CoChat
Sign Up
Cited by 429Genomics and Phylogenetic StudiesEvolution and Paleontology StudiesEvolution and Genetic Dynamics

Bayesian random local clocks, or one rate to rule them all

Open access
Drummond, Alexei J, Suchard, Marc A·2010·BMC Biology
DOI 10.1186/1741-7007-8-114PMC PMC2949620
Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: Relaxed molecular clock models allow divergence time dating and "relaxed phylogenetic" inference, in which a time tree is estimated in the face of unequal rates across lineages. We present a new method for relaxing the assumption of a strict molecular clock using Markov chain Monte Carlo to implement Bayesian modeling averaging over random local molecular clocks. The new method approaches the problem of rate variation among lineages by proposing a series of local molecular clocks, each extending over a subregion of the full phylogeny. Each branch in a phylogeny (subtending a clade) is a possible location for a change of rate from one local clock to a new one. Thus, including both the global molecular clock and the unconstrained model results, there are a total of 2(2n-2) possible rate models available for averaging with 1, 2, ..., 2n - 2 different rate categories. RESULTS: We propose an efficient method to sample this model space while simultaneously estimating the phylogeny. The new method conveniently allows a direct test of the strict molecular clock, in which one rate rules them all, against a large array of alternative local molecular clock models. We illustrate the method's utility on three example data sets involving mammal, primate and influenza evolution. Finally, we explore methods to visualize the complex posterior distribution that results from inference under such models. CONCLUSIONS: The examples suggest that large sequence datasets may only require a small number of local molecular clocks to reconcile their branch lengths with a time scale. All of the analyses described here are implemented in the open access software package BEAST 1.5.4 (http://beast-mcmc.googlecode.com/).

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/1741-7007-8-114

Cites

15 of 15 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

  • The random local clock model implemented in BEAST assumes an indicator variable for rate change at each node, enumerates all possible local clock configurations, and estimates the location and magnitude of rate changes between local clock regions on the phylogeny.

    “The random local clock model implemented in BEAST (Drummond and Suchard 2010) assumes an indicator variable for rate change at each node, enumerating all possible local clock configurations, and estimates the location and magnitude of rate changes between local clock regions on the phylogeny.”

    From Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees (2019) · cites this paper as Drummond and Suchard 2010

    Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • Several existing relaxed clock models explicitly model substitution rate variation across phylogeny.

    “Several existing relaxed clock models (Drummond and Suchard 2010; Heath et al. 2012) explicitly model substitution rate variation across phylogeny.”

    From Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees (2019) · cites this paper as Drummond and Suchard 2010

  • Our model is more specific in its goals than those implemented in more general phylogenetic packages.

    “Without doubt, our model is more specific in its goals than those implemented in more general phylogenetic packages (Drummond et al. 2006; Drummond and Suchard 2010; Heath et al. 2012; Ogilvie et al. 2017).”

    From Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees (2019) · cites this paper as Drummond and Suchard 2010

