@@ -582,5 +582,9 @@ be used to specify where you want to store the large data objects.  ldPath(outdi

 inside preprocessInfinium2()

 ** the 'batch' variable is now left empty and must be specified by the user

 ** X and Y are now initialized with zeroes by initializeBigMatrix( ,initdata=0) in RGtoXY().

-** open(A(callSet); open(B(callSet) replaces open(callSet) in genotyp.Illumina()

+** open(A(callSet); open(B(callSet) replaces open(callSet) in genotype.Illumina()

+2010-12-10 M. Ritchie 1.9.9

+** ffcolapply() now used instead of ffrowapply()

+** ff storage only used to initialize callSet - no longer used in storage of RG, XY, res data created along the way (matrices now used here) etc.

+** removed 'outdir' argument and ldPath() added in 1.9.8

@@ -1,8 +1,8 @@

 Package: crlmm

 Type: Package

 Title: Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays.

-Version: 1.9.8

-Date: 2010-11-18

+Version: 1.9.9

+Date: 2010-12-10

 Author: Benilton S Carvalho <carvalho@bclab.org>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.edu.au>, Ingo Ruczinski <iruczins@jhsph.edu>, Rafael A Irizarry

 Maintainer: Benilton S Carvalho <carvalho@bclab.org>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU>

 Description: Faster implementation of CRLMM specific to SNP 5.0 and 6.0 arrays, as well as a copy number tool specific to 5.0, 6.0, and Illumina platforms

@@ -11,7 +11,7 @@ readIdatFiles = function(sampleSheet=NULL,

 			  highDensity=FALSE,

 			  sep="_",

 			  fileExt=list(green="Grn.idat", red="Red.idat"),

-			  saveDate=FALSE) {

+			  saveDate=FALSE, verbose=FALSE) {

        if(!is.null(arrayNames)) {

                pd = new("AnnotatedDataFrame", data = data.frame(Sample_ID=arrayNames))

        }

@@ -72,9 +72,11 @@ readIdatFiles = function(sampleSheet=NULL,

                     scan=rep(NA, narrays))

        ## read in the data

        for(i in seq_along(arrayNames)) {

-	       cat("reading", arrayNames[i], "\t")

+	       if(verbose) {

+	         cat("reading", arrayNames[i], "\t")

+   	         cat(paste(sep, fileExt$green, sep=""), "\t")

+	       }

 	       idsG = idsR = G = R = NULL

-	       cat(paste(sep, fileExt$green, sep=""), "\t")

 	       G = readIDAT(grnidats[i])

 	       idsG = rownames(G$Quants)

 	       headerInfo$nProbes[i] = G$nSNPsRead

@@ -95,12 +97,12 @@ readIdatFiles = function(sampleSheet=NULL,

 		       nprobes = length(ids)

 		       narrays = length(arrayNames)

 		       RG = new("NChannelSet",

-		                 R=initializeBigMatrix(name="R", nr=nprobes, nc=narrays, vmode="integer"),

-		                 G=initializeBigMatrix(name="G", nr=nprobes, nc=narrays, vmode="integer"),

-		                 zero=initializeBigMatrix(name="zero", nr=nprobes, nc=narrays, vmode="integer"),

-				         annotation=headerInfo$Manifest[1],

-				         phenoData=pd, storage.mode="environment")

-			   featureNames(RG) = ids

+		                 R=matrix(NA, nprobes, narrays),

+		                 G=matrix(NA, nprobes, narrays),

+		                 zero=matrix(NA, nprobes, narrays),

+				 annotation=headerInfo$Manifest[1],

+				 phenoData=pd, storage.mode="environment")

+		       featureNames(RG) = ids

 		       if(!is.null(sampleSheet) && !is.null(sampleSheet$Sample_ID)){

 		            sampleNames(RG) = sampleSheet$Sample_ID

 		       } else  sampleNames(RG) = arrayNames

@@ -118,15 +120,16 @@ readIdatFiles = function(sampleSheet=NULL,

 	       }

 	       rm(G)

 	       gc()

-

-	       cat(paste(sep, fileExt$red, sep=""), "\n")

+	       if(verbose) { 

+                      cat(paste(sep, fileExt$red, sep=""), "\n")

+	       }

 	       R = readIDAT(redidats[i])

 	       idsR = rownames(R$Quants)

 	       if(length(ids)==length(idsG)) {

 		       if(sum(ids==idsR)==nprobes) {

 			       RG@assayData$R[,i] = R$Quants[ ,"Mean"]

-		           zeroR = R$Quants[ ,"NBeads"]==0

+		               zeroR = R$Quants[ ,"NBeads"]==0

 		       }

 	       } else {

 		       indR = match(ids, idsR)

@@ -141,12 +144,6 @@ readIdatFiles = function(sampleSheet=NULL,

 	       protocolData(RG)[["ScanDate"]] = dates$scan

        }

        storageMode(RG) = "lockedEnvironment"

-       is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

-       if(is.lds) {

-         close(RG@assayData$R)

-         close(RG@assayData$G)

-         close(RG@assayData$zero)

-       }

        RG

 }

@@ -421,7 +418,7 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

                "human1mduov3b",          # 1M Duo

                "humanomni1quadv1b",      # Omni1 quad

                "humanomni25quadv1b",     # Omni2.5 quad

-	       "humanomniexpress12v1b",  # Omni express 12

+	           "humanomniexpress12v1b",  # Omni express 12

                "humanimmuno12v1b")       # Immuno chip 12

   if(missing(chipType)){

 	  chipType = match.arg(annotation(RG), chipList)

@@ -462,9 +459,9 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

 #  brgrg = bids[rrgg]

   XY = new("NChannelSet",

-	     X=initializeBigMatrix(name="X", nr=nsnps, nc=narrays, vmode="integer", initdata=0),

-	     Y=initializeBigMatrix(name="Y", nr=nsnps, nc=narrays, vmode="integer", initdata=0),

-	     zero=initializeBigMatrix(name="zero", nr=nsnps, nc=narrays, vmode="integer", initdata=0),

+	     X=matrix(0, nsnps, narrays),

+	     Y=matrix(0, nsnps, narrays),

+	     zero=matrix(0, nsnps, narrays),

 	     annotation=chipType, phenoData=RG@phenoData,

 	     protocolData=RG@protocolData, storage.mode="environment")

   featureNames(XY) = ids

@@ -475,14 +472,6 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

 #  XY@assayData$Y[1:nsnps,] = 0

 #  XY@assayData$zero[1:nsnps,] = 0

-  is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

-

-  if(is.lds) {

-    open(RG@assayData$G)

-    open(RG@assayData$R)

-    open(RG@assayData$zero)

-  }

-

   # First sort out Infinium II SNPs, X -> R (allele A)  and Y -> G (allele B) from the same probe

   XY@assayData$X[!is.na(aord),] = exprs(channel(RG, "R"))[aord[!is.na(aord)],] # mostly red

   XY@assayData$Y[!is.na(aord),] = exprs(channel(RG, "G"))[aord[!is.na(aord)],] # mostly green

@@ -504,20 +493,10 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

 #  Y[infIGG,] = exprs(channel(RG, "G"))[bord[infIGG],] # mostly green

   #  For now zero out Infinium I probes

-  XY@assayData$X[infI,] = 0

-  XY@assayData$Y[infI,] = 0

-  XY@assayData$zero[infI,] = 0

-  gc()

-

-  is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

-  if(is.lds) {

-    close(RG@assayData$G)

-    close(RG@assayData$R)

-    close(RG@assayData$zero)

-    close(XY@assayData$X)

-    close(XY@assayData$Y)

-    close(XY@assayData$zero)

-  }

+#  XY@assayData$X[infI,] = 0

+#  XY@assayData$Y[infI,] = 0

+#  XY@assayData$zero[infI,] = 0

+#  gc()

   XY

 }

@@ -543,12 +522,7 @@ stripNormalize = function(XY, useTarget=TRUE, verbose=TRUE) {

     message("Quantile normalizing ", ncol(XY), " arrays by ", max(stripnum), " strips.")

     if (getRversion() > '2.7.0') pb = txtProgressBar(min=0, max=max(stripnum), style=3)

   }

-  is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

-  if(is.lds) {

-    open(XY@assayData$X)

