/// <summary>
/// Runs the MultiAlign analysis
/// </summary>
public void AlignDatasets( IEnumerable<UMCLight> baselineFeatures,
IEnumerable<UMCLight> aligneeFeatures,
ISpectraProvider providerX,
ISpectraProvider providerY,
IFeatureAligner<IEnumerable<UMCLight>,
IEnumerable<UMCLight>,
classAlignmentData> aligner,
IClusterer<UMCLight, UMCClusterLight> clusterer,
string matchPath,
string errorPath)
{
// cluster before we do anything else....
var allFeatures = new List<UMCLight>();
allFeatures.AddRange(baselineFeatures);
allFeatures.AddRange(aligneeFeatures);
var maxBaseline = baselineFeatures.Max(x => x.Scan);
var minBaseline = baselineFeatures.Min(x => x.Scan);
var maxAlignee = aligneeFeatures.Max(x => x.Scan);
var minAlignee = aligneeFeatures.Min(x => x.Scan);
foreach (var feature in aligneeFeatures)
{
feature.Net = Convert.ToDouble(feature.Scan - minAlignee) / Convert.ToDouble(maxAlignee - minAlignee);
feature.MassMonoisotopicAligned = feature.MassMonoisotopic;
}
foreach (var feature in baselineFeatures)
{
feature.Net = Convert.ToDouble(feature.Scan - minBaseline) / Convert.ToDouble(maxBaseline - minBaseline);
feature.MassMonoisotopicAligned = feature.MassMonoisotopic;
}
// This tells us the differences before we align.
var clusters = clusterer.Cluster(allFeatures);
var clusterId = 0;
foreach (var cluster in clusters)
{
cluster.Id = clusterId++;
}
var scorer = new GlobalPeptideClusterScorer();
var preAlignment = scorer.Score(clusters);
aligner.AligneeSpectraProvider = providerY;
aligner.BaselineSpectraProvider = providerX;
UpdateStatus("Aligning data");
// Aligner data
var data = aligner.Align(baselineFeatures, aligneeFeatures);
var matches = data.Matches;
// create anchor points for LCMSWarp alignment
var massPoints = new List<RegressionPoint>();
var netPoints = new List<RegressionPoint>();
foreach (var match in matches)
{
var massError = FeatureLight.ComputeMassPPMDifference(match.AnchorPointX.Mz,
match.AnchorPointY.Mz);
var netError = match.AnchorPointX.Net - match.AnchorPointY.Net;
var massPoint = new RegressionPoint(match.AnchorPointX.Mz, 0, massError, netError);
massPoints.Add(massPoint);
var netPoint = new RegressionPoint(match.AnchorPointX.Net, 0, massError, netError);
netPoints.Add(netPoint);
}
foreach (var feature in allFeatures)
{
feature.UmcCluster = null;
feature.ClusterId = -1;
}
// Then cluster after alignment!
UpdateStatus("clustering data");
clusters = clusterer.Cluster(allFeatures);
var postAlignment = scorer.Score(clusters);
UpdateStatus("Note\tSame\tDifferent");
UpdateStatus(string.Format("Pre\t{0}\t{1}",
preAlignment.SameCluster,
preAlignment.DifferentCluster));
UpdateStatus(string.Format("Post\t{0}\t{1}",
postAlignment.SameCluster,
postAlignment.DifferentCluster));
matches = FilterMatches(matches, 40);
SaveMatches(matchPath, matches);
DeRegisterProgressNotifier(aligner);
DeRegisterProgressNotifier(clusterer);
}
/// <summary>
/// Runs the MultiAlign analysis
/// </summary>
public void AlignDatasets(IEnumerable <UMCLight> baselineFeatures,
IEnumerable <UMCLight> aligneeFeatures,
ISpectraProvider providerX,
ISpectraProvider providerY,
IFeatureAligner <IEnumerable <UMCLight>,
IEnumerable <UMCLight>,
AlignmentData> aligner,
IClusterer <UMCLight, UMCClusterLight> clusterer,
string matchPath,
string errorPath)
{
// cluster before we do anything else....
var allFeatures = new List <UMCLight>();
allFeatures.AddRange(baselineFeatures);
allFeatures.AddRange(aligneeFeatures);
var maxBaseline = baselineFeatures.Max(x => x.Scan);
var minBaseline = baselineFeatures.Min(x => x.Scan);
var maxAlignee = aligneeFeatures.Max(x => x.Scan);
var minAlignee = aligneeFeatures.Min(x => x.Scan);
foreach (var feature in aligneeFeatures)
{
feature.Net = Convert.ToDouble(feature.Scan - minAlignee) / Convert.ToDouble(maxAlignee - minAlignee);
feature.MassMonoisotopicAligned = feature.MassMonoisotopic;
}
foreach (var feature in baselineFeatures)
{
feature.Net = Convert.ToDouble(feature.Scan - minBaseline) / Convert.ToDouble(maxBaseline - minBaseline);
feature.MassMonoisotopicAligned = feature.MassMonoisotopic;
}
// This tells us the differences before we align.
var clusters = clusterer.Cluster(allFeatures);
var clusterId = 0;
foreach (var cluster in clusters)
{
cluster.Id = clusterId++;
}
var scorer = new GlobalPeptideClusterScorer();
var preAlignment = scorer.Score(clusters);
aligner.AligneeSpectraProvider = providerY;
aligner.BaselineSpectraProvider = providerX;
UpdateStatus("Aligning data");
// Aligner data
var data = aligner.Align(baselineFeatures, aligneeFeatures);
var matches = data.Matches;
// create anchor points for LCMSWarp alignment
var massPoints = new List <RegressionPoint>();
var netPoints = new List <RegressionPoint>();
foreach (var match in matches)
{
var massError = FeatureLight.ComputeMassPPMDifference(match.AnchorPointX.Mz,
match.AnchorPointY.Mz);
var netError = match.AnchorPointX.Net - match.AnchorPointY.Net;
var massPoint = new RegressionPoint(match.AnchorPointX.Mz, 0, massError, netError);
massPoints.Add(massPoint);
var netPoint = new RegressionPoint(match.AnchorPointX.Net, 0, massError, netError);
netPoints.Add(netPoint);
}
foreach (var feature in allFeatures)
{
feature.UmcCluster = null;
feature.ClusterId = -1;
}
// Then cluster after alignment!
UpdateStatus("clustering data");
clusters = clusterer.Cluster(allFeatures);
var postAlignment = scorer.Score(clusters);
UpdateStatus("Note\tSame\tDifferent");
UpdateStatus(string.Format("Pre\t{0}\t{1}",
preAlignment.SameCluster,
preAlignment.DifferentCluster));
UpdateStatus(string.Format("Post\t{0}\t{1}",
postAlignment.SameCluster,
postAlignment.DifferentCluster));
matches = FilterMatches(matches, 40);
SaveMatches(matchPath, matches);
DeRegisterProgressNotifier(aligner);
DeRegisterProgressNotifier(clusterer);
}
