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• CanvasDiploidCaller

C# Class CanvasDiploidCaller.CanvasDiploidCaller

Afficher le fichier Open project: Illumina/canvas Class Usage Examples

Méthodes publiques

Свойство	Type	Description
CoverageWeighting	double
IsDbsnpVcf	bool
TempFolder	string

Protected Properties

Свойство	Type	Description
MeanCoverage	float
MedianHetSnpsDistance	int
MinimumVariantFrequenciesForInformativeSegment	int

Méthodes publiques

Méthode	Description
AggregateCounts ( List &segments ) : float[]
AggregateVariantCoverage ( List &segments ) : int
CallVariants ( string variantFrequencyFile, string inFile, string outFile, string ploidyBedPath, string referenceFolder, string sampleName, string truthDataPath ) : int
InitializePloidies ( ) : void	Setup: Model various copy ploidies.

Méthodes protégées

Méthode	Description
GetKnownCNForSegment ( CanvasSegment segment ) : int	Check whether we know the CN for this segment. Look for a known-CN interval that covers (at least half of) this segment. Return -1 if we don't know its CN.
GetProjectedMeanCoverage ( double diploidCoverage ) : double[]	Compute the expected bin counts for each copy number, given a specified bin count for CN=2 regions
InitializeModelPoints ( CoverageModel model ) : List

Private Methods

Méthode	Description
AssignPloidyCallsDistance ( CoverageModel model, List segments, int medianVariantCoverage ) : void
AssignPloidyCallsGaussianMixture ( ) : void	Assign a SegmentPloidy to each CanvasSegment, based on which model matches this segment best:
FitGaussians ( CoverageModel model, List segments, string debugPath = null ) : double	Fit a Gaussian mixture model. Fix the means to the model MAF and Coverage and run the EM algorithm until convergence. Compute the empirical MAF and Coverage. Fix the means to the empirical MAF and Coverage and run the EM algorithm again until convergence. Always estimate the full covariance matrix?
GenerateReportVersusKnownCN ( ) : void	Generate a table listing segments (and several features), and noting which are accurate (copy number exactly matches truth set) or directionally accurate (copy number and truth set are both <2, both =2, or both >2) This table will become our collection of feature vectors for training q-scores!

Method Details

Property Details