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        "author": "Emmanuel Naziga",
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        "description": "ABOUT\n++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\nPython implementation of Java SNP calling pipeline (https://github.com/DSGlab/SNPCallingPipeline).\nUsage is descriped below. For consistency the configuration file is exactly as described in the Java code.\nDescriptions of the various options in the Java code is given at https://github.com/DSGlab/SNPCallingPipeline.\nAn example configuration file is included in this directory.\n                                       USAGE\n+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\nusage: pySNPCallingPipeline.py [-h] -c CONF_FILE [--aln_only] [--no_aln]\n                               [--local] [--submit] [--subset SUBSET]\n                               [--def_run]\n\nRun pySNPCallingPipeline\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -c CONF_FILE, --conf CONF_FILE\n                        A configuration file is required to run\n                        pySNPCallingPipeline.\n  --aln_only            Alignment only, default is FALSE.\n  --no_aln              Run all analysis using pre-run alignments, default is\n                        FALSE.\n  --local               Is this a LOCAL run or should SLURM files be created?\n                        Default is True.\n  --submit              If running a supercomputing cluster, should only slurm\n                        files be created or should the jobs be submitted as\n                        well.\n  --subset SUBSET       Provide a comma seperated list of a subset of\n                        \"alignment, getHQSNPs, intraClonalSNPs, checkSNPs,\n                        filterSNPs\"\n  --def_run             Default: run entire calculation locally.\n\n\n\n",
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        "license": "MIT",
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        "name": "pySNPCall",
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