Abstract
Abstract Epigenome-wide association studies (EWAS) often detect a large number of differentially methylated sites or regions, many are located in distal regulatory regions. To further prioritize these significant sites, there is a critical need to better understand the functional impact of CpG methylation. Recent studies demonstrated CpG methylation-dependent transcriptional regulation is a widespread phenomenon. Here we present MethReg, an R/Bioconductor package that analyzes matched DNA-methylation and gene-expression data, along with external transcription factor (TF) binding information, to evaluate, prioritize, and annotate CpG sites with high regulatory potential. By simultaneous modeling three key elements that contribute to gene transcription (CpG methylation, target gene expression and TF activity), MethReg identifies TF-target gene associations that are present only in a subset of samples with high (or low) methylation levels at the CpG that influences TF activities, which can be missed in analyses that use all samples. Using real colorectal cancer and Alzheimer’s disease datasets, we show MethReg significantly enhances our understanding of the regulatory roles of DNA methylation in complex diseases. Competing Interest Statement The authors have declared no competing interest.