diff --git a/DESCRIPTION b/DESCRIPTION
index 10510ef..302ac39 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -16,7 +16,7 @@ Authors@R: c(
 Description: This package contains functions that help in manipulating tables and generating plots for multi-omics analysis including genomics, transcriptomics, proteomics, methylomics and immunoinformatics.
 License: CC BY-NC-SA 4.0
 Encoding: UTF-8
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
 Imports:
     dplyr,
     ggplot2,
@@ -29,10 +29,13 @@ Imports:
     scales,
     grid,
     utils,
-    patchwork
+    patchwork,
+    cowplot,
+    igraph,
+    visNetwork,
+    cluster
 Suggests: 
     biomaRt,
-    cowplot,
     dbscan,
     ggnewscale,
     ggrepel,
diff --git a/NAMESPACE b/NAMESPACE
index c7c52e6..ed9408b 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,24 +1,46 @@
 # Generated by roxygen2: do not edit by hand
 
 export(add_annotations)
-export(barplot_GSEA)
+export(build_net)
 export(detect_filter)
 export(get_annotations)
 export(get_stars)
-export(heatmap_GSEA)
-export(merge_GSEA)
+export(heatmap_PA)
+export(merge_PA)
 export(nice_KM)
 export(nice_PCA)
 export(nice_UMAP)
 export(nice_VSB)
 export(nice_Volcano)
 export(nice_tSNE)
-export(plot_GSEA)
+export(plot_PA)
 export(power_analysis)
 export(save_results)
 export(split_cases)
 export(tpm)
+export(view_net)
 import(ggplot2)
+importFrom(cluster,silhouette)
+importFrom(cowplot,get_legend)
+importFrom(dplyr,distinct)
+importFrom(dplyr,filter)
+importFrom(dplyr,left_join)
+importFrom(dplyr,pull)
+importFrom(dplyr,rename)
+importFrom(igraph,E)
+importFrom(igraph,V)
+importFrom(igraph,as_data_frame)
+importFrom(igraph,graph_from_adjacency_matrix)
 importFrom(magrittr,"%>%")
 importFrom(patchwork,plot_layout)
 importFrom(rlang,.data)
+importFrom(stats,cutree)
+importFrom(stats,dist)
+importFrom(stats,hclust)
+importFrom(tibble,tibble)
+importFrom(utils,modifyList)
+importFrom(utils,read.delim)
+importFrom(visNetwork,visLayout)
+importFrom(visNetwork,visNetwork)
+importFrom(visNetwork,visOptions)
+importFrom(visNetwork,visSave)
diff --git a/R/barplot_GSEA.R b/R/barplot_GSEA.R
deleted file mode 100644
index 8339beb..0000000
--- a/R/barplot_GSEA.R
+++ /dev/null
@@ -1,57 +0,0 @@
-#########################
-# Function barplot_GSEA #
-#########################
-
-#' Create and save a customized barplot for GSEA results
-#'
-#' This function generates a customized barplot with:
-#' * Grouped bars.
-#' * Adjusted aesthetics.
-#' * Personalized axis labels.
-#' * Optionally save the result in SVG format.
-#'
-#' @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 axis_y Name of the column to use for the y-axis aesthetic, as a string. Default: "NES".
-#' @import ggplot2
-#' @importFrom rlang .data
-#' @export
-
-barplot_GSEA <- function(data, output_path, custom_labels, axis_y = "NES")
-
-{
-  # Generate the barplot
-  barplot <- ggplot(data, aes(x = .data$datatype, y = .data[[axis_y]], fill = .data[["-Log10FDR"]])) +
-    geom_bar(stat = "identity", color = "black", size = 0.5, width = 0.6) +
-    scale_fill_gradient(
-      low = "white", high = "red", na.value = "white",
-      limits = c(0, 5.5),                # Fixed legend limits
-      oob = scales::squish,              # Squish out-of-bounds values
-      guide = guide_colorbar(barwidth = 3, barheight = 18)
-    ) +
-    labs(x = "Comparisons", y = axis_y) +
-    theme_bw() +
-    theme(
-      axis.line.x = element_blank(),
-      axis.line = element_line(color = "black", size = 0.5),
-      axis.title.x = element_text(size = 45, face = "bold", margin = margin(t = 25)),
-      axis.title.y = element_text(size = 45, face = "bold"),
-      axis.text.x = element_text(angle = 0, hjust = 0.5, vjust = 0.5, size = 30),
-      axis.text.y.left = element_text(size = 50),
-      legend.title = element_text(size = 50),
-      legend.text = element_text(size = 50),
-      panel.spacing = grid::unit(0.6, "lines"),
-      panel.border = element_blank(),
-      strip.background = element_rect(fill = "white", color = "white"),
-      strip.text.y.left = element_text(size = 50, angle = 0, hjust = 0.5),
-      strip.placement = "outside"
-    ) +
-    geom_hline(yintercept = 0, color = "black", size = 2) +
-    expand_limits(y = 0) +
-    ylim(-3.4, 3.2) +
-    facet_wrap(~ .data$New_name, ncol = 2, strip.position = "left", scales = "free_y") +
-    scale_x_discrete(labels = custom_labels)
-
-  return(barplot)
-}
diff --git a/R/build_net.R b/R/build_net.R
new file mode 100644
index 0000000..7c6bea5
--- /dev/null
+++ b/R/build_net.R
@@ -0,0 +1,238 @@
+###############################
+# Build enrichment clustering #
+###############################
+
+#' Calculate gene set clusters from GMT files and enrichment results
+#'
+#' This function parses one or more GMT files, filters an enrichment results
+#' data frame by an FDR column, computes a Jaccard similarity matrix between
+#' selected gene sets, performs hierarchical clustering, and determines the
+#' optimal number of clusters using the silhouette index.
+#'
+#' @param results_df A \code{data.frame} or \code{tibble} containing enrichment
+#'   results. Must contain at least the columns specified by \code{fdr_col} and
+#'   \code{pathway_col}.
+#' @param gmt_path A character scalar. Path to a directory containing one or
+#'   more \code{.gmt} files.
