protected void UpdateProteinEntries(IIdentifiedProteinGroup group) { try { this.lvProteins.BeginUpdate(); var items = new List <ListViewItem>(); foreach (ListViewItem item in this.lvProteins.Items) { if (item.Tag == group) { items.Add(item); } } for (int i = 0; i < group.Count && i < items.Count; i++) { UpdateProteinEntry(items[i], group, i); } } finally { this.lvProteins.EndUpdate(); } }
private void UpdateProteinEntry(ListViewItem item, IIdentifiedProteinGroup mpg, int index) { item.ImageIndex = index; IIdentifiedProtein mp = mpg[index]; var parts = new List <string>(this.format.ProteinFormat.GetString(mp).Split(new[] { '\t' })); if (item.SubItems.Count != this.proteinColumnIndecies.Count) { item.SubItems.Clear(); item.Text = MyConvert.Format("${0}-{1}", mpg.Index, index + 1); for (int i = 0; i < proteinColumnIndecies.Count; i++) { item.SubItems.Add(parts[proteinColumnIndecies[i]]); } } else { for (int i = 0; i < proteinColumnIndecies.Count; i++) { item.SubItems[i].Text = parts[proteinColumnIndecies[i]]; } } item.Checked = option.IsProteinRatioValid(mpg[0]) && !option.IsProteinOutlier(mpg[0]); item.Tag = mpg; UpdateProteinColor(mpg[index], item); }
public void Calculate(IIdentifiedProteinGroup proteinGroup, Func <IIdentifiedSpectrum, bool> validFunc) { List <IIdentifiedSpectrum> spectra = (from s in proteinGroup[0].GetSpectra() where s.GetRatioEnabled() && validFunc(s) select s).ToList(); QuantificationItem item; if (spectra.Count == 1) { item = spectra[0].GetQuantificationItem(); } else if (spectra.Count > 1) { var sampleIntensities = new List <double>(); var refIntensities = new List <double>(); spectra.ForEach(m => { sampleIntensities.Add(m.GetQuantificationItem().SampleIntensity); refIntensities.Add(m.GetQuantificationItem().ReferenceIntensity); }); var intensities = new double[2][]; intensities[0] = refIntensities.ToArray(); intensities[1] = sampleIntensities.ToArray(); LinearRegressionRatioResult lrrr = LinearRegressionRatioCalculator.CalculateRatio(intensities); item = new QuantificationItem(); item.Ratio = lrrr.Ratio; item.Correlation = lrrr.RSquare; double sampleIntensity, refIntensity; if (lrrr.Ratio > 1) { sampleIntensity = sampleIntensities.Max(); refIntensity = sampleIntensity / lrrr.Ratio; } else { refIntensity = refIntensities.Max(); sampleIntensity = refIntensity * lrrr.Ratio; } item.SampleIntensity = sampleIntensity; item.ReferenceIntensity = refIntensity; item.Enabled = true; } else { item = new QuantificationItem(); item.Enabled = false; } foreach (IIdentifiedProtein protein in proteinGroup) { protein.SetQuantificationItem(item); } }
private void CalculateProteinRatio(IIdentifiedProteinGroup group, Func <IsobaricItem, double> getSample, string dsName, string channelName, HashSet <string> expNames) { ratioCalc.GetSample = getSample; ratioCalc.DatasetName = dsName; ratioCalc.ChannelName = channelName; ratioCalc.Filter = m => expNames.Contains(m.Query.FileScan.Experimental); ratioCalc.Calculate(group); }
public void WriteToStream(StreamWriter sw, IIdentifiedProteinGroup mpg) { for (int proteinIndex = 0; proteinIndex < mpg.Count; proteinIndex++) { IIdentifiedProtein mpro = mpg[proteinIndex]; sw.WriteLine("${0}-{1}{2}", mpg.Index, proteinIndex + 1, ProteinFormat.GetString(mpro)); } }
public void SetUp() { group = new IdentifiedProteinGroup(); group.Add(new IdentifiedProtein("SHORT") { Sequence = shortSeq }); group.Add(new IdentifiedProtein("LONG") { Sequence = longSeq }); }
public bool Accept(IIdentifiedProteinGroup t) { foreach (IIdentifiedProteinGroupFilter filter in filters) { if (!filter.Accept(t)) { return(false); } } return(true); }
private void WriteProteinOneLine(StreamWriter sw, IIdentifiedProteinGroup mpg, IdentifiedProteinTextWriter proteinWriter) { //find user-defined protein IIdentifiedProtein filtered = null; foreach (Regex reg in this.perferAccessNumberRegexs) { foreach (IIdentifiedProtein mp in mpg) { if (reg.Match(mp.Name).Success) { filtered = mp; break; } } if (filtered != null) { break; } } string name; string reference; if (filtered != null) { name = filtered.Name; reference = filtered.Description; filtered.UniquePeptideCount = mpg[0].UniquePeptideCount; } else { var names = new StringBuilder(); var refs = new StringBuilder(); for (int proteinIndex = 0; proteinIndex < mpg.Count; proteinIndex++) { names.Append(" ! ").Append(mpg[proteinIndex].Name); refs.Append(" ! ").Append(mpg[proteinIndex].Description); IIdentifiedProtein mpro = mpg[proteinIndex]; mpro.UniquePeptideCount = mpg[0].UniquePeptideCount; } filtered = mpg[0]; name = names.ToString().Substring(3); reference = refs.ToString().Substring(3); } sw.WriteLine("${0}-1\t{1}\t{2}{3}", mpg.Index, name, reference, proteinWriter.GetString(filtered)); }
