Secure phasing of private genomes in a trusted execution environment with TX-Phase

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Genotype imputation servers enhance genomic data analysis but raise privacy concerns for sensitive cohorts.
• Existing privacy-preserving tools lack support for haplotype phasing, a crucial step in imputation.
• Haplotype phasing algorithms are complex, posing challenges for privacy-preserving implementations.

Purpose of the Study:

• To develop a secure haplotype phasing method that preserves data privacy.
• To enable secure analysis of private genomic data using large reference panels.
• To overcome limitations of existing privacy-preserving tools in genomic data analysis.

Main Methods:

• Introduction of TX-Phase, a secure haplotype phasing method utilizing trusted execution environments (TEEs).
• Implementation of novel data-oblivious algorithmic techniques, including compressed reference panels and dynamic fixed-point arithmetic.
• Mitigation of side-channel leakages within TEEs to ensure data confidentiality and computational integrity.

Main Results:

• TX-Phase demonstrates state-of-the-art phasing accuracy on diverse datasets (UK Biobank, Haplotype Reference Consortium).
• The method achieves practical runtimes, making it suitable for real-world applications.
• Successful secure phasing of private genomes is achieved, maintaining data confidentiality.

Conclusions:

• TX-Phase provides a robust solution for secure haplotype phasing, addressing critical privacy concerns.
• The developed techniques enable broader access to large reference genomic datasets for research.
• This work facilitates privacy-preserving genomic analysis, expanding research possibilities for sensitive cohorts.