Snakemake pipeline for Gene Set Enrichment: pathway and GO enrichment analysis

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Snakemake Workflow for Gene Set Enrichment: Pathway and GO Analysis

Author: Sherine Awad

Change the config.yaml file appropriately according to your data. Update parameters of Genrich in the config file. Also, change workdir where the reference genome, etc.

Then run: snakemake -jnumber_of_cores, for example for 5 cores use: 

snakemake -j5

and for a dry run use: 

snakemake -j1 -n

and to print the commands in a dry run use: 

snakemake -j1 -n -p

For the sake reproducibility, use conda to pull same versions of tools. Snakemake and conda have to be installed in your system: 

snakemake --cores --use-conda

TO DO

  1. Add more Genome for enrichment

  2. Add more parameters for a genric pipeline

Code Snippets

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library("edgeR")
library(biomaRt)
library(dplyr)
library("AnnotationDbi")
library("org.Hs.eg.db")
library(data.table)
library("gplots")
library(magrittr)
library(pathview)
library("org.Mm.eg.db")
library(gage)
library(gageData)
library(data.table)


args <- commandArgs(trailingOnly = TRUE)
dge = args[1]
ORGANISM  =args[2] 
compare_type = args[3]
outname = args[4]

res <- read.csv(file = dge, header = TRUE)
summary(res) 
foldchanges = res$logFC
names(foldchanges) = res$entrez
outname = paste(outname, compare_type, sep ="-")
outGO = paste(outname, "GO.csv", sep ="-")

if (ORGANISM == "HUMAN")
{
data(kegg.sets.hs)
data(go.sets.hs)
data(carta.hs)
data(sigmet.idx.hs)
data(go.subs.hs)
kegg.sets.hs = kegg.sets.hs[sigmet.idx.hs]
head(kegg.sets.hs,3)
#GO
data(go.sets.hs)
data(go.subs.hs)
gobpsets = go.sets.hs[go.subs.hs$BP]
gobpres = gage(foldchanges, gsets=kegg.sets.hs, same.dir =TRUE, compare =compare_type,cutoff=0.05)
lapply(gobpres, head)
write.csv(gobpres, outGO)

} else if (ORGANISM == "MOUSE"){
data(kegg.sets.mm)
data(go.sets.mm)
data(carta.mm)
data(sigmet.idx.mm)
data(go.subs.mm)


kegg.sets.mm = kegg.sets.mm[sigmet.idx.mm]
head(kegg.sets.mm,3)
data(go.sets.mm)
data(go.subs.mm)
gobpsets = go.sets.mm[go.subs.mm$BP]
gobpres = gage(foldchanges, gsets=kegg.sets.mm, same.dir =TRUE, compare =compare_type,cutoff=0.05)
lapply(gobpres, head)
write.csv(gobpres, outGO)
}
R dplyr data.table org.Hs.eg.db org.Mm.eg.db magrittr biomaRt gplots AnnotationDbi gage From line 1 of scripts/GO.R 
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library("edgeR")
library(biomaRt)
library(dplyr)
library("AnnotationDbi")
library("org.Hs.eg.db")
library(data.table)
library("gplots")
library(magrittr)
library(pathview)
library("org.Mm.eg.db")
library(gage)
library(gageData)
library(data.table)


args <- commandArgs(trailingOnly = TRUE)
dge = args[1]
ORGANISM  =args[2] 
compare_type = args[3]
outname = args[4]
outname 

res <- read.csv(file = dge, header = TRUE)
outname = paste(outname, compare_type, sep ="-")
out = paste(outname, "KEGG.csv", sep="-")
outUP = paste(outname, "KEGG_UP.csv", sep ="-")
outDOWN = paste(outname, "KEGG_DOWN.csv", sep ="-")

foldchanges = res$logFC
names(foldchanges) <- res$entrez
summary(foldchanges)
#---------------------------
#KEGG Analysis 
#---------------------------
if (ORGANISM == "HUMAN")
{
data(kegg.sets.hs)
data(go.sets.hs)
data(carta.hs)
data(sigmet.idx.hs)
data(go.subs.hs)
kegg.sets.hs = kegg.sets.hs[sigmet.idx.hs]
head(kegg.sets.hs,3)
#---------------------------------------------------Use Kegg and gage to get upregulated and downregulated pathways
data(kegg.gs)
keggres = gage(foldchanges, gsets =kegg.sets.hs, same.dir = TRUE, compare=compare_type,make.plot = TRUE)
lapply(keggres, head)
write.csv(keggres,out)
keggrespathwaysup = data.frame(id=rownames(keggres$greater), keggres$greater) %>%
  tbl_df() %>%
  filter(row_number()<=30) %>%
  .$id %>%
  as.character()
keggrespathwaysdn = data.frame(id=rownames(keggres$less), keggres$less) %>%
  tbl_df() %>%
  filter(row_number()<=30) %>%
  .$id %>%
  as.character()
write.csv(keggrespathwaysup, outUP)
write.csv(keggrespathwaysdn, outDOWN)
#-------------------------------------------------------------------------------------------------------------------------------
keggresidsup = substr(keggrespathwaysup, start=1, stop=8)
keggresidsup
keggresidsdn = substr(keggrespathwaysdn, start=1, stop=8)
#gobpres = gage(foldchanges, gsets=kegg.sets.hs, same.dir =FALSE, compare ="paired",cutoff=0.05)
#lapply(gobpres, head)
#---------------------------------------------------------Define plotting function for applying later
plot_pathway = function(pid) pathview(gene.data=foldchanges,gene.idtype="ENTREZID", pathway.id=pid, species="human", new.signature=FALSE)
#---------------------------------------------------------plot multiple pathways ups and downs 
tmpup = sapply(keggresidsup, function(pid) pathview(gene.data=foldchanges,gene.idtype="ENTREZID", pathway.id=pid, species="human"))
tmpdn = sapply(keggresidsdn, function(pid) pathview(gene.data=foldchanges,gene.idtype="ENTREZID", pathway.id=pid, species="human"))
} else if (ORGANISM == "MOUSE"){
data(kegg.sets.mm)
data(go.sets.mm)
data(carta.mm)
data(sigmet.idx.mm)
data(go.subs.mm)
kegg.sets.mm = kegg.sets.mm[sigmet.idx.mm]
head(kegg.sets.mm,3)
#---------------------------------------------------Use Kegg and gage to get upregulated and downregulated pathways
data(kegg.gs)
keggres = gage(foldchanges, gsets =kegg.sets.mm, same.dir = TRUE, compare=compare_type,make.plot = TRUE)
lapply(keggres, head)
write.csv(keggres,out)
keggrespathwaysup = data.frame(id=rownames(keggres$greater), keggres$greater) %>%
  tbl_df() %>%
  filter(row_number()<=30) %>%
  .$id %>%
  as.character()
keggrespathwaysdn = data.frame(id=rownames(keggres$less), keggres$less) %>%
  tbl_df() %>%
  filter(row_number()<=30) %>%
  .$id %>%
  as.character()
write.csv(keggrespathwaysup, outUP)
write.csv(keggrespathwaysdn, outDOWN)
#-------------------------------------------------------------------------------------------------------------------------------
keggresidsup = substr(keggrespathwaysup, start=1, stop=8)
keggresidsup
keggresidsdn = substr(keggrespathwaysdn, start=1, stop=8)
#gobpres = gage(foldchanges, gsets=kegg.sets.mm, same.dir =FALSE, compare ="paired",cutoff=0.05)
#lapply(gobpres, head)
#---------------------------------------------------------Define plotting function for applying later
plot_pathway = function(pid) pathview(gene.data=foldchanges,gene.idtype="ENTREZID", pathway.id=pid, species="mouse", new.signature=FALSE)
#---------------------------------------------------------plot multiple pathways ups and downs 
tmpup = sapply(keggresidsup, function(pid) pathview(gene.data=foldchanges,gene.idtype="ENTREZID", pathway.id=pid, species="mouse"))
tmpdn = sapply(keggresidsdn, function(pid) pathview(gene.data=foldchanges,gene.idtype="ENTREZID", pathway.id=pid, species="mouse"))
}
R dplyr data.table org.Hs.eg.db org.Mm.eg.db magrittr biomaRt gplots AnnotationDbi gage pathview From line 1 of scripts/pathway.R 
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shell: 
    """
    Rscript scripts/pathway.R {input} {params.organims} {params.comparison} {params.outname}
    """
SnakeMake From line 20 of master/Snakefile 
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shell:
    """
    Rscript scripts/GO.R {input} {params.organims} {params.comparison} {params.outname}
    """
SnakeMake From line 35 of master/Snakefile
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Created: 1yr ago
Updated: 1yr ago
Maitainers: public
URL: https://github.com/SherineAwad/GeneSetEnrichment
Name: genesetenrichment
Version: 1
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Copyright: Public Domain
License: BSD 3-Clause "New" or "Revised" License
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