def testWorkflow(self):
input_file_1 = Target(uuid="c39ded10-6073-11e4-9803-0800200c9a66")
input_file_2 = Target(uuid="26fd12a2-9096-4af2-a989-9e2f1cb692fe")
workflow = GalaxyWorkflow(
ga_file=get_abspath("../examples/simple_galaxy/SimpleWorkflow.ga"))
task = nebula.tasks.GalaxyWorkflowTask(
"workflow_test",
workflow,
inputs={
'input_file_1': input_file_1,
'input_file_2': input_file_2
},
parameters={"tail_select": {
"lineNum": 3
}})
task_data = task.to_dict()
task_data_str = json.dumps(task_data)
new_task_data = json.loads(task_data_str)
new_task = nebula.tasks.from_dict(new_task_data)
self.assertEqual(len(task.get_inputs()), len(new_task.get_inputs()))
task_inputs = task.get_inputs()
new_task_inputs = new_task.get_inputs()
for k, v in task_inputs.items():
self.assertIn(k, new_task_inputs)
self.assertEqual(v, new_task_inputs[k])
def testWorkflowCheck(self):
input_file_1 = Target(uuid="c39ded10-6073-11e4-9803-0800200c9a66")
input_file_2 = Target(uuid="26fd12a2-9096-4af2-a989-9e2f1cb692fe")
workflow = GalaxyWorkflow(
ga_file=get_abspath("../examples/simple_galaxy/SimpleWorkflow.ga"))
task_ok = nebula.tasks.GalaxyWorkflowTask(
"workflow_ok",
workflow,
inputs={
'input_file_1': input_file_1,
'input_file_2': input_file_2
},
parameters={"tail_select": {
"lineNum": 3
}})
task_missing = nebula.tasks.GalaxyWorkflowTask("workflow_broken",
workflow,
inputs={
'input_file_1':
input_file_1,
"tail_select": {
"lineNum": 3
}
})
self.assertTrue(task_ok.is_valid())
self.assertFalse(task_missing.is_valid())
def testMesosLaunch(self):
input_file_1 = Target("c39ded10-6073-11e4-9803-0800200c9a66"),
input_file_2 = Target("26fd12a2-9096-4af2-a989-9e2f1cb692fe")
doc = FileDocStore(file_path="./test_tmp/docstore")
logging.info("Adding files to object store")
sync_doc_dir("examples/simple_galaxy/",
doc,
uuid_set=[
"c39ded10-6073-11e4-9803-0800200c9a66",
"26fd12a2-9096-4af2-a989-9e2f1cb692fe"
])
task_1 = MD5Task(input_file_1)
md5_service = nebula.service.md5_service.MD5Service(doc)
sched = nebula.scheduler.Scheduler({})
mesos = nebula.drms.mesos_runner.MesosDRMS(
sched, {"mesos": "%s:%s" % (self.host_ip, CONFIG_PARENT_PORT)})
mesos.start()
mesos_md5_service = mesos.deploy_service(md5_service)
job_1 = mesos_md5_service.submit(task_1)
mesos_md5_service.wait([job_1])
print job_1
logging.info("Sleeping for 15")
time.sleep(15)
mesos.stop()
def testNebulaLaunch(self):
input = {
"input_file_1": Target("c39ded10-6073-11e4-9803-0800200c9a66"),
"input_file_2": Target("26fd12a2-9096-4af2-a989-9e2f1cb692fe")
}
parameters = {"tail_select": {"lineNum": 3}}
doc = FileDocStore(file_path=get_abspath("../test_tmp/docstore"))
logging.info("Adding files to object store")
sync_doc_dir("examples/simple_galaxy/",
doc,
uuid_set=[
"c39ded10-6073-11e4-9803-0800200c9a66",
"26fd12a2-9096-4af2-a989-9e2f1cb692fe"
])
logging.info("Creating Task")
workflow = GalaxyWorkflow(
ga_file=get_abspath("../examples/simple_galaxy/SimpleWorkflow.ga"))
task = nebula.tasks.GalaxyWorkflowTask("test_workflow",
workflow,
inputs=input,
parameters=parameters)
service = GalaxyService(docstore=doc,
name="nosetest_galaxy",
galaxy="bgruening/galaxy-stable:dev",
port=20022)
task_path = get_abspath("../test_tmp/test.tasks")
service_path = get_abspath("../test_tmp/test.service")
taskset = TaskGroup()
taskset.append(task)
with open(task_path, "w") as handle:
taskset.store(handle)
with open(service_path, "w") as handle:
service.get_config().set_docstore_config(
cache_path=get_abspath("../test_tmp/cache")).store(handle)
env = dict(os.environ)
if 'PYTHONPATH' in env:
env['PYTHONPATH'] += ":" + get_abspath("../")
else:
env['PYTHONPATH'] = get_abspath("../")
subprocess.check_call(
[get_abspath("../bin/nebula"), "run", service_path, task_path],
env=env)
for i in doc.filter():
print json.dumps(i, indent=4)
def syn_sync(syn, project, docstore, filter=None):
#download reference files from Synapse and populate the document store
for a in syn.chunkedQuery('select * from entity where parentId=="%s"' %
(project)):
if filter is None or a['entity.name'] in filter or a[
'entity.name'].replace(".gz", "") in filter:
ent = syn.get(a['entity.id'])
id = ent.annotations['uuid'][0]
t = Target(uuid=id)
docstore.create(t)
path = docstore.get_filename(t)
name = ent.name
if 'dataPrep' in ent.annotations:
if ent.annotations['dataPrep'][0] == 'gunzip':
subprocess.check_call("gunzip -c %s > %s" %
(ent.path, path),
shell=True)
name = name.replace(".gz", "")
else:
print "Unknown DataPrep"
else:
shutil.copy(ent.path, path)
docstore.update_from_file(t)
meta = {}
meta['name'] = name
meta['uuid'] = id
if 'dataPrep' in meta:
del meta['dataPrep']
docstore.put(id, meta)
def run_upload(args):
#syn = synapseclient.Synapse()
#syn.login()
docstore = from_url(args.out_base)
donor_map = {}
bam_map = {}
for id, doc in docstore.filter(
