOM 3782 CG1 ILE B 189 5.698 3.131 -8.066 1.00 89.61 C
ATOM 3783 CG2 ILE B 189 3.967 2.634 -9.794 1.00 88.40 C
ATOM 3784 CD1 ILE B 189 5.098 2.341 -6.905 1.00 90.14 C
ATOM 3785 N ILE B 190 3.592 6.263 -10.325 1.00 88.36 N
ATOM 3786 CA ILE B 190 2.581 6.969 -11.119 1.00 87.98 C
ATOM 3787 C ILE B 190 3.146 7.810 -12.265 1.00 87.97 C
ATOM 3788 O ILE B 190 2.526 7.920 -13.325 1.00 87.59 O
ATOM 3789 CB ILE B 190 1.694 7.891 -10.251 1.00 87.07 C
ATOM 3790 CG1 ILE B 190 2.566 8.697 -9.294 1.00 86.15 C
ATOM 3791 CG2 ILE B 190 0.653 7.072 -9.511 1.00 86.59 C
ATOM 3792 CD1 ILE B 190 1.773 9.612 -8.404 1.00 85.40 C
ATOM 3793 N LYS B 191 4.311 8.412 -12.047 1.00 88.65 N
ATOM 3794 CA LYS B 191 4.946 9.229 -13.078 1.00 88.53 C
ATOM 3795 C LYS B 191 5.478 8.304 -14.167 1.00 88.10 C
ATOM 3796 O LYS B 191 5.150 8.447 -15.349 1.00 88.34 O
ATOM 3797 CB LYS B 191 6.110 10.020 -12.483 1.00 88.47 C
ATOM 3798 CG LYS B 191 5.734 10.881 -11.302 1.00 88.98 C
ATOM 3799 CD LYS B 191 4.659 11.891 -11.672 1.00 90.42 C
ATOM 3800 CE LYS B 191 5.168 12.929 -12.664 1.00 91.22 C
ATOM 3801 NZ LYS B 191 4.133 13.950 -13.010 1.00 91.30 N
ATOM 3802 N THR B 192 6.301 7.351 -13.733 1.00 87.39 N
ATOM 3803 CA THR B 192 6.924 6.365 -14.603 1.00 86.37 C
ATOM 3804 C THR B 192 5.910 5.654 -15.472 1.00 85.11 C
ATOM 3805 O THR B 192 5.984 5.718 -16.695 1.00 85.30 O
ATOM 3806 CB THR B 192 7.669 5.297 -13.784 1.00 86.84 C
ATOM 3807 OG1 THR B 192 8.843 5.874 -13.194 1.00 87.24 O
ATOM 3808 CG2 THR B 192 8.064 4.127 -14.675 1.00 87.53 C
ATOM 3809 N LEU B 193 4.972 4.970 -14.828 1.00 83.59 N
ATOM 3810 CA LEU B 193 3.944 4.230 -15.535 1.00 81.81 C
ATOM 3811 C LEU B 193 2.908 5.135 -16.154 1.00 81.47 C
ATOM 3812 O LEU B 193 1.892 4.659 -16.647 1.00 82.12 O
ATOM 3813 CB LEU B 193 3.244 3.258 -14.596 1.00 81.24 C
ATOM 3814 CG LEU B 193 4.071 2.083 -14.085 1.00 80.57 C
ATOM 3815 CD1 LEU B 193 5.241 2.579 -13.243 1.00 80.60 C
ATOM 3816 CD2 LEU B 193 3.165 1.176 -13.272 1.00 80.83 C
ATOM 3817 N GLY B 194 3.157 6.437 -16.127 1.00 80.95 N
ATOM 3818 CA GLY B 194 2.208 7.367 -16.709 1.00 80.89 C
ATOM 3819 C GLY B 194 0.763 7.065 -16.339 1.00 80.68 C
ATOM 3820 O GLY B 194 0.018 6.492 -17.131 1.00 79.93 O
ATOM 3821 N ILE B 195 0.376 7.455 -15.129 1.00 81.64 N
ATOM 3822 CA ILE B 195 -0.975 7.245 -14.620 1.00 81.78 C
ATOM 3823 C ILE B 195 -1.699 8.581 -14.537 1.00 82.29 C
ATOM 3824 O ILE B 195 -1.225 9.493 -13.852 1.00 82.81 O
ATOM 3825 CB ILE B 195 -0.936 6.639 -13.209 1.00 81.34 C
ATOM 3826 CG1 ILE B 195 -0.470 5.191 -13.289 1.00 81.48 C
ATOM 3827 CG2 ILE B 195 -2.295 6.768 -12.547 1.00 81.33 C
ATOM 3828 CD1 ILE B 195 -0.196 4.567 -11.941 1.00 82.56 C
ATOM 3829 N LYS B 196 -2.834 8.698 -15.226 1.00 82.10 N
ATOM 3830 CA LYS B 196 -3.606 9.941 -15.202 1.00 82.86 C
ATOM 3831 C LYS B 196 -4.210 10.136 -13.809 1.00 83.44 C
ATOM 3832 O LYS B 196 -4.889 9.249 -13.278 1.00 82.76 O
ATOM 3833 CB LYS B 196 -4.712 9.914 -16.257 1.00 82.66 C
ATOM 3834 CG LYS B 196 -5.562 11.170 -16.322 1.00 82.46 C
ATOM 3835 CD LYS B 196 -4.793 12.377 -16.837 1.00 83.91 C
ATOM 3836 CE LYS B 196 -5.761 13.536 -17.155 1.00 86.21 C
ATOM 3837 NZ LYS B 196 -5.143 14.856 -17.539 1.00 85.46 N
ATOM 3838 N TYR B 197 -3.942 11.302 -13.222 1.00 83.30 N
ATOM 3839 CA TYR B 197 -4.417 11.631 -11.880 1.00 82.70 C
ATOM 3840 C TYR B 197 -4.800 13.100 -11.759 1.00 82.58 C
ATOM 3841 O TYR B 197 -4.612 13.887 -12.688 1.00 83.40 O
ATOM 3842 CB TYR B 197 -3.327 11.311 -10.838 1.00 82.50 C
ATOM 3843 CG TYR B 197 -2.018 12.066 -11.039 1.00 82.72 C
ATOM 3844 CD1 TYR B 197 -2.000 13.466 -11.124 1.00 82.81 C
ATOM 3845 CD2 TYR B 197 -0.798 11.385 -11.154 1.00 82.18 C
ATOM 3846 CE1 TYR B 197 -0.811 14.171 -11.323 1.00 82.44 C
ATOM 3847 CE2 TYR B 197 0.408 12.084 -11.351 1.00 82.21 C
ATOM 3848 CZ TYR B 197 0.390 13.484 -11.439 1.00 82.80 C
ATOM 3849 OH TYR B 197 1.548 14.208 -11.668 1.00 80.90 O
ATOM 3850 N PHE B 198 -5.326 13.467 -10.595 1.00 81.74 N
ATOM 3851 CA PHE B 198 -5.726 14.843 -10.327 1.00 79.29 C
ATOM 3852 C PHE B 198 -5.536 15.134 -8.854 1.00 75.97 C
ATOM 3853 O PHE B 198 -6.469 14.995 -8.071 1.00 76.68 O
ATOM 3854 CB PHE B 198 -7.199 15.074 -10.666 1.00 81.72 C
ATOM 3855 CG PHE B 198 -7.502 15.064 -12.132 1.00 84.47 C
ATOM 3856 CD1 PHE B 198 -7.627 13.863 -12.824 1.00 85.88 C
ATOM 3857 CD2 PHE B 198 -7.704 16.262 -12.818 1.00 85.59 C
ATOM 3858 CE1 PHE B 198 -7.954 13.856 -14.180 1.00 87.07 C
ATOM 3859 CE2 PHE B 198 -8.032 16.265 -14.170 1.00 86.78 C
ATOM 3860 CZ PHE B 198 -8.160 15.059 -14.855 1.00 86.99 C
ATOM 3861 N SER B 199 -4.337 15.538 -8.466 1.00 71.87 N
ATOM 3862 CA SER B 199 -4.110 15.836 -7.068 1.00 67.84 C
ATOM 3863 C SER B 199 -4.926 17.061 -6.683 1.00 66.10 C
ATOM 3864 O SER B 199 -5.390 17.812 -7.553 1.00 64.20 O
ATOM 3865 CB SER B 199 -2.636 16.102 -6.817 1.00 66.46 C
ATOM 3866 OG SER B 199 -2.214 17.195 -7.591 1.00 65.39 O
ATOM 3867 N MET B 200 -5.103 17.243 -5.375 1.00 64.09 N
ATOM 3868 CA MET B 200 -5.848 18.368 -4.838 1.00 61.01 C
ATOM 3869 C MET B 200 -5.461 19.628 -5.587 1.00 62.42 C
ATOM 3870 O MET B 200 -6.312 20.476 -5.867 1.00 62.06 O
ATOM 3871 CB MET B 200 -5.558 18.531 -3.346 1.00 56.33 C
ATOM 3872 CG MET B 200 -6.177 17.454 -2.477 1.00 53.16 C
ATOM 3873 SD MET B 200 -7.982 17.292 -2.699 1.00 46.37 S
ATOM 3874 CE MET B 200 -8.511 18.896 -2.264 1.00 48.10 C
ATOM 3875 N THR B 201 -4.179 19.741 -5.925 1.00 62.97 N
ATOM 3876 CA THR B 201 -3.706 20.908 -6.654 1.00 64.97 C
ATOM 3877 C THR B 201 -4.401 21.003 -8.025 1.00 66.10 C
ATOM 3878 O THR B 201 -4.685 22.115 -8.516 1.00 65.58 O
ATOM 3879 CB THR B 201 -2.146 20.895 -6.800 1.00 65.68 C
ATOM 3880 OG1 THR B 201 -1.778 20.951 -8.186 1.00 65.66 O
ATOM 3881 CG2 THR B 201 -1.552 19.649 -6.149 1.00 65.96 C
ATOM 3882 N GLU B 202 -4.696 19.850 -8.631 1.00 66.73 N
ATOM 3883 CA GLU B 202 -5.376 19.836 -9.926 1.00 67.80 C
ATOM 3884 C GLU B 202 -6.820 20.179 -9.720 1.00 68.66 C
ATOM 3885 O GLU B 202 -7.420 20.898 -10.525 1.00 70.18 O
ATOM 3886 CB GLU B 202 -5.283 18.482 -10.594 1.00 67.72 C
ATOM 3887 CG GLU B 202 -4.161 18.437 -11.594 1.00 72.08 C
ATOM 3888 CD GLU B 202 -2.816 18.741 -10.959 1.00 74.23 C
ATOM 3889 OE1 GLU B 202 -2.333 17.879 -10.184 1.00 73.29 O
ATOM 3890 OE2 GLU B 202 -2.256 19.838 -11.230 1.00 75.62 O
ATOM 3891 N VAL B 203 -7.379 19.646 -8.638 1.00 67.55 N
ATOM 3892 CA VAL B 203 -8.757 19.930 -8.290 1.00 65.53 C
ATOM 3893 C VAL B 203 -8.775 21.457 -8.216 1.00 64.91 C
ATOM 3894 O VAL B 203 -9.548 22.130 -8.908 1.00 64.87 O
ATOM 3895 CB VAL B 203 -9.116 19.363 -6.880 1.00 65.75 C
ATOM 3896 CG1 VAL B 203 -10.617 19.458 -6.641 1.00 65.81 C
ATOM 3897 CG2 VAL B 203 -8.638 17.929 -6.739 1.00 66.78 C
ATOM 3898 N ASP B 204 -7.877 21.984 -7.379 1.00 62.79 N
ATOM 3899 CA ASP B 204 -7.753 23.413 -7.151 1.00 61.49 C
ATOM 3900 C ASP B 204 -7.683 24.207 -8.423 1.00 62.37 C
ATOM 3901 O ASP B 204 -8.335 25.239 -8.549 1.00 61.65 O
ATOM 3902 CB ASP B 204 -6.510 23.706 -6.319 1.00 59.70 C
ATOM 3903 CG ASP B 204 -6.749 23.524 -4.841 1.00 56.79 C
ATOM 3904 OD1 ASP B 204 -7.690 22.777 -4.502 1.00 52.71 O
ATOM 3905 OD2 ASP B 204 -5.994 24.116 -4.032 1.00 54.02 O
ATOM 3906 N LYS B 205 -6.886 23.724 -9.369 1.00 64.38 N
ATOM 3907 CA LYS B 205 -6.718 24.421 -10.634 1.00 65.17 C
ATOM 3908 C LYS B 205 -7.944 24.411 -11.541 1.00 64.26 C
ATOM 3909 O LYS B 205 -8.485 25.457 -11.862 1.00 63.15 O
ATOM 3910 CB LYS B 205 -5.528 23.848 -11.396 1.00 66.18 C
ATOM 3911 CG LYS B 205 -5.198 24.644 -12.641 1.00 69.34 C
ATOM 3912 CD LYS B 205 -3.988 24.073 -13.366 1.00 73.83 C
ATOM 3913 CE LYS B 205 -3.535 24.947 -14.544 1.00 76.14 C
ATOM 3914 NZ LYS B 205 -2.993 26.290 -14.134 1.00 77.46 N
ATOM 3915 N LEU B 206 -8.388 23.228 -11.939 1.00 64.81 N
ATOM 3916 CA LEU B 206 -9.524 23.100 -12.851 1.00 67.28 C
ATOM 3917 C LEU B 206 -10.916 23.288 -12.264 1.00 68.71 C
ATOM 3918 O LEU B 206 -11.786 23.896 -12.893 1.00 69.72 O
ATOM 3919 CB LEU B 206 -9.492 21.726 -13.519 1.00 68.10 C
ATOM 3920 CG LEU B 206 -8.120 21.236 -13.970 1.00 67.44 C
ATOM 3921 CD1 LEU B 206 -8.217 19.790 -14.463 1.00 63.42 C
ATOM 3922 CD2 LEU B 206 -7.601 22.185 -15.045 1.00 67.18 C
ATOM 3923 N GLY B 207 -11.134 22.740 -11.074 1.00 69.83 N
ATOM 3924 CA GLY B 207 -12.446 22.823 -10.462 1.00 70.69 C
ATOM 3925 C GLY B 207 -13.101 21.490 -10.754 1.00 70.94 C
ATOM 3926 O GLY B 207 -13.170 21.073 -11.906 1.00 70.79 O
ATOM 3927 N ILE B 208 -13.568 20.820 -9.707 1.00 70.50 N
ATOM 3928 CA ILE B 208 -14.181 19.508 -9.837 1.00 70.18 C
ATOM 3929 C ILE B 208 -14.923 19.302 -11.165 1.00 72.13 C
ATOM 3930 O ILE B 208 -14.810 18.237 -11.780 1.00 71.07 O
ATOM 3931 CB ILE B 208 -15.118 19.217 -8.626 1.00 68.19 C
ATOM 3932 CG1 ILE B 208 -14.720 17.900 -7.959 1.00 66.86 C
ATOM 3933 CG2 ILE B 208 -16.567 19.223 -9.057 1.00 65.59 C
ATOM 3934 CD1 ILE B 208 -14.654 16.704 -8.873 1.00 63.60 C
ATOM 3935 N GLY B 209 -15.657 20.316 -11.620 1.00 74.55 N
ATOM 3936 CA GLY B 209 -16.386 20.185 -12.875 1.00 78.13 C
ATOM 3937 C GLY B 209 -15.525 19.721 -14.044 1.00 79.78 C
ATOM 3938 O GLY B 209 -15.795 18.682 -14.649 1.00 79.81 O
ATOM 3939 N LYS B 210 -14.492 20.506 -14.353 1.00 81.12 N
ATOM 3940 CA LYS B 210 -13.536 20.226 -15.428 1.00 81.72 C
ATOM 3941 C LYS B 210 -12.771 18.937 -15.110 1.00 81.92 C
ATOM 3942 O LYS B 210 -12.473 18.140 -15.999 1.00 82.06 O
ATOM 3943 CB LYS B 210 -12.568 21.414 -15.557 1.00 83.49 C
ATOM 3944 CG LYS B 210 -11.350 21.201 -16.445 1.00 86.80 C
ATOM 3945 CD LYS B 210 -11.730 20.875 -17.889 1.00 89.98 C
ATOM 3946 CE LYS B 210 -10.483 20.650 -18.764 1.00 90.59 C
ATOM 3947 NZ LYS B 210 -10.785 20.007 -20.091 1.00 91.17 N
ATOM 3948 N VAL B 211 -12.458 18.737 -13.836 1.00 81.88 N
ATOM 3949 CA VAL B 211 -11.743 17.542 -13.410 1.00 81.43 C
ATOM 3950 C VAL B 211 -12.502 16.296 -13.861 1.00 82.60 C
ATOM 3951 O VAL B 211 -11.893 15.349 -14.356 1.00 82.44 O
ATOM 3952 CB VAL B 211 -11.584 17.502 -11.872 1.00 80.75 C
ATOM 3953 CG1 VAL B 211 -10.963 16.188 -11.441 1.00 79.53 C
ATOM 3954 CG2 VAL B 211 -10.729 18.667 -11.407 1.00 80.56 C
ATOM 3955 N MET B 212 -13.826 16.297 -13.686 1.00 83.85 N
ATOM 3956 CA MET B 212 -14.660 15.155 -14.078 1.00 85.06 C
ATOM 3957 C MET B 212 -14.819 15.118 -15.590 1.00 87.35 C
ATOM 3958 O MET B 212 -14.680 14.071 -16.226 1.00 87.24 O
ATOM 3959 CB MET B 212 -16.043 15.238 -13.427 1.00 82.29 C
ATOM 3960 CG MET B 212 -16.040 15.107 -11.904 1.00 80.30 C
ATOM 3961 SD MET B 212 -15.371 13.544 -11.259 1.00 73.97 S
ATOM 3962 CE MET B 212 -16.744 12.515 -11.487 1.00 75.37 C
ATOM 3963 N GLU B 213 -15.121 16.281 -16.152 1.00 90.13 N
ATOM 3964 CA GLU B 213 -15.291 16.449 -17.585 1.00 92.16 C
ATOM 3965 C GLU B 213 -14.092 15.806 -18.295 1.00 92.77 C
ATOM 3966 O GLU B 213 -14.261 14.998 -19.212 1.00 94.09 O
ATOM 3967 CB GLU B 213 -15.374 17.945 -17.885 1.00 94.04 C
ATOM 3968 CG GLU B 213 -15.853 18.333 -19.265 1.00 99.07 C
ATOM 3969 CD GLU B 213 -16.051 19.843 -19.387 1.00102.30 C
ATOM 3970 OE1 GLU B 213 -16.887 20.393 -18.632 1.00103.12 O
ATOM 3971 OE2 GLU B 213 -15.373 20.481 -20.230 1.00104.92 O
ATOM 3972 N GLU B 214 -12.884 16.154 -17.859 1.00 92.07 N
ATOM 3973 CA GLU B 214 -11.675 15.594 -18.450 1.00 91.63 C
ATOM 3974 C GLU B 214 -11.647 14.088 -18.254 1.00 91.32 C
ATOM 3975 O GLU B 214 -11.891 13.337 -19.192 1.00 91.52 O
ATOM 3976 CB GLU B 214 -10.424 16.205 -17.813 1.00 92.05 C
ATOM 3977 CG GLU B 214 -9.948 17.483 -18.467 1.00 92.73 C
ATOM 3978 CD GLU B 214 -8.637 17.981 -17.883 1.00 93.79 C
ATOM 3979 OE1 GLU B 214 -7.633 17.229 -17.931 1.00 93.91 O
ATOM 3980 OE2 GLU B 214 -8.616 19.126 -17.382 1.00 93.93 O
ATOM 3981 N THR B 215 -11.349 13.661 -17.029 1.00 91.31 N
ATOM 3982 CA THR B 215 -11.275 12.241 -16.675 1.00 90.84 C
ATOM 3983 C THR B 215 -12.176 11.354 -17.518 1.00 90.63 C
ATOM 3984 O THR B 215 -11.810 10.222 -17.844 1.00 89.71 O
ATOM 3985 CB THR B 215 -11.653 11.998 -15.200 1.00 91.00 C
ATOM 3986 OG1 THR B 215 -12.828 12.751 -14.877 1.00 91.70 O
ATOM 3987 CG2 THR B 215 -10.537 12.401 -14.287 1.00 90.94 C
ATOM 3988 N PHE B 216 -13.362 11.857 -17.856 1.00 90.43 N
ATOM 3989 CA PHE B 216 -14.283 11.073 -18.662 1.00 90.26 C
ATOM 3990 C PHE B 216 -13.749 10.891 -20.069 1.00 91.62 C
ATOM 3991 O PHE B 216 -13.417 9.770 -20.459 1.00 92.03 O
ATOM 3992 CB PHE B 216 -15.674 11.710 -18.675 1.00 86.72 C
ATOM 3993 CG PHE B 216 -16.464 11.445 -17.423 1.00 83.81 C
ATOM 3994 CD1 PHE B 216 -15.985 10.567 -16.454 1.00 82.90 C
ATOM 3995 CD2 PHE B 216 -17.676 12.081 -17.202 1.00 82.83 C
ATOM 3996 CE1 PHE B 216 -16.688 10.345 -15.273 1.00 82.23 C
ATOM 3997 CE2 PHE B 216 -18.389 11.865 -16.021 1.00 82.56 C
ATOM 3998 CZ PHE B 216 -17.897 10.989 -15.057 1.00 81.79 C
ATOM 3999 N SER B 217 -13.650 11.973 -20.834 1.00 92.18 N
ATOM 4000 CA SER B 217 -13.121 11.854 -22.184 1.00 92.47 C
ATOM 4001 C SER B 217 -11.893 10.930 -22.157 1.00 92.71 C
ATOM 4002 O SER B 217 -11.853 9.927 -22.867 1.00 93.44 O
ATOM 4003 CB SER B 217 -12.718 13.225 -22.723 1.00 92.57 C
ATOM 4004 OG SER B 217 -11.504 13.656 -22.134 1.00 92.76 O
ATOM 4005 N TYR B 218 -10.907 11.260 -21.324 1.00 92.44 N
ATOM 4006 CA TYR B 218 -9.689 10.462 -21.207 1.00 93.21 C
ATOM 4007 C TYR B 218 -9.932 8.948 -21.085 1.00 94.61 C
ATOM 4008 O TYR B 218 -9.094 8.144 -21.498 1.00 93.90 O
ATOM 4009 CB TYR B 218 -8.872 10.932 -20.000 1.00 92.46 C
ATOM 4010 CG TYR B 218 -7.725 10.002 -19.653 1.00 92.79 C
ATOM 4011 CD1 TYR B 218 -6.457 10.175 -20.214 1.00 93.36 C
ATOM 4012 CD2 TYR B 218 -7.920 8.913 -18.804 1.00 91.95 C
ATOM 4013 CE1 TYR B 218 -5.410 9.279 -19.939 1.00 92.39 C
ATOM 4014 CE2 TYR B 218 -6.889 8.013 -18.523 1.00 92.17 C
ATOM 4015 CZ TYR B 218 -5.633 8.198 -19.094 1.00 92.07 C
ATOM 4016 OH TYR B 218 -4.617 7.293 -18.835 1.00 91.03 O
ATOM 4017 N LEU B 219 -11.070 8.564 -20.512 1.00 96.79 N
ATOM 4018 CA LEU B 219 -11.401 7.149 -20.324 1.00 99.53 C
ATOM 4019 C LEU B 219 -12.484 6.612 -21.269 1.00102.10 C
ATOM 4020 O LEU B 219 -12.382 5.493 -21.780 1.00102.34 O
ATOM 4021 CB LEU B 219 -11.851 6.902 -18.878 1.00 98.47 C
ATOM 4022 CG LEU B 219 -10.822 6.940 -17.752 1.00 97.30 C
ATOM 4023 CD1 LEU B 219 -11.544 6.960 -16.427 1.00 97.75 C
ATOM 4024 CD2 LEU B 219 -9.903 5.734 -17.834 1.00 96.22 C
ATOM 4025 N LEU B 220 -13.523 7.410 -21.490 1.00104.81 N
ATOM 4026 CA LEU B 220 -14.637 7.006 -22.344 1.00107.29 C
ATOM 4027 C LEU B 220 -14.636 7.770 -23.673 1.00109.31 C
ATOM 4028 O LEU B 220 -15.658 7.840 -24.358 1.00109.84 O
ATOM 4029 CB LEU B 220 -15.964 7.249 -21.603 1.00106.72 C
ATOM 4030 CG LEU B 220 -15.995 7.046 -20.077 1.00105.67 C
ATOM 4031 CD1 LEU B 220 -17.375 7.414 -19.539 1.00104.74 C
ATOM 4032 CD2 LEU B 220 -15.636 5.606 -19.721 1.00104.50 C
ATOM 4033 N GLY B 221 -13.487 8.341 -24.031 1.00111.26 N
ATOM 4034 CA GLY B 221 -13.390 9.094 -25.270 1.00113.38 C
ATOM 4035 C GLY B 221 -13.624 8.230 -26.492 1.00114.74 C
ATOM 4036 O GLY B 221 -14.453 8.553 -27.344 1.00114.30 O
ATOM 4037 N ARG B 222 -12.888 7.128 -26.574 1.00116.28 N
ATOM 4038 CA ARG B 222 -13.008 6.198 -27.688 1.00117.84 C
ATOM 4039 C ARG B 222 -14.142 5.199 -27.450 1.00117.49 C
ATOM 4040 O ARG B 222 -15.276 5.394 -27.900 1.00117.04 O
ATOM 4041 CB ARG B 222 -11.679 5.456 -27.883 1.00120.30 C
ATOM 4042 CG ARG B 222 -10.558 6.329 -28.452 1.00124.08 C
ATOM 4043 CD ARG B 222 -9.163 5.718 -28.250 1.00127.28 C
ATOM 4044 NE ARG B 222 -8.732 5.750 -26.849 1.00129.65 N
ATOM 4045 CZ ARG B 222 -7.486 5.519 -26.433 1.00130.39 C
ATOM 4046 NH1 ARG B 222 -6.529 5.235 -27.310 1.00131.75 N
ATOM 4047 NH2 ARG B 222 -7.190 5.578 -25.139 1.00130.10 N
ATOM 4048 N LYS B 223 -13.835 4.126 -26.732 1.00117.21 N
ATOM 4049 CA LYS B 223 -14.831 3.104 -26.440 1.00116.89 C
ATOM 4050 C LYS B 223 -15.462 3.298 -25.061 1.00115.74 C
ATOM 4051 O LYS B 223 -14.784 3.202 -24.036 1.00116.07 O
ATOM 4052 CB LYS B 223 -14.195 1.707 -26.506 1.00118.12 C
ATOM 4053 CG LYS B 223 -13.711 1.252 -27.887 1.00119.48 C
ATOM 4054 CD LYS B 223 -14.861 0.867 -28.819 1.00120.20 C
ATOM 4055 CE LYS B 223 -14.368 0.023 -30.001 1.00119.96 C
ATOM 4056 NZ LYS B 223 -13.356 0.714 -30.852 1.00120.32 N
ATOM 4057 N LYS B 224 -16.760 3.577 -25.044 1.00113.56 N
ATOM 4058 CA LYS B 224 -17.485 3.736 -23.788 1.00110.71 C
ATOM 4059 C LYS B 224 -17.474 2.377 -23.086 1.00108.17 C
ATOM 4060 O LYS B 224 -17.967 1.391 -23.633 1.00107.92 O
ATOM 4061 CB LYS B 224 -18.936 4.154 -24.055 1.00111.33 C
ATOM 4062 CG LYS B 224 -19.122 5.605 -24.451 1.00111.67 C
ATOM 4063 CD LYS B 224 -18.280 5.980 -25.655 1.00113.19 C
ATOM 4064 CE LYS B 224 -18.490 7.439 -26.031 1.00114.15 C
ATOM 4065 NZ LYS B 224 -17.552 7.879 -27.105 1.00114.36 N
ATOM 4066 N ARG B 225 -16.902 2.314 -21.888 1.00104.97 N
ATOM 4067 CA ARG B 225 -16.862 1.057 -21.143 1.00102.05 C
ATOM 4068 C ARG B 225 -17.546 1.188 -19.779 1.00 99.65 C
ATOM 4069 O ARG B 225 -18.135 2.227 -19.466 1.00100.15 O
ATOM 4070 CB ARG B 225 -15.412 0.571 -20.954 1.00101.03 C
ATOM 4071 CG ARG B 225 -14.477 1.509 -20.204 1.00 99.54 C
ATOM 4072 CD ARG B 225 -14.074 2.677 -21.080 1.00 99.50 C
ATOM 4073 NE ARG B 225 -12.767 3.230 -20.725 1.00 98.90 N
ATOM 4074 CZ ARG B 225 -11.629 2.537 -20.744 1.00 99.29 C
ATOM 4075 NH1 ARG B 225 -11.629 1.256 -21.090 1.00 99.63 N
ATOM 4076 NH2 ARG B 225 -10.486 3.132 -20.434 1.00 99.36 N
ATOM 4077 N PRO B 226 -17.528 0.114 -18.974 1.00 96.61 N
ATOM 4078 CA PRO B 226 -18.165 0.211 -17.657 1.00 93.91 C
ATOM 4079 C PRO B 226 -17.212 0.892 -16.687 1.00 90.68 C
ATOM 4080 O PRO B 226 -15.990 0.835 -16.865 1.00 90.41 O
ATOM 4081 CB PRO B 226 -18.417 -1.246 -17.285 1.00 94.90 C
ATOM 4082 CG PRO B 226 -18.562 -1.912 -18.626 1.00 96.02 C
ATOM 4083 CD PRO B 226 -17.429 -1.294 -19.390 1.00 95.93 C
ATOM 4084 N ILE B 227 -17.779 1.538 -15.671 1.00 86.58 N
ATOM 4085 CA ILE B 227 -16.997 2.250 -14.660 1.00 81.66 C
ATOM 4086 C ILE B 227 -16.958 1.510 -13.330 1.00 78.57 C
ATOM 4087 O ILE B 227 -17.920 0.836 -12.936 1.00 78.91 O
ATOM 4088 CB ILE B 227 -17.569 3.692 -14.381 1.00 81.09 C
ATOM 4089 CG1 ILE B 227 -16.952 4.712 -15.341 1.00 79.71 C
ATOM 4090 CG2 ILE B 227 -17.298 4.110 -12.930 1.00 79.22 C
ATOM 4091 CD1 ILE B 227 -17.508 4.672 -16.742 1.00 79.96 C
ATOM 4092 N HIS B 228 -15.826 1.631 -12.652 1.00 73.48 N
ATOM 4093 CA HIS B 228 -15.684 1.047 -11.345 1.00 69.84 C
ATOM 4094 C HIS B 228 -15.180 2.176 -10.457 1.00 67.82 C
ATOM 4095 O HIS B 228 -13.989 2.508 -10.451 1.00 66.60 O
ATOM 4096 CB HIS B 228 -14.678 -0.087 -11.335 1.00 70.56 C
ATOM 4097 CG HIS B 228 -14.567 -0.756 -10.002 1.00 73.54 C
ATOM 4098 ND1 HIS B 228 -15.543 -1.602 -9.511 1.00 75.85 N
ATOM 4099 CD2 HIS B 228 -13.635 -0.658 -9.026 1.00 74.60 C
ATOM 4100 CE1 HIS B 228 -15.217 -1.993 -8.293 1.00 75.11 C
ATOM 4101 NE2 HIS B 228 -14.063 -1.433 -7.973 1.00 76.27 N
ATOM 4102 N LEU B 229 -16.099 2.792 -9.728 1.00 65.08 N
ATOM 4103 CA LEU B 229 -15.736 3.875 -8.834 1.00 62.32 C
ATOM 4104 C LEU B 229 -15.356 3.320 -7.465 1.00 61.53 C
ATOM 4105 O LEU B 229 -16.220 2.898 -6.694 1.00 62.14 O
ATOM 4106 CB LEU B 229 -16.904 4.838 -8.663 1.00 59.30 C
ATOM 4107 CG LEU B 229 -16.654 5.899 -7.589 1.00 57.40 C
ATOM 4108 CD1 LEU B 229 -15.571 6.859 -8.058 1.00 54.44 C
ATOM 4109 CD2 LEU B 229 -17.948 6.621 -7.301 1.00 56.40 C
ATOM 4110 N SER B 230 -14.065 3.300 -7.167 1.00 59.36 N
ATOM 4111 CA SER B 230 -13.611 2.817 -5.874 1.00 58.06 C
ATOM 4112 C SER B 230 -13.491 4.100 -5.046 1.00 57.34 C
ATOM 4113 O SER B 230 -12.530 4.869 -5.180 1.00 57.15 O
ATOM 4114 CB SER B 230 -12.251 2.110 -6.014 1.00 58.58 C
ATOM 4115 OG SER B 230 -12.019 1.157 -4.984 1.00 57.12 O
ATOM 4116 N PHE B 231 -14.489 4.349 -4.207 1.00 55.66 N
ATOM 4117 CA PHE B 231 -14.479 5.555 -3.393 1.00 54.53 C
ATOM 4118 C PHE B 231 -13.973 5.307 -1.989 1.00 53.57 C
ATOM 4119 O PHE B 231 -14.475 4.447 -1.264 1.00 52.54 O
ATOM 4120 CB PHE B 231 -15.876 6.172 -3.320 1.00 52.60 C
ATOM 4121 CG PHE B 231 -15.866 7.634 -3.027 1.00 46.80 C
ATOM 4122 CD1 PHE B 231 -15.171 8.125 -1.939 1.00 44.29 C
ATOM 4123 CD2 PHE B 231 -16.571 8.514 -3.838 1.00 46.49 C
ATOM 4124 CE1 PHE B 231 -15.179 9.459 -1.658 1.00 44.81 C
ATOM 4125 CE2 PHE B 231 -16.593 9.857 -3.571 1.00 46.31 C
ATOM 4126 CZ PHE B 231 -15.892 10.338 -2.474 1.00 47.96 C
ATOM 4127 N ASP B 232 -12.979 6.099 -1.610 1.00 54.56 N
ATOM 4128 CA ASP B 232 -12.370 5.990 -0.296 1.00 54.94 C
ATOM 4129 C ASP B 232 -12.776 7.139 0.588 1.00 54.45 C
ATOM 4130 O ASP B 232 -12.152 8.184 0.566 1.00 53.16 O
ATOM 4131 CB ASP B 232 -10.854 5.969 -0.418 1.00 53.83 C
ATOM 4132 CG ASP B 232 -10.173 5.967 0.914 1.00 54.18 C
ATOM 4133 OD1 ASP B 232 -10.863 6.016 1.956 1.00 51.22 O
ATOM 4134 OD2 ASP B 232 -8.927 5.929 0.921 1.00 54.39 O
ATOM 4135 N VAL B 233 -13.819 6.916 1.377 1.00 55.37 N
ATOM 4136 CA VAL B 233 -14.347 7.896 2.306 1.00 56.07 C
ATOM 4137 C VAL B 233 -13.317 8.895 2.836 1.00 56.17 C
ATOM 4138 O VAL B 233 -13.677 10.003 3.236 1.00 57.17 O
ATOM 4139 CB VAL B 233 -14.968 7.199 3.504 1.00 58.18 C
ATOM 4140 CG1 VAL B 233 -13.855 6.592 4.378 1.00 57.95 C
ATOM 4141 CG2 VAL B 233 -15.800 8.182 4.288 1.00 59.10 C
ATOM 4142 N ASP B 234 -12.041 8.516 2.858 1.00 55.85 N
ATOM 4143 CA ASP B 234 -11.005 9.442 3.336 1.00 55.47 C
ATOM 4144 C ASP B 234 -10.579 10.531 2.333 1.00 52.10 C
ATOM 4145 O ASP B 234 -9.952 11.497 2.714 1.00 52.05 O
ATOM 4146 CB ASP B 234 -9.760 8.667 3.826 1.00 59.03 C
ATOM 4147 CG ASP B 234 -8.873 8.157 2.688 1.00 63.96 C
ATOM 4148 OD1 ASP B 234 -8.592 8.921 1.724 1.00 65.02 O
ATOM 4149 OD2 ASP B 234 -8.426 6.986 2.785 1.00 66.85 O
ATOM 4150 N GLY B 235 -10.911 10.367 1.060 1.00 50.06 N
ATOM 4151 CA GLY B 235 -10.549 11.357 0.058 1.00 49.84 C
ATOM 4152 C GLY B 235 -11.286 12.694 0.177 1.00 49.59 C
ATOM 4153 O GLY B 235 -11.076 13.623 -0.620 1.00 47.09 O
ATOM 4154 N LEU B 236 -12.187 12.779 1.148 1.00 50.09 N
ATOM 4155 CA LEU B 236 -12.909 14.007 1.390 1.00 50.76 C
ATOM 4156 C LEU B 236 -12.098 14.664 2.483 1.00 51.57 C
ATOM 4157 O LEU B 236 -11.187 14.041 3.034 1.00 52.88 O
ATOM 4158 CB LEU B 236 -14.311 13.700 1.886 1.00 52.43 C
ATOM 4159 CG LEU B 236 -15.413 13.984 0.869 1.00 54.89 C
ATOM 4160 CD1 LEU B 236 -14.991 13.475 -0.500 1.00 55.00 C
ATOM 4161 CD2 LEU B 236 -16.703 13.324 1.328 1.00 55.89 C
ATOM 4162 N ASP B 237 -12.390 15.912 2.809 1.00 52.93 N
ATOM 4163 CA ASP B 237 -11.617 16.540 3.874 1.00 57.18 C
ATOM 4164 C ASP B 237 -11.992 15.947 5.244 1.00 58.88 C
ATOM 4165 O ASP B 237 -13.131 15.511 5.450 1.00 59.95 O
ATOM 4166 CB ASP B 237 -11.829 18.046 3.891 1.00 58.63 C
ATOM 4167 CG ASP B 237 -10.918 18.735 4.882 1.00 60.03 C
ATOM 4168 OD1 ASP B 237 -11.193 18.639 6.102 1.00 60.59 O
ATOM 4169 OD2 ASP B 237 -9.913 19.339 4.437 1.00 60.31 O
ATOM 4170 N PRO B 238 -11.037 15.917 6.197 1.00 57.68 N
ATOM 4171 CA PRO B 238 -11.368 15.354 7.506 1.00 56.57 C
ATOM 4172 C PRO B 238 -12.566 15.972 8.228 1.00 56.08 C
ATOM 4173 O PRO B 238 -13.193 15.314 9.066 1.00 56.48 O
ATOM 4174 CB PRO B 238 -10.057 15.499 8.271 1.00 57.23 C
ATOM 4175 CG PRO B 238 -9.053 15.216 7.203 1.00 57.07 C
ATOM 4176 CD PRO B 238 -9.580 16.108 6.086 1.00 57.93 C
ATOM 4177 N VAL B 239 -12.903 17.218 7.898 1.00 53.68 N
ATOM 4178 CA VAL B 239 -14.043 17.883 8.531 1.00 52.34 C
ATOM 4179 C VAL B 239 -15.364 17.200 8.127 1.00 52.10 C
ATOM 4180 O VAL B 239 -16.357 17.230 8.858 1.00 50.40 O
ATOM 4181 CB VAL B 239 -14.107 19.371 8.117 1.00 51.91 C
ATOM 4182 CG1 VAL B 239 -15.021 19.551 6.927 1.00 51.39 C
ATOM 4183 CG2 VAL B 239 -14.569 20.214 9.279 1.00 51.86 C
ATOM 4184 N PHE B 240 -15.349 16.567 6.960 1.00 52.61 N
ATOM 4185 CA PHE B 240 -16.527 15.906 6.419 1.00 51.13 C
ATOM 4186 C PHE B 240 -16.638 14.432 6.758 1.00 50.55 C
ATOM 4187 O PHE B 240 -17.713 13.961 7.108 1.00 52.43 O
ATOM 4188 CB PHE B 240 -16.549 16.082 4.897 1.00 49.52 C
ATOM 4189 CG PHE B 240 -16.627 17.525 4.444 1.00 46.38 C
ATOM 4190 CD1 PHE B 240 -17.828 18.228 4.523 1.00 43.52 C
ATOM 4191 CD2 PHE B 240 -15.509 18.166 3.917 1.00 44.12 C
ATOM 4192 CE1 PHE B 240 -17.918 19.520 4.078 1.00 40.93 C
ATOM 4193 CE2 PHE B 240 -15.596 19.467 3.469 1.00 41.80 C
ATOM 4194 CZ PHE B 240 -16.801 20.146 3.550 1.00 40.90 C
ATOM 4195 N THR B 241 -15.535 13.706 6.657 1.00 49.79 N
ATOM 4196 CA THR B 241 -15.540 12.276 6.933 1.00 50.83 C
ATOM 4197 C THR B 241 -14.479 11.954 7.957 1.00 52.55 C
ATOM 4198 O THR B 241 -13.544 11.200 7.680 1.00 51.99 O
ATOM 4199 CB THR B 241 -15.218 11.480 5.670 1.00 51.65 C
ATOM 4200 OG1 THR B 241 -13.970 11.945 5.120 1.00 53.02 O
ATOM 4201 CG2 THR B 241 -16.330 11.645 4.649 1.00 50.87 C
ATOM 4202 N PRO B 242 -14.602 12.527 9.158 1.00 54.97 N
ATOM 4203 CA PRO B 242 -13.631 12.298 10.234 1.00 57.22 C
ATOM 4204 C PRO B 242 -13.348 10.862 10.689 1.00 56.87 C
ATOM 4205 O PRO B 242 -12.204 10.539 10.987 1.00 57.12 O
ATOM 4206 CB PRO B 242 -14.149 13.200 11.362 1.00 57.28 C
ATOM 4207 CG PRO B 242 -15.601 13.431 11.014 1.00 57.06 C
ATOM 4208 CD PRO B 242 -15.553 13.586 9.530 1.00 56.17 C
ATOM 4209 N ALA B 243 -14.370 10.009 10.741 1.00 58.31 N
ATOM 4210 CA ALA B 243 -14.186 8.618 11.175 1.00 58.19 C
ATOM 4211 C ALA B 243 -13.443 7.752 10.159 1.00 58.24 C
ATOM 4212 O ALA B 243 -14.070 6.949 9.465 1.00 57.68 O
ATOM 4213 CB ALA B 243 -15.545 7.980 11.498 1.00 56.37 C
ATOM 4214 N THR B 244 -12.120 7.912 10.086 1.00 59.71 N
ATOM 4215 CA THR B 244 -11.277 7.145 9.154 1.00 62.49 C
ATOM 4216 C THR B 244 -9.951 6.695 9.775 1.00 64.13 C
ATOM 4217 O THR B 244 -9.642 7.010 10.926 1.00 66.01 O
ATOM 4218 CB THR B 244 -10.891 7.958 7.889 1.00 60.93 C
ATOM 4219 OG1 THR B 244 -11.978 8.797 7.491 1.00 62.57 O
ATOM 4220 CG2 THR B 244 -10.574 7.012 6.741 1.00 62.79 C
ATOM 4221 N GLY B 245 -9.172 5.950 8.991 1.00 65.60 N
ATOM 4222 CA GLY B 245 -7.871 5.491 9.438 1.00 65.27 C
ATOM 4223 C GLY B 245 -6.922 6.656 9.290 1.00 65.53 C
ATOM 4224 O GLY B 245 -6.505 7.239 10.279 1.00 65.18 O
ATOM 4225 N THR B 246 -6.605 7.024 8.053 1.00 67.51 N
ATOM 4226 CA THR B 246 -5.704 8.147 7.817 1.00 69.03 C
ATOM 4227 C THR B 246 -6.395 9.426 7.380 1.00 70.69 C
ATOM 4228 O THR B 246 -6.941 9.472 6.277 1.00 72.99 O
ATOM 4229 CB THR B 246 -4.716 7.918 6.674 1.00 68.81 C
ATOM 4230 OG1 THR B 246 -4.566 6.521 6.404 1.00 70.16 O
ATOM 4231 CG2 THR B 246 -3.384 8.579 7.014 1.00 67.59 C
ATOM 4232 N PRO B 247 -6.414 10.473 8.231 1.00 69.84 N
ATOM 4233 CA PRO B 247 -7.075 11.665 7.696 1.00 67.28 C
ATOM 4234 C PRO B 247 -5.930 12.502 7.072 1.00 65.99 C
ATOM 4235 O PRO B 247 -4.760 12.353 7.459 1.00 64.86 O
ATOM 4236 CB PRO B 247 -7.699 12.305 8.938 1.00 66.52 C
ATOM 4237 CG PRO B 247 -6.711 11.986 10.000 1.00 67.42 C
ATOM 4238 CD PRO B 247 -6.329 10.536 9.706 1.00 69.14 C
ATOM 4239 N VAL B 248 -6.249 13.338 6.086 1.00 64.07 N
ATOM 4240 CA VAL B 248 -5.241 14.190 5.439 1.00 60.46 C
ATOM 4241 C VAL B 248 -5.921 15.535 5.101 1.00 58.21 C
ATOM 4242 O VAL B 248 -6.760 15.607 4.207 1.00 58.79 O
ATOM 4243 CB VAL B 248 -4.680 13.507 4.154 1.00 59.13 C
ATOM 4244 CG1 VAL B 248 -3.535 14.290 3.618 1.00 59.22 C
ATOM 4245 CG2 VAL B 248 -4.185 12.120 4.470 1.00 60.23 C
ATOM 4246 N VAL B 249 -5.577 16.598 5.824 1.00 54.05 N
ATOM 4247 CA VAL B 249 -6.222 17.889 5.588 1.00 51.52 C
ATOM 4248 C VAL B 249 -6.153 18.368 4.154 1.00 49.68 C
ATOM 4249 O VAL B 249 -5.299 17.924 3.388 1.00 50.93 O
ATOM 4250 CB VAL B 249 -5.605 18.974 6.443 1.00 50.57 C
ATOM 4251 CG1 VAL B 249 -5.885 18.694 7.887 1.00 50.72 C
ATOM 4252 CG2 VAL B 249 -4.123 19.038 6.179 1.00 48.35 C
ATOM 4253 N GLY B 250 -7.044 19.285 3.796 1.00 45.28 N
ATOM 4254 CA GLY B 250 -7.033 19.827 2.450 1.00 44.16 C
ATOM 4255 C GLY B 250 -7.448 18.882 1.329 1.00 45.03 C
ATOM 4256 O GLY B 250 -6.775 18.784 0.285 1.00 43.44 O
ATOM 4257 N GLY B 251 -8.575 18.205 1.551 1.00 45.14 N
ATOM 4258 CA GLY B 251 -9.112 17.275 0.582 1.00 44.15 C
ATOM 4259 C GLY B 251 -10.476 17.678 0.046 1.00 44.72 C
ATOM 4260 O GLY B 251 -11.002 18.752 0.360 1.00 45.93 O
ATOM 4261 N LEU B 252 -11.036 16.800 -0.781 1.00 43.77 N
ATOM 4262 CA LEU B 252 -12.327 16.987 -1.414 1.00 44.97 C
ATOM 4263 C LEU B 252 -13.434 17.433 -0.458 1.00 47.83 C
ATOM 4264 O LEU B 252 -13.544 16.954 0.689 1.00 51.38 O
ATOM 4265 CB LEU B 252 -12.731 15.677 -2.100 1.00 43.84 C
ATOM 4266 CG LEU B 252 -11.779 15.293 -3.231 1.00 43.55 C
ATOM 4267 CD1 LEU B 252 -11.824 13.802 -3.524 1.00 41.47 C
ATOM 4268 CD2 LEU B 252 -12.134 16.118 -4.447 1.00 41.53 C
ATOM 4269 N SER B 253 -14.274 18.344 -0.925 1.00 46.62 N
ATOM 4270 CA SER B 253 -15.364 18.809 -0.090 1.00 46.70 C
ATOM 4271 C SER B 253 -16.561 17.892 -0.282 1.00 47.40 C
ATOM 4272 O SER B 253 -16.631 17.166 -1.275 1.00 48.44 O
ATOM 4273 CB SER B 253 -15.728 20.206 -0.512 1.00 45.90 C
ATOM 4274 OG SER B 253 -15.761 20.249 -1.924 1.00 46.47 O
ATOM 4275 N TYR B 254 -17.493 17.919 0.668 1.00 47.39 N
ATOM 4276 CA TYR B 254 -18.703 17.112 0.575 1.00 47.44 C
ATOM 4277 C TYR B 254 -19.215 17.428 -0.818 1.00 49.11 C
ATOM 4278 O TYR B 254 -19.350 16.527 -1.646 1.00 49.44 O
ATOM 4279 CB TYR B 254 -19.721 17.560 1.625 1.00 46.22 C
ATOM 4280 CG TYR B 254 -21.033 16.780 1.680 1.00 47.21 C
ATOM 4281 CD1 TYR B 254 -21.074 15.463 2.129 1.00 48.90 C
ATOM 4282 CD2 TYR B 254 -22.246 17.399 1.382 1.00 47.33 C
ATOM 4283 CE1 TYR B 254 -22.293 14.781 2.293 1.00 49.41 C
ATOM 4284 CE2 TYR B 254 -23.468 16.738 1.537 1.00 49.47 C
ATOM 4285 CZ TYR B 254 -23.488 15.429 1.997 1.00 51.72 C
ATOM 4286 OH TYR B 254 -24.705 14.787 2.189 1.00 53.13 O
ATOM 4287 N ARG B 255 -19.458 18.717 -1.076 1.00 49.81 N
ATOM 4288 CA ARG B 255 -19.929 19.199 -2.380 1.00 50.99 C
ATOM 4289 C ARG B 255 -19.147 18.586 -3.550 1.00 52.53 C
ATOM 4290 O ARG B 255 -19.732 17.925 -4.422 1.00 53.55 O
ATOM 4291 CB ARG B 255 -19.824 20.730 -2.447 1.00 51.35 C
ATOM 4292 CG ARG B 255 -21.030 21.461 -1.878 1.00 54.18 C
ATOM 4293 CD ARG B 255 -20.807 22.965 -1.711 1.00 55.20 C
ATOM 4294 NE ARG B 255 -20.629 23.647 -2.991 1.00 59.63 N
ATOM 4295 CZ ARG B 255 -20.370 24.951 -3.120 1.00 62.22 C
ATOM 4296 NH1 ARG B 255 -20.262 25.723 -2.036 1.00 63.52 N
ATOM 4297 NH2 ARG B 255 -20.207 25.487 -4.332 1.00 60.66 N
ATOM 4298 N GLU B 256 -17.835 18.809 -3.577 1.00 52.25 N
ATOM 4299 CA GLU B 256 -17.012 18.253 -4.641 1.00 54.48 C
ATOM 4300 C GLU B 256 -17.175 16.732 -4.750 1.00 55.70 C
ATOM 4301 O GLU B 256 -17.172 16.174 -5.852 1.00 56.74 O
ATOM 4302 CB GLU B 256 -15.536 18.568 -4.408 1.00 55.00 C
ATOM 4303 CG GLU B 256 -15.167 20.024 -4.546 1.00 55.21 C
ATOM 4304 CD GLU B 256 -13.690 20.238 -4.363 1.00 56.50 C
ATOM 4305 OE1 GLU B 256 -13.136 19.646 -3.406 1.00 57.48 O
ATOM 4306 OE2 GLU B 256 -13.090 20.996 -5.165 1.00 57.60 O
ATOM 4307 N GLY B 257 -17.307 16.066 -3.605 1.00 55.23 N
ATOM 4308 CA GLY B 257 -17.458 14.621 -3.604 1.00 54.94 C
ATOM 4309 C GLY B 257 -18.809 14.196 -4.130 1.00 54.60 C
ATOM 4310 O GLY B 257 -18.952 13.171 -4.804 1.00 52.82 O
ATOM 4311 N LEU B 258 -19.816 14.985 -3.792 1.00 54.63 N
ATOM 4312 CA LEU B 258 -21.140 14.698 -4.262 1.00 55.19 C
ATOM 4313 C LEU B 258 -21.180 15.085 -5.724 1.00 56.88 C
ATOM 4314 O LEU B 258 -21.970 14.533 -6.492 1.00 58.61 O
ATOM 4315 CB LEU B 258 -22.189 15.472 -3.470 1.00 53.48 C
ATOM 4316 CG LEU B 258 -22.512 14.822 -2.128 1.00 51.43 C
ATOM 4317 CD1 LEU B 258 -23.756 15.439 -1.523 1.00 50.84 C
ATOM 4318 CD2 LEU B 258 -22.745 13.351 -2.353 1.00 52.56 C
ATOM 4319 N TYR B 259 -20.326 16.013 -6.139 1.00 56.63 N
ATOM 4320 CA TYR B 259 -20.360 16.361 -7.545 1.00 58.61 C
ATOM 4321 C TYR B 259 -19.828 15.208 -8.381 1.00 59.71 C
ATOM 4322 O TYR B 259 -20.349 14.921 -9.464 1.00 61.48 O
ATOM 4323 CB TYR B 259 -19.542 17.592 -7.860 1.00 58.79 C
ATOM 4324 CG TYR B 259 -19.789 18.056 -9.278 1.00 59.56 C
ATOM 4325 CD1 TYR B 259 -20.823 18.958 -9.563 1.00 58.31 C
ATOM 4326 CD2 TYR B 259 -18.976 17.609 -10.334 1.00 57.95 C
ATOM 4327 CE1 TYR B 259 -21.034 19.417 -10.863 1.00 60.55 C
ATOM 4328 CE2 TYR B 259 -19.172 18.055 -11.636 1.00 58.97 C
ATOM 4329 CZ TYR B 259 -20.199 18.965 -11.896 1.00 61.35 C
ATOM 4330 OH TYR B 259 -20.372 19.458 -13.168 1.00 61.49 O
ATOM 4331 N ILE B 260 -18.786 14.552 -7.880 1.00 59.36 N
ATOM 4332 CA ILE B 260 -18.202 13.421 -8.583 1.00 59.47 C
ATOM 4333 C ILE B 260 -19.249 12.321 -8.792 1.00 59.59 C
ATOM 4334 O ILE B 260 -19.676 12.079 -9.921 1.00 57.54 O
ATOM 4335 CB ILE B 260 -16.982 12.869 -7.808 1.00 60.43 C
ATOM 4336 CG1 ILE B 260 -15.830 13.883 -7.866 1.00 60.99 C
ATOM 4337 CG2 ILE B 260 -16.537 11.545 -8.394 1.00 61.05 C
ATOM 4338 CD1 ILE B 260 -14.602 13.463 -7.095 1.00 60.66 C
ATOM 4339 N THR B 261 -19.673 11.663 -7.715 1.00 61.59 N
ATOM 4340 CA THR B 261 -20.679 10.600 -7.830 1.00 63.51 C
ATOM 4341 C THR B 261 -21.848 11.051 -8.724 1.00 67.33 C
ATOM 4342 O THR B 261 -22.469 10.226 -9.416 1.00 68.11 O
ATOM 4343 CB THR B 261 -21.267 10.214 -6.463 1.00 60.27 C
ATOM 4344 OG1 THR B 261 -21.775 11.390 -5.839 1.00 57.46 O
ATOM 4345 CG2 THR B 261 -20.224 9.565 -5.562 1.00 57.45 C
ATOM 4346 N GLU B 262 -22.149 12.352 -8.694 1.00 69.10 N
ATOM 4347 CA GLU B 262 -23.231 12.911 -9.506 1.00 71.64 C
ATOM 4348 C GLU B 262 -22.948 12.847 -11.012 1.00 74.49 C
ATOM 4349 O GLU B 262 -23.808 12.429 -11.791 1.00 73.82 O
ATOM 4350 CB GLU B 262 -23.521 14.356 -9.100 1.00 70.03 C
ATOM 4351 CG GLU B 262 -24.330 14.476 -7.827 1.00 66.23 C
ATOM 4352 CD GLU B 262 -24.944 15.852 -7.659 1.00 64.16 C
ATOM 4353 OE1 GLU B 262 -24.311 16.850 -8.079 1.00 61.75 O
ATOM 4354 OE2 GLU B 262 -26.056 15.930 -7.091 1.00 61.96 O
ATOM 4355 N GLU B 263 -21.756 13.272 -11.424 1.00 77.10 N
ATOM 4356 CA GLU B 263 -21.389 13.210 -12.836 1.00 80.64 C
ATOM 4357 C GLU B 263 -21.162 11.756 -13.256 1.00 82.90 C
ATOM 4358 O GLU B 263 -21.287 11.410 -14.435 1.00 83.65 O
ATOM 4359 CB GLU B 263 -20.131 14.024 -13.100 1.00 81.10 C
ATOM 4360 CG GLU B 263 -20.421 15.491 -13.227 1.00 85.33 C
ATOM 4361 CD GLU B 263 -21.485 15.765 -14.284 1.00 87.53 C
ATOM 4362 OE1 GLU B 263 -21.239 15.415 -15.459 1.00 89.71 O
ATOM 4363 OE2 GLU B 263 -22.559 16.321 -13.943 1.00 87.81 O
ATOM 4364 N ILE B 264 -20.823 10.915 -12.283 1.00 83.91 N
ATOM 4365 CA ILE B 264 -20.611 9.497 -12.526 1.00 86.02 C
ATOM 4366 C ILE B 264 -21.955 8.900 -12.934 1.00 87.43 C
ATOM 4367 O ILE B 264 -22.090 8.238 -13.972 1.00 86.72 O
ATOM 4368 CB ILE B 264 -20.111 8.777 -11.239 1.00 86.67 C
ATOM 4369 CG1 ILE B 264 -18.624 9.057 -11.019 1.00 87.39 C
ATOM 4370 CG2 ILE B 264 -20.400 7.278 -11.320 1.00 86.51 C
ATOM 4371 CD1 ILE B 264 -17.722 8.636 -12.167 1.00 86.98 C
ATOM 4372 N TYR B 265 -22.947 9.151 -12.089 1.00 88.88 N
ATOM 4373 CA TYR B 265 -24.294 8.665 -12.313 1.00 89.33 C
ATOM 4374 C TYR B 265 -24.838 9.135 -13.662 1.00 89.27 C
ATOM 4375 O TYR B 265 -25.335 8.338 -14.451 1.00 89.51 O
ATOM 4376 CB TYR B 265 -25.211 9.151 -11.191 1.00 89.38 C
ATOM 4377 CG TYR B 265 -26.653 8.978 -11.527 1.00 89.34 C
ATOM 4378 CD1 TYR B 265 -27.218 7.713 -11.579 1.00 90.14 C
ATOM 4379 CD2 TYR B 265 -27.434 10.072 -11.894 1.00 90.59 C
ATOM 4380 CE1 TYR B 265 -28.532 7.528 -12.002 1.00 92.33 C
ATOM 4381 CE2 TYR B 265 -28.749 9.905 -12.318 1.00 92.63 C
ATOM 4382 CZ TYR B 265 -29.294 8.627 -12.373 1.00 92.95 C
ATOM 4383 OH TYR B 265 -30.590 8.450 -12.814 1.00 93.11 O
ATOM 4384 N LYS B 266 -24.736 10.434 -13.920 1.00 89.51 N
ATOM 4385 CA LYS B 266 -25.224 11.027 -15.161 1.00 90.13 C
ATOM 4386 C LYS B 266 -24.641 10.431 -16.447 1.00 89.83 C
ATOM 4387 O LYS B 266 -24.958 10.888 -17.547 1.00 89.92 O
ATOM 4388 CB LYS B 266 -24.980 12.542 -15.132 1.00 91.98 C
ATOM 4389 CG LYS B 266 -25.880 13.295 -14.154 1.00 93.52 C
ATOM 4390 CD LYS B 266 -25.434 14.744 -13.932 1.00 94.83 C
ATOM 4391 CE LYS B 266 -25.519 15.597 -15.201 1.00 95.81 C
ATOM 4392 NZ LYS B 266 -24.411 15.351 -16.180 1.00 96.25 N
ATOM 4393 N THR B 267 -23.799 9.411 -16.319 1.00 89.07 N
ATOM 4394 CA THR B 267 -23.203 8.782 -17.495 1.00 87.97 C
ATOM 4395 C THR B 267 -23.697 7.343 -17.653 1.00 88.38 C
ATOM 4396 O THR B 267 -23.315 6.633 -18.588 1.00 88.04 O
ATOM 4397 CB THR B 267 -21.683 8.776 -17.391 1.00 86.90 C
ATOM 4398 OG1 THR B 267 -21.280 7.862 -16.362 1.00 86.88 O
ATOM 4399 CG2 THR B 267 -21.189 10.174 -17.069 1.00 84.42 C
ATOM 4400 N GLY B 268 -24.547 6.930 -16.721 1.00 88.84 N
ATOM 4401 CA GLY B 268 -25.110 5.595 -16.745 1.00 88.87 C
ATOM 4402 C GLY B 268 -24.112 4.461 -16.897 1.00 89.07 C
ATOM 4403 O GLY B 268 -24.507 3.311 -17.090 1.00 90.27 O
ATOM 4404 N LEU B 269 -22.824 4.758 -16.793 1.00 87.70 N
ATOM 4405 CA LEU B 269 -21.826 3.715 -16.953 1.00 87.22 C
ATOM 4406 C LEU B 269 -21.290 3.108 -15.666 1.00 86.80 C
ATOM 4407 O LEU B 269 -20.222 2.487 -15.674 1.00 84.64 O
ATOM 4408 CB LEU B 269 -20.655 4.248 -17.770 1.00 88.82 C
ATOM 4409 CG LEU B 269 -20.966 4.646 -19.208 1.00 89.57 C
ATOM 4410 CD1 LEU B 269 -19.654 4.970 -19.908 1.00 89.71 C
ATOM 4411 CD2 LEU B 269 -21.686 3.506 -19.930 1.00 89.67 C
ATOM 4412 N LEU B 270 -22.021 3.273 -14.564 1.00 87.46 N
ATOM 4413 CA LEU B 270 -21.566 2.730 -13.284 1.00 88.00 C
ATOM 4414 C LEU B 270 -21.791 1.232 -13.229 1.00 87.09 C
ATOM 4415 O LEU B 270 -22.894 0.750 -13.487 1.00 87.38 O
ATOM 4416 CB LEU B 270 -22.285 3.384 -12.096 1.00 88.45 C
ATOM 4417 CG LEU B 270 -21.788 2.873 -10.728 1.00 88.79 C
ATOM 4418 CD1 LEU B 270 -20.402 3.440 -10.438 1.00 86.57 C
ATOM 4419 CD2 LEU B 270 -22.769 3.264 -9.631 1.00 88.64 C
ATOM 4420 N SER B 271 -20.745 0.496 -12.880 1.00 85.87 N
ATOM 4421 CA SER B 271 -20.863 -0.944 -12.812 1.00 85.51 C
ATOM 4422 C SER B 271 -20.491 -1.467 -11.422 1.00 83.98 C
ATOM 4423 O SER B 271 -21.197 -2.308 -10.853 1.00 83.61 O
ATOM 4424 CB SER B 271 -19.976 -1.567 -13.893 1.00 86.30 C
ATOM 4425 OG SER B 271 -20.537 -2.781 -14.356 1.00 87.42 O
ATOM 4426 N GLY B 272 -19.389 -0.953 -10.878 1.00 81.96 N
ATOM 4427 CA GLY B 272 -18.936 -1.374 -9.564 1.00 78.89 C
ATOM 4428 C GLY B 272 -18.612 -0.177 -8.691 1.00 76.86 C
ATOM 4429 O GLY B 272 -17.954 0.765 -9.139 1.00 75.55 O
ATOM 4430 N LEU B 273 -19.061 -0.221 -7.440 1.00 74.99 N
ATOM 4431 CA LEU B 273 -18.843 0.879 -6.505 1.00 72.30 C
ATOM 4432 C LEU B 273 -18.180 0.433 -5.200 1.00 70.78 C
ATOM 4433 O LEU B 273 -18.545 -0.588 -4.619 1.00 69.89 O
ATOM 4434 CB LEU B 273 -20.187 1.544 -6.180 1.00 71.11 C
ATOM 4435 CG LEU B 273 -20.298 3.047 -5.890 1.00 69.91 C
ATOM 4436 CD1 LEU B 273 -21.422 3.239 -4.886 1.00 68.42 C
ATOM 4437 CD2 LEU B 273 -18.994 3.623 -5.343 1.00 68.44 C
ATOM 4438 N ASP B 274 -17.208 1.209 -4.742 1.00 70.14 N
ATOM 4439 CA ASP B 274 -16.527 0.896 -3.493 1.00 69.92 C
ATOM 4440 C ASP B 274 -16.599 2.047 -2.480 1.00 68.55 C
ATOM 4441 O ASP B 274 -16.219 3.181 -2.767 1.00 68.14 O
ATOM 4442 CB ASP B 274 -15.061 0.504 -3.756 1.00 69.92 C
ATOM 4443 CG ASP B 274 -14.925 -0.871 -4.413 1.00 70.83 C
ATOM 4444 OD1 ASP B 274 -15.643 -1.813 -4.004 1.00 69.82 O
ATOM 4445 OD2 ASP B 274 -14.090 -1.014 -5.328 1.00 71.83 O
ATOM 4446 N ILE B 275 -17.131 1.742 -1.303 1.00 67.15 N
ATOM 4447 CA ILE B 275 -17.245 2.712 -0.223 1.00 65.60 C
ATOM 4448 C ILE B 275 -16.417 2.118 0.910 1.00 65.13 C
ATOM 4449 O ILE B 275 -16.938 1.399 1.780 1.00 63.76 O
ATOM 4450 CB ILE B 275 -18.717 2.901 0.215 1.00 65.55 C
ATOM 4451 CG1 ILE B 275 -19.465 3.725 -0.832 1.00 65.04 C
ATOM 4452 CG2 ILE B 275 -18.794 3.586 1.562 1.00 65.82 C
ATOM 4453 CD1 ILE B 275 -19.774 2.967 -2.099 1.00 67.21 C
ATOM 4454 N MET B 276 -15.119 2.436 0.866 1.00 63.90 N
ATOM 4455 CA MET B 276 -14.124 1.935 1.808 1.00 62.24 C
ATOM 4456 C MET B 276 -13.640 2.957 2.815 1.00 61.84 C
ATOM 4457 O MET B 276 -13.971 4.141 2.726 1.00 60.99 O
ATOM 4458 CB MET B 276 -12.892 1.446 1.047 1.00 62.85 C
ATOM 4459 CG MET B 276 -13.190 0.788 -0.276 1.00 66.01 C
ATOM 4460 SD MET B 276 -14.375 -0.544 -0.098 1.00 70.21 S
ATOM 4461 CE MET B 276 -13.533 -1.520 1.190 1.00 69.59 C
ATOM 4462 N GLU B 277 -12.831 2.451 3.756 1.00 61.47 N
ATOM 4463 CA GLU B 277 -12.154 3.196 4.840 1.00 61.13 C
ATOM 4464 C GLU B 277 -12.970 3.867 5.936 1.00 60.56 C
ATOM 4465 O GLU B 277 -12.479 4.789 6.589 1.00 58.86 O
ATOM 4466 CB GLU B 277 -11.188 4.252 4.261 1.00 60.57 C
ATOM 4467 CG GLU B 277 -9.977 3.708 3.482 1.00 59.95 C
ATOM 4468 CD GLU B 277 -9.153 2.713 4.268 1.00 60.38 C
ATOM 4469 OE1 GLU B 277 -9.195 2.718 5.516 1.00 60.82 O
ATOM 4470 OE2 GLU B 277 -8.460 1.892 3.649 1.00 63.05 O
ATOM 4471 N VAL B 278 -14.201 3.422 6.149 1.00 60.40 N
ATOM 4472 CA VAL B 278 -15.009 4.028 7.191 1.00 61.42 C
ATOM 4473 C VAL B 278 -14.776 3.290 8.486 1.00 61.69 C
ATOM 4474 O VAL B 278 -15.062 2.105 8.553 1.00 62.84 O
ATOM 4475 CB VAL B 278 -16.490 3.933 6.893 1.00 61.62 C
ATOM 4476 CG1 VAL B 278 -17.262 4.280 8.147 1.00 60.45 C
ATOM 4477 CG2 VAL B 278 -16.862 4.888 5.769 1.00 63.02 C
ATOM 4478 N ASN B 279 -14.288 3.987 9.514 1.00 62.09 N
ATOM 4479 CA ASN B 279 -14.014 3.355 10.806 1.00 62.05 C
ATOM 4480 C ASN B 279 -14.909 3.855 11.926 1.00 62.56 C
ATOM 4481 O ASN B 279 -14.475 4.674 12.726 1.00 62.08 O
ATOM 4482 CB ASN B 279 -12.564 3.597 11.218 1.00 61.37 C
ATOM 4483 CG ASN B 279 -11.976 2.422 11.977 1.00 60.61 C
ATOM 4484 OD1 ASN B 279 -12.700 1.672 12.638 1.00 58.30 O
ATOM 4485 ND2 ASN B 279 -10.655 2.257 11.888 1.00 57.50 N
ATOM 4486 N PRO B 280 -16.161 3.355 12.011 1.00 64.39 N
ATOM 4487 CA PRO B 280 -17.190 3.701 13.008 1.00 67.08 C
ATOM 4488 C PRO B 280 -16.722 3.820 14.455 1.00 69.58 C
ATOM 4489 O PRO B 280 -17.513 4.097 15.358 1.00 69.61 O
ATOM 4490 CB PRO B 280 -18.225 2.593 12.826 1.00 65.11 C
ATOM 4491 CG PRO B 280 -18.194 2.386 11.383 1.00 64.36 C
ATOM 4492 CD PRO B 280 -16.698 2.354 11.076 1.00 64.19 C
ATOM 4493 N THR B 281 -15.429 3.614 14.660 1.00 72.57 N
ATOM 4494 CA THR B 281 -14.835 3.685 15.980 1.00 75.80 C
ATOM 4495 C THR B 281 -13.861 4.852 16.071 1.00 76.44 C
ATOM 4496 O THR B 281 -13.657 5.423 17.141 1.00 76.53 O
ATOM 4497 CB THR B 281 -14.105 2.371 16.295 1.00 76.94 C
ATOM 4498 OG1 THR B 281 -13.387 1.939 15.132 1.00 79.55 O
ATOM 4499 CG2 THR B 281 -15.100 1.291 16.684 1.00 77.78 C
ATOM 4500 N LEU B 282 -13.259 5.207 14.945 1.00 78.33 N
ATOM 4501 CA LEU B 282 -12.316 6.310 14.927 1.00 80.29 C
ATOM 4502 C LEU B 282 -13.041 7.643 14.878 1.00 83.19 C
ATOM 4503 O LEU B 282 -12.875 8.417 13.938 1.00 85.02 O
ATOM 4504 CB LEU B 282 -11.357 6.185 13.740 1.00 77.40 C
ATOM 4505 CG LEU B 282 -10.506 4.921 13.807 1.00 75.93 C
ATOM 4506 CD1 LEU B 282 -9.445 4.935 12.731 1.00 75.40 C
ATOM 4507 CD2 LEU B 282 -9.874 4.837 15.173 1.00 75.90 C
ATOM 4508 N GLY B 283 -13.857 7.899 15.894 1.00 85.07 N
ATOM 4509 CA GLY B 283 -14.577 9.158 15.963 1.00 86.60 C
ATOM 4510 C GLY B 283 -14.207 9.929 17.223 1.00 87.56 C
ATOM 4511 O GLY B 283 -14.351 9.407 18.338 1.00 88.62 O
ATOM 4512 N LYS B 284 -13.715 11.159 17.047 1.00 86.77 N
ATOM 4513 CA LYS B 284 -13.327 12.019 18.170 1.00 85.88 C
ATOM 4514 C LYS B 284 -14.562 12.194 19.046 1.00 85.02 C
ATOM 4515 O LYS B 284 -14.466 12.259 20.275 1.00 84.12 O
ATOM 4516 CB LYS B 284 -12.864 13.392 17.662 1.00 87.29 C
ATOM 4517 CG LYS B 284 -11.694 14.023 18.422 1.00 87.71 C
ATOM 4518 CD LYS B 284 -10.348 13.677 17.777 1.00 87.88 C
ATOM 4519 CE LYS B 284 -10.090 12.171 17.780 1.00 88.18 C
ATOM 4520 NZ LYS B 284 -8.876 11.769 17.023 1.00 87.29 N
ATOM 4521 N THR B 285 -15.717 12.274 18.382 1.00 84.15 N
ATOM 4522 CA THR B 285 -17.013 12.416 19.030 1.00 83.26 C
ATOM 4523 C THR B 285 -18.043 11.672 18.189 1.00 82.99 C
ATOM 4524 O THR B 285 -17.906 11.557 16.969 1.00 81.31 O
ATOM 4525 CB THR B 285 -17.471 13.877 19.110 1.00 83.35 C
ATOM 4526 OG1 THR B 285 -17.924 14.311 17.820 1.00 84.05 O
ATOM 4527 CG2 THR B 285 -16.332 14.766 19.568 1.00 84.61 C
ATOM 4528 N PRO B 286 -19.093 11.157 18.838 1.00 83.41 N
ATOM 4529 CA PRO B 286 -20.171 10.419 18.180 1.00 82.95 C
ATOM 4530 C PRO B 286 -20.686 11.076 16.900 1.00 82.76 C
ATOM 4531 O PRO B 286 -20.970 10.385 15.918 1.00 83.94 O
ATOM 4532 CB PRO B 286 -21.227 10.336 19.271 1.00 83.43 C
ATOM 4533 CG PRO B 286 -20.376 10.131 20.497 1.00 83.83 C
ATOM 4534 CD PRO B 286 -19.289 11.174 20.301 1.00 84.08 C
ATOM 4535 N GLU B 287 -20.816 12.401 16.916 1.00 81.54 N
ATOM 4536 CA GLU B 287 -21.278 13.134 15.739 1.00 80.48 C
ATOM 4537 C GLU B 287 -20.350 12.844 14.549 1.00 79.49 C
ATOM 4538 O GLU B 287 -20.801 12.375 13.497 1.00 78.67 O
ATOM 4539 CB GLU B 287 -21.306 14.640 16.048 1.00 82.25 C
ATOM 4540 CG GLU B 287 -20.670 15.575 14.991 1.00 83.83 C
ATOM 4541 CD GLU B 287 -21.444 15.651 13.667 1.00 84.57 C
ATOM 4542 OE1 GLU B 287 -21.411 14.670 12.894 1.00 85.56 O
ATOM 4543 OE2 GLU B 287 -22.085 16.694 13.392 1.00 84.28 O
ATOM 4544 N GLU B 288 -19.058 13.124 14.730 1.00 77.25 N
ATOM 4545 CA GLU B 288 -18.054 12.893 13.695 1.00 73.95 C
ATOM 4546 C GLU B 288 -18.300 11.588 12.963 1.00 72.69 C
ATOM 4547 O GLU B 288 -18.205 11.531 11.741 1.00 72.64 O
ATOM 4548 CB GLU B 288 -16.660 12.858 14.303 1.00 72.46 C
ATOM 4549 CG GLU B 288 -16.253 14.151 14.968 1.00 70.50 C
ATOM 4550 CD GLU B 288 -14.748 14.285 15.077 1.00 69.40 C
ATOM 4551 OE1 GLU B 288 -14.042 13.305 14.736 1.00 68.54 O
ATOM 4552 OE2 GLU B 288 -14.269 15.363 15.503 1.00 68.62 O
ATOM 4553 N VAL B 289 -18.592 10.533 13.718 1.00 71.45 N
ATOM 4554 CA VAL B 289 -18.879 9.235 13.115 1.00 70.18 C
ATOM 4555 C VAL B 289 -20.140 9.457 12.289 1.00 69.20 C
ATOM 4556 O VAL B 289 -20.085 9.474 11.060 1.00 68.99 O
ATOM 4557 CB VAL B 289 -19.139 8.118 14.191 1.00 69.79 C
ATOM 4558 CG1 VAL B 289 -19.421 6.783 13.513 1.00 67.62 C
ATOM 4559 CG2 VAL B 289 -17.921 7.970 15.103 1.00 69.71 C
ATOM 4560 N THR B 290 -21.268 9.646 12.970 1.00 68.00 N
ATOM 4561 CA THR B 290 -22.547 9.886 12.301 1.00 66.88 C
ATOM 4562 C THR B 290 -22.354 10.705 11.022 1.00 66.56 C
ATOM 4563 O THR B 290 -22.879 10.361 9.956 1.00 66.19 O
ATOM 4564 CB THR B 290 -23.512 10.637 13.231 1.00 65.35 C
ATOM 4565 OG1 THR B 290 -23.831 9.796 14.340 1.00 63.64 O
ATOM 4566 CG2 THR B 290 -24.785 11.014 12.497 1.00 64.85 C
ATOM 4567 N ARG B 291 -21.601 11.794 11.149 1.00 65.26 N
ATOM 4568 CA ARG B 291 -21.305 12.673 10.019 1.00 64.06 C
ATOM 4569 C ARG B 291 -20.752 11.776 8.920 1.00 63.34 C
ATOM 4570 O ARG B 291 -21.368 11.576 7.869 1.00 64.70 O
ATOM 4571 CB ARG B 291 -20.242 13.694 10.431 1.00 61.65 C
ATOM 4572 CG ARG B 291 -19.924 14.758 9.410 1.00 58.64 C
ATOM 4573 CD ARG B 291 -18.895 15.714 9.997 1.00 56.90 C
ATOM 4574 NE ARG B 291 -19.239 16.039 11.378 1.00 57.01 N
ATOM 4575 CZ ARG B 291 -18.431 16.640 12.249 1.00 57.06 C
ATOM 4576 NH1 ARG B 291 -17.200 17.003 11.887 1.00 57.97 N
ATOM 4577 NH2 ARG B 291 -18.840 16.850 13.497 1.00 55.48 N
ATOM 4578 N THR B 292 -19.583 11.223 9.210 1.00 61.05 N
ATOM 4579 CA THR B 292 -18.870 10.335 8.319 1.00 58.67 C
ATOM 4580 C THR B 292 -19.791 9.300 7.690 1.00 58.47 C
ATOM 4581 O THR B 292 -19.712 9.011 6.501 1.00 57.49 O
ATOM 4582 CB THR B 292 -17.768 9.615 9.105 1.00 58.81 C
ATOM 4583 OG1 THR B 292 -16.924 10.586 9.758 1.00 56.48 O
ATOM 4584 CG2 THR B 292 -16.945 8.730 8.167 1.00 59.71 C
ATOM 4585 N VAL B 293 -20.680 8.754 8.504 1.00 59.78 N
ATOM 4586 CA VAL B 293 -21.613 7.736 8.055 1.00 58.82 C
ATOM 4587 C VAL B 293 -22.630 8.206 7.030 1.00 58.73 C
ATOM 4588 O VAL B 293 -22.764 7.603 5.974 1.00 60.24 O
ATOM 4589 CB VAL B 293 -22.347 7.136 9.250 1.00 57.64 C
ATOM 4590 CG1 VAL B 293 -23.587 6.420 8.796 1.00 59.61 C
ATOM 4591 CG2 VAL B 293 -21.424 6.177 9.968 1.00 56.78 C
ATOM 4592 N ASN B 294 -23.352 9.275 7.325 1.00 59.01 N
ATOM 4593 CA ASN B 294 -24.355 9.760 6.381 1.00 59.52 C
ATOM 4594 C ASN B 294 -23.742 10.253 5.077 1.00 57.04 C
ATOM 4595 O ASN B 294 -24.173 9.860 4.000 1.00 56.04 O
ATOM 4596 CB ASN B 294 -25.189 10.861 7.033 1.00 62.65 C
ATOM 4597 CG ASN B 294 -25.795 10.416 8.355 1.00 65.74 C
ATOM 4598 OD1 ASN B 294 -26.572 9.445 8.408 1.00 65.73 O
ATOM 4599 ND2 ASN B 294 -25.433 11.114 9.437 1.00 65.75 N
ATOM 4600 N THR B 295 -22.732 11.108 5.178 1.00 55.78 N
ATOM 4601 CA THR B 295 -22.048 11.630 3.995 1.00 53.42 C
ATOM 4602 C THR B 295 -21.631 10.459 3.087 1.00 51.63 C
ATOM 4603 O THR B 295 -21.720 10.529 1.853 1.00 51.32 O
ATOM 4604 CB THR B 295 -20.802 12.457 4.408 1.00 51.74 C
ATOM 4605 OG1 THR B 295 -20.117 12.920 3.243 1.00 51.03 O
ATOM 4606 CG2 THR B 295 -19.850 11.609 5.222 1.00 52.14 C
ATOM 4607 N ALA B 296 -21.181 9.381 3.712 1.00 48.87 N
ATOM 4608 CA ALA B 296 -20.797 8.205 2.972 1.00 48.83 C
ATOM 4609 C ALA B 296 -22.069 7.688 2.292 1.00 49.86 C
ATOM 4610 O ALA B 296 -22.149 7.586 1.066 1.00 48.11 O
ATOM 4611 CB ALA B 296 -20.250 7.180 3.919 1.00 48.98 C
ATOM 4612 N VAL B 297 -23.067 7.391 3.120 1.00 51.36 N
ATOM 4613 CA VAL B 297 -24.375 6.917 2.672 1.00 53.60 C
ATOM 4614 C VAL B 297 -24.870 7.798 1.533 1.00 55.78 C
ATOM 4615 O VAL B 297 -25.296 7.314 0.477 1.00 58.28 O
ATOM 4616 CB VAL B 297 -25.413 7.011 3.823 1.00 53.14 C
ATOM 4617 CG1 VAL B 297 -26.823 6.795 3.299 1.00 50.59 C
ATOM 4618 CG2 VAL B 297 -25.086 5.989 4.895 1.00 54.44 C
ATOM 4619 N ALA B 298 -24.816 9.100 1.767 1.00 56.73 N
ATOM 4620 CA ALA B 298 -25.261 10.070 0.796 1.00 58.92 C
ATOM 4621 C ALA B 298 -24.502 9.877 -0.505 1.00 61.14 C
ATOM 4622 O ALA B 298 -25.101 9.902 -1.583 1.00 62.85 O
ATOM 4623 CB ALA B 298 -25.035 11.481 1.341 1.00 58.61 C
ATOM 4624 N LEU B 299 -23.186 9.690 -0.415 1.00 60.82 N
ATOM 4625 CA LEU B 299 -22.391 9.511 -1.621 1.00 61.09 C
ATOM 4626 C LEU B 299 -22.836 8.292 -2.433 1.00 62.91 C
ATOM 4627 O LEU B 299 -22.633 8.249 -3.644 1.00 65.11 O
ATOM 4628 CB LEU B 299 -20.906 9.370 -1.286 1.00 57.81 C
ATOM 4629 CG LEU B 299 -20.026 10.567 -0.915 1.00 55.38 C
ATOM 4630 CD1 LEU B 299 -18.612 10.065 -0.868 1.00 53.96 C
ATOM 4631 CD2 LEU B 299 -20.096 11.695 -1.923 1.00 51.97 C
ATOM 4632 N THR B 300 -23.433 7.302 -1.779 1.00 62.76 N
ATOM 4633 CA THR B 300 -23.872 6.112 -2.499 1.00 62.65 C
ATOM 4634 C THR B 300 -25.097 6.447 -3.318 1.00 61.32 C
ATOM 4635 O THR B 300 -25.066 6.382 -4.543 1.00 59.77 O
ATOM 4636 CB THR B 300 -24.231 4.966 -1.539 1.00 63.73 C
ATOM 4637 OG1 THR B 300 -23.243 4.873 -0.507 1.00 65.35 O
ATOM 4638 CG2 THR B 300 -24.270 3.636 -2.291 1.00 63.25 C
ATOM 4639 N LEU B 301 -26.169 6.799 -2.618 1.00 60.60 N
ATOM 4640 CA LEU B 301 -27.430 7.189 -3.238 1.00 62.25 C
ATOM 4641 C LEU B 301 -27.212 8.230 -4.327 1.00 62.75 C
ATOM 4642 O LEU B 301 -28.117 8.541 -5.093 1.00 61.14 O
ATOM 4643 CB LEU B 301 -28.364 7.787 -2.187 1.00 62.64 C
ATOM 4644 CG LEU B 301 -28.728 6.888 -1.011 1.00 63.60 C
ATOM 4645 CD1 LEU B 301 -29.412 7.684 0.095 1.00 64.16 C
ATOM 4646 CD2 LEU B 301 -29.636 5.795 -1.528 1.00 64.47 C
ATOM 4647 N SER B 302 -26.014 8.797 -4.368 1.00 65.66 N
ATOM 4648 CA SER B 302 -25.693 9.803 -5.369 1.00 67.63 C
ATOM 4649 C SER B 302 -25.419 9.065 -6.667 1.00 69.13 C
ATOM 4650 O SER B 302 -26.016 9.357 -7.706 1.00 70.32 O
ATOM 4651 CB SER B 302 -24.467 10.605 -4.937 1.00 67.19 C
ATOM 4652 OG SER B 302 -24.310 11.748 -5.754 1.00 69.11 O
ATOM 4653 N CYS B 303 -24.527 8.083 -6.579 1.00 70.31 N
ATOM 4654 CA CYS B 303 -24.149 7.241 -7.706 1.00 71.32 C
ATOM 4655 C CYS B 303 -25.357 6.512 -8.289 1.00 72.31 C
ATOM 4656 O CYS B 303 -25.288 5.943 -9.380 1.00 72.83 O
ATOM 4657 CB CYS B 303 -23.153 6.190 -7.239 1.00 71.03 C
ATOM 4658 SG CYS B 303 -21.782 6.880 -6.365 1.00 72.69 S
ATOM 4659 N PHE B 304 -26.464 6.530 -7.557 1.00 73.09 N
ATOM 4660 CA PHE B 304 -27.655 5.831 -7.994 1.00 72.61 C
ATOM 4661 C PHE B 304 -28.883 6.682 -8.261 1.00 73.36 C
ATOM 4662 O PHE B 304 -30.007 6.239 -8.016 1.00 74.39 O
ATOM 4663 CB PHE B 304 -27.984 4.753 -6.975 1.00 71.80 C
ATOM 4664 CG PHE B 304 -26.899 3.738 -6.816 1.00 71.95 C
ATOM 4665 CD1 PHE B 304 -26.723 2.736 -7.763 1.00 72.36 C
ATOM 4666 CD2 PHE B 304 -26.029 3.798 -5.738 1.00 72.11 C
ATOM 4667 CE1 PHE B 304 -25.695 1.806 -7.639 1.00 71.54 C
ATOM 4668 CE2 PHE B 304 -24.999 2.873 -5.606 1.00 72.05 C
ATOM 4669 CZ PHE B 304 -24.833 1.875 -6.560 1.00 71.30 C
ATOM 4670 N GLY B 305 -28.685 7.899 -8.757 1.00 72.86 N
ATOM 4671 CA GLY B 305 -29.839 8.718 -9.067 1.00 72.03 C
ATOM 4672 C GLY B 305 -29.964 10.063 -8.392 1.00 71.73 C
ATOM 4673 O GLY B 305 -29.841 11.100 -9.055 1.00 72.28 O
ATOM 4674 N THR B 306 -30.224 10.047 -7.085 1.00 70.88 N
ATOM 4675 CA THR B 306 -30.388 11.276 -6.317 1.00 69.05 C
ATOM 4676 C THR B 306 -29.483 12.389 -6.854 1.00 69.72 C
ATOM 4677 O THR B 306 -28.260 12.218 -7.021 1.00 68.72 O
ATOM 4678 CB THR B 306 -30.085 11.068 -4.837 1.00 66.56 C
ATOM 4679 OG1 THR B 306 -30.506 9.762 -4.443 1.00 65.69 O
ATOM 4680 CG2 THR B 306 -30.840 12.083 -4.013 1.00 65.22 C
ATOM 4681 N LYS B 307 -30.117 13.522 -7.138 1.00 69.29 N
ATOM 4682 CA LYS B 307 -29.453 14.700 -7.672 1.00 69.35 C
ATOM 4683 C LYS B 307 -29.667 15.796 -6.639 1.00 68.64 C
ATOM 4684 O LYS B 307 -30.580 15.699 -5.831 1.00 68.97 O
ATOM 4685 CB LYS B 307 -30.096 15.051 -9.018 1.00 69.94 C
ATOM 4686 CG LYS B 307 -30.241 13.809 -9.917 1.00 71.55 C
ATOM 4687 CD LYS B 307 -31.297 13.970 -11.014 1.00 75.08 C
ATOM 4688 CE LYS B 307 -30.800 14.826 -12.165 1.00 76.43 C
ATOM 4689 NZ LYS B 307 -29.626 14.186 -12.835 1.00 77.73 N
ATOM 4690 N ARG B 308 -28.826 16.821 -6.628 1.00 68.82 N
ATOM 4691 CA ARG B 308 -29.007 17.873 -5.640 1.00 69.63 C
ATOM 4692 C ARG B 308 -30.032 18.907 -6.102 1.00 73.65 C
ATOM 4693 O ARG B 308 -30.206 19.973 -5.483 1.00 74.33 O
ATOM 4694 CB ARG B 308 -27.664 18.532 -5.308 1.00 65.67 C
ATOM 4695 CG ARG B 308 -27.001 17.925 -4.070 1.00 61.84 C
ATOM 4696 CD ARG B 308 -25.648 18.526 -3.776 1.00 56.86 C
ATOM 4697 NE ARG B 308 -24.675 18.123 -4.778 1.00 51.40 N
ATOM 4698 CZ ARG B 308 -23.667 18.885 -5.179 1.00 51.56 C
ATOM 4699 NH1 ARG B 308 -23.502 20.097 -4.661 1.00 50.69 N
ATOM 4700 NH2 ARG B 308 -22.829 18.439 -6.100 1.00 53.11 N
ATOM 4701 N GLU B 309 -30.723 18.580 -7.188 1.00 76.34 N
ATOM 4702 CA GLU B 309 -31.737 19.468 -7.713 1.00 78.81 C
ATOM 4703 C GLU B 309 -33.104 18.841 -7.508 1.00 81.14 C
ATOM 4704 O GLU B 309 -34.133 19.495 -7.688 1.00 80.97 O
ATOM 4705 CB GLU B 309 -31.491 19.737 -9.194 1.00 78.42 C
ATOM 4706 CG GLU B 309 -31.574 18.517 -10.065 1.00 79.83 C
ATOM 4707 CD GLU B 309 -31.942 18.874 -11.486 1.00 80.70 C
ATOM 4708 OE1 GLU B 309 -31.167 19.617 -12.136 1.00 79.92 O
ATOM 4709 OE2 GLU B 309 -33.015 18.418 -11.949 1.00 80.64 O
ATOM 4710 N GLY B 310 -33.109 17.570 -7.125 1.00 84.23 N
ATOM 4711 CA GLY B 310 -34.360 16.870 -6.893 1.00 88.85 C
ATOM 4712 C GLY B 310 -34.556 15.618 -7.734 1.00 92.10 C
ATOM 4713 O GLY B 310 -33.765 15.313 -8.622 1.00 91.07 O
ATOM 4714 N ASN B 311 -35.635 14.899 -7.446 1.00 97.12 N
ATOM 4715 CA ASN B 311 -36.004 13.672 -8.148 1.00102.29 C
ATOM 4716 C ASN B 311 -37.523 13.508 -7.993 1.00106.18 C
ATOM 4717 O ASN B 311 -38.073 13.783 -6.920 1.00107.49 O
ATOM 4718 CB ASN B 311 -35.299 12.452 -7.528 1.00102.14 C
ATOM 4719 CG ASN B 311 -33.787 12.453 -7.753 1.00102.71 C
ATOM 4720 OD1 ASN B 311 -33.317 12.390 -8.889 1.00103.04 O
ATOM 4721 ND2 ASN B 311 -33.022 12.519 -6.665 1.00102.31 N
ATOM 4722 N HIS B 312 -38.196 13.079 -9.061 1.00109.68 N
ATOM 4723 CA HIS B 312 -39.647 12.869 -9.030 1.00112.52 C
ATOM 4724 C HIS B 312 -40.027 11.699 -9.942 1.00113.52 C
ATOM 4725 O HIS B 312 -39.640 11.665 -11.116 1.00113.20 O
ATOM 4726 CB HIS B 312 -40.390 14.141 -9.472 1.00114.32 C
ATOM 4727 CG HIS B 312 -40.261 14.445 -10.937 1.00117.06 C
ATOM 4728 ND1 HIS B 312 -39.111 14.957 -11.493 1.00118.23 N
ATOM 4729 CD2 HIS B 312 -41.133 14.268 -11.960 1.00118.21 C
ATOM 4730 CE1 HIS B 312 -39.276 15.082 -12.802 1.00118.99 C
ATOM 4731 NE2 HIS B 312 -40.492 14.671 -13.108 1.00119.29 N
ATOM 4732 N LYS B 313 -40.774 10.739 -9.403 1.00114.77 N
ATOM 4733 CA LYS B 313 -41.193 9.572 -10.179 1.00116.23 C
ATOM 4734 C LYS B 313 -41.850 10.039 -11.476 1.00117.88 C
ATOM 4735 O LYS B 313 -42.826 10.791 -11.449 1.00118.20 O
ATOM 4736 CB LYS B 313 -42.173 8.728 -9.364 1.00115.55 C
ATOM 4737 CG LYS B 313 -41.627 8.267 -8.019 1.00114.52 C
ATOM 4738 CD LYS B 313 -42.718 7.583 -7.203 1.00113.62 C
ATOM 4739 CE LYS B 313 -42.253 7.217 -5.802 1.00111.93 C
ATOM 4740 NZ LYS B 313 -43.366 6.624 -5.003 1.00109.72 N
ATOM 4741 N PRO B 314 -41.313 9.606 -12.632 1.00119.02 N
ATOM 4742 CA PRO B 314 -41.856 9.993 -13.937 1.00119.57 C
ATOM 4743 C PRO B 314 -43.266 9.474 -14.194 1.00120.29 C
ATOM 4744 O PRO B 314 -43.763 8.587 -13.488 1.00119.94 O
ATOM 4745 CB PRO B 314 -40.852 9.399 -14.924 1.00119.10 C
ATOM 4746 CG PRO B 314 -39.584 9.357 -14.141 1.00119.32 C
ATOM 4747 CD PRO B 314 -40.064 8.846 -12.805 1.00119.29 C
ATOM 4748 N GLU B 315 -43.895 10.044 -15.217 1.00120.71 N
ATOM 4749 CA GLU B 315 -45.241 9.669 -15.630 1.00120.73 C
ATOM 4750 C GLU B 315 -46.317 9.933 -14.585 1.00119.42 C
ATOM 4751 O GLU B 315 -47.470 9.532 -14.757 1.00119.59 O
ATOM 4752 CB GLU B 315 -45.266 8.195 -16.046 1.00122.78 C
ATOM 4753 CG GLU B 315 -44.544 7.925 -17.364 1.00124.50 C
ATOM 4754 CD GLU B 315 -44.439 6.448 -17.690 1.00125.58 C
ATOM 4755 OE1 GLU B 315 -43.965 6.127 -18.799 1.00125.94 O
ATOM 4756 OE2 GLU B 315 -44.821 5.613 -16.840 1.00126.86 O
ATOM 4757 N THR B 316 -45.940 10.598 -13.500 1.00117.54 N
ATOM 4758 CA THR B 316 -46.907 10.923 -12.462 1.00115.78 C
ATOM 4759 C THR B 316 -47.093 12.429 -12.497 1.00113.97 C
ATOM 4760 O THR B 316 -46.118 13.178 -12.557 1.00113.84 O
ATOM 4761 CB THR B 316 -46.422 10.493 -11.046 1.00116.09 C
ATOM 4762 OG1 THR B 316 -46.225 9.073 -11.018 1.00116.18 O
ATOM 4763 CG2 THR B 316 -47.459 10.873 -9.980 1.00115.05 C
ATOM 4764 N ASP B 317 -48.352 12.860 -12.499 1.00111.82 N
ATOM 4765 CA ASP B 317 -48.691 14.278 -12.513 1.00109.43 C
ATOM 4766 C ASP B 317 -48.867 14.700 -11.054 1.00109.27 C
ATOM 4767 O ASP B 317 -49.880 14.384 -10.414 1.00109.58 O
ATOM 4768 CB ASP B 317 -49.979 14.506 -13.327 1.00106.72 C
ATOM 4769 CG ASP B 317 -50.421 15.968 -13.363 1.00104.53 C
ATOM 4770 OD1 ASP B 317 -49.615 16.849 -13.731 1.00103.22 O
ATOM 4771 OD2 ASP B 317 -51.593 16.239 -13.032 1.00102.42 O
ATOM 4772 N TYR B 318 -47.849 15.387 -10.529 1.00108.87 N
ATOM 4773 CA TYR B 318 -47.841 15.871 -9.150 1.00108.47 C
ATOM 4774 C TYR B 318 -48.716 17.110 -9.028 1.00109.21 C
ATOM 4775 O TYR B 318 -48.716 17.781 -8.004 1.00108.22 O
ATOM 4776 CB TYR B 318 -46.408 16.201 -8.711 1.00107.18 C
ATOM 4777 CG TYR B 318 -45.524 15.004 -8.369 1.00105.92 C
ATOM 4778 CD1 TYR B 318 -45.699 14.291 -7.172 1.00104.92 C
ATOM 4779 CD2 TYR B 318 -44.490 14.605 -9.222 1.00104.89 C
ATOM 4780 CE1 TYR B 318 -44.859 13.211 -6.836 1.00103.58 C
ATOM 4781 CE2 TYR B 318 -43.646 13.527 -8.895 1.00104.05 C
ATOM 4782 CZ TYR B 318 -43.837 12.839 -7.703 1.00103.64 C
ATOM 4783 OH TYR B 318 -43.007 11.785 -7.389 1.00102.85 O
ATOM 4784 N LEU B 319 -49.457 17.401 -10.092 1.00111.27 N
ATOM 4785 CA LEU B 319 -50.373 18.542 -10.145 1.00112.79 C
ATOM 4786 C LEU B 319 -51.834 18.080 -9.974 1.00113.76 C
ATOM 4787 O LEU B 319 -52.480 18.493 -8.978 1.00114.70 O
ATOM 4788 CB LEU B 319 -50.231 19.278 -11.488 1.00111.81 C
ATOM 4789 CG LEU B 319 -49.017 20.186 -11.675 1.00110.60 C
ATOM 4790 CD1 LEU B 319 -48.973 20.709 -13.104 1.00109.61 C
ATOM 4791 CD2 LEU B 319 -49.104 21.336 -10.679 1.00109.90 C
TER 4792 LEU B 319
ATOM 4793 N LYS C 6 -29.204 57.250 -3.818 1.00 99.08 N
ATOM 4794 CA LYS C 6 -30.445 56.415 -3.730 1.00 99.00 C
ATOM 4795 C LYS C 6 -30.956 56.282 -2.282 1.00 98.40 C
ATOM 4796 O LYS C 6 -30.220 56.533 -1.319 1.00 97.61 O
ATOM 4797 CB LYS C 6 -30.170 55.034 -4.340 1.00 99.66 C
ATOM 4798 CG LYS C 6 -30.959 54.727 -5.617 1.00 99.85 C
ATOM 4799 CD LYS C 6 -32.365 54.205 -5.292 1.00100.73 C
ATOM 4800 CE LYS C 6 -33.149 53.798 -6.542 1.00101.23 C
ATOM 4801 NZ LYS C 6 -34.437 53.110 -6.207 1.00100.75 N
ATOM 4802 N PRO C 7 -32.237 55.897 -2.117 1.00 97.80 N
ATOM 4803 CA PRO C 7 -32.835 55.741 -0.791 1.00 97.15 C
ATOM 4804 C PRO C 7 -33.133 54.299 -0.425 1.00 96.32 C
ATOM 4805 O PRO C 7 -33.459 53.485 -1.286 1.00 96.22 O
ATOM 4806 CB PRO C 7 -34.113 56.540 -0.920 1.00 97.20 C
ATOM 4807 CG PRO C 7 -34.574 56.093 -2.283 1.00 97.43 C
ATOM 4808 CD PRO C 7 -33.302 56.009 -3.131 1.00 97.47 C
ATOM 4809 N ILE C 8 -33.050 54.009 0.868 1.00 95.57 N
ATOM 4810 CA ILE C 8 -33.310 52.673 1.385 1.00 94.69 C
ATOM 4811 C ILE C 8 -34.324 52.737 2.505 1.00 94.01 C
ATOM 4812 O ILE C 8 -34.175 53.553 3.420 1.00 93.77 O
ATOM 4813 CB ILE C 8 -32.031 52.021 2.005 1.00 94.64 C
ATOM 4814 CG1 ILE C 8 -30.940 51.836 0.950 1.00 93.94 C
ATOM 4815 CG2 ILE C 8 -32.381 50.679 2.641 1.00 93.66 C
ATOM 4816 CD1 ILE C 8 -31.379 51.008 -0.217 1.00 94.03 C
ATOM 4817 N GLU C 9 -35.362 51.909 2.431 1.00 92.63 N
ATOM 4818 CA GLU C 9 -36.302 51.866 3.540 1.00 91.96 C
ATOM 4819 C GLU C 9 -36.350 50.415 3.994 1.00 91.79 C
ATOM 4820 O GLU C 9 -36.505 49.501 3.174 1.00 91.03 O
ATOM 4821 CB GLU C 9 -37.716 52.334 3.183 1.00 91.63 C
ATOM 4822 CG GLU C 9 -38.477 52.756 4.462 1.00 91.26 C
ATOM 4823 CD GLU C 9 -39.993 52.641 4.389 1.00 91.17 C
ATOM 4824 OE1 GLU C 9 -40.655 52.979 5.396 1.00 89.98 O
ATOM 4825 OE2 GLU C 9 -40.521 52.214 3.345 1.00 91.53 O
ATOM 4826 N ILE C 10 -36.188 50.210 5.298 1.00 91.97 N
ATOM 4827 CA ILE C 10 -36.192 48.870 5.873 1.00 92.34 C
ATOM 4828 C ILE C 10 -37.536 48.536 6.500 1.00 91.65 C
ATOM 4829 O ILE C 10 -38.085 49.328 7.264 1.00 91.67 O
ATOM 4830 CB ILE C 10 -35.103 48.726 6.961 1.00 93.05 C
ATOM 4831 CG1 ILE C 10 -33.729 48.971 6.333 1.00 93.78 C
ATOM 4832 CG2 ILE C 10 -35.192 47.338 7.618 1.00 91.79 C
ATOM 4833 CD1 ILE C 10 -32.569 48.945 7.309 1.00 92.99 C
ATOM 4834 N ILE C 11 -38.057 47.357 6.175 1.00 90.86 N
ATOM 4835 CA ILE C 11 -39.333 46.895 6.708 1.00 89.22 C
ATOM 4836 C ILE C 11 -39.066 45.637 7.517 1.00 88.75 C
ATOM 4837 O ILE C 11 -38.363 44.739 7.063 1.00 87.87 O
ATOM 4838 CB ILE C 11 -40.339 46.526 5.586 1.00 88.97 C
ATOM 4839 CG1 ILE C 11 -40.485 47.688 4.610 1.00 87.62 C
ATOM 4840 CG2 ILE C 11 -41.685 46.162 6.187 1.00 88.11 C
ATOM 4841 CD1 ILE C 11 -40.961 48.954 5.242 1.00 88.39 C
ATOM 4842 N GLY C 12 -39.625 45.585 8.718 1.00 88.08 N
ATOM 4843 CA GLY C 12 -39.445 44.417 9.551 1.00 86.84 C
ATOM 4844 C GLY C 12 -40.697 43.578 9.432 1.00 85.81 C
ATOM 4845 O GLY C 12 -41.799 44.093 9.605 1.00 86.11 O
ATOM 4846 N ALA C 13 -40.537 42.292 9.133 1.00 84.95 N
ATOM 4847 CA ALA C 13 -41.677 41.392 8.987 1.00 83.69 C
ATOM 4848 C ALA C 13 -41.699 40.326 10.081 1.00 83.14 C
ATOM 4849 O ALA C 13 -41.903 39.148 9.791 1.00 83.23 O
ATOM 4850 CB ALA C 13 -41.635 40.719 7.598 1.00 82.18 C
ATOM 4851 N PRO C 14 -41.509 40.727 11.352 1.00 82.39 N
ATOM 4852 CA PRO C 14 -41.513 39.757 12.452 1.00 82.40 C
ATOM 4853 C PRO C 14 -42.711 38.820 12.394 1.00 83.87 C
ATOM 4854 O PRO C 14 -43.726 39.068 13.032 1.00 84.25 O
ATOM 4855 CB PRO C 14 -41.533 40.645 13.684 1.00 81.00 C
ATOM 4856 CG PRO C 14 -42.274 41.856 13.207 1.00 80.99 C
ATOM 4857 CD PRO C 14 -41.629 42.095 11.880 1.00 81.10 C
ATOM 4858 N PHE C 15 -42.580 37.737 11.634 1.00 86.12 N
ATOM 4859 CA PHE C 15 -43.659 36.765 11.467 1.00 87.98 C
ATOM 4860 C PHE C 15 -43.106 35.344 11.582 1.00 88.21 C
ATOM 4861 O PHE C 15 -41.887 35.152 11.580 1.00 88.51 O
ATOM 4862 CB PHE C 15 -44.314 36.969 10.099 1.00 88.79 C
ATOM 4863 CG PHE C 15 -45.600 36.228 9.923 1.00 91.15 C
ATOM 4864 CD1 PHE C 15 -46.602 36.313 10.886 1.00 92.70 C
ATOM 4865 CD2 PHE C 15 -45.829 35.470 8.778 1.00 91.85 C
ATOM 4866 CE1 PHE C 15 -47.822 35.661 10.707 1.00 93.41 C
ATOM 4867 CE2 PHE C 15 -47.044 34.815 8.586 1.00 93.06 C
ATOM 4868 CZ PHE C 15 -48.043 34.907 9.552 1.00 93.27 C
ATOM 4869 N SER C 16 -43.979 34.345 11.677 1.00 87.82 N
ATOM 4870 CA SER C 16 -43.483 32.980 11.794 1.00 88.48 C
ATOM 4871 C SER C 16 -44.497 31.867 11.547 1.00 90.22 C
ATOM 4872 O SER C 16 -44.130 30.696 11.524 1.00 90.56 O
ATOM 4873 CB SER C 16 -42.854 32.776 13.175 1.00 86.82 C
ATOM 4874 OG SER C 16 -43.817 32.824 14.203 1.00 83.07 O
ATOM 4875 N LYS C 17 -45.762 32.215 11.364 1.00 92.02 N
ATOM 4876 CA LYS C 17 -46.787 31.198 11.144 1.00 93.42 C
ATOM 4877 C LYS C 17 -46.581 30.415 9.845 1.00 93.24 C
ATOM 4878 O LYS C 17 -47.211 29.375 9.617 1.00 92.98 O
ATOM 4879 CB LYS C 17 -48.180 31.844 11.170 1.00 95.56 C
ATOM 4880 CG LYS C 17 -49.031 31.528 12.419 1.00 96.54 C
ATOM 4881 CD LYS C 17 -48.271 31.767 13.720 1.00 97.30 C
ATOM 4882 CE LYS C 17 -49.218 31.846 14.909 1.00 97.15 C
ATOM 4883 NZ LYS C 17 -50.065 33.071 14.832 1.00 96.57 N
ATOM 4884 N GLY C 18 -45.696 30.907 8.990 1.00 92.44 N
ATOM 4885 CA GLY C 18 -45.441 30.198 7.753 1.00 92.27 C
ATOM 4886 C GLY C 18 -44.878 28.817 8.057 1.00 92.53 C
ATOM 4887 O GLY C 18 -44.874 27.943 7.189 1.00 92.29 O
ATOM 4888 N GLN C 19 -44.409 28.626 9.294 1.00 92.65 N
ATOM 4889 CA GLN C 19 -43.823 27.363 9.746 1.00 92.73 C
ATOM 4890 C GLN C 19 -43.897 27.207 11.273 1.00 94.03 C
ATOM 4891 O GLN C 19 -44.154 28.174 11.991 1.00 93.82 O
ATOM 4892 CB GLN C 19 -42.370 27.260 9.269 1.00 92.02 C
ATOM 4893 CG GLN C 19 -41.485 28.454 9.601 1.00 91.29 C
ATOM 4894 CD GLN C 19 -41.120 28.518 11.064 1.00 91.08 C
ATOM 4895 OE1 GLN C 19 -40.713 27.517 11.645 1.00 91.96 O
ATOM 4896 NE2 GLN C 19 -41.254 29.694 11.669 1.00 89.85 N
ATOM 4897 N PRO C 20 -43.653 25.983 11.784 1.00 95.05 N
ATOM 4898 CA PRO C 20 -43.680 25.597 13.205 1.00 95.93 C
ATOM 4899 C PRO C 20 -42.673 26.207 14.192 1.00 96.49 C
ATOM 4900 O PRO C 20 -43.066 26.814 15.194 1.00 97.00 O
ATOM 4901 CB PRO C 20 -43.558 24.076 13.141 1.00 95.49 C
ATOM 4902 CG PRO C 20 -42.680 23.880 11.967 1.00 95.38 C
ATOM 4903 CD PRO C 20 -43.283 24.823 10.953 1.00 94.96 C
ATOM 4904 N ARG C 21 -41.384 26.018 13.923 1.00 96.79 N
ATOM 4905 CA ARG C 21 -40.318 26.530 14.790 1.00 96.91 C
ATOM 4906 C ARG C 21 -40.454 28.033 15.074 1.00 94.86 C
ATOM 4907 O ARG C 21 -40.465 28.858 14.153 1.00 94.86 O
ATOM 4908 CB ARG C 21 -38.950 26.247 14.154 1.00 99.34 C
ATOM 4909 CG ARG C 21 -38.919 25.005 13.273 1.00102.34 C
ATOM 4910 CD ARG C 21 -37.559 24.838 12.618 1.00106.42 C
ATOM 4911 NE ARG C 21 -36.567 24.325 13.554 1.00109.60 N
ATOM 4912 CZ ARG C 21 -36.564 23.081 14.020 1.00111.63 C
ATOM 4913 NH1 ARG C 21 -37.498 22.223 13.632 1.00112.45 N
ATOM 4914 NH2 ARG C 21 -35.626 22.696 14.875 1.00112.44 N
ATOM 4915 N GLY C 22 -40.536 28.383 16.354 1.00 92.20 N
ATOM 4916 CA GLY C 22 -40.687 29.779 16.724 1.00 89.96 C
ATOM 4917 C GLY C 22 -39.409 30.560 16.968 1.00 88.10 C
ATOM 4918 O GLY C 22 -38.427 30.025 17.475 1.00 87.82 O
ATOM 4919 N GLY C 23 -39.433 31.840 16.615 1.00 86.64 N
ATOM 4920 CA GLY C 23 -38.270 32.681 16.807 1.00 85.01 C
ATOM 4921 C GLY C 23 -38.036 33.573 15.607 1.00 84.30 C
ATOM 4922 O GLY C 23 -37.631 34.727 15.750 1.00 84.52 O
ATOM 4923 N VAL C 24 -38.305 33.042 14.418 1.00 83.77 N
ATOM 4924 CA VAL C 24 -38.112 33.786 13.174 1.00 83.44 C
ATOM 4925 C VAL C 24 -38.639 35.226 13.160 1.00 84.55 C
ATOM 4926 O VAL C 24 -38.148 36.061 12.392 1.00 83.80 O
ATOM 4927 CB VAL C 24 -38.704 33.004 11.971 1.00 82.02 C
ATOM 4928 CG1 VAL C 24 -37.617 32.162 11.323 1.00 82.66 C
ATOM 4929 CG2 VAL C 24 -39.822 32.103 12.436 1.00 80.13 C
ATOM 4930 N GLU C 25 -39.634 35.521 13.997 1.00 85.75 N
ATOM 4931 CA GLU C 25 -40.173 36.877 14.043 1.00 86.17 C
ATOM 4932 C GLU C 25 -39.187 37.751 14.809 1.00 85.93 C
ATOM 4933 O GLU C 25 -39.204 38.985 14.696 1.00 86.45 O
ATOM 4934 CB GLU C 25 -41.552 36.919 14.713 1.00 86.78 C
ATOM 4935 CG GLU C 25 -41.566 36.765 16.223 1.00 88.34 C
ATOM 4936 CD GLU C 25 -41.282 35.350 16.673 1.00 90.53 C
ATOM 4937 OE1 GLU C 25 -41.474 34.413 15.860 1.00 91.06 O
ATOM 4938 OE2 GLU C 25 -40.888 35.174 17.848 1.00 91.16 O
ATOM 4939 N LYS C 26 -38.324 37.103 15.590 1.00 84.12 N
ATOM 4940 CA LYS C 26 -37.306 37.821 16.337 1.00 82.19 C
ATOM 4941 C LYS C 26 -36.212 38.198 15.341 1.00 80.51 C
ATOM 4942 O LYS C 26 -35.246 38.872 15.690 1.00 80.34 O
ATOM 4943 CB LYS C 26 -36.728 36.939 17.438 1.00 82.12 C
ATOM 4944 CG LYS C 26 -37.712 36.604 18.537 1.00 84.38 C
ATOM 4945 CD LYS C 26 -37.051 35.753 19.629 1.00 86.61 C
ATOM 4946 CE LYS C 26 -38.022 35.440 20.774 1.00 86.85 C
ATOM 4947 NZ LYS C 26 -37.428 34.592 21.858 1.00 86.67 N
ATOM 4948 N GLY C 27 -36.386 37.755 14.098 1.00 78.69 N
ATOM 4949 CA GLY C 27 -35.424 38.039 13.048 1.00 76.08 C
ATOM 4950 C GLY C 27 -35.016 39.496 12.972 1.00 74.71 C
ATOM 4951 O GLY C 27 -33.871 39.830 13.287 1.00 74.43 O
ATOM 4952 N PRO C 28 -35.923 40.395 12.544 1.00 74.00 N
ATOM 4953 CA PRO C 28 -35.602 41.824 12.444 1.00 74.28 C
ATOM 4954 C PRO C 28 -35.151 42.419 13.777 1.00 75.07 C
ATOM 4955 O PRO C 28 -34.476 43.448 13.828 1.00 74.60 O
ATOM 4956 CB PRO C 28 -36.909 42.429 11.938 1.00 73.18 C
