Abstract
Thousands of DNA methylation (DNAm) array samples from human blood are publicly available on the Gene Expression Omnibus (GEO), but they remain underutilized for experiment planning, replication, and cross-study and cross-platform analyses. To facilitate these tasks, we augmented our recountmethylation R/Bioconductor package with 12,537 uniformly processed EPIC and HM450K blood samples on GEO as well as several new features. We subsequently used our updated package in several illustrative analyses, finding (1) study ID bias adjustment increased variation explained by biological and demographic variables, (2) most variation in autosomal DNAm was explained by genetic ancestry and CD4+ T-cell fractions, and (3) the dependence of power to detect differential methylation on sample size was similar for each of peripheral blood mononuclear cells (PBMC), whole blood, and umbilical cord blood. Finally, we used PBMC and whole blood to perform independent validations, and we recovered 40-46% of differentially methylated probes (DMPs) between sexes from two previously published epigenome-wide association studies (EWAS).
Competing Interest Statement
The authors have declared no competing interest.
