def run_clearcut(session, args):
if args.clone_ids is not None:
clones = session.query(Clone.id).filter(
Clone.id.in_(args.clone_ids))
else:
if args.subject_ids is not None:
clones = session.query(Clone.id).filter(
Clone.subject_id.in_(args.subject_ids))
else:
clones = session.query(Clone.id)
if not args.force:
clones = clones.filter(Clone.tree.is_(None))
clones = [c.id for c in clones]
mod_log.make_mod('clone_tree', session=session, commit=True,
info=vars(args))
tasks = concurrent.TaskQueue()
logger.info('Creating task queue for clones')
for clone_id in clones:
tasks.add_task(clone_id)
for _ in range(0, args.nproc):
session = config.init_db(args.db_config)
tasks.add_worker(LineageWorker(
session, get_newick,
args.min_mut_copies, args.min_mut_samples,
args.min_seq_copies,
args.min_seq_samples,
args.exclude_stops,
args.full_seq,
post_tree_hook=minimize_tree))
tasks.start()
def run_clones(session, args):
"""Runs the clone-assignment pipeline stage.
:param Session session: The database session
:param Namespace args: The arguments passed to the command
"""
if args.subject_ids is None:
subject_ids = map(lambda s: s.id, session.query(Subject.id).all())
else:
subject_ids = args.subject_ids
mod_log.make_mod('clones', session=session, commit=True, info=vars(args))
if args.regen:
logger.info('Deleting existing clones')
session.query(Clone).filter(
Clone.subject_id.in_(subject_ids)
).delete(synchronize_session=False)
session.commit()
tasks = concurrent.TaskQueue()
for subject_id in subject_ids:
logger.info('Generating task queue for subject {}'.format(
subject_id))
buckets = session.query(
Sequence.subject_id, Sequence.v_gene, Sequence.j_gene,
Sequence.cdr3_num_nts, Sequence._insertions,
Sequence._deletions
).filter(
Sequence.subject_id == subject_id,
Sequence.clone_id.is_(None)
).group_by(
Sequence.subject_id, Sequence.v_gene, Sequence.j_gene,
Sequence.cdr3_num_nts, Sequence._insertions,
Sequence._deletions
)
for bucket in buckets:
tasks.add_task(bucket)
logger.info('Generated {} total tasks'.format(tasks.num_tasks()))
methods = {
'similarity': SimilarityClonalWorker,
'tcells': TCellClonalWorker,
'lineage': LineageClonalWorker,
}
for i in range(0, min(tasks.num_tasks(), args.nproc)):
worker = methods[args.method](
config.init_db(args.db_config), **args.__dict__
)
tasks.add_worker(worker)
tasks.start()
if args.subclones:
run_subclones(session, subject_ids, args)
else:
logger.info('Skipping subclones')
push_clone_ids(session)
session.commit()
def run_sample_stats(session, args):
np.seterr(all='raise')
mod_log.make_mod('sample_stats',
session=session,
commit=True,
info=vars(args))
if args.sample_ids is None:
samples = map(lambda s: s.id, session.query(Sample.id).all())
else:
samples = args.sample_ids
if args.force:
q = session.query(SampleStats).filter(
SampleStats.sample_id.in_(samples))
q.delete(synchronize_session=False)
session.commit()
tasks = concurrent.TaskQueue()
for sample_id in samples:
_queue_tasks(session, sample_id, args.force, tasks)
for i in range(0, args.nproc):
session = config.init_db(args.db_config)
tasks.add_worker(SampleStatsWorker(session))
tasks.start()
session.commit()
def run_selection_pressure(session, args):
mod_log.make_mod('clone_pressure',
session=session,
commit=True,
info=vars(args))
if args.clone_ids is not None:
clones = args.clone_ids
elif args.subject_ids is not None:
clones = map(
lambda c: c.id,
session.query(Clone.id).filter(
Clone.subject_id.in_(args.subject_ids)).all())
else:
clones = map(lambda c: c.id, session.query(Clone.id).all())
clones.sort()
tasks = concurrent.TaskQueue()
logger.info('Creating task queue to calculate selection pressure for {} '
'clones.'.format(len(clones)))
for cid in clones:
tasks.add_task(cid)
for i in range(0, args.nproc):
session = config.init_db(args.db_config)
tasks.add_worker(
SelectionPressureWorker(session, args.baseline_path, args.temp,
args.regen, args.thresholds))
tasks.start()
def run_collapse(session, args):
mod_log.make_mod('collapse', session=session, commit=True,
info=vars(args))
subject_ids = []
for subject in (args.subject_ids or map(
lambda e: e.id, session.query(Subject.id).all()
)):
if session.query(Sample).filter(
Sample.subject_id == subject,
~exists().where(
SequenceCollapse.sample_id == Sample.id
)).first() is None:
logger.info('Subject {} already collapsed. Skipping.'.format(