+#' @param fdr_threshold A numeric scalar specifying the FDR cutoff used to
+#'   filter \code{results_df}. Only pathways with FDR values less than this
+#'   threshold will be considered. Default is \code{0.25}.
+#' @param fdr_col A character scalar specifying the column name in
+#'   \code{results_df} that contains FDR values.
+#' @param pathway_col A character scalar specifying the column name in
+#'   \code{results_df} that contains pathway identifiers (names matching the
+#'   GMT gene set names).
+#' @param max_k_ratio A numeric scalar used to determine the maximum number of
+#'   clusters to evaluate with the silhouette index. The maximum k is computed
+#'   as \code{max(2, floor(n / max_k_ratio))}, where \code{n} is the number of
+#'   selected gene sets. Default is \code{2.5}.
+#'
+#' @details
+#' GMT files are expected to be tab-delimited, with the first column being the
+#' gene set name, the second column a description (which is ignored), and the
+#' remaining columns listing gene identifiers.
+#'
+#' Jaccard similarity between gene sets \eqn{A} and \eqn{B} is defined as:
+#' \deqn{J(A,B) = |A \cap B| / |A \cup B|}.
+#'
+#' Hierarchical clustering is performed using Euclidean distances derived from
+#' \code{1 - Jaccard_similarity} and the \code{"ward.D2"} linkage method.
+#' The optimal number of clusters is chosen as the \code{k} that maximizes the
+#' mean silhouette width for \code{k} in \code{2:max_k}.
+#'
+#' This function does not perform any file I/O beyond reading GMT files; it is
+#' intended to be used inside packages and downstream plotting functions.
+#'
+#' @return A named list with the following elements:
+#' \itemize{
+#'   \item \code{clusters}: A \code{tibble} with columns \code{pathway} and
+#'     \code{cluster} (integer cluster memberships).
+#'   \item \code{jaccard_matrix}: A symmetric numeric matrix of Jaccard
+#'     similarities between gene sets (rows and columns named by pathways).
+#'   \item \code{hclust_obj}: An \code{\link[stats]{hclust}} object containing
+#'     the hierarchical clustering result.
+#'   \item \code{optimal_k}: An integer giving the selected number of clusters.
+#'   \item \code{silhouette_data}: A \code{tibble} with columns \code{k} and
+#'     \code{silhouette}, suitable for plotting the silhouette index as a
+#'     function of \code{k}.
+#' }
+#'
+#' @examples
+#' \dontrun{
+#' res <- read.csv("pathway_results.csv")
+#' clustering <- build_net(
+#'   results_df   = res,
+#'   gmt_path     = "gmt_dir/",
+#'   fdr_threshold = 0.25,
+#'   fdr_col       = "FDR_gsea",
+#'   pathway_col   = "Pathway",
+#'   max_k_ratio   = 2.5
+#' )
+#' }
+#'
+#' @importFrom stats hclust dist cutree
+#' @importFrom utils read.delim
+#' @importFrom cluster silhouette
+#' @importFrom dplyr filter pull distinct
+#' @importFrom rlang .data
+#' @importFrom tibble tibble
+#' @export
+
+build_net <- function(results_df,
+                                       gmt_path,
+                                       fdr_threshold = 0.25,
+                                       fdr_col,
+                                       pathway_col,
+                                       max_k_ratio = 2.5) {
+  # Basic input checks
+  if (!dir.exists(gmt_path)) {
+    stop("The provided 'gmt_path' does not exist: ", gmt_path)
+  }
+  if (!is.data.frame(results_df)) {
+    stop("'results_df' must be a data.frame or tibble.")
+  }
+  if (!is.character(fdr_col) || length(fdr_col) != 1L) {
+    stop("'fdr_col' must be a single character string.")
+  }
+  if (!is.character(pathway_col) || length(pathway_col) != 1L) {
+    stop("'pathway_col' must be a single character string.")
+  }
+  if (!fdr_col %in% colnames(results_df)) {
+    stop("Column '", fdr_col, "' not found in 'results_df'.")
+  }
+  if (!pathway_col %in% colnames(results_df)) {
+    stop("Column '", pathway_col, "' not found in 'results_df'.")
+  }
+  if (!is.numeric(fdr_threshold) || length(fdr_threshold) != 1L || is.na(fdr_threshold)) {
+    stop("'fdr_threshold' must be a single numeric value.")
+  }
+  if (!is.numeric(max_k_ratio) || length(max_k_ratio) != 1L || is.na(max_k_ratio) || max_k_ratio <= 0) {
+    stop("'max_k_ratio' must be a single positive numeric value.")
+  }
+  
+  # Find GMT files
+  gmt_files <- list.files(gmt_path, pattern = "\\.gmt$", full.names = TRUE)
+  if (length(gmt_files) == 0L) {
+    stop("No .gmt files found in directory: ", gmt_path)
+  }
+  
+  # Read GMT files into a named list of gene vectors
+  geneset_list <- list()
+  for (f in gmt_files) {
+    gmt <- utils::read.delim(f,
+                             header = FALSE,
+                             stringsAsFactors = FALSE,
+                             sep = "\t",
+                             quote = "",
+                             comment.char = "")
+    if (ncol(gmt) < 3L) {
+      next
+    }
+    for (i in seq_len(nrow(gmt))) {
+      name <- as.character(gmt[i, 1])
+      genes <- as.character(gmt[i, 3:ncol(gmt)])
+      genes <- genes[genes != "" & !is.na(genes)]
+      geneset_list[[name]] <- unique(genes)
+    }
+  }
+  
+  if (length(geneset_list) == 0L) {
+    stop("No gene sets could be parsed from the GMT files in '", gmt_path, "'.")
+  }
+  
+  # Filter enrichment results by FDR and select pathways
+  results_tbl <- if (inherits(results_df, "tbl_df")) results_df else tibble::as_tibble(results_df)
+  
+  results_filtered <- dplyr::filter(
+    results_tbl,
+    .data[[fdr_col]] < fdr_threshold
+  )
+  
+  if (nrow(results_filtered) == 0L) {
+    stop("No pathways passed the FDR threshold (", fdr_threshold, ").")
