Dalla Lana School of Public Health

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Join us at the CANSSI Ontario STatistics Seminars (CAST) with…

Dr. Lisa Strug
Lisa Strug, PhD
Canada Research Chair in Genome Data Science Director, Data Sciences Institute at the University of Toronto

Faculty of Arts and Science, University of Toronto
Director, CANSSI Ontario
Professor of Statistical Sciences, Computer Science and Biostatistics

The Hospital for Sick Children
Senior Scientist, Program in Genetics and Genome Biology Associate Director, The Centre for Applied Genomics

Free Hybrid (On Line/In Person) Event | Registration Required

Talk Title:
Genome Data Science: Towards understanding GWAS loci

Abstract:
Genome Data Science includes the collection, manipulation, storage, visualization and extraction of information from increasingly larger, more heterogeneous and complex genomic data, in reproducible, fair and ethical ways. In the webinar I will describe our use of genome data science to identify genetic contributors to disease, using the example of the Canadian Cystic Fibrosis Gene Modifier Study. I will discuss data collection, manipulation, visualization, genome- wide association study (GWAS) analysis, and the development of novel tools to integrate heterogeneous data. These tools are necessary because GWAS identifies loci rather than the responsible gene(s), relevant tissue(s) of origin or mechanism of action for a studied trait. To understand the mechanism by which a locus contributes to disease requires functional investigation, and this needs to be hypothesis-driven, in a relevant cellular model of the contributing gene. To bridge this gap and guide the design of functional studies, we have developed data visualization and statistical integration tools implemented in our software LocusFocus, which integrates two sets of summary statistics, for example from a GWAS and gene expression analysis to pinpoint the most likely responsible gene and tissue of origin. Implementing LocusFocus at a genetic locus for Cystic Fibrosis (CF) lung disease variability identified through GWAS, I will demonstrate how it can guide our understanding of the mechanism by which the locus contributes to disease.

Speaker Profile:
Dr. Strug is a Professor in the Departments of Statistical Sciences, Computer Science and cross-appointed in Biostatistics at the University of Toronto and is a Senior Scientist in the Program in Genetics and Genome Biology at the Hospital for Sick Children. She is the Lead of the Canadian Cystic Fibrosis (CF) Gene Modifier Study, Co-Lead of the International CF Gene Modifier Consortium, Director of the Ontario Regional Centre of the Canadian Statistical Sciences Institute (CANSSI) and the Academic Director of the Data Science Institute at the University of Toronto. As a statistical geneticist, her research focuses on the development of novel statistical approaches to analyze and integrate multi-omics data to identify genetic contributors to complex human disease. She has received several honours and awards including the Tier 1 Canada Research Chair in Genome Data Science and Cystic Fibrosis Canada’s 2023 Senior Scientist Research Award.