Figure 1.

Graphical depiction of workflow for the identification of metabolites. (a) Mass spectral data collection and processing using XCMS. LC/MS data were first analyzed with XCMS software to produce a list of metabolite features, where each feature is defined by both a specific retention time and m/z value. The XCMS software then applies a non-linear retention time correction to align the same metabolite features found in different biological samples. The final XCMS output lists the t-test results based on the intensity variations of common metabolite features found among the defined sample classes. (b) Metabolite selection, characterization and identification. Metabolite features meeting statistical criteria for significance, based on XCMS processing, were further characterized by accurate mass measurement, identified using mass spectral databases such as the Metlin database and the LIPID MAPS database, and further confirmed by tandem (MS/MS) mass spectral data.

Mutch et al. Genome Biology 2007 8:R38   doi:10.1186/gb-2007-8-3-r38
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