Bayesian estimation of species divergence times under a molecular clock using multiple fossil calibrations with soft bounds
Bayesian estimation of species divergence times under a molecular clock using multiple fossil calibrations with soft bounds
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DOI：
10.1093/molbev/msj024
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发表时间：
2006-01-01
影响因子：
10.7
通讯作者：
Rannala, B
中科院分区：
文献类型：
--
作者：
Yang, ZH;Rannala, B
我们实现了贝叶斯马尔可夫链蒙特卡罗算法估计物种的分歧时间，使用多个基因位点的异质数据，并容纳多个化石校准节点。一个出生-死亡过程与物种抽样被用来指定一个前的分歧时间，这使得容易评估的影响，前后的时间估计。我们提出了一种新的方法，用于指定校准点的化石年代，它允许使用任意和灵活的统计分布来描述化石年代的不确定性。特别地，我们使用软边界，使得真实发散时间在边界之外的概率很小但非零。在当前的实现中假设了严格的分子钟，尽管该假设可以放宽。我们将我们的新算法应用到两个数据集的分歧，几个灵长类动物物种，检查的替代模型和先验的分歧时间贝叶斯时间估计的影响。我们还进行了计算机模拟，以检查软，硬边界之间的差异。我们证明，发散时间估计是固有的阻碍化石校准的不确定性，贝叶斯时间估计的误差不会去零与序列数据量的增加。我们对真实的和模拟数据的分析表明，使用软边界与硬边界获得的发散时间估计值之间存在潜在的巨大差异，软边界具有普遍的优越性。我们的主要发现如下。(1)当化石彼此一致且与分子数据一致时，并且后验时间估计在先验界限内，软界限和硬界限产生类似的结果。(2)当化石彼此冲突或与分子冲突时，软边界和硬边界的表现非常不同;软边界允许序列数据纠正不良校准，而不良的硬边界不可能通过任何数量的数据来克服。(3)软边界消除了对“安全”但不切实际的高上限的需要，这可能会使后验时间估计产生偏差。(4)软边界允许更可靠的评估估计误差，而硬边界产生误导性的高精度时，化石和分子的冲突。
We implement a Bayesian Markov chain Monte Carlo algorithm for estimating species divergence times that uses heterogeneous data from multiple gene loci and accommodates multiple fossil calibration nodes. A birth-death process with species sampling is used to specify a prior for divergence times, which allows easy assessment of the effects of that prior on posterior time estimates. We propose a new approach for specifying calibration points on the phylogeny, which allows the use of arbitrary and flexible statistical distributions to describe uncertainties in fossil dates. In particular, we use soft bounds, so that the probability that the true divergence time is outside the bounds is small but nonzero. A strict molecular clock is assumed in the current implementation, although this assumption may be relaxed. We apply our new algorithm to two data sets concerning divergences of several primate species, to examine the effects of the substitution model and of the prior for divergence times on Bayesian time estimation. We also conduct computer simulation to examine the differences between soft and hard bounds. We demonstrate that divergence time estimation is intrinsically hampered by uncertainties in fossil calibrations, and the error in Bayesian time estimates will not go to zero with increased amounts of sequence data. Our analyses of both real and simulated data demonstrate potentially large differences between divergence time estimates obtained using soft versus hard bounds and a general superiority of soft bounds. Our main findings are as follows. (1) When the fossils are consistent with each other and with the molecular data, and the posterior time estimates are well within the prior bounds, soft and hard bounds produce similar results. (2) When the fossils are in conflict with each other or with the molecules, soft and hard bounds behave very differently; soft bounds allow sequence data to correct poor calibrations, while poor hard bounds are impossible to overcome by any amount of data. (3) Soft bounds eliminate the need for "safe" but unrealistically high upper bounds, which may bias posterior time estimates. (4) Soft bounds allow more reliable assessment of estimation errors, while hard bounds generate misleadingly high precisions when fossils and molecules are in conflict.