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Shifted stochastic processes evolving on trees : application to models of adaptive evolution on phylogenies.

Abstract : This project is aiming at taking a step further in the process of systematic statistical modeling that is occurring in the field of comparative ecology. A way to account for correlations between quantitative traits of a set of sampled species due to common evolutionary histories is to see the current state as the result of a stochastic process running on a phylogenetic tree. Due to environmental changes, some ecological niches can shift in time, inducing a shift in the parameters values of the stochastic process modeling trait evolution. Because we only measure the value of the process at a single time point, for extant species, some evolutionary scenarios cannot be reconstructed, or have some identifiability issues, that we carefully study. We construct an incomplete-data model for statistical inference, along with an efficient implementation. We perform an automatic shift detection, and choose the number of shifts thanks to a model selection procedure, specifically crafted to handle the special structure of the problem. Theoretical guaranties are derived in some special cases. A phylogenetic tree cannot take into account hybridization or horizontal gene transfer events, that are widely spread in some groups of species, such as plants or bacterial organisms. A phylogenetic network can be used to deal with these events. We develop a new model of trait evolution on this kind of structure, that takes non-linear effects such as heterosis into account. Heterosis, or hybrid vigor or depression, is a well studied effect, that happens when a hybrid species has a trait value that is outside of the range of its two parents.
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Submitted on : Monday, November 6, 2017 - 4:06:08 PM
Last modification on : Friday, August 5, 2022 - 2:38:10 PM


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  • HAL Id : tel-01629648, version 1


Paul Bastide. Shifted stochastic processes evolving on trees : application to models of adaptive evolution on phylogenies.. Statistics [math.ST]. Université Paris Saclay (COmUE), 2017. English. ⟨NNT : 2017SACLS370⟩. ⟨tel-01629648⟩



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