报告题目:Incorporating functional annotation to develop genome-wide association study method

报告人：郝兴杰 博士

报告时间：2018年3月28日（周三）16:30

报告地点：逸夫楼C座314会议室

摘要：

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study.

报告人简介：

先后在太阳成集团官网动科动医学院获得学士（2012），硕士（2014）和博士（2018）学位，研究生期间在加拿大阿尔伯塔大学（1年）和美国密歇根大学（2年）进行合作研究项目。研究兴趣为统计遗传和生物信息学，目前主要从事整合功能注释信息的GWAS/GS方法研究，以及复杂性状和疾病遗传机制的挖掘。分别在Plos Genetics和BMC Genetics上发表一作文章，并有多篇一作文章目前正在BMC Genomics, Animal Genetics和Scientific Reports上审稿，也担任Scientific Reports审稿人。