Assessing topological congruence among concatenation-based phylogenomic approaches in empirical datasets

Abstract

Assessing the effect of methodological decisions on the resulting hypotheses is critical in phylogenetics. Recent studies have focused on evaluating how model selection, orthology definition and confounding factors affect phylogenomic results. Here, we compare the results of three concatenated phylogenetic methods (Maximum Likelihood, ML; Bayesian Inference, BI; Maximum Parsimony, MP) in 157 empirical phylogenomic datasets. The resulting trees were very similar, with 96.7% of all nodes shared between BI and ML (90.6% for ML-MP and 89.1% for BI-MP). Differing nodes were predominantly those of lower support. The main conclusions of most of the studies agreed for the three phylogenetic methods and the discordance involved nodes considered as recalcitrant problems in systematics. The differences between methods were proportionally larger in datasets that analyze the relationships at higher taxonomic levels (particularly phyla and kingdoms), and independent of the number of characters included in the datasets. Note: a spanish version of this article is available in the Supplementary material (Supplementary material online).