Statistical Methods for the Analysis of Genetic Data with Survival Outcomes

Collaborative Research Team Project: 2019-2022

The main goal of this project is to enhance collaborations among various Canadian teams and researchers, with research interests and expertise in the statistical genetic data analysis with correlated survival outcomes, through the joint supervision of graduate students and postdoctoral fellows and the organization of annual scientific team meetings and conferences. The specific aims of our project are:

  1.  Modelling the dependence between time-to-event outcomes occurring among related individuals in the context of genetic studies and deriving estimation and hypothesis testing procedures for the parameters of the obtained models.
  2. Deriving tests to detect association between high-dimensional genome-wide variant data and survival outcomes.
  3. Causal models and inferring direct and indirect genetic effects on survival outcomes in genetic association studies.
  4. Modelling and estimating the effects of medical interventions such as screening and prophylactic surgery (e.g. mastectomy, oophorectomy) on survival outcomes in the context of genetic studies.

The team co-leaders are Lajmi Lakhal-Chaieb, Université Laval; Richard Cook, University of Waterloo; and Laurent Briollais, Lunenfeld Tanenbaum Research Institute of Mount Sinai Hospital, Toronto. Other collaborators include Shelley Bull, Lunenfeld-Tanenbaum Research Institute; Yun-Hee Choi, Schulich School of Medicine and Dentistry, Western University; and Yildiz Yilmaz, Memorial University.

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