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PiMP my metabolome: an integrated, web-based tool for LC-MS metabolomics data
Yoann Gloaguen1, Fraser Morton1, Rónán Daly1
1Institute of Infection, Immunity and Inflammation, Glasgow Polyomics.
Bioinformatics (Oxford, England)
|September 30, 2017
Summary
The Polyomics integrated Metabolomics Pipeline (PiMP) provides automated, user-friendly analysis for metabolomics data. It simplifies mass spectrometry data interpretation with innovative Summary and Metabolite Pages for biological insights.
Area of Science:
- Biochemistry
- Bioinformatics
- Computational Biology
Background:
- Metabolomics data analysis presents challenges in automation and interpretation.
- A need exists for integrated pipelines simplifying the process from data acquisition to biological insights.
Purpose of the Study:
- To introduce the Polyomics integrated Metabolomics Pipeline (PiMP).
- To provide an automated and user-friendly solution for metabolomics data analysis.
Main Methods:
- PiMP integrates mass spectrometry data acquisition with biological interpretation.
- Key innovations include a Summary Page for experimental overview and a Metabolite Page with evidence cards for annotation.
Main Results:
- PiMP offers automated analysis from data acquisition to biological interpretation.
- The Summary Page presents key findings and metadata, mimicking a scientific paper.
- The Metabolite Page provides detailed metabolite annotation with evidence cards.
Conclusions:
- PiMP addresses an unmet need in metabolomics data analysis.
- The pipeline enhances user-friendliness and automation in the field.
- PiMP facilitates biological interpretation through innovative visualization tools.