+  }
+  
+  selected_sets <- dplyr::pull(results_filtered, .data[[pathway_col]])
+  selected_sets <- unique(as.character(selected_sets))
+  
+  # Intersect with gene sets available in GMTs
+  selected_sets <- intersect(selected_sets, names(geneset_list))
+  if (length(selected_sets) == 0L) {
+    stop(
+      "No overlap between pathways in 'results_df' and gene set names in GMT files. ",
+      "Check that '", pathway_col, "' matches the GMT gene set names."
+    )
+  }
+  
+  geneset_list <- geneset_list[selected_sets]
+  
+  # Build Jaccard similarity matrix
+  n <- length(geneset_list)
+  jaccard_sim <- matrix(
+    0,
+    nrow = n,
+    ncol  = n,
+    dimnames = list(names(geneset_list), names(geneset_list))
+  )
+  
+  for (i in seq_along(geneset_list)) {
+    for (j in seq_along(geneset_list)) {
+      a <- geneset_list[[i]]
+      b <- geneset_list[[j]]
+      inter <- length(intersect(a, b))
+      union <- length(unique(c(a, b)))
+      if (union == 0) {
+        jaccard_sim[i, j] <- 0
+      } else {
+        jaccard_sim[i, j] <- inter / union
+      }
+    }
+  }
+  
+  # Distance matrix for hierarchical clustering
+  dist_mat <- stats::as.dist(1 - jaccard_sim)
+  
+  # Hierarchical clustering using Ward.D2
+  hc <- stats::hclust(dist_mat, method = "ward.D2")
+  
+  # Determine maximum k for silhouette evaluation
+  max_k <- max(2L, floor(n / max_k_ratio))
+  max_k <- min(max_k, n - 1L) # cannot have k >= n for silhouette
+  
+  if (max_k < 2L) {
+    stop("Not enough gene sets to form at least two clusters.")
+  }
+  
+  ks <- 2:max_k
+  sil_scores <- numeric(length(ks))
+  
+  for (idx in seq_along(ks)) {
+    k <- ks[idx]
+    cl <- stats::cutree(hc, k = k)
+    sil <- cluster::silhouette(cl, dist_mat)
+    sil_scores[idx] <- mean(sil[, "sil_width"])
+  }
+  
+  optimal_k <- ks[which.max(sil_scores)]
+  
+  silhouette_data <- tibble::tibble(
+    k = ks,
+    silhouette = sil_scores
+  )
+  
+  # Cluster membership at optimal k
+  cluster_assignments <- stats::cutree(hc, k = optimal_k)
+  clusters_tbl <- tibble::tibble(
+    pathway = names(cluster_assignments),
+    cluster = as.integer(cluster_assignments)
+  )
+  
+  # Return structured output
+  list(
+    clusters        = clusters_tbl,
+    jaccard_matrix  = jaccard_sim,
+    hclust_obj      = hc,
+    optimal_k       = optimal_k,
+    silhouette_data = silhouette_data
+  )
+}
\ No newline at end of file
diff --git a/R/heatmap_GSEA.R b/R/heatmap_PA.R
similarity index 94%
rename from R/heatmap_GSEA.R
rename to R/heatmap_PA.R
index 40ca338..56f6e90 100644
--- a/R/heatmap_GSEA.R
+++ b/R/heatmap_PA.R
@@ -1,10 +1,10 @@
 #########################
-# Function heatmap_GSEA #
+# Function heatmap_PA #
 #########################
 
-#' Plot leading edge heatmaps from GSEA results.
+#' Plot leading edge heatmaps from GSEA/CAMERA/PADOG results.
 #'
-#' Generates heatmaps of leading edge genes for each gene set from GSEA output.
+#' Generates heatmaps based on normalized data of genes for each gene set from GSEA/CAMERA/PADOG 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.
@@ -19,10 +19,15 @@
 #' @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,
+heatmap_PA <- 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)
 {
+  # Avoid check NOTES for global variables across multiple functions
+  utils::globalVariables(c(
+    "NAME", "GENES", "SIZE", "tags", "L.EDGE_size"
+  ))
+  
   # 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)
diff --git a/R/merge_GSEA.R b/R/merge_PA.R
similarity index 85%
rename from R/merge_GSEA.R
rename to R/merge_PA.R
index 990d6b7..5f40792 100644
--- a/R/merge_GSEA.R
+++ b/R/merge_PA.R
@@ -1,19 +1,24 @@
 #######################
-# Function merge_GSEA #
+# Function merge_PA #
 #######################
 
 #' Merge GSEA results data frames.
 #'
-#' After running GSEA_all.sh from GSEA.sh, merge_GSEA function joins .tsv files to a single file
+#' After running GSEA_all.sh from GSEA.sh, merge_PA 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") {
-
+merge_PA <- function(input_directory, output_file = "collections_merged_gsea_data.tsv") {
+  
+  # Avoid check NOTES for global variables across multiple functions
+  utils::globalVariables(c(
+    "...12", "numeric_cols", "LEADING EDGE", "tags", "signal",
+    "FDR q-val", "Log10FDR", "FWER p-val", "Comparison"
+  ))
+  
+  # Ensure required packages are installed
   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)
diff --git a/R/plot_GSEA.R b/R/plot_GSEA.R
deleted file mode 100644
index 3be4b21..0000000
--- a/R/plot_GSEA.R
+++ /dev/null
@@ -1,117 +0,0 @@
-######################
-# 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/plot_PA.R b/R/plot_PA.R
new file mode 100644
index 0000000..1205d48
--- /dev/null
+++ b/R/plot_PA.R
@@ -0,0 +1,171 @@
+utils::globalVariables(c(
+  "NAME","GENES","SIZE","tags","L.EDGE_size",
+  "...12","numeric_cols","LEADING EDGE","signal",
+  "FDR q-val","Log10FDR","FWER p-val","Comparison"
+))
+
+#' Unified Pathway analysis results plotting function with theme configuration
+#'
+#' Creates either a global GSEA plot or a faceted barplot depending on the number of unique
+#' comparisons in the `Comparison` column. Allows customizing all previously hard-coded theme
+#' parameters via a single `theme_params` list.
+#'
+#' @param data A data frame containing GSEA results.
+#' @param Comparison Name of the column defining different comparisons. Default: "Comparison".
+#' @param custom_labels Named vector of labels for the x-axis discrete scale (barplot mode only). Default: NULL.
+#' @param axis_y Name of the column to use for the y-axis aesthetic. Default: "NES".
+#' @param fdr_col Name of the column containing FDR values. Default: "FDR".
+#' @param logFDR Logical; if TRUE, compute -log10(FDR) from `fdr_col`, otherwise use `fdr_col` directly. Default: TRUE.
+#' @param geneset_col Name of the column containing the geneset labels (single comparison mode).
+#' @param collection_col Name of the column containing the MSigDB collections (single comparison mode).
+#' @param nes_col Name of the column containing NES values (single comparison mode).
+#' @param logfdr_col Name of the column containing -log10(FDR) or similar (single comparison mode).
+#' @param order One of "desc" or "asc"; order of `axis_y` values. Default: c("desc","asc").
+#' @param ncol_wrap Number of columns for `facet_wrap` in barplot mode. Default: 2.
+#' @param free_y Logical; if TRUE, allow free y scales in facets. Default: TRUE.
+#' @param fill_limits Numeric vector of length 2 to set fill gradient limits (barplot mode). Default: NULL.
+#' @param fill_palette Character vector of two colors for fill gradient. Default: c("white","red").
+#' @param theme_params Named list to override default theme parameters (see details).
+#' @details theme_params may include:
+#'   \describe{
+#'     \item{side_label_size}{Size for side panel labels (default 35)}
+#'     \item{geneset_text_size}{Text size for geneset labels (default 5)}
+#'     \item{collection_text_size}{Text size for collection labels (default 5)}
+#'     \item{panel_widths}{Patchwork widths vector (default c(4,25,15,3,10,3))}
+#'     \item{bar_col}{Bar/col border color (default "black")}  
+#'     \item{bar_size}{Border size for bars (default 0.5)}
+#'     \item{bar_width}{Width for bars (default 0.6)}
+#'     \item{col_size}{Border size for geom_col (default 1)}
+#'     \item{hline_size}{Size for horizontal line at y=0 (default 2)}
+#'     \item{axis_title_size}{Font size for axis titles (default 45)}
+#'     \item{axis_text_size_x}{Font size for x-axis text (default 30)}
+#'     \item{axis_text_size_y}{Font size for y-axis text (default 50)}
+#'     \item{tick_size}{Size for axis ticks (default 1.5)}
+#'     \item{tick_length}{Length for axis ticks in cm (default 0.3)}
+#'     \item{strip_text_size}{Font size for strip text (default 50)}
+#'     \item{panel_spacing_single}{Facet spacing single mode (default 4)}
+#'     \item{panel_spacing_multi}{Facet spacing multi mode (default 0.6)}
+#'   }
+#' @return A ggplot or patchwork object for the GSEA plot.
+#' @import ggplot2
+#' @importFrom rlang .data
+#' @importFrom patchwork plot_layout
+#' @importFrom cowplot get_legend
+#' @importFrom utils modifyList
+#' @export
+plot_PA <- function(
+    data,
+    Comparison = "Comparison",
+    custom_labels = NULL,
+    axis_y = "NES",
+    fdr_col = "FDR",
+    logFDR = TRUE,
+    geneset_col,
+    collection_col,
+    nes_col,
+    logfdr_col,
+    order = c("desc", "asc"),
+    ncol_wrap = 2,
+    free_y = TRUE,
+    fill_limits = NULL,
+    fill_palette = c("white", "red"),
+    theme_params = list()
+) {
+  defaults <- list(
+    side_label_size      = 35,
+    geneset_text_size    = 5,
+    collection_text_size = 5,
+    panel_widths         = c(4,25,15,3,10,3),
+    bar_col              = "black",
+    bar_size             = 0.5,
+    bar_width            = 0.6,
+    col_size             = 1,
+    hline_size           = 2,
+    axis_title_size      = 45,
+    axis_text_size_x     = 30,
+    axis_text_size_y     = 50,
+    tick_size            = 1.5,
+    tick_length          = 0.3,
+    strip_text_size      = 50,
+    panel_spacing_single = 4,
+    panel_spacing_multi  = 0.6
+  )
+  params <- utils::modifyList(defaults, theme_params)
+  if (logFDR) data$logFDR <- -log10(data[[fdr_col]]) else data$logFDR <- data[[fdr_col]]
+  order <- match.arg(order)
+  data <- data[order(data[[axis_y]], decreasing = (order == "desc")), ]
+  if (length(unique(data[[Comparison]])) == 1) {
+    if (!requireNamespace("patchwork", quietly = TRUE)) stop("patchwork required", call. = FALSE)
+    if (!requireNamespace("cowplot", quietly = TRUE)) stop("cowplot required", call. = FALSE)
+    df <- data[, c(geneset_col, collection_col, nes_col, logfdr_col)]
+    colnames(df) <- c("Geneset", "Collection", "NES", "logFDR")
+    df$Geneset    <- factor(df$Geneset, levels = rev(unique(df$Geneset)))
+    df$Collection <- factor(df$Collection, levels = unique(df$Collection))
+    plot_text_pathways <- ggplot() +
+      annotate("text", label = "Pathways", fontface = "bold.italic", angle = 90,
+               size = params$side_label_size, x = 0, y = 0.5) + theme_void()
+    plot_left <- ggplot(df, aes(y = .data$Geneset, x = 0, label = .data$Geneset)) +
+      geom_text(hjust = 1, size = params$geneset_text_size) + theme_void() +
+      theme(axis.text.y = element_blank(), plot.margin = margin(0, 0, 0, -50))
+    plot_center <- ggplot(df, aes(x = .data$NES, y = .data$Geneset, fill = .data$logFDR)) +
+      geom_col(color = params$bar_col, size = params$col_size) +
+      scale_fill_gradient(low = fill_palette[1], high = fill_palette[2],
+                          limits = fill_limits, breaks = scales::pretty_breaks()) +
+      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(size = params$tick_size),
+            axis.ticks.length = grid::unit(params$tick_length, "cm"),
+            strip.text.y = element_text(size = 1), legend.position = "none",
+            axis.title.x = element_text(size = params$axis_title_size),
+            axis.text.x = element_text(size = params$axis_text_size_x),
