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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