mcbette (version 1.15.3)

mcbette-package: mcbette: Model Comparison Using Babette

Description

'mcbette' does a model comparing using babette, where the models are Bayesian phylogenetic models, as created by create_inference_model.

Author

Richèl J.C. Bilderbeek

Details

The main function is est_marg_liks, which estimate the marginal likelihoods (aka evidence) for one or more inference models, based on a single alignment. Also, the marginal likelihoods are compared, resulting in a relative weight for each model, where a relative weight of a model close to 1.0 means that that model is way likelier than the others.

In the process, multiple (temporary) files are created (where [x] denotes the index in a list)

• beast2_optionses[x]$input_filename path to the the BEAST2 XML input file

• beast2_optionses[x]$output_state_filename path to the BEAST2 XML state file

• inference_models[x]$mcmc$tracelog$filename path to the BEAST2 trace file with parameter estimates

• inference_models[x]$mcmc$treelog$filename path to the BEAST2 trees file with the posterior trees

• inference_models[x]$mcmc$screenlog$filename path to the BEAST2 screen output file

These file can be deleted manually by bbt_delete_temp_files, else these will be deleted automatically by the operating system.

See Also

Use can_run_mcbette to see if 'mcbette' can run.

Examples

if (can_run_mcbette()) {

  # An example FASTA file
  fasta_filename <- system.file("extdata", "simple.fas", package = "mcbette")

  inference_model_1 <- beautier::create_ns_inference_model(
    site_model = beautier::create_jc69_site_model()
  )
  inference_model_2 <- beautier::create_ns_inference_model(
    site_model = beautier::create_gtr_site_model()
  )

  # Shorten the run, by doing a short (dirty, unreliable) MCMC
  inference_model_1$mcmc <- beautier::create_test_ns_mcmc()
  inference_model_2$mcmc <- beautier::create_test_ns_mcmc()

  inference_models <- c(list(inference_model_1), list(inference_model_2))

  # Estimate the marginal log-likelihoods of the two models
  marg_liks <- est_marg_liks(
    fasta_filename = fasta_filename,
    inference_models = inference_models
  )

  # Interpret the results
  interpret_marg_lik_estimates(marg_liks)

  beastier::remove_beaustier_folders()
  beastier::check_empty_beaustier_folders()
}