public void TestAlignment(string datasetNameX, string datasetNameY)
{
var featureFileX = GetTestPath(datasetNameX + "_isos.csv");
var rawFileX = GetTestPath(datasetNameX + ".raw");
var featureFileY = GetTestPath(datasetNameY + "_isos.csv");
var rawFileY = GetTestPath(datasetNameY + ".raw");
Print("Detecting Features");
var featuresX = FindFeatures(rawFileX, featureFileX);
var featuresY = FindFeatures(rawFileY, featureFileY);
PrintFeatureMsMsData(featuresX);
PrintFeatureMsMsData(featuresY);
Print("Aligning Features");
// Align the features
var alignmentOptions = new AlignmentOptions();
var aligner = new LcmsWarpFeatureAligner(alignmentOptions.LCMSWarpOptions);
aligner.Align(featuresX, featuresY);
Print("");
Print("NET, NETAligned");
foreach (var feature in featuresY)
{
if (feature.HasMsMs())
{
Print(string.Format("{0}", feature.Net - feature.NetAligned));
}
}
}
/// <summary>
/// Constructor.
/// </summary>
public AnalysisOptions()
{
AlignmentOptions = new AlignmentOptions();
DriftTimeAlignmentOptions = new DriftTimeAlignmentOptions();
ClusterOptions = new LCMSFeatureClusteringOptions();
STACOptions = new StacOptions();
ConsolidationOptions = new FeatureConsolidatorOptions();
}
public static TestObject GetTestObject(BrowserOptions browserOptions, AlignmentOptions alignOptions)//factory call
{
try
{
return(new TestObject(browserOptions, alignOptions));
}
catch (Exception ex)
{
throw new Exception(ex.Message);
}
}
private TestObject(BrowserOptions browserOptions, AlignmentOptions alignOptions)
{
#region Init
this.elementCache = new Dictionary <By, IWebElement>();
this.dataCache = new Dictionary <int, string>();
#endregion
AppDomain domain = AppDomain.CurrentDomain;
string path = domain.BaseDirectory;
if (browserOptions.Equals(BrowserOptions.Chrome) && alignOptions.Equals(AlignmentOptions.Desktop))
{
ChromeOptions options = new ChromeOptions();
options.PageLoadStrategy = PageLoadStrategy.Normal;
options.AddArgument("--disable-notifications");
options.AddArgument("--start-maximized");
options.AddArgument("--disable-sync");
options.AddArgument("--disbale-gpu");
options.AddArguments("--mute-audio");
options.AddArguments("--no-sandbox");
//options.AddArgument("--headless");
this.driver = new ChromeDriver(path, options);
}
if (browserOptions.Equals(BrowserOptions.Chrome) && alignOptions.Equals(AlignmentOptions.MobileSite))
{
ChromeOptions options = new ChromeOptions();
options.PageLoadStrategy = PageLoadStrategy.Normal;
options.EnableMobileEmulation("iPhone 6");
options.AddArgument("--disable-notifications");
options.AddArgument("--start-maximized");
options.AddArgument("--disable-sync");
options.AddArgument("--disbale-gpu");
options.AddArguments("--mute-audio");
options.AddArguments("--no-sandbox");
//options.AddArgument("--headless");
this.driver = new ChromeDriver(path, options);
}
if (browserOptions.Equals(BrowserOptions.Firefox) && alignOptions.Equals(AlignmentOptions.Desktop))
{
}
if (browserOptions.Equals(BrowserOptions.Firefox) && alignOptions.Equals(AlignmentOptions.MobileSite))
{
}
this.driver.Manage().Timeouts().ImplicitWait = TimeSpan.FromSeconds(60);
this.driver.Manage().Timeouts().PageLoad = TimeSpan.FromSeconds(100);
}
public void TestSpectralAlignment(string basePath, string baselineName, string aligneeName,
double comparisonCutoff)
{
RootDataPath = basePath;
var featureFileX = GetTestPath(baselineName + "_isos.csv");
var rawFileX = GetTestPath(baselineName + ".raw");
var featureFileY = GetTestPath(aligneeName + "_isos.csv");
var rawFileY = GetTestPath(aligneeName + ".raw");
Print("Detecting Features");
var baselineFeatures = FindFeatures(rawFileX, featureFileX);
var aligneeFeatures = FindFeatures(rawFileY, featureFileY);
Print("Aligning Features");
// Align the features
var alignmentOptions = new AlignmentOptions();
var aligner = new LcmsWarpFeatureAligner(alignmentOptions.LCMSWarpOptions);
aligner.Align(baselineFeatures, aligneeFeatures);
PrintFeatureMsMsData(baselineFeatures);
PrintFeatureMsMsData(aligneeFeatures);
var matches = GetSpectralMatches(
baselineFeatures, aligneeFeatures, comparisonCutoff);
Print(string.Format("Found {0} spectral matches", matches.Count));
Print("Similarity, Pre-Alignment, Post-Alignment");
var counts = new Dictionary <double, int>();
counts.Add(.9, 0);
counts.Add(.8, 0);
counts.Add(.7, 0);
counts.Add(.6, 0);
counts.Add(.5, 0);
var preDist = new List <double>();
var postDist = new List <double>();
foreach (var match in matches)
{
var baselineFeature = match.Baseline.ParentFeature.GetParentFeature();
var aligneeFeature = match.Alignee.ParentFeature.GetParentFeature();
var preAlignment = baselineFeature.Net - aligneeFeature.Net;
var postAlignment = baselineFeature.Net - aligneeFeature.NetAligned;
postDist.Add(postAlignment);
preDist.Add(preAlignment);
Print(string.Format("{0},{1},{2}", match.Similarity, preAlignment, postAlignment));
if (match.Similarity > .9)
{
counts[.9]++;
}
else if (match.Similarity > .8)
{
counts[.8]++;
}
else if (match.Similarity > .7)
{
counts[.7]++;
}
else if (match.Similarity > .6)
{
counts[.6]++;
}
}
Print("");
Print("Counts");
Print("");
foreach (var key in counts.Keys)
{
Print(string.Format("{0},{1}", key, counts[key]));
}
var test = new MannWhitneyTest();
var data = test.Test(preDist, postDist);
Print(string.Format("Two Tail - {0} ", data.TwoTail));
Print(string.Format("Left Tail - {0} ", data.LeftTail));
Print(string.Format("Right Tail - {0} ", data.RightTail));
}
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);
}
}
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);
}
}
}
}