@@ -1160,6 +1160,8 @@ preprocessInf <- function(cnSet,

 		 useTarget=useTarget,

 		 A=A(cnSet),

 		 B=B(cnSet),

+		 GT=calls(cnSet),

+		 GTP=snpCallProbability(cnSet),

 		 SKW=cnSet$SKW,

 		 SNR=cnSet$SNR,

 		 mixtureParams=mixtureParams,

@@ -1178,22 +1180,22 @@ genotypeInf <- function(cnSet, mixtureParams, probs=rep(1/3,3),

 			badSNP=0.7,

 			gender=NULL,

 			DF=6){

-	is.snp = isSnp(cnSet)

-	snp.index = which(is.snp)

-	narrays = ncol(cnSet)

-	open(A(cnSet))

-	open(B(cnSet))

-	open(snpCall(cnSet))

-	open(snpCallProbability(cnSet))

-	## crlmmGT2 overwrites the normalized intensities with calls and confidenceScores

-	message("Writing to call and callProbability slots")

-	for(j in 1:ncol(cnSet)){

-		snpCall(cnSet)[snp.index, j] <- as.integer(A(cnSet)[snp.index, j])

-		snpCallProbability(cnSet)[snp.index, j] <- as.integer(B(cnSet)[snp.index, j])

-	}

-	message("Writing complete.  Begin genotyping...")

-	close(A(cnSet))

-	close(B(cnSet))

+##	is.snp = isSnp(cnSet)

+##	snp.index = which(is.snp)

+##	narrays = ncol(cnSet)

+##	open(A(cnSet))

+##	open(B(cnSet))

+##	open(snpCall(cnSet))

+##	open(snpCallProbability(cnSet))

+##	## crlmmGT2 overwrites the normalized intensities with calls and confidenceScores

+##	message("Writing to call and callProbability slots")

+##	for(j in 1:ncol(cnSet)){

+##		snpCall(cnSet)[snp.index, j] <- as.integer(A(cnSet)[snp.index, j])

+##		snpCallProbability(cnSet)[snp.index, j] <- as.integer(B(cnSet)[snp.index, j])

+##	}

+##	message("Writing complete.  Begin genotyping...")

+##	close(A(cnSet))

+##	close(B(cnSet))

 	tmp <- rscrlmmGT2(A=snpCall(cnSet),

 			  B=snpCallProbability(cnSet),

 			  SNR=cnSet$SNR,

@@ -1316,81 +1318,64 @@ processIDAT <- function(stratum, sampleBatches, sampleSheet=NULL,

 			sns,

 			stripNorm=TRUE,

 			useTarget=TRUE,

-			A, B, SKW, SNR, mixtureParams, is.snp) { #, outdir=".") {

+			A, B,

+			GT,

+			GTP,

+			SKW, SNR, mixtureParams, is.snp) { #, outdir=".") {

 	message("Processing sample stratum ", stratum, " of ", length(sampleBatches))

 	sel <- sampleBatches[[stratum]]

         if(length(path)>= length(sel)) path = path[sel]

-	##message("RS:... processIDAT:  calling readIdatFiles")

         RG = readIdatFiles(sampleSheet=sampleSheet[sel,], arrayNames=arrayNames[sel],

                        ids=ids, path=path, arrayInfoColNames=arrayInfoColNames,

                        highDensity=highDensity, sep=sep, fileExt=fileExt, saveDate=saveDate, verbose=verbose)

         XY = RGtoXY(RG, chipType=cdfName)

-#        open(RG@assayData$R); open(RG@assayData$G); open(RG@assayData$zero)

-#        delete(RG@assayData$R); delete(RG@assayData$G); delete(RG@assayData$zero);

         rm(RG)

         gc()

         if (missing(sns) || length(sns)!=ncol(XY)) sns = sampleNames(XY)

-

-	##message("RS:... processIDAT: calling preprocessInfinium2")

         res = preprocessInfinium2(XY, mixtureSampleSize=mixtureSampleSize, fitMixture=TRUE, verbose=verbose,

                                seed=seed, eps=eps, cdfName=cdfName, sns=sns, stripNorm=stripNorm, useTarget=useTarget) #, outdir=outdir)

-#							    save.it=save.it, snpFile=snpFile, cnFile=cnFile)

-#        open(XY@assayData$X); open(XY@assayData$Y); open(XY@assayData$zero)

-#        delete(XY@assayData$X); delete(XY@assayData$Y); delete(XY@assayData$zero);

         rm(XY)

         gc()

-	    if(verbose) message("Finished preprocessing.")

