New poster and relatively new to R, please be kind!
I've been using clusterProfiler to find enriched GO terms in my nanoString dataset. I'm not having any success finding downregulated terms however. Can this be done? The code I'm using to get the enrcihed terms is as follows:
up_gene_names is the output of filtered
GO_BP_up <- enrichGO(gene = up_gene_names, OrgDb = org.Hs.eg.db, keyType = 'SYMBOL', ont = "BP", pAdjustMethod = "BH", universe = all_gene_names, pvalueCutoff = 0.01, qvalueCutoff = 0.05)
I have a similar list
down_gene_names also from
DESeq2, however this does not return any results with the following code:
GO_BP_down <- enrichGO(gene = down_gene_names, OrgDb = org.Hs.eg.db, keyType = 'SYMBOL', ont = "BP", pAdjustMethod = "BH", universe = all_gene_names, pvalueCutoff = 0.01, qvalueCutoff = 0.05)
# # over-representation test # #...@organism Homo sapiens #...@ontology BP #...@keytype SYMBOL #...@gene chr [1:294] "SORBS1" "PIK3C3" "TBC1D4" "SKP2" "PELI1" "SCIN" "LPL" "SPOPL" "BRAF" "SIRT1" ... #...pvalues adjusted by 'BH' with cutoff <0.01 #...0 enriched terms found #...Citation T Wu, E Hu, S Xu, M Chen, P Guo, Z Dai, T Feng, L Zhou, W Tang, L Zhan, X Fu, S Liu, X Bo, and G Yu. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. The Innovation. 2021, 2(3):100141
There are significantly more genes down regulated than upregulated, so this result is surprising. I note that
enrichGO is an "over-representation test", what should I be using instead?