Automatic generation of evolutionary hypotheses using mixed Gaussian phylogenetic models

Proceedings of the National Academy of Sciences of the United States of America
Venelin MitovTanja Stadler

Abstract

Phylogenetic comparative methods are widely used to understand and quantify the evolution of phenotypic traits, based on phylogenetic trees and trait measurements of extant species. Such analyses depend crucially on the underlying model. Gaussian phylogenetic models like Brownian motion and Ornstein-Uhlenbeck processes are the workhorses of modeling continuous-trait evolution. However, these models fit poorly to big trees, because they neglect the heterogeneity of the evolutionary process in different lineages of the tree. Previous works have addressed this issue by introducing shifts in the evolutionary model occurring at inferred points in the tree. However, for computational reasons, in all current implementations, these shifts are "intramodel," meaning that they allow jumps in 1 or 2 model parameters, keeping all other parameters "global" for the entire tree. There is no biological reason to restrict a shift to a single model parameter or, even, to a single type of model. Mixed Gaussian phylogenetic models (MGPMs) incorporate the idea of jointly inferring different types of Gaussian models associated with different parts of the tree. Here, we propose an approximate maximum-likelihood method for fitting MGPMs to comparative ...Continue Reading

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Citations

Feb 28, 2020·Systematic Biology·Joëlle Barido-SottaniTanja Stadler
Oct 18, 2020·Trends in Ecology & Evolution·Danielle FraserS Kathleen Lyons

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Software Mentioned

MGPMMammals
package
RATEMATRIX BM
mvMorph
RATEMATRIX
SPLITT
SCALAR
MGPMSimulations
MGPM
R

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