Abstract
Genome-scale species tree inference is largely restricted to heuristic approaches that use estimated gene trees to reconstruct species-level relationships. Central to these heuristic species tree methods is the assumption that the gene trees are estimated without error. To increase the accuracy of input gene trees used to infer species trees, several techniques have recently been developed for constructing longer "supergenes" that represent sets of loci inferred to share the same genealogical history. While these supergene methods are designed to increase the amount of data for gene tree estimation by concatenating several loci into "supergenes" to increase gene tree accuracy, no formal protocols have been proposed to validate this key "supergene" concatenation step. In a recent study, we developed several supergene validation strategies for assessing the accuracy of a popular supergene method: the so-called "statistical binning" pipeline. In this article, we describe a more generalizable and model-based "supergene validation" protocol for assessing the accuracy of supergenes and supergene methods using model-based tests of phylogenetic congruency. •Supergenes are validated by adopting model-based tests of topological congruence•These model-based procedures out preform non-model based methods for supergene construction•The results of this protocol can be used to assess the overall performance of a supergene method across a phylogenomic dataset.