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Domelevo Entfellner, J.-B.

Publications and source records attributed to Domelevo Entfellner, J.-B..

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Distribution and asymptotic behavior of the phylogenetic transfer distance

The transfer distance (TD) was introduced in the classification framework and studied in the context of phylogenetic tree matching. Recently, Lemoine et al. (2018) showed that TD can be a powerful tool to assess the branch support of phylogenies with large data sets, thus providing a relevant alternative to Felsensteins bootstrap. This distance allows a reference branch {beta} in a reference tree [T] to be compared to a branch b from another tree T, both on the same set of n taxa. The TD between these branches is the number of taxa that must be transferred from one side of b to the other in order to obtain {beta}. By taking the minimum TD from {beta} to all branches in T we define the transfer index, denoted by{phi} ({beta}, T), measuring the degree of agreement of {beta} with T. Let us consider a reference branch {beta} having p tips on its light side and define the transfer support (TS) as 1 -{phi} ({beta}, T)/(p - 1). The aim of this article is to provide evidence that p 1 is a meaningful normalization constant in the definition of TS, and measure the statistical significance of TS, assuming that {beta} is compared to a tree T drawn according to a null model. We obtain several results that shed light on these questions in a number of settings. In particular, we study the asymptotic behavior of TS when n tends to {infty}, and fully characterize the distribution of{phi} when T is a caterpillar tree.

evolutionary biology

Boosting Felsenstein Phylogenetic Bootstrap

Felsensteins article describing the application of the bootstrap to evolutionary trees, is one of the most cited papers of all time. That statistical method, 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 with hundreds or thousands of taxa are becoming routine. In that framework, Felsensteins bootstrap tends to yield very low supports, especially on deep branches. We propose a revised version, in which the presence of inferred branches in replications is measured using a gradual \"transfer\" distance, as opposed to the original version using a binary presence/absence index. The resulting supports are higher, while not inducing falsely supported branches. Our method is applied to large simulation, mammal and HIV datasets, for which it reveals the phylogenetic signal, while Felsensteins bootstrap fails to do so.

evolutionary biology