## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ---- fig.align = "center", out.width = "50%", echo=FALSE--------------------- knitr::include_graphics("hex_padma_v2.png") ## ---- message = FALSE--------------------------------------------------------- library(padma) ## ---- eval = FALSE------------------------------------------------------------ # run_padma <- # padma(mae, pathway_name = "c2_cp_BIOCARTA_D4GDI_PATHWAY") ## ---- eval = FALSE------------------------------------------------------------ # assay(run_padma) # # factorMap(run_padma) # factorMap(run_padma, partial_id = "TCGA-78-7536") # omicsContrib(run_padma) ## ---- explore_LUAD_subset----------------------------------------------------- names(LUAD_subset) lapply(LUAD_subset, class) lapply(LUAD_subset, dim) ## ---- msigdb------------------------------------------------------------------ head(msigdb) ## ----------------------------------------------------------------------------- head(mirtarbase) ## ----------------------------------------------------------------------------- library(MultiAssayExperiment) LUAD_subset <- padma::LUAD_subset omics_data <- list(rnaseq = as.matrix(LUAD_subset$rnaseq), methyl = as.matrix(LUAD_subset$methyl), mirna = as.matrix(LUAD_subset$mirna), cna = as.matrix(LUAD_subset$cna)) pheno_data <- data.frame(LUAD_subset$clinical, row.names = LUAD_subset$clinical$bcr_patient_barcode) mae <- suppressMessages( MultiAssayExperiment::MultiAssayExperiment( experiments = omics_data, colData = pheno_data)) ## ---- runpadma---------------------------------------------------------------- D4GDI <- msigdb[grep("D4GDI", msigdb$geneset), "geneset"] run_padma <- padma(mae, pathway_name = D4GDI, verbose = FALSE) ## ---- runpadmalist------------------------------------------------------------ clinical_data <- data.frame(LUAD_subset$clinical) rownames(clinical_data) <- clinical_data$bcr_patient_barcode run_padma_list <- padma(omics_data, colData = clinical_data, pathway_name = D4GDI, verbose = FALSE) ## ---- runpadma2--------------------------------------------------------------- D4GDI_genes <- unlist(strsplit( msigdb[grep("D4GDI", msigdb$geneset), "symbol"], ", ")) D4GDI_genes run_padma_again <- padma(mae, pathway_name = D4GDI_genes, verbose = FALSE) ## ---- factorMAP--------------------------------------------------------------- factorMap(run_padma, dim_x = 1, dim_y = 2) ## ---- factorMAP2-------------------------------------------------------------- factorMap(run_padma, dim_x = 1, dim_y = 2, ggplot = FALSE) ## ---- factorMappartial-------------------------------------------------------- factorMap(run_padma, partial_id = "TCGA-78-7536", dim_x = 1, dim_y = 2) ## ---- factorMappartial2------------------------------------------------------- factorMap(run_padma, partial_id = "TCGA-78-7536", dim_x = 1, dim_y = 2, ggplot = FALSE) ## ---- omicscontrib------------------------------------------------------------ omicsContrib(run_padma, max_dim = 10) ## ---- omicscontrib2----------------------------------------------------------- omicsContrib(run_padma, max_dim = 10, ggplot = FALSE) ## ----------------------------------------------------------------------------- run_padma_supp <- padma(mae, pathway_name = D4GDI, verbose = FALSE, base_ids = sampleMap(mae)$primary[1:10], supp_ids = sampleMap(mae)$primary[15:20]) ## ----------------------------------------------------------------------------- run_padma_impute <- padma(mae, pathway_name = D4GDI, impute = TRUE, verbose = FALSE) ## ---- eval = FALSE------------------------------------------------------------ # run_padma_concise <- # padma(mae, pathway_name = D4GDI, full_results = FALSE) ## ----------------------------------------------------------------------------- sessionInfo()