allelefinder.py 9.13 KB
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#!/usr/bin/env python
"""
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Find true alleles in reference samples and detect possible
contaminations.
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In each sample, the sequences with the highest read counts of each
marker are called alleles, with a user-defined maximum number of alleles
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per marker.  The allele balance is kept within given bounds.  If the
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highest non-allelic sequence exceeds a given limit, no alleles are
called for this marker.  If this happens for multiple markers in one
sample, no alleles are called for this sample at all.
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"""
import argparse

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from ..lib import pos_int_arg, add_input_output_args, get_input_output_files, \
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                  ensure_sequence_format, get_sample_data, parse_library, \
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                  add_sequence_format_args
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__version__ = "0.1dev"


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# Default values for parameters are specified below.

# Default minimum number of reads required for the highest allele.
# This value can be overridden by the -n command line option.
_DEF_MIN_READS = 50

# Default minimum number of reads required for an allele to be called,
# as a percentage of the number of reads of the highest allele.
# This value can be overridden by the -m command line option.
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_DEF_MIN_ALLELE_PCT = 30.0
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# Default maximum amount of noise to allow, as a percentage of the
# number of reads of the highest allele of each marker.  If any noise
# (i.e., non-allelic sequences) above this threshold are detected, the
# sample is considered 'noisy' for this marker.
# This value can be overridden by the -M command line option.
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_DEF_MAX_NOISE_PCT = 10.0
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# Default maximum number of noisy markers allowed per sample.
# This value can be overridden by the -x command line option.
_DEF_MAX_NOISY = 2


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def find_alleles(samples_in, outfile, reportfile, min_reads, min_allele_pct,
                 max_noise_pct, max_alleles, max_noisy, stuttermark_column,
                 seqformat, library):
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    library = parse_library(library) if library is not None else {}
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    outfile.write("\t".join(["sample", "marker", "total", "allele"]) + "\n")
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    allelelist = {}
    get_sample_data(
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        samples_in,
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        lambda tag, data: find_alleles_sample(
            data if stuttermark_column is None
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                 else {key: data[key] for key in data if key[0] in
                       allelelist[tag]},
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            outfile, reportfile, tag, min_reads, min_allele_pct, max_noise_pct,
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            max_alleles, max_noisy, seqformat, library),
        allelelist,
        stuttermark_column)
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#find_alleles


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def find_alleles_sample(data, outfile, reportfile, tag, min_reads,
                        min_allele_pct, max_noise_pct, max_alleles, max_noisy,
                        seqformat, library):
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    top_noise = {}
    top_allele = {}
    alleles = {}
    for marker, allele in data:
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        reads = sum(data[marker, allele])
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        if marker not in alleles:
            alleles[marker] = {allele: reads}
            top_allele[marker] = reads
            top_noise[marker] = ["-", 0]
        else:
            if reads > top_allele[marker]:
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                # New highest allele!
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                top_allele[marker] = reads
                for allelex in alleles[marker].keys():
                    if (alleles[marker][allelex] <
                            top_allele[marker] * (min_allele_pct/100.)):
                        if alleles[marker][allelex] > top_noise[marker][1]:
                            top_noise[marker] = [
                                allelex, alleles[marker][allelex]]
                        del alleles[marker][allelex]
                alleles[marker][allele] = reads
            elif reads >= top_allele[marker]*(min_allele_pct/100.):
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                # New secundary allele!
                alleles[marker][allele] = reads
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            elif reads >= top_noise[marker][1]:
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                # New highest noise!
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                top_noise[marker] = [allele, reads]
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    # Find and eliminate noisy markers in this sample first.
    noisy_markers = 0
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    for marker in alleles:
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        if top_allele[marker] < min_reads:
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            reportfile.write(
                "Sample %s is not suitable for marker %s:\n"
                "highest allele has only %i reads\n\n" %
                    (tag, marker, top_allele[marker]))
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            alleles[marker] = {}
            continue
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        expect = get_max_expected_alleles(max_alleles, marker, library)
        if len(alleles[marker]) > expect:
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            allele_order = sorted(alleles[marker],
                                  key=lambda x: -alleles[marker][x])
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            top_noise[marker] = [allele_order[expect],
                alleles[marker][allele_order[expect]]]
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            alleles[marker] = {x: alleles[marker][x]
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                               for x in allele_order[:expect]}
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        if top_noise[marker][1] > top_allele[marker]*(max_noise_pct/100.):
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            reportfile.write(
                "Sample %s is not suitable for marker %s:\n"
                "highest non-allele is %.1f%% of the highest allele\n" %
                (tag, marker, 100.*top_noise[marker][1]/top_allele[marker]))
            for allele in sorted(alleles[marker],
                                 key=lambda x: -alleles[marker][x]):
                seq = allele if seqformat is None \
                    else ensure_sequence_format(allele, seqformat,
                        library=library, marker=marker)
                reportfile.write("%i\tALLELE\t%s\n" %
                    (alleles[marker][allele], seq))
            seq = top_noise[marker][0] if seqformat is None \
                else ensure_sequence_format(top_noise[marker][0],
                    seqformat, library=library, marker=marker)
            reportfile.write("%i\tNOISE\t%s\n\n" % (top_noise[marker][1], seq))
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            noisy_markers += 1
            alleles[marker] = {}

