Delete app.py

app.py

@@ -1,883 +0,0 @@
-#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
-
-st.set_page_config(layout="wide") 
-st.markdown(
-    """
-<style>
-.streamlit-expanderHeader {
-    font-size: x-large;
-}
-</style>
-""",
-    unsafe_allow_html=True,
-)
-caution = '<p style="font-family:sans-serif; color:Red; font-size: 18px;">Please note that Only one Guide (from pair) is found. Please see guides not found section for other guide</p>'
-caution1 = '<p style="font-family:sans-serif; color:Red; font-size: 18px;">Please note that Each mutated guide is reported as a sepearte line. sgID_1/2, sgRNA_1/2, chr_sgRNA_1/2 and position_sgRNA_1/2 represent values for reference/mutated guide</p>'
-caution2 = '<p style="font-family:sans-serif; color:Red; font-size: 18px;">Please Select a single/multiple guides and then select Check Box A, B or C Otherwise code will through error</p>'
-table_edit = '<p style="font-family:sans-serif; color:Green; font-size: 16px;">About Table: Please note that table can be <b>sorted by clicking on any column</b> and <b>Multiple rows can be selected</b> (by clicking check box in first column) to save only those rows.</p>'
-
-def transform(df,str):
-    # Select columns
-    #cols = st.multiselect('Please select columns to save current Table as csv file', 
-    cols = st.multiselect(str, 
-    df.columns.tolist(),
-    df.columns.tolist()
-    )
-    df = df[cols]
-    return df
-
-def convert_df(df):
-    return df.to_csv().encode('utf-8')
-def convert_df1(df):
-    return df.to_csv(index=False).encode('utf-8')
-
-
-# CSS to inject contained in a string
-hide_table_row_index = """
-            <style>
-            thead tr th:first-child {display:none}
-            tbody th {display:none}
-            </style>
-            """
-
-# Inject CSS with Markdown
-st.markdown(hide_table_row_index, unsafe_allow_html=True)
-
-
-#########TABLE DISPLAY
-def tbl_disp(dat,var,ref,flg=1):
-    dat.reset_index(drop=True, inplace=True)
-    #df = transform(dft,'Please Select columns to save whole table')
-    #fname = st.text_input('Please input file name to save Table', 'temp')
-    #fname = st_keyup("Please input file name to save Table", value='temp')
-    csv = convert_df(dat)
-    if flg==1:
-        st.download_button(
-            label="Download Full Table as CSV file",
-            data=csv,
-            file_name=var+'_'+ref+'.csv',#fname+'.csv',
-            mime='text/csv',
-        )
-    #st.table(dft)
-    #st.markdown(table_edit,unsafe_allow_html=True)
-    gb = GridOptionsBuilder.from_dataframe(dat)
-    gb.configure_pagination(enabled=False)#,paginationAutoPageSize=False)#True) #Add pagination
-    gb.configure_default_column(enablePivot=True, enableValue=True, enableRowGroup=True)
-    gb.configure_selection(selection_mode="multiple", use_checkbox=True)
-
-    gb.configure_side_bar()
-    gridOptions = gb.build()    
-
-    grid_response = AgGrid(
-            dat,
-            height=200,
-            gridOptions=gridOptions,
-            enable_enterprise_modules=True,
-            update_mode=GridUpdateMode.MODEL_CHANGED,
-            data_return_mode=DataReturnMode.FILTERED_AND_SORTED,
-            fit_columns_on_grid_load=False,
-            header_checkbox_selection_filtered_only=True,
-            use_checkbox=True,
-            width='100%'
-    )
-
-    selected = grid_response['selected_rows']   
-    if selected:
-        st.write('Selected rows')
-        
-        dfs = pd.DataFrame(selected)
-        st.dataframe(dfs[dfs.columns[1:dfs.shape[1]]])
-
-        #dfs1 = transform(dfs[dfs.columns[1:dfs.shape[1]]],'Please select columns to save selected Table')
-        csv = convert_df1(dfs[dfs.columns[1:dfs.shape[1]]])
-        #csv = convert_df1(dfs1)
-        
-
-        st.download_button(
-            label="Download data as CSV",
-            data=csv,
-            file_name=var+'_'+ref+'.csv',
-            mime='text/csv',
-        )
-        return dfs
-
- 
-
-def assemble_tbl(t):
-    dft = pd.DataFrame(columns=['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1','sgID_2','sgRNA_2','chr_sgRNA_2','position_sgRNA_2', 'sgID_1_2'])
-    for i in range(0,t.shape[0],2):
-        l1=t.iloc[[i]]
-        l1.columns=['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1','mutated_guide',	'strand',	'num_mismatch']
-
-        l2=t.iloc[[i+1]]
-        l2.columns=['sgID_2','sgRNA_2','chr_sgRNA_2','position_sgRNA_2','mutated_guide2',	'strand2',	'num_mismatch2']
-        listA_concatenated_match_LR1=pd.concat([l1.reset_index(drop=True),l2.reset_index(drop=True)],axis=1)
-        listA_concatenated_match_LR1=listA_concatenated_match_LR1[['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1','sgID_2','sgRNA_2','chr_sgRNA_2','position_sgRNA_2']]
-        listA_concatenated_match_LR1['sgRNA_1']=listA_concatenated_match_LR1['sgRNA_1'].str.slice(0, 20)
-        listA_concatenated_match_LR1['sgRNA_2']=listA_concatenated_match_LR1['sgRNA_2'].str.slice(0, 20)
-        listA_concatenated_match_LR1['sgID_1_2']=listA_concatenated_match_LR1['sgID_1']+"|"+listA_concatenated_match_LR1['sgID_1']
-        dft=dft.append(listA_concatenated_match_LR1)
-        
-    return dft
-    
-def get_lists(ref_list,list_found_ref,list_notfound_ref):
-    a_ref=[]  
-    for i in range(len(ref_list)):
