@@ -1443,8 +1443,8 @@ fit.lm4 <- function(idxBatch,

 			nu1[pseudoAR] <- 2^(mus[pseudoAR, 1]) - 2*phi1[pseudoAR]

 		}

-		normal.f <- NORM.np[, k]

-		A.F <- A.F*normal.f[, gend==2]

+##              normal.f <- NORM.np[, k]

+##		A.F <- A.F*normal.f[, gend==2]

 		A.F[A.F==0] <- NA

 		nuA[, J] <- nu2

 		phiA[, J] <- phi2

@@ -1459,13 +1459,9 @@ fit.lm4 <- function(idxBatch,

 ##		tmp[, gend==1] <- CT1

 ##		tmp[, gend==2] <- CT2

 ##		cA[, k] <- tmp

-		rm(A.F, normal.f, G, AA, BB, Y, X, Ns)

+		rm(A.F, G, AA, BB, Y, X, Ns)

 		##gc()

 	}

-##	cA[cA < 0.05] <- 0.05

-##	cA[cA > 5] <-  5

-##	cA <- matrix(as.integer(cA*100), nrow(cA), ncol(cA))

-##	CA(object)[snps, ] <- cA

 	open(lM(object))

 	tmp <- physical(lM(object))$nuA

 	tmp[snps, ] <- nuA

@@ -1476,9 +1472,6 @@ fit.lm4 <- function(idxBatch,

 	tmp <- physical(lM(object))$phiA

 	tmp[snps, ] <- phiA

 	lM(object)$sig2A <- tmp

-##	lM(object)$sig2A[snps, ] <- sig2A

-##	lM(object)$nuA[snps, ] <- nuA

-##	lM(object)$phiA[snps, ] <- phiA

 	lapply(assayData(object), close)

 	lapply(lM(object), close)

 	TRUE