Secure genome-wide association analysis using multiparty computation

Cho et al. ‘describe a protocol for large-scale genome-wide analysis that facilitates quality control and population stratification correction […] while maintaining the confidentiality of underlying genotypes and phenotypes. […] This approach may help to make currently restricted data available to the scientific community and could potentially enable secure genome crowdsourcing, allowing individuals to contribute their genomes to a study without compromising their privacy.’

  • Cho H, Wu DJ, Berger B
    Secure genome-wide association analysis using multiparty computation
    Nature Biotechnology. 2018. Online May 07.
    (Abstract, PDF, Source Code)

Deriving genomic diagnoses without revealing patient genomes

Jagadeesh et al. encode an individuals functional variants as a binary vector. They then use Yao’s protocol to identify relevant coincidences between pools of such vectors engaging in secure multiparty computation.

  • Jagadeesh KA, Wu DJ, Birgmeier JA, Boneh D, Bejerano G
    Deriving genomic diagnoses without revealing patient genomes
    Science. 2017. Volume 357. Issue 6352. Pages 692–695.
    (Abstract, PDF, Source Code)

A privacy-preserving solution for compressed storage and selective retrieval of genomic data

The authors ‘present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling).’

  • Huang Z, Ayday E, Lin H, Aiyar RS, Molyneaux A, Xu Z, Fellay J, Steinmetz LM, Hubaux JP
    A privacy-preserving solution for compressed storage and selective retrieval of genomic data
    Genome Research. 2016. Volume 26. Issue 12. Pages 1687-1696.
    (Abstract, PDF, Supplement including source code)

Efficient privacy-preserving string search and an application in genomics

The authors ‘propose a novel approach that combines efficient string data structures such as the Burrows–Wheeler transform with cryptographic techniques based on additive homomorphic encryption. [They] assume that the sequence data is searchable in efficient iterative query operations over a large indexed dictionary, for instance, from large genome collections and employing the (positional) Burrows–Wheeler transform. [They] use a technique called oblivious transfer that is based on additive homomorphic encryption to conceal the sequence query and the genomic region of interest in positional queries.’

  • Shimizu K, Nuida K, Rätsch G
    Efficient privacy-preserving string search and an application in genomics
    Bioinformatics. 2016. Volume 32. Issue 11. Pages 1652–1661.
    (Abstract, PDF)

Identifying genetic relatives without compromising privacy

Truncated hash values of haplotype segments are used as privately known ‘genome sketches’. These serve as fuzzy extractors to decode publicly known ‘secure genome sketches’ revealing information only between related individuals.

  • He D, Furlotte NA, Hormozdiari F, Joo JWJ, Wadia A, Ostrovsky R, Sahai A, Eskin E
    Identifying genetic relatives without compromising privacy
    Genome Research. 2014. Volume 24. Issue 4. Pages 664-672.
    (Abstract, PDF)