-        a_ref.append(ref_list.gene.values[i].split('|')[0])
-        a_ref.append(ref_list.gene.values[i].split('|')[1])
-    #check GRCh38
-    #st.table(a_ref)
-    set_found0_ref=[]
-    for i in range(len(a_ref)):
-        set_found0_ref.append(list_found_ref[list_found_ref['gene']==a_ref[i]])
-    list_concatenated_found_ref = pd.concat(set_found0_ref)
-    
-
-
-    #split in found and not found
-    
-    list_concatenated_match_ref = list_concatenated_found_ref[list_concatenated_found_ref.num_mismatch == 0]
-    #list_concatenated_match_ref=list_concatenated_match_ref.sort_values('position')
-    
-    #Also remove Alternate loci's data
-    list_concatenated_match_ref = list_concatenated_match_ref[list_concatenated_match_ref['chr'].str.contains('chr')]
-    
-    #also create new list with both sgRNAs in one row
-    dft=pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-    if list_concatenated_match_ref.shape[0]>0:
-        t=list_concatenated_match_ref.reset_index(drop=True)
-        #st.table(t)
-        
-        ##########
-        #check even/odd entries
-        if t.shape[0]==1:
-            t1=t.loc[t.index.repeat(2)].reset_index(drop=True)
-            #st.write(t1)
-            dft=assemble_tbl(t1)
-            
-        elif t.shape[0]%2==0: #even
-            dft=assemble_tbl(t)
-
-        else: #odd
-            t1 = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-            i=0
-            while i <t.shape[0]:
-            #for i in range(t.shape[0]):
-                #if t.iloc[i,['gene']] == t.iloc[i+1,['gene']]:
-                #st.table(t)
-                #st.write(i)
-                if i<t.shape[0]-1:
-                    if t.iloc[i]['gene'] == t.iloc[i+1]['gene'] and t.iloc[i]['chr'] == t.iloc[i+1]['chr'] and t.iloc[i]['position'] == t.iloc[i+1]['position']:
-                        t1=t1.append(t.iloc[[i]], ignore_index = True)
-                        t1=t1.append(t.iloc[[i+1]], ignore_index = True)
-                        i=i+2
-                    else: #repeat entries
-                        t1=t1.append(t.iloc[[i]], ignore_index = True)
-                        t1=t1.append(t.iloc[[i]], ignore_index = True)
-                        #st.table(t1)
-                        i=i+1
-                else:
-                    t1=t1.append(t.iloc[[i]], ignore_index = True)
-                    t1=t1.append(t.iloc[[i]], ignore_index = True)
-                    i=i+1
-                    #st.table(t1)
-                    
-                    
-            dft=assemble_tbl(t1)
-    list_concatenated_mutated_ref = list_concatenated_found_ref[list_concatenated_found_ref.num_mismatch > 0]
-    list_concatenated_mutated_ref=list_concatenated_mutated_ref.sort_values('position')
-    
-    #Also remove Alternate loci's data
-    
-    list_concatenated_mutated_ref = list_concatenated_mutated_ref[list_concatenated_mutated_ref['chr'].str.contains('chr')]
-    dft_mut = pd.DataFrame(columns=['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1','sgID_2','sgRNA_2','chr_sgRNA_2','position_sgRNA_2', 'sgID_1_2'])
-    if list_concatenated_mutated_ref.shape[0]>0:        
-        dft_mut = get_mutated_res(list_concatenated_mutated_ref)
-    #check not found        
-    seta_notfound0_ref=list_notfound_ref[list_notfound_ref['gene']==a_ref[0]]
-    seta_notfound1_ref=list_notfound_ref[list_notfound_ref['gene']==a_ref[1]]
-    list_concatenated_notfound_ref = pd.concat([seta_notfound0_ref,seta_notfound1_ref])
-    return dft, dft_mut,list_concatenated_notfound_ref,list_concatenated_match_ref,list_concatenated_mutated_ref
-    ###########
- 
-def get_mutated_res(list_concatenated_mutated_ref):
-    ######### 
-    #if list_concatenated_mutated_ref.shape[0]>0:
-    t=list_concatenated_mutated_ref.reset_index(drop=True)
-    #st.table(t)
-    dft_mut = pd.DataFrame(columns=['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1','sgID_2','sgRNA_2','chr_sgRNA_2','position_sgRNA_2', 'sgID_1_2'])
-    c1=['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1']
-    c2=['sgID_2','sgRNA_2','chr_sgRNA_2','position_sgRNA_2']#, 'sgID_1_2']
-    #st.table(listA_concatenated_match_ref)
-    #st.write(t.shape[0])
-    tf=0
-    #for i in range(0,t.shape[0],2):
-    for i in range(t.shape[0]):
-        l1=t.iloc[[i]]
-        l1.columns=['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1','mutated_guide',	'strand',	'num_mismatch']
-        l2=l1.copy()
-        l2.columns=['sgID_2','sgRNA_2','chr_sgRNA_2','position_sgRNA_2','mutated_guide2',	'strand2',	'num_mismatch2']
-        list_concatenated_mutated_ref1=[]
-        #listA_concatenated_mutated_ref1=pd.concat([l1.reset_index(drop=True),l2.reset_index(drop=True)],axis=1)
-        list_concatenated_mutated_ref1=pd.concat([l1.reset_index(drop=True),l2.reset_index(drop=True)],axis=1)
-        #st.table(listA_concatenated_mutated_ref1)
-        list_concatenated_mutated_ref1=list_concatenated_mutated_ref1[['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1','sgID_2','mutated_guide2','chr_sgRNA_2','position_sgRNA_2']]
-        #also change if not leading G
-        list_concatenated_mutated_ref1['sgRNA_1']='G'+list_concatenated_mutated_ref1['sgRNA_1'].str.slice(1, 20)
-        #also change name of mutated_guide2 column
