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HIV-DRLink: A Tool for Reporting Linked HIV-1 Drug Resistance Mutations in Large Single-Genome Datasets Using the Stanford HIV Database

  1. Author:
    Shao,Wei
    Boltz,Valerie
    Hattori, Junko
    Bale, Michael J
    Maldarelli,Frank
    Coffin,John
    Kearney,Mary
  2. Author Address

    Frederick National Laboratory for Cancer Research, 437329, Advanced Biomedical Computing Science, Frederick, Maryland, United States; shaow@mail.nih.gov., National Cancer Institute, 3421, HIV Dynamics & Replication, Frederick, Maryland, United States; boltzv@mail.nih.gov., National Cancer Institute, 3421, HIV Dynamics & Replication, Frederick, Maryland, United States., CMIC Ashfield Co. Ltd., Tokyo, Japan; microbiol101@gmail.com., National Cancer Institute, 3421, HIV Dynamics & Replication, Frederick, Maryland, United States; michael.bale@nih.gov., National Cancer Institute, 3421, HIV Dynamics & Replication, Frederick, Maryland, United States; fmalli@mail.nih.gov., Tufts University, Molecular Biology, 136 Harrison Ave, Boston, Massachusetts, United States, 02111; john.coffin@tufts.edu., National Cancer Institute, HIV Dynamics & Replication, Frederick, Maryland, United States; kearneym@mail.nih.gov.,
    1. Year: 2020
    2. Date: AUG 27
    3. Epub Date: 2020 07 19
  1. Journal: AIDS research and human retroviruses
  2. Type of Article: Article
  3. ISSN: 0889-2229
  1. Abstract:

    The prevalence of HIV-1 drug resistance is increasing worldwide and monitoring its emergence is important for the successful management of populations receiving combination antiretroviral therapy. It is likely that pre-existing drug resistance mutations linked on the same viral genomes are predictive of treatment failure. Because of the large numbers of sequences generated by Ultrasensitive Single-Genome Sequencing (uSGS) and other similar next-generation sequencing methods, it is difficult to assess each sequence individually for linked drug resistance mutations. Several software/programs exist to report the frequencies of individual mutations in large datasets, but they provide no information on linkage of resistance mutations. Here, we report the HIV-DRLink program, a research tool that provides resistance mutation frequencies as well as their genetic linkage by parsing and summarizing the Sierra output from the Stanford HIV Database (https://hivdb.stanford.edu/). The HIV-DRLink program should only be used on datasets generated by methods that eliminate artifacts due to PCR recombination, for example, standard Single-Genome Sequencing (SGS) or uSGS. HIV-DRLink is exclusively a research tool and is not intended to inform clinical decisions.

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External Sources

  1. DOI: 10.1089/AID.2020.0109
  2. PMID: 32683881
  3. WOS: 000565925300001

Library Notes

  1. Fiscal Year: FY2019-2020
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