MeTEor：一款用于探索纵向代谢组学数据的R Shiny应用程序。
MeTEor: an R Shiny app for exploring longitudinal metabolomics data.
作者信息
Grabert Gordon, Dehncke Daniel, More Tushar, List Markus, Kraft Anke R M, Cornberg Markus, Hiller Karsten, Kacprowski Tim
机构信息
Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics of Technische Universität Braunschweig and Hannover Medical School, Braunschweig, Lower Saxony 38106, Germany.
Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Lower Saxony 38106, Germany.
出版信息
Bioinform Adv. 2024 Nov 14;4(1):vbae178. doi: 10.1093/bioadv/vbae178. eCollection 2024.
MOTIVATION
The availability of longitudinal omics data is increasing in metabolomics research. Viewing metabolomics data over time provides detailed insight into biological processes and fosters understanding of how systems react over time. However, the analysis of longitudinal metabolomics data poses various challenges, both in terms of statistical evaluation and visualization.
RESULTS
To make explorative analysis of longitudinal data readily available to researchers without formal background in computer science and programming, we present MEtabolite Trajectory ExplORer (MeTEor). MeTEor is an R Shiny app providing a comprehensive set of statistical analysis methods. To demonstrate the capabilities of MeTEor, we replicated the analysis of metabolomics data from a previously published study on COVID-19 patients.
AVAILABILITY AND IMPLEMENTATION
MeTEor is available as an R package and as a Docker image. Source code and instructions for setting up the app can be found on GitHub (https://github.com/scibiome/meteor). The Docker image is available at Docker Hub (https://hub.docker.com/r/gordomics/meteor). MeTEor has been tested on Microsoft Windows, Unix/Linux, and macOS.
动机
在代谢组学研究中，纵向组学数据的可用性正在增加。随着时间推移观察代谢组学数据能深入了解生物过程，并有助于理解系统如何随时间变化。然而，纵向代谢组学数据的分析在统计评估和可视化方面都面临各种挑战。
结果
为了让没有计算机科学和编程背景的研究人员能够轻松地对纵向数据进行探索性分析，我们推出了代谢物轨迹探索器（MeTEor）。MeTEor是一个R Shiny应用程序，提供了一套全面的统计分析方法。为了展示MeTEor的功能，我们重复了之前一项关于COVID-19患者的代谢组学数据分析。
可用性与实现
MeTEor可作为R包和Docker镜像获取。应用程序的源代码和设置说明可在GitHub（https://github.com/scibiome/meteor）上找到。Docker镜像可在Docker Hub（https://hub.docker.com/r/gordomics/meteor）上获取。MeTEor已在Microsoft Windows、Unix/Linux和macOS上进行了测试。
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