A Statistical Test for Clades in Phylogenies

TL;DR

This paper introduces a statistical test based on SPR neighbors to evaluate the likelihood of phylogenetic trees, offering a faster and informative alternative for assessing tree accuracy compared to traditional methods.

Contribution

It proposes a novel SPR-based likelihood test for phylogenetic trees, demonstrating its effectiveness and efficiency through simulation studies.

Findings

SPR tests are informative for phylogenetic accuracy

The tests are reasonably fast compared to ML tree searches

SPR tests can identify potential inaccuracies in inferred topologies

Abstract

We investigated testing the likelihood of a phylogenetic tree by comparison to its subtree pruning and regrafting (SPR) neighbors, with or without re-optimizing branch lengths. This is inspired by aspects of Bayesian significance tests, and the use of SPRs for heuristically finding maximum likelihood trees. Through a number of simulations with the Jukes-Cantor model on various topologies, it is observed that the SPR tests are informative, and reasonably fast compared to searching for the maximum likelihood tree. This suggests that the SPR tests would be a useful addition to the suite of existing statistical tests, for identifying potential inaccuracies of inferred topologies.