{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:44:41Z","timestamp":1740185081312,"version":"3.37.3"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2016,12,22]],"date-time":"2016-12-22T00:00:00Z","timestamp":1482364800000},"content-version":"vor","delay-in-days":15,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001711","name":"Swiss National Science Foundation","doi-asserted-by":"crossref","award":["CR32I3_143768"],"award-info":[{"award-number":["CR32I3_143768"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Bayesian inference is widely used nowadays and relies largely on Markov chain Monte Carlo (MCMC) methods. Evolutionary biology has greatly benefited from the developments of MCMC methods, but the design of more complex and realistic models and the ever growing availability of novel data is pushing the limits of the current use of these methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We present a parallel Metropolis-Hastings (M-H) framework built with a novel combination of enhancements aimed towards parameter-rich and complex models. We show on a parameter-rich macroevolutionary model increases of the sampling speed up to 35 times with 32 processors when compared to a sequential M-H process. More importantly, our framework achieves up to a twentyfold faster convergence to estimate the posterior probability of phylogenetic trees using 32 processors when compared to the well-known software MrBayes for Bayesian inference of phylogenetic trees.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and Implementation<\/jats:title>\n                  <jats:p>https:\/\/bitbucket.org\/XavMeyer\/hogan<\/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\/btw712","type":"journal-article","created":{"date-parts":[[2016,11,11]],"date-time":"2016-11-11T12:05:57Z","timestamp":1478865957000},"page":"669-676","source":"Crossref","is-referenced-by-count":6,"title":["Accelerating Bayesian inference for evolutionary biology models"],"prefix":"10.1093","volume":"33","author":[{"given":"Xavier","family":"Meyer","sequence":"first","affiliation":[{"name":"Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland"},{"name":"Swiss Institute of Bioinformatics, Quartier Sorge, Lausanne, Switzerland"},{"name":"Department of Computer Science, University of Geneva, Geneva, Switzerland"}]},{"given":"Bastien","family":"Chopard","sequence":"additional","affiliation":[{"name":"Swiss Institute of Bioinformatics, Quartier Sorge, Lausanne, Switzerland"},{"name":"Department of Computer Science, University of Geneva, Geneva, Switzerland"}]},{"given":"Nicolas","family":"Salamin","sequence":"additional","affiliation":[{"name":"Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland"},{"name":"Swiss Institute of Bioinformatics, Quartier Sorge, Lausanne, Switzerland"}]}],"member":"286","published-online":{"date-parts":[[2016,12,7]]},"reference":[{"key":"2023020204433249900_btw712-B1","doi-asserted-by":"crossref","first-page":"2553","DOI":"10.1093\/molbev\/msu236","article-title":"Exabayes: massively parallel Bayesian tree inference for the whole-genome era","volume":"31","author":"Aberer","year":"2014","journal-title":"Mol. Biol. Evol"},{"key":"2023020204433249900_btw712-B2","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/s11222-008-9110-y","article-title":"A tutorial on adaptive MCMC","volume":"18","author":"Andrieu","year":"2008","journal-title":"Stat. Comput"},{"key":"2023020204433249900_btw712-B3","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1111\/j.1467-9868.2009.00736.x","article-title":"Particle Markov chain Monte Carlo methods","volume":"72","author":"Andrieu","year":"2010","journal-title":"J. R. Stat. Soc. Ser. B (Stat. Methodol.)"},{"key":"2023020204433249900_btw712-B4","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.1111\/j.1558-5646.2012.01619.x","article-title":"Modeling stabilizing selection: expanding the OrnsteinUhlenbeck Model of adaptive evolution","volume":"66","author":"Beaulieu","year":"2012","journal-title":"Evolution"},{"key":"2023020204433249900_btw712-B5","first-page":"syr131.","article-title":"Phylogenetic inference via sequential Monte Carlo","author":"Bouchard-C\u00f4t\u00e9","year":"2012","journal-title":"Syst. Biol"},{"key":"2023020204433249900_btw712-B6","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1198\/106186006X100579","article-title":"Parallel Markov chain Monte Carlo Simulation by Pre-Fetching","volume":"15","author":"Brockwell","year":"2006","journal-title":"J. Comput. Graph. Stat"},{"key":"2023020204433249900_btw712-B30","doi-asserted-by":"crossref","DOI":"10.1201\/b10905","article-title":"Handbook of Markov Chain Monte Carlo","author":"Brooks","year":"2011"},{"key":"2023020204433249900_btw712-B7","doi-asserted-by":"crossref","first-page":"899","DOI":"10.1109\/JPROC.2007.893250","article-title":"An