public bool Accept(IIdentifiedProteinGroup t) { foreach (var p in t) { var ac = acParser.GetValue(p.Name); if (conMap.Contains(ac)) { return(true); } } return(false); }
public int CompareTo(IIdentifiedProteinGroup other) { if (this.Count == 0) { return(1); } if (other.Count == 0) { return(-1); } return(this[0].CompareTo(other[0])); }
private IIdentifiedProteinGroup GetGroupContainClassifiedPeptideHitOnly(string keptClassifiedName, IIdentifiedProteinGroup group) { IIdentifiedProteinGroup result = (IIdentifiedProteinGroup)group.Clone(); foreach (IIdentifiedProtein protein in result) { protein.Peptides.RemoveAll(m => !sphc.GetClassification(m).Equals(keptClassifiedName)); protein.InitUniquePeptideCount(); protein.CalculateCoverage(); } return(result); }
private bool Accept(List <string> acNumbers, IIdentifiedProteinGroup group) { foreach (var protein in group) { foreach (var ac in acNumbers) { if (protein.Name.Contains(ac)) { return(true); } } } return(false); }
private void WriteProteinMultipleLines(StreamWriter sw, IIdentifiedProteinGroup mpg, IdentifiedProteinTextWriter proteinWriter) { for (int proteinIndex = 0; proteinIndex < mpg.Count; proteinIndex++) { IIdentifiedProtein mpro = mpg[proteinIndex]; mpro.UniquePeptideCount = mpg[0].UniquePeptideCount; sw.WriteLine("${0}-{1}\t{2}\t{3}\t{4}", mpg.Index, proteinIndex + 1, mpro.Name, mpro.Description, proteinWriter.GetString(mpro)); } }
protected override void PrintItem(StreamWriter pw, CalculationItem calculationItem) { IIdentifiedProteinGroup progroup = (IIdentifiedProteinGroup)calculationItem.Key; pw.Write(StringUtils.Merge( from p in progroup select parser.GetValue(p.Name), " ! ")); pw.Write("\t"); pw.Write(StringUtils.Merge( from p in progroup select p.Description, " ! ")); PrintClassifiedPeptideCount(pw, calculationItem); }
/// <summary> /// 输出每次条件下,每个fraction的protein group文件 /// </summary> protected override void ExportIndividualFractionFile() { DirectoryInfo individualDir = new DirectoryInfo(resultDir.FullName + "\\individual"); FileInfo sourceFile = new FileInfo(option.SourceFileName); SequestResultTextFormat writeFormat = GetWriteFormat(); for (int iMinCount = option.FilterFrom; iMinCount <= option.FilterTo; iMinCount += option.FilterStep) { List <CalculationItem> currentItems = GetFilteredItems(iMinCount); if (!individualDir.Exists) { individualDir.Create(); } foreach (string keptClassifiedName in option.GetClassifiedNames()) { string result_file = MyConvert.Format(@"{0}\{1}.{2}.{3}{4}", individualDir.FullName, FileUtils.ChangeExtension(sourceFile.Name, ""), GetOptionCondition(iMinCount), keptClassifiedName, sourceFile.Extension); List <IIdentifiedProteinGroup> groups = new List <IIdentifiedProteinGroup>(); foreach (var item in currentItems) { if (item.GetClassifiedCount(keptClassifiedName) >= iMinCount) { IIdentifiedProteinGroup group = (IIdentifiedProteinGroup)item.Key; IIdentifiedProteinGroup clonedGroup = GetGroupContainClassifiedPeptideHitOnly(keptClassifiedName, group); groups.Add(clonedGroup); } } IdentifiedResult curResult = new IdentifiedResult(); curResult.AddRange(groups); curResult.Sort(); writeFormat.WriteToFile(result_file, curResult); } } }
public void WriteToStream(StreamWriter sw, IIdentifiedProteinGroup mpg) { //find user-defined protein foreach (Regex reg in perferAccessNumberRegexs) { foreach (IIdentifiedProtein mp in mpg) { if (reg.Match(mp.Name).Success) { sw.WriteLine("${0}-1{1}", mpg.Index, ProteinFormat.GetString(mp)); return; } } } StringBuilder names = new StringBuilder(); StringBuilder refs = new StringBuilder(); for (int proteinIndex = 0; proteinIndex < mpg.Count; proteinIndex++) { if (proteinIndex != 0) { names.Append(" ! "); refs.Append(" ! "); } names.Append(mpg[proteinIndex].Name); refs.Append(mpg[proteinIndex].Description); } string oldName = mpg[0].Name; string oldReference = mpg[0].Description; mpg[0].Name = names.ToString(); mpg[0].Description = refs.ToString(); try { sw.WriteLine("${0}-1{1}", mpg.Index, ProteinFormat.GetString(mpg[0])); } finally { mpg[0].Name = oldName; mpg[0].Description = oldReference; } }
