Course Bayesian statistics with applications in genomics

The course C295 Applied Bayesian statistics with examples in genomics (previously called “Bayesian statistics with applications in genomics”) is being offered by the Graduate School of Health, Aarhus University, 2026.

Criteria for participation: The course targets computer scientists, bioinformaticians, biologists, or clinicians with a strong drive towards informatics and data analysis. The participants should have a university degree in the above disciplines and/or be postgraduate research fellows (PhD students and research-year medical students).

Requirements for participation: Some experience with programming and scripting languages, preferably R, is strongly recommended. A basic understanding of statistics and probability theory is also recommended.

Aim: To apply Bayesian statistics in the analysis of biological or clinical data.

Learning outcomes: 

• Understand the principles and central concepts of Bayesian statistics
• Be able to translate and formalize simple scientific questions into Bayesian models
• Be able to perform Bayesian statistical analysis in R and Stan
• Understand and apply a range of inference methods

Workload: Ten days: five days of on-premises teaching and workshop (hackathon), and five days of preparation.

Content:

• Bayesian statistics concepts (ideas, priors and posteriors, updating…, MAP and other measures on the posterior)
• Statistical model formalism and specification in R / Stan
• Inference: MAP using grid evaluation; perhaps normal approximations
• More advanced Bayesian stats concepts (posterior predictive value, model selection)
• Inference: MCMC -- basic concepts, implementation of MH sampler on some simple problem, and use in modern inference engines
• Information criteria
• Variational inference techniques
• Comprehensive practical exercises and workshops using R and Stan on data analysis
• Full day hackathon with focus on your own problem and data or locally available data and open problems
• Guest lectures on statistical data analysis, problems in genomics, clinical data analysis

Reading material:

• - Likely: Statistical Rethinking, 2nd edition: https://xcelab.net/rm/statistical-rethinking/

Instructors:  Asso. Prof. Søren Besenbacher and Prof. Jakob Skou Pedersen.

Venue: Aarhus University, Aarhus.

Participation in the course is without cost for:

• PhD students, Health Research Year students from Aarhus University
• PhD students enrolled at partner universities of the Nordoc collaboration
• PhD students from other institutions in the open market agreement for PhD courses

Course dates:

• 02 February 2026 08:30 - 16:30
• 03 February 2026 08:30 - 16:30
• 04 February 2026 08:30 - 16:30
• 18 February 2026 08:30 - 16:30
• 19 February 2026 08:30 - 16:30
• 20 February 2026 08:30 - 16:30