unis2pseudomulti {chromstaR} | R Documentation |
Combine multiple uniHMM
s to a multiHMM
without running callPeaksMultivariate
. This should only be done for comparison purposes.
unis2pseudomulti(hmms)
hmms |
A named list of |
Use this function if you want to combine ChIP-seq samples without actually running a multivariate Hidden Markov Model. The resulting object will be of class multiHMM
but will not be truly multivariate.
A multiHMM
object.
Aaron Taudt
# 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(1,4)] # Bin the data data(rn4_chrominfo) binned.data <- list() for (file in files) { binned.data[[basename(file)]] <- binReads(file, binsizes=1000, stepsizes=500, 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) } ## Combine the univariate HMMs without fitting a multivariate HMM names(models) <- c('H3K27me3','H3K4me3') pseudo.multi.HMM <- unis2pseudomulti(models) ## Compare frequencies with real multivariate HMM exp <- data.frame(file=files, mark=c("H3K27me3","H3K4me3"), condition=rep("SHR",2), replicate=c(1,1), pairedEndReads=FALSE, controlFiles=NA) states <- stateBrewer(exp, mode='combinatorial') real.multi.HMM <- callPeaksMultivariate(models, use.states=states, eps=1, max.time=60) genomicFrequencies(real.multi.HMM) genomicFrequencies(pseudo.multi.HMM)