diff --git a/R/methods.R b/R/methods.R
index f03fea94..4bf025e5 100755
--- a/R/methods.R
+++ b/R/methods.R
@@ -586,19 +586,25 @@ setMethod("scale_abundance", "tidybulk", .scale_abundance)
 #' @param .sample The name of the sample column
 #' @param .transcript The name of the transcript/gene column
 #' @param .abundance The name of the transcript/gene abundance column
-#' @param method A character string. Either "limma_normalize_quantiles" for limma::normalizeQuantiles or "preprocesscore_normalize_quantiles_use_target" for preprocessCore::normalize.quantiles.use.target for large-scale dataset, where limmma could not be compatible.
+#' @param method A character string. Either "limma_normalize_quantiles" for limma::normalizeQuantiles or "preprocesscore_normalize_quantiles_use_target" for preprocessCore::normalize.quantiles.use.target for large-scale datasets.
+#' @param target_distribution A numeric vector. If NULL the target distribution will be calculated by preprocessCore. This argument only affects the "preprocesscore_normalize_quantiles_use_target" method.
 #' @param action A character string between "add" (default) and "only". "add" joins the new information to the input tbl (default), "only" return a non-redundant tbl with the just new information.
 #'
 #'
-#' @details Scales transcript abundance compensating for sequencing depth
-#' (e.g., with TMM algorithm, Robinson and Oshlack doi.org/10.1186/gb-2010-11-3-r25).
-#' Lowly transcribed transcripts/genes (defined with minimum_counts and minimum_proportion parameters)
-#' are filtered out from the scaling procedure.
-#' The scaling inference is then applied back to all unfiltered data.
+#' @details Tranform the feature abundance across samples so to have the same quantile distribution (using preprocessCore).
 #'
 #' Underlying method
-#' edgeR::calcNormFactors(.data, method = c("TMM","TMMwsp","RLE","upperquartile"))
-#'
+#' 
+#' If `limma_normalize_quantiles` is chosen
+#' 
+#' .data |>limma::normalizeQuantiles()
+#'  
+#'  If `preprocesscore_normalize_quantiles_use_target` is chosen
+#'  
+#' .data |> 
+#'    preprocessCore::normalize.quantiles.use.target(
+#'       target = preprocessCore::normalize.quantiles.determine.target(.data)
+#'    )
 #'
 #'
 #' @return A tbl object with additional columns with scaled data as `<NAME OF COUNT COLUMN>_scaled`
@@ -621,6 +627,7 @@ setGeneric("quantile_normalise_abundance", function(.data,
                                                     .transcript = NULL,
                                                     .abundance = NULL,
                                                     method = "limma_normalize_quantiles",
+                                                    target_distribution = NULL,
                                                     action = "add")
   standardGeneric("quantile_normalise_abundance"))
 
@@ -630,6 +637,8 @@ setGeneric("quantile_normalise_abundance", function(.data,
                                           .transcript = NULL,
                                           .abundance = NULL,
                                           method = "limma_normalize_quantiles",
+                                          target_distribution = NULL,
+                                          
                                           action = "add")
 {
 
@@ -685,10 +694,12 @@ setGeneric("quantile_normalise_abundance", function(.data,
       BiocManager::install("preprocessCore", ask = FALSE)
     }
 
+    if(is.null(target_distribution)) target_distribution = preprocessCore::normalize.quantiles.determine.target(.data_norm)
+    
     .data_norm_quant =
       .data_norm |>
       preprocessCore::normalize.quantiles.use.target(
-        target = preprocessCore::normalize.quantiles.determine.target(.data_norm)
+        target = target_distribution
       )
 
     colnames(.data_norm_quant) = .data_norm |> colnames()
diff --git a/R/methods_SE.R b/R/methods_SE.R
index 8aa478b5..89edcddf 100755
--- a/R/methods_SE.R
+++ b/R/methods_SE.R
@@ -248,6 +248,7 @@ setMethod("scale_abundance",
                                .transcript = NULL,
                                .abundance = NULL,
                                method = "limma_normalize_quantiles",
+                               target_distribution = NULL,
                                action = NULL) {
 
 
@@ -311,10 +312,12 @@ setMethod("scale_abundance",
       assay(my_assay) |>
       as.matrix()
 
+    if(is.null(target_distribution)) target_distribution = preprocessCore::normalize.quantiles.determine.target(.data_norm)
+    
     .data_norm =
       .data_norm |>
       preprocessCore::normalize.quantiles.use.target(
-        target = preprocessCore::normalize.quantiles.determine.target(.data_norm)
+        target = target_distribution
       )
 
     colnames(.data_norm) = .data |> assay(my_assay) |> colnames()
diff --git a/man/quantile_normalise_abundance-methods.Rd b/man/quantile_normalise_abundance-methods.Rd
index fdaf6e46..5c527cd8 100644
--- a/man/quantile_normalise_abundance-methods.Rd
+++ b/man/quantile_normalise_abundance-methods.Rd
@@ -16,6 +16,7 @@ quantile_normalise_abundance(
   .transcript = NULL,
   .abundance = NULL,
   method = "limma_normalize_quantiles",
+  target_distribution = NULL,
   action = "add"
 )
 
@@ -25,6 +26,7 @@ quantile_normalise_abundance(
   .transcript = NULL,
   .abundance = NULL,
   method = "limma_normalize_quantiles",
+  target_distribution = NULL,
   action = "add"
 )
 
@@ -34,6 +36,7 @@ quantile_normalise_abundance(
   .transcript = NULL,
   .abundance = NULL,
   method = "limma_normalize_quantiles",
+  target_distribution = NULL,
   action = "add"
 )
 
@@ -43,6 +46,7 @@ quantile_normalise_abundance(
   .transcript = NULL,
   .abundance = NULL,
   method = "limma_normalize_quantiles",
+  target_distribution = NULL,
   action = "add"
 )
 
@@ -52,6 +56,7 @@ quantile_normalise_abundance(
   .transcript = NULL,
   .abundance = NULL,
   method = "limma_normalize_quantiles",
+  target_distribution = NULL,
   action = NULL
 )
 
@@ -61,6 +66,7 @@ quantile_normalise_abundance(
   .transcript = NULL,
   .abundance = NULL,
   method = "limma_normalize_quantiles",
+  target_distribution = NULL,
   action = NULL
 )
 }
@@ -73,7 +79,9 @@ quantile_normalise_abundance(
 
 \item{.abundance}{The name of the transcript/gene abundance column}
 
-\item{method}{A character string. Either "limma_normalize_quantiles" for limma::normalizeQuantiles or "preprocesscore_normalize_quantiles_use_target" for preprocessCore::normalize.quantiles.use.target for large-scale dataset, where limmma could not be compatible.}
+\item{method}{A character string. Either "limma_normalize_quantiles" for limma::normalizeQuantiles or "preprocesscore_normalize_quantiles_use_target" for preprocessCore::normalize.quantiles.use.target for large-scale datasets.}
+
+\item{target_distribution}{A numeric vector. If NULL the target distribution will be calculated by preprocessCore. This argument only affects the "preprocesscore_normalize_quantiles_use_target" method.}
 
 \item{action}{A character string between "add" (default) and "only". "add" joins the new information to the input tbl (default), "only" return a non-redundant tbl with the just new information.}
 }
@@ -96,14 +104,20 @@ quantile_normalise_abundance() takes as input A `tbl` (with at least three colum
 \details{
 `r lifecycle::badge("maturing")`
 
-Scales transcript abundance compensating for sequencing depth
-(e.g., with TMM algorithm, Robinson and Oshlack doi.org/10.1186/gb-2010-11-3-r25).
-Lowly transcribed transcripts/genes (defined with minimum_counts and minimum_proportion parameters)
-are filtered out from the scaling procedure.
-The scaling inference is then applied back to all unfiltered data.
+Tranform the feature abundance across samples so to have the same quantile distribution (using preprocessCore).
 
 Underlying method
-edgeR::calcNormFactors(.data, method = c("TMM","TMMwsp","RLE","upperquartile"))
+
+If `limma_normalize_quantiles` is chosen
+
+.data |>limma::normalizeQuantiles()
+ 
+ If `preprocesscore_normalize_quantiles_use_target` is chosen
+ 
+.data |> 
+   preprocessCore::normalize.quantiles.use.target(
+      target = preprocessCore::normalize.quantiles.determine.target(.data)
+   )
 }
 \examples{
 
diff --git a/tests/testthat/test-bulk_methods_SummarizedExperiment.R b/tests/testthat/test-bulk_methods_SummarizedExperiment.R
index 26df1262..3f9ed97e 100755
--- a/tests/testthat/test-bulk_methods_SummarizedExperiment.R
+++ b/tests/testthat/test-bulk_methods_SummarizedExperiment.R
@@ -105,7 +105,21 @@ test_that("quantile normalisation",{
           filter(a=="SRR1740035" & b=="ABCB9") |>
           dplyr::pull(c_scaled)
       )
-
+    
+    target_distribution = 
+      se_mini |> 
+      assay( "count") |> 
+      as.matrix() |> 
+      preprocessCore::normalize.quantiles.determine.target() 
+
+    se_mini |> 
+      quantile_normalise_abundance(
+        method = "preprocesscore_normalize_quantiles_use_target", 
+        target_distribution = target_distribution
+      ) |> 
+      expect_no_error()
+    
+    
 })
 
 test_that("tidybulk SummarizedExperiment normalisation subset",{