-        list_concatenated_mutated_ref1.columns=['sgID_1','sgRNA_1','chr_sgRNA_1','position_sgRNA_1','sgID_2','sgRNA_2','chr_sgRNA_2','position_sgRNA_2']
-        
-        list_concatenated_mutated_ref1['sgRNA_2']='G'+list_concatenated_mutated_ref1['sgRNA_2'].str.slice(1, 20)
-        list_concatenated_mutated_ref1['sgID_1_2']=list_concatenated_mutated_ref1['sgID_1']+"|"+list_concatenated_mutated_ref1['sgID_1']
-        dft_mut=dft_mut.append(list_concatenated_mutated_ref1)
-    return dft_mut
-        
-    #########
-
-#def get_notfound():
-    
-       
-cwd=os.getcwd()+'/'+'data/'
-
-#get genes list
-#listA = pd.read_csv(cwd+"20200513_library_1_2_unbalanced_dJR051.csv",index_col=False)
-#listA = pd.read_csv(cwd+"newa1.csv",index_col=False)
-#listB = pd.read_csv(cwd+"newb1.csv",index_col=False)
-#listC = pd.read_csv(cwd+"newc1.csv",index_col=False)
-
-listA = pd.read_csv(cwd+"guides_a_new.csv",index_col=False)
-
-listB = pd.read_csv(cwd+"guides_b_new.csv",index_col=False)
-listC = pd.read_csv(cwd+"guides_c_new.csv",index_col=False)
-variantsa1=listA['gene'].unique()
-variantsb1=listB['gene'].unique()
-variantsc1=listC['gene'].unique()
-
-con = np.concatenate((variantsa1, variantsb1,variantsc1))
-
-
-#st.write(type(variantsc1))
-variants_s=sorted(np.unique(con))
-#st.write(len(variants_s))
-#also get names for non-targetting guides
-
-
-#Also read GRCh38 and LR guides for stea
-listA_found_ref = pd.read_csv(cwd+"seta_found_ref1.csv",index_col=False)
-#remove # from chr# #
-listA_found_ref['chr'] = [x.split(' ')[-0] for x in listA_found_ref['chr']]
-listA_found_ref.rename(columns = {'strnad':'strand'}, inplace = True)
-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_found_lr.rename(columns = {'strnad':'strand'}, inplace = True)
-listA_notfound_lr = pd.read_csv(cwd+"seta_notfound_LR1.csv",index_col=False)
-
-#Also read GRCh38 and LR guides for set b
-listB_found_ref = pd.read_csv(cwd+"setb_found_ref1.csv",index_col=False)
-#remove # from chr# #
-listB_found_ref['chr'] = [x.split(' ')[-0] for x in listB_found_ref['chr']]
-listB_found_ref.rename(columns = {'strnad':'strand'}, inplace = True)
-listB_notfound_ref = pd.read_csv(cwd+"setb_notfound_ref1.csv",index_col=False)
-
-listB_found_lr = pd.read_csv(cwd+"setb_found_LR1.csv",index_col=False)
-listB_found_lr.rename(columns = {'strnad':'strand'}, inplace = True)
-listB_notfound_lr = pd.read_csv(cwd+"setb_notfound_LR1.csv",index_col=False)
-
-#Also read GRCh38 and LR guides for set c
-listC_found_ref = pd.read_csv(cwd+"setc_found_ref1.csv",index_col=False)
-#remove # from chr# #
-listC_found_ref['chr'] = [x.split(' ')[-0] for x in listC_found_ref['chr']]
-listC_found_ref.rename(columns = {'strnad':'strand'}, inplace = True)
-listC_notfound_ref = pd.read_csv(cwd+"setc_notfound_ref1.csv",index_col=False)
-
-listC_found_lr = pd.read_csv(cwd+"setc_found_LR1.csv",index_col=False)
-listC_found_lr.rename(columns = {'strnad':'strand'}, inplace = True)
-listC_notfound_lr = pd.read_csv(cwd+"setc_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', 'Single Gene','Multiple Genes'))
-
-
-if Calc == 'ReadME':
-    expander = st.expander("How to use this app")   
-    #st.header('How to use this app')
-    expander.markdown('Please select **Single Gene** OR **Multiple Genes** Menue checkbox from the sidebar')
-    expander.markdown('Select a Gene (from genes dropdown list) OR Multiple genes (from table)')
-    expander.markdown('A table showing all reference gudies from three LISTS will appear in the main panel. **Please not some of the genes (for example A1BG and GJB7) have multiple guide pairs and all of these are selected.**')
-    expander.markdown('To see results for each of the selected reference guide from ListA, ListB and ListC, Please select respective checkbox')
-    expander.markdown('Results are shown as two tables, **Matched** and **Mutated** guides tables and **NOT FOUND** table if guides are not found in GRCh38 and LR reference fasta files')
-    expander.markdown('**Mutated** guides table shows the genomic postion in GRCh38 and LR Fasta file along other fields. **If a guide is found in GRCh38 but not in LR fasta, then corresponding columns will be NA**')
-    expander.markdown('**Mutated** guides table shows the genomic postion in GRCh38 and LR Fasta file along other fields. **If a guide is found in GRCh38 but not in LR fasta, then corresponding columns will be NA**')
-    
-    expander1 = st.expander('Introduction')
-    
-    expander1.markdown(
-        """ This app helps navigate all probable genomic **miss-matched/Mutations (upto 2 bp)** for a given sgRNA (from 3 lists of CRISPRi dual sgRNA libraries) in GRCh38 reference fasta and a Reference fasta generated from BAM generated against KOLF2.1J longread data.
-            """
-            )
-    expander1.markdown('Merged bam file was converted to fasta file using following steps:')
-    expander1.markdown('- samtools mpileup to generate bcf file')
-    expander1.markdown('- bcftools to generate vcf file')
-    expander1.markdown('- bcftools consensus to generate fasta file')
-    expander1.markdown('A GPU based [Cas-OFFinder](http://www.rgenome.net/cas-offinder/) tool was used to find off-target sequences (upto 2 miss-matched) for each geiven reference guide against GRCh38 and LR fasta references.')
