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: