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Title: Multi-resolution localization of causal variants across the genome
Abstract

In the statistical analysis of genome-wide association data, it is challenging to precisely localize the variants that affect complex traits, due to linkage disequilibrium, and to maximize power while limiting spurious findings. Here we report onKnockoffZoom: a flexible method that localizes causal variants at multiple resolutions by testing the conditional associations of genetic segments of decreasing width, while provably controlling the false discovery rate. Our method utilizes artificial genotypes as negative controls and is equally valid for quantitative and binary phenotypes, without requiring any assumptions about their genetic architectures. Instead, we rely on well-established genetic models of linkage disequilibrium. We demonstrate that our method can detect more associations than mixed effects models and achieve fine-mapping precision, at comparable computational cost. Lastly, we applyKnockoffZoomto data from 350k subjects in the UK Biobank and report many new findings.

Authors:
; ; ; ;
Award ID(s):
1934578 1712800
Publication Date:
NSF-PAR ID:
10153674
Journal Name:
Nature Communications
Volume:
11
Issue:
1
ISSN:
2041-1723
Publisher:
Nature Publishing Group
Sponsoring Org:
National Science Foundation
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