A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes.

• Main Authors: Vagner Fonseca, Pieter J K Libin, Kristof Theys, Nuno R Faria, Marcio R T Nunes, Maria I Restovic, Murilo Freire, Marta Giovanetti, Lize Cuypers, Ann Nowé, Ana Abecasis, Koen Deforche, Gilberto A Santiago, Isadora C de Siqueira, Emmanuel J San, Kaliane C B Machado, Vasco Azevedo, Ana Maria Bispo-de Filippis, Rivaldo Venâncio da Cunha, Oliver G Pybus, Anne-Mieke Vandamme, Luiz C J Alcantara, Tulio de Oliveira
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2019-05-01
• Series: PLoS Neglected Tropical Diseases
• Online Access: https://doi.org/10.1371/journal.pntd.0007231
• ISSN: 1935-2727; 1935-2735

In 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. Available online: http://krisp.org.za/tools.php.