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tooluniverse-metabolomics-analysis

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Analyze metabolomics data including metabolite identification, quantification, pathway analysis, and metabolic flux. Processes LC-MS, GC-MS, NMR data from targeted and untargeted experiments. Performs normalization, statistical analysis, pathway enrichment, metabolite-enzyme integration, and biomarker discovery. Use when analyzing metabolomics datasets, identifying differential metabolites, studying metabolic pathways, integrating with transcriptomics/proteomics, discovering metabolic biomarkers, performing flux balance analysis, or characterizing metabolic phenotypes in disease, drug response, or physiological conditions.

When to use

• User has metabolomics data (LC-MS, GC-MS, NMR)
• Questions about metabolite abundance or concentrations
• Differential metabolite analysis requests
• Metabolic pathway analysis
• Multi-omics integration with metabolomics
• Metabolic biomarker discovery
• Flux balance analysis or metabolic modeling
• Metabolite-enzyme correlation

When not to use

• **Identification**: Many features remain unidentified (Level 4)
• **Coverage**: Cannot detect all metabolites (depends on method)
• **Quantification**: Relative abundance (not absolute concentration without standards)
• **Isomers**: Difficult to distinguish structural isomers
• **Ion suppression**: Matrix effects can affect quantification
• **Dynamic range**: Limited compared to targeted methods

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