Phylogenetic Least Squares Inference Without Distances

• Activity Number: 453
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
• Sponsor: WNAR
• Author(s): Peter Chi*+ and Vladimir Minin
• Companies: Cal Poly, San Luis Obispo and University of Washington
• Keywords: phylogenetics ; least squares ; DNA sequence

Abstract

Least squares phylogenetic inference is typically based a DNA sequence alignment. Fundamentally, an analysis proceeds by first estimating the distance matrix, and then finding the phylogeny that is in the highest agreement with this estimated distance matrix. This inherently makes least squares phylogenetic inference a two-stage procedure, and since the inference is based merely upon a summary statistic (the estimated distance matrix) of the actual data (the DNA sequence alignment), the potential loss of information through this procedure is a concern. In this work, we propose a modification of least squares phylogenetic inference, in which we use a new loss function that considers sequence data simultaneously with candidate phylogenies. We show that this approach leads to substantial gains in the estimation procedure, in terms of bias, variance and mean squared error. Furthermore, our new loss function allows for a natural consideration of rate heterogeneity in the sequence data, which leads to an improvement of inference in the presence of such rate heterogeneity.