The Contribution Plot: Decomposition and Graphical Display of the RV Coefficient, with Application to Genetic and Brain Imaging Biomarkers of Alzheimer’s Disease

IF 1.1 4区生物学 Q4 GENETICS & HEREDITY

Human Heredity Pub Date : 2019-04-08 DOI:10.1159/000501334

JinCheol Choi, Donghuan Lu, M. Beg, J. Graham, B. McNeney

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引用次数: 3

Abstract

Background/Aims: Alzheimer’s disease (AD) is a chronic neurodegenerative disease that causes memory loss and a decline in cognitive abilities. AD is the sixth leading cause of death in the USA, affecting an estimated 5 million Americans. To assess the association between multiple genetic variants and multiple measurements of structural changes in the brain, a recent study of AD used a multivariate measure of linear dependence, the RV coefficient. The authors decomposed the RV coefficient into contributions from individual variants and displayed these contributions graphically. Methods: We investigate the properties of such a “contribution plot” in terms of an underlying linear model, and discuss shrinkage estimation of the components of the plot when the correlation signal may be sparse. Results: The contribution plot is applied to simulated data and to genomic and brain imaging data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Conclusions: The contribution plot with shrinkage estimation can reveal truly associated explanatory variables.

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贡献图:RV系数的分解和图形显示，应用于阿尔茨海默病的遗传和脑成像生物标志物

背景/目的：阿尔茨海默病（AD）是一种导致记忆丧失和认知能力下降的慢性神经退行性疾病。AD是美国第六大死亡原因，估计有500万美国人受到影响。为了评估多种遗传变异与大脑结构变化的多种测量之间的相关性，最近的一项AD研究使用了线性依赖性的多变量测量，即RV系数。作者将RV系数分解为各个变量的贡献，并以图形方式显示这些贡献。方法：我们根据潜在的线性模型研究了这种“贡献图”的性质，并讨论了当相关信号可能是稀疏的时，图的分量的收缩估计。结果：贡献图应用于阿尔茨海默病神经成像倡议（ADNI）的模拟数据以及基因组和大脑成像数据。结论：收缩估计的贡献图可以揭示真正相关的解释变量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Human Heredity 生物-遗传学

CiteScore

2.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Gathering original research reports and short communications from all over the world, ''Human Heredity'' is devoted to methodological and applied research on the genetics of human populations, association and linkage analysis, genetic mechanisms of disease, and new methods for statistical genetics, for example, analysis of rare variants and results from next generation sequencing. The value of this information to many branches of medicine is shown by the number of citations the journal receives in fields ranging from immunology and hematology to epidemiology and public health planning, and the fact that at least 50% of all ''Human Heredity'' papers are still cited more than 8 years after publication (according to ISI Journal Citation Reports). Special issues on methodological topics (such as ‘Consanguinity and Genomics’ in 2014; ‘Analyzing Rare Variants in Complex Diseases’ in 2012) or reviews of advances in particular fields (‘Genetic Diversity in European Populations: Evolutionary Evidence and Medical Implications’ in 2014; ‘Genes and the Environment in Obesity’ in 2013) are published every year. Renowned experts in the field are invited to contribute to these special issues.

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