--- /dev/null
+EBMultiTest <-
+function(Data,NgVector=NULL,Conditions,AllParti=NULL, sizeFactors, maxround, tau=NULL,CI=NULL,CIthre=NULL, Pool=F, NumBin=1000, Approx=10^-10,PoolLower=.25, PoolUpper=.75)
+{
+
+ if(is.null(NgVector))NgVector=rep(1,nrow(Data))
+ if(!is.factor(Conditions))Conditions=as.factor(Conditions)
+
+
+ #ReNameThem
+ IsoNamesIn=rownames(Data)
+ Names=paste("I",c(1:dim(Data)[1]),sep="")
+ names(IsoNamesIn)=Names
+ rownames(Data)=paste("I",c(1:dim(Data)[1]),sep="")
+ names(NgVector)=paste("I",c(1:dim(Data)[1]),sep="")
+
+ # If PossibleCond==NULL, use all combinations
+ NumCond=nlevels(Conditions)
+ CondLevels=levels(Conditions)
+ #library(blockmodeling)
+ if(is.null(AllParti)){
+ AllPartiList=sapply(1:NumCond,function(i)nkpartitions(NumCond,i))
+ AllParti=do.call(rbind,AllPartiList)
+ colnames(AllParti)=CondLevels
+ rownames(AllParti)=paste("Pattern",1:nrow(AllParti),sep="")
+ }
+ if(!length(sizeFactors)==ncol(Data)){
+ rownames(sizeFactors)=rownames(Data)
+ colnames(sizeFactors)=Conditions
+ }
+
+
+ NoneZeroLength=nlevels(as.factor(NgVector))
+ NameList=sapply(1:NoneZeroLength,function(i)names(NgVector)[NgVector==i],simplify=F)
+ DataList=sapply(1:NoneZeroLength , function(i) Data[NameList[[i]],],simplify=F)
+ names(DataList)=names(NameList)
+
+ NumEachGroup=sapply(1:NoneZeroLength , function(i)dim(DataList)[i])
+ # Unlist
+ DataList.unlist=do.call(rbind, DataList)
+
+ # Divide by SampleSize factor
+
+ if(length(sizeFactors)==ncol(Data))
+ DataList.unlist.dvd=t(t( DataList.unlist)/sizeFactors)
+
+ if(length(sizeFactors)!=ncol(Data))
+ DataList.unlist.dvd=DataList.unlist/sizeFactors
+
+ # Pool or Not
+ if(Pool==T){
+ DataforPoolSP.dvd=MeanforPoolSP.dvd=vector("list",NumCond)
+ for(lv in 1:NumCond){
+ DataforPoolSP.dvd[[lv]]=matrix(DataList.unlist.dvd[,Conditions==levels(Conditions)[lv]],nrow=dim(DataList.unlist)[1])
+ MeanforPoolSP.dvd[[lv]]=rowMeans(DataforPoolSP.dvd[[lv]])
+ }
+ MeanforPool.dvd=rowMeans(DataList.unlist.dvd)
+ NumInBin=floor(dim(DataList.unlist)[1]/NumBin)
+ StartSeq=c(0:(NumBin-1))*NumInBin+1
+ EndSeq=c(StartSeq[-1]-1,dim(DataList.unlist)[1])
+ MeanforPool.dvd.Sort=sort(MeanforPool.dvd,decreasing=T)
+ MeanforPool.dvd.Order=order(MeanforPool.dvd,decreasing=T)
+ PoolGroups=sapply(1:NumBin,function(i)(names(MeanforPool.dvd.Sort)[StartSeq[i]:EndSeq[i]]),simplify=F)
+ #FCforPool=MeanforPoolSP.dvd1/MeanforPoolSP.dvd2
+ # Use GeoMean of every two-group partition
+ Parti2=nkpartitions(NumCond,2)
+ FCForPoolList=sapply(1:nrow(Parti2),function(i)rowMeans(do.call(cbind,
+ MeanforPoolSP.dvd[Parti2[i,]==1]))/
+ rowMeans(do.call(cbind,MeanforPoolSP.dvd[Parti2[i,]==2])),
+ simplify=F)
+ FCForPoolMat=do.call(cbind,FCForPoolList)
+ FCforPool=apply(FCForPoolMat,1,function(i)exp(mean(log(i))))
+ names(FCforPool)=names(MeanforPool.dvd)
