@@ -252,3 +252,7 @@ is decoded and scanned

   a) samplesheet5 by get("samplesheet5")

   b) path by get("path")

   c) res by get("res")

+

+2009-08-04 R. Scharpf - committed version 1.3.17

+

+* changed readIdatFiles function to check whether arrayNames is NULL

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

 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: 1.3.16

+Version: 1.3.17

 Date: 2009-07-22

 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>

@@ -819,7 +819,7 @@ thresholdCopyNumberSet <- function(object){

 			       priorProb,

 			       gender=NULL,

 			       SNR,

-			       SNRmin=5, seed=123,

+			       SNRmin, seed=123,

 			       cdfName,

 			       verbose=TRUE, ...){

 	if(missing(cdfName)) stop("cdfName must be provided")

@@ -7,21 +7,23 @@ 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"), 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))) {

-		       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)

+	       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)

@@ -46,17 +48,14 @@ readIdatFiles <- function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

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

        grnidats = file.path(path, grnfiles)

        redidats = file.path(path, redfiles)

-       

        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

+       ## read in the data

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

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

 	       idsG = idsR = G = R = NULL

@@ -68,7 +67,6 @@ readIdatFiles <- function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 	       headerInfo$ChipType[i] = G$ChipType

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

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

-         

 	       if(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

@@ -76,29 +74,23 @@ readIdatFiles <- function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 		       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))

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

 			       ids = idsG

-		       else

-			       stop("Could not find probe IDs")

+		       }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))

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

 			       colnames(tmpmat) = sampleSheet$Sample_ID

-		       else

-			       colnames(tmpmat) = arrayNames

-

-		       RG = new("NChannelSet",

-		       R=tmpmat, G=tmpmat, Rnb=tmpmat, Gnb=tmpmat,

-		       Rse=tmpmat, Gse=tmpmat, annotation=headerInfo$Manifest[1],

-		       phenoData=pd, storage.mode="environment")

+		       }else  colnames(tmpmat) = arrayNames

+		       RG <- new("NChannelSet",

+				 R=tmpmat, G=tmpmat, Rnb=tmpmat, Gnb=tmpmat,

+				 Rse=tmpmat, Gse=tmpmat, annotation=headerInfo$Manifest[1],

+				 phenoData=pd, storage.mode="environment")

 		       rm(tmpmat)

 		       gc()

 	       }

@@ -109,8 +101,7 @@ readIdatFiles <- function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

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

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

 		       }

-	       }

-	       else {

+	       } else {

 		       indG = match(ids, idsG)

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

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

@@ -129,8 +120,7 @@ readIdatFiles <- function(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

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

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

 		       }

-	       }

-	       else {

+	       } else {

 		       indR = match(ids, idsR)

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

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

@@ -14,7 +14,7 @@

 \newcommand{\R}{\textsf{R}}

 \begin{document}

-\title{Trisomy analysis}

+\title{Copy number estimation}

 \date{May, 2009}

 \author{Rob Scharpf}

 \maketitle

@@ -171,7 +171,7 @@ Plot physical position versus copy number for the first sample.  Recall

 that the copy number estimates were multiplied by 100 and stored as an

 integer.

-<<oneSample, fig=TRUE, width=8, height=4, include=FALSE, eval=FALSE>>=

+<<oneSample, fig=TRUE, width=8, height=4, include=FALSE>>=

 par(las=1)

 plot(position(crlmmResults), copyNumber(crlmmResults)[, 1], pch=".", cex=2, xaxt="n", col="grey20", ylim=c(0,6), 

      ylab="copy number", xlab="physical position (Mb)",

@@ -199,7 +199,7 @@ plate. Plotting symbols are the genotype calls (1=AA, 2=AB, 3=BB); light

 grey points are from other plates. One could also add the prediction

 regions for 0-4 copies, but it gets crowded.

-<<genotypeCalls, fig=TRUE, width=8, height=8, include=FALSE, eval=FALSE>>=

+<<genotypeCalls, fig=TRUE, width=8, height=8, include=FALSE>>=

 xlim <- ylim <- c(6.5,13)

 pch <- 21

 colors <- c("red", "blue", "green3")

@@ -221,7 +221,7 @@ for(i in indices[[j]]){

 }

 @ 

-<<predictionRegion, fig=TRUE, width=8, height=8, include=FALSE, eval=FALSE>>=

+<<predictionRegion, fig=TRUE, width=8, height=8, include=FALSE>>=

 require(RColorBrewer)

 greens <- brewer.pal(9, "Greens")

 J <- split(1:ncol(crlmmResults), batch(crlmmResults))