def transcript_stats(value, args):
if not value:
return
print('Generating transcripts statistics')
loc = args.location
filename = loc + 'transcript_variation.txt.gz'
all = float(count_lines(filename))
enst = count_lines(filename, grep='ENST')
lrg = count_lines(filename, grep='LRG_')
print('All transcripts: %s ' % all)
print('ENST transcripts: %s (%s percent)' % (enst, enst / all))
print('LRG transcripts: %s (%s percent)' % (lrg, lrg / all))
print('Other transcripts: %s (%s percent)' % (all - enst - lrg,
(all - lrg - enst) / all))
def load_transcript_strands(loc):
transcript_strand = {}
filename = loc + 'transcript.txt.gz'
with fast_gzip_read(filename) as f:
for line in tqdm(f, total=count_lines(filename)):
data = line.split('\t')
transcript_strand[data[14]] = int(data[6])
return transcript_strand
def load_chromosome_and_region_names(loc):
seq_region = {}
# seq_region_id, name, cord_system_fk
filename = loc + 'seq_region.txt.gz'
with fast_gzip_read(filename) as f:
for line in tqdm(f, total=count_lines(filename)):
data = line.split('\t')
seq_region[int(data[0])] = data[1]
return seq_region
def load_variation_sources(loc):
sources = {}
# 'source_id', 'name', 'version', 'description', 'url', 'type', 'somatic_status', 'data_types'
filename = loc + 'source.txt.gz'
with fast_gzip_read(filename) as f:
for line in tqdm(f, total=count_lines(filename)):
data = line.split('\t')
sources[int(data[0])] = data[1]
gc.collect()
return sources
def count_spidex():
from multiprocess import count_lines
return count_lines(SPIDEX_LOCATION)
def count_all(tissues_list, path=DEFAULT_PATH, suffix=DEFAULT_SUFFIX):
return sum(
count_lines(path)
for path in expression_file_paths(tissues_list, path, suffix))