public void FeatureFind(List <ProteinSpectrumMatch> prsms, LcMsRun run, string outTsvFilePath)
{
var featureFinder = new LcMsPeakMatrix(run, new LcMsFeatureLikelihood());
// write result files
var tsvWriter = new StreamWriter(outTsvFilePath);
tsvWriter.WriteLine(LcMsFeatureFinderLauncher.GetHeaderString(false));
var featureId = 1;
foreach (var match in prsms)
{
var minScan = run.GetPrevScanNum(match.ScanNum, 1);
var maxScan = run.GetNextScanNum(match.ScanNum, 1);
var feature = featureFinder.GetLcMsPeakCluster(match.Mass, match.Charge, minScan, maxScan);
if (feature == null)
{
continue;
}
tsvWriter.WriteLine("{0}\t{1}", featureId, LcMsFeatureFinderLauncher.GetString(feature, false));
featureId++;
}
tsvWriter.Close();
}
public void TestFeatureExampleForFigure()
{
var methodName = MethodBase.GetCurrentMethod().Name;
Utils.ShowStarting(methodName);
const string rawFile = @"\\proto-11\MSXML_Cache\PBF_Gen_1_193\2015_1\CPTAC_Intact_rep6_15Jan15_Bane_C2-14-08-02RZ.pbf";
//const string rawFile = @"D:\MassSpecFiles\training\raw\QC_Shew_Intact_26Sep14_Bane_C2Column3.pbf";
if (!File.Exists(rawFile))
{
Assert.Ignore(@"Skipping test {0} since file not found: {1}", methodName, rawFile);
}
var run = PbfLcMsRun.GetLcMsRun(rawFile);
var scorer = new LcMsFeatureLikelihood();
var featureFinder = new LcMsPeakMatrix(run, scorer);
var feature = featureFinder.GetLcMsPeakCluster(28061.6177, 20, 34, 7624, 7736);
var resultsFilePath = Path.Combine(Path.GetTempPath(), Path.GetFileNameWithoutExtension(rawFile) + "_peaks.txt");
var writer = new StreamWriter(resultsFilePath);
writer.Write("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}\n", "Scan", "Elution_Time", "Charge", "ID", "MZ", "Intensity", "Pearson_Correlation");
var envelope = feature.TheoreticalEnvelope;
foreach (var e in envelope.Isotopes)
{
Console.WriteLine(e.Ratio);
}
foreach (var env in feature.EnumerateEnvelopes())
{
var corr = env.PearsonCorrelation;
for (var i = 0; i < envelope.Size; i++)
{
var peak = env.Peaks[i];
if (peak == null)
{
continue;
}
writer.Write("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}\n", env.ScanNum, run.GetElutionTime(env.ScanNum), env.Charge, i, peak.Mz, peak.Intensity, corr);
}
}
writer.Close();
Console.WriteLine("Results are in file " + resultsFilePath);
}
public void TestQuantifyIdedProteoforms()
{
var methodName = MethodBase.GetCurrentMethod().Name;
Utils.ShowStarting(methodName);
const string rawFolder = @"\\proto-11\MSXML_Cache\PBF_Gen_1_193\2015_2";
const string promexOutFolder = @"D:\MassSpecFiles\UTEX\MSAlign";
const string msAlignResultFolder = @"D:\MassSpecFiles\UTEX\MSAlign";
if (!Directory.Exists(rawFolder))
{
Assert.Ignore(@"Skipping test {0} since folder not found: {1}", methodName, rawFolder);
}
var nDataset = 32;
var dataset = new string[nDataset];
for (var i = 0; i < nDataset; i++)
{
dataset[i] = string.Format("Syn_utex2973_Top_{0,2:D2}_TopDown_7May15_Bane_14-09-01RZ", i + 1);
//var rawFile = string.Format(@"{0}\{1}.pbf", rawFolder, dataset[i]);
}
var prsmReader = new ProteinSpectrumMatchReader(0.01);
var filesProcessed = 0;
