## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set(echo = TRUE, fig.wide = TRUE) ## ----eval=FALSE--------------------------------------------------------------- # if (!require("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("mitology") ## ----------------------------------------------------------------------------- library(mitology) data(MitoGenesDB) head(MitoGenesDB) ## ----echo=FALSE, fig.wide=FALSE----------------------------------------------- knitr::include_graphics("figures/MitoCarta_gene_sets.png") # ## ----echo=FALSE, fig.wide=FALSE----------------------------------------------- knitr::include_graphics("figures/GO_gene_sets.png") # ## ----echo=FALSE, fig.wide=FALSE----------------------------------------------- knitr::include_graphics("figures/Reactome_gene_sets.png") # ## ----message=FALSE------------------------------------------------------------ MC_df <- getGeneSets( database = "MitoCarta", nametype = "SYMBOL", objectType = "dataframe") MC_list <- getGeneSets( database = "MitoCarta", nametype = "SYMBOL", objectType = "list") ## ----message=FALSE------------------------------------------------------------ # loading packages library(SummarizedExperiment) library(AnnotationDbi) library(org.Hs.eg.db) library(GSVA) library(Biobase) ## ----------------------------------------------------------------------------- # load data data(ovse) ovse ## ----warning=FALSE------------------------------------------------------------ genes <- rownames(ovse)[elementMetadata(ovse)$PROvsIMR_FDR < 0.01] genes <- mapIds( org.Hs.eg.db, keys = genes, column = "ENSEMBL", keytype = "SYMBOL", multiVals = "first") enrichresMC <- enrichMito(genes = genes, database = "MitoCarta") enrichresRT <- enrichMito(genes = genes, database = "Reactome") ## ----warning=FALSE------------------------------------------------------------ geneslFC <- elementMetadata(ovse)$PROvsIMR_logFC names(geneslFC) <- rownames(ovse) names(geneslFC) <- mapIds( org.Hs.eg.db, keys = names(geneslFC), column = "ENSEMBL", keytype = "SYMBOL", multiVals = "first") geneslFC <- sort(geneslFC, decreasing = TRUE) geneslFC <- geneslFC[!is.na(names(geneslFC))] gsearesMC <- gseaMito(genes = geneslFC, database = "MitoCarta") gsearesRT <- gseaMito(genes = geneslFC, database = "Reactome") ## ----------------------------------------------------------------------------- gsvaPar <- ssgseaParam(exprData = ovse, geneSets = MC_list) res_ssGSEA <- gsva(gsvaPar) ## ----------------------------------------------------------------------------- mitoTreePoint(data = enrichresMC, database = "MitoCarta", pvalCutoff = .9, color = "pvalue") mitoTreePoint(data = enrichresRT, database = "Reactome", pvalCutoff = .4, color = "pvalue") ## ----------------------------------------------------------------------------- res_ssGSEA_subtype <- do.call( cbind, lapply(unique(ovse$OV_subtype), function(x){ rowMeans(assay(res_ssGSEA)[,ovse$OV_subtype==x]) })) colnames(res_ssGSEA_subtype) <- unique(ovse$OV_subtype) rownames(res_ssGSEA_subtype) <- rownames(res_ssGSEA) res_ssGSEA_subtype <- t(scale(t(res_ssGSEA_subtype))) ## ----fig.height=5.5, fig.width=4.5-------------------------------------------- mitoHeatmap(data = res_ssGSEA_subtype, database = "MitoCarta") ## ----fig.height=5.2, fig.width=5.5-------------------------------------------- mitoHeatmap(data = res_ssGSEA_subtype, database = "MitoCarta", splitSections = TRUE) ## ----message=FALSE------------------------------------------------------------ mitoTreeHeatmap( data = res_ssGSEA_subtype, database = "MitoCarta", labelNames = "leaves", font.size = 1) ## ----message=FALSE------------------------------------------------------------ mitoTreeHeatmap( data = res_ssGSEA_subtype, database = "MitoCarta", labelNames = "sections", font.size = 3) ## ----------------------------------------------------------------------------- sessionInfo()