diff --git a/DESCRIPTION b/DESCRIPTION
index ea3882d..1dfc1a5 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -27,14 +27,22 @@ Imports:
     umap,
     tibble,
     scales,
-    grid
+    grid,
+    utils,
+    patchwork
 Suggests: 
     biomaRt,
+    cowplot,
     dbscan,
     ggnewscale,
     ggrepel,
+    grDevices,
     matrixStats,
     openxlsx,
+    pheatmap,
+    readr,
     survival,
-    survminer
+    survminer,
+    tidyr,
+    tidyselect
 Roxygen: list(markdown = TRUE)
diff --git a/NAMESPACE b/NAMESPACE
index 9251469..821d6cc 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,23 +1,23 @@
 # Generated by roxygen2: do not edit by hand
 
 export(add_annotations)
+export(barplot_GSEA)
 export(detect_filter)
 export(get_annotations)
-export(merge_GSEA)
 export(get_stars)
-export(gsea_barplot)
-export(nice_BSV)
+export(heatmap_GSEA)
+export(merge_GSEA)
 export(nice_KM)
 export(nice_PCA)
 export(nice_UMAP)
+export(nice_VSB)
 export(nice_tSNE)
-export(plot_global_GSEA)
+export(plot_GSEA)
 export(power_analysis)
 export(save_results)
 export(split_cases)
-export(plotheatmap_leadingedge_GSEA)
 export(tpm)
-export(plot_global_GSEA)
 import(ggplot2)
 importFrom(magrittr,"%>%")
+importFrom(patchwork,plot_layout)
 importFrom(rlang,.data)
diff --git a/R/gsea_barplot.R b/R/barplot_GSEA.R
similarity index 85%
rename from R/gsea_barplot.R
rename to R/barplot_GSEA.R
index 69759f8..8339beb 100644
--- a/R/gsea_barplot.R
+++ b/R/barplot_GSEA.R
@@ -1,5 +1,5 @@
 #########################
-# Function gsea_barplot #
+# Function barplot_GSEA #
 #########################
 
 #' Create and save a customized barplot for GSEA results
@@ -13,15 +13,12 @@
 #' @param data A data frame containing GSEA results with columns such as `datatype`, `NES`, `-Log10FDR`, and `New_name`.
 #' @param output_path The file path where the barplot will be saved (SVG format).
 #' @param custom_labels A named vector of custom expressions for x-axis labels.
-#' @param height Height of the saved plot in inches. Default: 49.
-#' @param width Width of the saved plot in inches. Default: 30.
 #' @param axis_y Name of the column to use for the y-axis aesthetic, as a string. Default: "NES".
 #' @import ggplot2
 #' @importFrom rlang .data
 #' @export
 
-gsea_barplot <- function(data, output_path, custom_labels,
-                         height = 49, width = 30, axis_y = "NES")
+barplot_GSEA <- function(data, output_path, custom_labels, axis_y = "NES")
 
 {
   # Generate the barplot
@@ -56,6 +53,5 @@ gsea_barplot <- function(data, output_path, custom_labels,
     facet_wrap(~ .data$New_name, ncol = 2, strip.position = "left", scales = "free_y") +
     scale_x_discrete(labels = custom_labels)
 
-  # Save the barplot
-  ggsave(filename = output_path, plot = barplot, height = height, width = width, limitsize = FALSE)
+  return(barplot)
 }
diff --git a/R/heatmap_GSEA.R b/R/heatmap_GSEA.R
new file mode 100644
index 0000000..40ca338
--- /dev/null
+++ b/R/heatmap_GSEA.R
@@ -0,0 +1,165 @@
+#########################
+# Function heatmap_GSEA #
+#########################
+
+#' Plot leading edge heatmaps from GSEA results.
+#'
+#' Generates heatmaps of leading edge genes for each gene set from GSEA output.
+#'
+#' @param main_dir Optional base directory. If supplied, it will be prepended to all relative file paths.
+#' @param expression_file Path to the expression data file (tab-delimited) or relative to main_dir.
+#' @param metadata_file Path to the metadata file (Excel) or relative to main_dir.
+#' @param gmt_file Path to the GMT file defining gene sets or relative to main_dir.
+#' @param ranked_genes_file Path to the ranked genes list file or relative to main_dir.
+#' @param gsea_file Path to the GSEA results file with leading edge genes or relative to main_dir.
+#' @param output_dir Directory to save heatmaps and optional TSV; default "leading_edge_heatmaps".
+#' @param sample_col Name of the sample ID column in metadata; default "Sample".
+#' @param group_col Name of the group column in metadata; default "group".
+#' @param save_dataframe Logical; if TRUE, saves the merged data frame as TSV before plotting.
+#' @return Saves one PDF and one JPG heatmap per gene set under output_dir; optionally saves intermediate TSV.
+#' @export
+
+heatmap_GSEA <- function(main_dir = NULL, expression_file, metadata_file, gmt_file,
+                         ranked_genes_file, gsea_file, output_dir = "leading_edge_heatmaps",
+                         sample_col = "Sample", group_col = "group", save_dataframe = FALSE)
+{
+  # Ensure required packages are installed
+  if (!requireNamespace("readr", quietly = TRUE)) stop("Package \"readr\" must be installed to use this function.", call. = FALSE)
+  if (!requireNamespace("grDevices", quietly = TRUE)) stop("Package \"grDevices\" must be installed to use this function.", call. = FALSE)
+  if (!requireNamespace("tidyselect", quietly = TRUE)) stop("Package \"tidyselect\" must be installed to use this function.", call. = FALSE)
+  if (!requireNamespace("openxlsx", quietly = TRUE)) stop("Package \"openxlsx\" must be installed to use this function.", call. = FALSE)
+  if (!requireNamespace("pheatmap", quietly = TRUE)) stop("Package \"pheatmap\" must be installed to use this function.", call. = FALSE)
+
+  # Prepend base directory if provided
+  if (!is.null(main_dir)) {
+    expression_file <- file.path(main_dir, expression_file)
+    metadata_file <- file.path(main_dir, metadata_file)
+    gmt_file <- file.path(main_dir, gmt_file)
+    ranked_genes_file <- file.path(main_dir, ranked_genes_file)
+    gsea_file <- file.path(main_dir, gsea_file)
+    output_dir <- file.path(main_dir, output_dir)
+  }
+
+  # 1) Read and process GMT
+  gmt_data <- readLines(gmt_file) %>%
+    strsplit("\t") %>%
+    lapply(function(x) data.frame(NAME = x[1], DESCRIPTION = x[2], GENES = paste(x[-c(1,2)], collapse = ","), stringsAsFactors = FALSE)) %>%
+    dplyr::bind_rows()
+
+  # 2) Read GSEA results and join genes
+  gsea_df <- readr::read_tsv(gsea_file, show_col_types = FALSE) %>%
+    dplyr::left_join(gmt_data %>% dplyr::select(NAME, GENES), by = "NAME")
+
+  # 3) Read ranked genes list
+  ranked_df <- readr::read_tsv(ranked_genes_file, show_col_types = FALSE)
+  ranked_vector <- ranked_df[[1]]
+
+  # 4) Internal helper: extract top-n genes from leading edge
+  extract_top_n <- function(genes_str, n) {
+    if (is.na(genes_str) || n <= 0) return(NA_character_)
+    glist <- unlist(strsplit(genes_str, ","))
+    glist <- glist[order(match(glist, ranked_vector), na.last = TRUE)]
+    paste(utils::head(glist, n), collapse = ",")
+  }
+
+  # 5) Compute leading edge size and genes
+  gsea_df <- gsea_df %>%
+    dplyr::mutate(L.EDGE_size = ifelse(is.na(SIZE * tags), NA, ifelse((SIZE * tags) %% 1 <= 0.5, floor(SIZE * tags), ceiling(SIZE * tags)))) %>%
+    dplyr::rowwise() %>% dplyr::mutate(LEADING_EDGE_GENES = extract_top_n(GENES, L.EDGE_size)) %>%
+    dplyr::ungroup()
+
+  # Save intermediate dataframe if requested
+  if (save_dataframe) {
+    if (!dir.exists(output_dir)) dir.create(output_dir, recursive = TRUE)
+    intermediate_file <- file.path(output_dir, "leading_edge_genes_df.tsv")
+    readr::write_tsv(gsea_df, intermediate_file)
+    message("Saved data frame to: ", intermediate_file)
+  }
+
+  # 6) Read metadata and prepare annotation
+  meta <- openxlsx::read.xlsx(metadata_file) %>%
+    dplyr::select(tidyselect::all_of(c(sample_col, group_col))) %>%
+    dplyr::rename(Sample = tidyselect::all_of(sample_col), Group = tidyselect::all_of(group_col)) %>%
+    as.data.frame()
+  rownames(meta) <- meta$Sample
+
+  # 7) Read expression data
+  expr_raw <- utils::read.table(expression_file, header = TRUE, sep = "\t",
+                                stringsAsFactors = FALSE, check.names = FALSE)
+  # Determine gene-name column
+  if ("NAME" %in% colnames(expr_raw)) {
+    rownames(expr_raw) <- expr_raw$NAME
+    expr_mat <- expr_raw[, setdiff(colnames(expr_raw), "NAME"), drop = FALSE]
+  } else {
+    gene_col <- colnames(expr_raw)[1]
+    rownames(expr_raw) <- expr_raw[[gene_col]]
+    expr_mat <- expr_raw[, -1, drop = FALSE]
+  }
+  # Clean sample names
+  colnames(expr_mat) <- sub("^X", "", colnames(expr_mat))
+
+  # Ensure output directory exists
+  if (!dir.exists(output_dir)) dir.create(output_dir, recursive = TRUE)
+
+  # 8) Loop through each gene set and plot heatmap
+  for (i in seq_len(nrow(gsea_df))) {
+    geneset_name <- gsea_df$NAME[i]
+    leading_genes <- unlist(strsplit(gsea_df$LEADING_EDGE_GENES[i], ","))
+    genes_present <- leading_genes[leading_genes %in% rownames(expr_mat)]
+    if (length(genes_present) == 0) next
+
+    heatmap_mat <- expr_mat[genes_present, , drop = FALSE]
+    common_samps <- intersect(colnames(heatmap_mat), rownames(meta))
+    if (length(common_samps) == 0) next
+
+    heatmap_mat <- heatmap_mat[, common_samps, drop = FALSE]
+    annot_col <- data.frame(Group = meta[common_samps, "Group"])
+    rownames(annot_col) <- common_samps
+
+    # Dynamic sizing
+    w <- 10
+    h <- max(5, nrow(heatmap_mat) * 0.1 + 2)
+
+    # PDF output
+    grDevices::pdf(file.path(output_dir, paste0(geneset_name, "_heatmap.pdf")), width = w, height = h)
+    pheatmap::pheatmap(
+      heatmap_mat,
+      main = geneset_name,
+      color = grDevices::colorRampPalette(c("blue","white","red"))(30),
+      scale = "row",
+      clustering_distance_rows = "euclidean",
+      cluster_cols = FALSE,
+      clustering_method = "complete",
+      fontsize_row = 6,
+      fontsize_col = 7,
+      annotation_col = annot_col,
+      border_color = NA,
+      cellheight = 5,
+      cellwidth = 8
+    )
+    grDevices::dev.off()
+
+    # JPG output
+    grDevices::jpeg(file.path(output_dir, paste0(geneset_name, "_heatmap.jpg")),
+                    width = w * 100, height = h * 100, res = 150)
+    pheatmap::pheatmap(
+      heatmap_mat,
+      main = geneset_name,
+      color = grDevices::colorRampPalette(c("blue","white","red"))(30),
+      scale = "row",
+      clustering_distance_rows = "euclidean",
+      cluster_cols = FALSE,
+      clustering_method  = "complete",
+      fontsize_row = 6,
+      fontsize_col = 7,
+      annotation_col = annot_col,
+      border_color = NA,
+      cellheight = 5,
+      cellwidth = 8
+    )
+    grDevices::dev.off()
+  }
+
+  message("Heatmaps saved in: ", normalizePath(output_dir))
+  return(TRUE)
+}
diff --git a/R/merge_GSEA.R b/R/merge_GSEA.R
index a52618f..990d6b7 100644
--- a/R/merge_GSEA.R
+++ b/R/merge_GSEA.R
@@ -1,22 +1,23 @@
-
-# Function merge_GSEA #  
+#######################
+# Function merge_GSEA #
+#######################
 
 #' Merge GSEA results data frames.
-#' 
-#' After run GSEA_all.sh from GSEA.sh, merge_GSEA function join .tsv files to a single file 
-#' 
+#'
+#' After running GSEA_all.sh from GSEA.sh, merge_GSEA function joins .tsv files to a single file
+#'
 #' @param input_directory The directory containing the GSEA collection results in TSV format.
 #' @param output_file The output file to save the merged data. If not provided, the file will be saved in the input directory.
 #' @importFrom magrittr %>%
 #' @export
- 
+
 
 merge_GSEA <- function(input_directory, output_file = "collections_merged_gsea_data.tsv") {
-  
-  if (!requireNamespace("dplyr", quietly = TRUE)) {
-    stop("Package \"dplyr\" must be installed to use this function.", call. = FALSE)
-  }
- 
+
+  if (!requireNamespace("dplyr", quietly = TRUE)) stop("Package \"dplyr\" must be installed to use this function.", call. = FALSE)
+  if (!requireNamespace("readr", quietly = TRUE)) stop("Package \"readr\" must be installed to use this function.", call. = FALSE)
+  if (!requireNamespace("tidyr", quietly = TRUE)) stop("Package \"tidyr\" must be installed to use this function.", call. = FALSE)
+
   # Validate input directory and check for TSV files
   if (!dir.exists(input_directory)) {
     stop("The specified directory does not exist: ", input_directory)
@@ -25,7 +26,7 @@ merge_GSEA <- function(input_directory, output_file = "collections_merged_gsea_d
   if (length(files) == 0) {
     stop("No TSV files found in ", input_directory)
   }
-  
+
   # Function to read each file and add a column with the modified file name
   read_file <- function(file) {
     data <- readr::read_tsv(file)
@@ -33,7 +34,7 @@ merge_GSEA <- function(input_directory, output_file = "collections_merged_gsea_d
     file_name <- sub("_all.tsv$", "", file_name)  # Change the pattern if necessary
     numeric_cols <- c("SIZE", "ES", "NES", "NOM p-val", "FDR q-val", "FWER p-val", "RANK AT MAX")
     data <- data %>%
-      dplyr::mutate(across(tidyselect::all_of(numeric_cols), as.numeric))
+      dplyr::mutate(dplyr::across(tidyselect::all_of(numeric_cols), as.numeric))
     data$COLLECTION <- file_name
     return(data)
   }
@@ -43,12 +44,12 @@ merge_GSEA <- function(input_directory, output_file = "collections_merged_gsea_d
 
  # Find problematic values in numeric columns
   gsea_data %>%
-    dplyr::filter(dplyr::if_any(all_of(numeric_cols), ~ !grepl("^-?[0-9.]+$", .))) %>%
+    dplyr::filter(dplyr::if_any(tidyselect::all_of(numeric_cols), ~ !grepl("^-?[0-9.]+$", .))) %>%
     print()
-  
+
   # Data processing: selection, separation, mutation, and renaming of columns
   gsea_data <- gsea_data %>%
-    dplyr::select(-"GS<br> follow link to MSigDB", -"GS DETAILS") %>% 
+    dplyr::select(-"GS<br> follow link to MSigDB", -"GS DETAILS") %>%
     tidyr::separate(col = `LEADING EDGE`, into = c("tags", "list", "signal"), sep = ",", remove = FALSE) %>%
     dplyr::mutate(
       tags = 0.01 * as.numeric(sub("%", "", sub("tags=", "", tags))),
@@ -59,8 +60,10 @@ merge_GSEA <- function(input_directory, output_file = "collections_merged_gsea_d
     ) %>%
     dplyr::relocate(`Log10FDR`, .after = `FWER p-val`) %>%
     dplyr::rename(COMPARISON = Comparison, FDR = `FDR q-val`)
-  
+
   # Save the processed data to a TSV file
   readr::write_tsv(gsea_data, output_file)
-  cat("GSEA data saved to:", output_file, "\n")
+  message("GSEA data saved to:", output_file, "\n")
+
+  return(TRUE)
 }
diff --git a/R/nice_BSV.R b/R/nice_VSB.R
similarity index 95%
rename from R/nice_BSV.R
rename to R/nice_VSB.R
index 0b80c81..97be5c6 100644
--- a/R/nice_BSV.R
+++ b/R/nice_VSB.R
@@ -1,8 +1,8 @@
-#######################
-# Function nice_BSV.R #
-#######################
+#####################
+# Function nice_VSB #
+#####################
 
-#' Function to make Box-Scatter-Violin plots.
+#' Function to make Violin-Scatter-Box plots.
 #'
 #' This function will make a Boxplot, using a DEseq object.
 #' It will show the data points on top with a small deviation (jitter) for a better visualization.
@@ -27,7 +27,7 @@
 #' @importFrom rlang .data
 #' @export
 
-nice_BSV <- function (object = NULL, annotations, variables = c(fill = "VarFill", shape = "VarShape"),
+nice_VSB <- function (object = NULL, annotations, variables = c(fill = "VarFill", shape = "VarShape"),
                       genename = NULL, symbol = NULL, labels = c("N", "P", "R", "M"),
                       categories = c("normal", "primary", "recurrence", "metastasis"),
                       colors = NULL, shapes = NULL, markersize = NULL, alpha = 0.8, jitter = 0.2,
diff --git a/R/plot_GSEA.R b/R/plot_GSEA.R
index 1c79858..3be4b21 100644
--- a/R/plot_GSEA.R
+++ b/R/plot_GSEA.R
@@ -1,114 +1,117 @@
-#' Plot global GSEA results
-#'
-#' Generates a composite plot displaying NES values, pathway labels,
-#' and a \emph{logFDR} legend, organized by MSigDB collections.
-#'
-#' @param data Data frame containing the GSEA results.
-#' @param geneset_col Name of the column containing the genesets.
-#' @param collection_col Name of the column containing the collections.
-#' @param nes_col Name of the column containing the NES values.
-#' @param logfdr_col Name of the column containing \eqn{-\log_{10}(FDR)} values.
-#' @param output_path_base Path and base name for the output files (without extension).
-#' @param width_output Plot width in inches.
-#' @param height_output Plot height in inches.
-#' @param text_size_genesets Text size for the geneset labels.
-#' @param text_size_collection Text size for the collection labels.
-#' @return Saves two files: \code{output_path_base}.jpg and \code{output_path_base}.pdf.
