FilePayload(file_access='controlled',
file_name=file.get('file_name'),
md5sum=md5sum(file_path),
file_type=get_file_type(file.get('file_name')),
file_size=os.stat(file_path).st_size))
if os.path.isfile(idx_file_path):
song_payload.add_file_payload(
FilePayload(file_access='controlled',
file_name=idx_file,
md5sum=md5sum(idx_file_path),
file_type=get_file_type(idx_file),
file_size=os.stat(idx_file_path).st_size))
file_path = os.path.join(input_dir, metadata_file_name)
song_payload.add_file_payload(
FilePayload(file_access='open',
file_name=metadata_file_name,
md5sum=md5sum(file_path),
file_type=get_file_type(metadata_file_name),
file_size=os.stat(file_path).st_size))
song_payload.to_json_file(output_file)
save_output_json({
'payload':
'payload.json',
'payload_json':
json.load(open(os.path.join(input_dir, 'payload.json')))
})
try:
#print subprocess.check_output(['icgc-storage-client', '--profile', 'aws', 'upload','--file', file_, '--object-id', object_id, '--md5', file_md5sum, '--force'])
pass
#metadata step
if file_.endswith('.xml'):
#print subprocess.check_output(['aws', '--profile', 'amazon', 's3', 'cp', file_, os.path.join('s3://oicr.icgc.meta/metadata/', object_id)])
pass
except Exception, e:
with open('jt.log', 'w') as f:
f.write(str(e))
sys.exit(1)
task_stop = int(time.time())
output_json = {
'file': file_,
'allowed_upload': run,
'file_md5sum': file_md5sum,
'idx_file': idx_file_,
'idx_file_md5sum': idx_file_md5sum,
'file_size': file_size,
'idx_file_size': idx_file_size,
'runtime': {
'task_start': task_start,
'task_stop': task_stop
}
}
save_output_json(output_json)
subprocess.check_output([
'docker', 'run', '--net=host', '-e', 'ACCESSTOKEN', '-e',
'STORAGEURL=' + os.environ.get('STORAGEURL_AWS'), '-e',
'METADATAURL=' + os.environ.get('METADATAURL_AWS'), '-v',
input_directory + ':/app', upload_container, 'upload', '-s', study_id,
'-u',
os.environ.get('METADATAURL_AWS'), '-p', '/app/' + payload, '-o',
'manifest.txt', '-j', 'manifest.json', '-d', '/app/'
])
return json.load(open(os.path.join(input_directory, 'manifest.json')))
task_dict = get_task_dict(sys.argv[1])
cwd = os.getcwd()
payloads = task_dict.get('input').get('payloads')
input_directory = task_dict.get('input').get('input_directory')
study_id = task_dict.get('input').get('study_id')
task_start = int(time.time())
manifests = []
if study_id in allowed_codes:
for i in range(0, len(payloads)):
manifests.append(upload_file(input_directory, study_id, payloads[i]))
save_output_json({'manifests': manifests})
input_dir = task_dict.get('input').get('input_dir')
study_id = task_dict.get('input').get('study_id')
upload_container = "quay.io/oicr/dckr_song_upload:latest"
song_server = os.environ.get('SONG_SERVER_COLLAB')
subprocess.check_output(['docker', 'pull', upload_container])
subprocess.check_output([
'docker', 'run', '--net=host', '-e', 'ACCESSTOKEN', '-e',
'STORAGEURL=' + os.environ.get('STORAGEURL_COLLAB'), '-e',
'METADATAURL=' + os.environ.get('METADATAURL_COLLAB'), '-v',
input_dir + ':/app', upload_container, 'upload', '-s', study_id, '-u',
song_server, '-p', '/app/' + payload, '-o', 'manifest.txt', '-j',
'manifest.json', '-d', '/app/'
])
manifest = json.load(open(os.path.join(input_dir, 'manifest.json')))
#subprocess.check_output(['docker', 'pull', 'mesosphere/aws-cli'])
#for file in manifest.get('files'):
# if file.get('file_name').endswith('.xml'):
# subprocess.check_output(['docker', 'run',
# '-e', 'AWS_ACCESS_KEY_ID='+os.environ.get('COLLAB_ACCESS_KEY_ID'),
# '-e', 'AWS_SECRET_ACCESS_KEY='+os.environ.get('COLLAB_SECRET_ACCESS_KEY'),
# '-v', input_dir + ':/project',
# 'mesosphere/aws-cli', 's3', 'cp',
# os.path.join('/project', os.path.basename(file.get('file_name'))),
# os.path.join('https://object.cancercollaboratory.org:9080', file.get('object_id'))])
save_output_json({'manifest': manifest})
if not os.path.isfile(os.path.join(out_dir, file_name)):
raise ValueError(
'Object ID: ' + object_id +
' could not be downloaded. Try to download with icgc-storage-client for more info.'
