On the validity of evolutionary models with site-specific parameters
Open accessAbstract
Evolutionary models that make use of site-specific parameters have recently been criticized on the grounds that parameter estimates obtained under such models can be unreliable and lack theoretical guarantees of convergence. We present a simulation study providing empirical evidence that a simple version of the models in question does exhibit sensible convergence behavior and that additional taxa, despite not being independent of each other, lead to improved parameter estimates. Although it would be desirable to have theoretical guarantees of this, we argue that such guarantees would not be sufficient to justify the use of these models in practice. Instead, we emphasize the importance of taking the variance of parameter estimates into account rather than blindly trusting point estimates - this is standardly done by using the models to construct statistical hypothesis tests, which are then validated empirically via simulation studies.
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Branch-specific k_b maximum-likelihood estimates have high sampling variances because they are derived from a small volume of information (a single branch).
“However, we suggest exercising due caution when comparing k b maximum-likelihood estimates (or any of the other parameter estimates describing the !distribution) directly, as they are derived from a small volume of information (a single branch) and therefore have high sampling variances (Scheffler et al. 2014).”
From RELAX: Detecting Relaxed Selection in a Phylogenetic Framework (2015) · cites this paper as Scheffler et al. 2014
The Results report that branch-specific maximum-likelihood estimates have sampling variances that shrink as the number of sites increases, supporting caution when data are limited. The paper does not specifically discuss k_b or its distribution, and it does not say that estimating a parameter for a single branch alone makes its variance high. The Introduction’s statement about limited information at a single site concerns site-specific, not branch-specific, parameters. (LLM, conf=0.83)
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Cites
Detecting Individual Sites Subject to Episodic Diversifying Selection
Murrell, B., Wertheim, J. O., Moola, S., Weighill, T., Scheffler, K., & Kosakovsky Pond, S. L. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002764 · Cited by 1,811 · see citing works
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Research works printed but not linked: 14
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Cited by
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RELAX: Detecting Relaxed Selection in a Phylogenetic Framework
Wertheim, J. O., Murrell, B., Smith, M. D., Kosakovsky Pond, S. L., & Scheffler, K. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msu400 · Cited by 778 · see citing works
Self-citation
- Authors
- Scheffler, K., Murrell, B., & Kosakovsky Pond, S. L.
- Affiliations
- Stellenbosch University (ZA)
- University of California San Diego (US)
- Corresponding author
- Scheffler, Konrad
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-04-10
- Volume
- 9
- Issue
- 4
- Pages
- e94534
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3983186
- OpenAlex
- W2036475287
- Cited by
- 16
- References
- 1
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2021: 1 · 2020: 2 · 2018: 4 · 2016: 2 · 2015: 2 · 2014: 2
- FWCI
- 0.76
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- TUScholarShare (Temple University) (submittedVersion, cc-by)
- SUNScholar (Stellenbosch University) (submittedVersion)
- Funders
- National Institutes of Health (AI47745, AI74621, AI 036214)
- National Institute of Mental Health (R01MH083552, MH101012, R01MH101012, MH083552)
- National Institute on Drug Abuse (DA-034978, DP1DA034978)
- National Institute of General Medical Sciences (GM093939, R01GM093939)
- National Institute of Allergy and Infectious Diseases (R01AI057167, AI-74621, AI-47745, AI57167, R21AI047745, AI 036214, R56AI047745, R01AI047745, P01AI074621, P30AI036214)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Keywords
- site-specific parameters, evolutionary models, parameter estimation, convergence, phylogenetic inference, hypothesis testing, simulation study
- MeSH terms
- Algorithms, Biological Evolution, Phylogeny, Models, Statistical
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