def write_output(logger, args):
serializer = SeqNameSerializer()
index = None
fields = MARKER_DEF_FIELDS + ("status", "extended_mask")
try:
index = shelve.open(args.index_file, "r")
logger.info("getting extracted sequences")
extracted_seqs = get_extracted_seqs(args.input_file)
if args.align_file:
logger.info("getting sorting order from %r" % (args.align_file))
idx_map = get_sort_idx(args.align_file)
max_idx = max(idx_map.itervalues())
fields += ("marker_indx",)
with nested(open(args.orig_file), open(args.output_file,'w')) as (f, outf):
outf.write("\t".join(fields)+"\n")
reader = csv.DictReader(f, delimiter="\t")
logger.info("looking up against %r" % args.index_file)
for i, r in enumerate(reader):
label = r['label']
old_rs_label = r['rs_label']
mask = r['mask']
try:
seq, alleles = extracted_seqs[label]
except KeyError:
rs_label = extended_mask = 'None'
status = Status.NO_INFO
else:
extended_mask = build_mask(seq, alleles)
key = build_index_key(seq)
tags = index.get(key, [])
n_matches = len(tags)
if n_matches != 1:
logger.warning("%r maps to %d tags: %r" % (label, n_matches, tags))
rs_label = 'None'
status = Status.NO_MATCH if n_matches == 0 else Status.MULTI_MATCH
else:
rs_label, _, _, _ = serializer.deserialize(tags[0])
if old_rs_label == "None":
status = Status.ADDED
else:
status = (Status.CONFIRMED if rs_label == old_rs_label
else Status.REPLACED)
if rs_label == 'None':
rs_label = label
out_r = [label, rs_label, mask, r['allele_a'], r['allele_b'],
status, extended_mask]
if args.align_file:
try:
idx = idx_map[label]
except KeyError:
max_idx += 1
idx = max_idx
out_r.append(str(idx))
outf.write("%s\n" % "\t".join(out_r))
logger.info("processed %d records overall" % (i+1))
finally:
if index:
index.close()
def get_extracted_seqs(fn):
with open(fn) as f:
reader = csv.reader(f, delimiter="\t")
data = {}
serializer = SeqNameSerializer()
for r in reader:
try:
label, _, _, alleles = serializer.deserialize(r[3])
seq = r[-1].upper()
except IndexError:
raise ValueError("%r: bad input format" % fn)
data[label] = (seq, alleles)
return data
def get_extracted_seqs(fn):
with open(fn) as f:
reader = csv.reader(f, delimiter="\t")
data = {}
serializer = SeqNameSerializer()
for r in reader:
try:
label, _, _, alleles = serializer.deserialize(r[3])
seq = r[-1].upper()
except IndexError:
raise ValueError("%r: bad input format" % fn)
data[label] = (seq, alleles)
return data
def __init__(self,
ref_tag,
outf,
outfmt=DEFAULT_OUTPUT_FORMAT,
flank_size=DEFAULT_FLANK_SIZE,
logger=None):
self.logger = logger or NullLogger()
self.ref_tag = ref_tag
self.outf = outf
self.outfmt = outfmt
self.flank_size = flank_size
self.current_id = None
self.current_hits = []
self.serializer = SeqNameSerializer()
def __init__(self, ref_tag, outf, outfmt=DEFAULT_OUTPUT_FORMAT,
flank_size=DEFAULT_FLANK_SIZE, logger=None):
self.logger = logger or NullLogger()
self.ref_tag = ref_tag
self.outf = outf
self.outfmt = outfmt
self.flank_size = flank_size
self.current_id = None
self.current_hits = []
self.serializer = SeqNameSerializer()
def write_output(reader, outf, logger=None):
logger = logger or NullLogger()
seq_count = 0
name_serializer = SeqNameSerializer()
for r in reader:
fastq_records = build_fastq_records(r['label'],
r['mask'],
name_serializer,
logger=logger)
seq_count += len(fastq_records)
for r in fastq_records:
outf.write("%s\n" % "\n".join(r))
return seq_count
class SnpHitProcessor(object):
HEADER = MARKER_AL_FIELDS
def __init__(self,
ref_tag,
outf,
outfmt=DEFAULT_OUTPUT_FORMAT,
flank_size=DEFAULT_FLANK_SIZE,
logger=None):
self.logger = logger or NullLogger()
self.ref_tag = ref_tag
self.outf = outf
self.outfmt = outfmt
self.flank_size = flank_size
self.current_id = None
self.current_hits = []
self.serializer = SeqNameSerializer()
def process(self, hit):
"""
Process a hit in the SAMMapping format, looking for a perfect
(edit distance, i.e., NM tag value == 0) and unambiguous (mapping
quality > 0) hit.
"""
name = hit.get_name()
id_, allele, snp_offset, _ = self.serializer.deserialize(name)
if id_ != self.current_id:
if self.current_id is not None:
self.dump_current_hits()
self.current_id = id_
self.current_hits = []
nm = hit.tag_value('NM')
seq = hit.get_seq_5()
mapped = hit.is_mapped()
if mapped and nm <= 0 and hit.qual > 0:
snp_pos = hit.get_untrimmed_pos() + snp_offset
chr_code = CHR_CODES.get(hit.tid, 'None')
strand = '-' if hit.is_on_reverse() else '+'
if self.outfmt == DEFAULT_OUTPUT_FORMAT:
r = [
id_, self.ref_tag,
str(chr_code),
str(snp_pos), strand, allele
]
else:
if hit.tid is None:
self.logger.error("%r: can't use null chr for %r output" %
(name, self.outfmt))
return
start = snp_pos - self.flank_size - 1
end = snp_pos + self.flank_size
r = [hit.tid, str(start), str(end), name, '0', strand]
self.current_hits.append(r)
else:
self.logger.info("%r: mapped:%r; NM:%r; qual:%r" %
(name, mapped, nm, hit.qual))
def dump_current_hits(self):
nh = len(self.current_hits)
if nh != 1:
self.logger.warn("hit count for %s: %d != 1" %
(self.current_id, nh))
if nh == 0 and self.outfmt == DEFAULT_OUTPUT_FORMAT:
self.current_hits.append([
self.current_id,
self.ref_tag,
DUMMY_AL_VALUES["chromosome"],
DUMMY_AL_VALUES["pos"],
DUMMY_AL_VALUES["strand"],
DUMMY_AL_VALUES["allele"],
])
if self.outfmt == DEFAULT_OUTPUT_FORMAT:
for hit in self.current_hits:
hit.append(str(nh))
assert hit[0] == self.current_id
self.write_row(hit)
else:
if nh == 1:
self.write_row(self.current_hits[0])
def write_row(self, data):
self.outf.write("\t".join(data) + "\n")
def write_header(self):
if self.outfmt == DEFAULT_OUTPUT_FORMAT:
self.write_row(self.HEADER)
def close_open_handles(self):
self.outf.close()
def write_output(logger, args):
serializer = SeqNameSerializer()
index = None
fields = MARKER_DEF_FIELDS + ("status", "extended_mask")
try:
index = shelve.open(args.index_file, "r")
logger.info("getting extracted sequences")
extracted_seqs = get_extracted_seqs(args.input_file)
if args.align_file:
logger.info("getting sorting order from %r" % (args.align_file))
idx_map = get_sort_idx(args.align_file)
max_idx = max(idx_map.itervalues())
fields += ("marker_indx", )
with nested(open(args.orig_file), open(args.output_file,
'w')) as (f, outf):
outf.write("\t".join(fields) + "\n")
reader = csv.DictReader(f, delimiter="\t")
logger.info("looking up against %r" % args.index_file)
for i, r in enumerate(reader):
label = r['label']
old_rs_label = r['rs_label']
mask = r['mask']
try:
seq, alleles = extracted_seqs[label]
except KeyError:
rs_label = extended_mask = 'None'
status = Status.NO_INFO
else:
extended_mask = build_mask(seq, alleles)
key = build_index_key(seq)
tags = index.get(key, [])
n_matches = len(tags)
if n_matches != 1:
logger.warning("%r maps to %d tags: %r" %
(label, n_matches, tags))
rs_label = 'None'
