title: Pruning rogue taxa improves phylogenetic accuracy: an efficient algorithm and webservice.
abstract: The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees.
authors.affiliation: Exelixis Laboratory, Scientific Computing Group, Heidelberg Institute for Theoretical Studies (HITS gGmbH), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg, Germany. andre.aberer@h-its.org
authors.forename: Andre J
authors.initials: AJ
authors.lastname: Aberer
authors.forename: Denis
authors.initials: D
authors.lastname: Krompass
authors.forename: Alexandros
authors.initials: A
authors.lastname: Stamatakis
mesh_terms: D000465:Algorithms; D002965:Classification / Q000379:methods*; D003198:Computer Simulation; D020407:Internet; D010802:Phylogeny; D015203:Reproducibility of Results; D012984:Software