def __define_instance_variables(self):
"""
Define instance variables
:return:
"""
self.__universal_model = Model("universal_model")
self.__swapped = []
self.__compounds_ontology = CompoundsDBAccessor()
self.__compoundsAnnotationConfigs = file_utilities.read_conf_file(
COMPOUNDS_ANNOTATION_CONFIGS_PATH)
self.__reactionsAnnotationConfigs = file_utilities.read_conf_file(
REACTIONS_ANNOTATION_CONFIGS_PATH)
self.__compoundsIdConverter = CompoundsIDConverter()
self.__compounds_revisor = CompoundsRevisor(self.model,
self.__universal_model)
biocyc.set_organism("meta")
self.mapper = ModelMapper(self.model,
self.__compoundsAnnotationConfigs,
self.__compoundsIdConverter)
self.__compounds_revisor.set_model_mapper(self.mapper)
self.granulator = Granulator(self.model, self.mapper,
self.__database_format,
self.__compoundsIdConverter,
self.__compoundsAnnotationConfigs)
def __define_instance_variables(self):
"""
Method to define a set of instance values
:return:
"""
self.__swapped = []
self.lineage = []
# self.__compounds_ontology = CompoundsDBAccessor()
self.__compoundsAnnotationConfigs = file_utilities.read_conf_file(
COMPOUNDS_ANNOTATION_CONFIGS_PATH)
self.__reactionsAnnotationConfigs = file_utilities.read_conf_file(
REACTIONS_ANNOTATION_CONFIGS_PATH)
self.__compoundsAnnotationConfigs = file_utilities.read_conf_file(
COMPOUNDS_ANNOTATION_CONFIGS_PATH)
self.__reactionsAnnotationConfigs = file_utilities.read_conf_file(
REACTIONS_ANNOTATION_CONFIGS_PATH)
self.__compoundsIdConverter = CompoundsIDConverter()
# self.__ptw_handler_quinones = PathwayHandler(self.__modelseedCompoundsDb, self.__compoundsIdConverter)
# self.__ptw_handler_quinones.load_from_file(self.__home_path__ + self.__configs["quinones_pathways"])
self.__not_to_change_classes = ["cpd03476"]
self.__set_not_to_change_compounds()
self.__compounds_revisor = CompoundsRevisor(self.model,
self.__universal_model)
biocyc.set_organism("meta")
self.__swapper = MetaboliteSwapper(
self.model,
None,
None,
0,
self.__modelseedCompoundsDb,
model_database=self.__database_format,
compoundsIdConverter=self.__compoundsIdConverter,
universal_model=self.__universal_model,
not_to_change_compounds=self.__not_to_change_compounds)
self.__mapper = ModelMapper(self.model,
self.__compoundsAnnotationConfigs,
self.__compoundsIdConverter)
self.__swapper.set_model_mapper(self.__mapper)
self.__compounds_revisor.set_model_mapper(self.__mapper)
def __init__(self,compounds_database = None, compounds_converter = None):
self.target_pathways_map = {}
self.__pathways_map = {}
self.taxID_map = {}
self.__home_path__ = ROOT_DIR
if not compounds_converter:
self.__compoundsIdConverter = CompoundsIDConverter()
else:
self.__compoundsIdConverter = compounds_converter
if not compounds_database:
self.__compounds_database = ModelSeedCompoundsDB()
else:
self.__compounds_database = compounds_database
# if compounds_ontology:
# self.__compounds_ontology = compounds_ontology
biocyc.set_organism('meta')
def add_metacyc_pathway(self,metacyc_pathway_id,generic = False):
biocyc.set_organism('meta')
ptw = biocyc.get(metacyc_pathway_id)
network = self.scrap_metacyc_path(ptw,generic)
self.convert_compounds_into_modelseedid(network)
pathway = network.get_pathway()
if pathway:
target_reaction = pathway[-1]
last_reaction = biocyc.get(target_reaction)
products = last_reaction.compounds_right
targets = []
for product in products:
modelseedids = self.__compoundsIdConverter.convert_dbID_into_modelSeedId("MetaCyc",product.id)
if modelseedids is not None:
targets.extend(modelseedids)
self.__pathways_map[ptw.id] = network
self.target_pathways_map[ptw.id]=targets
from pathminer import mining
import pandas as pd
import numpy as np
import os
from biocyc import biocyc
biocyc.set_organism('HUMAN')
biocyc.secondary_cache_paths.append( os.path.join(_pathomx_database_path, 'biocyc') )
# Flatten input data to single row
data = []
for input_data in input_1, input_2, input_3, input_4:
if input_data is not None:
datam = input_data.mean()
# We need BioCyc identifiers
if 'BioCyc' in input_data.columns.names:
if type(input_data.columns) == pd.MultiIndex:
entities = [k[input_data.columns.names.index('BioCyc')] for k in input_1.columns.values]
else:
entities = input_data.columns.values
# Map to BioCyc if not already
biocyc_entities = []
for e in entities:
if hasattr(e, 'id'):
biocyc_entities.append(e)
elif type(e) is str:
try:
biocyc_entities[n] = biocyc.get(o)
except:
from pathminer import mining
import pandas as pd
import numpy as np
import os
from biocyc import biocyc
biocyc.set_organism('HUMAN')
biocyc.secondary_cache_paths.append(
os.path.join(_pathomx_database_path, 'biocyc'))
# Flatten input data to single row
data = []
for input_data in input_1, input_2, input_3, input_4:
if input_data is not None:
datam = input_data.mean()
# We need BioCyc identifiers
if 'BioCyc' in input_data.columns.names:
if type(input_data.columns) == pd.MultiIndex:
entities = [
k[input_data.columns.names.index('BioCyc')]
for k in input_1.columns.values
]
else:
entities = input_data.columns.values
# Map to BioCyc if not already
biocyc_entities = []
for e in entities:
if hasattr(e, 'id'):
biocyc_entities.append(e)
elif type(e) is str: