Example #1
0
        public MsToLcmsFeatures(IScanSummaryProvider provider, LcmsFeatureFindingOptions options = null)
        {
            if (provider == null)
            {
                throw new ArgumentNullException();
            }

            Comparison <MSFeatureLight> mzSort   = (x, y) => x.Mz.CompareTo(y.Mz);
            Comparison <UMCLight>       monoSort = (x, y) => x.MassMonoisotopic.CompareTo(y.MassMonoisotopic);
            Func <MSFeatureLight, MSFeatureLight, double> mzDiff   = (x, y) => FeatureLight.ComputeMassPPMDifference(x.Mz, y.Mz);
            Func <UMCLight, UMCLight, double>             monoDiff = (x, y) => FeatureLight.ComputeMassPPMDifference(x.MassMonoisotopic, y.MassMonoisotopic);

            this.provider = provider;
            this.options  = options ?? new LcmsFeatureFindingOptions();

            // Set clusterers
            if (this.options.FirstPassClusterer == MsFeatureClusteringAlgorithmType.BinarySearchTree)
            {
                this.firstPassClusterer = new MsFeatureTreeClusterer <MSFeatureLight, UMCLight>(
                    mzSort,
                    mzDiff,
                    MassComparison.Mz,
                    this.options.InstrumentTolerances.Mass);
            }
            else
            {
                this.firstPassClusterer = ClusterFactory.Create(this.options.FirstPassClusterer);
            }

            if (this.options.SecondPassClusterer == GenericClusteringAlgorithmType.BinarySearchTree)
            {
                this.secondPassClusterer = new MsFeatureTreeClusterer <UMCLight, UMCLight>(
                    monoSort,
                    monoDiff,
                    MassComparison.Monoisotopic,
                    this.options.InstrumentTolerances.Mass);
            }
            else
            {
                var clusterFactory = new GenericClusterFactory <UMCLight, UMCLight>();
                this.secondPassClusterer = clusterFactory.Create(this.options.SecondPassClusterer);
            }
        }
Example #2
0
        public void TestClustering(
            string directory,
            string outputPath,
            FeatureAlignmentType alignmentType,
            LcmsFeatureClusteringAlgorithmType clusterType)
        {
            var matchPath = string.Format("{0}.txt", outputPath);
            var errorPath = string.Format("{0}-errors.txt", outputPath);

            // Loads the supported MultiAlign types
            var supportedTypes = DatasetLoader.SupportedFileTypes;
            var extensions     = new List <string>();

            supportedTypes.ForEach(x => extensions.Add("*" + x.Extension));

            // Find our datasets
            var datasetLoader = new DatasetLoader();
            var datasets      = datasetLoader.GetValidDatasets(directory, extensions, SearchOption.TopDirectoryOnly);

            // Setup our alignment options
            var alignmentOptions = new AlignmentOptions();
            var spectralOptions  = new SpectralOptions
            {
                ComparerType      = SpectralComparison.CosineDotProduct,
                Fdr               = .01,
                IdScore           = 1e-09,
                MzBinSize         = .5,
                MzTolerance       = .5,
                NetTolerance      = .1,
                RequiredPeakCount = 32,
                SimilarityCutoff  = .75,
                TopIonPercent     = .8
            };


            // Options setup
            var instrumentOptions = InstrumentPresetFactory.Create(InstrumentPresets.LtqOrbitrap);
            var featureTolerances = new FeatureTolerances
            {
                Mass      = instrumentOptions.Mass + 6,
                Net       = instrumentOptions.NetTolerance,
                DriftTime = instrumentOptions.DriftTimeTolerance
            };
            var featureFindingOptions = new LcmsFeatureFindingOptions(featureTolerances)
            {
                MaximumNetRange  = .002,
                MaximumScanRange = 50
            };

            // Create our algorithms
            var finder  = FeatureFinderFactory.CreateFeatureFinder(FeatureFinderType.TreeBased);
            var aligner = FeatureAlignerFactory.CreateDatasetAligner(alignmentType,
                                                                     alignmentOptions.LCMSWarpOptions,
                                                                     spectralOptions);
            var clusterer = ClusterFactory.Create(clusterType);

            clusterer.Parameters = new FeatureClusterParameters <UMCLight>
            {
                Tolerances = featureTolerances
            };

