Most of proteomic researchers abstract the biological significance of their proteomic data by examine the up/down-regulated proteins first then perform functional enrichment analysis on these proteins to see which functions are "enriched" in those differential proteins. Is there a software tool for proteomic researchers not only look at the differential proteins, but instead view the abundance of proteins of a specific function as a whole, then to test if the abundance changes were signicantly different compared with random dataset.
I looked up the gene set enrichment analysis, but it was designed more for array data than proteomic data. We had a very pool connection with the EnrichNet, however.
You could use pre-ranked GSEA with the respective gene names of your proteins (e.g., TXNRD1 instead of TrxR1) and a t statistic or another ranking score and it should work just fine. I believe the row (gene) names have to be unique, so you could not submit multiple peptides of the same protein as different data points to be combined by the algorithm or processed separately. As for using the standard GSEA workflow, that would be impossible.
If you end up finding a workflow you like, please share it.
Hi all
Can you explain a little better in GSEA to get gene set ranked? I have statistical result of MS proteomic data but I dont know exactly how to convert to gene list for loading to GSEA
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