/// <summary>
/// Finds features
/// </summary>
/// <returns></returns>
public List <UMCLight> FindFeatures(List <MSFeatureLight> msFeatures,
LcmsFeatureFindingOptions options, IScanSummaryProvider provider,
IProgress <ProgressData> progress = null)
{
if (provider == null)
{
throw new ArgumentNullException(nameof(provider));
}
var tolerances = new FeatureTolerances
{
Mass = options.InstrumentTolerances.Mass,
Net = options.MaximumNetRange
};
var clusterer = new MsToLcmsFeatures(provider, options);
// MultiAlignCore.Algorithms.FeatureClustering.MsFeatureTreeClusterer
//var clusterer = new MsFeatureTreeClusterer<MSFeatureLight, UMCLight>
//{
// Tolerances =
// new FeatureTolerances
// {
// Mass = options.InstrumentTolerances.Mass,
// Net = options.MaximumNetRange
// },
// ScanTolerance = options.MaximumScanRange,
// SpectraProvider = (InformedProteomicsReader) provider
// //TODO: Make sure we have a mass range for XIC's too....
//};
//clusterer.SpectraProvider = (InformedProteomicsReader) provider;
//OnStatus("Starting cluster definition");
//clusterer.Progress += (sender, args) => OnStatus(args.Message);
var features = clusterer.Convert(msFeatures, progress);
var minScan = int.MaxValue;
var maxScan = int.MinValue;
foreach (var feature in msFeatures)
{
minScan = Math.Min(feature.Scan, minScan);
maxScan = Math.Max(feature.Scan, maxScan);
}
var minScanTime = provider.GetScanSummary(minScan).Time;
var maxScanTime = provider.GetScanSummary(maxScan).Time;
var id = 0;
var newFeatures = new List <UMCLight>();
foreach (var feature in features)
{
if (feature.MsFeatures.Count < 1)
{
continue;
}
feature.Net = (provider.GetScanSummary(feature.Scan).Time - minScanTime) /
(maxScanTime - minScanTime);
feature.CalculateStatistics();
feature.Id = id++;
newFeatures.Add(feature);
//Sets the width of the feature to be the width of the peak, not the width of the tails
var maxAbundance = double.MinValue;
var maxAbundanceIndex = 0;
for (var msFeatureIndex = 0; msFeatureIndex < feature.MsFeatures.Count - 1; msFeatureIndex++)
{
var msFeature = feature.MsFeatures[msFeatureIndex];
if (msFeature.Abundance > maxAbundance)
{
maxAbundance = msFeature.Abundance;
maxAbundanceIndex = msFeatureIndex;
}
}
for (var msFeatureIndex = maxAbundanceIndex; msFeatureIndex > 0; msFeatureIndex--)
{
if (feature.MsFeatures[msFeatureIndex].Abundance / maxAbundance <= 0.05)
{
feature.ScanStart = feature.MsFeatures[msFeatureIndex].Scan;
break;
}
}
for (var msFeatureIndex = maxAbundanceIndex; msFeatureIndex < feature.MsFeatures.Count - 1; msFeatureIndex++)
{
if (feature.MsFeatures[msFeatureIndex].Abundance / maxAbundance <= 0.05)
{
feature.ScanEnd = feature.MsFeatures[msFeatureIndex].Scan;
break;
}
}
}
return(features);
}
public void CompareMs2IdsToMs1Ids(string liquidResultsPath, string isosFile, string rawFile)
{
// Read mass tags.
var massTagReader = new LiquidResultsFileLoader(liquidResultsPath);
var massTags = massTagReader.LoadDatabase();
// Get identifications - this rereads the liquid results file, but I'm leaving it that way
// for now because this is just a test.
var scansToIds = this.GetIds(liquidResultsPath);
// Read raw data file.
