diff --git a/.github/workflows/sync-to-org.yml b/.github/workflows/sync-to-org.yml
new file mode 100644
index 0000000..9feb017
--- /dev/null
+++ b/.github/workflows/sync-to-org.yml
@@ -0,0 +1,67 @@
+name: "Sync main & tags to org (SSH, prune)"
+
+on:
+  push:
+    branches:
+      - main       # only when main changes
+    tags:
+      - "*"        # and on any tag push
+  release:
+    types: [published]
+  workflow_dispatch:
+
+jobs:
+  sync:
+    # only from the source repo (so the fork doesn't need secrets)
+    if: github.repository == 'yqkiuo/BreastSubtypeR'
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout source
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          persist-credentials: false
+
+      - name: Ensure secret exists
+        run: |
+          if [ -z "${{ secrets.MIRROR_DEPLOY_KEY }}" ]; then
+            echo "::error:: Secret MIRROR_DEPLOY_KEY is missing in yqkiuo/BreastSubtypeR."
+            exit 1
+          fi
+
+      - name: Start ssh-agent & add deploy key
+        uses: webfactory/ssh-agent@v0.9.0
+        with:
+          ssh-private-key: ${{ secrets.MIRROR_DEPLOY_KEY }}
+
+      - name: Trust github.com host key
+        run: |
+          mkdir -p ~/.ssh
+          ssh-keyscan -t rsa,ecdsa,ed25519 github.com >> ~/.ssh/known_hosts
+
+      - name: Configure git identity
+        run: |
+          git config --global user.name "github-actions[bot]"
+          git config --global user.email "41898282+github-actions[bot]@users.noreply.github.com"
+
+      - name: Add mirror remote (org fork)
+        run: |
+          git remote add mirror git@github.com:JohanHartmanGroupBioteam/BreastSubtypeR.git
+          git remote -v
+
+      - name: Fetch origin & mirror (for safe lease)
+        run: |
+          set -e
+          git fetch --tags --prune origin
+          git fetch --prune origin +refs/heads/*:refs/remotes/origin/*
+          git fetch --tags --prune mirror
+          git fetch --prune mirror +refs/heads/*:refs/remotes/mirror/*
+
+      - name: Push main & tags to mirror (prune deleted tags)
+        run: |
+          set -e
+          # Push main with a safe force (only if mirror hasn't moved unexpectedly)
+          git push --force-with-lease mirror refs/remotes/origin/main:refs/heads/main
+          # Push all tags, pruning tag deletions
+          git push --prune --tags mirror
diff --git a/DESCRIPTION b/DESCRIPTION
index 62371b7..ed0c668 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -10,8 +10,8 @@ Description: BreastSubtypeR provides an assumption-aware, multi-method framework
     (iBreastSubtypeR) is included for interactive analyses and to support users
     without programming experience.
 Encoding: UTF-8
-Version: 1.1.4
-biocViews: RNASeq, Software, GeneExpression, Classification
+Version: 1.1.5
+biocViews: RNASeq, Software, GeneExpression, Classification, Preprocessing, Visualization
 Authors@R: c(
     person(given = "Qiao", family = "Yang", 
 	   role = c("aut", "cre"), 
@@ -59,4 +59,4 @@ License: GPL-3
 VignetteBuilder: knitr
 Roxygen: list(markdown = TRUE, roclets = c("rd", "namespace", "collate"))
 LazyData: FALSE
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3
diff --git a/NAMESPACE b/NAMESPACE
index 1652a26..339fd94 100755
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -15,13 +15,10 @@ export(Vis_boxplot)
 export(Vis_heatmap)
 export(Vis_pie)
 export(iBreastSubtypeR)
-export(runShinyBreastSubtypeR)
 import(Biobase)
 import(ComplexHeatmap)
 import(RColorBrewer)
 import(circlize)
-import(e1071)
-import(ggplot2)
 import(ggrepel)
 import(grid)
 import(impute)
@@ -35,7 +32,30 @@ importFrom(SummarizedExperiment,colData)
 importFrom(SummarizedExperiment,rowData)
 importFrom(data.table,data.table)
 importFrom(data.table,set)
+importFrom(dplyr,across)
+importFrom(dplyr,everything)
+importFrom(dplyr,mutate)
 importFrom(dplyr,select)
+importFrom(e1071,naiveBayes)
+importFrom(ggplot2,aes)
+importFrom(ggplot2,coord_polar)
+importFrom(ggplot2,element_text)
+importFrom(ggplot2,geom_bar)
+importFrom(ggplot2,geom_boxplot)
+importFrom(ggplot2,geom_hline)
+importFrom(ggplot2,geom_line)
+importFrom(ggplot2,geom_point)
+importFrom(ggplot2,geom_text)
+importFrom(ggplot2,geom_vline)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,labs)
+importFrom(ggplot2,scale_color_manual)
+importFrom(ggplot2,scale_fill_manual)
+importFrom(ggplot2,scale_x_continuous)
+importFrom(ggplot2,theme)
+importFrom(ggplot2,theme_classic)
+importFrom(ggplot2,theme_minimal)
+importFrom(ggplot2,theme_void)
 importFrom(grDevices,dev.off)
 importFrom(grDevices,pdf)
 importFrom(graphics,barplot)
@@ -48,6 +68,7 @@ importFrom(stats,cor)
 importFrom(stats,cor.test)
 importFrom(stats,dist)
 importFrom(stats,median)
+importFrom(stats,na.omit)
 importFrom(stats,prcomp)
 importFrom(stats,quantile)
 importFrom(tidyselect,everything)
diff --git a/NEWS.md b/NEWS.md
index 2c22233..a6a97e4 100755
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,9 +1,9 @@
-# BreastSubtypeR 1.1.3
+# BreastSubtypeR 1.1.5
 
 ## Highlights
 - Paper published in *NAR Genomics and Bioinformatics* (2025), **Editor’s Choice** (DOI: 10.1093/nargab/lqaf131).
-- **New:** Support for raw RNA-seq counts (requires gene lengths).
-- Major **iBreastSubtypeR** refresh: cleaner UX, smarter AUTO guidance, consistent exports.
+- Support for raw RNA-seq counts (requires gene lengths).
+- **iBreastSubtypeR** refresh: cleaner UX, smarter AUTO guidance, consistent exports.
 - Refined, data-driven thresholds for ER/HER2 skew detection in AUTO.
 - Broader input-validation across the subtyping pipeline.
 
@@ -41,4 +41,4 @@
 ## Upgrade Notes
 - Raw RNA-seq counts are supported **from v1.1.3 onward** (requires gene lengths).
 - If you previously parsed `BS` / `BS.Subtype`, switch to **`Call_5class` / `Call_4class`**.
-- Package API unchanged (the `Subtype` argument remains).
+- Package API unchanged.
diff --git a/R/BreastSubtypeR_methods.R b/R/BreastSubtypeR_methods.R
index e2208ff..bf77be0 100755
--- a/R/BreastSubtypeR_methods.R
+++ b/R/BreastSubtypeR_methods.R
@@ -1,6 +1,6 @@
 #' @import stringr
-#' @import e1071
 #' @import Biobase
+#' @importFrom e1071 naiveBayes
 #' @importFrom SummarizedExperiment SummarizedExperiment
 #' @importFrom SummarizedExperiment colData
 #' @importFrom SummarizedExperiment rowData
@@ -12,12 +12,13 @@
 #' @importFrom utils data installed.packages read.delim write.table
 #' @importFrom graphics barplot mtext par
 #' @importFrom grDevices dev.off pdf
-#' @importFrom stats prcomp cor cor.test dist quantile median
+#' @importFrom stats prcomp cor cor.test dist quantile median na.omit
 #' @importFrom methods is
 #'
 NULL
 
-#' BreastSubtypeR: A Unified R/Bioconductor Package for Intrinsic Molecular Subtyping in Breast Cancer Research
+#' BreastSubtypeR: A Unified R/Bioconductor Package 
+#' for Intrinsic Molecular Subtyping in Breast Cancer Research
 #'
 #'
 #' @name BreastSubtypeR
@@ -77,7 +78,8 @@ NULL
 #'
 #' @param se_obj A `SummarizedExperiment` object containing:
 #'   - **Assay data**:
-#'     - If `RawCounts = FALSE`: `assay()` must contain log2-normalized expression (e.g., pre-normalized microarray/nCounter, or log2(FPKM+1) RNAseq).
+#'     - If `RawCounts = FALSE`: `assay()` must contain log2-normalized expression 
+#'     (e.g., pre-normalized microarray/nCounter, or log2(FPKM+1) RNAseq).
 #'     - If `RawCounts = TRUE`: `assay()` contains raw RNA-seq counts (see `RawCounts`).
 #'   - **Row metadata** (required):
 #'     - `"probe"`: feature identifiers (e.g., gene symbols or probe IDs)
@@ -87,7 +89,8 @@ NULL
 #'   - **Column metadata** (optional): sample-level metadata in `colData()`.
 #'
 #' @param RawCounts Logical. If `TRUE`, indicates that `assay()` holds raw RNA-seq counts.
-#'   In this case, `rowData()` must also provide gene lengths (column `"Length"`, in base pairs), used for:
+#'   In this case, `rowData()` must also provide gene lengths 
+#'   (column `"Length"`, in base pairs), used for:
 #'   - NC-based methods: log2-CPM (upper-quartile normalization).
 #'   - SSP-based methods: linear FPKM (not log-transformed).
 #'
@@ -104,8 +107,10 @@ NULL
 #'
 #' @return A named list with:
 #' \describe{
-#'   \item{se_NC}{`SummarizedExperiment` holding log2-transformed data prepared for NC-based methods (assay name: `counts`).}
-#'   \item{se_SSP}{`SummarizedExperiment` holding linear-scale data prepared for SSP-based methods (assay name: `counts`).}
+#'   \item{se_NC}{`SummarizedExperiment` holding log2-transformed data prepared for NC-based methods 
+#'   (assay name: `counts`).}
+#'   \item{se_SSP}{`SummarizedExperiment` holding linear-scale data prepared for SSP-based methods 
+#'   (assay name: `counts`).}
 #' }
 #'
 #' @references
@@ -123,38 +128,26 @@ NULL
 #' BreastSubtypeR automatically applies method-specific preprocessing.
 #'
 #' @examples
-#' \donttest{
-#' library(BreastSubtypeR)
-#'
-#' # Using raw RNA-seq counts (with gene lengths)
-#' se_obj <- SummarizedExperiment(
-#'     assays = list(counts = raw_counts_mat),
-#'     rowData = DataFrame(
-#'         probe = rownames(raw_counts_mat),
-#'         ENTREZID = entrez_ids,
-#'         Length = gene_lengths
-#'     )
-#' )
-#' res <- Mapping(se_obj, RawCounts = TRUE)
-#'
-#' # Using pre-normalized log2(FPKM+1)
-#' se_obj_fpkm <- SummarizedExperiment(
-#'     assays = list(expr = log2_fpkm_mat),
-#'     rowData = DataFrame(
-#'         probe = rownames(log2_fpkm_mat),
-#'         ENTREZID = entrez_ids
-#'     )
-#' )
-#' res <- Mapping(se_obj_fpkm, RawCounts = FALSE)
+#' if (requireNamespace("SummarizedExperiment", quietly = TRUE)) {
+#'     # Using example raw RNA-seq counts (with gene lengths)
+#'     data("TCGABRCAobj")
+#'     se_obj_counts <- TCGABRCAobj$se_obj[, 1:3] # tiny subset to keep checks fast
+#'     res <- Mapping(se_obj_counts, RawCounts = TRUE)
+#'
+#'     # Using example pre-normalized log2(FPKM+0.1)
+#'     data("OSLO2EMIT0obj")
+#'     se_obj_fpkm <- OSLO2EMIT0obj$se_obj[, 1:3] # tiny subset to keep checks fast
+#'     res <- Mapping(se_obj_fpkm, RawCounts = FALSE)
 #' }
+#'
 #' @export
 
 Mapping <- function(
-        se_obj,
-        RawCounts = FALSE,
-        method = c("max", "mean", "median", "iqr", "stdev"),
-        impute = TRUE,
-        verbose = TRUE) {
+    se_obj,
+    RawCounts = FALSE,
+    method = c("max", "mean", "median", "iqr", "stdev"),
+    impute = TRUE,
+    verbose = TRUE) {
     method <- match.arg(method)
 
     arguments <- rlang::dots_list(
@@ -198,8 +191,8 @@ Mapping <- function(
 #' (Luminal A, Luminal B, HER2-enriched, Basal-like, and optionally Normal-like).
 #'
 #' @param se_obj A `SummarizedExperiment` object containing:
-#'   - **Assay data**: A log-transformed, normalized gene expression matrix with genes (Gene Symbols) as rows
-#'   and samples as columns.
+#'   - **Assay data**: A log-transformed, normalized gene expression matrix with genes 
+#'   (Gene Symbols) as rows and samples as columns.
 #'   - **Column metadata** (`colData`): Optional sample- or patient-level
 #'     information.
 #'
@@ -231,8 +224,8 @@ Mapping <- function(
 #'
 #' @param hasClinical Logical. If `TRUE`, incorporates clinical variables from
 #'   `colData(se_obj)`. Required columns:
-#'   - `"TSIZE"`: Tumor size (`0` = &le;2 cm; `1` = >2 cm).
-#'   - `"NODE"`: Lymph node status (`0` = negative; &ge;1 = positive). Must be numeric.
+#' - "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 #'
 #' @return A list containing PAM50 intrinsic subtype calls using the Parker
 #'   classifier and selected calibration strategy.
@@ -262,13 +255,13 @@ Mapping <- function(
 #' @export
 
 BS_parker <- function(
-        se_obj,
-        calibration = "None",
-        internal = NA,
-        external = NA,
-        medians = NA,
-        Subtype = FALSE,
-        hasClinical = FALSE) {
+    se_obj,
+    calibration = "None",
+    internal = NA,
+    external = NA,
+    medians = NA,
+    Subtype = FALSE,
+    hasClinical = FALSE) {
     # Check if input is a SummarizedExperiment object
     if (!inherits(se_obj, "SummarizedExperiment")) {
         stop("Input must be a SummarizedExperiment object.")
@@ -359,8 +352,8 @@ BS_parker <- function(
 #'
 #' @param hasClinical Logical. If `TRUE`, incorporates additional clinical
 #'   variables from `colData(se_obj)`. Required columns:
-#'   - `"TSIZE"`: Tumor size (`0` = &le;2 cm; `1` = >2 cm).
-#'   - `"NODE"`: Lymph node status (`0` = negative; &ge;1 = positive). Must be numeric.
+#' - "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 #'
 #' @param seed Integer. Random seed for reproducibility of ER-balancing.
 #'
@@ -385,9 +378,9 @@ BS_parker <- function(
 
