Statistical tests of models of DNA substitution

Goldman, Nick

doi:10.1007/bf00166252

Cited by 736Genomics and Phylogenetic StudiesRNA and protein synthesis mechanismsEvolution and Genetic Dynamics

Statistical tests of models of DNA substitution

Goldman, Nick·1993·Journal of Molecular Evolution

DOI 10.1007/bf00166252

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Abstract

Penny et al. have written that "The most fundamental criterion for a scientific method is that the data must, in principle, be able to reject the model. Hardly any [phylogenetic] tree-reconstruction methods meet this simple requirement." The ability to reject models is of such great importance because the results of all phylogenetic analyses depend on their underlying models--to have confidence in the inferences, it is necessary to have confidence in the models. In this paper, a test statistic suggested by Cox is employed to test the adequacy of some statistical models of DNA sequence evolution used in the phylogenetic inference method introduced by Felsenstein. Monte Carlo simulations are used to assess significance levels. The resulting statistical tests provide an objective and very general assessment of all the components of a DNA substitution model; more specific versions of the test are devised to test individual components of a model. In all cases, the new analyses have the additional advantage that values of phylogenetic parameters do not have to be assumed in order to perform the tests.

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An adequate modeling of the evolutionary process that generated the data is fundamental to the recovery of accurate phylogenies.
“An adequate modeling of the evolutionary process that generated the data is fundamental to the recovery of accurate phylogenies [16-20].”
From Improved Modeling of Compositional Heterogeneity Supports Sponges as Sister to All Other Animals (2017) · cites this paper as [16]
If the best-fitting model does not describe the evolutionary process that generated the data adequately, there can still be a high probability of recovering a tree with relationships representing systematic error.
“Yet, if the best-fitting model does not describe the evolutionary process that generated the data adequately, there can still be a high probability of recovering a tree with relationships representing systematic error [16-20].”
From Improved Modeling of Compositional Heterogeneity Supports Sponges as Sister to All Other Animals (2017) · cites this paper as [16]
Porifera-sister better represents the phylogenetic signal in the data.
“As phylogenetic methods are less likely to recover artifactual topologies when the models of evolution moreadequatelydescribethedata[16-20],weconcludethatPorifera-sister better represents the phylogenetic signal in the data.”
From Improved Modeling of Compositional Heterogeneity Supports Sponges as Sister to All Other Animals (2017) · cites this paper as [16]

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Detecting Amino Acid Sites Under Positive Selection and Purifying Selection
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Authors: Goldman, N.
Affiliations: University of Cambridge (GB)
Corresponding author: Goldman, Nick
ORCID: Goldman, Nick
Venue: Journal of Molecular Evolution
Publisher: Springer Science and Business Media LLC
Published: 1993-02
Volume: 36
Issue: 2
Pages: 182-198
ISSN: 0022-2844 (ISSN-L)
1432-1432
DOI: 10.1007/bf00166252
OpenAlex: W2162250327
Cited by: 736
References: 78
Citations by year: 2026: 5 · 2025: 5 · 2024: 7 · 2023: 6 · 2022: 7 · 2021: 11 · 2020: 16 · 2019: 13 · 2018: 9 · 2017: 11 · 2016: 5 · 2015: 10 · 2014: 33 · 2013: 16 · 2012: 22
FWCI: 5.02
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Journal of Molecular Evolution (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
Keywords: model adequacy testing, phylogenetic inference, DNA sequence evolution, model rejection
MeSH terms: Animals, Base Sequence, DNA, Biological Evolution, Globins, Humans, Models, Genetic, Phylogeny, Primates, Pseudogenes, RNA, Statistics as Topic

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