Skip to contents

Compute Overlaps Between Multiple Sets or Genomic Regions

Source: R/computeOverlaps.R
computeOverlaps.Rd

computeOverlaps() is the main entry point for overlap analysis. It accepts either genomic region objects (GRanges/GRangesList) or ordinary sets (character/numeric vectors) and computes a binary overlap matrix describing the presence or absence of each element across sets.

Usage

computeOverlaps(x)

Arguments

x

Input sets. One of:

  • A GRangesList object.

  • A named list of GRanges objects.

  • A named list of atomic vectors (character, numeric, factor, etc.), all of the same type.

Value

An S3 object encoding the overlap result whose class depends on the input type:

GenomicOverlapResult

Returned when the input is genomic (GRangesList or list of GRanges). A list with:

  • reduced_regions: A GRanges object containing the merged (non-redundant) intervals. Each region is annotated with an intersect_category column.

  • overlap_matrix: A logical matrix indicating whether each reduced region overlaps each input set (rows = regions, columns = sets).

SetOverlapResult

Returned when the input is a list of atomic vectors. A list with:

  • unique_elements: Character vector of all unique elements across the sets.

  • overlap_matrix: A logical matrix indicating whether each element is present in each set (rows = elements, columns = sets).

  • intersect_category: Character vector of category codes (e.g., "110") for each element.

Details

  • When provided with genomic regions, the function merges all intervals into a non-redundant set (reduce()), then determines which original sets each region overlaps.

  • When provided with ordinary sets (e.g., gene symbols), it collects all unique elements and records which sets contain them.

The resulting object encodes both the overlap matrix and compact category labels (e.g., "110") representing the overlap pattern of each element. These results can be directly passed to visualization functions such as plotVenn() or plotUpSet().

Internally, computeOverlaps() dispatches to either computeGenomicOverlaps() (for genomic inputs) or computeSetOverlaps() (for ordinary sets). Users are encouraged to call only computeOverlaps().

See also

plotVenn, plotUpSet, GRangesList, reduce

Examples

# Example with gene sets (built-in dataset)
data(gene_list)
ov_sets <- computeOverlaps(gene_list)
head(ov_sets$overlap_matrix)
#>          random_genes_A random_genes_B random_genes_C
#> ALPP               TRUE          FALSE          FALSE
#> ACTG1P9            TRUE          FALSE          FALSE
#> AHSG               TRUE          FALSE          FALSE
#> ASIC2              TRUE          FALSE          FALSE
#> ACTG1P10           TRUE          FALSE          FALSE
#> ALAS1              TRUE          FALSE          FALSE
plotVenn(ov_sets)


# Example with genomic regions (built-in dataset)
data(a549_chipseq_peaks)
ov_gr <- computeOverlaps(a549_chipseq_peaks)
head(ov_gr$overlap_matrix)
#>      MED1_Dex_chr7 BRD4_Dex_chr7 GR_Dex_chr7
#> [1,]         FALSE          TRUE       FALSE
#> [2,]         FALSE          TRUE       FALSE
#> [3,]         FALSE         FALSE        TRUE
#> [4,]          TRUE          TRUE        TRUE
#> [5,]         FALSE          TRUE       FALSE
#> [6,]         FALSE          TRUE       FALSE
plotVenn(ov_gr)