Abstract
Genome-wide association study (GWAS) has been a great success in the past decade with thousands of chromosomal regions in the human genome implicated in hundreds of complex diseases. A typical GWAS involves thousands to hundreds of thousands of individuals, each queried at over millions of sites in the human genome. Despite the successes, significant challenges remain in both identifying new risk loci and interpreting results from these large data sets. In this lecture, the speaker will describe his recent efforts to develop statistical methods and resources to infer the genetic architecture of complex disease. These methods include the proportion of phenotypic variations explained by genetic variations, the tissue and cell-type origin of diseases, genetic correlations among phenotypes, and genetic risk predictions. The effectiveness of his methods will be demonstrated through the applications to a large number of GWAS results.
This is joint work with Qiongshi Lu, Can Yang, Jiming Jiang, Ryan Powels, Yiming Hu, Qian Wang and others.
About the speaker
Prof Hongyu Zhao received his PhD in statistics from University of California at Berkeley in 1995 and joined the University of California at Los Angeles as an Adjunct Assistant Professor afterwards. He moved to Yale University in 1996, and is currently the Ira V Hiscock Professor of Biostatistics, Professor of Genetics and Professor of Statistics and Data Science.
Prof Zhao’s research interests are the applications of statistical methods in molecular biology, genetics, drug developments, and personalized medicine. Some of his recent projects include large scale genome wide studies to identify genetic variants underlying complex, biological network modeling and analysis, disease biomarker identification, genome annotations, microbiome analysis and systems biology study of herbal medicine.
Prof Zhao received the Mortimer Spiegelman Award by the American Public Health Association (2008). He was elected a Fellow of the American Association for the Advancement of Science (2010), Fellow of the Institute of Mathematical Statistics (2007) and Fellow of the American Statistical Association (2006). He was also elected a member of the International Statistical Institute (2006).
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