The impact of the rate prior on Bayesian estimation of divergence times with multiple Loci.
The impact of the rate prior on Bayesian estimation of divergence times with multiple Loci.
复制标题
先验率对多个基因座发散时间的贝叶斯估计的影响。
DOI：
10.1093/sysbio/syu020
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发表时间：
2014-07
影响因子：
6.5
通讯作者：
Yang Z
中科院分区：
文献类型：
--
作者：
Dos Reis M;Zhu T;Yang Z
贝叶斯方法通过将分子序列的信息与化石记录中的信息结合在一起，提供了一种强大的方法来估计物种差异时间。随着基因组数据的爆炸性增加，差异时间估计越来越多地使用了多个基因座（基因或位点分区）的数据。广泛使用的计算机程序来估计分歧时间使用独立和相同分布的（I.I.D.）先验，以替代不同基因座的替代率。 I.I.D.先验是有问题的。随着基因座（L）的数量的增加，所有基因座的平均率的先前差异以1/L的速度为零。结果，先前的速率在分析许多基因座时主导了后时间估计，如果误指定的速率率，估计的差异时间将在非常狭窄的可信度间隔内收敛到错误的值。在这里，我们根据Dirichlet分布开发了一个关于基因座率的新先验，该分布纠正了I.I.D的问题行为。事先的。我们使用计算机模拟和实际数据分析来突出新先验之间的差异。对于六种灵长类动物的数据集，我们证明了旧的I.I.D.先前，如果先前的速率太高（或太低），则估计的差异时间太年轻（或太老），在化石校准所施加的边界之外。相反，随着新的Dirichlet先验，后时间估计值对先验率不敏感，并且与化石校准兼容。我们重新分析了36种哺乳动物物种的系统基因组数据集，并表明，使用许多化石校准可以减轻在一定程度上缩写率的不利影响。我们建议在贝叶斯分歧时间估计中使用新的Dirichlet先验。 [贝叶斯推论，发散时间，放松时钟，速率先验，分区分析。]
Bayesian methods provide a powerful way to estimate species divergence times by combining information from molecular sequences with information from the fossil record. With the explosive increase of genomic data, divergence time estimation increasingly uses data of multiple loci (genes or site partitions). Widely used computer programs to estimate divergence times use independent and identically distributed (i.i.d.) priors on the substitution rates for different loci. The i.i.d. prior is problematic. As the number of loci (L) increases, the prior variance of the average rate across all loci goes to zero at the rate 1/L. As a consequence, the rate prior dominates posterior time estimates when many loci are analyzed, and if the rate prior is misspecified, the estimated divergence times will converge to wrong values with very narrow credibility intervals. Here we develop a new prior on the locus rates based on the Dirichlet distribution that corrects the problematic behavior of the i.i.d. prior. We use computer simulation and real data analysis to highlight the differences between the old and new priors. For a dataset for six primate species, we show that with the old i.i.d. prior, if the prior rate is too high (or too low), the estimated divergence times are too young (or too old), outside the bounds imposed by the fossil calibrations. In contrast, with the new Dirichlet prior, posterior time estimates are insensitive to the rate prior and are compatible with the fossil calibrations. We re-analyzed a phylogenomic data set of 36 mammal species and show that using many fossil calibrations can alleviate the adverse impact of a misspecified rate prior to some extent. We recommend the use of the new Dirichlet prior in Bayesian divergence time estimation. [Bayesian inference, divergence time, relaxed clock, rate prior, partition analysis.]
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