TY - JOUR
T1 - Meta-analysis of untargeted metabolomic data from multiple profiling experiments
AU - Patti, Gary J.
AU - Tautenhahn, Ralf
AU - Siuzdak, Gary
N1 - Funding Information:
acknowleDGMents This work was supported by the California Institute of Regenerative Medicine (grant TR1-01219), the US National Institutes of Health (grants R24 EY017540-04, P30 MH062261-10 and P01 DA026146-02) and a US National Institutes of Health/National Institute on Aging grant (L30 AG0 038036; to G.J.P.). Financial support was also received from the US Department of Energy (grants FG02-07ER64325 and DE-AC0205CH11231).
PY - 2012/3
Y1 - 2012/3
N2 - metaXCMS is a software program for the analysis of liquid chromatography/mass spectrometry-based untargeted metabolomic data. It is designed to identify the differences between metabolic profiles across multiple sample groups (e.g., 'healthy' versus 'active disease' versus 'inactive disease'). Although performing pairwise comparisons alone can provide physiologically relevant data, these experiments often result in hundreds of differences, and comparison with additional biologically meaningful sample groups can allow for substantial data reduction. By performing second-order (meta-) analysis, metaXCMS facilitates the prioritization of interesting metabolite features from large untargeted metabolomic data sets before the rate-limiting step of structural identification. Here we provide a detailed step-by-step protocol for going from raw mass spectrometry data to metaXCMS results, visualized as Venn diagrams and exported Microsoft Excel spreadsheets. There is no upper limit to the number of sample groups or individual samples that can be compared with the software, and data from most commercial mass spectrometers are supported. The speed of the analysis depends on computational resources and data volume, but will generally be less than 1 d for most users. metaXCMS is freely available at http://metlin.scripps.edu/metaxcms/.
AB - metaXCMS is a software program for the analysis of liquid chromatography/mass spectrometry-based untargeted metabolomic data. It is designed to identify the differences between metabolic profiles across multiple sample groups (e.g., 'healthy' versus 'active disease' versus 'inactive disease'). Although performing pairwise comparisons alone can provide physiologically relevant data, these experiments often result in hundreds of differences, and comparison with additional biologically meaningful sample groups can allow for substantial data reduction. By performing second-order (meta-) analysis, metaXCMS facilitates the prioritization of interesting metabolite features from large untargeted metabolomic data sets before the rate-limiting step of structural identification. Here we provide a detailed step-by-step protocol for going from raw mass spectrometry data to metaXCMS results, visualized as Venn diagrams and exported Microsoft Excel spreadsheets. There is no upper limit to the number of sample groups or individual samples that can be compared with the software, and data from most commercial mass spectrometers are supported. The speed of the analysis depends on computational resources and data volume, but will generally be less than 1 d for most users. metaXCMS is freely available at http://metlin.scripps.edu/metaxcms/.
UR - http://www.scopus.com/inward/record.url?scp=84858764020&partnerID=8YFLogxK
U2 - 10.1038/nprot.2011.454
DO - 10.1038/nprot.2011.454
M3 - Review article
C2 - 22343432
AN - SCOPUS:84858764020
SN - 1754-2189
VL - 7
SP - 508
EP - 516
JO - Nature Protocols
JF - Nature Protocols
IS - 3
ER -