@@ -2,4 +2,24 @@ setOldClass("ellipse")

 setOldClass("ff_matrix")

 setOldClass("ffdf")

 setClassUnion("ff_or_matrix", c("ff_matrix", "matrix", "ffdf"))

+<<<<<<< HEAD

+=======

+setClass("CNSetLM", contains="CNSet", representation(lM="list_or_ffdf"))

+setMethod("initialize", "CNSetLM", function(.Object, lM=new("list"), ...){

+	.Object@lM <- lM

+	.Object <- callNextMethod(.Object, ...)

+})

+setValidity("CNSetLM",

+	    function(object){

+		    if(!"batch" %in% varLabels(protocolData(object)))

+			    return("'batch' not defined in protocolData")

+		    if(!"chromosome" %in% fvarLabels(object))

+			    return("'chromosome' not defined in featureData")

+		    if(!"position" %in% fvarLabels(object))

+			    return("'position' not defined in featureData")

+		    if(!"isSnp" %in% fvarLabels(object))

+			    return("'isSnp' not defined in featureData")

+		    return(TRUE)

+	    })

+>>>>>>> Removed tryCatch() statements in readIdatFiles. Restored previous implementation.

@@ -101,3 +101,4 @@ setGeneric("tau2B<-", function(object, value) standardGeneric("tau2B<-"))

 setGeneric("flags<-", function(object, value) standardGeneric("flags<-"))

+

@@ -12,7 +12,7 @@ readIdatFiles <- function(sampleSheet=NULL,

 			  sep="_",

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

 			  saveDate=FALSE) {

-			  

+

        if(!is.null(arrayNames)) {

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

        }

@@ -22,7 +22,7 @@ readIdatFiles <- function(sampleSheet=NULL,

 			       barcode = sampleSheet[,arrayInfoColNames$barcode]

 			       arrayNames=barcode

 		       }

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

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

 			       position = sampleSheet[,arrayInfoColNames$position]

 			       if(is.null(arrayNames))

 				       arrayNames=position

@@ -36,7 +36,7 @@ readIdatFiles <- function(sampleSheet=NULL,

 		       }

 	       }

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

-	       sampleNames(pd) <- basename(arrayNames)               

+	       sampleNames(pd) <- basename(arrayNames)

        }

        if(is.null(arrayNames)) {

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

@@ -46,7 +46,7 @@ readIdatFiles <- function(sampleSheet=NULL,

                }

                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)

@@ -63,7 +63,7 @@ readIdatFiles <- function(sampleSheet=NULL,

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

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

                          Barcode = rep(NA, narrays),

                          ChipType = rep(NA, narrays),

@@ -119,12 +119,12 @@ readIdatFiles <- function(sampleSheet=NULL,

 	       }

 	       rm(G)

 	       gc()

-         

+

 	       cat(paste(sep, fileExt$red, sep=""), "\n")

 	       R = readIDAT(redidats[i])

 	       idsR = rownames(R$Quants)

-         

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

+

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

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

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

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

@@ -145,7 +145,7 @@ readIdatFiles <- function(sampleSheet=NULL,

 #       if(class(RG@assayData$R)[1]=="ff_matrix") {

          close(RG@assayData$R)

          close(RG@assayData$G)

-         close(RG@assayData$zero)         

+         close(RG@assayData$zero)

 #       }

        RG

 }

@@ -161,27 +161,27 @@ readIDAT <- function(idatFile){

   }

-  versionNumber <- readBin(tempCon, "integer", n=1, size=8, 

+  versionNumber <- readBin(tempCon, "integer", n=1, size=8,

                            endian="little", signed=FALSE)

   if(versionNumber<3)

 	  stop("Older style IDAT files not supported:  consider updating your scanner settings")

-  

-  nFields <- readBin(tempCon, "integer", n=1, size=4, 

+

+  nFields <- readBin(tempCon, "integer", n=1, size=4,

                      endian="little", signed=FALSE)

   fields <- matrix(0,nFields,3);

   colnames(fields) <- c("Field Code", "Byte Offset", "Bytes")

   for(i1 in 1:nFields){

-    fields[i1,"Field Code"] <- 

+    fields[i1,"Field Code"] <-

       readBin(tempCon, "integer", n=1, size=2, endian="little", signed=FALSE)

-    fields[i1,"Byte Offset"] <- 

+    fields[i1,"Byte Offset"] <-

       readBin(tempCon, "integer", n=1, size=8, endian="little", signed=FALSE)

   }

   knownCodes <- c(1000, 102, 103, 104, 107, 200, 300, 400,

                   401, 402, 403, 404, 405, 406, 407, 408, 409)

-  names(knownCodes) <- 

+  names(knownCodes) <-

     c("nSNPsRead",  # 1000

       "IlluminaID", #  102

       "SD",         #  103

@@ -214,35 +214,35 @@ readIDAT <- function(idatFile){

   }

   seek(tempCon, fields["nSNPsRead", "Byte Offset"])

-  nSNPsRead <- readBin(tempCon, "integer", n=1, size=4, 

+  nSNPsRead <- readBin(tempCon, "integer", n=1, size=4,

                        endian="little", signed=FALSE)

   seek(tempCon, fields["IlluminaID", "Byte Offset"])

-  IlluminaID <- readBin(tempCon, "integer", n=nSNPsRead, size=4, 

+  IlluminaID <- readBin(tempCon, "integer", n=nSNPsRead, size=4,

                        endian="little", signed=FALSE)

   seek(tempCon, fields["SD", "Byte Offset"])

-  SD <- readBin(tempCon, "integer", n=nSNPsRead, size=2, 

+  SD <- readBin(tempCon, "integer", n=nSNPsRead, size=2,

                 endian="little", signed=FALSE)

   seek(tempCon, fields["Mean", "Byte Offset"])

-  Mean <- readBin(tempCon, "integer", n=nSNPsRead, size=2, 

+  Mean <- readBin(tempCon, "integer", n=nSNPsRead, size=2,

                   endian="little", signed=FALSE)

   seek(tempCon, fields["NBeads", "Byte Offset"])

   NBeads <- readBin(tempCon, "integer", n=nSNPsRead, size=1, signed=FALSE)

   seek(tempCon, fields["MidBlock", "Byte Offset"])

-  nMidBlockEntries <- readBin(tempCon, "integer", n=1, size=4, 

+  nMidBlockEntries <- readBin(tempCon, "integer", n=1, size=4,

                               endian="little", signed=FALSE)

-  MidBlock <- readBin(tempCon, "integer", n=nMidBlockEntries, size=4, 

+  MidBlock <- readBin(tempCon, "integer", n=nMidBlockEntries, size=4,

                       endian="little", signed=FALSE)

   seek(tempCon, fields["RunInfo", "Byte Offset"])

-  nRunInfoBlocks <- readBin(tempCon, "integer", n=1, size=4, 

+  nRunInfoBlocks <- readBin(tempCon, "integer", n=1, size=4,

                             endian="little", signed=FALSE)

   RunInfo <- matrix(NA, nRunInfoBlocks, 5)

-  colnames(RunInfo) <- c("RunTime", "BlockType", "BlockPars", 

+  colnames(RunInfo) <- c("RunTime", "BlockType", "BlockPars",

                          "BlockCode", "CodeVersion")

   for(i1 in 1:2) { #nRunInfoBlocks){  ## MR edit

     for(i2 in 1:5){

@@ -252,50 +252,50 @@ readIDAT <- function(idatFile){

   }

   seek(tempCon, fields["RedGreen", "Byte Offset"])

-  RedGreen <- readBin(tempCon, "numeric", n=1, size=4, 

+  RedGreen <- readBin(tempCon, "numeric", n=1, size=4,

                       endian="little", signed=FALSE)

-  #RedGreen <- readBin(tempCon, "integer", n=4, size=1, 

+  #RedGreen <- readBin(tempCon, "integer", n=4, size=1,

   #                    endian="little", signed=FALSE)

   seek(tempCon, fields["MostlyNull", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  MostlyNull <- readChar(tempCon, nChars) 

+  MostlyNull <- readChar(tempCon, nChars)

   seek(tempCon, fields["Barcode", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  Barcode <- readChar(tempCon, nChars) 

+  Barcode <- readChar(tempCon, nChars)

   seek(tempCon, fields["ChipType", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  ChipType <- readChar(tempCon, nChars) 

+  ChipType <- readChar(tempCon, nChars)

   seek(tempCon, fields["MostlyA", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  MostlyA <- readChar(tempCon, nChars) 

+  MostlyA <- readChar(tempCon, nChars)

   seek(tempCon, fields["Unknown.1", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  Unknown.1 <- readChar(tempCon, nChars) 

+  Unknown.1 <- readChar(tempCon, nChars)

   seek(tempCon, fields["Unknown.2", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  Unknown.2 <- readChar(tempCon, nChars) 

+  Unknown.2 <- readChar(tempCon, nChars)

   seek(tempCon, fields["Unknown.3", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  Unknown.3 <- readChar(tempCon, nChars) 

+  Unknown.3 <- readChar(tempCon, nChars)

   seek(tempCon, fields["Unknown.4", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  Unknown.4 <- readChar(tempCon, nChars) 

+  Unknown.4 <- readChar(tempCon, nChars)

   seek(tempCon, fields["Unknown.5", "Byte Offset"])

   nChars <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  Unknown.5 <- readChar(tempCon, nChars) 

+  Unknown.5 <- readChar(tempCon, nChars)

   close(tempCon)

-  Unknowns <- 

+  Unknowns <-

     list(MostlyNull=MostlyNull,

          MostlyA=MostlyA,

          Unknown.1=Unknown.1,

@@ -308,21 +308,21 @@ readIDAT <- function(idatFile){

   colnames(Quants) <- c("Mean", "SD", "NBeads")

   rownames(Quants) <- as.character(IlluminaID)

-  idatValues <- 

-    list(fileSize=fileSize, 

-         versionNumber=versionNumber, 

-         nFields=nFields, 

+  idatValues <-

+    list(fileSize=fileSize,

+         versionNumber=versionNumber,

+         nFields=nFields,

          fields=fields,

-         nSNPsRead=nSNPsRead, 

-         #IlluminaID=IlluminaID, 

-         #SD=SD, 

-         #Mean=Mean, 

+         nSNPsRead=nSNPsRead,

+         #IlluminaID=IlluminaID,

+         #SD=SD,

+         #Mean=Mean,

          #NBeads=NBeads,

          Quants=Quants,

-         MidBlock=MidBlock, 

-         RunInfo=RunInfo, 

-         RedGreen=RedGreen, 

-         Barcode=Barcode, 

+         MidBlock=MidBlock,

+         RunInfo=RunInfo,

+         RedGreen=RedGreen,

+         Barcode=Barcode,

          ChipType=ChipType,

          Unknowns=Unknowns)

@@ -333,20 +333,20 @@ readIDAT <- function(idatFile){

 readBPM <- function(bpmFile){

   ## Reads and parses Illumina BPM files

-  

+

   fileSize <- file.info(bpmFile)$size

   tempCon <- file(bpmFile,"rb")

   # The first few bytes of the egtFile are some type of

-  # header, but there's no related byte offset information. 

+  # header, but there's no related byte offset information.

   prefixCheck <- readChar(tempCon,3) ## should be "BPM"

   null.1 <- readBin(tempCon, "integer", n=1, size=1, signed=FALSE)

-  ## should be 1  

-  

-  versionNumber <- 

+  ## should be 1

+

+  versionNumber <-

     readBin(tempCon, "integer", n=1, size=4, endian="little", signed=FALSE)

   ## should be 4

@@ -360,14 +360,14 @@ readBPM <- function(bpmFile){

   entriesByteOffset <- seek(tempCon);

   nEntries <- readBin(tempCon, "integer", n=1, size=4,

                       endian="little", signed=FALSE)

-    

+

   if(FALSE){

-    

+

     snpIndexByteOffset <- seek(tempCon)

     snpIndex <- readBin(tempCon, "integer", n=nEntries, size=4,

                         endian="little", signed=FALSE)

     ## for the 1M array, these are simply in order from 1 to 1072820.

-    

+

     snpNamesByteOffset <- seek(tempCon)

     snpNames <- rep("A", nEntries)

     for(i1 in 1:nEntries){

@@ -378,21 +378,21 @@ readBPM <- function(bpmFile){

   }

   seek(tempCon, 15278138)

-    

+

   normIDByteOffset <- seek(tempCon)

   normID <- readBin(tempCon, "integer", n=nEntries, size=1, signed=FALSE) + 1

-  

+

   newBlockByteOffset <- seek(tempCon)

   newBlock <- readBin(tempCon, "integer", n=10000, size=1, signed=FALSE)

-  

+

   close(tempCon)

   byteOffsets <- list(entriesByteOffset=entriesByteOffset,

-                      #snpIndexByteOffset=snpIndexByteOffset, 

+                      #snpIndexByteOffset=snpIndexByteOffset,

                       #snpNamesByteOffset=snpNamesByteOffset,

                       normIDByteOffset=normIDByteOffset,

                       newBlockByteOffset=newBlockByteOffset)

