def fix_bams(jira_ticket=None, dry_run=False):
tantalus_api = TantalusApi()
analyses_list = []
storage_name = "singlecellresults"
if jira_ticket is not None:
analyses_list.append(tantalus_api.get('analysis', jira_ticket=jira_ticket, analysis_type__name="align", status="complete"))
else:
# Get all completed align analyses ran with specific version
# the bams associated to these analyses are in the wrong storage account
for version in ('v0.5.2', 'v0.5.3'):
analyses = tantalus_api.list('analysis', analysis_type__name="align", status="complete", version=version)
analyses_list += [a for a in analyses]
for analysis in analyses_list:
jira_ticket = analysis["jira_ticket"]
filename = f'{jira_ticket}/results/bams/metadata.yaml'
logging.info(f'adding file {filename}')
if not dry_run:
file_instance, file_resource = tantalus_api.add_file(storage_name, filename)
# get all bam datasets associated with the jira ticket
bam_datasets = tantalus_api.list(
"sequencedataset",
dataset_type="BAM",
analysis__jira_ticket=jira_ticket,
)
for dataset in bam_datasets:
dataset_id = dataset['id']
logging.info(f'adding file to dataset {dataset_id}')
if not dry_run:
file_resource_ids = dataset['file_resources']
file_resource_ids = file_resource_ids.append(file_resource['id'])
tantalus_api.update('sequencedataset', id=dataset['id'], file_resources=file_resource_ids)
def create_fastq_metadata_yaml(library_id, storage_name, dry_run=False):
"""
Create a metadata.yaml file for a all FQ datasets for a library id.
"""
tantalus_api = TantalusApi()
storage = tantalus_api.get_storage(storage_name)
client = tantalus_api.get_storage_client(storage_name)
for dataset_info, metadata in create_lane_fastq_metadata(
tantalus_api, library_id):
metadata_filename = os.path.join(dataset_info['base_dir'],
'metadata.yaml')
metadata_filepath = tantalus_api.get_filepath(storage_name,
metadata_filename)
metadata_io = io.BytesIO()
metadata_io.write(
yaml.dump(metadata, default_flow_style=False).encode())
logging.info(f'writing metadata to file {metadata_filepath}')
client.write_data(metadata_filename, metadata_io)
logging.info(f'adding {metadata_filepath} to tantalus')
if not dry_run:
file_resource, file_instance = tantalus_api.add_file(
storage_name, metadata_filepath, update=True)
for dataset_id in dataset_info['dataset_ids']:
dataset = tantalus_api.get('sequencedataset', id=dataset_id)
new_file_resources = set(dataset['file_resources'])
new_file_resources.add(file_resource['id'])
tantalus_api.update('sequencedataset',
id=dataset_id,
file_resources=list(new_file_resources))
def add_fastq_metadata_yaml(dataset_id, storage_name, dry_run=False):
"""
Create a metadata.yaml file for a dataset and add to tantalus.
"""
tantalus_api = TantalusApi()
storage = tantalus_api.get_storage(storage_name)
client = tantalus_api.get_storage_client(storage_name)
metadata, base_dir = create_lane_fastq_metadata(tantalus_api, dataset_id)
metadata_filename = os.path.join(base_dir, 'metadata.yaml')
metadata_filepath = tantalus_api.get_filepath(storage_name,
metadata_filename)
metadata_io = io.BytesIO()
metadata_io.write(yaml.dump(metadata, default_flow_style=False).encode())
print(f'writing metadata to file {metadata_filepath}')
client.write_data(metadata_filename, metadata_io)
print(f'adding {metadata_filepath} to tantalus')
if not dry_run:
file_resource, file_instance = tantalus_api.add_file(storage_name,
metadata_filepath,
update=True)
dataset = tantalus_api.get('sequencedataset', id=dataset_id)
new_file_resources = set(dataset['file_resources'])
new_file_resources.add(file_resource['id'])
tantalus_api.update('sequencedataset',
id=dataset_id,
file_resources=list(new_file_resources))