-     
-elif Calc=='Single Gene':
-#if Calc == 'Selection Menu':
-    #ReadMe = st.sidebar.checkbox('ReadME',value=False)
-    select_variant = st.sidebar.selectbox(
-        "Please select Gene",
-        variants_s
-    )
-    #ref_sgrna=listA[listA['sgID_A']==select_variant][['protospacer_A','protospacer_B']]
-    #get all references
-    
-    ref_listA=listA[listA['gene']==select_variant][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-    ref_listA = ref_listA[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-    ref_listA.columns=['gene','guide_type','protospacer_A','protospacer_B']
-        
-    ref_listB=listB[listB['gene']==select_variant][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-    ref_listB = ref_listB[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-    ref_listB.columns=['gene','guide_type','protospacer_A','protospacer_B']
-    
-    ref_listC=listC[listC['gene']==select_variant][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-    ref_listC = ref_listC[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-    ref_listC.columns=['gene','guide_type','protospacer_A','protospacer_B']
-    listA_concatenated_orig = pd.concat([ref_listA,ref_listB,ref_listC])
-
-    st.write('**Input** Guides (all 6 from 3 sets)')
-    st.markdown(table_edit,unsafe_allow_html=True)
-    tbl_disp(listA_concatenated_orig,select_variant,'ref_guides',0)
-    #st.table(listA_concatenated_orig)
-    
-    #now search from results for list a
-    #st.write(ref_listA)
-    ListARes = st.checkbox('Results For SetA',key=1)
-    if ListARes:
-        if len(ref_listA)>0:  
-            #st.table(ref_listA)
-            
-##########
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listA,listA_found_ref,listA_notfound_ref)
-            st.write('Selected Reference Guides for **Set A**')
-            st.table(ref_listA)
-            #tbl_disp(ref_listA,select_variant,'ReferenceGuides',0)
-            if res.shape[0]>0:
-                st.write('Matched to **GRCh38** Reference Guides for **Set A**')
-                tbl_disp(res,select_variant,'SetA_GRCh38')
-            elif res_mut.shape[0]>0:
-                st.write('Mutated to **GRCh38** Reference Guides for **Set A**')
-                st.markdown(caution1,unsafe_allow_html=True)
-                tbl_disp(res_mut,select_variant,'SetA_Mutated_GRCh38')
-            if res_notfound.shape[0]>0:
-                st.write('**SetA Guides Not Found in GRCh38**')
-                #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-                st.table(res_notfound)            
-##########            
-            
-            
-        #For LR
-##########
-            res_lr,res_mut_lr,res_notfound_lr,list_match_lr,list_mutated_lr=get_lists(ref_listA,listA_found_lr,listA_notfound_lr)
-            #st.write('Selected Reference Guides for **Set A**')
-            #tbl_disp(ref_listA,select_variant,'ReferenceGuides',0)
-            if res_lr.shape[0]>0:
-                st.write('Matched to **CHM13** Reference Guides for **Set A**')
-                tbl_disp(res_lr,select_variant,'SetA_CHM13')
-            elif res_mut_lr.shape[0]>0:
-                st.write('Mutated to **CHM13** Reference Guides for **Set A**')
-                st.markdown(caution1,unsafe_allow_html=True)
-                tbl_disp(res_mut_lr,select_variant,'SetA_Mutated_CHM13')
-            if res_notfound_lr.shape[0]>0:
-                st.write('**SetA Guides Not Found in CHM13**')
-                #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-                st.table(res_notfound_lr)            
-##########            
-        
-        
-#######
-            #NOW MERGE FROM GRCh38 and LR
-            merged_mutated_set=pd.merge(list_mutated,list_mutated_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-            merged_mutated_set = merged_mutated_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-            merged_match_set=pd.merge(list_match,list_match_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-            merged_match_set = merged_match_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-            if merged_match_set.shape[0]>0:        
-                #st.write('**Matched** Guides for **Set C** (*Each guide sequence has a trailing NGG*)')
-                st.write('**Matched** Guides for **Set A** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-                tbl_disp(merged_match_set,select_variant,'SetA_Matched_GRCh38_CHM13',0)
-                
-                #st.table(merged_match_seta)
-            elif merged_mutated_set.shape[0]>0:
-                #st.write('**Missmatched** Guides **Set C** (*Each guide sequence has a trailing NGG*)')
-                st.write('**Mutated** Guides for **Set A** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-                
-                tbl_disp(merged_mutated_set,select_variant,'SetA_Mutated_GRCh38_CHM13',0)
-
-########        
-
-        else:
-            st.write('**Gene: **'+select_variant+' Not found in listA')
-
-    
-    #list B
-    ListBRes = st.checkbox('Results For SetB',key=2)  
-    if ListBRes:  
-        if len(ref_listB)>0:
-##########
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listB,listB_found_ref,listB_notfound_ref)
-            st.write('Selected Reference Guides for **Set B**')
-            st.table(ref_listB)
-            #tbl_disp(ref_listB,select_variant,'ReferenceGuides',0)
-            if res.shape[0]>0:
-                st.write('Matched to **GRCh38** Reference Guides for **Set B**')
-                tbl_disp(res,select_variant,'SetB_GRCh38')
-            elif res_mut.shape[0]>0:
-                st.write('Mutated to **GRCh38** Reference Guides for **Set B**')
-                st.markdown(caution1,unsafe_allow_html=True)
-                tbl_disp(res_mut,select_variant,'SetA_Mutated_GRCh38')
-            if res_notfound.shape[0]>0:
-                st.write('**SetB Guides Not Found in GRCh38**')
-                #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-                st.table(res_notfound)            
-##########            
-            
-            
-        #For LR
-##########
