StarBEAST2 brings faster species tree inference and accurate estimates of substitution rates
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Abstract
Fully Bayesian multispecies coalescent (MSC) methods like *BEAST estimate species trees from multiple sequence alignments. Today thousands of genes can be sequenced for a given study, but using that many genes with *BEAST is intractably slow. An alternative is to use heuristic methods which compromise accuracy or completeness in return for speed. A common heuristic is concatenation, which assumes that the evolutionary history of each gene tree is identical to the species tree. This is an inconsistent estimator of species tree topology, a worse estimator of divergence times, and induces spurious substitution rate variation when incomplete lineage sorting is present. Another class of heuristics directly motivated by the MSC avoids many of the pitfalls of concatenation but cannot be used to estimate divergence times. To enable fuller use of available data and more accurate inference of species tree topologies, divergence times, and substitution rates, we have developed a new version of *BEAST called StarBEAST2. To improve convergence rates we add analytical integration of population sizes, novel MCMC operators and other optimizations. Computational performance improved by 13.5× and 13.8× respectively when analyzing two empirical data sets, and an average of 33.1× across 30 simulated data sets. To enable accurate estimates of per-species substitution rates, we introduce species tree relaxed clocks, and show that StarBEAST2 is a more powerful and robust estimator of rate variation than concatenation. StarBEAST2 is available through the BEAUTi package manager in BEAST 2.4 and above.
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Bayesian multispecies coalescent models like *BEAST and starBEAST2 consider gene tree variations and can give more accurate estimate of per-species substitution rates.
“Bayesian multispecies coalescent models like *BEAST and starBEAST2 consider gene tree variations and can give more accurate estimate of per-species substitution rates (Heled and Drummond 2010; Ogilvie et al. 2017).”
From Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees (2019) · cites this paper as Ogilvie et al. 2017
The Introduction identifies *BEAST and StarBEAST2 as Bayesian multispecies coalescent methods, and the Conclusions say StarBEAST2’s new species-tree relaxed clock enables accurate inference of per-species branch rates despite incomplete lineage sorting. But the Species Tree Relaxed Clocks section says *BEAST’s gene-tree relaxed clocks do not produce species-branch-rate estimates. The claim therefore overextends the rate-estimation finding to *BEAST. Page numbers are not available in our copy. (LLM, conf=0.87)
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Cites
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“Branch rate models that can be used with a species tree relaxed clock currently include the wellestablished uncorrelated log-normal (UCLN) and uncorrelated exponential (UCED) models (Drummond et al. 2006), as well as the newer random local clock model (Drummond and Suchard 2010).”
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- Authors
- Ogilvie, H. A., Bouckaert, R. R., & Drummond, A. J.
- Affiliations
- Australian National University (AU)
- University of Auckland (NZ)
- Corresponding author
- Ogilvie, Huw A.
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-04-14
- Volume
- 34
- Issue
- 8
- Pages
- 2101-2114
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- PMC
- PMC5850801
- OpenAlex
- W2950847777
- Cited by
- 469
- References
- 7
- Citations by year
- 2026: 30 · 2025: 42 · 2024: 34 · 2023: 55 · 2022: 76 · 2021: 59 · 2020: 62 · 2019: 58 · 2018: 41 · 2017: 12
- FWCI
- 18.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Molecular Biology and Evolution (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ANU Open Research (Australian National University) (submittedVersion, cc-by)
- ResearchSpace (University of Auckland) (submittedVersion)
- Funders
- Australian Research Council (FL110100104)
- National Computational Infrastructure
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
- Keywords
- species tree inference, multispecies coalescent, Bayesian phylogenetics, substitution rate estimation, relaxed molecular clock, incomplete lineage sorting, divergence time estimation, population size estimation, MCMC convergence, concatenation, BEAST
- MeSH terms
- Base Sequence, Bayes Theorem, Computer Simulation, Biological Evolution, Models, Genetic, Phylogeny, Software, Sequence Alignment, Genetic Speciation, Mutation Rate
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