A Robust ANOVA Approach to Estimating a Phylogeny from Multiple Genes

Abstract

In this article, we address the issue of estimating the phylogenetic tree based on sequence data across a set of genes. Recognizing that the individual gene trees may not all share the same evolutionary history due to lateral gene transfer or differences in rates of evolution for instance, we develop a robust algorithm for tree estimation based on pairwise distances computed gene by gene. A robust analysis of variance (ANOVA) is used to combine the distances across all genes giving a summary distance for all genes. The tree can then be constructed using any distance method such as BIONJ. Using the weights from the robust ANOVA, we can then identify the outlying genes and taxa for further examination. As the method is based on distances, computation is much faster than maximum likelihood on the concatenated genes. It is also very straightforward to carry out a bootstrap analysis using standard methods for regression models. We test our methods in a comprehensive simulation study and apply them to three data sets recently analyzed in the literature.

Keywords: analysis of variance; multigene analysis; outlier genes; phylogenetic trees; robust regression.