## ----path-to-data, eval=TRUE-------------------------------------------------- library(DAAGbio) path2data <- system.file("extdata", package="DAAGbio") ## ----load-limma, echo=TRUE, eval=TRUE----------------------------------------- if(!require(limma)){print("Package `limma` is not installed") knit_exit() } ## ----readTargets, echo=TRUE, eval=TRUE, results="hide"------------------------ targets <- readTargets("coralTargets.txt", path=path2data) targets$FileName # Display the file names ## ----see-targets, echo=TRUE, eval=FALSE--------------------------------------- # targets ## ----read-images, echo=TRUE, eval=TRUE, results="hide"------------------------ coralRG <- read.maimages(targets$FileName, source = "spot", path=path2data, other.columns=list(area="area", badspot="badspot")) ## ----echo=TRUE, eval=TRUE, results="hide"------------------------------------- summary(coralRG$other$area) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- plot(density(coralRG$other$area[,1])) ## ----echo=TRUE, eval=TRUE, results="hide"------------------------------------- coralRG$genes <- readGAL(path=path2data) coralRG$printer <- getLayout(coralRG$genes) coralRG$printer ## ----printseq----------------------------------------------------------------- plotprintseq() ## ----echo=TRUE, eval=TRUE----------------------------------------------------- spottypes<-readSpotTypes(path=path2data) coralRG$genes$Status <- controlStatus(spottypes, coralRG) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- imageplot(log2(coralRG$Rb[, 1]+1), layout = coralRG$printer, low="white", high="red") ## ----echo=TRUE, eval=TRUE----------------------------------------------------- imageplot(log2(coralRG$Rb[, 2]+1), layout = coralRG$printer, low="white", high="red") ## ----six-plots, eval=FALSE---------------------------------------------------- # x11(width=7.5, height=11) # xplot(data = coralRG$R, layout = coralRG$printer, FUN=imageplot) ## ----hard-copy, eval=FALSE---------------------------------------------------- # quartz(width=7.5, height=11) # xplot(data = coralRG$R, layout = coralRG$printer, FUN=imageplot, # device=pdf) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- plotMA(coralRG, array=1) ## ----all-six, eval=FALSE------------------------------------------------------ # oldpar <- par(mfrow=c(3,2), mar=c(5.1, 4.1, 1.1, 0.6)) # ## When done with the 3 by 2 layout, be sure to type # par(oldpar) # This returns to the original settings. ## ----echo=TRUE, eval=TRUE----------------------------------------------------- rawMA <- normalizeWithinArrays(coralRG, method = "none") plotPrintTipLoess(rawMA, array=1) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- MA <- normalizeWithinArrays(coralRG, method = "printtiploess") plotPrintTipLoess(MA) ## ----echo=TRUE, eval=FALSE---------------------------------------------------- # boxplot(MA$M ~ col(MA$M), names = colnames(MA$M)) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- nMA <- normalizeBetweenArrays(MA) boxplot(nMA$M ~ col(nMA$M), names = colnames(nMA$M)) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- wanted <- coralRG$genes$Status == "diff-exp ctl" rawdeM <- rawMA$M[wanted, ] pairs(rawdeM) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- wanted <- coralRG$genes$Status == "diff-exp ctl" deM <- nMA$M[wanted, ] pairs(rawdeM) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- imageplot(nMA$M[,5], layout=coralRG$printer) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- design <- c(-1, 1, -1, 1, 0, 1) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- fit <- lmFit(nMA, design) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- efit <- eBayes(fit) qqt(efit$t, df = efit$df.prior + efit$df.residual, pch = 16, cex = 0.2) ## ----echo=TRUE, eval=TRUE, results="hide"------------------------------------- options(digits = 3) topvals <- topTable(efit, number = 50) topvals ## ----echo=TRUE, eval=TRUE----------------------------------------------------- plot(efit$coef, efit$lods, pch = 16, cex = 0.2, xlab = "log(fold change)", ylab = "log(odds)") ord <- order(efit$lods, decreasing = TRUE) top8 <- ord[1:8] text(efit$coef[top8], efit$lods[top8], labels = coralRG$genes[top8, "Name"], cex = 0.8, col = "blue") ## ----prior02, eval=FALSE------------------------------------------------------ # efit.02 <- eBayes(fit, prop=0.02) # topTable(efit.02, number = 50) ## ----prior01, eval=FALSE------------------------------------------------------ # efit.1 <- eBayes(fit, prop=0.1) # B.1 <- topTable(efit.1, number = 3072)$B # B.01 <- topvals$B # points(B.01, B.1, col="gray") ## ----echo=TRUE, eval=TRUE, results="hide"------------------------------------- coral2RG <- read.maimages(targets$FileName, source = "spot", path=path2data, wt.fun=wtarea(100)) coral2RG$genes <- readGAL(path=path2data) coral2RG$printer <- getLayout(coral2RG$genes) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- MA2 <- normalizeWithinArrays(coral2RG, method = "printtiploess") plotPrintTipLoess(MA2) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- boxplot(MA2$M ~ col(MA2$M), names = colnames(MA2$M)) nMA2 <- normalizeBetweenArrays(MA2) boxplot(nMA2$M ~ col(nMA2$M), names = colnames(nMA2$M)) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- imageplot(nMA2$M[,5], layout=coral2RG$printer) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- design <- c(-1, 1, -1, 1, 0, 1) fit2 <- lmFit(nMA2, design) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- efit2 <- eBayes(fit2) qqt(efit2$t, df = efit2$df.prior + efit2$df.residual, pch = 16, cex = 0.2) ## ----echo=TRUE, eval=TRUE, results="hide"------------------------------------- options(digits = 3) topTable(efit2, number = 50) ## ----echo=TRUE, eval=TRUE, results="hide"------------------------------------- ## Get & store results with & without weights topvals2 <- topTable(efit2, number = 50) cbind(row.names(topvals), row.names(topvals2)) ## ----echo=TRUE, eval=TRUE, results="hide"------------------------------------- sum(row.names(topvals)%in%row.names(topvals2)) ## ----echo=TRUE, eval=TRUE----------------------------------------------------- imgplot(coralRG$R[, 1], layout = coralRG$printer) ## ----process-Rnw, eval=FALSE-------------------------------------------------- # library(knitr) # knit("marray-notes.Rnw")