Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies.

Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies.
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DOI:
10.1198/jasa.2011.ap10657
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发表时间:
2011-09-01
影响因子:
3.7
通讯作者:
Liu JS
Liu JS
中科院分区:
数学1区
文献类型:
--
作者:
Zhang Y;Liu JS

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全基因组关联研究通常涉及数百万个单核苷酸多态性(SNP)的疾病关联同时测试。然而,由于连锁不平衡(LD,相关性的遗传术语),附近基因组区域中的SNP通常高度相关。因此,多重比较的简单Bonferonni校正过于保守。在实践中经常使用的排列测试对于全基因组研究来说既在计算上昂贵又在其范围内受到限制。我们提出了一个准确的和计算效率高的方法,基于泊松去聚类算法,近似全基因组意义的SNP协会。与排列检验和其他多重比较调整方法相比,我们的方法在几秒钟内为数百万次相关比较计算出最准确和最强大的p值调整。我们分析表明,我们的方法的准确性和效率是几乎独立的样本量,SNPs的数量,和规模的p值进行调整。此外,我们的方法可以很容易地采用估计错误发现率。当应用于全基因组SNP数据集时,我们观察到从不同基因组区域评估的高度可变的p值调整结果。然而,在欧洲和非洲人群之间,基因组沿着调整的变化是很好的保守的。p值调整与SNP、重组率和SNP密度之间的LD显著相关。鉴于基因组序列特征的巨大变异性,我们进一步讨论了一种新的方法,使用SNP特异性(局部)阈值来检测全基因组的显着关联。这篇文章在网上有补充材料。
Genome-wide association studies commonly involve simultaneous tests of millions of single nucleotide polymorphisms (SNP) for disease association. The SNPs in nearby genomic regions, however, are often highly correlated due to linkage disequilibrium (LD, a genetic term for correlation). Simple Bonferonni correction for multiple comparisons is therefore too conservative. Permutation tests, which are often employed in practice, are both computationally expensive for genome-wide studies and limited in their scopes. We present an accurate and computationally efficient method, based on Poisson de-clumping heuristics, for approximating genome-wide significance of SNP associations. Compared with permutation tests and other multiple comparison adjustment approaches, our method computes the most accurate and robust p-value adjustments for millions of correlated comparisons within seconds. We demonstrate analytically that the accuracy and the efficiency of our method are nearly independent of the sample size, the number of SNPs, and the scale of p-values to be adjusted. In addition, our method can be easily adopted to estimate false discovery rate. When applied to genome-wide SNP datasets, we observed highly variable p-value adjustment results evaluated from different genomic regions. The variation in adjustments along the genome, however, are well conserved between the European and the African populations. The p-value adjustments are significantly correlated with LD among SNPs, recombination rates, and SNP densities. Given the large variability of sequence features in the genome, we further discuss a novel approach of using SNP-specific (local) thresholds to detect genome-wide significant associations. This article has supplementary material online.
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