DNA methylation plays a fundamental role in the regulation of the genome, but the optimal strategy for analysis of
genome-wide DNA methylation data remains to be determined. We developed a comprehensive analysis pipeline
for epigenome-wide association studies (EWAS) using the Illumina Infinium HumanMethylation450 BeadChip, based
on 2,687 individuals, with 36 samples measured in duplicate. We propose new approaches to quality control, data
normalisation and batch correction through control-probe adjustment and establish a null hypothesis for EWAS
using permutation testing. Our analysis pipeline outperforms existing approaches, enabling accurate identification
of methylation quantitative trait loci for hypothesis driven follow-up experiments.