Author

John Hessington

University of Pennsylvania

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Alex Rodriguez· 1 shared Anurag VermaiD· 1 shared Benjamin F. VoightiD· 1 shared Drew Schmidt· 1 shared Edmon BegoliiD· 1 shared Georgia D. TourassiiD· 1 shared J. Michael GazianoiD· 1 shared Jennifer E. HuffmaniD· 1 shared

Activity by Year

2024-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperGenetics

Alex Rodriguez

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran Program

Alex Rodriguez, Young‐Dae Kim, Tarak Nandi, Karl Keat, Rachit Kumar, Rohan Bhukar, Mitchell Conery, Molei Liu, John Hessington, Ketan C. Maheshwari, Drew Schmidt, VA Million Veteran Program, Edmon Begoli, Georgia D. Tourassi, Sumitra Muralidhar, , Ravi Madduri

This paper optimizes the SAIGE algorithm using GPUs to accelerate GWAS on large datasets, achieving 20x speedup on the Million Veteran Program data.

bioRxiv · May 17, 2024 · PreprintGenetics