-#' @import ggplot2 patchwork cowplot scales
-#' @export
-plot_GSEA <- function(data, geneset_col, collection_col, nes_col, logfdr_col, output_path_base, width_output, height_output, text_size_genesets = 5, text_size_collection = 5) {
-  
-  # Rename columns dynamically
-  data <- data[, c(geneset_col, collection_col, nes_col, logfdr_col)]
-  colnames(data) <- c("Geneset", "Collection", "NES", "logFDR")
-  
-  # Order data by NES value (descending)
-  data <- data[order(data$NES, decreasing = TRUE), ]
-  
-  # Ensure Geneset and Collection are factors with ordered levels
-  data$Geneset <- factor(data$Geneset, levels = rev(unique(data$Geneset)))
-  data$Collection <- factor(data$Collection, levels = unique(data$Collection))
-  
-  # Right-side label: "MSigDB" vertically centered, in bold and italic
-  plot_text_msigdb <- ggplot() + 
-    annotate("text", label = "MSigDB", fontface = "bold.italic", angle = 90, size = 35, x = 0, y = 0.5)+
-    theme_void()
-  
-  # Lef-side label: "Pathways" vertically centered, in bold and italic
-  plot_text_pathways <- ggplot() + 
-    annotate("text", label = "Pathways", fontface = "bold.italic", angle = 90, size = 35, x = 0, y = 0.5)+
-    theme_void()
-  
-  # Right panel: Collection labels (without repetition)
-  plot_right <- ggplot(data, aes(y = Geneset, x = 1.5, label = Collection)) +
-    geom_text(aes(label = ifelse(duplicated(Collection), "", Collection)), 
-              hjust = 0.5, size = 0, fontface = "bold") +  
-    facet_grid(Collection ~ ., scales = "free_y", space = "free", switch = "y") + 
-    theme_void() + 
-    theme(strip.text.y = element_text(angle = 0, hjust = 1, size = text_size_collection),
-          panel.spacing = unit(1, "lines"))
-  
-  # Center panel: NES bar plot
-  plot_center <- ggplot(data, aes(x = NES, y = Geneset, fill = logFDR)) +
-    geom_col(color = "black", size = 1) +
-    scale_fill_gradient(low = "white", high = "red", 
-                        limits = c(0,3), breaks = seq(0,3,1)) +
-    scale_y_discrete(position = "right") +  
-    facet_grid(Collection ~ ., scales = "free_y", space = "free_y") +
-    theme_bw() +
-    labs(x = "NES", y = "") +
-    theme(axis.text.y = element_blank(),
-          strip.background = element_rect(fill = "white", color = "black",linewidth = 1 ),
-          axis.ticks.y = element_line(color = "black", size = 1.5),
-          axis.ticks.length = unit(0.3, "cm"),
-          strip.text.y = element_text(size = 1, margin = margin(0, 0, 0, 0)),# element_blank(),
-          legend.position = "none",
-          axis.title.x = element_text(size = 49),
-          axis.text.x = element_text(size = 45),
-          panel.spacing = unit(4, "lines")
-    )
-  
-  # Left panel: Pathays labels
-  plot_left <- ggplot(data, aes(y = Geneset, x = 0, label = Geneset)) +
-    geom_text(hjust = 1, size = text_size_genesets) +  
-    theme_void() + 
-    theme(axis.text.y = element_blank(),
-          plot.margin = margin(0, 0, 0, -50))
-  
-  # Legend panel
-  plot_legend <- ggplot(data, aes(x = NES, y = Geneset, fill = logFDR)) +
-    geom_tile() + 
-    scale_fill_gradient(low = "white", high = "red",
-                        name = expression(-log[10] ~ FDR),  # log10FDR with subscrip,
-                        limits = c(0,3), breaks = seq(0,3,1),
-                        guide = guide_colorbar(ticks.colour = "black",   # Make ticks black
-                                               ticks.linewidth = 1.5,    # Make ticks thicker
-                                               draw.ulim = TRUE,       # Draw upper limit tick
-                                               draw.llim = TRUE)) +    # Draw lower limit tick  
-    theme_bw() +
-    theme(legend.position = "right",
-          legend.box = "vertical",
-          legend.title = element_text(size = 44, hjust = 0.5, face = "bold"),  # Bigger title
-          legend.text = element_text(size = 30),  # Bigger legend text
-          legend.key.size = unit(1.5, "cm"),  # Bigger color key size
-          legend.key.height = unit(2, "cm"),  # Increase the height of the legend box
-          legend.spacing = unit(3.5, "cm"),  # More space between title and legend
-          legend.box.margin = margin(10, 20, 10, 10))#5, 5, 10, 5))  # Adjust internal spacing
-  
-  plot_legend <- plot_legend + theme(legend.box = "vertical")
-  plot_right_legend <- get_legend(plot_legend)
-  
-  # Extract legend
-  #plot_right_legend <- get_legend(plot_legend)
-  
-  # Combine all plots
-  final_plot <- plot_text_pathways + plot_left +  plot_center + plot_right + plot_text_msigdb + plot_right_legend + 
-    plot_layout(ncol = 6, widths = c(4, 25, 15, 3, 10, 3))  
-  
-  # Display the plot
-  #print(final_plot)
-  
-  # Save the plot as JPG and PDF
-  ggsave(paste0(output_path_base, ".jpg"), final_plot, width = width_output, height = height_output, units = "in", dpi = 300)
-  ggsave(paste0(output_path_base, ".pdf"), final_plot, width = width_output, height = height_output, units = "in")
-}
+######################
+# Function plot_GSEA #
+######################
+
+#' Plot global GSEA results
+#'
+#' Generates a composite plot displaying NES values, pathway labels,
+#' and a \emph{logFDR} legend, organized by MSigDB collections.
+#'
+#' @param data Data frame containing the GSEA results.
+#' @param geneset_col Name of the column containing the genesets.
+#' @param collection_col Name of the column containing the collections.
+#' @param nes_col Name of the column containing the NES values.
+#' @param logfdr_col Name of the column containing \eqn{-\log_{10}(FDR)} values.
+#' @param text_size_genesets Text size for the geneset labels.
+#' @param text_size_collection Text size for the collection labels.
+#' @import ggplot2
+#' @importFrom patchwork plot_layout
+#' @return GSEA barplots arranged in a grid.
+#' @export
+
+plot_GSEA <- function(data, geneset_col, collection_col, nes_col, logfdr_col,
+                      text_size_genesets = 5, text_size_collection = 5)
+{
+
+  if (!requireNamespace("patchwork", quietly = TRUE)) stop("Package \"patchwork\" must be installed to use this function.", call. = FALSE)
+  if (!requireNamespace("cowplot", quietly = TRUE)) stop("Package \"cowplot\" must be installed to use this function.", call. = FALSE)
+
+  # Rename columns dynamically
+  data <- data[, c(geneset_col, collection_col, nes_col, logfdr_col)]
+  colnames(data) <- c("Geneset", "Collection", "NES", "logFDR")
+
+  # Order data by NES value (descending)
+  data <- data[order(data$NES, decreasing = TRUE), ]
+
+  # Ensure Geneset and Collection are factors with ordered levels
+  data$Geneset <- factor(data$Geneset, levels = rev(unique(data$Geneset)))
+  data$Collection <- factor(data$Collection, levels = unique(data$Collection))
+
+  # Right-side label: "MSigDB" vertically centered, in bold and italic
+  plot_text_msigdb <- ggplot() +
+    annotate("text", label = "MSigDB", fontface = "bold.italic", angle = 90, size = 35, x = 0, y = 0.5)+
+    theme_void()
+
+  # Lef-side label: "Pathways" vertically centered, in bold and italic
+  plot_text_pathways <- ggplot() +
+    annotate("text", label = "Pathways", fontface = "bold.italic", angle = 90, size = 35, x = 0, y = 0.5)+
+    theme_void()
+
+  # Right panel: Collection labels (without repetition)
+  plot_right <- ggplot(data, aes(y = Geneset, x = 1.5, label = Collection)) +
+    geom_text(aes(label = ifelse(duplicated(Collection), "", Collection)),
+              hjust = 0.5, size = 0, fontface = "bold") +
+    facet_grid(Collection ~ ., scales = "free_y", space = "free", switch = "y") +
+    theme_void() +
+    theme(strip.text.y = element_text(angle = 0, hjust = 1, size = text_size_collection),
+          panel.spacing = grid::unit(1, "lines"))
+
+  # Center panel: NES bar plot
+  plot_center <- ggplot(data, aes(x = NES, y = Geneset, fill = logFDR)) +
+    geom_col(color = "black", size = 1) +
+    scale_fill_gradient(low = "white", high = "red",
+                        limits = c(0,3), breaks = seq(0,3,1)) +
+    scale_y_discrete(position = "right") +
+    facet_grid(Collection ~ ., scales = "free_y", space = "free_y") +
+    theme_bw() +
+    labs(x = "NES", y = "") +
+    theme(axis.text.y = element_blank(),
+          strip.background = element_rect(fill = "white", color = "black",linewidth = 1 ),
+          axis.ticks.y = element_line(color = "black", size = 1.5),
+          axis.ticks.length = grid::unit(0.3, "cm"),
+          strip.text.y = element_text(size = 1, margin = margin(0, 0, 0, 0)),# element_blank(),
+          legend.position = "none",
+          axis.title.x = element_text(size = 49),
+          axis.text.x = element_text(size = 45),
+          panel.spacing = grid::unit(4, "lines")
+    )
+
+  # Left panel: Pathays labels
+  plot_left <- ggplot(data, aes(y = Geneset, x = 0, label = Geneset)) +
+    geom_text(hjust = 1, size = text_size_genesets) +
+    theme_void() +
+    theme(axis.text.y = element_blank(),
+          plot.margin = margin(0, 0, 0, -50))
+
+  # Legend panel
+  plot_legend <- ggplot(data, aes(x = NES, y = Geneset, fill = logFDR)) +
+    geom_tile() +
+    scale_fill_gradient(low = "white", high = "red",
+                        name = expression(-log[10] ~ FDR),  # log10FDR with subscrip,
+                        limits = c(0,3), breaks = seq(0,3,1),
+                        guide = guide_colorbar(ticks.colour = "black",   # Make ticks black
+                                               ticks.linewidth = 1.5,    # Make ticks thicker
+                                               draw.ulim = TRUE,       # Draw upper limit tick
+                                               draw.llim = TRUE)) +    # Draw lower limit tick
+    theme_bw() +
+    theme(legend.position = "right",
+          legend.box = "vertical",
+          legend.title = element_text(size = 44, hjust = 0.5, face = "bold"),  # Bigger title
+          legend.text = element_text(size = 30),  # Bigger legend text
+          legend.key.size = grid::unit(1.5, "cm"),  # Bigger color key size
+          legend.key.height = grid::unit(2, "cm"),  # Increase the height of the legend box
+          legend.spacing = grid::unit(3.5, "cm"),  # More space between title and legend
+          legend.box.margin = margin(10, 20, 10, 10)) # 5, 5, 10, 5))  # Adjust internal spacing
+
+  plot_legend <- plot_legend + theme(legend.box = "vertical")
+  plot_right_legend <- cowplot::get_legend(plot_legend)
+
+  # Extract legend
+  #plot_right_legend <- get_legend(plot_legend)
+
+  # Combine all plots
+  final_plot <- plot_text_pathways + plot_left +  plot_center + plot_right + plot_text_msigdb + plot_right_legend +
+    patchwork::plot_layout(ncol = 6, widths = c(4, 25, 15, 3, 10, 3))
+
+  return(final_plot)
+}
diff --git a/R/plotheatmap_leadingedge_GSEA.R b/R/plotheatmap_leadingedge_GSEA.R
deleted file mode 100644
index c770b3e..0000000
--- a/R/plotheatmap_leadingedge_GSEA.R
+++ /dev/null
@@ -1,185 +0,0 @@
-#' Plot leading edge heatmaps from GSEA results
-#'
-#' Generates heatmaps for leading edge genes of each gene set from GSEA output.
-#'
-#' @param main_dir_2 Optional base directory to prepend to file paths.
-#' @param expression_file Path to the expression data file (tab-delimited) or relative to main_dir_2.
-#' @param metadata_file Path to the metadata file (Excel) or relative to main_dir_2.
-#' @param gmt_file Path to the GMT file defining gene sets or relative to main_dir_2.
-#' @param ranked_genes_file Path to the ranked genes list file or relative to main_dir_2.
-#' @param gsea_file Path to the GSEA results file with leading edge genes or relative to main_dir_2.
-#' @param output_dir Directory to save heatmaps and optional TSV; default "leading_edge_heatmaps".
-#' @param sample_col Name of the sample ID column in metadata; default "Sample".
-#' @param group_col Name of the group column in metadata; default "group".
-#' @param save_dataframe Logical; if TRUE, saves the merged data frame as TSV before plotting.
-#' @return Saves one PDF and one JPG heatmap per gene set under output_dir; optionally saves intermediate TSV.
-#' @import dplyr readr tidyr readxl pheatmap
-#' @export
-plotheatmap_leadingedge_GSEA <- function(
-  main_dir_2         = NULL,
-  expression_file,
-  metadata_file,
-  gmt_file,
-  ranked_genes_file,
-  gsea_file,
-  output_dir        = "leading_edge_heatmaps",
-  sample_col        = "Sample",
-  group_col         = "group",
-  save_dataframe    = FALSE
-) {
-  # Ensure required packages are installed
-  if (!requireNamespace("dplyr", quietly = TRUE)) stop("Package 'dplyr' is required.")
-  if (!requireNamespace("readr", quietly = TRUE)) stop("Package 'readr' is required.")
-  if (!requireNamespace("tidyr", quietly = TRUE)) stop("Package 'tidyr' is required.")
-  if (!requireNamespace("readxl", quietly = TRUE)) stop("Package 'readxl' is required.")
-  if (!requireNamespace("pheatmap", quietly = TRUE)) stop("Package 'pheatmap' is required.")
-
-  # Prepend base directory if provided
-  if (!is.null(main_dir_2)) {
-    expression_file   <- file.path(main_dir_2, expression_file)
-    metadata_file     <- file.path(main_dir_2, metadata_file)
-    gmt_file          <- file.path(main_dir_2, gmt_file)
-    ranked_genes_file <- file.path(main_dir_2, ranked_genes_file)
-    gsea_file         <- file.path(main_dir_2, gsea_file)
-    output_dir        <- file.path(main_dir_2, output_dir)
-  }
-
-  # 1) Read and process GMT
-  gmt_data <- readLines(gmt_file) %>%
-    strsplit("\t") %>%
-    lapply(function(x) data.frame(
-      NAME        = x[1],
-      DESCRIPTION = x[2],
-      GENES       = paste(x[-c(1,2)], collapse = ","),
-      stringsAsFactors = FALSE
-    )) %>%
-    dplyr::bind_rows()
-
-  # 2) Read GSEA results and join genes
-  gsea_df <- readr::read_tsv(gsea_file, show_col_types = FALSE) %>%
-    dplyr::left_join(gmt_data %>% dplyr::select(NAME, GENES), by = "NAME")
-
-  # 3) Read ranked genes list
-  ranked_df     <- readr::read_tsv(ranked_genes_file, show_col_types = FALSE)
-  ranked_vector <- ranked_df[[1]]
-
-  # 4) Internal helper: extract top-n genes from leading edge
-  extract_top_n <- function(genes_str, n) {
-    if (is.na(genes_str) || n <= 0) return(NA_character_)
-    glist <- unlist(strsplit(genes_str, ","))
-    glist <- glist[order(match(glist, ranked_vector), na.last = TRUE)]
-    paste(head(glist, n), collapse = ",")
-  }
-
-  # 5) Compute leading edge size and genes
-  gsea_df <- gsea_df %>%
-    dplyr::mutate(
-      L.EDGE_size = ifelse(
-        is.na(SIZE * tags), NA,
-        ifelse((SIZE * tags) %% 1 <= 0.5,
-               floor(SIZE * tags),
-               ceiling(SIZE * tags))
-      )
-    ) %>%
-    dplyr::rowwise() %>%
-    dplyr::mutate(
-      LEADING_EDGE_GENES = extract_top_n(GENES, L.EDGE_size)
-    ) %>%
-    dplyr::ungroup()
-
-  # Save intermediate dataframe if requested
-  if (save_dataframe) {
-    if (!dir.exists(output_dir)) dir.create(output_dir, recursive = TRUE)
-    intermediate_file <- file.path(output_dir, "leading_edge_genes_df.tsv")
-    readr::write_tsv(gsea_df, intermediate_file)
-    message("Saved data frame to: ", intermediate_file)
-  }
-
-  # 6) Read metadata and prepare annotation
-  meta <- readxl::read_xlsx(metadata_file) %>%
-    dplyr::select(dplyr::all_of(c(sample_col, group_col))) %>%
-    dplyr::rename(Sample = dplyr::all_of(sample_col),
-                  Group  = dplyr::all_of(group_col)) %>%
-    as.data.frame()
-  rownames(meta) <- meta$Sample
-
-  # 7) Read expression data
-  expr_raw <- read.table(expression_file, header = TRUE, sep = "\t",
-                         stringsAsFactors = FALSE, check.names = FALSE)
-  # Determine gene-name column
-  if ("NAME" %in% colnames(expr_raw)) {
-    rownames(expr_raw) <- expr_raw$NAME
-    expr_mat <- expr_raw[, setdiff(colnames(expr_raw), "NAME"), drop = FALSE]
-  } else {
-    gene_col  <- colnames(expr_raw)[1]
-    rownames(expr_raw) <- expr_raw[[gene_col]]
-    expr_mat  <- expr_raw[, -1, drop = FALSE]
-  }
-  # Clean sample names
-  colnames(expr_mat) <- sub("^X", "", colnames(expr_mat))
-
-  # Ensure output directory exists
-  if (!dir.exists(output_dir)) dir.create(output_dir, recursive = TRUE)
-
-  # 8) Loop through each gene set and plot heatmap
-  for (i in seq_len(nrow(gsea_df))) {
-    geneset_name   <- gsea_df$NAME[i]
-    leading_genes  <- unlist(strsplit(gsea_df$LEADING_EDGE_GENES[i], ","))
-    genes_present  <- leading_genes[leading_genes %in% rownames(expr_mat)]
-    if (length(genes_present) == 0) next
-
-    heatmap_mat <- expr_mat[genes_present, , drop = FALSE]
-    common_samps <- intersect(colnames(heatmap_mat), rownames(meta))
-    if (length(common_samps) == 0) next
-
-    heatmap_mat   <- heatmap_mat[, common_samps, drop = FALSE]
-    annot_col     <- data.frame(Group = meta[common_samps, "Group"])
-    rownames(annot_col) <- common_samps
-
-    # Dynamic sizing
-    w <- 10
-    h <- max(5, nrow(heatmap_mat) * 0.1 + 2)
-
-    # PDF output
-    pdf(file.path(output_dir, paste0(geneset_name, "_heatmap.pdf")),
-        width = w, height = h)
-    pheatmap::pheatmap(
-      heatmap_mat,
-      main               = geneset_name,
-      color              = colorRampPalette(c("blue","white","red"))(30),
-      scale              = "row",
-      clustering_distance_rows = "euclidean",
-      cluster_cols       = FALSE,
-      clustering_method  = "complete",
-      fontsize_row       = 6,
-      fontsize_col       = 7,
-      annotation_col     = annot_col,
-      border_color       = NA,
-      cellheight         = 5,
-      cellwidth          = 8
-    )
-    dev.off()
-
-    # JPG output
-    jpeg(file.path(output_dir, paste0(geneset_name, "_heatmap.jpg")),
-         width = w * 100, height = h * 100, res = 150)
-    pheatmap::pheatmap(
-      heatmap_mat,
-      main               = geneset_name,
-      color              = colorRampPalette(c("blue","white","red"))(30),
-      scale              = "row",
-      clustering_distance_rows = "euclidean",
-      cluster_cols       = FALSE,
-      clustering_method  = "complete",
-      fontsize_row       = 6,
-      fontsize_col       = 7,
