@@ -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: 1.9.22

+Version: 1.9.23

 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>

@@ -99,22 +99,7 @@ construct <- function(filenames,

 	return(cnSet)

 }

-genotype <- function(filenames,

-		     cdfName,

-		     batch,

-		     mixtureSampleSize=10^5,

-		     eps=0.1,

-		     verbose=TRUE,

-		     seed=1,

-		     sns,

-		     probs=rep(1/3, 3),

-		     DF=6,

-		     SNRMin=5,

-		     recallMin=10,

-		     recallRegMin=1000,

-		     gender=NULL,

-		     returnParams=TRUE,

-		     badSNP=0.7){

+constructAffy <- function(filenames, sns, cdfName, batch, verbose=TRUE){

 	is.lds <- ifelse(isPackageLoaded("ff"), TRUE, FALSE)

 	if(!is.lds) stop("this function now requires that the ff package be loaded")

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

@@ -139,8 +124,8 @@ genotype <- function(filenames,

 	gns <- getVarInEnv("gns")

 	rm(list=obj, envir=.crlmmPkgEnv)

 	rm(obj)

-	if(verbose) message("Initializing objects.")

-	mixtureParams <- initializeBigMatrix("crlmmMixt-", 4, length(filenames), "double")

+	if(verbose) message("Initializing ff objects.")

+	##mixtureParams <- initializeBigMatrix("crlmmMixt-", 4, length(filenames), "double")

 	SNR <- initializeBigVector("crlmmSNR-", length(filenames), "double")

 	SKW <- initializeBigVector("crlmmSKW-", length(filenames), "double")

 	genderff <- initializeBigVector("gender", length(filenames), "integer")

@@ -148,30 +133,16 @@ genotype <- function(filenames,

 	nr <- nrow(featureData); nc <- length(sns)

 	A <- initializeBigMatrix("crlmmA-", nr, length(filenames), "integer")

 	B <- initializeBigMatrix("crlmmB-", nr, length(filenames), "integer")

+	call <- initializeBigMatrix("call-", nr, length(filenames), "integer")

+	callPr <- initializeBigMatrix("callPr-", nr, length(filenames), "integer")

 	rownames(A) <- rownames(B) <- featureNames(featureData)

-	sampleBatches <- splitIndicesByNode(seq(along=filenames))

-	if(verbose) message("Processing ", length(filenames), " files.")

-	ocLapply(sampleBatches, rsprocessCEL, filenames=filenames,

-		 fitMixture=TRUE, A=A, B=B, SKW=SKW, SNR=SNR,

-		 mixtureParams=mixtureParams, eps=eps, seed=seed,

-		 mixtureSampleSize=mixtureSampleSize, pkgname=pkgname,

-		 neededPkgs=c("crlmm", pkgname))

-	## Now we initialize a CNSet object, cloning A and B

-	if(verbose) message("Cloning A and B matrices to store genotype calls and confidence scores.")

-	## The clones will be used to store calls and confidence scores

-	open(A)

-	open(B)

-	##user do

-	## options("ffbatchbytes"=XXX) to make this efficient

-	call <- clone(A)

-	callProbability=clone(B)

-	close(A)

-	close(B)

+	rownames(call) <- rownames(callPr) <- featureNames(featureData)

+	if(verbose) message("Instantiating CNSet container")

 	cnSet <- new("CNSet",

 		     alleleA=A,

 		     alleleB=B,

 		     call=call,

-		     callProbability=callProbability,

+		     callProbability=callPr,

 		     featureData=featureData,

 		     annotation=cdfName,

 		     batch=batch)

@@ -190,26 +161,152 @@ genotype <- function(filenames,

 	cnSet$SNR <- SNR

 	cnSet$gender <- genderff

 	stopifnot(validObject(cnSet))

-	snp.I <- isSnp(cnSet)

-	snp.index <- which(snp.I)

-	##pData(cnSet)$SKW <- SKW

-	##pData(cnSet)$SNR <- SNR

-	np.index <- which(!snp.I)

-	if(verbose) message("Normalizing nonpolymorphic markers")

-	FUN <- ifelse(is.lds, "cnrma2", "cnrma")

-	if(verbose) message("Quantile normalizing nonpolymorphic markers")

-	cnrma2(A=A(cnSet),

-	       filenames=filenames,

-	       row.names=featureNames(cnSet)[np.index],

-	       cdfName=cdfName,

-	       sns=sampleNames(cnSet),

-	       seed=seed,

-	       verbose=verbose)

+	return(cnSet)

+}

+

+snprmaAffy <- function(cnSet, filenames,

+		       mixtureSampleSize=10^5,

+		       eps=0.1,

+		       seed=1,

+		       verbose=TRUE){

+	if(verbose) message("Preprocessing ", length(filenames), " files.")

