Data Analysis of DNA Methylation Epigenome-Wide Association Studies (EWAS): A Guide to the Principles of Best Practice

Basharat Bhat; Gregory T Jones

doi:10.1007/978-1-0716-2140-0_2

Data Analysis of DNA Methylation Epigenome-Wide Association Studies (EWAS): A Guide to the Principles of Best Practice

Methods Mol Biol. 2022:2458:23-45. doi: 10.1007/978-1-0716-2140-0_2.

Authors

Basharat Bhat¹, Gregory T Jones²

Affiliations

¹ Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
² Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand. greg.jones@otago.ac.nz.

PMID: 35103960
DOI: 10.1007/978-1-0716-2140-0_2

Abstract

Array-based EWAS have become an increasingly popular technique to identify population epigenetic effects, particularly in humans. With the arrival of nonhuman species arrays, such as the mouse, this is likely to become an even more widely used technology. This chapter provides the less experienced researcher a guide to the analysis of data from the most widely used platform, the Illumina Infinium Methylation assay. This includes an overview of quality filtering, data normalization, analysis options, and techniques to improve the interpretation of results.

Keywords: DNA methylation; Epigenome-wide association studies; Methylation quantitative trait loci (meQTL).

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Animals
CpG Islands
DNA Methylation*
Data Analysis
Epigenesis, Genetic
Epigenome*
Genome-Wide Association Study / methods
Humans
Mice