Skip to main content
`Ctrl`+`K`

Note

Go to the end to download the full example code.

# Betweenness Centrality

Betweenness centrality measures of positive gene functional associations using WormNet v.3-GS.

Data from: https://www.inetbio.org/wormnet/downloadnetwork.php

    from random import sample
    import networkx as nx
    import matplotlib.pyplot as plt

    # Gold standard data of positive gene functional associations
    # from https://www.inetbio.org/wormnet/downloadnetwork.php
    G = nx.read_edgelist("WormNet.v3.benchmark.txt")

    # remove randomly selected nodes (to make example fast)
    num_to_remove = int(len(G) / 1.5)
    nodes = sample(list(G.nodes), num_to_remove)
    G.remove_nodes_from(nodes)

    # remove low-degree nodes
    low_degree = [n for n, d in G.degree() if d < 10]
    G.remove_nodes_from(low_degree)

    # largest connected component
    components = nx.connected_components(G)
    largest_component = max(components, key=len)
    H = G.subgraph(largest_component)

    # compute centrality
    centrality = nx.betweenness_centrality(H, k=10, endpoints=True)

    # compute community structure
    lpc = nx.community.label_propagation_communities(H)
    community_index = {n: i for i, com in enumerate(lpc) for n in com}

    #### draw graph ####
    fig, ax = plt.subplots(figsize=(20, 15))
    pos = nx.spring_layout(H, k=0.15, seed=4572321)
    node_color = [community_index[n] for n in H]
    node_size = [v * 20000 for v in centrality.values()]
    nx.draw_networkx(
        H,
        pos=pos,
        with_labels=False,
        node_color=node_color,
        node_size=node_size,
        edge_color="gainsboro",
        alpha=0.4,
    )

    # Title/legend
    font = {"color": "k", "fontweight": "bold", "fontsize": 20}
    ax.set_title("Gene functional association network (C. elegans)", font)
    # Change font color for legend
    font["color"] = "r"

    ax.text(
        0.80,
        0.10,
        "node color = community structure",
        horizontalalignment="center",
        transform=ax.transAxes,
        fontdict=font,
    )
    ax.text(
        0.80,
        0.06,
        "node size = betweenness centrality",
        horizontalalignment="center",
        transform=ax.transAxes,
        fontdict=font,
    )

    # Resize figure for label readability
    ax.margins(0.1, 0.05)
    fig.tight_layout()
    plt.axis("off")
    plt.show()

Total running time of the script: (0 minutes 3.628 seconds)

Gallery generated by Sphinx-Gallery