Stephen Kanyerezi, Ivan Sserwadda, A. Ssemaganda, Julius Seruyange, Alisen Ayitewala, Hellen Rosette Oundo, Wilson Tenywa, Brian A. Kagurusi, Godwin Tusabe, Stacy Were, Isaac Ssewanyana, Susan Nabadda, Maria Magdalene Namaganda, Gerald Mboowa
{"title":"HIV-DRIVES: HIV drug resistance identification, variant evaluation, and surveillance pipeline","authors":"Stephen Kanyerezi, Ivan Sserwadda, A. Ssemaganda, Julius Seruyange, Alisen Ayitewala, Hellen Rosette Oundo, Wilson Tenywa, Brian A. Kagurusi, Godwin Tusabe, Stacy Were, Isaac Ssewanyana, Susan Nabadda, Maria Magdalene Namaganda, Gerald Mboowa","doi":"10.1099/acmi.0.000815.v3","DOIUrl":null,"url":null,"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 for 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.","PeriodicalId":6956,"journal":{"name":"Access Microbiology","volume":"180 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Access Microbiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1099/acmi.0.000815.v3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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 for 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.