multiDimensionalClustering: Establish clusters and assign mutations for multi-dimensional...

In Wedge-Oxford/dpclust: DPClust - An R package for subclonal reconstruction of tumours using sequencing data

Establish clusters and assign mutations for multi-dimensional clustering using a multi-dimensional density

Description

Establish clusters and assign mutations for multi-dimensional clustering using a multi-dimensional density

Usage

multiDimensionalClustering(mutation.copy.number, copyNumberAdjustment,
  GS.data, density.smooth, opts)

Arguments

mutation.copy.number	Mutation copy number values for all samples
copyNumberAdjustment	Multiplicity values for all samples
GS.data	Output from the MCMC chain containing mutation assignments, cluster positions and cluster weights
density.smooth	Parameter that determines the amount of smoothing applied when establishing multi-dimensional density
opts	List with parameters, including donorname (samplename), individual samplenames (subsamples) and iterations and burnin

Value

List with various standardised clustering results, including cluster positions, assignments and probabilities

Author(s)

dw9, sd11

Wedge-Oxford/dpclust documentation built on July 6, 2024, 2:02 p.m.