UK BioCoin: swift trait-specific summary statistics regression for UK Biobank.

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Large-scale biobanks generate valuable genetic discovery statistics.
• Current methods use fixed covariate adjustments, limiting trait-specific analyses.
• Access to individual-level data is often restricted due to privacy concerns.

Purpose of the Study:

• To introduce UK BioCoin (UKC), a computational tool for efficient, user-specified covariate adjustment.
• To enable privacy-preserving sharing of genetic statistics without individual-level data.
• To demonstrate UKC's utility and computational efficiency in genetic research.

Main Methods:

• UKC was developed as a computational device for covariate adjustment.
• UK Biobank data (505 traits, 10 million SNPs) was used for demonstration.
• UKC's performance was compared to individual-level data analyses.

Main Results:

• UKC generated summary statistics closely mirroring individual-level data.
• UKC achieved approximately 80 times greater computational efficiency.
• The framework demonstrated portability to other biobanks, like Westlake Biobank.

Conclusions:

• UKC provides a privacy-preserving method for flexible genetic data sharing.
• The tool significantly enhances computational efficiency in biobank analyses.
• UKC facilitates collaborative research and broadens the scope of genetic discovery.