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, Stanford, California, United States of America.
PLoS computational biology
|March 15, 2024
概括
我们开发了一个贝叶斯管道,从DNA条形码测序数据中准确推断微生物适应性,克服实验噪声. 这种方法提高了微生物进化研究的可靠性.
科学领域:
- 微生物生态学 微生物生态学
- 进化生物学 进化生物学
- 计算生物学 计算生物学
背景情况:
- DNA条形码测序跟踪微生物血统频率以量化适应性.
- 来自生物和非生物来源的实验噪声妨碍了准确的适应性推断.
- 现有的方法难以应对复杂的噪音和大数据集.
研究的目的:
- 提出一个强大的贝叶斯管道,从高通量血统追踪推断微生物适应性.
- 系统地考虑和传播来自多个噪音源的不确定性.
- 为了使大规模实验进化数据的可扩展分析.
主要方法:
- 贝叶斯推理管道使用变量方法和自动差异化.
- 模型包含多个实验噪声源 (生物和非生物).
- 为多环境测定,复制和基因型链接条形码扩展框架.
主要成果:
- 模拟显示在可信的间隔内准确恢复已知的参数.
- 管道有效地处理大量独特的条形码.
- 不确定性在整个推断过程中被系统地传播.
结论:
- 开发的贝叶斯框架为分析血统追踪实验提供了一个可概括的方法.
- 开源软件有助于在实验进化中采用先进的统计方法.
- 这项工作提高了微生物健康量化的可靠性和可扩展性.
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