+            panel.spacing = grid::unit(params$panel_spacing_single, "lines"))
+    plot_text_msigdb <- ggplot() +
+      annotate("text", label = "MSigDB", fontface = "bold.italic", angle = 90,
+               size = params$side_label_size, x = 0, y = 0.5) + theme_void()
+    plot_right <- ggplot(df, aes(y = .data$Geneset, x = 1.5, label = .data$Collection)) +
+      geom_text(aes(label = ifelse(duplicated(.data$Collection), "", .data$Collection)),
+                hjust = 0.5, size = params$collection_text_size, fontface = "bold") +
+      facet_grid(Collection ~ ., scales = "free_y", space = "free", switch = "y") + theme_void() +
+      theme(strip.text.y = element_text(size = params$collection_text_size),
+            panel.spacing = grid::unit(1, "lines"))
+    plot_legend <- ggplot(df, aes(x = .data$NES, y = .data$Geneset, fill = .data$logFDR)) +
+      geom_tile() + scale_fill_gradient(low = fill_palette[1], high = fill_palette[2],
+                                        name = expression(-log[10] ~ FDR), limits = fill_limits,
+                                        guide = guide_colorbar(ticks.colour = "black", ticks.linewidth = 1.5,
+                                                               draw.ulim = TRUE, draw.llim = TRUE)) + theme_bw() +
+      theme(legend.title = element_text(size = 44, face = "bold"),
+            legend.text = element_text(size = 30),
+            legend.key.size = grid::unit(1.5, "cm"),
+            legend.key.height = grid::unit(2, "cm"),
+            legend.spacing = grid::unit(3.5, "cm"),
+            legend.box.margin = margin(10, 20, 10, 10))
+    plot_right_legend <- cowplot::get_legend(plot_legend)
+    final_plot <- plot_text_pathways + plot_left + plot_center + plot_right +
+      plot_text_msigdb + plot_right_legend +
+      patchwork::plot_layout(ncol = 6, widths = params$panel_widths)
+  } else {
+    final_plot <- ggplot(data, aes(x = .data[[Comparison]], y = .data[[axis_y]], fill = .data$logFDR)) +
+      geom_bar(stat = "identity", color = params$bar_col, size = params$bar_size,
+               width = params$bar_width) +
+      scale_fill_gradient(low = fill_palette[1], high = fill_palette[2],
+                          limits = fill_limits, oob = scales::squish,
+                          guide = guide_colorbar(barwidth = 3, barheight = 18)) +
+      labs(x = "Comparisons", y = axis_y) + theme_bw() +
+      theme(axis.line.x = element_blank(), axis.line = element_line(size = 0.5),
+            axis.title.x = element_text(size = params$axis_title_size),
+            axis.title.y = element_text(size = params$axis_title_size),
+            axis.text.x = element_text(size = params$axis_text_size_x),
+            axis.text.y = element_text(size = params$axis_text_size_y),
+            axis.ticks = element_line(size = params$tick_size),
+            axis.ticks.length = grid::unit(params$tick_length, "cm"),
+            strip.text = element_text(size = params$strip_text_size),
+            panel.spacing = grid::unit(params$panel_spacing_multi, "lines")) +
+      geom_hline(yintercept = 0, size = params$hline_size) + expand_limits(y = 0) +
+      facet_wrap(~ .data$New_name, ncol = ncol_wrap,
+                 scales = if (free_y) "free_y" else "fixed")
+    if (!is.null(custom_labels)) final_plot <- final_plot +
+        scale_x_discrete(labels = custom_labels)
+  }
+  return(final_plot)
+}
diff --git a/R/view_net.R b/R/view_net.R
new file mode 100644
index 0000000..6fdc79c
--- /dev/null
+++ b/R/view_net.R
@@ -0,0 +1,164 @@
+###############################
+# Plot enrichment clustering #
+###############################
+
+#' Plot a gene set network based on clustering output
+#'
+#' This function takes the output of [build_net()],
+#' constructs a gene set similarity network using Jaccard similarity as edge
+#' weights, and generates both a static igraph object and an interactive
+#' \code{visNetwork} visualization.
+#'
+#' @param clustering_output A named list as returned by
+#'    [build_net()], containing at least
+#'   \code{clusters} (a tibble with columns \code{pathway} and \code{cluster})
+#'   and \code{jaccard_matrix} (a symmetric numeric matrix).
+#' @param edge_threshold A numeric scalar specifying the minimum Jaccard
+#'   similarity required for an edge to be drawn between two gene sets.
+#'   All similarities below this threshold are set to zero before network
+#'   construction. Default is \code{0.25}.
+#' @param save_html_path Optional character scalar. If non-\code{NULL}, the
+#'   interactive \code{visNetwork} object will be saved as an HTML file at the
+#'   specified path using \code{visNetwork::visSave}. If \code{NULL}, no HTML
+#'   file is written. Default is \code{NULL}.
+#'
+#' @details
+#' The static graph is built with \pkg{igraph} from a thresholded Jaccard
+#' similarity matrix. Nodes represent gene sets (pathways), and edges represent
+#' Jaccard similarity greater than or equal to \code{edge_threshold}.
+#'
+#' Cluster memberships are taken from \code{clustering_output$clusters} and
+#' mapped to the node attribute \code{group} in the interactive network, which
+#' can be used by \pkg{visNetwork} for coloring.
+#'
+#' This function does not perform any plotting side effects by default; it
+#' returns objects that can be plotted or further customized by the caller.
+#'
+#' @return A named list with the following elements:
+#' \itemize{
+#'   \item \code{static_graph}: An \code{\link[igraph]{igraph}} object built
+#'     from the thresholded Jaccard similarity matrix.
+#'   \item \code{interactive_plot}: A \code{\link[visNetwork]{visNetworkProxy}}
+#'     or \code{visNetwork} object representing the interactive network
+#'     visualization.
