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dc.contributor.authorZhu, Ten_US
dc.contributor.authorDos Reis, Men_US
dc.contributor.authorYang, Zen_US
dc.date.accessioned2016-10-03T15:01:19Z
dc.date.issued2015-03en_US
dc.date.submitted2016-07-22T19:19:49.572Z
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/15695
dc.description.abstractGenetic sequence data provide information about the distances between species or branch lengths in a phylogeny, but not about the absolute divergence times or the evolutionary rates directly. Bayesian methods for dating species divergences estimate times and rates by assigning priors on them. In particular, the prior on times (node ages on the phylogeny) incorporates information in the fossil record to calibrate the molecular tree. Because times and rates are confounded, our posterior time estimates will not approach point values even if an infinite amount of sequence data are used in the analysis. In a previous study we developed a finite-sites theory to characterize the uncertainty in Bayesian divergence time estimation in analysis of large but finite sequence data sets under a strict molecular clock. As most modern clock dating analyses use more than one locus and are conducted under relaxed clock models, here we extend the theory to the case of relaxed clock analysis of data from multiple loci (site partitions). Uncertainty in posterior time estimates is partitioned into three sources: Sampling errors in the estimates of branch lengths in the tree for each locus due to limited sequence length, variation of substitution rates among lineages and among loci, and uncertainty in fossil calibrations. Using a simple but analogous estimation problem involving the multivariate normal distribution, we predict that as the number of loci ([Formula: see text]) goes to infinity, the variance in posterior time estimates decreases and approaches the infinite-data limit at the rate of 1/[Formula: see text], and the limit is independent of the number of sites in the sequence alignment. We then confirmed the predictions by using computer simulation on phylogenies of two or three species, and by analyzing a real genomic data set for six primate species. Our results suggest that with the fossil calibrations fixed, analyzing multiple loci or site partitions is the most effective way for improving the precision of posterior time estimation. However, even if a huge amount of sequence data is analyzed, considerable uncertainty will persist in time estimates.en_US
dc.description.sponsorshipThis work was supported by a grant from the Biotechnological and Biological Sciences Research Council (BB/J009709/1) to Z.Y., and grants from Natural Science Foundation of China (31301093, 11301294 and 11201224) to T.Z.en_US
dc.format.extent267 - 280en_US
dc.languageengen_US
dc.relation.ispartofSyst Biolen_US
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.subjectBayesian inferenceen_US
dc.subjectdivergence timeen_US
dc.subjectfinite-sites theoryen_US
dc.subjectinfinite-sites theoryen_US
dc.subjectposterior varianceen_US
dc.subjectrelaxed clocken_US
dc.subjectAnimalsen_US
dc.subjectClassificationen_US
dc.subjectComputer Simulationen_US
dc.subjectFossilsen_US
dc.subjectModels, Geneticen_US
dc.subjectPhylogenyen_US
dc.subjectPrimatesen_US
dc.subjectSequence Analysis, DNAen_US
dc.subjectTimeen_US
dc.subjectUncertaintyen_US
dc.titleCharacterization of the uncertainty of divergence time estimation under relaxed molecular clock models using multiple loci.en_US
dc.typeArticle
dc.rights.holder© The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.
dc.identifier.doi10.1093/sysbio/syu109en_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/25503979en_US
pubs.issue2en_US
pubs.notesNot knownen_US
pubs.organisational-group/Queen Mary University of London
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering/Biological and Chemical Sciences - Staff
pubs.publication-statusPublisheden_US
pubs.volume64en_US


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