讲座信息
主题:使用全基因组汇总统计数据加强因果推断
Strengthen Causal Inference Using Genome-wide Summary Statistics
嘉宾:杨灿
地点:腾讯会议
时间:2022/5/27(周五)20:00
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讲座摘要
Inferring the causal relationship between a risk factor (exposure) and a complex trait of interest (outcome) is essential in biomedical research and social science. Mendelian Randomization (MR) is a valuable tool for inferring causal relationships among a wide range of traits using summary statistics from genome-wide association studies (GWAS). Existing MR methods often rely on strong assumptions, resulting in many false positive findings. To relax MR assumptions, ongoing research has been primarily focused on accounting for confounding due to pleiotropy. Here we show that sample structure is another major confounding factor, including population stratification, cryptic relatedness, and sample overlap.  We propose a unified MR approach, MR-APSS, which (i) accounts for pleiotropy and sample structure simultaneously by leveraging genome-wide information; (ii) allows to include more genetic instruments with moderate effects to improve statistical power without inflating type I errors. We first evaluated MR-APSS using comprehensive simulations and negative controls, and then applied MR-APSS to study the causal relationships among a collection of diverse complex traits. The results suggest that MR-APSS can better identify plausible causal relationships with high reliability. In particular, MR-APSS can perform well for highly polygenic traits, such as psychiatric disorders and social traits, where the strengths of IVs tend to be relatively weak and existing methods for causal inference are vulnerable to confounding effects. This is a joint work with Hu Xianghong, Zhao Jia, Lin Zhixiang, Wang Yang, Peng Heng, Wan Xiang and Zhao Hongyu.

个人简介
杨灿博士现为香港科技大学数学系副教授,健康数据分析中心主任,大数据研究院教授成员他分别于2003年和2006年在浙江大学获得工学学士学位和工学硕士学位,并于2011年在香港科技大学获得电子计算机工程博士学位。他是耶鲁大学的博士后(2011-2012)和副研究员(2012-2014)。他的研究领域专注于统计方法的开发以及计算工具在大规模数据分析中的应用他的研究论文发表在高影响力的期刊上,Nature Computational Science, Nature Communications, Proceedings of the National Academy of Sciences (PNAS), IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Annals of Statistics, The American Journal of Human Genetics杨灿博士获得了2012年香港青年科学家一等奖。截至2022年4月,杨博士的工作已被引用4007次,h指数为28。杨博士还得到香港政府创新技术基金的支持与产业界建立紧密合作。

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