Why output enrichment analysis Reactome with the same gene list?

Question

[camillab.]

Hi,

I have tried to perform enrichment analysis on reactome with a list of 481 genes. I have tried using reactomePA (R package), reactome website analysis tool, and enrichR (which has reactome2016 database) and I got different results:

ReactomePA: 843 terms

Reactome analysis tool: 1277 terms

Reactome 2016 enrichR: 788 terms

Since enrichR is older compare to the others, I am not surprised to have fewer terms but I don`t understand why comparison reactomePA and reactome analysis tool I got so different results. is it possible that I wrote a wrong script for reactomePA?

My dataset looks like:

# A tibble: 6 x 2
  Entrezgene_ID log2fc
  <chr>          <dbl>
1 14             -1.02
2 80755          -1.45
3 60496          -1.17
4 6059           -1.48
5 10061          -1.35
6 10006          -1.51

and my code for reactomePA is:

#load packages
library(org.Hs.eg.db) #human genome
library(DOSE)
library(ReactomePA) # to perform enrichment analysis

#organise the datasets
genes <- d[[2]] #numeric vector #selected log2fc
names(genes) <- d[[1]] #named vector
geneLIST <- sort(genes, decreasing = TRUE) #decreasing order
head(geneLIST)

de <- names(geneLIST) 
head(de)
x <- enrichPathway(gene=de,pvalueCutoff=0.05, readable=T)
head(as.data.frame(x))
x@result # 843 terms

Did I have done something wrong?

Thank you in advance

Camilla

[Friederike]

The devil's probably in the detail of the parameters chosen by both enrichPathway and the REACTOME website. You'd have to dig into the documentation of both tools to, for example, understand (a) how the enrichment's significance (p-value) is calculated, (b) whether there are any additional corrections/calculations and (c) which thresholds are used to determine the final output.