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PyLOH.py
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#!/usr/bin/env python
#=======================================================================================================================
# Created on 2013-07-28
# @author: Yi Li
#
# PyLOH
# Copyright (c) 2013 Yi Li <yil8@uci.edu>
#
# This code is free software; you can redistribute it and/or modify it
# under the terms of GNU GPL v2.0 (see the file LICENSE included with the distribution).
# Some features are built on top of JointSNVMix-0.6.2 (http://code.google.com/p/joint-snv-mix/).
#=======================================================================================================================
import argparse
from pyloh.preprocess.run_preprocess import run_preprocess
from pyloh.model.run_model import run_poisson_model
from pyloh.postprocess.plot import plot_BAF_heatmap
parser = argparse.ArgumentParser(prog='PyLOH')
subparsers = parser.add_subparsers()
#===============================================================================
# Add preprocess sub-command
#===============================================================================
parser_preprocess = subparsers.add_parser('preprocess',
help='''Preprocess paired normal and tumor BAM files''')
parser_preprocess.add_argument('reference_genome',
help='''FASTA file for reference genome.''')
parser_preprocess.add_argument('normal_bam',
help='''BAM file for normal sample.''')
parser_preprocess.add_argument('tumor_bam',
help='''BAM file for tumor sample.''')
parser_preprocess.add_argument('filename_base',
help='''Base name of preprocessed files to be created.''')
parser_preprocess.add_argument('--segments_bed', default=None, type=str,
help='''BED file for segments. If not provided,
use autosomes as segments. Default is None.''')
parser_preprocess.add_argument('--min_depth', default=20, type=int,
help='''Minimum reads depth required for both normal and tumor samples.
Default is 20.''')
parser_preprocess.add_argument('--min_base_qual', default=10, type=int,
help='''Minimum base quality required. Default is 10.''')
parser_preprocess.add_argument('--min_map_qual', default=10, type=int,
help='''Minimum mapping quality required. Default is 10.''')
parser_preprocess.add_argument('--process_num', default=1, type=int,
help='''Number of processes to launch for preprocessing. Default is 1.''')
parser_preprocess.set_defaults(func=run_preprocess)
#===============================================================================
# Add run_model sub-command
#===============================================================================
parser_run_model = subparsers.add_parser('run_model',
help='''Run a probabilistic model based analysis. Requires preprocessed counts
file and segments file that have been created.''')
parser_run_model.add_argument('filename_base',
help='Base name of preprocessed files created.')
parser_run_model.add_argument('--allele_number_max', default=2, type=int,
help='''Maximum copy number of each allele allows to take. Default is 2.''')
parser_run_model.add_argument('--priors', default=None, type=str,
help='''File of the prior distribution. If not provided,
use uniform prior. Default is None.''')
parser_run_model.add_argument('--max_iters', default=100, type=int,
help='''Maximum number of iterations for training. Default is 100.''')
parser_run_model.add_argument('--stop_value', default=1e-7, type=float,
help='''Stop value of the EM algorithm for training. If the change of log-likelihood is lower
than this value, stop training. Default is 1e-7.''')
parser_run_model.set_defaults(func=run_poisson_model)
#===============================================================================
# Add BAF_heatmap sub-command
#===============================================================================
parser_BAF_heatmap = subparsers.add_parser('BAF_heatmap',
help='''Plot the BAF heat map for each segment. Requires preprocessed
heatmap file that have been created.''')
parser_BAF_heatmap.add_argument('filename_base',
help='''Base name of preprocessed files created.''')
parser_BAF_heatmap.set_defaults(func=plot_BAF_heatmap)
#===============================================================================
# Run
#===============================================================================
args = parser.parse_args()
args.func(args)