def cons_self_tandem_record(r_array, low_repeat_ratio=low_repeat_ratio):
rlen = 0.0 + pb.get_read_op_length(r_array[0])
cons_len = rlen / 2
for r in r_array:
map_len = pb.get_aligned_read_length(r)
if map_len / cons_len >= low_repeat_ratio:
return r
return None
def is_cons_partial(r_array):
query_pos, map_len = [], []
for r in r_array:
qstart = (0 if r.cigartuples[-1][0] != 4 else r.cigartuples[-1][1] +
1) if r.is_reverse else r.query_alignment_start + 1
query_pos.append(qstart)
map_len.append(pb.get_aligned_read_length(r))
for i in range(1, len(query_pos)):
if abs(query_pos[i] - query_pos[i - 1]) > 10:
return False
elif abs(map_len[i] - map_len[i - 1]) > 10:
return False
return True
def high_qual_record(r_array,
high_max_ratio=high_max_ratio,
high_min_ratio=high_min_ratio,
high_iden_ratio=high_iden_ratio):
if not r_array: return None
primary_r = r_array[0]
# primary_r = ps.AlignedSegment()
if primary_r.is_secondary or primary_r.is_supplementary or primary_r.is_unmapped:
ut.fatal_format_time('high_qual_record',
'Error: input SAM file is sorted or modified.')
primary_start = primary_r.reference_start + 1
primary_end = primary_start + pb.get_ref_op_length(primary_r) - 1
rlen = 0.0 + pb.get_read_op_length(primary_r)
cons_len = rlen / 2
best_i = -1
best_r = None
best_AS = -1
best_iden_ratio = -1.0
primary_is_high = False
for i, r in iter(enumerate(r_array)):
map_len = pb.get_aligned_read_length(r)
mc = map_len / cons_len
iden_ratio = get_iden_ratio(r)
AS = int(r.get_tag('AS'))
if high_min_ratio <= mc <= high_max_ratio and iden_ratio >= high_iden_ratio:
if len(r.reference_name) >= 6 or r.reference_name.startswith(
'chrM') or r.reference_name.startswith('chrUn'):
return None
if AS > best_AS:
if i == 0:
primary_is_high = True
best_r, best_i, best_AS = r, i, AS
# if r is not primary record, r has to NOT overlap with primary r
elif r.reference_name != primary_r.reference_name or (
r.reference_start + 1 > primary_end
or r.reference_start + pb.get_ref_op_length(r) <
primary_start):
best_r, best_i, best_AS = r, i, AS
if best_i == -1:
return None
else:
return primary_r if primary_is_high else best_r
def cons_repeat_record(r_array,
high_iden_ratio=high_iden_ratio,
high_repeat_ratio=high_repeat_ratio):
map_pos, map_len = [], []
rlen = 0.0 + pb.get_read_op_length(r_array[0])
cons_len = rlen / 2
for r in r_array:
map_pos.append(r.reference_start + 1)
map_len.append(pb.get_aligned_read_length(r))
for i in range(len(map_pos) - 1):
for j in range(i + 1, len(map_pos)):
if abs(map_pos[i] - map_pos[j]) <= 10 and \
abs(map_len[i] - map_len[j]) <= 10 and map_len[i] / cons_len <= high_repeat_ratio:
if get_iden_ratio(
r_array[i]) >= high_iden_ratio and get_iden_ratio(
r_array[j]) >= high_iden_ratio:
return r_array[i]
return None
def get_iden_ratio(r):
new_block = 1
ins_len, del_len = 0, 0
for tuples in r.cigartuples:
if tuples[0] == pb.BAM_CINS:
ins_len += tuples[1]
if ins_len > max_ins_len: return -1.0
elif tuples[0] == pb.BAM_CDEL:
del_len += tuples[1]
if del_len > max_del_len: return -1.0
elif tuples[0] == pb.BAM_CREF_SKIP:
ins_len, del_len = 0, 0
map_len = pb.get_aligned_read_length(r)
if not r.has_tag('NM'):
ut.fatal_format_time('bam_classify', 'No NM tag found.\n')
NM = int(r.get_tag('NM'))
del_len = int(pb.get_cigar_len(r, pb.BAM_CDEL))
iden_len = map_len - NM + del_len
return iden_len / (map_len + 0.0)
def cla_record(r_array,
high_bam,
low_bam,
high_max_ratio=high_max_ratio,
high_min_ratio=high_min_ratio,
high_iden_ratio=high_iden_ratio,
high_repeat_ratio=high_repeat_ratio,
low_repeat_ratio=low_repeat_ratio):
if not r_array: return
if len(r_array) == 1: # single record
rlen = 0.0 + pb.get_read_op_length(r_array[0])
cons_len = rlen / 2
map_len = pb.get_aligned_read_length(r_array[0])
mc = map_len / cons_len
if high_min_ratio <= mc <= high_max_ratio and get_iden_ratio(
r_array[0]) >= high_iden_ratio:
high_bam.write(r_array[0])
elif mc >= low_repeat_ratio:
low_bam.write(r_array[0])
else:
low_bam.write(r_array[0])
else: # multiple records
high_r = high_qual_record(r_array, high_max_ratio, high_min_ratio,
high_iden_ratio)
if high_r:
high_bam.write(high_r)
else:
rep_r = cons_repeat_record(r_array, high_iden_ratio,
high_repeat_ratio)
if rep_r:
# high_bam.write(rep_r) # TODO
low_bam.write(rep_r)
return
self_r = cons_self_tandem_record(r_array, low_repeat_ratio)
if self_r:
low_bam.write(self_r)
else:
for r in r_array:
if not (r.is_secondary or r.is_supplementary):
low_bam.write(r)
break