)
# Download normal bam file
object_id = task_dict.get('input').get('normal_bam').get('object_id')
file_name = task_dict.get('input').get('normal_bam').get('file_name')
download_file(object_id, cwd, file_name)
# Download tumour bam files
for i in range(0, len(task_dict.get('input').get('tumour_bams'))):
object_id = task_dict.get('input').get('tumour_bams')[i].get('object_id')
file_name = task_dict.get('input').get('tumour_bams')[i].get('file_name')
download_file(object_id, cwd, file_name)
# Download VCF files
for i in range(0, len(task_dict.get('input').get('vcf_files'))):
file_name = task_dict.get('input').get('vcf_files')[i].get('file_name')
if not task_dict.get('input').get('vcf_files')[i].get('is_smufin'):
object_id = task_dict.get('input').get('vcf_files')[i].get('object_id')
download_file(object_id, cwd, file_name)
else:
copyfile(os.path.join('/icgc_smufin_calls', file_name),
os.path.join(cwd, file_name))
save_output_json({'directory': cwd})
json_input['snv-padding'] = str(task_dict.get('input').get('snv_padding'))
json_input['sv-padding'] = str(task_dict.get('input').get('sv_padding'))
json_input['indel-padding'] = str(task_dict.get('input').get('indel_padding'))
json_input['tumours'] = []
for i in range(0, len(task_dict.get('input').get('tumour_bams'))):
tmp_json = {}
tmp_json['tumourId'] = task_dict.get('input').get('tumour_bams')[i].get(
'file_name').replace('.bam', '')
tmp_json['bamFileName'] = task_dict.get('input').get('tumour_bams')[i].get(
'file_name')
tmp_json['oxoQScore'] = task_dict.get('input').get('tumour_bams')[i].get(
'oxog_score')
tmp_json['associatedVcfs'] = []
for j in range(0, len(task_dict.get('input').get('vcf_files'))):
tmp_json['associatedVcfs'].append(
task_dict.get('input').get('vcf_files')[j].get('file_name'))
json_input['tumours'].append(tmp_json)
json_file = 'run.json'
with open(json_file, 'w') as f:
json.dump(json_input, f, indent=4, sort_keys=True)
subprocess.check_output([
'cwltool', '--debug', '--relax-path-checks', '--non-strict',
'/home/ubuntu/pcawg-minibam/pcawg_minibam_wf.cwl', json_file
])
save_output_json({'output_directory': os.getcwd()})
import os
import hashlib
task_dict = get_task_dict(sys.argv[1])
cwd = os.getcwd()
input_directory = task_dict.get('input').get('input_directory')
normal_bam = task_dict.get('input').get('normal_bam')
tumour_bams = task_dict.get('input').get('tumour_bams')
experiment = task_dict.get('input').get('experiment')
indel_padding = task_dict.get('input').get('indel_padding')
snv_padding = task_dict.get('input').get('snv_padding')
sv_padding = task_dict.get('input').get('sv_padding')
associated_vcfs = task_dict.get('input').get('associated_vcfs')
save_output_json(task_dict)
def create_payload_json(bam, experiment, input_directory, output_file,
associated_vcfs):
donor_payload = DonorPayload(
donor_gender=bam.get('sample').get('donor').get('gender'),
donor_submitter_id=bam.get('sample').get('donor').get('submitter_id'))
experiment_payload = ExperimentPayload(
aligned=experiment.get('aligned'),
library_strategy=experiment.get('library_strategy'),
reference_genome=experiment.get('reference_genome'))
file_path = os.path.join(input_directory,
bam.get('minibam').get('bam_file_name'))
minibam_payload = FilePayload(
