Power of genetic association studies with fixed and random genotype frequencies.
Power of genetic association studies with fixed and random genotype frequencies.
复制标题
固定和随机基因型频率的遗传关联研究的力量。
DOI：
10.1111/j.1469-1809.2010.00598.x
复制
发表时间：
2010
影响因子：
1.9
通讯作者：
Schucany,WilliamR
中科院分区：
文献类型：
--
作者：
Kozlitina,Julia;Xing,Chao;Pertsemlidis,Alexander;Schucany,WilliamR
在估计遗传关联研究的功效时，通常假设等位基因和基因型频率是已知的，并且每个基因型的个体数量被设置为等于他们在哈代温伯格平衡下的期望值。事实上，等位基因和基因型频率都是未知的，因此是随机的。以前有人建议，忽略这些参数的不确定性可能会导致夸大的功率预期。为了克服这个问题，可以在未知频率的分布上平均功率估计。我们研究了幂平均方法，发现尽管直观上很吸引人，但它在实践中可能不会提高精度，同时会显着增加计算时间。对于一个固定的等位基因频率，我们表明，高估的数量迅速减少样本大小，是完全可以忽略不计的N> 200。对于未知频率，平均结果取决于遗传模型，并且可能并不总是提供更保守的功效估计。我们探讨的影响因素，确定关联研究的统计功率的不确定性，并提出了一个更经济的方法进行功率分析。
When estimating the power of genetic association studies, the allele and genotype frequencies are often assumed to be known, and the numbers of individuals with each genotype are set equal to their expectations under Hardy‐Weinberg equilibrium. In fact, both allele and genotype frequencies are unknown and thus random. It has previously been suggested that ignoring uncertainty in these parameters could lead to inflated power expectations. To overcome the problem, one can average power estimates over the distributions of unknown frequencies. We investigate the power‐averaging method and find that, despite the intuitive appeal, it may not improve accuracy in practice, while significantly increasing computational time. For a fixed allele frequency, we show that the amount of overestimation diminishes rapidly with sample size and is completely negligible forN> 200. For an unknown frequency, the result of averaging depends on the genetic model, and may not always provide a more conservative estimate of power. We explore the effect of uncertainty in the factors that determine statistical power of association studies and propose a more economical approach to the power analysis.