@@ -72,3 +72,4 @@ export(crlmm,

 ##export(initializeParamObject, biasAdjNP2)

+exportMethods(totalCopyNumber)

\ No newline at end of file

@@ -157,12 +157,12 @@ ellipse.CNSet <- function(x, copynumber, batch, ...){

 setMethod("totalCopyNumber",

-	  signature=signature(object="CNSet", ...),

+	  signature=signature(object="CNSet"),

 	  function(object, ...){

 		  is.ff <- is(CA(object), "ff") | is(CA(object), "ffdf")

-		  dotArgs <- names(list(...))

-		  missing.i <- "i" %in% dotArgs

-		  missing.j <- "j" %in% dotArgs

+		  dotArgs <- list(...)

+		  missing.i <- !"i" %in% names(dotArgs)

+		  missing.j <- !"j" %in% names(dotArgs)

 		  if(missing.i & missing.j){

 			  if(is.ff) stop("Must specify i and/or j for ff objects")

 		  }

@@ -173,7 +173,8 @@ setMethod("totalCopyNumber",

 			  snp.index2 <- which(isSnp(object)[i])

 		  } else {

 			  i <- 1:nrow(object)

-			  snp.index2 <- snp.index <- which(isSnp(object))

+			  snp.index <- which(isSnp(object))

+			  snp.index2 <- snp.index

 		  }

 		  if(!missing.j){

 			  j <- dotArgs[["j"]]

@@ -181,8 +182,7 @@ setMethod("totalCopyNumber",

 		  cn.total <- as.matrix(CA(object)[i, j])

 		  if(length(snp.index) > 0){

 			  cb <- as.matrix(CB(object)[snp.index, j])

-			  ##				 snps <- (1:nrow(cn.total))[i %in% snp.index]

-			  cn.total[snp.index2, ] <- cn.total[snp.index, ] + cb

+			  cn.total[snp.index2, ] <- cn.total[snp.index2, ] + cb

 		  }

 		  cn.total <- cn.total/100

 		  return(cn.total)

@@ -319,6 +319,8 @@ genotypeConf <- integerScoreToProbability(snpCallProbability(x)[snp.index[1:10],

 Allele-specific copy number at polymorphic loci:

 <<ca>>=

 ca <- CA(x[snp.index, ])/100

+cb <- CB(x[snp.index, ])/100

+ct <- ca+cb

 @

 Total copy number at nonpolymorphic loci:

@@ -328,9 +330,9 @@ cn.nonpolymorphic <- CA(x[np.index, ])/100

 Total copy number at both polymorphic and nonpolymorphic loci:

 <<totalCopynumber>>=

-path <- system.file("scripts", package="crlmm")

-source(file.path(path, "helperFunctions.R"))

-cn <- totalCopyNumber(x, i=c(snp.index, np.index))

+##path <- system.file("scripts", package="crlmm")

+##source(file.path(path, "helperFunctions.R"))

+cn <- crlmm:::totalCopyNumber(x, i=c(snp.index, np.index))

 apply(cn, 2, median, na.rm=TRUE)

 @

@@ -251,23 +251,27 @@ cb <- cb[-missing.index, ]

 \noindent Negating the \Robject{isSnp} function could be used to

 extract the estimates at nonpolymorphic markers. For instance,

 <<monomorphic-accessor>>=

-cn.monomorphic <- CA(cnSet)[which(chromosome(cnSet) == 21 & !isSnp(cnSet)), ]/100

+np.index <- which(chromosome(cnSet) == 21 & !isSnp(cnSet))

+cn.monomorphic <- CA(cnSet)[np.index, ]/100

 @

 At polymorphic loci, the total copy number is the sum of the number of

 copies of the A allele and the number of copies for the B allele.  At

 nonpolymorphic loci, the total copy number is the number of copies for

-the A allele.  The helper function totalCopyNumber can be used to

-extract the total copy number for all polymorphic and nonpolymorphic

-markers.  Documentation of the \Rfunction{totalCopyNumber} will be

-available in the devel version of the \Rpackage{oligoClasses}.

+the A allele.  The helper function \Rfunction{totalCopyNumber} can be

+used to extract the total copy number for all polymorphic and

+nonpolymorphic markers.  Documentation of the

+\Rfunction{totalCopyNumber} will be available in the devel version of

+the \Rpackage{oligoClasses}.

-<<copyNumberHelper>>=

+<<totalCopyNumber>>=

 cn.total <- ca+cb

-cn.total2 <- totalCopyNumber(cnSet, i=marker.index)

+cn.total2 <- crlmm:::totalCopyNumber(cnSet, i=marker.index)

 cn.total2 <- cn.total2[-missing.index, ]

-dimnames(cn.total) <- NULL

-all.equal(cn.total2, cn.total)

+stopifnot(all.equal(cn.total2, cn.total))

+

+cn.monomorphic2 <- totalCopyNumber(cnSet, i=np.index)

+stopifnot(all.equal(cn.monomorphic, cn.monomorphic2))

 @

 A few simple visualizations may be helpful at this point. The first

@@ -322,40 +326,6 @@ axis(1, at=pretty(x), labels=pretty(x/1e6))

 mtext("Mb", 1, outer=TRUE, line=2)

 @

-%Next we remove some of the waves using \Rpackage{limma}'s function

-%\Rfunction{loessFit}.

-%<<wavecorrection, fig=TRUE>>=

-%require(limma)

-%par(mfrow=c(2,2), las=1, mar=c(0.5, 4, 0.5, 0.5), oma=c(4, 1, 1,1))

-%for(j in c(low.snr, high.snr)){

-%	y <- copyNumber(cnSet)[chromosome(cnSet) == 1, j]/100

-%	missing <- is.na(y)

-%	x <- x[!missing]

-%	y <- y[!missing]

-%	dist <- diff(x)

-%	index <- c(0, cumsum(log10(dist) > 6))

-%	x.split <- split(x, index)

-%	y <- as.numeric(runmed(y, k=3))

-%	y.split <- split(y, index)

-%	y.smooth <- vector("list", length(y.split))

-%	for(i in seq_along(y.smooth)){

-%		fit <- loessFit(y=y.split[[i]], x= x.split[[i]], span=0.3)

-%		y.smooth[[i]] <- 2+fit$residuals

-%	}

-%	plot(unlist(x.split),

-%	     unlist(y.split),

-%	     pch=".", ylab="copy number", xaxt="n", log="y", ylim=c(0.5,5))

-%	plot(unlist(x.split),

-%	     unlist(y.smooth),

-%	     pch=".", ylab="copy number", xaxt="n", log="y", ylim=c(0.5,5), yaxt="n")

-%	legend("topright", bty="n", legend=paste("SNR =", round(cnSet$SNR[j], 1)))

-%	abline(h=2, col="grey70")

-%	if(j == high.snr){

-%		axis(1, at=pretty(x), labels=pretty(x/1e6))

-%		mtext("Mb", 1, outer=TRUE, line=2)

-%	}

-%}

-%@

 \section{Session information}

 <<sessionInfo, results=tex>>=

 toLatex(sessionInfo())