def test_get_read_group_info():
'Tests get_read_group_info'
sam_sample = '''@SQ\tSN:SGN-U576692\tLN:1714
@SQ\tSN:SGN-U572743\tLN:833
@RG\tID:g1\tLB:g1\tSM:g1\tPL:sanger
@RG\tID:g3\tLB:g3\tSM:g3\tPL:sanger
SGN-E200000\t0\tSGN-U572743\t317\t226\t14M\t*\t0\t0\tGGATGATKTTAGAG\t*\tAS:i:250\tXS:i:0\tXF:i:0\tXE:i:7\tXN:i:0\tRG:Z:g1
SGN-E40000\t0\tSGN-U576692\t1416\t207\t10M\t*\t0\t0\tAGCCTGATAA\t,,09377777\tAS:i:160\tXS:i:0\tXF:i:3\tXE:i:4\tXN:i:0\tRG:Z:g3
SGN-E40000\t20\tSGN-U576692\t1416\t207\t10M\t*\t0\t0\tAGCCTGATAA\t,,09377777\tAS:i:160\tXS:i:0\tXF:i:3\tXE:i:4\tXN:i:0\tRG:Z:g3
'''
sam_fhand = NamedTemporaryFile(suffix='.sam')
sam_fhand.write(sam_sample)
sam_fhand.flush()
bam_fhand = NamedTemporaryFile(suffix='.bam')
sam2bam(sam_fhand.name, bam_fhand.name)
bam_fhand.flush()
bam = pysam.Samfile(bam_fhand.name, 'rb')
read_gro_i = get_read_group_info(bam)
assert read_gro_i == {'g3': {'LB': 'g3', 'SM': 'g3', 'PL': 'sanger'},
'g1': {'LB': 'g1', 'SM': 'g1', 'PL': 'sanger'}}
def _snvs_in_bam(bam, reference, min_quality, default_sanger_quality,
min_mapq, min_num_alleles, max_maf, min_num_reads_for_allele,
read_edge_conf=None, default_bam_platform=None):
'It yields the snv information for every snv in the given reference'
min_num_alleles = int(min_num_alleles)
read_groups_info = get_read_group_info(bam)
if not read_groups_info:
if default_bam_platform is None:
msg = 'Platform is not present either in header or in '
msg += 'configuration'
raise ValueError(msg)
read_groups_info = {UNKNOWN_RG:{'PL':default_bam_platform}}
reference_id = get_seq_name(reference)
reference_seq = reference.seq
reference_len = len(reference_seq)
#we can clean the cache of segments because we're in a new molecule
global SEGMENTS_CACHE
SEGMENTS_CACHE = {}
for column in bam.pileup(reference=reference_id):
alleles = {}
ref_pos = column.pos
if ref_pos >= reference_len:
continue
ref_id = bam.getrname(column.tid)
ref_allele = reference_seq[ref_pos].upper()
for pileup_read in column.pileups:
#for each read in the column we add its allele to the alleles dict
aligned_read = pileup_read.alignment
read_mapping_qual = aligned_read.mapq
#We ignore the reads that are likely to be missaligned
if read_mapping_qual < min_mapq:
continue
try:
read_group = aligned_read.opt('RG')
except KeyError:
read_group = UNKNOWN_RG
read_name = aligned_read.qname
if read_groups_info and read_group in read_groups_info:
platform = read_groups_info[read_group]['PL']
else:
platform = default_bam_platform
read_pos = pileup_read.qpos
alleles_here, read_limits = _get_alleles_from_read(ref_allele,
ref_pos,
pileup_read)
if read_edge_conf and platform in read_edge_conf:
edge_left, edge_right = read_edge_conf[platform]
#if we're in the edge region to be ignored we continue to
#the next read, because there's no allele to add for this one.
if (edge_left is not None and
read_limits[0] + edge_left > read_pos):
continue
if (edge_right is not None and
read_pos > read_limits[1] - edge_right):
continue
for allele in alleles_here:
allele, kind, qual, is_reverse = allele
_add_allele(alleles, allele, kind, read_name, read_group,
is_reverse, qual, read_mapping_qual,
read_groups_info)
#remove N
_remove_alleles_n(alleles)
#add default sanger qualities to the sanger reads with no quality
_add_default_sanger_quality(alleles, default_sanger_quality,
read_groups_info)
#remove bad quality alleles
_remove_bad_quality_alleles(alleles, min_quality)
#check maf
if not check_maf_ok(alleles, max_maf):
continue
# min_num_reads_for_allele
_remove_alleles_by_read_number(alleles, min_num_reads_for_allele)
#if there are a min_num number of alleles requested and there are more
#alleles than that
#OR
#there is some allele different than invariant
#a variation is yield
if not alleles:
continue
if (len(alleles) > min_num_alleles or
(min_num_alleles == 1 and alleles.keys()[0][1] != INVARIANT) or
(min_num_alleles > 1 and len(alleles) >= min_num_alleles)):
yield {'ref_name':ref_id,
'ref_position':ref_pos,
'reference_allele':ref_allele,
'alleles':alleles,
'read_groups':read_groups_info}