Abstract:
|
Differentially methylation regions (DMRs) or positions (DMPs) are genomic regions methylated differentially across phenotypes or biological samples. Identifying DMPs/DMRs is essential for disease prevention, treatment, and mechanism studies. In our study, by taking the correlation of methylation levels among spatially neighboring CpG sites into account, we propose a generalized linear model based on the generalized beta distribution to identify DMRs. Simulation studies from a real DNA methylation dataset show that the proposed method has a higher true positive rate compared to existing methods. Particularly, the proposed model performs well in detecting DMRs that are moderately correlated to the phenotype. To further illustrate our methods, we applied the proposed model to identify age-related DMRs on two genomic datasets from National Center for Biotechnology Information.
|