Literature DB >> 32683881

Short Communication: HIV-DRLink: A Tool for Reporting Linked HIV-1 Drug Resistance Mutations in Large Single-Genome Data Sets Using the Stanford HIV Database.

Wei Shao1, Valerie F Boltz2, Junko Hattori2, Michael J Bale2, Frank Maldarelli2, John M Coffin3, Mary F Kearney2.   

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 number 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 data sets, but they provide no information on linkage of resistance mutations. In this study, 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. The HIV-DRLink program should only be used on data sets generated by methods that eliminate artifacts due to polymerase chain reaction recombination, for example, standard single-genome sequencing or uSGS. HIV-DRLink is exclusively a research tool and is not intended to inform clinical decisions.

Entities:  

Keywords:  HIV; HIV-DRLink; Stanford HIVdb; linked drug resistance mutations; next-generation sequencing; uSGS

Year:  2020        PMID: 32683881      PMCID: PMC7699007          DOI: 10.1089/AID.2020.0109

Source DB:  PubMed          Journal:  AIDS Res Hum Retroviruses        ISSN: 0889-2229            Impact factor:   2.205


  27 in total

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Authors:  Michele W Tang; Tommy F Liu; Robert W Shafer
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2.  Primer ID Validates Template Sampling Depth and Greatly Reduces the Error Rate of Next-Generation Sequencing of HIV-1 Genomic RNA Populations.

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4.  VirVarSeq: a low-frequency virus variant detection pipeline for Illumina sequencing using adaptive base-calling accuracy filtering.

Authors:  Bie M P Verbist; Kim Thys; Joke Reumers; Yves Wetzels; Koen Van der Borght; Willem Talloen; Jeroen Aerssens; Lieven Clement; Olivier Thas
Journal:  Bioinformatics       Date:  2014-08-31       Impact factor: 6.937

5.  Linked dual-class HIV resistance mutations are associated with treatment failure.

Authors:  Valerie F Boltz; Wei Shao; Michael J Bale; Elias K Halvas; Brian Luke; James A McIntyre; Robert T Schooley; Shahin Lockman; Judith S Currier; Fred Sawe; Evelyn Hogg; Michael D Hughes; Mary F Kearney; John M Coffin; John W Mellors
Journal:  JCI Insight       Date:  2019-10-03

6.  HIV population dynamics in vivo: implications for genetic variation, pathogenesis, and therapy.

Authors:  J M Coffin
Journal:  Science       Date:  1995-01-27       Impact factor: 47.728

7.  Prevalence of HIV-1 transmitted drug resistance in the incarcerated population.

Authors:  J Sapozhnikov; J D Young; M Patel; T D Chiampas; P Vaughn; M E Badowski
Journal:  HIV Med       Date:  2017-06-06       Impact factor: 3.180

8.  Effectiveness and cost-effectiveness of potential responses to future high levels of transmitted HIV drug resistance in antiretroviral drug-naive populations beginning treatment: modelling study and economic analysis.

Authors:  Andrew N Phillips; Valentina Cambiano; Alec Miners; Paul Revill; Deenan Pillay; Jens D Lundgren; Diane Bennett; Elliott Raizes; Fumiyo Nakagawa; Andrea De Luca; Marco Vitoria; Jhoney Barcarolo; Joseph Perriens; Michael R Jordan; Silvia Bertagnolio
Journal:  Lancet HIV       Date:  2014-10-14       Impact factor: 12.767

9.  Analysis of 454 sequencing error rate, error sources, and artifact recombination for detection of Low-frequency drug resistance mutations in HIV-1 DNA.

Authors:  Wei Shao; Valerie F Boltz; Jonathan E Spindler; Mary F Kearney; Frank Maldarelli; John W Mellors; Claudia Stewart; Natalia Volfovsky; Alexander Levitsky; Robert M Stephens; John M Coffin
Journal:  Retrovirology       Date:  2013-02-13       Impact factor: 4.602

10.  HIV-1 drug resistance before initiation or re-initiation of first-line antiretroviral therapy in low-income and middle-income countries: a systematic review and meta-regression analysis.

Authors:  Ravindra K Gupta; John Gregson; Neil Parkin; Hiwot Haile-Selassie; Amilcar Tanuri; Liliana Andrade Forero; Pontiano Kaleebu; Christine Watera; Avelin Aghokeng; Nicholus Mutenda; Janet Dzangare; San Hone; Zaw Zaw Hang; Judith Garcia; Zully Garcia; Paola Marchorro; Enrique Beteta; Amalia Giron; Raph Hamers; Seth Inzaule; Lisa M Frenkel; Michael H Chung; Tulio de Oliveira; Deenan Pillay; Kogie Naidoo; Ayesha Kharsany; Ruthiran Kugathasan; Teresa Cutino; Gillian Hunt; Santiago Avila Rios; Meg Doherty; Michael R Jordan; Silvia Bertagnolio
Journal:  Lancet Infect Dis       Date:  2017-12-05       Impact factor: 25.071

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  1 in total

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Journal:  Cell       Date:  2022-01-12       Impact factor: 41.582

  1 in total

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