@@ -541,4 +541,9 @@ function (which expects ff objects and supports parallel processing)

 ** added omni express 12 as one of the chip options for Illumina.  Also added a check for copy number probes (this chip doesn't have any).

 2010-07-30 R. Scharpf 1.7.8

-** edited construct function for CNSetLM

\ No newline at end of file

+** edited construct function for CNSetLM

+

+2010-08-25 M. Ritchie 1.7.12

+** Renamed functions readIdatFiles2() -> readIdatFiles(), RGtoXY2() -> RGtoXY(), preprocessInfinium2v2() -> preprocessInfinium2(), crlmmIllumina2() -> crlmmIllumina().  These make use of ff objects to store data.

+** Exported crlmmIlluminaV2(), which combines reading in of idats and genotyping in one.  Also added a man page for this function

+** tidied up crlmm-illumina.R, removing commented out code.

\ No newline at end of file

@@ -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: 1.7.11

-Date: 2010-07-30

+Version: 1.7.12

+Date: 2010-08-25

 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

@@ -63,11 +63,10 @@ exportMethods(lines)

 exportMethods(CA, CB)

 export(crlmm,

        crlmmIllumina,

-       crlmmIllumina2,

+       crlmmIlluminaV2,

        ellipseCenters,

        genotype,

        readIdatFiles,

-       readIdatFiles2,

        snprma,

        snprma2,

        crlmm2,

@@ -12,193 +12,12 @@ readIdatFiles <- function(sampleSheet=NULL,

 			  sep="_",

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

 			  saveDate=FALSE) {

-#       if(!is.null(arrayNames)) {

-#	       arrayNames = gsub(paste(sep, fileExt$green, sep=""), "", dir(pattern=fileExt$green, path=path))

-#	       if(!is.null(sampleSheet)) {

-#		       sampleSheet=NULL

-#		       cat("Could not find required info in \'sampleSheet\' - ignoring.  Check \'sampleSheet\' and/or \'arrayInfoColNames\'\n")

-#	       }

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

-#       }

-       if(!is.null(arrayNames)) {

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

-       }

-       if(!is.null(sampleSheet)) { # get array info from Illumina's sample sheet

-	       if(is.null(arrayNames)){

-		       ##arrayNames=NULL

-		       if(!is.null(arrayInfoColNames$barcode) && (arrayInfoColNames$barcode %in% colnames(sampleSheet))) {

-			       barcode = sampleSheet[,arrayInfoColNames$barcode]

-			       arrayNames=barcode

-		       }

-		       if(!is.null(arrayInfoColNames$position) && (arrayInfoColNames$position %in% colnames(sampleSheet))) {  

-			       position = sampleSheet[,arrayInfoColNames$position]

-			       if(is.null(arrayNames))

-				       arrayNames=position

-			       else

-				       arrayNames = paste(arrayNames, position, sep=sep)

-			       if(highDensity) {

-				       hdExt = list(A="R01C01", B="R01C02", C="R02C01", D="R02C02")

-				       for(i in names(hdExt))

-					       arrayNames = sub(paste(sep, i, sep=""), paste(sep, hdExt[[i]], sep=""), arrayNames)

-			       }

-		       }

-	       }

-	       pd = new("AnnotatedDataFrame", data = sampleSheet)

-	       sampleNames(pd) <- basename(arrayNames)               

-       }

-       if(is.null(arrayNames)) {

-               arrayNames = gsub(paste(sep, fileExt$green, sep=""), "", dir(pattern=fileExt$green, path=path))

-               if(!is.null(sampleSheet)) {

-                      sampleSheet=NULL

-                      cat("Could not find required info in \'sampleSheet\' - ignoring.  Check \'sampleSheet\' and/or \'arrayInfoColNames\'\n")

-               }

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

-       }

-       narrays = length(arrayNames)

-       grnfiles = paste(arrayNames, fileExt$green, sep=sep)

-       redfiles = paste(arrayNames, fileExt$red, sep=sep)

-       if(length(grnfiles)==0 || length(redfiles)==0)

-	       stop("Cannot find .idat files")

-       if(length(grnfiles)!=length(redfiles))

-	       stop("Cannot find matching .idat files")

-       if(path[1] != "."){

-	       grnidats = file.path(path, grnfiles)

-	       redidats = file.path(path, redfiles)

-       }  else {

-	       message("path arg not set.  Assuming files are in local directory")

-	       grnidats <- grnfiles

-	       redidats <- redfiles

-       }

-       if(!all(file.exists(grnidats))) stop("Missing some of the *Grn.idat files")

-       if(!all(file.exists(redidats))) stop("Missing some of the *Red.idat files")       

-##       if(!all(c(redfiles,grnfiles) %in% dir(path=path))){

-##	       stop("Missing .idat files: red\n", paste(redfiles[!(redfiles %in% dir(path=path))], sep=" "), "\n green\n",

-##		    paste(grnfiles[!(grnfiles %in% dir(path=path))], sep=" "))

-##       }

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

-                         Barcode = rep(NA, narrays),

-                         ChipType = rep(NA, narrays),

-                         Manifest = rep(NA, narrays), # not sure about this one - sometimes blank

-                         Position = rep(NA, narrays)) # this may also vary a bit

-       dates = list(decode=rep(NA, narrays),

-                    scan=rep(NA, narrays))

-       ## read in the data

-       for(i in seq(along=arrayNames)) {

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

-	       headerInfo$Barcode[i] = G$Barcode

-	       headerInfo$ChipType[i] = G$ChipType

-	       headerInfo$Manifest[i] = G$Unknown$MostlyNull

-	       headerInfo$Position[i] = G$Unknowns$MostlyA

-               if(headerInfo$nProbes[i]>(headerInfo$nProbes[1]+10000) || headerInfo$nProbes[i]<(headerInfo$nProbes[1]-10000)) {

-                       ## headerInfo$ChipType[i]!=headerInfo$ChipType[1] || headerInfo$Manifest[i]!=headerInfo$Manifest[1]) {

-		       ## || headerInfo$nProbes[i]!=headerInfo$nProbes[1] ## removed this condition as some arrays used the same manifest

-		       ## but differed by a few SNPs for some reason - most of the chip was the same though

-		       ##           stop("Chips are not of all of the same type - please check your data")

-		       warning("Chips are not of the same type.  Skipping ", basename(grnidats[i]), " and ", basename(redidats[i]))

-		       next()

-	       }

-	       dates$decode[i] = G$RunInfo[1, 1]

-	       dates$scan[i] = G$RunInfo[2, 1]

-	       if(i==1) {

-		       if(is.null(ids) && !is.null(G)){

-			       ids = idsG

-		       }else stop("Could not find probe IDs")

-		       nprobes = length(ids)

-		       narrays = length(arrayNames)

-		       tmpmat = matrix(NA, nprobes, narrays)

-		       rownames(tmpmat) = ids

-		       if(!is.null(sampleSheet)){

-			       colnames(tmpmat) = sampleSheet$Sample_ID

-		       }else  colnames(tmpmat) = arrayNames

-		       RG <- new("NChannelSet",

-				 R=tmpmat,

-				 G=tmpmat,

-				 zero=tmpmat,

-#				 Rnb=tmpmat,

-#				 Gnb=tmpmat,

-#				 Rse=tmpmat,

-#				 Gse=tmpmat,

-				 annotation=headerInfo$Manifest[1],

-				 phenoData=pd,

-				 storage.mode="environment")

-		       rm(tmpmat)

-		       gc()

-	       }

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

-		       if(sum(ids==idsG)==nprobes) {

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

-				   zeroG = G$Quants[, "NBeads"]==0

-#			       RG@assayData$Gnb[,i] = G$Quants[, "NBeads"]

-#			       RG@assayData$Gse[,i] = G$Quants[, "SD"]

-		       }

-	       } else {

-		       indG = match(ids, idsG)

-		       RG@assayData$G[,i] = G$Quants[indG, "Mean"]

-			   zeroG = G$Quants[indG, "NBeads"]==0

-#		       RG@assayData$Gnb[,i] = G$Quants[indG, "NBeads"]

-#		       RG@assayData$Gse[,i] = G$Quants[indG, "SD"]

-	       }

-	       rm(G)

-	       gc()

-         

-	       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

-#			       RG@assayData$Rnb[,i] = R$Quants[ ,"NBeads"]

-#			       RG@assayData$Rse[,i] = R$Quants[ ,"SD"]

-		       }

-	       } else {

-		       indR = match(ids, idsR)

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

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

-#		       RG@assayData$Rnb[,i] = R$Quants[indR, "NBeads"]

-#		       RG@assayData$Rse[,i] = R$Quants[indR, "SD"]

-	       }

-		   RG@assayData$zero[,i] = zeroG | zeroR

-	       rm(R, zeroG, zeroR)

-	       gc()

-       }

-       if(saveDate) {

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

-       }

-       storageMode(RG) = "lockedEnvironment"

-       RG

-}

-

-

-readIdatFiles2 <- 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"),

-			  saveDate=FALSE) {

-#       if(!is.null(arrayNames)) {

-#	       arrayNames = gsub(paste(sep, fileExt$green, sep=""), "", dir(pattern=fileExt$green, path=path))

-#	       if(!is.null(sampleSheet)) {

-#		       sampleSheet=NULL

-#		       cat("Could not find required info in \'sampleSheet\' - ignoring.  Check \'sampleSheet\' and/or \'arrayInfoColNames\'\n")

-#	       }

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

-#       }

+			  

        if(!is.null(arrayNames)) {

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

        }

        if(!is.null(sampleSheet)) { # get array info from Illumina's sample sheet

 	       if(is.null(arrayNames)){

-		       ##arrayNames=NULL

 		       if(!is.null(arrayInfoColNames$barcode) && (arrayInfoColNames$barcode %in% colnames(sampleSheet))) {

 			       barcode = sampleSheet[,arrayInfoColNames$barcode]

 			       arrayNames=barcode

@@ -245,10 +64,6 @@ readIdatFiles2 <- function(sampleSheet=NULL,

        }

        if(!all(file.exists(grnidats))) stop("Missing some of the *Grn.idat files")

        if(!all(file.exists(redidats))) stop("Missing some of the *Red.idat files")       

