Guidance for DNA methylation studies: statistical insights from the Illumina EPIC array

Publication type

Journal Article

Published in

BMC Genomics


Georgina Mansell, Tyler J. Gorrie-Stone, Yanchun Bao, Meena Kumari, Leonard S. Schalkwyk, Jonathan Mill and Eilis Hannon

Publication date


There has been a steady increase in the number of studies aiming to identify DNA methylation differences associated with complex phenotypes. Many of the challenges of epigenetic epidemiology regarding study design and interpretation have been discussed in detail, however there are analytical concerns that are outstanding and require further exploration. In this study we seek to address three analytical issues. First, we quantify the multiple testing burden and propose a standard statistical significance threshold for identifying DNA methylation sites that are associated with an outcome. Second, we establish whether linear regression, the chosen statistical tool for the majority of studies, is appropriate and whether it is biased by the underlying distribution of DNA methylation data. Finally, we assess the sample size required for adequately powered DNA methylation association studies.







Statistical Analysis, Biology and Genetics


Open Access; © The Author(s) 2019