Hi!

Apologies for the stupid question! but I think I am doing something wrong but i do not understand what. I would like to do ORA analysis on bulk-RNAseq dataset so I tried both clusterProfiler and also genekitr.` However, despite getting the same terms, but I have different p-adjusted value and q-value (practically with clusterprofiler none of the term have a p.adjusted or value <= 0.01 whereas wit the genekitr I have few). why is that? Do I do something wrong with my code?

for clusterProfiler:

# we want the log2 fold change 
original_gene_list <- d$log2FC # on the unfiltered dataset

# name the vector
names(original_gene_list) <- d$ENSEMBL

# omit any NA values 
gene_list<-na.omit(original_gene_list)

# sort the list in decreasing order (required for clusterProfiler)
gene_list = sort(gene_list, decreasing = TRUE)

# Exctract significant results (padj < 0.05)
sig_genes_df = subset(d, p_value <= 0.05)

# From significant results, we want to filter on log2fold change
genes <- sig_genes_df$log2FC

# Name the vector
names(genes) <- sig_genes_df$ENSEMBL

# omit NA values
genes <- na.omit(genes)

# filter on min log2fold change (log2FoldChange > 1.5)
genes <- names(genes)[abs(genes) > 1.5]

go_enrich <- enrichGO(gene = genes,
                      universe = names(gene_list),
                      OrgDb = org.Hs.eg.db, 
                      keyType = "ENSEMBL",
                      readable = T,
                      ont = "BP",
                      pvalueCutoff = 0.05, 
                      qvalueCutoff = 0.01)

and for genekitr i have used this code (section 1.7 :

# 1st step: get input IDs
id <- c(dpg6$Associated.Gene.Name) # DEGs

# 2nd step: get gene set 
gs2 <- geneset::getGO(org = "human",ont = "bp") # biological process

#analysis
ego2 <- genORA(id,
               geneset = gs2,
               universe = names (d$ENSEMBL), # bakground aka dataset unfiltered
               p_cutoff = 0.05,
               q_cutoff = 0.01) # bp

What I am doing wrong?

Thank you very much for your help!

Camilla