pax_global_header00006660000000000000000000000064134576555460014536gustar00rootroot0000000000000052 comment=6e065d18a8090c81c0f89bbdec410cfffff6cef4 pairtools-0.3.0/000077500000000000000000000000001345765554600135525ustar00rootroot00000000000000pairtools-0.3.0/.gitignore000066400000000000000000000021141345765554600155400ustar00rootroot00000000000000# vim undos *.un~ # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] *$py.class # C extensions *.so # Distribution / packaging .Python env/ build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib/ lib64/ parts/ sdist/ var/ *.egg-info/ .installed.cfg *.egg # PyInstaller # Usually these files are written by a python script from a template # before PyInstaller builds the exe, so as to inject date/other infos into it. *.manifest *.spec # Installer logs pip-log.txt pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *,cover .hypothesis/ # Translations *.mo *.pot # Django stuff: *.log local_settings.py # Flask stuff: instance/ .webassets-cache # Scrapy stuff: .scrapy # Sphinx documentation docs/_build/ # PyBuilder target/ # IPython Notebook .ipynb_checkpoints # pyenv .python-version # celery beat schedule file celerybeat-schedule # dotenv .env # virtualenv venv/ ENV/ # Spyder project settings .spyderproject # Rope project settings .ropeproject # cython compiled C extension _*.c pairtools-0.3.0/.travis.yml000066400000000000000000000020731345765554600156650ustar00rootroot00000000000000language: python python: # We don't actually use the Travis Python, but this keeps it organized. - "3.4" - "3.5" - "3.6" install: # We do this conditionally because it saves us some downloading if the version is the same. - wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh; - bash miniconda.sh -b -p $HOME/miniconda - export PATH="$HOME/miniconda/bin:$PATH" - hash -r - conda config --set always_yes yes --set changeps1 no - conda config --add channels conda-forge - conda config --add channels defaults - conda config --add channels bioconda - conda config --get #- conda update -q conda # Useful for debugging any issues with conda - conda info -a # Create test environment and install deps - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION setuptools pip cython numpy nose pbgzip - source activate test-environment - pip install click - python setup.py build_ext -i script: nosetests pairtools-0.3.0/CHANGES.md000066400000000000000000000007171345765554600151510ustar00rootroot00000000000000### 0.3.0 (2019-04-23) ### * parse: tag pairs with missing FASTQ/SAM on one side as corrupt, pair type "XX" ### 0.2.2 (2019-01-07) ### * sort: enable lz4c compression of sorted chunks by default ### 0.2.1 (2018-12-21) ### * automatically convert mapq1 and mapq2 to int in `select` ### 0.2.0 (2018-09-03) ### * add the `flip` tool ### 0.1.1 (2018-07-19) ### * Bugfix: include _dedup.pyx in the Python package ### 0.1.0 (2018-07-19) ### * First release. pairtools-0.3.0/LICENSE000066400000000000000000000020511345765554600145550ustar00rootroot00000000000000MIT License Copyright (c) 2017 mirnylab Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. pairtools-0.3.0/MANIFEST.in000066400000000000000000000005641345765554600153150ustar00rootroot00000000000000include CHANGES.md include README.md include requirements.txt include requirements_doc.txt include LICENSE graft tests graft doc prune doc/_build prune doc/_templates global-include *.pyx global-include *.pxd global-exclude __pycache__/* global-exclude *.so global-exclude *.pyd global-exclude *.pyc global-exclude .git* global-exclude .deps/* global-exclude .DS_Store pairtools-0.3.0/Makefile000066400000000000000000000012661345765554600152170ustar00rootroot00000000000000.PHONY: init install clean-pyc clean-build build test publish docs-init docs init: conda install --file requirements.txt install: pip install -e . test: nosetests clean-pyc: find . -name '*.pyc' -exec rm --force {} + find . -name '*.pyo' -exec rm --force {} + find . -name '*~' -exec rm --force {} + clean-build: rm -rf build/ rm -rf dist/ clean: clean-pyc clean-build build: clean-build python setup.py sdist # python setup.py bdist_wheel publish: build twine upload dist/* publish-test: twine upload --repository-url https://test.pypi.org/legacy/ dist/* #docs-init: # conda install --file docs/requirements.txt # #docs: # cd docs && python make_cli_rst.py && make html pairtools-0.3.0/README.md000066400000000000000000000154421345765554600150370ustar00rootroot00000000000000# pairtools [![Documentation Status](https://readthedocs.org/projects/pairtools/badge/?version=latest)](http://pairtools.readthedocs.org/en/latest/) [![Build Status](https://travis-ci.org/mirnylab/pairtools.svg?branch=master)](https://travis-ci.org/mirnylab/pairtools) [![Join the chat at https://gitter.im/mirnylab/distiller](https://badges.gitter.im/mirnylab/distiller.svg)](https://gitter.im/mirnylab/distiller?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1490831.svg)](https://doi.org/10.5281/zenodo.1490831) ## Process Hi-C pairs with pairtools `pairtools` is a simple and fast command-line framework to process sequencing data from a Hi-C experiment. `pairtools` process pair-end sequence alignments and perform the following operations: - detect ligation junctions (a.k.a. Hi-C pairs) in aligned paired-end sequences of Hi-C DNA molecules - sort .pairs files for downstream analyses - detect, tag and remove PCR/optical duplicates - generate extensive statistics of Hi-C datasets - select Hi-C pairs given flexibly defined criteria - restore .sam alignments from Hi-C pairs To get started: - Take a look at a [quick example](https://github.com/mirnylab/pairtools#quick-example) - Check out the detailed [documentation](http://pairtools.readthedocs.io). ## Data formats `pairtools` produce and operate on tab-separated files compliant with the [.pairs](https://github.com/4dn-dcic/pairix/blob/master/pairs_format_specification.md) format defined by the [4D Nucleome Consortium](https://www.4dnucleome.org/). All pairtools properly manage file headers and keep track of the data processing history. Additionally, `pairtools` define the .pairsam format, an extension of .pairs that includes the SAM alignments of a sequenced Hi-C molecule. .pairsam complies with the .pairs format, and can be processed by any tool that operates on .pairs files. ## Installation Requirements: - Python 3.x - Python packages `cython`, `numpy` and `click`. - Command-line utilities `sort` (the Unix version), `bgzip` (shipped with `tabix`) and `samtools`. If available, `pairtools` can compress outputs with `pbgzip` and `lz4`. We highly recommend using the `conda` package manager to install `pairtools` together with all its dependencies. To get it, you can either install the full [Anaconda](https://www.continuum.io/downloads) Python distribution or just the standalone [conda](http://conda.pydata.org/miniconda.html) package manager. With `conda`, you can install `pairtools` and all of its dependencies from the [bioconda](https://bioconda.github.io/index.html) channel. ```sh $ conda install -c conda-forge -c bioconda pairtools ``` Alternatively, install `pairtools` and only Python dependencies from PyPI using pip: ```sh $ pip install pairtools ``` ## Quick example Setup a new test folder and download a small Hi-C dataset mapped to sacCer3 genome: ```bash $ mkdir /tmp/test-pairtools $ cd /tmp/test-pairtools $ wget https://github.com/mirnylab/distiller-test-data/raw/master/bam/MATalpha_R1.bam ``` Additionally, we will need a .chromsizes file, a TAB-separated plain text table describing the names, sizes and the order of chromosomes in the genome assembly used during mapping: ```bash $ wget https://raw.githubusercontent.com/mirnylab/distiller-test-data/master/genome/sacCer3.reduced.chrom.sizes ``` With `pairtools parse`, we can convert paired-end sequence alignments stored in .sam/.bam format into .pairs, a TAB-separated table of Hi-C ligation junctions: ```bash $ pairtools parse -c sacCer3.reduced.chrom.sizes -o MATalpha_R1.pairs.gz --drop-sam MATalpha_R1.bam ``` Inspect the resulting table: ```bash $ less MATalpha_R1.pairs.gz ``` ## Pipelines - We provide a simple working example of a mapping bash pipeline in /examples/. - [distiller](https://github.com/mirnylab/distiller-nf) is a powerful Hi-C data analysis workflow, based on `pairtools` and [nextflow](https://www.nextflow.io/). ## Tools - `parse`: read .sam files produced by bwa and form Hi-C pairs - form Hi-C pairs by reporting the outer-most mapped positions and the strand on the either side of each molecule; - report unmapped/multimapped (ambiguous alignments)/chimeric alignments as chromosome "!", position 0, strand "-"; - identify and rescue chrimeric alignments produced by singly-ligated Hi-C molecules with a sequenced ligation junction on one of the sides; - perform upper-triangular flipping of the sides of Hi-C molecules such that the first side has a lower sorting index than the second side; - form hybrid pairsam output, where each line contains all available data for one Hi-C molecule (outer-most mapped positions on the either side, read ID, pair type, and .sam entries for each alignment); - print the .sam header as #-comment lines at the start of the file. - `sort`: sort pairs files (the lexicographic order for chromosomes, the numeric order for the positions, the lexicographic order for pair types). - `merge`: merge sorted .pairs files - merge sort .pairs; - combine the .pairs headers from all input files; - check that each .pairs file was mapped to the same reference genome index (by checking the identity of the @SQ sam header lines). - `select`: select pairs according to specified criteria - select pairs entries according to the provided condition. A programmable interface allows for arbitrarily complex queries on specific pair types, chromosomes, positions, strands, read IDs (including matches to a wildcard/regexp/list). - optionally print the non-matching entries into a separate file. - `dedup`: remove PCR duplicates from a sorted triu-flipped .pairs file - remove PCR duplicates by finding pairs of entries with both sides mapped to similar genomic locations (+/- N bp); - optionally output the PCR duplicate entries into a separate file. - NOTE: in order to remove all PCR duplicates, the input must contain \*all\* mapped read pairs from a single experimental replicate; - `maskasdup`: mark all pairs in a pairsam as Hi-C duplicates - change the field pair_type to DD; - change the pair_type tag (Yt:Z:) for all sam alignments; - set the PCR duplicate binary flag for all sam alignments (0x400). - `split`: split a .pairsam file into .pairs and .sam. - `stats`: calculate various statistics of .pairs files - `restrict`: identify the span of the restriction fragment forming a Hi-C junction ## Contributing [Pull requests](https://akrabat.com/the-beginners-guide-to-contributing-to-a-github-project/) are welcome. For development, clone and install in "editable" (i.e. development) mode with the `-e` option. This way you can also pull changes on the fly. ```sh $ git clone https://github.com/mirnylab/pairtools.git $ cd pairtools $ pip install -e . ``` ## License MIT pairtools-0.3.0/doc/000077500000000000000000000000001345765554600143175ustar00rootroot00000000000000pairtools-0.3.0/doc/Makefile000066400000000000000000000176141345765554600157700ustar00rootroot00000000000000# Makefile for Sphinx documentation # # You can set these variables from the command line. SPHINXOPTS = SPHINXBUILD = sphinx-build PAPER = BUILDDIR = _build # User-friendly check for sphinx-build ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1) $(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. 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Reads can have multiplealignments on either side When reads have multiple alignments at either side, we need a rule to select the one to report By default, we report the 5'-most unique alignment at each side Chimeric rescue --max-inter-align-gap ! ! Some reads with three alignments mayin fact represent Hi-C molecules formedthrough a single ligation event UU ! NU ? MU ! MM ! ! NM ! ! ! WW ! ! WW ! NN ? ? ! ? ? ! ! WW UU UR ? 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Mk2M͢MOQ=>(r؏̞R,.~pgBsry[ޓpaze%&BYc~-Xc3Omwbt %hd?aiD2Z2B(3#=F6E6:-_ [AH_1-Խ%QqUm1tAf휲Qa+882CJxo#WB2ul-7t1g8[O<߉3xW ElFc`cM|mNWVGVL|oz˻MD lƛmSN۳%'QZ|11gy;`Y*~NxϘ+Dc\o0ˆ=z4+epb )¼Wؙ0T\!X,6Vң V"WCv{ ΀r7Y^7O"FpAQ@nl/Q?LJW+m$zT#lXüA5B.[oavBSo/g8dLK0ǍZ`c~ 0qE \+GB ޶K;Oǐܓ3}OڣIeb^aU;ac00W R$?-z!&i]gLC <'@Sm{$1;7Vo'baBe7QlKH22g H]n̟܋b 懊,551%=v7`' `}V`63Bʣm L  ?'isV\=baOcP=l&g0cY~N}(BdǼNӰ~o {wos<?>1yq=3x_cֿ Iy 3{kG܏1C+l~mC[u'0Z@0 4*N.oq_E#qۤ )Ag!DnW,x/opSiXLX9xS-n`nr}9ɈF\n3b(lh&]Shc.w 3t9޶>X=1q#{Un]g>#XƥC0f4Fk.{?oҴ˗ʼ@dSX)!D/#R9߈*rO܊Kij9m1gBtYUM02k>vI<"ƅ8mą%*Q&-#Zy|iMVXXXY`p%9 `1!Jx3I5>Xa\q .5C \3K|Ƽ]1v&P i.1-R5L`#VB@/K0#az ֝]nG}v<`c,{BjoK1Ö8ļ3bI0-\[ _~6`ϝ@Yփ3t-|l96u/Q}ayKM1¢VcFH$e_biR 鈭1~r{Hx#&B0Xyc =OQ!$L65=3]^Y BѴ J}Nƅaf=~ˏ͗P'ǩ_.ljXn+l_,'r v documentation" by default. #html_title = 'pairtools v0.0.1' # 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 (relative to this directory) to use as a 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'] # Add any extra paths that contain custom files (such as robots.txt or # .htaccess) here, relative to this directory. These files are copied # directly to the root of the documentation. #html_extra_path = [] # If not None, a 'Last updated on:' timestamp is inserted at every page # bottom, using the given strftime format. # The empty string is equivalent to '%b %d, %Y'. #html_last_updated_fmt = None # 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_domain_indices = 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, "Created using Sphinx" is shown in the HTML footer. Default is True. #html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. #html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = None # Language to be used for generating the HTML full-text search index. # Sphinx supports the following languages: # 'da', 'de', 'en', 'es', 'fi', 'fr', 'h', 'it', 'ja' # 'nl', 'no', 'pt', 'ro', 'r', 'sv', 'tr', 'zh' #html_search_language = 'en' # A dictionary with options for the search language support, empty by default. # 'ja' uses this config value. # 'zh' user can custom change `jieba` dictionary path. #html_search_options = {'type': 'default'} # The name of a javascript file (relative to the configuration directory) that # implements a search results scorer. If empty, the default will be used. #html_search_scorer = 'scorer.js' # Output file base name for HTML help builder. htmlhelp_basename = 'pairtoolsdoc' # -- Options for LaTeX output --------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', # Latex figure (float) alignment #'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'pairtools.tex', 'pairtools Documentation', 'Mirny Lab', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output --------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'pairtools', 'pairtools Documentation', [author], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'pairtools', 'pairtools Documentation', author, 'pairtools', 'One line description of project.', 'Miscellaneous'), ] # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' # If true, do not generate a @detailmenu in the "Top" node's menu. #texinfo_no_detailmenu = False pairtools-0.3.0/doc/formats.rst000066400000000000000000000212701345765554600165260ustar00rootroot00000000000000Formats for storing Hi-C pairs ============================== .pairs ------ `.pairs` is a simple tabular format for storing DNA contacts detected in a Hi-C experiment. The detailed `.pairs specification `_ is defined by the 4DN Consortium. The body of a .pairs contains a table with a variable number of fields separated by a "\\t" character (a horizontal tab). The .pairs specification fixes the content and the order of the first seven columns: ======== =========== =============================================================================== index name description ======== =========== =============================================================================== 1 read_id the ID of the read as defined in fastq files 2 chrom1 the chromosome of the alignment on side 1 3 pos1 the 1-based genomic position of the outer-most (5') mapped bp on side 1 4 chrom2 the chromosome of the alignment on side 2 5 pos2 the 1-based genomic position of the outer-most (5') mapped bp on side 2 6 strand1 the strand of the alignment on side 1 7 strand2 the strand of the alignment on side 2 ======== =========== =============================================================================== A .pairs file starts with a header, an arbitrary number of lines starting with a "#" character. By convention, the header lines have a format of "#field_name: field_value". The `.pairs specification `_ mandates a few standard header lines (e.g., column names, chromosome order, sorting order, etc), all of which are automatically filled in by `pairtools`. The entries of a .pairs file can be flipped and sorted. "Flipping" means that *the sides 1 and 2 do not correspond to side1 and side2 in sequencing data.* Instead, side1 is defined as the side with the alignment with a lower sorting index (using the lexographic order for chromosome names, followed by the numeric order for positions and the lexicographic order for pair types). This particular order of "flipping" is defined as "upper-triangular flipping", or "triu-flipping". Finally, pairs are *typically* block-sorted: i.e. first lexicographically by chrom1 and chrom2, then numerically by pos1 and pos2. Pairtools' flavor of .pairs --------------------------- .pairs files produced by `pairtools` extend .pairs format in a few ways. 1. `pairtools` store null/ambiguous/chimeric alignments as chrom='!', pos=0, strand='-'. #. `pairtools` store the header of the source .sam files in the '#samheader:' fields of the pairs header. When multiple .pairs files are merged, the respective '#samheader:' fields are checked for consistency and merged. #. Each pairtool applied to .pairs leaves a record in the '#samheader' fields (using a @PG sam tag), thus preserving the full history of data processing. #. `pairtools` append an extra column describing the type of a Hi-C pair: ======== =========== =============================================================================== index name description ======== =========== =============================================================================== 8 pair_type the type of a Hi-C pair ======== =========== =============================================================================== Pair types ---------- `pairtools` use a simple two-character notation to define all possible pair types, according to the quality of alignment of the two sides. The type of a pair can be defined unambiguously using the table below. To use this table, identify which side has an alignment of a "poorer" quality (unmapped < multimapped < unique alignment) and which side has a "better" alignment and find the corresponding row in the table. =============== ========= ================== ========= ================== ======================== ====== =========== . Less informative alignment More informative alignment . . . --------------- ---------------------------- ---------------------------- ------------------------ ------ ----------- >2 alignments Mapped Unique Mapped Unique Pair type Code Sidedness |check| |cross| |cross| |cross| |cross| walk-walk WW 0 [1]_ |cross| |cross| |cross| null NN 0 |cross| |cross| |cross| corrupt XX 0 [2]_ |cross| |cross| |check| |cross| null-multi NM 0 |check| |cross| |check| |check| null-rescued NR 1 [3]_ |cross| |cross| |check| |check| null-unique NU 1 |cross| |check| |cross| |check| |cross| multi-multi MM 0 |check| |check| |cross| |check| |check| multi-rescued MR 1 [3]_ |cross| |check| |cross| |check| |check| multi-unique MU 1 |check| |check| |check| |check| |check| rescued-unique RU 2 [3]_ |check| |check| |check| |check| |check| unique-rescued UR 2 [3]_ |cross| |check| |check| |check| |check| unique-unique UU 2 |cross| |check| |check| |check| |check| duplicate DD 2 [4]_ =============== ========= ================== ========= ================== ======================== ====== =========== .. [1] "walks", or, `C-walks `_ are Hi-C molecules formed via multiple ligation events which cannot be reported as a single pair. .. [2] "corrupt" pairs are those with technical issues - e.g. missing a FASTQ sequence/SAM entry from one side of the molecule. .. [2] "rescued" pairs have two non-overlapping alignments on one of the sides (referred below as the chimeric side/read), but the inner (3'-) one extends the only alignment on the other side (referred as the non-chimeric side/read). Such pairs form when one of the two ligated DNA fragments is shorter than the read length. In this case, one of the reads contains this short fragment entirely, together with the ligation junction and a chunk of the other DNA fragment (thus, this read ends up having two non-overlapping alignments). Following the procedure introduced in `HiC-Pro `_ and `Juicer `_, `pairtools parse` rescues such Hi-C molecules, reports the position of the 5' alignment on the chimeric side, and tags them as "NU", "MU", "UR" or "RU" pair type, depending on the type of the 5' alignment on the chimeric side. Such molecules can and should be used in downstream analysis. Read more on the rescue procedure in :doc:`the section on parsing `. .. [3] `pairtools dedup` detects molecules that could be formed via PCR duplication and tags them as "DD" pair type. These pairs should be excluded from downstream analyses. .pairsam -------- `pairtools` also define .pairsam, a valid extension of the .pairs format. On top of the pairtools' flavor of .pairs, .pairsam format adds two extra columns containing the alignments from which the Hi-C pair was extracted: ======== =========== =============================================================================== index name description ======== =========== =============================================================================== 9 sam1 the sam alignment(s) on side 1; separate supplemental alignments by NEXT_SAM 10 sam2 the sam alignment(s) on side 2; separate supplemental alignments by NEXT_SAM ======== =========== =============================================================================== Note that, normally, the fields of a sam alignment are separated by a horizontal tab character (\\t), which we already use to separate .pairs columns. To avoid confusion, we replace the tab character in sam entries stored in sam1 and sam2 columns with a UNIT SEPARATOR character (\\031). Finally, sam1 and sam2 can store multiple .sam alignments, separated by a string '\\031NEXT_SAM\\031' .. |check| unicode:: U+2714 .. check .. |cross| unicode:: U+274C .. cross pairtools-0.3.0/doc/index.rst000066400000000000000000000046241345765554600161660ustar00rootroot00000000000000.. pairtools documentation master file, created by sphinx-quickstart on Wed Dec 6 12:32:49 2017. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Overview ======== `pairtools` is a simple and fast command-line framework to process sequencing data from a Hi-C experiment. `pairtools` perform various operations on Hi-C pairs and occupy the middle position in a typical Hi-C data processing pipeline: .. figure:: _static/hic-processing-pipeline.png :width: 100% :alt: The diagram of a typical processing pipeline for Hi-C data :align: center In a typical Hi-C pipeline, DNA sequences (reads) are aligned to the reference genome, converted into ligation junctions and binned, thus producing a Hi-C contact map. `pairtools` aim to be an all-in-one tool for processing Hi-C pairs, and can perform following operations: - detect ligation junctions (a.k.a. Hi-C pairs) in aligned paired-end sequences of Hi-C DNA molecules - sort .pairs files for downstream analyses - detect, tag and remove PCR/optical duplicates - generate extensive statistics of Hi-C datasets - select Hi-C pairs given flexibly defined criteria - restore .sam alignments from Hi-C pairs `pairtools` produce .pairs files compliant with the `4DN standard `_. The full list of available pairtools: ============ ============================================== Pairtool Description ============ ============================================== dedup Find and remove PCR/optical duplicates. filterbycov Remove pairs from regions of high coverage. flip Flip pairs to get an upper-triangular matrix. markasdup Tag pairs as duplicates. merge Merge sorted .pairs/.pairsam files. parse Find ligation junctions in .sam, make .pairs. phase Phase pairs mapped to a diploid genome. restrict Assign restriction fragments to pairs. select Select pairs according to some condition. sort Sort a .pairs/.pairsam file. split Split a .pairsam file into .pairs and .sam. stats Calculate pairs statistics. ============ ============================================== Contents: .. toctree:: :hidden: self .. toctree:: :maxdepth: 3 quickstart installation parsing sorting formats technotes cli_tools * :ref:`genindex` pairtools-0.3.0/doc/installation.rst000066400000000000000000000033451345765554600175570ustar00rootroot00000000000000Installation ============ Requirements ------------ - Python 3.x - Python packages `numpy` and `click` - Command-line utilities `sort` (the Unix version), `bgzip` (shipped with `tabix`) and `samtools`. If available, `pairtools` can compress outputs with `pbgzip` and `lz4`. Install using conda ------------------- We highly recommend using the `conda` package manager to install pre-compiled `pairtools` together with all its dependencies. To get it, you can either install the full `Anaconda `_ Python distribution or just the standalone `conda `_ package manager. With `conda`, you can install pre-compiled `pairtools` and all of its dependencies from the `bioconda `_ channel: .. code-block:: bash $ conda install -c conda-forge -c bioconda pairtools Install using pip ----------------- Alternatively, compile and install `pairtools` and its Python dependencies from PyPI using pip: .. code-block:: bash $ pip install pairtools Install the development version ------------------------------- Finally, you can install the latest development version of `pairtools` from github. First, make a local clone of the github repository: .. code-block:: bash $ git clone https://github.com/mirnylab/pairtools Then, you can compile and install `pairtools` in `the development mode `_, which installs the package without moving it to a system folder and thus allows immediate live-testing any changes in the python code. Please, make sure that you have `cython` installed! .. code-block:: bash $ cd pairtools $ pip install -e ./ pairtools-0.3.0/doc/parsing.rst000066400000000000000000000205711345765554600165210ustar00rootroot00000000000000Parsing sequence alignments into Hi-C pairs =========================================== Overview -------- Hi-C experiments aim to measure the frequencies of contacts between all pairs of loci in the genome. In these experiments, the spacial structure of chromosomes if first fixed with formaldehyde crosslinks, after which DNA is partially digested with restriction enzymes and then re-ligated back. Then, DNA is shredded into smaller pieces, released from nucleus, sequenced and aligned to the reference genome. The resulting sequence alignments reveal if DNA molecules were formed through ligations between DNA from different locations in the genome. These ligation events imply that ligated loci were close to each other when the ligation enzyme was active, i.e. they formed "a contact". ``pairtools parse`` detects ligation events in the aligned sequences of DNA molecules formed in Hi-C experiments and reports them in the .pairs/.pairsam format. Terminology ----------- Throughout this document we will be using the same visual language to describe how DNA sequences (in the .fastq format) are transformed into sequence alignments (.sam/.bam) and into ligation events (.pairs). .. figure:: _static/terminology.png :scale: 50 % :alt: The visual language to describe transformation of Hi-C data :align: center DNA sequences (reads) are aligned to the reference genome and converted into ligation events Short-read sequencing determines the sequences of the both ends (or, **sides**) of DNA molecules (typically 50-300 bp), producing **read pairs** in .fastq format (shown in the first row on the figure above). In such reads, base pairs are reported from the tips inwards, which is also defined as the **5'->3'** direction (in accordance of the 5'->3' direction of the DNA strand that sequence of the corresponding side of the read). Alignment software maps both reads of a pair to the reference genome, producing **alignments**, i.e. segments of the reference genome with matching sequences. Typically, there will be only two alignments per read pair, one on each side. But, sometimes, the parts of one or both sides may map to different locations on the genome, producing more than two alignments per DNA molecule (see :ref:`section-walks`). ``pairtools parse`` converts alignments into **ligation events** (aka **Hi-C pairs** aka **pairs**). In the simplest case, when each side has only one unique alignment (i.e. the whole side maps to a single unique segment of the genome), for each side, we report the chromosome, the genomic position of the outer-most (5') aligned base pair and the strand of the reference genome that the read aligns to. ``pairtools parse`` assigns to such pairs the type ``UU`` (unique-unique). Unmapped/multimapped reads -------------------------- Sometimes, one side or both sides of a read pair may not align to the reference genome: .. figure:: _static/read_pair_NU_NN.png :scale: 50 % :alt: Read pairs missing an alignment on one or both sides :align: center Read pairs missing an alignment on one or both sides In this case, ``pairtools parse`` fills in the chromosome of the corresponding side of Hi-C pair with ``!``, the position with ``0`` and the strand with ``-``. Such pairs are reported as type ``NU`` (null-unique, when the other side has a unique alignment) or ``NN`` (null-null, when both sides lack any alignment). Similarly, when one or both sides map to many genome locations equally well (i.e. have non-unique, or, multi-mapping alignments), ``pairtools parse`` reports the corresponding sides as (chromosome= ``!``, position= ``0``, strand= ``-``) and type ``MU`` (multi-unique) or ``MM`` (multi-multi) or ``NM`` (null-multi), depending on the type of the alignment on the other side. .. figure:: _static/read_pair_MU_MM_NM.png :scale: 50 % :alt: Read pairs with a non-unique alignment on one or both sides :align: center Read pairs with a non-unique (multi-) alignment on one side ``pairtools parse`` calls an alignment to be multi-mapping when its `MAPQ score `_ (which depends on the scoring gap between the two best candidate alignments for a segment) is equal or greater than the value specied with the ``--min-mapq`` flag (by default, 1). .. _section-walks: Multiple ligations (walks) -------------------------- Finally, a read pair may contain more than two alignments: .. figure:: _static/read_pair_WW.png :scale: 50 % :alt: A sequenced Hi-C molecule that was formed via multiple ligations :align: center A sequenced Hi-C molecule that was formed via multiple ligations Molecules like these typically form via multiple ligation events and we call them walks [1]_. Currently, ``pairtools parse`` does not process such molecules and tags them as type ``WW``. .. _section-gaps: Interpreting gaps between alignments ------------------------------------ Reads that are only partially aligned to the genome can be interpreted in two different ways. One possibility is to assume that this molecule was formed via at least two ligations (i.e. it's a *walk*) but the non-aligned part (a **gap**) was missing from the reference genome for one reason or another. Another possibility is to simply ignore this gap (for example, because it could be an insertion or a technical artifact), thus assuming that our molecule was formed via a single ligation and has to be reported: .. figure:: _static/read_pair_gaps_vs_null_alignment.png :scale: 50 % :alt: A gap between alignments can be ignored or interpeted as a "null" alignment :align: center A gap between alignments can interpeted as a legitimate segment without an alignment or simply ignored Both options have their merits, depending on a dataset, quality of the reference genome and sequencing. ``pairtools parse`` ignores shorter *gaps* and keeps longer ones as "null" alignments. The maximal size of ignored *gaps* is set by the ``--max-inter-align-gap`` flag (by default, 20bp). Rescuing single ligations ------------------------- Importantly, some of DNA molecules containing only one ligation junction may still end up with three alignments: .. figure:: _static/read_pair_UR.png :scale: 50 % :alt: Not all read pairs with three alignments come from "walks" :align: center Not all read pairs with three alignments come from "walks" A molecule formed via a single ligation gets three alignments when one of the two ligated DNA pieces is shorter than the read length, such that that read on the corresponding side sequences through the ligation junction and into the other piece [2]_. The amount of such molecules depends on the type of the restriction enzyme, the typical size of DNA molecules in the Hi-C library and the read length, and sometimes can be considerable. ``pairtools parse`` detects such molecules and **rescues** them (i.e. changes their type from a *walk* to a single-ligation molecule). It tests walks with three aligments using three criteria: .. figure:: _static/read_pair_UR_criteria.png :scale: 50 % :alt: The three criteria used for "rescue" :align: center The three criteria used to "rescue" three-alignment walks: cis, point towards each other, short distance 1. On the side with two alignments (the **chimeric** side), the "inner" (or, 3') alignment must be on the same chromosome as the alignment on the non-chimeric side. 2. The "inner" alignment on the chimeric side and the alignment on the non-chimeric side must point toward each other. 3. These two alignments must be within the distance specified with the ``--max-molecule-size`` flag (by default, 2000bp). Sometimes, the "inner" alignment on the chimeric side can be non-unique or "null" (i.e. when the unmapped segment is longer than ``--max-inter-align-gap``, as described in :ref:`section-gaps`). ``pairtools parse`` ignores such alignments altogether and thus rescues such *walks* as well. .. figure:: _static/read_pair_UR_MorN.png :scale: 50 % :alt: A walk with three alignments get rescued, when the middle alignment is multi- or null :align: center A walk with three alignments get rescued, when the middle alignment is multi- or null. .. [1] Following the lead of `C-walks `_ .. [2] This procedure was first introduced in `HiC-Pro `_ and the in `Juicer `_ . pairtools-0.3.0/doc/quickstart.rst000066400000000000000000000024171345765554600172470ustar00rootroot00000000000000Quickstart ========== Install `pairtools` and all of its dependencies using the `conda `_ package manager and the `bioconda `_ channel for bioinformatics software. .. code-block:: bash $ conda install -c conda-forge -c bioconda pairtools Setup a new test folder and download a small Hi-C dataset mapped to sacCer3 genome: .. code-block:: bash $ mkdir /tmp/test-pairtools $ cd /tmp/test-pairtools $ wget https://github.com/mirnylab/distiller-test-data/raw/master/bam/MATalpha_R1.bam Additionally, we will need a .chromsizes file, a TAB-separated plain text table describing the names, sizes and the order of chromosomes in the genome assembly used during mapping: .. code-block:: bash $ wget https://raw.githubusercontent.com/mirnylab/distiller-test-data/master/genome/sacCer3.reduced.chrom.sizes With `pairtools parse`, we can convert paired-end sequence alignments stored in .sam/.bam format into .pairs, a TAB-separated table of Hi-C ligation junctions: .. code-block:: bash $ pairtools parse -c sacCer3.reduced.chrom.sizes -o MATalpha_R1.pairs.gz --drop-sam MATalpha_R1.bam Inspect the resulting table: .. code-block:: bash $ less MATalpha_R1.pairs.gz pairtools-0.3.0/doc/sorting.rst000066400000000000000000000076131345765554600165450ustar00rootroot00000000000000Sorting pairs ============= In order to enable efficient random access to Hi-C pairs, we **flip** and **sort** pairs. After sorting, interactions become arranged in the order of their genomic position, such that, for any given pair of regions, we easily find and extract all of their interactions. And, after flipping, all artificially duplicated molecules (either during PCR or in optical sequencing) end up in adjacent rows in sorted lists of interactions, such that we can easily identify and remove them. Sorting ------- ``pairtools sort`` arrange pairs in the order of (chrom1, chrom2, pos1, pos2). This order is also known as *block sorting*, because all pairs between any given pair of chromosomes become grouped into one continuous block. Additionally, ``pairtools sort`` also sorts pairs with identical positions by `pair_type`. This does not really do much for mapped reads, but it nicely splits unmapped reads into blocks of null-mapped and multi-mapped reads. We note that there is an alternative to block sorting, called *row sorting*, where pairs are sorted by (chrom1, pos1, chrom2, pos2). In `pairtools sort`, we prefer block-sorting since it cleanly separates cis interactions from trans ones and thus is a more optimal solution for typical use cases. Flipping -------- In a typical paired-end experiment, *side1* and *side2* of a DNA molecule are defined by the order in which they got sequenced. Since this order is essentially random, any given Hi-C pair, e.g. (chr1, 1.1Mb; chr2, 2.1Mb), may appear in a reversed orientation, i.e. (chr2, 2.1Mb; chr1, 1.1Mb). If we were to preserve this order of sides, interactions between same loci would appear in two different locations of the sorted pair list, which would complicate finding PCR/optical duplicates. To ensure that Hi-C pairs with similar coordinates end up in the same location of the sorted list, we **flip** pairs, i.e. we choose *side1* as the side with the lowest genomic coordinate. Thus, after flipping, for *trans* pairs (chrom1!=chrom2), order(chrom1)`_ compression by default instead of gzip. Using `bgzip` allows us to create an index with `pairix `_ and get random access to data. - `paritools` have an option to compress outputs with `lz4 `_. `Lz4 is much faster and only slighly less efficient than gzip `_. This makes lz4 a better choice for passing data between individual pairtools before producing final result (which, in turn, requires bgzip compression). pairtools-0.3.0/examples/000077500000000000000000000000001345765554600153705ustar00rootroot00000000000000pairtools-0.3.0/examples/example_pipeline.sh000066400000000000000000000045071345765554600212520ustar00rootroot00000000000000#!/usr/bin/env bash if [ $# -le 3 ] ; then echo "Usage: bash example_pipeline.sh BWA_INDEX FASTQ_1 FASTQ_2 OUTPUT_PREFIX" echo "" echo "A example of a bash pipeline to align the sequencing data from a " echo "single Hi-C experiment." echo "" echo "positional arguments:" echo "" echo "BWA_INDEX The path to a bwa index of the reference genome." echo "CHROM_SIZES The path to a file with chromosome sizes." echo "FASTQ_1 The path to a fastq file with the sequences of " echo " the first side of Hi-C molecules." echo "FASTQ_2 The path to a fastq file with the sequences of " echo " the second side of Hi-C molecules." echo "OUTPUT_PREFIX The prefix to the paths of generated outputs. " echo "" echo "" exit 0 fi set -o errexit set -o nounset set -o pipefail INDEX=$1 CHROM_SIZES=$2 FASTQ1=$3 FASTQ2=$4 OUTPREFIX=$5 N_THREADS=8 UNMAPPED_SAM_PATH=${OUTPREFIX}.unmapped.bam UNMAPPED_PAIRS_PATH=${OUTPREFIX}.unmapped.pairs.gz NODUPS_SAM_PATH=${OUTPREFIX}.nodups.bam NODUPS_PAIRS_PATH=${OUTPREFIX}.nodups.pairs.gz DUPS_SAM_PATH=${OUTPREFIX}.dups.bam DUPS_PAIRS_PATH=${OUTPREFIX}.dups.pairs.gz bwa mem -SP -t "${N_THREADS}" "${INDEX}" "${FASTQ1}" "${FASTQ2}" | { # Classify Hi-C molecules as unmapped/single-sided/multimapped/chimeric/etc # and output one line per read, containing the following, separated by \\v: # * triu-flipped pairs # * read id # * type of a Hi-C molecule # * corresponding sam entries pairtools parse "{CHROM_SIZES}" } | { # Block-sort pairs together with SAM entries pairtools sort } | { # Set unmapped and ambiguous reads aside pairtools select '(pair_type == "UU") or (pair_type == "UR") or (pair_type == "RU")' \ --output-rest >( pairtools split \ --output-pairs ${UNMAPPED_PAIRS_PATH} \ --output-sam ${UNMAPPED_SAM_PATH} ) } | { # Remove duplicates pairtools dedup \ --output \ >( pairtools split \ --output-pairs ${NODUPS_PAIRS_PATH} \ --output-sam ${NODUPS_SAM_PATH} ) \ --output-dups \ >( pairtools markasdup \ | pairtools split \ --output-pairs ${DUPS_PAIRS_PATH} \ --output-sam ${DUPS_SAM_PATH} ) } pairtools-0.3.0/examples/example_singlecell_pipeline.sh000066400000000000000000000055271345765554600234560ustar00rootroot00000000000000#!/usr/bin/env bash if [ $# -le 3 ] ; then echo "Usage: bash example_pipeline.sh BWA_INDEX FASTQ_1 FASTQ_2 OUTPUT_PREFIX" echo "" echo "A example of a bash pipeline to align the sequencing data from a " echo "single Hi-C experiment." echo "" echo "positional arguments:" echo "" echo "BWA_INDEX The path to a bwa index of the reference genome." echo "CHROM_SIZES The path to a file with chromosome sizes." echo "FASTQ_1 The path to a fastq file with the sequences of " echo " the first side of Hi-C molecules." echo "FASTQ_2 The path to a fastq file with the sequences of " echo " the second side of Hi-C molecules." echo "OUTPUT_PREFIX The prefix to the paths of generated outputs. " echo "" echo "" exit 0 fi set -o errexit set -o nounset set -o pipefail INDEX=$1 CHROM_SIZES=$2 FASTQ1=$3 FASTQ2=$4 OUTPREFIX=$5 N_THREADS=8 UNMAPPED_SAM_PATH=${OUTPREFIX}.unmapped.bam UNMAPPED_PAIRS_PATH=${OUTPREFIX}.unmapped.pairs.gz NODUPS_SAM_PATH=${OUTPREFIX}.nodups.bam NODUPS_PAIRS_PATH=${OUTPREFIX}.nodups.pairs.gz DUPS_SAM_PATH=${OUTPREFIX}.dups.bam DUPS_PAIRS_PATH=${OUTPREFIX}.dups.pairs.gz LOWFREQPAIRS_SAM_PATH=${OUTPREFIX}.lowfreq.bam LOWFREQPAIRS_PAIRS_PATH=${OUTPREFIX}.lowfreq.pairs.gz HIGHFREQPAIRS_SAM_PATH=${OUTPREFIX}.highfreq.bam HIGHFREQPAIRS_PAIRS_PATH=${OUTPREFIX}.highfreq.pairs.gz bwa mem -SP -t "${N_THREADS}" "${INDEX}" "${FASTQ1}" "${FASTQ2}" | { # Classify Hi-C molecules as unmapped/single-sided/multimapped/chimeric/etc # and output one line per read, containing the following, separated by \\v: # * triu-flipped pairs # * read id # * type of a Hi-C molecule # * corresponding sam entries pairtools parse "{CHROM_SIZES}" } | { # Block-sort pairs together with SAM entries pairtools sort } | { # Set unmapped and ambiguous reads aside pairtools select '(pair_type == "UU") or (pair_type == "UR") or (pair_type == "RU")' \ --output-rest >( pairtools split \ --output-pairs ${UNMAPPED_PAIRS_PATH} \ --output-sam ${UNMAPPED_SAM_PATH} ) } | { # Remove duplicates pairtools dedup \ --output-dups \ >( pairtools markasdup \ | pairtools split \ --output-pairs ${DUPS_PAIRS_PATH} \ --output-sam ${DUPS_SAM_PATH} ) } | { # Remove high frequency interactors pairtools multifilter \ --output \ >( pairtools split \ --output-pairs ${LOWFREQ_PAIRS_PATH} \ --output-sam ${LOWFREQ_SAM_PATH} ) \ --output-high-frequency-interactors \ >( pairtools markasdup \ | pairtools split \ --output-pairs ${HIGHFREQPAIRS_PAIRS_PATH} \ --output-sam ${HIGHFREQPAIRS_SAM_PATH} ) } pairtools-0.3.0/pairtools/000077500000000000000000000000001345765554600155665ustar00rootroot00000000000000pairtools-0.3.0/pairtools/__init__.py000066400000000000000000000063251345765554600177050ustar00rootroot00000000000000# -*- coding: utf-8 -*- """ pairtools ~~~~~~~~~ CLI tools to process mapped Hi-C data :copyright: (c) 2017-2019 Massachusetts Institute of Technology :author: Mirny Lab :license: MIT """ __version__ = '0.3.0' import click import functools import sys CONTEXT_SETTINGS = { 'help_option_names': ['-h', '--help'], } @click.version_option(version=__version__) @click.group(context_settings=CONTEXT_SETTINGS) @click.option( '--post-mortem', help="Post mortem debugging", is_flag=True, default=False ) @click.option( '--output-profile', help="Profile performance with Python cProfile and dump the statistics " "into a binary file", type=str, default='' ) def cli(post_mortem, output_profile): '''Flexible tools for Hi-C data processing. All pairtools have a few common options, which should be typed _before_ the command name. ''' if post_mortem: import traceback try: import ipdb as pdb except ImportError: import pdb def _excepthook(exc_type, value, tb): traceback.print_exception(exc_type, value, tb) print() pdb.pm() sys.excepthook = _excepthook if output_profile: import cProfile import atexit pr = cProfile.Profile() pr.enable() def _atexit_profile_hook(): pr.disable() pr.dump_stats(output_profile) atexit.register(_atexit_profile_hook) def common_io_options(func): @click.option( '--nproc-in', type=int, default=3, show_default=True, help='Number of processes used by the auto-guessed input decompressing command.' ) @click.option( '--nproc-out', type=int, default=8, show_default=True, help='Number of processes used by the auto-guessed output compressing command.' ) @click.option( '--cmd-in', type=str, default=None, help='A command to decompress the input file. ' 'If provided, fully overrides the auto-guessed command. ' 'Does not work with stdin. ' 'Must read input from stdin and print output into stdout. ' 'EXAMPLE: pbgzip -dc -n 3' ) @click.option( '--cmd-out', type=str, default=None, help='A command to compress the output file. ' 'If provided, fully overrides the auto-guessed command. ' 'Does not work with stdout. ' 'Must read input from stdin and print output into stdout. ' 'EXAMPLE: pbgzip -c -n 8' ) @functools.wraps(func) def wrapper(*args, **kwargs): return func(*args, **kwargs) return wrapper from .pairtools_dedup import dedup from .pairtools_sort import sort from .pairtools_flip import flip from .pairtools_merge import merge from .pairtools_markasdup import markasdup from .pairtools_select import select from .pairtools_split import split from .pairtools_restrict import restrict from .pairtools_phase import phase from .pairtools_parse import parse, parse_cigar, parse_algn from .pairtools_stats import stats from .pairtools_filterbycov import filterbycov pairtools-0.3.0/pairtools/__main__.py000066400000000000000000000000671345765554600176630ustar00rootroot00000000000000from . import cli if __name__=='__main__': cli() pairtools-0.3.0/pairtools/_dedup.pyx000066400000000000000000000212111345765554600175650ustar00rootroot00000000000000""" ``mark_duplicates`` is an offline method that finds duplicates in a given input dataset. For other applications on much larger datasets you may consider an online method ``OnlineDuplicateDetector`` which is implemented as a class. Note that for both methods data types are fixed: * chromosomes are int32 * position is int32 * strand is int32, which is basically the same as C type "char". """ import numpy as np import cython cimport numpy as np cimport cython def mark_duplicates( cython.int [:] c1, cython.int [:] c2, cython.int [:] p1, cython.int [:] p2, cython.int [:] s1, cython.int [:] s2, #uncomment for testing probably since it will do boundary check #np.ndarray[np.int16_t, ndim=1]c2, #np.ndarray[np.int32_t, ndim=1] p1, #np.ndarray[np.int32_t, ndim=1] p2, #np.ndarray[np.int8_t, ndim=1] s1, #np.ndarray[np.int8_t, ndim=1] s2, int max_mismatch=3, method = "sum"): """ Mark duplicates, allowing for some mismatch on the both sides of the molecule. You can use it to filter single-cell data as well by setting max_mismatch to 500bp or even larger. It works as fast as we could make it. This methods scans through a list of reads. It then flags duplicates, which are defined as molecules, with both ends located within `max_mismatch` bp from each other. There are two ways define duplicates: "max": two reads are duplicates if the mismatch of the genomic locations of both ends is less-or-equal "max_mismatch" "sum": two reads are duplicates if the sum of the mismatches of the either ends of the molecule is less-or-equal "max_mismatch" Other methods could be added below by editing the code Parameters ---------- c1, c2 : int32 array chromosome IDs p1, p2 : int32 arrays positions s1, s2 : int32 (or bool) arrays strands max_mismatch : int method : "sum" or "max" use the sum of mismatches, or the max of the two Returns ------- mask : int8 array A binary mask, where 1 denotes that a read is a duplicate. Notes ----- Arrays MUST be ordered by (c1, p1) """ cdef int N = len(c1) cdef np.ndarray[np.int8_t, ndim=1] mask = np.zeros(N, dtype=np.int8) cdef int low = 0 cdef int high = 1 cdef int extraCondition cdef int methodid if method == "max": methodid = 0 elif method == "sum": methodid = 1 else: raise ValueError('method should be "sum" or "max"') while True: assert False if low == N: break if high == N: low += 1 high = low + 1 continue if mask[low] == 1: low += 1 high = low+1 continue # if high already removed, just continue if mask[high] == 1: high += 1 continue # if we jumped too far, continue if (c1[high] != c1[low]) or (p1[high] - p1[low] > max_mismatch) or (p1[high] < p1[low]) or (c2[high] != c2[low]): low += 1 high = low + 1 # restart high continue if methodid == 0: extraCondition = (max(abs(p1[low] - p1[high]), abs(p2[low] - p2[high])) <= max_mismatch) elif methodid == 1: extraCondition = (abs(p1[low] - p1[high]) + abs(p2[low] - p2[high]) <= max_mismatch) else: raise ValueError( "Unknown method id, this should not happen. " "Check code of this function.") if ((c2[low] == c2[high]) and (s1[low] == s1[high]) and (s2[low] == s2[high]) and extraCondition): mask[high] = 1 high += 1 continue high += 1 return mask cdef class OnlineDuplicateDetector(object): cdef cython.int [:] c1 cdef cython.int [:] c2 cdef cython.int [:] p1 cdef cython.int [:] p2 cdef cython.int [:] s1 cdef cython.int [:] s2 cdef cython.char [:] rm cdef int methodid cdef int low cdef int high cdef int N cdef int max_mismatch cdef int returnData def __init__(self, method, max_mismatch, returnData=False): if returnData == False: self.returnData = 0 else: self.returnData = 1 self.N = 0 self.c1 = np.zeros(0, np.int32) self.c2 = np.zeros(0, np.int32) self.p1 = np.zeros(0, np.int32) self.p2 = np.zeros(0, np.int32) self.s1 = np.zeros(0, np.int32) self.s2 = np.zeros(0, np.int32) self.rm = np.zeros(0, np.int8) if method == "max": self.methodid = 0 elif method == "sum": self.methodid = 1 else: raise ValueError('method should be "sum" or "max"') self.max_mismatch = int(max_mismatch) self.low = 0 self.high = 1 def _shrink(self): if self.returnData == 1: firstret = self.rm[:self.low] retainMask = (np.asarray(firstret) == False) del firstret ret = [] for ar in [self.c1, self.c2, self.p1, self.p2, self.s1, self.s2]: ret.append(np.asarray(ar)[:self.low][retainMask]) self.c1 = self.c1[self.low:] self.c2 = self.c2[self.low:] self.p1 = self.p1[self.low:] self.p2 = self.p2[self.low:] self.s1 = self.s1[self.low:] self.s2 = self.s2[self.low:] pastrm = self.rm[:self.low] self.rm = self.rm[self.low:] self.high = self.high-self.low self.N = self.N - self.low self.low = 0 if self.returnData == 1: return ret return pastrm def _run(self, finish=False): cdef int finishing = 0 cdef int extraCondition if finish: finishing = 1 while True: if self.low == self.N: break if self.high == self.N: if finishing == 1: self.low += 1 self.high = self.low + 1 continue else: break if self.rm[self.low] == 1: self.low += 1 self.high = self.low+1 continue # if high already removed, just continue if self.rm[self.high] == 1: self.high += 1 continue # if we jumped too far, continue if ((self.c1[self.high] != self.c1[self.low]) or (self.p1[self.high] - self.p1[self.low] > self.max_mismatch) or (self.p1[self.high] - self.p1[self.low] < 0 )): self.low += 1 self.high = self.low + 1 # restart high continue if self.methodid == 0: extraCondition = max( abs(self.p1[self.low] - self.p1[self.high]), abs(self.p2[self.low] - self.p2[self.high])) <= self.max_mismatch elif self.methodid == 1: # sum of distances <= max_mismatch extraCondition = ( abs(self.p1[self.low] - self.p1[self.high]) + abs(self.p2[self.low] - self.p2[self.high]) <= self.max_mismatch ) else: raise ValueError( "Unknown method id, this should not happen. " "Check code of this function.") if ((self.c2[self.low] == self.c2[self.high]) and (self.s1[self.low] == self.s1[self.high]) and (self.s2[self.low] == self.s2[self.high]) and extraCondition): self.rm[self.high] = 1 self.high += 1 continue self.high += 1 return self._shrink() def push(self, c1, c2, p1, p2, s1, s2): self.c1 = np.concatenate([self.c1, c1]) self.c2 = np.concatenate([self.c2, c2]) self.p1 = np.concatenate([self.p1, p1]) self.p2 = np.concatenate([self.p2, p2]) self.s1 = np.concatenate([self.s1, s1]) self.s2 = np.concatenate([self.s2, s2]) self.rm = np.concatenate([self.rm, np.zeros(len(c1), dtype=np.int8)]) self.N = self.N + len(c1) return self._run(finish=False) def finish(self): return self._run(finish=True) def getLen(self): return int(self.N) pairtools-0.3.0/pairtools/_fileio.py000066400000000000000000000071451345765554600175550ustar00rootroot00000000000000import shutil import pipes class ParseError(Exception): pass def auto_open(path, mode, nproc=1, command=None): '''Guess the file format from the extension and use the corresponding binary to open it for reading or writing. If the extension is not known, open the file as text. If the binary allows parallel execution, specify the number of threads with `nproc`. If `command` is supplied, use it to open the file instead of auto-guessing. The command must accept the filename as the last argument, accept input through stdin and print output into stdout. Supported extensions and binaries (with comments): .bam - samtools view (allows parallel writing) .gz - pbgzip .lz4 - lz4c (does not support parallel execution) ''' if command: if mode =='w': t = pipes.Template() t.append(command, '--') f = t.open(path, 'w') elif mode =='r': t = pipes.Template() t.append(command, '--') f = t.open(path, 'r') else: raise ValueError("Unknown mode : {}".format(mode)) return f elif path.endswith('.bam'): if shutil.which('samtools') is None: raise ValueError({ 'w':'samtools is not found, cannot compress output', 'r':'samtools is not found, cannot decompress input' }[mode]) if mode =='w': t = pipes.Template() t.append('samtools view -bS {} -'.format( '-@ '+str(nproc-1) if nproc>1 else ''), '--') f = t.open(path, 'w') elif mode =='r': t = pipes.Template() t.append('samtools view -h', '--') f = t.open(path, 'r') else: raise ValueError("Unknown mode for .bam : {}".format(mode)) return f elif path.endswith('.gz'): if shutil.which('pbgzip') is None: raise ValueError({ 'w':'pbgzip is not found, cannot compress output', 'a':'pbgzip is not found, cannot compress output', 'r':'pbgzip is not found, cannot decompress input' }[mode]) if mode =='w': t = pipes.Template() t.append('pbgzip -c -n {}'.format(nproc), '--') f = t.open(path, 'w') elif mode =='a': t = pipes.Template() t.append('pbgzip -c -n {} $IN >> $OUT'.format(nproc), 'ff') f = t.open(path, 'w') elif mode =='r': t = pipes.Template() t.append('pbgzip -dc -n {}'.format(nproc), '--') f = t.open(path, 'r') else: raise ValueError("Unknown mode for .gz : {}".format(mode)) return f elif path.endswith('.lz4'): if shutil.which('lz4c') is None: raise ValueError({ 'w':'lz4c is not found, cannot compress output', 'a':'lz4c is not found, cannot compress output', 'r':'lz4c is not found, cannot decompress input' }[mode]) if mode =='w': t = pipes.Template() t.append('lz4c -cz', '--') f = t.open(path, 'w') elif mode =='a': t = pipes.Template() t.append('lz4c -cz $IN >> $OUT', 'ff') f = t.open(path, 'w') elif mode =='r': t = pipes.Template() t.append('lz4c -cd', '--') f = t.open(path, 'r') else: raise ValueError("Unknown mode : {}".format(mode)) return f else: return open(path, mode) pairtools-0.3.0/pairtools/_headerops.py000066400000000000000000000412721345765554600202570ustar00rootroot00000000000000from collections import OrderedDict, defaultdict import sys import copy import itertools from . import __version__, _pairsam_format from ._fileio import ParseError PAIRS_FORMAT_VERSION = '1.0.0' def get_header(instream, comment_char='#'): '''Returns a header from the stream and an the reaminder of the stream with the actual data. Parameters ---------- instream : a file object An input stream. comment_char : str The character prepended to header lines (use '@' when parsing sams, '#' when parsing pairsams). Returns ------- header : list The header lines, stripped of terminal spaces and newline characters. remainder_stream : stream/file-like object Stream with the remaining lines. ''' header = [] if not comment_char: raise ValueError('Please, provide a comment char!') comment_byte = comment_char.encode() # get peekable buffer for the instream inbuffer = instream.buffer current_peek = inbuffer.peek() while current_peek.startswith(comment_byte): # consuming a line from buffer guarantees # that the remainder of the buffer starts # with the beginning of the line. line = inbuffer.readline() # append line to header, since it does start with header header.append(line.decode().strip()) # peek into the remainder of the instream current_peek = inbuffer.peek() # apparently, next line does not start with the comment # return header and the instream, advanced to the beginning of the data return header, instream def extract_fields(header, field_name, save_rest=False): ''' Extract the specified fields from the pairs header and returns a list of corresponding values, even if a single field was found. Additionally, can return the list of intact non-matching entries. ''' fields = [] rest = [] for l in header: if l.lstrip('#').startswith(field_name+':'): fields.append(l.split(':',1)[1].strip()) elif save_rest: rest.append(l) if save_rest: return fields, rest else: return fields def extract_column_names(header): ''' Extract column names from header lines. ''' columns = extract_fields(header, 'columns') if len(columns) != 0: return columns[0].split(' ') else: return [] def get_chromsizes_from_sam_header(samheader): SQs = [l.split('\t') for l in samheader if l.startswith('@SQ')] chromsizes = [(sq[1][3:], int(sq[2][3:])) for sq in SQs] return OrderedDict(chromsizes) def get_chrom_order(chroms_file, sam_chroms=None): """ Produce an "enumeration" of chromosomes based on the list of chromosomes """ chrom_enum = OrderedDict() i = 1 with open(chroms_file, 'rt') as f: for line in f: chrom = line.strip().split('\t')[0] if chrom and ((not sam_chroms) or (chrom in sam_chroms)): chrom_enum[chrom] = i i += 1 if sam_chroms: remaining = sorted(chrom for chrom in sam_chroms if chrom not in chrom_enum.keys()) for chrom in remaining: chrom_enum[chrom] = i i += 1 return chrom_enum def make_standard_pairsheader( assembly=None, chromsizes=None, columns=_pairsam_format.COLUMNS, shape = 'upper triangle'): header = [] header.append( '## pairs format v{}'.format(PAIRS_FORMAT_VERSION)) header.append('#shape: {}'.format(shape)) header.append('#genome_assembly: {}'.format( assembly if assembly is not None else 'unknown')) if chromsizes is not None: try: chromsizes = chromsizes.items() except AttributeError: pass for chrom, length in chromsizes: header.append('#chromsize: {} {}'.format(chrom, length)) header.append('#columns: '+ ' '.join(columns)) return header def subset_chroms_in_pairsheader(header, chrom_subset): new_header = [] for line in header: if line.startswith('#chromsize:'): if line.strip().split()[1] in chrom_subset: new_header.append(line) elif line.startswith('#chromosomes:'): line = ' '.join( ['#chromosomes:'] + [c for c in line.strip().split()[1:] if c in chrom_subset]) new_header.append(line) else: new_header.append(line) return new_header def insert_samheader(header, samheader): new_header = [l for l in header if not l.startswith('#columns')] if samheader: new_header += ['#samheader: '+l for l in samheader] new_header += [l for l in header if l.startswith('#columns')] return new_header def mark_header_as_sorted(header): header = copy.deepcopy(header) if not any([l.startswith('#sorted') for l in header]): if header[0].startswith('##'): header.insert(1, '#sorted: chr1-chr2-pos1-pos2') else: header.insert(0, '#sorted: chr1-chr2-pos1-pos2') for i in range(len(header)): if header[i].startswith('#chromosomes'): chroms = header[i][12:].strip().split(' ') header[i] = '#chromosomes: {}'.format(' '.join(sorted(chroms))) return header def append_new_pg(header, ID='', PN='', VN=None, CL=None, force=False): header = copy.deepcopy(header) samheader, other_header = extract_fields(header, 'samheader', save_rest=True) new_samheader = _add_pg_to_samheader(samheader, ID, PN, VN, CL, force) new_header = insert_samheader(other_header, new_samheader) return new_header def _update_header_entry(header, field, new_value): header = copy.deepcopy(header) found = False newline = '#{}: {}'.format(field, new_value) for i in range(len(header)): if header[i].startswith('#'+field): header[i] = newline found = True if not found: if header[-1].startswith('#columns'): header.insert(-1, newline) else: header.append(newline) return header def _add_pg_to_samheader(samheader, ID='', PN='', VN=None, CL=None, force=False): '''Append a @PG record to an existing sam header. If the header comes from a merged file and thus has multiple chains of @PG, append the provided PG to all of the chains, adding the numerical suffix of the branch to the ID. Parameters ---------- header : list of str ID, PN, VN, CL : std The keys of a new @PG record. If absent, VN is the version of pairtools and CL is taken from sys.argv. force : bool If True, ignore the inconsistencies among @PG records of the existing header. Returns ------- new_header : list of str A list of new headers lines, stripped of newline characters. ''' if VN is None: VN = __version__ if CL is None: CL = ' '.join(sys.argv) pre_pg_header = [line.strip() for line in samheader if line.startswith('@HD') or line.startswith('@SQ') or line.startswith('@RG') ] post_pg_header = [line.strip() for line in samheader if not line.startswith('@HD') and (not line.startswith('@SQ')) and (not line.startswith('@RG')) and (not line.startswith('@PG')) ] pg_chains = _parse_pg_chains(samheader, force=force) for i,br in enumerate(pg_chains): new_pg = {'ID':ID, 'PN':PN, 'VN':VN, 'CL':CL} new_pg['PP'] = br[-1]['ID'] if len(pg_chains) > 1: new_pg['ID'] = new_pg['ID'] + '-' + str(i+1) + '.' + str(len(br)+1) new_pg['raw'] = _format_pg(**new_pg) br.append(new_pg) new_header = ( pre_pg_header + [pg['raw'] for br in pg_chains for pg in br] + post_pg_header) return new_header def _format_pg(**kwargs): out = ( ['@PG'] + ['{}:{}'.format(field, kwargs[field]) for field in ['ID', 'PN', 'CL', 'PP', 'DS', 'VN'] if field in kwargs]) return '\t'.join(out) def _parse_pg_chains(header, force=False): pg_chains = [] parsed_pgs = [ dict( [field.split(':', maxsplit=1) for field in l.strip().split('\t')[1:]] + [('raw', l.strip())] ) for l in header if l.startswith('@PG') ] while True: if len(parsed_pgs) == 0: break for i in range(len(parsed_pgs)): pg = parsed_pgs[i] if 'PP' not in pg: pg_chains.append([pg]) parsed_pgs.pop(i) break else: matching_chains = [ branch for branch in pg_chains if branch[-1]['ID'] == pg['PP'] ] if len(matching_chains) > 1: if force: matching_chains[0].append(pg) parsed_pgs.pop(i) break else: raise ParseError( 'Multiple @PG records with the IDs identical to the PP field of another record:\n' + '\n'.join([br[-1]['raw'] for br in matching_chains]) + '\nvs\n' + pg['raw'] ) if len(matching_chains) == 1: matching_chains[0].append(pg) parsed_pgs.pop(i) break if force: pg_chains.append([pg]) parsed_pgs.pop(i) break else: raise ParseError( 'Cannot find the parental @PG record for the @PG records:\n' + '\n'.join([pg['raw'] for pg in parsed_pgs]) ) return pg_chains def _toposort(dag, tie_breaker): """ Topological sort on a directed acyclic graph Uses Kahn's algorithm with a custom tie-breaking option. The dictionary ``dag`` can be interpreted in two ways: 1. A dependency graph (i.e. arcs point from values to keys), and the generator yields items with no dependences followed by items that depend on previous ones. 2. Arcs point from keys to values, in which case the generator produces a **reverse** topological ordering of the nodes. Parameters ---------- dag: dict of nodes to sets of nodes Directed acyclic graph encoded as a dictionary. tie_breaker: callable Function that picks a tie breaker from a set of nodes with no unprocessed dependences. Returns ------- Generator Notes ----- See . Based in part on activestate recipe: by Sam Denton (MIT licensed). """ # Drop self-edges. for k, v in dag.items(): v.discard(k) # Find all nodes that don't depend on anything # and include them with empty dependencies. indep_nodes = set.union(*dag.values()) - set(dag.keys()) dag.update({node: set() for node in indep_nodes}) while True: if not indep_nodes: break out = tie_breaker(indep_nodes) indep_nodes.discard(out) del dag[out] yield out for node, deps in dag.items(): deps.discard(out) if len(deps) == 0: indep_nodes.add(node) if len(dag) != 0: raise ValueError( 'Circular dependencies exist: {} '.format(list(dag.items()))) def merge_chrom_lists(*lsts): sentinel = '!NONE!' g = defaultdict(set) for lst in lsts: if len(lst) == 1: g[lst[0]].add(sentinel) for a, b in zip(lst[:-1], lst[1:]): g[b].add(a) if len(g) == 0: return [] chrom_list = list(_toposort(g.copy(), tie_breaker=min)) if sentinel in chrom_list: chrom_list.remove(sentinel) return chrom_list def _merge_samheaders(samheaders, force=False): # first, append an HD line if it is present in any files # if different lines are present, raise an error HDs = set.union(*[set(line for line in samheader if line.startswith('@HD')) for samheader in samheaders]) if len(HDs) > 1 and not force: raise ParseError('More than one unique @HD line is found in samheaders!') HDs = [list(HDs)[0]] if HDs else [] # second, confirm that all files had the same SQ lines # add SQs from the first file, keeping its order SQs = [set(line for line in samheader if line.startswith('@SQ')) for samheader in samheaders] common_SQs = set.intersection(*SQs) SQs_same = all([len(samheader) == len(common_SQs) for samheader in SQs]) if not SQs_same and not(force): raise ParseError('The SQ (sequence) lines of the sam headers are not identical') SQs = [line for line in samheaders[0] if line.startswith('@SQ')] # third, append _all_ PG chains, adding a unique index according to the # provided merging order PGs = [] for i, samheader in enumerate(samheaders): for line in samheader: if line.startswith('@PG'): split_line = line.split('\t') for j in range(len(split_line)): if (split_line[j].startswith('ID:') or split_line[j].startswith('PP:')): split_line[j] = split_line[j] + '-' + str(i+1) PGs.append('\t'.join(split_line)) # finally, add all residual unique lines rest = sum([ list(set(line for line in samheader if (not line.startswith('@HD')) and (not line.startswith('@SQ')) and (not line.startswith('@PG')) )) for samheader in samheaders], []) new_header = [] new_header += HDs new_header += SQs new_header += PGs new_header += rest return new_header def _merge_pairheaders(pairheaders, force=False): new_header = [] # first, add all keys that are expected to be the same among all headers keys_expected_identical = [ '## pairs format', '#sorted:', '#shape:', '#genome_assembly:', '#columns:' ] for k in keys_expected_identical: lines = [[l for l in header if l.startswith(k)] for header in pairheaders] same = all([l == lines[0] for l in lines]) if not (same or force): raise ParseError( 'The following header entries must be the same ' 'the merged files: {}'.format(k)) new_header += lines[0] # second, merge and add the chromsizes fields. chrom_lists = [] chromsizes = {} for header in pairheaders: chromlist = [] for line in header: if line.startswith('#chromsize:'): chrom, length = line.strip('#chromsize:').split() chromsizes[chrom] = length chromlist.append(chrom) chrom_lists.append(chromlist) chroms_merged = merge_chrom_lists(*chrom_lists) chrom_lines = ["#chromsize: {} {}".format(chrom, chromsizes[chrom]) for chrom in chroms_merged] new_header.extend(chrom_lines) # finally, add a sorted list of other unique fields other_lines = sorted(set( l for h in pairheaders for l in h if not any(l.startswith(k) for k in keys_expected_identical + ['#chromsize']))) if other_lines: if new_header[-1].startswith('#columns'): new_header = new_header[:-1] + other_lines + [new_header[-1]] else: new_header = new_header + other_lines return new_header def merge_headers(headers, force=False): samheaders, pairheaders = zip(*[extract_fields(h, 'samheader', save_rest=True) for h in headers]) # HD headers contain information that becomes invalid after processing # with distiller. Do not print into the output. new_pairheader = _merge_pairheaders(pairheaders, force=False) new_samheader = _merge_samheaders(samheaders, force=force) new_header = insert_samheader(new_pairheader, new_samheader) return new_header #def _guess_genome_assembly(samheader): # PG = [l for l in samheader if l.startswith('@PG') and '\tID:bwa' in l][0] # CL = [field for field in PG.split('\t') if field.startswith('CL:')] # # return ga pairtools-0.3.0/pairtools/_pairsam_format.py000066400000000000000000000007151345765554600213060ustar00rootroot00000000000000PAIRSAM_FORMAT_VERSION = '1.0.0' PAIRSAM_SEP = '\t' PAIRSAM_SEP_ESCAPE = r'\t' SAM_SEP = '\031' SAM_SEP_ESCAPE = r'\031' INTER_SAM_SEP = '\031NEXT_SAM\031' COL_READID = 0 COL_C1 = 1 COL_P1 = 2 COL_C2 = 3 COL_P2 = 4 COL_S1 = 5 COL_S2 = 6 COL_PTYPE = 7 COL_SAM1 = 8 COL_SAM2 = 9 COLUMNS = ['readID', 'chrom1', 'pos1', 'chrom2', 'pos2', 'strand1', 'strand2', 'pair_type', 'sam1', 'sam2'] UNMAPPED_CHROM = '!' UNMAPPED_POS = 0 UNMAPPED_STRAND = '-' pairtools-0.3.0/pairtools/pairtools_dedup.py000066400000000000000000000366331345765554600213500ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- import sys import ast import warnings import pathlib import click import numpy as np from . import _dedup, _fileio, _pairsam_format, _headerops, cli, common_io_options from .pairtools_markasdup import mark_split_pair_as_dup from .pairtools_stats import PairCounter UTIL_NAME = 'pairtools_dedup' # you don't need to load more than 10k lines at a time b/c you get out of the # CPU cache, so this parameter is not adjustable MAX_LEN = 10000 @cli.command() @click.argument( 'pairs_path', type=str, required=False) @click.option( "-o", "--output", type=str, default="", help='output file for pairs after duplicate removal.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, the output is printed into stdout.') @click.option( "--output-dups", type=str, default="", help='output file for duplicated pairs. ' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' If the path is the same as in --output or -, output duplicates together ' ' with deduped pairs. By default, duplicates are dropped.') @click.option( "--output-unmapped", type=str, default="", help='output file for unmapped pairs. ' 'If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed. ' 'If the path is the same as in --output or -, output unmapped pairs together ' 'with deduped pairs. If the path is the same as --output-dups, output ' 'unmapped reads together with dups. By default, unmapped pairs are dropped.') @click.option( "--output-stats", type=str, default="", help='output file for duplicate statistics. ' ' If file exists, it will be open in the append mode.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, statistics are not printed.') @click.option( "--max-mismatch", type=int, default=3, show_default=True, help='Pairs with both sides mapped within this distance (bp) from each ' 'other are considered duplicates.') @click.option( '--method', type=click.Choice(['max', 'sum']), default="max", help='define the mismatch as either the max or the sum of the mismatches of' 'the genomic locations of the both sides of the two compared molecules', show_default=True,) @click.option( "--sep", type=str, default=_pairsam_format.PAIRSAM_SEP_ESCAPE, help=r"Separator (\t, \v, etc. characters are " "supported, pass them in quotes) ") @click.option( "--comment-char", type=str, default="#", help="The first character of comment lines") @click.option( "--send-header-to", type=click.Choice(['dups', 'dedup', 'both', 'none']), default="both", help="Which of the outputs should receive header and comment lines") @click.option( "--c1", type=int, default=_pairsam_format.COL_C1, help='Chrom 1 column; default {}'.format(_pairsam_format.COL_C1)) @click.option( "--c2", type=int, default=_pairsam_format.COL_C2, help='Chrom 2 column; default {}'.format(_pairsam_format.COL_C2)) @click.option( "--p1", type=int, default=_pairsam_format.COL_P1, help='Position 1 column; default {}'.format(_pairsam_format.COL_P1)) @click.option( "--p2", type=int, default=_pairsam_format.COL_P2, help='Position 2 column; default {}'.format(_pairsam_format.COL_P2)) @click.option( "--s1", type=int, default=_pairsam_format.COL_S1, help='Strand 1 column; default {}'.format(_pairsam_format.COL_S1)) @click.option( "--s2", type=int, default=_pairsam_format.COL_S2, help='Strand 2 column; default {}'.format(_pairsam_format.COL_S2)) @click.option( "--unmapped-chrom", type=str, default=_pairsam_format.UNMAPPED_CHROM, help='Placeholder for a chromosome on an unmapped side; default {}'.format(_pairsam_format.UNMAPPED_CHROM)) @click.option( "--mark-dups", is_flag=True, help='If specified, duplicate pairs are marked as DD in "pair_type" and ' 'as a duplicate in the sam entries.') @click.option( "--extra-col-pair", nargs=2, #type=click.Tuple([str, str]), multiple=True, help='Extra columns that also must match for two pairs to be marked as ' 'duplicates. Can be either provided as 0-based column indices or as column ' 'names (requires the "#columns" header field). The option can be provided ' 'multiple times if multiple column pairs must match. ' 'Example: --extra-col-pair "phase1" "phase2"' ) @common_io_options def dedup(pairs_path, output, output_dups, output_unmapped, output_stats, max_mismatch, method, sep, comment_char, send_header_to, c1, c2, p1, p2, s1, s2, unmapped_chrom, mark_dups, extra_col_pair, **kwargs ): '''Find and remove PCR/optical duplicates. Find PCR duplicates in an upper-triangular flipped sorted pairs/pairsam file. Allow for a +/-N bp mismatch at each side of duplicated molecules. PAIRS_PATH : input triu-flipped sorted .pairs or .pairsam file. If the path ends with .gz/.lz4, the input is decompressed by pbgzip/lz4c. By default, the input is read from stdin. ''' dedup_py(pairs_path, output, output_dups, output_unmapped, output_stats, max_mismatch, method, sep, comment_char, send_header_to, c1, c2, p1, p2, s1, s2, unmapped_chrom, mark_dups, extra_col_pair, **kwargs ) def dedup_py( pairs_path, output, output_dups, output_unmapped, output_stats, max_mismatch, method, sep, comment_char, send_header_to, c1, c2, p1, p2, s1, s2, unmapped_chrom, mark_dups, extra_col_pair, **kwargs ): sep = ast.literal_eval('"""' + sep + '"""') send_header_to_dedup = send_header_to in ['both', 'dedup'] send_header_to_dup = send_header_to in ['both', 'dups'] instream = (_fileio.auto_open(pairs_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairs_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) out_stats_stream = (_fileio.auto_open(output_stats, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output_stats else None) # generate empty PairCounter if stats output is requested: out_stat = PairCounter() if output_stats else None if not output_dups: outstream_dups = None elif (output_dups == '-' or (pathlib.Path(output_dups).absolute() == pathlib.Path(output).absolute())): outstream_dups = outstream else: outstream_dups = _fileio.auto_open(output_dups, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if not output_unmapped: outstream_unmapped = None elif (output_unmapped == '-' or (pathlib.Path(output_unmapped).absolute() == pathlib.Path(output).absolute())): outstream_unmapped = outstream elif (pathlib.Path(output_unmapped).absolute() == pathlib.Path(output_dups).absolute()): outstream_unmapped = outstream_dups else: outstream_unmapped = _fileio.auto_open(output_unmapped, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) if send_header_to_dedup: outstream.writelines((l+'\n' for l in header)) if send_header_to_dup and outstream_dups and (outstream_dups != outstream): outstream_dups.writelines((l+'\n' for l in header)) if (outstream_unmapped and (outstream_unmapped != outstream) and (outstream_unmapped != outstream_dups)): outstream_unmapped.writelines((l+'\n' for l in header)) column_names = _headerops.extract_column_names(header) extra_cols1 = [] extra_cols2 = [] if extra_col_pair is not None: for col1, col2 in extra_col_pair: extra_cols1.append( int(col1) if col1.isdigit() else column_names.index(col1)) extra_cols2.append( int(col2) if col2.isdigit() else column_names.index(col2)) streaming_dedup( method, max_mismatch, sep, c1, c2, p1, p2, s1, s2, extra_cols1, extra_cols2, unmapped_chrom, body_stream, outstream, outstream_dups, outstream_unmapped, out_stat, mark_dups) # save statistics to a file if it was requested: if out_stat: out_stat.save(out_stats_stream) if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() if outstream_dups and (outstream_dups != outstream): outstream_dups.close() if (outstream_unmapped and (outstream_unmapped != outstream) and (outstream_unmapped != outstream_dups)): outstream_unmapped.close() if out_stats_stream: out_stats_stream.close() def fetchadd(key, mydict): key = key.strip() if key not in mydict: mydict[key] = len(mydict) return mydict[key] def ar(mylist, val): return np.array(mylist, dtype={8: np.int8, 16: np.int16, 32: np.int32}[val]) def streaming_dedup( method, max_mismatch, sep, c1ind, c2ind, p1ind, p2ind, s1ind, s2ind, extra_cols1, extra_cols2, unmapped_chrom, instream, outstream, outstream_dups, outstream_unmapped, out_stat, mark_dups): maxind = max(c1ind, c2ind, p1ind, p2ind, s1ind, s2ind) if bool(extra_cols1) and bool(extra_cols2): maxind = max(maxind, max(extra_cols1), max(extra_cols2)) all_scols1 = [s1ind] + extra_cols1 all_scols2 = [s2ind] + extra_cols2 # if we do stats in the dedup, we need PAIR_TYPE # i do not see way around this: if out_stat: ptind = _pairsam_format.COL_PTYPE maxind = max(maxind, ptind) dd = _dedup.OnlineDuplicateDetector(method, max_mismatch, returnData=False) c1 = []; c2 = []; p1 = []; p2 = []; s1 = []; s2 = [] line_buffer = [] cols_buffer = [] chromDict = {} strandDict = {} n_unmapped = 0 n_dups = 0 n_nodups = 0 curMaxLen = max(MAX_LEN, dd.getLen()) instream = iter(instream) while True: rawline = next(instream, None) stripline = rawline.strip() if rawline else None # take care of empty lines not at the end of the file separately if rawline and (not stripline): warnings.warn("Empty line detected not at the end of the file") continue if stripline: cols = stripline.split(sep) if len(cols) <= maxind: raise ValueError( "Error parsing line {}: ".format(stripline) + " expected {} columns, got {}".format(maxind, len(cols))) if ((cols[c1ind] == unmapped_chrom) or (cols[c2ind] == unmapped_chrom)): if outstream_unmapped: outstream_unmapped.write(stripline) # don't forget terminal newline outstream_unmapped.write("\n") # add a pair to PairCounter if stats output is requested: if out_stat: out_stat.add_pair(cols[c1ind], int(cols[p1ind]), cols[s1ind], cols[c2ind], int(cols[p2ind]), cols[s2ind], cols[ptind]) else: line_buffer.append(stripline) cols_buffer.append(cols) c1.append(fetchadd(cols[c1ind], chromDict)) c2.append(fetchadd(cols[c2ind], chromDict)) p1.append(int(cols[p1ind])) p2.append(int(cols[p2ind])) if bool(extra_cols1) and bool(extra_cols2): s1.append(fetchadd(''.join(cols[i] for i in all_scols1), strandDict)) s2.append(fetchadd(''.join(cols[i] for i in all_scols2), strandDict)) else: s1.append(fetchadd(cols[s1ind], strandDict)) s2.append(fetchadd(cols[s2ind], strandDict)) if (not stripline) or (len(c1) == curMaxLen): res = dd.push(ar(c1, 32), ar(c2, 32), ar(p1, 32), ar(p2, 32), ar(s1, 32), ar(s2, 32)) if not stripline: res = np.concatenate([res, dd.finish()]) for i in range(len(res)): # not duplicated pair: if not res[i]: outstream.write(line_buffer[i]) # don't forget terminal newline outstream.write("\n") if out_stat: out_stat.add_pair(cols_buffer[i][c1ind], int(cols_buffer[i][p1ind]), cols_buffer[i][s1ind], cols_buffer[i][c2ind], int(cols_buffer[i][p2ind]), cols_buffer[i][s2ind], cols_buffer[i][ptind]) # duplicated pair: else: if out_stat: out_stat.add_pair(cols_buffer[i][c1ind], int(cols_buffer[i][p1ind]), cols_buffer[i][s1ind], cols_buffer[i][c2ind], int(cols_buffer[i][p2ind]), cols_buffer[i][s2ind], 'DD' ) if outstream_dups: outstream_dups.write( # DD-marked pair: sep.join(mark_split_pair_as_dup(cols_buffer[i])) if mark_dups # pair as is: else line_buffer[i] ) # don't forget terminal newline outstream_dups.write('\n') # flush buffers and perform necessary checks here: c1 = []; c2 = []; p1 = []; p2 = []; s1 = []; s2 = [] line_buffer = line_buffer[len(res):] cols_buffer = cols_buffer[len(res):] if not stripline: if(len(line_buffer) != 0): raise ValueError( "{} lines left in the buffer, ".format(len(line_buffer)) + "should be none;" + "something went terribly wrong") break # process next line ... # all lines have been processed at this point. # streaming_dedup is over. if __name__ == '__main__': dedup() pairtools-0.3.0/pairtools/pairtools_filterbycov.py000066400000000000000000000416571345765554600226010ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- import sys import ast import warnings import pathlib import click import numpy as np from . import _dedup, _fileio, _pairsam_format, _headerops, cli, common_io_options from .pairtools_markasdup import mark_split_pair_as_dup from .pairtools_stats import PairCounter UTIL_NAME = 'pairtools_filterbycov' ###################################### ## TODO: - output stats after filtering ## edit/update mark as dup to mark as multi ################################### @cli.command() @click.argument( 'pairs_path', type=str, required=False) @click.option( "-o", "--output", type=str, default="", help='output file for pairs from low coverage regions.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, the output is printed into stdout.') @click.option( "--output-highcov", type=str, default="", help='output file for pairs from high coverage regions.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' If the path is the same as in --output or -, output duplicates together ' ' with deduped pairs. By default, duplicates are dropped.') @click.option( "--output-unmapped", type=str, default="", help='output file for unmapped pairs. ' 'If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed. ' 'If the path is the same as in --output or -, output unmapped pairs together ' 'with deduped pairs. If the path is the same as --output-highcov, ' 'output unmapped reads together. By default, unmapped pairs are dropped.') @click.option( "--output-stats", type=str, default="", help='output file for statistics of multiple interactors. ' ' If file exists, it will be open in the append mode.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, statistics are not printed.') @click.option( "--max-cov", type=int, default=8, help='The maximum allowed coverage per region.' ) @click.option( "--max-dist", type=int, default=500, help='The resolution for calculating coverage. For each pair, the local ' 'coverage around each end is calculated as (1 + the number of neighbouring ' 'pairs within +/- max_dist bp) ') @click.option( '--method', type=click.Choice(['max', 'sum']), default="max", help='calculate the number of neighbouring pairs as either the sum or the max' ' of the number of neighbours on the two sides', show_default=True) @click.option( "--sep", type=str, default=_pairsam_format.PAIRSAM_SEP_ESCAPE, help=r"Separator (\t, \v, etc. characters are " "supported, pass them in quotes) ") @click.option( "--comment-char", type=str, default="#", help="The first character of comment lines") @click.option( "--send-header-to", type=click.Choice(['lowcov', 'highcov', 'both', 'none']), default="both", help="Which of the outputs should receive header and comment lines") @click.option( "--c1", type=int, default=_pairsam_format.COL_C1, help='Chrom 1 column; default {}'.format(_pairsam_format.COL_C1)) @click.option( "--c2", type=int, default=_pairsam_format.COL_C2, help='Chrom 2 column; default {}'.format(_pairsam_format.COL_C2)) @click.option( "--p1", type=int, default=_pairsam_format.COL_P1, help='Position 1 column; default {}'.format(_pairsam_format.COL_P1)) @click.option( "--p2", type=int, default=_pairsam_format.COL_P2, help='Position 2 column; default {}'.format(_pairsam_format.COL_P2)) @click.option( "--s1", type=int, default=_pairsam_format.COL_S1, help='Strand 1 column; default {}'.format(_pairsam_format.COL_S1)) @click.option( "--s2", type=int, default=_pairsam_format.COL_S2, help='Strand 2 column; default {}'.format(_pairsam_format.COL_S2)) @click.option( "--unmapped-chrom", type=str, default=_pairsam_format.UNMAPPED_CHROM, help='Placeholder for a chromosome on an unmapped side; default {}'.format(_pairsam_format.UNMAPPED_CHROM)) @click.option( "--mark-multi", is_flag=True, help='If specified, duplicate pairs are marked as FF in "pair_type" and ' 'as a duplicate in the sam entries.') @common_io_options def filterbycov( pairs_path, output, output_highcov, output_unmapped, output_stats, max_dist,max_cov, method, sep, comment_char, send_header_to, c1, c2, p1, p2, s1, s2, unmapped_chrom, mark_multi, **kwargs ): '''Remove pairs from regions of high coverage. Find and remove pairs with >(MAX_COV-1) neighbouring pairs within a +/- MAX_DIST bp window around either side. Useful for single-cell Hi-C experiments, where coverage is naturally limited by the chromosome copy number. PAIRS_PATH : input triu-flipped sorted .pairs or .pairsam file. If the path ends with .gz/.lz4, the input is decompressed by pbgzip/lz4c. By default, the input is read from stdin. ''' filterbycov_py( pairs_path, output, output_highcov, output_unmapped,output_stats, max_dist,max_cov, method, sep, comment_char, send_header_to, c1, c2, p1, p2, s1, s2, unmapped_chrom, mark_multi, **kwargs ) def filterbycov_py( pairs_path, output, output_highcov, output_unmapped, output_stats, max_dist,max_cov, method, sep, comment_char, send_header_to, c1, c2, p1, p2, s1, s2, unmapped_chrom, mark_multi, **kwargs ): ## Prepare input, output streams based on selected outputs ## Default ouput stream is low-frequency interactors sep = ast.literal_eval('"""' + sep + '"""') send_header_to_lowcov = send_header_to in ['both', 'lowcov'] send_header_to_highcov = send_header_to in ['both', 'highcov'] instream = (_fileio.auto_open(pairs_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairs_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) out_stats_stream = (_fileio.auto_open(output_stats, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output_stats else None) # generate empty PairCounter if stats output is requested: out_stat = PairCounter() if output_stats else None # output the high-frequency interacting pairs if not output_highcov: outstream_high = None elif (output_highcov == '-' or (pathlib.Path(output_highcov).absolute() == pathlib.Path(output).absolute())): outstream_high = outstream else: outstream_high = _fileio.auto_open(output_highcov, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) # output unmapped pairs if not output_unmapped: outstream_unmapped = None elif (output_unmapped == '-' or (pathlib.Path(output_unmapped).absolute() == pathlib.Path(output).absolute())): outstream_unmapped = outstream elif (pathlib.Path(output_unmapped).absolute() == pathlib.Path(output_highcov).absolute()): outstream_unmapped = outstream_high else: outstream_unmapped = _fileio.auto_open(output_unmapped, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) # prepare file headers header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) # header for low-frequency interactors if send_header_to_lowcov: outstream.writelines((l+'\n' for l in header)) # header for high-frequency interactors if send_header_to_highcov and outstream_high and (outstream_high != outstream): outstream_high.writelines((l+'\n' for l in header)) # header for unmapped pairs if (outstream_unmapped and (outstream_unmapped != outstream) and (outstream_unmapped != outstream_high)): outstream_unmapped.writelines((l+'\n' for l in header)) # perform filtering of pairs based on low/high-frequency of interaction streaming_filterbycov( method, max_dist,max_cov, sep, c1, c2, p1, p2, s1, s2, unmapped_chrom, body_stream, outstream, outstream_high, outstream_unmapped, out_stat, mark_multi) ## FINISHED! # save statistics to a file if it was requested: TO BE TESTED if out_stat: out_stat.save(out_stats_stream) if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() if outstream_high and (outstream_high != outstream): outstream_high.close() if (outstream_unmapped and (outstream_unmapped != outstream) and (outstream_unmapped != outstream_high)): outstream_unmapped.close() if out_stats_stream: out_stats_stream.close() def fetchadd(key, mydict): key = key.strip() if key not in mydict: mydict[key] = len(mydict) return mydict[key] def ar(mylist, val): return np.array(mylist, dtype={8: np.int8, 16: np.int16, 32: np.int32}[val]) def _filterbycov(c1_in, p1_in, c2_in, p2_in, max_dist, method): """ This is a slow version of the filtering code used for testing purposes only Use cythonized version in the future!! """ c1 = np.asarray(c1_in,dtype=int) p1 = np.asarray(p1_in,dtype=int) c2 = np.asarray(c2_in,dtype=int) p2 = np.asarray(p2_in,dtype=int) M = np.r_[np.c_[c1,p1],np.c_[c2,p2]] # M is a table of (chrom, pos) with 2*N rows assert (c1.shape[0] == c2.shape[0]) N = 2*c1.shape[0] ind_sorted = np.lexsort((M[:,1],M[:,0])) # sort by chromosomes, then positions # M[ind_sorted] # ind_sorted # M, M[ind_sorted] if (method == 'sum'): proximity_count = np.zeros(N) # keeps track of how many molecules each framgent end is close to elif (method == 'max'): proximity_count = np.zeros(N) else: raise ValueError('Unknown method: {}'.format(method)) low = 0 high = 1 while True: # boundary case finish if low == N: break # boundary case - CHECK if high == N: low += 1 high = low + 1 continue # check if "high" is proximal enough to "low" # first, if chromosomes not equal, we have gone too far, and the positions are not proximal if M[ind_sorted[low],0] != M[ind_sorted[high],0]: low += 1 high = low + 1 # restart high continue # next, if positions are not proximal, increase low, and continue elif np.abs(M[ind_sorted[high],1] - M[ind_sorted[low],1]) > max_dist: low += 1 high = low + 1 # restart high continue # if on the same chromosome, and the distance is "proximal enough", add to count of both "low" and "high" positions else: proximity_count[low] += 1 proximity_count[high] += 1 high += 1 # unsort proximity count #proximity_count = proximity_count[ind_sorted] proximity_count[ind_sorted] = np.copy(proximity_count) #print(M) #print(proximity_count) # if method is sum of pairs if method == 'sum': pcounts = proximity_count[0:N//2] + proximity_count[N//2:] + 1 elif method == 'max': pcounts = np.maximum(proximity_count[0:N//2]+1, proximity_count[N//2:]+1) else: raise ValueError('Unknown method: {}'.format(method)) return pcounts def streaming_filterbycov( method, max_dist, max_cov, sep, c1ind, c2ind, p1ind, p2ind, s1ind, s2ind, unmapped_chrom, instream, outstream, outstream_high, outstream_unmapped, out_stat, mark_multi): # doing everything in memory maxind = max(c1ind, c2ind, p1ind, p2ind, s1ind, s2ind) # if we do stats in the dedup, we need PAIR_TYPE # i do not see way around this: if out_stat: ptind = _pairsam_format.COL_PTYPE maxind = max(maxind, ptind) c1 = []; c2 = []; p1 = []; p2 = []; s1 = []; s2 = [] line_buffer = [] cols_buffer = [] chromDict = {} strandDict = {} n_unmapped = 0 n_high = 0 n_low = 0 instream = iter(instream) while True: rawline = next(instream, None) stripline = rawline.strip() if rawline else None # take care of empty lines not at the end of the file separately if rawline and (not stripline): warnings.warn("Empty line detected not at the end of the file") continue if stripline: cols = stripline.split(sep) if len(cols) <= maxind: raise ValueError( "Error parsing line {}: ".format(stripline) + " expected {} columns, got {}".format(maxind, len(cols))) if ((cols[c1ind] == unmapped_chrom) or (cols[c2ind] == unmapped_chrom)): if outstream_unmapped: outstream_unmapped.write(stripline) # don't forget terminal newline outstream_unmapped.write("\n") # add a pair to PairCounter if stats output is requested: if out_stat: out_stat.add_pair(cols[c1ind], int(cols[p1ind]), cols[s1ind], cols[c2ind], int(cols[p2ind]), cols[s2ind], cols[ptind]) else: line_buffer.append(stripline) cols_buffer.append(cols) c1.append(fetchadd(cols[c1ind], chromDict)) c2.append(fetchadd(cols[c2ind], chromDict)) p1.append(int(cols[p1ind])) p2.append(int(cols[p2ind])) s1.append(fetchadd(cols[s1ind], strandDict)) s2.append(fetchadd(cols[s2ind], strandDict)) else: # when everything is loaded in memory... res = _filterbycov(c1, p1, c2, p2, max_dist, method) for i in range(len(res)): # not high-frequency interactor pairs: if not res[i] > max_cov: outstream.write(line_buffer[i]) # don't forget terminal newline outstream.write("\n") if out_stat: out_stat.add_pair(cols_buffer[i][c1ind], int(cols_buffer[i][p1ind]), cols_buffer[i][s1ind], cols_buffer[i][c2ind], int(cols_buffer[i][p2ind]), cols_buffer[i][s2ind], cols_buffer[i][ptind]) # high-frequency interactor pairs: else: if out_stat: out_stat.add_pair(cols_buffer[i][c1ind], int(cols_buffer[i][p1ind]), cols_buffer[i][s1ind], cols_buffer[i][c2ind], int(cols_buffer[i][p2ind]), cols_buffer[i][s2ind], 'FF' ) if outstream_high: outstream_high.write( # FF-marked pair: sep.join(mark_split_pair_as_dup(cols_buffer[i])) if mark_multi # pair as is: else line_buffer[i] ) # don't forget terminal newline outstream_high.write('\n') # flush buffers and perform necessary checks here: c1 = []; c2 = []; p1 = []; p2 = []; s1 = []; s2 = [] line_buffer = line_buffer[len(res):] cols_buffer = cols_buffer[len(res):] if not stripline: if(len(line_buffer) != 0): raise ValueError( "{} lines left in the buffer, ".format(len(line_buffer)) + "should be none;" + "something went terribly wrong") break break if __name__ == '__main__': filterbycov() pairtools-0.3.0/pairtools/pairtools_flip.py000066400000000000000000000077501345765554600211770ustar00rootroot00000000000000import sys import click from . import _fileio, _pairsam_format, cli, _headerops, common_io_options UTIL_NAME = 'pairtools_flip' @cli.command() @click.argument( 'pairs_path', type=str, required=False) @click.option( "-c", "--chroms-path", type=str, required=True, help='Chromosome order used to flip interchromosomal mates: ' 'path to a chromosomes file (e.g. UCSC chrom.sizes or similar) whose ' 'first column lists scaffold names. Any scaffolds not listed will be ' 'ordered lexicographically following the names provided.') @click.option( '-o', "--output", type=str, default="", help='output file.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, the output is printed into stdout.') @common_io_options def flip( pairs_path, chroms_path, output, **kwargs ): '''Flip pairs to get an upper-triangular matrix. Change the order of side1 and side2 in pairs, such that (order(chrom1) < order(chrom2) or (order(chrom1) == order(chrom2)) and (pos1 <=pos2)) Equivalent to reflecting the lower triangle of a Hi-C matrix onto its upper triangle, resulting in an upper triangular matrix. The order of chromosomes must be provided via a .chromsizes file. PAIRS_PATH : input .pairs/.pairsam file. If the path ends with .gz or .lz4, the input is decompressed by pbgzip/lz4c. By default, the input is read from stdin. ''' flip_py( pairs_path, chroms_path, output, **kwargs ) def flip_py( pairs_path, chroms_path, output, **kwargs ): instream = (_fileio.auto_open(pairs_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairs_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) chromosomes = _headerops.get_chrom_order(chroms_path) chrom_enum = dict(zip([_pairsam_format.UNMAPPED_CHROM] + list(chromosomes), range(len(chromosomes)+1))) header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) outstream.writelines((l+'\n' for l in header)) column_names = _headerops.extract_column_names(header) if len(column_names) == 0: column_names = _pairsam_format.COLUMNS chrom1_col = column_names.index('chrom1') chrom2_col = column_names.index('chrom2') pos1_col = column_names.index('pos1') pos2_col = column_names.index('pos2') pair_type_col = (column_names.index('pair_type') if 'pair_type' in column_names else -1) col_pairs_to_flip = [ (column_names.index(col), column_names.index(col[:-1]+'2')) for col in column_names if col.endswith('1') and (col[:-1]+'2') in column_names] for line in body_stream: cols = line.rstrip().split(_pairsam_format.PAIRSAM_SEP) has_correct_order = ( (chrom_enum[cols[chrom1_col]], int(cols[pos1_col])) <= (chrom_enum[cols[chrom2_col]], int(cols[pos2_col])) ) if not has_correct_order: for col1, col2 in col_pairs_to_flip: if (col1 < len(cols)) and (col2 < len(cols)): cols[col1], cols[col2] = cols[col2], cols[col1] if pair_type_col != -1 and pair_type_col < len(cols): cols[pair_type_col] = ( cols[pair_type_col][1] + cols[pair_type_col][0]) outstream.write(_pairsam_format.PAIRSAM_SEP.join(cols)) outstream.write('\n') if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() if __name__ == '__main__': pair() pairtools-0.3.0/pairtools/pairtools_markasdup.py000066400000000000000000000064241345765554600222310ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- import sys import pipes import click from . import _fileio, _pairsam_format, cli, _headerops, common_io_options UTIL_NAME = 'pairtools_markasdup' @cli.command() @click.argument( 'pairsam_path', type=str, required=False) @click.option( "-o", "--output", type=str, default="", help='output .pairsam file.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, the output is printed into stdout.') @common_io_options def markasdup(pairsam_path, output, **kwargs): '''Tag pairs as duplicates. Change the type of all pairs inside a .pairs/.pairsam file to DD. If sam entries are present, change the pair type in the Yt SAM tag to 'Yt:Z:DD'. PAIRSAM_PATH : input .pairs/.pairsam file. If the path ends with .gz, the input is gzip-decompressed. By default, the input is read from stdin. ''' markasdup_py(pairsam_path, output, **kwargs) def markasdup_py(pairsam_path, output, **kwargs): instream = (_fileio.auto_open(pairsam_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairsam_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) outstream.writelines((l+'\n' for l in header)) for line in body_stream: cols = line.rstrip().split(_pairsam_format.PAIRSAM_SEP) mark_split_pair_as_dup(cols) outstream.write(_pairsam_format.PAIRSAM_SEP.join(cols)) outstream.write('\n') if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() def mark_split_pair_as_dup(cols): # if the original columns ended with a new line, the marked columns # should as well. original_has_newline = cols[-1].endswith('\n') cols[_pairsam_format.COL_PTYPE] = 'DD' if (len(cols) > _pairsam_format.COL_SAM1) and (len(cols) > _pairsam_format.COL_SAM2): for i in (_pairsam_format.COL_SAM1, _pairsam_format.COL_SAM2): # split each sam column into sam entries, tag and assemble back cols[i] = _pairsam_format.INTER_SAM_SEP.join( [mark_sam_as_dup(sam) for sam in cols[i].split(_pairsam_format.INTER_SAM_SEP) ]) if original_has_newline and not cols[-1].endswith('\n'): cols[-1] = cols[-1]+'\n' return cols def mark_sam_as_dup(sam): '''Tag the binary flag and the optional pair type field of a sam entry as a PCR duplicate.''' samcols = sam.split(_pairsam_format.SAM_SEP) if len(samcols) == 1: return sam samcols[1] = str(int(samcols[1]) | 1024) for j in range(11, len(samcols)): if samcols[j].startswith('Yt:Z:'): samcols[j] = 'Yt:Z:DD' return _pairsam_format.SAM_SEP.join(samcols) if __name__ == '__main__': markasdup() pairtools-0.3.0/pairtools/pairtools_merge.py000066400000000000000000000144721345765554600213430ustar00rootroot00000000000000#!/usr/bin/env python import sys import glob import math import subprocess import click from . import _fileio, _pairsam_format, _headerops, cli UTIL_NAME = 'pairtools_merge' @cli.command() @click.argument( 'pairs_path', nargs=-1, type=str, ) @click.option( "-o", "--output", type=str, default="", help='output file.' ' If the path ends with .gz/.lz4, the output is compressed by pbgzip/lz4c.' ' By default, the output is printed into stdout.') @click.option( "--max-nmerge", type=int, default=8, show_default=True, help='The maximal number of inputs merged at once. For more, store ' 'merged intermediates in temporary files.' ) @click.option( "--tmpdir", type=str, default='', help='Custom temporary folder for merged intermediates.' ) @click.option( "--memory", type=str, default='2G', show_default=True, help='The amount of memory used by default.', ) @click.option( "--compress-program", type=str, default='', show_default=True, help='A binary to compress temporary merged chunks. ' 'Must decompress input when the flag -d is provided. ' 'Suggested alternatives: lz4c, gzip, lzop, snzip. ' 'NOTE: fails silently if the command syntax is wrong. ' ) @click.option( "--nproc", type=int, default=8, help='Number of threads for merging.', show_default=True, ) @click.option( '--nproc-in', type=int, default=1, show_default=True, help='Number of processes used by the auto-guessed input decompressing command.' ) @click.option( '--nproc-out', type=int, default=8, show_default=True, help='Number of processes used by the auto-guessed output compressing command.' ) @click.option( '--cmd-in', type=str, default=None, help='A command to decompress the input. ' 'If provided, fully overrides the auto-guessed command. ' 'Does not work with stdin. ' 'Must read input from stdin and print output into stdout. ' 'EXAMPLE: pbgzip -dc -n 3' ) @click.option( '--cmd-out', type=str, default=None, help='A command to compress the output. ' 'If provided, fully overrides the auto-guessed command. ' 'Does not work with stdout. ' 'Must read input from stdin and print output into stdout. ' 'EXAMPLE: pbgzip -c -n 8' ) # Using custom IO options def merge(pairs_path, output, max_nmerge, tmpdir, memory, compress_program, nproc, **kwargs): """Merge sorted .pairs/.pairsam files. Merge triu-flipped sorted pairs/pairsam files. If present, the @SQ records of the SAM header must be identical; the sorting order of these lines is taken from the first file in the list. The ID fields of the @PG records of the SAM header are modified with a numeric suffix to produce unique records. The other unique SAM and non-SAM header lines are copied into the output header. PAIRS_PATH : upper-triangular flipped sorted .pairs/.pairsam files to merge or a group/groups of .pairs/.pairsam files specified by a wildcard. For paths ending in .gz/.lz4, the files are decompressed by pbgzip/lz4c. """ merge_py(pairs_path, output, max_nmerge, tmpdir, memory, compress_program, nproc, **kwargs) def merge_py(pairs_path, output, max_nmerge, tmpdir, memory, compress_program, nproc, **kwargs): paths = sum([glob.glob(mask) for mask in pairs_path], []) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) # if there is only one input, bypass merging and do not modify the header if len(paths) == 1: instream = _fileio.auto_open(paths[0], mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) for line in instream: outstream.write(line) if outstream != sys.stdout: outstream.close() return headers = [] for path in paths: f = _fileio.auto_open(path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) h, _ = _headerops.get_header(f) headers.append(h) f.close() merged_header = _headerops.merge_headers(headers) merged_header = _headerops.append_new_pg( merged_header, ID=UTIL_NAME, PN=UTIL_NAME) outstream.writelines((l+'\n' for l in merged_header)) outstream.flush() command = r''' /bin/bash -c 'export LC_COLLATE=C; export LANG=C; sort -k {0},{0} -k {1},{1} -k {2},{2}n -k {3},{3}n -k {4},{4} --merge --field-separator=$'\''{5}'\'' {6} {7} {8} -S {9} {10} '''.replace('\n',' ').format( _pairsam_format.COL_C1+1, _pairsam_format.COL_C2+1, _pairsam_format.COL_P1+1, _pairsam_format.COL_P2+1, _pairsam_format.COL_PTYPE+1, _pairsam_format.PAIRSAM_SEP_ESCAPE, ' --parallel={} '.format(nproc) if nproc > 1 else ' ', ' --batch-size={} '.format(max_nmerge) if max_nmerge else ' ', ' --temporary-directory={} '.format(tmpdir) if tmpdir else ' ', memory, (' --compress-program={} '.format(compress_program) if compress_program else ' '), ) for path in paths: if kwargs.get('cmd_in', None): command += r''' <(cat {} | {} | sed -n -e '\''/^[^#]/,$p'\'')'''.format(path, kwargs['cmd_in']) elif path.endswith('.gz'): command += r''' <(pbgzip -dc -n {} {} | sed -n -e '\''/^[^#]/,$p'\'')'''.format(kwargs['nproc_in'], path) elif path.endswith('.lz4'): command += r''' <(lz4c -dc {} | sed -n -e '\''/^[^#]/,$p'\'')'''.format(path) else: command += r''' <(sed -n -e '\''/^[^#]/,$p'\'' {})'''.format(path) command += "'" subprocess.check_call(command, shell=True, stdout=outstream) if outstream != sys.stdout: outstream.close() if __name__ == '__main__': merge() pairtools-0.3.0/pairtools/pairtools_parse.py000066400000000000000000000737061345765554600213630ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- from collections import OrderedDict import subprocess import fileinput import itertools import click import pipes import sys import os import io from . import _fileio, _pairsam_format, _headerops, cli, common_io_options from .pairtools_stats import PairCounter UTIL_NAME = 'pairtools_parse' EXTRA_COLUMNS = [ 'mapq', 'pos5', 'pos3', 'cigar', 'read_len', 'matched_bp', 'algn_ref_span', 'algn_read_span', 'dist_to_5', 'dist_to_3', 'seq' ] @cli.command() @click.argument( 'sam_path', type=str, required=False) @click.option( "-c", "--chroms-path", type=str, required=True, help='Chromosome order used to flip interchromosomal mates: ' 'path to a chromosomes file (e.g. UCSC chrom.sizes or similar) whose ' 'first column lists scaffold names. Any scaffolds not listed will be ' 'ordered lexicographically following the names provided.') @click.option( "-o", "--output", type=str, default="", help='output file. ' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4-compressed.' 'By default, the output is printed into stdout. ') @click.option( "--assembly", type=str, help='Name of genome assembly (e.g. hg19, mm10) to store in the pairs header.') @click.option( "--min-mapq", type=int, default=1, show_default=True, help='The minimal MAPQ score to consider a read as uniquely mapped') @click.option( "--max-molecule-size", type=int, default=2000, show_default=True, help='The maximal size of a Hi-C molecule; used to rescue single ligations' 'from molecules with three alignments.') @click.option( "--drop-readid", is_flag=True, help='If specified, do not add read ids to the output') @click.option( "--drop-seq", is_flag=True, help='If specified, remove sequences and PHREDs from the sam fields') @click.option( "--drop-sam", is_flag=True, help='If specified, do not add sams to the output') @click.option( "--add-columns", type=click.STRING, default='', help='Report extra columns describing alignments ' 'Possible values (can take multiple values as a comma-separated ' 'list): a SAM tag (any pair of uppercase letters) or {}.'.format( ', '.join(EXTRA_COLUMNS))) @click.option( "--output-parsed-alignments", type=str, default="", help='output file for all parsed alignments, including walks.' ' Useful for debugging and rnalysis of walks.' ' If file exists, it will be open in the append mode.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4-compressed.' ' By default, not used.' ) @click.option( "--output-stats", type=str, default="", help='output file for various statistics of pairs file. ' ' By default, statistics is not generated.') @click.option( '--report-alignment-end', type=click.Choice(['5', '3']), default='5', help='specifies whether the 5\' or 3\' end of the alignment is reported as' ' the position of the Hi-C read.') @click.option( '--max-inter-align-gap', type=int, default=20, show_default=True, help='read segments that are not covered by any alignment and' ' longer than the specified value are treated as "null" alignments.' ' These null alignments convert otherwise linear alignments into walks,' ' and affect how they get reported as a Hi-C pair (see --walks-policy).' ) @click.option( "--walks-policy", type=click.Choice(['mask', 'all', '5any', '5unique', '3any', '3unique']), default='mask', help='the policy for reporting unrescuable walks (reads containing more' ' than one alignment on one or both sides, that can not be explained by a' ' single ligation between two mappable DNA fragments).' ' "mask" - mask walks (chrom="!", pos=0, strand="-"); ' ' "all" - report all pairs of consecutive alignments [NOT IMPLEMENTED]; ' ' "5any" - report the 5\'-most alignment on each side;' ' "5unique" - report the 5\'-most unique alignment on each side, if present;' ' "3any" - report the 3\'-most alignment on each side;' ' "3unique" - report the 3\'-most unique alignment on each side, if present.', show_default=True ) @click.option( "--no-flip", is_flag=True, help='If specified, do not flip pairs in genomic order and instead preserve ' 'the order in which they were sequenced.') @common_io_options def parse(sam_path, chroms_path, output, assembly, min_mapq, max_molecule_size, drop_readid, drop_seq, drop_sam, add_columns, output_parsed_alignments, output_stats, **kwargs): '''Find ligation junctions in .sam, make .pairs. SAM_PATH : an input .sam/.bam file with paired-end sequence alignments of Hi-C molecules. If the path ends with .bam, the input is decompressed from bam with samtools. By default, the input is read from stdin. ''' parse_py(sam_path, chroms_path, output, assembly, min_mapq, max_molecule_size, drop_readid, drop_seq, drop_sam, add_columns, output_parsed_alignments, output_stats, **kwargs) def parse_py(sam_path, chroms_path, output, assembly, min_mapq, max_molecule_size, drop_readid, drop_seq, drop_sam, add_columns, output_parsed_alignments, output_stats, **kwargs): instream = (_fileio.auto_open(sam_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if sam_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) out_alignments_stream = (_fileio.auto_open(output_parsed_alignments, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output_parsed_alignments else None) out_stats_stream = (_fileio.auto_open(output_stats, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output_stats else None) if out_alignments_stream: out_alignments_stream.write('readID\tside\tchrom\tpos\tstrand\tmapq\tcigar\tdist_5_lo\tdist_5_hi\tmatched_bp\n') # generate empty PairCounter if stats output is requested: out_stat = PairCounter() if output_stats else None samheader, body_stream = _headerops.get_header(instream, comment_char='@') sam_chromsizes = _headerops.get_chromsizes_from_sam_header(samheader) chromosomes = _headerops.get_chrom_order( chroms_path, list(sam_chromsizes.keys())) add_columns = [col for col in add_columns.split(',') if col] for col in add_columns: if not( (col in EXTRA_COLUMNS) or (len(col) == 2 and col.isupper())): raise Exception('{} is not a valid extra column'.format(col)) columns = (_pairsam_format.COLUMNS + ([c+side for c in add_columns for side in ['1', '2']]) ) if drop_sam: columns.pop(columns.index('sam1')) columns.pop(columns.index('sam2')) header = _headerops.make_standard_pairsheader( assembly = assembly, chromsizes = [(chrom, sam_chromsizes[chrom]) for chrom in chromosomes], columns = columns, shape = 'whole matrix' if kwargs['no_flip'] else 'upper triangle' ) header = _headerops.insert_samheader(header, samheader) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) outstream.writelines((l+'\n' for l in header)) streaming_classify(body_stream, outstream, chromosomes, min_mapq, max_molecule_size, drop_readid, drop_seq, drop_sam, add_columns, out_alignments_stream, out_stat, **kwargs) # save statistics to a file if it was requested: if out_stat: out_stat.save(out_stats_stream) if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() # close optional output streams if needed: if out_alignments_stream: out_alignments_stream.close() if out_stats_stream: out_stats_stream.close() def parse_cigar(cigar): matched_bp = 0 algn_ref_span = 0 algn_read_span = 0 read_len = 0 clip5_ref = 0 clip3_ref = 0 if cigar != '*': cur_num = 0 for char in cigar: charval = ord(char) if charval >= 48 and charval <= 57: cur_num = cur_num * 10 + (charval - 48) else: if char == 'M': matched_bp += cur_num algn_ref_span += cur_num algn_read_span += cur_num read_len += cur_num elif char == 'I': algn_read_span += cur_num read_len += cur_num elif char == 'D': algn_ref_span += cur_num elif char == 'S' or char == 'H': read_len += cur_num if matched_bp == 0: clip5_ref = cur_num else: clip3_ref = cur_num cur_num = 0 return { 'clip5_ref': clip5_ref, 'clip3_ref': clip3_ref, 'cigar': cigar, 'algn_ref_span': algn_ref_span, 'algn_read_span': algn_read_span, 'read_len': read_len, 'matched_bp': matched_bp, } def empty_alignment(): return { 'chrom': _pairsam_format.UNMAPPED_CHROM, 'pos5': _pairsam_format.UNMAPPED_POS, 'pos3': _pairsam_format.UNMAPPED_POS, 'pos': _pairsam_format.UNMAPPED_POS, 'strand': _pairsam_format.UNMAPPED_STRAND, 'dist_to_5': 0, 'dist_to_3': 0, 'mapq': 0, 'is_unique': False, 'is_mapped': False, 'is_linear': True, 'cigar' : '*', 'algn_ref_span': 0, 'algn_read_span': 0, 'matched_bp': 0, 'clip3_ref': 0, 'clip5_ref': 0, 'read_len': 0, 'type':'N' } def parse_algn( samcols, min_mapq, report_3_alignment_end=False, sam_tags=None, store_seq=False): is_mapped = (int(samcols[1]) & 0x04) == 0 mapq = int(samcols[4]) is_unique = (mapq >= min_mapq) is_linear = not any([col.startswith('SA:Z:') for col in samcols[11:]]) cigar = parse_cigar(samcols[5]) if is_mapped: if ((int(samcols[1]) & 0x10) == 0): strand = '+' dist_to_5 = cigar['clip5_ref'] dist_to_3 = cigar['clip3_ref'] else: strand = '-' dist_to_5 = cigar['clip3_ref'] dist_to_3 = cigar['clip5_ref'] if is_unique: chrom = samcols[2] if strand == '+': pos5 = int(samcols[3]) pos3 = int(samcols[3]) + cigar['algn_ref_span'] - 1 else: pos5 = int(samcols[3]) + cigar['algn_ref_span'] - 1 pos3 = int(samcols[3]) else: chrom = _pairsam_format.UNMAPPED_CHROM strand = _pairsam_format.UNMAPPED_STRAND pos5 = _pairsam_format.UNMAPPED_POS pos3 = _pairsam_format.UNMAPPED_POS else: chrom = _pairsam_format.UNMAPPED_CHROM strand = _pairsam_format.UNMAPPED_STRAND pos5 = _pairsam_format.UNMAPPED_POS pos3 = _pairsam_format.UNMAPPED_POS dist_to_5 = 0 dist_to_3 = 0 algn = { 'chrom': chrom, 'pos5': pos5, 'pos3': pos3, 'strand': strand, 'mapq': mapq, 'is_mapped': is_mapped, 'is_unique': is_unique, 'is_linear': is_linear, 'dist_to_5': dist_to_5, 'dist_to_3': dist_to_3, 'type': ('N' if not is_mapped else ('M' if not is_unique else 'U')) } algn.update(cigar) algn['pos'] = algn['pos3'] if report_3_alignment_end else algn['pos5'] if sam_tags: for tag in sam_tags: algn[tag] = '' for col in samcols[11:]: for tag in sam_tags: if col.startswith(tag+':'): algn[tag] = col[5:] continue if store_seq: algn['seq'] = samcols[9] return algn def rescue_walk(algns1, algns2, max_molecule_size): """ Rescue a single ligation that appears as a walk. Checks if a molecule with three alignments could be formed via a single ligation between two fragments, where one fragment was so long that it got sequenced on both sides. Uses three criteria: a) the 3'-end alignment on one side maps to the same chromosome as the alignment fully covering the other side (i.e. the linear alignment) b) the two alignments point towards each other on the chromosome c) the distance between the outer ends of the two alignments is below the specified threshold. Alternatively, a single ligation get rescued when the 3' sub-alignment maps to multiple locations or no locations at all. In the case of a successful rescue, tags the 3' sub-alignment with type='X' and the linear alignment on the other side with type='R'. Returns ------- linear_side : int If the case of a successful rescue, returns the index of the side with a linear alignment. """ # If both sides have one alignment or none, no need to rescue! n_algns1 = len(algns1) n_algns2 = len(algns2) if (n_algns1 <= 1) and (n_algns2 <= 1): return None # Can rescue only pairs with one chimeric alignment with two parts. if not ( ((n_algns1 == 1) and (n_algns2 == 2)) or ((n_algns1 == 2) and (n_algns2 == 1)) ): return None first_read_is_chimeric = n_algns1 > 1 chim5_algn = algns1[0] if first_read_is_chimeric else algns2[0] chim3_algn = algns1[1] if first_read_is_chimeric else algns2[1] linear_algn = algns2[0] if first_read_is_chimeric else algns1[0] # the linear alignment must be uniquely mapped if not(linear_algn['is_mapped'] and linear_algn['is_unique']): return None can_rescue = True # we automatically rescue chimeric alignments with null and non-unique # alignments at the 3' side if (chim3_algn['is_mapped'] and chim5_algn['is_unique']): # 1) in rescued walks, the 3' alignment of the chimeric alignment must be on # the same chromosome as the linear alignment on the opposite side of the # molecule can_rescue &= (chim3_algn['chrom'] == linear_algn['chrom']) # 2) in rescued walks, the 3' supplemental alignment of the chimeric # alignment and the linear alignment on the opposite side must point # towards each other can_rescue &= (chim3_algn['strand'] != linear_algn['strand']) if linear_algn['strand'] == '+': can_rescue &= (linear_algn['pos5'] < chim3_algn['pos5']) else: can_rescue &= (linear_algn['pos5'] > chim3_algn['pos5']) # 3) in single ligations appearing as walks, we can infer the size of # the molecule and this size must be smaller than the maximal size of # Hi-C molecules after the size selection step of the Hi-C protocol if linear_algn['strand'] == '+': molecule_size = ( chim3_algn['pos5'] - linear_algn['pos5'] + chim3_algn['dist_to_5'] + linear_algn['dist_to_5'] ) else: molecule_size = ( linear_algn['pos5'] - chim3_algn['pos5'] + chim3_algn['dist_to_5'] + linear_algn['dist_to_5'] ) can_rescue &= (molecule_size <= max_molecule_size) if can_rescue: if first_read_is_chimeric: # changing the type of the 3' alignment on side 1, does not show up # in the output algns1[1]['type'] = 'X' algns2[0]['type'] = 'R' return 2 else: algns1[0]['type'] = 'R' # changing the type of the 3' alignment on side 2, does not show up # in the output algns2[1]['type'] = 'X' return 1 else: return None def _convert_gaps_into_alignments(sorted_algns, max_inter_align_gap): if (len(sorted_algns) == 1) and (not sorted_algns[0]['is_mapped']): return last_5_pos = 0 for i in range(len(sorted_algns)): algn = sorted_algns[i] if (algn['dist_to_5'] - last_5_pos > max_inter_align_gap): new_algn = empty_alignment() new_algn['dist_to_5'] = last_5_pos new_algn['algn_read_span'] = algn['dist_to_5'] - last_5_pos new_algn['read_len'] = algn['read_len'] new_algn['dist_to_3'] = new_algn['read_len'] - algn['dist_to_5'] last_5_pos = algn['dist_to_5'] + algn['algn_read_span'] sorted_algns.insert(i, new_algn) i += 2 else: last_5_pos = max(last_5_pos, algn['dist_to_5'] + algn['algn_read_span']) i += 1 def _mask_alignment(algn): """ Reset the coordinates of an alignment. """ algn['chrom'] = _pairsam_format.UNMAPPED_CHROM algn['pos5'] = _pairsam_format.UNMAPPED_POS algn['pos3'] = _pairsam_format.UNMAPPED_POS algn['pos'] = _pairsam_format.UNMAPPED_POS algn['strand'] = _pairsam_format.UNMAPPED_STRAND return algn def parse_sams_into_pair(sams1, sams2, min_mapq, max_molecule_size, max_inter_align_gap, walks_policy, report_3_alignment_end, sam_tags, store_seq): """ Parse sam entries corresponding to a Hi-C molecule into alignments for a Hi-C pair. Returns ------- algn1, algn2: dict Two alignments selected for reporting as a Hi-C pair. algns1, algns2 All alignments, sorted according to their order in on a read. """ # Check if there is at least one SAM entry per side: if (len(sams1) == 0) or (len(sams2) == 0): algns1 = [empty_alignment()] algns2 = [empty_alignment()] algns1[0]['type'] = 'X' algns2[0]['type'] = 'X' return algns1[0], algns2[0], algns1, algns2 # Generate a sorted, gap-filled list of all alignments algns1 = [parse_algn(sam.rstrip().split('\t'), min_mapq, report_3_alignment_end, sam_tags, store_seq) for sam in sams1] algns2 = [parse_algn(sam.rstrip().split('\t'), min_mapq, report_3_alignment_end, sam_tags, store_seq) for sam in sams2] algns1 = sorted(algns1, key=lambda algn: algn['dist_to_5']) algns2 = sorted(algns2, key=lambda algn: algn['dist_to_5']) if max_inter_align_gap is not None: _convert_gaps_into_alignments(algns1, max_inter_align_gap) _convert_gaps_into_alignments(algns2, max_inter_align_gap) # Define the type of alignment on each side. # The most important split is between chimeric alignments and linear # alignments. is_chimeric_1 = len(algns1) > 1 is_chimeric_2 = len(algns2) > 1 hic_algn1 = algns1[0] hic_algn2 = algns2[0] # Parse chimeras rescued_linear_side = None if is_chimeric_1 or is_chimeric_2: # Pick two alignments to report as a Hi-C pair. rescued_linear_side = rescue_walk(algns1, algns2, max_molecule_size) # if the walk is unrescueable: if rescued_linear_side is None: if walks_policy == 'mask': if is_chimeric_1 or is_chimeric_2: hic_algn1 = _mask_alignment(dict(hic_algn1)) hic_algn2 = _mask_alignment(dict(hic_algn2)) hic_algn1['type'] = 'W' hic_algn2['type'] = 'W' elif walks_policy == '5any': hic_algn1 = algns1[0] hic_algn2 = algns2[0] elif walks_policy == '5unique': hic_algn1 = algns1[0] for algn in algns1: if algn['is_mapped'] and algn['is_unique']: hic_algn1 = algn break hic_algn2 = algns2[0] for algn in algns2: if algn['is_mapped'] and algn['is_unique']: hic_algn2 = algn break elif walks_policy == '3any': hic_algn1 = algns1[-1] hic_algn2 = algns2[-1] elif walks_policy == '3unique': hic_algn1 = algns1[-1] for algn in algns1[::-1]: if algn['is_mapped'] and algn['is_unique']: hic_algn1 = algn break hic_algn2 = algns2[-1] for algn in algns2[::-1]: if algn['is_mapped'] and algn['is_unique']: hic_algn2 = algn break elif walks_policy == 'all': # TO BE IMPLEMENTED pass # lower-case reported walks on the chimeric side if walks_policy != 'mask': if is_chimeric_1: hic_algn1 = dict(hic_algn1) hic_algn1['type'] = hic_algn1['type'].lower() if is_chimeric_2: hic_algn2 = dict(hic_algn2) hic_algn2['type'] = hic_algn2['type'].lower() return hic_algn1, hic_algn2, algns1, algns2 def check_pair_order(algn1, algn2, chrom_enum): ''' Check if a pair of alignments has the upper-triangular order or has to be flipped. ''' # First, the pair is flipped according to the type of mapping on its sides. # Later, we will check it is mapped on both sides and, if so, flip the sides # according to these coordinates. has_correct_order = ( (algn1['is_mapped'], algn1['is_unique']) <= (algn2['is_mapped'], algn2['is_unique']) ) # If a pair has coordinates on both sides, it must be flipped according to # its genomic coordinates. if ((algn1['chrom'] != _pairsam_format.UNMAPPED_CHROM) and (algn2['chrom'] != _pairsam_format.UNMAPPED_CHROM)): has_correct_order = ( (chrom_enum[algn1['chrom']], algn1['pos']) <= (chrom_enum[algn2['chrom']], algn2['pos'])) return has_correct_order def push_sam(line, drop_seq, sams1, sams2): """ """ sam = line.rstrip() if drop_seq: split_sam = sam.split('\t') split_sam[9] = '*' split_sam[10] = '*' sam = '\t'.join(split_sam) flag = split_sam[1] flag = int(flag) else: _, flag, _ = sam.split('\t', 2) flag = int(flag) if ((flag & 0x40) != 0): sams1.append(sam) else: sams2.append(sam) return def write_all_algnments(read_id, all_algns1, all_algns2, out_file): for side_idx, all_algns in enumerate((all_algns1, all_algns2)): out_file.write(read_id) out_file.write('\t') out_file.write(str(side_idx+1)) out_file.write('\t') for algn in sorted(all_algns, key=lambda x: x['dist_to_5']): out_file.write(algn['chrom']) out_file.write('\t') out_file.write(str(algn['pos5'])) out_file.write('\t') out_file.write(algn['strand']) out_file.write('\t') out_file.write(str(algn['mapq'])) out_file.write('\t') out_file.write(str(algn['cigar'])) out_file.write('\t') out_file.write(str(algn['dist_to_5'])) out_file.write('\t') out_file.write(str(algn['dist_to_5']+algn['algn_read_span'])) out_file.write('\t') out_file.write(str(algn['matched_bp'])) out_file.write('\t') out_file.write('\n') def write_pairsam( algn1, algn2, read_id, sams1, sams2, out_file, drop_readid, drop_sam, add_columns): """ SAM is already tab-separated and any printable character between ! and ~ may appear in the PHRED field! (http://www.ascii-code.com/) Thus, use the vertical tab character to separate fields! """ cols = [ '.' if drop_readid else read_id, algn1['chrom'], str(algn1['pos']), algn2['chrom'], str(algn2['pos']), algn1['strand'], algn2['strand'], algn1['type'] + algn2['type'] ] if not drop_sam: for sams in [sams1, sams2]: cols.append( _pairsam_format.INTER_SAM_SEP.join([ (sam.replace('\t', _pairsam_format.SAM_SEP) + _pairsam_format.SAM_SEP + 'Yt:Z:' + algn1['type'] + algn2['type']) for sam in sams ]) ) for col in add_columns: # use get b/c empty alignments would not have sam tags (NM, AS, etc) cols.append(str(algn1.get(col, ''))) cols.append(str(algn2.get(col, ''))) out_file.write(_pairsam_format.PAIRSAM_SEP.join(cols) + '\n') def streaming_classify(instream, outstream, chromosomes, min_mapq, max_molecule_size, drop_readid, drop_seq, drop_sam, add_columns, out_alignments_stream, out_stat, **kwargs): """ """ chrom_enum = dict(zip([_pairsam_format.UNMAPPED_CHROM] + list(chromosomes), range(len(chromosomes)+1))) sam_tags = [col for col in add_columns if len(col)==2 and col.isupper()] prev_read_id = '' sams1 = [] sams2 = [] line = '' store_seq = ('seq' in add_columns) instream = iter(instream) while line is not None: line = next(instream, None) read_id = line.split('\t', 1)[0] if line else None if not(line) or ((read_id != prev_read_id) and prev_read_id): algn1, algn2, all_algns1, all_algns2 = parse_sams_into_pair( sams1, sams2, min_mapq, max_molecule_size, kwargs['max_inter_align_gap'], kwargs['walks_policy'], kwargs['report_alignment_end']=='3', sam_tags, store_seq ) flip_pair = (not kwargs['no_flip']) and ( not check_pair_order(algn1, algn2, chrom_enum)) if flip_pair: algn1, algn2 = algn2, algn1 sams1, sams2 = sams2, sams1 write_pairsam( algn1, algn2, prev_read_id, sams1, sams2, outstream, drop_readid, drop_sam, add_columns) # add a pair to PairCounter if stats output is requested: if out_stat: out_stat.add_pair(algn1['chrom'], int(algn1['pos']), algn1['strand'], algn2['chrom'], int(algn2['pos']), algn2['strand'], algn1['type'] + algn2['type']) if out_alignments_stream: write_all_algnments(prev_read_id, all_algns1, all_algns2, out_alignments_stream) sams1.clear() sams2.clear() if line is not None: push_sam(line, drop_seq, sams1, sams2) prev_read_id = read_id if __name__ == '__main__': parse() def parse_alternative_algns(samcols): alt_algns = [] for col in samcols[11:]: if not col.startswith('XA:Z:'): continue for SA in col[5:].split(';'): if not SA: continue SAcols = SA.split(',') chrom = SAcols[0] strand = '-' if SAcols[1]<0 else '+' cigar = parse_cigar(SAcols[2]) NM = SAcols[3] pos = _pairsam_format.UNMAPPED_POS if strand == '+': pos = int(SAcols[1]) else: pos = int(SAcols[1]) + cigar['algn_ref_span'] alt_algns.append({ 'chrom': chrom, 'pos': pos, 'strand': strand, 'mapq': mapq, 'is_mapped': True, 'is_unique': False, 'is_linear': None, 'cigar': cigar, 'NM': NM, 'dist_to_5': cigar['clip5_ref'] if strand == '+' else cigar['clip3_ref'], }) return supp_algns #def parse_supp(samcols, min_mapq): # supp_algns = [] # for col in samcols[11:]: # if not col.startswith('SA:Z:'): # continue # # for SA in col[5:].split(';'): # if not SA: # continue # SAcols = SA.split(',') # mapq = int(SAcols[4]) # is_unique = (mapq >= min_mapq) # # chrom = SAcols[0] if is_unique else _pairsam_format.UNMAPPED_CHROM # strand = SAcols[2] if is_unique else _pairsam_format.UNMAPPED_STRAND # # cigar = parse_cigar(SAcols[3]) # # pos = _pairsam_format.UNMAPPED_POS # if is_unique: # if strand == '+': # pos = int(SAcols[1]) # else: # pos = int(SAcols[1]) + cigar['algn_ref_span'] # # supp_algns.append({ # 'chrom': chrom, # 'pos': pos, # 'strand': strand, # 'mapq': mapq, # 'is_mapped': True, # 'is_unique': is_unique, # 'is_linear': None, # 'cigar': cigar, # 'dist_to_5': cigar['clip5_ref'] if strand == '+' else cigar['clip3_ref'], # }) # # return supp_algns pairtools-0.3.0/pairtools/pairtools_phase.py000066400000000000000000000147131345765554600213420ustar00rootroot00000000000000import sys import click import re, fnmatch from . import _fileio, _pairsam_format, cli, _headerops, common_io_options UTIL_NAME = 'pairtools_phase' @cli.command() @click.argument( 'pairs_path', type=str, required=False) @click.option( '-o', "--output", type=str, default="", help='output file.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, the output is printed into stdout.') @click.option( "--phase-suffixes", nargs=2, #type=click.Tuple([str, str]), help='phase suffixes.' ) @click.option( "--clean-output", is_flag=True, help='drop all columns besides the standard ones and phase1/2' ) @common_io_options def phase( pairsam_path, output, phase_suffixes, clean_output, **kwargs ): '''Phase pairs mapped to a diploid genome. PAIRS_PATH : input .pairs/.pairsam file. If the path ends with .gz or .lz4, the input is decompressed by pbgzip/lz4c. By default, the input is read from stdin. ''' phase_py( pairs_path, output, phase_suffixes, clean_output, **kwargs ) def phase_py( pairs_path, output, phase_suffixes, clean_output, **kwargs ): instream = (_fileio.auto_open(pairsam_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairsam_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) old_column_names = _headerops.extract_column_names(header) if clean_output: new_column_names = [col for col in old_column_names if col in _pairsam_format.COLUMNS] new_column_idxs = [i for i,col in enumerate(old_column_names) if col in _pairsam_format.COLUMNS] + [ len(old_column_names), len(old_column_names)+1] else: new_column_names = list(old_column_names) new_column_names.append('phase1') new_column_names.append('phase2') header = _headerops._update_header_entry( header, 'columns', ' '.join(new_column_names)) if ( ('XB1' not in old_column_names) or ('XB2' not in old_column_names) or ('AS1' not in old_column_names) or ('AS2' not in old_column_names) or ('XS1' not in old_column_names) or ('XS2' not in old_column_names) ): raise ValueError( 'The input pairs file must be parsed with the flag --add-columns XB,AS,XS --min-mapq 0') COL_XB1 = old_column_names.index('XB1') COL_XB2 = old_column_names.index('XB2') COL_AS1 = old_column_names.index('AS1') COL_AS2 = old_column_names.index('AS2') COL_XS1 = old_column_names.index('XS1') COL_XS2 = old_column_names.index('XS2') outstream.writelines((l+'\n' for l in header)) def get_chrom_phase(chrom, phase_suffixes): if chrom.endswith(phase_suffixes[0]): return '0', chrom[:-len(phase_suffixes[0])] elif chrom.endswith(phase_suffixes[1]): return '1', chrom[:-len(phase_suffixes[1])] else: return '!', chrom def phase_side(chrom, XB, AS, XS, phase_suffixes): phase, chrom_base = get_chrom_phase(chrom, phase_suffixes) XBs = [i for i in XB.split(';') if len(i)>0] if AS > XS: return phase, chrom_base elif len(XBs) >= 1: if len(XBs) >= 2: alt2_chrom, alt2_pos, alt2_CIGAR, alt2_NM, alt2_AS = XBs[1].split(',') if alt2_AS == XS == AS: return '!', '!' alt_chrom, alt_pos, alt_CIGAR, alt_NM, alt_AS = XBs[0].split(',') alt_phase, alt_chrom_base = get_chrom_phase(alt_chrom, phase_suffixes) alt_is_homologue = ( (chrom_base == alt_chrom_base) and ( ((phase=='0') and (alt_phase=='1')) or ((phase=='1') and (alt_phase=='0')) ) ) if alt_is_homologue: return '.', chrom_base return '!', '!' for line in body_stream: cols = line.rstrip().split(_pairsam_format.PAIRSAM_SEP) cols.append('!') cols.append('!') pair_type = cols[_pairsam_format.COL_PTYPE] if cols[_pairsam_format.COL_C1] != _pairsam_format.UNMAPPED_CHROM: phase1, chrom_base1 = phase_side( cols[_pairsam_format.COL_C1], cols[COL_XB1], int(cols[COL_AS1]), int(cols[COL_XS1]), phase_suffixes ) cols[-2] = phase1 cols[_pairsam_format.COL_C1] = chrom_base1 if chrom_base1 == '!': cols[_pairsam_format.COL_C1] = _pairsam_format.UNMAPPED_CHROM cols[_pairsam_format.COL_P1] = str(_pairsam_format.UNMAPPED_POS) cols[_pairsam_format.COL_S1] = _pairsam_format.UNMAPPED_STRAND pair_type = 'M' + pair_type[1] if cols[_pairsam_format.COL_C2] != _pairsam_format.UNMAPPED_CHROM: phase2, chrom_base2 = phase_side( cols[_pairsam_format.COL_C2], cols[COL_XB2], int(cols[COL_AS2]), int(cols[COL_XS2]), phase_suffixes ) cols[-1] = phase2 cols[_pairsam_format.COL_C2] = chrom_base2 if chrom_base2 == '!': cols[_pairsam_format.COL_C2] = _pairsam_format.UNMAPPED_CHROM cols[_pairsam_format.COL_P2] = str(_pairsam_format.UNMAPPED_POS) cols[_pairsam_format.COL_S2] = _pairsam_format.UNMAPPED_STRAND pair_type = pair_type[0] + 'M' cols[_pairsam_format.COL_PTYPE] = pair_type if clean_output: cols = [cols[i] for i in new_column_idxs] outstream.write(_pairsam_format.PAIRSAM_SEP.join(cols)) outstream.write('\n') if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() if __name__ == '__main__': phase() pairtools-0.3.0/pairtools/pairtools_restrict.py000066400000000000000000000066371345765554600221070ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- import io import sys import click import subprocess import numpy as np from . import _fileio, _pairsam_format, cli, _headerops, common_io_options UTIL_NAME = 'pairtools_restrict' @cli.command() @click.argument( 'pairs_path', type=str, required=False) @click.option( '-f', '--frags', type=str, required=True, help='a tab-separated BED file with the positions of restriction fragments ' '(chrom, start, end). Can be generated using cooler digest.') @click.option( '-o', "--output", type=str, default="", help='output .pairs/.pairsam file.' ' If the path ends with .gz/.lz4, the output is compressed by pbgzip/lz4c.' ' By default, the output is printed into stdout.') @common_io_options def restrict(pairs_path, frags, output, **kwargs): '''Assign restriction fragments to pairs. Identify the restriction fragments that got ligated into a Hi-C molecule. PAIRS_PATH : input .pairs/.pairsam file. If the path ends with .gz/.lz4, the input is decompressed by pbgzip/lz4c. By default, the input is read from stdin. ''' restrict_py(pairs_path, frags, output, **kwargs) def restrict_py(pairs_path, frags, output, **kwargs): instream = (_fileio.auto_open(pairs_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairs_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) outstream.writelines((l+'\n' for l in header)) rfrags = np.genfromtxt( frags, delimiter='\t', comments='#', dtype=None, names=['chrom', 'start', 'end']) rfrags.sort(order=['chrom', 'start','end']) rfrags.sort(order=['chrom', 'start', 'end']) chrom_borders = np.r_[0, 1+np.where(rfrags['chrom'][:-1] != rfrags['chrom'][1:])[0], rfrags.shape[0]] rfrags = {rfrags['chrom'][i]:rfrags['end'][i:j] +1 for i, j in zip(chrom_borders[:-1], chrom_borders[1:])} for line in body_stream: cols = line.rstrip().split(_pairsam_format.PAIRSAM_SEP) chrom1, pos1 = cols[_pairsam_format.COL_C1], int(cols[_pairsam_format.COL_P1]) rfrag_idx1, rfrag_start1, rfrag_end1 = find_rfrag(rfrags, chrom1, pos1) chrom2, pos2 = cols[_pairsam_format.COL_C2], int(cols[_pairsam_format.COL_P2]) rfrag_idx2, rfrag_start2, rfrag_end2 = find_rfrag(rfrags, chrom2, pos2) cols += [str(rfrag_idx1), str(rfrag_start1), str(rfrag_end1)] cols += [str(rfrag_idx2), str(rfrag_start2), str(rfrag_end2)] outstream.write(_pairsam_format.PAIRSAM_SEP.join(cols)) outstream.write('\n') if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() def find_rfrag(rfrags, chrom, pos): rsites_chrom = rfrags[chrom.encode('ascii')] idx = min(max(0,rsites_chrom.searchsorted(pos, 'right')-1), len(rsites_chrom)-2) return idx, rsites_chrom[idx], rsites_chrom[idx+1] if __name__ == '__main__': restrict() pairtools-0.3.0/pairtools/pairtools_select.py000066400000000000000000000164221345765554600215200ustar00rootroot00000000000000import sys import click import re, fnmatch from . import _fileio, _pairsam_format, cli, _headerops, common_io_options UTIL_NAME = 'pairtools_select' @cli.command() @click.argument( 'condition', type=str ) @click.argument( 'pairs_path', type=str, required=False) @click.option( '-o', "--output", type=str, default="", help='output file.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, the output is printed into stdout.') @click.option( "--output-rest", type=str, default="", help='output file for pairs of other types. ' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' By default, such pairs are dropped.') @click.option( "--send-comments-to", type=click.Choice(['selected', 'rest', 'both', 'none']), default="both", help="Which of the outputs should receive header and comment lines", show_default=True) @click.option( "--chrom-subset", type=str, default=None, help="A path to a chromosomes file (tab-separated, 1st column contains " "chromosome names) containing a chromosome subset of interest. " "If provided, additionally filter pairs with both sides originating from " "the provided subset of chromosomes. This operation modifies the #chromosomes: " "and #chromsize: header fields accordingly." ) @click.option( "--startup-code", type=str, default=None, help="An auxiliary code to execute before filtering. " "Use to define functions that can be evaluated in the CONDITION statement" ) @click.option( "-t", "--type-cast", type=(str,str), default=(), multiple=True, help="Cast a given column to a given type. By default, only pos and mapq " "are cast to int, other columns are kept as str. Provide as " "-t , e.g. -t read_len1 int. Multiple entries are allowed." ) @common_io_options def select( condition, pairs_path, output, output_rest, send_comments_to, chrom_subset, startup_code, type_cast, **kwargs ): '''Select pairs according to some condition. CONDITION : A Python expression; if it returns True, select the read pair. Any column declared in the #columns line of the pairs header can be accessed by its name. If the header lacks the #columns line, the columns are assumed to follow the .pairs/.pairsam standard (readID, chrom1, chrom2, pos1, pos2, strand1, strand2, pair_type). Finally, CONDITION has access to COLS list which contains the string values of columns. In Bash, quote CONDITION with single quotes, and use double quotes for string variables inside CONDITION. PAIRS_PATH : input .pairs/.pairsam file. If the path ends with .gz or .lz4, the input is decompressed by pbgzip/lz4c. By default, the input is read from stdin. The following functions can be used in CONDITION besides the standard Python functions: - csv_match(x, csv) - True if variable x is contained in a list of comma-separated values, e.g. csv_match(chrom1, 'chr1,chr2') - wildcard_match(x, wildcard) - True if variable x matches a wildcard, e.g. wildcard_match(pair_type, 'C*') - regex_match(x, regex) - True if variable x matches a Python-flavor regex, e.g. regex_match(chrom1, 'chr\d') \b Examples: pairtools select '(pair_type=="UU") or (pair_type=="UR") or (pair_type=="RU")' pairtools select 'chrom1==chrom2' pairtools select 'COLS[1]==COLS[3]' pairtools select '(chrom1==chrom2) and (abs(pos1 - pos2) < 1e6)' pairtools select '(chrom1=="!") and (chrom2!="!")' pairtools select 'regex_match(chrom1, "chr\d+") and regex_match(chrom2, "chr\d+")' pairtools select 'True' --chr-subset mm9.reduced.chromsizes ''' select_py( condition, pairs_path, output, output_rest, send_comments_to, chrom_subset, startup_code, type_cast, **kwargs ) def select_py( condition, pairs_path, output, output_rest, send_comments_to, chrom_subset, startup_code, type_cast, **kwargs ): instream = (_fileio.auto_open(pairs_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairs_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) outstream_rest = (_fileio.auto_open(output_rest, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output_rest else None) wildcard_library = {} def wildcard_match(x, wildcard): if wildcard not in wildcard_library: regex = fnmatch.translate(wildcard) reobj = re.compile(regex) wildcard_library[wildcard] = reobj return wildcard_library[wildcard].fullmatch(x) csv_library = {} def csv_match(x, csv): if csv not in csv_library: csv_library[csv] = set(csv.split(',')) return x in csv_library[csv] regex_library = {} def regex_match(x, regex): if regex not in regex_library: reobj = re.compile(regex) regex_library[regex] = reobj return regex_library[regex].fullmatch(x) new_chroms = None if chrom_subset is not None: new_chroms = [l.strip().split('\t')[0] for l in open(chrom_subset, 'r')] TYPES = {'pos1':'int', 'pos2':'int', 'mapq1':'int', 'mapq2':'int'} TYPES.update(dict(type_cast)) header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) if new_chroms is not None: header = _headerops.subset_chroms_in_pairsheader(header, new_chroms) outstream.writelines((l+'\n' for l in header)) if outstream_rest: outstream_rest.writelines((l+'\n' for l in header)) column_names = _headerops.extract_column_names(header) if len(column_names) == 0: column_names = _pairsam_format.COLUMNS if startup_code is not None: exec(startup_code, globals()) condition = condition.strip() if new_chroms is not None: condition = ('({}) and (chrom1 in new_chroms) ' 'and (chrom2 in new_chroms)').format(condition) for i,col in enumerate(column_names): if col in TYPES: col_type = TYPES[col] condition = condition.replace(col, '{}(COLS[{}])'.format(col_type,i)) else: condition = condition.replace(col, 'COLS[{}]'.format(i)) match_func = compile(condition, '', 'eval') for line in body_stream: COLS = line.rstrip().split(_pairsam_format.PAIRSAM_SEP) if eval(match_func): outstream.write(line) elif outstream_rest: outstream_rest.write(line) if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() if outstream_rest: outstream_rest.close() if __name__ == '__main__': select() pairtools-0.3.0/pairtools/pairtools_sort.py000066400000000000000000000107621345765554600212310ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- import io import sys import click import subprocess import shutil import warnings from . import _fileio, _pairsam_format, cli, _headerops, common_io_options UTIL_NAME = 'pairtools_sort' @cli.command() @click.argument( 'pairs_path', type=str, required=False) @click.option( '-o', "--output", type=str, default="", help='output pairs file.' ' If the path ends with .gz or .lz4, the output is compressed by pbgzip ' 'or lz4, correspondingly. By default, the output is printed into stdout.') @click.option( "--nproc", type=int, default=8, show_default=True, help='Number of processes to split the sorting work between.' ) @click.option( "--tmpdir", type=str, default='', help='Custom temporary folder for sorting intermediates.' ) @click.option( "--memory", type=str, default='2G', show_default=True, help='The amount of memory used by default.', ) @click.option( "--compress-program", type=str, default='auto', show_default=True, help='A binary to compress temporary sorted chunks. ' 'Must decompress input when the flag -d is provided. ' 'Suggested alternatives: gzip, lzop, lz4c, snzip. ' 'If "auto", then use lz4c if available, and gzip ' 'otherwise.' ) @common_io_options def sort(pairs_path, output, nproc, tmpdir, memory, compress_program, **kwargs): '''Sort a .pairs/.pairsam file. Sort pairs in the lexicographic order along chrom1 and chrom2, in the numeric order along pos1 and pos2 and in the lexicographic order along pair_type. PAIRS_PATH : input .pairs/.pairsam file. If the path ends with .gz or .lz4, the input is decompressed by pbgzip or lz4c, correspondingly. By default, the input is read as text from stdin. ''' sort_py(pairs_path, output, nproc, tmpdir, memory, compress_program, **kwargs) def sort_py(pairs_path, output, nproc, tmpdir, memory, compress_program, **kwargs): instream = (_fileio.auto_open(pairs_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairs_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) header = _headerops.mark_header_as_sorted(header) outstream.writelines((l+'\n' for l in header)) outstream.flush() if compress_program == 'auto': if shutil.which('lz4c') is not None: compress_program = 'lz4c' else: warnings.warn( 'lz4c is not found. Using gzip for compression of sorted chunks, ' 'which results in a minor decrease in performance. Please install ' 'lz4c for faster sorting.') compress_program = 'gzip' command = r''' /bin/bash -c 'export LC_COLLATE=C; export LANG=C; sort -k {0},{0} -k {1},{1} -k {2},{2}n -k {3},{3}n -k {4},{4} --stable --field-separator=$'\''{5}'\'' {6} {7} -S {8} {9} '''.replace('\n',' ').format( _pairsam_format.COL_C1+1, _pairsam_format.COL_C2+1, _pairsam_format.COL_P1+1, _pairsam_format.COL_P2+1, _pairsam_format.COL_PTYPE+1, _pairsam_format.PAIRSAM_SEP_ESCAPE, ' --parallel={} '.format(nproc) if nproc > 0 else ' ', ' --temporary-directory={} '.format(tmpdir) if tmpdir else ' ', memory, (' --compress-program={} '.format(compress_program) if compress_program else ' '), ) command += "'" with subprocess.Popen( command, stdin=subprocess.PIPE, bufsize=-1, shell=True, stdout=outstream) as process: stdin_wrapper = io.TextIOWrapper(process.stdin, 'utf-8') for line in body_stream: stdin_wrapper.write(line) stdin_wrapper.flush() process.communicate() if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() if __name__ == '__main__': sort() pairtools-0.3.0/pairtools/pairtools_split.py000066400000000000000000000116151345765554600213730ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- import sys import pipes import click from . import _fileio, _pairsam_format, _headerops, cli, common_io_options UTIL_NAME = 'pairtools_split' @cli.command() @click.argument( 'pairsam_path', type=str, required=False) @click.option( "--output-pairs", type=str, default="", help='output pairs file.' ' If the path ends with .gz or .lz4, the output is pbgzip-/lz4c-compressed.' ' If -, pairs are printed to stdout.' ' If not specified, pairs are dropped.') @click.option( "--output-sam", type=str, default="", help='output sam file.' ' If the path ends with .bam, the output is compressed into a bam file.' ' If -, sam entries are printed to stdout.' ' If not specified, sam entries are dropped.') @common_io_options def split(pairsam_path, output_pairs, output_sam, **kwargs): '''Split a .pairsam file into .pairs and .sam. Restore a .sam file from sam1 and sam2 fields of a .pairsam file. Create a .pairs file without sam1/sam2 fields. PAIRSAM_PATH : input .pairsam file. If the path ends with .gz or .lz4, the input is decompressed by pbgzip or lz4c. By default, the input is read from stdin. ''' split_py(pairsam_path, output_pairs, output_sam, **kwargs) def split_py(pairsam_path, output_pairs, output_sam, **kwargs): instream = (_fileio.auto_open(pairsam_path, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if pairsam_path else sys.stdin) # Output streams if (not output_pairs) and (not output_sam): raise ValueError('At least one output (pairs and/or sam) must be specified!') if (output_pairs == '-') and (output_sam == '-'): raise ValueError('Only one output (pairs or sam) can be printed in stdout!') outstream_pairs = (sys.stdout if (output_pairs=='-') else (_fileio.auto_open(output_pairs, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output_pairs else None)) outstream_sam = (sys.stdout if (output_sam=='-') else (_fileio.auto_open(output_sam, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output_sam else None)) header, body_stream = _headerops.get_header(instream) header = _headerops.append_new_pg(header, ID=UTIL_NAME, PN=UTIL_NAME) columns = _headerops.extract_column_names(header) has_sams = False if columns: # trust the column order specified in the header if ('sam1' in columns) and ('sam2' in columns): sam1col = columns.index('sam1') sam2col = columns.index('sam2') columns.pop(max(sam1col, sam2col)) columns.pop(min(sam1col, sam2col)) header = _headerops._update_header_entry( header, 'columns', ' '.join(columns)) has_sams = True elif ('sam1' in columns) != ('sam1' in columns): raise ValueError( 'According to the #columns header field only one sam entry is present') else: # assume that the file has sam columns and follows the pairsam format sam1col = _pairsam_format.COL_SAM1 sam2col = _pairsam_format.COL_SAM2 has_sams = True if outstream_pairs: outstream_pairs.writelines((l+'\n' for l in header)) if outstream_sam: outstream_sam.writelines( (l[11:].strip()+'\n' for l in header if l.startswith('#samheader:'))) # Split sam1 = None sam2 = None for line in body_stream: cols = line.rstrip().split(_pairsam_format.PAIRSAM_SEP) if has_sams: if sam1col < sam2col: sam2 = cols.pop(sam2col) sam1 = cols.pop(sam1col) else: sam1 = cols.pop(sam1col) sam2 = cols.pop(sam2col) if outstream_pairs: # hard-coded tab separator to follow the DCIC pairs standard outstream_pairs.write('\t'.join(cols)) outstream_pairs.write('\n') if (outstream_sam and has_sams): for col in (sam1, sam2): if col != '.': for sam_entry in col.split(_pairsam_format.INTER_SAM_SEP): outstream_sam.write(sam_entry.replace(_pairsam_format.SAM_SEP,'\t')) outstream_sam.write('\n') if outstream_pairs and outstream_pairs != sys.stdout: outstream_pairs.close() if outstream_sam and outstream_sam != sys.stdout: outstream_sam.close() if __name__ == '__main__': split() pairtools-0.3.0/pairtools/pairtools_stats.py000066400000000000000000000503001345765554600213700ustar00rootroot00000000000000 #!/usr/bin/env python # -*- coding: utf-8 -*- import io import sys import click import numpy as np from collections import OrderedDict, Mapping from . import _fileio, _pairsam_format, cli, _headerops, common_io_options UTIL_NAME = 'pairtools_stats' @cli.command() @click.argument( 'input_path', type=str, nargs=-1, required=False) @click.option( '-o', "--output", type=str, default="", help='output stats tsv file.') @click.option( "--merge", is_flag=True, help='If specified, merge multiple input stats files instead of calculating' ' statistics of a .pairs/.pairsam file. Merging is performed via summation of' ' all overlapping statistics. Non-overlapping statistics are appended to' ' the end of the file.', ) @common_io_options def stats(input_path, output, merge, **kwargs): '''Calculate pairs statistics. INPUT_PATH : by default, a .pairs/.pairsam file to calculate statistics. If not provided, the input is read from stdin. If --merge is specified, then INPUT_PATH is interpreted as an arbitrary number of stats files to merge. The files with paths ending with .gz/.lz4 are decompressed by pbgzip/lz4c. ''' stats_py(input_path, output, merge, **kwargs) def stats_py(input_path, output, merge, **kwargs): if merge: do_merge(output, input_path, **kwargs) return instream = (_fileio.auto_open(input_path[0], mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) if input_path else sys.stdin) outstream = (_fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) if output else sys.stdout) header, body_stream = _headerops.get_header(instream) # new stats class stuff would come here ... stats = PairCounter() # Collecting statistics for line in body_stream: cols = line.rstrip().split(_pairsam_format.PAIRSAM_SEP) # algn1: chrom1 = cols[_pairsam_format.COL_C1] pos1 = int(cols[_pairsam_format.COL_P1]) strand1 = cols[_pairsam_format.COL_S1] # algn2: chrom2 = cols[_pairsam_format.COL_C2] pos2 = int(cols[_pairsam_format.COL_P2]) strand2 = cols[_pairsam_format.COL_S2] # pair type: pair_type = cols[_pairsam_format.COL_PTYPE] stats.add_pair(chrom1, pos1, strand1, chrom2, pos2, strand2, pair_type) # save statistics to file ... stats.save(outstream) if instream != sys.stdin: instream.close() if outstream != sys.stdout: outstream.close() def do_merge(output, files_to_merge, **kwargs): # Parse all stats files. stats = [] for stat_file in files_to_merge: f = _fileio.auto_open(stat_file, mode='r', nproc=kwargs.get('nproc_in'), command=kwargs.get('cmd_in', None)) # use a factory method to instanciate PairCounter stat = PairCounter.from_file(f) stats.append(stat) f.close() # combine stats from several files (files_to_merge): out_stat = sum(stats) # Save merged stats. outstream = _fileio.auto_open(output, mode='w', nproc=kwargs.get('nproc_out'), command=kwargs.get('cmd_out', None)) # save statistics to file ... out_stat.save(outstream) if outstream != sys.stdout: outstream.close() class PairCounter(Mapping): """ A Counter for Hi-C pairs that accumulates various statistics. PairCounter implements two interfaces to access multi-level statistics: 1. as a nested dict, e.g. pairCounter['pair_types']['LL'] 2. as a flat dict, with the level keys separated by '/', e.g. pairCounter['pair_types/LL'] Other features: -- PairCounters can be saved into/loaded from a file -- multiple PairCounters can be merged via addition. """ _SEP = '\t' _KEY_SEP = '/' def __init__(self, min_log10_dist=0, max_log10_dist=9, log10_dist_bin_step=0.25): self._stat = OrderedDict() # some variables used for initialization: # genomic distance bining for the ++/--/-+/+- distribution self._dist_bins = (np.r_[0, np.round(10**np.arange(min_log10_dist, max_log10_dist+0.001, log10_dist_bin_step)) .astype(np.int)] ) # establish structure of an empty _stat: self._stat['total'] = 0 self._stat['total_unmapped'] = 0 self._stat['total_single_sided_mapped'] = 0 # total_mapped = total_dups + total_nodups self._stat['total_mapped'] = 0 self._stat['total_dups'] = 0 self._stat['total_nodups'] = 0 ######################################## # the rest of stats are based on nodups: ######################################## self._stat['cis'] = 0 self._stat['trans'] = 0 self._stat['pair_types'] = {} # to be removed: self._stat['dedup'] = {} self._stat['cis_1kb+'] = 0 self._stat['cis_2kb+'] = 0 self._stat['cis_4kb+'] = 0 self._stat['cis_10kb+'] = 0 self._stat['cis_20kb+'] = 0 self._stat['cis_40kb+'] = 0 self._stat['chrom_freq'] = OrderedDict() self._stat['dist_freq'] = OrderedDict([ ('+-', np.zeros(len(self._dist_bins), dtype=np.int)), ('-+', np.zeros(len(self._dist_bins), dtype=np.int)), ('--', np.zeros(len(self._dist_bins), dtype=np.int)), ('++', np.zeros(len(self._dist_bins), dtype=np.int)), ]) def __getitem__(self, key): if isinstance(key, str): # let's strip any unintentional '/' # from either side of the key key = key.strip('/') if self._KEY_SEP in key: # multi-key to access nested elements k_fields = key.split(self._KEY_SEP) else: # single-key access flat part of PairCounter # or to access highest level of hierarchy return self._stat[key] else: # clearly an error: raise ValueError( '{} is not a valid key: must be str'.format(key)) # K_FIELDS: # process multi-key case: # in this case key must be in ['pair_types','chrom_freq','dist_freq','dedup'] # get the first 'k' and keep the remainders in 'k_fields' k = k_fields.pop(0) if k in ['pair_types', 'dedup']: # assert there is only one element in key_fields left: # 'pair_types' and 'dedup' treated the same if len(k_fields) == 1: return self._stat[k][k_fields[0]] else: raise ValueError( '{} is not a valid key: {} section implies 1 identifier'.format(key, k)) elif k == 'chrom_freq': # assert remaining key_fields == [chr1, chr2]: if len(k_fields) == 2: return self._stat[k][tuple(k_fields)] else: raise ValueError( '{} is not a valid key: {} section implies 2 identifiers'.format(key, k)) elif k == 'dist_freq': # assert that last element of key_fields is the 'directions' # THIS IS DONE FOR CONSISTENCY WITH .stats FILE # SHOULD THAT BE CHANGED IN .stats AND HERE AS WELL? if len(k_fields) == 2: # assert 'dirs' in ['++','--','+-','-+'] dirs = k_fields.pop() # there is only genomic distance range of the bin that's left: bin_range, = k_fields # extract left border of the bin "1000000+" or "1500-6000": dist_bin_left = bin_range.strip('+') if bin_range.endswith('+') \ else bin_range.split('-')[0] # get the index of that bin: bin_idx = np.searchsorted(self._dist_bins, int(dist_bin_left), 'right') - 1 # store corresponding value: return self._stat['dist_freq'][dirs][bin_idx] else: raise ValueError( '{} is not a valid key: {} section implies 2 identifiers'.format(key,k)) else: raise ValueError( '{} is not a valid key'.format(k)) def __iter__(self): return iter(self._stat) def __len__(self): return len(self._stat) @classmethod def from_file(cls, file_handle): """create instance of PairCounter from file Parameters ---------- file_handle: file handle Returns ------- PairCounter new PairCounter filled with the contents of the input file """ # fill in from file - file_handle: stat_from_file = cls() for l in file_handle: fields = l.strip().split(cls._SEP) if len(fields) == 0: # skip empty lines: continue if len(fields) != 2: # expect two _SEP separated values per line: raise _fileio.ParseError( '{} is not a valid stats file'.format(file_handle.name)) # extract key and value, then split the key: putative_key, putative_val = fields[0], fields[1] key_fields = putative_key.split(cls._KEY_SEP) # we should impose a rigid structure of .stats or redo it: if len(key_fields)==1: key = key_fields[0] if key in stat_from_file._stat: stat_from_file._stat[key] = int(fields[1]) else: raise _fileio.ParseError( '{} is not a valid stats file: unknown field {} detected'.format(file_handle.name,key)) else: # in this case key must be in ['pair_types','chrom_freq','dist_freq','dedup'] # get the first 'key' and keep the remainders in 'key_fields' key = key_fields.pop(0) if key in ['pair_types', 'dedup']: # assert there is only one element in key_fields left: # 'pair_types' and 'dedup' treated the same if len(key_fields) == 1: stat_from_file._stat[key][key_fields[0]] = int(fields[1]) else: raise _fileio.ParseError( '{} is not a valid stats file: {} section implies 1 identifier'.format(file_handle.name,key)) elif key == 'chrom_freq': # assert remaining key_fields == [chr1, chr2]: if len(key_fields) == 2: stat_from_file._stat[key][tuple(key_fields)] = int(fields[1]) else: raise _fileio.ParseError( '{} is not a valid stats file: {} section implies 2 identifiers'.format(file_handle.name,key)) elif key == 'dist_freq': # assert that last element of key_fields is the 'directions' if len(key_fields) == 2: # assert 'dirs' in ['++','--','+-','-+'] dirs = key_fields.pop() # there is only genomic distance range of the bin that's left: bin_range, = key_fields # extract left border of the bin "1000000+" or "1500-6000": dist_bin_left = (bin_range.strip('+') if bin_range.endswith('+') else bin_range.split('-')[0]) # get the index of that bin: bin_idx = np.searchsorted( stat_from_file._dist_bins, int(dist_bin_left), 'right') - 1 # store corresponding value: stat_from_file._stat[key][dirs][bin_idx] = int(fields[1]) else: raise _fileio.ParseError( '{} is not a valid stats file: {} section implies 2 identifiers'.format(file_handle.name,key)) else: raise _fileio.ParseError( '{} is not a valid stats file: unknown field {} detected'.format(file_handle.name,key)) # return PairCounter from a non-empty dict: return stat_from_file def add_pair(self, chrom1, pos1, strand1, chrom2, pos2, strand2, pair_type): """Gather statistics for a Hi-C pair and add to the PairCounter. Parameters ---------- chrom1: str chromosome of the first read pos1: int position of the first read strand1: str strand of the first read chrom2: str chromosome of the first read pos2: int position of the first read strand2: str strand of the first read pair_type: str type of the mapped pair of reads """ self._stat['total'] += 1 # collect pair type stats including DD: self._stat['pair_types'][pair_type] = self._stat['pair_types'].get(pair_type,0) + 1 if chrom1 == '!' and chrom2 == '!': self._stat['total_unmapped'] += 1 elif chrom1 != '!' and chrom2 != '!': self._stat['total_mapped'] += 1 # only mapped ones can be duplicates: if pair_type == 'DD': self._stat['total_dups'] += 1 else: self._stat['total_nodups'] += 1 self._stat['chrom_freq'][(chrom1, chrom2)] = ( self._stat['chrom_freq'].get((chrom1, chrom2), 0) + 1) if chrom1 == chrom2: self._stat['cis'] += 1 dist = np.abs(pos2-pos1) bin_idx = np.searchsorted(self._dist_bins, dist, 'right') - 1 self._stat['dist_freq'][strand1+strand2][bin_idx] += 1 if dist >= 1000: self._stat['cis_1kb+'] += 1 if dist >= 2000: self._stat['cis_2kb+'] += 1 if dist >= 4000: self._stat['cis_4kb+'] += 1 if dist >= 10000: self._stat['cis_10kb+'] += 1 if dist >= 20000: self._stat['cis_20kb+'] += 1 if dist >= 40000: self._stat['cis_40kb+'] += 1 else: self._stat['trans'] += 1 else: self._stat['total_single_sided_mapped'] += 1 def __add__(self, other): # both PairCounter are implied to have a list of common fields: # # 'total', 'total_unmapped', 'total_single_sided_mapped', 'total_mapped', # 'cis', 'trans', 'pair_types', 'cis_1kb+', 'cis_2kb+', # 'cis_10kb+', 'cis_20kb+', 'chrom_freq', 'dist_freq', 'dedup' # # initialize empty PairCounter for the result of summation: sum_stat = PairCounter() # use the empty PairCounter to iterate over: for k,v in sum_stat._stat.items(): # not nested fields are summed trivially: if isinstance(v, int): sum_stat._stat[k] = self._stat[k] + other._stat[k] # sum nested dicts/arrays in a context dependet manner: else: if k in ['pair_types','dedup']: # handy function for summation of a pair of dicts: # https://stackoverflow.com/questions/10461531/merge-and-sum-of-two-dictionaries sum_dicts = lambda dict_x,dict_y: { key: dict_x.get(key, 0) + dict_y.get(key, 0) for key in set(dict_x) | set(dict_y) } # sum a pair of corresponding dicts: sum_stat._stat[k] = sum_dicts(self._stat[k], other._stat[k]) if k == 'chrom_freq': # union list of keys (chr1,chr2) with potential duplicates: union_keys_with_dups = list(self._stat[k].keys()) + list(other._stat[k].keys()) # OrderedDict.fromkeys will take care of keys' order and duplicates in a consistent manner: # https://stackoverflow.com/questions/1720421/how-to-concatenate-two-lists-in-python # last comment to the 3rd Answer sum_stat._stat[k] = OrderedDict.fromkeys( union_keys_with_dups ) # perform a summation: for union_key in sum_stat._stat[k]: sum_stat._stat[k][union_key] = ( self._stat[k].get(union_key, 0) + other._stat[k].get(union_key, 0) ) if k == 'dist_freq': for dirs in sum_stat[k]: sum_stat[k][dirs] = self._stat[k][dirs] + other._stat[k][dirs] return sum_stat # we need this to be able to sum(list_of_PairCounters) def __radd__(self, other): if other == 0: return self else: return self.__add__(other) def flatten(self): """return a flattened OrderedDic (formatted same way as .stats file) """ # OrderedDict for flat store: flat_stat = OrderedDict() # Storing statistics for k,v in self._stat.items(): if isinstance(v, int): flat_stat[k] = v # store nested dicts/arrays in a context dependet manner: # nested categories are stored only if they are non-trivial else: if (k == 'dist_freq') and v: for i in range(len(self._dist_bins)): for dirs, freqs in v.items(): # last bin is treated differently: "100000+" vs "1200-3000": if i != len(self._dist_bins) - 1: formatted_key = self._KEY_SEP.join(['{}','{}-{}','{}']).format( k, self._dist_bins[i], self._dist_bins[i+1], dirs) else: formatted_key = self._KEY_SEP.join(['{}','{}+','{}']).format( k, self._dist_bins[i], dirs) #store key,value pair: flat_stat[formatted_key] = freqs[i] elif (k in ['pair_types','dedup']) and v: # 'pair_types' and 'dedup' are simple dicts inside, # treat them the exact same way: for k_item, freq in v.items(): formatted_key = self._KEY_SEP.join(['{}','{}']).format(k, k_item) #store key,value pair: flat_stat[formatted_key] = freq elif (k == 'chrom_freq') and v: for (chrom1, chrom2), freq in v.items(): formatted_key = self._KEY_SEP.join(['{}','{}','{}']).format(k, chrom1, chrom2) #store key,value pair: flat_stat[formatted_key] = freq # return flattened OrderedDict return flat_stat def save(self, outstream): """save PairCounter to tab-delimited text file. Flattened version of PairCounter is stored in the file. Parameters ---------- outstream: file handle Note ---- The order of the keys is not guaranteed Merging several .stats is not associative with respect to key order: merge(A,merge(B,C)) != merge(merge(A,B),C). Theys shou5ld match exactly, however, when soprted: sort(merge(A,merge(B,C))) == sort(merge(merge(A,B),C)) """ # write flattened version of the PairCounter to outstream for k,v in self.flatten().items(): outstream.write('{}{}{}\n'.format(k, self._SEP, v)) if __name__ == '__main__': stats() pairtools-0.3.0/readthedocs.yml000066400000000000000000000002021345765554600165540ustar00rootroot00000000000000 # .readthedocs.yml build: image: latest python: version: 3.6 pip_install: true requirements_file: requirements_doc.txt pairtools-0.3.0/requirements.txt000066400000000000000000000000501345765554600170310ustar00rootroot00000000000000cython numpy>=1.10 nose>=1.3 click>=6.6 pairtools-0.3.0/requirements_doc.txt000066400000000000000000000001451345765554600176630ustar00rootroot00000000000000Cython numpy>=1.10 nose>=1.3 click>=6.6 git+https://github.com/golobor/sphinx-click sphinx_rtd_theme pairtools-0.3.0/setup.py000066400000000000000000000062661345765554600152760ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- import io import os import re import glob from setuptools import setup, find_packages from setuptools.extension import Extension try: from Cython.Distutils import build_ext as _build_ext from Cython.Build import cythonize HAVE_CYTHON = True except ImportError: from setuptools.command.build_ext import build_ext as _build_ext HAVE_CYTHON = False classifiers = """\ Development Status :: 4 - Beta Operating System :: OS Independent Programming Language :: Python Programming Language :: Python :: 3 Programming Language :: Python :: 3.4 Programming Language :: Python :: 3.5 Programming Language :: Python :: 3.6 """ def _read(*parts, **kwargs): filepath = os.path.join(os.path.dirname(__file__), *parts) encoding = kwargs.pop('encoding', 'utf-8') with io.open(filepath, encoding=encoding) as fh: text = fh.read() return text def get_version(): version = re.search( r'^__version__\s*=\s*[\'"]([^\'"]*)[\'"]', _read('pairtools', '__init__.py'), re.MULTILINE).group(1) return version long_description = _read('README.md') install_requires = [l for l in _read('requirements.txt').split('\n') if l] def get_ext_modules(): ext = '.pyx' if HAVE_CYTHON else '.c' src_files = glob.glob(os.path.join( os.path.dirname(__file__), "pairtools", "*" + ext)) ext_modules = [] for src_file in src_files: name = "pairtools." + os.path.splitext(os.path.basename(src_file))[0] ext_modules.append(Extension(name, [src_file])) if HAVE_CYTHON: # .pyx to .c ext_modules = cythonize(ext_modules) #, annotate=True return ext_modules class build_ext(_build_ext): # Extension module build configuration def finalize_options(self): _build_ext.finalize_options(self) # Fix to work with bootstrapped numpy installation # http://stackoverflow.com/a/21621689/579416 # Prevent numpy from thinking it is still in its setup process: __builtins__.__NUMPY_SETUP__ = False import numpy self.include_dirs.append(numpy.get_include()) def run(self): # Import numpy here, only when headers are needed import numpy # Add numpy headers to include_dirs self.include_dirs.append(numpy.get_include()) # Call original build_ext command _build_ext.run(self) setup( name='pairtools', author='Mirny Lab', author_email='espresso@mit.edu', version=get_version(), license='MIT', description='CLI tools to process mapped Hi-C data', long_description=long_description, long_description_content_type="text/markdown", keywords=['genomics', 'bioinformatics', 'Hi-C', 'contact'], url='https://github.com/mirnylab/pairtools', ext_modules=get_ext_modules(), cmdclass = {'build_ext': build_ext}, zip_safe=False, classifiers=[s.strip() for s in classifiers.split('\n') if s], install_requires=install_requires, entry_points={ 'console_scripts': [ 'pairtools = pairtools:cli', #'pairsamtools = pairtools:cli', ] }, packages = find_packages() ) pairtools-0.3.0/tests/000077500000000000000000000000001345765554600147145ustar00rootroot00000000000000pairtools-0.3.0/tests/data/000077500000000000000000000000001345765554600156255ustar00rootroot00000000000000pairtools-0.3.0/tests/data/mock.2.pairsam000066400000000000000000000021361345765554600202760ustar00rootroot00000000000000## pairs format v1.0.0 #shape: upper triangle #genome_assembly: unknown #samheader: @SQ SN:chr1 LN:100 #samheader: @SQ SN:chr2 LN:100 #samheader: @SQ SN:chr3 LN:100 #samheader: @PG ID:bwa PN:bwa VN:0.7.15-r1140 CL:bwa mem -SP /path/ucsc.hg19.fasta.gz /path/1.fastq.gz /path/2.fastq.gz #chromosomes: chr2 chr3 chr1 #columns: readID chrom1 pos1 chrom2 pos2 strand1 strand2 pair_type sam1 sam2 readid01 chr1 1 chr2 25 + + UU readid01129chr1160101Mchr2250CGFFXS:i:0Yt:Z:UU readid0165chr22560101Mchr110ATIIXS:i:0Yt:Z:UU readid02 chr1 1 chr1 40 + + UU readid02129chr1160101Mchr1400CGFFXS:i:0Yt:Z:UU readid0265chr14060101Mchr110ATIIXS:i:0Yt:Z:UU readid03 chr1 1 chr1 3 + + UR readid03129chr1160101Mchr130CGFFXS:i:0Yt:Z:UR readid0365chr1360101Mchr110ATIIXS:i:0Yt:Z:UR readid04 ! 0 chr1 3 - + NU readid04129chr1160101Mchr130CGFFXS:i:0Yt:Z:NU readid0465chr1360101Mchr110ATIIXS:i:0Yt:Z:NU readid05 ! 0 ! 0 - - NN readid05129chr1160101Mchr130CGFFXS:i:0Yt:Z:NN readid0565chr1360101Mchr110ATIIXS:i:0Yt:Z:NN pairtools-0.3.0/tests/data/mock.4dedup.pairsam000066400000000000000000000007341345765554600213240ustar00rootroot00000000000000## pairs format v1.0.0 #sorted: chr1-chr2-pos1-pos2 #shape: upper triangle #genome_assembly: unknown #chromosomes: chr1 chr2 #columns: readID chrom1 pos1 chrom2 pos2 strand1 strand2 pair_type sam1 sam2 . ! 0 chr1 25 - + NU . . . ! 0 chr1 25 - + NU . . . chr1 1 chr1 20 + + UU . . . chr1 1 chr1 20 + + UU . . . chr1 1 chr1 25 + + UU . . . chr1 1 chr1 27 + + UU . . . chr1 1 chr1 28 + - UU . . . chr1 1 chr1 28 + + UU . . . chr1 1 chr1 50 + + UU . . . chr1 1 chr2 25 + + UU . . pairtools-0.3.0/tests/data/mock.4filterbycov.pairs000066400000000000000000000013151345765554600222310ustar00rootroot00000000000000## pairs format v1.0.0 #shape: upper triangle #genome_assembly: unknown #samheader: @SQ SN:chr1 LN:100 #samheader: @SQ SN:chr2 LN:100 #samheader: @SQ SN:chr3 LN:100 #samheader: @PG ID:bwa PN:bwa VN:0.7.15-r1140 CL:bwa mem -SP /path/ucsc.hg19.fasta.gz /path/1.fastq.gz /path/2.fastq.gz #chromosomes: chr2 chr3 chr1 #chromsize: chr2 100 #chromsize: chr3 100 #chromsize: chr1 100 #columns: readID chrom1 pos1 chrom2 pos2 strand1 strand2 pair_type sam1 sam2 readid01 chr2 40 chr3 2 + + UU readid02 chr1 6 chr1 9 + + UR readid03 chr1 1 chr2 20 + + UU readid04 chr1 50 chr1 1 + + UU readid05 chr1 1 chr1 5 + + UU readid06 chr1 20 chr1 30 + + UR readid07 ! 0 chr1 3 - + NU readid08 ! 0 chr1 3 - + MU readid09 ! 0 ! 0 - - WW pairtools-0.3.0/tests/data/mock.4flip.pairs000066400000000000000000000014051345765554600206330ustar00rootroot00000000000000## pairs format v1.0.0 #shape: upper triangle #genome_assembly: unknown #samheader: @SQ SN:chr1 LN:100 #samheader: @SQ SN:chr2 LN:100 #samheader: @SQ SN:chr3 LN:100 #samheader: @PG ID:bwa PN:bwa VN:0.7.15-r1140 CL:bwa mem -SP /path/ucsc.hg19.fasta.gz /path/1.fastq.gz /path/2.fastq.gz #chromosomes: chr1 chr2 chr3 #chromsize: chr1 100 #chromsize: chr2 100 #chromsize: chr3 100 #columns: readID chrom1 pos1 chrom2 pos2 strand1 strand2 pair_type sam1 sam2 readid01 chr1 1 chr1 2 + + UU readid02 chr1 1 chr2 2 + + UU readid03 chr1 2 chr1 1 + + UU readid04 chr1 21 chr1 2 + + UU readid05 chr2 2 chr1 1 + + UU readid06 chr2 1 chr1 2 + + UU readid07 chr1 2 chr1 1 - + UU readid08 chr1 2 chr1 1 + + RU readid09 ! 0 chr1 3 - + NU readid10 ! 0 chr1 3 - + MU readid11 ! 0 ! 0 + - WW pairtools-0.3.0/tests/data/mock.chrom.sizes000066400000000000000000000000221345765554600207360ustar00rootroot00000000000000chr1 100 chr2 100 pairtools-0.3.0/tests/data/mock.pairsam000066400000000000000000000031201345765554600201300ustar00rootroot00000000000000## pairs format v1.0.0 #shape: upper triangle #genome_assembly: unknown #samheader: @SQ SN:chr1 LN:100 #samheader: @SQ SN:chr2 LN:100 #samheader: @SQ SN:chr3 LN:100 #samheader: @PG ID:bwa PN:bwa VN:0.7.15-r1140 CL:bwa mem -SP /path/ucsc.hg19.fasta.gz /path/1.fastq.gz /path/2.fastq.gz #chromosomes: chr2 chr3 chr1 #chromsize: chr2 100 #chromsize: chr3 100 #chromsize: chr1 100 #columns: readID chrom1 pos1 chrom2 pos2 strand1 strand2 pair_type sam1 sam2 readid01 chr1 1 chr2 20 + + UU readid01129chr1160101Mchr2200CGFFXS:i:0Yt:Z:UU readid0165chr22060101Mchr110ATIIXS:i:0Yt:Z:UU readid02 chr1 1 chr1 50 + + UU readid02129chr1160101Mchr1500CGFFXS:i:0Yt:Z:UU readid0265chr15060101Mchr110ATIIXS:i:0Yt:Z:UU readid03 chr1 1 chr1 2 + + UU readid03129chr1160101Mchr120CGFFXS:i:0Yt:Z:UU readid0365chr1260101Mchr110ATIIXS:i:0Yt:Z:UU readid04 chr1 1 chr1 3 + + UR readid04129chr1160101Mchr130CGFFXS:i:0Yt:Z:UR readid0465chr1360101Mchr110ATIIXS:i:0Yt:Z:UR readid05 chr2 1 chr3 2 + + UU readid05129chr2160101Mchr320CGFFXS:i:0Yt:Z:UU readid0565chr3260101Mchr210ATIIXS:i:0Yt:Z:UU readid06 ! 0 chr1 3 - + NU readid06129chr1160101Mchr130CGFFXS:i:0Yt:Z:NU readid0665chr1360101Mchr110ATIIXS:i:0Yt:Z:NU readid07 ! 0 chr1 3 - + MU readid07129chr1160101Mchr130CGFFXS:i:0Yt:Z:NU readid0765chr1360101Mchr110ATIIXS:i:0Yt:Z:NU readid08 ! 0 ! 0 - - WW readid08129chr1160101Mchr130CGFFXS:i:0Yt:Z:WW readid0865chr1360101Mchr110ATIIXS:i:0Yt:Z:WW pairtools-0.3.0/tests/data/mock.sam000066400000000000000000000120711345765554600172610ustar00rootroot00000000000000@SQ SN:chr1 LN:100 @SQ SN:chr2 LN:100 @PG ID:mock PN:mock VN:0.0.0 CL:mock readid01 65 chr1 10 60 50M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,200,+,+,UU readid01 129 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,200,+,+,UU readid02 97 chr1 10 60 50M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,249,+,-,UU readid02 145 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,249,+,-,UU readid03 65 chr1 10 60 1S49M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,200,+,+,UU readid03 129 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,200,+,+,UU readid04 81 chr1 10 60 49M1S chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,58,chr1,200,-,+,UU readid04 161 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,58,chr1,200,-,+,UU readid05 97 chr1 10 60 50M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,248,+,-,UU readid05 145 chr1 200 60 1S49M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,248,+,-,UU readid06 97 chr1 10 60 50M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,248,+,-,UU readid06 145 chr1 200 60 49M1S chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,248,+,-,UU readid07 97 chr1 10 60 50M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,247,+,-,UU readid07 145 chr1 200 60 1S48M1S chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,247,+,-,UU readid08 105 chr1 10 60 50M = 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,chr1,10,-,+,NU readid08 149 * 0 0 * chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,chr1,10,-,+,NU readid09 85 * 0 0 * chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,chr1,10,-,+,NU readid09 169 chr1 10 60 50M = 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,chr1,10,-,+,NU readid10 77 * 0 0 * * 0 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,NN readid10 141 * 0 0 * * 0 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,NN readid11 105 chr1 10 0 50M = 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,NM readid11 149 * 0 0 * chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,NM readid12 85 * 0 0 * chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,NM readid12 169 chr1 10 0 50M = 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,NM readid13 65 chr1 10 0 50M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,chr1,200,-,+,MU readid13 129 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,chr1,200,-,+,MU readid14 65 chr1 10 60 50M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,chr1,10,-,+,MU readid14 129 chr1 200 0 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,chr1,10,-,+,MU readid15 65 chr1 10 0 50M chr1 200 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,MM readid15 129 chr1 200 0 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,MM readid16 65 chr1 10 60 25M25S chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,300,-,25M25H,60,0; SIMULATED:chr1,10,chr1,200,+,+,UR readid16 2129 chr1 300 60 25M25H chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,10,+,25M25S,60,0; SIMULATED:chr1,10,chr1,200,+,+,UR readid16 129 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,200,+,+,UR readid17 65 chr1 10 60 25M25S chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,5300,-,25M25H,60,0; SIMULATED:!,0,!,0,-,-,WW readid17 2129 chr1 5300 60 25M25H chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,10,+,25M25S,60,0; SIMULATED:!,0,!,0,-,-,WW readid17 129 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,WW readid18 65 chr1 10 60 25M25S chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,300,+,25M25H,60,0; SIMULATED:!,0,!,0,-,-,WW readid18 2113 chr1 300 60 25M25H chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,10,+,25M25S,60,0; SIMULATED:!,0,!,0,-,-,WW readid18 129 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,WW readid19 81 chr1 300 60 25M25S chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,10,+,25M25H,60,0; SIMULATED:chr1,10,chr1,200,+,+,UR readid19 2113 chr1 10 60 25M25H chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr10,300,-,25M25S,60,0; SIMULATED:chr1,10,chr1,200,+,+,UR readid19 129 chr1 200 60 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:chr1,10,chr1,200,+,+,UR readid20 65 chr1 10 60 25M25S chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,300,+,25M25H,60,0; SIMULATED:!,0,!,0,-,-,WW readid20 2113 chr1 300 60 25M25H chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,10,+,25M25S,60,0; SIMULATED:!,0,!,0,-,-,WW readid20 129 chr1 200 60 25M25S chr1 10 0 SEQ PHRED FLAG1 SA:Z:chr1,2000,+,25S25M,60,0; SIMULATED:!,10,!,0,-,-,WW readid20 2177 chr1 2000 60 25S25M chr1 10 0 SEQ PHRED FLAG1 SA:Z:chr1,2000,+,25S25M,60,0; SIMULATED:!,0,!,0,-,-,WW readid21 105 chr1 10 60 25M25S * 0 0 SEQ PHRED FLAG1 SA:Z:chr1,5300,-,25M25H,60,0; SIMULATED:!,0,!,0,-,-,WW readid21 2169 chr1 5300 60 25M25H * 0 0 SEQ PHRED FLAG1 SA:Z:chr1,10,+,25M25S,60,0; SIMULATED:!,0,!,0,-,-,WW readid21 141 * 0 0 * chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,WW readid22 65 chr1 10 60 25M25S chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,5300,-,25M25H,60,0; SIMULATED:!,0,!,0,-,-,WW readid22 2129 chr1 5300 60 25M25H chr1 200 0 SEQ PHRED FLAG1 SA:Z:chr1,10,+,25M25S,60,0; SIMULATED:!,0,!,0,-,-,WW readid22 129 chr1 200 0 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,WW readid23 129 chr1 200 0 50M chr1 10 0 SEQ PHRED FLAG1 FLAG2 SIMULATED:!,0,!,0,-,-,XX pairtools-0.3.0/tests/test_dedup.py000066400000000000000000000076171345765554600174410ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises, with_setup import tempfile testdir = os.path.dirname(os.path.realpath(__file__)) mock_pairsam_path = os.path.join(testdir, 'data', 'mock.4dedup.pairsam') tmpdir = tempfile.TemporaryDirectory() tmpdir_name = tmpdir.name dedup_path = os.path.join(tmpdir_name, 'dedup.pairsam') unmapped_path = os.path.join(tmpdir_name, 'unmapped.pairsam') dups_path = os.path.join(tmpdir_name, 'dups.pairsam') dedup_markdups_path = os.path.join(tmpdir_name, 'dedup.markdups.pairsam') unmapped_markdups_path = os.path.join(tmpdir_name, 'unmapped.markdups.pairsam') dups_markdups_path = os.path.join(tmpdir_name, 'dups.markdups.pairsam') max_mismatch = 3 def setup_func(): try: subprocess.check_output( ['python', '-m', 'pairtools', 'dedup', mock_pairsam_path, '--output', dedup_path, '--output-dups', dups_path, '--output-unmapped', unmapped_path, '--max-mismatch', str(max_mismatch) ], ) subprocess.check_output( ['python', '-m', 'pairtools', 'dedup', mock_pairsam_path, '--mark-dups', '--output', dedup_markdups_path, '--output-dups', dups_markdups_path, '--output-unmapped', unmapped_markdups_path, '--max-mismatch', str(max_mismatch) ], ) except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e def teardown_func(): tmpdir.cleanup() @with_setup(setup_func, teardown_func) def test_mock_pairsam(): pairsam_pairs = [l.strip().split('\t') for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] for (ddp, up, dp) in [(dedup_path, unmapped_path, dups_path), (dedup_markdups_path, unmapped_markdups_path, dups_markdups_path)]: dedup_pairs = [l.strip().split('\t') for l in open(ddp, 'r') if not l.startswith('#') and l.strip()] unmapped_pairs = [l.strip().split('\t') for l in open(up, 'r') if not l.startswith('#') and l.strip()] dup_pairs = [l.strip().split('\t') for l in open(dp, 'r') if not l.startswith('#') and l.strip()] # check that at least a few pairs remained in deduped and dup files assert len(dedup_pairs) > 0 assert len(dup_pairs) > 0 assert len(unmapped_pairs) > 0 # check that all pairsam entries survived deduping: assert (len(dedup_pairs) + len(unmapped_pairs) + len(dup_pairs) == len(pairsam_pairs)) def pairs_overlap(pair1, pair2, max_mismatch): overlap = ( (pair1[1] == pair2[1]) and (pair1[3] == pair2[3]) and (pair1[5] == pair2[5]) and (pair1[6] == pair2[6]) and (abs(int(pair1[2]) - int(pair2[2])) <= max_mismatch) and (abs(int(pair1[4]) - int(pair2[4])) <= max_mismatch) ) return overlap # check that deduped pairs do not overlap assert all([not pairs_overlap(pair1, pair2, 3) for i, pair1 in enumerate(dedup_pairs) for j, pair2 in enumerate(dedup_pairs) if i != j]) # check that the removed duplicates overlap with at least one of the # deduplicated entries assert all([ any([pairs_overlap(pair1, pair2, 3) for pair2 in dedup_pairs]) for pair1 in dup_pairs ]) pairtools-0.3.0/tests/test_filterbycov.py000066400000000000000000000102051345765554600206530ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises, with_setup import tempfile testdir = os.path.dirname(os.path.realpath(__file__)) mock_pairs_path = os.path.join(testdir, 'data', 'mock.4filterbycov.pairs') tmpdir = tempfile.TemporaryDirectory() tmpdir_name = tmpdir.name params = [ {'max_dist': 0, 'max_cov' : 3}, {'max_dist': 0, 'max_cov' : 2}, {'max_dist': 1, 'max_cov' : 1}, ] for p in params: p['lowcov_path'] = os.path.join( tmpdir_name, 'lowcov.