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 30

  1. Sarich VM Wilson AC Immunological time scale for hominid evolution Science 1967 158 1200 1203 10.1126/science.158.3805.1200 4964406 · DOI
  2. Huelsenbeck JP Larget B Swofford D A compound poisson process for relaxing the molecular clock Genetics 2000 154 1879 1892 10747076 PMC1461022
  3. Gillespie JH Lineage effects and the index of dispersion of molecular evolution Mol Biol Evol 1989 6 636 647 2488476
  4. Gillespie JH The Causes of Molecular Evolution 1991 Oxford: Oxford University Press
  5. Drummond AJ Rambaut A BEAST: Bayesian evolutionary analysis by sampling trees BMC Evol Biol 2007 7 214 10.1186/1471-2148-7-214 17996036 PMC2247476 · DOI
  6. Lange K Applied Probability 2003 New York: Springer [Springer Texts in Statistics.]
  7. Lanave C Preparata G Saccone C Serio G A new method for calculating evolutionary substitution rates J Mol Evol 1984 20 86 93 10.1007/BF02101990 6429346 · DOI
  8. Yang Z Among-site rate variation and its impact on phylogenetic analyses Trends Ecol Evol 1996 11 367 372 10.1016/0169-5347(96)10041-0 21237881 · DOI
  9. Yang Z Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods J Mol Evol 1994 39 306 314 10.1007/BF00160154 7932792 · DOI · Paper page
  10. Metropolis N Rosenbluth AW Rosenbluth MN Teller AH Teller E Equations of state calculations by fast computing machines J Chem Phys 1953 21 1087 1092 10.1063/1.1699114 · DOI · Paper page
  11. Hastings WK Monte Carlo sampling methods using Markov chains and their applications Biometrika 1970 57 97 109 10.1093/biomet/57.1.97 · DOI · Paper page
  12. Drummond AJ Nicholls GK Rodrigo AG Solomon W Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data Genetics 2002 161 1307 1320 12136032 PMC1462188
  13. Jeffreys H Some tests of significance, treated by the theory of probability Proc Camb Philos Soc 1935 31 203 222 10.1017/S030500410001330X · DOI
  14. Jeffreys H Theory of Probability 1961 1 London: Oxford University Press
  15. Kass RE Raftery AE Bayes factors J Am Stat Assoc 1995 90 773 795 10.2307/2291091 · DOI
  16. Suchard MA Weiss RE Sinsheimer JS Models for estimating Bayes factors with applications in phylogeny and tests of monophyly Biometrics 2005 61 665 673 10.1111/j.1541-0420.2005.00352.x 16135017 · DOI
  17. Brown WM Prager EM Wang A Wilson AC Mitochondrial DNA sequences of primates, tempo and mode of evolution J Mol Evol 1982 18 225 239 10.1007/BF01734101 6284948 · DOI · Paper page
  18. Hayasaka K Gojobori KT Horai S Molecular phylogeny and evolution of primate mitochondrial DNA Mol Biol Evol 1988 5 626 644 3146681
  19. Suchard MA Weiss RE Sinsheimer JS Bayesian selection of continuous-time Markov chain evolutionary models Mol Biol Evol 2001 18 1001 1013 11371589
  20. Suchard MA Weiss RE Sinsheimer JS Testing a molecular clock without an outgroup: derivations of induced priors on branch length restrictions in a Bayesian framework Syst Biol 2003 52 48 54 10.1080/10635150390132713 12554439 · DOI
  21. Huelsenbeck JP Ronquist F Mrbayes: Bayesian inference of phylogenetic trees Bioinformatics 2001 17 754 755 10.1093/bioinformatics/17.8.754 11524383 · DOI · Paper page
  22. Yang Z PAML 4: a program package for phylogenetic analysis by maximum likelihood Mol Biol Evol 2007 24 1586 1591 10.1093/molbev/msm088 17483113 · DOI · Paper page
  23. Drummond AJ Suchard MA Fully Bayesian tests of neutrality using genealogical summary statistics BMC Genet 2008 9 68 10.1186/1471-2156-9-68 18976476 PMC2645432 · DOI
  24. Drummond A Forsberg R Rodrigo AG The inference of stepwise changes in substitution rates using serial sequence samples Mol Biol Evol 2001 18 1365 1371 11420374
  25. Gray RD Drummond AJ Greenhill SJ Language phylogenies reveal expansion pulses and pauses in pacific settlement Science 2009 323 479 483 10.1126/science.1166858 19164742 · DOI · Paper page
  26. Lartillot N Philippe H Computing Bayes factors using thermodynamic integration Syst Biol 2006 55 195 207 10.1080/10635150500433722 16522570 · DOI · Paper page
  27. Beerli P Palczewski M Unified framework to evaluate panmixia and migration direction among multiple sampling locations Genetics 2010 185 313 326 10.1534/genetics.109.112532 20176979 PMC2870966 · DOI
  28. Fan Y Wu R Chen M-H Kuo L Lewis PO Choosing among partition models in Bayesian phylogenetics Mol Biol Evol 2010 in press 20801907 PMC3002242
  29. Liu JS The collasped Gibbs sampler in Bayesian computations with applications to a gene regulation problem J Am Stat Assoc 1994 89 958 966 10.2307/2290921 · DOI
  30. Redelings BD Suchard MA Joint Bayesian estimation of alignment and phylogeny Syst Biol 2005 54 401 418 10.1080/10635150590947041 16012107 · DOI

Cited by

Sorted by citations

Authors
Drummond, A. J., & Suchard, M. A.
Affiliations
  • University of Auckland (NZ)
  • University of California, Los Angeles (US)
Corresponding author
  • Drummond, Alexei J
  • Suchard, Marc A
ORCID
Venue
BMC Biology
Publisher
Springer Science and Business Media LLC
Published
2010-08-31
Volume
8
Issue
1
Pages
114-114
ISSN
1741-7007 (ISSN-L)
DOI
10.1186/1741-7007-8-114
PMC
PMC2949620
OpenAlex
W1987423081
Cited by
429
References
15
Citations by year
2026: 8 · 2025: 11 · 2024: 21 · 2023: 17 · 2022: 32 · 2021: 36 · 2020: 47 · 2019: 26 · 2018: 26 · 2017: 25 · 2016: 34 · 2015: 51 · 2014: 25 · 2013: 27 · 2012: 25
FWCI
8.25
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Biology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • National Science Foundation (0423641)
  • John Simon Guggenheim Memorial Foundation
  • National Evolutionary Synthesis Center (#EF-0423641)
  • National Institutes of Health (NIH-R01)
  • National Institute of General Medical Sciences (R01GM086887)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
Keywords
relaxed molecular clock, Bayesian model averaging, divergence time estimation, phylogenetic inference, Markov chain Monte Carlo, BEAST
MeSH terms
Animals, Bayes Theorem, Computer Simulation, DNA, Mitochondrial, Mammals, Markov Chains, Models, Genetic, Monte Carlo Method, Phylogeny, Software, Time Factors, Evolution, Molecular, Hemagglutinin Glycoproteins, Influenza Virus, Internet

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