# Get the genome object from the workspace.
wsClient = Workspace(url=args.wsURL, token=args.token)
try:
# The get() method returns an array of tuples where the first element is
# the object's metadata (which is valid json) and the second element is
# the object's data (which is not valid json).
object = wsClient.get({ 'objects': [ args.genomeref ] })
genome = json.loads(object[0][1])
except WorkspaceServerError as e:
sys.stderr.write('Failed to get genome using reference %s\n' %(args.genomeref))
exit(1)
# Create a worker for running the algorithm.
worker = ProbAnnotationWorker(genome['id'])
# Run the probabilistic annotation algorithm.
try:
# Convert the features in the genome object to a fasta file.
fastaFile = worker.genomeToFasta(genome['features'])
# Run blast using the fasta file.
blastResultFile = worker.runBlast(fastaFile)
# Calculate roleset probabilities.
rolestringTuples = worker.rolesetProbabilitiesMarble(blastResultFile)
# Calculate per-gene role probabilities.
roleProbs = worker.rolesetProbabilitiesToRoleProbabilities(rolestringTuples)
complexesToRoles[complexId].append(roleId)
# Create a dictionary to map a reaction to a list of complexes as defined in the template.
reactionsToComplexes = dict()
for index in range(len(template['reactions'])):
reactionId = template['reactions'][index]['id']
if len(template['reactions'][index]['templatecomplex_refs']) > 0:
reactionsToComplexes[reactionId] = list()
for complexRef in template['reactions'][index][
'templatecomplex_refs']:
# Complex ID is last element in reference.
reactionsToComplexes[reactionId].append(
complexRef.split('/')[-1])
# Create a worker for running the algorithm.
worker = ProbAnnotationWorker(genome['id'])
# Run the probabilistic annotation algorithm.
try:
# Convert the features in the genome object to a fasta file.
fastaFile = worker.genomeToFasta(genome['features'])
# Run blast using the fasta file.
blastResultFile = worker.runBlast(fastaFile)
# Calculate roleset probabilities.
rolestringTuples = worker.rolesetProbabilitiesMarble(blastResultFile)
# Calculate per-gene role probabilities.
roleProbs = worker.rolesetProbabilitiesToRoleProbabilities(
rolestringTuples)
