Time:
Monday 3 November 2025, at 8:30 - 17:00
Location:
Aarhus University, Universitetsbyen 81, 8000 Aarhus
Builiding 1873 room K20
Registration fee:
DKK 150 incl. VAT
Registration deadline:
Monday 20 October 2025
Seats are limited
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.
Participants are expected to have experience with genetic data analysis, as well as basic knowledge of linear algebra, probability distributions, and coding in R.
Jian Zeng (University of Queensland, Brisbane, Australia)
Peter Sørensen (Aarhus University)
Palle D Rohde (Aalborg University)
Bjarni J Vilhjálmsson (Aarhus University)
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