Interactive XCMS Online: simplifying advanced metabolomic data processing and subsequent statistical analyses.

Details

Serval ID
serval:BIB_74685673E9DD
Type
Article: article from journal or magazin.
Collection
Publications
Title
Interactive XCMS Online: simplifying advanced metabolomic data processing and subsequent statistical analyses.
Journal
Analytical Chemistry
Author(s)
Gowda H. (co-first), Ivanisevic J. (co-first), Johnson C.H., Kurczy M.E., Benton H.P., Rinehart D., Nguyen T., Ray J., Kuehl J., Arevalo B., Westenskow P.D., Wang J., Arkin A.P., Deutschbauer A.M., Patti G.J., Siuzdak G. (co-last)
ISSN
1520-6882 (Electronic)
ISSN-L
0003-2700
Publication state
Published
Issued date
2014
Peer-reviewed
Oui
Volume
86
Number
14
Pages
6931-6939
Language
english
Abstract
XCMS Online (xcmsonline.scripps.edu) is a cloud-based informatic platform designed to process and visualize mass-spectrometry-based, untargeted metabolomic data. Initially, the platform was developed for two-group comparisons to match the independent, "control" versus "disease" experimental design. Here, we introduce an enhanced XCMS Online interface that enables users to perform dependent (paired) two-group comparisons, meta-analysis, and multigroup comparisons, with comprehensive statistical output and interactive visualization tools. Newly incorporated statistical tests cover a wide array of univariate analyses. Multigroup comparison allows for the identification of differentially expressed metabolite features across multiple classes of data while higher order meta-analysis facilitates the identification of shared metabolic patterns across multiple two-group comparisons. Given the complexity of these data sets, we have developed an interactive platform where users can monitor the statistical output of univariate (cloud plots) and multivariate (PCA plots) data analysis in real time by adjusting the threshold and range of various parameters. On the interactive cloud plot, metabolite features can be filtered out by their significance level (p-value), fold change, mass-to-charge ratio, retention time, and intensity. The variation pattern of each feature can be visualized on both extracted-ion chromatograms and box plots. The interactive principal component analysis includes scores, loadings, and scree plots that can be adjusted depending on scaling criteria. The utility of XCMS functionalities is demonstrated through the metabolomic analysis of bacterial stress response and the comparison of lymphoblastic leukemia cell lines.
Keywords
Blood/metabolism, Data Interpretation, Statistical, Databases, Factual, Desulfovibrio/metabolism, Female, Humans, Internet, Lymphoma/metabolism, Male, Mass Spectrometry, Meta-Analysis as Topic, Metabolomics/methods, Multivariate Analysis, Principal Component Analysis, Software, User-Computer Interface
Pubmed
Open Access
Yes
Create date
06/06/2016 21:51
Last modification date
07/02/2024 17:15
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