Genealogies and inference for populations with highly skewed offspring distributions under further evolutionary forces

• Applicants: Professor Dr. Matthias Birkner; Professor Dr. Jochen Blath
• Subject Area: Mathematics
• Term: from 2012 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 221571119

Multiple merger coalescent modeling and analysis has up to now been mainly focused on neutral, haploid, single-locus set-ups. The central aim of this project is to develop the stochastic models, theoretical results and inference methods required to effectively describe and analyse the observed patterns of genetic variation in sequence data in real populations with skewed offspring distributions under the influence of further evolutionary forces, especially recombination, selection and population structure; in other words, the systematic development of the basics of a `mathematical population genetics for highly variableoffspring distributions'. Given recent progress in DNA sequencing technology, and insight in the limitations of inference methods based single locus set-ups, particular emphasis will be put on realistic diploid multi-locus models and the corresponding statistical machinery for data analysis.

• DFG Programme: Priority Programmes
• Subproject of: SPP 1590: Probabilistic Structures in Evolution
• International Connection: Iceland
• Cooperation Partner: Professor Dr. Einar Arnason