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# DEPRECATE AND REMOVE ME IN THE FUTURE
import sys
import argparse
import operator
import itertools
import warnings
import traceback
import os.path
import multiprocessing
import numpy as np
import pysam
import random
import HTSeq
from HTSeq.scripts.utils import (
UnknownChrom,
my_showwarning,
invert_strand,
_write_output,
)
def count_reads_single_file(
isam,
sam_filename,
features,
feature_attr,
order,
max_buffer_size,
stranded,
overlap_mode,
multimapped_mode,
secondary_alignment_mode,
supplementary_alignment_mode,
feature_type,
id_attribute,
additional_attributes,
quiet,
minaqual,
samout_format,
samout_filename,
):
def write_to_samout(r, assignment, samoutfile, template=None):
if samoutfile is None:
return
if not pe_mode:
r = (r,)
for read in r:
if read is not None:
read.optional_fields.append(('XF', assignment))
if template is not None:
samoutfile.write(read.to_pysam_AlignedSegment(template))
elif samout_format in ('SAM', 'sam'):
samoutfile.write(read.get_sam_line() + "\n")
else:
raise ValueError(
'BAM/SAM output: no template and not a test SAM file',
)
try:
if sam_filename == "-":
read_seq_file = HTSeq.BAM_Reader(sys.stdin)
else:
read_seq_file = HTSeq.BAM_Reader(sam_filename)
# Get template for output BAM/SAM if possible
if samout_filename is None:
template = None
samoutfile = None
elif samout_format in ('bam', 'BAM'):
template = read_seq_file.get_template()
samoutfile = pysam.AlignmentFile(
samout_filename, 'wb',
template=template,
)
elif (samout_format in ('sam', 'SAM')) and \
hasattr(read_seq_file, 'get_template'):
template = read_seq_file.get_template()
samoutfile = pysam.AlignmentFile(
samout_filename, 'w',
template=template,
)
else:
template = None
samoutfile = open(samout_filename, 'w')
read_seq_iter = iter(read_seq_file)
# Catch empty BAM files
try:
first_read = next(read_seq_iter)
pe_mode = first_read.paired_end
# FIXME: catchall can hide subtle bugs
except:
first_read = None
pe_mode = False
if first_read is not None:
read_seq = itertools.chain([first_read], read_seq_iter)
else:
read_seq = []
except:
sys.stderr.write(
"Error occured when reading beginning of SAM/BAM file.\n")
raise
# CIGAR match characters (including alignment match, sequence match, and
# sequence mismatch
com = ('M', '=', 'X')
counts = {key: 0 for key in feature_attr}
try:
if pe_mode:
if ((supplementary_alignment_mode == 'ignore') and
(secondary_alignment_mode == 'ignore')):
primary_only = True
else:
primary_only = False
if order == "name":
read_seq = HTSeq.pair_SAM_alignments(
read_seq,
primary_only=primary_only)
elif order == "pos":
read_seq = HTSeq.pair_SAM_alignments_with_buffer(
read_seq,
max_buffer_size=max_buffer_size,
primary_only=primary_only)
else:
raise ValueError("Illegal order specified.")
