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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 computational cost is notorious in genome-wide association studies (GWAS). Here, we developed a supercomputing-aided approach...

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Detalles Bibliográficos
Autores principales: Paik, Hyojung, Cho, Yongseong, Cho, Seong Beom, Kwon, Oh-Kyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001997/
https://www.ncbi.nlm.nih.gov/pubmed/35399013
http://dx.doi.org/10.5808/gi.22001
Descripción
Sumario: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 computational 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 10(7) permutations of one locus in MPI-GWAS, it was calculated in 600 s using 2,720 CPU cores. For 10(7) 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.