Abstract
Integrating phenotype and genotype data with functional genomic annotations can deepen our understanding of the genetic basis of complex traits. Previous studies have shown that the distribution of genetic effects varies across functional annotation categories, partly shaped by natural selection. In this presentation, I will discuss statistical methods we have developed to leverage functional annotations for improving polygenic prediction of complex traits and for genome-wide fine-mapping of causal variants. I will also review current strategies for integrating functional genomics with GWAS data to identify cell types associated with complex traits, share key lessons we learned from benchmarking different methods, and present our findings from applying a temporal single-cell transcriptomic data analysis to psychiatric disorders.

Biography
Dr Jian Zeng is a Group Leader in statistical genetics and an NHMRC Emerging Leadership Fellow at the Institute for Molecular Bioscience (IMB) at the University of Queensland (UQ). He received his PhD in Quantitative Genetics from Iowa State University and joined the Program in Complex Trait Genomics at UQ in 2016. His research focuses on developing and applying innovative statistical methods to understand the genetic architecture of complex traits. He works on identifying genetic variants, genes, and molecular phenotypes associated with trait variation, as well as disease risk prediction using genome sequence data. Since 2022, Dr Zeng has also served as Director of the Genetics & Genomics Winter School, an annual in-person course held each July, which provides training in computational methods for genetic data analysis.