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#! /usr/bin/env python
# This file is part of khmer, https://github.com/dib-lab/khmer/, and is
# Copyright (C) 2014-2015, 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=invalid-name,missing-docstring,no-member
"""
Estimate number of unique k-mers, with precision <= ERROR_RATE.
% python scripts/unique-kmers.py [ -k <k size> ] [ -e <ERROR_RATE> ] <data1>
<data2> ...
Use '-h' for parameter help.
"""
from __future__ import print_function
import argparse
import os
import sys
import textwrap
import khmer
from khmer.khmer_args import DEFAULT_K, sanitize_help, KhmerArgumentParser
from khmer.khmer_args import graphsize_args_report
def get_parser():
descr = "Estimate number of unique k-mers, with precision <= ERROR_RATE."
epilog = """\
A HyperLogLog counter is used to do cardinality estimation. Since this
counter is based on a tradeoff between precision and memory consumption,
the :option:`-e`/:option:`--error-rate` can be used to control how much
memory will be used. In practice the memory footprint is small even
at low error rates (< 0.01).
:option:`-k`/:option:`--ksize` should be set to the desired k-mer size.
Informational output is sent to STDERR, but a report file can be generated
with :option:`-R`/:option:`--report`.
:option:`--stream-records` will write the sequences taken in to STDOUT.
This is useful for workflows: count unique kmers in a stream, then do
digital normalization.
:option:`--diagnostics` will provide detailed options for tablesize
and memory limitations for various false positive rates. This is useful for
configuring other khmer scripts. This will be written to STDERR.
Example::
unique-kmers.py -k 17 tests/test-data/test-abund-read{,-2,-3}.fa
Example::
unique-kmers.py -k 17 --diagnostics tests/test-data/test-abund-read.fa
Example::
unique-kmers.py --stream-records -k 17 tests/test-data/test-reads.fa | \\
normalize-by-median.py -k 17 -o normalized /dev/stdin
Example::
unique-kmers.py -R unique_count -k 30 \\
tests/test-data/test-abund-read-paired.fa""" # noqa
parser = KhmerArgumentParser(
description=descr, epilog=textwrap.dedent(epilog),
citations=['SeqAn', 'hll'])
env_ksize = os.environ.get('KHMER_KSIZE', DEFAULT_K)
parser.add_argument('-q', '--quiet', dest='quiet', default=False,
action='store_true')
parser.add_argument('-k', '--ksize', type=int, default=env_ksize,
help='k-mer size to use')
parser.add_argument('-e', '--error-rate', type=float, default=0.01,
help='Acceptable error rate')
parser.add_argument('-R', '--report',
metavar='filename', type=argparse.FileType('w'),
help='generate informational report and write to'
' filename')
parser.add_argument('-S', '--stream-records', default=False,
action='store_true',
help='write input sequences to STDOUT')
parser.add_argument('--diagnostics', default=False, action='store_true',
help='print out recommended tablesize arguments and '
'restrictions')
parser.add_argument('input_filenames', metavar='input_sequence_filename',
help='Input FAST[AQ] sequence filename(s).', nargs='+')
return parser
def main():
args = sanitize_help(get_parser()).parse_args()
total_hll = khmer.HLLCounter(args.error_rate, args.ksize)
report_fp = args.report
input_filename = None
for _, input_filename in enumerate(args.input_filenames):
hllcpp = khmer.HLLCounter(args.error_rate, args.ksize)
hllcpp.consume_seqfile(input_filename,
stream_records=args.stream_records)
cardinality = hllcpp.estimate_cardinality()
print('Estimated number of unique {0}-mers in {1}: {2}'.format(
args.ksize, input_filename, cardinality), file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, '(total)', file=report_fp)
report_fp.flush()
total_hll.merge(hllcpp)
cardinality = total_hll.estimate_cardinality()
print('Total estimated number of unique {0}-mers: {1}'.format(
args.ksize, cardinality), file=sys.stderr)
to_print = graphsize_args_report(cardinality, args.error_rate)
if args.diagnostics:
print(to_print, file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, 'total', file=report_fp)
print(to_print, file=report_fp)
report_fp.flush()
if __name__ == "__main__":
main()
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