-    open(XY@assayData$Y)

-  }

   for(s in 1:max(stripnum)) {

     if(verbose) {

       if (getRversion() > '2.7.0') setTxtProgressBar(pb, s)

@@ -566,10 +540,6 @@ stripNormalize = function(XY, useTarget=TRUE, verbose=TRUE) {

     rm(subX, subY, tmp, sel)

     gc()

   }

-  if(is.lds) {

-    close(XY@assayData$X)

-    close(XY@assayData$Y)

-  }

   if(verbose)

     cat("\n")

@@ -585,8 +555,8 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5,

 				cdfName,

 				sns,

 				stripNorm=TRUE,

-				useTarget=TRUE,

-                                outdir=".") {

+				useTarget=TRUE) { #,

+#               outdir=".") {

 #				save.it=FALSE,

 #				snpFile,

 #				cnFile) {

@@ -615,42 +585,30 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5,

   theKnots = getVarInEnv("theKnots")

   narrays = ncol(XY)

-  is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

-  if(is.lds)

-    ldPath(outdir)

 #  if(save.it & !missing(cnFile)) {

     # separate out copy number probes

-    npIndex = getVarInEnv("npProbesFid")

-    nprobes = length(npIndex)

-    if(length(nprobes)>0) {

-      if(is.lds) {

-        open(XY@assayData$X)

-        open(XY@assayData$Y)

-        open(XY@assayData$zero)

-      }

-      A = matrix(as.integer(exprs(channel(XY, "X"))[npIndex,]), nprobes, narrays)

-      B = matrix(as.integer(exprs(channel(XY, "Y"))[npIndex,]), nprobes, narrays)

+  npIndex = getVarInEnv("npProbesFid")

+  if(length(nprobes)>0) {

+     nprobes = length(npIndex)

+

+     A = matrix(as.integer(exprs(channel(XY, "X"))[npIndex,]), nprobes, narrays)

+     B = matrix(as.integer(exprs(channel(XY, "Y"))[npIndex,]), nprobes, narrays)

-      # new lines below - useful to keep track of zeroed out probes

-      zero = matrix(as.integer(exprs(channel(XY, "zero"))[npIndex,]), nprobes, narrays)

+     # new lines below - useful to keep track of zeroed out probes

+     zero = matrix(as.integer(exprs(channel(XY, "zero"))[npIndex,]), nprobes, narrays)

-      colnames(A) = colnames(B) = colnames(zero) = sns

-      rownames(A) = rownames(B) = rownames(zero) = names(npIndex)

+     colnames(A) = colnames(B) = colnames(zero) = sns

+     rownames(A) = rownames(B) = rownames(zero) = names(npIndex)

-      cnAB = list(A=A, B=B, zero=zero, sns=sns, gns=names(npIndex), cdfName=cdfName)

+     cnAB = list(A=A, B=B, zero=zero, sns=sns, gns=names(npIndex), cdfName=cdfName)

 #      t0 <- proc.time()

 #      save(cnAB, file=cnFile)

 #      t0 <- proc.time()-t0

 #      if(verbose) message("Used ", round(t0[3],1), " seconds to save ", cnFile, ".")

-       rm(A, B, zero)

-      if(is.lds) {

-        close(XY@assayData$X)

-        close(XY@assayData$Y)

-        close(XY@assayData$zero)

-      }

-    }

-#  }

+     rm(A, B, zero)

+#    }

+  }

   # next process snp probes

   snpIndex = getVarInEnv("snpProbesFid")

@@ -658,9 +616,9 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5,

   ##We will read each cel file, summarize, and run EM one by one

   ##We will save parameters of EM to use later

-  mixtureParams = initializeBigMatrix("crlmmMixt-", 4, narrays, "double")

-  SNR = initializeBigVector("crlmmSNR-", narrays, "double")

-  SKW = initializeBigVector("crlmmSKW-", narrays, "double")

+  mixtureParams = matrix(NA, 4, narrays)

+  SNR = rep(NA, narrays)

+  SKW = rep(NA, narrays)

   ## This is the sample for the fitting of splines

   ## BC: I like better the idea of the user passing the seed,

@@ -674,21 +632,15 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5,

   ##NOTE: We actually dont need to save S. Only for pics etc...

   ##f is the correction. we save to avoid recomputing

-  A = initializeBigMatrix("crlmmA-", nprobes, narrays, "integer")

-  B = initializeBigMatrix("crlmmB-", nprobes, narrays, "integer")

-  zero = initializeBigMatrix("crlmmZero-", nprobes, narrays, "integer")

+  A = matrix(NA, nprobes, narrays)

+  B = matrix(NA, nprobes, narrays)

+  zero = matrix(NA, nprobes, narrays)

   if(verbose){

      message("Calibrating ", narrays, " arrays.")

      if (getRversion() > '2.7.0') pb = txtProgressBar(min=0, max=narrays, style=3)

   }

-  if(is.lds) {

-    open(XY@assayData$X)

-    open(XY@assayData$Y)

-    open(XY@assayData$zero)

-  }

-

   for(i in 1:narrays){

      A[,i] = as.integer(exprs(channel(XY, "X"))[snpIndex,i])

      B[,i] = as.integer(exprs(channel(XY, "Y"))[snpIndex,i])

@@ -722,17 +674,6 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5,

 #    t0 <- proc.time()-t0

 #    if(verbose) message("Used ", round(t0[3],1), " seconds to save ", snpFile, ".")

 #  }

-  if(is.lds) {

-    close(XY@assayData$X)

-    close(XY@assayData$Y)

-    close(XY@assayData$zero)

-    close(A)

-    close(B)

-    close(zero)

-    close(SKW)

-    close(mixtureParams)

-    close(SNR)

-  }

   res = list(A=A, B=B,

              zero=zero, sns=sns, gns=names(snpIndex), SNR=SNR, SKW=SKW,

@@ -790,14 +731,15 @@ crlmmIllumina = function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

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

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

-    is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

+#    is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

+     is.lds=FALSE

-    if(is.lds) {

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

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

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

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

-    }

+#    if(is.lds) {

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

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

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

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

+#    }

 #    fD = featureData(XY)

 #    phenD = XY@phenoData

@@ -915,7 +857,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 			  saveDate=FALSE,

 			  stripNorm=TRUE,

 			  useTarget=TRUE,

-                          outdir=".",

+ #                         outdir=".",

 			  row.names=TRUE,

 			  col.names=TRUE,

 			  probs=c(1/3, 1/3, 1/3), DF=6, SNRMin=5, gender=NULL,

@@ -927,30 +869,30 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

     if(missing(cdfName)) stop("must specify cdfName")

     if(!isValidCdfName(cdfName)) stop("cdfName not valid.  see validCdfNames")

-    is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

-

+#    is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

+    is.lds=FALSE

     RG = readIdatFiles(sampleSheet=sampleSheet, arrayNames=arrayNames,

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

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

     XY = RGtoXY(RG, chipType=cdfName)

-    if(is.lds) {

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

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

-    }

+#    if(is.lds) {

+#      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)) { sns = sampleNames(XY)

     }

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

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

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

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

-    if(is.lds) {

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

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

-    }

+#    if(is.lds) {

+#      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(row.names) row.names=res$gns else row.names=NULL

@@ -981,9 +923,9 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

                      returnParams=returnParams,

                      badSNP=badSNP)

-    if(is.lds) {

-      open(res[["SNR"]]); open(res[["SKW"]])

-    }

+#    if(is.lds) {

+#      open(res[["SNR"]]); open(res[["SKW"]])

+#    }

     res2[["SNR"]] = res[["SNR"]]

     res2[["SKW"]] = res[["SKW"]]

  #  if(is.lds) {

@@ -995,7 +937,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 }

 # Functions analogous to Rob's Affy functions to set up container

-getProtocolData.Illumina = function(filenames, sep="_", fileExt="Grn.idat") {

+getProtocolData.Illumina = function(filenames, sep="_", fileExt="Grn.idat", verbose=FALSE) {

        narrays = length(filenames)

        headerInfo = list(nProbes = rep(NA, narrays),

@@ -1008,7 +950,8 @@ getProtocolData.Illumina = function(filenames, sep="_", fileExt="Grn.idat") {

        rownames(scanDates) = gsub(paste(sep, fileExt, sep=""), "", filenames)

        ## read in the data

        for(i in seq_along(filenames)) {

-	       cat("reading", filenames[i], "\n")

+               if(verbose)

+	               cat("reading", filenames[i], "\n")

 	       idsG = G = NULL

 	       G = readIDAT(filenames[i])

 	       idsG = rownames(G$Quants)

@@ -1043,10 +986,10 @@ construct.Illumina = function(sampleSheet=NULL,

 			  sep="_",

 			  fileExt=list(green="Grn.idat",

 			  red="Red.idat"),

-		      	  cdfName,

-		      	  copynumber=TRUE,

-		      	  verbose=TRUE, batch, #fns,

-                          saveDate=TRUE, outdir="."){

+		      cdfName,

+			  copynumber=TRUE,

+			  verbose=FALSE, batch, #fns,

+			  saveDate=TRUE) { #, outdir="."){

        if(!is.null(arrayNames)) {

                pd = new("AnnotatedDataFrame", data = data.frame(Sample_ID=arrayNames))

        }

@@ -1115,7 +1058,7 @@ construct.Illumina = function(sampleSheet=NULL,

 #		featureData = featureData[index, ]

 #	}

 	nr = nrow(featureData); nc = narrays

-        ldPath(outdir)

+#        ldPath(outdir)

 	cnSet = new("CNSet",

 		     alleleA=initializeBigMatrix(name="A", nr, nc),

 		     alleleB=initializeBigMatrix(name="B", nr, nc),

@@ -1129,7 +1072,7 @@ construct.Illumina = function(sampleSheet=NULL,

         else sampleNames(cnSet) = arrayNames

 	if(saveDate){

-		protocolData = getProtocolData.Illumina(grnidats, sep=sep, fileExt=fileExt$green)

+		protocolData = getProtocolData.Illumina(grnidats, sep=sep, fileExt=fileExt$green, verbose=verbose)

 	} else{

 		protocolData = annotatedDataFrameFrom(A(cnSet), byrow=FALSE)

 	}

@@ -1151,51 +1094,52 @@ genotype.Illumina = function(sampleSheet=NULL,

 			  arrayInfoColNames=list(barcode="SentrixBarcode_A", position="SentrixPosition_A"),

 			  highDensity=FALSE,

 			  sep="_",

-			  fileExt=list(green="Grn.idat",

-			  red="Red.idat"),

-		      	  cdfName,

-		      	  copynumber=TRUE,

-                          batch,

-                          outdir=".",

+			  fileExt=list(green="Grn.idat", red="Red.idat"),

+			  cdfName,

+			  copynumber=TRUE,

+			  batch,

+#                          outdir=".",

 #                          fns,

-                          saveDate=TRUE,

-       			  stripNorm=TRUE,

+              saveDate=TRUE,

+			  stripNorm=TRUE,

 			  useTarget=TRUE,

-		          mixtureSampleSize=10^5,

-                          fitMixture=TRUE,

-		          eps=0.1,

-		          verbose=TRUE,

-		          seed=1,

-		          sns,

-		          probs=rep(1/3, 3),

-		          DF=6,

-		          SNRMin=5,

-		          recallMin=10,

-		          recallRegMin=1000,

-		          gender=NULL,

-		          returnParams=TRUE,

-		          badSNP=0.7) {

+		      mixtureSampleSize=10^5,

+              fitMixture=TRUE,

+		      eps=0.1,

+		      verbose=TRUE,

+		      seed=1,

+		      sns,

+		      probs=rep(1/3, 3),

+		      DF=6,

+		      SNRMin=5,

+		      recallMin=10,

+		      recallRegMin=1000,

+		      gender=NULL,

+		      returnParams=TRUE,

+		      badSNP=0.7) {

 	is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

 	if(missing(cdfName)) stop("must specify cdfName")

 	if(!isValidCdfName(cdfName)) stop("cdfName not valid.  see validCdfNames")

         pkgname = getCrlmmAnnotationName(cdfName)

-        if(missing(outdir))

-          stop("Must specify a directory to store large data objects")

+#        if(missing(outdir))

+#          stop("Must specify a directory to store large data objects")

 	callSet = construct.Illumina(sampleSheet=sampleSheet, arrayNames=arrayNames,

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

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

                              highDensity=highDensity, sep=sep, fileExt=fileExt,

-			     cdfName=cdfName, copynumber=copynumber, verbose=verbose, batch=batch, # fns=fns, 

-                             saveDate=saveDate, outdir=outdir)

-        if(missing(sns)) sns = sampleNames(callSet)

-        

-        open(A(callSet))

-        open(B(callSet))

-        # open(callSet)

+			                 cdfName=cdfName, copynumber=copynumber, verbose=verbose, batch=batch, # fns=fns, 

+                             saveDate=saveDate) #, outdir=outdir)

+	if(missing(sns)) sns = sampleNames(callSet)

+    

+    if(is.lds) {

+		open(A(callSet))

+		open(B(callSet))

+	# open(callSet)

+	}

  	is.snp = isSnp(callSet)

 	snp.index = which(is.snp)

-        narrays = ncol(callSet)

-        if(is.lds) {

-          sampleBatches = splitIndicesByNode(seq(along=sampleNames(callSet)))

+	narrays = ncol(callSet)

+	if(is.lds) {

+          sampleBatches = splitIndicesByLength(seq(along=sampleNames(callSet)), ocSamples())

           mixtureParams = initializeBigMatrix("crlmmMixt-", 4, narrays, "double")

           SNR = initializeBigVector("crlmmSNR-", narrays, "double")

@@ -1206,7 +1150,7 @@ genotype.Illumina = function(sampleSheet=NULL,

                  sep=sep, fileExt=fileExt, saveDate=saveDate, verbose=verbose, mixtureSampleSize=mixtureSampleSize,

                  fitMixture=fitMixture, eps=eps, seed=seed, cdfName=cdfName, sns=sns, stripNorm=stripNorm,

                  useTarget=useTarget, A=A(callSet), B=B(callSet), SKW=SKW, SNR=SNR,

-                 mixtureParams=mixtureParams, is.snp=is.snp, outdir=outdir, neededPkgs=c("crlmm", pkgname))

+                 mixtureParams=mixtureParams, is.snp=is.snp, neededPkgs=c("crlmm", pkgname)) # outdir=outdir, 

           open(SKW)

           open(SNR)

@@ -1214,7 +1158,7 @@ genotype.Illumina = function(sampleSheet=NULL,

           pData(callSet)$SNR = SNR

           close(SNR)

           close(SKW)

-        } else {

+	} else {

           mixtureParams = matrix(NA, 4, nrow(callSet))

           RG = readIdatFiles(sampleSheet=sampleSheet, arrayNames=arrayNames,

@@ -1225,23 +1169,21 @@ genotype.Illumina = function(sampleSheet=NULL,

           rm(RG); gc()

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

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

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

           rm(XY); gc()

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

           np.index = which(!is.snp)

           A(callSet)[snp.index, ] = res[["A"]]

           B(callSet)[snp.index, ] = res[["B"]]

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

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

         	A(callSet)[np.index, ] = res[["cnAB"]]$A

         	B(callSet)[np.index, ] = res[["cnAB"]]$B

-        	}

           }

-	  SKW = pData(callSet)$SKW = res[["SKW"]]

-	  SNR = pData(callSet)$SNR = res[["SNR"]]

-	  mixtureParams = res[["mixtureParams"]]

-          rm(res)

-        }

+		  SKW = pData(callSet)$SKW = res[["SKW"]]

+		  SNR = pData(callSet)$SNR = res[["SNR"]]

+		  mixtureParams = res[["mixtureParams"]]

+		  rm(res)

+	}

 	FUN = ifelse(is.lds, "crlmmGT2", "crlmmGT")

 	## genotyping

@@ -1251,22 +1193,23 @@ genotype.Illumina = function(sampleSheet=NULL,

 		       crlmmGT=crlmmGT(...))