+	pkgname <- getCrlmmAnnotationName(annotation(cnSet))

+	stopifnot(require(pkgname, character.only=TRUE, quietly=!verbose))

+	mixtureParams <- initializeBigMatrix("crlmmMixt-", 4, length(filenames), "double")

+	sampleBatches <- splitIndicesByNode(seq(along=filenames))

+	ocLapply(sampleBatches, rsprocessCEL, filenames=filenames,

+		 fitMixture=TRUE, A=A(cnSet), B=B(cnSet), C=calls(cnSet),

+		 D=snpCallProbability(cnSet),

+		 SKW=cnSet$SKW, SNR=cnSet$SNR,

+		 mixtureParams=mixtureParams, eps=eps, seed=seed,

+		 mixtureSampleSize=mixtureSampleSize, pkgname=pkgname,

+		 neededPkgs=c("crlmm", pkgname))

+	if(verbose) message("Cloning A and B matrices to store genotype calls and confidence scores.")

+	return(mixtureParams)

+}

+genotype <- function(filenames,

+		     cdfName,

+		     batch,

+		     mixtureSampleSize=10^5,

+		     eps=0.1,

+		     verbose=TRUE,

+		     seed=1,

+		     sns,

+		     probs=rep(1/3, 3),

+		     DF=6,

+		     SNRMin=5,

+		     recallMin=10,

+		     recallRegMin=1000,

+		     gender=NULL,

+		     returnParams=TRUE,

+		     badSNP=0.7){

+##	is.lds <- ifelse(isPackageLoaded("ff"), TRUE, FALSE)

+##	if(!is.lds) stop("this function now requires that the ff package be loaded")

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

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

+##	if(missing(sns)) sns <- basename(filenames)

+##	stopifnot(!missing(batch))

+##	##---------------------------------------------------------------------------

+##	##

+##	## from snprma2.  Goal is to initialize A and B with

+##	## appropriate dimension for snps+nps

+##	##

+##	##---------------------------------------------------------------------------

+##	if (missing(sns)) sns <- basename(filenames)

+##	if (missing(cdfName))

+##		cdfName <- read.celfile.header(filenames[1])[["cdfName"]]

+##	pkgname <- getCrlmmAnnotationName(cdfName)

+##	stopifnot(require(pkgname, character.only=TRUE, quietly=!verbose))

+##	if(verbose) message("Loading annotations and mixture model parameters.")

+##	obj <- loader("preprocStuff.rda", .crlmmPkgEnv, pkgname)

+##	pnsa <- getVarInEnv("pnsa")

+##	pnsb <- getVarInEnv("pnsb")

+##	gns <- getVarInEnv("gns")

+##	rm(list=obj, envir=.crlmmPkgEnv)

+##	rm(obj)

+##	if(verbose) message("Initializing objects.")

+##	mixtureParams <- initializeBigMatrix("crlmmMixt-", 4, length(filenames), "double")

+##	SNR <- initializeBigVector("crlmmSNR-", length(filenames), "double")

+##	SKW <- initializeBigVector("crlmmSKW-", length(filenames), "double")

+##	genderff <- initializeBigVector("gender", length(filenames), "integer")

+##	featureData <- getFeatureData(cdfName, copynumber=TRUE)

+##	nr <- nrow(featureData); nc <- length(sns)

+##	A <- initializeBigMatrix("crlmmA-", nr, length(filenames), "integer")

+##	B <- initializeBigMatrix("crlmmB-", nr, length(filenames), "integer")

+##	rownames(A) <- rownames(B) <- featureNames(featureData)

+##	sampleBatches <- splitIndicesByNode(seq(along=filenames))

+##	if(verbose) message("Processing ", length(filenames), " files.")

+##	ocLapply(sampleBatches, rsprocessCEL, filenames=filenames,

+##		 fitMixture=TRUE, A=A, B=B, SKW=SKW, SNR=SNR,

+##		 mixtureParams=mixtureParams, eps=eps, seed=seed,

+##		 mixtureSampleSize=mixtureSampleSize, pkgname=pkgname,

+##		 neededPkgs=c("crlmm", pkgname))

+##	## Now we initialize a CNSet object, cloning A and B

+##	if(verbose) message("Cloning A and B matrices to store genotype calls and confidence scores.")