-##       if(!all(c(redfiles,grnfiles) %in% dir(path=path))){

-##	       stop("Missing .idat files: red\n", paste(redfiles[!(redfiles %in% dir(path=path))], sep=" "), "\n green\n",

-##		    paste(grnfiles[!(grnfiles %in% dir(path=path))], sep=" "))

-##       }

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

                          Barcode = rep(NA, narrays),

                          ChipType = rep(NA, narrays),

@@ -268,11 +83,7 @@ readIdatFiles2 <- function(sampleSheet=NULL,

 	       headerInfo$ChipType[i] = G$ChipType

 	       headerInfo$Manifest[i] = G$Unknown$MostlyNull

 	       headerInfo$Position[i] = G$Unknowns$MostlyA

-               if(headerInfo$nProbes[i]>(headerInfo$nProbes[1]+10000) || headerInfo$nProbes[i]<(headerInfo$nProbes[1]-10000)) {

-                       ## headerInfo$ChipType[i]!=headerInfo$ChipType[1] || headerInfo$Manifest[i]!=headerInfo$Manifest[1]) {

-		       ## || headerInfo$nProbes[i]!=headerInfo$nProbes[1] ## removed this condition as some arrays used the same manifest

-		       ## but differed by a few SNPs for some reason - most of the chip was the same though

-		       ##           stop("Chips are not of all of the same type - please check your data")

+           if(headerInfo$nProbes[i]>(headerInfo$nProbes[1]+10000) || headerInfo$nProbes[i]<(headerInfo$nProbes[1]-10000)) {

 		       warning("Chips are not of the same type.  Skipping ", basename(grnidats[i]), " and ", basename(redidats[i]))

 		       next()

 	       }

@@ -284,27 +95,13 @@ readIdatFiles2 <- function(sampleSheet=NULL,

 		       } else stop("Could not find probe IDs")

 		       nprobes = length(ids)

 		       narrays = length(arrayNames)

-#		        tmpmat = matrix(NA, nprobes, narrays)

-#		        rownames(tmpmat) = ids

-#		       fD <- new("AnnotatedDataFrame", data=data.frame(row.names=ids))##, varMetadata=data.frame(labelDescript

 		       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"),

-#		                 featureData=fD,

-#		                 annotation=cdfName)

-#				 R=tmpmat,

-#				 G=tmpmat,

-#				 zero=tmpmat,

-#				 Rnb=tmpmat,

-#				 Gnb=tmpmat,

-#				 Rse=tmpmat,

-#				 Gse=tmpmat,

-				 annotation=headerInfo$Manifest[1],

-				 phenoData=pd,

-				 storage.mode="environment")

-                       featureNames(RG) = ids

-#		       rm(tmpmat)

+				         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

@@ -314,15 +111,11 @@ readIdatFiles2 <- function(sampleSheet=NULL,

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

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

 			       zeroG = G$Quants[, "NBeads"]==0

-#			       RG@assayData$Gnb[,i] = G$Quants[, "NBeads"]

-#			       RG@assayData$Gse[,i] = G$Quants[, "SD"]

 		       }

 	       } else {

 		       indG = match(ids, idsG)

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

 		       zeroG = G$Quants[indG, "NBeads"]==0

-#		       RG@assayData$Gnb[,i] = G$Quants[indG, "NBeads"]

-#		       RG@assayData$Gse[,i] = G$Quants[indG, "SD"]

 	       }

 	       rm(G)

 	       gc()

@@ -334,16 +127,12 @@ readIdatFiles2 <- function(sampleSheet=NULL,

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

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

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

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

-#			       RG@assayData$Rnb[,i] = R$Quants[ ,"NBeads"]

-#			       RG@assayData$Rse[,i] = R$Quants[ ,"SD"]

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

 		       }

 	       } else {

 		       indR = match(ids, idsR)

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

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

-#		       RG@assayData$Rnb[,i] = R$Quants[indR, "NBeads"]

-#		       RG@assayData$Rse[,i] = R$Quants[indR, "SD"]

 	       }

 	       RG@assayData$zero[,i] = zeroG | zeroR

 	       rm(R, zeroG, zeroR)

@@ -615,114 +404,8 @@ readBPM <- function(bpmFile){

 }

-RGtoXY = function(RG, chipType, verbose=TRUE) {

-  chipList = c("human1mv1c",             # 1M

-               "human370v1c",            # 370CNV

-               "human650v3a",            # 650Y

-               "human610quadv1b",        # 610 quad

-               "human660quadv1a",        # 660 quad

-               "human370quadv3c",        # 370CNV quad

-               "human550v3b",            # 550K

-               "human1mduov3b",          # 1M Duo

-               "humanomni1quadv1b",      # Omni1 quad

-               "humanomniexpress12v1b") # Omni express 12

-  if(missing(chipType)){

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

-  } else chipType = match.arg(chipType, chipList)

-  

-  pkgname <- getCrlmmAnnotationName(chipType)

-  if(!require(pkgname, character.only=TRUE, quietly=!verbose)){

-     suggCall <- paste("library(", pkgname, ", lib.loc='/Altern/Lib/Loc')", sep="")

-     msg <- paste("If", pkgname, "is installed on an alternative location, please load it manually by using", suggCall)

-     message(strwrap(msg))

-     stop("Package ", pkgname, " could not be found.")

