# Compute Overlaps Profile

### Description

This function computes the distribution of a subset of regions
(`GRanges`

object) over a large region (`GRanges`

object)

### Usage

1 2 | ```
computeOverlapProfile(subRegions, largeRegion,
windowSize = floor(width(largeRegion)/500), binary = TRUE, cores = 1)
``` |

### Arguments

`subRegions` |
a |

`largeRegion` |
a |

`windowSize` |
The |

`binary` |
a value indicating whether to count 1 for each overlap or to compute the width of the overlap |

`cores` |
the number of cores used to compute the DMRs. |

### Value

a `GRanges`

object with equal sized tiles of the regions.
The object has one metadata file `score`

which represents: the number of
subRegions overlapping with the tile, in the case of `binary = TRUE`

,
and the width of the subRegions overlapping with the tile , in the case of
`binary = FALSE`

.

### Author(s)

Nicolae Radu Zabet

### See Also

`plotOverlapProfile`

, `filterDMRs`

,
`computeDMRs`

and `mergeDMRsIteratively`

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 | ```
# 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
hotspots <- computeOverlapProfile(DMRsNoiseFilterCG, largeRegion,
windowSize = 10000, binary = FALSE)
``` |