+ FC_Use=names(FCforPool)[which(FCforPool>=quantile(FCforPool[!is.na(FCforPool)],PoolLower) & FCforPool<=quantile(FCforPool[!is.na(FCforPool)],PoolUpper))]
+ PoolGroupVar=sapply(1:NumBin,function(i)(mean(apply(matrix(DataList.unlist[PoolGroups[[i]][PoolGroups[[i]]%in%FC_Use],],ncol=ncol(DataList.unlist)),1,var))))
+ PoolGroupVarInList=sapply(1:NumBin,function(i)(rep(PoolGroupVar[i],length(PoolGroups[[i]]))),simplify=F)
+ PoolGroupVarVector=unlist(PoolGroupVarInList)
+ VarPool=PoolGroupVarVector[MeanforPool.dvd.Order]
+ names(VarPool)=names(MeanforPool.dvd)
+ }
+
+ DataListSP=vector("list",nlevels(Conditions))
+ DataListSP.dvd=vector("list",nlevels(Conditions))
+ SizeFSP=DataListSP
+ MeanSP=DataListSP
+ VarSP=DataListSP
+ GetPSP=DataListSP
+ RSP=DataListSP
+ CISP=DataListSP
+ tauSP=DataListSP
+
+ NumEachCondLevel=summary(Conditions)
+ if(Pool==F & is.null(CI)) CondLevelsUse=CondLevels[NumEachCondLevel>1]
+ if(Pool==T | !is.null(CI)) CondLevelsUse=CondLevels
+ NumCondUse=length(CondLevelsUse)
+
+ for (lv in 1:nlevels(Conditions)){
+ DataListSP[[lv]]= matrix(DataList.unlist[,Conditions==levels(Conditions)[lv]],nrow=dim(DataList.unlist)[1])
+ rownames(DataListSP[[lv]])=rownames(DataList.unlist)
+ DataListSP.dvd[[lv]]= matrix(DataList.unlist.dvd[,Conditions==levels(Conditions)[lv]],nrow=dim(DataList.unlist.dvd)[1])
+ if(ncol(DataListSP[[lv]])==1 & Pool==F & !is.null(CI)){
+ CISP[[lv]]=matrix(CI[,Conditions==levels(Conditions)[lv]],nrow=dim(DataList.unlist.dvd)[1])
+ tauSP[[lv]]=matrix(tau[,Conditions==levels(Conditions)[lv]],nrow=dim(DataList.unlist.dvd)[1])
+ }
+ # no matter sizeFactors is a vector or a matrix. Matrix should be columns are the normalization factors
+ # may input one for each
+ if(length(sizeFactors)==ncol(Data))SizeFSP[[lv]]=sizeFactors[Conditions==levels(Conditions)[lv]]
+ if(length(sizeFactors)!=ncol(Data))SizeFSP[[lv]]=sizeFactors[,Conditions==levels(Conditions)[lv]]
+
+ MeanSP[[lv]]=rowMeans(DataListSP.dvd[[lv]])
+
+ if(length(sizeFactors)==ncol(Data))PrePareVar=sapply(1:ncol( DataListSP[[lv]]),function(i)( DataListSP[[lv]][,i]- SizeFSP[[lv]][i]*MeanSP[[lv]])^2 /SizeFSP[[lv]][i])
+ if(length(sizeFactors)!=ncol(Data))PrePareVar=sapply(1:ncol( DataListSP[[lv]]),function(i)( DataListSP[[lv]][,i]- SizeFSP[[lv]][,i]*MeanSP[[lv]])^2 /SizeFSP[[lv]][,i])
+
+ if(ncol(DataListSP[[lv]])==1 & Pool==F & !is.null(CI))
+ VarSP[[lv]]=as.vector(((DataListSP[[lv]]/tauSP[[lv]]) * CISP[[lv]]/(CIthre*2))^2)
+ if( Pool==T){
+ VarSP[[lv]]=VarPool
+ }
+ if(ncol(DataListSP[[lv]])!=1){
+ VarSP[[lv]]=rowSums(PrePareVar)/ncol( DataListSP[[lv]])
+ names(VarSP[[lv]])=rownames(DataList.unlist)
+ GetPSP[[lv]]=MeanSP[[lv]]/VarSP[[lv]]
+ RSP[[lv]]=MeanSP[[lv]]*GetPSP[[lv]]/(1-GetPSP[[lv]])
+ }
+ names(MeanSP[[lv]])=rownames(DataList.unlist)
+ }
+
+ # Get Empirical R
+ # POOL R???
