LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor
By Nathan C. Sheffield, Christoph Bock. Bioinform., 2015
424 citations recorded by the source corpus.
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
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/7a32b390607ee5854f2969f99b4a9ec8738b18db
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Citations in the corpus
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- Specification of tissue-resident macrophages during organogenesis (2016, methodology): “We also incorporated ChIP-seq binding profiles (bigWig) for factors identified in the LOLA analysis from the CODEX database.”
- The impact of sex on gene expression across human tissues (2020, methodology): “Transcription factor binding site enrichment in promoter regions of sex-biased genes was performed with Unibind (22) and runLOLA (69) (fig.”