HIV-DRLink: a tool for reporting linked HIV-1 drug resistance mutations in large single-genome data sets using the Stanford HIV database

W Shao, VF Boltz, J Hattori, MJ Bale… - AIDS Research and …, 2020 - liebertpub.com
W Shao, VF Boltz, J Hattori, MJ Bale, F Maldarelli, JM Coffin, MF Kearney
AIDS Research and Human Retroviruses, 2020liebertpub.com
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 …
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.
Mary Ann Liebert