+ MeanList=rowMeans(DataList.unlist.dvd)
+ VarList=apply(DataList.unlist.dvd, 1, var)
+ Varcbind=do.call(cbind,VarSP[CondLevels%in%CondLevelsUse])
+ PoolVarSpeedUp_MDFPoi_NoNormVarList=rowMeans(Varcbind)
+ VarrowMin=apply(Varcbind,1,min)
+ GetP=MeanList/PoolVarSpeedUp_MDFPoi_NoNormVarList
+
+ EmpiricalRList=MeanList*GetP/(1-GetP)
+ # sep
+ #Rcb=cbind(RSP[[1]],RSP[[2]])
+ #Rbest=apply(Rcb,1,function(i)max(i[!is.na(i) & i!=Inf]))
+ EmpiricalRList[EmpiricalRList==Inf] =max(EmpiricalRList[EmpiricalRList!=Inf])
+ # fine
+ #
+ GoodData=names(MeanList)[EmpiricalRList>0 & VarrowMin!=0 & EmpiricalRList!=Inf & !is.na(VarrowMin) & !is.na(EmpiricalRList)]
+ NotIn=names(MeanList)[EmpiricalRList<=0 | VarrowMin==0 | EmpiricalRList==Inf | is.na(VarrowMin) | is.na(EmpiricalRList)]
+ #NotIn.BestR=Rbest[NotIn.raw]
+ #NotIn.fix=NotIn.BestR[which(NotIn.BestR>0)]
+ #EmpiricalRList[names(NotIn.fix)]=NotIn.fix
+ #print(paste("ZeroVar",sum(VarrowMin==0), "InfR", length(which(EmpiricalRList==Inf)), "Poi", length(which(EmpiricalRList<0)), ""))
+ #GoodData=c(GoodData.raw,names(NotIn.fix))
+ #NotIn=NotIn.raw[!NotIn.raw%in%names(NotIn.fix)]
+ EmpiricalRList.NotIn=EmpiricalRList[NotIn]
+ EmpiricalRList.Good=EmpiricalRList[GoodData]
+ EmpiricalRList.Good[EmpiricalRList.Good<1]=1+EmpiricalRList.Good[EmpiricalRList.Good<1]
+ if(length(sizeFactors)==ncol(Data))
+ EmpiricalRList.Good.mat= outer(EmpiricalRList.Good, sizeFactors)
+ if(!length(sizeFactors)==ncol(Data))
+ EmpiricalRList.Good.mat=EmpiricalRList.Good* sizeFactors[GoodData,]
+
+
+ # Only Use Data has Good q's
+ DataList.In=sapply(1:NoneZeroLength, function(i)DataList[[i]][GoodData[GoodData%in%rownames(DataList[[i]])],],simplify=F)
+ DataList.NotIn=sapply(1:NoneZeroLength, function(i)DataList[[i]][NotIn[NotIn%in%rownames(DataList[[i]])],],simplify=F)
+ DataListIn.unlist=do.call(rbind, DataList.In)
+ DataListNotIn.unlist=do.call(rbind, DataList.NotIn)
+
+ DataListSPIn=vector("list",nlevels(Conditions))
