def filter_read_pair(reads,
ref,
hist_distance_from_consensus=None,
hist_dist_along=None,
binsize=None,
max_mismatches=100,
match_len_min=30,
trim_bad_cigars=3,
VERBOSE=0):
'''Filter read pair'''
from hivwholeseq.utils.mapping import trim_short_cigars_pair
(read1, read2) = reads
# Check names to make sure we are looking at paired reads, this would
# screw up the whole bamfile
if read1.qname != read2.qname:
n_wrongname += 1
raise ValueError('Read pair ' + str(irp) +
': reads have different names!')
# Ignore unmapped reads
if read1.is_unmapped or read2.is_unmapped:
if VERBOSE >= 2:
print 'Read pair ' + read1.qname + ': unmapped'
return 'unmapped'
# Ignore not properly paired reads (this includes mates sitting on
# different fragments)
if (not read1.is_proper_pair) or (not read2.is_proper_pair):
if VERBOSE >= 2:
print 'Read pair ' + read1.qname + ': not properly paired'
return 'unpaired'
i_fwd = reads[0].is_reverse
i_rev = not i_fwd
readf = reads[i_fwd]
readr = reads[i_rev]
# Mismappings are often characterized by many mutations:
# check the number of mismatches and skip reads with too many
dc = get_distance_from_consensus(ref, reads, VERBOSE=VERBOSE)
if hist_distance_from_consensus is not None:
hist_distance_from_consensus[dc.sum()] += 1
if hist_dist_along is not None:
hbin = (readf.pos + readf.isize / 2) // binsize
hist_dist_along[hbin, dc.sum()] += 1
if (dc.sum() > max_mismatches):
if VERBOSE >= 2:
print 'Read pair '+read1.qname+': too many mismatches '+\
'('+str(dc[0])+' + '+str(dc[1])+')'
return 'mutator'
# Trim the bad CIGARs from the sides, if there are any good ones
# FIXME: this must have a bug with leading insertions
# NOTE: I rewrote the function, now simpler, it should work
skip = trim_short_cigars_pair(reads,
match_len_min=match_len_min,
trim_pad=trim_bad_cigars,
throw=False)
if skip:
return 'bad_cigar'
# Check the reads are still long enough after trimming
if (len(read1.seq) < 100):
if VERBOSE >= 2:
print 'Read too short:', read1.qname, len(read1.seq)
return 'tiny'
if (len(read2.seq) < 100):
if VERBOSE >= 2:
print 'Read too short:', read2.qname, len(read2.seq)
return 'tiny'
# NOTE: cross-overhang and similar stuff should never happen, because we
# filter only insert sizes > 400 after premapping. Nonetheless...
if readf.isize < 300:
if VERBOSE >= 2:
print 'Insert too small:', readf.isize
return 'tiny'
return 'good'
def fish_distant_reads(bamfilename, ref,
min_mismatches=20, max_mismatches=30,
VERBOSE=0, maxseqs=-1):
'''Fish distant reads from the trash'''
import numpy as np
from hivwholeseq.utils.mapping import pair_generator, reads_to_seqrecord
from hivwholeseq.sequencing.filter_mapped_reads import check_overhanging_reads, \
get_distance_from_consensus
distances = []
seqs = []
edges = []
with pysam.Samfile(bamfilename, 'rb') as bamfile:
for irp, reads in enumerate(pair_generator(bamfile)):
if VERBOSE >= 2:
if not ((irp + 1) % 10000):
print irp + 1
(read1, read2) = reads
i_fwd = reads[0].is_reverse
# Check a few things to make sure we are looking at paired reads
if read1.qname != read2.qname:
raise ValueError('Read pair '+str(irp)+': reads have different names!')
# Ignore unmapped reads
if read1.is_unmapped or read2.is_unmapped:
continue
# Ignore not properly paired reads (this includes mates sitting on
# different fragments)
if (not read1.is_proper_pair) or (not read2.is_proper_pair):
continue
# Check for overhangs beyond the edge
skip = check_overhanging_reads(reads, len(ref))
if skip:
continue
# Fish out our reads
dc = get_distance_from_consensus(ref, reads, VERBOSE=VERBOSE)
if (min_mismatches <= dc.sum() <= max_mismatches):
if VERBOSE >= 3:
print 'Gotcha!', reads[0].qname
seqs.append(reads[0])
seqs.append(reads[1])
distances.append(dc)
edge = [(read.pos, read.pos + sum(bl for bt, bl in read.cigar if bt in (0, 2)))
for read in reads]
edges.append(edge)
if len(seqs) // 2 == maxseqs:
if VERBOSE >= 2:
print 'Max seqs reached:', maxseqs
break
seqs = list(pair_generator(reads_to_seqrecord(seqs)))
distances = np.array(distances, int)
return (distances, edges, seqs)
def filter_read_pair(reads,
ref,
hist_distance_from_consensus=None,
hist_dist_along=None,
binsize=None,
max_mismatches=100,
match_len_min=30,
trim_bad_cigars=3,
VERBOSE=0):
'''Filter read pair'''
from hivwholeseq.utils.mapping import trim_short_cigars_pair
(read1, read2) = reads
# Check names to make sure we are looking at paired reads, this would
# screw up the whole bamfile
if read1.qname != read2.qname:
n_wrongname += 1
raise ValueError('Read pair '+str(irp)+': reads have different names!')
# Ignore unmapped reads
if read1.is_unmapped or read2.is_unmapped:
if VERBOSE >= 2:
print 'Read pair '+read1.qname+': unmapped'
return 'unmapped'
# Ignore not properly paired reads (this includes mates sitting on
# different fragments)
if (not read1.is_proper_pair) or (not read2.is_proper_pair):
if VERBOSE >= 2:
print 'Read pair '+read1.qname+': not properly paired'
return 'unpaired'
i_fwd = reads[0].is_reverse
i_rev = not i_fwd
readf = reads[i_fwd]
readr = reads[i_rev]
# Mismappings are often characterized by many mutations:
# check the number of mismatches and skip reads with too many
dc = get_distance_from_consensus(ref, reads, VERBOSE=VERBOSE)
if hist_distance_from_consensus is not None:
hist_distance_from_consensus[dc.sum()] += 1
if hist_dist_along is not None:
hbin = (readf.pos + readf.isize / 2) // binsize
hist_dist_along[hbin, dc.sum()] += 1
if (dc.sum() > max_mismatches):
if VERBOSE >= 2:
print 'Read pair '+read1.qname+': too many mismatches '+\
'('+str(dc[0])+' + '+str(dc[1])+')'
return 'mutator'
# Trim the bad CIGARs from the sides, if there are any good ones
# FIXME: this must have a bug with leading insertions
# NOTE: I rewrote the function, now simpler, it should work
skip = trim_short_cigars_pair(reads, match_len_min=match_len_min,
trim_pad=trim_bad_cigars, throw=False)
if skip:
return 'bad_cigar'
# Check the reads are still long enough after trimming
if (len(read1.seq) < 100):
if VERBOSE >= 2:
print 'Read too short:', read1.qname, len(read1.seq)
return 'tiny'
if (len(read2.seq) < 100):
if VERBOSE >= 2:
print 'Read too short:', read2.qname, len(read2.seq)
return 'tiny'
# NOTE: cross-overhang and similar stuff should never happen, because we
# filter only insert sizes > 400 after premapping. Nonetheless...
if readf.isize < 300:
if VERBOSE >= 2:
print 'Insert too small:', readf.isize
return 'tiny'
return 'good'
