Recent years have seen revolutions in biological and biomedical research through the rapid developments of technologies for collecting multi-omics, imaging, deep phenotype and other data at scale, as well as the establishment of biobanks enrolling hundreds of thousands of individuals across diverse populations. The rich and complex data collected from these resources present great challenges in data analysis and interpretation. This proposed session showcases some of the most exciting progresses in statistical genetics and genomics to address these challenges with the aims of identifying the genetic basis of complex diseases and uncovering the biological processes underlying disease onset, progression, and treatment response. We have four outstanding speakers discussing novel statistical and computational approaches to inferring layer-specific gene expression profiles from integrated analysis of spatial transcriptomics and imaging data, inferring cell-type-specific co-expression networks from bulk samples, transcriptome wide association studies across populations using imputed expression levels, and image wide association studies using imputed imaging traits. This session will be of interest to a broader audience at the World Statistics Congress.

Organiser: Dr Hongyu Zhao 

Chair: Dr Hongyu Zhao

Speaker: Emma Jingfei Zhang 

Speaker: Josee Dupuis

Speaker: Xiang Zhou 

Speaker: Yongjin Park