visible=True,
state='ok',
name=['OUTPUT_BAM_1', 'OUTPUT_BAM_2', 'OUTPUT_BAM_3']):
print doc['name'], doc['tags']
for t in doc['tags']:
ts = t.split(":")
if ts[0] == 'donor':
if ts[1] not in donor_map:
donor_map[ts[1]] = []
donor_map[ts[1]].append(id)
if ts[0] == 'original_bam':
bam_map[ts[1]] = id
if not os.path.exists(args.out):
os.mkdir(args.out)
for key, value in bam_map.items():
t = Target(uuid=value)
path = docstore.get_filename(t)
print "%s\t%s" % (value, path)
os.symlink(path, os.path.join(args.out, "MC3." + key + ".bam"))
def action_cp(args):
rg = nebula.warpdrive.RemoteGalaxy(args.url, args.api_key)
if not args.dir:
docstore = from_url(args.dst)
else:
if not os.path.exists(args.dst):
os.mkdir(args.dst)
for hda in rg.get_history_contents(args.src):
if hda['visible']:
if args.filter is None or re.search(args.filter, hda['name']):
if hda['name'] not in args.exclude:
print hda['name']
meta = rg.get_dataset(hda['id'], 'hda')
if args.dir:
dst_path = os.path.join(args.dst, hda['name'])
rg.download(meta['download_url'], dst_path)
else:
meta['id'] = meta['uuid'] #use the glocal id
hda = Target(uuid=meta['uuid'])
docstore.create(hda)
path = docstore.get_filename(hda)
rg.download(meta['download_url'], path)
docstore.update_from_file(hda)
def run_audit(args):
args = parser.parse_args()
syn = synapseclient.Synapse()
syn.login()
docstore = from_url(args.out_base)
donor_map = {}
for id, ent in docstore.filter(state="ok"):
if ent['visible']:
if docstore.size(Target(id)) > 0:
donor = None
for i in ent['tags']:
t = i.split(":")
if t[0] == "donor":
donor = t[1]
if donor not in donor_map:
donor_map[donor] = {}
donor_map[donor][ent['name']] = id
for ent in synqueue.listAssignments(syn, list_all=True, **config):
if ent['meta']['Submitter_donor_ID'] in donor_map:
print ent['meta']['Submitter_donor_ID'], len(
donor_map[ent['meta']['Submitter_donor_ID']])
def testToolTagging(self):
doc = FileDocStore(file_path=get_abspath("../test_tmp/docstore"))
sync_doc_dir(get_abspath("../examples/simple_galaxy/"),
doc,
uuid_set=[
"c39ded10-6073-11e4-9803-0800200c9a66",
"26fd12a2-9096-4af2-a989-9e2f1cb692fe"
])
input_file_1 = Target(uuid="c39ded10-6073-11e4-9803-0800200c9a66")
input_file_2 = Target(uuid="26fd12a2-9096-4af2-a989-9e2f1cb692fe")
workflow = GalaxyWorkflow(
ga_file=get_abspath("../examples/simple_galaxy/SimpleWorkflow.ga"))
task_tag = nebula.tasks.GalaxyWorkflowTask(
"workflow_ok",
workflow,
inputs={
'input_file_1': input_file_1,
'input_file_2': input_file_2
},
parameters={"tail_select": {
"lineNum": 3
}},
tags=["run:testing"],
tool_tags={
"tail_select": {
"out_file1": ["file:tail"]
},
"concat_out": {
"out_file1": ["file:output"]
}
})
print "Starting Service"
service = GalaxyService(docstore=doc,
name="nosetest_galaxy",
galaxy="bgruening/galaxy-stable:dev",
force=True,
port=20022)
service.start()
self.service = service
job = service.submit(task_tag)
print "JOB", job.get_status()
service.wait([job])
self.assertIn(job.get_status(), ['ok'])
self.assertFalse(service.in_error())
print service.in_error()
def from_dict(data):
request = {}
for k,v in data['inputs'].items():
if isinstance(v,dict) and 'uuid' in v:
request[k] = Target(uuid=v['uuid'])
else:
request[k] = v
return GalaxyWorkflowTask(
data['task_id'], workflow=GalaxyWorkflow(data['workflow']),
inputs=request, parameters=data.get('parameters', None),
tags=data.get('tags', None), tool_tags=data.get('tool_tags', None)
)
def testDocStore(self):
docstore = nebula.docstore.from_url(
get_abspath("../test_tmp/docstore"))
f_uuid = "c39ded10-6073-11e4-9803-0800200c9a66"
t = Target(f_uuid)
docstore.update_from_file(
t,
get_abspath("../examples/simple_galaxy/P04637.fasta"),
create=True)
self.assertEqual(
docstore.size(t),
os.stat(
get_abspath("../examples/simple_galaxy/P04637.fasta")).st_size)
def testCaching(self):
docstore_1 = nebula.docstore.FileDocStore(
get_abspath("../test_tmp/docstore"),
cache_path=get_abspath("../test_tmp/cache_1"))
f_uuid = "c39ded10-6073-11e4-9803-0800200c9a66"
t = Target(f_uuid)
docstore_1.update_from_file(
t,
get_abspath("../examples/simple_galaxy/P04637.fasta"),
create=True)
docstore_2 = nebula.docstore.FileDocStore(
get_abspath("../test_tmp/docstore"),
cache_path=get_abspath("../test_tmp/cache_2"))
self.assertTrue(docstore_2.exists(t))
print docstore_2.get_filename(t)
def sync_doc_dir(path, docstore, uuid_set=None, filter=None):
data_map = scan_doc_dir(path)
#print "Scanned", path, data_map
for uuid, path in data_map.items():
t = Target(uuid)
if not docstore.exists(t):
copy = True
if uuid_set is not None and uuid not in uuid_set:
copy = False
if filter is not None:
with open(path + ".json") as handle:
meta = json.loads(handle.read())
if not filter(meta):
copy = False
if copy:
logging.info("Adding file: %s" % (path))
docstore.update_from_file(t, path, create=True)
with open(path + ".json") as handle:
meta = json.loads(handle.read())
docstore.put(t.id, meta)
def run_extract(args):
docstore = from_url(args.out_base)
for id, ent in docstore.filter(file_ext="vcf", name=[
"muse.vcf", "pindel.vcf", "radia.dna-rna.vcf", "radia.dna.vcf", "somatic_sniper.vcf",
"varscan.indel.vcf", "varscan.snp.vcf", "mutect.vcf"
]):
t = Target(uuid=ent['id'])
if docstore.size(t) > 0:
donor = None
for e in ent['tags']:
tmp = e.split(":")
if tmp[0] == 'donor':
donor = tmp[1]
if donor is not None:
donor_dir = os.path.join(args.out_dir, donor)
if not os.path.exists(donor_dir):
os.makedirs(donor_dir)
print "Found", donor, ent['name']
shutil.copy( docstore.get_filename(t), os.path.join(donor_dir, ent['name']) )
def run_query(docstore, fields, size, filters):
doc = FileDocStore(file_path=docstore)
filter = {}
for k in filters:
tmp=k.split("=")
filter[tmp[0]] = tmp[1]
for id, entry in doc.filter(**filter):
if fields is None or len(fields) == 0:
line = entry
else:
line = dict( (i, entry.get(i, "")) for i in fields )
if size:
size_value = doc.size(Target(uuid=entry['uuid']))
else:
size_value = ""
print size_value, json.dumps(line)
def run_synapse(docstore, parent, workdir):
doc = FileDocStore(file_path=docstore)
syn = synapseclient.Synapse()
syn.login()
for id, entry in doc.filter(visible=True, data_type='galaxy.datatypes.tabular.Vcf'):
if 'tags' in entry:
sample = None
for s in entry['tags']:
tmp = s.split(":")
if tmp[0] == 'sample':
sample = tmp[1]
name = entry['name']
name = re.sub(r'.vcf$', '', name)
file_name = sample + "." + name + ".snv_mnv.vcf"
target = Target(uuid=entry['uuid'])
if doc.size(target) > 0:
src_file = doc.get_filename(target)
dst_file = os.path.join(workdir, file_name)
query = "select * from entity where parentId=='%s' and name=='%s'" % (parent, file_name + ".gz")
r = syn.query(query)['results']
if len(r) == 0:
#print r
print dst_file
shutil.copy(src_file, dst_file)
subprocess.check_call("bgzip %s" % (dst_file), shell=True)
f = synapseclient.File(dst_file + ".gz", parentId = parent, name=file_name + ".gz" )
f.fileType = 'vcf'
f.pipeline = 'UCSC'
f.variant_type = "snv"
f = syn.store(f,
executed="https://github.com/ucsccancer/pcawg_tools"
)
else:
print "Skipping", file_name
def run_uploadprep(args):
if not os.path.exists(args.workdir):
os.mkdir(args.workdir)
doc = from_url(args.out_base)
file_map = {'broad': {}, 'muse': {}, 'broad_tar': {}}
syn = synapseclient.Synapse()
syn.login()
wl_map = {}
job_map = {}
for ent in synqueue.listAssignments(syn, list_all=True, **config):
wl_map[ent['id']] = ent['meta']
uuid_map = {}
uuid_map['broad'] = synqueue.getValues(syn,
"Broad_VCF_UUID",
orSet=lambda x: str(uuid.uuid4()),
**config)
uuid_map['muse'] = synqueue.getValues(syn,
"Muse_VCF_UUID",
orSet=lambda x: str(uuid.uuid4()),
**config)
uuid_map['broad_tar'] = synqueue.getValues(
syn, "Broad_TAR_UUID", orSet=lambda x: str(uuid.uuid4()), **config)
#scan through all of the docs
for id, entry in doc.filter():
donor = None
#look for docs with donor tags
if 'tags' in entry and 'state' in entry and entry['state'] == 'ok':
for s in entry['tags']:
tmp = s.split(":")
if tmp[0] == 'donor':
donor = tmp[1]
if donor is not None and donor in wl_map:
if donor not in job_map:
job_map[donor] = {}
#scan out the job metrics for this job
if 'job' in entry and 'job_metrics' in entry['job']:
job_id = entry['job']['id']
tool_id = entry['job']['tool_id']
job_info = {tool_id: {}}
for met in entry['job']['job_metrics']:
job_info[tool_id][met['name']] = met['raw_value']
job_map[donor][job_id] = job_info
donor_tumor = wl_map[donor][
'Tumour_WGS_alignment_GNOS_analysis_IDs']
#look for the vcf output files
if entry.get('visible', False) and entry.get(
'extension', None) in ["vcf", "vcf_bgzip"]:
pipeline = None
method = None
call_type = None
variant_type = None
#fill out the info depending on which caller created the file
if entry['name'].split('.')[0] in ['MUSE_1']:
pipeline = "muse"
method = entry['name'].replace(".", "-")
variant_type = 'somatic'
call_type = 'snv_mnv'
elif entry['name'].split(".")[0] in [
'broad-dRanger', 'broad-dRanger_snowman',
'broad-snowman', 'broad-mutect'
]:
pipeline = "broad"
method = entry['name'].split(".")[0]
if 'somatic' in entry['name']:
variant_type = 'somatic'
elif 'germline' in entry['name']:
variant_type = 'germline'
else:
raise Exception("Unknown variant type")
if 'snv_mnv.vcf' in entry['name']:
call_type = 'snv_mnv'
elif 'sv.vcf' in entry['name']:
call_type = 'sv'
elif 'indel.vcf' in entry['name']:
call_type = 'indel'
else:
raise Exception("Unknown call type: %s" %
(entry['name']))
else:
raise Exception("Unknown pipeline %s" % (entry['name']))
datestr = datetime.datetime.now().strftime("%Y%m%d")
name = "%s.%s.%s.%s.%s" % (donor_tumor, method, datestr,
variant_type, call_type)
name = re.sub(r'.vcf$', '', name)
if entry['extension'] == 'vcf':
file_name = name + ".vcf"
elif entry['extension'] == 'vcf_bgzip':
file_name = name + ".vcf.gz"
target = Target(uuid=entry['uuid'])
if doc.size(target) > 0:
src_file = doc.get_filename(target)
dst_file = os.path.join(args.workdir, file_name)
shutil.copy(src_file, dst_file)
#if the files wasn't compressed already, go ahead and do that
if entry['extension'] == 'vcf':
subprocess.check_call("bgzip -c %s > %s.gz" %
(dst_file, dst_file),
shell=True)
dst_file = dst_file + ".gz"
#add file to output map
if donor not in file_map[pipeline]:
file_map[pipeline][donor] = []
input_file = os.path.basename(dst_file)
file_map[pipeline][donor].append(input_file)
else:
if entry['name'] == "broad.tar.gz":
target = Target(uuid=entry['uuid'])
src_file = doc.get_filename(target)
file_map['broad_tar'][donor] = [src_file]
timing_map = {}
for donor in job_map:
timing_map[donor] = {}
for job_id in job_map[donor]:
for tool_id in job_map[donor][job_id]:
if tool_id not in timing_map[donor]:
timing_map[donor][tool_id] = []
timing_map[donor][tool_id].append(
job_map[donor][job_id][tool_id])
result_counts = {}
for pipeline, donors in file_map.items():
for donor in donors:
result_counts[donor] = result_counts.get(donor, 0) + 1
#go through every pipeline
for pipeline, donors in file_map.items():
#for that pipeline go through every donor
for donor, files in donors.items():
#we're only outputing data for donors on the work list
if donor in wl_map and result_counts[donor] == 3:
#output the timing json
timing_json = os.path.abspath(
os.path.join(args.workdir,
"%s.%s.timing.json" % (pipeline, donor)))
with open(timing_json, "w") as handle:
handle.write(json.dumps(timing_map[donor]))
#output the uploader script
with open(
os.path.join(args.workdir,
"%s.%s.sh" % (pipeline, donor)),
"w") as handle:
input_file = os.path.basename(dst_file)
urls = [
"%scghub/metadata/analysisFull/%s" %
(wl_map[donor]['Normal_WGS_alignment_GNOS_repos'],
wl_map[donor]['Normal_WGS_alignment_GNOS_analysis_ID']
),
"%scghub/metadata/analysisFull/%s" %
(wl_map[donor]['Tumour_WGS_alignment_GNOS_repos'],
wl_map[donor]
['Tumour_WGS_alignment_GNOS_analysis_IDs'])
]
donor_tumor = wl_map[donor][
'Tumour_WGS_alignment_GNOS_analysis_IDs']
if pipeline in ['broad', 'muse']:
prep_cmd_str = ""
for vcf in files:
prep_cmd_str += "tabix -p vcf %s\n" % (vcf)
prep_cmd_str += "mv %s.tbi %s.idx\n" % (vcf, vcf)
prep_cmd_str += "md5sum %s | awk '{print$1}' > %s.md5\n" % (
vcf, vcf)
prep_cmd_str += "md5sum %s.idx | awk '{print$1}' > %s.idx.md5\n\n" % (
vcf, vcf)
related_uuids = []
for p in uuid_map:
if p != pipeline:
related_uuids.append(uuid_map[p][donor])
submit_cmd_str = "perl -I /opt/gt-download-upload-wrapper/gt-download-upload-wrapper-2.0.11/lib"
submit_cmd_str += " /opt/vcf-uploader/vcf-uploader-2.0.5/gnos_upload_vcf.pl"
submit_cmd_str += " --metadata-urls %s" % (
",".join(urls))
submit_cmd_str += " --vcfs %s " % (",".join(files))
submit_cmd_str += " --vcf-md5sum-files %s " % (
(",".join(("%s.md5" % i for i in files))))
submit_cmd_str += " --vcf-idxs %s" % ((",".join(
("%s.idx" % i for i in files))))
submit_cmd_str += " --vcf-idx-md5sum-files %s" % (
(",".join(("%s.idx.md5" % i for i in files))))
submit_cmd_str += " --outdir %s.%s.dir" % (pipeline,
donor_tumor)
submit_cmd_str += " --key %s " % (args.keyfile)
submit_cmd_str += " --upload-url %s" % (
args.upload_url)
submit_cmd_str += " --study-refname-override %s" % (
args.study)
submit_cmd_str += " --workflow-url '%s'" % args.pipeline_src
submit_cmd_str += " --workflow-src-url '%s'" % args.pipeline_src
submit_cmd_str += " --workflow-name '%s'" % args.pipeline_name
submit_cmd_str += " --workflow-version '%s'" % args.pipeline_version
submit_cmd_str += " --vm-instance-type '%s'" % args.vm_instance_type
submit_cmd_str += " --vm-instance-cores %s" % args.vm_instance_cores
submit_cmd_str += " --vm-instance-mem-gb %s" % args.vm_instance_mem_gb
submit_cmd_str += " --vm-location-code %s" % args.vm_location_code
submit_cmd_str += " --timing-metrics-json %s" % (
timing_json)
submit_cmd_str += " --workflow-file-subset %s" % (
pipeline)
submit_cmd_str += " --related-file-subset-uuids %s" % (
",".join(related_uuids))
submit_cmd_str += " --uuid %s" % (
uuid_map[pipeline][donor])
#submit_cmd_str += " --skip-upload"
if pipeline in ['broad_tar']:
prep_cmd_str = ""
new_files = []
for tar in files:
basename = donor_tumor + ".broad.intermediate"
prep_cmd_str = "%s/remap_broad_tar.py %s %s %s --rename %s %s" % (
os.path.dirname(os.path.abspath(__file__)),
tar, "./", basename, donor, donor_tumor)
new_files.append(basename + ".tar")
related_uuids = []
for p in uuid_map:
if p != pipeline:
related_uuids.append(uuid_map[p][donor])
submit_cmd_str = "perl -I /opt/gt-download-upload-wrapper/gt-download-upload-wrapper-2.0.11/lib"
submit_cmd_str += " /opt/vcf-uploader/vcf-uploader-2.0.5/gnos_upload_vcf.pl"
submit_cmd_str += " --metadata-urls %s" % (
",".join(urls))
submit_cmd_str += " --tarballs %s " % (
",".join(new_files))
submit_cmd_str += " --tarball-md5sum-files %s " % (
(",".join(("%s.md5" % i for i in new_files))))
submit_cmd_str += " --outdir %s.%s.dir" % (pipeline,
donor_tumor)
submit_cmd_str += " --key %s " % (args.keyfile)
submit_cmd_str += " --upload-url %s" % (
args.upload_url)
submit_cmd_str += " --study-refname-override %s" % (
args.study)
submit_cmd_str += " --workflow-url '%s'" % args.pipeline_src
submit_cmd_str += " --workflow-src-url '%s'" % args.pipeline_src
submit_cmd_str += " --workflow-name '%s'" % args.pipeline_name
submit_cmd_str += " --workflow-version '%s'" % args.pipeline_version
submit_cmd_str += " --vm-instance-type '%s'" % args.vm_instance_type
submit_cmd_str += " --vm-instance-cores %s" % args.vm_instance_cores
submit_cmd_str += " --vm-instance-mem-gb %s" % args.vm_instance_mem_gb
submit_cmd_str += " --workflow-file-subset %s" % (
pipeline)
submit_cmd_str += " --timing-metrics-json %s" % (
timing_json)
submit_cmd_str += " --related-file-subset-uuids %s" % (
",".join(related_uuids))
submit_cmd_str += " --uuid %s" % (
uuid_map[pipeline][donor])
#submit_cmd_str += " --skip-upload"
handle.write(
string.Template("""#!/bin/bash
set -ex
${PREP}
${SUBMIT}
echo $$? > $$0.submitted
#pushd ${SUBMIT_DIR}
#gtupload -v -c ${KEY} -u ./manifest.xml
#ECODE=$$?
#popd
#echo $$ECODE > $$0.uploaded
""").substitute(PREP=prep_cmd_str,
SUBMIT=submit_cmd_str,
SUBMIT_DIR=os.path.join(os.path.abspath(args.workdir), "vcf",
pipeline + "." + donor_tumor + ".dir",
uuid_map[pipeline][donor]),
KEY=args.keyfile))
def run_scan(docstore, workdir, keyfile, upload_url, manifest):
doc = FileDocStore(file_path=docstore)
file_map = {
'broad' : {},
'muse' : {}
}
wl_map = {}
with open(manifest) as handle:
reader = csv.DictReader(handle, delimiter="\t")
for row in reader:
wl_map[row['Donor_ID']] = row
for id, entry in doc.filter(visible=True):
if entry.get('extension', None) in ["vcf", "vcf_bgzip"]:
if 'tags' in entry:
sample = None
for s in entry['tags']:
tmp = s.split(":")
if tmp[0] == 'sample':
sample = tmp[1]
pipeline = None
method = None
call_type = None
variant_type = None
if entry['name'] in ['MUSE_1.0rc', 'MUSE_0.9.9.5']:
pipeline = "muse"
method = entry['name'].replace(".", "-")
variant_type = 'somatic'
call_type = 'snv_mnv'
elif entry['name'].split(".")[0] in ['broad-dRanger', 'broad-dRanger_snowman', 'broad-snowman', 'broad-mutect' ]:
pipeline = "broad"
method = entry['name'].split(".")[0]
if 'somatic' in entry['name']:
variant_type = 'somatic'
elif 'germline' in entry['name']:
variant_type = 'germline'
else:
raise Exception("Unknown variant type")
if 'snv_mnv.vcf' in entry['name']:
call_type = 'snv_mnv'
elif 'sv.vcf' in entry['name']:
call_type = 'sv'
elif 'indel.vcf' in entry['name']:
call_type = 'indel'
else:
raise Exception("Unknown call type: %s" % (entry['name']))
else:
raise Exeception("Unknown pipeline %s" % (entry['name']))
datestr = datetime.datetime.now().strftime("%Y%m%d")
name = "%s.%s.%s.%s.%s" % (sample, method, datestr, variant_type, call_type )
name = re.sub(r'.vcf$', '', name)
if entry['extension'] == 'vcf':
file_name = name + ".vcf"
elif entry['extension'] == 'vcf_bgzip':
file_name = name + ".vcf.gz"
print file_name
target = Target(uuid=entry['uuid'])
if doc.size(target) > 0:
src_file = doc.get_filename(target)
dst_file = os.path.join(workdir, file_name)
shutil.copy(src_file, dst_file)
if entry['extension'] == 'vcf':
subprocess.check_call( "bgzip %s" % dst_file, shell=True )
dst_file = dst_file + ".gz"
subprocess.check_call("tabix -p vcf %s" % (dst_file), shell=True)
shutil.move("%s.tbi" % (dst_file), "%s.idx" % (dst_file))
subprocess.check_call("md5sum %s | awk '{print$1}' > %s.md5" % (dst_file, dst_file), shell=True)
subprocess.check_call("md5sum %s.idx | awk '{print$1}' > %s.idx.md5" % (dst_file, dst_file), shell=True)
if sample not in file_map[pipeline]:
file_map[pipeline][sample] = []
input_file = os.path.basename(dst_file)
file_map[pipeline][sample].append(input_file)
for pipeline, samples in file_map.items():
for sample, files in samples.items():
with open( os.path.join(workdir, "%s.%s.sh" %(pipeline, sample)), "w" ) as handle:
input_file = os.path.basename(dst_file)
urls = [
"%scghub/metadata/analysisFull/%s" % (wl_map[sample]['Normal_GNOS_endpoint'], wl_map[sample]['Normal_Analysis_ID']),
"%scghub/metadata/analysisFull/%s" % (wl_map[sample]['Tumour_GNOS_endpoint'], wl_map[sample]['Tumour_Analysis_ID'])
]
cmd_str = "perl /opt/vcf-uploader/gnos_upload_vcf.pl"
cmd_str += " --metadata-urls %s" % (",".join(urls))
cmd_str += " --vcfs %s " % (",".join(files))
