Ejemplo n.º 1
0
        public LipidGroupSearchResult(LipidTarget lipidTarget, List <Lipid> lipidList, SpectrumSearchResult spectrumSearchResult, ScoreModel scoreModel)
        {
            LipidTarget          = lipidTarget;
            LipidList            = lipidList;
            SpectrumSearchResult = spectrumSearchResult;
            ShouldExport         = false;
            Score = scoreModel.ScoreLipid(this);

            if (spectrumSearchResult.HcdSpectrum != null)
            {
                DisplayScanNum = spectrumSearchResult.HcdSpectrum.ScanNum;
                DisplayMz      = spectrumSearchResult.HcdSpectrum.IsolationWindow.IsolationWindowTargetMz;
            }
            else if (spectrumSearchResult.CidSpectrum != null)
            {
                DisplayScanNum = spectrumSearchResult.CidSpectrum.ScanNum;
                DisplayMz      = spectrumSearchResult.CidSpectrum.IsolationWindow.IsolationWindowTargetMz;
            }

            if (spectrumSearchResult.PrecursorSpectrum == null)
            {
                return;
            }

            var pearsonCorrelationCalculator = new PearsonCorrelationFitUtil();

            PearsonCorrScore       = pearsonCorrelationCalculator.GetFitScore(spectrumSearchResult, lipidTarget.Composition);
            PearsonCorrScoreMinus1 = pearsonCorrelationCalculator.GetFitMinus1Score(spectrumSearchResult, lipidTarget.Composition);

            var cosineCalculator = new CosineFitUtil();

            CosineScore       = cosineCalculator.GetFitScore(spectrumSearchResult, lipidTarget.Composition);
            CosineScoreMinus1 = cosineCalculator.GetFitMinus1Score(spectrumSearchResult, lipidTarget.Composition);
        }
Ejemplo n.º 2
0
        public void TestPearsonCorrelation(int precursor, string commonName, string composition, Tolerance tolerance)
        {
            var rawFilePath = @"\\proto-2\UnitTest_Files\Liquid\PearsonCorrelationTests\OMICS_IM102_691_1d_Lipid_pooled_POS_150mm_17Apr15_Polaroid_14-12-16.raw";

            var lcmsRun = PbfLcMsRun.GetLcMsRun(rawFilePath);

            var spectrum = lcmsRun.GetSpectrum(precursor);

            var parsedComposition     = Composition.ParseFromPlainString(composition);
            var correlationCalculator = new PearsonCorrelationFitUtil();
            //var target = new LipidTarget(commonName, LipidClass.DG, FragmentationMode.Positive, parsedComposition, new List<AcylChain>(), Adduct.Hydrogen);
            var spectrumSearchResult = new SpectrumSearchResult(null, null, spectrum, null, null, new Xic(), lcmsRun)
            {
                PrecursorTolerance = tolerance
            };
            var correlation = correlationCalculator.GetFitScore(spectrumSearchResult, parsedComposition);

            Console.WriteLine("The Pearson correlation is: " + correlation);
        }
Ejemplo n.º 3
0
        public void PearsonCorrelationFileCombiner(string directoryPath)
        {
            var dirFiles = Directory.GetFiles(directoryPath);

            var correlationCalculator = new PearsonCorrelationFitUtil();
            var cosineCalculator      = new CosineFitUtil();

            // Each dictionary corresponds to a dataset, each dictionary key corresponds to the TSV header.
            var results = new List <Dictionary <string, List <string> > >();
            var headers = new HashSet <string>();

            foreach (var pathToResults in dirFiles.Where(path => path.EndsWith(".txt")))
            {
                var datasetName = Path.GetFileNameWithoutExtension(pathToResults);
                var pathToRaw   = GetRawFilePath(directoryPath, datasetName);
                var rawName     = Path.GetFileName(pathToRaw);
                if (string.IsNullOrEmpty(pathToRaw))
                {
                    continue;
                }

                var lcmsRun   = PbfLcMsRun.GetLcMsRun(pathToRaw);
                var tolerance = new Tolerance(30, ToleranceUnit.Ppm);
                using (var reader = new StreamReader(new FileStream(pathToResults, FileMode.Open, FileAccess.Read, FileShare.ReadWrite)))
                {
                    results.Add(new Dictionary <string, List <string> >()); // Add dictionary for new dataset.
                    var datasetResults = results.Last();                    // Results for the current dataset.
                    var lineCount      = 0;
                    var headerToIndex  = new Dictionary <string, int>();
                    while (!reader.EndOfStream)
                    {
                        var line = reader.ReadLine();
                        if (string.IsNullOrWhiteSpace(line))
                        {
                            continue;
                        }

                        var pieces = line.Split('\t').ToArray();

                        if (lineCount++ == 0)
                        {   // First line
                            for (var i = 0; i < pieces.Length; i++)
                            {
                                var header = pieces[i];
                                headerToIndex.Add(header, i);
                                datasetResults.Add(header, new List <string>());
                            }

                            datasetResults.Add("Raw File", new List <string>());
                            datasetResults.Add("Pearson Corr Score", new List <string>());
                            datasetResults.Add("Pearson Corr M-1 Score", new List <string>());
                            datasetResults.Add("Cosine Score", new List <string>());
                            datasetResults.Add("Cosine M-1 Score", new List <string>());
                            headers.UnionWith(datasetResults.Keys);
                            continue;
                        }

                        var precursor  = Convert.ToInt32(pieces[headerToIndex["Precursor Scan"]]);
                        var commonName = pieces[headerToIndex["Common Name"]];
                        var adduct     = pieces[headerToIndex["Adduct"]];
                        var spectrum   = lcmsRun.GetSpectrum(precursor);
                        if (spectrum == null)
                        {
                            Console.WriteLine("Invalid scan number: {0}", precursor);
                            continue;
                        }

                        var lipid = new Lipid {
                            AdductFull = adduct, CommonName = commonName
                        };
                        var lipidTarget          = lipid.CreateLipidTarget();
                        var spectrumSearchResult = new SpectrumSearchResult(null, null, spectrum, null, null, new Xic(), lcmsRun)
                        {
                            PrecursorTolerance = tolerance
                        };
                        var pearsonCorrScore       = correlationCalculator.GetFitScore(spectrumSearchResult, lipidTarget.Composition);
                        var pearsonCorrMinus1Score = correlationCalculator.GetFitMinus1Score(spectrumSearchResult, lipidTarget.Composition);
                        var cosineScore            = cosineCalculator.GetFitScore(spectrumSearchResult, lipidTarget.Composition);
                        var cosineMinus1Score      = cosineCalculator.GetFitScore(
                            spectrumSearchResult,
                            lipidTarget.Composition);

                        // Add results to results dictionary.
                        datasetResults["Raw File"].Add(rawName);
                        foreach (var header in headerToIndex.Keys)
                        {
                            datasetResults[header].Add(pieces[headerToIndex[header]]);
                        }

                        datasetResults["Pearson Corr Score"].Add(pearsonCorrScore.ToString());
                        datasetResults["Pearson Corr M-1 Score"].Add(pearsonCorrMinus1Score.ToString());
                        datasetResults["Cosine Score"].Add(cosineScore.ToString());
                        datasetResults["Cosine M-1 Score"].Add(cosineMinus1Score.ToString());
                    }
                }
            }

            // Write results
            var outputFilePath = Path.Combine(directoryPath, "training.tsv");

            using (var writer = new StreamWriter(outputFilePath))
            {
                // Write headers
                foreach (var header in headers)
                {
                    writer.Write("{0}\t", header);
                }

                writer.WriteLine();

                // Write data
                foreach (var datasetResults in results)
                {
                    var fileLength = datasetResults["Pearson Corr Score"].Count;
                    for (var i = 0; i < fileLength; i++)
                    {
                        foreach (var header in headers)
                        {
                            var value = datasetResults.ContainsKey(header) ? datasetResults[header][i] : string.Empty;
                            writer.Write("{0}\t", value);
                        }

                        writer.WriteLine();
                    }
                }
            }
        }
Ejemplo n.º 4
0
        public void TestPearsonCorrelationWholeFile(string directoryPath)
        {
            var dirFiles = Directory.GetFiles(directoryPath);

            var correlationCalculator = new PearsonCorrelationFitUtil();

            foreach (var pathToResults in dirFiles.Where(path => path.EndsWith(".txt")))
            {
                var datasetName = Path.GetFileNameWithoutExtension(pathToResults);
                var pathToRaw   = GetRawFilePath(directoryPath, datasetName);
                if (string.IsNullOrEmpty(pathToRaw))
                {
                    continue;
                }

                var lcmsRun        = PbfLcMsRun.GetLcMsRun(pathToRaw);
                var tolerance      = new Tolerance(30, ToleranceUnit.Ppm);
                var rawFileName    = Path.GetFileName(pathToRaw);
                var datasetDirPath = Path.GetDirectoryName(pathToResults);
                var outputFileName = string.Format("{0}_training.tsv", datasetName);
                var outputPath     = Path.Combine(datasetDirPath, outputFileName);
                using (var writer = new StreamWriter(outputPath))
                    using (var reader = new StreamReader(new FileStream(pathToResults, FileMode.Open, FileAccess.Read, FileShare.ReadWrite)))
                    {
                        var lineCount     = 0;
                        var headerToIndex = new Dictionary <string, int>();
                        while (!reader.EndOfStream)
                        {
                            var line = reader.ReadLine();
                            if (string.IsNullOrWhiteSpace(line))
                            {
                                continue;
                            }

                            var pieces = line.Split('\t').ToArray();

                            if (lineCount++ == 0)
                            { // First line
                                writer.Write("Raw File\t");
                                for (var i = 0; i < pieces.Length; i++)
                                {
                                    headerToIndex.Add(pieces[i], i);
                                    writer.Write("{0}\t", pieces[i]);
                                }

                                writer.WriteLine("Fit Score\tFit M-1 Score");

                                continue;
                            }

                            var precursor  = Convert.ToInt32(pieces[headerToIndex["Precursor Scan"]]);
                            var commonName = pieces[headerToIndex["Common Name"]];
                            var adduct     = pieces[headerToIndex["Adduct"]];
                            var spectrum   = lcmsRun.GetSpectrum(precursor);
                            if (spectrum == null)
                            {
                                Console.WriteLine("Invalid scan number: {0}", precursor);
                                continue;
                            }

                            var lipid = new Lipid {
                                AdductFull = adduct, CommonName = commonName
                            };
                            var lipidTarget          = lipid.CreateLipidTarget();
                            var spectrumSearchResult = new SpectrumSearchResult(null, null, spectrum, null, null, new Xic(), lcmsRun)
                            {
                                PrecursorTolerance = tolerance
                            };
                            var fitScore       = correlationCalculator.GetFitScore(spectrumSearchResult, lipidTarget.Composition);
                            var fitMinus1Score = correlationCalculator.GetFitMinus1Score(spectrumSearchResult, lipidTarget.Composition);

                            writer.Write(rawFileName + "\t");
                            writer.Write(line);

                            writer.WriteLine("{0}\t{1}", fitScore, fitMinus1Score);
                        }
                    }
            }
        }