+#' }
+#'
+#' @examples
+#' \dontrun{
+#' clustering <- build_net(
+#'   results_df   = res,
+#'   gmt_path     = "gmt_dir/",
+#'   fdr_threshold = 0.25,
+#'   fdr_col       = "FDR_gsea",
+#'   pathway_col   = "Pathway"
+#' )
+#'
+#' plots <- view_net(
+#'   clustering_output = clustering,
+#'   edge_threshold    = 0.25,
+#'   save_html_path    = "network.html"
+#' )
+#'
+#' # Static plot
+#' plot(plots$static_graph,
+#'      vertex.label.cex = 0.7,
+#'      edge.width       = igraph::E(plots$static_graph)$weight * 5)
+#'
+#' # Interactive plot (in RStudio viewer or browser)
+#' plots$interactive_plot
+#' }
+#'
+#' @importFrom igraph graph_from_adjacency_matrix V E as_data_frame
+#' @importFrom visNetwork visNetwork visOptions visLayout visSave
+#' @importFrom dplyr left_join rename
+#' @importFrom tibble tibble
+#' @export
+view_net <- function(clustering_output,
+                                 edge_threshold = 0.25,
+                                 save_html_path = NULL) {
+  # Basic input checks
+  if (!is.list(clustering_output)) {
+    stop("'clustering_output' must be a list as returned by 'calculate_geneset_clusters'.")
+  }
+  required_elements <- c("clusters", "jaccard_matrix")
+  missing_elements <- setdiff(required_elements, names(clustering_output))
+  if (length(missing_elements) > 0L) {
+    stop(
+      "'clustering_output' is missing required elements: ",
+      paste(missing_elements, collapse = ", ")
+    )
+  }
+  
+  clusters_tbl <- clustering_output$clusters
+  jaccard_matrix <- clustering_output$jaccard_matrix
+  
+  if (!is.matrix(jaccard_matrix) || !is.numeric(jaccard_matrix)) {
+    stop("'clustering_output$jaccard_matrix' must be a numeric matrix.")
+  }
+  if (is.null(rownames(jaccard_matrix)) || is.null(colnames(jaccard_matrix))) {
+    stop("The Jaccard matrix must have row and column names corresponding to pathways.")
+  }
+  if (!is.data.frame(clusters_tbl)) {
+    stop("'clustering_output$clusters' must be a data.frame or tibble.")
+  }
+  if (!all(c("pathway", "cluster") %in% colnames(clusters_tbl))) {
+    stop("'clusters' must contain 'pathway' and 'cluster' columns.")
+  }
+  if (!is.numeric(edge_threshold) || length(edge_threshold) != 1L || is.na(edge_threshold)) {
+    stop("'edge_threshold' must be a single numeric value.")
+  }
+  
+  # Threshold the Jaccard matrix to define edges
+  adj <- jaccard_matrix
+  adj[adj < edge_threshold] <- 0
+  diag(adj) <- 0
+  
+  # Build igraph object
+  g <- igraph::graph_from_adjacency_matrix(
+    adjmatrix = adj,
+    mode      = "undirected",
+    weighted  = TRUE,
+    diag      = FALSE
+  )
+  
+  # Static graph (igraph object)
+  static_graph <- g
+  
+  # Prepare nodes and edges for visNetwork
+  pathways <- rownames(adj)
+  
+  nodes <- tibble::tibble(
+    id    = pathways,
+    label = pathways
+  )
+  
+  # Merge cluster membership
+  clusters_tbl <- dplyr::distinct(clusters_tbl, .data$pathway, .data$cluster)
+  nodes <- dplyr::left_join(
+    nodes,
+    dplyr::rename(clusters_tbl, id = .data$pathway, group = .data$cluster),
+    by = "id"
+  )
+  
+  # Convert edges to data.frame
+  edges_df <- igraph::as_data_frame(g, what = "edges")
+  # visNetwork uses columns 'from' and 'to'
+  colnames(edges_df)[1:2] <- c("from", "to")
+  
+  interactive_plot <- visNetwork::visNetwork(nodes, edges_df) |>
+    visNetwork::visOptions(highlightNearest = TRUE) |>
+    visNetwork::visLayout(randomSeed = 174)
+  
+  # Save HTML if requested
+  if (!is.null(save_html_path)) {
+    if (!is.character(save_html_path) || length(save_html_path) != 1L) {
+      stop("'save_html_path' must be a single character string if provided.")
+    }
+    visNetwork::visSave(interactive_plot, file = save_html_path)
+  }
+  
+  list(
+    static_graph     = static_graph,
+    interactive_plot = interactive_plot
+  )
+}
\ No newline at end of file
diff --git a/data/raw_counts.rda b/data/raw_counts.rda
index ea791d6..082f445 100644
Binary files a/data/raw_counts.rda and b/data/raw_counts.rda differ
diff --git a/data/sampledata.rda b/data/sampledata.rda
index 6e956c6..d7d03fc 100644
Binary files a/data/sampledata.rda and b/data/sampledata.rda differ
diff --git a/man/barplot_GSEA.Rd b/man/barplot_GSEA.Rd
deleted file mode 100644
index ba47ad0..0000000
--- a/man/barplot_GSEA.Rd
+++ /dev/null
@@ -1,26 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% 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{
-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}.}
-
-\item{output_path}{The file path where the barplot will be saved (SVG format).}
-
-\item{custom_labels}{A named vector of custom expressions for x-axis labels.}
-
-\item{axis_y}{Name of the column to use for the y-axis aesthetic, as a string. Default: "NES".}
-}
-\description{
-This function generates a customized barplot with:
-\itemize{
-\item Grouped bars.
-\item Adjusted aesthetics.
-\item Personalized axis labels.
-\item Optionally save the result in SVG format.
