Update app.py

app.py

@@ -106,24 +106,16 @@ def matplotlib_to_plotly(cmap, pl_entries):
 
 red_blue = matplotlib_to_plotly(red_blue, 255)
 
-df_shap = df_total[df_total.index.isin(gene_list)]
-df_shap.drop(columns='XGB_Score', inplace=True)
-shap_values = explainer.shap_values(df_shap)
-summary_plot = shap.summary_plot(shap_values, df_shap)
-feature_order = np.argsort(np.sum(np.abs(shap_values), axis=0)[:-1])
-feature_order = feature_order[-min(8, len(feature_order)):]
-col_order = [df_shap.columns[i] for i in feature_order]
-
 if len(gene_list) > 1:
     df = df_total[df_total.index.isin(gene_list)]
     df['Gene'] = df.index
     df.reset_index(drop=True, inplace=True)
     df = df[['Gene','XGB_Score', 'mousescore_Exomiser',
- 'SDI', 'Liver_GTExTPM',  'pLI_ExAC',
- 'HIPred',
- 'Cells - EBV-transformed lymphocytes_GTExTPM',
- 'Pituitary_GTExTPM',
- 'IPA_BP_annotation']]
+     'SDI', 'Liver_GTExTPM',  'pLI_ExAC',
+     'HIPred',
+     'Cells - EBV-transformed lymphocytes_GTExTPM',
+     'Pituitary_GTExTPM',
+     'IPA_BP_annotation']]
     st.dataframe(df)
     output = df[['Gene', 'XGB_Score']]
     csv = convert_df(output)
@@ -138,13 +130,13 @@ if len(gene_list) > 1:
     df_shap.drop(columns='XGB_Score', inplace=True)
     shap_values = explainer.shap_values(df_shap)
     summary_plot = shap.summary_plot(shap_values, df_shap)
+    st.pyplot(fig=summary_plot)
+    st.caption("SHAP Summary Plot of All Input Genes")
     feature_order = np.argsort(np.sum(np.abs(shap_values), axis=0)[:-1])
     feature_order = feature_order[-min(8, len(feature_order)):]
     col_order = [df.columns[i] for i in feature_order]
-    st.caption("SHAP Summary Plot of All Input Genes")
-    st.pyplot(fig=summary_plot)
     st.caption("Interactive SHAP Summary Plot of All Input Genes")
-    mpl_fig = shap_summary_plot(shap_values, df_shap, max_display=8, show=False, feature_names=df_shap.columns)
+    mpl_fig = shap_summary_plot(shap_values, df_shap, max_display=8, show=False, feature_names=col_order)
     plotly_fig = tls.mpl_to_plotly(mpl_fig)
     plotly_fig['layout'] = {'xaxis': {'title': 'SHAP value (impact on model output)'}}
     max_display=8