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

Gowda H, Ivanisevic J, Johnson CH, Kurczy ME, Benton HP, Rinehart D, Nguyen T, Ray J, Kuehl J, Arevalo B, Westenskow PD, Wang J, Arkin AP, Deutschbauer AM, Patti GJ, Siuzdak G - Anal. Chem. (2014)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Scripps Center for Metabolomics and Mass Spectrometry and ‡Department of Cell Biology, The Scripps Research Institute , 10550 North Torrey Pines Road, La Jolla, California 92037, United States.

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.

Show MeSH

Related in: MedlinePlus

Meta-analysis of the salt-stress response across fivedifferentmutant strains of Desulfovibrio alaskensis G20. Theresults of five two-group comparisons (left). Shared patterns of stressresponse are characterized by significant up-regulation (p < 0.01) of three metabolites displayed in the center of the Venndiagram (middle). The putative identity of those metabolites, verifiedby MS/MS matching to standards in METLIN, is shown on the right. Mutantannotations: 143C7, transcriptional regulator (Cro/Cl family); 206E3,potassium uptake protein TrkA; 34A9, lysine 2,3-aminomutase; 126cll,beta-lysine N-acetyltransferase; 116G4, V-type ATPase (subunit J,trk1).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4215863&req=5

fig5: Meta-analysis of the salt-stress response across fivedifferentmutant strains of Desulfovibrio alaskensis G20. Theresults of five two-group comparisons (left). Shared patterns of stressresponse are characterized by significant up-regulation (p < 0.01) of three metabolites displayed in the center of the Venndiagram (middle). The putative identity of those metabolites, verifiedby MS/MS matching to standards in METLIN, is shown on the right. Mutantannotations: 143C7, transcriptional regulator (Cro/Cl family); 206E3,potassium uptake protein TrkA; 34A9, lysine 2,3-aminomutase; 126cll,beta-lysine N-acetyltransferase; 116G4, V-type ATPase (subunit J,trk1).

Mentions: An interface for meta-analysishas been implemented within theXCMS Online platform to enable the identification of shared homologouspatterns of metabolic variation across the results of multiple differentexperiments (Table 2). The main interface isorganized as a step-navigation wizard that allows users to selectthe preprocessed experiments for comparison and define threshold parametersfor feature filtering and chromatogram realignment. Metabolite featurescan be filtered based on fold change, p-value, andion intensity. Subsequently, the metabolic profiles from multipleexperiments are realigned and the results of meta-analysis can bevisualized by using two different modalities, the traditional Venndiagram (Figure 5) and the Edwards’sVenn diagram constructed as segments of a sphere. Venn diagrams displaythe number of shared metabolic features that are hyperlinked to atabular output providing a list of corresponding m/z and retention-time values along with potentialmatches to the METLIN database.


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

Gowda H, Ivanisevic J, Johnson CH, Kurczy ME, Benton HP, Rinehart D, Nguyen T, Ray J, Kuehl J, Arevalo B, Westenskow PD, Wang J, Arkin AP, Deutschbauer AM, Patti GJ, Siuzdak G - Anal. Chem. (2014)

Meta-analysis of the salt-stress response across fivedifferentmutant strains of Desulfovibrio alaskensis G20. Theresults of five two-group comparisons (left). Shared patterns of stressresponse are characterized by significant up-regulation (p < 0.01) of three metabolites displayed in the center of the Venndiagram (middle). The putative identity of those metabolites, verifiedby MS/MS matching to standards in METLIN, is shown on the right. Mutantannotations: 143C7, transcriptional regulator (Cro/Cl family); 206E3,potassium uptake protein TrkA; 34A9, lysine 2,3-aminomutase; 126cll,beta-lysine N-acetyltransferase; 116G4, V-type ATPase (subunit J,trk1).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4215863&req=5

fig5: Meta-analysis of the salt-stress response across fivedifferentmutant strains of Desulfovibrio alaskensis G20. Theresults of five two-group comparisons (left). Shared patterns of stressresponse are characterized by significant up-regulation (p < 0.01) of three metabolites displayed in the center of the Venndiagram (middle). The putative identity of those metabolites, verifiedby MS/MS matching to standards in METLIN, is shown on the right. Mutantannotations: 143C7, transcriptional regulator (Cro/Cl family); 206E3,potassium uptake protein TrkA; 34A9, lysine 2,3-aminomutase; 126cll,beta-lysine N-acetyltransferase; 116G4, V-type ATPase (subunit J,trk1).
Mentions: An interface for meta-analysishas been implemented within theXCMS Online platform to enable the identification of shared homologouspatterns of metabolic variation across the results of multiple differentexperiments (Table 2). The main interface isorganized as a step-navigation wizard that allows users to selectthe preprocessed experiments for comparison and define threshold parametersfor feature filtering and chromatogram realignment. Metabolite featurescan be filtered based on fold change, p-value, andion intensity. Subsequently, the metabolic profiles from multipleexperiments are realigned and the results of meta-analysis can bevisualized by using two different modalities, the traditional Venndiagram (Figure 5) and the Edwards’sVenn diagram constructed as segments of a sphere. Venn diagrams displaythe number of shared metabolic features that are hyperlinked to atabular output providing a list of corresponding m/z and retention-time values along with potentialmatches to the METLIN database.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Scripps Center for Metabolomics and Mass Spectrometry and ‡Department of Cell Biology, The Scripps Research Institute , 10550 North Torrey Pines Road, La Jolla, California 92037, United States.

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.

Show MeSH
Related in: MedlinePlus