 	}

-        if(is.lds) {

+	if(is.lds) {

           open(A(callSet))

           open(B(callSet))

           tmpA = initializeBigMatrix(name="A", length(snp.index), narrays)

-          tmpB = initializeBigMatrix(name="B", length(snp.index), narrays)

-          bb = ocProbesets()*length(sns)*8

-	  ffrowapply(tmpA[i1:i2, ] <- A(callSet)[snp.index,][i1:i2, ], X=A(callSet)[snp.index,], BATCHBYTES=bb)

-	  ffrowapply(tmpB[i1:i2, ] <- B(callSet)[snp.index,][i1:i2, ], X=B(callSet)[snp.index,], BATCHBYTES=bb)

+          tmpB = initializeBigMatrix(name="B", length(snp.index), narrays) 

+#          bb = getOption("ffbatchbytes")          

+#          bb = ocProbesets()*length(sns)*8

+		  ffcolapply(tmpA[,i1:i2] <- A(callSet)[snp.index,i1:i2], X=A(callSet)) #, BATCHBYTES=bb) # X=A(callSet)[snp.index,]

+		  ffcolapply(tmpB[,i1:i2] <- B(callSet)[snp.index,i1:i2], X=B(callSet)) #, BATCHBYTES=bb) # X=B(callSet)[snp.index,]

           close(A(callSet))

           close(B(callSet))

           close(tmpA)

           close(tmpB)

-        } else {

+	} else {

           tmpA = A(callSet)[snp.index,]

           tmpB = B(callSet)[snp.index,]

-        }

+	}

 	tmp = crlmmGTfxn(FUN,

 			  A=tmpA,

@@ -1287,24 +1230,24 @@ genotype.Illumina = function(sampleSheet=NULL,

 			  badSNP=badSNP)

 	if(verbose) message("Genotyping finished.  Updating container with genotype calls and confidence scores.")

 	if(is.lds){

-		bb = ocProbesets()*ncol(callSet)*8

+#       bb = getOption("ffbatchbytes") # ocProbesets()*ncol(callSet)*8

 		open(tmp[["calls"]])

 		open(tmp[["confs"]])

-		ffrowapply(snpCall(callSet)[snp.index,][i1:i2, ] <- tmp[["calls"]][i1:i2, ], X=tmp[["calls"]], BATCHBYTES=bb)

-		ffrowapply(snpCallProbability(callSet)[snp.index,][i1:i2, ] <- tmp[["confs"]][i1:i2, ], X=tmp[["confs"]], BATCHBYTES=bb)

+		ffcolapply(snpCall(callSet)[snp.index,i1:i2] <- tmp[["calls"]][,i1:i2], X=tmp[["calls"]]) #, BATCHBYTES=bb)

+		ffcolapply(snpCallProbability(callSet)[snp.index,i1:i2] <- tmp[["confs"]][,i1:i2], X=tmp[["confs"]]) #, BATCHBYTES=bb)

 #		close(tmp[["calls"]])

 #		close(tmp[["confs"]])

-#                open(tmpA); open(tmpB)

-#                delete(tmpA); delete(tmpB);

-                delete(tmp[["calls"]]); delete(tmp[["confs"]])

-                rm(tmpA, tmpB)

+		open(tmpA); open(tmpB)

+		delete(tmpA); delete(tmpB);

+	    delete(tmp[["calls"]]); delete(tmp[["confs"]])

+		rm(tmpA, tmpB)

 	} else {

 		calls(callSet)[snp.index, ] = tmp[["calls"]]

 		snpCallProbability(callSet)[snp.index, ] = tmp[["confs"]]

-                rm(tmpA, tmpB)

+		rm(tmpA, tmpB)

 	}

 	callSet$gender = tmp$gender

-        rm(tmp)

+	rm(tmp)

 	close(callSet)

 	return(callSet)

 }

@@ -1319,8 +1262,8 @@ processIDAT =  function(sel, sampleSheet=NULL,

 			  sep="_",

 			  fileExt=list(green="Grn.idat", red="Red.idat"),

 			  saveDate=FALSE,

-                          verbose=TRUE,

-                          mixtureSampleSize=10^5,

+			  verbose=TRUE,

+              mixtureSampleSize=10^5,

 			  fitMixture=TRUE,

 			  eps=0.1,

 			  seed=1,

@@ -1328,53 +1271,61 @@ processIDAT =  function(sel, sampleSheet=NULL,

 			  sns,

 			  stripNorm=TRUE,

 			  useTarget=TRUE,

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

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

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

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

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

-                       highDensity=highDensity, sep=sep, fileExt=fileExt, saveDate=saveDate)