 
 BS_cIHC <- function(se_obj,
-    Subtype = FALSE,
-    hasClinical = FALSE,
-    seed = 118) {
+                    Subtype = FALSE,
+                    hasClinical = FALSE,
+                    seed = 118) {
     # Check if input is a SummarizedExperiment object
     if (!inherits(se_obj, "SummarizedExperiment")) {
         stop("Input must be a SummarizedExperiment object.")
@@ -406,7 +399,8 @@ BS_cIHC <- function(se_obj,
     if (hasClinical) {
         req <- c("TSIZE", "NODE")
         miss <- setdiff(req, colnames(pheno))
-        if (length(miss)) stop("When hasClinical = TRUE, colData(se_obj) must include: TSIZE and NODE. Missing: ", paste(miss, collapse = ", "), ".")
+        if (length(miss)) stop("When hasClinical = TRUE, colData(se_obj) must include: TSIZE and NODE. 
+                               Missing: ", paste(miss, collapse = ", "), ".")
         if (!is.numeric(pheno$NODE)) stop("colData(se_obj)$NODE must be numeric.")
     }
 
@@ -444,7 +438,7 @@ BS_cIHC <- function(se_obj,
 #'     - `"ER"`: Estrogen receptor status, coded as `"ER+"` or `"ER-"`.
 #'
 #' @param iteration Integer. Number of iterations for the ER-balancing procedure.
-#'   Default: `100`.
+#'   Default: 100.
 #'
 #' @param ratio Numeric. Target ER+/ER– ratio for balancing. Options:
 #'   - `1:1`: Equal balancing.
@@ -455,8 +449,8 @@ BS_cIHC <- function(se_obj,
 #'
 #' @param hasClinical Logical. If `TRUE`, incorporates additional clinical
 #'   variables from `colData(se_obj)`. Required columns:
-#'   - `"TSIZE"`: Tumor size (`0` = &le;2 cm; `1` = >2 cm).
-#'   - `"NODE"`: Lymph node status (`0` = negative; &ge;1 = positive). Must be numeric.
+#' - "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 #'
 #' @param seed Integer. Random seed for reproducibility.
 #'
@@ -483,11 +477,11 @@ BS_cIHC <- function(se_obj,
 #' @export
 
 BS_cIHC.itr <- function(se_obj,
-    iteration = 100,
-    ratio = 54 / 64,
-    Subtype = FALSE,
-    hasClinical = FALSE,
-    seed = 118) {
+                        iteration = 100,
+                        ratio = 54 / 64,
+                        Subtype = FALSE,
+                        hasClinical = FALSE,
+                        seed = 118) {
     # Check if input is a SummarizedExperiment object
     if (!inherits(se_obj, "SummarizedExperiment")) {
         stop("Input must be a SummarizedExperiment object.")
@@ -506,7 +500,8 @@ BS_cIHC.itr <- function(se_obj,
     if (hasClinical) {
         req <- c("TSIZE", "NODE")
         miss <- setdiff(req, colnames(pheno))
-        if (length(miss)) stop("When hasClinical = TRUE, colData(se_obj) must include: TSIZE and NODE. Missing: ", paste(miss, collapse = ", "), ".")
+        if (length(miss)) stop("When hasClinical = TRUE, colData(se_obj) must include: TSIZE and NODE. 
+                               Missing: ", paste(miss, collapse = ", "), ".")
         if (!is.numeric(pheno$NODE)) stop("colData(se_obj)$NODE must be numeric.")
     }
 
@@ -549,8 +544,8 @@ BS_cIHC.itr <- function(se_obj,
 #'
 #' @param hasClinical Logical. If `TRUE`, incorporates additional clinical
 #'   variables from `colData(se_obj)`. Required columns:
-#'   - `"TSIZE"`: Tumor size (`0` = &le;2 cm; `1` = >2 cm).
-#'   - `"NODE"`: Lymph node status (`0` = negative; &ge;1 = positive). Must be numeric.
+#' - "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 #'
 #' @param seed Integer. Random seed for reproducibility.
 #'
@@ -574,9 +569,9 @@ BS_cIHC.itr <- function(se_obj,
 #' @export
 
 BS_PCAPAM50 <- function(se_obj,
-    Subtype = FALSE,
-    hasClinical = FALSE,
-    seed = 118) {
+                        Subtype = FALSE,
+                        hasClinical = FALSE,
+                        seed = 118) {
     # Check if input is a SummarizedExperiment object
     if (!inherits(se_obj, "SummarizedExperiment")) {
         stop("Input must be a SummarizedExperiment object.")
@@ -595,7 +590,8 @@ BS_PCAPAM50 <- function(se_obj,
     if (hasClinical) {
         req <- c("TSIZE", "NODE")
         miss <- setdiff(req, colnames(pheno))
-        if (length(miss)) stop("When hasClinical = TRUE, colData(se_obj) must include: TSIZE and NODE. Missing: ", paste(miss, collapse = ", "), ".")
+        if (length(miss)) stop("When hasClinical = TRUE, colData(se_obj) must include: TSIZE and NODE. 
+                               Missing: ", paste(miss, collapse = ", "), ".")
         if (!is.numeric(pheno$NODE)) stop("colData(se_obj)$NODE must be numeric.")
     }
 
@@ -696,8 +692,8 @@ BS_PCAPAM50 <- function(se_obj,
 #'
 #' @param hasClinical Logical. If `TRUE`, incorporates additional clinical
 #'   variables from `colData(se_obj)`. Required columns:
-#'   - `"TSIZE"`: Tumor size (`0` = &le;2 cm; `1` = >2 cm).
-#'   - `"NODE"`: Lymph node status (`0` = negative; &ge;1 = positive). Must be numeric.
+#' - "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 #'
 #' @return A character vector of intrinsic subtype predictions assigned to each
 #'   sample using the ssBC method.
@@ -726,9 +722,9 @@ BS_PCAPAM50 <- function(se_obj,
 #' @export
 
 BS_ssBC <- function(se_obj,
-    s,
-    Subtype = FALSE,
-    hasClinical = FALSE) {
+                    s,
+                    Subtype = FALSE,
+                    hasClinical = FALSE) {
     # Check that input is a SummarizedExperiment object
     if (!inherits(se_obj, "SummarizedExperiment")) {
         stop("Input must be a SummarizedExperiment object.")
@@ -747,7 +743,8 @@ BS_ssBC <- function(se_obj,
     if (hasClinical) {
         req <- c("TSIZE", "NODE")
         miss <- setdiff(req, colnames(pheno))
-        if (length(miss)) stop("When hasClinical = TRUE, colData(se_obj) must include: TSIZE and NODE. Missing: ", paste(miss, collapse = ", "), ".")
+        if (length(miss)) stop("When hasClinical = TRUE, colData(se_obj) must include: TSIZE and NODE. 
+                               Missing: ", paste(miss, collapse = ", "), ".")
         if (!is.numeric(pheno$NODE)) stop("colData(se_obj)$NODE must be numeric.")
     }
 
@@ -762,7 +759,8 @@ BS_ssBC <- function(se_obj,
 
     missing_columns <- setdiff(required_columns, colnames(pheno))
     if (length(missing_columns) > 0) {
-        stop(paste("The following required columns are missing from 'colData':", paste(missing_columns, collapse = ", ")))
+        stop(paste("The following required columns are missing from 'colData':", 
+                   paste(missing_columns, collapse = ", ")))
     }
 
     arguments <- rlang::dots_list(
@@ -958,8 +956,8 @@ BS_sspbc <- function(se_obj, ssp.name = "ssp.pam50") {
 #'
 #' @param hasClinical Logical. If `TRUE`, incorporates clinical data from
 #'   `colData(se_obj)`. Required columns:
-#'   - `"TSIZE"`: Tumor size (`0` = &le;2 cm; `1` = >2 cm).
-#'   - `"NODE"`: Lymph node status (`0` = negative; &ge;1 = positive; must be numeric).
+#' - "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive).
 #'
 #' @return A list containing per-method subtype assignments for each sample.
 #'
@@ -1014,10 +1012,10 @@ BS_sspbc <- function(se_obj, ssp.name = "ssp.pam50") {
 #' @export
 
