The interbreeding of individuals coming from genetically differentiated but incompletely isolated populations can lead to the formation of admixed populations, having important implications in ecology and evolution. In this simulation study, we evaluate how individual admixture proportions estimated by the software structure are quantitatively affected by different factors. Using various scenarios of admixture between two diverging populations, we found that unbalanced sampling from parental populations may seriously bias the inferred admixture proportions; moreover, proportionally large samples from the admixed population can also decrease the accuracy and precision of the inferences. As expected, weak differentiation between parental populations and drift after the admixture event strongly increase the biases caused by uneven sampling. We also show that admixture proportions are generally more biased when parental populations unequally contributed to the admixed population. Finally, with few exceptions, using a large number of markers reduces those biases, but using alternative priors for individual ancestry or the uncorrelated allele model only marginally affect the inference of admixture in most situations. We conclude that unbalanced sampling may cause important biases in the admixture proportions estimated by structure, especially when a small number of markers are used, and those biases can be worsened by the effect of drift and unequal genetic contribution of parental populations. Empirical studies should thus be careful with their sampling design and consider historical characteristics when using this software to estimate the ancestry of individuals from admixed populations.

中文翻译：

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采样方案和漂移可以使结构推断的混合比例产生偏差。

来自遗传分化但不完全隔离的种群的个体的杂交可导致混合种群的形成，对生态和进化具有重要意义。在这个模拟研究中，我们评估了软件结构如何估计单个混合比例受到不同因素的定量影响。使用两个不同群体之间的各种混合场景，我们发现来自父母群体的不平衡抽样可能会严重影响推断的混合比例；此外，来自混合总体的按比例大的样本也会降低推断的准确性和精确度。正如预期的那样，混合事件后亲本种群和漂移之间的微弱分化强烈增加了由不均匀采样引起的偏差。我们还表明，当父母群体对混合群体的贡献不均时，混合比例通常更偏向于偏向性。最后，除了少数例外，使用大量标记可以减少这些偏差，但在大多数情况下，对个体祖先使用替代先验或不相关的等位基因模型只会略微影响混合物的推断。我们得出结论，不平衡的抽样可能会导致估计的混合比例的重要偏差结构，尤其是当使用少量标记时，这些偏差可能会因漂移的影响和亲本种群的不平等遗传贡献而恶化。因此，在使用该软件估计来自混合种群的个体的血统时，实证研究应谨慎对待其抽样设计并考虑历史特征。