Using temporally spaced sequences to simultaneously estimate migration rates, mutation rate and population sizes in measurably evolving populations
Using temporally spaced sequences to simultaneously estimate migration rates, mutation rate and population sizes in measurably evolving populations
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DOI：
10.1534/genetics.104.030411
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发表时间：
2004-12-01
期刊：
影响因子：
3.3
通讯作者：
Rodrigo, A
中科院分区：
文献类型：
--
作者：
Ewing, G;Nicholls, G;Rodrigo, A
我们提出了一种贝叶斯统计推断方法，利用时间和空间序列数据同时估计所有海岛结构种群的突变率、乳突大小和迁移率。用马尔可夫链蒙特卡罗方法采集后验概率分布前面的样本。我们证明了这种链实现成功地达到了平衡，并恢复了模拟数据的真值。以一个含有精液和血液两个特征的真实HIV DNA序列数据集为例，通过对不对称迁移率和不同种群规模的拟合来验证该方法。该数据集呈现双峰联合后验分布，模式倾向于不同的优先迁移方向。这一完整的数据集随后被暂时拆分，以供进一步分析。一个子集的定性行为类似于用整个数据集观察到的双峰分布。时间分割的数据显示，随着时间的推移，后验分布和参数值的估计有显著差异。
We present a Bayesian statistical inference approach for simultaneously estimating mutation rate, papulation sizes, and migration rates in all island-structured population, using temporal and spatial sequence data. Markov chain Monte Carlo is used to collect samples front the posterior probability distribution. We demonstrate that this chain implementation successfully reaches equilibrium and recovers truth for simulated data. A real HIV DNA sequence data set with two demes, semen and blood, is used as an example to demonstrate the method by fitting asymmetric migration rates and different Population Sizes. This data set exhibits a bimodal joint posterior distribution, with modes favoring different preferred migration directions. This full data set was subsequently split temporally for further analysis. Qualitative behavior of one subset was similar to the bimodal distribution observed with the full data set. The temporally split data showed significant differences in the posterior distributions and estimates of parameter values over time.