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Copy pathanalysis_of_dRep_and_galah_results.py
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analysis_of_dRep_and_galah_results.py
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import pandas as pd
import os, sys
import matplotlib.pyplot as plt
from matplotlib_venn import venn2
import pprint
import pickle
def read_in_drep_cluster_table(path_to_drep_cluster_table,path_to_drep_RG_dir):
drep_RG=[]
drep_RG=os.listdir(path_to_drep_RG_dir)
if '.ipynb_checkpoints' in drep_RG:
drep_RG.remove('.ipynb_checkpoints')
return pd.read_csv(path_to_drep_cluster_table,sep=','),drep_RG
def read_in_galah_cluster_table(path_to_galah_cluster_table):
galah_cluster_table=[]
galah_cluster_table=pd.read_csv(path_to_galah_cluster_table,sep='\t',header=None,names=['RG','member'])
for i in range(len(galah_cluster_table)):
galah_cluster_table['RG'][i]=galah_cluster_table['RG'][i].split('/')[-1]
galah_cluster_table['member'][i]=galah_cluster_table['member'][i].split('/')[-1]
galah_RG=[]
[galah_RG.append(i) for i in galah_cluster_table['RG'] if i not in galah_RG]
return galah_cluster_table,galah_RG
def read_in_taxon_table(path_to_taxon_table):
return pd.read_csv(path_to_taxon_table,sep='\t')
def venn_plot_of_RG(drep_RG,galah_RG):
venn2([set(drep_RG),set(galah_RG)],set_labels=('drep_RG','galah_RG'))
def get_drep_or_galah_only_cluster_dict(drep_cluster_table,drep_RG,galah_cluster_table,galah_RG,\
show_drep=False,show_galah=False,return_drep=False,return_galah=False,return_same_mamber_cluster=False):
def mkdict(RG1,RG2,table):
table_type=len(table.columns)
diff=[i for i in RG1 if i not in RG2]
if len(diff)==0:
if table_type>2:
print('There are no drep only clusters, because drep_RG is a subset of galah_RG!')
else:
print('There are no galah only clusters, because galah_RG is a subset of drep_RG!')
else:
cluster={}.fromkeys(diff)
if table_type>2:
col1='genome' #table.columns[0]
col2='secondary_cluster' #table.columns[1]
else:
col1='member' #table.columns[1]
col2='RG' #table.columns[0]
for i in diff:
start_index=list(table[col1]).index(i)
cluster_members_index=[j for j in range(len(table)) if table[col2][start_index]==table[col2][j]]
cluster[i]=list(table[col1][cluster_members_index[0]:(cluster_members_index[-1]+1)])
return cluster
drep_result=mkdict(drep_RG,galah_RG,drep_cluster_table)
galah_result=mkdict(galah_RG,drep_RG,galah_cluster_table)
same_member_cluster={}
for i in drep_result:
for j in galah_result:
if sorted(drep_result[i])==sorted(galah_result[j]):
same_member_cluster[i]=drep_result[i]
break
if same_member_cluster:
print('\n**************')
print(f'There are {len(same_member_cluster)} clusters between {len(drep_result)} drep_only and {len(galah_result)} galah_only clusters with different RG but same members!\n')
pprint.pprint(same_member_cluster)
print('**************\n')
else:
print('\n**************')
print(f'There are no clusters with different RG but same members!')
print('**************\n')
if return_same_mamber_cluster:
return same_member_cluster
returns=[]
if show_drep:
print('\n**************')
print(f'dRep_only: total= {len(drep_result)} results')
pprint.pprint(drep_result)
print('**************\n')
if show_galah:
print('\n**************')
print(f'galah_only: total= {len(galah_result)} results')
pprint.pprint(galah_result)
print('**************\n')
if return_drep:
returns.append(drep_result)
if return_galah:
returns.append(galah_result)
if returns:
return returns
def get_intersection_cluster_dict_of_drep_or_galah(drep_cluster_table,drep_RG,galah_cluster_table,galah_RG,\
show_inter_cluster_drep=False,show_inter_cluster_galah=False,show_diff_of_inter=False,return_drep=False,return_galah=False,return_diff_or_same=None):
def mkdict_drep(RG1,RG2,table):
inter=[i for i in RG1 if i in RG2]
col1='genome' #table.columns[0]
col2='secondary_cluster' #table.columns[1]
inter_cluster_drep={}.fromkeys(inter)
for i in inter:
start_index=list(table[col1]).index(i)
cluster_members_index=[j for j in range(len(table)) if table[col2][start_index]==table[col2][j]]
inter_cluster_drep[i]=list(table[col1][cluster_members_index[0]:(cluster_members_index[-1]+1)])
return inter_cluster_drep
def mkdict_galah(RG1,RG2,table):
diff=[i for i in RG1 if i not in RG2]
col1='RG'#table.columns[0]
col2='member'#table.columns[1]
i=0
j=0
depth_of_cluster=[[]]
while i<(len(table)-1):
if table[col1][i]!=table[col1][i+1]:
depth_of_cluster.append([i-j,j+1])
i=i+1
j=0
else:
i=i+1
j=j+1
if j==0:
depth_of_cluster.append([i,j+1])
else:
depth_of_cluster.append([i-j,j+1])
depth_of_cluster.pop(0)