ATOM 4957 CG PRO C 28 -37.460 41.340 11.073 1.00 71.70 C
ATOM 4958 CD PRO C 28 -37.236 40.114 11.936 1.00 72.82 C
ATOM 4959 N ALA C 29 -35.524 41.750 14.858 1.00 77.64 N
ATOM 4960 CA ALA C 29 -35.168 42.191 16.199 1.00 79.22 C
ATOM 4961 C ALA C 29 -33.675 42.019 16.456 1.00 79.71 C
ATOM 4962 O ALA C 29 -33.050 42.857 17.118 1.00 81.37 O
ATOM 4963 CB ALA C 29 -35.976 41.408 17.239 1.00 79.86 C
ATOM 4964 N ALA C 30 -33.110 40.934 15.933 1.00 78.80 N
ATOM 4965 CA ALA C 30 -31.689 40.661 16.112 1.00 78.62 C
ATOM 4966 C ALA C 30 -30.878 41.438 15.084 1.00 78.68 C
ATOM 4967 O ALA C 30 -29.809 41.980 15.387 1.00 78.63 O
ATOM 4968 CB ALA C 30 -31.421 39.169 15.969 1.00 78.52 C
ATOM 4969 N LEU C 31 -31.402 41.501 13.867 1.00 78.19 N
ATOM 4970 CA LEU C 31 -30.721 42.199 12.787 1.00 77.40 C
ATOM 4971 C LEU C 31 -30.490 43.667 13.095 1.00 77.67 C
ATOM 4972 O LEU C 31 -29.412 44.187 12.836 1.00 77.84 O
ATOM 4973 CB LEU C 31 -31.506 42.041 11.480 1.00 75.60 C
ATOM 4974 CG LEU C 31 -31.285 40.704 10.765 1.00 73.01 C
ATOM 4975 CD1 LEU C 31 -32.554 40.231 10.122 1.00 70.89 C
ATOM 4976 CD2 LEU C 31 -30.189 40.871 9.742 1.00 71.89 C
ATOM 4977 N ARG C 32 -31.490 44.348 13.640 1.00 78.94 N
ATOM 4978 CA ARG C 32 -31.301 45.757 13.959 1.00 80.72 C
ATOM 4979 C ARG C 32 -30.293 45.853 15.090 1.00 81.47 C
ATOM 4980 O ARG C 32 -29.445 46.738 15.095 1.00 80.36 O
ATOM 4981 CB ARG C 32 -32.614 46.424 14.392 1.00 82.03 C
ATOM 4982 CG ARG C 32 -33.564 46.824 13.264 1.00 82.49 C
ATOM 4983 CD ARG C 32 -34.584 47.865 13.753 1.00 84.29 C
ATOM 4984 NE ARG C 32 -35.688 48.077 12.818 1.00 85.70 N
ATOM 4985 CZ ARG C 32 -36.617 47.164 12.537 1.00 86.70 C
ATOM 4986 NH1 ARG C 32 -36.578 45.974 13.123 1.00 87.41 N
ATOM 4987 NH2 ARG C 32 -37.585 47.436 11.670 1.00 86.01 N
ATOM 4988 N LYS C 33 -30.411 44.930 16.045 1.00 82.85 N
ATOM 4989 CA LYS C 33 -29.528 44.867 17.200 1.00 84.50 C
ATOM 4990 C LYS C 33 -28.087 44.636 16.749 1.00 85.48 C
ATOM 4991 O LYS C 33 -27.140 45.000 17.446 1.00 85.93 O
ATOM 4992 CB LYS C 33 -29.973 43.744 18.140 1.00 85.61 C
ATOM 4993 CG LYS C 33 -28.944 43.369 19.198 1.00 88.84 C
ATOM 4994 CD LYS C 33 -28.673 44.502 20.194 1.00 91.56 C
ATOM 4995 CE LYS C 33 -29.611 44.438 21.403 1.00 93.10 C
ATOM 4996 NZ LYS C 33 -29.512 43.133 22.144 1.00 93.72 N
ATOM 4997 N ALA C 34 -27.917 44.022 15.584 1.00 86.44 N
ATOM 4998 CA ALA C 34 -26.575 43.788 15.058 1.00 86.60 C
ATOM 4999 C ALA C 34 -26.145 45.081 14.355 1.00 86.88 C
ATOM 5000 O ALA C 34 -25.141 45.129 13.640 1.00 85.52 O
ATOM 5001 CB ALA C 34 -26.589 42.618 14.081 1.00 87.03 C
ATOM 5002 N GLY C 35 -26.945 46.123 14.565 1.00 88.26 N
ATOM 5003 CA GLY C 35 -26.674 47.430 13.995 1.00 89.33 C
ATOM 5004 C GLY C 35 -26.861 47.548 12.502 1.00 89.25 C
ATOM 5005 O GLY C 35 -26.258 48.413 11.868 1.00 89.47 O
ATOM 5006 N LEU C 36 -27.702 46.699 11.932 1.00 89.38 N
ATOM 5007 CA LEU C 36 -27.916 46.741 10.493 1.00 90.16 C
ATOM 5008 C LEU C 36 -28.264 48.133 9.964 1.00 90.88 C
ATOM 5009 O LEU C 36 -27.765 48.553 8.915 1.00 90.76 O
ATOM 5010 CB LEU C 36 -29.000 45.733 10.088 1.00 89.73 C
ATOM 5011 CG LEU C 36 -29.374 45.630 8.603 1.00 89.10 C
ATOM 5012 CD1 LEU C 36 -28.141 45.709 7.716 1.00 89.09 C
ATOM 5013 CD2 LEU C 36 -30.113 44.322 8.381 1.00 88.91 C
ATOM 5014 N VAL C 37 -29.098 48.864 10.693 1.00 91.52 N
ATOM 5015 CA VAL C 37 -29.495 50.189 10.234 1.00 92.05 C
ATOM 5016 C VAL C 37 -28.308 51.143 10.026 1.00 93.18 C
ATOM 5017 O VAL C 37 -28.058 51.600 8.906 1.00 93.84 O
ATOM 5018 CB VAL C 37 -30.500 50.831 11.205 1.00 90.22 C
ATOM 5019 CG1 VAL C 37 -31.328 51.861 10.467 1.00 88.34 C
ATOM 5020 CG2 VAL C 37 -31.386 49.764 11.819 1.00 89.51 C
ATOM 5021 N GLU C 38 -27.577 51.429 11.102 1.00 93.67 N
ATOM 5022 CA GLU C 38 -26.427 52.337 11.052 1.00 93.22 C
ATOM 5023 C GLU C 38 -25.405 51.996 9.966 1.00 91.50 C
ATOM 5024 O GLU C 38 -25.059 52.847 9.142 1.00 89.54 O
ATOM 5025 CB GLU C 38 -25.719 52.370 12.418 1.00 95.27 C
ATOM 5026 CG GLU C 38 -26.632 52.699 13.599 1.00 97.90 C
ATOM 5027 CD GLU C 38 -27.433 51.499 14.082 1.00 98.72 C
ATOM 5028 OE1 GLU C 38 -26.881 50.674 14.844 1.00 98.61 O
ATOM 5029 OE2 GLU C 38 -28.611 51.376 13.691 1.00100.35 O
ATOM 5030 N LYS C 39 -24.917 50.758 9.970 1.00 89.99 N
ATOM 5031 CA LYS C 39 -23.932 50.351 8.981 1.00 89.24 C
ATOM 5032 C LYS C 39 -24.451 50.703 7.604 1.00 89.66 C
ATOM 5033 O LYS C 39 -23.711 51.211 6.760 1.00 90.45 O
ATOM 5034 CB LYS C 39 -23.668 48.855 9.061 1.00 87.39 C
ATOM 5035 CG LYS C 39 -23.102 48.411 10.375 1.00 86.93 C
ATOM 5036 CD LYS C 39 -22.894 46.918 10.378 1.00 87.74 C
ATOM 5037 CE LYS C 39 -22.446 46.443 11.744 1.00 88.21 C
ATOM 5038 NZ LYS C 39 -21.158 47.076 12.116 1.00 89.64 N
ATOM 5039 N LEU C 40 -25.734 50.445 7.378 1.00 89.66 N
ATOM 5040 CA LEU C 40 -26.328 50.753 6.086 1.00 89.32 C
ATOM 5041 C LEU C 40 -26.164 52.239 5.794 1.00 90.45 C
ATOM 5042 O LEU C 40 -25.829 52.626 4.675 1.00 89.95 O
ATOM 5043 CB LEU C 40 -27.809 50.345 6.060 1.00 85.82 C
ATOM 5044 CG LEU C 40 -28.095 48.940 5.506 1.00 82.28 C
ATOM 5045 CD1 LEU C 40 -29.515 48.544 5.817 1.00 82.14 C
ATOM 5046 CD2 LEU C 40 -27.855 48.919 4.012 1.00 80.23 C
ATOM 5047 N LYS C 41 -26.373 53.071 6.810 1.00 92.70 N
ATOM 5048 CA LYS C 41 -26.246 54.515 6.639 1.00 95.26 C
ATOM 5049 C LYS C 41 -24.840 54.875 6.171 1.00 96.02 C
ATOM 5050 O LYS C 41 -24.647 55.841 5.430 1.00 96.02 O
ATOM 5051 CB LYS C 41 -26.567 55.237 7.950 1.00 95.44 C
ATOM 5052 CG LYS C 41 -28.009 55.054 8.416 1.00 97.67 C
ATOM 5053 CD LYS C 41 -28.196 55.519 9.857 1.00 98.54 C
ATOM 5054 CE LYS C 41 -29.551 55.101 10.412 1.00 97.92 C
ATOM 5055 NZ LYS C 41 -29.674 55.419 11.862 1.00 96.37 N
ATOM 5056 N GLU C 42 -23.865 54.082 6.594 1.00 97.23 N
ATOM 5057 CA GLU C 42 -22.478 54.310 6.225 1.00 99.27 C
ATOM 5058 C GLU C 42 -22.217 54.251 4.726 1.00100.29 C
ATOM 5059 O GLU C 42 -21.103 54.515 4.276 1.00 99.46 O
ATOM 5060 CB GLU C 42 -21.587 53.296 6.921 1.00100.72 C
ATOM 5061 CG GLU C 42 -21.350 53.579 8.379 1.00104.56 C
ATOM 5062 CD GLU C 42 -20.521 52.489 9.035 1.00107.81 C
ATOM 5063 OE1 GLU C 42 -19.633 51.929 8.347 1.00108.24 O
ATOM 5064 OE2 GLU C 42 -20.750 52.204 10.234 1.00110.21 O
ATOM 5065 N THR C 43 -23.228 53.892 3.948 1.00102.51 N
ATOM 5066 CA THR C 43 -23.047 53.816 2.503 1.00104.86 C
ATOM 5067 C THR C 43 -23.457 55.117 1.823 1.00106.85 C
ATOM 5068 O THR C 43 -23.637 56.154 2.478 1.00107.03 O
ATOM 5069 CB THR C 43 -23.875 52.668 1.877 1.00104.47 C
ATOM 5070 OG1 THR C 43 -25.263 52.851 2.191 1.00104.26 O
ATOM 5071 CG2 THR C 43 -23.405 51.324 2.403 1.00103.94 C
ATOM 5072 N GLU C 44 -23.590 55.045 0.500 1.00108.54 N
ATOM 5073 CA GLU C 44 -23.994 56.183 -0.321 1.00109.37 C
ATOM 5074 C GLU C 44 -25.529 56.255 -0.411 1.00109.21 C
ATOM 5075 O GLU C 44 -26.089 57.103 -1.116 1.00109.70 O
ATOM 5076 CB GLU C 44 -23.380 56.048 -1.720 1.00109.72 C
ATOM 5077 CG GLU C 44 -23.313 54.609 -2.221 1.00111.43 C
ATOM 5078 CD GLU C 44 -22.909 54.510 -3.685 1.00112.66 C
ATOM 5079 OE1 GLU C 44 -21.923 55.172 -4.078 1.00113.58 O
ATOM 5080 OE2 GLU C 44 -23.575 53.764 -4.441 1.00112.10 O
ATOM 5081 N TYR C 45 -26.196 55.361 0.318 1.00108.44 N
ATOM 5082 CA TYR C 45 -27.655 55.291 0.345 1.00107.04 C
ATOM 5083 C TYR C 45 -28.233 55.920 1.616 1.00106.43 C
ATOM 5084 O TYR C 45 -27.638 55.825 2.697 1.00106.41 O
ATOM 5085 CB TYR C 45 -28.121 53.834 0.279 1.00106.81 C
ATOM 5086 CG TYR C 45 -27.819 53.099 -1.009 1.00106.18 C
ATOM 5087 CD1 TYR C 45 -26.509 52.809 -1.390 1.00106.02 C
ATOM 5088 CD2 TYR C 45 -28.851 52.669 -1.835 1.00106.09 C
ATOM 5089 CE1 TYR C 45 -26.243 52.102 -2.571 1.00106.12 C
ATOM 5090 CE2 TYR C 45 -28.599 51.968 -3.011 1.00105.75 C
ATOM 5091 CZ TYR C 45 -27.298 51.686 -3.374 1.00105.62 C
ATOM 5092 OH TYR C 45 -27.062 50.997 -4.543 1.00104.68 O
ATOM 5093 N ASN C 46 -29.390 56.562 1.478 1.00105.11 N
ATOM 5094 CA ASN C 46 -30.064 57.168 2.619 1.00103.37 C
ATOM 5095 C ASN C 46 -30.955 56.060 3.129 1.00101.06 C
ATOM 5096 O ASN C 46 -31.628 55.393 2.343 1.00 99.33 O
ATOM 5097 CB ASN C 46 -30.921 58.358 2.191 1.00106.07 C
ATOM 5098 CG ASN C 46 -30.118 59.433 1.497 1.00108.03 C
ATOM 5099 OD1 ASN C 46 -29.105 59.903 2.020 1.00109.57 O
ATOM 5100 ND2 ASN C 46 -30.569 59.834 0.311 1.00108.96 N
ATOM 5101 N VAL C 47 -30.979 55.864 4.438 1.00 99.24 N
ATOM 5102 CA VAL C 47 -31.779 54.782 4.982 1.00 98.07 C
ATOM 5103 C VAL C 47 -32.871 55.231 5.939 1.00 96.62 C
ATOM 5104 O VAL C 47 -32.633 56.043 6.830 1.00 96.63 O
ATOM 5105 CB VAL C 47 -30.879 53.752 5.715 1.00 98.47 C
ATOM 5106 CG1 VAL C 47 -31.594 52.413 5.820 1.00 97.35 C
ATOM 5107 CG2 VAL C 47 -29.555 53.598 4.981 1.00 98.39 C
ATOM 5108 N ARG C 48 -34.069 54.691 5.741 1.00 94.83 N
ATOM 5109 CA ARG C 48 -35.197 54.995 6.597 1.00 93.46 C
ATOM 5110 C ARG C 48 -35.712 53.675 7.131 1.00 92.09 C
ATOM 5111 O ARG C 48 -36.036 52.774 6.359 1.00 90.53 O
ATOM 5112 CB ARG C 48 -36.303 55.706 5.811 1.00 95.23 C
ATOM 5113 CG ARG C 48 -37.579 55.970 6.622 1.00 96.76 C
ATOM 5114 CD ARG C 48 -38.686 56.572 5.758 1.00 98.94 C
ATOM 5115 NE ARG C 48 -40.004 55.967 6.003 1.00102.01 N
ATOM 5116 CZ ARG C 48 -40.792 56.229 7.048 1.00102.83 C
ATOM 5117 NH1 ARG C 48 -40.412 57.099 7.978 1.00103.67 N
ATOM 5118 NH2 ARG C 48 -41.967 55.617 7.159 1.00103.04 N
ATOM 5119 N ASP C 49 -35.753 53.557 8.456 1.00 91.94 N
ATOM 5120 CA ASP C 49 -36.243 52.348 9.101 1.00 92.13 C
ATOM 5121 C ASP C 49 -37.738 52.573 9.307 1.00 92.71 C
ATOM 5122 O ASP C 49 -38.146 53.543 9.946 1.00 93.23 O
ATOM 5123 CB ASP C 49 -35.541 52.140 10.447 1.00 92.41 C
ATOM 5124 CG ASP C 49 -35.781 50.752 11.026 1.00 93.21 C
ATOM 5125 OD1 ASP C 49 -36.952 50.408 11.301 1.00 93.93 O
ATOM 5126 OD2 ASP C 49 -34.801 49.995 11.209 1.00 94.25 O
ATOM 5127 N HIS C 50 -38.546 51.675 8.748 1.00 93.35 N
ATOM 5128 CA HIS C 50 -40.009 51.746 8.816 1.00 93.56 C
ATOM 5129 C HIS C 50 -40.559 51.064 10.087 1.00 93.08 C
ATOM 5130 O HIS C 50 -41.727 51.236 10.444 1.00 92.89 O
ATOM 5131 CB HIS C 50 -40.568 51.100 7.531 1.00 94.71 C
ATOM 5132 CG HIS C 50 -42.057 51.171 7.372 1.00 95.99 C
ATOM 5133 ND1 HIS C 50 -42.939 50.591 8.266 1.00 97.39 N
ATOM 5134 CD2 HIS C 50 -42.823 51.665 6.368 1.00 95.59 C
ATOM 5135 CE1 HIS C 50 -44.174 50.720 7.819 1.00 96.73 C
ATOM 5136 NE2 HIS C 50 -44.132 51.369 6.666 1.00 96.87 N
ATOM 5137 N GLY C 51 -39.708 50.313 10.778 1.00 92.46 N
ATOM 5138 CA GLY C 51 -40.151 49.639 11.981 1.00 92.91 C
ATOM 5139 C GLY C 51 -40.703 48.266 11.653 1.00 93.76 C
ATOM 5140 O GLY C 51 -40.542 47.777 10.533 1.00 93.36 O
ATOM 5141 N ASP C 52 -41.369 47.646 12.625 1.00 94.72 N
ATOM 5142 CA ASP C 52 -41.937 46.313 12.432 1.00 95.39 C
ATOM 5143 C ASP C 52 -43.436 46.244 12.258 1.00 95.22 C
ATOM 5144 O ASP C 52 -44.188 46.443 13.204 1.00 94.37 O
ATOM 5145 CB ASP C 52 -41.572 45.385 13.590 1.00 96.23 C
ATOM 5146 CG ASP C 52 -40.180 44.838 13.469 1.00 96.65 C
ATOM 5147 OD1 ASP C 52 -39.783 44.494 12.335 1.00 97.76 O
ATOM 5148 OD2 ASP C 52 -39.490 44.744 14.505 1.00 97.38 O
ATOM 5149 N LEU C 53 -43.862 45.928 11.046 1.00 96.11 N
ATOM 5150 CA LEU C 53 -45.276 45.791 10.770 1.00 97.52 C
ATOM 5151 C LEU C 53 -45.888 44.845 11.814 1.00 99.27 C
ATOM 5152 O LEU C 53 -45.693 43.632 11.744 1.00100.25 O
ATOM 5153 CB LEU C 53 -45.489 45.210 9.365 1.00 95.74 C
ATOM 5154 CG LEU C 53 -44.942 45.974 8.158 1.00 94.64 C
ATOM 5155 CD1 LEU C 53 -45.423 45.287 6.893 1.00 93.53 C
ATOM 5156 CD2 LEU C 53 -45.420 47.423 8.182 1.00 94.55 C
ATOM 5157 N ALA C 54 -46.604 45.397 12.791 1.00101.13 N
ATOM 5158 CA ALA C 54 -47.247 44.566 13.804 1.00102.37 C
ATOM 5159 C ALA C 54 -48.339 43.814 13.060 1.00103.74 C
ATOM 5160 O ALA C 54 -49.067 44.397 12.257 1.00102.75 O
ATOM 5161 CB ALA C 54 -47.846 45.434 14.901 1.00101.69 C
ATOM 5162 N PHE C 55 -48.449 42.517 13.309 1.00106.29 N
ATOM 5163 CA PHE C 55 -49.449 41.733 12.607 1.00109.42 C
ATOM 5164 C PHE C 55 -50.578 41.236 13.493 1.00111.23 C
ATOM 5165 O PHE C 55 -50.366 40.429 14.402 1.00111.53 O
ATOM 5166 CB PHE C 55 -48.788 40.550 11.891 1.00110.05 C
ATOM 5167 CG PHE C 55 -47.779 40.956 10.848 1.00109.86 C
ATOM 5168 CD1 PHE C 55 -48.147 41.777 9.783 1.00109.98 C
ATOM 5169 CD2 PHE C 55 -46.460 40.530 10.939 1.00109.37 C
ATOM 5170 CE1 PHE C 55 -47.217 42.167 8.825 1.00109.69 C
ATOM 5171 CE2 PHE C 55 -45.523 40.914 9.988 1.00109.52 C
ATOM 5172 CZ PHE C 55 -45.904 41.736 8.929 1.00109.89 C
ATOM 5173 N VAL C 56 -51.776 41.737 13.207 1.00113.41 N
ATOM 5174 CA VAL C 56 -52.995 41.378 13.925 1.00114.90 C
ATOM 5175 C VAL C 56 -53.239 39.884 13.728 1.00115.83 C
ATOM 5176 O VAL C 56 -53.206 39.394 12.596 1.00115.87 O
ATOM 5177 CB VAL C 56 -54.201 42.171 13.365 1.00115.37 C
ATOM 5178 CG1 VAL C 56 -53.984 43.672 13.569 1.00114.66 C
ATOM 5179 CG2 VAL C 56 -54.380 41.868 11.877 1.00115.29 C
ATOM 5180 N ASP C 57 -53.494 39.159 14.813 1.00116.87 N
ATOM 5181 CA ASP C 57 -53.695 37.721 14.689 1.00118.41 C
ATOM 5182 C ASP C 57 -55.121 37.287 14.369 1.00119.01 C
ATOM 5183 O ASP C 57 -56.076 37.713 15.023 1.00118.81 O
ATOM 5184 CB ASP C 57 -53.209 37.003 15.947 1.00118.79 C
ATOM 5185 CG ASP C 57 -52.573 35.657 15.631 1.00119.33 C
ATOM 5186 OD1 ASP C 57 -53.261 34.799 15.036 1.00118.72 O
ATOM 5187 OD2 ASP C 57 -51.382 35.468 15.969 1.00119.85 O
ATOM 5188 N VAL C 58 -55.239 36.425 13.358 1.00119.62 N
ATOM 5189 CA VAL C 58 -56.523 35.896 12.900 1.00119.95 C
ATOM 5190 C VAL C 58 -57.089 34.832 13.840 1.00120.08 C
ATOM 5191 O VAL C 58 -56.696 33.660 13.787 1.00120.20 O
ATOM 5192 CB VAL C 58 -56.400 35.284 11.480 1.00120.15 C
ATOM 5193 CG1 VAL C 58 -57.711 34.612 11.074 1.00119.13 C
ATOM 5194 CG2 VAL C 58 -56.028 36.372 10.482 1.00120.11 C
ATOM 5195 N PRO C 59 -58.036 35.231 14.707 1.00119.88 N
ATOM 5196 CA PRO C 59 -58.652 34.298 15.654 1.00118.69 C
ATOM 5197 C PRO C 59 -59.267 33.119 14.925 1.00117.26 C
ATOM 5198 O PRO C 59 -59.909 33.279 13.888 1.00116.68 O
ATOM 5199 CB PRO C 59 -59.693 35.162 16.360 1.00119.27 C
ATOM 5200 CG PRO C 59 -60.067 36.172 15.303 1.00119.94 C
ATOM 5201 CD PRO C 59 -58.721 36.537 14.735 1.00119.85 C
ATOM 5202 N ASN C 60 -59.060 31.931 15.473 1.00116.37 N
ATOM 5203 CA ASN C 60 -59.582 30.716 14.871 1.00116.10 C
ATOM 5204 C ASN C 60 -59.229 30.643 13.383 1.00115.83 C
ATOM 5205 O ASN C 60 -60.073 30.878 12.511 1.00115.68 O
ATOM 5206 CB ASN C 60 -61.104 30.635 15.064 1.00115.54 C
ATOM 5207 CG ASN C 60 -61.692 29.322 14.554 1.00115.47 C
ATOM 5208 OD1 ASN C 60 -61.215 28.238 14.893 1.00114.68 O
ATOM 5209 ND2 ASN C 60 -62.739 29.419 13.739 1.00115.65 N
ATOM 5210 N ASP C 61 -57.966 30.334 13.108 1.00115.14 N
ATOM 5211 CA ASP C 61 -57.479 30.191 11.743 1.00114.13 C
ATOM 5212 C ASP C 61 -57.525 28.679 11.479 1.00113.89 C
ATOM 5213 O ASP C 61 -56.857 27.899 12.165 1.00113.46 O
ATOM 5214 CB ASP C 61 -56.042 30.717 11.646 1.00113.36 C
ATOM 5215 CG ASP C 61 -55.621 31.003 10.224 1.00112.30 C
ATOM 5216 OD1 ASP C 61 -56.004 30.228 9.329 1.00111.35 O
ATOM 5217 OD2 ASP C 61 -54.899 31.997 10.003 1.00111.82 O
ATOM 5218 N SER C 62 -58.322 28.268 10.497 1.00113.79 N
ATOM 5219 CA SER C 62 -58.480 26.845 10.185 1.00113.65 C
ATOM 5220 C SER C 62 -57.510 26.284 9.135 1.00112.82 C
ATOM 5221 O SER C 62 -57.203 26.939 8.134 1.00112.49 O
ATOM 5222 CB SER C 62 -59.926 26.577 9.743 1.00114.15 C
ATOM 5223 OG SER C 62 -60.852 27.026 10.721 1.00113.73 O
ATOM 5224 N PRO C 63 -57.018 25.051 9.360 1.00111.99 N
ATOM 5225 CA PRO C 63 -56.079 24.346 8.472 1.00111.53 C
ATOM 5226 C PRO C 63 -56.644 23.879 7.122 1.00110.84 C
ATOM 5227 O PRO C 63 -56.997 22.710 6.970 1.00111.39 O
ATOM 5228 CB PRO C 63 -55.616 23.164 9.329 1.00111.29 C
ATOM 5229 CG PRO C 63 -55.727 23.696 10.723 1.00111.54 C
ATOM 5230 CD PRO C 63 -57.066 24.393 10.677 1.00111.51 C
ATOM 5231 N PHE C 64 -56.711 24.791 6.153 1.00109.81 N
ATOM 5232 CA PHE C 64 -57.203 24.505 4.798 1.00109.33 C
ATOM 5233 C PHE C 64 -56.675 23.154 4.284 1.00108.56 C
ATOM 5234 O PHE C 64 -55.682 23.107 3.559 1.00108.37 O
ATOM 5235 CB PHE C 64 -56.753 25.644 3.867 1.00110.08 C
ATOM 5236 CG PHE C 64 -57.212 25.508 2.431 1.00110.63 C
ATOM 5237 CD1 PHE C 64 -58.535 25.751 2.076 1.00110.93 C
ATOM 5238 CD2 PHE C 64 -56.301 25.202 1.422 1.00110.60 C
ATOM 5239 CE1 PHE C 64 -58.939 25.698 0.739 1.00110.88 C
ATOM 5240 CE2 PHE C 64 -56.698 25.147 0.085 1.00110.13 C
ATOM 5241 CZ PHE C 64 -58.016 25.396 -0.255 1.00110.58 C
ATOM 5242 N GLN C 65 -57.348 22.064 4.655 1.00108.06 N
ATOM 5243 CA GLN C 65 -56.952 20.705 4.265 1.00107.81 C
ATOM 5244 C GLN C 65 -55.710 20.273 5.051 1.00107.14 C
ATOM 5245 O GLN C 65 -55.814 19.625 6.096 1.00107.01 O
ATOM 5246 CB GLN C 65 -56.638 20.626 2.768 1.00108.70 C
ATOM 5247 CG GLN C 65 -57.714 21.192 1.855 1.00110.56 C
ATOM 5248 CD GLN C 65 -57.404 20.966 0.380 1.00110.91 C
ATOM 5249 OE1 GLN C 65 -57.299 19.825 -0.073 1.00110.88 O
ATOM 5250 NE2 GLN C 65 -57.256 22.055 -0.373 1.00110.95 N
ATOM 5251 N ILE C 66 -54.539 20.639 4.526 1.00106.12 N
ATOM 5252 CA ILE C 66 -53.241 20.337 5.139 1.00103.69 C
ATOM 5253 C ILE C 66 -52.580 21.659 5.552 1.00101.94 C
ATOM 5254 O ILE C 66 -51.979 21.756 6.628 1.00100.49 O
ATOM 5255 CB ILE C 66 -52.313 19.568 4.141 1.00103.32 C
ATOM 5256 CG1 ILE C 66 -52.063 18.147 4.643 1.00102.53 C
ATOM 5257 CG2 ILE C 66 -51.001 20.296 3.955 1.00103.34 C
ATOM 5258 CD1 ILE C 66 -53.282 17.249 4.559 1.00102.55 C
ATOM 5259 N VAL C 67 -52.715 22.667 4.684 1.00100.15 N
ATOM 5260 CA VAL C 67 -52.161 24.002 4.912 1.00 98.05 C
ATOM 5261 C VAL C 67 -52.627 24.605 6.231 1.00 97.96 C
ATOM 5262 O VAL C 67 -53.821 24.660 6.511 1.00 98.49 O
ATOM 5263 CB VAL C 67 -52.542 24.964 3.775 1.00 96.47 C
ATOM 5264 CG1 VAL C 67 -51.896 26.328 4.014 1.00 95.16 C
ATOM 5265 CG2 VAL C 67 -52.128 24.370 2.437 1.00 94.29 C
ATOM 5266 N LYS C 68 -51.680 25.079 7.030 1.00 97.30 N
ATOM 5267 CA LYS C 68 -52.008 25.637 8.331 1.00 97.06 C
ATOM 5268 C LYS C 68 -51.930 27.145 8.354 1.00 97.44 C
ATOM 5269 O LYS C 68 -51.491 27.759 7.383 1.00 97.46 O
ATOM 5270 CB LYS C 68 -51.073 25.032 9.370 1.00 95.66 C
ATOM 5271 CG LYS C 68 -50.903 23.561 9.119 1.00 94.66 C
ATOM 5272 CD LYS C 68 -50.065 22.871 10.151 1.00 94.77 C
ATOM 5273 CE LYS C 68 -49.857 21.423 9.728 1.00 95.37 C
ATOM 5274 NZ LYS C 68 -51.131 20.803 9.235 1.00 93.99 N
ATOM 5275 N ASN C 69 -52.387 27.724 9.463 1.00 98.69 N
ATOM 5276 CA ASN C 69 -52.399 29.176 9.688 1.00100.55 C
ATOM 5277 C ASN C 69 -52.529 30.000 8.396 1.00101.33 C
ATOM 5278 O ASN C 69 -51.827 30.998 8.217 1.00100.98 O
ATOM 5279 CB ASN C 69 -51.114 29.584 10.423 1.00101.27 C
ATOM 5280 CG ASN C 69 -50.891 28.796 11.713 1.00101.35 C
ATOM 5281 OD1 ASN C 69 -51.313 29.217 12.795 1.00101.81 O
ATOM 5282 ND2 ASN C 69 -50.226 27.644 11.598 1.00100.63 N
ATOM 5283 N PRO C 70 -53.453 29.608 7.497 1.00102.26 N
ATOM 5284 CA PRO C 70 -53.674 30.294 6.217 1.00102.62 C
ATOM 5285 C PRO C 70 -54.065 31.761 6.290 1.00102.96 C
ATOM 5286 O PRO C 70 -53.358 32.623 5.766 1.00103.01 O
ATOM 5287 CB PRO C 70 -54.751 29.440 5.556 1.00103.21 C
ATOM 5288 CG PRO C 70 -55.553 28.976 6.717 1.00103.31 C
ATOM 5289 CD PRO C 70 -54.490 28.582 7.715 1.00102.72 C
ATOM 5290 N ARG C 71 -55.199 32.038 6.921 1.00103.42 N
ATOM 5291 CA ARG C 71 -55.678 33.407 7.053 1.00104.26 C
ATOM 5292 C ARG C 71 -54.586 34.312 7.620 1.00104.02 C
ATOM 5293 O ARG C 71 -54.424 35.462 7.191 1.00104.32 O
ATOM 5294 CB ARG C 71 -56.914 33.426 7.950 1.00105.61 C
ATOM 5295 CG ARG C 71 -58.037 32.568 7.402 1.00107.38 C
ATOM 5296 CD ARG C 71 -59.201 32.462 8.367 1.00109.01 C
ATOM 5297 NE ARG C 71 -60.278 31.651 7.805 1.00109.72 N
ATOM 5298 CZ ARG C 71 -60.164 30.361 7.505 1.00110.10 C
ATOM 5299 NH1 ARG C 71 -59.016 29.727 7.717 1.00110.13 N
ATOM 5300 NH2 ARG C 71 -61.196 29.708 6.987 1.00109.92 N
ATOM 5301 N SER C 72 -53.835 33.785 8.582 1.00103.10 N
ATOM 5302 CA SER C 72 -52.745 34.534 9.195 1.00101.82 C
ATOM 5303 C SER C 72 -51.793 35.025 8.088 1.00101.36 C
ATOM 5304 O SER C 72 -51.661 36.232 7.843 1.00100.77 O
ATOM 5305 CB SER C 72 -51.984 33.636 10.186 1.00101.15 C
ATOM 5306 OG SER C 72 -52.818 33.189 11.244 1.00 99.62 O
ATOM 5307 N VAL C 73 -51.155 34.064 7.419 1.00100.71 N
ATOM 5308 CA VAL C 73 -50.205 34.320 6.341 1.00 99.43 C
ATOM 5309 C VAL C 73 -50.808 35.080 5.162 1.00 98.74 C
ATOM 5310 O VAL C 73 -50.088 35.669 4.360 1.00 98.50 O
ATOM 5311 CB VAL C 73 -49.622 32.995 5.807 1.00 99.57 C
ATOM 5312 CG1 VAL C 73 -48.575 33.285 4.751 1.00 99.47 C
ATOM 5313 CG2 VAL C 73 -49.032 32.175 6.956 1.00 98.64 C
ATOM 5314 N GLY C 74 -52.128 35.055 5.051 1.00 98.05 N
ATOM 5315 CA GLY C 74 -52.769 35.762 3.963 1.00 98.09 C
ATOM 5316 C GLY C 74 -52.900 37.242 4.274 1.00 98.36 C
ATOM 5317 O GLY C 74 -52.688 38.097 3.408 1.00 97.94 O
ATOM 5318 N LYS C 75 -53.249 37.551 5.518 1.00 98.26 N
ATOM 5319 CA LYS C 75 -53.411 38.937 5.922 1.00 98.70 C
ATOM 5320 C LYS C 75 -52.086 39.602 6.279 1.00 98.41 C
ATOM 5321 O LYS C 75 -51.914 40.813 6.082 1.00 98.11 O
ATOM 5322 CB LYS C 75 -54.372 39.046 7.104 1.00 99.64 C
ATOM 5323 CG LYS C 75 -54.514 40.479 7.633 1.00101.06 C
ATOM 5324 CD LYS C 75 -54.885 41.458 6.513 1.00101.25 C
ATOM 5325 CE LYS C 75 -54.785 42.906 6.972 1.00100.94 C
ATOM 5326 NZ LYS C 75 -55.007 43.844 5.837 1.00100.45 N
ATOM 5327 N ALA C 76 -51.157 38.812 6.814 1.00 98.25 N
ATOM 5328 CA ALA C 76 -49.844 39.329 7.190 1.00 97.31 C
ATOM 5329 C ALA C 76 -49.086 39.723 5.930 1.00 96.60 C
ATOM 5330 O ALA C 76 -48.401 40.745 5.905 1.00 95.57 O
ATOM 5331 CB ALA C 76 -49.062 38.271 7.963 1.00 96.93 C
ATOM 5332 N ASN C 77 -49.228 38.898 4.890 1.00 97.00 N
ATOM 5333 CA ASN C 77 -48.579 39.116 3.598 1.00 97.74 C
ATOM 5334 C ASN C 77 -49.314 40.172 2.785 1.00 98.75 C
ATOM 5335 O ASN C 77 -48.745 40.767 1.870 1.00 98.91 O
ATOM 5336 CB ASN C 77 -48.510 37.804 2.805 1.00 97.23 C
ATOM 5337 CG ASN C 77 -47.228 37.016 3.077 1.00 97.89 C
ATOM 5338 OD1 ASN C 77 -46.160 37.342 2.550 1.00 96.57 O
ATOM 5339 ND2 ASN C 77 -47.331 35.980 3.911 1.00 97.76 N
ATOM 5340 N GLU C 78 -50.585 40.392 3.113 1.00 99.93 N
ATOM 5341 CA GLU C 78 -51.375 41.406 2.426 1.00100.34 C
ATOM 5342 C GLU C 78 -50.932 42.771 2.943 1.00 99.33 C
ATOM 5343 O GLU C 78 -50.755 43.719 2.177 1.00 99.02 O
ATOM 5344 CB GLU C 78 -52.867 41.214 2.702 1.00101.86 C
ATOM 5345 CG GLU C 78 -53.722 42.358 2.171 1.00103.76 C
ATOM 5346 CD GLU C 78 -55.202 42.110 2.346 1.00104.81 C
ATOM 5347 OE1 GLU C 78 -55.625 41.853 3.494 1.00105.01 O
ATOM 5348 OE2 GLU C 78 -55.935 42.177 1.332 1.00105.37 O
ATOM 5349 N GLN C 79 -50.752 42.859 4.255 1.00 98.33 N
ATOM 5350 CA GLN C 79 -50.315 44.094 4.876 1.00 98.14 C
ATOM 5351 C GLN C 79 -48.932 44.502 4.370 1.00 98.36 C
ATOM 5352 O GLN C 79 -48.658 45.695 4.185 1.00 99.37 O
ATOM 5353 CB GLN C 79 -50.278 43.930 6.395 1.00 98.02 C
ATOM 5354 CG GLN C 79 -49.596 45.083 7.119 1.00 98.51 C
ATOM 5355 CD GLN C 79 -49.649 44.936 8.627 1.00 99.74 C
ATOM 5356 OE1 GLN C 79 -49.107 45.766 9.363 1.00100.42 O
ATOM 5357 NE2 GLN C 79 -50.308 43.880 9.096 1.00 99.69 N
ATOM 5358 N LEU C 80 -48.071 43.509 4.140 1.00 97.08 N
ATOM 5359 CA LEU C 80 -46.703 43.746 3.682 1.00 96.12 C
ATOM 5360 C LEU C 80 -46.607 44.224 2.243 1.00 95.39 C
ATOM 5361 O LEU C 80 -46.072 45.300 1.983 1.00 94.88 O
ATOM 5362 CB LEU C 80 -45.852 42.476 3.872 1.00 96.94 C
ATOM 5363 CG LEU C 80 -44.405 42.402 3.345 1.00 96.90 C
ATOM 5364 CD1 LEU C 80 -43.543 43.538 3.884 1.00 96.64 C
ATOM 5365 CD2 LEU C 80 -43.816 41.065 3.756 1.00 97.01 C
ATOM 5366 N ALA C 81 -47.111 43.423 1.308 1.00 95.38 N
ATOM 5367 CA ALA C 81 -47.068 43.787 -0.109 1.00 95.32 C
ATOM 5368 C ALA C 81 -47.397 45.272 -0.220 1.00 95.15 C
ATOM 5369 O ALA C 81 -46.698 46.029 -0.901 1.00 95.06 O
ATOM 5370 CB ALA C 81 -48.077 42.951 -0.912 1.00 94.39 C
ATOM 5371 N ALA C 82 -48.458 45.672 0.480 1.00 94.53 N
ATOM 5372 CA ALA C 82 -48.917 47.052 0.513 1.00 92.86 C
ATOM 5373 C ALA C 82 -47.767 48.022 0.804 1.00 92.77 C
ATOM 5374 O ALA C 82 -47.420 48.859 -0.038 1.00 94.08 O
ATOM 5375 CB ALA C 82 -49.991 47.198 1.565 1.00 91.55 C
ATOM 5376 N VAL C 83 -47.168 47.911 1.988 1.00 90.57 N
ATOM 5377 CA VAL C 83 -46.071 48.803 2.347 1.00 87.86 C
ATOM 5378 C VAL C 83 -44.981 48.797 1.287 1.00 87.81 C
ATOM 5379 O VAL C 83 -44.440 49.838 0.948 1.00 87.85 O
ATOM 5380 CB VAL C 83 -45.443 48.424 3.695 1.00 85.44 C
ATOM 5381 CG1 VAL C 83 -44.475 49.521 4.131 1.00 83.17 C
ATOM 5382 CG2 VAL C 83 -46.541 48.200 4.738 1.00 84.36 C
ATOM 5383 N VAL C 84 -44.672 47.619 0.760 1.00 88.67 N
ATOM 5384 CA VAL C 84 -43.640 47.476 -0.268 1.00 89.97 C
ATOM 5385 C VAL C 84 -43.946 48.301 -1.526 1.00 90.78 C
ATOM 5386 O VAL C 84 -43.107 49.066 -2.010 1.00 89.94 O
ATOM 5387 CB VAL C 84 -43.471 45.986 -0.662 1.00 89.27 C
ATOM 5388 CG1 VAL C 84 -42.409 45.848 -1.746 1.00 88.30 C
ATOM 5389 CG2 VAL C 84 -43.108 45.160 0.566 1.00 88.68 C
ATOM 5390 N ALA C 85 -45.151 48.136 -2.059 1.00 92.01 N
ATOM 5391 CA ALA C 85 -45.545 48.879 -3.243 1.00 93.16 C
ATOM 5392 C ALA C 85 -45.523 50.350 -2.858 1.00 93.76 C
ATOM 5393 O ALA C 85 -45.211 51.226 -3.679 1.00 92.85 O
ATOM 5394 CB ALA C 85 -46.954 48.464 -3.687 1.00 92.48 C
ATOM 5395 N GLU C 86 -45.836 50.596 -1.586 1.00 94.93 N
ATOM 5396 CA GLU C 86 -45.892 51.938 -1.014 1.00 96.65 C
ATOM 5397 C GLU C 86 -44.571 52.688 -1.113 1.00 97.30 C
ATOM 5398 O GLU C 86 -44.531 53.875 -1.453 1.00 96.34 O
ATOM 5399 CB GLU C 86 -46.322 51.849 0.450 1.00 97.43 C
ATOM 5400 CG GLU C 86 -47.183 53.002 0.865 1.00101.11 C
ATOM 5401 CD GLU C 86 -48.251 53.291 -0.176 1.00103.56 C
ATOM 5402 OE1 GLU C 86 -49.022 52.360 -0.516 1.00104.28 O
ATOM 5403 OE2 GLU C 86 -48.312 54.446 -0.657 1.00104.59 O
ATOM 5404 N THR C 87 -43.494 51.978 -0.803 1.00 98.79 N
ATOM 5405 CA THR C 87 -42.157 52.536 -0.847 1.00 99.86 C
ATOM 5406 C THR C 87 -41.722 52.536 -2.291 1.00101.87 C
ATOM 5407 O THR C 87 -41.326 53.565 -2.822 1.00102.78 O
ATOM 5408 CB THR C 87 -41.175 51.680 -0.055 1.00 99.41 C
ATOM 5409 OG1 THR C 87 -41.824 51.156 1.110 1.00 99.80 O
ATOM 5410 CG2 THR C 87 -40.002 52.516 0.385 1.00 99.73 C
ATOM 5411 N GLN C 88 -41.805 51.366 -2.919 1.00104.27 N
ATOM 5412 CA GLN C 88 -41.431 51.196 -4.324 1.00107.00 C
ATOM 5413 C GLN C 88 -41.853 52.362 -5.226 1.00107.90 C
ATOM 5414 O GLN C 88 -41.137 52.717 -6.170 1.00107.08 O
ATOM 5415 CB GLN C 88 -42.033 49.897 -4.873 1.00107.91 C
ATOM 5416 CG GLN C 88 -41.208 48.652 -4.604 1.00109.47 C
ATOM 5417 CD GLN C 88 -39.779 48.787 -5.106 1.00110.31 C
ATOM 5418 OE1 GLN C 88 -39.511 49.514 -6.067 1.00110.06 O
ATOM 5419 NE2 GLN C 88 -38.856 48.075 -4.462 1.00110.80 N
ATOM 5420 N LYS C 89 -43.020 52.938 -4.931 1.00109.56 N
ATOM 5421 CA LYS C 89 -43.564 54.059 -5.694 1.00110.90 C
ATOM 5422 C LYS C 89 -42.773 55.344 -5.427 1.00111.00 C
ATOM 5423 O LYS C 89 -42.549 56.151 -6.334 1.00110.95 O
ATOM 5424 CB LYS C 89 -45.034 54.271 -5.330 1.00111.68 C
ATOM 5425 CG LYS C 89 -45.757 55.250 -6.238 1.00113.68 C
ATOM 5426 CD LYS C 89 -47.199 55.485 -5.784 1.00116.52 C
ATOM 5427 CE LYS C 89 -48.025 54.191 -5.759 1.00117.23 C
ATOM 5428 NZ LYS C 89 -49.448 54.420 -5.351 1.00117.27 N
ATOM 5429 N ASN C 90 -42.360 55.525 -4.175 1.00110.80 N
ATOM 5430 CA ASN C 90 -41.574 56.689 -3.776 1.00110.60 C
ATOM 5431 C ASN C 90 -40.198 56.616 -4.417 1.00110.46 C
ATOM 5432 O ASN C 90 -39.443 57.591 -4.422 1.00110.57 O
ATOM 5433 CB ASN C 90 -41.425 56.720 -2.257 1.00110.18 C
ATOM 5434 CG ASN C 90 -42.743 56.914 -1.558 1.00109.88 C
ATOM 5435 OD1 ASN C 90 -43.316 57.998 -1.601 1.00110.06 O
ATOM 5436 ND2 ASN C 90 -43.244 55.861 -0.922 1.00109.05 N
ATOM 5437 N GLY C 91 -39.876 55.437 -4.942 1.00110.39 N
ATOM 5438 CA GLY C 91 -38.600 55.232 -5.598 1.00109.77 C
ATOM 5439 C GLY C 91 -37.501 54.598 -4.757 1.00109.04 C
ATOM 5440 O GLY C 91 -36.437 54.277 -5.291 1.00109.23 O
ATOM 5441 N THR C 92 -37.739 54.400 -3.461 1.00107.90 N
ATOM 5442 CA THR C 92 -36.714 53.815 -2.596 1.00106.35 C
ATOM 5443 C THR C 92 -36.637 52.293 -2.726 1.00105.86 C
ATOM 5444 O THR C 92 -37.586 51.651 -3.194 1.00105.70 O
ATOM 5445 CB THR C 92 -36.940 54.194 -1.096 1.00105.45 C
ATOM 5446 OG1 THR C 92 -37.588 53.122 -0.406 1.00103.68 O
ATOM 5447 CG2 THR C 92 -37.797 55.451 -0.979 1.00104.19 C
ATOM 5448 N ILE C 93 -35.491 51.730 -2.331 1.00104.70 N
ATOM 5449 CA ILE C 93 -35.261 50.283 -2.374 1.00101.94 C
ATOM 5450 C ILE C 93 -35.797 49.633 -1.104 1.00100.46 C
ATOM 5451 O ILE C 93 -35.450 50.037 0.011 1.00100.27 O
ATOM 5452 CB ILE C 93 -33.764 49.944 -2.477 1.00101.61 C
ATOM 5453 CG1 ILE C 93 -33.147 50.629 -3.694 1.00101.79 C
ATOM 5454 CG2 ILE C 93 -33.585 48.439 -2.573 1.00101.59 C
ATOM 5455 CD1 ILE C 93 -33.813 50.258 -4.997 1.00102.89 C
ATOM 5456 N SER C 94 -36.648 48.630 -1.286 1.00 98.22 N
ATOM 5457 CA SER C 94 -37.249 47.921 -0.168 1.00 96.48 C
ATOM 5458 C SER C 94 -36.354 46.783 0.316 1.00 95.30 C
ATOM 5459 O SER C 94 -35.854 45.986 -0.492 1.00 94.98 O
ATOM 5460 CB SER C 94 -38.616 47.363 -0.576 1.00 96.70 C
ATOM 5461 OG SER C 94 -38.528 46.616 -1.782 1.00 96.79 O
ATOM 5462 N VAL C 95 -36.137 46.720 1.632 1.00 92.94 N
ATOM 5463 CA VAL C 95 -35.308 45.673 2.232 1.00 89.32 C
ATOM 5464 C VAL C 95 -36.050 45.048 3.409 1.00 87.17 C
ATOM 5465 O VAL C 95 -36.049 45.580 4.523 1.00 86.40 O
ATOM 5466 CB VAL C 95 -33.969 46.230 2.718 1.00 88.54 C
ATOM 5467 CG1 VAL C 95 -32.985 45.078 2.909 1.00 88.25 C
ATOM 5468 CG2 VAL C 95 -33.435 47.240 1.717 1.00 87.16 C
ATOM 5469 N VAL C 96 -36.662 43.900 3.140 1.00 85.04 N
ATOM 5470 CA VAL C 96 -37.463 43.182 4.116 1.00 83.33 C
ATOM 5471 C VAL C 96 -36.753 42.226 5.065 1.00 81.90 C
ATOM 5472 O VAL C 96 -36.457 41.087 4.702 1.00 81.87 O
ATOM 5473 CB VAL C 96 -38.575 42.379 3.408 1.00 83.38 C
ATOM 5474 CG1 VAL C 96 -39.501 41.740 4.436 1.00 83.72 C
ATOM 5475 CG2 VAL C 96 -39.347 43.288 2.479 1.00 83.57 C
ATOM 5476 N LEU C 97 -36.485 42.696 6.282 1.00 80.03 N
ATOM 5477 CA LEU C 97 -35.883 41.850 7.305 1.00 76.82 C
ATOM 5478 C LEU C 97 -37.056 40.934 7.593 1.00 75.41 C
ATOM 5479 O LEU C 97 -38.188 41.404 7.631 1.00 74.63 O
ATOM 5480 CB LEU C 97 -35.558 42.652 8.563 1.00 75.09 C
ATOM 5481 CG LEU C 97 -34.639 43.860 8.388 1.00 75.32 C
ATOM 5482 CD1 LEU C 97 -34.205 44.349 9.757 1.00 72.55 C
ATOM 5483 CD2 LEU C 97 -33.434 43.475 7.544 1.00 74.86 C
ATOM 5484 N GLY C 98 -36.821 39.643 7.793 1.00 74.85 N
ATOM 5485 CA GLY C 98 -37.967 38.799 8.025 1.00 74.16 C
ATOM 5486 C GLY C 98 -38.008 37.702 9.063 1.00 74.60 C
ATOM 5487 O GLY C 98 -37.151 37.549 9.932 1.00 73.56 O
ATOM 5488 N GLY C 99 -39.107 36.972 8.959 1.00 75.85 N
ATOM 5489 CA GLY C 99 -39.409 35.851 9.808 1.00 78.40 C
ATOM 5490 C GLY C 99 -39.398 34.814 8.717 1.00 80.54 C
ATOM 5491 O GLY C 99 -38.617 34.968 7.774 1.00 80.94 O
ATOM 5492 N ASP C 100 -40.261 33.805 8.781 1.00 82.59 N
ATOM 5493 CA ASP C 100 -40.259 32.777 7.741 1.00 84.85 C
ATOM 5494 C ASP C 100 -40.344 33.365 6.323 1.00 84.58 C
ATOM 5495 O ASP C 100 -40.812 34.486 6.120 1.00 84.05 O
ATOM 5496 CB ASP C 100 -41.378 31.757 7.990 1.00 87.56 C
ATOM 5497 CG ASP C 100 -42.678 32.132 7.323 1.00 90.13 C
ATOM 5498 OD1 ASP C 100 -42.720 32.118 6.074 1.00 89.63 O
ATOM 5499 OD2 ASP C 100 -43.651 32.430 8.053 1.00 92.61 O
ATOM 5500 N HIS C 101 -39.876 32.587 5.355 1.00 84.89 N
ATOM 5501 CA HIS C 101 -39.810 32.984 3.955 1.00 85.65 C
ATOM 5502 C HIS C 101 -41.146 33.115 3.236 1.00 85.99 C
ATOM 5503 O HIS C 101 -41.175 33.316 2.021 1.00 85.93 O
ATOM 5504 CB HIS C 101 -38.912 31.985 3.210 1.00 86.72 C
ATOM 5505 CG HIS C 101 -38.209 32.553 2.013 1.00 86.60 C
ATOM 5506 ND1 HIS C 101 -37.077 31.968 1.478 1.00 85.54 N
ATOM 5507 CD2 HIS C 101 -38.491 33.616 1.223 1.00 86.26 C
ATOM 5508 CE1 HIS C 101 -36.698 32.647 0.414 1.00 86.39 C
ATOM 5509 NE2 HIS C 101 -37.540 33.652 0.234 1.00 86.65 N
ATOM 5510 N SER C 102 -42.253 33.009 3.961 1.00 86.24 N
ATOM 5511 CA SER C 102 -43.557 33.132 3.316 1.00 86.63 C
ATOM 5512 C SER C 102 -43.957 34.599 3.207 1.00 85.62 C
ATOM 5513 O SER C 102 -45.023 34.928 2.694 1.00 84.65 O
ATOM 5514 CB SER C 102 -44.615 32.364 4.096 1.00 87.71 C
ATOM 5515 OG SER C 102 -44.884 33.011 5.324 1.00 91.99 O
ATOM 5516 N MET C 103 -43.099 35.482 3.707 1.00 85.08 N
ATOM 5517 CA MET C 103 -43.370 36.905 3.623 1.00 84.48 C
ATOM 5518 C MET C 103 -42.837 37.348 2.276 1.00 83.76 C
ATOM 5519 O MET C 103 -42.787 38.539 1.969 1.00 83.39 O
ATOM 5520 CB MET C 103 -42.669 37.669 4.745 1.00 84.83 C
ATOM 5521 CG MET C 103 -43.120 37.260 6.136 1.00 87.32 C
ATOM 5522 SD MET C 103 -44.920 37.234 6.336 1.00 88.58 S
ATOM 5523 CE MET C 103 -45.261 38.997 6.300 1.00 87.63 C
ATOM 5524 N ALA C 104 -42.431 36.367 1.475 1.00 83.38 N
ATOM 5525 CA ALA C 104 -41.912 36.630 0.141 1.00 83.07 C
ATOM 5526 C ALA C 104 -43.068 37.036 -0.777 1.00 82.42 C
ATOM 5527 O ALA C 104 -42.933 37.953 -1.593 1.00 82.21 O
ATOM 5528 CB ALA C 104 -41.209 35.393 -0.401 1.00 84.51 C
ATOM 5529 N ILE C 105 -44.206 36.352 -0.649 1.00 80.53 N
ATOM 5530 CA ILE C 105 -45.371 36.708 -1.455 1.00 78.98 C
ATOM 5531 C ILE C 105 -45.629 38.200 -1.211 1.00 77.86 C
ATOM 5532 O ILE C 105 -45.603 39.006 -2.143 1.00 76.47 O
ATOM 5533 CB ILE C 105 -46.646 35.884 -1.067 1.00 78.15 C
ATOM 5534 CG1 ILE C 105 -46.406 35.046 0.186 1.00 77.60 C
ATOM 5535 CG2 ILE C 105 -47.012 34.936 -2.201 1.00 78.93 C
ATOM 5536 CD1 ILE C 105 -47.572 34.117 0.496 1.00 74.53 C
ATOM 5537 N GLY C 106 -45.852 38.559 0.051 1.00 76.94 N
ATOM 5538 CA GLY C 106 -46.077 39.948 0.385 1.00 76.15 C
ATOM 5539 C GLY C 106 -45.066 40.830 -0.318 1.00 76.23 C
ATOM 5540 O GLY C 106 -45.422 41.560 -1.239 1.00 77.43 O
ATOM 5541 N SER C 107 -43.806 40.754 0.100 1.00 75.72 N
ATOM 5542 CA SER C 107 -42.737 41.560 -0.494 1.00 75.71 C
ATOM 5543 C SER C 107 -42.783 41.586 -2.024 1.00 75.75 C
ATOM 5544 O SER C 107 -42.938 42.648 -2.638 1.00 74.82 O
ATOM 5545 CB SER C 107 -41.367 41.030 -0.037 1.00 76.72 C
ATOM 5546 OG SER C 107 -40.278 41.666 -0.709 1.00 75.74 O
ATOM 5547 N ILE C 108 -42.652 40.411 -2.631 1.00 75.95 N
ATOM 5548 CA ILE C 108 -42.645 40.293 -4.079 1.00 75.58 C
ATOM 5549 C ILE C 108 -43.867 40.935 -4.724 1.00 76.75 C
ATOM 5550 O ILE C 108 -43.729 41.724 -5.658 1.00 77.19 O
ATOM 5551 CB ILE C 108 -42.519 38.817 -4.503 1.00 74.49 C
ATOM 5552 CG1 ILE C 108 -41.231 38.228 -3.924 1.00 73.59 C
ATOM 5553 CG2 ILE C 108 -42.485 38.712 -6.012 1.00 75.30 C
ATOM 5554 CD1 ILE C 108 -40.872 36.866 -4.439 1.00 71.41 C
ATOM 5555 N SER C 109 -45.058 40.612 -4.224 1.00 77.84 N
ATOM 5556 CA SER C 109 -46.290 41.197 -4.757 1.00 78.47 C
ATOM 5557 C SER C 109 -46.192 42.713 -4.714 1.00 78.55 C
ATOM 5558 O SER C 109 -46.242 43.377 -5.746 1.00 77.36 O
ATOM 5559 CB SER C 109 -47.500 40.749 -3.930 1.00 78.95 C
ATOM 5560 OG SER C 109 -47.919 39.450 -4.304 1.00 81.14 O
ATOM 5561 N GLY C 110 -46.055 43.246 -3.504 1.00 79.20 N
ATOM 5562 CA GLY C 110 -45.944 44.675 -3.333 1.00 81.12 C
ATOM 5563 C GLY C 110 -44.992 45.269 -4.347 1.00 83.10 C
ATOM 5564 O GLY C 110 -45.269 46.319 -4.924 1.00 83.47 O
ATOM 5565 N HIS C 111 -43.875 44.592 -4.580 1.00 85.03 N
ATOM 5566 CA HIS C 111 -42.876 45.069 -5.533 1.00 87.81 C
ATOM 5567 C HIS C 111 -43.398 45.135 -6.984 1.00 88.96 C
ATOM 5568 O HIS C 111 -43.240 46.157 -7.663 1.00 87.29 O
ATOM 5569 CB HIS C 111 -41.628 44.171 -5.462 1.00 88.57 C
ATOM 5570 CG HIS C 111 -40.443 44.715 -6.205 1.00 89.32 C
ATOM 5571 ND1 HIS C 111 -39.254 44.027 -6.308 1.00 89.05 N
ATOM 5572 CD2 HIS C 111 -40.270 45.873 -6.888 1.00 88.94 C
ATOM 5573 CE1 HIS C 111 -38.398 44.737 -7.025 1.00 89.41 C
ATOM 5574 NE2 HIS C 111 -38.990 45.860 -7.388 1.00 88.73 N
ATOM 5575 N ALA C 112 -44.015 44.040 -7.437 1.00 90.99 N
ATOM 5576 CA ALA C 112 -44.561 43.912 -8.796 1.00 92.37 C
ATOM 5577 C ALA C 112 -45.599 44.979 -9.143 1.00 93.72 C
ATOM 5578 O ALA C 112 -45.825 45.289 -10.320 1.00 93.91 O
ATOM 5579 CB ALA C 112 -45.173 42.518 -8.980 1.00 91.27 C
ATOM 5580 N ARG C 113 -46.237 45.526 -8.116 1.00 94.50 N
ATOM 5581 CA ARG C 113 -47.241 46.554 -8.314 1.00 94.94 C
ATOM 5582 C ARG C 113 -46.625 47.787 -8.966 1.00 95.62 C
ATOM 5583 O ARG C 113 -47.198 48.357 -9.894 1.00 96.16 O
ATOM 5584 CB ARG C 113 -47.900 46.898 -6.969 1.00 94.28 C
ATOM 5585 CG ARG C 113 -48.905 45.834 -6.538 1.00 94.48 C
ATOM 5586 CD ARG C 113 -49.435 46.004 -5.120 1.00 95.26 C
ATOM 5587 NE ARG C 113 -50.510 45.043 -4.845 1.00 96.22 N
ATOM 5588 CZ ARG C 113 -50.989 44.747 -3.632 1.00 96.89 C
ATOM 5589 NH1 ARG C 113 -50.493 45.332 -2.543 1.00 96.87 N
ATOM 5590 NH2 ARG C 113 -51.973 43.859 -3.507 1.00 96.57 N
ATOM 5591 N VAL C 114 -45.444 48.177 -8.502 1.00 96.02 N
ATOM 5592 CA VAL C 114 -44.765 49.347 -9.041 1.00 96.73 C
ATOM 5593 C VAL C 114 -43.841 49.010 -10.215 1.00 97.56 C
ATOM 5594 O VAL C 114 -43.620 49.841 -11.098 1.00 97.44 O
ATOM 5595 CB VAL C 114 -43.962 50.053 -7.934 1.00 97.09 C
ATOM 5596 CG1 VAL C 114 -43.369 51.347 -8.464 1.00 97.30 C
ATOM 5597 CG2 VAL C 114 -44.867 50.319 -6.729 1.00 96.77 C
ATOM 5598 N HIS C 115 -43.305 47.791 -10.215 1.00 99.09 N
ATOM 5599 CA HIS C 115 -42.409 47.319 -11.278 1.00100.13 C
ATOM 5600 C HIS C 115 -42.781 45.888 -11.662 1.00100.23 C
ATOM 5601 O HIS C 115 -42.141 44.934 -11.228 1.00100.81 O
ATOM 5602 CB HIS C 115 -40.950 47.337 -10.816 1.00100.57 C
ATOM 5603 CG HIS C 115 -40.456 48.687 -10.397 1.00101.28 C
ATOM 5604 ND1 HIS C 115 -40.787 49.260 -9.190 1.00101.75 N
ATOM 5605 CD2 HIS C 115 -39.625 49.559 -11.015 1.00101.64 C
ATOM 5606 CE1 HIS C 115 -40.176 50.428 -9.077 1.00102.42 C
ATOM 5607 NE2 HIS C 115 -39.465 50.632 -10.170 1.00102.31 N
ATOM 5608 N PRO C 116 -43.813 45.728 -12.494 1.00100.42 N
ATOM 5609 CA PRO C 116 -44.321 44.438 -12.965 1.00100.72 C
ATOM 5610 C PRO C 116 -43.414 43.751 -13.972 1.00100.87 C
ATOM 5611 O PRO C 116 -43.747 42.680 -14.488 1.00100.56 O
ATOM 5612 CB PRO C 116 -45.650 44.817 -13.582 1.00101.70 C
ATOM 5613 CG PRO C 116 -45.298 46.124 -14.245 1.00102.18 C
ATOM 5614 CD PRO C 116 -44.524 46.838 -13.153 1.00101.10 C
ATOM 5615 N ASP C 117 -42.279 44.374 -14.266 1.00101.28 N
ATOM 5616 CA ASP C 117 -41.332 43.805 -15.224 1.00102.06 C
ATOM 5617 C ASP C 117 -40.113 43.186 -14.536 1.00101.05 C
ATOM 5618 O ASP C 117 -39.187 42.715 -15.201 1.00101.44 O
ATOM 5619 CB ASP C 117 -40.882 44.883 -16.221 1.00103.66 C
ATOM 5620 CG ASP C 117 -40.296 46.113 -15.537 1.00105.43 C
ATOM 5621 OD1 ASP C 117 -40.949 46.658 -14.616 1.00106.09 O
ATOM 5622 OD2 ASP C 117 -39.186 46.540 -15.931 1.00106.50 O
ATOM 5623 N LEU C 118 -40.133 43.177 -13.202 1.00 98.82 N
ATOM 5624 CA LEU C 118 -39.034 42.635 -12.403 1.00 95.55 C
ATOM 5625 C LEU C 118 -38.774 41.136 -12.601 1.00 93.68 C
ATOM 5626 O LEU C 118 -39.627 40.385 -13.089 1.00 93.41 O
ATOM 5627 CB LEU C 118 -39.278 42.909 -10.901 1.00 93.59 C
ATOM 5628 CG LEU C 118 -40.488 42.276 -10.188 1.00 92.16 C
ATOM 5629 CD1 LEU C 118 -40.366 40.762 -10.140 1.00 92.08 C
ATOM 5630 CD2 LEU C 118 -40.570 42.816 -8.781 1.00 90.84 C
ATOM 5631 N CYS C 119 -37.565 40.726 -12.231 1.00 90.59 N
ATOM 5632 CA CYS C 119 -37.156 39.334 -12.293 1.00 86.30 C
ATOM 5633 C CYS C 119 -36.972 39.002 -10.832 1.00 83.38 C
ATOM 5634 O CYS C 119 -37.245 39.832 -9.970 1.00 83.17 O
ATOM 5635 CB CYS C 119 -35.832 39.194 -13.032 1.00 85.90 C
ATOM 5636 SG CYS C 119 -34.685 40.514 -12.633 1.00 85.58 S
ATOM 5637 N VAL C 120 -36.498 37.804 -10.542 1.00 80.52 N
ATOM 5638 CA VAL C 120 -36.310 37.409 -9.158 1.00 76.40 C
ATOM 5639 C VAL C 120 -35.185 36.400 -8.991 1.00 73.42 C
ATOM 5640 O VAL C 120 -35.177 35.355 -9.635 1.00 72.14 O
ATOM 5641 CB VAL C 120 -37.627 36.805 -8.575 1.00 75.95 C
ATOM 5642 CG1 VAL C 120 -37.347 36.116 -7.245 1.00 74.91 C
ATOM 5643 CG2 VAL C 120 -38.673 37.911 -8.390 1.00 73.63 C
ATOM 5644 N ILE C 121 -34.231 36.729 -8.129 1.00 71.26 N
ATOM 5645 CA ILE C 121 -33.119 35.823 -7.829 1.00 69.79 C
ATOM 5646 C ILE C 121 -33.463 35.213 -6.465 1.00 66.24 C
ATOM 5647 O ILE C 121 -33.593 35.921 -5.464 1.00 65.09 O
ATOM 5648 CB ILE C 121 -31.744 36.575 -7.767 1.00 71.19 C
ATOM 5649 CG1 ILE C 121 -31.323 37.065 -9.159 1.00 71.26 C
ATOM 5650 CG2 ILE C 121 -30.659 35.635 -7.276 1.00 71.09 C
ATOM 5651 CD1 ILE C 121 -32.386 37.851 -9.888 1.00 72.36 C
ATOM 5652 N TRP C 122 -33.627 33.899 -6.436 1.00 62.73 N
ATOM 5653 CA TRP C 122 -34.005 33.217 -5.210 1.00 60.62 C
ATOM 5654 C TRP C 122 -32.900 32.331 -4.625 1.00 60.19 C
ATOM 5655 O TRP C 122 -32.720 31.176 -5.034 1.00 59.32 O
ATOM 5656 CB TRP C 122 -35.277 32.401 -5.488 1.00 58.94 C
ATOM 5657 CG TRP C 122 -35.961 31.801 -4.282 1.00 56.58 C
ATOM 5658 CD1 TRP C 122 -35.587 30.676 -3.598 1.00 55.86 C
ATOM 5659 CD2 TRP C 122 -37.168 32.264 -3.659 1.00 55.45 C
ATOM 5660 NE1 TRP C 122 -36.488 30.406 -2.590 1.00 55.24 N
ATOM 5661 CE2 TRP C 122 -37.465 31.370 -2.596 1.00 55.02 C
ATOM 5662 CE3 TRP C 122 -38.021 33.357 -3.877 1.00 54.23 C
ATOM 5663 CZ2 TRP C 122 -38.586 31.519 -1.775 1.00 54.64 C
ATOM 5664 CZ3 TRP C 122 -39.142 33.513 -3.055 1.00 54.27 C
ATOM 5665 CH2 TRP C 122 -39.408 32.601 -2.012 1.00 55.66 C
ATOM 5666 N VAL C 123 -32.159 32.890 -3.670 1.00 59.72 N
ATOM 5667 CA VAL C 123 -31.093 32.151 -2.987 1.00 59.40 C
ATOM 5668 C VAL C 123 -31.721 31.513 -1.732 1.00 57.38 C
ATOM 5669 O VAL C 123 -31.998 32.184 -0.734 1.00 55.82 O
ATOM 5670 CB VAL C 123 -29.918 33.073 -2.565 1.00 59.65 C
ATOM 5671 CG1 VAL C 123 -28.727 32.233 -2.164 1.00 58.94 C
ATOM 5672 CG2 VAL C 123 -29.535 33.998 -3.699 1.00 58.72 C
ATOM 5673 N ASP C 124 -31.947 30.205 -1.816 1.00 55.40 N
ATOM 5674 CA ASP C 124 -32.583 29.423 -0.759 1.00 54.22 C
ATOM 5675 C ASP C 124 -32.041 28.025 -1.002 1.00 55.31 C
ATOM 5676 O ASP C 124 -31.593 27.723 -2.118 1.00 55.23 O
ATOM 5677 CB ASP C 124 -34.110 29.442 -0.980 1.00 50.71 C
ATOM 5678 CG ASP C 124 -34.893 28.911 0.187 1.00 47.58 C
ATOM 5679 OD1 ASP C 124 -34.645 27.776 0.623 1.00 46.94 O
ATOM 5680 OD2 ASP C 124 -35.793 29.623 0.675 1.00 46.77 O
ATOM 5681 N ALA C 125 -32.054 27.184 0.029 1.00 56.37 N
ATOM 5682 CA ALA C 125 -31.599 25.805 -0.138 1.00 57.62 C
ATOM 5683 C ALA C 125 -32.745 25.090 -0.869 1.00 58.34 C
ATOM 5684 O ALA C 125 -32.534 24.198 -1.694 1.00 56.62 O
ATOM 5685 CB ALA C 125 -31.351 25.151 1.223 1.00 56.07 C
ATOM 5686 N HIS C 126 -33.960 25.547 -0.566 1.00 59.92 N
ATOM 5687 CA HIS C 126 -35.194 25.010 -1.109 1.00 61.14 C
ATOM 5688 C HIS C 126 -35.820 25.875 -2.186 1.00 64.86 C
ATOM 5689 O HIS C 126 -35.616 27.098 -2.218 1.00 65.54 O
ATOM 5690 CB HIS C 126 -36.210 24.855 0.014 1.00 58.52 C
ATOM 5691 CG HIS C 126 -35.594 24.490 1.318 1.00 57.04 C
ATOM 5692 ND1 HIS C 126 -35.190 25.434 2.237 1.00 59.20 N
ATOM 5693 CD2 HIS C 126 -35.202 23.291 1.806 1.00 55.86 C
ATOM 5694 CE1 HIS C 126 -34.562 24.834 3.234 1.00 58.98 C
ATOM 5695 NE2 HIS C 126 -34.555 23.533 2.995 1.00 58.70 N
ATOM 5696 N THR C 127 -36.598 25.221 -3.052 1.00 67.28 N
ATOM 5697 CA THR C 127 -37.325 25.882 -4.127 1.00 69.38 C
ATOM 5698 C THR C 127 -38.539 26.553 -3.472 1.00 70.18 C
ATOM 5699 O THR C 127 -38.912 27.681 -3.817 1.00 68.18 O
ATOM 5700 CB THR C 127 -37.814 24.857 -5.183 1.00 71.32 C
ATOM 5701 OG1 THR C 127 -38.155 23.629 -4.526 1.00 72.91 O
ATOM 5702 CG2 THR C 127 -36.739 24.594 -6.238 1.00 70.67 C
ATOM 5703 N ASP C 128 -39.136 25.848 -2.510 1.00 72.64 N
ATOM 5704 CA ASP C 128 -40.307 26.346 -1.785 1.00 76.54 C
ATOM 5705 C ASP C 128 -41.461 26.577 -2.777 1.00 78.32 C
ATOM 5706 O ASP C 128 -42.374 27.368 -2.523 1.00 77.37 O
ATOM 5707 CB ASP C 128 -39.979 27.676 -1.054 1.00 76.13 C
ATOM 5708 CG ASP C 128 -38.773 27.567 -0.111 1.00 74.37 C
ATOM 5709 OD1 ASP C 128 -38.566 26.485 0.488 1.00 74.66 O
ATOM 5710 OD2 ASP C 128 -38.042 28.575 0.035 1.00 71.25 O
ATOM 5711 N ILE C 129 -41.398 25.868 -3.906 1.00 81.57 N
ATOM 5712 CA ILE C 129 -42.378 25.964 -4.995 1.00 82.62 C
ATOM 5713 C ILE C 129 -43.511 24.920 -4.911 1.00 83.95 C
ATOM 5714 O ILE C 129 -44.165 24.609 -5.913 1.00 83.15 O
ATOM 5715 CB ILE C 129 -41.637 25.879 -6.390 1.00 81.91 C
ATOM 5716 CG1 ILE C 129 -42.613 26.114 -7.531 1.00 81.40 C
ATOM 5717 CG2 ILE C 129 -40.929 24.532 -6.542 1.00 80.22 C
ATOM 5718 CD1 ILE C 129 -43.354 27.409 -7.411 1.00 82.11 C
ATOM 5719 N ASN C 130 -43.748 24.406 -3.703 1.00 85.83 N
ATOM 5720 CA ASN C 130 -44.803 23.429 -3.474 1.00 86.95 C
ATOM 5721 C ASN C 130 -46.153 24.122 -3.347 1.00 87.55 C
ATOM 5722 O ASN C 130 -46.242 25.293 -2.977 1.00 87.00 O
ATOM 5723 CB ASN C 130 -44.540 22.603 -2.203 1.00 88.13 C
ATOM 5724 CG ASN C 130 -43.678 21.370 -2.464 1.00 90.24 C
ATOM 5725 OD1 ASN C 130 -43.803 20.715 -3.503 1.00 91.56 O
ATOM 5726 ND2 ASN C 130 -42.812 21.038 -1.510 1.00 91.70 N
ATOM 5727 N THR C 131 -47.203 23.379 -3.663 1.00 88.52 N
ATOM 5728 CA THR C 131 -48.559 23.882 -3.599 1.00 88.78 C
ATOM 5729 C THR C 131 -49.300 23.181 -2.465 1.00 90.67 C
ATOM 5730 O THR C 131 -48.818 22.184 -1.909 1.00 89.83 O
ATOM 5731 CB THR C 131 -49.278 23.599 -4.908 1.00 87.72 C
ATOM 5732 OG1 THR C 131 -49.353 22.179 -5.108 1.00 86.20 O
ATOM 5733 CG2 THR C 131 -48.519 24.228 -6.060 1.00 87.64 C
ATOM 5734 N PRO C 132 -50.483 23.701 -2.103 1.00 92.13 N
ATOM 5735 CA PRO C 132 -51.328 23.150 -1.034 1.00 92.76 C
ATOM 5736 C PRO C 132 -51.606 21.666 -1.282 1.00 92.59 C
ATOM 5737 O PRO C 132 -51.990 20.914 -0.375 1.00 91.94 O
ATOM 5738 CB PRO C 132 -52.599 23.997 -1.134 1.00 93.72 C
ATOM 5739 CG PRO C 132 -52.085 25.325 -1.635 1.00 92.98 C
ATOM 5740 CD PRO C 132 -51.104 24.902 -2.696 1.00 92.38 C
ATOM 5741 N LEU C 133 -51.402 21.280 -2.539 1.00 92.49 N
ATOM 5742 CA LEU C 133 -51.611 19.923 -3.030 1.00 92.47 C
ATOM 5743 C LEU C 133 -50.386 19.063 -2.764 1.00 92.31 C
ATOM 5744 O LEU C 133 -50.488 17.937 -2.266 1.00 92.59 O
ATOM 5745 CB LEU C 133 -51.864 19.961 -4.540 1.00 92.42 C
ATOM 5746 CG LEU C 133 -52.849 21.015 -5.052 1.00 93.22 C
ATOM 5747 CD1 LEU C 133 -52.945 20.924 -6.573 1.00 92.74 C
ATOM 5748 CD2 LEU C 133 -54.215 20.807 -4.397 1.00 93.47 C
ATOM 5749 N THR C 134 -49.228 19.615 -3.111 1.00 91.80 N
ATOM 5750 CA THR C 134 -47.943 18.943 -2.956 1.00 90.29 C
ATOM 5751 C THR C 134 -47.434 18.849 -1.513 1.00 88.61 C
ATOM 5752 O THR C 134 -47.287 17.756 -0.973 1.00 87.36 O
ATOM 5753 CB THR C 134 -46.892 19.667 -3.791 1.00 90.62 C
ATOM 5754 OG1 THR C 134 -46.794 21.019 -3.336 1.00 91.28 O
ATOM 5755 CG2 THR C 134 -47.291 19.679 -5.256 1.00 89.53 C
ATOM 5756 N THR C 135 -47.164 20.001 -0.908 1.00 87.08 N
ATOM 5757 CA THR C 135 -46.653 20.066 0.459 1.00 87.00 C
ATOM 5758 C THR C 135 -47.089 18.937 1.375 1.00 86.71 C
ATOM 5759 O THR C 135 -48.257 18.572 1.404 1.00 86.97 O
ATOM 5760 CB THR C 135 -47.060 21.362 1.162 1.00 86.89 C
ATOM 5761 OG1 THR C 135 -48.417 21.673 0.832 1.00 85.36 O
ATOM 5762 CG2 THR C 135 -46.140 22.505 0.769 1.00 87.48 C
ATOM 5763 N SER C 136 -46.129 18.392 2.117 1.00 86.78 N
ATOM 5764 CA SER C 136 -46.392 17.343 3.089 1.00 87.04 C
ATOM 5765 C SER C 136 -46.449 18.097 4.398 1.00 88.13 C
ATOM 5766 O SER C 136 -46.087 17.581 5.454 1.00 88.17 O
ATOM 5767 CB SER C 136 -45.259 16.320 3.141 1.00 86.80 C
ATOM 5768 OG SER C 136 -45.393 15.348 2.125 1.00 87.18 O
ATOM 5769 N SER C 137 -46.885 19.348 4.298 1.00 89.21 N
ATOM 5770 CA SER C 137 -47.011 20.223 5.452 1.00 91.19 C
ATOM 5771 C SER C 137 -47.723 21.484 4.992 1.00 91.93 C
ATOM 5772 O SER C 137 -47.570 21.909 3.845 1.00 90.67 O
ATOM 5773 CB SER C 137 -45.628 20.572 6.004 1.00 92.06 C
ATOM 5774 OG SER C 137 -44.859 21.268 5.024 1.00 93.47 O
ATOM 5775 N GLY C 138 -48.506 22.072 5.890 1.00 93.57 N
ATOM 5776 CA GLY C 138 -49.249 23.271 5.551 1.00 95.55 C
ATOM 5777 C GLY C 138 -48.429 24.524 5.762 1.00 96.50 C
ATOM 5778 O GLY C 138 -48.951 25.648 5.804 1.00 97.48 O
ATOM 5779 N ASN C 139 -47.125 24.308 5.887 1.00 96.37 N
ATOM 5780 CA ASN C 139 -46.151 25.367 6.105 1.00 95.32 C
ATOM 5781 C ASN C 139 -45.978 26.173 4.817 1.00 94.83 C
ATOM 5782 O ASN C 139 -45.139 25.865 3.964 1.00 94.93 O
ATOM 5783 CB ASN C 139 -44.837 24.724 6.534 1.00 95.07 C
ATOM 5784 CG ASN C 139 -45.049 23.591 7.532 1.00 95.16 C
ATOM 5785 OD1 ASN C 139 -46.031 22.842 7.450 1.00 96.11 O
ATOM 5786 ND2 ASN C 139 -44.124 23.450 8.470 1.00 95.53 N
ATOM 5787 N LEU C 140 -46.791 27.208 4.685 1.00 93.89 N
ATOM 5788 CA LEU C 140 -46.753 28.057 3.511 1.00 94.05 C
ATOM 5789 C LEU C 140 -45.395 28.696 3.218 1.00 94.50 C
ATOM 5790 O LEU C 140 -45.225 29.317 2.166 1.00 94.62 O
ATOM 5791 CB LEU C 140 -47.826 29.138 3.629 1.00 93.18 C
ATOM 5792 CG LEU C 140 -49.252 28.630 3.457 1.00 91.51 C
ATOM 5793 CD1 LEU C 140 -50.188 29.487 4.269 1.00 91.57 C
ATOM 5794 CD2 LEU C 140 -49.624 28.627 1.981 1.00 89.96 C
ATOM 5795 N HIS C 141 -44.431 28.558 4.132 1.00 94.12 N
ATOM 5796 CA HIS C 141 -43.105 29.133 3.891 1.00 93.21 C
ATOM 5797 C HIS C 141 -42.415 28.289 2.826 1.00 93.53 C
ATOM 5798 O HIS C 141 -41.284 28.571 2.426 1.00 93.63 O
ATOM 5799 CB HIS C 141 -42.253 29.175 5.177 1.00 90.47 C
ATOM 5800 CG HIS C 141 -41.694 27.846 5.602 1.00 88.47 C
ATOM 5801 ND1 HIS C 141 -40.829 27.718 6.665 1.00 86.91 N
ATOM 5802 CD2 HIS C 141 -41.875 26.596 5.109 1.00 87.52 C
ATOM 5803 CE1 HIS C 141 -40.498 26.445 6.810 1.00 86.12 C
ATOM 5804 NE2 HIS C 141 -41.118 25.744 5.879 1.00 85.96 N
ATOM 5805 N GLY C 142 -43.113 27.244 2.385 1.00 93.98 N
ATOM 5806 CA GLY C 142 -42.584 26.354 1.368 1.00 95.37 C
ATOM 5807 C GLY C 142 -43.467 26.325 0.131 1.00 96.23 C
ATOM 5808 O GLY C 142 -43.521 25.317 -0.580 1.00 95.98 O
ATOM 5809 N GLN C 143 -44.150 27.444 -0.113 1.00 96.91 N
ATOM 5810 CA GLN C 143 -45.061 27.617 -1.244 1.00 97.13 C
ATOM 5811 C GLN C 143 -45.019 29.008 -1.918 1.00 97.15 C
ATOM 5812 O GLN C 143 -45.469 29.163 -3.051 1.00 96.46 O
ATOM 5813 CB GLN C 143 -46.487 27.322 -0.778 1.00 97.37 C
ATOM 5814 CG GLN C 143 -46.639 25.922 -0.202 1.00 98.88 C
ATOM 5815 CD GLN C 143 -48.016 25.652 0.379 1.00 99.70 C
ATOM 5816 OE1 GLN C 143 -49.036 25.846 -0.283 1.00 98.74 O
ATOM 5817 NE2 GLN C 143 -48.048 25.186 1.624 1.00100.53 N
ATOM 5818 N PRO C 144 -44.454 30.025 -1.242 1.00 97.65 N
ATOM 5819 CA PRO C 144 -44.364 31.390 -1.770 1.00 97.32 C
ATOM 5820 C PRO C 144 -44.320 31.605 -3.277 1.00 96.74 C
ATOM 5821 O PRO C 144 -44.925 32.546 -3.786 1.00 96.95 O
ATOM 5822 CB PRO C 144 -43.120 31.937 -1.080 1.00 97.93 C
ATOM 5823 CG PRO C 144 -43.234 31.335 0.268 1.00 98.75 C
ATOM 5824 CD PRO C 144 -43.587 29.896 -0.053 1.00 98.52 C
ATOM 5825 N VAL C 145 -43.601 30.755 -3.996 1.00 96.76 N
ATOM 5826 CA VAL C 145 -43.504 30.931 -5.443 1.00 96.67 C
ATOM 5827 C VAL C 145 -44.789 30.483 -6.138 1.00 95.18 C
ATOM 5828 O VAL C 145 -45.204 31.069 -7.143 1.00 94.04 O
ATOM 5829 CB VAL C 145 -42.282 30.155 -6.027 1.00 97.80 C
ATOM 5830 CG1 VAL C 145 -42.163 30.416 -7.521 1.00 97.24 C
ATOM 5831 CG2 VAL C 145 -40.993 30.585 -5.322 1.00 97.02 C
ATOM 5832 N ALA C 146 -45.415 29.449 -5.582 1.00 94.06 N
ATOM 5833 CA ALA C 146 -46.653 28.898 -6.121 1.00 93.54 C
ATOM 5834 C ALA C 146 -47.802 29.917 -6.100 1.00 93.29 C
ATOM 5835 O ALA C 146 -48.802 29.761 -6.813 1.00 93.69 O
ATOM 5836 CB ALA C 146 -47.041 27.640 -5.339 1.00 92.75 C
ATOM 5837 N PHE C 147 -47.660 30.955 -5.282 1.00 91.80 N
ATOM 5838 CA PHE C 147 -48.676 31.995 -5.189 1.00 89.97 C
ATOM 5839 C PHE C 147 -48.355 33.143 -6.119 1.00 88.94 C
ATOM 5840 O PHE C 147 -49.247 33.838 -6.600 1.00 88.67 O
ATOM 5841 CB PHE C 147 -48.764 32.532 -3.769 1.00 90.00 C
ATOM 5842 CG PHE C 147 -49.477 31.625 -2.840 1.00 90.95 C
ATOM 5843 CD1 PHE C 147 -48.885 30.446 -2.413 1.00 91.17 C
ATOM 5844 CD2 PHE C 147 -50.769 31.923 -2.425 1.00 91.91 C
ATOM 5845 CE1 PHE C 147 -49.572 29.568 -1.578 1.00 92.42 C
ATOM 5846 CE2 PHE C 147 -51.469 31.057 -1.594 1.00 92.68 C
ATOM 5847 CZ PHE C 147 -50.871 29.873 -1.168 1.00 92.65 C
ATOM 5848 N LEU C 148 -47.068 33.333 -6.366 1.00 88.06 N
ATOM 5849 CA LEU C 148 -46.603 34.412 -7.212 1.00 87.82 C
ATOM 5850 C LEU C 148 -46.560 34.009 -8.678 1.00 89.07 C
ATOM 5851 O LEU C 148 -46.613 34.853 -9.577 1.00 88.06 O
ATOM 5852 CB LEU C 148 -45.224 34.851 -6.727 1.00 85.29 C
ATOM 5853 CG LEU C 148 -45.223 35.166 -5.232 1.00 82.72 C
ATOM 5854 CD1 LEU C 148 -43.823 35.460 -4.751 1.00 81.84 C
ATOM 5855 CD2 LEU C 148 -46.134 36.345 -4.982 1.00 82.23 C
ATOM 5856 N LEU C 149 -46.472 32.708 -8.916 1.00 91.44 N
ATOM 5857 CA LEU C 149 -46.421 32.204 -10.277 1.00 94.48 C
ATOM 5858 C LEU C 149 -47.781 32.193 -10.955 1.00 96.57 C
ATOM 5859 O LEU C 149 -48.803 31.855 -10.342 1.00 96.50 O
ATOM 5860 CB LEU C 149 -45.843 30.786 -10.308 1.00 93.94 C
ATOM 5861 CG LEU C 149 -44.332 30.616 -10.440 1.00 93.30 C
ATOM 5862 CD1 LEU C 149 -44.038 29.135 -10.550 1.00 92.84 C
ATOM 5863 CD2 LEU C 149 -43.807 31.355 -11.677 1.00 93.57 C
ATOM 5864 N LYS C 150 -47.773 32.561 -12.233 1.00 98.82 N
ATOM 5865 CA LYS C 150 -48.980 32.583 -13.049 1.00100.82 C
ATOM 5866 C LYS C 150 -49.235 31.158 -13.556 1.00101.32 C
ATOM 5867 O LYS C 150 -50.357 30.650 -13.477 1.00101.72 O
ATOM 5868 CB LYS C 150 -48.797 33.541 -14.233 1.00101.79 C
ATOM 5869 CG LYS C 150 -48.401 34.963 -13.835 1.00102.99 C
ATOM 5870 CD LYS C 150 -48.169 35.853 -15.056 1.00103.99 C
ATOM 5871 CE LYS C 150 -47.788 37.278 -14.641 1.00104.51 C
ATOM 5872 NZ LYS C 150 -47.582 38.203 -15.802 1.00104.60 N
ATOM 5873 N GLU C 151 -48.182 30.515 -14.059 1.00101.60 N
ATOM 5874 CA GLU C 151 -48.272 29.154 -14.579 1.00102.29 C
ATOM 5875 C GLU C 151 -48.759 28.179 -13.523 1.00102.54 C
ATOM 5876 O GLU C 151 -48.884 26.982 -13.781 1.00102.16 O
ATOM 5877 CB GLU C 151 -46.911 28.683 -15.089 1.00102.95 C
ATOM 5878 CG GLU C 151 -46.352 29.485 -16.248 1.00104.96 C
ATOM 5879 CD GLU C 151 -45.497 30.652 -15.801 1.00106.23 C
ATOM 5880 OE1 GLU C 151 -46.005 31.524 -15.066 1.00107.34 O
ATOM 5881 OE2 GLU C 151 -44.311 30.697 -16.191 1.00107.33 O
ATOM 5882 N LEU C 152 -49.034 28.692 -12.334 1.00102.97 N
ATOM 5883 CA LEU C 152 -49.496 27.852 -11.249 1.00104.39 C
ATOM 5884 C LEU C 152 -50.868 28.281 -10.762 1.00105.77 C
ATOM 5885 O LEU C 152 -51.474 27.621 -9.913 1.00105.76 O
ATOM 5886 CB LEU C 152 -48.491 27.904 -10.103 1.00104.29 C
ATOM 5887 CG LEU C 152 -47.813 26.586 -9.726 1.00104.15 C
ATOM 5888 CD1 LEU C 152 -47.527 25.743 -10.955 1.00103.71 C
ATOM 5889 CD2 LEU C 152 -46.535 26.911 -8.985 1.00104.71 C
ATOM 5890 N LYS C 153 -51.355 29.394 -11.303 1.00107.04 N
ATOM 5891 CA LYS C 153 -52.664 29.910 -10.923 1.00107.67 C
ATOM 5892 C LYS C 153 -53.733 28.891 -11.305 1.00107.92 C
ATOM 5893 O LYS C 153 -53.634 28.223 -12.341 1.00108.76 O
ATOM 5894 CB LYS C 153 -52.933 31.246 -11.623 1.00107.80 C
ATOM 5895 CG LYS C 153 -54.234 31.920 -11.208 1.00108.64 C
ATOM 5896 CD LYS C 153 -54.395 33.289 -11.867 1.00109.46 C
ATOM 5897 CE LYS C 153 -55.763 33.913 -11.570 1.00110.70 C
ATOM 5898 NZ LYS C 153 -56.001 34.178 -10.115 1.00111.92 N
ATOM 5899 N GLY C 154 -54.746 28.765 -10.454 1.00107.54 N
ATOM 5900 CA GLY C 154 -55.813 27.824 -10.720 1.00107.33 C
ATOM 5901 C GLY C 154 -55.285 26.411 -10.852 1.00107.30 C
ATOM 5902 O GLY C 154 -55.922 25.558 -11.470 1.00108.46 O
ATOM 5903 N LYS C 155 -54.108 26.166 -10.287 1.00106.64 N
ATOM 5904 CA LYS C 155 -53.507 24.840 -10.323 1.00105.81 C
ATOM 5905 C LYS C 155 -53.682 24.215 -8.940 1.00105.92 C
ATOM 5906 O LYS C 155 -53.170 23.129 -8.656 1.00105.68 O
ATOM 5907 CB LYS C 155 -52.025 24.939 -10.694 1.00104.96 C
ATOM 5908 CG LYS C 155 -51.778 25.459 -12.099 1.00103.47 C
ATOM 5909 CD LYS C 155 -52.336 24.498 -13.132 1.00104.34 C
ATOM 5910 CE LYS C 155 -52.188 25.043 -14.548 1.00104.97 C
ATOM 5911 NZ LYS C 155 -52.695 24.084 -15.580 1.00103.63 N
ATOM 5912 N PHE C 156 -54.421 24.928 -8.091 1.00106.22 N
ATOM 5913 CA PHE C 156 -54.719 24.499 -6.727 1.00106.40 C
ATOM 5914 C PHE C 156 -55.875 25.320 -6.128 1.00106.38 C
ATOM 5915 O PHE C 156 -56.113 26.466 -6.528 1.00105.46 O
ATOM 5916 CB PHE C 156 -53.461 24.597 -5.838 1.00107.04 C
ATOM 5917 CG PHE C 156 -52.809 25.965 -5.820 1.00107.71 C
ATOM 5918 CD1 PHE C 156 -52.304 26.539 -6.992 1.00107.58 C
ATOM 5919 CD2 PHE C 156 -52.682 26.669 -4.622 1.00106.90 C
ATOM 5920 CE1 PHE C 156 -51.683 27.788 -6.968 1.00106.82 C
ATOM 5921 CE2 PHE C 156 -52.064 27.913 -4.586 1.00106.77 C
ATOM 5922 CZ PHE C 156 -51.563 28.476 -5.763 1.00107.12 C
ATOM 5923 N PRO C 157 -56.615 24.732 -5.166 1.00106.61 N
ATOM 5924 CA PRO C 157 -57.749 25.398 -4.511 1.00106.37 C
ATOM 5925 C PRO C 157 -57.407 26.719 -3.839 1.00106.46 C
ATOM 5926 O PRO C 157 -56.606 26.762 -2.904 1.00106.53 O
ATOM 5927 CB PRO C 157 -58.236 24.349 -3.509 1.00106.35 C
ATOM 5928 CG PRO C 157 -56.986 23.582 -3.179 1.00106.43 C
ATOM 5929 CD PRO C 157 -56.363 23.417 -4.547 1.00106.79 C
ATOM 5930 N ASP C 158 -58.026 27.793 -4.323 1.00106.90 N
ATOM 5931 CA ASP C 158 -57.803 29.126 -3.772 1.00106.90 C
ATOM 5932 C ASP C 158 -57.690 29.006 -2.255 1.00107.41 C
ATOM 5933 O ASP C 158 -58.492 28.327 -1.603 1.00107.55 O
ATOM 5934 CB ASP C 158 -58.953 30.053 -4.170 1.00104.94 C
ATOM 5935 CG ASP C 158 -59.260 29.977 -5.652 1.00104.15 C
ATOM 5936 OD1 ASP C 158 -58.323 30.151 -6.465 1.00103.27 O
ATOM 5937 OD2 ASP C 158 -60.431 29.735 -6.009 1.00103.26 O
ATOM 5938 N VAL C 159 -56.681 29.658 -1.696 1.00107.49 N
ATOM 5939 CA VAL C 159 -56.446 29.572 -0.267 1.00107.43 C
ATOM 5940 C VAL C 159 -57.010 30.724 0.559 1.00105.92 C
ATOM 5941 O VAL C 159 -56.914 31.896 0.175 1.00105.41 O
ATOM 5942 CB VAL C 159 -54.929 29.422 0.016 1.00108.72 C
ATOM 5943 CG1 VAL C 159 -54.687 29.201 1.509 1.00109.55 C
ATOM 5944 CG2 VAL C 159 -54.367 28.256 -0.800 1.00109.32 C
ATOM 5945 N PRO C 160 -57.615 30.386 1.712 1.00104.72 N
ATOM 5946 CA PRO C 160 -58.236 31.280 2.691 1.00104.41 C
ATOM 5947 C PRO C 160 -57.314 32.357 3.252 1.00103.98 C
ATOM 5948 O PRO C 160 -56.639 32.140 4.261 1.00103.74 O
ATOM 5949 CB PRO C 160 -58.710 30.319 3.775 1.00103.93 C
ATOM 5950 CG PRO C 160 -59.068 29.116 2.996 1.00103.63 C
ATOM 5951 CD PRO C 160 -57.901 28.982 2.058 1.00104.02 C
ATOM 5952 N GLY C 161 -57.301 33.515 2.596 1.00103.53 N
ATOM 5953 CA GLY C 161 -56.485 34.622 3.054 1.00103.26 C
ATOM 5954 C GLY C 161 -55.585 35.216 1.993 1.00103.11 C
ATOM 5955 O GLY C 161 -55.055 36.315 2.165 1.00102.78 O
ATOM 5956 N PHE C 162 -55.428 34.506 0.881 1.00102.76 N
ATOM 5957 CA PHE C 162 -54.552 34.968 -0.185 1.00102.25 C
ATOM 5958 C PHE C 162 -55.310 35.403 -1.425 1.00101.97 C
ATOM 5959 O PHE C 162 -54.764 35.424 -2.526 1.00101.94 O
ATOM 5960 CB PHE C 162 -53.559 33.860 -0.522 1.00101.45 C
ATOM 5961 CG PHE C 162 -52.942 33.233 0.692 1.00101.08 C
ATOM 5962 CD1 PHE C 162 -53.709 32.445 1.550 1.00100.76 C
ATOM 5963 CD2 PHE C 162 -51.610 33.465 1.010 1.00101.58 C
ATOM 5964 CE1 PHE C 162 -53.163 31.905 2.706 1.00100.12 C
ATOM 5965 CE2 PHE C 162 -51.052 32.928 2.169 1.00101.83 C
ATOM 5966 CZ PHE C 162 -51.834 32.146 3.018 1.00101.45 C
ATOM 5967 N SER C 163 -56.574 35.754 -1.236 1.00102.29 N
ATOM 5968 CA SER C 163 -57.417 36.206 -2.335 1.00102.63 C
ATOM 5969 C SER C 163 -56.718 37.357 -3.069 1.00102.57 C
ATOM 5970 O SER C 163 -56.464 37.277 -4.273 1.00102.59 O
ATOM 5971 CB SER C 163 -58.767 36.668 -1.783 1.00102.37 C
ATOM 5972 OG SER C 163 -59.335 35.663 -0.956 1.00101.02 O
ATOM 5973 N TRP C 164 -56.401 38.409 -2.314 1.00102.49 N
ATOM 5974 CA TRP C 164 -55.719 39.619 -2.802 1.00101.47 C
ATOM 5975 C TRP C 164 -54.440 39.334 -3.596 1.00 99.77 C
ATOM 5976 O TRP C 164 -53.917 40.208 -4.291 1.00 98.35 O
ATOM 5977 CB TRP C 164 -55.358 40.500 -1.607 1.00103.47 C
ATOM 5978 CG TRP C 164 -54.560 39.743 -0.573 1.00106.13 C
ATOM 5979 CD1 TRP C 164 -55.048 38.997 0.470 1.00106.71 C
ATOM 5980 CD2 TRP C 164 -53.135 39.592 -0.545 1.00106.44 C
ATOM 5981 NE1 TRP C 164 -54.008 38.395 1.145 1.00106.48 N
ATOM 5982 CE2 TRP C 164 -52.834 38.746 0.553 1.00106.26 C
ATOM 5983 CE3 TRP C 164 -52.092 40.099 -1.326 1.00106.62 C
ATOM 5984 CZ2 TRP C 164 -51.521 38.388 0.864 1.00106.64 C
ATOM 5985 CZ3 TRP C 164 -50.791 39.741 -1.010 1.00106.79 C
ATOM 5986 CH2 TRP C 164 -50.518 38.898 0.083 1.00107.31 C
ATOM 5987 N VAL C 165 -53.931 38.114 -3.470 1.00 98.45 N
ATOM 5988 CA VAL C 165 -52.722 37.714 -4.167 1.00 97.02 C
ATOM 5989 C VAL C 165 -52.978 37.523 -5.654 1.00 96.57 C
ATOM 5990 O VAL C 165 -53.953 36.888 -6.055 1.00 95.58 O
ATOM 5991 CB VAL C 165 -52.166 36.410 -3.592 1.00 96.60 C
ATOM 5992 CG1 VAL C 165 -50.889 36.029 -4.312 1.00 96.25 C
ATOM 5993 CG2 VAL C 165 -51.925 36.573 -2.104 1.00 95.83 C
ATOM 5994 N THR C 166 -52.082 38.073 -6.466 1.00 96.74 N
ATOM 5995 CA THR C 166 -52.193 37.984 -7.916 1.00 96.80 C
ATOM 5996 C THR C 166 -50.917 37.413 -8.530 1.00 96.74 C
ATOM 5997 O THR C 166 -49.866 38.056 -8.498 1.00 96.41 O
ATOM 5998 CB THR C 166 -52.430 39.376 -8.537 1.00 96.99 C
ATOM 5999 OG1 THR C 166 -53.440 40.065 -7.793 1.00 97.70 O
ATOM 6000 CG2 THR C 166 -52.873 39.248 -9.997 1.00 96.21 C
ATOM 6001 N PRO C 167 -50.993 36.190 -9.087 1.00 96.68 N
ATOM 6002 CA PRO C 167 -49.814 35.573 -9.706 1.00 97.04 C
ATOM 6003 C PRO C 167 -49.160 36.630 -10.588 1.00 97.98 C
ATOM 6004 O PRO C 167 -49.699 36.990 -11.633 1.00 98.54 O
ATOM 6005 CB PRO C 167 -50.422 34.429 -10.499 1.00 96.70 C
ATOM 6006 CG PRO C 167 -51.560 33.991 -9.597 1.00 96.21 C
ATOM 6007 CD PRO C 167 -52.171 35.306 -9.176 1.00 95.91 C
ATOM 6008 N CYS C 168 -47.999 37.122 -10.160 1.00 99.21 N
ATOM 6009 CA CYS C 168 -47.297 38.195 -10.869 1.00100.39 C
ATOM 6010 C CYS C 168 -46.129 37.901 -11.819 1.00100.22 C
ATOM 6011 O CYS C 168 -45.781 38.759 -12.628 1.00100.36 O
ATOM 6012 CB CYS C 168 -46.849 39.251 -9.850 1.00101.41 C
ATOM 6013 SG CYS C 168 -46.011 38.580 -8.396 1.00102.86 S
ATOM 6014 N ILE C 169 -45.499 36.734 -11.730 1.00100.14 N
ATOM 6015 CA ILE C 169 -44.393 36.450 -12.650 1.00 99.43 C
ATOM 6016 C ILE C 169 -44.377 35.016 -13.152 1.00100.06 C
ATOM 6017 O ILE C 169 -44.802 34.086 -12.461 1.00 99.94 O
ATOM 6018 CB ILE C 169 -43.003 36.764 -12.027 1.00 97.80 C
ATOM 6019 CG1 ILE C 169 -42.736 35.850 -10.828 1.00 97.02 C
ATOM 6020 CG2 ILE C 169 -42.926 38.225 -11.632 1.00 97.30 C
ATOM 6021 CD1 ILE C 169 -43.743 35.960 -9.704 1.00 96.20 C
ATOM 6022 N SER C 170 -43.898 34.850 -14.378 1.00100.49 N
ATOM 6023 CA SER C 170 -43.805 33.536 -14.987 1.00101.32 C
ATOM 6024 C SER C 170 -42.440 32.925 -14.645 1.00101.91 C
ATOM 6025 O SER C 170 -41.592 33.589 -14.039 1.00102.46 O
ATOM 6026 CB SER C 170 -44.005 33.654 -16.502 1.00100.78 C
ATOM 6027 OG SER C 170 -43.292 34.748 -17.040 1.00100.26 O
ATOM 6028 N ALA C 171 -42.232 31.667 -15.022 1.00101.63 N
ATOM 6029 CA ALA C 171 -40.974 30.980 -14.735 1.00101.52 C
ATOM 6030 C ALA C 171 -39.808 31.531 -15.558 1.00101.47 C
ATOM 6031 O ALA C 171 -38.653 31.133 -15.379 1.00101.00 O
ATOM 6032 CB ALA C 171 -41.138 29.487 -14.991 1.00101.29 C
ATOM 6033 N LYS C 172 -40.119 32.459 -16.451 1.00101.77 N
ATOM 6034 CA LYS C 172 -39.106 33.053 -17.303 1.00102.19 C
ATOM 6035 C LYS C 172 -38.432 34.257 -16.656 1.00100.80 C
ATOM 6036 O LYS C 172 -37.487 34.822 -17.211 1.00100.93 O
ATOM 6037 CB LYS C 172 -39.737 33.449 -18.644 1.00104.75 C
ATOM 6038 CG LYS C 172 -39.429 32.471 -19.786 1.00107.35 C
ATOM 6039 CD LYS C 172 -39.637 31.000 -19.385 1.00107.90 C
ATOM 6040 CE LYS C 172 -39.005 30.055 -20.413 1.00108.26 C
ATOM 6041 NZ LYS C 172 -38.998 28.625 -19.986 1.00107.62 N
ATOM 6042 N ASP C 173 -38.909 34.637 -15.475 1.00 98.57 N
ATOM 6043 CA ASP C 173 -38.343 35.782 -14.775 1.00 95.87 C
ATOM 6044 C ASP C 173 -37.755 35.431 -13.405 1.00 92.84 C
ATOM 6045 O ASP C 173 -37.124 36.275 -12.763 1.00 92.74 O
ATOM 6046 CB ASP C 173 -39.406 36.879 -14.612 1.00 97.37 C
ATOM 6047 CG ASP C 173 -40.050 37.277 -15.933 1.00 97.26 C
ATOM 6048 OD1 ASP C 173 -39.316 37.584 -16.900 1.00 95.86 O
ATOM 6049 OD2 ASP C 173 -41.300 37.286 -15.993 1.00 98.11 O
ATOM 6050 N ILE C 174 -37.961 34.188 -12.968 1.00 89.13 N
ATOM 6051 CA ILE C 174 -37.449 33.709 -11.678 1.00 83.93 C
ATOM 6052 C ILE C 174 -36.171 32.885 -11.834 1.00 80.70 C
ATOM 6053 O ILE C 174 -36.029 32.139 -12.795 1.00 80.98 O
ATOM 6054 CB ILE C 174 -38.489 32.816 -10.953 1.00 82.90 C
ATOM 6055 CG1 ILE C 174 -37.888 32.249 -9.672 1.00 81.94 C
ATOM 6056 CG2 ILE C 174 -38.906 31.668 -11.838 1.00 82.20 C
ATOM 6057 CD1 ILE C 174 -37.434 33.312 -8.713 1.00 82.59 C
ATOM 6058 N VAL C 175 -35.238 33.033 -10.895 1.00 77.49 N
ATOM 6059 CA VAL C 175 -33.985 32.269 -10.918 1.00 74.17 C
ATOM 6060 C VAL C 175 -33.581 31.836 -9.499 1.00 71.60 C
ATOM 6061 O VAL C 175 -33.419 32.664 -8.596 1.00 70.28 O
ATOM 6062 CB VAL C 175 -32.811 33.070 -11.575 1.00 73.83 C
ATOM 6063 CG1 VAL C 175 -31.533 32.241 -11.556 1.00 72.13 C
ATOM 6064 CG2 VAL C 175 -33.160 33.422 -13.002 1.00 71.71 C
ATOM 6065 N TYR C 176 -33.430 30.525 -9.328 1.00 68.81 N
ATOM 6066 CA TYR C 176 -33.060 29.914 -8.056 1.00 65.95 C
ATOM 6067 C TYR C 176 -31.571 29.658 -7.976 1.00 66.00 C
ATOM 6068 O TYR C 176 -30.980 29.178 -8.943 1.00 66.47 O
ATOM 6069 CB TYR C 176 -33.743 28.570 -7.917 1.00 63.07 C
ATOM 6070 CG TYR C 176 -35.182 28.610 -7.498 1.00 62.07 C
ATOM 6071 CD1 TYR C 176 -35.529 28.864 -6.182 1.00 61.02 C
ATOM 6072 CD2 TYR C 176 -36.191 28.239 -8.383 1.00 62.56 C
ATOM 6073 CE1 TYR C 176 -36.846 28.726 -5.743 1.00 60.83 C
ATOM 6074 CE2 TYR C 176 -37.515 28.095 -7.954 1.00 62.19 C
ATOM 6075 CZ TYR C 176 -37.833 28.333 -6.626 1.00 61.80 C
ATOM 6076 OH TYR C 176 -39.115 28.113 -6.168 1.00 61.14 O
ATOM 6077 N ILE C 177 -30.964 29.974 -6.835 1.00 66.80 N
ATOM 6078 CA ILE C 177 -29.533 29.710 -6.644 1.00 67.11 C
ATOM 6079 C ILE C 177 -29.345 29.110 -5.243 1.00 68.56 C
ATOM 6080 O ILE C 177 -29.829 29.668 -4.244 1.00 69.41 O
ATOM 6081 CB ILE C 177 -28.637 30.996 -6.761 1.00 65.54 C
ATOM 6082 CG1 ILE C 177 -29.263 32.022 -7.711 1.00 65.06 C
ATOM 6083 CG2 ILE C 177 -27.263 30.625 -7.310 1.00 61.44 C
ATOM 6084 CD1 ILE C 177 -28.408 33.255 -7.927 1.00 62.70 C
ATOM 6085 N GLY C 178 -28.675 27.956 -5.181 1.00 68.46 N
ATOM 6086 CA GLY C 178 -28.411 27.307 -3.909 1.00 68.24 C
ATOM 6087 C GLY C 178 -29.284 26.110 -3.568 1.00 68.59 C
ATOM 6088 O GLY C 178 -29.184 25.574 -2.453 1.00 68.65 O
ATOM 6089 N LEU C 179 -30.121 25.675 -4.511 1.00 67.99 N
ATOM 6090 CA LEU C 179 -31.016 24.535 -4.275 1.00 65.97 C
ATOM 6091 C LEU C 179 -30.246 23.243 -3.977 1.00 64.84 C
ATOM 6092 O LEU C 179 -29.312 22.861 -4.683 1.00 62.84 O
ATOM 6093 CB LEU C 179 -31.960 24.338 -5.473 1.00 63.88 C
ATOM 6094 CG LEU C 179 -32.747 25.595 -5.887 1.00 61.65 C
ATOM 6095 CD1 LEU C 179 -33.625 25.289 -7.091 1.00 60.43 C
ATOM 6096 CD2 LEU C 179 -33.573 26.094 -4.715 1.00 58.38 C
ATOM 6097 N ARG C 180 -30.650 22.573 -2.908 1.00 64.18 N
ATOM 6098 CA ARG C 180 -29.986 21.354 -2.513 1.00 63.57 C
ATOM 6099 C ARG C 180 -30.923 20.447 -1.726 1.00 65.71 C
ATOM 6100 O ARG C 180 -30.547 19.346 -1.344 1.00 67.12 O
ATOM 6101 CB ARG C 180 -28.742 21.698 -1.691 1.00 60.48 C
ATOM 6102 CG ARG C 180 -28.995 21.823 -0.206 1.00 58.48 C
ATOM 6103 CD ARG C 180 -27.780 22.311 0.545 1.00 55.45 C
ATOM 6104 NE ARG C 180 -27.593 23.716 0.259 1.00 58.34 N
ATOM 6105 CZ ARG C 180 -27.527 24.676 1.175 1.00 60.04 C
ATOM 6106 NH1 ARG C 180 -27.621 24.388 2.468 1.00 58.90 N
ATOM 6107 NH2 ARG C 180 -27.403 25.942 0.782 1.00 60.12 N
ATOM 6108 N ASP C 181 -32.141 20.907 -1.475 1.00 68.57 N
ATOM 6109 CA ASP C 181 -33.122 20.084 -0.764 1.00 72.38 C
ATOM 6110 C ASP C 181 -34.517 20.290 -1.374 1.00 73.65 C
ATOM 6111 O ASP C 181 -35.397 20.954 -0.800 1.00 72.86 O
ATOM 6112 CB ASP C 181 -33.115 20.416 0.734 1.00 74.74 C
ATOM 6113 CG ASP C 181 -34.318 19.832 1.468 1.00 76.50 C
ATOM 6114 OD1 ASP C 181 -34.798 18.754 1.052 1.00 76.76 O
ATOM 6115 OD2 ASP C 181 -34.769 20.451 2.462 1.00 77.76 O
ATOM 6116 N VAL C 182 -34.715 19.701 -2.550 1.00 75.62 N
ATOM 6117 CA VAL C 182 -35.979 19.851 -3.256 1.00 77.84 C
ATOM 6118 C VAL C 182 -36.890 18.642 -3.246 1.00 78.44 C
ATOM 6119 O VAL C 182 -36.466 17.544 -3.601 1.00 79.02 O
ATOM 6120 CB VAL C 182 -35.737 20.268 -4.718 1.00 78.31 C
ATOM 6121 CG1 VAL C 182 -36.843 19.734 -5.618 1.00 79.03 C
ATOM 6122 CG2 VAL C 182 -35.691 21.785 -4.807 1.00 79.08 C
ATOM 6123 N ASP C 183 -38.151 18.875 -2.866 1.00 79.14 N
ATOM 6124 CA ASP C 183 -39.180 17.837 -2.805 1.00 78.94 C
ATOM 6125 C ASP C 183 -39.618 17.348 -4.180 1.00 79.30 C
ATOM 6126 O ASP C 183 -39.540 18.082 -5.169 1.00 79.36 O
ATOM 6127 CB ASP C 183 -40.404 18.344 -2.042 1.00 78.05 C
ATOM 6128 CG ASP C 183 -40.178 18.381 -0.548 1.00 79.06 C
ATOM 6129 OD1 ASP C 183 -39.926 17.306 0.037 1.00 78.74 O
ATOM 6130 OD2 ASP C 183 -40.247 19.481 0.045 1.00 80.08 O
ATOM 6131 N PRO C 184 -40.092 16.092 -4.256 1.00 79.74 N
ATOM 6132 CA PRO C 184 -40.549 15.490 -5.513 1.00 80.29 C
