Incorporating genetic networks into case-control association studies with high-dimensional DNA methylation data.

ABSTRACT:

Background

In human genetic association studies with high-dimensional gene expression data, it has been well known that statistical selection methods utilizing prior biological network knowledge such as genetic pathways and signaling pathways can outperform other methods that ignore genetic network structures in terms of true positive selection. In recent epigenetic research on case-control association studies, relatively many statistical methods have been proposed to identify cancer-related CpG sites and their corresponding genes from high-dimensional DNA methylation array data. However, most of existing methods are not designed to utilize genetic network information although methylation levels between linked genes in the genetic networks tend to be highly correlated with each oth

SUBMITTER: Kim K 

PROVIDER: S-EPMC6805595 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature