update shiny app branch

.Rbuildignore

@@ -20,4 +20,5 @@
 ^\\.git$
 ^codecov\.yml$
 ^vignettes/articles$
-^data_aux$
+^data_aux$ 
+^python(/.*)?$

.gitignore

@@ -18,3 +18,4 @@ markeR.Rproj
 inst/doc
 data_aux
 markeR.Rcheck 
+/python/.venv

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: markeR
 Title: An R Toolkit for Evaluating Gene Signatures as Phenotypic Markers
-Version: 1.1.0
+Version: 1.1.2
 Authors@R: 
     c(
       person("Rita", "Martins-Silva", 
@@ -25,7 +25,7 @@ Encoding: UTF-8
 Language: en-GB
 LazyData: false
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Additional_repositories: https://bioconductor.org/packages/release/bioc
 Imports:
     circlize,

NEWS.md

@@ -1,3 +1,28 @@
+# markeR 1.1.2 (12 Mar, 2026) 
+
+## Minor Changes
+- Moved Python bridge scripts from `inst/python/` to a top-level `python/` 
+  directory, as these are supplementary scripts not part of the R package itself.
+- Added `requirements.txt` to the `python/` directory listing all needed 
+  Python dependencies (`rpy2`, `pandas`, `numpy`, and optionally 
+  `ipython` and `jupyter`) for easier environment setup. 
+- Removed redundant code snippets from the Python bridge scripts.
+
+# markeR 1.1.1 (11 Mar, 2026) 
+
+  - Added `p.adjust.method` parameter across all functions performing or
+  depending on multiple testing correction, allowing users to specify
+  any correction method supported by `stats::p.adjust()`, beyond the default 
+  Benjamini-Hochberg FDR.
+- Added Python bridge scripts in `inst/python/` for users who wish to call
+  markeR from a Python environment via `rpy2`. Includes a tutorial workflow
+  script and a generic command-line wrapper capable of invoking any exported
+  markeR function. See `inst/python/README.md` for installation and usage.
+
+# markeR 1.0.0 (31 Oct, 2025)
+
+- Official Bioconductor Release.
+
 # markeR 0.99.5 (17 Sep, 2025)
 
 - Minor fix in `.onAttach()` to avoid errors when checking `ggplot2` version and ensure the startup warning works correctly.

R/FPR_Simulation.R

@@ -44,7 +44,11 @@ utils::globalVariables(c( "cohen", "method", "contrast" ))
 #'   grid layout. If `NULL`, layout is auto-calculated.
 #' @param nrow Integer. Number of rows for arranging signature plots in a grid
 #'   layout. If `NULL`, layout is auto-calculated.
-#'
+#' @param p.adjust.method Character string specifying the method to use for
+#'   multiple testing correction. Must be one of \code{"BH"} (Benjamini-Hochberg,
+#'   default), \code{"holm"}, \code{"hommel"}, \code{"bonferroni"},
+#'   \code{"BY"} (Benjamini-Yekutieli), \code{"fdr"}, or \code{"none"}.
+#'   Passed to \code{\link[stats]{p.adjust}}. 
 #'
 #' @return Invisibly returns a list containing:
 #'   \describe{
@@ -111,7 +115,7 @@ FPR_Simulation <- function(data, metadata, original_signatures, Variable,
                            gene_list = NULL, number_of_sims=100, title=NULL,
                            widthTitle = 30, titlesize = 12,  pointSize = 2,
                            labsize = 10,mode = c( "none","simple","medium","extensive"),
-                           ColorValues=NULL, ncol=NULL, nrow=NULL) {
+                           ColorValues=NULL, ncol=NULL, nrow=NULL, p.adjust.method="BH") {
   data <- as.data.frame(data) # Ensure data is a data frame
   if (is.null(gene_list)) gene_list <- row.names(data)
 
@@ -128,7 +132,7 @@ FPR_Simulation <- function(data, metadata, original_signatures, Variable,
       results <- suppressMessages(CohenF_allConditions(data = data,
                                                        metadata = metadata,
                                                        gene_sets = original_signatures,
-                                                       variable = Variable ))
+                                                       variable = Variable, p.adjust.method = p.adjust.method ))
       cohentype <- "f"
 
