Drug resistance mutations in HIV: new bioinformatics approaches and challenges

Luc Blassel, Anna Zhukova, Christian J Villabona-Arenas, Katherine E Atkins, Stéphane Hué, Olivier Gascuel

Abstract: Highlights•Machine learning is increasingly used to predict and understand drug resistance in HIV.•Phylogenetics helps to track the emergence and spread of HIV drug resistance mutations.•Deep sequencing accurately measures within-host HIV genetic diversity and low frequency resistant variants.•Confidentiality, securely and accessibly sharing of sequence data and associated metadata remain a challenge.

External IDs:doi:10.1016/j.coviro.2021.09.009