overview of existing methods and recent advances in Sequential Monte Carlo","volume":"95","author":"Cappe","year":"2007","journal-title":"Proc. IEEE"},{"key":"2023020204433249900_btw712-B8","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1093\/bioinformatics\/btu012","article-title":"Evolutionary footprint of coevolving positions in genes","volume":"30","author":"Dib","year":"2014","journal-title":"Bioinformatics"},{"key":"2023020204433249900_btw712-B9","doi-asserted-by":"crossref","first-page":"e88.","DOI":"10.1371\/journal.pbio.0040088","article-title":"Relaxed Phylogenetics and dating with confidence","volume":"4","author":"Drummond","year":"2006","journal-title":"PLoS Biol"},{"key":"2023020204433249900_btw712-B10","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":"2023020204433249900_btw712-B11","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/0370-2693(87)91197-X","article-title":"Hybrid Monte Carlo","volume":"195","author":"Duane","year":"1987","journal-title":"Phys. Lett. B"},{"year":"2004","author":"Felsenstein","key":"2023020204433249900_btw712-B12"},{"key":"2023020204433249900_btw712-B13","doi-asserted-by":"crossref","first-page":"1450","DOI":"10.1111\/j.1365-294X.2011.05015.x","article-title":"Enhanced AFLP genome scans detect local adaptation in high-altitude populations of a small rodent (Microtus arvalis)","volume":"20","author":"Fischer","year":"2011","journal-title":"Mol. Ecol"},{"key":"2023020204433249900_btw712-B14","doi-asserted-by":"crossref","first-page":"1084","DOI":"10.1111\/j.2041-210X.2012.00234.x","article-title":"Diversitree: comparative phylogenetic analyses of diversification in R","volume":"3","author":"FitzJohn","year":"2012","journal-title":"Methods Ecol. Evol"},{"key":"2023020204433249900_btw712-B15","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1093\/molbev\/msp098","article-title":"INDELible: a flexible simulator of biological sequence evolution","volume":"26","author":"Fletcher","year":"2009","journal-title":"Mol. Biol. Evol"},{"key":"2023020204433249900_btw712-B16","first-page":"599","article-title":"Efficient metropolis jumping rules","author":"Gelman","year":"1996"},{"key":"2023020204433249900_btw712-B17","doi-asserted-by":"crossref","DOI":"10.1201\/b14835","volume-title":"Markov Chain Monte Carlo in Practice","author":"Gilks","year":"1995"},{"key":"2023020204433249900_btw712-B18","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1007\/s11222-015-9574-5","article-title":"Bayesian computation: a summary of the current state, and samples backwards and forwards","volume":"25","author":"Green","year":"2015","journal-title":"Stat. Comput"},{"key":"2023020204433249900_btw712-B19","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":"Bernoulli"},{"key":"2023020204433249900_btw712-B20","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/BF02789703","article-title":"Componentwise adaptation for high dimensional MCMC","volume":"20","author":"Haario","year":"2005","journal-title":"Comput. Stat"},{"key":"2023020204433249900_btw712-B21","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":"2023020204433249900_btw712-B22","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1093\/bioinformatics\/btk051","article-title":"LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters","volume":"22","author":"Kuhner","year":"2006","journal-title":"Bioinformatics"},{"key":"2023020204433249900_btw712-B23","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1080\/10635150801886156","article-title":"Efficiency of Markov chain Monte Carlo tree proposals in Bayesian phylogenetics","volume":"57","author":"Lakner","year":"2008","journal-title":"Syst. Biol"},{"key":"2023020204433249900_btw712-B24","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1080\/10635150500433722","article-title":"Computing Bayes factors using thermodynamic integration","volume":"55","author":"Lartillot","year":"2006","journal-title":"Syst. Biol"},{"key":"2023020204433249900_btw712-B25","first-page":"syt022.","article-title":"PhyloBayes MPI. Phylogenetic reconstruction with infinite mixtures of profiles in a parallel environment","author":"Lartillot","year":"2013","journal-title":"Syst. Biol"},{"volume-title":"Monte Carlo Strategies in Scientific Computing","year":"2008","author":"Liu","key":"2023020204433249900_btw712-B26"},{"key":"2023020204433249900_btw712-B27","doi-asserted-by":"crossref","first-page":"15324","DOI":"10.1073\/pnas.0306899100","article-title":"Markov chain Monte Carlo without likelihoods","volume":"100","author":"Marjoram","year":"2003","journal-title":"Proc. Natl. Acad. Sci. U. S. A"},{"key":"2023020204433249900_btw712-B28","doi-asserted-by":"crossref","first-page":"1321","DOI":"10.1073\/pnas.1208827110","article-title":"Bayesian