Computational approaches in clinical epigenomics
Speaker: Fei-Man Hsu, Ph.D.
IDRE Fellow
Department of Molecular, Cell, and Developmental Biology
University of California Los Angeles
Abstract: DNA methylation signatures have high predictive value and could be used to predict health outcomes. Challenges remained in clinical studies such as the large population variations and the biopsy with mixed cell types which all contribute to DNA methylation dynamics. In this presentation I will introduce the computational approaches of clinical epigenomics with our recent research that applied targeted bisulfite sequencing (TBS-seq) to peripheral blood mononuclear cells (PBMCs) from 156 individuals before lung or kidney transplant in two medical centers to study the impact of cytomegalovirus (CMV) to the host epigenome. Cell type composition contributes most DNA methylation changes in PBMCs, and we resolved the mixed cell type issue with a reference-based cell type deconvolution method. Lastly, I will direct to a reference-free source-of-origin cell type classifier under development.
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