NitroGene: privacy-preserving collaborative genomic analysis using AWS nitro enclaves

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 analyse 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 analysed 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.

We demonstrate that NitroGene produces results that are concordant with centrally pooled analyses across three representative genomic applications: collaborative principal component analysis (PCA) on 2712 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.

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.