 BS_Multi <- function(
-        data_input,
-        methods = "AUTO",
-        Subtype = FALSE,
-        hasClinical = FALSE) {
+    data_input,
+    methods = "AUTO",
+    Subtype = FALSE,
+    hasClinical = FALSE) {
     valid_methods <- c(
         "parker.original", "genefu.scale", "genefu.robust",
         "ssBC", "ssBC.v2", "cIHC", "cIHC.itr", "PCAPAM50",
@@ -1044,7 +1042,8 @@ BS_Multi <- function(
     rownames(pheno) <- pheno$PatientID
 
     # Check ER and HER2 columns in pheno
-    if (!("ER" %in% colnames(pheno)) && any(methods %in% c("ssBC", "ssBC.v2", "cIHC", "cIHC.itr", "PCAPAM50"))) {
+    if (!("ER" %in% colnames(pheno)) && any(methods %in% 
+                                            c("ssBC", "ssBC.v2", "cIHC", "cIHC.itr", "PCAPAM50"))) {
         stop("The 'ER' column is required for selected methods.")
     }
     if (!("HER2" %in% colnames(pheno)) && "ssBC.v2" %in% methods) {
@@ -1141,7 +1140,7 @@ BS_Multi <- function(
                 },
                 error = function(e) {
                     # Error handling
-                    warning("PCAPAM50 failed in this iteration. Error: ")
+                    warning("PCAPAM50 failed in this iteration: ")
                     return(NULL) # Return NULL or a dummy tibble with NAs
                 }
             )
@@ -1183,7 +1182,7 @@ BS_Multi <- function(
                 length(samples_ER.icd) < nrow(pheno)) {
                 unprocessed_patients <- base::setdiff(pheno$PatientID, samples_ER.icd)
 
-                # Create NA-filled dataframe for unprocessed patients with matching structure
+                # Create NA-filled data frame for unprocessed patients with matching structure
                 na_df <- data.frame(
                     PatientID = unprocessed_patients,
                     matrix(
@@ -1235,7 +1234,7 @@ BS_Multi <- function(
                 unprocessed_patients <- base::setdiff(pheno$PatientID, samples_ERHER2.icd)
 
 
-                # Create NA-filled dataframe for unprocessed patients with matching structure
+                # Create NA-filled data frame for unprocessed patients with matching structure
                 na_df <- data.frame(
                     PatientID = unprocessed_patients,
                     matrix(
@@ -1306,8 +1305,10 @@ BS_Multi <- function(
     names(results) <- methods
 
     # Prefer se_NC samples; fall back to se_SSP if needed
-    samples_NC <- if (!is.null(data_input$se_NC)) colnames(SummarizedExperiment::assay(data_input$se_NC)) else character(0)
-    samples_SSP <- if (!is.null(data_input$se_SSP)) colnames(SummarizedExperiment::assay(data_input$se_SSP)) else character(0)
+    samples_NC <- if (!is.null(data_input$se_NC)) 
+      colnames(SummarizedExperiment::assay(data_input$se_NC)) else character(0)
+    samples_SSP <- if (!is.null(data_input$se_SSP)) 
+      colnames(SummarizedExperiment::assay(data_input$se_SSP)) else character(0)
     samples <- if (length(samples_NC)) samples_NC else samples_SSP
 
     # Hold per-method calls; start empty and fill by matching PatientID
@@ -1349,7 +1350,8 @@ BS_Multi <- function(
     res_subtypes$row_id <- NULL
 
     if (Subtype) {
-        res_subtypes.Subtype <- as.data.frame(res_subtypes.Subtype, stringsAsFactors = FALSE, check.names = FALSE)
+        res_subtypes.Subtype <- 
+          as.data.frame(res_subtypes.Subtype, stringsAsFactors = FALSE, check.names = FALSE)
         rownames(res_subtypes.Subtype) <- res_subtypes.Subtype$row_id
         res_subtypes.Subtype$row_id <- NULL
     }
diff --git a/R/NC_functions.R b/R/NC_functions.R
index 21b8861..3e3147e 100755
--- a/R/NC_functions.R
+++ b/R/NC_functions.R
@@ -99,11 +99,11 @@ overlapSets <- function(x, y) {
 #' @param external    For External: NAME of a column in medians.all (e.g., "RNAseq.V2", "Given.mdns")
 #' @noRd
 docalibration <- function(
-        y,
-        medians.all,
-        calibration = c("None", "Internal", "External"),
-        internal = NA,
-        external = NA) {
+    y,
+    medians.all,
+    calibration = c("None", "Internal", "External"),
+    internal = NA,
+    external = NA) {
     calibration <- match.arg(calibration)
     y <- as.matrix(y)
     mq <- 0.05 # robust quantiles for 'qCtr' (genefu.robust)
@@ -169,8 +169,8 @@ standardize <- function(x) {
 #' Function for suffix of medians for gene centering
 #' @noRd
 getsuffix <- function(calibration,
-    internal = NA,
-    external = NA) {
+                      internal = NA,
+                      external = NA) {
     calibration <- match.arg(calibration, choices = c("None", "Internal", "External"))
 
     suffix <- switch(calibration,
@@ -327,14 +327,14 @@ sspPredict <- function(x, y, std = FALSE, distm = "spearman", Subtype = TRUE) {
 #' @param Subtype Logic.
 #' @param hasClinical Logic. Specify whether clinical information is included.
 #'   For example, tumor size should be in the "T" column, and lymph node status
-#'   should be in the "NODE" column.
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive).
 #' @return ROR, ROR risk group and other indications
 #' @noRd
 
 RORgroup <- function(out,
-    df.cln,
-    Subtype = FALSE,
-    hasClinical = FALSE) {
+                     df.cln,
+                     Subtype = FALSE,
+                     hasClinical = FALSE) {
     sample <- data.frame(patientID = names(out$predictions))
 
     distance <- data.frame(out$distances, row.names = names(out$predictions))
@@ -717,13 +717,13 @@ RORgroup <- function(out,
 #'
 
 makeCalls.parker <- function(mat,
-    df.cln,
-    calibration = c("None", "Internal", "External"),
-    internal = NA,
-    external = NA,
-    medians = NULL,
-    Subtype = FALSE,
-    hasClinical = FALSE) {
+                             df.cln,
+                             calibration = c("None", "Internal", "External"),
+                             internal = NA,
+                             external = NA,
+                             medians = NULL,
+                             Subtype = FALSE,
+                             hasClinical = FALSE) {
     ## loading dataset
     data_env <- new.env(parent = emptyenv())
     data("BreastSubtypeRobj", envir = data_env, package = "BreastSubtypeR")
@@ -828,20 +828,20 @@ makeCalls.parker <- function(mat,
 #' @param Subtype Logic.
 #' @param hasClinical Logic. Specify whether clinical information is included.
 #'   For example, tumor size should be in the "T" column, and lymph node status
-#'   should be in the "NODE" column.
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive).
 #' @param seed An integer value is used to set the random seed.
 #' @noRd
 
