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What is GREAT?

Many coding genes are well annotated with their biological functions. Non-coding regions typically lack such annotation. GREAT, the Genomic Regions Enrichment of Annotations Tool, assigns biological meaning to a set of non-coding genomic regions by analyzing the annotations of the nearby genes. Thus, it is useful in studying cis functions of non-coding genomic regions.

The Bejerano Lab developed GREAT and hosts the GREAT web server.

When is GREAT useful?

Many experimental and computational screens produce sets of interest for GREAT. One natural application is analyzing data from a chromatin immunoprecipitation (ChIP) experiment with a transcription factor of interest. To hypothesize the processes that involve a given transcription factor:

  1. Identify transcription factor binding sites via ChIP.
  2. Use GREAT to find annotations enriched among the genes near the binding sites.
  3. Hypothesize that the transcription factor helps regulate the processes whose annotations are highly enriched.

Why should I use GREAT instead of other annotation tools such as DAVID1 2 or GO::TermFinder3 ?

Other annotation enrichment tools are gene based. The input consists of a list of genes, and the tools provide annotations more common in the input list than in a background list of genes. This does not accurately model input sets of genomic regions because gene-based tests do not account for biases in the assignment of genomic regions to genes. Genes in gene deserts have larger domains of attraction. In other words, a random genomic region is more likely to be assigned to a gene in a gene desert simply because deserts provide large regions where the gene is the nearest one. GREAT more accurately models this situation. Thus, it more accurately calculates enrichments for a set of genomic regions.

GREAT also includes numerous ontologies providing a range of annotations. Many other tools use only the Gene Ontology, but it is useful to consider other types of annotation, such as protein domains and pathways.

References

Footnotes
Ref Notes
1 Huang, D. W., Sherman, B. T., and Lempicki, R. A. Systematic and intergrative analysis of large gene lists using DAVID Bioinformatics Resources, Nature Protoc. 2009; 4(1):44-57.
2 Dennis, G. Jr. et al., DAVID: Database for Annotation, Visualization, and Integrated Discovery, Genome Biol. 2003; 4(5):P3.
3 Boyle E. I. et al., GO::TermFinder – open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes, Bioinformatics 2004; 20(18): 3710-3715.
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