+                       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)

+#        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)

         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)

+                               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"]])

-	bb = ocProbesets()*length(sns)*8

-        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)) {

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

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

-          }

+	    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

+        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)) {

+			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]

+#          }

         }

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

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

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

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

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

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

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

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

         close(A)

         close(B)

         close(SNR)

         close(SKW)

         close(mixtureParams)

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

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

         rm(res)

+		gc()

         TRUE

-      }

+      }

\ No newline at end of file

@@ -10,7 +10,7 @@

 crlmmIlluminaV2(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

       arrayInfoColNames=list(barcode="SentrixBarcode_A", position="SentrixPosition_A"),

       highDensity=FALSE, sep="_", fileExt=list(green="Grn.idat", red="Red.idat"),

-      saveDate=FALSE, stripNorm=TRUE, useTarget=TRUE, outdir=".", 

+      saveDate=FALSE, stripNorm=TRUE, useTarget=TRUE,  

       row.names=TRUE, col.names=TRUE, probs=c(1/3, 1/3, 1/3), 

       DF=6, SNRMin=5, gender=NULL, seed=1, mixtureSampleSize=10^5, 

       eps=0.1, verbose=TRUE, cdfName, sns, recallMin=10, 

@@ -47,8 +47,6 @@ crlmmIlluminaV2(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   \item{stripNorm}{'logical'.  Should the data be strip-level normalized?}

   \item{useTarget}{'logical' (only used when \code{stripNorm=TRUE}).

     Should the reference HapMap intensities be used in strip-level normalization?}

-  \item{outdir}{character string specifying the location to store large data objects 

-    (used when \code{ff} package is loaded)}

   \item{row.names}{'logical'. Use rownames - SNP names?}

   \item{col.names}{'logical'. Use colnames - Sample names?}

   \item{probs}{'numeric' vector with priors for AA, AB and BB.}

@@ -11,7 +11,7 @@

 genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

       arrayInfoColNames=list(barcode="SentrixBarcode_A", position="SentrixPosition_A"),

       highDensity=FALSE, sep="_", fileExt=list(green="Grn.idat", red="Red.idat"),

-      cdfName, copynumber=TRUE, batch, outdir=".", saveDate=TRUE, stripNorm=TRUE, useTarget=TRUE, 

+      cdfName, copynumber=TRUE, batch, saveDate=TRUE, stripNorm=TRUE, useTarget=TRUE, 

       mixtureSampleSize=10^5, fitMixture=TRUE, eps =0.1, verbose = TRUE, seed = 1, 

       sns, probs = rep(1/3, 3), DF = 6, SNRMin = 5, recallMin = 10, recallRegMin = 1000,

       gender = NULL, returnParams = TRUE, badSNP = 0.7)

@@ -43,8 +43,7 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

     specify the .idat file extension for the Cy3 and Cy5 channels.}

   \item{cdfName}{ annotation package  (see also \code{validCdfNames})}

   \item{copynumber}{ 'logical.' Whether to store copy number intensities with SNP output.} 

-  \item{batch}{ batch variable. See details. }

-  \item{outdir}{character string specifying the location to store large data objects.}

+  \item{batch}{ batch variable. See details.}

   \item{saveDate}{'logical'.  Should the dates from each .idat be saved

     with sample information?}

   \item{stripNorm}{'logical'.  Should the data be strip-level normalized?}

@@ -14,7 +14,7 @@ readIdatFiles(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path="",

                                      position="SentrixPosition_A"),

               highDensity=FALSE, sep="_",

               fileExt=list(green="Grn.idat", red="Red.idat"),

-              saveDate=FALSE)

+              saveDate=FALSE, verbose=FALSE)

 }

 \arguments{

@@ -44,6 +44,7 @@ readIdatFiles(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path="",

     specify the .idat file extension for the Cy3 and Cy5 channels.}

   \item{saveDate}{logical.  Should the dates from each .idat be saved

     with sample information?}

+  \item{verbose}{logical.  Should processing information be displayed as data is read in?}

 }

 \details{