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哈迪-温伯格平衡精确检验中的中位p值。

The mid p-value in exact tests for Hardy-Weinberg equilibrium.

作者信息

Graffelman Jan, Moreno Victor

机构信息

Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Avinguda Diagonal 647, Barcelona, Spain

出版信息

Stat Appl Genet Mol Biol. 2013 Aug;12(4):433-48. doi: 10.1515/sagmb-2012-0039.

Abstract

OBJECTIVE

Exact tests for Hardy-Weinberg equilibrium are widely used in genetic association studies. We evaluate the mid p-value, unknown in the genetics literature, as an alternative for the standard p-value in the exact test.

METHOD

The type 1 error rate and the power of the exact test are calculated for different sample sizes, significance levels, minor allele counts and degrees of deviation from equilibrium. Three different p-value are considered: the standard two-sided p-value, the doubled one-sided p-value and the mid p-value. Practical implications of using the mid p-value are discussed with HapMap datasets and a data set on colon cancer.

RESULTS

The mid p-value is shown to have a type 1 error rate that is always closer to the nominal level, and to have better power. Differences between the standard p-value and the mid p-value can be large for insignificant results, and are smaller for significant results. The analysis of empirical databases shows that the mid p-value uncovers more significant markers, and that the equilibrium null distribution is not tenable for both databases.

CONCLUSION

The standard exact p-value is overly conservative, in particular for small minor allele frequencies. The mid p-value ameliorates this problem by bringing the rejection rate closer to the nominal level, at the price of occasionally exceeding the nominal level.

摘要

目的

哈迪-温伯格平衡的确切检验在基因关联研究中被广泛应用。我们评估遗传学文献中未知的中间p值,作为确切检验中标准p值的替代。

方法

针对不同样本量、显著性水平、次要等位基因计数和偏离平衡的程度,计算确切检验的I型错误率和检验效能。考虑三种不同的p值:标准双侧p值、双侧单尾p值的两倍以及中间p值。利用国际人类基因组单体型图计划(HapMap)数据集和一个结肠癌数据集讨论使用中间p值的实际意义。

结果

结果显示中间p值的I型错误率始终更接近名义水平,且检验效能更高。对于不显著的结果,标准p值与中间p值之间的差异可能很大,而对于显著结果,差异较小。对经验数据库的分析表明,中间p值能发现更多显著的标记,且两个数据库的平衡零分布均不成立。

结论

标准的确切p值过于保守,尤其是对于小的次要等位基因频率。中间p值通过使拒绝率更接近名义水平来改善这一问题,但代价是偶尔会超过名义水平。

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