{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T19:29:15Z","timestamp":1780082955203,"version":"3.54.0"},"reference-count":26,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2017,2,13]],"date-time":"2017-02-13T00:00:00Z","timestamp":1486944000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007229","name":"\u2018Bijzonder Onderzoeksfonds', KU Leuven","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007229","id-type":"DOI","asserted-by":"publisher"}]},{"name":"European Union Seventh Framework Programme for research, technological development and demonstration"},{"name":"European Union\u2019s Horizon 2020 research and innovation programme"},{"name":"European Union\u2019s Horizon 2020 research and innovation programme"},{"name":"Research Foundation - Flanders"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Advances in sequencing technology continue to deliver increasingly large molecular sequence datasets that are often heavily partitioned in order to accurately model the underlying evolutionary processes. In phylogenetic analyses, partitioning strategies involve estimating conditionally independent models of molecular evolution for different genes and different positions within those genes, requiring a large number of evolutionary parameters that have to be estimated, leading to an increased computational burden for such analyses. The past two decades have also seen the rise of multi-core processors, both in the central processing unit (CPU) and Graphics processing unit processor markets, enabling massively parallel computations that are not yet fully exploited by many software packages for multipartite analyses.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We here propose a Markov chain Monte Carlo (MCMC) approach using an adaptive multivariate transition kernel to estimate in parallel a large number of parameters, split across partitioned data, by exploiting multi-core processing. Across several real-world examples, we demonstrate that our approach enables the estimation of these multipartite parameters more efficiently than standard approaches that typically use a mixture of univariate transition kernels. In one case, when estimating the relative rate parameter of the non-coding partition in a heterochronous dataset, MCMC integration efficiency improves by\u2009&amp;gt;\u200914-fold.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and Implementation<\/jats:title>\n                  <jats:p>Our implementation is part of the BEAST code base, a widely used open source software package to perform Bayesian phylogenetic inference.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btx088","type":"journal-article","created":{"date-parts":[[2017,2,15]],"date-time":"2017-02-15T08:58:08Z","timestamp":1487149088000},"page":"1798-1805","source":"Crossref","is-referenced-by-count":45,"title":["Adaptive MCMC in Bayesian phylogenetics: an application to analyzing partitioned data in BEAST"],"prefix":"10.1093","volume":"33","author":[{"given":"Guy","family":"Baele","sequence":"first","affiliation":[{"name":"Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philippe","family":"Lemey","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Rambaut","sequence":"additional","affiliation":[{"name":"Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK"},{"name":"Centre for Immunology, Infection and Evolution, University of Edinburgh, Ashworth Laboratories, King\u2019s Buildings, Edinburgh, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marc A","family":"Suchard","sequence":"additional","affiliation":[{"name":"Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA"},{"name":"Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA, USA"},{"name":"Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2017,2,13]]},"reference":[{"key":"2023020301105033400_btx088-B1","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1093\/sysbio\/syr100","article-title":"BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics","volume":"61","author":"Ayres","year":"2012","journal-title":"Syst. Biol"},{"key":"2023020301105033400_btx088-B2","doi-asserted-by":"crossref","first-page":"1970","DOI":"10.1093\/bioinformatics\/btt340","article-title":"Bayesian evolutionary model testing in the phylogenomics era: matching model complexity with computational efficiency","volume":"29","author":"Baele","year":"2013","journal-title":"Bioinformatics"},{"key":"2023020301105033400_btx088-B3","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1093\/molbev\/mss243","article-title":"Accurate model selection of relaxed molecular clocks in Bayesian phylogenetics","volume":"30","author":"Baele","year":"2013","journal-title":"Mol. Biol. Evol"},{"key":"2023020301105033400_btx088-B4","doi-asserted-by":"crossref","first-page":"1969","DOI":"10.1093\/molbev\/mss075","article-title":"Bayesian phylogenetics with BEAUti and the BEAST 1.7","volume":"29","author":"Drummond","year":"2012","journal-title":"Mol. Biol. Evol"},{"key":"2023020301105033400_btx088-B5","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1002\/cjs.5550360302","article-title":"Bayesian anaylsis of elasped times in continuous-time Markov chains","volume":"26","author":"Ferreira","year":"2008","journal-title":"Canadian Journal of Statistics"},{"key":"2023020301105033400_btx088-B6","volume-title":"Markov Chain Monte Carlo in Practice","author":"Gilks","year":"1996"},{"key":"2023020301105033400_btx088-B7","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1111\/j.2517-6161.1995.tb02046.x","article-title":"Multivariate logistic models","volume":"57","author":"Glonek","year":"1995","journal-title":"Journal of the Royal Statistical Society. Series B (Methodological)"},{"key":"2023020301105033400_btx088-B8","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1007\/s001800050022","article-title":"Adaptive