bio-phylo-modern-tree-inference

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---

name: bio-phylo-modern-tree-inference

description: Build maximum likelihood phylogenetic trees using IQ-TREE2 and RAxML-ng. Use when inferring publication-quality trees with model selection, ultrafast bootstrap, or partitioned analyses from sequence alignments.

tool_type: cli

primary_tool: IQ-TREE2

measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.

allowed-tools:

• read_file
• run_shell_command

---

Modern ML Tree Inference

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

| File | Description |

|------|-------------|

| .treefile | Best ML tree in Newick format |

| .iqtree | Full analysis report with model parameters |

| .log | Run log |

| .contree | Consensus tree with bootstrap support |

| .splits.nex | Bootstrap splits in Nexus format |

| .model.gz | Model parameters |

| .bionj | Initial BIONJ tree |

| .mldist | ML distance matrix |

| .ckp.gz | Checkpoint file for resuming |

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

| Model | Parameters | Use Case |

|-------|------------|----------|

| JC | Equal rates | Very simple, rarely appropriate |

| K2P/K80 | Ti/Tv ratio | Simple, some rate variation |

| HKY | Ti/Tv + base freq | Moderate complexity |

| GTR | 6 rates + base freq | Most general, recommended default |

| +G4 | Gamma rate variation | 4 discrete rate categories |

| +I | Invariant sites | Sites that never change |

| +R4 | FreeRate model | More flexible than Gamma |

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

| UFBoot | SH-aLRT | Interpretation |

|--------|---------|----------------|

| >= 95 | >= 80 | Strong support |

| 80-94 | 70-79 | Moderate support |

| < 80 | < 70 | Weak support |

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

| File | Description |

|------|-------------|

| .raxml.bestTree | Best ML tree |

| .raxml.support | Tree with bootstrap support values |

| .raxml.bootstraps | All bootstrap trees |

| .raxml.mlTrees | All ML trees from search |

| .raxml.log | Analysis log |

| .raxml.rba | Binary alignment (for restart) |

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

| Feature | IQ-TREE2 | RAxML-ng |

|---------|----------|----------|

| Model selection | Built-in ModelFinder | External (ModelTest-NG) |

| Ultrafast bootstrap | Yes (UFBoot2) | No |

| Standard bootstrap | Yes | Yes |

| Partition models | Extensive | Good |

| Speed | Faster for UFBoot | Faster for standard BS |

| Memory | Lower | Higher |

| Checkpointing | Yes | Yes |

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

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