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Calculate the posterior probability of ancestral host repertoires at time points in the past (ages)

Source: R/posterior_at_ages.R
posterior_at_ages.Rd

Calculate the posterior probability of ancestral host repertoires at time points in the past (ages)

Usage

posterior_at_ages(
  history,
  ages,
  tree,
  host_tree,
  extant_prob = FALSE,
  state = 2,
  drop_empty = TRUE
)

Arguments

history

Data frame with posterior samples of interaction histories. Output from read_history().

ages

Vector of ages (time points in the past) at which samples will be retrieved. The present (age = 0) must be included.

tree

Symbiont tree.

host_tree

Host tree.

extant_prob

Should posterior probabilities be calculated for extant network? Default to FALSE. TRUE only makes sense if interactions in the extant network were also inferred. When FALSE, only the first MCMC sample will be retrieved at age = 0.

state

Which state? Default is 2. For analyses using the 3-state model, give c(1, 2) to include both states (where 1 is a potential host and 2 an actual host).

drop_empty

Logical. Remove taxa without any interactions?

Value

A list of three lists, containing:

  • "samples" Arrays of samples x nodes x hosts, containing the state of each sample.

  • "post_states" Arrays of nodes x hosts x state containing the posterior probability for each state.

  • "post_repertoires" Arrays of nodes x hosts x repertoire containing the posterior probability for 1) the "realized" repertoire which is defined as state 2, and 2) the "fundamental" repertoire which is defined as having any state (usually 1 or 2).

Each array in these lists is for one of the ages. The number of samples is the number of iterations in history.

Examples

# read symbiont and host tree
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"))

# read histories sampled during MCMC
history <- read_history(paste0(data_path,"/history_thin_pieridae.txt"), burnin = 0)

# get samples at ages
ages <- c(80,70,0)
at_ages <- posterior_at_ages(history, ages, tree, host_tree)
samples_at_ages <- at_ages$samples

# get posterior probabilities of states at ages
pp_at_ages <- at_ages$post_states