Overview: Genome-wide association studies (GWAS) have led to the identification of thousands of genetic variants associated with diseases such as type-2 diabetes and hypertension.  However, discoveries were made only after very large samples were collected and analyzed.  Because of confidentiality restrictions on individual-level data sharing, such large samples were often reached by combining GWAS summary results from multiple cohorts using meta-analysis approaches.  In this workshop, we will introduce statistical meta-analysis approaches for combining GWAS results.  This will be followed by a hands-on tutorial on how to perform meta-analyses of genetic association results.

Learning Goals: At the end of this workshop, students should be able to perform a meta-analysis of results form genome-wide association studies using commonly used meta-analysis software such as METAL and GWAMA.

Prerequisites:

• Before registering for the workshop, students must first follow the software installation instructions found in the attached PDF document. At the end of the document, there is a quiz question and the student must provide the answer in the Registration Form below.
• Students should already have experience with Linux and/or Cluster Computing. If you do not have experience, please contact CDSI's admin. assistant, Nadime Rahimian, at cdsi.science@mcgill.ca for recordings of our workshops Intro to Linux and Intro to Cluster Computing. 
• Students must bring their own laptop to this workshop.

Location: HYBRID. Online via Zoom, or in-person at the Education Building room 113.
Instructor: Josee Dupuis, Ph.D., Professor and Chair of the Department of Epidemiology, Biostatistics and Occupational Health