IQ-TREE

Efficient software for phylogenomic inference

Stable release 1.6.12 (August 15, 2019)

COVID-19 release 2.1.3 (April 21, 2021)

All Downloads Documentation

LATEST NEWS

May 17, 2021: We published a Code of Conduct for the IQ-TREE community
April 21, 2021: Rooting phylogenies and Rootstrap measure is now available in v2.1.3

IQ-TREE key features

IQ-TREE - Efficient Tree Reconstruction

A fast and effective stochastic algorithm to infer phylogenetic trees by maximum likelihood. IQ-TREE compares favorably to RAxML and PhyML in terms of likelihoods with similar computing time (Nguyen et al., 2015).

ModelFinder - Fast and Accurate Model Selection

ModelFinder (Kalyaanamoorthy et al., 2017) enables a free rate variation model and is 10 to 100 times faster than jModelTest and ProtTest. It also finds best-fit partitioning scheme like PartitionFinder.

UFBoot - Ultrafast Bootstrap Approximation

UFBoot provides approximately unbiased branch support values and runs 100X faster than nonparametric bootstrap and 10 to 40 times faster than RAxML rapid bootstrap (Minh et al., 2013).

Big Data Analysis

Supporting huge datasets with thousands of sequences or millions of alignment sites via checkpointing, safe numerical and low memory mode. Multicore CPUs and parallel MPI system are utilized to speedup analysis.


Version 2.0 Highlights

→ IQ-TREE 2 paper in Mol. Biol. Evol.


IQ-TREE supports a wide range of evolutionary models

Common Models

All common substitution models for DNA, protein, codon, binary and morphological data with rate heterogeneity among sites.

Partition Models

Phylogenomic partition models allowing for mixed data types, mixed rate heterogeneity types, linked or unlinked branch lengths.

Mixture Models

Mixture models such as empirical protein mixture models and customizable mixture models.



IQ-TREE is user-friendly and well-documented

W-IQ-TREE Web Service

Easy to use web servers provided by:
Center for Integrative Bioinformatics Vienna, Austria
Los Alamos National Laboratory, USA New!

User Support

Please refer to Frequently Asked Questions. For further feedback and bug reports, please sign up and post a topic to IQ-TREE Google group.

The average response time is two working days.

User Documentation

User guide, tutorial and extensive documentation for how to use IQ-TREE.

Download

The stable IQ-TREE version 1.6.12 (August 15, 2019)

COVID-19 release 2.1.3 (April 21, 2021)


How to cite?

To maintain IQ-TREE, support users and secure fundings, it is important for us that you cite the following papers, whenever the corresponding features were applied for your analysis. Note that the paper of Nguyen et al. (2015) only described the tree search algorithm. Thus, it is not enough to only cite this paper if you, for example, use partition models, where Chernomor et al. (2016) should be cited.

General citation for IQ-TREE 2: New!

B.Q. Minh, H.A. Schmidt, O. Chernomor, D. Schrempf, M.D. Woodhams, A. von Haeseler, R. Lanfear (2020) IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol., 37:1530-1534. https://doi.org/10.1093/molbev/msaa015

When using concordance factors please cite: New!

B.Q. Minh, M.W. Hahn, R. Lanfear (2020) New methods to calculate concordance factors for phylogenomic datasets. Mol. Biol. Evol. https://doi.org/10.1093/molbev/msaa106

When using heterotachy models please cite: New!

S.M. Crotty, B.Q. Minh, N.G. Bean, B.R. Holland, J. Tuke, L.S. Jermiin, A. von Haeseler (2020) GHOST: Recovering historical signal from heterotachously-evolved sequence alignments. Syst. Biol., 69:249-264. https://doi.org/10.1093/sysbio/syz051

When using the tests of symmetry please cite: New!

S. Naser-Khdour, B.Q. Minh, W. Zhang, E.A. Stone, R. Lanfear (2019) The Prevalence and Impact of Model Violations in Phylogenetic Analysis. Genome Biol. Evol., 11:3341-3352. https://doi.org/10.1093/gbe/evz193

When using polymorphism-aware models please cite:

D. Schrempf, B.Q. Minh, A. von Haeseler, C. Kosiol (2019) Polymorphism-aware species trees with advanced mutation models, bootstrap, and rate heterogeneity. Mol. Biol. Evol., 36:1294–1301. https://doi.org/10.1093/molbev/msz043

When performing ultrafast bootstrap (UFBoot) please cite:

D.T. Hoang, O. Chernomor, A. von Haeseler, B.Q. Minh, L.S. Vinh (2018) UFBoot2: Improving the ultrafast bootstrap approximation. Mol. Biol. Evol., 35:518–522. https://doi.org/10.1093/molbev/msx281

When using posterior mean site frequency model (PMSF) please cite:

H.C. Wang, B.Q. Minh, S. Susko, A.J. Roger (2018) Modeling site heterogeneity with posterior mean site frequency profiles accelerates accurate phylogenomic estimation. Syst. Biol., 67:216–235. https://doi.org/10.1093/sysbio/syx068

When using model selection (ModelFinder) please cite:

S. Kalyaanamoorthy, B.Q. Minh, T.K.F. Wong, A. von Haeseler, L.S. Jermiin (2017) ModelFinder: Fast model selection for accurate phylogenetic estimates. Nat. Methods, 14:587-589. https://doi.org/10.1038/nmeth.4285

When using partition models please cite:

O. Chernomor, A. von Haeseler, B.Q. Minh (2016) Terrace aware data structure for phylogenomic inference from supermatrices. Syst. Biol., 65:997-1008. https://doi.org/10.1093/sysbio/syw037

When using IQ-TREE web server please cite:

J. Trifinopoulos, L.-T. Nguyen, A. von Haeseler, B.Q. Minh (2016) W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis.. Nucleic Acids Res., 44:W232-W235. https://doi.org/10.1093/nar/gkw256

For IQ-TREE 1 please cite:

L.-T. Nguyen, H.A. Schmidt, A. von Haeseler, B.Q. Minh (2015) IQ-TREE: A fast and effective stochastic algorithm for estimating maximum likelihood phylogenies.. Mol. Biol. Evol., 32:268-274. https://doi.org/10.1093/molbev/msu300

IQ-TREE would not be possible without generous fundings by: