Degree Model

class pygna.degree_model.DegreeModel(network_prob: float = 0.5, vip_prob: float = 1, n_nodes: int = 10, vip_percentage: float = 0.1)

This class is used to calculate a degree model

create_graph() → None

Create a graph from the nodes

Example

>>> dm = DegreeModel()
>>> dm.create_graph()

set_nodes(nodes_names: list) → None

Set the name of the nodes and calculate the lenght of the list

Parameters:nodes_names – the list with the nodes name

Example

>>> nodes = list("A", "B", "C")
>>> dm = DegreeModel()
>>> dm.set_nodes(nodes)

write_genelist(output_file: str) → None

Write the GMT gene list on a specific file

Parameters:output_file – the file path where to save the gene list

Example

>>> dm = DegreeModel()
>>> dm.write_genelist("myoutput.gmt")

write_network(output_file: str) → None

Write on file the network as an edge list

Parameters:output_file – the file path where to save the network

Example

>>> dm = DegreeModel()
>>> dm.write_network("myoutputfile.tsv")

pygna.degree_model.generate_graph_vip(n_nodes: int, n_vip: int, network_prob: float = 0.5, vip_prob: float = 1, node_names: list = None) → networkx.classes.graph.Graph

This function creates a graph with n_nodes number of vertices and a matrix block_model that describes the intra e inter-block connectivity. The nodes_in_block is parameter, list, to control the number of nodes in each cluster

Parameters:

• n_nodes – number of nodes in the network
• n_vip – number of VIP to create
• network_prob – probability of connection in the network
• vip_prob – probability of connection of the vip
• node_names – list of nodes for the network

Example

>>> n_nodes = 100
>>> n_vip = 10
>>> network_prob = 0.5
>>> vip_prob = 1
>>> nodes = ["A", "B", "C"]
>>> graph = generate_graph_vip(n_nodes, n_vip, network_prob=network_prob, vip_prob=vip_prob, node_names=nodes)

pygna.degree_model.plot_vip_graph(graph: networkx.classes.graph.Graph, output_folder: str = None) → None

Plot the VIP graph in the specific folder

Parameters:

• graph – the graph to plot
• output_folder – the folder path where to save the file

Example

>>> g = nx.complete_graph(100)
>>> plot_vip_graph(g, "./")

pygna.degree_model.plot_adjacency(graph: networkx.classes.graph.Graph, output_folder: str, prefix: str) → None

Plot the adjacency matrix on file

Parameters:

• graph – the graph to plot
• output_folder – the folder where to save the file
• prefix – the prefix to give to the file

Example

>>> g = nx.complete_graph(100)
>>> plot_adjacency(g, "./","adj_matrix_")