var tolerance = new Tolerance(10);
for (var i = 0; i < dataset.Length; i++)
{
var rawFile = string.Format(@"{0}\{1}.pbf", rawFolder, dataset[i]);
if (!File.Exists(rawFile))
{
Console.WriteLine(@"Warning: Skipping file not found: {0}", rawFile);
continue;
}
var run = PbfLcMsRun.GetLcMsRun(rawFile);
var path = string.Format(@"{0}\{1}_MSAlign_ResultTable.txt", msAlignResultFolder, dataset[i]);
if (!File.Exists(path))
{
Console.WriteLine(@"Warning: Skipping file not found: {0}", path);
continue;
}
var prsmList = prsmReader.LoadIdentificationResult(path, ProteinSpectrumMatch.SearchTool.MsAlign);
filesProcessed++;
for (var j = 0; j < prsmList.Count; j++)
{
var match = prsmList[j];
match.ProteinId = match.ProteinName.Substring(match.ProteinName.IndexOf(ProteinNamePrefix) + ProteinNamePrefix.Length, 5);
}
// PrSM To Feature
var prsmToFeatureIdMap = new int[prsmList.Count];
for (var k = 0; k < prsmToFeatureIdMap.Length; k++)
{
prsmToFeatureIdMap[k] = -1;
}
// Feature To PrSM
var featureToPrsm = new List <ProteinSpectrumMatchSet>();
var featureFinder = new LcMsPeakMatrix(run, new LcMsFeatureLikelihood());
var featureList = new List <LcMsPeakCluster>();
var featureId = 0;
for (var j = 0; j < prsmList.Count; j++)
{
if (prsmToFeatureIdMap[j] >= 0)
{
continue;
}
var match = prsmList[j];
var minScanNum = match.ScanNum;
var maxScanNum = match.ScanNum;
var mass = match.Mass;
var charge = match.Charge;
var massTh = tolerance.GetToleranceAsMz(mass);
var id1 = match.ProteinId;
var feature = featureFinder.GetLcMsPeakCluster(mass, charge, minScanNum, maxScanNum);
var prsmSet = new ProteinSpectrumMatchSet(i)
{
match
};
if (feature == null)
{
feature = featureFinder.GetLcMsPeaksFromNoisePeaks(mass, charge, minScanNum, maxScanNum, charge, charge);
prsmToFeatureIdMap[j] = featureId;
}
else
{
prsmToFeatureIdMap[j] = featureId;
var etTol = Math.Max(run.GetElutionTime(run.MaxLcScan) * 0.005, feature.ElutionLength * 0.2);
for (var k = j + 1; k < prsmList.Count; k++)
{
var otherMatch = prsmList[k];
var id2 = otherMatch.ProteinId;
var et2 = run.GetElutionTime(otherMatch.ScanNum);
if (id1.Equals(id2) &&
feature.MinElutionTime - etTol < et2 && et2 < feature.MaxElutionTime - etTol &&
Math.Abs(otherMatch.Mass - mass) < massTh)
{
prsmToFeatureIdMap[k] = featureId;
prsmSet.Add(otherMatch);
}
}
}
featureId++;
feature.Flag = 1;
featureList.Add(feature);
featureToPrsm.Add(prsmSet);
}
// Overlap between features???
for (var j = 0; j < featureList.Count; j++)
{
var f1 = featureList[j];
if (f1.Flag < 1)
{
continue;
}
var prsm1 = featureToPrsm[j];
for (var k = j + 1; k < featureList.Count; k++)
{
var f2 = featureList[k];
if (f2.Flag < 1)
{
continue;
}
var prsm2 = featureToPrsm[k];
if (Math.Abs(f1.Mass - f2.Mass) > tolerance.GetToleranceAsMz(f1.Mass))
{
continue;
}
if (!f1.CoElutedByNet(f2, 0.005))
{
continue;
}
if (!prsm1.ShareProteinId(prsm2))
{
continue;
}
// let us merge!!
if (f1.ScanLength > f2.ScanLength)
{
prsm1.AddRange(prsm2);
prsm2.Clear();
f2.Flag = 0;
}
else
{
prsm2.AddRange(prsm1);
prsm1.Clear();
f1.Flag = 0;
}
}
}
// now output results!!
var ms1ftFilePath = string.Format(@"{0}\{1}.ms1ft", promexOutFolder, dataset[i]);
var writer = new StreamWriter(ms1ftFilePath);
writer.WriteLine(LcMsFeatureFinderLauncher.GetHeaderString());
for (var j = 0; j < featureList.Count; j++)
{
var f1 = featureList[j];
if (f1.Flag < 1)
{
continue;
}
var prsm1 = featureToPrsm[j];
var minScanNum = run.GetPrevScanNum(prsm1.MinScanNum, 1);
var maxScanNum = run.GetNextScanNum(prsm1.MaxScanNum, 1);
f1.ExpandScanRange(minScanNum, maxScanNum);
writer.Write("{0}\t", j + 1);
writer.WriteLine(LcMsFeatureFinderLauncher.GetString(f1));
}
writer.Close();
Console.WriteLine(ms1ftFilePath);
}
if (filesProcessed == 0)
{
Assert.Ignore("Skipped since data files not found");
}
}
public void TestLcMsFeatureXic()
{
var methodName = MethodBase.GetCurrentMethod().Name;
Utils.ShowStarting(methodName);
const string rawFile = @"\\proto-11\MSXML_Cache\PBF_Gen_1_193\2015_1\CPTAC_Intact_rep2_15Jan15_Bane_C2-14-08-02RZ.pbf";
//const string rawFile = @"D:\MassSpecFiles\training\raw\QC_Shew_Intact_26Sep14_Bane_C2Column3.pbf";
if (!File.Exists(rawFile))
{
Assert.Ignore(@"Skipping test {0} since file not found: {1}", methodName, rawFile);
}
var run = PbfLcMsRun.GetLcMsRun(rawFile);
var scorer = new LcMsFeatureLikelihood();
var featureFinder = new LcMsPeakMatrix(run, scorer);
var feature = featureFinder.GetLcMsPeakCluster(2388.278, 4, 3774, 3907);
//feature = featureFinder.GetLcMsPeakCluster(8151.3706, 7, 13, 4201, 4266);
//feature = featureFinder.GetLcMsPeakCluster(8151.41789, 7, 13, 2861, 2941);
var ms1ScanToIndex = run.GetMs1ScanNumToIndex();
var minCol = ms1ScanToIndex[feature.MinScanNum];
var maxCol = ms1ScanToIndex[feature.MaxScanNum];
//var minRow = feature.MinCharge - LcMsPeakMatrix.MinScanCharge;
//var maxRow = feature.MaxCharge - LcMsPeakMatrix.MinScanCharge;
Console.WriteLine("---------------------------------------------------------------");
for (var i = 0; i < feature.Envelopes.Length; i++)
{
for (var j = 0; j < feature.Envelopes[i].Length; j++)
{
Console.Write(feature.Envelopes[i][j] != null ? feature.Envelopes[i][j].PearsonCorrelation : 0);
Console.Write("\t");
}
Console.Write("\n");
}
Console.WriteLine("---------------------------------------------------------------");
for (var i = 0; i < feature.Envelopes.Length; i++)
{
for (var j = 0; j < feature.Envelopes[i].Length; j++)
{
Console.Write(feature.Envelopes[i][j] != null ? feature.Envelopes[i][j].BhattacharyyaDistance : 0);
Console.Write("\t");
}
Console.Write("\n");
}
Console.WriteLine("---------------------------------------------------------------");
for (var i = 0; i < feature.Envelopes.Length; i++)
{
for (var j = 0; j < feature.Envelopes[i].Length; j++)
{
Console.Write(feature.Envelopes[i][j] != null ? feature.Envelopes[i][j].Abundance : 0);
Console.Write("\t");
}
Console.Write("\n");
}
}
public void FillMissingFeatures(int dataSetIndex, double scoreThreshold = -30, IProgress <ProgressData> progressReporter = null)
{
if (_alignedFeatures == null)
{
return;
}
var run = _runList[dataSetIndex];
var ms1ScanNums = run.GetMs1ScanVector();
var featureFinder = new LcMsPeakMatrix(run, new LcMsFeatureLikelihood());
var progressData = new ProgressData(progressReporter);
for (var j = 0; j < CountAlignedFeatures; j++)
{
if (_alignedFeatures[j][dataSetIndex] != null)
{
continue;
}
var mass = 0d;
var charge = 0;
