A computational method for the identification of dengue, zika and chikungunya virus species and genotypes

Vagner S. Fonseca; Pieter J. K. Libin; Kristof Theys; Nuno Rodrigues Faria; Márcio Roberto Texeira Nunes; Maria I. Restovic; Murilo Freire; Marta Giovanetti; Lize Cuypers; Ann Nowé; AB Abecasis; Koen Deforche; Gilberto A. Santiago; Isadora Cristina de Siqueira; Emmanuel J. San; Kaliane C.B. Machado; Vasco Ariston De Carvalho Azevedo; Ana Maria Bispo de Filippis; Rivaldo Venâncio da Cunha; Oliver George Pybus; AM Vandamme; L. C. J. Alcantara; Túlio de Oliveira

doi:10.1371/journal.pntd.0007231

A computational method for the identification of dengue, zika and chikungunya virus species and genotypes

Vagner S. Fonseca, Pieter J. K. Libin, Kristof Theys, Nuno Rodrigues Faria, Márcio Roberto Texeira Nunes, Maria I. Restovic, Murilo Freire, Marta Giovanetti, Lize Cuypers, Ann Nowé, AB Abecasis, Koen Deforche, Gilberto A. Santiago, Isadora Cristina de Siqueira, Emmanuel J. San, Kaliane C.B. Machado, Vasco Ariston De Carvalho Azevedo, Ana Maria Bispo de Filippis, Rivaldo Venâncio da Cunha, Oliver George PybusAM Vandamme, L. C. J. Alcantara, Túlio de Oliveira

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Abstract

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.

Original language	English
Article number	e0007231
Number of pages	15
Journal	PLoS Neglected Tropical Diseases
Volume	13
Issue number	5
DOIs	https://doi.org/10.1371/journal.pntd.0007231
Publication status	Published - 8 May 2019

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10.1371/journal.pntd.0007231Licence: CC BY

A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypesFinal published version, 1.42 MBLicence: CC BY

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Fonseca, V. S., Libin, P. J. K., Theys, K., Faria, N. R., Nunes, M. R. T., Restovic, M. I., Freire, M., Giovanetti, M., Cuypers, L., Nowé, A., Abecasis, AB., Deforche, K., Santiago, G. A., de Siqueira, I. C., San, E. J., Machado, K. C. B., Azevedo, V. A. D. C., de Filippis, A. M. B., da Cunha, R. V., ... de Oliveira, T. (2019). A computational method for the identification of dengue, zika and chikungunya virus species and genotypes. PLoS Neglected Tropical Diseases, 13(5), Article e0007231. https://doi.org/10.1371/journal.pntd.0007231

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abstract = "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.",

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AU - Fonseca, Vagner S.

AU - Libin, Pieter J. K.

AU - Theys, Kristof

AU - Faria, Nuno Rodrigues

AU - Nunes, Márcio Roberto Texeira

AU - Restovic, Maria I.

AU - Freire, Murilo

AU - Giovanetti, Marta

AU - Cuypers, Lize

AU - Nowé, Ann

AU - Abecasis, AB

AU - Deforche, Koen

AU - Santiago, Gilberto A.

AU - de Siqueira, Isadora Cristina

AU - San, Emmanuel J.

AU - Machado, Kaliane C.B.

AU - Azevedo, Vasco Ariston De Carvalho

AU - de Filippis, Ana Maria Bispo

AU - da Cunha, Rivaldo Venâncio

AU - Pybus, Oliver George

AU - Vandamme, AM

AU - Alcantara, L. C. J.

AU - de Oliveira, Túlio

PY - 2019/5/8

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AB - 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.

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A computational method for the identification of dengue, zika and chikungunya virus species and genotypes

Abstract

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