@@ -57,6 +57,7 @@ importFrom(ff, ffdf, physical.ff, physical.ffdf)

 exportClasses(CNSetLM, ffdf, list)

 exportMethods(open, "[", show, lM, lines, nu, phi, corr, sigma2, tau2)

+exportMethods(CA, CB)

 export(crlmm, 

        crlmmCopynumber, 

        crlmmIllumina, 

@@ -73,8 +74,9 @@ export(crlmm,

        crlmmCopynumber2, crlmmCopynumberLD)

 export(constructIlluminaCNSet)

 export(linesCNSetLM)

-export(linearModel.noweights, computeCN, fit.lm1, fit.lm2, fit.lm3, fit.lm4, construct,

+export(computeCN, fit.lm1, fit.lm2, fit.lm3, fit.lm4, construct,

        dqrlsWrapper, nuphiAllele)

+export(computeCopynumber)

@@ -406,32 +406,6 @@ fit.wls <- function(allele, Ystar, W, Ns, autosome=TRUE){

 	return(betahat)

 }

-## linear regression without weights -- design matrix is same for all snps

-linearModel.noweights <- function(allele, Ystar, W, Ns){

-	complete <- rowSums(is.na(W)) == 0 

-	if(any(!is.finite(W))){## | any(!is.finite(V))){

-		i <- which(rowSums(!is.finite(W)) > 0)

-		stop("Possible zeros in the within-genotype estimates of the spread (vA, vB). ")

-	}

-	NOHET <- mean(Ns[, 2], na.rm=TRUE) < 0.05

-	if(missing(allele)) stop("must specify allele")

-	if(allele == "A") X <- cbind(1, 2:0) else X <- cbind(1, 0:2)

-	if(NOHET) X <- X[-2, ] ##more than 1 X chromosome, but all homozygous		

-	##How to quickly generate Xstar, Xstar = diag(W) %*% X

-	Xstar <- apply(W, 1, generateX, X)

-	IXTX <- apply(Xstar, 2, generateIXTX, nrow=nrow(X))

-	betahat <- matrix(NA, 2, nrow(Ystar))

-	ses <- matrix(NA, 2, nrow(Ystar))

-	for(i in 1:nrow(Ystar)){

-		betahat[, i] <- crossprod(matrix(IXTX[, i], ncol(X), ncol(X)), crossprod(matrix(Xstar[, i], nrow=nrow(X)), Ystar[i, ]))

-		ssr <- sum((Ystar[i, ] - matrix(Xstar[, i], nrow(X), ncol(X)) %*% matrix(betahat[, i], ncol(X), 1))^2)

-		ses[, i] <- sqrt(diag(matrix(IXTX[, i], ncol(X), ncol(X)) * ssr))

-	}

-	nu <- betahat[1, ]

-	phi <- betahat[2, ]

-	return(list(nu, phi))

-}

-

 ##nuphiAlleleX <- function(allele, Ystar, W, Ns, chrX=FALSE){

 ##	complete <- rowSums(is.na(W)) == 0 

 ##	if(any(!is.finite(W))){## | any(!is.finite(V))){

@@ -1865,7 +1839,7 @@ nonpolymorphic <- function(object, cnOptions, tmp.objects){

 			nuA <- getParam(object, "nuA", batch)

 			phiA <- getParam(object, "phiA", batch)

 		}

-		CA(object)[!isSnp(object), ] <- 1/phiA[!isSnp(object)]*(A - nuA[!isSnp(object)])

+		##CA(object)[!isSnp(object), ] <- 1/phiA[!isSnp(object)]*(A - nuA[!isSnp(object)])

 		sig2A <- getParam(object, "sig2A", batch)

 		sig2A[!isSnp(object)] <- rowMAD(log2(A*normal), na.rm=TRUE)^2

 		object <- pr(object, "sig2A", batch, sig2A)

@@ -93,7 +93,7 @@ setMethod("computeCopynumber", "CNSet",

 				    THR.NU.PHI=THR.NU.PHI,

 				    thresholdCopynumber=thresholdCopynumber)

 	bias.adj <- cnOptions[["bias.adj"]]

-	if(bias.adj & all(is.na(nu(object, "A")[, 1])){

+	if(bias.adj & all(is.na(fData(object)$nuA_1))){

 		cnOptions[["bias.adj"]] <- FALSE

 	}

 	object <- computeCopynumber.CNSet(object, cnOptions)				

@@ -237,3 +237,11 @@ setMethod("corr", c("CNSetLM", "character"), function(object, allele){

 	return(res)

 })

+setMethod("CB", "CNSet", function(object){

+	##assayDataElement(object, "CB")

+	browser()

+})

+setMethod("CA", "CNSet", function(object) {

+	browser()

+	##assayDataElement(object, "CA")

+})