SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs

Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

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Publication Details

Journal
Bioinformatics
Published
2026-01-15
DOI
https://doi.org/10.1093/bioinformatics/btag032
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs

Mitchell Conery, Rohan Bhukar, John Hessington, M.R. Ravi et al.
Bioinformatics
Genetic Associations and Epidemiology
article

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs

Mitchell Conery, Rohan Bhukar, John Hessington, M.R. Ravi, Rachit Kumar, Tarak Nath Nandi, Molei Liu, Ketan Maheshwari, Karl Keat, Youngdae Kim, Alex Rodriguez, J Michael Gaziano, Wei Zhou, Jennifer E Huffman, Anurag Verma
article en

Abstract

Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

BioinformaticsVol. 42(3)
Broad Institute (US), Argonne National Laboratory (US), Brigham and Women's Hospital (US), Oak Ridge National Laboratory (US), Harvard University (US), VA Boston Healthcare System (US), VA Office of Research and Development (US), Stanley Foundation (US), Massachusetts General Hospital (US), Palo Alto Veterans Institute for Research (US), Translational Therapeutics (United States) (US), Philadelphia VA Medical Center (US), Ulsan National Institute of Science and Technology (KR), New York University (US), Columbia University (US), University of Pennsylvania (US), Philadelphia University (US)
U.S. Department of Energy, U.S. Department of Veterans Affairs, Office of Research and Development, National Research Foundation, Ulsan National Institute of Science and Technology, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, Office of Science, Institute for Information and Communications Technology Promotion, National Institute of General Medical Sciences, National Institute of Diabetes and Digestive and Kidney Diseases, U.S. National Library of Medicine, Oak Ridge National Laboratory
Openalex Percentile: Top 75%
Genetic Associations and Epidemiology
DOIOpen Access PDFOpenAlex
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