 
 makeCalls_ihc <- function(mat,
-    df.cln,
-    calibration = "Internal",
-    internal = "IHC.mdns",
-    external = NA,
-    medians = NA,
-    Subtype = FALSE,
-    hasClinical = FALSE,
-    seed = 118) {
+                          df.cln,
+                          calibration = "Internal",
+                          internal = "IHC.mdns",
+                          external = NA,
+                          medians = NA,
+                          Subtype = FALSE,
+                          hasClinical = FALSE,
+                          seed = 118) {
     ## loading dataset
     data_env <- new.env(parent = emptyenv())
     data("BreastSubtypeRobj", envir = data_env, package = "BreastSubtypeR")
@@ -971,16 +971,16 @@ makeCalls_ihc <- function(mat,
 #' @noRd
 
 makeCalls_ihc.iterative <- function(mat,
-    df.cln,
-    iteration = 100,
-    ratio = 54 / 64,
-    calibration = "Internal",
-    internal = "ER.mdns",
-    external = NA,
-    medians = NA,
-    Subtype = FALSE,
-    hasClinical = FALSE,
-    seed = 118) {
+                                    df.cln,
+                                    iteration = 100,
+                                    ratio = 54 / 64,
+                                    calibration = "Internal",
+                                    internal = "ER.mdns",
+                                    external = NA,
+                                    medians = NA,
+                                    Subtype = FALSE,
+                                    hasClinical = FALSE,
+                                    seed = 118) {
     ## loading dataset
     data_env <- new.env(parent = emptyenv())
     data("BreastSubtypeRobj", envir = data_env, package = "BreastSubtypeR")
@@ -1163,20 +1163,20 @@ makeCalls_ihc.iterative <- function(mat,
 #' @param Subtype Logic
 #' @param hasClinical Logic. Specify whether clinical information is included.
 #'   For example, tumor size should be in the "T" column, and lymph node status
-#'   should be in the "NODE" column.
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive).
 #' @param seed An integer value is used to set the random seed.
 #' @noRd
 
 makeCalls.PC1ihc <- function(
-        mat,
-        df.cln,
-        calibration = "Internal",
-        internal = "PC1ihc.mdns",
-        external = NA,
-        medians = NA,
-        Subtype = FALSE,
-        hasClinical = FALSE,
-        seed = 118) {
+    mat,
+    df.cln,
+    calibration = "Internal",
+    internal = "PC1ihc.mdns",
+    external = NA,
+    medians = NA,
+    Subtype = FALSE,
+    hasClinical = FALSE,
+    seed = 118) {
     ## loading dataset
     data_env <- new.env(parent = emptyenv())
     data("BreastSubtypeRobj", envir = data_env, package = "BreastSubtypeR")
@@ -1356,20 +1356,20 @@ makeCalls.PC1ihc <- function(
 #' @param Subtype Logic.
 #' @param hasClinical Logic. Specify whether clinical information is included.
 #'   For example, tumor size should be in the "T" column, and lymph node status
-#'   should be in the "NODE" column.
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive).
 #' @param seed An integer value is used to set the random seed.
 #' @noRd
 
 makeCalls.v1PAM <- function(
-        mat,
-        df.pam,
-        calibration = "Internal",
-        internal = "v1PAM.mdns",
-        external = NA,
-        medians = NA,
-        Subtype = FALSE,
-        hasClinical = FALSE,
-        seed = 118) {
+    mat,
+    df.pam,
+    calibration = "Internal",
+    internal = "v1PAM.mdns",
+    external = NA,
+    medians = NA,
+    Subtype = FALSE,
+    hasClinical = FALSE,
+    seed = 118) {
     ## loading dataset
     data_env <- new.env(parent = emptyenv())
     data("BreastSubtypeRobj", envir = data_env, package = "BreastSubtypeR")
@@ -1484,15 +1484,15 @@ makeCalls.v1PAM <- function(
 #' @param Subtype Logic. Specify whether to predict Subtype-like subtyping.
 #' @param hasClinical Logic. Specify whether clinical information is included.
 #'   For example, tumor size should be in the "T" column, and lymph node status
-#'   should be in the "NODE" column.
+#' - "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive).
 #' @noRd
 
 makeCalls.ssBC <- function(
-        mat,
-        df.cln,
-        s = c("ER", "TN", "ER.v2", "TN.v2"),
-        Subtype = FALSE,
-        hasClinical = FALSE) {
+    mat,
+    df.cln,
+    s = c("ER", "TN", "ER.v2", "TN.v2"),
+    Subtype = FALSE,
+    hasClinical = FALSE) {
     ## loading dataset
     data_env <- new.env(parent = emptyenv())
     data("BreastSubtypeRobj", envir = data_env, package = "BreastSubtypeR")
diff --git a/R/SSPBC_functions.R b/R/SSPBC_functions.R
index fa335e6..2aeed2b 100755
--- a/R/SSPBC_functions.R
+++ b/R/SSPBC_functions.R
@@ -1,10 +1,11 @@
 ## adapted from original sspbc codes (Staaf et al., 2022)
 
 #' Function sspbc
-#' @import e1071
 #' @import methods
 #' @import stats
 #' @import grid
+#' @importFrom e1071 naiveBayes
+#'
 #' @description
 #' This function assign classes to breast cancer samples using a selection of provided models. It works on raw gene expression data.
 #' Provided models were developed using gene expression data from mRNAseq generated using HiSat/StringTie.
@@ -13,19 +14,19 @@
 #' @noRd
 
 applySSP <- function(
-        tsv,
-        ssp = "",
-        plot = FALSE,
-        txt = FALSE,
-        report = FALSE,
-        add.is.num = TRUE,
-        mylas = 1,
-        ssp.name = "",
-        gex = NULL,
-        id = NULL,
-        id.type = "Gene.ID",
-        full.out = FALSE,
-        output) {
+    tsv,
+    ssp = "",
+    plot = FALSE,
+    txt = FALSE,
+    report = FALSE,
+    add.is.num = TRUE,
+    mylas = 1,
+    ssp.name = "",
+    gex = NULL,
+    id = NULL,
+    id.type = "Gene.ID",
+    full.out = FALSE,
+    output) {
     data_env <- new.env(parent = emptyenv())
     data("Gene.ID.ann", envir = data_env, package = "BreastSubtypeR")
     Gene.ID.ann <- data_env[["Gene.ID.ann"]]
@@ -334,11 +335,11 @@ read_StringTie_tsv_FPKM <- function(tsv, id, report = FALSE) {
 
