Create a Bayesian phylogenetic inference model.

Create a Bayesian phylogenetic inference model, as can be done by BEAUti.

Usage

create_inference_model(
  site_model = create_jc69_site_model(),
  clock_model = create_strict_clock_model(),
  tree_prior = create_yule_tree_prior(),
  mrca_prior = NA,
  mcmc = create_mcmc(),
  beauti_options = create_beauti_options(),
  tipdates_filename = NA
)

Arguments

site_model

a site model, as returned by create_site_model

clock_model

a clock model, as returned by create_clock_model

tree_prior

a tree priors, as returned by create_tree_prior

mrca_prior

a Most Recent Common Ancestor prior, as returned by create_mrca_prior

mcmc

one MCMC. Use create_mcmc to create an MCMC. Use create_ns_mcmc to create an MCMC for a Nested Sampling run. Use check_mcmc to check if an MCMC is valid. Use rename_mcmc_filenames to rename the filenames in an MCMC.

beauti_options

one BEAUti options object, as returned by create_beauti_options

tipdates_filename

name of the file containing the tip dates. This file is assumed to have two columns, separated by a tab. The first column contains the taxa names, the second column contains the date.

Value

an inference model

See also

Use create_test_inference_model to create an inference model with a short MCMC, to be used in testing. Use create_ns_inference_model to create an inference model to estimate the marginal likelihood (aka evidence) using a nested sampling approach.

Author

Richèl J.C. Bilderbeek

Examples

if (is_on_ci()) {

  check_empty_beautier_folder()

  # Create an MCMC chain with 50 states
  inference_model <- create_inference_model(
    mcmc = create_mcmc(chain_length = 50000, store_every = 1000)
  )

  output_filename <- get_beautier_tempfilename()
  create_beast2_input_file_from_model(
    input_filename = get_fasta_filename(),
    output_filename = output_filename,
    inference_model = inference_model
  )
  file.remove(output_filename)

  remove_beautier_folder()
  check_empty_beautier_folder()
}