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  • 1
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    Mapping the origins and expansion of the Indo-European language family (2012)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2012-08-28
    Description: There are two competing hypotheses for the origin of the Indo-European language family. The conventional view places the homeland in the Pontic steppes about 6000 years ago. An alternative hypothesis claims that the languages spread from Anatolia with the expansion of farming 8000 to 9500 years ago. We used Bayesian phylogeographic approaches, together with basic vocabulary data from 103 ancient and contemporary Indo-European languages, to explicitly model the expansion of the family and test these hypotheses. We found decisive support for an Anatolian origin over a steppe origin. Both the inferred timing and root location of the Indo-European language trees fit with an agricultural expansion from Anatolia beginning 8000 to 9500 years ago. These results highlight the critical role that phylogeographic inference can play in resolving debates about human prehistory.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112997/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112997/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Bouckaert, Remco -- Lemey, Philippe -- Dunn, Michael -- Greenhill, Simon J -- Alekseyenko, Alexander V -- Drummond, Alexei J -- Gray, Russell D -- Suchard, Marc A -- Atkinson, Quentin D -- 260864/European Research Council/International -- R01 GM086887/GM/NIGMS NIH HHS/ -- R01 HG006139/HG/NHGRI NIH HHS/ -- New York, N.Y. -- Science. 2012 Aug 24;337(6097):957-60. doi: 10.1126/science.1219669.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Computer Science, University of Auckland, Auckland 1142, New Zealand.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22923579" target="_blank"〉PubMed〈/a〉
    Keywords: Agriculture/history ; Bayes Theorem ; *Cultural Evolution ; History, Ancient ; Humans ; Language/*history ; Linguistics/history ; Phylogeography ; Turkey ; Vocabulary
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    Birth-death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV) (2012)
    National Academy of Sciences
    Details
    Publication Date: 2012-12-17
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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  • 3
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    Bayesian Selection of Nucleotide Substitution Models and Their Site Assignments (2013)
    Oxford University Press
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    Publication Date: 2013-02-06
    Description: Probabilistic inference of a phylogenetic tree from molecular sequence data is predicated on a substitution model describing the relative rates of change between character states along the tree for each site in the multiple sequence alignment. Commonly, one assumes that the substitution model is homogeneous across sites within large partitions of the alignment, assigns these partitions a priori, and then fixes their underlying substitution model to the best-fitting model from a hierarchy of named models. Here, we introduce an automatic model selection and model averaging approach within a Bayesian framework that simultaneously estimates the number of partitions, the assignment of sites to partitions, the substitution model for each partition, and the uncertainty in these selections. This new approach is implemented as an add-on to the BEAST 2 software platform. We find that this approach dramatically improves the fit of the nucleotide substitution model compared with existing approaches, and we show, using a number of example data sets, that as many as nine partitions are required to explain the heterogeneity in nucleotide substitution process across sites in a single gene analysis. In some instances, this improved modeling of the substitution process can have a measurable effect on downstream inference, including the estimated phylogeny, relative divergence times, and effective population size histories.
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
    Published by Oxford University Press
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  • 4
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    Efficient Bayesian inference under the structured coalescent (2014)
    Oxford University Press
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    Publication Date: 2014-08-06
    Description: Motivation: Population structure significantly affects evolutionary dynamics. Such structure may be due to spatial segregation, but may also reflect any other gene-flow-limiting aspect of a model. In combination with the structured coalescent, this fact can be used to inform phylogenetic tree reconstruction, as well as to infer parameters such as migration rates and subpopulation sizes from annotated sequence data. However, conducting Bayesian inference under the structured coalescent is impeded by the difficulty of constructing Markov Chain Monte Carlo (MCMC) sampling algorithms (samplers) capable of efficiently exploring the state space. Results: In this article, we present a new MCMC sampler capable of sampling from posterior distributions over structured trees: timed phylogenetic trees in which lineages are associated with the distinct subpopulation in which they lie. The sampler includes a set of MCMC proposal functions that offer significant mixing improvements over a previously published method. Furthermore, its implementation as a BEAST 2 package ensures maximum flexibility with respect to model and prior specification. We demonstrate the usefulness of this new sampler by using it to infer migration rates and effective population sizes of H3N2 influenza between New Zealand, New York and Hong Kong from publicly available hemagglutinin (HA) gene sequences under the structured coalescent. Availability and implementation: The sampler has been implemented as a publicly available BEAST 2 package that is distributed under version 3 of the GNU General Public License at http://compevol.github.io/MultiTypeTree . Contact: tgvaughan@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 5
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    Bayesian Phylogenetics with BEAUti and the BEAST 1.7 (2012)
    Oxford University Press
    Details
    Publication Date: 2012-07-31
    Description: Computational evolutionary biology, statistical phylogenetics and coalescent-based population genetics are becoming increasingly central to the analysis and understanding of molecular sequence data. We present the Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7, which implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography and related molecular evolutionary analyses. This package includes an enhanced graphical user interface program called Bayesian Evolutionary Analysis Utility (BEAUti) that enables access to advanced models for molecular sequence and phenotypic trait evolution that were previously available to developers only. The package also provides new tools for visualizing and summarizing multispecies coalescent and phylogeographic analyses. BEAUti and BEAST 1.7 are open source under the GNU lesser general public license and available at http://beast-mcmc.googlecode.com and http://beast.bio.ed.ac.uk
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
    Published by Oxford University Press
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  • 6
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    Birth-death skyline plot [Evolution] (2013)
    National Academy of Sciences
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    Publication Date: 2013-01-04
    Description: Phylogenetic trees can be used to infer the processes that generated them. Here, we introduce a model, the Bayesian birth–death skyline plot, which explicitly estimates the rate of transmission, recovery, and sampling and thus allows inference of the effective reproductive number directly from genetic data. Our method allows these parameters...
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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  • 7
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    A Stochastic Simulator of Birth-Death Master Equations with Application to Phylodynamics (2013)
    Oxford University Press
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    Publication Date: 2013-05-10
    Description: In this article, we present a versatile new software tool for the simulation and analysis of stochastic models of population phylodynamics and chemical kinetics. Models are specified via an expressive and human-readable XML format and can be used as the basis for generating either single population histories or large ensembles of such histories. Importantly, phylogenetic trees or networks can be generated alongside the histories they correspond to, enabling investigations into the interplay between genealogies and population dynamics. Summary statistics such as means and variances can be recorded in place of the full ensemble, allowing for a reduction in the amount of memory used—an important consideration for models including large numbers of individual subpopulations or demes. In the case of population size histories, the resulting simulation output is written to disk in the flexible JSON format, which is easily read into numerical analysis environments such as R for visualization or further processing. Simulated phylogenetic trees can be recorded using the standard Newick or NEXUS formats, with extensions to these formats used for non-tree-like inheritance relationships.
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
    Published by Oxford University Press
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  • 8
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    Accurate Model Selection of Relaxed Molecular Clocks in Bayesian Phylogenetics (2013)
    Oxford University Press
    Details
    Publication Date: 2013-01-19
    Description: Recent implementations of path sampling (PS) and stepping-stone sampling (SS) have been shown to outperform the harmonic mean estimator (HME) and a posterior simulation-based analog of Akaike’s information criterion through Markov chain Monte Carlo (AICM), in Bayesian model selection of demographic and molecular clock models. Almost simultaneously, a Bayesian model averaging approach was developed that avoids conditioning on a single model but averages over a set of relaxed clock models. This approach returns estimates of the posterior probability of each clock model through which one can estimate the Bayes factor in favor of the maximum a posteriori (MAP) clock model; however, this Bayes factor estimate may suffer when the posterior probability of the MAP model approaches 1. Here, we compare these two recent developments with the HME, stabilized/smoothed HME (sHME), and AICM, using both synthetic and empirical data. Our comparison shows reassuringly that MAP identification and its Bayes factor provide similar performance to PS and SS and that these approaches considerably outperform HME, sHME, and AICM in selecting the correct underlying clock model. We also illustrate the importance of using proper priors on a large set of empirical data sets.
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
    Published by Oxford University Press
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  • 9
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    A Bayesian Phylogenetic Method to Estimate Unknown Sequence Ages (2010)
    Oxford University Press
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    Publication Date: 2010-10-01
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
    Published by Oxford University Press
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  • 10
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    Model Averaging and Bayes Factor Calculation of Relaxed Molecular Clocks in Bayesian Phylogenetics (2011)
    Oxford University Press
    Details
    Publication Date: 2011-09-22
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
    Published by Oxford University Press
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