Estimating population divergence time and phylogeny from single-nucleotide polymorphisms data with outgroup ascertainment bias.
The inference of population divergence times and branching patterns is of fundamental importance in many population genetic analyses. Many methods have been developed for estimating population divergence times, and recently, there has been particular attention towards genome-wide single-nucleotide polymorphisms (SNP) data. However, most SNP data have been affected by an ascertainment bias caused by the SNP selection and discovery protocols. Here, we present a modification of an existing maximum likelihood method that will allow approximately unbiased inferences when ascertainment is based on a set of outgroup populations. We also present a method for estimating trees from the asymmetric dissimilarity measures arising from pairwise divergence time estimation in population genetics. We evaluate the methods by simulations and by applying them to a large SNP data set of seven East Asian populations.
Department of Integrative Biology, University of California, 3060 VLSB, Berkeley, CA 94720, USA. ywang@berkeley.edu
Yong
Y
Wang
Rasmus
R
Nielsen
D015982:Bias; D003198:Computer Simulation; D019143:Evolution, Molecular; D051456:Gene Flow; D005828:Genetics, Population / Q000379:methods*; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide