The genomic control (GC) approach is extensively used to effectively control false positive signals due to population stratification in genome-wide association studies (GWAS). However, GC affects the statistical power of GWAS. The loss of power depends on the magnitude of the inflation factor (λ) that is used for GC. We simulated meta-analyses of different GWAS. Minor allele frequency (MAF) ranged from 0·001 to 0·5 and λ was sampled from two scenarios: (i) random scenario (empirically-derived distribution of real λ values) and (ii) selected scenario from simulation parameter modification. Adjustment for λ was considered under single correction (within study corrected standard errors) and double correction (additional λ corrected summary estimate). MAF was a pivotal determinant of observed power. In random λ scenario, double correction induced a symmetric power reduction in comparison to single correction. For MAF 1·2 and MAF >5%. Our results provide a quick but detailed index for power considerations of future meta-analyses of GWAS that enables a more flexible design from early steps based on the number of studies accumulated in different groups and the λ values observed in the single studies.

中文翻译：

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在全基因组关联研究的荟萃分析中考虑λ膨胀因子的功效。

在全基因组关联研究（GWAS）中，由于种群分层，基因组控制（GC）方法被广泛用于有效控制假阳性信号。但是，GC影响GWAS的统计能力。功率损耗取决于用于GC的膨胀因子（λ）的大小。我们模拟了不同GWAS的荟萃分析。次要等位基因频率（MAF）在0·001到0·5范围内，并且从两个场景中采样了λ：（i）随机场景（根据经验得出的实际λ值的分布）和（ii）从模拟参数修改中选择的场景。在单校正（在研究校正的标准误差范围内）和双校正（在其他λ校正的总估算值）下考虑对λ的调整。MAF是观察功率的关键决定因素。在随机λ情况下，与单次校正相比，双次校正导致对称功率降低。对于MAF 1·2和MAF> 5％。我们的结果为GWAS未来荟萃分析的功率考虑提供了一个快速而详细的索引，该索引可根据不同组中积累的研究数量和单个研究中观察到的λ值，从早期步骤进行更灵活的设计。