rGREAT: an R/Bioconductor Package for Functional Enrichment on Genomic Regions

rGREAT: an R/Bioconductor Package for Functional Enrichment on Genomic Regions


Author(s): Zuguang Gu

Affiliation(s): German Cancer Research Center



Functional interpretation is important for genomics and epigenomic studies. GREAT (http://great.stanford.edu/) is a popular tool for functional enrichment on genomic regions and it has been very widely used in current studies. However, as an online tool, GREAT still has limitations, such as outdated annotation data, small numbers of supported organisms (only human and mouse) and gene set collections (only seven). In this package demo, I will introduce an R/Bioconductor package named “rGREAT”. It applies GREAT analysis in two ways. First it serves as a client to directly interact with the GREAT web service in the R environment. It automatically submits the input regions to GREAT and retrieves results from there. Second, it implements the GREAT algorithm locally and it is seamlessly integrated with the Bioconductor annotation ecosystem. The major advantages of rGREAT are listed as follows:1. It allows users to interact with the GREAT web service programmatically and it generates identical results as from the GREAT web service; 2. With the Bioconductor annotation ecosystem, local rGREAT by default supports more than 600 organisms and 31 gene set collections; 3. The API of local rGREAT allows users to perform enrichment analysis on any organism and with any type of gene set collection; 4. We also proposed a general solution for dealing with background regions. The rGREAT package has been published on Bioinformatics (https://doi.org/10.1093/bioinformatics/btac745).

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