代谢组学
计算机科学
协议(科学)
元数据
数据挖掘
探索性数据分析
数据科学
生物信息学
生物
万维网
医学
替代医学
病理
作者
Zhiqiang Pang,Guohui Zhou,Jessica Ewald,Le Chang,Orçun Haçarız,Niladri Basu,Jianguo Xia
出处
期刊:Nature Protocols
[Springer Nature]
日期:2022-06-17
卷期号:17 (8): 1735-1761
被引量:661
标识
DOI:10.1038/s41596-022-00710-w
摘要
Liquid chromatography coupled with high-resolution mass spectrometry (LC–HRMS) has become a workhorse in global metabolomics studies with growing applications across biomedical and environmental sciences. However, outstanding bioinformatics challenges in terms of data processing, statistical analysis and functional interpretation remain critical barriers to the wider adoption of this technology. To help the user community overcome these barriers, we have made major updates to the well-established MetaboAnalyst platform ( www.metaboanalyst.ca ). This protocol extends the previous 2011 Nature Protocol by providing stepwise instructions on how to use MetaboAnalyst 5.0 to: optimize parameters for LC–HRMS spectra processing; obtain functional insights from peak list data; integrate metabolomics data with transcriptomics data or combine multiple metabolomics datasets; conduct exploratory statistical analysis with complex metadata. Parameter optimization may take ~2 h to complete depending on the server load, and the remaining three stages may be executed in ~60 min. LC–HRMS is used for metabolomics studies in the biomedical and environmental sciences. MetaboAnalyst (metaboanalyst.ca) can be used to address challenges in data processing, statistical analysis, functional interpretation and multi-omics integration.
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