status = Status.NO_MATCH if n_matches == 0 else Status.MULTI_MATCH
else:
rs_label, _, _, _ = serializer.deserialize(tags[0])
if old_rs_label == "None":
status = Status.ADDED
else:
status = (Status.CONFIRMED if rs_label
== old_rs_label else Status.REPLACED)
if rs_label == 'None':
rs_label = label
out_r = [
label, rs_label, mask, r['allele_a'], r['allele_b'],
status, extended_mask
]
if args.align_file:
try:
idx = idx_map[label]
except KeyError:
max_idx += 1
idx = max_idx
out_r.append(str(idx))
outf.write("%s\n" % "\t".join(out_r))
logger.info("processed %d records overall" % (i + 1))
finally:
if index:
index.close()
class SnpHitProcessor(object):
HEADER = MARKER_AL_FIELDS
def __init__(self, ref_tag, outf, outfmt=DEFAULT_OUTPUT_FORMAT,
flank_size=DEFAULT_FLANK_SIZE, logger=None):
self.logger = logger or NullLogger()
self.ref_tag = ref_tag
self.outf = outf
self.outfmt = outfmt
self.flank_size = flank_size
self.current_id = None
self.current_hits = []
self.serializer = SeqNameSerializer()
def process(self, hit):
"""
Process a hit in the SAMMapping format, looking for a perfect
(edit distance, i.e., NM tag value == 0) and unambiguous (mapping
quality > 0) hit.
"""
name = hit.get_name()
id_, allele, snp_offset, _ = self.serializer.deserialize(name)
if id_ != self.current_id:
if self.current_id is not None:
self.dump_current_hits()
self.current_id = id_
self.current_hits = []
nm = hit.tag_value('NM')
seq = hit.get_seq_5()
mapped = hit.is_mapped()
if mapped and nm <= 0 and hit.qual > 0:
snp_pos = hit.get_untrimmed_pos() + snp_offset
chr_code = CHR_CODES.get(hit.tid, 'None')
strand = '-' if hit.is_on_reverse() else '+'
if self.outfmt == DEFAULT_OUTPUT_FORMAT:
r = [id_, self.ref_tag, str(chr_code), str(snp_pos), strand, allele]
else:
if hit.tid is None:
self.logger.error("%r: can't use null chr for %r output" %
(name, self.outfmt))
return
start = snp_pos - self.flank_size - 1
end = snp_pos + self.flank_size
r = [hit.tid, str(start), str(end), name, '0', strand]
self.current_hits.append(r)
else:
self.logger.info("%r: mapped:%r; NM:%r; qual:%r" %
(name, mapped, nm, hit.qual))
def dump_current_hits(self):
nh = len(self.current_hits)
if nh != 1:
self.logger.warn("hit count for %s: %d != 1" % (self.current_id, nh))
if nh == 0 and self.outfmt == DEFAULT_OUTPUT_FORMAT:
self.current_hits.append([
self.current_id,
self.ref_tag,
DUMMY_AL_VALUES["chromosome"],
DUMMY_AL_VALUES["pos"],
DUMMY_AL_VALUES["strand"],
DUMMY_AL_VALUES["allele"],
])
if self.outfmt == DEFAULT_OUTPUT_FORMAT:
for hit in self.current_hits:
hit.append(str(nh))
assert hit[0] == self.current_id
self.write_row(hit)
else:
if nh == 1:
self.write_row(self.current_hits[0])
def write_row(self, data):
self.outf.write("\t".join(data)+"\n")
def write_header(self):
if self.outfmt == DEFAULT_OUTPUT_FORMAT:
self.write_row(self.HEADER)
def close_open_handles(self):
self.outf.close()
