Genealogical traits of spatial models in Population Genetics

• Applicant: Johannes Wirtz, Ph.D.
• Subject Area: Bioinformatics and Theoretical Biology ; Mathematics
• Term: from 2020 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 448871728

In the analysis of genomic Data, methods that allow for the treatment of geo-referenced data (i.e., the inclusion of information on sampling locations), are of increasing importance. For example, this is an important feature in virology, where the geographical origin of data is very important in the analysis, and generally in cases where the evolutionary history of a population is heavily influenced by geographical traits of its habitat. One approach to model populations in space is given by the spatial Lambda-Fleming-Viot-Process. This process exhibits favorable probabilistic traits and is considered to be in several ways superior to other approaches of Population Genetics including a spatial component. However, so far little is known about the statistical properties of sample data generated under the assumption of this process, in particular with respect to sample genealogies. The primary aim of this project is to provide insight on some key features of the process. Special focus will be placed on the derivation of coalescence rates and probabilities. Following up on that, the goal will be an approximate description of the probability space of sample genealogies, given the present locations of sample members. These results will be utilized to perform Bayesian Statistics. In particular, an implementation in software shall be provided, which is capable of estimating population-genetical parameters from data by Markov-Chain Monte-Carlo simulation. Since the advantages of this approach result from the use of prior knowledge on statistical properties of the underlying model, the results from the first part of the project will provide a substantial improvement to the existing methods. Finally, it is planned to apply these improved methods to data from Influenza and Rice Yellow-Mottle viruses.

• DFG Programme: WBP Fellowship
• International Connection: France
• Host: Professor Dr. Stephane Guindon