/// <summary>
/// Constructor.
/// </summary>
/// <param name="featureCache">LCMS Features</param>
/// <param name="clusterCache">LCMS Feature clusters</param>
/// <param name="msFeatureCache">MS Features</param>
/// <param name="msnFeatureCache">MS/MS Features</param>
/// <param name="msFeatureMap">MS To LCMS Feature map</param>
/// <param name="msnFeatureMap">MS to MSn Feature map</param>
public FeatureDataAccessProviders(IUmcDAO featureCache,
IUmcClusterDAO clusterCache,
IMSFeatureDAO msFeatureCache,
IMSnFeatureDAO msnFeatureCache,
IMsnFeatureToMSFeatureDAO msnFeatureMap,
IDatasetDAO datasetCache,
IMassTagMatchDAO massTagMatches,
IMassTagDAO massTags,
IFactorDao factorCache,
IDatasetToFactorMapDAO factorAssignmentCache,
IMSMSClusterMapDAO msmsClusterCache,
IDatabaseSearchSequenceDAO sequenceCache,
ISequenceToMsnFeatureDAO sequenceMapCache) :
this()
{
ClusterCache = clusterCache;
FeatureCache = featureCache;
MSFeatureCache = msFeatureCache;
MSnFeatureCache = msnFeatureCache;
MSFeatureToMSnFeatureCache = msnFeatureMap;
DatasetCache = datasetCache;
MassTagMatches = massTagMatches;
MassTags = massTags;
FactorAssignmentCache = factorAssignmentCache;
FactorCache = factorCache;
MSMSClusterCache = msmsClusterCache;
DatabaseSequenceCache = sequenceCache;
SequenceMsnMapCache = sequenceMapCache;
}
/// <summary>
/// Constructor.
/// </summary>
/// <param name="featureCache">LCMS Features</param>
/// <param name="clusterCache">LCMS Feature clusters</param>
/// <param name="msFeatureCache">MS Features</param>
/// <param name="msnFeatureCache">MS/MS Features</param>
/// <param name="msFeatureMap">MS To LCMS Feature map</param>
/// <param name="msnFeatureMap">MS to MSn Feature map</param>
public FeatureDataAccessProviders(IUmcDAO featureCache,
IUmcClusterDAO clusterCache,
IMSFeatureDAO msFeatureCache,
IMSnFeatureDAO msnFeatureCache,
IMsnFeatureToMSFeatureDAO msnFeatureMap,
IDatasetDAO datasetCache,
IMassTagMatchDAO massTagMatches,
IMassTagDAO massTags,
IFactorDao factorCache,
IDatasetToFactorMapDAO factorAssignmentCache,
IMSMSClusterMapDAO msmsClusterCache,
IDatabaseSearchSequenceDAO sequenceCache,
ISequenceToMsnFeatureDAO sequenceMapCache)
: this()
{
ClusterCache = clusterCache;
FeatureCache = featureCache;
MSFeatureCache = msFeatureCache;
MSnFeatureCache = msnFeatureCache;
MSFeatureToMSnFeatureCache = msnFeatureMap;
DatasetCache = datasetCache;
MassTagMatches = massTagMatches;
MassTags = massTags;
FactorAssignmentCache = factorAssignmentCache;
FactorCache = factorCache;
MSMSClusterCache = msmsClusterCache;
DatabaseSequenceCache = sequenceCache;
SequenceMsnMapCache = sequenceMapCache;
}
/// <summary>
/// The main entry point for the application.