-            res_lr,res_mut_lr,res_notfound_lr,list_match_lr,list_mutated_lr=get_lists(ref_listB,listB_found_lr,listB_notfound_lr)
-            #st.write('Selected Reference Guides for **Set A**')
-            #tbl_disp(ref_listA,select_variant,'ReferenceGuides',0)
-            if res_lr.shape[0]>0:
-                st.write('Matched to **CHM13** Reference Guides for **Set B**')
-                tbl_disp(res_lr,select_variant,'SetB_CHM13')
-            elif res_mut_lr.shape[0]>0:
-                st.write('Mutated to **CHM13** Reference Guides for **Set B**')
-                st.markdown(caution1,unsafe_allow_html=True)
-                tbl_disp(res_mut_lr,select_variant,'SetB_Mutated_CHM13')
-            if res_notfound_lr.shape[0]>0:
-                st.write('**SetB Guides Not Found in CHM13**')
-                #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-                st.table(res_notfound_lr)            
-##########            
-        
-        
-#######
-            #NOW MERGE FROM GRCh38 and LR
-            merged_mutated_set=pd.merge(list_mutated,list_mutated_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-            merged_mutated_set = merged_mutated_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-            merged_match_set=pd.merge(list_match,list_match_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-            merged_match_set = merged_match_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-            if merged_match_set.shape[0]>0:        
-                #st.write('**Matched** Guides for **Set C** (*Each guide sequence has a trailing NGG*)')
-                st.write('**Matched** Guides for **Set B** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-                tbl_disp(merged_match_set,select_variant,'SetB_Matched_GRCh38_CHM13',0)
-                
-                #st.table(merged_match_seta)
-            elif merged_mutated_set.shape[0]>0:
-                #st.write('**Missmatched** Guides **Set C** (*Each guide sequence has a trailing NGG*)')
-                st.write('**Mutated** Guides for **Set B** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-                
-                tbl_disp(merged_mutated_set,select_variant,'SetB_Mutated_GRCh38_CHM13',0)
-
-########        
-
-        else:
-            st.write('**Gene: **'+select_variant+' Not found in listB')
-            
-    ### list B   
-    
-    #list C
-    ListCRes = st.checkbox('Results For SetC',key=3)  
-    if ListCRes:
-        if len(ref_listC)>0:
-##########
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listC,listC_found_ref,listC_notfound_ref)
-            st.write('Selected Reference Guides for **Set C**')
-            st.table(ref_listC)
-            #tbl_disp(ref_listC,select_variant,'ReferenceGuides',0)
-            if res.shape[0]>0:
-                st.write('Matched to **GRCh38** Reference Guides for **Set C**')
-                tbl_disp(res,select_variant,'SetC_GRCh38')
-            elif res_mut.shape[0]>0:
-                st.write('Mutated to **GRCh38** Reference Guides for **Set C**')
-                st.markdown(caution1,unsafe_allow_html=True)
-                tbl_disp(res_mut,select_variant,'SetC_Mutated_GRCh38')
-            if res_notfound.shape[0]>0:
-                st.write('**SetC Guides Not Found in GRCh38**')
-                #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-                st.table(res_notfound)            
-##########            
-            
-            
-        #For LR
-##########
-            res_lr,res_mut_lr,res_notfound_lr,list_match_lr,list_mutated_lr=get_lists(ref_listC,listC_found_lr,listC_notfound_lr)
-            #st.write('Selected Reference Guides for **Set A**')
-            #tbl_disp(ref_listA,select_variant,'ReferenceGuides',0)
-            if res_lr.shape[0]>0:
-                st.write('Matched to **CHM13** Reference Guides for **Set C**')
-                tbl_disp(res_lr,select_variant,'SetC_CHM13')
-            elif res_mut_lr.shape[0]>0:
-                st.write('Mutated to **CHM13** Reference Guides for **Set C**')
-                st.markdown(caution1,unsafe_allow_html=True)
-                tbl_disp(res_mut_lr,select_variant,'SetC_Mutated_CHM13')
-            if res_notfound_lr.shape[0]>0:
-                st.write('**SetC Guides Not Found in CHM13**')
-                #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-                st.table(res_notfound_lr)            
-##########            
-        
-        
-#######
-            #NOW MERGE FROM GRCh38 and LR
-            merged_mutated_set=pd.merge(list_mutated,list_mutated_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-            merged_mutated_set = merged_mutated_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-            merged_match_set=pd.merge(list_match,list_match_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-            merged_match_set = merged_match_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-            if merged_match_set.shape[0]>0:        
-                #st.write('**Matched** Guides for **Set C** (*Each guide sequence has a trailing NGG*)')
-                st.write('**Matched** Guides for **Set C** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-                tbl_disp(merged_match_set,select_variant,'SetC_Matched_GRCh38_CHM13',0)
-                
-                #st.table(merged_match_seta)
-            elif merged_mutated_set.shape[0]>0:
-                #st.write('**Missmatched** Guides **Set C** (*Each guide sequence has a trailing NGG*)')
-                st.write('**Mutated** Guides for **Set C** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-                
-                tbl_disp(merged_mutated_set,select_variant,'SetC_Mutated_GRCh38_CHM13',0)
-
-########        
-
-        else:
-            st.write('**Gene: **'+select_variant+' Not found in listC')
-            
-        
-    ### list C   
-else:
-    select_mode = st.radio(
-    "Please select an option",
-    ('Select Single/Multiple Genes', 'Select All'))
-    #st.write('Please Select A **Single/Multiple/SelectAll** Reference Guides')
-    #get_table = pd.DataFrame(columns=['gene','sgID_A','protospacer_A','sgID_B','protospacer_B','sgID_AB'])
