比较贝叶斯的凝聚式天际线图谱模型,用于推断人口历史
Ronja J Billenstein1,2, Sebastian Höhna1,2
1GeoBio-Center, Ludwig-Maximilians-Universität München, Munich 80333, Germany.
Molecular biology and evolution
|April 17, 2024
概括
贝叶斯的凝聚天际线情节模型推断出人口统计历史. 这项研究实施和评估了各种模型,发现变化点规范显著影响结果,独立的变化点可能会过度平滑历史.
科学领域:
- 进化生物学 进化生物学
- 人口遗传学 人口遗传学
- 计算生物学 计算生物学
背景情况:
- 贝叶斯的凝聚天际线图模型是重建过去人口规模变化的标准工具.
- 现有的模型在如何处理人口大小波动 (独立与自相关的先验) 和变化点规范 (数量,放置,推断) 上有所不同.
- 缺乏标准化实施和用户对模型选择的控制,阻碍了比较评估.
研究的目的:
- 在统一的软件框架 (RevBayes) 中实现所有描述的贝叶斯凝聚天际线图案.
- 用实证 (马) 和模拟数据评估不同建模选择对推断的人口历史的影响.
- 为选择适合的人口推理模型提供指导.
主要方法:
- 在RevBayes中统一实现贝叶斯的凝聚天际线图案模型.
- 使用经验数据集对马种群序列的评估.
- 补充模拟研究,以评估在受控条件下的模型性能.
主要成果:
- 推断的人口历史基于变化点规范 (独立与凝聚事件) 进行聚类.
- 在凝聚事件中使用变化点的模型产生了虚假的近期变化.
- 使用独立变化点的模型倾向于过度平滑人口统计历史.
结论:
- 变化点规范的选择至关重要,并影响人口统计推理的准确性.
- 独立的变化点可能会导致过度平滑,而基于凝聚事件的变化点可以引入文物.
- RevBayes的实施促进了严格的模型评估,帮助研究人员选择适当的人口推理方法.
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