| plotOverlapProfile {DMRcaller} | R Documentation |
This function plots the distribution of a set of subregions on a large region.
plotOverlapProfile(overlapsProfiles1, overlapsProfiles2 = NULL, names = NULL, labels = NULL, col = NULL, title = "", logscale = FALSE, maxValue = NULL)
overlapsProfiles1 |
a |
overlapsProfiles2 |
a |
names |
a |
labels |
a |
col |
a |
title |
the title of the plot. |
logscale |
a |
maxValue |
a maximum value in a region. Used for the colour scheme. |
Invisibly returns NULL.
Nicolae Radu Zabet
computeOverlapProfile, filterDMRs,
computeDMRs and mergeDMRsIteratively
# 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)