Speaker: 焦泽宇博士，中国科学技术大学

Title: Insights and challenges in the replicability of large-scale multi-omics association studies

Language: Chinese

Time & Venue: 2025.08.08 16:00-17:00 思源楼405会议室

Abstract: The development of high-throughput multi-omics platforms and recent breakthroughs in artificial intelligence (AI) have enhanced our understanding of the molecular mechanisms underlying various human behaviors and diseases. In recent years, association analyses remain fundamental in large-scale high-throughput studies, yet replicability challenges arise in these studies. Given the continuous expansion for large-scale multi-omics association studies, there is still a lack of systematic replicability investigations. Recently, our studies addressed this foundational issue and delivered three insights: (1) We developed a model-based approach to assess replicability for large-scale high-throughput radiomics-based association studies; (2) We demonstrated the merits and challenges for plasma proteomics in the replicability of associations; and (3) Based on kernel density estimation (KDE) approach, we proposed a novel framework to assess the theoretical replicability and sample size requirements for large-scale multi-omics association studies.