MetaboShiny: interactive analysis and metabolite annotation of mass spectrometry-based metabolomics data
MetaboShiny: interactive analysis and metabolite annotation of mass spectrometry-based metabolomics data
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DOI：
10.1007/s11306-020-01717-8
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发表时间：
2020-09-11
期刊：
影响因子：
3.6
通讯作者：
de Ridder, Jeroen
中科院分区：
文献类型：
--
作者：
Wolthuis, Joanna C.;Magnusdottir, Stefania;de Ridder, Jeroen
直接输注非靶向的基于质谱的代谢组学允许快速洞察样品的代谢活性。然而，分析往往是复杂的检测的m/z值的大阵列和困难的优先级重要的m/z和同时注释其推定的身份。为了应对这一挑战，我们开发了MetaboShiny，这是一种基于R/RShiny的新型代谢组学软件包，具有数据分析，基于数据库和公式预测的注释和可视化功能。为了证明这一点，我们复制并进一步探索肺癌患者尿液样本的代谢组学生物信息学研究。MetaboShiny可对直接输注非靶向质谱代谢组学数据进行快速、严格的分析和解释。
Direct infusion untargeted mass spectrometry-based metabolomics allows for rapid insight into a sample's metabolic activity. However, analysis is often complicated by the large array of detected m/z values and the difficulty to prioritize important m/z and simultaneously annotate their putative identities. To address this challenge, we developed MetaboShiny, a novel R/RShiny-based metabolomics package featuring data analysis, database- and formula-prediction-based annotation and visualization. To demonstrate this, we reproduce and further explore a MetaboLights metabolomics bioinformatics study on lung cancer patient urine samples. MetaboShiny enables rapid and rigorous analysis and interpretation of direct infusion untargeted mass spectrometry-based metabolomics data.