Accelerated Estimation of Frequency Classes in Site-Heterogeneous Profile Mixture Models
Open accessAbstract
As a consequence of structural and functional constraints, proteins tend to have site-specific preferences for particular amino acids. Failing to adjust for heterogeneity of frequencies over sites can lead to artifacts in phylogenetic estimation. Site-heterogeneous mixture-models have been developed to address this problem. However, due to prohibitive computational times, maximum likelihood implementations utilize fixed component frequency vectors inferred from sequences in a database that are external to the alignment under analysis. Here, we propose a composite likelihood approach to estimation of component frequencies for a mixture model that directly uses the data from the alignment of interest. In the common case that the number of taxa under study is not large, several adjustments to the default composite likelihood are shown to be necessary. In simulations, the approach is shown to provide large improvements over hierarchical clustering. For empirical data, substantial improvements in likelihoods are found over mixtures using fixed components.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Previous studies analysing the test datasets without partitioning have found support for the accepted topology under a variety of site-heterogeneous models.
“Previous studies analysing the test datasets used here, but without partitioning, have found support for the accepted topology under a variety of site-heterogeneous models22,56,60.”
From Evidence for sponges as sister to all other animals from partitioned phylogenomics with mixture models and recoding (2021) · cites this paper as [60]
Cites
Phylotranscriptomic analysis of the origin and early diversification of land plants
Wickett, N. J., Mirarab, S., Nguyen, N., Warnow, T., Carpenter, E., Matasci, N., Ayyampalayam, S., Barker, M. S., Burleigh, J. G., Gitzendanner, M. A., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1323926111 · Cited by 1,252 · see citing works
Resolving difficult phylogenetic questions: Why more sequences are not enough
Philippe, H., Brinkmann, H., Lavrov, D. V., Littlewood, D. T. J., Manuel, M., Wörheide, G., & Baurain, D. (2011) · PLoS Biology · doi:10.1371/journal.pbio.1000602 · Cited by 1,129 · see citing works
Lartillot, N., Rodrigue, N., Stubbs, D., & Richer, J. (2013) · Systematic Biology · doi:10.1093/sysbio/syt022 · Cited by 871 · see citing works
Lartillot, N., Brinkmann, H., & Philippe, H. (2007) · BMC Evolutionary Biology · doi:10.1186/1471-2148-7-s1-s4 · Cited by 705 · see citing works
Contentious relationships in phylogenomic studies can be driven by a handful of genes
Shen, X.-X., Hittinger, C. T., & Rokas, A. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0126 · Cited by 520 · see citing works
Genomic data do not support comb jellies as the sister group to all other animals
Pisani, D., Pett, W., Dohrmann, M., Feuda, R., Rota-Stabelli, O., Philippe, H., Lartillot, N., & Wörheide, G. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1518127112 · Cited by 319 · cited 2× · see citing works
“2007), a concern has been that the Markov chain Monte Carlo computational techniques used to approximate posterior probabilities can suffer from convergence difficulties with large data (Pisani et al. 2015; Whelan et al. 2015; Whelan and Halanych 2016).”
BackgroundWhelan, N. V., & Halanych, K. M. (2016) · Systematic Biology · doi:10.1093/sysbio/syw084 · Cited by 96 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Redmond, A. K., & McLysaght, A. (2021) · Nature Communications · doi:10.1038/s41467-021-22074-7 · Cited by 139 · see citing works
Muñoz-Gómez, S. A., Susko, E., Williamson, K., Eme, L., Slamovits, C. H., Moreira, D., López-García, P., & Roger, A. J. (2022) · Nature Ecology & Evolution · doi:10.1038/s41559-021-01638-2 · Cited by 111 · see citing works
Self-citationScalable empirical mixture models that account for across-site compositional heterogeneity
Schrempf, D., Lartillot, N., & Szöllősi, G. (2019) · doi:10.1101/794263 · Cited by 61 · see citing works
- Authors
- Susko, E., Lincker, L., & Roger, A. J.
- Affiliations
- Dalhousie University (CA)
- Corresponding author
- Susko, Edward
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-02-22
- Volume
- 35
- Issue
- 5
- Pages
- 1266-1283
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- OpenAlex
- W2792381687
- Cited by
- 29
- References
- 7
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 6 · 2023: 4 · 2022: 5 · 2021: 4 · 2020: 2 · 2019: 1 · 2018: 2
- FWCI
- 0.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Molecular Biology and Evolution (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- 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
- composite likelihood, protein sequence alignment, phylogenetic estimation, hierarchical clustering, maximum likelihood estimation
- MeSH terms
- Computer Simulation, Models, Genetic, Phylogeny, Likelihood Functions, Amino Acid Substitution
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
