{
"info": {
"author": "Chenfu Shi",
"author_email": "chenfu.shi@postgrad.manchester.ac.uk",
"bugtrack_url": null,
"classifiers": [
"Development Status :: 3 - Alpha",
"Environment :: Console",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: BSD License",
"Natural Language :: English",
"Operating System :: POSIX :: Linux",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Topic :: Scientific/Engineering :: Bio-Informatics"
],
"description": "# HiChIP peaks\n\nThis package can be used to find enriched peak regions from HiChIP datasets that can then be used as an input to available loop calling tools or to do differential peak analysis.\n\nIt takes the HiC-Pro output and converts it to a restriction site level resolution map. It then selects reads within a specified number of restriction sites from the diagonal(default = 2) and models the background as a negative binomial. It calls peaks regions that significantly exceed the background.\nThe output is a list of peaks with their properties and a bedgraph at a restriction site level resolution that describes the reads per site.\nUsing the differential analysis command it can be used to create a consensus peakset and then identify differentially bound regions across samples.\n\nResults from this package can then be used for further analysis and as a peaks dataset input for various loop calling software.\n\n#### Table of Contents \n- [Getting Started](#getting-started)\n * [Installation](#installation)\n * [Usage](#usage)\n * [Peak Calling](#peak-calling)\n * [Example run](#example-run)\n * [Differential peak analysis](#differential-peak-analysis)\n\n- [Authors](#authors)\n- [License](#license)\n- [Citation](#citation)\n\n## Getting started\n\n### Installation\n\nThe package requires bedtools to run. The package can then be installed through pip\n\n```\npip install hichip-peaks\n```\n\nWe suggest using conda environments to avoid cluttering\n\n```\nconda create --name hichip-peaks python=3.7 bedtools pip\npip install hichip-peaks\n```\n\n\n### Usage\n#### Peak calling\nClean the raw reads and align using HiC-Pro with normal settings making sure that these settings are set as follows(for MboI digested libraries):\n\n```\n#######################################################################\n## Digestion Hi-C\n#######################################################################\n\nGENOME_FRAGMENT = MboI_resfrag_hg38.bed\nLIGATION_SITE = GATCGATC\nMIN_FRAG_SIZE = \nMAX_FRAG_SIZE =\nMIN_INSERT_SIZE =\nMAX_INSERT_SIZE =\n\n#######################################################################\n## Hi-C processing\n#######################################################################\n\nMIN_CIS_DIST =\nGET_ALL_INTERACTION_CLASSES = 1\nGET_PROCESS_SAM = 0\nRM_SINGLETON = 1\nRM_MULTI = 1\nRM_DUP = 1\n```\n\nUse the peak_call command\n\n```\nusage: peak_call [-h] -i HICPRO_RESULTS -o OUTPUT_DIRECTORY -r RESFRAG\n [-p PREFIX] [-f FDR] [-a SIZES] [-t TEMPORARY_LOC]\n [-w THREADS] [-k] [-d] [-s OFF_DIAG] [-x] [-c]\n\nPeak calling from HiChIP data\n\noptional arguments:\n -h, --help show this help message and exit\n -i HICPRO_RESULTS, --input HICPRO_RESULTS\n HiC-Pro results directory containing validPairs file\n and others\n -o OUTPUT_DIRECTORY, --output OUTPUT_DIRECTORY\n Output directory\n -r RESFRAG, --resfrag RESFRAG\n HiCpro resfrag file\n -p PREFIX, --prefix PREFIX\n Output file name prefix, if not provided will be name\n of HiC-Pro results directory\n -f FDR, --FDR FDR False discovery rate, default = 0.01\n -a SIZES, --annotation SIZES\n HiCpro chromosome annotation file, default uses human\n chromosomes, excludes chrY\n -t TEMPORARY_LOC, --temporary_loc TEMPORARY_LOC\n Temporary directory. If not supplied will be output\n directory\n -w THREADS, --worker_threads THREADS\n Number of threads, minimum 4. Warning: Increasing this\n significantly increases RAM usage\n -k, --keep_temp Keep temporary files\n -d, --keep_diff Prepare files for differential analysis\n -s OFF_DIAG, --offdiag OFF_DIAG\n How many off diagonal needs to be included (default =\n 2)\n -x, --chromX Want to compensate Sex chromosomes weights? Requires\n specify annotation(SIZES) containing chrX and chrY\n -c, --class_store Store sparse site_matrix object for further use\n\n```\n\nThis command needs the HICPRO_RESULTS/hic_results/data/sample/ output folder where all the valid pairs files are.\nThe command requires that all the files in that folder are present, including the .REPairs, SCPairs and DEPairs file.\n\nThis command will generate the following files:\n\n- log.log file, contains all the inputs used, the logs and the quality metrics calculated such as number of peaks called and fraction of reads in peaks.\n- bedgraph.bdg file, containing the coverage track with all the reads used in the peak calling step.\n- peaks.bed file, contains all the peaks called. The 3 extra information columns are:\n * average signal in the peak\n * maximum signal in the peak\n * -log10 of p value of the peak\n- report.pdf, contains some useful plots and quality metrics.\n\nIf enabled this command will also generate:\n- diffpeak_data.pickle, file containing the information necessary for differential peak analysis.\n- mat_obj.pickle, file containing the sparse matrix representation at a restriction site level of all the interactions. Currently in development but you can look into site_matrix_class.py to understand how it works.\n\n#### Example run\nAssuming the data is in HICPRO_RESULTS/hic_results/data/sample/ and installation of HiC-Pro is in HICPRO_dir/\nYou can run the software with the following command:\n\n```\npeak_call -i HICPRO_RESULTS/hic_results/data/sample/ -o ./results -r HICPRO_dir/annotation/MboI_resfrag_hg38.bed \n\n```\nSome example results can be found in [example_results](https://github.com/ChenfuShi/HiChIP_peaks/tree/master/example_results).\n\n#### Differential peak analysis\n\nRun the previous commands with the --keepdiff flag enabled. This will produce a temporary file that can be used with the diff_peaks command to integrate all samples together. This utility will look for all the correct files in a specified folder, merge the peaks at a fragment site level a produce a table with the signal in each peak from each sample. This can then be imported in R or others and analysed using DESeq2 or other differential expression analysis tools. See example R script for inspiration.\n\n```\nusage: diff_peaks [-h] -i hichip_peaks_RESULTS -o OUTPUT_FILE -r RESFRAG\n [-a SIZES] [-m MINIMUM]\n\ninput directory with outputfiles from peak_call and create table for\ndifferential analysis. Make sure to activate --keep_diff in the previous step!\n\noptional arguments:\n -h, --help show this help message and exit\n -i hichip_peaks_RESULTS, --input hichip_peaks_RESULTS\n directory containing previous step results\n -o OUTPUT_FILE, --output OUTPUT_FILE\n Output file\n -r RESFRAG, --resfrag RESFRAG\n HiCpro resfrag file\n -a SIZES, --annotation SIZES\n HiCpro chromosome annotation file, default uses human\n chromosomes, excludes chrY\n -m MINIMUM, --minimum MINIMUM\n How many samples need to be peak to be considered peak\n for analysis\n```\n\n\n## Authors\n\nThis packages was developed by Chenfu Shi1, Magnus Rattray2,3 and Gisela Orozco1,3 at the University of Manchester.\n\n1) Centre for Genetics and Genomics Versus Arthritis. Division of Musculoskeletal and Dermatolog-ical Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The Universi-ty of Manchester, UK\n2) Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK.\n3) NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.\n\n\nThis work was funded by the Wellcome Trust (award references 207491/Z/17/Z and 215207/Z/19/Z), Versus Arthritis (award reference 21754), NIHR Manchester BRC and the Medical Research Council (award reference MR/N00017X/1).\nConflict of Interest: none declared.\n\n\n## License\n\nThe software is released with a BSD-3-Clause License\n\n```\nBSD-3-Clause License\nCopyright 2019 Chenfu Shi\nAll rights reserved.\n\nRedistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:\n\n1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.\n\n2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.\n\n3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n```\n\n## Citation\n\nPlease cite our paper when using this package for your research!\n```\nShi,C. et al. (2019) HiChIP-Peaks: A HiChIP peak calling algorithm. bioRxiv, 682781.\nhttps://doi.org/10.1101/682781\n```\n\n\n",