empty = 0
ambiguous = 0
notaligned = 0
lowqual = 0
nonunique = 0
i = 0
for r in read_seq:
if i > 0 and i % 100000 == 0 and not quiet:
sys.stderr.write(
"%d alignment record%s processed.\n" %
(i, "s" if not pe_mode else " pairs"))
sys.stderr.flush()
i += 1
if not pe_mode:
if not r.aligned:
notaligned += 1
write_to_samout(
r, "__not_aligned", samoutfile,
template)
continue
if ((secondary_alignment_mode == 'ignore') and
r.not_primary_alignment):
continue
if ((supplementary_alignment_mode == 'ignore') and
r.supplementary):
continue
try:
if r.optional_field("NH") > 1:
nonunique += 1
write_to_samout(
r,
"__alignment_not_unique",
samoutfile,
template)
if multimapped_mode == 'none':
continue
except KeyError:
pass
if r.aQual < minaqual:
lowqual += 1
write_to_samout(
r, "__too_low_aQual", samoutfile,
template)
continue
if stranded != "reverse":
iv_seq = (co.ref_iv for co in r.cigar if co.type in com
and co.size > 0)
else:
iv_seq = (invert_strand(co.ref_iv)
for co in r.cigar if (co.type in com and
co.size > 0))
else:
if r[0] is not None and r[0].aligned:
if stranded != "reverse":
iv_seq = (co.ref_iv for co in r[0].cigar
if co.type in com and co.size > 0)
else:
iv_seq = (invert_strand(co.ref_iv) for co in r[0].cigar
if co.type in com and co.size > 0)
else:
iv_seq = tuple()
if r[1] is not None and r[1].aligned:
if stranded != "reverse":
iv_seq = itertools.chain(
iv_seq,
(invert_strand(co.ref_iv) for co in r[1].cigar
if co.type in com and co.size > 0))
else:
iv_seq = itertools.chain(
iv_seq,
(co.ref_iv for co in r[1].cigar
if co.type in com and co.size > 0))
else:
if (r[0] is None) or not (r[0].aligned):
write_to_samout(
r, "__not_aligned", samoutfile,
template)
notaligned += 1
continue
if secondary_alignment_mode == 'ignore':
if (r[0] is not None) and r[0].not_primary_alignment:
continue
elif (r[1] is not None) and r[1].not_primary_alignment:
continue
if supplementary_alignment_mode == 'ignore':
if (r[0] is not None) and r[0].supplementary:
continue
elif (r[1] is not None) and r[1].supplementary:
continue
try:
if ((r[0] is not None and r[0].optional_field("NH") > 1) or
(r[1] is not None and r[1].optional_field("NH") > 1)):
nonunique += 1
write_to_samout(
r, "__alignment_not_unique", samoutfile,
template)
if multimapped_mode == 'none':
continue
except KeyError:
pass
if ((r[0] and r[0].aQual < minaqual) or
(r[1] and r[1].aQual < minaqual)):
lowqual += 1
write_to_samout(
r, "__too_low_aQual", samoutfile,
template)
continue
try:
if overlap_mode == "union":
fs = set()
for iv in iv_seq:
if iv.chrom not in features.chrom_vectors:
raise UnknownChrom
for iv2, fs2 in features[iv].steps():
fs = fs.union(fs2)
elif overlap_mode in ("intersection-strict",
"intersection-nonempty"):
fs = None
for iv in iv_seq:
if iv.chrom not in features.chrom_vectors:
raise UnknownChrom
for iv2, fs2 in features[iv].steps():
if ((len(fs2) > 0) or
(overlap_mode == "intersection-strict")):
if fs is None:
fs = fs2.copy()
else:
fs = fs.intersection(fs2)
else:
sys.exit("Illegal overlap mode.")
if fs is None or len(fs) == 0:
write_to_samout(
r, "__no_feature", samoutfile,
template)
empty += 1
elif len(fs) > 1:
write_to_samout(
r, "__ambiguous[" + '+'.join(sorted(fs)) + "]",
samoutfile,
template)
ambiguous += 1
else:
write_to_samout(
r, list(fs)[0], samoutfile,
template)
if fs is not None and len(fs) > 0:
if multimapped_mode == 'none':
if len(fs) == 1:
counts[list(fs)[0]] += 1
elif multimapped_mode == 'all':
for fsi in list(fs):
counts[fsi] += 1
elif multimapped_mode == 'fraction':
for fsi in list(fs):
counts[fsi] += 1.0 / len(fs)
elif multimapped_mode == 'random':
fsi = random.choice(list(fs))
counts[fsi] += 1
else:
sys.exit("Illegal multimap mode.")
