booldog.io.interaction_networks

Read standard networks formats/objects (networkx, igraph, graphml, SIF) and convert to Boolean network.

Attributes

`_IGRAPH_AVAILABLE`
`logger`

Functions

`networkx2interactions`(g[, edge_type_key])	Convert a NetworkX Graph into a nested dictionary of interactions.
`igraph2interactions`(g[, node_id_key, edge_type_key])	Convert an igraph Graph into a list of interactions.
`read_interactions`(interactions_input[, node_names])	Create Network from interactions (list)
`read_sif`(file[, delim, source_col, target_col, ...])	Reads in a SIF file of interactions
`read_igraph`(g[, node_id_key, edge_type_key, node_name_key])	Create BooleanNetwork from a igraph Graph object.
`read_networkx`(g[, edge_type_key, node_name_key])	Create BooleanNetwork from a networkx (Di)Graph object.
`read_graphml`(file[, edge_type_key, node_id_key, ...])	Extract relavent parts for a Boolean network from a graphml file.

Module Contents

booldog.io.interaction_networks._IGRAPH_AVAILABLE = True

booldog.io.interaction_networks.logger

booldog.io.interaction_networks.networkx2interactions(g, edge_type_key='interaction', **_)

Convert a NetworkX Graph into a nested dictionary of interactions.

Parameters:

g (networkx.(Di)Graph) – The input graph object from the Networkx library. (Assumed to be directed.)
edge_type_key (str, optional) – The edge attribute key to use for interaction values (e.g., weight, type). Default is “interaction”.
**_ (dict) – Additional keyword arguments (ignored).

Returns:

A nested dictionary where interactions[source][target] = symbol, with symbol being the edge attribute specified by edge_type_key.

Return type:

dict of dict

booldog.io.interaction_networks.igraph2interactions(g, node_id_key='name', edge_type_key='interaction')

Convert an igraph Graph into a list of interactions.

Parameters:

g (igraph.Graph) – The input graph object from the igraph library.
node_id_key (str, optional) – The vertex attribute key that contains the primary identifier to use for node identifiers. Default is “name”.
edge_type_key (str, optional) – The edge attribute key to use for interaction type (e.g., weight, type). Default is “interaction”.

Returns:

A nested dictionary where interactions[source][target] = symbol, with symbol being the edge attribute specified by edge_type_key.

Return type:

dict of dict

booldog.io.interaction_networks.read_interactions(interactions_input, node_names=None, **kwargs)

Create Network from interactions (list)

Parameters:

interactions_input (list or str) – A list of interactions in the network. Each interaction should be a tuple of (source, target, sign), where source and target are node identifiers and sign is either activator_symbol or inhibitor_symbol. Or a path to a JSON file containing such a list of interactions.
activator_symbol (int, optional) – The value representing activation in the network. Default is 1.
inhibitor_symbol (int, optional) – The value representing inhibition in the network. Default is -1.
**kwargs (dict) – Additional keyword arguments (ignored).

Returns:

n – A BoolDogModel object representing the Boolean network.

Return type:

booldog.BoolDogModel

Notes

Uses SQUAD logic to obtain Boolean network.

booldog.io.interaction_networks.read_sif(file, delim='\t', source_col=0, target_col=1, interaction_col=2, header=True, **kwargs)

Reads in a SIF file of interactions

Parameters:

file (str) – Path to the SIF file
delim (str, optional) – Delimiter used in the SIF file (default=” “)
header (bool, optional) – If the first line of the file is a header (default=True)
source_col (int or str, optional) – Column index (if int) or column name (if str) of source node (default=0)
target_col (int or str, optional) – Column index (if int) or column name (if str) of target node (default=1)
interaction_col (int, optional) – Column index (if int) or column name (if str) of interaction type (symbol) (default=2)
activator_symbol (str, optional) – Symbol of activation edges in interaction_col (default=”1”)
inhibitor_symbol (str, optional) – Symbol of inhibition edges in interaction_col (default=”-1”)
**kwargs (dict) – Additional keyword arguments (ignored).

