@@ -1,3 +1,4 @@

+.auto*

 test/*

 myCrlmmGT2.Rnw

 ffobjs*

new file mode 100644

Binary files /dev/null and b/data/sample.CNSet.rda differ

deleted file mode 100644

Binary files a/data/sample.CNSetLM.rda and /dev/null differ

@@ -77,10 +77,8 @@ log-scale the variance is rougly constant for CA, CB > 0).

 }

 \examples{

-data(sample.CNSetLM)

-## update to class CNSet

-cnSet <- as(sample.CNSetLM, "CNSet")

-## All NAs. Need to replace sample.CNSetLM with a HapMap example

+data(sample.CNSet)

+## All NAs. Need to replace sample.CNSet with a HapMap example

 Ns(cnSet, i=1:5, j=1:2)

 corr(cnSet, i=1:5, j=1:2)

 medians(cnSet, i=1:5, j=1:2)

@@ -78,10 +78,7 @@ rawCopynumber(object,...)

 \examples{

 ## Version 1.6* of crlmm used CNSetLM objects.

-data(sample.CNSetLM)

-

-## To update to class CNSet, use

-cnSet <- as(sample.CNSetLM, "CNSet")

+data(sample.CNSet)

 all(isCurrent(cnSet)) ## is the cnSet object current?

 ## --------------------------------------------------

similarity index 53%

rename from man/sample.CNSetLM.Rd

rename to man/sample.CNSet.Rd

@@ -1,63 +1,34 @@

-\name{sample.CNSetLM}

-\alias{sample.CNSetLM}

+\name{sample.CNSet}

+\alias{sample.CNSet}

 \docType{data}

 \title{

-	Dataset of class 'CNSetLM'

+	Object of class 'CNSet'

 }

 \description{

-	The data for 2119 polymorphic and nonpolymorphic markers on

-	chromosome 1 for the CEPH and Yoruban HapMap samples.

+	The data for the first 16 polymorphic markers in the HapMap analysis.

 }

-\usage{data(sample.CNSetLM)}

+\details{

+  This object was created from the copynumber vignette in inst/scripts.

+}

+\usage{data(sample.CNSet)}

 \format{

-

-	This class has been deprecated.  See example below for how to

-	update an existing 'CNSetLM' object to class 'CNSet'.

-

-	The data illustrates the \code{CNSetLM-class}, with

+  The data illustrates the \code{CNSet-class}, with

 	\code{assayData} containing the quantile-normalized

 	intensities for the A and B alleles, genotype calls and

-	confidence scores (call and callProbability), and

-	allele-specific copy number (CA and CB). The parameters from

-	the linear model are stored in the lM slot.

+	confidence scores.  New slots that specific to copy number

+	estimation are \code{batch} and \code{batchStatistics}.

 }

 \examples{

-## class CNSetLM has been deprecated

-data(sample.CNSetLM)

-## update to class CNSet

-cnSet <- as(sample.CNSetLM, "CNSet")

-all(isCurrent(cnSet)) ## is the cnSet object current?

-##subsetting

-cnSet2 <- cnSet[, 1:5]

-stopifnot(batchNames(cnSet2) == "C")

-\dontrun{

-	## updating class CNSetLM using ff objects

-	## a bigger object with multiple batches

-	if(require(ff)){

-		outdir <- "/amber1/scratch/rscharpf/jss/hapmap2"

-		load(file.path(outdir, "container.rda"))

-		container <- object; rm(object); gc()

-		container2 <- as(container, "CNSet")

-		all(isCurrent(container2))

-		## test replacement methods, subset methods

-		table(batch(container2))

-		##generates warning ... would need open, close in the '[' method

-		invisible(open(nuA(container2)))

-		xx <- nu(container2, "A")[1:5, ]

-		nuA(container2)[1:5, ] <- xx

-		invisible(close(nuA(container2)))

-	}

-}

+data(sample.CNSet)

 ## --------------------------------------------------

 ## accessors for the feature-level info

 ## --------------------------------------------------

 chromosome(cnSet)[1:5]

 position(cnSet)[1:5]

 isSnp(cnSet)[1:5]

-## 980 nonpolymorphic markers and 1139 polymoprhic markers

 table(isSnp(cnSet))

 ## --------------------------------------------------

 ## sample-level statistics computed by crlmm

@@ -71,14 +42,9 @@ cnSet$SKW[1:5]

 ## the gender (gender is imputed unless specified in the call to crlmm)

 table(cnSet$gender)  ## 1=male, 2=female

 ## --------------------------------------------------

-## --------------------------------------------------

-##

-## accessors for parameters estimated from the linear model for copy

-## number (note that the parameters have dimension R x C, where R

-## corresponds to the number of features and C corresponds to the

-## number of batches)

+## batchStatistics

 ## -------------------------------------------------- estimate of

-## background

+## intercept from linear model

 dim(nu(cnSet, "A"))

 ## background for the A allele in the 2 batches for the

 ## first 5 markers

@@ -123,14 +89,5 @@ all.equal(cn4, cn2)

 cn5 <- totalCopynumber(cnSet, i=1:5)

 ## all markers, samples 1-5

 cn6 <- totalCopynumber(cnSet, j=1:5)

-

-## NOTE: subsetting the object before extracting copy number

-##       can be very inefficient when the data set is very large,

-##       particularly if using ff objects.  IN particular, subsetting

-##       the CNSet object will subset all of the assay data elements

-##       and all of the elements in the LinearModelParameter slot

-\dontrun{

-	cnsubset <- cnSet[1:5, ]

-}

 }

 \keyword{datasets}