except UnknownChrom:
write_to_samout(
r, "__no_feature", samoutfile,
template)
empty += 1
except:
sys.stderr.write(
"Error occured when processing input (%s):\n" %
(read_seq_file.get_line_number_string()))
raise
if not quiet:
sys.stderr.write(
"%d %s processed.\n" %
(i, "alignments " if not pe_mode else "alignment pairs"))
sys.stderr.flush()
if samoutfile is not None:
samoutfile.close()
return {
'isam': isam,
'counts': counts,
'empty': empty,
'ambiguous': ambiguous,
'lowqual': lowqual,
'notaligned': notaligned,
'nonunique': nonunique,
}
def count_reads_in_features(
sam_filenames,
gff_filename,
order,
max_buffer_size,
stranded,
overlap_mode,
multimapped_mode,
secondary_alignment_mode,
supplementary_alignment_mode,
feature_type,
id_attribute,
additional_attributes,
add_chromosome_info,
quiet,
minaqual,
samouts,
samout_format,
output_delimiter,
output_filename,
output_append,
nprocesses,
feature_query,
counts_output_sparse,
):
'''Count reads in features, parallelizing by file'''
# Never use more CPUs than files
nprocesses = min(nprocesses, len(sam_filenames))
if samouts != []:
if len(samouts) != len(sam_filenames):
raise ValueError(
'Select the same number of input and output files')
# Try to open samout files early in case any of them has issues
if samout_format in ('SAM', 'sam'):
for samout in samouts:
with open(samout, 'w'):
pass
else:
# We don't have a template if the input is stdin
if (len(sam_filenames) != 1) or (sam_filenames[0] != '-'):
for sam_filename, samout in zip(sam_filenames, samouts):
with pysam.AlignmentFile(sam_filename, 'r') as sf:
with pysam.AlignmentFile(samout, 'w', template=sf):
pass
else:
samouts = [None for x in sam_filenames]
# Try to open samfiles to fail early in case any of them is not there
if (len(sam_filenames) != 1) or (sam_filenames[0] != '-'):
for sam_filename in sam_filenames:
with pysam.AlignmentFile(sam_filename, 'r') as sf:
pass
# Deal with custom id_attribute lists. This is never shorter than 1 because
# gene_id is the default. However, if the option was called at least once,
# that should _override_ the default, which means skipping the first
# element (i.e., gene_id).
if len(id_attribute) > 1:
del id_attribute[0]
# Prepare features
gff = HTSeq.GFF_Reader(gff_filename)
feature_scan = HTSeq.make_feature_genomicarrayofsets(
gff,
id_attribute,
feature_type=feature_type,
feature_query=feature_query,
additional_attributes=additional_attributes,
stranded=stranded != 'no',
verbose=not quiet,
add_chromosome_info=add_chromosome_info,
)
features = feature_scan['features']
attributes = feature_scan['attributes']
feature_attr = sorted(attributes.keys())
if len(feature_attr) == 0:
sys.stderr.write(
"Warning: No features of type '%s' found.\n" % feature_type)
# Prepare arguments for counting function
args = []
for isam, (sam_filename, samout_filename) in enumerate(zip(sam_filenames, samouts)):
args.append((
isam,
sam_filename,
features,
feature_attr,
order,
max_buffer_size,
stranded,
overlap_mode,
multimapped_mode,
secondary_alignment_mode,
supplementary_alignment_mode,
feature_type,
id_attribute,
additional_attributes,
quiet,
minaqual,
samout_format,
samout_filename,
))
# Count reads in parallel
if nprocesses > 1:
with multiprocessing.Pool(nprocesses) as pool:
results = pool.starmap(count_reads_single_file, args)
results.sort(key=operator.itemgetter('isam'))
else:
results = list(itertools.starmap(count_reads_single_file, args))
# Merge and write output
_write_output(
results,
sam_filenames,
attributes,
additional_attributes,
output_filename,
output_delimiter,
output_append,
sparse=counts_output_sparse,
dtype=np.float32,
)
def main():
pa = argparse.ArgumentParser(
usage="%(prog)s [options] alignment_file gff_file",
description="This script takes one or more alignment files in SAM/BAM " +
"format and a feature file in GFF format and calculates for each feature " +
"the number of reads mapping to it. See " +
"http://htseq.readthedocs.io/en/master/count.html for details.",
epilog="Written by Simon Anders (sanders@fs.tum.de), " +
"European Molecular Biology Laboratory (EMBL) and Fabio Zanini " +
"(fabio.zanini@unsw.edu.au), UNSW Sydney. (c) 2010-2020. " +
"Released under the terms of the GNU General Public License v3. " +
"Part of the 'HTSeq' framework, version %s." % HTSeq.__version__)
pa.add_argument(
"--version", action="store_true",
help='Show software version and exit')
args, argv = pa.parse_known_args()
# Version is the only case where the BAM and GTF files are optional
if args.version:
print(HTSeq.__version__)
sys.exit()
pa.add_argument(
"samfilenames", nargs='+', type=str,
help="Path to the SAM/BAM files containing the mapped reads. " +
"If '-' is selected, read from standard input")
pa.add_argument(
"featuresfilename", type=str,
help="Path to the GTF file containing the features")
pa.add_argument(
"-f", "--format", dest="samtype",
choices=("sam", "bam", "auto"), default="auto",
help="Type of <alignment_file> data. DEPRECATED: " +
"file format is detected automatically. This option is ignored.")
