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Metabox: A Toolbox for Metabolomic Data Analysis, Interpretation and Integrative Exploration

Author

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  • Kwanjeera Wanichthanarak
  • Sili Fan
  • Dmitry Grapov
  • Dinesh Kumar Barupal
  • Oliver Fiehn

Abstract

Similar to genomic and proteomic platforms, metabolomic data acquisition and analysis is becoming a routine approach for investigating biological systems. However, computational approaches for metabolomic data analysis and integration are still maturing. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. With the number of options provided in each analysis module, it also supports data analysis of other ‘omic’ families. The toolbox is an R-based web application, and it is freely available at http://kwanjeeraw.github.io/metabox/ under the GPL-3 license.

Suggested Citation

  • Kwanjeera Wanichthanarak & Sili Fan & Dmitry Grapov & Dinesh Kumar Barupal & Oliver Fiehn, 2017. "Metabox: A Toolbox for Metabolomic Data Analysis, Interpretation and Integrative Exploration," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-14, January.
    • Handle: RePEc:plo:pone00:0171046
    DOI: 10.1371/journal.pone.0171046
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    Cited by:

    1. Rodrigo Manjarin & Magdalena A Maj & Michael R La Frano & Hunter Glanz, 2020. "%polynova_2way: A SAS macro for implementation of mixed models for metabolomics data," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-10, December.

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