Infer maximum-likelihood phylogenetic trees from aligned protein, DNA, or binary character data with bootstrap support. Learn more
What is RAxML-NG?
RAxML-NG infers phylogenetic trees from an existing multiple sequence alignment using maximum likelihood. It is the current-generation rewrite of RAxML and ExaML, built for faster likelihood calculations, more stable optimization, and large alignments where branch support still matters.
The practical point of RAxML-NG is not just tree building. It is tree building under explicit evolutionary models, with branch lengths, likelihood scores, and bootstrap support that can stand up in downstream comparative analyses. That makes it a better fit than approximate methods when the topology will be interpreted biologically or used in a manuscript.
ProteinIQ runs the verified RAxML-NG 2.0.2 release. This release includes fixes for automatic model selection during bootstrapping, bootstrap support metrics, and alignment-format detection that are not present in the older 2.0.0 binary.
This tool expects an alignment, not raw sequences. If the sequences are not already aligned, start with MAFFT, MUSCLE5, or Clustal Omega before running tree inference.
How does RAxML-NG work?
RAxML-NG searches tree space for the topology and branch lengths that maximize the likelihood of the observed alignment under a substitution model. In practice, that means comparing many candidate trees, optimizing branch lengths and model parameters, and keeping the trees that improve the score.
The rewrite improved several pieces of the original RAxML search procedure. The published implementation fixes missed topological moves from earlier versions, improves optimization for models such as LG4X, adds transfer bootstrap expectation (TBE), and reports terraces in tree space when the data structure implies many equally scoring topologies. It also incorporates site-repeat optimizations and parallelization improvements that matter on taxon-rich datasets.
One consequence of maximum likelihood inference is that alignment quality dominates the final result. RAxML-NG can optimize a tree very efficiently, but it cannot rescue a poor alignment, mixed paralogs, or a nucleotide alignment forced into a protein model.
How to use RAxML-NG online
RAxML-NG runs on ProteinIQ from a pre-aligned protein, DNA, or binary character dataset in FASTA or PHYLIP format. Submit the alignment, choose whether to run ML search, bootstrapping, or both, and the job returns every native result file written by RAxML-NG, including Newick trees, model information, binary alignment/checkpoint data, reduced alignments when needed, and the execution log.
Inputs
| Input | Description |
|---|---|
Alignment | One aligned protein, DNA, or binary (0/1) dataset in FASTA, PHYLIP, or plain text containing one of those formats. At least 4 sequences with unique, Newick-compatible taxon names are required. |
Job name | Optional label for the submitted job in the ProteinIQ interface. |
Settings
| Setting | Description |
|---|---|
Analysis mode | ML tree search, Bootstrapping only, or ML search + bootstrapping. ML search is the native default. |
Sequence type | Auto-detect from alignment, Protein, DNA, or Binary (0/1). Auto-detection recognizes binary matrices directly when their observed states are 0 and 1. Short nucleotide alignments made only of A, C, G, and N may need manual selection. |
Model mode | Automatic (AA, DNA, or BIN) asks RAxML-NG to select a model within the chosen family. Custom model string passes an explicit model such as GTR+G, LG+G8+F, or BIN+FO. The result summary reports the effective optimized model from the native bestModel file. |
Custom model | Required only when Model mode is set to custom. Useful when a manuscript or lab workflow needs a specific model string instead of the family default. |
Starting tree | auto, pars{N}, or rand{N}. pars{10} starts from 10 parsimony trees, rand{10} starts from 10 random trees. This only affects ML search workflows. |
Random seed | Optional positive integer used for reproducibility. Leave blank to preserve the native current-time seed. |
CPU threads | Automatic lets RAxML-NG choose up to the hosted 8-core allocation. Fixed choices of 1, 2, 4, or 8 threads are also available. |
Bootstrap trees | The native default is autoMRE{1000}, which checks convergence and can stop before 1,000 trees. Enter a fixed integer from 1 to 1,000 when an exact replicate count is required. |
Bootstrap method | Bootstrap-only mode accepts FBP, RBS, PS, or PBS. TBE requires a reference tree and is therefore available only in the combined ML search + bootstrapping mode. |
Bootstrap support metric | Combined mode supports FBP, TBE, RBS, PS, and PBS. |
Output prefix | Optional prefix for native .raxml.* filenames. Leave blank to derive it from the submitted alignment name. |
Outputs
| Output file | When it appears | Meaning |
|---|---|---|
prefix.raxml.bestTree | ML search or combined mode | Best maximum-likelihood tree in Newick format. |
