@@ -363,9 +363,17 @@ is decoded and scanned

  * Added 'humanomni1quadv1b" to chip types allowed in RGtoXY()

-

 2010-01-20 R. Scharpf - committed version 1.5.21

  * Added CopyNumberVariants to DESCRIPTION

 2010-01-20 R. Scharpf - committed version 1.5.22

  * restored inst/doc/crlmmDownstream.Rnw

+

+2010-02-04 M. Ritchie - committed version 1.5.23

+ * crlmmIllumina now exported in NAMESPACE (removed at some point)

+ * new function crlmmIlluminaV2() which reads in .idats and genotypes 

+in the one function to reduce memory usage (not exported as yet)

+ * readIdatFiles() modified to no longer store number of beads and beads SE

+to save memory.  Instead, 'zero', which indicates which SNPs have zero beads 

+is stored in the assayData slot.

+ * now store 'zero' with copy number AB intensities in preprocessInfinium2()

@@ -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: 1.5.22

-Date: 2010-01-20

+Version: 1.5.23

+Date: 2010-02-04

 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>

 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

@@ -50,7 +50,7 @@ importFrom(mvtnorm, dmvnorm)

 importFrom(ellipse, ellipse)

 exportMethods(A, B, copyNumber)

-export(cnOptions, crlmm, crlmmCopynumber, ellipse, readIdatFiles, snprma, getParam) 

+export(cnOptions, crlmm, crlmmIllumina, crlmmCopynumber, ellipse, readIdatFiles, snprma, getParam) 

 ##export(##viterbi.CNSet, ##move to VanillaICE

 ##	combineIntensities,

@@ -119,10 +119,11 @@ readIdatFiles <- function(sampleSheet=NULL,

 		       RG <- new("NChannelSet",

 				 R=tmpmat,

 				 G=tmpmat,

-				 Rnb=tmpmat,

-				 Gnb=tmpmat,

-				 Rse=tmpmat,

-				 Gse=tmpmat,

+				 zero=tmpmat,

+#				 Rnb=tmpmat,

+#				 Gnb=tmpmat,

+#				 Rse=tmpmat,

+#				 Gse=tmpmat,

 				 annotation=headerInfo$Manifest[1],

 				 phenoData=pd,

 				 storage.mode="environment")

@@ -132,14 +133,16 @@ readIdatFiles <- function(sampleSheet=NULL,

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

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

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

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

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

+				   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"]

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

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

+			   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()

@@ -151,16 +154,19 @@ readIdatFiles <- function(sampleSheet=NULL,

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

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

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

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

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

+				   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"]

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

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

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

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

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

 	       }

-	       rm(R)

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

+	       rm(R, zeroG, zeroR)

 	       gc()

        }

        if(saveDate) {

@@ -482,7 +488,7 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

   tmpmat = matrix(0, nsnps, narrays)

   rownames(tmpmat) = ids

   colnames(tmpmat) = sampleNames(RG)

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

+  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()

@@ -490,10 +496,11 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

   # 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$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)],]

+  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

@@ -521,12 +528,13 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

   #  For now zero out Infinium I probes

   XY@assayData$X[infI,] = 0

   XY@assayData$Y[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[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

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

   gc()

 #  storageMode(XY) = "lockedEnvironment"

@@ -644,7 +652,15 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

   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)

+

+  # 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)

+  rm(A, B, zero)

   # next process snp probes

   snpIndex = getVarInEnv("snpProbesFid")

@@ -768,3 +784,64 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

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

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

 }

+

+## MR: Below is a more memory efficient version of crlmmIllumina() which 

+## reads in the .idats and genotypes in the one function and removes objects 

+## after they have been used

+crlmmIlluminaV2 = 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,

+              save.rg=FALSE,

+              rgFile,

+			  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.ab=FALSE, abFile,

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

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

+              returnParams=FALSE, badSNP=.7) {

+			  

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

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

+  if (save.ab & missing(abFile))

+    stop("'abFile' is missing, and you chose save.ab")

+				  

+  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 = RGtoXY(RG, chipType=cdfName)

+  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,

+                        save.it=save.ab, intensityFile=abFile)

+  rm(XY)

+  gc()

+  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"]]

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

+}

@@ -46,8 +46,7 @@ readIdatFiles(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path="",

 }

 \details{

-The summarised Cy3 (G) and Cy5 (R) intensity, number of beads that

-were used in each channel and standard errors (all on the orginal scale)

+The summarised Cy3 (G) and Cy5 (R) intensities (on the orginal scale)

 are read in from the .idat files.

 Where available, a \code{sampleSheet} data.frame, in the same format

@@ -59,9 +58,8 @@ Thanks to Keith Baggerly who provided the code to read in the binary .idat files

 }

 \value{

-  NChannelSet with intensity data (\code{R}, \code{G}), number of beads

-  (\code{Rnb}, \code{Gnb}) and standard errors (\code{Rse}, \code{Gse})

-  for each bead type.

+  NChannelSet with intensity data (\code{R}, \code{G}), and indicator 

+  for SNPs with 0 beads (\code{zero}) for each bead type.

 }

 \author{Matt Ritchie}