def run_query(args):
predicates = get_row_predicates(args)
add_required_columns_to_query(args)
formatter = select_formatter(args)
genotypes_needed = needs_genotypes(args)
gene_needed = needs_gene(args)
try:
subjects = get_subjects(args)
except KeyError:
subjects = []
kwargs = {}
if args.bcolz:
from . import gemini_bcolz
kwargs['variant_id_getter'] = gemini_bcolz.filter
gq = GeminiQuery.GeminiQuery(args.db, out_format=formatter, **kwargs)
gq.run(args.query,
args.gt_filter,
args.show_variant_samples,
args.sample_delim,
predicates,
genotypes_needed,
gene_needed,
args.show_families,
subjects=subjects)
if args.use_header and gq.header:
print(gq.header)
if not args.dgidb:
for row in gq:
print(row)
else:
# collect a list of all the genes that need to be queried
# from DGIdb
genes = defaultdict()
for row in gq:
genes[row['gene']] = True
# collect info from DGIdb
dgidb_info = query_dgidb(genes)
# rerun the query (the cursor is now consumed)
gq = GeminiQuery.GeminiQuery(args.db, out_format=formatter)
gq.run(args.query,
args.gt_filter,
args.show_variant_samples,
args.sample_delim,
predicates,
genotypes_needed,
gene_needed,
args.show_families,
subjects=subjects,
**kwargs)
# report the query results with DGIdb info added at the end.
for row in gq:
print(str(row) + "\t" + str(dgidb_info[row['gene']]))
def get_actionable_mutations(parser, args):
t_n_pairs = gemini_subjects.get_families(args.db)
query = "SELECT variants.chrom, start, end, ref, alt, \
variants.gene, impact, is_somatic, \
gene_summary.in_cosmic_census \
FROM variants, gene_summary \
WHERE variants.is_somatic = 1 \
AND (variants.type = 'snp' \
OR variants.type = 'indel') \
AND (variants.impact_severity = 'HIGH' \
OR variants.impact_severity = 'MED') \
AND variants.chrom = gene_summary.chrom \
AND variants.gene = gene_summary.gene \
AND gene_summary.in_cosmic_census = 1"
# collect the relevant genes and query DGIDB
gq = GeminiQuery.GeminiQuery(args.db)
gq.run(query)
genes = defaultdict()
for row in gq:
genes[row['gene']] = True
# collect info from DGIdb
dgidb_info = query_dgidb(genes)
# now rerun the query and report actionable mutations per DGIDB and COSMIC census.
gq = GeminiQuery.GeminiQuery(args.db)
gq.run(query)
print('\t'.join(['tum_name', 'chrom', 'start', 'end', 'ref', 'alt', \
'gene', 'impact', 'is_somatic', 'in_cosmic_census',
'dgidb_info']))
for row in gq:
for pair in t_n_pairs:
samples = pair.subjects
if len(samples) != 2:
continue
tumor = pair.subjects[0]
normal = pair.subjects[1]
# swap if we guessed the tumor incorrectly
if tumor.affected is False:
tumor, normal = normal, tumor
print('\t'.join(str(s) for s in [tumor.name, row['chrom'], \
row['start'], row['end'], \
row['ref'], row['alt'], \
row['gene'], row['impact'], \
row['is_somatic'], \
row['in_cosmic_census'], \
str(dgidb_info[row['gene']])]))
def run_query(args):
predicates = get_row_predicates(args)
add_required_columns_to_query(args)
formatter = select_formatter(args)
genotypes_needed = needs_genotypes(args)
gene_needed = needs_gene(args)
try:
subjects = get_subjects(args)
except KeyError:
subjects = []
kwargs = {}
if args.bcolz:
from . import gemini_bcolz
kwargs['variant_id_getter'] = gemini_bcolz.filter
gq = GeminiQuery.GeminiQuery(args.db, out_format=formatter, **kwargs)
gq.run(args.query, args.gt_filter, args.show_variant_samples,
args.sample_delim, predicates, genotypes_needed,
gene_needed, args.show_families, subjects=subjects)
if args.use_header and gq.header:
print(gq.header)
if not args.dgidb:
for row in gq:
print(row)
else:
# collect a list of all the genes that need to be queried
# from DGIdb
genes = defaultdict()
for row in gq:
genes[row['gene']] = True
# collect info from DGIdb
dgidb_info = query_dgidb(genes)
# rerun the query (the cursor is now consumed)
gq = GeminiQuery.GeminiQuery(args.db, out_format=formatter)
gq.run(args.query, args.gt_filter, args.show_variant_samples,
args.sample_delim, predicates, genotypes_needed,
gene_needed, args.show_families, subjects=subjects, **kwargs)
# report the query results with DGIdb info added at the end.
for row in gq:
print(str(row) + "\t" + str(dgidb_info[row['gene']]))