识别接触追踪对从植物遗传数据的流行病学推断的影响
Michael D Kupperman1,2, Ruian Ke1, Thomas Leitner1
1Theoretical Biology and Biophysics, Los Alamos National Laboratory, New Mexico, United States of America.
bioRxiv : the preprint server for biology
|December 11, 2023
概括
接触追踪是一种不统一的采样方法,它对病原体的基因有重大影响. 该SEEPS (序列进化和流行病学过程模拟器) 工具揭示了这如何影响树结构和流行病学推断.
科学领域:
- 分子流行病学分子流行病学
- 计算生物学是一种计算生物学.
- 公共卫生 公共卫生
背景情况:
- 遗传学推断依赖于可靠的抽样方法.
- 接触追踪,一种不统一的采样策略,对病原体类型的影响在分子流行病学中仍未得到充分研究.
研究的目的:
- 调查接触追踪对遗传树结构的影响.
- 开发一个模拟工具SEEPS,用于建模接触追踪及其对病原体类型和遗传序列的影响.
主要方法:
- 开发了SEEPS (序列进化和流行病学过程模拟器) 来模拟接触追踪,传播树,病原体类型和遗传序列,包括宿主内部的进化.
- 将SEEPS应用于来自瑞典和欧洲的模拟数据和真实世界HIV-1疫情数据.
主要成果:
- 接触追踪显著改变了家族遗传树的结构,导致树木不太平衡,并影响了内部/外部树枝长度比率.
- 模拟显示,接触追踪影响了树统计数据,而真实数据分析证实了其对瑞典HIV-1爆发数据的影响,与更广泛的欧洲流行病不同.
结论:
- 接触追踪引入了家族遗传重建中的偏差,需要考虑非统一的抽样方案以获得准确的流行病学推断.
- 该SEEPS工具是有价值的评估采样策略对植物系的影响,增强疾病爆发分析.
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