Jouganous Julien, Long Will, Ragsdale Aaron P, Gravel Simon
Department of Human Genetics and Genome Quebec Innovation Centre, McGill University, Montreal, QC H3A 0G1, Canada.
Department of Human Genetics and Genome Quebec Innovation Centre, McGill University, Montreal, QC H3A 0G1, Canada
Genetics. 2017 Jul;206(3):1549-1567. doi: 10.1534/genetics.117.200493. Epub 2017 May 11.
Understanding variation in allele frequencies across populations is a central goal of population genetics. Classical models for the distribution of allele frequencies, using forward simulation, coalescent theory, or the diffusion approximation, have been applied extensively for demographic inference, medical study design, and evolutionary studies. Here we propose a tractable model of ordinary differential equations for the evolution of allele frequencies that is closely related to the diffusion approximation but avoids many of its limitations and approximations. We show that the approach is typically faster, more numerically stable, and more easily generalizable than the state-of-the-art software implementation of the diffusion approximation. We present a number of applications to human sequence data, including demographic inference with a five-population joint frequency spectrum and a discussion of the robustness of the out-of-Africa model inference to the choice of modern population.
理解不同人群中等位基因频率的变异是群体遗传学的核心目标。使用正向模拟、合并理论或扩散近似的等位基因频率分布经典模型，已广泛应用于人口统计学推断、医学研究设计和进化研究。在此，我们提出了一个关于等位基因频率演化的常微分方程的易处理模型，该模型与扩散近似密切相关，但避免了其许多局限性和近似。我们表明，该方法通常比扩散近似的最新软件实现更快、数值上更稳定且更易于推广。我们展示了对人类序列数据的一些应用，包括使用五群体联合频率谱进行人口统计学推断，以及讨论走出非洲模型推断对现代人群选择的稳健性。
