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
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