## ----echo=TRUE, message=FALSE, warning=FALSE, eval=FALSE---------------------- # if (!requireNamespace("BiocManager", quietly = TRUE)) { # install.packages("BiocManager") # } # BiocManager::install("Rvisdiff") ## ----echo=TRUE, message=FALSE, warning=FALSE, eval=TRUE----------------------- library("Rvisdiff") ## ----echo=TRUE, message=FALSE, warning=FALSE, eval=TRUE----------------------- library(Rvisdiff) library(airway) data("airway") se <- airway se$dex <- relevel(se$dex, ref="untrt") countdata <- assay(se) coldata <- colData(se) ## ----echo=TRUE, message=FALSE, warning=FALSE, eval=TRUE----------------------- library(DESeq2) dds <- DESeqDataSet(se, design = ~ cell + dex) dds <- DESeq(dds) dres <- results(dds, independentFiltering = FALSE) DEreport(dres, countdata, coldata$dex) ## ----echo=TRUE, message=FALSE, warning=FALSE, eval=TRUE----------------------- library(edgeR) design <- model.matrix(~ cell + dex, data = coldata) dl <- DGEList(counts = countdata, group = coldata$dex) dl <- calcNormFactors(dl) dl <- estimateDisp(dl, design=design) de <- exactTest(dl,pair=1:2) tt <- topTags(de, n = Inf, adjust.method = "BH", sort.by = "none") DEreport(tt, countdata, coldata$dex) ## ----echo=TRUE, message=FALSE, warning=FALSE, eval=TRUE----------------------- library(limma) design <- model.matrix(~ 0 + dex + cell, data = coldata) contr <- makeContrasts(dextrt - dexuntrt,levels=colnames(design)) limmaexprs <- voom(countdata, design) fit <- lmFit(limmaexprs, design) fit <- contrasts.fit(fit, contrasts=contr) fit <- eBayes(fit) limmares <- topTable(fit, coef = 1, number = Inf, sort.by = "none", adjust.method = "BH") DEreport(limmares, countdata, coldata$dex) ## ----echo=TRUE, message=FALSE, warning=FALSE, eval=TRUE----------------------- untrt <- countdata[,coldata$dex=="untrt"] trt <- countdata[,coldata$dex=="trt"] library(matrixTests) wilcox <- col_wilcoxon_twosample(t(untrt), t(trt)) stat <- wilcox$statistic p <- wilcox$pvalue log2FoldChange <- log2(rowMeans(trt)+1) - log2(rowMeans(untrt)+1) wilcox <- cbind(stat = stat, pvalue = round(p, 6), padj = p.adjust(wilcox[,2], method = "BH"), baseMean = rowMeans(countdata), log2FoldChange = log2FoldChange) rownames(wilcox) <- rownames(countdata) DEreport(wilcox, countdata, coldata$dex) ## ----echo=FALSE--------------------------------------------------------------- knitr::include_graphics("figure1.png") ## ----sessionInfo-------------------------------------------------------------- sessionInfo()