combineMultivariates: Combine combinatorial states from several Multivariates

In ataudt/chromstaR: Combinatorial and Differential Chromatin State Analysis for ChIP-Seq Data

Description

Combine combinatorial states from several multiHMM objects. Combinatorial states can be combined for objects containing multiple marks (mode='combinatorial') or multiple conditions (mode='differential').

Usage

combineMultivariates(hmms, mode)

Arguments

hmms	A list() with multiHMM objects. Alternatively a character vector with filenames that contain multiHMM objects.
mode	Mode of combination. See Chromstar for a description of the mode parameter.

Value

A combinedMultiHMM objects with combinatorial states for each condition.

Author(s)

Aaron Taudt

Examples

### Multivariate peak calling for spontaneous hypertensive rat (SHR) ###
# Get example BAM files for 2 different marks in hypertensive rat (SHR)
file.path <- system.file("extdata","euratrans", package='chromstaRData')
files <- list.files(file.path, full.names=TRUE, pattern='SHR.*bam$')[c(1:2,4:5)]
# Construct experiment structure
exp <- data.frame(file=files, mark=c("H3K27me3","H3K27me3","H3K4me3","H3K4me3"),
                 condition=rep("SHR",4), replicate=c(1:2,1:2), pairedEndReads=FALSE,
                 controlFiles=NA)
states <- stateBrewer(exp, mode='combinatorial')
# Bin the data
data(rn4_chrominfo)
binned.data <- list()
for (file in files) {
 binned.data[[basename(file)]] <- binReads(file, binsizes=1000, stepsizes=500,
                                           experiment.table=exp,
                                           assembly=rn4_chrominfo, chromosomes='chr12')
}
# Obtain the univariate fits
models <- list()
for (i1 in 1:length(binned.data)) {
 models[[i1]] <- callPeaksUnivariate(binned.data[[i1]], max.time=60, eps=1)
}
# Call multivariate peaks
multimodel.SHR <- callPeaksMultivariate(models, use.states=states, eps=1, max.time=60)

#'### Multivariate peak calling for brown norway (BN) rat ###
# Get example BAM files for 2 different marks in brown norway rat
file.path <- system.file("extdata","euratrans", package='chromstaRData')
files <- list.files(file.path, full.names=TRUE, pattern='BN.*bam$')[c(1:2,3:4)]
# Construct experiment structure
exp <- data.frame(file=files, mark=c("H3K27me3","H3K27me3","H3K4me3","H3K4me3"),
                 condition=rep("BN",4), replicate=c(1:2,1:2), pairedEndReads=FALSE,
                 controlFiles=NA)
states <- stateBrewer(exp, mode='combinatorial')
# Bin the data
data(rn4_chrominfo)
binned.data <- list()
for (file in files) {
 binned.data[[basename(file)]] <- binReads(file, binsizes=1000, stepsizes=500,
                                           experiment.table=exp,
                                           assembly=rn4_chrominfo, chromosomes='chr12')
}
# Obtain the univariate fits
models <- list()
for (i1 in 1:length(binned.data)) {
 models[[i1]] <- callPeaksUnivariate(binned.data[[i1]], max.time=60, eps=1)
}
# Call multivariate peaks
multimodel.BN <- callPeaksMultivariate(models, use.states=states, eps=1, max.time=60)

### Combine multivariates ###
hmms <- list(multimodel.SHR, multimodel.BN)
comb.model <- combineMultivariates(hmms, mode='combinatorial')

ataudt/chromstaR documentation built on Dec. 26, 2021, 12:07 a.m.