ViWrap: A modular pipeline to identify, bin, classify, and predict viral-host relationships for viruses from metagenomes.
ViWrap: A modular pipeline to identify, bin, classify, and predict viral-host relationships for viruses from metagenomes.
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ViWrap：一种模块化管道，用于从宏基因组中识别、分类、分类和预测病毒与宿主的关系。
DOI：
10.1101/2023.01.30.526317
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Anantharaman,Karthik
中科院分区：
文献类型：
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作者：
Zhou,Zhichao;Martin,Cody;Kosmopoulos,JamesC;Anantharaman,Karthik
病毒越来越被认为是人类和环境微生物组的重要组成部分。然而，微生物组中的病毒仍然很难研究，因为培养它们很困难，而且缺乏足够的模型系统。因此，用于从宏基因组中识别和分析未培养的病毒基因组的计算方法引起了极大的关注。这种生物信息学方法有助于从源自各种环境的巨大测序数据集中筛选病毒。尽管已经开发了许多工具和数据库来推进从宏基因组研究病毒，但缺乏集成工具，从而能够实现涵盖病毒研究的所有不同部分的综合工作流程和分析平台。在这里，我们开发了ViWrap，一个用Python编写的模块化管道。ViWrap将多个工具的强大功能整合到一个平台中，以支持病毒分析的各个步骤，包括识别、注释、基因组分箱、种和属级聚类、分类分配、宿主预测、基因组质量表征、全面总结和直观可视化结果。总的来说，ViWrap为宏基因组、病毒组和微生物基因组中病毒的广泛和严格表征提供了标准化和可重现的管道。我们的方法具有灵活性，可以针对不同的应用和场景使用各种选项，并且其模块化结构可以根据需要轻松修改附加功能。ViWrap被设计成易于广泛用于研究人类和环境系统中的病毒。ViWrap可通过GitHub（https：//github.com/AnantharamanLab/ViWrap）公开获取。该软件的详细说明，其使用和结果的解释可以在网站上找到。
Viruses are increasingly being recognized as important components of human and environmental microbiomes. However, viruses in microbiomes remain difficult to study because of the difficulty in culturing them and the lack of sufficient model systems. As a result, computational methods for identifying and analyzing uncultivated viral genomes from metagenomes have attracted significant attention. Such bioinformatics approaches facilitate the screening of viruses from enormous sequencing data sets originating from various environments. Although many tools and databases have been developed for advancing the study of viruses from metagenomes, there is a lack of integrated tools enabling a comprehensive workflow and analysis platform encompassing all the diverse segments of virus studies. Here, we developed ViWrap, a modular pipeline written in Python. ViWrap combines the power of multiple tools into a single platform to enable various steps of virus analyses, including identification, annotation, genome binning, species‐ and genus‐level clustering, assignment of taxonomy, prediction of hosts, characterization of genome quality, comprehensive summaries, and intuitive visualization of results. Overall, ViWrap enables a standardized and reproducible pipeline for both extensive and stringent characterization of viruses from metagenomes, viromes, and microbial genomes. Our approach has flexibility in using various options for diverse applications and scenarios, and its modular structure can be easily amended with additional functions as necessary. ViWrap is designed to be easily and widely used to study viruses in human and environmental systems. ViWrap is publicly available via GitHub (https://github.com/AnantharamanLab/ViWrap). A detailed description of the software, its usage, and interpretation of results can be found on the website.