2014.5.26 Mixture Models for Joint Analysis of Multiple Genomics Data Sets
Title：Mixture Models for Joint Analysis of Multiple Genomics Data Sets.
Speaker：Hongyu Zhao, Ph.D.
Ira V. Hiscock Professor of Public Health (Biostatistics) and Professor of Genetics and of Statistics
Time： 1:00pm May 26th 2014
Address： Rm 102, East wing of Old Chemistry Building, Peking Unversity
Chair： Prof. Minghua Deng, Center for Quantitative Biology
With genomics data rapidly accumulating, much more may be learned from joint analysis of multiple data sets. In this presentation, we first present a mixture model-based framework for joint data analysis, and then illustrate its usefulness to joint analysis of multiple ChIP-chip data sets to infer protein-DNA bindings, multiple cancer expression profiles from the Cancer Genome Atlas project to identify miRNA–gene interactions, and multiple genome wide associate data and genome annotation data to prioritize candidate single nucleotide polymorphisms for follow-up studies.