## ----style-knitr, eval=TRUE, echo=FALSE, results="asis"-------------------- BiocStyle::latex() knitr::opts_chunk$set(message = FALSE) ## ----setup, echo = FALSE--------------------------------------------------- library(EnrichmentBrowser) library(ALL) library(airway) ## ----readSE---------------------------------------------------------------- library(EnrichmentBrowser) data.dir <- system.file("extdata", package = "EnrichmentBrowser") exprs.file <- file.path(data.dir, "exprs.tab") cdat.file <- file.path(data.dir, "colData.tab") rdat.file <- file.path(data.dir, "rowData.tab") se <- readSE(exprs.file, cdat.file, rdat.file) ## ----help, eval=FALSE------------------------------------------------------ # ?readSE # ?SummarizedExperiment ## ----sexp2eset------------------------------------------------------------- eset <- as(se, "ExpressionSet") ## ----eset2sexp------------------------------------------------------------- se <- as(eset, "SummarizedExperiment") ## ----load-ALL-------------------------------------------------------------- library(ALL) data(ALL) ## ----subset-ALL------------------------------------------------------------ ind.bs <- grep("^B", ALL$BT) ind.mut <- which(ALL$mol.biol %in% c("BCR/ABL", "NEG")) sset <- intersect(ind.bs, ind.mut) all.eset <- ALL[, sset] ## ----show-ALL-------------------------------------------------------------- dim(all.eset) exprs(all.eset)[1:4,1:4] ## ----probe2gene------------------------------------------------------------ allSE <- probe2gene(all.eset) head(rownames(allSE)) ## ----show-probe2gene------------------------------------------------------- rowData(se) ## ----load-airway----------------------------------------------------------- library(airway) data(airway) ## ----preproc-airway-------------------------------------------------------- airSE <- airway[grep("^ENSG", rownames(airway)),] airSE <- airSE[rowSums(assay(airSE)) > 4,] dim(airSE) assay(airSE)[1:4,1:4] ## ----norm-ma--------------------------------------------------------------- allSE <- normalize(allSE, norm.method = "quantile") ## ----plot-norm, fig.width=12, fig.height=6--------------------------------- par(mfrow=c(1,2)) boxplot(assay(allSE, "raw")) boxplot(assay(allSE, "norm")) ## ----norm-rseq------------------------------------------------------------- airSE <- normalize(airSE, norm.method = "quantile") ## ----sample-groups-ALL----------------------------------------------------- allSE$GROUP <- ifelse(allSE$mol.biol == "BCR/ABL", 1, 0) table(allSE$GROUP) ## ----sample-groups-airway-------------------------------------------------- airSE$GROUP <- ifelse(airway$dex == "trt", 1, 0) table(airSE$GROUP) ## ----sample-blocks--------------------------------------------------------- airSE$BLOCK <- airway$cell table(airSE$BLOCK) ## ----DE-ana-ALL------------------------------------------------------------ allSE <- deAna(allSE, padj.method = "BH") rowData(allSE) ## ----plot-DE, fig.width=12, fig.height=6----------------------------------- par(mfrow = c(1,2)) pdistr(rowData(allSE)$PVAL) volcano(rowData(allSE)$FC, rowData(allSE)$ADJ.PVAL) ## ----DE-exmpl-------------------------------------------------------------- ind.min <- which.min(rowData(allSE)$ADJ.PVAL) rowData(allSE)[ind.min,] ## ----DE-ana-airway--------------------------------------------------------- airSE <- deAna(airSE, de.method = "edgeR") rowData(airSE) ## ----idmap-idtypes--------------------------------------------------------- idTypes("hsa") ## ----idmap-airway---------------------------------------------------------- head(rownames(airSE)) airSE <- idMap(airSE, org = "hsa", from = "ENSEMBL", to = "ENTREZID") head(rownames(airSE)) ## ----get-kegg-gs, eval=FALSE----------------------------------------------- # kegg.gs <- getGenesets(org = "hsa", db = "kegg") ## ----get-go-gs, eval=FALSE------------------------------------------------- # go.gs <- getGenesets(org = "hsa", db = "go", onto = "BP", mode = "GO.db") ## ----parseGMT-------------------------------------------------------------- gmt.file <- file.path(data.dir, "hsa_kegg_gs.gmt") hsa.gs <- getGenesets(gmt.file) length(hsa.gs) hsa.gs[1:2] ## ----sbeaMethods----------------------------------------------------------- sbeaMethods() ## ----sbea------------------------------------------------------------------ sbea.res <- sbea(method = "ora", se = allSE, gs = hsa.gs, perm = 0, alpha = 0.1) gsRanking(sbea.res) ## ----vst------------------------------------------------------------------- airSE <- normalize(airSE, norm.method = "vst") ## ----gsea-rseq, eval=FALSE------------------------------------------------- # air.res <- sbea(method = "gsea", se = airSE, gs = hsa.gs) # gsRanking(sbea.res) ## ----fullrank-------------------------------------------------------------- gsRanking(sbea.res, signif.only = FALSE) ## ----eaBrowse, eval=FALSE-------------------------------------------------- # eaBrowse(sbea.res) ## ----compile-grn----------------------------------------------------------- hsa.grn <- compileGRN(org="hsa", db="kegg") head(hsa.grn) ## ----nbeaMethods----------------------------------------------------------- nbeaMethods() ## ----nbea------------------------------------------------------------------ nbea.res <- nbea(method="ggea", se=allSE, gs=hsa.gs, grn=hsa.grn) gsRanking(nbea.res) ## ----ggea-graph, fig.width=12, fig.height=6-------------------------------- par(mfrow=c(1,2)) ggeaGraph( gs=hsa.gs[["hsa05217_Basal_cell_carcinoma"]], grn=hsa.grn, se=allSE) ggeaGraphLegend() ## ----dummySBEA------------------------------------------------------------- dummySBEA <- function(se, gs) { sig.ps <- sample(seq(0, 0.05, length = 1000), 5) insig.ps <- sample(seq(0.1, 1, length = 1000), length(gs) - 5) ps <- sample(c(sig.ps, insig.ps), length(gs)) names(ps) <- names(gs) return(ps) } ## ----sbea2----------------------------------------------------------------- sbea.res2 <- sbea(method = dummySBEA, se = allSE, gs = hsa.gs) gsRanking(sbea.res2) ## ----combine--------------------------------------------------------------- res.list <- list(sbea.res, nbea.res) comb.res <- combResults(res.list) ## ----browse-comb, eval=FALSE----------------------------------------------- # eaBrowse(comb.res, graph.view=hsa.grn, nr.show=5) ## ----all-in-one, eval=FALSE------------------------------------------------ # ebrowser( meth=c("ora", "ggea"), # exprs=exprs.file, cdat=cdat.file, rdat=rdat.file, # org="hsa", gs=hsa.gs, grn=hsa.grn, comb=TRUE, nr.show=5) ## ----config-set------------------------------------------------------------ configEBrowser(key="OUTDIR.DEFAULT", value="/my/out/dir") ## ----config-get------------------------------------------------------------ configEBrowser("OUTDIR.DEFAULT") ## ----config-man, eval=FALSE------------------------------------------------ # ?configEBrowser ## ----deTbl----------------------------------------------------------------- deTable <- matrix(c(28, 142, 501, 12000), nrow = 2, dimnames = list(c("DE", "Not.DE"), c("In.gene.set", "Not.in.gene.set"))) deTable ## ----fisher---------------------------------------------------------------- fisher.test(deTable, alternative = "greater")