proposal distribution for random walk Metropolis algorithm","volume":"14","author":"Haario","year":"1999","journal-title":"Comput. Statist"},{"key":"2023020301105033400_btx088-B9","doi-asserted-by":"crossref","first-page":"223","DOI":"10.2307\/3318737","article-title":"An adaptive Metropolis algorithm","volume":"7","author":"Haario","year":"2001","journal-title":"Bernouilli"},{"key":"2023020301105033400_btx088-B10","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1007\/BF02101694","article-title":"Dating of the human-ape splitting by a molecular clock of mitochondrial DNA","volume":"22","author":"Hasegawa","year":"1985","journal-title":"J. Mol. Evol"},{"key":"2023020301105033400_btx088-B11","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1093\/biomet\/57.1.97","article-title":"Monte Carlo sampling methods using Markov chains and their applications","volume":"57","author":"Hastings","year":"1970","journal-title":"Biometrika"},{"key":"2023020301105033400_btx088-B12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/sysbio\/syr074","article-title":"Guided tree topology proposals for Bayesian phylogenetic inference","volume":"61","author":"H\u00f6hna","year":"2012","journal-title":"Syst. Biol"},{"key":"2023020301105033400_btx088-B13","doi-asserted-by":"crossref","first-page":"2310","DOI":"10.1126\/science.1065889","article-title":"Bayesian inference of phylogeny and its impact on evolutionary biology","volume":"294","author":"Huelsenbeck","year":"2001","journal-title":"Science"},{"key":"2023020301105033400_btx088-B14","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.1063\/1.1699114","article-title":"Equations of state calculations by fast computing machines","volume":"21","author":"Metropolis","year":"1953","journal-title":"J. Chem. Phys"},{"key":"2023020301105033400_btx088-B15","first-page":"7","article-title":"CODA: Convergence Diagnosis and Output Analysis for MCMC","volume":"6","author":"Plummer","year":"2006","journal-title":"R News"},{"key":"2023020301105033400_btx088-B16","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1214\/ss\/1015346320","article-title":"Optimal scaling for various Metropolis-Hastings algorithms","volume":"16","author":"Roberts","year":"2001","journal-title":"Stat. Sci"},{"key":"2023020301105033400_btx088-B17","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1239\/jap\/1183667414","article-title":"Coupling and ergodicity of adaptive MCMC","volume":"44","author":"Roberts","year":"2007","journal-title":"J. Appl. Prob"},{"key":"2023020301105033400_btx088-B18","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1198\/jcgs.2009.06134","article-title":"Examples of adaptive MCMC","volume":"18","author":"Roberts","year":"2009","journal-title":"J. Comp. Graph. Stat"},{"key":"2023020301105033400_btx088-B19","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1093\/sysbio\/sys029","article-title":"MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space","volume":"61","author":"Ronquist","year":"2012","journal-title":"Syst. Biol"},{"key":"2023020301105033400_btx088-B20","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1093\/molbev\/msj021","article-title":"Choosing appropriate substitution models for the phylogenetic analysis of protein-coding genes","volume":"23","author":"Shapiro","year":"2006","journal-title":"Mol. Biol. Evol"},{"key":"2023020301105033400_btx088-B21","doi-asserted-by":"crossref","first-page":"1370","DOI":"10.1093\/bioinformatics\/btp244","article-title":"Many-core algorithms for statistical phylogenetics","volume":"25","author":"Suchard","year":"2009","journal-title":"Bioinformatics"},{"key":"2023020301105033400_btx088-B22","first-page":"57","volume-title":"Some Mathematical Questions in Biology: DNA Sequence Analysis","author":"Tavar\u00e9","year":"1986"},{"key":"2023020301105033400_btx088-B23","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/0169-5347(96)10041-0","article-title":"Among-site rate variation and its impact on phylogenetic analyses","volume":"11","author":"Yang","year":"1996","journal-title":"Trends Ecol. Evol"},{"key":"2023020301105033400_btx088-B24","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1007\/s002390010105","article-title":"Maximum likelihood estimation on large phylogeneis and analysis of adaptive evolution in human influenza virus A","volume":"51","author":"Yang","year":"2000","journal-title":"J. Mol. Evol"},{"key":"2023020301105033400_btx088-B25","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1093\/oxfordjournals.molbev.a025811","article-title":"Bayesian phylogenetic inference using DNA sequences: a Markov chain Monte Carlo method","volume":"14","author":"Yang","year":"1997","journal-title":"Mol. Biol. Evol"},{"key":"2023020301105033400_btx088-B26","first-page":"21","article-title":"A mathematical theory of evolution based on the conclusions of Dr. J.C. willis. F.R.S","volume":"213","author":"Yule","year":"1924","journal-title":"Philos. Trans. R. Soc. Lond. B Biol. Sci"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/12\/1798\/49039951\/bioinformatics_33_12_1798.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/12\/1798\/49039951\/bioinformatics_33_12_1798.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,3]],"date-time":"2023-02-03T01:11:32Z","timestamp":1675386692000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/33\/12\/1798\/2991430"}},"subtitle":[],"editor":[{"given":"Alfonso","family":"Valencia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2017,2,13]]},"references-count":26,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2017,6,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btx088","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2017,6,15]]},"published":{"date-parts":[[2017,2,13]]}}}