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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Achieving GWAS with homomorphic encryption.

Jun Jie Sim1, Fook Mun Chan2, Shibin Chen2

  • 1Institute of Infocomm Research, Agency for Science, Technology and Research, Singapore, Singapore. simjj@i2r.a-star.edu.sg.

BMC Medical Genomics
|July 23, 2020
PubMed
Summary
This summary is machine-generated.

Homomorphic encryption (HE) enables private genome-wide association studies (GWAS) by securing single-nucleotide polymorphisms (SNPs). This method allows for secure genetic analysis, protecting participant privacy during complex data computations.

Keywords:
Genome wide association studies (GWAS)Homomorphic encryption (HE)Single nucleotide polymorphism (SNP)

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Area of Science:

  • Genomics
  • Cryptography
  • Bioinformatics

Background:

  • Genome-wide association studies (GWAS) investigate gene-trait relationships using single-nucleotide polymorphisms (SNPs).
  • The use of numerous SNPs in GWAS raises significant privacy and security concerns due to unique individual identification.
  • Large SNP datasets increase the risk of participant privacy breaches.

Purpose of the Study:

  • To develop and demonstrate a privacy-preserving method for conducting genome-wide association studies (GWAS).
  • To adapt existing GWAS algorithms for secure computation using homomorphic encryption (HE).

Main Methods:

  • Implemented a secure GWAS method utilizing homomorphic encryption (HE).
  • Adapted the semi-parallel GWAS algorithm for HE through encrypted matrix operations and approximations.
  • Leveraged the CKKS encryption scheme to enhance SNP packing within ciphertexts.
  • Developed a cache module for efficient ciphertext management, reducing memory usage.

Main Results:

  • Successfully implemented the HE-based GWAS solution using HEAAN and SEAL libraries.
  • Achieved a computation time of 24.70 minutes for a dataset of 245 samples, 4 covariates, and 10,643 SNPs.
  • Demonstrated the feasibility of performing GWAS with HE.

Conclusions:

  • Homomorphic encryption (HE) can be effectively used to perform genome-wide association studies (GWAS) while ensuring privacy.
  • Suitable approximations allow for the adaptation of GWAS algorithms to HE environments.
  • This approach enhances data security in genetic research.