Unit

UNIT 14.11 LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

  1. Michelle F. Clasquin1,2,
  2. Eugene Melamud1,3,
  3. Joshua D. Rabinowitz1

Published Online: 1 MAR 2012

DOI: 10.1002/0471250953.bi1411s37

Current Protocols in Bioinformatics

Current Protocols in Bioinformatics

How to Cite

Clasquin, M. F., Melamud, E. and Rabinowitz, J. D. 2012. LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine. Current Protocols in Bioinformatics. 37:14.11:14.11.1–14.11.23.

Author Information

  1. 1

    Department of Chemistry and Integrative Genomics, Carl Icahn Laboratory, Princeton, New Jersey

  2. 2

    Molecular Biomarkers, Merck Research Laboratories, West Point, Pennsylvania

  3. 3

    Oncology, Pfizer, Pearl River, New York

Publication History

  1. Published Online: 1 MAR 2012
  2. Published Print: MAR 2012

Abstract

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis. Curr. Protoc. Bioinform. 37:14.11.1-14.11.23. © 2012 by John Wiley & Sons, Inc.

Keywords:

  • metabolomics;
  • liquid chromatography-mass spectrometry;
  • pathway visualization and mapping;
  • stable isotope labeling;
  • metabolic flux analysis;
  • kinetic flux profiling