private void OutputAlignmentResult(LcMsFeatureAlignment align, string outFilePath, string[] dataName) { var alignedFeatureList = align.GetAlignedFeatures(); var writer = new StreamWriter(outFilePath); writer.Write("MonoMass\tMinElutionTime\tMaxElutionTime"); for (var i = 0; i < align.CountDatasets; i++) { writer.Write("\t{0}", dataName[i]); } writer.Write("\n"); for (var i = 0; i < align.CountAlignedFeatures; i++) { var features = alignedFeatureList[i]; var minMaxNet = TestLcMsFeatureAlignment.GetMinMaxNet(features); writer.Write(@"{0} {1:0.00000} {2:0.00000}", minMaxNet.Item1, minMaxNet.Item3, minMaxNet.Item4); for (var j = 0; j < align.CountDatasets; j++) { var feature = features[j]; writer.Write("\t"); writer.Write(feature != null ? feature.Abundance : 0d); } writer.Write("\n"); } writer.Close(); }
public void CompareClustering() { // Cluster using MultiAlign to Promex adapters var provider = new ScanSummaryProviderCache(); var reader1 = provider.GetScanSummaryProvider(pbf1, 0) as InformedProteomicsReader; var reader2 = provider.GetScanSummaryProvider(pbf2, 1) as InformedProteomicsReader; var promexFileReader1 = new PromexFileReader(reader1, 0); var features1 = promexFileReader1.ReadFile(ms1ft1); var promexFileReader2 = new PromexFileReader(reader2, 1); var features2 = promexFileReader2.ReadFile(ms1ft2); var features = new List <UMCLight>(); features.AddRange(features1); features.AddRange(features2); var clusterer = new PromexClusterer { Readers = provider, }; var clusters = clusterer.Cluster(features); var clusterCount = clusters.Count(c => c.UmcList.Count > 1); // Cluster using only ProMex var lcmsRun1 = PbfLcMsRun.GetLcMsRun(pbf1); var lcmsRun2 = PbfLcMsRun.GetLcMsRun(pbf2); var aligner = new LcMsFeatureAlignment(new LcMsFeatureAlignComparer(new Tolerance(10, ToleranceUnit.Ppm))); var promexFeatures1 = LcMsFeatureAlignment.LoadProMexResult(0, ms1ft1, lcmsRun1); aligner.AddDataSet(0, promexFeatures1, lcmsRun1); var promexFeatures2 = LcMsFeatureAlignment.LoadProMexResult(1, ms1ft2, lcmsRun2); aligner.AddDataSet(1, promexFeatures2, lcmsRun2); aligner.AlignFeatures(); var promexClusters = aligner.GetAlignedFeatures(); var promexClusterCount = promexClusters.Count(c => c.Count(f => f != null) > 1); Assert.AreEqual(clusters.Count, promexClusters.Count); Assert.AreEqual(clusterCount, promexClusterCount); }
public void TestAlignFeatures() { 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 tolerance = new Tolerance(10); var ftComparer = new UtexFeatureComparer(tolerance); var align = new LcMsFeatureAlignment(ftComparer); var prsmReader = new ProteinSpectrumMatchReader(0.01); var filesProcessed = 0; 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 ms1ftPath = string.Format(@"{0}\{1}.ms1ft", promexOutFolder, dataset[i]); if (!File.Exists(ms1ftPath)) { Console.WriteLine(@"Warning: Skipping file not found: {0}", ms1ftPath); continue; } filesProcessed++; //var map = new ProteinSpectrumMathMap(run, i, dataset[i]); //map.LoadIdentificationResult(path, ProteinSpectrumMatch.SearchTool.MsAlign); var prsmList = prsmReader.LoadIdentificationResult(path, ProteinSpectrumMatch.SearchTool.MsAlign); for (var j = 0; j < prsmList.Count; j++) { var match = prsmList[j]; match.ProteinId = match.ProteinName.Substring( match.ProteinName.IndexOf(ProteinNamePrefix) + ProteinNamePrefix.Length, 5); } var features = LcMsFeatureAlignment.LoadProMexResult(i, ms1ftPath, run); // tag features by PrSMs for (var j = 0; j < features.Count; j++) { //features[j].ProteinSpectrumMatches = new ProteinSpectrumMatchSet(i); var massTol = tolerance.GetToleranceAsMz(features[j].Mass); foreach (var match in prsmList) { if (features[j].MinScanNum < match.ScanNum && match.ScanNum < features[j].MaxScanNum && Math.Abs(features[j].Mass - match.Mass) < massTol) { features[j].ProteinSpectrumMatches.Add(match); } } } align.AddDataSet(i, features, run); } if (filesProcessed == 0) { Assert.Ignore("Skipped since input files not found"); } align.AlignFeatures(); Console.WriteLine("{0} alignments ", align.CountAlignedFeatures); align.RefineAbundance(); var alignedFeatureList = align.GetAlignedFeatures(); for (var i = 0; i < nDataset; i++) { var ms1ftPath = string.Format(@"{0}\{1}_aligned.ms1ft", promexOutFolder, dataset[i]); var writer = new StreamWriter(ms1ftPath); writer.Write(LcMsFeatureFinderLauncher.GetHeaderString()); writer.WriteLine("\tIdedMs2ScanNums"); for (var j = 0; j < alignedFeatureList.Count; j++) { writer.Write(j + 1); writer.Write("\t"); if (alignedFeatureList[j][i] == null) { for (var k = 0; k < 14; k++) { writer.Write("0\t"); } writer.Write("0\n"); } else { writer.Write(LcMsFeatureFinderLauncher.GetString(alignedFeatureList[j][i])); writer.Write("\t"); if (alignedFeatureList[j][i].ProteinSpectrumMatches == null) { writer.Write(""); } else { var scanNums = string.Join(";", alignedFeatureList[j][i].ProteinSpectrumMatches.Select(prsm => prsm.ScanNum)); writer.Write(scanNums); } writer.Write("\n"); } } writer.Close(); } }
private void OutputAlignmentResult(LcMsFeatureAlignment align, string outFilePath, IReadOnlyList <string> rawFiles, bool isTemp = true) { var alignedFeatureList = align.GetAlignedFeatures(); var writer = new StreamWriter(outFilePath); writer.Write("MonoMass\tMinElutionTime\tMaxElutionTime"); for (var i = 0; i < align.CountDatasets; i++) { var dataSetName = Path.GetFileNameWithoutExtension(rawFiles[i]); writer.Write("\t{0}", dataSetName); } for (var i = 0; i < align.CountDatasets; i++) { //var dataSetName = Path.GetFileNameWithoutExtension(align.RawFileList[i]); writer.Write("\t{0}_Score", i); } /* * for (var i = 0; i < align.CountDatasets; i++) * { * //var dataSetName = Path.GetFileNameWithoutExtension(align.RawFileList[i]); * writer.Write("\t{0}_Net", i); * }*/ writer.Write("\n"); for (var i = 0; i < align.CountAlignedFeatures; i++) { var features = alignedFeatureList[i]; var minMaxNet = GetMinMaxNet(features); writer.Write(@"{0}\t{1:0.00000}\t{2:0.00000}", minMaxNet.Item1, minMaxNet.Item3, minMaxNet.Item4); for (var j = 0; j < align.CountDatasets; j++) { var feature = features[j]; writer.Write("\t"); writer.Write(feature?.Abundance ?? 0d); } for (var j = 0; j < align.CountDatasets; j++) { var feature = features[j]; writer.Write("\t"); writer.Write(feature?.Score ?? 0d); } /* * for (var j = 0; j < align.CountDatasets; j++) * { * var feature = features[j]; * writer.Write("\t"); * if (feature != null) writer.Write("{0:0.00000}", feature.MinNet); * else writer.Write(0); * } * * for (var j = 0; j < align.CountDatasets; j++) * { * var feature = features[j]; * writer.Write("\t"); * if (feature != null) writer.Write("{0:0.00000}", feature.MaxNet); * else writer.Write(0); * }*/ writer.Write("\n"); } writer.Close(); if (isTemp) { return; } var outDirectory = Path.GetDirectoryName(Path.GetFullPath(outFilePath)); for (var i = 0; i < align.CountDatasets; i++) { var dataSetName = Path.GetFileNameWithoutExtension(rawFiles[i]); //writer.Write("\t{0}", dataSetName); // now output results!! var ms1ftFilePath = string.Format(@"{0}\{1}.aligned.ms1ft", outDirectory, dataSetName); var writer2 = new StreamWriter(ms1ftFilePath); writer2.WriteLine(LcMsFeatureFinderLauncher.GetHeaderString()); for (var j = 0; j < align.CountAlignedFeatures; j++) { var f1 = alignedFeatureList[j][i]; writer2.Write("{0}\t", j + 1); writer2.WriteLine(LcMsFeatureFinderLauncher.GetString(f1)); } writer2.Close(); } }
private void OutputCrossTabWithId(string outputFilePath, LcMsFeatureAlignment alignment) { using (var writer = new StreamWriter(outputFilePath)) { var headerLine = new List <string> { "MonoMass", "MinElutionTime", "MaxElutionTime" }; for (var i = 0; i < DATASET_COUNT; i++) { var dataName = GetDataSetNames(i); headerLine.Add(dataName + "_Abundance"); } for (var i = 0; i < DATASET_COUNT; i++) { var dataName = GetDataSetNames(i); headerLine.Add(dataName + "_Ms1Score"); } headerLine.Add("Pre"); headerLine.Add("Sequence"); headerLine.Add("Post"); headerLine.Add("Modifications"); headerLine.Add("ProteinName"); headerLine.Add("ProteinDesc"); headerLine.Add("ProteinLength"); headerLine.Add("Start"); headerLine.Add("End"); for (var i = 0; i < DATASET_COUNT; i++) { var dataName = GetDataSetNames(i); headerLine.Add(dataName + "_SpectraCount"); } writer.WriteLine(string.Join("\t", headerLine)); var alignedFeatureList = alignment.GetAlignedFeatures(); foreach (var features in alignedFeatureList) { var mass = features.Where(f => f != null).Select(f => f.Mass).Median(); var minElutionTime = features.Where(f => f != null).Select(f => f.MinElutionTime).Median(); var maxElutionTime = features.Where(f => f != null).Select(f => f.MaxElutionTime).Median(); var dataLine = new List <string> { PRISM.StringUtilities.DblToString(mass, 4), PRISM.StringUtilities.DblToString(minElutionTime, 3), PRISM.StringUtilities.DblToString(maxElutionTime, 3) }; for (var i = 0; i < DATASET_COUNT; i++) { if (features[i] == null) { dataLine.Add("0"); } else { dataLine.Add(PRISM.StringUtilities.DblToString(features[i].Abundance, 2)); } } for (var i = 0; i < DATASET_COUNT; i++) { if (features[i] == null) { dataLine.Add("0"); } else { if (features[i].Score <= float.MinValue) { dataLine.Add(PRISM.StringUtilities.DblToStringScientific(float.MinValue, 2)); } else { dataLine.Add(PRISM.StringUtilities.DblToString(features[i].Score, 3)); } } } var prsm = (from f in features where f?.ProteinSpectrumMatches != null && f.ProteinSpectrumMatches.Count > 0 select f.ProteinSpectrumMatches[0]).FirstOrDefault(); if (prsm == null) { for (var k = 0; k < 9; k++) { dataLine.Add(" "); } } else { dataLine.Add(prsm.Pre); dataLine.Add(prsm.Sequence); dataLine.Add(prsm.Post); dataLine.Add(prsm.Modifications); dataLine.Add(prsm.ProteinName); dataLine.Add(prsm.ProteinDesc); dataLine.Add(prsm.ProteinLength.ToString()); dataLine.Add(prsm.FirstResidue.ToString()); dataLine.Add(prsm.LastResidue.ToString()); } // spectral count from ms2 for (var i = 0; i < DATASET_COUNT; i++) { if (features[i] == null) { dataLine.Add("0"); } else { dataLine.Add(features[i].ProteinSpectrumMatches.Count.ToString()); } } writer.WriteLine(string.Join("\t", dataLine)); } } Console.WriteLine("Results written to " + outputFilePath); }
public List <UMCClusterLight> Cluster(List <UMCLight> data, IProgress <ProgressData> progress = null) { progress = progress ?? new Progress <ProgressData>(); if (data.Count == 0) { return(new List <UMCClusterLight>()); } this.maxFeatureId = data.Select(d => d.Id).Max(); this.featureMap = new Dictionary <Tuple <int, int>, UMCLight>(); foreach (var feature in data) { var key = new Tuple <int, int>(feature.GroupId, feature.Id); this.featureMap.Add(key, feature); } var lcmsFeatureAligner = new LcMsFeatureAlignment(new LcMsFeatureAlignComparer(new Tolerance(10, ToleranceUnit.Ppm))); // Group features by dataset var idToFeatures = new Dictionary <int, List <UMCLight> >(); foreach (var umcLight in data) { if (!idToFeatures.ContainsKey(umcLight.GroupId)) { idToFeatures.Add(umcLight.GroupId, new List <UMCLight>()); } idToFeatures[umcLight.GroupId].Add(umcLight); } // Convert UMCLights to InformedProteomics LcMsFeatures foreach (var ds in idToFeatures) { var lcmsFeatures = new List <LcMsFeature>(ds.Value.Select(this.GetLcMsFeature)); lcmsFeatureAligner.AddDataSet(ds.Key, lcmsFeatures, this.GetLcMsRun(ds.Key)); } // Perform clustering lcmsFeatureAligner.AlignFeatures(); // Fill in mising features using noise. lcmsFeatureAligner.RefineAbundance(-30, progress); var clusteredFeatures = lcmsFeatureAligner.GetAlignedFeatures(); // Convert InformedProteomics clusters to UMCClusterLight int clustId = 0; var clusters = new List <UMCClusterLight>(); foreach (var cluster in clusteredFeatures) { var firstFeature = cluster.FirstOrDefault(f => f != null); if (firstFeature == null) { continue; } var umcCluster = new UMCClusterLight { Id = clustId++, }; int datasetId = 0; // Promex doesn't keep track of which dataset noise features belong to, so we need to. foreach (var feature in cluster) { if (feature == null) { continue; } feature.DataSetId = datasetId++; var umc = this.GetUMC(feature); umcCluster.AddChildFeature(umc); umc.SetParentFeature(umcCluster); } umcCluster.CalculateStatistics(ClusterCentroidRepresentation.Median); clusters.Add(umcCluster); } return(clusters); }
public void OutputCrossTabWithId(string outputFilePath, LcMsFeatureAlignment alignment, string[] runLabels) { var nDataset = runLabels.Length; var writer = new StreamWriter(outputFilePath); writer.Write("MonoMass"); writer.Write("\t"); writer.Write("MinElutionTime"); writer.Write("\t"); writer.Write("MaxElutionTime"); foreach (var dataName in runLabels) { writer.Write("\t"); writer.Write(dataName + "_Abundance"); } foreach (var dataName in runLabels) { writer.Write("\t"); writer.Write(dataName + "_Ms1Score"); } writer.Write("\t"); writer.Write("Pre"); writer.Write("\t"); writer.Write("Sequence"); writer.Write("\t"); writer.Write("Post"); writer.Write("\t"); writer.Write("Modifications"); writer.Write("\t"); writer.Write("SequenceText"); writer.Write("\t"); writer.Write("ProteinName"); writer.Write("\t"); writer.Write("ProteinDesc"); writer.Write("\t"); writer.Write("ProteinLength"); writer.Write("\t"); writer.Write("Start"); writer.Write("\t"); writer.Write("End"); foreach (var dataName in runLabels) { writer.Write("\t"); writer.Write(dataName + "_SpectraCount"); } writer.Write("\n"); var alignedFeatureList = alignment.GetAlignedFeatures(); for (var j = 0; j < alignedFeatureList.Count; j++) { var features = alignedFeatureList[j]; var mass = features.Where(f => f != null).Select(f => f.Mass).Median(); var minElutionTime = features.Where(f => f != null).Select(f => f.MinElutionTime).Median(); var maxElutionTime = features.Where(f => f != null).Select(f => f.MaxElutionTime).Median(); writer.Write(mass); writer.Write("\t"); writer.Write(minElutionTime); writer.Write("\t"); writer.Write(maxElutionTime); for (var i = 0; i < nDataset; i++) { writer.Write("\t"); writer.Write(features[i] == null ? 