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Compute Network Topological Properties

Source: R/compute_topology_metrics.R
compute_topology_metrics.Rd

Calculates topological properties (modularity, number of communities, density, transitivity) for one or more networks.

Usage

compute_topology_metrics(control_output, predicted_list)

Arguments

control_output

A list output from community_path() representing the ground truth network. Must contain a graph (igraph object) and communities$membership.

predicted_list

A list of lists, each output from community_path() representing predicted networks.

Value

A list containing:

  • topology_measures: A data frame with Modularity,Communities, Density, and Transitivity for each prediction.

  • control_topology: A numeric vector of the same metrics for the control network.

Details

This function requires the igraph package. Topological metrics include:

  • Modularity: Quality of community division

  • Communities: Number of detected communities

  • Density: Proportion of actual vs. possible edges

  • Transitivity: Clustering coefficient

Examples

data(toy_counts)
data(toy_adj_matrix)


# Infer networks (toy_counts is already a MultiAssayExperiment)
networks <- infer_networks(
    count_matrices_list = toy_counts,
    method = "GENIE3",
    nCores = 1
)

# Generate adjacency matrices
wadj_se <- generate_adjacency(networks)
swadj_se <- symmetrize(wadj_se, weight_function = "mean")

# Apply cutoff
binary_se <- cutoff_adjacency(
    count_matrices = toy_counts,
    weighted_adjm_list = swadj_se,
    n = 1,
    method = "GENIE3",
    quantile_threshold = 0.95,
    nCores = 1
)

consensus <- create_consensus(binary_se, method = "union")
comm_cons <- community_path(consensus)
#> Detecting communities...

#> Running pathway enrichment...
#> 'select()' returned 1:1 mapping between keys and columns
#> 'select()' returned 1:1 mapping between keys and columns
#> 'select()' returned 1:1 mapping between keys and columns
comm_truth <- community_path(toy_adj_matrix)
#> Detecting communities...

#> Running pathway enrichment...
#> 'select()' returned 1:1 mapping between keys and columns
#> 'select()' returned 1:1 mapping between keys and columns
#> 'select()' returned 1:1 mapping between keys and columns

topo <- compute_topology_metrics(comm_truth, list(comm_cons))