-  

+

   allStuff <- list(prefixCheck=prefixCheck,

                    null.1=null.1,

                    versionNumber=versionNumber,

@@ -406,7 +406,7 @@ readBPM <- function(bpmFile){

                    newBlock=newBlock,

                    byteOffsets=byteOffsets)

   allStuff

-  

+

 }

@@ -424,7 +424,7 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

   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="")

@@ -439,21 +439,21 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

   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)) 

+#  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  

+#  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]

@@ -463,7 +463,7 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

 	     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, 

+	     annotation=chipType, phenoData=RG@phenoData,

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

   featureNames(XY) = ids # featureNames(RG)

   gc()

@@ -471,39 +471,39 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

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

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

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

-  

+

   open(RG@assayData$R)

   open(RG@assayData$G)

   open(RG@assayData$zero)

-  

+

   # 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

   gc()

-  

+

   close(RG@assayData$R)

   close(RG@assayData$G)

   close(RG@assayData$zero)

-  

+

   ## 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

-  

+

   # 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

-    

+

   #  For now zero out Infinium I probes

   XY@assayData$X[infI,] = 0

   XY@assayData$Y[infI,] = 0

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

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

   gc()

 #  if(class(XY@assayData$X)[1]=="ff_matrix") {

@@ -511,7 +511,7 @@ RGtoXY = function(RG, chipType, verbose=TRUE) {

     close(XY@assayData$Y)

     close(XY@assayData$zero)

 #  }

-  

+

 #  storageMode(XY) = "lockedEnvironment"

   XY

 }

@@ -530,15 +530,15 @@ stripNormalize = function(XY, useTarget=TRUE, verbose=TRUE) {

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

   stripnum <- getVarInEnv("stripnum")

-  

+

   if(useTarget)

     targetdist = getVarInEnv("reference")

-  

+

   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)

   }

-  

+

 #  if(class(XY@assayData$X)[1]=="ff_matrix") {

     open(XY@assayData$X)

     open(XY@assayData$Y)

@@ -566,7 +566,7 @@ stripNormalize = function(XY, useTarget=TRUE, verbose=TRUE) {

     close(XY@assayData$X)

     close(XY@assayData$Y)

 #  }

-  

+

   if(verbose)

     cat("\n")

   XY

@@ -609,7 +609,7 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

   SMEDIAN <- getVarInEnv("SMEDIAN")

   theKnots <- getVarInEnv("theKnots")

   narrays = ncol(XY)

-  

+

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

     # separate out copy number probes

     npIndex = getVarInEnv("npProbesFid")

@@ -618,7 +618,7 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

       open(XY@assayData$X)

       open(XY@assayData$Y)

       open(XY@assayData$zero)

-      

+

       A <- matrix(as.integer(exprs(channel(XY, "X"))[npIndex,]), nprobes, narrays)

       B <- matrix(as.integer(exprs(channel(XY, "Y"))[npIndex,]), nprobes, narrays)

@@ -631,26 +631,26 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

       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)

-    

-      t0 <- proc.time() 

-      save(cnAB, file=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 <- initializeBigMatrix("crlmmMixt-", 4, narrays, "double")

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

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

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

   ## This is the sample for the fitting of splines

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

@@ -659,7 +659,7 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

   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

@@ -667,7 +667,7 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

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

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

   zero <- initializeBigMatrix("crlmmZero-", nprobes, narrays, "integer")

-  

+

   if(verbose){

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

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

@@ -676,11 +676,11 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

   open(XY@assayData$X)

   open(XY@assayData$Y)

   open(XY@assayData$zero)

-  

+

   for(i in 1:narrays){

      A[,i] = exprs(channel(XY, "X"))[snpIndex,i]

      B[,i] = exprs(channel(XY, "Y"))[snpIndex,i]

-     zero[,i] = exprs(channel(XY, "zero"))[snpIndex,i] 

+     zero[,i] = exprs(channel(XY, "zero"))[snpIndex,i]

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

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

     if(fitMixture){

@@ -707,8 +707,8 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

   close(XY@assayData$X)

   close(XY@assayData$Y)

-  close(XY@assayData$zero)  

-  

+  close(XY@assayData$zero)

+

 #  if(class(A)[1]=="ff_matrix") {

     close(A)

     close(B)

