Six-state amino acid recoding is not an effective strategy to offset the effects of compositional heterogeneity and saturation in phylogenetic analyses
Six-state amino acid recoding strategies are commonly applied to combat the effects of compositional heterogeneity and substitution saturation in phylogenetic analyses. While these methods have been endorsed from a theoretical perspective, their performance has never been extensively tested. Here, we test the effectiveness of 6-state recoding approaches by comparing the performance of analyses on recoded and non-recoded datasets that have been simulated under gradients of compositional heterogeneity or saturation. In all of our simulation analyses, non-recoding approaches greatly outperformed 6-state recoding approaches. Our results suggest that 6-state recoding strategies are not effective in the face of high saturation. Further, while recoding strategies do buffer the effects of compositional heterogeneity, the loss of information that accompanies 6-state recoding outweighs its benefits, even in the most compositionally heterogeneous datasets. In addition, we evaluate recoding schemes with 9, 12, 15, and 18 states and show that these all outperform 6-state recoding. Our results have important implications for the more than 70 published papers that have incorporated 6-state recoding, many of which have significant bearing on relationships across the tree of life.