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Kaever A, Landesfeind M, Feussner K, et al. MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data. Metabolomics. 2014;11(3):764-777doi: 10.1007/s11306-014-0734-y.
Kaever, A., Landesfeind, M., Feussner, K., Mosblech, A., Heilmann, I., Morgenstern, B., Feussner, I., & Meinicke, P. (2015). MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data. Metabolomics : Official journal of the Metabolomic Society, 11(3), 764-777. https://doi.org/10.1007/s11306-014-0734-y
Kaever, Alexander, et al. "MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data." Metabolomics : Official journal of the Metabolomic Society vol. 11,3 (2015): 764-777. doi: https://doi.org/10.1007/s11306-014-0734-y
Kaever A, Landesfeind M, Feussner K, Mosblech A, Heilmann I, Morgenstern B, Feussner I, Meinicke P. MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data. Metabolomics. 2015;11(3):764-777. doi: 10.1007/s11306-014-0734-y. Epub 2014 Oct 10. PMID: 25972773; PMCID: PMC4419191.
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Metabolomics. 2015;11(3):764-777. doi: 10.1007/s11306-014-0734-y. Epub 2014 Oct 10.

MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data.

Metabolomics : Official journal of the Metabolomic Society

Alexander Kaever, Manuel Landesfeind, Kirstin Feussner, Alina Mosblech, Ingo Heilmann, Burkhard Morgenstern, Ivo Feussner, Peter Meinicke

Affiliations

  1. Department of Bioinformatics, Institute of Microbiology and Genetics, Georg-August-University Göttingen, Goldschmidtstr. 1, 37077 Göttingen, Germany.
  2. Department of Plant Biochemistry, Albrecht-von-Haller-Institute for Plant Sciences, Georg-August-University Göttingen, Justus-von-Liebig-Weg 11, 37077 Göttingen, Germany.

PMID: 25972773 PMCID: PMC4419191 DOI: 10.1007/s11306-014-0734-y

Abstract

A central aim in the evaluation of non-targeted metabolomics data is the detection of intensity patterns that differ between experimental conditions as well as the identification of the underlying metabolites and their association with metabolic pathways. In this context, the identification of metabolites based on non-targeted mass spectrometry data is a major bottleneck. In many applications, this identification needs to be guided by expert knowledge and interactive tools for exploratory data analysis can significantly support this process. Additionally, the integration of data from other omics platforms, such as DNA microarray-based transcriptomics, can provide valuable hints and thereby facilitate the identification of metabolites via the reconstruction of related metabolic pathways. We here introduce the MarVis-Pathway tool, which allows the user to identify metabolites by annotation of pathways from cross-omics data. The analysis is supported by an extensive framework for pathway enrichment and meta-analysis. The tool allows the mapping of data set features by ID, name, and accurate mass, and can incorporate information from adduct and isotope correction of mass spectrometry data. MarVis-Pathway was integrated in the MarVis-Suite (http://marvis.gobics.de), which features the seamless highly interactive filtering, combination, clustering, and visualization of omics data sets. The functionality of the new software tool is illustrated using combined mass spectrometry and DNA microarray data. This application confirms jasmonate biosynthesis as important metabolic pathway that is upregulated during the wound response of Arabidopsis plants.

Keywords: Mass spectrometry; Metabolic fingerprinting; Metabolic pathways; Metabolomics; Set enrichment analysis ; Transcriptomics

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