Performance of Matrix Representation with Parsimony for Inferring Species from Gene Trees

Phylogenomic datasets often contain sequence alignments on different subsets of taxa for different genes. A major goal of phylogenetics is often to combine estimated gene trees from many loci into an overall estimate of a species tree. When data are missing for some combinations of genes and taxa, supertree methods can be used to combine gene trees on different subsets of taxa into an overall tree. However, studies of the performance of supertree methods when gene tree conflict is due to incomplete lineage sorting are needed to understand their statistical properties in this setting. We find that Matrix Representation with Parsimony (MRP), the most commonly used supertree method, can in many cases infer the species tree in spite of high levels of conflict in the input gene trees. However, for some species trees with short branches, MRP can be increasingly likely to return a tree other than the species tree as the number of loci increases. In some cases, deleting taxa at random or using estimated (rather than known) gene trees can either improve or hinder MRP for recovering the species tree. Although MRP is able to handle large amounts of conflict in the input gene trees, MRP is not statistically consistent for estimating species trees when gene trees arise under the multispecies coalescent model. However, triplet MRP is statistically consistent in this setting.