def process_cellenone_dataset(dataset,
storage_name,
tag_name=None,
update=False,
remote_storage_name=None):
assert len(dataset['libraries']) == 1
library_id = dataset['libraries'][0]['library_id']
tantalus_api = TantalusApi()
if not tantalus_api.is_dataset_on_storage(dataset['id'], 'resultsdataset',
storage_name):
raise ValueError(
f"dataset {dataset['id']} not on storage {storage_name}")
# Assume all files in the raw dataset are under the directory:
# single_cell_indexing/Cellenone/Cellenone_images/{date}_{library_id}
filename_prefix = 'single_cell_indexing/Cellenone/Cellenone_images/'
source_dir = None
for file_resource in tantalus_api.get_dataset_file_resources(
dataset['id'], 'resultsdataset'):
if source_dir is None:
if not file_resource['filename'].startswith(filename_prefix):
raise ValueError(
f"file {file_resource['filename']} is not in directory {filename_prefix}"
)
library_subdir = file_resource['filename'].split('/')[3]
if not library_subdir.endswith(library_id):
raise ValueError(
f"file {file_resource['filename']} is not in a directory ending with {library_id}"
)
source_dir = '/'.join(file_resource['filename'].split('/')[:4])
elif not file_resource['filename'].startswith(source_dir):
raise ValueError(
f"file {file_resource['filename']} is not in directory {source_dir}"
)
assert source_dir is not None
source_dir = tantalus_api.get_filepath(storage_name, source_dir)
process_cellenone_images(
library_id,
source_dir,
storage_name,
tag_name=tag_name,
update=update,
remote_storage_name=remote_storage_name,
)
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))
def add_generic_results(filepaths,
storage_name,
results_name,
results_type,
results_version,
sample_ids=(),
library_ids=(),
analysis_pk=None,
recursive=False,
tag_name=None,
update=False,
remote_storage_name=None):
tantalus_api = TantalusApi()
storage_client = tantalus_api.get_storage_client(storage_name)
sample_pks = []
for sample_id in sample_ids:
samples = tantalus_api.get(
"sample",
sample_id=sample_id,
)
sample_pks.append(samples['id'])
library_pks = []
for library_id in library_ids:
librarys = tantalus_api.get(
"dna_library",
library_id=library_id,
)
library_pks.append(librarys['id'])
#Add the file resource to tantalus
file_resource_pks = []
for filepath in filepaths:
if recursive:
logging.info("Recursing directory {}".format(filepath))
filename_prefix = tantalus_api.get_file_resource_filename(
storage_name, filepath)
add_filepaths = []
for filename in storage_client.list(filename_prefix):
add_filepaths.append(
tantalus_api.get_filepath(storage_name, filename))
else:
add_filepaths = [filepath]
for add_filepath in add_filepaths:
logging.info(
"Adding file resource for {} to Tantalus".format(add_filepath))
resource, instance = tantalus_api.add_file(
storage_name=storage_name,
filepath=add_filepath,
update=update,
)
file_resource_pks.append(resource["id"])
results_dataset_fields = dict(
name=results_name,
results_type=results_type,
results_version=results_version,
analysis=analysis_pk,
samples=sample_pks,
libraries=library_pks,
file_resources=file_resource_pks,
)
#Add the dataset to tantalus
try:
results_id = tantalus_api.get(
"results", name=results_dataset_fields["name"])["id"]
except NotFoundError:
results_id = None
if update and results_id is not None:
logging.warning("results dataset {} exists, updating".format(
results_dataset_fields["name"]))
results_dataset = tantalus_api.update("results",
id=results_id,
**results_dataset_fields)
else:
logging.info("creating results dataset {}".format(
results_dataset_fields["name"]))
results_dataset = tantalus_api.get_or_create("results",
**results_dataset_fields)
if tag_name is not None:
tantalus_api.tag(tag_name, resultsdataset_set=[results_id])
logging.info("Succesfully created sequence dataset with ID {}".format(
results_dataset["id"]))
if remote_storage_name is not None:
transfer_files.transfer_dataset(tantalus_api, results_dataset['id'],
"resultsdataset", storage_name,
remote_storage_name)
return results_dataset