ATOM 6133 C PRO C 184 -41.403 16.491 -6.289 1.00 81.42 C
ATOM 6134 O PRO C 184 -40.961 17.054 -7.295 1.00 81.63 O
ATOM 6135 CB PRO C 184 -41.365 14.290 -5.041 1.00 78.84 C
ATOM 6136 CG PRO C 184 -40.695 13.907 -3.784 1.00 78.62 C
ATOM 6137 CD PRO C 184 -40.448 15.234 -3.114 1.00 78.97 C
ATOM 6138 N GLY C 185 -42.621 16.709 -5.794 1.00 81.81 N
ATOM 6139 CA GLY C 185 -43.545 17.632 -6.423 1.00 82.31 C
ATOM 6140 C GLY C 185 -42.854 18.864 -6.954 1.00 82.89 C
ATOM 6141 O GLY C 185 -43.068 19.263 -8.096 1.00 82.84 O
ATOM 6142 N GLU C 186 -42.017 19.469 -6.121 1.00 83.40 N
ATOM 6143 CA GLU C 186 -41.291 20.655 -6.529 1.00 84.01 C
ATOM 6144 C GLU C 186 -40.413 20.404 -7.758 1.00 85.43 C
ATOM 6145 O GLU C 186 -40.388 21.227 -8.678 1.00 85.30 O
ATOM 6146 CB GLU C 186 -40.455 21.178 -5.360 1.00 82.52 C
ATOM 6147 CG GLU C 186 -41.201 22.154 -4.478 1.00 80.01 C
ATOM 6148 CD GLU C 186 -40.527 22.356 -3.147 1.00 80.52 C
ATOM 6149 OE1 GLU C 186 -40.402 21.351 -2.422 1.00 82.23 O
ATOM 6150 OE2 GLU C 186 -40.128 23.499 -2.821 1.00 79.04 O
ATOM 6151 N HIS C 187 -39.705 19.273 -7.788 1.00 87.43 N
ATOM 6152 CA HIS C 187 -38.843 18.967 -8.931 1.00 89.34 C
ATOM 6153 C HIS C 187 -39.693 18.917 -10.193 1.00 91.26 C
ATOM 6154 O HIS C 187 -39.319 19.454 -11.241 1.00 91.25 O
ATOM 6155 CB HIS C 187 -38.119 17.630 -8.748 1.00 88.09 C
ATOM 6156 CG HIS C 187 -36.968 17.438 -9.693 1.00 87.99 C
ATOM 6157 ND1 HIS C 187 -36.223 16.285 -9.743 1.00 88.58 N
ATOM 6158 CD2 HIS C 187 -36.419 18.282 -10.601 1.00 87.65 C
ATOM 6159 CE1 HIS C 187 -35.258 16.422 -10.642 1.00 87.86 C
ATOM 6160 NE2 HIS C 187 -35.356 17.623 -11.174 1.00 86.86 N
ATOM 6161 N TYR C 188 -40.842 18.259 -10.073 1.00 93.24 N
ATOM 6162 CA TYR C 188 -41.792 18.125 -11.170 1.00 94.52 C
ATOM 6163 C TYR C 188 -42.043 19.524 -11.722 1.00 93.43 C
ATOM 6164 O TYR C 188 -41.693 19.837 -12.858 1.00 93.13 O
ATOM 6165 CB TYR C 188 -43.098 17.537 -10.632 1.00 97.75 C
ATOM 6166 CG TYR C 188 -44.121 17.192 -11.687 1.00101.26 C
ATOM 6167 CD1 TYR C 188 -43.908 16.131 -12.560 1.00102.84 C
ATOM 6168 CD2 TYR C 188 -45.303 17.922 -11.805 1.00103.00 C
ATOM 6169 CE1 TYR C 188 -44.843 15.801 -13.527 1.00105.63 C
ATOM 6170 CE2 TYR C 188 -46.251 17.601 -12.772 1.00105.61 C
ATOM 6171 CZ TYR C 188 -46.014 16.539 -13.632 1.00106.52 C
ATOM 6172 OH TYR C 188 -46.933 16.207 -14.604 1.00107.84 O
ATOM 6173 N ILE C 189 -42.639 20.352 -10.875 1.00 91.82 N
ATOM 6174 CA ILE C 189 -42.978 21.724 -11.192 1.00 89.96 C
ATOM 6175 C ILE C 189 -41.868 22.511 -11.885 1.00 89.45 C
ATOM 6176 O ILE C 189 -42.083 23.040 -12.971 1.00 90.11 O
ATOM 6177 CB ILE C 189 -43.397 22.464 -9.916 1.00 89.42 C
ATOM 6178 CG1 ILE C 189 -44.398 21.602 -9.144 1.00 89.61 C
ATOM 6179 CG2 ILE C 189 -44.017 23.798 -10.268 1.00 88.40 C
ATOM 6180 CD1 ILE C 189 -44.767 22.115 -7.754 1.00 90.14 C
ATOM 6181 N ILE C 190 -40.683 22.593 -11.282 1.00 88.36 N
ATOM 6182 CA ILE C 190 -39.589 23.349 -11.900 1.00 87.98 C
ATOM 6183 C ILE C 190 -39.159 22.836 -13.274 1.00 87.97 C
ATOM 6184 O ILE C 190 -38.780 23.623 -14.145 1.00 87.59 O
ATOM 6185 CB ILE C 190 -38.332 23.398 -11.000 1.00 87.07 C
ATOM 6186 CG1 ILE C 190 -38.038 22.009 -10.444 1.00 86.15 C
ATOM 6187 CG2 ILE C 190 -38.519 24.420 -9.895 1.00 86.59 C
ATOM 6188 CD1 ILE C 190 -36.833 21.976 -9.547 1.00 85.40 C
ATOM 6189 N LYS C 191 -39.201 21.522 -13.464 1.00 88.65 N
ATOM 6190 CA LYS C 191 -38.823 20.927 -14.743 1.00 88.53 C
ATOM 6191 C LYS C 191 -39.913 21.242 -15.762 1.00 88.10 C
ATOM 6192 O LYS C 191 -39.652 21.807 -16.829 1.00 88.34 O
ATOM 6193 CB LYS C 191 -38.693 19.411 -14.604 1.00 88.47 C
ATOM 6194 CG LYS C 191 -37.735 18.968 -13.527 1.00 88.98 C
ATOM 6195 CD LYS C 191 -36.335 19.509 -13.773 1.00 90.42 C
ATOM 6196 CE LYS C 191 -35.702 18.905 -15.021 1.00 91.22 C
ATOM 6197 NZ LYS C 191 -34.312 19.400 -15.257 1.00 91.30 N
ATOM 6198 N THR C 192 -41.139 20.865 -15.399 1.00 87.39 N
ATOM 6199 CA THR C 192 -42.321 21.066 -16.222 1.00 86.37 C
ATOM 6200 C THR C 192 -42.460 22.503 -16.674 1.00 85.11 C
ATOM 6201 O THR C 192 -42.466 22.783 -17.869 1.00 85.30 O
ATOM 6202 CB THR C 192 -43.599 20.691 -15.454 1.00 86.84 C
ATOM 6203 OG1 THR C 192 -43.662 19.268 -15.286 1.00 87.24 O
ATOM 6204 CG2 THR C 192 -44.831 21.173 -16.208 1.00 87.53 C
ATOM 6205 N LEU C 193 -42.582 23.405 -15.709 1.00 83.59 N
ATOM 6206 CA LEU C 193 -42.736 24.819 -15.997 1.00 81.81 C
ATOM 6207 C LEU C 193 -41.452 25.451 -16.474 1.00 81.47 C
ATOM 6208 O LEU C 193 -41.378 26.667 -16.607 1.00 82.12 O
ATOM 6209 CB LEU C 193 -43.219 25.567 -14.763 1.00 81.24 C
ATOM 6210 CG LEU C 193 -44.638 25.267 -14.291 1.00 80.57 C
ATOM 6211 CD1 LEU C 193 -44.763 23.807 -13.868 1.00 80.60 C
ATOM 6212 CD2 LEU C 193 -44.965 26.195 -13.135 1.00 80.83 C
ATOM 6213 N GLY C 194 -40.440 24.633 -16.729 1.00 80.95 N
ATOM 6214 CA GLY C 194 -39.176 25.170 -17.196 1.00 80.89 C
ATOM 6215 C GLY C 194 -38.723 26.401 -16.426 1.00 80.68 C
ATOM 6216 O GLY C 194 -38.871 27.527 -16.896 1.00 79.93 O
ATOM 6217 N ILE C 195 -38.167 26.177 -15.240 1.00 81.64 N
ATOM 6218 CA ILE C 195 -37.675 27.245 -14.377 1.00 81.78 C
ATOM 6219 C ILE C 195 -36.155 27.205 -14.336 1.00 82.29 C
ATOM 6220 O ILE C 195 -35.579 26.181 -13.955 1.00 82.81 O
ATOM 6221 CB ILE C 195 -38.193 27.065 -12.942 1.00 81.34 C
ATOM 6222 CG1 ILE C 195 -39.684 27.371 -12.895 1.00 81.48 C
ATOM 6223 CG2 ILE C 195 -37.399 27.938 -11.987 1.00 81.33 C
ATOM 6224 CD1 ILE C 195 -40.334 27.023 -11.576 1.00 82.56 C
ATOM 6225 N LYS C 196 -35.510 28.306 -14.723 1.00 82.10 N
ATOM 6226 CA LYS C 196 -34.048 28.367 -14.710 1.00 82.86 C
ATOM 6227 C LYS C 196 -33.552 28.357 -13.262 1.00 83.44 C
ATOM 6228 O LYS C 196 -33.980 29.172 -12.436 1.00 82.76 O
ATOM 6229 CB LYS C 196 -33.550 29.620 -15.430 1.00 82.66 C
ATOM 6230 CG LYS C 196 -32.041 29.767 -15.485 1.00 82.46 C
ATOM 6231 CD LYS C 196 -31.378 28.724 -16.372 1.00 83.91 C
ATOM 6232 CE LYS C 196 -29.900 29.091 -16.621 1.00 86.21 C
ATOM 6233 NZ LYS C 196 -29.061 28.082 -17.364 1.00 85.46 N
ATOM 6234 N TYR C 197 -32.656 27.416 -12.965 1.00 83.30 N
ATOM 6235 CA TYR C 197 -32.108 27.253 -11.621 1.00 82.70 C
ATOM 6236 C TYR C 197 -30.638 26.856 -11.653 1.00 82.58 C
ATOM 6237 O TYR C 197 -30.065 26.617 -12.717 1.00 83.40 O
ATOM 6238 CB TYR C 197 -32.900 26.178 -10.852 1.00 82.50 C
ATOM 6239 CG TYR C 197 -32.889 24.799 -11.502 1.00 82.72 C
ATOM 6240 CD1 TYR C 197 -31.681 24.162 -11.820 1.00 82.81 C
ATOM 6241 CD2 TYR C 197 -34.085 24.132 -11.809 1.00 82.18 C
ATOM 6242 CE1 TYR C 197 -31.655 22.905 -12.430 1.00 82.44 C
ATOM 6243 CE2 TYR C 197 -34.073 22.863 -12.419 1.00 82.21 C
ATOM 6244 CZ TYR C 197 -32.846 22.258 -12.731 1.00 82.80 C
ATOM 6245 OH TYR C 197 -32.789 21.028 -13.364 1.00 80.90 O
ATOM 6246 N PHE C 198 -30.036 26.772 -10.471 1.00 81.74 N
ATOM 6247 CA PHE C 198 -28.636 26.387 -10.343 1.00 79.29 C
ATOM 6248 C PHE C 198 -28.445 25.648 -9.036 1.00 75.97 C
ATOM 6249 O PHE C 198 -28.090 26.252 -8.030 1.00 76.68 O
ATOM 6250 CB PHE C 198 -27.718 27.611 -10.330 1.00 81.72 C
ATOM 6251 CG PHE C 198 -27.609 28.313 -11.648 1.00 84.47 C
ATOM 6252 CD1 PHE C 198 -28.608 29.182 -12.076 1.00 85.88 C
ATOM 6253 CD2 PHE C 198 -26.481 28.134 -12.450 1.00 85.59 C
ATOM 6254 CE1 PHE C 198 -28.482 29.869 -13.283 1.00 87.07 C
ATOM 6255 CE2 PHE C 198 -26.345 28.816 -13.655 1.00 86.78 C
ATOM 6256 CZ PHE C 198 -27.347 29.688 -14.074 1.00 86.99 C
ATOM 6257 N SER C 199 -28.673 24.345 -9.039 1.00 71.87 N
ATOM 6258 CA SER C 199 -28.496 23.594 -7.815 1.00 67.84 C
ATOM 6259 C SER C 199 -27.020 23.591 -7.444 1.00 66.10 C
ATOM 6260 O SER C 199 -26.157 23.893 -8.280 1.00 64.20 O
ATOM 6261 CB SER C 199 -28.983 22.167 -7.993 1.00 66.46 C
ATOM 6262 OG SER C 199 -28.254 21.544 -9.020 1.00 65.39 O
ATOM 6263 N MET C 200 -26.747 23.257 -6.183 1.00 64.09 N
ATOM 6264 CA MET C 200 -25.391 23.195 -5.669 1.00 61.01 C
ATOM 6265 C MET C 200 -24.500 22.517 -6.690 1.00 62.42 C
ATOM 6266 O MET C 200 -23.349 22.918 -6.882 1.00 62.06 O
ATOM 6267 CB MET C 200 -25.360 22.426 -4.348 1.00 56.33 C
ATOM 6268 CG MET C 200 -25.975 23.176 -3.183 1.00 53.16 C
ATOM 6269 SD MET C 200 -25.235 24.823 -2.909 1.00 46.37 S
ATOM 6270 CE MET C 200 -23.569 24.389 -2.627 1.00 48.10 C
ATOM 6271 N THR C 201 -25.038 21.499 -7.357 1.00 62.97 N
ATOM 6272 CA THR C 201 -24.269 20.786 -8.366 1.00 64.97 C
ATOM 6273 C THR C 201 -23.873 21.736 -9.512 1.00 66.10 C
ATOM 6274 O THR C 201 -22.776 21.608 -10.092 1.00 65.58 O
ATOM 6275 CB THR C 201 -25.049 19.537 -8.900 1.00 65.68 C
ATOM 6276 OG1 THR C 201 -25.211 19.624 -10.323 1.00 65.66 O
ATOM 6277 CG2 THR C 201 -26.412 19.421 -8.223 1.00 65.96 C
ATOM 6278 N GLU C 202 -24.746 22.699 -9.821 1.00 66.73 N
ATOM 6279 CA GLU C 202 -24.451 23.665 -10.881 1.00 67.80 C
ATOM 6280 C GLU C 202 -23.439 24.647 -10.374 1.00 68.66 C
ATOM 6281 O GLU C 202 -22.535 25.058 -11.108 1.00 70.18 O
ATOM 6282 CB GLU C 202 -25.690 24.416 -11.315 1.00 67.72 C
ATOM 6283 CG GLU C 202 -26.301 23.806 -12.546 1.00 72.08 C
ATOM 6284 CD GLU C 202 -26.684 22.351 -12.333 1.00 74.23 C
ATOM 6285 OE1 GLU C 202 -27.655 22.112 -11.574 1.00 73.29 O
ATOM 6286 OE2 GLU C 202 -26.009 21.459 -12.916 1.00 75.62 O
ATOM 6287 N VAL C 203 -23.606 25.031 -9.113 1.00 67.55 N
ATOM 6288 CA VAL C 203 -22.674 25.943 -8.478 1.00 65.53 C
ATOM 6289 C VAL C 203 -21.335 25.228 -8.657 1.00 64.91 C
ATOM 6290 O VAL C 203 -20.383 25.771 -9.232 1.00 64.87 O
ATOM 6291 CB VAL C 203 -22.962 26.076 -6.949 1.00 65.75 C
ATOM 6292 CG1 VAL C 203 -22.137 27.210 -6.355 1.00 65.81 C
ATOM 6293 CG2 VAL C 203 -24.442 26.299 -6.697 1.00 66.78 C
ATOM 6294 N ASP C 204 -21.299 23.983 -8.175 1.00 62.79 N
ATOM 6295 CA ASP C 204 -20.110 23.149 -8.228 1.00 61.49 C
ATOM 6296 C ASP C 204 -19.480 23.109 -9.590 1.00 62.37 C
ATOM 6297 O ASP C 204 -18.264 23.214 -9.715 1.00 61.65 O
ATOM 6298 CB ASP C 204 -20.448 21.726 -7.799 1.00 59.70 C
ATOM 6299 CG ASP C 204 -20.458 21.562 -6.300 1.00 56.79 C
ATOM 6300 OD1 ASP C 204 -20.639 22.589 -5.614 1.00 52.71 O
ATOM 6301 OD2 ASP C 204 -20.296 20.414 -5.820 1.00 54.02 O
ATOM 6302 N LYS C 205 -20.312 22.956 -10.612 1.00 64.38 N
ATOM 6303 CA LYS C 205 -19.814 22.877 -11.977 1.00 65.17 C
ATOM 6304 C LYS C 205 -19.240 24.177 -12.527 1.00 64.26 C
ATOM 6305 O LYS C 205 -18.069 24.242 -12.870 1.00 63.15 O
ATOM 6306 CB LYS C 205 -20.913 22.381 -12.910 1.00 66.18 C
ATOM 6307 CG LYS C 205 -20.408 22.116 -14.313 1.00 69.34 C
ATOM 6308 CD LYS C 205 -21.515 21.591 -15.216 1.00 73.83 C
ATOM 6309 CE LYS C 205 -21.001 21.166 -16.598 1.00 76.14 C
ATOM 6310 NZ LYS C 205 -20.089 19.970 -16.569 1.00 77.46 N
ATOM 6311 N LEU C 206 -20.060 25.215 -12.597 1.00 64.81 N
ATOM 6312 CA LEU C 206 -19.633 26.497 -13.156 1.00 67.28 C
ATOM 6313 C LEU C 206 -18.773 27.392 -12.274 1.00 68.71 C
ATOM 6314 O LEU C 206 -17.830 28.026 -12.753 1.00 69.72 O
ATOM 6315 CB LEU C 206 -20.859 27.309 -13.571 1.00 68.10 C
ATOM 6316 CG LEU C 206 -21.969 26.530 -14.269 1.00 67.44 C
ATOM 6317 CD1 LEU C 206 -23.191 27.428 -14.473 1.00 63.42 C
ATOM 6318 CD2 LEU C 206 -21.420 25.983 -15.582 1.00 67.18 C
ATOM 6319 N GLY C 207 -19.118 27.467 -10.993 1.00 69.83 N
ATOM 6320 CA GLY C 207 -18.389 28.336 -10.091 1.00 70.69 C
ATOM 6321 C GLY C 207 -19.233 29.587 -9.981 1.00 70.94 C
ATOM 6322 O GLY C 207 -19.587 30.186 -10.991 1.00 70.79 O
ATOM 6323 N ILE C 208 -19.566 29.968 -8.752 1.00 70.50 N
ATOM 6324 CA ILE C 208 -20.410 31.126 -8.503 1.00 70.18 C
ATOM 6325 C ILE C 208 -20.253 32.242 -9.545 1.00 72.13 C
ATOM 6326 O ILE C 208 -21.249 32.826 -9.982 1.00 71.07 O
ATOM 6327 CB ILE C 208 -20.178 31.674 -7.062 1.00 68.19 C
ATOM 6328 CG1 ILE C 208 -21.506 31.750 -6.309 1.00 66.86 C
ATOM 6329 CG2 ILE C 208 -19.471 33.009 -7.105 1.00 65.59 C
ATOM 6330 CD1 ILE C 208 -22.599 32.525 -6.997 1.00 63.60 C
ATOM 6331 N GLY C 209 -19.020 32.522 -9.960 1.00 74.55 N
ATOM 6332 CA GLY C 209 -18.802 33.570 -10.949 1.00 78.13 C
ATOM 6333 C GLY C 209 -19.653 33.422 -12.205 1.00 79.78 C
ATOM 6334 O GLY C 209 -20.438 34.311 -12.540 1.00 79.81 O
ATOM 6335 N LYS C 210 -19.483 32.291 -12.892 1.00 81.12 N
ATOM 6336 CA LYS C 210 -20.219 31.951 -14.112 1.00 81.72 C
ATOM 6337 C LYS C 210 -21.711 31.813 -13.790 1.00 81.92 C
ATOM 6338 O LYS C 210 -22.570 32.204 -14.580 1.00 82.06 O
ATOM 6339 CB LYS C 210 -19.663 30.634 -14.679 1.00 83.49 C
ATOM 6340 CG LYS C 210 -20.466 29.987 -15.800 1.00 86.80 C
ATOM 6341 CD LYS C 210 -20.593 30.892 -17.025 1.00 89.98 C
ATOM 6342 CE LYS C 210 -21.420 30.222 -18.137 1.00 90.59 C
ATOM 6343 NZ LYS C 210 -21.859 31.173 -19.218 1.00 91.17 N
ATOM 6344 N VAL C 211 -22.012 31.259 -12.622 1.00 81.88 N
ATOM 6345 CA VAL C 211 -23.394 31.087 -12.200 1.00 81.43 C
ATOM 6346 C VAL C 211 -24.116 32.432 -12.229 1.00 82.60 C
ATOM 6347 O VAL C 211 -25.250 32.513 -12.697 1.00 82.44 O
ATOM 6348 CB VAL C 211 -23.475 30.507 -10.768 1.00 80.75 C
ATOM 6349 CG1 VAL C 211 -24.916 30.467 -10.297 1.00 79.53 C
ATOM 6350 CG2 VAL C 211 -22.871 29.114 -10.736 1.00 80.56 C
ATOM 6351 N MET C 212 -23.462 33.482 -11.726 1.00 83.85 N
ATOM 6352 CA MET C 212 -24.055 34.823 -11.697 1.00 85.06 C
ATOM 6353 C MET C 212 -24.041 35.432 -13.091 1.00 87.35 C
ATOM 6354 O MET C 212 -25.034 35.993 -13.558 1.00 87.24 O
ATOM 6355 CB MET C 212 -23.289 35.740 -10.739 1.00 82.29 C
ATOM 6356 CG MET C 212 -23.374 35.336 -9.267 1.00 80.30 C
ATOM 6357 SD MET C 212 -25.049 35.307 -8.562 1.00 73.97 S
ATOM 6358 CE MET C 212 -25.276 36.996 -8.259 1.00 75.37 C
ATOM 6359 N GLU C 213 -22.892 35.316 -13.743 1.00 90.13 N
ATOM 6360 CA GLU C 213 -22.692 35.814 -15.093 1.00 92.16 C
ATOM 6361 C GLU C 213 -23.855 35.328 -15.967 1.00 92.77 C
ATOM 6362 O GLU C 213 -24.495 36.120 -16.664 1.00 94.09 O
ATOM 6363 CB GLU C 213 -21.354 35.282 -15.606 1.00 94.04 C
ATOM 6364 CG GLU C 213 -20.810 35.920 -16.864 1.00 99.07 C
ATOM 6365 CD GLU C 213 -19.400 35.423 -17.182 1.00102.30 C
ATOM 6366 OE1 GLU C 213 -18.495 35.637 -16.341 1.00103.12 O
ATOM 6367 OE2 GLU C 213 -19.196 34.819 -18.263 1.00104.92 O
ATOM 6368 N GLU C 214 -24.136 34.028 -15.917 1.00 92.07 N
ATOM 6369 CA GLU C 214 -25.230 33.459 -16.694 1.00 91.63 C
ATOM 6370 C GLU C 214 -26.551 34.073 -16.264 1.00 91.32 C
ATOM 6371 O GLU C 214 -27.105 34.908 -16.971 1.00 91.52 O
ATOM 6372 CB GLU C 214 -25.300 31.940 -16.507 1.00 92.05 C
ATOM 6373 CG GLU C 214 -24.434 31.151 -17.464 1.00 92.73 C
ATOM 6374 CD GLU C 214 -24.632 29.652 -17.323 1.00 93.79 C
ATOM 6375 OE1 GLU C 214 -25.781 29.178 -17.499 1.00 93.91 O
ATOM 6376 OE2 GLU C 214 -23.635 28.952 -17.042 1.00 93.93 O
ATOM 6377 N THR C 215 -27.044 33.651 -15.101 1.00 91.31 N
ATOM 6378 CA THR C 215 -28.310 34.139 -14.547 1.00 90.84 C
ATOM 6379 C THR C 215 -28.658 35.555 -14.973 1.00 90.63 C
ATOM 6380 O THR C 215 -29.830 35.873 -15.189 1.00 89.71 O
ATOM 6381 CB THR C 215 -28.305 34.119 -13.005 1.00 91.00 C
ATOM 6382 OG1 THR C 215 -27.065 34.651 -12.524 1.00 91.70 O
ATOM 6383 CG2 THR C 215 -28.482 32.726 -12.486 1.00 90.94 C
ATOM 6384 N PHE C 216 -27.644 36.413 -15.077 1.00 90.43 N
ATOM 6385 CA PHE C 216 -27.890 37.787 -15.481 1.00 90.26 C
ATOM 6386 C PHE C 216 -28.342 37.853 -16.927 1.00 91.62 C
ATOM 6387 O PHE C 216 -29.489 38.213 -17.197 1.00 92.03 O
ATOM 6388 CB PHE C 216 -26.653 38.655 -15.246 1.00 86.72 C
ATOM 6389 CG PHE C 216 -26.470 39.056 -13.808 1.00 83.81 C
ATOM 6390 CD1 PHE C 216 -27.450 38.770 -12.860 1.00 82.90 C
ATOM 6391 CD2 PHE C 216 -25.316 39.705 -13.395 1.00 82.83 C
ATOM 6392 CE1 PHE C 216 -27.273 39.101 -11.520 1.00 82.23 C
ATOM 6393 CE2 PHE C 216 -25.129 40.041 -12.053 1.00 82.56 C
ATOM 6394 CZ PHE C 216 -26.113 39.745 -11.114 1.00 81.79 C
ATOM 6395 N SER C 217 -27.464 37.502 -17.861 1.00 92.18 N
ATOM 6396 CA SER C 217 -27.855 37.525 -19.262 1.00 92.47 C
ATOM 6397 C SER C 217 -29.263 36.921 -19.394 1.00 92.71 C
ATOM 6398 O SER C 217 -30.170 37.568 -19.914 1.00 93.44 O
ATOM 6399 CB SER C 217 -26.871 36.719 -20.106 1.00 92.57 C
ATOM 6400 OG SER C 217 -27.079 35.329 -19.925 1.00 92.76 O
ATOM 6401 N TYR C 218 -29.442 35.695 -18.907 1.00 92.44 N
ATOM 6402 CA TYR C 218 -30.733 35.014 -18.972 1.00 93.21 C
ATOM 6403 C TYR C 218 -31.929 35.880 -18.542 1.00 94.61 C
ATOM 6404 O TYR C 218 -33.050 35.678 -19.015 1.00 93.90 O
ATOM 6405 CB TYR C 218 -30.699 33.750 -18.108 1.00 92.46 C
ATOM 6406 CG TYR C 218 -32.065 33.119 -17.915 1.00 92.79 C
ATOM 6407 CD1 TYR C 218 -32.549 32.153 -18.800 1.00 93.36 C
ATOM 6408 CD2 TYR C 218 -32.900 33.528 -16.874 1.00 91.95 C
ATOM 6409 CE1 TYR C 218 -33.838 31.611 -18.655 1.00 92.39 C
ATOM 6410 CE2 TYR C 218 -34.185 33.000 -16.719 1.00 92.17 C
ATOM 6411 CZ TYR C 218 -34.652 32.041 -17.614 1.00 92.07 C
ATOM 6412 OH TYR C 218 -35.934 31.535 -17.474 1.00 91.03 O
ATOM 6413 N LEU C 219 -31.693 36.831 -17.643 1.00 96.79 N
ATOM 6414 CA LEU C 219 -32.759 37.705 -17.145 1.00 99.53 C
ATOM 6415 C LEU C 219 -32.714 39.143 -17.679 1.00102.10 C
ATOM 6416 O LEU C 219 -33.749 39.730 -18.007 1.00102.34 O
ATOM 6417 CB LEU C 219 -32.722 37.756 -15.612 1.00 98.47 C
ATOM 6418 CG LEU C 219 -33.171 36.540 -14.807 1.00 97.30 C
ATOM 6419 CD1 LEU C 219 -32.771 36.730 -13.364 1.00 97.75 C
ATOM 6420 CD2 LEU C 219 -34.674 36.357 -14.917 1.00 96.22 C
ATOM 6421 N LEU C 220 -31.514 39.706 -17.759 1.00104.81 N
ATOM 6422 CA LEU C 220 -31.336 41.079 -18.223 1.00107.29 C
ATOM 6423 C LEU C 220 -30.700 41.128 -19.616 1.00109.31 C
ATOM 6424 O LEU C 220 -30.151 42.155 -20.020 1.00109.84 O
ATOM 6425 CB LEU C 220 -30.457 41.848 -17.220 1.00106.72 C
ATOM 6426 CG LEU C 220 -30.587 41.505 -15.724 1.00105.67 C
ATOM 6427 CD1 LEU C 220 -29.577 42.321 -14.922 1.00104.74 C
ATOM 6428 CD2 LEU C 220 -32.010 41.765 -15.236 1.00104.50 C
ATOM 6429 N GLY C 221 -30.774 40.016 -20.344 1.00111.26 N
ATOM 6430 CA GLY C 221 -30.191 39.962 -21.675 1.00113.38 C
ATOM 6431 C GLY C 221 -30.854 40.927 -22.636 1.00114.74 C
ATOM 6432 O GLY C 221 -30.185 41.726 -23.290 1.00114.30 O
ATOM 6433 N ARG C 222 -32.178 40.848 -22.717 1.00116.28 N
ATOM 6434 CA ARG C 222 -32.952 41.716 -23.594 1.00117.84 C
ATOM 6435 C ARG C 222 -33.260 43.051 -22.912 1.00117.49 C
ATOM 6436 O ARG C 222 -32.542 44.042 -23.085 1.00117.04 O
ATOM 6437 CB ARG C 222 -34.255 41.011 -23.993 1.00120.30 C
ATOM 6438 CG ARG C 222 -34.057 39.846 -24.966 1.00124.08 C
ATOM 6439 CD ARG C 222 -35.270 38.905 -25.026 1.00127.28 C
ATOM 6440 NE ARG C 222 -35.425 38.106 -23.807 1.00129.65 N
ATOM 6441 CZ ARG C 222 -36.229 37.049 -23.689 1.00130.39 C
ATOM 6442 NH1 ARG C 222 -36.965 36.649 -24.720 1.00131.75 N
ATOM 6443 NH2 ARG C 222 -36.296 36.383 -22.541 1.00130.10 N
ATOM 6444 N LYS C 223 -34.330 43.073 -22.127 1.00117.21 N
ATOM 6445 CA LYS C 223 -34.725 44.288 -21.427 1.00116.89 C
ATOM 6446 C LYS C 223 -34.217 44.306 -19.985 1.00115.74 C
ATOM 6447 O LYS C 223 -34.612 43.475 -19.164 1.00116.07 O
ATOM 6448 CB LYS C 223 -36.255 44.424 -21.419 1.00118.12 C
ATOM 6449 CG LYS C 223 -36.918 44.649 -22.781 1.00119.48 C
ATOM 6450 CD LYS C 223 -36.709 46.068 -23.313 1.00120.20 C
ATOM 6451 CE LYS C 223 -37.710 46.407 -24.424 1.00119.96 C
ATOM 6452 NZ LYS C 223 -37.623 45.502 -25.607 1.00120.32 N
ATOM 6453 N LYS C 224 -33.336 45.253 -19.684 1.00113.56 N
ATOM 6454 CA LYS C 224 -32.815 45.403 -18.330 1.00110.71 C
ATOM 6455 C LYS C 224 -33.990 45.810 -17.438 1.00108.17 C
ATOM 6456 O LYS C 224 -34.618 46.842 -17.670 1.00107.92 O
ATOM 6457 CB LYS C 224 -31.744 46.499 -18.285 1.00111.33 C
ATOM 6458 CG LYS C 224 -30.398 46.103 -18.857 1.00111.67 C
ATOM 6459 CD LYS C 224 -30.510 45.593 -20.280 1.00113.19 C
ATOM 6460 CE LYS C 224 -29.144 45.207 -20.827 1.00114.15 C
ATOM 6461 NZ LYS C 224 -29.244 44.548 -22.163 1.00114.36 N
ATOM 6462 N ARG C 225 -34.300 44.999 -16.431 1.00104.97 N
ATOM 6463 CA ARG C 225 -35.399 45.321 -15.522 1.00102.05 C
ATOM 6464 C ARG C 225 -34.920 45.417 -14.071 1.00 99.65 C
ATOM 6465 O ARG C 225 -33.719 45.333 -13.796 1.00100.15 O
ATOM 6466 CB ARG C 225 -36.530 44.281 -15.631 1.00101.03 C
ATOM 6467 CG ARG C 225 -36.157 42.841 -15.310 1.00 99.54 C
ATOM 6468 CD ARG C 225 -35.356 42.230 -16.441 1.00 99.50 C
ATOM 6469 NE ARG C 225 -35.509 40.777 -16.528 1.00 98.90 N
ATOM 6470 CZ ARG C 225 -36.671 40.156 -16.719 1.00 99.29 C
ATOM 6471 NH1 ARG C 225 -37.795 40.853 -16.835 1.00 99.63 N
ATOM 6472 NH2 ARG C 225 -36.709 38.834 -16.813 1.00 99.36 N
ATOM 6473 N PRO C 226 -35.848 45.654 -13.130 1.00 96.61 N
ATOM 6474 CA PRO C 226 -35.422 45.742 -11.730 1.00 93.91 C
ATOM 6475 C PRO C 226 -35.277 44.338 -11.161 1.00 90.68 C
ATOM 6476 O PRO C 226 -35.930 43.401 -11.631 1.00 90.41 O
ATOM 6477 CB PRO C 226 -36.560 46.512 -11.068 1.00 94.90 C
ATOM 6478 CG PRO C 226 -37.097 47.348 -12.199 1.00 96.02 C
ATOM 6479 CD PRO C 226 -37.130 46.350 -13.317 1.00 95.93 C
ATOM 6480 N ILE C 227 -34.414 44.204 -10.156 1.00 86.58 N
ATOM 6481 CA ILE C 227 -34.157 42.917 -9.510 1.00 81.66 C
ATOM 6482 C ILE C 227 -34.793 42.823 -8.130 1.00 78.57 C
ATOM 6483 O ILE C 227 -34.899 43.817 -7.398 1.00 78.91 O
ATOM 6484 CB ILE C 227 -32.615 42.642 -9.339 1.00 81.09 C
ATOM 6485 CG1 ILE C 227 -32.050 41.947 -10.580 1.00 79.71 C
ATOM 6486 CG2 ILE C 227 -32.354 41.783 -8.095 1.00 79.22 C
ATOM 6487 CD1 ILE C 227 -31.840 42.853 -11.767 1.00 79.96 C
ATOM 6488 N HIS C 228 -35.230 41.619 -7.792 1.00 73.48 N
ATOM 6489 CA HIS C 228 -35.780 41.374 -6.486 1.00 69.84 C
ATOM 6490 C HIS C 228 -35.026 40.163 -5.955 1.00 67.82 C
ATOM 6491 O HIS C 228 -35.321 39.015 -6.308 1.00 66.60 O
ATOM 6492 CB HIS C 228 -37.262 41.058 -6.543 1.00 70.56 C
ATOM 6493 CG HIS C 228 -37.871 40.871 -5.191 1.00 73.54 C
ATOM 6494 ND1 HIS C 228 -38.117 41.927 -4.334 1.00 75.85 N
ATOM 6495 CD2 HIS C 228 -38.223 39.753 -4.514 1.00 74.60 C
ATOM 6496 CE1 HIS C 228 -38.593 41.466 -3.191 1.00 75.11 C
ATOM 6497 NE2 HIS C 228 -38.665 40.149 -3.272 1.00 76.27 N
ATOM 6498 N LEU C 229 -34.023 40.423 -5.130 1.00 65.08 N
ATOM 6499 CA LEU C 229 -33.239 39.348 -4.550 1.00 62.32 C
ATOM 6500 C LEU C 229 -33.881 38.874 -3.250 1.00 61.53 C
ATOM 6501 O LEU C 229 -33.808 39.555 -2.226 1.00 62.14 O
ATOM 6502 CB LEU C 229 -31.823 39.824 -4.252 1.00 59.30 C
ATOM 6503 CG LEU C 229 -31.000 38.800 -3.468 1.00 57.40 C
ATOM 6504 CD1 LEU C 229 -30.705 37.596 -4.350 1.00 54.44 C
ATOM 6505 CD2 LEU C 229 -29.729 39.457 -2.985 1.00 56.40 C
ATOM 6506 N SER C 230 -34.525 37.717 -3.292 1.00 59.36 N
ATOM 6507 CA SER C 230 -35.142 37.170 -2.095 1.00 58.06 C
ATOM 6508 C SER C 230 -34.066 36.226 -1.550 1.00 57.34 C
ATOM 6509 O SER C 230 -33.871 35.110 -2.050 1.00 57.15 O
ATOM 6510 CB SER C 230 -36.428 36.406 -2.456 1.00 58.58 C
ATOM 6511 OG SER C 230 -37.350 36.342 -1.375 1.00 57.12 O
ATOM 6512 N PHE C 231 -33.341 36.688 -0.539 1.00 55.66 N
ATOM 6513 CA PHE C 231 -32.279 35.875 0.034 1.00 54.53 C
ATOM 6514 C PHE C 231 -32.714 35.142 1.284 1.00 53.57 C
ATOM 6515 O PHE C 231 -33.201 35.738 2.246 1.00 52.54 O
ATOM 6516 CB PHE C 231 -31.055 36.732 0.356 1.00 52.60 C
ATOM 6517 CG PHE C 231 -29.780 35.958 0.390 1.00 46.80 C
ATOM 6518 CD1 PHE C 231 -29.671 34.821 1.167 1.00 44.29 C
ATOM 6519 CD2 PHE C 231 -28.684 36.384 -0.350 1.00 46.49 C
ATOM 6520 CE1 PHE C 231 -28.499 34.127 1.216 1.00 44.81 C
ATOM 6521 CE2 PHE C 231 -27.498 35.700 -0.314 1.00 46.31 C
ATOM 6522 CZ PHE C 231 -27.400 34.561 0.473 1.00 47.96 C
ATOM 6523 N ASP C 232 -32.504 33.833 1.261 1.00 54.56 N
ATOM 6524 CA ASP C 232 -32.871 32.977 2.376 1.00 54.94 C
ATOM 6525 C ASP C 232 -31.653 32.517 3.130 1.00 54.45 C
ATOM 6526 O ASP C 232 -31.050 31.520 2.776 1.00 53.16 O
ATOM 6527 CB ASP C 232 -33.636 31.762 1.878 1.00 53.83 C
ATOM 6528 CG ASP C 232 -33.945 30.791 2.974 1.00 54.18 C
ATOM 6529 OD1 ASP C 232 -33.542 31.028 4.134 1.00 51.22 O
ATOM 6530 OD2 ASP C 232 -34.590 29.768 2.670 1.00 54.39 O
ATOM 6531 N VAL C 233 -31.317 33.250 4.184 1.00 55.37 N
ATOM 6532 CA VAL C 233 -30.185 32.955 5.041 1.00 56.07 C
ATOM 6533 C VAL C 233 -29.810 31.474 5.117 1.00 56.17 C
ATOM 6534 O VAL C 233 -28.661 31.140 5.405 1.00 57.17 O
ATOM 6535 CB VAL C 233 -30.462 33.431 6.456 1.00 58.18 C
ATOM 6536 CG1 VAL C 233 -31.519 32.520 7.107 1.00 57.95 C
ATOM 6537 CG2 VAL C 233 -29.182 33.432 7.251 1.00 59.10 C
ATOM 6538 N ASP C 234 -30.767 30.579 4.877 1.00 55.85 N
ATOM 6539 CA ASP C 234 -30.459 29.143 4.915 1.00 55.47 C
ATOM 6540 C ASP C 234 -29.741 28.589 3.670 1.00 52.10 C
ATOM 6541 O ASP C 234 -29.200 27.504 3.713 1.00 52.05 O
ATOM 6542 CB ASP C 234 -31.735 28.316 5.194 1.00 59.03 C
ATOM 6543 CG ASP C 234 -32.639 28.157 3.969 1.00 63.96 C
ATOM 6544 OD1 ASP C 234 -32.131 27.871 2.850 1.00 65.02 O
ATOM 6545 OD2 ASP C 234 -33.877 28.288 4.144 1.00 66.85 O
ATOM 6546 N GLY C 235 -29.748 29.327 2.569 1.00 50.06 N
ATOM 6547 CA GLY C 235 -29.084 28.871 1.358 1.00 49.84 C
ATOM 6548 C GLY C 235 -27.556 28.830 1.435 1.00 49.59 C
ATOM 6549 O GLY C 235 -26.866 28.466 0.468 1.00 47.09 O
ATOM 6550 N LEU C 236 -27.019 29.247 2.576 1.00 50.09 N
ATOM 6551 CA LEU C 236 -25.590 29.207 2.786 1.00 50.76 C
ATOM 6552 C LEU C 236 -25.393 27.897 3.511 1.00 51.57 C
ATOM 6553 O LEU C 236 -26.371 27.259 3.908 1.00 52.88 O
ATOM 6554 CB LEU C 236 -25.157 30.367 3.666 1.00 52.43 C
ATOM 6555 CG LEU C 236 -24.391 31.462 2.929 1.00 54.89 C
ATOM 6556 CD1 LEU C 236 -25.070 31.761 1.603 1.00 55.00 C
ATOM 6557 CD2 LEU C 236 -24.323 32.703 3.805 1.00 55.89 C
ATOM 6558 N ASP C 237 -24.156 27.463 3.689 1.00 52.93 N
ATOM 6559 CA ASP C 237 -23.966 26.206 4.402 1.00 57.18 C
ATOM 6560 C ASP C 237 -24.269 26.377 5.901 1.00 58.88 C
ATOM 6561 O ASP C 237 -24.085 27.466 6.460 1.00 59.95 O
ATOM 6562 CB ASP C 237 -22.550 25.681 4.222 1.00 58.63 C
ATOM 6563 CG ASP C 237 -22.377 24.302 4.820 1.00 60.03 C
ATOM 6564 OD1 ASP C 237 -22.299 24.206 6.068 1.00 60.59 O
ATOM 6565 OD2 ASP C 237 -22.354 23.321 4.040 1.00 60.31 O
ATOM 6566 N PRO C 238 -24.745 25.307 6.572 1.00 57.68 N
ATOM 6567 CA PRO C 238 -25.045 25.446 7.996 1.00 56.57 C
ATOM 6568 C PRO C 238 -23.903 25.940 8.886 1.00 56.08 C
ATOM 6569 O PRO C 238 -24.151 26.513 9.954 1.00 56.48 O
ATOM 6570 CB PRO C 238 -25.546 24.055 8.368 1.00 57.23 C
ATOM 6571 CG PRO C 238 -26.308 23.673 7.142 1.00 57.07 C
ATOM 6572 CD PRO C 238 -25.296 24.039 6.063 1.00 57.93 C
ATOM 6573 N VAL C 239 -22.660 25.744 8.450 1.00 53.68 N
ATOM 6574 CA VAL C 239 -21.507 26.195 9.233 1.00 52.34 C
ATOM 6575 C VAL C 239 -21.462 27.734 9.297 1.00 52.10 C
ATOM 6576 O VAL C 239 -20.932 28.325 10.241 1.00 50.40 O
ATOM 6577 CB VAL C 239 -20.189 25.685 8.607 1.00 51.91 C
ATOM 6578 CG1 VAL C 239 -19.608 26.724 7.675 1.00 51.39 C
ATOM 6579 CG2 VAL C 239 -19.203 25.328 9.691 1.00 51.86 C
ATOM 6580 N PHE C 240 -22.045 28.368 8.286 1.00 52.61 N
ATOM 6581 CA PHE C 240 -22.053 29.819 8.181 1.00 51.13 C
ATOM 6582 C PHE C 240 -23.275 30.490 8.777 1.00 50.55 C
ATOM 6583 O PHE C 240 -23.150 31.498 9.462 1.00 52.43 O
ATOM 6584 CB PHE C 240 -21.921 30.217 6.707 1.00 49.52 C
ATOM 6585 CG PHE C 240 -20.636 29.752 6.055 1.00 46.38 C
ATOM 6586 CD1 PHE C 240 -19.432 30.403 6.319 1.00 43.52 C
ATOM 6587 CD2 PHE C 240 -20.638 28.684 5.162 1.00 44.12 C
ATOM 6588 CE1 PHE C 240 -18.272 30.016 5.702 1.00 40.93 C
ATOM 6589 CE2 PHE C 240 -19.472 28.291 4.541 1.00 41.80 C
ATOM 6590 CZ PHE C 240 -18.287 28.956 4.812 1.00 40.90 C
ATOM 6591 N THR C 241 -24.451 29.938 8.521 1.00 49.79 N
ATOM 6592 CA THR C 241 -25.688 30.520 9.023 1.00 50.83 C
ATOM 6593 C THR C 241 -26.468 29.475 9.782 1.00 52.55 C
ATOM 6594 O THR C 241 -27.590 29.128 9.407 1.00 51.99 O
ATOM 6595 CB THR C 241 -26.566 31.003 7.871 1.00 51.65 C
ATOM 6596 OG1 THR C 241 -26.785 29.915 6.952 1.00 53.02 O
ATOM 6597 CG2 THR C 241 -25.898 32.162 7.153 1.00 50.87 C
ATOM 6598 N PRO C 242 -25.884 28.948 10.863 1.00 54.97 N
ATOM 6599 CA PRO C 242 -26.537 27.919 11.679 1.00 57.22 C
ATOM 6600 C PRO C 242 -27.917 28.210 12.280 1.00 56.87 C
ATOM 6601 O PRO C 242 -28.754 27.315 12.327 1.00 57.12 O
ATOM 6602 CB PRO C 242 -25.474 27.591 12.736 1.00 57.28 C
ATOM 6603 CG PRO C 242 -24.566 28.800 12.734 1.00 57.06 C
ATOM 6604 CD PRO C 242 -24.487 29.138 11.283 1.00 56.17 C
ATOM 6605 N ALA C 243 -28.157 29.440 12.731 1.00 58.31 N
ATOM 6606 CA ALA C 243 -29.450 29.798 13.329 1.00 58.19 C
ATOM 6607 C ALA C 243 -30.590 29.888 12.317 1.00 58.24 C
ATOM 6608 O ALA C 243 -30.996 30.992 11.948 1.00 57.68 O
ATOM 6609 CB ALA C 243 -29.331 31.128 14.089 1.00 56.37 C
ATOM 6610 N THR C 244 -31.102 28.733 11.883 1.00 59.71 N
ATOM 6611 CA THR C 244 -32.203 28.669 10.909 1.00 62.49 C
ATOM 6612 C THR C 244 -33.234 27.584 11.238 1.00 64.13 C
ATOM 6613 O THR C 244 -33.086 26.831 12.205 1.00 66.01 O
ATOM 6614 CB THR C 244 -31.711 28.354 9.471 1.00 60.93 C
ATOM 6615 OG1 THR C 244 -30.455 28.992 9.228 1.00 62.57 O
ATOM 6616 CG2 THR C 244 -32.715 28.875 8.454 1.00 62.79 C
ATOM 6617 N GLY C 245 -34.281 27.517 10.417 1.00 65.60 N
ATOM 6618 CA GLY C 245 -35.311 26.510 10.589 1.00 65.27 C
ATOM 6619 C GLY C 245 -34.765 25.225 10.013 1.00 65.53 C
ATOM 6620 O GLY C 245 -34.442 24.308 10.752 1.00 65.18 O
ATOM 6621 N THR C 246 -34.626 25.166 8.693 1.00 67.51 N
ATOM 6622 CA THR C 246 -34.096 23.966 8.052 1.00 69.03 C
ATOM 6623 C THR C 246 -32.652 24.083 7.599 1.00 70.69 C
ATOM 6624 O THR C 246 -32.367 24.852 6.679 1.00 72.99 O
ATOM 6625 CB THR C 246 -34.805 23.596 6.749 1.00 68.81 C
ATOM 6626 OG1 THR C 246 -36.101 24.199 6.687 1.00 70.16 O
ATOM 6627 CG2 THR C 246 -34.876 22.078 6.625 1.00 67.59 C
ATOM 6628 N PRO C 247 -31.714 23.357 8.240 1.00 69.84 N
ATOM 6629 CA PRO C 247 -30.362 23.519 7.699 1.00 67.28 C
ATOM 6630 C PRO C 247 -30.208 22.366 6.675 1.00 65.99 C
ATOM 6631 O PRO C 247 -30.905 21.343 6.771 1.00 64.86 O
ATOM 6632 CB PRO C 247 -29.472 23.366 8.935 1.00 66.52 C
ATOM 6633 CG PRO C 247 -30.213 22.369 9.749 1.00 67.42 C
ATOM 6634 CD PRO C 247 -31.669 22.810 9.613 1.00 69.14 C
ATOM 6635 N VAL C 248 -29.344 22.545 5.678 1.00 64.07 N
ATOM 6636 CA VAL C 248 -29.111 21.507 4.663 1.00 60.46 C
ATOM 6637 C VAL C 248 -27.613 21.554 4.290 1.00 58.21 C
ATOM 6638 O VAL C 248 -27.157 22.490 3.639 1.00 58.79 O
ATOM 6639 CB VAL C 248 -30.008 21.745 3.410 1.00 59.13 C
ATOM 6640 CG1 VAL C 248 -29.900 20.591 2.477 1.00 59.22 C
ATOM 6641 CG2 VAL C 248 -31.453 21.878 3.816 1.00 60.23 C
ATOM 6642 N VAL C 249 -26.841 20.556 4.715 1.00 54.05 N
ATOM 6643 CA VAL C 249 -25.405 20.568 4.439 1.00 51.52 C
ATOM 6644 C VAL C 249 -25.052 20.723 2.976 1.00 49.68 C
ATOM 6645 O VAL C 249 -25.874 20.450 2.103 1.00 50.93 O
ATOM 6646 CB VAL C 249 -24.745 19.292 4.916 1.00 50.57 C
ATOM 6647 CG1 VAL C 249 -24.821 19.218 6.410 1.00 50.72 C
ATOM 6648 CG2 VAL C 249 -25.423 18.108 4.277 1.00 48.35 C
ATOM 6649 N GLY C 250 -23.823 21.150 2.709 1.00 45.28 N
ATOM 6650 CA GLY C 250 -23.385 21.299 1.333 1.00 44.16 C
ATOM 6651 C GLY C 250 -24.027 22.421 0.528 1.00 45.03 C
ATOM 6652 O GLY C 250 -24.466 22.222 -0.621 1.00 43.44 O
ATOM 6653 N GLY C 251 -24.059 23.606 1.139 1.00 45.14 N
ATOM 6654 CA GLY C 251 -24.626 24.777 0.506 1.00 44.15 C
ATOM 6655 C GLY C 251 -23.616 25.890 0.275 1.00 44.72 C
ATOM 6656 O GLY C 251 -22.416 25.736 0.530 1.00 45.93 O
ATOM 6657 N LEU C 252 -24.123 27.013 -0.224 1.00 43.77 N
ATOM 6658 CA LEU C 252 -23.339 28.194 -0.529 1.00 44.97 C
ATOM 6659 C LEU C 252 -22.387 28.620 0.588 1.00 47.83 C
ATOM 6660 O LEU C 252 -22.727 28.585 1.789 1.00 51.38 O
ATOM 6661 CB LEU C 252 -24.296 29.344 -0.862 1.00 43.84 C
ATOM 6662 CG LEU C 252 -25.121 29.072 -2.118 1.00 43.55 C
ATOM 6663 CD1 LEU C 252 -26.404 29.887 -2.138 1.00 41.47 C
ATOM 6664 CD2 LEU C 252 -24.255 29.354 -3.324 1.00 41.53 C
ATOM 6665 N SER C 253 -21.191 29.040 0.206 1.00 46.62 N
ATOM 6666 CA SER C 253 -20.233 29.480 1.201 1.00 46.70 C
ATOM 6667 C SER C 253 -20.447 30.960 1.475 1.00 47.40 C
ATOM 6668 O SER C 253 -21.067 31.655 0.668 1.00 48.44 O
ATOM 6669 CB SER C 253 -18.846 29.265 0.659 1.00 45.90 C
ATOM 6670 OG SER C 253 -18.822 29.700 -0.685 1.00 46.47 O
ATOM 6671 N TYR C 254 -19.947 31.436 2.613 1.00 47.39 N
ATOM 6672 CA TYR C 254 -20.057 32.846 2.966 1.00 47.44 C
ATOM 6673 C TYR C 254 -19.560 33.548 1.716 1.00 49.11 C
ATOM 6674 O TYR C 254 -20.295 34.329 1.111 1.00 49.44 O
ATOM 6675 CB TYR C 254 -19.145 33.168 4.150 1.00 46.22 C
ATOM 6676 CG TYR C 254 -19.179 34.605 4.666 1.00 47.21 C
ATOM 6677 CD1 TYR C 254 -20.296 35.112 5.323 1.00 48.90 C
ATOM 6678 CD2 TYR C 254 -18.050 35.420 4.587 1.00 47.33 C
ATOM 6679 CE1 TYR C 254 -20.288 36.394 5.903 1.00 49.41 C
ATOM 6680 CE2 TYR C 254 -18.022 36.697 5.156 1.00 49.47 C
ATOM 6681 CZ TYR C 254 -19.143 37.180 5.817 1.00 51.72 C
ATOM 6682 OH TYR C 254 -19.100 38.432 6.416 1.00 53.13 O
ATOM 6683 N ARG C 255 -18.323 33.233 1.317 1.00 49.81 N
ATOM 6684 CA ARG C 255 -17.700 33.797 0.115 1.00 50.99 C
ATOM 6685 C ARG C 255 -18.642 33.784 -1.097 1.00 52.53 C
ATOM 6686 O ARG C 255 -18.949 34.841 -1.669 1.00 53.55 O
ATOM 6687 CB ARG C 255 -16.419 33.022 -0.230 1.00 51.35 C
ATOM 6688 CG ARG C 255 -15.178 33.516 0.497 1.00 54.18 C
ATOM 6689 CD ARG C 255 -13.975 32.584 0.349 1.00 55.20 C
ATOM 6690 NE ARG C 255 -13.495 32.508 -1.029 1.00 59.63 N
ATOM 6691 CZ ARG C 255 -12.489 31.728 -1.435 1.00 62.22 C
ATOM 6692 NH1 ARG C 255 -11.848 30.952 -0.558 1.00 63.52 N
ATOM 6693 NH2 ARG C 255 -12.129 31.712 -2.720 1.00 60.66 N
ATOM 6694 N GLU C 256 -19.093 32.596 -1.493 1.00 52.25 N
ATOM 6695 CA GLU C 256 -20.004 32.490 -2.623 1.00 54.48 C
ATOM 6696 C GLU C 256 -21.251 33.362 -2.433 1.00 55.70 C
ATOM 6697 O GLU C 256 -21.761 33.952 -3.391 1.00 56.74 O
ATOM 6698 CB GLU C 256 -20.449 31.044 -2.829 1.00 55.00 C
ATOM 6699 CG GLU C 256 -19.366 30.104 -3.297 1.00 55.21 C
ATOM 6700 CD GLU C 256 -19.900 28.719 -3.533 1.00 56.50 C
ATOM 6701 OE1 GLU C 256 -20.668 28.242 -2.664 1.00 57.48 O
ATOM 6702 OE2 GLU C 256 -19.553 28.112 -4.576 1.00 57.60 O
ATOM 6703 N GLY C 257 -21.741 33.433 -1.198 1.00 55.23 N
ATOM 6704 CA GLY C 257 -22.925 34.227 -0.918 1.00 54.94 C
ATOM 6705 C GLY C 257 -22.643 35.709 -1.005 1.00 54.60 C
ATOM 6706 O GLY C 257 -23.480 36.507 -1.440 1.00 52.82 O
ATOM 6707 N LEU C 258 -21.454 36.080 -0.559 1.00 54.63 N
ATOM 6708 CA LEU C 258 -21.064 37.459 -0.622 1.00 55.19 C
ATOM 6709 C LEU C 258 -20.738 37.756 -2.068 1.00 56.88 C
ATOM 6710 O LEU C 258 -20.847 38.903 -2.508 1.00 58.61 O
ATOM 6711 CB LEU C 258 -19.858 37.735 0.271 1.00 53.48 C
ATOM 6712 CG LEU C 258 -20.237 37.897 1.740 1.00 51.43 C
ATOM 6713 CD1 LEU C 258 -19.076 38.466 2.530 1.00 50.84 C
ATOM 6714 CD2 LEU C 258 -21.408 38.840 1.830 1.00 52.56 C
ATOM 6715 N TYR C 259 -20.358 36.741 -2.835 1.00 56.63 N
ATOM 6716 CA TYR C 259 -20.067 37.035 -4.225 1.00 58.61 C
ATOM 6717 C TYR C 259 -21.350 37.378 -4.965 1.00 59.71 C
ATOM 6718 O TYR C 259 -21.368 38.273 -5.816 1.00 61.48 O
ATOM 6719 CB TYR C 259 -19.405 35.879 -4.937 1.00 58.79 C
ATOM 6720 CG TYR C 259 -18.909 36.300 -6.303 1.00 59.56 C
ATOM 6721 CD1 TYR C 259 -17.621 36.831 -6.461 1.00 58.31 C
ATOM 6722 CD2 TYR C 259 -19.719 36.149 -7.441 1.00 57.95 C
ATOM 6723 CE1 TYR C 259 -17.146 37.188 -7.723 1.00 60.55 C
ATOM 6724 CE2 TYR C 259 -19.262 36.501 -8.706 1.00 58.97 C
ATOM 6725 CZ TYR C 259 -17.971 37.015 -8.844 1.00 61.35 C
ATOM 6726 OH TYR C 259 -17.483 37.316 -10.094 1.00 61.49 O
ATOM 6727 N ILE C 260 -22.423 36.662 -4.643 1.00 59.36 N
ATOM 6728 CA ILE C 260 -23.710 36.911 -5.273 1.00 59.47 C
ATOM 6729 C ILE C 260 -24.158 38.355 -5.023 1.00 59.59 C
ATOM 6730 O ILE C 260 -24.182 39.165 -5.949 1.00 57.54 O
ATOM 6731 CB ILE C 260 -24.773 35.916 -4.753 1.00 60.43 C
ATOM 6732 CG1 ILE C 260 -24.457 34.504 -5.270 1.00 60.99 C
ATOM 6733 CG2 ILE C 260 -26.157 36.335 -5.204 1.00 61.05 C
ATOM 6734 CD1 ILE C 260 -25.410 33.442 -4.777 1.00 60.66 C
ATOM 6735 N THR C 261 -24.500 38.687 -3.780 1.00 61.59 N
ATOM 6736 CA THR C 261 -24.933 40.052 -3.457 1.00 63.51 C
ATOM 6737 C THR C 261 -23.986 41.088 -4.085 1.00 67.33 C
ATOM 6738 O THR C 261 -24.413 42.197 -4.450 1.00 68.11 O
ATOM 6739 CB THR C 261 -24.953 40.306 -1.940 1.00 60.27 C
ATOM 6740 OG1 THR C 261 -23.666 39.996 -1.413 1.00 57.46 O
ATOM 6741 CG2 THR C 261 -26.011 39.464 -1.239 1.00 57.45 C
ATOM 6742 N GLU C 262 -22.704 40.728 -4.197 1.00 69.10 N
ATOM 6743 CA GLU C 262 -21.704 41.617 -4.789 1.00 71.64 C
ATOM 6744 C GLU C 262 -21.929 41.868 -6.285 1.00 74.49 C
ATOM 6745 O GLU C 262 -21.887 43.013 -6.739 1.00 73.82 O
ATOM 6746 CB GLU C 262 -20.294 41.067 -4.569 1.00 70.03 C
ATOM 6747 CG GLU C 262 -19.766 41.300 -3.170 1.00 66.23 C
ATOM 6748 CD GLU C 262 -18.262 41.124 -3.082 1.00 64.16 C
ATOM 6749 OE1 GLU C 262 -17.713 40.263 -3.810 1.00 61.75 O
ATOM 6750 OE2 GLU C 262 -17.636 41.842 -2.272 1.00 61.96 O
ATOM 6751 N GLU C 263 -22.154 40.803 -7.051 1.00 77.10 N
ATOM 6752 CA GLU C 263 -22.417 40.954 -8.480 1.00 80.64 C
ATOM 6753 C GLU C 263 -23.804 41.564 -8.695 1.00 82.90 C
ATOM 6754 O GLU C 263 -24.069 42.186 -9.729 1.00 83.65 O
ATOM 6755 CB GLU C 263 -22.333 39.609 -9.186 1.00 81.10 C
ATOM 6756 CG GLU C 263 -20.915 39.211 -9.478 1.00 85.33 C
ATOM 6757 CD GLU C 263 -20.176 40.290 -10.260 1.00 87.53 C
ATOM 6758 OE1 GLU C 263 -20.627 40.603 -11.384 1.00 89.71 O
ATOM 6759 OE2 GLU C 263 -19.157 40.825 -9.754 1.00 87.81 O
ATOM 6760 N ILE C 264 -24.683 41.376 -7.714 1.00 83.91 N
ATOM 6761 CA ILE C 264 -26.026 41.929 -7.764 1.00 86.02 C
ATOM 6762 C ILE C 264 -25.895 43.448 -7.712 1.00 87.43 C
ATOM 6763 O ILE C 264 -26.427 44.182 -8.556 1.00 86.72 O
ATOM 6764 CB ILE C 264 -26.872 41.455 -6.545 1.00 86.67 C
ATOM 6765 CG1 ILE C 264 -27.355 40.020 -6.761 1.00 87.39 C
ATOM 6766 CG2 ILE C 264 -28.037 42.414 -6.299 1.00 86.51 C
ATOM 6767 CD1 ILE C 264 -28.188 39.811 -8.013 1.00 86.98 C
ATOM 6768 N TYR C 265 -25.172 43.903 -6.696 1.00 88.88 N
ATOM 6769 CA TYR C 265 -24.938 45.318 -6.487 1.00 89.33 C
ATOM 6770 C TYR C 265 -24.290 45.962 -7.712 1.00 89.27 C
ATOM 6771 O TYR C 265 -24.756 46.984 -8.204 1.00 89.51 O
ATOM 6772 CB TYR C 265 -24.041 45.517 -5.266 1.00 89.38 C
ATOM 6773 CG TYR C 265 -23.490 46.900 -5.189 1.00 89.34 C
ATOM 6774 CD1 TYR C 265 -24.316 47.972 -4.886 1.00 90.14 C
ATOM 6775 CD2 TYR C 265 -22.162 47.155 -5.523 1.00 90.59 C
ATOM 6776 CE1 TYR C 265 -23.840 49.280 -4.924 1.00 92.33 C
ATOM 6777 CE2 TYR C 265 -21.670 48.457 -5.565 1.00 92.63 C
ATOM 6778 CZ TYR C 265 -22.517 49.519 -5.266 1.00 92.95 C
ATOM 6779 OH TYR C 265 -22.043 50.815 -5.327 1.00 93.11 O
ATOM 6780 N LYS C 266 -23.214 45.355 -8.199 1.00 89.51 N
ATOM 6781 CA LYS C 266 -22.484 45.863 -9.356 1.00 90.13 C
ATOM 6782 C LYS C 266 -23.317 46.043 -10.630 1.00 89.83 C
ATOM 6783 O LYS C 266 -22.786 46.429 -11.674 1.00 89.92 O
ATOM 6784 CB LYS C 266 -21.284 44.950 -9.643 1.00 91.98 C
ATOM 6785 CG LYS C 266 -20.165 45.055 -8.607 1.00 93.52 C
ATOM 6786 CD LYS C 266 -19.118 43.946 -8.751 1.00 94.83 C
ATOM 6787 CE LYS C 266 -18.360 44.007 -10.080 1.00 95.81 C
ATOM 6788 NZ LYS C 266 -19.139 43.494 -11.253 1.00 96.25 N
ATOM 6789 N THR C 267 -24.615 45.774 -10.553 1.00 89.07 N
ATOM 6790 CA THR C 267 -25.481 45.925 -11.720 1.00 87.97 C
ATOM 6791 C THR C 267 -26.494 47.050 -11.506 1.00 88.38 C
ATOM 6792 O THR C 267 -27.320 47.344 -12.375 1.00 88.04 O
ATOM 6793 CB THR C 267 -26.230 44.630 -12.007 1.00 86.90 C
ATOM 6794 OG1 THR C 267 -27.202 44.405 -10.976 1.00 86.88 O
ATOM 6795 CG2 THR C 267 -25.249 43.474 -12.058 1.00 84.42 C
ATOM 6796 N GLY C 268 -26.417 47.667 -10.333 1.00 88.84 N
ATOM 6797 CA GLY C 268 -27.304 48.761 -9.990 1.00 88.87 C
ATOM 6798 C GLY C 268 -28.784 48.500 -10.201 1.00 89.07 C
ATOM 6799 O GLY C 268 -29.596 49.419 -10.092 1.00 90.27 O
ATOM 6800 N LEU C 269 -29.156 47.258 -10.478 1.00 87.70 N
ATOM 6801 CA LEU C 269 -30.558 46.957 -10.711 1.00 87.22 C
ATOM 6802 C LEU C 269 -31.323 46.402 -9.520 1.00 86.80 C
ATOM 6803 O LEU C 269 -32.388 45.802 -9.696 1.00 84.64 O
ATOM 6804 CB LEU C 269 -30.686 45.984 -11.876 1.00 88.82 C
ATOM 6805 CG LEU C 269 -30.217 46.494 -13.233 1.00 89.57 C
ATOM 6806 CD1 LEU C 269 -30.594 45.463 -14.287 1.00 89.71 C
ATOM 6807 CD2 LEU C 269 -30.871 47.840 -13.548 1.00 89.67 C
ATOM 6808 N LEU C 270 -30.797 46.600 -8.312 1.00 87.46 N
ATOM 6809 CA LEU C 270 -31.467 46.084 -7.118 1.00 88.00 C
ATOM 6810 C LEU C 270 -32.659 46.948 -6.759 1.00 87.09 C
ATOM 6811 O LEU C 270 -32.543 48.168 -6.644 1.00 87.38 O
ATOM 6812 CB LEU C 270 -30.519 46.021 -5.912 1.00 88.45 C
ATOM 6813 CG LEU C 270 -31.179 45.429 -4.650 1.00 88.79 C
ATOM 6814 CD1 LEU C 270 -31.360 43.923 -4.821 1.00 86.57 C
ATOM 6815 CD2 LEU C 270 -30.334 45.732 -3.420 1.00 88.64 C
ATOM 6816 N SER C 271 -33.806 46.311 -6.570 1.00 85.87 N
ATOM 6817 CA SER C 271 -35.001 47.055 -6.236 1.00 85.51 C
ATOM 6818 C SER C 271 -35.610 46.565 -4.918 1.00 83.98 C
ATOM 6819 O SER C 271 -35.984 47.371 -4.057 1.00 83.61 O
ATOM 6820 CB SER C 271 -36.002 46.932 -7.387 1.00 86.30 C
ATOM 6821 OG SER C 271 -36.794 48.101 -7.484 1.00 87.42 O
ATOM 6822 N GLY C 272 -35.693 45.245 -4.766 1.00 81.96 N
ATOM 6823 CA GLY C 272 -36.254 44.664 -3.560 1.00 78.89 C
ATOM 6824 C GLY C 272 -35.352 43.576 -3.009 1.00 76.86 C
ATOM 6825 O GLY C 272 -34.864 42.728 -3.760 1.00 75.55 O
ATOM 6826 N LEU C 273 -35.144 43.591 -1.696 1.00 74.99 N
ATOM 6827 CA LEU C 273 -34.273 42.617 -1.044 1.00 72.30 C
ATOM 6828 C LEU C 273 -34.960 41.876 0.105 1.00 70.78 C
ATOM 6829 O LEU C 273 -35.657 42.475 0.922 1.00 69.89 O
ATOM 6830 CB LEU C 273 -33.027 43.331 -0.503 1.00 71.11 C
ATOM 6831 CG LEU C 273 -31.658 42.640 -0.449 1.00 69.91 C
ATOM 6832 CD1 LEU C 273 -30.918 43.183 0.762 1.00 68.42 C
ATOM 6833 CD2 LEU C 273 -31.785 41.122 -0.354 1.00 68.44 C
ATOM 6834 N ASP C 274 -34.752 40.567 0.165 1.00 70.14 N
ATOM 6835 CA ASP C 274 -35.333 39.767 1.235 1.00 69.92 C
ATOM 6836 C ASP C 274 -34.273 38.987 2.026 1.00 68.55 C
ATOM 6837 O ASP C 274 -33.479 38.233 1.468 1.00 68.14 O
ATOM 6838 CB ASP C 274 -36.399 38.807 0.676 1.00 69.92 C
ATOM 6839 CG ASP C 274 -37.677 39.528 0.245 1.00 70.83 C
ATOM 6840 OD1 ASP C 274 -38.136 40.439 0.973 1.00 69.82 O
ATOM 6841 OD2 ASP C 274 -38.231 39.176 -0.816 1.00 71.83 O
ATOM 6842 N ILE C 275 -34.253 39.215 3.334 1.00 67.15 N
ATOM 6843 CA ILE C 275 -33.330 38.533 4.230 1.00 65.60 C
ATOM 6844 C ILE C 275 -34.230 37.775 5.198 1.00 65.13 C
ATOM 6845 O ILE C 275 -34.582 38.278 6.279 1.00 63.76 O
ATOM 6846 CB ILE C 275 -32.434 39.540 4.990 1.00 65.55 C
ATOM 6847 CG1 ILE C 275 -31.370 40.100 4.046 1.00 65.04 C
ATOM 6848 CG2 ILE C 275 -31.771 38.879 6.179 1.00 65.82 C
ATOM 6849 CD1 ILE C 275 -31.905 41.092 3.044 1.00 67.21 C
ATOM 6850 N MET C 276 -34.592 36.560 4.773 1.00 63.90 N
ATOM 6851 CA MET C 276 -35.497 35.677 5.501 1.00 62.24 C
ATOM 6852 C MET C 276 -34.823 34.496 6.167 1.00 61.84 C
ATOM 6853 O MET C 276 -33.631 34.251 5.970 1.00 60.99 O
ATOM 6854 CB MET C 276 -36.543 35.108 4.544 1.00 62.85 C
ATOM 6855 CG MET C 276 -36.998 36.061 3.469 1.00 66.01 C
ATOM 6856 SD MET C 276 -37.572 37.611 4.162 1.00 70.21 S
ATOM 6857 CE MET C 276 -38.808 36.970 5.337 1.00 69.59 C
ATOM 6858 N GLU C 277 -35.641 33.771 6.943 1.00 61.47 N
ATOM 6859 CA GLU C 277 -35.303 32.533 7.679 1.00 61.13 C
ATOM 6860 C GLU C 277 -34.294 32.571 8.819 1.00 60.56 C
ATOM 6861 O GLU C 277 -33.719 31.537 9.163 1.00 58.86 O
ATOM 6862 CB GLU C 277 -34.869 31.416 6.706 1.00 60.57 C
ATOM 6863 CG GLU C 277 -35.954 30.894 5.746 1.00 59.95 C
ATOM 6864 CD GLU C 277 -37.209 30.430 6.452 1.00 60.38 C
ATOM 6865 OE1 GLU C 277 -37.158 30.084 7.650 1.00 60.82 O
ATOM 6866 OE2 GLU C 277 -38.277 30.421 5.822 1.00 63.05 O
ATOM 6867 N VAL C 278 -34.073 33.737 9.409 1.00 60.40 N
ATOM 6868 CA VAL C 278 -33.127 33.815 10.507 1.00 61.42 C
ATOM 6869 C VAL C 278 -33.856 33.569 11.804 1.00 61.69 C
ATOM 6870 O VAL C 278 -34.746 34.336 12.137 1.00 62.84 O
ATOM 6871 CB VAL C 278 -32.488 35.183 10.615 1.00 61.62 C
ATOM 6872 CG1 VAL C 278 -31.780 35.285 11.948 1.00 60.45 C
ATOM 6873 CG2 VAL C 278 -31.497 35.392 9.479 1.00 63.02 C
ATOM 6874 N ASN C 279 -33.467 32.529 12.543 1.00 62.09 N
ATOM 6875 CA ASN C 279 -34.125 32.201 13.810 1.00 62.05 C
ATOM 6876 C ASN C 279 -33.226 32.376 15.021 1.00 62.56 C
ATOM 6877 O ASN C 279 -32.710 31.393 15.536 1.00 62.08 O
ATOM 6878 CB ASN C 279 -34.618 30.756 13.793 1.00 61.37 C
ATOM 6879 CG ASN C 279 -35.914 30.580 14.562 1.00 60.61 C
ATOM 6880 OD1 ASN C 279 -36.198 31.330 15.501 1.00 58.30 O
ATOM 6881 ND2 ASN C 279 -36.708 29.583 14.169 1.00 57.50 N
ATOM 6882 N PRO C 280 -33.045 33.625 15.503 1.00 64.39 N
ATOM 6883 CA PRO C 280 -32.217 34.020 16.657 1.00 67.08 C
ATOM 6884 C PRO C 280 -32.314 33.136 17.898 1.00 69.58 C
ATOM 6885 O PRO C 280 -31.664 33.394 18.912 1.00 69.61 O
ATOM 6886 CB PRO C 280 -32.678 35.450 16.931 1.00 65.11 C
ATOM 6887 CG PRO C 280 -32.904 35.957 15.583 1.00 64.36 C
ATOM 6888 CD PRO C 280 -33.673 34.818 14.915 1.00 64.19 C
ATOM 6889 N THR C 281 -33.124 32.092 17.798 1.00 72.57 N
ATOM 6890 CA THR C 281 -33.326 31.164 18.893 1.00 75.80 C
ATOM 6891 C THR C 281 -32.786 29.785 18.538 1.00 76.44 C
ATOM 6892 O THR C 281 -32.366 29.027 19.410 1.00 76.53 O
ATOM 6893 CB THR C 281 -34.822 31.069 19.226 1.00 76.94 C
ATOM 6894 OG1 THR C 281 -35.575 31.023 18.008 1.00 79.55 O
ATOM 6895 CG2 THR C 281 -35.266 32.279 20.029 1.00 77.78 C
ATOM 6896 N LEU C 282 -32.796 29.461 17.253 1.00 78.33 N
ATOM 6897 CA LEU C 282 -32.299 28.170 16.812 1.00 80.29 C
ATOM 6898 C LEU C 282 -30.784 28.173 16.728 1.00 83.19 C
ATOM 6899 O LEU C 282 -30.211 27.961 15.662 1.00 85.02 O
ATOM 6900 CB LEU C 282 -32.904 27.789 15.458 1.00 77.40 C
ATOM 6901 CG LEU C 282 -34.421 27.645 15.516 1.00 75.93 C
ATOM 6902 CD1 LEU C 282 -34.953 27.080 14.219 1.00 75.40 C
ATOM 6903 CD2 LEU C 282 -34.776 26.743 16.671 1.00 75.90 C
ATOM 6904 N GLY C 283 -30.138 28.427 17.861 1.00 85.07 N
ATOM 6905 CA GLY C 283 -28.687 28.423 17.900 1.00 86.60 C
ATOM 6906 C GLY C 283 -28.170 27.376 18.879 1.00 87.56 C
ATOM 6907 O GLY C 283 -28.531 27.400 20.064 1.00 88.62 O
ATOM 6908 N LYS C 284 -27.345 26.450 18.381 1.00 86.77 N
ATOM 6909 CA LYS C 284 -26.763 25.389 19.209 1.00 85.88 C
ATOM 6910 C LYS C 284 -25.985 26.071 20.328 1.00 85.02 C
ATOM 6911 O LYS C 284 -25.950 25.589 21.465 1.00 84.12 O
ATOM 6912 CB LYS C 284 -25.806 24.523 18.379 1.00 87.29 C
ATOM 6913 CG LYS C 284 -25.815 23.025 18.701 1.00 87.71 C
ATOM 6914 CD LYS C 284 -26.790 22.259 17.802 1.00 87.88 C
ATOM 6915 CE LYS C 284 -28.228 22.740 17.990 1.00 88.18 C
ATOM 6916 NZ LYS C 284 -29.191 22.144 17.026 1.00 87.29 N
ATOM 6917 N THR C 285 -25.363 27.198 19.976 1.00 84.15 N
ATOM 6918 CA THR C 285 -24.589 28.016 20.900 1.00 83.26 C
ATOM 6919 C THR C 285 -24.749 29.473 20.484 1.00 82.99 C
ATOM 6920 O THR C 285 -24.942 29.782 19.306 1.00 81.31 O
ATOM 6921 CB THR C 285 -23.090 27.697 20.850 1.00 83.35 C
ATOM 6922 OG1 THR C 285 -22.517 28.265 19.663 1.00 84.05 O
ATOM 6923 CG2 THR C 285 -22.866 26.198 20.848 1.00 84.61 C
ATOM 6924 N PRO C 286 -24.668 30.389 21.455 1.00 83.41 N
ATOM 6925 CA PRO C 286 -24.795 31.829 21.225 1.00 82.95 C
ATOM 6926 C PRO C 286 -23.996 32.341 20.027 1.00 82.76 C
ATOM 6927 O PRO C 286 -24.479 33.195 19.279 1.00 83.94 O
ATOM 6928 CB PRO C 286 -24.326 32.416 22.547 1.00 83.43 C
ATOM 6929 CG PRO C 286 -24.896 31.430 23.532 1.00 83.83 C
ATOM 6930 CD PRO C 286 -24.526 30.101 22.896 1.00 84.08 C
ATOM 6931 N GLU C 287 -22.779 31.833 19.855 1.00 81.54 N
ATOM 6932 CA GLU C 287 -21.938 32.235 18.729 1.00 80.48 C
ATOM 6933 C GLU C 287 -22.671 31.956 17.408 1.00 79.49 C
ATOM 6934 O GLU C 287 -22.880 32.867 16.598 1.00 78.67 O
ATOM 6935 CB GLU C 287 -20.606 31.467 18.780 1.00 82.25 C
ATOM 6936 CG GLU C 287 -20.127 30.825 17.456 1.00 83.83 C
ATOM 6937 CD GLU C 287 -19.708 31.837 16.378 1.00 84.57 C
ATOM 6938 OE1 GLU C 287 -20.594 32.497 15.797 1.00 85.56 O
ATOM 6939 OE2 GLU C 287 -18.491 31.972 16.106 1.00 84.28 O
ATOM 6940 N GLU C 288 -23.058 30.696 17.205 1.00 77.25 N
ATOM 6941 CA GLU C 288 -23.774 30.279 16.002 1.00 73.95 C
ATOM 6942 C GLU C 288 -24.805 31.309 15.584 1.00 72.69 C
ATOM 6943 O GLU C 288 -24.928 31.627 14.406 1.00 72.64 O
ATOM 6944 CB GLU C 288 -24.477 28.950 16.233 1.00 72.46 C
ATOM 6945 CG GLU C 288 -23.537 27.811 16.548 1.00 70.50 C
ATOM 6946 CD GLU C 288 -24.157 26.462 16.247 1.00 69.40 C
ATOM 6947 OE1 GLU C 288 -25.364 26.431 15.906 1.00 68.54 O
ATOM 6948 OE2 GLU C 288 -23.444 25.435 16.352 1.00 68.62 O
ATOM 6949 N VAL C 289 -25.565 31.812 16.553 1.00 71.45 N
ATOM 6950 CA VAL C 289 -26.567 32.835 16.268 1.00 70.18 C
ATOM 6951 C VAL C 289 -25.771 34.033 15.764 1.00 69.20 C
ATOM 6952 O VAL C 289 -25.810 34.351 14.577 1.00 68.99 O
ATOM 6953 CB VAL C 289 -27.389 33.242 17.545 1.00 69.79 C
ATOM 6954 CG1 VAL C 289 -28.427 34.300 17.193 1.00 67.62 C
ATOM 6955 CG2 VAL C 289 -28.097 32.019 18.129 1.00 69.71 C
ATOM 6956 N THR C 290 -25.039 34.680 16.669 1.00 68.00 N
ATOM 6957 CA THR C 290 -24.216 35.837 16.317 1.00 66.88 C
ATOM 6958 C THR C 290 -23.624 35.684 14.913 1.00 66.56 C
ATOM 6959 O THR C 290 -23.688 36.604 14.088 1.00 66.19 O
ATOM 6960 CB THR C 290 -23.068 36.012 17.323 1.00 65.35 C
ATOM 6961 OG1 THR C 290 -23.620 36.329 18.600 1.00 63.64 O
ATOM 6962 CG2 THR C 290 -22.130 37.120 16.885 1.00 64.85 C
ATOM 6963 N ARG C 291 -23.042 34.515 14.661 1.00 65.26 N
ATOM 6964 CA ARG C 291 -22.446 34.204 13.363 1.00 64.06 C
ATOM 6965 C ARG C 291 -23.522 34.491 12.325 1.00 63.34 C
ATOM 6966 O ARG C 291 -23.416 35.415 11.513 1.00 64.70 O
ATOM 6967 CB ARG C 291 -22.070 32.722 13.315 1.00 61.65 C
ATOM 6968 CG ARG C 291 -21.321 32.273 12.084 1.00 58.64 C
ATOM 6969 CD ARG C 291 -20.982 30.796 12.223 1.00 56.90 C
ATOM 6970 NE ARG C 291 -20.501 30.514 13.572 1.00 57.01 N
ATOM 6971 CZ ARG C 291 -20.356 29.298 14.096 1.00 57.06 C
ATOM 6972 NH1 ARG C 291 -20.652 28.215 13.378 1.00 57.97 N
ATOM 6973 NH2 ARG C 291 -19.947 29.164 15.355 1.00 55.48 N
ATOM 6974 N THR C 292 -24.571 33.685 12.396 1.00 61.05 N
ATOM 6975 CA THR C 292 -25.714 33.772 11.514 1.00 58.67 C
ATOM 6976 C THR C 292 -26.176 35.209 11.320 1.00 58.47 C
ATOM 6977 O THR C 292 -26.492 35.637 10.215 1.00 57.49 O
ATOM 6978 CB THR C 292 -26.865 32.949 12.101 1.00 58.81 C
ATOM 6979 OG1 THR C 292 -26.421 31.598 12.348 1.00 56.48 O
ATOM 6980 CG2 THR C 292 -28.060 32.957 11.147 1.00 59.71 C
ATOM 6981 N VAL C 293 -26.198 35.955 12.413 1.00 59.78 N
ATOM 6982 CA VAL C 293 -26.636 37.340 12.392 1.00 58.82 C
ATOM 6983 C VAL C 293 -25.748 38.280 11.596 1.00 58.73 C
ATOM 6984 O VAL C 293 -26.230 38.991 10.724 1.00 60.24 O
ATOM 6985 CB VAL C 293 -26.773 37.867 13.817 1.00 57.64 C
ATOM 6986 CG1 VAL C 293 -26.797 39.368 13.819 1.00 59.61 C
ATOM 6987 CG2 VAL C 293 -28.046 37.323 14.426 1.00 56.78 C
ATOM 6988 N ASN C 294 -24.457 38.297 11.882 1.00 59.01 N
ATOM 6989 CA ASN C 294 -23.562 39.196 11.157 1.00 59.52 C
ATOM 6990 C ASN C 294 -23.461 38.852 9.677 1.00 57.04 C
ATOM 6991 O ASN C 294 -23.614 39.719 8.825 1.00 56.04 O
ATOM 6992 CB ASN C 294 -22.180 39.183 11.807 1.00 62.65 C
ATOM 6993 CG ASN C 294 -22.242 39.493 13.295 1.00 65.74 C
ATOM 6994 OD1 ASN C 294 -22.705 40.574 13.705 1.00 65.73 O
ATOM 6995 ND2 ASN C 294 -21.789 38.541 14.117 1.00 65.75 N
ATOM 6996 N THR C 295 -23.210 37.584 9.374 1.00 55.78 N
ATOM 6997 CA THR C 295 -23.116 37.131 7.986 1.00 53.42 C
ATOM 6998 C THR C 295 -24.360 37.601 7.211 1.00 51.63 C
ATOM 6999 O THR C 295 -24.282 38.017 6.046 1.00 51.32 O
ATOM 7000 CB THR C 295 -22.999 35.585 7.925 1.00 51.74 C
ATOM 7001 OG1 THR C 295 -22.957 35.154 6.564 1.00 51.03 O
ATOM 7002 CG2 THR C 295 -24.188 34.938 8.600 1.00 52.14 C
ATOM 7003 N ALA C 296 -25.506 37.535 7.871 1.00 48.87 N
ATOM 7004 CA ALA C 296 -26.735 37.984 7.263 1.00 48.83 C
ATOM 7005 C ALA C 296 -26.574 39.489 7.025 1.00 49.86 C
ATOM 7006 O ALA C 296 -26.649 39.974 5.894 1.00 48.11 O
ATOM 7007 CB ALA C 296 -27.876 37.715 8.197 1.00 48.98 C
ATOM 7008 N VAL C 297 -26.326 40.207 8.117 1.00 51.36 N
ATOM 7009 CA VAL C 297 -26.105 41.651 8.102 1.00 53.60 C
ATOM 7010 C VAL C 297 -25.119 42.001 6.996 1.00 55.78 C
ATOM 7011 O VAL C 297 -25.353 42.901 6.179 1.00 58.28 O
ATOM 7012 CB VAL C 297 -25.490 42.125 9.446 1.00 53.14 C
ATOM 7013 CG1 VAL C 297 -24.996 43.557 9.341 1.00 50.59 C
ATOM 7014 CG2 VAL C 297 -26.517 42.000 10.554 1.00 54.44 C
ATOM 7015 N ALA C 298 -24.007 41.284 6.988 1.00 56.73 N
ATOM 7016 CA ALA C 298 -22.964 41.499 6.015 1.00 58.92 C
ATOM 7017 C ALA C 298 -23.532 41.351 4.614 1.00 61.14 C
ATOM 7018 O ALA C 298 -23.238 42.165 3.735 1.00 62.85 O
ATOM 7019 CB ALA C 298 -21.835 40.494 6.242 1.00 58.61 C
ATOM 7020 N LEU C 299 -24.340 40.314 4.397 1.00 60.82 N
ATOM 7021 CA LEU C 299 -24.910 40.100 3.075 1.00 61.09 C
ATOM 7022 C LEU C 299 -25.771 41.280 2.618 1.00 62.91 C
ATOM 7023 O LEU C 299 -25.934 41.498 1.419 1.00 65.11 O
ATOM 7024 CB LEU C 299 -25.757 38.826 3.040 1.00 57.81 C
ATOM 7025 CG LEU C 299 -25.138 37.427 2.971 1.00 55.38 C
ATOM 7026 CD1 LEU C 299 -26.268 36.467 2.740 1.00 53.96 C
ATOM 7027 CD2 LEU C 299 -24.143 37.269 1.841 1.00 51.97 C
ATOM 7028 N THR C 300 -26.327 42.038 3.557 1.00 62.76 N
ATOM 7029 CA THR C 300 -27.162 43.172 3.181 1.00 62.65 C
ATOM 7030 C THR C 300 -26.286 44.286 2.656 1.00 61.32 C
ATOM 7031 O THR C 300 -26.383 44.662 1.493 1.00 59.77 O
ATOM 7032 CB THR C 300 -27.963 43.711 4.378 1.00 63.73 C
ATOM 7033 OG1 THR C 300 -28.508 42.618 5.125 1.00 65.35 O
ATOM 7034 CG2 THR C 300 -29.119 44.587 3.892 1.00 63.25 C
ATOM 7035 N LEU C 301 -25.438 44.804 3.537 1.00 60.60 N
ATOM 7036 CA LEU C 301 -24.492 45.862 3.202 1.00 62.25 C
ATOM 7037 C LEU C 301 -23.715 45.529 1.936 1.00 62.75 C
ATOM 7038 O LEU C 301 -23.016 46.372 1.385 1.00 61.14 O
ATOM 7039 CB LEU C 301 -23.491 46.045 4.342 1.00 62.64 C
ATOM 7040 CG LEU C 301 -24.070 46.408 5.704 1.00 63.60 C
ATOM 7041 CD1 LEU C 301 -23.018 46.275 6.800 1.00 64.16 C
ATOM 7042 CD2 LEU C 301 -24.587 47.827 5.624 1.00 64.47 C
ATOM 7043 N SER C 302 -23.811 44.281 1.498 1.00 65.66 N
ATOM 7044 CA SER C 302 -23.114 43.852 0.296 1.00 67.63 C
ATOM 7045 C SER C 302 -23.919 44.359 -0.888 1.00 69.13 C
ATOM 7046 O SER C 302 -23.392 45.036 -1.774 1.00 70.32 O
ATOM 7047 CB SER C 302 -23.008 42.328 0.262 1.00 67.19 C
ATOM 7048 OG SER C 302 -22.107 41.917 -0.746 1.00 69.11 O
ATOM 7049 N CYS C 303 -25.209 44.043 -0.867 1.00 70.31 N
ATOM 7050 CA CYS C 303 -26.152 44.460 -1.897 1.00 71.32 C
ATOM 7051 C CYS C 303 -26.206 45.979 -2.024 1.00 72.31 C
ATOM 7052 O CYS C 303 -26.758 46.516 -2.987 1.00 72.83 O
ATOM 7053 CB CYS C 303 -27.546 43.974 -1.531 1.00 71.03 C
ATOM 7054 SG CYS C 303 -27.601 42.247 -1.161 1.00 72.69 S
ATOM 7055 N PHE C 304 -25.632 46.672 -1.048 1.00 73.09 N
ATOM 7056 CA PHE C 304 -25.665 48.119 -1.046 1.00 72.61 C
ATOM 7057 C PHE C 304 -24.326 48.830 -1.129 1.00 73.36 C
ATOM 7058 O PHE C 304 -24.154 49.897 -0.536 1.00 74.39 O
ATOM 7059 CB PHE C 304 -26.420 48.584 0.188 1.00 71.80 C
ATOM 7060 CG PHE C 304 -27.834 48.101 0.233 1.00 71.95 C
ATOM 7061 CD1 PHE C 304 -28.813 48.705 -0.548 1.00 72.36 C
ATOM 7062 CD2 PHE C 304 -28.186 47.022 1.029 1.00 72.11 C
ATOM 7063 CE1 PHE C 304 -30.125 48.241 -0.536 1.00 71.54 C
ATOM 7064 CE2 PHE C 304 -29.495 46.551 1.047 1.00 72.05 C
ATOM 7065 CZ PHE C 304 -30.466 47.164 0.261 1.00 71.30 C
ATOM 7066 N GLY C 305 -23.374 48.253 -1.855 1.00 72.86 N
ATOM 7067 CA GLY C 305 -22.100 48.929 -1.993 1.00 72.03 C
ATOM 7068 C GLY C 305 -20.854 48.206 -1.542 1.00 71.73 C
ATOM 7069 O GLY C 305 -20.025 47.825 -2.377 1.00 72.28 O
ATOM 7070 N THR C 306 -20.712 48.034 -0.227 1.00 70.88 N
ATOM 7071 CA THR C 306 -19.545 47.369 0.341 1.00 69.05 C
ATOM 7072 C THR C 306 -19.032 46.264 -0.585 1.00 69.72 C
ATOM 7073 O THR C 306 -19.784 45.374 -1.028 1.00 68.72 O
ATOM 7074 CB THR C 306 -19.844 46.765 1.709 1.00 66.56 C
ATOM 7075 OG1 THR C 306 -20.766 47.601 2.408 1.00 65.69 O
ATOM 7076 CG2 THR C 306 -18.573 46.674 2.517 1.00 65.22 C
ATOM 7077 N LYS C 307 -17.740 46.354 -0.883 1.00 69.29 N
ATOM 7078 CA LYS C 307 -17.051 45.418 -1.757 1.00 69.35 C
ATOM 7079 C LYS C 307 -15.970 44.776 -0.901 1.00 68.64 C
ATOM 7080 O LYS C 307 -15.589 45.336 0.117 1.00 68.97 O
ATOM 7081 CB LYS C 307 -16.458 46.199 -2.935 1.00 69.94 C
ATOM 7082 CG LYS C 307 -17.487 47.167 -3.547 1.00 71.55 C
ATOM 7083 CD LYS C 307 -16.851 48.305 -4.351 1.00 75.08 C
ATOM 7084 CE LYS C 307 -16.374 47.843 -5.716 1.00 76.43 C
ATOM 7085 NZ LYS C 307 -17.522 47.364 -6.547 1.00 77.73 N
ATOM 7086 N ARG C 308 -15.490 43.598 -1.275 1.00 68.82 N
ATOM 7087 CA ARG C 308 -14.465 42.962 -0.463 1.00 69.63 C
ATOM 7088 C ARG C 308 -13.070 43.478 -0.814 1.00 73.65 C
ATOM 7089 O ARG C 308 -12.043 42.942 -0.358 1.00 74.33 O
ATOM 7090 CB ARG C 308 -14.543 41.438 -0.597 1.00 65.67 C
ATOM 7091 CG ARG C 308 -15.371 40.791 0.514 1.00 61.84 C
ATOM 7092 CD ARG C 308 -15.506 39.296 0.351 1.00 56.86 C
ATOM 7093 NE ARG C 308 -16.356 38.976 -0.784 1.00 51.40 N
ATOM 7094 CZ ARG C 308 -16.196 37.906 -1.549 1.00 51.56 C
ATOM 7095 NH1 ARG C 308 -15.211 37.050 -1.299 1.00 50.69 N
ATOM 7096 NH2 ARG C 308 -17.015 37.692 -2.566 1.00 53.11 N
ATOM 7097 N GLU C 309 -13.038 44.534 -1.619 1.00 76.34 N
ATOM 7098 CA GLU C 309 -11.779 45.127 -2.009 1.00 78.81 C
ATOM 7099 C GLU C 309 -11.648 46.494 -1.362 1.00 81.14 C
ATOM 7100 O GLU C 309 -10.577 47.103 -1.381 1.00 80.97 O
ATOM 7101 CB GLU C 309 -11.696 45.247 -3.527 1.00 78.42 C
ATOM 7102 CG GLU C 309 -12.736 46.144 -4.133 1.00 79.83 C
ATOM 7103 CD GLU C 309 -12.273 46.717 -5.453 1.00 80.70 C
ATOM 7104 OE1 GLU C 309 -12.021 45.924 -6.392 1.00 79.92 O
ATOM 7105 OE2 GLU C 309 -12.154 47.961 -5.545 1.00 80.64 O
ATOM 7106 N GLY C 310 -12.745 46.970 -0.784 1.00 84.23 N
ATOM 7107 CA GLY C 310 -12.735 48.265 -0.129 1.00 88.85 C
ATOM 7108 C GLY C 310 -13.747 49.263 -0.672 1.00 92.10 C
ATOM 7109 O GLY C 310 -14.419 49.014 -1.668 1.00 91.07 O
ATOM 7110 N ASN C 311 -13.837 50.408 -0.004 1.00 97.12 N
ATOM 7111 CA ASN C 311 -14.739 51.495 -0.374 1.00102.29 C
ATOM 7112 C ASN C 311 -14.133 52.790 0.187 1.00106.18 C
ATOM 7113 O ASN C 311 -13.600 52.796 1.304 1.00107.49 O
ATOM 7114 CB ASN C 311 -16.135 51.284 0.240 1.00102.14 C
ATOM 7115 CG ASN C 311 -16.881 50.093 -0.359 1.00102.71 C
ATOM 7116 OD1 ASN C 311 -17.191 50.075 -1.550 1.00103.04 O
ATOM 7117 ND2 ASN C 311 -17.176 49.094 0.473 1.00102.31 N
ATOM 7118 N HIS C 312 -14.198 53.873 -0.588 1.00109.68 N
ATOM 7119 CA HIS C 312 -13.667 55.169 -0.154 1.00112.52 C
ATOM 7120 C HIS C 312 -14.519 56.304 -0.733 1.00113.52 C
ATOM 7121 O HIS C 312 -14.763 56.353 -1.944 1.00113.20 O
ATOM 7122 CB HIS C 312 -12.204 55.334 -0.599 1.00114.32 C
ATOM 7123 CG HIS C 312 -12.034 55.529 -2.077 1.00117.06 C
ATOM 7124 ND1 HIS C 312 -12.164 54.503 -2.985 1.00118.23 N
ATOM 7125 CD2 HIS C 312 -11.781 56.648 -2.801 1.00118.21 C
ATOM 7126 CE1 HIS C 312 -12.002 54.979 -4.211 1.00118.99 C
ATOM 7127 NE2 HIS C 312 -11.769 56.276 -4.125 1.00119.29 N
ATOM 7128 N LYS C 313 -14.977 57.207 0.131 1.00114.77 N
ATOM 7129 CA LYS C 313 -15.803 58.331 -0.308 1.00116.23 C
ATOM 7130 C LYS C 313 -15.102 59.055 -1.454 1.00117.88 C
ATOM 7131 O LYS C 313 -13.966 59.512 -1.305 1.00118.20 O
ATOM 7132 CB LYS C 313 -16.040 59.291 0.858 1.00115.55 C
ATOM 7133 CG LYS C 313 -16.682 58.641 2.078 1.00114.52 C
ATOM 7134 CD LYS C 313 -16.724 59.619 3.246 1.00113.62 C
ATOM 7135 CE LYS C 313 -17.241 58.977 4.524 1.00111.93 C
ATOM 7136 NZ LYS C 313 -17.194 59.936 5.666 1.00109.72 N
ATOM 7137 N PRO C 314 -15.766 59.158 -2.620 1.00119.02 N
ATOM 7138 CA PRO C 314 -15.190 59.828 -3.789 1.00119.57 C
ATOM 7139 C PRO C 314 -14.955 61.320 -3.589 1.00120.29 C
ATOM 7140 O PRO C 314 -15.468 61.931 -2.643 1.00119.94 O
ATOM 7141 CB PRO C 314 -16.221 59.565 -4.886 1.00119.10 C
ATOM 7142 CG PRO C 314 -16.864 58.291 -4.456 1.00119.32 C
ATOM 7143 CD PRO C 314 -17.045 58.522 -2.976 1.00119.29 C
ATOM 7144 N GLU C 315 -14.171 61.891 -4.499 1.00120.71 N
ATOM 7145 CA GLU C 315 -13.845 63.311 -4.488 1.00120.73 C
ATOM 7146 C GLU C 315 -13.066 63.768 -3.263 1.00119.42 C
ATOM 7147 O GLU C 315 -12.851 64.966 -3.067 1.00119.59 O
ATOM 7148 CB GLU C 315 -15.126 64.140 -4.633 1.00122.78 C
ATOM 7149 CG GLU C 315 -15.743 64.063 -6.027 1.00124.50 C
ATOM 7150 CD GLU C 315 -17.087 64.757 -6.119 1.00125.58 C
ATOM 7151 OE1 GLU C 315 -17.623 64.847 -7.242 1.00125.94 O
ATOM 7152 OE2 GLU C 315 -17.609 65.204 -5.073 1.00126.86 O
ATOM 7153 N THR C 316 -12.649 62.818 -2.435 1.00117.54 N
ATOM 7154 CA THR C 316 -11.869 63.158 -1.255 1.00115.78 C
ATOM 7155 C THR C 316 -10.466 62.627 -1.492 1.00113.97 C
ATOM 7156 O THR C 316 -10.295 61.487 -1.921 1.00113.84 O
ATOM 7157 CB THR C 316 -12.452 62.524 0.042 1.00116.09 C
ATOM 7158 OG1 THR C 316 -13.784 63.009 0.255 1.00116.18 O
ATOM 7159 CG2 THR C 316 -11.589 62.889 1.258 1.00115.05 C
ATOM 7160 N ASP C 317 -9.473 63.478 -1.245 1.00111.82 N
ATOM 7161 CA ASP C 317 -8.072 63.108 -1.408 1.00109.43 C
ATOM 7162 C ASP C 317 -7.587 62.618 -0.043 1.00109.27 C
ATOM 7163 O ASP C 317 -7.352 63.414 0.876 1.00109.58 O
ATOM 7164 CB ASP C 317 -7.258 64.323 -1.894 1.00106.72 C
ATOM 7165 CG ASP C 317 -5.768 64.025 -2.060 1.00104.53 C
ATOM 7166 OD1 ASP C 317 -5.405 63.058 -2.761 1.00103.22 O
ATOM 7167 OD2 ASP C 317 -4.950 64.777 -1.491 1.00102.42 O
ATOM 7168 N TYR C 318 -7.478 61.292 0.084 1.00108.87 N
ATOM 7169 CA TYR C 318 -7.032 60.644 1.315 1.00108.47 C
ATOM 7170 C TYR C 318 -5.520 60.763 1.448 1.00109.21 C
ATOM 7171 O TYR C 318 -4.915 60.142 2.311 1.00108.22 O
ATOM 7172 CB TYR C 318 -7.439 59.165 1.313 1.00107.18 C
ATOM 7173 CG TYR C 318 -8.907 58.878 1.614 1.00105.92 C
ATOM 7174 CD1 TYR C 318 -9.418 58.991 2.917 1.00104.92 C
ATOM 7175 CD2 TYR C 318 -9.781 58.459 0.605 1.00104.89 C
ATOM 7176 CE1 TYR C 318 -10.764 58.689 3.204 1.00103.58 C
ATOM 7177 CE2 TYR C 318 -11.127 58.156 0.881 1.00104.05 C
ATOM 7178 CZ TYR C 318 -11.608 58.272 2.179 1.00103.64 C
ATOM 7179 OH TYR C 318 -12.927 57.973 2.443 1.00102.85 O
ATOM 7180 N LEU C 319 -4.925 61.568 0.574 1.00111.27 N
ATOM 7181 CA LEU C 319 -3.482 61.820 0.566 1.00112.79 C
ATOM 7182 C LEU C 319 -3.164 63.199 1.177 1.00113.76 C
ATOM 7183 O LEU C 319 -2.466 63.244 2.222 1.00114.70 O
ATOM 7184 CB LEU C 319 -2.940 61.768 -0.872 1.00111.81 C
ATOM 7185 CG LEU C 319 -2.749 60.393 -1.510 1.00110.60 C
ATOM 7186 CD1 LEU C 319 -2.346 60.548 -2.969 1.00109.61 C
ATOM 7187 CD2 LEU C 319 -1.684 59.631 -0.730 1.00109.90 C
TER 7188 LEU C 319
HETATM 7189 MN MN A 500 -0.105 42.231 7.506 1.00 67.49 MN
HETATM 7190 MN MN A 501 -3.619 40.640 7.969 1.00 56.97 MN
HETATM 7191 N HAR A 906 -4.248 48.081 7.923 1.00 64.15 N
HETATM 7192 CA HAR A 906 -5.197 48.023 9.112 1.00 65.82 C
HETATM 7193 C HAR A 906 -4.618 48.827 10.404 1.00 67.85 C
HETATM 7194 O HAR A 906 -5.328 48.805 11.513 1.00 67.91 O
HETATM 7195 CB HAR A 906 -5.473 46.547 9.503 1.00 62.42 C
HETATM 7196 CG HAR A 906 -4.329 45.979 10.273 1.00 59.37 C
HETATM 7197 CD HAR A 906 -3.927 44.648 9.756 1.00 57.53 C
HETATM 7198 NE HAR A 906 -2.776 44.175 10.510 1.00 55.07 N
HETATM 7199 CZ HAR A 906 -2.142 43.037 10.299 1.00 53.02 C
HETATM 7200 NH1 HAR A 906 -2.527 42.193 9.331 1.00 53.12 N
HETATM 7201 NH2 HAR A 906 -1.092 42.735 11.048 1.00 53.69 N
HETATM 7202 OH1 HAR A 906 -1.802 41.073 9.157 1.00 52.94 O
HETATM 7203 OXT HAR A 906 -3.457 49.433 10.293 1.00 70.33 O
HETATM 7204 MN MN B 502 -7.166 3.574 -0.012 1.00 67.49 MN
HETATM 7205 MN MN B 503 -6.846 7.018 1.758 1.00 56.97 MN
HETATM 7206 N HAR B 907 -0.036 4.190 0.576 1.00 64.15 N
HETATM 7207 CA HAR B 907 0.387 4.581 1.985 1.00 65.82 C
HETATM 7208 C HAR B 907 0.823 3.292 2.879 1.00 67.85 C
HETATM 7209 O HAR B 907 1.161 3.499 4.135 1.00 67.91 O
HETATM 7210 CB HAR B 907 -0.765 5.338 2.697 1.00 62.42 C
HETATM 7211 CG HAR B 907 -1.808 4.387 3.178 1.00 59.37 C
HETATM 7212 CD HAR B 907 -3.173 4.838 2.810 1.00 57.53 C
HETATM 7213 NE HAR B 907 -4.137 3.844 3.257 1.00 55.07 N
HETATM 7214 CZ HAR B 907 -5.442 3.910 3.072 1.00 53.02 C
HETATM 7215 NH1 HAR B 907 -6.003 4.945 2.430 1.00 53.12 N
HETATM 7216 NH2 HAR B 907 -6.207 2.923 3.513 1.00 53.69 N
HETATM 7217 OH1 HAR B 907 -7.336 4.916 2.250 1.00 52.94 O
HETATM 7218 OXT HAR B 907 0.788 2.104 2.319 1.00 70.33 O
HETATM 7219 MN MN C 504 -37.524 29.674 1.725 1.00 67.49 MN
HETATM 7220 MN MN C 505 -34.646 27.277 2.757 1.00 56.97 MN
HETATM 7221 N HAR C 908 -40.478 23.270 0.371 1.00 64.15 N
HETATM 7222 CA HAR C 908 -40.316 22.310 1.540 1.00 65.82 C
HETATM 7223 C HAR C 908 -41.633 22.271 2.496 1.00 67.85 C
HETATM 7224 O HAR C 908 -41.593 21.513 3.572 1.00 67.91 O
HETATM 7225 CB HAR C 908 -39.075 22.703 2.386 1.00 62.42 C
HETATM 7226 CG HAR C 908 -39.381 23.867 3.267 1.00 59.37 C
HETATM 7227 CD HAR C 908 -38.326 24.906 3.189 1.00 57.53 C
HETATM 7228 NE HAR C 908 -38.709 26.034 4.024 1.00 55.07 N
HETATM 7229 CZ HAR C 908 -38.014 27.146 4.169 1.00 53.02 C
HETATM 7230 NH1 HAR C 908 -36.851 27.330 3.529 1.00 53.12 N
HETATM 7231 NH2 HAR C 908 -38.488 28.107 4.949 1.00 53.69 N
HETATM 7232 OH1 HAR C 908 -36.225 28.509 3.700 1.00 52.94 O
HETATM 7233 OXT HAR C 908 -42.663 23.020 2.169 1.00 70.33 O
HETATM 7234 O HOH A 601 -4.336 39.787 11.132 1.00 30.80 O
HETATM 7235 O HOH A 602 12.633 23.151 13.834 1.00 72.37 O
HETATM 7236 O HOH A 603 -0.705 37.841 15.495 1.00 72.08 O
HETATM 7237 O HOH A 604 -12.526 31.118 -6.884 1.00 44.81 O
HETATM 7238 O HOH A 605 -15.138 31.020 -5.114 1.00 31.75 O
HETATM 7239 O HOH B 606 -7.208 6.890 5.089 1.00 30.80 O
HETATM 7240 O HOH B 607 -29.959 -0.474 5.507 1.00 72.37 O
HETATM 7241 O HOH B 608 -10.623 3.267 8.438 1.00 72.08 O
HETATM 7242 O HOH B 609 -11.012 23.809 -7.798 1.00 44.81 O
HETATM 7243 O HOH B 610 -9.810 25.382 -5.340 1.00 31.75 O
HETATM 7244 O HOH C 611 -34.509 26.628 6.045 1.00 30.80 O
HETATM 7245 O HOH C 612 -29.740 48.863 13.452 1.00 72.37 O
HETATM 7246 O HOH C 613 -35.917 30.135 10.706 1.00 72.08 O
HETATM 7247 O HOH C 614 -18.178 25.878 -8.082 1.00 44.81 O
HETATM 7248 O HOH C 615 -17.347 23.403 -6.306 1.00 31.75 O
CONECT 714 7189
CONECT 887 7190
CONECT 888 7189
CONECT 900 7190
CONECT 918 7189
CONECT 1738 7190
CONECT 1752 7190
CONECT 1753 7190
CONECT 3110 7204
CONECT 3283 7205
CONECT 3284 7204
CONECT 3296 7205
CONECT 3314 7204
CONECT 4134 7205
CONECT 4148 7205
CONECT 4149 7205
CONECT 5506 7219
CONECT 5679 7220
CONECT 5680 7219
CONECT 5692 7220
CONECT 5710 7219
CONECT 6530 7220
CONECT 6544 7220
CONECT 6545 7220
CONECT 7189 714 888 918 7202
CONECT 7190 887 900 1738 1752
CONECT 7190 1753 7200 7202
CONECT 7191 7192
CONECT 7192 7191 7193 7195
CONECT 7193 7192 7194 7203
CONECT 7194 7193
CONECT 7195 7192 7196
CONECT 7196 7195 7197
CONECT 7197 7196 7198
CONECT 7198 7197 7199
CONECT 7199 7198 7200 7201
CONECT 7200 7190 7199 7202
CONECT 7201 7199
CONECT 7202 7189 7190 7200
CONECT 7203 7193
CONECT 7204 3110 3284 3314 7217
CONECT 7205 3283 3296 4134 4148
CONECT 7205 4149 7215 7217
CONECT 7206 7207
CONECT 7207 7206 7208 7210
CONECT 7208 7207 7209 7218
CONECT 7209 7208
CONECT 7210 7207 7211
CONECT 7211 7210 7212
CONECT 7212 7211 7213
CONECT 7213 7212 7214
CONECT 7214 7213 7215 7216
CONECT 7215 7205 7214 7217
CONECT 7216 7214
CONECT 7217 7204 7205 7215
CONECT 7218 7208
CONECT 7219 5506 5680 5710 7232
CONECT 7220 5679 5692 6530 6544
CONECT 7220 6545 7230 7232
CONECT 7221 7222
CONECT 7222 7221 7223 7225
CONECT 7223 7222 7224 7233
CONECT 7224 7223
CONECT 7225 7222 7226
CONECT 7226 7225 7227
CONECT 7227 7226 7228
CONECT 7228 7227 7229
CONECT 7229 7228 7230 7231
CONECT 7230 7220 7229 7232
CONECT 7231 7229
CONECT 7232 7219 7220 7230
CONECT 7233 7223
MASTER 498 0 9 36 24 0 24 6 7245 3 72 75
END
PyCogent-1.5.3/doc/data/4TSV.pdb 000644 000765 000024 00000335736 11305747275 017201 0 ustar 00jrideout staff 000000 000000 HEADER LYMPHOKINE 29-OCT-97 4TSV
TITLE HIGH RESOLUTION CRYSTAL STRUCTURE OF A HUMAN TNF-ALPHA
TITLE 2 MUTANT
COMPND MOL_ID: 1;
COMPND 2 MOLECULE: TUMOR NECROSIS FACTOR-ALPHA;
COMPND 3 CHAIN: A;
COMPND 4 ENGINEERED: YES;
COMPND 5 MUTATION: YES
SOURCE MOL_ID: 1;
SOURCE 2 ORGANISM_SCIENTIFIC: HOMO SAPIENS;
SOURCE 3 ORGANISM_COMMON: HUMAN;
SOURCE 4 CELL_LINE: BL21;
SOURCE 5 EXPRESSION_SYSTEM: ESCHERICHIA COLI;
SOURCE 6 EXPRESSION_SYSTEM_STRAIN: BL21 (DE3);
SOURCE 7 EXPRESSION_SYSTEM_PLASMID: BL21
KEYWDS LYMPHOKINE, TNF
EXPDTA X-RAY DIFFRACTION
AUTHOR S.-S.CHA,J.-S.KIM,H.-S.CHO,B.-H.OH
REVDAT 2 02-MAR-99 4TSV 1 COMPND REMARK HEADER SOURCE
REVDAT 2 2 1 KEYWDS
REVDAT 1 30-DEC-98 4TSV 0
JRNL AUTH S.S.CHA,J.S.KIM,H.S.CHO,N.K.SHIN,W.JEONG,H.C.SHIN,
JRNL AUTH 2 Y.J.KIM,J.H.HAHN,B.H.OH
JRNL TITL HIGH RESOLUTION CRYSTAL STRUCTURE OF A HUMAN TUMOR
JRNL TITL 2 NECROSIS FACTOR-ALPHA MUTANT WITH LOW SYSTEMIC
JRNL TITL 3 TOXICITY.
