Guo Jiarong, Bolduc Ben, Zayed Ahmed A, Varsani Arvind, Dominguez-Huerta Guillermo, Delmont Tom O, Pratama Akbar Adjie, Gazitúa M Consuelo, Vik Dean, Sullivan Matthew B, Roux Simon
Department of Microbiology, Ohio State University, Columbus, OH, 43210, USA.
The Biodesign Center for Fundamental and Applied Microbiomics, Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA.
Microbiome. 2021 Feb 1;9(1):37. doi: 10.1186/s40168-020-00990-y.
Viruses are a significant player in many biosphere and human ecosystems, but most signals remain "hidden" in metagenomic/metatranscriptomic sequence datasets due to the lack of universal gene markers, database representatives, and insufficiently advanced identification tools.
Here, we introduce VirSorter2, a DNA and RNA virus identification tool that leverages genome-informed database advances across a collection of customized automatic classifiers to improve the accuracy and range of virus sequence detection. When benchmarked against genomes from both isolated and uncultivated viruses, VirSorter2 uniquely performed consistently with high accuracy (F1-score > 0.8) across viral diversity, while all other tools under-detected viruses outside of the group most represented in reference databases (i.e., those in the order Caudovirales). Among the tools evaluated, VirSorter2 was also uniquely able to minimize errors associated with atypical cellular sequences including eukaryotic genomes and plasmids. Finally, as the virosphere exploration unravels novel viral sequences, VirSorter2's modular design makes it inherently able to expand to new types of viruses via the design of new classifiers to maintain maximal sensitivity and specificity.
With multi-classifier and modular design, VirSorter2 demonstrates higher overall accuracy across major viral groups and will advance our knowledge of virus evolution, diversity, and virus-microbe interaction in various ecosystems. Source code of VirSorter2 is freely available ( https://bitbucket.org/MAVERICLab/virsorter2 ), and VirSorter2 is also available both on bioconda and as an iVirus app on CyVerse ( https://de.cyverse.org/de ). Video abstract.
病毒在许多生物圈和人类生态系统中扮演着重要角色，但由于缺乏通用基因标记、数据库代表以及不够先进的识别工具，大多数信号仍“隐藏”在宏基因组/宏转录组序列数据集中。
在此，我们介绍了VirSorter2，这是一种DNA和RNA病毒识别工具，它利用一系列定制自动分类器中基于基因组的数据库进展，提高病毒序列检测的准确性和范围。在与来自分离病毒和未培养病毒的基因组进行基准测试时，VirSorter2在病毒多样性方面始终以高精度（F1分数>0.8）独特地表现出色，而所有其他工具在参考数据库中代表性最强的组之外（即尾病毒目那些病毒）检测到的病毒不足。在所评估的工具中，VirSorter2还独特地能够将与非典型细胞序列（包括真核基因组和质粒）相关的错误降至最低。最后，随着病毒圈探索揭示出新的病毒序列，VirSorter2的模块化设计使其能够通过设计新的分类器固有地扩展到新型病毒，以保持最大的灵敏度和特异性。
凭借多分类器和模块化设计，VirSorter2在主要病毒组中展示出更高的总体准确性，并将推进我们对各种生态系统中病毒进化、多样性以及病毒-微生物相互作用的认识。VirSorter2的源代码可免费获取（https://bitbucket.org/MAVERICLab/virsorter2），并且VirSorter2在生物conda上以及作为CyVerse（https://de.cyverse.org/de）上的iVirus应用程序也均可使用。视频摘要。
