Spaces:
Sleeping
Sleeping
Commit
•
dd69d15
1
Parent(s):
cb692e5
fixed
Browse files
app.py
CHANGED
@@ -92,43 +92,31 @@ if selected_model == 'Cas9':
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# Actions based on the selected enzyme
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if target_selection == 'on-target':
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# app initialization for Cas9 on-target
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if 'gene_symbol' not in st.session_state:
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st.session_state.gene_symbol = None
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if 'on_target_results' not in st.session_state:
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st.session_state.on_target_results = None
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# Gene symbol entry
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st.text_input(
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mime='text/csv'
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)
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else:
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st.write('No significant on-target effects detected!')
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else:
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on_target_results.empty()
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elif target_selection == 'off-target':
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ENTRY_METHODS = dict(
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# Actions based on the selected enzyme
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if target_selection == 'on-target':
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# Gene symbol entry
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gene_symbol = st.text_input('Enter a Gene Symbol:', key='gene_symbol')
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# Prediction button
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predict_button = st.button('Predict on-target')
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# Process predictions
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if predict_button and gene_symbol:
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predictions = cas9on.process_gene(gene_symbol, cas9on_path)
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# Store only first 10 for display and save full predictions for download
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st.session_state['on_target_results'] = predictions[:10]
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st.session_state['full_on_target_results'] = predictions
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# On-target results display
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if 'on_target_results' in st.session_state and st.session_state['on_target_results']:
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st.write('On-target predictions:', st.session_state['on_target_results'])
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if 'full_on_target_results' in st.session_state:
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# Provide a download button for the full results
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full_predictions_csv = cas9on.convert_df(st.session_state['full_on_target_results'])
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st.download_button(
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label='Download on-target predictions',
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data=full_predictions_csv,
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file_name='on_target_results.csv',
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mime='text/csv'
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)
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elif target_selection == 'off-target':
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ENTRY_METHODS = dict(
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