public bool Accept(IIdentifiedProteinGroup t) { var decoy = (from p in t[0].Peptides where p.Spectrum.FromDecoy select p.Spectrum.Query.FileScan.LongFileName).Distinct().Count(); var target = (from p in t[0].Peptides where !p.Spectrum.FromDecoy select p.Spectrum.Query.FileScan.LongFileName).Distinct().Count(); if (decoy == 0) { return(false); } var tdratio = target * 1.0 / decoy; return(tdratio < this.minTargetDecoyRatio); }
public override IEnumerable <string> Process(string fileName) { var format = new SequestResultTextFormat(); format.Progress = this.Progress; Progress.SetMessage("Reading identified result from " + fileName + " ..."); IIdentifiedResult ir = format.ReadFromFile(fileName); Progress.SetMessage("Removing duplicated peptide ..."); Progress.SetRange(0, ir.Count); for (int i = 0; i < ir.Count; i++) { Progress.SetPosition(i); IIdentifiedProteinGroup group = ir[i]; List <IIdentifiedSpectrum> peps = UniquePeptideDistiller.KeepMaxScorePeptideOnly(group.GetPeptides()); foreach (var protein in group) { protein.Peptides.RemoveAll(m => !peps.Contains(m.Spectrum)); } } string resultFileName = fileName + ".unique"; Progress.SetMessage("Saving proteins to " + resultFileName + " ..."); format.WriteToFile(resultFileName, ir); List <IIdentifiedSpectrum> spectra = ir.GetSpectra(); var peptideFormat = new SequestPeptideTextFormat(format.PeptideFormat.GetHeader()); string peptideFileName = fileName + ".unique.peptides"; Progress.SetMessage("Saving peptides to " + peptideFileName + " ..."); peptideFormat.WriteToFile(peptideFileName, spectra); Progress.SetMessage("Finished."); return(new[] { resultFileName, peptideFileName }); }
public override IEnumerable <string> Process(string filename) { string resultFile = FileUtils.ChangeExtension(filename, "peptides"); using (IdentifiedProteinGroupEnumerator iter = new IdentifiedProteinGroupEnumerator(filename, true)) { using (StreamWriter sw = new StreamWriter(resultFile)) { sw.WriteLine(iter.PeptideFormat.GetHeader()); HashSet <string> saved = new HashSet <string>(); HashSet <string> uniquepeptides = new HashSet <string>(); while (iter.MoveNext()) { IIdentifiedProteinGroup group = iter.Current; List <IIdentifiedSpectrum> spectra = group[0].GetSpectra(); spectra.ForEach(delegate(IIdentifiedSpectrum spectrum) { string dta = spectrum.Query.FileScan.LongFileName; if (!saved.Contains(dta)) { saved.Add(dta); uniquepeptides.Add(spectrum.Peptide.PureSequence); sw.WriteLine(iter.PeptideFormat.GetString(spectrum)); } }); } sw.WriteLine(); sw.WriteLine("----- summary -----"); sw.WriteLine("Total peptides: {0}", saved.Count); sw.WriteLine("Unique peptides: {0}", uniquepeptides.Count); } } return(new [] { resultFile }); }
public static void CalcRatioSignificanceProteinGroups(SilacType type, ICombinedData combinedData, RawFileInfo fileInfo) { if (type == SilacType.Doublets) { { List <double> lNormRatio = new List <double>(); List <double> lRatio = new List <double>(); List <double> lIntensity = new List <double>(); List <int> indices = new List <int>(); for (int i = 0; i < combinedData.GetProteinGroupCount(); i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(i); double ratio; double normalizedRatio; int count; double dev; int nOutliers; double pval; group.GetRatio10(combinedData, out ratio, out normalizedRatio, out count, out dev, out nOutliers, out pval); double intensity = group.GetIntensity0(combinedData) + group.GetIntensity1(combinedData); if (normalizedRatio > 0 && !double.IsInfinity(normalizedRatio) && !double.IsNaN(normalizedRatio) && intensity > 0) { lNormRatio.Add(Math.Log(normalizedRatio)); lRatio.Add(Math.Log(ratio)); lIntensity.Add(Math.Log(intensity)); indices.Add(i); } } double[] ratioSignificanceA = NumUtil.MovingBoxPlot(lNormRatio.ToArray(), lIntensity.ToArray(), 1); double[] ratioSignificanceB = NumUtil.MovingBoxPlot(lNormRatio.ToArray(), lIntensity.ToArray(), -1); for (int i = 0; i < indices.Count; i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(indices[i]); group.RatioSignificanceA10 = ratioSignificanceA[i]; group.RatioSignificanceB10 = ratioSignificanceB[i]; } } if (fileInfo.HasExperiment) { string[] exps = fileInfo.GetAllExperimentValues(); foreach (string exp in exps) { List <double> lratio = new List <double>(); List <double> lIntensity = new List <double>(); List <int> indices = new List <int>(); for (int i = 0; i < combinedData.GetProteinGroupCount(); i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(i); double ratio; double normalizedRatio; int count; double dev; int nOutliers; double pval; group.GetRatio10(combinedData, out ratio, out normalizedRatio, out count, out dev, out nOutliers, fileInfo.GetRawFileIndicesFromExperiment(exp), out pval); double intensity = group.GetIntensity0(combinedData) + group.GetIntensity1(combinedData); if (normalizedRatio > 0 && !double.IsInfinity(normalizedRatio) && !double.IsNaN(normalizedRatio) && intensity > 0) { lratio.Add(Math.Log(normalizedRatio)); lIntensity.Add(Math.Log(intensity)); indices.Add(i); } } double[] ratioSignificanceA = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), 1); double[] ratioSignificanceB = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), -1); for (int i = 0; i < indices.Count; i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(indices[i]); group.AddRatioSignificanceA10(exp, ratioSignificanceA[i]); group.AddRatioSignificanceB10(exp, ratioSignificanceB[i]); } } } } if (type == SilacType.Triplets) { { List <double> lratio = new List <double>(); List <double> lIntensity = new List <double>(); List <int> indices = new List <int>(); for (int i = 0; i < combinedData.GetProteinGroupCount(); i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(i); double ratio; double normalizedRatio; int count; double dev; int nOutliers; double pval; group.GetRatio10(combinedData, out ratio, out normalizedRatio, out count, out dev, out nOutliers, out pval); double intensity = group.GetIntensity0(combinedData) + group.GetIntensity1(combinedData) + group.GetIntensity2(combinedData); if (normalizedRatio > 0 && !double.IsInfinity(normalizedRatio) && !double.IsNaN(normalizedRatio) && intensity > 0) { lratio.Add(Math.Log(normalizedRatio)); lIntensity.Add(Math.Log(intensity)); indices.Add(i); } } double[] ratioSignificanceA = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), 1); double[] ratioSignificanceB = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), -1); for (int i = 0; i < indices.Count; i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(indices[i]); group.RatioSignificanceA10 = ratioSignificanceA[i]; group.RatioSignificanceB10 = ratioSignificanceB[i]; } } if (fileInfo.HasExperiment) { string[] exps = fileInfo.GetAllExperimentValues(); foreach (string exp in exps) { List <double> lratio = new List <double>(); List <double> lIntensity = new List <double>(); List <int> indices = new List <int>(); for (int i = 0; i < combinedData.GetProteinGroupCount(); i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(i); double ratio; double normalizedRatio; int count; double dev; int nOutliers; double pval; group.GetRatio10(combinedData, out ratio, out normalizedRatio, out count, out dev, out nOutliers, fileInfo.GetRawFileIndicesFromExperiment(exp), out pval); double intensity = group.GetIntensity0(combinedData) + group.GetIntensity1(combinedData) + group.GetIntensity2(combinedData); if (normalizedRatio > 0 && !double.IsInfinity(normalizedRatio) && !double.IsNaN(normalizedRatio) && intensity > 0) { lratio.Add(Math.Log(normalizedRatio)); lIntensity.Add(Math.Log(intensity)); indices.Add(i); } } double[] ratioSignificanceA = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), 1); double[] ratioSignificanceB = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), -1); for (int i = 0; i < indices.Count; i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(indices[i]); group.AddRatioSignificanceA10(exp, ratioSignificanceA[i]); group.AddRatioSignificanceB10(exp, ratioSignificanceB[i]); } } } { List <double> lratio = new List <double>(); List <double> lIntensity = new List <double>(); List <int> indices = new List <int>(); for (int i = 0; i < combinedData.GetProteinGroupCount(); i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(i); double ratio; double normalizedRatio; int count; double dev; int nOutliers; double pval; group.GetRatio20(combinedData, out ratio, out normalizedRatio, out count, out dev, out nOutliers, out pval); double intensity = group.GetIntensity0(combinedData) + group.GetIntensity1(combinedData) + group.GetIntensity2(combinedData); if (normalizedRatio > 0 && !double.IsInfinity(normalizedRatio) && !double.IsNaN(normalizedRatio) && intensity > 