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)
# Calculate whole cell role probabilities.
totalRoleProbs = worker.totalRoleProbabilities(roleProbs)
# Calculate complex probabilities.
complexProbs = worker.complexProbabilities(totalRoleProbs)
# Calculate reaction probabilities.
reactionProbs = worker.reactionProbabilities(complexProbs)
# Cleanup work directory.
worker.cleanup()
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)
# Calculate whole cell role probabilities.
totalRoleProbs = worker.totalRoleProbabilities(roleProbs)
# Calculate complex probabilities.
complexProbs = worker.complexProbabilities(
totalRoleProbs, complexesToRequiredRoles=complexesToRoles)
# Calculate reaction probabilities.
reactionProbs = worker.reactionProbabilities(
complexProbs, rxnsToComplexes=reactionsToComplexes)
