Tool for estimating the Felsenstein Bootstrap support of phylogenetic trees
Project description
EBG: Educated Bootstrap Guesser
Documentation: https://github.com/wiegertj/EBG/wiki
Description
EBG is a Python tool for predicting the Felsenstein Bootstrap Support of phylogenies inferred by RAxML-NG. It was trained on empirical datasets from TreeBASE and can use both AA and DNA data.
Installation
Using conda
The latest version of EBG can easily be installed via conda:
conda install ebg -c conda-forge
Using pip
pip install ebg
Usage Example
A simple command line call of EBG looks like this:
ebg -msa /test/example.fasta -tree /test/example.bestTree -model /test/example.bestModel -t b -o test
This command will use the MSA in fasta format, and the best tree inferred with RAxML-NG and the model.
By selecting -t b
(oth) EBG will output the bootstrap predictions as well as the probabilities for exceeding different bootstrap thresholds (70, 75, 80, 85).
The results will be stored in a folder called test.
Please keep in mind that EBG requires an installation of RAxML-NG. By default, it uses the command raxml-ng
.
If your RAxML-NG installation is not part of the PATH variable, you can specify the path to the RAxML-NG binary file with the parameter -raxmlng PATH_TO_RAXMLNG
.
References
- A. M. Kozlov, D. Darriba, T. Flouri, B. Morel, and A. Stamatakis (2019) RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference Bioinformatics, 35(21): 4453–4455. https://doi.org/10.1093/bioinformatics/btz305
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