def get_mutation_statistics(self, disease_name, mutation_type):
study_ids = self._get_studies_from_disease_name(disease_name)
if not study_ids:
raise DiseaseNotFoundException
gene_list = self._get_gene_list()
mutation_dict = {}
num_case = 0
for study_id in study_ids:
num_case += cbio_client.get_num_sequenced(study_id)
mutations = cbio_client.get_mutations(study_id, gene_list,
mutation_type)
for g, a in zip(mutations['gene_symbol'],
mutations['amino_acid_change']):
mutation_effect = self.find_mutation_effect(g, a)
if mutation_effect is None:
mutation_effect_key = 'other'
else:
mutation_effect_key = mutation_effect
try:
mutation_dict[g][0] += 1.0
mutation_dict[g][1][mutation_effect_key] += 1
except KeyError:
effect_dict = {'activate': 0.0, 'deactivate': 0.0,
'other': 0.0}
effect_dict[mutation_effect_key] += 1.0
mutation_dict[g] = [1.0, effect_dict]
# Normalize entries
for k, v in mutation_dict.items():
mutation_dict[k][0] /= num_case
effect_sum = numpy.sum(list(v[1].values()))
mutation_dict[k][1]['activate'] /= effect_sum
mutation_dict[k][1]['deactivate'] /= effect_sum
mutation_dict[k][1]['other'] /= effect_sum
return mutation_dict
def test_get_num_sequenced():
num_case = cbio_client.get_num_sequenced('paad_tcga')
assert(num_case > 0)
def get_mutation_statistics(self, disease_name, mutation_type):
study_ids = self._get_studies_from_disease_name(disease_name)
if not study_ids:
raise DiseaseNotFoundException
gene_list = self._get_gene_list()
mutation_dict = {}
num_case = 0
logger.info("Found %d studies and a gene_list of %d elements."
% (len(study_ids), len(gene_list)))
mut_patt = re.compile("([A-Z]+)(\d+)([A-Z]+)")
for study_id in study_ids:
try:
num_case += cbio_client.get_num_sequenced(study_id)
except Exception as e:
continue
mutations = cbio_client.get_mutations(study_id, gene_list,
mutation_type)
if not mutations['gene_symbol']:
logger.info("Found no genes for %s." % study_id)
continue
# Create agents from the results of the search.
agent_dict = {}
for g, a in zip(mutations['gene_symbol'],
mutations['amino_acid_change']):
m = mut_patt.match(a)
if m is None:
logger.warning("Unrecognized residue: %s" % a)
continue
res_from, pos, res_to = m.groups()
try:
mut = MutCondition(pos, res_from, res_to)
except InvalidResidueError:
logger.warning("Invalid residue: %s or %s."
% (res_from, res_to))
continue
ag = Agent(g, db_refs={'HGNC': hgnc_client.get_hgnc_id(g)},
mutations=[mut])
if g not in agent_dict.keys():
agent_dict[g] = []
agent_dict[g].append(ag)
if not agent_dict:
return {}
# Get the most mutated gene.
top_gene = max(agent_dict.keys(),
key=lambda k: len(agent_dict[k]))
logger.info("Found %d genes, with top hit %s for %s."
% (len(agent_dict.keys()), top_gene, study_id))
if top_gene not in mutation_dict.keys():
effect_dict = {'activate': 0, 'deactivate': 0,
'other': 0}
mutation_dict[top_gene] = {'count': 0, 'effects': effect_dict,
'total_effects': 0, 'agents': []}
for agent in agent_dict[top_gene]:
# Get the mutations effects for that gene.
mutation_effect = self.find_mutation_effect(agent)
if mutation_effect is None:
mutation_effect_key = 'other'
else:
mutation_effect_key = mutation_effect
mutation_dict[top_gene]['count'] += 1
mutation_dict[top_gene]['effects'][mutation_effect_key] += 1
mutation_dict[top_gene]['agents'].append(agent)
# Calculate normalized entries
for k, v in mutation_dict.items():
mutation_dict[k]['fraction'] = v['count'] / num_case
for eff in v['effects'].copy().keys():
v['effects'][eff + '_percent'] = v['effects'][eff] / v['count']
return mutation_dict
def test_get_num_sequenced():
num_case = cbio_client.get_num_sequenced('paad_tcga')
assert num_case > 0