index_to_delet=[]
for i in diff:
index_to_delet.append(RG1.index(i))
depth_of_cluster=[depth_of_cluster[i] for i in range(len(depth_of_cluster)) if i not in index_to_delet]
inter_cluster_galah={}
for i in depth_of_cluster:
inter_cluster_galah[table[col1][i[0]]]=list(table[col2][i[0]:(i[0]+i[1])])
return inter_cluster_galah
returns=[]
if show_inter_cluster_drep:
result=mkdict_drep(drep_RG,galah_RG,drep_cluster_table)
print('\n**************')
print(f'dRep_inter: total= {len(result)} results')
pprint.pprint(result)
print('**************\n')
if show_inter_cluster_galah:
result=mkdict_galah(galah_RG,drep_RG,galah_cluster_table)
print('\n**************')
print(f'galah_inter: total= {len(result)} results')
pprint.pprint(result)
print('**************\n')
if show_diff_of_inter:
inter=[i for i in drep_RG if i in galah_RG]
inter_cluster_drep=mkdict_drep(drep_RG,galah_RG,drep_cluster_table)
inter_cluster_galah=mkdict_galah(galah_RG,drep_RG,galah_cluster_table)
result=[('*',k,'<dRep>:',inter_cluster_drep[k],'<galah>:',inter_cluster_galah[k]) for k in inter if sorted(inter_cluster_drep[k]) != sorted(inter_cluster_galah[k])]
print('\n**************')
print(f'difference between clusters of intersections: total= {len(result)} results')
pprint.pprint(result)
print('**************\n')
if return_drep:
returns.append(mkdict_drep(drep_RG,galah_RG,drep_cluster_table))
if return_galah:
returns.append(mkdict_galah(galah_RG,drep_RG,galah_cluster_table))
if return_diff_or_same:
inter=[i for i in drep_RG if i in galah_RG]
inter_cluster_drep=mkdict_drep(drep_RG,galah_RG,drep_cluster_table)
inter_cluster_galah=mkdict_galah(galah_RG,drep_RG,galah_cluster_table)
if return_diff_or_same=='diff':
return [(k,inter_cluster_drep[k],inter_cluster_galah[k]) for k in inter if sorted(inter_cluster_drep[k]) != sorted(inter_cluster_galah[k])]
elif return_diff_or_same=='same':
dict_list=[{k:inter_cluster_drep[k]} for k in inter if sorted(inter_cluster_drep[k]) == sorted(inter_cluster_galah[k])]
result=dict_list.pop()
for i in range(len(dict_list)):
result.update(dict_list.pop())
same_member_cluster=get_drep_or_galah_only_cluster_dict(drep_cluster_table,drep_RG,galah_cluster_table,galah_RG,return_same_mamber_cluster=True)
if same_member_cluster:
result.update(same_member_cluster)
print('\n**************')
print(f'\nAdding {len(same_member_cluster)} clusters with different RG but same members to the "same" result set!\n')
print('**************\n')
return result
else:
print('Please input the selection (\'diff\'/\'same\') you want to return!')
if returns:
return returns
def taxonomy_verification(taxon_table,diff=None,same=None,show_diff=None,show_same=None,check_cluster_replication=False,write_to_file=None):
def taxon_diff(taxon_table,diff):
same_taxon={}
diff_taxon={}
for i in range(len(diff)):
members=diff[i][1] if len(diff[i][1])>len(diff[i][2]) else diff[i][2]
taxon=[]
for j in members:
taxon.append(taxon_table['GTDB classification'][list(taxon_table['user_genome']).index(j)])
if len(list(set(taxon)))==1:
result={}
result['RG']=diff[i][0]
result['same species']=list(set(taxon))
result['dRep']=diff[i][1]
result['galah']=diff[i][2]
same_taxon[f'result{len(same_taxon)+1}']=result
else:
result={}
result['RG']=diff[i][0]
result['each\'s species']=taxon
result['dRep']=diff[i][1]
result['galah']=diff[i][2]
diff_taxon[f'result{len(diff_taxon)+1}']=result
return same_taxon,diff_taxon
def taxon_same(taxon_table,same):
same_taxon_single={}
same_taxon_multi={}
diff_taxon={}
single_RG_count=0
for i in same.keys():
if len(same[i])==1:
taxon=[]
taxon.append(taxon_table['GTDB classification'][list(taxon_table['user_genome']).index(i)])
result={}
result['RG']=i
result['species']=taxon
result['member']=i
same_taxon_single[f'result{len(same_taxon_single)+1}']=result
single_RG_count=single_RG_count+1
else:
taxon=[]
for j in same[i]:
taxon.append(taxon_table['GTDB classification'][list(taxon_table['user_genome']).index(j)])
if len(list(set(taxon)))==1:
result={}
result['RG']=i
result['species']=list(set(taxon))
result['members']=same[i]
same_taxon_multi[f'result{len(same_taxon_multi)+1}']=result
else:
result={}
result['RG']=i
result['each\'s species']=taxon
result['dRep']=same[i]
diff_taxon[f'result{len(diff_taxon)+1}']=result
return same_taxon_single,same_taxon_multi,single_RG_count,diff_taxon
if show_diff:
same_taxon,diff_taxon=taxon_diff(taxon_table,diff)
print('\n**************')
print('Show: RG same but members not same results')
print('-------------')
print(f'| S | There are total {len(same_taxon)+len(diff_taxon)} results below:')
