Version Compatibility

Reference examples tested with: ASTER 1.15+ (ASTRAL-III/wASTRAL/ASTRAL-Pro), IQ-TREE 2.2+ (concordance factors), PAUP* 4.0a168+ (SVDQuartets)

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

• CLI:

  astral --version

  then

  astral --help

  to confirm flags
• CLI:

  iqtree2 --version

  then

  iqtree2 --help

  to confirm flags
• CLI: PAUP* version displayed at startup

If commands fail, introspect the installed version and adapt flags rather than retrying.

Coalescent-Based Species Tree Estimation

"Estimate a species tree from multi-locus data" -> Infer the species-level phylogeny accounting for gene tree discordance caused by incomplete lineage sorting (ILS), using summary coalescent or full-likelihood methods.

• CLI:

  astral -i gene_trees.tre -o species_tree.tre

  (ASTER/ASTRAL-III)
• CLI:

  iqtree2 -t species.tre --gcf gene_trees.tre -s concat.fasta --scfl 100

  (concordance factors)
• CLI:

  svdquartets nquartets=all bootstrap=standard nreps=100

  (PAUP*)

When Concatenation Fails

The multispecies coalescent (MSC) models gene tree discordance arising from incomplete lineage sorting. Concatenation assumes all genes share the same tree, an assumption violated in three key scenarios:

1. Short internal branches relative to population size: When internodes are short (in coalescent units), lineages fail to coalesce within species boundaries, producing ILS. The shorter the internode and the larger the effective population size, the more discordance.

2. The anomaly zone: A region of tree space where the most common gene tree topology does NOT match the species tree. Concatenation becomes statistically inconsistent in the anomaly zone; more data makes the wrong answer more confident. This occurs when successive internal branches are both very short.

3. Rapid radiations: Short successive speciation events maximize the proportion of tree space in the anomaly zone. Phylogenomic datasets spanning rapid radiations routinely show >50% of gene trees conflicting with the species tree.

Practical signal: If gene concordance factor (gCF) values frequently fall below 50% across backbone nodes, coalescent methods should be considered. Concordance factors below 33% at a node indicate that a different resolution has more support than the species tree at that branch.

Concatenation vs Coalescent Decision

Condition	Recommended Approach
All gCF > 70%	Concatenation is reliable; coalescent and concatenation will agree
Some gCF 30-70%	Run both; compare topologies and report concordance factors
Many gCF < 30%	Coalescent methods required; concatenation is unreliable
Known hybridization/introgression	Neither pure method works; use network approaches

When gCF and species tree disagree at a node, the coalescent analysis should be given priority, as it is statistically consistent under the MSC while concatenation is not.

Method Comparison

Tool	Input	Speed	Key Features
ASTRAL-III	Single-copy gene tree topologies	Fast	Most widely used; handles hundreds of genes
wASTRAL	Gene trees with branch lengths/support	Fast	Uses gene tree uncertainty for improved accuracy
ASTRAL-Pro 2/3	Multi-copy gene family trees	Fast	Handles gene duplication and loss
CASTER	Multiple sequence alignments	Fast	Bypasses gene tree estimation entirely
SVDQuartets	Concatenated alignment (site patterns)	Fast	In PAUP*; works from site patterns without gene trees
BPP	Multi-locus alignments	Very slow	Most accurate; jointly estimates species tree + divergences; species delimitation
StarBEAST3	Multi-locus alignments	Very slow	Integrates with BEAST2 for dating

ASTER package (2025): Consolidates ASTRAL-III, wASTRAL, ASTRAL-Pro 2/3, CASTER, and WASTER into a single C++ package. Much faster and more memory-efficient than the original Java ASTRAL implementations. Install from https://github.com/chaoszhang/ASTER.

ASTRAL Species Tree Pipeline

Infer Gene Trees and Estimate Species Tree

Goal: Estimate a species tree from multi-locus sequence data by first inferring per-locus ML gene trees, then summarizing them under the coalescent model.

Approach: Run IQ-TREE2 independently on each locus alignment with model selection and bootstrap, collect all gene trees, then run ASTRAL to find the species tree that agrees with the largest number of quartet topologies from the gene trees.

# 1. Infer gene trees (one per locus, single-threaded for parallelism across loci)
for f in loci/*.fasta; do
    iqtree2 -s "$f" -m MFP -B 1000 -bnni -T 1 --prefix "${f%.fasta}"
done

# 2. Collect gene trees into a single file
cat loci/*.treefile > gene_trees.tre

# 3. Run ASTRAL species tree estimation (via ASTER)
# Local posterior probability (pp) replaces bootstrap for branch support
astral -i gene_trees.tre -o species_tree.tre

# 4. wASTRAL for datasets with noisy gene trees (uses branch length information)
wastral -i gene_trees.tre -o species_tree_wastral.tre

Compute Concordance Factors

Goal: Quantify how much gene-level and site-level data supports each branch in the species tree.

Approach: Map each gene tree and each informative site onto the species tree, counting concordant vs discordant quartets at every internal branch.

