SCiMS:在元基因组序列中进行性调用
bioRxiv : the preprint server for biology
|February 27, 2026
概括
一个名为SCiMS (Sex Calling in Metagenomic Sequences) 的新工具可以准确地从微生物组样本中的DNA中确定宿主性别. 这种方法即使在少量宿主DNA的情况下也有效,提高了微生物组研究数据的质量.
科学领域:
- 微生物组研究的研究.
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 主体性别显著影响微生物社区结构,但在研究中经常缺失或被错误标记.
- 现有的性别调用工具与低宿主DNA度作斗争,这种度在便等样本中很常见.
- 准确的宿主性别数据对于理解性别特异性的生物变异至关重要.
研究的目的:
- 开发一个强大的生物信息工具,用于在元基因组数据集中准确地确定宿主性别.
- 解决微生物组研究中缺少或不可靠的性别元数据的挑战.
- 为不同物种的宿主性别分类提供可扩展和通用化的解决方案.
主要方法:
- 开发了SCiMS (基因组序列中的性调用),这是一种利用性染色体读取密度比率的工具.
- 采用贝叶斯分类器来预测在元基因组样本中从宿主衍生的DNA中预测宿主性别.
- 通过模拟和应用到真实世界的数据集 (人类微生物组项目,小鼠,) 验证了SCiMS的性能.
主要成果:
- 即使使用最小的宿主DNA,SCiMS也能准确地预测宿主性别 (例如,在模拟中读取约450个宿主时,准确率>85%).
- 在人类微生物组项目数据上表现优于现有的工具,显示出卓越的准确性和精确性-回忆平衡.
- 显示了跨物种的概括性,在小鼠中准确率为100%,在肉数据集中表现强.
结论:
- 在元基因组研究中,SCiMS为宿主性别分类提供了一种准确,可扩展和广泛适用的方法.
- 能够恢复关键的性别元数据,提高微生物组分析的完整性和可靠性.
- 该工具是微生物组研究的重要质量控制措施,并可供公众使用.
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