-}
-}
diff --git a/man/build_net.Rd b/man/build_net.Rd
new file mode 100644
index 0000000..096eb7e
--- /dev/null
+++ b/man/build_net.Rd
@@ -0,0 +1,90 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/build_net.R
+\name{build_net}
+\alias{build_net}
+\title{Calculate gene set clusters from GMT files and enrichment results}
+\usage{
+build_net(
+  results_df,
+  gmt_path,
+  fdr_threshold = 0.25,
+  fdr_col,
+  pathway_col,
+  max_k_ratio = 2.5
+)
+}
+\arguments{
+\item{results_df}{A \code{data.frame} or \code{tibble} containing enrichment
+results. Must contain at least the columns specified by \code{fdr_col} and
+\code{pathway_col}.}
+
+\item{gmt_path}{A character scalar. Path to a directory containing one or
+more \code{.gmt} files.}
+
+\item{fdr_threshold}{A numeric scalar specifying the FDR cutoff used to
+filter \code{results_df}. Only pathways with FDR values less than this
+threshold will be considered. Default is \code{0.25}.}
+
+\item{fdr_col}{A character scalar specifying the column name in
+\code{results_df} that contains FDR values.}
+
+\item{pathway_col}{A character scalar specifying the column name in
+\code{results_df} that contains pathway identifiers (names matching the
+GMT gene set names).}
+
+\item{max_k_ratio}{A numeric scalar used to determine the maximum number of
+clusters to evaluate with the silhouette index. The maximum k is computed
+as \code{max(2, floor(n / max_k_ratio))}, where \code{n} is the number of
+selected gene sets. Default is \code{2.5}.}
+}
+\value{
+A named list with the following elements:
+\itemize{
+\item \code{clusters}: A \code{tibble} with columns \code{pathway} and
+\code{cluster} (integer cluster memberships).
+\item \code{jaccard_matrix}: A symmetric numeric matrix of Jaccard
+similarities between gene sets (rows and columns named by pathways).
+\item \code{hclust_obj}: An \code{\link[stats]{hclust}} object containing
+the hierarchical clustering result.
+\item \code{optimal_k}: An integer giving the selected number of clusters.
+\item \code{silhouette_data}: A \code{tibble} with columns \code{k} and
+\code{silhouette}, suitable for plotting the silhouette index as a
+function of \code{k}.
+}
+}
+\description{
+This function parses one or more GMT files, filters an enrichment results
+data frame by an FDR column, computes a Jaccard similarity matrix between
+selected gene sets, performs hierarchical clustering, and determines the
+optimal number of clusters using the silhouette index.
+}
+\details{
+GMT files are expected to be tab-delimited, with the first column being the
+gene set name, the second column a description (which is ignored), and the
+remaining columns listing gene identifiers.
+
+Jaccard similarity between gene sets \eqn{A} and \eqn{B} is defined as:
+\deqn{J(A,B) = |A \cap B| / |A \cup B|}.
+
+Hierarchical clustering is performed using Euclidean distances derived from
+\code{1 - Jaccard_similarity} and the \code{"ward.D2"} linkage method.
+The optimal number of clusters is chosen as the \code{k} that maximizes the
+mean silhouette width for \code{k} in \code{2:max_k}.
+
+This function does not perform any file I/O beyond reading GMT files; it is
+intended to be used inside packages and downstream plotting functions.
+}
+\examples{
+\dontrun{
+res <- read.csv("pathway_results.csv")
+clustering <- build_net(
+  results_df   = res,
+  gmt_path     = "gmt_dir/",
+  fdr_threshold = 0.25,
+  fdr_col       = "FDR_gsea",
+  pathway_col   = "Pathway",
+  max_k_ratio   = 2.5
+)
+}
+
+}
diff --git a/man/heatmap_GSEA.Rd b/man/heatmap_PA.Rd
similarity index 83%
rename from man/heatmap_GSEA.Rd
rename to man/heatmap_PA.Rd
index 788d4b0..23a8f53 100644
--- a/man/heatmap_GSEA.Rd
+++ b/man/heatmap_PA.Rd
@@ -1,10 +1,10 @@
 % 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.}
+% Please edit documentation in R/heatmap_PA.R
+\name{heatmap_PA}
+\alias{heatmap_PA}
+\title{Plot leading edge heatmaps from GSEA/CAMERA/PADOG results.}
 \usage{
-heatmap_GSEA(
+heatmap_PA(
   main_dir = NULL,
   expression_file,
   metadata_file,
@@ -42,5 +42,5 @@ heatmap_GSEA(
 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.
+Generates heatmaps based on normalized data of genes for each gene set from GSEA/CAMERA/PADOG output.
 }
diff --git a/man/merge_GSEA.Rd b/man/merge_PA.Rd
similarity index 57%
rename from man/merge_GSEA.Rd
rename to man/merge_PA.Rd
index d845bc8..c0a5bc9 100644
--- a/man/merge_GSEA.Rd
+++ b/man/merge_PA.Rd
@@ -1,10 +1,10 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/merge_GSEA.R
-\name{merge_GSEA}
-\alias{merge_GSEA}
+% Please edit documentation in R/merge_PA.R
+\name{merge_PA}
+\alias{merge_PA}
 \title{Merge GSEA results data frames.}
 \usage{
-merge_GSEA(input_directory, output_file = "collections_merged_gsea_data.tsv")
+merge_PA(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 = "collections_merged_gsea_data.tsv")
 \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 running GSEA_all.sh from GSEA.sh, merge_GSEA function joins .tsv files to a single file
+After running GSEA_all.sh from GSEA.sh, merge_PA function joins .tsv files to a single file
 }
diff --git a/man/plot_GSEA.Rd b/man/plot_GSEA.Rd
deleted file mode 100644
index 9e39ad3..0000000
--- a/man/plot_GSEA.Rd
+++ /dev/null
@@ -1,38 +0,0 @@
-% 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_PA.Rd b/man/plot_PA.Rd
new file mode 100644
index 0000000..3fb9ced
--- /dev/null
+++ b/man/plot_PA.Rd
@@ -0,0 +1,88 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plot_PA.R
+\name{plot_PA}
+\alias{plot_PA}
+\title{Unified Pathway analysis results plotting function with theme configuration}
+\usage{
+plot_PA(
+  data,
+  Comparison = "Comparison",
+  custom_labels = NULL,
+  axis_y = "NES",
+  fdr_col = "FDR",
+  logFDR = TRUE,
+  geneset_col,
+  collection_col,
+  nes_col,
+  logfdr_col,
+  order = c("desc", "asc"),
+  ncol_wrap = 2,
+  free_y = TRUE,
+  fill_limits = NULL,
+  fill_palette = c("white", "red"),
+  theme_params = list()
+)
+}
+\arguments{
+\item{data}{A data frame containing GSEA results.}
+
+\item{Comparison}{Name of the column defining different comparisons. Default: "Comparison".}
+
+\item{custom_labels}{Named vector of labels for the x-axis discrete scale (barplot mode only). Default: NULL.}
+
+\item{axis_y}{Name of the column to use for the y-axis aesthetic. Default: "NES".}
+
+\item{fdr_col}{Name of the column containing FDR values. Default: "FDR".}
+
+\item{logFDR}{Logical; if TRUE, compute -log10(FDR) from \code{fdr_col}, otherwise use \code{fdr_col} directly. Default: TRUE.}
+
+\item{geneset_col}{Name of the column containing the geneset labels (single comparison mode).}
+
+\item{collection_col}{Name of the column containing the MSigDB collections (single comparison mode).}
+
+\item{nes_col}{Name of the column containing NES values (single comparison mode).}
+
+\item{logfdr_col}{Name of the column containing -log10(FDR) or similar (single comparison mode).}
+
+\item{order}{One of "desc" or "asc"; order of \code{axis_y} values. Default: c("desc","asc").}
+
+\item{ncol_wrap}{Number of columns for \code{facet_wrap} in barplot mode. Default: 2.}
+
+\item{free_y}{Logical; if TRUE, allow free y scales in facets. Default: TRUE.}
+
+\item{fill_limits}{Numeric vector of length 2 to set fill gradient limits (barplot mode). Default: NULL.}
+
+\item{fill_palette}{Character vector of two colors for fill gradient. Default: c("white","red").}
+
+\item{theme_params}{Named list to override default theme parameters (see details).}
+}
+\value{
+A ggplot or patchwork object for the GSEA plot.
