@@ -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: 1.11.27

+Version: 1.11.28

 Date: 2010-12-10

 Author: Benilton S Carvalho <Benilton.Carvalho@cancer.org.uk>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.edu.au>, Ingo Ruczinski <iruczins@jhsph.edu>, Rafael A Irizarry

 Maintainer: Benilton S Carvalho <Benilton.Carvalho@cancer.org.uk>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU>

@@ -2675,15 +2675,25 @@ posteriorMean.snp <- function(stratum, object, index.list, CN,

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

 ##}

-genotypes <- function(copyNumber){

+genotypes <- function(copyNumber, is.snp=TRUE){

 	stopifnot(copyNumber %in% 0:4)

 	cn <- paste("x", copyNumber, sep="")

-	switch(cn,

-	       x0="NULL",

-	       x1=LETTERS[1:2],

-	       x2=c("AA", "AB", "BB"),

-	       x3=c("AAA", "AAB", "ABB", "BBB"),

-	       x4=c("AAAA", "AAAB", "AABB", "ABBB", "BBBB"))

+	if(is.snp){

+		res <- switch(cn,

+			      x0="NULL",

+			      x1=LETTERS[1:2],

+			      x2=c("AA", "AB", "BB"),

+			      x3=c("AAA", "AAB", "ABB", "BBB"),

+			      x4=c("AAAA", "AAAB", "AABB", "ABBB", "BBBB"))

+	} else {

+		res <- switch(cn,

+			      x0="NULL",

+			      x1="A",

+			      x2="AA",

+			      x3="AAA",

+			      x4="AAAA")

+	}

+	return(res)

 }

 dbvn <- function(x, mu, Sigma){

@@ -446,5 +446,9 @@ setMethod("xyplotcrlmm", signature(x="formula", data="CNSet", predictRegion="lis

 	  })

 setMethod("xyplot", signature(x="formula", data="CNSet"),

 	  function(x, data, ...){

-		  xyplotcrlmm(x, data, ...)

+		  if("predictRegion" %in% names(list(...))){

+			  xyplotcrlmm(x, data, ...)

+		  } else{

+			  callNextMethod()

+		  }

 })

@@ -74,11 +74,12 @@ rawCopynumber(object,...)

 Subsetting the \code{CNSet} object before extracting copy number can be

 very inefficient when the data set is very large, particularly if using

-ff objects.  The \code{[] method will subset all of the assay data

+ff objects.  The \code{[} method will subset all of the assay data

 elements and all of the elements in the LinearModelParameter slot.

 }

+

 \seealso{

 	\code{\link{crlmmCopynumber}}, \code{\link{CNSet-class}}

@@ -8,12 +8,15 @@

   The possible genotypes for an integer copy number (0-4).

 }

 \usage{

-genotypes(copyNumber)

+genotypes(copyNumber, is.snp=TRUE)

 }

 \arguments{

   \item{copyNumber}{

     Integer (0-4 allowed).}

+

+  \item{is.snp}{Logical. If TRUE, possible genotypes for a polymorphic

+    SNP is returned. If FALSE, only monomorphic genotypes returned.}

 }

 \value{

@@ -27,6 +30,7 @@ R. Scharpf

 \examples{

 for(i in 0:4) print(genotypes(i))

+for(i in 0:4) print(genotypes(i, FALSE))

 }

@@ -110,7 +110,7 @@ all.equal(cn4, cn2)

 ## markers 1-5, all samples

 cn5 <- totalCopynumber(sample.CNSet, i=1:5)

-## all markers, samples 1-5

-cn6 <- totalCopynumber(sample.CNSet, j=1:5)

+## all markers, samples 1-2

+cn6 <- totalCopynumber(sample.CNSet, j=1:2)

 }

 \keyword{datasets}

@@ -78,10 +78,22 @@ xyplot(B~A|snpid, data=sample.CNSet2[1:10, sample.index],

 ## nonpolymorphic markers

-np.index <- which(!isSnp(sample.CNSet2))

-sample.index <- which(batch(sample.CNSet2) %in% bns)

-pr <- predictionRegion(sample.CNSet2[np.index, sample.index], copyNumber=0:4)

+data(sample.CNSet2)

+tab <- table(batch(sample.CNSet2))

+bns <- names(tab)[tab > 50]

+sample.index <- which(batch(sample.CNSet2) %in% bns[1:3])

+np.index <- which(!isSnp(sample.CNSet2))[1:10]

+taus <- tau2(sample.CNSet)[np.index, , , ]

+trace(predictionRegion, browser, signature=c("CNSet", "integer"))

+pr <- predictionRegion(sample.CNSet2[np.index, sample.index],

+		       copyNumber=0:4)

+trace(posteriorProbability, browser, signature="CNSet")

+pp <- posteriorProbability(sample.CNSet2[np.index, sample.index],

+			   predictRegion=pr,

+			   copyNumber=0:4)

+pm <- calculatePosteriorMean(sample.CNSet2[np.index, sample.index], posteriorProb=pp)

+

 }

 \keyword{dplot}

-\keyword{hplot}

\ No newline at end of file

+\keyword{hplot}