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R/BioconductorのGOstats packageをもちいたGene Ontology(GO)やKEGGのenrichment解析

Last updated at Posted at 2016-07-13

#GO enrichment analysis

R/Bioconductorの GOstats packageをもちいてGene Ontology (GO) enrichment analysisをおこなう。
-1*log10(p-value)の棒グラフや、各アノテーションに該当した遺伝子のリストも一緒に取得する。

##準備

以下の2種類の遺伝子リストをEntrez GeneのID番号(=NCBI Gene, LocusLink)で用意する。

  • EntrezGeneID_interest.txt : 自分の注目する遺伝子セット
  • EntrezGeneID_background.txt : その遺伝子セットをみつけてきたときのおおもとの遺伝子全体のリスト

Gene SymbolなどからBioMartなどでEntrez Gene IDに変換すると楽かも。

##Entrez Geneのリスト読み込み

BGFILE <- "EntrezGeneID_background.txt"
INFILE <- "EntrezGeneID_interest.txt"

geneIds <- as.character(read.table(INFILE,header=FALSE)[,1])
univIds <- as.character(read.table(BGFILE,header=FALSE)[,1])

##閾値などの設定

ANNOTATION <- "org.Mm.eg.db"
ONTOLOGY <- "BP"
PVALUE<-0.01
TOP <- 30
OUTNAME <- "myinterest"

ANNOTATIONはマウスなら"org.Mm.eg.db"だしヒトなら"org.Hs.eg.db"
ONTOLOGYは"BP","MF","CC"
(それぞれbiological process, molecular function, cellular component)

##ライブラリの読み込み

library("GOstats")
library("GO.db")
library("annotate")
library("org.Mm.eg.db")

##関数を作成

GOHYPERG <- function(geneIds,univIds,ANNOTATION,ONTOLOGY,PVALUE,TOP,OUTNAME) {
	param <- new(
 		"GOHyperGParams",
 		geneIds=geneIds,
 		universeGeneIds=univIds,
 		annotation= ANNOTATION,
 		ontology=ONTOLOGY
 	)
 	GOHypG <- hyperGTest(param)
 	DETECTGO <- sigCategories(
 		GOHypG,
 		pvalue <- PVALUE
 	)
 	if (length(DETECTGO)==0) {
 		RESULT_GOHYP <- data.frame(
 			GOid="",
 			pvalue="",
 			oddratio="",
 			expected="",
 			obserbed="",
 			background="",
 			numberMappedGenes=paste(geneMappedCount(GOHypG),length(geneIds),sep="/"),
 			numberMappedBkgGenes=paste(universeMappedCount(GOHypG),length(univIds),sep="/"),
 			GOterm="-",
 			observedGenes="-"
 		)
 	} else {
 		RESULT_GOHYP <- data.frame(
 			GOid=DETECTGO,
 			pvalue=pvalues(GOHypG)[DETECTGO],
 			oddratio=oddsRatios(GOHypG)[DETECTGO],
 			expected=expectedCounts(GOHypG)[DETECTGO],
 			obserbed=geneCounts(GOHypG)[DETECTGO],
 			background=universeCounts(GOHypG)[DETECTGO],
 			numberMappedGenes=paste(geneMappedCount(GOHypG),length(geneIds),sep="/"),
 			numberMappedBkgGenes=paste(universeMappedCount(GOHypG),length(univIds),sep="/"),
 			GOterm=sapply(
 				DETECTGO,
 				function(goIDs){
 					sapply(
 						goIDs,
 						function(goID){Term(get(goID,GOTERM))}
 					)
 				}
 			),
 			observedGenes=sapply(
 				DETECTGO,
 				function(X){
 					paste(
 						sapply(
 							geneIdsByCategory(GOHypG,catids = NULL)[[X]],
 							function(XXX){paste(get(XXX,org.Mm.egSYMBOL),"(",XXX,")",sep="")}
 						),
 						collapse=","
 					)
 				}
 			)
 		)
 		
	 	BARHEIGHT <- -1 * log(RESULT_GOHYP[1:TOP,2],10)[TOP:1]
 		BARNAME <- RESULT_GOHYP$GOterm[TOP:1]
 	 	SAVEPDFNAME <- paste("RESULT_GOHYP_",ONTOLOGY,"_",OUTNAME,".pdf",sep="")
 	 	pdf(SAVEPDFNAME)
 	 	par(oma=c(2,2,2,2),mar=c(6,16,1,1))
 	 	barplot(
 			BARHEIGHT,
 			width=1,
 			space=NULL,
 			horiz=TRUE,
 			las=1,
 			main=paste(strsplit(SAVEFILENAME,".txt")[[1]][1]),
 			cex.main=.7,
 			sub=paste("(TOP",TOP," GOs)",sep=""),
 			cex.sub=.7,
 			names.arg=BARNAME,
 			cex.names=.6,
 			xlab="-1 * log10(p-value)",
 			cex.axis = 1
 		)
 		dev.off()
 	}
 			
