methHMEM-method: methHMEM method

In DMCHMM: Differentially Methylated CpG using Hidden Markov Model

Description

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

Usage

methHMEM(object, MaxK, MaxEmiter, epsEM, useweight, mc.cores)

## S4 method for signature 'BSData'
methHMEM(object, MaxK, MaxEmiter, epsEM, useweight, mc.cores)

Arguments

object	A BSData-class or BSDMCs-class object
MaxK	An integer value
MaxEmiter	An integer value
epsEM	A positive numeric value
useweight	A logical 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)
OBJ2

DMCHMM documentation built on Nov. 8, 2020, 8:20 p.m.