-      annotation_col     = annot_col,
-      border_color       = NA,
-      cellheight         = 5,
-      cellwidth          = 8
-    )
-    dev.off()
-  }
-
-  message("Heatmaps saved in: ", normalizePath(output_dir))
-}
diff --git a/man/gsea_barplot.Rd b/man/barplot_GSEA.Rd
similarity index 69%
rename from man/gsea_barplot.Rd
rename to man/barplot_GSEA.Rd
index fd67b12..ba47ad0 100644
--- a/man/gsea_barplot.Rd
+++ b/man/barplot_GSEA.Rd
@@ -1,17 +1,10 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/gsea_barplot.R
-\name{gsea_barplot}
-\alias{gsea_barplot}
+% Please edit documentation in R/barplot_GSEA.R
+\name{barplot_GSEA}
+\alias{barplot_GSEA}
 \title{Create and save a customized barplot for GSEA results}
 \usage{
-gsea_barplot(
-  data,
-  output_path,
-  custom_labels,
-  height = 49,
-  width = 30,
-  axis_y = "NES"
-)
+barplot_GSEA(data, output_path, custom_labels, axis_y = "NES")
 }
 \arguments{
 \item{data}{A data frame containing GSEA results with columns such as \code{datatype}, \code{NES}, \code{-Log10FDR}, and \code{New_name}.}
@@ -20,10 +13,6 @@ gsea_barplot(
 
 \item{custom_labels}{A named vector of custom expressions for x-axis labels.}
 
-\item{height}{Height of the saved plot in inches. Default: 49.}
-
-\item{width}{Width of the saved plot in inches. Default: 30.}
-
 \item{axis_y}{Name of the column to use for the y-axis aesthetic, as a string. Default: "NES".}
 }
 \description{
diff --git a/man/heatmap_GSEA.Rd b/man/heatmap_GSEA.Rd
new file mode 100644
index 0000000..788d4b0
--- /dev/null
+++ b/man/heatmap_GSEA.Rd
@@ -0,0 +1,46 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/heatmap_GSEA.R
+\name{heatmap_GSEA}
+\alias{heatmap_GSEA}
+\title{Plot leading edge heatmaps from GSEA results.}
+\usage{
+heatmap_GSEA(
+  main_dir = NULL,
+  expression_file,
+  metadata_file,
+  gmt_file,
+  ranked_genes_file,
+  gsea_file,
+  output_dir = "leading_edge_heatmaps",
+  sample_col = "Sample",
+  group_col = "group",
+  save_dataframe = FALSE
+)
+}
+\arguments{
+\item{main_dir}{Optional base directory. If supplied, it will be prepended to all relative file paths.}
+
+\item{expression_file}{Path to the expression data file (tab-delimited) or relative to main_dir.}
+
+\item{metadata_file}{Path to the metadata file (Excel) or relative to main_dir.}
+
+\item{gmt_file}{Path to the GMT file defining gene sets or relative to main_dir.}
+
+\item{ranked_genes_file}{Path to the ranked genes list file or relative to main_dir.}
+
+\item{gsea_file}{Path to the GSEA results file with leading edge genes or relative to main_dir.}
+
+\item{output_dir}{Directory to save heatmaps and optional TSV; default "leading_edge_heatmaps".}
+
+\item{sample_col}{Name of the sample ID column in metadata; default "Sample".}
+
+\item{group_col}{Name of the group column in metadata; default "group".}
+
+\item{save_dataframe}{Logical; if TRUE, saves the merged data frame as TSV before plotting.}
+}
+\value{
+Saves one PDF and one JPG heatmap per gene set under output_dir; optionally saves intermediate TSV.
+}
+\description{
+Generates heatmaps of leading edge genes for each gene set from GSEA output.
+}
diff --git a/man/merge_GSEA.Rd b/man/merge_GSEA.Rd
index fab3e99..d845bc8 100644
--- a/man/merge_GSEA.Rd
+++ b/man/merge_GSEA.Rd
@@ -4,7 +4,7 @@
 \alias{merge_GSEA}
 \title{Merge GSEA results data frames.}
 \usage{
-merge_GSEA(input_directory, output_file)
+merge_GSEA(input_directory, output_file = "collections_merged_gsea_data.tsv")
 }
 \arguments{
 \item{input_directory}{The directory containing the GSEA collection results in TSV format.}
@@ -12,5 +12,5 @@ merge_GSEA(input_directory, output_file)
 \item{output_file}{The output file to save the merged data. If not provided, the file will be saved in the input directory.}
 }
 \description{
-After run GSEA_all.sh from GSEA.sh, move the .tsv files to a single directory
+After running GSEA_all.sh from GSEA.sh, merge_GSEA function joins .tsv files to a single file
 }
diff --git a/man/nice_BSV.Rd b/man/nice_VSB.Rd
similarity index 93%
rename from man/nice_BSV.Rd
rename to man/nice_VSB.Rd
index ba5a925..c7ad3c4 100644
--- a/man/nice_BSV.Rd
+++ b/man/nice_VSB.Rd
@@ -1,10 +1,10 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/nice_BSV.R
-\name{nice_BSV}
-\alias{nice_BSV}
-\title{Function to make Box-Scatter-Violin plots.}
+% Please edit documentation in R/nice_VSB.R
+\name{nice_VSB}
+\alias{nice_VSB}
+\title{Function to make Violin-Scatter-Box plots.}
 \usage{
-nice_BSV(
+nice_VSB(
   object = NULL,
   annotations,
   variables = c(fill = "VarFill", shape = "VarShape"),
diff --git a/man/plot_GSEA.Rd b/man/plot_GSEA.Rd
new file mode 100644
index 0000000..9e39ad3
--- /dev/null
+++ b/man/plot_GSEA.Rd
@@ -0,0 +1,38 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plot_GSEA.R
+\name{plot_GSEA}
+\alias{plot_GSEA}
+\title{Plot global GSEA results}
+\usage{
+plot_GSEA(
+  data,
+  geneset_col,
+  collection_col,
+  nes_col,
+  logfdr_col,
+  text_size_genesets = 5,
+  text_size_collection = 5
+)
+}
+\arguments{
+\item{data}{Data frame containing the GSEA results.}
+
+\item{geneset_col}{Name of the column containing the genesets.}
+
+\item{collection_col}{Name of the column containing the collections.}
+
+\item{nes_col}{Name of the column containing the NES values.}
+
+\item{logfdr_col}{Name of the column containing \eqn{-\log_{10}(FDR)} values.}
+
+\item{text_size_genesets}{Text size for the geneset labels.}
+
+\item{text_size_collection}{Text size for the collection labels.}
+}
+\value{
+GSEA barplots arranged in a grid.
