for isotopelabel_id, data in allsumionratiodata.iteritems():
allfractionbgratios[isotopelabel_id] = np.median(data)
# second normalization so that the bg-ratios all add to 1
for isotopelabel_id, data in allfractionbgratios.iteritems():
allfractionbgratios[isotopelabel_id] = data / sum(allfractionbgratios.values())
logger.log.debug(('allfractionbgratios are %s' % str(allfractionbgratios)))
for corrects2iquantob in corrects2iquantoblist:
# perform correction for each of the analyzed .hdf5 files.
s2icorrecteddata = corrects2iquantob.performS2Icorrection(allfractionbgratios)
corrects2iquantob.hdf5corrects2iquant.updates2ivalues(s2icorrecteddata)
hdf5corrects2iquant.close()
except ExHa.czException as czEx:
ExHa.reformatException(czEx)
ExHa.addContext(czEx, 'Error during corrects2iquant run')
ExHa.exportError2File(czEx, cfg.parameters['runtime']['datadir'] / Path('errors.error'))
if logger:
logger.log.warning(ExHa.oneLineRepr(czEx))
else:
print ExHa.multiLineRepr(czEx)
except Exception as genEx:
ExHa.reformatException(genEx)
ExHa.addContext(genEx, 'Error during corrects2iquant run')
ExHa.exportError2File(genEx, cfg.parameters['runtime']['datadir'] / 'errors.error')
if logger:
logger.log.warning(ExHa.oneLineRepr(genEx))
else:
print ExHa.multiLineRepr(genEx)
def updateHDF5(self):
"""
@brief controls the updating of the data to the hdf5 results file
@return finalMessage <string>: constructed from the protein data this is the RESULT stored in the DB
"""
pep2unique = self.pep2unique
baseContext = 'updateHDF5: '
context = 'updateHDF5'
try:
# find the peptide sequences that are being imported
usedPeps = self.setsManager.findUsedPeptides()
logger.log.info('there are %s usedPeps' % len(usedPeps))
context = baseContext + 'Retrieving sample IDs'
sample_ids = range(1, len(self.hdfFiles) + 1)
# create proteinset and proteinhit data
starting_protein_group_no = 1
self.setsManager.setProteinGroupNo(starting_protein_group_no)
logger.log.info('adding protein group data to HDF5')
logger.log.debug(str(self.hdfFiles.keys()))
spectrum_id = 0
peptide_id = 0
hdfFileList = self.hdfFiles.keys()
hdfFileList.sort()
for key in hdfFileList:
baseContext += '%s: ' % key
logger.log.log(
logger.PROCESS,
'Integrating Spectrum, Peptide & Quantification data from %s'
% key)
# collect fileData
hdf = self.hdfFiles[key]
hdfObj = hdf.hdfObject
# set the current sample_id from the list of IDs extracted from the DB
current_sample_id = sample_ids.pop()
hdf.acquired_spectra, hdf.mascot_matched_spectra, numIsotopes, runTime = hdfObj.getNumbers(
)
# read the Mascot data
context = baseContext + 'Reading Mascot data'
tmp = hdfObj.readImporterData(usedPeps, hdf)
peptides = tmp[0]
queryDict = tmp[1]
headerArray = tmp[2]
quanArray = tmp[3]
hdf.spectra_in_qc_proteins = len(peptides)
logger.log.debug('getting spectrum_ids')
context = baseContext + 'Retrieving spectrum IDs'
acqTime, hdf.idAct, hdf.quanAct = hdfObj.getTimeAndActivation()
# create blank lists to hold data for writing to hdf5 file
spectrum_list = []
peptide_list = []
quant_list = []
logger.log.info('collating spectrum, peptide & quant data')
pBar = progBar.ProgressBar(widgets=progBar.name_widgets,
maxval=len(queryDict),
name='collate data').start()
for idx, q in enumerate(queryDict):
# loop round all the required spectra
pBar.nextPrimary()
context = baseContext + 'query %i: Setting spectrum data' % q
# extract a spectrum_id from the list
spectrum_id += 1
query = queryDict[q]
spec = int(query['spec_id'])
context = baseContext + 'spectrum %i: Updating DB with spectrum data' % spec
# add spectrum data to spectrum_list
header = self.filterArrayEqual(headerArray, 'spec_id',
spec)
spectrum_list.append(
self.makeSpectrumDict(spectrum_id, current_sample_id,
query, acqTime, header))
# find the appropriate peptides
pepList = peptides[q]
logger.log.debug('there are %s in peplist %s' %
(len(pepList), str(pepList)))
quantFound = 0
# this list will hold all peptides returned from makePeptideDictList and then filter
# those non-rank1 equivalents based on the score of the rank 1 peptide
tmplist = []
for pep in pepList:
# find the sets that the peptide belongs to and add to the peptide_list
sets = self.setsManager.peptide2set[pep['peptide']]
context = baseContext + 'spectrum %i: Creating peptide data entries for hdf5' % spec
tmp, qf = self.makePeptideDictList(
spectrum_id, pep, query, sets, hdf, pep2unique)
tmplist.extend(tmp)
peptide_list += tmp
quantFound += qf
# only keep rank1 equivalent peptides (based on score)
tmplist.sort(key=lambda x: x['rank'])
toprankscore = tmplist[0]['score']
tmplist = [
x for x in tmplist if x['score'] == toprankscore
]
if quantMethID and quantFound:
# extract quantification data for the spectrum
context = baseContext + 'spectrum %i: Creating quantitation data entries for DB' % spec
newquant, deltas = self.makeQuantDictLists(
spectrum_id, spec, tmplist, header, quanArray, hdf)
quant_list += newquant
if quantSource == 'ms2':
context = baseContext + 'spectrum %i: Adding reporter ion delta data' % spec
hdf.addReporterDeltas(deltas)
pBar.finish()
# calculate statistics
context = baseContext + 'Calculating statistics'
hdf.calcReporterStats()
context = baseContext + 'Calculating delta m/z for fragment ions'
context = baseContext + 'Updating sample table (%i)' % current_sample_id
sample_data = hdf.getSampleDataDict(current_sample_id, key,
runTime)
hdf5results.writeSample(sample_data)
self.importData.combineStatistics(hdf)
# write data to HDF5
context = baseContext + 'Updating spectrum table'
logger.log.info('updating HDF5 with spectrum data')
hdf5results.writeSpectrum(spectrum_list)
if quantMethID:
context = baseContext + 'Updating specquant table'
logger.log.info('updating HDF5 with quant data')
hdf5results.writeSpecQuant(quant_list)
context = baseContext + 'Retrieving peptide IDs'
logger.log.info('updating HDF5 with peptide data')
for pepdata in peptide_list:
pepdata['peptide_id'] = peptide_id
peptide_id += 1
context = baseContext + 'Updating peptide table'
hdf5results.writePeptide(peptide_list)
hdf5results.createIndexes()
logger.log.info('finalising HDF5 entries')
hdf5results.writeFDRdata(self.importData.score2fdr, 'peptide')
hdf5results.writeFDRdata(self.importData.proteinscore2fdr,
'protein')
topScoringProteinInfo = self.setsManager.addPeptideSetDBdata(
hdf5results, self.importData.proteinscore2fdr)
runtimedata = self.importData.getSummaryStatisticsDict()
hdf5results.writeStatistics(runtimedata)
finalMessage = 'queries matched: %i / %s (%.1f%%) ' % (
runtimedata['spectra_in_qc_proteins'],
runtimedata['mascot_matched_spectra'],
(runtimedata['spectra_in_qc_proteins'] /
float(runtimedata['mascot_matched_spectra'])) * 100)
finalMessage += 'spectra quantified: %i top hit %s (%s) ' % (
runtimedata['quantified_spectra'], '', '')
finalMessage += 'with total score %f and %i matched peptides (hook AND non hook)' % \
(topScoringProteinInfo[0], topScoringProteinInfo[2])
baseContext = 'updateHDF5: '
context = baseContext + 'Finalising HDF5 entries'
except Exception, genEx:
# make sure that there aren't any permanent changes
ExHa.addContext(genEx, context)
finalMessage = 'Error: %s' % ExHa.oneLineRepr(genEx)
raise
ret = cfg.evaluateCommandLineArgs(sys.argv)
try:
cfg.scalePpmMda()
dataDir = cfg.parameters['runtime']['datadir']
logParam = cfg.parameters['logging']
logPath = Path(dataDir.joinpath(logParam['logdir']))
if not logPath.exists():
logPath.mkdir(parents=True)
logFile = logPath.joinpath(logParam['logfile'])
logger = Logger(logFile, logParam['loglevel'], logParam['screenlevel'],
False)
logger.setMascotParserLogs()
jobcontrol(cfg, logger)
except ExHa.UsageError as useEx:
ExHa.reformatException(useEx)
print useEx.context
except Exception as genEx:
ExHa.reformatException(genEx)
errorFile = Path(cfg.parameters['runtime']['hdf5file']).stem + '.error'
ExHa.exportError2File(
genEx, cfg.parameters['runtime']['datadir'].joinpath(errorFile))
if logs:
logs.datlog.warning(ExHa.oneLineRepr(genEx))
else:
print ExHa.multiLineRepr(genEx)
importer.importData.mascot_matched_spectra)
logger.log.info('Total Spectra Matched = %6i' %
importer.importData.spectra_in_qc_proteins)
logger.log.info('Total Spectra w Quant = %6i' %
importer.importData.quantified_spectra)
logger.log.info('Total Spectra All Rep = %6i' %
importer.importData.numSpectraAllReporters)
times = sw.stop()
logger.log.info(sw.format())
hdf5results.close()
except ExHa.UsageError as useEx:
ExHa.reformatException(useEx)
logger.log.warning(ExHa.oneLineRepr(useEx))
except Exception as genEx:
# error
if logger:
logger.log.warning(ExHa.oneLineRepr(genEx))
print ExHa.multiLineRepr(genEx)
else:
print ExHa.multiLineRepr(genEx)
if cfg:
ExHa.exportError2File(genEx,
dataDir.joinpath(resultfile.stem + '.error'))
else:
ExHa.exportError2File(genEx, dataDir.joinpath('errors.error'))
sys.exit(ExHa.oneLineRepr(genEx))
