Identity-By-Descent Mapping Using Multi-Individual IBD With Genome-Wide Multiple Testing Adjustment

IF 3.8 4区 医学 Q3 GENETICS & HEREDITY
Ruoyi Cai, Sharon R. Browning
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引用次数: 0

Abstract

We present an identity-by-descent mapping approach to test the association between genome-wide loci and complex traits. Our method evaluates whether levels of genetic similarities at specific genomic locations, captured by local relatedness matrices derived from multi-individual IBD sharing, are associated with phenotypic variation in complex traits. In addition, we propose an approach to adjust for multiple testing in genome-wide IBD mapping scans based on the correlation structure between test statistics across the genome. Through simulation studies, we demonstrate that our test has a well-controlled genome-wide type I error rate and superior power to detect rare and untyped variants compared to standard single-variant tests. We applied our method to systolic blood pressure data from White British individuals in the UK Biobank.

使用多个体IBD与全基因组多重测试调整的血统识别映射
我们提出了一种身份-血统映射方法来测试全基因组位点和复杂性状之间的关联。我们的方法评估了特定基因组位置的遗传相似性水平是否与复杂性状的表型变异有关,这些水平是由多个体IBD共享产生的局部相关性矩阵捕获的。此外,我们提出了一种基于全基因组测试统计量之间的相关结构来调整IBD全基因组定位扫描中多个测试的方法。通过模拟研究,我们证明,与标准的单变异测试相比,我们的测试具有良好控制的全基因组I型错误率和更强的检测稀有和未分型变异的能力。我们将我们的方法应用于英国生物银行中英国白人个体的收缩压数据。
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来源期刊
Genetic Epidemiology
Genetic Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
4.40
自引率
9.50%
发文量
49
审稿时长
6-12 weeks
期刊介绍: Genetic Epidemiology is a peer-reviewed journal for discussion of research on the genetic causes of the distribution of human traits in families and populations. Emphasis is placed on the relative contribution of genetic and environmental factors to human disease as revealed by genetic, epidemiological, and biologic investigations. Genetic Epidemiology primarily publishes papers in statistical genetics, a research field that is primarily concerned with development of statistical, bioinformatical, and computational models for analyzing genetic data. Incorporation of underlying biology and population genetics into conceptual models is favored. The Journal seeks original articles comprising either applied research or innovative statistical, mathematical, computational, or genomic methodologies that advance studies in genetic epidemiology. Other types of reports are encouraged, such as letters to the editor, topic reviews, and perspectives from other fields of research that will likely enrich the field of genetic epidemiology.
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