The IQ-Tree phylogenetic reconstruction software is available for download to run locally on your computer from http://www.iqtree.org/. The developers also provide a web service (http://iqtree.cibiv.univie.ac.at/), and have kindly allowed us to generate our web service here. Any use of IQ-Tree should cite:
Trifinopoulos J, Nguyen LT, von Haeseler A, Minh BQ. "W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis." Nucleic Acids Res. 2016 Jul 8;44(W1):W232-5. doi: 10.1093/nar/gkw256; Epub 2016 Apr 15.
One of the useful features of IQ-Tree in HIV research is the ability to output a file of the site-specific rates of evolution calculated by the program. One value for the rate of evolution is calculated for each column in the alignment. Thus if you wish to compare the pattern of evolution in subtype B vs subtype C, you would build one tree from each data set (a subtype B tree and a subtype C tree, both aligned the same).
The maximum number of sequences allowed is 300. For larger data sets, the program is available to download on your own computer at http://www.iqtree.org/.
On this interface, the default evolutionary model for nucleotide data is GTR (General time-reversible model) and you can select a gamma distribution of site-specific rates (designed for sequences with significant between-site rate heterogeneity, such as HIV), or select a FreeRate model (Yang, 1995; Soubrier et al., 2012) that generalizes the +G model by relaxing the assumption of Gamma-distributed rates. The number of categories can be specified with e.g. +R6 (default 4 categories if not specified). The FreeRate model typically fits data better than the +G model and is recommended for analysis of large data sets. The default evolutionary model for protein data is HIVb (designed for between-patient HIV-1 data).
These models may not be suitable for your data! We recommend first testing your data with FindModel for DNA, or with ProtTest for protein. IQ-TREE can also make its own choice of a model by selecting "Find model" in the Model option.
For additional information about evolutionary models, see references below.
Bootstrapping puts a high load on web servers. In addition to the maximum of 300 sequences per alignment, we recommend the following maximum file sizes:
|# Bootstraps||Max. filesize|
See TreeRate for details about Generalized midpoint optimization or Simple midpoint rooting.
Your results will be returned by e-mail if any of the following are true:
For the full IQtree manual, see http://www.iqtree.org/ http://www.iqtree.org/doc/iqtree-doc.pdf
|HKY85||Hasegawa M, Kishino H, Yano T (1985). "Dating of human-ape splitting by a molecular clock of mitochondrial DNA". Journal of Molecular Evolution 22: 160–174.|
|JC69||Jukes TH and Cantor CR (1969). Evolution of Protein Molecules. New York: Academic Press. pp. 21–132.|
|K80||Kimura M (1980). "A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences". Journal of Molecular Evolution 16: 111–120|
|F81||Felsenstein J (1981). "Evolutionary trees from DNA sequences: a maximum likelihood approach". Journal of Molecular Evolution 17: 368–376|
|TN93||Tamura K, Nei M (1993). "Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees". Molecular Biology and Evolution 10 (3): 512–526.|
|GTR||Tavaré S (1986). "Some Probabilistic and Statistical Problems in the Analysis of DNA Sequences". Lectures on Mathematics in the Life Sciences (American Mathematical Society) 17: 57–86.|
|Blosum62||"Amino acid substitution matrices from protein blocks." Henikoff S. & Henikoff J. PNAS 89, 10915–10919 (1992).|
|CpREV||"Plastid genome phylogeny and a model of amino acid substitution for proteins encoded by chloroplast DNA." Adachi J.P.W., Martin W. & Hasegawa M. Journal of Molecular Evolution 50, 348–358 (2000).|
|Dayhoff||"A model of evolutionary change in proteins." Dayhoff M., Schwartz R. & Orcutt B. In Dayhoff, M. (ed.) Atlas of Protein Sequence and Structure, vol. 5, 345–352 (National Biomedical Research Foundation, Washington, D. C., 1978).|
|DCMut||"Different versions of the Dayhoff rate matrix." Kosiol C. & Goldman N. Molecular Biology and Evolution 22, 193–19 (2004).|
|Nickle, D.C., Heath, L., Jensen, M.A., Gilbert, P.B., Mullins, J.I., and Kosakovsky Pond, S.L. 2007. HIV-specific probabilistic models of protein evolution. PLoS ONE 2: e503|
|JTT||"The rapid generation of mutation data matrices from protein sequences." Jones D., Taylor W. & Thornton J. Computer Applications in the Biosciences (CABIOS) 8, 275–282 (1992).|
|LG||"An improved general amino-acid replacement matrix." Le S. & Gascuel O. Mol. Biol. Evol. 25(7):1307-20 (2008|
|MtArt||Abascal, F., Posada, D., and Zardoya, R. 2007. MtArt: a new model of amino acid replacement for Arthropoda. Mol Biol Evol 24: 1-5|
|MtMam||"Conflict among individual mitochondrial proteins in resolving the phylogeny of eutherian orders." Cao Y. et al. Journal of Molecular Evolution 47, 307–322 (1998)|
|RtREV||"rtREV: an amino acid substitution matrix for inference of retrovirus and reverse transcriptase phylogeny." Dimmic M., Rest J., Mindell D. & Goldstein D. Journal of Molecular Evolution 55, 65–73 (2002).|
|VT||"Modeling amino acid replacement." Muller T. & Vingron M. Journal of Computational Biology 7, 761–776 (2000).|
|WAG||"A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach." Whelan S. & Goldman N. Mol. Biol. Evol. 18, 691–699 (2001)|