15.1.1.2.1.1. cobra.flux_analysis.deletion

15.1.1.2.1.1.1. Module Contents

cobra.flux_analysis.deletion._reactions_knockouts_with_restore(model, reactions)[source]
cobra.flux_analysis.deletion._get_growth(model)[source]
cobra.flux_analysis.deletion._reaction_deletion(model, ids)[source]
cobra.flux_analysis.deletion._gene_deletion(model, ids)[source]
cobra.flux_analysis.deletion._reaction_deletion_worker(ids)[source]
cobra.flux_analysis.deletion._gene_deletion_worker(ids)[source]
cobra.flux_analysis.deletion._init_worker(model)[source]
cobra.flux_analysis.deletion._multi_deletion(model, entity, element_lists, method="fba", solution=None, processes=None, **kwargs)[source]

Provide a common interface for single or multiple knockouts.

Parameters:
  • model (cobra.Model) – The metabolic model to perform deletions in.
  • entity ('gene' or 'reaction') – The entity to knockout (cobra.Gene or cobra.Reaction).
  • element_lists (list) – List of iterables ``cobra.Reaction``s or ``cobra.Gene``s (or their IDs) to be deleted.
  • method ({"fba", "moma", "linear moma", "room", "linear room"}, optional) – Method used to predict the growth rate.
  • solution (cobra.Solution, optional) – A previous solution to use as a reference for (linear) MOMA or ROOM.
  • processes (int, optional) – The number of parallel processes to run. Can speed up the computations if the number of knockouts to perform is large. If not passed, will be set to the number of CPUs found.
  • kwargs – Passed on to underlying simulation functions.
Returns:

A representation of all combinations of entity deletions. The columns are ‘growth’ and ‘status’, where

index : frozenset([str])

The gene or reaction identifiers that were knocked out.

growth : float

The growth rate of the adjusted model.

status : str

The solution’s status.

Return type:

pandas.DataFrame

cobra.flux_analysis.deletion._entities_ids(entities)[source]
cobra.flux_analysis.deletion._element_lists(entities, *ids)[source]
cobra.flux_analysis.deletion.single_reaction_deletion(model, reaction_list=None, method="fba", solution=None, processes=None, **kwargs)[source]

Knock out each reaction from a given list.

Parameters:
  • model (cobra.Model) – The metabolic model to perform deletions in.
  • reaction_list (iterable, optional) – ``cobra.Reaction``s to be deleted. If not passed, all the reactions from the model are used.
  • method ({"fba", "moma", "linear moma", "room", "linear room"}, optional) – Method used to predict the growth rate.
  • solution (cobra.Solution, optional) – A previous solution to use as a reference for (linear) MOMA or ROOM.
  • processes (int, optional) – The number of parallel processes to run. Can speed up the computations if the number of knockouts to perform is large. If not passed, will be set to the number of CPUs found.
  • kwargs – Keyword arguments are passed on to underlying simulation functions such as add_room.
Returns:

A representation of all single reaction deletions. The columns are ‘growth’ and ‘status’, where

index : frozenset([str])

The reaction identifier that was knocked out.

growth : float

The growth rate of the adjusted model.

status : str

The solution’s status.

Return type:

pandas.DataFrame

cobra.flux_analysis.deletion.single_gene_deletion(model, gene_list=None, method="fba", solution=None, processes=None, **kwargs)[source]

Knock out each gene from a given list.

Parameters:
  • model (cobra.Model) – The metabolic model to perform deletions in.
  • gene_list (iterable) – ``cobra.Gene``s to be deleted. If not passed, all the genes from the model are used.
  • method ({"fba", "moma", "linear moma", "room", "linear room"}, optional) – Method used to predict the growth rate.
  • solution (cobra.Solution, optional) – A previous solution to use as a reference for (linear) MOMA or ROOM.
  • processes (int, optional) – The number of parallel processes to run. Can speed up the computations if the number of knockouts to perform is large. If not passed, will be set to the number of CPUs found.
  • kwargs – Keyword arguments are passed on to underlying simulation functions such as add_room.
Returns:

A representation of all single gene deletions. The columns are ‘growth’ and ‘status’, where

index : frozenset([str])

The gene identifier that was knocked out.

growth : float

The growth rate of the adjusted model.

status : str

The solution’s status.

Return type:

pandas.DataFrame

cobra.flux_analysis.deletion.double_reaction_deletion(model, reaction_list1=None, reaction_list2=None, method="fba", solution=None, processes=None, **kwargs)[source]

Knock out each reaction pair from the combinations of two given lists.

We say ‘pair’ here but the order order does not matter.

Parameters:
  • model (cobra.Model) – The metabolic model to perform deletions in.
  • reaction_list1 (iterable, optional) – First iterable of ``cobra.Reaction``s to be deleted. If not passed, all the reactions from the model are used.
  • reaction_list2 (iterable, optional) – Second iterable of ``cobra.Reaction``s to be deleted. If not passed, all the reactions from the model are used.
  • method ({"fba", "moma", "linear moma", "room", "linear room"}, optional) – Method used to predict the growth rate.
  • solution (cobra.Solution, optional) – A previous solution to use as a reference for (linear) MOMA or ROOM.
  • processes (int, optional) – The number of parallel processes to run. Can speed up the computations if the number of knockouts to perform is large. If not passed, will be set to the number of CPUs found.
  • kwargs – Keyword arguments are passed on to underlying simulation functions such as add_room.
Returns:

A representation of all combinations of reaction deletions. The columns are ‘growth’ and ‘status’, where

index : frozenset([str])

The reaction identifiers that were knocked out.

growth : float

The growth rate of the adjusted model.

status : str

The solution’s status.

Return type:

pandas.DataFrame

cobra.flux_analysis.deletion.double_gene_deletion(model, gene_list1=None, gene_list2=None, method="fba", solution=None, processes=None, **kwargs)[source]

Knock out each gene pair from the combination of two given lists.

We say ‘pair’ here but the order order does not matter.

Parameters:
  • model (cobra.Model) – The metabolic model to perform deletions in.
  • gene_list1 (iterable, optional) – First iterable of ``cobra.Gene``s to be deleted. If not passed, all the genes from the model are used.
  • gene_list2 (iterable, optional) – Second iterable of ``cobra.Gene``s to be deleted. If not passed, all the genes from the model are used.
  • method ({"fba", "moma", "linear moma", "room", "linear room"}, optional) – Method used to predict the growth rate.
  • solution (cobra.Solution, optional) – A previous solution to use as a reference for (linear) MOMA or ROOM.
  • processes (int, optional) – The number of parallel processes to run. Can speed up the computations if the number of knockouts to perform is large. If not passed, will be set to the number of CPUs found.
  • kwargs – Keyword arguments are passed on to underlying simulation functions such as add_room.
Returns:

A representation of all combinations of gene deletions. The columns are ‘growth’ and ‘status’, where

index : frozenset([str])

The gene identifiers that were knocked out.

growth : float

The growth rate of the adjusted model.

status : str

The solution’s status.

Return type:

pandas.DataFrame