@@ -1243,153 +1243,8 @@ construct.Illumina <- function(sampleSheet=NULL,

 	return(cnSet)

 }

-genotype.Illumina <- function(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,

-                          fns,

-                          saveDate=TRUE,

-       			  stripNorm=TRUE,

-			  useTarget=TRUE,

-		          mixtureSampleSize=10^5,

-		          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")

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

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

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

-			     cdfName=cdfName, copynumber=copynumber, verbose=verbose, batch=batch,

-                             fns=fns, saveDate=saveDate)

-	open(callSet)

-	mixtureParams <- matrix(NA, 4, nrow(callSet))

-	is.snp <- isSnp(callSet)

-	snp.index <- which(is.snp)

-

-        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)

-        rm(RG); gc()

-        if (missing(sns)) { sns = sampleNames(XY) #subsns = sampleNames(XY)

-        } # else subsns = sns[j]

-        

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

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

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

-        rm(XY); gc()

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

-	np.index <- which(!is.snp)        

-	if(is.lds){

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

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

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

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

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

-		ffrowapply(A(callSet)[i1:i2, ] <- res[["A"]][i1:i2, ], X=res[["A"]], BATCHBYTES=bb)

-		ffrowapply(B(callSet)[i1:i2, ] <- res[["B"]][i1:i2, ], X=res[["B"]], BATCHBYTES=bb)

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

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

-        			A(callSet)[np.index, j] <- res[["cnAB"]]$A[,j]

-        			B(callSet)[np.index, j] <- res[["cnAB"]]$B[,j]

-        		}

-                }        

-                

-	} else{

-		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

-        		}

-                }

-	}

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

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

-	mixtureParams <- res[["mixtureParams"]]

-

-#	if(verbose) message("Normalizing nonpolymorphic markers")

-#	FUN <- ifelse(is.lds, "cnrma2", "cnrma")

-	## main purpose is to update 'alleleA'

-#	cnrmaFxn <- function(FUN,...){

-#		switch(FUN,

-#		       cnrma=cnrma(...),

-#		       cnrma2=cnrma2(...))

-#	}

-	## consider passing only A for NPs.

-#	AA <- cnrmaFxn(FUN, A=A(callSet),

-#		       filenames=filenames,

-#		       row.names=featureNames(callSet)[np.index],

-#		       cdfName=cdfName,

-#		       sns=sns,

-#		       seed=seed,

-#		       verbose=verbose)

-#	if(!is.lds) A(callSet) <- AA

-#	rm(AA)

-	FUN <- ifelse(is.lds, "crlmmGT2", "crlmmGT")

-	## genotyping

-	crlmmGTfxn <- function(FUN,...){

-		switch(FUN,

-		       crlmmGT2=crlmmGT2(...),

-		       crlmmGT=crlmmGT(...))

-	}

-	tmp <- crlmmGTfxn(FUN,

-			  A=res[["A"]],

-			  B=res[["B"]],

-			  SNR=res[["SNR"]],

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

-			  cdfName=cdfName,

-			  row.names=NULL,

-			  col.names=sampleNames(callSet),

-			  probs=probs,

-			  DF=DF,

-			  SNRMin=SNRMin,

-			  recallMin=recallMin,

-			  recallRegMin=recallRegMin,

-			  gender=gender,

-			  verbose=verbose,

-			  returnParams=returnParams,

-			  badSNP=badSNP)

-        rm(res); gc()

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

-	if(is.lds){

-		open(tmp[["calls"]])

-		open(tmp[["confs"]])

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

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

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

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

-	} else {

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

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

-	}

-	callSet$gender <- tmp$gender

-	close(callSet)

-	return(callSet)

-}

-genotype.Illumina2 <- function(sampleSheet=NULL,

+genotype.Illumina <- function(sampleSheet=NULL,

 			  arrayNames=NULL,

 			  ids=NULL,

 			  path=".",