prefix.raxml.bestTreeCollapsed | ML search or combined mode | Best tree with near-zero branches collapsed. |
prefix.raxml.startTree | ML search or combined mode | Starting trees generated or used by the search. This can contain more than one tree. |
prefix.raxml.mlTrees | ML search or combined mode | Candidate ML trees from the starting-tree searches. |
prefix.raxml.bootstraps | Bootstrap or combined mode | Complete bootstrap replicate tree collection. The result reports the number actually generated when automatic stopping is used. |
prefix.raxml.support or metric-specific support tree | Combined mode | Final support-annotated tree, including suffixes such as supportTBE, supportRBS, supportPS, or supportPBS. |
prefix.raxml.bestModel | When emitted by RAxML-NG | Optimized model parameters and the effective model reported in the result summary. |
prefix.raxml.rba | When emitted by RAxML-NG | Native binary alignment used for efficient reuse or diagnosis. |
prefix.raxml.reduced.phy and prefix.raxml.reduced.partition | When RAxML-NG removes fully undetermined columns | Reduced alignment and matching partition definition. |
prefix.raxml.ckp | When retained by RAxML-NG | Native checkpoint for resuming or diagnosing an analysis. |
prefix.raxml.log | Successful runs | Full native log, including final log-likelihood, AIC, and BIC when available. |
The tree viewer opens only a single final tree. Bootstrap-only runs return a multi-tree collection and are shown as downloadable files instead of being misread as one tree.
Understanding the results
RAxML-NG results are easiest to interpret in three layers: topology, branch lengths, and branch support.
Topology
The branching pattern is the inferred evolutionary hypothesis. Internal nodes define clades. A change in topology is biologically meaningful, so any region of the tree with weak support should be treated as unresolved rather than overinterpreted.
Branch lengths
Branch lengths are reported in substitutions per site. Longer branches indicate more inferred evolutionary change. Extremely long terminal branches often signal problematic sequences, alignment issues, contamination, or highly divergent taxa.
Support values
Support values only appear when bootstrap analysis is run. Lower values indicate that small changes in the resampled alignment often alter that split.
| Support value | Interpretation |
|---|---|
>= 95 | Strong support for that clade in most datasets |
80-94 | Reasonable support, often usable but worth checking against alignment quality |
70-79 | Weak to moderate support, commonly treated with caution |
< 70 | Unstable split, usually not strong evidence for that relationship |
Those cutoffs are conventions, not laws. Deep trees with uneven taxon sampling can show lower classical bootstrap support even when the overall signal is meaningful. That is one reason TBE exists.
FBP vs TBE vs RBS
| Metric | What it emphasizes | When it is useful |
|---|---|---|
FBP | Exact recovery of the same bipartition across replicates | Standard reporting and direct comparison with older phylogenetics literature |
TBE | Similarity between splits rather than exact matching | Large trees where a few unstable taxa would otherwise deflate support for deep branches |
RBS | Rapid bootstrap workflow | Faster support estimation when runtime matters more than strict comparability with classical bootstrap |
TBE is not a valid metric for bootstrap-only generation in RAxML-NG 2.0.2. Use the combined mode when TBE support is required.
When to use RAxML-NG vs alternatives
RAxML-NG occupies the middle ground between very fast approximate tree builders and feature-rich ML packages with their own model-selection ecosystems.
| Tool | Best use case | Tradeoff |
|---|---|---|
| RAxML-NG | Maximum-likelihood inference when a solid ML search and standard bootstrap workflow are the priority | Requires a pre-aligned dataset and is slower than approximate methods |
| IQ-TREE | Analyses where built-in model selection and ultrafast bootstrap are central | Different search heuristics and support framework, often more feature-focused on model testing |
| FastTree | Very large alignments where speed matters more than exact ML optimization | Much faster, but approximate |
RAxML-NG is a strong default when the alignment is already prepared and the goal is a conventional ML tree with explicit bootstrap support. IQ-TREE is often the better choice when systematic model testing is part of the analysis plan. FastTree is better for exploratory work on very large datasets where approximate topology is good enough.
Related tools
- MAFFT: Builds multiple sequence alignments before phylogenetic inference.
- MUSCLE5: Alternative MSA method for protein or nucleotide datasets.
- Clustal Omega: Scalable alignment tool that fits naturally before tree building.
- IQ-TREE: Another maximum-likelihood phylogeny tool with strong model-selection features.
- FastTree: Approximate maximum-likelihood trees for very large alignments.
Based on the RAxML-NG paper by Kozlov et al. (2019) in Bioinformatics and the official RAxML-NG source repository.
