Hi EagleEye, I checked GeneSCF , but we have been using topGO in our pipeline for long and repeating all the analysis using GeneSCF is not feasible at this point of time. It will be great if you can suggest any modification in the above script. Thank you
Hi Biostars, I used topGO to do GO enrichment analysis for my list of interesting genes. After the run, I used the following script to retrieve significant genes for each GO ID. Can anyone help me to automate this process in such a way that I will get a table with all enriched GO IDs with corresponding significant genes? Thank you
# retrieving the gene list related to a GO ID
# retrieve genes2GO list from the "expanded" annotation in GOdata
allGO <- genesInTerm(topGOobject)
#Getting all annotated genes for a GO ID
allGO["GO:123456"]
RetrivedGenes <- lapply(allGO,function(x) x[x %in% INT.GENES$V1] ) # where INT.GENES$V1 is my list of interesting genes
# Your significant genes for GO:123456
RetrivedGenes[["GO:123456"]]
3 answers
Give a try with GeneSCF (simple to use),
Here is an example to download complete Gene Ontology as simple table with corresponding genes
Hi,
I have automated the package for species of my interest. Use below github link for automated script of topGO. Input format provided in the sample data folder.
https://github.com/cparsania/topGO_Customized
~Chirag.
Hi,
I encountered the same issue and solved it this way:
results <- runTest(topGOobject, algorithm = "elim", statistic = "fisher")
results.tab <- GenTable(object = topGOobject, elimFisher = results) # results.tab is the table with enriched GO
AnnotatedGenes = lapply(results.tab$GO.ID, function(x) as.character(unlist(genesInTerm(object = topGOobject, whichGO = x)))) # list containg genes annotated to significant GO terms
SignificantGenes = lapply(AnnotatedGenes, function(x) intersect(x, INT.GENES$V1)) # where INT.GENES$V1 is your list of interesting genes
HTH
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