PETM: a penalized Exponential Tilt Model for analysis of correlated high-dimensional DNA methylation data.

ABSTRACT:

Motivation

DNA methylation plays an important role in many biological processes and cancer progression. Recent studies have found that there are also differences in methylation variations in different groups other than differences in methylation means. Several methods have been developed that consider both mean and variance signals in order to improve statistical power of detecting differentially methylated loci. Moreover, as methylation levels of neighboring CpG sites are known to be strongly correlated, methods that incorporate correlations have also been developed. We previously developed a network-based penalized logistic regression for correlated methylation data, but only focusing on mean signals. We have also developed a generalized exponential tilt model that captures both

SUBMITTER: Sun H 

PROVIDER: S-EPMC5860278 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature