VAFclusterEM: Gaussian mixture model clustering for VAF data
In junseonghwan/ScRNACloneEvaluation: ScRNA clone evaluation.

Description Usage Arguments Value Author(s) See Also Examples

View source: R/VAFclusterEM.R

Parameter estimation and cluster assignment is performed using the EM algorithm, implemented by VAFclusterEM.

1	VAFclusterEM(dataVec, coverage, kclust, startseed=100, nIterations=40, verbose=FALSE)

`dataVec`	A vector of mutation frequencies, or a matrix or dataframe with each row corresponding to a bulk sample.
`coverage`	Average coverage of the sequencing data
`kclust`	Number of clusters
`startseed`	Offset for the seed for the random number generator
`nIterations`	Maximum number of iterations
`verbose`	Whether to report on results for each iteration

Returns a list with these elements:

`AIC`	Minimum AIC over all iterations
`bestseed`	Seed with the minimum AIC
`kclust`	The number of clusters
`relativeweights`	The relative weights of each sample to be in all groups. Maximum value is chosen for group assignment.
`newclustermembership`	Group membership for each sample

Jack Kuipers

flexmix

coverage <- 1e4
kclust <- 3
freqs<-c(0.25,0.32,0.36)
nos <- c(5,3,1)
datas <- c()
for(ii in 1:length(nos)){
  datas<-c(datas,rnorm(nos[ii],mean=freqs[ii],sd=VAFclusterEM:::sdfromcoverage(freqs[ii],coverage)))
}

VAFclusterEM(datas, coverage, kclust)