ClusterV-Web: A User-Friendly Tool for Profiling HIV Quasispecies and Generating Drug Resistance Reports from Nanopore Long-Read Data

Abstract

AbstractSummaryThird-generation long-read sequencing is an increasingly utilized technique for profiling HIV quasispecies and detecting drug resistance mutations due to its ability to cover the entire viral genome in individual reads. Recently, the ClusterV tool has demonstrated accurate detection of HIV quasispecies from Nanopore long-read sequencing data. However, the need for scripting skills and a computational environment may act as a barrier for many potential users. To address this issue, we have introduced ClusterV-Web, a user-friendly web-based application that enables easy configuration and execution of ClusterV, both remotely and locally. Our tool provides interactive tables and data visualizations to aid in the interpretation of results. This development is expected to democratize access to long-read sequencing data analysis, enabling a wider range of researchers and clinicians to efficiently profile HIV quasispecies and detect drug resistance mutations.Availability and implementationClusterV-Web is freely available and open source, with detailed documentation accessible athttp://www.bio8.cs.hku.hk/ClusterVW/. The standalone Docker image and source code are also available athttps://github.com/HKU-BAL/ClusterV-Web.Contactrbluo@cs.hku.hk, Department of Computer Science, The University of Hong Kong, Hong Kong, China;jhsu@cs.hku.hk, Department of Computer Science, The University of Hong Kong, Hong Kong, ChinaSupplementary informationNone