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doc/Command-Reference.md

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---
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layout: userdoc
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title: "Command Reference"
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author: Hector Banos, Diep Thi Hoang, Dominik Schrempf, Heiko Schmidt, Jana Trifinopoulos, Minh Bui, Thomas Wong, Nhan Ly-Trong
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date: 2025-03-28
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author: Hector Banos, Diep Thi Hoang, Dominik Schrempf, Heiko Schmidt, Jana Trifinopoulos, Minh Bui, Thomas Wong, Nhan Ly-Trong, Hiroaki Sato
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date: 2025-05-30
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docid: 19
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icon: book
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doctype: manual
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| Protein | Mixture models: C10, ..., C60 (CAT model) ([Lartillot and Philippe, 2004]), EX2, EX3, EHO, UL2, UL3, EX_EHO, LG4M, LG4X, CF4. See [Protein models](Substitution-Models#protein-models) for more details. |
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| Codon | MG, MGK, MG1KTS, MG1KTV, MG2K, GY, GY1KTS, GY1KTV, GY2K, ECMK07/KOSI07, ECMrest, ECMS05/SCHN05 and combined empirical-mechanistic models. See [Codon models](Substitution-Models#codon-models) for more details. |
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| Binary | JC2, GTR2. See [Binary and morphological models](Substitution-Models#binary-and-morphological-models) for more details. |
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| Morphology | MK, ORDERED. See [Binary and morphological models](Substitution-Models#binary-and-morphological-models) for more details. |
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| Morphology | MK, (GTRX), ORDERED. WARNING: GTRX (which can also be invoked as GTR) can only be applied to data with non-arbitrary state labels (e.g., recoded amino acids [for practical application, see [Najle et al., 2023]; [xgrau/recoded-mixture-models]] and certain types of genomic information) and should not be used for general morphological characters (transformational morphological characters; for the term, see [Sereno, 2007]). See [Binary and morphological models](Substitution-Models#binary-and-morphological-models) for more details. |
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The following `FreqType`s are supported:
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[Strimmer and von Haeseler, 1997]: http://www.pnas.org/content/94/13/6815.long
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[Yang, 1994]: https://doi.org/10.1007/BF00160154
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[Yang, 1995]: http://www.genetics.org/content/139/2/993.abstract
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[Najle et al., 2023]: https://doi.org/10.1016/j.cell.2023.08.027
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[xgrau/recoded-mixture-models]: https://github.com/xgrau/recoded-mixture-models
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[Sereno, 2007]: https://doi.org/10.1111/j.1096-0031.2007.00161.x
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doc/Substitution-Models.md

