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BEAST

Description

beastx website

BEAST is a cross-platform program for Bayesian analysis of molecular sequences using MCMC. It is entirely orientated towards rooted, time- measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability. We include a simple to use user-interface program for setting up standard analyses and a suit of programs for analysing the results.

Environment Modules

Run module spider beastx to find out what environment modules are available for this application.

Environment Variables

  • HPC_BEASTX_DIR - installation directory
  • HPC_BEASTX_BIN - executable directory
  • HPC_BEASTX_DOC - documentation directory

Additional Usage Information

  • Load the beastx module in the terminal
  • Type "beast -h" to view usage

Interactive BEAST X and BEAUti use

See https://beast.community/beast and https://beast.community/beauti for general documentation on using BEAST X and BEAUti, respectively.

  • Start an OnDemand session (console or desktop)
  • Load the beastx module in the terminal
  • Type "beast" or "beauti" to launch the application

See GUI Programs for reference.

Beagle Use

  • Use -beagle_GPU beast command-line argument to invoke BEAST with GPU acceleration when running in a GPU Job
  • To use CPU acceleration with the beagle library, use the '-beagle_SSE -beagle_instances N' command line switches where 'N' equals to the number of requested Beagle library instances.
  • To limit the number of computing cores Beast will use for posterior computation to the number requested from the batch system use the '-threads N' where 'N' is the number of threads. Then, the job resource request should be equal to
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=X

where X = N + 1.

Categories

biology, phylogenetics