marsi.cobra.flux_analysis package

Submodules

marsi.cobra.flux_analysis.analysis module

marsi.cobra.flux_analysis.analysis.metabolite_knockout_fitness(model, simulation_method=<function pfba>, compartments=None, elements=['C', 'N'], objective=None, ndecimals=6, progress=False, ncarbons=2, **simulation_kwargs)

Calculate the landscape of fitness for each metabolite knockout in the model.

Parameters:

• model (cameo.core.SolverBasedModel) – A constraint-based model.
• simulation_method (cameo.flux_analysis.simulation.fba) – A method to simulate the knockouts (e.g. cameo.flux_analysis.simulation.moma)
• compartments (list) – The compartments to consider (e.g. [“c”, “g”, “r”] for cytosol, golgi aparatus and endoplasmatic reticulum)
• elements (list) – Atomic elements to add to the result.
• objective (str, cameo.core.Reaction, other) – A valid objective for the model.
• ndecimals (int) – Number of decimals to use as precision.
• progress (bool) – Report progress.
• ncarbons (int) – Minimum number of carbons to consider.
• simulation_kwargs (dict) – Arguments for `simulation_method

Returns:

The fitness landscape.

Return type:

MetaboliteKnockoutFitness

marsi.cobra.flux_analysis.analysis.metabolite_knockout_phenotype(model, compartments=None, objective=None, ndecimals=6, elements=['C', 'N'], progress=False, ncarbons=2)

marsi.cobra.flux_analysis.analysis.sensitivity_analysis(model, metabolite, biomass=None, variables=None, is_essential=False, steps=10, reference_dist=None, simulation_method=<function fba>, **simulation_kwargs)

marsi.cobra.flux_analysis.manipulation module

marsi.cobra.flux_analysis.manipulation.compete_metabolite(model, metabolite, reference_dist, fraction=0.5, allow_accumulation=True, constant=10000.0)

Increases the usage of a metabolite based on a reference flux distributions.

Parameters:

• model (Model) – A constraint-based model.
• metabolite (cobra.Metabolite) – A metabolite.
• reference_dist (dict or FluxDistributionResult) – The result of a FBA like simulation. Alternative can be dictionaries of reaction.id -> flux.
• fraction (float) – How much does it requires the reactions to go up.
• allow_accumulation (bool) – Allow to accumulate the metabolite (add a exchange reaction).
• constant (float) – A large number (like 10000).

Returns:

If allow accumulation returns the exchange reaction associated with the metabolite.

Return type:

cobra.core.Reaction

marsi.cobra.flux_analysis.manipulation.inhibit_metabolite(model, metabolite, reference_dist, fraction=0.5, allow_accumulation=True, constant=10000.0)

Inhibits the usage of a metabolite based on a reference flux distributions.

Parameters:

• model (Model) – A constraint-based model.
• metabolite (cobra.Metabolite) – A metabolite.
• reference_dist (dict, FluxDistributionResult) – The result of a FBA like simulation. Alternative can be dictionaries of reaction.id -> flux.
• fraction (float) – How much does it inhibits the reactions. A float applies the same amount of inhibition. A dictionary must contain an inhibition percentage to all reactions associated with the metabolite.
• allow_accumulation (bool) – Allow to accumulate the metabolite (add a exchange reaction).
• constant (float) – A large number (like 10000).

Returns:

If allow accumulation returns the exchange reaction associated with the metabolite.

Return type:

cameo.core.Reaction, None

marsi.cobra.flux_analysis.manipulation.knockout_metabolite(model, metabolite, ignore_transport=True, allow_accumulation=True)

Inhibits the usage of a metabolite based on a reference flux distributions.

Parameters:

• model (Model) – A constraint-based model.
• metabolite (cobra.Metabolite) – A metabolite.
• ignore_transport (bool) – Choose to ignore transport reactions.
• allow_accumulation (bool) – Allow to accumulate the metabolite (add a exchange reaction).

Returns:

If allow accumulation returns the exchange reaction associated with the metabolite.

Return type:

cameo.core.Reaction, None

marsi.cobra.flux_analysis.manipulation.apply_anti_metabolite(model, metabolites, essential_metabolites, reference, inhibition_fraction=0.0, competition_fraction=0.0, allow_accumulation=True)

Apply a metabolite in the context of a model without knowing if it is activating or inhibiting.

Parameters:

• model (cameo.core.SolverBasedModel) – A constraint-based model.
• metabolites (list) – Metabolites of the same species.
• essential_metabolites (list) – A list of essential metabolites.
• reference (dict, cameo.core.FluxDistributionResult) – A flux distribution.
• inhibition_fraction (float) – How much a metabolite inhibits.
• competition_fraction (float) – How much a metabolite competes.
• allow_accumulation (bool) – Allow accumulation of the metabolite.

Returns:

Exchange reactions added for accumulation.

Return type:

set

Module contents

marsi.cobra.flux_analysis.metabolite_knockout_fitness(model, simulation_method=<function pfba>, compartments=None, elements=['C', 'N'], objective=None, ndecimals=6, progress=False, ncarbons=2, **simulation_kwargs)

Calculate the landscape of fitness for each metabolite knockout in the model.

Parameters:

• model (cameo.core.SolverBasedModel) – A constraint-based model.
• simulation_method (cameo.flux_analysis.simulation.fba) – A method to simulate the knockouts (e.g. cameo.flux_analysis.simulation.moma)
• compartments (list) – The compartments to consider (e.g. [“c”, “g”, “r”] for cytosol, golgi aparatus and endoplasmatic reticulum)
• elements (list) – Atomic elements to add to the result.
• objective (str, cameo.core.Reaction, other) – A valid objective for the model.
• ndecimals (int) – Number of decimals to use as precision.
• progress (bool) – Report progress.
• ncarbons (int) – Minimum number of carbons to consider.
• simulation_kwargs (dict) – Arguments for `simulation_method

Returns:

The fitness landscape.

Return type:

MetaboliteKnockoutFitness

marsi.cobra.flux_analysis.metabolite_knockout_phenotype(model, compartments=None, objective=None, ndecimals=6, elements=['C', 'N'], progress=False, ncarbons=2)

marsi.cobra.flux_analysis.sensitivity_analysis(model, metabolite, biomass=None, variables=None, is_essential=False, steps=10, reference_dist=None, simulation_method=<function fba>, **simulation_kwargs)