+}
+\description{
+Generates a composite plot displaying NES values, pathway labels,
+and a \emph{logFDR} legend, organized by MSigDB collections.
+}
diff --git a/man/plot_global_GSEA.Rd b/man/plot_global_GSEA.Rd
deleted file mode 100644
index 2504c0a..0000000
--- a/man/plot_global_GSEA.Rd
+++ /dev/null
@@ -1,44 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-\name{plot_global_GSEA}
-\alias{plot_global_GSEA}
-\title{Plot global GSEA results}
-\usage{
-plot_global_GSEA(data, geneset_col, collection_col, nes_col,
-                 logfdr_col, output_path_base, width_output,
-                 height_output, text_size_genesets = 5,
-                 text_size_collection = 5)
-}
-\arguments{
-  \item{data}{Data frame containing the GSEA results.}
-  \item{geneset_col}{Name of the column containing the genesets.}
-  \item{collection_col}{Name of the column containing the MSigDB collections.}
-  \item{nes_col}{Name of the column containing NES values.}
-  \item{logfdr_col}{Name of the column containing \eqn{-\log_{10}(FDR)} values.}
-  \item{output_path_base}{Path and base name for the output files (no extension).}
-  \item{width_output}{Width of the output plot in inches.}
-  \item{height_output}{Height of the output plot in inches.}
-  \item{text_size_genesets}{Text size for the geneset labels.}
-  \item{text_size_collection}{Text size for the collection labels.}
-}
-\description{
-Generates a multi-panel plot summarizing GSEA results, showing pathways,
-normalized enrichment scores (NES), and log-transformed FDR values
-grouped by MSigDB collection.
-}
-\details{
-This function creates a visual summary of GSEA results by combining:
-\itemize{
-  \item \strong{Pathway labels} on the left,
-  \item \strong{NES bars} filled by \emph{log10 FDR} in the center,
-  \item \strong{Collection labels} on the right,
-  \item Vertical titles on both ends ("Pathways" and "MSigDB").
-}
-The final figure is saved as both PDF and JPG.
-}
-\examples{
-\dontrun{
-df <- readr::read_tsv("collections_merged_gsea_data.tsv")
-plot_global_GSEA(df, "Geneset", "COLLECTION", "NES", "Log10FDR",
-                 "output/plotGSEA", 12, 8)
-}
-}
diff --git a/man/plotheatmap_leadingedge_GSEA.Rd b/man/plotheatmap_leadingedge_GSEA.Rd
deleted file mode 100644
index cf741da..0000000
--- a/man/plotheatmap_leadingedge_GSEA.Rd
+++ /dev/null
@@ -1,65 +0,0 @@
-% Generated by roxygen2; do not edit by hand
-\name{plotheatmap_leadingedge_GSEA}
-\alias{plotheatmap_leadingedge_GSEA}
-\title{Plot leading edge heatmaps from GSEA results}
-\usage{
-plotheatmap_leadingedge_GSEA(
-  main_dir_2 = NULL,
-  expression_file,
-  metadata_file,
-  gmt_file,
-  ranked_genes_file,
-  gsea_file,
-  output_dir = "leading_edge_heatmaps",
-  sample_col = "Sample",
-  group_col = "group",
-  save_dataframe = FALSE
-)
-}
-\arguments{
-  \item{main_dir_2}{Optional base directory to prepend to all file paths.}
-  \item{expression_file}{Path to the expression data file (tab-delimited) or relative to \code{main_dir_2}.}
-  \item{metadata_file}{Path to the metadata file (Excel) or relative to \code{main_dir_2}.}
-  \item{gmt_file}{Path to the GMT file defining gene sets or relative to \code{main_dir_2}.}
-  \item{ranked_genes_file}{Path to the ranked genes list file or relative to \code{main_dir_2}.}
-  \item{gsea_file}{Path to the GSEA results file with leading edge genes or relative to \code{main_dir_2}.}
-  \item{output_dir}{Directory to save heatmap outputs and optional TSV; default \code{"leading_edge_heatmaps"}.}
-  \item{sample_col}{Name of the sample ID column in metadata; default \code{"Sample"}.}
-  \item{group_col}{Name of the group column in metadata; default \code{"group"}.}
-  \item{save_dataframe}{Logical; if \code{TRUE}, saves the merged data frame as TSV before plotting.}
-}
-\description{
-Generates and saves per-geneset heatmaps of leading edge genes from GSEA results.  
-Reads input files, extracts top-ranked leading edge genes, and plots expression heatmaps.
-}
-\details{
-This function performs the following steps:
-\enumerate{
-  \item Reads a GMT file to map gene set names to member genes.
-  \item Reads GSEA output and merges in the full gene lists for each gene set.
-  \item Reads a ranked gene list and determines the order for leading edge extraction.
-  \item Calculates the leading-edge size (\code{SIZE * tags}) and extracts the top genes accordingly.
-  \item Optionally saves the intermediate merged data frame to a TSV file.
-  \item Reads expression and metadata tables, aligns sample names, and prepares annotation.
-  \item Iterates over each gene set, selecting expression rows for the leading edge genes, and writes a heatmap (PDF and JPG) to \code{output_dir}.
-}
-}
-\value{
-No return value; files are written to disk. A message indicates the final output directory.
-}
-\examples{
-\dontrun{
-plotheatmap_leadingedge_GSEA(
-  main_dir_2         = "C:/Projects/project1",
-  expression_file    = "Results/expression_data.txt",
-  metadata_file      = "sample_data.xlsx",
-  gmt_file           = "GSEA/genesets.gmt",
-  ranked_genes_file  = "Ranking/ranked_gene_list.tsv",
-  gsea_file          = "GSEA/gsea_results.tsv",
-  output_dir         = "LeadingEdgePlots",
-  sample_col         = "id",
-  group_col          = "group",
-  save_dataframe     = TRUE
-)
-}
-}