+##	## The clones will be used to store calls and confidence scores

+##	open(A)

+##	open(B)

+##	##user do

+##	## options("ffbatchbytes"=XXX) to make this efficient

+##	call <- clone(A)

+##	callProbability=clone(B)

+##	close(A)

+##	close(B)

+##	cnSet <- new("CNSet",

+##		     alleleA=A,

+##		     alleleB=B,

+##		     call=call,

+##		     callProbability=callProbability,

+##		     featureData=featureData,

+##		     annotation=cdfName,

+##		     batch=batch)

+##	if(!missing(sns)){

+##		sampleNames(cnSet) <- sns

+##	} else {

+##		sampleNames(cnSet) <- basename(filenames)

+##	}

+##	protocolData <- getProtocolData.Affy(filenames)

+##	rownames(pData(protocolData)) <- sns

+##	protocolData(cnSet) <- protocolData

+##	##pd <- data.frame(matrix(NA, nc, 3), row.names=sns)

+##	##colnames(pd)=c("SKW", "SNR", "gender")

+##	##phenoData(cnSet) <- new("AnnotatedDataFrame", data=pd)

+##	cnSet$SKW <- SKW

+##	cnSet$SNR <- SNR

+##	cnSet$gender <- genderff

+##	save(cnSet, file=file.path(ldPath(), "cnSet.rda"))

+##	stopifnot(validObject(cnSet))

+	cnSet <- constructAffy(filenames=filenames,

+			       cdfName=cdfName,

+			       batch=batch, verbose=verbose)

+	mixtureParams <- snprmaAffy(cnSet, filenames=filenames,

+				    mixtureSampleSize=mixtureSampleSize,

+				    eps=eps,

+				    seed=seed,

+				    verbose=verbose)

+	ok <- cnrmaAffy(cnSet=cnSet, filenames=filenames, seed=seed,

+			verbose=verbose)

+	stopifnot(ok)

+	ok <- genotypeAffy(cnSet=cnSet, mixtureParams=mixtureParams,

+			   SNRMin=SNRMin, recallMin=recallMin,

+			   recallRegMin=recallRegMin,

+			   gender=gender,

+			   badSNP=badSNP,

+			   returnParams=returnParams,

+			   verbose=verbose)

+	return(cnSet)

+}

+

+genotypeAffy <- function(cnSet, mixtureParams, SNRMin=5, recallMin=10,

+			 recallRegMin=1000,

+			 gender=NULL, badSNP=0.7, returnParams=TRUE,

+			 verbose=TRUE){

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

 	tmp <- crlmmGT2(A=calls(cnSet),

 			B=snpCallProbability(cnSet),

-			SNR=SNR,

+			SNR=cnSet$SNR,

 			mixtureParams=mixtureParams,

-			cdfName=cdfName,

+			cdfName=annotation(cnSet),

 			row.names=NULL,

 			col.names=sampleNames(cnSet),

 			SNRMin=SNRMin,

@@ -224,10 +321,25 @@ genotype <- function(filenames,

 	open(cnSet$gender)

 	cnSet$gender[,] <- tmp[["gender"]]

 	close(cnSet$gender)

-	return(cnSet)

+	return(TRUE)

+}

+

+cnrmaAffy <- function(cnSet, filenames, seed=1, verbose=TRUE){

+	snp.I <- isSnp(cnSet)

+	snp.index <- which(snp.I)

+	np.index <- which(!snp.I)

+	if(verbose) message("Quantile normalizing nonpolymorphic markers")

+	cnrma2(A=A(cnSet),

+	       filenames=filenames,

+	       row.names=featureNames(cnSet)[np.index],

+	       cdfName=cdfName,

+	       sns=sampleNames(cnSet),

+	       seed=seed,

+	       verbose=verbose)

+	TRUE

 }

-rsprocessCEL <- function(i, filenames, fitMixture, A, B, SKW, SNR,

+rsprocessCEL <- function(i, filenames, fitMixture, A, B, C, D, SKW, SNR,

 			 mixtureParams, eps, seed, mixtureSampleSize,

 			 pkgname){

 	obj1 <- loader("preprocStuff.rda", .crlmmPkgEnv, pkgname)

@@ -254,6 +366,8 @@ rsprocessCEL <- function(i, filenames, fitMixture, A, B, SKW, SNR,

 	open(A)

 	open(B)

