The robustness of two phylogenetic methods: four-taxon simulations reveal a slight superiority of maximum likelihood over neighbor joining

Abstract

The robustness (sensitivity to violation of assumptions) of the maximum-likelihood and neighbor-joining methods was examined using simulation. Maximum likelihood and neighbor joining were implemented with Jukes-Cantor, Kimura, and gamma models of DNA substitution. Simulations were performed in which the assumptions of the methods were violated to varying degrees on three model four-taxon trees. The performance of the methods was evaluated with respect to ability to correctly estimate the unrooted four-taxon tree. Maximum likelihood outperformed neighbor joining in 29 of the 36 cases in which the assumptions of both methods were satisfied. In 133 of 180 of the simulations in which the assumptions of the maximum-likelihood and neighbor-joining methods were violated, maximum likelihood outperformed neighbor joining. These results are consistent with a general superiority of maximum likelihood over neighbor joining under comparable conditions. They extend and clarify an earlier study that found an advantage for neighbor joining over maximum likelihood for gamma-distributed mutation rates.