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Included EBSeq for downstream differential expression analysis
[rsem.git] / EBSeq / R / IsoSimuAt.R
diff --git a/EBSeq/R/IsoSimuAt.R b/EBSeq/R/IsoSimuAt.R
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+IsoSimuAt<-function(DVDconstant=NULL, DVDqt1=NULL, DVDqt2=NULL, Conditions, NumofSample, NumofIso=NULL, DEIsoProp, Phiconstant=NULL, Phi.qt1=NULL, Phi.qt2=NULL,NormFactor=NULL, OnlyData=T)
+{
+#Ng paired 2012 feb 1
+if(is.null(NormFactor)) NormFactor=rep(1,NumofSample)
+data(IsoEBresultGouldBart2)
+
+MeansC1=IsoEBresultGouldBart2$C1Mean
+MeansC2=IsoEBresultGouldBart2$C2Mean
+MeanDVD=sapply(1:9,function(i) MeansC1[[i]]/MeansC2[[i]])
+if (length(DVDconstant)==0) DVDLibrary= unlist(MeanDVD)[unlist(MeanDVD)<quantile(unlist(MeanDVD)[unlist(MeanDVD)!=Inf],DVDqt2) & unlist(MeanDVD)>quantile(unlist(MeanDVD)[unlist(MeanDVD)!=Inf],DVDqt1)]
+
+
+
+
+VarInput=IsoEBresultGouldBart2$VarList
+VarInputNg=list(VarInput[[1]],unlist(VarInput[c(2,4,6,8)]),unlist(VarInput[c(3,5,7,9)]))
+
+if(length(NumofIso)==0) NumofIso=sapply(1:3,function(i)length(VarInputNg[[i]]))
+PhiInput.raw=IsoEBresultGouldBart2$RList
+PhiInput.raw.Ng=list(PhiInput.raw[[1]],unlist(PhiInput.raw[c(2,4,6,8)]),unlist(PhiInput.raw[c(3,5,7,9)]))
+
+
+if (length(Phiconstant)==0){
+       PhiLibrary=sapply(1:3,function(i)PhiInput.raw.Ng[[i]][1/PhiInput.raw.Ng[[i]]<quantile(1/PhiInput.raw.Ng[[i]],Phi.qt2) & 1/PhiInput.raw.Ng[[i]]>quantile(1/PhiInput.raw.Ng[[i]],Phi.qt1)],simplify=F)
+       PhiIndex=sapply(1:3, function(i)sample(names(PhiLibrary[[i]]),NumofIso[[i]],replace=T),simplify=F)
+       PhiInputNg=sapply(1:3, function(i)PhiLibrary[[i]][PhiIndex[[i]]])
+}
+if (length(Phiconstant)!=0)PhiInputNg=sapply(1:3,function(i)rep(Phiconstant,NumofIso[[i]]),simplify=F)
+
+# Wanna DENumbers be proportion to 2 
+DEIsoNumbers=round(NumofIso*DEIsoProp/2)*2
+IsoNames=sapply(1:3,function(i)paste("I",i,c(1:NumofIso[i]),sep="_"),simplify=F)
+MeanNg=list(IsoEBresultGouldBart2$MeanList[[1]],unlist(IsoEBresultGouldBart2$MeanList[c(2,4,6,8)]),
+unlist(IsoEBresultGouldBart2$MeanList[c(3,5,7,9)]))
+MeanInputNg=sapply(1:3, function(i)MeanNg[[i]][PhiIndex[[i]]])
+
+for(i in 1:3){
+       names(MeanInputNg[[i]])=IsoNames[[i]]
+       names(PhiInputNg[[i]])=IsoNames[[i]]
+       }
+
+#########
+# data
+#########
+EEList=sapply(1:3,function(i) sapply(1:NumofIso[[i]], function(j)sapply(1:NumofSample,function(h) rnbinom(1,mu=MeanInputNg[[i]][j]*NormFactor[h], size=PhiInputNg[[i]][j]))),simplify=F)
+
+
+generateDataraw=vector("list",3)
+MeanVector=vector("list",3)
+VarVector=vector("list",3)
+MOV.post=vector("list",3)
+
+
+for(g in 1:3){
+    generateDataraw[[g]]=t(EEList[[g]][,1:NumofIso[g]])
+       if(length(DVDconstant)==0){
+               for(j in 1:NumofIso[g]){
+                if (j<=(DEIsoNumbers[g]/2)) generateDataraw[[g]][j,((NumofSample/2)+1):NumofSample]=sapply((NumofSample/2+1):NumofSample, function(h)rnbinom(1, size=PhiInputNg[[g]][j], mu=sample(DVDLibrary,1)*MeanInputNg[[g]][j]*NormFactor[h]), simplify=T)
