protected void evaluateIdentification(IDs id)
{
log.Debug("NoExclusion. Scores added, but nothing added to the exclusion list");
// check if the peptide is identified or not
if (id == null)
{
performanceEvaluator.countMS2UnidentifiedAnalyzed();
return;
}
Peptide pep = getPeptideFromIdentification(id); // if it was going to be null, it already returned
// is fragmented
// add decoy or non-existent protein connections
// database.addProteinFromIdentification(pep, id.getParentProteinAccessions());
Double xCorr = id.getXCorr();
Double dCN = id.getDeltaCN();
pep.addScore(xCorr, 0.0, dCN);
performanceEvaluator.evaluateAnalysis(exclusionList, pep);
RetentionTime rt = pep.getRetentionTime();
if (!rtCalcPredictedRT.Keys.Contains(pep.getSequence()))
{
rtCalcPredictedRT.Add(pep.getSequence(), rt.getRetentionTimePeak());
}
ObservedPeptideRtTrackerObject observedPep = new ObservedPeptideRtTrackerObject(pep.getSequence(), id.getScanTime(), id.getXCorr(),
rt.getRetentionTimePeak(), rt.getRetentionTimeStart() + GlobalVar.retentionTimeWindowSize,
RetentionTime.getRetentionTimeOffset(), rtCalcPredictedRT[pep.getSequence()], (rt.IsPredicted() ? 1 : 0));
if ((xCorr > 2.5))
{
// calibrates our retention time alignment if the observed time is different
// from the predicted only if it passes this threshold
calibrateRetentionTime(pep);
}
observedPep.offset = RetentionTime.getRetentionTimeOffset();
peptideIDRT.Add(observedPep);
}
//actual experiment hooked up to the mass spec
public static void RunRealTimeExperiment()
{
PreExperimentSetUp();
Console.WriteLine("Running real time experiment");
double startTime = getCurrentTime();
GlobalVar.ppmTolerance = 5.0 / 1000000.0;
GlobalVar.retentionTimeWindowSize = 1.0;
GlobalVar.AccordThreshold = 0.5;
Console.WriteLine("Creating exclusion profile");
ExclusionProfile exclusionProfile = new MachineLearningGuidedExclusion(InputFileOrganizer.AccordNet_LogisticRegressionClassifier_WeightAndInterceptSavedFile, database, GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize);
String experimentName = GlobalVar.experimentName + String.Format("_MLGE:ppmTol_{0}_rtWin_{1}_prThr_{2}", GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize, GlobalVar.AccordThreshold);
Experiment experiment = new Experiment(exclusionProfile, experimentName, 1, ExclusionProfileEnum.MACHINE_LEARNING_GUIDED_EXCLUSION_PROFILE, startTime);
new DataReceiver().DoJob(exclusionProfile);
double analysisTime = getCurrentTime() - startTime;
try
{
WriteUnusedSpectra(experiment);
WriteScanArrivalProcessedTime(DataProcessor.scanArrivalAndProcessedTimeList);
WriteScanArrivalProcessedTime(DataProcessor.spectraNotAdded);
WriteUsedSpectra(experiment);
WriterClass.writeln("ExclusionList size: " + exclusionProfile.getExclusionList().getExclusionList().Count);
WriterClass.writeln("Number of exclusion: " + exclusionProfile.getUnusedSpectra().Count);
WriterClass.writeln("Final rtoffset: " + RetentionTime.getRetentionTimeOffset());
}
catch (Exception e)
{
Console.WriteLine("Writing exception catched at end of experiment");
}
finally
{
WriterClass.CloseWriter();
}
exclusionProfile.reset();
reset();
}
//Called by DataProcessor, entry point to Alex's program
public bool evaluate(Spectra spec)
{
currentTime = spec.getStartTime();
updateExclusionList(spec);
if (spec.getMSLevel() == 1)
{
log.Debug("Evaluating ms1 scan");
processMS1(spec);
}
else if (spec.getMSLevel() == 2)
{
log.Debug("evaluating ms2 scan");
if (spec.getIndex() % GlobalVar.ScansPerOutput == 0)
{
#if SIMULATION
double progressPercent = spec.getIndex() / GlobalVar.ExperimentTotalScans * 100;
log.Info("Progress: {0:F2}% Processing ID: {1}\t ScanNum: {2} \t Excluded: {3}", progressPercent, spec.getIndex(), spec.getScanNum(),
excludedSpectra.Count);
#else
log.Info("Progress: {0}\t{1} excluded------------------------", spec.getIndex(), excludedSpectra.Count);
log.Info("ExclusionListSize: {0}\tRTOffset: {1}", exclusionList.getExclusionList().Count, RetentionTime.getRetentionTimeOffset());
#endif
}
return(processMS2(spec));
}
else
{
log.Debug("unrecognized msScan");
}
return(true);
}
