Hello All,

I have performed differential expression analysis of RNAseq data for Colon cancer dataset taken  from TCGA. I got a list of differentially expressed genes by using edgeR. I also performed the goseq analysis and got the results for it. Now, I am trying to extract only those genes that are DE from my list of DE list given to goseq after the enrichment analysis. 

I used the following code, but I get an error that is posted below:

#Goseq analysis
genes=as.integer(p.adjust(de.cmn$table$PValue[de.cmn$table$logFC!=0],method="BH")<.05)

names(genes)=row.names(de.cmn$table[de.cmn$table$logFC!=0,])
table(genes)

pwf=nullp(genes,"hg19","knownGene")

GO.wall=goseq(pwf,"hg19","knownGene")

enriched=GO.wall$category[p.adjust(GO.wall$over_represented_pvalue, method="BH")<.05]

biocLite("org.Hs.eg.db")
library(org.Hs.eg.db)
biocLite("GO.db")
library(GO.db)
biocLite("annotate")
library(annotate)
sigCats <- GO.wall[which(GO.wall[,2] < 0.05),]
cats <- sigCats$category
terms <- stack(lapply(mget(cats, GO:0005615, ifnotfound=NA), extracellular space))

ERROR: Error: unexpected symbol in "terms <- stack(lapply(mget(cats, GO:0005615, ifnotfound=NA), extracellular space"

Could someone tell me what is the error about. I would really appreciate your help and thanks in advance.

This is not valid R syntax:

terms <- stack(lapply(mget(cats, GO:0005615, ifnotfound=NA), extracellular space))

You might have meant to wrap GO:0005615 and extracellular space in quotes, like so:

terms <- stack(lapply(mget(cats, "GO:0005615", ifnotfound=NA), "extracellular space"))

which will fix your syntax error, but once that's fixed, it's not clear that your mget call will work.

Are you trying to find the list of genes that you found to be DE that belong to a particular GO category that was also found significant via goseq?

Hi @Steve Lianoglou,

Thanks for the reply. As you said I have put quotes for the GO:TERM and "extracellular space" and still got the error. Yes, I wanted to get the list of genes that are DE from that particular GO category which are found significant through goseq analysis. Could you please tell me how to proceed further. Thanks in advance.

There are many ways to get the genes belonging to a particular GO term, but this is the method I find the quickest:

library(org.Hs.eg.db)
x <- org.Hs.egGO2ALLEGS
Rkeys(x) <- "GO:0005615"
EntrezIDs <- mappedLkeys(x)

Now EntrezIDs contains the Entrez Gene IDs of all the genes in this GO term.

To examine which of these genes are DE, you can subset your edgeR object:

i <- rownames(de.cmn) %in% EntrezIDs
de.cmn[i,]