Our research group works on three synergistic areas, statistical genetics, functional genomics and complex disease genetics. We develop novel methods to analyze very large scale datasets, in order to identify genes that are responsible for disease, understand the disease mechanism, and gain clinical insights.
We develop statistical methods and software tools to efficiently and effectively analyze large scale sequence dataset. We focus on the analysis of biobank scale dataset and the meta-analysis of sequence based association studies. We developed a few highly popular software tools including RVTESTS and RAREMETAL. Our methodology work has led to numerous publications in leading journals such as Nature Genetics, the American Journal of Human Genetics and PLOS Genetics.
In functional genomics, we develop and apply statistical methods and softwares to understand the biology of X-chromosome inactivation. We also investigate how to fine map causal genetic variants, and identify target genes and relevant tissues from the association analysis results.
Complex Trait Genetics:
Our current focus on the complex traits include cardiovascular disease, substance use and addiction and lupus. Our goal is to interpret the GWAS results, elucidate the genetic basis of associated genes, and gain clinical insights. Our group played leading roles in these studies, and our work has led to the publication of a few high profile studies in top journals including Nature Genetics.