pa.add_argument(
"-r", "--order", dest="order",
choices=("pos", "name"), default="name",
help="'pos' or 'name'. Sorting order of <alignment_file> (default: name). Paired-end sequencing " +
"data must be sorted either by position or by read name, and the sorting order " +
"must be specified. Ignored for single-end data.")
pa.add_argument(
"--max-reads-in-buffer", dest="max_buffer_size", type=int,
default=30000000,
help="When <alignment_file> is paired end sorted by position, " +
"allow only so many reads to stay in memory until the mates are " +
"found (raising this number will use more memory). Has no effect " +
"for single end or paired end sorted by name")
pa.add_argument(
"-s", "--stranded", dest="stranded",
choices=("yes", "no", "reverse"), default="yes",
help="Whether the data is from a strand-specific assay. Specify 'yes', " +
"'no', or 'reverse' (default: yes). " +
"'reverse' means 'yes' with reversed strand interpretation")
pa.add_argument(
"-a", "--minaqual", type=int, dest="minaqual",
default=10,
help="Skip all reads with MAPQ alignment quality lower than the given " +
"minimum value (default: 10). MAPQ is the 5th column of a SAM/BAM " +
"file and its usage depends on the software used to map the reads.")
pa.add_argument(
"-t", "--type", type=str, dest="featuretype",
default="exon",
help="Feature type (3rd column in GTF file) to be used, " +
"all features of other type are ignored (default, suitable for Ensembl " +
"GTF files: exon)")
pa.add_argument(
"-i", "--idattr", type=str, dest="idattr",
action='append',
default=["gene_id"],
help="GTF attribute to be used as feature ID (default, " +
"suitable for Ensembl GTF files: gene_id). All feature of the " +
"right type (see -t option) within the same GTF attribute will " +
"be added together. The typical way of using this option is to " +
"count all exonic reads from each gene and add the exons " +
"but other uses are possible as well. You can call this option " +
"multiple times: in that case, the combination of all attributes " +
"separated by colons (:) will be used as a unique identifier, " +
"e.g. for exons you might use -i gene_id -i exon_number.")
pa.add_argument(
"--additional-attr", type=str,
action='append',
default=[],
help="Additional feature attributes (default: none, " +
"suitable for Ensembl GTF files: gene_name). Use multiple times " +
"for more than one additional attribute. These attributes are " +
"only used as annotations in the output, while the determination " +
"of how the counts are added together is done based on option -i.")
