Dr. Lisa Strug

Speaker: Dr. Lisa Strug, Director of the Data Sciences Institute at the University of Toronto, Director of the Ontario Region of CANSSI, and Senior Scientist, Genetics and Genome Biology at SickKids in Toronto
Title: Statistical Tools For Improved Understanding of GWAS Loci: Applications in Cystic Fibrosis
February 18, 2022
Time: 1:30PM (PDT)    
Location: Hybrid - Hal 126 and Zoom 


Genome-wide association studies (GWAS) identify loci rather than responsible gene(s), relevant tissue(s) of origin or mechanism of action for a studied trait.  To understand the mechanism by which the locus contributes to disease requires functional investigation, and this needs to be hypothesis-driven, in a relevant cellular model of the contributing gene.  I will discuss two statistical tools we have developed to bridge this gap and guide the design of functional studies.  The first being a data integration approach referred to as colocalization and implemented in our software tool LocusFocus, which integrates GWAS and gene expression summary statistics to pinpoint the most likely responsible gene and tissue of origin.  The second is a novel tool for differential gene expression analysis based on robust profile likelihoods, made possible by the increasing availability of larger sample sizes for what has historically been cost-prohibitive.  Implementing these tools at a Cystic Fibrosis (CF) modifier gene locus identified through GWAS of CF lung disease, I will demonstrate how they guide our understanding of the mechanism by which the locus contributes to disease, generate hypotheses for functional investigation and of which gene in what model.