def run_msa(queries, input_state):
args = input_state.args
if args['subsample'] != 1:
if args['subsample'] < 1:
subsample_size = int(args['subsample']*len(queries))
elif args['subsample'] > 1:
subsample_size = int(min(len(queries),args['subsample']))
if args['random_subset']:
# Randomize order and take first _subsample_size_ sequences, then reorder
query_ids = [x for x in range(len(queries))]
shuffle(query_ids)
query_ids = sorted(query_ids[0:subsample_size])
queries = list([queries[i] for i in query_ids])
else:
if args['subsample_start'] < 1:
start = int(args['subsample_start']*len(queries))
else:
start = int(args['subsample_start'])
queries = list([queries[i] for i in range(start,start+subsample_size)])
if args['random_order']:
shuffle(queries)
msa_driver = MultipleSequenceDriver(queries, input_state)
# Build composite
msa_driver.build_composite()
# Align sequences (iteratively if given in params)
msa_driver.align()
# Build resultant consensus
consensus_object = msa_driver.build_consensus(args['thresh'],args['type'])
# Write MSA and consensus to file
consensus_fact = ConsensusFilterFactory(msa_driver,consensus_object)
consensus_fact.write(fname=args['build'])
def _extract_domains(targets, is_baseline, input_state, threshold, thresh_type, max_domain_size=15, min_domain_size=1):
# Run MSA
msa_driver = MultipleSequenceDriver(targets, input_state)
msa_driver.build_composite()
msa_driver.align()
# Derive consensus
consensus_obj = msa_driver.build_consensus(threshold,thresh_type)
#consensus_fact = ConsensusFilterFactory(msa_driver.alns,msa_driver.composite, threshold, thresh_type)
#consensus_fact.build_consensus()
#if (is_baseline):
# print('Baseline Consensus: '+str(consensus_fact.consensus).replace('-',''))
#else:
# print('Target Consensus: '+str(consensus_fact.consensus).replace('-',''))
# Extract domains (consensus_obj.consensus is already stripped of - chars)
domainBuilder = DomainSetBuilder(consensus_obj.consensus,max_domain_size,0,True,is_enum=True,allowable_treeseq_types=['complete_tree','incomplete_tree'],min_win=min_domain_size)
domains = domainBuilder.build()
return is_baseline, domains, consensus_obj.consensus