Function-valued traits in evolution
Copyright policy )Function-valued traits in evolution
Many biological characteristics of evolutionary interest are not scalar variables but continuous functions. Given a dataset of function-valued traits generated by evolution, we develop a practical, statistical approach to infer ancestral function-valued traits, and estimate the generative evolutionary process. We do this by combining dimension reduction and phylogenetic Gaussian process regression, a non-parametric procedure that explicitly accounts for known phylogenetic relationships. We test the performance of methods on simulated, function-valued data generated from a stochastic evolutionary model. The methods are applied assuming that only the phylogeny, and the function-valued traits of taxa at its tips are known. Our method is robust and applicable to a wide range of function-valued data, and also offers a phylogenetically aware method for estimating the autocorrelation of function-valued traits.
- University of Warwick United Kingdom
- University of Manchester United Kingdom
- Imperial College London United Kingdom
- THE UNIVERSITY OF MANCHESTER United Kingdom
- University of Manchester United Kingdom
FOS: Computer and information sciences, 570, comparative analysis, Evolution, General Science & Technology, Quantitative Trait Loci, Normal Distribution, ancestral reconstruction, Quantitative Biology - Quantitative Methods, Ornstein–Uhlenbeck process, Evolution, Molecular, Methodology (stat.ME), QH301, CHARACTERS, Genetic, Models, functional Gaussian process regression, MD Multidisciplinary, Animals, Humans, ADAPTATION, QA, Quantitative Biology - Populations and Evolution, PHYLOGENIES, non-parametric Bayesian inference, Statistics - Methodology, Research Articles, Phylogeny, Quantitative Methods (q-bio.QM), ENVIRONMENT, Stochastic Processes, Science & Technology, INDEPENDENT COMPONENT ANALYSIS, Models, Genetic, STABILIZING SELECTION, Populations and Evolution (q-bio.PE), Molecular, comparative analysis, Ornstein–Uhlenbeck process, non-parametric Bayesian inference, functional phylogenetics, ancestral reconstruction, functional Gaussian process regression, Multidisciplinary Sciences, ADAPTIVE EVOLUTION, MODEL, FOS: Biological sciences, PATTERNS, Science & Technology - Other Topics, Ornstein-Uhlenbeck process, functional phylogenetics
FOS: Computer and information sciences, 570, comparative analysis, Evolution, General Science & Technology, Quantitative Trait Loci, Normal Distribution, ancestral reconstruction, Quantitative Biology - Quantitative Methods, Ornstein–Uhlenbeck process, Evolution, Molecular, Methodology (stat.ME), QH301, CHARACTERS, Genetic, Models, functional Gaussian process regression, MD Multidisciplinary, Animals, Humans, ADAPTATION, QA, Quantitative Biology - Populations and Evolution, PHYLOGENIES, non-parametric Bayesian inference, Statistics - Methodology, Research Articles, Phylogeny, Quantitative Methods (q-bio.QM), ENVIRONMENT, Stochastic Processes, Science & Technology, INDEPENDENT COMPONENT ANALYSIS, Models, Genetic, STABILIZING SELECTION, Populations and Evolution (q-bio.PE), Molecular, comparative analysis, Ornstein–Uhlenbeck process, non-parametric Bayesian inference, functional phylogenetics, ancestral reconstruction, functional Gaussian process regression, Multidisciplinary Sciences, ADAPTIVE EVOLUTION, MODEL, FOS: Biological sciences, PATTERNS, Science & Technology - Other Topics, Ornstein-Uhlenbeck process, functional phylogenetics
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