Canopy (version 1.3.0)

canopy.cluster: EM algorithm for multivariate clustering of SNAs

Description

EM algorithm for multivariate clustering of SNAs.

Usage

canopy.cluster(R, X, num_cluster, num_run, Mu.init = NULL, Tau_Kplus1 = NULL)

Arguments

R

alternative allele read depth matrix

X

total read depth matrix

num_cluster

number of mutation clusters (BIC as model selection metric)

num_run

number of EM runs for estimation for each specific number of clusters (to avoid EM being stuck in local optima)

Mu.init

(optional) initial value of the VAF centroid for each mutation cluster in each sample

Tau_Kplus1

(optional) pre-specified proportion of noise component in clustering, uniformly distributed between 0 and 1

Value

Matrix of posterior probability of cluster assignment for each mutation.

Examples

# NOT RUN {
    data(AML43)
    R = AML43$R
    X = AML43$X
    Mu = AML43$Mu
    Tau = AML43$Tau
    pG = canopy.cluster.Estep(Tau, Mu, R, X)
# }