@@ -716,8 +716,8 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

     close(SKW)

     close(mixtureParams)

     close(SNR)

-#  }  

-  

+#  }

+

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

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

              mixtureParams=mixtureParams, cdfName=cdfName)

@@ -726,11 +726,11 @@ preprocessInfinium2 <- function(XY, mixtureSampleSize=10^5,

   open(res[["B"]])

   open(res[["zero"]])

   open(res[["SNR"]])

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

-  

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

+

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

-    t0 <- proc.time() 

-    save(res, file=snpFile) 

+    t0 <- proc.time()

+    save(res, file=snpFile)

     t0 <- proc.time()-t0

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

   }

@@ -770,7 +770,7 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

         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, snpFile=snpFile, cnFile=cnFile)

@@ -786,13 +786,13 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

 #                    alleleB=initializeBigMatrix(name="B", nr=nrow(res[[1]]), nc=length(sns)),

 #                    call=initializeBigMatrix(name="call", nr=nrow(res[[1]]), nc=length(sns)),

 #                    callProbability=initializeBigMatrix(name="callPr", nr=nrow(res[[1]]), nc=length(sns)),

-#  	            annotation=cdfName, protocolData=protD, phenoData=phenD, featureData=fD) 

+#  	            annotation=cdfName, protocolData=protD, phenoData=phenD, featureData=fD)

 #    sampleNames(callSet) <- sns

 #    featureNames(callSet) <- res[["gns"]]

 #    pData(callSet)$SKW <- rep(NA, length(sns))

 #    pData(callSet)$SNR <- rep(NA, length(sns))

 #    pData(callSet)$gender <- rep(NA, length(sns))

-					  

+

   }else{

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

         obj <- load(snpFile)

@@ -808,7 +808,7 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

 #    rm(phenD, protD , fD)

-#    snp.index <- res$snpIndex #match(res$gns, featureNames(callSet))                

+#    snp.index <- res$snpIndex #match(res$gns, featureNames(callSet))

 #    suppressWarnings(A(callSet) <- res[["A"]])

 #    suppressWarnings(B(callSet) <- res[["B"]])

 #    pData(callSet)$SKW <- res$SKW

@@ -817,7 +817,7 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

 #    rm(res); gc()

   if(row.names) row.names=res$gns else row.names=NULL

   if(col.names) col.names=res$sns else col.names=NULL

-  

+

   res2 <- crlmmGT2(A=res[["A"]], #as.matrix(A(callSet)[snp.index,]), # j]),

                   B=res[["B"]], # as.matrix(B(callSet)[snp.index,]),  # j]),

                   SNR=res[["SNR"]], # callSet$SNR, # [j],

@@ -834,7 +834,7 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

                   verbose=verbose,

                   returnParams=returnParams,

                   badSNP=badSNP)

-#    rm(res); gc()  

+#    rm(res); gc()

 #    suppressWarnings(snpCall(callSet)[snp.index, j] <- tmp[["calls"]])

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

 #    callSet$gender[j] <- tmp$gender

@@ -851,8 +851,8 @@ crlmmIllumina <- function(RG, XY, stripNorm=TRUE, useTarget=TRUE,

 }

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

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

+## 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,

@@ -867,7 +867,7 @@ 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.it=FALSE, snpFile, cnFile,

@@ -878,7 +878,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

   if(missing(cdfName)) stop("must specify cdfName")

   if(!isValidCdfName(cdfName)) stop("cdfName not valid.  see validCdfNames")

 #  if(missing(sns)) sns <- basename(arrayNames)

-			  

+

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

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

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

@@ -914,7 +914,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

     open(res[["B"]])

     open(res[["SNR"]])

     open(res[["mixtureParams"]])

-						   

+

 #    fD = featureData(XY)

 #    phenD = XY@phenoData

 #    protD = XY@protocolData

@@ -938,7 +938,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 #    featureNames(callSet) <- res[["gns"]]

 #    pData(callSet)$SKW <- rep(NA, length(sns))

 #    pData(callSet)$SNR <- rep(NA, length(sns))

-#    pData(callSet)$gender <- rep(NA, length(sns))			

+#    pData(callSet)$gender <- rep(NA, length(sns))

 #	}

 #	pData(callSet)[j,] <- phenD

 #	pData(protocolData(callSet))[j,] <- protD

@@ -946,7 +946,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 #	pData(protocolData(callSet)) <- protD

