Department of Chemistry, University of Louisville, Louisville, Kentucky 40292, USA.
Anal Chem. 2011 Oct 15;83(20):7668-75. doi: 10.1021/ac2017025. Epub 2011 Sep 20.
Data analysis in metabolomics is currently a major challenge, particularly when large sample sets are analyzed. Herein, we present a novel computational platform entitled MetSign for high-resolution mass spectrometry-based metabolomics. By converting the instrument raw data into mzXML format as its input data, MetSign provides a suite of bioinformatics tools to perform raw data deconvolution, metabolite putative assignment, peak list alignment, normalization, statistical significance tests, unsupervised pattern recognition, and time course analysis. MetSign uses a modular design and an interactive visual data mining approach to enable efficient extraction of useful patterns from data sets. Analysis steps, designed as containers, are presented with a wizard for the user to follow analyses. Each analysis step might contain multiple analysis procedures and/or methods and serves as a pausing point where users can interact with the system to review the results, to shape the next steps, and to return to previous steps to repeat them with different methods or parameter settings. Analysis of metabolite extract of mouse liver with spiked-in acid standards shows that MetSign outperforms the existing publically available software packages. MetSign has also been successfully applied to investigate the regulation and time course trajectory of metabolites in hepatic liver.
代谢组学中的数据分析目前是一个主要的挑战，特别是在分析大型样本集时。在此，我们提出了一个名为 MetSign 的新的计算平台，用于基于高分辨率质谱的代谢组学。通过将仪器原始数据转换为 mzXML 格式作为输入数据，MetSign 提供了一套生物信息学工具，用于执行原始数据解卷积、代谢物假定分配、峰列表对齐、归一化、统计显著性检验、无监督模式识别和时程分析。MetSign 采用模块化设计和交互式可视化数据挖掘方法，能够从数据集高效提取有用的模式。分析步骤被设计为容器，并带有向导，供用户遵循分析过程。每个分析步骤可能包含多个分析过程和/或方法，并作为一个暂停点，用户可以在其中与系统交互，以查看结果、塑造下一步，以及返回上一步，以便使用不同的方法或参数设置重复操作。对加标酸标准的小鼠肝提取物的代谢物分析表明，MetSign 优于现有的公开可用软件包。MetSign 还成功地应用于研究肝组织中代谢物的调节和时程轨迹。
