报告题目：Integrative analysis of metabolomics and epigenetics using the ELEMENT cohort
报 告 人: Prof. Peter Song
Dept. of Biostatistics, University of Michigan
Biological pathway plays the central role in translational medicine. Association analysis of epigenome and metabolome involves high-throughput, high-dimensional data, which presents a great analytic challenge for biostatisticians to overcome in order to minimize false discovery rate. In this talk, I will present an association analysis of blood leukocyte DNA methylation with plasma metabolite levels in peripubertal children based on a cross-sectional dataset from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) cohort. Methodological illustration will be given throughout the talk.
Dr. Song received his PhD in Statistics from the University of British Columbia, Vancouver, Canada in 1996. Dr. Song‘s research interests include bioinformatics, longitudinal data analysis, and statistical genetics. Dr. Song was awarded to prestigious John von Neumann’s Professorship at Technical University of Munich, Germany in 2013. He was an Elected Member of International Statistical Institute. Dr. Song now serves as an Associate Editor of Canadian Journal of Statistics, Statistica Sinica, and Sankhya.