Update app.py

app.py

@@ -112,35 +112,35 @@ opt = st.sidebar.radio("Select a PubMed Corpus", options=('Breast Cancer corpus'
 #     database_name = "Neuroblastoma"
 if opt == "Breast Cancer corpus":
     model_used = ("breast_cancer_pubmed_model")
-    num_abstracts = 204381
+    num_abstracts = 204414
     database_name = "Breast_cancer"
 if opt == "Lung Cancer corpus":
     model_used = ("lung_cancer_pubmed_model")
-    num_abstracts = 143886
+    num_abstracts = 143916
     database_name = "Lung_cancer"
 if opt == "Colorectal Cancer corpus":
     model_used = ("colorectal_cancer_pubmed_model")
-    num_abstracts = 140000
+    num_abstracts = 138679
     database_name = "Colorectal_cancer"
 if opt == "Prostate Cancer corpus":
     model_used = ("prostate_cancer_pubmed_model")
-    num_abstracts = 89782
+    num_abstracts = 89791
     database_name = "Prostate_cancer"
 if opt == "Skin Cancer corpus":
     model_used = ("skin_cancer_pubmed_model")
-    num_abstracts = 176568
+    num_abstracts = 176587
     database_name = "Skin_cancer"
 if opt == "Lymphoma Cancer corpus":
     model_used = ("lymphoma_cancer_pubmed_model")
-    num_abstracts = 79000
+    num_abstracts = 102603
     database_name = "Lymphoma_cancer"
 if opt == "Urinary Cancer corpus":
     model_used = ("urinary_cancer_pubmed_model")
-    num_abstracts = 65000
+    num_abstracts = 60876
     database_name = "Urinary_cancer"
 if opt == "Kidney Cancer corpus":
     model_used = ("kidney_cancer_pubmed_model")
-    num_abstracts = 40000
+    num_abstracts = 39016
     database_name = "Kidney_cancer"    
     
 
@@ -470,6 +470,7 @@ if query:
                 "Human gene designation and database provided by HUGO Gene Nomenclature Committee (HGNC): https://www.genenames.org/")
             st.caption("Gene designation add in exceptions [p21, p53, her2, her3]")
             st.caption("Gene information provided by GeneCards: https://www.genecards.org//")
+            st.caption("In some cases genes may represent abbreviations of words and not genes, use pubmed link to confirm output is a gene")
 
             csv = df1.head(value_gene).to_csv().encode('utf-8')
             st.download_button(label=f"download top {value_gene} genes (csv)", data=csv,