BioinformaticsBioinformaticsPeer-reviewed journal article
ebayGSEA: An improved Gene Set Enrichment Analysis method for Epigenome-Wide-Association Studies
Danyue DongiD, Yuan TianiD, Shijie ZhengiD, Andrew Erich TeschendorffiD
Abstract
MotivationThe biological interpretation of differentially methylated sites derived from Epigenome-Wide-Association Studies remains a significant challenge. Gene Set Enrichment Analysis (GSEA) is a general tool to help aid biological interpretation, yet its correct and unbiased implementation in the EWAS context is difficult due to the differential probe representation of Illumina Infinium DNA methylation beadchips.\n\nResultsWe present a novel GSEA method, called ebayGSEA, which ranks genes, not CpGs, according to the overall level of differential methylation, as assessed using all the probes mapping to the given gene. Applied on simulated and real EWAS data, we show how ebayGSEA may exhibit higher sensitivity and specificity than the current state-of-the-art, whilst also avoiding differential probe representation bias. Thus, ebayGSEA will be a useful additional tool to aid the interpretation of EWAS data.\n\nAvailability and implementationebayGSEA is available from https://github.com/aet21/ebayGSEA, and has been incorporated into the ChAMP Bioconductor package (https://www.bioconductor.org).
- assay: DNA methylation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 24
- FWCI
- 0.99
- Field percentile
- top 27%
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