methHMMCMC-method: methHMMCMC method

In shokoohi/DMCHMM: Differentially Methylated CpG using Hidden Markov Model

methHMMCMC method

Description

Estimates the HMM methylation paths and the HMM order for each sample using the MCMC algorithm

Usage

methHMMCMC(object, useweight, nburn, nthin, nsamp, mc.cores)

## S4 method for signature 'BSDMCs'
methHMMCMC(object, useweight, nburn, nthin, nsamp, mc.cores)

Arguments

object	A BSData-class or BSDMCs-class object
useweight	A logical value
nburn	An integer value
nthin	An integer value
nsamp	An integer value
mc.cores	An integer greater than 0

Value

BSDMCs-class object

Author(s)

Farhad Shokoohi <[e-mail]>

Examples

set.seed(1980)
nr <- 150; nc <- 8
metht <- matrix(as.integer(runif(nr * nc, 0, 100)), nr)
methc <- matrix(rbinom(n=nr*nc,c(metht),prob = runif(nr*nc)),nr,nc)
r1 <- GRanges(rep('chr1', nr), IRanges(1:nr, width=1), strand='*')
names(r1) <- 1:nr
cd1 <- DataFrame(Group=rep(c('G1','G2'),each=nc/2),row.names=LETTERS[1:nc])
OBJ1 <- cBSData(rowRanges=r1,methReads=methc,totalReads=metht,colData=cd1)
OBJ2 <- methHMEM(OBJ1, MaxK=2, mc.cores=2)
OBJ3 <- methHMMCMC(OBJ2, mc.cores=2)
OBJ3

shokoohi/DMCHMM documentation built on April 19, 2022, 3:25 a.m.