Update app.py

app.py

@@ -8,8 +8,8 @@ import shap
 st.set_option('deprecation.showPyplotGlobalUse', False)
 seed=42
 
-data = pd.read_csv("annotations_dataset.csv")
-data = data.set_index("Gene")
+annotations = pd.read_csv("annotations_dataset.csv")
+annotations = annotations.set_index("Gene")
 
 training_data = pd.read_csv("./selected_features_training_data.csv", header=0)
 training_data.columns = [
@@ -34,12 +34,14 @@ xgb = xgboost.XGBRegressor(
 
 xgb.fit(X, Y)
 
-predictions = list(xgb.predict(data))
-predictions = [round(item, 2) for item in predictions]
+prediction_list = list(xgb.predict(data))
+predictions = [round(prediction, 2) for prediction in prediction_list]
 
-output = pd.Series(data=predictions, index=data.index, name="XGB_Score")
-df_total = pd.concat([data, output], axis=1)
-df_total.rename_axis('Gene').reset_index()
+output = pd.Series(data=predictions, index=annotations.index, name="XGB_Score")
+df_total = pd.concat([annotations, output], axis=1)
+#df_total['Gene'] = df_total.index
+#df_total.reset_index()
+df_total.rename_axis('Gene')
 
 df_total = df_total[['XGB_Score', 'mousescore_Exomiser',
  'SDI', 'Liver_GTExTPM',  'pLI_ExAC',