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#! /usr/bin/env python
# This file is part of khmer, https://github.com/dib-lab/khmer/, and is
# Copyright (C) 2013-2015, Michigan State University.
# Copyright (C) 2015, The Regents of the University of California.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
#
# * Neither the name of the Michigan State University nor the names
# of its contributors may be used to endorse or promote products
# derived from this software without specific prior written
# permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
# Contact: khmer-project@idyll.org
# pylint: disable=missing-docstring,invalid-name
"""
Sequence trimming by abundance w/o countgraph.
Trim sequences at k-mers of the given abundance for the given file,
without loading a prebuilt countgraph. Output sequences will be
placed in 'infile.abundfilt'.
% python scripts/filter-abund-single.py <data>
Use '-h' for parameter help.
"""
from __future__ import print_function
import os
import sys
import khmer
import threading
import textwrap
from khmer.thread_utils import ThreadedSequenceProcessor, verbose_loader
from khmer import khmer_args
from khmer.khmer_args import (build_counting_args, report_on_config,
add_threading_args, info, calculate_graphsize,
sanitize_help)
from khmer.kfile import (check_input_files, check_space,
check_space_for_graph,
add_output_compression_type,
get_file_writer)
DEFAULT_CUTOFF = 2
def get_parser():
epilog = """\
Trimmed sequences will be placed in
``${input_sequence_filename}.abundfilt``.
This script is constant memory.
To trim reads based on k-mer abundance across multiple files, use
:program:`load-into-counting.py` and :program:`filter-abund.py`.
Example::
filter-abund-single.py -k 20 -x 5e7 -C 2 data/100k-filtered.fa
"""
parser = build_counting_args(
descr="Trims sequences at a minimum k-mer abundance "
"(in memory version).", epilog=textwrap.dedent(epilog))
add_threading_args(parser)
parser.add_argument('--cutoff', '-C', default=DEFAULT_CUTOFF, type=int,
help="Trim at k-mers below this abundance.")
parser.add_argument('--savegraph', metavar="filename", default='',
help="If present, the name of the file to save the "
"k-mer countgraph to")
parser.add_argument('datafile', metavar='input_sequence_filename',
help="FAST[AQ] sequence file to trim")
parser.add_argument('-f', '--force', default=False, action='store_true',
help='Overwrite output file if it exists')
add_output_compression_type(parser)
return parser
def main():
info('filter-abund-single.py', ['counting', 'SeqAn'])
args = sanitize_help(get_parser()).parse_args()
check_input_files(args.datafile, args.force)
check_space([args.datafile], args.force)
if args.savegraph:
tablesize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, tablesize, args.force)
report_on_config(args)
print('making countgraph', file=sys.stderr)
graph = khmer_args.create_countgraph(args)
# first, load reads into graph
rparser = khmer.ReadParser(args.datafile)
threads = []
print('consuming input, round 1 --', args.datafile, file=sys.stderr)
for _ in range(args.threads):
cur_thread = \
threading.Thread(
target=graph.consume_fasta_with_reads_parser,
args=(rparser, )
)
threads.append(cur_thread)
cur_thread.start()
for _ in threads:
_.join()
print('Total number of unique k-mers: {0}'.format(
graph.n_unique_kmers()), file=sys.stderr)
fp_rate = khmer.calc_expected_collisions(graph, args.force)
print('fp rate estimated to be %1.3f' % fp_rate, file=sys.stderr)
# now, trim.
# the filtering function.
def process_fn(record):
name = record.name
seq = record.sequence
seqN = seq.replace('N', 'A')
_, trim_at = graph.trim_on_abundance(seqN, args.cutoff)
if trim_at >= args.ksize:
# be sure to not to change the 'N's in the trimmed sequence -
# so, return 'seq' and not 'seqN'.
return name, seq[:trim_at]
return None, None
# the filtering loop
print('filtering', args.datafile, file=sys.stderr)
outfile = os.path.basename(args.datafile) + '.abundfilt'
outfile = open(outfile, 'wb')
outfp = get_file_writer(outfile, args.gzip, args.bzip)
tsp = ThreadedSequenceProcessor(process_fn)
tsp.start(verbose_loader(args.datafile), outfp)
print('output in', outfile.name, file=sys.stderr)
if args.savegraph:
print('Saving k-mer countgraph filename',
args.savegraph, file=sys.stderr)
graph.save(args.savegraph)
if __name__ == '__main__':
main()
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