Below is the command I used to run Dmrcate and enrichment analysis.
dmrCate<-cpg.annotate("array", BetaValue, what="Beta", arraytype ="EPIC", analysis.type="differential",,fdr=0.01) dmrcoutput <- dmrcate(dmrCate,lambda=500, C=5, pcutoff="fdr",min.cpgs=1,mc.cores=1) wgbs.ranges_all <- extractRanges(dmrcoutput, genome = "hg19")
enrichment_GO <- goregion(wgbs.ranges_all,collection = "GO", array.type = "EPIC") enrichment_GO <- enrichment_GO[order(enrichment_GO$P.DE),]
I have got the following results too
"ONTOLOGY" "TERM" "N" "DE" "P.DE" "FDR" "GO:0005654" "CC" "nucleoplasm" 3501 1911.66666666667 5.78302322878527e-28 1.31685221942669e-23 "GO:0043231" "CC" "intracellular membrane-bounded organelle" 11367 5316.54285714286 8.60779986601549e-27 9.80041053745193e-23 "GO:0043229" "CC" "intracellular organelle" 13162 6092.37619047619 8.98325926857439e-24 6.25634156984302e-20
Is there any ways I could fetch the genes that are used/involved to identify in each of these pathways?
Hi,
Do any one have any input on this?