High-speed Westfall-Young permutation procedure for genome-wide association studies.
High-speed Westfall-Young permutation procedure for genome-wide association studies.
复制标题
用于全基因组关联研究的高速 Westfall-Young 排列程序。
DOI：
10.1145/2808719.2808721
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Sese J.
中科院分区：
文献类型：
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作者：
Terada A;Kim H;Sese J.
全基因组关联研究（GWAS）被广泛用于研究疾病与单核苷酸多态性（SNP）之间的统计学显著关联，以确定疾病的致病因素。在GWAS中，最近已经评估了超过一百万个SNP的统计显著性，但在许多情况下，由于应用保守的多重检验校正（如Bonferroni校正），因此没有发现任何关联。虽然更敏感的方法，如Westfall-Young排列程序（WY），将更多的SNPs与疾病联系起来，但其极长的计算时间阻碍了WY在GWAS中的应用。我们介绍了一种算法来加速WY，命名为高速Westfall-Young置换过程（HWY）。HWY利用三种技术使WY在计算上实用。首先，修剪不能影响调整的显著性水平的SNP的P值计算。其次，使用P值查找表来避免频繁的重复计算。最后，使用GPGPU并行计算。HWY比WY快619倍，比广泛使用的GWAS软件PLINK快122倍以上，并在大约两小时内分析了包含100万个SNP和1000个个体的数据集。用HWY重新分析现有的GWAS数据集可能会发现更多隐藏的SNP-性状关联。
Genome-wide association studies (GWASs) are widely used to investigate statistically significant associations between diseases and single nucleotide polymorphisms (SNPs) to identify causal factors of diseases. In GWAS, statistical significance of more than one million SNPs have been recently assessed, but in many case, no associations are found because of the application of conservative multiple testing corrections, such as Bonferroni correction. While more sensitive methods, such as Westfall-Young permutation procedure (WY), would relate more SNPs with diseases, its extremely long computational time has prohibited from the application of WY to GWAS. We introduce an algorithm to accelerate WY, named High-speed Westfall-Young permutation procedure (HWY). HWY utilizes three techniques to make WY computationally practical. First, P-value calculations for SNPs that cannot affect the adjusted significance level are pruned. Second, a lookup table of P-values is used to avoid frequent duplicate calculations. Finally, computations are parallelized using a GPGPU. HWY was 619 times faster than WY and more than 122 times faster than PLINK, a widely used GWAS software, and analyzed a dataset contained one million SNPs and one thousand individuals in approximately two hours. Re-analysis of existing GWAS datasets with HWY may uncover additional hidden SNP-trait associations.