private static void PostExperimentProcessing(Experiment e)
{
//WriterClass.writeln(exclusionProfile.ReportFailedCometSearchStatistics());
WriterClass.Flush();
if (GlobalVar.IsSimulation)
{
ProteinProphetResult ppr;
if (GlobalVar.isSimulationForFeatureExtraction)
{
ppr = ProteinProphetEvaluator.getProteinProphetResult(InputFileOrganizer.OriginalProtXMLFile);
}
else
{
String proteinProphetResultFileName = e.experimentNumber + GlobalVar.experimentName;
ppr = PostProcessingScripts.postProcessing(e.exclusionProfile, proteinProphetResultFileName, true);
}
e.totalRunTime = getCurrentTime() - e.experimentStartTime;
String result = e.exclusionProfile.getPerformanceVector(e.experimentName, e.exclusionProfile.getAnalysisType().getDescription()
, e.analysisTime, e.totalRunTime, ppr, 12, e.exclusionProfile);
Console.WriteLine(result);
Console.WriteLine("Protein groups: " + ppr.getFilteredProteinGroups().Count);
WriterClass.writeln(result);
//WriterClass.writeln("Protein groups: "+ ppr.getFilteredProteinGroups().Count) ;
e.ppr = ppr;
}
else
{
WriterClass.writeln(e.exclusionProfile.GetPerformanceEvaluator().outputPerformance());
}
}
protected bool processMS2(Spectra spec)
{
performanceEvaluator.countMS2();
log.Debug(spec);
IDs id = performDatabaseSearch(spec);
Boolean isExcluded = false;
if (id != null)
{
Peptide pep = getPeptideFromIdentification(id);
isExcluded = exclusionList.containsPeptide(pep);
}
if (isExcluded)
{
#if SIMULATION
//log.Debug("Mass " + spectraMass + " is on the exclusion list. Scan " + spec.getScanNum() + " excluded.");
evaluateExclusion(id);
WriterClass.LogScanTime("Excluded", (int)spec.getIndex());
#endif
performanceEvaluator.countExcludedSpectra();
excludedSpectra.Add(spec.getScanNum());
return(false);
}
else
{
performanceEvaluator.countAnalyzedSpectra();
//log.Debug("Mass " + spectraMass + " was not on the exclusion list. Scan " + spec.getScanNum() + " analyzed.");
evaluateIdentification(id);
includedSpectra.Add(spec.getScanNum());
// calibrate peptide if the observed retention time doesn't match the predicted
//WriterClass.LogScanTime("Processed", (int)spec.getIndex());
return(true);
}
}
private static void OutputCrossedHeaderNames(List <String> crs)
{
String header = String.Join("\t", crs);
String outputFileName = "CrossedHeaderName.txt";
WriterClass.QuickWrite(header, outputFileName);
return;
}
public static void CometSingleSearchTest()
{
String idx = "C:\\Coding\\2019LavalleeLab\\GitProjectRealTimeMS\\TestData\\PreComputedFiles\\uniprot_SwissProt_Human_1_11_2017_decoyConcacenated.fasta.idx";
//String idx = "C:\\temp\\comet_2019015\\comet_source_2019015\\IDXMake\\uniprot_SwissProt_Human_1_11_2017_decoyConcacenated.fasta.idx";
String param = "C:\\Coding\\2019LavalleeLab\\temp2\\ExampleDataSet\\2019.comet.params";
CometSingleSearch.InitializeComet(idx, param);
CometSingleSearch.QualityCheck();
Program.ExitProgram(1);
String dataRoot = "C:\\Users\\LavalleeLab\\Documents\\JoshTemp\\MealTimeMS_APITestRun\\Data\\";
String outputRoot = "C:\\Users\\LavalleeLab\\Documents\\JoshTemp\\MealTimeMS_APITestRun\\Output\\";
//String mzmlPath = dataRoot+"60minMZMLShrink.csv";
String mzmlPath = dataRoot + "8001.ms2.txt";
String dbPath = dataRoot + "tinyDB.fasta.idx"; //
String outputPath = outputRoot + "output.txt";
String paramsPath = dataRoot + "comet.params";
MZMLFile mzml = Loader.parseMS2File(mzmlPath);
