Workshop on computer simulations for population genomics

To introduce key concepts and methods in population genomics through discussions and hands-on computer simulations and to develop practical skills in computational modelling, simulation design, and data analysis.

Master, PhD students and researchers who want to expand their skills in computational aspects of population genetics research.

By the end of the workshop, participants will be able to: develop and implement demographic simulation models using the slendr framework and tree-sequence methodology; apply population genomic statistics to investigate evolutionary and demographic processes; interpret and evaluate limitations of commonly used population genetic metrics under different simulated scenarios; design and execute simulation-based analysis pipelines, including benchmarking and exploratory workflows.

Martin Petr

Topic	Credit	Lectors
1. Extensive introduction to the R package slendr as a powerful, modern framework to program demographic models, simulate genomic data, and compute a wide range of population genomic statistics from such simulations, all revolving around the tree-sequence a core genomic data structure.	5	Martin Petr
2. Practice programming slendr modeling and analysis pipelines by simulation-based exploration of fundamental concepts in population genetics, such as effective population size, nucleotide diversity, FST, Tajima’s D, or the allele frequency spectrum, as well as investigating the inner workings of f-statistics (f3, f4, f4-ratio).	5	Martin Petr
3. The behavior and limitations of these metrics across various relevant simulated scenarios to practice skills in programming simulations and statistical workflows with slendr, while learning general strategies for applying this methodology to other modeling problems.	5	Martin Petr
4. the ideas behind methods for dating admixture events and other haplotype-based methods, and conclude with several small “case study projects” focused on developing complete benchmarking and exploratory pipelines inspired by practical examples from published research, intended to inspire programming custom simulations during self-driven practice sessions.	5	Martin Petr
5. Development and implementation of demographic simulation models using the slendr framework and tree-sequence methodology. Application of population genomic statistical methods to investigate evolutionary and demographic processes, as well as interpretation and evaluation of the behaviour and limitations of commonly used population genetic statistics under different simulated scenarios.	5	Martin Petr
6. Independent work	1

Natural sciences, mathematics and statistics n.e.c.

LTGI.TK.007

Participation in classroom learning 80%; completion of the course tasks.

non-differentiated (pass, fail, not present)

Eristamata

Participation in classroom learning 80%; completion of the course tasks.