I have analysed my data (from the Epic Illumina array), using limma to find single differentially methylated CpGs (DMPs), and DMRcate to find DMRs. The data and the model is exactly the same for both analyses; using no intercept and specifying a contrast of interest.
When I compare the lists of genes that the significant DMRs and DMPs map to, there is of course an overlap, but more than half of the genes with a significant DMR do not show up on the list I get using limma. When I check all CpGs mapping to these genes (not just the ones in the DMR), then none of them show up on the list of significant DMPs. I understand that due to the smoothing function, some DMRs may stretch into the promoter region of a gene, hence it is possible to get genes on the list of DMRs that do not appear on the list from limma, but I have examples where the DMR is the exon of a gene. In this case I would expect that at least one of the CpGs would show up on the list of significant DMPs from limma, since I thought at least one CpG within the DMR would have to be individually significant. Is this not the case?
My question is therefore why this happens? Does the smoothing function of DMRcate give me lots of false positives?
Kind regards, Anne-Kristin