 #    rm(phenD, protD, fD)

-	

+

 #    if(k > 1 & nrow(res[[1]]) != nrow(callSet)){

         ##RS: I don't understand why the IDATS for the

         ##same platform potentially have different lengths

@@ -954,7 +954,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 #        res[["B"]] <- res[["B"]][res$gns %in% featureNames(callSet), ]

 #    }

-#    snp.index <- res$snpIndex #match(res$gns, featureNames(callSet))                

+#    snp.index <- res$snpIndex #match(res$gns, featureNames(callSet))

 #    suppressWarnings(A(callSet)[, j] <- res[["A"]])

 #    suppressWarnings(B(callSet)[, j] <- res[["B"]])

 #    suppressWarnings(A(callSet) <- res[["A"]])

@@ -966,7 +966,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

 #    mixtureParams <- res$mixtureParams

 #    rm(res); gc()

   if(row.names) row.names=res$gns else row.names=NULL

-  if(col.names) col.names=res$sns else col.names=NULL    

+  if(col.names) col.names=res$sns else col.names=NULL

   res2 <- crlmmGT2(A=res[["A"]], #as.matrix(A(callSet)[snp.index,]), # j]),

                   B=res[["B"]], # as.matrix(B(callSet)[snp.index,]),  # j]),

                   SNR=res[["SNR"]], # callSet$SNR, # [j],

@@ -983,7 +983,7 @@ crlmmIlluminaV2 = function(sampleSheet=NULL,

                   verbose=verbose,

                   returnParams=returnParams,

                   badSNP=badSNP)

-#    rm(res); gc()  

+#    rm(res); gc()

 #    suppressWarnings(snpCall(callSet)[snp.index, j] <- tmp[["calls"]])

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

 #    callSet$gender[j] <- tmp$gender

@@ -18,9 +18,9 @@

 \begin{document}

 \title{Using \crlmm{} for copy number estimation and genotype calling

-  with Illumina platforms} 

+  with Illumina platforms}

-\date{\today} 

+\date{\today}

 \author{Rob Scharpf}

 \maketitle

@@ -40,10 +40,11 @@ which annotation packages are currently available. Next we create a

 directory where output files will be stored and indicate the directory

 that contains the IDAT files that will be used in our analysis.

+

 <<setup, echo=FALSE, results=hide>>=

 options(width=70)

 options(continue=" ")

-@ 

+@

 <<libraries>>=

 library(ff)

@@ -52,9 +53,9 @@ crlmm:::validCdfNames()

 if(getRversion() < "2.12.0"){

 	rpath <- getRversion()

 } else rpath <- "trunk"

-outdir <- paste("/thumper/ctsa/snpmicroarray/rs/ProcessedData/crlmm/", rpath, "/illumina_vignette", sep="")	

+outdir <- paste("/thumper/ctsa/snpmicroarray/rs/ProcessedData/crlmm/", rpath, "/illumina_vignette", sep="")

 datadir <- "/thumper/ctsa/snpmicroarray/illumina/IDATS/370k"

-@ 

+@

 \paragraph{About this vignette.} This vignette was created using

 Illumina IDAT files that are located in a specific directory on my

@@ -66,7 +67,7 @@ these directories exist.

 <<checkSetup>>=

 if(!file.exists(outdir)) stop("Please specify valid directory for storing output")

 if(!file.exists(pathToCels)) stop("Please specify the correct path to the CEL files")

-@ 

+@

 \paragraph{Preprocessing Illumina IDAT files.}

 To perform copy number analysis on the Illumina platform, several

@@ -95,50 +96,51 @@ from the RG object and added to the \Robject{SnpSet} returned by

 %(Users wanting the \Rpackage{ff} implementation should try

 %\Rfunction{crlmm:::crlmmIllumina2} with the same arguments.)

