napistu.modify.pathwayannot

Functions

`add_complex_formation`(sbml_dfs)	Add Complex Formation
`add_complex_formation_species`(sbml_dfs)	Add Complex Formation - Species
`add_entity_sets`(sbml_dfs, neo4j_members)	Add Entity Sets
`add_reactome_identifiers`(sbml_dfs, crossref_path)	Add Reactome Identifiers

napistu.modify.pathwayannot._add_complex_formation_compartmentalized_species(sbml_dfs: SBML_dfs, merged_membership: DataFrame, new_species_for_sbml_dfs: DataFrame, complex_component_species_ids: DataFrame) → tuple[DataFrame, DataFrame]

Add Complex Formation - Compartmentalized Species

Define all compartmentalized species in complexes and format newly created compartmentalized species

Parameters:

sbml_dfs (SBML_dfs) – A relational mechanistic network
merged_membership (pd.DataFrame) – A table of complexes and their component members
new_species_for_sbml_dfs (pd.DataFrame) – New entries to add to sbml_dfs.species
complex_component_species_ids (pd.DataFrame) – All complex components

Returns:

new_compartmentalized_species_for_sbml_dfs (pd.DataFrame) – New entries to add to sbml_dfs.compartmentalized_species
updated_compartmentalized_membership (pd.DataFrame) – Compartmentalized complex components with updated IDs

napistu.modify.pathwayannot._add_entity_sets_reactions(sbml_dfs: SBML_dfs, new_compartmentalized_species_for_sbml_dfs: DataFrame, updated_compartmentalized_membership: DataFrame) → tuple[DataFrame, DataFrame]

Add Entity Sets - Reactions

Create reactions which indicate membership in an entity set

Parameters:

sbml_dfs (SBML_dfs) – A relational mechanistic network
new_compartmentalized_species_for_sbml_dfs (pd.DataFrame) – New entries to add to sbml_dfs.compartmentalized_species
updated_compartmentalized_membership (pd.DataFrame) – Compartmentalized complex components with updated IDs

Returns:

new_reactions_for_sbml_dfs (pd.DataFrame) – New entries to add to sbml_dfs.reactions
new_reaction_species_for_sbml_dfs (pd.DataFrame) – New entries to add to sbml_dfs.reaction_species

napistu.modify.pathwayannot._add_entity_sets_species(sbml_dfs: SBML_dfs, reactome_members: DataFrame) → tuple[DataFrame, DataFrame, DataFrame]

Add Entity Sets - Species

Define all species which are part of “entity sets” in the pathway

Parameters:

sbml_dfs (SBML_dfs) – A relational mechanistic network
reactome_members (pd.DataFrame) – A table of all Reactome entity sets members - obtained using a Neo4j query

Returns:

merged_membership (pd.DataFrame) – A table of complexes and their component members
new_species_for_sbml_dfs (pd.DataFrame) – New entries to add to sbml_dfs.species
set_component_species_ids (pd.DataFrame) – All set components

napistu.modify.pathwayannot._merge_reactome_crossref_ids(current_molecular_ids: DataFrame, select_reactome_ids: DataFrame) → DataFrame

Merge Reactome CrossRef IDs

Combine existing molecular IDs with Reactome crossref identifiers.

Parameters:

current_molecular_ids (pd.DataFrame) – Molecular features in the current pathway model
select_reactome_ids (pd.DataFrame) – Crossref identifiers produced by _format_reactome_crossref_ids()

Returns:

merged_crossrefs – Molecular feature sids matched to crossref annotations

Return type:

pd.DataFrame

napistu.modify.pathwayannot._read_neo4j_members(neo4j_members: str) → DataFrame: Read a table containing entity sets (members) derived from Reactome’s Neo4J database.

napistu.modify.pathwayannot._read_reactome_crossref_ids(crossref_path: str) → DataFrame

Format Reactome CrossRef IDs

Read and reformat Reactome’s crossref identifiers

Parameters:: crossref_path (str) – Path to the cross ref file extracted from Reactome’s Neo4j database
Returns:: select_reactome_ids – Crossref identifiers
Return type:: pd.DataFrame

napistu.modify.pathwayannot.add_complex_formation(sbml_dfs: SBML_dfs)

Add Complex Formation

Using Reactome-style complex annotations, where complex components are an attribute of complexes, add explicit complex formation reactions.

Reactome represents complexers using BQB_HAS_PART annotations, which are extracted into Identifiers objects. This is sufficient to define membership but does not include stoichiometry. Also, in this approach components are defined by their identifiers (URIs) rather than internal s_ids/sc_ids.

napistu.modify.pathwayannot.add_complex_formation_species(sbml_dfs: SBML_dfs) → tuple[DataFrame, DataFrame, DataFrame]

Add Complex Formation - Species

Define all species in complexes and format newly created species

Parameters:

sbml_dfs (SBML_dfs) – A relational mechanistic network

Returns:

merged_membership (pd.DataFrame) – A table of complexes and their component members
new_species_for_sbml_dfs (pd.DataFrame) – New entries to add to sbml_dfs.species
complex_component_species_ids (pd.DataFrame) – All complex components

napistu.modify.pathwayannot.add_entity_sets(sbml_dfs: SBML_dfs, neo4j_members: str) → SBML_dfs

Add Entity Sets

Reactome represents some sets of interchangeable molecules as “entity sets”. Common examples are ligands for a receptor. This function add members of each entity set as a “is a” style reaction.

Parameters:

sbml_dfs (SBML_dfs) – A relational mechanistic network
neo4j_members (str) – Path to a table containing Reactome entity sets and corresponding members. This is currently extracted manually with Neo4j.

Returns:

sbml_dfs – An updated database which includes entity set species and formation reactions

Return type:

SBML_dfs

napistu.modify.pathwayannot.add_reactome_identifiers(sbml_dfs: SBML_dfs, crossref_path: str) → SBML_dfs

Add Reactome Identifiers

Add reactome-specific identifiers to existing species

Params

sbml_dfs: SBML_dfs: A pathway model
crossref_path:: Path to the cross ref file extracted from Reactome’s Neo4j database

returns:: sbml_dfs – A pathway model with updated species’ identifiers
rtype:: SBML_dfs