//MZMLFile mzml = null;
CometSingleSearch.InitializeComet(dbPath, paramsPath);
var watch = System.Diagnostics.Stopwatch.StartNew();
int counter = 0;
Console.WriteLine("Starting comet search");
WriterClass.initiateWriter(outputPath);
for (int i = 0; i < 1; i++)
{
if (i % 1 == 0)
{
Spectra spec = mzml.getSpectraArray()[i];
if (spec.getMSLevel() != 2)
{
continue;
}
Console.WriteLine("scanNum {0} RT {2} Mass {2} MSLevel {3}", spec.getScanNum(), spec.getStartTime(),
spec.getCalculatedPrecursorMass(), spec.getMSLevel());
IDs id = null;
if (CometSingleSearch.Search(spec, out id))
{
String outLine = String.Format("{0}\t{1}\txcorr\t{2}\tdcn\t{3}", id.getScanNum(), id.getPeptideSequence(), id.getXCorr(), id.getDeltaCN());
Console.WriteLine(outLine);
WriterClass.writeln(outLine);
}
else
{
Console.WriteLine("Spectrum cannot be matched\n");
}
counter++;
}
}
watch.Stop();
Console.WriteLine("Comet search of " + counter + " spectra took " + watch.ElapsedMilliseconds + " milliseconds");
WriterClass.CloseWriter();
}
private static void WriteScanArrivalProcessedTime(List <double[]> list)
{
String header = "ScanNum\tArrival\tProcessed";
WriterClass.writeln(header, writerClassOutputFile.scanArrivalAndProcessedTime);
foreach (double[] scan in list)
{
String data = "";
foreach (double d in scan)
{
data = data + d + "\t";
}
WriterClass.writeln(data, writerClassOutputFile.scanArrivalAndProcessedTime);
}
}
protected bool processMS2(Spectra spec)
{
performanceEvaluator.countMS2();
log.Debug(spec);
IDs id = performDatabaseSearch(spec);
// check if mass is on exclusion list
Boolean isExcluded = false;
if (id != null)
{
Peptide pep = getPeptideFromIdentification(id);
isExcluded = exclusionList.containsPeptide(pep); //checks if the mass should've been excluded,
//in a real experiment, this should never equal to true
//since the mass should not have been scanned in the first place
//if MS exclusion table was updated correctly through API
if (!peptideRT.Keys.Contains(pep.getSequence()))
{
peptideRT.Add(pep.getSequence(), spec.getStartTime());
}
}
if (isExcluded)
{
#if SIMULATION
//log.Debug("Mass " + spectraMass + " is on the exclusion list. Scan " + spec.getScanNum() + " excluded.");
evaluateExclusion(id);
WriterClass.LogScanTime("Excluded", (int)spec.getIndex());
#endif
performanceEvaluator.countExcludedSpectra();
excludedSpectra.Add(spec.getScanNum());
return(false);
}
else
{
performanceEvaluator.countAnalyzedSpectra();
//log.Debug("Mass " + spectraMass + " was not on the exclusion list. Scan " + spec.getScanNum() + " analyzed.");
evaluateIdentification(id);
includedSpectra.Add(spec.getScanNum());
// calibrate peptide if the observed retention time doesn't match the predicted
//WriterClass.LogScanTime("Processed", (int)spec.getIndex());
return(true);
}
}
public static void DoJob(String fileIn, String fileOut, int start, int num)
{
WriterClass.initiateWriter(fileOut);
StreamReader reader = new StreamReader(fileIn);
WriterClass.writeln(reader.ReadLine());
for (int i = 0; i < start - 1; i++)
{
reader.ReadLine();
}
for (int i = 0; i < num; i++)
{
WriterClass.writeln(reader.ReadLine());
}
WriterClass.CloseWriter();
}
//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();
}
protected virtual bool processMS2(Spectra spec)
{
performanceEvaluator.countMS2();
log.Debug(spec);
// check if mass is on exclusion list
