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

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rGREAT is a new R package that provides local functional enrichment analysis for genomic regions. It overcomes limitations of the online GREAT tool by supporting over 600 organisms and custom datasets.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • The Genomic Regions Enrichment of Annotations Tool (GREAT) is a popular online resource for functional enrichment analysis of genomic regions.
  • Online GREAT tool limitations include outdated annotation data, limited organism support, and lack of user extensibility.

Purpose of the Study:

  • To develop a local, extensible R/Bioconductor package implementing the GREAT algorithm.
  • To enhance functional enrichment analysis by supporting a wider range of organisms and custom gene sets.

Main Methods:

  • Developed the rGREAT R/Bioconductor package to perform GREAT analysis locally.
  • Integrated support for over 600 organisms and numerous gene set collections.
  • Implemented a generalized method for handling background genomic regions.
  • Utilized Ensembl BioMart for retrieving Gene Ontology gene sets.

Main Results:

  • rGREAT provides local functional enrichment analysis, overcoming limitations of the online GREAT tool.
  • The package supports over 600 organisms with extensive gene set collections.
  • Users can incorporate custom gene sets and organisms for analysis.
  • A general background region handling method is included.

Conclusions:

  • rGREAT offers a flexible and comprehensive local alternative for genomic region functional enrichment.
  • The package enhances accessibility and customizability for researchers in genomics and bioinformatics.
  • rGREAT expands the utility of the GREAT algorithm for diverse biological research.