-     rm(suggCall, msg)

-  }

-  if(verbose) message("Loading chip annotation information.")

-    loader("address.rda", .crlmmPkgEnv, pkgname)

-#    data(annotation, package=pkgname, envir=.crlmmPkgEnv)

-  aids <- getVarInEnv("addressA") # comes from AddressA_ID or Address column in manifest

-  bids <- getVarInEnv("addressB") # comes from AddressB_ID or Address2 column in manifest

-  ids <- names(aids)

-  snpbase <- getVarInEnv("base")

-  

-  nsnps = length(aids)

-  narrays = ncol(RG)

-  

-#  aidcol = match("AddressA_ID", colnames(annot))

-#  if(is.na(aidcol))

-#    aidcol = match("Address", colnames(annot))

-#  bidcol = match("AddressB_ID", colnames(annot))

-#  if(is.na(bidcol)) 

-#    bidcol = match("Address2", colnames(annot))

-#  aids = annot[, aidcol]

-#  bids = annot[, bidcol]

-#  snpids = annot[,"Name"]

-#  snpbase = annot[,"SNP"] 

-  infI = !is.na(bids) & bids!=0  

-  aord = match(aids, featureNames(RG)) # NAs are possible here

-  bord = match(bids, featureNames(RG)) # and here

-#  argrg = aids[rrgg]

-#  brgrg = bids[rrgg]

-  tmpmat = matrix(as.integer(0), nsnps, narrays)

-  rownames(tmpmat) = ids

-  colnames(tmpmat) = sampleNames(RG)

-  XY = new("NChannelSet", X=tmpmat, Y=tmpmat, zero=tmpmat, # Xnb=tmpmat, Ynb=tmpmat, Xse=tmpmat, Yse=tmpmat, zero=tmpmat,

-                 annotation=chipType, phenoData=RG@phenoData, protocolData=RG@protocolData, storage.mode="environment")

-  rm(tmpmat)

-  gc()

-  

-  # 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

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

-#  XY@assayData$Xnb[!is.na(aord),] = exprs(channel(RG, "Rnb"))[aord[!is.na(aord)],]

-#  XY@assayData$Ynb[!is.na(aord),] = exprs(channel(RG, "Gnb"))[aord[!is.na(aord)],]

-#  XY@assayData$Xse[!is.na(aord),] = exprs(channel(RG, "Rse"))[aord[!is.na(aord)],]

-#  XY@assayData$Yse[!is.na(aord),] = exprs(channel(RG, "Gse"))[aord[!is.na(aord)],]

-  gc()

-  

-  ## Warning - not 100% sure that the code below is correct - could be more complicated than this

-  

-  # Next Infinium I where X -> R from allele A probe and Y -> R from allele B probe

-#  infIRR = infI & (snpbase=="[A/T]" | snpbase=="[T/A]" | snpbase=="[a/t]" | snpbase=="[t/a]")

-  

-#  X[infIRR,] = exprs(channel(RG, "R"))[aord[infIRR],] # mostly red

-#  Y[infIRR,] = exprs(channel(RG, "R"))[bord[infIRR],] # mostly green

-#  Xnb[infIRR,] = exprs(channel(RG, "Rnb"))[aord[infIRR],]

-#  Ynb[infIRR,] = exprs(channel(RG, "Rnb"))[bord[infIRR],]

-#  Xse[infIRR,] = exprs(channel(RG, "Rse"))[aord[infIRR],]

-#  Yse[infIRR,] = exprs(channel(RG, "Rse"))[bord[infIRR],]

-  

-  # Finally Infinium I where X -> G from allele A probe and Y -> G from allele B probe

-#  infIGG = infI & (snpbase=="[C/G]" | snpbase=="[G/C]" | snpbase=="[g/c]" | snpbase=="[c/g]")

-

-#  X[infIGG,] = exprs(channel(RG, "G"))[aord[infIGG],] # mostly red

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

-#  Xnb[infIGG,] = exprs(channel(RG, "Gnb"))[aord[infIGG],]

-#  Ynb[infIGG,] = exprs(channel(RG, "Gnb"))[bord[infIGG],]

-#  Xse[infIGG,] = exprs(channel(RG, "Gse"))[aord[infIGG],]

-#  Yse[infIGG,] = exprs(channel(RG, "Gse"))[bord[infIGG],]

-    

-  #  For now zero out Infinium I probes

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

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

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

-#  XY@assayData$Xnb[infI,] = 0

-#  XY@assayData$Ynb[infI,] = 0

-#  XY@assayData$Xse[infI,] = 0

-#  XY@assayData$Yse[infI,] = 0

-

-#  XY@assayData$zero[XY@assayData$X==0 | XY@assayData$Y==0] = 1

-  gc()

-

-#  storageMode(XY) = "lockedEnvironment"

-  XY

-}

-

-

-RGtoXY2 = function(RG, chipType, verbose=TRUE) {

+RGtoXY = function(RG, chipType, verbose=TRUE) {

   chipList = c("human1mv1c",             # 1M

                "human370v1c",            # 370CNV

                "human650v3a",            # 650Y

@@ -747,7 +430,6 @@ RGtoXY2 = function(RG, chipType, verbose=TRUE) {

   }

   if(verbose) message("Loading chip annotation information.")