# Gene concordance factors (gCF) + likelihood-based site concordance factors (sCF)
iqtree2 -t species_tree.tre --gcf gene_trees.tre -s concat.fasta --scfl 100

# Output: species_tree.tre.cf.tree  (tree with gCF/sCF annotations)
#         species_tree.tre.cf.stat  (per-branch statistics)

Interpreting Concordance Factors

Metric	Range	Meaning
gCF	0-100%	Percentage of decisive gene trees containing this branch
sCF	~33-100%	Percentage of decisive sites supporting this branch (three possible resolutions)

Interpretation Guide

• gCF = 100%, sCF = 100%: Complete concordance across all loci and sites (rare in practice).
• gCF > 50%, sCF > 50%: Majority support; branch is well-supported under the coalescent.
• gCF ~ 33%, sCF ~ 33%: Completely equivocal; three possible resolutions are equally likely. No topological information at this node.
• gCF ~ 0%: No gene tree contains this branch. Could indicate severe ILS, introgression, or systematic gene tree estimation error.
• gCF much lower than sCF: Gene tree estimation error is inflating discordance. Individual locus alignments lack sufficient signal to resolve gene trees correctly. Consider wASTRAL, which accounts for gene tree uncertainty.
• sCF < 33%: A different resolution is better supported than the current species tree at this node. The species tree topology may be incorrect here.

Distinguishing Quartet Asymmetry

For any internal branch, gene trees partition into three quartet topologies (q1, q2, q3). Under ILS alone, the two minor quartets should be approximately equal (q2 ~ q3). A significant excess of one minor quartet over the other suggests introgression or hybridization rather than ILS.

Gene Tree Estimation Error vs Biological Discordance

Short alignments produce noisy gene trees, and low gCF may reflect estimation error rather than genuine ILS. Strategies to distinguish:

• Compare gCF and sCF: If gCF is much lower than sCF, gene tree estimation error is the primary driver. Sites contain signal that gene tree inference failed to capture.
• Filter gene trees: Remove gene trees inferred from very short alignments (<200 informative sites) or with very low bootstrap support.
• Use wASTRAL: Weights gene tree quartets by branch support, down-weighting poorly resolved splits.
• Use CASTER: Bypasses gene tree estimation entirely, working directly from alignments.

SVDQuartets (Site-Pattern Method)

When individual locus alignments are too short for reliable gene tree estimation, SVDQuartets works directly from site patterns in the concatenated alignment:

# In PAUP* (interactive or via script)
execute concat.nex;
svdquartets evalQuartets=all bootstrap=standard nreps=100;
savetrees file=svdq_species.tre;

SVDQuartets is statistically consistent under the MSC and avoids gene tree estimation entirely. Best suited for RADseq/UCE datasets where per-locus alignments are short.

BPP for Species Delimitation and Species Trees

BPP (Bayesian Phylogenetics and Phylogeography) is the most statistically rigorous coalescent method but computationally expensive:

• A01 analysis: Species delimitation on a fixed guide tree. Tests which populations represent distinct species.
• A11 analysis: Joint species tree estimation and species delimitation. Simultaneously infers the tree and tests species boundaries.
• Appropriate for small numbers of closely related species/populations (typically <20 species, <50 loci due to computational cost).
• Requires an Imap file mapping individuals to populations/species.

ASTRAL Branch Support and Branch Lengths

ASTRAL reports local posterior probabilities (localPP) rather than bootstrap values:

localPP	Interpretation
>= 0.95	Strong support
0.7-0.95	Moderate support
< 0.7	Weak support

ASTRAL branch lengths are in coalescent units (not substitutions per site). A branch length of 1 coalescent unit means divergence equals one effective population size generation. Short branches (<0.5 CU) indicate high expected ILS at that node.

Network Phylogenetics (When Trees Are Insufficient)

When gene tree discordance cannot be explained by ILS alone, reticulate evolution (hybridization, introgression, horizontal gene transfer) may be involved.

Detection: If one minor quartet frequency is significantly greater than the other (q2 >> q3 or q3 >> q2) across multiple branches, this violates the ILS-only expectation of q2 ~ q3.

• D-statistics (ABBA-BABA): Quick initial test for introgression between specific taxa. Available in genomics-population or via custom scripts.
• PhyloNetworks.jl (SNaQ): Scalable pseudolikelihood network inference; estimates the number and placement of hybridization events.
• SplitsTree: Exploratory visualization of conflicting phylogenetic signal via split networks.

When introgression is detected, report the species tree alongside the network; the tree still represents the dominant vertical signal.

Practical Workflow Summary

1. Infer per-locus gene trees (IQ-TREE2 with

   -m MFP -B 1000 -bnni

   )
2. Compute concordance factors to assess discordance levels
3. If gCF > 70% everywhere, concatenation and coalescent methods will agree
4. If gCF < 50% at backbone nodes, run ASTRAL and trust the coalescent result
5. Check quartet asymmetry for introgression signal
6. For short loci (RADseq/UCE), consider SVDQuartets or CASTER instead
7. For species delimitation with few taxa, BPP provides the gold standard

Related Skills

• modern-tree-inference - ML gene tree inference needed as input for ASTRAL
• bayesian-inference - Bayesian tree inference; StarBEAST3 for co-estimation of species tree and gene trees
• phylogenetics/divergence-dating - Dating divergences after species tree is resolved
• tree-manipulation - Rooting and manipulating species trees
• tree-visualization - Visualizing species trees with concordance factor annotations
• alignment/multiple-alignment - Alignment quality directly affects gene tree accuracy