Mercurial > repos > mheinzl > variant_analyzer2
view mut2read.py @ 21:b67d4c7da780 draft
planemo upload for repository https://github.com/Single-Molecule-Genetics/VariantAnalyzerGalaxy/tree/master/tools/variant_analyzer commit ee4a8e6cf290e6c8a4d55f9cd2839d60ab3b11c8
author | mheinzl |
---|---|
date | Mon, 22 Feb 2021 15:12:40 +0000 |
parents | 84a1a3f70407 |
children | d21960b45a6b |
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 2.0.0 2020-10-30 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 from cyvcf2 import VCF def make_argparser(): parser = argparse.ArgumentParser(description='Takes a vcf 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='VCF 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 dcs bam file bam = pysam.AlignmentFile(file2, "rb") # get tags tag_dict = {} cvrg_dict = {} for variant in VCF(file1): chrom = variant.CHROM stop_pos = variant.start #chrom_stop_pos = str(chrom) + "#" + str(stop_pos) ref = variant.REF alt = variant.ALT[0] chrom_stop_pos = str(chrom) + "#" + str(stop_pos) + "#" + ref + "#" + alt dcs_len = [] if len(ref) == len(alt): for pileupcolumn in bam.pileup(chrom, stop_pos - 1, stop_pos + 1, max_depth=100000000): if pileupcolumn.reference_pos == stop_pos: 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)) else: print("indels are currently not evaluated") 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))