VIRify:一个集成的检测,注释和分类学分类管道,使用病毒特异性蛋白质配置隐藏的马尔科夫模型
Guillermo Rangel-Pineros1,2,3, Alexandre Almeida3,4,5, Martin Beracochea3
1The Globe Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
PLoS computational biology
|August 28, 2023
概括
VIRify是一个新的计算管道,用于从测序数据中准确地描述病毒社区. 它可以识别和分类病毒序列,改善人类肠道和海洋生态系统等多种环境中的分类学分辨率.
科学领域:
- 病毒学 病毒学
- 生物信息学是一种生物信息学.
- 转基因组学是指转基因组学.
背景情况:
- 病毒社区是多样化的,在整个生态系统中具有影响力.
- 从测序数据中精确计算对病毒群体的特征有很大的兴趣.
- 现有的方法可能缺乏用户友好性或全面准确性.
研究的目的:
- 介绍VIRify,一个用户友好和准确的计算管道,用于病毒社区的特征.
- 为了能够对病毒序列进行全面的功能和分类学注释.
- 改进各种元基因组数据集中的病毒检测和分类.
主要方法:
- VIRify可以从元基因组组合中识别病毒结合体和传播体.
- 它使用了一系列病毒形状隐藏的马尔科夫模型 (HMMs),包括手动策划的集合,用于注释.
- 该管道在模拟社区,大型元基因组学研究以及人类肠道和海洋病毒序列上进行了测试.
主要成果:
- VIRify能够准确地识别和分类 prokaryotic 和 eukaryotic 病毒序列.
- 实现了从属到家族等级的分类学分类的平均准确率为86.6%.
- 在海洋元基因组组合中成功检测和分类病毒,并改进了人类肠道病毒分类.
结论:
- VIRify是病毒社区分析的新和强大的资源.
- 它增强了检测和分类广泛的病毒结合体的能力.
- 该管道为病毒分类学分类提供了更高的准确性和分辨率.
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