"description_content_type": "text/markdown",
"docs_url": null,
"download_url": "",
"downloads": {
"last_day": -1,
"last_month": -1,
"last_week": -1
},
"home_page": "https://github.com/ChenfuShi/HiChIP_peaks",
"keywords": "",
"license": "BSD",
"maintainer": "",
"maintainer_email": "",
"name": "hichip-peaks",
"package_url": "https://pypi.org/project/hichip-peaks/",
"platform": "",
"project_url": "https://pypi.org/project/hichip-peaks/",
"project_urls": {
"Homepage": "https://github.com/ChenfuShi/HiChIP_peaks"
},
"release_url": "https://pypi.org/project/hichip-peaks/0.1.1/",
"requires_dist": [
"scipy",
"numpy",
"statsmodels",
"matplotlib"
],
"requires_python": ">=3.6",
"summary": "A tool to find peaks from hichip data",
"version": "0.1.1"
},
"last_serial": 5540867,
"releases": {
"0.1.0": [
{
"comment_text": "",
"digests": {
"md5": "53d0856e870dc2b263c9f2ba70834fa9",
"sha256": "59647b3b61ccbea0fd2c27e3cb3a05c18481e9ec9cfa487858851cb0a3b61756"
},
"downloads": -1,
"filename": "hichip_peaks-0.1.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "53d0856e870dc2b263c9f2ba70834fa9",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 22112,
"upload_time": "2019-06-19T16:21:53",
"url": "https://files.pythonhosted.org/packages/2f/a4/39cd7e9829d479770f2c33c45c4c4fcee931fcefda14d8dbea5a3b47fc8c/hichip_peaks-0.1.0-py3-none-any.whl"
},
{
"comment_text": "",
"digests": {
"md5": "097d501b96b45ed40514c9c467723935",
"sha256": "dff91c618a7e1fd8e2d42e974e59a3c066cb73e9e5c6792bf2b5bc3edfbf990f"
},
"downloads": -1,
"filename": "hichip_peaks-0.1.0.tar.gz",
"has_sig": false,
"md5_digest": "097d501b96b45ed40514c9c467723935",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 20361,
"upload_time": "2019-06-19T16:21:55",
"url": "https://files.pythonhosted.org/packages/6b/c5/79f5427c94d8404bc819b7c02d8b2d293cfaeab7a0c55f9b3736ad496707/hichip_peaks-0.1.0.tar.gz"
}
],
"0.1.1": [
{
"comment_text": "",
"digests": {
"md5": "4043a6ff112f1c76141bc9e594b594d2",
"sha256": "aa05029d0ee75967f26f4af4161630ab8296ef0d8a16be89da020d5fd05e8d79"
},
"downloads": -1,
"filename": "hichip_peaks-0.1.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "4043a6ff112f1c76141bc9e594b594d2",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 25850,
"upload_time": "2019-07-16T14:21:23",
"url": "https://files.pythonhosted.org/packages/d8/13/51335d5393c89cb53f0a8ea0dd5220f1d853f0fb20d2f855aa95df98537b/hichip_peaks-0.1.1-py3-none-any.whl"
},
{
"comment_text": "",
"digests": {
"md5": "abf50e0a30548d964033c8d9179cd013",
"sha256": "0d5a00d45742e862921056a11b5b70c70c7a158590a0aba461b5ca56f4111a23"
},
"downloads": -1,
"filename": "hichip_peaks-0.1.1.tar.gz",
"has_sig": false,
"md5_digest": "abf50e0a30548d964033c8d9179cd013",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 24859,
"upload_time": "2019-07-16T14:21:24",
"url": "https://files.pythonhosted.org/packages/00/d9/9a81af8894ae2f7004a5691ee927e4e06461e1e47533b240e180808dc74d/hichip_peaks-0.1.1.tar.gz"
}
]
},
"urls": [
{
"comment_text": "",
"digests": {
"md5": "4043a6ff112f1c76141bc9e594b594d2",
"sha256": "aa05029d0ee75967f26f4af4161630ab8296ef0d8a16be89da020d5fd05e8d79"
},
"downloads": -1,
"filename": "hichip_peaks-0.1.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "4043a6ff112f1c76141bc9e594b594d2",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 25850,
"upload_time": "2019-07-16T14:21:23",
"url": "https://files.pythonhosted.org/packages/d8/13/51335d5393c89cb53f0a8ea0dd5220f1d853f0fb20d2f855aa95df98537b/hichip_peaks-0.1.1-py3-none-any.whl"
},
{
"comment_text": "",
"digests": {
"md5": "abf50e0a30548d964033c8d9179cd013",
"sha256": "0d5a00d45742e862921056a11b5b70c70c7a158590a0aba461b5ca56f4111a23"
},
"downloads": -1,
"filename": "hichip_peaks-0.1.1.tar.gz",
"has_sig": false,
"md5_digest": "abf50e0a30548d964033c8d9179cd013",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 24859,
"upload_time": "2019-07-16T14:21:24",
"url": "https://files.pythonhosted.org/packages/00/d9/9a81af8894ae2f7004a5691ee927e4e06461e1e47533b240e180808dc74d/hichip_peaks-0.1.1.tar.gz"
}
]
}