Multi-resolution localization of causal variants across the genome

Author:

Sesia MatteoORCID,Katsevich Eugene,Bates Stephen,Candès Emmanuel,Sabatti ChiaraORCID

Abstract

AbstractWe present KnockoffZoom, a flexible method for the genetic mapping of complex traits at multiple resolutions. KnockoffZoom localizes causal variants by testing the conditional associations of genetic segments of decreasing width while provably controlling the false discovery rate using artificial genotypes as negative controls. Our method is equally valid for quantitative and binary phenotypes, making no 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 apply KnockoffZoom to data from 350k subjects in the UK Biobank and report many new findings.

Publisher

Cold Spring Harbor Laboratory

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Error‐controlled feature selection for ultrahigh‐dimensional and highly correlated feature space using deep learning;Statistical Analysis and Data Mining: The ASA Data Science Journal;2024-03-05

2. Powerful knockoffs via minimizing reconstructability;The Annals of Statistics;2022-02-01

3. SNPknock: Knockoffs for Hidden Markov Models and Genetic Data;CRAN: Contributed Packages;2017-10-10

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