Analysis of Metabolomic Profiling Data Acquired on GC-MS

作者:Koo Imhoi; Wei Xiaoli; Zhang Xiang*
来源:CELL-WIDE METABOLIC ALTERATIONS ASSOCIATED WITH MALIGNANCY, ELSEVIER ACADEMIC PRESS INC, 525 B STREET, SUITE 1900, SAN DIEGO, CA 92101-4495 USA, 315-324, 2014.
DOI:10.1016/B978-0-12-801329-8.00016-7

摘要

Gas chromatography-mass spectrometry (GC-MS) is one of the three most popular analytical platforms for metabolomics and is largely employed for the study of oncometabolism. Large volumes of data are usually generated in a GC-MS experiment, and many analytical steps are required to extract biologically relevant information from GC-MS data. These steps include (1) spectrum deconvolution, to convert raw data into a peak list; (2) metabolite identification, to recognize metabolites associated to chromatographic peaks; (3) quantification, to compare the abundance of a specific metabolite in different samples; (4) association network analysis, to reveal correlations among the changes in the abundance of multiple metabolites; and (5) pathway analysis, to understand the biochemical interrelationship between several metabolites that vary in a coordinated or differential manner. Here, we describe in detail the analytical steps that are necessary to interpret a GC-MS dataset.

  • 出版日期2014