pa.add_argument(
"--add-chromosome-info", action='store_true',
help="Store information about the chromosome of each feature as " +
"an additional attribute (e.g. colunm in the TSV output file).",
)
pa.add_argument(
"-m", "--mode", dest="mode",
choices=("union", "intersection-strict", "intersection-nonempty"),
default="union",
help="Mode to handle reads overlapping more than one feature " +
"(choices: union, intersection-strict, intersection-nonempty; default: union)")
pa.add_argument(
"--nonunique", dest="nonunique", type=str,
choices=("none", "all", "fraction", "random"), default="none",
help="Whether and how to score reads that are not uniquely aligned " +
"or ambiguously assigned to features " +
"(choices: none, all, fraction, random; default: none)")
pa.add_argument(
"--secondary-alignments", dest="secondary_alignments", type=str,
choices=("score", "ignore"), default="ignore",
help="Whether to score secondary alignments (0x100 flag)")
pa.add_argument(
"--supplementary-alignments", dest="supplementary_alignments", type=str,
choices=("score", "ignore"), default="ignore",
help="Whether to score supplementary alignments (0x800 flag)")
pa.add_argument(
"-o", "--samout", type=str, dest="samouts",
action='append',
default=[],
help="Write out all SAM alignment records into " +
"SAM/BAM files (one per input file needed), annotating each line " +
"with its feature assignment (as an optional field with tag 'XF')" +
". See the -p option to use BAM instead of SAM.")
pa.add_argument(
"-p", '--samout-format', type=str, dest='samout_format',
choices=('SAM', 'BAM', 'sam', 'bam'), default='SAM',
help="Format to use with the --samout option."
)
pa.add_argument(
"-d", '--delimiter', type=str, dest='output_delimiter',
default='\t',
help="Column delimiter in output (default: TAB)."
)
pa.add_argument(
"-c", '--counts_output', type=str, dest='output_filename',
default='',
help="Filename to output the counts to instead of stdout."
)
pa.add_argument(
"--counts-output-sparse", action='store_true',
help="Store the counts as a sparse matrix (mtx, h5ad, loom)."
)
pa.add_argument(
'--append-output', action='store_true', dest='output_append',
help='Append counts output to an existing file instead of ' +
'creating a new one. This option is useful if you have ' +
'already creates a TSV/CSV/similar file with a header for your ' +
'samples (with additional columns for the feature name and any ' +
'additionl attributes) and want to fill in the rest of the file.'
)
pa.add_argument(
"-n", '--nprocesses', type=int, dest='nprocesses',
default=1,
help="Number of parallel CPU processes to use (default: 1). " +
"This option is useful to process several input files at once. " +
"Each file will use only 1 CPU. It is possible, of course, to " +
"split a very large input SAM/BAM files into smaller chunks " +
"upstream to make use of this option."
)
pa.add_argument(
'--feature-query', type=str, dest='feature_query',
default=None,
help='Restrict to features descibed in this expression. Currently ' +
'supports a single kind of expression: attribute == "one attr" to ' +
'restrict the GFF to a single gene or transcript, e.g. ' +
'--feature-query \'gene_name == "ACTB"\' - notice the single ' +
'quotes around the argument of this option and the double ' +
'quotes around the gene name. Broader queries might become ' +
'available in the future.',
)
pa.add_argument(
"-q", "--quiet", action="store_true", dest="quiet",
help="Suppress progress report") # and warnings" )
args = pa.parse_args()
warnings.showwarning = my_showwarning
try:
count_reads_in_features(
args.samfilenames,
args.featuresfilename,
args.order,
args.max_buffer_size,
args.stranded,
args.mode,
args.nonunique,
args.secondary_alignments,
args.supplementary_alignments,
args.featuretype,
args.idattr,
args.additional_attr,
args.add_chromosome_info,
args.quiet,
args.minaqual,
args.samouts,
args.samout_format,
args.output_delimiter,
args.output_filename,
args.output_append,
args.nprocesses,
args.feature_query,
args.counts_output_sparse,
)
except:
sys.stderr.write(" %s\n" % str(sys.exc_info()[1]))
sys.stderr.write(" [Exception type: %s, raised in %s:%d]\n" %
(sys.exc_info()[1].__class__.__name__,
os.path.basename(traceback.extract_tb(
sys.exc_info()[2])[-1][0]),
traceback.extract_tb(sys.exc_info()[2])[-1][1]))
sys.exit(1)
if __name__ == "__main__":
main()
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