Function reference • BiomarkerWrappers

All functions

bkable() bforest() bresults() `bresults<-`() boutput() `boutput<-`() bcaption() `bcaption<-`() bheader() `bheader<-`() dim(<Bclass>) nrow(<Bclass>) ncol(<Bclass>) colnames(<Bclass>) `colnames<-`(<Bclass>) rownames(<Bclass>) `rownames<-`(<Bclass>) `[[`(<Bclass>,<ANY>) `$`(<Bclass>) `[`(<Bclass>,<ANY>,<ANY>,<ANY>) rbind(<Bclass>) cbind(<Bclass>): Bclass object

compute_lower_whisker(): Compute lower whisker

compute_trim_values() apply_trim_values(): Compute trimming values and trim data to a specified range

compute_upper_whisker(): Compute upper whisker

csv2eSet(): Load content from a CSV file into an eSet

cut2(): My version of cut

densVals(): Density Values for Smooth Density Plots

duplicated2(): My version of duplicated

eSet2csv(): Save content of an eSet into a CSV file

fig.rename(): Helper function to rename plots generated by the code chunks

format_colors_cat() format_colors() format_colors_cat_strata(): Format or create colors for a vector with categorical values

format_colors_num(): Generate colors for ComplexHeatmap for continuous variables

format_shapes(): Format or create shapes for a vector with categorical values

format_variable_names(): Create variable names

isValidAndUnreservedName(): Check if a vector consists of valid names

jaccard_matrix(): Compute Jaccard similarity for pairs of covariates

or_matrix(): Compute odds ratios for pairs of covariates

order2(): My version of order for data frame

subchunkify(): My version of subchunkify

wrapper_HR_dotplot: Dot plot with HR and 95 wrapper_HR_dotplot( x, biomarker_var = "biomarker", hr_prefix = "HR", hr_ci_lower_prefix = "HR.CI95.lower", hr_ci_upper_prefix = "HR.CI95.upper", pval_prefix = "P.Value", adjp_prefix = "adj.P.Val", sep = "_", pval = 0.05, title = "", color_low = "#42399B", color_mid = "white", color_high = "#D70131", trim_values = c(0.25, 4), trim_prop = NULL, trim_range = NULL, ceiling = FALSE, radius_range = c(3, 10), legend_position = "right", axis_text_y_size = NULL, axis_text_y_width = 80, title_size = NULL ) xTopTable with Cox regression results Dot plot with HR and 95

wrapper_KM_plot_biomarker(): KM plots with biomarker effect per treatment arm

wrapper_KM_plot_core() wrapper_KM_plot_core_strat(): KM plot

wrapper_KM_plot_interaction(): KM plot with curves per biomarker and treatment in a single panel

wrapper_KM_plot_treatment(): KM plot with treatment effect per biomarker subgroup

wrapper_NES_barplot(): Bar plot with NES from GSEA

wrapper_NES_barplot2(): Bar plot with NES from GSEA

wrapper_bar_plot_biomarker(): Bar plot with biomarker effect on response per treatment arm

wrapper_bar_plot_core() wrapper_bar_plot_core_strat(): Barplot

wrapper_bar_plot_treatment(): Bar plot with treatment effect on response per biomarker subgroup

wrapper_bar_plot_yvars_core_strat(): Barplots

wrapper_box_plot_core() wrapper_box_plot_core_strat(): Boxplot

wrapper_box_plot_yvars_core_strat(): Boxplots

wrapper_bresults_to_topTable(): Convert results from Cox regression into a topTable

wrapper_calculate_sample_logFC(): Calculate logFC for expression data that will be plotted in a heatmap

wrapper_cameraPR(): Run CAMERA

wrapper_cameraPR_core(): Run CAMERA

wrapper_characteristics_bep(): Table with distribution summary for a list of covariates for ITT and BEP

wrapper_characteristics_core(): Table with distribution summary for categorical and numerical covariates

wrapper_characteristics_core_cat(): Table with distribution summary for a categorical covariate

wrapper_characteristics_core_num(): Table with distribution summary for a numerical covariate

wrapper_cooccurence_dotplot(): Dotplot with cooccurence odds ratios

wrapper_cooccurence_heatmap(): Heatmap of Jaccard similarity between pairs of covariates

wrapper_cox_regression_biomarker(): Cox regression estimating biomarker effect

wrapper_cox_regression_core_interaction() wrapper_cox_regression_core_interaction_strat(): Cox regression with additive model with interaction

wrapper_cox_regression_core_simple() wrapper_cox_regression_core_simple_strat(): Cox regression with simple additive model

wrapper_cox_regression_interaction(): Cox regression estimating interaction effect between biomaker and treatment

wrapper_cox_regression_treatment(): Cox regression estimating treatment effect within biomarker subgroups

wrapper_cut_2groups() wrapper_cut_2groups_strat(): Stratify data into two groups

wrapper_cut_median() wrapper_cut_median_strat(): Dichotomize data by median

wrapper_cut_quartiles() wrapper_cut_quartiles_strat(): Stratify data into quartiles

