Visualize Community and Topology Comparison

Creates visualization plots for community assignment metrics and topological properties comparison.

Usage

plot_community_comparison(
  community_metrics,
  topology_measures,
  control_topology
)

Arguments

community_metrics

A data frame with VI, NMI, and ARI scores (output from compute_community_metrics()).

topology_measures

A data frame with Modularity, Communities, Density, and Transitivity (from compute_topology_metrics()).

control_topology

A named numeric vector of control network topology metrics (from compute_topology_metrics()).

Value

Invisibly returns NULL. Displays a radar plot for community metrics and bar plots for topology comparison.

Details

This function requires the fmsb package for radar chart visualization. The radar plot shows normalized community similarity metrics. The bar plots compare raw topological properties between predicted and control networks.

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
#> '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

comm_metrics <- compute_community_metrics(comm_truth, list(comm_cons))
topo_metrics <- compute_topology_metrics(comm_truth, list(comm_cons))

plot_community_comparison(
    comm_metrics,
    topo_metrics$topology_measures,
    topo_metrics$control_topology
)