Update pages/Suture.py

pages/Suture.py

@@ -55,7 +55,7 @@ storage_options={'account_name': AZURE_STORAGE_ACCOUNT, 'account_key': AZURE_STO
 # Load in multiple dataframes
 df = pl.scan_parquet(f"az://{dataset}.parquet", storage_options=storage_options).collect()
 
-# Create the second tab content with scatter-plot_db0-5 and scatter-plot_db0-6
+# Create the second tab content with scatter-plot_db1-5 and scatter-plot_db1-6
 tab2_content = html.Div([
     html.Div([
             html.Label("S-cycle genes"),
@@ -164,20 +164,20 @@ tab2_content = html.Div([
 ]),
     ]),
     html.Div([
-        dcc.Graph(id='scatter-plot_db0-5', figure={}, className='three columns',config=config_fig)
+        dcc.Graph(id='scatter-plot_db1-5', figure={}, className='three columns',config=config_fig)
     ]),
     html.Div([
-        dcc.Graph(id='scatter-plot_db0-6', figure={}, className='three columns',config=config_fig)
+        dcc.Graph(id='scatter-plot_db1-6', figure={}, className='three columns',config=config_fig)
     ]),
     html.Div([
-        dcc.Graph(id='scatter-plot_db0-7', figure={}, className='three columns',config=config_fig)
+        dcc.Graph(id='scatter-plot_db1-7', figure={}, className='three columns',config=config_fig)
     ]),
     html.Div([
-        dcc.Graph(id='scatter-plot_db0-8', figure={}, className='three columns',config=config_fig)
+        dcc.Graph(id='scatter-plot_db1-8', figure={}, className='three columns',config=config_fig)
     ]),
 ])
 
-# Create the second tab content with scatter-plot_db0-5 and scatter-plot_db0-6
+# Create the second tab content with scatter-plot_db1-5 and scatter-plot_db1-6
 tab3_content = html.Div([
     html.Div([
             html.Label("UMAP condition 1"),
@@ -187,16 +187,16 @@ tab3_content = html.Div([
             dcc.Dropdown(id='dpdn6', value="Pax6", multi=False,
                  options=df.columns),
     html.Div([
-        dcc.Graph(id='scatter-plot_db0-9', figure={}, className='four columns', hoverData=None ,config=config_fig)
+        dcc.Graph(id='scatter-plot_db1-9', figure={}, className='four columns', hoverData=None ,config=config_fig)
     ]),
     html.Div([
-        dcc.Graph(id='scatter-plot_db0-10', figure={}, className='four columns', hoverData=None, config=config_fig)
+        dcc.Graph(id='scatter-plot_db1-10', figure={}, className='four columns', hoverData=None, config=config_fig)
     ]),
     html.Div([
-        dcc.Graph(id='scatter-plot_db0-11', figure={}, className='four columns',config=config_fig)
+        dcc.Graph(id='scatter-plot_db1-11', figure={}, className='four columns',config=config_fig)
     ]),
     html.Div([
-            dcc.Graph(id='my-graph_db02', figure={}, clickData=None, hoverData=None,
+            dcc.Graph(id='my-graph_db12', figure={}, clickData=None, hoverData=None,
                   className='four columns',config=config_fig
                   )
     ]),
@@ -217,7 +217,7 @@ tab4_content = html.Div([
                  options=df.columns),
 ]),
     html.Div([
-        dcc.Graph(id='scatter-plot_db0-12', figure={}, className='row',style={'width': '100vh', 'height': '90vh'})
+        dcc.Graph(id='scatter-plot_db1-12', figure={}, className='row',style={'width': '100vh', 'height': '90vh'})
     ]),
 ])
 
@@ -236,15 +236,15 @@ layout = html.Div([
 ])
 
 @callback(
-    Output(component_id='scatter-plot_db0-5', component_property='figure'),
-    Output(component_id='scatter-plot_db0-6', component_property='figure'),
-    Output(component_id='scatter-plot_db0-7', component_property='figure'),
-    Output(component_id='scatter-plot_db0-8', component_property='figure'),
-    Output(component_id='scatter-plot_db0-9', component_property='figure'),
-    Output(component_id='scatter-plot_db0-10', component_property='figure'),
-    Output(component_id='scatter-plot_db0-11', component_property='figure'),
-    Output(component_id='scatter-plot_db0-12', component_property='figure'),
-    Output(component_id='my-graph_db02', component_property='figure'),
+    Output(component_id='scatter-plot_db1-5', component_property='figure'),
+    Output(component_id='scatter-plot_db1-6', component_property='figure'),
+    Output(component_id='scatter-plot_db1-7', component_property='figure'),
+    Output(component_id='scatter-plot_db1-8', component_property='figure'),
+    Output(component_id='scatter-plot_db1-9', component_property='figure'),
+    Output(component_id='scatter-plot_db1-10', component_property='figure'),
+    Output(component_id='scatter-plot_db1-11', component_property='figure'),
+    Output(component_id='scatter-plot_db1-12', component_property='figure'),
+    Output(component_id='my-graph_db12', component_property='figure'),
     Input(component_id='dpdn2', component_property='value'),
     Input(component_id='dpdn3', component_property='value'),
     Input(component_id='dpdn4', component_property='value'),
@@ -298,53 +298,53 @@ def update_graph_and_pie_chart(col_chosen, s_chosen, g2m_chosen, condition1_chos
     # Final part to join the percentage expressed and mean expression levels
     expression_means = expression_means.join(dff_5, on=[col_chosen,"Gene"], how="inner")
     