/// </summary>
static int Main(string [] args)
{
var handle = System.Diagnostics.Process.GetCurrentProcess().MainWindowHandle;
SetConsoleMode(handle, ENABLE_EXTENDED_FLAGS);
try
{
if (args.Length < 2)
{
Console.WriteLine(@"MultiAlignChargeStateProcessor databasePath chargeState crossTabPath [dataset List]");
Console.WriteLine(@"\tThe cross-tab file will be placed in the same directory as the database path");
return(1);
}
// Setup the analysis processing
var databasePath = args[0];
var databaseName = Path.GetFileNameWithoutExtension(databasePath);
var path = Path.GetDirectoryName(databasePath);
var crossPath = args[2];
var chargeState = Convert.ToInt32(args[1]);
List <string> datasetList = null;
if (args.Length == 4)
{
datasetList = File.ReadAllLines(args[3]).ToList();
}
if (path == null)
{
Console.WriteLine(@"The directory path is invalid");
return(1);
}
NHibernateUtil.ConnectToDatabase(databasePath, false);
IDatasetDAO datasetCache = new DatasetDAOHibernate();
var dateSuffix = AnalysisPathUtils.BuildDateSuffix();
Logger.LogPath = Path.Combine(path, string.Format("{0}_charge_{2}_{1}.txt", databaseName, dateSuffix, chargeState));
Logger.PrintMessage("Find all datasets", true);
var datasets = datasetCache.FindAll();
Logger.PrintMessage(string.Format("Found {0} datasets", datasets.Count), true);
// Create the clustering algorithm - average linkage
IClusterer <UMCLight, UMCClusterLight> clusterer = new UMCAverageLinkageClusterer <UMCLight, UMCClusterLight>();
// Create the DAO object to extract the features
var database = new UmcAdoDAO {
DatabasePath = databasePath
};
IUmcDAO featureDao = database;
Logger.PrintMessage(string.Format("Extracting Features"), true);
var tempFeatures = featureDao.FindByCharge(chargeState);
Logger.PrintMessage(string.Format("Found {0} features", tempFeatures.Count), true);
var features = new List <UMCLight>();
if (datasetList != null)
{
var featuremap = datasets.ToDictionary(info => info.DatasetName.ToLower());
var focusedDatasetList = new Dictionary <int, DatasetInformation>();
foreach (var name in datasetList)
{
var key = name.ToLower();
if (featuremap.ContainsKey(key))
{
Logger.PrintMessage("Using dataset: " + name);
focusedDatasetList.Add(featuremap[key].DatasetId, featuremap[key]);
}
else
{
throw new Exception("Didn't find the dataset required..." + name);
}
}
features.AddRange(from feature in tempFeatures let use = focusedDatasetList.ContainsKey(feature.GroupId) where use select feature);
Logger.PrintMessage(string.Format("Found {0} filtered features for dataset list", features.Count), true);
}
else
{
features = tempFeatures;
}
// Handle logging progress.
clusterer.Progress += clusterer_Progress;
clusterer.Parameters.Tolerances.DriftTime = .3;
clusterer.Parameters.Tolerances.Mass = 16;
clusterer.Parameters.Tolerances.Net = .014;
clusterer.Parameters.OnlyClusterSameChargeStates = true;
clusterer.Parameters.CentroidRepresentation = ClusterCentroidRepresentation.Mean;
clusterer.Parameters.DistanceFunction = DistanceFactory <UMCLight> .CreateDistanceFunction(DistanceMetric.WeightedEuclidean);
// Then cluster
var clusterWriter = new UmcClusterWriter();
IClusterWriter <UMCClusterLight> writer = clusterWriter; //new UMCClusterDummyWriter();
try
{
clusterWriter.Open(crossPath);
clusterWriter.WriteHeader(datasets);
clusterer.ClusterAndProcess(features, writer);
Logger.PrintMessage("", true);
Logger.PrintMessage("ANALYSIS SUCCESS", true);
return(0);
}
catch (Exception ex)
{
Logger.PrintMessage("Unhandled Error: " + ex.Message);
var innerEx = ex.InnerException;
while (innerEx != null)
{
Logger.PrintMessage("Inner Exception: " + innerEx.Message);
innerEx = innerEx.InnerException;
}
Logger.PrintMessage("Stack: " + ex.StackTrace);
Logger.PrintMessage("");
Logger.PrintMessage("ANALYSIS FAILED");
return(1);
}
finally
{
clusterWriter.Close();
}
}
catch (Exception ex)
{
Logger.PrintMessage("Unhandled Error: " + ex.Message, true);
var innerEx = ex.InnerException;
while (innerEx != null)
{
Logger.PrintMessage("Inner Exception: " + innerEx.Message);
innerEx = innerEx.InnerException;
}
Logger.PrintMessage("Stack: " + ex.StackTrace, true);
Logger.PrintMessage("");
Logger.PrintMessage("ANALYSIS FAILED");
return(1);
}
}
/// <summary>
/// Loads feature data from the files provided.
/// </summary>
/// <returns></returns>
public static IList<UMCLight> LoadUmcFeatureData(string path,
int datasetId,
IUmcDAO featureCache)
{
var features = new List<UMCLight>();
var extension = Path.GetExtension(path);
if (extension == null) return features;
extension = extension.ToUpper();
switch (extension)
{
case ".TXT":
var umcReader = new LCMSFeatureFileReader(path);
features = umcReader.GetUmcList();
break;
case ".DB3":
features = featureCache.FindByDatasetId(datasetId);
break;
default: //Was reconstructing features from scratch even when they were already cached because the file extention was ".csv" not ".db3"
features = featureCache.FindByDatasetId(datasetId);
break;
}
return features;
}
/// <summary>
/// Loads feature data from the files provided.
