sweep-reads3.py

#! /usr/bin/env python
# This file is part of khmer, https://github.com/dib-lab/khmer/, and is
# Copyright (C) 2012-2015, Michigan State University.
# Copyright (C) 2015, The Regents of the University of California.
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# Contact: khmer-project@idyll.org
"""
Use a set of query reads to sweep out overlapping reads from multiple files.

% python scripts/sweep-reads3.py <query1> [ <query2> ... ] <search reads>

Results end up in <search reads>.sweep3.

Use '-h' for parameter help.
"""

import sys
import os.path
import screed
import khmer
from khmer.khmer_args import (build_nodegraph_args, DEFAULT_MAX_TABLESIZE)


def output_single(r):
    if hasattr(r, 'quality'):
        return "@%s\n%s\n+\n%s\n" % (r.name, r.sequence, r.quality)
    else:
        return ">%s\n%s\n" % (r.name, r.sequence)


def main():
    parser = build_construct_args()
    parser.add_argument('input_filenames', nargs='+')
    parser.add_argument('read_filename')

    args = parser.parse_args()

    if not args.quiet:
        if args.min_hashsize == DEFAULT_MAX_TABLESIZE:
            print("** WARNING: hashsize is default!  " \
                "You absodefly want to increase this!\n** " \
                "Please read the docs!", file=sys.stderr)

        print('\nPARAMETERS:', file=sys.stderr)
        print(' - kmer size =    %d \t\t(-k)' % args.ksize, file=sys.stderr)
        print(' - n hashes =     %d \t\t(-N)' % args.n_hashes, file=sys.stderr)
        print(' - min hashsize = %-5.2g \t(-x)' % \
            args.min_hashsize, file=sys.stderr)
        print('', file=sys.stderr)
        print('Estimated memory usage is %.2g bytes ' \
            '(n_hashes x min_hashsize / 8)' % (
                args.n_hashes * args.min_hashsize * len(args.input_filenames) / 8.), file=sys.stderr)
        print('-' * 8, file=sys.stderr)

    K = args.ksize
    HT_SIZE = args.min_hashsize
    N_HT = args.n_hashes

    inputlist = args.input_filenames
    readsfile = args.read_filename

    query_list = []
    for n, inp_name in enumerate(inputlist):
        # create a nodegraph data structure
        ht = khmer.Nodegraph(K, HT_SIZE, N_HT)

        outfile = os.path.basename(inp_name) + '.sweep3'
        outfp = open(outfile, 'w')
        query_list.append((ht, outfp))

    for n, inp_name in enumerate(inputlist):
        ht = query_list[n][0]

        # load contigs, connect into N partitions
        print('loading input reads from', inp_name)
        ht.consume_seqfile(inp_name)

    print('starting sweep.')

    n = 0
    m = 0
    for n, record in enumerate(screed.open(readsfile)):
        if len(record.sequence) < K:
            continue

        if n % 10000 == 0:
            print('...', n, m)

        for ht, outfp in query_list:
            count = ht.get_median_count(record.sequence)[0]
            if count:
                outfp.write(output_single(record))

if __name__ == '__main__':
    main()

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