Interactive XCMS Online: Simplifying Advanced Metabolomic Data Processing and Subsequent Statistical Analyses
By H. Gowda, J. Ivanisevic, C. Johnson, M. Kurczy, H. Benton, Duane Rinehart, T. Nguyen, J. Ray, J. Kuehl, B. Arévalo and 6 more. Analytical Chemistry, 2014
355 citations recorded by the source corpus.
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.
Subfields: Molecular Biology, Spectroscopy
View Paper: https://www.semanticscholar.org/paper/a23d33d3b9eb9b1a19633e84b95a694f37f3a7c0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- David S. Wishart
- Jianguo Xia
- Igor Sinelnikov
- Beomsoo Han
- Yuzong Chen
- Alexandra C. Schrimpe-Rutledge
- J. McLean
- S. Sherrod
In Spectroscopy
- David S. Wishart
- Jianguo Xia
- Igor Sinelnikov
- Beomsoo Han
- Jasmine Chong
- Robert E. W. Hancock
- Erin E. Gill
Citations in the corpus
- Untargeted metabolomics strategies – Challenges and Emerging Directions (2016, methodology): “Levels 5 and 4 (Unique m/z feature or Molecular formula) Ranking significant differences t-test Most statistical software packages Principle Component Analysis (PCA) Partial Least Squares (PLS) Modeling Data visualization and prioritization Cloud Plot/Volcano Plot XCMS Online [38] Self-organizing Ma”
- NOREVA: normalization and evaluation of MS-based metabolomics data (2017, methodology): “Moreover, input file in correct format could be readily generated based on results of several popular tools such as XCMS online (41).”
- MetaboAnalyst 3.0—making metabolomics more meaningful (2015, methodology): “Users are encouraged to use other dedicated and freely available tools such as XCMSOnline (30) and MZmine (31) for such tasks.”