Get summary networks from posterior probabilities of interactions of extant lineages at given time points in the past

Usage

get_summary_networks(
  at_ages,
  threshold,
  ages = NULL,
  weighted = TRUE,
  type = "states",
  state = 2,
  repertoire = "fundamental"
)

Arguments

at_ages: List of lists, with samples and posterior probabilities for each interaction of extant lineages at given ages. Usually calculated posterior_at_ages, see example.
threshold: Probability threshold to include an interaction in the network. Interactions with posterior probability < threshold will be dropped.
ages: Vector of ages (time points in the past) at which samples were retrieved. By default, uses all ages present in pp_at_ages.
weighted: Logical. Use posterior probabilities as interaction weights?
type: One of 'states' or 'repertoires'. If 'states', will plot the presence of a state when its posterior probablity is higher than threshold. If 'repertoires', will plot the same but for the given repertoire. Note that this is also applied to the extant network.
state: Which state? Default is 2. For analyses using the 3-state model, choose 1, 2 or both using c(1, 2) (where 1 is a potential host and 2 an actual host). Only used if type is 'states'. Note that this is also applied to the extant network.
repertoire: Either the 'realized' repertoire which is defined as state 2, or the 'fundamental' repertoire (default) which is defined as having any state (usually 1 or 2), and in the 3-state model includes both actual and potential hosts. Note that this is also applied to the extant network.

Value

A list of incidence matrices (summary network) for each time slice in ages.

Examples

# read data that comes with the package
data_path <- system.file("extdata", package = "evolnets")
tree <- read_tree_from_revbayes(paste0(data_path,"/tree_pieridae.tre"))
host_tree <- ape::read.tree(paste0(data_path,"/host_tree_pieridae.phy"))
history <- read_history(paste0(data_path,"/history_thin_pieridae.txt"), burnin = 0)

# choose ages in the past
ages <- c(60, 50, 40, 0)

# calculate posterior probabilities of interactions
at_ages <- posterior_at_ages(history, ages, tree, host_tree)

# get ancestral summary networks
weighted_net_50 <- get_summary_networks(at_ages, threshold = 0.5, weighted = TRUE)
binary_net_90 <- get_summary_networks(at_ages, threshold = 0.9, weighted = FALSE)