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();
}
}
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();
}