-    if select_mode=='Select Single/Multiple Genes':
-        st.markdown(table_edit,unsafe_allow_html=True)
-        get_table=tbl_disp(listA[['gene','sgID_A','protospacer_A','sgID_B','protospacer_B','sgID_AB']],'SetA','ReferenceGuides',0)  
-    
-        st.markdown(caution2,unsafe_allow_html=True)  
-    else:
-        st.markdown(table_edit,unsafe_allow_html=True)
-        get_table=listA[['gene','sgID_A','protospacer_A','sgID_B','protospacer_B','sgID_AB']]
-    
-        st.markdown(caution2,unsafe_allow_html=True)  
-        
-    
-    #st.write(get_table)
-    
-    ListARes = st.checkbox('Results For SetA',key=30)  
-    if ListARes and not isinstance(get_table, type(None)):#get_table!=None:        
-    #if ListARes and get_table.shape[0]>0:        
-        variant_set=get_table[['gene']]  
-        dft_a = pd.DataFrame(columns=['gene','guide_type','protospacer_A','protospacer_B'])    
-        dft_res=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_res_mut=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_notfound=pd.DataFrame(columns=['gene','ref_guide'])  
-        df_matched_guides_ref = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        df_mutated_guides_ref = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        #CHECK FOR GRCh38
-        for i in range(variant_set.shape[0]):
-            ref_listA=listA[listA['gene']==variant_set.iloc[i]['gene']][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-            ref_listA = ref_listA[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-            
-            ref_listA.columns=['gene','guide_type','protospacer_A','protospacer_B']
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listA,listA_found_ref,listA_notfound_ref)
-            dft_a=dft_a.append(ref_listA)  
-            if res.shape[0]>0:
-                dft_res=dft_res.append(res)
-            if res_mut.shape[0]>0:
-                dft_res_mut=dft_res_mut.append(res_mut)
-            if res_notfound.shape[0]>0:    
-                dft_notfound= dft_notfound.append(res_notfound)
-            if list_match.shape[0]>0:    
-                df_matched_guides_ref= df_matched_guides_ref.append(list_match)
-            if list_mutated.shape[0]>0:    
-                df_mutated_guides_ref= df_mutated_guides_ref.append(list_mutated)
-        
-        st.write('Selected Reference Guides for **Set A**')
-        tbl_disp(dft_a,'All','ReferenceGuides',0)
-        if dft_res.shape[0]>0:
-            st.write('Matched to **GRCh38** Reference Guides for **Set A**')
-            tbl_disp(dft_res,'select_genes','SetA_GRCh38')
-        elif dft_res_mut.shape[0]>0:
-            st.write('Mutated to **GRCh38** Reference Guides for **Set A**')
-            st.markdown(caution1,unsafe_allow_html=True)
-            tbl_disp(dft_res_mut,'select_genes','SetA_Mutated_GRCh38')
-        if dft_notfound.shape[0]>0:
-            st.write('**SetA Guides Not Found in GRCh38**')
-            #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-            st.table(dft_notfound)
-        #Now CHECK FOR CHM13
-        dft_a = pd.DataFrame(columns=['gene','guide_type','protospacer_A','protospacer_B'])    
-        dft_res=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_res_mut=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_notfound=pd.DataFrame(columns=['gene','ref_guide'])  
-        df_matched_guides_lr = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        df_mutated_guides_lr = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-
-        for i in range(variant_set.shape[0]):
-            ref_listA=listA[listA['gene']==variant_set.iloc[i]['gene']][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-            ref_listA = ref_listA[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-            
-            ref_listA.columns=['gene','guide_type','protospacer_A','protospacer_B']
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listA,listA_found_lr,listA_notfound_lr)
-            dft_a=dft_a.append(ref_listA)  
-            if res.shape[0]>0:
-                dft_res=dft_res.append(res)
-            if res_mut.shape[0]>0:
-                dft_res_mut=dft_res_mut.append(res_mut)
-            if res_notfound.shape[0]>0:
-                dft_notfound= dft_notfound.append(res_notfound)
-            if list_match.shape[0]>0:    
-                df_matched_guides_lr= df_matched_guides_lr.append(list_match)
-            if list_mutated.shape[0]>0:    
-                df_mutated_guides_lr= df_mutated_guides_lr.append(list_mutated)
-                
-        if dft_res.shape[0]>0:
-            st.write('Matched to **CHM13** Reference Guides for **Set A**')
-            tbl_disp(dft_res,'select_genes','SetA_CHM13')
-        elif dft_res_mut.shape[0]>0:
-            st.write('Mutated to **CHM13** Reference Guides for **Set A**')
-            st.markdown(caution1,unsafe_allow_html=True)
-            tbl_disp(dft_res_mut,'select_genes','SetA_Mutated_CHM13')
-        if dft_notfound.shape[0]>0:
-            st.write('**SetA Guides Not Found in CHM13**')
-            st.table(dft_notfound)
-        #NOW MERGE FROM GRCh38 and LR
-        merged_mutated_set=pd.merge(df_mutated_guides_ref,df_mutated_guides_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-        merged_mutated_set = merged_mutated_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-        merged_match_set=pd.merge(df_matched_guides_ref,df_matched_guides_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-        merged_match_set = merged_match_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-        if merged_match_set.shape[0]>0:        
-            #st.write('**Matched** Guides for **Set C** (*Each guide sequence has a trailing NGG*)')
-            st.write('**Matched** Guides for **Set A** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-            tbl_disp(merged_match_set,'select_genes','SetA_Matched_GRCh38_CHM13',0)
-            
-            #st.table(merged_match_seta)
-        elif merged_mutated_set.shape[0]>0:
-            #st.write('**Missmatched** Guides **Set C** (*Each guide sequence has a trailing NGG*)')
-            st.write('**Mutated** Guides for **Set A** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-            
-            tbl_disp(merged_mutated_set,'select_genes','SetA_Mutated_GRCh38_CHM13',0)
-    elif ListARes:
-        st.write("**Please select genes from the above table to begin**")
-
-    ListBRes = st.checkbox('Results For SetB',key=40)  
-    if ListBRes and not isinstance(get_table, type(None)):#get_table!=None:        
-        variant_set=get_table[['gene']]  
-        dft_b = pd.DataFrame(columns=['gene','guide_type','protospacer_A','protospacer_B'])    
-        dft_res=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_res_mut=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_notfound=pd.DataFrame(columns=['gene','ref_guide'])  
-        df_matched_guides_ref = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        df_mutated_guides_ref = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        #CHECK FOR GRCh38
-        for i in range(variant_set.shape[0]):
-            ref_listB=listB[listB['gene']==variant_set.iloc[i]['gene']][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-            ref_listB =ref_listB[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-            
-            ref_listB.columns=['gene','guide_type','protospacer_A','protospacer_B']
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listB,listB_found_ref,listB_notfound_ref)
-            dft_b=dft_b.append(ref_listB)  
-            if res.shape[0]>0:
-                dft_res=dft_res.append(res)
-            if res_mut.shape[0]>0:
-                dft_res_mut=dft_res_mut.append(res_mut)
-            if res_notfound.shape[0]>0:    
-                dft_notfound= dft_notfound.append(res_notfound)
-            if list_match.shape[0]>0:    
-                df_matched_guides_ref= df_matched_guides_ref.append(list_match)
-            if list_mutated.shape[0]>0:    
-                df_mutated_guides_ref= df_mutated_guides_ref.append(list_mutated)
-        
-        st.write('Selected Reference Guides for **Set B**')
-        tbl_disp(dft_b,'All','ReferenceGuides',0)
-        if dft_res.shape[0]>0:
-            st.write('Matched to **GRCh38** Reference Guides for **Set B**')
-            tbl_disp(dft_res,'select_genes','SetB_GRCh38')
-        elif dft_res_mut.shape[0]>0:
-            st.write('Mutated to **GRCh38** Reference Guides for **Set B**')
-            st.markdown(caution1,unsafe_allow_html=True)
-            tbl_disp(dft_res_mut,'select_genes','SetB_Mutated_GRCh38')
-        if dft_notfound.shape[0]>0:
-            st.write('**SetB Guides Not Found in GRCh38**')
-            #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-            st.table(dft_notfound)
-            
-        #Now CHECK FOR CHM13
-        dft_b = pd.DataFrame(columns=['gene','guide_type','protospacer_A','protospacer_B'])    
-        dft_res=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_res_mut=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_notfound=pd.DataFrame(columns=['gene','ref_guide'])  
-        df_matched_guides_lr = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        df_mutated_guides_lr = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-
-        for i in range(variant_set.shape[0]):
-            ref_listB=listB[listB['gene']==variant_set.iloc[i]['gene']][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-            ref_listB=ref_listB[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-            
-            ref_listB.columns=['gene','guide_type','protospacer_A','protospacer_B']
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listB,listB_found_lr,listB_notfound_lr)
-            dft_b=dft_b.append(ref_listB)  
-            if res.shape[0]>0:
-                dft_res=dft_res.append(res)
-            if res_mut.shape[0]>0:
-                dft_res_mut=dft_res_mut.append(res_mut)
-            if res_notfound.shape[0]>0:
-                dft_notfound= dft_notfound.append(res_notfound)
-            if list_match.shape[0]>0:    
-                df_matched_guides_lr= df_matched_guides_lr.append(list_match)
-            if list_mutated.shape[0]>0:    
-                df_mutated_guides_lr= df_mutated_guides_lr.append(list_mutated)
-                
-        if dft_res.shape[0]>0:
-            st.write('Matched to **CHM13** Reference Guides for **Set B**')
-            tbl_disp(dft_res,'select_genes','SetB_CHM13')
-        elif dft_res_mut.shape[0]>0:
-            st.write('Mutated to **CHM13** Reference Guides for **Set B**')
-            st.markdown(caution1,unsafe_allow_html=True)
-            tbl_disp(dft_res_mut,'select_genes','SetB_Mutated_CHM13')
-        if dft_notfound.shape[0]>0:
-            st.write('**SetB Guides Not Found in CHM13**')
-            st.table(dft_notfound)
-        #NOW MERGE FROM GRCh38 and LR
-        merged_mutated_set=pd.merge(df_mutated_guides_ref,df_mutated_guides_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-        merged_mutated_set = merged_mutated_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-        merged_match_set=pd.merge(df_matched_guides_ref,df_matched_guides_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-        merged_match_set = merged_match_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-        if merged_match_set.shape[0]>0:        
-            #st.write('**Matched** Guides for **Set C** (*Each guide sequence has a trailing NGG*)')
-            st.write('**Matched** Guides for **Set B** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-            tbl_disp(merged_match_set,'select_genes','SetB_Matched_GRCh38_CHM13',0)
-            
-            #st.table(merged_match_seta)
-        elif merged_mutated_set.shape[0]>0:
-            #st.write('**Missmatched** Guides **Set C** (*Each guide sequence has a trailing NGG*)')
-            st.write('**Mutated** Guides for **Set B** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-            #st.markdown(caution1,unsafe_allow_html=True)
-            tbl_disp(merged_mutated_set,'select_genes','SetB_Mutated_GRCh38_CHM13',0)
-            
-    elif ListBRes:
-        st.write("**Please select genes from the above table to begin**")
-            
-    ListCRes = st.checkbox('Results For SetC',key=50)  
