Genomics Inform.  2022 Mar;20(1):e14. 10.5808/gi.22001.

MPI-GWAS: a supercomputing-aided permutation approach for genome-wide association studies

Affiliations
  • 1Division of Supercomputing, Center for supercomputing application and research, Korea Institute of Science and Technology Information (KISTI), Daejeon 34141, Korea
  • 2Department of Data and HPC Science, University of Science and Technology (UST), Dae-jeon, 34141, Korea
  • 3Department of Bio-Medical Informatics, Gachon University, College of Medicine, Incheon 21565, Korea

Abstract

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.

Keyword

genome-wide association study; message-passing interface; parallel computing; supercomputing
Full Text Links
  • GNI
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr