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不变率出生-死亡的极限 在原生树拓推理推理之前
Mark P Khurana1, Neil Scheidwasser-Clow1, Matthew J Penn2
1Section of Epidemiology, Department of Public Health, University of Copenhagen, 1352 Copenhagen, Denmark.
Systematic biology
|December 28, 2023
概括
恒定率出生死亡 (crBD) 模型经常产生与实证数据不同的家族遗传树,特别是在树不平衡方面. 虽然crBD先验通常是强大的,但它们可以在信息含量低的数据集中引入偏差.
科学领域:
- 进化生物学是进化的生物学.
- 人类遗传学 是一个学科.
- 计算生物学是一种计算生物学.
背景情况:
- 出生死亡模型对于推断进化时间尺度至关重要.
- 以前的研究表明,恒定出生死亡率 (crBD) 模型预期与实证遗传树之间存在差异,特别是在树不平衡方面.
- 需要全面了解这些差异以及模型的实际局限性.
研究的目的:
- 量化crBD模型预期和经验推断的族系之间的拓差异.
- 评估crBD模型在遗传学推断中的实际限制和稳定性.
- 调查crBD先验对不同进化速率和树不平衡下的树拓推理的影响.
主要方法:
- 将crBD模型的预期与使用各种拓指数的1189个实证树数据集进行比较.
- 采用贝叶斯方法与crBD先验对比非crBD先验和非贝叶斯方法的研究的元分析.
- 在不同的进化速率下,对高度不平衡的实证树拓学的序列数据的模拟,然后使用最大概率和贝叶斯crBD模型进行树重推理.
主要成果:
- 与实证树相比,crBD模型树经常表现出拓差异.
- 在元分析中,贝叶斯式crBD先验与其他方法之间没有发现树拓推断的显著差异.
- 在较低的替代率下,crBD前期倾向于产生过度平衡的树木,这种趋势在更高的替代率下会减少.
结论:
- 在crBD之前,它在各种类遗传推断场景中表现出一般的稳定性.
- 在crBD模型下,经验观察到的基因失衡不太可能发生,这表明在有限信息的数据集中存在潜在的系统偏差.
- 在高度不平衡的树木和低替代率的场景中,crBD模型的局限性最明显.
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