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

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

doi:10.1371/journal.pntd.0007231

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

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 PybusAnne-Mieke Vandamme, Luiz C J Alcantara, Tulio 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. Available online: http://krisp.org.za/tools.php.

Original language	English
Article number	e0007231
Number of pages	14
Journal	PLoS Neglected Tropical Diseases
Volume	13
Issue number	5
DOIs	https://doi.org/10.1371/journal.pntd.0007231
Publication status	Published - 2019

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Fonseca, V., 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, A., Deforche, K., Santiago, G. A., Siqueira, I. C. D., San, E. J., Machado, K. C. B., Azevedo, V., Filippis, A. M. B., Cunha, R. V. D., ... 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. Available online: http://krisp.org.za/tools.php.",

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Fonseca, V, Libin, PJK, Theys, K, Faria, NR, Nunes, MRT, Restovic, MI, Freire, M, Giovanetti, M, Cuypers, L, Nowé, A, Abecasis, A, Deforche, K, Santiago, GA, Siqueira, ICD, San, EJ, Machado, KCB, Azevedo, V, Filippis, AMB, Cunha, RVD, Pybus, OG, Vandamme, A-M, Alcantara, LCJ & de Oliveira, T 2019, 'A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes', PLoS Neglected Tropical Diseases, vol. 13, no. 5, e0007231. https://doi.org/10.1371/journal.pntd.0007231

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T1 - A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes

AU - Fonseca, Vagner

AU - Libin, Pieter J K

AU - Theys, Kristof

AU - Faria, Nuno R

AU - Nunes, Marcio R T

AU - Restovic, Maria I

AU - Freire, Murilo

AU - Giovanetti, Marta

AU - Cuypers, Lize

AU - Nowé, Ann

AU - Abecasis, Ana

AU - Deforche, Koen

AU - Santiago, Gilberto A

AU - Siqueira, Isadora C de

AU - San, Emmanuel J

AU - Machado, Kaliane C B

AU - Azevedo, Vasco

AU - Filippis, Ana Maria Bispo-de

AU - Cunha, Rivaldo Venâncio da

AU - Pybus, Oliver G

AU - Vandamme, Anne-Mieke

AU - Alcantara, Luiz C J

AU - de Oliveira, Tulio

PY - 2019

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

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SN - 1935-2727

VL - 13

JO - PLoS Neglected Tropical Diseases

JF - PLoS Neglected Tropical Diseases

IS - 5

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ER -

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

Abstract

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FWOTM1058: Real-time geospatial control of emerging infectious diseases

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

Abstract

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FWOTM1058: Real-time geospatial control of emerging infectious diseases

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