print(f'| T | Cluster\'s members from same species: {len(same_taxon)}; ')
print(f'| A | Cluster\'s members from different species: {len(diff_taxon)}; ')
print('| T |')
if show_diff=='all':
print('-------------')
print(f'<same species>: total= {len(same_taxon)} results')
pprint.pprint(same_taxon)
print('-------------')
print(f'<different species>: total= {len(diff_taxon)} results')
pprint.pprint(diff_taxon)
print('**************\n')
if show_same:
same_taxon_single,same_taxon_multi,single_RG_count,diff_taxon=taxon_same(taxon_table,same)
print('\n**************')
print('Show: RG and members same results')
print('-------------')
print(f'| S | There are total {single_RG_count+len(same_taxon_multi)+len(diff_taxon)} results below:')
print(f'| T | Cluster with only one member: {single_RG_count}; ')
print(f'| A | Cluster with at least two members and are from same species: {len(same_taxon_multi)}; ')
print(f'| T | Cluster\'s members from different species: {len(diff_taxon)}; ')
print('-------------')
if show_same=='simple':
print(f'Omitting {single_RG_count} results of one member clusters')
print('-------------')
print(f'<same species>: total= {len(same_taxon_multi)} results')
pprint.pprint(same_taxon_multi)
print('-------------')
print(f'<different species>: total= {len(diff_taxon)} results')
pprint.pprint(diff_taxon)
elif show_same=='all':
print(f'<one member>: total= {single_RG_count} results')
pprint.pprint(same_taxon_single)
print('-------------')
print(f'<same species>: total= {len(same_taxon_multi)} results')
pprint.pprint(same_taxon_multi)
print('-------------')
print(f'<different species>: total= {len(diff_taxon)} results')
pprint.pprint(diff_taxon)
else:
print('Please select \'simple\' or \'all\' mode to print results')
print('**************\n')
def species_point_to_result_dict(same_taxon):
species_point_to_result={}
replication_count=0
for i in same_taxon:
species_name=same_taxon[i]['species'][0]
if species_name in species_point_to_result:
species_point_to_result[species_name].append(i)
replication_count=replication_count+1
else:
species_point_to_result[species_name]=[i]
return species_point_to_result,replication_count
def replication_result_dict(same_taxon,species_point_to_result):
replication_result={}
for i in species_point_to_result:
per_species_result=species_point_to_result[i]
if len(per_species_result)>1:
result={}
result['result count']=len(per_species_result)
result['result number of <one member> or <same species>']=per_species_result
result['RG']=[]
for j in per_species_result:
result['RG'].append(same_taxon[j]['RG'])
result['species']=i
replication_result[f'result{len(replication_result)+1}']=result
return replication_result
if check_cluster_replication:
same_taxon_single,same_taxon_multi=taxon_same(taxon_table,same)[0:2]
species_point_to_result_single,replication_count_single=species_point_to_result_dict(same_taxon_single)
species_point_to_result_multi,replication_count_multi=species_point_to_result_dict(same_taxon_multi)
# print(species_point_to_result_single,replication_count_single)
# print('-------------')
# print(species_point_to_result_multi,replication_count_multi)
if replication_count_single>0:
replication_result_single=replication_result_dict(same_taxon_single,species_point_to_result_single)
if replication_count_multi>0:
replication_result_multi=replication_result_dict(same_taxon_multi,species_point_to_result_multi)
print('-------------')
print('<check results>')
if replication_count_single>0 and replication_count_multi==0:
print(f'There are total {len(replication_result_single)} replicate species between the set of <one member> clusters!')
print(f'There are no replicate species between the set of <same species> clusters!')
pprint.pprint(replication_result_single)
elif replication_count_single==0 and replication_count_multi>0:
print(f'There are no replicate species between the set of <one member> clusters!')
print(f'There are total {len(replication_result_multi)} replicate species between the set of <same species> clusters!')
pprint.pprint(replication_result_multi)
elif replication_count_single>0 and replication_count_multi>0:
print(f'There are total {len(replication_result_single)} and {len(replication_result_multi)} replicate species between the set of <one member> and <same species> clusters!')
print(f'<one member>: {len(replication_result_single)} results')
pprint.pprint(replication_result_single)
print('-------------')
print(f'<same species>: {len(replication_result_multi)} results')
pprint.pprint(replication_result_multi)
else:
print('There are no replicate species between all same species clusters.')
