fix

app.py

@@ -214,7 +214,8 @@ if selected_model == 'Cas9':
                 # Iterate over the sorted predictions to create the plot
                 for i, prediction in enumerate(st.session_state['on_target_results'], start=1):
                     chrom, start, end, strand, target, gRNA, pred_score = prediction
-                    midpoint = (start + end) / 2
+
+                    midpoint = (int(start) + int(end)) / 2
                     y_value = i * 0.1 if strand == '1' else -i * 0.1  # Adjust multiplier for spacing
 
                     fig.add_trace(go.Scatter(