def get_deltas_for_mutations(args, infmat, index2gene, heat_params):
print "* Performing permuted mutation data delta selection..."
heat_permutations = permutations.generate_mutation_permutation_heat(
heat_params["heat_fn"], heat_params["sample_file"],
heat_params["gene_file"], index2gene.values(), heat_params["snv_file"],
args.gene_length_file, args.bmr, args.bmr_file, heat_params["cna_file"],
args.gene_order_file, heat_params["cna_filter_threshold"],
heat_params["min_freq"], args.num_permutations, args.parallel)
return get_deltas_from_heat_permutations(infmat, index2gene, heat_permutations, args.parallel)
def get_deltas_for_mutations(args, infmat, index2gene, heat_params):
print "* Performing permuted mutation data delta selection..."
heat_permutations = permutations.generate_mutation_permutation_heat(
heat_params["heat_fn"],
heat_params["sample_file"], heat_params["gene_file"],
index2gene.values(), heat_params["snv_file"], args.gene_length_file,
args.bmr, args.bmr_file, heat_params["cna_file"], args.gene_order_file,
heat_params["cna_filter_threshold"], heat_params["min_freq"],
args.num_permutations, args.parallel)
return get_deltas_from_heat_permutations(infmat, index2gene,
heat_permutations, args.parallel)
def mutation_permutation_significance(args, infmat, infmat_index, G, heat_params):
print "* Performing permuted mutation data statistical significance..."
heat_permutations = permutations.generate_mutation_permutation_heat(
heat_params["heat_fn"], heat_params["sample_file"],
heat_params["gene_file"], infmat_index.values(), heat_params["snv_file"],
args.gene_length_file, args.bmr, args.bmr_file, heat_params["cna_file"],
args.gene_order_file, heat_params["cna_filter_threshold"],
heat_params["min_freq"], args.num_permutations, args.parallel)
return calculate_significance(args, infmat, infmat_index, G, heat_permutations)
def mutation_permutation_significance(args, infmat, infmat_index, G,
heat_params):
print "* Performing permuted mutation data statistical significance..."
heat_permutations = permutations.generate_mutation_permutation_heat(
heat_params["heat_fn"],
heat_params["sample_file"], heat_params["gene_file"],
infmat_index.values(), heat_params["snv_file"], args.gene_length_file,
args.bmr, args.bmr_file, heat_params["cna_file"], args.gene_order_file,
heat_params["cna_filter_threshold"], heat_params["min_freq"],
args.num_permutations, args.parallel)
return calculate_significance(args, infmat, infmat_index, G,
heat_permutations)
