Pruning Rogue Taxa Improves Phylogenetic Accuracy: An Efficient Algorithm and Webservice

By Andre J. Aberer, Denis Krompass, Alexandros Stamatakis. Systematic Biology, 2012

367 citations recorded by the source corpus.

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.

Subfields: Ecological Modeling, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1d4fbb70d748d35c0a9de12f9fd8fe3d87478f49

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Citations in the corpus

TreeShrink: fast and accurate detection of outlier long branches in collections of phylogenetic trees (2018, methodology): “While the goals of RTR are somewhat different from ours, we also compare our method with RogueNaRok [16], which defines a rogue taxon as one that has unstable positions in replicate bootstrap runs.”
GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy (2021, methodology): “The quality of MAGs is an ongoing concern and we are evaluating methods for decontaminating MAGs (39) and identifying and removing MAGs that may contribute to phylogenetic instability (40).”
Renewing Felsenstein’s Phylogenetic Bootstrap in the Era of Big Data (2018, methodology): “Protein sequences were evolved along this tree using INDELible 49 , which was launched with options and parameter values derived from the PhyML analysis, and similar to the experiments conducted by Aberer et al. 24 to assess the accuracy of rogue-taxon detection: • Length of the root sequence: 250 A”
A new phylogeny of ichthyosaurs (Reptilia: Diapsida) (2019, background): “by pruning) will often provide an increase in resolution and, potentially, accuracy (Pol & Escapa 2009; Aberer et al. 2013).”