Using a nucleotide model
------------------------

We load the unaligned sequences we will use in our examples.

.. doctest::

    >>> from cogent3.app import io
    >>> reader = io.load_unaligned(format="fasta")
    >>> seqs = reader("data/SCA1-cds.fasta")

Nucleotide alignment with default settings
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The default setting for "nucleotide" is a HKY85 model.

.. doctest::

    >>> from cogent3.app.align import progressive_align
    >>> nt_aligner = progressive_align("nucleotide")
    >>> aligned = nt_aligner(seqs)
    >>> aligned
    6 x 2475 dna alignment...

Specify a different distance measure for estimating the guide tree
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

For the nucleotide case, you can use TN93 or paralinear.

.. doctest::
    
    >>> nt_aligner = progressive_align("nucleotide", distance="TN93")
    >>> aligned = nt_aligner(seqs)
    >>> aligned
    6 x 2475 dna alignment...

Providing a guide tree
^^^^^^^^^^^^^^^^^^^^^^

.. doctest::

    >>> 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)"
    >>> nt_aligner = progressive_align("nucleotide", guide_tree=tree)
    >>> aligned = nt_aligner(seqs)
    >>> aligned
    6 x 2475 dna alignment...

.. note:: You can also specify ``unique_guides=True``, which means a guide tree will be estimated for every alignment.

Specifying the substitution model
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

You can use any nucleotide substitution model. For a list of all available, see ``cogent3.available_models()``.

.. doctest::

    >>> 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)"
    >>> nt_aligner = progressive_align("F81", guide_tree=tree)
    >>> aligned = nt_aligner(seqs)
    >>> aligned
    6 x 2475 dna alignment...