Hello,
I used MetaboAnalyst 5.0 to analyze data generated using the Biocrate MxP kit. We have 8 wildtype samples and 8 knockout samples.
I uploaded the .csv file containing ~630 metabolites quantified using the Biocrate MxP kit (for ease of reference in this post, this .csv file is called “file_1”. There were more than 100 metabolites not recognized by the MetaboAnalyst 5.0 database. As a result, these 100 metabolites were excluded by MetaboAnalyst 5.0 in the subsequent KEGG pathway analysis.
To reintroduce these 100 metabolites to MetaboAnalyst 5.0, I manually added these unrecognized metabolites to KEGG .csv file following the instruction of MetaboAnalyst 5.0 (i.e., add metabolite1; metabolite2; … to the 2nd column of this KEGG .csv file).
Later, I found that if a metabolite in file_1 was unrecognized by the MetaboAnalyst 5.0 database, even if I manually added this metabolite to the KEGG dataset, this manual editing did not change the result of pathway enrichment.
For example, the metabolite “Hydroxyglutaric acid” in my file_1 was not recognized by the MetaboAnalyst 5.0 database. I added “Hydroxyglutaric acid” to the KEGG dataset (either to an already existing pathway, or a newly created pathway in the KEGG dataset.csv file). Adding it to an already existing pathway did not change the enrichment ratio or p value of this existing pathway. We also created a new pathway containing “Hydroxyglutaric acid” and several other metabolites unmapped to MetaboAnalyst 5.0. All the metabolites defined in this new pathway exist in our file_1, so we expected the enrichment ratio of this newly created pathway to be 100%, but it was 0%.
Besides “Hydroxyglutaric acid”, I have tried multiple metabolites that were neglected by the MetaboAnalyst 5.0 database and results were the same.
Having said so much, my question is that, is there a way not to exclude the unmapped metabolites from the final KEGG pathway enrichment analysis?
Thanks!
Guoliang Cui
