+++ /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