JRNL REF J.BIOL.CHEM. V. 273 2153 1998
JRNL REFN ASTM JBCHA3 US ISSN 0021-9258
REMARK 1
REMARK 1 REFERENCE 1
REMARK 1 AUTH M.J.ECK,S.R.SPRANG
REMARK 1 TITL THE STRUCTURE OF TUMOR NECROSIS FACTOR-ALPHA AT
REMARK 1 TITL 2 2.6 A RESOLUTION. IMPLICATIONS FOR RECEPTOR BINDING
REMARK 1 REF J.BIOL.CHEM. V. 264 17595 1989
REMARK 1 REFN ASTM JBCHA3 US ISSN 0021-9258
REMARK 2
REMARK 2 RESOLUTION. 1.80 ANGSTROMS.
REMARK 3
REMARK 3 REFINEMENT.
REMARK 3 PROGRAM : X-PLOR 3.01
REMARK 3 AUTHORS : BRUNGER
REMARK 3
REMARK 3 DATA USED IN REFINEMENT.
REMARK 3 RESOLUTION RANGE HIGH (ANGSTROMS) : 1.80
REMARK 3 RESOLUTION RANGE LOW (ANGSTROMS) : 8.00
REMARK 3 DATA CUTOFF (SIGMA(F)) : 1.000
REMARK 3 DATA CUTOFF HIGH (ABS(F)) : NULL
REMARK 3 DATA CUTOFF LOW (ABS(F)) : NULL
REMARK 3 COMPLETENESS (WORKING+TEST) (%) : 99.9
REMARK 3 NUMBER OF REFLECTIONS : 13102
REMARK 3
REMARK 3 FIT TO DATA USED IN REFINEMENT.
REMARK 3 CROSS-VALIDATION METHOD : NULL
REMARK 3 FREE R VALUE TEST SET SELECTION : NULL
REMARK 3 R VALUE (WORKING SET) : 0.200
REMARK 3 FREE R VALUE : 0.262
REMARK 3 FREE R VALUE TEST SET SIZE (%) : 10.000
REMARK 3 FREE R VALUE TEST SET COUNT : NULL
REMARK 3 ESTIMATED ERROR OF FREE R VALUE : NULL
REMARK 3
REMARK 3 FIT IN THE HIGHEST RESOLUTION BIN.
REMARK 3 TOTAL NUMBER OF BINS USED : NULL
REMARK 3 BIN RESOLUTION RANGE HIGH (A) : NULL
REMARK 3 BIN RESOLUTION RANGE LOW (A) : NULL
REMARK 3 BIN COMPLETENESS (WORKING+TEST) (%) : NULL
REMARK 3 REFLECTIONS IN BIN (WORKING SET) : NULL
REMARK 3 BIN R VALUE (WORKING SET) : NULL
REMARK 3 BIN FREE R VALUE : NULL
REMARK 3 BIN FREE R VALUE TEST SET SIZE (%) : NULL
REMARK 3 BIN FREE R VALUE TEST SET COUNT : NULL
REMARK 3 ESTIMATED ERROR OF BIN FREE R VALUE : NULL
REMARK 3
REMARK 3 NUMBER OF NON-HYDROGEN ATOMS USED IN REFINEMENT.
REMARK 3 PROTEIN ATOMS : 1118
REMARK 3 NUCLEIC ACID ATOMS : NULL
REMARK 3 HETEROGEN ATOMS : NULL
REMARK 3 SOLVENT ATOMS : 80
REMARK 3
REMARK 3 B VALUES.
REMARK 3 FROM WILSON PLOT (A**2) : NULL
REMARK 3 MEAN B VALUE (OVERALL, A**2) : NULL
REMARK 3 OVERALL ANISOTROPIC B VALUE.
REMARK 3 B11 (A**2) : NULL
REMARK 3 B22 (A**2) : NULL
REMARK 3 B33 (A**2) : NULL
REMARK 3 B12 (A**2) : NULL
REMARK 3 B13 (A**2) : NULL
REMARK 3 B23 (A**2) : NULL
REMARK 3
REMARK 3 ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM LUZZATI PLOT (A) : 0.30
REMARK 3 ESD FROM SIGMAA (A) : NULL
REMARK 3 LOW RESOLUTION CUTOFF (A) : NULL
REMARK 3
REMARK 3 CROSS-VALIDATED ESTIMATED COORDINATE ERROR.
REMARK 3 ESD FROM C-V LUZZATI PLOT (A) : NULL
REMARK 3 ESD FROM C-V SIGMAA (A) : NULL
REMARK 3
REMARK 3 RMS DEVIATIONS FROM IDEAL VALUES.
REMARK 3 BOND LENGTHS (A) : 0.015
REMARK 3 BOND ANGLES (DEGREES) : 2.18
REMARK 3 DIHEDRAL ANGLES (DEGREES) : NULL
REMARK 3 IMPROPER ANGLES (DEGREES) : NULL
REMARK 3
REMARK 3 ISOTROPIC THERMAL MODEL : NULL
REMARK 3
REMARK 3 ISOTROPIC THERMAL FACTOR RESTRAINTS. RMS SIGMA
REMARK 3 MAIN-CHAIN BOND (A**2) : NULL ; NULL
REMARK 3 MAIN-CHAIN ANGLE (A**2) : NULL ; NULL
REMARK 3 SIDE-CHAIN BOND (A**2) : NULL ; NULL
REMARK 3 SIDE-CHAIN ANGLE (A**2) : NULL ; NULL
REMARK 3
REMARK 3 NCS MODEL : NULL
REMARK 3
REMARK 3 NCS RESTRAINTS. RMS SIGMA/WEIGHT
REMARK 3 GROUP 1 POSITIONAL (A) : NULL ; NULL
REMARK 3 GROUP 1 B-FACTOR (A**2) : NULL ; NULL
REMARK 3
REMARK 3 PARAMETER FILE 1 : NULL
REMARK 3 TOPOLOGY FILE 1 : NULL
REMARK 3
REMARK 3 OTHER REFINEMENT REMARKS: NULL
REMARK 4
REMARK 4 4TSV COMPLIES WITH FORMAT V. 3.0, 1-DEC-2006
REMARK 4
REMARK 4 THIS IS THE REMEDIATED VERSION OF THIS PDB ENTRY.
REMARK 4 REMEDIATED DATA FILE REVISION 3.100 (2007-03-18)
REMARK 4 REMEDIATOR VALIDATED PDB VERSION 2.3 COMPLIANT
REMARK 200
REMARK 200 EXPERIMENTAL DETAILS
REMARK 200 EXPERIMENT TYPE : X-RAY DIFFRACTION
REMARK 200 DATE OF DATA COLLECTION : DEC-1995
REMARK 200 TEMPERATURE (KELVIN) : 298.0
REMARK 200 PH : 6.80
REMARK 200 NUMBER OF CRYSTALS USED : 1
REMARK 200
REMARK 200 SYNCHROTRON (Y/N) : N
REMARK 200 RADIATION SOURCE : NULL
REMARK 200 BEAMLINE : NULL
REMARK 200 X-RAY GENERATOR MODEL : MAC SCIENCE M18XHF22
REMARK 200 MONOCHROMATIC OR LAUE (M/L) : M
REMARK 200 WAVELENGTH OR RANGE (A) : 1.5418
REMARK 200 MONOCHROMATOR : GRAPHITE(002)
REMARK 200 OPTICS : NULL
REMARK 200
REMARK 200 DETECTOR TYPE : IMAGE PLATE AREA DETECTOR
REMARK 200 DETECTOR MANUFACTURER : MACSCIENCE
REMARK 200 INTENSITY-INTEGRATION SOFTWARE : DENZO
REMARK 200 DATA SCALING SOFTWARE : SCALEPACK
REMARK 200
REMARK 200 NUMBER OF UNIQUE REFLECTIONS : 13102
REMARK 200 RESOLUTION RANGE HIGH (A) : 1.800
REMARK 200 RESOLUTION RANGE LOW (A) : 10.000
REMARK 200 REJECTION CRITERIA (SIGMA(I)) : 1.000
REMARK 200
REMARK 200 OVERALL.
REMARK 200 COMPLETENESS FOR RANGE (%) : 99.9
REMARK 200 DATA REDUNDANCY : NULL
REMARK 200 R MERGE (I) : NULL
REMARK 200 R SYM (I) : 0.04000
REMARK 200 FOR THE DATA SET : NULL
REMARK 200
REMARK 200 IN THE HIGHEST RESOLUTION SHELL.
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE HIGH (A) : NULL
REMARK 200 HIGHEST RESOLUTION SHELL, RANGE LOW (A) : NULL
REMARK 200 COMPLETENESS FOR SHELL (%) : NULL
REMARK 200 DATA REDUNDANCY IN SHELL : NULL
REMARK 200 R MERGE FOR SHELL (I) : NULL
REMARK 200 R SYM FOR SHELL (I) : NULL
REMARK 200 FOR SHELL : NULL
REMARK 200
REMARK 200 DIFFRACTION PROTOCOL: NULL
REMARK 200 METHOD USED TO DETERMINE THE STRUCTURE: NULL
REMARK 200 SOFTWARE USED: X-PLOR 3.0
REMARK 200 STARTING MODEL: NULL
REMARK 200
REMARK 200 REMARK: NULL
REMARK 280
REMARK 280 CRYSTAL
REMARK 280 SOLVENT CONTENT, VS (%): 44.02
REMARK 280 MATTHEWS COEFFICIENT, VM (ANGSTROMS**3/DA): 2.20
REMARK 280
REMARK 280 CRYSTALLIZATION CONDITIONS: 1.4 M SODIUM FORMATE, PH 6.8
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY
REMARK 290 SYMMETRY OPERATORS FOR SPACE GROUP: H 3
REMARK 290
REMARK 290 SYMOP SYMMETRY
REMARK 290 NNNMMM OPERATOR
REMARK 290 1555 X,Y,Z
REMARK 290 2555 -Y,X-Y,Z
REMARK 290 3555 -X+Y,-X,Z
REMARK 290 4555 2/3+X,1/3+Y,1/3+Z
REMARK 290 5555 2/3-Y,1/3+X-Y,1/3+Z
REMARK 290 6555 2/3-X+Y,1/3-X,1/3+Z
REMARK 290 7555 1/3+X,2/3+Y,2/3+Z
REMARK 290 8555 1/3-Y,2/3+X-Y,2/3+Z
REMARK 290 9555 1/3-X+Y,2/3-X,2/3+Z
REMARK 290
REMARK 290 WHERE NNN -> OPERATOR NUMBER
REMARK 290 MMM -> TRANSLATION VECTOR
REMARK 290
REMARK 290 CRYSTALLOGRAPHIC SYMMETRY TRANSFORMATIONS
REMARK 290 THE FOLLOWING TRANSFORMATIONS OPERATE ON THE ATOM/HETATM
REMARK 290 RECORDS IN THIS ENTRY TO PRODUCE CRYSTALLOGRAPHICALLY
REMARK 290 RELATED MOLECULES.
REMARK 290 SMTRY1 1 1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 1 0.000000 1.000000 0.000000 0.00000
REMARK 290 SMTRY3 1 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 2 -0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 2 0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 2 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 3 -0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 3 -0.866025 -0.500000 0.000000 0.00000
REMARK 290 SMTRY3 3 0.000000 0.000000 1.000000 0.00000
REMARK 290 SMTRY1 4 1.000000 0.000000 0.000000 33.36000
REMARK 290 SMTRY2 4 0.000000 1.000000 0.000000 19.26040
REMARK 290 SMTRY3 4 0.000000 0.000000 1.000000 28.36333
REMARK 290 SMTRY1 5 -0.500000 -0.866025 0.000000 33.36000
REMARK 290 SMTRY2 5 0.866025 -0.500000 0.000000 19.26040
REMARK 290 SMTRY3 5 0.000000 0.000000 1.000000 28.36333
REMARK 290 SMTRY1 6 -0.500000 0.866025 0.000000 33.36000
REMARK 290 SMTRY2 6 -0.866025 -0.500000 0.000000 19.26040
REMARK 290 SMTRY3 6 0.000000 0.000000 1.000000 28.36333
REMARK 290 SMTRY1 7 1.000000 0.000000 0.000000 0.00000
REMARK 290 SMTRY2 7 0.000000 1.000000 0.000000 38.52081
REMARK 290 SMTRY3 7 0.000000 0.000000 1.000000 56.72667
REMARK 290 SMTRY1 8 -0.500000 -0.866025 0.000000 0.00000
REMARK 290 SMTRY2 8 0.866025 -0.500000 0.000000 38.52081
REMARK 290 SMTRY3 8 0.000000 0.000000 1.000000 56.72667
REMARK 290 SMTRY1 9 -0.500000 0.866025 0.000000 0.00000
REMARK 290 SMTRY2 9 -0.866025 -0.500000 0.000000 38.52081
REMARK 290 SMTRY3 9 0.000000 0.000000 1.000000 56.72667
REMARK 290
REMARK 290 REMARK: NULL
REMARK 300
REMARK 300 BIOMOLECULE: 1
REMARK 300 THIS ENTRY CONTAINS THE CRYSTALLOGRAPHIC ASYMMETRIC UNIT
REMARK 300 WHICH CONSISTS OF 1 CHAIN(S). SEE REMARK 350 FOR
REMARK 300 INFORMATION ON GENERATING THE BIOLOGICAL MOLECULE(S).
REMARK 350
REMARK 350 GENERATING THE BIOMOLECULE
REMARK 350 COORDINATES FOR A COMPLETE MULTIMER REPRESENTING THE KNOWN
REMARK 350 BIOLOGICALLY SIGNIFICANT OLIGOMERIZATION STATE OF THE
REMARK 350 MOLECULE CAN BE GENERATED BY APPLYING BIOMT TRANSFORMATIONS
REMARK 350 GIVEN BELOW. BOTH NON-CRYSTALLOGRAPHIC AND
REMARK 350 CRYSTALLOGRAPHIC OPERATIONS ARE GIVEN.
REMARK 350
REMARK 350 BIOMOLECULE: 1
REMARK 350 APPLY THE FOLLOWING TO CHAINS: A
REMARK 350 BIOMT1 1 1.000000 0.000000 0.000000 0.00000
REMARK 350 BIOMT2 1 0.000000 1.000000 0.000000 0.00000
REMARK 350 BIOMT3 1 0.000000 0.000000 1.000000 0.00000
REMARK 350 BIOMT1 2 -0.500000 -0.866025 0.000000 233.52000
REMARK 350 BIOMT2 2 0.866025 -0.500000 0.000000 -57.78121
REMARK 350 BIOMT3 2 0.000000 0.000000 1.000000 0.00000
REMARK 350 BIOMT1 3 -0.500000 0.866025 0.000000 166.80000
REMARK 350 BIOMT2 3 -0.866025 -0.500000 0.000000 173.34364
REMARK 350 BIOMT3 3 0.000000 0.000000 1.000000 0.00000
REMARK 465
REMARK 465 MISSING RESIDUES
REMARK 465 THE FOLLOWING RESIDUES WERE NOT LOCATED IN THE
REMARK 465 EXPERIMENT. (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN
REMARK 465 IDENTIFIER; SSSEQ=SEQUENCE NUMBER; I=INSERTION CODE.)
REMARK 465
REMARK 465 M RES C SSSEQI
REMARK 465 PRO A 8
REMARK 465 SER A 9
REMARK 470
REMARK 470 MISSING ATOM
REMARK 470 THE FOLLOWING RESIDUES HAVE MISSING ATOMS(M=MODEL NUMBER;
REMARK 470 RES=RESIDUE NAME; C=CHAIN IDENTIFIER; SSEQ=SEQUENCE NUMBER;
REMARK 470 I=INSERTION CODE):
REMARK 470 M RES CSSEQI ATOMS
REMARK 470 ASP A 10 CG OD1 OD2
REMARK 470 GLU A 23 CG CD OE1 OE2
REMARK 470 GLN A 25 CG CD OE1 NE2
REMARK 470 TYR A 87 CG CD1 CD2 CE1 CE2 CZ OH
REMARK 470 GLN A 88 CG CD OE1 NE2
REMARK 470 ARG A 103 CG CD NE CZ NH1 NH2
REMARK 470 GLU A 107 CG CD OE1 OE2
REMARK 470 GLU A 110 CG CD OE1 OE2
REMARK 470 GLU A 146 CG CD OE1 OE2
REMARK 470 LEU A 157 O
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: CLOSE CONTACTS IN SAME ASYMMETRIC UNIT
REMARK 500
REMARK 500 THE FOLLOWING ATOMS ARE IN CLOSE CONTACT.
REMARK 500
REMARK 500 ATM1 RES C SSEQI ATM2 RES C SSEQI
REMARK 500 CA THR A 105 O HOH 261 2.18
REMARK 500 NZ LYS A 98 O PRO A 117 2.19
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: CLOSE CONTACTS
REMARK 500
REMARK 500 THE FOLLOWING ATOMS THAT ARE RELATED BY CRYSTALLOGRAPHIC
REMARK 500 SYMMETRY ARE IN CLOSE CONTACT. AN ATOM LOCATED WITHIN 0.15
REMARK 500 ANGSTROMS OF A SYMMETRY RELATED ATOM IS ASSUMED TO BE ON A
REMARK 500 SPECIAL POSITION AND IS, THEREFORE, LISTED IN REMARK 375
REMARK 500 INSTEAD OF REMARK 500. ATOMS WITH NON-BLANK ALTERNATE
REMARK 500 LOCATION INDICATORS ARE NOT INCLUDED IN THE CALCULATIONS.
REMARK 500
REMARK 500 DISTANCE CUTOFF:
REMARK 500 2.2 ANGSTROMS FOR CONTACTS NOT INVOLVING HYDROGEN ATOMS
REMARK 500 1.6 ANGSTROMS FOR CONTACTS INVOLVING HYDROGEN ATOMS
REMARK 500
REMARK 500 ATM1 RES C SSEQI ATM2 RES C SSEQI SSYMOP DISTANCE
REMARK 500 NH2 ARG A 32 OG SER A 71 6985 1.91
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: COVALENT BOND LENGTHS
REMARK 500
REMARK 500 THE STEREOCHEMICAL PARAMETERS OF THE FOLLOWING RESIDUES
REMARK 500 HAVE VALUES WHICH DEVIATE FROM EXPECTED VALUES BY MORE
REMARK 500 THAN 6*RMSD (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN
REMARK 500 IDENTIFIER; SSEQ=SEQUENCE NUMBER; I=INSERTION CODE).
REMARK 500
REMARK 500 STANDARD TABLE:
REMARK 500 FORMAT: (10X,I3,1X,2(A3,1X,A1,I4,A1,1X,A4,3X),F6.3)
REMARK 500
REMARK 500 EXPECTED VALUES: ENGH AND HUBER, 1991
REMARK 500
REMARK 500 M RES CSSEQI ATM1 RES CSSEQI ATM2 DEVIATION
REMARK 500 ILE A 83 C ALA A 84 N 0.165
REMARK 500 GLU A 110 C ALA A 111 N 0.409
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: COVALENT BOND ANGLES
REMARK 500
REMARK 500 THE STEREOCHEMICAL PARAMETERS OF THE FOLLOWING RESIDUES
REMARK 500 HAVE VALUES WHICH DEVIATE FROM EXPECTED VALUES BY MORE
REMARK 500 THAN 6*RMSD (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN
REMARK 500 IDENTIFIER; SSEQ=SEQUENCE NUMBER; I=INSERTION CODE).
REMARK 500
REMARK 500 STANDARD TABLE:
REMARK 500 FORMAT: (10X,I3,1X,A3,1X,A1,I4,A1,3(1X,A4,2X),12X,F5.1)
REMARK 500
REMARK 500 EXPECTED VALUES: ENGH AND HUBER, 1991
REMARK 500
REMARK 500 M RES CSSEQI ATM1 ATM2 ATM3
REMARK 500 PRO A 70 CA - C - N ANGL. DEV. = 31.6 DEGREES
REMARK 500 PRO A 70 O - C - N ANGL. DEV. =-90.0 DEGREES
REMARK 500 ILE A 83 O - C - N ANGL. DEV. =-44.1 DEGREES
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: TORSION ANGLES
REMARK 500
REMARK 500 TORSION ANGLES OUTSIDE THE EXPECTED RAMACHANDRAN REGIONS:
REMARK 500 (M=MODEL NUMBER; RES=RESIDUE NAME; C=CHAIN IDENTIFIER;
REMARK 500 SSEQ=SEQUENCE NUMBER; I=INSERTION CODE).
REMARK 500
REMARK 500 STANDARD TABLE:
REMARK 500 FORMAT:(10X,I3,1X,A3,1X,A1,I4,A1,4X,F7.2,3X,F7.2)
REMARK 500
REMARK 500 M RES CSSEQI PSI PHI
REMARK 500 SER A 71 -31.86 56.56
REMARK 500 VAL A 85 -95.80 78.36
REMARK 500
REMARK 500 GEOMETRY AND STEREOCHEMISTRY
REMARK 500 SUBTOPIC: NON-CIS, NON-TRANS
REMARK 500
REMARK 500 THE FOLLOWING PEPTIDE BONDS DEVIATE SIGNIFICANTLY FROM BOTH
REMARK 500 CIS AND TRANS CONFORMATION. CIS BONDS, IF ANY, ARE LISTED
REMARK 500 ON CISPEP RECORDS. TRANS IS DEFINED AS 180 +/- 30 AND
REMARK 500 CIS IS DEFINED AS 0 +/- 30 DEGREES.
REMARK 500 MODEL OMEGA
REMARK 500 GLU A 110 ALA A 111 137.31
REMARK 525
REMARK 525 SOLVENT
REMARK 525 THE FOLLOWING SOLVENT MOLECULES LIE FARTHER THAN EXPECTED
REMARK 525 FROM THE PROTEIN OR NUCLEIC ACID MOLECULE AND MAY BE
REMARK 525 ASSOCIATED WITH A SYMMETRY RELATED MOLECULE (M=MODEL
REMARK 525 NUMBER; RES=RESIDUE NAME; C=CHAIN IDENTIFIER; SSEQ=SEQUENCE
REMARK 525 NUMBER; I=INSERTION CODE):
REMARK 525
REMARK 525 M RES CSSEQI
REMARK 525 HOH 225 DISTANCE = 5.67 ANGSTROMS
REMARK 525 HOH 244 DISTANCE = 8.73 ANGSTROMS
REMARK 525 HOH 248 DISTANCE = 7.30 ANGSTROMS
REMARK 525 HOH 252 DISTANCE = 6.32 ANGSTROMS
REMARK 525 HOH 253 DISTANCE = 5.65 ANGSTROMS
REMARK 525 HOH 254 DISTANCE = 5.68 ANGSTROMS
REMARK 525 HOH 267 DISTANCE = 6.29 ANGSTROMS
REMARK 525 HOH 269 DISTANCE = 6.10 ANGSTROMS
DBREF 4TSV A 8 157 UNP P01375 TNFA_HUMAN 84 233
SEQADV 4TSV SER A 29 UNP P01375 LEU 105 ENGINEERED
SEQADV 4TSV ILE A 52 UNP P01375 SER 128 ENGINEERED
SEQADV 4TSV PHE A 56 UNP P01375 TYR 132 ENGINEERED
SEQRES 1 A 150 PRO SER ASP LYS PRO VAL ALA HIS VAL VAL ALA ASN PRO
SEQRES 2 A 150 GLN ALA GLU GLY GLN LEU GLN TRP SER ASN ARG ARG ALA
SEQRES 3 A 150 ASN ALA LEU LEU ALA ASN GLY VAL GLU LEU ARG ASP ASN
SEQRES 4 A 150 GLN LEU VAL VAL PRO ILE GLU GLY LEU PHE LEU ILE TYR
SEQRES 5 A 150 SER GLN VAL LEU PHE LYS GLY GLN GLY CYS PRO SER THR
SEQRES 6 A 150 HIS VAL LEU LEU THR HIS THR ILE SER ARG ILE ALA VAL
SEQRES 7 A 150 SER TYR GLN THR LYS VAL ASN LEU LEU SER ALA ILE LYS
SEQRES 8 A 150 SER PRO CYS GLN ARG GLU THR PRO GLU GLY ALA GLU ALA
SEQRES 9 A 150 LYS PRO TRP TYR GLU PRO ILE TYR LEU GLY GLY VAL PHE
SEQRES 10 A 150 GLN LEU GLU LYS GLY ASP ARG LEU SER ALA GLU ILE ASN
SEQRES 11 A 150 ARG PRO ASP TYR LEU ASP PHE ALA GLU SER GLY GLN VAL
SEQRES 12 A 150 TYR PHE GLY ILE ILE ALA LEU
FORMUL 2 HOH *70(H2 O)
HELIX 1 1 PRO A 139 TYR A 141 5 3
SHEET 1 A 5 LEU A 36 ALA A 38 0
SHEET 2 A 5 VAL A 13 VAL A 17 -1 N HIS A 15 O LEU A 36
SHEET 3 A 5 TYR A 151 ALA A 156 -1 N ILE A 154 O ALA A 14
SHEET 4 A 5 GLY A 54 GLN A 67 -1 N GLN A 61 O TYR A 151
SHEET 5 A 5 PRO A 113 LEU A 126 -1 N LEU A 126 O GLY A 54
SHEET 1 B 2 GLU A 42 ARG A 44 0
SHEET 2 B 2 GLN A 47 VAL A 49 -1 N VAL A 49 O GLU A 42
SHEET 1 C 3 ARG A 131 ILE A 136 0
SHEET 2 C 3 LEU A 75 ILE A 83 -1 N ILE A 83 O ARG A 131
SHEET 3 C 3 LYS A 90 SER A 99 -1 N LYS A 98 O LEU A 76
SSBOND 1 CYS A 69 CYS A 101
CRYST1 66.720 66.720 85.090 90.00 90.00 120.00 H 3 9
ORIGX1 1.000000 0.000000 0.000000 0.00000
ORIGX2 0.000000 1.000000 0.000000 0.00000
ORIGX3 0.000000 0.000000 1.000000 0.00000
SCALE1 0.014988 0.008653 0.000000 0.00000
SCALE2 0.000000 0.017307 0.000000 0.00000
SCALE3 0.000000 0.000000 0.011752 0.00000
ATOM 1 N ASP A 10 143.224 41.252 20.262 1.00 33.32 N
ATOM 2 CA ASP A 10 143.865 39.983 20.718 1.00 33.75 C
ATOM 3 C ASP A 10 143.660 38.778 19.790 1.00 32.25 C
ATOM 4 O ASP A 10 144.253 37.736 20.022 1.00 37.02 O
ATOM 5 CB ASP A 10 143.405 39.643 22.148 1.00 35.94 C
ATOM 6 N LYS A 11 142.780 38.905 18.793 1.00 32.19 N
ATOM 7 CA LYS A 11 142.495 37.859 17.785 1.00 26.76 C
ATOM 8 C LYS A 11 143.600 37.697 16.725 1.00 22.39 C
ATOM 9 O LYS A 11 144.151 38.698 16.231 1.00 18.85 O
ATOM 10 CB LYS A 11 141.249 38.245 16.966 1.00 28.02 C
ATOM 11 CG LYS A 11 139.941 38.456 17.713 1.00 32.27 C
ATOM 12 CD LYS A 11 138.765 38.699 16.745 1.00 34.99 C
ATOM 13 CE LYS A 11 137.481 38.943 17.534 1.00 40.00 C
ATOM 14 NZ LYS A 11 136.210 38.723 16.752 1.00 43.13 N
ATOM 15 N PRO A 12 143.913 36.445 16.338 1.00 19.62 N
ATOM 16 CA PRO A 12 144.939 36.256 15.304 1.00 15.56 C
ATOM 17 C PRO A 12 144.367 36.883 14.027 1.00 14.16 C
ATOM 18 O PRO A 12 143.174 36.739 13.743 1.00 13.12 O
ATOM 19 CB PRO A 12 144.999 34.740 15.151 1.00 16.36 C
ATOM 20 CG PRO A 12 144.721 34.276 16.535 1.00 18.42 C
ATOM 21 CD PRO A 12 143.561 35.158 16.956 1.00 18.73 C
ATOM 22 N VAL A 13 145.192 37.598 13.283 1.00 12.41 N
ATOM 23 CA VAL A 13 144.717 38.227 12.076 1.00 13.30 C
ATOM 24 C VAL A 13 145.859 38.454 11.090 1.00 14.05 C
ATOM 25 O VAL A 13 147.026 38.654 11.472 1.00 12.10 O
ATOM 26 CB VAL A 13 144.026 39.573 12.439 1.00 17.06 C
ATOM 27 CG1 VAL A 13 145.024 40.511 13.176 1.00 19.48 C
ATOM 28 CG2 VAL A 13 143.470 40.256 11.238 1.00 13.49 C
ATOM 29 N ALA A 14 145.510 38.434 9.800 1.00 13.51 N
ATOM 30 CA ALA A 14 146.461 38.682 8.731 1.00 10.53 C
ATOM 31 C ALA A 14 145.780 39.225 7.506 1.00 8.76 C
ATOM 32 O ALA A 14 144.642 38.862 7.208 1.00 7.01 O
ATOM 33 CB ALA A 14 147.243 37.395 8.355 1.00 12.75 C
ATOM 34 N HIS A 15 146.389 40.256 6.945 1.00 11.87 N
ATOM 35 CA HIS A 15 145.956 40.816 5.673 1.00 10.59 C
ATOM 36 C HIS A 15 147.262 41.122 4.955 1.00 12.24 C
ATOM 37 O HIS A 15 147.978 42.069 5.283 1.00 10.64 O
ATOM 38 CB HIS A 15 145.049 42.045 5.772 1.00 10.41 C
ATOM 39 CG HIS A 15 144.611 42.572 4.429 1.00 8.60 C
ATOM 40 ND1 HIS A 15 143.476 42.127 3.787 1.00 8.51 N
ATOM 41 CD2 HIS A 15 145.152 43.508 3.612 1.00 8.05 C
ATOM 42 CE1 HIS A 15 143.332 42.764 2.640 1.00 9.72 C
ATOM 43 NE2 HIS A 15 144.340 43.608 2.508 1.00 9.91 N
ATOM 44 N VAL A 16 147.608 40.240 4.037 1.00 11.98 N
ATOM 45 CA VAL A 16 148.826 40.371 3.274 1.00 12.24 C
ATOM 46 C VAL A 16 148.525 40.670 1.799 1.00 12.12 C
ATOM 47 O VAL A 16 147.447 40.332 1.280 1.00 7.76 O
ATOM 48 CB VAL A 16 149.758 39.126 3.505 1.00 10.30 C
ATOM 49 CG1 VAL A 16 150.012 38.973 5.008 1.00 12.61 C
ATOM 50 CG2 VAL A 16 149.132 37.810 2.973 1.00 11.85 C
ATOM 51 N VAL A 17 149.459 41.366 1.160 1.00 12.95 N
ATOM 52 CA VAL A 17 149.331 41.748 -0.237 1.00 13.09 C
ATOM 53 C VAL A 17 150.446 41.190 -1.128 1.00 11.45 C
ATOM 54 O VAL A 17 151.493 40.738 -0.654 1.00 13.18 O
ATOM 55 CB VAL A 17 149.341 43.306 -0.382 1.00 13.98 C
ATOM 56 CG1 VAL A 17 148.215 43.928 0.446 1.00 14.42 C
ATOM 57 CG2 VAL A 17 150.683 43.863 0.050 1.00 15.72 C
ATOM 58 N ALA A 18 150.185 41.181 -2.426 1.00 14.79 N
ATOM 59 CA ALA A 18 151.175 40.742 -3.388 1.00 15.88 C
ATOM 60 C ALA A 18 152.362 41.709 -3.283 1.00 15.79 C
ATOM 61 O ALA A 18 152.204 42.931 -3.133 1.00 17.49 O
ATOM 62 CB ALA A 18 150.574 40.779 -4.812 1.00 12.09 C
ATOM 63 N ASN A 19 153.552 41.153 -3.385 1.00 17.64 N
ATOM 64 CA ASN A 19 154.773 41.948 -3.338 1.00 20.04 C
ATOM 65 C ASN A 19 155.024 42.328 -4.821 1.00 20.85 C
ATOM 66 O ASN A 19 155.319 41.474 -5.636 1.00 21.96 O
ATOM 67 CB ASN A 19 155.898 41.077 -2.738 1.00 20.94 C
ATOM 68 CG ASN A 19 157.279 41.714 -2.844 1.00 25.71 C
ATOM 69 OD1 ASN A 19 157.469 42.766 -3.478 1.00 23.72 O
ATOM 70 ND2 ASN A 19 158.255 41.065 -2.235 1.00 26.30 N
ATOM 71 N PRO A 20 154.883 43.610 -5.183 1.00 22.12 N
ATOM 72 CA PRO A 20 155.100 44.040 -6.574 1.00 28.28 C
ATOM 73 C PRO A 20 156.542 43.933 -7.135 1.00 31.58 C
ATOM 74 O PRO A 20 156.775 44.203 -8.322 1.00 33.79 O
ATOM 75 CB PRO A 20 154.555 45.474 -6.567 1.00 28.83 C
ATOM 76 CG PRO A 20 154.906 45.946 -5.200 1.00 28.31 C
ATOM 77 CD PRO A 20 154.548 44.759 -4.324 1.00 23.42 C
ATOM 78 N GLN A 21 157.495 43.551 -6.281 1.00 33.56 N
ATOM 79 CA GLN A 21 158.887 43.374 -6.686 1.00 35.60 C
ATOM 80 C GLN A 21 159.118 41.910 -7.067 1.00 34.82 C
ATOM 81 O GLN A 21 160.213 41.556 -7.509 1.00 37.51 O
ATOM 82 CB GLN A 21 159.874 43.764 -5.564 1.00 39.05 C
ATOM 83 CG GLN A 21 159.747 45.192 -5.013 1.00 44.97 C
ATOM 84 CD GLN A 21 160.081 46.289 -6.035 1.00 50.39 C
ATOM 85 OE1 GLN A 21 159.534 46.329 -7.148 1.00 53.45 O
ATOM 86 NE2 GLN A 21 160.967 47.201 -5.645 1.00 50.90 N
ATOM 87 N ALA A 22 158.136 41.050 -6.807 1.00 31.14 N
ATOM 88 CA ALA A 22 158.255 39.647 -7.170 1.00 28.99 C
ATOM 89 C ALA A 22 157.710 39.539 -8.585 1.00 31.71 C
ATOM 90 O ALA A 22 156.514 39.725 -8.826 1.00 34.93 O
ATOM 91 CB ALA A 22 157.475 38.772 -6.233 1.00 26.11 C
ATOM 92 N GLU A 23 158.618 39.349 -9.538 1.00 32.39 N
ATOM 93 CA GLU A 23 158.256 39.235 -10.956 1.00 27.89 C
ATOM 94 C GLU A 23 157.829 37.834 -11.272 1.00 24.65 C
ATOM 95 O GLU A 23 158.553 36.914 -10.958 1.00 23.15 O
ATOM 96 CB GLU A 23 159.425 39.592 -11.820 1.00 26.66 C
ATOM 97 N GLY A 24 156.636 37.670 -11.841 1.00 26.46 N
ATOM 98 CA GLY A 24 156.138 36.345 -12.200 1.00 25.24 C
ATOM 99 C GLY A 24 155.941 35.332 -11.077 1.00 26.12 C
ATOM 100 O GLY A 24 156.214 34.138 -11.235 1.00 23.73 O
ATOM 101 N GLN A 25 155.499 35.812 -9.922 1.00 24.28 N
ATOM 102 CA GLN A 25 155.222 34.939 -8.812 1.00 22.78 C
ATOM 103 C GLN A 25 154.237 35.683 -7.928 1.00 21.14 C
ATOM 104 O GLN A 25 154.180 36.915 -7.953 1.00 23.46 O
ATOM 105 CB GLN A 25 156.496 34.657 -8.046 1.00 23.59 C
ATOM 106 N LEU A 26 153.410 34.948 -7.195 1.00 20.41 N
ATOM 107 CA LEU A 26 152.500 35.586 -6.248 1.00 17.69 C
ATOM 108 C LEU A 26 153.184 35.466 -4.888 1.00 17.34 C
ATOM 109 O LEU A 26 153.082 34.432 -4.220 1.00 19.82 O
ATOM 110 CB LEU A 26 151.170 34.867 -6.224 1.00 16.13 C
ATOM 111 CG LEU A 26 150.126 35.362 -5.230 1.00 15.88 C
ATOM 112 CD1 LEU A 26 150.134 36.851 -5.096 1.00 15.60 C
ATOM 113 CD2 LEU A 26 148.790 34.823 -5.621 1.00 15.18 C
ATOM 114 N GLN A 27 153.940 36.490 -4.514 1.00 20.61 N
ATOM 115 CA GLN A 27 154.654 36.517 -3.229 1.00 19.35 C
ATOM 116 C GLN A 27 153.908 37.402 -2.240 1.00 16.18 C
ATOM 117 O GLN A 27 153.790 38.615 -2.464 1.00 16.65 O
ATOM 118 CB GLN A 27 156.029 37.095 -3.466 1.00 23.85 C
ATOM 119 CG GLN A 27 157.104 36.564 -2.576 1.00 34.07 C
ATOM 120 CD GLN A 27 158.455 37.180 -2.955 1.00 41.80 C
ATOM 121 OE1 GLN A 27 158.911 38.167 -2.331 1.00 43.70 O
ATOM 122 NE2 GLN A 27 159.060 36.665 -4.047 1.00 44.39 N
ATOM 123 N TRP A 28 153.391 36.813 -1.169 1.00 14.32 N
ATOM 124 CA TRP A 28 152.628 37.579 -0.167 1.00 13.78 C
ATOM 125 C TRP A 28 153.525 38.388 0.767 1.00 11.87 C
ATOM 126 O TRP A 28 154.602 37.927 1.159 1.00 15.31 O
ATOM 127 CB TRP A 28 151.710 36.649 0.656 1.00 14.44 C
ATOM 128 CG TRP A 28 150.707 35.960 -0.160 1.00 14.13 C
ATOM 129 CD1 TRP A 28 150.592 34.615 -0.356 1.00 12.17 C
ATOM 130 CD2 TRP A 28 149.658 36.579 -0.907 1.00 14.18 C
ATOM 131 NE1 TRP A 28 149.515 34.357 -1.175 1.00 14.75 N
ATOM 132 CE2 TRP A 28 148.920 35.544 -1.533 1.00 11.76 C
ATOM 133 CE3 TRP A 28 149.263 37.910 -1.111 1.00 14.41 C
ATOM 134 CZ2 TRP A 28 147.804 35.791 -2.357 1.00 11.06 C
ATOM 135 CZ3 TRP A 28 148.151 38.166 -1.929 1.00 14.92 C
ATOM 136 CH2 TRP A 28 147.435 37.101 -2.542 1.00 12.82 C
ATOM 137 N SER A 29 153.060 39.567 1.170 1.00 12.87 N
ATOM 138 CA SER A 29 153.850 40.429 2.060 1.00 12.86 C
ATOM 139 C SER A 29 153.003 41.246 2.997 1.00 14.62 C
ATOM 140 O SER A 29 151.941 41.729 2.611 1.00 14.58 O
ATOM 141 CB SER A 29 154.662 41.400 1.240 1.00 14.50 C
ATOM 142 OG SER A 29 155.469 42.187 2.091 1.00 19.88 O
ATOM 143 N ASN A 30 153.477 41.396 4.238 1.00 16.28 N
ATOM 144 CA ASN A 30 152.767 42.192 5.250 1.00 18.59 C
ATOM 145 C ASN A 30 153.471 43.532 5.442 1.00 19.03 C
ATOM 146 O ASN A 30 153.075 44.316 6.302 1.00 19.54 O
ATOM 147 CB ASN A 30 152.792 41.475 6.599 1.00 14.38 C
ATOM 148 CG ASN A 30 154.177 41.267 7.079 1.00 16.24 C
ATOM 149 OD1 ASN A 30 154.952 40.533 6.461 1.00 20.35 O
ATOM 150 ND2 ASN A 30 154.555 41.985 8.114 1.00 18.77 N
ATOM 151 N ARG A 31 154.498 43.786 4.628 1.00 21.43 N
ATOM 152 CA ARG A 31 155.308 44.991 4.755 1.00 25.65 C
ATOM 153 C ARG A 31 154.732 46.101 3.932 1.00 26.84 C
ATOM 154 O ARG A 31 155.339 46.565 2.973 1.00 26.52 O
ATOM 155 CB ARG A 31 156.752 44.731 4.340 1.00 25.24 C
ATOM 156 CG ARG A 31 157.279 43.390 4.733 1.00 29.66 C
ATOM 157 CD ARG A 31 158.281 43.486 5.820 1.00 34.97 C
ATOM 158 NE ARG A 31 157.612 43.458 7.097 1.00 37.26 N
ATOM 159 CZ ARG A 31 158.207 43.193 8.248 1.00 35.45 C
ATOM 160 NH1 ARG A 31 159.501 42.932 8.318 1.00 34.87 N
ATOM 161 NH2 ARG A 31 157.480 43.164 9.336 1.00 40.35 N
ATOM 162 N ARG A 32 153.553 46.533 4.345 1.00 26.97 N
ATOM 163 CA ARG A 32 152.838 47.585 3.682 1.00 24.26 C
ATOM 164 C ARG A 32 151.980 48.292 4.746 1.00 23.68 C
ATOM 165 O ARG A 32 151.603 47.701 5.759 1.00 19.33 O
ATOM 166 CB ARG A 32 151.953 46.924 2.610 1.00 27.52 C
ATOM 167 CG ARG A 32 151.174 47.874 1.742 1.00 34.83 C
ATOM 168 CD ARG A 32 150.779 47.201 0.458 1.00 40.41 C
ATOM 169 NE ARG A 32 151.418 47.850 -0.681 1.00 49.54 N
ATOM 170 CZ ARG A 32 152.454 47.358 -1.355 1.00 55.11 C
ATOM 171 NH1 ARG A 32 152.992 46.185 -1.022 1.00 58.48 N
ATOM 172 NH2 ARG A 32 152.977 48.069 -2.347 1.00 57.80 N
ATOM 173 N ALA A 33 151.742 49.584 4.584 1.00 20.12 N
ATOM 174 CA ALA A 33 150.844 50.231 5.510 1.00 21.21 C
ATOM 175 C ALA A 33 149.520 49.577 5.018 1.00 22.20 C
ATOM 176 O ALA A 33 149.435 49.140 3.854 1.00 24.03 O
ATOM 177 CB ALA A 33 150.853 51.755 5.284 1.00 19.68 C
ATOM 178 N ASN A 34 148.521 49.485 5.894 1.00 19.97 N
ATOM 179 CA ASN A 34 147.229 48.860 5.591 1.00 16.85 C
ATOM 180 C ASN A 34 147.285 47.321 5.352 1.00 14.45 C
ATOM 181 O ASN A 34 146.436 46.755 4.670 1.00 15.47 O
ATOM 182 CB ASN A 34 146.515 49.608 4.445 1.00 19.98 C
ATOM 183 CG ASN A 34 146.272 51.098 4.763 1.00 22.23 C
ATOM 184 OD1 ASN A 34 145.660 51.419 5.773 1.00 24.36 O
ATOM 185 ND2 ASN A 34 146.724 51.997 3.888 1.00 20.16 N
ATOM 186 N ALA A 35 148.330 46.668 5.854 1.00 13.25 N
ATOM 187 CA ALA A 35 148.461 45.212 5.782 1.00 11.96 C
ATOM 188 C ALA A 35 148.664 44.812 7.252 1.00 12.70 C
ATOM 189 O ALA A 35 149.051 45.662 8.057 1.00 13.40 O
ATOM 190 CB ALA A 35 149.646 44.796 4.942 1.00 11.98 C
ATOM 191 N LEU A 36 148.331 43.572 7.608 1.00 13.11 N
ATOM 192 CA LEU A 36 148.432 43.072 8.990 1.00 16.33 C
ATOM 193 C LEU A 36 149.007 41.657 9.089 1.00 14.41 C
ATOM 194 O LEU A 36 148.816 40.842 8.203 1.00 11.82 O
ATOM 195 CB LEU A 36 147.027 42.994 9.613 1.00 21.14 C
ATOM 196 CG LEU A 36 146.051 44.159 9.469 1.00 22.22 C
ATOM 197 CD1 LEU A 36 144.638 43.720 9.638 1.00 23.27 C
ATOM 198 CD2 LEU A 36 146.431 45.218 10.518 1.00 26.78 C
ATOM 199 N LEU A 37 149.682 41.364 10.196 1.00 14.13 N
ATOM 200 CA LEU A 37 150.216 40.024 10.472 1.00 15.60 C
ATOM 201 C LEU A 37 150.462 40.021 11.993 1.00 18.45 C
ATOM 202 O LEU A 37 151.615 40.157 12.445 1.00 19.89 O
ATOM 203 CB LEU A 37 151.517 39.794 9.702 1.00 15.71 C
ATOM 204 CG LEU A 37 151.954 38.317 9.650 1.00 16.03 C
ATOM 205 CD1 LEU A 37 150.932 37.490 8.815 1.00 17.74 C
ATOM 206 CD2 LEU A 37 153.339 38.183 9.008 1.00 18.39 C
ATOM 207 N ALA A 38 149.367 39.871 12.760 1.00 20.95 N
ATOM 208 CA ALA A 38 149.377 39.954 14.232 1.00 19.69 C
ATOM 209 C ALA A 38 148.858 38.784 15.021 1.00 22.65 C
ATOM 210 O ALA A 38 148.229 37.889 14.493 1.00 25.21 O
ATOM 211 CB ALA A 38 148.591 41.206 14.669 1.00 18.54 C
ATOM 212 N ASN A 39 149.155 38.802 16.314 1.00 22.40 N
ATOM 213 CA ASN A 39 148.675 37.788 17.238 1.00 18.76 C
ATOM 214 C ASN A 39 148.899 36.310 16.918 1.00 18.30 C
ATOM 215 O ASN A 39 147.995 35.491 17.128 1.00 19.70 O
ATOM 216 CB ASN A 39 147.183 38.019 17.568 1.00 17.42 C
ATOM 217 CG ASN A 39 146.926 39.368 18.160 1.00 19.10 C
ATOM 218 OD1 ASN A 39 147.650 39.818 19.021 1.00 21.87 O
ATOM 219 ND2 ASN A 39 145.891 40.026 17.707 1.00 23.83 N
ATOM 220 N GLY A 40 150.073 35.966 16.391 1.00 17.34 N
ATOM 221 CA GLY A 40 150.389 34.563 16.152 1.00 17.19 C
ATOM 222 C GLY A 40 150.386 34.016 14.747 1.00 18.10 C
ATOM 223 O GLY A 40 150.978 32.957 14.470 1.00 16.88 O
ATOM 224 N VAL A 41 149.655 34.678 13.862 1.00 18.73 N
ATOM 225 CA VAL A 41 149.625 34.217 12.485 1.00 20.10 C
ATOM 226 C VAL A 41 151.021 34.446 11.898 1.00 20.46 C
ATOM 227 O VAL A 41 151.597 35.525 12.064 1.00 25.52 O
ATOM 228 CB VAL A 41 148.589 34.965 11.667 1.00 14.08 C
ATOM 229 CG1 VAL A 41 148.546 34.394 10.275 1.00 18.10 C
ATOM 230 CG2 VAL A 41 147.261 34.845 12.314 1.00 11.27 C
ATOM 231 N GLU A 42 151.569 33.418 11.252 1.00 21.47 N
ATOM 232 CA GLU A 42 152.903 33.483 10.663 1.00 21.65 C
ATOM 233 C GLU A 42 152.840 33.360 9.172 1.00 20.06 C
ATOM 234 O GLU A 42 152.000 32.644 8.659 1.00 22.92 O
ATOM 235 CB GLU A 42 153.764 32.312 11.138 1.00 27.01 C
ATOM 236 CG GLU A 42 154.236 32.372 12.566 1.00 36.48 C
ATOM 237 CD GLU A 42 155.124 31.170 12.935 1.00 42.54 C
ATOM 238 OE1 GLU A 42 155.050 30.094 12.257 1.00 42.73 O
ATOM 239 OE2 GLU A 42 155.897 31.312 13.918 1.00 46.54 O
ATOM 240 N LEU A 43 153.755 34.032 8.492 1.00 19.87 N
ATOM 241 CA LEU A 43 153.879 33.946 7.048 1.00 19.12 C
ATOM 242 C LEU A 43 155.203 33.138 6.918 1.00 20.37 C
ATOM 243 O LEU A 43 156.279 33.616 7.269 1.00 22.76 O
ATOM 244 CB LEU A 43 153.947 35.346 6.397 1.00 16.01 C
ATOM 245 CG LEU A 43 153.795 35.429 4.876 1.00 19.75 C
ATOM 246 CD1 LEU A 43 152.538 34.734 4.436 1.00 20.57 C
ATOM 247 CD2 LEU A 43 153.747 36.882 4.422 1.00 20.33 C
ATOM 248 N ARG A 44 155.065 31.866 6.559 1.00 21.56 N
ATOM 249 CA ARG A 44 156.147 30.911 6.389 1.00 24.64 C
ATOM 250 C ARG A 44 155.988 30.273 5.011 1.00 24.69 C
ATOM 251 O ARG A 44 154.906 29.807 4.664 1.00 22.92 O
ATOM 252 CB ARG A 44 156.003 29.820 7.449 1.00 29.62 C
ATOM 253 CG ARG A 44 156.899 30.045 8.623 1.00 38.09 C
ATOM 254 CD ARG A 44 156.849 28.938 9.690 1.00 43.38 C
ATOM 255 NE ARG A 44 157.905 29.133 10.700 1.00 49.92 N
ATOM 256 CZ ARG A 44 158.219 30.300 11.279 1.00 53.06 C
ATOM 257 NH1 ARG A 44 157.565 31.422 10.965 1.00 52.63 N
ATOM 258 NH2 ARG A 44 159.186 30.349 12.199 1.00 53.67 N
ATOM 259 N ASP A 45 157.063 30.196 4.241 1.00 25.43 N
ATOM 260 CA ASP A 45 157.005 29.598 2.889 1.00 26.80 C
ATOM 261 C ASP A 45 155.834 30.148 2.060 1.00 24.86 C
ATOM 262 O ASP A 45 155.170 29.376 1.370 1.00 24.60 O
ATOM 263 CB ASP A 45 156.816 28.048 2.860 1.00 29.11 C
ATOM 264 CG ASP A 45 157.497 27.297 3.990 1.00 37.23 C
ATOM 265 OD1 ASP A 45 158.709 27.511 4.235 1.00 39.94 O
ATOM 266 OD2 ASP A 45 156.799 26.430 4.585 1.00 39.20 O
ATOM 267 N ASN A 46 155.548 31.438 2.144 1.00 23.46 N
ATOM 268 CA ASN A 46 154.447 32.027 1.383 1.00 20.18 C
ATOM 269 C ASN A 46 153.062 31.519 1.816 1.00 19.44 C
ATOM 270 O ASN A 46 152.076 31.760 1.116 1.00 18.47 O
ATOM 271 CB ASN A 46 154.654 31.807 -0.139 1.00 20.87 C
ATOM 272 CG ASN A 46 154.067 32.948 -0.999 1.00 18.87 C
ATOM 273 OD1 ASN A 46 154.167 34.116 -0.655 1.00 17.15 O
ATOM 274 ND2 ASN A 46 153.461 32.591 -2.121 1.00 17.43 N
ATOM 275 N GLN A 47 152.997 30.892 2.993 1.00 17.36 N
ATOM 276 CA GLN A 47 151.751 30.341 3.546 1.00 18.22 C
ATOM 277 C GLN A 47 151.418 30.963 4.886 1.00 15.93 C
ATOM 278 O GLN A 47 152.304 31.472 5.541 1.00 14.38 O
ATOM 279 CB GLN A 47 151.865 28.838 3.739 1.00 15.71 C
ATOM 280 CG GLN A 47 152.136 28.051 2.462 1.00 22.03 C
ATOM 281 CD GLN A 47 152.347 26.558 2.722 1.00 25.55 C
ATOM 282 OE1 GLN A 47 151.439 25.763 2.537 1.00 32.21 O
ATOM 283 NE2 GLN A 47 153.537 26.184 3.181 1.00 31.59 N
ATOM 284 N LEU A 48 150.132 30.986 5.256 1.00 17.41 N
ATOM 285 CA LEU A 48 149.675 31.543 6.536 1.00 16.58 C
ATOM 286 C LEU A 48 149.446 30.373 7.473 1.00 16.02 C
ATOM 287 O LEU A 48 148.699 29.451 7.163 1.00 16.21 O
ATOM 288 CB LEU A 48 148.391 32.380 6.395 1.00 12.90 C
ATOM 289 CG LEU A 48 148.439 33.713 5.627 1.00 14.27 C
ATOM 290 CD1 LEU A 48 147.083 34.410 5.668 1.00 15.87 C
ATOM 291 CD2 LEU A 48 149.469 34.620 6.205 1.00 13.62 C
ATOM 292 N VAL A 49 150.164 30.398 8.591 1.00 16.03 N
ATOM 293 CA VAL A 49 150.129 29.354 9.608 1.00 15.49 C
ATOM 294 C VAL A 49 149.208 29.776 10.758 1.00 15.64 C
ATOM 295 O VAL A 49 149.358 30.870 11.290 1.00 15.29 O
ATOM 296 CB VAL A 49 151.574 29.100 10.119 1.00 16.30 C
ATOM 297 CG1 VAL A 49 151.635 27.848 10.990 1.00 16.98 C
ATOM 298 CG2 VAL A 49 152.522 28.952 8.958 1.00 18.92 C
ATOM 299 N VAL A 50 148.174 28.987 11.048 1.00 18.05 N
ATOM 300 CA VAL A 50 147.234 29.307 12.139 1.00 18.82 C
ATOM 301 C VAL A 50 147.789 28.999 13.550 1.00 16.51 C
ATOM 302 O VAL A 50 148.261 27.902 13.837 1.00 15.43 O
ATOM 303 CB VAL A 50 145.837 28.635 11.908 1.00 20.27 C
ATOM 304 CG1 VAL A 50 145.899 27.163 12.056 1.00 19.66 C
ATOM 305 CG2 VAL A 50 144.862 29.144 12.865 1.00 24.11 C
ATOM 306 N PRO A 51 147.758 29.992 14.433 1.00 18.89 N
ATOM 307 CA PRO A 51 148.241 29.943 15.827 1.00 20.91 C
ATOM 308 C PRO A 51 147.393 29.238 16.885 1.00 21.62 C
ATOM 309 O PRO A 51 147.878 28.984 17.995 1.00 21.70 O
ATOM 310 CB PRO A 51 148.402 31.425 16.179 1.00 20.57 C
ATOM 311 CG PRO A 51 147.274 32.080 15.392 1.00 19.04 C
ATOM 312 CD PRO A 51 147.365 31.364 14.048 1.00 21.27 C
ATOM 313 N ILE A 52 146.132 28.957 16.555 1.00 21.33 N
ATOM 314 CA ILE A 52 145.185 28.336 17.477 1.00 23.54 C
ATOM 315 C ILE A 52 144.044 27.704 16.697 1.00 23.32 C
ATOM 316 O ILE A 52 143.750 28.092 15.573 1.00 23.21 O
ATOM 317 CB ILE A 52 144.527 29.393 18.416 1.00 26.69 C
ATOM 318 CG1 ILE A 52 143.930 30.530 17.569 1.00 27.85 C
ATOM 319 CG2 ILE A 52 145.529 29.926 19.459 1.00 25.90 C
ATOM 320 CD1 ILE A 52 143.074 31.516 18.337 1.00 29.67 C
ATOM 321 N GLU A 53 143.397 26.728 17.297 1.00 24.87 N
ATOM 322 CA GLU A 53 142.282 26.084 16.635 1.00 27.88 C
ATOM 323 C GLU A 53 141.106 27.031 16.790 1.00 26.53 C
ATOM 324 O GLU A 53 141.071 27.792 17.759 1.00 29.04 O
ATOM 325 CB GLU A 53 142.017 24.754 17.313 1.00 30.38 C
ATOM 326 CG GLU A 53 140.839 24.010 16.796 1.00 37.75 C
ATOM 327 CD GLU A 53 140.201 23.232 17.897 1.00 42.92 C
ATOM 328 OE1 GLU A 53 140.744 22.148 18.226 1.00 41.02 O
ATOM 329 OE2 GLU A 53 139.197 23.750 18.456 1.00 48.72 O
ATOM 330 N GLY A 54 140.203 27.068 15.811 1.00 24.62 N
ATOM 331 CA GLY A 54 139.053 27.964 15.898 1.00 20.71 C
ATOM 332 C GLY A 54 138.336 28.176 14.575 1.00 15.54 C
ATOM 333 O GLY A 54 138.655 27.517 13.610 1.00 17.51 O
ATOM 334 N LEU A 55 137.346 29.052 14.544 1.00 17.03 N
ATOM 335 CA LEU A 55 136.627 29.356 13.308 1.00 15.60 C
ATOM 336 C LEU A 55 137.334 30.575 12.742 1.00 16.96 C
ATOM 337 O LEU A 55 137.585 31.521 13.487 1.00 16.95 O
ATOM 338 CB LEU A 55 135.182 29.747 13.603 1.00 17.07 C
ATOM 339 CG LEU A 55 134.221 28.621 13.998 1.00 20.60 C
ATOM 340 CD1 LEU A 55 132.880 29.188 14.500 1.00 23.33 C
ATOM 341 CD2 LEU A 55 134.003 27.708 12.818 1.00 19.59 C
ATOM 342 N PHE A 56 137.696 30.539 11.448 1.00 16.39 N
ATOM 343 CA PHE A 56 138.358 31.661 10.788 1.00 14.03 C
ATOM 344 C PHE A 56 137.631 32.117 9.523 1.00 12.38 C
ATOM 345 O PHE A 56 137.116 31.275 8.786 1.00 11.33 O
ATOM 346 CB PHE A 56 139.772 31.282 10.335 1.00 12.51 C
ATOM 347 CG PHE A 56 140.787 31.224 11.448 1.00 17.83 C
ATOM 348 CD1 PHE A 56 140.890 30.089 12.262 1.00 20.70 C
ATOM 349 CD2 PHE A 56 141.634 32.311 11.689 1.00 16.16 C
ATOM 350 CE1 PHE A 56 141.811 30.045 13.298 1.00 16.83 C
ATOM 351 CE2 PHE A 56 142.556 32.280 12.717 1.00 15.39 C
ATOM 352 CZ PHE A 56 142.641 31.150 13.519 1.00 18.90 C
ATOM 353 N LEU A 57 137.469 33.428 9.346 1.00 11.29 N
ATOM 354 CA LEU A 57 136.955 33.938 8.076 1.00 10.66 C
ATOM 355 C LEU A 57 138.249 34.015 7.214 1.00 10.32 C
ATOM 356 O LEU A 57 139.232 34.611 7.642 1.00 13.78 O
ATOM 357 CB LEU A 57 136.367 35.321 8.241 1.00 12.96 C
ATOM 358 CG LEU A 57 136.038 35.976 6.877 1.00 18.10 C
ATOM 359 CD1 LEU A 57 134.941 35.164 6.105 1.00 16.74 C
ATOM 360 CD2 LEU A 57 135.552 37.418 7.076 1.00 16.36 C
ATOM 361 N ILE A 58 138.251 33.422 6.024 1.00 9.30 N
ATOM 362 CA ILE A 58 139.436 33.410 5.164 1.00 10.57 C
ATOM 363 C ILE A 58 139.019 34.019 3.831 1.00 12.12 C
ATOM 364 O ILE A 58 137.945 33.701 3.345 1.00 13.73 O
ATOM 365 CB ILE A 58 139.885 31.969 4.927 1.00 14.53 C
ATOM 366 CG1 ILE A 58 140.017 31.227 6.252 1.00 13.43 C
ATOM 367 CG2 ILE A 58 141.213 31.968 4.213 1.00 19.55 C
ATOM 368 CD1 ILE A 58 140.209 29.739 6.090 1.00 20.93 C
ATOM 369 N TYR A 59 139.846 34.863 3.223 1.00 10.68 N
ATOM 370 CA TYR A 59 139.450 35.494 1.959 1.00 9.28 C
ATOM 371 C TYR A 59 140.647 35.894 1.058 1.00 9.65 C
ATOM 372 O TYR A 59 141.806 35.932 1.491 1.00 9.24 O
ATOM 373 CB TYR A 59 138.549 36.721 2.245 1.00 11.30 C
ATOM 374 CG TYR A 59 139.284 37.830 2.996 1.00 6.97 C
ATOM 375 CD1 TYR A 59 140.044 38.792 2.306 1.00 6.96 C
ATOM 376 CD2 TYR A 59 139.300 37.868 4.400 1.00 10.69 C
ATOM 377 CE1 TYR A 59 140.796 39.752 3.009 1.00 8.24 C
ATOM 378 CE2 TYR A 59 140.042 38.812 5.087 1.00 8.56 C
ATOM 379 CZ TYR A 59 140.786 39.739 4.384 1.00 7.21 C
ATOM 380 OH TYR A 59 141.562 40.615 5.080 1.00 11.01 O
ATOM 381 N SER A 60 140.385 36.181 -0.205 1.00 9.01 N
ATOM 382 CA SER A 60 141.476 36.559 -1.088 1.00 10.88 C
ATOM 383 C SER A 60 140.928 37.103 -2.398 1.00 7.56 C
ATOM 384 O SER A 60 139.832 36.737 -2.819 1.00 9.72 O
ATOM 385 CB SER A 60 142.405 35.348 -1.368 1.00 6.90 C
ATOM 386 OG SER A 60 143.481 35.664 -2.268 1.00 12.31 O
ATOM 387 N GLN A 61 141.642 38.045 -2.982 1.00 8.65 N
ATOM 388 CA GLN A 61 141.260 38.568 -4.277 1.00 9.33 C
ATOM 389 C GLN A 61 142.531 38.566 -5.126 1.00 9.29 C
ATOM 390 O GLN A 61 143.640 38.736 -4.607 1.00 7.39 O
ATOM 391 CB GLN A 61 140.734 39.987 -4.159 1.00 6.88 C
ATOM 392 CG GLN A 61 140.477 40.672 -5.497 1.00 12.16 C
ATOM 393 CD GLN A 61 140.021 42.131 -5.377 1.00 8.16 C
ATOM 394 OE1 GLN A 61 139.004 42.444 -4.757 1.00 12.48 O
ATOM 395 NE2 GLN A 61 140.772 43.025 -6.013 1.00 10.82 N
ATOM 396 N VAL A 62 142.358 38.265 -6.410 1.00 10.07 N
ATOM 397 CA VAL A 62 143.423 38.307 -7.372 1.00 8.77 C
ATOM 398 C VAL A 62 142.868 39.093 -8.531 1.00 9.55 C
ATOM 399 O VAL A 62 141.665 39.068 -8.752 1.00 10.13 O
ATOM 400 CB VAL A 62 143.817 36.916 -7.873 1.00 10.60 C
ATOM 401 CG1 VAL A 62 144.564 36.172 -6.749 1.00 12.98 C
ATOM 402 CG2 VAL A 62 142.594 36.155 -8.343 1.00 15.30 C
ATOM 403 N LEU A 63 143.732 39.809 -9.240 1.00 11.16 N
ATOM 404 CA LEU A 63 143.328 40.547 -10.417 1.00 12.38 C
ATOM 405 C LEU A 63 144.270 40.186 -11.591 1.00 12.36 C
ATOM 406 O LEU A 63 145.498 40.353 -11.512 1.00 9.63 O
ATOM 407 CB LEU A 63 143.353 42.040 -10.136 1.00 12.38 C
ATOM 408 CG LEU A 63 142.498 42.905 -11.052 1.00 14.68 C
ATOM 409 CD1 LEU A 63 142.600 44.337 -10.522 1.00 18.87 C
ATOM 410 CD2 LEU A 63 143.012 42.873 -12.413 1.00 20.69 C
ATOM 411 N PHE A 64 143.690 39.708 -12.696 1.00 13.07 N
ATOM 412 CA PHE A 64 144.466 39.327 -13.879 1.00 10.92 C
ATOM 413 C PHE A 64 144.319 40.378 -14.960 1.00 10.72 C
ATOM 414 O PHE A 64 143.305 41.056 -15.073 1.00 10.15 O
ATOM 415 CB PHE A 64 143.999 37.974 -14.424 1.00 13.06 C
ATOM 416 CG PHE A 64 144.112 36.825 -13.425 1.00 15.95 C
ATOM 417 CD1 PHE A 64 145.342 36.218 -13.145 1.00 14.39 C
ATOM 418 CD2 PHE A 64 142.968 36.293 -12.836 1.00 11.76 C
ATOM 419 CE1 PHE A 64 145.412 35.098 -12.310 1.00 14.59 C
ATOM 420 CE2 PHE A 64 143.035 35.178 -12.005 1.00 12.78 C
ATOM 421 CZ PHE A 64 144.255 34.583 -11.745 1.00 12.65 C
ATOM 422 N LYS A 65 145.318 40.507 -15.789 1.00 12.13 N
ATOM 423 CA LYS A 65 145.203 41.493 -16.823 1.00 14.96 C
ATOM 424 C LYS A 65 145.825 40.938 -18.064 1.00 19.75 C
ATOM 425 O LYS A 65 146.846 40.245 -17.968 1.00 17.88 O
ATOM 426 CB LYS A 65 145.962 42.744 -16.428 1.00 17.82 C
ATOM 427 CG LYS A 65 145.903 43.851 -17.457 1.00 21.84 C
ATOM 428 CD LYS A 65 147.214 44.578 -17.555 1.00 23.46 C
ATOM 429 CE LYS A 65 147.050 45.714 -18.538 1.00 27.61 C
ATOM 430 NZ LYS A 65 147.858 46.916 -18.193 1.00 31.18 N
ATOM 431 N GLY A 66 145.229 41.247 -19.222 1.00 20.48 N
ATOM 432 CA GLY A 66 145.776 40.802 -20.501 1.00 27.18 C
ATOM 433 C GLY A 66 145.701 41.841 -21.610 1.00 31.95 C
ATOM 434 O GLY A 66 145.100 42.896 -21.424 1.00 30.27 O
ATOM 435 N GLN A 67 146.315 41.714 -22.694 1.00 37.91 N
ATOM 436 CA GLN A 67 146.253 42.712 -23.787 1.00 40.98 C
ATOM 437 C GLN A 67 145.757 42.065 -25.063 1.00 40.98 C
ATOM 438 O GLN A 67 146.529 41.739 -25.939 1.00 40.65 O
ATOM 439 CB GLN A 67 147.586 43.485 -23.985 1.00 45.12 C
ATOM 440 CG GLN A 67 148.828 42.591 -24.198 1.00 53.61 C
ATOM 441 CD GLN A 67 150.169 43.256 -23.796 1.00 58.12 C
ATOM 442 OE1 GLN A 67 150.979 43.691 -24.649 1.00 60.58 O
ATOM 443 NE2 GLN A 67 150.417 43.309 -22.480 1.00 60.80 N
ATOM 444 N GLY A 68 144.441 41.918 -25.112 1.00 41.86 N
ATOM 445 CA GLY A 68 143.758 41.331 -26.218 1.00 44.13 C
ATOM 446 C GLY A 68 143.674 39.853 -25.996 1.00 47.55 C
ATOM 447 O GLY A 68 144.083 39.357 -24.963 1.00 44.84 O
ATOM 448 N CYS A 69 143.174 39.143 -26.997 1.00 53.62 N
ATOM 449 CA CYS A 69 143.033 37.684 -26.938 1.00 62.25 C
ATOM 450 C CYS A 69 143.862 36.894 -27.991 1.00 67.78 C
ATOM 451 O CYS A 69 143.275 36.120 -28.764 1.00 68.75 O
ATOM 452 CB CYS A 69 141.565 37.272 -27.096 1.00 60.88 C
ATOM 453 SG CYS A 69 140.448 37.934 -25.905 1.00 64.44 S
ATOM 454 N PRO A 70 145.224 37.026 -27.989 1.00 73.36 N
ATOM 455 CA PRO A 70 146.159 36.353 -28.915 1.00 78.19 C
ATOM 456 C PRO A 70 145.780 34.988 -29.567 1.00 82.11 C
ATOM 457 O PRO A 70 145.954 34.782 -30.788 1.00 83.22 O
ATOM 458 CB PRO A 70 147.443 36.283 -28.072 1.00 76.96 C
ATOM 459 CG PRO A 70 147.461 37.643 -27.445 1.00 74.67 C
ATOM 460 CD PRO A 70 145.995 37.843 -27.018 1.00 74.33 C
ATOM 461 N SER A 71 145.424 34.395 -30.550 1.00 86.04 N
ATOM 462 CA SER A 71 145.404 33.039 -31.113 1.00 89.11 C
ATOM 463 C SER A 71 144.767 31.771 -30.458 1.00 88.40 C
ATOM 464 O SER A 71 144.315 30.849 -31.179 1.00 89.46 O
ATOM 465 CB SER A 71 146.854 32.696 -31.540 1.00 91.69 C
ATOM 466 OG SER A 71 147.092 31.285 -31.632 1.00 96.00 O
ATOM 467 N THR A 72 144.762 31.677 -29.131 1.00 86.12 N
ATOM 468 CA THR A 72 144.239 30.469 -28.486 1.00 82.35 C
ATOM 469 C THR A 72 143.702 30.815 -27.093 1.00 76.27 C
ATOM 470 O THR A 72 143.692 32.009 -26.718 1.00 77.40 O
ATOM 471 CB THR A 72 145.338 29.403 -28.396 1.00 84.78 C
ATOM 472 OG1 THR A 72 144.906 28.310 -27.566 1.00 87.54 O
ATOM 473 CG2 THR A 72 146.624 30.048 -27.838 1.00 86.05 C
ATOM 474 N HIS A 73 142.990 28.379 -25.746 1.00 68.68 N
ATOM 475 CA HIS A 73 142.679 29.508 -24.901 1.00 59.58 C
ATOM 476 C HIS A 73 143.088 29.268 -23.438 1.00 53.71 C
ATOM 477 O HIS A 73 143.383 28.135 -22.998 1.00 51.71 O
ATOM 478 CB HIS A 73 141.202 29.919 -25.032 1.00 61.72 C
ATOM 479 CG HIS A 73 140.932 30.976 -26.088 1.00 64.15 C
ATOM 480 ND1 HIS A 73 141.903 31.839 -26.569 1.00 64.93 N
ATOM 481 CD2 HIS A 73 139.773 31.339 -26.707 1.00 64.65 C
ATOM 482 CE1 HIS A 73 141.352 32.687 -27.425 1.00 64.78 C
ATOM 483 NE2 HIS A 73 140.063 32.405 -27.527 1.00 64.61 N
ATOM 484 N VAL A 74 143.056 30.287 -22.721 1.00 46.33 N
ATOM 485 CA VAL A 74 143.599 30.460 -21.376 1.00 36.22 C
ATOM 486 C VAL A 74 142.495 30.468 -20.322 1.00 31.87 C
ATOM 487 O VAL A 74 141.454 31.107 -20.485 1.00 25.32 O
ATOM 488 CB VAL A 74 144.373 31.810 -21.216 1.00 36.31 C
ATOM 489 CG1 VAL A 74 145.156 31.835 -19.914 1.00 37.31 C
ATOM 490 CG2 VAL A 74 145.325 32.050 -22.388 1.00 36.17 C
ATOM 491 N LEU A 75 142.726 29.697 -19.266 1.00 28.74 N
ATOM 492 CA LEU A 75 141.836 29.617 -18.117 1.00 27.40 C
ATOM 493 C LEU A 75 142.633 30.164 -16.946 1.00 25.13 C
ATOM 494 O LEU A 75 143.834 29.903 -16.804 1.00 24.29 O
ATOM 495 CB LEU A 75 141.399 28.184 -17.844 1.00 30.26 C
ATOM 496 CG LEU A 75 140.192 27.799 -18.683 1.00 31.53 C
ATOM 497 CD1 LEU A 75 139.784 26.367 -18.386 1.00 34.94 C
ATOM 498 CD2 LEU A 75 139.091 28.764 -18.387 1.00 32.19 C
ATOM 499 N LEU A 76 141.973 30.933 -16.108 1.00 20.85 N
ATOM 500 CA LEU A 76 142.648 31.541 -14.975 1.00 18.54 C
ATOM 501 C LEU A 76 142.027 30.944 -13.724 1.00 15.05 C
ATOM 502 O LEU A 76 140.807 30.899 -13.605 1.00 14.77 O
ATOM 503 CB LEU A 76 142.473 33.067 -15.039 1.00 18.52 C
ATOM 504 CG LEU A 76 143.265 33.949 -16.046 1.00 25.31 C
ATOM 505 CD1 LEU A 76 144.103 33.185 -17.028 1.00 25.29 C
ATOM 506 CD2 LEU A 76 142.343 34.937 -16.723 1.00 27.38 C
ATOM 507 N THR A 77 142.846 30.415 -12.832 1.00 13.04 N
ATOM 508 CA THR A 77 142.317 29.797 -11.615 1.00 14.45 C
ATOM 509 C THR A 77 142.874 30.479 -10.366 1.00 13.18 C
ATOM 510 O THR A 77 143.940 31.116 -10.418 1.00 11.55 O
ATOM 511 CB THR A 77 142.647 28.273 -11.564 1.00 14.37 C
ATOM 512 OG1 THR A 77 144.057 28.074 -11.327 1.00 11.98 O
ATOM 513 CG2 THR A 77 142.205 27.596 -12.882 1.00 15.82 C
ATOM 514 N HIS A 78 142.120 30.391 -9.277 1.00 10.47 N
ATOM 515 CA HIS A 78 142.504 30.958 -7.977 1.00 8.86 C
ATOM 516 C HIS A 78 141.938 29.994 -6.972 1.00 9.82 C
ATOM 517 O HIS A 78 140.743 29.680 -7.043 1.00 10.74 O
ATOM 518 CB HIS A 78 141.825 32.315 -7.792 1.00 11.94 C
ATOM 519 CG HIS A 78 142.116 32.991 -6.485 1.00 15.09 C
ATOM 520 ND1 HIS A 78 141.206 33.815 -5.855 1.00 19.91 N
ATOM 521 CD2 HIS A 78 143.247 33.047 -5.742 1.00 16.68 C
ATOM 522 CE1 HIS A 78 141.769 34.361 -4.791 1.00 14.79 C
ATOM 523 NE2 HIS A 78 143.005 33.913 -4.701 1.00 16.53 N
ATOM 524 N THR A 79 142.757 29.513 -6.040 1.00 10.36 N
ATOM 525 CA THR A 79 142.228 28.583 -5.050 1.00 10.26 C
ATOM 526 C THR A 79 142.897 28.810 -3.719 1.00 12.48 C
ATOM 527 O THR A 79 143.973 29.418 -3.655 1.00 14.17 O
ATOM 528 CB THR A 79 142.249 27.049 -5.536 1.00 16.73 C
ATOM 529 OG1 THR A 79 143.291 26.303 -4.931 1.00 25.39 O
ATOM 530 CG2 THR A 79 142.414 26.907 -7.010 1.00 13.30 C
ATOM 531 N ILE A 80 142.160 28.548 -2.655 1.00 12.25 N
ATOM 532 CA ILE A 80 142.738 28.679 -1.310 1.00 12.39 C
ATOM 533 C ILE A 80 142.715 27.255 -0.786 1.00 9.85 C
ATOM 534 O ILE A 80 141.685 26.636 -0.857 1.00 9.71 O
ATOM 535 CB ILE A 80 141.898 29.619 -0.388 1.00 8.84 C
ATOM 536 CG1 ILE A 80 142.010 31.064 -0.877 1.00 12.23 C
ATOM 537 CG2 ILE A 80 142.428 29.581 1.083 1.00 11.01 C
ATOM 538 CD1 ILE A 80 141.009 32.035 -0.201 1.00 10.77 C
ATOM 539 N SER A 81 143.879 26.673 -0.500 1.00 11.87 N
ATOM 540 CA SER A 81 143.942 25.339 0.075 1.00 11.73 C
ATOM 541 C SER A 81 144.341 25.356 1.547 1.00 15.56 C
ATOM 542 O SER A 81 144.961 26.305 2.039 1.00 17.30 O
ATOM 543 CB SER A 81 144.999 24.542 -0.617 1.00 15.75 C
ATOM 544 OG SER A 81 144.969 24.870 -1.966 1.00 28.39 O
ATOM 545 N ARG A 82 144.064 24.241 2.207 1.00 16.85 N
ATOM 546 CA ARG A 82 144.392 24.027 3.602 1.00 17.03 C
ATOM 547 C ARG A 82 145.340 22.828 3.601 1.00 20.76 C
ATOM 548 O ARG A 82 145.089 21.860 2.864 1.00 17.91 O
ATOM 549 CB ARG A 82 143.120 23.631 4.326 1.00 16.82 C
ATOM 550 CG ARG A 82 143.307 23.378 5.803 1.00 20.13 C
ATOM 551 CD ARG A 82 142.050 22.836 6.404 1.00 20.04 C
ATOM 552 NE ARG A 82 142.376 22.207 7.671 1.00 27.98 N
ATOM 553 CZ ARG A 82 141.563 21.419 8.361 1.00 30.32 C
ATOM 554 NH1 ARG A 82 140.344 21.140 7.917 1.00 28.33 N
ATOM 555 NH2 ARG A 82 141.979 20.919 9.514 1.00 30.81 N
ATOM 556 N ILE A 83 146.457 22.912 4.332 1.00 25.59 N
ATOM 557 CA ILE A 83 147.383 21.766 4.421 1.00 30.86 C
ATOM 558 C ILE A 83 147.474 21.225 5.848 1.00 36.26 C
ATOM 559 O ILE A 83 147.381 21.984 6.814 1.00 33.38 O
ATOM 560 CB ILE A 83 148.828 22.018 3.803 1.00 30.20 C
ATOM 561 CG1 ILE A 83 149.908 21.913 4.884 1.00 30.27 C
ATOM 562 CG2 ILE A 83 148.877 23.322 2.987 1.00 30.31 C
ATOM 563 CD1 ILE A 83 151.328 22.075 4.403 1.00 34.89 C
ATOM 564 N ALA A 84 146.356 20.588 6.607 1.00 44.19 N
ATOM 565 CA ALA A 84 146.115 20.233 8.004 1.00 52.59 C
ATOM 566 C ALA A 84 147.272 19.603 8.765 1.00 58.50 C
ATOM 567 O ALA A 84 148.209 19.043 8.170 1.00 58.67 O
ATOM 568 CB ALA A 84 144.902 19.348 8.111 1.00 49.84 C
ATOM 569 N VAL A 85 147.233 19.792 10.088 1.00 65.35 N
ATOM 570 CA VAL A 85 148.220 19.211 10.990 1.00 70.50 C
ATOM 571 C VAL A 85 149.622 19.861 11.127 1.00 74.31 C
ATOM 572 O VAL A 85 149.837 20.772 11.956 1.00 74.83 O
ATOM 573 CB VAL A 85 148.349 17.661 10.677 1.00 69.90 C
ATOM 574 CG1 VAL A 85 149.630 17.059 11.272 1.00 69.59 C
ATOM 575 CG2 VAL A 85 147.086 16.900 11.170 1.00 68.52 C
ATOM 576 N SER A 86 150.582 19.332 10.373 1.00 78.14 N
ATOM 577 CA SER A 86 151.997 19.737 10.424 1.00 82.42 C
ATOM 578 C SER A 86 152.586 18.760 9.436 1.00 83.87 C
ATOM 579 O SER A 86 153.049 17.682 9.847 1.00 84.70 O
ATOM 580 CB SER A 86 152.609 19.421 11.797 1.00 83.63 C
ATOM 581 OG SER A 86 152.535 20.550 12.643 1.00 84.92 O
ATOM 582 N TYR A 87 152.417 19.082 8.150 1.00 84.60 N
ATOM 583 CA TYR A 87 152.865 18.257 7.030 1.00 83.31 C
ATOM 584 C TYR A 87 151.891 17.094 6.724 1.00 82.14 C
ATOM 585 O TYR A 87 152.282 15.927 6.704 1.00 82.75 O
ATOM 586 CB TYR A 87 154.304 17.748 7.264 1.00 83.13 C
ATOM 587 N GLN A 88 150.603 17.407 6.582 1.00 80.64 N
ATOM 588 CA GLN A 88 149.613 16.386 6.220 1.00 79.15 C
ATOM 589 C GLN A 88 149.231 16.706 4.773 1.00 78.25 C
ATOM 590 O GLN A 88 150.010 17.371 4.075 1.00 78.91 O
ATOM 591 CB GLN A 88 148.395 16.419 7.130 1.00 77.67 C
ATOM 592 N THR A 89 148.038 16.295 4.331 1.00 76.42 N
ATOM 593 CA THR A 89 147.611 16.535 2.939 1.00 73.67 C
ATOM 594 C THR A 89 147.156 17.962 2.651 1.00 70.63 C
ATOM 595 O THR A 89 146.904 18.747 3.573 1.00 69.90 O
ATOM 596 CB THR A 89 146.420 15.632 2.539 1.00 75.37 C
ATOM 597 OG1 THR A 89 146.210 15.698 1.109 1.00 76.17 O
ATOM 598 CG2 THR A 89 145.135 16.109 3.282 1.00 76.34 C
ATOM 599 N LYS A 90 147.009 18.256 1.360 1.00 66.36 N
ATOM 600 CA LYS A 90 146.530 19.545 0.894 1.00 61.48 C
ATOM 601 C LYS A 90 145.094 19.310 0.380 1.00 58.73 C
ATOM 602 O LYS A 90 144.824 18.253 -0.216 1.00 59.46 O
ATOM 603 CB LYS A 90 147.424 20.065 -0.225 1.00 59.63 C
ATOM 604 CG LYS A 90 147.179 21.505 -0.488 1.00 60.67 C
ATOM 605 CD LYS A 90 148.261 22.086 -1.311 1.00 61.36 C
ATOM 606 CE LYS A 90 148.201 23.594 -1.276 1.00 62.29 C
ATOM 607 NZ LYS A 90 149.379 24.147 -1.982 1.00 61.77 N
ATOM 608 N VAL A 91 144.170 20.233 0.666 1.00 52.42 N
ATOM 609 CA VAL A 91 142.774 20.118 0.217 1.00 46.24 C
ATOM 610 C VAL A 91 142.198 21.511 -0.106 1.00 40.66 C
ATOM 611 O VAL A 91 142.445 22.470 0.632 1.00 39.95 O
ATOM 612 CB VAL A 91 141.902 19.446 1.280 1.00 46.28 C
ATOM 613 CG1 VAL A 91 141.986 20.190 2.606 1.00 46.22 C
ATOM 614 CG2 VAL A 91 140.484 19.410 0.800 1.00 47.03 C
ATOM 615 N ASN A 92 141.524 21.766 -1.080 1.00 32.03 N
ATOM 616 CA ASN A 92 140.933 23.048 -1.501 1.00 25.84 C
ATOM 617 C ASN A 92 139.702 23.402 -0.676 1.00 20.98 C
ATOM 618 O ASN A 92 138.856 22.567 -0.402 1.00 21.80 O
ATOM 619 CB ASN A 92 140.554 23.048 -2.981 1.00 26.50 C
ATOM 620 CG ASN A 92 141.756 22.983 -3.912 1.00 29.41 C
ATOM 621 OD1 ASN A 92 142.912 22.913 -3.482 1.00 31.51 O
ATOM 622 ND2 ASN A 92 141.477 22.998 -5.210 1.00 30.18 N
ATOM 623 N LEU A 93 139.692 24.622 -0.178 1.00 16.21 N
ATOM 624 CA LEU A 93 138.612 25.103 0.623 1.00 12.23 C
ATOM 625 C LEU A 93 137.719 25.967 -0.234 1.00 10.77 C
ATOM 626 O LEU A 93 136.507 25.860 -0.146 1.00 11.33 O
ATOM 627 CB LEU A 93 139.173 25.939 1.775 1.00 13.27 C
ATOM 628 CG LEU A 93 139.961 25.224 2.885 1.00 11.22 C
ATOM 629 CD1 LEU A 93 140.563 26.206 3.818 1.00 15.16 C
ATOM 630 CD2 LEU A 93 139.122 24.208 3.622 1.00 9.71 C
ATOM 631 N LEU A 94 138.321 26.757 -1.122 1.00 12.44 N
ATOM 632 CA LEU A 94 137.610 27.724 -1.980 1.00 10.12 C
ATOM 633 C LEU A 94 138.335 27.727 -3.317 1.00 12.04 C
ATOM 634 O LEU A 94 139.569 27.640 -3.353 1.00 11.28 O
ATOM 635 CB LEU A 94 137.681 29.117 -1.329 1.00 11.80 C
ATOM 636 CG LEU A 94 137.166 29.301 0.113 1.00 9.62 C
ATOM 637 CD1 LEU A 94 137.760 30.589 0.739 1.00 13.27 C
ATOM 638 CD2 LEU A 94 135.639 29.394 0.082 1.00 11.46 C
ATOM 639 N SER A 95 137.586 27.871 -4.403 1.00 12.23 N
ATOM 640 CA SER A 95 138.173 27.804 -5.740 1.00 13.05 C
ATOM 641 C SER A 95 137.259 28.478 -6.783 1.00 11.64 C
ATOM 642 O SER A 95 136.018 28.402 -6.701 1.00 11.49 O
ATOM 643 CB SER A 95 138.356 26.317 -6.082 1.00 13.46 C
ATOM 644 OG SER A 95 139.257 26.170 -7.153 1.00 22.53 O
ATOM 645 N ALA A 96 137.876 29.134 -7.760 1.00 9.33 N
ATOM 646 CA ALA A 96 137.139 29.785 -8.858 1.00 9.37 C
ATOM 647 C ALA A 96 137.952 29.692 -10.136 1.00 10.16 C
ATOM 648 O ALA A 96 139.165 29.533 -10.085 1.00 9.13 O
ATOM 649 CB ALA A 96 136.803 31.212 -8.555 1.00 7.20 C
ATOM 650 N ILE A 97 137.271 29.702 -11.275 1.00 11.82 N
ATOM 651 CA ILE A 97 137.910 29.636 -12.591 1.00 14.10 C
ATOM 652 C ILE A 97 137.260 30.696 -13.411 1.00 13.14 C
ATOM 653 O ILE A 97 136.063 30.944 -13.264 1.00 14.36 O
ATOM 654 CB ILE A 97 137.611 28.329 -13.356 1.00 15.42 C
ATOM 655 CG1 ILE A 97 137.996 27.138 -12.508 1.00 16.89 C
ATOM 656 CG2 ILE A 97 138.413 28.279 -14.661 1.00 15.09 C
ATOM 657 CD1 ILE A 97 137.346 25.874 -12.964 1.00 23.07 C
ATOM 658 N LYS A 98 138.010 31.228 -14.357 1.00 13.95 N
ATOM 659 CA LYS A 98 137.496 32.261 -15.216 1.00 18.27 C
ATOM 660 C LYS A 98 138.182 32.125 -16.574 1.00 18.16 C
ATOM 661 O LYS A 98 139.328 31.672 -16.637 1.00 20.04 O
ATOM 662 CB LYS A 98 137.865 33.575 -14.571 1.00 21.03 C
ATOM 663 CG LYS A 98 137.177 34.727 -15.120 1.00 24.61 C
ATOM 664 CD LYS A 98 137.445 35.824 -14.211 1.00 28.64 C
ATOM 665 CE LYS A 98 136.258 36.097 -13.386 1.00 30.54 C
ATOM 666 NZ LYS A 98 136.787 37.129 -12.545 1.00 34.04 N
ATOM 667 N SER A 99 137.470 32.402 -17.654 1.00 19.28 N
ATOM 668 CA SER A 99 138.102 32.351 -18.974 1.00 20.54 C
ATOM 669 C SER A 99 137.992 33.746 -19.551 1.00 24.24 C
ATOM 670 O SER A 99 136.903 34.315 -19.638 1.00 24.84 O
ATOM 671 CB SER A 99 137.508 31.274 -19.909 1.00 23.81 C
ATOM 672 OG SER A 99 136.089 31.254 -19.939 1.00 29.79 O
ATOM 673 N PRO A 100 139.146 34.376 -19.793 1.00 26.60 N
ATOM 674 CA PRO A 100 139.153 35.724 -20.348 1.00 27.42 C
ATOM 675 C PRO A 100 138.741 35.833 -21.810 1.00 30.40 C
ATOM 676 O PRO A 100 137.987 36.715 -22.152 1.00 32.15 O
ATOM 677 CB PRO A 100 140.589 36.178 -20.109 1.00 27.70 C
ATOM 678 CG PRO A 100 141.382 34.875 -20.065 1.00 27.75 C
ATOM 679 CD PRO A 100 140.484 33.969 -19.322 1.00 26.12 C
ATOM 680 N CYS A 101 139.200 34.945 -22.678 1.00 34.08 N
ATOM 681 CA CYS A 101 138.827 35.074 -24.082 1.00 40.79 C
ATOM 682 C CYS A 101 137.980 33.968 -24.697 1.00 46.10 C
ATOM 683 O CYS A 101 138.386 32.802 -24.774 1.00 48.78 O
ATOM 684 CB CYS A 101 140.066 35.249 -24.930 1.00 39.94 C
ATOM 685 SG CYS A 101 141.039 36.676 -24.519 1.00 44.90 S
ATOM 686 N GLN A 102 136.814 34.342 -25.199 1.00 52.41 N
ATOM 687 CA GLN A 102 135.984 33.343 -25.826 1.00 57.68 C
ATOM 688 C GLN A 102 136.564 33.224 -27.247 1.00 59.52 C
ATOM 689 O GLN A 102 136.710 32.116 -27.769 1.00 60.62 O
ATOM 690 CB GLN A 102 134.503 33.763 -25.796 1.00 59.89 C
ATOM 691 CG GLN A 102 133.525 32.641 -25.367 1.00 61.98 C
ATOM 692 CD GLN A 102 133.596 32.274 -23.881 1.00 64.75 C
ATOM 693 OE1 GLN A 102 134.541 31.621 -23.407 1.00 65.12 O
ATOM 694 NE2 GLN A 102 132.565 32.664 -23.145 1.00 65.07 N
ATOM 695 N ARG A 103 137.022 34.356 -27.796 1.00 60.57 N
ATOM 696 CA ARG A 103 137.613 34.409 -29.140 1.00 61.59 C
ATOM 697 C ARG A 103 138.560 35.609 -29.387 1.00 63.50 C
ATOM 698 O ARG A 103 138.672 36.508 -28.548 1.00 63.76 O
ATOM 699 CB ARG A 103 136.504 34.388 -30.200 1.00 59.24 C
ATOM 700 N GLU A 104 139.262 35.539 -30.527 1.00 66.69 N
ATOM 701 CA GLU A 104 140.233 36.502 -31.106 1.00 70.55 C
ATOM 702 C GLU A 104 141.344 35.674 -31.722 1.00 74.59 C
ATOM 703 O GLU A 104 141.116 34.526 -32.110 1.00 74.13 O
ATOM 704 CB GLU A 104 140.844 37.523 -30.129 1.00 70.37 C
ATOM 705 CG GLU A 104 142.194 38.109 -30.655 1.00 70.82 C
ATOM 706 CD GLU A 104 142.312 39.640 -30.624 1.00 70.34 C
ATOM 707 OE1 GLU A 104 141.556 40.336 -31.332 1.00 70.07 O
ATOM 708 OE2 GLU A 104 143.212 40.156 -29.930 1.00 70.09 O
ATOM 709 N THR A 105 140.954 35.709 -33.677 1.00 81.65 N
ATOM 710 CA THR A 105 141.464 34.824 -34.784 1.00 87.35 C
ATOM 711 C THR A 105 142.067 35.652 -36.007 1.00 90.13 C
ATOM 712 O THR A 105 142.365 36.897 -35.846 1.00 90.21 O
ATOM 713 CB THR A 105 140.210 33.881 -35.242 1.00 88.59 C
ATOM 714 OG1 THR A 105 138.945 34.518 -34.900 1.00 91.31 O
ATOM 715 CG2 THR A 105 140.258 32.431 -34.596 1.00 88.63 C
ATOM 716 N PRO A 106 142.138 35.039 -37.260 1.00 92.17 N
ATOM 717 CA PRO A 106 142.707 35.754 -38.453 1.00 93.63 C
ATOM 718 C PRO A 106 142.790 37.327 -38.651 1.00 94.86 C
ATOM 719 O PRO A 106 141.880 37.952 -39.325 1.00 95.77 O
ATOM 720 CB PRO A 106 141.911 35.133 -39.627 1.00 93.20 C
ATOM 721 CG PRO A 106 141.846 33.701 -39.239 1.00 92.26 C
ATOM 722 CD PRO A 106 141.618 33.710 -37.688 1.00 91.68 C
ATOM 723 N GLU A 107 143.884 37.954 -38.169 1.00 95.05 N
ATOM 724 CA GLU A 107 144.098 39.400 -38.363 1.00 95.21 C
ATOM 725 C GLU A 107 142.929 40.384 -38.107 1.00 95.40 C
ATOM 726 O GLU A 107 141.917 40.078 -37.440 1.00 95.78 O
ATOM 727 CB GLU A 107 144.685 39.655 -39.759 1.00 94.25 C
ATOM 728 N GLY A 108 143.050 41.558 -38.708 1.00 95.84 N
ATOM 729 CA GLY A 108 142.069 42.606 -38.482 1.00 96.19 C
ATOM 730 C GLY A 108 142.831 43.580 -37.558 1.00 96.70 C
ATOM 731 O GLY A 108 144.083 43.792 -37.695 1.00 96.78 O
ATOM 732 N ALA A 109 142.104 44.147 -36.585 1.00 95.66 N
ATOM 733 CA ALA A 109 142.717 45.087 -35.625 1.00 93.55 C
ATOM 734 C ALA A 109 142.830 44.271 -34.326 1.00 90.80 C
ATOM 735 O ALA A 109 142.545 43.036 -34.375 1.00 91.97 O
ATOM 736 CB ALA A 109 141.813 46.324 -35.454 1.00 94.49 C
ATOM 737 N GLU A 110 143.211 44.872 -33.178 1.00 86.58 N
ATOM 738 CA GLU A 110 143.303 43.963 -32.004 1.00 82.70 C
ATOM 739 C GLU A 110 143.579 44.490 -30.581 1.00 78.42 C
ATOM 740 O GLU A 110 143.296 45.670 -30.268 1.00 78.66 O
ATOM 741 CB GLU A 110 144.364 42.852 -32.341 1.00 83.97 C
ATOM 742 N ALA A 111 144.270 43.452 -29.371 1.00 72.29 N
ATOM 743 CA ALA A 111 145.294 44.198 -28.632 1.00 66.49 C
ATOM 744 C ALA A 111 144.734 45.116 -27.531 1.00 61.84 C
ATOM 745 O ALA A 111 145.439 45.997 -27.011 1.00 62.47 O
ATOM 746 CB ALA A 111 146.177 45.003 -29.601 1.00 66.89 C
ATOM 747 N LYS A 112 143.448 44.955 -27.233 1.00 55.77 N
ATOM 748 CA LYS A 112 142.796 45.729 -26.176 1.00 49.52 C
ATOM 749 C LYS A 112 143.017 45.015 -24.827 1.00 44.66 C
ATOM 750 O LYS A 112 142.829 43.798 -24.721 1.00 41.76 O
ATOM 751 CB LYS A 112 141.287 45.926 -26.466 1.00 49.12 C
ATOM 752 CG LYS A 112 140.665 44.917 -27.424 1.00 48.61 C
ATOM 753 CD LYS A 112 140.797 43.504 -26.875 1.00 48.10 C
ATOM 754 CE LYS A 112 140.826 42.448 -27.968 1.00 46.57 C
ATOM 755 NZ LYS A 112 140.954 41.129 -27.321 1.00 45.20 N
ATOM 756 N PRO A 113 143.527 45.740 -23.817 1.00 40.92 N
ATOM 757 CA PRO A 113 143.751 45.103 -22.513 1.00 38.66 C
ATOM 758 C PRO A 113 142.431 44.747 -21.836 1.00 34.21 C
ATOM 759 O PRO A 113 141.413 45.438 -21.990 1.00 33.86 O
ATOM 760 CB PRO A 113 144.523 46.171 -21.722 1.00 39.82 C
ATOM 761 CG PRO A 113 144.008 47.451 -22.300 1.00 39.92 C
ATOM 762 CD PRO A 113 143.990 47.137 -23.802 1.00 40.85 C
ATOM 763 N TRP A 114 142.460 43.682 -21.055 1.00 27.41 N
ATOM 764 CA TRP A 114 141.263 43.265 -20.375 1.00 21.71 C
ATOM 765 C TRP A 114 141.659 43.034 -18.939 1.00 19.51 C
ATOM 766 O TRP A 114 142.835 42.812 -18.674 1.00 17.22 O
ATOM 767 CB TRP A 114 140.667 41.999 -21.030 1.00 18.83 C
ATOM 768 CG TRP A 114 141.609 40.863 -21.269 1.00 17.27 C
ATOM 769 CD1 TRP A 114 142.200 40.501 -22.466 1.00 18.02 C
ATOM 770 CD2 TRP A 114 142.067 39.918 -20.289 1.00 18.20 C
ATOM 771 NE1 TRP A 114 142.996 39.395 -22.278 1.00 16.57 N
ATOM 772 CE2 TRP A 114 142.932 39.016 -20.957 1.00 17.54 C
ATOM 773 CE3 TRP A 114 141.834 39.745 -18.908 1.00 13.25 C
ATOM 774 CZ2 TRP A 114 143.572 37.961 -20.285 1.00 19.73 C
ATOM 775 CZ3 TRP A 114 142.470 38.697 -18.238 1.00 10.85 C
ATOM 776 CH2 TRP A 114 143.330 37.821 -18.929 1.00 15.22 C
ATOM 777 N TYR A 115 140.707 43.181 -18.010 1.00 17.91 N
ATOM 778 CA TYR A 115 140.948 42.939 -16.596 1.00 13.28 C
ATOM 779 C TYR A 115 139.891 42.001 -16.076 1.00 12.72 C
ATOM 780 O TYR A 115 138.726 42.072 -16.480 1.00 14.81 O
ATOM 781 CB TYR A 115 140.843 44.191 -15.811 1.00 11.84 C
ATOM 782 CG TYR A 115 141.950 45.092 -16.053 1.00 14.28 C
ATOM 783 CD1 TYR A 115 141.934 45.951 -17.151 1.00 16.77 C
ATOM 784 CD2 TYR A 115 143.009 45.131 -15.163 1.00 13.80 C
ATOM 785 CE1 TYR A 115 142.963 46.846 -17.357 1.00 21.10 C
ATOM 786 CE2 TYR A 115 144.038 46.005 -15.341 1.00 18.22 C
ATOM 787 CZ TYR A 115 144.023 46.875 -16.436 1.00 21.70 C
ATOM 788 OH TYR A 115 145.046 47.795 -16.581 1.00 25.62 O
ATOM 789 N GLU A 116 140.303 41.156 -15.132 1.00 13.08 N
ATOM 790 CA GLU A 116 139.438 40.167 -14.538 1.00 12.20 C
ATOM 791 C GLU A 116 139.799 39.901 -13.072 1.00 12.50 C
ATOM 792 O GLU A 116 140.875 39.349 -12.773 1.00 9.75 O
ATOM 793 CB GLU A 116 139.552 38.836 -15.291 1.00 18.67 C
ATOM 794 CG GLU A 116 139.029 38.844 -16.696 1.00 18.84 C
ATOM 795 CD GLU A 116 137.532 38.956 -16.781 1.00 22.77 C
ATOM 796 OE1 GLU A 116 136.854 39.311 -15.797 1.00 19.57 O
ATOM 797 OE2 GLU A 116 137.009 38.696 -17.881 1.00 28.82 O
ATOM 798 N PRO A 117 138.910 40.327 -12.143 1.00 12.52 N
ATOM 799 CA PRO A 117 139.120 40.117 -10.697 1.00 13.93 C
ATOM 800 C PRO A 117 138.445 38.779 -10.240 1.00 13.59 C
ATOM 801 O PRO A 117 137.480 38.324 -10.845 1.00 12.95 O
ATOM 802 CB PRO A 117 138.454 41.352 -10.053 1.00 12.17 C
ATOM 803 CG PRO A 117 137.279 41.641 -11.010 1.00 10.30 C
ATOM 804 CD PRO A 117 137.718 41.176 -12.408 1.00 10.60 C
ATOM 805 N ILE A 118 139.002 38.098 -9.241 1.00 13.57 N
ATOM 806 CA ILE A 118 138.329 36.902 -8.711 1.00 11.65 C
ATOM 807 C ILE A 118 138.365 37.112 -7.207 1.00 11.47 C
ATOM 808 O ILE A 118 139.392 37.556 -6.727 1.00 12.50 O
ATOM 809 CB ILE A 118 139.034 35.558 -9.058 1.00 13.40 C
ATOM 810 CG1 ILE A 118 139.049 35.329 -10.576 1.00 13.37 C
ATOM 811 CG2 ILE A 118 138.240 34.397 -8.420 1.00 10.68 C
ATOM 812 CD1 ILE A 118 139.757 33.996 -11.002 1.00 16.92 C
ATOM 813 N TYR A 119 137.239 36.915 -6.513 1.00 11.48 N
ATOM 814 CA TYR A 119 137.134 37.025 -5.049 1.00 10.08 C
ATOM 815 C TYR A 119 136.712 35.635 -4.449 1.00 10.55 C
ATOM 816 O TYR A 119 135.822 34.952 -4.972 1.00 12.30 O
ATOM 817 CB TYR A 119 136.095 38.093 -4.645 1.00 10.67 C
ATOM 818 CG TYR A 119 136.150 38.438 -3.177 1.00 10.16 C
ATOM 819 CD1 TYR A 119 137.016 39.436 -2.704 1.00 10.32 C
ATOM 820 CD2 TYR A 119 135.386 37.741 -2.249 1.00 10.91 C
ATOM 821 CE1 TYR A 119 137.129 39.733 -1.317 1.00 13.12 C
ATOM 822 CE2 TYR A 119 135.489 38.024 -0.864 1.00 11.39 C
ATOM 823 CZ TYR A 119 136.362 39.017 -0.398 1.00 12.66 C
ATOM 824 OH TYR A 119 136.488 39.251 0.965 1.00 9.71 O
ATOM 825 N LEU A 120 137.341 35.242 -3.343 1.00 8.03 N
ATOM 826 CA LEU A 120 137.031 33.992 -2.648 1.00 10.64 C
ATOM 827 C LEU A 120 136.903 34.362 -1.162 1.00 10.02 C
ATOM 828 O LEU A 120 137.649 35.218 -0.679 1.00 10.90 O
ATOM 829 CB LEU A 120 138.198 33.041 -2.805 1.00 13.66 C
ATOM 830 CG LEU A 120 138.351 31.970 -3.879 1.00 16.92 C
ATOM 831 CD1 LEU A 120 137.585 32.237 -5.130 1.00 19.17 C
ATOM 832 CD2 LEU A 120 139.795 31.760 -4.108 1.00 14.58 C
ATOM 833 N GLY A 121 135.950 33.777 -0.440 1.00 11.07 N
ATOM 834 CA GLY A 121 135.812 34.083 0.990 1.00 9.55 C
ATOM 835 C GLY A 121 134.894 33.099 1.683 1.00 7.39 C
ATOM 836 O GLY A 121 133.918 32.701 1.080 1.00 11.47 O
ATOM 837 N GLY A 122 135.266 32.596 2.868 1.00 8.95 N
ATOM 838 CA GLY A 122 134.416 31.650 3.578 1.00 10.35 C
ATOM 839 C GLY A 122 134.859 31.421 5.013 1.00 11.54 C
ATOM 840 O GLY A 122 135.983 31.778 5.356 1.00 12.43 O
ATOM 841 N VAL A 123 134.005 30.793 5.822 1.00 7.76 N
ATOM 842 CA VAL A 123 134.295 30.527 7.248 1.00 10.38 C
ATOM 843 C VAL A 123 134.631 29.069 7.456 1.00 11.59 C
ATOM 844 O VAL A 123 133.854 28.202 7.051 1.00 13.11 O
ATOM 845 CB VAL A 123 133.101 30.924 8.138 1.00 10.65 C
ATOM 846 CG1 VAL A 123 133.312 30.485 9.603 1.00 11.84 C
ATOM 847 CG2 VAL A 123 132.925 32.412 8.072 1.00 11.48 C
ATOM 848 N PHE A 124 135.782 28.803 8.086 1.00 11.38 N
ATOM 849 CA PHE A 124 136.265 27.432 8.285 1.00 12.17 C
ATOM 850 C PHE A 124 136.835 27.118 9.658 1.00 13.82 C
ATOM 851 O PHE A 124 137.458 27.970 10.287 1.00 13.27 O
ATOM 852 CB PHE A 124 137.338 27.096 7.216 1.00 14.08 C
ATOM 853 CG PHE A 124 136.847 27.241 5.767 1.00 11.98 C
ATOM 854 CD1 PHE A 124 136.884 28.479 5.111 1.00 14.47 C
ATOM 855 CD2 PHE A 124 136.356 26.133 5.065 1.00 13.95 C
ATOM 856 CE1 PHE A 124 136.440 28.610 3.788 1.00 14.57 C
ATOM 857 CE2 PHE A 124 135.909 26.249 3.738 1.00 12.52 C
ATOM 858 CZ PHE A 124 135.950 27.486 3.105 1.00 9.95 C
ATOM 859 N GLN A 125 136.625 25.876 10.100 1.00 13.56 N
ATOM 860 CA GLN A 125 137.141 25.379 11.388 1.00 12.70 C
ATOM 861 C GLN A 125 138.526 24.827 11.114 1.00 13.91 C
ATOM 862 O GLN A 125 138.692 23.898 10.324 1.00 12.60 O
ATOM 863 CB GLN A 125 136.256 24.286 11.969 1.00 15.58 C
ATOM 864 CG GLN A 125 136.746 23.711 13.299 1.00 22.63 C
ATOM 865 CD GLN A 125 136.333 24.529 14.512 1.00 28.47 C
ATOM 866 OE1 GLN A 125 135.219 24.384 15.024 1.00 35.75 O
ATOM 867 NE2 GLN A 125 137.233 25.374 14.998 1.00 32.26 N
ATOM 868 N LEU A 126 139.512 25.483 11.721 1.00 15.10 N
ATOM 869 CA LEU A 126 140.922 25.165 11.565 1.00 18.02 C
ATOM 870 C LEU A 126 141.492 24.763 12.909 1.00 18.46 C
ATOM 871 O LEU A 126 140.898 25.068 13.933 1.00 16.37 O
ATOM 872 CB LEU A 126 141.686 26.392 11.015 1.00 17.52 C
ATOM 873 CG LEU A 126 141.195 26.964 9.685 1.00 16.72 C
ATOM 874 CD1 LEU A 126 142.183 28.035 9.229 1.00 16.79 C
ATOM 875 CD2 LEU A 126 141.123 25.853 8.667 1.00 13.83 C
ATOM 876 N GLU A 127 142.628 24.070 12.871 1.00 21.14 N
ATOM 877 CA GLU A 127 143.348 23.591 14.042 1.00 24.34 C
ATOM 878 C GLU A 127 144.648 24.364 14.073 1.00 24.58 C
ATOM 879 O GLU A 127 145.098 24.819 13.040 1.00 25.10 O
ATOM 880 CB GLU A 127 143.715 22.127 13.878 1.00 26.09 C
ATOM 881 CG GLU A 127 142.592 21.161 13.702 1.00 34.51 C
ATOM 882 CD GLU A 127 143.093 19.770 13.194 1.00 40.22 C
ATOM 883 OE1 GLU A 127 144.315 19.600 12.902 1.00 43.77 O
ATOM 884 OE2 GLU A 127 142.253 18.847 13.051 1.00 40.57 O
ATOM 885 N LYS A 128 145.273 24.491 15.240 1.00 24.50 N
ATOM 886 CA LYS A 128 146.557 25.180 15.327 1.00 25.01 C
ATOM 887 C LYS A 128 147.618 24.473 14.446 1.00 23.06 C
ATOM 888 O LYS A 128 147.774 23.244 14.483 1.00 22.50 O
ATOM 889 CB LYS A 128 147.077 25.189 16.778 1.00 27.04 C
ATOM 890 CG LYS A 128 148.592 25.483 16.859 1.00 27.48 C
ATOM 891 CD LYS A 128 149.237 24.865 18.062 1.00 34.45 C
ATOM 892 CE LYS A 128 149.595 25.928 19.106 1.00 36.05 C
ATOM 893 NZ LYS A 128 149.942 25.334 20.441 1.00 37.00 N
ATOM 894 N GLY A 129 148.407 25.260 13.725 1.00 20.68 N
ATOM 895 CA GLY A 129 149.452 24.684 12.889 1.00 22.11 C
ATOM 896 C GLY A 129 149.089 24.481 11.431 1.00 21.56 C
ATOM 897 O GLY A 129 149.985 24.284 10.588 1.00 19.83 O
ATOM 898 N ASP A 130 147.783 24.493 11.139 1.00 21.38 N
ATOM 899 CA ASP A 130 147.297 24.355 9.774 1.00 18.41 C
ATOM 900 C ASP A 130 147.944 25.445 8.947 1.00 16.89 C
ATOM 901 O ASP A 130 148.225 26.529 9.444 1.00 15.45 O
ATOM 902 CB ASP A 130 145.774 24.512 9.707 1.00 18.00 C
ATOM 903 CG ASP A 130 145.043 23.226 10.001 1.00 16.97 C
ATOM 904 OD1 ASP A 130 145.660 22.179 10.288 1.00 21.79 O
ATOM 905 OD2 ASP A 130 143.820 23.247 9.930 1.00 18.73 O
ATOM 906 N ARG A 131 148.178 25.153 7.681 1.00 16.54 N
ATOM 907 CA ARG A 131 148.779 26.110 6.774 1.00 20.89 C
ATOM 908 C ARG A 131 147.813 26.400 5.651 1.00 19.92 C
ATOM 909 O ARG A 131 147.163 25.486 5.120 1.00 20.50 O
ATOM 910 CB ARG A 131 150.039 25.544 6.162 1.00 24.49 C
ATOM 911 CG ARG A 131 151.200 25.583 7.080 1.00 34.08 C
ATOM 912 CD ARG A 131 152.229 24.599 6.657 1.00 40.41 C
ATOM 913 NE ARG A 131 153.393 24.781 7.504 1.00 50.20 N
ATOM 914 CZ ARG A 131 154.364 25.653 7.255 1.00 53.51 C
ATOM 915 NH1 ARG A 131 154.346 26.363 6.130 1.00 56.09 N
ATOM 916 NH2 ARG A 131 155.381 25.766 8.104 1.00 55.90 N
ATOM 917 N LEU A 132 147.733 27.669 5.278 1.00 18.92 N
ATOM 918 CA LEU A 132 146.855 28.106 4.198 1.00 16.11 C
ATOM 919 C LEU A 132 147.639 28.689 3.019 1.00 17.03 C
ATOM 920 O LEU A 132 148.501 29.584 3.169 1.00 15.95 O
ATOM 921 CB LEU A 132 145.843 29.143 4.714 1.00 13.19 C
ATOM 922 CG LEU A 132 144.911 28.663 5.775 1.00 9.98 C
ATOM 923 CD1 LEU A 132 144.331 29.836 6.403 1.00 13.44 C
ATOM 924 CD2 LEU A 132 143.867 27.766 5.189 1.00 15.06 C
ATOM 925 N SER A 133 147.252 28.252 1.832 1.00 15.91 N
ATOM 926 CA SER A 133 147.864 28.741 0.616 1.00 18.56 C
ATOM 927 C SER A 133 146.816 29.408 -0.323 1.00 14.84 C
ATOM 928 O SER A 133 145.706 28.909 -0.439 1.00 16.32 O
ATOM 929 CB SER A 133 148.477 27.543 -0.094 1.00 18.21 C
ATOM 930 OG SER A 133 149.563 27.955 -0.882 1.00 27.00 O
ATOM 931 N ALA A 134 147.125 30.572 -0.880 1.00 12.26 N
ATOM 932 CA ALA A 134 146.255 31.234 -1.857 1.00 12.13 C
ATOM 933 C ALA A 134 147.136 31.182 -3.098 1.00 15.17 C
ATOM 934 O ALA A 134 148.187 31.864 -3.169 1.00 14.98 O
ATOM 935 CB ALA A 134 146.005 32.627 -1.483 1.00 14.25 C
ATOM 936 N GLU A 135 146.659 30.447 -4.101 1.00 14.49 N
ATOM 937 CA GLU A 135 147.413 30.191 -5.310 1.00 14.62 C
ATOM 938 C GLU A 135 146.696 30.396 -6.614 1.00 10.52 C
