Dear Colleagues,
The ASA Statistical Learning and Data Science Section is pleased to announce the July webinar, presented by Dr. Lisa Strug on July 28, 2022.
Title: Genome Data Science: Towards understanding GWAS loci
Speakers: Dr. Lisa Strug, Departments of Statistical Sciences, Computer Science and Biostatistics, University of Toronto
Date and Time: July 28, 2022, 2:00 to 3:30 pm Eastern Time
Registration Link: ASA SLDS Webinar Registration Link [eventbrite.com]
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.
Presenter: Dr. Strug is 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. Dr. Strug is the inaugural Director of the Data Sciences Institute (DSI), a tri-campus, multi-divisional, multi-institutional, multi-disciplinary hub for data science activity at the University of Toronto and affiliated Research Institutes. The DSI's goal is to accelerate the impact of data sciences across the disciplines to address pressing societal questions and drive positive social change. Dr. Strug holds several other leadership positions at the University of Toronto including the Director of the Canadian Statistical Sciences Institute Ontario Region (CANSSI Ontario), and at the Hospital for Sick Children as Associate Director of the Centre for Applied Genomics and the Lead of the Canadian Cystic Fibrosis Gene Modifier Consortium and the Biology of Juvenile Myoclonic Epilepsy International Consortium. She is a statistical geneticist and 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 including the Tier 1 Canada Research Chair in Genome Data Science.
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Zhihua Su, PhD
Associate Professor
Department of Statistics
University of Florida
zhihuasu@stat.ufl.edu------------------------------