Renewing Felsenstein’s phylogenetic bootstrap in the era of big data

F. Lemoine, J.-B. Domelevo Entfellner, E. Wilkinson, D. Correia, M. Dávila Felipe, T. Oliveira and O. Gascuel ()
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F. Lemoine: Unité Bioinformatique Evolutive, C3BI USR 3756, Institut Pasteur & CNRS
J.-B. Domelevo Entfellner: University of the Western Cape
E. Wilkinson: School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal
D. Correia: Unité Bioinformatique Evolutive, C3BI USR 3756, Institut Pasteur & CNRS
M. Dávila Felipe: Unité Bioinformatique Evolutive, C3BI USR 3756, Institut Pasteur & CNRS
T. Oliveira: School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal
O. Gascuel: Unité Bioinformatique Evolutive, C3BI USR 3756, Institut Pasteur & CNRS

Nature, 2018, vol. 556, issue 7702, 452-456

Abstract: Abstract Felsenstein’s application of the bootstrap method to evolutionary trees is one of the most cited scientific papers of all time. The bootstrap method, which is based on resampling and replications, is used extensively to assess the robustness of phylogenetic inferences. However, increasing numbers of sequences are now available for a wide variety of species, and phylogenies based on hundreds or thousands of taxa are becoming routine. With phylogenies of this size Felsenstein’s bootstrap tends to yield very low supports, especially on deep branches. Here we propose a new version of the phylogenetic bootstrap in which the presence of inferred branches in replications is measured using a gradual ‘transfer’ distance rather than the binary presence or absence index used in Felsenstein’s original version. The resulting supports are higher and do not induce falsely supported branches. The application of our method to large mammal, HIV and simulated datasets reveals their phylogenetic signals, whereas Felsenstein’s bootstrap fails to do so.

Date: 2018
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DOI: 10.1038/s41586-018-0043-0

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