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Inferring demographic parameters in bacterial genomic data using Bayesian and hybrid phylogenetic methods.

Sebastian Duchene | David A Duchene | Jemma L Geoghegan | Zoe A Dyson | Jane Hawkey | Kathryn E Holt
BMC evolutionary biology | 2018

Recent developments in sequencing technologies make it possible to obtain genome sequences from a large number of isolates in a very short time. Bayesian phylogenetic approaches can take advantage of these data by simultaneously inferring the phylogenetic tree, evolutionary timescale, and demographic parameters (such as population growth rates), while naturally integrating uncertainty in all parameters. Despite their desirable properties, Bayesian approaches can be computationally intensive, hindering their use for outbreak investigations involving genome data for a large numbers of pathogen isolates. An alternative to using full Bayesian inference is to use a hybrid approach, where the phylogenetic tree and evolutionary timescale are estimated first using maximum likelihood. Under this hybrid approach, demographic parameters are inferred from estimated trees instead of the sequence data, using maximum likelihood, Bayesian inference, or approximate Bayesian computation. This can vastly reduce the computational burden, but has the disadvantage of ignoring the uncertainty in the phylogenetic tree and evolutionary timescale.

Pubmed ID: 29914372

Research resources used in this publication

None found

Antibodies used in this publication

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Associated grants

  • Agency: Wellcome Trust, United Kingdom
  • Agency: National Health and Medical Research Council, International
    Id: 1061409
  • Agency: Wellcome Trust (GB), International
    Id: 106158
  • Agency: University of Melbourne (AU), International
    Id: McKenzie

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This is a list of tools and resources that we have found mentioned in this publication.


BEAST (tool)

RRID:SCR_010228

A cross-platform software program for Bayesian MCMC analysis of molecular sequences. It is entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability. We include a simple to use user-interface program for setting up standard analyses and a suit of programs for analysing the results.

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PhyML (tool)

RRID:SCR_014629

Web phylogeny server based on the maximum-likelihood principle.

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Seq-Gen (tool)

RRID:SCR_014934

Software program that simulates the evolution of nucleotide or amino acid sequences along a phylogeny using common models of the substitution process. A range of models of molecular evolution are implemented, including the general reversible model. State frequencies and other parameters of the model may be given and site-specific rate heterogeneity may also be incorporated in a number of ways. Any number of trees may be read in and the program will produce any number of data sets for each tree.

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TempEst (tool)

RRID:SCR_017304

Software tool for investigating temporal signal and clocklikeness of molecular phylogenies. Used for visualization and analysis of temporally sampled sequence data to assess whether there is sufficient temporal signal in data to proceed with phylogenetic molecular clock analysis, and to identify sequences whose genetic divergence and sampling date are incongruent. Not available for downloading as of August 8, 2019.

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