cmd_str += " --vcf-md5sum-files %s " % ((",".join( ("%s.md5" % i for i in files) )))
cmd_str += " --vcf-idxs %s" % ((",".join( ("%s.idx" % i for i in files) )))
cmd_str += " --vcf-idx-md5sum-files %s" % ((",".join( ("%s.idx.md5" % i for i in files) )))
cmd_str += " --outdir %s.%s.dir" % (pipeline, sample)
cmd_str += " --key %s " % (keyfile)
cmd_str += " --upload-url %s" % (upload_url)
cmd_str += " --study-refname-override tcga_pancancer_vcf_test"
handle.write("""#!/bin/bash
%s
""" % (cmd_str) )
def run_gen(args):
syn = synapseclient.Synapse()
syn.login()
if args.alt_table is not None:
config['table_id'] = args.alt_table
docstore = from_url(args.out_base)
if args.ref_download:
#download reference files from Synapse and populate the document store
for a in syn.chunkedQuery('select * from entity where parentId=="%s"' %
(REFDATA_PROJECT)):
ent = syn.get(a['entity.id'])
id = ent.annotations['uuid'][0]
t = Target(uuid=id)
docstore.create(t)
path = docstore.get_filename(t)
name = ent.name
if 'dataPrep' in ent.annotations:
if ent.annotations['dataPrep'][0] == 'gunzip':
subprocess.check_call("gunzip -c %s > %s" %
(ent.path, path),
shell=True)
name = name.replace(".gz", "")
else:
print "Unknown DataPrep"
else:
shutil.copy(ent.path, path)
docstore.update_from_file(t)
meta = {}
meta['name'] = name
meta['uuid'] = id
if 'dataPrep' in meta:
del meta['dataPrep']
docstore.put(id, meta)
data_mapping = {
"dbsnp": "dbsnp_132_b37.leftAligned.vcf",
"cosmic": "b37_cosmic_v54_120711.vcf",
"gold_indels":
"Mills_and_1000G_gold_standard.indels.hg19.sites.fixed.vcf",
"phase_one_indels": "1000G_phase1.indels.hg19.sites.fixed.vcf"
}
dm = {}
for k, v in data_mapping.items():
hit = None
for a in docstore.filter(name=v):
hit = a[0]
if hit is None:
raise Exception("%s not found" % (v))
dm[k] = {"uuid": hit}
workflow_2 = GalaxyWorkflow(
ga_file="workflows/Galaxy-Workflow-GATK_CGHub_2.ga")
workflow_3 = GalaxyWorkflow(
ga_file="workflows/Galaxy-Workflow-GATK_CGHub_3.ga")
ref_rename = {"HG19_Broad_variant": "Homo_sapiens_assembly19"}
tasks = TaskGroup()
for ent in synqueue.listAssignments(syn, **config):
bam_set = list(
a[1] for a in ent['meta'].items()
if a[0].startswith("id_") and isinstance(a[1], basestring))
ref_set = set(a[1] for a in ent['meta'].items()
if a[0].startswith("ref_assembly_")
and isinstance(a[1], basestring))
assert (len(ref_set) == 1)
ref_name = ref_set.pop()
if ref_name in ref_rename:
ref_name = ref_rename[ref_name]
hit = None
for a in docstore.filter(name=ref_name + ".fasta"):
hit = a[0]
for a in docstore.filter(name=ref_name + ".fa"):
hit = a[0]
if hit is None:
raise Exception("%s not found" % (ref_name))
workflow_dm = dict(dm)
workflow_dm['reference_genome'] = {"uuid": hit}
if len(bam_set) == 2:
task = GalaxyWorkflowTask(
"workflow_%s" % (ent['id']),
workflow_2,
inputs=workflow_dm,
parameters={
'INPUT_BAM_1': {
"uuid": bam_set[0],
"gnos_endpoint": "cghub.ucsc.edu",
"cred_file": "/tool_data/files/cghub.key"
},
'INPUT_BAM_2': {
"uuid": bam_set[1],
"gnos_endpoint": "cghub.ucsc.edu",
"cred_file": "/tool_data/files/cghub.key"
}
},
tags=["donor:%s" % (ent['meta']['participant_id'])],
tool_tags={
"BQSR_1": {
"output_bam": ["original_bam:%s" % (bam_set[0])]
},
"BQSR_2": {
"output_bam": ["original_bam:%s" % (bam_set[1])]
}
})
tasks.append(task)
elif len(bam_set) == 3:
task = GalaxyWorkflowTask(
"workflow_%s" % (ent['id']),
workflow_3,
inputs=workflow_dm,
parameters={
'INPUT_BAM_1': {
"uuid": bam_set[0],
"gnos_endpoint": "cghub.ucsc.edu",
"cred_file": "/tool_data/files/cghub.key"
},
'INPUT_BAM_2': {
"uuid": bam_set[1],
"gnos_endpoint": "cghub.ucsc.edu",
"cred_file": "/tool_data/files/cghub.key"
},
'INPUT_BAM_3': {
"uuid": bam_set[2],
"gnos_endpoint": "cghub.ucsc.edu",
"cred_file": "/tool_data/files/cghub.key"
}
},
tags=["donor:%s" % (ent['meta']['participant_id'])],
tool_tags={
"BQSR_1": {
"output_bam": ["original_bam:%s" % (bam_set[0])]
},
"BQSR_2": {
"output_bam": ["original_bam:%s" % (bam_set[1])]
},
"BQSR_3": {
"output_bam": ["original_bam:%s" % (bam_set[2])]
}
})
tasks.append(task)
if not os.path.exists("%s.tasks" % (args.out_base)):
os.mkdir("%s.tasks" % (args.out_base))
for data in tasks:
with open("%s.tasks/%s" % (args.out_base, data.task_id),
"w") as handle:
handle.write(json.dumps(data.to_dict()))
if args.create_service:
service = GalaxyService(docstore=docstore,
galaxy="bgruening/galaxy-stable",
sudo=True,
tool_data=args.tool_data,
tool_dir=args.tool_dir,
work_dir=args.work_dir,
smp=[["gatk_bqsr", 12], ["gatk_indel", 24]])
with open("%s.service" % (args.out_base), "w") as handle:
s = service.get_config()
if args.scratch:
print "Using scratch", args.scratch
s.set_docstore_config(cache_path=args.scratch, open_perms=True)
s.store(handle)
def testWorkflowCaching(self):
input = {
"input_file_1": Target("c39ded10-6073-11e4-9803-0800200c9a66"),