Notes

Uses SQUAD logic to obtain Boolean network.

booldog.io.interaction_networks.read_igraph(g, node_id_key='name', edge_type_key='interaction', node_name_key='name', **kwargs)

Create BooleanNetwork from a igraph Graph object.

Parameters:

g (igraph.Graph) – The input graph object from the igraph library.
node_id_key (str, optional) – The vertex attribute key that contains the primary identifier to use for node names. Default is “name”.
node_name_key (str, optional) – The vertex attribute key that contains the node name (e.g. display label). Default is “name”.
edge_type_key (str, optional) – The edge attribute key to use for interaction values (e.g., weight, type). Default is “interaction”.
activator_symbol (str, optional) – Symbol or value of activation edges in edge_type_key of g (default=”1”)
inhibitor_symbol (str, optional) – Symbol or value of inhibition edges in edge_type_key of g (default=”-1”)
**kwargs (dict) – Additional keyword arguments (ignored).

Notes

Uses SQUAD logic to obtain Boolean network.

booldog.io.interaction_networks.read_networkx(g, edge_type_key='interaction', node_name_key='name', **kwargs)

Create BooleanNetwork from a networkx (Di)Graph object.

Parameters:

g (networkx.(Di)Graph) – The input graph object from the networkx library.
edge_type_key (str, optional) – The edge attribute key to use for interaction values (e.g., weight, type). Default is “interaction”.
activator_symbol (str, optional) – Symbol or value of activation edges in edge_type_key of g (default=”1”)
inhibitor_symbol (str, optional) – Symbol or value of inhibition edges in edge_type_key of g (default=”-1”)
node_name_key (str, optional) – The vertex attribute key that contains the node name (display label). Default is “name”.
**kwargs (dict) – Additional keyword arguments (ignored).

Returns:

n – A BoolDogModel object representing the Boolean network.

Return type:

booldog.BoolDogModel

Notes

Uses SQUAD logic to obtain Boolean network.

booldog.io.interaction_networks.read_graphml(file, edge_type_key='interaction', node_id_key='name', node_name_key='name', yEd_labels=False, yEd_arrow_head=False, use_labels=True, **kwargs)

Extract relavent parts for a Boolean network from a graphml file.

Since graphml is not well defined for Boolean networks (or even standard for interaction networks), this read functionality has limited support.

Parameters:

file (str) – Path to the graphml file
edge_type_key (str, optional) – The edge attribute key to use for interaction type (e.g., weight, type). Default is “interaction”. Only if yEd=False (yEd uses the arrow head symbol).
node_id_key (str, optional) – The vertex attribute key that contains the primary identifier to use for node names. Default is “name”.
node_name_key (str, optional) – The vertex attribute key that contains the node name (e.g. display label). Default is “name”.
yEd_labels (bool, optional) – If graphml file originates as a yEd export, the node attribute “y:NodeLabel” is used to determine node names (default=False)
yEd_arrow_head (bool, optional) – If graphml file originates as a yEd export, the edge attribute “y:Arrows” is used to determine interaction type (default=False)
activator_symbol (int or str, optional) – Symbol or value of activation edges. If yEd=True, default=”standard”, else default is 1.
inhibitor_symbol (int or str, optional) – Symbol or value of inhibition edges. If yEd=True, default=”t_shape”, else default is -1.

Returns:

n – A BoolDogModel object representing the Boolean network.

Return type:

booldog.BoolDogModel

Notes

Uses igraph to parse the graphml file, and extracts node and edge attributes to determine interactions.

If yEd_label=True, it also parses the yEd-specific attributes to extract node labels (y:NodeLabel) for node names.

If yEd_arrow_head=True, it parses the yEd-specific edge arrow types (arrow head symbols of y:Arrows) to determine interaction types (activation/inhibition).