Simultaneous Alignment and Phylogenetic Tree Estimation

Molecular sequences evolve under processes that include substitutions, insertions, and deletions (jointly called "indels"), as well as other mechanisms (e.g., duplications and rearrangements). The inference of the evolutionary history of these sequences has thus been performed in two stages: the first estimates the alignment on the sequences, and the second estimates the tree given that alignment. While such methods seem to work well on relatively small datasets, these two-stage approaches can produce highly incorrect trees and alignments when applied to large datasets, or ones that evolve with many indels. In this talk, I will present a new method, SATe, that my lab has been developing that uses maximum likelihood to estimate the alignment and tree at the same time, and that can be used to analyze datasets with up to 1000 sequences on a desktop in 24 hours. Our study, using both real and simulated data, shows that this method produces much more accurate trees than the current best methods.

Tandy Warnow is Professor of Computer Sciences at the University of Texas at Austin. Her research combines mathematics, computer science, and statistics to develop improved models and algorithms for estimating complex and large-scale evolutionary histories in both biology and historical linguistics. Tandy received her PhD in Mathematics at UC Berkeley under the direction of Gene Lawler, and did postdoctoral training with Simon Tavare and Michael Waterman at USC. She received the National Science Foundation Young Investigator Award in 1994, and the David and Lucile Packard Foundation Award in Science and Engineering in 1996. Tandy is a member of five graduate programs at the University of Texas, including Computer Science; Ecology, Evolution, and Behavior; Molecular and Cellular Biology; Mathematics; and Computational and Applied Mathematics. She is also the director for the multi-disciplinary CIPRES (Cyber-Infrastructure for Phylogenetic Research) Project, currently funded by the NSF under their Information Technology Program.