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(standing for **GEN**ome-wide **I**mputation\n**P**ipelin**E**) includes a script (named `genipe-launcher`) that\nautomatically runs a genome-wide imputation pipeline using *Plink*, *shapeit*\nand *impute2*.\n\nIf you use `genipe` in any published work, please cite the paper describing the\ntool:\n\n\u003e Lemieux Perreault LP, Legault MA, Asselin G, Dubé MP:\n\u003e **genipe: an automated genome-wide imputation pipeline with automatic reporting\n\u003e and statistical tools.** *Bioinformatics* 2016, **32** (23): 3661-3663\n\u003e (DOI:[10.1093/bioinformatics/btw487](http://dx.doi.org/10.1093/bioinformatics/btw487)).\n\n\n## Documentation\n\nFull documentation is available at\n[http://pgxcentre.github.io/genipe/](http://pgxcentre.github.io/genipe/).\n\n\n## Installation\n\nVersion 1.5.0 of `genipe` should work with the most recent versions of the\npackages.\n\nWe recommend installing the package in a Python 3.7 (or latest) virtual\nenvironment. There are two ways to install: `pip` or `conda`.\n\n```bash\n# Using pip\npip install genipe\n```\n\n```bash\n# Using conda\nconda install genipe -c http://statgen.org/wp-content/uploads/Softwares/genipe\n```\n\nThe installation process should install all required dependencies to run the\nmain imputation pipeline. Optional dependencies can also be installed manually\nin order to perform statistical analysis and data management (see below).\n\nThe complete installation procedure is available in the\n[documentation](http://pgxcentre.github.io/genipe/installation.html).\n\n\n### Dependencies\n\nThe tool requires a standard [Python](http://python.org/) 3.4 (or latest)\ninstallation with the following modules:\n\n* `numpy` version 1.11.3 and latest\n* `Jinja2` version 2.9 and latest\n* `pandas` version 0.19.2 and latest\n* `setuptools` version 12.0.5 and latest\n\nThe tool requires the binaries for\n[Plink](http://pngu.mgh.harvard.edu/~purcell/plink/download.shtml),\n[shapeit](https://mathgen.stats.ox.ac.uk/genetics_software/shapeit/shapeit.html#download)\nand [impute2](https://mathgen.stats.ox.ac.uk/impute/impute_v2.html#download).\n\n\n### Optional dependencies\n\nIn order to perform data management and statistical analysis (linear, logistic\nand Cox's regressions), `genipe` requires the following Python modules:\n\n* `Matplotlib`\n* `scipy`\n* `patsy`\n* `statsmodels`\n* `lifelines`\n* `Biopython`\n* `pyfaidx`\n* `drmaa`\n* `pyplink`\n\nNote that `statsmodels` (specifically MixedLM analysis) version 0.6 **is not\ncompatible** with `numpy` version 1.12 and latest.\n\nFinally, the tool requires a LaTeX installation to compile the automatically\ngenerated report in PDF format.\n\n\n### Testing\n\nBasic testing was implemented for the script to merge *impute2* files resulting\nfrom different segments of the same chromosome along with some utility\nfunctions of the main package. To test the package (once installed), launch\nPython and execute the following command:\n\n```python\n\u003e\u003e\u003e import genipe\n\u003e\u003e\u003e genipe.test()\n```\n\nSome functionalities are difficult to test, since they mostly use external\ntools to perform analysis (*i.e.* *Plink*, *shapeit* and *impute2*) and it\nis assumed that they were properly tested by their author.\n\nWe will try to add further tests in the future.\n\n\n## Basic usage\n\nThe following options are available when launching a genome-wide imputation\nanalysis.\n\n```console\n$ genipe-launcher --help\nusage: genipe-launcher [-h] [-v] [--debug] [--thread THREAD] --bfile PREFIX\n                       [--reference FILE] [--chrom CHROM [CHROM ...]]\n                       [--output-dir DIR] [--bgzip] [--use-drmaa]\n                       [--drmaa-config FILE] [--preamble FILE]\n                       [--shapeit-bin BINARY] [--shapeit-thread INT]\n                       [--shapeit-extra OPTIONS] [--plink-bin BINARY]\n                       [--hap-template TEMPLATE] [--legend-template TEMPLATE]\n                       [--map-template TEMPLATE] --sample-file FILE\n                       [--hap-nonPAR FILE] [--hap-PAR1 FILE] [--hap-PAR2 FILE]\n                       [--legend-nonPAR FILE] [--legend-PAR1 FILE]\n                       [--legend-PAR2 FILE] [--map-nonPAR FILE]\n                       [--map-PAR1 FILE] [--map-PAR2 FILE]\n                       [--impute2-bin BINARY] [--segment-length BP]\n                       [--filtering-rules RULE [RULE ...]]\n                       [--impute2-extra OPTIONS] [--probability FLOAT]\n                       [--completion FLOAT] [--info FLOAT]\n                       [--report-number NB] [--report-title TITLE]\n                       [--report-author AUTHOR]\n                       [--report-background BACKGROUND]\n\nExecute the genome-wide imputation pipeline. This script is part of the\n'genipe' package, version 1.4.2.\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -v, --version         show program's version number and exit\n  --debug               set the logging level to debug\n  --thread THREAD       number of threads [1]\n\nInput Options:\n  --bfile PREFIX        The prefix of the binary pedfiles (input data).\n  --reference FILE      The human reference to perform an initial strand check\n                        (useful for genotyped markers not in the IMPUTE2\n                        reference files) (optional).\n\nOutput Options:\n  --chrom CHROM [CHROM ...]\n                        The chromosomes to process. It is possible to write\n                        'autosomes' to process all the autosomes (from\n                        chromosome 1 to 22, inclusively).\n  --output-dir DIR      The name of the output directory. [genipe]\n  --bgzip               Use bgzip to compress the impute2 files.\n\nHPC Options:\n  --use-drmaa           Launch tasks using DRMAA.\n  --drmaa-config FILE   The configuration file for tasks (use this option when\n                        launching tasks using DRMAA). This file should\n                        describe the walltime and the number of\n                        nodes/processors to use for each task.\n  --preamble FILE       This option should be used when using DRMAA on a HPC\n                        to load required module and set environment variables.\n                        The content of the file will be added between the\n                        'shebang' line and the tool command.\n\nSHAPEIT Options:\n  --shapeit-bin BINARY  The SHAPEIT binary if it's not in the path.\n  --shapeit-thread INT  The number of thread for phasing. [1]\n  --shapeit-extra OPTIONS\n                        SHAPEIT extra parameters. Put extra parameters between\n                        single or normal quotes (e.g. --shapeit-extra '--\n                        states 100 --window 2').\n\nPlink Options:\n  --plink-bin BINARY    The Plink binary if it's not in the path.\n\nIMPUTE2 Autosomal Reference:\n  --hap-template TEMPLATE\n                        The template for IMPUTE2's haplotype files (replace\n                        the chromosome number by '{chrom}', e.g.\n                        '1000GP_Phase3_chr{chrom}.hap.gz').\n  --legend-template TEMPLATE\n                        The template for IMPUTE2's legend files (replace the\n                        chromosome number by '{chrom}', e.g.\n                        '1000GP_Phase3_chr{chrom}.legend.gz').\n  --map-template TEMPLATE\n                        The template for IMPUTE2's map files (replace the\n                        chromosome number by '{chrom}', e.g.\n                        'genetic_map_chr{chrom}_combined_b37.txt').\n  --sample-file FILE    The name of IMPUTE2's sample file.\n\nIMPUTE2 Chromosome X Reference:\n  --hap-nonPAR FILE     The IMPUTE2's haplotype file for the non-\n                        pseudoautosomal region of chromosome 23.\n  --hap-PAR1 FILE       The IMPUTE2's haplotype file for the first\n                        pseudoautosomal region of chromosome 23.\n  --hap-PAR2 FILE       The IMPUTE2's haplotype file for the second\n                        pseudoautosomal region of chromosome 23.\n  --legend-nonPAR FILE  The IMPUTE2's legend file for the non-pseudoautosomal\n                        region of chromosome 23.\n  --legend-PAR1 FILE    The IMPUTE2's legend file for the first\n                        pseudoautosomal region of chromosome 23.\n  --legend-PAR2 FILE    The IMPUTE2's legend file for the second\n                        pseudoautosomal region of chromosome 23.\n  --map-nonPAR FILE     The IMPUTE2's map file for the non-pseudoautosomal\n                        region of chromosome 23.\n  --map-PAR1 FILE       The IMPUTE2's map file for the first pseudoautosomal\n                        region of chromosome 23.