fixed bugs

app.py

@@ -136,33 +136,36 @@ if selected_model == 'Cas9':
                 # Now create a Plotly plot with the sorted_predictions
                 fig = go.Figure()
 
-                # Variables to initialize the y position for the positive and negative strands
-                positive_strand_y = 1
-                negative_strand_y = -1
+                # Initialize the y position for the positive and negative strands
+                positive_strand_y = 0.1
+                negative_strand_y = -0.1
+
+                # Use an offset to spread gRNA sequences vertically
+                offset = 0.05
 
                 # 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, target, gRNA, pred_score = prediction
                     # Set the y-value and arrow symbol based on the strand
-                    if strand == 1:
+                    if strand == '1':
                         y_value = positive_strand_y
                         arrow_symbol = 'triangle-right'
-                        positive_strand_y += 0.1  # Increment the y-value for the next positive strand gRNA
+                        positive_strand_y += offset  # Increment the y-value for the next positive strand gRNA
                     else:
                         y_value = negative_strand_y
                         arrow_symbol = 'triangle-left'
-                        negative_strand_y -= 0.1  # Decrement the y-value for the next negative strand gRNA
+                        negative_strand_y -= offset  # Decrement the y-value for the next negative strand gRNA
 
                     fig.add_trace(go.Scatter(
-                        x=[start, end],
-                        y=[y_value, y_value],  # Use the y_value set above for the strand
-                        mode='lines+markers+text',
+                        x=[(start + end) / 2],  # Place the marker at the midpoint of the start and end
+                        y=[y_value],  # Use the y_value set above for the strand
+                        mode='markers+text',
                         marker=dict(symbol=arrow_symbol, size=10),
                         name=f"gRNA: {gRNA}",
-                        text=[f"Rank: {i}", ""],  # Text at the first point
+                        text=f"Rank: {i}",  # Place text at the marker
                         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>Prediction Score: {pred_score:.4f}",
+                        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>Prediction Score: {pred_score:.4f}",
                     ))
 
                 # Update the layout of the plot
@@ -366,33 +369,36 @@ elif selected_model == 'Cas12':
             # Now create a Plotly plot with the sorted_predictions
             fig = go.Figure()
 
-            # Variables to initialize the y position for the positive and negative strands
-            positive_strand_y = 1
-            negative_strand_y = -1
+            # Initialize the y position for the positive and negative strands
+            positive_strand_y = 0.1
+            negative_strand_y = -0.1
+
+            # Use an offset to spread gRNA sequences vertically
+            offset = 0.05
 
             # 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, target, gRNA, pred_score = prediction
                 # Set the y-value and arrow symbol based on the strand
-                if strand == 1:
+                if strand == '1':
                     y_value = positive_strand_y
                     arrow_symbol = 'triangle-right'
-                    positive_strand_y += 0.1  # Increment the y-value for the next positive strand gRNA
+                    positive_strand_y += offset  # Increment the y-value for the next positive strand gRNA
                 else:
                     y_value = negative_strand_y
                     arrow_symbol = 'triangle-left'
-                    negative_strand_y -= 0.1  # Decrement the y-value for the next negative strand gRNA
+                    negative_strand_y -= offset  # Decrement the y-value for the next negative strand gRNA
 
                 fig.add_trace(go.Scatter(
-                    x=[start, end],
-                    y=[y_value, y_value],  # Use the y_value set above for the strand
-                    mode='lines+markers+text',
+                    x=[(start + end) / 2],  # Place the marker at the midpoint of the start and end
+                    y=[y_value],  # Use the y_value set above for the strand
+                    mode='markers+text',
                     marker=dict(symbol=arrow_symbol, size=10),
                     name=f"gRNA: {gRNA}",
-                    text=[f"Rank: {i}", ""],  # Text at the first point
+                    text=f"Rank: {i}",  # Place text at the marker
                     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>Prediction Score: {pred_score:.4f}",
+                    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>Prediction Score: {pred_score:.4f}",
                 ))
 
             # Update the layout of the plot