Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
Bioinformatics. 2011 Sep 1;27(17):2455-6. doi: 10.1093/bioinformatics/btr392. Epub 2011 Jun 27.
Time-series and multifactor studies have become increasingly common in metabolomic studies. Common tasks for analyzing data from these relatively complex experiments include identification of major variations associated with each experimental factor, comparison of temporal profiles across different biological conditions, as well as detection and validation of the presence of interactions. Here we introduce MetATT, a web-based tool for time-series and two-factor metabolomic data analysis. MetATT offers a number of complementary approaches including 3D interactive principal component analysis, two-way heatmap visualization, two-way ANOVA, ANOVA-simultaneous component analysis and multivariate empirical Bayes time-series analysis. These procedures are presented through an intuitive web interface. At the end of each session, a detailed analysis report is generated to facilitate understanding of the results.
Freely available at http://metatt.metabolomics.ca
时间序列和多因素研究在代谢组学研究中变得越来越普遍。分析这些相对复杂实验数据的常见任务包括识别与每个实验因素相关的主要变化,比较不同生物条件下的时间进程,以及检测和验证相互作用的存在。本文介绍了 MetATT,这是一个用于时间序列和双因素代谢组学数据分析的网络工具。MetATT 提供了多种互补的方法,包括 3D 交互式主成分分析、双向热图可视化、双向方差分析、方差分析-同时成分分析和多元经验贝叶斯时间序列分析。这些程序通过直观的网络界面呈现。在每个会话结束时,生成详细的分析报告,以帮助理解结果。
可免费在 http://metatt.metabolomics.ca 获取。