Introduction:

The tool takes a compounds annotation file as input and performs metabolite set enrichment analysis for human and mammalian species. The analysis is based on eight metabolite set libraries containing ~6300 groups of biologically meaningful metabolite sets collected primarily from human studies. This tool is a wrapper of the ‘enrichment analysis’ modules of the popular MetaboAnalyst platform.

Input files:

Compounds ID mapping results. Must be obtained from Tool: 'Compounds ID mapping'.

Parameter:

metabolite set library: Eight different metabolite set libraries have been provided, containing ~7000 groups of biologically meaningful metabolite sets collected primarily from human studies. Pathway-associated metabolite set library contains 99 metabolite sets based on normal metabolic pathways. Diseased-associated metabolite set library contains 344 metabolite sets reported in human blood. Disease-associated metabolite set library contains 384 metabolite sets reported in human urine. Disease-associated metabolite set (CSF) library contains 166 metabolite sets reported in human cerebral spinal fluid (CSF). SNP-associated metabolite set library contains 4598 metabolite sets based on their associations with detected single nucleotide polymorphisms (SNPs) loci. Predicted metabolite set library contains 912 metabolic sets that are predicted to be changed in the case of dysfunctional enzymes using genome-scale network model of human metabolism. Location-based metabolite set library contains 73 metabolite sets based on organ, tissue and subcellular localizations. Drug-pathway-associated metabolite set library contains 461 metabolite sets based on drug pathway.

Output files:

1. 'MSEA_Result.txt', enrichment analysis result.

2. 'Enrichment_Barplot.pdf', enrichment result visualization diagram.

3. 'Network.pdf, enrichment result visualization diagram.

Reference:

[1] Xia J, Wishart D S. Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst[J]. Nature Protocols, 2011, 6(6):743-760.

[2] Chong, J., et al. (2018) MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucleic acids research, 46, W486-w494. http://www.metaboanalyst.ca.