def setUpModule():
global REFERENCE_GENOME
REFERENCE_GENOME = load_reference_genome(get_data('mock_reference_genome.fa'))
if 'CTCCAAAGAAATTGTAGTTTTCTTCTGGCTTAGAGGTAGATCATCTTGGT' != REFERENCE_GENOME['fake'].seq[0:50].upper():
raise AssertionError('fake genome file does not have the expected contents')
global BAM_CACHE
BAM_CACHE = BamCache(get_data('mini_mock_reads_for_events.sorted.bam'))
def setUpModule():
global REFERENCE_GENOME
REFERENCE_GENOME = load_reference_genome(
get_data('mock_reference_genome.fa'))
if ('CTCCAAAGAAATTGTAGTTTTCTTCTGGCTTAGAGGTAGATCATCTTGGT' !=
REFERENCE_GENOME[REF_CHR].seq[0:50].upper()):
raise AssertionError(
'fake genome file does not have the expected contents')
def setUpModule():
warnings.simplefilter('ignore')
global REFERENCE_GENOME
REFERENCE_GENOME = load_reference_genome(REFERENCE_GENOME_FILE)
if 'CTCCAAAGAAATTGTAGTTTTCTTCTGGCTTAGAGGTAGATCATCTTGGT' != REFERENCE_GENOME[
'fake'].seq[0:50].upper():
raise AssertionError(
'fake genome file does not have the expected contents')
def setUpModule():
global REFERENCE_GENOME
REFERENCE_GENOME = load_reference_genome(REFERENCE_GENOME_FILE)
if 'CTCCAAAGAAATTGTAGTTTTCTTCTGGCTTAGAGGTAGATCATCTTGGT' != REFERENCE_GENOME[
'fake'].seq[0:50].upper():
raise AssertionError(
'fake genome file does not have the expected contents')
global BAM_CACHE
BAM_CACHE = BamCache(BAM_INPUT)
def setUpModule():
global annotations, reference_genome, template_metadata, genome_bam_fh, trans_bam_fh, masking
print('setup start')
annotations = load_reference_genes(FULL_REFERENCE_ANNOTATIONS_FILE_JSON)
reference_genome = load_reference_genome(REFERENCE_GENOME_FILE)
template_metadata = load_templates(TEMPLATE_METADATA_FILE)
genome_bam_fh = pysam.AlignmentFile(FULL_BAM_INPUT)
trans_bam_fh = pysam.AlignmentFile(TRANSCRIPTOME_BAM_INPUT)
print('setup loading is complete')
def __init__(self, input_bams, reference_genome, max_event_size=6, buffer=1):
if isinstance(reference_genome, str):
log('loading:', reference_genome, time_stamp=True)
self.reference_genome = load_reference_genome(reference_genome)
else:
self.reference_genome = reference_genome
self._load_bams(input_bams)
self.bpp_cache = dict()
self.max_event_size = max_event_size
self.buffer = buffer
def __init__(self, input_bams, reference_genome, max_event_size=6, buffer=1):
if isinstance(reference_genome, str):
logger.info(f'loading: {reference_genome}')
self.reference_genome = load_reference_genome(reference_genome)
else:
self.reference_genome = reference_genome
self._load_bams(input_bams)
self.bpp_cache = dict()
self.max_event_size = max_event_size
self.buffer = buffer
def main():
args = parse_arguments()
repeat_sequences = sorted(list(set([s.lower() for s in args.repeat_seq])))
log('loading:', args.input)
reference_genome = load_reference_genome(args.input)
comments = [
os.path.basename(__file__),
'input: {}'.format(args.input),
'min_length: {}'.format(args.min_length),
'repeat_seq: {}'.format(', '.join(args.repeat_seq)),
]
log('writing:', args.output)
with open(args.output, 'w') as fh:
for comment in comments:
fh.write('## {}\n'.format(comment))
fh.write('chr\tstart\tend\tname\n')
visited = set()
for chrom, seq in sorted(reference_genome.items()):
if chrom.startswith('chr'):
chrom = chrom[3:]
seq = str(seq.seq).lower()
if seq in visited:
continue
else:
visited.add(seq)
spans = []
for repseq in repeat_sequences:
log(
'finding {}_repeat (min_length: {}), for chr{} (length: {})'.format(
repseq, args.min_length, chrom, len(seq)
)
)
index = 0
while index < len(seq):
next_n = seq.find(repseq, index)
if next_n < 0:
break
index = next_n
while (
index + len(repseq) <= len(seq)
and seq[index : index + len(repseq)] == repseq
):
index += len(repseq)
span = BioInterval(chrom, next_n + 1, index, name='repeat_{}'.format(repseq))
if len(span) >= args.min_length and len(span) >= 2 * len(repseq):
spans.append(span)
log('found', len(spans), 'spans', time_stamp=False)
for span in spans:
fh.write(
'{}\t{}\t{}\t{}\n'.format(
span.reference_object, span.start, span.end, span.name
)
)
def set_example_genes():
result = {}
genes = load_annotations(os.path.join(DATA_DIR, 'example_genes.json'))
seqs = load_reference_genome(os.path.join(DATA_DIR, 'example_genes.fa'))
for chr_genes in genes.values():
for gene in chr_genes:
if gene.name in seqs:
gene.seq = str(seqs[gene.name].seq)
result[gene.name] = gene
if gene.aliases:
for alias in gene.aliases:
result[alias] = gene
print(result.keys())
return result
def setUpModule():
global REFERENCE_GENOME
REFERENCE_GENOME = load_reference_genome(get_data('mock_reference_genome.fa'))
if 'CTCCAAAGAAATTGTAGTTTTCTTCTGGCTTAGAGGTAGATCATCTTGGT' != REFERENCE_GENOME['fake'].seq[0:50].upper():
raise AssertionError('fake genome file does not have the expected contents')
global BAM_CACHE
BAM_CACHE = BamCache(get_data('mini_mock_reads_for_events.sorted.bam'))
global FULL_BAM_CACHE
FULL_BAM_CACHE = BamCache(get_data('mock_reads_for_events.sorted.bam'))
global READS
READS = {}
for read in BAM_CACHE.fetch('reference3', 1, 8000):
if read.qname not in READS:
READS[read.qname] = [None, None]
if read.is_supplementary:
continue
if read.is_read1:
READS[read.qname][0] = read
else:
READS[read.qname][1] = read