     loader("address.rda", .crlmmPkgEnv, pkgname)

-#    data(annotation, package=pkgname, envir=.crlmmPkgEnv)

   aids <- getVarInEnv("addressA") # comes from AddressA_ID or Address column in manifest

   bids <- getVarInEnv("addressB") # comes from AddressB_ID or Address2 column in manifest

   ids <- names(aids)

@@ -772,12 +454,11 @@ RGtoXY2 = function(RG, chipType, verbose=TRUE) {

 #  argrg = aids[rrgg]

 #  brgrg = bids[rrgg]

-#  fD <- new("AnnotatedDataFrame", data=data.frame(row.names=ids))##, varMetadata=data.frame(labelDescript

   XY <- new("NChannelSet",

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

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

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

-	     annotation=chipType, phenoData=RG@phenoData, # featureData=fD

+	     annotation=chipType, phenoData=RG@phenoData, 

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

   featureNames(XY) = ids # featureNames(RG)

   gc()

@@ -790,10 +471,6 @@ RGtoXY2 = function(RG, chipType, verbose=TRUE) {

   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

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

-#  XY@assayData$Xnb[!is.na(aord),] = exprs(channel(RG, "Rnb"))[aord[!is.na(aord)],]

-#  XY@assayData$Ynb[!is.na(aord),] = exprs(channel(RG, "Gnb"))[aord[!is.na(aord)],]

-#  XY@assayData$Xse[!is.na(aord),] = exprs(channel(RG, "Rse"))[aord[!is.na(aord)],]

-#  XY@assayData$Yse[!is.na(aord),] = exprs(channel(RG, "Gse"))[aord[!is.na(aord)],]

   gc()

   ## Warning - not 100% sure that the code below is correct - could be more complicated than this

@@ -803,31 +480,17 @@ RGtoXY2 = function(RG, chipType, verbose=TRUE) {

 #  X[infIRR,] = exprs(channel(RG, "R"))[aord[infIRR],] # mostly red

 #  Y[infIRR,] = exprs(channel(RG, "R"))[bord[infIRR],] # mostly green

-#  Xnb[infIRR,] = exprs(channel(RG, "Rnb"))[aord[infIRR],]

-#  Ynb[infIRR,] = exprs(channel(RG, "Rnb"))[bord[infIRR],]

-#  Xse[infIRR,] = exprs(channel(RG, "Rse"))[aord[infIRR],]

-#  Yse[infIRR,] = exprs(channel(RG, "Rse"))[bord[infIRR],]

   # Finally Infinium I where X -> G from allele A probe and Y -> G from allele B probe

 #  infIGG = infI & (snpbase=="[C/G]" | snpbase=="[G/C]" | snpbase=="[g/c]" | snpbase=="[c/g]")

 #  X[infIGG,] = exprs(channel(RG, "G"))[aord[infIGG],] # mostly red

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

-#  Xnb[infIGG,] = exprs(channel(RG, "Gnb"))[aord[infIGG],]

-#  Ynb[infIGG,] = exprs(channel(RG, "Gnb"))[bord[infIGG],]

-#  Xse[infIGG,] = exprs(channel(RG, "Gse"))[aord[infIGG],]

-#  Yse[infIGG,] = exprs(channel(RG, "Gse"))[bord[infIGG],]

   #  For now zero out Infinium I probes

   XY@assayData$X[infI,] = 0

   XY@assayData$Y[infI,] = 0

   XY@assayData$zero[infI,] = 0  

-#  XY@assayData$Xnb[infI,] = 0

-#  XY@assayData$Ynb[infI,] = 0

-#  XY@assayData$Xse[infI,] = 0

-#  XY@assayData$Yse[infI,] = 0

-

-#  XY@assayData$zero[XY@assayData$X==0 | XY@assayData$Y==0] = 1

   gc()

 #  storageMode(XY) = "lockedEnvironment"

@@ -846,17 +509,12 @@ stripNormalize = function(XY, useTarget=TRUE, verbose=TRUE) {

   }

   if(verbose) message("Loading strip and reference normalization information.")

   loader("preprocStuff.rda", .crlmmPkgEnv, pkgname)

-#  data(preprocStuff, package=pkgname, envir=.crlmmPkgEnv)

   stripnum <- getVarInEnv("stripnum")

   if(useTarget)

     targetdist = getVarInEnv("reference")

-#  Xqws = Yqws = matrix(0, nrow(XY), ncol(XY))

-#  colnames(Xqws) = colnames(Yqws) = sampleNames(XY) #$X

-#  rownames(Xqws) = rownames(Yqws) = featureNames(XY)

-

   if(verbose){

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

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

@@ -883,160 +541,10 @@ stripNormalize = function(XY, useTarget=TRUE, verbose=TRUE) {

   if(verbose)

     cat("\n")

