napistu.matching.interactions

Functions

edgelist_to_pathway_species(...[, ...])

Edgelist to Pathway Species

edgelist_to_scids(formatted_edgelist, ...)

Edgelist to Compartmentalized Species IDds

filter_to_direct_mechanistic_interactions(...)

Filter to Direct Mechanistic Interactions

filter_to_indirect_mechanistic_interactions(...)

Filter to Indirect Mechanistic Interactions

napistu.matching.interactions._edgelist_to_scids_if_needed(edgelist: DataFrame, sbml_dfs: SBML_dfs, species_identifiers: DataFrame, ontologies: set) DataFrame

Map a set of edgelist species to cspecies or skip if cspecies were provided.

napistu.matching.interactions.edgelist_to_pathway_species(formatted_edgelist: DataFrame, species_identifiers: DataFrame, ontologies: set, feature_id_var: str = 'feature_id', verbose: bool = False) DataFrame

Edgelist to Pathway Species

Match an edgelist of molecular species pairs to their corresponding species in a pathway representation.

Parameters: formatted_edgelist: pd.DataFrame

pd.Dataframe containing a “identifier_upstream” and “identifier_downstream” variables used to to match entries

species_identifiers: pd.DataFrame

A table of molecular species identifiers produced from sbml_dfs.get_identifiers(“species”) generally using sbml_dfs.export_sbml_dfs()

ontologies: set

A set of ontologies used to match features to pathway species

feature_id_var: str, default=FEATURE_ID_VAR_DEFAULT

Variable in “formatted_edgelist” containing feature ids

verbose: bool, default=False

Whether to print verbose output

Returns: edges_on_pathway: pd.DataFrame

formatted_edgelist with upstream features mapped to “s_id_upstream” and downstream species mapped to “s_id_downstream”

napistu.matching.interactions.edgelist_to_scids(formatted_edgelist: DataFrame, sbml_dfs: SBML_dfs, species_identifiers: DataFrame, ontologies: set)

Edgelist to Compartmentalized Species IDds

Map an edgelist of possible mechanistic interactions onto a pathadex pathway

Parameters: formatted_edgelist: pd.DataFrame

pd.Dataframe containing a “identifier_upstream” and “identifier_downstream” variables used to to match entries

sbml_dfs: sbml_dfs_core.SBML_dfs

A mechanistic model

species_identifiers: pd.DataFrame

A table of molecular species identifiers produced from sbml_dfs.get_identifiers(“species”) generally using sbml_dfs.export_sbml_dfs()

ontologies: set

A set of ontologies used to match features to pathway species

Returns: edgelist_w_scids: pd.DataFrame

formatted_edgelist with upstream features mapped to “sc_id_upstream” and downstream species mapped to “sc_id_downstream”

napistu.matching.interactions.filter_to_direct_mechanistic_interactions(formatted_edgelist: DataFrame, sbml_dfs: SBML_dfs, species_identifiers: DataFrame, ontologies: set) DataFrame

Filter to Direct Mechanistic Interactions

Filter an edgelist to direct mechanistic interactions

Parameters: formatted_edgelist: pd.DataFrame

pd.Dataframe containing a “identifier_upstream” and “identifier_downstream” variables used to to match entries

sbml_dfs: sbml_dfs_core.SBML_dfs

A mechanistic model

species_identifiers: pd.DataFrame

A table of molecular species identifiers produced from sbml_dfs.get_identifiers(“species”) generally using sbml_dfs.export_sbml_dfs()

ontologies: set

A set of ontologies used to match features to pathway species

Returns: edgelist_w_direct_mechanistic_interactions: pd.DataFrame

formatted_edgelist filtered to mechanistic reactions present in the pathway representation

napistu.matching.interactions.filter_to_indirect_mechanistic_interactions(formatted_edgelist: DataFrame, sbml_dfs: SBML_dfs, species_identifiers: DataFrame, napistu_graph: Graph, ontologies: set, precomputed_distances=None, max_path_length=10)

Filter to Indirect Mechanistic Interactions

Filter an edgelist to indirect mechanistic interactions. Indirect relationships are identified by searching a network for paths from an upstream species to a downstream species

Parameters: formatted_edgelist: pd.DataFrame

pd.Dataframe containing a “identifier_upstream” and “identifier_downstream” variables used to to match entries

sbml_dfs: sbml_dfs_core.SBML_dfs

A mechanistic model

species_identifiers: pandas.DataFrame

A table of molecular species identifiers produced from sbml_dfs.get_identifiers(“species”) generally using sbml_dfs.export_sbml_dfs()

napistu_graph: igraph.Graph

A network representation of the sbml_dfs model

ontologies: set

A set of ontologies used to match features to pathway species

precomputed_distances: None or a pd.DataFrame containing path lengths and weights

between pairs of cspecies.

max_path_length: int

Maximum number of steps to consider.

Returns: edgelist_w_indirect_mechanistic_interactions: pd.DataFrame

formatted_edgelist filtered to mechanistic reactions which can be described by an indirect mechanism. The mechanism is described by a path weight, length, and a vpath and epath list of vertices and edges which were traversed to create the path.