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comment code for computing the grand intercept and slope -- need to shrink genotype summaries first

git-svn-id: file:///home/git/hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/crlmm@53575 bc3139a8-67e5-0310-9ffc-ced21a209358

Rob Scharp authored on 10/03/2011 19:30:44
Showing2 changed files

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@@ -1,7 +1,7 @@
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 Package: crlmm
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 Type: Package
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 Title: Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays.
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-Version: 1.9.15
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+Version: 1.9.16
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 Date: 2010-12-10
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 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
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 Maintainer: Benilton S Carvalho <Benilton.Carvalho@cancer.org.uk>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU>
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@@ -554,7 +554,10 @@ fit.lm1 <- function(strata,
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 	## Grand mean
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 	##
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 	##---------------------------------------------------------------------------
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-	if(length(batches) > 1 && "grandMean" %in% batchNames(object)){
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+##	if(length(batches) > 1 && "grandMean" %in% batchNames(object)){
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+	##  TODO:  There are NA's in the medianA.AA for the grandMean and 0's in the madA
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+	##         - both need to be handled prior to estimating a grand intercept and slope
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+	if(FALSE){
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 		## then the last column is for the grandMean
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 		k <- ncol(medianA.AA)
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 		medianA <- cbind(medianA.AA[, k], medianA.AB[, k], medianA.BB[, k])
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@@ -562,8 +565,8 @@ fit.lm1 <- function(strata,
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 		madA <- cbind(madA.AA[, k], madA.AB[, k], madA.BB[, k])
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 		madB <- cbind(madB.AA[, k], madB.AB[, k], madB.BB[, k])
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 		NN <- cbind(N.AA[, k], N.AB[, k], N.BB[, k])
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-		##index <- which(rowSums(is.na(medianA)) > 0)
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-		res <- fit.wls(NN=NN, sigma=madA, allele="A", Y=medianA, autosome=!CHR.X)
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+		index <- which(rowSums(is.na(medianA)) == 0)
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+		res <- fit.wls(NN=NN[index, ], sigma=madA[index, ], allele="A", Y=medianA[index, ], autosome=!CHR.X)
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 		nuA[, k] <- res[1, ]
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 		phiA[, k] <- res[2, ]
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 		rm(res)
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@@ -1738,6 +1741,9 @@ summarizeSnps <- function(strata,
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 		corrAA[, k] <- rowCors(AA*G.AA, BB*G.AA, na.rm=TRUE)
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 		corrAB[, k] <- rowCors(AA*G.AB, BB*G.AB, na.rm=TRUE)
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 		corrBB[, k] <- rowCors(AA*G.BB, BB*G.BB, na.rm=TRUE)
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+		##
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+		## TODO:   fill in NAs -- use code from shrinkGenotypeSummaries
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+		##
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 		rm(GG, CP, AA, BB, FL, stats)
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 		gc()
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 	}