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.. jupyter-execute::
:hide-code:
import set_working_directory
Using a codon model
===================
We load the unaligned sequences we will use in our examples.
.. jupyter-execute::
:raises:
from cogent3 import get_app
loader = get_app("load_unaligned", format="fasta")
seqs = loader("data/SCA1-cds.fasta")
.. note:: We use an app loader, but since this is just a single file we could have used the ``cogent3.load_unaligned_seqs()`` function.
Codon alignment with default settings
-------------------------------------
The default settings will result in estimation of a guide tree (using percent identity between the sequences). The default "codon" model is MG94HKY.
.. jupyter-execute::
:raises:
from cogent3 import get_app
codon_aligner = get_app("progressive_align", "codon")
aligned = codon_aligner(seqs)
aligned
.. note:: If you specify ``unique_guides=True``, a guide tree will be estimated for every alignment.
Specify a different distance measure for estimating the guide tree
------------------------------------------------------------------
The distance measures available are the same as for the nucleotide case (percent, TN93 or paralinear).
.. note:: An estimated guide tree has its branch lengths scaled so they are consistent with usage in a codon model.
.. jupyter-execute::
:raises:
nt_aligner = get_app("progressive_align", "codon", distance="paralinear")
aligned = nt_aligner(seqs)
aligned
Providing a guide tree
----------------------
.. jupyter-execute::
:raises:
tree = "((Chimp:0.001,Human:0.001):0.0076,Macaque:0.01,((Rat:0.01,Mouse:0.01):0.02,Mouse_Lemur:0.02):0.01)"
codon_aligner = get_app("progressive_align", "codon", guide_tree=tree)
aligned = codon_aligner(seqs)
aligned
.. warning:: The guide tree must have branch lengths, otherwise a ``ValueError`` is raised.
Specifying the gap parameters
-----------------------------
.. jupyter-execute::
:raises:
codon_aligner = get_app("progressive_align",
"codon", guide_tree=tree, indel_rate=0.001, indel_length=0.01
)
aligned = codon_aligner(seqs)
aligned
Specifying the substitution model and parameters
------------------------------------------------
Any ``cogent3`` codon substitution model can be used. (See ``cogent3.available_models()``.)
.. jupyter-execute::
:raises:
codon_aligner = get_app("progressive_align",
"CNFHKY", guide_tree=tree, param_vals=dict(omega=0.1, kappa=3)
)
aligned = codon_aligner(seqs)
aligned
.. note:: If you provide parameter values, those must be consistent with the model definition.
Alignment settings and file provenance are recorded in the ``info`` attribute
-----------------------------------------------------------------------------
The parameters used to construct the alignment, including the guide tree and substitution model, are record in the alignment ``info`` attribute.
.. jupyter-execute::
:raises:
aligned.info
|