0 : features[i].Abundance); } for (var i = 0; i < nDataset; i++) { writer.Write("\t"); writer.Write(features[i] == null ? 0 : features[i].Score); } var prsm = (from f in features where f != null && f.ProteinSpectrumMatches != null && f.ProteinSpectrumMatches.Count > 0 select f.ProteinSpectrumMatches[0]).FirstOrDefault(); if (prsm == null) { for (var k = 0; k < 10; k++) { writer.Write("\t"); writer.Write(" "); } } else { writer.Write("\t"); writer.Write(prsm.Pre); writer.Write("\t"); writer.Write(prsm.Sequence); writer.Write("\t"); writer.Write(prsm.Post); writer.Write("\t"); writer.Write(prsm.Modifications); writer.Write("\t"); writer.Write(prsm.SequenceText); writer.Write("\t"); writer.Write(prsm.ProteinName); writer.Write("\t"); writer.Write(prsm.ProteinDesc); writer.Write("\t"); writer.Write(prsm.ProteinLength); writer.Write("\t"); writer.Write(prsm.FirstResidue); writer.Write("\t"); writer.Write(prsm.LastResidue); } // spectral count from ms2 for (var i = 0; i < nDataset; i++) { writer.Write("\t"); writer.Write(features[i] == null ? 0 : features[i].ProteinSpectrumMatches.Count); } writer.Write("\n"); } writer.Close(); }
public void OutputCrossTabWithId(string outputFilePath, LcMsFeatureAlignment alignment) { var writer = new StreamWriter(outputFilePath); writer.Write("MonoMass"); writer.Write("\t"); writer.Write("MinElutionTime"); writer.Write("\t"); writer.Write("MaxElutionTime"); for (var i = 0; i < NdataSet; i++) { var dataName = GetDataSetNames(i); writer.Write("\t"); writer.Write(dataName + "_Abundance"); } for (var i = 0; i < NdataSet; i++) { var dataName = GetDataSetNames(i); writer.Write("\t"); writer.Write(dataName + "_Ms1Score"); } writer.Write("\t"); writer.Write("Pre"); writer.Write("\t"); writer.Write("Sequence"); writer.Write("\t"); writer.Write("Post"); writer.Write("\t"); writer.Write("Modifications"); writer.Write("\t"); writer.Write("ProteinName"); writer.Write("\t"); writer.Write("ProteinDesc"); writer.Write("\t"); writer.Write("ProteinLength"); writer.Write("\t"); writer.Write("Start"); writer.Write("\t"); writer.Write("End"); for (var i = 0; i < NdataSet; i++) { var dataName = GetDataSetNames(i); writer.Write("\t"); writer.Write(dataName + "_SpectraCount"); } writer.Write("\n"); var alignedFeatureList = alignment.GetAlignedFeatures(); for (var j = 0; j < alignedFeatureList.Count; j++) { var features = alignedFeatureList[j]; var mass = features.Where(f => f != null).Select(f => f.Mass).Median(); var minElutionTime = features.Where(f => f != null).Select(f => f.MinElutionTime).Median(); var maxElutionTime = features.Where(f => f != null).Select(f => f.MaxElutionTime).Median(); writer.Write(mass); writer.Write("\t"); writer.Write(minElutionTime); writer.Write("\t"); writer.Write(maxElutionTime); for (var i = 0; i < NdataSet; i++) { writer.Write("\t"); writer.Write(features[i] == null ? 0 : features[i].Abundance); } for (var i = 0; i < NdataSet; i++) { writer.Write("\t"); writer.Write(features[i] == null ? 