Mercurial > repos > mheinzl > variant_analyzer2
view mut2read.py @ 1:2a505d46f682 draft
planemo upload for repository https://github.com/gpovysil/VariantAnalyzerGalaxy/tree/master/tools/variant_analyzer commit ee4a8e6cf290e6c8a4d55f9cd2839d60ab3b11c8
author | mheinzl |
---|---|
date | Sun, 04 Oct 2020 19:09:51 +0000 |
parents | e5953c54cfb5 |
children | 11a2a34f8a2b |
line wrap: on
line source
#!/usr/bin/env python """mut2read.py Author -- Gundula Povysil Contact -- povysil@bioinf.jku.at Takes a tabular file with mutations and a BAM file as input and prints all tags of reads that carry the mutation to a user specified output file. Creates fastq file of reads of tags with mutation. ======= ========== ================= ================================ Version Date Author Description 0.2.1 2019-10-27 Gundula Povysil - ======= ========== ================= ================================ USAGE: python mut2read.py DCS_Mutations.tabular DCS.bam Aligned_Families.tabular Interesting_Reads.fastq tag_count_dict.json """ import argparse import json import os import sys import numpy as np import pysam def make_argparser(): parser = argparse.ArgumentParser(description='Takes a tabular file with mutations and a BAM file as input and prints all tags of reads that carry the mutation to a user specified output file and creates a fastq file of reads of tags with mutation.') parser.add_argument('--mutFile', help='TABULAR file with DCS mutations.') parser.add_argument('--bamFile', help='BAM file with aligned DCS reads.') parser.add_argument('--familiesFile', help='TABULAR file with aligned families.') parser.add_argument('--outputFastq', help='Output FASTQ file of reads with mutations.') parser.add_argument('--outputJson', help='Output JSON file to store collected data.') return parser def mut2read(argv): parser = make_argparser() args = parser.parse_args(argv[1:]) file1 = args.mutFile file2 = args.bamFile file3 = args.familiesFile outfile = args.outputFastq json_file = args.outputJson if os.path.isfile(file1) is False: sys.exit("Error: Could not find '{}'".format(file1)) if os.path.isfile(file2) is False: sys.exit("Error: Could not find '{}'".format(file2)) if os.path.isfile(file3) is False: sys.exit("Error: Could not find '{}'".format(file3)) # read mut file with open(file1, 'r') as mut: mut_array = np.genfromtxt(mut, skip_header=1, delimiter='\t', comments='#', dtype=str) # read dcs bam file # pysam.index(file2) bam = pysam.AlignmentFile(file2, "rb") # get tags tag_dict = {} cvrg_dict = {} if mut_array.shape == (1,13): mut_array = mut_array.reshape((1, len(mut_array))) for m in range(len(mut_array[:, 0])): print(str(m + 1) + " of " + str(len(mut_array[:, 0]))) chrom = mut_array[m, 1] stop_pos = mut_array[m, 2].astype(int) chrom_stop_pos = str(chrom) + "#" + str(stop_pos) ref = mut_array[m, 9] alt = mut_array[m, 10] dcs_len = [] for pileupcolumn in bam.pileup(chrom.tostring(), stop_pos - 2, stop_pos, max_depth=100000000): if pileupcolumn.reference_pos == stop_pos - 1: count_alt = 0 count_ref = 0 count_indel = 0 count_n = 0 count_other = 0 count_lowq = 0 print("unfiltered reads=", pileupcolumn.n, "filtered reads=", len(pileupcolumn.pileups), "difference= ", len(pileupcolumn.pileups) - pileupcolumn.n) for pileupread in pileupcolumn.pileups: if not pileupread.is_del and not pileupread.is_refskip: # query position is None if is_del or is_refskip is set. nuc = pileupread.alignment.query_sequence[pileupread.query_position] dcs_len.append(len(pileupread.alignment.query_sequence)) if nuc == alt: count_alt += 1 tag = pileupread.alignment.query_name if tag in tag_dict: tag_dict[tag][chrom_stop_pos] = alt else: tag_dict[tag] = {} tag_dict[tag][chrom_stop_pos] = alt elif nuc == ref: count_ref += 1 elif nuc == "N": count_n += 1 elif nuc == "lowQ": count_lowq += 1 else: count_other += 1 else: count_indel += 1 dcs_median = np.median(np.array(dcs_len)) cvrg_dict[chrom_stop_pos] = (count_ref, count_alt, dcs_median) print("coverage at pos %s = %s, ref = %s, alt = %s, other bases = %s, N = %s, indel = %s, low quality = %s, median length of DCS = %s\n" % (pileupcolumn.pos, count_ref + count_alt, count_ref, count_alt, count_other, count_n, count_indel, count_lowq, dcs_median)) bam.close() with open(json_file, "w") as f: json.dump((tag_dict, cvrg_dict), f) # create fastq from aligned reads with open(outfile, 'w') as out: with open(file3, 'r') as families: for line in families: line = line.rstrip('\n') splits = line.split('\t') tag = splits[0] if tag in tag_dict: str1 = splits[4] curr_seq = str1.replace("-", "") str2 = splits[5] curr_qual = str2.replace(" ", "") out.write("@" + splits[0] + "." + splits[1] + "." + splits[2] + "\n") out.write(curr_seq + "\n") out.write("+" + "\n") out.write(curr_qual + "\n") if __name__ == '__main__': sys.exit(mut2read(sys.argv))