\n  --map-PAR2 FILE       The IMPUTE2's map file for the second pseudoautosomal\n                        region of chromosome 23.\n\nIMPUTE2 Options:\n  --impute2-bin BINARY  The IMPUTE2 binary if it's not in the path.\n  --segment-length BP   The length of a single segment for imputation. [5e+06]\n  --filtering-rules RULE [RULE ...]\n                        IMPUTE2 filtering rules (optional).\n  --impute2-extra OPTIONS\n                        IMPUTE2 extra parameters. Put the extra parameters\n                        between single or normal quotes (e.g. --impute2-extra\n                        '-buffer 250 -Ne 20000').\n\nIMPUTE2 Merger Options:\n  --probability FLOAT   The probability threshold for no calls. [\u003c0.9]\n  --completion FLOAT    The completion rate threshold for site exclusion.\n                        [\u003c0.98]\n  --info FLOAT          The measure of the observed statistical information\n                        associated with the allele frequency estimate\n                        threshold for site exclusion. [\u003c0.00]\n\nAutomatic Report Options:\n  --report-number NB    The report number. [genipe automatic report]\n  --report-title TITLE  The report title. [genipe: Automatic genome-wide\n                        imputation]\n  --report-author AUTHOR\n                        The report author. [Automatically generated by genipe]\n  --report-background BACKGROUND\n                        The report background section (can either be a string\n                        or a file containing the background. [General\n                        background]\n```\n\n\n### Real life example\n\nThe documentation provides a quick and easy tutorial for the complete pipeline.\nRefer to [this page](http://pgxcentre.github.io/genipe/tutorials.html)\n\n\n### Automatic report\n\nThe pipeline provides a report containing relevant imputation statistics. This\nreport is located in the `report` directory. It can be compiled into a PDF file\nusing the following `make` command:\n\n```console\n$ make \u0026\u0026 make clean\n...\n```\n\nThis report uses LaTeX and the `*.tex` file can be modified to add project\nspecific information.\n\n\n### Statistical analysis\n\nOnce the genome-wide imputation analysis is performed and the quality metrics\nprovided by the automatic report have been reviewed, it is possible to\nperform different statistical analyses (e.g. linear or logistic regression,\nor survival analysis using Cox's proportional hazard model) using the provided\nscript named `imputed-stats`.\n\n```console\n$ imputed-stats --help\nusage: imputed-stats [-h] [-v] {cox,linear,logistic,mixedlm,skat} ...\n\nPerforms statistical analysis on imputed data (either SKAT analysis, or\nlinear, logistic or survival regression). This script is part of the 'genipe'\npackage, version 1.4.2.\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -v, --version         show program's version number and exit\n\nStatistical Analysis Type:\n  The type of statistical analysis to be performed on the imputed data.\n\n  {cox,linear,logistic,mixedlm,skat}\n    cox                 Cox's proportional hazard model (survival regression).\n    linear              Linear regression (ordinary least squares).\n    logistic            Logistic regression (GLM with binomial distribution).\n    mixedlm             Linear mixed effect model (random intercept).\n    skat                SKAT analysis.\n```\n\nSee the tutorials for more information:\n[http://pgxcentre.github.io/genipe/tutorials.html](http://pgxcentre.github.io/genipe/tutorials.html)\n\n\n# About\n\nThis project was initiated at the\n[Beaulieu-Saucier Pharmacogenomics Centre](http://www.pharmacogenomics.ca/) of\nthe [Montreal Heart Institute](https://www.icm-mhi.org/). The aim was to speed\nup (and automatize) the imputation process for the whole genome.\n\n\n\u003cimg src=http://pgxcentre.github.io/genipe/_images/logo_pgx.png width=350 /\u003e\n\n\u003cimg src=http://pgxcentre.github.io/genipe/_images/logo_statgen.png width=200 /\u003e\n\n\u003cimg src=http://pgxcentre.github.io/genipe/_images/logo_icm.jpg width=350 /\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpgxcentre%2Fgenipe","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpgxcentre%2Fgenipe","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpgxcentre%2Fgenipe/lists"}