easyEWAS

Last updated: 2026-03-04

easyEWAS is an R package for conducting Epigenome-Wide Association Study (EWAS) in a unified and reproducible way. It supports Illumina methylation array platforms including 27K, 450K, EPIC v1, EPIC v2, and MSA, and provides an end-to-end analysis workflow covering association modeling, batch-effect handling, result visualization, bootstrap-based internal validation, enrichment analysis, and optional DMR discovery.

Tutorial

For detailed instruction, you can refer to https://easyewas-tutorial.github.io/.

Installation

Before installing easyEWAS, we recommend pre-installing optional dependencies used by advanced modules.

Core dependencies by function

Function	Required packages	Notes
batchEWAS()	sva	Required for ComBat batch correction
batchEWAS(..., parallel = TRUE)	sva, BiocParallel	BiocParallel is needed only for parallel mode
enrichEWAS()	clusterProfiler, org.Hs.eg.db	Required for ID conversion and GO/KEGG enrichment
enrichEWAS(plot = TRUE, plotType = "dot")	enrichplot	Required for dotplot visualization
dmrEWAS()	DMRcate	Required for DMR analysis

Recommended pre-install

if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install(c(
  "sva",
  "BiocParallel",
  "clusterProfiler",
  "org.Hs.eg.db",
  "enrichplot",
  "DMRcate"
), ask = FALSE, update = TRUE)

Install from GitHub:

remotes::install_github("ytwangZero/easyEWAS")

Load package:

library(easyEWAS)

If you prefer installing only when needed:

• batchEWAS(): BiocManager::install(c("sva", "BiocParallel"))
• enrichEWAS(): BiocManager::install(c("clusterProfiler", "org.Hs.eg.db", "enrichplot"))
• dmrEWAS(): BiocManager::install("DMRcate")

Update: Annotation Data Loading

Large chip annotation tables are now downloaded on demand and cached locally, instead of being bundled inside the main package tarball. This makes installation lighter, faster, and more stable for GitHub users.

Download annotation (one-time per chip type):

downloadAnnotEWAS(chipType = "EPICV2")

Citation

Wang Y, Jiang M, Niu S, Gao X. easyEWAS: a flexible and user-friendly R package for epigenome-wide association study[J]. Bioinformatics Advances, 2025, 5(1): vbaf026.