+	if(verbose) message("Finished preprocessing.")

         snp.index = which(is.snp)

 	np.index = which(!is.snp)

-

-#        open(res[["A"]])

-#        open(res[["B"]])

-#        open(res[["SKW"]])

-#        open(res[["SNR"]])

-#        open(res[["mixtureParams"]])

-# remove this line: bb = ocProbesets()*length(sns)*8

-# Add these

-	##segfault came after 'Finished preprocessing', but the processIDAT loop was not yet complete

 	open(A); open(B);

+	open(GT); open(GTP)

 	Amatrix <- res[["A"]]

 	Bmatrix <- res[["B"]]

+

+	## Amatrix and Bmatrix are ordinary matrices--not ff objects.

+	## By writing columns of a ordinary matrix to GT and GTP, we

+	## save one read step later on.  GT and GTP will be updated to

+	## calls and call probabilities by the crlmmGT2 function. The A

+	## and B slots will retain the normalized intensities for the

+	## A and B alleles

 	for(j in seq_along(sel)){

 		jj <- sel[j]

 		A[snp.index, jj] <- Amatrix[, j]

+		GT[snp.index, jj] <- Amatrix[, j]

 		B[snp.index, jj] <- Bmatrix[, j]

+		GTP[snp.index, jj] <- Bmatrix[, j]

 	}

-		##ffcolapply(A[snp.index,sel][,i1:i2] <- res[["A"]][,i1:i2], X=res[["A"]])

-		##ffcolapply(B[snp.index,sel][,i1:i2] <- res[["B"]][,i1:i2], X=res[["B"]])

-##	}

-#   ffrowapply(A[snp.index,][i1:i2, sel] <- res[["A"]][i1:i2, ], X=res[["A"]], BATCHBYTES=bb)

-#	ffrowapply(B[snp.index,][i1:i2, sel] <- res[["B"]][i1:i2, ], X=res[["B"]], BATCHBYTES=bb)

-	    if(length(np.index)>0) {

-#			for (j in 1:length(sel)) {

-		    cnAmatrix <- res[["cnAB"]]$A

-		    cnBmatrix <- res[["cnAB"]]$B

-		    for(j in seq_along(sel)){

-			    jj <- sel[j]

-			    A[np.index, jj] <- cnAmatrix[, j]

-			    B[np.index, jj] <- cnBmatrix[, j]

-		    }

-

-##			ffcolapply(A[np.index,sel][,i1:i2] <- res[["cnAB"]]$A[,i1:i2], X=res[["cnAB"]]$A)

-##			ffcolapply(B[np.index,sel][,i1:i2] <- res[["cnAB"]]$B[,i1:i2], X=res[["cnAB"]]$B)

-#            A[np.index, sel[j]] = res[["cnAB"]]$A[,j]

-#            B[np.index, sel[j]] = res[["cnAB"]]$B[,j]

-#          }

+	if(length(np.index)>0) {

+		cnAmatrix <- res[["cnAB"]]$A

+		cnBmatrix <- res[["cnAB"]]$B

+		for(j in seq_along(sel)){

+			jj <- sel[j]

+			A[np.index, jj] <- cnAmatrix[, j]

+			GT[np.index, jj] <- cnAmatrix[, j]

+			B[np.index, jj] <- cnBmatrix[, j]

+			GTP[np.index, jj] <- cnBmatrix[, j]

+		}

         }

-#        delete(res[["A"]]); delete(res[["B"]])

 	open(SKW); open(SNR); open(mixtureParams)

 	SKW[sel] = res[["SKW"]][]

 	SNR[sel] = res[["SNR"]][]

 	mixtureParams[, sel] = res[["mixtureParams"]][]

-        close(A)

-        close(B)

-        close(SNR)

-        close(SKW)

+        close(A); close(B)

+	close(GT); close(GTP)

+        close(SNR); close(SKW)

         close(mixtureParams)

-#        delete(res[["SKW"]]); delete(res[["SNR"]]); delete(res[["mixtureParams"]])

         rm(res)

 	gc()

         TRUE