title: MetATT: a web-based metabolomics tool for analyzing time-series and two-factor datasets.
abstract: CONCLUSIONS
  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.
  
  
  BACKGROUND
  Freely available at http://metatt.metabolomics.ca
  
  
  BACKGROUND
  jianguox@ualberta.ca.
authors.affiliation: Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada. jianguox@ualberta.ca
authors.forename: Jianguo
authors.initials: J
authors.lastname: Xia
authors.forename: Igor V
authors.initials: IV
authors.lastname: Sinelnikov
authors.forename: David S
authors.initials: DS
authors.lastname: Wishart
mesh_terms: D001499:Bayes Theorem; D003196:Computer Graphics; D020407:Internet; D055432:Metabolomics / Q000379:methods*; D012984:Software; D013997:Time Factors