if write_to_file:
if write_to_file=='CC_and_PC':
same_taxon=taxon_diff(taxon_table,diff)[0]
same_taxon_multi=taxon_same(taxon_table,same)[1]
with open('candidate_cluster.pkl','wb') as f:
pickle.dump(same_taxon,f)
with open('perfect_cluster.pkl','wb') as f:
pickle.dump(same_taxon_multi,f)
print('Candidate and perfect cluster were already written to files: candidate_cluster.pkl perfect_cluster.pkl!')
else:
print("Please input option to write files!")
def main():
# assembler_name=['megahit','metaspades']
# binner_name=['dastools','metabat2']
# plt.ion()
# for i in assembler_name:
# for j in binner_name:
# path_to_drep_cluster_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/shaoyanhan/metapitest1/metapiin_temp/results/10.dereplicate/mags/hmq.bins.{i}.{j}.drep.out/data_tables/Cdb.csv'
# path_to_galah_cluster_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/shaoyanhan/metapitest1/metapiin_temp/results/10.dereplicate_galah/{i}_{j}/output-cluster-definition.tsv'
# path_to_drep_RG_dir=f'/hwfssz1/ST_META/P18Z10200N0127_MA/shaoyanhan/metapitest1/metapiin_temp/results/10.dereplicate/mags/hmq.bins.{i}.{j}.drep.out/dereplicated_genomes'
# path_to_taxon_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/shaoyanhan/metapitest1/metapiin_temp/results/09.classify/report/bins_hmq.{i}.{j}.gtdbtk.all.tsv'
# a1,a2=read_in_drep_cluster_table(path_to_drep_cluster_table,path_to_drep_RG_dir)
# b1,b2=read_in_galah_cluster_table(path_to_galah_cluster_table)
# c=read_in_taxon_table(path_to_taxon_table)
# # print(a1,a2,b1,b2)
# print(f'{i}_{j}')
# venn_plot_of_RG(a2,b2)
# plt.pause(.2)
# # print('**************')
# # get_drep_or_galah_only_cluster_dict(a1,a2,b1,b2,show_drep=True,show_galah=True)
# print('**************')
# get_intersection_cluster_dict_of_drep_or_galah(a1,a2,b1,b2,show_inter_cluster_drep=False,show_inter_cluster_galah=False,show_diff_of_inter=True)
# # print('**************')
# # same=get_intersection_cluster_dict_of_drep_or_galah(a1,a2,b1,b2,return_diff_or_same='same')
# # diff=get_intersection_cluster_dict_of_drep_or_galah(a1,a2,b1,b2,return_diff_or_same='diff')
# # taxonomy_verification(c,diff,same,check_cluster_replication=True)
# print('**************\n')
# plt.ioff()
# plt.show()
#CAMI
path_to_drep_cluster_table=f'/store/yhshao/META/metapi_result_cami/drep_vamb_no_graphbin_beyond_50_completeness_no_contamination/data_tables/Cdb.csv'
path_to_galah_cluster_table=f'/store/yhshao/META/metapi_result_cami/galah_vamb_no_graphbin_beyond_50_completeness_no_contamination/cluster.tsv'
path_to_drep_RG_dir=f'/store/yhshao/META/metapi_result_cami/drep_vamb_no_graphbin_beyond_50_completeness_no_contamination/dereplicated_genomes/'
path_to_taxon_table=f'/store/yhshao/META/metapi_result_cami/gtdbtk.bac120.summary.tsv'
#ANI95
# path_to_drep_cluster_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_drep/ANI95/data_tables/Cdb.csv'
# path_to_galah_cluster_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools.tsv'
# path_to_drep_RG_dir=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_drep/ANI95/dereplicated_genomes'
# path_to_taxon_table=f'/zfssz3/ST_META/ST_META_CD/PROJECT/P18Z10200N0127_ZJ/vagina/vagina_mag/results/09.classify/report/bins_hmq.metaspades.dastools.gtdbtk.all.tsv'
#as_mt_qh
# path_to_drep_cluster_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_as_mt_qh_drep_galah/drep/data_tables/Cdb.csv'
# path_to_galah_cluster_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_as_mt_qh_drep_galah/galah/cluster-definition.tsv'
# path_to_drep_RG_dir=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_as_mt_qh_drep_galah/drep/dereplicated_genomes'
# path_to_taxon_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_as_mt_qh_drep_galah/cluster_mag_dastools_as_mt_qh.taxonmy.tsv'
# ANI99
# path_to_drep_cluster_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_drep/ANI99/data_tables/Cdb.csv'
# path_to_galah_cluster_table=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_drep/galah_ani99/cluster-definition.tsv'
# path_to_drep_RG_dir=f'/hwfssz1/ST_META/P18Z10200N0127_MA/zhujie/vagina/vagina_mag_analysis/assay/cluster/cluster_mag_dastools_drep/ANI99/dereplicated_genomes'
# path_to_taxon_table=f'/zfssz3/ST_META/ST_META_CD/PROJECT/P18Z10200N0127_ZJ/vagina/vagina_mag/results/09.classify/report/bins_hmq.metaspades.dastools.gtdbtk.all.tsv'
a1,a2=read_in_drep_cluster_table(path_to_drep_cluster_table,path_to_drep_RG_dir)
b1,b2=read_in_galah_cluster_table(path_to_galah_cluster_table)
c=read_in_taxon_table(path_to_taxon_table)
plt.ion()
venn_plot_of_RG(a2,b2)
plt.ioff()
plt.show()
get_drep_or_galah_only_cluster_dict(a1,a2,b1,b2,show_drep=True,show_galah=True)
get_intersection_cluster_dict_of_drep_or_galah(a1,a2,b1,b2,show_inter_cluster_drep=True,show_inter_cluster_galah=True,show_diff_of_inter=True)
same=get_intersection_cluster_dict_of_drep_or_galah(a1,a2,b1,b2,return_diff_or_same='same')
diff=get_intersection_cluster_dict_of_drep_or_galah(a1,a2,b1,b2,return_diff_or_same='diff')
taxonomy_verification(c,diff,same,show_diff='all',show_same='all',check_cluster_replication=True,write_to_file='CC_and_PC')
if __name__=='__main__':
main()
#Example output of this workflow:
