diff --git a/libclusterseq/libclusterseq.py b/libclusterseq/libclusterseq.py
index f0b1a69f69fc362c61fd195ed30e1d961a500085..ba663b0a71eaae7e6dd8f466f2b5c1970e3f81f3 100644
--- a/libclusterseq/libclusterseq.py
+++ b/libclusterseq/libclusterseq.py
@@ -200,11 +200,18 @@ def plot_score_density(scores, min_density_score, axis):
     # (maybe not the same one as obtained using scipy.stats.gaussian_kde)
     # rug=True plots small lines where a value exits
     # his=False disables default plotting of a histogram
-    if len(scores) < 100:
-        sns.distplot(scores, kde=True, rug=True, hist=False, ax=axis)
-    else:
-        # Figure too heavy when lots of rug lines
-        sns.distplot(scores, kde=True, rug=False, hist=False, ax=axis)
+    try:
+        if len(scores) < 100:
+            sns.distplot(scores, kde=True, rug=True, hist=False, ax=axis)
+        else:
+            # Figure too heavy when lots of rug lines
+            sns.distplot(scores, kde=True, rug=False, hist=False, ax=axis)
+    except RuntimeError as err:
+        if str(err) == "Selected KDE bandwidth is 0. Cannot estiamte density.":
+            logging.warn("%s\n" % str(err))
+            sns.distplot(scores, kde=False, rug=False, hist=True, ax=axis)
+        else:
+            raise
     # Vertical bar at min_density_score,
     # indicating the estimated score of minimal density
     # which will be used as threshold to cut edges in the graph.
@@ -225,7 +232,7 @@ def make_sequence_similarity_groups(in_fname, cell_dir):
     """
     (score_graph, complete_graph) = build_similarity_graph(in_fname)
     if len(score_graph.nodes()) <= 2:
-        logging.debug(
+        logging.info(
             "Not enough sequences to make interesting groups for %s",
             in_fname)
         # TODO: Use percent similarity between the 2 sequences
@@ -258,7 +265,7 @@ def make_sequence_similarity_groups(in_fname, cell_dir):
     plot_score_density(scores, min_density_score, axis)
     plt.savefig(out_plot)
     plt.close(fig)
-    logging.debug("Similarity score distribution plot: see %s", out_plot)
+    logging.info("Similarity score distribution plot: see %s", out_plot)
     #######################
     # Splitting the graph #
     #######################
@@ -301,6 +308,7 @@ def split_fasta(in_fname, cell_id, cell_dir):
     logging.info("split_fasta: Creating %s", cell_dir)
     cell_dir.mkdir(parents=True, exist_ok=True)
     split_graph = make_sequence_similarity_groups(in_fname, cell_dir)
+    logging.info("Made sequence similarity groups for %s", cell_id)
 
     def compute_seq_num(node_set):
         """