Autor: |
Shiyang Ma, Chen Wang, Atlas Khan, Linxi Liu, James Dalgleish, Krzysztof Kiryluk, Zihuai He, Iuliana Ionita-Laza |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
Genome Biology, Vol 24, Iss 1, Pp 1-28 (2023) |
Druh dokumentu: |
article |
ISSN: |
1474-760X |
DOI: |
10.1186/s13059-023-02864-6 |
Popis: |
Abstract We propose BIGKnock (BIobank-scale Gene-based association test via Knockoffs), a computationally efficient gene-based testing approach for biobank-scale data, that leverages long-range chromatin interaction data, and performs conditional genome-wide testing via knockoffs. BIGKnock can prioritize causal genes over proxy associations at a locus. We apply BIGKnock to the UK Biobank data with 405,296 participants for multiple binary and quantitative traits, and show that relative to conventional gene-based tests, BIGKnock produces smaller sets of significant genes that contain the causal gene(s) with high probability. We further illustrate its ability to pinpoint potential causal genes at $$\sim 80\%$$ ∼ 80 % of the associated loci. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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