Lie Markov models with purine/pyrimidine symmetry

Continuous-time Markov chains are a standard tool in phylogenetic inference. If homogeneity is assumed, the chain is formulated by specifying time-independent rates of substitutions between states in the chain. In applications, there are usually extra constraints on the rates, depending on the situa...

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Veröffentlicht in:Journal of mathematical biology Jg. 70; H. 4; S. 855 - 891
Hauptverfasser: Fernández-Sánchez, Jesús, Sumner, Jeremy G., Jarvis, Peter D., Woodhams, Michael D.
Format: Journal Article Verlag
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2015
Springer Nature B.V
Schlagworte:
15 Linear and multilinear algebra; matrix theory
22 Topological groups, lie groups
22E Lie groups
52 Convex and discrete geometry
52B Polytopes and polyhedra
62 Statistics
62P Applications
Animals
Applications of Mathematics
Classificació AMS
DNA - genetics
Evolution, Molecular
Humans
Lie algebras
Lie, Àlgebres de
Markov Chains
Markov model
Matemàtiques i estadística
Mathematical and Computational Biology
Mathematical Concepts
Mathematics
Mathematics and Statistics
Models, Genetic
Permutation groups
Phylogenetics
Phylogeny
Purine Nucleotides - genetics
Pyrimidine Nucleotides - genetics
Representation theory
sequences
Stochastic Processes
Àrees temàtiques de la UPC
15A30
62P10
Permutation groups
Lie algebras
22E60
52B99
Phylogenetics
Representation theory
Markov model
ISSN:0303-6812, 1432-1416, 1432-1416
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Zusammenfassung:Continuous-time Markov chains are a standard tool in phylogenetic inference. If homogeneity is assumed, the chain is formulated by specifying time-independent rates of substitutions between states in the chain. In applications, there are usually extra constraints on the rates, depending on the situation. If a model is formulated in this way, it is possible to generalise it and allow for an inhomogeneous process, with time-dependent rates satisfying the same constraints. It is then useful to require that, under some time restrictions, there exists a homogeneous average of this inhomogeneous process within the same model. This leads to the definition of “Lie Markov models” which, as we will show, are precisely the class of models where such an average exists. These models form Lie algebras and hence concepts from Lie group theory are central to their derivation. In this paper, we concentrate on applications to phylogenetics and nucleotide evolution, and derive the complete hierarchy of Lie Markov models that respect the grouping of nucleotides into purines and pyrimidines—that is, models with purine/pyrimidine symmetry. We also discuss how to handle the subtleties of applying Lie group methods, most naturally defined over the complex field, to the stochastic case of a Markov process, where parameter values are restricted to be real and positive. In particular, we explore the geometric embedding of the cone of stochastic rate matrices within the ambient space of the associated complex Lie algebra.
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ISSN:0303-6812
1432-1416
1432-1416
DOI:10.1007/s00285-014-0773-z