def get_parser():
epilog = """
The output is one file for each input file, <input file>.abundtrim, placed
in the current directory. This output contains the input sequences
trimmed at low-abundance k-mers.
The ``-V/--variable-coverage`` parameter will, if specified,
prevent elimination of low-abundance reads by only trimming
low-abundance k-mers from high-abundance reads; use this for
non-genomic data sets that may have variable coverage.
Note that the output reads will not necessarily be in the same order
as the reads in the input files; if this is an important consideration,
use ``load-into-counting.py`` and ``filter-abund.py``. However, read
pairs will be kept together, in "broken-paired" format; you can use
``extract-paired-reads.py`` to extract read pairs and orphans.
Example::
trim-low-abund.py -x 5e7 -k 20 -C 2 data/100k-filtered.fa
"""
parser = build_counting_args(
descr='Trim low-abundance k-mers using a streaming algorithm.',
epilog=textwrap.dedent(epilog))
parser.add_argument('input_filenames', nargs='+')
parser.add_argument('--cutoff', '-C', type=int,
help='remove k-mers below this abundance',
default=DEFAULT_CUTOFF)
parser.add_argument('--normalize-to', '-Z', type=int,
help='base cutoff on this median k-mer abundance',
default=DEFAULT_NORMALIZE_LIMIT)
parser.add_argument('-o', '--out', metavar="filename",
type=argparse.FileType('w'),
default=None, help='only output a single file with '
'the specified filename; use a single dash "-" to '
'specify that output should go to STDOUT (the '
'terminal)')
parser.add_argument('--variable-coverage', '-V', action='store_true',
default=False,
help='Only trim low-abundance k-mers from sequences '
'that have high coverage.')
add_loadhash_args(parser)
parser.add_argument('-s', '--savetable', metavar="filename", default='',
help='save the k-mer counting table to disk after all'
'reads are loaded.')
# expert options
parser.add_argument('--force', default=False, action='store_true')
parser.add_argument('--ignore-pairs', default=False, action='store_true')
parser.add_argument('--tempdir', '-T', type=str, default='./')
return parser
def main():
parser = build_counting_args()
parser.add_argument("--trusted-cov",
dest="trusted_cov",
type=int,
default=2)
parser.add_argument("--theta", type=float, default=1.0)
parser.add_argument("input_table")
parser.add_argument("input_filenames", nargs="+")
add_loadhash_args(parser)
args = parser.parse_args()
counting_ht = args.input_table
infiles = args.input_filenames
print >> sys.stderr, 'file with ht: %s' % counting_ht
print >> sys.stderr, 'loading hashtable'
ht = khmer.load_counting_hash(counting_ht)
K = ht.ksize()
aligner = khmer.new_readaligner(
ht, args.trusted_cov, args.theta
) # counting hash, trusted kmer coverage cutoff, bits theta (threshold value for terminating unproductive alignemnts)
### the filtering loop
for infile in infiles:
print >> sys.stderr, 'aligning', infile
for n, record in enumerate(screed.open(infile)):
name = record['name']
seq = record['sequence'].upper()
print >> sys.stderr, name
print >> sys.stderr, seq
score, graph_alignment, read_alignment, truncated = aligner.align(
seq)
print >> sys.stderr, score
print >> sys.stderr, graph_alignment
print >> sys.stderr, read_alignment
print >> sys.stderr, truncated
print ">{0}\n{1}".format(name, graph_alignment)
def main():
parser = build_counting_args()
parser.add_argument("--trusted-cov", dest="trusted_cov", type=int, default=2)
parser.add_argument("--theta", type=float, default=1.0)
parser.add_argument("input_table")
parser.add_argument("input_filenames", nargs="+")
add_loadhash_args(parser)
args = parser.parse_args()
counting_ht = args.input_table
infiles = args.input_filenames
print >>sys.stderr, 'file with ht: %s' % counting_ht
print >>sys.stderr, 'loading hashtable'
ht = khmer.load_counting_hash(counting_ht)
K = ht.ksize()
aligner = khmer.new_readaligner(ht, args.trusted_cov, args.theta) # counting hash, trusted kmer coverage cutoff, bits theta (threshold value for terminating unproductive alignemnts)
### the filtering loop
for infile in infiles:
print >>sys.stderr, 'aligning', infile
for n, record in enumerate(screed.open(infile)):
name = record['name']
seq = record['sequence'].upper()
print >>sys.stderr, name
print >>sys.stderr, seq
score, graph_alignment, read_alignment, truncated = aligner.align(seq)
print >>sys.stderr, score
print >>sys.stderr, graph_alignment
print >>sys.stderr, read_alignment
print >>sys.stderr, truncated
print ">{0}\n{1}".format(name, graph_alignment)
def get_parser():
epilog = ("""
Discard sequences based on whether or not their median k-mer abundance lies
above a specified cutoff. Kept sequences will be placed in <fileN>.keep.
Paired end reads will be considered together if :option:`-p` is set. If
either read will be kept, then both will be kept. This should result in
keeping (or discarding) each sequencing fragment. This helps with retention
of repeats, especially.
With :option:`-s`/:option:`--savetable`, the k-mer counting table
will be saved to the specified file after all sequences have been
processed. With :option:`-d`, the k-mer counting table will be
saved every d files for multifile runs; if :option:`-s` is set,
the specified name will be used, and if not, the name `backup.ct`
will be used. :option:`-l`/:option:`--loadtable` will load the
specified k-mer counting table before processing the specified
files. Note that these tables are are in the same format as those
produced by :program:`load-into-counting.py` and consumed by
:program:`abundance-dist.py`.
:option:`-f`/:option:`--fault-tolerant` will force the program to continue
upon encountering a formatting error in a sequence file; the k-mer counting
table up to that point will be dumped, and processing will continue on the
next file.
Example::
normalize-by-median.py -k 17 tests/test-data/test-abund-read-2.fa
Example::
""" " normalize-by-median.py -p -k 17 tests/test-data/test-abund-read-paired.fa" # noqa
"""
Example::
""" " normalize-by-median.py -k 17 -f tests/test-data/test-error-reads.fq tests/test-data/test-fastq-reads.fq" # noqa
"""
Example::
""" " normalize-by-median.py -k 17 -d 2 -s test.ct tests/test-data/test-abund-read-2.fa tests/test-data/test-fastq-reads") # noqa
parser = build_counting_args(
descr="Do digital normalization (remove mostly redundant sequences)",
epilog=textwrap.dedent(epilog))
parser.add_argument('-C', '--cutoff', type=int,
default=DEFAULT_DESIRED_COVERAGE)
parser.add_argument('-p', '--paired', action='store_true')
parser.add_argument('-s', '--savetable', metavar="filename", default='')
parser.add_argument('-R', '--report',
metavar='filename', type=argparse.FileType('w'))
parser.add_argument('-f', '--fault-tolerant', dest='force',
help='continue on next file if read errors are \
encountered', action='store_true')
parser.add_argument('--save-on-failure', dest='fail_save',
action='store_false', default=True,
help='Save k-mer counting table when an error occurs')
parser.add_argument('-d', '--dump-frequency', dest='dump_frequency',
type=int, help='dump k-mer counting table every d '
'files', default=-1)
parser.add_argument('-o', '--out', metavar="filename",
dest='single_output_filename',
default='', help='only output a single'
' file with the specified filename')
parser.add_argument('input_filenames', metavar='input_sequence_filename',
help='Input FAST[AQ] sequence filename.', nargs='+')
parser.add_argument('--report-total-kmers', '-t', action='store_true',
help="Prints the total number of k-mers"
" post-normalization to stderr")
parser.add_argument('--force', default=False, action='store_true',
help='Overwrite output file if it exists')
add_loadhash_args(parser)
return parser
def get_parser():
epilog = (
"""
Discard sequences based on whether or not their median k-mer abundance lies
above a specified cutoff. Kept sequences will be placed in <fileN>.keep.
Paired end reads will be considered together if :option:`-p` is set. If
either read will be kept, then both will be kept. This should result in
keeping (or discarding) each sequencing fragment. This helps with retention
of repeats, especially.
With :option:`-s`/:option:`--savetable`, the k-mer counting table
will be saved to the specified file after all sequences have been
processed. With :option:`-d`, the k-mer counting table will be
saved every d files for multifile runs; if :option:`-s` is set,
the specified name will be used, and if not, the name `backup.ct`
will be used. :option:`-l`/:option:`--loadtable` will load the
specified k-mer counting table before processing the specified
files. Note that these tables are are in the same format as those
produced by :program:`load-into-counting.py` and consumed by
:program:`abundance-dist.py`.
:option:`-f`/:option:`--fault-tolerant` will force the program to continue
upon encountering a formatting error in a sequence file; the k-mer counting
table up to that point will be dumped, and processing will continue on the
next file.
Example::
saturate-by-median.py -k 17 tests/test-data/test-abund-read-2.fa
Example::
"""
" saturate-by-median.py -p -k 17 tests/test-data/test-abund-read-paired.fa" # noqa
"""
Example::
"""
" saturate-by-median.py -k 17 -f tests/test-data/test-error-reads.fq tests/test-data/test-fastq-reads.fq" # noqa
"""
Example::
"""
" saturate-by-median.py -k 17 -d 2 -s test.ct tests/test-data/test-abund-read-2.fa tests/test-data/test-fastq-reads"
) # noqa
parser = build_counting_args(
descr="Do digital normalization (remove mostly redundant sequences)",
epilog=textwrap.dedent(epilog))
parser.add_argument('-C',
'--cutoff',
type=int,
default=DEFAULT_DESIRED_COVERAGE)
parser.add_argument('-p', '--paired', action='store_true')
parser.add_argument('-s', '--savetable', metavar="filename", default='')
parser.add_argument('-R',
'--report',
metavar='filename',
type=argparse.FileType('w'))
parser.add_argument('--report-frequency',
metavar='report_frequency',
default=100000,
type=int)
parser.add_argument('-f',
'--fault-tolerant',
dest='force',
help='continue on next file if read errors are \
encountered',
action='store_true')
parser.add_argument('-o',
'--out',
metavar="filename",
dest='single_output_filename',
default='',
help='only output a single'
' file with the specified filename')
parser.add_argument('input_filenames',
metavar='input_sequence_filename',
help='Input FAST[AQ] sequence filename.',
nargs='+')
add_loadhash_args(parser)
return parser
def get_parser():
epilog = """
The output is one file for each input file, <input file>.abundtrim, placed
in the current directory. This output contains the input sequences
trimmed at low-abundance k-mers.
The ``-V/--variable-coverage`` parameter will, if specified,
prevent elimination of low-abundance reads by only trimming
low-abundance k-mers from high-abundance reads; use this for
non-genomic data sets that may have variable coverage.
Note that the output reads will not necessarily be in the same order
as the reads in the input files; if this is an important consideration,
use ``load-into-counting.py`` and ``filter-abund.py``. However, read
pairs will be kept together, in "broken-paired" format; you can use
``extract-paired-reads.py`` to extract read pairs and orphans.
Example::
trim-low-abund.py -x 5e7 -k 20 -C 2 data/100k-filtered.fa
"""
parser = build_counting_args(
descr='Trim low-abundance k-mers using a streaming algorithm.',
epilog=textwrap.dedent(epilog))
parser.add_argument('input_filenames', nargs='+')
parser.add_argument('--cutoff',
'-C',
type=int,
help='remove k-mers below this abundance',
default=DEFAULT_CUTOFF)
parser.add_argument('--normalize-to',
'-Z',
type=int,
help='base cutoff on this median k-mer abundance',
default=DEFAULT_NORMALIZE_LIMIT)
parser.add_argument('-o',
'--out',
metavar="filename",
type=argparse.FileType('w'),
default=None,
help='only output a single file with '
'the specified filename; use a single dash "-" to '
'specify that output should go to STDOUT (the '
'terminal)')
parser.add_argument('--variable-coverage',
'-V',
action='store_true',
default=False,
help='Only trim low-abundance k-mers from sequences '
'that have high coverage.')
add_loadhash_args(parser)
parser.add_argument('-s',
'--savetable',
metavar="filename",
default='',
help='save the k-mer counting table to disk after all'
'reads are loaded.')
# expert options
parser.add_argument('--force', default=False, action='store_true')
parser.add_argument('--ignore-pairs', default=False, action='store_true')
parser.add_argument('--tempdir', '-T', type=str, default='./')
return parser
def get_parser():
epilog = ("""
Discard sequences based on whether or not their median k-mer abundance lies
above a specified cutoff. Kept sequences will be placed in <fileN>.keep.
By default, paired end reads will be considered together; if
either read should be kept, both will be kept. (This keeps both
reads from a fragment, and helps with retention of repeats.)
Unpaired reads are treated individually.
If :option:`-p`/`--paired` is set, then proper pairing is required
and the script will exit on unpaired reads, although
:option:`--unpaired-reads` can be used to supply a file of orphan
reads to be read after the paired reads.
:option:`--force-single` will ignore all pairing information and treat
reads individually.
With :option:`-s`/:option:`--savetable`, the k-mer counting table
will be saved to the specified file after all sequences have been
processed. With :option:`-d`, the k-mer counting table will be
saved every d files for multifile runs; if :option:`-s` is set,
the specified name will be used, and if not, the name `backup.ct`
will be used. :option:`-l`/:option:`--loadtable` will load the
specified k-mer counting table before processing the specified
files. Note that these tables are are in the same format as those
produced by :program:`load-into-counting.py` and consumed by
:program:`abundance-dist.py`.
To append reads to an output file (rather than overwriting it), send output
to STDOUT with `--out -` and use UNIX file redirection syntax (`>>`) to
append to the file.
Example::
normalize-by-median.py -k 17 tests/test-data/test-abund-read-2.fa
Example::
""" " normalize-by-median.py -p -k 17 tests/test-data/test-abund-read-paired.fa" # noqa
"""
Example::
""" " normalize-by-median.py -p -k 17 -o - tests/test-data/paired.fq >> appended-output.fq" # noqa
"""
Example::
""" " normalize-by-median.py -k 17 -f tests/test-data/test-error-reads.fq tests/test-data/test-fastq-reads.fq" # noqa
"""
Example::
""" " normalize-by-median.py -k 17 -d 2 -s test.ct tests/test-data/test-abund-read-2.fa tests/test-data/test-fastq-reads") # noqa
parser = build_counting_args(
descr="Do digital normalization (remove mostly redundant sequences)",
epilog=textwrap.dedent(epilog))
parser.add_argument('-C', '--cutoff', type=int,
default=DEFAULT_DESIRED_COVERAGE)
parser.add_argument('-p', '--paired', action='store_true',
help='require that all sequences be properly paired')
parser.add_argument('--force-single', dest='force_single',
action='store_true',
help='treat all sequences as single-ended/unpaired')
parser.add_argument('-u', '--unpaired-reads',
metavar="unpaired_reads_filename",
help='include a file of unpaired reads to which '
'-p/--paired does not apply.')
parser.add_argument('-s', '--savetable', metavar="filename", default='',
help='save the k-mer counting table to disk after all'
'reads are loaded.')
parser.add_argument('-R', '--report',
metavar='filename', type=argparse.FileType('w'))
parser.add_argument('-f', '--force', dest='force',
help='continue on next file if read errors are \
encountered', action='store_true')
parser.add_argument('-o', '--out', metavar="filename",
dest='single_output_file',
type=argparse.FileType('w'),
default=None, help='only output a single file with '
'the specified filename; use a single dash "-" to '
'specify that output should go to STDOUT (the '
'terminal)')
parser.add_argument('input_filenames', metavar='input_sequence_filename',
help='Input FAST[AQ] sequence filename.', nargs='+')
add_loadhash_args(parser)
return parser
def get_parser():
epilog = (
"""
Discard sequences based on whether or not their median k-mer abundance lies
above a specified cutoff. Kept sequences will be placed in <fileN>.keep.
By default, paired end reads will be considered together; if
either read should be kept, both will be kept. (This keeps both
reads from a fragment, and helps with retention of repeats.)
Unpaired reads are treated individually.
If :option:`-p`/`--paired` is set, then proper pairing is required
and the script will exit on unpaired reads, although
:option:`--unpaired-reads` can be used to supply a file of orphan
reads to be read after the paired reads.
:option:`--force-single` will ignore all pairing information and treat
reads individually.
With :option:`-s`/:option:`--savetable`, the k-mer counting table
will be saved to the specified file after all sequences have been
processed. With :option:`-d`, the k-mer counting table will be
saved every d files for multifile runs; if :option:`-s` is set,
the specified name will be used, and if not, the name `backup.ct`
will be used. :option:`-l`/:option:`--loadtable` will load the
specified k-mer counting table before processing the specified
files. Note that these tables are are in the same format as those
produced by :program:`load-into-counting.py` and consumed by
:program:`abundance-dist.py`.
To append reads to an output file (rather than overwriting it), send output
to STDOUT with `--out -` and use UNIX file redirection syntax (`>>`) to
append to the file.
Example::
normalize-by-median.py -k 17 tests/test-data/test-abund-read-2.fa
Example::
"""
" normalize-by-median.py -p -k 17 tests/test-data/test-abund-read-paired.fa" # noqa
"""
Example::
"""
" normalize-by-median.py -p -k 17 -o - tests/test-data/paired.fq >> appended-output.fq" # noqa
"""
Example::
"""
" normalize-by-median.py -k 17 -f tests/test-data/test-error-reads.fq tests/test-data/test-fastq-reads.fq" # noqa
"""
Example::
"""
" normalize-by-median.py -k 17 -d 2 -s test.ct tests/test-data/test-abund-read-2.fa tests/test-data/test-fastq-reads"
) # noqa
parser = build_counting_args(
descr="Do digital normalization (remove mostly redundant sequences)",
epilog=textwrap.dedent(epilog))
parser.add_argument('-C',
'--cutoff',
type=int,
default=DEFAULT_DESIRED_COVERAGE)
parser.add_argument('-p',
'--paired',
action='store_true',
help='require that all sequences be properly paired')
parser.add_argument('--force-single',
dest='force_single',
action='store_true',
help='treat all sequences as single-ended/unpaired')
parser.add_argument('-u',
'--unpaired-reads',
metavar="unpaired_reads_filename",
help='include a file of unpaired reads to which '
'-p/--paired does not apply.')
parser.add_argument('-s',
'--savetable',
metavar="filename",
default='',
help='save the k-mer counting table to disk after all'
'reads are loaded.')
parser.add_argument('-R',
'--report',
metavar='filename',
type=argparse.FileType('w'))
parser.add_argument('-f',
'--force',
dest='force',
help='continue on next file if read errors are \
encountered',
action='store_true')
parser.add_argument('-o',
'--out',
metavar="filename",
dest='single_output_file',
type=argparse.FileType('w'),
default=None,
help='only output a single file with '
'the specified filename; use a single dash "-" to '
'specify that output should go to STDOUT (the '
'terminal)')
parser.add_argument('input_filenames',
metavar='input_sequence_filename',
help='Input FAST[AQ] sequence filename.',
nargs='+')
add_loadhash_args(parser)
return parser
def get_parser():
epilog = (
"""
Discard sequences based on whether or not their median k-mer abundance lies
above a specified cutoff. Kept sequences will be placed in <fileN>.keep.
Paired end reads will be considered together if :option:`-p` is set. If
either read will be kept, then both will be kept. This should result in
keeping (or discarding) each sequencing fragment. This helps with retention
of repeats, especially. With :option: `-u`/:option:`--unpaired-reads`,
unpaired reads from the specified file will be read after the paired data
is read.
With :option:`-s`/:option:`--savetable`, the k-mer counting table
will be saved to the specified file after all sequences have been
processed. With :option:`-d`, the k-mer counting table will be
saved every d files for multifile runs; if :option:`-s` is set,
the specified name will be used, and if not, the name `backup.ct`
will be used. :option:`-l`/:option:`--loadtable` will load the
specified k-mer counting table before processing the specified
files. Note that these tables are are in the same format as those
produced by :program:`load-into-counting.py` and consumed by
:program:`abundance-dist.py`.
:option:`-f`/:option:`--fault-tolerant` will force the program to continue
upon encountering a formatting error in a sequence file; the k-mer counting
table up to that point will be dumped, and processing will continue on the
next file.
To append reads to an output file (rather than overwriting it), send output
to STDOUT with `--out -` and use UNIX file redirection syntax (`>>`) to
append to the file.
Example::
normalize-by-median.py -k 17 tests/test-data/test-abund-read-2.fa
Example::
"""
" normalize-by-median.py -p -k 17 tests/test-data/test-abund-read-paired.fa" # noqa
"""
Example::
"""
" normalize-by-median.py -p -k 17 -o - tests/test-data/paired.fq >> appended-output.fq" # noqa
"""
Example::
"""
" normalize-by-median.py -k 17 -f tests/test-data/test-error-reads.fq tests/test-data/test-fastq-reads.fq" # noqa
"""
Example::
"""
" normalize-by-median.py -k 17 -d 2 -s test.ct tests/test-data/test-abund-read-2.fa tests/test-data/test-fastq-reads"
) # noqa
parser = build_counting_args(
descr="Do digital normalization (remove mostly redundant sequences)",
epilog=textwrap.dedent(epilog))
parser.add_argument('-C',
'--cutoff',
type=int,
default=DEFAULT_DESIRED_COVERAGE)
parser.add_argument('-p', '--paired', action='store_true')
parser.add_argument('-u',
'--unpaired-reads',
metavar="unpaired_reads_filename",
help='with paired data only,\
include an unpaired file')
parser.add_argument('-s',
'--savetable',
metavar="filename",
default='',
help='save the k-mer counting table to disk after all'
'reads are loaded.')
