Algorithms for knowledge-enhanced supertrees

Abstract

Supertree algorithms combine smaller phylogenetic trees into a single, comprehensive phylogeny, or supertree. Most supertree problems are NP-hard, and often heuristics identify supertrees with anomalous or unwanted relationships. We introduce knowledge-enhanced supertree problems, which seek an optimal supertree for a collection of input trees that can only be assembled from a set of given, possibly incompatible, phylogenetic relationships. For these problems we introduce efficient algorithms that, in a special setting, also provide exact solutions for the original supertree problems. We describe our algorithms and verify their performance based on the Robinson Foulds (RF) supertree problem. We demonstrate that our algorithms (i) can significantly improve upon estimates of existing RF-heuristics, and (ii) can compute exact RF supertrees with up to 17 taxa. © 2012 Springer-Verlag.