computation via empirical likelihood","volume":"110","author":"Mengersen","year":"2013","journal-title":"Proc. Natl. Acad. Sci. U. S. A"},{"key":"2023020204433249900_btw712-B29","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.1063\/1.1699114","article-title":"Equation of state calculations by fast computing machines","volume":"21","author":"Metropolis","year":"1953","journal-title":"J. Chem. Phys"},{"key":"2023020204433249900_btw712-B31","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1016\/j.ympev.2011.06.012","article-title":"A large-scale phylogeny of amphibia including over 2800 species, and a revised classification of extant frogs, salamanders, and caecilians","volume":"61","author":"Pyron","year":"2011","journal-title":"Mol. Phylogenet. Evol"},{"key":"2023020204433249900_btw712-B32","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1214\/aoms\/1177729586","article-title":"A stochastic approximation method","volume":"22","author":"Robbins","year":"1951","journal-title":"Ann. Math. Stat"},{"key":"2023020204433249900_btw712-B33","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":"2023020204433249900_btw712-B34","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. Comput. Graph. Stat"},{"key":"2023020204433249900_btw712-B35","first-page":"110","article-title":"Weak convergence and optimal scaling of random walk Metropolis algorithms","volume":"7","author":"Roberts","year":"1997","journal-title":"Ann. Appl. Probab"},{"key":"2023020204433249900_btw712-B36","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":"2023020204433249900_btw712-B37","first-page":"syu006.","article-title":"Bayesian estimation of speciation and extinction from incomplete fossil occurrence data","author":"Silvestro","year":"2014","journal-title":"Syst. Biol"},{"key":"2023020204433249900_btw712-B38","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1111\/2041-210X.12263","article-title":"PyRate: a new program to estimate speciation and extinction rates from incomplete fossil data","volume":"5","author":"Silvestro","year":"2014","journal-title":"Methods Ecol. Evol"},{"key":"2023020204433249900_btw712-B39","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1111\/nph.13247","article-title":"Revisiting the origin and diversification of vascular plants through a comprehensive Bayesian analysis of the fossil record","volume":"2","author":"Silvestro","year":"2015","journal-title":"New Phytol"},{"key":"2023020204433249900_btw712-B40","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1198\/016214505000000664","article-title":"Transdimensional Markov Chains. A decade of progress and future perspectives","volume":"100","author":"Sisson","year":"2005","journal-title":"J. Am. Stat. Assoc"},{"key":"2023020204433249900_btw712-B41","doi-asserted-by":"crossref","first-page":"2814","DOI":"10.1016\/j.csda.2009.11.019","article-title":"Efficient parallelisation of Metropolis-Hastings algorithms using a prefetching approach","volume":"54","author":"Strid","year":"2010","journal-title":"Comput. Stat. Data Anal"},{"key":"2023020204433249900_btw712-B42","first-page":"57","article-title":"Some probabilistic and statistical problems in the analysis of DNA sequences","volume":"17","author":"Tavar\u00e9","year":"1986","journal-title":"Lect. Math. Life Sci"},{"key":"2023020204433249900_btw712-B43","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1007\/s11222-011-9269-5","article-title":"Robust adaptive Metropolis algorithm with coerced acceptance rate","volume":"22","author":"Vihola","year":"2012","journal-title":"Stat. Comput"},{"key":"2023020204433249900_btw712-B44","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1093\/genetics\/155.1.431","article-title":"Codon-substitution models for heterogeneous selection pressure at amino acid sites","volume":"155","author":"Yang","year":"2000","journal-title":"Genetics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/5\/669\/49038005\/bioinformatics_33_5_669.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/5\/669\/49038005\/bioinformatics_33_5_669.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,2]],"date-time":"2023-02-02T04:49:08Z","timestamp":1675313348000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/33\/5\/669\/2733168"}},"subtitle":[],"editor":[{"given":"Janet","family":"Kelso","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2016,12,7]]},"references-count":44,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2017,3,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btw712","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"type":"print","value":"1367-4803"},{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2017,3,1]]},"published":{"date-parts":[[2016,12,7]]}}}