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Bootstrapping phylogenies inferred from rearrangement data

Lin, Yu; Rajan, Vaibhav; Moret, Bernard

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Background: Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in...[Show more]

dc.contributor.authorLin, Yu
dc.contributor.authorRajan, Vaibhav
dc.contributor.authorMoret, Bernard
dc.date.accessioned2018-11-29T22:55:54Z
dc.date.available2018-11-29T22:55:54Z
dc.identifier.issn1748-7188
dc.identifier.urihttp://hdl.handle.net/1885/153326
dc.description.abstractBackground: Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date. The standard method used in sequence-based phylogenetic inference is the bootstrap, but it relies on a large number of homologous characters that can be resampled; yet in the case of rearrangements, the entire genome is a single character. Alternatives such as the jackknife suffer from the same problem, while likelihood tests cannot be applied in the absence of well established probabilistic models. Results: We present a new approach to the assessment of distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experimental testing, in both sequence-based and genome-based frameworks. Through the feature-by-feature comparison and the experimental results, we show that our bootstrapping approach is on par with the classic phylogenetic bootstrap used in sequence-based reconstruction, and we establish the clear superiority of the classic bootstrap for sequence data and of our corresponding new approach for rearrangement data over proposed variants. Finally, we test our approach on a small dataset of mammalian genomes, verifying that the support values match current thinking about the respective branches. Conclusions: Our method is the first to provide a standard of assessment to match that of the classic phylogenetic bootstrap for aligned sequences. Its support values follow a similar scale and its receiver-operating characteristics are nearly identical, indicating that it provides similar levels of sensitivity and specificity. Thus our assessment method makes it possible to conduct phylogenetic analyses on whole genomes with the same degree of confidence as for analyses on aligned sequences. Extensions to search-based inference methods such as maximum parsimony and maximum likelihood are possible, but remain to be thoroughly tested.
dc.format.mimetypeapplication/pdf
dc.publisherBioMed Central
dc.sourceAlgorithms for Molecular Biology
dc.titleBootstrapping phylogenies inferred from rearrangement data
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume7
dc.date.issued2012
local.identifier.absfor080201 - Analysis of Algorithms and Complexity
local.identifier.absfor060408 - Genomics
local.identifier.absfor060102 - Bioinformatics
local.identifier.ariespublicationu1046907xPUB43
local.type.statusPublished Version
local.contributor.affiliationLin, Yu, College of Engineering and Computer Science, ANU
local.contributor.affiliationRajan, Vaibhav, École Polytechnique Fédérale de Lausanne (EPFL)
local.contributor.affiliationMoret, Bernard, EPFL
local.bibliographicCitation.issue21
local.identifier.doi10.1186/1748-7188-7-21
dc.date.updated2018-11-29T08:08:51Z
local.identifier.thomsonID000310613700001
dcterms.accessRightsOpen Access
CollectionsANU Research Publications

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