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3.5.1.5 General multiple site models

Word(model={model name} [,relrate1={1>real>0}, ..., relrate{n-1}={1>real>0}, "equilibrium frequencies"])

or

Word(model1={model name}, model1={model name}, ..., modeln={model name}[, relrate1={1> real>0}, ..., relrate{n-1}={1> real>0}, "equilibrium frequencies"])

substitution model on words. The arguments model and model{i} are for descriptions of models on single sites such as nucleotides or proteins. The alphabet must be a Word alphabet.

If the argument is model, the length of the words in the substitution model is determined by the length of the words in the alphabet, and the same single site model is used (ie the parameters are shared between all positions).

If the arguments are model1, ..., model{n}, the length of the words in the alphabet must be n, and each single site model stands for a single-site substitution model. In that case, all single site models parameters are position dependent.

Each single site model is normalized and the substitution rates between words that differ on more than one letter are null.

Arguments relrate{i} stands for the relative substitution rates of the sites. Default: relrate{i}=1/{n-i+1}, such that the rate of each site is 1/n.

alphabet=Word(letter=DNA,length=4)
model=Word(model=T92())

builds a model on 4 bases words, such all sites follow the same T92 model. The parameters names are Word.1234_T92.kappa, Word.relrate1, Word.relrate2, Word.relrate3.

alphabet=Word(letter=DNA,length=4)
model=Word(model1=T92(), model2=T92(), model3=JC69(), \
           model4=HKY85())

builds a model on 4 bases words, such first and second sites follow independent T92 models, third site follows a JC69 model, and fourth site follows a HKY85 model. Then the parameters names are Word.1_T92.kappa, Word.2_T92.kappa, Word.4_HKY85.kappa, Word.4_HKY85.theta, Word.4_HKY85.theta1, Word.4_HKY85.theta2, Word.relrate1, Word.relrate2, Word.relrate3.

See the Bio++ description.

Triplet(model={model description} [, relrate1={real>0}, relrate2={real>0}])

or

Triplet(model1={model description}, model2={model description}, model3={model description}[, relrate1={real>0}, relrate2={real>0}])

substitution model on 3 letters words. The arguments model and model{i} are for descriptions of models on single sites such as nucleotides or proteins. The alphabet must be a 3-letters word alphabet or a codon alphabet.

If the argument is model, the same single site model is used on all positions (ie the parameters are shared between all positions).

If the arguments are model1, model2, model3, each single site model stands for a single-site substitution model. In that case, all single site models parameters are position dependent.

Each single site model is normalized and the substitution rates between triplets that differ on more than one letter are null.

Arguments relrate{i} stands for the relative substitution rates of the sites. Default: relrate{i}=1/{4-i}, such that the rate of each site is 1/3.

alphabet=Codon(letter=DNA, type=Standard)
model=Triplet(model=T92)

builds a model on codons, such all sites follow the same T92 model. The parameters names are Triplet.123_T92.kappa, Triplet.relrate1, Triplet.relrate2.

alphabet=Word(letter=DNA, length=3)
model=Triplet(model1=T92, model2=T92, model3=JC69)

builds a model on 3 bases words, such first and second sites follow independent T92 models, and third site follows a JC69 model. Then the parameters names are Triplet.1_T92.kappa, Triplet.2_T92.kappa, Triplet.relrate1, Triplet.relrate2.

See the Bio++ description.

YpR_Sym(model={model description}, [rCgT={real>=0}, rTgC={real>=0}, rCaT={real>=0}, rTaC={real>=0}])

substitution model on quotiented triplets to handle strand symetric neighbour-dependency inside dinucleotides YpR (see Bérard and Guéguen 2012). See the Bio++ description.

YpR_Gen(model={model description}, [rCgT={real>=0}, rcGA={real>=0}, rTgC={real>=0}, rtGA={real>=0}, rCaT={real>=0}, rcAG={real>=0}, rTaC={real>=0}, rtAG={real>=0}])

substitution model on quotiented triplets to handle general symetric neighbour-dependency inside dinucleotides YpR (see Bérard and Guéguen 2012). See the Bio++ description.


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