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Functionality to detect alignment bias
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -8,4 +8,5 @@ dependencies: | |
| - sh | ||
| - biopython | ||
| - scipy | ||
| - pysam | ||
| - mafft=7.305 | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,135 @@ | ||
| #!/usr/bin/env python3 | ||
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| import argparse | ||
| import pysam | ||
| from Bio import SeqIO, pairwise2 | ||
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| __author__ = "Susana Posada-Cespedes" | ||
| __license__ = "Apache2.0" | ||
| __maintainer__ = "Ivan Topolsky" | ||
| __email__ = "[email protected]" | ||
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| def parse_args(): | ||
| """ Set up the parsing of command-line arguments """ | ||
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| parser = argparse.ArgumentParser( | ||
| formatter_class=argparse.ArgumentDefaultsHelpFormatter) | ||
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| requiredNamed = parser.add_argument_group('required named arguments') | ||
| requiredNamed.add_argument( | ||
| "-r", required=True, default=None, metavar='FASTA', | ||
| dest='reference_file', type=str, help="Referene sequence" | ||
| ) | ||
| requiredNamed.add_argument( | ||
| "-b", required=True, default=None, metavar='BAM', dest='bamfile', | ||
| help="BAM file" | ||
| ) | ||
| requiredNamed.add_argument( | ||
| "-f", required=True, default=None, metavar='FASTQ', dest='fastq_file', | ||
| help="FASTQ file containing reads after QC" | ||
| ) | ||
| requiredNamed.add_argument( | ||
| "--hap", required=True, default=None, metavar='FASTA', | ||
| dest='haplotype_seqs', help="FASTA file containing haplotype sequences" | ||
| ) | ||
| requiredNamed.add_argument( | ||
| "-N", required=False, default='sample', metavar='STR', | ||
| dest='sampleID', help="Patient/sample identifiers" | ||
| ) | ||
| parser.add_argument( | ||
| "-p", required=False, default=False, action='store_true', | ||
| dest='paired', help="Indicate whether to simulate paired-end reads" | ||
| ) | ||
| parser.add_argument( | ||
| "-o", required=False, default='alignment_bias.tsv', metavar='FILENAME', | ||
| dest='output_file', type=str, | ||
| help="Output file" | ||
| ) | ||
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| return parser.parse_args() | ||
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| def hamming_dist(s1, s2): | ||
| """Return the Hamming distance between sequences""" | ||
| assert len(s1) == len(s2), ("Hamming distance is undefined for sequences " | ||
| "differing in their lengths") | ||
| return sum(el1 != el2 for el1, el2 in zip(s1, s2)) | ||
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| def main(): | ||
| args = parse_args() | ||
| reference = SeqIO.read(args.reference_file, "fasta") | ||
| reference_len = len(reference) | ||
| start = None | ||
| end = None | ||
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| hap_cnt = {} | ||
| hap_coverage = {} | ||
| with pysam.AlignmentFile(args.bamfile, 'rb') as alnfile: | ||
| for read in alnfile.fetch(reference=reference.id, start=start, end=end): | ||
| query_name = read.query_name | ||
| hapID = query_name.split('-')[0] | ||
| if hapID in hap_cnt: | ||
| hap_cnt[hapID] += 1 | ||
| else: | ||
| hap_cnt[hapID] = 1 | ||
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| # Get the percent of aligned bases per read | ||
| cigar_arr = read.get_cigar_stats()[0] | ||
| aux = (cigar_arr[0] + cigar_arr[1]) | ||
| assert aux == read.query_alignment_length | ||
| percent_aligned = read.query_alignment_length / read.infer_read_length() | ||
| assert percent_aligned <= 1, f"{cigar_arr}" | ||
| if hapID in hap_coverage: | ||
| hap_coverage[hapID] += percent_aligned | ||
| else: | ||
| hap_coverage[hapID] = percent_aligned | ||
|
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| for k, v in hap_cnt.items(): | ||
| aux = hap_coverage[k] / v | ||
| assert aux <= 1, f"{aux}" | ||
| hap_coverage[k] = aux | ||
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| # Parse FASTQ file to compute the expected number of reads per haplotype | ||
| hap_expected = {} | ||
| total = 0 | ||
| for read in SeqIO.parse(args.fastq_file, "fastq"): | ||
| total += 1 | ||
| hapID = read.id.split('-')[0] | ||
| if hapID in hap_expected: | ||
| hap_expected[hapID] += 1 | ||
| else: | ||
| hap_expected[hapID] = 1 | ||
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| percent_aligned = {} | ||
| for k, v in hap_expected.items(): | ||
| if k in hap_cnt: | ||
| if args.paired: | ||
| percent_aligned[k] = hap_cnt[k] / (v * 2) | ||
| else: | ||
| percent_aligned[k] = hap_cnt[k] / v | ||
| else: | ||
| percent_aligned[k] = 0 | ||
| hap_coverage[k] = 0 | ||
|
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| # Compute divergence from the reference sequence | ||
| divergence = {} | ||
| affine_pen = pairwise2.affine_penalty(-1, -0.1, True) | ||
| with open(args.haplotype_seqs, 'r') as infile: | ||
| for record in SeqIO.parse(infile, 'fasta'): | ||
| alignment = pairwise2.align.globalmc(reference.seq, record.seq, 1, 0, | ||
| affine_pen, affine_pen, | ||
| one_alignment_only=True) | ||
| divergence[record.id] = hamming_dist(alignment[0][0], | ||
| alignment[0][1]) / alignment[0][4] | ||
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| with open(args.output_file, 'w') as outfile: | ||
| outfile.write("SampleID\tHaplotypeID\tDivergence\tPercent-aligned\t" | ||
| "Percent-bases-aligned\n") | ||
| for k, v in percent_aligned.items(): | ||
| outfile.write(f"{args.sampleID}\t{k}\t{divergence[k]}\t{v}\t" | ||
| f"{hap_coverage[k]}\n") | ||
|
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||
| if __name__ == '__main__': | ||
| main() |
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