@@ -42,7 +42,7 @@ BioC data packages

 2009-03-25 Rob Scharpf - committed version 1.0.60

 * simplified some of the preliminary steps for the computeCopynumber function

-** crlmm output subset within the body of the function

+* crlmm output subset within the body of the function

 * modified vignette -- store results in an oligoSnpSet object (for now)

 * added function to extract the date from the celfile headers (celDates)

@@ -78,7 +78,6 @@ BioC data packages

 * added functions to read in idat files, pre-process and genotype 

 data from Illumina SNP arrays (functions named readIdatFiles() 

 and crlmmIllumina() in crlmm-illumina.R)

-

 * added man pages for these functions

 2009-04-01 Matt Ritchie - committed version 1.0.67

@@ -91,8 +90,18 @@ and crlmmIllumina() in crlmm-illumina.R)

 2009-04-03 B Carvalho - committed version 1.0.70

-** Updated TODO and DESCRIPTION

+* Updated TODO and DESCRIPTION

 2009-04-04 R.Scharpf - committed version 1.0.71

 *  bug in oneBatch function for chromosome X.  added additional checks for missing values

+

+2009-04-06 Matt Ritchie - committed version 1.0.72

+

+* new argument in readIdatFiles() 'saveDate', which saves the date and time each array

+is decoded and scanned

+* results from crlmmIllumina() now saved as 'SnpSet' just like crlmm()

+* reorganised Illumina preprocessing functions slightly to

+  - allow copy number intensities to be saved along with snp intensities

+  - make use of new indexing objects in the chip specific crlmm data packages

+  - fix a few bugs

@@ -1,7 +1,7 @@

 Package: crlmm

 Type: Package

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

-Version: 1.0.71

+Version: 1.0.72

 Date: 2008-12-30

 Author: Rafael A Irizarry, Benilton S Carvalho <bcarvalh@jhsph.edu>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU>

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

@@ -5,7 +5,7 @@

 readIdatFiles = 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")) {

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

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

          arrayNames=NULL

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

@@ -33,6 +33,7 @@ readIdatFiles = function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

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

          }

        }

+       narrays = length(arrayNames)

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

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

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

@@ -45,11 +46,17 @@ readIdatFiles = function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

        grnidats = file.path(path, grnfiles)

        redidats = file.path(path, redfiles)

-       headerInfo = list(nProbes = rep(NA, length(arrayNames)),

-                         Barcode = rep(NA, length(arrayNames)),

-                         ChipType = rep(NA, length(arrayNames)),

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

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

+       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),

+                    register=rep(NA, narrays),

+                    extract=rep(NA, narrays))

+

        # read in the data

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

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

@@ -80,6 +87,12 @@ readIdatFiles = function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

                   # || 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")

+

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

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

+         dates$register[i] = G$RunInfo[3, 1]

+         dates$extract[i] = G$RunInfo[4, 1]

+

          if(i==1) {

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

              ids = idsG

@@ -122,14 +135,22 @@ readIdatFiles = function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

            Rstderr[,i] = R$Quants[indR, "SD"]

          }

        }

-       if(is.null(sampleSheet))

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

-       else

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

+       if(is.null(sampleSheet)) {

+         if(saveDate)

+           pd = new("AnnotatedDataFrame", data = data.frame(Sample_ID=arrayNames, DecodeDate=dates$decode, ScanDate=dates$scan))

+         else

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

+       }

+       else {

+         if(saveDate)

+           pd = new("AnnotatedDataFrame", data = cbind(sampleSheet, DecodeDate=dates$decode, ScanDate=dates$scan))

+         else

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

+       }

        RG = new("NChannelSet",

                 R=Rintens, G=Gintens, Rnb=Rnobeads, Gnb=Gnobeads,

                 Rse=Rstderr, Gse=Gstderr, annotation=headerInfo$Manifest[1],

-                phenoData = pd)

+                phenoData=pd)

 }

@@ -390,7 +411,7 @@ readBPM <- function(bpmFile){

 }

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

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

   chipList = c("human1mv1c",             # 1M

                "human370v1c",            # 370CNV

                "human650v3a",            # 650Y

@@ -413,32 +434,36 @@ RGtoXY = function(RG, chipType, remove=TRUE, verbose=TRUE) {

      rm(suggCall, msg)

   }

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

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

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

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

-  annot <- getVarInEnv("annot")

+  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")

-  if(remove)

-    annot = annot[annot[,"ToCall"]==1,]

