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THETA

Authors :
Nicolas Jeanne
Caroline Lefebvre
Pierre Delobel
Romain Carcenac
Florence Nicot
Chloé Dimeglio
Stéphanie Raymond
Christelle Reynes
Michelle Cazabat
Jacques Izopet
Laboratoire de Virologie [Toulouse]
CHU Toulouse [Toulouse]
Centre de Physiopathologie Toulouse Purpan (CPTP)
Université Toulouse III - Paul Sabatier (UT3)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Institut de Génomique Fonctionnelle (IGF)
Université de Montpellier (UM)-Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS)
Service des maladies infectieuses et tropicales [Toulouse]
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Hôpital Purpan [Toulouse]
Source :
Bioinformatics, Bioinformatics, Oxford University Press (OUP), 2019, 36 (2), pp.416-421. ⟨10.1093/bioinformatics/btz585⟩
Publication Year :
2019
Publisher :
Oxford University Press (OUP), 2019.

Abstract

Motivation The circulating recombinant form of HIV-1 CRF02-AG is the most frequent non-B subtype in Europe. Anti-HIV therapy and pathophysiological studies on the impact of HIV-1 tropism require genotypic determination of HIV-1 tropism for non-B subtypes. But genotypic approaches based on analysis of the V3 envelope region perform poorly when used to determine the tropism of CRF02-AG. We, therefore, designed an algorithm based on information from the gp120 and gp41 ectodomain that better predicts the tropism of HIV-1 subtype CRF02-AG. Results We used a bio-statistical method to identify the genotypic determinants of CRF02-AG coreceptor use. Toulouse HIV Extended Tropism Algorithm (THETA), based on a Least Absolute Shrinkage and Selection Operator method, uses HIV envelope sequence from phenotypically characterized clones. Prediction of R5X4/X4 viruses was 86% sensitive and that of R5 viruses was 89% specific with our model. The overall accuracy of THETA was 88%, making it sufficiently reliable for predicting the tropism of subtype CRF02-AG sequences. Availability and implementation Binaries are freely available for download at https://github.com/viro-tls/THETA. It was implemented in Matlab and supported on MS Windows platform. The sequence data used in this work are available from GenBank under the accession numbers MK618182-MK618417.

Details

ISSN :
13674811 and 13674803
Volume :
36
Database :
OpenAIRE
Journal :
Bioinformatics
Accession number :
edsair.doi.dedup.....4d6bcb55088e4a6b127e700f67f7e55d
Full Text :
https://doi.org/10.1093/bioinformatics/btz585