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调整常见变异多基因评分可提高罕见变异关联分析的产量。

Adjusting for common variant polygenic scores improves yield in rare variant association analyses.

机构信息

Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.

出版信息

Nat Genet. 2023 Apr;55(4):544-548. doi: 10.1038/s41588-023-01342-w. Epub 2023 Mar 23.

Abstract

With the emergence of large-scale sequencing data, methods for improving power in rare variant association tests are needed. Here we show that adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests across 65 quantitative traits in the UK Biobank (up to 20% increase at α = 2.6 × 10), without marked increases in false-positive rates or genomic inflation. Benefits were seen for various models, with the largest improvements seen for efficient sparse mixed-effects models. Our results illustrate how polygenic score adjustment can efficiently improve power in rare variant association discovery.

摘要

随着大规模测序数据的出现,需要改进稀有变异关联测试的功效的方法。在这里,我们表明,调整常见变异多基因评分可提高英国生物库中 65 种定量性状的基于基因的稀有变异关联测试的功效(在α=2.6×10 时最多可提高 20%),而不会显著增加假阳性率或基因组膨胀。各种模型都有好处,高效稀疏混合效应模型的改进最大。我们的结果说明了多基因评分调整如何能够有效地提高稀有变异关联发现的功效。

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