Aika Terada
ABSTRACT
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.
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Index Terms
- High-speed westfall-young permutation procedure for genome-wide association studies
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