Spaces:
Running
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supercat666
commited on
Commit
•
e9b9cc0
1
Parent(s):
4527ffd
fix
Browse files
app.py
CHANGED
@@ -119,6 +119,16 @@ if selected_model == 'Cas9':
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df = pd.DataFrame(st.session_state['on_target_results'],
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columns=["Gene ID", "Start Pos", "End Pos", "Strand", "Target", "gRNA", "Prediction"])
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st.dataframe(df)
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# Now create a Plotly plot with the sorted_predictions
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fig = go.Figure()
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@@ -174,42 +184,28 @@ if selected_model == 'Cas9':
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),
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showlegend=False # Hide the legend if it's not necessary
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)
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# Display the plot
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st.plotly_chart(fig)
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if 'gene_sequence' in st.session_state and st.session_state['gene_sequence']:
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gene_sequence = st.session_state['gene_sequence']
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# Define file paths
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genbank_file_path = f"{gene_symbol}_crispr_targets.gb"
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bed_file_path = f"{gene_symbol}_crispr_targets.bed"
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csv_file_path = f"{gene_symbol}_crispr_predictions.csv"
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# Generate files
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cas9on.generate_genbank_file_from_df(df, gene_sequence, gene_symbol, genbank_file_path)
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cas9on.create_bed_file_from_df(df, bed_file_path)
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cas9on.create_csv_from_df(df, csv_file_path)
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# Layout for download buttons
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col1, col2, col3 = st.columns(3)
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with col1:
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with open(genbank_file_path, "rb") as file:
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st.download_button(label="Download GenBank File", data=file, file_name=genbank_file_path,
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mime="text/x-genbank")
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with col2:
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with open(bed_file_path, "rb") as file:
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st.download_button(label="Download BED File", data=file, file_name=bed_file_path,
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mime="text/plain")
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with col3:
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with open(csv_file_path, "rb") as file:
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st.download_button(label="Download CSV File", data=file, file_name=csv_file_path,
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mime="text/csv")
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# Links for user guidance on using the downloaded files
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st.markdown(
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"GenBank files can be visualized using [PyGenomeViz](https://pygenomeviz.streamlit.app/). "
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"BED files can be used with the [UCSC Genome Browser](https://genome.ucsc.edu/cgi-bin/hgCustom).")
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elif target_selection == 'off-target':
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ENTRY_METHODS = dict(
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df = pd.DataFrame(st.session_state['on_target_results'],
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columns=["Gene ID", "Start Pos", "End Pos", "Strand", "Target", "gRNA", "Prediction"])
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st.dataframe(df)
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# Define file paths
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genbank_file_path = f"{gene_symbol}_crispr_targets.gb"
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bed_file_path = f"{gene_symbol}_crispr_targets.bed"
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csv_file_path = f"{gene_symbol}_crispr_predictions.csv"
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# Generate files
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cas9on.generate_genbank_file_from_df(df, gene_sequence, gene_symbol, genbank_file_path)
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cas9on.create_bed_file_from_df(df, bed_file_path)
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cas9on.create_csv_from_df(df, csv_file_path)
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# Now create a Plotly plot with the sorted_predictions
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fig = go.Figure()
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),
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showlegend=False # Hide the legend if it's not necessary
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)
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# Display the plot
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st.plotly_chart(fig)
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# Download buttons
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col1, col2, col3 = st.columns(3)
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with col1:
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with open(genbank_file_path, "rb") as file:
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st.download_button(label="Download GenBank File", data=file, file_name=genbank_file_path,
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mime="text/x-genbank")
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with col2:
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with open(bed_file_path, "rb") as file:
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st.download_button(label="Download BED File", data=file, file_name=bed_file_path,
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mime="text/plain")
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with col3:
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with open(csv_file_path, "rb") as file:
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st.download_button(label="Download CSV File", data=file, file_name=csv_file_path,
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mime="text/csv")
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# Links for user guidance on using the downloaded files
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st.markdown(
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"GenBank files can be visualized using [PyGenomeViz](https://pygenomeviz.streamlit.app/). "
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"BED files can be used with the [UCSC Genome Browser](https://genome.ucsc.edu/cgi-bin/hgCustom).")
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elif target_selection == 'off-target':
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ENTRY_METHODS = dict(
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