├── .gitattributes ├── .gitignore ├── .travis.yml ├── Dockerfile ├── LICENSE ├── README.md ├── README.txt ├── example_usage.ipynb ├── paper.bib ├── paper.md ├── schematic.jpg ├── setup.py └── xenomapper ├── __init__.py ├── mappability.py ├── tests ├── __init__.py ├── data │ ├── paired_end_testdata_human.bam │ ├── paired_end_testdata_human.sam │ ├── paired_end_testdata_mouse.bam │ ├── paired_end_testdata_mouse.sam │ ├── test_from_EcoliK12DH10B.1.bt2 │ ├── test_from_EcoliK12DH10B.2.bt2 │ ├── test_from_EcoliK12DH10B.3.bt2 │ ├── test_from_EcoliK12DH10B.4.bt2 │ ├── test_from_EcoliK12DH10B.fasta │ ├── test_from_EcoliK12DH10B.rev.1.bt2 │ ├── test_from_EcoliK12DH10B.rev.2.bt2 │ ├── test_from_EcoliK12DH10B_10reads.fasta │ ├── test_from_EcoliK12DH10B_10reads.sam │ ├── test_from_EcoliK12DH10B_10reads.wig │ ├── test_from_EcoliK12DH10B_150reads.fasta │ ├── test_from_EcoliK12DH10B_150reads.sam │ ├── test_from_EcoliK12DH10B_150reads.wig │ ├── test_human_in.sam │ └── test_mouse_in.sam ├── test_all.py ├── test_mappability.py └── test_xenomapper.py └── xenomapper.py /.gitattributes: -------------------------------------------------------------------------------- 1 | *.ipynb linguist-language=Python 2 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | #ignore pyc files anywhere 2 | *.pyc 3 | 4 | #ignore .DS_Store files 5 | **/.DS_store 6 | 7 | #ignore egg info files 8 | XenoMapper.egg-info 9 | \.eggs/ 10 | 11 | \.pytest_cache/v/cache/ 12 | 13 | \.vscode/ 14 | 15 | dist/ 16 | -------------------------------------------------------------------------------- /.travis.yml: -------------------------------------------------------------------------------- 1 | language: python 2 | matrix: 3 | include: 4 | - python: "3.6" 5 | - python: "3.7" 6 | - python: "3.8" 7 | - python: "3.9" 8 | - python: "3.9-dev" 9 | allow_failures: 10 | - python: "3.9-dev" 11 | - python: "pypy3" 12 | # command to install dependencies, e.g. pip install -r requirements.txt --use-mirrors 13 | install: 14 | - pip3 install . 15 | before_script: 16 | - pip3 install python-coveralls 17 | - pip3 install coverage 18 | # command to run tests, e.g. python setup.py test 19 | script: 20 | - coverage run --source xenomapper.xenomapper,xenomapper.mappability -m xenomapper.tests.test_all 21 | after_success: 22 | - coveralls 23 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | # How to run Xenomapper in a docker container 2 | 3 | # Docker File Author / Maintainer 4 | # MAINTAINER Matthew Wakefield 5 | 6 | # First you will need install docker. On MacOS you do 7 | # brew install Caskroom/cask/virtualbox 8 | # brew install docker 9 | # brew install boot2docker 10 | # boot2docker download 11 | # boot2docker init 12 | # boot2docker up 13 | # $(boot2docker shellinit) 14 | 15 | # You then need to create a docker container. In the same directory as this file you type 16 | 17 | # docker build -t xenomapper . 18 | 19 | # This will run the following executable part of this file 20 | 21 | FROM ubuntu:trusty-20190515 22 | MAINTAINER Matthew Wakefield 23 | RUN apt-get update && apt-get install -y \ 24 | samtools \ 25 | python3-pip \ 26 | git 27 | RUN pip3 install git+https://github.com/genomematt/xenomapper.git 28 | 29 | # congratulations - you now have a docker container with xenomapper installed! 30 | 31 | # To test it run 32 | # docker run -i xenomapper xenomapper --version 33 | # (note the first xenomapper is the container name, the second the program name) 34 | 35 | # To do anything useful with it you will need to mount some data in the container 36 | # The simplest version of this is to mount a directory from the host. 37 | # This must be an absolute path, and something like $HOME/my/data/directory:/data 38 | # will mount your host directory in the container as /data 39 | 40 | # docker run -it -v $HOME/repos/xenomapper/xenomapper/tests/data/:/data/ xenomapper xenomapper --primary_sam /data/paired_end_testdata_human.sam --secondary_sam /data/paired_end_testdata_mouse.sam --unresolve /data/docker_unresolved.sam 41 | 42 | # Note that you will get the primary_specific on std_out, the read count category summary on std_err and unresolved in a host file $HOME/repos/xenomapper/xenomapper/tests/data/docker_unresolved.sam 43 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | {project} Copyright (C) {year} {fullname} 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | [![Build Status](https://travis-ci.com/genomematt/xenomapper.svg?branch=master)](https://travis-ci.com/genomematt/xenomapper) 2 | [![Coverage Status](https://coveralls.io/repos/genomematt/xenomapper/badge.svg)](https://coveralls.io/r/genomematt/xenomapper) 3 | [![JOSS](http://joss.theoj.org/papers/7065e20e97ff4e44695b5e9fef7cdcd8/status.svg)](http://dx.doi.org/10.21105/joss.00018) 4 | [![DOI](https://zenodo.org/badge/11450/genomematt/xenomapper.svg)](https://zenodo.org/badge/latestdoi/11450/genomematt/xenomapper) 5 | [![DOI](https://img.shields.io/pypi/v/xenomapper.svg)](https://pypi.python.org/pypi/XenoMapper/) 6 | 7 | Xenomapper 8 | ========== 9 | 10 | Xenomapper is a utility for post processing mapped reads that have been aligned to a primary genome and a secondary genome and binning reads into species specific, multimapping in each species, unmapped and unassigned bins. It can be used on single end or paired end sequencing data. In paired end data evidence of sequence specificity for either read will be used to assign both reads. 11 | 12 | Use cases include xenografts of human cancers and host pathogen interactions. 13 | 14 | Xenomapper is most effective with mapped reads that include an XS or ZS score that gives the mapping score of the next best read. These include Bowtie2 (Langmead, 2012) and HISAT (Kim, 2015). 15 | 16 | ![Schematic of Xenomapper Use](/schematic.jpg "Schematic of Xenomapper Use") 17 | 18 | Installation 19 | ============ 20 | Xenomapper requires python 3.3 or higher and is tested on linux and MacOS with CPython and pypy3. For bam file decoding samtools must be installed. 21 | 22 | Installing from the Python Package Index with pip is the easiest option: 23 | 24 | pip3 install xenomapper 25 | 26 | Alternatively if you would like to install from the github repository 27 | 28 | git clone https://github.com/genomematt/xenomapper 29 | pip3 install --upgrade xenomapper 30 | 31 | Although the repository tests by continuous integration with TravisCI its good practice to run the tests locally and check your install works correctly. The tests are run with the following command: 32 | 33 | python3 -m xenomapper.tests.test_all 34 | 35 | All users should upgrade to v0.5.0 or higher as earlier versions have known bugs. 36 | 37 | Using Xenomapper 38 | ================ 39 | 40 | usage: 41 | 42 | xenomapper [-h] [--primary_sam PRIMARY_SAM] 43 | [--secondary_sam SECONDARY_SAM] 44 | [--primary_bam PRIMARY_BAM] 45 | [--secondary_bam SECONDARY_BAM] 46 | [--primary_specific PRIMARY_SPECIFIC] 47 | [--secondary_specific SECONDARY_SPECIFIC] 48 | [--primary_multi PRIMARY_MULTI] 49 | [--secondary_multi SECONDARY_MULTI] 50 | [--unassigned UNASSIGNED] 51 | [--unresolved UNRESOLVED] 52 | [--paired] 53 | [--min_score MIN_SCORE] 54 | [--cigar_scores] 55 | [--version] 56 | 57 | A script for parsing pairs of sam files and returning sam files 58 | containing only reads where no better mapping exist in other files. 59 | Used for filtering reads where multiple species may contribute 60 | (eg human tissue xenografted into mouse, pathogen growing on plant). 61 | 62 | Files should contain an AS and XS score and better matches must have 63 | a higher alignment score (but can be negative). 64 | Reads must be in the same order in both species. 65 | 66 | In practice this is best acchieved by using Bowtie2 in --local mode. 67 | If the -p option is used you must also use --reorder. 68 | 69 | Limited support is provided for aligners that do not produce AS and XS 70 | score tags via the --cigar_score option. 71 | 72 | All input files must be seekable 73 | (ie not a FIFO, process substitution or pipe)' 74 | 75 | optional arguments: 76 | -h, --help show this help message and exit 77 | --primary_sam PRIMARY_SAM 78 | a SAM format Bowtie2 mapping output file corresponding 79 | to the primary species of interest 80 | --secondary_sam SECONDARY_SAM 81 | a SAM format Bowtie2 mapping output file corresponding 82 | to the secondary or contaminating species 83 | --primary_bam PRIMARY_BAM 84 | a BAM format Bowtie2 mapping output file corresponding 85 | to the primary species of interest 86 | --secondary_bam SECONDARY_BAM 87 | a BAM format Bowtie2 mapping output file corresponding 88 | to the secondary or contaminating species 89 | --primary_specific PRIMARY_SPECIFIC 90 | name for SAM format output file for reads mapping to a 91 | specific location in the primary species 92 | --secondary_specific SECONDARY_SPECIFIC 93 | name for SAM format output file for reads mapping to a 94 | specific location in the secondary species 95 | --primary_multi PRIMARY_MULTI 96 | name for SAM format output file for reads multi 97 | mapping in the primary species 98 | --secondary_multi SECONDARY_MULTI 99 | name for SAM format output file for reads multi 100 | mapping in the secondary species 101 | --unassigned UNASSIGNED 102 | name for SAM format output file for unassigned (non- 103 | mapping) reads 104 | --unresolved UNRESOLVED 105 | name for SAM format output file for unresolved (maps 106 | equally well in both species) reads 107 | --paired the SAM files consist of paired reads with forward and 108 | reverse reads occuring once and interlaced 109 | --conservative conservatively allocate paired end reads with 110 | discordant category allocations. Only pairs that are 111 | both specific, or specific and multi will be allocated 112 | as specific. Pairs that are discordant for species 113 | will be deemed unresolved. Pairs where any read is 114 | unassigned will be deemed unassigned. 115 | --min_score MIN_SCORE 116 | the minimum mapping score. Reads with scores less than 117 | or equal to min_score will be considered unassigned. 118 | Values should be chosen based on the mapping program 119 | and read length 120 | --cigar_scores Use the cigar line and the NM tag to calculate a 121 | score. For aligners that do not support the AS tag. No 122 | determination of multimapping state will be done. 123 | Reads that are unique in one species and multimap in 124 | the other species may be misassigned as no score can 125 | be calculated in the multimapping species. Score is -6 126 | * mismatches + -5 * indel open + -3 * indel extend + 127 | -2 * softclip. 128 | --use_zs Use the value of the ZS tag in place of XS for 129 | determining the mapping score of the next best 130 | alignment. Used with HISAT as the XS:A tag is 131 | conventionally used for strand in spliced mappers. 132 | --version print version information and exit 133 | 134 | 135 | To output bam files in a bash shell use process substitution: 136 | 137 | 138 | xenomapper --primary_specific >(samtools view -bS - > outfilename.bam) 139 | 140 | 141 | A worked example of using xenomapper can be found in [example_usage.ipynb](example_usage.ipynb) 142 | 143 | xenomappability 144 | =============== 145 | xenomappability is a tool for creating mappability wiggle files that reflect the paired end and multi species nature of the final number more accurately than the commonly used single end mappability tracks. 146 | 147 | This feature is computationally intensive for useful genomes. In most cases you will want to segment into chromosomal or smaller regions and calculate on a cluster. 