This vignette shows some examples how to set up different inference
models in babette.
For all examples, do load babette:
All these examples check that BEAST2 is installed at the
default location at /home/richel/.local/share/beast/lib/launcher.jar. If
this is not the case, we will use some fabricated output:
posterior <- create_test_bbt_run_output()
posterior$anthus_aco_sub_trees <- posterior$anthus_aco_trees
names(posterior)
#> [1] "estimates"            "anthus_aco_trees"     "operators"           
#> [4] "output"               "anthus_aco_sub_trees"All examples read the alignment from a FASTA file (usually
my_fasta.fas).
Instead of a full run, the MCMC chain length is shortened to 10K states, with a measurement every 1K states:
We will re-create this MCMC setup, as doing so initializes it with new filenames for temporary files. These temporary files should not exist before a run and should exist after a run. Sure, there is the option to overwrite…
Using all default settings, only specify a DNA alignment.
if (is_beast2_installed()) {
  inference_model <- create_inference_model(
    mcmc = mcmc
  )
  beast2_options <- create_beast2_options()
  posterior <- bbt_run_from_model(
    fasta_filename = fasta_filename,
    inference_model = inference_model,
    beast2_options = beast2_options
  )
  bbt_delete_temp_files(
    inference_model = inference_model,
    beast2_options = beast2_options
  )
}All other parameters are set to their defaults, as in BEAUti.
An alternative is to date the node of the most recent common ancestor of all taxa.
Create the MCMC:
if (is_beast2_installed()) {
  inference_model <- create_inference_model(
    mcmc = mcmc,
    mrca_prior = create_mrca_prior(
      taxa_names = sample(get_taxa_names(fasta_filename), size = 3),
      alignment_id = get_alignment_id(fasta_filename),
      is_monophyletic = TRUE,
      mrca_distr = create_normal_distr(
        mean = 15.0,
        sigma = 0.025
      )
    )
  )
  beast2_options <- create_beast2_options()
  posterior <- bbt_run_from_model(
    fasta_filename = fasta_filename,
    inference_model = inference_model,
    beast2_options = beast2_options
  )
  bbt_delete_temp_files(
    inference_model = inference_model,
    beast2_options = beast2_options
  )
}Here we use an MRCA prior with fixed (non-estimated) values of the mean and standard deviation for the common ancestor node’s time.
if (is_beast2_installed()) {
  inference_model <- create_inference_model(
    site_model = create_jc69_site_model(),
    mcmc = mcmc
  )
  beast2_options <- create_beast2_options()
  posterior <- bbt_run_from_model(
    fasta_filename = fasta_filename,
    inference_model = inference_model,
    beast2_options = beast2_options
  )
  bbt_delete_temp_files(
    inference_model = inference_model,
    beast2_options = beast2_options
  )
}if (is_beast2_installed()) {
  inference_model <- create_inference_model(
    clock_model = create_rln_clock_model(),
    mcmc = mcmc
  )
  beast2_options <- create_beast2_options()
  posterior <- bbt_run_from_model(
    fasta_filename = fasta_filename,
    inference_model = inference_model,
    beast2_options = beast2_options
  )
  bbt_delete_temp_files(
    inference_model = inference_model,
    beast2_options = beast2_options
  )
}if (is_beast2_installed()) {
  inference_model <- create_inference_model(
    tree_prior = create_bd_tree_prior(),
    mcmc = mcmc
  )
  beast2_options <- create_beast2_options()
  posterior <- bbt_run_from_model(
    fasta_filename = fasta_filename,
    inference_model = inference_model,
    beast2_options = beast2_options
  )
  bbt_delete_temp_files(
    inference_model = inference_model,
    beast2_options = beast2_options
  )
}if (is_beast2_installed()) {
  inference_model <- create_inference_model(
    tree_prior = create_yule_tree_prior(
      birth_rate_distr = create_normal_distr(
        mean = 1.0,
        sigma = 0.1
      )
    ),
    mcmc = mcmc
  )
  beast2_options <- create_beast2_options()
  posterior <- bbt_run_from_model(
    fasta_filename = fasta_filename,
    inference_model = inference_model,
    beast2_options = beast2_options
  )
  bbt_delete_temp_files(
    inference_model = inference_model,
    beast2_options = beast2_options
  )
}Thanks to Yacine Ben Chehida for this use case
if (is_beast2_installed()) {
  inference_model <- create_inference_model(
    site_model = create_hky_site_model(
      gamma_site_model = create_gamma_site_model(prop_invariant = 0.5)
    ),
    mcmc = mcmc
  )
  beast2_options <- create_beast2_options()
  posterior <- bbt_run_from_model(
    fasta_filename = fasta_filename,
    inference_model = inference_model,
    beast2_options = beast2_options
  )
  bbt_delete_temp_files(
    inference_model = inference_model,
    beast2_options = beast2_options
  )
}Thanks to Yacine Ben Chehida for this use case
if (is_beast2_installed()) {
  inference_model <- create_inference_model(
    clock_model = create_strict_clock_model(
      clock_rate_param = 0.5
    ),
    mcmc = mcmc
  )
  beast2_options <- create_beast2_options()
  posterior <- bbt_run_from_model(
    fasta_filename = fasta_filename,
    inference_model = inference_model,
    beast2_options = beast2_options
  )
  bbt_delete_temp_files(
    inference_model = inference_model,
    beast2_options = beast2_options
  )
}Thanks to Paul van Els and Yacine Ben Chehida for this use case.