diff --git a/R/annotate_sce.R b/R/annotate_sce.R
index aa0a931..52273a5 100644
--- a/R/annotate_sce.R
+++ b/R/annotate_sce.R
@@ -44,6 +44,9 @@
 #' @param max_features the maximum number of features per cell or "adaptive"
 #' @param max_mito the maximum proportion of counts mapping to
 #'   mitochondrial genes (0 - 1) or "adaptive"
+#' @param type_mito see [scater::isOutlier()]. By default, both ends of the
+#'   distribution of mitochondrial content will be tested for outliers. If using
+#'   single-nucleus RNA-sequencing data, consider setting this to "higher".
 #' @param min_ribo the minimum proportion of counts mapping to
 #'   ribosomal genes (0 - 1)
 #' @param max_ribo the maximum proportion of counts mapping to
@@ -79,6 +82,7 @@ annotate_sce <- function(sce,
                          min_features = 100,
                          max_features = "adaptive",
                          max_mito = "adaptive",
+                         type_mito = "both",
                          min_ribo = 0.00,
                          max_ribo = 1.00,
                          min_counts = 2,
@@ -135,6 +139,7 @@ annotate_sce <- function(sce,
       min_features = min_features,
       max_features = max_features,
       max_mito = max_mito,
+      type_mito = type_mito,
       min_ribo = min_ribo,
       max_ribo = max_ribo,
       min_counts = min_counts,
diff --git a/R/annotate_sce_cells.R b/R/annotate_sce_cells.R
index 86d655d..98d08cb 100644
--- a/R/annotate_sce_cells.R
+++ b/R/annotate_sce_cells.R
@@ -13,6 +13,8 @@
 #'   number of genes with >0 counts)
 #' max_mito the maximum proportion of counts mapping to
 #'   mitochondrial genes (0 - 1)
+#' type_mito choice indicating whether outliers in pc_mito should be looked for
+#'   at both tails, or only at the lower/higher end
 #' min_ribo
 #' max_ribo the maximum proportion of counts mapping to
 #'   ribosomal genes (0 - 1)
@@ -86,7 +88,7 @@ annotate_sce_cells <- function(sce, ...) {
       sce$pc_mito,
       nmads = args$nmads,
       subset = sce$qc_metric_passed,
-      type = "both",
+      type = args$type_mito,
       log = FALSE)
     higher <-
       as.numeric(attributes(outliers)$thresholds["higher"]) #not int for pcmito
diff --git a/man/annotate_sce.Rd b/man/annotate_sce.Rd
index 1301d54..6851432 100644
--- a/man/annotate_sce.Rd
+++ b/man/annotate_sce.Rd
@@ -11,6 +11,7 @@ annotate_sce(
   min_features = 100,
   max_features = "adaptive",
   max_mito = "adaptive",
+  type_mito = "both",
   min_ribo = 0,
   max_ribo = 1,
   min_counts = 2,
@@ -40,6 +41,10 @@ number of genes with >0 counts)}
 \item{max_mito}{the maximum proportion of counts mapping to
 mitochondrial genes (0 - 1) or "adaptive"}
 
+\item{type_mito}{see \code{\link[scater:reexports]{scater::isOutlier()}}. By default, both ends of the
+distribution of mitochondrial content will be tested for outliers. If using
+single-nucleus RNA-sequencing data, consider setting this to "higher".}
+
 \item{min_ribo}{the minimum proportion of counts mapping to
 ribosomal genes (0 - 1)}
 
diff --git a/man/annotate_sce_cells.Rd b/man/annotate_sce_cells.Rd
index a7dde8d..f1077dd 100644
--- a/man/annotate_sce_cells.Rd
+++ b/man/annotate_sce_cells.Rd
@@ -16,6 +16,8 @@ min_features the minimum number of features per cell (i.e. the minimum
 number of genes with >0 counts)
 max_mito the maximum proportion of counts mapping to
 mitochondrial genes (0 - 1)
+type_mito choice indicating whether outliers in pc_mito should be looked for
+at both tails, or only at the lower/higher end
 min_ribo
 max_ribo the maximum proportion of counts mapping to
 ribosomal genes (0 - 1)