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.. jupyter-execute::
:hide-code:
import set_working_directory
Applying a time-reversible codon model
--------------------------------------
We display the full set of codon models available.
.. jupyter-execute::
from cogent3 import available_models
available_models("codon")
Using the conditional nucleotide form codon model
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The CNFGTR model (`Yap et al <https://www.ncbi.nlm.nih.gov/pubmed/19815689>`__) is the most robust of the time-reversible codon models available (`Kaehler et al <https://www.ncbi.nlm.nih.gov/pubmed/28175284>`__). By default, this model does not optimise the codon frequencies but uses the average estimated from the alignment. We configure the model to optimise the root motif probabilities.
.. jupyter-execute::
from cogent3 import get_app
loader = get_app("load_aligned", format="fasta", moltype="dna")
aln = loader("data/primate_brca1.fasta")
model = get_app("model",
"CNFGTR",
tree="data/primate_brca1.tree",
optimise_motif_probs=True,
)
result = model(aln)
result
.. jupyter-execute::
result.lf
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