title: MetICA: independent component analysis for high-resolution mass-spectrometry based non-targeted metabolomics.
abstract: BACKGROUND
  Interpreting non-targeted metabolomics data remains a challenging task. Signals from non-targeted metabolomics studies stem from a combination of biological causes, complex interactions between them and experimental bias/noise. The resulting data matrix usually contain huge number of variables and only few samples, and classical techniques using nonlinear mapping could result in computational complexity and overfitting. Independent Component Analysis (ICA) as a linear method could potentially bring more meaningful results than Principal Component Analysis (PCA). However, a major problem with most ICA algorithms is the output variations between different runs and the result of a single ICA run should be interpreted with reserve.
  
  
  RESULTS
  ICA was applied to simulated and experimental mass spectrometry (MS)-based non-targeted metabolomics data, under the hypothesis that underlying sources are mutually independent. Inspired from the Icasso algorithm, a new ICA method, MetICA was developed to handle the instability of ICA on complex datasets. Like the original Icasso algorithm, MetICA evaluated the algorithmic and statistical reliability of ICA runs. In addition, MetICA suggests two ways to select the optimal number of model components and gives an order of interpretation for the components obtained.
  
  
  CONCLUSIONS
  Correlating the components obtained with prior biological knowledge allows understanding how non-targeted metabolomics data reflect biological nature and technical phenomena. We could also extract mass signals related to this information. This novel approach provides meaningful components due to their independent nature. Furthermore, it provides an innovative concept on which to base model selection: that of optimizing the number of reliable components instead of trying to fit the data. The current version of MetICA is available at https://github.com/daniellyz/MetICA.
authors.affiliation: Research Unit Analytical BioGeoChemistry, Department of Environmental Sciences, Helmholtz Zentrum München, Ingolstädter Landstr.1, 85758, Neuherberg, Germany. youzhong.liu@u-bourgogne.fr.|UMR PAM Université de Bourgogne/Agrosup Dijon, Institut Universitaire de la Vigne et du Vin, Jules Guyot, Rue Claude Ladrey, BP 27877, Dijon, Cedex, France. youzhong.liu@u-bourgogne.fr.
authors.forename: Youzhong
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Research Unit Analytical BioGeoChemistry, Department of Environmental Sciences, Helmholtz Zentrum München, Ingolstädter Landstr.1, 85758, Neuherberg, Germany. kirill.smirnov@helmholtz-muenchen.de.
authors.forename: Kirill
authors.initials: K
authors.lastname: Smirnov
authors.affiliation: Research Unit Analytical BioGeoChemistry, Department of Environmental Sciences, Helmholtz Zentrum München, Ingolstädter Landstr.1, 85758, Neuherberg, Germany. marianna.lucio@helmholtz-muenchen.de.
authors.forename: Marianna
authors.initials: M
authors.lastname: Lucio
authors.affiliation: UMR PAM Université de Bourgogne/Agrosup Dijon, Institut Universitaire de la Vigne et du Vin, Jules Guyot, Rue Claude Ladrey, BP 27877, Dijon, Cedex, France. regis.gougeon@u-bourgogne.fr.
authors.forename: Régis D
authors.initials: RD
authors.lastname: Gougeon
authors.affiliation: UMR PAM Université de Bourgogne/Agrosup Dijon, Institut Universitaire de la Vigne et du Vin, Jules Guyot, Rue Claude Ladrey, BP 27877, Dijon, Cedex, France. rvalex@u-bourgogne.fr.
authors.forename: Hervé
authors.initials: H
authors.lastname: Alexandre
authors.affiliation: Research Unit Analytical BioGeoChemistry, Department of Environmental Sciences, Helmholtz Zentrum München, Ingolstädter Landstr.1, 85758, Neuherberg, Germany. schmitt-kopplin@helmholtz-muenchen.de.|Technische Universität München, Chair of Analytical Food Chemistry, Alte Akademie 1085354, Freising-Weihenstephan, Germany. schmitt-kopplin@helmholtz-muenchen.de.
authors.forename: Philippe
authors.initials: P
authors.lastname: Schmitt-Kopplin
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D055432:Metabolomics / Q000379:methods*; D025341:Principal Component Analysis; D015203:Reproducibility of Results