A simulation comparison of phylogeny algorithms under equal and unequal evolutionary rates.

TLDR

The study simulated 5,000 datasets per condition across 50 trees to compare five phylogenetic methods—parsimony, compatibility, maximum likelihood, Fitch‑Margoliash, and neighbor joining—using two distance metrics and bias assessment based on consistency across replicates. When constrained to non‑negative branch lengths, Fitch‑Margoliash and neighbor joining outperformed other methods, with maximum likelihood overall best but sometimes surpassed by distance‑matrix methods on short sequences; parsimony and compatibility suffered from bias and inaccuracy when branch or site rates varied, and all methods displayed errors under rate heterogeneity across sites.

Abstract

Using simulated data, we compared five methods of phylogenetic tree estimation: parsimony, compatibility, maximum likelihood, Fitch-Margoliash, and neighbor joining. For each combination of substitution rates and sequence length, 100 data sets were generated for each of 50 trees, for a total of 5,000 replications per condition. Accuracy was measured by two measures of the distance between the true tree and the estimate of the tree, one measure sensitive to accuracy of branch lengths and the other not. The distance-matrix methods (Fitch-Margoliash and neighbor joining) performed best when they were constrained from estimating negative branch lengths; all comparisons with other methods used this constraint. Parsimony and compatibility had similar results, with compatibility generally inferior; Fitch-Margoliash and neighbor joining had similar results, with neighbor joining generally slightly inferior. Maximum likelihood was the most successful method overall, although for short sequences Fitch-Margoliash and neighbor joining were sometimes better. Bias of the estimates was inferred by measuring whether the independent estimates of a tree for different data sets were closer to the true tree than to each other. Parsimony and compatibility had particular difficulty with inaccuracy and bias when substitution rates varied among different branches. When rates of evolution varied among different sites, all methods showed signs of inaccuracy and bias.