MPI-GWAS: a supercomputing-aided permutation approach for genome-wide association studies
Permutation testing is a robust and popular approach for significance testing in genomic research that has the advantage of reducing inflated type 1 error rates; however, its compu-tational cost is notorious in genome-wide association studies (GWAS). Here, we developed a supercomputing-aided approac...
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          | Published in | Genomics & informatics Vol. 20; no. 1; p. e14 | 
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| Main Authors | , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
            Korea Genome Organization
    
        31.03.2022
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 2234-0742 1598-866X 2234-0742  | 
| DOI | 10.5808/gi.22001 | 
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| Summary: | Permutation testing is a robust and popular approach for significance testing in genomic research that has the advantage of reducing inflated type 1 error rates; however, its compu-tational cost is notorious in genome-wide association studies (GWAS). Here, we developed a supercomputing-aided approach to accelerate the permutation testing for GWAS, based on the message-passing interface (MPI) on parallel computing architecture. Our application, called MPI-GWAS, conducts MPI-based permutation testing using a parallel computing approach with our supercomputing system, Nurion (8,305 compute nodes, and 563,740 central processing units [CPUs]). For 107 permutations of one locus in MPI-GWAS, it was calculated in 600 s using 2,720 CPU cores. For 107 permutations of ~30,000–50,000 loci in over 7,000 subjects, the total elapsed time was ~4 days in the Nurion supercomputer. Thus, MPI-GWAS enables us to feasibly compute the permutation-based GWAS within a reason-able time by harnessing the power of parallel computing resources. | 
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| Bibliography: | Hyojung Paik and Yongseong Cho contributed equally to this work. | 
| ISSN: | 2234-0742 1598-866X 2234-0742  | 
| DOI: | 10.5808/gi.22001 |