Package index • statplot

All functions

combine_pvalues(): Combine p-values
comma(): Format numbers with comma as thousands separator
ex_data_heatmap: Example tidy expression dataset for heatmap plotting
ex_expr_pathway: Example expression matrix for pathway correlation network plots
ex_log2fc_pathway: Example log2 fold-change vector for pathway correlation network plots
format_pvalue(): Format p-values for display
hallmark_pathway_categories: Hallmark pathway process categories
hallmark_t2g: Hallmark gene sets (Human) from MSigDB
plot_2_categorical_vars(): Stacked percent bar chart for two categorical variables
plot_bars(): Bar plot by group
plot_covariate_heatmap(): Plot a covariate heatmap
plot_data_avail_by_group(): Plot data availability by group
plot_dot_whiskers(): Dot-and-whisker plot of estimates with confidence intervals
plot_dotmap(): Create a dotmap showing effect size (dot size & color) and p-value (tile fill)
plot_effectsize_01_intervals(): Plot effect-size estimates and confidence intervals. All values must be between 0 and 1.
plot_heatmap(): Plot a heatmap from tidy data
plot_numeric_by_2groups(): Violin + boxplot with Wilcoxon rank-sum test
plot_numeric_by_3plusgroups(): Violin + boxplot of a numeric variable by a grouping factor
plot_pathway_correlation_network(): Gene–Gene correlation network for a single pathway
plot_pathways(): Gene–Pathway network plot (cnetplot)
plot_pvalue_barplot(): Plot p-value barplot
plot_survival_curves(): Kaplan–Meier plot from a Surv object
plot_upset(): Build an upset plot from a named list of sets
quarto_html_tabset_list(): Render a named list as a Quarto tabset
run_gsea(): Run Gene Set Enrichment Analysis (GSEA)
table_overall(): Create a table that summarizes the entire cohort.
table_overall_and_group(): Create overall and by-group summary table