var spectraProviderCache = new SpectraProviderCache();
var spectraProvider = spectraProviderCache.GetSpectraProvider(rawFile);
// Read isos features
var isosReader = new MsFeatureLightFileReader();
isosReader.IsosFilteroptions = new DeconToolsIsosFilterOptions {
MaximumIsotopicFit = 0.15
};
var msFeatures = isosReader.ReadFile(isosFile).ToList();
// Get LCMS features
var msFeatureClusterer = new MsToLcmsFeatures(spectraProvider);
var lcmsFeatures = msFeatureClusterer.Convert(msFeatures);
lcmsFeatures.ForEach(feature => { feature.NetAligned = feature.Net; feature.MassMonoisotopicAligned = feature.MassMonoisotopic; });
// Create clusters - Since this is only working on a single dataset, there should be a 1:1 mapping
// between LCMS features and clusters.
var clusters = new List <UMCClusterLight> {
Capacity = lcmsFeatures.Count
};
foreach (var lcmsFeature in lcmsFeatures)
{
var cluster = new UMCClusterLight(lcmsFeature);
cluster.CalculateStatistics(ClusterCentroidRepresentation.Median);
clusters.Add(cluster);
}
// Do STAC AMT matching
var stacAdapter = new STACAdapter <UMCClusterLight>
{
Options = new FeatureMatcherParameters
{
ShouldCalculateShiftFDR = false,
UsePriors = true,
UseEllipsoid = true,
UseDriftTime = false,
ShouldCalculateSTAC = true,
}
};
var amtMatches = stacAdapter.PerformPeakMatching(clusters, massTags);
// Group AMT matches by cluster, convert MassTags to Protein objects (represents lipid ID,
// rather than Protein ID here) for simplicity in comparing them to the MS/MS IDs.
var ms1Matches = clusters.ToDictionary(cluster => cluster, cluster => new List <Protein>());
foreach (var amtMatch in amtMatches)
{
var cluster = amtMatch.Observed;
var massTag = amtMatch.Target;
ms1Matches[cluster].Add(new Protein
{
Name = massTag.ProteinName,
Sequence = massTag.PeptideSequence,
ChemicalFormula = massTag.PeptideSequence
});
}
// Now we need to backtrack MS/MS identifications -> clusters
var ms2Matches = new Dictionary <UMCClusterLight, List <Protein> >();
foreach (var cluster in clusters)
{
ms2Matches.Add(cluster, new List <Protein>());
foreach (var lcmsFeature in cluster.UmcList)
{
foreach (var msFeature in lcmsFeature.MsFeatures)
{
foreach (var msmsFeature in msFeature.MSnSpectra)
{
if (scansToIds.ContainsKey(msmsFeature.Scan))
{
ms2Matches[cluster].AddRange(scansToIds[msmsFeature.Scan]);
}
}
}
}
}
// How many clusters have IDs from MS/MS?
var clusterMs1IdCount = ms1Matches.Values.Count(value => value.Any());
var clusterMs2IdCount = ms2Matches.Values.Count(value => value.Any());
int overlapCount = 0; // Number of IDs that overlapped between MS1 and MS2 identifications.
// Finally compare the MS1 IDs to the MS2 IDs.
foreach (var cluster in clusters)
{
// For now only comparing by name
var ms1Ids = ms1Matches[cluster];
var ms1Lipids = ms1Ids.Select(id => id.Name);
var ms2Ids = ms2Matches[cluster];
var ms2Lipids = ms2Ids.Select(id => id.Name);
// Compare MS1 IDs for the cluster vs MS2 IDs for the cluster.
var ms1OnlyIds = ms1Lipids.Where(lipid => !ms2Lipids.Contains(lipid));
var ms2OnlyIds = ms2Lipids.Where(lipid => !ms1Lipids.Contains(lipid));
overlapCount += ms1OnlyIds.Intersect(ms2OnlyIds).Count();
// Write Results
if (ms1OnlyIds.Any() || ms2OnlyIds.Any())
{
Console.WriteLine("Cluster {0}:", cluster.Id);
if (ms1OnlyIds.Any())
{
Console.WriteLine("\tMs1 Only IDs:");
foreach (var id in ms1OnlyIds)
{
Console.WriteLine("\t\t{0}", id);
}
}
if (ms2OnlyIds.Any())
{
Console.WriteLine("\tMs2 Only IDs:");
foreach (var id in ms2OnlyIds)
{
Console.WriteLine("\t\t{0}", id);
}
}
}
}
Console.WriteLine("Overlap: {0}", overlapCount);
}
