shz9/ukb-ld

Linkage-Disequilibrium (LD) matrices for six continental ancestry groups from the UK Biobank

This dataset contains Linkage Disequilibrium (LD) matrices for six ancestry groups from the UK Biobank.

LD matrices record the SNP-by-SNP correlations in a given sample of individuals from the general population. In this case, we threshold the matrices so that we only record the correlations between variants in the same LD block (defined by LDetect). The continental ancestry groups are defined by the Pan-UKB initiative as:

• EUR = European ancestry (N=362446)
• CSA = Central/South Asian ancestry (N=8284)
• AFR = African ancestry (N=6255)
• EAS = East Asian ancestry (N=2700)
• MID = Middle Eastern ancestry (N=1567)
• AMR = Admixed American ancestry (N=987)

The sample sizes here are restricted to unrelated individuals in the UK Biobank. The matrices were computed using magenpy and quantized to int8 data type for better compressibility. These matrices contain pairwise correlations for up to 1.4 million HapMap3+ variants.

To access these matrices, consult the codebase of magenpy, our custom python package with special data structures for processing these LD matrices.

For more details on how these matrices were computed, please consult our manuscript:

Zabad, S., Haryan, C. A., Gravel, S., Misra, S., Li, Y. (2025). Toward whole-genome inference of polygenic scores with fast and memory-efficient algorithms. The American Journal of Human Genetics, 112(7), 1528-1546. https://doi.org/10.1016/j.ajhg.2025.05.002

@article{ZABAD20251528,
    title = {Toward whole-genome inference of polygenic scores with fast and memory-efficient algorithms},
    journal = {The American Journal of Human Genetics},
    volume = {112},
    number = {7},
    pages = {1528-1546},
    year = {2025},
    issn = {0002-9297},
    doi = {https://doi.org/10.1016/j.ajhg.2025.05.002},
    url = {https://www.sciencedirect.com/science/article/pii/S000292972500182X},
    author = {Shadi Zabad and Chirayu Anant Haryan and Simon Gravel and Sanchit Misra and Yue Li},
}