diff --git a/Orange/widgets/visualize/owheatmap.py b/Orange/widgets/visualize/owheatmap.py
index a51c747a1d4..7228d910e6e 100644
--- a/Orange/widgets/visualize/owheatmap.py
+++ b/Orange/widgets/visualize/owheatmap.py
@@ -662,8 +662,8 @@ def is_variable(obj):
 
         self.update_heatmaps()
         if data is not None and self.__pending_selection is not None:
-            assert self.scene.widget is not None
-            self.scene.widget.selectRows(self.__pending_selection)
+            if self.scene.widget is not None:
+                self.scene.widget.selectRows(self.__pending_selection)
             self.selected_rows = self.__pending_selection
             self.__pending_selection = None
 
diff --git a/Orange/widgets/visualize/tests/test_owheatmap.py b/Orange/widgets/visualize/tests/test_owheatmap.py
index c61075f77dd..cd0a3c246e1 100644
--- a/Orange/widgets/visualize/tests/test_owheatmap.py
+++ b/Orange/widgets/visualize/tests/test_owheatmap.py
@@ -205,6 +205,20 @@ def test_saved_selection(self):
         self.send_signal(w.Inputs.data, iris, widget=w)
         self.assertEqual(len(self.get_output(w.Outputs.selected_data)), 21)
 
+    def test_saved_selection_when_not_possible(self):
+        # Has stored selection but ot enough columns for clustering.
+        iris = Table("iris")[:, ["petal width"]]
+        w = self.create_widget(
+            OWHeatMap, stored_settings={
+                "__version__": 3,
+                "col_clustering_method": "Clustering",
+                "selected_rows": [1, 2, 3],
+            }
+        )
+        self.send_signal(w.Inputs.data, iris)
+        out = self.get_output(w.Outputs.selected_data)
+        self.assertSequenceEqual(list(out.ids), list(iris.ids[[1, 2, 3]]))
+
     def test_set_split_var(self):
         data = self.brown_selected[::3]
         w = self.widget