148 | 149 | 150 | xenomappability --fasta tests/data/test_from_EcoliK12DH10B.fasta --readlength 10 > tests/data/test_from_EcoliK12DH10B_10reads.fasta 151 | 152 | bowtie2-build tests/data/test_from_EcoliK12DH10B.fasta tests/data/test_from_EcoliK12DH10B 153 | bowtie2 -x tests/data/test_from_EcoliK12DH10B -f -U tests/data/test_from_EcoliK12DH10B_10reads.fasta -S tests/data/test_from_EcoliK12DH10B_10reads.sam 154 | 155 | xenomappability --mapped_test_data tests/data/test_from_EcoliK12DH10B_10reads.sam > tests/data/test_from_EcoliK12DH10B_10reads.wig 156 | xenomappability --single_end_wiggle tests/data/test_from_EcoliK12DH10B_10reads.wig --sam_for_sizes tests/data/paired_end_testdata_human.sam` 157 | 158 | Contributing to Xenomapper 159 | ========================== 160 | Xenomapper is licensed under the GPLv3. You are free to fork this repository under the terms of that license. If you have suggested changes please start by raising an issue in the issue tracker. Pull requests are welcome and will be included at the discretion of the author, but must have 100% test coverage. 161 | Bug reports should be made to the issue tracker. Difficulty in understanding how to use the software is a documentation bug, and should also be raised on the issue tracker with the tag `question` so your question and my response are easily found by others. 162 | 163 | 164 | Citing Xenomapper 165 | ================= 166 | 167 | Xenomapper is published in the Journal of Open Source Software. Please cite the paper in academic publications [DOI:10.21105.joss.00018](http://dx.doi.org/10.21105/joss.00018). Each release also has a Zenodo DOI identifier for each release. In an ideal world this is what you would cite to indicate the code you use, and make everything more reproducible but academic credit is better served at the moment by the paper. Try and include the Zenodo DOI or a version number in your methods. The DOI for the current release is [![DOI](https://zenodo.org/badge/11450/genomematt/xenomapper.svg)](https://zenodo.org/badge/latestdoi/11450/genomematt/xenomapper) 168 | 169 | References 170 | ================= 171 | Langmead B, Salzberg S. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012, 9:357-359. http://bowtie-bio.sourceforge.net/bowtie2/ 172 | 173 | Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015 12:357-60. https://github.com/infphilo/hisat 174 | -------------------------------------------------------------------------------- /README.txt: -------------------------------------------------------------------------------- 1 | xenomappability 2 | =============== 3 | 4 | xenomappability --fasta tests/data/test_from_EcoliK12DH10B.fasta --readlength 10 > tests/data/test_from_EcoliK12DH10B_10reads.fasta 5 | 6 | bowtie2-build tests/data/test_from_EcoliK12DH10B.fasta tests/data/test_from_EcoliK12DH10B 7 | bowtie2 -x tests/data/test_from_EcoliK12DH10B -f -U tests/data/test_from_EcoliK12DH10B_10reads.fasta -S tests/data/test_from_EcoliK12DH10B_10reads.sam 8 | 9 | xenomappability --mapped_test_data tests/data/test_from_EcoliK12DH10B_10reads.sam > tests/data/test_from_EcoliK12DH10B_10reads.wig 10 | xenomappability --single_end_wiggle tests/data/test_from_EcoliK12DH10B_10reads.wig --sam_for_sizes tests/data/paired_end_testdata_human.sam 11 | -------------------------------------------------------------------------------- /paper.bib: -------------------------------------------------------------------------------- 1 | @article{HISAT, 2 | author = {Kim, D. and Langmead, B. and Salzberg, S. L.}, 3 | title = {HISAT: a fast spliced aligner with low memory requirements}, 4 | journal = {Nat Methods}, 5 | volume = {12}, 6 | number = {4}, 7 | pages = {357-60}, 8 | ISSN = {1548-7105}, 9 | DOI = {10.1038/nmeth.3317}, 10 | url = {http://www.ncbi.nlm.nih.gov/pubmed/25751142}, 11 | year = {2015}, 12 | type = {Journal Article} 13 | } 14 | @article{BOWTIE2, 15 | author = {Langmead, B. and Salzberg, S. L.}, 16 | title = {Fast gapped-read alignment with Bowtie 2}, 17 | journal = {Nat Methods}, 18 | volume = {9}, 19 | number = {4}, 20 | pages = {357-9}, 21 | ISSN = {1548-7105}, 22 | DOI = {10.1038/nmeth.1923}, 23 | url = {http://www.ncbi.nlm.nih.gov/pubmed/22388286}, 24 | year = {2012}, 25 | type = {Journal Article} 26 | } 27 | @article{ROSSELLO, 28 | author = {Rossello, F. J. and Tothill, R. W. and Britt, K. and Marini, K. D. and Falzon, J. and Thomas, D. M. and Peacock, C. D. and Marchionni, L. and Li, J. and Bennett, S. and Tantoso, E. and Brown, T. and Chan, P. and Martelotto, L. G. and Watkins, D. N.}, 29 | title = {Next-generation sequence analysis of cancer xenograft models}, 30 | journal = {PLoS One}, 31 | volume = {8}, 32 | number = {9}, 33 | pages = {e74432}, 34 | ISSN = {1932-6203}, 35 | DOI = {10.1371/journal.pone.0074432}, 36 | url = {http://www.ncbi.nlm.nih.gov/pubmed/24086345}, 37 | year = {2013}, 38 | type = {Journal Article} 39 | } -------------------------------------------------------------------------------- /paper.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: 'Xenomapper: Mapping reads in a mixed species context' 3 | tags: 4 | - bioinformatics 5 | - short read mapping 6 | - multispecies 7 | - xenograft 8 | authors: 9 | - name: Matthew J. Wakefield 10 | orcid: 0000-0001-6624-4698 11 | affiliation: The Walter and Eliza Hall Institute 12 | affiliation: The University of Melbourne 13 | date: 12 May 2016 14 | bibliography: paper.bib 15 | --- 16 | 17 | # Summary 18 | 19 | Xenomapper is a utility for post processing mapped DNA sequencing reads that have been aligned to a primary genome and a secondary genome, and binning reads into species specific, multimapping in each species, unmapped and unassigned categories. It can be used on single end or paired end sequencing data across a wide range of genomics methods including RNAseq. In paired end data evidence of sequence specificity for either read will be used to assign both reads. 20 | 21 | Use cases include xenografts of human cancers and host pathogen interactions. 22 | 23 | Xenomapper is most effective with mapped reads that include an XS or ZS score that gives the mapping score of the next best read. These include Bowtie2 [@BOWTIE2] and HISAT [@HISAT]. 24 | 25 | This work builds upon a similar approach by Rossello et. al. [@ROSSELLO] with a more rigorous implementation and extensions for paired end data and exon aware aligners. 26 | 27 | # References 28 | 29 | -------------------------------------------------------------------------------- /schematic.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/genomematt/xenomapper/5c859fb75747cf98e0ba7c7061ff795c8091dad0/schematic.jpg -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | # encoding: utf-8 3 | 4 | from setuptools import setup 5 | 6 | install_requires = [] 7 | 8 | try: 9 | import statistics 10 | except ImportError: 11 | install_requires.append('statistics') 12 | 13 | setup( 14 | name='XenoMapper', 15 | version='1.0.2', 16 | author='Matthew Wakefield', 17 | author_email='matthew.wakefield@unimelb.edu.au', 18 | packages=['xenomapper'], 19 | include_package_data = True, 20 | install_requires=install_requires, 21 | url='https://github.com/genomematt/xenomapper.git', 22 | license='GPLv3', 23 | entry_points={ 24 | 'console_scripts': ['xenomapper = xenomapper.xenomapper:main', 25 | 'xenomappability = xenomapper.mappability:main' 26 | ] 27 | }, 28 | test_suite='xenomapper.tests.test_all', 29 | description='xenomapper - mapping mixed reads from two species', 30 | long_description=open('README.md').read(), 31 | classifiers=[ 32 | 'Development Status :: 5 - Production/Stable', 33 | 'License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)', 34 | 'Operating System :: POSIX', 35 | 'Programming Language :: Python :: 3 :: Only', 36 | 'Programming Language :: Python :: 3.3', 37 | 'Programming Language :: Python :: 3.4', 38 | 'Programming Language :: Python :: 3.5', 39 | 'Programming Language :: Python :: 3.6', 40 | 'Programming Language :: Python :: 3.7', 41 | 'Programming Language :: Python :: Implementation :: CPython', 42 | 'Programming Language :: Python :: Implementation :: PyPy', 43 | 'Intended Audience :: Science/Research', 44 | 'Topic :: Scientific/Engineering :: Bio-Informatics', 45 | ], 46 | 47 | ) 48 | -------------------------------------------------------------------------------- /xenomapper/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/genomematt/xenomapper/5c859fb75747cf98e0ba7c7061ff795c8091dad0/xenomapper/__init__.py -------------------------------------------------------------------------------- /xenomapper/mappability.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | # encoding: utf-8 3 | """ 4 | mappability.py 5 | 6 | This is an experimental addition to the Xenomapper tool for parsing pairs of sam files and returning 7 | sam files containing only reads where no better mapping exist in other files. 8 | Used for filtering reads where multiple species may contribute (eg human tissue xenografted into mouse). 9 | 10 | This file contains functionality for calculating paired end mappability estimates using a distribution 11 | of insert sizes observed in the data and the probabilistic inference of a pair rescuing an otherwise 12 | non-unique read. This process is computationally intensive and in practice only improves mapping as 13 | very low coverages. 14 | 15 | This module should be considered experimental, and unlike the core xenomapper code which has been in 16 | active use for several years, should be considered beta quality. Caveat Emptor. 17 | 18 | Created by Matthew Wakefield on 2011-12-08. 19 | Copyright (c) 2011-2016 Matthew Wakefield and The Walter and Eliza Hall Institute. All rights reserved. 20 | """ 21 | import sys 22 | import os 23 | import argparse 24 | from statistics import * 25 | from collections import Counter 26 | from xenomapper.xenomapper import get_sam_header 27 | 28 | __author__ = "Matthew Wakefield" 29 | __copyright__ = "Copyright 2011-2019 Matthew Wakefield, The Walter and Eliza Hall Institute and The University of Melbourne" 30 | __credits__ = ["Matthew Wakefield",] 31 | __license__ = "GPLv3" 32 | __version__ = "1.0.2" 33 | __maintainer__ = "Matthew Wakefield" 34 | __email__ = "wakefield@wehi.edu.au" 35 | __status__ = "Development" 36 | 37 | 38 | class Mappability(dict): 39 | def __init__(self, chromosome_sizes = {}): 40 | if chromosome_sizes: 41 | for chrom in chromosome_sizes: 42 | self[chrom] = [0,]*chromosome_sizes[chrom] 43 | self.chromosome_sizes = chromosome_sizes 44 | pass 45 | 46 | def to_wiggle(self, wigglefile=sys.stdout, chromosomes=[]): 47 | """Output mappability data to file in wiggle format""" 48 | ## Wiggle file format is: 49 | #fixedStep chrom=chrN start=pos step=1 50 | #value 51 | #value 52 | for chrom in sorted(self): 53 | if not chromosomes or chrom in chromosomes: 54 | print('fixedStep\tchrom={0}\tstart=1\tstep=1'.format(chrom), file=wigglefile) 55 | for score in self[chrom]: 56 | print(str(score), file=wigglefile) 57 | pass 58 | 59 | def from_wiggle(self,wigglefile=sys.stdin,datatype=float): 60 | """Load mapability data from a wiggle file 61 | The wiggle file must be fixed step format, step of one and start at 1 62 | Multiple chromosomes may be present in the same file 63 | This function will overwrite any existing chromosomes 64 | with the same name but can be used sequentially for 65 | different chromosomes 66 | """ 67 | chrom=None 68 | values=[] 69 | for line in wigglefile: 70 | if line.startswith('fixedStep'): 71 | #add a chromosome to self 72 | #check it is not already there 73 | #check start=1 and step=1 74 | line = line.strip().split('\t') 75 | if line[1].split('=')[0] != 'chrom' or line[2] != 'start=1' or line[3] != 'step=1': #pragma: no cover 76 | raise ValueError('Unsupported wiggle fixed step format [must be in the format "fixedStep chrom=chrX start=1 step=1"] {0}'.format(line)) 77 | if chrom and values: 78 | #if we have accumulated values for a previous chromosome add them to self 79 | self[chrom]=values 80 | chrom=line[1].split('=')[1] 81 | values=[] 82 | else: 83 | try: 84 | values.append(datatype(line)) 85 | except: #pragma: no cover 86 | #placeholder for type conversion error handling 87 | raise 88 | #at end of file add remaining data to self 89 | self[chrom]=values 90 | for chrom in self: 91 | self.chromosome_sizes[chrom]=len(self[chrom]) 92 | pass 93 | 94 | def single_end_to_paired(self, mate_density = [1,]): 95 | """Produce a new mappability object with paired end mapping probilities 96 | Defines paired end mappability as either end being uniquely mappable. 