一个黄金标准的数据集和评估从废水中估计血统丰度的方法
Jannatul Ferdous1, Samuel Kunkleman1, William Taylor1
1Department of Bioinformatics and Genomics, UNC Charlotte, 9201 University City Blvd, Charlotte, NC 28223, USA.
The Science of the total environment
|July 6, 2024
概括
废水监测有效地通过基因组测序追踪SARS-CoV-2变种. 弗雷亚和VaQuERo软件在从复杂的废水样本中识别病毒系的精度更高.
科学领域:
- 环境微生物学环境微生物学
- 病毒学 病毒学
- 生物信息学是一种生物信息学.
背景情况:
- 基于基因组的废水监测对于监测SARS-CoV-2变种至关重要.
- 废水的复杂基因复杂化了病毒解和变种识别.
- 需要标准化的数据集来评估解卷工具的性能.
研究的目的:
- 为评估SARS-CoV-2废水解工具创建一个黄金标准数据集.
- 为了比较八个常见的解卷软件包的性能.
- 评估原料计划和废水矩阵对序列化和解卷化的影响.
主要方法:
- 创建了一个合成病毒控制混合物,其成分已知.
- 混合物被入废水RNA矩阵中,并使用牛津纳米孔技术进行了测序.
- 八个解卷工具 (Freyja, kallisto, Kraken 2/Bracken, LCS, Lollipop, lineagespot, Alcov, VaQuERo) 进行了评估. 这些工具包括:
主要成果:
- 弗雷亚和VaQuERo在识别SARS-CoV-2血统方面显示出最高的准确性.
- 弗雷耶超越了CDC废水监测协议中的其他工具.
- 在Freyja和VaQuERo之间,在处理虚假阴性和虚假阳性方面观察到微小的差异.
结论:
- 弗雷亚和VaQuERo是SARS-CoV-2变种在废水中脱的高度准确的工具.
- 该研究强调了初级选择和样本矩阵对测序结果的影响.
- 这项工作为基于废水的病毒监测工具开发提供了基准.
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