Introduction to the statistical analysis of genome-wide association studies
Monday 4 July - Friday 8 July 2016
Duration: 5 Days
Organising department: Genomics of Common Disease
Location: Hammersmith Campus, London, UK
Course fee: Academic £650, non-academic £1050
Course leader: Inga Prokopenko
The course will enable human geneticists to analyse their large-scale genetic data using standard analytical approaches and freely available software tools. The course will cover statistical background for association studies; primer on scripting in the most frequently used computational environments, design and analysis of such studies, interpretation of the results. Each topic will be covered by a lecture, followed by a practical exercise, which will include use of the state-of-art software tools and example datasets.
At the end of the course participants will be able to undertake quality control, imputation and analysis of genome-wide data using standard statistical approaches and software tools. Meta-analysis of genome-wide association studies and analysis of rare variants will also be among their skills. They will be able to evaluate critically the results of association analysis and visualise them. They will know the requirements to the study design and findings for publications in peer-reviewed journals.
Attendance fee: £650/£1050 (pounds sterling, academic/non-academic rate) to include course registration fee, lunch, 5 nights’ accommodation (extra nights can be booked at own expense). Payment information will be provided to applicants after their registration has been verified.
The 2016 course is now closed. We can regretfully no longer accept any new applications but we aim to organise a new course around the same time next year. Details of future courses will be published here as well as via ESHG and other websites in due course. If you register your interest by emailing firstname.lastname@example.org we will inform you as soon as the new course opens for applications.
Organising Committee: Prof Philippe Froguel, Dr Inga Prokopenko, Dr Nick Henriquez, Mrs Patricia Murphy