代谢组学
计算机科学
预处理器
软件
鉴定(生物学)
数据预处理
源代码
数据挖掘
原始数据
过程(计算)
构造(python库)
计算生物学
生物信息学
生物
操作系统
人工智能
植物
程序设计语言
作者
Qingrong Sun,Qingqing Xu,Majie Wang,Yongcheng Wang,Dandan Zhang,Maode Lai
标识
DOI:10.21147/j.issn.1000-9604.2023.05.11
摘要
ObjectiveAs an important part of metabolomics analysis, untargeted metabolomics has become a powerful tool in the study of tumor mechanisms and the discovery of metabolic markers with high-throughput spectrometric data which also poses great challenges to data analysis, from the extraction of raw data to the identification of differential metabolites. To date, a large number of analytical tools and processes have been developed and constructed to serve untargeted metabolomics research. The different selection of analytical tools and parameter settings lead to varied results of untargeted metabolomics data. Our goal is to establish an easily operated platform and obtain a repeatable analysis result.MethodsWe used the R language basic environment to construct the preprocessing system of the original data and the LAMP (Linux+Apache+MySQL+PHP) architecture to build a cloud mass spectrum data analysis system.ResultsAn open-source analysis software for untargeted metabolomics data (openNAU) was constructed. It includes the extraction of raw mass data and quality control for the identification of differential metabolic ion peaks. A reference metabolomics database based on public databases was also constructed.ConclusionsA complete analysis system platform for untargeted metabolomics was established. This platform provides a complete template interface for the addition and updating of the analysis process, so we can finish complex analyses of untargeted metabolomics with simple human-computer interactions. The source code can be downloaded from https://github.com/zjuRong/openNAU.
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