if currentFASTAChecksum != originalFASTAChecksum:
print('MD5 of FASTA used to create chains file: ' + str(originalFASTAChecksum))
print('MD5 of the given FASTA: ' + str(currentFASTAChecksum))
print('These are not the same. Exiting')
assert(False)
assert(args.length == chainCollection.peptideLength)
chainHash = chainCollection.checksum()
bindingScoreTableFile = None
bindingScoreTable = None
if os.path.isfile(args.bindingScoreTable):
bindingScoreTableFile = open(args.bindingScoreTable, 'rb+')
bindingScoreTable = ScoreTable.readExisting(bindingScoreTableFile)
if bindingScoreTable.chainHash != chainHash:
print('checksum for chains used to create binding score table: ' + bindingScoreTable.chainHash.hex())
print('checksum for these chains: ' + chainHash.hex())
print('These are not the same. Exiting')
assert(False)
else:
bindingScoreTableFile = open(args.bindingScoreTable, 'wb+')
bindingScoreTable = ScoreTable.empty(bindingScoreTableFile, ScoreCategory.PAN_AFF, 'H', 1, ' ', args.length, chainHash)
assert(bindingScoreTable.peptideLength == chainCollection.peptideLength)
parser.add_argument('chains')
parser.add_argument('scoreTable')
parser.add_argument('allele')
parser.add_argument('k', type=int)
args = parser.parse_args()
assert (os.path.isfile(args.chains))
assert (os.path.isfile(args.fasta))
assert (os.path.isfile(args.scoreTable))
assert (args.k > 0)
chainCollection = None
with open(args.chains, 'rb') as f:
chainCollection = pickle.load(f)
f = open(args.scoreTable, 'rb')
st = ScoreTable.readExisting(f)
print('alleles: ')
print(st.getAlleles())
assert (args.allele in st.getAlleles())
length = st.peptideLength
n = st.numPeptides
assert (args.k <= n)
print('num peptides: ' + str(n))
pepGen = peptideGenerator(chainCollection, args.fasta, length)
selection = sorted(random.sample(range(0, n), args.k))
scoreIter = st.scoreIter(args.allele)
pepAndScores = extractPeptidesAndScores(scoreIter, pepGen, selection)
for pep, score in pepAndScores:
print(str(pep) + '\t' + str(score))
str(x),
str(THREADS)
]
proc = subprocess.Popen(precomputeCommand,
stdout=subprocess.DEVNULL)
outs, errors = proc.communicate()
additionalScoreFile = None
if allele[2] == 'elute':
additionalScoreFile = open(
additionalPanEluteScoreTablePath, 'rb')
elif allele[2] == 'ba':
additionalScoreFile = open(additionalPanBAScoreTablePath,
'rb')
else:
assert (0)
additionalScoreTable = ScoreTable.readExisting(
additionalScoreFile)
baseScoreTable = None
baseChains = None
baseFasta = None
if usingBase:
baseChainPath = os.path.join(args.baseDirectory,
str(x) + '.chains')
with open(baseChainPath, 'rb') as f:
baseChains = pickle.load(f)
baseScoreFile = None
baseFasta = os.path.join(args.baseDirectory, args.baseFasta)
if allele[0] == 'netmhcPanPrecompute':
if allele[2] == 'elute':
baseScoreFile = open(
os.path.join(args.baseDirectory,
args.netmhcPanScoreDir,
else:
break
"""
"""pepIter = peptideGenerator(chainCollection, fastaPath, pepLen)
for pep in pepIter:
print('>' + ' @ '.join(pep.getHeaders()))
print(pep.getPeptideSequence())
"""
#os.remove('scores.bin')
scorePath = 'scores.bin'
scoreFileObj = None
scoreTable = None
if os.path.isfile(scorePath):
scoreFileObj = open(scorePath, 'rb+')
scoreTable = ScoreTable.readExisting(scoreFileObj)
else:
scoreFileObj = open(scorePath, 'wb+')
scoreTable = ScoreTable.empty(scoreFileObj, 'H', 1, ' ')
"""first_scorer = DummyScorer(0)
second_scorer = DummyScorer(1)
third_scorer = DummyScorer(2)
scoreTable.addAllele(first_scorer, 'A', map(lambda x: x.getPeptideSequence(), peptideGenerator(chainCollection, 'test.fasta', 3)))
scoreTable.addAllele(second_scorer, 'B', map(lambda x: x.getPeptideSequence(), peptideGenerator(chainCollection, 'test.fasta', 3)))
scoreTable.addAllele(third_scorer, 'C', map(lambda x: x.getPeptideSequence(), peptideGenerator(chainCollection, 'test.fasta', 3)))
for peptide, row in itertools.zip_longest(map(lambda x: x.getPeptideSequence(), peptideGenerator(chainCollection, 'test.fasta', 3)), scoreTable):
print('peptide: ' + peptide)
print('row')
print(row)
"""
originalFASTAChecksum = chainCollection.md5
currentFASTAChecksum = fileMD5(args.fasta)
if currentFASTAChecksum != originalFASTAChecksum:
print('MD5 of FASTA used to create chains file: ' +
str(originalFASTAChecksum))
print('MD5 of the given FASTA: ' + str(currentFASTAChecksum))
print('These are not the same. Exiting')
assert (False)
chainHash = chainCollection.checksum()
scoreTableFile = None
scoreTable = None
if os.path.isfile(args.scoreTable):
scoreTableFile = open(args.scoreTable, 'rb+')
scoreTable = ScoreTable.readExisting(scoreTableFile)
if scoreTable.chainHash != chainHash:
print('checksum for chains used to create score table: ' +
scoreTable.chainHash.hex())
print('checksum for these chains: ' + chainHash.hex())
print('These are not the same. Exiting')
assert (False)
else:
scoreTableFile = open(args.scoreTable, 'wb+')
scoreTable = ScoreTable.empty(scoreTableFile, ScoreCategory.AFFINITY, 'H',
1, ' ', args.length, chainHash)
assert (args.length == chainCollection.peptideLength)
assert (scoreTable.peptideLength == chainCollection.peptideLength)
if args.allele in scoreTable.getAlleles():