    # Drop this sample completely if it has too many noisy markers.
    if noisy_markers > max_noisy:
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        reportfile.write("Sample %s appears to be contaminated!\n\n" % tag)
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        return

    # The sample is OK, write out its alleles.
    for marker in alleles:
        for allele in sorted(alleles[marker],
                             key=lambda x: -alleles[marker][x]):
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            seq = allele if seqformat is None else ensure_sequence_format(
                allele, seqformat, library=library, marker=marker)
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            outfile.write("\t".join(
                [tag, marker, str(alleles[marker][allele]), seq]) + "\n")
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#find_alleles_sample
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def get_max_expected_alleles(max_alleles, marker, library):
    if max_alleles is not None:
        return max_alleles
    if "max_expected_copies" in library:
        return library["max_expected_copies"].get(marker, 2)
    return 2
#get_max_expected_alleles


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def add_arguments(parser):
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    add_input_output_args(parser, False, False, True)
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    filtergroup = parser.add_argument_group("filtering options")
    filtergroup.add_argument('-m', '--min-allele-pct', metavar="PCT",
        type=float, default=_DEF_MIN_ALLELE_PCT,
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        help="call heterozygous if the second allele is at least this "
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             "percentage of the highest allele of a marker "
             "(default: %(default)s)")
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    filtergroup.add_argument('-M', '--max-noise-pct', metavar="PCT",
        type=float, default=_DEF_MAX_NOISE_PCT,
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        help="a sample is considered contaminated/unsuitable for a marker if "
             "the highest non-allelic sequence is at least this percentage of "
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             "the highest allele of that marker (default: %(default)s)")
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    filtergroup.add_argument('-n', '--min-reads', metavar="N",
        type=pos_int_arg, default=_DEF_MIN_READS,
        help="require at least this number of reads for the highest allele "
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             "of each marker (default: %(default)s)")
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    filtergroup.add_argument('-a', '--max-alleles', metavar="N",
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        type=pos_int_arg,
        help="allow no more than this number of alleles per marker; if "
             "unspecified, the amounts given in the library file are used, "
             "which have a default value of 2")
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    filtergroup.add_argument('-x', '--max-noisy', metavar="N",
        type=pos_int_arg, default=_DEF_MAX_NOISY,
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        help="entirely reject a sample if more than this number of markers "
             "have a high non-allelic sequence (default: %(default)s)")
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    filtergroup.add_argument('-c', '--stuttermark-column', metavar="COLNAME",
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        help="name of column with Stuttermark output; if specified, sequences "
             "for which the value in this column does not start with ALLELE "
             "are ignored")
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    add_sequence_format_args(parser)
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#add_arguments


def run(args):
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    files = get_input_output_files(args)
    if not files:
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        raise ValueError("please specify an input file, or pipe in the output "
                         "of another program")
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    find_alleles(files[0], files[1], args.report, args.min_reads,
                 args.min_allele_pct, args.max_noise_pct, args.max_alleles,
                 args.max_noisy, args.stuttermark_column, args.sequence_format,
                 args.library)
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#run


def main():
    """
    Main entry point.
    """
    parser = argparse.ArgumentParser(
        description=__doc__)
    try:
        add_arguments(parser)
        run(parser.parse_args())
    except OSError as error:
        parser.error(error)
#main


if __name__ == "__main__":
    main()