Wellcome Trust Centre for Human Genetics, Roosevelt Drive, University of Oxford, Oxford, United Kingdom.
Genet Epidemiol. 2011 Dec;35(8):781-9. doi: 10.1002/gepi.20627. Epub 2011 Sep 15.
Large-scale meta-analyses of genome-wide association scans (GWAS) have been successful in discovering common risk variants with modest and small effects. The detection of lower frequency signals will undoubtedly require concerted efforts of at least similar scale. We investigate the sample size-dictated power limits of GWAS meta-analyses, in the presence and absence of modest levels of heterogeneity and across a range of different allelic architectures. We find that data combination through large-scale collaboration is vital in the quest for complex trait susceptibility loci, but that effect size heterogeneity across meta-analyzed studies drawn from similar populations does not appear to have a profound effect on sample size requirements.
大规模的全基因组关联扫描（GWAS）元分析已经成功地发现了具有中等和小效应的常见风险变异。检测低频信号无疑需要至少类似规模的协同努力。我们研究了 GWAS 元分析在存在和不存在适度异质性以及在不同等位基因结构范围内的样本量决定的功效限制。我们发现，通过大规模合作进行数据组合对于寻找复杂性状易感性基因座至关重要，但来自相似人群的元分析研究中效应大小的异质性似乎对样本量要求没有深远的影响。
