Plot protein-protein interaction network from edge list

Usage

plot_ppi(
  edgelist_int,
  color_by = "community",
  clustering_method = igraph::cluster_infomap,
  show_labels = "tophubs",
  top_n_hubs = 5,
  add_color_legend = TRUE,
  curvature = 0,
  interactive = FALSE,
  dim_interactive = c(600, 600)
)

Arguments

edgelist_int: Data frame containing the edge list for the PPI network. First column is the protein 1 and second column is the protein 2. All other columns are interpreted as edge attributes.
color_by: How should nodes be colored? It must be either "community" or a 2-column data frame containing proteins in the first column and a custom annotation in the second column. If "community", a clustering algorithm will be applied. Default: "community".
clustering_method: igraph function to be used for community detection. Available functions are cluster_infomap, cluster_edge_betweenness, cluster_fast_greedy, cluster_walktrap, cluster_spinglass, cluster_leading_eigen, cluster_louvain, and cluster_label_prop. Default is cluster_infomap.
show_labels: Character indicating which nodes will be labeled. One of "all", "allhubs", "tophubs", or "none".
top_n_hubs: Number of top hubs to be labeled. It is only valid if show_labels equals "tophubs". Default is 5.
add_color_legend: Logical indicating whether to add a color legend for nodes. Default: TRUE.
curvature: Numeric indicating the amount of curvature in edges. Negative values produce left-hand curves, positive values produce right-hand curves, and zero produces a straight line. Default: 0.
interactive: Logical indicating whether the network should be interactive or not. Default is FALSE.
dim_interactive: Numeric vector with width and height of window for interactive plotting. Default: c(600,600).

Value

A ggplot object.

Author

Fabricio Almeida-Silva

Examples

ppi_edges <- igraph::sample_pa(n = 500)
ppi_edges <- igraph::as_edgelist(ppi_edges)
p <- plot_ppi(ppi_edges, add_color_legend = FALSE)