Data from: On the occurrence of false positives in tests of migration under an isolation with migration model

The population genetic study of divergence is often done using a Bayesian genealogy sampler, like those implemented in IMa2 and related programs, and these analyses frequently include a likelihood-ratio test of the null hypothesis of no migration between populations. Cruickshank and Hahn (2014, Molecular Ecology, 23, 3133-3157) recently reported a high rate of false positive test results with IMa2 for data simulated with small numbers of loci under models with no migration and recent splitting times. We confirm these findings and discover that they are caused by a failure of the assumptions underlying likelihood ratio tests that arises when using marginal likelihoods for a subset of model parameters. We also show that for small data sets, with little divergence between samples from two populations, an excellent fit can often be found by a model with a low migration rate and recent splitting time and a model with a high migration rate and a deep splitting time.

种群分化的群体遗传学研究通常采用贝叶斯谱系采样器（Bayesian genealogy sampler），例如IMa2及相关程序中实现的此类工具，这类分析常会包含针对“种群间无基因流”这一零假设（null hypothesis）的似然比检验（likelihood-ratio test）。Cruickshank与Hahn（2014年，《分子生态学（Molecular Ecology）》，第23卷，第3133-3157页）此前报道，当使用基于无基因流且分化时间较近的模型所模拟的少量基因座（loci）数据开展分析时，IMa2会出现较高的假阳性检验结果率。本研究验证了上述结论，并揭示其根源在于：当使用模型参数子集的边际似然（marginal likelihood）时，似然比检验所依托的假设条件发生失效。本研究同时证实，对于两类种群样本分化程度较低的小数据集，通常可找到两种拟合效果极佳的模型：一种为低基因流且分化时间较近的模型，另一种为高基因流且分化时间较久远的模型。