# Version info: R 3.2.3, Biobase 2.30.0, GEOquery 2.40.0, limma 3.26.8 # R scripts generated Wed Jul 15 09:25:36 EDT 2020 ################################################################ # Differential expression analysis with limma library(Biobase) library(GEOquery) library(limma) # load series and platform data from GEO gset <- getGEO("GSE39099", GSEMatrix =TRUE, AnnotGPL=TRUE) if (length(gset) > 1) idx <- grep("GPL570", attr(gset, "names")) else idx <- 1 gset <- gset[[idx]] # make proper column names to match toptable fvarLabels(gset) <- make.names(fvarLabels(gset)) # group names for all samples gsms <- "X011" sml <- c() for (i in 1:nchar(gsms)) { sml[i] <- substr(gsms,i,i) } # eliminate samples marked as "X" sel <- which(sml != "X") sml <- sml[sel] gset <- gset[ ,sel] # log2 transform ex <- exprs(gset) qx <- as.numeric(quantile(ex, c(0., 0.25, 0.5, 0.75, 0.99, 1.0), na.rm=T)) LogC <- (qx[5] > 100) || (qx[6]-qx[1] > 50 && qx[2] > 0) || (qx[2] > 0 && qx[2] < 1 && qx[4] > 1 && qx[4] < 2) if (LogC) { ex[which(ex <= 0)] <- NaN exprs(gset) <- log2(ex) } # set up the data and proceed with analysis sml <- paste("G", sml, sep="") # set group names fl <- as.factor(sml) gset$description <- fl design <- model.matrix(~ description + 0, gset) colnames(design) <- levels(fl) fit <- lmFit(gset, design) cont.matrix <- makeContrasts(G1-G0, levels=design) fit2 <- contrasts.fit(fit, cont.matrix) fit2 <- eBayes(fit2, 0.01) tT <- topTable(fit2, adjust="fdr", sort.by="B", number=250) tT <- subset(tT, select=c("ID","adj.P.Val","P.Value","t","B","logFC","Gene.symbol","Gene.title")) write.table(tT, file=stdout(), row.names=F, sep="\t") ################################################################ # Boxplot for selected GEO samples library(Biobase) library(GEOquery) # load series and platform data from GEO gset <- getGEO("GSE39099", GSEMatrix =TRUE, getGPL=FALSE) if (length(gset) > 1) idx <- grep("GPL570", attr(gset, "names")) else idx <- 1 gset <- gset[[idx]] # group names for all samples in a series gsms <- "X011" sml <- c() for (i in 1:nchar(gsms)) { sml[i] <- substr(gsms,i,i) } sml <- paste("G", sml, sep="") # set group names # eliminate samples marked as "X" sel <- which(sml != "X") sml <- sml[sel] gset <- gset[ ,sel] # order samples by group ex <- exprs(gset)[ , order(sml)] sml <- sml[order(sml)] fl <- as.factor(sml) labels <- c("NEM","EC") # set parameters and draw the plot palette(c("#dfeaf4","#f4dfdf", "#AABBCC")) dev.new(width=4+dim(gset)[[2]]/5, height=6) par(mar=c(2+round(max(nchar(sampleNames(gset)))/2),4,2,1)) title <- paste ("GSE39099", '/', annotation(gset), " selected samples", sep ='') boxplot(ex, boxwex=0.6, notch=T, main=title, outline=FALSE, las=2, col=fl) legend("topleft", labels, fill=palette(), bty="n")