DMRcaller (version 1.4.2)

plotOverlapProfile: Plot overlap profile

Description

This function plots the distribution of a set of subregions on a large region.

Usage

plotOverlapProfile(overlapsProfiles1, overlapsProfiles2 = NULL, names = NULL, labels = NULL, col = NULL, title = "", logscale = FALSE, maxValue = NULL)

Arguments

overlapsProfiles1

a GRanges object with the overlaps profile; see computeOverlapProfile.

overlapsProfiles2

a GRanges object with the overlaps profile; see computeOverlapProfile. This is optional. For example, one can be use overlapsProfiles1 to display hypomethylated regions and overlapsProfiles2 the hypermethylated regions.

names

a vector of character to add labels for the two overlapsProfiles. This is an optinal parameter.

labels

a vector of character used to add a subfigure character to the plot. If NULL nothing is added.

col

a character vector with the colours. It needs to contain 2 colours. If not or if NULL, the defalut colours will be used.

title

the title of the plot.

logscale

a logical value indicating if the colours are on logscale or not.

maxValue

a maximum value in a region. Used for the colour scheme.

Value

Invisibly returns NULL.

See Also

computeOverlapProfile, filterDMRs, computeDMRs and mergeDMRsIteratively

Examples

# load the methylation data
data(methylationDataList)

# load the DMRs in CG context
data(DMRsNoiseFilterCG)

# the coordinates of the area to be plotted
largeRegion <- GRanges(seqnames = Rle("Chr3"), ranges = IRanges(1,1E5))

# compute overlaps distribution
hotspotsHypo <- computeOverlapProfile(DMRsNoiseFilterCG, largeRegion,
                 windowSize = 10000, binary = FALSE)

plotOverlapProfile(GRangesList("Chr3"=hotspotsHypo),
                   names = c("hypomethylated"), title = "CG methylation")

## Not run: 
# 
# largeRegion <- GRanges(seqnames = Rle("Chr3"), ranges = IRanges(1,1E6))
# 
# hotspotsHypo <- computeOverlapProfile(
#                DMRsNoiseFilterCG[(DMRsNoiseFilterCG$regionType == "loss")],
#                largeRegion, windowSize=2000, binary=TRUE, cores=1)
# 
# hotspotsHyper <- computeOverlapProfile(
#                DMRsNoiseFilterCG[(DMRsNoiseFilterCG$regionType == "gain")],
#                largeRegion, windowSize=2000, binary=TRUE, cores=1)
# 
# plotOverlapProfile(GRangesList("Chr3"=hotspotsHypo),
#                    GRangesList("Chr3"=hotspotsHyper),
#                    names=c("loss", "gain"), title="CG methylation")
# ## End(Not run)