plotOverlapProfile: Plot overlap profile
In DMRcaller: Differentially Methylated Regions caller

Description Usage Arguments Value Author(s) See Also Examples

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

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

`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.

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)