Direction-aware functional class scoring enrichment analysis of infinium DNA methylation data.

Abstract

Infinium Methylation BeadChip arrays remain one of the most popular platforms for epigenome-wide association studies, but tools for downstream pathway analysis have their limitations. Functional class scoring (FCS) is a group of pathway enrichment techniques that involve the ranking of genes and evaluation of their collective regulation in biological systems, but the implementations described for Infinium methylation array data do not retain direction information, which is important for mechanistic understanding of genomic regulation. Here, we evaluate several candidate FCS methods that retain directional information. According to simulation results, the best-performing method involves the mean aggregation of probe limma t-statistics by gene followed by a rank-ANOVA enrichment test using the mitch package. This method, which we call 'LAM,' outperformed an existing over-representation analysis method in simulations, and showed higher sensitivity and robustness in an analysis of real lung tumour-normal paired datasets. Using matched RNA-seq data, we examine the relationship of methylation differences at promoters and gene bodies with RNA expression at the level of pathways in lung cancer. To demonstrate the utility of our approach, we apply it to three other contexts where public data were available. First, we examine the differential pathway methylation associated with chronological age. Second, we investigate pathway methylation differences in infants conceived with in vitro fertilization. Lastly, we analyse differential pathway methylation in 19 disease states, identifying hundreds of novel associations. These results show LAM is a powerful method for the detection of differential pathway methylation complementing existing methods. A reproducible vignette is provided to illustrate how to implement this method.