UW Aquatic & Fishery Sciences Quantitative Seminar

Vladimir Minin

UW, Department of Statistics

Bayesian inference of population dynamics from genetic data

Changes in population size influence genetic diversity of the population and, as a result, leave imprints in genomes of individuals in the population. Often, one is interested in an inverse problem of reconstructing past population dynamics from genetic data. In this talk, I will review methods for estimating population dynamics using the coalescent, a stochastic process that generates genealogies connecting randomly sampled individuals from the population of interest. These genealogies serve as a glue between the population demographic history and genetic sequences and allow for likelihood-based inference of population dynamics directly from sequence data. I will give case studies from my own work on hepatitis C and human influenza viruses, but will also show examples, drawn from the literature, of how the coalescent framework is used to uncover demographic history of marine populations.