#Draw the venn picture of dRep and galah RG
# **************
# There are 3 clusters between 3 drep_only and 3 galah_only clusters with different RG but same members!
# {'CAMI_UT_2.metaspades.maxbin2.bin.1.fa': ['CAMI_UT_0.metaspades.concoct.bin.42.fa',
# 'CAMI_UT_2.metaspades.maxbin2.bin.1.fa',
# 'CAMI_UT_22.metaspades.maxbin2.bin.1.fa'],
# 'CAMI_UT_22.metaspades.concoct.bin.21.fa': ['CAMI_UT_2.metaspades.vamb.bin.2.fa',
# 'CAMI_UT_22.metaspades.concoct.bin.21.fa'],
# 'CAMI_UT_5.metaspades.vamb.bin.14.fa': ['CAMI_UT_25.metaspades.vamb.bin.16.fa',
# 'CAMI_UT_3.metaspades.vamb.bin.20.fa',
# 'CAMI_UT_5.metaspades.vamb.bin.14.fa']}
# **************
# **************
# dRep_only: total= 3 results
# {'CAMI_UT_2.metaspades.maxbin2.bin.1.fa': ['CAMI_UT_0.metaspades.concoct.bin.42.fa',
# 'CAMI_UT_2.metaspades.maxbin2.bin.1.fa',
# 'CAMI_UT_22.metaspades.maxbin2.bin.1.fa'],
# 'CAMI_UT_22.metaspades.concoct.bin.21.fa': ['CAMI_UT_2.metaspades.vamb.bin.2.fa',
# 'CAMI_UT_22.metaspades.concoct.bin.21.fa'],
# 'CAMI_UT_5.metaspades.vamb.bin.14.fa': ['CAMI_UT_25.metaspades.vamb.bin.16.fa',
# 'CAMI_UT_3.metaspades.vamb.bin.20.fa',
# 'CAMI_UT_5.metaspades.vamb.bin.14.fa']}
# **************
# **************
# galah_only: total= 3 results
# {'CAMI_UT_2.metaspades.vamb.bin.2.fa': ['CAMI_UT_2.metaspades.vamb.bin.2.fa',
# 'CAMI_UT_22.metaspades.concoct.bin.21.fa'],
# 'CAMI_UT_22.metaspades.maxbin2.bin.1.fa': ['CAMI_UT_22.metaspades.maxbin2.bin.1.fa',
# 'CAMI_UT_0.metaspades.concoct.bin.42.fa',
# 'CAMI_UT_2.metaspades.maxbin2.bin.1.fa'],
# 'CAMI_UT_3.metaspades.vamb.bin.20.fa': ['CAMI_UT_3.metaspades.vamb.bin.20.fa',
# 'CAMI_UT_5.metaspades.vamb.bin.14.fa',
# 'CAMI_UT_25.metaspades.vamb.bin.16.fa']}
# **************
# **************
# dRep_inter: total= 14 results
# {'CAMI_UT_2.metaspades.concoct.bin.21.fa': ['CAMI_UT_2.metaspades.concoct.bin.21.fa',
# 'CAMI_UT_24.metaspades.metabat2.bin.10.fa',
# 'CAMI_UT_25.metaspades.maxbin2.bin.1_sub.fa'],
# 'CAMI_UT_2.metaspades.maxbin2.bin.14.fa': ['CAMI_UT_2.metaspades.maxbin2.bin.14.fa'],
# 'CAMI_UT_2.metaspades.metabat2.bin.10_sub.fa': ['CAMI_UT_2.metaspades.metabat2.bin.10_sub.fa'],
# 'CAMI_UT_2.metaspades.metabat2.bin.22.fa': ['CAMI_UT_2.metaspades.metabat2.bin.22.fa',
# 'CAMI_UT_25.metaspades.concoct.bin.46_sub.fa',
# 'CAMI_UT_3.metaspades.vamb.bin.13_sub.fa'],
# 'CAMI_UT_2.metaspades.vamb.bin.17.fa': ['CAMI_UT_2.metaspades.vamb.bin.17.fa'],
# 'CAMI_UT_24.metaspades.metabat2.bin.5.fa': ['CAMI_UT_22.metaspades.maxbin2.bin.2_sub.fa',
# 'CAMI_UT_24.metaspades.metabat2.bin.5.fa',
# 'CAMI_UT_25.metaspades.metabat2.bin.15.fa',
# 'CAMI_UT_3.metaspades.metabat2.bin.6.fa'],
# 'CAMI_UT_24.metaspades.metabat2.bin.6_sub.fa': ['CAMI_UT_24.metaspades.metabat2.bin.6_sub.fa',
# 'CAMI_UT_25.metaspades.maxbin2.bin.6.fa',
# 'CAMI_UT_5.metaspades.metabat2.bin.6_sub.fa'],
# 'CAMI_UT_25.metaspades.metabat2.bin.7.fa': ['CAMI_UT_24.metaspades.metabat2.bin.15.fa',
# 'CAMI_UT_25.metaspades.metabat2.bin.7.fa',
# 'CAMI_UT_3.metaspades.maxbin2.bin.6_sub.fa',
# 'CAMI_UT_5.metaspades.vamb.bin.8.fa'],
# 'CAMI_UT_3.metaspades.concoct.bin.25.fa': ['CAMI_UT_3.metaspades.concoct.bin.25.fa',
# 'CAMI_UT_6.metaspades.concoct.bin.14.fa'],
# 'CAMI_UT_3.metaspades.concoct.bin.3.fa': ['CAMI_UT_3.metaspades.concoct.bin.3.fa'],
# 'CAMI_UT_6.metaspades.concoct.bin.12.fa': ['CAMI_UT_6.metaspades.concoct.bin.12.fa'],
# 'CAMI_UT_6.metaspades.concoct.bin.2.fa': ['CAMI_UT_6.metaspades.concoct.bin.2.fa'],
# 'CAMI_UT_6.metaspades.maxbin2.bin.1.fa': ['CAMI_UT_6.metaspades.maxbin2.bin.1.fa'],
# 'CAMI_UT_6.metaspades.maxbin2.bin.3.fa': ['CAMI_UT_6.metaspades.maxbin2.bin.3.fa']}
# **************
# **************
# galah_inter: total= 14 results
# {'CAMI_UT_2.metaspades.concoct.bin.21.fa': ['CAMI_UT_2.metaspades.concoct.bin.21.fa',
# 'CAMI_UT_24.metaspades.metabat2.bin.10.fa',
# 'CAMI_UT_25.metaspades.maxbin2.bin.1_sub.fa'],
# 'CAMI_UT_2.metaspades.maxbin2.bin.14.fa': ['CAMI_UT_2.metaspades.maxbin2.bin.14.fa'],
# 'CAMI_UT_2.metaspades.metabat2.bin.10_sub.fa': ['CAMI_UT_2.metaspades.metabat2.bin.10_sub.fa'],
# 'CAMI_UT_2.metaspades.metabat2.bin.22.fa': ['CAMI_UT_2.metaspades.metabat2.bin.22.fa',
# 'CAMI_UT_3.metaspades.vamb.bin.13_sub.fa',
# 'CAMI_UT_25.metaspades.concoct.bin.46_sub.fa'],
# 'CAMI_UT_2.metaspades.vamb.bin.17.fa': ['CAMI_UT_2.metaspades.vamb.bin.17.fa'],
# 'CAMI_UT_24.metaspades.metabat2.bin.5.fa': ['CAMI_UT_24.metaspades.metabat2.bin.5.fa',
# 'CAMI_UT_3.metaspades.metabat2.bin.6.fa',
# 'CAMI_UT_25.metaspades.metabat2.bin.15.fa',
# 'CAMI_UT_22.metaspades.maxbin2.bin.2_sub.fa'],
# 'CAMI_UT_24.metaspades.metabat2.bin.6_sub.fa': ['CAMI_UT_24.metaspades.metabat2.bin.6_sub.fa',
# 'CAMI_UT_5.metaspades.metabat2.bin.6_sub.fa',
# 'CAMI_UT_25.metaspades.maxbin2.bin.6.fa'],
# 'CAMI_UT_25.metaspades.metabat2.bin.7.fa': ['CAMI_UT_25.metaspades.metabat2.bin.7.fa',
# 'CAMI_UT_24.metaspades.metabat2.bin.15.fa',
# 'CAMI_UT_5.metaspades.vamb.bin.8.fa',
# 'CAMI_UT_3.metaspades.maxbin2.bin.6_sub.fa'],
# 'CAMI_UT_3.metaspades.concoct.bin.25.fa': ['CAMI_UT_3.metaspades.concoct.bin.25.fa',
# 'CAMI_UT_6.metaspades.concoct.bin.14.fa'],
# 'CAMI_UT_3.metaspades.concoct.bin.3.fa': ['CAMI_UT_3.metaspades.concoct.bin.3.fa'],
# 'CAMI_UT_6.metaspades.concoct.bin.12.fa': ['CAMI_UT_6.metaspades.concoct.bin.12.fa'],
# 'CAMI_UT_6.metaspades.concoct.bin.2.fa': ['CAMI_UT_6.metaspades.concoct.bin.2.fa'],
# 'CAMI_UT_6.metaspades.maxbin2.bin.1.fa': ['CAMI_UT_6.metaspades.maxbin2.bin.1.fa'],
# 'CAMI_UT_6.metaspades.maxbin2.bin.3.fa': ['CAMI_UT_6.metaspades.maxbin2.bin.3.fa']}
# **************
# **************
# difference between clusters of intersections: total= 0 results
# []
# **************
# **************
# There are 3 clusters between 3 drep_only and 3 galah_only clusters with different RG but same members!
# {'CAMI_UT_2.metaspades.maxbin2.bin.1.fa': ['CAMI_UT_0.metaspades.concoct.bin.42.fa',
# 'CAMI_UT_2.metaspades.maxbin2.bin.1.fa',
# 'CAMI_UT_22.metaspades.maxbin2.bin.1.fa'],
# 'CAMI_UT_22.metaspades.concoct.bin.21.fa': ['CAMI_UT_2.metaspades.vamb.bin.2.fa',
# 'CAMI_UT_22.metaspades.concoct.bin.21.fa'],
# 'CAMI_UT_5.metaspades.vamb.bin.14.fa': ['CAMI_UT_25.metaspades.vamb.bin.16.fa',
# 'CAMI_UT_3.metaspades.vamb.bin.20.fa',
# 'CAMI_UT_5.metaspades.vamb.bin.14.fa']}
# **************
# **************
# Adding 3 clusters with different RG but same members to the "same" result set!