 	SAVEFILENAME <- paste("RESULT_GOHYP_",ONTOLOGY,"_",OUTNAME,".txt",sep="")
 	write.table(RESULT_GOHYP,SAVEFILENAME,sep="\t",eol="\n",quote=FALSE,row.names=FALSE)
 	
 	return(OUTNAME)
 	
} ## end of func. GOHYPERG

##実行

GOHYPERG(geneIds,univIds,ANNOTATION,ONTOLOGY,PVALUE,TOP,OUTNAME)

"BP","MF","CC"全部やりたいなら

for (ONTOLOGY in c("BP","MF","CC")) {
	GOHYPERG(geneIds,univIds,ANNOTATION,ONTOLOGY,PVALUE,TOP,OUTNAME)
}

#KEGGでenrichment analysis

GOのかわりにKEGGでもやれる。"BP","MF","CC"のかわりに"over","under"になる

##ライブラリ読み込み

library("KEGG.db")

##関数を作成

KEGGHYPERG <- function(geneIds,univIds,ANNOTATION,OVERUNDER,PVALUE,TOP,OUTNAME) {
	keggparam <- new(
		"KEGGHyperGParams",
		geneIds=geneIds,
		universeGeneIds=univIds,
		annotation= ANNOTATION,
		pvalueCutoff=PVALUE,
		testDirection=OVERUNDER
	)
	KEGGHypG <- hyperGTest(keggparam)
	DETECTKEGG <- sigCategories(KEGGHypG,pvalue<-PVALUE)
	if (length(DETECTKEGG)==0) {
		RESULT_KEGGHYP <- data.frame(
			KEGGid="",
			pvalue="",
			oddratio="",
			expected="",
			obserbed="",
			background="",
			numberMappedGenes=paste(geneMappedCount(KEGGHypG),length(geneIds),sep="/"),
			numberMappedBkgGenes=paste(universeMappedCount(KEGGHypG),length(univIds),sep="/"),
			KEGGterm="-",
			observedGenes="-"
		)
	} else {
		RESULT_KEGGHYP <- data.frame(
			KEGGid=DETECTKEGG,
			pvalue=pvalues(KEGGHypG)[DETECTKEGG],
			oddratio=oddsRatios(KEGGHypG)[DETECTKEGG],
			expected=expectedCounts(KEGGHypG)[DETECTKEGG],
			obserbed=geneCounts(KEGGHypG)[DETECTKEGG],
			background=universeCounts(KEGGHypG)[DETECTKEGG],
			numberMappedGenes=paste(geneMappedCount(KEGGHypG),length(geneIds),sep="/"),
			numberMappedBkgGenes=paste(universeMappedCount(KEGGHypG),length(univIds),sep="/"),
			KEGGterm=sapply(DETECTKEGG,function(keggIDs){sapply(keggIDs,function(keggID){get(keggID,KEGGPATHID2NAME)})}),
			observedGenes=sapply(
				DETECTKEGG,
				function(X){paste(sapply(
					geneIdsByCategory(KEGGHypG, catids = NULL)[[X]],
					function(XXX){paste(get(XXX,org.Mm.egSYMBOL),"(",XXX,")",sep="")}),collapse=",")}
			)
		)
		SAVEFILENAME <- paste("RESULT_KEGGHYP_",OVERUNDER,OUTNAME,".txt",sep="")
		write.table(RESULT_KEGGHYP,SAVEFILENAME,sep="\t",eol="\n",quote=FALSE,row.names=FALSE)
		BARHEIGHT <- -1 * log(RESULT_KEGGHYP[1:TOP,2],10)[TOP:1]
		BARNAME <- RESULT_KEGGHYP$KEGGterm[TOP:1]
		SAVEPDFNAME <- paste("RESULT_KEGGHYP_",OVERUNDER,OUTNAME,".pdf",sep="")
		pdf(SAVEPDFNAME)
		par(oma=c(2,2,2,2),mar=c(6,16,1,1))
		barplot(
			BARHEIGHT,
	   		width=1,
	   		space=NULL,
	   		horiz=TRUE,
	   		las=1,
	   		main=paste(strsplit(SAVEFILENAME,".txt")[[1]][1]),
	   		cex.main=.7,
	   		sub=paste("(TOP",TOP," KEGGs)",sep=""),
	   		cex.sub=.7,
    		names.arg=BARNAME,
    		cex.names=.6,
    		xlab="-1 * log10(p-value)",
    		cex.axis = 1
    	)
    	dev.off()
	}
	return(OUTNAME)
} ## end of func. KEGGHYPERG

##実行

for (OVERUNDER in c("over","under")) {
	KEGGHYPERG(geneIds,univIds,ANNOTATION,OVERUNDER,PVALUE,TOP,OUTNAME)
}
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