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Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection

hal.structure.identifierGembloux Agro-Bio Tech [Gembloux]
dc.contributor.authorTAMISIER, Lucie
hal.structure.identifierResearch Institute for Agricultural, Fisheries and Food [ILVO]
dc.contributor.authorHAEGEMAN, Annelies
hal.structure.identifierResearch Institute for Agricultural, Fisheries and Food [ILVO]
dc.contributor.authorFOUCART, Yoika
hal.structure.identifierGembloux Agro-Bio Tech [Gembloux]
dc.contributor.authorFOUILLIEN, Nicolas
hal.structure.identifierUniversity of California- Davis [UCDAVIS]
dc.contributor.authorRWAHNIH, Maher Al
hal.structure.identifierKahramanmaras Sutcu Imam Univ
dc.contributor.authorBUZKAN, Nihal
hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorCANDRESSE, Thierry
hal.structure.identifierCNR Istituto per la Protezione Sostenibile delle Piante [Torino, Italia] [IPSP]
dc.contributor.authorCHIUMENTI, Michela
hal.structure.identifierResearch Institute for Agricultural, Fisheries and Food [ILVO]
dc.contributor.authorJONGHE, Kris De
hal.structure.identifierPlateforme Exploration du Métabolisme [PFEM]
hal.structure.identifierInstitut National de la Recherche Agronomique [INRA]
hal.structure.identifierUniversité Blaise Pascal - Clermont-Ferrand 2 [UBP]
hal.structure.identifierMetaboHUB-Clermont
hal.structure.identifierMetaboHUB
hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorLEFEBVRE, Marie
hal.structure.identifierLeibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH / Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures [DSMZ]
dc.contributor.authorMARGARIA, Paolo
hal.structure.identifierAgroscope
dc.contributor.authorREYNARD, Jean-Sébastien
hal.structure.identifierUniversity of California [Davis] [UC Davis]
dc.contributor.authorSTEVENS, Kristian
hal.structure.identifierNational Institute of Biology [Ljubljana] [NIB]
dc.contributor.authorKUTNJAK, Denis
dc.date.accessioned2024-04-11T10:06:46Z
dc.date.available2024-04-11T10:06:46Z
dc.date.conference2021-04-20
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/197560
dc.description.abstractEnIn the last decade, High-Throughput Sequencing (HTS) has revolutionized plant virus discovery and diagnosis. Currently, many bioinformatics pipelines for virus detection are available, making the choice of a suitable one difficult. A robust benchmarking is needed for the unbiased comparison of the pipelines.We present 7 semi-artificial datasets composed of real RNA-seq datasets from virus-infected plants spiked with artificial virus reads. Each dataset addresses challenges that could prevent virus detection (i.e. low viral concentration, new viral species, non-complete virus genome, etc). We also present 3 real datasets showing a challenging virus composition as well as 8 completely artificial datasets to test haplotype reconstruction software. With these datasets, we hope to encourage virologists, diagnosticians and bioinformaticians to evaluate and benchmark their pipeline(s).
dc.language.isoen
dc.title.enSemi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection
dc.typeAutre communication scientifique (congrès sans actes - poster - séminaire...)
dc.subject.halSciences du Vivant [q-bio]
bordeaux.hal.laboratoriesBiologie du Fruit & Pathologie (BFP) - UMR 1332*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionINRAE
bordeaux.conference.titleInternational Advances in Plant Virology
bordeaux.countryFR
bordeaux.conference.cityAvignon (en ligne)
bordeaux.peerReviewedoui
hal.identifierhal-04315151
hal.version1
hal.invitednon
hal.proceedingsnon
hal.conference.end2021-04-22
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04315151v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=TAMISIER,%20Lucie&HAEGEMAN,%20Annelies&FOUCART,%20Yoika&FOUILLIEN,%20Nicolas&RWAHNIH,%20Maher%20Al&rft.genre=conference


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