Wellcome Connecting Science Course Run Website Link
Course Time Table 2025
Course Informatics Guide
The growing availability of African genomic datasets is opening new opportunities to deepen our understanding of the aetiology of human diseases. As African genomic data from genome-wide analytical studies continues to grow, it is crucial to empower African scientists with the tools and approaches needed to analyse these data using state-of-the-art tools and methodologies, advancing research and genomics applications both in Africa and globally.
This short course is designed to equip scientists based in Africa with the skills and knowledge to perform polygenic risk scores (PRS) analysis. Participants will explore both theoretical and practical aspects of PRS research through lectures, tutorials, hands-on computational sessions, and guest seminars by experts in the field. By the end of the workshop, attendees will have a strong grasp of PRS concepts and practical expertise to analyse global genomic data.
The course begins with a high-level overview of genome-wide association studies, followed by foundational and advanced topics in PRS, such as pathway-based PRS and methods for identifying rare variants. A key focus will be the “PRS Portability Problem” and strategies for applying PRS to diverse and admixed ancestry samples. The workshop concludes with group projects where participants design, conduct, and present research, receiving feedback from the workshop team.
Students and scientists based in Africa who are interested in the theory and/or application of polygenic risk scores, important for those undertaking research in: Bioinformatics, Genetic Epidemiology, Population Genetics, Statistical Genetics, Clinical Genetics, and Quantitative Genetics.
By the end of the course, participants will be able to:
- Analyse the use of GWAS and PRS methods in investigating the genetic basis of disease aetiology.
- Describe how PRS is used to determine complex disease genetic risk.
- Perform key steps in PRS analysis using standard methodologies and tools.
- Utilise appropriate tools and software to analyse global genomic datasets from diverse and admixed populations.
- Evaluate and interpret results generated from PRS analyses.
- Customise data visualisations to effectively present PRS analysis results.
The course will run over five and a half days (Sunday to Friday) and will include a combination of lectures, tutorials, computational practicals, and special guest seminars from leading experts in the field. Participants will have multiple opportunities to engage with the training team in a one-to-one setting, as well as to interact with other attendees throughout the week. This approach is designed to foster a supportive, collegiate, and interactive environment, maximising learning for all participants.
The course will begin with an introduction to Polygenic Risk Scores (PRS), providing a solid foundation before progressing to more advanced topics. The week will conclude with a mini research project, carried out in groups of 4–5 participants. This project will enable attendees to apply their PRS knowledge and skills in a practical, real-time setting.
- Introduction to PRS: Genome-Wide Association Studies (GWAS) for PRS, calculating PRS, running PRS software, interpreting PRS results
- Advanced PRS Topics: pathway PRS, PRS to detect rare variants
- PRS in Diverse Ancestries: the PRS portability problem, methods for addressing PRS portability issues, PRS for diverse and admixed population samples
Course Instructors
- Itunuoluwa Isewon, Covenant University, Nigeria
- Conrad Iyegbe, Icahn School of Medicine at Mount Sinai
- Segun Fatumo, Queen Mary University of London and MRC Uganda
Wellcome Connecting Science Team
- Michelle Bishop, Associate Director of Learning and Training at Wellcome Connecting Science
- Alice Matimba, Head of Training and Global Capacity
- Mel Sharpe, Systems and Processes Manager
- Isabela Malta, Assistant Overseas Courses Manager
- Vaishnavi Vikas Gangadhar, Informatics Technical Officer
The course data are free to reuse and adapt with appropriate attribution. All course data in these repositories are licensed under the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
Each course landing page is assigned a DOI via Zenodo, providing a stable and citable reference. These DOIs can be found on the respective course landing pages and can be included in CVs or research publications, offering a professional record of the course contributions.
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