+

 <<samplesToProcess>>=

 samplesheet = read.csv(file.path(datadir, "HumanHap370Duo_Sample_Map.csv"), header=TRUE, as.is=TRUE)

 samplesheet <- samplesheet[-c(28:46,61:75,78:79), ]

 arrayNames <- file.path(datadir, unique(samplesheet[, "SentrixPosition"]))

 grnfiles = all(file.exists(paste(arrayNames, "_Grn.idat", sep="")))

 redfiles = all(file.exists(paste(arrayNames, "_Red.idat", sep="")))

-@ 

+@

 <<samplesToProcess2, echo=FALSE>>=

-## To speed up repeated calls to Sweave 

+## To speed up repeated calls to Sweave

 RG <- checkExists("RG", .path=outdir,

 		  .FUN=readIdatFiles2,

 		  sampleSheet=samplesheet,

 		  path=dirname(arrayNames[1]),

-		  arrayInfoColNames=list(barcode=NULL, position="SentrixPosition"), 

+		  arrayInfoColNames=list(barcode=NULL, position="SentrixPosition"),

 		  saveDate=TRUE)

 annotation(RG) <- "human370v1c"

 crlmmResult <- checkExists("crlmmResult",

 			   .path=outdir,

 			   .FUN=crlmmIllumina2,

 			   RG=RG,

-			   sns=pData(RG)$ID, 

+			   sns=pData(RG)$ID,

 			   returnParams=TRUE,

 			   cnFile=file.path(outdir, "cnFile.rda"),

 			   snpFile=file.path(outdir, "snpFile.rda"),

 			   save.it=TRUE)

 protocolData(crlmmResult)$ScanDate <- protocolData(RG)$ScanDate

-@ 

+@

 <<samplesToProcess3, eval=FALSE>>=

-RG <- readIdatFiles2(samplesheet[1:10, ], 

-		    path=dirname(arrayNames[1]), 

-		    arrayInfoColNames=list(barcode=NULL, position="SentrixPosition"), 

+RG <- readIdatFiles2(samplesheet[1:10, ],

+		    path=dirname(arrayNames[1]),

+		    arrayInfoColNames=list(barcode=NULL, position="SentrixPosition"),

 		    saveDate=TRUE)

 annotation(RG) <- "human370v1c"

-crlmmResult <- crlmmIllumina2(RG=RG, 

-			     cdfName="human370v1c", 

-			     sns=pData(RG)$ID, 

+crlmmResult <- crlmmIllumina2(RG=RG,

+			     cdfName="human370v1c",

+			     sns=pData(RG)$ID,

 			     returnParams=TRUE,

 			     cnFile=file.path(outdir, "cnFile.rda"),

 			     snpFile=file.path(outdir, "snpFile.rda"),

 			     save.it=TRUE)

 protocolData(crlmmResult)$ScanDate <- protocolData(RG)$ScanDate

-@ 

+@

 %\noindent Finally, we load a few of the intermediate files that were

 %created during the preprocessing and genotyping.

@@ -147,13 +149,13 @@ protocolData(crlmmResult)$ScanDate <- protocolData(RG)$ScanDate

 %res <- get("res")

 %load(file.path(outdir, "cnFile.rda"))

 %cnAB <- get("cnAB")

-%@ 

+%@

 %

 %<<loadIntermediate, echo=FALSE>>=

 %trace(checkExists, browser)

 %res <- checkExists("snpFile", .path=outdir, .FUN=load, file=file.path(outdir, "snpFile.rda"))

 %cnAB <- checkExists("cnFile", .path=outdir, .FUN=load, file=file.path(outdir, "cnFile.rda"))

-%@ 

+%@

 After running the crlmm algorithm, we construct a container for

 storing the quantile normalized intensities, genotype calls, and

@@ -172,11 +174,11 @@ if(!file.exists(file.path(outdir, "cnSet.rda"))){

 				 snpFile=snpFile,

 				 cnFile=cnFile)

 }

-@ 

+@

 <<constructContainer2, eval=FALSE>>=

 container <- constructIlluminaCNSet(crlmmResult=crlmmResult, snpFile=snpFile, cnFile=cnFile)

-@ 

+@

 As described in the \texttt{copynumber} vignette, two \R{} functions

 for copy number estimation are available: \Rfunction{crlmmCopynumber}

@@ -194,11 +196,11 @@ the genotyping and copy number estimation steps.  Here, we use the

 cnSet <- checkExists("cnSet", .path=outdir,

 		     .FUN=crlmmCopynumber,

 		     object=container)

-@ 

+@

 <<estimateCopynumber, eval=FALSE>>=

 cnSet <- crlmmCopynumberLD(container)

-@ 

+@

 %In the following code, we define helper functions to construct a

 %\Robject{featureData} object that chromosome and physical position

@@ -230,12 +232,12 @@ cb <- CB(cnSet)[marker.index, ]/100

 missing.index <- which(rowSums(is.na(ca))==ncol(cnSet))

 ca <- ca[-missing.index, ]

 cb <- cb[-missing.index, ]

-@