fix cas12

app.py

@@ -325,7 +325,7 @@ elif selected_model == 'Cas12':
         # Visualization and file generation
         if 'on_target_results' in st.session_state and st.session_state['on_target_results']:
             df = pd.DataFrame(st.session_state['on_target_results'],
-                              columns=["Gene ID", "Start Pos", "End Pos", "Strand", "gRNA", "Prediction"])
+                              columns=["Gene ID", "Start Pos", "End Pos", "Strand", "Target", "gRNA", "Prediction"])
 
             # Now create a Plotly plot with the sorted_predictions
             fig = go.Figure()
@@ -333,7 +333,7 @@ elif selected_model == 'Cas12':
             # Iterate over the sorted predictions to create the plot
             for i, prediction in enumerate(sorted_predictions, start=1):
                 # Extract data for plotting
-                chrom, start, end, strand, gRNA, pred_score = prediction
+                chrom, start, end, strand, Target, gRNA, pred_score = prediction
                 # Strand is not used in this plot, but you could use it to determine marker symbol, for example
                 fig.add_trace(go.Scatter(
                     x=[start, end],
@@ -343,7 +343,7 @@ elif selected_model == 'Cas12':
                     text=[f"Rank: {i}", ""],  # Text at the start position only
                     hoverinfo='text',
                     hovertext=[
-                        f"Rank: {i}<br>Chromosome: {chrom}<br>Target: {gRNA}<br>Start: {start}<br>End: {end}<br>Strand: {'+' if strand == 1 else '-'}<br>Prediction Score: {pred_score:.4f}",
+                        f"Rank: {i}<br>Chromosome: {chrom}<br>Target: {Target}<br>Start: {start}<br>End: {end}<br>Strand: {'+' if strand == 1 else '-'}<br>Prediction Score: {pred_score:.4f}",
                         ""
                     ],
                 ))