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Substitution Models

SIMMAP 1.5 implements a wide variety of nucleotide and morphological/standard models.

The following nucleotide substitution models and their sub-variants are available:

  1. General-time-reversible model (GTR)
  2. Symmetric model (SYM)
  3. Hasegawa-Kishino-Yano model (HKY85)
  4. Kimura 2-parameter (K2P)
  5. Felsenstein 1981 (F81)
  6. Jukes-Cantor (JC69)

Among-site rate variation can be accommodated using:

  1. Discrete gamma (Yang 1994)
  2. Site-specific rates
  3. Invariant sites

Morphological or standard characters are modeled using the Mk class of models. Uncertainty in the overall rate and bias (state frequencies) is accommodated by placing priors on these values. For more details on morphology priors see here.

Nucleotide Models:

Nucleotide models can be configured and parameterized in two ways. First, by using a model definition, with the parameters and values, from the input control file. Alternatively, by configuring the model with fixed values in the Models window (Figure 1; to open the window select Analysis->Configure Model... from the main menu).

                        Figure 1.


If you wish to use values from the input file select Use model definitions in control file. (For more details on the control file see here.) Each model definition in the control file must have a matching tree. By default each definition is "linked" to a tree as defined by the order (first-to-last) in the file.

To configure the model manually you can select the desired parameters and values in the window (Figure 1). The parameters required depend on the number of substitution types selected.

Morphology Models:

Morphology/standard models must be configured manually for each character (Figure 2; to open the window select Analysis->Configure Model... from the main menu). For more details on morphology priors see here.

                        Figure 2.


To configure the model for a character select the character in the table on the left (Figure 2) and then select teh desired options for Bias Parameter and Rate Parameter parameters. The following options are available.

Bias parameters -

  1. Beta distribution defined by the parameter alpha and number of categories (k)
  2. Fixed 2 state prior defined by entering a value for π(0) (π(1) is defined as 1-π(0)).
  3. Equal prior defined as 1/k
  4. Empirical prior defined by the frequency of states in the data

Rate parameters -

  1. Gamma distribution prior defined by the parameters α, β and k categories.
  2. Fixed rate defined by entering a value for T(rate)
  3. Branch length prior in which the branch lengths reflect the rate

In addition, the tree can be rescaled to a length of 1.0 before the rate is applied by selecting Rescale tree length.

State ordering -

Changes from one state to another can be either ordered or unordered by selecting the option from the State Ordering box. Ordered characters results in linear ordering. For example, 0<=>1<=>2.