LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor | Zendy

Nathan C. Sheffield | Zendy; Christoph Bock | Zendy

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LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor

Author(s) -

Nathan C. Sheffield,

Christoph Bock

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv612

Subject(s) - bioconductor , epigenomics , computational biology , context (archaeology) , genomics , locus (genetics) , computer science , r package , biology , functional genomics , genetics , genome , gene , dna methylation , programming language , paleontology , gene expression

Genomic datasets are often interpreted in the context of large-scale reference databases. One approach is to identify significantly overlapping gene sets, which works well for gene-centric data. However, many types of high-throughput data are based on genomic regions. Locus Overlap Analysis (LOLA) provides easy and automatable enrichment analysis for genomic region sets, thus facilitating the interpretation of functional genomics and epigenomics data.

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