output_handle = open(args.write_fastq, "w")
for fastq_file in fastq_files:
file_handle = open(fastq_file, "rU")
#create a parser to parse file handle with seqio
parser = SeqIO.parse(file_handle, "fastq")
for record in parser:
quality = record.letter_annotations["phred_quality"]
badscores = [i for i in quality if i < 20]
if len(badscores) < 3:
record_index = record.description.strip()[-6:]
(accepted_index,
index_distance) = seqmatch.smart_match(record_index,
indices_list,
max_dist=args.index_cutoff)
if accepted_index is not None:
seq = record.seq
constant = str(seq[-7:])
(accepted_constant, constant_distance) = seqmatch.smart_match(
constant, [
READ_CONSTANT,
], max_dist=args.const_cutoff)
if accepted_constant is not None:
time_point = indices_dict[accepted_index]
if time_point not in constant_dists:
constant_dists[time_point] = {}
if constant_distance not in constant_dists[time_point]:
constant_dists[time_point][constant_distance] = 0
if args.write_fastq is not None:
output_handle = open(args.write_fastq, "w")
for fastq_file in fastq_files:
file_handle = open(fastq_file, "rU")
#create a parser to parse file handle with seqio
parser = SeqIO.parse(file_handle,"fastq")
for record in parser:
quality = record.letter_annotations["phred_quality"]
badscores = [i for i in quality if i<20]
if len(badscores) < 3:
record_index = record.description.strip()[-6:]
(accepted_index, index_distance) = seqmatch.smart_match(record_index,indices_list,max_dist=args.index_cutoff)
if accepted_index is not None:
seq = record.seq
constant = str(seq[-7:])
(accepted_constant, constant_distance) = seqmatch.smart_match(constant, [READ_CONSTANT,], max_dist=args.const_cutoff)
if accepted_constant is not None:
time_point = indices_dict[accepted_index]
if time_point not in constant_dists:
constant_dists[time_point] = {}
if constant_distance not in constant_dists[time_point]:
constant_dists[time_point][constant_distance]=0
constant_dists[time_point][constant_distance]+=1
if time_point not in index_dists:
index_dists[time_point] = {}
print "Pickles loaded."
for timepoint in matched_index.keys():
tp_count_dict = {k: 0 for k in barcode_keys}
total = 0
direct = 0
fuzzy = 0
unmatched = 0
print timepoint
for barcode, quality in matched_index[timepoint]:
total += 1
if args.fuzzy_cutoff is None:
(accepted_index,
index_distance) = seqmatch.smart_match(barcode, barcode_keys)
else:
(accepted_index,
index_distance) = seqmatch.smart_match(barcode,
barcode_keys,
max_dist=args.fuzzy_cutoff)
if accepted_index is not None:
if index_distance == 0:
tp_count_dict[accepted_index] += 1
direct += 1
else:
tp_count_dict[accepted_index] += 1
fuzzy += 1
else:
unmatched += 1
