def _shard_variants(known_args, pipeline_args, pipeline_mode):
# type: (argparse.Namespace, List[str], int) -> List[str]
"""Reads the variants and writes them to VCF shards.
Returns:
The VCF shards directory.
"""
options = pipeline_options.PipelineOptions(pipeline_args)
google_cloud_options = options.view_as(pipeline_options.GoogleCloudOptions)
shard_files_job_name = pipeline_common.generate_unique_name(
_SHARD_VCF_FILES_JOB_NAME)
_update_google_cloud_job_name(google_cloud_options, shard_files_job_name)
vcf_shards_output_dir = filesystems.FileSystems.join(
known_args.annotation_output_dir, _SHARDS_FOLDER)
with beam.Pipeline(options=options) as p:
variants = _read_variants(
known_args.all_patterns, p, known_args, pipeline_mode)
call_names = (variants
| 'CombineCallNames' >>
combine_call_names.CallNamesCombiner())
_ = (variants
| 'DensifyVariants' >> densify_variants.DensifyVariants(
beam.pvalue.AsSingleton(call_names))
| 'WriteToShards' >> write_variants_to_shards.WriteToShards(
vcf_shards_output_dir,
beam.pvalue.AsSingleton(call_names),
known_args.number_of_variants_per_shard))
return [vep_runner_util.format_dir_path(vcf_shards_output_dir) +
_GCS_RECURSIVE_WILDCARD]
def test_write_to_shards_pipeline(self):
with temp_dir.TempDir() as tempdir:
pipeline = TestPipeline()
_ = (pipeline
| Create(self._get_variants())
| 'WriteToShards' >> write_variants_to_shards.WriteToShards(
tempdir.get_path(), ['Sample 1', 'Sample 2']))
pipeline.run()
def _shard_variants(known_args, pipeline_args, pipeline_mode):
# type: (argparse.Namespace, List[str], int) -> List[str]
"""Reads the variants and writes them to VCF shards.
Returns:
The VCF shards directory.
"""
options = pipeline_options.PipelineOptions(pipeline_args)
google_cloud_options = options.view_as(pipeline_options.GoogleCloudOptions)
shard_files_job_name = pipeline_common.generate_unique_name(
_SHARD_VCF_FILES_JOB_NAME)
_update_google_cloud_job_name(google_cloud_options, shard_files_job_name)
vcf_shards_output_dir = filesystems.FileSystems.join(
known_args.annotation_output_dir, _SHARDS_FOLDER)
with beam.Pipeline(options=options) as p:
variants = _read_variants(known_args.all_patterns,
p,
known_args,
pipeline_mode,
pre_infer_headers=False,
keep_raw_sample_names=True,
use_1_based_coordinate=False)
sample_ids = (
variants
| 'CombineSampleIds' >> combine_sample_ids.SampleIdsCombiner()
| 'CombineToList' >> beam.combiners.ToList())
# TODO(tneymanov): Annotation pipeline currently stores sample IDs instead
# of sample names in the the sharded VCF files, which would lead to double
# hashing of samples. Needs to be fixed ASAP.
_ = (variants
| 'DensifyVariants' >> densify_variants.DensifyVariants(
beam.pvalue.AsSingleton(sample_ids))
| 'WriteToShards' >> write_variants_to_shards.WriteToShards(
vcf_shards_output_dir, beam.pvalue.AsSingleton(sample_ids),
known_args.number_of_variants_per_shard))
return [
vep_runner_util.format_dir_path(vcf_shards_output_dir) +
_GCS_RECURSIVE_WILDCARD
]
