Inferring gene regulatory networks using DNA methylation data
We show much-improved accuracy of inference of GRN (gene regulatory network) structure resulting from the use of an epigenomic prior network. We also find that DNAme data are very effective for inferring the epigenomic prior network, recapitulating known epigenomic network structure found previously from chromatin accessibility data, and in some cases providing potential TF cis-regulations for eight times as many genes compared to chromatin accessibility data. When our proposed methodology is applied to real datasets from human embryonic development and from women at risk of breast cancer, we find patterns of differential cis-regulation that are in line with expectations under appropriate biological models. ### Competing Interest Statement The authors have declared no competing interest.