changed output format to contain FPKM etc. ; fixed a bug for paired-end reads

[rsem.git] / EBSeq / R / LogNMultiDVDP.R

diff --git a/EBSeq/R/LogNMultiDVDP.R b/EBSeq/R/LogNMultiDVDP.R
deleted file mode 100644 (file)
index 6e85a5d..0000000
--- a/EBSeq/R/LogNMultiDVDP.R
+++ /dev/null
@@ -1,57 +0,0 @@
-LogNMulti <-
-function(Input, InputSP, EmpiricalR, EmpiricalRSP, NumOfEachGroup, AlphaIn, BetaIn,  PIn, NoneZeroLength, AllParti, Conditions)
-{
-
-        #For each gene (m rows of Input---m genes)
-        #Save each gene's F0, F1 for further likelihood calculation. 
-               FList=sapply(1:nrow(AllParti),function(i)sapply(1:nlevels(as.factor(AllParti[i,])),
-                                  function(j)f0(do.call(cbind,InputSP[AllParti[i,]==j]),AlphaIn, BetaIn, 
-                                                                        do.call(cbind,EmpiricalRSP[AllParti[i,]==j]), NumOfEachGroup, log=T)),
-                                         simplify=F) 
-               FPartiLog=sapply(FList,rowSums)
-               FMat=exp(FPartiLog)
-               rownames(FMat)=rownames(Input)
-        #Get z
-               #Use data.list in logfunction
-        PInMat=matrix(rep(1,nrow(Input)),ncol=1)%*%matrix(PIn,nrow=1)
-               FmultiP=FMat*PInMat
-               Denom=rowSums(FmultiP)
-               ZEach=apply(FmultiP,2,function(i)i/Denom)
-               zNaNName1=names(Denom)[is.na(Denom)]
-               # other NAs in LikeFun
-               LF=ZEach*(log(FmultiP))
-               zNaNMore=rownames(LF)[which(is.na(rowSums(LF)))]
-               zNaNName=unique(c(zNaNName1,zNaNMore))
-               zGood=which(!rownames(LF)%in%zNaNName)
-               ZEachGood=ZEach[zGood,]
-               ###Update P
-        PFromZ=colSums(ZEach[zGood,])/length(zGood)
-        NewPInMat=matrix(rep(1,nrow(Input)),ncol=1)%*%matrix(PFromZ,nrow=1)
-               FGood=FMat[zGood,]
-               ### MLE Part ####
-        # Since we dont wanna update p and Z in this step
-        # Each Ng for one row
-               
-               NumGroupVector=rep(c(1:NoneZeroLength),NumOfEachGroup)
-               
-               NumGroupVector.zGood=NumGroupVector[zGood]
-               NumOfEachGroup.zGood=tapply(NumGroupVector.zGood,NumGroupVector.zGood,length)
-
-        StartValue=c(AlphaIn, BetaIn)
-               InputSPGood=sapply(1:length(InputSP),function(i)InputSP[[i]][zGood,],simplify=F)
-        EmpiricalRSPGood=sapply(1:length(EmpiricalRSP),function(i)EmpiricalRSP[[i]][zGood,],simplify=F)
-
-               Result<-optim(StartValue,LikefunMulti,InputPool=list(InputSPGood,Input[zGood,],ZEach[zGood,], 
-                                        NoneZeroLength,EmpiricalR[zGood, ],EmpiricalRSPGood, NumOfEachGroup.zGood, AllParti,
-                                        NewPInMat))
-               AlphaNew= Result$par[1]
-               BetaNew=Result$par[2:(1+NoneZeroLength)]
-        #PNewNo1=Result$par[(2+NoneZeroLength):length(Result$par)]
-               #PNew=c(1-sum(PNewNo1),PNewNo1)
-               PNew= PFromZ
-               ##
-        Output=list(AlphaNew=AlphaNew,BetaNew=BetaNew,PNew=PNew,ZEachNew=ZEach, ZEachGood=ZEachGood, 
-                                       PFromZ=PFromZ, zGood=zGood, zNaNName=zNaNName,FGood=FGood)
-        Output
-    }
-