Description Usage Arguments Value Author(s) Examples
View source: R/combineMultivariates.R
Combine combinatorial states from several multiHMM
objects. Combinatorial states can be combined for objects containing multiple marks (mode='combinatorial'
) or multiple conditions (mode='differential'
).
1 | combineMultivariates(hmms, mode)
|
hmms |
A |
mode |
Mode of combination. See |
A combinedMultiHMM
objects with combinatorial states for each condition.
Aaron Taudt
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | ### 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')
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