     } else {
@@ -138,15 +142,15 @@ FPR_Simulation <- function(data, metadata, original_signatures, Variable,
         results <- suppressMessages(CohenF_allConditions(data = data,
                                                          metadata = metadata,
                                                          gene_sets = original_signatures,
-                                                         variable = Variable ))
+                                                         variable = Variable, p.adjust.method = p.adjust.method ))
         cohentype <- "f"
 
       } else {
 
         results <- suppressMessages(CohenD_allConditions(data = data,
                                                          metadata = metadata,
                                                          gene_sets = original_signatures,
-                                                         variable = Variable, mode = mode))
+                                                         variable = Variable, mode = mode, p.adjust.method = p.adjust.method))
         cohentype <- "d"
 
       }
@@ -219,14 +223,14 @@ FPR_Simulation <- function(data, metadata, original_signatures, Variable,
         metadata = metadata,
         gene_sets = simulatedsigs,
         variable = Variable,
-        mode = mode
+        mode = mode, p.adjust.method = p.adjust.method
       ))
     } else {
       results2 <- suppressMessages(CohenF_allConditions(
         data = data,
         metadata = metadata,
         gene_sets = simulatedsigs,
-        variable = Variable
+        variable = Variable, p.adjust.method = p.adjust.method
       ))
     }
 

R/GSEA_VariableAssociation.R

@@ -57,7 +57,12 @@
 #'   removed before analysis, leading to a loss of data to be fitted in the
 #'   model.
 #' @param printplt Boolean specifying if plot is to be printed. Default: `TRUE`.
-#'
+#' @param p.adjust.method Character string specifying the method to use for
+#'   multiple testing correction. Must be one of \code{"BH"} (Benjamini-Hochberg,
+#'   default), \code{"holm"}, \code{"hommel"}, \code{"bonferroni"},
+#'   \code{"BY"} (Benjamini-Yekutieli), \code{"fdr"}, or \code{"none"}.
+#'   Passed to \code{\link[stats]{p.adjust}}. 
+#'   
 #' @return A list with two elements:
 #'   - `data`: A data frame containing the GSEA results, including normalized
 #'   enrichment scores (NES), adjusted p-values, and contrasts.
@@ -70,7 +75,8 @@ GSEA_VariableAssociation <- function(data, metadata, cols, stat=NULL,
                                      signif_color = "red", saturation_value=NULL,
                                      sig_threshold = 0.05, widthlabels=18,
                                      labsize=10, titlesize=14, pointSize=5,
-                                     ignore_NAs = FALSE, printplt =TRUE) {
+                                     ignore_NAs = FALSE, printplt =TRUE,
+                                     p.adjust.method = "BH") {
   data <- as.data.frame(data) # Ensure data is a data frame
   mode <- match.arg(mode)
   metadata <- metadata[, cols %in% colnames(metadata), drop = FALSE]
@@ -129,7 +135,7 @@ GSEA_VariableAssociation <- function(data, metadata, cols, stat=NULL,
   combined_results$Contrast <- cont_vec
 
   # correct adjusted p value to correct for multiple testing for the contrasts?
-  combined_results$padj <- stats::p.adjust(combined_results$padj, method = "BH")
+  combined_results$padj <- stats::p.adjust(combined_results$padj, method = p.adjust.method)
 
 
   combined_results_toreturn <- combined_results

R/Heatmap_Cohen.R

@@ -33,6 +33,7 @@
 #' @param ColorValues A character vector specifying the colors for the gradient
 #'   fill in the heatmaps. Default is \code{c("#F9F4AE", "#B44141")}.
 #' @param title Title for the grid of plots.
+#' 
 #' @return A list with two elements:
 #' \describe{
 #'   \item{plt}{A combined heatmap arranged in a grid using \code{ggpubr::ggarrange}.}
@@ -61,7 +62,7 @@
 #' @keywords internal
 Heatmap_Cohen <- function(cohenlist, nrow = NULL, ncol = NULL, limits = NULL,
                           widthTitle = 22, titlesize = 12, ColorValues = NULL,
-                          title=NULL ) {
+                          title=NULL) {
 
   cohentype <- ifelse("CohenD" %in% names(cohenlist[[1]]), "d",
                       ifelse("CohenF" %in% names(cohenlist[[1]]), "f", NULL))
@@ -201,7 +202,12 @@ Heatmap_Cohen <- function(cohenlist, nrow = NULL, ncol = NULL, limits = NULL,
 #' groups.
 #' - `"extensive"`: All possible groupwise contrasts, ensuring balance in the
 #' number of terms on each side.
-#'
+#' @param p.adjust.method Character string specifying the method to use for
+#'   multiple testing correction. Must be one of \code{"BH"} (Benjamini-Hochberg,
+#'   default), \code{"holm"}, \code{"hommel"}, \code{"bonferroni"},
+#'   \code{"BY"} (Benjamini-Yekutieli), \code{"fdr"}, or \code{"none"}.
+#'   Passed to \code{\link[stats]{p.adjust}}. 
+#'   
 #' @return A named list where each element corresponds to a gene signature. Each
 #'   signature element is a list with three components:
 #' \describe{
@@ -227,7 +233,7 @@ Heatmap_Cohen <- function(cohenlist, nrow = NULL, ncol = NULL, limits = NULL,
 #'
 #' @keywords internal
 CohenD_allConditions <- function(data, metadata, gene_sets, variable,
-                                 mode = c("simple","medium","extensive")) {
+                                 mode = c("simple","medium","extensive"), p.adjust.method = "BH") {
   data <- as.data.frame(data) # Ensure data is a data frame
   # Step 1: Check if variable exists in metadata
   if (!variable %in% colnames(metadata)) {
@@ -292,8 +298,8 @@ CohenD_allConditions <- function(data, metadata, gene_sets, variable,
     }
   }
 
-  # Step 2: Apply BH correction within each method
-  all_padj <- lapply(all_pvalues, function(pvals) stats::p.adjust(pvals, method = "BH"))
+  # Step 2: Apply  correction within each method
+  all_padj <- lapply(all_pvalues, function(pvals) stats::p.adjust(pvals, method = p.adjust.method))
 
   # Step 3: Store corrected p-values back into result_list
   index_tracker <- list()  # Track index position for each method
@@ -495,6 +501,12 @@ flatten_results <- function(nested_list) {
 #'   downregulated).
 #' @param variable A string specifying the categorical variable in
 #'   \code{metadata} used to model the gene signature scores.
+#' @param p.adjust.method Character string specifying the method to use for
+#'   multiple testing correction. Must be one of \code{"BH"} (Benjamini-Hochberg,
+#'   default), \code{"holm"}, \code{"hommel"}, \code{"bonferroni"},
+#'   \code{"BY"} (Benjamini-Yekutieli), \code{"fdr"}, or \code{"none"}.
+#'   Passed to \code{\link[stats]{p.adjust}}. 
+#'   
 #' @return A named list where each element corresponds to a gene signature. Each
 #'   signature element is a list with three components:
 #' \describe{
@@ -508,7 +520,7 @@ flatten_results <- function(nested_list) {
 #' }
 #'
 #' @keywords internal
-CohenF_allConditions <- function(data, metadata, gene_sets, variable ) {
+CohenF_allConditions <- function(data, metadata, gene_sets, variable, p.adjust.method = "BH" ) {
   data <- as.data.frame(data) # Ensure data is a data frame
   # Step 1: Check if variable exists in metadata
   if (!variable %in% colnames(metadata)) {
@@ -579,8 +591,8 @@ CohenF_allConditions <- function(data, metadata, gene_sets, variable ) {
     }
   }
 
-  # Step 2: Apply BH correction within each method
-  all_padj <- lapply(all_pvalues, function(pvals) stats::p.adjust(pvals, method = "BH"))
+  # Step 2: Apply   correction within each method
+  all_padj <- lapply(all_pvalues, function(pvals) stats::p.adjust(pvals, method = p.adjust.method))
 
   # Step 3: Store corrected p-values back into result_list
   index_tracker <- list()  # Track index position for each method

