It is a very efficient phylogenetic software and web interface for reconstructing maximum-likelihood trees and assessing branch supports with the ultrafast bootstrap approximation. It is based on the IQPNNI algorithm with 10-fold speedup together with substantially additional features. It is actively maintained by the core development team and a number of collabrators.
IQ-TREE supports multiple sequence types (DNA, protein, codon, binary and morphology) in common alignment formats and a wide range of evolutionary models including mixture and partition models. IQ-TREE performs fast model selection, partition scheme finding, efficient tree reconstruction, ultrafast bootstrapping, branch tests, and tree topology tests. All computations are conducted on a dedicated computer cluster and the users receive the results via URL or email.
A web interface for IQ TREE is W-IQ-TREE, available at http://iqtree.cibiv.univie.ac.at. It is free and open to all users and there is no login requirement.
The amount of phylogenomic/transcriptomic data have been rapidly accumulated. This facilitates resolving many “deep phylogenetic” questions in the tree of life. At the same time it poses major computational challenges to analyze such big data, where most phylogenetic software cannot handle. Moreover, there is a need to develop more complex probabilistic models to adequately capture realistic aspects of genomic sequence evolution.
This trend motivated us to develop the IQ-TREE software with a strong emphasis on phylogenomic inference. The goals are:
Accuracy: Proposing novel computational methods that perform better than existing approaches.
Speed: Allowing fast analysis on big data sets and utilizing high performance computing platforms.
Flexibility: Facilitating the inclusion of new (phylogenomic) models and sequence data types.
Versatility: Implementing a broad range of commonly-used maximum likelihood analyses.
Efficient search algorithm: Fast and effective stochastic algorithm to reconstruct phylogenetic trees by maximum likelihood.
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 Ultrafast model selection: An ultrafast and automatic model selection (ModelFinder) which is 10 to 100 times faster than jModelTest and ProtTest. ModelFinder also finds best-fit partitioning scheme like PartitionFinder.
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.
Phylogenetic testing: Several fast branch tests like SH-aLRT and aBayes and tree topology tests like the approximately unbiased (AU) test
There are two types of models in IQ-TREE for a variety of phylogenetic models and theses are;
Common models: All common substitution models for DNA, protein, codon, binary and morphological data with rate heterogeneity among sites and ascertainment bias correction for e.g. SNP data.
Partition models: Allowing individual models for different genomic loci (e.
Mixture models: fully customizable mixture models and empirical protein mixture models and.