# **************
# **************
# Show: RG same but members not same results
# -------------
# | S | There are total 0 results below:
# | T | Cluster's members from same species: 0;
# | A | Cluster's members from different species: 0;
# | T |
# -------------
# <same species>: total= 0 results
# {}
# -------------
# <different species>: total= 0 results
# {}
# **************
# **************
# Show: RG and members same results
# -------------
# | S | There are total 17 results below:
# | T | Cluster with only one member: 8;
# | A | Cluster with at least two members and are from same species: 9;
# | T | Cluster's members from different species: 0;
# -------------
# <one member>: total= 8 results
# {'result1': {'RG': 'CAMI_UT_6.metaspades.maxbin2.bin.3.fa',
# 'member': 'CAMI_UT_6.metaspades.maxbin2.bin.3.fa',
# 'species': ['d__Bacteria;p__Firmicutes_C;c__Negativicutes;o__Veillonellales;f__Dialisteraceae;g__Dialister_A;s__Dialister_A '
# 'pneumosintes']},
# 'result2': {'RG': 'CAMI_UT_6.metaspades.concoct.bin.2.fa',
# 'member': 'CAMI_UT_6.metaspades.concoct.bin.2.fa',
# 'species': ['d__Bacteria;p__Actinobacteriota;c__Coriobacteriia;o__Coriobacteriales;f__Eggerthellaceae;g__Denitrobacterium;s__Denitrobacterium '
# 'detoxificans']},
# 'result3': {'RG': 'CAMI_UT_6.metaspades.concoct.bin.12.fa',
# 'member': 'CAMI_UT_6.metaspades.concoct.bin.12.fa',
# 'species': ['d__Bacteria;p__Actinobacteriota;c__Coriobacteriia;o__Coriobacteriales;f__Eggerthellaceae;g__Slackia;s__Slackia '
# 'heliotrinireducens']},
# 'result4': {'RG': 'CAMI_UT_3.metaspades.concoct.bin.3.fa',
# 'member': 'CAMI_UT_3.metaspades.concoct.bin.3.fa',
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Mycoplasmatales;f__Mycoplasmoidaceae;g__Ureaplasma;s__Ureaplasma '
# 'parvum']},
# 'result5': {'RG': 'CAMI_UT_6.metaspades.maxbin2.bin.1.fa',
# 'member': 'CAMI_UT_6.metaspades.maxbin2.bin.1.fa',
# 'species': ['d__Bacteria;p__Bacteroidota;c__Bacteroidia;o__Bacteroidales;f__Bacteroidaceae;g__Prevotella;s__Prevotella '
# 'intermedia']},
# 'result6': {'RG': 'CAMI_UT_2.metaspades.vamb.bin.17.fa',
# 'member': 'CAMI_UT_2.metaspades.vamb.bin.17.fa',
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Limosilactobacillus;s__Limosilactobacillus '
# 'mucosae']},
# 'result7': {'RG': 'CAMI_UT_2.metaspades.metabat2.bin.10_sub.fa',
# 'member': 'CAMI_UT_2.metaspades.metabat2.bin.10_sub.fa',
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lacticaseibacillus;s__Lacticaseibacillus '
# 'paracasei']},
# 'result8': {'RG': 'CAMI_UT_2.metaspades.maxbin2.bin.14.fa',
# 'member': 'CAMI_UT_2.metaspades.maxbin2.bin.14.fa',
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lacticaseibacillus;s__Lacticaseibacillus '
# 'rhamnosus']}}
# -------------
# <same species>: total= 9 results
# {'result1': {'RG': 'CAMI_UT_2.metaspades.metabat2.bin.22.fa',
# 'members': ['CAMI_UT_2.metaspades.metabat2.bin.22.fa',
# 'CAMI_UT_25.metaspades.concoct.bin.46_sub.fa',
# 'CAMI_UT_3.metaspades.vamb.bin.13_sub.fa'],
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lactobacillus;s__Lactobacillus '
