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Rapidly Computing the Phylogenetic Transfer Index

Authors Jakub Truszkowski , Olivier Gascuel, Krister M. Swenson

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  • 12 pages

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Author Details

Jakub Truszkowski
  • LIRMM, CNRS, Université Montpellier, Montpellier, France
Olivier Gascuel
  • Unité Bioinformatique Evolutive, Département de Biologie Computationnelle, USR 3756, Institut Pasteur et CNRS, Paris, France
  • LIRMM, CNRS, Université Montpellier, Montpellier, France
Krister M. Swenson
  • LIRMM, CNRS, Université Montpellier, Montpellier, France


We would like to thank Jeet Sukuraman for his help with the Dendropy package.

Cite AsGet BibTex

Jakub Truszkowski, Olivier Gascuel, and Krister M. Swenson. Rapidly Computing the Phylogenetic Transfer Index. In 19th International Workshop on Algorithms in Bioinformatics (WABI 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 143, pp. 20:1-20:12, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)


Given trees T and T_o on the same taxon set, the transfer index phi(b,T_o) is the number of taxa that need to be ignored so that the bipartition induced by branch b in T is equal to some bipartition in T_o. Recently, Lemoine et al. [Lemoine et al., 2018] used the transfer index to design a novel bootstrap analysis technique that improves on Felsenstein’s bootstrap on large, noisy data sets. In this work, we propose an algorithm that computes the transfer index for all branches b in T in O(n log^3 n) time, which improves upon the current O(n^2)-time algorithm by Lin, Rajan and Moret [Lin et al., 2012]. Our implementation is able to process pairs of trees with hundreds of thousands of taxa in minutes and considerably speeds up the method of Lemoine et al. on large data sets. We believe our algorithm can be useful for comparing large phylogenies, especially when some taxa are misplaced (e.g. due to horizontal gene transfer, recombination, or reconstruction errors).

Subject Classification

ACM Subject Classification
  • Applied computing → Bioinformatics
  • Theory of computation → Design and analysis of algorithms
  • large phylogenies
  • bootstrap analysis
  • tree comparison
  • data structures on trees


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