ArticlePloS one2010
Correcting the bias of empirical frequency parameter estimators in codon models.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed, 62 citations in OpenAlex.
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- An Improved Codon Modeling Approach for Accurate Estimation of the Mutation Bias.Molecular biology and evolution · 2022Article
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- Contrast-FEL-A Test for Differences in Selective Pressures at Individual Sites among Clades and Sets of Branches.Molecular biology and evolution · 2021Article
- Extra base hits: Widespread empirical support for instantaneous multiple-nucleotide changes.PloS one · 2021Article
- Synonymous Site-to-Site Substitution Rate Variation Dramatically Inflates False Positive Rates of Selection Analyses: Ignore at Your Own Peril.Molecular biology and evolution · 2020Article
- Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence.Virus evolution · 2018Article
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- Adaptive molecular evolution ofEcology and evolution · 2017Article
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Corrections and comments
- Erratum issued
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Markov models of codon substitution are powerful inferential tools for studying biological processes such as natural selection and preferences in amino acid substitution. The equilibrium character distributions of these models are almost always estimated using nucleotide frequencies observed in a sequence alignment, primarily as a matter of historical convention. In this note, we demonstrate that a popular class of such estimators are biased, and that this bias has an adverse effect on goodness of fit and estimates of substitution rates. We propose a "corrected" empirical estimator that begins with observed nucleotide counts, but accounts for the nucleotide composition of stop codons. We show via simulation that the corrected estimates outperform the de facto standard estimates not just by providing better estimates of the frequencies themselves, but also by leading to improved estimation of other parameters in the evolutionary models. On a curated collection of sequence alignments, our estimators show a significant improvement in goodness of fit compared to the approach. Maximum likelihood estimation of the frequency parameters appears to be warranted in many cases, albeit at a greater computational cost. Our results demonstrate that there is little justification, either statistical or computational, for continued use of the -style estimators.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.