Interactive XCMS Online: Simplifying Advanced Metabolomic Data Processing and Subsequent Statistical Analyses

被引:309
作者
Gowda, Harsha [1 ]
Ivanisevic, Julijana [1 ]
Johnson, Caroline H. [1 ]
Kurczy, Michael E. [1 ]
Benton, H. Paul [1 ]
Rinehart, Duane [1 ]
Thomas Nguyen [1 ]
Ray, Jayashree [3 ]
Kuehl, Jennifer [3 ]
Arevalo, Bernardo [1 ]
Westenskow, Peter D. [2 ]
Wang, Junhua [1 ]
Arkin, Adam P. [3 ]
Deutschbauer, Adam M. [3 ]
Patti, Gary J. [4 ,5 ,6 ]
Siuzdak, Gary [1 ]
机构
[1] Scripps Res Inst, Scripps Ctr Metabol & Mass Spectrometry, La Jolla, CA 92037 USA
[2] Scripps Res Inst, Dept Cell Biol, La Jolla, CA 92037 USA
[3] Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Phys Biosci Div, Berkeley, CA 94720 USA
[4] Washington Univ, Dept Chem, St Louis, MO 63130 USA
[5] Washington Univ, Dept Genet, St Louis, MO 63130 USA
[6] Washington Univ, Dept Med, St Louis, MO 63130 USA
基金
美国国家卫生研究院;
关键词
GENOME-WIDE ASSOCIATION; MASS-SPECTROMETRY DATA; METAANALYSIS; EXPRESSION; UNIVARIATE; MECHANISM; METLIN;
D O I
10.1021/ac500734c
中图分类号
O65 [分析化学];
学科分类号
070302 [分析化学];
摘要
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 trnivariate 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 fiinctionalities is demonstrated through the metabolomic analysis of bacterial stress response and the comparison of lymphoblastic leukemia cell lines.
引用
收藏
页码:6931 / 6939
页数:9
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