R/PlotScores.R

@@ -114,7 +114,12 @@ utils::globalVariables(c("score"))
 #' @param cor Correlation method for numeric variables. One of `"pearson"`
 #'   (default), `"spearman"`, or `"kendall"`. Only applies when the variable is
 #'   numeric and `method != "all"`.
-#'
+#' @param p.adjust.method Character string specifying the method to use for
+#'   multiple testing correction. Must be one of \code{"BH"} (Benjamini-Hochberg,
+#'   default), \code{"holm"}, \code{"hommel"}, \code{"bonferroni"},
+#'   \code{"BY"} (Benjamini-Yekutieli), \code{"fdr"}, or \code{"none"}.
+#'   Passed to \code{\link[stats]{p.adjust}}. Only if `method == "all"`.
+#'   
 #' @return Depending on `method`:
 #'
 #'   If `method = "all"`, returns a list with `heatmap` and `volcano` ggplot objects.
@@ -241,7 +246,8 @@ PlotScores <- function(data, metadata, gene_sets,
                        cond_cohend = NULL, pvalcalc = FALSE,
                        mode = c("simple","medium","extensive"),
                        widthlegend=22, sig_threshold=0.05, cohen_threshold=0.5,
-                       colorPalette="Set3", cor=c("pearson","spearman","kendall")) {
+                       colorPalette="Set3", cor=c("pearson","spearman","kendall"),
+                       p.adjust.method="BH") {
   data <- as.data.frame(data) # Ensure data is a data frame
   method <- match.arg(method)
   mode <- match.arg(mode)
@@ -254,13 +260,13 @@ PlotScores <- function(data, metadata, gene_sets,
     if (type =="Numeric"){
 
       cohenlist <- CohenF_allConditions(data = data, metadata = metadata,
-                                        gene_sets = gene_sets, variable = Variable )
+                                        gene_sets = gene_sets, variable = Variable, p.adjust.method = p.adjust.method )
 
     } else {
 
       cohenlist <- CohenD_allConditions(data = data, metadata = metadata,
                                         gene_sets = gene_sets, variable = Variable,
-                                        mode = mode)
+                                        mode = mode, p.adjust.method = p.adjust.method )
 
     }
 

R/Score_VariableAssociation.R

@@ -161,7 +161,12 @@ create_contrast_column <- function(metadata, variable_name, contrast) {
 #' @param color_palette A string specifying the color palette for discrete
 #' variables. Default: `"Set2"`.
 #' @param printplt Boolean specifying if plot is to be printed. Default: `TRUE`.
-#'
+#' @param p.adjust.method Character string specifying the method to use for
+#'   multiple testing correction. Must be one of \code{"BH"} (Benjamini-Hochberg,
+#'   default), \code{"holm"}, \code{"hommel"}, \code{"bonferroni"},
+#'   \code{"BY"} (Benjamini-Yekutieli), \code{"fdr"}, or \code{"none"}.
+#'   Passed to \code{\link[stats]{p.adjust}}. 
+#'   
 #' @return A list with:
 #'   - `Overall`: Data frame of effect sizes and p-values for each contrasted
 #'   phenotypic variable.
@@ -207,7 +212,8 @@ Score_VariableAssociation <- function(data,
                                       discrete_colors=NULL,
                                       continuous_color = "#8C6D03",
                                       color_palette = "Set2",
-                                      printplt =TRUE){
+                                      printplt =TRUE, 
+                                      p.adjust.method = "BH"){
   method <- match.arg(method)  # Validate method input
   mode <- match.arg(mode)
   data <- as.data.frame(data) # Ensure data is a data frame
@@ -296,8 +302,7 @@ Score_VariableAssociation <- function(data,
   # Would happen if we have only numeric variables
   if (nrow(df_results_contrast)!=0){
 
-    df_results_contrast$padj <- stats::p.adjust(df_results_contrast$PValue,
-                                         method = "BH")
+    df_results_contrast$padj <- stats::p.adjust(df_results_contrast$PValue,  method = p.adjust.method)
 
     if(is.null(saturation_value)){
       if (min(df_results_contrast$padj)>sig_threshold){

