def plot_module_and_pathway_combinaison_heatmap(biodb,
ref_tree,
pathway_list,
module_list,
taxon_id_list=[],
group_by_KO=True,
rotate=False):
import manipulate_biosqldb
import ete_motifs
import module_heatmap
pathway_list, code2taxon2count_pathway = pathway_list2profile_dico(
biodb,
pathway_list,
taxon_id_list=taxon_id_list,
group_by_KO=group_by_KO)
module_list, code2taxon2count_modules = module_heatmap.module_list2profile_dico(
biodb, module_list, taxon_id_list=taxon_id_list)
merged_list = sorted(pathway_list + module_list)
code2taxon2count_pathway.update(code2taxon2count_modules)
tree2 = ete_motifs.multiple_profiles_heatmap(biodb,
merged_list,
code2taxon2count_pathway,
show_labels=True,
column_scale=True,
tree=ref_tree,
as_float=False,
rotate=rotate)
return tree2
def plot_module_heatmap(biodb, ref_tree, module_list, taxon_id_list=[], rotate=False):
import ete_motifs
module_list, code2taxon2count = module_list2profile_dico(biodb,
module_list,
taxon_id_list=taxon_id_list)
tree2 = ete_motifs.multiple_profiles_heatmap(biodb,
module_list,
code2taxon2count,
show_labels=True,
column_scale=True,
tree=ref_tree,
as_float=False,
rotate=rotate)
return tree2
def plot_hmm_heatmap(biodb,
ref_tree,
taxon_id_list=[],
frequency=False,
six_frame_translation=False):
from chlamdb.biosqldb import manipulate_biosqldb
import ete_motifs
code2taxon2count, set_list = get_set_data(biodb)
tree2 = ete_motifs.multiple_profiles_heatmap(biodb,
set_list,
code2taxon2count,
show_labels=True,
column_scale=True,
tree=ref_tree,
as_float=frequency)
return tree2
def plot_pathway_heatmap(biodb,
ref_tree,
pathway_list,
taxon_id_list=[],
rotate=False,
group_by_KO=True):
import manipulate_biosqldb
import ete_motifs
pathway_list, code2taxon2count = pathway_list2profile_dico(
biodb,
pathway_list,
taxon_id_list=taxon_id_list,
group_by_KO=group_by_KO)
tree2 = ete_motifs.multiple_profiles_heatmap(biodb,
pathway_list,
code2taxon2count,
show_labels=True,
column_scale=True,
tree=ref_tree,
as_float=False,
rotate=rotate)
return tree2
def plot_cog_eatmap(biodb,
ref_tree,
taxon_id_list=[],
frequency=False,
group_by_cog_id=False):
import manipulate_biosqldb
import ete_motifs
server, db = manipulate_biosqldb.load_db(biodb)
sql = 'select biodatabase_id from biodatabase where name="%s"' % biodb
db_id = server.adaptor.execute_and_fetchall(sql, )[0][0]
# RESTRICT TO AS SUBSET OF THE TAXON AVAILABLE
sql = ''
if len(taxon_id_list) > 0:
filter = ','.join(taxon_id_list)
sql = 'select taxon_id, code, count(*) as n from COG.seqfeature_id2best_COG_hit_%s t1 ' \
' inner join biosqldb.bioentry t2 on t1.bioentry_id=t2.bioentry_id' \
' inner join COG.cog_id2cog_category t3 on t1.hit_cog_id=t3.COG_id ' \
' inner join COG.code2category t4 on t3.category_id=t4.category_id ' \
' where t2.biodatabase_id=%s and taxon_id in (%s)' \
' group by taxon_id, code;' % (biodb,
db_id,
filter)
print(sql)
else:
if not group_by_cog_id:
sql = 'select taxon_id,functon,count(*) as n ' \
' from COG.locus_tag2gi_hit_%s t1 ' \
' inner join COG.cog_names_2014 t2 on t1.COG_id=t2.COG_id ' \
' inner join biosqldb.bioentry as t3 on t1.accession=t3.accession ' \
' where biodatabase_id=%s group by taxon_id,functon' % (biodb, db_id)
else:
sql = ' select A.taxon_id,B.functon,count(*) from (select t1.COG_id, t3.taxon_id from COG.locus_tag2gi_hit_%s t1 ' \
' inner join biosqldb.orthology_detail_%s t3 on t1.locus_tag=t3.locus_tag ' \
' group by taxon_id,t1.COG_id) A inner join COG.cog_names_2014 B on A.COG_id=B.COG_id ' \
' group by A.taxon_id,B.functon;' % (biodb, biodb)
data = server.adaptor.execute_and_fetchall(sql, )
if frequency:
'''
ATTENTION: based on total annotated with COG and not genome size
'''
sql = 'select taxon_id, count(*) as n from COG.seqfeature_id2best_COG_hit_%s t1' \
' inner join biosqldb.bioentry t2 on t1.bioentry_id=t2.bioentry_id' \
' where t2.biodatabase_id=%s group by taxon_id;' % (biodb, db_id)
taxon_id2count = manipulate_biosqldb.to_dict(
server.adaptor.execute_and_fetchall(sql, ))
code2taxon2count = {}
cog_list = []
else:
sql = 'select taxon_id, count(*) from biosqldb.orthology_detail_%s t1 left join COG.locus_tag2gi_hit_%s t2 ' \
' on t1.locus_tag=t2.locus_tag where COG_id is NULL group by t1.taxon_id;' % (biodb, biodb)
taxon2count_no_GOG = manipulate_biosqldb.to_dict(
server.adaptor.execute_and_fetchall(sql, ))
sql = 'select taxon_id, count(*) from orthology_detail_%s group by taxon_id' % biodb
taxon2proteome_size = manipulate_biosqldb.to_dict(
server.adaptor.execute_and_fetchall(sql, ))
code2taxon2count = {}
code2taxon2count['-'] = {}
code2taxon2count['TOTAL'] = {}
for taxon in taxon2count_no_GOG:
if taxon in taxon_id_list:
code2taxon2count['-'][taxon] = int(taxon2count_no_GOG[taxon])
code2taxon2count['TOTAL'][taxon] = int(
taxon2proteome_size[taxon])
cog_list = ['TOTAL', '-']
sql = 'select code, description from COG.code2category;'
code2description = manipulate_biosqldb.to_dict(
server.adaptor.execute_and_fetchall(sql, ))
for row in data:
descr = "%s (%s)" % (code2description[row[1]], row[1])
if descr not in cog_list:
cog_list.append(descr)
if descr not in code2taxon2count:
code2taxon2count[descr] = {}
if frequency:
code2taxon2count[descr][str(row[0])] = round(
(float(row[2]) / float(taxon_id2count[str(row[0])])) * 100,
2)
else:
code2taxon2count[descr][str(row[0])] = int(row[2])
else:
if frequency:
code2taxon2count[descr][str(row[0])] = round(
(float(row[2]) / float(taxon_id2count[str(row[0])])) * 100,
2)
else:
code2taxon2count[descr][str(row[0])] = int(row[2])
tree2 = ete_motifs.multiple_profiles_heatmap(biodb,
cog_list,
code2taxon2count,
show_labels=True,
column_scale=True,
tree=ref_tree,
as_float=frequency)
return tree2