Establishing an analytic pipeline for genome-wide DNA methylation

Michelle L. Wright, Mikhail G. Dozmorov, Aaron R. Wolen, Colleen Jackson-Cook, Angela R. Starkweather, Debra E. Lyon, Timothy P. York

The need for research investigating DNA methylation (DNAm) in clinical studies has increased, leading to the evolution of new analytic methods to improve accuracy and reproducibility of the interpretation of results from these studies. The purpose of this article is to provide clinical researchers with a summary of the major data processing steps routinely applied in clinical studies investigating genome-wide DNAm using the Illumina HumanMethylation 450K BeadChip. In most studies, the primary goal of employing DNAm analysis is to identify differential methylation at CpG sites among phenotypic groups. Experimental design considerations are crucial at the onset to minimize bias from factors related to sample processing and avoid confounding experimental variables with non-biological batch effects. Although there are currently no de facto standard methods for analyzing these data, we review the major steps in processing DNAm data recommended by several research studies. We describe several variations available for clinical researchers to process, analyze, and interpret DNAm data. These insights are applicable to most types of genome-wide DNAm array platforms and will be applicable for the next generation of DNAm array technologies (e.g., the 850K array). Selection of the DNAm analytic pipeline followed by investigators should be guided by the research question and supported by recently published methods.