Mixed-up trees: the structure of phylogenetic mixtures

TL;DR

This paper introduces geometric and combinatorial methods to analyze phylogenetic mixture models, revealing the structure, identifiability, and prevalence of non-identifiable mixtures in evolutionary tree models.

Contribution

It develops a geometric framework for understanding phylogenetic mixture distributions, extends identifiability results, and addresses open questions about mixture models on larger trees.

Findings

Mixture distributions form convex polytopes with computable dimensions.

A simple criterion for mixture mimicry of resolved quartet trees.

Quantification of how common non-identifiable mixtures are under the CFN model.

Abstract

In this paper we apply new geometric and combinatorial methods to the study of phylogenetic mixtures. The focus of the geometric approach is to describe the geometry of phylogenetic mixture distributions for the two state random cluster model, which is a generalization of the two state symmetric (CFN) model. In particular, we show that the set of mixture distributions forms a convex polytope and we calculate its dimension; corollaries include a simple criterion for when a mixture of branch lengths on the star tree can mimic the site pattern frequency vector of a resolved quartet tree. Furthermore, by computing volumes of polytopes we can clarify how ``common'' non-identifiable mixtures are under the CFN model. We also present a new combinatorial result which extends any identifiability result for a specific pair of trees of size six to arbitrary pairs of trees. Next we present a positive result showing identifiability of rates-across-sites models. Finally, we answer a question raised in a previous paper concerning ``mixed branch repulsion'' on trees larger than quartet trees under the CFN model.