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Update app.py
Browse files
app.py
CHANGED
@@ -252,18 +252,22 @@ elif tab == "Supervised SHAP Clustering":
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# Initialize an empty figure
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fig = go.Figure()
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# Plot clustered genes based on PCA components
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for cluster in df_for_plot['Cluster'].unique():
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filtered_df = df_for_plot[(df_for_plot['Cluster'] == cluster) & (df_for_plot['SpecialGroup'] == 'None')]
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fig.add_trace(go.Scatter(
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x=filtered_df['PCA_1'], y=filtered_df['PCA_2'],
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mode='markers',
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name=f'Cluster {cluster}',
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text=filtered_df['Gene'],
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hoverinfo="text+x+y",
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))
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# Overlay "Most Likely Training Gene"
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filtered_df = df_for_plot[df_for_plot['SpecialGroup'] == 'Most Likely Training Gene']
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fig.add_trace(go.Scatter(
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@@ -271,10 +275,10 @@ elif tab == "Supervised SHAP Clustering":
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mode='markers',
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name='Most Likely Training Gene',
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text=filtered_df['Gene'],
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marker=dict(color='
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hoverinfo="text+x+y",
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))
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# Overlay "User Input Gene"
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filtered_df = df_for_plot[df_for_plot['SpecialGroup'] == 'User Input Gene']
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fig.add_trace(go.Scatter(
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@@ -282,10 +286,10 @@ elif tab == "Supervised SHAP Clustering":
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mode='markers',
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name='User Input Gene',
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text=filtered_df['Gene'],
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marker=dict(color='
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hoverinfo="text+x+y",
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))
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# Customize layout
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fig.update_layout(
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title='Supervised SHAP Clustering with PCA',
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@@ -294,5 +298,5 @@ elif tab == "Supervised SHAP Clustering":
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showlegend=True,
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legend_title_text='Gene Category',
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)
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st.plotly_chart(fig, use_container_width=True)
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# Initialize an empty figure
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fig = go.Figure()
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# Define color mapping for clusters
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cluster_colors = ['red', 'blue', 'purple']
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# Plot clustered genes based on PCA components
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for i, cluster in enumerate(df_for_plot['Cluster'].unique()):
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filtered_df = df_for_plot[(df_for_plot['Cluster'] == cluster) & (df_for_plot['SpecialGroup'] == 'None')]
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fig.add_trace(go.Scatter(
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x=filtered_df['PCA_1'], y=filtered_df['PCA_2'],
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mode='markers',
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name=f'Cluster {cluster}',
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text=filtered_df['Gene'],
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marker=dict(color=cluster_colors[i]),
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hoverinfo="text+x+y",
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))
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# Overlay "Most Likely Training Gene"
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filtered_df = df_for_plot[df_for_plot['SpecialGroup'] == 'Most Likely Training Gene']
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fig.add_trace(go.Scatter(
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mode='markers',
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name='Most Likely Training Gene',
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text=filtered_df['Gene'],
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marker=dict(color='black'),
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hoverinfo="text+x+y",
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))
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# Overlay "User Input Gene"
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filtered_df = df_for_plot[df_for_plot['SpecialGroup'] == 'User Input Gene']
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fig.add_trace(go.Scatter(
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mode='markers',
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name='User Input Gene',
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text=filtered_df['Gene'],
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marker=dict(color='orange'),
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hoverinfo="text+x+y",
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))
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+
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# Customize layout
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fig.update_layout(
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title='Supervised SHAP Clustering with PCA',
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showlegend=True,
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legend_title_text='Gene Category',
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)
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+
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st.plotly_chart(fig, use_container_width=True)
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