Data from: Effects of sampling close relatives on some elementary population genetics analyses

In many molecular ecology analyses, the genotyped individuals are assumed to be sampled at random from a population and thus to be representative of the population. Realistically, however, a sample may contain excessive close relatives (ECR) because, for example, localized juveniles are drawn from fecund species. How the routinely conducted elementary genetic analyses are affected by and thus how best to deal with ECR are lacking. This study quantifies systematically the effects of ECR on some popular population genetics analyses, including the estimation of allele frequencies, F-statistics, expected heterozygosity (He), effective and observed numbers of alleles, and the tests of Hardy-Weinberg equilibrium (HWE) and linkage equilibrium (LE). My analytical work, assisted by simulations, shows that ECR has large and global effects on all of the above marker analyses. The naïve approach of simply ignoring ECR could yield low-precision and often biased parameter estimates, and could cause too many false rejections of HWE and LE. The bold approach, which simply identifies and removes ECR, and the cautious approach, which estimates target parameters (e.g. He) by accounting for ECR and using naïve allele frequency estimates, eliminate the bias and the false HWE and LE rejections, but could reduce estimation precision substantially. The likelihood approach, which accounts for ECR in estimating allele frequencies and thus target parameters, usually yields unbiased and the most accurate parameter estimates. The choice of the four approaches may depend on the particular marker analysis. The results are discussed in the context of using marker data for understanding population properties and marker properties.在诸多分子生态学（molecular ecology）分析中，学界通常默认基因型个体是从种群中随机抽取的，因而可代表该种群的遗传特征。然而实际情况中，样本往往可能包含过多的过度近缘个体（excessive close relatives, ECR）——例如，从繁殖力旺盛的物种中取样时，局部种群的幼体常会构成这类偏倚样本。目前，针对常规基础遗传分析如何受过度近缘个体影响，以及应如何最优应对这类个体的相关研究仍较为匮乏。本研究系统量化了过度近缘个体对若干主流种群遗传学分析的影响，所涵盖的分析包括等位基因频率估计、F统计量（F-statistics）、期望杂合度（He）、有效等位基因数与观测等位基因数，以及哈迪-温伯格平衡（Hardy-Weinberg equilibrium, HWE）与连锁平衡（linkage equilibrium, LE）检验。本研究结合模拟辅助开展的分析工作表明，过度近缘个体对上述所有标记分析均具有广泛且显著的影响。若采用直接忽略过度近缘个体的朴素分析方法，不仅会得到精度较低且常带有偏倚的参数估计结果，还会导致过多的哈迪-温伯格平衡与连锁平衡假阳性拒绝。而直接识别并移除过度近缘个体的大胆处理方法，以及通过考虑过度近缘个体的影响、结合朴素等位基因频率估计来计算目标参数（如期望杂合度）的谨慎处理方法，虽可消除参数偏倚与平衡检验的假阳性错误，但会大幅降低参数估计的精度。而在估计等位基因频率乃至后续目标参数时纳入过度近缘个体影响的似然方法，通常可得到无偏且精度最优的参数估计结果。四种方法的选择需依据具体的标记分析场景而定。本研究结果将结合利用分子标记数据解析种群特性与标记特性的研究背景展开讨论。