International Research Training Group "Computational Methods for the Analysis of the Diversity and Dynamics of Genomes", Faculty of Technology, Bielefeld University, Bielefeld, Germany.
Biodata Mining Group, Center for Biotechnology (CeBiTec), Faculty of Technology, Bielefeld University, Bielefeld, Germany.
BMC Bioinformatics. 2022 Jul 8;23(1):267. doi: 10.1186/s12859-022-04793-w.
Modern mass spectrometry has revolutionized the detection and analysis of metabolites but likewise, let the data skyrocket with repositories for metabolomics data filling up with thousands of datasets. While there are many software tools for the analysis of individual experiments with a few to dozens of chromatograms, we see a demand for a contemporary software solution capable of processing and analyzing hundreds or even thousands of experiments in an integrative manner with standardized workflows.
Here, we introduce MetHoS as an automated web-based software platform for the processing, storage and analysis of great amounts of mass spectrometry-based metabolomics data sets originating from different metabolomics studies. MetHoS is based on Big Data frameworks to enable parallel processing, distributed storage and distributed analysis of even larger data sets across clusters of computers in a highly scalable manner. It has been designed to allow the processing and analysis of any amount of experiments and samples in an integrative manner. In order to demonstrate the capabilities of MetHoS, thousands of experiments were downloaded from the MetaboLights database and used to perform a large-scale processing, storage and statistical analysis in a proof-of-concept study.
MetHoS is suitable for large-scale processing, storage and analysis of metabolomics data aiming at untargeted metabolomic analyses. It is freely available at: https://methos.cebitec.uni-bielefeld.de/ . Users interested in analyzing their own data are encouraged to apply for an account.
现代质谱技术彻底改变了代谢物的检测和分析，但同样地，代谢组学数据存储库中的数据也呈爆炸式增长，成千上万的数据集填满了这些存储库。虽然有许多用于分析单个实验的软件工具，其中一些工具可以处理几十个色谱图，但我们需要一个现代化的软件解决方案，能够以标准化的工作流程集成方式处理和分析数百甚至数千个实验。
在这里，我们介绍了 MetHoS，这是一个自动化的基于网络的软件平台，用于处理、存储和分析来自不同代谢组学研究的大量基于质谱的代谢组学数据集。MetHoS 基于大数据框架，能够以高度可扩展的方式对大量数据集进行并行处理、分布式存储和分布式分析，甚至跨越计算机集群。它的设计目的是允许以集成的方式处理和分析任意数量的实验和样本。为了展示 MetHoS 的功能，我们从 MetaboLights 数据库中下载了数千个实验，并在概念验证研究中使用这些实验进行了大规模的处理、存储和统计分析。
MetHoS 适用于代谢组学数据的大规模处理、存储和分析，旨在进行非靶向代谢组学分析。它可以在以下网址免费获得：https://methos.cebitec.uni-bielefeld.de/。有兴趣分析自己数据的用户可以申请账号。
