Maximum likelihood estimation of recombination rates from population data.
Maximum likelihood estimation of recombination rates from population data.
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DOI：
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发表时间：
2000-11
期刊：
影响因子：
3.3
通讯作者：
M. Kuhner;Jon A Yamato;J. Felsenstein
中科院分区：
文献类型：
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作者：
M. Kuhner;Jon A Yamato;J. Felsenstein
我们描述了一种从分子数据的种群样本中联合估计r=C/Mu(其中C是每个位置的重组率，Mu是每个位置的中性突变率)和Theta=4N(E)Mu(其中N(E)是有效的种群大小)的方法。技术是Metropolis-Hastings抽样：我们探索大量可能的重组家谱重建，根据它们相对于数据和参数工作值的后验概率进行加权。如果从外部证据中知道不同位置的不同相对重组率，就可以适应不同的重组率，但算法本身不能估计速率差异。对于大范围的参数值，Theta的估计是准确的，而且显然是没有偏见的。然而，当Theta和r都相对较低时，需要非常长的序列来准确地估计r，并且估计往往偏向于向上。我们将这种方法应用于人脂蛋白脂肪酶基因座的数据。
We describe a method for co-estimating r = C/mu (where C is the per-site recombination rate and mu is the per-site neutral mutation rate) and Theta = 4N(e)mu (where N(e) is the effective population size) from a population sample of molecular data. The technique is Metropolis-Hastings sampling: we explore a large number of possible reconstructions of the recombinant genealogy, weighting according to their posterior probability with regard to the data and working values of the parameters. Different relative rates of recombination at different locations can be accommodated if they are known from external evidence, but the algorithm cannot itself estimate rate differences. The estimates of Theta are accurate and apparently unbiased for a wide range of parameter values. However, when both Theta and r are relatively low, very long sequences are needed to estimate r accurately, and the estimates tend to be biased upward. We apply this method to data from the human lipoprotein lipase locus.