wrapper_cut_quintiles() wrapper_cut_quintiles_strat(): Stratify data into quintiles

wrapper_cut_tertiles() wrapper_cut_tertiles_strat(): Stratify data into tertiles

wrapper_deside_tests(): Create a summary variable indicating significant genes

wrapper_dispaly_significant_camera(): Display significantly enriched gene sets

wrapper_dispaly_significant_genes(): Display significantly DE genes

wrapper_dispaly_significant_gsea(): Display significantly enriched gene sets

wrapper_dispaly_significant_ora(): Display significant pathways for a given contrast and direction

wrapper_error_line_plot_core() wrapper_error_line_plot_core_strat(): Error line plot

wrapper_extract_from_topTable(): Extract given statistics for all contrasts available in merged topTable

wrapper_fishers_test(): Fisher's test

wrapper_fishers_test_core() wrapper_fishers_test_core_strat(): Fisher's test

wrapper_gene_expression_heatmap(): Heatmap with logFC or z-score normalized gene expression

wrapper_gsea(): Run GSEA

wrapper_gsea_core(): Run GSEA

wrapper_gsea_plot(): Plot GSEA statistics ranks

wrapper_gsea_plot_core(): Plot GSEA statistics ranks

wrapper_kruskal_test(): Kruskal-Wallis H test or Wilcoxon Rank-Sum test

wrapper_kruskal_test_core_col_cat() wrapper_kruskal_test_core_col_cat_strat(): Kruskal-Wallis H test or Wilcoxon Rank-Sum test (know also as Wilcoxon-Mann-Whitney test) or t-test

wrapper_kruskal_test_core_col_num() wrapper_kruskal_test_core_col_num_strat(): Kruskal-Wallis H test or Wilcoxon Rank-Sum test (know also as Wilcoxon-Mann-Whitney test) or t-test

wrapper_line_plot_core() wrapper_line_plot_core_strat(): Line plot

wrapper_lm(): Fit a linear model

wrapper_lmer(): Fit a linear mixed model

wrapper_logFC_dotplot(): Dot plot with logFC and p-values for multiple contrasts

wrapper_logFC_heatmap(): Heatmap with logFC for multiple contrasts

wrapper_log_rank_test_biomarker(): Log-rank test testing biomarker effect

wrapper_log_rank_test_core_simple() wrapper_log_rank_test_core_simple_strat(): Log-rank test

wrapper_log_rank_test_treatment(): Log-rank test testing treatment effect within biomarker subgroups

wrapper_logistic_regression_biomarker(): Logistic regression estimating biomarker effect

wrapper_logistic_regression_core_interaction() wrapper_logistic_regression_core_interaction_strat(): Logistic regression with additive model with interaction

wrapper_logistic_regression_core_simple() wrapper_logistic_regression_core_simple_strat(): Logistic regression with simple additive model

wrapper_logistic_regression_interaction(): Logistic regression estimating effect of interaction between biomarker and treatment

wrapper_logistic_regression_treatment(): Logistic regression estimating treatment effect within biomarker subgroups

wrapper_max_text_height(): Maximum height of text

wrapper_max_text_width(): Maximum width of text

wrapper_merge_topTables(): Merge topTable results for multiple contrasts

wrapper_ncc_cox_regression_core_predictive(): Cox regression with additive model with interactions for Nested Case-Control NCC study

wrapper_ncc_cox_regression_core_predictive2(): Cox regression with additive model with interactions for Nested Case-Control NCC study

wrapper_ncc_cox_regression_core_prognostic(): Cox regression with simple additive model for Nested Case-Control NCC study

wrapper_ora(): Over-representation analysis (ORA)

wrapper_ora_core(): Over-representation analysis (ORA)

wrapper_ora_dotplot_multiple(): Dot plot with ORA results for multiple contrasts

wrapper_ora_dotplot_single(): Dot plot with ORA results for a single contrast

wrapper_pearsons_test_biomarker(): Testing biomarker effect on response with Pearson's Chi-squared test or Cochran-Mantel-Haenszel Chi-Squared Test

wrapper_pearsons_test_core() wrapper_pearsons_test_core_strat(): Pearson's Chi-squared test or Fisher's exact test or Cochran-Mantel-Haenszel Chi-Squared Test

wrapper_pearsons_test_treatment(): Testing treatment effect on response with Pearson's Chi-squared test or Cochran-Mantel-Haenszel Chi-Squared Test

wrapper_point_plot_core() wrapper_point_plot_core_strat(): Scatter plot

wrapper_print_plot_grid(): Spit a list of plots into chunks and plot them in a grid layout

wrapper_read_gmt(): Read gmt file and return a list of genes

wrapper_renumber_clusters(): Renumber clusters based on their splitting so they can be traced

wrapper_signature_heatmap(): Heatmap with signature and expression of genes defining that signature

wrapper_summarized_expression_dotplot(): Dotplot of gene expression summarized per group

wrapper_summarized_expression_heatmap(): Heatmap of gene expression summarized per group

wrapper_tile_plot1_core() wrapper_tile_plot2_core(): Tile plot

wrapper_write_gmt(): Write a list of genes into a gmt file