-    fig_scatter_db0_5 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color=s_chosen,
+    fig_scatter_db1_5 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color=s_chosen,
                             labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                             hover_name=None, title="S-cycle gene:",template="seaborn")
 
-    fig_scatter_db0_6 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color=g2m_chosen,
+    fig_scatter_db1_6 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color=g2m_chosen,
                             labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                             hover_name='condition', title="G2M-cycle gene:",template="seaborn")
     
-    fig_scatter_db0_7 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color="S_score",
+    fig_scatter_db1_7 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color="S_score",
                             labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                             hover_name='condition', title="S score:",template="seaborn")
     
-    fig_scatter_db0_8 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color="G2M_score",
+    fig_scatter_db1_8 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color="G2M_score",
                             labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                             hover_name='condition', title="G2M score:",template="seaborn")
 
     # Sort values of custom in-between
     dff = dff.sort(condition1_chosen)
     
-    fig_scatter_db0_9 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color=condition1_chosen,
+    fig_scatter_db1_9 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color=condition1_chosen,
                             labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                             hover_name=None,hover_data = None, template="seaborn",category_orders=cat_ord)
-    fig_scatter_db0_9.update_traces(hoverinfo='none', hovertemplate=None)
-    fig_scatter_db0_9.update_layout(hovermode=False)
+    fig_scatter_db1_9.update_traces(hoverinfo='none', hovertemplate=None)
+    fig_scatter_db1_9.update_layout(hovermode=False)
     
-    fig_scatter_db0_10 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color=condition2_chosen,
+    fig_scatter_db1_10 = px.scatter(data_frame=dff, x='X_umap-0', y='X_umap-1', color=condition2_chosen,
                             labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                             hover_name='condition',template="seaborn")
     
-    fig_scatter_db0_11 = px.scatter(data_frame=dff, x=condition1_chosen, y=condition2_chosen, color=condition1_chosen,
+    fig_scatter_db1_11 = px.scatter(data_frame=dff, x=condition1_chosen, y=condition2_chosen, color=condition1_chosen,
                             #labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                             hover_name='condition',template="seaborn",category_orders=cat_ord)
 
     # Reorder categories on natural sorting or on the integrated cell state order of the paper
     if col_chosen == "integrated_cell_states":
-        fig_scatter_db0_12 = px.scatter(data_frame=expression_means, x="Gene", y=col_chosen, color="Mean expression",
+        fig_scatter_db1_12 = px.scatter(data_frame=expression_means, x="Gene", y=col_chosen, color="Mean expression",
                                     size="percentage", size_max = 20,
                                 #labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                                 hover_name=col_chosen,template="seaborn",category_orders={col_chosen: natsorted(expression_means[col_chosen].unique())})
     else:                                                                                
-        fig_scatter_db0_12 = px.scatter(data_frame=expression_means, x="Gene", y=col_chosen, color="Mean expression",
+        fig_scatter_db1_12 = px.scatter(data_frame=expression_means, x="Gene", y=col_chosen, color="Mean expression",
                                     size="percentage", size_max = 20,
                                 #labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
                                 hover_name=col_chosen,template="seaborn",category_orders={col_chosen: natsorted(expression_means[col_chosen].unique()),"Gene": condition3_chosen})
     
-    fig_violin_db02 = px.violin(data_frame=dff, x=condition1_chosen, y=condition2_chosen, box=True, points="all",
+    fig_violin_db12 = px.violin(data_frame=dff, x=condition1_chosen, y=condition2_chosen, box=True, points="all",
                             color=condition1_chosen, hover_name=condition1_chosen,template="seaborn",category_orders=cat_ord)
 
 
-    return fig_scatter_db0_5, fig_scatter_db0_6, fig_scatter_db0_7, fig_scatter_db0_8, fig_scatter_db0_9, fig_scatter_db0_10, fig_scatter_db0_11, fig_scatter_db0_12, fig_violin_db02
+    return fig_scatter_db1_5, fig_scatter_db1_6, fig_scatter_db1_7, fig_scatter_db1_8, fig_scatter_db1_9, fig_scatter_db1_10, fig_scatter_db1_11, fig_scatter_db1_12, fig_violin_db12