edgeR returns a list of differentially expressed genes OK, at least they do not always return genes in the same order.

However, when I run edgeR to get the top Gene Ontology pathways like the following:

rst<-topTags(qlfTest, n=nrow(d));
drst <- data.frame("GENE_ID"=rownames(rst), rst);
write.table(drst, file="mytreatment.DEG.txt", sep="\t", row.names=F, quote=F);

## the above "drst" returns a list of differentially expressed genes with pvalues, FDR, etc., and they look alright.

# get the differentially expressed genes list, throw away genes with FDR >= 0.25
degs <- as.vector(subset(drst, FDR < 0.25)[[1]])

# do GO analysis
go <- goana(degs, species="Hs");
tgo <- topGO(go);

It always return the following list of pathways:

GO_ID   Term    Ont N   DE  P.DE
GO:0000002  mitochondrial genome maintenance    BP  20  0   1
GO:0000003  reproduction    BP  925 0   1
GO:0000009  alpha-1,6-mannosyltransferase activity  MF  2   0   1
GO:0000010  trans-hexaprenyltranstransferase activity   MF  2   0   1
GO:0000012  single strand break repair  BP  8   0   1
GO:0000014  single-stranded DNA endodeoxyribonuclease activity  MF  6   0   1
GO:0000015  phosphopyruvate hydratase complex   CC  4   0   1
GO:0000016  lactase activity    MF  1   0   1
GO:0000018  regulation of DNA recombination BP  51  0   1
GO:0000019  regulation of mitotic recombination BP  4   0   1
GO:0000022  mitotic spindle elongation  BP  2   0   1
GO:0000023  maltose metabolic process   BP  1   0   1
GO:0000026  alpha-1,2-mannosyltransferase activity  MF  3   0   1
GO:0000027  ribosomal large subunit assembly    BP  2   0   1
GO:0000028  ribosomal small subunit assembly    BP  8   0   1
GO:0000030  mannosyltransferase activity    MF  17  0   1
GO:0000033  alpha-1,3-mannosyltransferase activity  MF  3   0   1
GO:0000035  acyl binding    MF  1   0   1
GO:0000036  ACP phosphopantetheine attachment site binding involved in fatty acid biosynthetic process  MF  1   0   1
GO:0000038  very long-chain fatty acid metabolic process    BP  25  0   1

No matter what experiment datasets (can be totally unrelated experiments). I guess something is not done right.

Thanks!