Hi List I use spot weights (binary) to A) ignore spots "Not found" in GenePix during normalization: RG <- read.maimages(fnames, source="genepix", path=datadir, columns=columns, other.columns=other.columns, wt.fun=wtflags(weight=0,cutoff=0)) MA <- normalizeWithinArrays(RG, method="loess", weights=RG$weights, bc.method="none") ... and B) include "cDNA" spots only in lmFit (ignoring various control spots): MA$weights[MA$genes$Status!="cDNA",] <- 0 fit <- lmFit(MA, design, ndups=2, weights=MA$weights, method="robust", correlation=cor$cor) Does the use of array weights in lmFit... arrayw <- arrayWeights(MA, design, weights=MA$weights) fit2 <- lmFit(MA, design, ndups=2, weights=arrayw, method="robust", correlation=cor$cor) ... exclude the individual spot weights? Are all spots from an "array weighted" array given the same weight in lmFit - thereby ignoring the "original" spot weights (in MA$weights)? How can the various control spots then be ignored in lmFit? > arrayw 1 2 3 4 5 6 7 8 0.9003237 0.5224861 0.8302243 0.7377452 0.6727376 1.1749278 1.0347314 0.4233758 9 10 11 12 13 14 15 16 0.5922037 0.5770843 1.1066639 0.5070331 1.1136625 0.8131061 0.9608490 0.3578452 ............ 81 82 83 84 85 86 87 88 1.1762249 0.8947206 1.0537712 1.2835124 1.4650973 1.8305352 1.4610934 1.4539068 89 90 91 92 93 94 95 96 1.3118581 1.1803798 1.5399506 1.2547482 1.3258992 1.0470026 1.0130834 1.1672451 > sessionInfo() R version 2.4.1 (2006-12-18) x86_64-redhat-linux-gnu locale: LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US .UTF-8;LC_MONETARY=en_US.UTF-8;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US. UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8 ;LC_IDENTIFICATION=C attached base packages: [1] "stats" "graphics" "grDevices" "utils" "datasets" "methods" [7] "base" other attached packages: MASS statmod GDD limma "7.2-30" "1.3.0" "0.1-8" "2.9.16" Looking forward hearing from you Jakob Hedegaard Project scientist UNIVERSITY OF AARHUS Faculty of Agricultural Sciences Dept. of Genetics and Biotechnology Blichers All? 20, P.O. BOX 50 DK-8830 Tjele

> ---------------------------------------------------------------------- > > Message: 1 > Date: Wed, 2 May 2007 15:04:26 +0200 > From: "Jakob Hedegaard" <jakob.hedegaard at="" agrsci.dk=""> > Subject: [BioC] Limma - using both array and spot weights in lmFit > To: <bioconductor at="" stat.math.ethz.ch=""> > Message-ID: > <ea09c4b2b0f16e44b8f3311629493c0d0346e77c at="" djfpost01.djf.agrsci.dk=""> > Content-Type: text/plain; charset="iso-8859-1" > > Hi List > > I use spot weights (binary) to A) ignore spots "Not found" in GenePix > during normalization: > > RG <- read.maimages(fnames, source="genepix", path=datadir, > columns=columns, other.columns=other.columns, > wt.fun=wtflags(weight=0,cutoff=0)) > MA <- normalizeWithinArrays(RG, method="loess", weights=RG$weights, > bc.method="none") > > ... and B) include "cDNA" spots only in lmFit (ignoring various control > spots): > > MA$weights[MA$genes$Status!="cDNA",] <- 0 > fit <- lmFit(MA, design, ndups=2, weights=MA$weights, method="robust", > correlation=cor$cor) > > > Does the use of array weights in lmFit... > > arrayw <- arrayWeights(MA, design, weights=MA$weights) > fit2 <- lmFit(MA, design, ndups=2, weights=arrayw, method="robust", > correlation=cor$cor) > > ... exclude the individual spot weights? > > Are all spots from an "array weighted" array given the same weight in > lmFit - thereby ignoring the "original" spot weights (in MA$weights)? > > How can the various control spots then be ignored in lmFit? The following codes do this job. i<-MA$genes$Status=="cDNA" #Filter for all cDNA spots. corMAi<-duplicateCorrelation(MA[i,],design,ndups=2) fitMAi<-lmFit(MA[i,], design, ndups=2, correlation=corMAi$consensus.correlation) contrast.matrix<-makeContrasts(......) #Fabricate your own contrasts. fit2MAi<-contrasts.fit(fitMAi,contrast.matrix) fit2MAi<-eBayes(fit2MAi) > > > >> arrayw > 1 2 3 4 5 6 7 > 8 > 0.9003237 0.5224861 0.8302243 0.7377452 0.6727376 1.1749278 1.0347314 > 0.4233758 > 9 10 11 12 13 14 15 > 16 > 0.5922037 0.5770843 1.1066639 0.5070331 1.1136625 0.8131061 0.9608490 > 0.3578452 > ............ > 81 82 83 84 85 86 87 > 88 > 1.1762249 0.8947206 1.0537712 1.2835124 1.4650973 1.8305352 1.4610934 > 1.4539068 > 89 90 91 92 93 94 95 > 96 > 1.3118581 1.1803798 1.5399506 1.2547482 1.3258992 1.0470026 1.0130834 > 1.1672451 > > >> sessionInfo() > R version 2.4.1 (2006-12-18) > x86_64-redhat-linux-gnu > > locale: > LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_ US.UTF-8;LC_MONETARY=en_US.UTF-8;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_U S.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF -8;LC_IDENTIFICATION=C > > attached base packages: > [1] "stats" "graphics" "grDevices" "utils" "datasets" "methods" > [7] "base" > > other attached packages: > MASS statmod GDD limma > "7.2-30" "1.3.0" "0.1-8" "2.9.16" > > > > Looking forward hearing from you > > Jakob Hedegaard > Project scientist > > UNIVERSITY OF AARHUS > Faculty of Agricultural Sciences > Dept. of Genetics and Biotechnology > Blichers All? 20, P.O. BOX 50 > DK-8830 Tjele