+	open(C)

+	open(D)

 	open(SKW)

 	open(mixtureParams)

 	open(SNR)

@@ -270,6 +384,8 @@ rsprocessCEL <- function(i, filenames, fitMixture, A, B, SKW, SNR,

 		## RS: add index for row assignment

 		A[index, k] <- intMedianSummaries(y[aIndex, 1, drop=FALSE], pnsa)

 		B[index, k] <- intMedianSummaries(y[bIndex, 1, drop=FALSE], pnsb)

+		C[index, k] <- intMedianSummaries(y[aIndex, 1, drop=FALSE], pnsa)

+		D[index, k] <- intMedianSummaries(y[bIndex, 1, drop=FALSE], pnsb)

 		rm(y)

 		if(fitMixture){

 			S <- (log2(A[idx,k])+log2(B[idx, k]))/2 - SMEDIAN

@@ -25,7 +25,7 @@ crlmmGT2 <- function(A, B, SNR, mixtureParams, cdfName, row.names=NULL,

 	}

 	snpBatches <- splitIndicesByLength(index, ocProbesets())

 	NR <- length(unlist(snpBatches))

-	if(verbose) cat("Calling", NR, "SNPs for recalibration... ")

+	if(verbose) message("Calling ", NR, " SNPs for recalibration... ")

 	NC <- ncol(A)

 	##

 	if(verbose) message("Loading annotations.")

@@ -61,7 +61,6 @@ crlmmGT2 <- function(A, B, SNR, mixtureParams, cdfName, row.names=NULL,

 	cIndexes <- list(keepIndex,

 			 keepIndex[which(gender[keepIndex]==2)],

 			 keepIndex[which(gender[keepIndex]==1)])

-	if(verbose) cat("Calling", NR, "SNPs for recalibration... ")

 	## call C

 	fIndex <- which(gender==2)

 	mIndex <- which(gender==1)

@@ -101,6 +100,7 @@ crlmmGT2 <- function(A, B, SNR, mixtureParams, cdfName, row.names=NULL,

 		tmp

 	}

 	##

+	if(verbose) message("Calling process1")

 	newparamsBatch <- ocLapply(seq(along=snpBatches), process1,

 				   snpBatches=snpBatches,

 				   autosomeIndex=autosomeIndex, XIndex=XIndex,

@@ -1,10 +1,34 @@

 \name{NEWS}

 \title{News for Package 'crlmm'}

-\section{Changes in version 1.10}{

+

+\section{Changes in version 1.9}{

   \subsection{USER VISIBLE CHANGES}{

     \itemize{

       \item Using NEWS.Rd

+

+      \item batch slot in CNSet objects is class 'character'

+      (previously, class was 'factor')

+

+      \item the ff package is required for preprocessing and genotyping

+      prior to copy number analyses with the crlmmCopynumber function.

+

+      \item We have added several vignettes pertaining to copy number

+      analyses in the crlmm package: CopyNumberOverview,

+      AffymetrixPreprocessCN, IlluminaPreprocessCN, and Infrastructure.

+      The 'copynumber' and 'Infrastructure' vignettes are applicable to

+      both the Illumina and Affymetrix platforms. The CopyNumberOverview

+      vignette gives a brief summary of the available vignettes for copy

+      number analyses.

+

+      \item Exporting function constructInf, preprocessInf, and

+      genotypeInf for preprocessing and genotyping Illumina files prior

+      to copy number analyses.  The genotype.Illumina function is now a

+      wrapper for these functions.

+

+      \item additional documentation for crlmm is provided in a

+      compendium: http://www.biostat.jhsph.edu/~rscharpf/crlmmCompendium/index.html

+

     }

   }

 }

@@ -37,7 +61,7 @@

  	  elements of this object, including featureNames,

  	  sampleNames, and '['.

 	}

-	

+

         \item 'CopyNumberSet': contains locus-level estimates of copy

   	number for SNPs and polymorphic probes.

 	\enumerate{

@@ -47,7 +71,7 @@

 	  \item For nonpolymorphic probes, the total copy number is

           stored in the 'CA' slot and a NA is recorded for the

-          corresponding row in the CB matrix. 

+          corresponding row in the CB matrix.

 	  \item Useful methods: 'copyNumber', 'ellipse', 'points'

 	}

@@ -60,4 +84,5 @@

      'CrlmmSetList' and returns an object of class 'CopyNumberSet'.

     }

   }

+

 }