def calculate_distance_distribution(interleave_fhand, index_fpath,
max_clipping, max_distance=None,
tempdir=None, threads=None):
bam_fhand = NamedTemporaryFile(suffix='.bam')
extra_params = ['-a', '-M']
bwa = map_with_bwamem(index_fpath, interleave_fpath=interleave_fhand.name,
extra_params=extra_params)
map_process_to_sortedbam(bwa, bam_fhand.name, key='queryname',
tempdir=tempdir)
bamfile = Samfile(bam_fhand.name)
stats = {'outies': IntCounter(), 'innies': IntCounter(),
'others': IntCounter()}
for grouped_mates in _group_alignments_reads_by_qname(bamfile):
mates = _split_mates(grouped_mates)
for aligned_read1 in _get_totally_mapped_alignments(mates[0],
max_clipping):
for aligned_read2 in _get_totally_mapped_alignments(mates[1],
max_clipping):
if aligned_read1.rname == aligned_read2.rname:
aligned_reads = [aligned_read1, aligned_read2]
distance = _find_distance(aligned_reads)
if _mates_are_outies(aligned_reads):
kind = 'outies'
elif _mates_are_innies(aligned_reads):
kind = 'innies'
else:
kind = 'others'
if max_distance is None or max_distance > distance:
stats[kind][distance] += 1
return stats
def test_add_rg_to_bam(self):
reference_fpath = os.path.join(TEST_DATA_DIR, 'arabidopsis_genes')
reads_fpath = os.path.join(TEST_DATA_DIR, 'arabidopsis_reads.fastq')
directory = TemporaryDir()
index_fpath = get_or_create_bwa_index(reference_fpath, directory.name)
bam_fhand = NamedTemporaryFile(suffix='.bam')
lib_name = 'aa'
log_fhand = NamedTemporaryFile()
readgroup = {
'ID': lib_name,
'PL': 'illumina',
'LB': lib_name,
'SM': '{0}_illumina_pe'.format(lib_name),
'PU': '0'
}
bwa = map_with_bwamem(index_fpath,
unpaired_fpath=reads_fpath,
readgroup=readgroup,
log_fpath=log_fhand.name)
map_process_to_bam(bwa, bam_fhand.name)
out = subprocess.check_output(
[get_binary_path('samtools'), 'view', '-h', bam_fhand.name],
stderr=log_fhand)
assert '@RG\tID:aa' in out
assert 'TTCTGATTCAATCTACTTCAAAGTTGGCTTTATCAATAAG' in out
directory.close()
def test_classify_paired_reads(self):
index_fpath = os.path.join(TEST_DATA_DIR, 'ref_example.fasta')
# Non chimeric
query1 = '>seq1 1:N:0:GATCAG\nGGGATCGCAGACCCATCTCGTCAGCATGTACCCTTGCTACATTGAACTT\n'
query2 = '>seq1 2:N:0:GATCAG\nAGGAGGGATCGGGCACCCACGGCGCGGTAGACTGAGGCCTTCTCGAACT\n'
# Chimeric
query3 = '>seq2 1:N:0:GATCAG\nAAGTTCAATGTAGCAAGGGTACATGCTGACGAGATGGGTCTGCGATCCC\n'
query4 = '>seq2 2:N:0:GATCAG\nACGTGGATGCGGCGACGGCCCTACGGCACATACTGTTATTAGGGTCACT\n'
# unknown
query5 = '>seq3 1:N:0:GATCAG\nAGTGACCCTAATAACAGTATGTGCCGTAGGGCCGTCGCCGCATCCACGT\n'
query6 = '>seq3 2:N:0:GATCAG\nGTCGTGCGCAGCCATTGAGACCTTCCTAGGGTTTTCCCCATGGAATCGG\n'
query = query1 + query2 + query5 + query6 + query3 + query4
in_fhand = NamedTemporaryFile()
in_fhand.write(query)
in_fhand.flush()
bam_fhand = NamedTemporaryFile(suffix='.bam')
extra_params = ['-a', '-M']
bwa = map_with_bwamem(index_fpath,
interleave_fpath=in_fhand.name,
extra_params=extra_params)
map_process_to_sortedbam(bwa, bam_fhand.name, key='queryname')
result = classify_mapped_reads(bam_fhand, mate_distance=2000)
for pair, kind in result:
if kind == NON_CHIMERIC:
assert 'seq1' in get_name(pair[0])
elif kind == UNKNOWN:
assert 'seq3' in get_name(pair[0])
elif kind == CHIMERA:
assert 'seq2' in get_name(pair[0])
else:
self.fail()
def classify_chimeras(in_fhand,
index_fpath,
mate_distance,
out_fhand,
chimeras_fhand=None,
unknown_fhand=None,
tempdir=None,
threads=None,
settings=get_setting('CHIMERAS_SETTINGS')):
'''It maps sequences from input files, sorts them and writes to output
files according to its classification'''
bam_fhand = NamedTemporaryFile(suffix='.bam')
extra_params = ['-a', '-M']
bwa = map_with_bwamem(index_fpath,
interleave_fpath=in_fhand.name,
extra_params=extra_params)
map_process_to_sortedbam(bwa,
bam_fhand.name,
key='queryname',
tempdir=tempdir)
for pair, kind in classify_mapped_reads(bam_fhand,
settings=settings,
mate_distance=mate_distance):
if kind is NON_CHIMERIC:
write_seqs(pair, out_fhand)
elif kind is CHIMERA and chimeras_fhand is not None:
write_seqs(pair, chimeras_fhand)
elif kind is UNKNOWN and unknown_fhand is not None:
write_seqs(pair, unknown_fhand)
def test_classify_paired_reads(self):
index_fpath = os.path.join(TEST_DATA_DIR, 'ref_example.fasta')
#Non chimeric
query1 = '>seq1 1:N:0:GATCAG\nGGGATCGCAGACCCATCTCGTCAGCATGTACCCTTGCTACATTGAACTT\n'
query2 = '>seq1 2:N:0:GATCAG\nAGGAGGGATCGGGCACCCACGGCGCGGTAGACTGAGGCCTTCTCGAACT\n'
#Chimeric
query3 = '>seq2 1:N:0:GATCAG\nAAGTTCAATGTAGCAAGGGTACATGCTGACGAGATGGGTCTGCGATCCC\n'
query4 = '>seq2 2:N:0:GATCAG\nACGTGGATGCGGCGACGGCCCTACGGCACATACTGTTATTAGGGTCACT\n'
#unknown
query5 = '>seq3 1:N:0:GATCAG\nAGTGACCCTAATAACAGTATGTGCCGTAGGGCCGTCGCCGCATCCACGT\n'
query6 = '>seq3 2:N:0:GATCAG\nGTCGTGCGCAGCCATTGAGACCTTCCTAGGGTTTTCCCCATGGAATCGG\n'
query = query1 + query2 + query5 + query6 + query3 + query4
in_fhand = NamedTemporaryFile()
in_fhand.write(query)
in_fhand.flush()
bam_fhand = NamedTemporaryFile(suffix='.bam')
extra_params = ['-a', '-M']
bwa = map_with_bwamem(index_fpath, interleave_fpath=in_fhand.name,
extra_params=extra_params)
map_process_to_sortedbam(bwa, bam_fhand.name, key='queryname')
result = classify_mapped_reads(bam_fhand, mate_distance=2000)
for pair, kind in result:
if kind == NON_CHIMERIC:
assert 'seq1' in get_name(pair[0])
elif kind == UNKNOWN:
assert 'seq3' in get_name(pair[0])
elif kind == CHIMERA:
assert 'seq2' in get_name(pair[0])
else:
self.fail()
def test_map_with_bwa(self):
reference_fpath = os.path.join(TEST_DATA_DIR, 'arabidopsis_genes')
reads_fpath = os.path.join(TEST_DATA_DIR, 'arabidopsis_reads.fastq')
directory = TemporaryDir()
index_fpath = get_or_create_bwa_index(reference_fpath, directory.name)
bam_fhand = NamedTemporaryFile(suffix='.bam')
bwa = map_with_bwamem(index_fpath, unpaired_fpath=reads_fpath)
map_process_to_bam(bwa, bam_fhand.name)
out = subprocess.check_output([get_binary_path('samtools'), 'view',
bam_fhand.name])
assert 'TTCTGATTCAATCTACTTCAAAGTTGGCTTTATCAATAAG' in out
directory.close()
def test_map_with_bwa(self):
reference_fpath = os.path.join(TEST_DATA_DIR, 'arabidopsis_genes')
reads_fpath = os.path.join(TEST_DATA_DIR, 'arabidopsis_reads.fastq')
directory = TemporaryDir()
index_fpath = get_or_create_bwa_index(reference_fpath, directory.name)
bam_fhand = NamedTemporaryFile(suffix='.bam')
bwa = map_with_bwamem(index_fpath, unpaired_fpath=reads_fpath)
map_process_to_bam(bwa, bam_fhand.name)
out = subprocess.check_output(
[get_binary_path('samtools'), 'view', bam_fhand.name])
assert 'TTCTGATTCAATCTACTTCAAAGTTGGCTTTATCAATAAG' in out
directory.close()
def _pre_trim(self, trim_packet):
seqs = [s for seqs in trim_packet[SEQS_PASSED]for s in seqs]
reads_fhand = NamedTemporaryFile(dir=self._tempdir, suffix='.trimming')
write_seqs(seqs, reads_fhand)
reads_fhand.flush()
bwa = map_with_bwamem(self._index_fpath,
interleave_fpath=reads_fhand.name)
bam_fhand = NamedTemporaryFile(dir=self._tempdir)
map_process_to_sortedbam(bwa, bam_fhand.name, key='queryname',
tempdir=self._tempdir)
self._bam_fhand = bam_fhand
reads_fhand.close()
def _pre_trim(self, trim_packet):
seqs = [s for seqs in trim_packet[SEQS_PASSED]for s in seqs]
reads_fhand = NamedTemporaryFile(dir=self._tempdir, suffix='.trimming')
write_seqs(seqs, reads_fhand)
reads_fhand.flush()
bwa = map_with_bwamem(self._index_fpath,
interleave_fpath=reads_fhand.name)
bam_fhand = NamedTemporaryFile(dir=self._tempdir)
map_process_to_sortedbam(bwa, bam_fhand.name, key='queryname',
tempdir=self._tempdir)
self._bam_fhand = bam_fhand
reads_fhand.close()
def test_add_rg_to_bam(self):
reference_fpath = os.path.join(TEST_DATA_DIR, 'arabidopsis_genes')
reads_fpath = os.path.join(TEST_DATA_DIR, 'arabidopsis_reads.fastq')
directory = TemporaryDir()
index_fpath = get_or_create_bwa_index(reference_fpath, directory.name)
bam_fhand = NamedTemporaryFile(suffix='.bam')
lib_name = 'aa'
log_fhand = NamedTemporaryFile()
readgroup = {'ID': lib_name, 'PL': 'illumina', 'LB': lib_name,
'SM': '{0}_illumina_pe'.format(lib_name), 'PU': '0'}
bwa = map_with_bwamem(index_fpath, unpaired_fpath=reads_fpath,
readgroup=readgroup, log_fpath=log_fhand.name)
map_process_to_bam(bwa, bam_fhand.name)
out = subprocess.check_output([get_binary_path('samtools'), 'view',
'-h', bam_fhand.name], stderr=log_fhand)
assert '@RG\tID:aa' in out
assert 'TTCTGATTCAATCTACTTCAAAGTTGGCTTTATCAATAAG' in out
directory.close()
def _sorted_mapped_reads(ref_fpath, paired_fpaths=None,
unpaired_fpaths=None, directory=None,
file_format=None, min_seed_len=None):
fhand = open(paired_fpaths[0]) if paired_fpaths else open(unpaired_fpaths[0])
if file_format is not None:
set_format(fhand, file_format)
else:
file_format = get_format(fhand)
index_fpath = get_or_create_bwa_index(ref_fpath, directory)
extra_params = ['-a', '-M']
if min_seed_len is not None:
extra_params.extend(['-k', min_seed_len])
bwa = map_with_bwamem(index_fpath, paired_fpaths=paired_fpaths,
unpaired_fpath=unpaired_fpaths,
extra_params=extra_params)
bam_fhand = NamedTemporaryFile(dir='/home/carlos/tmp')
sort_mapped_reads(bwa, bam_fhand.name, key='queryname')
bamfile = pysam.Samfile(bam_fhand.name)
return bamfile
def calculate_distance_distribution(interleave_fhand,
index_fpath,
max_clipping,
max_distance=None,
tempdir=None,
threads=None):
bam_fhand = NamedTemporaryFile(suffix='.bam')
extra_params = ['-a', '-M']
bwa = map_with_bwamem(index_fpath,
interleave_fpath=interleave_fhand.name,
extra_params=extra_params,
threads=threads)
map_process_to_sortedbam(bwa,
bam_fhand.name,
key='queryname',
tempdir=tempdir)
return calculate_distance_distribution_in_bam(bam_fhand,
max_clipping=max_clipping,
max_distance=max_distance)
def classify_chimeras(in_fhand, index_fpath, mate_distance, out_fhand,
chimeras_fhand=None, unknown_fhand=None, tempdir=None,
threads=None, settings=get_setting('CHIMERAS_SETTINGS')):
'''It maps sequences from input files, sorts them and writes to output
files according to its classification'''
bam_fhand = NamedTemporaryFile(suffix='.bam')
extra_params = ['-a', '-M']
bwa = map_with_bwamem(index_fpath, interleave_fpath=in_fhand.name,
extra_params=extra_params)
map_process_to_sortedbam(bwa, bam_fhand.name, key='queryname',
tempdir=tempdir)
for pair, kind in classify_mapped_reads(bam_fhand, settings=settings,
mate_distance=mate_distance):
if kind is NON_CHIMERIC:
write_seqs(pair, out_fhand)
elif kind is CHIMERA and chimeras_fhand is not None:
write_seqs(pair, chimeras_fhand)
elif kind is UNKNOWN and unknown_fhand is not None:
write_seqs(pair, unknown_fhand)
def test_rev_compl_fragmented_reads(self):
reference_seq = GENOME
#with paired_reads.
#f is reversed r is direct
query1 = '>seq10 f\nGGGATCGCAGACCCATCTCGTCAGCATGTACCCTTGCTACATTGAACTT'
query1 += '\n'
query2 = '>seq10 r\nATGTAATACGGGCTAGCCGGGGATGCCGACGATTAAACACGCTGTCATA'
query2 += 'GTAGCGTCTTCCTAGGGTTTTCCCCATGGAATCGGTTATCGTGATACGTTAAATTT\n'
#f is direct, r is reversed
query3 = '>seq11 f\nAAGTTCAATGTAGCAAGGGTACATGCTGACGAGATGGGTCTGCGATCCC'
query3 += '\n'
query4 = '>seq11 r\nAAATTTAACGTATCACGATAACCGATTCCATGGGGAAAACCCTAGGAAG'
query4 += 'ACGCTACTATGACAGCGTGTTTAATCGTCGGCATCCCCGGCTAGCCCGTATTACAT\n'
#f is fragmented in two reference sequences. r mapps completely
query7 = '>seq4 f\nCAAATCATCACCAGACCATGTCCGATCCCGGGAGTCTTTTCCAAGGTGTGC'
query7 += 'TCTTTATCCGGCCCTTGCTCAAGGGTATGTTAAAACGGCAAGAGCTGCCTGAGCGCG\n'
query8 = '>seq4 r\nTGTTCTGCAATCGATACAACGATCGAATTTAATCTGAGTAACTGCCAATTC'
query8 += 'TGAGTAATATTATAGAAAGT\n'
query_f = query1 + query3 + query7
query_r = query2 + query4 + query8
f_fhand = NamedTemporaryFile()
f_fhand.write(query_f)
f_fhand.flush()
r_fhand = NamedTemporaryFile()
r_fhand.write(query_r)
r_fhand.flush()
