diff --git a/starfish/test/full_pipelines/api/test_dartfish.py b/starfish/test/full_pipelines/api/test_dartfish.py
index aa4cf0a0..6234d0fc 100644
--- a/starfish/test/full_pipelines/api/test_dartfish.py
+++ b/starfish/test/full_pipelines/api/test_dartfish.py
@@ -179,7 +179,8 @@ def test_dartfish_pipeline_cropped_data(tmpdir):
     cnts_starfish.rename(columns={'target': 'gene', 'area': 'cnt_starfish'}, inplace=True)
 
     # get top 5 genes and verify they are correct
-    high_expression_genes = cnts_starfish.sort_values('cnt_starfish', ascending=False).head(5)
+    high_expression_genes = cnts_starfish.sort_values('cnt_starfish', ascending=False,
+                                                      kind='stable').head(5)
 
     assert np.array_equal(
         high_expression_genes['cnt_starfish'].values,
@@ -187,7 +188,7 @@ def test_dartfish_pipeline_cropped_data(tmpdir):
     )
     assert np.array_equal(
         high_expression_genes['gene'].values,
-        ['MBP', 'MOBP', 'ADCY8', 'TRIM66', 'SYT6']
+        ['MBP', 'MOBP', 'ADCY8', 'SYT6', 'TRIM66']
     )
 
     # verify correlation is accurate for this subset of the image
diff --git a/starfish/test/full_pipelines/api/test_merfish.py b/starfish/test/full_pipelines/api/test_merfish.py
index f6d2362e..df344a6c 100644
--- a/starfish/test/full_pipelines/api/test_merfish.py
+++ b/starfish/test/full_pipelines/api/test_merfish.py
@@ -236,12 +236,12 @@ def test_merfish_pipeline_cropped_data():
         spot_intensities[Features.PASSES_THRESHOLDS], drop=True
     )
     genes, counts = np.unique(spot_intensities_passing_filters[Features.TARGET], return_counts=True)
-    result_counts = pd.Series(counts, index=genes).sort_values(ascending=False)[:5]
+    result_counts = pd.Series(counts, index=genes).sort_values(ascending=False, kind='stable')[:5]
 
     # assert that number of high-expression detected genes are correct
     expected_counts = pd.Series(
         [107, 59, 46, 32, 32],
-        index=('MALAT1', 'SRRM2', 'FASN', 'IGF2R', 'TLN1')
+        index=('MALAT1', 'SRRM2', 'FASN', 'TLN1', 'IGF2R')
     )
     assert np.array_equal(
         expected_counts.values,