support for app

app.py

@@ -1,3 +1,4 @@
+import pandas as pd
 import streamlit as st
 from tiger import tiger_exhibit, TARGET_LEN, NUCLEOTIDE_TOKENS
 
@@ -23,7 +24,7 @@ if len(st.session_state['userInput']) < TARGET_LEN:
 
 # valid input
 elif all([True if nt.upper() in NUCLEOTIDE_TOKENS.keys() else False for nt in st.session_state['userInput']]):
-    on_target, off_target = tiger_exhibit(st.session_state['userInput'])
+    on_target, off_target = tiger_exhibit(pd.DataFrame(dict(id=['ManualEntry'], seq=[st.session_state['userInput']])))
     st.write('On-target predictions: ', on_target)
     st.download_button(label='Download', data=convert_df(on_target), file_name='on_target.csv', mime='text/csv')
     if len(off_target) > 0:

tiger.py

@@ -214,7 +214,7 @@ if __name__ == '__main__':
     # simple test case
     if args.simple_test:
         # first 50 from EIF3B-003's CDS
-        simple_test = pd.DataFrame(dict(id=['user entry'], seq=['ATGCAGGACGCGGAGAACGTGGCGGTGCCCGAGGCGGCCGAGGAGCGCGC']))
+        simple_test = pd.DataFrame(dict(id=['ManualEntry'], seq=['ATGCAGGACGCGGAGAACGTGGCGGTGCCCGAGGCGGCCGAGGAGCGCGC']))
         simple_test.set_index('id', inplace=True)
         df_on_target, df_off_target = tiger_exhibit(simple_test)
         df_on_target.to_csv('on_target.csv')