paired_fpaths = [f_fhand.name, r_fhand.name]
ref_fhand = NamedTemporaryFile()
ref_fhand.write(reference_seq)
ref_fhand.flush()
index_fpath = get_or_create_bwa_index(ref_fhand.name)
bam_fhand = NamedTemporaryFile(suffix='.bam')
bwa = map_with_bwamem(index_fpath, paired_fpaths=paired_fpaths)
map_process_to_bam(bwa, bam_fhand.name)
samfile = pysam.Samfile(bam_fhand.name)
def calculate_distance_distribution(interleave_fhand,
index_fpath,
max_clipping,
max_distance=None,
tempdir=None,
threads=None):
bam_fhand = NamedTemporaryFile(suffix='.bam')
extra_params = ['-a', '-M']
bwa = map_with_bwamem(index_fpath,
interleave_fpath=interleave_fhand.name,
extra_params=extra_params,
threads=threads)
map_process_to_sortedbam(bwa,
bam_fhand.name,
key='queryname',
tempdir=tempdir)
bamfile = AlignmentFile(bam_fhand.name)
stats = {
'outies': IntCounter(),
'innies': IntCounter(),
'others': IntCounter()
}
for grouped_mates in _group_alignments_reads_by_qname(bamfile):
mates = _split_mates(grouped_mates)
for aligned_read1 in _get_totally_mapped_alignments(
mates[0], max_clipping):
for aligned_read2 in _get_totally_mapped_alignments(
mates[1], max_clipping):
if aligned_read1.rname == aligned_read2.rname:
aligned_reads = [aligned_read1, aligned_read2]
distance = _find_distance(aligned_reads)
if _mates_are_outies(aligned_reads):
kind = 'outies'
elif _mates_are_innies(aligned_reads):
kind = 'innies'
else:
kind = 'others'
if max_distance is None or max_distance > distance:
stats[kind][distance] += 1
return stats
def test_rev_compl_fragmented_reads(self):
index_fpath = os.path.join(TEST_DATA_DIR, 'ref_example.fasta')
# with paired_reads.
# f is reversed r is direct
query1 = '>seq10 f\nGGGATCGCAGACCCATCTCGTCAGCATGTACCCTTGCTACATTGAACTT'
query1 += '\n'
query2 = '>seq10 r\nATGTAATACGGGCTAGCCGGGGATGCCGACGATTAAACACGCTGTCATA'
query2 += 'GTAGCGTCTTCCTAGGGTTTTCCCCATGGAATCGGTTATCGTGATACGTTAAATTT\n'
# f is direct, r is reversed
query3 = '>seq11 f\nAAGTTCAATGTAGCAAGGGTACATGCTGACGAGATGGGTCTGCGATCCC'
query3 += '\n'
query4 = '>seq11 r\nAAATTTAACGTATCACGATAACCGATTCCATGGGGAAAACCCTAGGAAG'
query4 += 'ACGCTACTATGACAGCGTGTTTAATCGTCGGCATCCCCGGCTAGCCCGTATTACAT\n'
# f is fragmented in two reference sequences. r mapps completely
query7 = '>seq4 f\nCAAATCATCACCAGACCATGTCCGATCCCGGGAGTCTTTTCCAAGGTGTGC'
query7 += 'TCTTTATCCGGCCCTTGCTCAAGGGTATGTTAAAACGGCAAGAGCTGCCTGAGCGCG\n'
query8 = '>seq4 r\nTGTTCTGCAATCGATACAACGATCGAATTTAATCTGAGTAACTGCCAATTC'
query8 += 'TGAGTAATATTATAGAAAGT\n'
query_f = query1 + query3 + query7
query_r = query2 + query4 + query8
f_fhand = NamedTemporaryFile()
f_fhand.write(query_f)
f_fhand.flush()
r_fhand = NamedTemporaryFile()
r_fhand.write(query_r)
r_fhand.flush()
paired_fpaths = (f_fhand.name, r_fhand.name)
bam_fhand = NamedTemporaryFile(suffix='.bam')
bwa = map_with_bwamem(index_fpath, paired_fpaths=paired_fpaths)
map_process_to_bam(bwa, bam_fhand.name)
samfile = pysam.Samfile(bam_fhand.name)
