Studies in epigenetics have shown that DNA methylation is a key factor in regulating gene expression. DNA methylation typically occurs in CpG context. When located in a gene promoter, DNA methylation often acts to repress transcription and gene expression. The most commonly used technology of studying DNA methylation is bisulfite sequencing (BS-seq), which can be used to measure genomewide methylation levels on the single-nucleotide scale. Notably, BS-seq can also be combined with enrichment strategies such as reduced representation bisulfite sequencing (RRBS) to target CpG-rich regions in order to save per-sample costs.
A typical DNA methylation analysis often involves identifying differentially methylated regions (DMRs) between different experimental conditions. Many statistical methods have been developed for finding DMRs in BS-seq data. In this talk, I will describe a novel approach of detecting DMRs using edgeR. A case study will be provided to demonstrate how differential methylation analyses can be fit into the existing pipelines specifically designed for RNA-seq differential expression studies. The method proposed in the talk can be applied to any BS-seq data that includes some replication, but it is especially appropriate for RRBS data with small numbers of biological replicates.