@@ -576,3 +576,11 @@ function (which expects ff objects and supports parallel processing)

 2010-10-17 M. Ritchie 1.7.22

 **  added "humanomni25quadv1b" to validCdfName() in utils.R and RGtoXY() in crlmm-illumina.R

+2010-11-18 M. Ritchie 1.9.8

+** genotype.Illumina() is now exported and has a man page.  The argument 'outdir' should 

+be used to specify where you want to store the large data objects.  ldPath(outdir) is specified 

+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()

+

@@ -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: 1.9.7

-Date: 2010-11-14

+Version: 1.9.8

+Date: 2010-11-18

 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

@@ -68,6 +68,7 @@ export(crlmm,

        snprma2,

        crlmm2,

        genotype2, genotypeLD,

+       genotype.Illumina, 

        crlmmCopynumber2, crlmmCopynumberLD, crlmmCopynumber)

 export(constructIlluminaCNSet)

 export(totalCopynumber)

@@ -462,18 +462,18 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

 #  brgrg = bids[rrgg]

   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"),

+	     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),

 	     annotation=chipType, phenoData=RG@phenoData,

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

   featureNames(XY) = ids

   sampleNames(XY) = sampleNames(RG)

   gc()

   # Need to initialize - matrices filled with NAs to begin with

-  XY@assayData$X[1:nsnps,] = 0

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

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

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

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

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

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

@@ -585,7 +585,8 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5,

 				cdfName,

 				sns,

 				stripNorm=TRUE,

-				useTarget=TRUE) {

+				useTarget=TRUE,

+                                outdir=".") {

 #				save.it=FALSE,

 #				snpFile,

 #				cnFile) {

@@ -615,7 +616,8 @@ preprocessInfinium2 = function(XY, mixtureSampleSize=10^5,

   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")

@@ -913,6 +915,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 			  saveDate=FALSE,

 			  stripNorm=TRUE,

 			  useTarget=TRUE,

+                          outdir=".",

 			  row.names=TRUE,

 			  col.names=TRUE,

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

@@ -941,7 +944,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

     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) #,

+                               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) {

@@ -1042,7 +1045,8 @@ construct.Illumina = function(sampleSheet=NULL,

 			  red="Red.idat"),

 		      	  cdfName,

 		      	  copynumber=TRUE,

-		      	  verbose=TRUE, batch, fns, saveDate=TRUE){

+		      	  verbose=TRUE, batch, #fns,

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

        if(!is.null(arrayNames)) {

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

        }

@@ -1083,7 +1087,7 @@ construct.Illumina = function(sampleSheet=NULL,

 		stopifnot(length(batch) == narrays)

        }

        if(missing(batch)) {

-                batch = as.factor(rep(1, narrays))

+                stop("Must specify 'batch'") # batch = as.factor(rep(1, narrays))

        }

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

@@ -1105,12 +1109,13 @@ construct.Illumina = function(sampleSheet=NULL,

 	if(verbose) message("Initializing container for genotyping and copy number estimation")

 	featureData = getFeatureData.Affy(cdfName, copynumber=copynumber)

-	if(!missing(fns)){

-		index = match(fns, featureNames(featureData))

-		if(all(is.na(index))) stop("fns not in featureNames")

-		featureData = featureData[index, ]

-	}

+#	if(!missing(fns)){

+#		index = match(fns, featureNames(featureData))

+#		if(all(is.na(index))) stop("fns not in featureNames")

+#		featureData = featureData[index, ]

+#	}

 	nr = nrow(featureData); nc = narrays

+        ldPath(outdir)

 	cnSet = new("CNSet",

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

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

@@ -1151,7 +1156,8 @@ genotype.Illumina = function(sampleSheet=NULL,

 		      	  cdfName,

 		      	  copynumber=TRUE,

                           batch,

-                          fns,

+                          outdir=".",

+#                          fns,

                           saveDate=TRUE,

        			  stripNorm=TRUE,

 			  useTarget=TRUE,

@@ -1173,14 +1179,19 @@ genotype.Illumina = function(sampleSheet=NULL,

 	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")

 	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)

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

+                             saveDate=saveDate, outdir=outdir)

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

-	open(callSet)

-	is.snp = isSnp(callSet)

+        

+        open(A(callSet))

+        open(B(callSet))

+        # open(callSet)

+ 	is.snp = isSnp(callSet)

 	snp.index = which(is.snp)

         narrays = ncol(callSet)

         if(is.lds) {

@@ -1195,7 +1206,7 @@ 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, neededPkgs=c("crlmm", pkgname))

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

           open(SKW)

           open(SNR)

@@ -1214,7 +1225,7 @@ 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)

+                               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)

@@ -1317,7 +1328,7 @@ processIDAT =  function(sel, sampleSheet=NULL,

 			  sns,

 			  stripNorm=TRUE,

 			  useTarget=TRUE,

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

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

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

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

@@ -1331,7 +1342,7 @@ processIDAT =  function(sel, sampleSheet=NULL,

         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)

+                               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)

@@ -10,11 +10,11 @@

 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, 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, recallRegMin=1000,

-      returnParams=FALSE, badSNP=.7)

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

+      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, 

+      recallRegMin=1000, returnParams=FALSE, badSNP=.7)

 }

 \arguments{

@@ -47,6 +47,8 @@ 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.}