            RegisterProgressNotifier(aligner);
            RegisterProgressNotifier(finder);
            RegisterProgressNotifier(clusterer);

            var lcmsFilters = new LcmsFeatureFilteringOptions
            {
                FeatureLengthRangeScans = new FilterRange(50, 300)
            };
            var msFilterOptions = new MsFeatureFilteringOptions
            {
                MinimumIntensity           = 5000,
                ChargeRange                = new FilterRange(1, 6),
                ShouldUseChargeFilter      = true,
                ShouldUseDeisotopingFilter = true,
                ShouldUseIntensityFilter   = true
            };

            for (var i = 0; i < 1; i++)
            {
                var aligneeDatasets = datasets.Where((t, j) => j != i).ToList();
                PerformMultiAlignAnalysis(datasets[0],
                                          aligneeDatasets,
                                          featureFindingOptions,
                                          msFilterOptions,
                                          lcmsFilters,
                                          spectralOptions,
                                          finder,
                                          aligner,
                                          clusterer,
                                          matchPath,
                                          errorPath);
            }
        }
Example #3
0
        public void GenerateClusterAlignmentStatistics(string relativeDatabasePath,
                                                       string relativeName,
                                                       string name,
                                                       FeatureAlignmentType alignmentType,
                                                       LcmsFeatureClusteringAlgorithmType clusterType)
        {
            var databasePath = GetPath(relativeDatabasePath);
            var outputPath   = GetOutputPath(relativeName);

            if (!Directory.Exists(outputPath))
            {
                Directory.CreateDirectory(outputPath);
            }

            // Connect to the NHibernate database
            var providers = DataAccessFactory.CreateDataAccessProviders(databasePath, false);

            // Setup our alignment options
            var alignmentOptions = new AlignmentOptions();
            var spectralOptions  = new SpectralOptions
            {
                ComparerType      = SpectralComparison.CosineDotProduct,
                Fdr               = .01,
                IdScore           = 1e-09,
                MzBinSize         = .5,
                MzTolerance       = .5,
                NetTolerance      = .1,
                RequiredPeakCount = 32,
                SimilarityCutoff  = .75,
                TopIonPercent     = .8
            };

            // Options setup
            var instrumentOptions = InstrumentPresetFactory.Create(InstrumentPresets.LtqOrbitrap);
            var featureTolerances = new FeatureTolerances
            {
                Mass      = instrumentOptions.Mass + 6,
                Net       = instrumentOptions.NetTolerance,
                DriftTime = instrumentOptions.DriftTimeTolerance
            };

            UpdateStatus("Retrieving all datasets for test.");
            var datasets = providers.DatasetCache.FindAll();

            // Create our algorithms
            var aligner = FeatureAlignerFactory.CreateDatasetAligner(alignmentType,
                                                                     alignmentOptions.LCMSWarpOptions,
                                                                     spectralOptions);
            var clusterer = ClusterFactory.Create(clusterType);

            clusterer.Parameters = new FeatureClusterParameters <UMCLight>
            {
                Tolerances = featureTolerances
            };

            RegisterProgressNotifier(aligner);
            RegisterProgressNotifier(clusterer);

            for (var i = 0; i < datasets.Count - 1; i++)
            {
                var matchPath = string.Format("{0}-{1}-matches.txt", name, i);
                var errorPath = string.Format("{0}-{1}-errors.txt", name, i);

                matchPath = Path.Combine(outputPath, matchPath);
                errorPath = Path.Combine(outputPath, errorPath);



                var aligneeDataset  = datasets[i + 1];
                var baselineDataset = datasets[i];

                // Load the baseline reference set
                using (var rawProviderX = new InformedProteomicsReader())
                {
                    rawProviderX.AddDataFile(baselineDataset.RawFile.Path, 0);
                    // Load the baseline reference set
                    using (var rawProviderY = new InformedProteomicsReader())
                    {
                        rawProviderY.AddDataFile(aligneeDataset.RawFile.Path, 0);

                        var baselineFeatures = RetrieveFeatures(baselineDataset.DatasetId, providers);
                        var aligneeFeatures  = RetrieveFeatures(aligneeDataset.DatasetId, providers);
                        var providerX        = new CachedFeatureSpectraProvider(rawProviderX, baselineFeatures);
                        var providerY        = new CachedFeatureSpectraProvider(rawProviderY, aligneeFeatures);

                        AlignDatasets(baselineFeatures,
                                      aligneeFeatures,
                                      providerX,
                                      providerY,
                                      aligner,
                                      clusterer,
                                      matchPath,
                                      errorPath);
                    }
                }
            }
        }