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Tutorial
RAxML-NG replaces standard RAxML as well as the corresponding supercomputer version ExaML. So RAxML-NG is one single code base that scales from the laptop to the supercomputer. RAxML-NG does not (yet) support all options of standard RAxML, only the most important and frequently used ones. Some options are now implemented as stand-alone tools, e.g. phylogenetic placement (EPA).
This tutorial is based on RAxML-NG practical taught by Alexandros Stamatakis at COME 2018. It will cover most common use cases, for information on advanced usage see next section.
Before you start:
- Download and install RAxML-NG (instructions)
- Download a toy dataset:
If you run RAxML-NG executable without parameters, it will show quick usage help:
RAxML-NG v. 0.7.0git BETA released on 31.10.2018 by The Exelixis Lab.
Authors: Alexey Kozlov, Alexandros Stamatakis, Diego Darriba, Tomas Flouri, Benoit Morel.
Latest version: https://github.com/amkozlov/raxml-ng
Questions/problems/suggestions? Please visit: https://groups.google.com/forum/#!forum/raxml
WARNING: This is a BETA release, please use at your own risk!
Usage: raxml-ng [OPTIONS]
Commands (mutually exclusive):
--help display help information
--version display version information
--evaluate evaluate the likelihood of a tree (with model+brlen optimization)
--search ML tree search.
--bootstrap bootstrapping
--all all-in-one (ML search + bootstrapping).
--support compute bipartition support for a given reference tree (e.g., best ML tree)
and a set of replicate trees (e.g., from a bootstrap analysis)
--bsconverge test for bootstrapping convergence using autoMRE criterion
--terrace check whether a tree lies on a phylogenetic terrace
--check check alignment correctness and remove empty columns/rows
--parse parse alignment, compress patterns and create binary MSA file
--start generate parsimony/random starting trees and exit
--loglh compute the likelihood of a fixed tree (no model/brlen optimization)
Input and output options:
[...]
More comprehensive documentation is available in GitHub wiki. Further information and benchmarks can be found in biorxiv preprint and in Chapter 4 of Alexey's PhD thesis.
If you cannot find an answer to your question in the above sources, or if you think you found a bug, please contact us via RAxML google group.
- Please use search function before posting, since many questions have been answered before.
- Please use google group and not personal e-mail for asking questions about RAxML-NG. This will save everybody's time: you might get help sooner from other Exelixis lab members or your fellow users. And whoever might encounter the same problem in the future will benefit from the answer.