97 | Arguments: 98 | mate_density: a list of floats between 0.0 and 1.0 representing mate densities. 99 | First entry corresponds to current position 100 | all entries must sum to 1.0 101 | """ 102 | def _mappability_by_mate_density(mapability,mate_density): 103 | #defined as local scope function as may be replaced for speed. 104 | result = 0.0 105 | j = 0 106 | while j < len(mapability) and j < len(mate_density): 107 | result += mapability[j] * mate_density[j] 108 | j += 1 109 | return result 110 | 111 | #should sum to 1 but allow for numerical error 112 | #summing to 1 is not algorythmically essential 113 | assert abs(sum(mate_density)-1.0) < 0.000001 114 | 115 | paired_mappability = Mappability(chromosome_sizes = self.chromosome_sizes) 116 | 117 | for chrom in self: 118 | for i in range(len(self[chrom])): 119 | if self[chrom][i] == 1: 120 | paired_mappability[chrom][i] = 1.0 121 | else: 122 | paired_mappability[chrom][i] = _mappability_by_mate_density(self[chrom][i:i+len(mate_density)],mate_density) 123 | 124 | return paired_mappability 125 | 126 | 127 | def parse_fasta(fastafile, token='>'): 128 | """fasta and multi-fasta file parser 129 | Usage: for name,seq in fasta(open(filename)): 130 | do something 131 | next(parse_fasta(open(filename))) 132 | """ 133 | with fastafile as f: 134 | seq = None 135 | name = None 136 | for line in f: 137 | line = line.strip() 138 | if line.startswith(token): 139 | if name: 140 | yield (name, seq) 141 | seq = '' 142 | name = line[1:] 143 | elif seq != None: 144 | seq += line 145 | if name: 146 | yield (name, seq) 147 | 148 | def make_blocklist(seqstring, block_size=80): 149 | """format sequence into a list of blocks""" 150 | blocklist = [] 151 | seqlength = len(seqstring) 152 | for block in range(0, seqlength, block_size): 153 | if block + block_size < seqlength: 154 | blocklist.append(seqstring[block: block + block_size]) 155 | else: 156 | blocklist.append(seqstring[block:]) 157 | return blocklist 158 | 159 | def slice_string_in_blocks(seqstring, block_size=80): 160 | """slice string into block_size[=80] lines""" 161 | blocklist = make_blocklist(seqstring, block_size) 162 | return '\n'.join(blocklist) + '\n' 163 | 164 | def format_fasta(name,seq, block_size=80): 165 | """returns a string in fasta format""" 166 | return '>'+name+'\n'+slice_string_in_blocks(seq,block_size) 167 | 168 | def simulate_reads(fastafile, readlength=100, outfile=sys.stdout): 169 | for name, seq in parse_fasta(fastafile): 170 | for x in range(len(seq)-readlength+1): 171 | newname = '{chrom}_{one_based_pos}'.format(chrom=name.split()[0],one_based_pos=x+1) 172 | outfile.write(format_fasta(newname,seq[x:x+readlength])) 173 | pass 174 | 175 | def single_end_mappability_from_sam(samfile, outfile=sys.stdout, fill_sequence_gaps=True, chromosome_sizes = {}): 176 | mappable = Mappability(chromosome_sizes=chromosome_sizes) 177 | 178 | #parse sam data and add to object 179 | header = get_sam_header(samfile) 180 | mappable_chrom = None 181 | mappable_pos = 0 182 | mappable_values = [] 183 | for line in samfile: 184 | name, x, chrom, pos, flag, cigar, mate_chr, mate_pos, insert_size, seq, qual, *tags = line.strip('\n').split() 185 | true_chrom = '_'.join(name.split('_')[:-1]) #name may have _ so we split off last and join 186 | if mappable_chrom != true_chrom: #add next chromosome to mappable_chrom if new 187 | if mappable_chrom and mappable_values: 188 | mappable[mappable_chrom] = mappable_values 189 | mappable_chrom = chrom 190 | mappable_pos = 0 191 | mappable_values = [] 192 | mappable_pos += 1 193 | name_pos = int(name.split('_')[-1]) 194 | if name_pos != mappable_pos: #pragma: no cover 195 | if not name_pos > mappable_pos: 196 | raise ValueError('Name is not sequential. SAM must be in name sorted order Name: {0} Expected: {1}_{2}'.format(name,mappable_chrom,mappable_pos)) 197 | else: 198 | #there are missing reads in the sequence. 199 | number_missing = name_pos - mappable_pos 200 | mappable_pos = name_pos 201 | mappable_values.extend([0,]*number_missing) 202 | 203 | if (true_chrom, name_pos) == (chrom, int(pos)) and flag == '42': 204 | mappable_values.append(1) 205 | else: 206 | mappable_values.append(0) 207 | #add remainging chromosome and values at the end of the file 208 | if mappable_chrom and mappable_values: 209 | mappable[mappable_chrom] = mappable_values 210 | 211 | #write wiggle file 212 | mappable.to_wiggle(wigglefile=outfile) 213 | 214 | pass 215 | 216 | def paired_end_mappability(wiggle, mate_density, outfile=sys.stdout, chromosome_sizes={}): 217 | """Create a wiggle file of read mappability using inferred mapping rate of pairs 218 | Arguments: 219 | wiggle - a wiggle file of mappability 220 | mate_density - an iterable of floats summing to 1 representing 221 | the probability of observing a pair. 222 | (Usually output of mate_distribution_from_sam) 223 | outfile - file object for writing ouput wiggle file 224 | chromosome_sizes - a dictionary of chromosome sizes 225 | """ 226 | mappable = Mappability(chromosome_sizes=chromosome_sizes) 227 | chromosomes = list(chromosome_sizes.keys()) 228 | 229 | mappable.from_wiggle(wiggle, datatype=float) 230 | 231 | pair_mappability = mappable.single_end_to_paired(mate_density = mate_density) 232 | 233 | pair_mappability.to_wiggle(wigglefile=outfile, chromosomes=chromosomes) 234 | 235 | pass 236 | 237 | def smoothed_list(the_list,width=10): 238 | return [mean(the_list[max(0,x-width-1):x+width]) for x in range(len(the_list))] 239 | 240 | def normalised_list(the_list): 241 | total = sum(the_list) 242 | return [x/total for x in the_list] 243 | 244 | def remove_small_values(the_list,relative_limit=0.1): 245 | """replaces values less than maximum_value * relative_limit with 0""" 246 | min_value = max(the_list) * relative_limit 247 | result = [] 248 | for x in the_list: 249 | if x > min_value: 250 | result.append(x) 251 | else: 252 | result.append(0) 253 | return result 254 | 255 | def mate_distribution_from_sam(samfile=sys.stdin, sample_size=10000): 256 | """Calculate the mate density (distribution) of read pair sizes from a sam file""" 257 | sizes = [] 258 | for line in samfile: 259 | if not line or line[0] == '@': 260 | continue 261 | name, x, chrom, pos, flag, cigar, mate_chr, mate_pos, insert_size, seq, qual, *tags = line.strip('\n').split() 262 | if flag not in [] and insert_size != '0':#this should be for flag in and list of valid mate pair mapped flags 263 | sizes.append(abs(int(insert_size))) 264 | if sample_size and len(sizes) > sample_size: 265 | break 266 | frequencies = Counter(sizes) 267 | mate_density = [] 268 | for i in range(0,max(sizes)): 269 | if i in frequencies: 270 | mate_density.append(frequencies[i]) 271 | else: 272 | mate_density.append(0) 273 | return normalised_list(remove_small_values(smoothed_list(mate_density))) 274 | 275 | def command_line_interface(): #pragma: no cover 276 | parser = argparse.ArgumentParser(description='Caution: Experimental - Beta quality functionality.\ 277 | A script for generating mappability estimates for paired end data.\ 278 | Paired end mappability is inferred from single end mappability.\ 279 | Step one is to generate a fasta file of reads from a fasta file using --fasta \ 280 | You then process these reads through your mapping process. \ 281 | For xenomapper this is mapping against the two reference genomes in \ 282 | single end mode, and processing to primary unique mappings. \ 283 | Step three is to generate a single end mappability wiggle with --mapped_test_data.\ 284 | Step four is to generate a mappability wiggle file using the --single_end_wiggle and --sam_for_sizes.') 285 | parser.add_argument('--fasta', 286 | type=argparse.FileType('rt'), 287 | help='Process a fasta genome file of sequences to simulated reads in fasta format.\ 288 | Outputs fasta file to standard output.') 289 | parser.add_argument('--readlength', 290 | type=int, 291 | default = 100, 292 | help='The readlength to simulate.') 293 | parser.add_argument('--mapped_test_data', 294 | type=argparse.FileType('rt'), 295 | help='a SAM format input file of mapped reads generated by the --fasta command.\ 296 | The SAM file must be sorted by read name.\ 297 | outputs a fixed step wiggle file to standard output.') 298 | parser.add_argument('--single_end_wiggle', 299 | type=argparse.FileType('rt'), 300 | help='a wiggle file of single end mappabilities') 301 | parser.add_argument('--sam_for_sizes', 302 | type=argparse.FileType('rt'), 303 | help='a sam file for calculating insert sizes') 304 | parser.add_argument('--version', 305 | action='store_true', 306 | help='print version information and exit') 307 | args = parser.parse_args() 308 | if args.version: 309 | print(__version__) 310 | sys.exit() 311 | if (not args.fasta) and (not args.mapped_test_data) and (not args.single_end_wiggle): 312 | print('ERROR: Insufficient arguments provided') 313 | parser.print_help() 314 | sys.exit(1) 315 | return args 316 | 317 | def main(args=None): #pragma: no cover 318 | if not args: 319 | args = command_line_interface() 320 | if args.fasta: 321 | simulate_reads(fastafile=args.fasta, readlength=args.readlength) 322 | elif args.mapped_test_data: 323 | single_end_mappability_from_sam(samfile=args.mapped_test_data) 324 | elif args.single_end_wiggle: 325 | if not args.sam_for_sizes: 326 | raise RuntimeError('You must provide a sam file to estimate the mate pair distance distribution') 327 | mate_density = mate_distribution_from_sam(args.sam_for_sizes) 328 | paired_end_mappability(wiggle=args.single_end_wiggle, mate_density=mate_density) 329 | pass 330 | 331 | 332 | if __name__ == '__main__': # pragma: no cover 333 | main() 334 | 335 | 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TGATAGCAGCTTCTGAACTGGTTACCTGCCGTGAGTAAATTAAAATTTTATTGACTTAGG 4 | TCACTAAATACTTTAACCAATATAGGCATAGCGCACAGACAGATAAAAATTACAGAGTAC 5 | ACAACATCCATGAAACGCATTAGCACCACCATTACCACCACCATCACCATTACCACAGGT 6 | AACGGTGCGGGCTGACGCGTACAGGAAACACAGAAAAAAGCCCGCACCTGACAGTGCGGG 7 | CTTTTTTTTTCGACCAAAGGTAACGAGGTAACAACCATGCGAGTGTTGAAGTTCGGCGGT 8 | ACATCAGTGGCAAATGCAGAACGTTTTCTGCGTGTTGCCGATATTCTGGAAAGCAATGCC 9 | AGGCAGGGGCAGGTGGCCACCGTCCTCTCTGCCCCCGCCAAAATCACCAACCACCTGGTG 10 | GCGATGATTGAAAAAACCATTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGAA 11 | CGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGCG 12 | CAATTGAAAACTTTCGTCGATCAGGAATTTGCCCAAATAAAACATGTCCTGCATGGCATT 13 | AGTTTGTTGGGGCAGTGCCCGGATAGCATCAACGCTGCGCTGATTTGCCGTGGCGAGAAA 14 | ATGTCGATCGCCATTATGGCCGGCGTATTAGAAGCGCGCGGTCACAACGTTACTGTTATC 15 | GATCCGGTCGAAAAACTGCTGGCAGTGGGGCATTACCTCGAATCTACCGTCGATATTGCT 16 | GAGTCCACCCGCCGTATTGCGGCAAGCCGCATTCCGGCTGATCACATGGTGCTGATGGCA 17 | GGTTTCACCGCCGGTAATGAAAAAGGCGAACTGGTGGTGCTTGGACGCAACGGTTCCGAC 18 | TACTCTGCTGCGGTGCTGGCTGCCTGTTTACGCGCCGATTGTTGCGAGATTTGGACGGAC 19 | GTTGACGGGGTCTATACCTGCGACCCGCGTCAGGTGCCCGATGCGAGGTTGTTGAAGTCG 20 | ATGTCCTACCAGGAAGCGATGGAGCTTTCCTACTTCGGCGCTAAAGTTCTTCACCCCCGC 21 | ACCATTACCCCCATCGCCCAGTTCCAGATCCCTTGCCTGATTAAAAATACCGGAAATCCT 22 | CAAGCACCAGGTACGCTCATTGGTGCCAGCCGTGATGAAGACGAATTACCGGTCAAGGGC 23 | ATTTCCAATCTGAATAACATGGCAATGTTCAGCGTTTCTGGTCCGGGGATGAAAGGGATG 24 | GTCGGCATGGCGGCGCGCGTCTTTGCAGCGATGTCACGCGCCCGTATTTCCGTGGTGCTG 25 | ATTACGCAATCATCTTCCGAATACAGCATCAGTTTCTGCGTTCCACAAAGCGACTGTGTG 26 | CGAGCTGAACGGGCAATGCAGGAAGAGTTCTACCTGGAACTGAAAGAAGGCTTACTGGAG 27 | CCGCTGGCAGTGACGGAACGGCTGGCCATTATCTCGGTGGTAGGTGATGGTATGCGCACC 28 | TTGCGTGGGATCTCGGCGAAATTCTTTGCCGCACTGGCCCGCGCCAATATCAACATTGTC 29 | GCCATTGCTCAGGGATCTTCTGAACGCTCAATCTCTGTCGTGGTAAATAACGATGATGCG 30 | ACCACTGGCGTGCGCGTTACTCATCAGATGCTGTTCAATACCGATCAGGTTATCGAAGTG 31 | TTTGTGATTGGCGTCGGTGGCGTTGGCGGTGCGCTGCTGGAGCAACTGAAGCGTCAGCAA 32 | AGCTGGCTGAAGAATAAACATATCGACTTACGTGTCTGCGGTGTTGCCAACTCGAAGGCT 33 | CTGCTCACCAATGTACATGGCCTTAATCTGGAAAACTGGCAGGAAGAACTGGCGCAAGCC 34 | AAAGAGCCGTTTAATCTCGGGCGCTTAATTCGCCTCGTGAAAGAATATCATCTGCTGAAC 35 | CCGGTCATTGTTGACTGCACTTCCAGCCAGGCAGTGGCGGATCAATATGCCGACTTCCTG 36 | CGCGAAGGTTTCCACGTTGTCACGCCGAACAAAAAGGCCAACACCTCGTCGATGGATTAC 37 | TACCATCAGTTGCGTTATGCGGCGGAAAAATCGCGGCGTAAATTCCTCTATGACACCAAC 38 | GTTGGGGCTGGATTACCGGTTATTGAGAACCTGCAAAATCTGCTCAATGCAGGTGATGAA 