subject))
else:
logger.info('Resetting collapse info for subject {}'.format(
subject))
samples = session.query(Sample).filter(
Sample.subject_id == subject
).all()
for sample in samples:
session.query(SequenceCollapse).filter(
SequenceCollapse.sample_id == sample.id
).delete(synchronize_session=False)
logger.info('Resetting clone info for subject {}'.format(subject))
session.query(Clone).filter(Clone.subject_id == subject).delete()
subject_ids.append(subject)
session.commit()
logger.info('Creating task queue to collapse {} subjects.'.format(
len(subject_ids)))
tasks = concurrent.TaskQueue()
for subject_id in subject_ids:
buckets = session.query(
Sequence.subject_id, Sequence.v_gene, Sequence.j_gene,
Sequence.cdr3_num_nts, Sequence._insertions, Sequence._deletions
).filter(
Sequence.subject_id == subject_id
).group_by(
Sequence.subject_id, Sequence.v_gene, Sequence.j_gene,
Sequence.cdr3_num_nts, Sequence._insertions, Sequence._deletions
)
for bucket in buckets:
tasks.add_task(bucket)
logger.info('Generated {} total tasks'.format(tasks.num_tasks()))
for i in range(0, min(tasks.num_tasks(), args.nproc)):
tasks.add_worker(CollapseWorker(config.init_db(args.db_config)))
tasks.start()
session.close()
def run_identify(session, args):
mod_log.make_mod('identification',
session=session,
commit=True,
info=vars(args))
session.close()
# Load the germlines from files
v_germlines = VGermlines(args.v_germlines)
j_germlines = JGermlines(args.j_germlines, args.upstream_of_cdr3,
args.anchor_len, args.min_anchor_len)
tasks = concurrent.TaskQueue()
# If metadata is not specified, assume it is "metadata." in the
# directory
meta_fn = args.metadata if args.metadata else os.path.join(
args.sample_dir, 'metadata.tsv')
# Verify the metadata file exists
if not os.path.isfile(meta_fn):
logger.error('Metadata file not found.')
return
with open(meta_fn, 'rU') as fh:
try:
metadata = parse_metadata(session, fh, args.warn_existing,
args.sample_dir)
except MetadataException as ex:
logger.error(ex.message)
return
# Create the tasks for each file
for sample_name in sorted(metadata.keys()):
tasks.add_task({
'path':
os.path.join(args.sample_dir, metadata[sample_name]['file_name']),
'meta':
metadata[sample_name]
})
props = IdentificationProps(**args.__dict__)
lock = mp.Lock()
for i in range(0, min(args.nproc, tasks.num_tasks())):
worker_session = config.init_db(args.db_config)
tasks.add_worker(
IdentificationWorker(worker_session, v_germlines, j_germlines,
props, lock))
tasks.start()
def run_subclones(session, subject_ids, args):
tasks = concurrent.TaskQueue()
for subject_id in subject_ids:
logger.info(
'Generating subclone task queue for subject {}'.format(subject_id))
buckets = session.query(Clone.subject_id, Clone.v_gene, Clone.j_gene,
Clone.cdr3_num_nts).filter(
Clone.subject_id == subject_id).group_by(
Clone.subject_id, Clone.v_gene,
Clone.j_gene, Clone.cdr3_num_nts)
for bucket in buckets:
tasks.add_task(bucket)
logger.info('Generated {} total subclone tasks'.format(tasks.num_tasks()))
for i in range(0, min(tasks.num_tasks(), args.nproc)):
tasks.add_worker(SubcloneWorker(config.init_db(args.db_config)))
tasks.start()
def run_clone_stats(session, args):
"""Runs the clone statistics generation stage of the pipeline.
:param Session session: The database session
:param Namespace args: The arguments passed to the command
"""
mod_log.make_mod('clone_stats',
session=session,
commit=True,
info=vars(args))
if args.clone_ids is not None:
clones = args.clone_ids
elif args.subject_ids is not None:
clones = map(
lambda c: c.id,
session.query(Clone.id).filter(
Clone.subject_id.in_(args.subject_ids)).all())
else:
clones = map(lambda c: c.id, session.query(Clone.id).all())
clones.sort()
if args.regen:
logger.info('Deleting old clone statistics for {} clones'.format(
len(clones)))
session.query(CloneStats).filter(
CloneStats.clone_id.in_(clones)).delete(synchronize_session=False)
session.commit()
tasks = concurrent.TaskQueue()
logger.info('Creating task queue to generate stats for {} clones.'.format(
len(clones)))
for cid in clones:
tasks.add_task(cid)
for i in range(0, args.nproc):
session = config.init_db(args.db_config)
tasks.add_worker(CloneStatsWorker(session))
tasks.start()
def run_clones(session, args):
"""Runs the clone-assignment pipeline stage.
