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SmileFinder: a resampling-based approach to evaluate signatures of selection from genome-wide sets of matching allele frequency data in two or more diploid populations

机译:SmileFinder:一种基于重采样的方法用于评估两个或多个二倍体群体中全基因组匹配等位基因频率数据的选择签名

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摘要

BackgroundAdaptive alleles may rise in frequency as a consequence of positive selection, creating a pattern of decreased variation in the neighboring loci, known as a selective sweep. When the region containing this pattern is compared to another population with no history of selection, a rise in variance of allele frequencies between populations is observed. One challenge presented by large genome-wide datasets is the ability to differentiate between patterns that are remnants of natural selection from those expected to arise at random and/or as a consequence of selectively neutral demographic forces acting in the population.
机译:背景自适应等位基因可能会由于阳性选择而导致频率升高,从而在相邻基因座中产生减少的变异模式,称为选择性扫描。当将包含该模式的区域与没有选择历史的另一个种群进行比较时,会观察到种群之间等位基因频率的方差增加。大型全基因组数据集提出的一项挑战是,如何区分自然选择的残留模式与预期随机产生的模式和/或由于人口中选择性中性人口力量的结果而产生的模式。

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