 # function
 translate_id2entrez <- function(
-        id,
-        ann,
-        id.type = "Gene.ID",
-        e = FALSE,
-        report = FALSE) {
+    id,
+    ann,
+    id.type = "Gene.ID",
+    e = FALSE,
+    report = FALSE) {
     if (id.type %in% c("Gene.ID", "Gene.Name", "HGNC", "EntrezGene")) {
         # find first index for id in ann
         id.i <- match(as.character(id), ann[, id.type])
diff --git a/R/Utilities.R b/R/Utilities.R
index 1438829..0d8894b 100755
--- a/R/Utilities.R
+++ b/R/Utilities.R
@@ -1,16 +1,17 @@
 #'
 #' Functions for BreastSubtypeR package
-#' @import ggplot2
+#' @keywords internal
 #' @import ComplexHeatmap
 #' @import RColorBrewer
 #' @import circlize
 #' @import ggrepel
 #' @import magrittr
 #' @import impute
-#' @importFrom SummarizedExperiment SummarizedExperiment
-#' @importFrom SummarizedExperiment colData
-#' @importFrom SummarizedExperiment rowData
-#' @importFrom SummarizedExperiment assay
+#' @importFrom dplyr mutate across everything
+#' @importFrom ggplot2 ggplot aes geom_point geom_bar geom_text geom_line geom_vline geom_hline
+#' @importFrom ggplot2 geom_boxplot scale_x_continuous scale_color_manual scale_fill_manual
+#' @importFrom ggplot2 coord_polar labs theme theme_classic theme_minimal theme_void element_text
+#' @importFrom SummarizedExperiment SummarizedExperiment colData rowData assay
 #'
 #' @noRd
 NULL
@@ -170,10 +171,10 @@ prepare_ssp_matrix <- function(x, genes.s, RawCounts, samplenames, verbose) {
 #' @noRd
 
 domapping <- function(se_obj,
-    RawCounts = FALSE,
-    method = "max",
-    impute = TRUE,
-    verbose = TRUE) {
+                      RawCounts = FALSE,
+                      method = "max",
+                      impute = TRUE,
+                      verbose = TRUE) {
     ## 1. Input raw counts
     if (RawCounts && !"Length" %in% colnames(rowData(se_obj))) {
         stop(
@@ -515,12 +516,15 @@ get_average_subtype <- function(res_ihc_iterative, consensus_subtypes) {
 
             ## if FALSE, make the cell as NULL
             keep <- res_ihc$predictions == consensus_subtypes
-            res_ihc$distances[!keep, ] <- as.list(rep(NA, 5))
+            res_ihc$distances[!keep, ] <- as.list(rep(NA, ncol(res_ihc$distances)))
 
-            res <- dplyr::mutate_at(
+            ## convert every column to numeric (preserving NA), same as before
+            res <- dplyr::mutate(
                 res_ihc$distances,
-                vars(everything()),
-                ~ ifelse(!is.na(.), as.numeric(as.character(.)), NA)
+                dplyr::across(
+                    dplyr::everything(),
+                    ~ ifelse(!is.na(.x), as.numeric(as.character(.x)), NA_real_)
+                )
             )
 
             return(res)
@@ -577,12 +581,14 @@ get_average_subtype <- function(res_ihc_iterative, consensus_subtypes) {
 
             ## if FALSE, make the cell as NULL
             keep <- res_ihc$predictions == consensus_subtypes
-            res_ihc$distances.Subtype[!keep, ] <- as.list(rep(NA, 4))
+            res_ihc$distances.Subtype[!keep, ] <- as.list(rep(NA, ncol(res_ihc$distances.Subtype)))
 
-            res <- dplyr::mutate_at(
+            res <- dplyr::mutate(
                 res_ihc$distances.Subtype,
-                vars(everything()),
-                ~ ifelse(!is.na(.), as.numeric(as.character(.)), NA)
+                dplyr::across(
+                    dplyr::everything(),
+                    ~ ifelse(!is.na(.x), as.numeric(as.character(.x)), NA_real_)
+                )
             )
 
             return(res)
diff --git a/R/runShinyBreastSubtypeR.R b/R/runShinyBreastSubtypeR.R
index 9b634d6..9519488 100755
--- a/R/runShinyBreastSubtypeR.R
+++ b/R/runShinyBreastSubtypeR.R
@@ -9,21 +9,18 @@
 #' @param attach_tidyverse Logical; if TRUE and tidyverse is installed, it will
 #'        be attached quietly for the session (purely optional).
 #' @param max_upload_mb Numeric; Shiny upload size limit (in MB). Default 1000.
-#' @return Opens the app; returns the value of `shiny::runApp()`.
+#' @return The value returned by `shiny::runApp()` (usually `invisible(NULL)`).
 #'
 #' @examples
-#' \donttest{
-#' # Basic
-#' iBreastSubtypeR()
-#'
-#' # Skip attaching packages (if UI/server fully qualify all calls)
-#' iBreastSubtypeR(attach = character(0))
+#' if (interactive()) {
+#'     iBreastSubtypeR()
+#'     iBreastSubtypeR(attach = character(0))
 #' }
 #'
 #' @export
 iBreastSubtypeR <- function(attach = c("shiny", "bslib"),
-    attach_tidyverse = FALSE,
-    max_upload_mb = 1000) {
+                            attach_tidyverse = FALSE,
+                            max_upload_mb = 1000) {
     # helper: check install + attach quietly
     .attach_if <- function(pkgs) {
         pkgs <- unique(pkgs)
@@ -70,14 +67,11 @@ iBreastSubtypeR <- function(attach = c("shiny", "bslib"),
     shiny::runApp(appDir, display.mode = "normal")
 }
 
-#' @title (Deprecated) Run iBreastSubtypeR
-#' @description Back-compat wrapper; use [iBreastSubtypeR()] instead.
-#' @param ... Arguments passed on to [iBreastSubtypeR()].
-#' @export
+#' (Deprecated) Run iBreastSubtypeR
+#'
+#' Internal wrapper kept for back-compat. Use [iBreastSubtypeR()] directly.
+#' @keywords internal
+#' @noRd
 runShinyBreastSubtypeR <- function(...) {
-    .Deprecated("iBreastSubtypeR",
-        package = "BreastSubtypeR",
-        msg = "runShinyBreastSubtypeR() is deprecated; use iBreastSubtypeR()."
-    )
     iBreastSubtypeR(...)
 }
diff --git a/R/zzz.R b/R/zzz.R
index 32d611a..259f505 100755
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -2,4 +2,4 @@
 utils::globalVariables(c("AIMSmodel", "BreastSubtypeRobj"))
 
 ## AIMS/sspbc
-utils::globalVariables(c("Gene.ID.ann", "sspbc.models", "sspbc.models.fullname"))
+utils::globalVariables(c(".data", "Gene.ID.ann", "sspbc.models", "sspbc.models.fullname"))
diff --git a/man/BS_Multi.Rd b/man/BS_Multi.Rd
index b67d72c..b818970 100755
--- a/man/BS_Multi.Rd
+++ b/man/BS_Multi.Rd
@@ -38,8 +38,8 @@ HER2-enriched, Basal-like), excluding Normal-like.}
 \item{hasClinical}{Logical. If \code{TRUE}, incorporates clinical data from
 \code{colData(se_obj)}. Required columns:
 \itemize{
-\item \code{"TSIZE"}: Tumor size (\code{0} = ≤2 cm; \code{1} = >2 cm).
-\item \code{"NODE"}: Lymph node status (\code{0} = negative; ≥1 = positive; must be numeric).
+\item "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+\item "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive).
 }}
 }
 \value{
diff --git a/man/BS_PCAPAM50.Rd b/man/BS_PCAPAM50.Rd
index e99cc22..3230755 100755
--- a/man/BS_PCAPAM50.Rd
+++ b/man/BS_PCAPAM50.Rd
@@ -24,8 +24,8 @@ genes (Gene Symbols) as rows and samples as columns.
 \item{hasClinical}{Logical. If \code{TRUE}, incorporates additional clinical
 variables from \code{colData(se_obj)}. Required columns:
 \itemize{
-\item \code{"TSIZE"}: Tumor size (\code{0} = ≤2 cm; \code{1} = >2 cm).
-\item \code{"NODE"}: Lymph node status (\code{0} = negative; ≥1 = positive). Must be numeric.
+\item "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+\item "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 }}
 