0 : features[i].Score); } var prsm = (from f in features where f != null && f.ProteinSpectrumMatches != null && f.ProteinSpectrumMatches.Count > 0 select f.ProteinSpectrumMatches[0]).FirstOrDefault(); if (prsm == null) { for (var k = 0; k < 9; k++) { writer.Write("\t"); writer.Write(" "); } } else { writer.Write("\t"); writer.Write(prsm.Pre); writer.Write("\t"); writer.Write(prsm.Sequence); writer.Write("\t"); writer.Write(prsm.Post); writer.Write("\t"); writer.Write(prsm.Modifications); writer.Write("\t"); writer.Write(prsm.ProteinName); writer.Write("\t"); writer.Write(prsm.ProteinDesc); writer.Write("\t"); writer.Write(prsm.ProteinLength); writer.Write("\t"); writer.Write(prsm.FirstResidue); writer.Write("\t"); writer.Write(prsm.LastResidue); } // spectral count from ms2 for (var i = 0; i < NdataSet; i++) { writer.Write("\t"); writer.Write(features[i] == null ? 0 : features[i].ProteinSpectrumMatches.Count); } writer.Write("\n"); } writer.Close(); }
private void OutputAlignmentResult(LcMsFeatureAlignment align, string outFilePath, List<string> rawFiles, bool isTemp = true) { var alignedFeatureList = align.GetAlignedFeatures(); var writer = new StreamWriter(outFilePath); writer.Write("MonoMass\tMinElutionTime\tMaxElutionTime"); for (var i = 0; i < align.CountDatasets; i++) { var dataSetName = Path.GetFileNameWithoutExtension(rawFiles[i]); writer.Write("\t{0}", dataSetName); } for (var i = 0; i < align.CountDatasets; i++) { //var dataSetName = Path.GetFileNameWithoutExtension(align.RawFileList[i]); writer.Write("\t{0}_Score", i); } /* for (var i = 0; i < align.CountDatasets; i++) { //var dataSetName = Path.GetFileNameWithoutExtension(align.RawFileList[i]); writer.Write("\t{0}_Net", i); }*/ writer.Write("\n"); for (var i = 0; i < align.CountAlignedFeatures; i++) { var features = alignedFeatureList[i]; var minMaxNet = GetMinMaxNet(features); writer.Write(@"{0} {1:0.00000} {2:0.00000}", minMaxNet.Item1, minMaxNet.Item3, minMaxNet.Item4); for (var j = 0; j < align.CountDatasets; j++) { var feature = features[j]; writer.Write("\t"); writer.Write(feature != null ? feature.Abundance : 0d); } for (var j = 0; j < align.CountDatasets; j++) { var feature = features[j]; writer.Write("\t"); writer.Write(feature != null ? feature.Score : 0d); } /* for (var j = 0; j < align.CountDatasets; j++) { var feature = features[j]; writer.Write("\t"); if (feature != null) writer.Write("{0:0.00000}", feature.MinNet); else writer.Write(0); } for (var j = 0; j < align.CountDatasets; j++) { var feature = features[j]; writer.Write("\t"); if (feature != null) writer.Write("{0:0.00000}", feature.MaxNet); else writer.Write(0); }*/ writer.Write("\n"); } writer.Close(); if (isTemp) return; var outDirectory = Path.GetDirectoryName(Path.GetFullPath(outFilePath)); for (var i = 0; i < align.CountDatasets; i++) { var dataSetName = Path.GetFileNameWithoutExtension(rawFiles[i]); //writer.Write("\t{0}", dataSetName); // now output results!! var ms1ftFilePath = String.Format(@"{0}\{1}.aligned.ms1ft", outDirectory, dataSetName); var writer2 = new StreamWriter(ms1ftFilePath); writer2.WriteLine(LcMsFeatureFinderLauncher.GetHeaderString()); for (var j = 0; j < align.CountAlignedFeatures; j++) { var f1 = alignedFeatureList[j][i]; writer2.Write("{0}\t", j + 1); writer2.WriteLine(LcMsFeatureFinderLauncher.GetString(f1)); } writer2.Close(); } }