First, we aim to develop computational methods for analyzing viral DNA next-generation sequencing data that allow for predicting HIV-1 drug resistance. Viral DNA isolated from PBMCs is heavily hypermutated; hence statistical methods are needed that can separate hypermutations from causal drug resistance mutations. Second, building on our previous work on V-pipe, we aim at creating a computational pipeline that supports fully automated and reproducible end-to-end analyses of viral next-generation sequencing data in a diagnostic setting. Third, we aim to validate DNA-based drug resistance testing on a large dataset from the Swiss HIV Cohort Study comprising data from over 2000 people living with HIV. We will assess the sensitivity of detecting drug resistance mutations and their predictive value for treatment failure.