   XY

-#  XYNorm = new("NChannelSet",

-#                X=Xqws+16,

-#                Y=Yqws+16,

-#                Xnb=exprs(channel(XY, "Xnb")),

-#                Ynb=exprs(channel(XY, "Ynb")),

-#                Xse=exprs(channel(XY, "Xse")),

-#                Yse=exprs(channel(XY, "Yse")),

-#                zero=exprs(channel(XY, "zero")),

-#                annotation=annotation(XY),

-#                phenoData=XY@phenoData)

 }

 preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

-				fitMixture=TRUE,

-				eps=0.1,

-				verbose=TRUE,

-				seed=1,

-				cdfName,

-				sns,

-				stripNorm=TRUE,

-				useTarget=TRUE,

-				save.it=FALSE,

-				snpFile,

-				cnFile) {

-  if(stripNorm)

-    XY = stripNormalize(XY, useTarget=useTarget, verbose=verbose)

-

-## MR: the code below is mostly straight from snprma.R

-  if (missing(sns)) sns <- sampleNames(XY) #$X

-  if(missing(cdfName))

-    cdfName <- annotation(XY)

-##  stuffDir <- changeToCrlmmAnnotationName(cdfName)

-  pkgname <- getCrlmmAnnotationName(cdfName)

-  if(!require(pkgname, character.only=TRUE, quietly=!verbose)){

-    suggCall <- paste("library(", pkgname, ", lib.loc='/Altern/Lib/Loc')", sep="")

-    msg <- paste("If", pkgname, "is installed on an alternative location, please load it manually by using", suggCall)

-    message(strwrap(msg))

-    stop("Package ", pkgname, " could not be found.")

-    rm(suggCall, msg)

-  }

-  if(verbose) message("Loading snp annotation and mixture model parameters.")

-  loader("genotypeStuff.rda", .crlmmPkgEnv, pkgname)

-  loader("mixtureStuff.rda", .crlmmPkgEnv, pkgname)

-  loader("snpProbesFid.rda", .crlmmPkgEnv, pkgname)

-  loader("npProbesFid.rda", .crlmmPkgEnv, pkgname)

-#  data(genotypeStuff, mixtureStuff, package=pkgname, envir=.crlmmPkgEnv)

-  autosomeIndex <- getVarInEnv("autosomeIndex")

-  #  pnsa <- getVarInEnv("pnsa")

-  #  pnsb <- getVarInEnv("pnsb")

-  #  fid <- getVarInEnv("fid")

-  #  reference <- getVarInEnv("reference")

-  #  aIndex <- getVarInEnv("aIndex")

-  #  bIndex <- getVarInEnv("bIndex")

-  SMEDIAN <- getVarInEnv("SMEDIAN")

-  theKnots <- getVarInEnv("theKnots")

-  gns <- getVarInEnv("gns")

-  

-  # separate out copy number probes

-  npIndex = getVarInEnv("npProbesFid")

-  nprobes = length(npIndex)

-  if(length(nprobes)>0) {

-    narrays = ncol(XY)

-    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) 

-

-    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)

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

-      t0 <- proc.time() 

-      save(cnAB, file=cnFile) 

-      t0 <- proc.time()-t0

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

-    }

-    rm(cnAB, B, zero)

-  }

-

-  # next process snp probes

-  snpIndex = getVarInEnv("snpProbesFid")

-  nprobes <- length(snpIndex)

-  

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

-  ##We will save parameters of EM to use later

-  mixtureParams <- matrix(0, 4, narrays)

-  SNR <- vector("numeric", narrays)

-  SKW <- vector("numeric", narrays)

-

-  ## This is the sample for the fitting of splines

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

-  ##     because this might intefere with other analyses

-  ##     (like what happened to GCRMA)

-  set.seed(seed)

-  idx <- sort(sample(autosomeIndex, mixtureSampleSize))

-  idx2 <- sample(nprobes, 10^5)

-  

-  ##S will hold (A+B)/2 and M will hold A-B

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

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

-  A <- matrix(as.integer(exprs(channel(XY, "X"))[snpIndex,]), nprobes, narrays) # matrix(as.integer(0), length(pnsa), length(filenames))

-  B <- matrix(as.integer(exprs(channel(XY, "Y"))[snpIndex,]), nprobes, narrays) # matrix(as.integer(0), length(pnsb), length(filenames))

-

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

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

-    

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

-  rownames(A) <- rownames(B) <- rownames(zero) <- names(snpIndex) # gns # featureNames(XY)

-  

-  if(verbose){

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

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

-  }

-

-

-  for(i in 1:narrays){

-    SKW[i] = mean((A[idx2,i]-mean(A[idx2,i]))^3)/(sd(A[idx2,i])^3)

-    if(fitMixture){

-      S <- (log2(A[idx, i])+log2(B[idx, i]))/2 - SMEDIAN

-      M <- log2(A[idx, i])-log2(B[idx, i])

-

-      ##we need to test the choice of eps.. it is not the max diff between funcs

-      tmp <- fitAffySnpMixture56(S, M, theKnots, eps=eps)

-

-      mixtureParams[, i] <- tmp[["coef"]]

-      SNR[i] <- tmp[["medF1"]]^2/(tmp[["sigma1"]]^2+tmp[["sigma2"]]^2)

-    }

-    if(verbose) {

-       if (getRversion() > '2.7.0') setTxtProgressBar(pb, i)

-       else cat(".")

-    }

-  }

-  if (verbose) {

-    if (getRversion() > '2.7.0') close(pb)

-    else cat("\n")

-  }

-  if (!fitMixture) SNR <- mixtureParams <- NA

-  ## gns comes from preprocStuff.rda

-  res = list(A=A, B=B, zero=zero, sns=sns, gns=gns, SNR=SNR, SKW=SKW, mixtureParams=mixtureParams, cdfName=cdfName)

-

-  if(save.it & !missing(snpFile)) {

-    t0 <- proc.time() 

-    save(res, file=snpFile) 

-    t0 <- proc.time()-t0

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

-  }

-  return(res)

-}

-

-

-preprocessInfinium2v2 <- function(XY, mixtureSampleSize=10^5,

 				fitMixture=TRUE,

 				eps=0.1,

 				verbose=TRUE,

@@ -1055,7 +563,6 @@ preprocessInfinium2v2 <- function(XY, mixtureSampleSize=10^5,

   if (missing(sns)) sns <- sampleNames(XY) #$X

   if(missing(cdfName))

     cdfName <- annotation(XY)

-##  stuffDir <- changeToCrlmmAnnotationName(cdfName)

   pkgname <- getCrlmmAnnotationName(cdfName)

   if(!require(pkgname, character.only=TRUE, quietly=!verbose)){

     suggCall <- paste("library(", pkgname, ", lib.loc='/Altern/Lib/Loc')", sep="")

@@ -1069,17 +576,9 @@ preprocessInfinium2v2 <- function(XY, mixtureSampleSize=10^5,

   loader("mixtureStuff.rda", .crlmmPkgEnv, pkgname)

   loader("snpProbesFid.rda", .crlmmPkgEnv, pkgname)

   loader("npProbesFid.rda", .crlmmPkgEnv, pkgname)

-#  data(genotypeStuff, mixtureStuff, package=pkgname, envir=.crlmmPkgEnv)

   autosomeIndex <- getVarInEnv("autosomeIndex")

-  #  pnsa <- getVarInEnv("pnsa")

-  #  pnsb <- getVarInEnv("pnsb")

-  #  fid <- getVarInEnv("fid")

-  #  reference <- getVarInEnv("reference")

-  #  aIndex <- getVarInEnv("aIndex")

-  #  bIndex <- getVarInEnv("bIndex")

   SMEDIAN <- getVarInEnv("SMEDIAN")

   theKnots <- getVarInEnv("theKnots")

-#  gns <- featureNames(XY) # getVarInEnv("gns") # needs to include np probes - gns is only for snps

   narrays = ncol(XY)

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

@@ -1115,9 +614,6 @@ preprocessInfinium2v2 <- function(XY, mixtureSampleSize=10^5,

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

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

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

-#  mixtureParams <- matrix(0, 4, narrays)

-#  SNR <- vector("numeric", narrays)

-#  SKW <- vector("numeric", narrays)

   ## This is the sample for the fitting of splines

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

@@ -1130,25 +626,6 @@ preprocessInfinium2v2 <- function(XY, mixtureSampleSize=10^5,

   ##S will hold (A+B)/2 and M will hold A-B

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

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

-#  A <- exprs(channel(XY, "X"))[,] # ), nrow(XY), narrays) # [snpIndex,]), nprobes, narrays) # matrix(as.integer(0), length(pnsa), length(filenames))

-#  B <- exprs(channel(XY, "Y"))[,] # ), nrow(XY), narrays) # [snpIndex,]), nprobes, narrays) # matrix(as.integer(0), length(pnsb), length(filenames))

-

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

-#  zero <- exprs(channel(XY, "zero"))[,] # )) #[snpIndex,]), nprobes, narrays)

-

-#  if(!is.matrix(A)) {

-#     A = A[,]

-#     B = B[,]

-#     zero = zero[,]

-#  }

-

-#  if(!is.integer(A)) {

-#     A = matrix(as.integer(A), nrow(A), ncol(A))

-#     B = matrix(as.integer(B), nrow(B), ncol(B))

-#  }  

-    

-#  colnames(A) <- colnames(B) <- colnames(zero) <- sns

-#  rownames(A) <- rownames(B) <- rownames(zero) <- names(snpIndex) # gns # featureNames(XY)

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

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

@@ -1188,7 +665,7 @@ preprocessInfinium2v2 <- function(XY, mixtureSampleSize=10^5,

   ## gns comes from preprocStuff.rda

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

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

-             mixtureParams=mixtureParams, cdfName=cdfName) # , snpIndex=snpIndex, npIndex=npIndex)

+             mixtureParams=mixtureParams, cdfName=cdfName)

   if(save.it & !missing(snpFile)) {

     t0 <- proc.time() 

@@ -1235,61 +712,6 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

     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)

-  }else{

-      if(verbose) message("Loading ", snpFile, ".")

-        obj <- load(snpFile)

-        if(verbose) message("Done.")

-        if(!any(obj == "res"))

-          stop("Object in ", snpFile, " seems to be invalid.")

-  }

-  if(row.names) row.names=res[["gns"]] else row.names=NULL

-  if(col.names) col.names=res[["sns"]] else col.names=NULL

-

-  res2 <- crlmmGT(res[["A"]], res[["B"]], res[["SNR"]],

-                  res[["mixtureParams"]], res[["cdfName"]],

-                  gender=gender, row.names=row.names,

-                  col.names=col.names, recallMin=recallMin,

-                  recallRegMin=1000, SNRMin=SNRMin,

-                  returnParams=returnParams, badSNP=badSNP,

-                  verbose=verbose)

-  

-  res2[["SNR"]] <- res[["SNR"]]

-  res2[["SKW"]] <- res[["SKW"]]

-  rm(res)

-  gc()

-  return(list2SnpSet(res2, returnParams=returnParams)) # return(res2)

-}

-

-

-crlmmIllumina2 <- function(RG, XY, 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, save.it=FALSE, load.it=FALSE, snpFile, cnFile,

-                  mixtureSampleSize=10^5, eps=0.1, verbose=TRUE,

-                  cdfName, sns, recallMin=10, recallRegMin=1000,

-                  returnParams=FALSE, badSNP=.7) {

-  if (save.it & (missing(snpFile) | missing(cnFile)))

-    stop("'snpFile' and/or 'cnFile' is missing and you chose to save.it")

-  if (load.it & missing(snpFile))

-    stop("'snpFile' is missing and you chose to load.it")

-  if (!missing(snpFile))

-    if (load.it & !file.exists(snpFile)){

-      load.it <- FALSE

-      message("File ", snpFile, " does not exist.")

-      stop("Cannot load SNP data.")

-  }

-  if (!load.it){

-    if(!missing(RG)) {

-      if(missing(XY))

-        XY = RGtoXY2(RG, chipType=cdfName)

-      else

-        stop("Both RG and XY specified - please use one or the other")

-    }

-    if (missing(sns)) sns <- sampleNames(XY) #$X

-    

-    res = preprocessInfinium2v2(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)

 #    fD = featureData(XY)

 #    phenD = XY@phenoData

@@ -1378,10 +800,10 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 #                          rgFile,

 			  stripNorm=TRUE,

 			  useTarget=TRUE,

-          	          row.names=TRUE, 

+			  row.names=TRUE, 

 			  col.names=TRUE,

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

-                          seed=1, save.ab=FALSE, snpFile, cnFile,

+                          seed=1, save.it=FALSE, snpFile, cnFile,

                           mixtureSampleSize=10^5, eps=0.1, verbose=TRUE,

                           cdfName, sns, recallMin=10, recallRegMin=1000,

                           returnParams=FALSE, badSNP=.7) {

@@ -1392,8 +814,8 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 #  if (save.rg & missing(rgFile))

 #    stop("'rgFile' is missing, and you chose save.rg")

-  if (save.ab & (missing(snpFile) | missing(cnFile)))

-    stop("'snpFile' or 'cnFile' is missing and you chose save.ab")

+  if (save.it & (missing(snpFile) | missing(cnFile)))

+    stop("'snpFile' or 'cnFile' is missing and you chose save.it")

 #  batches = NULL

 #  if(!is.null(arrayNames))

 #    batches <- rep(1, length(arrayNames)) # problem here if arrayNames not specified! # splitIndicesByLength(seq(along=arrayNames), ocSamples())

@@ -1407,20 +829,20 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 #     RG = readIdatFiles(sampleSheet=sampleSheet[j,], arrayNames=arrayNames[j],

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

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

-     RG = readIdatFiles2(sampleSheet=sampleSheet, arrayNames=arrayNames,

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

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

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

 #  if(save.rg)

 #	save(RG, file=rgFile)

-    XY = RGtoXY2(RG, chipType=cdfName)

+    XY = RGtoXY(RG, chipType=cdfName)

     rm(RG); gc()

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

     } # else subsns = sns[j]

-    res = preprocessInfinium2v2(XY, mixtureSampleSize=mixtureSampleSize, fitMixture=TRUE, verbose=verbose,

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

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

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

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

 #    fD = featureData(XY)

 #    phenD = XY@phenoData

 #    protD = XY@protocolData

@@ -1,6 +1,5 @@

 \name{crlmmIllumina}

 \alias{crlmmIllumina}

-\alias{crlmmIllumina2}

 \title{Genotype Illumina Infinium II BeadChip data with CRLMM}

 \description{

   Implementation of the CRLMM algorithm for

@@ -15,14 +14,6 @@ crlmmIllumina(RG, XY, stripNorm=TRUE,

       snpFile, cnFile, mixtureSampleSize=10^5,

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

       recallRegMin=1000, returnParams=FALSE, badSNP=0.7)

-

-crlmmIllumina2(RG, XY, 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, save.it=FALSE, load.it=FALSE,

-      snpFile, cnFile, mixtureSampleSize=10^5,

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

-      recallRegMin=1000, returnParams=FALSE, badSNP=0.7)

 }

 \arguments{

@@ -54,7 +45,7 @@ crlmmIllumina2(RG, XY, stripNorm=TRUE,

   \item{cdfName}{'character' defining the chip annotation (manifest) to use

     ('human370v1c', human550v3b', 'human650v3a', 'human1mv1c',