Hi everyone,

I have a question about an R-package: “ClusterProfiler”. There are two methods I’m using:

• gseKEGG (or gseGO, etc.)
• enrichKEGG (or enrichGO, etc.)

I can’t find an answer to what the exact input for these methods should be:

• For gseKEGG, I need a genelist with FC values, but does this genelist contain only DE genes? Or does this list contain all genes, DE and not DE (after filtering low expressed genes offcourse)?
• For enrichKEGG, I believe I only need the gene ID’s of DE genes, right?

I hope someone can help me out!

Tom

Hey Tom,

In general, you can regard the following as being true:

• for gseKEGG(), the input can be a named vector of fold changes, and these can be either statistically significant or non-statistically significant genes, or both. Those that are not statistically significant will almost certainly have lower fold changes anyway, and this will be taken into account [via ranking] when performing the enrichment.
• for enrichKEGG() / enrichGO(), yes, these just take a vector of gene names; therefore, the assumption would be that these are already genes of particular interest, i.e., genes that you have found as statistically significantly differentially expressed in your study.

There are a few examples in the Vignete

Kevin