diff --git a/R/getMDS.R b/R/getMDS.R
index d1c200a51..4d2cd10d6 100644
--- a/R/getMDS.R
+++ b/R/getMDS.R
@@ -17,6 +17,13 @@
 #' difference is that these functions apply microbiome-specific options such
 #' as \code{getDissimilarity} function by default.
 #'
+#' By default \code{scater::calculateMDS} keeps only the \code{ntop = 500}
+#' most variable features. When rarefaction is enabled (\code{niter > 0}) the
+#' sampling depth is evaluated on this filtered matrix, so samples whose depth
+#' falls below the requested \code{sample} are dropped. Pass \code{ntop = Inf}
+#' (or specify \code{subset.row}) if you need to retain all taxa so that the
+#' minimum depth of \code{assay(x, assay.type)} remains reachable.
+#'
 #' See \code{\link[scater:runMDS]{scater::calculateMDS}} for details.
 #'
 #' @return
@@ -40,6 +47,13 @@
 #'     \item \code{subset.result}: \code{Logical result}. Specifies whether to
 #'     subset \code{x} to match the result if some samples were removed during
 #'     calculation. (Default: \code{TRUE})
+#'
+#'     \item \code{ntop}: \code{Numeric scalar}. Forwarded to
+#'     \code{scater::calculateMDS}. Controls how many of the most variable
+#'     features are kept before MDS is run. (Default: \code{500}). Set
+#'     \code{ntop = Inf} (or supply \code{subset.row}) when you need the full
+#'     assay for operations such as rarefaction where absolute library sizes
+#'     matter.
 #' }
 #'
 #' @examples
@@ -60,6 +74,18 @@
 #' # Calculate PCoA with Unifrac and rarefaction. (Note: increase iterations)
 #' tse <- addMDS(tse, method = "unifrac", name = "unifrac_rare", niter = 2L)
 #'
+#' # Disable feature filtering when rarefying at the minimum depth
+#' min_depth <- min(colSums(assay(tse, "counts")))
+#' tse <- addMDS(
+#'     tse,
+#'     assay.type = "counts",
+#'     method = "bray",
+#'     niter = 2L,
+#'     sample = min_depth,
+#'     ntop = Inf
+#' )
+#' reducedDim(tse, "MDS")[1:3, 1:2]
+#'
 #' # Visualize results
 #' p1 <- plotReducedDim(tse, "unifrac", colour_by = "SampleType") +
 #'     labs(title = "Not rarefied")
diff --git a/man/addMDS.Rd b/man/addMDS.Rd
index 85e3b7072..f76412454 100644
--- a/man/addMDS.Rd
+++ b/man/addMDS.Rd
@@ -29,6 +29,13 @@ calculate dissimilarity. (Default: \code{getDissimilarity})
 \if{html}{\out{<div class="sourceCode">}}\preformatted{\\item \code{subset.result}: \code{Logical result}. Specifies whether to
 subset \code{x} to match the result if some samples were removed during
 calculation. (Default: \code{TRUE})
+
+\\item \code{ntop}: \code{Numeric scalar}. Forwarded to
+\code{scater::calculateMDS}. Controls how many of the most variable
+features are kept before MDS is run. (Default: \code{500}). Set
+\code{ntop = Inf} (or supply \code{subset.row}) when you need the full
+assay for operations such as rarefaction where absolute library sizes
+matter.
 }\if{html}{\out{</div>}}
 
 }}
@@ -57,6 +64,13 @@ returns the results, \code{addMDS} adds them to \code{reducedDim(x)}. The
 difference is that these functions apply microbiome-specific options such
 as \code{getDissimilarity} function by default.
 
+By default \code{scater::calculateMDS} keeps only the \code{ntop = 500}
+most variable features. When rarefaction is enabled (\code{niter > 0}) the
+sampling depth is evaluated on this filtered matrix, so samples whose depth
+falls below the requested \code{sample} are dropped. Pass \code{ntop = Inf}
+(or specify \code{subset.row}) if you need to retain all taxa so that the
+minimum depth of \code{assay(x, assay.type)} remains reachable.
+
 See \code{\link[scater:runMDS]{scater::calculateMDS}} for details.
 }
 \examples{
@@ -77,6 +91,18 @@ tse <- addMDS(tse, method = "unifrac", name = "unifrac")
 # Calculate PCoA with Unifrac and rarefaction. (Note: increase iterations)
 tse <- addMDS(tse, method = "unifrac", name = "unifrac_rare", niter = 2L)
 
+# Disable feature filtering when rarefying at the minimum depth
+min_depth <- min(colSums(assay(tse, "counts")))
+tse <- addMDS(
+    tse,
+    assay.type = "counts",
+    method = "bray",
+    niter = 2L,
+    sample = min_depth,
+    ntop = Inf
+)
+reducedDim(tse, "MDS")[1:3, 1:2]
+
 # Visualize results
 p1 <- plotReducedDim(tse, "unifrac", colour_by = "SampleType") +
     labs(title = "Not rarefied")