SIRA-HIV: A User-friendly System to Evaluate HIV-1 Drug Resistance from Next-generation Sequencing Data

Letícia Martins Raposo, Letícia Martins Raposo, Mônica Barcellos Arruda, Rodrigo de Moraes Brindeiro, Flavio Fonseca Nobre

2020

Abstract

Evaluating next-generation sequencing (NGS) data requires an extensive knowledge of bioinformatics and programming commands, which could limit the studies in this area. We propose a user-friendly system to analyse raw NGS data from HIV-1 patient samples to identify amino acid variants and the virus susceptibility to antiretrovirals. SIRA-HIV was developed as an R Shiny web application. The software Segminator II was applied to analyse viral data. Four genotypic interpretation systems were implemented in R language to classify the HIV susceptibility: the French National Agency for AIDS Research (ANRS), the Stanford HIV Drug Resistance Database (HIVdb), the Rega Institute (Rega) and the Brazilian Network for HIV-1 Genotyping (Brazilian Algorithm). SIRA-HIV was structured in two analysis components. The Drug Resistance Positions module shows the resistance positions, their frequencies, and the coverage. In the Genotypic Resistance Interpretation Algorithms module, the rule-based systems are available to interpret HIV-1 drug resistance genotyping results. SIRA-HIV exhibited comparable results to Deep Gen HIV, HyDRA, and PASeq. As advantage, the proposed application shows susceptibility levels from the most widely used rule-based systems and works locally, allowing analysis not to rely on the internet. SIRA-HIV could be a promising system to aid in HIV-1 patient data analysis.

Paper Citation

in Harvard Style

Raposo L., Arruda M., Brindeiro R. and Nobre F. (2020). SIRA-HIV: A User-friendly System to Evaluate HIV-1 Drug Resistance from Next-generation Sequencing Data. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 3: BIOINFORMATICS; ISBN 978-989-758-398-8, SciTePress, pages 93-100. DOI: 10.5220/0008874700930100

in Bibtex Style

@conference{bioinformatics20,
author={Letícia Martins Raposo and Mônica Barcellos Arruda and Rodrigo de Moraes Brindeiro and Flavio Fonseca Nobre},
title={SIRA-HIV: A User-friendly System to Evaluate HIV-1 Drug Resistance from Next-generation Sequencing Data},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 3: BIOINFORMATICS},
year={2020},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008874700930100},
isbn={978-989-758-398-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 3: BIOINFORMATICS
TI - SIRA-HIV: A User-friendly System to Evaluate HIV-1 Drug Resistance from Next-generation Sequencing Data
SN - 978-989-758-398-8
AU - Raposo L.
AU - Arruda M.
AU - Brindeiro R.
AU - Nobre F.
PY - 2020
SP - 93
EP - 100
DO - 10.5220/0008874700930100
PB - SciTePress