babette: Step by Step

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Richèl J.C. Bilderbeek

2024-06-24

Introduction

This step-by-step demo shows how to run the babette pipeline in detail.

First, load babette:

library(babette)

In all cases, this is done for a short MCMC chain length of 10K:

inference_model <- create_inference_model()
inference_model$mcmc$chain_length <- 10000
inference_model$mcmc$tracelog$filename <- normalizePath(
  get_beautier_tempfilename(
    pattern = "tracelog_", fileext = ".log"
  ),
  mustWork = FALSE
)
inference_model$mcmc$treelog$filename <- normalizePath(
  get_beautier_tempfilename(
    pattern = "treelog_",
    fileext = ".trees"
  ),
  mustWork = FALSE
)

Create a ‘BEAST2’ input file

This step is commonly done using BEAUti. With babette, this can be done as follows:

beast2_input_file <- tempfile(pattern = "beast2_", fileext = ".xml")
create_beast2_input_file_from_model(
  input_filename = get_babette_path("anthus_aco.fas"),
  inference_model = inference_model,
  output_filename = beast2_input_file
)

Display (part of) the ‘BEAST2’ input file

print(head(readLines(beast2_input_file)))
#> [1] "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?><beast beautitemplate='Standard' beautistatus='' namespace=\"beast.core:beast.evolution.alignment:beast.evolution.tree.coalescent:beast.core.util:beast.evolution.nuc:beast.evolution.operators:beast.evolution.sitemodel:beast.evolution.substitutionmodel:beast.evolution.likelihood\" required=\"\" version=\"2.4\">"
#> [2] ""                                                                                                                                                                                                                                                                                                                                                                                   
#> [3] ""                                                                                                                                                                                                                                                                                                                                                                                   
#> [4] "    <data"                                                                                                                                                                                                                                                                                                                                                                          
#> [5] "id=\"anthus_aco\""                                                                                                                                                                                                                                                                                                                                                                  
#> [6] "name=\"alignment\">"

This file can both be loaded by BEAUti and be used by ‘BEAST2’.

The file can be checked if it is indeed a valid input file:

if (is_beast2_installed()) {
  is_beast2_input_file(beast2_input_file)
}

Run MCMC

This step is commonly done using ‘BEAST2’ from the command-line or using its GUI. With babette, this can be done as follows:

if (is_beast2_installed()) {
  beast2_options <- create_beast2_options(
    input_filename = beast2_input_file
  )
  beastier::check_can_create_file(beast2_options$output_state_filename)
  beastier::check_can_create_treelog_file(beast2_options)
  run_beast2_from_options(
    beast2_options = beast2_options
  )
  if (!file.exists(beast2_options$output_state_filename)) {
    stop("the filename should have been created.")
  }
}

Display (part of) the ‘BEAST2’ output files

The .log file contains the model parameters and parameter estimates:

if (is_beast2_installed()) {
  print(head(readLines(inference_model$mcmc$tracelog$filename)))
  print(tail(readLines(inference_model$mcmc$tracelog$filename)))
}

The .trees file contains the alignment, taxa and posterior trees:

if (is_beast2_installed()) {
  print(head(readLines(inference_model$mcmc$treelog$filename)))
  print(tail(readLines(inference_model$mcmc$treelog$filename)))
}

The .xml.state file contains the final state of the MCMC run and the MCMC operator acceptances thus far:

if (is_beast2_installed()) {
  print(head(readLines(beast2_options$output_state_filename)))
  print(tail(readLines(beast2_options$output_state_filename)))
}

Parse output

This step is commonly done using Tracer. With babette, this can be done as follows.

Parsing .log file to obtain the parameter estimates:

if (is_beast2_installed()) {
  knitr::kable(
    head(parse_beast_tracelog_file(inference_model$mcmc$tracelog$filename))
  )
}

Parsing .trees file to obtain the posterior phylogenies:

if (is_beast2_installed()) {
  plot_densitree(parse_beast_trees(inference_model$mcmc$treelog$filename))
}

Parsing .xml.state file to obtain the MCMC operator acceptances:

if (is_beast2_installed()) {
  knitr::kable(
    head(parse_beast_state_operators(beast2_options$output_state_filename))
  )
}

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.