def ranked_vaccine_peptides_with_metadata_from_parsed_args(args):
"""
Computes all the data needed for report generation.
Parameters
----------
args : Namespace
Parsed user args from this run
Returns a dictionary containing 3 items:
- ranked variant/vaccine peptide list
- a dictionary of command-line arguments used to generate it
- patient info object
"""
if hasattr(args, 'input_json_file'):
with open(args.input_json_file) as f:
data = serializable.from_json(f.read())
# the JSON data from the previous run will have the older args saved, which may need to
# be overridden with args from this run (which all be output related)
data['args'].update(vars(args))
# if we need to truncate the variant list based on max_mutations_in_report, do that here
if len(data['variants']) > args.max_mutations_in_report:
data['variants'] = data['variants'][:args.
max_mutations_in_report]
return data
# get various things from user args
mhc_alleles = mhc_alleles_from_args(args)
logger.info("MHC alleles: %s", mhc_alleles)
variants = variant_collection_from_args(args)
logger.info("Variants: %s", variants)
vaxrank_results = run_vaxrank_from_parsed_args(args)
variants_count_dict = vaxrank_results.variant_counts()
assert len(variants) == variants_count_dict['num_total_variants'], \
"Len(variants) is %d but variants_count_dict came back with %d" % (
len(variants), variants_count_dict['num_total_variants'])
if args.output_passing_variants_csv:
variant_metadata_dicts = vaxrank_results.variant_properties(
gene_pathway_check=GenePathwayCheck())
df = pd.DataFrame(variant_metadata_dicts)
df.to_csv(args.output_passing_variants_csv, index=False)
ranked_variants_with_vaccine_peptides = vaxrank_results.ranked_vaccine_peptides
ranked_variants_with_vaccine_peptides_for_report = \
ranked_variants_with_vaccine_peptides[:args.max_mutations_in_report]
patient_info = PatientInfo(
patient_id=args.output_patient_id,
vcf_paths=variants.sources,
bam_path=args.bam,
mhc_alleles=mhc_alleles,
num_somatic_variants=variants_count_dict['num_total_variants'],
num_coding_effect_variants=variants_count_dict[
'num_coding_effect_variants'],
num_variants_with_rna_support=variants_count_dict[
'num_variants_with_rna_support'],
num_variants_with_vaccine_peptides=variants_count_dict[
'num_variants_with_vaccine_peptides'])
# return variants, patient info, and command-line args
data = {
# TODO:
# change this field to 'ranked_variants_with_vaccine_peptides'
# but figure out how to do it in a backwards compatible way
'variants': ranked_variants_with_vaccine_peptides_for_report,
'patient_info': patient_info,
'args': vars(args),
}
logger.info('About to save args: %s', data['args'])
# save JSON data if necessary. as of time of writing, vaxrank takes ~25 min to run,
# most of which is core logic. the formatting is super fast, and it can
# be useful to save the data to be able to iterate just on the formatting
if args.output_json_file:
with open(args.output_json_file, 'w') as f:
f.write(serializable.to_json(data))
logger.info('Wrote JSON report data to %s', args.output_json_file)
return data
def ranked_variant_list_with_metadata(args):
"""
Computes all the data needed for report generation.
Parameters
----------
args : Namespace
Parsed user args from this run
Returns a dictionary containing 3 items:
- ranked variant/vaccine peptide list
- a dictionary of command-line arguments used to generate it
- patient info object
"""
if hasattr(args, 'input_json_file'):
with open(args.input_json_file) as f:
data = serializable.from_json(f.read())
# the JSON data from the previous run will have the older args saved, which may need to
# be overridden with args from this run (which all be output related)
data['args'].update(vars(args))
# if we need to truncate the variant list based on max_mutations_in_report, do that here
if len(data['variants']) > args.max_mutations_in_report:
data['variants'] = data['variants'][:args.
max_mutations_in_report]
return data
# get various things from user args
mhc_alleles = mhc_alleles_from_args(args)
logger.info("MHC alleles: %s", mhc_alleles)
variants = variant_collection_from_args(args)
logger.info("Variants: %s", variants)
# generator that for each variant gathers all RNA reads, both those
# supporting the variant and reference alleles
reads_generator = allele_reads_generator_from_args(args)
mhc_predictor = mhc_binding_predictor_from_args(args)
ranked_list, variants_count_dict = ranked_vaccine_peptides(
reads_generator=reads_generator,
mhc_predictor=mhc_predictor,
vaccine_peptide_length=args.vaccine_peptide_length,
padding_around_mutation=args.padding_around_mutation,
max_vaccine_peptides_per_variant=args.
max_vaccine_peptides_per_mutation,
min_alt_rna_reads=args.min_alt_rna_reads,
min_variant_sequence_coverage=args.min_variant_sequence_coverage,
min_epitope_score=args.min_epitope_score,
num_mutant_epitopes_to_keep=args.num_epitopes_per_peptide,
variant_sequence_assembly=args.variant_sequence_assembly)
ranked_list_for_report = ranked_list[:args.max_mutations_in_report]
patient_info = PatientInfo(
patient_id=args.output_patient_id,
vcf_paths=variants.sources,
bam_path=args.bam,
mhc_alleles=mhc_alleles,
num_somatic_variants=len(variants),
num_coding_effect_variants=variants_count_dict[
'num_coding_effect_variants'],
num_variants_with_rna_support=variants_count_dict[
'num_variants_with_rna_support'],
num_variants_with_vaccine_peptides=variants_count_dict[
'num_variants_with_vaccine_peptides'])
# return variants, patient info, and command-line args
data = {
'variants': ranked_list_for_report,
'patient_info': patient_info,
'args': vars(args),
}
logger.info('About to save args: %s', data['args'])
# save JSON data if necessary. as of time of writing, vaxrank takes ~25 min to run,
# most of which is core logic. the formatting is super fast, and it can
# be useful to save the data to be able to iterate just on the formatting
if args.output_json_file:
with open(args.output_json_file, 'w') as f:
f.write(serializable.to_json(data))
logger.info('Wrote JSON report data to %s', args.output_json_file)
return data
def ranked_variant_list_with_metadata(args):
"""
Computes all the data needed for report generation.
Parameters
----------
args : Namespace
Parsed user args from this run
Returns a dictionary containing 3 items:
- ranked variant/vaccine peptide list
- a dictionary of command-line arguments used to generate it
- patient info object
"""
if hasattr(args, 'input_json_file'):
with open(args.input_json_file) as f:
data = serializable.from_json(f.read())
# the JSON data from the previous run will have the older args saved, which may need to
# be overridden with args from this run (which all be output related)
data['args'].update(vars(args))
# if we need to truncate the variant list based on max_mutations_in_report, do that here
if len(data['variants']) > args.max_mutations_in_report:
data['variants'] = data['variants'][:args.max_mutations_in_report]
return data
# get various things from user args
mhc_alleles = mhc_alleles_from_args(args)
logger.info("MHC alleles: %s", mhc_alleles)
variants = variant_collection_from_args(args)
logger.info("Variants: %s", variants)
# generator that for each variant gathers all RNA reads, both those
# supporting the variant and reference alleles
reads_generator = allele_reads_generator_from_args(args)
mhc_predictor = mhc_binding_predictor_from_args(args)
ranked_list, variants_count_dict = ranked_vaccine_peptides(
reads_generator=reads_generator,
mhc_predictor=mhc_predictor,
vaccine_peptide_length=args.vaccine_peptide_length,
padding_around_mutation=args.padding_around_mutation,
max_vaccine_peptides_per_variant=args.max_vaccine_peptides_per_mutation,
min_alt_rna_reads=args.min_alt_rna_reads,
min_variant_sequence_coverage=args.min_variant_sequence_coverage,
min_epitope_score=args.min_epitope_score,
num_mutant_epitopes_to_keep=args.num_epitopes_per_peptide,
variant_sequence_assembly=args.variant_sequence_assembly)
ranked_list_for_report = ranked_list[:args.max_mutations_in_report]
patient_info = PatientInfo(
patient_id=args.output_patient_id,
vcf_paths=variants.sources,
bam_path=args.bam,
mhc_alleles=mhc_alleles,
num_somatic_variants=len(variants),
num_coding_effect_variants=variants_count_dict['num_coding_effect_variants'],
num_variants_with_rna_support=variants_count_dict['num_variants_with_rna_support'],
num_variants_with_vaccine_peptides=variants_count_dict['num_variants_with_vaccine_peptides']
)
# return variants, patient info, and command-line args
data = {
'variants': ranked_list_for_report,
'patient_info': patient_info,
'args': vars(args),
}
logger.info('About to save args: %s', data['args'])
# save JSON data if necessary. as of time of writing, vaxrank takes ~25 min to run,
# most of which is core logic. the formatting is super fast, and it can
# be useful to save the data to be able to iterate just on the formatting
if args.output_json_file:
with open(args.output_json_file, 'w') as f:
f.write(serializable.to_json(data))
logger.info('Wrote JSON report data to %s', args.output_json_file)
return data