Research summary
Our ability to prevent and treat disease increasingly depends on understanding human genetic variation—where it comes from, how it functions, and how it can be used to improve health outcomes. But most genomic data come from narrow population groups, which limits their usefulness across diverse communities. As Canada Research Chair in Statistical and Population Genetics, Dr. Simon Gravel is developing statistical tools to better analyze population-scale genomic data and interpret genetic risk in real-world, heterogeneous populations.
Drawing on topological data analysis and interpretable machine learning, Gravel and his research team are developing risk prediction models and clarifying how genes and the environment interact. They are also using unique genealogical and genomic resources from Quebec to model the evolution of disease-related variants over time and geography. Working with clinicians, anthropologists, historians and ethicists, they aim to support equitable, ethically grounded genomic research that reflects and benefits diverse populations across Canada and beyond.