fluxpy.utils.model

Utilities to parse, convert and edit cobra models

Attributes

all_namespaces

Classes

_Conversions	Generic enumeration.
Models	Load a list of sbml models with cobra as attributes of a class.
NameIdConverter	A class to switch indexes of a dataframe from ids to names and vice versa for metabolites and reactions of a model.
CompareModels	Using mergem <https://mergem.readthedocs.io/> to compare a pair of models and returns a dataframe with
CofactorSpecificity	Class is used to identify cases where the same biochemical conversion is carried out by different cofactors in the model,

Functions

map_namespace_to_ModelSEEDDatabase(seed_compounds, ...)	This function makes use of the ModelSEEDpy and the ModelSEEDDatabase libraries to map a list of ModelSEED compounds
map_to_namespace(compounds[, from_namespace, to_namespace])	compounds -- a list
sync_with_medium(model, medium)	Adds metabolites and reactions required to allow a medium to be assigned to a cobra.Model
_check_if_modelseed_model(model)

Module Contents

fluxpy.utils.model.all_namespaces = ['chebi', 'metacyc', 'kegg', 'reactome', 'metanetx', 'hmdb', 'biocyc', 'bigg', 'seed', 'sabiork', 'rhea']

class fluxpy.utils.model._Conversions

Bases: enum.Enum

Generic enumeration.

Derive from this class to define new enumerations.

REACTION_NAMES = 'reactionNames'

REACTION_IDS = 'reactionIds'

METABOLITE_NAMES = 'metaboliteNames'

METABOLITE_IDS = 'metaboliteIds'

class fluxpy.utils.model.Models(model_list: List[str], model_names: List[str] = None)

Load a list of sbml models with cobra as attributes of a class.

class fluxpy.utils.model.NameIdConverter(model, to_convert: pandas.DataFrame | Dict | List | cobra.Solution, convert: str, to: str)

A class to switch indexes of a dataframe from ids to names and vice versa for metabolites and reactions of a model.

met_map_df

react_map_df

convert

to

model

isIndex

run_convert()

_met_ids_to_met_names()

_met_names_to_met_ids()

_react_ids_to_react_names()

_react_names_to_react_ids()

class fluxpy.utils.model.CompareModels(model_list: List[str], trans_to_db=None)

Using mergem <https://mergem.readthedocs.io/> to compare a pair of models and returns a dataframe with reactions unique in model1 and model2 and those they share.

Key arguments:

model_list – list of paths to model files to compare

trans_to_db – mergem allows to map metabolite and reaction ids to a series of namespaces.

number_of_models

model_names

models

namespace = None

res

metabolites_df

reactions_df

unique_metabolites(model_name)

Returns: unique_mets – a pd.Index with the metabolites that are only present in model_name and not in any other of those in model_list

unique_reactions(model_name)

Key arguments: model_name – the name (column name) of the model for which unique reactions will be found

Returns: model_unique_reactions – a pd.Index with the reactions that are only present in the model_name and not in any other of those in model_list

compare_model_pair(base_model=None, model_to_compare=None)

Compare pairwise models

Key arguments: base_model – name of the model as in dataframe, i.e. filename without the extension model_to_compare – name of the model as in dataframe, i.e. filename without the extension

Returns: r1 – reactions only present in base model r2 – reactions only present in model_to_compare m1 – metabolites only present in base_model m2 – metabolites only present in model_to_compare

shared_metabolites(models_subset=None)

Key arguments: models_subset – list of models to get shared metabolites and reactions

Returns: shared_reactions – a pd.Index with rearctions present among all models of models_subset

shared_reactions(models_subset=None)

Key arguments: models_subset – list of models to get shared metabolites and reactions

Returns: shared_reactions – a pd.Index with rearctions present among all models of models_subset

fluxpy.utils.model.map_namespace_to_ModelSEEDDatabase(seed_compounds: List[str], path_to_modelSEEDDatabase: str, annotations_to_keep=['BiGG', 'BiGG1'])

This function makes use of the ModelSEEDpy and the ModelSEEDDatabase libraries to map a list of ModelSEED compounds to their annotations returning a pandas dataframe with those

seed_compouds – a list with seed compound ids path_to_modelSEEDDatabase – path to the modelSEEDDatabase. To get it: git clone https://github.com/ModelSEED/ModelSEEDDatabase.git

fluxpy.utils.model.map_to_namespace(compounds, from_namespace='seed', to_namespace='bigg')

compounds – a list from_namesapce – to_namespace –

fluxpy.utils.model.sync_with_medium(model: cobra.Model, medium: Dict)

Adds metabolites and reactions required to allow a medium to be assigned to a cobra.Model

Parameters:

• model (cobra.Model, mandatory) – model to which the new medium will be assigned to and to which metabolites and reactions will be added to

• medium (Dict, mandatory) – a dictionary with the medium to be used with the metabolites as keys and their boundaries as values

Returns:

A cobra.Model with added metabolites and reactions to enable medium to be used

fluxpy.utils.model._check_if_modelseed_model(model: cobra.Model)

class fluxpy.utils.model.CofactorSpecificity(model)

Class is used to identify cases where the same biochemical conversion is carried out by different cofactors in the model, while in reality the organism only uses one of the cofactors. If the cofactor specificity information is available, the reaction with non-specific cofactor can be removed or turned off.

This is how to initialize the class: cofactor_specificity = CofactorSpecificity(cobra_model)

model

find_reactants_products_cofactors()

find_reactions_combinations()

merge_connected_combinations()

This function takes as input the pairwise combinations of reactions from above and creates groups of reactions that are candidates for cofactor specificity. It uses a graph-based approach to find connected components in the graph of reactions.

cofactors_abundance()

remove_reactions()

filter_reactions()