-    if ListCRes and not isinstance(get_table, type(None)):#get_table!=None:        
-        variant_set=get_table[['gene']]  
-        dft_c = pd.DataFrame(columns=['gene','guide_type','protospacer_A','protospacer_B'])    
-        dft_res=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_res_mut=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_notfound=pd.DataFrame(columns=['gene','ref_guide'])  
-        df_matched_guides_ref = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        df_mutated_guides_ref = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        #CHECK FOR GRCh38
-        for i in range(variant_set.shape[0]):
-            ref_listC=listC[listC['gene']==variant_set.iloc[i]['gene']][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-            ref_listC =ref_listC[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-            
-            ref_listC.columns=['gene','guide_type','protospacer_A','protospacer_B']
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listC,listC_found_ref,listC_notfound_ref)
-            dft_c=dft_c.append(ref_listC)  
-            if res.shape[0]>0:
-                dft_res=dft_res.append(res)
-            if res_mut.shape[0]>0:
-                dft_res_mut=dft_res_mut.append(res_mut)
-            if res_notfound.shape[0]>0:    
-                dft_notfound= dft_notfound.append(res_notfound)
-            if list_match.shape[0]>0:    
-                df_matched_guides_ref= df_matched_guides_ref.append(list_match)
-            if list_mutated.shape[0]>0:    
-                df_mutated_guides_ref= df_mutated_guides_ref.append(list_mutated)
-        
-        st.write('Selected Reference Guides for **Set B**')
-        tbl_disp(dft_c,'All','ReferenceGuides',0)
-        if dft_res.shape[0]>0:
-            st.write('Matched to **GRCh38** Reference Guides for **Set C**')
-            tbl_disp(dft_res,'select_genes','SetC_GRCh38')
-        elif dft_res_mut.shape[0]>0:
-            st.write('Mutated to **GRCh38** Reference Guides for **Set C**')
-            st.markdown(caution1,unsafe_allow_html=True)
-            tbl_disp(dft_res_mut,'select_genes','SetC_Mutated_GRCh38')
-        if dft_notfound.shape[0]>0:
-            st.write('**SetC Guides Not Found in GRCh38**')
-            #tbl_disp(dft_notfound,'select_genes','SetA_Notfound_GRCh38')
-            st.table(dft_notfound)
-            
-        #Now CHECK FOR CHM13
-        dft_c = pd.DataFrame(columns=['gene','guide_type','protospacer_A','protospacer_B'])    
-        dft_res=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_res_mut=pd.DataFrame(columns=['sgID_1',	'sgRNA_1',	'chr_sgRNA_1',	'position_sgRNA_1',	'sgID_2',	'sgRNA_2',	'chr_sgRNA_2',	'position_sgRNA_2',	'sgID_1_2'])  
-        dft_notfound=pd.DataFrame(columns=['gene','ref_guide'])  
-        df_matched_guides_lr = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-        df_mutated_guides_lr = pd.DataFrame(columns=['gene','ref_guide',	'chr',	'position',	'mutated_guide',	'strand',	'num_mismatch'])
-
-        for i in range(variant_set.shape[0]):
-            ref_listC=listC[listC['gene']==variant_set.iloc[i]['gene']][['guide_type','protospacer_A','protospacer_B','sgID_AB']]
-            ref_listC=ref_listC[['sgID_AB','guide_type','protospacer_A','protospacer_B']]
-            
-            ref_listC.columns=['gene','guide_type','protospacer_A','protospacer_B']
-            res,res_mut,res_notfound,list_match,list_mutated=get_lists(ref_listC,listC_found_lr,listC_notfound_lr)
-            dft_c=dft_c.append(ref_listC)  
-            if res.shape[0]>0:
-                dft_res=dft_res.append(res)
-            if res_mut.shape[0]>0:
-                dft_res_mut=dft_res_mut.append(res_mut)
-            if res_notfound.shape[0]>0:
-                dft_notfound= dft_notfound.append(res_notfound)
-            if list_match.shape[0]>0:    
-                df_matched_guides_lr= df_matched_guides_lr.append(list_match)
-            if list_mutated.shape[0]>0:    
-                df_mutated_guides_lr= df_mutated_guides_lr.append(list_mutated)
-                
-        if dft_res.shape[0]>0:
-            st.write('Matched to **CHM13** Reference Guides for **Set C**')
-            tbl_disp(dft_res,'select_genes','SetC_CHM13')
-        elif dft_res_mut.shape[0]>0:
-            st.write('Mutated to **CHM13** Reference Guides for **Set C**')
-            st.markdown(caution1,unsafe_allow_html=True)
-            tbl_disp(dft_res_mut,'select_genes','SetC_Mutated_CHM13')
-        if dft_notfound.shape[0]>0:
-            st.write('**SetC Guides Not Found in CHM13**')
-            st.table(dft_notfound)
-        #NOW MERGE FROM GRCh38 and LR
-        merged_mutated_set=pd.merge(df_mutated_guides_ref,df_mutated_guides_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-        merged_mutated_set = merged_mutated_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-        merged_match_set=pd.merge(df_matched_guides_ref,df_matched_guides_lr, how="outer",on=["gene","ref_guide","chr"],suffixes=["_GRCh38",'_LR'])
-        merged_match_set = merged_match_set[['gene','ref_guide','chr','position_GRCh38','position_LR','strand_GRCh38','strand_LR','mutated_guide_GRCh38','mutated_guide_LR','num_mismatch_GRCh38','num_mismatch_LR']]
-        if merged_match_set.shape[0]>0:        
-            #st.write('**Matched** Guides for **Set C** (*Each guide sequence has a trailing NGG*)')
-            st.write('**Matched** Guides for **Set C** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-            tbl_disp(merged_match_set,'select_genes','SetC_Matched_GRCh38_CHM13',0)
-            
-            #st.table(merged_match_seta)
-        elif merged_mutated_set.shape[0]>0:
-            #st.write('**Missmatched** Guides **Set C** (*Each guide sequence has a trailing NGG*)')
-            st.write('**Mutated** Guides for **Set C** to both **GRCh38 and CHM13 references** (*Each guide sequence has a trailing NGG* and **leading G even if it is a missmatch**)')
-            #st.markdown(caution1,unsafe_allow_html=True)
-            tbl_disp(merged_mutated_set,'select_genes','SetC_Mutated_GRCh38_CHM13',0)
-    elif ListCRes:
-        st.write("**Please select genes from the above table to begin**")
-