Pan-cancer analysis of differential DNA methylation patterns.

ABSTRACT:

Background

DNA methylation is a key epigenetic regulator contributing to cancer development. To understand the role of DNA methylation in tumorigenesis, it is important to investigate and compare differential methylation (DM) patterns between normal and case samples across different cancer types. However, current pan-cancer analyses call DM separately for each cancer, which suffers from lower statistical power and fails to provide a comprehensive view for patterns across cancers.

Methods

In this work, we propose a rigorous statistical model, PanDM, to jointly characterize DM patterns across diverse cancer types. PanDM uses the hidden correlations in the combined dataset to improve statistical power through joint modeling. PanDM takes summary statistics from separate analyses

SUBMITTER: Shi M 

PROVIDER: S-EPMC7579968 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature