Consistency of Bayesian inference of resolved phylogenetic trees

TL;DR

This paper proves that Bayesian inference of fully-resolved phylogenetic trees is statistically consistent across various models and conditions, supporting its reliability in evolutionary studies.

Contribution

It formally demonstrates the statistical consistency of maximum posterior tree topology in Bayesian phylogenetics under broad conditions, including gene and species tree inference.

Findings

Maximum posterior tree topology is consistent for fully-resolved trees.

Consistency holds across a wide range of branch lengths and priors.

Addresses and confirms Bayesian method reliability in phylogenetics.

Abstract

Bayesian inference is now a leading technique for reconstructing phylogenetic trees from aligned sequence data. In this short note, we formally show that the maximum posterior tree topology provides a statistically consistent estimate of a fully-resolved evolutionary tree under a wide variety of conditions. This includes the inference of gene trees from aligned sequence data across the entire parameter range of branch lengths, and under general conditions on priors in models where the usual `identifiability' conditions hold. We extend this to the inference of species trees from sequence data, where the gene trees constitute `nuisance parameters', as in the program *BEAST. This note also addresses earlier concerns raised in the literature questioning the extent to which statistical consistency for Bayesian methods might hold in general.