Asymptotic guarantees for Bayesian phylogenetic tree reconstruction

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dc.contributor.authorKirichenko, Alisaen
dc.contributor.authorKelly, Luke J.en
dc.contributor.authorKoskela, Jereen
dc.contributor.funderAgence Nationale de la Rechercheen
dc.contributor.funderUK Research and Innovationen
dc.date.accessioned2025-08-01T13:01:19Z
dc.date.available2025-08-01T13:01:19Z
dc.date.issued2025-07-23en
dc.description.abstractWe derive tractable criteria for the consistency of Bayesian tree reconstruction procedures, which constitute a central class of algorithms for inferring common ancestry among DNA sequence samples in phylogenetics. Our results encompass several Bayesian algorithms in widespread use, such as BEAST, MrBayes, and RevBayes. Unlike essentially all existing asymptotic guarantees for tree reconstruction, we require no discretization or boundedness assumptions on branch lengths. Our results are also very flexible, and easy to adapt to variations of the underlying inference problem. We demonstrate the practicality of our criteria on two examples: a Kingman coalescent prior on rooted, ultrametric trees, and an independence prior on unconstrained binary trees, though we emphasize that our result also applies to nonbinary tree models. In both cases, the convergence rate we obtain matches known, frequentist results obtained using stronger boundedness assumptions, up to logarithmic factors. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationKirichenko, A., Kelly, L.J. and Koskela, J. (2025) ‘Asymptotic guarantees for Bayesian phylogenetic tree reconstruction’, Journal of the American Statistical Association, pp. 1–11. https://doi.org/10.1080/01621459.2025.2485359en
dc.identifier.doi10.1080/01621459.2025.2485359en
dc.identifier.eissn1537-274Xen
dc.identifier.issn0162-1459en
dc.identifier.journaltitleJournal of the American Statistical Associationen
dc.identifier.urihttps://hdl.handle.net/10468/17769
dc.language.isoenen
dc.publisherTaylor & Francisen
dc.relation.projectinfo:eu-repo/grantAgreement/ANR//ANR-18-CE40-0034/FR/Approximate Bayesian solutions for the interpretation of large datasets and complex models/ABSinten
dc.relation.projectinfo:eu-repo/grantAgreement/ANR//ANR-19-P3IA-0001/FR//PRAIRIEen
dc.relation.projectinfo:eu-repo/grantAgreement/UKRI/EPSRC/EP/V049208/1/GB/Mathematical foundations of non-reversible MCMC for genome-scale inference/en
dc.rights© 2025 The Author(s). Published with license by Taylor & Francis Group, LLC. This 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 use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.rights.licensehttp://creativecommons.org/licenses/by/4.0/
dc.subjectBayesian methodsen
dc.subjectCoalescent processen
dc.subjectPhylogenetic treeen
dc.subjectPosteriorconsistencyen
dc.titleAsymptotic guarantees for Bayesian phylogenetic tree reconstructionen
dc.typeArticle (peer-reviewed)en
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