IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

Bui Quang Minh; Heiko A Schmidt; Olga Chernomor; Dominik Schrempf; Michael D Woodhams; Arndt von Haeseler; Robert Lanfear

doi:10.1093/molbev/msaa015

IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

Mol Biol Evol. 2020 May 1;37(5):1530-1534. doi: 10.1093/molbev/msaa015.

Authors

Bui Quang Minh^{1

2}, Heiko A Schmidt³, Olga Chernomor³, Dominik Schrempf^{3

4}, Michael D Woodhams⁵, Arndt von Haeseler^{3

6}, Robert Lanfear²

Affiliations

¹ Research School of Computer Science, Australian National University, Canberra, ACT, Australia.
² Department of Ecology and Evolution, Research School of Biology, Australian National University, Canberra, ACT, Australia.
³ Center for Integrative Bioinformatics Vienna, Max Perutz Labs, University of Vienna and Medical University of Vienna, Vienna, Austria.
⁴ Department of Biological Physics, Eötvös Lórand University, Budapest, Hungary.
⁵ Discipline of Mathematics, University of Tasmania, Hobart, TAS, Australia.
⁶ Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria.

Abstract

IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

Keywords: maximum likelihood; models of sequence evolution; phylogenetics; phylogenomics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Evolution, Molecular*
Genomics*
Models, Genetic*
Phylogeny*
Software*