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ViralBottleneck:一个R包,用于通过使用多种方法从深度测序数据中估计病毒传播瓶

Bowen Zheng¹, Paul C D Johnson², Joseph Hughes¹

¹MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, 464 Bearsden Road, Glasgow G61 1QH, United Kingdom.

Virus evolution

|October 15, 2025

概括

了解病毒传播瓶是控制传染病的关键. 本研究介绍了ViralBottleneck,这是一个用于估计瓶大小的R包,揭示了不同估计方法之间的显著差异.

科学领域:

病毒学病毒学
计算生物学计算生物学
流行病学流行病学

背景情况:

急性病毒感染对公众健康构成重大关注.
病毒进化,免疫逃生和疾病严重程度都受到宿主对宿主传播动态的影响.
传播瓶,减少病毒在传播过程中的遗传多样性,对于理解疾病的出现和演变至关重要.

研究的目的:

推出 ViralBottleneck,一个用于估计病毒传播瓶大小的 R 包.
将六种已建立的瓶大小估计方法整合到一个单一的包裹中.
为研究病毒传播的研究人员提供一个用户友好的工具.

主要方法:

病毒瓶R包整合了六种方法:存在-缺席,Kullback-Leibler (KL),二项式,两个β-二项式版本,以及Wright-Fisher.
使用SANTA-Sim生成的模拟数据集用于在已知瓶大小的各种场景下测试包功能.
使用这些模拟数据集,评估了每个方法的性能和输出.

主要成果:

该研究使用模拟数据证明了ViralBottleneck包的功能.
在六种综合方法中观察到传输瓶大小估计的显著差异.
估计方法的选择明显影响了由此产生的瓶大小估计.

结论:

病毒瓶套件提供了一套全面的工具,用于传输瓶分析.
方法选择对估计病毒传播瓶大小有重大影响.
准确估计瓶大小对于预测疾病动态和为公共卫生干预提供信息至关重要.

关键词:

在R包中,R包是R包.瓶瓶瓶瓶是指一个瓶.深度测序是一种深度测序.宿主内部的病毒多样性传输传输传输传输传输传输

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