+ DataListSPNotIn=vector("list",nlevels(Conditions))
+ EmpiricalRList.Good.mat.SP=vector("list",nlevels(Conditions))
+ for (lv in 1:nlevels(Conditions)){
+ DataListSPIn[[lv]]= matrix(DataListIn.unlist[,Conditions==levels(Conditions)[lv]],nrow=dim(DataListIn.unlist)[1])
+ if(length(NotIn)>0) DataListSPNotIn[[lv]]= matrix(DataListNotIn.unlist[,Conditions==levels(Conditions)[lv]],nrow=dim(DataListNotIn.unlist)[1])
+ rownames(DataListSPIn[[lv]])=rownames(DataListIn.unlist)
+ if(length(NotIn)>0)rownames(DataListSPNotIn[[lv]])=rownames(DataListNotIn.unlist)
+ EmpiricalRList.Good.mat.SP[[lv]]=matrix(EmpiricalRList.Good.mat[,Conditions==levels(Conditions)[lv]],nrow=dim(EmpiricalRList.Good.mat)[1])
+ }
+
+ NumOfEachGroupIn=sapply(1:NoneZeroLength, function(i)max(0,dim(DataList.In[[i]])[1]))
+ NumOfEachGroupNotIn=sapply(1:NoneZeroLength, function(i)max(0,dim(DataList.NotIn[[i]])[1]))
+
+ #Initialize SigIn & ...
+ AlphaIn=0.5
+ BetaIn=rep(0.5,NoneZeroLength)
+ PIn=rep(1/nrow(AllParti),nrow(AllParti))
+
+ ####use while to make an infinity round?
+ UpdateAlpha=NULL
+ UpdateBeta=NULL
+ UpdateP=NULL
+ UpdatePFromZ=NULL
+ Timeperround=NULL
+ for (times in 1:maxround){
+ temptime1=proc.time()
+ UpdateOutput=suppressWarnings(LogNMulti(DataListIn.unlist,DataListSPIn, EmpiricalRList.Good.mat ,EmpiricalRList.Good.mat.SP,
+ NumOfEachGroupIn, AlphaIn, BetaIn, PIn, NoneZeroLength, AllParti,Conditions))
+ print(paste("iteration", times, "done",sep=" "))
+ AlphaIn=UpdateOutput$AlphaNew
+ BetaIn=UpdateOutput$BetaNew
+ PIn=UpdateOutput$PNew
+ PFromZ=UpdateOutput$PFromZ
+ FOut=UpdateOutput$FGood
+ UpdateAlpha=rbind(UpdateAlpha,AlphaIn)
+ UpdateBeta=rbind(UpdateBeta,BetaIn)
+ UpdateP=rbind(UpdateP,PIn)
+ UpdatePFromZ=rbind(UpdatePFromZ,PFromZ)
+ temptime2=proc.time()
+ Timeperround=c(Timeperround,temptime2[3]-temptime1[3])
+ print(paste("time" ,Timeperround[times],sep=" "))
+ Z.output=UpdateOutput$ZEachGood
+ Z.NA.Names=UpdateOutput$zNaNName
+ }
+ #Remove this } after testing!!
+
+# if (times!=1){
+# if((UpdateAlpha[times]-UpdateAlpha[times-1])^2+UpdateBeta[times]-UpdateBeta[times-1])^2+UpdateR[times]-UpdateR[times-1])^2+UpdateP[times]-UpdateP[times-1])^2<=10^(-6)){
+# Result=list(Sig=SigIn, Miu=MiuIn, Tau=TauIn)
+# break
+# }
+# }
+#}
+
+##########Change Names############
+## Only z are for Good Ones
+## Others are for ALL Data
+GoodData=GoodData[!GoodData%in%Z.NA.Names]
+IsoNamesIn.Good=as.vector(IsoNamesIn[GoodData])
+RealName.Z.output=Z.output
+RealName.F=FOut
+rownames(RealName.Z.output)=IsoNamesIn.Good
+rownames(RealName.F)=IsoNamesIn.Good
+
+RealName.EmpiricalRList=sapply(1:NoneZeroLength,function(i)EmpiricalRList[names(EmpiricalRList)%in%NameList[[i]]], simplify=F)
+RealName.MeanList=sapply(1:NoneZeroLength,function(i)MeanList[names(MeanList)%in%NameList[[i]]], simplify=F)
+RealName.SPMeanList=sapply(1:NoneZeroLength,function(i)sapply(1:length(MeanSP), function(j)MeanSP[[j]][names(MeanSP[[j]])%in%NameList[[i]]],simplify=F), simplify=F)
+RealName.SPVarList=sapply(1:NoneZeroLength,function(i)sapply(1:length(VarSP), function(j)VarSP[[j]][names(VarSP[[j]])%in%NameList[[i]]],simplify=F), simplify=F)
+RealName.DataList=sapply(1:NoneZeroLength,function(i)DataList[[i]][rownames(DataList[[i]])%in%NameList[[i]],], simplify=F)
+
+RealName.VarList=sapply(1:NoneZeroLength,function(i)VarList[names(VarList)%in%NameList[[i]]], simplify=F)
+RealName.PoolVarList=sapply(1:NoneZeroLength,function(i)PoolVarSpeedUp_MDFPoi_NoNormVarList[names(PoolVarSpeedUp_MDFPoi_NoNormVarList)%in%NameList[[i]]], simplify=F)
+RealName.QList=sapply(1:NoneZeroLength,function(i)sapply(1:length(GetPSP), function(j)GetPSP[[j]][names(GetPSP[[j]])%in%NameList[[i]]],simplify=F), simplify=F)
+
+
+for (i in 1:NoneZeroLength){
+tmp=NameList[[i]]
+names=IsoNamesIn[tmp]
+RealName.MeanList[[i]]=RealName.MeanList[[i]][NameList[[i]]]
+RealName.VarList[[i]]=RealName.VarList[[i]][NameList[[i]]]
+ for(j in 1:NumCond){
+ RealName.SPMeanList[[i]][[j]]=RealName.SPMeanList[[i]][[j]][NameList[[i]]]
+ if(!is.null(RealName.QList[[i]][[j]])){
+ RealName.QList[[i]][[j]]=RealName.QList[[i]][[j]][NameList[[i]]]
+ RealName.SPVarList[[i]][[j]]=RealName.SPVarList[[i]][[j]][NameList[[i]]]
+ names(RealName.QList[[i]][[j]])=names
+ names(RealName.SPVarList[[i]][[j]])=names
+ }
+ names(RealName.SPMeanList[[i]][[j]])=names
+ }
+RealName.EmpiricalRList[[i]]=RealName.EmpiricalRList[[i]][NameList[[i]]]
+RealName.PoolVarList[[i]]=RealName.PoolVarList[[i]][NameList[[i]]]
+RealName.DataList[[i]]=RealName.DataList[[i]][NameList[[i]],]
+
+names(RealName.MeanList[[i]])=names
+names(RealName.VarList[[i]])=names
+
+names(RealName.EmpiricalRList[[i]])=names
+names(RealName.PoolVarList[[i]])=names
+rownames(RealName.DataList[[i]])=names
+
+}
+
+
+#########posterior part for other data set here later############
+AllNA=unique(c(Z.NA.Names,NotIn))
+AllZ=NULL
+AllF=NULL
+if(length(AllNA)==0){
+ AllZ=RealName.Z.output[IsoNamesIn,]
+ AllF=RealName.F[IsoNamesIn,]
+}
+ZEachNA=NULL
+if (length(AllNA)>0){
+ Ng.NA=NgVector[AllNA]
+ AllNA.Ngorder=AllNA[order(Ng.NA)]
+ NumOfEachGroupNA=rep(0,NoneZeroLength)
+ NumOfEachGroupNA.tmp=tapply(Ng.NA,Ng.NA,length)
+ names(NumOfEachGroupNA)=c(1:NoneZeroLength)
+ NumOfEachGroupNA[names(NumOfEachGroupNA.tmp)]=NumOfEachGroupNA.tmp
+ PNotIn=rep(1-Approx,length(AllNA.Ngorder))
+ MeanList.NotIn=MeanList[AllNA.Ngorder]
+ R.NotIn.raw=MeanList.NotIn*PNotIn/(1-PNotIn)
+ if(length(sizeFactors)==ncol(Data))
+ R.NotIn=matrix(outer(R.NotIn.raw,sizeFactors),nrow=length(AllNA.Ngorder))
+ if(!length(sizeFactors)==ncol(Data))
+ R.NotIn=matrix(R.NotIn.raw*sizeFactors[NotIn,],nrow=length(AllNA.Ngorder))
+
+ DataListNotIn.unlistWithZ=DataList.unlist[AllNA.Ngorder,]
+ DataListSPNotInWithZ=vector("list",nlevels(Conditions))
+ RListSPNotInWithZ=vector("list",nlevels(Conditions))
+ for (lv in 1:nlevels(Conditions)) {
+ DataListSPNotInWithZ[[lv]] = matrix(DataListSP[[lv]][AllNA.Ngorder,],nrow=length(AllNA.Ngorder))
+ RListSPNotInWithZ[[lv]]=matrix(R.NotIn[,Conditions==levels(Conditions)[lv]],nrow=length(AllNA.Ngorder))
+ }
+ FListNA=sapply(1:nrow(AllParti),function(i)sapply(1:nlevels(as.factor(AllParti[i,])),
+ function(j)f0(do.call(cbind, DataListSPNotInWithZ[AllParti[i,]==j]),AlphaIn, BetaIn,
+ do.call(cbind,RListSPNotInWithZ[AllParti[i,]==j]), NumOfEachGroupNA, log=T)),
+ simplify=F)
+ FPartiLogNA=sapply(FListNA,rowSums)
+ FMatNA=exp(FPartiLogNA)
+
+ rownames(FMatNA)=rownames(DataListNotIn.unlistWithZ)
+ PMatNA=matrix(rep(1,nrow(DataListNotIn.unlistWithZ)),ncol=1)%*%matrix(PIn,nrow=1)
+ FmultiPNA=FMatNA*PMatNA
+ DenomNA=rowSums(FmultiPNA)
+ ZEachNA=apply(FmultiPNA,2,function(i)i/DenomNA)
+
+ rownames(ZEachNA)=IsoNamesIn[AllNA.Ngorder]
+
+ AllZ=rbind(RealName.Z.output,ZEachNA)
+ AllZ=AllZ[IsoNamesIn,]
+
+ F.NotIn=FMatNA
+ rownames(F.NotIn)=IsoNamesIn[rownames(FMatNA)]
+ AllF=rbind(RealName.F,F.NotIn)
+ AllF=AllF[IsoNamesIn,]
+
+}
+colnames(AllZ)=rownames(AllParti)
+colnames(AllF)=rownames(AllParti)
+
+#############Result############################
+Result=list(Alpha=UpdateAlpha,Beta=UpdateBeta,P=UpdateP,PFromZ=UpdatePFromZ,
+ Z=RealName.Z.output,PoissonZ=ZEachNA, RList=RealName.EmpiricalRList, MeanList=RealName.MeanList,
+ VarList=RealName.VarList, QList=RealName.QList, SPMean=RealName.SPMeanList, SPEstVar=RealName.SPVarList,
+ PoolVar=RealName.PoolVarList , DataList=RealName.DataList,PPDE=AllZ,f=AllF, AllParti=AllParti)
+}
+
projects / rsem.git / blobdiff