Correcting for sample heterogeneity in methylome-wide association studies

Abstract

Epigenome-wide association studies (EWAS) face many of the same challenges as genome-wide association studies (GWAS), but have an added challenge in that the epigenome can vary dramatically across cell types. When cell-type composition differs between cases and controls, this leads to spurious associations that may obscure true associations. We have developed a computational method, FaST-LMM-EWASher, which automatically corrects for cell-type composition without needing explicit knowledge of it. In this chapter, we provide a tutorial on using FaST-LMM-EWASher for DNA methylation data and discuss data analysis strategies.