OpenNAU: An open-source platform for normalizing, analyzing, and visualizing cancer untargeted metabolomics data.

IF 7 2区 医学 Q1 ONCOLOGY
Qingrong Sun, Qingqing Xu, Majie Wang, Yongcheng Wang, Dandan Zhang, Maode Lai
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引用次数: 0

Abstract

Objective: As 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.

Methods: We 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.

Results: An 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.

Conclusions: A 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.

OpenNAU:一个用于规范化、分析和可视化癌症非靶向代谢组学数据的开源平台。
目的:作为代谢组学分析的重要组成部分,非靶向代谢组学已经成为研究肿瘤机制和利用高通量光谱数据发现代谢标志物的有力工具,这也给数据分析带来了巨大的挑战,从原始数据的提取到差异代谢物的鉴定。迄今为止,已经开发和构建了大量的分析工具和过程来服务于非靶向代谢组学研究。分析工具的不同选择和参数设置导致非靶向代谢组学数据的结果不同。我们的目标是建立一个易于操作的平台,并获得可重复的分析结果。方法:采用R语言基础环境构建原始数据预处理系统,采用LAMP (Linux+Apache+MySQL+PHP)架构构建云质谱数据分析系统。结果:构建了非靶向代谢组学数据的开源分析软件openNAU。它包括原始质量数据的提取和鉴别差异代谢离子峰的质量控制。建立了基于公共数据库的参考代谢组学数据库。结论:建立了完整的非靶向代谢组学分析系统平台。该平台为分析过程的添加和更新提供了完整的模板界面,因此我们可以通过简单的人机交互完成非靶向代谢组学的复杂分析。源代码可以从https://github.com/zjuRong/openNAU下载。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
9.80%
发文量
1726
审稿时长
4.5 months
期刊介绍: Chinese Journal of Cancer Research (CJCR; Print ISSN: 1000-9604; Online ISSN:1993-0631) is published by AME Publishing Company in association with Chinese Anti-Cancer Association.It was launched in March 1995 as a quarterly publication and is now published bi-monthly since February 2013. CJCR is published bi-monthly in English, and is an international journal devoted to the life sciences and medical sciences. It publishes peer-reviewed original articles of basic investigations and clinical observations, reviews and brief communications providing a forum for the recent experimental and clinical advances in cancer research. This journal is indexed in Science Citation Index Expanded (SCIE), PubMed/PubMed Central (PMC), Scopus, SciSearch, Chemistry Abstracts (CA), the Excerpta Medica/EMBASE, Chinainfo, CNKI, CSCI, etc.
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