News & Events

Speaker: J. Sunil Rao, PhD
Division of Biostatistics and Health Data Science
School of Public Health
Masonic Cancer Center
University of Minnesota

Topic: "New Developments in Mixed Model Prediction with Applications to Predicting DNA Methylation Profiles"

Time: 2 – 3 p.m.

Join Zoom Meeting

Abstract: Epigenetic modifications link the environment to gene expression and play a crucial role in tumor development. DNA methylation has gained significant attention in cancer research, including cervical cancer, the focus of this study. Public repositories such as The Cancer Genome Atlas (TCGA) provide extensive genetic profiles but comparatively limited epigenetic data. We propose a new method, called multivariate classified mixed model prediction (mvCMMP), a multivariate nested-error regression framework for predicting DNA methylation from genetic and clinical data in cervical cancer. The mvCMMP exploits dependencies among outcomes and class-specific random effects associated with new observations.  We show that mvCMMP improves prediction accuracy over competing methods, highlighting the benefits of borrowing strength across methylation markers and shared random effects.

––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––

Organizer: Zhengjia (Nelson) Chen, PhD