parser.add_argument('-R',
'--report',
metavar='filename',
type=argparse.FileType('w'))
parser.add_argument('-f',
'--fault-tolerant',
dest='force',
help='continue on next file if read errors are \
encountered',
action='store_true')
parser.add_argument('--save-on-failure',
dest='fail_save',
action='store_false',
default=True,
help='Save k-mer counting table when an error occurs')
parser.add_argument('-d',
'--dump-frequency',
dest='dump_frequency',
type=int,
help='dump k-mer counting table every d '
'files',
default=-1)
parser.add_argument('-o',
'--out',
metavar="filename",
dest='single_output_file',
type=argparse.FileType('w'),
default=None,
help='only output a single file with '
'the specified filename; use a single dash "-" to '
'specify that output should go to STDOUT (the '
'terminal)')
parser.add_argument('input_filenames',
metavar='input_sequence_filename',
help='Input FAST[AQ] sequence filename.',
nargs='+')
parser.add_argument('--report-total-kmers',
'-t',
action='store_true',
help="Prints the total number of k-mers"
" post-normalization to stderr")
parser.add_argument('--force',
default=False,
action='store_true',
help='Overwrite output file if it exists')
add_loadhash_args(parser)
return parser
def get_parser():
epilog = (
"""
Discard sequences based on whether or not their median k-mer abundance lies
above a specified cutoff. Kept sequences will be placed in <fileN>.keep.
Paired end reads will be considered together if :option:`-p` is set. If
either read will be kept, then both will be kept. This should result in
keeping (or discarding) each sequencing fragment. This helps with retention
of repeats, especially.
With :option:`-s`/:option:`--savetable`, the k-mer counting table
will be saved to the specified file after all sequences have been
processed. With :option:`-d`, the k-mer counting table will be
saved every d files for multifile runs; if :option:`-s` is set,
the specified name will be used, and if not, the name `backup.ct`
will be used. :option:`-l`/:option:`--loadtable` will load the
specified k-mer counting table before processing the specified
files. Note that these tables are are in the same format as those
produced by :program:`load-into-counting.py` and consumed by
:program:`abundance-dist.py`.
:option:`-f`/:option:`--fault-tolerant` will force the program to continue
upon encountering a formatting error in a sequence file; the k-mer counting
table up to that point will be dumped, and processing will continue on the
next file.
Example::
saturate-by-median.py -k 17 tests/test-data/test-abund-read-2.fa
Example::
"""
" saturate-by-median.py -p -k 17 tests/test-data/test-abund-read-paired.fa" # noqa
"""
Example::
"""
" saturate-by-median.py -k 17 -f tests/test-data/test-error-reads.fq tests/test-data/test-fastq-reads.fq" # noqa
"""
Example::
"""
" saturate-by-median.py -k 17 -d 2 -s test.ct tests/test-data/test-abund-read-2.fa tests/test-data/test-fastq-reads"
) # noqa
parser = build_counting_args(
descr="Do digital normalization (remove mostly redundant sequences)", epilog=textwrap.dedent(epilog)
)
parser.add_argument("-C", "--cutoff", type=int, default=DEFAULT_DESIRED_COVERAGE)
parser.add_argument("-p", "--paired", action="store_true")
parser.add_argument("-s", "--savetable", metavar="filename", default="")
parser.add_argument("-R", "--report", metavar="filename", type=argparse.FileType("w"))
parser.add_argument("--report-frequency", metavar="report_frequency", default=100000, type=int)
parser.add_argument(
"-f",
"--fault-tolerant",
dest="force",
help="continue on next file if read errors are \
encountered",
action="store_true",
)
parser.add_argument(
"-o",
"--out",
metavar="filename",
dest="single_output_filename",
default="",
help="only output a single" " file with the specified filename",
)
parser.add_argument(
"input_filenames", metavar="input_sequence_filename", help="Input FAST[AQ] sequence filename.", nargs="+"
)
add_loadhash_args(parser)
return parser
