A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data.

ABSTRACT: DNA methylation is an important epigenetic modification that has essential roles in cellular processes including gene regulation, development and disease and is widely dysregulated in most types of cancer. Recent advances in sequencing technology have enabled the measurement of DNA methylation at single nucleotide resolution through methods such as whole-genome bisulfite sequencing and reduced representation bisulfite sequencing. In DNA methylation studies, a key task is to identify differences under distinct biological contexts, for example, between tumor and normal tissue. A challenge in sequencing studies is that the number of biological replicates is often limited by the costs of sequencing. The small number of replicates leads to unstable variance estimation, which can reduce accuracy

SUBMITTER: Feng H 

PROVIDER: S-EPMC4005660 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature