diff --git a/planet/models/coexpression_clusters.py b/planet/models/coexpression_clusters.py
index 5f74aa9..0038737 100644
--- a/planet/models/coexpression_clusters.py
+++ b/planet/models/coexpression_clusters.py
@@ -8,6 +8,7 @@
 
 from utils.enrichment import hypergeo_sf, fdr_correction
 from utils.benchmark import benchmark
+from utils.jaccard import jaccard
 
 from sqlalchemy import join
 from sqlalchemy.orm import joinedload, load_only
@@ -195,7 +196,7 @@ def calculate_enrichment(empty=True):
 
     @staticmethod
     @benchmark
-    def calculate_similarities(gene_family_method_id=1):
+    def calculate_similarities(gene_family_method_id=1, percentile_pass=0.95):
 
         # sqlalchemy to fetch cluster associations
         fields = [SequenceCoexpressionClusterAssociation.__table__.c.sequence_id,
@@ -225,5 +226,28 @@ def calculate_similarities(gene_family_method_id=1):
             if len(families) > 0:
                 cluster_to_families[cluster_id] = families
 
-        for c, f in cluster_to_families.items():
-            print(c,f)
\ No newline at end of file
+        keys = list(cluster_to_families.keys())
+
+        data = []
+
+        for i in range(len(keys) - 1):
+            for j in range(i+1, len(keys)):
+                current_keys = [keys[x] for x in [i, j]]
+                current_families = [cluster_to_families[k] for k in current_keys]
+
+                if len(current_families[0]) > 4 and len(current_families[1]) > 4:
+                    j = jaccard(current_families[0], current_families[1])
+                    data.append([current_keys[0], current_keys[1], j])
+
+        ordered_j = sorted([a[2] for a in data])
+        percentile_cutoff = ordered_j[int(len(ordered_j)*percentile_pass)]
+
+        database = [{'source_id': d[0],
+                     'target_id': d[1],
+                     'gene_family_method_id': gene_family_method_id,
+                     'jaccard_index': d[2],
+                     'p_value': 0,
+                     'corrected_p_value': 0} for d in data if d[2] >= percentile_cutoff]
+
+        db.engine.execute(CoexpressionClusterSimilarity.__table__.insert(), database)
+
diff --git a/utils/jaccard.py b/utils/jaccard.py
index ced1a85..d63b046 100644
--- a/utils/jaccard.py
+++ b/utils/jaccard.py
@@ -11,3 +11,4 @@ def jaccard(list_a, list_b):
     intersection_count = len(set(list_a).intersection(set(list_b)))
 
     return intersection_count/union_count
+