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ClusterV-Web:一种用户友好的工具,用于分析HIV准种并根据纳米孔长读长数据生成耐药性报告。

ClusterV-Web: a user-friendly tool for profiling HIV quasispecies and generating drug resistance reports from nanopore long-read data.

作者信息

Su Junhao, Li Shumin, Zheng Zhenxian, Lam Tak-Wah, Luo Ruibang

机构信息

Department of Computer Science, The University of Hong Kong, Hong Kong 999077, China.

出版信息

Bioinform Adv. 2024 Jan 13;4(1):vbae006. doi: 10.1093/bioadv/vbae006. eCollection 2024.

Abstract

SUMMARY

Third-generation long-read sequencing is an increasingly utilized technique for profiling human immunodeficiency virus (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 IMPLEMENTATION

ClusterV-Web is freely available and open source, with detailed documentation accessible at http://www.bio8.cs.hku.hk/ClusterVW/. The standalone Docker image and source code are also available at https://github.com/HKU-BAL/ClusterV-Web.

摘要

摘要

由于能够在单条读段中覆盖整个病毒基因组,第三代长读长测序技术在分析人类免疫缺陷病毒(HIV)准种和检测耐药性突变方面的应用越来越广泛。最近,ClusterV工具已证明能够从纳米孔长读长测序数据中准确检测HIV准种。然而,对脚本技能和计算环境的要求可能会成为许多潜在用户的障碍。为解决这一问题,我们推出了ClusterV-Web,这是一个基于网络的用户友好型应用程序,能够在远程和本地轻松配置和运行ClusterV。我们的工具提供交互式表格和数据可视化,以辅助结果解读。这一进展有望使长读长测序数据分析更普及,使更多研究人员和临床医生能够有效地分析HIV准种并检测耐药性突变。

可用性与实施情况

ClusterV-Web免费且开源,详细文档可在http://www.bio8.cs.hku.hk/ClusterVW/获取。独立的Docker镜像和源代码也可在https://github.com/HKU-BAL/ClusterV-Web获取。

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