+               if (j>=((DEIsoNumbers[g]/2)+1) & j <=DEIsoNumbers[g]) generateDataraw[[g]][j,1:(NumofSample/2)]=sapply(1:(NumofSample/2),function(h) rnbinom(1, size=MeanInputNg[[g]][j], mu= sample(DVDLibrary,1)*MeanInputNg[[g]][j]*NormFactor[h]),simplify=T)
+}
+        }
+       if(length(DVDconstant)!=0){
+        for(j in 1:NumofIso[g]){
+             if (j<=(DEIsoNumbers[g]/2)) generateDataraw[[g]][j,((NumofSample/2)+1):NumofSample]=sapply((NumofSample/2+1):NumofSample, function(h)rnbinom(1, DVDconstant*MeanInputNg[[g]][j]*NormFactor[h]),simplify=T)
+             if (j>=((DEIsoNumbers[g]/2)+1) & j <=DEIsoNumbers[g]) generateDataraw[[g]][j,1:(NumofSample/2)]=sapply(1:(NumofSample/2),function(h) rnbinom(1, DVDconstant*MeanInputNg[[g]][j]*NormFactor[h]),simplify=T)
+               }
+       }
+rownames(generateDataraw[[g]])=IsoNames[[g]][1:NumofIso[g]]
+MeanVector[[g]]=rowMeans(generateDataraw[[g]])
+VarVector[[g]]=apply(generateDataraw[[g]],1,var)
+MOV.post[[g]]=MeanVector[[g]]/VarVector[[g]]
+}
+
+
+### Remove MOV=NA
+generateData=generateDataraw
+for (i in 1:3) generateData[[i]]=generateData[[i]][!is.na(MOV.post[[i]]),] 
+print(paste("NA MOV's",sum(is.na(unlist(MOV.post)))))
+#tmpmean=sapply(1:9,function(i)rowMeans(generateData[[i]]))
+#tmpvar=sapply(1:9,function(i)apply(generateData[[i]],1,var))
+#source("plot_functions.R")
+#CheckSimuNg(tmpmean,tmpvar,c(-1,5),c(-1,7))
+
+
+
+
+## DE
+UseName=sapply(1:3, function(i)rownames(generateData[[i]]),simplify=F)
+TrueDE=sapply(1:3, function(i)UseName[[i]][UseName[[i]] %in% rownames(generateData[[i]])[1:DEIsoNumbers[i]]],simplify=F)
+TrueDE.unlist=do.call(c,TrueDE)
+
+TrueDELength=sapply(TrueDE,length)
+
+AtNames_Level=vector("list",4)
+AtLoc=vector("list",3)
+AtFold=vector("list",3)
+names(AtNames_Level)=c(4,6,8,10)
+
+
+for(j in 1:3){
+AtLoc[[j]]=sample(c(1:length(Conditions)), TrueDELength[j], replace=T)
+AtFold[[j]]=sample(c(4,6,8,10),TrueDELength[j], replace=T)
+
+for(i in 1:TrueDELength[j]){
+
+generateData[[j]][(TrueDELength[j]+i),AtLoc[[j]][i]]=generateData[[j]][(TrueDELength[j]+i),AtLoc[[j]][i]]*AtFold[[j]][i]
+AtNames_Level[[as.character(AtFold[[j]][i])]]=c(AtNames_Level[[as.character(AtFold[[j]][i])]],rownames(generateData[[j]])[TrueDELength[j]+i])
+}
+}
+phiuse=sapply(1:3,function(i)PhiInputNg[[i]][UseName[[i]]])
+meanuse=sapply(1:3,function(i)MeanInputNg[[i]][UseName[[i]]])
+
+#generateDataNg=list(generateData[[1]], do.call(rbind,generateData[c(2,4,6,8)]), do.call(rbind,generateData[c(3,5,7,9)]))
+generateDataNg=generateData
+
+#if(OnlyData==T){
+
+OutName=sapply(1:3,function(i)paste("Iso",i,c(1:nrow(generateDataNg[[i]])),sep="_"))
+for(i in 1:3)names(OutName[[i]])=rownames(generateDataNg[[i]])
+OutData=generateDataNg
+for(i in 1:3)rownames(OutData[[i]])=as.vector(OutName[[i]])
+OutTrueDE=as.vector(unlist(OutName)[TrueDE.unlist])
+OutAt=as.vector(unlist(OutName)[AtNames <- Level])
+
+output=list(data=OutData, TrueDE=OutTrueDE, Outliers=OutAt)
+#      return(output)
+#    }
+       }