39 | TTGATGAAGTTCTCCGGCATTCTTTCTGGTTCGCTTTCTTATATCTTCGGCAAGTTAGAC 40 | GAAGGCATGAGTTTCTCCGAGGCGACCACGCTGGCGCGGGAAATGGGTTATACCGAACCG 41 | GACCCGCGAGATGATCTTTCTGGTATGGATGTGGCGCGTAAACTATTGATTCTCGCTCGT 42 | GAAACGGGACGTGAACTGGAGCTGGCGGATATTGAAATTGAACCTGTGCTGCCCGCAGAG 43 | TTTAACGCCGAGGGTGATGTTGCCGCTTTTATGGCGAATCTGTCACAACTCGACGATCTC 44 | TTTGCCGCGCGCGTGGCGAAGGCCCGTGATGAAGGAAAAGTTTTGCGCTATGTTGGCAAT 45 | ATTGATGAAGATGGCGTCTGCCGCGTGAAGATTGCCGAAGTGGATGGTAATGATCCGCTG 46 | TTCAAAGTGAAAAATGGCGAAAACGCCCTGGCCTTCTATAGCCACTATTATCAGCCGCTG 47 | CCGTTGGTACTGCGCGGATATGGTGCGGGCAATGACGTTACAGCTGCCGGTGTCTTTGCT 48 | >A_Repeat 49 | TTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTT 50 | TGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGCTTAGCGGCCAGGATGCTTTA 51 | CCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCC 52 | CAGCCGGGGTTCCCGCTGGCTTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGA 53 | ACGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGC 54 | TTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTT 55 | TGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGCTTAGCGGCCAGGATGCTTTA 56 | CCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCC 57 | CAGCCGGGGTTCCCGCTGGCTTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGA 58 | ACGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGC 59 | TTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTT 60 | TGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGCTTAGCGGCCAGGATGCTTTA 61 | CCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCC 62 | CAGCCGGGGTTCCCGCTGGCTTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGA 63 | ACGTATTTTTGCCGAACTTTTGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGC 64 | TTAGCGGCCAGGATGCTTTACCCAATATCAGCGATGCCGAACGTATTTTTGCCGAACTTT 65 | TGACGGGACTCGCCGCCGCCCAGCCGGGGTTCCCGCTGGC 66 | -------------------------------------------------------------------------------- /xenomapper/tests/data/test_from_EcoliK12DH10B.rev.1.bt2: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/genomematt/xenomapper/5c859fb75747cf98e0ba7c7061ff795c8091dad0/xenomapper/tests/data/test_from_EcoliK12DH10B.rev.1.bt2 -------------------------------------------------------------------------------- /xenomapper/tests/data/test_from_EcoliK12DH10B.rev.2.bt2: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/genomematt/xenomapper/5c859fb75747cf98e0ba7c7061ff795c8091dad0/xenomapper/tests/data/test_from_EcoliK12DH10B.rev.2.bt2 -------------------------------------------------------------------------------- /xenomapper/tests/data/test_from_EcoliK12DH10B_10reads.wig: -------------------------------------------------------------------------------- 1 | fixedStep chrom=Chromosome start=1 step=1 2 | 1 3 | 1 4 | 0 5 | 1 6 | 1 7 | 1 8 | 1 9 | 1 10 | 1 11 | 1 12 | 1 13 | 1 14 | 1 15 | 1 16 | 1 17 | 1 18 | 1 19 | 0 20 | 0 21 | 0 22 | 0 23 | 1 24 | 1 25 | 1 26 | 1 27 | 1 28 | 1 29 | 1 30 | 1 31 | 1 32 | 1 33 | 1 34 | 1 35 | 1 36 | 1 37 | 1 38 | 1 39 | 1 40 | 1 41 | 1 42 | 1 43 | 0 44 | 0 45 | 0 46 | 1 47 | 1 48 | 0 49 | 1 50 | 1 51 | 1 52 | 1 53 | 1 54 | 1 55 | 1 56 | 1 57 | 1 58 | 1 59 | 1 60 | 1 61 | 0 62 | 1 63 | 1 64 | 1 65 | 1 66 | 1 67 | 1 68 | 0 69 | 0 70 | 0 71 | 0 72 | 1 73 | 1 74 | 1 75 | 1 76 | 1 77 | 1 78 | 1 79 | 0 80 | 1 81 | 1 82 | 1 83 | 1 84 | 1 85 | 1 86 | 0 87 | 1 88 | 1 89 | 1 90 | 1 91 | 1 92 | 1 93 | 1 94 | 1 95 | 1 96 | 1 97 | 1 98 | 1 99 | 1 100 | 0 101 | 0 102 | 0 103 | 0 104 | 0 105 | 1 106 | 1 107 | 1 108 | 1 109 | 1 110 | 0 111 | 1 112 | 1 113 | 1 114 | 1 115 | 1 116 | 1 117 | 1 118 | 1 119 | 1 120 | 1 121 | 1 122 | 1 123 | 1 124 | 1 125 | 1 126 | 1 127 | 1 128 | 1 129 | 1 130 | 1 131 | 1 132 | 0 133 | 0 134 | 0 135 | 0 136 | 1 137 | 1 138 | 1 139 | 1 140 | 0 141 | 1 142 | 1 143 | 1 144 | 1 145 | 1 146 | 1 147 | 0 148 | 0 149 | 0 150 | 1 151 | 1 152 | 1 153 | 1 154 | 1 155 | 1 156 | 1 157 | 1 158 | 1 159 | 1 160 | 0 161 | 1 162 | 1 163 | 1 164 | 1 165 | 1 166 | 1 167 | 1 168 | 1 169 | 1 170 | 1 171 | 1 172 | 1 173 | 1 174 | 1 175 | 1 176 | 1 177 | 1 178 | 1 179 | 1 180 | 1 181 | 1 182 | 1 183 | 0 184 | 0 185 | 1 186 | 1 187 | 1 188 | 1 189 | 1 190 | 1 191 | 1 192 | 1 193 | 1 194 | 1 195 | 1 196 | 1 197 | 1 198 | 1 199 | 0 200 | 0 201 | 0 202 | 0 203 | 0 204 | 0 205 | 0 206 | 0 207 | 0 208 | 0 209 | 0 210 | 0 211 | 0 212 | 0 213 | 0 214 | 0 215 | 0 216 | 0 217 | 0 218 | 0 219 | 0 220 | 0 221 | 0 222 | 0 223 | 0 224 | 0 225 | 0 226 | 0 227 | 0 228 | 0 229 | 0 230 | 1 231 | 1 232 | 1 233 | 0 234 | 0 235 | 0 236 | 0 237 | 1 238 | 1 239 | 0 240 | 0 241 | 0 242 | 0 243 | 0 244 | 0 245 | 0 246 | 0 247 | 0 248 | 1 249 | 1 250 | 1 251 | 1 252 | 0 253 | 1 254 | 1 255 | 1 256 | 1 257 | 1 258 | 1 259 | 1 260 | 1 261 | 1 262 | 1 263 | 1 264 | 1 265 | 1 266 | 1 267 | 1 268 | 0 269 | 0 270 | 1 271 | 0 272 | 1 273 | 0 274 | 0 275 | 0 276 | 0 277 | 0 278 | 0 279 | 0 280 | 0 281 | 0 282 | 1 283 | 1 284 | 0 285 | 0 286 | 1 287 | 1 288 | 1 289 | 1 290 | 1 291 | 0 292 | 0 293 | 0 294 | 0 295 | 0 296 | 0 297 | 0 298 | 0 299 | 0 300 | 0 301 | 0 302 | 0 303 | 1 304 | 0 305 | 1 306 | 0 307 | 0 308 | 0 309 | 1 310 | 1 311 | 0 312 | 1 313 | 1 314 | 0 315 | 0 316 | 0 317 | 0 318 | 1 319 | 0 320 | 1 321 | 1 322 | 1 323 | 1 324 | 1 325 | 1 326 | 1 327 | 1 328 | 1 329 | 1 330 | 1 331 | 0 332 | 1 333 | 1 334 | 1 335 | 1 336 | 1 337 | 1 338 | 1 339 | 1 340 | 1 341 | 1 342 | 1 343 | 1 344 | 0 345 | 0 346 | 0 347 | 1 348 | 1 349 | 0 350 | 0 351 | 1 352 | 1 353 | 0 354 | 1 355 | 1 356 | 1 357 | 1 358 | 1 359 | 1 360 | 1 361 | 1 362 | 1 363 | 0 364 | 1 365 | 1 366 | 1 367 | 1 368 | 1 369 | 1 370 | 1 371 | 1 372 | 1 373 | 1 374 | 1 375 | 0 376 | 0 377 | 1 378 | 1 379 | 1 380 | 0 381 | 1 382 | 1 383 | 1 384 | 1 385 | 0 386 | 0 387 | 1 388 | 1 389 | 1 390 | 1 391 | 1 392 | 1 393 | 0 394 | 0 395 | 1 396 | 1 397 | 0 398 | 1 399 | 1 400 | 1 401 | 1 402 | 1 403 | 0 404 | 0 405 | 1 406 | 0 407 | 1 408 | 1 409 | 1 410 | 1 411 | 1 412 | 1 413 | 1 414 | 1 415 | 1 416 | 0 417 | 0 418 | 0 419 | 0 420 | 0 421 | 0 422 | 0 423 | 0 424 | 0 425 | 1 426 | 1 427 | 1 428 | 1 429 | 1 430 | 1 431 | 1 432 | 0 433 | 0 434 | 0 435 | 1 436 | 1 437 | 1 438 | 1 439 | 1 440 | 1 441 | 1 442 | 1 443 | 1 444 | 1 445 | 1 446 | 1 447 | 1 448 | 1 449 | 1 450 | 0 451 | 0 452 | 0 453 | 0 454 | 1 455 | 0 456 | 1 457 | 0 458 | 0 459 | 1 460 | 0 461 | 1 462 | 1 463 | 0 464 | 0 465 | 0 466 | 0 467 | 0 468 | 1 469 | 1 470 | 1 471 | 1 472 | 0 473 | 0 474 | 1 475 | 1 476 | 1 477 | 1 478 | 0 479 | 1 480 | 1 481 | 1 482 | 1 483 | 1 484 | 1 485 | 1 486 | 0 487 | 0 488 | 0 489 | 1 490 | 1 491 | 1 492 | 1 493 | 1 494 | 1 495 | 1 496 | 1 497 | 1 498 | 1 499 | 0 500 | 0 501 | 0 502 | 0 503 | 0 504 | 0 505 | 0 506 | 0 507 | 0 508 | 0 509 | 0 510 | 0 511 | 0 512 | 0 513 | 0 514 | 0 515 | 0 516 | 0 517 | 0 518 | 0 519 | 0 520 | 0 521 | 0 522 | 0 523 | 0 524 | 0 525 | 0 526 | 0 527 | 0 528 | 0 529 | 0 530 | 0 531 | 0 532 | 0 533 | 0 534 | 0 535 | 0 536 | 0 537 | 0 538 | 0 539 | 0 540 | 0 541 | 0 542 | 0 543 | 0 544 | 0 545 | 0 546 | 0 547 | 0 548 | 0 549 | 0 550 | 0 551 | 0 552 | 0 553 | 0 554 | 0 555 | 0 556 | 0 557 | 0 558 | 0 559 | 0 560 | 0 561 | 0 562 | 0 563 | 0 564 | 0 565 | 0 566 | 0 567 | 0 568 | 0 569 | 0 570 | 0 571 | 0 572 | 0 573 | 0 574 | 0 575 | 0 576 | 0 577 | 0 578 | 0 579 | 0 580 | 0 581 | 0 582 | 0 583 | 0 584 | 0 585 | 0 586 | 0 587 | 0 588 | 0 589 | 0 590 | 0 591 | 0 592 | 0 593 | 0 594 | 0 595 | 0 596 | 0 597 | 1 598 | 1 599 | 1 600 | 1 601 | 1 602 | 1 603 | 1 604 | 1 605 | 1 606 | 1 607 | 0 608 | 1 609 | 1 610 | 1 611 | 1 612 | 0 613 | 1 614 | 1 615 | 1 616 | 1 617 | 1 618 | 1 619 | 1 620 | 1 621 | 1 622 | 1 623 | 1 624 | 0 625 | 1 626 | 1 627 | 1 628 | 1 629 | 1 630 | 1 631 | 1 632 | 1 633 | 1 634 | 1 635 | 1 636 | 1 637 | 1 638 | 1 639 | 1 640 | 1 641 | 1 642 | 1 643 | 1 644 | 1 645 | 1 646 | 1 647 | 1 648 | 0 649 | 0 650 | 0 651 | 0 652 | 0 653 | 0 654 | 1 655 | 1 656 | 0 657 | 0 658 | 1 659 | 1 660 | 1 661 | 1 662 | 1 663 | 1 664 | 1 665 | 1 666 | 1 667 | 0 668 | 1 669 | 1 670 | 0 671 | 0 672 | 0 673 | 0 674 | 1 675 | 1 676 | 1 677 | 0 678 | 1 679 | 1 680 | 1 681 | 1 682 | 1 683 | 1 684 | 1 685 | 1 686 | 1 687 | 1 688 | 1 689 | 1 690 | 1 691 | 1 692 | 1 693 | 1 694 | 0 695 | 1 696 | 0 697 | 1 698 | 1 699 | 1 700 | 1 701 | 1 702 | 1 703 | 1 704 | 1 705 | 1 706 | 1 707 | 1 708 | 1 709 | 1 710 | 1 711 | 1 712 | 1 713 | 1 714 | 1 715 | 0 716 | 1 717 | 1 718 | 1 719 | 0 720 | 1 721 | 0 722 | 0 723 | 1 724 | 1 725 | 1 726 | 0 727 | 0 728 | 0 729 | 0 730 | 1 731 | 0 732 | 0 733 | 1 734 | 1 735 | 1 736 | 1 737 | 1 738 | 1 739 | 1 740 | 1 741 | 0 742 | 1 743 | 1 744 | 1 745 | 1 746 | 1 747 | 1 748 | 1 749 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2554 | 0 2555 | 1 2556 | 1 2557 | 1 2558 | 1 2559 | 1 2560 | 1 2561 | 1 2562 | 1 2563 | 0 2564 | 0 2565 | 0 2566 | 1 2567 | 1 2568 | 1 2569 | 1 2570 | 1 2571 | 1 2572 | 1 2573 | 0 2574 | 1 2575 | 0 2576 | 1 2577 | 0 2578 | 0 2579 | 1 2580 | 0 2581 | 0 2582 | 0 2583 | 0 2584 | 0 2585 | 0 2586 | 1 2587 | 0 2588 | 1 2589 | 1 2590 | 1 2591 | 1 2592 | 1 2593 | 1 2594 | 1 2595 | 1 2596 | 1 2597 | 1 2598 | 1 2599 | 1 2600 | 1 2601 | 0 2602 | 1 2603 | 1 2604 | 1 2605 | 1 2606 | 1 2607 | 0 2608 | 0 2609 | 0 2610 | 1 2611 | 1 2612 | 0 2613 | 0 2614 | 1 2615 | 0 2616 | 1 2617 | 1 2618 | 0 2619 | 1 2620 | 1 2621 | 1 2622 | 1 2623 | 1 2624 | 0 2625 | 1 2626 | 0 2627 | 1 2628 | 1 2629 | 0 2630 | 0 2631 | 1 2632 | 1 2633 | 1 2634 | 1 2635 | 1 2636 | 1 2637 | 0 2638 | 0 2639 | 1 2640 | 1 2641 | 1 2642 | 1 2643 | 1 2644 | 1 2645 | 1 2646 | 1 2647 | 1 2648 | 1 2649 | 1 2650 | 0 2651 | 0 2652 | 0 2653 | 0 2654 | 0 2655 | 0 2656 | 1 2657 | 1 2658 | 1 2659 | 1 2660 | 1 2661 | 1 2662 | 1 2663 | 1 2664 | 1 2665 | 0 2666 | 1 2667 | 1 2668 | 1 2669 | 1 2670 | 1 2671 | 1 2672 | 1 2673 | 1 2674 | 1 2675 | 1 2676 | 1 2677 | 1 2678 | 1 2679 | 1 2680 | 1 2681 | 1 2682 | 1 2683 | 1 2684 | 1 2685 | 1 2686 | 1 2687 | 1 2688 | 1 2689 | 0 2690 | 1 2691 | 1 2692 | 1 2693 | 1 2694 | 0 2695 | 1 2696 | 1 2697 | 1 2698 | 0 2699 | 1 2700 | 1 2701 | 1 2702 | 1 2703 | 1 2704 | 1 2705 | 1 2706 | 1 2707 | 1 2708 | 1 2709 | 1 2710 | 1 2711 | 0 2712 | 0 2713 | 1 2714 | 1 2715 | 0 2716 | 1 2717 | 1 2718 | 1 2719 | 1 2720 | 0 2721 | 0 2722 | 0 2723 | 0 2724 | 1 2725 | 1 2726 | 0 2727 | 0 2728 | 1 2729 | 0 2730 | 1 2731 | 1 2732 | 1 2733 | 1 2734 | 1 2735 | 1 2736 | 1 2737 | 1 2738 | 1 2739 | 1 2740 | 1 2741 | 1 2742 | 1 2743 | 1 2744 | 0 2745 | 1 2746 | 1 2747 | 1 2748 | 1 2749 | 1 2750 | 1 2751 | 0 2752 | 1 2753 | fixedStep chrom=Repeat start=1 step=1 2754 | 0 2755 | 0 2756 | 0 2757 | 0 2758 | 0 2759 | 0 2760 | 0 2761 | 0 2762 | 0 2763 | 0 2764 | 0 2765 | 0 2766 | 0 2767 | 0 2768 | 0 2769 | 0 2770 | 0 2771 | 0 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fixedStep chrom=Chromosome start=1 step=1 2 | 1 3 | 1 4 | 0 5 | 1 6 | 1 7 | 1 8 | 1 9 | 1 10 | 1 11 | 1 12 | 1 13 | 1 14 | 1 15 | 1 16 | 1 17 | 1 18 | 1 19 | 0 20 | 0 21 | 0 22 | 0 23 | 1 24 | 1 25 | 1 26 | 1 27 | 1 28 | 1 29 | 1 30 | 1 31 | 1 32 | 1 33 | 1 34 | 1 35 | 1 36 | 1 37 | 1 38 | 1 39 | 1 40 | 1 41 | 1 42 | 1 43 | 0 44 | 0 45 | 0 46 | 1 47 | 1 48 | 0 49 | 1 50 | 1 51 | 1 52 | 1 53 | 1 54 | 1 55 | 1 56 | 1 57 | 1 58 | 1 59 | 1 60 | 1 61 | 0 62 | 1 63 | 1 64 | 1 65 | 1 66 | 1 67 | 1 68 | 0 69 | 0 70 | 0 71 | 0 72 | 1 73 | 1 74 | 1 75 | 1 76 | 1 77 | 1 78 | 1 79 | 0 80 | 1 81 | 1 82 | 1 83 | 1 84 | 1 85 | 1 86 | 0 87 | 1 88 | 1 89 | 1 90 | 1 91 | 1 92 | 1 93 | 1 94 | 1 95 | 1 96 | 1 97 | 1 98 | 1 99 | 1 100 | 0 101 | 0 102 | 0 103 | 0 104 | 0 105 | 1 106 | 1 107 | 1 108 | 1 109 | 1 110 | 0 111 | 1 112 | 1 113 | 1 114 | 1 115 | 1 116 | 1 117 | 1 118 | 1 119 | 1 120 | 1 121 | 1 122 | 1 123 | 1 124 | 1 125 | 1 126 | 1 127 | 1 128 | 1 129 | 1 130 | 1 131 | 1 132 | 0 133 | 0 134 | 0 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2563 | 0 2564 | 0 2565 | 0 2566 | 1 2567 | 1 2568 | 1 2569 | 1 2570 | 1 2571 | 1 2572 | 1 2573 | 0 2574 | 1 2575 | 0 2576 | 1 2577 | 0 2578 | 0 2579 | 1 2580 | 0 2581 | 0 2582 | 0 2583 | 0 2584 | 0 2585 | 0 2586 | 1 2587 | 0 2588 | 1 2589 | 1 2590 | 1 2591 | 1 2592 | 1 2593 | 1 2594 | 1 2595 | 1 2596 | 1 2597 | 1 2598 | 1 2599 | 1 2600 | 1 