NeuroimaGene:用于评估基因调控基因表达的神经相关性的 R 软件包。

IF 2.9 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Xavier Bledsoe, Eric R Gamazon
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引用次数: 0

摘要

背景:我们介绍的 NeuroimaGene 资源是一个 R 软件包,旨在帮助研究人员识别与精神和神经健康相关的基因和神经特征。虽然最近的研究已经确定了数百个基因是神经和精神疾病病理生理学的潜在组成部分,但解释这种变异的生理后果仍具有挑战性。将神经影像数据与分子研究结果相结合是应对这一挑战的一个步骤。除了与分子变异和临床表型有关联外,神经影像学特征还能为认知过程提供内在信息。NeuroimaGene 为了解疾病相关基因与大脑中间结构的关系提供了一种工具:我们创建了 NeuroimaGene,它是一个用户友好、开放存取的 R 软件包,现在可供公众使用。它的主要功能是识别受用户提供的基因或基因组的基因调控表达影响的神经影像衍生大脑特征。该资源可用于:(1) 鉴定与大脑结构和功能相关的单个基因或基因组;(2) 识别目标基因的表达与神经相关的大脑或身体区域;(3) 估算受用户定义的基因组(如队列水平基因关联研究产生的基因组)影响最大的大脑特征;(4) 生成发表水平、可修改的重要发现可视化图谱。我们从已有的分析中确定了中风相关基因的神经相关性,从而证明了该资源的实用性:结论:在从基因到基于大脑的诊断表型的过程中,将神经学数据作为中间表型进行整合,可提高分子研究的可解释性,并丰富我们对疾病病理生理学的理解。NeuroimaGene R 软件包旨在协助这一过程,并可公开使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NeuroimaGene: an R package for assessing the neurological correlates of genetically regulated gene expression.

Background: We present the NeuroimaGene resource as an R package designed to assist researchers in identifying genes and neurologic features relevant to psychiatric and neurological health. While recent studies have identified hundreds of genes as potential components of pathophysiology in neurologic and psychiatric disease, interpreting the physiological consequences of this variation is challenging. The integration of neuroimaging data with molecular findings is a step toward addressing this challenge. In addition to sharing associations with both molecular variation and clinical phenotypes, neuroimaging features are intrinsically informative of cognitive processes. NeuroimaGene provides a tool to understand how disease-associated genes relate to the intermediate structure of the brain.

Results: We created NeuroimaGene, a user-friendly, open access R package now available for public use. Its primary function is to identify neuroimaging derived brain features that are impacted by genetically regulated expression of user-provided genes or gene sets. This resource can be used to (1) characterize individual genes or gene sets as relevant to the structure and function of the brain, (2) identify the region(s) of the brain or body in which expression of target gene(s) is neurologically relevant, (3) impute the brain features most impacted by user-defined gene sets such as those produced by cohort level gene association studies, and (4) generate publication level, modifiable visual plots of significant findings. We demonstrate the utility of the resource by identifying neurologic correlates of stroke-associated genes derived from pre-existing analyses.

Conclusions: Integrating neurologic data as an intermediate phenotype in the pathway from genes to brain-based diagnostic phenotypes increases the interpretability of molecular studies and enriches our understanding of disease pathophysiology. The NeuroimaGene R package is designed to assist in this process and is publicly available for use.

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来源期刊
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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