"input_file_2": Target("26fd12a2-9096-4af2-a989-9e2f1cb692fe")
}
parameters = {"tail_select": {"lineNum": 3}}
doc = nebula.docstore.FileDocStore(
get_abspath("../test_tmp/docstore"),
cache_path=get_abspath("../test_tmp/cache"))
logging.info("Adding files to object store")
sync_doc_dir(get_abspath("../examples/simple_galaxy/"),
doc,
uuid_set=[
"c39ded10-6073-11e4-9803-0800200c9a66",
"26fd12a2-9096-4af2-a989-9e2f1cb692fe"
])
logging.info("Creating Task")
workflow = GalaxyWorkflow(
ga_file=get_abspath("../examples/simple_galaxy/SimpleWorkflow.ga"))
task = nebula.tasks.GalaxyWorkflowTask("test_workflow",
workflow,
inputs=input,
parameters=parameters,
tags=["run:testing"],
tool_tags={
"tail_select": {
"out_file1":
["file:tail"]
},
"concat_out": {
"out_file1":
["file:output"]
}
})
service = GalaxyService(docstore=doc,
name="nosetest_galaxy",
galaxy="bgruening/galaxy-stable:dev",
force=True,
port=20022)
self.service = service
logging.info("Starting Service")
print "Starting service"
service.start()
self.assertFalse(service.in_error())
logging.info("Starting Tasks")
job = service.submit(task)
self.assertTrue(isinstance(job, TaskJob))
self.assertFalse(service.in_error())
#logging.info("Waiting")
service.wait([job])
found = False
for id, info in doc.filter(tags="file:output"):
logging.info("Found result object: %s size: %d" %
(id, doc.size(info)))
self.assertTrue(doc.size(info) > 0)
found = True
self.assertTrue(found)
self.assertFalse(service.in_error())
self.assertIn(job.get_status(), ['ok'])
def runService(self):
#FIXME: the 'file_path' value is specific to the DiskObjectStore
docstore_path = self.docstore.file_path
if 'lib_data' in self.config:
self.config['lib_data'].append(self.docstore.local_cache_base())
else:
self.config['lib_data'] = [self.docstore.local_cache_base()]
self.rg = run_up(**self.config)
library_id = self.rg.library_find("Imported")['id']
folder_id = self.rg.library_find_contents(library_id, "/")['id']
self.ready = True
logging.info("Galaxy Running")
while self.running:
time.sleep(3)
req = self.get_queued()
if req is not None:
logging.info("Received task request")
uuid_ldda_map = {}
with self.queue_lock:
job_id, job = req
wids = []
for k, v in job.get_inputs().items():
file_path = self.docstore.get_filename(Target(v.id))
file_meta = self.docstore.get(v.id)
file_name = v.id
if 'name' in file_meta:
file_name = file_meta['name']
logging.info("Loading FilePath: %s (%s) %s" %
(v.id, file_name, file_path))
nli = self.rg.library_paste_file(
library_id=library_id,
library_folder_id=folder_id,
name=file_name,
datapath=file_path,
uuid=v.uuid)
if 'id' not in nli:
raise Exception("Failed to load data: %s" %
(str(nli)))
wids.append(nli['id'])
uuid_ldda_map[v.uuid] = nli['id']
#wait for the uploading of the files to finish
while True:
done = True
for w in wids:
d = self.rg.library_get_contents(library_id, w)
if d['state'] == 'error':
raise Exception("Data loading Error")
if d['state'] != 'ok':
logging.debug("Data loading: %s" %
(d['state']))
done = False
break
if done:
break
time.sleep(2)
workflow_data = job.task.to_dict()['workflow']
logging.info("Loading Workflow: %s" %
(workflow_data['uuid']))
self.rg.add_workflow(workflow_data)
wf = GalaxyWorkflow(workflow_data)
print "uuid_map", uuid_ldda_map
request = job.task.get_workflow_request(uuid_ldda_map)
print "Calling Workflow", json.dumps(request)
invc = self.rg.call_workflow(request=request)
print "Called Workflow", json.dumps(invc)
if 'err_msg' in invc:
logging.error("Workflow invocation failed")
job.set_error("Workflow Invocation Failed")
else:
job.history = invc['history']
job.instance_id = invc['uuid']
job.outputs = {}
job.hidden = {}
wf_outputs = wf.get_outputs()
for step in invc['steps']:
if 'outputs' in step:
step_name = step['workflow_step_label'] if step[
'workflow_step_label'] is not None else str(
step['workflow_step_uuid'])
for ok, ov in step['outputs'].items():
output_name = "%s|%s" % (step_name, ok)
if output_name in wf_outputs: #filter out produced items that are not part of the final output
job.outputs[output_name] = ov
else:
job.hidden[output_name] = ov
down_config = {}
#if "work_dir" in self.config:
# down_config['work_dir'] = self.config['work_dir']
run_down(name=self.config['name'],
rm=True,
sudo=self.config.get("sudo", False),
**down_config)
def run_get(docstore, uuid, outpath):
doc = FileDocStore(file_path=docstore)
print doc.get_filename(Target(uuid=uuid))
def run_gen(args):
args = parser.parse_args()
syn = synapseclient.Synapse()
syn.login()
docstore = from_url(args.out_base)
data_mapping = {
"reference_genome": "genome.fa",
"dbsnp": "dbsnp_132_b37.leftAligned.vcf",
"cosmic": "b37_cosmic_v54_120711.vcf",
"gold_indels":
"Mills_and_1000G_gold_standard.indels.hg19.sites.fixed.vcf",
"phase_one_indels": "1000G_phase1.indels.hg19.sites.fixed.vcf",