 \item{seed}{Integer. Random seed for reproducibility.}
diff --git a/man/BS_cIHC.Rd b/man/BS_cIHC.Rd
index 97c6f3a..d855fe9 100755
--- a/man/BS_cIHC.Rd
+++ b/man/BS_cIHC.Rd
@@ -24,8 +24,8 @@ genes (Gene Symbols) as rows and samples as columns.
 \item{hasClinical}{Logical. If \code{TRUE}, incorporates additional clinical
 variables from \code{colData(se_obj)}. Required columns:
 \itemize{
-\item \code{"TSIZE"}: Tumor size (\code{0} = ≤2 cm; \code{1} = >2 cm).
-\item \code{"NODE"}: Lymph node status (\code{0} = negative; ≥1 = positive). Must be numeric.
+\item "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+\item "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 }}
 
 \item{seed}{Integer. Random seed for reproducibility of ER-balancing.}
diff --git a/man/BS_cIHC.itr.Rd b/man/BS_cIHC.itr.Rd
index 945a16a..52d3b39 100755
--- a/man/BS_cIHC.itr.Rd
+++ b/man/BS_cIHC.itr.Rd
@@ -26,7 +26,7 @@ genes (Gene Symbols) as rows and samples as columns.
 }}
 
 \item{iteration}{Integer. Number of iterations for the ER-balancing procedure.
-Default: \code{100}.}
+Default: 100.}
 
 \item{ratio}{Numeric. Target ER+/ER– ratio for balancing. Options:
 \itemize{
@@ -40,8 +40,8 @@ Default: \code{100}.}
 \item{hasClinical}{Logical. If \code{TRUE}, incorporates additional clinical
 variables from \code{colData(se_obj)}. Required columns:
 \itemize{
-\item \code{"TSIZE"}: Tumor size (\code{0} = ≤2 cm; \code{1} = >2 cm).
-\item \code{"NODE"}: Lymph node status (\code{0} = negative; ≥1 = positive). Must be numeric.
+\item "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+\item "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 }}
 
 \item{seed}{Integer. Random seed for reproducibility.}
diff --git a/man/BS_parker.Rd b/man/BS_parker.Rd
index 90f29c8..6ad2a8d 100755
--- a/man/BS_parker.Rd
+++ b/man/BS_parker.Rd
@@ -17,8 +17,8 @@ BS_parker(
 \arguments{
 \item{se_obj}{A \code{SummarizedExperiment} object containing:
 \itemize{
-\item \strong{Assay data}: A log-transformed, normalized gene expression matrix with genes (Gene Symbols) as rows
-and samples as columns.
+\item \strong{Assay data}: A log-transformed, normalized gene expression matrix with genes
+(Gene Symbols) as rows and samples as columns.
 \item \strong{Column metadata} (\code{colData}): Optional sample- or patient-level
 information.
 }}
@@ -60,8 +60,8 @@ excluding Normal-like.}
 \item{hasClinical}{Logical. If \code{TRUE}, incorporates clinical variables from
 \code{colData(se_obj)}. Required columns:
 \itemize{
-\item \code{"TSIZE"}: Tumor size (\code{0} = ≤2 cm; \code{1} = >2 cm).
-\item \code{"NODE"}: Lymph node status (\code{0} = negative; ≥1 = positive). Must be numeric.
+\item "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+\item "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 }}
 }
 \value{
diff --git a/man/BS_ssBC.Rd b/man/BS_ssBC.Rd
index a4c25fe..2d714d5 100755
--- a/man/BS_ssBC.Rd
+++ b/man/BS_ssBC.Rd
@@ -35,8 +35,8 @@ genes (Gene Symbols) as rows and samples as columns.
 \item{hasClinical}{Logical. If \code{TRUE}, incorporates additional clinical
 variables from \code{colData(se_obj)}. Required columns:
 \itemize{
-\item \code{"TSIZE"}: Tumor size (\code{0} = ≤2 cm; \code{1} = >2 cm).
-\item \code{"NODE"}: Lymph node status (\code{0} = negative; ≥1 = positive). Must be numeric.
+\item "TSIZE": Tumor size (0 = \eqn{\le 2}{<= 2} cm; 1 = \eqn{> 2}{> 2} cm).
+\item "NODE": Lymph node status (0 = negative; \eqn{\ge 1}{>= 1} = positive). Must be numeric.
 }}
 }
 \value{
diff --git a/man/BreastSubtypeR.Rd b/man/BreastSubtypeR.Rd
index b3d613a..59c03ad 100755
--- a/man/BreastSubtypeR.Rd
+++ b/man/BreastSubtypeR.Rd
@@ -4,7 +4,8 @@
 \name{BreastSubtypeR}
 \alias{BreastSubtypeR}
 \alias{BreastSubtypeR-package}
-\title{BreastSubtypeR: A Unified R/Bioconductor Package for Intrinsic Molecular Subtyping in Breast Cancer Research}
+\title{BreastSubtypeR: A Unified R/Bioconductor Package
+for Intrinsic Molecular Subtyping in Breast Cancer Research}
 \description{
 \strong{BreastSubtypeR} is an R/Bioconductor package that unifies multiple
 published intrinsic subtyping (IS) methods for breast cancer into a single,
diff --git a/man/Mapping.Rd b/man/Mapping.Rd
index 4f3907f..088b77b 100755
--- a/man/Mapping.Rd
+++ b/man/Mapping.Rd
@@ -17,7 +17,8 @@ Mapping(
 \itemize{
 \item \strong{Assay data}:
 \itemize{
-\item If \code{RawCounts = FALSE}: \code{assay()} must contain log2-normalized expression (e.g., pre-normalized microarray/nCounter, or log2(FPKM+1) RNAseq).
+\item If \code{RawCounts = FALSE}: \code{assay()} must contain log2-normalized expression
+(e.g., pre-normalized microarray/nCounter, or log2(FPKM+1) RNAseq).
 \item If \code{RawCounts = TRUE}: \code{assay()} contains raw RNA-seq counts (see \code{RawCounts}).
 }
 \item \strong{Row metadata} (required):
@@ -31,7 +32,8 @@ renamed as \code{probe}.
 }}
 
 \item{RawCounts}{Logical. If \code{TRUE}, indicates that \code{assay()} holds raw RNA-seq counts.
-In this case, \code{rowData()} must also provide gene lengths (column \code{"Length"}, in base pairs), used for:
+In this case, \code{rowData()} must also provide gene lengths
+(column \code{"Length"}, in base pairs), used for:
 \itemize{
 \item NC-based methods: log2-CPM (upper-quartile normalization).
 \item SSP-based methods: linear FPKM (not log-transformed).
@@ -53,8 +55,10 @@ In this case, \code{rowData()} must also provide gene lengths (column \code{"Len
 \value{
 A named list with:
 \describe{
-\item{se_NC}{\code{SummarizedExperiment} holding log2-transformed data prepared for NC-based methods (assay name: \code{counts}).}
-\item{se_SSP}{\code{SummarizedExperiment} holding linear-scale data prepared for SSP-based methods (assay name: \code{counts}).}
+\item{se_NC}{\code{SummarizedExperiment} holding log2-transformed data prepared for NC-based methods
+(assay name: \code{counts}).}
+\item{se_SSP}{\code{SummarizedExperiment} holding linear-scale data prepared for SSP-based methods
+(assay name: \code{counts}).}
 }
 }
 \description{
@@ -73,30 +77,18 @@ This design allows users to supply a single expression format, while
 BreastSubtypeR automatically applies method-specific preprocessing.
 }
 \examples{
-\donttest{
-library(BreastSubtypeR)
+if (requireNamespace("SummarizedExperiment", quietly = TRUE)) {
+    # Using example raw RNA-seq counts (with gene lengths)
+    data("TCGABRCAobj")
+    se_obj_counts <- TCGABRCAobj$se_obj[, 1:3] # tiny subset to keep checks fast
+    res <- Mapping(se_obj_counts, RawCounts = TRUE)
 
-# Using raw RNA-seq counts (with gene lengths)
-se_obj <- SummarizedExperiment(
-    assays = list(counts = raw_counts_mat),
-    rowData = DataFrame(
-        probe = rownames(raw_counts_mat),
-        ENTREZID = entrez_ids,
-        Length = gene_lengths
-    )
-)
-res <- Mapping(se_obj, RawCounts = TRUE)
-
-# Using pre-normalized log2(FPKM+1)
-se_obj_fpkm <- SummarizedExperiment(
-    assays = list(expr = log2_fpkm_mat),
-    rowData = DataFrame(
-        probe = rownames(log2_fpkm_mat),
-        ENTREZID = entrez_ids
-    )
-)
-res <- Mapping(se_obj_fpkm, RawCounts = FALSE)
+    # Using example pre-normalized log2(FPKM+0.1)
+    data("OSLO2EMIT0obj")
+    se_obj_fpkm <- OSLO2EMIT0obj$se_obj[, 1:3] # tiny subset to keep checks fast
+    res <- Mapping(se_obj_fpkm, RawCounts = FALSE)
 }
+
 }
 \references{
 Yang Q, Hartman J, Sifakis EG.
diff --git a/man/iBreastSubtypeR.Rd b/man/iBreastSubtypeR.Rd
index 20807ce..6f7abb3 100755
--- a/man/iBreastSubtypeR.Rd
+++ b/man/iBreastSubtypeR.Rd
@@ -20,7 +20,7 @@ be attached quietly for the session (purely optional).}
 \item{max_upload_mb}{Numeric; Shiny upload size limit (in MB). Default 1000.}
 }
 \value{
-Opens the app; returns the value of \code{shiny::runApp()}.
+The value returned by \code{shiny::runApp()} (usually \code{invisible(NULL)}).
 }
 \description{
 Starts the Shiny UI bundled with the BreastSubtypeR package.
@@ -28,12 +28,9 @@ The launcher can (optionally) attach Shiny/Bslib so UI/server can use
 unqualified functions like \code{tags}, \code{icon}, \code{fileInput}, etc.
 }
 \examples{
-\donttest{
-# Basic
-iBreastSubtypeR()
-
-# Skip attaching packages (if UI/server fully qualify all calls)
-iBreastSubtypeR(attach = character(0))
+if (interactive()) {
+    iBreastSubtypeR()
+    iBreastSubtypeR(attach = character(0))
 }
 
 }
diff --git a/man/runShinyBreastSubtypeR.Rd b/man/runShinyBreastSubtypeR.Rd
deleted file mode 100644
index cae88d0..0000000
--- a/man/runShinyBreastSubtypeR.Rd
+++ /dev/null
@@ -1,14 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/runShinyBreastSubtypeR.R
-\name{runShinyBreastSubtypeR}
-\alias{runShinyBreastSubtypeR}
-\title{(Deprecated) Run iBreastSubtypeR}
-\usage{
-runShinyBreastSubtypeR(...)
-}
-\arguments{
-\item{...}{Arguments passed on to \code{\link[=iBreastSubtypeR]{iBreastSubtypeR()}}.}
-}
-\description{
-Back-compat wrapper; use \code{\link[=iBreastSubtypeR]{iBreastSubtypeR()}} instead.
-}
diff --git a/vignettes/BreastSubtypeR.Rmd b/vignettes/BreastSubtypeR.Rmd
index 6688b80..62da02d 100755
--- a/vignettes/BreastSubtypeR.Rmd
+++ b/vignettes/BreastSubtypeR.Rmd
@@ -22,6 +22,7 @@ knitr::opts_chunk$set(
     collapse = TRUE,
     comment  = "#>",
     fig.path = "figures/",
+    fig.crop = FALSE,
     warning  = FALSE,
     message  = FALSE
 )
@@ -91,7 +92,7 @@ The package includes implementations of commonly used subtyping methods (NC-base
 
 The examples below use small example datasets shipped with the package. For your own data, provide a `SummarizedExperiment` **with clinical metadata in `colData`** (e.g., `PatientID`, ER/HER2; for ROR: `TSIZE`, `NODE`).
 
-```{r, eval=FALSE}
+```{r pkgs-and-data, message=FALSE}
 library(BreastSubtypeR)
 
 # Example data
@@ -101,8 +102,9 @@ data("OSLO2EMIT0obj")
 
 **1) Map & prepare (method-specific pre-processing + mapping)**
 
-```{r, eval=FALSE}
-# Pre-processing: automatically apply tailored normalisation, map probes/IDs to Entrez, and (optionally) impute missing values
+```{r, eval=TRUE}
+# Pre-processing: automatically apply tailored normalisation, map probes/IDs to Entrez, 
+# and (optionally) impute missing values
 data_input <- Mapping(
     OSLO2EMIT0obj$se_obj,
     method = "max", # mapping strategy (example)
@@ -127,7 +129,7 @@ data_input <- Mapping(
 
 **2) Multi-method run (user-defined)**
 
-```{r, eval=FALSE}
+```{r, eval=TRUE}
 methods <- c("parker.original", "PCAPAM50", "sspbc")
 
 res <- BS_Multi(
@@ -145,7 +147,7 @@ head(res$res_subtypes, 5)
 
 AUTO evaluates cohort diagnostics (for example, ER/HER2 distribution, subtype purity, and subgroup sizes) and selects methods compatible with the cohort. It disables classifiers whose distributional assumptions would likely be violated.
 
-```{r, eval=FALSE}
+```{r, eval=TRUE}
 res_auto <- BS_Multi(
     data_input = data_input,
     methods = "AUTO",
@@ -161,7 +163,7 @@ Vis_Multi(res_auto$res_subtypes)
 
 PAM50 (NC-based)
 
-```{r, eval=FALSE}
+```{r, eval=TRUE}
 res_pam <- BS_parker(
     se_obj = data_input$se_NC, # object prepared for NC-based methods
     calibration = "Internal",
@@ -173,7 +175,7 @@ res_pam <- BS_parker(
 
 AIMS (SSP-based)
 
-```{r, eval=FALSE}
+```{r, eval=TRUE}
 res_aims <- BS_AIMS(data_input$se_SSP)
 ```
 
@@ -191,7 +193,8 @@ res_aims <- BS_AIMS(data_input$se_SSP)
 
 - Use `methods = "AUTO"` (i.e. `BS_Multi(methods = "AUTO", ...)`) for exploratory datasets or cohorts of unknown / skewed composition.
 - Use `AUTO` when you want the package to **select only classifiers compatible with the cohort** (it disables methods whose assumptions appear violated).
-- For validation against a single published method or a clinical assay (e.g., Prosigna®), run the corresponding **single-method** implementation directly (e.g., `BS_parker()`).
+- For validation against a single published method or a clinical assay (e.g., Prosigna®), 
+run the corresponding **single-method** implementation directly (e.g., `BS_parker()`).
 
 ## Interpretation
 
@@ -226,7 +229,8 @@ The app runs locally; **no data leave your machine**.
 
 BreastSubtypeR harmonises many published, signature-based classifiers but has known limitations:\
 
-- It is not a clinical-grade replacement for assays like Prosigna; clinical validation requires paired clinical assay data.\
+- It is not a clinical-grade replacement for assays like Prosigna; 
+clinical validation requires paired clinical assay data.\
 
 - AUTO selects compatible methods; it does not perform consensus voting by default.