ATOM 939 O GLU A 135 145.484 30.224 -6.687 1.00 10.35 O
ATOM 940 CB GLU A 135 147.829 28.737 -5.285 1.00 16.30 C
ATOM 941 CG GLU A 135 148.645 28.342 -4.086 1.00 19.37 C
ATOM 942 CD GLU A 135 148.810 26.841 -3.993 1.00 22.13 C
ATOM 943 OE1 GLU A 135 148.160 26.102 -4.753 1.00 32.17 O
ATOM 944 OE2 GLU A 135 149.578 26.366 -3.149 1.00 28.78 O
ATOM 945 N ILE A 136 147.447 30.838 -7.622 1.00 12.41 N
ATOM 946 CA ILE A 136 146.933 31.017 -8.993 1.00 11.83 C
ATOM 947 C ILE A 136 147.713 30.153 -10.016 1.00 13.72 C
ATOM 948 O ILE A 136 148.868 29.819 -9.793 1.00 12.90 O
ATOM 949 CB ILE A 136 146.970 32.492 -9.429 1.00 14.35 C
ATOM 950 CG1 ILE A 136 148.409 33.023 -9.368 1.00 15.26 C
ATOM 951 CG2 ILE A 136 146.006 33.303 -8.565 1.00 12.94 C
ATOM 952 CD1 ILE A 136 148.644 34.160 -10.201 1.00 19.85 C
ATOM 953 N ASN A 137 147.124 29.819 -11.157 1.00 10.76 N
ATOM 954 CA ASN A 137 147.871 29.031 -12.136 1.00 12.31 C
ATOM 955 C ASN A 137 148.844 29.859 -12.976 1.00 10.82 C
ATOM 956 O ASN A 137 149.952 29.409 -13.230 1.00 14.19 O
ATOM 957 CB ASN A 137 146.943 28.202 -13.050 1.00 13.50 C
ATOM 958 CG ASN A 137 145.982 29.061 -13.909 1.00 17.42 C
ATOM 959 OD1 ASN A 137 145.659 30.213 -13.564 1.00 17.90 O
ATOM 960 ND2 ASN A 137 145.503 28.474 -15.024 1.00 17.14 N
ATOM 961 N ARG A 138 148.476 31.083 -13.345 1.00 9.75 N
ATOM 962 CA ARG A 138 149.366 31.896 -14.167 1.00 11.53 C
ATOM 963 C ARG A 138 149.776 33.240 -13.532 1.00 13.51 C
ATOM 964 O ARG A 138 149.137 34.287 -13.757 1.00 13.12 O
ATOM 965 CB ARG A 138 148.723 32.117 -15.530 1.00 11.98 C
ATOM 966 CG ARG A 138 148.431 30.839 -16.363 1.00 15.10 C
ATOM 967 CD ARG A 138 149.717 30.214 -16.977 1.00 16.37 C
ATOM 968 NE ARG A 138 150.477 31.138 -17.856 1.00 20.70 N
ATOM 969 CZ ARG A 138 150.373 31.246 -19.198 1.00 17.21 C
ATOM 970 NH1 ARG A 138 149.520 30.488 -19.884 1.00 14.90 N
ATOM 971 NH2 ARG A 138 151.158 32.109 -19.859 1.00 15.65 N
ATOM 972 N PRO A 139 150.864 33.233 -12.726 1.00 15.85 N
ATOM 973 CA PRO A 139 151.341 34.450 -12.070 1.00 16.17 C
ATOM 974 C PRO A 139 151.777 35.498 -13.046 1.00 16.86 C
ATOM 975 O PRO A 139 151.943 36.658 -12.673 1.00 18.12 O
ATOM 976 CB PRO A 139 152.491 33.957 -11.202 1.00 14.86 C
ATOM 977 CG PRO A 139 152.915 32.693 -11.886 1.00 21.02 C
ATOM 978 CD PRO A 139 151.607 32.066 -12.223 1.00 14.27 C
ATOM 979 N ASP A 140 151.978 35.082 -14.293 1.00 15.58 N
ATOM 980 CA ASP A 140 152.395 36.004 -15.351 1.00 16.68 C
ATOM 981 C ASP A 140 151.242 36.844 -15.906 1.00 13.10 C
ATOM 982 O ASP A 140 151.471 37.748 -16.692 1.00 14.78 O
ATOM 983 CB ASP A 140 153.173 35.270 -16.485 1.00 16.07 C
ATOM 984 CG ASP A 140 152.413 34.080 -17.080 1.00 17.87 C
ATOM 985 OD1 ASP A 140 151.609 33.411 -16.391 1.00 15.77 O
ATOM 986 OD2 ASP A 140 152.630 33.820 -18.277 1.00 23.51 O
ATOM 987 N TYR A 141 150.021 36.571 -15.456 1.00 10.86 N
ATOM 988 CA TYR A 141 148.853 37.335 -15.883 1.00 13.66 C
ATOM 989 C TYR A 141 148.377 38.237 -14.732 1.00 14.58 C
ATOM 990 O TYR A 141 147.396 38.951 -14.879 1.00 15.33 O
ATOM 991 CB TYR A 141 147.679 36.412 -16.288 1.00 14.82 C
ATOM 992 CG TYR A 141 147.694 35.953 -17.701 1.00 12.10 C
ATOM 993 CD1 TYR A 141 148.440 34.863 -18.064 1.00 16.76 C
ATOM 994 CD2 TYR A 141 146.970 36.611 -18.671 1.00 14.69 C
ATOM 995 CE1 TYR A 141 148.473 34.413 -19.363 1.00 20.95 C
ATOM 996 CE2 TYR A 141 146.984 36.177 -19.987 1.00 20.43 C
ATOM 997 CZ TYR A 141 147.752 35.061 -20.327 1.00 23.10 C
ATOM 998 OH TYR A 141 147.816 34.568 -21.613 1.00 22.16 O
ATOM 999 N LEU A 142 149.062 38.222 -13.594 1.00 16.72 N
ATOM 1000 CA LEU A 142 148.624 39.051 -12.488 1.00 19.03 C
ATOM 1001 C LEU A 142 148.908 40.523 -12.686 1.00 23.10 C
ATOM 1002 O LEU A 142 149.821 40.924 -13.432 1.00 22.49 O
ATOM 1003 CB LEU A 142 149.267 38.614 -11.171 1.00 15.87 C
ATOM 1004 CG LEU A 142 148.660 37.477 -10.355 1.00 17.46 C
ATOM 1005 CD1 LEU A 142 149.556 37.281 -9.137 1.00 19.75 C
ATOM 1006 CD2 LEU A 142 147.210 37.784 -9.909 1.00 16.31 C
ATOM 1007 N ASP A 143 148.046 41.321 -12.060 1.00 22.61 N
ATOM 1008 CA ASP A 143 148.189 42.752 -12.054 1.00 23.51 C
ATOM 1009 C ASP A 143 148.118 43.270 -10.600 1.00 22.94 C
ATOM 1010 O ASP A 143 147.077 43.184 -9.954 1.00 22.01 O
ATOM 1011 CB ASP A 143 147.110 43.391 -12.915 1.00 23.96 C
ATOM 1012 CG ASP A 143 147.323 44.879 -13.111 1.00 27.00 C
ATOM 1013 OD1 ASP A 143 148.461 45.353 -13.008 1.00 28.49 O
ATOM 1014 OD2 ASP A 143 146.347 45.593 -13.381 1.00 30.38 O
ATOM 1015 N PHE A 144 149.249 43.682 -10.039 1.00 25.83 N
ATOM 1016 CA PHE A 144 149.265 44.264 -8.687 1.00 30.40 C
ATOM 1017 C PHE A 144 149.961 45.599 -8.840 1.00 33.28 C
ATOM 1018 O PHE A 144 150.579 46.118 -7.902 1.00 35.56 O
ATOM 1019 CB PHE A 144 149.962 43.394 -7.612 1.00 31.48 C
ATOM 1020 CG PHE A 144 151.122 42.564 -8.113 1.00 29.63 C
ATOM 1021 CD1 PHE A 144 152.310 43.152 -8.522 1.00 28.05 C
ATOM 1022 CD2 PHE A 144 151.010 41.180 -8.188 1.00 30.50 C
ATOM 1023 CE1 PHE A 144 153.356 42.374 -8.997 1.00 32.18 C
ATOM 1024 CE2 PHE A 144 152.057 40.399 -8.663 1.00 32.03 C
ATOM 1025 CZ PHE A 144 153.227 40.997 -9.066 1.00 32.31 C
ATOM 1026 N ALA A 145 149.826 46.134 -10.055 1.00 32.57 N
ATOM 1027 CA ALA A 145 150.380 47.410 -10.467 1.00 32.42 C
ATOM 1028 C ALA A 145 150.062 48.455 -9.439 1.00 35.45 C
ATOM 1029 O ALA A 145 150.689 49.519 -9.394 1.00 35.79 O
ATOM 1030 CB ALA A 145 149.771 47.832 -11.769 1.00 32.80 C
ATOM 1031 N GLU A 146 149.046 48.180 -8.636 1.00 35.09 N
ATOM 1032 CA GLU A 146 148.665 49.124 -7.613 1.00 33.95 C
ATOM 1033 C GLU A 146 147.642 48.588 -6.646 1.00 30.04 C
ATOM 1034 O GLU A 146 147.219 47.438 -6.734 1.00 28.78 O
ATOM 1035 CB GLU A 146 148.084 50.373 -8.295 1.00 34.26 C
ATOM 1036 N SER A 147 147.439 49.377 -5.606 1.00 28.85 N
ATOM 1037 CA SER A 147 146.342 49.177 -4.682 1.00 29.39 C
ATOM 1038 C SER A 147 146.059 47.929 -3.889 1.00 27.62 C
ATOM 1039 O SER A 147 146.935 47.206 -3.432 1.00 33.54 O
ATOM 1040 CB SER A 147 145.092 49.522 -5.476 1.00 29.12 C
ATOM 1041 OG SER A 147 144.054 50.040 -4.675 1.00 37.21 O
ATOM 1042 N GLY A 148 144.772 47.786 -3.637 1.00 26.24 N
ATOM 1043 CA GLY A 148 144.258 46.676 -2.911 1.00 20.01 C
ATOM 1044 C GLY A 148 143.746 45.780 -3.976 1.00 12.10 C
ATOM 1045 O GLY A 148 142.638 45.320 -3.849 1.00 11.21 O
ATOM 1046 N GLN A 149 144.549 45.532 -5.014 1.00 13.54 N
ATOM 1047 CA GLN A 149 144.171 44.633 -6.124 1.00 11.77 C
ATOM 1048 C GLN A 149 144.359 43.109 -5.883 1.00 11.26 C
ATOM 1049 O GLN A 149 143.589 42.308 -6.410 1.00 11.23 O
ATOM 1050 CB GLN A 149 144.934 45.021 -7.393 1.00 13.29 C
ATOM 1051 CG GLN A 149 144.566 46.376 -7.972 1.00 18.69 C
ATOM 1052 CD GLN A 149 145.250 46.657 -9.316 1.00 17.78 C
ATOM 1053 OE1 GLN A 149 144.912 47.622 -10.016 1.00 21.20 O
ATOM 1054 NE2 GLN A 149 146.191 45.798 -9.692 1.00 19.36 N
ATOM 1055 N VAL A 150 145.392 42.720 -5.121 1.00 12.06 N
ATOM 1056 CA VAL A 150 145.710 41.314 -4.824 1.00 10.98 C
ATOM 1057 C VAL A 150 145.957 41.267 -3.326 1.00 11.31 C
ATOM 1058 O VAL A 150 146.863 41.947 -2.854 1.00 10.87 O
ATOM 1059 CB VAL A 150 147.024 40.862 -5.575 1.00 8.44 C
ATOM 1060 CG1 VAL A 150 147.249 39.380 -5.414 1.00 7.85 C
ATOM 1061 CG2 VAL A 150 146.910 41.187 -7.092 1.00 10.42 C
ATOM 1062 N TYR A 151 145.188 40.443 -2.608 1.00 10.87 N
ATOM 1063 CA TYR A 151 145.286 40.296 -1.156 1.00 7.76 C
ATOM 1064 C TYR A 151 144.745 38.957 -0.686 1.00 6.81 C
ATOM 1065 O TYR A 151 143.959 38.301 -1.369 1.00 9.17 O
ATOM 1066 CB TYR A 151 144.553 41.428 -0.417 1.00 8.04 C
ATOM 1067 CG TYR A 151 143.124 41.671 -0.878 1.00 10.04 C
ATOM 1068 CD1 TYR A 151 142.086 40.891 -0.405 1.00 7.86 C
ATOM 1069 CD2 TYR A 151 142.808 42.701 -1.796 1.00 12.17 C
ATOM 1070 CE1 TYR A 151 140.796 41.123 -0.812 1.00 9.92 C
ATOM 1071 CE2 TYR A 151 141.491 42.938 -2.221 1.00 9.29 C
ATOM 1072 CZ TYR A 151 140.494 42.144 -1.718 1.00 8.74 C
ATOM 1073 OH TYR A 151 139.173 42.363 -2.079 1.00 10.19 O
ATOM 1074 N PHE A 152 145.192 38.571 0.498 1.00 8.63 N
ATOM 1075 CA PHE A 152 144.838 37.309 1.148 1.00 7.60 C
ATOM 1076 C PHE A 152 144.780 37.626 2.659 1.00 7.28 C
ATOM 1077 O PHE A 152 145.731 38.199 3.218 1.00 6.24 O
ATOM 1078 CB PHE A 152 145.958 36.313 0.775 1.00 7.78 C
ATOM 1079 CG PHE A 152 145.894 34.920 1.417 1.00 12.16 C
ATOM 1080 CD1 PHE A 152 144.683 34.285 1.800 1.00 12.65 C
ATOM 1081 CD2 PHE A 152 147.102 34.200 1.557 1.00 11.05 C
ATOM 1082 CE1 PHE A 152 144.685 32.931 2.319 1.00 11.97 C
ATOM 1083 CE2 PHE A 152 147.114 32.870 2.062 1.00 11.38 C
ATOM 1084 CZ PHE A 152 145.905 32.232 2.444 1.00 9.60 C
ATOM 1085 N GLY A 153 143.667 37.324 3.310 1.00 9.92 N
ATOM 1086 CA GLY A 153 143.585 37.569 4.747 1.00 11.12 C
ATOM 1087 C GLY A 153 142.841 36.501 5.519 1.00 10.83 C
ATOM 1088 O GLY A 153 142.167 35.655 4.950 1.00 12.36 O
ATOM 1089 N ILE A 154 142.986 36.523 6.838 1.00 13.35 N
ATOM 1090 CA ILE A 154 142.265 35.600 7.725 1.00 13.98 C
ATOM 1091 C ILE A 154 142.077 36.328 9.036 1.00 12.09 C
ATOM 1092 O ILE A 154 142.904 37.162 9.396 1.00 14.29 O
ATOM 1093 CB ILE A 154 142.987 34.219 8.090 1.00 16.58 C
ATOM 1094 CG1 ILE A 154 144.222 34.423 8.963 1.00 14.91 C
ATOM 1095 CG2 ILE A 154 143.340 33.376 6.845 1.00 20.27 C
ATOM 1096 CD1 ILE A 154 144.680 33.112 9.614 1.00 21.92 C
ATOM 1097 N ILE A 155 140.993 36.032 9.728 1.00 12.24 N
ATOM 1098 CA ILE A 155 140.701 36.628 11.031 1.00 11.73 C
ATOM 1099 C ILE A 155 139.934 35.578 11.866 1.00 11.73 C
ATOM 1100 O ILE A 155 138.996 34.912 11.359 1.00 9.05 O
ATOM 1101 CB ILE A 155 139.934 37.999 10.911 1.00 11.44 C
ATOM 1102 CG1 ILE A 155 139.553 38.515 12.300 1.00 14.11 C
ATOM 1103 CG2 ILE A 155 138.708 37.888 10.030 1.00 14.33 C
ATOM 1104 CD1 ILE A 155 140.080 39.930 12.603 1.00 18.47 C
ATOM 1105 N ALA A 156 140.400 35.341 13.094 1.00 12.07 N
ATOM 1106 CA ALA A 156 139.724 34.378 13.960 1.00 14.71 C
ATOM 1107 C ALA A 156 138.398 34.995 14.392 1.00 17.52 C
ATOM 1108 O ALA A 156 138.340 36.180 14.727 1.00 17.55 O
ATOM 1109 CB ALA A 156 140.570 34.035 15.142 1.00 13.77 C
ATOM 1110 N LEU A 157 137.334 34.202 14.295 1.00 21.24 N
ATOM 1111 CA LEU A 157 135.967 34.622 14.639 1.00 27.30 C
ATOM 1112 C LEU A 157 135.522 34.202 16.044 1.00 29.11 C
ATOM 1113 CB LEU A 157 134.955 34.050 13.633 1.00 30.48 C
ATOM 1114 CG LEU A 157 135.004 34.466 12.159 1.00 32.78 C
ATOM 1115 CD1 LEU A 157 133.788 33.891 11.444 1.00 31.95 C
ATOM 1116 CD2 LEU A 157 134.976 35.991 12.040 1.00 35.27 C
ATOM 1117 OXT LEU A 157 134.446 34.662 16.457 1.00 31.94 O
TER 1118 LEU A 157
HETATM 1119 O HOH 201 137.069 41.771 -6.850 1.00 17.83 O
HETATM 1120 O HOH 202 134.516 36.472 -8.339 1.00 19.46 O
HETATM 1121 O HOH 204 145.132 25.531 -11.730 1.00 32.55 O
HETATM 1122 O HOH 205 144.666 28.030 -8.681 1.00 16.62 O
HETATM 1123 O HOH 206 145.999 26.779 -3.125 1.00 21.29 O
HETATM 1124 O HOH 207 149.919 31.401 -0.735 1.00 15.23 O
HETATM 1125 O HOH 208 155.666 26.973 -0.378 1.00 46.78 O
HETATM 1126 O HOH 209 151.921 28.765 -1.919 1.00 28.44 O
HETATM 1127 O HOH 210 150.433 31.196 -6.749 1.00 16.68 O
HETATM 1128 O HOH 211 147.899 47.948 9.515 1.00 17.19 O
HETATM 1129 O HOH 212 145.211 47.227 8.546 1.00 15.96 O
HETATM 1130 O HOH 213 144.706 45.193 6.669 1.00 9.40 O
HETATM 1131 O HOH 214 144.507 50.081 7.882 1.00 18.16 O
HETATM 1132 O HOH 215 146.202 51.682 10.249 1.00 25.94 O
HETATM 1133 O HOH 216 147.659 45.005 -5.373 1.00 22.32 O
HETATM 1134 O HOH 217 145.917 44.434 -2.185 1.00 27.40 O
HETATM 1135 O HOH 218 144.751 45.522 0.359 1.00 14.64 O
HETATM 1136 O HOH 219 146.331 47.118 1.782 1.00 28.76 O
HETATM 1137 O HOH 220 154.188 31.414 -15.920 1.00 32.81 O
HETATM 1138 O HOH 221 155.223 31.090 -9.958 1.00 25.08 O
HETATM 1139 O HOH 222 160.131 36.058 -8.682 1.00 33.75 O
HETATM 1140 O HOH 223 156.028 35.122 1.212 1.00 23.18 O
HETATM 1141 O HOH 224 156.810 33.593 3.329 1.00 17.90 O
HETATM 1142 O HOH 225 131.548 26.688 18.681 1.00 51.58 O
HETATM 1143 O HOH 226 139.719 21.261 14.235 1.00 33.22 O
HETATM 1144 O HOH 227 138.199 31.513 16.287 1.00 28.45 O
HETATM 1145 O HOH 228 151.999 42.522 -19.516 1.00 39.47 O
HETATM 1146 O HOH 229 155.593 35.680 9.917 1.00 21.41 O
HETATM 1147 O HOH 230 154.129 39.073 12.894 1.00 29.64 O
HETATM 1148 O HOH 231 154.582 36.121 12.756 1.00 32.19 O
HETATM 1149 O HOH 232 154.114 38.814 -17.897 1.00 26.17 O
HETATM 1150 O HOH 233 153.958 38.932 -6.122 1.00 17.76 O
HETATM 1151 O HOH 234 151.457 46.828 -5.607 1.00 35.17 O
HETATM 1152 O HOH 235 151.071 50.634 9.434 1.00 30.11 O
HETATM 1153 O HOH 236 152.883 23.313 10.011 1.00 34.98 O
HETATM 1154 O HOH 237 139.672 31.590 -22.014 1.00 39.91 O
HETATM 1155 O HOH 238 148.208 50.498 8.586 1.00 35.43 O
HETATM 1156 O HOH 239 136.993 21.320 1.081 1.00 63.99 O
HETATM 1157 O HOH 240 135.861 38.266 -31.914 1.00 34.44 O
HETATM 1158 O HOH 241 144.105 22.014 17.148 1.00 33.48 O
HETATM 1159 O HOH 242 158.385 48.495 5.435 1.00 23.41 O
HETATM 1160 O HOH 243 158.241 40.897 2.047 1.00 40.82 O
HETATM 1161 O HOH 244 167.036 38.524 8.384 1.00 87.86 O
HETATM 1162 O HOH 245 145.907 38.427 -23.488 1.00 51.70 O
HETATM 1163 O HOH 246 151.903 43.747 -12.234 1.00 27.51 O
HETATM 1164 O HOH 247 152.055 53.152 -7.506 1.00 45.10 O
HETATM 1165 O HOH 248 165.628 39.438 6.445 1.00 31.65 O
HETATM 1166 O HOH 249 158.710 34.770 -6.387 1.00 30.31 O
HETATM 1167 O HOH 250 162.568 40.773 -7.961 1.00 75.22 O
HETATM 1168 O HOH 251 163.288 45.013 -7.285 1.00 48.22 O
HETATM 1169 O HOH 252 153.343 30.821 -32.435 1.00 31.89 O
HETATM 1170 O HOH 253 151.032 34.651 -28.310 1.00 50.45 O
HETATM 1171 O HOH 254 153.664 38.706 -24.238 1.00 65.31 O
HETATM 1172 O HOH 255 153.665 38.774 -13.000 1.00 35.47 O
HETATM 1173 O HOH 256 159.158 44.270 -11.773 1.00 66.65 O
HETATM 1174 O HOH 257 149.572 22.243 8.230 1.00 25.62 O
HETATM 1175 O HOH 258 151.608 53.171 8.943 1.00 41.70 O
HETATM 1176 O HOH 259 146.325 28.874 -25.979 1.00 43.62 O
HETATM 1177 O HOH 260 141.897 33.449 -22.872 1.00 60.15 O
HETATM 1178 O HOH 261 142.901 33.610 -33.680 1.00 32.13 O
HETATM 1179 O HOH 262 142.993 26.074 -27.292 1.00 56.58 O
HETATM 1180 O HOH 263 149.097 13.806 -1.263 1.00 37.20 O
HETATM 1181 O HOH 264 143.952 19.577 4.867 1.00 34.68 O
HETATM 1182 O HOH 265 146.180 25.248 -6.294 1.00 44.91 O
HETATM 1183 O HOH 266 148.111 50.620 -3.136 1.00 55.61 O
HETATM 1184 O HOH 267 144.093 13.465 10.360 1.00 64.38 O
HETATM 1185 O HOH 268 141.577 14.676 13.168 1.00 54.76 O
HETATM 1186 O HOH 269 137.019 17.606 19.854 1.00 33.36 O
HETATM 1187 O HOH 270 149.639 55.203 4.611 1.00 49.01 O
HETATM 1188 O HOH 271 156.238 32.191 -4.204 1.00 64.53 O
CONECT 453 685
CONECT 685 453
MASTER 357 0 0 1 10 0 0 6 1187 1 2 12
END
PyCogent-1.5.3/doc/data/abglobin_aa.phylip 000644 000765 000024 00000003215 10665667404 021402 0 ustar 00jrideout staff 000000 000000 5 285 I
human
goat-cow
rabbit
rat
marsupial
VLSPADKTNV KAAWGKVGAH AGEYGAEALE RMFLSFPTTK TYFPHFDLSH GSAQVKGHGK
VLSAADKSNV KAAWGKVGGN AGAYGAEALE RMFLSFPTTK TYFPHFDLSH GSAQVKGHGE
VLSPADKTNI KTAWEKIGSH GGEYGAEAVE RMFLGFPTTK TYFPHFDFTH GSEQIKAHGK
VLSADDKTNI KNCWGKIGGH GGEYGEEALQ RMFAAFPTTK TYFSHIDVSP GSAQVKAHGK
VLSDADKTHV KAIWGKVGGH AGAYAAEALA RTFLSFPTTK TYFPHFDLSP GSAQIQGHGK
KVADALTNAV AHVDDMPNAL SALSDLHAHK LRVDPVNFKL LSHCLLVTLA AHLPAEFTPA
KVAAALTKAV GHLDDLPGTL SDLSDLHAHK LRVDPVNFKL LSHSLLVTLA CHLPNDFTPA
KVSEALTKAV GHLDDLPGAL STLSDLHAHK LRVDPVNFKL LSHCLLVTLA NHHPSEFTPA
KVADALAKAA DHVEDLPGAL STLSDLHAHK LRVDPVNFKF LSHCLLVTLA CHHPGDFTPA
KVADALSQAV AHLDDLPGTM SKLSDLHAHK LRVDPVNFKL LSHCLIVTLA AHLSKDLTPE
VHASLDKFLA SVSTVLTSKY RLTPEEKSAV TALWGKVNVD EVGGEALGRL LVVYPWTQRF
VHASLDKFLA NVSTVLTSKY RLTAEEKAAV TAFWGKVKVD EVGGEALGRL LVVYPWTQRF
VHASLDKFLA NVSTVLTSKY RLSSEEKSAV TALWGKVNVE EVGGEALGRL LVVYPWTQRF
MHASLDKFLA SVSTVLTSKY RLTDAEKAAV NALWGKVNPD DVGGEALGRL LVVYPWTQRY
VHASMDKFFA SVATVLTSKY RLTSEEKNCI TTIWSKVQVD QTGGEALGRM LVVYPWTTRF
FESFGDLSTP DAVMGNPKVK AHGKKVLGAF SDGLAHLDNL KGTFATLSEL HCDKLHVDPE
FESFGDLSTA DAVMNNPKVK AHGKKVLDSF SNGMKHLDDL KGTFAALSEL HCDKLHVDPE
FESFGDLSSA NAVMNNPKVK AHGKKVLAAF SEGLSHLDNL KGTFAKLSEL HCDKLHVDPE
FDSFGDLSSA SAIMGNPKVK AHGKKVINAF NDGLKHLDNL KGTFAHLSEL HCDKLHVDPE
FGSFGDLSSP GAVMSNSKVQ AHGAKVLTSF GEAVKHLDNL KGTYAKLSEL HCDKLHVDPE
NFRLLGNVLV CVLAHHFGKE FTPPVQAAYQ KVVAGVANAL AHKYH
NFKLLGNVLV VVLARNFGKE FTPVLQADFQ KVVAGVANAL AHRYH
NFRLLGNVLV IVLSHHFGKE FTPQVQAAYQ KVVAGVANAL AHKYH
NFRLLGNMIV IVLGHHLGKE FTPCAQAAFQ KVVAGVASAL AHKYH
NFKMLGNIIV ICLAEHFGKD FTPECQVAWQ KLVAGVAHAL AHKYH
PyCogent-1.5.3/doc/data/count_seqs.py 000644 000765 000024 00000004321 11612102756 020454 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
from __future__ import division
__author__ = "Greg Caporaso"
__copyright__ = "Copyright 2011, The PyCogent project"
__credits__ = ["Greg Caporaso"]
__license__ = "GPL"
__version__ = "1.6.0dev"
__maintainer__ = "Greg Caporaso"
__email__ = "gregcaporaso@gmail.com"
__status__ = "Development"
from glob import glob
from cogent.util.option_parsing import (
parse_command_line_parameters,
make_option)
from cogent.parse.fasta import MinimalFastaParser
script_info = {}
script_info['brief_description'] = "Count sequences in one or more fasta files."
script_info['script_description'] = "This script counts the number of sequences in one or more fasta files and prints the results to stdout."
script_info['script_usage'] = [\
("Count sequences in one file",
"Count the sequences in a fasta file and write results to stdout.",
"%prog -i in.fasta"),
("Count sequences in two file",
"Count the sequences in two fasta files and write results to stdout.",
"%prog -i in1.fasta,in2.fasta"),
("Count the sequences in many fasta files",
"Count the sequences all .fasta files in current directory and write results to stdout. Note that -i option must be quoted.",
"%prog -i \"*.fasta\"")]
script_info['output_description']= "Tabular data is written to stdout."
script_info['required_options'] = [
make_option('-i','--input_fps',
help='the input filepaths (comma-separated)'),
]
script_info['optional_options'] = [
make_option('--suppress_errors',action='store_true',\
help='Suppress warnings about missing files [default: %default]',
default=False)
]
script_info['version'] = __version__
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
suppress_errors = opts.suppress_errors
input_fps = []
for input_fp in opts.input_fps.split(','):
input_fps.extend(glob(input_fp))
for input_fp in input_fps:
i = 0
try:
input_f = open(input_fp,'U')
except IOError,e:
if suppress_errors:
continue
else:
print input_fp, e
for s in MinimalFastaParser(input_f):
i += 1
print input_fp, i
if __name__ == "__main__":
main() PyCogent-1.5.3/doc/data/Crump_et_al_example_env_file.txt 000644 000765 000024 00000005325 11444723227 024306 0 ustar 00jrideout staff 000000 000000 AF141399 R_FL 1
AF141411 R_FL 1
AF141408 R_FL 2
AF141403 R_FL 1
AF141410 R_FL 1
AF141398 R_FL 2
AF141391 R_FL 1
AF141389 R_FL 1
AF141395 R_FL 1
AF141401 R_FL 1
AF141390 R_FL 1
AF141393 R_FL 1
AF141396 R_FL 1
AF141402 R_FL 1
AF141407 R_FL 1
AF141387 R_FL 1
AF141394 R_FL 2
AF141409 R_FL 1
AF141400 R_FL 1
AF141397 R_FL 1
AF141405 R_FL 1
AF141388 R_FL 1
AF141424 R_PA 1
AF141421 R_PA 1
AF141433 R_PA 1
AF141428 R_PA 1
AF141432 R_PA 1
AF141426 R_PA 1
AF141430 R_PA 1
AF141413 R_PA 1
AF141419 R_PA 1
AF141423 R_PA 2
AF141429 R_PA 2
AF141422 R_PA 1
AF141431 R_PA 1
AF141415 R_PA 1
AF141418 R_PA 1
AF141416 R_PA 1
AF141420 R_PA 1
AF141417 R_PA 1
AF141434 R_PA 1
AF141412 R_PA 1
AF141414 R_PA 1
AF141463 E_FL 1
AF141493 E_FL 14
AF141459 E_FL 1
AF141461 E_FL 1
AF141447 E_FL 1
AF141479 E_FL 1
AF141449 E_FL 1
AF141465 E_FL 2
AF141435 E_FL 1
AF141457 E_FL 3
AF141468 E_FL 1
AF141487 E_FL 1
AF141472 E_FL 1
AF141466 E_FL 1
AF141444 E_FL 4
AF141473 E_FL 3
AF141439 E_FL 1
AF141436 E_FL 1
AF141455 E_FL 1
AF141443 E_FL 3
AF141483 E_FL 1
AF141476 E_FL 1
AF141441 E_FL 1
AF141440 E_FL 2
AF141474 E_FL 1
AF141486 E_FL 1
AF141481 E_FL 1
AF141480 E_FL 1
AF141470 E_FL 1
AF141458 E_FL 1
AF141460 E_FL 1
AF141478 E_FL 1
AF141450 E_FL 1
AF141471 E_FL 2
AF141442 E_FL 1
AF141454 E_FL 1
AF141488 E_FL 1
AF141451 E_FL 1
AF141456 E_FL 1
AF141452 E_FL 1
AF141482 E_FL 1
AF141448 E_FL 1
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AF141475 E_FL 1
AF141548 E_PA 4
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AF141523 E_PA 1
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AF141524 E_PA 1
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AF141543 E_PA 1
AF141503 E_PA 11
AF141498 E_PA 1
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AF141525 E_PA 1
AF141534 E_PA 1
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AF141519 E_PA 1
AF141550 E_PA 1
AF141496 E_PA 1
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AF141512 E_PA 1
AF141514 E_PA 1
AF141537 E_PA 1
AF141533 E_PA 2
AF141511 E_PA 1
AF141539 E_PA 1
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AF141505 E_PA 1
AF141497 E_PA 1
AF141541 E_PA 1
AF141518 E_PA 1
AF141551 E_PA 1
AF141504 E_PA 1
AF141546 E_PA 1
AF141515 E_PA 1
AF141529 E_PA 1
AF141507 E_PA 1
AF141540 E_PA 1
AF141521 E_PA 1
AF141538 E_PA 1
AF141522 E_PA 1
AF141509 E_PA 1
AF141517 E_PA 1
AF141536 E_PA 1
AF141557 O_UN 1
AF141569 O_UN 2
AF141561 O_UN 4
AF141578 O_UN 2
AF141567 O_UN 1
AF141566 O_UN 1
AF141568 O_UN 2
AF141579 O_UN 6
AF141562 O_UN 1
AF141559 O_UN 1
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AF141583 O_FL 2
AF141595 O_FL 1
AF141599 O_FL 2
AF141582 O_FL 2
AF141600 O_FL 1
AF141594 O_FL 2
AF141592 O_FL 1
AF141597 O_FL 1
AF141590 O_FL 3
AF141581 O_FL 1
AF141587 O_FL 1
AF141588 O_FL 1
AF141586 O_FL 1
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AF141589 O_FL 1
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PyCogent-1.5.3/doc/data/Crump_example_tree_newick.txt 000644 000765 000024 00000062330 11444723227 023651 0 ustar 00jrideout staff 000000 000000 (
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AF141410:0.06022
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(
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AF141439:0.03364
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(
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AF141528:0.00000
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AF141498:0.12862
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AF141464:0.00485,
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AF141453:0.00513
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AF141443:0.01027
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(
(
AF141465:0.00513,
AF141491:0.00256
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AF141405:0.00256
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AF141431:0.03263
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AF141456:0.01328
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AF141462:0.01064,
AF141414:0.00513
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AF141457:0.00000
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AF141413:0.00383
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AF141459:0.08285
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AF141392:0.00256
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AF141394:0.00000
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AF141388:0.05424
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AF141581:0.00998
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AF141444:0.00000,
AF141446:0.00000
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AF141478:0.02523
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AF141595:0.05097
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AF141458:0.00256
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AF141469:0.03147
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AF141538:0.10137
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AF141449:0.06970
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AF141600:0.07983,
AF141482:0.04023
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AF141486:0.00000,
AF141403:0.00256
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AF141551:0.02426,
AF141507:0.04615
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AF141517:0.09902
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(
(
AF141532:0.01292,
AF141542:0.00257
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AF141424:0.00262
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(
(
AF141557:0.00513,
AF141480:0.00256
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AF141529:0.01265,
AF141434:0.03671
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(
AF141526:0.00256,
AF141495:0.00000
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AF141556:0.00513
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AF141548:0.00514
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(
AF141421:0.04514,
AF141432:0.01539
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(
AF141544:0.00000,
AF141545:0.00000
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AF141450:0.02767
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AF141396:0.07575
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(
AF141530:0.00000,
AF141531:0.00000
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AF141448:0.04585
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):0.04010,
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(
AF141598:0.00323,
AF141479:0.00836
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AF141593:0.01564
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AF141588:0.01033
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AF141583:0.00257
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AF141539:0.00000
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AF141601:0.00162,
AF141580:0.00769
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(
AF141582:0.00000,
AF141585:0.00000
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AF141590:0.02328
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AF141395:0.04863
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(
AF141447:0.05616,
(
AF141594:0.00256,
AF141584:0.00000
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AF141567:0.22932
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AF141589:0.05577
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AF141435:0.09271
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(
AF141472:0.16321,
(
AF141537:0.01302,
AF141496:0.00838
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AF141454:0.14646
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AF141504:0.15471
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AF141505:0.13406
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AF141560:0.18908
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AF141518:0.07560
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AF141474:0.07724
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AF141452:0.04379
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AF141466:0.06719
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AF141407:0.14560
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AF141488:0.10821
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AF141397:0.07576
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AF141436:0.01862,
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AF141460:0.00797
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AF141418:0.03264
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AF141514:0.25839
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AF141562:0.03493
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AF141399:0.00528,
AF141417:0.00262
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(
AF141391:0.02575,
(
AF141508:0.16401,
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(
(
AF141475:0.07537,
AF141487:0.02921
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AF141513:0.08164
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AF141541:0.05472
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(
AF141455:0.00512,
AF141387:0.00256
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(
AF141408:0.00767,
AF141406:0.00257
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AF141536:0.11511
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AF141463:0.01550,
AF141476:0.01081
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(
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AF141426:0.01026
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(
AF141402:0.01525,
(
AF141484:0.00418,
AF141445:0.00257
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AF141587:0.00170
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(
AF141442:0.00674,
AF141389:0.00000
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AF141411:0.06787
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AF141467:0.01136
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(
AF141400:0.00767,
AF141481:0.00000
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(
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AF141433:0.00256
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AF141520:0.00256
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AF141597:0.00256
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AF141591:0.00256
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AF141564:0.00513
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AF141578:0.01026
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(
AF141523:0.01285,
AF141425:0.00258
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AF141429:0.00260
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AF141470:0.10407
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AF141533:0.04316
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AF141570:0.00000
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AF141576:0.00000
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AF141506:0.00743
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AF141573:0.00743
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AF141566:0.02577
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AF141512:0.08318
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AF141511:0.19093
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AF141540:0.22389
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(
AF141509:0.23520,
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AF141483:0.15819
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(
AF141415:0.00647,
AF141535:0.00260
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PyCogent-1.5.3/doc/data/dayhoff.dat 000644 000765 000024 00000003177 10665667404 020056 0 ustar 00jrideout staff 000000 000000
27
98 32
120 0 905
36 23 0 0
89 246 103 134 0
198 1 148 1153 0 716
240 9 139 125 11 28 81
23 240 535 86 28 606 43 10
65 64 77 24 44 18 61 0 7
41 15 34 0 0 73 11 7 44 257
26 464 318 71 0 153 83 27 26 46 18
72 90 1 0 0 114 30 17 0 336 527 243
18 14 14 0 0 0 0 15 48 196 157 0 92
250 103 42 13 19 153 51 34 94 12 32 33 17 11
409 154 495 95 161 56 79 234 35 24 17 96 62 46 245
371 26 229 66 16 53 34 30 22 192 33 136 104 13 78 550
0 201 23 0 0 0 0 0 27 0 46 0 0 76 0 75 0
24 8 95 0 96 0 22 0 127 37 28 13 0 698 0 34 42 61
208 24 15 18 49 35 37 54 44 889 175 10 258 12 48 30 157 0 28
0.087127 0.040904 0.040432 0.046872 0.033474 0.038255 0.049530
0.088612 0.033618 0.036886 0.085357 0.080482 0.014753 0.039772
0.050680 0.069577 0.058542 0.010494 0.029916 0.064718
Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val
S_ij = S_ji and PI_i for the Dayhoff model, with the rate Q_ij=S_ij*PI_j
The rest of the file is not used.
Prepared by Z. Yang, March 1995.
From the PAML distribution.
PyCogent-1.5.3/doc/data/dists_for_phylo.pickle 000644 000765 000024 00000011674 10665667404 022345 0 ustar 00jrideout staff 000000 000000 (dp1
(S'SpermWhale'
p2
S'Jackrabbit'
p3
tp4
F0.23558133673269555
s(S'LeafNose'
p5
S'TreeShrew'
p6
tp7
F0.22278929978754272
s(g5
S'Hedgehog'
p8
tp9
F0.25237868673223468
s(g3
S'Anteater'
p10
tp11
F0.23657337673373716
s(g6
S'Gorilla'
p12
tp13
F0.18676231969492157
s(S'FreeTaile'
p14
S'Llama'
p15
tp16
F0.16003181770424132
s(g14
S'Pangolin'
p17
tp18
F0.1603579293663818
s(S'Rat'
p19
S'LesserEle'
p20
tp21
F0.42828304384234206
s(g15
g6
tp22
F0.20581286739688848
s(g8
S'Wombat'
p23
tp24
F0.61998461379703196
s(g12
g3
tp25
F0.21764010128591116
s(g12
S'AfricanEl'
p26
tp27
F0.17413706816807067
s(g26
S'GoldenMol'
p28
tp29
F0.16381078019769496
s(g12
g28
tp30
F0.21665860241388582
s(g5
S'Mole'
p31
tp32
F0.20376495738316491
s(g6
g20
tp33
F0.2804198266016712
s(g15
g23
tp34
F0.56706563327409432
s(g17
g10
tp35
F0.18634249480113463
s(g14
g28
tp36
F0.23896070726886304
s(g2
g26
tp37
F0.19175198045399872
s(g2
g8
tp38
F0.24161185834356419
s(g15
S'Sloth'
p39
tp40
F0.16754632039974526
s(g3
g28
tp41
F0.28529535427776653
s(g17
g23
tp42
F0.55554889797566909
s(g19
g23
tp43
F0.68514773363006787
s(g14
g8
tp44
F0.24840744685320804
s(g5
g20
tp45
F0.26814374655962026
s(g2
g31
tp46
F0.20381415104564346
s(g2
g19
tp47
F0.36507283188667267
s(g19
g26
tp48
F0.36098887414715852
s(g2
g10
tp49
F0.18660004132482483
s(g5
g12
tp50
F0.17706328308590918
s(g2
g6
tp51
F0.21142599693080405
s(g6
g26
tp52
F0.21295142747772908
s(g6
g3
tp53
F0.24464518837038263
s(g15
g26
tp54
F0.17670838821812171
s(g39
g20
tp55
F0.24408791205710079
s(g14
g2
tp56
F0.15881905159696566
s(g5
g19
tp57
F0.35294087691991094
s(g12
g39
tp58
F0.1684966665016325
s(g8
g26
tp59
F0.25963862266271504
s(g15
g19
tp60
F0.35372121548659219
s(g31
g26
tp61
F0.22043254465350556
s(g3
g20
tp62
F0.31724601399917407
s(g12
g19
tp63
F0.31928646619856205
s(g14
g19
tp64
F0.35853994863389005
s(g19
g10
tp65
F0.36076410676098597
s(g5
g2
tp66
F0.1552418100705735
s(g8
g12
tp67
F0.25351166585922669
s(g15
g2
tp68
F0.11541046335984746
s(g14
g39
tp69
F0.17429921193670331
s(g6
g10
tp70
F0.21793050355674712
s(g6
g23
tp71
F0.54524246572012069
s(g5
g15
tp72
F0.15371168872395888
s(g17
g26
tp73
F0.18307091636646436
s(g10
g23
tp74
F0.54283966576227993
s(g6
g39
tp75
F0.20347481450512622
s(g39
g28
tp76
F0.19626573589070589
s(g31
g10
tp77
F0.22934425261435534
s(g5
g39
tp78
F0.17481118696254297
s(g10
g20
tp79
F0.26273051893624683
s(g8
g39
tp80
F0.25507622514211981
s(g14
g12
tp81
F0.17645529962671383
s(g28
g23
tp82
F0.57958513433104586
s(g6
g28
tp83
F0.2523275028705062
s(g2
g28
tp84
F0.23379205703803776
s(g26
g20
tp85
F0.202434309645733
s(g14
g26
tp86
F0.19290342630687046
s(g14
g5
tp87
F0.13259776625919503
s(g39
g23
tp88
F0.52862866877459347
s(g8
g6
tp89
F0.28306453011242577
s(g31
g39
tp90
F0.21055499043334253
s(g17
g19
tp91
F0.34953396164153971
s(g5
g17
tp92
F0.15611423240637898
s(g20
g23
tp93
F0.57341059979350384
s(g15
g3
tp94
F0.23579080572698605
s(g14
g31
tp95
F0.2035375708124624
s(g10
g26
tp96
F0.17198063443413589
s(g31
g8
tp97
F0.2514186346183323
s(g2
g12
tp98
F0.17427958001912375
s(g12
g23
tp99
F0.54897931148601919
s(g31
g3
tp100
F0.26305710513226543
s(g31
g23
tp101
F0.58419001011914529
s(g17
g2
tp102
F0.15061801593919677
s(g31
g6
tp103
F0.23157223340912828
s(g31
g12
tp104
F0.20030071593079626
s(g5
g28
tp105
F0.2356211665616679
s(g31
g20
tp106
F0.30047877128702466
s(g2
g23
tp107
F0.58717050903439605
s(g14
g3
tp108
F0.23535606447601404
s(g15
g28
tp109
F0.22391018143489855
s(g3
g23
tp110
F0.60050563531851719
s(g19
g28
tp111
F0.38781922994069989
s(g17
g31
tp112
F0.19663617963790703
s(g14
g20
tp113
F0.27697713155467224
s(g17
g28
tp114
F0.22139844503006362
s(g15
g8
tp115
F0.22963441872671392
s(g2
g39
tp116
F0.17537168206526232
s(g8
g19
tp117
F0.44528498187553256
s(g39
g26
tp118
F0.15707714792985861
s(g8
g10
tp119
F0.262069531052805
s(g15
g20
tp120
F0.26186754674282603
s(g15
g31
tp121
F0.19500762515085551
s(g5
g23
tp122
F0.56372551302180518
s(g5
g10
tp123
F0.18431861844687059
s(g31
g28
tp124
F0.26123994830524716
s(g12
g20
tp125
F0.2556467459575969
s(g15
g10
tp126
F0.18649954620741344
s(g15
g12
tp127
F0.16892629241793777
s(g10
g39
tp128
F0.10430995903020382
s(g14
g23
tp129
F0.5724514681894517
s(g12
g10
tp130
F0.17953067369611775
s(g17
g20
tp131
F0.26576072655285454
s(g17
g12
tp132
F0.17154547111760352
s(g28
g20
tp133
F0.23784467508495774
s(g17
g6
tp134
F0.20514478285357235
s(g14
g6
tp135
F0.21926904153263413
s(g17
g3
tp136
F0.22895223603506784
s(g6
g19
tp137
F0.3643788194875382
s(g8
g28
tp138
F0.30424919454836291
s(g14
g10
tp139
F0.19114094081112373
s(g17
g8
tp140
F0.23876822737703321
s(g26
g23
tp141
F0.5387491498191419
s(g5
g26
tp142
F0.18819818650279263
s(g3
g26
tp143
F0.23469538913725793
s(g3
g39
tp144
F0.22055976180843367
s(g19
g39
tp145
F0.34696523857967398
s(g31
g19
tp146
F0.39839525397146391
s(g8
g20
tp147
F0.34529762840916212
s(g17
g39
tp148
F0.17675542635071309
s(g17
g15
tp149
F0.15559649688143493
s(g2
g20
tp150
F0.26909857983936736
s(g10
g28
tp151
F0.20422976142040555
s(g8
g3
tp152
F0.30157557875560231
s(g3
g19
tp153
F0.3759948154971699
s(g5
g3
tp154
F0.22443287357052219
s. PyCogent-1.5.3/doc/data/fastq.txt 000755 000765 000024 00000000000 12024703640 024144 2../../tests/data/fastq.txt ustar 00jrideout staff 000000 000000 PyCogent-1.5.3/doc/data/inseqs.fasta 000644 000765 000024 00000000052 11350301455 020232 0 ustar 00jrideout staff 000000 000000 >s2_like_seq
TGCAGCTTGAGCACAGGTTAGAGCCTTC
PyCogent-1.5.3/doc/data/inseqs_protein.fasta 000644 000765 000024 00000000202 11361457314 021777 0 ustar 00jrideout staff 000000 000000 >1091044_fragment
IPLDFDKEFRDKTVVIVAIPGAFTPT
>13541053_fragment
KKKNTEVISVSEDTVYVHKAWVQYD
>15605725_fragment
FEILAINMDPENLTGFLKNNP PyCogent-1.5.3/doc/data/long_testseqs.fasta 000644 000765 000024 00000031171 11213030412 021616 0 ustar 00jrideout staff 000000 000000 >Human
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTATTACTCACT
AAAGACAGAATGAATGTAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTA
GCAAGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAACATGTAATGATAGGCGGACT
CCCAGCGAAAAAAAGGTAGATCTGAATGCTGATCCCCTGTGTGAGAGAAAAGAATGGAAT
AAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGATACTGAAGATGTTCCTTGGATAACA
CTAAATAGCAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAGGT
TCTGATGACTCACATGATGGGGAGTCTGAATCAAATGCCTTGGACGTTCTAAATGAGGTA
GATGAATATTCTGGTTCTTCAGAGAAAATAGACTTACTGGCCAGTGATCCTCATGAGGCT
TTAATATGTGAAAGAGTTCACTCCAAATCAGTAGAGAGTAATATTGAAGACAAAATATTT
GGGAAAACCTATCGGAAGAAGGCAAGCCTCCCCAACTTAAGCCATGTAACTGAAATTATA
GGAGCATTTGTTACTGAGCCACAGATAATACAAGAGCGTCCCCTCACAAATAAATTAAAG
CGTAAAAGGACATCAGGCCTTCATCCTGAGGATTTTATCAAGAAAGCAGATTTGGCAGTT
CAAAAGACTCCTGAAATGATAAATCAGGGAACTAACCAAACGGAGCAGAATGGTCAAGTG
ATGAATATTACTAATAGTGGTCATGAGAATAAAACAAAAGGTGATTCTATTCAGAATGAG
AAAAATCCTAACCCAATAGAATCACTCGAAAAAGAATCTTTCAAAACGAAAGCTGAACCT
ATAAGCAGCAGTATAAGCAATATGGAACTCGAATTAAATATCCACAATTCAAAAGCACCT
AAAAAGAATCTGAGGAGGAAGTCTACCAGGCATATTCATGCGCTTGAACTAGTCAGTAGA
AATCTAAGCCCACCTAATTGTACTGAATTGCAAATTGATAGTTGTTCTAGCAGTGAAGAG
ATAAAGAAAAAAAAGTACAACCAAATGCCAGTCAGGCACAGCAGAAACCTACAACTCATG
GAAGGTAAAGAACCTGCAACTGGAGCCAAGAAGAACAAGCCAAATGAACAGACAAGTAAA
AGACATGACAGCGATACTTTCCCAGAGCTGAAGAATGCACCTGGTTCTTTTACTAAGTGT
TCAAATACCAGTGAACTTAAAGAATTTAATCCTAGCCTTCCAAGAGAAGAAAAAGAGAAA
CTAGAAACAGTTAAAGTGTCTAATAATGCTGAAGACCCCAAAGATCTCATGTTAAGTGGA
GAAAGGGTTTTGCAAACTGAAAGATCTGTAGAGAGTAGCAGTATTTCATTGGTACCTGGT
ACTGATTATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGGAAGGCA
AAAACAGAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGGACTA
ATTCATGGTTCCAAAGATAATAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGACAT
GAAGTTAACCACTCAAATCCAGAAGAGGAATGTGCACACTCTGGGTCCTTAAAGAAACAA
AGTCCAAAAGTCACTTTTGAATGTGAACAAAAGGAAAATCAAGGAAAGAATGAGTCTAAT
AAGCCTGTACAGACAGTTAATATCACTGCAGGCTTTCCTGTGGTTGGTCAGAAAGATAAG
CCAGTTGATAATGCCAAATGTAAAGGAGGCTCTAGGTTTTGTCTATCATCTCAGTTCAGA
GGCAACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTTACAAAACCCATATCGT
ATACCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAATCTGCTA
GAGGAAAACTTTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAATGAGAACATT
CCAAGTACAGTGAGCACAATTAGCCGTAATAACAGAGAAAATGTTTTTAAAGAAGCCAGC
TCAAGCAATATTAATGAAGTAGGTTCCAGTGATGAAAACATTCAAGCAGAACTAGGTAGA
AACAGAGGGCCAAAATTGAATGCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTAT
AAACAAAGTCTTCCTGGAAGTAATAAGCATCCTGAAATAAAAAAGCAAGAAGTTCAGACT
GTTAATACAGATTTCTCTCCACTGATTTCAGATAACTTAGAACAGCCTATGAGTAGTCAT
GCATCTCAGGTTTGTTCTGAGACACCTGATGACCTGTTAGATGATGGTGAAATAAAGGAA
GATACTAGTTTTGCTGAAAATGACATTAAGGAAAGTTCTGCTGTTTTTAGCAAAAGCGTC
CAGAAAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCATACACATTTGGCTCAGGGT
TACCGAAGAGGG
>HowlerMon
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTTGTTACTCACT
AAAGACACACTGAATGTAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTA
GCAAGGAGCCAACATAACAGATGGGCTGAAAGTGAGGAAACATGTAATGATAGGCAGACT
CCCAGCGAGAAAAAGGTAGATGTGGATGCTGATCCCCTGCATGGGAGAAAAGAATGGAAT
AAGCAGAAACCTCCGTGCTCTGAGAATCCTAGAGATACTGAAGATGTTGCTTGGATAATG
CTAAATAGCAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAACT
TCTGATGACTCACATGATGGGGGGTCTGAATCAAATGCCTTGGAAGTTCTAAATGAGGTA
GATGGATATTCTAGTTCTTCAGAGAAAATAGACTTACTGGCCAGTGATCCTCATGATCAT
TTGATATGTGAAAGAGTTCACTGCAAATCAGTAGAGAGTAGTATTGAAGATAAAATATTT
GGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTGAGCCACGTAACTGAAATTATA
GGAGCATTTGTTACTGAGCCACAGATAATACAAGAGCATCCTCTCACAAATAAATTAAAG
CGTAAAAGGACATCAGGACTTCATCCTGAGGATTTTATCAAGAAAGCAGATTTGGCAGTT
CAAAAGACTCCTGAAAAGATAAATCAGGGAACTAACCAAACAGAGCGGAATGATCAAGTG
ATGAATATTACTAACAGTGGTCATGAGAATAAAACAAAAGGTGATTCTATTCAGAATGAG
AACAATCCTAACCCAGTAGAATCACTGGAAAAAGAATCATTCAAAAGTAAAGCTGAACCT
ATAAGCAGTAGTATAAGCAATATGGAATTAGAATTGAATGTCCACAATTCCAAAGCATCT
AAAAAGAATCTGAGAAGGAAGTCTACCAGGCATATTCATGAGCTTGAACTAGTCAGTAGA
AATCTAAGCCCACCTAATTATACTGAAGTACAAATTGATAGTTGTTCTAGCAGTGAAGAG
ATAAAGAAAAAAAATTACAACCAAATGCCAGTCAGGCACAGCAGAAAGCTACAACTCATG
GAAGATAAAGAACGTGCAGCTAGAGCCAAAAAGAGCAAGCCAAATGAACAAACAAGTAAA
AGACATGCCAGTGATACTTTCCCAGAACTGAGGAACATACCTGGTTCTTTTACTAACTGT
TCAAATACTAATGAATTTAAAGAATTTAATCCTAGCCTTCCAAGAGAACAAACAGAGAAA
CTAGAAACAGTTAAACTGTCTAATAATGCCAAAGACCCCAAAGATCTCATGTTAAGTGGA
GAAAGTGTTTTGCAAATTGAAAGATCTGTAGAGAGTAGCAGTATTTTGTTGATACCTGGT
ACTGATTATGGCACTCAGGAAAGTATCTCATTACTGGAAGTTAGCACTCTGGGGAAGGCA
AAAACAGAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGAACTA
ATTCATGGTTCTAAAGATACTAGAAATGGCACAGAAGGCTTGAAGTATCCATTGGGACCT
GAAGTTAACTACTCAAATCCAGAAAAGGAATGTGCATGCTCTAGGTCCTTAAAGAAACAA
AGTCCAAAGGTCACTCCTGAATGTGAACAAAAGGAAAATCAAGGAGAGAAAGAGTCTAAT
GAGCTTGTAGAGACAGTTAATACCACTGCAGGCTTTCCTATGGTTTGTCAGAAAGATAAG
CCAGTTGATTATGCCAGATGTGAAGGAGGCTCTAGGCTTTGTCTATCATCTCAGTTCAGA
GGCAACGAAACTGGACTCATTATTCCAAATAAACATGGACTTTTACAGAACCCATATCAT
ATGTCACCGCTTATTCCCACCAGGTCATTTGTTAAAACTAAATGTAAGAAAAACCTGCTA
GAAGAAAACTCTGAGGAACATTCAATGTCACCTGAAAGAGCAATGGGAAACAAGAACATT
CCAAGTACAGTGAGCACAATTAGCCATAATAACAGAGAAAATGCTTTTAAAGAAACCAGC
TCAAGCAGTATTTATGAAGTAGGTTCCAGTGATGAAAACATTCAAGCAGAGCTAGGTAGA
AACAGAAGGCCAAAATTGAATGCTATGCTTAGATTAGGGCTTCTGCAACCTGAGATTTGT
AAGCAAAGTCTTCCTATAAGTGATAAACATCCTGAAATTAAAAAGCAAGAAGTTCAGACT
GTTAATACAGACGTCTCTCTACTGATTTCATATAACCTAGAACAGCATATGAGCAGTCAT
ACATCTCAGGTTTGTTCTGAGACACCTGACAACCTGTTAGATGATGGTGAAATAAAGGAA
GATACTAGTTTTGCTGAATATGGCATTAAGGAGACTTCTACTGTTTTTAGCAAAAGTGTC
CAGAGAGGAGAGCTCAGCAGGAGCCCTAGCCCTTTCACCCATACACATTTGGCTCAGGTT
TACCAAAGAGGG
>Mouse
TGTGGCACAGATGCTCATGCCAGCTCATTACAGCCTGAGACCAGCAGTTTATTGCTCATT
GAAGACAGAATGAATGCAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCATA
GCAGTGAGCCAGCAGAGCAGATGGGCTGCAAGTAAAGGAACATGTAACGACAGGCAGGTT
CCCAGCGGGGAAAAGGTAGGTCCAAACGCTGACTCCCTTAGTGATAGAGAGAAGTGGACT
CACCCGCAAAGTCTGTGCCCTGAGAATTCTGGAGCTACCACCGATGTTCCTTGGATAACA
CTAAATAGCAGCGTTCAGAAAGTTAATGAGTGGTTTTCCAGAACTGGTGAAATGTTAACT
TCTGACAGCGCATCTGCCAGGAGGCACGAGTCAAATGCTTTGGAAGTTTCAAACGAAGTG
GATGGGGGTTTTAGTTCTTCAAGGAAAACAGACTTAGTAACCCCCGACCCCCATCATACT
TTAATGTGTGGAAGAGACTTCTCCAAACCAGTAGAGGATAATATCAGTGATAAAATATTT
GGGAAATCCTATCAGAGAAAGGGAAGCCGCCCTCACCTGAACCATGTGACTGAAATTATA
GGCACATTTATTACAGAACCACAGATAACACAAGAGCAGCCCTTCACAAATAAATTAAAA
CGTAAGAGAAGTACATCCCTTCAACCTGAGGACTTCATCAAGAAAGCAGATTCAGCAGGT
CAAAGGACTCCTGACAACATAAATCAGGGAACTGACCTAATGGAGCCAAATGAGCAAGCA
GTGAGTACTACCAGTAACTGTCAGGAGAACAAAATAGCAGGTAGTAATCTCCAGAAAGAG
AAAAGCGCTCATCCAACTGAATCATTGAGAAAGGAACCTTCCACAGCAGGAGCCAAATCT
ATAAGCAACAGTGTAAGTGATTTGGAGGTAGAATTAAACGTCCACAGTTCAAAAGCACCT
AAGAAAAATCTGAGGAGGAAGTCTATCAGGTGTGCTCTTCCACTTGAACCAATCAGTAGA
AATCCAAGCCCACCTACTTGTGCTGAGCTTCAAATCGATAGTTGTGGTAGCAGTGAAGAA
ACAAAGAAAAACCATTCCAACCAACAGCCAGCCGGGCACCTTAGAGAGCCTCAACTCATC
GAAGACACTGAACCTGCAGCGGATGCCAAGAAGAACGAGCCAAATGAACACATAAGGAAG
AGACGTGCCAGCGATGCTTTCCCAGAAGAGAAAAACAAAGCTGGTTTATTAACTAGCTGT
TCAAGTCCTAGAAAATCTCAAGGGCCTAATCCCAGCCCTCAGAGAACAGGAACAGAGCAA
CTTGAAACACGCCAAATGTCTGACAGTGCCAAAGAACTCGGGGATCGGGTCCTAGGAGGA
GAGCCCAGTGGCAAAACTGACCGATCTGAGGAGAGCACCAGCGTATCCTTGGTACCTGAC
ACTGACTACGACACTCAGAACAGTGTCTCAGTCCTGGACGCTCACACTGTCAGATATGCA
AGAACAGGATCCGCTCAGTGTATGACTCAGTTTGTAGCAAGCGAAAACCCCAAGGAACTC
GTCCATGGCTCTAACAATGCTGGGAGTGGCACAGAGGGTCTCAAGCCCCCCTTGAGACAC
GCGCTTAACCTCTCAAAACCTCAAAAGGACTGTGCTCACTCTGTGCCCTCAAAGGAACTG
AGTCCAAAGGTGACAGCTAAAGGTAAACAAAAAGAACGTCAGGGACAGGAAGAATTTGAA
AGTCACGTACAAGCAGTTGCGGCCACAGTGGGCTTACCTGTGCCCTGTCAAGAAGGTAAG
CTAGCTGCTGATACAATGTGTGATAGAGGTTGTAGGCTTTGTCCATCATCTCATTACAGA
AGCGGGGAGAATGGACTCAGCGCCACAGGTAAATCAGGAATTTCACAAAACTCACATTTT
AAACAATCAGTTTCTCCCATCAGGTCATCTATAAAAACTGACAATAGGAAACCTCTGACA
GAGGGACGATTTGAGAGACATACATCATCAACTGAGATGGCGGTGGGAAATGAGAACCTT
CAGAGTACAGTGCACACAGTTAGCCTGAATAACAGAGGAAATGCTTGTCAAGAAGCCGGC
TCGGGCAGTATTCATGAAGTATGTTCCACTGGTGACTCCTTCCCAGGACAACTAGGTAGA
AACAGAGGGCCTAAGGTGAACACTGTGCCTCCATTAGATAGTATGCAGCCTGGTGTCTGT
CAGCAAAGTGTTCCTGTAAGTGATAAGTATCTTGAAATAAAAAAGCAGGAGGGTGAGGCT
GTCTGTGCAGACTTCTCTCCACTATTCTCAGACCATCTTGAGCAATCTATGAGTGGTAAG
GTTTTTCAGGTTTGCTCTGAGACACCTGATGACCTGCTGGATGATGTTGAAATACAGGGA
CATACTAGCTTTGGTGAAGGTGACATAATGGAGAGATCTGCTGTCTTTAACGGAAGCATC
CTGAGAAGGGAGTCCAGTAGGAGCCCTAGTCCTGTAACCCATGCATCGAAGTCTCAGAGT
CTCCACAGAGCG
>NineBande
TGTGGCACAAATACTCATGCCAACTTATTACAGCATGAGAACAGCAGTTTATTACTCACT
AAAGACAGAATGAATGTAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTA
GCAAGGCGCCAACAGAGCAGATGGGCTGAAAGTAAGGAAACATGTAATGATAGGCAGACT
CCCAGCGAGAAAAAGGTAGATGTGGATGCTGATCCCCTGTATGGGCGAAAAGAACTGAAT
AAGCAGAAACCTCCATGCTCTGAGAGTCATAGAGATACCCAAGATATTCCTTGGATAATG
CTGAATAGTAGCATTCAGAAAGTTAACGAGTGGTTTTCCAGAGGTGATGACATATTAACT
TCTGATGACTCACACGATAGGGGGTCTGAATTAAATGCATTGAAAGTTTCAAAAGAAGTA
GATGAATATTCTAGTTTTTCAGAGAAGATAGACTTAATGGCCATTAATCCTCATGATACT
TTACAATTTGAAAGAGTCCAATTGAAACCAGCAGAGAGTAACATCAAAGATAAAATATTT
GGGAAAACCTATCATAGGAAGGCAAGCCTCCCTAACTTGAGCCACATAACCCGATTTATA
GGAGCTATTGCTGCAGAGCCCAAGATAACACAAGAGCATTCCCTCCAAAATAAAATAAAG
CGTAAAAGGGCATCAGGCCTTCGTCCTGAGGATTTATCCAAGAAAGTAGATTTGACAGTT
CAAAAAACCCCTGAAAAGATAAATCAGGGAACTGACCAAATGGAGCAGAATGATCCAGTG
ATGAATATTGCTAATAGTGGTCATGAGAATGAAACAAAAGGTGATTGTGTTCAGAAAGAG
AAAAATGCTAATCCGACAGAATCATTGGGAAAAGAATCTTTCAGAACTAAAGGCGAACCT
ATAAGCAGCAGTATAAGCAATATGGAACTAGAATTAAATATTTTAAATTCAAAAGCATCT
AAGAAGAATCCGAAGAGGATGTCCACCAGGCATATTCATGCACTTGAACTAGGCAGTAGA
AATCCAAGCCCACCTAATCATACTGAACTACAAATTGATAGTTGTTCTAGCATTGAAGAG
ATAGAGAAAATAAATTCTAACCAAAAGCCAATCAGACACAACAGAATGCTTCAACTCACG
AAAGAAAAAGAAACCACAACTGGAGCCAAAAAGAATAAGCCAAATGAACAAATAAGTGAA
AGACATGCCAGTGATGCTTTCCTAGAACTTAAAAATGTAACTGATTTTCTTCCTAAATGT
TCAAGTTCTGATAAACTTCAAAAATTTAATTCTAGCCTGCAAGGAGAAGTAGCAGAGAAC
CTAGAAACAATTCAAGTGTCTGATAGTACCAGGGACCCTGAAGATCTGGTGGTAAGTGGA
GAAAAGTGTTTGCAAACTGAAAGATCTGCAGAGAGTACCGGTATTTCAGTGGTACCTGAT
ACTGATTATGGCACTCAAGACAGTATCTCATTACTGGAAGCTGACACCCTGGGGAAGGCA
AAAACAGCACTAAATCAACATGTGAGTCAGTATGTAGCAATTAGAAATGCCACTGAACTT
TCCCATGGTTCTAAAGACACTAGAAATGACACTGAAGATTTTAAGGATTCATTGAGACAT
GAAGTTAACCACTCGAATCCAGAAAATGAATGTGCACACTCCAGGTTCTTAGGGAAACAA
AGTCCAAAAGTCACCTTTGAATGTAGACATAAAGAAAATCAGGGGAAGAAAGAGTCTAAA
AAACATGTGCAGGTAATTCACACAACTGCAGGCTTTCCTATAGTTTGTCAGAAAGATAAG
CCAGGTGATTATGCCAAAGGTCAAGGAGTCTCTAGGCTTTGTCAGTCCTCTCAGGCCAGA
GGCAATGAATCTGAACTCATTAATTCAAATGAACATGAAATTTCACAAAACCCAGATCAA
ATGCCATCACTTTCTCACATGAAGTCATCTGTTAAAACTAAATGTAAGGAAAACCTGTCA
GAGGAAAAGTTTGAGGAACTTACAGTGTCACTTGAAAGAACAATGGTAAATGAGAACATT
CAAAGTACAGTAAGCACAATTAGCCACAGTAACAGAGAAAACACTTTTAAAGAAGCCAGC
TCAAGCAGTATTAATGAAGTAGGGTCCAGTGATGAGAACATTCAAGCAGAAGTAGGTAGA
AACAGAGCACCTAAATTAAATGCTATGCTCAGATTAGGTCTTATGCAACCTGAAGTCTAT
AAGCAAAGTCTTCCTATAACCAATAAATATCCTGAAATAAAAAGTCAAGGAATTCGGGCT
GTTGATATAGACTTCTCTCCACTAATTTCAGATAACCTACAACTACCTATGAATAGTTGT
GCTTCCCAGATTTGTTCTGAGACACCTGATGACTTGTTAGATGATGATGAAATAAAGGAA
AATAACTGCTTTGCTGAAAGTGACATTAAGGAAAGATCTGCTATTTTTAGCAAAACTGTC
CAGAAAAGAGAGTTCAGAAGGAGCCCTAGCCCTTTAGTCCATACAAGTTTTGCTCAGGGT
CACCAAAGAAAG
>DogFaced
TGTGGCACAAATACTCATGCCAACTCATTACAGCATGAGAACAGCAGTTTATTATACACT
AAAGACAGAATGAATGTAGAAAAGACTGACTTCTGTAATAAAAGCAAACAGCCTGGCTTA
GCAAGGAGCCAGCAGAACAGATGGGTTGAAACTAAGGAAACATGTAATGATAGGCAGACT
TCCAGCGAGAAAAAGGTAGTTCTGAATGCTGATCCCCTGAATGGAAGAATAAAACTGAAT
AAGCAGAAACCTCCATGCTCTGACAGTCCTAGAGATTCCAAAGATATTCCTTGGATAACA
CGGAATAGTAGCATACAGAAAGTTAATGAGTGGTTTTCCAGACGTGATGAAACATTAACT
TCTGATGTCTTACTTGATGAGAGGTCTGAATCAAATGTGGTAGAAGTTCCAAATGAAGTA
GATGGATACTCTGGTGCTTCAGAGGAAATAGCCTTAAAGGCCAGTGATCCTCATGGTGCT
TTAATATGTGAAAGAGTTCACTCCAAATTGATAGAAAGTAATATTGAAGATAAAATATTT
GGGAAAACATATCGGAGGAAAGCAAGCCTCCCTAACTTAAGCCACATAACTGAAATTACA
AGAGCATCTGCTACAGAACCTCAGATAACACAAGAGTGCCCCCTCACAAATAAACTAAAA
CGTAAAAGAACATCAGGCCTTCATCCTGAGGATTTTATCAAGAAAATAGATTTGACAACT
CAAAAAACTTCTGAAAATATAATTGAGGGAACTGACCAAATAGAGCAGAATGGTCATGTG
ATGAATAGTTCTAATGATGGTCATGAGAATGAAACAAAAGGTGATTATGTTCAGAAGAAG
AAAAATACAAACCCAACAGAATCATTGGAAAAAGAATCTTTCAGAACTAAAGTTGAGTCT
GTACCCAACAACATAAGCAATGTGGAACTAGAATTAAATATTCACGGTTCAAAAGCACTC
AAGAAGAATCTGAGGAGGAAGTCCACCAGGCATATTCATGCACTTGAACTAGTCAATAGA
AATTCAAGCCCACCTAATCATACTGAACTACAAATTGATAGTTGTTCCAGCAGTGAAGAA
CTGAAGGAAAAAAATTCTGACCGAATGCCAGACAGACACAGCAAAAAACTTCAGTTCGTA
GAAGATAAAGAATCTGCAACTGGAGCCAAGAAGAACATGCCAAATGAGGCAATAAATAAA
AGACTTTCCAGTGAAGCTTTTCCCGAATTAAATAACGTACCTGGTTTTTTTACTAATGGT
TCAAGTTCTAATAAACGTCAAGAGTTTAATCCTAGCCTTCAAGGAGAAGAAATAGAGAAT
CTACGAACAATTCAAGTGTCTAATAGCACCAAAGACCCCAAAATTCTAATCTTTGGTGAA
GGAAGAGGTTCACAAACTGATCGATCTACAGAGAGTACCAGTATTTTATTGGGACCTGAA
ACGGATTATGGCACTCAAGATAGTATCTCATTACTGGAATCTGACATCCCAGGGAGGGCA
AAGACAGCACCAAACCAACATGCAGATCTGTGTGCAGCAATTGAAAACCCCAGAGAACTT
ATTCATGATTTTAAAGAAACTAGAAATGACACAGAGAGCTTTAAAGATCCATTGAGACAT
GAAGTTAACTCCTCAGACCCAGAAAAGGAATGTGCACACTCCAGGTCCTTGATAAAACAA
AGTCCAAAAGTCACTCTTGAATGTGACCGAAAAGGAAATCAGGGAAAGAAAGAGTCTAAC
GAGCATGTGCAGGCAGTTTATACAACTATAGGCTTTCCTGGGGTTTCTGAGAAAGACAAA
CCAGGAGATTATGCCAGATATAAAGAAGTCTCTAGGCTTTGTCAGTCATTTCAGTCTAGA
AGAAATGAAACTGAGCTCACTATTGCAAATAAACTTGGACTTTCACAAAACCCATATCAT
ATGCCATCCATTTCTCCCATCAAGTCATCTGTTAAAACTATATGTAAGAAAAATCTGTCA
GAGGAAAAGTTTGAAGAACATTCAATATTCCCTGAAAGAGCAATAGGAAATGAGACCATT
CAAAGTACAGTGGGCACAATTAGCCAAAATAACAGAGAAAGCACTTTTAAAGAAGGCAGC
TCAAGCGGTATTTATGAAGCAGGTTCCAGTGGTGAAAACATTCAAGCAGAACTAAGTAGA
AACAGAGGACCAAAATTAAATGCTGTGCTTCAGTTGGGTCTCATGCAGCCTGAAGTCTAT
GAGCAAAGCCTTCCTCTAAGTAATAAACATTCTGAAATAAAAAGGCAAGGAGTTCAGGCT
GTTAATGCAGATGTCTCTCCACAAATTTCAGATAACTTAGAGCAACCTATGAACAGTAAT
ATTTCTCAGGTTTGTTCTGAGACACCGGATGACCTGTTAAATGATGACAAAATAAAGGAC
AATATCAGCTTTGATGAAAGTGGCATTCAGGAAAGATCTGCTGTTTTTAGCAAAAATGTC
CAGAAAGGAGAATTCAGAAGGAGCCCTAGTCCCTTAGCCCATGCAAGTTTGTCTCAAGGT
CGCCCAAGAAGG
PyCogent-1.5.3/doc/data/motif_example.fasta 000644 000765 000024 00000041664 11115453517 021605 0 ustar 00jrideout staff 000000 000000 >1091044
VTDKFPEDVKFLYIAYTPAKADITACGIPIPLDFDKEFRDKTVVIVAIPGAFTPTCTANHIPPFVEKFTALKSAGVDAVIVLSANDPFVQSAFGKALGVTDEAFIFASDPGAEFSKSAGLSLDLPPAFGTRTARYAIIVSNGVVKYVEKDSEGVAGSGVDAVLAAL
>11467494
MTNFPKIGKTPPNFLTIGVYKKRLGKIRLSDYRGKKYVILFFYPANFTAISPTELMLLSDRISEFRKLSTQILAISVDSPFSHLQYLLCNREEGGLEDLNYPLVSDLTQTITRDYQVLTDEGLAFPGLFIIDKEGIIQYYTVNNLLCGRNINELLRILESIQYVKENPGYACPVNWNFGDQVFYSHPLKSKIYFKDLYSPKKSS
>11499727
MERLNSERFREVIQSDKLVVVDFYADWCMPCRYISPILEKLSKEYNGEVEFYKLNVDENQDVAFEYGIASIPTVLFFRNGKVVGGFIGAMPESAVRAEIEKALGA
>1174686
MSDGVKHINSAQEFANLLNTTQYVVADFYADWCGPCKAIAPMYAQFAKTFSIPNFLAFAKINVDSVQQVAQHYRVSAMPTFLFFKNGKQVAVNGSVMIQGADVNSLRAAAEKMGRLAKEKAAAAGSS
>12044976
MVTEIRSLKQLEEIFSAKKNVIVDFWAAWCGPCKLTSPEFQKAADEFSDAQFVKVNVDDHTDIAAAYNITSLPTIVVFENGVEKKRAIGFMPKTKIIDLFNN
>13186328
MLNTRIKPFKNISYYKKKFYEIKEIDLKSNWNVFFFYPYSYSFICPLELKNISNKIKEFKNLNTKIYAISNDSHFVQKNWIENELKFINFPFISDFNHKISNNFNILNKKDGNCLRSTIIIDKNLIIKYINIVDDSIGRSIDEILKNIKMLQFINTNENKLCPYSWNNDSKSIEIN
>13358154
MLIKLESNQNLNELLKENHSKPILIDFYADWCPPCRMLIPVLDSIEKKHGDEFTIIKINVDHFPELSTQYQVKSIPALFYLKNGDIKATSLGFIDENSLVNKLRSI
>13541053
MSLVNKAAPDFEANAFVNGEVKKIRLSSYRGKWVVLFFYPADFTFVCPTEVEGFAEDYEKFKKKNTEVISVSEDTVYVHKAWVQYDERVAKAKYPMVEDRKGIIARAYDVYNEETGNAQRGLFIINPDGIVKYVVITDDNVGRSTDETLRVLEALQSGGLCPVNWHEGEPTLKV
>13541117
MSPKVNEKAPDFEAPDTALKMRKLSEFRGQNVVLAFFPGAFTSVCTKEMCTFRDSMANFNKFKAKVIGISVDSPFSLAEFAKKNNLTFDLLSDSNREISKKYDVLHQNFAGVPGLTASKRSVFIIDGDGIVRYAWVSDDPGKEPDYKAIQEFLSKMN
>135765
AIVKATDQSFSAETSEGVVLADFWAPWCGPCKMIAPVLEELDQEMGDKLKIVKIDVDENQETAGKYGVMSIPTLLVLKDGEVVETSVGFKPKEALQELVNKHL
>1388082
MAAEEGQVIGCHTNDVWTVQLDKAKESNKLIVIDFTASWCPPCRMIAPIFNDLAKKFMSSAIFFKVDVDELQSVAKEFGVEAMPTFVFIKAGEVVDKLVGANKEDLQAKI
>140543
MLFYKPVMRMAVRPLKSIRFQSSYTSITKLTNLTEFRNLIKQNDKLVIDFYATWCGPCKMMQPHLTKLIQAYPDVRFVKCDVDESPDIAKECEVTAMPTFVLGKDGQLIGKIIGANPTALEKGIKDL
>14286173
MPLIGDKFPEMEVQTTHGPMELPDEFEGKWFILFSHPADFTPVCTTEFVAFQEVYPELRELDCELVGLSVDQVFSHIKWIEWIAENLDTEIEFPVIADTGRVADTLGLIHPARPTNTVRAVFVVDPEGIIRAILYYPQELGRNIPEIVRMIRAFRVIDAEGVAAPANWPDNQLIGDHVIVPPASDIETARKRKDEYECYDWWLCTQSRG
>14578634
MKKNFFYAGGLSLLLWGMAACSGQGKADKAAVVADSVVVKTDSVAADSTGYIVKVGESAPDFTITLTDGKQMKLSELRGKVVMLQFTASWCGVCRKEMPFIEKDIWLKHKNNPEFALIGIDRDEPLDKVIAFGKSVGVTYPLGLDPGADIFAKYALRESGITRNVLIDREGKIVKLTRLYNEEEFASLVDQIDEMLKK
>14600438
MPGVGEQAPDFEGIAHTGEKIRLSDFRGRIVVLYFYPRAMTPGCTREGVRFNELLDEFEKLGAVVIGVSTDSVEKNRKFAEKHGFRFKLVSDEKGEIGMKYGVVRGEGSNLAAERVTFIIDREGNIRAILRNIRPAEKHADLALEEVKKLVLGKKAERAGEVI
>15218394
MQVRAAKKQTFNSFDDLLQNSDKPVLVDFYATWCGPCQLMVPILNEVSETLKDIIAVVKIDTEKYPSLANKYQIEALPTFILFKDGKLWDRFVSFLSRMNTAYLLLASKAQL
>15597673
MLSFSLGPLVVSLQHLLLFLALGAALLGGWLAARGGGRNAEPVLFNLLLLGLLVARLAFVVRYWPQYRGDFAQMLDIRDGGFLAWPGLLAAVLGALFWAWRRPALRRSLGVGASLGLAFWLLGSLGLGIYERGTRLPELSLRNAAGESVQLADFRGRPLVINLWASWCPPCRREMPVLQQAQAENPDVVFLFANQGESAETVRHFLQGENLRLDNLLFDNGGQLGQQVGSVALPTTVFYTAEGRLLGSHLGELSRGSLARYLEAFEPAAAAPATRSSE
>15599256
MSDTPYIFDVTGANFEQLVIENSFHKPVLVDFWADWCAPCKALMPLLAQIAESYQGELLLAKVNCDVEQDIVMRFGIRSLPTVVLFKDGQPVDGFAGAQPESQIRALLEPHVKAPALPDEDPLEVAQALFAEGRIGDAEATLKALLAENNENAAALILYARCLAERGELEEAQAILDAVKSDEHKQALAGARAQLTFLRQAADLPDSAELKSRLAADAGDDEAAYQLAVQQLARQQYEAALDGLLKLFLRNRGYQDDLPRKTLVQVFDLLGNDHPLVTAYRRKLYQALY
>15602312
MVNSYEKPQMKTSVLLTALFKPLLLCTIVLSCIGCKEDIAVIGKQAPEIAVFDLVGTQRSLNEGKGKTILLNFWSETCGVCIAELKTFEQLLQSYPQNNLHIIAINVDGDKADTQALVKKREISLLVVKDQLKITAERYQLVGTPTSFVIDPEGKILYKFEGLIPTQDLHLFFKG
>15605725
MKRLLPVFLALILFGLLVYIGLNQDKHDHYTITTQKGQKIPNVTLTTPDGKKVSIEEFKGKVLLINFWATWCPPCKEEIPMFKEIYEKYRDRGFEILAINMDPENLTGFLKNNPLPFPVFVINEKWKEPLTFQGFQRRTWLTEEEL
>15605963
MARTVNLKGNPVTLVGPELKVGDRAPEAVVVTKDLQEKIVGGAKDVVQVIITVPSLDTPVCETETKKFNEIMAGMEGVDVTVVSMDLPFAQKRFCESFNIQNVTVASDFRYRDMEKYGVLIGEGALKGILARAVFIIDKEGKVAYVQLVPEITEEPNYDEVVNKVKELI
>15609375
MLNVGATAPDFTLRDQNQQLVTLRGYRGAKNVLLVFFPLAFTGICQGELDQLRDHLPEFENDDSAALAISVGPPPTHKIWATQSGFTFPLLSDFWPHGAVSQAYGVFNEQAGIANRGTFVVDRSGIIRFAEMKQPGEVRDQRLWTDALAALTA
>15609658
MTKTTRLTPGDKAPAFTLPDADGNNVSLADYRGRRVIVYFYPAASTPGCTKQACDFRDNLGDFTTAGLNVVGISPDKPEKLATFRDAQGLTFPLLSDPDREVLTAWGAYGEKQMYGKTVQGVIRSTFVVDEDGKIVVAQYNVKATGHVAKLRRDLSV
>15613511
MLEGKQAPDFSLPASNGETVSLSDFKGKNIVLYFYPKDMTPGCTTEACDFRDRVEDFKGLNTVILGVSPDPVERHKKFIEKYSLPFLLLADEDTKVAQQYDVWKLKKNFGKEYMGIERSTFVIDKDGTVVKEWRKVRVKDHVEEALAFIKENLE
>15614085
MNKKRLTTIVVLIAVVASVIIILTQNNLEVGNGKGMLAEDFTLPLYEESQSRSLSDYRGDVVILNVWASWCEPCRKEMPALMELQSDYESEDVSIVTVNMQTFERTVNDAGEFIEELGITLPVFLDEEGEFADAYQVQHLPMTYVLDREGIINEVILGEVTYEQLEQLIVPLLEKAS
>15614140
MDKRKRFWMRLSILAVISVALGYTFYSNFFADRSLARAGEQAVNFVLEDLEGESIELRELEGKGVFLNFWGTYCPPCEREMPHMEKLYGEYKEQGVEIIAVNANEPELTVQRFVDRYGLSFPIVIDKGLNVIDAYGIRPLPTTILINEHGEIVKVHTGGMTEQMVEEFMELIKPEA
>15615431
MKGKQAFYRSFLILALCTVGYFYSQSEHVYRPVDKEAITTFNEGVQVGQRAVPFSLTTLEGQVVDLSSLRGQPVILHFFATWCPVCQDEMPSLVKLDKEYRQKGGQFLAINLTNQESSIKDVRAFVQHYRAEFDPLLDTDGEVMETYQVIGIPTTLILDEEGTIVKRYNGVLTEEIIDEIMDIH
>15643152
MRVKHFELLTDEGKTFTHVDLYGKYTILFFFPKAGTSGCTREAVEFSRENFEKAQVVGISRDSVEALKRFKEKNDLKVTLLSDPEGILHEFFNVLENGKTVRSTFLIDRWGFVRKEWRRVKVEGHVQEVKEALDRLIEEDLSLNKHIEWRRARRALKKDRVPREELELLIKAAHLAPSCMNNQPWRFVVVDEEELLKKIHEALPGGNYWMKNAPALIAVHSKKDFDCALPDNRDYFLFDTGLAVGNLLVQATQMGLVAHPVAGYDPVKVKEILKIPEDHVLITLIAVGYLGDESELSEKHRELERSERVRKELSEIVRWNL
>15672286
MPMNITSHGEKIATLNPPISGDAPDFELTDLKGNKIKLSKLEKPVLISVFPDINTRVCSLQTKHFNLEAAKHSEIDFLSISNNTADEQKNWCATEGVDMTILADDGTFGKAYGLILNGGPLEGRLARSVFVVKNGQIVYSEVLSELSDEPNYEKALAATK
>15790738
MQRGWGSERLAPRLSPGRAGSVISNDTDTPSMRCEGARAPAFELPGVSDGTQTRLGLTDALADNRAVVLFFYPFDFSPVCATELCAIQNARWFDCTPGLAVWGISPDSTYAHEAFADEYALTFPLLSDHAGAIADAFGVLQASAEDHDRVPERAVFLIDADRVIRYAWASSDLSESPDLGAVKAAIDDLQPDTAGVAPRTISDAHDDGTTDG
>15791337
MTVTLKDFYADWCGPCKTQDPILEELEADYDEDVSFEKIDVDEAEDVANEYQVRSIPTIVVENDDGVVERFVGVTQREQLEDAIESAGA
>15801846
MSQTVHFQGNPVTVANSIPQAGSKAQTFTLVAKDLSDVTLGQFAGKRKVLNIFPSIDTGVCAASVRKFNQLATEIDNTVVLCISADLPFAQSRFCGAEGLNNVITLSTFRNAEFLQAYGVAIADGPLKGLAARAVVVIDENDNVIFSQLVDEITTEPDYEAALAVLKA
>15805225
MTEPAPASPARPAWTRALPPLLAAALVGGLGWALLKPAGNAANGPLVGKPAPQFNLTGLDGQPVALADYRGRPVVLNFWASWCGPCREEAPLFAKLAAHPGAPAVLGILFNETKPQNARDFARQYGLTYPNLQDPGVATAIAYQVTGIPRTVFIDAQGVVRHIDQGGLDTARLNAGLSKIGVPGL
>15805374
MTSPTPPTSPSLSPQPRRASWTRWIVPAVMVGLVGLLAYGLFTPDPEGGPALLGKPAPAFALEDLGGRTHALTAAQGKPVVINFWASWCVPCRQEAPLFSKLSQETAGKAEFFGVIYNDQPADARRFMDQYGLIYPALLDPGSRTALSYGVGKLPITFIVDGQGKVVHIKDGPIEEPELRAALKQAGL
>15807234
MTLVGQPAPDFTLPASTGQDITLSSYRGQSHVVLVFYPLDFSPVCSMQLPEYSGSQDDFTEAGAVVLGINRDSVYAHRAWAAEYGIEVPLLADMQLEVARQYGVAIDERGISGRAVFVIDREGVVRYQHVEEQTGQYTVRPGAVLEQLRGL
>15826629
APIKVGDAIPAVEVFEGEPGNKVNLAELFKGKKGVLFGVPGAFTPGCSKTHLPGFVEQAEALKAKGVQVVACLSVNDAFVTGEWGRAHKAEGKVRLLADPTGAFGKETDLLLDDSLVSIFGNRRLKRFSMVVQDGIVKALNVEPDGTGLTCSLAPNIISQL
>15899007
MNDELNDPELQKILSKKTTQILNNLKEKVKEPVKHLNSKNFDEFITKNKIVVVDFWAEWCAPCLILAPVIEELANDYPQVAFGKLNTEESQDIAMRYGIMSLPTIMFFKNGELVDQILGAVPREEIEVRLKSLLE
>15899339
MVEIGEKAPEIELVDTDLKKVKIPSDFKGKVVVLAFYPAAFTSVCTKEMCTFRDSMAKFNEVNAVVIGISVDPPFSNKAFKEQNKINFTIVSDFNREAVKAYGVAGELPILKGYVLAKRSVFVIDKNGIVRYKWVSEDPTKEPNYDEIKDVVTKLS
>15964668
MTIAVGDKLPNATFKEKTADGPVEVTTELLFKGKRVVLFAVPGAFTPTCSLNHLPGYLENRDAILARGVDDIAVVAVNDLHVMGAWATHSGGMGKIHFLSDWNAAFTKAIGMEIDLSAGTLGIRSKRYSMLVEDGVVKALNIEESPGQATASGAAAMLELL
>15966937
MSGSDNPYQGSFGTQMTGSASFGGQPASAASGPNDLTPDDLIRETTTAAFTRDVLEASRQQPVLVDFWAPWCGPCKQLTPVIEKVVREAAGRVKLVKMNIDDHPSIAGQLGIQSIPAVIAFIDGRPVDGFMGAVPESQIKEFIDRIAGPAADNGKAEIESVLADAKALIDAGDAQNAAGLYGAVLQADPENAAAVAGMIECMIALGQVAEARQALSGLPEALAGEAAVAAVSKKLDQIEEARKLGDPAALERQLALDPDDHAARLKLAKLRNVEGDRTAAAEHLLTIMKRDRSFEDDGARRELLSFFEVWGPKDPATIAARRKLSSILFS
>15988313
SRAPTGDPACRAAVATAQKIAPLAHGEVAALTMASAPLKLPDLAFEDADGKPKKLSDFRGKTLLVNLWATWCVPCRKEMPALDELQGKLSGPNFEVVAINIDTRDPEKPKTFLKEANLTRLGYFNDQKAKVFQDLKAIGRALGMPTSVLVDPQGCEIATIAGPAEWASEDALKLIRAATGKAAAAL
>16078864
MLKKWLAGILLIMLVGYTGWNLYQTYSKKEVGIQEGQQAPDFSLKTLSGEKSSLQDAKGKKVLLNFWATWCKPCRQEMPAMEKLQKEYADKLAVVAVNFTSAEKSEKQVRAFADTYDLTFPILIDKKGINADYNVMSYPTTYILDEKGVIQDIHVGTMTKKEMEQKLDLD
>16123427
MNTVCTACMATNRLPEERIDDGAKCGRCGHSLFDGEVINATAETLDKLLQDDLPMVIDFWAPWCGPCRSFAPIFAETAAERAGKVRFVKVNTEAEPALSTRFRIRSIPTIMLYRNGKMIDMLNGAVPKAPFDNWLDEQLSRDPNS
>16125919
MKIVLAGVAAVALAFASPALAALKAGDKAPDFSAKGALAGKDFDFNLAKALKKGPVVLYFFPAAYTAGCTAEAREFAEATPEFEKLGATVIGMTAGNVDRLKDFSKEHCRDKFAVAAADKALIKAYDVALAVKPDWSNRTSYVIAPDGKILLSHTDGNFMGHVQQTMGAVKAYKAKK
>16330420
MNLQIELYKFQQESLKRSSPERAAIFSDFIQGLSEEFRNRRLLRIGDFAPDFTLKNTKGETIILSEQLKTGPILLKFFRGYWCPYCGLELRAYQKVVNKIRALGGTILAISPQTLVASQKTIDRHDLTYDLLSDSGFQTAQDYGLVFTVPDAVKQIYLQSGCVIPEHNGTEEWLLPVPATFVIDRRGHIALAYANVDFRVRYEPEDAIAILLSLFVGN
>1633495
XDKIIHLTDDSFDTDVLKADGAILVDFWAEWCGPCKMIAPILDEIADEYQGKLTVAKLNIDQNPGTAPKYGIRGIPTLLLFKNGEVAATKVGALSKGQLKEFLDANLA
>16501671
MVLVTRQAPDFTAAAVLGSGEIVDKFNFKQHTNGKTTVLFFWPMDFTFVCPSELIAFDKRYEEFQKRGVEVVGVSFDSEFVHNAWRNTPVDKGGIGPVKYAMVADVKREIQKAYGIEHPDEGVALRGSFLIDANGIVRHQVVNDLPLGRNIDEMLRMVDALQFHEEHGDVCPAQWEKGKEGMNASPDGVAKYLAENISSL
>1651717
MVVAWTTRDQSARNMPMLAVNEDNFDNLVLQCPKPILVYFGAPWCGLCHFVKPLLNHLHGEWQEQLVCVEVNADVNLHLANAYRLKNLPTLILFNRGQVIQRLEDFRVREDLHRIREQIAVSLFSP
>16759994
MAGKLRRWLREAAVFLALLIAIMVVMDVWRAPQAPPAFAATPLHTLTGESTTLATLSEERPVLLYFWASWCGVCRFTTPAVAHLAAEGENVMTVALRSGGDAEVARWLARKGVDFPVVNDANGALSAGWEISVTPTLVVVSQGRVVFTTSGWTSYWGMKLRLWWAKTF
>16761507
MNTVCTHCQAINRIPGDRLQDAAKCGRCGHELFDGEVINATGETLDKLLKDDLPVVIDFWAPWCGPCRNFAPIFEDVAEERSGKVRFVKVNTEAERELSARFGIRSIPMIMIFKHGQVVDMLNGAVPKAPFDSWLNEAL
>16803644
MAERLVGTQAPRFEMEAVMPNQTFGKVSLEKNIEDDKWTILFFYPMDFTFVCPTEIVAISARSDEFDALNARIIGASTDTIHSHLAWTNTPIKEGGIGKLNYPLAADTNHQVASDYGVLIEEEGVALRGLFIINPKGEIQYEVVHHNNIGREVDEVLRVLQALQTGGLCPINWQPGEKTIV
>16804867
MAIIFAKEDDLEEIISSHPKILLNFWAEWCAPCRCFWPTLEQFAEMEEGNVQVVKINVDKQRALAQKFDVKGIPNSLVLVDGEIKGAIAGIVSCDELRSRFKSLAK
>17229033
MFSNREGQRVPQVTFRTRQNNEWVNVTTDDLFAGKTVAVFSLPGAFTPTCSSTHLPGYNELAKVFKDNGVDEIVCISVNDAFVMNEWAKTQEAENITLIPDGNGEFTEGMGMLVDKTDLGFGKRSWRYSMLVKDGVIEKMFIEPDVPGDPFEVSDAQTMLKHINPQAAKPKLVSLFTKVGCPFCARAKAALQENGIEYEEITLGKGITTRSLRAVTGATTVPQVFIDGVLIGGSEALTDYLSTIKQEKVGV
>17229859
MPTDTVAYVQENEFDTVLSEDKVVVVDFTATWCGPCRLVSPLMDQLADEYKGRVKVVKVDVDNNKPLFKRFGLRSIPAVLIFKDGELTEKIVGVSPYEQFSGAVEKLI
>1729944
MLMLDKDTFKTEVLEGTGYVLVDYFSDGCVPCKALMPAVEELSKKYEGRVVFAKLNTTGARRLAISQKILGLPTLSLYKDGVKVDEVTKDDATIENIEAMVEEHISK
>17531233
MLKRCNFKNQVKYFQSDFEQLIRQHPEKIIILDFYATWCGPCKAIAPLYKELATTHKGIIFCKVDVDEAEDLCSKYDVKMMPTFIFTKNGDAIEALEGCVEDELRQKVLEHVSAQ
>17537401
MPQFLKGVTLENREGDELPAEEHLKGKIIGLYFSASWCPPCRAFTPKLKEFFEEIKKTHPEFEIIFVSRDRNSSDLVTYFKEHQGEWTYIPFGSDKIMSLMQKYEVKTIPAMRIVNDQGEVIVQDARTEIQNKGENVEGLWAEWMALIK
>17547503
MSRRQTLIALILAGIVAAVLGVYAGHRATQPRPPADGAVTAFFDARLPDANGTPIDLSAFRGQPVVINFWAPWCGPCVEEMPELSALAQEQKARVKFIGIGIDSAANIQAFLGKVPVTYPIAVAGFGGTELGRQLGNQAGGLPFTVILNAQGEITFRKMGRVHADELRAALQRT
>18309723
MENINLFIVFIEGILSIFSPCILPILPIYLSMLSNSSVEDIRDSNFKSGVLIRNTLFFTLGISTTFFILGSSISALSSFFNTNKNIIMILGGVIILFMGLFYLGLINLNILNREKRLNFKYKNMSPVSAFVLGFTFSFGWTPCIGPILASVLVMASSSKNLLMSNLLILVYTIGFILPFIIASLFYGKLFKKFDGIKKHMDLIKKISGIFIIIAGLIMLVGGIRNMNNEIKINNNPQINKSESVNKDSKNESDNKKQEEENKIPPIDFTLYDQYGNKHTLSEYKGKTIFLNFWATWCPPCRGEMPYIDELYKEYNENKDDVVILGVASPNLGREGSEEHIKNFLKEENHVFPVVLDENGAMVYQYGINAFPSTFIINKEGYITKYIPGAMTKETMKTLIESER
>18313548
MVLKVGDKAPDFELLNEELKPVRLSEVLKRGRPVVLLFFPGAFTSVCTKELCTFRDKMALLNKANAEVLAISVDSPFALKAFKDANRLNFPLLSDYNRIVIGMYDVVQANLLGLPLYHLAKRAVYIIDPTGTIRYVWYSDDPRDEPPYDEVIKEAEKIGAQK
>18406743
MAETSKQVNGDDAQDLHSLLSSPARDFLVRNDGEQVKVDSLLGKKIGLYFSAAWCGPCQRFTPQLVEVYNELSSKVGFEIVFVSGDEDEESFGDYFRKMPWLAVPFTDSETRDRLDELFKVRGIPNLVMVDDHGKLVNENGVGVIRSYGADAYPFTPEKMKEIKEDEDRARRGQTLRSVLVTPSRDFVISPDGNKVPVSELEGKTIGLLFSVASYRKCTELTPKLVEFYTKLKENKEDFEIVLISLEDDEESFNQDFKTKPWLALPFNDKSGSKLARHFMLSTLPTLVILGPDGKTRHSNVAEAIDDYGVLAYPFTPEKFQELKELEKAKVEAQTLESLLVSGDLNYVLGKDGAKVLVSDLVGKTILMYFSAHWCPPCRAFTPKLVEVYKQIKERNEAFELIFISSDRDQESFDEYYSQMPWLALPFGDPRKASLAKTFKVGGIPMLAALGPTGQTVTKEARDLVVAHGADAYPFTEERLKEIEAKYDEIAKDWPKKVKHVLHEEHELELTRVQVYTCDKCEEEGTIWSYHCDECDFDLHAKCALNEDTKENGDEAVKVGGDESKDGWVCEGNVCTKA
>19173077
MFPKTLTDSKYKAFVDGEIKEISLQDYIGKYVVLAFYPLDFTFVCPTEINRFSDLKGAFLRRNAVVLLISCDSVYTHKAWASIPREQNGVLGTAWPMVWDAKRELCNQFGLYDEENGHPMRSTVILAKDLSVRHISSNYHAIGRSVDEIIRLIDAITFNDENGDICPAEWRSENKDN
>19554157
MEEGEEISLSDFEGEVVVLNAWGQWCAPCRAEVDDLQLVQETLDPLGGTVLGINVRDYNQTIAQDFKLDNAVTYPSIYDPPFRIAAALGGVPTSVIPTTIVLDRSHRPAAVFLREVTALSG
>19705357
MSFSVFAAKSDKKDDVKLPNIVLYDQYGKKHNIEEYKGKVVVINFWATWCGYCVEEMPGFEKVYKEFGSNKKDVIILGVAGPKSKENLNNVDVEKDKIISFLKKKNITYPSLMDETGKSFDDYKVRALPMTYVINKNGYLEGFVNGAITDEQLRKAINETLKKK
>19746502
MKKGLLVTTGLACLGLLTACSTQDNMAKKEITQDKMSMAAKKKDKMSTSKDKSMMADKSSDKKMTNDGPMAPDFELKGIDGKTYRLSEFKGKKVYLKFWASWCSICLSTLADTEDLAKMSDKDYVVLTVVSPGHQGEKSEADFTKWFQGTDYKDLPVLLDPDGKLLEAYGVRSYPTEVFIGSDGVLAKKHIGYAKKSDIKKALKGIH
>20092028
MAGDFMKPMLLDFSATWCGPCRMQKPILEELEKKYGDKVEFKVVDVDENQELASKYGIHAVPTLIIQKDGTEVKRFMGVTQGSILAAELDKLL
>20151112
SLINTKIKPFKNQAFKNGEFIEVTEKDTEGRWSVFFFYPADFTFVCPTELGDVADHYEELQKLGVDVYSVSTDTHFTHKAWHSSSETIAKIKYAMIGDPTGALTRNFDNMREDEGLADRATFVVDPQGIIQAIEVTAEGIGRDASDLLRKIKAAQYVAAHPGEVCPAKWKEGEATLAPSLDLVGKI
>21112072
MTIQVGDRIPEVVLKHLREGIEAVDTHTLFTGRKVVLFAVPGAFTPTCSAKHLPGYVEQFEAFRKRGIEVLCTAVNDPFVMQAWGRSQLVPDGLHLVPDGNAELARALGLEIDASGSGMGLRSRRYALYADDGVVKALFVEEPGEFKVSAADYVLQHLPD
>21222859
MSAASRAPLRSNRTAERFTERTADARARVRSRAARAAVGAAAAALLVSACSSGGTSGGGGQTGFITGSDGIATAKKGERADAPELSGETVDGGQVDVADYKGKVVVLNVWGSWCPPCRAEAKNFEKVYQDVKDQGVQFVGINTRDTSTGPARAFEKDYGVTYPSLYDPAGRLMLRFEKGTLNPQAVPSTLIIDREGKVAARTLQALSEEKLRKMLAPYLQPEK
>21223405
MLTVGDKFPEFDLTACVSLEKGKEFQQINHKTYEGQWKVVFAWPKDFTFVCPTEIAAFGKLNDEFADRDAQILGFSGDSEFVHHAWRKDHPDLTDLPFPMLADSKHELMRDLGIEGEDGFAQRAVFIVDQNNEIQFTMVTAGSVGRNPKEVLRVLDALQTDELCPCNWSKGDETLDPVALLSGE
>21227878
MTDEIRVGETIQDFRLRDQKREEIHLYDLKGKKVLLSFHPLAWTQVCAQQMKSLEENYELFTELNTVPLGISVDPIPSKKAWARELGINHIKLLSDFWPHGEVARTCGIFRGKEGVSERANIIIDENRQVIYFKKYLGHELPDIKEIIEVLKNK
>21283385
MTEITFKGGPIHLKGQQINEGDFAPDFTVLDNDLNQVTLADYAGKKKLISVVPSIDTGVCDQQTRKFNSDASKEEGIVLTISADLPFAQKRWCASAGLDNVITLSDHRDLSFGENYGVVMEELRLLARAVFVLDADNKVVYKEIVSEGTDFPDFDAALAAYKNI
>21674812
MIEEGKIAPDFTLPDSTGKMVSLSEFKGRKVLLIFYPGDDTPVCTAQLCDYRNNVAAFTSRGITVIGISGDSPESHKQFAEKHKLPFLLLSDQERTVAKAYDALGFLGMAQRAYVLIDEQGLVLLSYSDFLPVTYQPMKDLLARIDAS
>23098307
MKILKYVLIISISMFLPIMTAYAEGTEVGERAPDFELKTIDGQQLRLSDFKGERVLINFWTTWCPPCRQEMPDMQRFYQDLQPNILAVNLTDTEMNKEQVVRFSQELELTFPILLDEKGEVSKAYRISPIPTTYMIDSEGIIRHKSYGALTYEQMVAEYNKME
>2649838
MVFTSKYCPYCRAFEKVVERLMGELNGTVEFEVVDVDEKRELAEKYEVLMLPTLVLADGDEVLGGFMGFADYKTAREAILEQISAFLKPDYKN
>267116
MSKVIHVTSNEELDKYLQHQRVVVDFSAEWCGPCRAIAPVFDKLSNEFTTFTFVHVDIDKVNTHPIGKEIRSVPTFYFYVNGAKVSEFSGANEATLRSTLEANI
>27375582
MSEQSTSANPQRRTFLMVLPLIAFIGLALLFWFRLGSGDPSRIPSALIGRPAPQTALPPLEGLQADNVQVPGLDPAAFKGKVSLVNVWASWCVPCHDEAPLLTELGKDKRFQLVGINYKDAADNARRFLGRYGNPFGRVGVDANGRASIEWGVYGVPETFVVGREGTIVYKLVGPITPDNLRSVLLPQMEKALK
>2822332
MATDTAATTGTASPDEPLYVNGQTELDDVTSDNDVVLADFYADWCGPCQMLEPVVETLAEQTDAAVAKIDVDENQALASAYGVRGVPTLVLFADGEQVEEVVGLQDEDALKDLIESYTE
>30021713
MWRKLTIIVVLLCLAGYAAYEQFGNKEQAVKVKQEKSEAAMKEIIARNGIEIGKSAPDFELTKLDGTNVKLSDLKGKKVILNFWATWCGPCQQEMPDMEAFYKEHKENVEILAVNYTPSEKGGGEEKVSNFIKEKGITFPVLLDKNIDVTTAYKVITIPTSYFIDTKGVIQDKFIGPMTQKEMEKRVAKLK
>3261501
MTTRDLTAAYFQQTISANSNVLVYFWAPLCAPCDLFTPTYEASSRKHFDVVHGKVNIETEKDLASIAGVKLLPTLMAFKKGKLVFKQAGIANPAIMDNLVQQLRAYTFKSPAGEGIGPGTKTSS
>3318841
MPGGLLLGDVAPNFEANTTVGRIRFHDFLGDSWGILFSHPRDFTPVCTTELGRAAKLAPEFAKRNVKLIALSIDSVEDHLAWSKDINAYNSEEPTEKLPFPIIDDRNRELAILLGMLDPAEKDEKGMPVTARVVFVFGPDKKLKLSILYPATTGRNFDEILRVVISLQLTAEKRVATPVDWKDGDSVMVLPTIPEEEAKKLFPKGVFTKELPSGKKYLRYTPQP
>3323237
MALLDISSGNVRKTIETNPLVIVDFWAPWCGSCKMLGPVLEEVESEVGSGVVIGKLNVDDDQDLAVEFNVASIPTLIVFKDGKEVDRSIGFVDKSKILTLIQKNA
>4155972
MLEVINGKNYAEKTAHQAVVVNVGASWCPDCRKIEPIMENLAKTYKGKVEFFKVSFDESQDLKESLGIRKIPTLIFYKNAKEVGERLVEPSSQKPIEDALKALL
>4200327
MAQRLLLRRFLASVISRKPSQGQWPPLTSRALQTPQCSPGGLTVTPNPARTIYTTRISLTTFNIQDGPDFQDRVVNSETPVVVDFHAQWCGPCKILGPRLEKMVAKQHGKVVMAKVDIDDHTDLAIEYEVSAVPTVLAMKNGDVVDKFVGIKDEDQLEAFLKKLIG
>4433065
GSIKEIDINEYKGKYVVLLFYPLDWTFVCPTEMIGYSEVAGQLKEINCEVIGVSVDSVYCHQAWCEADKSKGGVGKLGFPLVSDIKRCISIKYGMLNVETGVSRRGYVIIDDKGKVRYIQMNDDGIGRSTEET
>4704732
MAPITVGDVVPDGTISFFDENDQLQTVSVHSIAAGKKVILFGVPGAFTPTCSMSHVPGFIGKAEELKSKGIDEIICFSVNDPFVMKAWGKTYPENKHVKFVADGSGEYTHLLGLELDLKDKGSGISSGRFALLLDNLKVTVANVESGGEFTVSSAEDILKAL
>4996210
MAYHLGATFPNFTATASNVDGVFDFYKYVGDNWAILFSHPHDFTPVCTTELAEFGKMHEEFLKLNCKLIGFSCNSKESHDQWIEDIKFYGNLDKWDIPMVCDESRELANQLKIMDEKEKDIKGLPLTCRCVFFISPDKKVKATVLYPATTGRNSQEILRVLKSLQLTNTHPVATPVNWKEGDKCCILPSVDNADLPKLFKNEVKKLDVPSQKAYLRFVQM
>5326864
MSLKAGDSFPEGVTFSYIPWAEDASEITSCGIPINYNASKEFANKKVVLFALPGAFTPVCSANHVPEYIQKLPELRAKGVDQVAVLAYNDAYVMSAWGKANGVTGDDILFLSDPEAKFSKSIGWADEEGRTYRYVLVIDNGKIIYAAKEAAKNSLELSRADHVLKQL
>6322180
MGEALRRSTRIAISKRMLEEEESKLAPISTPEVPKKKIKTGPKHNANQAVVQEANRSSDVNELEIGDPIPDLSLLNEDNDSISLKKITENNRVVVFFVYPRASTPGCTRQACGFRDNYQELKKYAAVFGLSADSVTSQKKFQSKQNLPYHLLSDPKREFIGLLGAKKTPLSGSIRSHFIFVDGKLKFKRVKISPEVSVNDAKKEVLEVAEKFKEE
>6323138
MSDLVNKKFPAGDYKFQYIAISQSDADSESCKMPQTVEWSKLISENKKVIITGAPAAFSPTCTVSHIPGYINYLDELVKEKEVDQVIVVTVDNPFANQAWAKSLGVKDTTHIKFASDPGCAFTKSIGFELAVGDGVYWSGRWAMVVENGIVTYAAKETNPGTDVTVSSVESVLAHL
>6687568
MRVLATAADLEKLINENKGRLIVVDFFAQWCGPCRNIAPKVEALAKEIPEVEFAKVDVDQNEEAAAKYSVTAMPTFVFIKDGKEVDRFSGANETKLRETITRHK
>6850955
MVSVGKKAPDFEMAGFYKGEFKTFRLSEYLGKWVVLCFYPGDFTFVXATEVSAVAEKYPEFQKLGVEVLSVSVDSVFVHKMWNDNELSKMVEGGIPFPMLSDGGGNVGTLYGVYDPEAGVENRGRFLIDPDGIIQGYEVLILPVGRNVSETLRQIQAFQLVRETKGAEVAPSGWKPGKKTLKPGPGLVGNVYKEWSVKEAFED
>7109697
MKHITNKAELDQLLTTNKKVVVDFYANWCGPCKILGPIFEEVAQDKKDWTFVKVDVDQANEISSEYEIRSIPTIIFFQDGKMADKRIGFIPKNELKELLK
>7290567
MVYPVRNKDDLDQQLILAEDKLVVIDFYADWCGPCKIIAPKLDELAQQYSDRVVVLKVNVDENEDITVEYNVNSMPTFVFIKGGNVLELFVGCNSDKLAKLMEKHARRLYR
>9955016
XSGNARIGKPAPDFKATAVVDGAFKEVKLSDYKGKYVVLFFYPLDFTFVCPTEIIAFSNRAEDFRKLGCEVLGVSVDSQFTHLAWINTPRKEGGLGPLNIPLLADVTRRLSEDYGVLKTDEGIAYRGLFIIDGKGVLRQITVNDLPVGRSVDEALRLVQAFQYTDEHGEVCPAGWKPGSDTIKPNVDDSKEYFSKHN
>15677788
MKKILTAAVVALIGILLAIVLIPDSKTAPAFSLPDLHGKTVSNADLQGKVTLINFWFPSCPGCVSEMPKIIKTANDYKNKNFQVLAVAQPIDPIESVRQYVKDYGLPFTVMYDADKAVGQAFGTQVYPTSVLIGKKGEILKTYVGEPDFGKLYQEIDTAWRNSDAV PyCogent-1.5.3/doc/data/motif_example_meme_results.txt 000644 000765 000024 00000611657 11115453517 024117 0 ustar 00jrideout staff 000000 000000 ********************************************************************************
MEME - Motif discovery tool
********************************************************************************
MEME version 3.0.14 (Release date: 2005/07/19 07:15:54)
For further information on how to interpret these results or to get
a copy of the MEME software please access http://meme.nbcr.net.
This file may be used as input to the MAST algorithm for searching
sequence databases for matches to groups of motifs. MAST is available
for interactive use and downloading at http://meme.nbcr.net.
********************************************************************************
********************************************************************************
REFERENCE
********************************************************************************
If you use this program in your research, please cite:
Timothy L. Bailey and Charles Elkan,
"Fitting a mixture model by expectation maximization to discover
motifs in biopolymers", Proceedings of the Second International
Conference on Intelligent Systems for Molecular Biology, pp. 28-36,
AAAI Press, Menlo Park, California, 1994.
********************************************************************************
********************************************************************************
TRAINING SET
********************************************************************************
DATAFILE= superfamily_aln_gis.fasta
ALPHABET= ACDEFGHIKLMNPQRSTVWY
Sequence name Weight Length Sequence name Weight Length
------------- ------ ------ ------------- ------ ------
1091044 1.0000 166 11467494 1.0000 204
11499727 1.0000 105 1174686 1.0000 127
12044976 1.0000 102 13186328 1.0000 176
13358154 1.0000 106 13541053 1.0000 174
13541117 1.0000 157 135765 1.0000 103
1388082 1.0000 110 140543 1.0000 127
14286173 1.0000 209 14578634 1.0000 198
14600438 1.0000 163 15218394 1.0000 112
15597673 1.0000 278 15599256 1.0000 289
15602312 1.0000 175 15605725 1.0000 146
15605963 1.0000 169 15609375 1.0000 153
15609658 1.0000 157 15613511 1.0000 154
15614085 1.0000 177 15614140 1.0000 176
15615431 1.0000 184 15643152 1.0000 321
15672286 1.0000 160 15790738 1.0000 212
15791337 1.0000 89 15801846 1.0000 168
15805225 1.0000 185 15805374 1.0000 188
15807234 1.0000 151 15826629 1.0000 161
15899007 1.0000 135 15899339 1.0000 156
15964668 1.0000 161 15966937 1.0000 330
15988313 1.0000 186 16078864 1.0000 170
16123427 1.0000 145 16125919 1.0000 177
16330420 1.0000 218 1633495 1.0000 108
16501671 1.0000 200 1651717 1.0000 126
16759994 1.0000 168 16761507 1.0000 139
16803644 1.0000 181 16804867 1.0000 106
17229033 1.0000 251 17229859 1.0000 108
1729944 1.0000 107 17531233 1.0000 115
17537401 1.0000 149 17547503 1.0000 174
18309723 1.0000 403 18313548 1.0000 162
18406743 1.0000 578 19173077 1.0000 177
19554157 1.0000 121 19705357 1.0000 164
19746502 1.0000 207 20092028 1.0000 93
20151112 1.0000 186 21112072 1.0000 160
21222859 1.0000 223 21223405 1.0000 184
21227878 1.0000 154 21283385 1.0000 164
21674812 1.0000 148 23098307 1.0000 163
2649838 1.0000 93 267116 1.0000 104
27375582 1.0000 194 2822332 1.0000 119
30021713 1.0000 191 3261501 1.0000 124
3318841 1.0000 224 3323237 1.0000 105
4155972 1.0000 104 4200327 1.0000 166
4433065 1.0000 133 4704732 1.0000 162
4996210 1.0000 220 5326864 1.0000 167
6322180 1.0000 215 6323138 1.0000 176
6687568 1.0000 104 6850955 1.0000 203
7109697 1.0000 100 7290567 1.0000 111
9955016 1.0000 197 15677788 1.0000 166
********************************************************************************
********************************************************************************
COMMAND LINE SUMMARY
********************************************************************************
This information can also be useful in the event you wish to report a
problem with the MEME software.
command: meme superfamily_aln_gis.fasta -protein -mod anr -evt 1e-10 -nmotifs 10
model: mod= anr nmotifs= 10 evt= 1e-10
object function= E-value of product of p-values
width: minw= 8 maxw= 50 minic= 0.00
width: wg= 11 ws= 1 endgaps= yes
nsites: minsites= 2 maxsites= 50 wnsites= 0.8
theta: prob= 1 spmap= pam spfuzz= 120
em: prior= megap b= 81535 maxiter= 50
distance= 1e-05
data: n= 16307 N= 96
sample: seed= 0 seqfrac= 1
Dirichlet mixture priors file: prior30.plib
Letter frequencies in dataset:
A 0.084 C 0.016 D 0.064 E 0.071 F 0.051 G 0.068 H 0.014 I 0.059 K 0.072
L 0.093 M 0.021 N 0.040 P 0.051 Q 0.032 R 0.041 S 0.051 T 0.051 V 0.082
W 0.014 Y 0.027
Background letter frequencies (from dataset with add-one prior applied):
A 0.084 C 0.016 D 0.064 E 0.071 F 0.051 G 0.068 H 0.014 I 0.059 K 0.072
L 0.093 M 0.021 N 0.040 P 0.051 Q 0.032 R 0.041 S 0.051 T 0.051 V 0.082
W 0.014 Y 0.027
********************************************************************************
********************************************************************************
MOTIF 1 width = 29 sites = 50 llr = 2381 E-value = 2.4e-621
********************************************************************************
--------------------------------------------------------------------------------
Motif 1 Description
--------------------------------------------------------------------------------
Simplified A :::::1:::9:::1:::2:3:1:11:41:
pos.-specific C ::::::::::::a::a:::::::::::::
probability D 11::::5:::2::::::::::1:11::11
matrix E 1:::::::::1::::::13::::44:115
F :::::::91:::::::::1:::2::1:::
G 41:::::::::::5:::::1:::::::1:
H 1::::::::::::::::::::::::::::
I ::1212:::::::::::12::21::1:::
K :51:::::::::::::31:::1:13::31
L ::1143:::::::::::12::15::6:::
M :::::::::::::::::2:3::1::::::
N 1:::::3::::::::::::::::1:::1:
P ::3:::::::1::29:::::a::::::::
Q :1::::::::::::::11:::::11:121
R :1::::::::::::::51:::::::::::
S ::::::::1:2::::::::1::::::1::
T ::1:::::::3:::::::11::::::::1
V ::2644:1:::::1:::::::211:2:::
W ::::::::5::a:::::::::::::::::
Y ::::::1:2:::::::::::::::::2::
bits 6.2 * *
5.6 ** *
5.0 ** *
4.3 ** *
Information 3.7 ** ** * *
content 3.1 **** ** ** *
(68.7 bits) 2.5 * **** ** *** *
1.9 ** ******* ****** * * ** *
1.2 ***************** *** *******
0.6 *****************************
0.0 -----------------------------
Multilevel GKPVVVDFWATWCGPCRxEAPILEELAKE
consensus ILLN Y S P K IM F K
sequence I
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 1 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- -----------------------------
16078864 59 7.26e-28 GEKSSLQDAK GKKVLLNFWATWCKPCRQEMPAMEKLQKE YADKLAVVAV
30021713 76 1.70e-27 GTNVKLSDLK GKKVILNFWATWCGPCQQEMPDMEAFYKE HKENVEILAV
15805374 77 2.01e-27 GRTHALTAAQ GKPVVINFWASWCVPCRQEAPLFSKLSQE TAGKAEFFGV
15805225 71 3.96e-26 GQPVALADYR GRPVVLNFWASWCGPCREEAPLFAKLAAH PGAPAVLGIL
17547503 62 1.68e-25 GTPIDLSAFR GQPVVINFWAPWCGPCVEEMPELSALAQE QKARVKFIGI
18309723 285 4.41e-25 GNKHTLSEYK GKTIFLNFWATWCPPCRGEMPYIDELYKE YNENKDDVVI
16761507 52 4.41e-25 GETLDKLLKD DLPVVIDFWAPWCGPCRNFAPIFEDVAEE RSGKVRFVKV
135765 16 4.41e-25 TDQSFSAETS EGVVLADFWAPWCGPCKMIAPVLEELDQE MGDKLKIVKI
7290567 20 5.05e-25 DLDQQLILAE DKLVVIDFYADWCGPCKIIAPKLDELAQQ YSDRVVVLKV
19705357 38 1.66e-24 GKKHNIEEYK GKVVVINFWATWCGYCVEEMPGFEKVYKE FGSNKKDVII
20092028 6 1.89e-24 MAGDF MKPMLLDFSATWCGPCRMQKPILEELEKK YGDKVEFKVV
11499727 16 2.44e-24 SERFREVIQS DKLVVVDFYADWCMPCRYISPILEKLSKE YNGEVEFYKL
7109697 17 3.57e-24 KAELDQLLTT NKKVVVDFYANWCGPCKILGPIFEEVAQD KKDWTFVKVD
267116 19 4.58e-24 SNEELDKYLQ HQRVVVDFSAEWCGPCRAIAPVFDKLSNE FTTFTFVHVD
1388082 28 6.65e-24 TVQLDKAKES NKLIVIDFTASWCPPCRMIAPIFNDLAKK FMSSAIFFKV
15599256 25 9.60e-24 FEQLVIENSF HKPVLVDFWADWCAPCKALMPLLAQIAES YQGELLLAKV
1633495 20 1.08e-23 DSFDTDVLKA DGAILVDFWAEWCGPCKMIAPILDEIADE YQGKLTVAKL
15966937 60 3.99e-23 FTRDVLEASR QQPVLVDFWAPWCGPCKQLTPVIEKVVRE AAGRVKLVKM
15605725 60 3.99e-23 GKKVSIEEFK GKVLLINFWATWCPPCKEEIPMFKEIYEK YRDRGFEILA
16123427 52 5.03e-23 AETLDKLLQD DLPMVIDFWAPWCGPCRSFAPIFAETAAE RAGKVRFVKV
23098307 52 5.65e-23 GQQLRLSDFK GERVLINFWTTWCPPCRQEMPDMQRFYQD LQPNILAVNL
17229859 21 6.33e-23 ENEFDTVLSE DKVVVVDFTATWCGPCRLVSPLMDQLADE YKGRVKVVKV
6687568 19 8.90e-23 DLEKLINENK GRLIVVDFFAQWCGPCRNIAPKVEALAKE IPEVEFAKVD
15597673 156 9.96e-23 GESVQLADFR GRPLVINLWASWCPPCRREMPVLQQAQAE NPDVVFLFAN
15218394 22 9.96e-23 NSFDDLLQNS DKPVLVDFYATWCGPCQLMVPILNEVSET LKDIIAVVKI
15899007 48 3.01e-22 SKNFDEFITK NKIVVVDFWAEWCAPCLILAPVIEELAND YPQVAFGKLN
15988313 60 4.16e-22 GKPKKLSDFR GKTLLVNLWATWCVPCRKEMPALDELQGK LSGPNFEVVA
17531233 27 7.10e-22 DFEQLIRQHP EKIIILDFYATWCGPCKAIAPLYKELATT HKGIIFCKVD
13358154 20 7.89e-22 NLNELLKENH SKPILIDFYADWCPPCRMLIPVLDSIEKK HGDEFTIIKI
1174686 21 1.08e-21 AQEFANLLNT TQYVVADFYADWCGPCKAIAPMYAQFAKT FSIPNFLAFA
3323237 18 1.20e-21 SGNVRKTIET NPLVIVDFWAPWCGSCKMLGPVLEEVESE VGSGVVIGKL
18406743 363 1.48e-21 GAKVLVSDLV GKTILMYFSAHWCPPCRAFTPKLVEVYKQ IKERNEAFEL
15614085 59 1.64e-21 SQSRSLSDYR GDVVILNVWASWCEPCRKEMPALMELQSD YESEDVSIVT
16804867 18 1.82e-21 EDDLEEIISS HPKILLNFWAEWCAPCRCFWPTLEQFAEM EEGNVQVVKI
21222859 102 2.01e-21 GGQVDVADYK GKVVVLNVWGSWCPPCRAEAKNFEKVYQD VKDQGVQFVG
2822332 33 2.73e-21 QTELDDVTSD NDVVLADFYADWCGPCQMLEPVVETLAEQ TDAAVAKIDV
16759994 59 2.73e-21 ESTTLATLSE ERPVLLYFWASWCGVCRFTTPAVAHLAAE GENVMTVALR
140543 43 5.53e-21 LTEFRNLIKQ NDKLVIDFYATWCGPCKMMQPHLTKLIQA YPDVRFVKCD
15614140 62 8.21e-21 GESIELRELE GKGVFLNFWGTYCPPCEREMPHMEKLYGE YKEQGVEIIA
17537401 26 1.21e-20 DELPAEEHLK GKIIGLYFSASWCPPCRAFTPKLKEFFEE IKKTHPEFEI
18406743 43 1.34e-20 GEQVKVDSLL GKKIGLYFSAAWCGPCQRFTPQLVEVYNE LSSKVGFEIV
27375582 80 1.63e-20 VPGLDPAAFK GKVSLVNVWASWCVPCHDEAPLLTELGKD KRFQLVGINY
15615431 71 1.79e-20 GQVVDLSSLR GQPVILHFFATWCPVCQDEMPSLVKLDKE YRQKGGQFLA
12044976 18 3.84e-20 LKQLEEIFSA KKNVIVDFWAAWCGPCKLTSPEFQKAADE FSDAQFVKVN
4200327 78 6.73e-20 PDFQDRVVNS ETPVVVDFHAQWCGPCKILGPRLEKMVAK QHGKVVMAKV
4155972 16 2.21e-19 NGKNYAEKTA HQAVVVNVGASWCPDCRKIEPIMENLAKT YKGKVEFFKV
15791337 1 2.90e-19 . MTVTLKDFYADWCGPCKTQDPILEELEAD YDEDVSFEKI
1651717 33 5.02e-18 DNFDNLVLQC PKPILVYFGAPWCGLCHFVKPLLNHLHGE WQEQLVCVEV
1729944 17 2.50e-16 DTFKTEVLEG TGYVLVDYFSDGCVPCKALMPAVEELSKK YEGRVVFAKL
19746502 91 2.34e-15 GKTYRLSEFK GKKVYLKFWASWCSICLSTLADTEDLAKM SDKDYVVLTV
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 1 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
16078864 7.3e-28 58_[1]_83
30021713 1.7e-27 75_[1]_87
15805374 2e-27 76_[1]_83
15805225 4e-26 70_[1]_86
17547503 1.7e-25 61_[1]_84
18309723 4.4e-25 284_[1]_90
16761507 4.4e-25 51_[1]_59
135765 4.4e-25 15_[1]_59
7290567 5e-25 19_[1]_63
19705357 1.7e-24 37_[1]_98
20092028 1.9e-24 5_[1]_59
11499727 2.4e-24 15_[1]_61
7109697 3.6e-24 16_[1]_55
267116 4.6e-24 18_[1]_57
1388082 6.7e-24 27_[1]_54
15599256 9.6e-24 24_[1]_236
1633495 1.1e-23 19_[1]_60
15966937 4e-23 59_[1]_242
15605725 4e-23 59_[1]_58
16123427 5e-23 51_[1]_65
23098307 5.6e-23 51_[1]_83
17229859 6.3e-23 20_[1]_59
6687568 8.9e-23 18_[1]_57
15597673 1e-22 155_[1]_94
15218394 1e-22 21_[1]_62
15899007 3e-22 47_[1]_59
15988313 4.2e-22 59_[1]_98
17531233 7.1e-22 26_[1]_60
13358154 7.9e-22 19_[1]_58
1174686 1.1e-21 20_[1]_78
3323237 1.2e-21 17_[1]_59
18406743 1.3e-20 42_[1]_291_[1]_187
15614085 1.6e-21 58_[1]_90
16804867 1.8e-21 17_[1]_60
21222859 2e-21 101_[1]_93
2822332 2.7e-21 32_[1]_58
16759994 2.7e-21 58_[1]_81
140543 5.5e-21 42_[1]_56
15614140 8.2e-21 61_[1]_86
17537401 1.2e-20 25_[1]_95
27375582 1.6e-20 79_[1]_86
15615431 1.8e-20 70_[1]_85
12044976 3.8e-20 17_[1]_56
4200327 6.7e-20 77_[1]_60
4155972 2.2e-19 15_[1]_60
15791337 2.9e-19 [1]_60
1651717 5e-18 32_[1]_65
1729944 2.5e-16 16_[1]_62
19746502 2.3e-15 90_[1]_88
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 1 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 1 width=29 seqs=50
16078864 ( 59) GKKVLLNFWATWCKPCRQEMPAMEKLQKE 1
30021713 ( 76) GKKVILNFWATWCGPCQQEMPDMEAFYKE 1
15805374 ( 77) GKPVVINFWASWCVPCRQEAPLFSKLSQE 1
15805225 ( 71) GRPVVLNFWASWCGPCREEAPLFAKLAAH 1
17547503 ( 62) GQPVVINFWAPWCGPCVEEMPELSALAQE 1
18309723 ( 285) GKTIFLNFWATWCPPCRGEMPYIDELYKE 1
16761507 ( 52) DLPVVIDFWAPWCGPCRNFAPIFEDVAEE 1
135765 ( 16) EGVVLADFWAPWCGPCKMIAPVLEELDQE 1
7290567 ( 20) DKLVVIDFYADWCGPCKIIAPKLDELAQQ 1
19705357 ( 38) GKVVVINFWATWCGYCVEEMPGFEKVYKE 1
20092028 ( 6) MKPMLLDFSATWCGPCRMQKPILEELEKK 1
11499727 ( 16) DKLVVVDFYADWCMPCRYISPILEKLSKE 1
7109697 ( 17) NKKVVVDFYANWCGPCKILGPIFEEVAQD 1
267116 ( 19) HQRVVVDFSAEWCGPCRAIAPVFDKLSNE 1
1388082 ( 28) NKLIVIDFTASWCPPCRMIAPIFNDLAKK 1
15599256 ( 25) HKPVLVDFWADWCAPCKALMPLLAQIAES 1
1633495 ( 20) DGAILVDFWAEWCGPCKMIAPILDEIADE 1
15966937 ( 60) QQPVLVDFWAPWCGPCKQLTPVIEKVVRE 1
15605725 ( 60) GKVLLINFWATWCPPCKEEIPMFKEIYEK 1
16123427 ( 52) DLPMVIDFWAPWCGPCRSFAPIFAETAAE 1
23098307 ( 52) GERVLINFWTTWCPPCRQEMPDMQRFYQD 1
17229859 ( 21) DKVVVVDFTATWCGPCRLVSPLMDQLADE 1
6687568 ( 19) GRLIVVDFFAQWCGPCRNIAPKVEALAKE 1
15597673 ( 156) GRPLVINLWASWCPPCRREMPVLQQAQAE 1
15218394 ( 22) DKPVLVDFYATWCGPCQLMVPILNEVSET 1
15899007 ( 48) NKIVVVDFWAEWCAPCLILAPVIEELAND 1
15988313 ( 60) GKTLLVNLWATWCVPCRKEMPALDELQGK 1
17531233 ( 27) EKIIILDFYATWCGPCKAIAPLYKELATT 1
13358154 ( 20) SKPILIDFYADWCPPCRMLIPVLDSIEKK 1
1174686 ( 21) TQYVVADFYADWCGPCKAIAPMYAQFAKT 1
3323237 ( 18) NPLVIVDFWAPWCGSCKMLGPVLEEVESE 1
18406743 ( 363) GKTILMYFSAHWCPPCRAFTPKLVEVYKQ 1
15614085 ( 59) GDVVILNVWASWCEPCRKEMPALMELQSD 1
16804867 ( 18) HPKILLNFWAEWCAPCRCFWPTLEQFAEM 1
21222859 ( 102) GKVVVLNVWGSWCPPCRAEAKNFEKVYQD 1
2822332 ( 33) NDVVLADFYADWCGPCQMLEPVVETLAEQ 1
16759994 ( 59) ERPVLLYFWASWCGVCRFTTPAVAHLAAE 1
140543 ( 43) NDKLVIDFYATWCGPCKMMQPHLTKLIQA 1
15614140 ( 62) GKGVFLNFWGTYCPPCEREMPHMEKLYGE 1
17537401 ( 26) GKIIGLYFSASWCPPCRAFTPKLKEFFEE 1
18406743 ( 43) GKKIGLYFSAAWCGPCQRFTPQLVEVYNE 1
27375582 ( 80) GKVSLVNVWASWCVPCHDEAPLLTELGKD 1
15615431 ( 71) GQPVILHFFATWCPVCQDEMPSLVKLDKE 1
12044976 ( 18) KKNVIVDFWAAWCGPCKLTSPEFQKAADE 1
4200327 ( 78) ETPVVVDFHAQWCGPCKILGPRLEKMVAK 1
4155972 ( 16) HQAVVVNVGASWCPDCRKIEPIMENLAKT 1
15791337 ( 1) MTVTLKDFYADWCGPCKTQDPILEELEAD 1
1651717 ( 33) PKPILVYFGAPWCGLCHFVKPLLNHLHGE 1
1729944 ( 17) TGYVLVDYFSDGCVPCKALMPAVEELSKK 1
19746502 ( 91) GKKVYLKFWASWCSICLSTLADTEDLAKM 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 1 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 29 n= 13619 bayes= 8.57575 E= 2.4e-621
-307 -432 105 24 -485 245 244 -447 -123 -431 83 153 -129 -26 -235 -84 -26 -433 -461 -356
-323 -445 -10 -128 -502 -26 -191 -453 278 -121 -330 -256 -40 185 99 -248 -28 -441 -465 -370
-91 -296 -491 -418 -344 -172 -280 16 85 15 -196 -92 242 -322 -7 -308 24 110 -379 51
-235 -246 -491 -455 -397 -487 -312 153 -471 -56 48 -432 -441 -405 -376 -160 -122 300 -462 -441
-436 -381 -695 -621 -31 -83 -426 107 -601 199 -233 -539 -598 -492 -521 -455 -393 223 -460 -42
-48 -374 -695 -625 -425 -596 -444 202 -186 165 6 -544 -607 -509 -533 -461 -389 210 -494 -433
-525 -579 298 -425 -689 -405 60 -758 -172 -738 -677 308 -564 -396 -487 -315 -430 -744 -684 181
-507 -364 -614 -603 406 -604 -345 -365 -613 -118 -298 -525 -554 -523 -543 -436 -519 -41 -282 -5
-740 -586 -790 -794 38 -81 61 -626 -751 -568 -542 -597 -750 -589 -627 94 -39 -663 527 291
341 -314 -658 -630 -618 -74 -511 -570 -648 -581 -475 -534 -569 -535 -556 -95 -123 -448 -601 -600
-94 -462 126 25 -521 -388 63 -486 -280 -470 -365 -56 134 43 -272 202 233 -471 -498 -390
-447 -335 -462 -462 -190 -303 -297 -430 -453 -288 -291 -389 -480 -349 -348 -389 -407 -416 607 -90
-484 593 -632 -597 -590 -612 -466 -511 -649 -567 -458 -553 -619 -552 -529 -501 -462 -587 -617 -586
-54 -390 -443 -184 -550 306 -352 -480 -187 -510 -26 -359 199 -389 -395 -117 -385 -26 -509 -476
-312 -425 -182 -432 -527 -457 -328 -174 -423 -227 -420 -422 405 -339 -381 -122 -354 -127 -550 -75
-484 593 -632 -597 -590 -612 -466 -511 -649 -567 -458 -553 -619 -552 -529 -501 -462 -587 -617 -586
-528 -578 -626 -171 -724 -578 152 -591 206 -123 -467 -421 -605 163 344 -453 -461 -107 -572 -521
83 18 -57 25 -48 -160 -158 30 -9 -69 274 13 -377 160 58 -12 -95 -400 -431 -45
-338 -292 -591 205 116 -483 -322 173 -493 94 99 -432 -500 25 -415 -344 24 -68 -379 -321
169 -383 -136 -55 -432 -27 -171 -58 -56 -193 344 -231 -387 -23 -219 31 89 -179 41 -327
-176 -429 -465 -438 -533 -461 -334 -485 -190 -464 -427 -427 418 -345 -387 -300 -360 -471 -556 -511
22 -402 -9 -52 -450 -161 150 159 24 45 83 -61 -379 -19 -61 -79 -95 80 -429 -45
-483 -422 -735 -657 204 -634 -459 14 -638 230 247 -583 -626 -510 -548 -503 -129 0 -471 50
22 -420 103 243 -468 -378 -169 -425 -10 -409 -8 60 -386 96 -216 -14 -25 -53 -443 -342
-41 -418 -7 236 -466 -376 150 -424 174 -408 -302 -63 -385 160 -62 -81 -98 -410 -441 -340
-114 -354 -635 -555 80 -557 -378 44 -539 261 16 -496 -534 -419 -448 -420 -131 99 -421 -379
209 -390 -59 24 -139 -161 65 -149 -222 -390 -286 -222 -381 130 -210 94 -247 -104 -427 252
45 -410 -8 94 -458 -27 -160 -418 202 -401 -295 61 -380 221 -61 -12 -96 -404 -434 -333
-170 -501 108 268 -545 -435 58 -489 91 -473 83 -290 -435 95 -286 -101 58 -469 -520 -416
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 1 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 29 nsites= 50 E= 2.4e-621
0.000000 0.000000 0.140000 0.080000 0.000000 0.420000 0.080000 0.000000 0.020000 0.000000 0.040000 0.120000 0.020000 0.020000 0.000000 0.020000 0.040000 0.000000 0.000000 0.000000
0.000000 0.000000 0.060000 0.020000 0.000000 0.060000 0.000000 0.000000 0.540000 0.040000 0.000000 0.000000 0.040000 0.120000 0.080000 0.000000 0.040000 0.000000 0.000000 0.000000
0.040000 0.000000 0.000000 0.000000 0.000000 0.020000 0.000000 0.060000 0.140000 0.100000 0.000000 0.020000 0.300000 0.000000 0.040000 0.000000 0.060000 0.180000 0.000000 0.040000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.220000 0.000000 0.080000 0.040000 0.000000 0.000000 0.000000 0.000000 0.020000 0.020000 0.620000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.040000 0.040000 0.000000 0.120000 0.000000 0.380000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.400000 0.000000 0.020000
0.060000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.240000 0.020000 0.300000 0.020000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.360000 0.000000 0.000000
0.000000 0.000000 0.520000 0.000000 0.000000 0.000000 0.020000 0.000000 0.020000 0.000000 0.000000 0.340000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.100000
0.000000 0.000000 0.000000 0.000000 0.860000 0.000000 0.000000 0.000000 0.000000 0.040000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.080000 0.000000 0.020000
0.000000 0.000000 0.000000 0.000000 0.060000 0.040000 0.020000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.100000 0.040000 0.000000 0.540000 0.200000
0.920000 0.000000 0.000000 0.000000 0.000000 0.040000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.020000 0.020000 0.000000 0.000000 0.000000
0.040000 0.000000 0.160000 0.080000 0.000000 0.000000 0.020000 0.000000 0.000000 0.000000 0.000000 0.020000 0.140000 0.040000 0.000000 0.220000 0.280000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.020000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.960000 0.020000
0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.060000 0.000000 0.000000 0.020000 0.000000 0.540000 0.000000 0.000000 0.020000 0.000000 0.020000 0.000000 0.240000 0.000000 0.000000 0.020000 0.000000 0.080000 0.000000 0.000000
0.000000 0.000000 0.020000 0.000000 0.000000 0.000000 0.000000 0.020000 0.000000 0.020000 0.000000 0.000000 0.860000 0.000000 0.000000 0.020000 0.000000 0.040000 0.000000 0.020000
0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.020000 0.000000 0.000000 0.040000 0.000000 0.300000 0.040000 0.000000 0.000000 0.000000 0.100000 0.460000 0.000000 0.000000 0.040000 0.000000 0.000000
0.160000 0.020000 0.040000 0.080000 0.040000 0.020000 0.000000 0.080000 0.060000 0.060000 0.160000 0.040000 0.000000 0.100000 0.060000 0.040000 0.020000 0.000000 0.000000 0.020000
0.000000 0.000000 0.000000 0.320000 0.120000 0.000000 0.000000 0.200000 0.000000 0.180000 0.040000 0.000000 0.000000 0.040000 0.000000 0.000000 0.060000 0.040000 0.000000 0.000000
0.300000 0.000000 0.020000 0.040000 0.000000 0.060000 0.000000 0.040000 0.040000 0.020000 0.260000 0.000000 0.000000 0.020000 0.000000 0.060000 0.100000 0.020000 0.020000 0.000000
0.020000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.020000 0.000000 0.000000 0.000000 0.960000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.100000 0.000000 0.060000 0.040000 0.000000 0.020000 0.040000 0.200000 0.080000 0.140000 0.040000 0.020000 0.000000 0.020000 0.020000 0.020000 0.020000 0.160000 0.000000 0.020000
0.000000 0.000000 0.000000 0.000000 0.220000 0.000000 0.000000 0.060000 0.000000 0.460000 0.120000 0.000000 0.000000 0.000000 0.000000 0.000000 0.020000 0.080000 0.000000 0.040000
0.100000 0.000000 0.140000 0.420000 0.000000 0.000000 0.000000 0.000000 0.060000 0.000000 0.020000 0.060000 0.000000 0.060000 0.000000 0.040000 0.040000 0.060000 0.000000 0.000000
0.060000 0.000000 0.060000 0.400000 0.000000 0.000000 0.040000 0.000000 0.260000 0.000000 0.000000 0.020000 0.000000 0.100000 0.020000 0.020000 0.020000 0.000000 0.000000 0.000000
0.040000 0.000000 0.000000 0.000000 0.100000 0.000000 0.000000 0.080000 0.000000 0.560000 0.020000 0.000000 0.000000 0.000000 0.000000 0.000000 0.020000 0.180000 0.000000 0.000000
0.400000 0.000000 0.040000 0.080000 0.020000 0.020000 0.020000 0.020000 0.000000 0.000000 0.000000 0.000000 0.000000 0.080000 0.000000 0.100000 0.000000 0.040000 0.000000 0.180000
0.120000 0.000000 0.060000 0.140000 0.000000 0.060000 0.000000 0.000000 0.320000 0.000000 0.000000 0.060000 0.000000 0.160000 0.020000 0.040000 0.020000 0.000000 0.000000 0.000000
0.020000 0.000000 0.140000 0.480000 0.000000 0.000000 0.020000 0.000000 0.140000 0.000000 0.040000 0.000000 0.000000 0.060000 0.000000 0.020000 0.080000 0.000000 0.000000 0.000000
--------------------------------------------------------------------------------
Time 66.68 secs.
********************************************************************************
********************************************************************************
MOTIF 2 width = 17 sites = 41 llr = 1175 E-value = 7.3e-239
********************************************************************************
--------------------------------------------------------------------------------
Motif 2 Description
--------------------------------------------------------------------------------
Simplified A :::11::24:::::11:
pos.-specific C :::::::::::::a:::
probability D ::::::::41:::::::
matrix E ::::::::::::::::6
F ::1562:::6:2:::::
G ::::1::3:::12::::
H :::::1:::::::::::
I :21:::::1:::1::::
K 1::::::1:::::::1:
L :17::::1:::::::1:
M :::::::::::::::::
N ::::::::::::::::1
P ::::::a::::5::2::
Q ::::::::::::::::2
R :::::::1:::::::1:
S :::11::1::11::2:1
T 1:::::::::9:1:44:
V 661111::::::6::::
W :::::::::1:::::::
Y :::1:4:::::::::::
bits 6.2
5.6 *
5.0 *
4.3 * *
Information 3.7 * * *
content 3.1 * * *
(41.3 bits) 2.5 ** ** *** * *
1.9 ******* ******* *
1.2 *****************
0.6 *****************
0.0 -----------------
Multilevel VVLFFYPGAFTPVCTTE
consensus I D F P
sequence
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 2 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- -----------------
13541053 34 1.14e-19 IRLSSYRGKW VVLFFYPADFTFVCPTE VEGFAEDYEK
9955016 37 2.52e-19 VKLSDYKGKY VVLFFYPLDFTFVCPTE IIAFSNRAED
19173077 32 1.46e-17 ISLQDYIGKY VVLAFYPLDFTFVCPTE INRFSDLKGA
16803644 39 2.64e-17 LEKNIEDDKW TILFFYPMDFTFVCPTE IVAISARSDE
15790738 67 8.20e-17 LTDALADNRA VVLFFYPFDFSPVCATE LCAIQNARWF
15899339 32 1.24e-16 KIPSDFKGKV VVLAFYPAAFTSVCTKE MCTFRDSMAK
14600438 31 1.61e-16 IRLSDFRGRI VVLYFYPRAMTPGCTRE GVRFNELLDE
4433065 16 2.10e-16 IDINEYKGKY VVLLFYPLDWTFVCPTE MIGYSEVAGQ
4996210 34 4.01e-16 DFYKYVGDNW AILFSHPHDFTPVCTTE LAEFGKMHEE
20151112 33 4.55e-16 VTEKDTEGRW SVFFFYPADFTFVCPTE LGDVADHYEE
13541117 32 4.55e-16 RKLSEFRGQN VVLAFFPGAFTSVCTKE MCTFRDSMAN
15807234 32 5.16e-16 TLSSYRGQSH VVLVFYPLDFSPVCSMQ LPEYSGSQDD
3318841 34 6.63e-16 RFHDFLGDSW GILFSHPRDFTPVCTTE LGRAAKLAPE
18313548 34 6.63e-16 LSEVLKRGRP VVLLFFPGAFTSVCTKE LCTFRDKMAL
15613511 30 7.50e-16 VSLSDFKGKN IVLYFYPKDMTPGCTTE ACDFRDRVED
14286173 31 7.50e-16 ELPDEFEGKW FILFSHPADFTPVCTTE FVAFQEVYPE
16501671 37 1.75e-15 NFKQHTNGKT TVLFFWPMDFTFVCPSE LIAFDKRYEE
21674812 31 1.97e-15 VSLSEFKGRK VLLIFYPGDDTPVCTAQ LCDYRNNVAA
5326864 47 5.55e-15 NASKEFANKK VVLFALPGAFTPVCSAN HVPEYIQKLP
15964668 36 1.20e-14 TTELLFKGKR VVLFAVPGAFTPTCSLN HLPGYLENRD
4704732 38 2.05e-14 SVHSIAAGKK VILFGVPGAFTPTCSMS HVPGFIGKAE
15609658 36 2.82e-14 VSLADYRGRR VIVYFYPAASTPGCTKQ ACDFRDNLGD
21112072 35 3.47e-14 DTHTLFTGRK VVLFAVPGAFTPTCSAK HLPGYVEQFE
16125919 56 3.85e-14 NLAKALKKGP VVLYFFPAAYTAGCTAE AREFAEATPE
6322180 94 4.26e-14 LKKITENNRV VVFFVYPRASTPGCTRQ ACGFRDNYQE
21223405 38 1.05e-13 INHKTYEGQW KVVFAWPKDFTFVCPTE IAAFGKLNDE
6850955 34 1.16e-13 FRLSEYLGKW VVLCFYPGDFTFVXATE VSAVAEKYPE
1091044 43 3.68e-13 DFDKEFRDKT VVIVAIPGAFTPTCTAN HIPPFVEKFT
21227878 34 5.85e-13 IHLYDLKGKK VLLSFHPLAWTQVCAQQ MKSLEENYEL
15826629 34 7.69e-13 NLAELFKGKK GVLFGVPGAFTPGCSKT HLPGFVEQAE
15643152 26 1.21e-12 FTHVDLYGKY TILFFFPKAGTSGCTRE AVEFSRENFE
11467494 38 1.72e-12 RLSDYRGKKY VILFFYPANFTAISPTE LMLLSDRISE
15609375 32 3.44e-12 TLRGYRGAKN VLLVFFPLAFTGICQGE LDQLRDHLPE
17229033 37 8.66e-12 TTDDLFAGKT VAVFSLPGAFTPTCSST HLPGYNELAK
13186328 32 3.67e-11 IKEIDLKSNW NVFFFYPYSYSFICPLE LKNISNKIKE
6323138 49 9.94e-11 WSKLISENKK VIITGAPAAFSPTCTVS HIPGYINYLD
15605963 48 5.32e-10 KIVGGAKDVV QVIITVPSLDTPVCETE TKKFNEIMAG
15672286 45 6.58e-10 KIKLSKLEKP VLISVFPDINTRVCSLQ TKHFNLEAAK
15801846 48 1.51e-09 VTLGQFAGKR KVLNIFPSIDTGVCAAS VRKFNQLATE
16330420 73 5.37e-09 ILSEQLKTGP ILLKFFRGYWCPYCGLE LRAYQKVVNK
21283385 47 6.53e-09 VTLADYAGKK KLISVVPSIDTGVCDQQ TRKFNSDASK
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 2 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
13541053 1.1e-19 33_[2]_124
9955016 2.5e-19 36_[2]_144
19173077 1.5e-17 31_[2]_129
16803644 2.6e-17 38_[2]_126
15790738 8.2e-17 66_[2]_129
15899339 1.2e-16 31_[2]_108
14600438 1.6e-16 30_[2]_116
4433065 2.1e-16 15_[2]_101
4996210 4e-16 33_[2]_170
20151112 4.6e-16 32_[2]_137
13541117 4.6e-16 31_[2]_109
15807234 5.2e-16 31_[2]_103
3318841 6.6e-16 33_[2]_174
18313548 6.6e-16 33_[2]_112
15613511 7.5e-16 29_[2]_108
14286173 7.5e-16 30_[2]_162
16501671 1.7e-15 36_[2]_147
21674812 2e-15 30_[2]_101
5326864 5.5e-15 46_[2]_104
15964668 1.2e-14 35_[2]_109
4704732 2.1e-14 37_[2]_108
15609658 2.8e-14 35_[2]_105
21112072 3.5e-14 34_[2]_109
16125919 3.8e-14 55_[2]_105
6322180 4.3e-14 93_[2]_105
21223405 1.1e-13 37_[2]_130
6850955 1.2e-13 33_[2]_153
1091044 3.7e-13 42_[2]_107
21227878 5.9e-13 33_[2]_104
15826629 7.7e-13 33_[2]_111
15643152 1.2e-12 25_[2]_279
11467494 1.7e-12 37_[2]_150
15609375 3.4e-12 31_[2]_105
17229033 8.7e-12 36_[2]_198
13186328 3.7e-11 31_[2]_128
6323138 9.9e-11 48_[2]_111
15605963 5.3e-10 47_[2]_105
15672286 6.6e-10 44_[2]_99
15801846 1.5e-09 47_[2]_104
16330420 5.4e-09 72_[2]_129
21283385 6.5e-09 46_[2]_101
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 2 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 2 width=17 seqs=41
13541053 ( 34) VVLFFYPADFTFVCPTE 1
9955016 ( 37) VVLFFYPLDFTFVCPTE 1
19173077 ( 32) VVLAFYPLDFTFVCPTE 1
16803644 ( 39) TILFFYPMDFTFVCPTE 1
15790738 ( 67) VVLFFYPFDFSPVCATE 1
15899339 ( 32) VVLAFYPAAFTSVCTKE 1
14600438 ( 31) VVLYFYPRAMTPGCTRE 1
4433065 ( 16) VVLLFYPLDWTFVCPTE 1
4996210 ( 34) AILFSHPHDFTPVCTTE 1
20151112 ( 33) SVFFFYPADFTFVCPTE 1
13541117 ( 32) VVLAFFPGAFTSVCTKE 1
15807234 ( 32) VVLVFYPLDFSPVCSMQ 1
3318841 ( 34) GILFSHPRDFTPVCTTE 1
18313548 ( 34) VVLLFFPGAFTSVCTKE 1
15613511 ( 30) IVLYFYPKDMTPGCTTE 1
14286173 ( 31) FILFSHPADFTPVCTTE 1
16501671 ( 37) TVLFFWPMDFTFVCPSE 1
21674812 ( 31) VLLIFYPGDDTPVCTAQ 1
5326864 ( 47) VVLFALPGAFTPVCSAN 1
15964668 ( 36) VVLFAVPGAFTPTCSLN 1
4704732 ( 38) VILFGVPGAFTPTCSMS 1
15609658 ( 36) VIVYFYPAASTPGCTKQ 1
21112072 ( 35) VVLFAVPGAFTPTCSAK 1
16125919 ( 56) VVLYFFPAAYTAGCTAE 1
6322180 ( 94) VVFFVYPRASTPGCTRQ 1
21223405 ( 38) KVVFAWPKDFTFVCPTE 1
6850955 ( 34) VVLCFYPGDFTFVXATE 1
1091044 ( 43) VVIVAIPGAFTPTCTAN 1
21227878 ( 34) VLLSFHPLAWTQVCAQQ 1
15826629 ( 34) GVLFGVPGAFTPGCSKT 1
15643152 ( 26) TILFFFPKAGTSGCTRE 1
11467494 ( 38) VILFFYPANFTAISPTE 1
15609375 ( 32) VLLVFFPLAFTGICQGE 1
17229033 ( 37) VAVFSLPGAFTPTCSST 1
13186328 ( 32) NVFFFYPYSYSFICPLE 1
6323138 ( 49) VIITGAPAAFSPTCTVS 1
15605963 ( 48) QVIITVPSLDTPVCETE 1
15672286 ( 45) VLISVFPDINTRVCSLQ 1
15801846 ( 48) KVLNIFPSIDTGVCAAS 1
16330420 ( 73) ILLKFFRGYWCPYCGLE 1
21283385 ( 47) KLISVVPSIDTGVCDQQ 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 2 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 17 n= 14771 bayes= 10.3384 E= 7.3e-239
-116 -174 -408 -375 -195 -171 -234 8 -125 -248 -201 -175 -362 -145 -296 -176 -32 311 -404 -399
-172 -419 -770 -736 -538 -738 -643 192 -746 63 -364 -680 -715 -687 -692 -630 -459 287 -710 -615
-551 -462 -759 -677 44 -711 -502 101 -667 296 -174 -643 -635 -510 -559 -591 -502 -19 -485 -472
-19 58 -550 -476 311 -448 -277 -1 -157 -62 -161 -74 -463 -358 -379 45 -80 0 -338 173
56 -311 -635 -578 343 7 -395 -99 -566 -361 -283 -475 -515 -452 -479 93 -88 -9 -461 -408
-156 -223 -358 -326 181 -378 244 -136 -338 -109 -193 -283 -354 -271 -262 -207 -279 22 132 404
-480 -568 -613 -598 -677 -593 -479 -645 -587 -619 -587 -579 425 -503 -80 -461 -519 -632 -669 -644
107 -373 -109 -204 -114 187 90 -369 14 48 107 -198 -357 -134 82 57 -223 -361 -403 -20
227 -356 250 -380 -424 -400 -264 32 -396 -165 -285 -42 -480 -319 -372 -79 -313 -340 -451 -17
-440 -304 -15 -525 382 -213 -311 -329 -539 -257 57 -132 -491 -463 -482 -68 -454 -385 171 66
-357 39 -512 -541 -528 -495 -369 -399 -471 -508 -330 -301 -502 -375 -409 98 402 -390 -500 -499
-81 -400 -445 -420 187 -22 -316 -467 -410 -448 -407 -402 344 -56 -93 67 -337 -450 -537 -491
-412 -365 -687 -633 -458 121 -472 50 -625 -348 -302 -558 -611 -538 -553 -468 143 280 -538 -21
-400 591 -545 -508 -503 -535 -389 -425 -557 -480 -374 -469 -538 -468 -447 -330 -379 -498 -537 -503
16 -427 -108 -115 -534 -137 -223 -487 -311 -490 -379 -207 213 -21 -302 185 274 -470 -512 -411
69 -366 -286 -217 -417 -138 -149 -355 73 -5 108 -208 -366 71 81 11 264 -157 -403 -309
-414 -633 -247 306 -696 -466 -319 -603 -136 -588 -493 86 -497 234 -398 49 -11 -566 -665 -538
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 2 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 17 nsites= 41 E= 7.3e-239
0.024390 0.000000 0.000000 0.000000 0.024390 0.048780 0.000000 0.048780 0.073171 0.000000 0.000000 0.024390 0.000000 0.024390 0.000000 0.024390 0.073171 0.634146 0.000000 0.000000
0.024390 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.219512 0.000000 0.146341 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.609756 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.073171 0.000000 0.000000 0.121951 0.000000 0.731707 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.073171 0.000000 0.000000
0.073171 0.024390 0.000000 0.000000 0.487805 0.000000 0.000000 0.048780 0.024390 0.048780 0.000000 0.024390 0.000000 0.000000 0.000000 0.073171 0.024390 0.073171 0.000000 0.097561
0.121951 0.000000 0.000000 0.000000 0.585366 0.073171 0.000000 0.024390 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.097561 0.024390 0.073171 0.000000 0.000000
0.024390 0.000000 0.000000 0.000000 0.195122 0.000000 0.097561 0.024390 0.000000 0.048780 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.146341 0.048780 0.414634
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.975610 0.000000 0.024390 0.000000 0.000000 0.000000 0.000000 0.000000
0.195122 0.000000 0.024390 0.000000 0.024390 0.292683 0.024390 0.000000 0.073171 0.146341 0.048780 0.000000 0.000000 0.000000 0.073171 0.073171 0.000000 0.000000 0.000000 0.024390
0.439024 0.000000 0.390244 0.000000 0.000000 0.000000 0.000000 0.073171 0.000000 0.024390 0.000000 0.024390 0.000000 0.000000 0.000000 0.024390 0.000000 0.000000 0.000000 0.024390
0.000000 0.000000 0.097561 0.000000 0.634146 0.024390 0.000000 0.000000 0.000000 0.000000 0.048780 0.024390 0.000000 0.000000 0.000000 0.048780 0.000000 0.000000 0.073171 0.048780
0.000000 0.024390 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.097561 0.878049 0.000000 0.000000 0.000000
0.048780 0.000000 0.000000 0.000000 0.243902 0.073171 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.487805 0.024390 0.024390 0.097561 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.170732 0.000000 0.073171 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.146341 0.585366 0.000000 0.024390
0.002057 0.951610 0.001551 0.001720 0.001239 0.001669 0.000335 0.001427 0.001751 0.002265 0.000513 0.000965 0.001233 0.000782 0.001003 0.025633 0.001255 0.001999 0.000330 0.000665
0.097561 0.000000 0.024390 0.024390 0.000000 0.024390 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.243902 0.024390 0.000000 0.195122 0.365854 0.000000 0.000000 0.000000
0.146341 0.000000 0.000000 0.000000 0.000000 0.024390 0.000000 0.000000 0.121951 0.097561 0.048780 0.000000 0.000000 0.048780 0.073171 0.048780 0.365854 0.024390 0.000000 0.000000
0.000000 0.000000 0.000000 0.609756 0.000000 0.000000 0.000000 0.000000 0.024390 0.000000 0.000000 0.073171 0.000000 0.170732 0.000000 0.073171 0.048780 0.000000 0.000000 0.000000
--------------------------------------------------------------------------------
Time 130.52 secs.
********************************************************************************
********************************************************************************
MOTIF 3 width = 29 sites = 45 llr = 1514 E-value = 2.2e-254
********************************************************************************
--------------------------------------------------------------------------------
Motif 3 Description
--------------------------------------------------------------------------------
Simplified A 2:::::11:1:612::::2::1::1::::
pos.-specific C :::::::::::::::::::::::::::::
probability D :::3:811:3::::::::::::::::241
matrix E :::::13112::12:2::::::::::::1
F 2:1:::::::::::2:::::::2133:::
G 1::1::::2::::::4::2:::::::1:6
H :::::::1:::::::::::::::::::::
I ::2:1:::::2:1:::4::4::1222:::
K :6::::111:::12:1:1::::::::4::
L 1:111:::::5:::::1::2::3222:::
M :::::::::::::::::::1:1:1:::::
N :::4:::3::::1::1::::::::::12:
P :2::::::1:::::::::::a::::::1:
Q ::::::1:2:::11:1:::::::::::::
R ::::::::11:::1:1:3:::::::::1:
S :::::::1:1:21::::14:::1::::::
T ::::1:1:::1:1::::11::81::::::
V 3:514:::::2:::::5::1::1321:::
W :::::::::::::::::::::::::::::
Y ::::::::::::::6::::::::1:1:::
bits 6.2
5.6
5.0
4.3 *
Information 3.7 *
content 3.1 * * **
(48.5 bits) 2.5 * * * ** *
1.9 *** * ** * * *** *
1.2 ****** **** ****************
0.6 *****************************
0.0 -----------------------------
Multilevel VKVNVDENQDLAxEYGVRSIPTLVFFKDG
consensus PID E KF I GL ILI N
sequence V
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 3 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- -----------------------------
135765 52 2.50e-23 DQEMGDKLKI VKIDVDENQETAGKYGVMSIPTLLVLKDG EVVETSVGFK
7109697 52 2.06e-22 VAQDKKDWTF VKVDVDQANEISSEYEIRSIPTIIFFQDG KMADKRIGFI
2822332 67 2.06e-22 TLAEQTDAAV AKIDVDENQALASAYGVRGVPTLVLFADG EQVEEVVGLQ
11499727 52 2.40e-21 SKEYNGEVEF YKLNVDENQDVAFEYGIASIPTVLFFRNG KVVGGFIGAM
15899007 83 2.81e-21 LANDYPQVAF GKLNTEESQDIAMRYGIMSLPTIMFFKNG ELVDQILGAV
1174686 59 4.48e-21 TFSIPNFLAF AKINVDSVQQVAQHYRVSAMPTFLFFKNG KQVAVNGSVM
6687568 54 1.30e-20 LAKEIPEVEF AKVDVDQNEEAAAKYSVTAMPTFVFIKDG KEVDRFSGAN
12044976 53 1.30e-20 AADEFSDAQF VKVNVDDHTDIAAAYNITSLPTIVVFENG VEKKRAIGFM
7290567 56 2.34e-20 AQQYSDRVVV LKVNVDENEDITVEYNVNSMPTFVFIKGG NVLELFVGCN
20092028 42 3.13e-20 EKKYGDKVEF KVVDVDENQELASKYGIHAVPTLIIQKDG TEVKRFMGVT
1633495 56 4.19e-20 ADEYQGKLTV AKLNIDQNPGTAPKYGIRGIPTLLLFKNG EVAATKVGAL
3323237 54 8.53e-20 ESEVGSGVVI GKLNVDDDQDLAVEFNVASIPTLIVFKDG KEVDRSIGFV
15599256 61 8.53e-20 AESYQGELLL AKVNCDVEQDIVMRFGIRSLPTVVLFKDG QPVDGFAGAQ
1388082 64 8.53e-20 AKKFMSSAIF FKVDVDELQSVAKEFGVEAMPTFVFIKAG EVVDKLVGAN
17531233 62 9.82e-20 LATTHKGIIF CKVDVDEAEDLCSKYDVKMMPTFIFTKNG DAIEALEGCV
16761507 88 5.79e-19 AEERSGKVRF VKVNTEAERELSARFGIRSIPMIMIFKHG QVVDMLNGAV
15791337 37 6.61e-19 EADYDEDVSF EKIDVDEAEDVANEYQVRSIPTIVVENDD GVVERFVGVT
15218394 58 9.80e-19 SETLKDIIAV VKIDTEKYPSLANKYQIEALPTFILFKDG KLWDRFVSFL
4200327 114 1.65e-18 VAKQHGKVVM AKVDIDDHTDLAIEYEVSAVPTVLAMKNG DVVDKFVGIK
16123427 88 1.65e-18 AAERAGKVRF VKVNTEAEPALSTRFRIRSIPTIMLYRNG KMIDMLNGAV
140543 78 5.14e-18 LIQAYPDVRF VKCDVDESPDIAKECEVTAMPTFVLGKDG QLIGKIIGAN
13358154 56 1.07e-17 EKKHGDEFTI IKINVDHFPELSTQYQVKSIPALFYLKNG DIKATSLGFI
17229859 57 3.99e-17 ADEYKGRVKV VKVDVDNNKPLFKRFGLRSIPAVLIFKDG ELTEKIVGVS
16804867 54 4.74e-16 AEMEEGNVQV VKINVDKQRALAQKFDVKGIPNSLVLVDG EIKGAIAGIV
1651717 69 1.70e-15 HGEWQEQLVC VEVNADVNLHLANAYRLKNLPTLILFNRG QVIQRLEDFR
15966937 96 2.09e-15 VREAAGRVKL VKMNIDDHPSIAGQLGIQSIPAVIAFIDG RPVDGFMGAV
23098307 111 2.85e-15 VRFSQELELT FPILLDEKGEVSKAYRISPIPTTYMIDSE GIIRHKSYGA
4155972 52 5.25e-15 AKTYKGKVEF FKVSFDESQDLKESLGIRKIPTLIFYKNA KEVGERLVEP
2649838 32 5.25e-15 MGELNGTVEF EVVDVDEKRELAEKYEVLMLPTLVLADGD EVLGGFMGFA
3261501 53 1.56e-14 SSRKHFDVVH GKVNIETEKDLASIAGVKLLPTLMAFKKG KLVFKQAGIA
15614085 121 4.93e-14 GEFIEELGIT LPVFLDEEGEFADAYQVQHLPMTYVLDRE GIINEVILGE
30021713 139 1.49e-13 SNFIKEKGIT FPVLLDKNIDVTTAYKVITIPTSYFIDTK GVIQDKFIGP
15614140 121 2.81e-13 QRFVDRYGLS FPIVIDKGLNVIDAYGIRPLPTTILINEH GEIVKVHTGG
267116 54 3.07e-13 LSNEFTTFTF VHVDIDKVNTHPIGKEIRSVPTFYFYVNG AKVSEFSGAN
19746502 155 3.66e-13 KWFQGTDYKD LPVLLDPDGKLLEAYGVRSYPTEVFIGSD GVLAKKHIGY
18309723 351 5.20e-13 KNFLKEENHV FPVVLDENGAMVYQYGINAFPSTFIINKE GYITKYIPGA
16759994 115 1.13e-12 ARWLARKGVD FPVVNDANGALSAGWEISVTPTLVVVSQG RVVFTTSGWT
1729944 53 1.23e-12 SKKYEGRVVF AKLNTTGARRLAISQKILGLPTLSLYKDG VKVDEVTKDD
15615431 133 3.09e-12 RAFVQHYRAE FDPLLDTDGEVMETYQVIGIPTTLILDEE GTIVKRYNGV
17537401 90 1.42e-11 FKEHQGEWTY IPFGSDKIMSLMQKYEVKTIPAMRIVNDQ GEVIVQDART
27375582 137 1.67e-11 RFLGRYGNPF GRVGVDANGRASIEWGVYGVPETFVVGRE GTIVYKLVGP
15602312 125 1.02e-10 QALVKKREIS LLVVKDQLKITAERYQLVGTPTSFVIDPE GKILYKFEGL
18406743 265 1.70e-10 QDFKTKPWLA LPFNDKSGSKLARHFMLSTLPTLVILGPD GKTRHSNVAE
18406743 105 7.89e-10 YFRKMPWLAV PFTDSETRDRLDELFKVRGIPNLVMVDDH GKLVNENGVG
18406743 425 9.84e-09 EYYSQMPWLA LPFGDPRKASLAKTFKVGGIPMLAALGPT GQTVTKEARD
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 3 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
135765 2.5e-23 51_[3]_23
7109697 2.1e-22 51_[3]_20
2822332 2.1e-22 66_[3]_24
11499727 2.4e-21 51_[3]_25
15899007 2.8e-21 82_[3]_24
1174686 4.5e-21 58_[3]_40
6687568 1.3e-20 53_[3]_22
12044976 1.3e-20 52_[3]_21
7290567 2.3e-20 55_[3]_27
20092028 3.1e-20 41_[3]_23
1633495 4.2e-20 55_[3]_24
3323237 8.5e-20 53_[3]_23
15599256 8.5e-20 60_[3]_200
1388082 8.5e-20 63_[3]_18
17531233 9.8e-20 61_[3]_25
16761507 5.8e-19 87_[3]_23
15791337 6.6e-19 36_[3]_24
15218394 9.8e-19 57_[3]_26
4200327 1.6e-18 113_[3]_24
16123427 1.6e-18 87_[3]_29
140543 5.1e-18 77_[3]_21
13358154 1.1e-17 55_[3]_22
17229859 4e-17 56_[3]_23
16804867 4.7e-16 53_[3]_24
1651717 1.7e-15 68_[3]_29
15966937 2.1e-15 95_[3]_206
23098307 2.8e-15 110_[3]_24
4155972 5.2e-15 51_[3]_24
2649838 5.2e-15 31_[3]_33
3261501 1.6e-14 52_[3]_43
15614085 4.9e-14 120_[3]_28
30021713 1.5e-13 138_[3]_24
15614140 2.8e-13 120_[3]_27
267116 3.1e-13 53_[3]_22
19746502 3.7e-13 154_[3]_24
18309723 5.2e-13 350_[3]_24
16759994 1.1e-12 114_[3]_25
1729944 1.2e-12 52_[3]_26
15615431 3.1e-12 132_[3]_23
17537401 1.4e-11 89_[3]_31
27375582 1.7e-11 136_[3]_29
15602312 1e-10 124_[3]_22
18406743 9.8e-09 104_[3]_131_[3]_131_[3]_125
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 3 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 3 width=29 seqs=45
135765 ( 52) VKIDVDENQETAGKYGVMSIPTLLVLKDG 1
7109697 ( 52) VKVDVDQANEISSEYEIRSIPTIIFFQDG 1
2822332 ( 67) AKIDVDENQALASAYGVRGVPTLVLFADG 1
11499727 ( 52) YKLNVDENQDVAFEYGIASIPTVLFFRNG 1
15899007 ( 83) GKLNTEESQDIAMRYGIMSLPTIMFFKNG 1
1174686 ( 59) AKINVDSVQQVAQHYRVSAMPTFLFFKNG 1
6687568 ( 54) AKVDVDQNEEAAAKYSVTAMPTFVFIKDG 1
12044976 ( 53) VKVNVDDHTDIAAAYNITSLPTIVVFENG 1
7290567 ( 56) LKVNVDENEDITVEYNVNSMPTFVFIKGG 1
20092028 ( 42) KVVDVDENQELASKYGIHAVPTLIIQKDG 1
1633495 ( 56) AKLNIDQNPGTAPKYGIRGIPTLLLFKNG 1
3323237 ( 54) GKLNVDDDQDLAVEFNVASIPTLIVFKDG 1
15599256 ( 61) AKVNCDVEQDIVMRFGIRSLPTVVLFKDG 1
1388082 ( 64) FKVDVDELQSVAKEFGVEAMPTFVFIKAG 1
17531233 ( 62) CKVDVDEAEDLCSKYDVKMMPTFIFTKNG 1
16761507 ( 88) VKVNTEAERELSARFGIRSIPMIMIFKHG 1
15791337 ( 37) EKIDVDEAEDVANEYQVRSIPTIVVENDD 1
15218394 ( 58) VKIDTEKYPSLANKYQIEALPTFILFKDG 1
4200327 ( 114) AKVDIDDHTDLAIEYEVSAVPTVLAMKNG 1
16123427 ( 88) VKVNTEAEPALSTRFRIRSIPTIMLYRNG 1
140543 ( 78) VKCDVDESPDIAKECEVTAMPTFVLGKDG 1
13358154 ( 56) IKINVDHFPELSTQYQVKSIPALFYLKNG 1
17229859 ( 57) VKVDVDNNKPLFKRFGLRSIPAVLIFKDG 1
16804867 ( 54) VKINVDKQRALAQKFDVKGIPNSLVLVDG 1
1651717 ( 69) VEVNADVNLHLANAYRLKNLPTLILFNRG 1
15966937 ( 96) VKMNIDDHPSIAGQLGIQSIPAVIAFIDG 1
23098307 ( 111) FPILLDEKGEVSKAYRISPIPTTYMIDSE 1
4155972 ( 52) FKVSFDESQDLKESLGIRKIPTLIFYKNA 1
2649838 ( 32) EVVDVDEKRELAEKYEVLMLPTLVLADGD 1
3261501 ( 53) GKVNIETEKDLASIAGVKLLPTLMAFKKG 1
15614085 ( 121) LPVFLDEEGEFADAYQVQHLPMTYVLDRE 1
30021713 ( 139) FPVLLDKNIDVTTAYKVITIPTSYFIDTK 1
15614140 ( 121) FPIVIDKGLNVIDAYGIRPLPTTILINEH 1
267116 ( 54) VHVDIDKVNTHPIGKEIRSVPTFYFYVNG 1
19746502 ( 155) LPVLLDPDGKLLEAYGVRSYPTEVFIGSD 1
18309723 ( 351) FPVVLDENGAMVYQYGINAFPSTFIINKE 1
16759994 ( 115) FPVVNDANGALSAGWEISVTPTLVVVSQG 1
1729944 ( 53) AKLNTTGARRLAISQKILGLPTLSLYKDG 1
15615431 ( 133) FDPLLDTDGEVMETYQVIGIPTTLILDEE 1
17537401 ( 90) IPFGSDKIMSLMQKYEVKTIPAMRIVNDQ 1
27375582 ( 137) GRVGVDANGRASIEWGVYGVPETFVVGRE 1
15602312 ( 125) LLVVKDQLKITAERYQLVGTPTSFVIDPE 1
18406743 ( 265) LPFNDKSGSKLARHFMLSTLPTLVILGPD 1
18406743 ( 105) PFTDSETRDRLDELFKVRGIPNLVMVDDH 1
18406743 ( 425) LPFGDPRKASLAKTFKVGGIPMLAALGPT 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 3 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 29 n= 13619 bayes= 8.61696 E= 2.2e-254
81 47 -567 -75 169 26 -299 -11 -167 54 -171 -408 -123 -369 -391 -320 -272 163 -358 -23
-330 -444 -133 -122 -126 -415 76 -448 294 -193 -330 -263 198 -180 -37 -256 -293 -92 -463 -373
-202 3 -457 -416 -26 -439 -264 132 -427 -23 -23 -385 -169 -354 -333 -315 -106 288 -396 -366
-465 -495 234 -411 -122 -3 -278 -527 -451 -12 -483 321 -537 -373 -455 -90 -392 6 -602 -477
-133 5 -117 -413 -152 -434 -259 89 -211 0 -191 -134 -400 -349 -330 -69 56 270 -386 -353
-402 -451 366 57 -547 -442 -260 -498 -212 -521 -435 -161 -182 -300 -412 -343 -171 -497 -494 -435
7 -395 41 208 -442 -147 79 -402 86 -385 -279 -48 -115 145 -47 1 37 -93 -418 -317
7 -394 5 65 -126 -66 216 -138 4 -108 -279 268 -364 -5 -47 46 -232 -93 -418 -32
-139 -394 -118 38 -442 101 -145 -138 4 -108 5 26 121 264 107 -65 -10 -388 -418 -317
35 -395 200 154 -442 -147 79 -138 -38 -385 -279 -48 -115 -5 71 108 -82 -388 -418 -317
-83 -278 -573 -495 -102 -469 61 135 -475 233 31 -417 -480 -371 -394 -330 34 106 -362 -306
292 22 -210 -400 -173 -236 -307 -171 -216 -218 40 -367 -189 -347 -345 112 -62 -96 -381 -382
7 -394 -44 88 -126 -66 -145 43 64 -385 95 74 -115 110 -47 108 37 -93 -418 -32
96 -395 -278 140 -443 -66 163 -138 138 -188 -279 -204 -364 110 159 1 -10 -388 -418 -317
-164 5 -363 -332 194 -384 34 -282 -185 -117 -200 -289 -360 -84 -268 -213 -286 -302 123 435
-283 -413 -43 109 -463 227 -161 -421 37 -404 5 75 -381 197 107 -70 -250 -407 -437 -335
-549 -455 -845 -812 -560 -801 -760 276 -819 -3 -383 -740 -786 -761 -794 -699 -506 262 -761 -649
-73 -394 -278 -38 -442 -147 79 -51 86 -108 95 26 -364 63 263 108 37 -175 -418 -32
96 -373 -293 -224 -422 136 78 -360 -105 -182 97 -51 -28 -154 -205 263 38 -167 -410 -315
-391 -340 -634 -565 -105 -538 -377 280 -544 136 257 -484 -548 -440 -467 -401 -21 49 -416 -30
-848 -763 -850 -921 -898 -765 -701 -968 -906 -898 -912 -838 430 -810 -799 -797 -833 -962 -797 -827
-19 -324 -498 -190 -518 -525 -357 -385 -456 -498 135 0 -502 -363 -397 -27 385 -381 -490 -489
-317 -271 -570 -168 169 -461 -301 119 -472 175 31 -411 -479 -372 -394 35 130 50 -359 -300
-153 -270 -569 -492 74 -460 -299 172 -471 91 202 -409 -477 -371 -87 -101 -272 174 -358 160
6 -316 -620 -544 229 -512 -350 140 -523 124 113 -462 -526 -418 -443 -374 -322 126 -397 -26
-153 -270 -569 -167 257 -160 -299 172 -470 74 32 -409 -477 -53 -392 -320 -90 24 -358 160
-139 -396 115 -100 -444 24 -146 -139 246 -387 -280 139 -365 -5 24 -65 -234 -93 -419 -318
-140 -399 229 -39 -447 -65 79 -407 -39 -391 -285 246 26 -6 71 1 -83 -393 -423 -321
-181 -492 30 77 -623 325 142 -580 -170 -591 -477 -277 -498 -58 -391 -317 -133 -554 -543 -495
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 3 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 29 nsites= 45 E= 2.2e-254
0.155556 0.022222 0.000000 0.044444 0.177778 0.088889 0.000000 0.044444 0.022222 0.133333 0.000000 0.000000 0.022222 0.000000 0.000000 0.000000 0.000000 0.266667 0.000000 0.022222
0.000000 0.000000 0.022222 0.022222 0.022222 0.000000 0.022222 0.000000 0.600000 0.022222 0.000000 0.000000 0.222222 0.000000 0.022222 0.000000 0.000000 0.044444 0.000000 0.000000
0.000000 0.022222 0.000000 0.000000 0.066667 0.000000 0.000000 0.200000 0.000000 0.111111 0.022222 0.000000 0.022222 0.000000 0.000000 0.000000 0.022222 0.533333 0.000000 0.000000
0.000000 0.000000 0.333333 0.000000 0.022222 0.066667 0.000000 0.000000 0.000000 0.088889 0.000000 0.377778 0.000000 0.000000 0.000000 0.022222 0.000000 0.088889 0.000000 0.000000
0.022222 0.022222 0.044444 0.000000 0.022222 0.000000 0.000000 0.133333 0.022222 0.133333 0.000000 0.022222 0.000000 0.000000 0.000000 0.044444 0.111111 0.422222 0.000000 0.000000
0.000000 0.000000 0.800000 0.133333 0.000000 0.000000 0.000000 0.000000 0.022222 0.000000 0.000000 0.000000 0.022222 0.000000 0.000000 0.000000 0.022222 0.000000 0.000000 0.000000
0.088889 0.000000 0.088889 0.333333 0.000000 0.022222 0.022222 0.000000 0.133333 0.000000 0.000000 0.022222 0.022222 0.088889 0.022222 0.044444 0.066667 0.044444 0.000000 0.000000
0.088889 0.000000 0.066667 0.111111 0.022222 0.044444 0.066667 0.022222 0.066667 0.044444 0.000000 0.288889 0.000000 0.022222 0.022222 0.066667 0.000000 0.044444 0.000000 0.022222
0.022222 0.000000 0.022222 0.088889 0.000000 0.155556 0.000000 0.022222 0.066667 0.044444 0.022222 0.044444 0.133333 0.222222 0.088889 0.022222 0.044444 0.000000 0.000000 0.000000
0.111111 0.000000 0.288889 0.222222 0.000000 0.022222 0.022222 0.022222 0.044444 0.000000 0.000000 0.022222 0.022222 0.022222 0.066667 0.111111 0.022222 0.000000 0.000000 0.000000
0.044444 0.000000 0.000000 0.000000 0.022222 0.000000 0.022222 0.155556 0.000000 0.488889 0.022222 0.000000 0.000000 0.000000 0.000000 0.000000 0.066667 0.177778 0.000000 0.000000
0.555556 0.022222 0.022222 0.000000 0.022222 0.000000 0.000000 0.022222 0.022222 0.022222 0.044444 0.000000 0.022222 0.000000 0.000000 0.155556 0.044444 0.044444 0.000000 0.000000
0.088889 0.000000 0.044444 0.133333 0.022222 0.044444 0.000000 0.088889 0.111111 0.000000 0.044444 0.066667 0.022222 0.066667 0.022222 0.111111 0.066667 0.044444 0.000000 0.022222
0.177778 0.000000 0.000000 0.200000 0.000000 0.044444 0.044444 0.022222 0.200000 0.022222 0.000000 0.000000 0.000000 0.066667 0.133333 0.044444 0.044444 0.000000 0.000000 0.000000
0.022222 0.022222 0.000000 0.000000 0.222222 0.000000 0.000000 0.000000 0.022222 0.044444 0.000000 0.000000 0.000000 0.022222 0.000000 0.000000 0.000000 0.000000 0.044444 0.600000
0.000000 0.000000 0.044444 0.155556 0.000000 0.377778 0.000000 0.000000 0.088889 0.000000 0.022222 0.066667 0.000000 0.133333 0.088889 0.022222 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.400000 0.000000 0.088889 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.511111 0.000000 0.000000
0.044444 0.000000 0.000000 0.044444 0.000000 0.022222 0.022222 0.044444 0.133333 0.044444 0.044444 0.044444 0.000000 0.044444 0.288889 0.111111 0.066667 0.022222 0.000000 0.022222
0.177778 0.000000 0.000000 0.000000 0.000000 0.200000 0.022222 0.000000 0.022222 0.022222 0.044444 0.022222 0.044444 0.000000 0.000000 0.355556 0.066667 0.022222 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.022222 0.000000 0.000000 0.422222 0.000000 0.244444 0.133333 0.000000 0.000000 0.000000 0.000000 0.000000 0.044444 0.111111 0.000000 0.022222
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.088889 0.000000 0.000000 0.022222 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.066667 0.044444 0.000000 0.000000 0.000000 0.022222 0.755556 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.022222 0.177778 0.000000 0.000000 0.133333 0.000000 0.333333 0.022222 0.000000 0.000000 0.000000 0.000000 0.066667 0.133333 0.111111 0.000000 0.000000
0.022222 0.000000 0.000000 0.000000 0.088889 0.000000 0.000000 0.200000 0.000000 0.177778 0.088889 0.000000 0.000000 0.000000 0.022222 0.022222 0.000000 0.288889 0.000000 0.088889
0.088889 0.000000 0.000000 0.000000 0.266667 0.000000 0.000000 0.155556 0.000000 0.222222 0.044444 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.200000 0.000000 0.022222
0.022222 0.000000 0.000000 0.022222 0.333333 0.022222 0.000000 0.200000 0.000000 0.155556 0.022222 0.000000 0.000000 0.022222 0.000000 0.000000 0.022222 0.088889 0.000000 0.088889
0.022222 0.000000 0.155556 0.022222 0.000000 0.088889 0.000000 0.022222 0.444444 0.000000 0.000000 0.111111 0.000000 0.022222 0.044444 0.022222 0.000000 0.044444 0.000000 0.000000
0.022222 0.000000 0.355556 0.044444 0.000000 0.044444 0.022222 0.000000 0.044444 0.000000 0.000000 0.244444 0.066667 0.022222 0.066667 0.044444 0.022222 0.000000 0.000000 0.000000
0.022222 0.000000 0.088889 0.133333 0.000000 0.644444 0.044444 0.000000 0.022222 0.000000 0.000000 0.000000 0.000000 0.022222 0.000000 0.000000 0.022222 0.000000 0.000000 0.000000
--------------------------------------------------------------------------------
Time 188.79 secs.
********************************************************************************
********************************************************************************
MOTIF 4 width = 21 sites = 37 llr = 1031 E-value = 7.8e-153
********************************************************************************
--------------------------------------------------------------------------------
Motif 4 Description
--------------------------------------------------------------------------------
Simplified A 11:31::1::1::1:2::5:3
pos.-specific C :::1:::1::1:::::::::1
probability D :1111::::::81::::::::
matrix E 111:3::::::::12:::1::
F :::::1::1:::::5::::4:
G :13::::5::1:::::::::1
H :::::::::::::1::5::::
I :::1:24:5:1::1::::::1
K 511:1::::::::::::51:1
L :3:::14:1:::1:::11::1
M ::::::::::::::::1::::
N 1:3:::::::12::::111::
P ::::::::::1:141::::::
Q ::::1:::::::::::211::
R :2::::::::1::::::11:1
S :::::::1:9::5::2:1:::
T :::2::::::1:1::1:::::
V ::1226113:4::3:3:::::
W :::::::::::::::::::6:
Y ::::::1:::::::1::::::
bits 6.2
5.6
5.0
4.3 *
Information 3.7 * *
content 3.1 * * * *
(40.2 bits) 2.5 * * * * *
1.9 ***** **** * **
1.2 * *******************
0.6 *********************
0.0 ---------------------
Multilevel KLNAEVLGISVDSPFVHKAWA
consensus G V I V V S F
sequence A
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 4 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- ---------------------
4433065 45 1.59e-19 GYSEVAGQLK EINCEVIGVSVDSVYCHQAWC EADKSKGGVG
9955016 66 5.72e-19 AFSNRAEDFR KLGCEVLGVSVDSQFTHLAWI NTPRKEGGLG
6850955 63 7.15e-18 AVAEKYPEFQ KLGVEVLSVSVDSVFVHKMWN DNELSKMVEG
19173077 61 6.34e-17 RFSDLKGAFL RRNAVVLLISCDSVYTHKAWA SIPREQNGVL
18313548 63 3.76e-16 TFRDKMALLN KANAEVLAISVDSPFALKAFK DANRLNFPLL
20151112 62 6.13e-16 DVADHYEELQ KLGVDVYSVSTDTHFTHKAWH SSSETIAKIK
16501671 66 9.92e-16 AFDKRYEEFQ KRGVEVVGVSFDSEFVHNAWR NTPVDKGGIG
15899339 61 1.59e-15 TFRDSMAKFN EVNAVVIGISVDPPFSNKAFK EQNKINFTIV
21674812 60 3.58e-15 DYRNNVAAFT SRGITVIGISGDSPESHKQFA EKHKLPFLLL
13541053 63 3.58e-15 GFAEDYEKFK KKNTEVISVSEDTVYVHKAWV QYDERVAKAK
15807234 61 7.89e-15 EYSGSQDDFT EAGAVVLGINRDSVYAHRAWA AEYGIEVPLL
11467494 67 1.23e-14 LLSDRISEFR KLSTQILAISVDSPFSHLQYL LCNREEGGLE
13186328 61 1.37e-14 NISNKIKEFK NLNTKIYAISNDSHFVQKNWI ENELKFINFP
4704732 69 3.60e-14 FIGKAEELKS KGIDEIICFSVNDPFVMKAWG KTYPENKHVK
13541117 61 7.49e-14 TFRDSMANFN KFKAKVIGISVDSPFSLAEFA KKNNLTFDLL
4996210 63 9.20e-14 EFGKMHEEFL KLNCKLIGFSCNSKESHDQWI EDIKFYGNLD
21112072 65 1.25e-13 GYVEQFEAFR KRGIEVLCTAVNDPFVMQAWG RSQLVPDGLH
21223405 67 1.53e-13 AFGKLNDEFA DRDAQILGFSGDSEFVHHAWR KDHPDLTDLP
6323138 81 1.69e-13 INYLDELVKE KEVDQVIVVTVDNPFANQAWA KSLGVKDTTH
15801846 75 1.69e-13 VRKFNQLATE IDNTVVLCISADLPFAQSRFC GAEGLNNVIT
14286173 60 3.08e-13 AFQEVYPELR ELDCELVGLSVDQVFSHIKWI EWIAENLDTE
3318841 63 4.55e-13 RAAKLAPEFA KRNVKLIALSIDSVEDHLAWS KDINAYNSEE
21227878 63 5.52e-13 SLEENYELFT ELNTVPLGISVDPIPSKKAWA RELGINHIKL
14600438 60 5.52e-13 RFNELLDEFE KLGAVVIGVSTDSVEKNRKFA EKHGFRFKLV
21283385 73 1.08e-12 QTRKFNSDAS KEEGIVLTISADLPFAQKRWC ASAGLDNVIT
17229033 68 1.43e-12 YNELAKVFKD NGVDEIVCISVNDAFVMNEWA KTQEAENITL
15613511 59 2.74e-12 DFRDRVEDFK GLNTVILGVSPDPVERHKKFI EKYSLPFLLL
16803644 68 6.75e-12 AISARSDEFD ALNARIIGASTDTIHSHLAWT NTPIKEGGIG
15790738 96 6.75e-12 AIQNARWFDC TPGLAVWGISPDSTYAHEAFA DEYALTFPLL
15605963 75 8.06e-12 TKKFNEIMAG MEGVDVTVVSMDLPFAQKRFC ESFNIQNVTV
15643152 51 1.62e-11 REAVEFSREN FEKAQVVGISRDSVEALKRFK EKNDLKVTLL
6322180 122 3.49e-11 CGFRDNYQEL KKYAAVFGLSADSVTSQKKFQ SKQNLPYHLL
1091044 74 1.02e-10 FVEKFTALKS AGVDAVIVLSANDPFVQSAFG KALGVTDEAF
15609375 61 1.30e-10 QLRDHLPEFE NDDSAALAISVGPPPTHKIWA TQSGFTFPLL
15826629 65 2.10e-10 FVEQAEALKA KGVQVVACLSVNDAFVTGEWG RAHKAEGKVR
15672286 72 1.32e-09 TKHFNLEAAK HSEIDFLSISNNTADEQKNWC ATEGVDMTIL
17547503 92 2.18e-08 PELSALAQEQ KARVKFIGIGIDSAANIQAFL GKVPVTYPIA
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 4 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
4433065 1.6e-19 44_[4]_68
9955016 5.7e-19 65_[4]_111
6850955 7.1e-18 62_[4]_120
19173077 6.3e-17 60_[4]_96
18313548 3.8e-16 62_[4]_79
20151112 6.1e-16 61_[4]_104
16501671 9.9e-16 65_[4]_114
15899339 1.6e-15 60_[4]_75
21674812 3.6e-15 59_[4]_68
13541053 3.6e-15 62_[4]_91
15807234 7.9e-15 60_[4]_70
11467494 1.2e-14 66_[4]_117
13186328 1.4e-14 60_[4]_95
4704732 3.6e-14 68_[4]_73
13541117 7.5e-14 60_[4]_76
4996210 9.2e-14 62_[4]_137
21112072 1.2e-13 64_[4]_75
21223405 1.5e-13 66_[4]_97
6323138 1.7e-13 80_[4]_75
15801846 1.7e-13 74_[4]_73
14286173 3.1e-13 59_[4]_129
3318841 4.5e-13 62_[4]_141
21227878 5.5e-13 62_[4]_71
14600438 5.5e-13 59_[4]_83
21283385 1.1e-12 72_[4]_71
17229033 1.4e-12 67_[4]_163
15613511 2.7e-12 58_[4]_75
16803644 6.7e-12 67_[4]_93
15790738 6.7e-12 95_[4]_96
15605963 8.1e-12 74_[4]_74
15643152 1.6e-11 50_[4]_250
6322180 3.5e-11 121_[4]_73
1091044 1e-10 73_[4]_72
15609375 1.3e-10 60_[4]_72
15826629 2.1e-10 64_[4]_76
15672286 1.3e-09 71_[4]_68
17547503 2.2e-08 91_[4]_62
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 4 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 4 width=21 seqs=37
4433065 ( 45) EINCEVIGVSVDSVYCHQAWC 1
9955016 ( 66) KLGCEVLGVSVDSQFTHLAWI 1
6850955 ( 63) KLGVEVLSVSVDSVFVHKMWN 1
19173077 ( 61) RRNAVVLLISCDSVYTHKAWA 1
18313548 ( 63) KANAEVLAISVDSPFALKAFK 1
20151112 ( 62) KLGVDVYSVSTDTHFTHKAWH 1
16501671 ( 66) KRGVEVVGVSFDSEFVHNAWR 1
15899339 ( 61) EVNAVVIGISVDPPFSNKAFK 1
21674812 ( 60) SRGITVIGISGDSPESHKQFA 1
13541053 ( 63) KKNTEVISVSEDTVYVHKAWV 1
15807234 ( 61) EAGAVVLGINRDSVYAHRAWA 1
11467494 ( 67) KLSTQILAISVDSPFSHLQYL 1
13186328 ( 61) NLNTKIYAISNDSHFVQKNWI 1
4704732 ( 69) KGIDEIICFSVNDPFVMKAWG 1
13541117 ( 61) KFKAKVIGISVDSPFSLAEFA 1
4996210 ( 63) KLNCKLIGFSCNSKESHDQWI 1
21112072 ( 65) KRGIEVLCTAVNDPFVMQAWG 1
21223405 ( 67) DRDAQILGFSGDSEFVHHAWR 1
6323138 ( 81) KEVDQVIVVTVDNPFANQAWA 1
15801846 ( 75) IDNTVVLCISADLPFAQSRFC 1
14286173 ( 60) ELDCELVGLSVDQVFSHIKWI 1
3318841 ( 63) KRNVKLIALSIDSVEDHLAWS 1
21227878 ( 63) ELNTVPLGISVDPIPSKKAWA 1
14600438 ( 60) KLGAVVIGVSTDSVEKNRKFA 1
21283385 ( 73) KEEGIVLTISADLPFAQKRWC 1
17229033 ( 68) NGVDEIVCISVNDAFVMNEWA 1
15613511 ( 59) GLNTVILGVSPDPVERHKKFI 1
16803644 ( 68) ALNARIIGASTDTIHSHLAWT 1
15790738 ( 96) TPGLAVWGISPDSTYAHEAFA 1
15605963 ( 75) MEGVDVTVVSMDLPFAQKRFC 1
15643152 ( 51) FEKAQVVGISRDSVEALKRFK 1
6322180 ( 122) KKYAAVFGLSADSVTSQKKFQ 1
1091044 ( 74) AGVDAVIVLSANDPFVQSAFG 1
15609375 ( 61) NDDSAALAISVGPPPTHKIWA 1
15826629 ( 65) KGVQVVACLSVNDAFVTGEWG 1
15672286 ( 72) HSEIDFLSISNNTADEQKNWC 1
17547503 ( 92) KARVKFIGIGIDSAANIQAFL 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 4 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 21 n= 14387 bayes= 8.76477 E= 7.8e-153
-49 -371 -94 88 -103 -124 103 -115 254 -362 29 97 -340 -116 -23 -41 -59 -364 -394 -293
-4 -365 -21 61 -102 48 -124 -113 -15 144 -251 -183 -91 -119 182 -42 -210 -149 -392 -293
-250 -377 29 -16 -426 175 -128 -115 -16 -370 -264 282 -348 -125 -25 -43 -216 22 -403 -8
155 259 58 -433 -298 -135 -264 57 -416 -113 -151 -366 -445 -26 -350 -74 154 97 -336 -276
30 -389 30 181 -437 -346 -138 -115 87 -377 -271 -196 -354 169 -27 -183 -63 118 -412 -311
-114 -176 -411 -377 -106 -416 -236 95 -397 -100 -199 -361 -186 -334 -298 -298 -174 309 -403 -396
-129 -249 -548 -471 -76 -440 -279 247 -450 191 -148 -389 -456 -350 -372 -300 -66 48 87 90
75 303 -698 -683 -624 278 -524 -553 -701 -176 -485 -535 -537 -544 -584 112 -79 -3 -620 -599
-179 -330 -545 -521 23 -527 -391 311 -495 37 -154 -439 -533 -429 -450 -386 -110 152 -433 -359
-150 -225 -414 -463 -444 -177 -295 -433 -392 -448 -329 -72 -390 -348 -321 398 57 -463 -427 -371
-25 72 -414 -213 -167 -141 -233 13 -393 -241 -34 -66 -97 -326 -61 -291 -10 286 -388 -370
-474 -516 357 -342 -640 -125 -256 -658 -444 -658 -589 218 -527 -363 -449 -286 -398 -652 -613 -483
-338 -346 86 -347 -516 -361 -234 -505 -354 -48 -400 -22 79 -33 -332 335 109 -521 -499 -403
25 -333 -330 -36 -388 -377 179 -20 -108 -323 -239 -255 275 -8 -236 -217 -72 161 -398 -319
-141 -363 -105 106 319 -386 105 -386 -294 -376 -296 -229 -9 -219 -275 -239 -83 -392 -300 249
119 55 -95 -77 -417 -333 -124 -373 -76 -360 -255 -24 -343 -119 -24 208 97 148 -395 -294
-381 -314 -338 -352 -322 -420 536 -159 -172 -75 127 67 -407 201 -186 -248 -119 -396 -300 -102
-115 -371 -95 -76 -419 -124 103 -115 247 5 -256 49 -341 168 47 24 -209 -364 -395 -293
241 -406 -301 25 -463 -371 -153 -115 66 -395 30 47 -382 134 137 -210 -249 -401 -426 -331
-710 -548 -757 -758 277 -718 -267 -587 -713 -527 -503 -561 -711 -549 -587 -593 -632 -625 546 60
150 282 -275 -206 -390 48 101 101 24 -78 -232 -29 -353 12 44 -46 -60 -140 -383 -290
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 4 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 21 nsites= 37 E= 7.8e-153
0.054054 0.000000 0.027027 0.135135 0.027027 0.027027 0.027027 0.027027 0.486486 0.000000 0.027027 0.081081 0.000000 0.000000 0.027027 0.027027 0.027027 0.000000 0.000000 0.000000
0.081081 0.000000 0.054054 0.108108 0.027027 0.108108 0.000000 0.027027 0.054054 0.297297 0.000000 0.000000 0.027027 0.000000 0.162162 0.027027 0.000000 0.027027 0.000000 0.000000
0.000000 0.000000 0.081081 0.054054 0.000000 0.270270 0.000000 0.027027 0.054054 0.000000 0.000000 0.324324 0.000000 0.000000 0.027027 0.027027 0.000000 0.108108 0.000000 0.027027
0.270270 0.108108 0.108108 0.000000 0.000000 0.027027 0.000000 0.081081 0.000000 0.027027 0.000000 0.000000 0.000000 0.027027 0.000000 0.027027 0.162162 0.162162 0.000000 0.000000
0.108108 0.000000 0.081081 0.270270 0.000000 0.000000 0.000000 0.027027 0.135135 0.000000 0.000000 0.000000 0.000000 0.108108 0.027027 0.000000 0.027027 0.216216 0.000000 0.000000
0.027027 0.000000 0.000000 0.000000 0.054054 0.000000 0.000000 0.189189 0.000000 0.081081 0.000000 0.000000 0.027027 0.000000 0.000000 0.000000 0.000000 0.621622 0.000000 0.000000
0.027027 0.000000 0.000000 0.000000 0.027027 0.000000 0.000000 0.351351 0.000000 0.378378 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.027027 0.108108 0.027027 0.054054
0.135135 0.135135 0.000000 0.000000 0.000000 0.486486 0.000000 0.000000 0.000000 0.027027 0.000000 0.000000 0.000000 0.000000 0.000000 0.108108 0.027027 0.081081 0.000000 0.000000
0.027027 0.000000 0.000000 0.000000 0.081081 0.000000 0.000000 0.459459 0.000000 0.135135 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.027027 0.270270 0.000000 0.000000
0.027027 0.000000 0.000000 0.000000 0.000000 0.027027 0.000000 0.000000 0.000000 0.000000 0.000000 0.027027 0.000000 0.000000 0.000000 0.891892 0.027027 0.000000 0.000000 0.000000
0.108108 0.054054 0.000000 0.027027 0.027027 0.054054 0.000000 0.054054 0.000000 0.000000 0.027027 0.054054 0.054054 0.000000 0.054054 0.000000 0.081081 0.405405 0.000000 0.000000
0.000000 0.000000 0.783784 0.000000 0.000000 0.027027 0.000000 0.000000 0.000000 0.000000 0.000000 0.189189 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.135135 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.081081 0.000000 0.027027 0.108108 0.027027 0.000000 0.513514 0.108108 0.000000 0.000000 0.000000
0.108108 0.000000 0.000000 0.054054 0.000000 0.000000 0.054054 0.054054 0.027027 0.000000 0.000000 0.000000 0.351351 0.027027 0.000000 0.000000 0.027027 0.297297 0.000000 0.000000
0.027027 0.000000 0.027027 0.162162 0.540541 0.000000 0.027027 0.000000 0.000000 0.000000 0.000000 0.000000 0.054054 0.000000 0.000000 0.000000 0.027027 0.000000 0.000000 0.135135
0.216216 0.027027 0.027027 0.027027 0.000000 0.000000 0.000000 0.000000 0.027027 0.000000 0.000000 0.027027 0.000000 0.000000 0.027027 0.243243 0.108108 0.270270 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.486486 0.027027 0.027027 0.081081 0.081081 0.081081 0.000000 0.189189 0.000000 0.000000 0.027027 0.000000 0.000000 0.000000
0.027027 0.000000 0.027027 0.027027 0.000000 0.027027 0.027027 0.027027 0.459459 0.108108 0.000000 0.054054 0.000000 0.108108 0.054054 0.054054 0.000000 0.000000 0.000000 0.000000
0.513514 0.000000 0.000000 0.081081 0.000000 0.000000 0.000000 0.027027 0.108108 0.000000 0.027027 0.054054 0.000000 0.081081 0.108108 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.351351 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.621622 0.027027
0.270270 0.135135 0.000000 0.000000 0.000000 0.108108 0.027027 0.135135 0.081081 0.054054 0.000000 0.027027 0.000000 0.027027 0.054054 0.027027 0.027027 0.027027 0.000000 0.000000
--------------------------------------------------------------------------------
Time 241.79 secs.
********************************************************************************
********************************************************************************
MOTIF 5 width = 50 sites = 13 llr = 1029 E-value = 2.9e-120
********************************************************************************
--------------------------------------------------------------------------------
Motif 5 Description
--------------------------------------------------------------------------------
Simplified A 1:1::51:2::::11:::::2::::221::::1::1:::::71:::22::
pos.-specific C :::::11:1:::::::::::::::::::1:::::::::::::::::::2:
probability D :32:::1::::::6:4:::::::::32::::1:51:::::2::::12:::
matrix E 344::1:::::::::2:2:::12:::11:::1::9:::::2:::::2511
F ::::1:1:::811:::::::1:::::::::::1:::::::::2:2:::::
G 12:8::::5::::11:6:::1:::::11:a:::::::::::::::22::3
H ::::1:::::::::::::::2:::111::::::::::::::::::1::3:
I ::::1:::::156::::55::412:1::3:::3::41:141:2::2::::
K 21::::::::::::2222:3:::::::::::::1:::11:2:::::1:11
L ::1:2:2::3:21:::2:2:1:121:312::::::28:24::5:2::2::
M ::1:::1:::::::::::::::1::::::::::::1::2::1::::::::
N ::1:2:1::::::2:21:::::1:3112:::5:1::::1::::::12:2:
P 2:12:1:1::::::5::::::::::2:2::::11:::::::::::::::5
Q ::::::2:::::::11:::411::::1::::::1::::1:2::8::::::
R :1:::::9:1:::::::::3::::::::::a::::::9::1::1::1::1
S ::::::::21:::1:::1:::111:::2:::312:::::::2::1:::::
T 2:11:2:::2:::::::::::22:2::22:::1::2:::::::122:21:
V ::::3:1:13122::::13::1351:::3:::3::21:42::::12::::
W ::::::::::::::::::::::::::::::::::::::::::::::::::
Y ::::::1:::::::::::::32:121::::::::::::::::::2:::::
bits 6.2
5.6
5.0
4.3 * * * *
Information 3.7 * * ** * * *
content 3.1 * * * * *** * * * *
(114.2 bits) 2.5 * * ***** * ** * *** * ** * * * **
1.9 * *** *************** *** **** ************ ***
1.2 **************************************************
0.6 **************************************************
0.0 --------------------------------------------------
Multilevel EEEGVALRGLFIIDPDGIIQYIVVNDLPIGRNIDEILRVIDALQFTDEHP
consensus KD LT AV VV KN VKA TP V SV LKSF LV LCG
sequence N T R Y VQ Y N
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 5 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- --------------------------------------------------
16803644 121 5.68e-41 QVASDYGVLI EEEGVALRGLFIINPKGEIQYEVVHHNNIGREVDEVLRVLQALQTGGLCP INWQPGEKTI
16501671 119 2.15e-40 EIQKAYGIEH PDEGVALRGSFLIDANGIVRHQVVNDLPLGRNIDEMLRMVDALQFHEEHG DVCPAQWEKG
13541053 113 3.96e-39 IIARAYDVYN EETGNAQRGLFIINPDGIVKYVVITDDNVGRSTDETLRVLEALQSGGLCP VNWHEGEPTL
9955016 119 7.82e-38 RLSEDYGVLK TDEGIAYRGLFIIDGKGVLRQITVNDLPVGRSVDEALRLVQAFQYTDEHG EVCPAGWKPG
11467494 119 2.81e-37 QTITRDYQVL TDEGLAFPGLFIIDKEGIIQYYTVNNLLCGRNINELLRILESIQYVKENP GYACPVNWNF
6850955 116 5.66e-34 NVGTLYGVYD PEAGVENRGRFLIDPDGIIQGYEVLILPVGRNVSETLRQIQAFQLVRETK GAEVAPSGWK
21223405 116 9.87e-34 HELMRDLGIE GEDGFAQRAVFIVDQNNEIQFTMVTAGSVGRNPKEVLRVLDALQTDELCP CNWSKGDETL
13186328 109 1.48e-32 KISNNFNILN KKDGNCLRSTIIIDKNLIIKYINIVDDSIGRSIDEILKNIKMLQFINTNE NKLCPYSWNN
20151112 112 3.57e-32 ALTRNFDNMR EDEGLADRATFVVDPQGIIQAIEVTAEGIGRDASDLLRKIKAAQYVAAHP GEVCPAKWKE
4996210 122 2.00e-31 KIMDEKEKDI KGLPLTCRCVFFISPDKKVKATVLYPATTGRNSQEILRVLKSLQLTNTHP VATPVNWKEG
14286173 112 6.53e-29 VADTLGLIHP ARPTNTVRAVFVVDPEGIIRAILYYPQELGRNIPEIVRMIRAFRVIDAEG VAAPANWPDN
19173077 114 3.86e-28 ELCNQFGLYD EENGHPMRSTVILAKDLSVRHISSNYHAIGRSVDEIIRLIDAITFNDENG DICPAEWRSE
3318841 125 8.83e-27 GMLDPAEKDE KGMPVTARVVFVFGPDKKLKLSILYPATTGRNFDEILRVVISLQLTAEKR VATPVDWKDG
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 5 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
16803644 5.7e-41 120_[5]_11
16501671 2.2e-40 118_[5]_32
13541053 4e-39 112_[5]_12
9955016 7.8e-38 118_[5]_29
11467494 2.8e-37 118_[5]_36
6850955 5.7e-34 115_[5]_38
21223405 9.9e-34 115_[5]_19
13186328 1.5e-32 108_[5]_18
20151112 3.6e-32 111_[5]_25
4996210 2e-31 121_[5]_49
14286173 6.5e-29 111_[5]_48
19173077 3.9e-28 113_[5]_14
3318841 8.8e-27 124_[5]_50
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 5 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 5 width=50 seqs=13
16803644 ( 121) EEEGVALRGLFIINPKGEIQYEVVHHNNIGREVDEVLRVLQALQTGGLCP 1
16501671 ( 119) PDEGVALRGSFLIDANGIVRHQVVNDLPLGRNIDEMLRMVDALQFHEEHG 1
13541053 ( 113) EETGNAQRGLFIINPDGIVKYVVITDDNVGRSTDETLRVLEALQSGGLCP 1
9955016 ( 119) TDEGIAYRGLFIIDGKGVLRQITVNDLPVGRSVDEALRLVQAFQYTDEHG 1
11467494 ( 119) TDEGLAFPGLFIIDKEGIIQYYTVNNLLCGRNINELLRILESIQYVKENP 1
6850955 ( 116) PEAGVENRGRFLIDPDGIIQGYEVLILPVGRNVSETLRQIQAFQLVRETK 1
21223405 ( 116) GEDGFAQRAVFIVDQNNEIQFTMVTAGSVGRNPKEVLRVLDALQTDELCP 1
13186328 ( 109) KKDGNCLRSTIIIDKNLIIKYINIVDDSIGRSIDEILKNIKMLQFINTNE 1
20151112 ( 112) EDEGLADRATFVVDPQGIIQAIEVTAEGIGRDASDLLRKIKAAQYVAAHP 1
4996210 ( 122) KGLPLTCRCVFFISPDKKVKATVLYPATTGRNSQEILRVLKSLQLTNTHP 1
14286173 ( 112) ARPTNTVRAVFVVDPEGIIRAILYYPQELGRNIPEIVRMIRAFRVIDAEG 1
19173077 ( 114) EENGHPMRSTVILAKDLSVRHISSNYHAIGRSVDEIIRLIDAITFNDENG 1
3318841 ( 125) KGMPVTARVVFVFGPDKKLKLSILYPATTGRNFDEILRVVISLQLTAEKR 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 5 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 50 n= 11603 bayes= 10.3312 E= 2.9e-120
-9 -287 -140 182 -338 -12 -37 -293 139 -277 -172 -90 112 -24 -81 -81 124 -277 -313 -211
-256 -472 206 241 -524 86 -168 -434 9 -419 -320 -173 -343 -88 71 -205 -255 -400 -492 -376
-8 -271 92 203 -319 -232 -24 -273 -81 -55 140 84 20 -14 -71 -68 49 -260 -296 -195
-218 -300 -318 -381 -497 357 -265 -471 -378 -507 -375 -233 42 -347 -308 -200 -45 -433 -398 -398
-177 -133 -426 -349 45 -322 210 68 -329 117 -31 209 -339 -230 -252 -183 -135 169 -218 -157
276 174 -389 -40 -384 -214 -253 -322 -353 -336 -236 -294 0 -273 -299 -77 159 -227 -374 -353
-10 185 -12 -251 41 -295 -106 -77 -239 109 168 63 -309 183 -193 -147 -124 18 -217 133
-399 -295 -491 -486 -523 -433 -154 -445 -192 -438 -384 -333 -66 -231 445 -349 -387 -530 -333 -408
149 215 -539 -538 -523 265 -392 -479 -558 -497 -388 -389 -400 -408 -445 159 -239 -16 -501 -491
-174 -137 -399 -325 -188 -314 -153 -68 -293 147 -41 -252 -334 -211 60 46 188 166 -227 -167
-358 -218 -473 -460 405 -467 -308 -104 -478 -160 -171 -408 -412 -414 -425 -292 -381 -155 -190 -42
-325 -278 -442 -433 -85 -457 -327 342 -403 15 -51 -350 -458 -348 -370 -312 -256 104 -357 -281
-322 -277 -432 -425 -109 -450 -321 349 -394 -22 -47 -341 -452 -342 -362 -304 -250 99 -355 -276
-148 -353 358 -137 -459 -121 -159 -431 -373 -456 -373 87 -437 -276 -334 -64 -321 -436 -410 -342
-49 -305 -319 -282 -407 -60 -187 -357 82 -336 -290 -269 363 53 -219 -169 -227 -343 -420 -367
-265 -430 240 134 -503 -290 -141 -443 89 -429 -332 230 -346 120 -232 -175 -243 -415 -476 -352
-248 -332 -261 -312 -477 338 -194 -438 16 -39 -343 22 -397 -245 -203 -197 -306 -425 -386 -358
-203 -221 -256 68 -266 -315 -124 295 65 -148 -91 -194 -327 -123 -146 27 -164 15 -291 -216
-340 -282 -480 -470 -309 -491 -370 334 -442 31 -86 -388 -490 -389 -411 -350 -275 146 -400 -319
-357 -406 -452 -294 -552 -406 -123 -419 210 -382 -295 -248 -433 335 282 -281 -289 -420 -400 -349
22 -152 -282 -248 134 -104 252 -198 -257 -88 -119 -206 -282 6 -186 -134 -201 -218 -61 397
-162 -154 -289 -8 -200 -287 -104 235 -208 -130 -51 -186 -301 100 -171 48 129 15 -231 203
-165 -136 -351 69 -186 -303 -131 61 -265 0 169 60 -317 -180 -210 43 130 170 -223 -161
-168 -146 -422 -364 -224 -356 -191 121 -357 37 -76 -303 -351 -269 -273 7 -149 267 -272 83
-177 -166 -294 -234 -162 -296 213 -107 -220 -11 -69 249 -312 -146 -182 -144 182 8 -213 272
60 -264 181 -99 -313 -230 214 0 -97 -259 -158 89 171 -33 -85 -73 -117 -258 -299 105
61 -270 92 35 -319 -12 214 -278 -80 117 -156 88 -239 127 -69 -64 -108 -264 -295 -193
-8 -262 -150 29 -313 -15 -21 -269 -81 -55 -152 159 170 -18 -69 134 123 -257 -292 -192
-267 191 -514 -455 -275 -434 -288 243 -438 63 -111 -376 -444 -350 -371 -299 126 182 -343 -276
-317 -393 -382 -446 -554 379 -324 -540 -440 -569 -446 -303 -473 -415 -368 -294 -423 -519 -446 -453
-509 -400 -575 -587 -605 -506 -267 -558 -312 -541 -497 -442 -491 -345 455 -455 -491 -631 -435 -496
-343 -387 42 4 -510 -238 -101 -515 -293 -528 -450 370 -384 -211 -304 232 -249 -526 -481 -350
-26 -136 -410 -346 16 -330 -168 215 -331 -112 -44 -275 -5 -239 -254 17 31 197 -238 -181
-266 -348 307 -145 -434 -254 -99 -411 -19 -405 -309 96 3 87 -210 115 -218 -402 -405 -297
-503 -534 -197 377 -630 -518 -368 -532 -562 -614 -522 -396 -620 -324 -510 -481 -507 -579 -566 -549
-69 -190 -435 -390 -227 -378 -227 298 -365 42 129 -307 -390 -283 -304 -237 74 90 -279 -213
-364 -284 -538 -454 -210 -506 -297 17 -445 310 -18 -427 -427 -304 -340 -371 -312 -43 -327 -303
-369 -272 -462 -426 -500 -409 -117 -410 -60 -401 -341 -292 -373 -178 442 -314 -346 -488 -306 -374
-168 -132 -389 -315 -183 -313 -147 66 -24 66 251 57 -327 89 -229 -172 -128 200 -222 -162
-382 -296 -637 -601 -323 -594 -481 271 -592 188 -148 -526 -578 -502 -542 -477 -335 152 -471 -409
-180 -319 150 116 -372 -270 -60 1 145 -301 -197 -121 -276 251 90 -112 -152 -302 -338 -240
305 -93 -418 -377 -369 -194 -278 -311 -390 -323 98 -325 -413 -312 -317 152 -194 -196 -357 -356
-42 -299 -605 -525 184 -527 -336 125 -511 256 -43 -470 -487 -365 -411 -401 -326 -204 -330 -303
-279 -283 -379 -139 -439 -419 64 -361 -274 -278 -140 -214 -324 466 -62 -241 -131 -382 -297 -357
-181 -140 -366 -313 182 -318 -11 -95 -306 89 -58 -248 -319 -220 -230 26 106 -2 -142 320
-161 -189 4 -164 -240 73 212 110 -159 -174 -89 78 -282 -89 -136 -105 181 118 -258 -181
62 -290 149 101 -343 76 -35 -304 28 -287 -182 168 -257 -34 83 -78 -127 -289 -318 -214
70 -301 -153 255 -385 -318 -170 -278 -216 100 -217 -218 -335 -107 -223 -180 132 -277 -394 -311
-210 339 -145 20 -382 -237 412 -348 24 -333 -232 229 -297 -76 -115 -102 49 -337 -355 -242
-220 -329 -266 -15 -426 152 -139 -367 3 -345 -277 -196 327 -132 67 -172 -223 -356 -403 -332
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 5 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 50 nsites= 13 E= 2.9e-120
0.076923 0.000000 0.000000 0.307692 0.000000 0.076923 0.000000 0.000000 0.230769 0.000000 0.000000 0.000000 0.153846 0.000000 0.000000 0.000000 0.153846 0.000000 0.000000 0.000000
0.000000 0.000000 0.307692 0.384615 0.000000 0.153846 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000
0.076923 0.000000 0.153846 0.384615 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.076923 0.076923 0.076923 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.769231 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.153846 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.076923 0.076923 0.000000 0.230769 0.000000 0.230769 0.000000 0.000000 0.000000 0.000000 0.000000 0.307692 0.000000 0.000000
0.538462 0.076923 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000 0.000000
0.076923 0.076923 0.076923 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.230769 0.076923 0.076923 0.000000 0.153846 0.000000 0.000000 0.000000 0.076923 0.000000 0.076923
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.923077 0.000000 0.000000 0.000000 0.000000 0.000000
0.230769 0.076923 0.000000 0.000000 0.000000 0.461538 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.153846 0.000000 0.076923 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.307692 0.000000 0.000000 0.000000 0.000000 0.076923 0.076923 0.230769 0.307692 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.846154 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.538462 0.000000 0.153846 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.615385 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000
0.076923 0.000000 0.615385 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.153846 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000
0.076923 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.230769 0.000000 0.000000 0.000000 0.538462 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.384615 0.153846 0.000000 0.000000 0.000000 0.000000 0.153846 0.000000 0.000000 0.230769 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.615385 0.000000 0.000000 0.153846 0.153846 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.153846 0.000000 0.000000 0.000000 0.538462 0.153846 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.076923 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.538462 0.000000 0.153846 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.307692 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.307692 0.000000 0.000000 0.000000 0.000000 0.384615 0.307692 0.000000 0.000000 0.000000 0.000000 0.000000
0.230769 0.000000 0.000000 0.000000 0.076923 0.076923 0.153846 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.307692
0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.384615 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.076923 0.153846 0.076923 0.000000 0.153846
0.000000 0.000000 0.000000 0.153846 0.000000 0.000000 0.000000 0.076923 0.000000 0.076923 0.076923 0.076923 0.000000 0.000000 0.000000 0.076923 0.153846 0.307692 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.153846 0.000000 0.153846 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.538462 0.000000 0.076923
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.076923 0.000000 0.307692 0.000000 0.000000 0.000000 0.000000 0.230769 0.076923 0.000000 0.230769
0.153846 0.000000 0.307692 0.000000 0.000000 0.000000 0.076923 0.076923 0.000000 0.000000 0.000000 0.076923 0.230769 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923
0.153846 0.000000 0.153846 0.076923 0.000000 0.076923 0.076923 0.000000 0.000000 0.307692 0.000000 0.076923 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.076923 0.000000 0.000000 0.076923 0.000000 0.076923 0.000000 0.000000 0.000000 0.076923 0.000000 0.153846 0.230769 0.000000 0.000000 0.153846 0.153846 0.000000 0.000000 0.000000
0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.307692 0.000000 0.153846 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.153846 0.307692 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.076923 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.538462 0.000000 0.000000 0.000000 0.307692 0.000000 0.000000 0.000000 0.000000
0.076923 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.307692 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.076923 0.076923 0.307692 0.000000 0.000000
0.000000 0.000000 0.538462 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.076923 0.076923 0.076923 0.000000 0.153846 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.076923 0.923077 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.384615 0.000000 0.153846 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.153846 0.153846 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.846154 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000 0.923077 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.076923 0.153846 0.153846 0.076923 0.000000 0.076923 0.000000 0.000000 0.000000 0.384615 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.384615 0.000000 0.384615 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000
0.000000 0.000000 0.230769 0.153846 0.000000 0.000000 0.000000 0.076923 0.230769 0.000000 0.000000 0.000000 0.000000 0.230769 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000
0.692308 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000 0.000000 0.000000
0.076923 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000 0.153846 0.000000 0.538462 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.846154 0.076923 0.000000 0.076923 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000 0.000000 0.000000 0.000000 0.076923 0.153846 0.076923 0.000000 0.230769
0.000000 0.000000 0.076923 0.000000 0.000000 0.153846 0.076923 0.153846 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.230769 0.230769 0.000000 0.000000
0.153846 0.000000 0.230769 0.153846 0.000000 0.153846 0.000000 0.000000 0.076923 0.000000 0.000000 0.153846 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000
0.153846 0.000000 0.000000 0.461538 0.000000 0.000000 0.000000 0.000000 0.000000 0.230769 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.153846 0.000000 0.000000 0.000000
0.000000 0.230769 0.000000 0.076923 0.000000 0.000000 0.307692 0.000000 0.076923 0.000000 0.000000 0.230769 0.000000 0.000000 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.076923 0.000000 0.307692 0.000000 0.000000 0.076923 0.000000 0.000000 0.000000 0.461538 0.000000 0.076923 0.000000 0.000000 0.000000 0.000000 0.000000
--------------------------------------------------------------------------------
Time 289.77 secs.
********************************************************************************
********************************************************************************
MOTIF 6 width = 21 sites = 29 llr = 814 E-value = 2.0e-099
********************************************************************************
--------------------------------------------------------------------------------
Motif 6 Description
--------------------------------------------------------------------------------
Simplified A :::8:1:11:211::::1:2:
pos.-specific C :::::::::::::::::::::
probability D :2:::7::::4:3::1::::4
matrix E :2:::1:2:1:11:2:::::3
F ::1:::9::::::::::::::
G 8:::::::::1::8:::::::
H ::::::::::::::::1::::
I :::1:::::::1::::21:::
K :22::::::1::1:22:1::1
L ::::::1:81:3:1::::9::
M :::::::::::::::1:::::
N :::::1::::1:1:11:::::
P ::2:8::::2:::::1:::::
Q :12:1::::::1::21:::::
R ::1::::::1::::::11:1:
S 1:1::::2:::1::11:3:51
T ::1::::4:2111:12:2:::
V ::::1:::1:::::::4::::
W :::::::::::::::::::::
Y :::::::::::::::::::::
bits 6.2
5.6
5.0
4.3
Information 3.7 *
content 3.1 * * * *
(40.5 bits) 2.5 * **** * * *
1.9 * ****** * * * ***
1.2 *********** *********
0.6 *********************
0.0 ---------------------
Multilevel GKQAPDFTLPDLDGExVSLSD
consensus E E T K I E
sequence S
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 6 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- ---------------------
15613511 4 1.82e-19 MLE GKQAPDFSLPASNGETVSLSD FKGKNIVLYF
21674812 5 3.37e-19 MIEE GKIAPDFTLPDSTGKMVSLSE FKGRKVLLIF
15807234 5 3.01e-17 MTLV GQPAPDFTLPASTGQDITLSS YRGQSHVVLV
16330420 46 9.44e-17 EFRNRRLLRI GDFAPDFTLKNTKGETIILSE QLKTGPILLK
23098307 29 1.05e-16 MTAYAEGTEV GERAPDFELKTIDGQQLRLSD FKGERVLINF
30021713 53 1.18e-16 EIIARNGIEI GKSAPDFELTKLDGTNVKLSD LKGKKVILNF
15609658 10 3.44e-16 MTKTTRLTP GDKAPAFTLPDADGNNVSLAD YRGRRVIVYF
16078864 36 6.39e-16 YSKKEVGIQE GQQAPDFSLKTLSGEKSSLQD AKGKKVLLNF
14578634 56 3.40e-15 ADSTGYIVKV GESAPDFTITLTDGKQMKLSE LRGKVVMLQF
19746502 68 5.44e-15 KSSDKKMTND GPMAPDFELKGIDGKTYRLSE FKGKKVYLKF
14600438 5 5.44e-15 MPGV GEQAPDFEGIAHTGEKIRLSD FRGRIVVLYF
18313548 6 7.88e-15 MVLKV GDKAPDFELLNEELKPVRLSE VLKRGRPVVL
21283385 21 2.53e-14 IHLKGQQINE GDFAPDFTVLDNDLNQVTLAD YAGKKKLISV
15805225 48 4.65e-14 AGNAANGPLV GKPAPQFNLTGLDGQPVALAD YRGRPVVLNF
15672286 20 9.16e-14 EKIATLNPPI SGDAPDFELTDLKGNKIKLSK LEKPVLISVF
15609375 5 2.46e-13 MLNV GATAPDFTLRDQNQQLVTLRG YRGAKNVLLV
15677788 25 2.67e-13 ILLAIVLIPD SKTAPAFSLPDLHGKTVSNAD LQGKVTLINF
15615431 48 3.66e-12 ITTFNEGVQV GQRAVPFSLTTLEGQVVDLSS LRGQPVILHF
13541117 6 3.66e-12 MSPKV NEKAPDFEAPDTALKMRKLSE FRGQNVVLAF
15614140 39 4.56e-12 FFADRSLARA GEQAVNFVLEDLEGESIELRE LEGKGVFLNF
18309723 262 7.05e-12 SDNKKQEEEN KIPPIDFTLYDQYGNKHTLSE YKGKTIFLNF
21227878 8 1.34e-11 MTDEIRV GETIQDFRLRDQKREEIHLYD LKGKKVLLSF
15605725 37 1.34e-11 HDHYTITTQK GQKIPNVTLTTPDGKKVSIEE FKGKVLLINF
15805374 54 3.79e-11 PDPEGGPALL GKPAPAFALEDLGGRTHALTA AQGKPVVINF
6322180 66 1.10e-10 RSSDVNELEI GDPIPDLSLLNEDNDSISLKK ITENNRVVVF
15597673 133 1.26e-10 GSLGLGIYER GTRLPELSLRNAAGESVQLAD FRGRPLVINL
15602312 43 2.41e-10 IGCKEDIAVI GKQAPEIAVFDLVGTQRSLNE GKGKTILLNF
15801846 22 1.08e-09 VTVANSIPQA GSKAQTFTLVAKDLSDVTLGQ FAGKRKVLNI
16501671 5 1.80e-07 MVLV TRQAPDFTAAAVLGSGEIVDK FNFKQHTNGK
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 6 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
15613511 1.8e-19 3_[6]_130
21674812 3.4e-19 4_[6]_123
15807234 3e-17 4_[6]_126
16330420 9.4e-17 45_[6]_152
23098307 1.1e-16 28_[6]_114
30021713 1.2e-16 52_[6]_118
15609658 3.4e-16 9_[6]_127
16078864 6.4e-16 35_[6]_114
14578634 3.4e-15 55_[6]_122
19746502 5.4e-15 67_[6]_119
14600438 5.4e-15 4_[6]_138
18313548 7.9e-15 5_[6]_136
21283385 2.5e-14 20_[6]_123
15805225 4.7e-14 47_[6]_117
15672286 9.2e-14 19_[6]_120
15609375 2.5e-13 4_[6]_128
15677788 2.7e-13 24_[6]_121
15615431 3.7e-12 47_[6]_116
13541117 3.7e-12 5_[6]_131
15614140 4.6e-12 38_[6]_117
18309723 7e-12 261_[6]_121
21227878 1.3e-11 7_[6]_126
15605725 1.3e-11 36_[6]_89
15805374 3.8e-11 53_[6]_114
6322180 1.1e-10 65_[6]_129
15597673 1.3e-10 132_[6]_125
15602312 2.4e-10 42_[6]_112
15801846 1.1e-09 21_[6]_126
16501671 1.8e-07 4_[6]_175
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 6 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 6 width=21 seqs=29
15613511 ( 4) GKQAPDFSLPASNGETVSLSD 1
21674812 ( 5) GKIAPDFTLPDSTGKMVSLSE 1
15807234 ( 5) GQPAPDFTLPASTGQDITLSS 1
16330420 ( 46) GDFAPDFTLKNTKGETIILSE 1
23098307 ( 29) GERAPDFELKTIDGQQLRLSD 1
30021713 ( 53) GKSAPDFELTKLDGTNVKLSD 1
15609658 ( 10) GDKAPAFTLPDADGNNVSLAD 1
16078864 ( 36) GQQAPDFSLKTLSGEKSSLQD 1
14578634 ( 56) GESAPDFTITLTDGKQMKLSE 1
19746502 ( 68) GPMAPDFELKGIDGKTYRLSE 1
14600438 ( 5) GEQAPDFEGIAHTGEKIRLSD 1
18313548 ( 6) GDKAPDFELLNEELKPVRLSE 1
21283385 ( 21) GDFAPDFTVLDNDLNQVTLAD 1
15805225 ( 48) GKPAPQFNLTGLDGQPVALAD 1
15672286 ( 20) SGDAPDFELTDLKGNKIKLSK 1
15609375 ( 5) GATAPDFTLRDQNQQLVTLRG 1
15677788 ( 25) SKTAPAFSLPDLHGKTVSNAD 1
15615431 ( 48) GQRAVPFSLTTLEGQVVDLSS 1
13541117 ( 6) NEKAPDFEAPDTALKMRKLSE 1
15614140 ( 39) GEQAVNFVLEDLEGESIELRE 1
18309723 ( 262) KIPPIDFTLYDQYGNKHTLSE 1
21227878 ( 8) GETIQDFRLRDQKREEIHLYD 1
15605725 ( 37) GQKIPNVTLTTPDGKKVSIEE 1
15805374 ( 54) GKPAPAFALEDLGGRTHALTA 1
6322180 ( 66) GDPIPDLSLLNEDNDSISLKK 1
15597673 ( 133) GTRLPELSLRNAAGESVQLAD 1
15602312 ( 43) GKQAPEIAVFDLVGTQRSLNE 1
15801846 ( 22) GSKAQTFTLVAKDLSDVTLGQ 1
16501671 ( 5) TRQAPDFTAAAVLGSGEIVDK 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 6 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 21 n= 14387 bayes= 9.59338 E= 2.0e-099
-278 -369 -338 -403 -529 363 -290 -503 -177 -543 -407 -77 -450 -377 -330 -29 -137 -483 -421 -423
-87 -344 122 139 -391 -96 -94 -87 157 -334 -228 -153 -63 196 5 -14 -31 -337 -367 -266
-214 -343 -67 -158 17 -304 -94 -86 115 -333 57 -153 147 248 123 52 89 -335 -366 -266
321 -180 -507 -463 -412 -289 -360 47 -474 -146 -260 -415 -97 -397 -402 -150 -279 -234 -429 -419
-257 -369 -404 -377 -471 -402 -274 -116 -368 -400 -363 -367 399 64 -327 -241 -300 -70 -495 -450
-124 -370 365 -60 -469 -389 -197 -432 -423 -461 -377 6 -214 -127 -364 -292 -193 -440 -416 -363
-392 -251 -506 -493 406 -500 -341 -139 -511 -87 -193 -441 -444 -445 -457 -325 -417 -194 -222 -74
-41 -310 -306 144 -438 -378 -184 -351 -250 -395 -259 -16 -382 -180 -28 181 296 -131 -413 -346
-99 -309 -547 -462 -246 -176 -306 -59 -452 308 -47 -435 -439 -315 -348 -375 -331 -62 -351 -324
-91 -282 -281 2 -63 -333 -133 -59 83 7 -176 -199 175 -138 120 -173 180 -96 -340 24
93 -449 258 -280 -538 0 -183 -523 -86 -148 -413 181 -430 -233 -299 -213 133 -510 -519 -391
-21 -337 -230 13 -385 -306 131 2 -48 144 -223 3 -63 161 -143 97 89 -121 -364 -264
-21 -343 215 57 -391 -96 131 -350 56 -136 -227 77 -312 -88 -140 -13 89 -123 -366 19
-280 -370 -340 -402 -530 357 -288 -502 -384 -42 -407 -75 -451 -73 -95 -256 -389 -483 -422 -423
-228 -358 -65 161 -407 -313 -106 -366 158 -349 -243 163 -325 226 3 51 40 -351 -382 -280
-213 -343 8 -48 -390 -96 -93 -350 115 -136 147 77 24 196 -140 97 153 -123 -366 -265
-193 -188 -445 -150 -289 -402 166 159 -395 -114 42 -348 -383 -314 15 -86 -187 266 -335 -19
-21 -343 -66 -48 -391 -304 131 1 89 -334 -228 -152 -313 47 158 220 154 -337 -367 -266
-391 -315 -549 -464 -244 -522 -309 -61 -454 318 -45 -99 -440 -316 -349 -383 -338 -127 -352 -327
85 -336 -68 -51 -392 -98 -97 -352 -49 -336 -230 3 -314 44 73 298 -25 -339 -368 18
-117 -619 246 232 -654 -104 -292 -542 46 -528 -429 -309 -443 29 -361 37 -369 -502 -624 -504
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 6 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 21 nsites= 29 E= 2.0e-099
0.000000 0.000000 0.000000 0.000000 0.000000 0.827586 0.000000 0.000000 0.034483 0.000000 0.000000 0.034483 0.000000 0.000000 0.000000 0.068966 0.034483 0.000000 0.000000 0.000000
0.034483 0.000000 0.172414 0.206897 0.000000 0.034483 0.000000 0.034483 0.241379 0.000000 0.000000 0.000000 0.034483 0.137931 0.034483 0.034483 0.034483 0.000000 0.000000 0.000000
0.000000 0.000000 0.034483 0.000000 0.068966 0.000000 0.000000 0.034483 0.172414 0.000000 0.034483 0.000000 0.172414 0.206897 0.103448 0.068966 0.103448 0.000000 0.000000 0.000000
0.827586 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.103448 0.000000 0.034483 0.000000 0.000000 0.034483 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.034483 0.000000 0.000000 0.000000 0.000000 0.827586 0.068966 0.000000 0.000000 0.000000 0.068966 0.000000 0.000000
0.103448 0.000000 0.655172 0.068966 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.068966 0.034483 0.034483 0.000000 0.000000 0.034483 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.862069 0.000000 0.000000 0.034483 0.000000 0.068966 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.034483 0.000000 0.000000
0.068966 0.000000 0.000000 0.241379 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.034483 0.000000 0.000000 0.034483 0.206897 0.379310 0.034483 0.000000 0.000000
0.068966 0.000000 0.000000 0.000000 0.000000 0.034483 0.000000 0.034483 0.000000 0.793103 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.068966 0.000000 0.000000
0.034483 0.000000 0.000000 0.068966 0.034483 0.000000 0.000000 0.034483 0.137931 0.103448 0.000000 0.000000 0.206897 0.000000 0.103448 0.000000 0.206897 0.034483 0.000000 0.034483
0.172414 0.000000 0.413793 0.000000 0.000000 0.068966 0.000000 0.000000 0.034483 0.034483 0.000000 0.137931 0.000000 0.000000 0.000000 0.000000 0.137931 0.000000 0.000000 0.000000
0.068966 0.000000 0.000000 0.068966 0.000000 0.000000 0.034483 0.068966 0.034483 0.310345 0.000000 0.034483 0.034483 0.103448 0.000000 0.103448 0.103448 0.034483 0.000000 0.000000
0.068966 0.000000 0.344828 0.103448 0.000000 0.034483 0.034483 0.000000 0.103448 0.034483 0.000000 0.068966 0.000000 0.000000 0.000000 0.034483 0.103448 0.034483 0.000000 0.034483
0.000000 0.000000 0.000000 0.000000 0.000000 0.758621 0.000000 0.000000 0.000000 0.137931 0.000000 0.034483 0.000000 0.034483 0.034483 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.034483 0.241379 0.000000 0.000000 0.000000 0.000000 0.241379 0.000000 0.000000 0.137931 0.000000 0.172414 0.034483 0.068966 0.068966 0.000000 0.000000 0.000000
0.000000 0.000000 0.068966 0.034483 0.000000 0.034483 0.000000 0.000000 0.172414 0.034483 0.068966 0.068966 0.068966 0.137931 0.000000 0.103448 0.172414 0.034483 0.000000 0.000000
0.000000 0.000000 0.000000 0.034483 0.000000 0.000000 0.068966 0.241379 0.000000 0.034483 0.034483 0.000000 0.000000 0.000000 0.068966 0.034483 0.000000 0.448276 0.000000 0.034483
0.068966 0.000000 0.034483 0.034483 0.000000 0.000000 0.034483 0.068966 0.137931 0.000000 0.000000 0.000000 0.000000 0.034483 0.137931 0.275862 0.172414 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.034483 0.000000 0.896552 0.000000 0.034483 0.000000 0.000000 0.000000 0.000000 0.000000 0.034483 0.000000 0.000000
0.172414 0.000000 0.034483 0.034483 0.000000 0.034483 0.000000 0.000000 0.034483 0.000000 0.000000 0.034483 0.000000 0.034483 0.068966 0.482759 0.034483 0.000000 0.000000 0.034483
0.034483 0.000000 0.379310 0.344828 0.000000 0.034483 0.000000 0.000000 0.103448 0.000000 0.000000 0.000000 0.000000 0.034483 0.000000 0.068966 0.000000 0.000000 0.000000 0.000000
--------------------------------------------------------------------------------
Time 336.47 secs.
********************************************************************************
********************************************************************************
MOTIF 7 width = 18 sites = 20 llr = 553 E-value = 4.2e-054
********************************************************************************
--------------------------------------------------------------------------------
Motif 7 Description
--------------------------------------------------------------------------------
Simplified A 42:5::::11::::213:
pos.-specific C ::::::::::::::::::
probability D ::::::::a131:::1::
matrix E :2:::::::32:::::11
F :::::6::::::1::11:
G :1:1:::::1:8::::::
H ::::::::::::1::::2
I 11:::148::::241:2:
K :2:::::::21:3::111
L 1::::121::::1:12:1
M ::::::::::::::::::
N :1::1:::::211:::::
P 1:2::::::1::::::::
Q :1::::::::1:1:1:12
R :19::::::311::5:1:
S 3::31:::::1:::::2:
T 1::14:::::1:1::::1
V 12:14251::::26211:
W ::::::::::1::::::3
Y :1::12:::::::::5:1
bits 6.2
5.6
5.0
4.3
Information 3.7 * *
content 3.1 * ** * *
(39.9 bits) 2.5 * ***** * * *
1.9 ******** * *** *
1.2 * ****************
0.6 ******************
0.0 ------------------
Multilevel AERATFVIDRDGKVRYAW
consensus S SV I EE I Q
sequence
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 7 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- ------------------
13541117 118 1.24e-17 NFAGVPGLTA SKRSVFIIDGDGIVRYAW VSDDPGKEPD
15899339 117 1.72e-17 ELPILKGYVL AKRSVFVIDKNGIVRYKW VSEDPTKEPN
15807234 112 5.06e-17 YGVAIDERGI SGRAVFVIDREGVVRYQH VEEQTGQYTV
18313548 120 1.71e-15 NLLGLPLYHL AKRAVYIIDPTGTIRYVW YSDDPRDEPP
15605963 130 1.42e-14 LIGEGALKGI LARAVFIIDKEGKVAYVQ LVPEITEEPN
15790738 151 1.98e-14 QASAEDHDRV PERAVFLIDADRVIRYAW ASSDLSESPD
15643152 100 4.69e-14 EFFNVLENGK TVRSTFLIDRWGFVRKEW RRVKVEGHVQ
15613511 116 4.69e-14 KKNFGKEYMG IERSTFVIDKDGTVVKEW RKVRVKDHVE
4433065 103 1.19e-13 YGMLNVETGV SRRGYVIIDDKGKVRYIQ MNDDGIGRST
15609375 114 1.61e-13 YGVFNEQAGI ANRGTFVVDRSGIIRFAE MKQPGEVRDQ
14600438 113 2.40e-13 VVRGEGSNLA AERVTFIIDREGNIRAIL RNIRPAEKHA
16330420 176 1.01e-12 EHNGTEEWLL PVPATFVIDRRGHIALAY ANVDFRVRYE
15609658 122 2.98e-12 KQMYGKTVQG VIRSTFVVDEDGKIVVAQ YNVKATGHVA
15801846 131 7.71e-12 AIADGPLKGL AARAVVVIDENDNVIFSQ LVDEITTEPD
21227878 117 2.46e-11 CGIFRGKEGV SERANIIIDENRQVIYFK KYLGHELPDI
21222859 185 2.46e-11 RFEKGTLNPQ AVPSTLIIDREGKVAART LQALSEEKLR
21283385 126 3.38e-11 YGVVMEELRL LARAVFVLDADNKVVYKE IVSEGTDFPD
21674812 110 3.97e-11 AYDALGFLGM AQRAYVLIDEQGLVLLSY SDFLPVTYQP
16125919 137 6.86e-11 DVALAVKPDW SNRTSYVIAPDGKILLSH TDGNFMGHVQ
16078864 137 1.36e-10 KGINADYNVM SYPTTYILDEKGVIQDIH VGTMTKKEME
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 7 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
13541117 1.2e-17 117_[7]_22
15899339 1.7e-17 116_[7]_22
15807234 5.1e-17 111_[7]_22
18313548 1.7e-15 119_[7]_25
15605963 1.4e-14 129_[7]_22
15790738 2e-14 150_[7]_44
15643152 4.7e-14 99_[7]_204
15613511 4.7e-14 115_[7]_21
4433065 1.2e-13 102_[7]_13
15609375 1.6e-13 113_[7]_22
14600438 2.4e-13 112_[7]_33
16330420 1e-12 175_[7]_25
15609658 3e-12 121_[7]_18
15801846 7.7e-12 130_[7]_20
21227878 2.5e-11 116_[7]_20
21222859 2.5e-11 184_[7]_21
21283385 3.4e-11 125_[7]_21
21674812 4e-11 109_[7]_21
16125919 6.9e-11 136_[7]_23
16078864 1.4e-10 136_[7]_16
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 7 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 7 width=18 seqs=20
13541117 ( 118) SKRSVFIIDGDGIVRYAW 1
15899339 ( 117) AKRSVFVIDKNGIVRYKW 1
15807234 ( 112) SGRAVFVIDREGVVRYQH 1
18313548 ( 120) AKRAVYIIDPTGTIRYVW 1
15605963 ( 130) LARAVFIIDKEGKVAYVQ 1
15790738 ( 151) PERAVFLIDADRVIRYAW 1
15643152 ( 100) TVRSTFLIDRWGFVRKEW 1
15613511 ( 116) IERSTFVIDKDGTVVKEW 1
4433065 ( 103) SRRGYVIIDDKGKVRYIQ 1
15609375 ( 114) ANRGTFVVDRSGIIRFAE 1
14600438 ( 113) AERVTFIIDREGNIRAIL 1
16330420 ( 176) PVPATFVIDRRGHIALAY 1
15609658 ( 122) VIRSTFVVDEDGKIVVAQ 1
15801846 ( 131) AARAVVVIDENDNVIFSQ 1
21227878 ( 117) SERANIIIDENRQVIYFK 1
21222859 ( 185) AVPSTLIIDREGKVAART 1
21283385 ( 126) LARAVFVLDADNKVVYKE 1
21674812 ( 110) AQRAYVLIDEQGLVLLSY 1
16125919 ( 137) SNRTSYVIAPDGKILLSH 1
16078864 ( 137) SYPTTYILDEKGVIQDIH 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 7 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 18 n= 14675 bayes= 9.76903 E= 4.2e-054
192 -170 -447 -376 -242 -332 -208 10 -361 16 -95 -307 65 -268 -292 224 3 -26 -278 -221
64 -302 -187 130 -350 -56 -54 -47 96 -293 -187 117 -273 86 45 -99 -141 51 -326 60
-610 -538 -675 -682 -717 -593 -420 -708 -447 -675 -635 -568 148 -480 436 -560 -600 -739 -579 -609
247 -213 -557 -532 -521 45 -409 -473 -551 -485 -379 -426 -454 -430 -456 241 84 -73 -504 -500
-266 -233 -398 -414 -345 -388 -247 -233 -374 -300 -191 14 -414 -284 -317 33 309 186 -360 144
-411 -296 -565 -540 366 -533 -293 -38 -542 -68 -177 -463 -496 -440 -467 -376 -397 40 -244 203
-436 -345 -712 -680 -427 -672 -601 275 -680 68 -249 -607 -658 -612 -646 -563 -391 241 -602 -510
-346 -298 -459 -452 -309 -478 -352 361 -422 -9 -75 -369 -479 -371 -392 -333 -275 68 -386 -305
-227 -356 379 -129 -456 -380 -187 -420 -422 -450 -366 -74 -470 -313 -357 -284 -364 -428 -402 -352
17 -344 -20 168 -393 -56 -89 -346 96 -329 -224 -143 68 -70 255 -134 -177 -330 -366 -265
-177 -307 187 130 -355 -265 -57 -314 53 -298 -192 166 -276 86 44 26 9 -300 145 -229
-257 -347 -123 -378 -507 362 -264 -481 -374 -521 -386 -50 -427 -352 11 -230 -365 -462 -399 -400
-200 -208 -302 -231 -13 -319 166 120 175 -56 -106 110 -332 62 -190 -165 84 76 -281 -210
-435 -343 -730 -698 -468 -686 -653 274 -705 -301 -288 -627 -674 -658 -684 -583 -393 282 -675 -546
69 -188 -455 -375 -236 -369 -200 86 -319 23 -88 -306 -386 49 314 -229 -186 87 -275 -215
-46 -171 -119 -275 138 -327 89 -219 -50 -16 -140 -232 -304 -219 -211 -156 -225 -119 -80 412
127 -288 -196 51 -32 -269 -61 98 51 -277 -176 -121 -279 84 43 137 -143 3 -321 -224
-187 -308 -202 52 -352 -277 310 -309 -5 -95 -194 -126 -286 238 -98 -113 7 -299 402 152
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 7 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 18 nsites= 20 E= 4.2e-054
0.350000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.050000 0.000000 0.100000 0.000000 0.000000 0.100000 0.000000 0.000000 0.300000 0.050000 0.050000 0.000000 0.000000
0.150000 0.000000 0.000000 0.200000 0.000000 0.050000 0.000000 0.050000 0.150000 0.000000 0.000000 0.100000 0.000000 0.050000 0.050000 0.000000 0.000000 0.150000 0.000000 0.050000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.150000 0.000000 0.850000 0.000000 0.000000 0.000000 0.000000 0.000000
0.450000 0.000000 0.000000 0.000000 0.000000 0.100000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.300000 0.100000 0.050000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.050000 0.000000 0.000000 0.000000 0.050000 0.400000 0.400000 0.000000 0.100000
0.000000 0.000000 0.000000 0.000000 0.600000 0.000000 0.000000 0.050000 0.000000 0.050000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.150000 0.000000 0.150000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.400000 0.000000 0.150000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.450000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.800000 0.000000 0.100000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.100000 0.000000 0.000000
0.050000 0.000000 0.950000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.100000 0.000000 0.050000 0.250000 0.000000 0.050000 0.000000 0.000000 0.150000 0.000000 0.000000 0.000000 0.100000 0.000000 0.300000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.300000 0.200000 0.000000 0.000000 0.000000 0.000000 0.100000 0.000000 0.000000 0.150000 0.000000 0.050000 0.050000 0.050000 0.050000 0.000000 0.050000 0.000000
0.000000 0.000000 0.050000 0.000000 0.000000 0.800000 0.000000 0.000000 0.000000 0.000000 0.000000 0.050000 0.000000 0.000000 0.100000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.050000 0.000000 0.050000 0.150000 0.300000 0.050000 0.000000 0.100000 0.000000 0.050000 0.000000 0.000000 0.100000 0.150000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.400000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.600000 0.000000 0.000000
0.150000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.100000 0.000000 0.100000 0.000000 0.000000 0.000000 0.050000 0.450000 0.000000 0.000000 0.150000 0.000000 0.000000
0.100000 0.000000 0.050000 0.000000 0.100000 0.000000 0.000000 0.000000 0.100000 0.150000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.050000 0.000000 0.450000
0.250000 0.000000 0.000000 0.100000 0.050000 0.000000 0.000000 0.150000 0.100000 0.000000 0.000000 0.000000 0.000000 0.050000 0.050000 0.150000 0.000000 0.100000 0.000000 0.000000
0.000000 0.000000 0.000000 0.100000 0.000000 0.000000 0.150000 0.000000 0.050000 0.050000 0.000000 0.000000 0.000000 0.200000 0.000000 0.000000 0.050000 0.000000 0.300000 0.100000
--------------------------------------------------------------------------------
Time 380.88 secs.
********************************************************************************
********************************************************************************
MOTIF 8 width = 15 sites = 29 llr = 571 E-value = 6.1e-041
********************************************************************************
--------------------------------------------------------------------------------
Motif 8 Description
--------------------------------------------------------------------------------
Simplified A :1::::::2::1:11
pos.-specific C :::::::::::::::
probability D :2:::1:::a:1:::
matrix E 1::1::::::11:3:
F ::1:6:::::1:1::
G 13:::::::::23::
H 1:::::::::::1::
I ::2:::111::::13
K 12:::::::::2:1:
L ::6::167::::::2
M ::::::1::::::::
N 21:2:::::::2:::
P :::2:7::::2::::
Q 1::::::::::::1:
R ::::::::::1:31:
S 1:::::1:5:1::::
T 1::4:1::::11:11
V ::1:1:11::::::2
W :::::::::::::::
Y 2:::3:::1::::::
bits 6.2
5.6
5.0
4.3
Information 3.7 *
content 3.1 * *
(28.4 bits) 2.5 * ** * *
1.9 * ******** *
1.2 ********** ****
0.6 ***************
0.0 ---------------
Multilevel YGLTFPLLSDPNREI
consensus INY A G V
sequence P
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 8 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- ---------------
15609658 88 1.88e-14 PEKLATFRDA QGLTFPLLSDPDREV LTAWGAYGEK
13541117 84 5.14e-13 PFSLAEFAKK NNLTFDLLSDSNREI SKKYDVLHQN
18313548 86 6.00e-13 PFALKAFKDA NRLNFPLLSDYNRIV IGMYDVVQAN
15790738 119 2.25e-12 TYAHEAFADE YALTFPLLSDHAGAI ADAFGVLQAS
6322180 145 1.28e-11 VTSQKKFQSK QNLPYHLLSDPKREF IGLLGAKKTP
21223405 94 3.84e-11 HAWRKDHPDL TDLPFPMLADSKHEL MRDLGIEGED
16330420 125 6.86e-11 LVASQKTIDR HDLTYDLLSDSGFQT AQDYGLVFTV
21674812 83 8.61e-11 PESHKQFAEK HKLPFLLLSDQERTV AKAYDALGFL
21222859 158 1.34e-10 TGPARAFEKD YGVTYPSLYDPAGRL MLRFEKGTLN
6850955 93 1.67e-10 NDNELSKMVE GGIPFPMLSDGGGNV GTLYGVYDPE
16803644 98 1.67e-10 TNTPIKEGGI GKLNYPLAADTNHQV ASDYGVLIEE
4433065 75 3.89e-10 CEADKSKGGV GKLGFPLVSDIKRCI SIKYGMLNVE
16078864 116 5.84e-10 EKQVRAFADT YDLTFPILIDKKGIN ADYNVMSYPT
15609375 84 7.88e-10 PPTHKIWATQ SGFTFPLLSDFWPHG AVSQAYGVFN
11467494 97 7.88e-10 LLCNREEGGL EDLNYPLVSDLTQTI TRDYQVLTDE
13186328 86 8.70e-10 VQKNWIENEL KFINFPFISDFNHKI SNNFNILNKK
15805225 125 1.16e-09 PQNARDFARQ YGLTYPNLQDPGVAT AIAYQVTGIP
15899339 84 1.28e-09 PFSNKAFKEQ NKINFTIVSDFNREA VKAYGVAGEL
3318841 96 1.41e-09 INAYNSEEPT EKLPFPIIDDRNREL AILLGMLDPA
14600438 83 2.48e-09 VEKNRKFAEK HGFRFKLVSDEKGEI GMKYGVVRGE
19705357 105 2.72e-09 KDKIISFLKK KNITYPSLMDETGKS FDDYKVRALP
15807234 84 5.59e-09 VYAHRAWAAE YGIEVPLLADMQLEV ARQYGVAIDE
9955016 96 8.63e-09 INTPRKEGGL GPLNIPLLADVTRRL SEDYGVLKTD
15805374 131 8.63e-09 PADARRFMDQ YGLIYPALLDPGSRT ALSYGVGKLP
15643152 74 9.40e-09 VEALKRFKEK NDLKVTLLSDPEGIL HEFFNVLENG
19554157 70 1.02e-08 QTIAQDFKLD NAVTYPSIYDPPFRI AAALGGVPTS
15613511 82 1.11e-08 VERHKKFIEK YSLPFLLLADEDTKV AQQYDVWKLK
14578634 159 1.47e-07 DIFAKYALRE SGITRNVLIDREGKI VKLTRLYNEE
14286173 89 3.42e-07 WIEWIAENLD TEIEFPVIADTGRVA DTLGLIHPAR
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 8 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
15609658 1.9e-14 87_[8]_55
13541117 5.1e-13 83_[8]_59
18313548 6e-13 85_[8]_62
15790738 2.3e-12 118_[8]_79
6322180 1.3e-11 144_[8]_56
21223405 3.8e-11 93_[8]_76
16330420 6.9e-11 124_[8]_79
21674812 8.6e-11 82_[8]_51
21222859 1.3e-10 157_[8]_51
6850955 1.7e-10 92_[8]_96
16803644 1.7e-10 97_[8]_69
4433065 3.9e-10 74_[8]_44
16078864 5.8e-10 115_[8]_40
15609375 7.9e-10 83_[8]_55
11467494 7.9e-10 96_[8]_93
13186328 8.7e-10 85_[8]_76
15805225 1.2e-09 124_[8]_46
15899339 1.3e-09 83_[8]_58
3318841 1.4e-09 95_[8]_114
14600438 2.5e-09 82_[8]_66
19705357 2.7e-09 104_[8]_45
15807234 5.6e-09 83_[8]_53
9955016 8.6e-09 95_[8]_87
15805374 8.6e-09 130_[8]_43
15643152 9.4e-09 73_[8]_233
19554157 1e-08 69_[8]_37
15613511 1.1e-08 81_[8]_58
14578634 1.5e-07 158_[8]_25
14286173 3.4e-07 88_[8]_106
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 8 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 8 width=15 seqs=29
15609658 ( 88) QGLTFPLLSDPDREV 1
13541117 ( 84) NNLTFDLLSDSNREI 1
18313548 ( 86) NRLNFPLLSDYNRIV 1
15790738 ( 119) YALTFPLLSDHAGAI 1
6322180 ( 145) QNLPYHLLSDPKREF 1
21223405 ( 94) TDLPFPMLADSKHEL 1
16330420 ( 125) HDLTYDLLSDSGFQT 1
21674812 ( 83) HKLPFLLLSDQERTV 1
21222859 ( 158) YGVTYPSLYDPAGRL 1
6850955 ( 93) GGIPFPMLSDGGGNV 1
16803644 ( 98) GKLNYPLAADTNHQV 1
4433065 ( 75) GKLGFPLVSDIKRCI 1
16078864 ( 116) YDLTFPILIDKKGIN 1
15609375 ( 84) SGFTFPLLSDFWPHG 1
11467494 ( 97) EDLNYPLVSDLTQTI 1
13186328 ( 86) KFINFPFISDFNHKI 1
15805225 ( 125) YGLTYPNLQDPGVAT 1
15899339 ( 84) NKINFTIVSDFNREA 1
3318841 ( 96) EKLPFPIIDDRNREL 1
14600438 ( 83) HGFRFKLVSDEKGEI 1
19705357 ( 105) KNITYPSLMDETGKS 1
15807234 ( 84) YGIEVPLLADMQLEV 1
9955016 ( 96) GPLNIPLLADVTRRL 1
15805374 ( 131) YGLIYPALLDPGSRT 1
15643152 ( 74) NDLKVTLLSDPEGIL 1
19554157 ( 70) NAVTYPSIYDPPFRI 1
15613511 ( 82) YSLPFLLLADEDTKV 1
14578634 ( 159) SGITRNVLIDREGKI 1
14286173 ( 89) TEIEFPVIADTGRVA 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 8 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 15 n= 14963 bayes= 8.89339 E= 6.1e-041
-231 -358 -226 11 -408 79 270 -370 11 -353 -248 194 -328 114 -157 52 41 -356 -384 285
-22 -349 123 -50 -74 189 -99 -358 115 -342 -236 127 -63 -95 3 -14 -187 -344 -374 -272
-542 -448 -797 -721 41 -727 -529 198 -713 272 -164 -673 -662 -539 -603 -623 -496 -18 -475 -464
-242 -362 -238 10 -418 -96 -116 -86 -52 -361 -255 218 177 -114 2 -157 264 -362 -392 -292
-554 -453 -647 -629 337 -624 -196 -77 -608 -428 -393 -492 -613 -478 -32 -482 -520 -31 -228 353
-258 -371 -35 -372 -473 -399 86 -424 -133 -85 -366 -59 381 -282 -324 -239 2 -411 -495 -448
-150 -266 -528 -445 -75 -463 -275 53 -431 271 141 -75 -426 -307 -336 42 -278 -41 -327 -286
-137 -380 -699 -630 -371 -652 -485 122 -623 285 -188 -585 -601 -498 -534 -529 -418 75 -503 -462
112 -239 -95 -302 -290 -370 -189 32 -291 -95 77 -266 -384 14 -255 311 -190 -200 -319 116
-740 -662 396 -575 -786 -665 -553 -816 -785 -792 -763 -511 -717 -681 -691 -664 -721 -821 -694 -695
-214 -338 -229 56 73 -96 131 -85 -48 -135 58 -155 194 46 75 97 41 -121 -364 20
-21 -345 8 57 -393 106 -95 -353 115 -336 -230 215 -63 46 -142 -140 89 -338 105 -267
-222 -314 -251 -181 21 172 268 -290 -173 -126 -204 -173 -64 40 280 -19 -32 -111 -355 -263
-21 83 -227 176 -391 -304 131 55 89 -334 -227 4 -313 115 158 -139 41 -123 -366 -265
-24 -216 -512 -436 -46 -106 -245 212 -415 86 -116 -30 -422 -316 -337 -47 92 147 -303 -244
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 8 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 15 nsites= 29 E= 6.1e-041
0.000000 0.000000 0.000000 0.068966 0.000000 0.137931 0.103448 0.000000 0.068966 0.000000 0.000000 0.172414 0.000000 0.068966 0.000000 0.068966 0.068966 0.000000 0.000000 0.241379
0.068966 0.000000 0.172414 0.034483 0.034483 0.310345 0.000000 0.000000 0.172414 0.000000 0.000000 0.103448 0.034483 0.000000 0.034483 0.034483 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.068966 0.000000 0.000000 0.241379 0.000000 0.620690 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.068966 0.000000 0.000000
0.000000 0.000000 0.000000 0.068966 0.000000 0.034483 0.000000 0.034483 0.034483 0.000000 0.000000 0.206897 0.206897 0.000000 0.034483 0.000000 0.379310 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.551724 0.000000 0.000000 0.034483 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.034483 0.000000 0.000000 0.068966 0.000000 0.310345
0.000000 0.000000 0.068966 0.000000 0.000000 0.000000 0.034483 0.000000 0.034483 0.068966 0.000000 0.034483 0.689655 0.000000 0.000000 0.000000 0.068966 0.000000 0.000000 0.000000
0.034483 0.000000 0.000000 0.000000 0.034483 0.000000 0.000000 0.103448 0.000000 0.551724 0.068966 0.034483 0.000000 0.000000 0.000000 0.103448 0.000000 0.068966 0.000000 0.000000
0.034483 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.137931 0.000000 0.689655 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.137931 0.000000 0.000000
0.206897 0.000000 0.034483 0.000000 0.000000 0.000000 0.000000 0.068966 0.000000 0.034483 0.034483 0.000000 0.000000 0.034483 0.000000 0.517241 0.000000 0.000000 0.000000 0.068966
0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.103448 0.103448 0.034483 0.034483 0.034483 0.034483 0.034483 0.034483 0.000000 0.241379 0.034483 0.068966 0.103448 0.068966 0.034483 0.000000 0.034483
0.068966 0.000000 0.068966 0.103448 0.000000 0.172414 0.000000 0.000000 0.172414 0.000000 0.000000 0.206897 0.034483 0.034483 0.000000 0.000000 0.103448 0.000000 0.034483 0.000000
0.000000 0.000000 0.000000 0.000000 0.068966 0.275862 0.103448 0.000000 0.000000 0.034483 0.000000 0.000000 0.034483 0.034483 0.344828 0.034483 0.034483 0.034483 0.000000 0.000000
0.068966 0.034483 0.000000 0.275862 0.000000 0.000000 0.034483 0.103448 0.137931 0.000000 0.000000 0.034483 0.000000 0.068966 0.137931 0.000000 0.068966 0.034483 0.000000 0.000000
0.068966 0.000000 0.000000 0.000000 0.034483 0.034483 0.000000 0.275862 0.000000 0.172414 0.000000 0.034483 0.000000 0.000000 0.000000 0.034483 0.103448 0.241379 0.000000 0.000000
--------------------------------------------------------------------------------
Time 422.25 secs.
********************************************************************************
********************************************************************************
MOTIF 9 width = 21 sites = 9 llr = 338 E-value = 3.5e-015
********************************************************************************
--------------------------------------------------------------------------------
Motif 9 Description
--------------------------------------------------------------------------------
Simplified A ::2::4::1::::::332::1
pos.-specific C :::::::::::::::::::::
probability D :::::::::34::::::::1:
matrix E :::::::::2::::1::2:82
F ::::2:1::::::::::2:::
G ::2::::::::9:::::::::
H :::::::::::::::::::::
I ::::::111:::231:::2::
K ::2::::::2::2:41::3::
L :2::::331::1::::3::1:
M ::::::4:::::::::1::::
N ::::::::::6::::::3:::
P ::::::::::::::::::::2
Q :::::::::1::1::::::::
R 8:1a:::::::::::::::::
S 16::13:::1::::::1:::3
T :2::::::::::::2:::::1
V :::::2:47:::47111:4::
W 1:1:1::::::::::::::::
Y ::1:6::1:::::::4:::::
bits 6.2
5.6
5.0
4.3 *
Information 3.7 * *
content 3.1 * ** * ** * *
(54.2 bits) 2.5 ** **** * ** * * ***
1.9 *********************
1.2 *********************
0.6 *********************
0.0 ---------------------
Multilevel RSARYAMVVDNGVVKYANVES
consensus LG FSLL ED IITALAK E
sequence TK V K K EI P
F
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 9 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- ---------------------
15964668 124 1.20e-20 IDLSAGTLGI RSKRYSMLVEDGVVKALNIEE SPGQATASGA
17229033 124 3.84e-19 VDKTDLGFGK RSWRYSMLVKDGVIEKMFIEP DVPGDPFEVS
6323138 138 3.52e-18 FELAVGDGVY WSGRWAMVVENGIVTYAAKET NPGTDVTVSS
15826629 124 6.10e-18 DSLVSIFGNR RLKRFSMVVQDGIVKALNVEP DGTGLTCSLA
21112072 122 1.16e-17 IDASGSGMGL RSRRYALYADDGVVKALFVEE PGEFKVSAAD
1091044 131 1.31e-16 SLDLPPAFGT RTARYAIIVSNGVVKYVEKDS EGVAGSGVDA
5326864 130 2.32e-16 KSIGWADEEG RTYRYVLVIDNGKIIYAAKEA AKNSLELSRA
4704732 126 2.30e-13 LDLKDKGSGI SSGRFALLLDNLKVTVANVES GGEFTVSSAE
15672286 124 3.35e-13 LILNGGPLEG RLARSVFVVKNGQIVYSEVLS ELSDEPNYEK
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 9 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
15964668 1.2e-20 123_[9]_17
17229033 3.8e-19 123_[9]_107
6323138 3.5e-18 137_[9]_18
15826629 6.1e-18 123_[9]_17
21112072 1.2e-17 121_[9]_18
1091044 1.3e-16 130_[9]_15
5326864 2.3e-16 129_[9]_17
4704732 2.3e-13 125_[9]_16
15672286 3.4e-13 123_[9]_16
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 9 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 9 width=21 seqs=9
15964668 ( 124) RSKRYSMLVEDGVVKALNIEE 1
17229033 ( 124) RSWRYSMLVKDGVIEKMFIEP 1
6323138 ( 138) WSGRWAMVVENGIVTYAAKET 1
15826629 ( 124) RLKRFSMVVQDGIVKALNVEP 1
21112072 ( 122) RSRRYALYADDGVVKALFVEE 1
1091044 ( 131) RTARYAIIVSNGVVKYVEKDS 1
5326864 ( 130) RTYRYVLVIDNGKIIYAAKEA 1
4704732 ( 126) SSGRFALLLDNLKVTVANVES 1
15672286 ( 124) RLARSVFVVKNGQIVYSEVLS 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 9 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 21 n= 14387 bayes= 11.49 E= 3.5e-015
-338 -256 -434 -406 -446 -385 -106 -392 -130 -385 -324 -274 -359 -170 436 -81 -324 -461 82 -321
-168 -149 -339 -369 -346 -293 -211 -300 -307 -28 -221 -146 -315 -257 -240 361 176 -323 -340 -283
95 -237 -151 -79 -277 108 -2 -237 135 -229 -128 -69 -230 2 128 -57 -95 -230 227 144
-442 -339 -517 -515 -546 -452 -200 -490 -237 -476 -427 -374 -433 -274 452 -388 -424 -564 -373 -433
-214 -175 -314 -285 189 -331 90 -227 -293 -206 -145 -231 -309 -218 -214 29 -233 -248 204 424
251 -120 -449 -417 -402 -202 -298 -323 -432 -356 -258 -325 -364 -322 -347 236 -181 104 -394 -380
-404 -315 -677 -597 103 -577 -374 101 -583 195 415 -534 -525 -395 -468 -473 -359 -211 -310 -302
-241 -184 -499 -431 -201 -407 -247 120 -415 168 -47 -354 -410 -310 -337 -274 -200 223 -284 164
-48 -140 -384 -349 -297 -383 -208 57 -367 -88 -149 -329 -336 -302 -271 -265 -142 311 -364 -346
-181 -362 200 178 -409 -267 -84 -342 127 -326 -224 -116 -273 162 -137 87 -169 -316 -381 -273
-316 -369 262 -206 -497 -204 -90 -539 -268 -524 -460 361 -358 -190 -282 -114 -227 -526 -480 -326
-229 -316 -299 -362 -472 367 -246 -444 -355 -132 -353 -218 -402 -333 -286 -208 -340 -427 -373 -372
-166 -159 -342 -260 -239 -324 -128 157 99 -149 -83 -228 -326 114 -113 -186 -141 237 -272 -213
-268 -218 -540 -506 -346 -517 -397 234 -517 -193 -174 -460 -489 -458 -450 -405 -250 293 -495 -413
-134 -199 -172 53 -252 -233 -26 53 210 -184 -93 -93 -244 -23 -46 -72 163 14 -251 -167
132 -151 -273 -211 -14 -271 17 -134 16 -161 -85 -177 -286 -127 -129 -119 -143 9 -139 372
171 -97 -380 -308 -159 -267 -135 -41 -291 149 200 -237 -311 -197 -220 75 -109 53 -200 -144
103 -257 -111 140 156 -208 -38 -271 -118 -273 -177 264 -260 -48 -110 -72 -127 -265 -309 -194
-271 -211 -514 -443 -305 -460 -306 193 184 -176 -140 -387 -464 -333 -303 -333 -234 236 -401 -323
-404 -537 -87 368 -618 -468 -318 -506 -406 -229 -459 -345 -504 -224 -425 -391 -423 -518 -560 -515
26 -225 -151 129 -332 -219 -50 -285 -113 -276 -174 -92 179 -42 -101 232 88 -265 -313 -219
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 9 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 21 nsites= 9 E= 3.5e-015
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.777778 0.111111 0.000000 0.000000 0.111111 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.222222 0.000000 0.000000 0.000000 0.000000 0.000000 0.555556 0.222222 0.000000 0.000000 0.000000
0.222222 0.000000 0.000000 0.000000 0.000000 0.222222 0.000000 0.000000 0.222222 0.000000 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.000000 0.000000 0.111111 0.111111
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.222222 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.000000 0.111111 0.555556
0.444444 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.333333 0.000000 0.222222 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.000000 0.111111 0.000000 0.333333 0.444444 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.333333 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.444444 0.000000 0.111111
0.111111 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.111111 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.666667 0.000000 0.000000
0.000000 0.000000 0.333333 0.222222 0.000000 0.000000 0.000000 0.000000 0.222222 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.111111 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.444444 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.555556 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.888889 0.000000 0.000000 0.000000 0.111111 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.222222 0.222222 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.000000 0.000000 0.444444 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.333333 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.666667 0.000000 0.000000
0.000000 0.000000 0.000000 0.111111 0.000000 0.000000 0.000000 0.111111 0.444444 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.222222 0.111111 0.000000 0.000000
0.333333 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.444444
0.333333 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.333333 0.111111 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.111111 0.000000 0.000000
0.222222 0.000000 0.000000 0.222222 0.222222 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.333333 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.222222 0.333333 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.444444 0.000000 0.000000
0.000000 0.000000 0.111111 0.777778 0.000000 0.000000 0.000000 0.000000 0.000000 0.111111 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.111111 0.000000 0.000000 0.222222 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.222222 0.000000 0.000000 0.333333 0.111111 0.000000 0.000000 0.000000
--------------------------------------------------------------------------------
Time 458.65 secs.
********************************************************************************
********************************************************************************
MOTIF 10 width = 29 sites = 7 llr = 376 E-value = 5.3e-014
********************************************************************************
--------------------------------------------------------------------------------
Motif 10 Description
--------------------------------------------------------------------------------
Simplified A ::14::::316::::1:::::::::::::
pos.-specific C :::::::::::::::::::::::::::::
probability D :::::6:::::::3:::::::::7:::::
matrix E :::::::3:::::::6::6::3:1:1:::
F ::::::9::::6::::6::1:::::::::
G 4:::::::::3:::7::1::::::::9::
H :::::::::::::::::::::::::::::
I :::3:::::3::::::11:6::1::1:::
K :73:3::6:1::1431:63:3:1::3:71
L :::1:::1::::::::1::::7::11:::
M ::::::::1::::::::::::::::::::
N 4::::1::31:::3:::::::::::::1:
P 1:1163:::::::::::::::::::::::
Q :::::::::1::::::::::::1::::::
R ::1::::::::::::1::::4::::3:1:
S ::::::1:::1:::::::::1:61::1::
T :33:1:::11::::::::1:1:::1::::
V :::::::::::34:::1::3:::::::::
W ::::::::::::::::::::::::::::6
Y ::::::::1::14::::1::::::7:::3
bits 6.2
5.6
5.0
4.3 *
Information 3.7 * * *
content 3.1 ** * ** * ** ***
(77.5 bits) 2.5 ** ***** *************** ***
1.9 *****************************
1.2 *****************************
0.6 *****************************
0.0 -----------------------------
Multilevel GKKAPDFKAIAFVKGEFKEIRLSDYKGKW
consensus NTTIKP EN GVYDK KVKE R Y
sequence N
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 10 sites sorted by position p-value
--------------------------------------------------------------------------------
Sequence name Start P-value Site
------------- ----- --------- -----------------------------
13541053 5 1.28e-26 MSLV NKAAPDFEANAFVNGEVKKIRLSSYRGKW VVLFFYPADF
6850955 5 8.03e-26 MVSV GKKAPDFEMAGFYKGEFKTFRLSEYLGKW VVLCFYPGDF
9955016 8 5.16e-25 XSGNARI GKPAPDFKATAVVDGAFKEVKLSDYKGKY VVLFFYPLDF
19173077 3 1.71e-21 MF PKTLTDSKYKAFVDGEIKEISLQDYIGKY VVLAFYPLDF
20151112 4 4.55e-21 SLI NTKIKPFKNQAFKNGEFIEVTEKDTEGRW SVFFFYPADF
11467494 8 9.97e-21 MTNFPKI GKTPPNFLTIGVYKKRLGKIRLSDYRGKK YVILFFYPAN
13186328 3 7.45e-19 ML NTRIKPFKNISYYKKKFYEIKEIDLKSNW NVFFFYPYSY
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 10 block diagrams
--------------------------------------------------------------------------------
SEQUENCE NAME POSITION P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
13541053 1.3e-26 4_[10]_141
6850955 8e-26 4_[10]_170
9955016 5.2e-25 7_[10]_161
19173077 1.7e-21 2_[10]_146
20151112 4.5e-21 3_[10]_154
11467494 1e-20 7_[10]_168
13186328 7.4e-19 2_[10]_145
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 10 in BLOCKS format
--------------------------------------------------------------------------------
BL MOTIF 10 width=29 seqs=7
13541053 ( 5) NKAAPDFEANAFVNGEVKKIRLSSYRGKW 1
6850955 ( 5) GKKAPDFEMAGFYKGEFKTFRLSEYLGKW 1
9955016 ( 8) GKPAPDFKATAVVDGAFKEVKLSDYKGKY 1
19173077 ( 3) PKTLTDSKYKAFVDGEIKEISLQDYIGKY 1
20151112 ( 4) NTKIKPFKNQAFKNGEFIEVTEKDTEGRW 1
11467494 ( 8) GKTPPNFLTIGVYKKRLGKIRLSDYRGKK 1
13186328 ( 3) NTRIKPFKNISYYKKKFYEIKEIDLKSNW 1
//
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 10 position-specific scoring matrix
--------------------------------------------------------------------------------
log-odds matrix: alength= 20 w= 29 n= 13619 bayes= 9.90401 E= 5.3e-014
-216 -281 -99 -207 -449 255 -84 -455 -242 -453 -365 306 101 -172 -238 -88 -194 -421 -417 -302
-284 -314 -338 -261 -473 -344 -127 -359 330 -365 -272 -199 -378 -116 13 -223 145 -378 -363 -322
40 -232 -138 -64 -293 -205 11 -239 160 -225 -123 -54 86 20 151 -40 182 -229 -259 -165
191 -98 -362 -291 -158 -265 -133 189 -277 57 -9 -229 91 -187 -213 -125 -107 -43 -204 -146
-159 -268 -279 -241 -371 -290 -144 -318 80 -300 -251 -222 368 -149 -159 -134 38 -306 -379 -325
-278 -330 321 -121 -444 -214 -84 -437 -255 -441 -363 149 156 -170 -254 -119 -221 -431 -413 -299
-336 -205 -452 -443 406 -439 -274 -233 -460 -158 -169 -383 -395 -394 -404 -97 -367 -291 -170 -18
-200 -316 -151 171 -396 -281 -55 -308 263 8 -197 -132 -290 -17 8 -139 -169 -300 -330 -250
123 -134 -169 -106 -177 -206 -13 -96 -97 -127 206 210 -226 -30 -75 -46 108 -109 -202 168
42 -199 -113 -44 -249 -185 24 139 81 -188 -88 132 -195 174 -17 -20 103 -182 -234 -138
281 -87 -395 -375 -381 143 -265 -331 -393 -342 -238 -283 -348 -293 -314 123 -160 -213 -366 -360
-356 -235 -474 -456 366 -449 -116 -228 -450 -185 -175 -351 -419 -342 -365 -294 -343 77 -105 207
-204 -176 -332 -264 -51 -317 -30 -114 65 -160 -93 -210 -329 -149 -121 -174 -170 189 -129 363
-238 -319 192 -124 -426 -173 -39 -421 217 -402 -315 265 -298 -98 -145 -71 -166 -407 -400 -264
-226 -310 -275 -324 -471 353 -209 -442 56 -467 -345 -188 -388 -269 -217 -194 -313 -421 -368 -358
39 -311 -102 260 -373 -254 -42 -302 94 -283 -183 -107 -258 -1 152 -105 -142 -285 -325 -233
-305 -204 -493 -457 362 -448 -283 63 -458 30 -66 -393 -415 -360 -388 -295 -284 13 -217 -92
-200 -238 -255 -183 -290 -10 -75 20 301 -242 -153 -148 -303 -79 -3 -145 -163 -236 -275 120
-185 -365 -71 272 -425 -273 -82 -338 159 -322 -223 -127 -276 -15 -81 -136 101 -314 -379 -281
-295 -240 -440 -425 -7 -442 -313 339 -398 -58 -46 -343 -443 -340 -362 -301 -232 126 -347 -267
-206 -291 -242 -149 -389 -275 -30 -305 189 -280 -185 -119 -295 -10 302 111 107 -300 -304 -232
-291 -271 -281 120 -207 -402 -220 -119 -300 286 -24 -305 -371 -192 -257 -278 -262 -194 -304 -258
-138 -201 -173 -106 -298 -230 -27 38 70 -237 -137 -75 -243 153 -22 306 -6 -239 -273 -188
-320 -339 369 -32 -438 -341 -157 -400 -363 -426 -342 -50 -428 -251 -320 -90 -323 -405 -386 -329
-205 -166 -320 -286 75 -323 72 -169 -285 2 -105 -227 -310 -210 -210 -162 55 -200 -60 435
-160 -253 -191 73 -322 -243 -12 67 179 12 -141 -93 -256 3 241 -89 -119 -244 -275 -193
-203 -289 -280 -343 -465 365 -229 -439 -339 -478 -343 -197 -383 -314 -270 -12 -312 -412 -360 -362
-347 -330 -444 -368 -533 -422 -209 -384 356 -429 -325 -56 -421 -221 66 -325 -318 -451 -385 -390
-415 -304 -443 -432 -87 -426 -145 -373 -50 -266 -257 -334 -450 -296 -290 -344 -367 -378 574 217
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
Motif 10 position-specific probability matrix
--------------------------------------------------------------------------------
letter-probability matrix: alength= 20 w= 29 nsites= 7 E= 5.3e-014
0.000000 0.000000 0.000000 0.000000 0.000000 0.428571 0.000000 0.000000 0.000000 0.000000 0.000000 0.428571 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.714286 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000
0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.142857 0.000000 0.142857 0.000000 0.285714 0.000000 0.000000 0.000000
0.428571 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.142857 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.571429 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000
0.000000 0.000000 0.571429 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.857143 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.571429 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.285714 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.142857
0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.285714 0.142857 0.000000 0.000000 0.142857 0.000000 0.142857 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000
0.571429 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.571429 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.142857
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.428571 0.000000 0.428571
0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.428571 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.714286 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.142857 0.000000 0.000000 0.571429 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.571429 0.000000 0.000000 0.142857 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.142857 0.571429 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857
0.000000 0.000000 0.000000 0.571429 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.571429 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.428571 0.142857 0.142857 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000 0.714286 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.142857 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.571429 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.714286 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.714286
0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.142857 0.285714 0.142857 0.000000 0.000000 0.000000 0.000000 0.285714 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.857143 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.714286 0.000000 0.000000 0.142857 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.142857 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.571429 0.285714
--------------------------------------------------------------------------------
Time 495.64 secs.
********************************************************************************
********************************************************************************
SUMMARY OF MOTIFS
********************************************************************************
--------------------------------------------------------------------------------
Combined block diagrams: non-overlapping sites with p-value < 0.0001
--------------------------------------------------------------------------------
SEQUENCE NAME COMBINED P-VALUE MOTIF DIAGRAM
------------- ---------------- -------------
1091044 2.42e-23 42_[2(3.68e-13)]_14_[4(1.02e-10)]_36_[9(1.31e-16)]_15
11467494 1.57e-72 7_[10(9.97e-21)]_1_[2(1.72e-12)]_12_[4(1.23e-14)]_9_[8(7.88e-10)]_7_[5(2.81e-37)]_36
11499727 6.74e-33 15_[1(2.44e-24)]_7_[3(2.40e-21)]_25
1174686 2.97e-30 20_[1(1.08e-21)]_9_[3(4.48e-21)]_40
12044976 2.53e-29 17_[1(3.84e-20)]_6_[3(1.30e-20)]_21
13186328 1.31e-65 2_[10(7.45e-19)]_[2(3.67e-11)]_12_[4(1.37e-14)]_4_[8(8.70e-10)]_8_[5(1.48e-32)]_18
13358154 6.02e-27 19_[1(7.89e-22)]_7_[3(1.07e-17)]_22
13541053 1.55e-86 4_[10(1.28e-26)]_[2(1.14e-19)]_12_[4(3.58e-15)]_6_[8(1.69e-05)]_8_[5(3.96e-39)]_12
13541117 1.86e-50 5_[6(3.66e-12)]_5_[2(4.55e-16)]_12_[4(7.49e-14)]_2_[8(5.14e-13)]_19_[7(1.24e-17)]_22
135765 5.48e-36 15_[1(4.41e-25)]_7_[3(2.50e-23)]_23
1388082 1.52e-30 27_[1(6.65e-24)]_7_[3(8.53e-20)]_18
140543 2.16e-26 42_[1(5.53e-21)]_6_[3(5.14e-18)]_21
14286173 1.16e-52 4_[6(9.90e-05)]_5_[2(7.50e-16)]_12_[4(3.08e-13)]_8_[8(3.42e-07)]_8_[5(6.53e-29)]_48
14578634 1.79e-24 55_[6(3.40e-15)]_2_[1(9.96e-13)]_28_[8(3.64e-05)]_8_[8(1.47e-07)]_25
14600438 5.52e-50 4_[6(5.44e-15)]_5_[2(1.61e-16)]_12_[4(5.52e-13)]_2_[8(2.48e-09)]_15_[7(2.40e-13)]_33
15218394 4.73e-28 21_[1(9.96e-23)]_7_[3(9.80e-19)]_26
15597673 1.63e-22 132_[6(1.26e-10)]_2_[1(9.96e-23)]_29_[3(7.76e-06)]_36
15599256 9.34e-30 24_[1(9.60e-24)]_7_[3(8.53e-20)]_200
15602312 1.02e-24 42_[6(2.41e-10)]_2_[1(7.24e-13)]_30_[3(1.02e-10)]_22
15605725 1.09e-23 36_[6(1.34e-11)]_2_[1(3.99e-23)]_58
15605963 3.45e-22 21_[6(3.89e-05)]_5_[2(5.32e-10)]_10_[4(8.06e-12)]_34_[7(1.42e-14)]_22
15609375 1.05e-35 4_[6(2.46e-13)]_6_[2(3.44e-12)]_12_[4(1.30e-10)]_2_[8(7.88e-10)]_15_[7(1.61e-13)]_22
15609658 5.42e-42 9_[6(3.44e-16)]_5_[2(2.82e-14)]_12_[4(7.40e-07)]_2_[8(1.88e-14)]_19_[7(2.98e-12)]_18
15613511 8.97e-47 3_[6(1.82e-19)]_5_[2(7.50e-16)]_12_[4(2.74e-12)]_2_[8(1.11e-08)]_19_[7(4.69e-14)]_21
15614085 9.35e-29 34_[6(5.78e-05)]_3_[1(1.64e-21)]_33_[3(4.93e-14)]_28
15614140 3.44e-39 38_[6(4.56e-12)]_2_[1(8.21e-21)]_30_[3(2.81e-13)]_27
15615431 5.03e-37 47_[6(3.66e-12)]_2_[1(1.79e-20)]_33_[3(3.09e-12)]_23
15643152 2.42e-25 25_[2(1.21e-12)]_8_[4(1.62e-11)]_2_[8(9.40e-09)]_11_[7(4.69e-14)]_204
15672286 6.37e-29 19_[6(9.16e-14)]_4_[2(6.58e-10)]_10_[4(1.32e-09)]_31_[9(3.35e-13)]_16
15790738 2.18e-39 35_[10(1.17e-05)]_2_[2(8.20e-17)]_12_[4(6.75e-12)]_2_[8(2.25e-12)]_17_[7(1.98e-14)]_44
15791337 3.50e-28 [1(2.90e-19)]_7_[3(6.61e-19)]_24
15801846 6.95e-27 21_[6(1.08e-09)]_5_[2(1.51e-09)]_10_[4(1.69e-13)]_35_[7(7.71e-12)]_20
15805225 1.36e-39 47_[6(4.65e-14)]_2_[1(3.96e-26)]_25_[8(1.16e-09)]_6_[8(6.83e-05)]_25
15805374 3.44e-37 53_[6(3.79e-11)]_2_[1(2.01e-27)]_25_[8(8.63e-09)]_6_[8(6.72e-06)]_22
15807234 6.99e-52 4_[6(3.01e-17)]_6_[2(5.16e-16)]_12_[4(7.89e-15)]_2_[8(5.59e-09)]_13_[7(5.06e-17)]_22
15826629 1.24e-25 33_[2(7.69e-13)]_14_[4(2.10e-10)]_38_[9(6.10e-18)]_17
15899007 5.23e-28 47_[1(3.01e-22)]_6_[3(2.81e-21)]_24
15899339 6.23e-45 4_[6(3.56e-09)]_6_[2(1.24e-16)]_12_[4(1.59e-15)]_2_[8(1.28e-09)]_18_[7(1.72e-17)]_22
15964668 3.66e-26 35_[2(1.20e-14)]_14_[4(1.58e-07)]_36_[9(1.20e-20)]_17
15966937 2.09e-23 59_[1(3.99e-23)]_7_[3(2.09e-15)]_206
15988313 1.83e-20 36_[6(1.33e-06)]_2_[1(4.16e-22)]_98
16078864 1.65e-46 35_[6(6.39e-16)]_2_[1(7.26e-28)]_28_[8(5.84e-10)]_6_[7(1.36e-10)]_16
16123427 2.80e-28 51_[1(5.03e-23)]_7_[3(1.65e-18)]_29
16125919 1.43e-20 25_[10(2.05e-05)]_1_[2(3.85e-14)]_12_[4(4.39e-07)]_31_[7(6.86e-11)]_23
16330420 7.96e-33 45_[6(9.44e-17)]_6_[2(5.37e-09)]_35_[8(6.86e-11)]_36_[7(1.01e-12)]_25
1633495 1.63e-31 19_[1(1.08e-23)]_7_[3(4.19e-20)]_24
16501671 6.10e-67 4_[6(1.80e-07)]_11_[2(1.75e-15)]_12_[4(9.92e-16)]_9_[8(2.22e-06)]_8_[5(2.15e-40)]_32
1651717 1.52e-21 32_[1(5.02e-18)]_7_[3(1.70e-15)]_29
16759994 3.23e-25 58_[1(2.73e-21)]_27_[3(1.13e-12)]_25
16761507 5.77e-31 51_[1(4.41e-25)]_7_[3(5.79e-19)]_23
16803644 4.66e-62 38_[2(2.64e-17)]_12_[4(6.75e-12)]_9_[8(1.67e-10)]_8_[5(5.68e-41)]_11
16804867 1.08e-24 17_[1(1.82e-21)]_7_[3(4.74e-16)]_24
17229033 2.65e-27 36_[2(8.66e-12)]_14_[4(1.43e-12)]_35_[9(3.84e-19)]_107
17229859 4.12e-27 20_[1(6.33e-23)]_7_[3(3.99e-17)]_23
1729944 3.67e-17 16_[1(2.50e-16)]_7_[3(1.23e-12)]_26
17531233 1.02e-26 26_[1(7.10e-22)]_6_[3(9.82e-20)]_25
17537401 7.66e-21 25_[1(1.21e-20)]_35_[3(1.42e-11)]_31
17547503 5.49e-26 38_[6(6.75e-05)]_2_[1(1.68e-25)]_1_[4(2.18e-08)]_27_[8(2.08e-05)]_20
18309723 5.43e-36 261_[6(7.05e-12)]_2_[1(4.41e-25)]_37_[3(5.20e-13)]_24
18313548 5.34e-50 5_[6(7.88e-15)]_7_[2(6.63e-16)]_12_[4(3.76e-16)]_2_[8(6.00e-13)]_19_[7(1.71e-15)]_25
18406743 6.87e-21 42_[1(1.34e-20)]_33_[3(7.89e-10)]_69_[1(2.86e-07)]_33_[3(1.70e-10)]_69_[1(1.48e-21)]_33_[3(9.84e-09)]_125
19173077 4.24e-66 2_[10(1.71e-21)]_[2(1.46e-17)]_12_[4(6.34e-17)]_32_[5(3.86e-28)]_14
19554157 3.34e-14 13_[1(3.42e-14)]_27_[8(1.02e-08)]_37
19705357 1.78e-31 14_[6(2.53e-06)]_2_[1(1.66e-24)]_38_[8(2.72e-09)]_45
19746502 1.82e-28 67_[6(5.44e-15)]_2_[1(2.34e-15)]_35_[3(3.66e-13)]_24
20092028 2.59e-33 5_[1(1.89e-24)]_7_[3(3.13e-20)]_23
20151112 6.22e-71 3_[10(4.55e-21)]_[2(4.55e-16)]_12_[4(6.13e-16)]_6_[8(2.19e-05)]_8_[5(3.57e-32)]_25
21112072 8.72e-28 34_[2(3.47e-14)]_13_[4(1.25e-13)]_36_[9(1.16e-17)]_18
21222859 3.39e-31 78_[6(2.90e-06)]_2_[1(2.01e-21)]_27_[8(1.34e-10)]_12_[7(2.46e-11)]_21
21223405 6.27e-55 37_[2(1.05e-13)]_12_[4(1.53e-13)]_6_[8(3.84e-11)]_7_[5(9.87e-34)]_19
21227878 4.61e-31 7_[6(1.34e-11)]_5_[2(5.85e-13)]_12_[4(5.52e-13)]_33_[7(2.46e-11)]_20
21283385 3.54e-29 20_[6(2.53e-14)]_5_[2(6.53e-09)]_9_[4(1.08e-12)]_32_[7(3.38e-11)]_21
21674812 6.74e-49 4_[6(3.37e-19)]_5_[2(1.97e-15)]_12_[4(3.58e-15)]_2_[8(8.61e-11)]_12_[7(3.97e-11)]_21
23098307 3.79e-49 28_[6(1.05e-16)]_2_[1(5.65e-23)]_30_[3(2.85e-15)]_24
2649838 3.34e-07 31_[3(5.25e-15)]_33
267116 8.58e-25 18_[1(4.58e-24)]_6_[3(3.07e-13)]_22
27375582 2.01e-26 48_[6(2.50e-05)]_10_[1(1.63e-20)]_28_[3(1.67e-11)]_29
2822332 2.00e-30 32_[1(2.73e-21)]_5_[3(2.06e-22)]_24
30021713 5.30e-48 52_[6(1.18e-16)]_2_[1(1.70e-27)]_34_[3(1.49e-13)]_24
3261501 4.00e-17 17_[1(3.79e-13)]_6_[3(1.56e-14)]_43
3318841 9.83e-45 33_[2(6.63e-16)]_12_[4(4.55e-13)]_12_[8(1.41e-09)]_14_[5(8.83e-27)]_50
3323237 3.75e-28 17_[1(1.20e-21)]_7_[3(8.53e-20)]_23
4155972 5.34e-21 15_[1(2.21e-19)]_7_[3(5.25e-15)]_24
4200327 6.70e-24 77_[1(6.73e-20)]_7_[3(1.65e-18)]_24
4433065 2.70e-43 15_[2(2.10e-16)]_12_[4(1.59e-19)]_9_[8(3.89e-10)]_13_[7(1.19e-13)]_13
4704732 3.13e-25 37_[2(2.05e-14)]_14_[4(3.60e-14)]_36_[9(2.30e-13)]_16
4996210 7.00e-45 33_[2(4.01e-16)]_12_[4(9.20e-14)]_38_[5(2.00e-31)]_49
5326864 3.94e-25 46_[2(5.55e-15)]_14_[4(2.04e-08)]_31_[9(2.32e-16)]_17
6322180 5.27e-28 65_[6(1.10e-10)]_7_[2(4.26e-14)]_11_[4(3.49e-11)]_2_[8(1.28e-11)]_56
6323138 1.01e-24 48_[2(9.94e-11)]_15_[4(1.69e-13)]_36_[9(3.52e-18)]_18
6687568 3.18e-29 18_[1(8.90e-23)]_6_[3(1.30e-20)]_22
6850955 2.59e-79 4_[10(8.03e-26)]_[2(1.16e-13)]_12_[4(7.15e-18)]_9_[8(1.67e-10)]_8_[5(5.66e-34)]_38
7109697 5.90e-32 16_[1(3.57e-24)]_6_[3(2.06e-22)]_20
7290567 5.98e-30 19_[1(5.05e-25)]_7_[3(2.34e-20)]_27
9955016 8.64e-90 7_[10(5.16e-25)]_[2(2.52e-19)]_12_[4(5.72e-19)]_9_[8(8.63e-09)]_8_[5(7.82e-38)]_29
15677788 1.21e-24 24_[6(2.67e-13)]_2_[1(5.24e-13)]_31_[3(7.37e-07)]_30
--------------------------------------------------------------------------------
********************************************************************************
********************************************************************************
Stopped because nmotifs = 10 reached.