double spectraMass = spec.getCalculatedPrecursorMass();
Boolean isExcluded = exclusionList.isExcluded(spectraMass); //checks if the mass should've been excluded,
//in a real experiment, this should never equal to true
//since the mass should not have been scanned in the first place
//if MS exclusion table was updated correctly through API
if (isExcluded)
{
#if (SIMULATION)
IDs id = performDatabaseSearch(spec);
log.Debug("Mass " + spectraMass + " is on the exclusion list. Scan " + spec.getScanNum() + " excluded.");
evaluateExclusion(id);
WriterClass.LogScanTime("Excluded", (int)spec.getIndex());
#endif
performanceEvaluator.countExcludedSpectra();
excludedSpectra.Add(spec.getScanNum());
return(false);
}
else
{
IDs id = performDatabaseSearch(spec);
performanceEvaluator.countAnalyzedSpectra();
log.Debug("Mass " + spectraMass + " was not on the exclusion list. Scan " + spec.getScanNum() + " analyzed.");
evaluateIdentification(id);
includedSpectra.Add(spec.getScanNum());
// calibrate peptide if the observed retention time doesn't match the predicted
//WriterClass.LogScanTime("Processed", (int)spec.getIndex());
return(true);
}
}
////MLGE parameters:
//static readonly List<double> PPM_TOLERANCE_LIST = new List<double>(new double[] { 10.0 / 1000000.0 });
//static readonly List<double> RETENTION_TIME_WINDOW_LIST = new List<double>(new double[] { 0.75, 1.0, 2.0 });
//static readonly List<double> LR_PROBABILITY_THRESHOLD_LIST = new List<double>(new double[] { 0.3, 0.5, 0.7, 0.9 });
////Nora parameters:
//static readonly List<double> XCORR_THRESHOLD_LIST = new List<double>(new double[] { 1.5, 2, 2.5 });
////static readonly List<double> XCORR_THRESHOLD_LIST = new List<double>(new double[] {1.5, 2.0 });
//static readonly List<int> NUM_DB_THRESHOLD_LIST = new List<int>(new int[] { 2 });
public static void RunExclusionExplorer(ExclusionProfileEnum exclusionType)
{
PreExperimentSetUp();
WriterClass.writeln(new PerformanceEvaluator().getHeader());
int experimentNumber = 0;
if (exclusionType == ExclusionProfileEnum.MACHINE_LEARNING_GUIDED_EXCLUSION_PROFILE)
{
foreach (double ppmTol in GlobalVar.PPM_TOLERANCE_LIST)
{
foreach (double rtWin in GlobalVar.RETENTION_TIME_WINDOW_LIST)
{
foreach (double prThr in GlobalVar.LR_PROBABILITY_THRESHOLD_LIST)
{
experimentNumber++;
double startTime = getCurrentTime();
GlobalVar.ppmTolerance = ppmTol;
GlobalVar.retentionTimeWindowSize = rtWin;
GlobalVar.AccordThreshold = prThr;
ExclusionProfile exclusionProfile = new MachineLearningGuidedExclusion(InputFileOrganizer.AccordNet_LogisticRegressionClassifier_WeightAndInterceptSavedFile, database, GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize);
String experimentName = "EXP_" + experimentNumber + GlobalVar.experimentName + String.Format("_MachineLearningGuidedExclusion:ppmTol_{0}_rtWin_{1}_prThr_{2}", ppmTol, rtWin, prThr);
Experiment experiment = new Experiment(exclusionProfile, experimentName, experimentNumber, exclusionType, startTime);
RunSimulationAndPostProcess(experiment);
}
}
}
}
else if (exclusionType == ExclusionProfileEnum.NORA_EXCLUSION_PROFILE)
{
foreach (double xCorr in GlobalVar.XCORR_THRESHOLD_LIST)
{
foreach (int numDB in GlobalVar.NUM_DB_THRESHOLD_LIST)
{
foreach (double ppmTol in GlobalVar.PPM_TOLERANCE_LIST)
{
foreach (double rtWin in GlobalVar.RETENTION_TIME_WINDOW_LIST)
{
experimentNumber++;
double startTime = getCurrentTime();