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layout: userdoc
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title: "Substitution Models"
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author: Hector Banos, Cuong Cao Dang, Heiko Schmidt, Jana Trifinopoulos, Minh Bui, Nhan Ly-Trong, Hiroaki Sato
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date: 2024-05-27
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date: 2024-05-30
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docid: 10
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icon: book
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The binary alignments should contain state `0` and `1`, whereas for morphological data, the valid states are `0` to `9` and `A` to `V`.
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| Model | Explanation |
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|---------|------------------------------------------------------------------------|
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| JC2 | Jukes-Cantor type model for binary data.|
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| GTR2 | General time reversible model for binary data.|
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| MK | Jukes-Cantor type model for morphological data.|
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| ORDERED | Allowing exchange of neighboring states only.|
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| Model | Explanation |
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|------------|------------------------------------------------------------------------|
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| JC2 | Jukes-Cantor type model for binary data.|
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| GTR2 | General time reversible model for binary data.|
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| MK | Jukes-Cantor type model for morphological data with equal rates.|
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| GTRX (GTR) | General time reversible model for morphological (or rather, multistate; **see the warning below**) data with unequal rates.|
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| ORDERED | Allowing exchange of neighboring states only.|
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Except for `GTR2` that has unequal state frequencies, all other models have equal state frequencies. Users can change how state frequencies are modeled in morphological models by appending `+FQ`, `+F`, `+F{...}`, or `+FO`.
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Except for `GTR2` that has unequal state frequencies, all other models have equal state frequencies.
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> **WARNING**: Models with unequal rates and/or frequencies (e.g., `GTR2+FO`, `MK+FO`, `GTRX+FQ`, `GTRX+FO`) should not be applied to general morphological characters (transformational morphological characters; for the term, see [Sereno, 2007]) as their state labels are fundamentally arbitrary. These models are for data with non-arbitrary state labels (e.g., recoded amino acids [for practical application, see [Najle et al., 2023]; [xgrau/recoded-mixture-models]] and certain types of genomic information). For morphological data, it is the common practice to apply the `MK+FQ+ASC` model (or for ordered [additive] characters `ORDERED+FQ+ASC`) (for `+ASC`, see below) with or without rate heterogeneity across characters parameters.
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> **WARNING**: If you use `GTRX` for your multistate data, because of its sometimes very great number of free parameters, please make sure your data are sufficiently large and always test for model fit.
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> **TIP**: Recent studies have indicated that applying a single morphological model to morphological data with heterogeneity of state space among characters may not be appropriate ([Khakurel et al., 2024]; [Mulvey et al., 2025]; [Huang, 2025 preprint]), and users may need to partition data by the number of states in each character before analyzing them in IQ-TREE. For information on how to analyze partitioned morphological data in IQ-TREE and some caveats about it, please refer to [davidcerny/GEOS26100-Fall2022], https://davidcerny.github.io/post/teaching_revbayes/, [Černý & Simonoff (2023)], and [ej91016/MorphoParse].
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{: .tip}
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> **TIP**: For binary morphological characters where `0`s represent ancestral conditions and `1`s represent derived conditions, mainly neomorphic (`absent`/`present`) morphological characters (for the term, see [Sereno, 2007]), allowing asymmetrical frequencies in models would make sense (see e.g. [Pyron, 2017]; [Sun et al., 2018]; https://ms609.github.io/hyoliths/bayesian.html). This can be achieved in IQ-TREE, for example, by using the `GTR2` model.
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{: .tip}
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>**TIP**: If morphological alignments do not contain constant sites (typically the case), then [an ascertainment bias correction model (`+ASC`)](#ascertainment-bias-correction) should be applied to correct the branch lengths for the absence of constant sites.
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{: .tip}
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[Yang, 1995]: http://www.genetics.org/content/139/2/993.abstract
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[Yang et al., 1998]: http://mbe.oxfordjournals.org/content/15/12/1600.abstract
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[Zharkikh, 1994]: https://doi.org/10.1007/BF00160155
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[Sereno, 2007]: https://doi.org/10.1111/j.1096-0031.2007.00161.x
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[Pyron, 2017]: https://doi.org/10.1093/sysbio/syw068
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[Sun et al., 2018]: https://doi.org/10.1098/rspb.2018.1780
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[xgrau/recoded-mixture-models]: https://github.com/xgrau/recoded-mixture-models
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[Najle et al., 2023]: https://doi.org/10.1016/j.cell.2023.08.027
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[Khakurel et al., 2024]: https://doi.org/10.1093/sysbio/syae033
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[Mulvey et al., 2025]: https://doi.org/10.1093/sysbio/syae055
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[Huang, 2025 preprint]: https://doi.org/10.1101/2025.04.22.650124
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[ej91016/MorphoParse]: https://github.com/ej91016/MorphoParse
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[davidcerny/GEOS26100-Fall2022]: https://github.com/davidcerny/GEOS26100-Fall2022
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[Černý & Simonoff (2023)]: https://doi.org/10.1038/s41598-023-35784-3
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workshop/index.md

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| Date | Course Name and Materials | Location | Instructor |
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|------|---------------|----------------------------|-------------|
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| May 22 - Jun 1, 2025 | [Workshop on Molecular Evolution](https://molevolworkshop.github.io), [IQ-TREE 3 tutorial](molevol_tutorial2025) | Marine Biological Laboratory, Woods Hole, USA | Course Assistants |
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| May 22 - Jun 1, 2025 | [Workshop on Molecular Evolution](https://molevolworkshop.github.io), [IQ-TREE 3 tutorial](molevol_tutorial2025) | Marine Biological Laboratory, Woods Hole, USA | Hanon Solomon McShea |
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### Past Workshops
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| Aug 4-9, 2024 | [28th Bioinformatics Workshop on Virus Evolution and Molecular Epidemiology (VEME)](https://veme.climade.health/) | Brasilia, Brazil | Heiko Schmidt |
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| Jul 15-19, 2024 | [Croucher Summer Course on Virus Evolution and Epidemiology](https://projects.croucher.org.hk/summer-courses/virus-evolution-and-epidemiology) | Hongkong | Heiko Schmidt |
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| May 24 - Jun 3, 2024 | [Workshop on Molecular Evolution](https://molevolworkshop.github.io), IQ-TREE 2 tutorial | Marine Biological Laboratory, Woods Hole, USA | Blake Fauskee |
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| May 26 - Jun 5, 2023 | [Workshop on Molecular Evolution](https://molevolworkshop.github.io), [IQ-TREE 2 tutorial](molevol2023) | Marine Biological Laboratory, Woods Hole, USA | Bui Quang Minh |
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| Aug 20-25, 2023 | [27th Bioinformatics Workshop on Virus Evolution and Molecular Epidemiology (VEME)](https://veme.climade.health/27th-international-bioinformatics-workshop-on-virus-evolution-and-molecular-epidemiology-veme/) | Stellenbosch, South Africa | Heiko Schmidt |
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| July 27-29, 2022 | [IQ-TREE workshop tutorial](sydney2022) | [13th Sydney Phylogenetics Workshop](https://meep.sydney.edu.au/workshops/), Online | Bui Quang Minh |

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