Differential expression in metabolomics data

Question

[Srw]

I have a data set of normalized metabolomic values from the company Metabolon. I wanted to perform a differential expression analysis, in R, between 5 cases and 5 controls for ~700 metabolites; however, I cannot find anything that seems to be straight forward. I have looked at CRAN and Bioconductor and there a a lot of packages that do differential expression analysis but most of them need raw peak data, which I don't currently have.

Since I have normalized data do I even need a metabolomics specific tool or can I simply compare the means and bonferroni correct the p.values?

I am using R version 3.2.1

Much thanks for any and all help.

[Egon Willighagen]

What kind of analysis do you want to do? Maybe http://projects.bigcat.unimaas.nl/rpathvisio/ is of interest?

Answer 1

[raghavsehgal1995]

Polly (http://elucidata.io/polly) has a tool called MetScape which can overlay day on cannonical KEGG pathways and colour them as well as show their differential expression and intensities. Helps me avoid the hassle of using any coding language all together. It can even directly go from the raw files to visualisations. This might be useful for you. Attaching a screenshot of the MetScape dashboard.