Point estimates in phylogenetic reconstructions

TL;DR

This paper introduces geometric-based statistical summaries like mean, median, and variance for Bayesian phylogenetic trees, improving the interpretation of posterior distributions especially when multiple topologies are present.

Contribution

It defines and computes geometric summary statistics for phylogenetic trees, addressing the lack of sound averaging methods in Bayesian phylogenetics.

Findings

Posterior mean balances contributions from different topologies.

Geometric summaries outperform consensus trees in complex cases.

Sound averaging improves phylogenetic reconstruction accuracy.

Abstract

Motivation: The construction of statistics for summarizing posterior samples returned by a Bayesian phylogenetic study has so far been hindered by the poor geometric insights available into the space of phylogenetic trees, and ad hoc methods such as the derivation of a consensus tree makeup for the ill-definition of the usual concepts of posterior mean, while bootstrap methods mitigate the absence of a sound concept of variance. Yielding satisfactory results with sufficiently concentrated posterior distributions, such methods fall short of providing a faithful summary of posterior distributions if the data do not offer compelling evidence for a single topology. Results: Building upon previous work of Billera et al., summary statistics such as sample mean, median and variance are defined as the geometric median, Fr\'echet mean and variance, respectively. Their computation is enabled by recently published works, and embeds an algorithm for computing shortest paths in the space of trees. Studying the phylogeny of a set of plants, where several tree topologies occur in the posterior sample, the posterior mean balances correctly the contributions from the different topologies, where a consensus tree would be biased. Comparisons of the posterior mean, median and consensus trees with the ground truth using simulated data also reveals the benefits of a sound averaging method when reconstructing phylogenetic trees.