diff --git a/R/accessory.R b/R/accessory.R
index 0ffc434..29c952f 100644
--- a/R/accessory.R
+++ b/R/accessory.R
@@ -910,6 +910,8 @@ checkListIsSubset <- function(test_list,
 #'   sample sheet variables to be used as blocking factors
 #' @param convert_to_list Convert output to a list as used internally by
 #'   shinyngs?
+#' @param validate_design Validate design matrix (check for NAs, full rank,
+#'   numeric columns, special characters)? Set to FALSE to skip these checks.
 #'
 #' @return output Validated contrasts data frame
 #' @export
@@ -921,7 +923,8 @@ read_contrasts <-
           reference_column = "reference",
           target_column = "target",
           blocking_column = "blocking",
-          convert_to_list = FALSE) {
+          convert_to_list = FALSE,
+          validate_design = TRUE) {
 
   # Read the contrasts depending on the file format (CSV or YAML)
   if (grepl("\\.csv$", filename)) {
@@ -1029,37 +1032,51 @@ read_contrasts <-
       formula_vars <- all.vars(as.formula(contrasts$formula[i]))
     }
 
-    design_cols <- unique(na.omit(c(contrasts[[variable_column]][i], blocking_vars, formula_vars)))
-    design_matrix <- samples[, design_cols, drop = FALSE]
-    
-    # Ensure there are no NA values in the design matrix.
-    if (any(is.na(design_matrix))) {
-      stop("NA values found in one or more design matrix columns.")
-    }
-    
-    # Check that the design matrix is full rank.
-    mm <- model.matrix(~ . - 1, data = design_matrix)
-    if (qr(mm)$rank < ncol(mm)) {
-      stop(paste("Design matrix is not full rank.", "Model matrix columns:", paste(colnames(mm), collapse = ", "), "\n"))
-    }
-    
-    # Warn about continuous covariates in the design matrix columns.
-    for (col in design_cols) {
-      if (is.numeric(samples[[col]])) {
-        warning(paste("Column", col, "is numeric and may be treated as continuous."))
+    if (validate_design) {
+      design_cols <- unique(na.omit(c(contrasts[[variable_column]][i], blocking_vars, formula_vars)))
+
+      # Filter samples if exclude columns are specified for this contrast
+      contrast_samples <- samples
+      if ("exclude_samples_col" %in% colnames(contrasts) && "exclude_samples_values" %in% colnames(contrasts)) {
+        if (!is.na(contrasts$exclude_samples_col[i]) && !is.na(contrasts$exclude_samples_values[i])) {
+          exclude_col <- contrasts$exclude_samples_col[i]
+          exclude_vals <- simpleSplit(contrasts$exclude_samples_values[i], ";")
+          contrast_samples <- samples[!samples[[exclude_col]] %in% exclude_vals, , drop = FALSE]
+        }
       }
-    }
-    
-    # Check that values in design matrix columns do not contain disallowed special characters.
-    for (col in design_cols) {
-      vals <- as.character(samples[[col]])
-      for (sc in c("/", "\\\\")) { # Default special characters: c("/", "\\\\")
-        if (any(grepl(sc, vals))) {
-          warning(paste("Column", col, "contains special character", sc, 
-                        "which may cause issues downstream."))
+
+      design_matrix <- contrast_samples[, design_cols, drop = FALSE]
+
+      # Ensure there are no NA values in the design matrix.
+      if (any(is.na(design_matrix))) {
+        stop("NA values found in one or more design matrix columns.")
+      }
+
+      # Check that the design matrix is full rank.
+      mm <- model.matrix(~ . - 1, data = design_matrix)
+      if (qr(mm)$rank < ncol(mm)) {
+        stop(paste("Design matrix is not full rank.", "Model matrix columns:", paste(colnames(mm), collapse = ", "), "\n"))
+      }
+
+      # Warn about continuous covariates in the design matrix columns.
+      for (col in design_cols) {
+        if (is.numeric(samples[[col]])) {
+          warning(paste("Column", col, "is numeric and may be treated as continuous."))
+        }
+      }
+
+      # Check that values in design matrix columns do not contain disallowed special characters.
+      for (col in design_cols) {
+        vals <- as.character(samples[[col]])
+        for (sc in c("/", "\\\\")) { # Default special characters: c("/", "\\\\")
+          if (any(grepl(sc, vals))) {
+            warning(paste("Column", col, "contains special character", sc,
+                          "which may cause issues downstream."))
+          }
         }
       }
     }
+
     var <- contrasts[i, variable_column]
     ref <- contrasts[i, reference_column]
     tgt <- contrasts[i, target_column]
diff --git a/man/read_contrasts.Rd b/man/read_contrasts.Rd
index c4c0e55..3585785 100644
--- a/man/read_contrasts.Rd
+++ b/man/read_contrasts.Rd
@@ -11,7 +11,8 @@ read_contrasts(
   reference_column = "reference",
   target_column = "target",
   blocking_column = "blocking",
-  convert_to_list = FALSE
+  convert_to_list = FALSE,
+  validate_design = TRUE
 )
 }
 \arguments{
@@ -33,10 +34,21 @@ sample sheet variables to be used as blocking factors}
 
 \item{convert_to_list}{Convert output to a list as used internally by
 shinyngs?}
+
+\item{validate_design}{Validate design matrix (check for NAs, full rank,
+numeric columns, special characters)? Set to FALSE to skip these checks.}
 }
 \value{
 output Validated contrasts data frame
 }
 \description{
-Read and validate a contrasts file against sample metadata
+Checks: 
+1. No duplicate contrast IDs. Ensure that the required columns (variable, reference, target) are present.  
+2. Values in the contrast variable column exist as column names in the sample metadata.
+3. If blocking factors are supplied, checks that they are present in the sample metadata.
+4. Design matrix is full rank.
+5. Warn about continuous covariates (e.g. numeric patient IDs treated as continuous).
+6. Values of specified columns don't contain special characters.
+7. Verify that the specified reference and target values exist in the corresponding sample metadata column.  
+8. Issue a warning if the reference and target levels are identical.
 }