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Abstract

The global prevalence of resistance to antiviral drugs combined with antiretroviral therapy (cART) emphasizes the need for continuous monitoring to better understand the dynamics of drug-resistant mutations to guide treatment optimization and patient management as well as check the spread of resistant viral strains. We have recently, integrated next-generation sequencing (NGS) into routine HIV drug resistance (HIVDR) monitoring, with key challenges in the bioinformatic analysis and interpretation of the complex data generated while ensuring data security and privacy of patient information. To address these challenges, here, we present HIV-DRIVES (HIV Drug Resistance Identification, Variant Evaluation, and Surveillance), an NGS-HIVDR bioinformatics pipeline that has been developed and validated using Illumina short-reads, FASTA, and Sanger ab1.seq files.

Funding
This study was supported by the:
  • PHA4GE (Award INV-038071)
    • Principle Award Recipient: Ivan Sserwadda
  • CAGE-TB Project
    • Principle Award Recipient: Ivan Sserwadda
  • Foundation for the National Institutes of Health (Award U2RTW012116)
    • Principle Award Recipient: Gerald Mboowa
  • Foundation for the National Institutes of Health (Award U2RTW010672)
    • Principle Award Recipient: Gerald Mboowa
  • EDCTP (Award TMA2020CDF-3159)
    • Principle Award Recipient: Gerald Mboowa
  • African Doctoral Dissertation Research Fellowship (ADDRF)
    • Principle Award Recipient: Stephen Kanyerezi
  • Eastern Africa Network of Bioinformatics Training (EANBiT) project
    • Principle Award Recipient: Stephen Kanyerezi
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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/content/journal/acmi/10.1099/acmi.0.000815.v1
2024-03-22
2024-05-15
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http://instance.metastore.ingenta.com/content/journal/acmi/10.1099/acmi.0.000815.v1
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