2601 | 0 2602 | 1 2603 | 1 2604 | 1 2605 | 1 2606 | 1 2607 | 0 2608 | 0 2609 | 0 2610 | 1 2611 | 1 2612 | 0 2613 | 0 2614 | 1 2615 | 0 2616 | 1 2617 | 1 2618 | 0 2619 | 1 2620 | 1 2621 | 1 2622 | 1 2623 | 1 2624 | 0 2625 | 1 2626 | 0 2627 | 1 2628 | 1 2629 | 0 2630 | 0 2631 | 1 2632 | 1 2633 | 1 2634 | 1 2635 | 1 2636 | 1 2637 | 0 2638 | 0 2639 | 1 2640 | 1 2641 | 1 2642 | 1 2643 | 1 2644 | 1 2645 | 1 2646 | 1 2647 | 1 2648 | 1 2649 | 1 2650 | 0 2651 | 0 2652 | 0 2653 | 0 2654 | 0 2655 | 0 2656 | 1 2657 | 1 2658 | 1 2659 | 1 2660 | 1 2661 | 1 2662 | 1 2663 | 1 2664 | 1 2665 | 0 2666 | 1 2667 | 1 2668 | 1 2669 | 1 2670 | 1 2671 | 1 2672 | 1 2673 | 1 2674 | 1 2675 | 1 2676 | 1 2677 | 1 2678 | 1 2679 | 1 2680 | 1 2681 | 1 2682 | 1 2683 | 1 2684 | 1 2685 | 1 2686 | 1 2687 | 1 2688 | 1 2689 | 0 2690 | 1 2691 | 1 2692 | 1 2693 | 1 2694 | 0 2695 | 1 2696 | 1 2697 | 1 2698 | 0 2699 | 1 2700 | 1 2701 | 1 2702 | 1 2703 | 1 2704 | 1 2705 | 1 2706 | 1 2707 | 1 2708 | 1 2709 | 1 2710 | 1 2711 | 0 2712 | 0 2713 | 1 2714 | 1 2715 | 0 2716 | 1 2717 | 1 2718 | 1 2719 | 1 2720 | 0 2721 | 0 2722 | 0 2723 | 0 2724 | 1 2725 | 1 2726 | 0 2727 | 0 2728 | 1 2729 | 0 2730 | 1 2731 | 1 2732 | 1 2733 | 1 2734 | 1 2735 | 1 2736 | 1 2737 | 1 2738 | 1 2739 | 1 2740 | 1 2741 | 1 2742 | 1 2743 | 1 2744 | 0 2745 | 1 2746 | 1 2747 | 1 2748 | 1 2749 | 1 2750 | 1 2751 | 0 2752 | 1 2753 | fixedStep chrom=Repeat start=1 step=1 2754 | 0 2755 | 0 2756 | 0 2757 | 0 2758 | 0 2759 | 0 2760 | 0 2761 | 0 2762 | 0 2763 | 0 2764 | 0 2765 | 0 2766 | 0 2767 | 0 2768 | 0 2769 | 0 2770 | 0 2771 | 0 2772 | 0 2773 | 0 2774 | 0 2775 | 0 2776 | 0 2777 | 0 2778 | 0 2779 | 0 2780 | 0 2781 | 0 2782 | 0 2783 | 0 2784 | 0 2785 | 0 2786 | 0 2787 | 0 2788 | 0 2789 | 0 2790 | 0 2791 | 0 2792 | 0 2793 | 0 2794 | 0 2795 | 0 2796 | 0 2797 | 0 2798 | 0 2799 | 0 2800 | 0 2801 | 0 2802 | 0 2803 | 0 2804 | 0 2805 | 0 2806 | 0 2807 | 0 2808 | 0 2809 | 0 2810 | 0 2811 | 0 2812 | 0 2813 | 0 2814 | 0 2815 | 0 2816 | 0 2817 | 0 2818 | 0 2819 | 0 2820 | 0 2821 | 0 2822 | 0 2823 | 0 2824 | 0 2825 | 0 2826 | 0 2827 | 0 2828 | 0 2829 | 0 2830 | 0 2831 | 0 2832 | 0 2833 | 0 2834 | 0 2835 | 0 2836 | 0 2837 | 0 2838 | 0 2839 | 0 2840 | 0 2841 | 0 2842 | 0 2843 | 0 2844 | 0 2845 | 0 2846 | 0 2847 | 0 2848 | 0 2849 | 0 2850 | 0 2851 | 0 2852 | 0 2853 | 0 2854 | 0 2855 | 0 2856 | 0 2857 | 0 2858 | 0 2859 | 0 2860 | 0 2861 | 0 2862 | 0 2863 | 0 2864 | 0 2865 | 0 2866 | 0 2867 | 0 2868 | 0 2869 | 0 2870 | 0 2871 | 0 2872 | 0 2873 | 0 2874 | 0 2875 | 0 2876 | 0 2877 | 0 2878 | 0 2879 | 0 2880 | 0 2881 | 0 2882 | 0 2883 | 0 2884 | 0 2885 | 0 2886 | 0 2887 | 0 2888 | 0 2889 | 0 2890 | 0 2891 | 0 2892 | 0 2893 | 0 2894 | 0 2895 | 0 2896 | 0 2897 | 0 2898 | 0 2899 | 0 2900 | 0 2901 | 0 2902 | 0 2903 | 0 2904 | 0 2905 | 0 2906 | 0 2907 | 0 2908 | 0 2909 | 0 2910 | 0 2911 | 0 2912 | 0 2913 | 0 2914 | 0 2915 | 0 2916 | 0 2917 | 0 2918 | 0 2919 | 0 2920 | 0 2921 | 0 2922 | 0 2923 | 0 2924 | 0 2925 | 0 2926 | 0 2927 | 0 2928 | 0 2929 | 0 2930 | 0 2931 | 0 2932 | 0 2933 | 0 2934 | 0 2935 | 0 2936 | 0 2937 | 0 2938 | 0 2939 | 0 2940 | 0 2941 | 0 2942 | 0 2943 | 0 2944 | 0 2945 | 0 2946 | 0 2947 | 0 2948 | 0 2949 | 0 2950 | 0 2951 | 0 2952 | 0 2953 | 0 2954 | 0 2955 | 0 2956 | 0 2957 | 0 2958 | 0 2959 | 0 2960 | 0 2961 | 0 2962 | 0 2963 | 0 2964 | 0 2965 | 0 2966 | 0 2967 | 0 2968 | 0 2969 | 0 2970 | 0 2971 | 0 2972 | 0 2973 | 0 2974 | 0 2975 | 0 2976 | 0 2977 | 0 2978 | 0 2979 | 0 2980 | 0 2981 | 0 2982 | 0 2983 | 0 2984 | 0 2985 | 0 2986 | 0 2987 | 0 2988 | 0 2989 | 0 2990 | 0 2991 | 0 2992 | 0 2993 | 0 2994 | 0 2995 | 0 2996 | 0 2997 | 0 2998 | 0 2999 | 0 3000 | 0 3001 | 0 3002 | 0 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3669 | 0 3670 | 0 3671 | 0 3672 | 0 3673 | 0 3674 | 0 3675 | 0 3676 | 0 3677 | 0 3678 | 0 3679 | 0 3680 | 0 3681 | 0 3682 | 0 3683 | 0 3684 | 0 3685 | 0 3686 | 0 3687 | 0 3688 | 0 3689 | 0 3690 | 0 3691 | 0 3692 | 0 3693 | 0 3694 | 0 3695 | 0 3696 | 0 3697 | 0 3698 | 0 3699 | 0 3700 | 0 3701 | 0 3702 | 0 3703 | 0 3704 | 0 3705 | 0 3706 | 0 3707 | 0 3708 | 0 3709 | 0 3710 | 0 3711 | 0 3712 | 0 3713 | 0 3714 | 0 3715 | 0 3716 | 0 3717 | 0 3718 | 0 3719 | 0 3720 | 0 3721 | 0 3722 | 0 3723 | 0 3724 | 0 3725 | 0 3726 | 0 3727 | 0 3728 | 0 3729 | 0 3730 | 0 3731 | 0 3732 | 0 3733 | 0 3734 | 0 3735 | 0 3736 | 0 3737 | 0 3738 | 0 3739 | 0 3740 | 0 3741 | 0 3742 | 0 3743 | 0 3744 | 0 3745 | -------------------------------------------------------------------------------- /xenomapper/tests/data/test_human_in.sam: -------------------------------------------------------------------------------- 1 | @testheader 2 | HWI-ST960:63:D0CYJACXX:4:1101:1724:2248 0 1 569095 1 50M * 0 0 CTTCATTCATTGCCCCCACAATCCTAGGCCTACCCGCCGCAGTACTGATC CCCFFFFFHHHGHJIJIJJJJJJJIJJJJJJJJJIIJJIIIICGIJJJJ@ AS:i:100 XS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 3 | HWI-ST960:63:D0CYJACXX:4:1101:2294:2233 0 5 177022571 19 50M * 0 0 CTTGGCTAATACTGAGCAGGTAGTGGGGCAAATTCCTGCCCTCTCTCTCT CCCFFFFFHHHHHJJJJJJJHIJJJJJJJJJJJJJJJJJJJJJJJJJIJJ AS:i:100 XS:i:44 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 4 | HWI-ST960:63:D0CYJACXX:4:1101:2794:2226 0 19 19023793 4 17S33M * 0 0 GCCACACCGAACTTCCTCTGCGCCAGGTACGCTCTATACAGGAAGACGTC :11=ADDFHHGHHJJJJJJJJIHHGEHBDGHJJJJFHGI9CHIJ>EGBDH AS:i:66 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:33 YT:Z:UU 5 | HWI-ST960:63:D0CYJACXX:4:1101:3653:2249 0 10 114193076 44 50M * 0 0 CTTGTCTCAATGTTGAAAAATCGCCTTTCCTCATCAACTGTCAGAGTGAT CCCFFFFFGHHHHJJJJJJJIIJJJJJJJJJJJJJJJIJJGJJIIIBGHG AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 6 | HWI-ST960:63:D0CYJACXX:4:1101:3944:2248 16 Y 10011782 1 50M * 0 0 TAAAAGCTTACTTGACATATTTTAGAGACAAATAACTTAGATCAAGAAGA HIIIIIIHFDIIIHFIIIIIIIGIIIIICIIIGFEIGDHHHHFFFFD@@@ AS:i:100 XS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 7 | HWI-ST960:63:D0CYJACXX:4:1101:5254:2228 0 MT 6907 11 50M * 0 0 CTGCTGCAGTGCTCTGAGCCCTAGGATTCATCTTTCTTTTCACCGTAGGT CCCFFFFFHHHHHJJJJJJJJJJJJGHJJJJJJJJJJJJJJJJJJJJJJF AS:i:100 XS:i:66 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 8 | HWI-ST960:63:D0CYJACXX:4:1101:5933:2226 16 16 28735689 1 50M * 0 0 GAAAACAACCTGGGAGAGGGCGTCATTGTCAAGATCAAGTTCAATATCAT JJJJJIHHJJIJJJJJJJJJJIJJIJJJJJJJJJJJJHHHHHFFFFFCCC AS:i:100 XS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 9 | HWI-ST960:63:D0CYJACXX:4:1101:6148:2247 0 MT 7864 3 50M * 0 0 CTCCCTTACCATCAAATCAATTGGCCACCAATGGTACTGAACCTACGAGT CCCFFFFFHHHHHIJJJJJJIGIJJJJJIFGHIJGIIGIJJJJIIJJIIF AS:i:100 XS:i:80 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 10 | HWI-ST960:63:D0CYJACXX:4:1101:6397:2216 4 * 0 0 * * 0 0 CNAGACAGTGAGGGGAAACAGGCACTTATTTGGTTACTTGGGGTCCACGG 1#1==ADD=CDDDDEACEFEICEEDIIIEIIIEIIIEECCEDD@@DEEDA YT:Z:UU 11 | HWI-ST960:63:D0CYJACXX:4:1101:6743:2229 4 * 0 0 * * 0 0 CAATTTGGGATTTCAAGGGTCCCCGGATAATGTGAAGCCGAGCGAGCCTC CCCFFFFFHHHHHJJJJJJFH:FHIJJJJJJJIJIJJJJJJJJIIJJHHH YT:Z:UU 12 | HWI-ST960:63:D0CYJACXX:4:1101:6800:2215 16 7 150067083 44 50M * 0 0 CTGGGAATGAGTGACCTTTGTGTTCCCTGAGAAGAGAGAGTGCGCTCTNG DJJJIIIIIGGGCGEJIIJIGIIGEFJJJJJJJJJJJHHHHGFDDBA4#C AS:i:97 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:48A1 YT:Z:UU 13 | HWI-ST960:63:D0CYJACXX:4:1101:6951:2219 0 9 20953017 44 49M1S * 0 0 GNTTTATTGGAGCAGCTATTGGCTTCTTCATTGCAGGAGGAAAAAAAGGT @#1ADDDFFHFFHIJIJJIJIJJJJ?EH@@FFFGIII@GHCHIIJJI@F8 AS:i:87 XN:i:0 XM:i:2 XO:i:0 XG:i:0 NM:i:2 MD:Z:1T30A16 YT:Z:UU 14 | HWI-ST960:63:D0CYJACXX:4:1101:6815:2237 16 4 1985711 19 50M * 0 0 GCAGGCGTGGGTGTGGCAGGGCTCAGGCCGCTGTTGTACATGGGCGCCCG @DFFDBGFJJIHDCIJIJJHGGGJIJIJJIJJIJJJJHHHHHFFFFFCCC AS:i:100 XS:i:40 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 15 | HWI-ST960:63:D0CYJACXX:4:1101:7158:2216 16 20 32677440 1 50M * 0 0 TTATCTTGTTTTTAATACAACGGTATATCCACTCTGATGGCAAACCTGNC JIEHGIJIJJJJIJIGHJJJJJJJIIIJHHCIIIJJJHGHHHEDFDA1#C AS:i:97 XS:i:97 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:48T1 YT:Z:UU 16 | HWI-ST960:63:D0CYJACXX:4:1101:7289:2213 4 * 0 0 * * 0 0 ANTGTTCCAACATGCCAGAGGCTGTTCACCTTGGAGACCTGCTGCGGATA C#1ADDFFHHHHHIJJJJJJIJJJIJJJJJIJJJIIIJJJJJIJIIJFHG YT:Z:UU 17 | HWI-ST960:63:D0CYJACXX:4:1101:7346:2229 0 2 133012300 1 50M * 0 0 CTCAATCTCGGGTGGCTGAACGCCACTTGTCCCTCTAAGAAGTTGGGGGA CCCFFFFFHHHGCFHIJJIJJJIJIJIJGIJJJIGJIJGIIGBFGIJJJB AS:i:92 XS:i:92 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:9A40 YT:Z:UU 18 | HWI-ST960:63:D0CYJACXX:4:1101:7531:2219 4 * 0 0 * * 0 0 CTGCCTTAAAAGAAGAATGCTGTTTCTATGCCGACCACACAGGATTGGTA CCCFFFFFHGFHHIHIJJJIIJIJJIIIGJIIJJJII=GGIIIFFHII4= YT:Z:UU 19 | HWI-ST960:63:D0CYJACXX:4:1101:7978:2235 16 11 102101947 3 1S49M * 0 0 ATCAGTGAGTAGGTTCATAATGTGCATGACAGAAATAAGCTTTATAGTGG IIJJJJJJJJIJJJJIJIIJIJJJIJJJIIJJJJJJJHHGHHFFFFD@BB AS:i:98 XS:i:82 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:49 YT:Z:UU 20 | HWI-ST960:63:D0CYJACXX:4:1101:8130:2227 0 6 31969589 1 50M * 0 0 GCTGCCTTCCGTCTCTTTGAGTCCAAGATCACCCAAGTCCTGCATTTCAG @CCFFFFFHHHHHJJJJCIJJJJJJJIIJJIJJJJJJJJJIJJJJJJIJJ AS:i:68 XS:i:68 XN:i:0 XM:i:4 XO:i:0 XG:i:0 NM:i:4 MD:Z:5T5C9A22C5 YT:Z:UU 21 | HWI-ST960:63:D0CYJACXX:4:1101:8100:2231 0 17 79477409 3 50M * 0 0 CTTCCACAAGCACGTTCTTACCTTAGCCACGAAGTGACCAAGCCACACGT CCCFFFFFHHHHHJJJJJJJJJJJJJJJIIJJJJFIJJJJJIJJJJJJJI AS:i:100 XS:i:76 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 22 | HWI-ST960:63:D0CYJACXX:4:1101:8299:2245 16 10 102124222 3 50M * 0 0 GAATTCTCAAGACCTGAGTATTTTTTATAATAGGAATGTCCACCATGAAC JJJIIHIIJJIHJJJJJJJJJJJJJJJJJJJJJJJJJHHHHHFFFFFCCC AS:i:100 XS:i:84 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 23 | HWI-ST960:63:D0CYJACXX:4:1101:8626:2217 16 X 154282978 3 48M2S * 0 0 TTTTTTCCAGCCAGCAGCCTCTACACTCCATCATAGGACATCGAGTCCNC JJJIGBJIIIJIIIJJJJJJIIHGDJIJJJJJJJJJJHHHHHFFDDA1#C AS:i:96 XS:i:70 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:48 YT:Z:UU 24 | HWI-ST960:63:D0CYJACXX:4:1101:9099:2213 4 * 0 0 * * 0 0 CNGGGAGTCTGTTAGGTTCTAACCAACCTAGTTTTCATTGTTGACAAGTG @#1ADDFDHHHHHJJJHIJJJJJJJJJJJJJGIJJJJJJJJJIJJJJJEH YT:Z:UU 25 | HWI-ST960:63:D0CYJACXX:4:1101:9310:2223 16 11 61067134 44 50M * 0 0 AAAAGGAAGGTCTCACTTCACAGACAATGAAACCCTCCTAACCCTCTTCC JJJIIIJIIHGGHHFJJJJIJJJJJJJJJJIGJJJHJHHHFHFFFFFCCB AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 26 | HWI-ST960:63:D0CYJACXX:4:1101:9716:2228 4 * 0 0 * * 0 0 CGTGGAGTTCTTGAGCTTTGGGGGTTGGCTTGGGGGGAGAATCTGGAAGA BCBFFFFDHHHHHIJJJJJJJJJJHIJJHIJJJJJJD8BBDDDDEDCDCB YT:Z:UU 27 | HWI-ST960:63:D0CYJACXX:4:1101:9963:2234 0 1 91852856 44 50M * 0 0 CCGACATCGAAGGATCAAAAAGCGACGTCGCTATGAACGCTTGGCCGCCA CCCFFFFFHHHGHJJJJJJJJIJJJJJJJJJJJJJJJJIJJJJHHHGFDD AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 28 | HWI-ST960:63:D0CYJACXX:4:1101:10466:2240 16 X 47424719 2 8S31M11S * 0 0 TCTCTCTGTGAATGAGCTGCTAACCCCCCAGGGTCCCAGCCCCTTTACCC ?BCDCDDDDEEDDDDDDDDDDB:DJJJJIJJJJGJJJHHHHHFFFDDCCC AS:i:54 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:8T22 YT:Z:UU 29 | HWI-ST960:63:D0CYJACXX:4:1101:11154:2245 16 X 70183087 1 50M * 0 0 GCCAATGTTTCTCTTTTGGCCCTATACAAAGGCAAGAAGGAAAGACCAAG JJJIJJIJIIIJJJJJJJJJJJJJJEJJJJJJJJJJJHHHHHDFEFFCCC AS:i:100 XS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 30 | HWI-ST960:63:D0CYJACXX:4:1101:11573:2230 0 4 113709779 1 50M * 0 0 CCTGGGTGAACTGGTTAATCGCAGGAGGCACTTTCAGCCGCTTATAGAGG BCCFFFBDHHHHHJHIJJJJJJJJJJJJIIJJJJJJIJJIJJJJJIIIJJ AS:i:100 XS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 31 | HWI-ST960:63:D0CYJACXX:4:1101:11647:2232 0 8 77933394 9 50M * 0 0 TGAAGATGAGATGGTTGTAGATGTGCGGTGTTATTTCTGAGGTCTCTGTT CCCFFFFFHHHHHJFHIGIJIJJIJIJJCGHIGIJJJJJIJJDHIIJJJJ AS:i:100 XS:i:70 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 32 | HWI-ST960:63:D0CYJACXX:4:1101:11923:2232 16 1 151667535 44 50M * 0 0 TGAGTATAGATTCCGGCTCATGGGTTGCCATAGAGTCTAGGAACAAGGAG JJIGD>FGGIIGIJIHEEGEGGIFJJIIIIJJJIIGJHHHHDDDDA=114 AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 33 | HWI-ST960:63:D0CYJACXX:4:1101:11844:2245 4 * 0 0 * * 0 0 TTATCCGCAGATGCGGTGATGGTTAAGGGGGAGGGGAAAGAAGCCTGGCA ;?EH>DHHEE@EAFFF?388DA)0908?BB@?# AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 57 | HWI-ST960:63:D0CYJACXX:4:1101:16679:2236 16 19 36066506 1 11S39M * 0 0 CCCGATGCCGACGCTCATCAGACCCCAGAAAAGGTGTTGGTTGATATAGA JJJJJJJIJIIJJJJJJJJIHGJJJJJJJJJJJJIJJHHHHHFFFFFCCC AS:i:78 XS:i:76 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:39 YT:Z:UU 58 | HWI-ST960:63:D0CYJACXX:4:1101:17340:2231 4 * 0 0 * * 0 0 GTGAAATGTGCCGGTGTGCTGAAGAGAACTGCTTCATGCAACAGTCACAG @@CFFFFFHGGDHG@ECGFHIGIGEEHEIJJIJIGEGIGIIIIJFICHIE YT:Z:UU 59 | HWI-ST960:63:D0CYJACXX:4:1101:17582:2215 16 10 94428970 3 3S41M6S * 0 0 CAACTCCTCATATGTGTAGTCTCTTTCTGAGCCTGCCCAAGCAGTTTGNC IHGJIIIGJIIJJJJJJJJJIGJJJIJJJJJJJJJJJHHHHHFFDDA1#C AS:i:82 XS:i:74 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:41 YT:Z:UU 60 | HWI-ST960:63:D0CYJACXX:4:1101:17686:2237 0 X 91368541 1 50M * 0 0 TCCATATCTCCATGCATGGCGGATACAGTGAAATCTCGAGCATGCATCTT CCCFFFFFHHHHHJJJJJJIJJIIJJJJGIJJJJJIJJIIIIJJJJJIII AS:i:92 XS:i:92 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:23G26 YT:Z:UU 61 | HWI-ST960:63:D0CYJACXX:4:1101:17533:2241 0 15 48633063 44 50M * 0 0 CTTTTTGACATTTTTATTTATGACTCAATCGTATTTCAATCTGGGTATTA CCCFFFFFHHHHHIGAGIHGCFHGFEGEEDG??FHBCGDD??DHE::BB< AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 62 | HWI-ST960:63:D0CYJACXX:4:1101:18005:2232 16 18 3457870 44 50M * 0 0 CAGCTTCTAGTGGATGTTGCACTCAAACGGGCTGCAGAGATGGAGCTTCA IIJIJJIJJJJIJJJJJJIHHJIJJJJJJJJJJJJJJHHHHHFFFFFCCC AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 63 | HWI-ST960:63:D0CYJACXX:4:1101:18091:2249 4 * 0 0 * * 0 0 GCGGGTCTTGTTGGGCGTTTAGCGCATCGGGTTGCCTAGAAGGACAGATG BCCFFADFHHHHHJJJJHIJJJIIJJJIJJJGIJJJJJIIGIJEHFHFEF YT:Z:UU 64 | HWI-ST960:63:D0CYJACXX:4:1101:18834:2225 16 11 502186 19 50M * 0 0 GTGGGAGGCAGAGGGAAGAGGACGTCTTGGCCGAATCCCCTCACAGTTTC AIFF=EHIIIGH>FGGGCHAHGIIGHHID7?FGE YT:Z:UU 68 | HWI-ST960:63:D0CYJACXX:4:1101:19682:2225 0 20 47679781 44 50M * 0 0 CACTGTTGCTTTTGACATTACTGGAGAAGTCCCAGGATAATGTTATCAAA CCCFFFFFHHHHHJIJJJJJJJJJJJJJJJIJJJJJJJJJJIIIIIIIJJ AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 69 | HWI-ST960:63:D0CYJACXX:4:1101:19531:2232 16 9 21968197 44 48M2S * 0 0 CCCGAGGTTTCTCAGAGCCTCTCTGGTTCTTTCAATCGGGGATGTCTGAG IIJIHJJIJJIJJJJJJJJIIJIJJJJIGJJJIJJJJHHHHHFFFFFCCC AS:i:96 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:48 YT:Z:UU 70 | HWI-ST960:63:D0CYJACXX:4:1101:19812:2225 4 * 0 0 * * 0 0 CCGGCGACCAGGCTTCTAGGCTGTGTGACAACTGCAAGAAGGAAATTCCT CCCFFFFFHHHHHJJJJJIJIJJHIDHGGIJJGIJIJIJJJJJJJJJJJJ YT:Z:UU 71 | HWI-ST960:63:D0CYJACXX:4:1101:20096:2241 0 2 85133171 3 50M * 0 0 CGCCAGCTTCGATAAGGCCAAGCTGAAGAAAACGGAGACGCAGGAGAAGA CCCFFFFFHHHHHJJJJJJJJJJJJJJJJJJIIJJJJJFIJIJIEEHGDH AS:i:100 XS:i:84 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 72 | HWI-ST960:63:D0CYJACXX:4:1101:20640:2224 0 1 568281 1 50M * 0 0 AAACTAACTAATACTAACATCTCAGACGCTCAGGAAATAGAAACCGTCTG CCCFFFFFHHHHHJJJJIJJJJJJJJJJJJJJJJJJJJJJJJJJJJHIIJ AS:i:100 XS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 73 | HWI-ST960:63:D0CYJACXX:4:1101:20617:2244 0 6 31701644 1 49M1S * 0 0 CCTCGATCTTGTTGGTGTCTGTGTGCACTTCGGTGCCATAGAGCAAGAAC CCCFFFFFHHHHHJIHIJJJJHIIIJJJJIJJIDGHIIIJJJJGIJIJJI AS:i:66 XS:i:60 XN:i:0 XM:i:4 XO:i:0 XG:i:0 NM:i:4 MD:Z:4A26A8C4G3 YT:Z:UU 74 | HWI-ST960:63:D0CYJACXX:4:1101:20903:2221 0 21 46276169 19 50M * 0 0 CCGGCTTCCGGCTCCTCTTCCTCCTGCAGCAGCAGCAGCAGCAGATGGCA CCCFFFFFHHHHHJJJJJJJJGIJIIGIIGGGIJJIFIJGGGGHGGEGGI AS:i:100 XS:i:46 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 75 | HWI-ST960:63:D0CYJACXX:4:1101:20929:2225 16 11 32124884 1 50M * 0 0 GGGAGCAGTTTAACGAATTCCGGGATCTGAACAAGGACGGGAAGTTAGAC IJIGIFJIJJJIJIIJJJIIJJJJJJJJJJJJJJJJJHHGHHFFFFFCCC AS:i:100 XS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 76 | HWI-ST960:63:D0CYJACXX:4:1101:21030:2249 16 11 65622418 9 50M * 0 0 CACAGAACTAAACAGACAAGCACAGAGTCACTATTGCGGTTAGAAGTTGG IIIJIJIIIJIIIJIIJJJJJJJJJJJIHCHHFFEJJHHHHHFFFFFCCC AS:i:100 XS:i:67 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 77 | HWI-ST960:63:D0CYJACXX:4:1101:21264:2228 16 MT 4691 3 50M * 0 0 CCTCTTCAACAATATACTCTCCGGACAATGAACCATAACCAATACTACCA IH@GEEEHGGHGEFC:FAIGJJJGIJJJIJIIIIIHHFGHHHDDFDBCBB AS:i:100 XS:i:92 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 78 | HWI-ST960:63:D0CYJACXX:4:4242:66666:6666 4 * 0 0 * * 0 0 NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB YT:Z:UU 79 | -------------------------------------------------------------------------------- /xenomapper/tests/data/test_mouse_in.sam: -------------------------------------------------------------------------------- 1 | @testheader 2 | HWI-ST960:63:D0CYJACXX:4:1101:1724:2248 4 * 0 0 * * 0 0 CTTCATTCATTGCCCCCACAATCCTAGGCCTACCCGCCGCAGTACTGATC CCCFFFFFHHHGHJIJIJJJJJJJIJJJJJJJJJIIJJIIIICGIJJJJ@ YT:Z:UU 3 | HWI-ST960:63:D0CYJACXX:4:1101:2294:2233 4 * 0 0 * * 0 0 CTTGGCTAATACTGAGCAGGTAGTGGGGCAAATTCCTGCCCTCTCTCTCT CCCFFFFFHHHHHJJJJJJJHIJJJJJJJJJJJJJJJJJJJJJJJJJIJJ YT:Z:UU 4 | HWI-ST960:63:D0CYJACXX:4:1101:2794:2226 4 * 0 0 * * 0 0 GCCACACCGAACTTCCTCTGCGCCAGGTACGCTCTATACAGGAAGACGTC :11=ADDFHHGHHJJJJJJJJIHHGEHBDGHJJJJFHGI9CHIJ>EGBDH YT:Z:UU 5 | HWI-ST960:63:D0CYJACXX:4:1101:3653:2249 4 * 0 0 * * 0 0 CTTGTCTCAATGTTGAAAAATCGCCTTTCCTCATCAACTGTCAGAGTGAT CCCFFFFFGHHHHJJJJJJJIIJJJJJJJJJJJJJJJIJJGJJIIIBGHG YT:Z:UU 6 | HWI-ST960:63:D0CYJACXX:4:1101:3944:2248 16 16 15427265 1 39M11S * 0 0 TAAAAGCTTACTTGACATATTTTAGAGACAAATAACTTAGATCAAGAAGA HIIIIIIHFDIIIHFIIIIIIIGIIIIICIIIGFEIGDHHHHFFFFD@@@ AS:i:54 XS:i:50 XN:i:0 XM:i:3 XO:i:0 XG:i:0 NM:i:3 MD:Z:4G6C4G22 YT:Z:UU 7 | HWI-ST960:63:D0CYJACXX:4:1101:5254:2228 4 * 0 0 * * 0 0 CTGCTGCAGTGCTCTGAGCCCTAGGATTCATCTTTCTTTTCACCGTAGGT CCCFFFFFHHHHHJJJJJJJJJJJJGHJJJJJJJJJJJJJJJJJJJJJJF YT:Z:UU 8 | HWI-ST960:63:D0CYJACXX:4:1101:5933:2226 0 7 133701244 40 50M * 0 0 ATGATATTGAACTTGATCTTGACAATGACGCCCTCTCCCAGGTTGTTTTC CCCFFFFFHHHHHJJJJJJJJJJJJIJJIJJJJJJJJJJIJJHHIJJJJJ AS:i:84 XN:i:0 XM:i:2 XO:i:0 XG:i:0 NM:i:2 MD:Z:33A1C14 YT:Z:UU 9 | HWI-ST960:63:D0CYJACXX:4:1101:6148:2247 4 * 0 0 * * 0 0 CTCCCTTACCATCAAATCAATTGGCCACCAATGGTACTGAACCTACGAGT CCCFFFFFHHHHHIJJJJJJIGIJJJJJIFGHIJGIIGIJJJJIIJJIIF YT:Z:UU 10 | HWI-ST960:63:D0CYJACXX:4:1101:6397:2216 0 3 103624175 40 10S40M * 0 0 CNAGACAGTGAGGGGAAACAGGCACTTATTTGGTTACTTGGGGTCCACGG 1#1==ADD=CDDDDEACEFEICEEDIIIEIIIEIIIEECCEDD@@DEEDA AS:i:80 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:40 YT:Z:UU 11 | HWI-ST960:63:D0CYJACXX:4:1101:6743:2229 0 5 145869265 4 15S35M * 0 0 CAATTTGGGATTTCAAGGGTCCCCGGATAATGTGAAGCCGAGCGAGCCTC CCCFFFFFHHHHHJJJJJJFH:FHIJJJJJJJIJIJJJJJJJJIIJJHHH AS:i:63 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:6T28 YT:Z:UU 12 | HWI-ST960:63:D0CYJACXX:4:1101:6800:2215 4 * 0 0 * * 0 0 CNAGAGCGCACTCTCTCTTCTCAGGGAACACAAAGGTCACTCATTCCCAG C#4ABDDFGHHHHJJJJJJJJJJJFEGIIGIJIIJEGCGGGIIIIIJJJD YT:Z:UU 13 | HWI-ST960:63:D0CYJACXX:4:1101:6951:2219 4 * 0 0 * * 0 0 GNTTTATTGGAGCAGCTATTGGCTTCTTCATTGCAGGAGGAAAAAAAGGT @#1ADDDFFHFFHIJIJJIJIJJJJ?EH@@FFFGIII@GHCHIIJJI@F8 YT:Z:UU 14 | HWI-ST960:63:D0CYJACXX:4:1101:6815:2237 4 * 0 0 * * 0 0 CGGGCGCCCATGTACAACAGCGGCCTGAGCCCTGCCACACCCACGCCTGC CCCFFFFFHHHHHJJJJIJJIJJIJIJGGGHJJIJICDHIJJFGBDFFD@ YT:Z:UU 15 | HWI-ST960:63:D0CYJACXX:4:1101:7158:2216 4 * 0 0 * * 0 0 GNCAGGTTTGCCATCAGAGTGGATATACCGTTGTATTAAAAACAAGATAA C#1ADFDEHHHGHJJJIIICHHJIIIJJJJJJJHGIJIJJJJIJIGHEIJ YT:Z:UU 16 | HWI-ST960:63:D0CYJACXX:4:1101:7289:2213 0 11 108872968 1 50M * 0 0 ANTGTTCCAACATGCCAGAGGCTGTTCACCTTGGAGACCTGCTGCGGATA C#1ADDFFHHHHHIJJJJJJIJJJIJJJJJIJJJIIIJJJJJIJIIJFHG AS:i:97 XS:i:97 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:1T48 YT:Z:UU 17 | HWI-ST960:63:D0CYJACXX:4:1101:7346:2229 16 17 39984736 3 50M * 0 0 TCCCCCAACTTCTTAGAGGGACAAGTGGCGTTCAGCCACCCGAGATTGAG BJJJIGFBGIIGJIJGIJJJIGJIJIJIJJJIJJIHFCGHHHFFFFFCCC AS:i:100 XS:i:76 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 18 | HWI-ST960:63:D0CYJACXX:4:1101:7531:2219 16 8 125950552 17 50M * 0 0 TACCAATCCTGTGTGGTCGGCATAGAAACAGCATTCTTCTTTTAAGGCAG =4IIHFFIIIGG=IIJJJIIJGIIIJJIJIIJJJIHIHHFGHFFFFFCCC AS:i:100 XS:i:52 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 19 | HWI-ST960:63:D0CYJACXX:4:1101:7978:2235 4 * 0 0 * * 0 0 CCACTATAAAGCTTATTTCTGTCATGCACATTATGAACCTACTCACTGAT BB@DFFFFHHGHHJJJJJJJIIJJJIJJJIJIIJIJJJJIJJJJJJJJII YT:Z:UU 20 | HWI-ST960:63:D0CYJACXX:4:1101:8130:2227 16 17 34866126 3 50M * 0 0 CTGAAATGCAGGACTTGGGTGATCTTGGACTCAAAGAGACGGAAGGCAGC JJIJJJJJJIJJJJJJJJJIJJIIJJJJJJJICJJJJHHHHHFFFFFCC@ AS:i:100 XS:i:92 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 21 | HWI-ST960:63:D0CYJACXX:4:1101:8100:2231 4 * 0 0 * * 0 0 CTTCCACAAGCACGTTCTTACCTTAGCCACGAAGTGACCAAGCCACACGT CCCFFFFFHHHHHJJJJJJJJJJJJJJJIIJJJJFIJJJJJIJJJJJJJI YT:Z:UU 22 | HWI-ST960:63:D0CYJACXX:4:1101:8299:2245 4 * 0 0 * * 0 0 GTTCATGGTGGACATTCCTATTATAAAAAATACTCAGGTCTTGAGAATTC CCCFFFFFHHHHHJJJJJJJJJJJJJJJJJJJJJJJJJHIJJIIHIIJJJ YT:Z:UU 23 | HWI-ST960:63:D0CYJACXX:4:1101:8626:2217 4 * 0 0 * * 0 0 GNGGACTCGATGTCCTATGATGGAGTGTAGAGGCTGCTGGCTGGAAAAAA C#1ADDFFHHHHHJJJJJJJJJJIJDGHIIJJJJJJIIIJIIIJBGIJJJ YT:Z:UU 24 | HWI-ST960:63:D0CYJACXX:4:1101:9099:2213 16 4 122536935 44 50M * 0 0 CACTTGTCAACAATGAAAACTAGGTTGGTTAGAACCTAACAGACTCCCNG HEJJJJJIJJJJJJJJJIGJJJJJJJJJJJJJIHJJJHHHHHDFDDA1#@ AS:i:89 XN:i:0 XM:i:2 XO:i:0 XG:i:0 NM:i:2 MD:Z:39T8T1 YT:Z:UU 25 | HWI-ST960:63:D0CYJACXX:4:1101:9310:2223 16 1 137016884 0 13S21M16S * 0 0 AAAAGGAAGGTCTCACTTCACAGACAATGAAACCCTCCTAACCCTCTTCC JJJIIIJIIHGGHHFJJJJIJJJJJJJJJJIGJJJHJHHHFHFFFFFCCB AS:i:42 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:21 YT:Z:UU 26 | HWI-ST960:63:D0CYJACXX:4:1101:9716:2228 16 14 70094262 19 50M * 0 0 TCTTCCAGATTCTCCCCCCAAGCCAACCCCCAAAGCTCAAGAACTCCACG BCDCDEDDDDBB8DJJJJJJIHJJIHJJJJJJJJJJIHHHHHDFFFFBCB AS:i:100 XS:i:42 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 27 | HWI-ST960:63:D0CYJACXX:4:1101:9963:2234 16 9 123371094 19 50M * 0 0 TGGCGGCCAAGCGTTCATAGCGACGTCGCTTTTTGATCCTTCGATGTCGG DDFGHHHJJJJIJJJJJJJJJJJJJJJJIJJJJJJJJHGHHHFFFFFCCC AS:i:100 XS:i:46 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 28 | HWI-ST960:63:D0CYJACXX:4:1101:10466:2240 16 X 20429116 28 39M11S * 0 0 TCTCTCTGTGAATGAGCTGCTAACCCCCCAGGGTCCCAGCCCCTTTACCC ?BCDCDDDDEEDDDDDDDDDDB:DJJJJIJJJJGJJJHHHHHFFFDDCCC AS:i:78 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:39 YT:Z:UU 29 | HWI-ST960:63:D0CYJACXX:4:1101:11154:2245 0 4 11347505 3 1S49M * 0 0 CTTGGTCTTTCCTTCTTGCCTTTGTATAGGGCCAAAAGAGAAACATTGGC CCCFFEFDHHHHHJJJJJJJJJJJEJJJJJJJJJJJJJJIIIJIJJIJJJ AS:i:82 XS:i:68 XN:i:0 XM:i:2 XO:i:0 XG:i:0 NM:i:2 MD:Z:9T30C8 YT:Z:UU 30 | HWI-ST960:63:D0CYJACXX:4:1101:11573:2230 4 * 0 0 * * 0 0 CCTGGGTGAACTGGTTAATCGCAGGAGGCACTTTCAGCCGCTTATAGAGG BCCFFFBDHHHHHJHIJJJJJJJJJJJJIIJJJJJJIJJIJJJJJIIIJJ YT:Z:UU 31 | HWI-ST960:63:D0CYJACXX:4:1101:11647:2232 4 * 0 0 * * 0 0 TGAAGATGAGATGGTTGTAGATGTGCGGTGTTATTTCTGAGGTCTCTGTT CCCFFFFFHHHHHJFHIGIJIJJIJIJJCGHIGIJJJJJIJJDHIIJJJJ YT:Z:UU 32 | HWI-ST960:63:D0CYJACXX:4:1101:11923:2232 4 * 0 0 * * 0 0 CTCCTTGTTCCTAGACTCTATGGCAACCCATGAGCCGGAATCTATACTCA 411=ADDDDHHHHJGIIJJJIIIIJJFIGGEGEEHIJIGIIGGF>DGIJJ YT:Z:UU 33 | HWI-ST960:63:D0CYJACXX:4:1101:11844:2245 16 7 19591549 44 50M * 0 0 TGCCAGGCTTCTTTCCCCTCCCCCTTAACCATCACCGCATCTGCGGATAA CBB?DBDHHEFHIIIIGD?IIIIHG@FFGEEFCEH>DHHEE@EAFFF?388DA)0908?BB@?