| Title: | Fast kernel-based association testing of non-linear genetic effects for biobank-scale data |
| Journal: | Nature Communications |
| Published: | 15 Aug 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37582955/ |
| DOI: | https://doi.org/10.1038/s41467-023-40346-2 |
| URL: | https://www.nature.com/articles/s41467-023-40346-2.pdf |
| Citations: | 4 (4 in last 2 years) as of 8 Aug 2024 |
Publication 9751
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Abstract
Our knowledge of non-linear genetic effects on complex traits remains limited, in part, due to the modest power to detect such effects. While kernel-based tests offer a versatile approach to test for non-linear relationships between sets of genetic variants and traits, current approaches cannot be applied to Biobank-scale datasets containing hundreds of thousands of individuals. We propose, FastKAST, a kernel-based approach that can test for non-linear effects of a set of variants on a quantitative trait. FastKAST provides calibrated hypothesis tests while enabling analysis of Biobank-scale datasets with hundreds of thousands of unrelated individuals from a homogeneous population. We apply FastKAST to 53 quantitative traits measured across ≈ 300 K unrelated white British individuals in the UK Biobank to detect sets of variants with non-linear effects at genome-wide significance.</p>
6 Authors
- Boyang Fu
- Ali Pazokitoroudi
- Mukund Sudarshan
- Zhengtong Liu
- Lakshminarayanan Subramanian
- Sriram Sankararaman
1 Application
| Application ID | Title |
|---|---|
| 33127 | Methods for large-scale medical and population genetic data |
Enabling scientific discoveries that improve human health