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| #from turtle import shape | |
| import streamlit as st | |
| #from st_keyup import st_keyup | |
| import pandas as pd | |
| import numpy as np | |
| from st_aggrid import AgGrid, GridOptionsBuilder,GridUpdateMode,DataReturnMode | |
| import os | |
| cwd=os.getcwd()+'/'+'data/' | |
| #get genes list | |
| listA = pd.read_csv(cwd+"20200513_library_1_2_unbalanced_dJR051.csv",index_col=False) | |
| listB = pd.read_csv(cwd+"20200513_library_3_4_unbalanced_dJR052.csv",index_col=False) | |
| listC = pd.read_csv(cwd+"20200513_library_5_6_unbalanced_dJR053.csv",index_col=False) | |
| #variants=listA['sgID_A'].unique() | |
| variants=listA['gene'].unique() | |
| variants_s=sorted(variants) | |
| #Also read LR guides | |
| listA_found_ref = pd.read_csv(cwd+"seta_found_ref1.csv",index_col=False) | |
| listA_notfound_ref = pd.read_csv(cwd+"seta_notfound_ref1.csv",index_col=False) | |
| listA_found_lr = pd.read_csv(cwd+"seta_found_LR1.csv",index_col=False) | |
| listA_notfound_lr = pd.read_csv(cwd+"seta_notfound_LR1.csv",index_col=False) | |
| st.title('Long Read Guides Search') | |
| #st.markdown('**Please select an option from the sidebar**') | |
| #st.write(variants) | |
| Calc = st.sidebar.radio( | |
| "", | |
| ('ReadME', 'Tools Selection Menu')) | |
| if Calc == 'ReadME': | |
| #st.markdown("[Introduction](#Introduction)") | |
| #st.markdown("[How do base editors work](#How-do-base-editors-work)") | |
| expander = st.expander("How to use this app") | |
| else: | |
| #if Calc == 'Selection Menu': | |
| #ReadMe = st.sidebar.checkbox('ReadME',value=False) | |
| select_variant = st.sidebar.selectbox( | |
| "Please select variant", | |
| variants_s | |
| ) | |
| #ref_sgrna=listA[listA['sgID_A']==select_variant][['protospacer_A','protospacer_B']] | |
| ref_listA=listA[listA['gene']==select_variant][['guide_type','protospacer_A','protospacer_B','sgID_AB']] | |
| #ref_listA=listA[listA['gene']==select_variant] | |
| #st.write(ref_listA) | |
| ref_listB=listB[listB['gene']==select_variant][['guide_type','protospacer_A','protospacer_B','sgID_AB']] | |
| #st.write(ref_listB) | |
| ref_listC=listC[listC['gene']==select_variant][['guide_type','protospacer_A','protospacer_B','sgID_AB']] | |
| #st.write(ref_listC) | |
| #m=pd.merge(ref_listA,ref_listC,ref_listC) | |
| listA_concatenated_orig = pd.concat([ref_listA,ref_listB,ref_listC]) | |
| st.write('Original Guides (all 6 from 3 sets)') | |
| st.write(listA_concatenated_orig) | |
| st.write('GRCh38 SetA Guides Found with at most 2 Missmatches') | |
| a_ref=ref_listA.sgID_AB.values[0].split('|') | |
| #check GRCh38 | |
| seta_found0_ref=listA_found_ref[listA_found_ref['gene']==a_ref[0]] | |
| seta_found1_ref=listA_found_ref[listA_found_ref['gene']==a_ref[1]] | |
| listA_concatenated_found_ref = pd.concat([seta_found0_ref,seta_found1_ref]) | |
| st.write(listA_concatenated_found_ref) | |
| st.write('LR SetA Guides Found with at most 2 Missmatches') | |
| seta_found0_lr=listA_found_lr[listA_found_lr['gene']==a_ref[0]] | |
| seta_found1_lr=listA_found_lr[listA_found_lr['gene']==a_ref[1]] | |
| listA_concatenated_found_LR = pd.concat([seta_found0_lr,seta_found1_lr]) | |
| st.write(listA_concatenated_found_LR) | |
| st.write('GRCh38 SetA Guides Not Found') | |
| seta_notfound0_ref=listA_notfound_ref[listA_notfound_ref['gene']==a_ref[0]] | |
| seta_notfound1_ref=listA_notfound_ref[listA_notfound_ref['gene']==a_ref[1]] | |
| listA_concatenated_notfound_ref = pd.concat([seta_notfound0_ref,seta_notfound1_ref]) | |
| st.write(listA_concatenated_notfound_ref) | |
| st.write('LR SetA Guides Not Found') | |
| seta_notfound0_lr=listA_notfound_lr[listA_notfound_lr['gene']==a_ref[0]] | |
| seta_notfound1_lr=listA_notfound_lr[listA_notfound_lr['gene']==a_ref[1]] | |
| listA_concatenated_notfound_lr = pd.concat([seta_notfound0_lr,seta_notfound1_lr]) | |
| st.write(listA_concatenated_notfound_lr) | |
| #protospacer_A | |