Mostrar el registro sencillo del ítem

hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
hal.structure.identifierPleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
dc.contributor.authorABOUABDALLAH, Mohamed Anwar
hal.structure.identifierUnité de Mathématiques et Informatique Appliquées de Toulouse [MIAT INRAE]
dc.contributor.authorPEYRARD, Nathalie
hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
hal.structure.identifierPleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
dc.contributor.authorFRANC, Alain
dc.date.issued2022
dc.identifier.issn1755-098X
dc.description.abstractEnCharacterizing biodiversity is one of the main challenges for the coming decades. Most diversity has not been morphologically described, and barcoding is now complementing morphological-based taxonomy to further develop inventories. Both approaches have been cross-validated at the level of species and OTUs. However, many known species are not listed in reference databases. One path to speed up inventories using barcoding is to directly identify individuals at coarser taxonomic levels. We therefore studied in barcoding of plants whether morphological-based and molecular-based approaches are in agreement at genus, family and order levels. We used Agglomerative Hierarchical Clustering (with Ward, Complete and Single Linkage) and Stochastic Block Models (SBM), with two dissimilarity measures (Smith-Waterman scores, kmers). The agreement between morphological-based and molecular-based classifications ranges in most of the cases from good to very good at taxonomic levels above species, even though it decreases when taxonomic levels increase, or when using the tetramer-based distance. Agreement is correlated with the entropy of morphological-based classification and with the ratio of the mean within- and mean between-groups dissimilarities. The Ward method globally leads to the best agreement, whereas Single Linkage can show poor behaviours. SBM provides a useful tool to test whether or not the dissimilarities are structured by the botanical groups. These results suggest that automatic clustering and group identification at taxonomic levels above species are possible in barcoding.
dc.description.sponsorshipCEnter of the study of Biodiversity in Amazonia - ANR-10-LABX-0025
dc.language.isoen
dc.publisherWiley/Blackwell
dc.subject.enbarcoding
dc.subject.enclustering
dc.subject.enFrench Guianan trees
dc.subject.enstochastic block model
dc.subject.entaxonomy
dc.subject.enWard method
dc.title.enDoes clustering of DNA barcodes agree with botanical classification directly at high taxonomic levels? Trees in French Guiana as a case study
dc.typeArticle de revue
dc.identifier.doi10.1111/1755-0998.13579
dc.subject.halSciences de l'environnement
bordeaux.journalMolecular Ecology Resources
bordeaux.peerReviewedoui
hal.identifierhal-03546609
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03546609v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Molecular%20Ecology%20Resources&rft.date=2022&rft.eissn=1755-098X&rft.issn=1755-098X&rft.au=ABOUABDALLAH,%20Mohamed%20Anwar&PEYRARD,%20Nathalie&FRANC,%20Alain&rft.genre=article


Archivos en el ítem

ArchivosTamañoFormatoVer

No hay archivos asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem