Fonseca, Vagner S.Libin, Pieter J. K.Theys, KristofFaria, Nuno RodriguesNunes, Márcio Roberto TexeiraRestovic, Maria I.Freire, MuriloGiovanetti, MartaCuypers, LizeNowé, AnnAbecasis, ABDeforche, KoenSantiago, Gilberto A.de Siqueira, Isadora CristinaSan, Emmanuel J.Machado, Kaliane C.B.Azevedo, Vasco Ariston De Carvalhode Filippis, Ana Maria Bispoda Cunha, Rivaldo VenâncioPybus, Oliver GeorgeVandamme, AMAlcantara, L. C. J.de Oliveira, Túlio2021-05-022021-05-022019-05-081935-2727PURE: 15187331PURE UUID: 48d5256a-8736-4bd8-a9d7-1a24da475916Scopus: 85066456449PubMed: 31067235PubMedCentral: PMC6527240http://hdl.handle.net/10362/116728In recent years, an increasing number of outbreaks of Dengue, Chikungunya and Zika viruses have been reported in Asia and the Americas. Monitoring virus genotype diversity is crucial to understand the emergence and spread of outbreaks, both aspects that are vital to develop effective prevention and treatment strategies. Hence, we developed an efficient method to classify virus sequences with respect to their species and sub-species (i.e. serotype and/or genotype). This tool provides an easy-to-use software implementation of this new method and was validated on a large dataset assessing the classification performance with respect to whole-genome sequences and partial-genome sequences.151483805engComputer Science ApplicationsVirologyInfectious DiseasesGeneticsSDG 3 - Good Health and Well-beingjournal article10.1371/journal.pntd.0007231https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0007231