{}.{}.pairs'.format(p['max_dist'], p['max_cov']) ) p['highcov_path'] = os.path.join( tmpdir_name, 'highcov.{}.{}.pairs'.format(p['max_dist'], p['max_cov']) ) p['unmapped_path'] = os.path.join( tmpdir_name, 'unmapped.{}.{}.pairs'.format(p['max_dist'], p['max_cov']) ) def setup_func(): try: for p in params: subprocess.check_output( ['python', '-m', 'pairtools', 'filterbycov', mock_pairs_path, '--output', p['lowcov_path'], '--output-highcov', p['highcov_path'], '--output-unmapped', p['unmapped_path'], '--max-dist', str(p['max_dist']), '--max-cov', str(p['max_cov']), ] ) except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e def teardown_func(): tmpdir.cleanup() @with_setup(setup_func, teardown_func) def test_mock_pairs(): all_pairs = [l.strip().split('\t') for l in open(mock_pairs_path, 'r') if not l.startswith('#') and l.strip()] for p in params: lowcov_pairs = [l.strip().split('\t') for l in open(p['lowcov_path'], 'r') if not l.startswith('#') and l.strip()] highcov_pairs = [l.strip().split('\t') for l in open(p['highcov_path'], 'r') if not l.startswith('#') and l.strip()] unmapped_pairs = [l.strip().split('\t') for l in open(p['unmapped_path'], 'r') if not l.startswith('#') and l.strip()] # check that at least a few pairs remained in deduped and dup files #assert len(lowcov_pairs) > 0 #assert len(highcov_pairs) > 0 #assert len(unmapped_pairs) > 0 # check that all pairs entries survived deduping: assert (len(lowcov_pairs) + len(unmapped_pairs) + len(highcov_pairs) == len(all_pairs)) assert all([(pair[1] != '!' and pair[3] != '!') for pair in lowcov_pairs]) assert all([(pair[1] != '!' and pair[3] != '!') for pair in highcov_pairs]) assert all([(pair[1] == '!' or pair[3] == '!') for pair in unmapped_pairs]) def update_coverage(coverage, chrom, pos, max_dist): if chrom == '!': return coverage[chrom] = coverage.get(chrom, {}) for i in range(max(0, pos-max_dist), pos+max_dist+1): coverage[chrom][i] = coverage[chrom].get(i,0) + 1 coverage = {} for pair in all_pairs: update_coverage(coverage, pair[1], int(pair[2]), p['max_dist']) update_coverage(coverage, pair[3], int(pair[4]), p['max_dist']) for pair in lowcov_pairs: #print (p['max_cov'],p['max_dist']) #print (pair, coverage[pair[1]][int(pair[2])]) #print (pair, coverage[pair[3]][int(pair[4])]) assert (coverage[pair[1]][int(pair[2])] <= p['max_cov']) assert (coverage[pair[3]][int(pair[4])] <= p['max_cov']) for pair in highcov_pairs: #print (p['max_cov'],p['max_dist']) #print (pair, coverage[pair[1]][int(pair[2])]) #print (pair, coverage[pair[3]][int(pair[4])]) assert ( (coverage[pair[1]][int(pair[2])] > p['max_cov']) or (coverage[pair[3]][int(pair[4])] > p['max_cov']) ) pairtools-0.3.0/tests/test_flip.py000066400000000000000000000034351345765554600172640ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises testdir = os.path.dirname(os.path.realpath(__file__)) mock_pairs_path = os.path.join(testdir, 'data', 'mock.4flip.pairs') mock_chromsizes_path = os.path.join(testdir, 'data', 'mock.chrom.sizes') def test_flip(): try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'flip', mock_pairs_path, '-c', mock_chromsizes_path ], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e orig_pairs = [l.strip().split('\t') for l in open(mock_pairs_path, 'r') if not l.startswith('#') and l.strip()] flipped_pairs = [l.strip().split('\t') for l in result.split('\n') if not l.startswith('#') and l.strip()] chrom_enum = {'!':0, 'chr1':1, 'chr2': 2} for orig_pair, flipped_pair in zip(orig_pairs, flipped_pairs): has_correct_order = ( (chrom_enum[orig_pair[1]], int(orig_pair[2])) <= (chrom_enum[orig_pair[3]], int(orig_pair[4])) ) if has_correct_order: assert(all([c1==c2 for c1,c2 in zip(orig_pair, flipped_pair)])) if not has_correct_order: assert(orig_pair[1] == flipped_pair[3]) assert(orig_pair[2] == flipped_pair[4]) assert(orig_pair[3] == flipped_pair[1]) assert(orig_pair[4] == flipped_pair[2]) assert(orig_pair[5] == flipped_pair[6]) assert(orig_pair[6] == flipped_pair[5]) assert(orig_pair[7] == flipped_pair[7][::-1]) pairtools-0.3.0/tests/test_headerops.py000066400000000000000000000107001345765554600202750ustar00rootroot00000000000000# -*- coding: utf-8 -*- from pairtools import _headerops from nose.tools import assert_raises, with_setup, raises def test_make_standard_header(): header = _headerops.make_standard_pairsheader() assert any([l.startswith('## pairs format') for l in header]) assert any([l.startswith('#shape') for l in header]) assert any([l.startswith('#columns') for l in header]) header = _headerops.make_standard_pairsheader( chromsizes=[('b', 100), ('c', 100), ('a', 100)]) assert sum([l.startswith('#chromsize') for l in header]) == 3 def test_samheaderops(): header = _headerops.make_standard_pairsheader() samheader = [ '@SQ\tSN:chr1\tLN:100', '@SQ\tSN:chr2\tLN:100', '@SQ\tSN:chr3\tLN:100', '@PG\tID:bwa\tPN:bwa\tCL:bwa', '@PG\tID:bwa-2\tPN:bwa\tCL:bwa\tPP:bwa' ] header_with_sam = _headerops.insert_samheader(header, samheader) assert len(header_with_sam) == len(header) + len(samheader) for l in samheader: assert any([l2.startswith('#samheader') and l in l2 for l2 in header_with_sam]) # test adding new programs to the PG chain header_extra_pg = _headerops.append_new_pg( header_with_sam, ID='test', PN='test') # test if all lines got transferred assert all([(old_l in header_extra_pg) for old_l in header_with_sam]) # test if one PG got added assert len(header_extra_pg) == len(header_with_sam) + 1 # test if the new PG has PP matching the ID of one of already existing PGs new_l = [l for l in header_extra_pg if l not in header_with_sam][0] pp = [f[3:] for f in new_l.split('\t') if f.startswith('PP:')][0] assert len([l for l in header_extra_pg if l.startswith('#samheader') and ('\tID:{}\t'.format(pp) in l) ]) == 1 def test_merge_pairheaders(): headers = [ ['## pairs format v1.0'], ['## pairs format v1.0'] ] merged_header = _headerops._merge_pairheaders(headers) assert merged_header == headers[0] headers = [ ['## pairs format v1.0', '#a'], ['## pairs format v1.0', '#b'] ] merged_header = _headerops._merge_pairheaders(headers) assert merged_header == ['## pairs format v1.0', '#a', '#b'] headers = [ ['## pairs format v1.0', '#chromsize: chr1 100', '#chromsize: chr2 200'], ['## pairs format v1.0', '#chromsize: chr1 100', '#chromsize: chr2 200'], ] merged_header = _headerops._merge_pairheaders(headers) assert merged_header == headers[0] @raises(Exception) def test_merge_different_pairheaders(): headers = [ ['## pairs format v1.0'], ['## pairs format v1.1'] ] merged_header = _headerops._merge_pairheaders(headers) def test_force_merge_pairheaders(): headers = [ ['## pairs format v1.0', '#chromsize: chr1 100'], ['## pairs format v1.0', '#chromsize: chr2 200'], ] merged_header = _headerops._merge_pairheaders(headers, force=True) assert merged_header == ['## pairs format v1.0', '#chromsize: chr1 100', '#chromsize: chr2 200'] def test_merge_samheaders(): headers = [ ['@HD\tVN:1'], ['@HD\tVN:1'], ] merged_header = _headerops._merge_samheaders(headers) assert merged_header == headers[0] headers = [ ['@HD\tVN:1', '@SQ\tSN:chr1\tLN:100', '@SQ\tSN:chr2\tLN:100', ], ['@HD\tVN:1', '@SQ\tSN:chr1\tLN:100', '@SQ\tSN:chr2\tLN:100', ], ] merged_header = _headerops._merge_samheaders(headers) assert merged_header == headers[0] headers = [ ['@HD\tVN:1', '@PG\tID:bwa\tPN:bwa\tPP:cat', ], ['@HD\tVN:1', '@PG\tID:bwa\tPN:bwa\tPP:cat', ], ] merged_header = _headerops._merge_samheaders(headers) print(merged_header) assert merged_header == [ '@HD\tVN:1', '@PG\tID:bwa-1\tPN:bwa\tPP:cat-1', '@PG\tID:bwa-2\tPN:bwa\tPP:cat-2', ] def test_merge_headers(): headers = [ ['## pairs format v1.0', '#samheader: @HD\tVN:1', '#samheader: @SQ\tSN:chr1\tLN:100', '#samheader: @SQ\tSN:chr2\tLN:100'] ] * 2 merged_header = _headerops.merge_headers(headers) assert merged_header == headers[0] pairtools-0.3.0/tests/test_markasdup.py000066400000000000000000000020331345765554600203120ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises testdir = os.path.dirname(os.path.realpath(__file__)) def test_mock_pairsam(): mock_pairsam_path = os.path.join(testdir, 'data', 'mock.pairsam') try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'markasdup', mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e pairsam_body = [l.strip() for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] # check that all pairsam entries survived sorting: assert len(pairsam_body) == len(output_body) # check that all pairtypes got changed to DD for l in output_body: assert l.split('\t')[7] == 'DD' pairtools-0.3.0/tests/test_merge.py000066400000000000000000000052751345765554600174350ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises, with_setup import tempfile testdir = os.path.dirname(os.path.realpath(__file__)) tmpdir = tempfile.TemporaryDirectory() tmpdir_name = tmpdir.name mock_pairsam_path_1 = os.path.join(testdir, 'data', 'mock.pairsam') mock_pairsam_path_2 = os.path.join(testdir, 'data', 'mock.2.pairsam') mock_sorted_pairsam_path_1 = os.path.join(tmpdir_name, '1.pairsam') mock_sorted_pairsam_path_2 = os.path.join(tmpdir_name, '2.pairsam') def setup_func(): try: subprocess.check_output( ['python', '-m', 'pairtools', 'sort', mock_pairsam_path_1, '--output', mock_sorted_pairsam_path_1 ], ) subprocess.check_output( ['python', '-m', 'pairtools', 'sort', mock_pairsam_path_2, '--output', mock_sorted_pairsam_path_2 ], ) except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e def teardown_func(): tmpdir.cleanup() @with_setup(setup_func, teardown_func) def test_mock_pairsam(): try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'merge', mock_sorted_pairsam_path_1, mock_sorted_pairsam_path_2 ], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e # check that all pairsam entries survived sorting: pairsam_body_1 = [l.strip() for l in open(mock_pairsam_path_1, 'r') if not l.startswith('#') and l.strip()] pairsam_body_2 = [l.strip() for l in open(mock_pairsam_path_2, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] assert len(pairsam_body_1) + len(pairsam_body_2) == len(output_body) # check the sorting order of the output: prev_pair = None for l in output_body: cur_pair = l.split('\t')[1:8] if prev_pair is not None: assert (cur_pair[0] >= prev_pair[0]) if (cur_pair[0] == prev_pair[0]): assert (cur_pair[1] >= prev_pair[1]) if (cur_pair[1] == prev_pair[1]): assert (cur_pair[2] >= prev_pair[2]) if (cur_pair[2] == prev_pair[2]): assert (cur_pair[3] >= prev_pair[3]) prev_pair = cur_pair pairtools-0.3.0/tests/test_parse.py000066400000000000000000000127571345765554600174530ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys from nose.tools import assert_raises import subprocess testdir = os.path.dirname(os.path.realpath(__file__)) from pairtools import parse, parse_algn, parse_cigar def test_python_version(): assert (sys.version_info[0] == 3), 'Use Python 3!' def test_parse_cigar(): assert (parse_cigar('*') == { 'cigar' : '*', 'read_len': 0, 'matched_bp': 0, 'algn_ref_span': 0, 'algn_read_span': 0, 'clip5_ref': 0, 'clip3_ref': 0}) assert (parse_cigar('50M') == { 'cigar' : '50M', 'read_len': 50, 'matched_bp': 50, 'algn_ref_span': 50, 'algn_read_span': 50, 'clip5_ref': 0, 'clip3_ref': 0}) assert (parse_cigar('40M10S') == { 'cigar' : '40M10S', 'read_len': 50, 'matched_bp': 40, 'algn_ref_span': 40, 'algn_read_span': 40, 'clip5_ref': 0, 'clip3_ref': 10}) assert (parse_cigar('10S40M') == { 'cigar' : '10S40M', 'read_len': 50, 'matched_bp': 40, 'algn_ref_span': 40, 'algn_read_span': 40, 'clip5_ref': 10, 'clip3_ref': 0}) assert (parse_cigar('10S30M10S') == { 'cigar' : '10S30M10S', 'read_len': 50, 'matched_bp': 30, 'algn_ref_span': 30, 'algn_read_span': 30, 'clip5_ref': 10, 'clip3_ref': 10}) assert (parse_cigar('30M10I10M') == { 'cigar' : '30M10I10M', 'read_len': 50, 'matched_bp': 40, 'algn_ref_span': 40, 'algn_read_span': 50, 'clip5_ref': 0, 'clip3_ref': 0}) assert (parse_cigar('30M10D10M10S') == { 'cigar' : '30M10D10M10S', 'read_len': 50, 'matched_bp': 40, 'algn_ref_span': 50, 'algn_read_span': 40, 'clip5_ref': 0, 'clip3_ref': 10}) def test_parse_algn(): min_mapq = 50 sam='SRR1658570.5\t65\tchr12\t24316205\t60\t90M11S\t' '=\t46893391\t22577187\t.\t.\t' 'NM:i:1\tMD:Z:36A53\tAS:i:85\tXS:i:19' samcols = sam.split('\t') parsed_algn = parse_algn(samcols, min_mapq) assert parsed_algn == { 'chrom': 'chr12', 'pos': 24316205, 'pos5': 24316205, 'pos3': 24316294, 'pos': 24316205, 'strand': '+', 'dist_to_5': 0, 'dist_to_3': 11, 'mapq': 60, 'is_unique': True, 'is_mapped': True, 'is_linear': True, 'cigar' : '90M11S', 'algn_ref_span': 90, 'algn_read_span': 90, 'matched_bp': 90, 'clip3_ref': 11, 'clip5_ref': 0, 'read_len': 101, 'type':'U'} sam = ('readid01\t65\tchr1\t10\t60\t50M\tchr1\t200\t0\tSEQ\tPHRED' '\tFLAG1\tFLAG2\tSIMULATED:readid01,chr1,chr1,10,200,+,+,UU') samcols = sam.split('\t') parsed_algn = parse_algn(samcols, min_mapq, True) assert parsed_algn == { 'chrom': 'chr1', 'pos': 59, 'pos5': 10, 'pos3': 59, 'strand': '+', 'dist_to_5': 0, 'dist_to_3': 0, 'mapq': 60, 'is_unique': True, 'is_mapped': True, 'is_linear': True, 'cigar' : '50M', 'algn_ref_span': 50, 'algn_read_span': 50, 'matched_bp': 50, 'clip3_ref': 0, 'clip5_ref': 0, 'read_len': 50, 'type':'U'} sam = ('readid10\t77\t*\t0\t0\t*\t*\t0\t0\tSEQ\tPHRED' '\tFLAG1\tFLAG2\tSIMULATED:readid10,!,!,0,0,-,-,NN') samcols = sam.split('\t') parsed_algn = parse_algn(samcols, min_mapq) assert parsed_algn == { 'chrom': '!', 'pos': 0, 'pos5': 0, 'pos3': 0, 'strand': '-', 'dist_to_5': 0, 'dist_to_3': 0, 'mapq': 0, 'is_unique': False, 'is_mapped': False, 'is_linear': True, 'cigar' : '*', 'algn_ref_span': 0, 'algn_read_span': 0, 'matched_bp': 0, 'clip3_ref': 0, 'clip5_ref': 0, 'read_len': 0, 'type':'N'} def test_mock_sam(): mock_sam_path = os.path.join(testdir, 'data', 'mock.sam') mock_chroms_path = os.path.join(testdir, 'data', 'mock.chrom.sizes') try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'parse', '--walks-policy', 'mask', '-c', mock_chroms_path, mock_sam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e # check if the header got transferred correctly sam_header = [l.strip() for l in open(mock_sam_path, 'r') if l.startswith('@')] pairsam_header = [l.strip() for l in result.split('\n') if l.startswith('#')] for l in sam_header: assert any([l in l2 for l2 in pairsam_header]) # check that the pairs got assigned properly for l in result.split('\n'): if l.startswith('#') or not l: continue assigned_pair = l.split('\t')[1:8] simulated_pair = l.split('SIMULATED:',1)[1].split('\031',1)[0].split(',') print(assigned_pair) print(simulated_pair) print() assert assigned_pair == simulated_pair pairtools-0.3.0/tests/test_select.py000066400000000000000000000131661345765554600176130ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises testdir = os.path.dirname(os.path.realpath(__file__)) mock_pairsam_path = os.path.join(testdir, 'data', 'mock.pairsam') mock_chromsizes_path = os.path.join(testdir, 'data', 'mock.chrom.sizes') def test_preserve(): try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'select', 'True', mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e pairsam_body = [l.strip() for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] assert all(l in pairsam_body for l in output_body) def test_equal(): try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'select', '(pair_type == "RU") or (pair_type == "UR") or (pair_type == "UU")', mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e print(result) pairsam_body = [l.strip() for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] assert all(l.split('\t')[7] in ['RU', 'UR', 'UU'] for l in output_body) assert all(l in output_body for l in pairsam_body if l.split('\t')[7] in ['RU', 'UR', 'UU']) def test_csv(): try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'select', 'csv_match(pair_type, "RU,UR,UU")', mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e print(result) pairsam_body = [l.strip() for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] assert all(l.split('\t')[7] in ['RU','UR', 'UU'] for l in output_body) assert all(l in output_body for l in pairsam_body if l.split('\t')[7] in ['RU', 'UR', 'UU']) def test_wildcard(): try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'select', 'wildcard_match(pair_type, "*U")', mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e print(result) pairsam_body = [l.strip() for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] assert all(l.split('\t')[7] in ['NU', 'MU', 'RU', 'UU'] for l in output_body) assert all(l in output_body for l in pairsam_body if l.split('\t')[7] in ['NU', 'MU', 'RU', 'UU']) def test_regex(): try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'select', 'regex_match(pair_type, "[NM]U")', mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e print(result) pairsam_body = [l.strip() for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] assert all(l.split('\t')[7] in ['NU', 'MU'] for l in output_body) assert all(l in output_body for l in pairsam_body if l.split('\t')[7] in ['NU', 'MU']) def test_chrom_subset(): try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'select', 'True', '--chrom-subset', mock_chromsizes_path, mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e pairsam_body = [l.strip() for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] output_header = [l.strip() for l in result.split('\n') if l.startswith('#') and l.strip()] chroms_from_chrom_field = [l.strip().split()[1:] for l in result.split('\n') if l.startswith('#chromosomes:')][0] assert set(chroms_from_chrom_field) == set(['chr1', 'chr2']) chroms_from_chrom_sizes = [l.strip().split()[1] for l in result.split('\n') if l.startswith('#chromsize:')] assert set(chroms_from_chrom_sizes) == set(['chr1', 'chr2']) pairtools-0.3.0/tests/test_sort.py000066400000000000000000000040751345765554600173220ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises testdir = os.path.dirname(os.path.realpath(__file__)) def test_mock_pairsam(): mock_pairsam_path = os.path.join(testdir, 'data', 'mock.pairsam') try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'sort', mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e # Check that the only changes strings are a @PG record of a SAM header, # the "#sorted" entry and chromosomes pairsam_header = [l.strip() for l in open(mock_pairsam_path, 'r') if l.startswith('#')] output_header = [l.strip() for l in result.split('\n') if l.startswith('#')] print(output_header) print(pairsam_header) for l in output_header: if not any([l in l2 for l2 in pairsam_header]): assert ( l.startswith('#samheader: @PG') or l.startswith('#sorted') or l.startswith('#chromosomes') ) pairsam_body = [l.strip() for l in open(mock_pairsam_path, 'r') if not l.startswith('#') and l.strip()] output_body = [l.strip() for l in result.split('\n') if not l.startswith('#') and l.strip()] # check that all pairsam entries survived sorting: assert len(pairsam_body) == len(output_body) # check the sorting order of the output: prev_pair = None for l in output_body: cur_pair = l.split('\t')[1:8] if prev_pair is not None: assert (cur_pair[0] >= prev_pair[0]) if (cur_pair[0] == prev_pair[0]): assert (cur_pair[2] >= prev_pair[2]) if (cur_pair[2] == prev_pair[2]): assert (cur_pair[1] >= prev_pair[1]) if (cur_pair[1] == prev_pair[1]): assert (cur_pair[3] >= prev_pair[3]) prev_pair = cur_pair pairtools-0.3.0/tests/test_split.py000066400000000000000000000052421345765554600174630ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises, with_setup import tempfile testdir = os.path.dirname(os.path.realpath(__file__)) mock_pairsam_path = os.path.join(testdir, 'data', 'mock.pairsam') tmpdir = tempfile.TemporaryDirectory() tmpdir_name = tmpdir.name pairs_path = os.path.join(tmpdir_name, 'out.pairs') sam_path = os.path.join(tmpdir_name, 'out.sam') def setup_func(): try: subprocess.check_output( ['python', '-m', 'pairtools', 'split', mock_pairsam_path, '--output-pairs', pairs_path, '--output-sam', sam_path, ], ) except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e def teardown_func(): tmpdir.cleanup() @with_setup(setup_func, teardown_func) def test_split(): pairsam_lines = [l.strip() for l in open(mock_pairsam_path, 'r') if l.strip()] pairs_lines = [l.strip() for l in open(pairs_path, 'r') if l.strip()] sam_lines = [l.strip() for l in open(sam_path, 'r') if l.strip()] # check that all entries survived splitting: n_pairsam = len([l for l in pairsam_lines if not l.startswith('#')]) n_pairs = len([l for l in pairs_lines if not l.startswith('#')]) n_sam = len([l for l in sam_lines if not l.startswith('@')]) // 2 assert n_pairsam == n_pairs assert n_pairsam == n_sam # check that the header survived splitting: pairsam_header = [l.strip() for l in open(mock_pairsam_path, 'r') if l.strip() and l.startswith('#')] pairs_header = [l.strip() for l in open(pairs_path, 'r') if l.strip() and l.startswith('#')] sam_header = [l.strip() for l in open(sam_path, 'r') if l.strip() and l.startswith('@')] assert all( any(l in l2 for l2 in pairsam_header) for l in sam_header if not l.startswith('@PG')) assert all( l in pairsam_header for l in pairs_header if (not (l.startswith('#columns') or l.startswith('#samheader')))) columns_pairsam = [l for l in pairsam_header if l.startswith('#columns')][0].split()[1:] columns_pairs = [l for l in pairs_header if l.startswith('#columns')][0].split()[1:] assert ( ('sam1' in columns_pairsam) and ('sam2' in columns_pairsam) and ('sam1' not in columns_pairs) and ('sam2' not in columns_pairs)) assert [c for c in columns_pairsam if c != 'sam1' and c != 'sam2'] == columns_pairs pairtools-0.3.0/tests/test_stats.py000066400000000000000000000032351345765554600174660ustar00rootroot00000000000000# -*- coding: utf-8 -*- import os import sys import subprocess from nose.tools import assert_raises testdir = os.path.dirname(os.path.realpath(__file__)) def test_mock_pairsam(): mock_pairsam_path = os.path.join(testdir, 'data', 'mock.pairsam') try: result = subprocess.check_output( ['python', '-m', 'pairtools', 'stats', mock_pairsam_path], ).decode('ascii') except subprocess.CalledProcessError as e: print(e.output) print(sys.exc_info()) raise e stats = dict(l.strip().split('\t') for l in result.split('\n') if not l.startswith('#') and l.strip()) for k in stats: stats[k] = int(stats[k]) print(stats) assert stats['total'] == 8 assert stats['total_single_sided_mapped'] == 2 assert stats['total_mapped'] == 5 assert stats['cis'] == 3 assert stats['trans'] == 2 assert stats['pair_types/UU'] == 4 assert stats['pair_types/NU'] == 1 assert stats['pair_types/WW'] == 1 assert stats['pair_types/UR'] == 1 assert stats['pair_types/MU'] == 1 assert stats['chrom_freq/chr1/chr2'] == 1 assert stats['chrom_freq/chr1/chr1'] == 3 assert stats['chrom_freq/chr2/chr3'] == 1 assert all(stats[k]==0 for k in stats if k.startswith('dist_freq') and k not in ['dist_freq/1-2/++', 'dist_freq/2-3/++', 'dist_freq/32-56/++']) assert stats['dist_freq/1-2/++'] == 1 assert stats['dist_freq/2-3/++'] == 1 assert stats['dist_freq/32-56/++'] == 1