:param Session session: The database session
:param Namespace args: The arguments passed to the command
"""
if args.subject_ids is None:
subject_ids = [s.id for s in session.query(Subject.id)]
else:
subject_ids = args.subject_ids
mod_log.make_mod('clones', session=session, commit=True, info=vars(args))
if not args.skip_regen:
logger.info('Deleting existing clones')
q = session.query(Clone).filter(Clone.subject_id.in_(subject_ids))
if args.gene:
q = q.filter(Clone.v_gene.like(args.gene + '%'))
q.delete(synchronize_session=False)
session.commit()
tasks = concurrent.TaskQueue()
all_buckets = []
for subject_id in subject_ids:
logger.info('Generating task queue for subject {}'.format(subject_id))
buckets = session.query(Sequence.subject_id, Sequence.v_gene,
Sequence.j_gene, Sequence.cdr3_num_nts).filter(
Sequence.subject_id == subject_id,
Sequence.clone_id.is_(None)).group_by(
Sequence.subject_id, Sequence.v_gene,
Sequence.j_gene, Sequence.cdr3_num_nts)
for bucket in buckets:
if not args.gene or bucket.v_gene.startswith(args.gene):
tasks.add_task(bucket)
all_buckets.extend(buckets)
logger.info('Generated {} total tasks'.format(tasks.num_tasks()))
methods = {
'similarity': SimilarityClonalWorker,
'cluster': ClusteringClonalWorker
}
for i in range(0, min(tasks.num_tasks(), args.nproc)):
worker = methods[args.method](config.init_db(args.db_config),
**args.__dict__)
tasks.add_worker(worker)
tasks.start()
session.commit()
if args.reduce_difference:
buckets = session.query(Clone.subject_id, Clone.cdr3_num_nts).filter(
Clone.subject_id.in_(subject_ids)).group_by(
Clone.subject_id, Clone.cdr3_num_nts)
collapse_similar_cdr3s(session, buckets, args.reduce_difference)
else:
logger.info('Skipping reduce since --reduce-differece set to 0')
push_clone_ids(session)
session.commit()
if not args.skip_subclones:
run_subclones(session, subject_ids, args)
else:
logger.info('Skipping subclones')
def run_identify(session, args):
mod_log.make_mod('identification',
session=session,
commit=True,
info=vars(args))
session.close()
# Load the germlines from files
v_germlines = VGermlines(args.v_germlines)
j_germlines = JGermlines(args.j_germlines, args.upstream_of_cdr3,
args.anchor_len, args.min_anchor_len)
tasks = concurrent.TaskQueue()
sample_names = set([])
fail = False
for directory in args.sample_dirs:
# If metadata is not specified, assume it is "metadata.json" in the
# directory
if args.metadata is None:
meta_fn = os.path.join(directory, 'metadata.json')
else:
meta_fn = args.metadata
# Verify the metadata file exists
if not os.path.isfile(meta_fn):
logger.error('Metadata file not found.')
return
with open(meta_fn) as fh:
metadata = json.load(fh)
# Create the tasks for each file
for fn in sorted(metadata.keys()):
if fn == 'all':
continue
meta = SampleMetadata(
metadata[fn], metadata['all'] if 'all' in metadata else None)
if session.query(Sample).filter(
Sample.name == meta.get('sample_name'),
exists().where(
Sequence.sample_id == Sample.id)).first() is not None:
log_f = logger.warning if args.warn_existing else logger.error
log_f('Sample {} already exists. {}'.format(
meta.get('sample_name'),
'Skipping.' if args.warn_existing else 'Cannot continue.'))
fail = True
elif meta.get('sample_name') in sample_names:
logger.error(
'Sample {} exists more than once in metadata.'.format(
meta.get('sample_name')))
return
else:
tasks.add_task({'path': directory, 'fn': fn, 'meta': meta})
sample_names.add(meta.get('sample_name'))
if fail and not args.warn_existing:
logger.error('Encountered errors. Not running any identification.'
' To skip samples that are already in the database '
'use --warn-existing.')
return
lock = mp.Lock()
for i in range(0, min(args.nproc, tasks.num_tasks())):
worker_session = config.init_db(args.db_config)
tasks.add_worker(
IdentificationWorker(worker_session, v_germlines, j_germlines,
args.trim_to, args.max_padding,
args.max_vties,
args.min_similarity / float(100), lock))
tasks.start()
