plotOverlapProfile {DMRcaller} | R Documentation

## 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`.

### Author(s)

Nicolae Radu Zabet

### 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)

[Package DMRcaller version 1.19.0 Index]