/// </summary>
/// <returns></returns>
public static IList <UMCLight> LoadUmcFeatureData(DatasetInformation dataset, IUmcDAO featureCache, IScanSummaryProvider provider = null)
{
var features = new List <UMCLight>();
var extension = Path.GetExtension(dataset.Features.Path);
if (extension == null)
{
return(features);
}
extension = extension.ToUpper();
switch (extension)
{
case ".TXT":
if (dataset.Features.Path.EndsWith("_LCMSFeatures.txt"))
{
var reader = new LcImsFeatureFileReader(provider, dataset.DatasetId);
features = reader.ReadFile(dataset.Features.Path).ToList();
}
else
{
var umcReader = new LCMSFeatureFileReader(dataset.Features.Path);
features = umcReader.GetUmcList();
}
break;
case ".DB3":
features = featureCache.FindByDatasetId(dataset.DatasetId);
break;
case ".MS1FT":
if (provider != null && provider is InformedProteomicsReader)
{
var promexReader = new PromexFileReader(provider as InformedProteomicsReader, dataset.DatasetId);
features = promexReader.ReadFile(dataset.Features.Path).ToList();
}
break;
default: //Was reconstructing features from scratch even when they were already cached because the file extention was ".csv" not ".db3"
features = featureCache.FindByDatasetId(dataset.DatasetId);
break;
}
if (features != null && provider is ISpectraProvider)
{
var spectraProvider = provider as ISpectraProvider;
LoadMsMs(features, spectraProvider);
}
return(features);
}
public void ClusterFeatures()
{
this.algorithms = this.builder.GetAlgorithmProvider(this.options);
var clusterer = this.algorithms.Clusterer;
clusterer.Parameters = LcmsClusteringOptions.ConvertToOmics(this.options.LcmsClusteringOptions);
this.featureCache = this.analysis.DataProviders.FeatureCache;
// This just tells us whether we are using mammoth memory partitions or not.
var clusterCount = 0;
var providers = this.analysis.DataProviders;
// Here we see if we need to separate the charge...
// IMS is said to require charge separation
if (!this.analysis.Options.LcmsClusteringOptions.ShouldSeparateCharge)
{
var features = this.featureCache.FindAll();
var clusters = new List<UMCClusterLight>();
clusters = clusterer.Cluster(features, clusters);
foreach (var cluster in clusters)
{
cluster.Id = clusterCount++;
cluster.UmcList.ForEach(x => x.ClusterId = cluster.Id);
// Updates the cluster with statistics
foreach (var feature in cluster.UmcList)
{
cluster.MsMsCount += feature.MsMsCount;
cluster.IdentifiedSpectraCount += feature.IdentifiedSpectraCount;
}
}
providers.ClusterCache.AddAll(clusters);
providers.FeatureCache.UpdateAll(features);
this.analysis.Clusters = clusters;
}
else
{
var maxChargeState = this.featureCache.FindMaxCharge();
/*
* Here we cluster all charge states separately. Probably IMS Data.