GlobalVar.ppmTolerance = ppmTol;
GlobalVar.retentionTimeWindowSize = rtWin;
GlobalVar.XCorr_Threshold = xCorr;
GlobalVar.NumDBThreshold = numDB;
ExclusionProfile exclusionProfile = new NoraExclusion(database, GlobalVar.XCorr_Threshold, GlobalVar.ppmTolerance, GlobalVar.NumDBThreshold, GlobalVar.retentionTimeWindowSize);
String experimentName = "EXP_" + experimentNumber + GlobalVar.experimentName + String.Format("_HeuristicExclusion:xCorr_{0}_numDB_{1}_ppmTol_{2}_rtWin_{3}", xCorr, numDB, ppmTol, rtWin) + "_expNum" + experimentNumber;
Experiment experiment = new Experiment(exclusionProfile, experimentName, experimentNumber, exclusionType, startTime);
RunSimulationAndPostProcess(experiment);
}
}
}
}
}
else if (exclusionType == ExclusionProfileEnum.COMBINED_EXCLUSION)
{
foreach (double rtWin in GlobalVar.RETENTION_TIME_WINDOW_LIST)
{
foreach (double prThr in GlobalVar.LR_PROBABILITY_THRESHOLD_LIST)
{
foreach (int numDB in GlobalVar.NUM_DB_THRESHOLD_LIST)
{
foreach (double xCorr in GlobalVar.XCORR_THRESHOLD_LIST)
{
foreach (double ppmTol in GlobalVar.PPM_TOLERANCE_LIST)
{
experimentNumber++;
double startTime = getCurrentTime();
GlobalVar.ppmTolerance = ppmTol;
GlobalVar.retentionTimeWindowSize = rtWin;
GlobalVar.AccordThreshold = prThr;
GlobalVar.XCorr_Threshold = xCorr;
GlobalVar.NumDBThreshold = numDB;
ExclusionProfile exclusionProfile = new CombinedExclusion(InputFileOrganizer.AccordNet_LogisticRegressionClassifier_WeightAndInterceptSavedFile, database, GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize, xCorr, numDB);
String experimentName = "EXP_" + experimentNumber + GlobalVar.experimentName + String.Format("_CombinedExclusion:xCorr_{0}_numDB_{1}_ppmTol_{2}_rtWin_{3}_prThr_{4}",
xCorr, numDB, GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize, GlobalVar.AccordThreshold);
Experiment experiment = new Experiment(exclusionProfile, experimentName, experimentNumber, exclusionType, startTime);
RunSimulationAndPostProcess(experiment);
}
}
}
}
}
}
else if (exclusionType == ExclusionProfileEnum.SVMEXCLUSION)
{
foreach (double ppmTol in GlobalVar.PPM_TOLERANCE_LIST)
{
foreach (double rtWin in GlobalVar.RETENTION_TIME_WINDOW_LIST)
{
experimentNumber++;
double startTime = getCurrentTime();
GlobalVar.ppmTolerance = ppmTol;
GlobalVar.retentionTimeWindowSize = rtWin;
ExclusionProfile exclusionProfile = new SVMExclusion(InputFileOrganizer.SVMSavedFile, database, GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize);
String experimentName = "EXP_" + experimentNumber + GlobalVar.experimentName + String.Format("_SVM:ppmTol_{0}_rtWin_{1}", ppmTol, rtWin);
Experiment experiment = new Experiment(exclusionProfile, experimentName, experimentNumber, exclusionType, startTime);
RunSimulationAndPostProcess(experiment);
}
}
}
else if (exclusionType == ExclusionProfileEnum.NO_EXCLUSION_PROFILE)
{
foreach (double rtWin in GlobalVar.RETENTION_TIME_WINDOW_LIST)
{
experimentNumber++;
double startTime = getCurrentTime();
GlobalVar.ppmTolerance = 0;
GlobalVar.retentionTimeWindowSize = rtWin;
ExclusionProfile exclusionProfile = new NoExclusion(database, GlobalVar.retentionTimeWindowSize);
String experimentName = "EXP_" + experimentNumber + GlobalVar.experimentName + String.Format("_NoExclusion:ppmTol_rtWin_{0}", rtWin);
Experiment experiment = new Experiment(exclusionProfile, experimentName, experimentNumber, exclusionType, startTime);
