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Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution
Regression analysis using line equations has been broadly applied in studying the evolutionary relationship between the response trait and its covariates. However, the characteristics among closely related species in nature present abundant diversities where the nonlinear relationship between traits...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916804/ https://www.ncbi.nlm.nih.gov/pubmed/33579023 http://dx.doi.org/10.3390/e23020218 |
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author | Jhwueng, Dwueng-Chwuan Wang, Chih-Ping |
author_facet | Jhwueng, Dwueng-Chwuan Wang, Chih-Ping |
author_sort | Jhwueng, Dwueng-Chwuan |
collection | PubMed |
description | Regression analysis using line equations has been broadly applied in studying the evolutionary relationship between the response trait and its covariates. However, the characteristics among closely related species in nature present abundant diversities where the nonlinear relationship between traits have been frequently observed. By treating the evolution of quantitative traits along a phylogenetic tree as a set of continuous stochastic variables, statistical models for describing the dynamics of the optimum of the response trait and its covariates are built herein. Analytical representations for the response trait variables, as well as their optima among a group of related species, are derived. Due to the models’ lack of tractable likelihood, a procedure that implements the Approximate Bayesian Computation (ABC) technique is applied for statistical inference. Simulation results show that the new models perform well where the posterior means of the parameters are close to the true parameters. Empirical analysis supports the new models when analyzing the trait relationship among kangaroo species. |
format | Online Article Text |
id | pubmed-7916804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79168042021-03-01 Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution Jhwueng, Dwueng-Chwuan Wang, Chih-Ping Entropy (Basel) Article Regression analysis using line equations has been broadly applied in studying the evolutionary relationship between the response trait and its covariates. However, the characteristics among closely related species in nature present abundant diversities where the nonlinear relationship between traits have been frequently observed. By treating the evolution of quantitative traits along a phylogenetic tree as a set of continuous stochastic variables, statistical models for describing the dynamics of the optimum of the response trait and its covariates are built herein. Analytical representations for the response trait variables, as well as their optima among a group of related species, are derived. Due to the models’ lack of tractable likelihood, a procedure that implements the Approximate Bayesian Computation (ABC) technique is applied for statistical inference. Simulation results show that the new models perform well where the posterior means of the parameters are close to the true parameters. Empirical analysis supports the new models when analyzing the trait relationship among kangaroo species. MDPI 2021-02-10 /pmc/articles/PMC7916804/ /pubmed/33579023 http://dx.doi.org/10.3390/e23020218 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jhwueng, Dwueng-Chwuan Wang, Chih-Ping Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution |
title | Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution |
title_full | Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution |
title_fullStr | Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution |
title_full_unstemmed | Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution |
title_short | Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution |
title_sort | phylogenetic curved optimal regression for adaptive trait evolution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916804/ https://www.ncbi.nlm.nih.gov/pubmed/33579023 http://dx.doi.org/10.3390/e23020218 |
work_keys_str_mv | AT jhwuengdwuengchwuan phylogeneticcurvedoptimalregressionforadaptivetraitevolution AT wangchihping phylogeneticcurvedoptimalregressionforadaptivetraitevolution |