NitroGene: Privacy-Preserving Collaborative Genomic Analysis Using AWS Nitro Enclaves

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ID: 320791
2026
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Abstract
Abstract Motivation Protecting participant privacy is a major challenge in large-scale biomedical collaborations. We present NitroGene, an open-source framework for privacy-preserving collaborative genomic analysis using AWS Nitro Enclaves. NitroGene uses an architecture consisting of a client application, proxy server, and hardware-isolated enclave, secured through end-to-end 256-bit encryption and cryptographic attestation via the Nitro Security Module. The framework enables multiple institutions to jointly analyze pooled genomic data without exposing raw data to other participants or the server operator. Each participant encrypts and uploads data files, which are decrypted, merged, and analyzed within the enclave before encrypted results are returned to each participant. NitroGene is application-agnostic and supports existing analysis tools without modification by encapsulating them in Docker images. Results We demonstrate that NitroGene produces results that are concordant with centrally pooled analyses across three representative genomic applications: collaborative principal component analysis (PCA) on 2,712 subjects, cross-cohort kinship estimation involving 32,604 pairwise comparisons, and collaborative genome-wide association studies (GWAS) on 1 million SNPs. Results show that NitroGene enables privacy-preserving collaborative genomic analysis while maintaining compatibility with existing analysis workflows. Availability and implementation NitroGene is publicly available on Github (https://github.com/zakkaz1/NitroGene) including the documentation to test the three analysis pipelines and for building new pipelines.
Reference Key
openalex_W7168135299 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zakariya Ali, Arif Harmanci
Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag191
URL
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