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你的树是多么可靠? 贝叶斯系系遗传学 通过蒙特卡洛镜头的有效样本大小 错误
Andrew Magee1, Michael Karcher2, Frederick A Matsen3
1Department of Biology, University of Washington, Seattle, WA, 98195, USA.
概括
评估贝叶斯的遗传学推理是具有挑战性的. 新的树有效样本大小 (ESS) 措施有助于量化马尔科夫链蒙特卡洛 (MCMC) 错误在进化树分析,提高可靠性.
科学领域:
- 计算生物学 计算生物学
- 进化生物学 进化生物学
- 统计类遗传学 统计类遗传学
背景情况:
- 贝叶斯推理是重建进化树 (系谱) 的标准方法.
- 评估马尔科夫链蒙特卡洛 (MCMC) 运行在探索遗传树空间中的性能仍然是一个重大挑战.
- 现有的方法很难准确地评估贝叶斯系遗传学分析中的蒙特卡洛误差.
研究的目的:
- 为了调查贝叶斯系遗传树推断中的蒙特卡洛错误.
- 为了确定有效的样本大小 (ESS) 适用于族系的措施,以量化此错误.
- 开发工具,以便更好地比较独立的MCMC运行.
主要方法:
- 专注于后部分布的高维总结,包括分割概率,树概率和总结树变性.
- 评估ESS措施的适用性,以捕捉这些家族遗传总结中的蒙特卡罗错误.
- 开发了可视化工具来比较MCMC运行,考虑蒙特卡洛误差.
主要成果:
- 确定了能够捕获植物遗传学分析中的蒙特卡罗误差的特定树ESS措施.
- 发现一组三棵ESS树的测量措施对于评估蒙特卡罗错误很实用.
- 可视化工具通过解决固有的蒙特卡洛错误来增强独立的MCMC运行之间的比较.
结论:
- 标准的MCMC后工作流程不足以捕捉家族遗传树的完整蒙特卡罗错误.
- 拟议的树ESS措施为评估MCMC收和混合提供了有价值的工具.
- 在家族遗传学分析中,有必要进行链内混合和链间融合评估.
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