var minScanNum = -1;
var maxScanNum = ms1ScanNums.Last();
var repFt = GetRepFeatureInfo(_alignedFeatures[j]);
mass = repFt.Mass;
charge = repFt.Charge;
var minNet = repFt.MinNet;
var maxNet = repFt.MaxNet;
for (var k = 0; k < ms1ScanNums.Length; k++)
{
var net = run.GetElutionTime(ms1ScanNums[k]) / run.GetElutionTime(run.MaxLcScan);
if (net > minNet && minScanNum < 0)
{
minScanNum = (k == 0) ? ms1ScanNums[k] : ms1ScanNums[k - 1];
}
if (net > maxNet)
{
maxScanNum = ms1ScanNums[k];
break;
}
}
if (minScanNum < 0)
{
minScanNum = 0;
}
var newFt = featureFinder.GetLcMsPeakCluster(mass, charge, minScanNum, maxScanNum);
_alignedFeatures[j][dataSetIndex] = (newFt == null) ? featureFinder.GetLcMsPeaksFromNoisePeaks(mass, charge, minScanNum, maxScanNum, repFt.MinCharge, repFt.MaxCharge) : newFt;
/*
* var ft = featureFinder.GetLcMsPeakCluster(mass, charge, minScanNum, maxScanNum);
*
* if (ft == null || ft.Score < scoreThreshold)
* _alignedFeatures[j][dataSetIndex] = featureFinder.CollectLcMsPeaksWithNoise(mass, charge, minScanNum,
* maxScanNum, repFt.MinCharge, repFt.MaxCharge);
* else
* _alignedFeatures[j][dataSetIndex] = ft;*/
progressData.Report(j, this.CountAlignedFeatures);
}
featureFinder = null;
}
private List <LcMsPeakCluster> MergeFeatures(LcMsPeakMatrix featureFinder, List <LcMsPeakCluster> features)
{
//foreach (var f in _featureList) f.ActivateAllPeaks();
var featureSet = new NodeSet <LcMsPeakCluster>();
featureSet.AddRange(features);
var connectedFeatureSet = featureSet.ConnnectedComponents(_mergeComparer);
var mergedFeatures = new List <LcMsPeakCluster>();
foreach (var fSet in connectedFeatureSet)
{
if (fSet.Count == 1)
{
mergedFeatures.Add(fSet[0]);
}
else
{
var maxScan = fSet.Max(f => f.MaxScanNum);
var minScan = fSet.Min(f => f.MinScanNum);
var maxCharge = fSet.Max(f => f.MaxCharge);
var minCharge = fSet.Min(f => f.MinCharge);
var maxScore = double.MinValue;//fSet.Max(f => f.Score);
LcMsPeakCluster maxScoredClusterOriginal = null;
LcMsPeakCluster maxScoredCluster = null;
foreach (var f in fSet)
{
var newFeature = featureFinder.GetLcMsPeakCluster(f.RepresentativeMass, minCharge, maxCharge, minScan, maxScan);
if (newFeature != null && (maxScoredCluster == null || newFeature.Score > maxScoredCluster.Score))
{
maxScoredCluster = newFeature;
}
if (f.Score > maxScore)
{
maxScoredClusterOriginal = f;
maxScore = f.Score;
}
}
var feature = featureFinder.GetLcMsPeakCluster(fSet.Select(f => f.Mass).Mean(), minCharge, maxCharge, minScan, maxScan);
if (feature != null && (maxScoredCluster == null || feature.Score > maxScoredCluster.Score))
{
maxScoredCluster = feature;
}
//Console.WriteLine("------------- Merge -----------------");
//foreach (var f in fSet) Console.WriteLine("*\t{0}\t{1}\t{2}\t{3}", f.RepresentativeMass, f.MinScanNum, f.MaxScanNum, f.Score);
//Console.WriteLine("**\t{0}\t{1}\t{2}\t{3}", maxScoredCluster.RepresentativeMass, maxScoredCluster.MinScanNum, maxScoredCluster.MaxScanNum, maxScoredCluster.Score);
if (maxScoredCluster == null)
{
maxScoredCluster = maxScoredClusterOriginal;
}
if (maxScoredCluster != null && maxScoredCluster.Score < maxScore)
{
maxScoredCluster.Score = maxScore;
}
mergedFeatures.Add(maxScoredCluster);
}
//if (selectedFeature != null) postFilteredSet.Add(selectedFeature);
}
//return postFilteredSet.OrderBy(f => f.RepresentativeMass);
return(mergedFeatures);
}