+}
+\description{
+Creates either a global GSEA plot or a faceted barplot depending on the number of unique
+comparisons in the \code{Comparison} column. Allows customizing all previously hard-coded theme
+parameters via a single \code{theme_params} list.
+}
+\details{
+theme_params may include:
+\describe{
+\item{side_label_size}{Size for side panel labels (default 35)}
+\item{geneset_text_size}{Text size for geneset labels (default 5)}
+\item{collection_text_size}{Text size for collection labels (default 5)}
+\item{panel_widths}{Patchwork widths vector (default c(4,25,15,3,10,3))}
+\item{bar_col}{Bar/col border color (default "black")}
+\item{bar_size}{Border size for bars (default 0.5)}
+\item{bar_width}{Width for bars (default 0.6)}
+\item{col_size}{Border size for geom_col (default 1)}
+\item{hline_size}{Size for horizontal line at y=0 (default 2)}
+\item{axis_title_size}{Font size for axis titles (default 45)}
+\item{axis_text_size_x}{Font size for x-axis text (default 30)}
+\item{axis_text_size_y}{Font size for y-axis text (default 50)}
+\item{tick_size}{Size for axis ticks (default 1.5)}
+\item{tick_length}{Length for axis ticks in cm (default 0.3)}
+\item{strip_text_size}{Font size for strip text (default 50)}
+\item{panel_spacing_single}{Facet spacing single mode (default 4)}
+\item{panel_spacing_multi}{Facet spacing multi mode (default 0.6)}
+}
+}
diff --git a/man/view_net.Rd b/man/view_net.Rd
new file mode 100644
index 0000000..b405b76
--- /dev/null
+++ b/man/view_net.Rd
@@ -0,0 +1,78 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/view_net.R
+\name{view_net}
+\alias{view_net}
+\title{Plot a gene set network based on clustering output}
+\usage{
+view_net(clustering_output, edge_threshold = 0.25, save_html_path = NULL)
+}
+\arguments{
+\item{clustering_output}{A named list as returned by
+\code{\link[=build_net]{build_net()}}, containing at least
+\code{clusters} (a tibble with columns \code{pathway} and \code{cluster})
+and \code{jaccard_matrix} (a symmetric numeric matrix).}
+
+\item{edge_threshold}{A numeric scalar specifying the minimum Jaccard
+similarity required for an edge to be drawn between two gene sets.
+All similarities below this threshold are set to zero before network
+construction. Default is \code{0.25}.}
+
+\item{save_html_path}{Optional character scalar. If non-\code{NULL}, the
+interactive \code{visNetwork} object will be saved as an HTML file at the
+specified path using \code{visNetwork::visSave}. If \code{NULL}, no HTML
+file is written. Default is \code{NULL}.}
+}
+\value{
+A named list with the following elements:
+\itemize{
+\item \code{static_graph}: An \code{\link[igraph]{igraph}} object built
+from the thresholded Jaccard similarity matrix.
+\item \code{interactive_plot}: A \code{\link[visNetwork]{visNetworkProxy}}
+or \code{visNetwork} object representing the interactive network
+visualization.
+}
+}
+\description{
+This function takes the output of \code{\link[=build_net]{build_net()}},
+constructs a gene set similarity network using Jaccard similarity as edge
+weights, and generates both a static igraph object and an interactive
+\code{visNetwork} visualization.
+}
+\details{
+The static graph is built with \pkg{igraph} from a thresholded Jaccard
+similarity matrix. Nodes represent gene sets (pathways), and edges represent
+Jaccard similarity greater than or equal to \code{edge_threshold}.
+
+Cluster memberships are taken from \code{clustering_output$clusters} and
+mapped to the node attribute \code{group} in the interactive network, which
+can be used by \pkg{visNetwork} for coloring.
+
+This function does not perform any plotting side effects by default; it
+returns objects that can be plotted or further customized by the caller.
+}
+\examples{
+\dontrun{
+clustering <- build_net(
+  results_df   = res,
+  gmt_path     = "gmt_dir/",
+  fdr_threshold = 0.25,
+  fdr_col       = "FDR_gsea",
+  pathway_col   = "Pathway"
+)
+
+plots <- view_net(
+  clustering_output = clustering,
+  edge_threshold    = 0.25,
+  save_html_path    = "network.html"
+)
+
+# Static plot
+plot(plots$static_graph,
+     vertex.label.cex = 0.7,
+     edge.width       = igraph::E(plots$static_graph)$weight * 5)
+
+# Interactive plot (in RStudio viewer or browser)
+plots$interactive_plot
+}
+
+}