在高通量聚合竞争试验上,贝叶斯推断的相对适应性
Manuel Razo-Mejia1, Madhav Mani2,3, Dmitri Petrov1,4,5
1Department of Biology, Stanford University.
bioRxiv : the preprint server for biology
|October 31, 2023
概括
这项研究引入了贝叶斯管道,以精确测量DNA条形码测序的微生物适应性,克服实验噪声. 该方法提供了一个可靠的框架,用于分析在实验进化中的血统跟踪数据.
科学领域:
- 微生物学 微生物学
- 进化生物学 进化生物学
- 计算生物学 计算生物学
背景情况:
- 量化微生物健康对于理解进化动态至关重要.
- 来自生物和非生物因素的实验噪音使得从血统追踪中推断准确的健康状况变得复杂.
- 高通量DNA条形码测序产生大型数据集,需要强大的分析方法.
研究的目的:
- 介绍一个贝叶斯管道,从高通量血统跟踪推断出相对微生物适应性.
- 系统地考虑多个噪声源并传播不确定性.
主要方法:
- 一个贝叶斯推理管道,利用变量方法和自动差异化.
- 对大量独特条形码进行可扩展的推断.
- 扩展用于分析多环境测试,复制实验和基因型链接条形码.
主要成果:
- 该模型在模拟中成功地在后面可信的间隔内恢复已知的参数.
- 具备处理复杂实验设计的能力,包括多环境和复制数据.
- 精确推断微生物健康,尽管有显著的实验噪声.
结论:
- 这项工作为分析实验进化数据提供了一个有原则的统计框架.
- 附带的开源软件有助于在微生物进化研究中采用先进的统计方法.
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