Calculate support for modules from summary networks based on modules of sampled networks

Validate modules from summary networks by calculating the frequency with which pairs of nodes are placed in the same module in networks sampled across MCMC

Usage

support_for_modules(
  mod_samples,
  modules_across_ages,
  threshold = 0.7,
  edge_list = TRUE,
  include_all = FALSE,
  colors = NULL,
  module_levels = NULL,
  axis_text = FALSE
)

Arguments

mod_samples

Data frame produced by modules_from_samples() containing module membership of each node for each sampled network at each time slice before the present.

modules_across_ages

Data frame containing the module information for the summary network. A list object returned from modules_across_ages() or a data.frame object defining the modules in the networks. If a data.frame is passed, it must contain three columns: $age - the age of the network, $name - taxon names, $module - the module the taxon was assigned to.

threshold

Minimum frequency with which two nodes are placed in the same module to consider it supported. Only pairs with frequency higher than this threshold are plotted with the color of the module from the summary network.

edge_list

Logical. Whether to return a list of edge lists or a list of matrices of pairwise frequency.

include_all

Logical. Include all nodes or only those present at the time slice?

colors

Optional. Vector of module colors in the plot.

module_levels

Optional. Order of modules in the color vector.

axis_text

Logical. Plot taxon names?

Value

A list containing:

1. plot: A plot of pairwise frequency with which the two nodes are placed in the same module in the ancestral network for each time slice in ages. Cells in the diagonal show how often a host is sampled in a network (symbionts are always present);

2. pairwise_membership: A list of edge lists or matrices with the pairwise frequencies at each time slice;

3. mean_support: A list of mean and geometric mean pairwise frequency for each module at each time slice.

Examples

if (FALSE) {
  ages <- c(60, 50, 40, 0)
  at_ages <- posterior_at_ages(history, ages, tree, host_tree)

  weighted_net_50 <- get_summary_network(at_ages, pt = 0.5, weighted = TRUE)
  all_mod <- modules_across_ages(weighted_net_50, tree)

  # find modules for each sampled network
  mod_samples <- modules_from_samples(at_ages)

  # calculate support
  support <- support_for_modules(mod_samples, all_mod)
  support$plot
  support$means
}