0) { lratio.Add(Math.Log(normalizedRatio)); lIntensity.Add(Math.Log(intensity)); indices.Add(i); } } double[] ratioSignificanceA = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), 1); double[] ratioSignificanceB = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), -1); for (int i = 0; i < indices.Count; i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(indices[i]); group.RatioSignificanceA20 = ratioSignificanceA[i]; group.RatioSignificanceB20 = ratioSignificanceB[i]; } } if (fileInfo.HasExperiment) { string[] exps = fileInfo.GetAllExperimentValues(); foreach (string exp in exps) { List <double> lratio = new List <double>(); List <double> lIntensity = new List <double>(); List <int> indices = new List <int>(); for (int i = 0; i < combinedData.GetProteinGroupCount(); i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(i); double ratio; double normalizedRatio; int count; double dev; int nOutliers; double pval; group.GetRatio20(combinedData, out ratio, out normalizedRatio, out count, out dev, out nOutliers, fileInfo.GetRawFileIndicesFromExperiment(exp), out pval); double intensity = group.GetIntensity0(combinedData) + group.GetIntensity1(combinedData) + group.GetIntensity2(combinedData); if (normalizedRatio > 0 && !double.IsInfinity(normalizedRatio) && !double.IsNaN(normalizedRatio) && intensity > 0) { lratio.Add(Math.Log(normalizedRatio)); lIntensity.Add(Math.Log(intensity)); indices.Add(i); } } double[] ratioSignificanceA = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), 1); double[] ratioSignificanceB = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), -1); for (int i = 0; i < indices.Count; i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(indices[i]); group.AddRatioSignificanceA20(exp, ratioSignificanceA[i]); group.AddRatioSignificanceB20(exp, ratioSignificanceB[i]); } } } { List <double> lratio = new List <double>(); List <double> lIntensity = new List <double>(); List <int> indices = new List <int>(); for (int i = 0; i < combinedData.GetProteinGroupCount(); i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(i); double ratio; double normalizedRatio; int count; double dev; int nOutliers; double pval; group.GetRatio21(combinedData, out ratio, out normalizedRatio, out count, out dev, out nOutliers, out pval); double intensity = group.GetIntensity0(combinedData) + group.GetIntensity1(combinedData) + group.GetIntensity2(combinedData); if (normalizedRatio > 0 && !double.IsInfinity(normalizedRatio) && !double.IsNaN(normalizedRatio) && intensity > 0) { lratio.Add(Math.Log(normalizedRatio)); lIntensity.Add(Math.Log(intensity)); indices.Add(i); } } double[] ratioSignificanceA = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), 1); double[] ratioSignificanceB = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), -1); for (int i = 0; i < indices.Count; i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(indices[i]); group.RatioSignificanceA21 = ratioSignificanceA[i]; group.RatioSignificanceB21 = ratioSignificanceB[i]; } } if (fileInfo.HasExperiment) { string[] exps = fileInfo.GetAllExperimentValues(); foreach (string exp in exps) { List <double> lratio = new List <double>(); List <double> lIntensity = new List <double>(); List <int> indices = new List <int>(); for (int i = 0; i < combinedData.GetProteinGroupCount(); i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(i); double ratio; double normalizedRatio; int count; double dev; int nOutliers; double pval; group.GetRatio21(combinedData, out ratio, out normalizedRatio, out count, out dev, out nOutliers, fileInfo.GetRawFileIndicesFromExperiment(exp), out pval); double intensity = group.GetIntensity0(combinedData) + group.GetIntensity1(combinedData) + group.GetIntensity2(combinedData); if (normalizedRatio > 0 && !double.IsInfinity(normalizedRatio) && !double.IsNaN(normalizedRatio) && intensity > 0) { lratio.Add(Math.Log(normalizedRatio)); lIntensity.Add(Math.Log(intensity)); indices.Add(i); } } double[] ratioSignificanceA = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), 1); double[] ratioSignificanceB = NumUtil.MovingBoxPlot(lratio.ToArray(), lIntensity.ToArray(), -1); for (int i = 0; i < indices.Count; i++) { IIdentifiedProteinGroup group = combinedData.GetIProteinGroupAt(indices[i]); group.AddRatioSignificanceA21(exp, ratioSignificanceA[i]); group.AddRatioSignificanceB21(exp, ratioSignificanceB[i]); } } } } }
public override void Update(object sender, UpdateQuantificationItemEventArgs e) { IQuantificationSummaryOption option = e.Option as IQuantificationSummaryOption; panel.InitGraphPane(title, option.Func.ReferenceKey, option.Func.SampleKey, true, 0.0); IIdentifiedProteinGroup group = e.Item as IIdentifiedProteinGroup; try { var pplNormal = new PointPairList(); var pplSelected = new PointPairList(); var pplOutlier = new PointPairList(); var spectra = group.GetPeptides(); foreach (var pep in spectra) { if (option.IsPeptideRatioValid(pep)) { PointPairList ppl; if (pep.Selected) { ppl = pplSelected; } else if (option.IsPeptideOutlier(pep)) { ppl = pplOutlier; } else { ppl = pplNormal; } double sampleIntensity = option.Func.GetSampleIntensity(pep); double refIntensity = option.Func.GetReferenceIntensity(pep); ppl.Add(refIntensity, sampleIntensity); ppl[ppl.Count - 1].Tag = pep; Debug.Assert(ppl[ppl.Count - 1].Tag == pep); } } this.panel.ClearData(); this.panel.AddPoints(pplSelected, SelectedColor); this.panel.AddPoints(pplNormal, NormalColor); this.panel.AddPoints(pplOutlier, OutlierColor); var pplTotal = new PointPairList(); pplTotal.AddRange(pplSelected); pplTotal.AddRange(pplNormal); pplTotal.AddRange(pplOutlier); if (pplTotal.Count > 0) { var maxValue = (from p in pplTotal select Math.Max(p.X, p.Y)).Max() * 1.1; this.panel.XAxis.Scale.Max = maxValue; this.panel.YAxis.Scale.Max = maxValue; var ratio = option.GetProteinRatio(group[0]); PointPairList line = pplTotal.GetRegressionLine(ratio); var lineItem = this.panel.AddCurve(option.GetProteinRatioDescription(group[0]), line, RegressionLineColor, SymbolType.None); lineItem.Label.FontSpec = new FontSpec() { Size = 15, Border = new Border() { IsVisible = false } }; } } finally { ZedGraphicExtension.UpdateGraph(this.zgcGraph); } }
protected override IEnumerable <string> DoProcess(string filename, List <string> result, Dictionary <IFilter <IIdentifiedSpectrum>, SpectrumEntry> map) { string database = filename + ".fasta"; if (!File.Exists(database)) { throw new Exception("Fasta file not exists : " + database); } IAccessNumberParser acParser = AccessNumberParserFactory.GuessParser(database); Dictionary <string, Sequence> seqMap = DatabaseUtils.GetAccessNumberMap(database, acParser); try { using (IdentifiedProteinGroupEnumerator iter = new IdentifiedProteinGroupEnumerator(filename)) { foreach (IFilter <IIdentifiedSpectrum> filter in map.Keys) { SpectrumEntry entry = map[filter]; entry.ResultWriter.WriteLine(iter.ProteinFormat.GetHeader()); entry.ResultWriter.WriteLine(iter.PeptideFormat.GetHeader()); } while (iter.MoveNext()) { IIdentifiedProteinGroup group = iter.Current; List <IIdentifiedSpectrum> spectra = group[0].GetSpectra(); foreach (IFilter <IIdentifiedSpectrum> filter in map.Keys) { SpectrumEntry entry = map[filter]; entry.Spectra.Clear(); foreach (IIdentifiedSpectrum spectrum in spectra) { if (filter.Accept(spectrum)) { entry.Spectra.Add(spectrum); } } if (entry.Spectra.Count > 0) { for (int i = 0; i < group.Count; i++) { entry.ResultWriter.WriteLine("${0}-{1}{2}", group.Index, i + 1, iter.ProteinFormat.GetString(group[i])); string ac = acParser.GetValue(group[i].Name); Sequence seq = seqMap[ac]; entry.FastaWriter.WriteLine(">" + seq.Reference); entry.FastaWriter.WriteLine(seq.SeqString); } foreach (IIdentifiedSpectrum spectrum in entry.Spectra) { entry.ResultWriter.WriteLine(iter.PeptideFormat.GetString(spectrum)); } } } } return(result); } } finally { foreach (SpectrumEntry entry in map.Values) { entry.Dispose(); } } }
public bool Accept(IIdentifiedProteinGroup t) { return(t[0].UniquePeptideCount > 1 || t[0].Peptides.Count >= peptideCount); }
public QuantificationItem Calculate(IIdentifiedProteinGroup proteinGroup, Func <IIdentifiedSpectrum, bool> validFunc) { List <IIdentifiedSpectrum> spectra = (from s in proteinGroup[0].GetSpectra() where s.IsEnabled(true) && validFunc(s) select s).ToList(); if (spectra.Count == 1) { var item = spectra[0].GetQuantificationItem(); return(new QuantificationItem() { Enabled = true, Ratio = item.Ratio, Correlation = item.Correlation, SampleIntensity = item.SampleIntensity, ReferenceIntensity = item.ReferenceIntensity }); } if (spectra.Count > 1) { var sampleIntensities = new List <double>(); var refIntensities = new List <double>(); spectra.ForEach(m => { sampleIntensities.Add(m.GetQuantificationItem().SampleIntensity); refIntensities.Add(m.GetQuantificationItem().ReferenceIntensity); }); var intensities = new double[2][]; intensities[0] = refIntensities.ToArray(); intensities[1] = sampleIntensities.ToArray(); LinearRegressionRatioResult lrrr = LinearRegressionRatioCalculator.CalculateRatio(intensities); double sampleIntensity, refIntensity; if (lrrr.Ratio > 1) { sampleIntensities.Sort(); sampleIntensity = sampleIntensities[sampleIntensities.Count - 1]; refIntensity = sampleIntensity / lrrr.Ratio; } else { refIntensities.Sort(); refIntensity = refIntensities[refIntensities.Count - 1]; sampleIntensity = refIntensity * lrrr.Ratio; } return(new QuantificationItem() { Enabled = true, Ratio = lrrr.Ratio, Correlation = lrrr.RSquare, SampleIntensity = sampleIntensity, ReferenceIntensity = refIntensity }); } return(new QuantificationItem() { Enabled = false }); }
public void Calculate(IIdentifiedProteinGroup proteinGroup, Func <IIdentifiedSpectrum, bool> validFunc) { DoCalculate(proteinGroup, validFunc, true); }
public override void Update(object sender, UpdateQuantificationItemEventArgs e) { IExtendQuantificationSummaryOption option = e.Option as IExtendQuantificationSummaryOption; string xTitle = string.Format("Log({0})", option.Func.ReferenceKey); string yTitle = string.Format("Log({0})", option.Func.SampleKey); panel.InitGraphPane(title, xTitle, yTitle, true, 0.0); IIdentifiedProteinGroup group = e.Item as IIdentifiedProteinGroup; try { Dictionary <string, List <PointPairList> > pplMap = new Dictionary <string, List <PointPairList> >(); var pplNormal = new PointPairList(); var pplSelected = new PointPairList(); var pplOutlier = new PointPairList(); var spectra = group.GetPeptides(); foreach (var pep in spectra) { if (pep.IsEnabled(true) && option.IsPeptideRatioValid(pep)) { var key = option.GetPeptideClassification(pep); if (!pplMap.ContainsKey(key)) { var lst = new List <PointPairList>(); pplMap[key] = lst; lst.Add(new PointPairList()); //selected lst.Add(new PointPairList()); //outlier lst.Add(new PointPairList()); //normal } var ppls = pplMap[key]; PointPairList ppl; if (pep.Selected) { ppl = ppls[0]; } else if (option.IsPeptideOutlier(pep)) { ppl = ppls[1]; } else { ppl = ppls[2]; } double refIntensity = option.Func.GetReferenceIntensity(pep); double sampleIntensity = option.Func.GetSampleIntensity(pep); ppl.Add(refIntensity, sampleIntensity); ppl[ppl.Count - 1].Tag = pep; Debug.Assert(ppl[ppl.Count - 1].Tag == pep); } } this.panel.ClearData(); foreach (var key in pplMap.Keys) { var ppls = pplMap[key]; this.panel.AddPoints(ppls[0], SelectedColor); this.panel.AddPoints(ppls[1], NormalColor); this.panel.AddPoints(ppls[2], OutlierColor); var pplTotal = new PointPairList(); pplTotal.AddRange(ppls[0]); pplTotal.AddRange(ppls[1]); pplTotal.AddRange(ppls[2]); if (pplTotal.Count > 0) { PointPairList line = ZedGraphicExtension.GetRegressionLine(pplTotal, option.GetProteinRatio(group[0], key)); var lineItem = this.panel.AddCurve(option.GetProteinRatioDescription(group[0], key), line, RegressionLineColor, SymbolType.None); lineItem.Label.FontSpec = new FontSpec() { Size = 15, Border = new Border() { IsVisible = false } }; } } } finally { ZedGraphicExtension.UpdateGraph(this.zgcGraph); } }
public bool Accept(IIdentifiedProteinGroup t) { return(t.Any(m => conRegex.Match(m.Reference).Success)); }
public override void Update(object sender, UpdateQuantificationItemEventArgs e) { IQuantificationSummaryOption option = e.Option as IQuantificationSummaryOption; panel.InitGraphPane(title, option.Func.ReferenceKey, option.Func.SampleKey, true, 0.0); IIdentifiedProteinGroup group = e.Item as IIdentifiedProteinGroup; try { var pplNormal = new PointPairList(); var pplSelected = new PointPairList(); var spectra = group.GetPeptides(); var format = new O18QuantificationSummaryItemXmlFormat(); foreach (var pep in spectra) { if (pep.IsEnabled(true) && option.IsPeptideRatioValid(pep)) { string ratioFile = GetRatioFile(option, pep); if (ratioFile == null) { continue; } O18QuantificationSummaryItem item = new O18QuantificationSummaryItemXmlFormat().ReadFromFile(ratioFile); item.CalculateIndividualAbundance(); PointPairList ppl; if (pep.Selected) { ppl = pplSelected; } else { ppl = pplNormal; } foreach (var envelope in item.ObservedEnvelopes) { if (!envelope.Enabled) { continue; } double refIntensity = envelope.SampleAbundance.O16; double