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Complex Models
Table of Contents
This document gives detailed descriptions of complex maximum-likelihood models available in IQ-TREE. It is assumed that you know the basic substitution models already.
Partition models are intended for phylogenomic (e.g., multi-gene) alignments, which allow each partition to have its own substitution models and evolutionary rates. IQ-TREE supports three types of partition models:
- Edge-equal partition model with equal branch lengths: All partitions share the same set of branch lengths.
- Edge-proportional partition model with proportional branch lengths: Like above but each partition has its own partition specific rate, that rescale all its branch lengths. This model accomodates different evolutionary rates between partitions (e.g. between 1st, 2nd, and 3rd codon positions).
- Edge-unlinked partition model: each partition has its own set of branch lengths. This is the most parameter-rich partition model, that accounts for e.g., heterotachy (Lopez et al., 2002).
NOTICE: The edge-equal partition model is typically unrealistic as it does not account for different evolutionary speeds between partitions, whereas edge-unlinked partition model can be overfitting if there are many short partitions. Therefore, the edge-proportional partition model is recommended for a typical analysis.
To apply partition models users must first prepare a partition file in RAxML-style or NEXUS format. The RAxML-style is defined by the RAxML software, which may look like:
DNA, part1 = 1-100
DNA, part2 = 101-384
This means two DNA partitions of an alignment, where one groups aligment sites 1-100 into part1 and 101-384 into part2.
The NEXUS format is more complex but more powerful. For example, the above partition scheme may look like:
#nexus
begin sets;
charset part1 = 1-100;
charset part2 = 101-384;
charpartition mine = HKY+G:part1, GTR+I+G:part2;
end;
The first line contains the keyword #nexus to indicate a NEXUS file. It has a sets block, which contains two character sets (charset command) named part1 and part2. Furthermore, with charpartition command we set the model HKY+G for part1 and GTR+I+G for part2. This is not possible with RAxML-style format (i.e., one cannot specify +G rate model for one partition and +I+G rate model for the other partition).
One can also specify non-consecutive sites of a partition, e.g. under RAxML-style format:
DNA, part1 = 1-100, 250-384
DNA, part2 = 101-249\3, 102-249\3
DNA, part3 = 103-249\3
or under NEXUS format:
#nexus
begin sets;
charset part1 = 1-100 250-384;
charset part2 = 101-249\3 102-249\3;
charset part3 = 103-249\3;
end;
This means, part2 contains sites 101, 102, 104, 105, 107, ..., 246, 248, 249; whereas part3 contains sites 103, 106, ..., 247. This is useful to specify partitions corresponding to 1st, 2nd and 3rd codon positions.
Moreover, the NEXUS file allows each partition to come from separate alignment file (not possible under RAxML-style format) with e.g.:
#nexus
begin sets;
charset part1 = aln1.phy: 1-100\3 201-300;
charset part2 = aln1.phy: 101-200;
charset part3 = aln2.phy: *;
charpartition mine = HKY:part1, GTR+G:part2, WAG+I+G:part3;
end;
Here, part1 and part2 correspond to sub-alignments of aln1.phy file and part3 is the entire alignment file aln2.phy. Note that aln2.phy is a protein alignment in this example. In fact, IQ-TREE fully supports mixed data types between partitions!
If you want to specify codon model for a partition, use the CODON keyword (otherwise, the partition may be detected as DNA):
#nexus
begin sets;
charset part1 = aln1.phy:CODON, 1-300;
charset part2 = aln1.phy: 301-400;
charset part3 = aln2.phy: *;
charpartition mine = GY:part1, GTR+G:part2, WAG+I+G:part3;
end;
Note that this assumes part1 has standard genetic code. If not, append CODON with an ID of the right genetic code.
Having prepared a partition file, one is ready to start a partitioned analysis with -q (edge-equal), -spp (edge-proportional) or -sp (edge-unlinked) option. See this tutorial for more details.
Copyright (c) 2010-2022 IQ-TREE development team.
- First example
- Model selection
- New model selection
- Codon models
- Binary, Morphological, SNPs
- Ultrafast bootstrap
- Nonparametric bootstrap
- Single branch tests
- Partitioned analysis
- Partitioning with mixed data
- Partition scheme selection
- Bootstrapping partition model
- Utilizing multi-core CPUs
- Tree topology tests
- User-defined models
- Consensus construction and bootstrap value assignment
- Computing Robinson-Foulds distance
- Generating random trees
- Estimating amino acid substitution models
- DNA models
- Protein models
- 3Di and TEA models
- Codon models
- Binary, morphological models
- Ascertainment bias correction
- Rate heterogeneity
- Counts files
- First running example
- Substitution models
- Virtual population size
- Sampling method
- Bootstrap branch support
- Interpretation of branch lengths