Genetic Analysis of Population-based Association Studies

2–6 September 2024

Wellcome Genome Campus, UK

Learn the latest statistical methods and software for analysis of genetic association studies


This advanced course aims to give researchers involved in genetic disease studies a firm grounding in the use of the latest statistical methods and software for analysis of genetic association studies. This includes both small-scale disease-specific studies and large-scale collaborative projects including those that can be used for analysis of multiple complex traits such as UK Biobank.

The course will cover both theoretical and practical aspects of the design and analysis of such studies. Each topic will include a lecture followed by a practical session in which state-of-the-art statistical software will be applied to relevant datasets. The practical sessions will illustrate the ideas presented in the lectures. All the software used will be freely available so that skills learned can be applied after the course and, for the course, will be pre-installed on machines in the training room.

The programme will also include seminars from internationally renowned researchers from the field of complex disease genetics, along with opportunities for participants to discuss their own research projects with course instructors and with each other.


The programme will include lecture and computer-based practical sessions covering the following topics:

Introduction to genetic association studies

  • Overview and history of genetic association studies leading up to and including genome-wide association studies

Basic association analysis and meta-analysis

  • Single marker association tests (frequentist and Bayesian approaches) 
  • Calculation of odds ratios and relative risks 
  • Logistic regression 
  • Meta-analysis (fixed- and random-effects)

Quality control and population structure

  • Data quality control procedures to avoid the generation of spurious false positives in association studies 
  • The confounding effects of population structure on association studies and methods for protecting against these effects 
  • Multivariate (principal components) and linear mixed modelling approaches to adjust for population substructure and relatedness in genome-wide association studies

Haplotype estimation and genotype imputation

  • Methods for genotype imputation using publicly available reference panels 
  • Pre-phasing of haplotypes and imputation based on these inferred haplotypes 
  • Frequentist and Bayesian methods of testing association at imputed SNPs and indels 
  • Quality control for imputed SNPs 
  • Meta-analysis using imputed data


  • Methods to identify distinct association signals
  • Fine-mapping causal variants and construction of credible sets
  • Leveraging diverse populations for fine-mapping through multi-ancestry meta-analysis

Analysis of rare variants

  • Methods for analysing rare variants from re-sequencing, genotyping and imputation studies via “collapsing approaches”
  • Burden and dispersion tests of association

Mendelian randomisation

  • Concepts behind using genetic variants for causal inference in epidemiology
  • Descriptions of the assumptions, limitations and sensitivity analyses of Mendelian randomisation
  • Practical session to apply the above and reproduce examples from the literature 

Introduction to post-GWAS interrogation

  • Approaches to integrate genome-wide association signals with multi-omics to understand disease biology

Practical Sessions
Lectures are followed by practical sessions using realistic datasets so that students learn how to apply the theory. Students will use a variety of computer programs during the course including: IMPUTE2, SHAPEIT2, SNPTEST2, META, GCTA, FaST-LMM, PLINK, SAIGE

Learning outcomes
On completion of the course, participants can expect to: 

  • Understand the general principles, assumptions and basic techniques used in genetic association studies 
  • Read and comprehend scientific articles that present results from candidate-gene and genome-wide association studies 
  • Analyse genetic data arising from candidate-gene and genome-wide association studies, (including quality control checks, association testing between genotype and phenotype, and post-association fine-mapping of implicated loci to point to likely causal variants, genes and pathways) 
  • Perform imputation of variants that have not been directly genotyped, using information from genotyped genetic variants 
  • Perform analysis of common and rare variants, accounting for population structure and family data

Instructors and speakers

Course instructors

Svetlana Cherlin
Newcastle University, UK

Heather Cordell
Newcastle University, UK

Gibran Hemani
University of Bristol, UK

Andrew Morris
University of Manchester, UK

Gisela Orozco
University of Manchester, UK

Guest Speakers

Gosia Trynka:
Wellcome Sanger Institute, UK

Frank Dudbridge
Professor of Statistical Genetics, Genetic Epidemiology Research Group, University of Leicester UK

How to apply


The course is open to scientists and clinicians/healthcare professionals engaged in relevant research. To ensure participants benefit fully from the course, applications should include clear evidence of the following existing knowledge and experience:

  • A strong quantitative background (including some familiarity with statistics, mathematics or bioinformatics).
  • A reasonable level of computer literacy.
  • A basic knowledge and understanding of genetics (both molecular genetics and concepts of inheritance/heritability).

How to Apply

Please click the Apply button above to begin the online application process. Places are limited and will be awarded on merit. If you have any problems with the online application process, please contact us.

Please note: Applications must be supported by a recommendation from a scientific or clinical sponsor (e.g. supervisor, line manager or head of department). Applicants must ensure that their sponsor provides this supporting statement by the application deadline as a pdf document and it is uploaded onto the registration system within their application. Applications without a supporting statement cannot be considered.

Travel visas

Successful applicants will be provided with a support letter for their visa application, if required.

Please visit the following websites for further information on visiting the UK:


*Course fee 820 This is a residential course and the fee includes all accommodation and meals.

*The course fee is subsidised by the Wellcome Connecting Science Courses and Conferences team, and applies to non-commercial applicants. Please contact us for the commercial fee.


Limited bursaries are available (up to 50% reduction on the course fee) and are awarded on merit. If you would like to apply for a bursary, please complete the bursary section of the online application form.

Where there are many bursary applications, the selection committee may issue smaller amounts.

Bursaries can be applied for as part of the course application form. Applicants will be notified of a bursary award along with their place on the course, usually within one month of the application deadline. The decision of the selection committee is final.

Please note that both the applicant and sponsor are required to provide a justification for the bursary as part of the application.

Additional funding opportunities
Visit our support page for additional financial support currently available.

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Feedback from the 2023 course:

In my opinion, every part of the course, including the demonstrators, was truly one-of-a-kind. Personally, I found this course to be perfect in every way, without any flaws whatsoever.

“I’m very grateful to have been able to take part in these courses. The different subjects were dealt with clearly, the message was adapted to the language level and also different backgrounds. I’m very satisfied to have learnt all these things. and I’m looking forward to applying them.”

My expectations were exceeded with respect to the social and holistic support and opportunities to network and excellent catering

“The depth of explanation and variability of speakers/topics exceeded the expected.”


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