## ----load_packages, include=TRUE, results="hide", message=FALSE, warning=FALSE---- library(MultiAssayExperiment) library(S4Vectors) ## ----load_miniacc------------------------------------------------------------- data(miniACC) miniACC ## ----coldata_access----------------------------------------------------------- colData(miniACC)[1:4, 1:4] table(miniACC$race) ## ----experiments_access------------------------------------------------------- experiments(miniACC) ## ----sample_map_access-------------------------------------------------------- sampleMap(miniACC) ## ----metadata_access---------------------------------------------------------- metadata(miniACC) ## ----subset_by_rownames, results='hide'--------------------------------------- miniACC[c("MAPK14", "IGFBP2"), , ] ## ----subset_by_stage, results='hide'------------------------------------------ stg4 <- miniACC$pathologic_stage == "stage iv" # remove NA values from vector miniACC[, stg4 & !is.na(stg4), ] ## ----subset_by_assay_name, results='hide'------------------------------------- miniACC[, , "RNASeq2GeneNorm"] ## ----double_bracket_subsetting------------------------------------------------ miniACC[[1L]] #or equivalently, miniACC[["RNASeq2GeneNorm"]] ## ----complete_cases_summary--------------------------------------------------- summary(complete.cases(miniACC)) ## ----intersect_columns-------------------------------------------------------- accmatched = intersectColumns(miniACC) ## ----accmatched_colnames------------------------------------------------------ colnames(accmatched) ## ----intersect_rows----------------------------------------------------------- accmatched2 <- intersectRows(miniACC[, , c("RNASeq2GeneNorm", "gistict", "Mutations")]) rownames(accmatched2) ## ----assay_singular----------------------------------------------------------- class(assay(miniACC)) ## ----assays_plural------------------------------------------------------------ assays(miniACC) ## ----longform_example--------------------------------------------------------- longForm( miniACC[c("TP53", "CTNNB1"), , ], colDataCols = c("vital_status", "days_to_death") ) ## ----wideform_example--------------------------------------------------------- wideFormat( miniACC[c("TP53", "CTNNB1"), , ], colDataCols = c("vital_status", "days_to_death") ) ## ----mae_constructor---------------------------------------------------------- MultiAssayExperiment( experiments=experiments(miniACC), colData=colData(miniACC), sampleMap=sampleMap(miniACC), metadata=metadata(miniACC) ) ## ----concatenate_mae---------------------------------------------------------- miniACC2 <- c( miniACC, log2rnaseq = log2(assays(miniACC)$RNASeq2GeneNorm), mapFrom=1L ) assays(miniACC2) ## ----upset_samples------------------------------------------------------------ library(UpSetR) upsetSamples(miniACC) ## ----kaplan_meier_plot_setup,message=FALSE------------------------------------ library(survival) library(survminer) coldat <- as.data.frame(colData(miniACC)) coldat$y <- Surv(miniACC$days_to_death, miniACC$vital_status) colData(miniACC) <- DataFrame(coldat) ## ----remove_missing_survival_data--------------------------------------------- miniACC <- miniACC[, complete.cases(coldat$y), ] coldat <- as(colData(miniACC), "data.frame") ## ----kaplan_meier_plot-------------------------------------------------------- fit <- survfit(y ~ pathology_N_stage, data = coldat) ggsurvplot(fit, data = coldat, risk.table = TRUE) ## ----prepare_cox_regression_data---------------------------------------------- wideacc <- wideFormat( miniACC["EZH2", , ], colDataCols = c("vital_status", "days_to_death", "pathology_N_stage") ) wideacc$y <- Surv(wideacc$days_to_death, wideacc$vital_status) head(wideacc) ## ----cox_regression_model----------------------------------------------------- coxph( Surv(days_to_death, vital_status) ~ gistict_EZH2 + log2(RNASeq2GeneNorm_EZH2) + pathology_N_stage, data = wideacc ) ## ----sessioninfo-------------------------------------------------------------- sessionInfo()