Bio Phylo Modern Tree Inference

Version Compatibility

Reference examples tested with: IQ-TREE 2.2+

Before using code patterns, verify installed versions match. If versions differ:

• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Modern ML Tree Inference

"Infer a maximum likelihood tree from my alignment" → Build publication-quality ML trees with automatic substitution model selection and ultrafast bootstrap support assessment.

• CLI: iqtree2 -s alignment.fa -m MFP -B 1000 (IQ-TREE2)
• CLI: raxml-ng --all --msa alignment.fa --model GTR+G --bs-trees 100 (RAxML-ng)

Build maximum likelihood phylogenetic trees with automatic model selection and ultrafast bootstrap.

IQ-TREE2 Basic Usage

# Simple ML tree with automatic model selection
iqtree2 -s alignment.fasta -m MFP -B 1000 -T AUTO

# -s: input alignment
# -m MFP: ModelFinder Plus (automatic model selection + tree inference)
# -B 1000: 1000 ultrafast bootstrap replicates (minimum recommended for publication)
# -T AUTO: automatic thread detection

IQ-TREE2 Output Files

Model Selection

# ModelFinder only (no tree inference)
iqtree2 -s alignment.fasta -m MF

# Use specific model
iqtree2 -s alignment.fasta -m GTR+G4 -B 1000

# Test only specific models
iqtree2 -s alignment.fasta -m MF -mset GTR,HKY,K2P

# Protein models
iqtree2 -s protein.fasta -m MFP -B 1000 -st AA

Common DNA Substitution Models

Ultrafast Bootstrap

# Standard ultrafast bootstrap (UFBoot2)
# B>=1000: Minimum for publication. Use 10000 for final analyses.
iqtree2 -s alignment.fasta -m GTR+G4 -B 1000

# Standard bootstrap (slower but more accurate for small datasets)
iqtree2 -s alignment.fasta -m GTR+G4 -b 100

# SH-aLRT test (fast approximate likelihood ratio test)
iqtree2 -s alignment.fasta -m GTR+G4 -alrt 1000

# Both UFBoot and SH-aLRT
iqtree2 -s alignment.fasta -m GTR+G4 -B 1000 -alrt 1000

Interpreting Bootstrap Values

Partitioned Analysis

For multi-gene datasets with different evolutionary rates:

# Create partition file (partitions.nex)
cat > partitions.nex << 'EOF'
#nexus
begin sets;
    charset gene1 = 1-500;
    charset gene2 = 501-1200;
    charset gene3 = 1201-1800;
    charpartition mine = HKY:gene1, GTR:gene2, GTR+G:gene3;
end;
EOF

# Run partitioned analysis
iqtree2 -s concat.fasta -p partitions.nex -m MFP -B 1000

# Edge-linked partition model (proportional branch lengths)
iqtree2 -s concat.fasta -q partitions.nex -m MFP -B 1000

# Edge-unlinked (independent branch lengths per partition)
iqtree2 -s concat.fasta -Q partitions.nex -m MFP -B 1000

RAxML-ng Basic Usage

# Simple ML tree with GTR+G
raxml-ng --all --msa alignment.fasta --model GTR+G --bs-trees 100

# --all: ML search + bootstrapping
# --msa: input alignment
# --model: substitution model
# --bs-trees: number of bootstrap replicates

RAxML-ng Model Specification

# DNA models
raxml-ng --msa alignment.fasta --model GTR+G4+I

# Protein models (automatic detection)
raxml-ng --msa protein.fasta --model LG+G8+F

# Check alignment and determine model
raxml-ng --check --msa alignment.fasta --model GTR+G

RAxML-ng Output Files

RAxML-ng Advanced Options

# Multiple ML searches (find global optimum)
# --tree pars{10}: 10 starting parsimony trees recommended for thorough search
raxml-ng --msa alignment.fasta --model GTR+G --tree pars{10} --prefix ml_search

# Constrained tree search
raxml-ng --msa alignment.fasta --model GTR+G --tree-constraint constraint.tre

# Site likelihoods for topology tests
raxml-ng --sitelh --msa alignment.fasta --model GTR+G --tree candidate.tre

Comparing IQ-TREE2 vs RAxML-ng

Large Dataset Strategies

# IQ-TREE2 with reduced memory
iqtree2 -s large.fasta -m GTR+G -B 1000 -T 4 -mem 8G

# Use approximate NNI search
iqtree2 -s large.fasta -m GTR+G -B 1000 -fast

# RAxML-ng with parsimony starting trees
raxml-ng --msa large.fasta --model GTR+G --tree pars{5} --threads 8

Tree Topology Tests

# IQ-TREE2: AU test comparing trees
iqtree2 -s alignment.fasta -m GTR+G -z trees.nwk -n 0 -zb 10000 -au

# Output interpretation:
# p-AU < 0.05: Reject tree
# p-AU >= 0.05: Cannot reject tree

Constrained Analysis

# IQ-TREE2: Enforce monophyly constraint
iqtree2 -s alignment.fasta -m GTR+G -g constraint.tre -B 1000

# Constraint file format (Newick with taxa to constrain):
# ((Human,Chimp),Gorilla);

Complete Workflow Example

# 1. Check alignment
iqtree2 -s alignment.fasta -m GTR+G -n 0

# 2. Find best model
iqtree2 -s alignment.fasta -m MF -T AUTO

# 3. Full analysis with best model
iqtree2 -s alignment.fasta -m GTR+I+G4 -B 1000 -alrt 1000 -T AUTO

# 4. Visualize result
cat alignment.fasta.treefile

Resuming Interrupted Runs

# IQ-TREE2: Resume from checkpoint
iqtree2 -s alignment.fasta -m GTR+G -B 1000 --redo-tree

# RAxML-ng: Resume
raxml-ng --msa alignment.fasta --model GTR+G --redo

Reproducibility

# Set random seed for reproducible results
# seed=12345: Any fixed seed ensures reproducibility across runs
iqtree2 -s alignment.fasta -m GTR+G -B 1000 --seed 12345

raxml-ng --msa alignment.fasta --model GTR+G --seed 12345 --bs-trees 100

Related Skills

• tree-io - Read and convert output tree files
• tree-visualization - Visualize trees with bootstrap support
• distance-calculations - Compare with distance-based methods
• alignment/alignment-io - Prepare alignments for tree inference