贝叶斯梯子 绘图用于推断单个人口人口统计历史从站点频谱
Sebastian Höhna1,2, Ana Catalán3
1GeoBio-Center LMU, Ludwig-Maximilians-Universität München, Munich, Germany.
Molecular ecology resources
|February 27, 2025
概括
本研究介绍了RevBayes中StairwayPlot方法的贝叶斯实现,用于从站点频谱数据中估计人口人口统计. 贝叶斯方法的准确性与现有方法相美,并且在建模人口变化时具有灵活性.
科学领域:
- 人口遗传学 人口遗传学
- 计算生物学是一种计算生物学.
- 进化模型的演化模型.
背景情况:
- 估计复杂的人口历史对于理解人口演变至关重要.
- StairwayPlot 方法提供了使用现场频谱数据的灵活方法.
- 贝叶斯推理为人口模型提供了一个强大的框架.
研究的目的:
- 为了在贝叶斯软件RevBayes中实现StairwayPlot方法.
- 将贝叶斯实现的性能与现有的最大概率方法进行比较.
- 评估不同先前分布对人口规模变化的变化,并评估模型选择策略.
主要方法:
- 利用了预期的凝聚时间和多项概率函数.
- 纳入的贝叶斯天际线图采用各种先前分布 (i.i.d.,GMRF,HMRF) 的方法.
- 实施了对模型选择进行一次性交叉验证.
主要成果:
- 在RevBayes的贝叶斯梯子Plot显示了与梯子Plot2.2相比的参数准确性.
- 高斯马尔科夫随机场 (GMRF) 先验最佳模型顺利变化的历史.
- 马马可夫随机场 (HMRF) 的先验对于突然变化的人口历史是最佳的.
- 仅仅10个双胞胎个体和500k个SNP就足以进行复杂的人口推断.
结论:
- 贝叶斯在RevBayes中实施的StairwayPlot是一个强大的人口推断工具.
- 以前的选择对人口历史重建的准确性产生了重大影响.
- 经验研究需要仔细考虑序列长度,突变率和潜在偏差.
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