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Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7
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Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.
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“We checked for convergence between runs using Tracer v. 1.7 [36], ensuring that ESS values were >200 to indicate adequate sampling.”
From Mitogenomic Crocodylia phylogeny and population structure of Crocodylus porosus including the extinct Seychelles crocodile (2026) · cites this paper as [36]
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“We ran eight independent MCMC chains and assessed convergence from effective sample sizes in Tracer (78)”
From Convergent genome streamlining accompanies independent miniaturization in the world’s smallest fishes (2026) · cites this paper as [78]
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MethodSelf-citationInference from iterative simulation using multiple sequences
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BackgroundBayesian Phylogenetics with BEAUti and the BEAST 1.7
Drummond, A. J., Suchard, M. A., Xie, D., & Rambaut, A. (2012) · Molecular Biology and Evolution · doi:10.1093/molbev/mss075 · Cited by 10,128 · cited 3×
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Metadata
- Authors
- Rambaut, A., Drummond, A. J., Xie, D., Baele, G., & Suchard, M. A.
- Affiliations
- University of Edinburgh (GB)
- University of Auckland (NZ)
- KU Leuven (BE)
- University of California, Los Angeles (US)
- Corresponding author
- Rambaut, Andrew
- Venue
- Systematic Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-04-27
- Volume
- 67
- Issue
- 5
- Pages
- 901-904
- ISSN
- 1063-5157 (ISSN-L)
- 1076-836X
- PMC
- PMC6101584
- OpenAlex
- W2801159594
- Cited by
- 11,159
- References
- 22
- Citations by year
- 2026: 1393 · 2025: 1633 · 2024: 1602 · 2023: 1501 · 2022: 1638 · 2021: 1477 · 2020: 1236 · 2019: 574 · 2018: 95
- FWCI
- 301.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Systematic Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lirias (KU Leuven) (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- National Science Foundation (1264153)
- National Institutes of Health (R01 AI107034, U19 AI135995)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Keywords
- tracers, Bayesian phylogenetics, kernel density estimation, multivariate data visualization, open source software
- MeSH terms
- Bayes Theorem, Markov Chains, Models, Genetic, Monte Carlo Method, Phylogeny, Software, Evolution, Molecular
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