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 \(\sim 80\%\) of the associated loci.

Details

Title
BIGKnock: fine-mapping gene-based associations via knockoff analysis of biobank-scale data
Author
Ma, Shiyang; Wang, Chen; Khan, Atlas; Liu, Linxi; Dalgleish, James; Kiryluk, Krzysztof; He, Zihuai; Ionita-Laza, Iuliana
Pages
1-28
Section
Method
Publication year
2023
Publication date
2023
Publisher
BioMed Central
ISSN
14747596
e-ISSN
1474760X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2777783757
Copyright
© 2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.