rGREAT: an R/bioconductor package for functional enrichment on genomic regions

Abstract

Summary: GREAT (Genomic Regions Enrichment of Annotations Tool) is a widely used tool for functional enrichment on genomic regions. However, as an online tool, it has limitations of outdated annotation data, small numbers of supported organisms and gene set collections, and not being extensible for users. Here, we developed a new R/Bioconductorpackage named rGREAT which implements the GREAT algorithm locally. rGREAT by default supports more than 600 organisms and a large number of gene set collections, as well as self-provided gene sets and organisms from users. Additionally, it implements a general method for dealing with background regions.

Availability and implementation: The package rGREAT is freely available from the Bioconductor project: https://bioconductor.org/packages/rGREAT/. The development version is available at https://github.com/jokergoo/rGREAT. Gene Ontology gene sets for more than 600 organisms retrieved from Ensembl BioMart are presented in an R package BioMartGOGeneSets which is available at https://github.com/jokergoo/BioMartGOGeneSets.

Supplementary information: Supplementary data are available at Bioinformatics online.

Fig. 1.

The binomial model of the GREAT analysis. (A) Basal domain and extensions around transcription start sites of genes. (B) A region set which is associated with genes in a specific gene set (green segments). The basal domain and its extensions are reduced as a single segment in the figure. (C) Overlapping regions in the region set are merged. The fraction of the genome that is covered by the region set is defined as p. (D) For a list of N input regions, the number of input regions that fall into the region set follows a binomial distribution. (E) When background regions are provided, the fraction of the background regions that is covered by the region set (within the red rectangles) is denoted as p₂. (F) For a list of N input regions, only N₂ input regions that fall into the background are considered. The number of input regions that fall in both region set and background also follows a binomial distribution. The figures are adapted from the original GREAT paper (A color version of this figure appears in the online version of this article)