********************************************************************************
CPU: bmf1
********************************************************************************
PyCogent-1.5.3/doc/data/primate_brca1.fasta 000644 000765 000024 00000047175 11261304034 021457 0 ustar 00jrideout staff 000000 000000 >Galago
TGTGGCAAAAATACTCATGCCAGCTCATTACAGCATGAGAGCAGTTTATTACTCACTAAA
GACAAAATGAATGTAGAAAAGGCTGAATTTTGTAATAAAAGCAAACAGCCTGGCTTAGCA
AGGAGCCAACAGAGCAGATCGGCTCAAAGTAAGGAAACATGCAATGATAGGCACACTTGC
AGCCCTGAGCAAAAGGTAGATCTGAATACTGCTCCCCCATATGGGAGAAAAGAACAGAAT
AAGGAGAAACTTCTATGCTCCAAGAATCCTAGAGATAGCCAAGATGTTCCTTGGATAACA
CTAAATAGCAGCATTCAGAAAGTTAATGAATGGTTTTCTAGAAGTGATGAAATGTTAACT
TCTGATGACTCACATGATGAGGGTTCTGAATCACATGCTGAAGTAGCTGGAGCCTTAGAA
GTTCCAAGTGAAGTAGATGGATATTCCAGTTCCTCAGAGAAAATAGACTTACTGGCCAGT
GATCCTCATTATCCTATAATATGTAAAAGTGAAAGAGTTCACTCCAAACCAATAAAGAGT
AAAGTTGAAGATAAAATATTTGGGAAAACTTATCGGAGGAAGGCAAGCCTCCCTAACTTA
AGCCATGTAACTGAAAATCTAATTATAAGAGCAGCTGCTACTGAGCCACAGATAACACAA
GAGTGTTCCCTCACAAATAAATTAAAACGTAAAAGGAGAACTACATCAGGTCTTTGTCCT
GAGGATTTTATCAAGAAGGCAGATTTGGCAGTTCAAAAGACACCTGAAAAGAGAATTCAG
GGAACTAACCAAGTGGATCAGAATAGTCACGTGGTAAATATTACTAATAGTGGTTATGAG
AATGAAACAAAAGGTGATTATGTTCAGAATGAAAAAAATGCTAACTCAACAGAATCATTG
GAAAAAGAATCTCTCGGAACTAAAGCTGAACCTATAAGCAGCAGTATAAGTAATATGAAA
TTAGAATTAAATATTCACAATTCAAAAGCAAGTAAAAAGAAAAGGCTGAGGAAGAAGTCT
TCTAGCAGGCATATTCGTGCACTTGAACTAGTAGTCAATAAAAATCCAAGCCCTCCTAAT
CATACCAACCTACAAATTGACAGTTGTTCTAGCAGTGAAGAAATAAAGGATAAAAGTTCT
GACCAAATACCAGTCAGGCATAGCAGAAAGCCTGGACTCATGGAAGATAGAGAACCTGCA
ACTGGAGCCAAGAAAAGTAACAAGCCAAATGAGCAAATAAGTAAAAGACATGTCAGTGAT
ACTTTCCCAGAAGTGGCATTAACAAATATATCTAGTTTTTTTACTAACTGTTCAGGTTCT
AATAGAAAAGAATTTGTCAATCCTAGCCTTCAAAGAAAAAAAACAGAAGAGAACGAAGAA
ACAATTCAAGTGTCTAATAGTACCAAAGGTCCGGTGTTAAGTGGAGAAAGGGTTTTGCAA
ATTGAAAGTGAAGAAAGATCTATAAAAAGCACCAGTATTTCATTGGTACCTGATACTGAT
TATGGTACTCAGGACAGTAACTCGTTACTGAAAGTTAAAGTCTTACGGAAGGTGAAAACA
GCACCAAATAAACATGCAAGTCAGGGTACAGCCACTGAAAACCCCAAGGAACTAATCCAT
GGTTGCTCTAAAGATACTGGAAATGACACAGAGGGCTATAAGGATCCATTGAGACATGAA
ATTAACCACATTCAGAAGATAAGCATGGAAATGGAAGACAGTGAACTTGATACTCAGTAT
TTACAGAATACATTCAAGTTTTCAAAGCGTCAGTCGTTTGCTCTGTTTTCAAACCTAGGA
AAGGAATGTGCAACAGTCTGTGCCCAGTCTCTCTCTGCGTCCTTAAGAAAAGGTTCAAAA
GTCATTCTTGAATGTGAACAAATAGAAAATCCAGGAATGAAAGAGCCTAAAATCAAGCAT
ATACAGGGAAATAATATCAATACAGGCTTCTCTGTAGTTTGTCAGAAAGATAAGACAGAT
GATTATGCCAAATACATCAAAGAAGCATCTAGGTTTTGTTTGTCAAATCAGTTTCGAGAC
AATGAAACTGAATCCATTACTGTAAATAAACTTGGAATTTTACAAAACCTCTATCATATA
CCACCACTTTCTCCTATCAGGCTATTTGATAAAACTAAATGTAATACAAACCTGTTAGAG
GAAAGGTTTGAAGAACATTCAGTGTTACCTGAAAAAGCAGTAGGAAACGAGAACGTTCCA
AGTACAATGAATACAATTAACCAAAATAACAGAGAAAGTGCTTATAAAGAAGCCAGTTCA
AGCAGTATCAATGAAGTAAGCTCGAGTACTAATGAAGTGGGCTCCAGTGTTAACGAAGTA
GGCCCCAGTAGTGAAAACATTCAAGCAGAACTAGATAAAAACAGAGGACCTAAGTTGAAT
GCTGTGCTTAGATTAGGTCTTATGCAACCTGAAGTCTATAAACAAAATCTTCCTATAAGT
AATTGTGAACATCCTAAAATAAAAGGGCAAGAAGAAAATGGAGTAGTTCAACCTGTTAAT
CCAGATTTTTCTTCATGTCTAATTTCAGATAACCTAGAACAACCTACGAGAAGTAGTCAT
GCTTCTCAGCTTTGTTCTGAGACACCTGATGACTTATTAGTTGATGATGAACTAAAGGAA
AATACCAGTTTTGCTGAAAATAACATTAAGGAAAGATCTGCTGTTTTTAGCAAAAATGTC
ATGAGAAGAGAGATTAGCAGGAGCCCTAGCCCTTTAGCCCATATACATTTGACTCAGGCT
CACCAAAGAGAGGTTAGGAAATTAGAGTCCTCAGAAGAGAACATGTCTAGTGAA
>HowlerMon
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGTTTGTTACTCACTAAA
GACACACTGAATGTAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCA
AGGAGCCAACATAACAGATGGGCTGAAAGTGAGGAAACATGTAATGATAGGCAGACTCCC
AGCACAGAGAAAAAGGTAGATGTGGATGCTGATCCCCTGCATGGGAGAAAAGAATGGAAT
AAGCAGAAACCTCCGTGCTCTGAGAATCCTAGAGATACTGAAGATGTTGCTTGGATAATG
CTAAATAGCAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAACT
TCTGATGACTCACATGATGGGGGGTCTGAATCAAATGCCAAAGTAGCTGAAGCATTGGAA
GTTCTAAATGAGGTAGATGGATATTCTAGTTCTTCAGAGAAAATAGACTTACTGGCCAGT
GATCCTCATGATCATTTGATATGTAAAAGTGAAAGAGTTCACTGCAAATCAGTAGAGAGT
AGTATTGAAGATAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCTAACTTG
AGCCACGTAACTGAAAATCTAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA
GAGCATCCTCTCACAAATAAATTAAAGCGTAAAAGGAGAGTTACATCAGGACTTCATCCT
GAGGATTTTATCAAGAAAGCAGATTTGGCAGTTCAAAAGACTCCTGAAAAGATAAATCAG
GGAACTAACCAAACAGAGCGGAATGATCAAGTGATGAATATTACTAACAGTGGTCATGAG
AATAAAACAAAAGGTGATTCTATTCAGAATGAGAACAATCCTAACCCAGTAGAATCACTG
GAAAAAGAATCATTCAAAAGTAAAGCTGAACCTATAAGCAGTAGTATAAGCAATATGGAA
TTAGAATTGAATGTCCACAATTCCAAAGCATCTAAAAAGAATAGGCTGAGAAGGAAGTCT
TCTACCAGGCATATTCATGAGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAAT
TATACTGAAGTACAAATTGATAGTTGTTCTAGCAGTGAAGAGATAAAGAAAAAAAATTAC
AACCAAATGCCAGTCAGGCACAGCAGAAAGCTACAACTCATGGAAGATAAAGAACGTGCA
GCTAGAGCCAAAAAGAGTAGCAAGCCAAATGAACAAACAAGTAAAAGACATGCCAGTGAT
ACTTTCCCAGAACTGAGGTTAACAAACATACCTGGTTCTTTTACTAACTGTTCAAATACT
AATGAAAAAGAATTTGTCAATCCTAGCCTTCCAAGAGAACAAACAGAAGAGAAACTAGAA
ACAGTTAAACTGTCTAATAATGCCAAAGACCCCAAAGATCTCATGTTAAGTGGAGAAAGT
GTTTTGCAAATTGAAAGATCTGTAGAGAGTAGCAGTATTTTGTTGATACCTGGTACTGAT
TATGGCACTCAGGAAAGTATCTCATTACTGGAAGTTAGCACTCTGGGGAAGGCAAAAACA
GAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGAACTAATTCAT
GGTTGTTCTAAAGATACTAGAAATGGCACAGAAGGCTTGAAGTATCCATTGGGACCTGAA
GTTAACTACAGTCAGGAAACAAGCATAGATATGAGAGAAAGTGAACTTGATACTCAATAT
TTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCTGTTTTCAAATCCAGGA
AAGGAATGTGCAACATTCTCTGCCTGCTCTAGGTCCTTAAAGAAACAAAGTCCAAAGGTC
ACTCCTGAATGTGAACAAAAGGAAGAAAATCAAGGAGAGAAAGAGTCTAATATCGAGCTT
GTAGAGACAGTTAATACCACTGCAGGCTTTCCTATGGTTTGTCAGAAAGATAAGCCAGTT
GATTATGCCAGATGTATCGAAGGAGGCTCTAGGCTTTGTCTATCATCTCAGTTCAGAGGC
AACGAAACTGGACTCATTATTCCAAATAAACATGGACTTTTACAGAACCCATATCATATG
TCACCGCTTATTCCCACCAGGTCATTTGTTAAAACTAAATGTAAGAAAAACCTGCTAGAA
GAAAACTCTGAGGAACATTCAATGTCACCTGAAAGAGCAATGGGAAACAAGAACATTCCA
AGTACAGTGAGCACAATTAGCCATAATAACAGAGAAAATGCTTTTAAAGAAACCAGCTCA
AGCAGTATTTATGAAGTAGGTTCCAGTACTAATGAAGCAGGTTCTAGTACTAATGAAGTA
GGCTCCAGTGATGAAAACATTCAAGCAGAGCTAGGTAGAAACAGAAGGCCAAAATTGAAT
GCTATGCTTAGATTAGGGCTTCTGCAACCTGAGATTTGTAAGCAAAGTCTTCCTATAAGT
GATTGTAAACATCCTGAAATTAAAAAGCAAGAACATGAAGAAGTAGTTCAGACTGTTAAT
ACAGACGTCTCTCTATGTCTGATTTCATATAACCTAGAACAGCATATGGGAAGCAGTCAT
ACATCTCAGGTTTGTTCTGAGACACCTGACAACCTGTTAGATGATGGTGAAATAAAGGAA
GATACTAGTTTTGCTGAATATGGCATTAAGGAGACTTCTACTGTTTTTAGCAAAAGTGTC
CAGAGAGGAGAGCTCAGCAGGAGCCCTAGCCCTTTCACCCATACACATTTGGCTCAGGTT
TACCAAAGAGGGGCCAAGAAATTAGAGTCCTCGGAAGAGAATTTATCTAGTGAG
>Rhesus
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGTTTGTTACTCACTAAA
GACAGAATGAATGTAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTGGCA
AGGAGCCAACATAACAGATGGACTGGAAGTAAGGAAACATGTAATGATAGGCAGACTCCC
AGCACAGAGAAAAAGGTAGATCTGAATGCTAATGCCCTGTATGAGAGAAAAGAATGGAAT
AAGCAAAAACTGCCATGCTCTGAGAATCCTAGAGACACTGAAGATGTTCCTTGGATAACA
CTAAATAGCAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAAGT
TCTGATGACTCACATGATGGGGGGTCTGAATCAAATGCCAAAGTAGCTGATGTATTGGAC
GTTCTAAATGAGGTAGATGAATATTCTGGTTCTTCAGAGAAAATAGACTTACTGGCCAGT
GATCCTCATGAGCCTTTAATATGTAAAAGTGAAAGAGTTCACTCCAGTTCAGTAGAGAGT
AATATTAAAGACAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAACCTTCCCAATTTA
AGCCATGTAACTGAAAATCTAATTATAGGAGCACTTGTTACTGAGTCACAGATAATGCAA
GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGAACTACATCAGGTCTTCATCCT
GAGGATTTTATAAAGAAAGCAGATTTGGCAGTTCAAAAGACTCCTGAAATAATAAATCAG
GGAACTAACCAAATGGAGCAGAATGGTCAAGTGATGAATATTACTAATAGTGCTCATGAG
AATAAAACAAAAGGTGATTCTATTCAGAATGAGAAAAATCCTAACCCAATAGAATCACTG
GAAGAAGAATCTTTCAAAACTAAAGCTGAACCTATAAGCAGCAGTATAAACAATATGGAA
CTAGAATTAAATATCCACAATTCAAAAGCACCTAAAAAAAATAGGCTGAGGAGGAAGTCT
TCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAAC
TGTACTGAACTACAAATTGATAGTTGTTCTAGCAGTGAAGAGATAAAGAAAAAAAATTAC
AACCAAATGCCAGTCAGGCACAGCAGAAACCTACAACTCATGGAAGATAAAGAATCTGCA
ACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGACATGCCAGTGAT
ACTTTCCCAGAACTGAAGTTAACAAAGGTACCTGGTTCTTTTACTAACTGTTCAAATACT
AGTGAAAAAGAATTTGTCAATCCTAGCCTTTCAAGAGAAGAAAAAGAAGAGAAACTAGAA
ACAGTTAAAGTGTCTAATAATGCCAAAGACCCCAAAGATCTCATCTTAAGTGGAGAAAGG
GTTTTACAAACTGAAAGATCTGTAGAGAGTAGCAGTATTTCATTGGTACCTGGTACCGAT
TATGGCACTCAGGAAAGTATCTCATTACTGGAAGTTAGCACTCTAGGGAAGGCAAAAACA
GAACGAAATAAATGTATGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGAACTAATTCAT
GGTTGTTCTGAAGATACTAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGAAGTGAA
GTTAACCACAGTCAGGAAACAAGCATAGAAATAGAAGAAAGTGAACTTGATACTCAGTAT
TTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCCTTTGCTCTGTTTTCAAATCCAGGA
GAGGAATGTGCAACATTCTCTGCCCACTCTAGGTCCTTAAAGAAACAAAGTCCAAAAGTT
ACTTCTGAATGTGAACAAAAGGAAGAAAATCAAGGAAAGAAACAGTCTAATATCAAGCCT
GTACAGACAGTTAATATCACTGCAGGCTTTTCTGTGGTTTGTCAGAAAGATAAGCCAGTT
GATAATGCCAAATGTATCAAAGGAGGCTCTAGGTTTTGTCTATCATCTCAGTTCAGAGGC
AACGAAACTGGACTCATTACTCCAAATAAACATGGACTGTTACAAAACCCATACCATATA
CCACCACTTTTTCCTGTCAAGTCATTTGTTAAAACTAAATGTAACAAAAACCTGCTAGAG
GAAAACTCTGAGGAACATTCAGTGTCACCTGAAAGAGCAGTGGGAAACAAGAACATTCCA
AGTACAGTGAGCACAATTAGCCATAATAACAGAGAAAATGCTTTTAAAGAAGCCAGCTCG
AGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGTGGGCTCCAGTATTAATGAAGTA
GGTTCCAGTGATGAAAACATTCAAGCAGAACTAGGTAGAAACAGAGGGCCAAAATTGAAT
GCTGTGCTTAGATTAGGGCTTTTGCAACCTGAGGTCTGTAAACAAAGTCTTCCTATAAGT
AATTGTAAGCATCCTGAAATAAAAAAGCAAGAACATGAAGAATTAGTTCAGACTGTTAAT
ACAGACTTCTCTCCATGTCTGATTTCAGATAACCTAGAACAGCCTATGGGAAGTAGTCAT
GCGTCTGAGGTTTGTTCTGAGACTCCTGATGATCTGTTAGATGATGGTGAAATAAAGGAA
GATACTAGTTTTGCTGAAAATGACATTAAGGAGAGTTCTGCTGTTTTTAGCAAAAGCATC
CAGAGAGGAGAGCTCAGCAGGAGCCCTAGCCCTTTCACCCATACACATTTAGCTCAGGGT
TACCGAAAAGAGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Orangutan
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGTTTATTACTCACTAAA
GACAGAATGAATGTAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCA
AGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAACATGTAATGATAGGCAGACTCCC
AGCACAGAAAAAAAGGTAGACCTGAATGCTGATCCCCTGTGTGAGAGAAAAGAATGGAAT
AAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGATACTGAAGATGTTCCTTGGATAACA
CTAAATAGCAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGACGAACTGTTAGGT
TCTGATGACTCACATGATGGGAGGTCTGAATCAAATGCCAAAGTAGCGGATGTATTGGAC
GTTCTAAATGAGGTAGATGAATATTCTGGTTCTTCAGAGAAAATAGACTTACTGGCCAGT
GATCCTCATGAGGCTTTAATTTGTAAAAGTGAAAGAGTTCACTCCAAATCAGTAGAGAGT
AATATTGAAGACAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCCAACTTA
AGCCATGTAACTGAAAATCTAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA
GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGAGCTACATCAGGCCTTCATCCT
GAGGATTTTATCAAGAAAGCAGATTTGGCAGTTCAAAAGACTCCTGAAATGATAAATCAG
GGAACTAACCAAATGGAGCAGAATGGTCAAGTGATGAATATTACTAATAGTGGTCATGAG
AATAAAACAAAAGGTGATTCTATTCAGAATGAGAAAAATCCTAACCCAATAGAATCACTC
GAAAAAGAATCTTTCAAAACAAAAGCTGAACCTATAAGCAGCAGTATAAGCAATATGGAA
CTCGAATTAAATATCCATAATTCAAAAGCACCTAAAAAGAATAGGCTGAGGAGGAAGTCT
TCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAAT
TGTACTGAATTGCAAATTGATAGTTGTTCTAGCAGTGAAGAGATAAAGAAAAAAAAATAC
AACCAAATGCCAGTCAGGCACAGCAGAAACCTACAACTCATGGAAGATAAAGAACCTGCA
ACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGACATGACAGCGAT
ACTTTCCCAGAGCTGAAGTTAACAAATGCACCTGGTTCTTTTACTAACTGTTCAAATACC
AGTGAGAAAGAATTTGTCAATCCTAGCCTTCCAAGAGAAGAAAAAGAAGAGAAACTAGGA
ACAGTTAAAGTGTCTAATAATGCCAAAGACCCCAAAGATCTCATGTTAAGTGGAGGAAGG
GTTTTGCAAACTGAAAGATCTGTAGAGAGTAGCAGTATTTCATTGGTACCTGGTACTGAT
TATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGGAAGGCAAAAACA
GAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGAACTAATTCAT
GGTTGTTTCAAAGATACTAGAAATGACACAGAAGGGTTTAAGTATCCATTGGGACATGAA
GTTAACCACAGTCAGGAAACAAGCATAGAAATGGAAGAAAGTGAACTTGATACTCAGTAT
TTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCTGTTTTCAAATCCAGGA
GAGGAATGTGCAACATTCTCTGCCCACTCTAGGTCCTTAAAGAAACAAAGTCCAAAAGTC
ACTTTTGAATGTGAACAAAAGGAAGAAAATCAAGGAAAGAATGAGTCTAATATCAAGCCT
GTACAGACAGCTAATATCACTGCAGGCTTTCCTGTGGTTTGTCAGAAAGATAAGCCAGTT
GATTATGCCAAATGTATCAAAGGAGGCTCTAGGTTTTGTCTATCATCTCAGTTCAGAGGC
AACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTCACAAAACCCATATCATATA
CCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAACCTGCTAGAG
GAAAACTCTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAACGAGAACATTCCA
AGTACAGTGAGCATAATTAGCCGTAATAACAGAGAAAATGTTTTTAAAGAAGCCAGCTCA
AGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGTGGGCTCCAGTATTAATGAAGTA
GGTTCCAGTGATGAAAACATTCAAGCAGAACTAGGTAGAAGCAGAGGGCCAAAATTGAAT
GCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTATAAACAAAGTTTTCCTGGAAGT
AATGGTAAGCATCCTGAAATAAAAAAGCAAGAATATGAAGAAGTACTTCAGACTGTTAAT
ACAGACTTCTCTCCATGTCTGATTTCAGATAACCTAGAACAGCCTATGAGAAGTAGTCAT
GCATCTCAGGTTTGTTCTGAGACACCTAATGACCTGTTAGATGATGGTGAAATAAAGGAA
GATACTAGTTTTGCTGAAAATGACATTAAGGAAAGTTCTGCTGTTTTTAGCAAAAGCGTC
CAGAGAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCATACACATTTGGCTCAGGGT
TACCGAAGAGGGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Gorilla
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGTTTATTACTCACTAAA
GACAGAATGAATGTAGAAAAGGCTGAATTCTGTAATAAAAACAAACAGCCTGGCTTAGCA
AGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAACATGTAATGATAGGCGGACTCCC
AGCACAGAAAAAAAGGTAGATCTGAATGCTGATCCCCTGTGTGAGAGAAACGAATGGAAT
AAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGATACTGAAGATGTTCCTTGGATAACA
CTAAATAGCAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAGGT
TCTGATGACTCACATGATGGGGGGTCTGAATCAAATGCCAAAGTAGCTGATGTATTGGAC
GTTCTAAATGAGGTAGATGAATATTCTGGTTCTTCAGAGAAAATAGACTTACTGGCCAGT
GATCCTCATGAGGCTTTAATATGTAAAAGTGAAAGAGTTCACTCCAAATCAGTAGAGAGT
AATATTGAAGACAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCCAGCTTA
AGCCATGTAACTGAAAATCTAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA
GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGAGCTACATCAGGCCTTCATCCT
GAGGATTTTATCAAGAAAGCAGATTTGGCAGTTCAAAAGACTCCTGAAATGATAAATCAG
GGAACTAACCAAATGGAGCAGAATGGTCAAGTGATGAATATTACTAATAGTGGTCATGAG
AATAAAACAAAAGGTGATTCTATTCAGAATGAGAAAAATCCTAACCCAATAGAATCACTA
GAAAAAGAATCTTTCAAAACGAAAGCTGAACCTATAAGCAGCAGTATAAGCAATATGGAA
CTCGAATTAAATATCCACAATTCAAAAGCGCCTAAAAAGAATAGGCTGAGGAGGAAGTCT
TCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAAT
TGTACTGAATTGCAAATTGATAGTTGTTCTAGCAGTGAAGAGATAAAGAAAAAAAAGTAC
AACCAAATGCCAGTCAGGCACAGCAGAAACCTACAGCTCATGGAAGATAAAGAACCTGCA
ACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGACATGACAGCGAT
ACTTTCCCAGAGCTGAAGTTAACAAATGCACCTGGTTCTTTTACTAACTGTTCAAATACC
AGTGAAAAAGAATTTGTCAATCCTAGCCTTCCAAGAGAAGAAAAAGAAGAGAAACTAGAA
ACAGTTAAAGTGTCTAATAATGCCGAAGACCCCAAAGATCTCATGTTAAGTGGAGAAAGG
GTTTTGCAAACTGAAAGATCTGTAGAGAGTAGCAGTATTTCATTGGTACCTGGTACTGAT
TATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGGAAGGCAAAAACA
GAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGGACTAATTCAT
GGTTGTTCCAAAGATACTAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGACATGAA
GTTAACCACAGTCGGGAAACAAGCATAGAAATGGAAGAAAGTGAACTTGATGCTCAGTAT
TTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCTGTTTTCAAATCCAGGA
GAGGAATGTGCAACATTCTCTGCCCACTCTAGGTCCTTAAAGAAACAAAGTCCAAAAGTC
ACTTTTGAATGTGAACAAAAGGAAGAAAATCAAGGAAAGAATGAGTCTAATATCAAGCCT
GTACAGACAGTTAATATCACTGCAGGCTTTCCTGTGGTTTGTCAGAAAGATAAGCCAGTT
GATTATGCCAAATGTATCAAAGGAGGCTCTAGGTTTTGTCTATCATCTCAGTTCAGAGGC
AACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTTACAAAACCCATATCATATA
CCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAACCTGCTAGAG
GAAAACTTTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAATGAGAACATTCCA
AGTACAGTGAGCACAATTAGCCGTAATAACAGAGAAAATGTTTTTAAAGAAGCCAGCTCA
AGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGTGGGCTCCAGTATTAATGAAGTA
GGTTCCAGTGATGAAAACATTCAAGCAGAACTAGGTAGAAACAGAGGGCCAAAATTGAAT
GCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTATAAACAAAGTCTTCCTGGAAGT
AATTGTAAGCATCCTGAAATAAAAAAGCAAGAATATGAAGAAGTAGTTCAGACTGTTAAT
ACAGATTTCTCTCCATGTCTGATTTCAGATAACTTAGAACAGCCTATGGGAAGTAGTCAT
GCATCTCAGGTTTGTTCTGAGACACCTGATGACCTGTTAGATGATGGTGAAATAAAGGAA
GATACTAGTTTTGCTAAAAATGACATTAAGGAAAGTTCTGCTGTTTTTAGCAAAAGCGTC
CAGAGAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCATACACATTTGGCTCAGGGT
TACCGAAGAGGGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Human
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGTTTATTACTCACTAAA
GACAGAATGAATGTAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCA
AGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAACATGTAATGATAGGCGGACTCCC
AGCACAGAAAAAAAGGTAGATCTGAATGCTGATCCCCTGTGTGAGAGAAAAGAATGGAAT
AAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGATACTGAAGATGTTCCTTGGATAACA
CTAAATAGCAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAGGT
TCTGATGACTCACATGATGGGGAGTCTGAATCAAATGCCAAAGTAGCTGATGTATTGGAC
GTTCTAAATGAGGTAGATGAATATTCTGGTTCTTCAGAGAAAATAGACTTACTGGCCAGT
GATCCTCATGAGGCTTTAATATGTAAAAGTGAAAGAGTTCACTCCAAATCAGTAGAGAGT
AATATTGAAGACAAAATATTTGGGAAAACCTATCGGAAGAAGGCAAGCCTCCCCAACTTA
AGCCATGTAACTGAAAATCTAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA
GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGACCTACATCAGGCCTTCATCCT
GAGGATTTTATCAAGAAAGCAGATTTGGCAGTTCAAAAGACTCCTGAAATGATAAATCAG
GGAACTAACCAAACGGAGCAGAATGGTCAAGTGATGAATATTACTAATAGTGGTCATGAG
AATAAAACAAAAGGTGATTCTATTCAGAATGAGAAAAATCCTAACCCAATAGAATCACTC
GAAAAAGAATCTTTCAAAACGAAAGCTGAACCTATAAGCAGCAGTATAAGCAATATGGAA
CTCGAATTAAATATCCACAATTCAAAAGCACCTAAAAAGAATAGGCTGAGGAGGAAGTCT
TCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAAT
TGTACTGAATTGCAAATTGATAGTTGTTCTAGCAGTGAAGAGATAAAGAAAAAAAAGTAC
AACCAAATGCCAGTCAGGCACAGCAGAAACCTACAACTCATGGAAGGTAAAGAACCTGCA
ACTGGAGCCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGACATGACAGCGAT
ACTTTCCCAGAGCTGAAGTTAACAAATGCACCTGGTTCTTTTACTAAGTGTTCAAATACC
AGTGAAAAAGAATTTGTCAATCCTAGCCTTCCAAGAGAAGAAAAAGAAGAGAAACTAGAA
ACAGTTAAAGTGTCTAATAATGCTGAAGACCCCAAAGATCTCATGTTAAGTGGAGAAAGG
GTTTTGCAAACTGAAAGATCTGTAGAGAGTAGCAGTATTTCATTGGTACCTGGTACTGAT
TATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGGAAGGCAAAAACA
GAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGGACTAATTCAT
GGTTGTTCCAAAGATAATAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGACATGAA
GTTAACCACAGTCGGGAAACAAGCATAGAAATGGAAGAAAGTGAACTTGATGCTCAGTAT
TTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCCGTTTTCAAATCCAGGA
GAGGAATGTGCAACATTCTCTGCCCACTCTGGGTCCTTAAAGAAACAAAGTCCAAAAGTC
ACTTTTGAATGTGAACAAAAGGAAGAAAATCAAGGAAAGAATGAGTCTAATATCAAGCCT
GTACAGACAGTTAATATCACTGCAGGCTTTCCTGTGGTTGGTCAGAAAGATAAGCCAGTT
GATAATGCCAAATGTATCAAAGGAGGCTCTAGGTTTTGTCTATCATCTCAGTTCAGAGGC
AACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTTACAAAACCCATATCGTATA
CCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAATCTGCTAGAG
GAAAACTTTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAATGAGAACATTCCA
AGTACAGTGAGCACAATTAGCCGTAATAACAGAGAAAATGTTTTTAAAGAAGCCAGCTCA
AGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGTGGGCTCCAGTATTAATGAAATA
GGTTCCAGTGATGAAAACATTCAAGCAGAACTAGGTAGAAACAGAGGGCCAAAATTGAAT
GCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTATAAACAAAGTCTTCCTGGAAGT
AATTGTAAGCATCCTGAAATAAAAAAGCAAGAATATGAAGAAGTAGTTCAGACTGTTAAT
ACAGATTTCTCTCCATATCTGATTTCAGATAACTTAGAACAGCCTATGGGAAGTAGTCAT
GCATCTCAGGTTTGTTCTGAGACACCTGATGACCTGTTAGATGATGGTGAAATAAAGGAA
GATACTAGTTTTGCTGAAAATGACATTAAGGAAAGTTCTGCTGTTTTTAGCAAAAGCGTC
CAGAAAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCATACACATTTGGCTCAGGGT
TACCGAAGAGGGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
>Chimpanzee
TGTGGCACAAATACTCATGCCAGCTCATTACAGCATGAGAACAGTTTATTACTCACTAAA
GACAGAATGAATGTAGAAAAGGCTGAATTCTGTAATAAAAGCAAACAGCCTGGCTTAGCA
AGGAGCCAACATAACAGATGGGCTGGAAGTAAGGAAACATGTAATGATAGGCGGACTCCC
AGCACAGAAAAAAAGGTAGATCTGAATGCTGATCCCCTGTGTGAGAGAAAAGAATGGAAT
AAGCAGAAACTGCCATGCTCAGAGAATCCTAGAGATACTGAAGATGTTCCTTGGATAACA
CTAAATAGCAGCATTCAGAAAGTTAATGAGTGGTTTTCCAGAAGTGATGAACTGTTAGGT
TCTGATGACTCACATGATGGGGGGTCTGAATCAAATGCCAAAGTAGCTGATGTATTGGAC
GTTCTAAATGAGGTAGATGAATATTCTGGTTCTTCAGAGAAAATAGACTTACTGGCCAGC
GATCCTCATGAGGCTTTAATATGTAAAAGTGAAAGAGTTCACTCCAAATCAGTAGAGAGT
AATACTGAAGACAAAATATTTGGGAAAACCTATCGGAGGAAGGCAAGCCTCCCCAACTTA
AGCCATGTAACTGAAAATCTAATTATAGGAGCATTTGTTACTGAGCCACAGATAATACAA
GAGCGTCCCCTCACAAATAAATTAAAGCGTAAAAGGAGAGCTACATCAGGCCTTCATCCT
GAGGATTTTATCAAGAAAGCAGATTTGGCAGTTCAAAAGACTCCTGAAATGATAAATCAG
GGAACTAACCAAATGGAGCAGAATGGTCAAGTGATGAATATTACTAATAGTGGTCATGAG
AATAAAACAAAAGGTGATTCTATTCAGAATGAGAAAAATCCTAACCCAATAGAATCACTC
GAAAAAGAATCTTTCAAAACGAAAGCTGAACCTATAAGCAGCAGTATAAGCAATATGGAA
CTCGAATTAAATATCCACAATTCAAAAGCACCTAAAAAGAATAGGCTGAGGAGGAAGTCT
TCTACCAGGCATATTCATGCGCTTGAACTAGTAGTCAGTAGAAATCTAAGCCCACCTAAT
TGTACTGAATTGCAAATTGATAGTTGTTCTAGCAGTGAAGAGATAAAGAAAAAAAAGTAC
AACCAAATGCCAGTCAGGCACAGCAGAAACCTACAACTCATGGAAGATAAAGAACCTGCA
ACTGGAGTCAAGAAGAGTAACAAGCCAAATGAACAGACAAGTAAAAGACATGACAGCGAT
ACTTTCCCAGAGCTGAAGTTAACAAATGCACCTGGTTCTTTTACTAACTGTTCAAATACC
AGTGAAAAAGAATTTGTCAATCCTAGCCTTCCAAGAGAAGAAGAAGAAGAGAAACTAGAA
ACAGTTAAAGTGTCTAATAATGCCGAAGACCCCAAAGATCTCATGTTAAGTGGAGAAAGG
GTTTTGCAAACTGAAAGATCTGTAGAGAGTAGCAGTATTTCATTGGTACCTGGTACTGAT
TATGGCACTCAGGAAAGTATCTCGTTACTGGAAGTTAGCACTCTAGGGAAGGCAAAAACA
GAACCAAATAAATGTGTGAGTCAGTGTGCAGCATTTGAAAACCCCAAGGGACTAATTCAT
GGTTGTTCCAAAGATACTAGAAATGACACAGAAGGCTTTAAGTATCCATTGGGACATGAA
GTTAACCACAGTCGGGAAACAAGCATAGAAATGGAAGAAAGTGAACTTGATGCTCAGTAT
TTGCAGAATACATTCAAGGTTTCAAAGCGCCAGTCATTTGCTCTGTTTTCAAATCCAGGA
GAGGAATGTGCAACATTCTCTGCCCACTGTAGGTCCTTAAAGAAACAAAGTCCAAAAGTC
ACTTTTGAACGTGAACAAAAGGAACAAAATCAAGGAAAGAATGAGTCTAATATCAAGCCT
GTACAGACAGTTAATATCACTGCAGGCTTTCCTGTGGTTTGTCAGAAAGATAAGCCAGTT
GATTATGCCAAATGTATCAAAGGAGGCTCTAGGTTTTGTCTATCATCTCAGTTCAGAGGC
AACGAAACTGGACTCATTACTCCAAATAAACATGGACTTTTACAAAACCCATATCATATA
CCACCACTTTTTCCCATCAAGTCATTTGTTAAAACTAAATGTAAGAAAAACCTGCTAGAG
GAAAACTTTGAGGAACATTCAATGTCACCTGAAAGAGAAATGGGAAATGAGAACATTCCA
AGTACAGTGAGCACAATTAGCCGTAATAACAGAGAAAATGTTTTTAAAGAAGCCAGCTCA
AGCAATATTAATGAAGTAGGTTCCAGTACTAATGAAGTGGGCTCCAGTATTAATGAAGTA
GGTTCCAGTGATGAAAACATTCAAGCAGAACTAGGTAGAAACAGAGGGCCAAAATTGAAT
GCTATGCTTAGATTAGGGGTTTTGCAACCTGAGGTCTATAAACAAAGTCTTCCTGAAAGT
AATTGTAAGCATCCTGAAATAAAAAAGCAAGAATATGAAGAAGTAGTTCAGACTGTTAAT
ACAGATTTCTCTCCATGTCTGATTTCAGATAACTTAGAACAGCCTATGGGAAGTAGTCAT
GCATCTCAGGTTTGTTCTGAGACACCTGATGACCTGTTAGATGATGGTGAAATAAAGGAA
GATACTAGTTTTGCTGAAAATGACATTAAGGAAAGTTCTGCTGTTTTTAGCAAAAGCGTC
CAGAGAGGAGAGCTTAGCAGGAGTCCTAGCCCTTTCACCCATACACATTTGGCTCAGGGT
TACCGAAGAGGGGCCAAGAAATTAGAGTCCTCAGAAGAGAACTTATCTAGTGAG
PyCogent-1.5.3/doc/data/primate_brca1.tree 000644 000765 000024 00000000105 11261304034 021276 0 ustar 00jrideout staff 000000 000000 (Galago,HowlerMon,(Rhesus,(Orangutan,(Gorilla,(Human,Chimpanzee))))); PyCogent-1.5.3/doc/data/primate_cdx2_promoter.fasta 000644 000765 000024 00000011104 11212010705 023230 0 ustar 00jrideout staff 000000 000000 >human
AGCGCCCGCGGGTTCTGAGAGCGCTCAAAGCCGCCGAGTCAGGCTGCCCAGCCCGCCGGG
CCTCGCCGCAGTGATCCTCATTCCCGAATCTGGCAGCGCTGTCAAAGGCTTGTATTAGGA
GGTGAACGGCGGCCGCAGGCCCACTCCACGCGGTTGCTGAAACCGAGCTGGGCGCGCGCG
GGGGCCGAATCTCGCCGCCTCCGCGCTCCTGTCGGGGCAGCTCCCGATCCCGGGCTGCGC
GGCTTCGGTCCCCAAGACGGCCACTTCCAGCCCTAGGCCCCTTGGCCGCAGCGCTTCCCA
AACCAAGAGAGATCCTTTCTCAACTCAGAGCTTTTCATTAGCAGTCGTTAATAATGGCCC
TGAGTTGCCTTATCATCTCCTGGAAATGAGAAATAAATTTCTTCGGAGAACGTTTCCCTT
TGTAAAGGACAGAGAGTTTTAAAGATACAGGTATGATGTAAGACACATAAATACCTAGGT
AAGCATTAGCAGAAATTCTCTTTTCCTT-------------------ATATTTAAGTATA
ATAAACATACAAGTGTAGCTCAATGAATTTTCACAAACTGACATTCTGTGTAACCAGCAG
CCTAAGAAACTGCTTTACCAACGATCCCCTAGCTCGCCTCCAGTTATGCACGCCAATAAC
CACTAGCCTAACTTCTACCACATGCCCATTACTTCTGTAGTTTAAAACTTCTGATTCTTG
AATGTAAACGTTTAACAATAAATCGCTTGAATTTAACTCAAATTTCAAATGTAAGATGAA
GTCAGAGATGCAGCCTGAATCTAGGATCATAATTTGTCTTGTGCGGAGGGCGAGTAATTT
CCTTGGGCAAGAAAATAACT----GGAGGTGACAGTTGTTTGGGGCTGCAGTCGTCCGGG
CCAGGAGCACAGGGCGGGAAGGAATGGCCCATCTCTTAGGGCTCTCTGCTTGTCACCTAC
CAGGTTGGTCAGAAACGTTCTCATCAAAGCAATGG-TTCTCTTTTCTTTTCTCTTTGGGA
CAGAAGGAGTTTCTTGACCGCCCTCTTCCCTGCAAATGCATAAACAACCACTGCTCCTGT
CTCCAAGCTCAGATTCCTACCAAGATAGCCTTTTCTCTTCCCCTCTCTTTTGTAAGTCTC
TTGATTTCATTCTTTGAACCTGTGATTGGAGGTTAAAGTGCACCAGGTTGGAAGGAGGAA
GCTCTTAACAATAAAGGTTTGAATATTTAGCTGTG-TCAGGTCGCTGCCCTCTCACGAGC
CTCCCTCCCCTTTATCTTTTAAAATGCAAATTATGTTTCGAGGGGTTGTGCGTAGAGTGC
GCGCTGCGCCTCGACGTCTCCAACCATTGGTGTCTGTGTCATTACTAATAGAGTCTTGTA
AACACTCGTTAATCACGGAAGGCCGCCGGCCTGGGGCTCCGCACGCCAGCCTGTGGCGGG
TCTTCCCCGCCTCTGCAGCCTAGTGGGAAGGAGGTGGGAGGAAAGAAGGAAGAAAGGGAG
GGAGGGAGGAGGCAGGCCAGAGGGA
>macaque
AGCGCCCGCGGGTTCTGAGAGCGCTCAAAGCCACCGAGTCAGGCTGCCCAGCCCGCCGGG
CCTCGCCGCAGTGATCCTCATTCCCGAATCTGGCAGCGCTGTCAAAGGCTGGTA-TAGGA
GGTGAACGGCGGCCGCAGGCCCACTCCACGCTGTTGTTGAAACCCAGTTGCGCGCGCGCG
AGAGCCGAATCTCGCCGCCTCCGCGCTCCTGTCGGGGTAGCTCCAGATTCCTGGCTGCGC
GGCTCCGGTCCCCAAGGCGGTCGCTCCCAGCCCTAGGCCCCTTGGCCGCAGCGCTTCCCA
AACCGAGAGAGATCCTTTCTCAACTCAGAGCTTTTCATTAACAATCGTTAATAACGGCCC
TGAGTTGCCTTGTGATCTCCTGGAGATGAAAAATAAATTTCTTAGGAGAATGTTTCACTT
TGTAAAGGACAAAGAGTTTTAAAGATATAGGTATGATGTAAGACACATAAATACCTAGGT
AAGTATTAGCAGAAATTCTCTTTTCCTTCATTGTTAACCACTTATGCA------AGTATA
AGAAAAATACAAGTGTAGCTCAATGAATTTTCACAAACTGACACTCCATGTAACCAGCAG
CCTAAGAAACAGCGTTACCAGCGATCCCCTAGTTCGCCTCC--TTATGCACGCCAATAAC
CACTAGCCTAACTTCTACCACATGCCCATTACTTTTGTAGTTTAAAACTTTTGATTCTTG
AATGTAAACGTTTATCAATAAATCGC-----TTTAACTCAAATCTCAAACGTAAGATGAA
GTCAGAGATGCAGCCTGAATCTCGGATCATAATTTATCTTGTACGGAGGGCGAGTAATTT
CCTTGGGCAAGAAAATAACTGATTGGAGGTGACAGTTGTTTAGGGCTGCAGTCGTCCGGG
CCAGGAGCACAGGGCGGGAAGGAATGGCCCATCTCTTAGGGCTCTCTGCTTGTCACCTAC
CAGGTTGGTCAGAAACGTTCTCATCAAAGCAATGGTTTCTCTTTTCTTTTCTCTTTGGGA
CAGAAGGAGTTCCTTGACCGCCCCCTTCCCTGCAAATGCATAAACAACCACTGCTCCTGT
CTCCAAGCTCAGATTCCCACCAAGATAGCCTTTTCTCTTCCCCTGTCTTTTGTAAGTCTC
TTGATTTCATTCTTTGAACCTGTGATTGGAGGTTAAAGTGCACCAGGTTGGAAGGAGGAA
GCTCTTAACAATAAAGGTTTGAATATTTAGCTGTGATCAGGTCGCTGCCCTCTCACGAAC
CTCCCCCCCCCTTATCTTTTAAAATGCAAATTATGTTTCAGGGGGTTGTGCGTTGAGTGC
GCGCTGCGCCTCGACGTCTCCAACCATTGGTGTCTGTGTCATTACTAATAGAGTCTTGTA
AACACTCGTTAATCACGGAAGGCCGCCGGCCTGGGGCTCCGCACGCCAGCCTGTGGCGGG
TCTTCCCCGCCTCTGCAGCCTAGTGGGAAGGAGGTGGGAGGAAAGAAGGAAGAAAGAGAG
GGAGGGAGGAGGCAGGCCAGAGGGA
>chimp
AGCGCCCGCGGGTTCTGAGAGCGCTCAAAGCCGCCGAGTCAGGCTGCCCAGCCCGCCGGG
CCTCGCCGCAGTGATCCTCATTCCCGAATCTGGCAGCGCTGTCAAAGGCTTGTA-TAGGA
GGTGAACGGCGGCCGCAGGCCCACCCCACGCGGTTGCTGAAACCGAGCTGGGCGCGCGCA
GGAGCCGAATCTCGCCGCCTCTGCCCTCCTGTCGGGGCAGCTCCCGATCCCGGGCTGCGC
GGCTCCGGTCCCCAAGACGGCCACTTCCAGCCCTAGGCCCCTTGGCCGCAGCGCTTCCCA
AACCAAGAGAGATCCTTTCTCAACTCAGAGCTTTTCATTAGCAGTCGTTAATAATGGCCC
TGAGTTGCCTTATCATCTCCTGGAAATAAGAAATAAATTTCTTCGGAGAACGTTTCCCTT
TGTAAAGGACAGAGAGTTTTAAAGATATAGATATGATGTAAGACACATAAATACCTAGGT
AAGCATTAGCAGAAATTCTCTTTTCCTT-------------------ATATTTAAGTATA
ATAAACATACAAGTGTAGCTCAATGAATTTTCACAAACTGACATTCTATGTAACCAGCAG
CCTAAGAAACTGCTTTACCAACGATCCCCTAGCTCGCCTCCAGTTATGCACGCCAATAAC
CACTAGCCTAACTTCTACCACATGCCCATTACTTCTGTAGTTTAAAACTTCTGATTCTTG
AATGTAAACGTTTAACAATAAATCGCTTGAATTTAACTCAAATTTCAAATGTAAGATGAA
GTCAGAGATGCAGCCTGAATCTAGGATCATAATTTGTCTTGTGCGGAGGGCGAGTAATTT
CCTTGGGCAAGAAAATAACTGATTGGAGGTGACAGTTGTTTGGGGCTGCAGTCATCTGGG
CCAGGAGCACAGGGCGGGAAGGAATGGCCCATCTCTTAGGGCTCTCTGCTTGTCACCTAC
CAGGTTGGTCAGAAACGTTCTCATCAAAGCAATGG-TTCTCTTTTCTTTTCTCTTTGGGA
CAGAAGGAGTTTCTTGACCGCCCCCTTCCCTGCAAATGCATAAACAACCACTGTTCCTGT
CTCCAAGCTCAGATTCCCACCAAGATAGCCTTTTCTCTTCCCCTCTCTTTTGTAAGTCTC
TTGATTTCATTCTTTGAACCTGTGATTGGAGGTTAAAGTGCACCAGGTTGGAAGGAGGAA
GCTCTTAACAATAAAGGTTTGAATATTTAGCTGTG-TCAGGTCGCTGCCCTCTCACGAGC
CTCCCTCCCCTTTATCTTTTAAAATGCAAATTATGTTTCGAGGGGTTGTGCGTAGAGTGC
GCGCTGCGCCTCGACGTCTCCAACCATTGGTGTCTGTGTCATTACTAATAGAGTCTTGTA
AACACTCGTTAATCACGGAAGGCCGCCGGCCTGGGGCTCCGCACGCCAGCCTGTGGCGGG
TCTTCCCCGCCTCTGCAGCCTAGTGGGAAGGAGGTGGGAGGAAAGAAGGAAGAAAGGGAG
GGAGGGAGGAGGCAGGCCAGAGGGA
PyCogent-1.5.3/doc/data/pycogent_script_template.py 000644 000765 000024 00000002061 11612102756 023377 0 ustar 00jrideout staff 000000 000000 #!/usr/bin/env python
# File created on 15 Jul 2011
from __future__ import division
__author__ = "AUTHOR_NAME"
__copyright__ = "COPYRIGHT_INFORMATION"
__credits__ = ["AUTHOR_NAME"]
__license__ = "GPL"
__version__ = "1.6.0dev"
__maintainer__ = "AUTHOR_NAME"
__email__ = "AUTHOR_EMAIL"
__status__ = "Development"
from cogent.util.option_parsing import parse_command_line_parameters, make_option
script_info = {}
script_info['brief_description'] = ""
script_info['script_description'] = ""
script_info['script_usage'] = [("","","")]
script_info['output_description']= ""
script_info['required_options'] = [\
# Example required option
#make_option('-i','--input_dir',type="existing_filepath",help='the input directory'),\
]
script_info['optional_options'] = [\
# Example optional option
#make_option('-o','--output_dir',type="new_dirpath",help='the output directory [default: %default]'),\
]
script_info['version'] = __version__
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
if __name__ == "__main__":
main() PyCogent-1.5.3/doc/data/refseqs.fasta 000644 000765 000024 00000000477 11350301455 020413 0 ustar 00jrideout staff 000000 000000 >s0
CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC
>s1
TGCAGCTTGAGCCACAGGAGAGAGAGAGCTTC
>s2
TGCAGCTTGAGCCACAGGAGAGAGCCTTC
>s3
TGCAGCTTGAGCCACAGGAGAGAGAGAGCTTC
>s4
ACCGATGAGATATTAGCACAGGGGAATTAGAACCA
>s5
TGTCGAGAGTGAGATGAGATGAGAACA
>s6
ACGTATTTTAATTTGGCATGGT
>s7
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT
>s8
CCAGAGCGAGTGAGATAGACACCCAC
PyCogent-1.5.3/doc/data/refseqs_protein.fasta 000644 000765 000024 00000041664 11361457314 022166 0 ustar 00jrideout staff 000000 000000 >1091044
VTDKFPEDVKFLYIAYTPAKADITACGIPIPLDFDKEFRDKTVVIVAIPGAFTPTCTANHIPPFVEKFTALKSAGVDAVIVLSANDPFVQSAFGKALGVTDEAFIFASDPGAEFSKSAGLSLDLPPAFGTRTARYAIIVSNGVVKYVEKDSEGVAGSGVDAVLAAL
>11467494
MTNFPKIGKTPPNFLTIGVYKKRLGKIRLSDYRGKKYVILFFYPANFTAISPTELMLLSDRISEFRKLSTQILAISVDSPFSHLQYLLCNREEGGLEDLNYPLVSDLTQTITRDYQVLTDEGLAFPGLFIIDKEGIIQYYTVNNLLCGRNINELLRILESIQYVKENPGYACPVNWNFGDQVFYSHPLKSKIYFKDLYSPKKSS
>11499727
MERLNSERFREVIQSDKLVVVDFYADWCMPCRYISPILEKLSKEYNGEVEFYKLNVDENQDVAFEYGIASIPTVLFFRNGKVVGGFIGAMPESAVRAEIEKALGA
>1174686
MSDGVKHINSAQEFANLLNTTQYVVADFYADWCGPCKAIAPMYAQFAKTFSIPNFLAFAKINVDSVQQVAQHYRVSAMPTFLFFKNGKQVAVNGSVMIQGADVNSLRAAAEKMGRLAKEKAAAAGSS
>12044976
MVTEIRSLKQLEEIFSAKKNVIVDFWAAWCGPCKLTSPEFQKAADEFSDAQFVKVNVDDHTDIAAAYNITSLPTIVVFENGVEKKRAIGFMPKTKIIDLFNN
>13186328
MLNTRIKPFKNISYYKKKFYEIKEIDLKSNWNVFFFYPYSYSFICPLELKNISNKIKEFKNLNTKIYAISNDSHFVQKNWIENELKFINFPFISDFNHKISNNFNILNKKDGNCLRSTIIIDKNLIIKYINIVDDSIGRSIDEILKNIKMLQFINTNENKLCPYSWNNDSKSIEIN
>13358154
MLIKLESNQNLNELLKENHSKPILIDFYADWCPPCRMLIPVLDSIEKKHGDEFTIIKINVDHFPELSTQYQVKSIPALFYLKNGDIKATSLGFIDENSLVNKLRSI
>13541053
MSLVNKAAPDFEANAFVNGEVKKIRLSSYRGKWVVLFFYPADFTFVCPTEVEGFAEDYEKFKKKNTEVISVSEDTVYVHKAWVQYDERVAKAKYPMVEDRKGIIARAYDVYNEETGNAQRGLFIINPDGIVKYVVITDDNVGRSTDETLRVLEALQSGGLCPVNWHEGEPTLKV
>13541117
MSPKVNEKAPDFEAPDTALKMRKLSEFRGQNVVLAFFPGAFTSVCTKEMCTFRDSMANFNKFKAKVIGISVDSPFSLAEFAKKNNLTFDLLSDSNREISKKYDVLHQNFAGVPGLTASKRSVFIIDGDGIVRYAWVSDDPGKEPDYKAIQEFLSKMN
>135765
AIVKATDQSFSAETSEGVVLADFWAPWCGPCKMIAPVLEELDQEMGDKLKIVKIDVDENQETAGKYGVMSIPTLLVLKDGEVVETSVGFKPKEALQELVNKHL
>1388082
MAAEEGQVIGCHTNDVWTVQLDKAKESNKLIVIDFTASWCPPCRMIAPIFNDLAKKFMSSAIFFKVDVDELQSVAKEFGVEAMPTFVFIKAGEVVDKLVGANKEDLQAKI
>140543
MLFYKPVMRMAVRPLKSIRFQSSYTSITKLTNLTEFRNLIKQNDKLVIDFYATWCGPCKMMQPHLTKLIQAYPDVRFVKCDVDESPDIAKECEVTAMPTFVLGKDGQLIGKIIGANPTALEKGIKDL
>14286173
MPLIGDKFPEMEVQTTHGPMELPDEFEGKWFILFSHPADFTPVCTTEFVAFQEVYPELRELDCELVGLSVDQVFSHIKWIEWIAENLDTEIEFPVIADTGRVADTLGLIHPARPTNTVRAVFVVDPEGIIRAILYYPQELGRNIPEIVRMIRAFRVIDAEGVAAPANWPDNQLIGDHVIVPPASDIETARKRKDEYECYDWWLCTQSRG
>14578634
MKKNFFYAGGLSLLLWGMAACSGQGKADKAAVVADSVVVKTDSVAADSTGYIVKVGESAPDFTITLTDGKQMKLSELRGKVVMLQFTASWCGVCRKEMPFIEKDIWLKHKNNPEFALIGIDRDEPLDKVIAFGKSVGVTYPLGLDPGADIFAKYALRESGITRNVLIDREGKIVKLTRLYNEEEFASLVDQIDEMLKK
>14600438
MPGVGEQAPDFEGIAHTGEKIRLSDFRGRIVVLYFYPRAMTPGCTREGVRFNELLDEFEKLGAVVIGVSTDSVEKNRKFAEKHGFRFKLVSDEKGEIGMKYGVVRGEGSNLAAERVTFIIDREGNIRAILRNIRPAEKHADLALEEVKKLVLGKKAERAGEVI
>15218394
MQVRAAKKQTFNSFDDLLQNSDKPVLVDFYATWCGPCQLMVPILNEVSETLKDIIAVVKIDTEKYPSLANKYQIEALPTFILFKDGKLWDRFVSFLSRMNTAYLLLASKAQL
>15597673
MLSFSLGPLVVSLQHLLLFLALGAALLGGWLAARGGGRNAEPVLFNLLLLGLLVARLAFVVRYWPQYRGDFAQMLDIRDGGFLAWPGLLAAVLGALFWAWRRPALRRSLGVGASLGLAFWLLGSLGLGIYERGTRLPELSLRNAAGESVQLADFRGRPLVINLWASWCPPCRREMPVLQQAQAENPDVVFLFANQGESAETVRHFLQGENLRLDNLLFDNGGQLGQQVGSVALPTTVFYTAEGRLLGSHLGELSRGSLARYLEAFEPAAAAPATRSSE
>15599256
MSDTPYIFDVTGANFEQLVIENSFHKPVLVDFWADWCAPCKALMPLLAQIAESYQGELLLAKVNCDVEQDIVMRFGIRSLPTVVLFKDGQPVDGFAGAQPESQIRALLEPHVKAPALPDEDPLEVAQALFAEGRIGDAEATLKALLAENNENAAALILYARCLAERGELEEAQAILDAVKSDEHKQALAGARAQLTFLRQAADLPDSAELKSRLAADAGDDEAAYQLAVQQLARQQYEAALDGLLKLFLRNRGYQDDLPRKTLVQVFDLLGNDHPLVTAYRRKLYQALY
>15602312
MVNSYEKPQMKTSVLLTALFKPLLLCTIVLSCIGCKEDIAVIGKQAPEIAVFDLVGTQRSLNEGKGKTILLNFWSETCGVCIAELKTFEQLLQSYPQNNLHIIAINVDGDKADTQALVKKREISLLVVKDQLKITAERYQLVGTPTSFVIDPEGKILYKFEGLIPTQDLHLFFKG
>15605725
MKRLLPVFLALILFGLLVYIGLNQDKHDHYTITTQKGQKIPNVTLTTPDGKKVSIEEFKGKVLLINFWATWCPPCKEEIPMFKEIYEKYRDRGFEILAINMDPENLTGFLKNNPLPFPVFVINEKWKEPLTFQGFQRRTWLTEEEL
>15605963
MARTVNLKGNPVTLVGPELKVGDRAPEAVVVTKDLQEKIVGGAKDVVQVIITVPSLDTPVCETETKKFNEIMAGMEGVDVTVVSMDLPFAQKRFCESFNIQNVTVASDFRYRDMEKYGVLIGEGALKGILARAVFIIDKEGKVAYVQLVPEITEEPNYDEVVNKVKELI
>15609375
MLNVGATAPDFTLRDQNQQLVTLRGYRGAKNVLLVFFPLAFTGICQGELDQLRDHLPEFENDDSAALAISVGPPPTHKIWATQSGFTFPLLSDFWPHGAVSQAYGVFNEQAGIANRGTFVVDRSGIIRFAEMKQPGEVRDQRLWTDALAALTA
>15609658
MTKTTRLTPGDKAPAFTLPDADGNNVSLADYRGRRVIVYFYPAASTPGCTKQACDFRDNLGDFTTAGLNVVGISPDKPEKLATFRDAQGLTFPLLSDPDREVLTAWGAYGEKQMYGKTVQGVIRSTFVVDEDGKIVVAQYNVKATGHVAKLRRDLSV
>15613511
MLEGKQAPDFSLPASNGETVSLSDFKGKNIVLYFYPKDMTPGCTTEACDFRDRVEDFKGLNTVILGVSPDPVERHKKFIEKYSLPFLLLADEDTKVAQQYDVWKLKKNFGKEYMGIERSTFVIDKDGTVVKEWRKVRVKDHVEEALAFIKENLE
>15614085
MNKKRLTTIVVLIAVVASVIIILTQNNLEVGNGKGMLAEDFTLPLYEESQSRSLSDYRGDVVILNVWASWCEPCRKEMPALMELQSDYESEDVSIVTVNMQTFERTVNDAGEFIEELGITLPVFLDEEGEFADAYQVQHLPMTYVLDREGIINEVILGEVTYEQLEQLIVPLLEKAS
>15614140
MDKRKRFWMRLSILAVISVALGYTFYSNFFADRSLARAGEQAVNFVLEDLEGESIELRELEGKGVFLNFWGTYCPPCEREMPHMEKLYGEYKEQGVEIIAVNANEPELTVQRFVDRYGLSFPIVIDKGLNVIDAYGIRPLPTTILINEHGEIVKVHTGGMTEQMVEEFMELIKPEA
>15615431
MKGKQAFYRSFLILALCTVGYFYSQSEHVYRPVDKEAITTFNEGVQVGQRAVPFSLTTLEGQVVDLSSLRGQPVILHFFATWCPVCQDEMPSLVKLDKEYRQKGGQFLAINLTNQESSIKDVRAFVQHYRAEFDPLLDTDGEVMETYQVIGIPTTLILDEEGTIVKRYNGVLTEEIIDEIMDIH
>15643152
MRVKHFELLTDEGKTFTHVDLYGKYTILFFFPKAGTSGCTREAVEFSRENFEKAQVVGISRDSVEALKRFKEKNDLKVTLLSDPEGILHEFFNVLENGKTVRSTFLIDRWGFVRKEWRRVKVEGHVQEVKEALDRLIEEDLSLNKHIEWRRARRALKKDRVPREELELLIKAAHLAPSCMNNQPWRFVVVDEEELLKKIHEALPGGNYWMKNAPALIAVHSKKDFDCALPDNRDYFLFDTGLAVGNLLVQATQMGLVAHPVAGYDPVKVKEILKIPEDHVLITLIAVGYLGDESELSEKHRELERSERVRKELSEIVRWNL
>15672286
MPMNITSHGEKIATLNPPISGDAPDFELTDLKGNKIKLSKLEKPVLISVFPDINTRVCSLQTKHFNLEAAKHSEIDFLSISNNTADEQKNWCATEGVDMTILADDGTFGKAYGLILNGGPLEGRLARSVFVVKNGQIVYSEVLSELSDEPNYEKALAATK
>15790738
MQRGWGSERLAPRLSPGRAGSVISNDTDTPSMRCEGARAPAFELPGVSDGTQTRLGLTDALADNRAVVLFFYPFDFSPVCATELCAIQNARWFDCTPGLAVWGISPDSTYAHEAFADEYALTFPLLSDHAGAIADAFGVLQASAEDHDRVPERAVFLIDADRVIRYAWASSDLSESPDLGAVKAAIDDLQPDTAGVAPRTISDAHDDGTTDG
>15791337
MTVTLKDFYADWCGPCKTQDPILEELEADYDEDVSFEKIDVDEAEDVANEYQVRSIPTIVVENDDGVVERFVGVTQREQLEDAIESAGA
>15801846
MSQTVHFQGNPVTVANSIPQAGSKAQTFTLVAKDLSDVTLGQFAGKRKVLNIFPSIDTGVCAASVRKFNQLATEIDNTVVLCISADLPFAQSRFCGAEGLNNVITLSTFRNAEFLQAYGVAIADGPLKGLAARAVVVIDENDNVIFSQLVDEITTEPDYEAALAVLKA
>15805225
MTEPAPASPARPAWTRALPPLLAAALVGGLGWALLKPAGNAANGPLVGKPAPQFNLTGLDGQPVALADYRGRPVVLNFWASWCGPCREEAPLFAKLAAHPGAPAVLGILFNETKPQNARDFARQYGLTYPNLQDPGVATAIAYQVTGIPRTVFIDAQGVVRHIDQGGLDTARLNAGLSKIGVPGL
>15805374
MTSPTPPTSPSLSPQPRRASWTRWIVPAVMVGLVGLLAYGLFTPDPEGGPALLGKPAPAFALEDLGGRTHALTAAQGKPVVINFWASWCVPCRQEAPLFSKLSQETAGKAEFFGVIYNDQPADARRFMDQYGLIYPALLDPGSRTALSYGVGKLPITFIVDGQGKVVHIKDGPIEEPELRAALKQAGL
>15807234
MTLVGQPAPDFTLPASTGQDITLSSYRGQSHVVLVFYPLDFSPVCSMQLPEYSGSQDDFTEAGAVVLGINRDSVYAHRAWAAEYGIEVPLLADMQLEVARQYGVAIDERGISGRAVFVIDREGVVRYQHVEEQTGQYTVRPGAVLEQLRGL
>15826629
APIKVGDAIPAVEVFEGEPGNKVNLAELFKGKKGVLFGVPGAFTPGCSKTHLPGFVEQAEALKAKGVQVVACLSVNDAFVTGEWGRAHKAEGKVRLLADPTGAFGKETDLLLDDSLVSIFGNRRLKRFSMVVQDGIVKALNVEPDGTGLTCSLAPNIISQL
>15899007
MNDELNDPELQKILSKKTTQILNNLKEKVKEPVKHLNSKNFDEFITKNKIVVVDFWAEWCAPCLILAPVIEELANDYPQVAFGKLNTEESQDIAMRYGIMSLPTIMFFKNGELVDQILGAVPREEIEVRLKSLLE
>15899339
MVEIGEKAPEIELVDTDLKKVKIPSDFKGKVVVLAFYPAAFTSVCTKEMCTFRDSMAKFNEVNAVVIGISVDPPFSNKAFKEQNKINFTIVSDFNREAVKAYGVAGELPILKGYVLAKRSVFVIDKNGIVRYKWVSEDPTKEPNYDEIKDVVTKLS
>15964668
MTIAVGDKLPNATFKEKTADGPVEVTTELLFKGKRVVLFAVPGAFTPTCSLNHLPGYLENRDAILARGVDDIAVVAVNDLHVMGAWATHSGGMGKIHFLSDWNAAFTKAIGMEIDLSAGTLGIRSKRYSMLVEDGVVKALNIEESPGQATASGAAAMLELL
>15966937
MSGSDNPYQGSFGTQMTGSASFGGQPASAASGPNDLTPDDLIRETTTAAFTRDVLEASRQQPVLVDFWAPWCGPCKQLTPVIEKVVREAAGRVKLVKMNIDDHPSIAGQLGIQSIPAVIAFIDGRPVDGFMGAVPESQIKEFIDRIAGPAADNGKAEIESVLADAKALIDAGDAQNAAGLYGAVLQADPENAAAVAGMIECMIALGQVAEARQALSGLPEALAGEAAVAAVSKKLDQIEEARKLGDPAALERQLALDPDDHAARLKLAKLRNVEGDRTAAAEHLLTIMKRDRSFEDDGARRELLSFFEVWGPKDPATIAARRKLSSILFS
>15988313
SRAPTGDPACRAAVATAQKIAPLAHGEVAALTMASAPLKLPDLAFEDADGKPKKLSDFRGKTLLVNLWATWCVPCRKEMPALDELQGKLSGPNFEVVAINIDTRDPEKPKTFLKEANLTRLGYFNDQKAKVFQDLKAIGRALGMPTSVLVDPQGCEIATIAGPAEWASEDALKLIRAATGKAAAAL
>16078864
MLKKWLAGILLIMLVGYTGWNLYQTYSKKEVGIQEGQQAPDFSLKTLSGEKSSLQDAKGKKVLLNFWATWCKPCRQEMPAMEKLQKEYADKLAVVAVNFTSAEKSEKQVRAFADTYDLTFPILIDKKGINADYNVMSYPTTYILDEKGVIQDIHVGTMTKKEMEQKLDLD
>16123427
MNTVCTACMATNRLPEERIDDGAKCGRCGHSLFDGEVINATAETLDKLLQDDLPMVIDFWAPWCGPCRSFAPIFAETAAERAGKVRFVKVNTEAEPALSTRFRIRSIPTIMLYRNGKMIDMLNGAVPKAPFDNWLDEQLSRDPNS
>16125919
MKIVLAGVAAVALAFASPALAALKAGDKAPDFSAKGALAGKDFDFNLAKALKKGPVVLYFFPAAYTAGCTAEAREFAEATPEFEKLGATVIGMTAGNVDRLKDFSKEHCRDKFAVAAADKALIKAYDVALAVKPDWSNRTSYVIAPDGKILLSHTDGNFMGHVQQTMGAVKAYKAKK
>16330420
MNLQIELYKFQQESLKRSSPERAAIFSDFIQGLSEEFRNRRLLRIGDFAPDFTLKNTKGETIILSEQLKTGPILLKFFRGYWCPYCGLELRAYQKVVNKIRALGGTILAISPQTLVASQKTIDRHDLTYDLLSDSGFQTAQDYGLVFTVPDAVKQIYLQSGCVIPEHNGTEEWLLPVPATFVIDRRGHIALAYANVDFRVRYEPEDAIAILLSLFVGN
>1633495
XDKIIHLTDDSFDTDVLKADGAILVDFWAEWCGPCKMIAPILDEIADEYQGKLTVAKLNIDQNPGTAPKYGIRGIPTLLLFKNGEVAATKVGALSKGQLKEFLDANLA
>16501671
MVLVTRQAPDFTAAAVLGSGEIVDKFNFKQHTNGKTTVLFFWPMDFTFVCPSELIAFDKRYEEFQKRGVEVVGVSFDSEFVHNAWRNTPVDKGGIGPVKYAMVADVKREIQKAYGIEHPDEGVALRGSFLIDANGIVRHQVVNDLPLGRNIDEMLRMVDALQFHEEHGDVCPAQWEKGKEGMNASPDGVAKYLAENISSL
>1651717
MVVAWTTRDQSARNMPMLAVNEDNFDNLVLQCPKPILVYFGAPWCGLCHFVKPLLNHLHGEWQEQLVCVEVNADVNLHLANAYRLKNLPTLILFNRGQVIQRLEDFRVREDLHRIREQIAVSLFSP
>16759994
MAGKLRRWLREAAVFLALLIAIMVVMDVWRAPQAPPAFAATPLHTLTGESTTLATLSEERPVLLYFWASWCGVCRFTTPAVAHLAAEGENVMTVALRSGGDAEVARWLARKGVDFPVVNDANGALSAGWEISVTPTLVVVSQGRVVFTTSGWTSYWGMKLRLWWAKTF
>16761507
MNTVCTHCQAINRIPGDRLQDAAKCGRCGHELFDGEVINATGETLDKLLKDDLPVVIDFWAPWCGPCRNFAPIFEDVAEERSGKVRFVKVNTEAERELSARFGIRSIPMIMIFKHGQVVDMLNGAVPKAPFDSWLNEAL
>16803644
MAERLVGTQAPRFEMEAVMPNQTFGKVSLEKNIEDDKWTILFFYPMDFTFVCPTEIVAISARSDEFDALNARIIGASTDTIHSHLAWTNTPIKEGGIGKLNYPLAADTNHQVASDYGVLIEEEGVALRGLFIINPKGEIQYEVVHHNNIGREVDEVLRVLQALQTGGLCPINWQPGEKTIV
>16804867
MAIIFAKEDDLEEIISSHPKILLNFWAEWCAPCRCFWPTLEQFAEMEEGNVQVVKINVDKQRALAQKFDVKGIPNSLVLVDGEIKGAIAGIVSCDELRSRFKSLAK
>17229033
MFSNREGQRVPQVTFRTRQNNEWVNVTTDDLFAGKTVAVFSLPGAFTPTCSSTHLPGYNELAKVFKDNGVDEIVCISVNDAFVMNEWAKTQEAENITLIPDGNGEFTEGMGMLVDKTDLGFGKRSWRYSMLVKDGVIEKMFIEPDVPGDPFEVSDAQTMLKHINPQAAKPKLVSLFTKVGCPFCARAKAALQENGIEYEEITLGKGITTRSLRAVTGATTVPQVFIDGVLIGGSEALTDYLSTIKQEKVGV
>17229859
MPTDTVAYVQENEFDTVLSEDKVVVVDFTATWCGPCRLVSPLMDQLADEYKGRVKVVKVDVDNNKPLFKRFGLRSIPAVLIFKDGELTEKIVGVSPYEQFSGAVEKLI
>1729944
MLMLDKDTFKTEVLEGTGYVLVDYFSDGCVPCKALMPAVEELSKKYEGRVVFAKLNTTGARRLAISQKILGLPTLSLYKDGVKVDEVTKDDATIENIEAMVEEHISK
>17531233
MLKRCNFKNQVKYFQSDFEQLIRQHPEKIIILDFYATWCGPCKAIAPLYKELATTHKGIIFCKVDVDEAEDLCSKYDVKMMPTFIFTKNGDAIEALEGCVEDELRQKVLEHVSAQ
>17537401
MPQFLKGVTLENREGDELPAEEHLKGKIIGLYFSASWCPPCRAFTPKLKEFFEEIKKTHPEFEIIFVSRDRNSSDLVTYFKEHQGEWTYIPFGSDKIMSLMQKYEVKTIPAMRIVNDQGEVIVQDARTEIQNKGENVEGLWAEWMALIK
>17547503
MSRRQTLIALILAGIVAAVLGVYAGHRATQPRPPADGAVTAFFDARLPDANGTPIDLSAFRGQPVVINFWAPWCGPCVEEMPELSALAQEQKARVKFIGIGIDSAANIQAFLGKVPVTYPIAVAGFGGTELGRQLGNQAGGLPFTVILNAQGEITFRKMGRVHADELRAALQRT
>18309723
MENINLFIVFIEGILSIFSPCILPILPIYLSMLSNSSVEDIRDSNFKSGVLIRNTLFFTLGISTTFFILGSSISALSSFFNTNKNIIMILGGVIILFMGLFYLGLINLNILNREKRLNFKYKNMSPVSAFVLGFTFSFGWTPCIGPILASVLVMASSSKNLLMSNLLILVYTIGFILPFIIASLFYGKLFKKFDGIKKHMDLIKKISGIFIIIAGLIMLVGGIRNMNNEIKINNNPQINKSESVNKDSKNESDNKKQEEENKIPPIDFTLYDQYGNKHTLSEYKGKTIFLNFWATWCPPCRGEMPYIDELYKEYNENKDDVVILGVASPNLGREGSEEHIKNFLKEENHVFPVVLDENGAMVYQYGINAFPSTFIINKEGYITKYIPGAMTKETMKTLIESER
>18313548
MVLKVGDKAPDFELLNEELKPVRLSEVLKRGRPVVLLFFPGAFTSVCTKELCTFRDKMALLNKANAEVLAISVDSPFALKAFKDANRLNFPLLSDYNRIVIGMYDVVQANLLGLPLYHLAKRAVYIIDPTGTIRYVWYSDDPRDEPPYDEVIKEAEKIGAQK
>18406743
MAETSKQVNGDDAQDLHSLLSSPARDFLVRNDGEQVKVDSLLGKKIGLYFSAAWCGPCQRFTPQLVEVYNELSSKVGFEIVFVSGDEDEESFGDYFRKMPWLAVPFTDSETRDRLDELFKVRGIPNLVMVDDHGKLVNENGVGVIRSYGADAYPFTPEKMKEIKEDEDRARRGQTLRSVLVTPSRDFVISPDGNKVPVSELEGKTIGLLFSVASYRKCTELTPKLVEFYTKLKENKEDFEIVLISLEDDEESFNQDFKTKPWLALPFNDKSGSKLARHFMLSTLPTLVILGPDGKTRHSNVAEAIDDYGVLAYPFTPEKFQELKELEKAKVEAQTLESLLVSGDLNYVLGKDGAKVLVSDLVGKTILMYFSAHWCPPCRAFTPKLVEVYKQIKERNEAFELIFISSDRDQESFDEYYSQMPWLALPFGDPRKASLAKTFKVGGIPMLAALGPTGQTVTKEARDLVVAHGADAYPFTEERLKEIEAKYDEIAKDWPKKVKHVLHEEHELELTRVQVYTCDKCEEEGTIWSYHCDECDFDLHAKCALNEDTKENGDEAVKVGGDESKDGWVCEGNVCTKA
>19173077
MFPKTLTDSKYKAFVDGEIKEISLQDYIGKYVVLAFYPLDFTFVCPTEINRFSDLKGAFLRRNAVVLLISCDSVYTHKAWASIPREQNGVLGTAWPMVWDAKRELCNQFGLYDEENGHPMRSTVILAKDLSVRHISSNYHAIGRSVDEIIRLIDAITFNDENGDICPAEWRSENKDN
>19554157
MEEGEEISLSDFEGEVVVLNAWGQWCAPCRAEVDDLQLVQETLDPLGGTVLGINVRDYNQTIAQDFKLDNAVTYPSIYDPPFRIAAALGGVPTSVIPTTIVLDRSHRPAAVFLREVTALSG
>19705357
MSFSVFAAKSDKKDDVKLPNIVLYDQYGKKHNIEEYKGKVVVINFWATWCGYCVEEMPGFEKVYKEFGSNKKDVIILGVAGPKSKENLNNVDVEKDKIISFLKKKNITYPSLMDETGKSFDDYKVRALPMTYVINKNGYLEGFVNGAITDEQLRKAINETLKKK
>19746502
MKKGLLVTTGLACLGLLTACSTQDNMAKKEITQDKMSMAAKKKDKMSTSKDKSMMADKSSDKKMTNDGPMAPDFELKGIDGKTYRLSEFKGKKVYLKFWASWCSICLSTLADTEDLAKMSDKDYVVLTVVSPGHQGEKSEADFTKWFQGTDYKDLPVLLDPDGKLLEAYGVRSYPTEVFIGSDGVLAKKHIGYAKKSDIKKALKGIH
>20092028
MAGDFMKPMLLDFSATWCGPCRMQKPILEELEKKYGDKVEFKVVDVDENQELASKYGIHAVPTLIIQKDGTEVKRFMGVTQGSILAAELDKLL
>20151112
SLINTKIKPFKNQAFKNGEFIEVTEKDTEGRWSVFFFYPADFTFVCPTELGDVADHYEELQKLGVDVYSVSTDTHFTHKAWHSSSETIAKIKYAMIGDPTGALTRNFDNMREDEGLADRATFVVDPQGIIQAIEVTAEGIGRDASDLLRKIKAAQYVAAHPGEVCPAKWKEGEATLAPSLDLVGKI
>21112072
MTIQVGDRIPEVVLKHLREGIEAVDTHTLFTGRKVVLFAVPGAFTPTCSAKHLPGYVEQFEAFRKRGIEVLCTAVNDPFVMQAWGRSQLVPDGLHLVPDGNAELARALGLEIDASGSGMGLRSRRYALYADDGVVKALFVEEPGEFKVSAADYVLQHLPD
>21222859
MSAASRAPLRSNRTAERFTERTADARARVRSRAARAAVGAAAAALLVSACSSGGTSGGGGQTGFITGSDGIATAKKGERADAPELSGETVDGGQVDVADYKGKVVVLNVWGSWCPPCRAEAKNFEKVYQDVKDQGVQFVGINTRDTSTGPARAFEKDYGVTYPSLYDPAGRLMLRFEKGTLNPQAVPSTLIIDREGKVAARTLQALSEEKLRKMLAPYLQPEK
>21223405
MLTVGDKFPEFDLTACVSLEKGKEFQQINHKTYEGQWKVVFAWPKDFTFVCPTEIAAFGKLNDEFADRDAQILGFSGDSEFVHHAWRKDHPDLTDLPFPMLADSKHELMRDLGIEGEDGFAQRAVFIVDQNNEIQFTMVTAGSVGRNPKEVLRVLDALQTDELCPCNWSKGDETLDPVALLSGE
>21227878
MTDEIRVGETIQDFRLRDQKREEIHLYDLKGKKVLLSFHPLAWTQVCAQQMKSLEENYELFTELNTVPLGISVDPIPSKKAWARELGINHIKLLSDFWPHGEVARTCGIFRGKEGVSERANIIIDENRQVIYFKKYLGHELPDIKEIIEVLKNK
>21283385
MTEITFKGGPIHLKGQQINEGDFAPDFTVLDNDLNQVTLADYAGKKKLISVVPSIDTGVCDQQTRKFNSDASKEEGIVLTISADLPFAQKRWCASAGLDNVITLSDHRDLSFGENYGVVMEELRLLARAVFVLDADNKVVYKEIVSEGTDFPDFDAALAAYKNI
>21674812
MIEEGKIAPDFTLPDSTGKMVSLSEFKGRKVLLIFYPGDDTPVCTAQLCDYRNNVAAFTSRGITVIGISGDSPESHKQFAEKHKLPFLLLSDQERTVAKAYDALGFLGMAQRAYVLIDEQGLVLLSYSDFLPVTYQPMKDLLARIDAS
>23098307
MKILKYVLIISISMFLPIMTAYAEGTEVGERAPDFELKTIDGQQLRLSDFKGERVLINFWTTWCPPCRQEMPDMQRFYQDLQPNILAVNLTDTEMNKEQVVRFSQELELTFPILLDEKGEVSKAYRISPIPTTYMIDSEGIIRHKSYGALTYEQMVAEYNKME
>2649838
MVFTSKYCPYCRAFEKVVERLMGELNGTVEFEVVDVDEKRELAEKYEVLMLPTLVLADGDEVLGGFMGFADYKTAREAILEQISAFLKPDYKN
>267116
MSKVIHVTSNEELDKYLQHQRVVVDFSAEWCGPCRAIAPVFDKLSNEFTTFTFVHVDIDKVNTHPIGKEIRSVPTFYFYVNGAKVSEFSGANEATLRSTLEANI
>27375582
MSEQSTSANPQRRTFLMVLPLIAFIGLALLFWFRLGSGDPSRIPSALIGRPAPQTALPPLEGLQADNVQVPGLDPAAFKGKVSLVNVWASWCVPCHDEAPLLTELGKDKRFQLVGINYKDAADNARRFLGRYGNPFGRVGVDANGRASIEWGVYGVPETFVVGREGTIVYKLVGPITPDNLRSVLLPQMEKALK
>2822332
MATDTAATTGTASPDEPLYVNGQTELDDVTSDNDVVLADFYADWCGPCQMLEPVVETLAEQTDAAVAKIDVDENQALASAYGVRGVPTLVLFADGEQVEEVVGLQDEDALKDLIESYTE
>30021713
MWRKLTIIVVLLCLAGYAAYEQFGNKEQAVKVKQEKSEAAMKEIIARNGIEIGKSAPDFELTKLDGTNVKLSDLKGKKVILNFWATWCGPCQQEMPDMEAFYKEHKENVEILAVNYTPSEKGGGEEKVSNFIKEKGITFPVLLDKNIDVTTAYKVITIPTSYFIDTKGVIQDKFIGPMTQKEMEKRVAKLK
>3261501
MTTRDLTAAYFQQTISANSNVLVYFWAPLCAPCDLFTPTYEASSRKHFDVVHGKVNIETEKDLASIAGVKLLPTLMAFKKGKLVFKQAGIANPAIMDNLVQQLRAYTFKSPAGEGIGPGTKTSS
>3318841
MPGGLLLGDVAPNFEANTTVGRIRFHDFLGDSWGILFSHPRDFTPVCTTELGRAAKLAPEFAKRNVKLIALSIDSVEDHLAWSKDINAYNSEEPTEKLPFPIIDDRNRELAILLGMLDPAEKDEKGMPVTARVVFVFGPDKKLKLSILYPATTGRNFDEILRVVISLQLTAEKRVATPVDWKDGDSVMVLPTIPEEEAKKLFPKGVFTKELPSGKKYLRYTPQP
>3323237
MALLDISSGNVRKTIETNPLVIVDFWAPWCGSCKMLGPVLEEVESEVGSGVVIGKLNVDDDQDLAVEFNVASIPTLIVFKDGKEVDRSIGFVDKSKILTLIQKNA
>4155972
MLEVINGKNYAEKTAHQAVVVNVGASWCPDCRKIEPIMENLAKTYKGKVEFFKVSFDESQDLKESLGIRKIPTLIFYKNAKEVGERLVEPSSQKPIEDALKALL
>4200327
MAQRLLLRRFLASVISRKPSQGQWPPLTSRALQTPQCSPGGLTVTPNPARTIYTTRISLTTFNIQDGPDFQDRVVNSETPVVVDFHAQWCGPCKILGPRLEKMVAKQHGKVVMAKVDIDDHTDLAIEYEVSAVPTVLAMKNGDVVDKFVGIKDEDQLEAFLKKLIG
>4433065
GSIKEIDINEYKGKYVVLLFYPLDWTFVCPTEMIGYSEVAGQLKEINCEVIGVSVDSVYCHQAWCEADKSKGGVGKLGFPLVSDIKRCISIKYGMLNVETGVSRRGYVIIDDKGKVRYIQMNDDGIGRSTEET
>4704732
MAPITVGDVVPDGTISFFDENDQLQTVSVHSIAAGKKVILFGVPGAFTPTCSMSHVPGFIGKAEELKSKGIDEIICFSVNDPFVMKAWGKTYPENKHVKFVADGSGEYTHLLGLELDLKDKGSGISSGRFALLLDNLKVTVANVESGGEFTVSSAEDILKAL
>4996210
MAYHLGATFPNFTATASNVDGVFDFYKYVGDNWAILFSHPHDFTPVCTTELAEFGKMHEEFLKLNCKLIGFSCNSKESHDQWIEDIKFYGNLDKWDIPMVCDESRELANQLKIMDEKEKDIKGLPLTCRCVFFISPDKKVKATVLYPATTGRNSQEILRVLKSLQLTNTHPVATPVNWKEGDKCCILPSVDNADLPKLFKNEVKKLDVPSQKAYLRFVQM
>5326864
MSLKAGDSFPEGVTFSYIPWAEDASEITSCGIPINYNASKEFANKKVVLFALPGAFTPVCSANHVPEYIQKLPELRAKGVDQVAVLAYNDAYVMSAWGKANGVTGDDILFLSDPEAKFSKSIGWADEEGRTYRYVLVIDNGKIIYAAKEAAKNSLELSRADHVLKQL
>6322180
MGEALRRSTRIAISKRMLEEEESKLAPISTPEVPKKKIKTGPKHNANQAVVQEANRSSDVNELEIGDPIPDLSLLNEDNDSISLKKITENNRVVVFFVYPRASTPGCTRQACGFRDNYQELKKYAAVFGLSADSVTSQKKFQSKQNLPYHLLSDPKREFIGLLGAKKTPLSGSIRSHFIFVDGKLKFKRVKISPEVSVNDAKKEVLEVAEKFKEE
>6323138
MSDLVNKKFPAGDYKFQYIAISQSDADSESCKMPQTVEWSKLISENKKVIITGAPAAFSPTCTVSHIPGYINYLDELVKEKEVDQVIVVTVDNPFANQAWAKSLGVKDTTHIKFASDPGCAFTKSIGFELAVGDGVYWSGRWAMVVENGIVTYAAKETNPGTDVTVSSVESVLAHL
>6687568
MRVLATAADLEKLINENKGRLIVVDFFAQWCGPCRNIAPKVEALAKEIPEVEFAKVDVDQNEEAAAKYSVTAMPTFVFIKDGKEVDRFSGANETKLRETITRHK
>6850955
MVSVGKKAPDFEMAGFYKGEFKTFRLSEYLGKWVVLCFYPGDFTFVXATEVSAVAEKYPEFQKLGVEVLSVSVDSVFVHKMWNDNELSKMVEGGIPFPMLSDGGGNVGTLYGVYDPEAGVENRGRFLIDPDGIIQGYEVLILPVGRNVSETLRQIQAFQLVRETKGAEVAPSGWKPGKKTLKPGPGLVGNVYKEWSVKEAFED
>7109697
MKHITNKAELDQLLTTNKKVVVDFYANWCGPCKILGPIFEEVAQDKKDWTFVKVDVDQANEISSEYEIRSIPTIIFFQDGKMADKRIGFIPKNELKELLK
>7290567
MVYPVRNKDDLDQQLILAEDKLVVIDFYADWCGPCKIIAPKLDELAQQYSDRVVVLKVNVDENEDITVEYNVNSMPTFVFIKGGNVLELFVGCNSDKLAKLMEKHARRLYR
>9955016
XSGNARIGKPAPDFKATAVVDGAFKEVKLSDYKGKYVVLFFYPLDFTFVCPTEIIAFSNRAEDFRKLGCEVLGVSVDSQFTHLAWINTPRKEGGLGPLNIPLLADVTRRLSEDYGVLKTDEGIAYRGLFIIDGKGVLRQITVNDLPVGRSVDEALRLVQAFQYTDEHGEVCPAGWKPGSDTIKPNVDDSKEYFSKHN
>15677788
MKKILTAAVVALIGILLAIVLIPDSKTAPAFSLPDLHGKTVSNADLQGKVTLINFWFPSCPGCVSEMPKIIKTANDYKNKNFQVLAVAQPIDPIESVRQYVKDYGLPFTVMYDADKAVGQAFGTQVYPTSVLIGKKGEILKTYVGEPDFGKLYQEIDTAWRNSDAV PyCogent-1.5.3/doc/data/ST_genome_part.gb 000644 000765 000024 00000077246 11350301455 021153 0 ustar 00jrideout staff 000000 000000 LOCUS AE006468 4857432 bp DNA circular BCT 23-FEB-2009
DEFINITION Salmonella enterica subsp. enterica serovar Typhimurium str. LT2,
complete genome.
ACCESSION AE006468 AE008693-AE008916
VERSION AE006468.1 GI:16445344
DBLINK Project:241
KEYWORDS .
SOURCE Salmonella enterica subsp. enterica serovar Typhimurium str. LT2
ORGANISM Salmonella enterica subsp. enterica serovar Typhimurium str. LT2
Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacteriales;
Enterobacteriaceae; Salmonella; Salmonella enterica subsp. enterica
serovar Typhimurium.
REFERENCE 1 (bases 1 to 4857432)
AUTHORS McClelland,M., Sanderson,K.E., Spieth,J., Clifton,S.W.,
Latreille,P., Courtney,L., Porwollik,S., Ali,J., Dante,M., Du,F.,
Hou,S., Layman,D., Leonard,S., Nguyen,C., Scott,K., Holmes,A.,
Grewal,N., Mulvaney,E., Ryan,E., Sun,H., Florea,L., Miller,W.,
Stoneking,T., Nhan,M., Waterston,R. and Wilson,R.K.
TITLE Complete genome sequence of Salmonella enterica serovar Typhimurium
LT2
JOURNAL Nature 413 (6858), 852-856 (2001)
PUBMED 11677609
REFERENCE 2 (bases 1 to 4857432)
CONSRTM The Salmonella typhimurium Genome Sequencing Project
TITLE Direct Submission
JOURNAL Submitted (29-MAR-2001) Genome Sequencing Center, Department of
Genetics, Washington University School of Medicine, 4444 Forest
Park Boulevard, St. Louis, MO 63108, USA
COMMENT On or before Feb 20, 2009 this sequence version replaced
gi:16418493, gi:16418512, gi:16418529, gi:16418549, gi:16418569,
gi:16418591, gi:16418608, gi:16418628, gi:16418650, gi:16418668,
gi:16418689, gi:16418705, gi:16418723, gi:16418742, gi:16418760,
gi:16418784, gi:16418804, gi:16418824, gi:16418844, gi:16418861,
gi:16418878, gi:16418900, gi:16418921, gi:16418944, gi:16418964,
gi:16418985, gi:16419003, gi:16419024, gi:16419047, gi:16419070,
gi:16419090, gi:16419110, gi:16419136, gi:16419161, gi:16419181,
gi:16419199, gi:16419219, gi:16419241, gi:16419261, gi:16419282,
gi:16419303, gi:16419326, gi:16419345, gi:16419364, gi:22024638,
gi:16419449, gi:16419469, gi:16419487, gi:22024639, gi:16419572,
gi:16419592, gi:16419620, gi:16419641, gi:16419665, gi:16419687,
gi:16419709, gi:16419731, gi:16419750, gi:16419776, gi:16419802,
gi:16419825, gi:16419849, gi:16419870, gi:16419888, gi:16419908,
gi:16419944, gi:16419969, gi:16419990, gi:16420008, gi:16420030,
gi:16420061, gi:16420079, gi:16420095, gi:16420112, gi:16420132,
gi:16420154, gi:16420173, gi:16420194, gi:16420213, gi:16420237,
gi:16420258, gi:16420281, gi:16420298, gi:16420325, gi:16420348,
gi:16420369, gi:16420391, gi:16420418, gi:16420438, gi:16420461,
gi:16420488, gi:16420517, gi:16420539, gi:16420565, gi:16420590,
gi:16420610, gi:16420630, gi:16420649, gi:16420666, gi:16420687,
gi:16420709, gi:16420731, gi:16420749, gi:16420769, gi:16420795,
gi:16420811, gi:16420832, gi:16420856, gi:16420874, gi:16420896,
gi:16420916, gi:16420938, gi:16420955, gi:16420979, gi:16421005,
gi:16421023, gi:16421046, gi:16421058, gi:16421075, gi:16421092,
gi:16421111, gi:16421131, gi:16421159, gi:16421190, gi:16421206,
gi:16421230, gi:16421239, gi:16421268, gi:16421292, gi:16421311,
gi:16421327, gi:16421347, gi:16421370, gi:16421388, gi:16421412,
gi:16421434, gi:16421460, gi:16421485, gi:16421501, gi:16421517,
gi:16421536, gi:16421550, gi:16421569, gi:16421592, gi:16421612,
gi:16421636, gi:16421663, gi:16421682, gi:16421705, gi:16421729,
gi:16421751, gi:16421769, gi:16421791, gi:16421808, gi:16421834,
gi:16421851, gi:16421879, gi:16421897, gi:16421920, gi:16421939,
gi:16421954, gi:16421987, gi:16422017, gi:16422036, gi:16422058,
gi:16422074, gi:16422092, gi:16422111, gi:16422137, gi:16422156,
gi:16422173, gi:16422188, gi:16422205, gi:16422228, gi:16422247,
gi:16422263, gi:16422283, gi:16422308, gi:16422324, gi:16422343,
gi:16422367, gi:16422393, gi:16422410, gi:16422430, gi:16422449,
gi:16422464, gi:16422484, gi:16422503, gi:16422527, gi:16422547,
gi:16422561, gi:16422586, gi:16422609, gi:16422630, gi:16422654,
gi:16422675, gi:16422691, gi:16422706, gi:16422728, gi:16422744,
gi:16422768, gi:16422789, gi:16422815, gi:16422822, gi:16422843,
gi:16422860, gi:16422882, gi:16422906, gi:16422923, gi:16422950,
gi:16422976, gi:16422994, gi:16423017, gi:16423037, gi:16423054,
gi:16423067, gi:16423088, gi:16423108, gi:16423133, gi:16423153.
Supported by NIH grant 5U 01 AI43283
Coding sequences below are predicted from manually evaluated
computer analysis, using similarity information and the programs;
GLIMMER; http://www.tigr.org/softlab/glimmer/glimmer.html and
GeneMark; http://opal.biology.gatech.edu/GeneMark/
EC numbers were kindly provided by Junko Yabuzaki and the Kyoto
Encyclopedia of Genes and Genomes; http://www.genome.ad.jp/kegg/,
and Pedro Romero and Peter Karp at EcoCyc;
http://ecocyc.PangeaSystems.com/ecocyc/
The analyses of ribosome binding sites and promoter binding sites
were kindly provided by Heladia Salgado, Julio Collado-Vides and
ReguonDB;
http://kinich.cifn.unam.mx:8850/db/regulondb_intro.frameset
This sequence was finished as follows unless otherwise noted: all
regions were double stranded, sequenced with an alternate
chemistries or covered by high quality data (i.e., phred quality >=
30); an attempt was made to resolve all sequencing problems, such
as compressions and repeats; all regions were covered by sequence
from more than one m13 subclone.
FEATURES Location/Qualifiers
source join(1..962611,1004276..1098227,1143715..2728971,
2776823..2844426,2879234..4857432)
/organism="Salmonella enterica subsp. enterica serovar
Typhimurium str. LT2"
/mol_type="genomic DNA"
/strain="LT2; SGSC 1412; ATCC 700720"
/serovar="Typhimurium"
/culture_collection="ATCC:700720"
/db_xref="taxon:99287"
/focus
source 962612..1004275
/organism="Salmonella phage Fels-1"
/mol_type="genomic DNA"
/db_xref="taxon:128975"
source 1098228..1143714
/organism="Phage Gifsy-2"
/mol_type="genomic DNA"
/db_xref="taxon:129862"
source 2728972..2776822
/organism="Phage Gifsy-1"
/mol_type="genomic DNA"
/db_xref="taxon:129861"
source 2844427..2879233
/organism="Enterobacteria phage Fels-2"
/mol_type="genomic DNA"
/db_xref="taxon:194701"
gene 190..255
/gene="thrL"
/locus_tag="STM0001"
CDS 190..255
/gene="thrL"
/locus_tag="STM0001"
/note="similar to E. coli thr operon leader peptide
(AAC73112.1); Blastp hit to AAC73112.1 (21 aa),
85-1073758644dentity in aa 1 - 21"
/codon_start=1
/transl_table=11
/product="thr operon leader peptide"
/protein_id="AAL18965.1"
/db_xref="GI:16418494"
/translation="MNRISTTTITTITITTGNGAG"
gene 325..2799
/gene="thrA"
/locus_tag="STM0002"
RBS 325..330
/gene="thrA"
/locus_tag="STM0002"
/note="putative RBS for thrA; RegulonDB:STMS1H000398"
CDS 337..2799
/gene="thrA"
/locus_tag="STM0002"
/EC_number="1.1.1.3"
/EC_number="2.7.2.4"
/note="bifunctional; N-terminaus is aspartokinase I and C
terminus is homoserine dehydrogenase I; similar to E. coli
aspartokinase I, homoserine dehydrogenase I (AAC73113.1);
Blastp hit to AAC73113.1 (820 aa), 94% identity in aa 1 -
820"
/codon_start=1
/transl_table=11
/product="aspartokinase I"
/protein_id="AAL18966.1"
/db_xref="GI:16418495"
/translation="MRVLKFGGTSVANAERFLRVADILESNARQGQVATVLSAPAKIT
NHLVAMIEKTIGGQDALPNISDAERIFSDLLAGLASAQPGFPLARLKMVVEQEFAQIK
HVLHGISLLGQCPDSINAALICRGEKMSIAIMAGLLEARGHRVTVIDPVEKLLAVGHY
LESTVDIAESTRRIAASQIPADHMILMAGFTAGNEKGELVVLGRNGSDYSAAVLAACL
RADCCEIWTDVDGVYTCDPRQVPDARLLKSMSYQEAMELSYFGAKVLHPRTITPIAQF
QIPCLIKNTGNPQAPGTLIGASSDDDNLPVKGISNLNNMAMFSVSGPGMKGMIGMAAR
VFAAMSRAGISVVLITQSSSEYSISFCVPQSDCARARRAMQDEFYLELKEGLLEPLAV
TERLAIISVVGDGMRTLRGISAKFFAALARANINIVAIAQGSSERSISVVVNNDDATT
GVRVTHQMLFNTDQVIEVFVIGVGGVGGALLEQLKRQQTWLKNKHIDLRVCGVANSKA
LLTNVHGLNLDNWQAELAQANAPFNLGRLIRLVKEYHLLNPVIVDCTSSQAVADQYAD
FLREGFHVVTPNKKANTSSMDYYHQLRFAAAQSRRKFLYDTNVGAGLPVIENLQNLLN
AGDELQKFSGILSGSLSFIFGKLEEGMSLSQATALAREMGYTEPDPRDDLSGMDVARK
LLILARETGRELELSDIVIEPVLPNEFDASGDVTAFMAHLPQLDDAFAARVAKARDEG
KVLRYVGNIEEDGVCRVKIAEVDGNDPLFKVKNGENALAFYSHYYQPLPLVLRGYGAG
NDVTAAGVFADLLRTLSWKLGV"
gene 2789..3730
/gene="thrB"
/locus_tag="STM0003"
RBS 2789..2794
/gene="thrB"
/locus_tag="STM0003"
/note="putative RBS for thrB; RegulonDB:STMS1H000399"
CDS 2801..3730
/gene="thrB"
/locus_tag="STM0003"
/EC_number="2.7.1.39"
/note="similar to E. coli homoserine kinase (AAC73114.1);
Blastp hit to AAC73114.1 (310 aa), 93% identity in aa 1 -
308"
/codon_start=1
/transl_table=11
/product="homoserine kinase"
/protein_id="AAL18967.1"
/db_xref="GI:16418496"
/translation="MVKVYAPASSANMSVGFDVLGAAVTPVDGTLLGDVVSVEAADHF
RLHNLGRFADKLPPEPRENIVYQCWERFCQALGKTIPVAMTLEKNMPIGSGLGSSACS
VVAALVAMNEHCGKPLNDTRLLALMGELEGRISGSIHYDNVAPCFLGGMQLMIEENGI
ISQQVPGFDEWLWVLAYPGIKVSTAEARAILPAQYRRQDCIAHGRHLAGFIHACYSRQ
PQLAAALMKDVIAEPYRARLLPGFSQARQAVSEIGALASGISGSGPTLFALCDKPETA
QRVADWLSKHYLQNQEGFVHICRLDTAGARVVG"
gene 3722..5020
/gene="thrC"
/locus_tag="STM0004"
RBS 3722..3727
/gene="thrB"
/locus_tag="STM0003"
/note="putative RBS for thrC; RegulonDB:STMS1H000400"
CDS 3734..5020
/gene="thrC"
/locus_tag="STM0004"
/EC_number="4.2.3.1"
/note="similar to E. coli threonine synthase (AAC73115.1);
Blastp hit to AAC73115.1 (428 aa), 93% identity in aa 1 -
428"
/codon_start=1
/transl_table=11
/product="threonine synthase"
/protein_id="AAL18968.1"
/db_xref="GI:16418497"
/translation="MKLYNLKDHNEQVSFAQAVTQGLGKQQGLFFPHDLPEFSLTEID
EMLNQDFVSRSAKILSAFIGDEIPQQILEERVRAAFAFPAPVAQVESDVGCLELFHGP
TLAFKDFGGRFMAQMLTHISGDKPVTILTATSGDTGAAVAHAFYGLENVRVVILYPRG
KISPLQEKLFCTLGGNIETVAIDGDFDACQALVKQAFDDEELKTALGLNSANSINISR
LLAQICYYFEAVAQLPQGARNQLVISVPSGNFGDLTAGLLAKSLGLPVKRFIAATNVN
DTVPRFLHDGKWAPKATQATLSNAMDVSQPNNWPRVEELFRRKIWRLTELGYAAVDDT
TTQQTMRELKAKGYISEPHAAVAYRALRDQLNPGEYGLFLGTAHPAKFKESVESILGE
TLALPEALAERADLPLLSHHLPADFAALRKLMMTRQ"
gene complement(5114..5898)
/gene="yaaA"
/locus_tag="STM0005"
CDS complement(5114..5887)
/gene="yaaA"
/locus_tag="STM0005"
/note="similar to E. coli orf, hypothetical protein
(AAC73117.1); Blastp hit to AAC73117.1 (258 aa), 86%
identity in aa 1 - 257"
/codon_start=1
/transl_table=11
/product="putative cytoplasmic protein"
/protein_id="AAL18969.1"
/db_xref="GI:16418498"
/translation="MLILISPAKTLDYQSPLATTRYTQPELLDHSQQLIQQARQLSAP
QISRLMGISDKLADLNATRFHDWQPHFTPDNARQAILAFKGDVYTGLQAETFNDADFD
FAQQHLRMLSGLYGVLRPLDLMQPYRLEMGIRLENPRGKDLYQFWGDIITDKLNEALE
AQGDRVVVNLASEEYFKSVKPKKLNAELIKPVFLDEKNGKFKVVSFYAKKARGLMSRF
IIENRLTKPEQLTAFDREGYFFDEETSTQDELVFKRYEQ"
RBS complement(5893..5898)
/gene="yaaA"
/locus_tag="STM0005"
/note="putative RBS for yaaA; RegulonDB:STMS1H000401"
gene complement(5966..7407)
/gene="yaaJ"
/locus_tag="STM0006"
CDS complement(5966..7396)
/gene="yaaJ"
/locus_tag="STM0006"
/note="AGCS family; similar to E. coli inner membrane
transport protein (AAC73118.1); Blastp hit to AAC73118.1
(476 aa), 76% identity in aa 1 - 476"
/codon_start=1
/transl_table=11
/product="putative alanine/glycine transport protein"
/protein_id="AAL18970.1"
/db_xref="GI:16418499"
/translation="MPEFFSFINEILWGSVMIYLLLGAGCWFTWRTGFIQFRYIRQFS
RSLKGSLSPQPGGLTSFQALCTSLAARIGSGNLAGVALAIAAGGPGAVFWMWVSAIIG
MATSFAECSLAQLYKERDPTGQFRGGPAWYMARGLGMRWMGVVFALFLLVAYGLIFNS
VQANAVSRALHFAFNIPPLISGIALAFCALLIIIRGIKGVARLMQWLIPLIALLWVAG
SVFICLWHIEQMPGVIASIVKSAFGWQEAAAGAAGYTLTQAITSGFQRGMFSNEAGMG
STPNAAAAATSYPPHPVAQGIVQMIGVFSDTIIICTASAMIILLAGNHASHSSTEGIQ
LLQHAMVSLTGEWGASFVALIVILFAFSSIVANYIYAENNLFFLRLHNAKAIWLLRLA
TLGMVIAGTLISFPLIWQLADMIMACMAITNLTAILLLSPVVYTLASDYLRQRKLGVR
PQFDPRRFPDIEPQLAPDTWEAASRD"
RBS complement(7402..7407)
/gene="yaaJ"
/locus_tag="STM0006"
/note="putative RBS for yaaJ; RegulonDB:STMS1H000402"
gene 7652..8618
/gene="talB"
/locus_tag="STM0007"
RBS 7652..7657
/gene="talB"
/locus_tag="STM0007"
/note="putative RBS for talB; RegulonDB:STMS1H000403"
CDS 7665..8618
/gene="talB"
/locus_tag="STM0007"
/EC_number="2.2.1.2"
/note="similar to E. coli transaldolase B (AAC73119.1);
Blastp hit to AAC73119.1 (317 aa), 94% identity in aa 1 -
317"
/codon_start=1
/transl_table=11
/product="transaldolase B"
/protein_id="AAL18971.1"
/db_xref="GI:16418500"
/translation="MTDKLTSLRQFTTVVADTGDIAAMKLYQPQDATTNPSLILNAAQ
IPEYRKLIDDAVAWAKQQSSDRAQQVVDATDKLAVNIGLEILKLVPGRISTEVDARLS
YDTEASIAKAKRIIKLYNDAGISNDRILIKLASTWQGIRAAEQLEKEGINCNLTLLFS
FAQARACAEAGVYLISPFVGRILDWYKANTDKKDYAPAEDPGVVSVTEIYEYYKQHGY
ETVVMGASFRNVGEILELAGCDRLTIAPALLKELAESEGAIERKLSFSGEVKARPERI
TEAEFLWQHHQDPMAVDKLADGIRKFAVDQEKLEKMIGDLL"
gene 8718..9319
/gene="mog"
/locus_tag="STM0008"
RBS 8718..8723
/gene="mog"
/locus_tag="STM0008"
/note="putative RBS for mog; RegulonDB:STMS1H000404"
CDS 8729..9319
/gene="mog"
/locus_tag="STM0008"
/note="molybdopterine biosynthesis; similar to E. coli
required for the efficient incorporation of molybdate into
molybdoproteins (AAC73120.1); Blastp hit to AAC73120.1
(195 aa), 91% identity in aa 1 - 192"
/codon_start=1
/transl_table=11
/product="putative molybdochetalase"
/protein_id="AAL18972.1"
/db_xref="GI:16418501"
/translation="MDTLRIGLVSISDRASSGVYQDKGIPALEEWLASALTTPFEVQR
RLIPDEQEIIEQTLCELVDEMSCHLVLTTGGTGPARRDVTPDATLAIADREMPGFGEQ
MRQISLRFVPTAILSRQVGVIRKQALILNLPGQPKSIKETLEGVKADDGSVSVPGIFA
SVPYCIQLLDGPYVETAPEVVAAFRPKSARRENMSD"
gene complement(9376..9950)
/gene="yaaH"
/locus_tag="STM0009"
CDS complement(9376..9942)
/gene="yaaH"
/locus_tag="STM0009"
/note="similar to E. coli orf, hypothetical protein
(AAC73121.1); Blastp hit to AAC73121.1 (188 aa), 90%
identity in aa 1 - 188"
/codon_start=1
/transl_table=11
/product="putative regulatory protein"
/protein_id="AAL18973.1"
/db_xref="GI:16418502"
/translation="MGNTKLANPAPLGLMGFGMTTILLNLHNAGFFALDGIILAMGIF
YGGIAQIFAGLLEYKKGNTFGLTAFTSYGSFWLTLVAILLMPKMGLTDAPDAQLLGAY
LGLWGVFTLFMFFGTLKAARALQFVFLSLTVLFALLAVGNITGNEATIHIAGWVGLVC
GASAIYLAMGEVLNEQFGRTILPIGEAH"
RBS complement(9945..9950)
/gene="yaaH"
/locus_tag="STM0009"
/note="putative RBS for yaaH; RegulonDB:STMS1H000405"
ORIGIN
1 agagattacg tctggttgca agagatcatg acagggggaa ttggttgaaa ataaatatat
61 cgccagcagc acatgaacaa gtttcggaat gtgatcaatt taaaaattta ttgacttagg
121 cgggcagata ctttaaccaa tataggaata caagacagac aaataaaaat gacagagtac
181 acaacatcca tgaaccgcat cagcaccacc accattacca ccatcaccat taccacaggt
241 aacggtgcgg gctgacgcgt acaggaaaca cagaaaaaag cccgcacctg aacagtgcgg
301 gctttttttt cgaccagaga tcacgaggta acaaccatgc gagtgttgaa gttcggcggt
361 acatcagtgg caaatgcaga acgttttctg cgtgttgccg atattctgga aagcaatgcc
421 aggcaagggc aggtagcgac cgtactttcc gcccccgcga aaattaccaa ccatctggtg
481 gcaatgattg aaaaaactat cggcggccag gatgctttgc cgaatatcag cgatgcagaa
541 cgtatttttt ctgacctgct cgcaggactt gccagcgcgc agccgggatt cccgcttgca
601 cggttgaaaa tggttgtcga acaagaattc gctcagatca aacatgttct gcatggtatc
661 agcctgctgg gtcagtgccc ggatagcatc aacgccgcgc tgatttgccg tggcgaaaaa
721 atgtcgatcg cgattatggc gggacttctg gaggcgcgtg ggcatcgcgt cacggtgatc
781 gatccggtag aaaaattgct ggcggtgggc cattaccttg aatctaccgt tgatatcgcg
841 gaatcgactc gccgtatcgc cgccagccag atcccggccg atcacatgat cctgatggcg
901 ggctttaccg ccggtaatga aaagggtgaa ctggtggtgc tgggccgtaa tggttccgac
961 tattccgccg ccgtgctggc cgcctgttta cgcgctgact gctgtgaaat ctggactgac
1021 gtcgatggcg tgtatacctg tgacccgcgc caggtgccgg acgccaggct gctgaaatcg
1081 atgtcctacc aggaagcgat ggaactctct tacttcggcg ccaaagtcct tcaccctcgc
1141 accattacgc ccatcgccca gttccagatc ccctgtctga ttaaaaatac cggtaatccg
1201 caggcgccag gaacgctgat cggcgcgtcc agcgacgatg ataacctgcc ggttaaaggg
1261 atctctaacc ttaacaacat ggcgatgttt agcgtctccg gcccgggaat gaaagggatg
1321 attgggatgg cggcgcgtgt tttcgccgcc atgtctcgcg ccgggatctc ggtggtgctc
1381 attacccagt cctcctctga gtacagcatc agtttctgtg tgccgcagag tgactgcgcg
1441 cgtgcccgcc gtgcgatgca ggatgagttc tatctggagc tgaaagaggg gctgctggag
1501 ccgctggcgg ttacggagcg gttggcgatt atctctgttg tcggcgacgg tatgcgcacg
1561 ctacgcggca tttcagcgaa attcttcgcc gcgctggcgc gggctaatat caatatcgtg
1621 gcgatcgctc agggatcttc tgagcgttct atttctgtgg tggtgaataa cgacgatgcc
1681 accaccggcg tgcgggtaac gcaccagatg ctgttcaata ccgatcaggt gattgaagtg
1741 tttgtcattg gcgtcggcgg cgtcggcggc gcgctactgg aacagcttaa acgtcagcaa
1801 acctggctga agaacaagca catcgatcta cgcgtgtgcg gcgtggcgaa ctcaaaggcg
1861 ttgctaacca atgtgcatgg cctgaatctg gacaactggc aggcggaact ggcgcaagcg
1921 aacgcgccgt tcaatctggg acgcttaatt cgcctggtga aagaatatca tctactcaat
1981 ccggtgattg ttgattgtac ctccagtcag gcggtggccg accagtatgc cgacttcctg
2041 cgtgaagggt tccatgtggt gacgccaaac aagaaagcga acacctcgtc aatggactac
2101 taccatcagc tacgtttcgc cgccgcgcaa tcacggcgca aattcttgta tgacaccaac
2161 gtcggcgccg gtttgccggt aatcgaaaac ctgcaaaacc tgctgaatgc cggtgatgaa
2221 ctgcaaaaat tttccggcat tctttccggg tcgctctctt ttattttcgg taaactggaa
2281 gaggggatga gtctctcaca ggcgaccgcc ctggcgcgcg agatgggcta taccgaaccc
2341 gatccgcgcg acgatctttc cggtatggat gtggcgcgta aactgttgat cctcgcccgc
2401 gagacgggcc gcgagctgga gctttccgat attgtgattg aaccggtgtt gccgaacgag
2461 tttgacgcct ccggcgatgt gaccgccttt atggcacatc tgccgcagct tgacgacgcg
2521 tttgccgccc gtgtggcgaa agctcgtgat gaaggtaagg tattgcgcta tgtgggcaat
2581 atcgaagagg atggcgtgtg ccgcgtgaaa attgccgaag ttgatggtaa cgatccgctc
2641 ttcaaagtga aaaacggtga aaacgcgctg gcgttctaca gccactatta tcagcccttg
2701 ccgttggtgc tgcgcggcta cggcgcaggc aatgatgtga cggcggcggg cgtgtttgcc
2761 gatctgttac ggaccctctc atggaagtta ggagtttaac atggtgaaag tgtatgcccc
2821 ggcttccagc gcgaacatga gcgtcggttt cgacgtgttg ggcgcagccg tcacacccgt
2881 tgacggcacg ttgctgggcg atgtggtatc cgttgaagca gcggaccatt tccgtctgca
2941 taacctgggg cgatttgccg ataaactgcc gccggagccg cgtgaaaata ttgtttatca
3001 gtgctgggaa cgtttttgcc aggcattggg gaaaaccatc ccggtggcga tgacgctgga
3061 aaaaaatatg ccgattggtt ccgggttagg gtccagcgcc tgttccgtcg tcgccgcgct
3121 ggtcgcgatg aatgagcact gcggcaaacc gttaaacgac acgcgtctgt tggcgctgat
3181 gggcgagctg gaaggccgta tctccggcag catccattac gataacgtcg cgccgtgctt
3241 tcttggcggt atgcagttga tgattgaaga aaacggcatt attagtcagc aggtgccggg
3301 ctttgatgag tggctatggg tactggctta tccgggcatt aaagtttcta ccgcagaagc
3361 acgggccatt ttgcctgcgc agtatcgccg tcaggattgc attgcgcatg gacggcatct
3421 ggccggtttt attcacgcct gttactcgcg gcagccgcag cttgccgccg cgctgatgaa
3481 agatgttatt gccgaaccat accgcgcgcg tttactgccg ggctttagcc aggcgcggca
3541 ggcggtgtcg gagatcggcg cgctggcgag cgggatttcc gggtcggggc cgacgctgtt
3601 tgcgctatgc gataaaccgg agacggcgca gcgcgtcgcg gactggctga gcaaacatta
3661 tctgcaaaat caggaaggct tcgttcatat ttgccggctg gatacggcgg gcgcacgagt
3721 agtgggataa tcaatgaaac tctataatct gaaagaccat aatgagcagg tcagctttgc
3781 gcaggccgtc acgcaaggac tgggcaaaca gcagggactt ttttttccgc acgatctgcc
3841 ggagtttagc ctgacggaaa ttgatgagat gctcaaccag gactttgtca gccgtagcgc
3901 aaagatcctc tcggcattta ttggcgatga aataccgcag caaattctgg aagagcgcgt
3961 ccgcgcggcg tttgcgttcc cggcaccggt agcgcaggta gaaagcgatg tcggctgcct
4021 ggagctgttc catggtccga cgctggcctt taaagacttc ggcgggcgtt ttatggcgca
4081 aatgctgacg catatcagcg gcgacaaacc ggtgacgatt ctgactgcaa cgtcaggcga
4141 taccggcgcg gcggtggctc acgcgttcta tggcctggaa aatgtgcggg tcgtcattct
4201 ctacccgcgc ggtaagatca gtccgttgca ggaaaaactg ttctgtacgc tgggcggcaa
4261 cattgaaacc gtggcgatcg acggcgattt cgacgcgtgc caggcgctgg tgaaacaggc
4321 atttgatgac gaagaactga aaacggcgct ggggctgaat tcggctaatt cgattaatat
4381 cagccgcctg ttggcgcaaa tttgctacta ctttgaagcc gtggcgcaac tgccgcaggg
4441 ggcgcgtaac caactggtga tctccgtccc cagcggcaac tttggcgatt tgacggcagg
4501 gctgctggcg aagtcgttag gcctaccggt gaaacgtttt atcgccgcca ccaacgtcaa
4561 cgacacggtg ccgcgttttc tgcatgacgg aaagtgggcg ccgaaagcga cgcaggcgac
4621 cctgtcgaat gcgatggatg tcagccagcc gaataactgg ccgcgcgtgg aggagctatt
4681 ccgccgtaaa atctggcgcc tgactgagct gggctatgcg gcggtggatg atactacgac
4741 acagcagacg atgcgcgagc tgaaagcgaa aggttatatc tcggaacctc atgcggcggt
4801 agcgtatcgg gcattacgcg accagttaaa ccctggcgag tatggcttgt ttctcggaac
4861 ggcgcatccg gcgaagttta aagagagcgt ggagtccatt ctgggagaaa cgctggcctt
4921 gcctgaagcg ctcgccgaac gcgccgacct gccgctgctt tcacatcatc tgcctgcgga
4981 ttttgccgcc ctgcgtaagc tgatgatgac ccgccaataa ccattgcgcc cggtggcgct
5041 gtcgcttacc gggcctatgg ggtggtgtcg atttgtaggc cggataaggc gtaaccgcca
5101 tccggcgatg ccgttactgc tcgtagcgtt taaagaccag ctcgtcttgt gtggaggttt
5161 cttcatcaaa gaaataccct tcacggtcaa acgcggtaag ctgttccggc ttcgttaagc
5221 ggttttcaat aataaaacgg ctcatcagtc cgcgcgcttt tttggcgtag aagcttacca
5281 ccttaaactt gccgtttttc tcatcaagga acacgggctt aatcagttcg gcattcagtt
5341 tcttcggctt caccgattta aaatattcct cggaggccag attcaccacc acccgatcgc
5401 cctgcgcctc aagcgcttcg ttgagcttat cggtaatgat atcgccccag aattgataaa
5461 gatctttgcc gcgcggattc tccaggcgaa tccccatctc cagacgataa ggctgcatta
5521 aatccagcgg gcgcaatacg ccatacaagc cagagagcat acgcagatgt tgttgagcaa
5581 aatcaaaatc cgcgtcgttg aacgtttccg cctgtaggcc ggtataaaca tcgcctttga
5641 acgccagaat cgcctggcgt gcattatccg gcgtaaaatg aggctgccag tcatgaaaac
5701 gcgtggcgtt gagatccgcc agtttgtcgc taattcccat cagcctggaa atttgcggcg
5761 ccgaaagctg gcgggcctgt tgaataagct gctggctgtg atccaacagc tccggctggg
5821 tatagcgggt cgtggccagc gggctttgat aatcaagcgt ttttgcaggt gaaatcagaa
5881 tcagcatatt cagtccttgc agggaatttt ctgcgacttt agcaaaaaaa cgccgcagag
5941 ttgaccgatg gttgcgattg tcggcttaat cgcgcgatgc cgcctcccag gtatctggcg
6001 ccagttgtgg ttcgatatcc gggaagcgcc gcggatcgaa ctgcggtctt acgcccagtt
6061 tccgttgtcg cagataatcg ctggcgaggg tatacaccac cggtgagagc aacaaaatcg
6121 ccgtcagatt ggtaatggcc atacaggcca tgatcatgtc agcgagctgc catatcagcg
6181 gaaaactgat aagcgtaccg gcgataacca tgccaagcgt cgcaaggcgt aatagccaga
6241 tagcctttgc gttatgtaac cgcagaaaaa acagattgtt ttcggcgtaa atatagttgg
6301 cgacgataga actgaacgcg aacagaatga cgataagcgc gacaaaactg gcgccccatt
6361 caccggtcaa cgaaaccatt gcatgttgga gaagctgaat gccttctgtt gacgagtggg
6421 acgcgtgatt ccccgccagc aggataatca tcgcgctggc ggtacagatg ataatggtgt
6481 cgctgaatac gccaatcatt tgcacaatcc cctgcgcgac agggtgaggg ggatacgacg
6541 ttgccgctgc ggccgcatta ggcgttgacc ccattcccgc ttcattagag aacatcccac
6601 gctgaaaacc gctggtaata gcctgggtga gcgtatatcc ggctgcgcct gccgcggctt
6661 cctgccagcc aaatgcgctt ttgactatcg aggcgataac gccaggcatt tgctcaatat
6721 gccagaggca aatgaatacg ctgccggcga cccacaataa cgcgatgagg ggaatcagcc
6781 attgcatcag acgggcgacg cctttgatgc cgcgaatgat aattaacagg gcacagaacg
6841 ccagagcaat gccggagata agcggcggaa tgttgaaggc gaaatggagc gcgcgtgaga
6901 cggcattcgc ctgcacgcta ttaaaaatca acccgtaggc gacgagcaga aagagggcga
6961 aaaccacgcc catccagcgc attcccagcc cacgcgccat ataccacgcc gggccgccgc
7021 ggaactggcc tgtcgggtca cgttctttat aaagctgggc aagcgaacac tcggcgaagg
7081 aggtcgccat gccaatgatg gccgagaccc acatccagaa taccgcgccg ggaccgcctg
7141 cggcgatagc cagcgccacg ccggccaggt taccgctgcc aatccgcgcc gcgaggctgg
7201 tacacagagc ctgaaatgac gtcaggccgc ctggctgcgg gctaaggctg cctttcagac
7261 tgcggctaaa ttggcgaata taacgaaact gaatgaatcc ggtacgccag gtaaaccaac
7321 atcctgcgcc gagcagcagg taaatcatta ccgagcccca gagtatttcg ttaataaaac
7381 tgaaaaactc aggcattaac gtccctcttg ttgatgccgg cacgctttga taatcctgta
7441 taagcgtgac ccatgatgta gatgaccttg tcagactaat attaacggca gtttaccata
7501 aatacggtgg tatcctttaa ttgcgcatca accgtcggca gatacgcaaa cagtgcacaa
7561 gggcagccag gtgcatgtag gcggttgcgc tgtgagtgcg tcgtgttatc atcagggtag
7621 accggttaca tcccctaaca agctgtttaa agagaaactc tatcatgacg gacaaattga
7681 cctcccttcg tcagttcacc accgtagtgg ctgataccgg agatatcgcg gcaatgaaac
7741 tgtatcagcc gcaggatgct acaactaacc cttctctcat tcttaacgca gcgcaaatcc
7801 cggaatatcg taagctgatt gacgatgctg tcgcctgggc gaaacagcag agcagcgacc
7861 gcgcgcagca ggttgttgac gcgaccgata agctggcggt gaatattggc ctggagatcc
7921 tgaagctggt gccggggcgt atttctaccg aagttgacgc gcgtctgtct tatgacactg
7981 aagcgtctat cgccaaagca aaacgtatca ttaaactcta caatgatgcg ggtatcagca
8041 acgatcgtat cctgatcaag ctggcgtcca cctggcaggg cattcgtgca gccgaacagc
8101 tggaaaaaga aggcatcaac tgtaacctga cgctgctgtt ctccttcgcg caggcgcgtg
8161 cgtgcgccga agcgggcgtc tacctgatct cgccgttcgt aggtcgtatt cttgactggt
8221 ataaagccaa taccgacaag aaagactatg cgccagctga agatccgggc gtggtttccg
8281 taacggaaat ctacgagtac tacaaacagc atggttacga aaccgtcgtt atgggcgcaa
8341 gcttccgtaa cgtaggcgaa attctggagc tggcgggctg cgaccgtctg actatcgcgc
8401 cggcattgct gaaagaactg gcggaaagcg aaggggcgat tgagcgtaag ctctctttct
8461 ccggcgaagt caaagcgcgc ccggaacgca ttaccgaagc cgagttcctg tggcagcatc
8521 accaggaccc catggcggtt gacaaactgg cggatggtat ccgtaagttt gcggtagacc
8581 aggaaaaact ggaaaaaatg atcggcgatc tgctgtaatc attaacgcgt ggccctgata
8641 tgggtcacgc tacctcttct gaaacctgtc tgtccttccc ttcgcagtgt atcattctgt
8701 ttaacgagac tgtttaaacg gaataatcat ggatacctta cgtattggct tagtttctat
8761 ctccgaccgc gcttcaagcg gcgtttacca ggataaaggc attcctgcgc ttgaggagtg
8821 gctcgcttct gcgctgacca cgcctttcga ggtccaacgg cgcttaattc ctgatgaaca
8881 ggaaattatc gagcaaacgt tgtgtgaact ggtcgatgag atgagctgtc atctggtgct
8941 gaccactggc ggtaccggtc cggcgcgtcg cgacgtcacg ccggacgcga cccttgccat
9001 cgccgaccgt gaaatgccag gttttggcga gcagatgcgc cagatcagcc tgcgctttgt
9061 gccgaccgcc attctttccc gccaggtggg cgttatccgt aaacaggcgt taattcttaa
9121 tctgcctgga cagccaaaat cgatcaaaga aacgctggaa ggcgtaaaag cggacgatgg
9181 cagcgttagc gtgccgggca tttttgcgag cgtgccgtat tgcatacagc tgcttgacgg
9241 gccgtatgtc gaaaccgcgc cggaagtggt tgccgctttc cgtccaaaga gcgccagacg
9301 tgagaatatg tcggactgac cggaaaatac tgatagtagg gttattcctc ccggtgcggg
9361 aggaataaaa gagatttagt gcgcctcgcc gattggcaga atagtgcggc caaattgctc
9421 gtttagcact tcacccatcg ccagataaat agcgctggcg ccgcaaacca gaccaaccca
9481 gcctgcgata tggatagttg cttcgttacc ggtgatattg ccgaccgcca gcagagcgaa
9541 cagtacggtc aggctcagga aaacaaattg cagcgcgcgg gcggctttca gcgtaccgaa
9601 gaacataaac agcgtgaaca cgccccacag acctaaataa gcgccgagta gctgagcgtc
9661 aggcgcatcc gtcagaccca ttttcggcat cagcaggata gcgaccagcg tcagccagaa
9721 cgaaccgtaa gaggtaaagg ccgttaaacc aaaggtattg ccttttttgt actccagcag
9781 accggcaaaa atttgcgcga taccgccgta gaaaatcccc atcgccagaa taataccgtc
9841 cagggcgaaa aaaccggcat tgtgcaggtt aagcagaatg gtggtcatgc cgaagcccat
9901 caggcccagc ggtgccggat tagccaactt agtgttgccc ataattcctc aaaatcatca
9961 taattgaatg gtgaaatagt ttcccagaat aacgagttcc gtattcgggg cgcggcataa
//
PyCogent-1.5.3/doc/data/test.paml 000644 000765 000024 00000000540 10665667404 017565 0 ustar 00jrideout staff 000000 000000 5 60
NineBande
gcaaggcgccaacagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
Mouse
gcagtgagccagcagagcagatgggctgcaagtaaaggaacatgtaacgacaggcaggtt
Human
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
HowlerMon
gcaaggagccaacataacagatgggctgaaagtgaggaaacatgtaatgataggcagact
DogFaced
gcaaggagccagcagaacagatgggttgaaactaaggaaacatgtaatgataggcagact
PyCogent-1.5.3/doc/data/test.tree 000644 000765 000024 00000000235 11213030412 017541 0 ustar 00jrideout staff 000000 000000 (((Human:0.0311054096183,HowlerMon:0.0415847131449):0.0382963424874,Mouse:0.277353608988):0.0197278502379,NineBande:0.0939768158209,DogFaced:0.113211053859); PyCogent-1.5.3/doc/data/test2.fasta 000644 000765 000024 00000000531 10665667404 020014 0 ustar 00jrideout staff 000000 000000 >NineBande
cgccaacagagcagatgggctgaaagtaaggaaacatgtaatgataggcagact
>Mouse
gcagtgagccagcagagcagatgggctgcaagtaaaggaacatgtaacgacaggcaggtt
>HowlerMon
gcaaggagccaacataacagatgggctgaaagtgaggaaacatgtaatgataggcagact
>Human
gcaaggagccaacataacagatgggctggaagtaaggaaacatgtaatgataggcggact
>DogFaced
gcaaggagccagcagaacagatgggttgaaactaaggaaacatgtaatgataggcagact
PyCogent-1.5.3/doc/data/trna_profile.fasta 000644 000765 000024 00000004253 11075742320 021427 0 ustar 00jrideout staff 000000 000000 >seq_50_Halobacterium_sp.
GCCGCCUUAGCUCAGACUGGGAGAGCACUCGACUGAAGAUCGAGCUGUCCCUGGUUCAAAUCCGGGAGGCGGC-CCA
>seq_23_Haemophilus_influenzae
GCCUCGAUAGCUCAGUC-GGUAGAGCAGGGGAUUGAAAAUCCCCGUGUCGGUGGUUCGAUUCCGCCUCGAGGCACCA
>seq_46_Salmonella_enterica
GCCCGGAUAGCUCAGUC-GGUAGAGCAGGGGAUUGAAAAUCCCCGUGUCCUUGGUUCGAUUCCGAGUCCGGGCACCA
>seq_135_Yersinia_pestis_biovar_Medievalis
GCCCGGAUAGCUCAGU-CGGUAGAGCAGGGGAUUGAAAAUCCCCGUGUCCUUGGUUCGAUUCCGAGUCCGGGCACCA
>seq_148_Bartonella_quintana
GCCCAGAUAGCUCAGUU-GGUAGAGCAGCGGACUGAAAAUCCGCGUGUCCGUGGUUCGAAUCCGCGUCUGGGCACCA
>seq_117_Pseudomonas_syringae_pv._Tomato
GCCCAGAUAGCUCAGU-CGGUAGAGCAGGGGAUUGAAAAUCCCCGUGUCGGCGGUUCGAUUCCGUCUCUGGGCACCA
>seq_31_Pseudomonas_aeruginosa
GCCCAGGUAGCUCAGUU-GGUAGAGCAGGGGAUUGAAAAUCCCCGUGUCGGCGGUUCGAUUCCGUCCCUGGGCACCA
>seq_95_Shewanella_oneidensis
GCCCGAAUAGCUCAGUC-GGUAGAGCAGAGGAUUGAAAAUCCUCGUGUCCCUGGUUCGAUUCCGGGUUCGGGCACCA
>seq_119_Bacillus_anthracis
GGCUCGGUAGCUCAGU-CGGUAGAGCAGAGGACUGAAAAUCCUCGUGUCGGCGGUUCGAUUCCGUCCCGAGCCACCA
>seq_86_Xanthomonas_axonopodis_pv._citri.
GGCCGAGUAGCUCAGUU-GGUAGAGCAGGGGAUUGAAAAUCCCCGUGUCGGCGGUUCGAUUCCGUCCUCGGCCACCA
>seq_146_Bacillus_thuringiensis_serovar_konkukian
GGCUCGGUAGCUCAGUC-GGUAGAGCAGAGGACUGAAAAUCCUCGUGUCGGCGGUUCGAUUCCGUCCCGAGCCACCA
>seq_24_Campylobacter_jejuni
GGUUGGAUAGCUCAGUC-GGUAGAGCAGCAGACUGAAAAUCUGCGUGUCGGCAGUUCGAUUCUGCCUCUAACCACCA
>seq_138_Bacillus_cereus
GGCUCGGUAGCUCAGU-CGGUAGAGCAGAGGACUGAAAAUCCUCGUGUCGGCGGUUCGAUUCCGUCCCGAGCCACCA
>seq_104_Tropheryma_whipplei
GGCUCUGUAGCUCAGU-UGGUAGAGCGUUCGACUGAAAAUCGAAAGGUCACCGGAUCGAUACCGGUCGGAGCCACAA
>seq_59_Thermoplasma_acidophilum
GCCGUGGUAGCUCAGUU-GGGAGAGCGCCAGACUGAAGAUCUGGAGGUCGCUGGUUCGAUCCCGGCCCACGGC-CCA
>seq_129_Bacillus_anthracis
GGCUCGGUAGCUCAGU-CGGUAGAGCAGAGGACUGAAAAUCCUCGUGUCGGCGGUUCGAUUCCGUCCCGAGCCACUC
>seq_130_Geobacter_sulfurreducens
GCCCAGAUAGCUCAGC-UGGUAGAGCAGAGGACUGAAAAUCCUCGUGUCGGCGGUUCGAUUCCGUCUCUGGGCACCA
>seq_48_Aeropyrum_pernix
GCCGCCGUAGCUCAGC--GGGAGAGCGCCCGGCUGAAGACCGGGUGGUCCGGGGUUCGAAUCCCCGCGGCGGCACCA
>seq_105_Xylella_fastidiosa
GGCCGGGUAGCUCAGU-CGGUAGAGCAGGGGACUGAAAAUCCCCGUGUCGGGGGUUCGAUUCCCUCCCCGGCCACCA
>seq_70_Saccharomyces_cerevisiae_(baker's_yeast)
GCGGAUUUAGCUCAGUU-GGGAGAGCGCCAGACUGAAGAUCUGGAGGUCCUGUGUUCGAUCCACAGAAUUCGCACCA
PyCogent-1.5.3/doc/cookbook/accessing_databases.rst 000644 000765 000024 00000042505 11751654700 023327 0 ustar 00jrideout staff 000000 000000 *******************
Accessing databases
*******************
.. Gavin Huttley, Kristian Rother, Patrick Yannul, Rob Knight, Yarden Katz
NCBI
====
EUtils is a web service offered by the NCBI to access the sequence, literature and other databases by a special format of URLs. PyCogent offers an interface to construct the URLs and retrieve the results in text format.
From Pubmed
-----------
Retrieving PubMed records from NCBI by PubMed ID
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The process for getting PubMed records by PubMed ID (PMID) is very similar to that for getting sequences. Basically, you just need to pass in the unique id associated with the article. For example, if you want to get the reference to the original PyCogent paper to see how far we've come since then, you can do this:
.. doctest::
>>> from cogent.db.ncbi import EFetch
>>> ef = EFetch(id='17708774', db='pubmed', rettype='brief')
>>> ef.read()
'\n1: Knight R et al. PyCogent: a toolkit for makin...[PMID: 17708774] \n'
If you want more information, there are other rettypes, e.g.
.. doctest::
>>> ef = EFetch(id='17708774', db='pubmed', rettype='citation')
>>> ef.read()
"\n1: Genome Biol. 2007;8(8):R171. \n\nPyCogent: a toolkit for making sense from sequence.\n\nKnight R, Maxwell P, Birmingham A, Carnes J, Caporaso JG, Easton BC, Eaton M,\nHamady M, Lindsay H, Liu Z, Lozupone C, McDonald D, Robeson M, Sammut R, Smit S,\nWakefield MJ, Widmann J, Wikman S, Wilson S, Ying H, Huttley GA.\n\nDepartment of Chemistry and Biochemistry, University of Colorado, Boulder,\nColorado, USA. rob@spot.colorado.edu\n\nWe have implemented in Python the COmparative GENomic Toolkit, a fully\nintegrated and thoroughly tested framework for novel probabilistic analyses of\nbiological sequences, devising workflows, and generating publication quality\ngraphics. PyCogent includes connectors to remote databases, built-in generalized\nprobabilistic techniques for working with biological sequences, and controllers\nfor third-party applications. The toolkit takes advantage of parallel\narchitectures and runs on a range of hardware and operating systems, and is\navailable under the general public license from\nhttp://sourceforge.net/projects/pycogent.\n\nPublication Types:\n Evaluation Studies\n Research Support, N.I.H., Extramural\n Research Support, Non-U.S. Gov't\n\nMeSH Terms:\n Animals\n BRCA1 Protein/genetics\n Databases, Genetic\n Genomics/methods*\n Humans\n Phylogeny\n Protein Conformation\n Proteobacteria/classification\n Proteobacteria/genetics\n Sequence Analysis/methods*\n Software*\n von Willebrand Factor/chemistry\n von Willebrand Factor/genetics\n\nSubstances:\n BRCA1 Protein\n von Willebrand Factor\n\nPMID: 17708774 [PubMed - indexed for MEDLINE]\n"
Similarly, if you want something more machine-readable (but quite a lot less human-readable), you can specify XML in the retmode:
.. doctest::
>>> ef = EFetch(id='17708774', db='pubmed', rettype='citation', retmode='xml')
>>> cite = ef.read()
>>> for line in cite.splitlines()[:5]:
... print line
...
Only a partial example is shown as there are quite a few lines. As with sequences, you can retrieve multiple accessions at once.
Searching for records using EUtils
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Getting records by their primary identifiers is very nice if you actually have the primary identifiers, but what if you don't? For example, what if you want to do a search based on a keyword, or have a genbank accession number rather than a gi, or want to get a range of records?
Fortunately, the more general EUtils class allows this kind of complex workflow with relatively little intervention. For example, if you want to search for articles that mention PyCogent:
.. doctest::
>>> from cogent.db.ncbi import EUtils
>>> eu = EUtils(db='pubmed', rettype='brief')
>>> res = eu['PyCogent']
>>> print res.read()
1: Smit S et al. From knotted to nested RNA st...[PMID: 18230758]
2: Knight R et al. PyCogent: a toolkit for makin...[PMID: 17708774]