WFABC：一种基于Wright-Fisher ABC的从时间采样数据推断有效种群大小和选择系数的方法
WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data
摘要：
随着测序技术的新发展，时间采样数据变得更加可用和可访问。自然，已经有平行的努力，从这些数据集推断群体遗传参数。在这里，我们比较和分析四个最近的方法的基础上，赖特-费舍尔模型推断选择系数（S）给定有效种群大小（Ne），模拟时间数据集。此外，我们证明了最近提出的基于ABC的方法的优点，该方法能够正确地从时间序列数据推断全基因组平均Ne，然后将其设置为准确和精确地推断每个位点选择系数的先验。我们在一个新的软件中实现了这种ABC方法，并将其应用于一个经典的时间序列数据集的medionigra基因型的蛾Panaxia dominula。我们表明，隐性致死模型是最好的解释所观察到的变化，等位基因频率通过实施估计的显性比（h）。
英文摘要：
With novel developments in sequencing technologies, time-sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these datasets. Here, we compare and analyze four recent approaches based on the Wright-Fisher model for inferring selection coefficients (s) given effective population size (Ne), with simulated temporal datasets. Furthermore, we demonstrate the advantage of a recently proposed ABC-based method that is able to correctly infer genome-wide average Ne from time-serial data, which is then set as a prior for inferring per-site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time-serial dataset of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h).
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