RunSimulationAndPostProcess(experiment);
if (exclusionType == ExclusionProfileEnum.NO_EXCLUSION_PROFILE)
{
List <ObservedPeptideRtTrackerObject> peptideIDRT = ((NoExclusion)exclusionProfile).peptideIDRT;
//actual arrival time, xcorr, rtCalc predicted RT, corrected RT, offset
//WriterClass.writeln("pepSeq\tarrivalTime\txcorr\trtPeak\tcorrectedRT\toffset\trtCalcPredicted\tisPredicted1", writerClassOutputFile.peptideRTTime);
//foreach (ObservedPeptideRtTrackerObject observedPeptracker in peptideIDRT)
//{
// WriterClass.writeln(observedPeptracker.ToString(), writerClassOutputFile.peptideRTTime);
//}
WriterClass.writeln("peptideSequence\tObservedRetentionTime", writerClassOutputFile.peptideRTTime);
foreach (ObservedPeptideRtTrackerObject observedPeptracker in peptideIDRT)
{
WriterClass.writeln(String.Format("{0}\t{1}", observedPeptracker.peptideSequence, observedPeptracker.arrivalTime), writerClassOutputFile.peptideRTTime);
}
}
break;
}
}
else if (exclusionType == ExclusionProfileEnum.RANDOM_EXCLUSION_PROFILE)
{
List <ExperimentResult> resultList = ParseExperimentResult(InputFileOrganizer.SummaryFileForRandomExclusion);
foreach (ExperimentResult expResult in resultList)
{
//Do 5 random experiments per normal experiment
for (int i = 0; i < GlobalVar.randomRepeatsPerExperiment; i++)
{
experimentNumber++;
double startTime = getCurrentTime();
String originalExperimentName = expResult.experimentName;
int numExcluded = expResult.numSpectraExcluded;
int numAnalyzed = expResult.numSpectraAnalyzed;
ExclusionProfile exclusionProfile = new RandomExclusion_Fast(database, ms2SpectraList, numExcluded, numAnalyzed, 12);
String experimentName = "EXP_" + experimentNumber + String.Format("Random:originalExperiment_{0}", originalExperimentName);
Experiment experiment = new Experiment(exclusionProfile, experimentName, experimentNumber, exclusionType, startTime);
RunSimulationAndPostProcess(experiment);
}
}
}
}
public static ExclusionProfile SingleSimulationRun(ExclusionProfileEnum expType)
{
PreExperimentSetUp();
int experimentNumber = 1;
double startTime = getCurrentTime();
//parameters:
//GlobalVar.ppmTolerance = 5.0 / 1000000.0;
//GlobalVar.retentionTimeWindowSize = 1.0;
//GlobalVar.AccordThreshold = 0.5;
//GlobalVar.XCorr_Threshold = 1.5;
//GlobalVar.NumDBThreshold = 2;
if (GlobalVar.isSimulationForFeatureExtraction == false)
{
GlobalVar.ppmTolerance = GlobalVar.PPM_TOLERANCE_LIST[0];
GlobalVar.retentionTimeWindowSize = GlobalVar.RETENTION_TIME_WINDOW_LIST[0];
GlobalVar.AccordThreshold = GlobalVar.LR_PROBABILITY_THRESHOLD_LIST[0];
GlobalVar.XCorr_Threshold = GlobalVar.XCORR_THRESHOLD_LIST[0];
GlobalVar.NumDBThreshold = GlobalVar.NUM_DB_THRESHOLD_LIST[0];
}
//random
int numExcluded = 14826;
int numAnalyzed = 22681;
//end parameters
ExclusionProfile exclusionProfile = null;
switch (expType)
{
case ExclusionProfileEnum.NORA_EXCLUSION_PROFILE:
exclusionProfile = new NoraExclusion(database, GlobalVar.XCorr_Threshold, GlobalVar.ppmTolerance, GlobalVar.NumDBThreshold, GlobalVar.retentionTimeWindowSize);
break;
case ExclusionProfileEnum.MACHINE_LEARNING_GUIDED_EXCLUSION_PROFILE:
exclusionProfile = new MachineLearningGuidedExclusion(InputFileOrganizer.AccordNet_LogisticRegressionClassifier_WeightAndInterceptSavedFile, database, GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize);
break;
case ExclusionProfileEnum.RANDOM_EXCLUSION_PROFILE:
exclusionProfile = new RandomExclusion_Fast(database, ms2SpectraList, numExcluded, numAnalyzed, 12);
break;
case ExclusionProfileEnum.NO_EXCLUSION_PROFILE:
exclusionProfile = new NoExclusion(database, GlobalVar.retentionTimeWindowSize);
break;
case ExclusionProfileEnum.MLGE_SEQUENCE_EXCLUSION_PROFILE:
exclusionProfile = new MLGESequenceExclusion(InputFileOrganizer.AccordNet_LogisticRegressionClassifier_WeightAndInterceptSavedFile, database, GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize);
break;
case ExclusionProfileEnum.NORA_SEQUENCE_EXCLUSION_PROFILE:
exclusionProfile = new NoraSequenceExclusion(database, GlobalVar.XCorr_Threshold, GlobalVar.ppmTolerance, GlobalVar.NumDBThreshold, GlobalVar.retentionTimeWindowSize);
break;
case ExclusionProfileEnum.SVMEXCLUSION:
exclusionProfile = new SVMExclusion(InputFileOrganizer.SVMSavedFile, database, GlobalVar.ppmTolerance, GlobalVar.retentionTimeWindowSize);
break;
}
WriterClass.writeln(exclusionProfile.GetPerformanceEvaluator().getHeader());
String experimentName = "EXP_" + experimentNumber + GlobalVar.experimentName;
Experiment experiment = new Experiment(exclusionProfile, experimentName, 1, expType, startTime);
new DataReceiverSimulation().DoJob(exclusionProfile, ms2SpectraList);
double analysisTime = getCurrentTime() - startTime;
//WriteScanArrivalProcessedTime(DataProcessor.scanArrivalAndProcessedTimeList);
//WriteExcludedProteinList(exclusionProfile.getDatabase().getExcludedProteins());
#if IGNORE
WriteScanArrivalProcessedTime(DataProcessor.spectraNotAdded);
foreach (double[] ignoredSpectra in DataProcessor.spectraNotAdded)
{
int scanNum = ms2SpectraList[(int)ignoredSpectra[0] - 1].getScanNum();
exclusionProfile.getSpectraUsed().Add(scanNum);
}
#endif
//if (expType == ExclusionProfileEnum.NO_EXCLUSION_PROFILE)
//{
// List<ObservedPeptideRtTrackerObject> peptideIDRT = ((NoExclusion)exclusionProfile).peptideIDRT;
// //actual arrival time, xcorr, rtCalc predicted RT, corrected RT, offset
// WriterClass.writeln("pepSeq\tarrivalTime\txcorr\trtPeak\tcorrectedRT\toffset\trtCalcPredicted\tisPredicted1", writerClassOutputFile.peptideRTTime);
// foreach (ObservedPeptideRtTrackerObject observedPeptracker in peptideIDRT)
// {
// WriterClass.writeln(observedPeptracker.ToString(), writerClassOutputFile.peptideRTTime);
// }
//}
//if (expType == ExclusionProfileEnum.MACHINE_LEARNING_GUIDED_EXCLUSION_PROFILE)
//{
// List<double[]> peptideIDRT = ((MachineLearningGuidedExclusion)exclusionProfile).peptideIDRT;
// //actual arrival time, xcorr, rtCalc predicted RT, corrected RT, offset
// WriterClass.writeln("arrivalTime\txcorr\trtPeak\tcorrectedRT\toffset\trtCalcPredicted\tisPredicted1", writerClassOutputFile.peptideRTTime);
// foreach(double[] id in peptideIDRT)
// {
// String str = "";
// foreach(double d in id)
// {
// str = str + "\t" + d;
// }
// str= str.Trim();
// WriterClass.writeln(str, writerClassOutputFile.peptideRTTime);
// }
//}
#if TRACKEXCLUDEDPROTEINFEATURE
if (expType == ExclusionProfileEnum.MACHINE_LEARNING_GUIDED_EXCLUSION_PROFILE)
{
List <object[]> excludedProteinFeatures = ((MachineLearningGuidedExclusion)exclusionProfile).excludedProteinFeatureList;
WriterClass.writeln("Accession\tCardinality\tHighestXCorr\tMeanXCorr\tMedianXCorr\tStDev", writerClassOutputFile.ExcludedSpectraScanNum);
foreach (object[] feature in excludedProteinFeatures)