# 'helveticus']},
# 'result2': {'RG': 'CAMI_UT_24.metaspades.metabat2.bin.5.fa',
# 'members': ['CAMI_UT_22.metaspades.maxbin2.bin.2_sub.fa',
# 'CAMI_UT_24.metaspades.metabat2.bin.5.fa',
# 'CAMI_UT_25.metaspades.metabat2.bin.15.fa',
# 'CAMI_UT_3.metaspades.metabat2.bin.6.fa'],
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lactobacillus;s__Lactobacillus '
# 'delbrueckii']},
# 'result3': {'RG': 'CAMI_UT_25.metaspades.metabat2.bin.7.fa',
# 'members': ['CAMI_UT_24.metaspades.metabat2.bin.15.fa',
# 'CAMI_UT_25.metaspades.metabat2.bin.7.fa',
# 'CAMI_UT_3.metaspades.maxbin2.bin.6_sub.fa',
# 'CAMI_UT_5.metaspades.vamb.bin.8.fa'],
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Levilactobacillus;s__Levilactobacillus '
# 'brevis']},
# 'result4': {'RG': 'CAMI_UT_3.metaspades.concoct.bin.25.fa',
# 'members': ['CAMI_UT_3.metaspades.concoct.bin.25.fa',
# 'CAMI_UT_6.metaspades.concoct.bin.14.fa'],
# 'species': ['d__Bacteria;p__Actinobacteriota;c__Actinomycetia;o__Actinomycetales;f__Bifidobacteriaceae;g__Bifidobacterium;s__Bifidobacterium '
# 'vaginale_G']},
# 'result5': {'RG': 'CAMI_UT_24.metaspades.metabat2.bin.6_sub.fa',
# 'members': ['CAMI_UT_24.metaspades.metabat2.bin.6_sub.fa',
# 'CAMI_UT_25.metaspades.maxbin2.bin.6.fa',
# 'CAMI_UT_5.metaspades.metabat2.bin.6_sub.fa'],
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Latilactobacillus;s__Latilactobacillus '
# 'curvatus']},
# 'result6': {'RG': 'CAMI_UT_2.metaspades.concoct.bin.21.fa',
# 'members': ['CAMI_UT_2.metaspades.concoct.bin.21.fa',
# 'CAMI_UT_24.metaspades.metabat2.bin.10.fa',
# 'CAMI_UT_25.metaspades.maxbin2.bin.1_sub.fa'],
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Limosilactobacillus;s__Limosilactobacillus '
# 'fermentum']},
# 'result7': {'RG': 'CAMI_UT_2.metaspades.maxbin2.bin.1.fa',
# 'members': ['CAMI_UT_0.metaspades.concoct.bin.42.fa',
# 'CAMI_UT_2.metaspades.maxbin2.bin.1.fa',
# 'CAMI_UT_22.metaspades.maxbin2.bin.1.fa'],
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Ligilactobacillus;s__Ligilactobacillus '
# 'salivarius']},
# 'result8': {'RG': 'CAMI_UT_5.metaspades.vamb.bin.14.fa',
# 'members': ['CAMI_UT_25.metaspades.vamb.bin.16.fa',
# 'CAMI_UT_3.metaspades.vamb.bin.20.fa',
# 'CAMI_UT_5.metaspades.vamb.bin.14.fa'],
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lactobacillus;s__Lactobacillus '
# 'amylovorus']},
# 'result9': {'RG': 'CAMI_UT_22.metaspades.concoct.bin.21.fa',
# 'members': ['CAMI_UT_2.metaspades.vamb.bin.2.fa',
# 'CAMI_UT_22.metaspades.concoct.bin.21.fa'],
# 'species': ['d__Bacteria;p__Firmicutes;c__Bacilli;o__Lactobacillales;f__Lactobacillaceae;g__Lentilactobacillus;s__Lentilactobacillus '
# 'buchneri']}}
# -------------
# <different species>: total= 0 results
# {}
# **************
# -------------
# <check results>
# There are no replicate species between all same species clusters.
# Candidate and perfect cluster were already written to files: candidate_cluster.pkl perfect_cluster.pkl!