I Built a Private Genomics Study with Stoffel MPC

7 hours ago

MPC (multi-party computation) enables genomic studies to compute aggregate results without collecting participants' raw DNA.
A proof of concept with Stoffel MPC successfully computed aggregate allele counts and a weighted cohort score from 100 simulated participants without any party seeing the complete dataset.
The experiment used a decentralized design where each user's genotype data remains on their device, shares are sent directly to MPC parties, and no central server collects all data.
Technical implementation involved 100 client processes, 4 Stoffel MPC parties, and a coordinator, all running on a single development machine.
The computation completed in under a minute (45.29 seconds total) with correct results: aggregate counts for 6 SNPs and a weighted score of 498.
Developer experience with StoffelLang was positive, making private computation feel like ordinary application development.
Production considerations include independent party operation, mobile SDK development, query controls to prevent inference, and scaling to thousands of clients.

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