add plot

app.py

@@ -4,7 +4,7 @@ import cas9on
 import cas9off
 import pandas as pd
 import streamlit as st
-from pygenomeviz import GenomeViz
+from pygenomeviz import Genbank, GenomeViz
 import numpy as np
 from pathlib import Path
 
@@ -96,8 +96,10 @@ if selected_model == 'Cas9':
     if target_selection == 'on-target':
         # Gene symbol entry
         gene_symbol = st.text_input('Enter a Gene Symbol:', key='gene_symbol')
+
         # Prediction button
         predict_button = st.button('Predict on-target')
+
         # Process predictions
         if predict_button and gene_symbol:
             predictions, gene_sequence = cas9on.process_gene(gene_symbol, cas9on_path)
@@ -108,8 +110,7 @@ if selected_model == 'Cas9':
                 df = pd.DataFrame(st.session_state['on_target_results'],
                                   columns=["Gene ID", "Start Pos", "End Pos", "Strand", "gRNA", "Prediction"])
 
-                # Make sure gene_sequence is defined before this point
-                if gene_sequence:  # Add a check to ensure gene_sequence is not empty
+                if gene_sequence:  # Ensure gene_sequence is not empty
                     genbank_file_path = f"{gene_symbol}_crispr_targets.gb"
                     cas9on.generate_genbank_file_from_df(df, gene_sequence, gene_symbol, genbank_file_path)
                     st.write('Top on-target predictions:')
@@ -123,7 +124,23 @@ if selected_model == 'Cas9':
                             file_name=genbank_file_path,
                             mime="text/x-genbank"
                         )
-            os.remove(genbank_file_path)
+
+                    # Visualize the GenBank file using pyGenomeViz
+                    gv = GenomeViz(
+                        feature_track_ratio=0.3,
+                        tick_track_ratio=0.5,
+                        tick_style="axis",
+                    )
+
+                    gbk = Genbank(genbank_file_path)
+                    track = gv.add_feature_track(gbk.name, gbk.range_size)
+                    track.add_genbank_features(gbk)
+
+                    fig = gv.plotfig()
+                    st.pyplot(fig)
+
+                    # Clean up the GenBank file after visualization
+                    os.remove(genbank_file_path)
 
     elif target_selection == 'off-target':
         ENTRY_METHODS = dict(