IQ-TREE

Efficient phylogenomic software by maximum likelihood

Latest version 1.4.3 released on July 15, 2016

First polymorphism-aware model released on July 22, 2016


IQ-TREE key features

Efficient Search Algorithm

A novel fast and effective stochastic algorithm to estimate maximum likelihood trees. IQ-TREE compares favorably to RAxML and PhyML in terms of likelihood while requiring similar amount of computing time (Nguyen et al., 2015).

Ultrafast Bootstrap

An ultrafast bootstrap approximation (UFBoot) to assess branch supports. UFBoot is 10 to 40 times faster than RAxML rapid bootstrap and obtains less biased support values (Minh et al., 2013).

Ultrafast Model Selection

An ultrafast and automatic model selection (ModelFinder) which is 10 to 100 times faster than jModelTest and ProtTest. ModelFinder also performs best-fit partitioning scheme selection like PartitionFinder.



IQ-TREE supports a wide range of substitution 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.



Online Web Service

IQ-TREE web server for online computations. It is very easy to use with as few as just 3 clicks!

http://iqtree.cibiv.univie.ac.at

User Documentation

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

User Support

Please first read Frequently Asked Questions. If you have further questions, feedback, feature requests and bug reports, please sign up and post a topic to IQ-TREE Google group

The average response time is one working day.

How to cite IQ-TREE?

To maintain IQ-TREE and secure fundings, it is very important for us that you cite the following papers, whenever the corresponding features were applied for your analysis.

Example 1: "...We obtained branch supports with the ultrafast bootstrap (Minh et al. 2013) implemented in the IQ-TREE software (Nguyen et al. 2015)..."

Example 2: "...We inferred the maximum-likelihood tree using the edge-linked partition model in IQ-TREE (Chernomor et al. 2016; Nguyen et al. 2015)..."

If you performed tree reconstruction or other features please cite:

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

If you used partition models e.g., for phylogenomic analysis please cite:

O. Chernomor, A. von Haeseler, and B.Q. Minh (2016) Terrace aware data structure for phylogenomic inference from supermatrices. Syst. Biol., in press. DOI: 10.1093/sysbio/syw037

If you performed the ultrafast bootstrap (UFBoot) please cite:

B.Q. Minh, M.A.T. Nguyen, and A. von Haeseler (2013) Ultrafast approximation for phylogenetic bootstrap. Mol. Biol. Evol., 30:1188-1195. DOI: 10.1093/molbev/mst024

If you used the IQ-TREE web server please cite:

J. Trifinopoulos, L.-T. Nguyen, A. von Haeseler, and B.Q. Minh (2016) W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res., 44 (W1): W232-W235. DOI: 10.1093/nar/gkw256

If you used the polymorphism-aware models please cite:

D. Schrempf, B.Q. Minh, N. De Maio, A. von Haeseler, and C. Kosiol (2016) Reversible polymorphism-aware phylogenetic models and their application to tree inference. J. Theor. Biol., in press. DOI: 10.1101/048496

Credits and Acknowledgements

Some parts of the code were taken from the following packages/libraries: Phylogenetic likelihood library, TREE-PUZZLE, BIONJ, Nexus Class Libary, Eigen library, SPRNG library, Zlib library, gzstream library, vectorclass library, GNU scientific library.

IQ-TREE was partially funded by the Austrian Science Fund - FWF (grants I 760-B17 from 2012-2015 and I 2508-B29 from 2016-2019) and the University of Vienna (Initiativkolleg I059-N from 2011-2014).