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

NC Sheffield, C Bock - Bioinformatics, 2016 - academic.oup.com
Bioinformatics, 2016academic.oup.com
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. Availability and Implementation: R package available in Bioconductor …
Abstract
Summary: 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.
Availability and Implementation: R package available in Bioconductor and on the following website: http://lola.computational-epigenetics.org.
Contact: nsheffield@cemm.oeaw.ac.at or cbock@cemm.oeaw.ac.at
Oxford University Press