IQ-TREE feature highlights

IQ-TREE - Efficient Tree Reconstruction

A fast search algorithm (Nguyen et al., 2015) to infer phylogenetic trees by maximum likelihood. IQ-TREE compares favorably to RAxML and PhyML.

ModelFinder - Fast and Accurate Model Selection

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

UFBoot - Ultrafast Bootstrap Approximation

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

AliSim - Alignment Simulator New!

AliSim (Ly-Trong et al., 2022) allows to quickly simulate multiple sequence alignments under more realistic models than Seq-Gen and INDELible.


Version 2.0 Highlights



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

User Support

Please refer to Frequently Asked Questions. For further questions and feedback, please create a new topic on IQ-TREE GitHub discussions New!

User Documentation

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

How to cite?

To maintain IQ-TREE, support users and obtain fundings, it is important that you not only cite the IQ-TREE version 2 paper (Minh et al., 2020) but also additional papers typically mentioned in the documentation of the features/options you are using in your analysis. These papers are also listed here.

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