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ADAS-viewer:一款基于网络的应用程序,用于阿尔茨海默病多组学数据的综合分析。

ADAS-viewer: web-based application for integrative analysis of multi-omics data in Alzheimer's disease.

机构信息

Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.

Department of Biomedical Informatics, University of Utah Asia campus, Incheon, South Korea.

出版信息

NPJ Syst Biol Appl. 2021 Mar 19;7(1):18. doi: 10.1038/s41540-021-00177-7.

Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder and is represented by complicated biological mechanisms and complexity of brain tissue. Our understanding of the complicated molecular architecture that contributes to AD progression benefits from performing comprehensive and systemic investigations with multi-layered molecular and biological data from different brain regions. Since recently different independent studies generated various omics data in different brain regions of AD patients, multi-omics data integration can be a useful resource for better comprehensive understanding of AD. Here we present a web platform, ADAS-viewer, that provides researchers with the ability to comprehensively investigate and visualize multi-omics data from multiple brain regions of AD patients. ADAS-viewer offers means to identify functional changes in transcript and exon expression (i.e., alternative splicing) along with associated genetic or epigenetic regulatory effects. Specifically, it integrates genomic, transcriptomic, methylation, and miRNA data collected from seven different brain regions (cerebellum, temporal cortex, dorsolateral prefrontal cortex, frontal pole, inferior frontal gyrus, parahippocampal gyrus, and superior temporal gyrus) across three independent cohort datasets. ADAS-viewer is particularly useful as a web-based application for analyzing and visualizing multi-omics data across multiple brain regions at both transcript and exon level, allowing the identification of candidate biomarkers of Alzheimer's disease.

摘要

阿尔茨海默病(AD)是一种神经退行性疾病,其表现为复杂的生物学机制和脑组织的复杂性。我们对导致 AD 进展的复杂分子结构的理解得益于对来自不同脑区的多层次分子和生物学数据进行全面系统的研究。由于最近不同的独立研究在 AD 患者的不同脑区产生了各种组学数据,因此多组学数据的整合可以成为更好地全面理解 AD 的有用资源。在这里,我们提出了一个名为 ADAS-viewer 的网络平台,为研究人员提供了综合研究和可视化 AD 患者多个脑区多组学数据的能力。ADAS-viewer 提供了识别转录和外显子表达(即选择性剪接)功能变化以及相关遗传或表观遗传调控效应的方法。具体来说,它整合了从三个独立队列数据集中的七个不同脑区(小脑、颞叶皮层、背外侧前额叶皮层、额极、下额回、海马旁回和颞上回)收集的基因组、转录组、甲基化和 miRNA 数据。ADAS-viewer 特别有用,因为它是一种基于网络的应用程序,可以在转录和外显子水平上分析和可视化多个脑区的多组学数据,从而识别阿尔茨海默病的候选生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cbcf/7979890/55f17cbefaa3/41540_2021_177_Fig1_HTML.jpg

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