Article

SECRET-GWAS: Confidential Computing for Population-Scale GWAS

2024-04-28

Abstract excerpt

Genomic data from a single institution lacks global diversity representation, especially for rare variants and diseases. Confidential computing can enable collaborative GWAS without compromising privacy or accuracy, however, due to limited secure memory space and performance overheads previous solutions fail to support widely used regression methods. We present SECRET-GWAS: a rapid, privacy-preserving, population-...

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Identifiers and source

Literature Corpus work: 83abce36-901f-5f54-bd2a-af809f5ce303
DOI: 10.1101/2024.04.24.590989

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