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Fast kernel-based association testing of non-linear genetic effects for biobank-scale data.

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.

SUBMITTER: Fu B

PROVIDER: S-EPMC10427662 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Fast kernel-based association testing of non-linear genetic effects for biobank-scale data.

Fu Boyang B Pazokitoroudi Ali A Sudarshan Mukund M Liu Zhengtong Z Subramanian Lakshminarayanan L Sankararaman Sriram S

Nature communications 20230815 1

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 quantitat ...[more]

PMID: 37582955

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