title: Joint inference of population assignment and demographic history.
abstract: A new approach to assigning individuals to populations using genetic data is described. Most existing methods work by maximizing Hardy-Weinberg and linkage equilibrium within populations, neither of which will apply for many demographic histories. By including a demographic model, within a likelihood framework based on coalescent theory, we can jointly study demographic history and population assignment. Genealogies and population assignments are sampled from a posterior distribution using a general isolation-with-migration model for multiple populations. A measure of partition distance between assignments facilitates not only the summary of a posterior sample of assignments, but also the estimation of the posterior density for the demographic history. It is shown that joint estimates of assignment and demographic history are possible, including estimation of population phylogeny for samples from three populations. The new method is compared to results of a widely used assignment method, using simulated and published empirical data sets.
authors.affiliation: Department of Genetics, Rutgers University, Piscataway, New Jersey 08846, USA.
authors.forename: Sang Chul
authors.initials: SC
authors.lastname: Choi
authors.forename: Jody
authors.initials: J
authors.lastname: Hey
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D005828:Genetics, Population / Q000379:methods*; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D010802:Phylogeny; D011156:Population Density; D011157:Population Dynamics