{
String featureStr = "";
foreach (object o in feature)
{
featureStr = featureStr + o.ToString() + "\t";
}
featureStr = featureStr.Trim();
WriterClass.writeln(featureStr, writerClassOutputFile.ExcludedSpectraScanNum);
}
}
#endif
//WriteUnusedSpectra(exclusionProfile);
//WriteUsedSpectra(exclusionProfile);
PostExperimentProcessing(experiment);
//WriteUnusedSpectra(exclusionProfile);
return(exclusionProfile);
}
private void WriteRetention(String str)
{
WriterClass.writeln(str, writerClassOutputFile.peptideRTTime);
}
static String mzml = "C:\\Coding\\2019LavalleeLab\\RealTest_Results_20200219\\MSQC_QE_200ng_HEK_2hr_to_run_200219172225.mzML"; //"C:\\Coding\\2019LavalleeLab\\GoldStandardData\\MZML_Files\\MS_QC_120min.mzml";
public static void DoJob()
{
//comet
Console.WriteLine("Performing Comet search on full ms2 data");
String fullCometFile = PostProcessingScripts.CometStandardSearch(ms2File, InputFileOrganizer.OutputFolderOfTheRun, true);
InputFileOrganizer.OriginalCometOutput = fullCometFile;
//protein prophet
Console.WriteLine("Perform a protein prophet search on full pepxml");
String fullProteinProphetFile = PostProcessingScripts.ProteinProphetSearch(fullCometFile, InputFileOrganizer.OutputFolderOfTheRun, true);
InputFileOrganizer.OriginalProtXMLFile = fullProteinProphetFile;
ProteinProphetResult baseLinePpr = ProteinProphetEvaluator.getProteinProphetResult(InputFileOrganizer.OriginalProtXMLFile);
//load spectra
Console.WriteLine("loading spectra array");
List <Spectra> ls = Loader.parseMS2File(ms2File).getSpectraArray();
List <int> includedSpectra = new List <int>();
List <int> excludedSpectra = new List <int>();
StreamReader sr = new StreamReader(excludedSpectraFile);
String line = sr.ReadLine();
while (line != null)
{
int excluded = int.Parse(line);
excludedSpectra.Add(excluded);
line = sr.ReadLine();
}
foreach (Spectra sp in ls)
{
if (!excludedSpectra.Contains(sp.getScanNum()))
{
includedSpectra.Add(sp.getScanNum());
}
}
String outputCometFile = Path.Combine(InputFileOrganizer.OutputFolderOfTheRun, "realTestpartialOut.pep.xml"); //"C:\\Coding\\2019LavalleeLab\\GoldStandardData\\pepxml\\MS_QC_120min_partial.pep.xml";
String fastaFile = InputFileOrganizer.FASTA_FILE; //"C:\\Coding\\2019LavalleeLab\\GoldStandardData\\Database\\uniprot_SwissProt_Human_1_11_2017.fasta";
PartialPepXMLWriter.writePartialPepXMLFile(fullCometFile, includedSpectra,
outputCometFile, mzml, fastaFile, outputCometFile);
String partialProt = PostProcessingScripts.ProteinProphetSearch(outputCometFile, InputFileOrganizer.OutputFolderOfTheRun, true);
ProteinProphetResult partialPpr = ProteinProphetEvaluator.getProteinProphetResult(partialProt);
double partialNum = partialPpr.getNum_proteins_identified();
double totalNum = baseLinePpr.getNum_proteins_identified();
double idSens = partialNum / totalNum * 100.0;
double includedScanNum = includedSpectra.Count;
double totalScanNum = ls.Count;
double usedResource = includedScanNum / totalScanNum * 100;
String line1 = String.Format("includedScans {0} \t totalScanNum {1} \tUsedResources {2}", includedScanNum, totalScanNum, usedResource);
String line2 = String.Format("partialNum {0} \t totalNum {1} \tidsens {2}", partialNum, totalNum, idSens);
Console.WriteLine(line1);
Console.WriteLine(line2);
WriterClass.writeln(line1);
WriterClass.writeln(line2);
WriterClass.CloseWriter();
}
