plotPeaks: Create a plot of ChIP read counts with called peaks and...

In plbaldoni/mixHMM: Differential Peak Calling via Hidden Markov Model With Mixture of Negative Binomial Distributions

Description

'plotPeaks()' imports the output from 'mixHMM()' and plots the peak calls of a given genomic region.

Usage

plotPeaks(output, ranges, ChIP, group, offset = NULL, peaks = NULL)

Arguments

output	An output from 'mixHMM()'
ranges	A vector with two elements that specifies the genomic windows to be plotted.
ChIP	M*N matrix of ChIP read counts, where M is the number of windows in the analyzed genome and N is the number of conditions*replicates
group	vector of length N with condition labels (e.g. c(1,1,2,2,3,3) for three conditions and two replicates each)
offset	M*N matrix of offsets (default is offset = matrix(0,nrow=M,ncol=N))
peaks	An optional vector of length M with zeros (background), ones (differential peaks), and twos (consensus peaks) representing the enriched windows. If not provided, 'plotPeaks()' will use the Viterbi sequence from 'output'.

Value

A ggplot

Author(s)

Pedro L. Baldoni, [e-mail]

References

https://github.com/plbaldoni/mixHMM

Examples

data(H3K36me3)
ChIP = SummarizedExperiment::assay(H3K36me3)
offset = ZIMHMM::createOffset(ChIP,method = 'loess',span = 1)
group = c(1,1,1,2,2,2,3,3,3)
B = 2^(length(unique(group)))-2
## Not run: output = mixHMMConstr(ChIP,Control=NULL,offset,group,B,control = controlPeaks(epsilon.em = rep(1e-6,4)))
## Not run: plotPeaks(output = test,ranges = c(which.min(abs(start(rowRanges(H3K36me3))-17800000)),
which.min(abs(end(rowRanges(H3K36me3))-18150000))),ChIP = ChIP,group = group,offset = offset)
## End(Not run)

plbaldoni/mixHMM documentation built on Nov. 8, 2019, 8:05 p.m.