# YT:Z:UU 57 | HWI-ST960:63:D0CYJACXX:4:1101:16679:2236 0 13 44964941 3 50M * 0 0 TCTATATCAACCAACACCTTTTCTGGGGTCTGATGAGCGTCGGCATCGGG CCCFFFFFHHHHHJJIJJJJJJJJJJJJGHIJJJJJJJJIIJIJJJJJJJ AS:i:92 XS:i:74 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:42A7 YT:Z:UU 58 | HWI-ST960:63:D0CYJACXX:4:1101:17340:2231 16 17 57344778 3 32M18S * 0 0 CTGTGACTGTTGCATGAAGCAGTTCTCTTCAGCACACCGGCACATTTCAC EIHCIFJIIIIGIGEGIJIJJIEHEEGIGIHFGCE@GHDGGHFFFFFC@@ AS:i:56 XS:i:48 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:28G3 YT:Z:UU 59 | HWI-ST960:63:D0CYJACXX:4:1101:17582:2215 16 8 53281880 1 50M * 0 0 CAACTCCTCATATGTGTAGTCTCTTTCTGAGCCTGCCCAAGCAGTTTGNC IHGJIIIGJIIJJJJJJJJJIGJJJIJJJJJJJJJJJHHHHHFFDDA1#C AS:i:97 XS:i:91 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:48G1 YT:Z:UU 60 | HWI-ST960:63:D0CYJACXX:4:1101:17686:2237 0 19 15034337 1 50M * 0 0 TCCATATCTCCATGCATGGCGGATACAGTGAAATCTCGAGCATGCATCTT CCCFFFFFHHHHHJJJJJJIJJIIJJJJGIJJJJJIJJIIIIJJJJJIII AS:i:76 XS:i:76 XN:i:0 XM:i:3 XO:i:0 XG:i:0 NM:i:3 MD:Z:20A2A14G11 YT:Z:UU 61 | HWI-ST960:63:D0CYJACXX:4:1101:17533:2241 16 9 23289538 0 29S21M * 0 0 TAATACCCAGATTGAAATACGATTGAGTCATAAATAAAAATGTCAAAAAG EHIIIGH>FGGGCHAHGIIGHHID7?FGE AS:i:97 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:1T48 YT:Z:UU 68 | HWI-ST960:63:D0CYJACXX:4:1101:19682:2225 4 * 0 0 * * 0 0 CACTGTTGCTTTTGACATTACTGGAGAAGTCCCAGGATAATGTTATCAAA CCCFFFFFHHHHHJIJJJJJJJJJJJJJJJIJJJJJJJJJJIIIIIIIJJ YT:Z:UU 69 | HWI-ST960:63:D0CYJACXX:4:1101:19531:2232 4 * 0 0 * * 0 0 CTCAGACATCCCCGATTGAAAGAACCAGAGAGGCTCTGAGAAACCTCGGG CCCFFFFFHHHHHJJJJIJJJGIJJJJIJIIJJJJJJJJIJJIJJHIJII YT:Z:UU 70 | HWI-ST960:63:D0CYJACXX:4:1101:19812:2225 16 5 121834049 2 16S29M5S * 0 0 AGGAATTTCCTTCTTGCAGTTGTCACACAGCCTAGAAGCCTGGTCGCCGG JJJJJJJJJJJJIJIJIGJJIGGHDIHJJIJIJJJJJHHHHHFFFFFCCC AS:i:58 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:29 YT:Z:UU 71 | HWI-ST960:63:D0CYJACXX:4:1101:20096:2241 16 3 86476011 1 50M * 0 0 TCTTCTCCTGCGTCTCCGTTTTCTTCAGCTTGGCCTTATCGAAGCTGGCG HDGHEEIJIJIFJJJJJIIJJJJJJJJJJJJJJJJJJHHHHHFFFFFCCC AS:i:92 XS:i:92 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:16G33 YT:Z:UU 72 | HWI-ST960:63:D0CYJACXX:4:1101:20640:2224 4 * 0 0 * * 0 0 AAACTAACTAATACTAACATCTCAGACGCTCAGGAAATAGAAACCGTCTG CCCFFFFFHHHHHJJJJIJJJJJJJJJJJJJJJJJJJJJJJJJJJJHIIJ YT:Z:UU 73 | HWI-ST960:63:D0CYJACXX:4:1101:20617:2244 16 17 35189771 44 50M * 0 0 GTTCTTGCTCTATGGCACCGAAGTGCACACAGACACCAACAAGATCGAGG IJJIJIGJJJJIIIHGDIJJIJJJJIIIHJJJJIHIJHHHHHFFFFFCCC AS:i:100 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:50 YT:Z:UU 74 | HWI-ST960:63:D0CYJACXX:4:1101:20903:2221 16 10 108763867 1 6S24M20S * 0 0 TGCCATCTGCTGCTGCTGCTGCTGCAGGAGGAAGAGGAGCCGGAAGCCGG IGGEGGHGGGGJIFIJJIGGGIIGIIJIGJJJJJJJJHHHHHFFFFFCCC AS:i:48 XS:i:46 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:24 YT:Z:UU 75 | HWI-ST960:63:D0CYJACXX:4:1101:20929:2225 0 7 52339038 0 9S24M17S * 0 0 GTCTAACTTCCCGTCCTTGTTCAGATCCCGGAATTCGTTAAACTGCTCCC CCCFFFFFHHGHHJJJJJJJJJJJJJJJJJIIJJJIIJIJJJIJFIGIJI AS:i:48 XN:i:0 XM:i:0 XO:i:0 XG:i:0 NM:i:0 MD:Z:24 YT:Z:UU 76 | HWI-ST960:63:D0CYJACXX:4:1101:21030:2249 0 19 5493831 11 50M * 0 0 CCAACTTCTAACCGCAATAGTGACTCTGTGCTTGTCTGTTTAGTTCTGTG CCCFFFFFHHHHHJJEFFHHCHIJJJJJJJJJJJIIJIIIJIIIJIJIII AS:i:92 XS:i:54 XN:i:0 XM:i:1 XO:i:0 XG:i:0 NM:i:1 MD:Z:13A36 YT:Z:UU 77 | HWI-ST960:63:D0CYJACXX:4:1101:21264:2228 4 * 0 0 * * 0 0 TGGTAGTATTGGTTATGGTTCATTGTCCGGAGAGTATATTGTTGAAGAGG BBCBDFDDHHHGFHHIIIIIJIJJJIGJJJGIAF:CFEGHGGHEEEG@HI YT:Z:UU 78 | HWI-ST960:63:D0CYJACXX:4:4242:66666:6666 4 * 0 0 * * 0 0 NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB YT:Z:UU 79 | 80 | -------------------------------------------------------------------------------- /xenomapper/tests/test_all.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | # encoding: utf-8 3 | """ 4 | test_xenomapper.py 5 | 6 | Created by Matthew Wakefield on 2012-08-16. 7 | Copyright (c) 2011-2019 Matthew Wakefield, The Walter and Eliza Hall Institute and The University of Melbourne. All rights reserved. 8 | """ 9 | 10 | import unittest 11 | from xenomapper.tests.test_xenomapper import * 12 | from xenomapper.tests.test_mappability import * 13 | 14 | __author__ = "Matthew Wakefield" 15 | __copyright__ = "Copyright 2011-2019 Matthew Wakefield, The Walter and Eliza Hall Institute and The University of Melbourne" 16 | __credits__ = ["Matthew Wakefield",] 17 | __license__ = "GPLv3" 18 | __version__ = "1.0.2" 19 | __maintainer__ = "Matthew Wakefield" 20 | __email__ = "wakefield@wehi.edu.au" 21 | __status__ = "Release/Stable" 22 | 23 | if __name__ == "__main__": 24 | unittest.main() -------------------------------------------------------------------------------- /xenomapper/tests/test_mappability.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | # encoding: utf-8 3 | """ 4 | test_mappability.py 5 | 6 | Created by Matthew Wakefield on 2012-08-16. 7 | Copyright (c) 2012 Matthew Wakefield and The Walter and Eliza Hall Institute. All rights reserved. 8 | """ 9 | 10 | import unittest 11 | import sys, io 12 | from xenomapper.mappability import * 13 | import hashlib 14 | from pkg_resources import resource_stream 15 | from string import ascii_uppercase, ascii_lowercase 16 | 17 | 18 | __author__ = "Matthew Wakefield" 19 | __copyright__ = "Copyright 2011-2019 Matthew Wakefield, The Walter and Eliza Hall Institute and The University of Melbourne" 20 | __credits__ = ["Matthew Wakefield",] 21 | __license__ = "GPLv3" 22 | __version__ = "1.0.2" 23 | __maintainer__ = "Matthew Wakefield" 24 | __email__ = "wakefield@wehi.edu.au" 25 | __status__ = "Development/Beta" 26 | 27 | class test_mappability(unittest.TestCase): 28 | def setUp(self): 29 | pass 30 | 31 | def test_parse_fasta(self): 32 | testdata = io.StringIO('>firstsequence\nGACAT\n>secondsequence\nGNATCAT') 33 | self.assertEqual(list(parse_fasta(testdata)),[('firstsequence', 'GACAT'), ('secondsequence', 'GNATCAT')]) 34 | pass 35 | 36 | def test_simulate_reads(self): 37 | outputfasta = io.StringIO() 38 | inputfastafile = io.TextIOWrapper(resource_stream(__name__, 'data/test_from_EcoliK12DH10B.fasta')) 39 | simulate_reads(inputfastafile,readlength=150,outfile=outputfasta) 40 | self.assertEqual(hashlib.sha224(outputfasta.getvalue().encode('latin-1')).hexdigest(),'227d299d0b0d2a348a41d6a5397668ca6a9ac5218ab4f85d68fd5c53') 41 | 42 | canned_result = '>testing_1\nabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWX\n' + \ 43 | '>testing_2\nbcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXY\n' + \ 44 | '>testing_3\ncdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ\n' 45 | testdata = io.StringIO('>testing\n'+ascii_lowercase+ascii_uppercase) 46 | testout = io.StringIO('') 47 | simulate_reads(testdata,readlength=50,outfile=testout) 48 | self.assertEqual(canned_result, testout.getvalue()) 49 | 50 | pass 51 | 52 | def test_make_blocklist(self): 53 | canned_result = ['abcdefghij', 'klmnopqrst', 'uvwxyzABCD', 54 | 'EFGHIJKLMN', 'OPQRSTUVWX', 'YZ'] 55 | result = make_blocklist(ascii_lowercase+ascii_uppercase, 10) 56 | self.assertEqual(canned_result, result) 57 | pass 58 | 59 | def test_slice_string_in_blocks(self): 60 | canned_result = 'abcdefghij\nklmnopqrst\nuvwxyzABCD\nEFGHIJKLMN\nOPQRSTUVWX\nYZ\n' 61 | result = slice_string_in_blocks(ascii_lowercase+ascii_uppercase, 10) 62 | self.assertEqual(canned_result, result) 63 | pass 64 | 65 | def test_format_fasta(self): 66 | canned_result = '>fooGene\nabcdefghij\nklmnopqrst\nuvwxyzABCD\nEFGHIJKLMN\nOPQRSTUVWX\nYZ\n' 67 | result = format_fasta('fooGene',ascii_lowercase+ascii_uppercase, 10) 68 | self.assertEqual(canned_result, result) 69 | pass 70 | 71 | def test_smoothed_list(self): 72 | testdata = [1,2,3]*10 + [100,] + [1,2,3]*10 73 | result = smoothed_list(testdata) 74 | self.assertEqual(sum(result),219.8090909090909) 75 | self.assertEqual(max(result),6.714285714285714) 76 | self.assertEqual(min(result),1.9) 77 | self.assertEqual(len(result),len(testdata)) 78 | pass 79 | 80 | def test_normalised_list(self): 81 | testdata = [1,2,3]*10 + [10,] + [1,2,3]*10 82 | result = normalised_list(testdata) 83 | self.assertAlmostEqual(sum(result),1.0) 84 | self.assertEqual(max(result),0.07692307692307693) 85 | self.assertEqual(min(result),0.007692307692307693) 86 | self.assertEqual(result[0]/result[2],1/3) 87 | self.assertEqual(len(result),len(testdata)) 88 | pass 89 | 90 | def test_remove_small_values(self): 91 | testdata = list(range(100)) 92 | result = remove_small_values(testdata) 93 | self.assertEqual(result[:10],[0,]*10) 94 | self.assertEqual(result[10:],testdata[10:]) 95 | self.assertEqual(len(result),len(testdata)) 96 | pass 97 | 98 | def test_mate_distribution_from_sam(self): 99 | hssam = io.TextIOWrapper(resource_stream(__name__, 'data/paired_end_testdata_human.sam')) 100 | result = mate_distribution_from_sam(samfile=hssam,sample_size=3) 101 | self.assertEqual(result, [0.0,]*164 + [0.047619047619047596,]*21 + [0.0,]*266) 102 | hssam.close() 103 | pass 104 | 105 | def test_single_end_mappability_from_sam(self): 106 | EcoliK12DH10B_150sam = io.TextIOWrapper(resource_stream(__name__, 'data/test_from_EcoliK12DH10B_150reads.sam')) 107 | resultfile = io.StringIO() 108 | single_end_mappability_from_sam(EcoliK12DH10B_150sam, outfile=resultfile, chromosome_sizes={'Chromosome':2752,'A_Repeat':991}) 109 | self.assertEqual(hashlib.sha224(resultfile.getvalue().encode('latin-1')).hexdigest(),'e8e8557a16c05aaa436c2c0fe616450d82a955e0f6de8eb3d190cdf4') 110 | EcoliK12DH10B_150sam.close() 111 | resultfile.close() 112 | pass 113 | 114 | def test_mappability_obj(self): 115 | mappable = Mappability(chromosome_sizes={'Chromosome':20,}) 116 | self.assertEqual(mappable['Chromosome'],[0,]*20) 117 | pair_mappability = mappable.single_end_to_paired(mate_density = [0,0.5,0.5,]) 118 | self.assertEqual(pair_mappability['Chromosome'],[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0]) 119 | mappable['Y'] = [0.0,]*15 120 | 121 | resultfile = io.StringIO() 122 | resultfile2 = io.StringIO() 123 | 124 | mappable.to_wiggle(wigglefile=resultfile, chromosomes = ['Chromosome']) 125 | self.assertEqual(resultfile.getvalue(),'fixedStep\tchrom=Chromosome\tstart=1\tstep=1\n' + '0\n'*20) 126 | resultfile.close() 127 | 128 | mappable = Mappability(chromosome_sizes={'X':30,}) 129 | mappable['X'] = [0,1,1]*10 130 | mappable.to_wiggle(wigglefile=resultfile2) 131 | self.assertEqual(resultfile2.getvalue(),'fixedStep\tchrom=X\tstart=1\tstep=1\n' + '0\n1\n1\n'*10) 132 | resultfile2.close() 133 | 134 | pair_mappability = mappable.single_end_to_paired(mate_density = [0,0.4,0.5,0.1]) 135 | self.assertEqual(pair_mappability['X'],[0.9, 1.0, 1.0,]*10 ) 136 | pass 137 | 138 | def test_paired_end_mappability(self): 139 | resultfile = io.StringIO() 140 | mate_density = [0,0,0,0,0,0,0,0,0,0.01,0.45,0.41,0.13,0,0,0,0] 141 | wigglefile = io.StringIO('fixedStep\tchrom=Chromosome\tstart=1\tstep=1\n' + '1\n0\n'*50 + 'fixedStep\tchrom=Repeat\tstart=1\tstep=1\n' + '0\n'*10) 142 | paired_end_mappability(wigglefile,mate_density, outfile=resultfile,chromosome_sizes= {'Chromosome':100,'X':10}) 143 | self.assertEqual(resultfile.getvalue(),'fixedStep\tchrom=Chromosome\tstart=1\tstep=1\n'+ '1.0\n0.42\n'*44 + '1.0\n0.01\n' + '1.0\n0.0\n'*5 + 'fixedStep\tchrom=X\tstart=1\tstep=1\n' + '0.0\n'*10) 144 | wigglefile.close() 145 | resultfile.close() 146 | 147 | if __name__ == '__main__': 148 | unittest.main() -------------------------------------------------------------------------------- /xenomapper/tests/test_xenomapper.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | # encoding: utf-8 3 | """ 4 | test_xenomapper.py 5 | 6 | Created by Matthew Wakefield on 2012-08-16. 7 | Copyright (c) 2011-2016 Matthew Wakefield and The Walter and Eliza Hall Institute. All rights reserved. 