-  nsnps = nrow(annot)

+  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"] 

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

+  

+#  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[!rrgg], featureNames(RG)) # and here

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

 #  argrg = aids[rrgg]

 #  brgrg = bids[rrgg]

   X = Y = Xnb = Ynb = Xse = Yse = zero = matrix(0, nsnps, narrays)

-  rownames(X) = rownames(Y) = rownames(Xnb) = rownames(Ynb) = rownames(Xse) = rownames(Yse) = snpids

+  rownames(X) = rownames(Y) = rownames(Xnb) = rownames(Ynb) = rownames(Xse) = rownames(Yse) = ids

   colnames(X) = colnames(Y) = colnames(Xnb) = colnames(Ynb) = colnames(Xse) = colnames(Yse) = sampleNames(RG)$G

+

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

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

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

   Xnb[!is.na(aord),] = exprs(channel(RG, "Rnb"))[aord[!is.na(aord)],]

@@ -446,23 +471,38 @@ RGtoXY = function(RG, chipType, remove=TRUE, verbose=TRUE) {

   Xse[!is.na(aord),] = exprs(channel(RG, "Rse"))[aord[!is.na(aord)],]

   Yse[!is.na(aord),] = exprs(channel(RG, "Gse"))[aord[!is.na(aord)],]

-  # Important addition needed to get the correct intensities for the transitional Infinium I SNPs

-  # these SNPs are intergorated by 2 separate bead types (the second bead type is given in the 'AddressB_ID'

-  # (or 'Address2') column, and will have bid != 0 | !is.na(bid)

-  # for these it could be that the X signal is the R/G from the A bead and the Y signal the R/G from the B snp

-  # at present these are all zeroed out, so will presumably be called as hets

-  # this is not a problem for the training data, since we get the X and Y intensities directly from BeadStudio output

+  ## 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],]

-  X[!is.na(bord),] = 0

-  Y[!is.na(bord),] = 0

-  Xnb[!is.na(bord),] = 0

-  Ynb[!is.na(bord),] = 0

-  Xse[!is.na(bord),] = 0

-  Yse[!is.na(bord),] = 0

+  # 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

+  X[infI,] = 0

+  Y[infI,] = 0

+  Xnb[infI,] = 0

+  Ynb[infI,] = 0

+  Xse[infI,] = 0

+  Yse[infI,] = 0

   zero[X==0 | Y==0] = 1

-  rm(annot)

   gc()

   XY = new("NChannelSet",

@@ -533,12 +573,12 @@ stripNormalize = function(XY, useTarget=TRUE, verbose=TRUE) {

 preprocessInfinium2 = function(XY, mixtureSampleSize=10^5, fitMixture=TRUE, eps=0.1, verbose=TRUE, seed=1,

-                               cdfName, sns, stripNorm=TRUE, useTarget=TRUE) {

+                               cdfName, sns, stripNorm=TRUE, useTarget=TRUE, save.it=FALSE, intensityFile) {

   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)

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

   if(missing(cdfName))

     cdfName <- annotation(XY)

 ##  stuffDir <- changeToCrlmmAnnotationName(cdfName)

@@ -552,7 +592,9 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5, fitMixture=TRUE, eps=

   }

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

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

-  loader("mixtureStuff.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")

@@ -564,9 +606,18 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5, fitMixture=TRUE, eps=

   SMEDIAN <- getVarInEnv("SMEDIAN")

   theKnots <- getVarInEnv("theKnots")

   gns <- getVarInEnv("gns")

-

-  nprobes <- nrow(XY)

-  narrays <- ncol(XY)

+  

+  # separate out copy number probes

+  npIndex = getVarInEnv("npProbesFid")

+  nprobes = length(npIndex)

+  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)

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

+  

+  # 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

@@ -585,14 +636,14 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5, fitMixture=TRUE, eps=

   ##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"))), nprobes, narrays) # matrix(as.integer(0), length(pnsa), length(filenames))

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

+  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"))), nprobes, narrays)

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

-  colnames(A) <- colnames(B) <- colnames(zero) <- sampleNames(XY)$X

-  rownames(A) <- rownames(B) <- rownames(zero) <- featureNames(XY)

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

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

   if(verbose){

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

@@ -613,8 +664,8 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5, fitMixture=TRUE, eps=

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

     }

     if(verbose) {

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

-      else cat(".")

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

+       else cat(".")

     }

   }

   if (verbose) {

@@ -623,11 +674,20 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5, fitMixture=TRUE, eps=

   }

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

   ## gns comes from preprocStuff.rda

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

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

+

+  if(save.it & !missing(intensityFile)) {

+    t0 <- proc.time() 

+    save(cnAB, res, file=intensityFile)

+    t0 <- proc.time()-t0

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

+  }

+  return(res)

 }

-## MR: Could add arguments to allow this function to read in idat data as well, although this add a further 7 arguments, which might over-complicate things

+## MR: Could add arguments to allow this function to read in idat data as well,

+## although this would add a further 7 arguments, which might over-complicate things

 crlmmIllumina <- 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,

@@ -635,15 +695,9 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

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

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

                   returnParams=FALSE, badSNP=.7) {

-  if(!missing(RG)) {

-    if(missing(XY))

-      XY = RGtoXY(RG, chipType=cdfName)

-    else

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

-  }

+

   if ((load.it | save.it) & missing(intensityFile))

     stop("'intensityFile' is missing, and you chose either load.it or save.it")

-  if (missing(sns)) sns <- sampleNames(XY) #basename(filenames)

   if (!missing(intensityFile))

     if (load.it & !file.exists(intensityFile)){

       load.it <- FALSE

@@ -651,23 +705,23 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

       message("Not loading it, but running SNPRMA from scratch.")

   }

   if (!load.it){

-#    res <- snprma(filenames, fitMixture=TRUE,

-#                    mixtureSampleSize=mixtureSampleSize, verbose=verbose,

-#                    eps=eps, cdfName=cdfName, sns=sns)

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

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

-    if(save.it){

-      t0 <- proc.time()

-      save(res, file=intensityFile)

-      t0 <- proc.time()-t0

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

+    if(!missing(RG)) {

+      if(missing(XY))

+        XY = RGtoXY(RG, chipType=cdfName)

+      else

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

     }

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

+    

+    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, intensityFile=intensityFile)

   }else{

       if(verbose) message("Loading ", intensityFile, ".")

         obj <- load(intensityFile)

         if(verbose) message("Done.")

-        if(obj != "res")

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

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

+          stop("Object in ", intensityFile, " 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

@@ -682,5 +736,5 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

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

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

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

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

 }

@@ -96,10 +96,10 @@ list2SnpSet <- function(x, returnParams=FALSE){

                           "SNP Quality Score",

                           "Center AA", "Center AB", "Center BB",

                           "Scale AA", "Scale AB", "Scale BB",

-                          "N AA", "N AB", "N BB",

-                          "Shift in parameters AA",

-                          "Shift in parameters AB",

-                          "Shift in parameters BB"),

+                          "N AA", "N AB", "N BB"),

+#                          "Shift in parameters AA",

+#                          "Shift in parameters AB",

+#                          "Shift in parameters BB"),

                         row.names=c(

                           "SNPQC",

                           "cAA", "cAB", "cBB",

@@ -50,16 +50,22 @@ crlmmIllumina(RG, XY, stripNorm=TRUE, useTarget=TRUE,

   \item{badSNP}{'numeric'. Threshold to flag as bad SNP (affects batchQC)}

 }

 \value{

+  A \code{SnpSet} object which contains

   \item{calls}{Genotype calls (1 - AA, 2 - AB, 3 - BB)}

-  \item{confs}{Confidence scores 'round(-1000*log2(1-p))'}

+  \item{callProbability}{confidence scores 'round(-1000*log2(1-p))'}

+  in the \code{assayData} slot and

   \item{SNPQC}{SNP Quality Scores}

-  \item{batchQC}{Batch Quality Score}

-  \item{params}{Recalibrated parameters}

+  \item{batchQC}{Batch Quality Scores}

+  along with center and scale parameters when \code{returnParams=TRUE}

+  in the \code{featureData} slot.

 }

 \details{

   Note: The user should specify either the \code{RG} or \code{XY}

-  intensities, not both.

+  intensities, not both.  Alternatively if \code{crlmmIllumina} has been

+  run already with \code{save.it=TRUE}, the preprocessed data can be

+  loaded from file by specifying \code{load.it=TRUE} and

+  \code{intensityFile} (\code{RG} or \code{XY} are not needed in this case).

 }

 \references{

@@ -12,7 +12,8 @@ readIdatFiles(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"))

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

+              saveDate=FALSE)

 }

 \arguments{

@@ -40,6 +41,8 @@ readIdatFiles(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

     names.}

   \item{fileExt}{list containing elements 'Green' and 'Red' which

     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?}

 }

 \details{