*/
for (var chargeState = 1; chargeState <= maxChargeState; chargeState++)
{
var features = this.featureCache.FindByCharge(chargeState);
if (features.Count < 1)
{
break;
}
var clusters = clusterer.Cluster(features);
foreach (var cluster in clusters)
{
cluster.Id = clusterCount++;
cluster.UmcList.ForEach(x => x.ClusterId = cluster.Id);
// Updates the cluster with statistics
foreach (var feature in cluster.Features)
{
cluster.MsMsCount += feature.MsMsCount;
cluster.IdentifiedSpectraCount += feature.IdentifiedSpectraCount;
}
}
this.analysis.DataProviders.ClusterCache.AddAll(clusters);
this.analysis.DataProviders.FeatureCache.UpdateAll(features);
}
this.analysis.Clusters = this.analysis.DataProviders.ClusterCache.FindAll();
}
MessageBox.Show("Working Command");
}
internal void ClusterFeatures(IProgress <ProgressData> workflowProgress = null)
{
var taskBarProgress = TaskBarProgress.GetInstance();
taskBarProgress.ShowProgress(this, true);
workflowProgress = workflowProgress ?? new Progress <ProgressData>();
IProgress <ProgressData> internalProgress = new Progress <ProgressData>(pd =>
{
this.progress.Report((int)pd.Percent);
this.ProgressPercent = pd.Percent;
taskBarProgress.SetProgress(this, pd.Percent);
workflowProgress.Report(pd);
});
this.algorithms = this.builder.GetAlgorithmProvider(this.options);
var clusterer = this.algorithms.Clusterer;
clusterer.Parameters = LcmsClusteringOptions.ConvertToOmics(this.options.LcmsClusteringOptions);
this.featureCache = this.analysis.DataProviders.FeatureCache;
if (clusterer is PromexClusterer)
{
var promexClusterer = clusterer as PromexClusterer;
promexClusterer.Readers = this.analysis.DataProviders.ScanSummaryProviderCache;
}
foreach (var dataset in this.Datasets)
{
if (dataset.FeaturesFound)
{
dataset.DatasetState = DatasetInformationViewModel.DatasetStates.Clustering;
}
}
ThreadSafeDispatcher.Invoke(this.ClusterFeaturesCommand.RaiseCanExecuteChanged);
ThreadSafeDispatcher.Invoke(this.DisplayClustersCommand.RaiseCanExecuteChanged);
this.ShouldShowProgress = true;
var progData = new ProgressData(internalProgress);
var clusterProgress = new Progress <ProgressData>(pd => progData.Report(pd.Percent));
this.analysis.DataProviders.DatabaseLock.EnterWriteLock();
DatabaseIndexer.IndexClustersDrop(NHibernateUtil.Path);
this.analysis.DataProviders.ClusterCache.ClearAllClusters();
this.analysis.DataProviders.DatabaseLock.ExitWriteLock();
// The id for a cluster - keep track here to avoid duplicates when separating by charge.
var clusterCount = 0;
// Here we see if we need to separate the charge...
// IMS is said to require charge separation
if (!this.analysis.Options.LcmsClusteringOptions.ShouldSeparateCharge)
{
progData.StepRange(45);
var features = new List <UMCLight>();
var i = 0;
var datasets = this.Datasets.Where(ds => ds.FeaturesFound).ToList();
foreach (var dataset in datasets)
{
this.analysis.DataProviders.DatabaseLock.EnterReadLock();
features.AddRange(this.featureCache.FindByDatasetId(dataset.DatasetId));
this.analysis.DataProviders.DatabaseLock.ExitReadLock();
progData.Report(++i, datasets.Count);
}
progData.StepRange(100);
ClusterGroupOfFeatures(clusterer, features, ref clusterCount, clusterProgress);
}
else
{
var maxChargeState = this.featureCache.FindMaxCharge();
// Here we cluster all charge states separately. Probably IMS Data.
for (var chargeState = 1; chargeState <= maxChargeState; chargeState++)
{
var maxPercent = ((100.0 * chargeState) / maxChargeState);
// TODO: Add restriction by selected dataset ids?
var features = this.featureCache.FindByCharge(chargeState);
if (features.Count < 1)
{
continue;
}
progData.StepRange(maxPercent);
ClusterGroupOfFeatures(clusterer, features, ref clusterCount, clusterProgress);
}
this.analysis.Clusters = this.analysis.DataProviders.ClusterCache.FindAll();
}
this.analysis.DataProviders.DatabaseLock.EnterWriteLock();
DatabaseIndexer.IndexClusters(NHibernateUtil.Path);
this.analysis.DataProviders.DatabaseLock.ExitWriteLock();
foreach (var dataset in this.Datasets)
{
if (dataset.DatasetState == DatasetInformationViewModel.DatasetStates.PersistingClusters)
{
dataset.DatasetState = DatasetInformationViewModel.DatasetStates.Clustered;
}
}
try
{
// Write to file
this.WriteClusterData(string.Format("{0}_crosstab.tsv", this.analysis.AnalysisName), this.analysis.Clusters);
}
catch (Exception ex)
{
var errMsg = "Error writing results to text file: " + ex.Message;
Logger.PrintMessage(errMsg);
// Todo: Add this: if (!GlobalSettings.AutomatedAnalysisMode)
MessageBox.Show(errMsg);
}
ThreadSafeDispatcher.Invoke(this.ClusterFeaturesCommand.RaiseCanExecuteChanged);
ThreadSafeDispatcher.Invoke(this.DisplayClustersCommand.RaiseCanExecuteChanged);
taskBarProgress.ShowProgress(this, false);
this.ShouldShowProgress = false;
}