8 | """ 9 | 10 | import unittest 11 | import sys, io 12 | from xenomapper.xenomapper import * 13 | import hashlib 14 | from pkg_resources import resource_stream 15 | 16 | __author__ = "Matthew Wakefield" 17 | __copyright__ = "Copyright 2011-2019 Matthew Wakefield, The Walter and Eliza Hall Institute and The University of Melbourne" 18 | __credits__ = ["Matthew Wakefield",] 19 | __license__ = "GPLv3" 20 | __version__ = "1.0.2" 21 | __maintainer__ = "Matthew Wakefield" 22 | __email__ = "wakefield@wehi.edu.au" 23 | __status__ = "Production/Stable" 24 | 25 | class test_main(unittest.TestCase): 26 | def setUp(self): 27 | pass 28 | 29 | def test_process_headers(self): 30 | test_primary_specific_outfile = io.StringIO() 31 | test_secondary_specific_outfile = io.StringIO() 32 | test_primary_multi_outfile = io.StringIO() 33 | test_secondary_multi_outfile = io.StringIO() 34 | test_unassigned_outfile = io.StringIO() 35 | test_unresolved_outfile = io.StringIO() 36 | sam1 = io.TextIOWrapper(resource_stream(__name__, 'data/paired_end_testdata_human.sam')) 37 | sam2 = io.TextIOWrapper(resource_stream(__name__, 'data/paired_end_testdata_mouse.sam')) 38 | process_headers(sam1,sam2, 39 | primary_specific=test_primary_specific_outfile, 40 | secondary_specific=test_secondary_specific_outfile, 41 | primary_multi=test_primary_multi_outfile, 42 | secondary_multi=test_secondary_multi_outfile, 43 | unresolved=test_unresolved_outfile, 44 | unassigned=test_unassigned_outfile, 45 | ) 46 | self.assertEqual(len(test_primary_specific_outfile.getvalue()),695) 47 | self.assertEqual(len(test_secondary_specific_outfile.getvalue()),629) 48 | self.assertEqual(len(test_primary_multi_outfile.getvalue()),708) 49 | self.assertEqual(len(test_secondary_multi_outfile.getvalue()),642) 50 | self.assertEqual(len(test_unassigned_outfile.getvalue()),705) 51 | self.assertEqual(len(test_unresolved_outfile.getvalue()),705) 52 | sam1.close() 53 | sam2.close() 54 | pass 55 | 56 | def test_consistent_output_SE(self): 57 | test_primary_specific_outfile = io.StringIO() 58 | test_secondary_specific_outfile = io.StringIO() 59 | test_primary_multi_outfile = io.StringIO() 60 | test_secondary_multi_outfile = io.StringIO() 61 | test_unassigned_outfile = io.StringIO() 62 | test_unresolved_outfile = io.StringIO() 63 | sam1 = io.TextIOWrapper(resource_stream(__name__, 'data/test_human_in.sam')) 64 | sam2 = io.TextIOWrapper(resource_stream(__name__, 'data/test_mouse_in.sam')) 65 | process_headers(sam1,sam2, 66 | primary_specific=test_primary_specific_outfile, 67 | secondary_specific=test_secondary_specific_outfile, 68 | primary_multi=test_primary_multi_outfile, 69 | secondary_multi=test_secondary_multi_outfile, 70 | unresolved=test_unresolved_outfile, 71 | unassigned=test_unassigned_outfile, 72 | ) 73 | cat_counts = main_single_end(getReadPairs(sam1,sam2), 74 | primary_specific=test_primary_specific_outfile, 75 | secondary_specific=test_secondary_specific_outfile, 76 | primary_multi=test_primary_multi_outfile, 77 | secondary_multi=test_secondary_multi_outfile, 78 | unresolved=test_unresolved_outfile, 79 | unassigned=test_unassigned_outfile, 80 | ) 81 | self.assertEqual(cat_counts['primary_specific'], 82 | len(test_primary_specific_outfile.getvalue().split('\n'))-4) #29 lines of header in this file 83 | self.assertEqual(cat_counts['primary_multi'], 84 | len(test_primary_multi_outfile.getvalue().split('\n'))-4) #29 lines of header in this file 85 | self.assertEqual(cat_counts['secondary_specific'], 86 | len(test_secondary_specific_outfile.getvalue().split('\n'))-4) #26 lines of header in this file 87 | self.assertEqual(cat_counts['secondary_multi'], 88 | len(test_secondary_multi_outfile.getvalue().split('\n'))-4) #26 lines of header in this file 89 | self.assertEqual(cat_counts['unassigned'], 90 | len(test_unassigned_outfile.getvalue().split('\n'))-4) #26 lines of header in this file 91 | self.assertEqual(cat_counts['unassigned'], 92 | len(test_unassigned_outfile.getvalue().split('\n'))-4) #26 lines of header in this file 93 | self.assertEqual(hashlib.sha224(test_primary_specific_outfile.getvalue().encode('latin-1')).hexdigest(),'381325b12dd9a9cd3afdd72eeb16b23cc92ddd16f675bb21bb21e08e') 94 | sam1.close() 95 | sam2.close() 96 | pass 97 | 98 | def test_consistent_output_PE(self): 99 | test_primary_specific_outfile = io.StringIO() 100 | test_secondary_specific_outfile = io.StringIO() 101 | test_primary_multi_outfile = io.StringIO() 102 | test_secondary_multi_outfile = io.StringIO() 103 | test_unassigned_outfile = io.StringIO() 104 | test_unresolved_outfile = io.StringIO() 105 | sam1 = io.TextIOWrapper(resource_stream(__name__, 'data/paired_end_testdata_human.sam')) 106 | sam2 = io.TextIOWrapper(resource_stream(__name__, 'data/paired_end_testdata_mouse.sam')) 107 | process_headers(sam1,sam2,primary_specific=test_primary_specific_outfile, secondary_specific=test_secondary_specific_outfile) 108 | cat_counts = main_paired_end(getReadPairs(sam1,sam2), 109 | primary_specific=test_primary_specific_outfile, 110 | secondary_specific=test_secondary_specific_outfile, 111 | primary_multi=test_primary_multi_outfile, 112 | secondary_multi=test_secondary_multi_outfile, 113 | unresolved=test_unresolved_outfile, 114 | unassigned=test_unassigned_outfile, 115 | ) 116 | self.assertEqual(sum([cat_counts[x] for x in cat_counts if 'primary_specific' in x])*2, 117 | len(test_primary_specific_outfile.getvalue().split('\n'))-30) #29 lines of header in this file 118 | self.assertEqual(sum([cat_counts[x] for x in cat_counts if 'secondary_specific' in x and not 'primary_specific' in x])*2, 119 | len(test_secondary_specific_outfile.getvalue().split('\n'))-27) #26 lines of header in this file 120 | self.assertEqual(sum([cat_counts[x] for x in cat_counts if 'primary_multi' in x and not 'primary_specific' in x and not 'secondary_specific' in x])*2, 121 | len(test_primary_multi_outfile.getvalue().split('\n'))-1) 122 | self.assertEqual(sum([cat_counts[x] for x in cat_counts if 'secondary_multi' in x \ 123 | and not 'primary_multi' in x and not 'primary_specific' in x and not 'secondary_specific' in x])*2, 124 | len(test_secondary_multi_outfile.getvalue().split('\n'))-1) 125 | self.assertEqual(hashlib.sha224(test_primary_specific_outfile.getvalue().encode('latin-1')).hexdigest(),'64c0e24bf141c5aa3bb0993c73b34cdfe630a504ac424843f746918d') 126 | sam1.close() 127 | sam2.close() 128 | pass 129 | 130 | def test_consistent_output_conservative_PE(self): 131 | test_primary_specific_outfile = io.StringIO() 132 | test_secondary_specific_outfile = io.StringIO() 133 | test_primary_multi_outfile = io.StringIO() 134 | test_secondary_multi_outfile = io.StringIO() 135 | test_unassigned_outfile = io.StringIO() 136 | test_unresolved_outfile = io.StringIO() 137 | sam1 = io.TextIOWrapper(resource_stream(__name__, 'data/paired_end_testdata_human.sam')) 138 | sam2 = io.TextIOWrapper(resource_stream(__name__, 'data/paired_end_testdata_mouse.sam')) 139 | process_headers(sam1,sam2,primary_specific=test_primary_specific_outfile, secondary_specific=test_secondary_specific_outfile) 140 | cat_counts = conservative_main_paired_end(getReadPairs(sam1,sam2), 141 | primary_specific=test_primary_specific_outfile, 142 | secondary_specific=test_secondary_specific_outfile, 143 | primary_multi=test_primary_multi_outfile, 144 | secondary_multi=test_secondary_multi_outfile, 145 | unresolved=test_unresolved_outfile, 146 | unassigned=test_unassigned_outfile, 147 | ) 148 | self.assertEqual(cat_counts[('primary_specific', 'secondary_specific')]*4 +\ 149 | cat_counts[('unresolved', 'unresolved')]*4, len(test_unresolved_outfile.getvalue().split('\n'))-1) #this test is not exhastive. Only states in test data 150 | self.assertEqual(cat_counts[('primary_multi', 'primary_multi')]*2, len(test_primary_multi_outfile.getvalue().split('\n'))-1) 151 | self.assertEqual(cat_counts[('secondary_multi', 'secondary_multi')]*2, len(test_secondary_multi_outfile.getvalue().split('\n'))-1) 152 | self.assertEqual(cat_counts[('primary_specific', 'primary_specific')]*2 + cat_counts[('primary_specific', 'primary_multi')]*2 + cat_counts[('primary_multi', 'primary_specific')]*2, 153 | len(test_primary_specific_outfile.getvalue().split('\n'))-30) #29 lines of header in this file 154 | self.assertEqual(cat_counts[('secondary_specific', 'secondary_specific')]*2 + cat_counts[('secondary_specific', 'secondary_multi')]*2 + cat_counts[('secondary_multi', 'secondary_specific')]*2, 155 | len(test_secondary_specific_outfile.getvalue().split('\n'))-27) #26 lines of header in this file 156 | self.assertEqual(cat_counts[('unassigned', 'unassigned')]*2, len(test_unassigned_outfile.getvalue().split('\n'))-1) 157 | 158 | self.assertEqual(hashlib.sha224(test_primary_specific_outfile.getvalue().encode('latin-1')).hexdigest(),'c4de3de755092c8f9ff1eb2cd360a502d74ebd4c1e65ed282515ed3e') 159 | sam1.close() 160 | sam2.close() 161 | pass 162 | 163 | 164 | def test_get_mapping_state(self): 165 | inpt_and_outpt = [ 166 | ((200,199,199,198,float('-inf')),'primary_specific'), 167 | ((200,200,199,198,float('-inf')),'primary_multi'), 168 | ((199,198,200,198,float('-inf')),'secondary_specific'), 169 | ((199,198,200,200,float('-inf')),'secondary_multi'), 170 | ((float('-inf'),float('-inf'),float('-inf'),float('-inf'),float('-inf')),'unassigned'), 171 | ((200,199,200,198,float('-inf')),'unresolved'), 172 | ((200,199,199,199,float('-inf')),'primary_specific'), 173 | ((200,200,199,199,float('-inf')),'primary_multi'), 174 | ((199,199,200,199,float('-inf')),'secondary_specific'), 175 | ((199,199,200,200,float('-inf')),'secondary_multi'), 176 | ((9,8,8,8,10),'unassigned'), 177 | ((200,200,200,200,float('-inf')),'unresolved'), 178 | ((-6,float('-inf'),float('-inf'),float('-inf'),float('-inf')),'primary_specific'), 179 | ((float('-inf'),float('-inf'),-6,float('-inf'),float('-inf')),'secondary_specific'), 180 | ((-6,float('-inf'),-2,float('-inf'),float('-inf')),'secondary_specific'), 181 | ((0,float('-inf'),-2,float('-inf'),float('-inf')),'primary_specific'), 182 | ((-2,float('-inf'),0,float('-inf'),float('-inf')),'secondary_specific'), 183 | 184 | ] 185 | 186 | for inpt, outpt in inpt_and_outpt: 187 | self.assertEqual(get_mapping_state(*inpt),outpt) 188 | pass 189 | 190 | def test_get_tag(self): 191 | inpt_and_outpt = [ 192 | ((['HWI-ST960:63:D0CYJACXX:4:1101:21264:2228', '4', '*', '0', '0', '*', '*', '0', '0', 'TGGTAGTATTGGTTATGGTTCATTGTCCGGAGAGTATATTGTTGAAGAGG', 'BBCBDFDDHHHGFHHIIIIIJIJJJIGJJJGIAF:CFEGHGGHEEEG@HI', 'YT:Z:UU'],'AS'), 193 | float('-inf')), 194 | ((['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0', 'AS:i:101', 'XS:i:99'],'AS'),101), 195 | ((['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0', 'AS:i:100', 'XS:i:99'],'XS'),99), 196 | ((['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0', 'AS:i:100', 'XS:i:99'],'NM'),0), 197 | ] 198 | for inpt, outpt in inpt_and_outpt: 199 | self.assertEqual(get_tag(*inpt),outpt) 200 | pass 201 | 202 | def test_get_tag_with_ZS_as_XS(self): 203 | inpt_and_outpt = [ 204 | ((['HWI-ST960:63:D0CYJACXX:4:1101:21264:2228', '4', '*', '0', '0', '*', '*', '0', '0', 'TGGTAGTATTGGTTATGGTTCATTGTCCGGAGAGTATATTGTTGAAGAGG', 'BBCBDFDDHHHGFHHIIIIIJIJJJIGJJJGIAF:CFEGHGGHEEEG@HI', 'YT:Z:UU'],'AS'), 205 | float('-inf')), 206 | ((['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0', 'AS:i:101', 'XS:A:+', 'ZS:i:99'],'AS'),101), 207 | ((['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0', 'AS:i:100', 'XS:A:+', 'ZS:i:99'],'XS'),99), 208 | ((['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0', 'AS:i:100', 'XS:A:+', 'ZS:i:99'],'NM'),0), 209 | ] 210 | for inpt, outpt in inpt_and_outpt: 211 | self.assertEqual(get_tag_with_ZS_as_XS(*inpt),outpt) 212 | pass 213 | 214 | def test_get_cigarbased_AS_tag(self): 215 | inpt_and_outpt = [ 216 | (['HWI-ST960:63:D0CYJACXX:4:1101:21264:2228', '4', '*', '0', '0', '*', '*', '0', '0', 'TGGTAGTATTGGTTATGGTTCATTGTCCGGAGAGTATATTGTTGAAGAGG', 'BBCBDFDDHHHGFHHIIIIIJIJJJIGJJJGIAF:CFEGHGGHEEEG@HI', 'YT:Z:UU'], 217 | float('-inf')), 218 | (['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0'],0), 219 | (['', '', '', '', '', '1S49M', '', '', '', '', '', 'NM:i:0'],-2), 220 | (['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:2'],-12), 221 | (['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0', 'AS:i:100', 'XS:i:99'],0), 222 | (['', '', '', '', '', '10M1I39M', '', '', '', '', '', 'NM:i:0'],-8), 223 | (['', '', '', '', '', '10M1D39M', '', '', '', '', '', 'NM:i:0'],-8), 224 | (['', '', '', '', '', '10M2D38M', '', '', '', '', '', 'NM:i:0'],-11), 225 | (['', '', '', '', '', '10M1I10M1D28M', '', '', '', '', '', 'NM:i:0'],-16), 226 | (['', '', '', '', '', '10M1234N40M', '', '', '', '', '', 'NM:i:0'],0), 227 | ] 228 | 229 | for inpt, outpt in inpt_and_outpt: 230 | self.assertEqual(get_cigarbased_AS_tag(inpt),outpt) 231 | 232 | self.assertEqual(get_cigarbased_AS_tag(['', '', '', '', '', '50M', '', '', '', '', '', 'NM:i:0', 'AS:i:100', 'XS:i:99'],tag='XS'),99) 233 | pass 234 | 235 | def test_output_summary(self): 236 | test_outfile = io.StringIO() 237 | canned_output='--------------------------------------------------------------------------------\n' + \ 238 | 'Read Count Category Summary\n\n' + \ 239 | '| Category | Count |\n' + \ 240 | '|:--------------------------------------------------:|:---------------:|\n' + \ 241 | '| bar | 101 |\n' + \ 242 | '| foo | 1 |\n\n' 243 | output_summary({'foo':1,'bar':101},outfile=test_outfile) 244 | self.assertEqual(test_outfile.getvalue(),canned_output) 245 | pass 246 | 247 | 248 | if __name__ == '__main__': 249 | unittest.main() --------------------------------------------------------------------------------