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Molecular Biology and EvolutionEvolutionary BiologyPeer-reviewed journal article

New methods to calculate concordance factors for phylogenomic datasets

Bùi Quang MinhiD, Matthew W. HahniD, Robert LanfeariD

Abstract

We implement two measures for quantifying genealogical concordance in phylogenomic datasets: the gene concordance factor (gCF) and the novel site concordance factor (sCF). For every branch of a reference tree, gCF is defined as the percentage of "decisive" gene trees containing that branch. This measure is already in wide usage, but here we introduce a package that calculates it while accounting for variable taxon coverage among gene trees. sCF is a new measure defined as the percentage of decisive sites supporting a branch in the reference tree. gCF and sCF complement classical measures of branch support in phylogenetics by providing a full description of underlying disagreement among loci and sites. An easy to use implementation and tutorial is freely available in the IQ-TREE software package (http://www.iqtree.org).

In-depth summary

Claude Opus 5.5 · max effort · 8 Nov 2026 · from the full text of version 2 (14 Feb 2020) · CC BY 4.0

IQ-TREE 2 implements taxon-coverage-aware gene concordance factors and introduces site concordance factors, quantifying gene- and site-level discordance that 100% bootstrap support leaves hidden.

Bootstrap and posterior probabilities gauge statistical support but not the topological disagreement among loci, and the widely used gene concordance factor (gCF) had few implementations, none correcting for incomplete taxon sampling, plus hard-to-interpret low values. Adding taxon-aware gCF to IQ-TREE alongside a site-level analogue, the site concordance factor (sCF), helps distinguish strong gene-tree conflict from weak per-locus signal.

Key results

  1. ShowngCF and sCF are both built into IQ-TREE 2: gCF counts only decisive gene trees (holding at least one taxon from each of the four clades around a branch), and sCF averages parsimony-informative site support over random quartets, each with matching discordance factors.

    New --gcf and --scf options can run together, and -S infers one tree per partition or alignment; gCF+gDF1+gDF2+gDFP and sCF+sDF1+sDF2 each sum to 1; a '.cf.stat' table holds all 16 values per branch, --cf-verbose adds per-gene and per-locus detail, and rooted reference plus gene trees let gCF differ across the root. · Gene Concordance Factor (gCF); Site Concordance Factor (sCF); gCF and sCF for rooted trees; Implementation in IQ-TREE 2

  2. ShownNear-universal 100% bootstrap support on the lizard tree coexisted with low gene- and site-level concordance on some branches, showing that maximal bootstrap values do not guarantee high concordance.

    Lizard tree (43 species, 3,220 ultra-conserved elements, UCEs): all branches but one (Lipinia rouxi + L. pulchella, 62%) had 100% bootstrap, yet the minimum gCF and sCF were 4.5% and 33.2%; the same decoupling recurred in all 200 analyses across the 10 empirical datasets. · Application to empirical datasets; Interpretation of gCF and sCF values; Figure legends

  3. ShownAdding loci tends to raise bootstrap values and the fraction of branches at 100%, whereas gCF and sCF vary mainly at small sample sizes and then stay nearly flat, consistent with bootstraps tracking sampling error and concordance tracking underlying variance.

    Each dataset was reanalysed 20 times (10 to 200 loci, in steps of 10) on the 200-locus concatenated maximum likelihood (ML) tree; bootstraps tended to rise in all 10 datasets, while concordance factors showed estimation error mainly in small subsamples (e.g., 30 or fewer lizard loci); standard and ultrafast bootstraps were very similar for lizards. · Application to empirical datasets; Interpretation of gCF and sCF values; Figure legends

  4. ShownsCF rarely falls below about 33% because each decisive site supports one of three quartet topologies, whereas gCF can approach 0% when gene trees break monophyly of neighbouring clades; for lizards sCF was always at least gCF, which the authors attribute to short UCE loci.

    Empirical gCF ranged from 0% to 100% while sCF seldom fell under 33%; random alignments or saturated long branches should give the three quartet trees near-equal site support (sCF near 33%); gCF can also lose weight to the paraphyly class gDFP, which has no site-level analogue. · Site Concordance Factor (sCF); Interpretation of gCF and sCF values; Figure legends

  5. ClaimedBranches with sCF under 33% mark splits that maximum parsimony (MP) would resolve differently from the reference tree, and are proposed as flags for reference trees misled by incomplete lineage sorting or driven by a few highly influential sites.

    Derived from the quartet definition of sCF; the authors point to parameter space where high incomplete lineage sorting misleads concatenated ML but not MP, and to outlier sites with extreme likelihood differences that MP weights like any other; no sub-33% branch is examined in the text. · Interpretation of gCF and sCF values

Methods, data and reproducibility

gCF is the share of decisive gene trees containing a reference-tree branch (discordant trees split into two nearest-neighbour-interchange alternatives or paraphyly); sCF averages, over m random quartets, the share of decisive parsimony-informative sites supporting it. Both were compared with bootstraps on 10 datasets subsampled from 10 to 200 loci.

  • Lizard ultra-conserved element (UCE) alignments used for a concatenated ML tree, per-UCE gene trees, gCF, sCF and both bootstrap types · lizards (43 species) · n = 3,220 UCEs totalling 1,301,107 bp; 43 species
  • Nine additional empirical phylogenomic datasets from varied clades and data types; together with lizards, five DNA and five amino acid datasets (Table 1) · multiple clades (species not listed in text) · n = 9 datasets
  • Random locus subsamples of every dataset (10 to 200 loci in steps of 10), scored against each dataset's 200-locus concatenated ML tree · n = 20 subsamples per dataset; 200 analyses in total
Methods & tools
IQ-TREE 2 (--gcf, --scf, -S, --cf-verbose), Gene concordance factor (gCF) with gDF1, gDF2, gDFP, Site concordance factor (sCF) with sDF1, sDF2, Concatenated maximum likelihood (ML) tree inference, Single-locus gene tree inference, Standard bootstrap (StdBoot), Ultrafast bootstrap (UFBoot), Nearest neighbour interchange (NNI) alternative topologies, Maximum parsimony site-pattern criterion on quartets, Spectral analysis (conceptual comparison only), Internode certainty (related measure, discussed)
Software & environment
IQ-TREE version 2 with --gcf, --scf, -S (one tree per partition or single-locus alignment) and --cf-verbose; outputs: annotated tree files, a '.cf.stat' table, plus '.cf.stat_tree' and '.cf.stat_loci' files.
Reproducibility gaps
The text omits runtime, hardware, substitution models and the default quartet count m for sCF; sources or accessions for the 10 datasets are not printed (only a Table 1 caption), leaving the Zenodo supplement as the route to the data.
Limitations (6)
  • Concordance factors carry estimation error in small datasets (e.g., 30 or fewer loci in the lizard subsamples) and only stabilise once more loci are included. · stated by the authors
  • Low gCF is not purely biological: gene trees from short, low-information alignments, or around very short branches, can fail to recover monophyly of neighbouring clades, pushing gCF toward 0% through technical as well as biological processes. · stated by the authors
  • sCF drifts toward about 33% when an alignment lacks consistent signal and, through saturation, on very long branches, as the three quartet resolutions then receive similar site support. · stated by the authors
  • The impact of missing data is unresolved: requiring decisive genes and sites should limit it, but because phylogenetic accuracy degrades with missingness, concordance factors could decline systematically as missing data increase. · stated by the authors
  • Assessment is purely empirical, on 10 datasets with unknown true histories; no simulations with known discordance check gCF or sCF for bias, and no confidence intervals or significance tests for concordance values are reported. · noted in this summary
  • sCF relies on equally weighted parsimony over randomly drawn quartets, yet the text neither states the default quartet number m nor quantifies run-to-run variability or sensitivity to among-site rate variation. · noted in this summary

Read this if you infer phylogenomic trees whose bootstraps are saturated at 100% and want gene- and site-level concordance factors in IQ-TREE 2 to quantify locus and site conflict.

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