This repository is set up so people can reproduce the benchmarking results for the paper A Generalized Phylogenetic Pruning Algorithm by Jun, Nasif, Jennings-Shaffer, Rich, Kooperberg, Fourment, Zhang, Suchard, and Matsen IV.
See the paper for data citations, and please cite the respective papers if you re-use the data.
- Install bito
- Install bito GP benchmark environment
- Install Git Large File Storage (LFS) and retrieve DS test data files
conda install -c conda-forge git-lfs && git lfs install
git lfs pull
- The MrBayes scripts to produce the posterior samples for each dataset are found in
ds-benchmark/MrBayesScripts
- There are two scripts used to sample from the posterior with either uniform or exponential prior on branch lengths.
- To execute one of the scripts, such as with the uniform prior:
bash run-unif-ds.sh
- MrBayes specifications and the posterior tree samples are located in the respective dataset directories found in
ds-benchmark/
- Git LFS is required to retrieve these data files.
- Location:
ds-benchmark/
- To run benchmark on all datasets:
conda activate bito && bash 0run-all-benchmark-golden.sh
- To run benchmark on all datasets through a SLURM job:
sbatch sbatch-run-all-golden.sh
- To run benchmark on all datasets:
- Results are output to:
ds-benchmark/_golden_benchmark-results/
- A copy of this results output is saved in the directory
manuscript_results/
- A copy of this results output is saved in the directory
- Location:
ds-benchmark/vbpi-exp
- See the following repository for instructions on reproducing these results:
- The Makona data estimation script is located in
makona-benchmark/
- To run the makona script:
conda activate bito && bash run-makona.sh
- To run the makona script:
- Results are output to:
makona-benchmark/_output