sampleIntensity = envelope.SampleAbundance.O18; if (refIntensity == 0.0 || sampleIntensity == 0.0) { continue; } ppl.Add(refIntensity, sampleIntensity); ppl[ppl.Count - 1].Tag = pep; Debug.Assert(ppl[ppl.Count - 1].Tag == pep); } } } this.panel.ClearData(); this.panel.AddPoints(pplSelected, SelectedColor); this.panel.AddPoints(pplNormal, NormalColor); var pplTotal = new PointPairList(); pplTotal.AddRange(pplSelected); pplTotal.AddRange(pplNormal); if (pplTotal.Count > 0) { var maxValue = (from p in pplTotal select Math.Max(p.X, p.Y)).Max() * 1.1; this.panel.XAxis.Scale.Max = maxValue; this.panel.YAxis.Scale.Max = maxValue; var ratio = option.GetProteinRatio(group[0]); PointPairList line = pplTotal.GetRegressionLine(ratio); var lineItem = this.panel.AddCurve(option.GetProteinRatioDescription(group[0]), line, RegressionLineColor, SymbolType.None); lineItem.Label.FontSpec = new FontSpec() { Size = 15, Border = new Border() { IsVisible = false } }; } } finally { ZedGraphicExtension.UpdateGraph(this.zgcGraph); } }
public void SetUp() { group = new IdentifiedProteinGroup(); group.Add(new IdentifiedProtein("SHORT") { Sequence = shortSeq }); group.Add(new IdentifiedProtein("LONG") { Sequence = longSeq }); }
private WaitingEntry DoCalculate(IIdentifiedProteinGroup proteinGroup, Func <IIdentifiedSpectrum, bool> validFunc, bool runRImmediately) { List <IIdentifiedSpectrum> spectra = (from s in proteinGroup[0].GetSpectra() where validFunc(s) && s.IsEnabled(true) && HasPeptideRatio(s) select s).ToList(); if (spectra.Count == 1) { var r = CalculatePeptideRatio(spectra[0]); foreach (var protein in proteinGroup) { protein.SetEnabled(true); protein.Annotations[O18QuantificationConstants.O18_RATIO] = new LinearRegressionRatioResult(r, 0.0) { PointCount = 1, FCalculatedValue = 0, FProbability = 1 }; protein.Annotations[this.intensityFunc.ReferenceKey] = spectra[0].Annotations[this.intensityFunc.ReferenceKey]; protein.Annotations[this.intensityFunc.SampleKey] = spectra[0].Annotations[this.intensityFunc.SampleKey]; } return(null); } else if (spectra.Count > 1) { var intensities = this.intensityFunc.ConvertToArray(spectra); double maxSam = intensities[0].Max(); double maxRef = intensities[1].Max(); LinearRegressionRatioResult ratioResult; if (maxSam == 0.0) { ratioResult = new LinearRegressionRatioResult(20, 0.0) { PointCount = intensities.Count(), FCalculatedValue = 0, FProbability = 0 }; maxSam = maxRef / ratioResult.Ratio; } else { if (maxRef == 0.0) { ratioResult = new LinearRegressionRatioResult(0.05, 0.0) { PointCount = intensities.Count(), FCalculatedValue = 0, FProbability = 0 }; } else { var dd = this.SummaryFileDirectory + "/" + this.DetailDirectory + "/"; var filename = (dd + proteinGroup[0].Name.Replace("|", "_") + ".csv").Replace("\\", "/"); PrepareIntensityFile(spectra, filename); if (!runRImmediately) { return(new WaitingEntry() { Group = proteinGroup, IntensityFile = filename, MaxReference = maxRef, MaxSample = maxSam }); } var linearfile = filename + ".linear"; var rfile = filename + ".r"; using (StreamWriter sw = new StreamWriter(rfile)) { sw.WriteLine(string.Format( @"require(MASS) data<-read.csv(""{0}"") yxPCA<-PcaHubert(~0+SamIntensity+RefIntensity, data=data) r<-yxPCA@loadings[1,1]/yxPCA@loadings[2,1] df<-data.frame(Ratio=r) colnames(df)<-c(""Ratio"") write.csv(df,""{1}"") ", filename, linearfile)); } new RProcessor(rExecute, rfile, linearfile).Process(); ratioResult = new LinearRegressionRatioResult(); var parts = File.ReadAllLines(linearfile).Skip(1).First().Split(','); ratioResult.Ratio = double.Parse(parts[1]); ratioResult.RSquare = 0; ratioResult.FCalculatedValue = 0; ratioResult.FProbability = 0; } maxRef = maxSam * ratioResult.Ratio; } foreach (IIdentifiedProtein protein in proteinGroup) { protein.SetEnabled(true); protein.Annotations[O18QuantificationConstants.O18_RATIO] = ratioResult; protein.Annotations[this.intensityFunc.ReferenceKey] = maxRef; protein.Annotations[this.intensityFunc.SampleKey] = maxSam; } } else { foreach (IIdentifiedProtein protein in proteinGroup) { protein.SetEnabled(false); protein.Annotations.Remove(O18QuantificationConstants.O18_RATIO); protein.Annotations.Remove(this.intensityFunc.ReferenceKey); protein.Annotations.Remove(this.intensityFunc.SampleKey); } } return(null); }
public bool Accept(IIdentifiedProteinGroup t) { return(acceptFunc(t)); }