@@ -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: 1.9.15

+Version: 1.9.16

 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>

@@ -554,7 +554,10 @@ fit.lm1 <- function(strata,

 	## Grand mean

 	##

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

-	if(length(batches) > 1 && "grandMean" %in% batchNames(object)){

+##	if(length(batches) > 1 && "grandMean" %in% batchNames(object)){

+	##  TODO:  There are NA's in the medianA.AA for the grandMean and 0's in the madA

+	##         - both need to be handled prior to estimating a grand intercept and slope

+	if(FALSE){

 		## then the last column is for the grandMean

 		k <- ncol(medianA.AA)

 		medianA <- cbind(medianA.AA[, k], medianA.AB[, k], medianA.BB[, k])

@@ -562,8 +565,8 @@ fit.lm1 <- function(strata,

 		madA <- cbind(madA.AA[, k], madA.AB[, k], madA.BB[, k])

 		madB <- cbind(madB.AA[, k], madB.AB[, k], madB.BB[, k])

 		NN <- cbind(N.AA[, k], N.AB[, k], N.BB[, k])

-		##index <- which(rowSums(is.na(medianA)) > 0)

-		res <- fit.wls(NN=NN, sigma=madA, allele="A", Y=medianA, autosome=!CHR.X)

+		index <- which(rowSums(is.na(medianA)) == 0)

+		res <- fit.wls(NN=NN[index, ], sigma=madA[index, ], allele="A", Y=medianA[index, ], autosome=!CHR.X)

 		nuA[, k] <- res[1, ]

 		phiA[, k] <- res[2, ]

 		rm(res)

@@ -1738,6 +1741,9 @@ summarizeSnps <- function(strata,

 		corrAA[, k] <- rowCors(AA*G.AA, BB*G.AA, na.rm=TRUE)

 		corrAB[, k] <- rowCors(AA*G.AB, BB*G.AB, na.rm=TRUE)

 		corrBB[, k] <- rowCors(AA*G.BB, BB*G.BB, na.rm=TRUE)

+		##

+		## TODO:   fill in NAs -- use code from shrinkGenotypeSummaries

+		##

 		rm(GG, CP, AA, BB, FL, stats)

 		gc()

 	}