ClusterProfiler GSEA with geneList
1
0
Entering edit mode
lucap • 0
@lucap-20484
Last seen 15 months ago
Italy

Hi everyone, Just a quick question. I want to perform GSEA on my geneList using clusterProfiler. Since I have a lot of genes and for some of them the logFC is small, I would like to perform GSEA only on the genes that have a logFC > 2. How do I do that in R?

I am following the recommended steps to prepare the geneList:

geneList = d[,2] names(geneList) = as.character(d[,1]) geneList = sort(geneList, decreasing = TRUE)

followed by:

gene <- names(geneList)[abs(geneList) > 2]

but then I do not understand how to "filter" the gene list that will be submitted to GSEA? Maybe I am not supposed to do it, and I should only run GSEA with the whole geneList set? The code for GSEA I am using is:

kkGSEA <- gseKEGG(geneList=geneList, organism = "hsa", nPerm = 1000, pvalueCutoff = pvalue_gsea, minGSSize = 5)

Any help would be much much appreciated. Thanks :D

clusterProfiler GSEA geneList • 4.1k views
ADD COMMENT
2
Entering edit mode
@ludwig-geistlinger-3939
Last seen 2.4 years ago
USA/Boston/HMS

GSEA works on the full gene vector, testing whether genes of a gene set (here: a KEGG pathway) accumulate at the top or bottom of the full gene vector ordered by direction and magnitude of expression change.

If you are interested only in genes of significant expression change (here: abs(log2FC) > 2), and want to know whether certain gene sets (here: KEGG pathways) contain a disproportional number of these significant genes, you would rather carry out a over-representation analysis (ORA).

In clusterProfiler: use enrichKEGG for that purpose.

ADD COMMENT
0
Entering edit mode

Thanks Ludwig for the clear explanation! I see what you mean. I’ll carry the over-representation test then

Thanks Luca

ADD REPLY

Login before adding your answer.

Traffic: 662 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6