test

app.py

@@ -180,62 +180,62 @@ if selected_model == 'Cas9':
                     # Optionally print or log the problematic data for debugging:
                     print(st.session_state['on_target_results'])
 
-                # Initialize Plotly figure
-                fig = go.Figure()
-
-                EXON_BASE = 0  # Base position for exons and CDS on the Y axis
-                EXON_HEIGHT = 0.02  # How 'tall' the exon markers should appear
-
-                # Plot Exons as small markers on the X-axis
-                for exon in st.session_state['exons']:
-                    exon_start, exon_end = exon['start'], exon['end']
-                    fig.add_trace(go.Bar(
-                        x=[(exon_start + exon_end) / 2],
-                        y=[EXON_HEIGHT],
-                        width=[exon_end - exon_start],
-                        base=[EXON_BASE],
-                        marker_color='rgba(128, 0, 128, 0.5)',
-                        name='Exon'
-                    ))
-
-                VERTICAL_GAP = 0.2  # Gap between different ranks
-
-                # Define max and min Y values based on strand and rank
-                MAX_STRAND_Y = 0.1  # Maximum Y value for positive strand results
-                MIN_STRAND_Y = -0.1  # Minimum Y value for negative strand results
-
-                # Iterate over top 5 sorted predictions to create the plot
-                for i, prediction in enumerate(st.session_state['on_target_results'][:5], start=1):  # Only top 5
-                    chrom, start, end, strand, transcript, target, gRNA, Prediction = prediction
-                    midpoint = (int(start) + int(end)) / 2
-
-                    # Vertical position based on rank, modified by strand
-                    y_value = (MAX_STRAND_Y - (i - 1) * VERTICAL_GAP) if strand == '1' else (
-                                MIN_STRAND_Y + (i - 1) * VERTICAL_GAP)
-
-                    fig.add_trace(go.Scatter(
-                        x=[midpoint],
-                        y=[y_value],
-                        mode='markers+text',
-                        marker=dict(symbol='triangle-up' if strand == '1' else 'triangle-down', size=12),
-                        text=f"Rank: {i}",  # Text label
-                        hoverinfo='text',
-                        hovertext=f"Rank: {i}<br>Chromosome: {chrom}<br>Target Sequence: {target}<br>gRNA: {gRNA}<br>Start: {start}<br>End: {end}<br>Strand: {'+' if strand == '1' else '-'}<br>Transcript: {transcript}<br>Prediction: {Prediction:.4f}",
-                    ))
-
-                # Update layout for clarity and interaction
-                fig.update_layout(
-                    title='Top 5 gRNA Sequences by Prediction Score',
-                    xaxis_title='Genomic Position',
-                    yaxis_title='Strand',
-                    yaxis=dict(tickvals=[MAX_STRAND_Y, MIN_STRAND_Y], ticktext=['+', '-']),
-                    # Adjusted to just show strand symbols
-                    showlegend=False,
-                    hovermode='x unified',  # Unified mode for better clarity when hovering
-                )
-
-                # Display the plot
-                st.plotly_chart(fig)
+                # # Initialize Plotly figure
+                # fig = go.Figure()
+                #
+                # EXON_BASE = 0  # Base position for exons and CDS on the Y axis
+                # EXON_HEIGHT = 0.02  # How 'tall' the exon markers should appear
+                #
+                # # Plot Exons as small markers on the X-axis
+                # for exon in st.session_state['exons']:
+                #     exon_start, exon_end = exon['start'], exon['end']
+                #     fig.add_trace(go.Bar(
+                #         x=[(exon_start + exon_end) / 2],
+                #         y=[EXON_HEIGHT],
+                #         width=[exon_end - exon_start],
+                #         base=[EXON_BASE],
+                #         marker_color='rgba(128, 0, 128, 0.5)',
+                #         name='Exon'
+                #     ))
+                #
+                # VERTICAL_GAP = 0.2  # Gap between different ranks
+                #
+                # # Define max and min Y values based on strand and rank
+                # MAX_STRAND_Y = 0.1  # Maximum Y value for positive strand results
+                # MIN_STRAND_Y = -0.1  # Minimum Y value for negative strand results
+                #
+                # # Iterate over top 5 sorted predictions to create the plot
+                # for i, prediction in enumerate(st.session_state['on_target_results'][:5], start=1):  # Only top 5
+                #     chrom, start, end, strand, transcript, Exon, target, gRNA, Prediction = prediction
+                #     midpoint = (int(start) + int(end)) / 2
+                #
+                #     # Vertical position based on rank, modified by strand
+                #     y_value = (MAX_STRAND_Y - (i - 1) * VERTICAL_GAP) if strand == '1' else (
+                #                 MIN_STRAND_Y + (i - 1) * VERTICAL_GAP)
+                #
+                #     fig.add_trace(go.Scatter(
+                #         x=[midpoint],
+                #         y=[y_value],
+                #         mode='markers+text',
+                #         marker=dict(symbol='triangle-up' if strand == '1' else 'triangle-down', size=12),
+                #         text=f"Rank: {i}",  # Text label
+                #         hoverinfo='text',
+                #         hovertext=f"Rank: {i}<br>Chromosome: {chrom}<br>Target Sequence: {target}<br>gRNA: {gRNA}<br>Start: {start}<br>End: {end}<br>Strand: {'+' if strand == '1' else '-'}<br>Transcript: {transcript}<br>Prediction: {Prediction:.4f}",
+                #     ))
+                #
+                # # Update layout for clarity and interaction
+                # fig.update_layout(
+                #     title='Top 5 gRNA Sequences by Prediction Score',
+                #     xaxis_title='Genomic Position',
+                #     yaxis_title='Strand',
+                #     yaxis=dict(tickvals=[MAX_STRAND_Y, MIN_STRAND_Y], ticktext=['+', '-']),
+                #     # Adjusted to just show strand symbols
+                #     showlegend=False,
+                #     hovermode='x unified',  # Unified mode for better clarity when hovering
+                # )
+                #
+                # # Display the plot
+                # st.plotly_chart(fig)
 
                 # if 'gene_sequence' in st.session_state and st.session_state['gene_sequence']:
                 #     gene_symbol = st.session_state['current_gene_symbol']