Babron Marie-Claude, Etcheto Adrien, Dizier Marie-Helene
Inserm, UMR946, Genetic variation and Human diseases, F-75010, Paris, France.
Université Paris-Diderot, Sorbonne Paris-Cité, UMR946, F-75010, Paris, France.
Ann Hum Genet. 2015 Sep;79(5):380-384. doi: 10.1111/ahg.12113. Epub 2015 Apr 23.
A major problem in gene-gene interaction studies in large marker panels is how to correct for multiple testing while accounting for the dependence between marker pairs due to the presence of linkage disequilibrium. The "gold standard" approach is to perform permutations of case/control labels. However, this is often not feasible in practice, due to computational demands. Here, we propose a correction based on the effective number of independent tests of interaction between marker pairs. This number depends on the effective number of independent single-marker tests. We tested its validity using simulated samples, as well as that of another correction of marker pair tests. We showed that our approach was valid while the other correction strongly underestimated the effective number of independent tests. Our method provides estimates of the effective number of independent tests close to those reported in the literature for a Genome-Wide Interaction Study on a 550K chip. Our correction method is quick and simple, and can be applied whatever the marker panel and the underlying linkage disequilibrium pattern.
在大型标记面板的基因-基因相互作用研究中,一个主要问题是如何在考虑由于连锁不平衡导致的标记对之间的依赖性的同时校正多重检验。“金标准”方法是对病例/对照标签进行置换。然而,由于计算需求,这在实际中通常不可行。在此,我们提出一种基于标记对之间相互作用的独立检验有效数量的校正方法。这个数量取决于独立单标记检验的有效数量。我们使用模拟样本测试了其有效性,以及另一种标记对检验校正方法的有效性。我们表明我们的方法是有效的,而另一种校正方法严重低估了独立检验的有效数量。我们的方法提供的独立检验有效数量估计值与文献中报道的关于550K芯片的全基因组相互作用研究的估计值相近。我们的校正方法快速且简单,并且无论标记面板和潜在的连锁不平衡模式如何都可应用。