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Seminar: Laura Kubatko

Statistics Seminar
March 27, 2014
All Day
209 W. Eighteenth Ave. (EA), Room 170

Title

Species Tree Inference Using Algebraic Statistics

Speaker

Laura Kubatko, The Ohio State University

Abstract

A phylogenetic tree is a graph that displays evolutionary relationships among a collection of present-day species. A fundamental problem in evolutionary biology is the inference of phylogenetic trees given data, such as DNA sequences, for a sample of organisms. Given advances in our ability to collect DNA sequences rapidly and inexpensively, it is becoming increasingly common to have large single nucleotide polymorphism (SNP) data sets available for species-level phylogenetic inference. We use techniques from algebraic statistics to show that the species tree is identifiable from SNP data generated under the coalescent model for speciation. We develop a method based on this result that can be used to estimate the species tree from a sample of SNPs, and we show that the method also works well for multi-locus phylogenomic data. We apply the method to both simulated and empirical genomic data sets.

This is joint work with Dr. Julia Chifman.