[BioC] List significant genes on a GO table

[Quentin Anstee]

Dear List,
 
Can anyone advise me how to add a list of significant genes onto a gene
ontology table so that I can see which of my differentially expressed genes
belong to a given GO group?
 
I would like to be able to output a table that looks like:
 
GO_id                         Description                         p-value
#Genes    Gene_ids/symbols
GO:12345                  Glucose Metabolism          0.0001            34
IDs of the *significant* probes from the affy chip that are in this GO
pathway.
 
 
Having read the vignettes I have been able to generate most of this table
but not the last column containing the Affy_Ids (or ideally gene symbols). I
would be very grateful if someone could help me out with this. The script I
have used so far is attached.
 
Many thanks,
 
Quentin
 
1. LOAD GENE EXPRESSION ANALYSIS DATA
=========================================================
 
a. This is a three way comparison. Data is normalised, filtered,
limma/eBayes to give a MArrayLM package called fit2.
 
2. LOAD LIBRARIES
=========================================================
 
library(GO)
library(GOstats)
library(annotate)
library(simpleaffy)
library(genefilter)
library(multtest)
library(affy)
library(limma)
library(gcrma)
library(xtable)
library(mouse4302)
library(mouse4302cdf)
library(annaffy)
library(Rgraphviz)
 
3. MAKE COMPARISONS FOR DFFERENTIAL EXPRESSION
==========================================================
# B-CONTROL
tab<-topTable(fit2,coef=1)
# A-CONTROL
tab<-topTable(fit2,coef=2)
# A-B
tab<-topTable(fit2,coef=3)    
 
# topTable contains a a default multadjust
 
4. Do GO ANALYSIS, MAKE FIGURE & MAKE TABLE
==========================================================
gn<-as.character(tab$ID)
gn
LLID<-unlist(mget(gn,mouse4302LOCUSID,ifnotfound=NA))
go<-makeGOGraph(as.character(LLID),"CC",removeRoot=FALSE)
go
 
# There are 3 choices for ontology: "MF", "BP" and "CC"
 
a. Plot Graphic
----------------------------------------------------------
att<-list()
lab<-rep(nodes(go),length(nodes(go)))
names(lab)<-nodes(go)
att$label<-lab
plot(go,nodeAttrs=att)
 
# Are there more genes at one GO than expected?
----------------------------------------------------------
hyp<-GOHyperG(unique(LLID),lib="mouse4302",what="CC")
names(hyp)
go.pv<-hyp$pvalues[nodes(go)]
go.pv<-sort(go.pv)
 
b. Create Table
----------------------------------------------------------
sig<-go.pv[go.pv<0.05]
counts<-hyp$goCounts[names(sig)]
terms<-getGOTerm(names(sig))[["CC"]]
nch<-nchar(unlist(terms))
terms2<-substr(unlist(terms),1,50)
terms3<-paste(terms2,ifelse(nch>50,"...",""),sep="")
mat<-matrix(c(names(terms),terms3,round(sig,3),counts),ncol=4,dimnames=list(
1:length(sig),c("GO ID","Term","p-value","# Genes")))
mat
write.table(mat,"A_B_GO-Table_CC.txt")