An interactive cluster heat map to visualize and explore multidimensional metabolomic data

Julijana Ivanisevic, H. Paul Benton, Duane Rinehart, Adrian Epstein, Michael E. Kurczy, Michael D. Boska, Howard E. Gendelman, Gary Siuzdak

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

Heat maps are a commonly used visualization tool for metabolomic data where the relative abundance of ions detected in each sample is represented with color intensity. A limitation of applying heat maps to global metabolomic data, however, is the large number of ions that have to be displayed and the lack of information provided about important metabolomic parameters such as m/z and retention time. Here we address these challenges by introducing the interactive cluster heat map in the data-processing software XCMS Online. XCMS Online (xcmsonline.scripps.edu) is a cloud-based informatic platform designed to process, statistically evaluate, and visualize mass-spectrometry based metabolomic data. An interactive heat map is provided for all data processed by XCMS Online. The heat map is clickable, allowing users to zoom and explore specific metabolite metadata (EICs, Box-and-whisker plots, mass spectra) that are linked to the METLIN metabolite database. The utility of the XCMS interactive heat map is demonstrated on metabolomic data set generated from different anatomical regions of the mouse brain.

Original languageEnglish (US)
Pages (from-to)1029-1034
Number of pages6
JournalMetabolomics
Volume11
Issue number4
DOIs
StatePublished - Aug 22 2015

Keywords

  • Anatomical brain regions
  • Bioinformatics software
  • Brain metabolomics
  • Interactive cluster heat map
  • Metabolomics
  • XCMS Online

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Clinical Biochemistry

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  • Cite this

    Ivanisevic, J., Benton, H. P., Rinehart, D., Epstein, A., Kurczy, M. E., Boska, M. D., Gendelman, H. E., & Siuzdak, G. (2015). An interactive cluster heat map to visualize and explore multidimensional metabolomic data. Metabolomics, 11(4), 1029-1034. https://doi.org/10.1007/s11306-014-0759-2