Workshop: Bayesian Methods for Complex Trait Genomic Analysis


Time:
Friday 9 January 2026, at 8:30 - 17:00

Location:
Seminar rooms Big Data Institute 
Old Road Campus, Roosevelt Drive Oxford OX3 7LF 

Registration deadline:
Friday 12 December 2025

Registration fee:
Registration is free. 

Please visit the course website for more information and link to registration site.



This SMARTbiomed workshop introduces current Bayesian methods for genomic analysis using genome-wide association study (GWAS) data. Participants will gain a foundation in Bayesian modelling, including the principles of Bayesian inference and parameter estimation. Building on this, we will cover widely used Bayesian approaches for estimating genetic architecture, predicting polygenic risk scores, and identifying likely causal variants (genetic fine-mapping) of complex traits and diseases.

The workshop emphasizes hands-on practice with 30-60 minute practical session following lectures to consolidate learning. Practical exercises will be conducted in R or Rstudio. The workshop is designed to help participants understand Bayesian methods conceptually, interpret results effectively, and gain insights into how new Bayesian methods can be developed.

Prerequisites:

Participants are expected to have experience with genetic data analysis, as well as basic knowledge of linear algebra, probability distributions, and coding in R.

Instructors:

Jian Zeng (University of Queensland, Brisbane, Australia)
Peter Sørensen (Aarhus University)
Palle D Rohde (Aalborg University)
Bjarni J Vilhjálmsson (Aarhus University)

Schedule:

8:30 - 8:45: Arrival and coffee.

8:45 – 9:45: Introduction to Bayesian linear regression, posterior inference and Markov chain Monte Carlo (MCMC)

9:45- 10:15: Coffee break

10:15-11:00: Bayesian estimation of genetic architecture for complex traits

11:00 – 12:00: Practical exercise: estimating SNP-based heritability, polygenicity and selection signature using SBayesS and LDpred2-auto

12:00 – 12:45: Lunch  (provided)

12:45 – 13:30: Bayesian prediction of polygenic risk scores for common diseases

13:30 – 14:00: Bayesian approaches for genetic fine-mapping

14:00 – 14:45: Practical exercise: polygenic prediction and fine-mapping using SBayesRC

14:45 – 15:15: Coffee and cake

15:15 – 16:00: Bayesian gene-set analyses

16:00 – 16:30: Practical exercise: Bayesian gene-set analyses

16:30 – 17:00: Wrap-up and Discussion