"centromere": "centromere_hg19.bed"
}
if args.ref_download:
#download reference files from Synapse and populate the document store
for a in syn.chunkedQuery('select * from entity where parentId=="%s"' %
(REFDATA_PROJECT)):
print "found", a['entity.name']
if a['entity.name'] in data_mapping.values(
) or a['entity.name'].replace(".gz", "") in data_mapping.values():
print "loading"
ent = syn.get(a['entity.id'])
id = ent.annotations['uuid'][0]
t = Target(uuid=id)
docstore.create(t)
path = docstore.get_filename(t)
name = ent.name
if 'dataPrep' in ent.annotations:
if ent.annotations['dataPrep'][0] == 'gunzip':
subprocess.check_call("gunzip -c %s > %s" %
(ent.path, path),
shell=True)
name = name.replace(".gz", "")
else:
print "Unknown DataPrep"
else:
shutil.copy(ent.path, path)
docstore.update_from_file(t)
meta = {}
meta['name'] = name
meta['uuid'] = id
if 'dataPrep' in meta:
del meta['dataPrep']
docstore.put(id, meta)
dm = {}
for k, v in data_mapping.items():
hit = None
for a in docstore.filter(name=v):
hit = a[0]
if hit is None:
raise Exception("%s not found" % (v))
dm[k] = {"uuid": hit}
workflow = GalaxyWorkflow(
ga_file="workflows/Galaxy-Workflow-PCAWG_CGHUB.ga")
tasks = TaskGroup()
for ent in synqueue.listAssignments(syn, **config):
#print "'%s'" % (ent['state']), ent['state'] == 'nan', type(ent['state']), type('nan')
if not isinstance(ent['state'], basestring) and isnan(ent['state']):
gnos_endpoint = urlparse(
ent['meta']['Normal_WGS_alignment_GNOS_repos']).netloc
task = GalaxyWorkflowTask(
"workflow_%s" % (ent['id']),
workflow,
inputs=dm,
parameters={
'normal_bam_download': {
"uuid":
ent['meta']['Normal_WGS_alignment_GNOS_analysis_ID'],
"gnos_endpoint":
gnos_endpoint,
"cred_file":
key_map[gnos_endpoint]
},
'tumor_bam_download': {
"uuid":
ent['meta']['Tumour_WGS_alignment_GNOS_analysis_IDs'],
"gnos_endpoint":
gnos_endpoint,
"cred_file":
key_map[gnos_endpoint]
},
'broad_variant_pipeline': {
"broad_ref_dir": "/tool_data/files/refdata",
"sample_id": ent['meta']['Submitter_donor_ID']
}
},
tags=["donor:%s" % (ent['meta']['Submitter_donor_ID'])])
tasks.append(task)
if not os.path.exists("%s.tasks" % (args.out_base)):
os.mkdir("%s.tasks" % (args.out_base))
for data in tasks:
with open("%s.tasks/%s" % (args.out_base, data.task_id),
"w") as handle:
handle.write(json.dumps(data.to_dict()))
state_file = "%s.tasks/%s.state" % (args.out_base, data.task_id)
if os.path.exists(state_file):
os.unlink(state_file)
print "Tasks Created: %s" % (len(tasks))
if args.create_service:
service = GalaxyService(docstore=docstore,
galaxy="bgruening/galaxy-stable",
sudo=args.sudo,
tool_data=os.path.abspath("tool_data"),
tool_dir=os.path.abspath("tools"),
work_dir=args.work_dir,
smp=[["MuSE", 8], ["pindel", 8], ["muTect", 8],
["delly", 4], ["gatk_bqsr", 12],
["gatk_indel", 24], ["bwa_mem", 12],
["broad_variant_pipline", 24]])
with open("%s.service" % (args.out_base), "w") as handle:
s = service.get_config()
if args.scratch:
print "Using scratch", args.scratch
s.set_docstore_config(cache_path=args.scratch, open_perms=True)
s.store(handle)
def testRunSimple(self):
input = {
"input_file_1" :
Target("c39ded10-6073-11e4-9803-0800200c9a66"),
"input_file_2" :
Target("26fd12a2-9096-4af2-a989-9e2f1cb692fe")
}
parameters = {
"tail_select" : {
"lineNum" : 3
}
}
bad_parameters = dict(parameters)
del bad_parameters['tail_select']
doc = FileDocStore(file_path="./test_tmp/docstore")
logging.info("Adding files to object store")
sync_doc_dir("examples/simple_galaxy/", doc,
uuid_set=["c39ded10-6073-11e4-9803-0800200c9a66", "26fd12a2-9096-4af2-a989-9e2f1cb692fe"]
)
logging.info("Creating Task")
workflow = GalaxyWorkflow(ga_file="examples/simple_galaxy/SimpleWorkflow.ga")
task = nebula.tasks.GalaxyWorkflowTask(
"test_workflow", workflow,
inputs=input,
parameters=parameters
)
task_data = task.to_dict()
#make sure the task data can be serialized
task_data_str = json.dumps(task_data)
service = GalaxyService(
docstore=doc,
name="nosetest_galaxy",
galaxy="bgruening/galaxy-stable",
force=True,
port=20022
)
self.service = service
#make sure the generated task is serializable
new_task_data = json.loads(task_data_str)
new_task = nebula.tasks.from_dict(new_task_data)
logging.info("Starting Service")
print "Starting service"
service.start()
self.assertFalse( service.in_error() )
logging.info("Starting Tasks")
job = service.submit(new_task)
self.assertTrue( isinstance(job, TaskJob) )
self.assertFalse( service.in_error() )
#logging.info("Waiting")
service.wait([job])
self.assertIn(job.get_status(), ['ok'])
bad_task = nebula.tasks.GalaxyWorkflowTask(
"test_workflow_bad",
workflow,
inputs=input,
parameters=bad_parameters
)
job = service.submit(bad_task)
service.wait([job])
self.assertIn(job.get_status(), ['error'])
self.assertFalse( service.in_error() )
