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encode_task_reproducibility.py
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#!/usr/bin/env python
# ENCODE DCC reproducibility QC wrapper
# Author: Jin Lee ([email protected])
import sys
import os
import argparse
from encode_lib_common import (
copy_f_to_f,
get_num_lines,
infer_n_from_nC2,
infer_pair_label_from_idx,
log,
mkdir_p,
)
from encode_lib_genomic import (
peak_to_bigbed,
peak_to_hammock,
get_region_size_metrics,
get_num_peaks,
peak_to_starch,
)
def parse_arguments():
parser = argparse.ArgumentParser(
prog='ENCODE DCC reproducibility QC.',
description='IDR peak or overlap peak only.')
parser.add_argument('peaks', type=str, nargs='*',
help='List of peak files \
from true replicates in a sorted order. \
For example of 4 true replicates, \
0,1 0,2 0,3 1,2 1,3 2,3. \
x,y means peak file from rep-x vs rep-y.')
parser.add_argument('--peaks-pr', type=str, nargs='+', required=True,
help='List of peak files from pseudo replicates.')
parser.add_argument('--peak-ppr', type=str,
help='Peak file from pooled pseudo replicate.')
parser.add_argument('--peak-type', type=str, default='narrowPeak',
choices=['narrowPeak', 'regionPeak',
'broadPeak', 'gappedPeak'],
help='Peak file type.')
parser.add_argument('--chrsz', type=str,
help='2-col chromosome sizes file.')
parser.add_argument('--prefix', type=str,
help='Basename prefix for reproducibility QC file.')
parser.add_argument('--mem-gb', type=float, default=4.0,
help='Max. memory for this job in GB. '
'This will be used to determine GNU sort -S (defaulting to 0.5 of this value). '
'It should be total memory for this task (not memory per thread).')
parser.add_argument('--out-dir', default='', type=str,
help='Output directory.')
parser.add_argument('--log-level', default='INFO',
choices=['NOTSET', 'DEBUG', 'INFO',
'WARNING', 'CRITICAL', 'ERROR',
'CRITICAL'],
help='Log level')
args = parser.parse_args()
if len(args.peaks_pr) != infer_n_from_nC2(len(args.peaks)):
raise argparse.ArgumentTypeError(
'Invalid number of peak files or --peaks-pr.')
log.setLevel(args.log_level)
log.info(sys.argv)
return args
def main():
# read params
args = parse_arguments()
log.info('Initializing and making output directory...')
mkdir_p(args.out_dir)
log.info('Reproducibility QC...')
# description for variables
# N: list of number of peaks in peak files from pseudo replicates
# Nt: top number of peaks in peak files
# from true replicates (rep-x_vs_rep-y)
# Np: number of peaks in peak files from pooled pseudo replicate
N = [get_num_lines(peak) for peak in args.peaks_pr]
if len(args.peaks):
# multiple replicate case
num_rep = infer_n_from_nC2(len(args.peaks))
num_peaks_tr = [get_num_lines(peak) for peak in args.peaks]
Nt = max(num_peaks_tr)
Np = get_num_lines(args.peak_ppr)
rescue_ratio = float(max(Np, Nt))/float(min(Np, Nt))
self_consistency_ratio = float(max(N))/float(min(N))
Nt_idx = num_peaks_tr.index(Nt)
label_tr = infer_pair_label_from_idx(num_rep, Nt_idx)
conservative_set = label_tr
conservative_peak = args.peaks[Nt_idx]
N_conservative = Nt
if Nt > Np:
optimal_set = conservative_set
optimal_peak = conservative_peak
N_optimal = N_conservative
else:
optimal_set = "pooled-pr1_vs_pooled-pr2"
optimal_peak = args.peak_ppr
N_optimal = Np
else:
# single replicate case
num_rep = 1
Nt = 0
Np = 0
rescue_ratio = 0.0
self_consistency_ratio = 1.0
conservative_set = 'rep1-pr1_vs_rep1-pr2'
conservative_peak = args.peaks_pr[0]
N_conservative = N[0]
optimal_set = conservative_set
optimal_peak = conservative_peak
N_optimal = N_conservative
reproducibility = 'pass'
if rescue_ratio > 2.0 or self_consistency_ratio > 2.0:
reproducibility = 'borderline'
if rescue_ratio > 2.0 and self_consistency_ratio > 2.0:
reproducibility = 'fail'
log.info('Writing optimal/conservative peak files...')
optimal_peak_file = os.path.join(
args.out_dir, '{}optimal_peak.{}.gz'.format(
(args.prefix + '.') if args.prefix else '',
args.peak_type))
conservative_peak_file = os.path.join(
args.out_dir, '{}conservative_peak.{}.gz'.format(
(args.prefix + '.') if args.prefix else '',
args.peak_type))
copy_f_to_f(optimal_peak, optimal_peak_file)
copy_f_to_f(conservative_peak, conservative_peak_file)
if args.chrsz:
log.info('Converting peak to bigbed...')
peak_to_bigbed(optimal_peak_file, args.peak_type,
args.chrsz, args.mem_gb, args.out_dir)
peak_to_bigbed(conservative_peak_file, args.peak_type,
args.chrsz, args.mem_gb, args.out_dir)
log.info('Converting peak to starch...')
peak_to_starch(optimal_peak_file, args.out_dir)
peak_to_starch(conservative_peak_file, args.out_dir)
log.info('Converting peak to hammock...')
peak_to_hammock(optimal_peak_file,
args.mem_gb,
args.out_dir)
peak_to_hammock(conservative_peak_file,
args.mem_gb,
args.out_dir)
log.info('Writing reproducibility QC log...')
if args.prefix:
reproducibility_qc = '{}.reproducibility.qc'.format(args.prefix)
else:
reproducibility_qc = 'reproducibility.qc'
reproducibility_qc = os.path.join(args.out_dir, reproducibility_qc)
with open(reproducibility_qc, 'w') as fp:
header = '{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\n'.format(
'Nt',
'\t'.join(['N{}'.format(i+1) for i in range(num_rep)]),
'Np',
'N_opt',
'N_consv',
'opt_set',
'consv_set',
'rescue_ratio',
'self_consistency_ratio',
'reproducibility',
)
line = '{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\t{}\n'.format(
Nt,
'\t'.join([str(i) for i in N]),
Np,
N_optimal,
N_conservative,
optimal_set,
conservative_set,
rescue_ratio,
self_consistency_ratio,
reproducibility)
fp.write(header)
fp.write(line)
log.info('Calculating (optimal) peak region size QC/plot...')
region_size_qc, region_size_plot = get_region_size_metrics(
optimal_peak_file)
log.info('Calculating number of peaks (optimal)...')
get_num_peaks(optimal_peak_file)
log.info('All done.')
if __name__ == '__main__':
main()