Accounting for Calibration Uncertainty: Bayesian Molecular Dating as a “Doubly Intractable” Problem - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier
Article Dans Une Revue Systematic Biology Année : 2018

Accounting for Calibration Uncertainty: Bayesian Molecular Dating as a “Doubly Intractable” Problem

Résumé

This study introduces a new Bayesian technique for molecular dating that explicitly accommodates for uncertainty in the phylogenetic position of calibrated nodes derived from the analysis of fossil data. The proposed approach thus defines an adequate framework for incorporating expert knowledge and/or prior information about the way fossils were collected in the inference of node ages. Although it belongs to the class of “node-dating” approaches, this method shares interesting properties with “tip-dating” techniques. Yet, it alleviates some of the computational and modeling difficulties that hamper tip-dating approaches. The influence of fossil data on the probabilistic distribution of trees is the crux of the matter considered here. More specifically, among all the phylogenies that a tree model (e.g., the birth–death process) generates, only a fraction of them “agree” with the fossil data. Bayesian inference under the new model requires taking this fraction into account. However, evaluating this quantity is difficult in practice. A generic solution to this issue is presented here. The proposed approach relies on a recent statistical technique, the so-called exchange algorithm, dedicated to drawing samples from “doubly intractable” distributions. A small example illustrates the problem of interest and the impact of uncertainty in the placement of calibration constraints in the phylogeny given fossil data. An analysis of land plant sequences and multiple fossils further highlights the pertinence of the proposed approach.
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lirmm-01800299 , version 1 (13-03-2019)

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Stéphane Guindon. Accounting for Calibration Uncertainty: Bayesian Molecular Dating as a “Doubly Intractable” Problem. Systematic Biology, 2018, 67 (4), pp.651-661. ⟨10.1093/sysbio/syy003⟩. ⟨lirmm-01800299⟩
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