R/VariableAssociation.R

@@ -96,7 +96,12 @@ identify_variable_type <- function(df, cols = NULL) {
 #' @param categorical_multi The statistical test for multi-level categorical
 #' variables.
 #'   Options: `"anova"` (default) or `"kruskal-wallis"`.
-#'
+#' @param p.adjust.method Character string specifying the method to use for
+#'   multiple testing correction. Must be one of \code{"BH"} (Benjamini-Hochberg,
+#'   default), \code{"holm"}, \code{"hommel"}, \code{"bonferroni"},
+#'   \code{"BY"} (Benjamini-Yekutieli), \code{"fdr"}, or \code{"none"}.
+#'   Passed to \code{\link[stats]{p.adjust}}. 
+#'   
 #' @return A named list (one entry per variable being analysed) where each
 #' element is a data frame with:
 #'   - **Metric**: The test statistic (correlation coefficient, t-statistic,
@@ -130,7 +135,7 @@ identify_variable_type <- function(df, cols = NULL) {
 compute_stat_tests <- function(df, target_var, cols = NULL,
                                numeric = "pearson",
                                categorical_bin = "t.test",
-                               categorical_multi = "anova") {
+                               categorical_multi = "anova", p.adjust.method="BH") {
 
   # Ensure only one method is selected per variable type
   if (length(numeric) > 1 | length(categorical_bin) > 1 |
@@ -202,7 +207,7 @@ compute_stat_tests <- function(df, target_var, cols = NULL,
     # scientific notation
     test_df$metric <- formatC(test_df$metric, format = "e", digits = 2)
     # correct for multiple testing per variable
-    test_df$p_value <- stats::p.adjust(test_df$p_value, method = "BH")
+    test_df$p_value <- stats::p.adjust(test_df$p_value,  method = p.adjust.method)
     test_df$p_value <- formatC(test_df$p_value, format = "e", digits = 3)
 
 
@@ -267,7 +272,12 @@ compute_stat_tests <- function(df, target_var, cols = NULL,
 #' (`"B"` or `"t"`). Auto-detected if `NULL`.
 #' @param ignore_NAs (GSEA only) Logical. If `TRUE`, rows with NA metadata are
 #' removed. Default: `FALSE`.
-#'
+#' @param p.adjust.method Character string specifying the method to use for
+#'   multiple testing correction. Must be one of \code{"BH"} (Benjamini-Hochberg,
+#'   default), \code{"holm"}, \code{"hommel"}, \code{"bonferroni"},
+#'   \code{"BY"} (Benjamini-Yekutieli), \code{"fdr"}, or \code{"none"}.
+#'   Passed to \code{\link[stats]{p.adjust}}. 
+#'   
 #' @return A list with method-specific results and ggplot2-based visualizations:
 #'
 #' **For score-based methods (`logmedian`, `ssGSEA`, `ranking`):**
@@ -355,7 +365,8 @@ VariableAssociation <- function(method = c("ssGSEA", "logmedian",
                                 discrete_colors = NULL,
                                 continuous_color = "#8C6D03",
                                 color_palette = "Set2",
-                                printplt = TRUE) {
+                                printplt = TRUE, 
+                                p.adjust.method = "BH") {
   method <- match.arg(method)
   mode <- match.arg(mode)
   data <- as.data.frame(data) # Ensure data is a data frame
@@ -375,7 +386,8 @@ VariableAssociation <- function(method = c("ssGSEA", "logmedian",
       labsize = labsize,
       titlesize = titlesize,
       pointSize = pointSize,
-      ignore_NAs = ignore_NAs
+      ignore_NAs = ignore_NAs,
+      p.adjust.method = p.adjust.method
     )
 
   } else if (method %in% c("ssGSEA", "logmedian", "ranking")) {
@@ -397,7 +409,8 @@ VariableAssociation <- function(method = c("ssGSEA", "logmedian",
       discrete_colors = discrete_colors,
       continuous_color = continuous_color,
       color_palette = color_palette,
-      printplt = printplt
+      printplt = printplt,
+      p.adjust.method = p.adjust.method
     )
   }