.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/gallery/sequence/homology/gpcr_evolution.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_gallery_sequence_homology_gpcr_evolution.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_gallery_sequence_homology_gpcr_evolution.py:


Phylogenetic tree of a protein family
=====================================

This example plots an unrooted phylogenetic tree depicting the evolution
of different G-protein coupled receptors (GPCRs).

The UniProt IDs and gene names of the GPCRs are obtained
via the corresponding keyword.
The corresponding sequences are downloaded and aligned.
Based on the pairwise sequence identity in the multiple sequence
alignment a tree is created via the *neighbor-joining* method.
Finally the unrooted tree is plotted using the graph drawing
capabilities of the *NetworkX* package.

.. GENERATED FROM PYTHON SOURCE LINES 16-94



.. image-sg:: /examples/gallery/sequence/homology/images/sphx_glr_gpcr_evolution_001.png
   :alt: gpcr evolution
   :srcset: /examples/gallery/sequence/homology/images/sphx_glr_gpcr_evolution_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    # Code source: Patrick Kunzmann
    # License: BSD 3 clause

    import re
    import matplotlib.pyplot as plt
    import networkx as nx
    import biotite.application.clustalo as clustalo
    import biotite.database.uniprot as uniprot
    import biotite.sequence as seq
    import biotite.sequence.align as align
    import biotite.sequence.io.fasta as fasta
    import biotite.sequence.phylo as phylo

    # The bovine GPCRs are investigated
    SPECIES = "Bovine"


    query = (
        uniprot.SimpleQuery("reviewed", "true")
        &
        # Bovine proteins
        uniprot.SimpleQuery("organism_name", "Bos taurus")
        &
        # Keyword ID for GPCRs
        uniprot.SimpleQuery("keyword", "KW-0297")
    )
    ids = uniprot.search(query)


    # Download sequence files and read the sequences from it
    genes = []
    sequences = []
    # RegEx pattern used to extract the gene name from fasta header
    gene_name_pattern = "(?<=GN=)[0-9A-Za-z]+"
    for file in uniprot.fetch(ids, "fasta"):
        fasta_file = fasta.FastaFile.read(file)
        # There is only one entry in file
        for header, seq_str in fasta_file.items():
            genes.append(re.search(gene_name_pattern, header).group(0))
            sequences.append(seq.ProteinSequence(seq_str))


    # Create multiple sequence alignment with Clustal Omega
    alignment = clustalo.ClustalOmegaApp.align(sequences)


    # The distance measure required for the tree calculation is the
    # percentage of non-identical amino acids in the respective two
    # sequences
    distances = 1 - align.get_pairwise_sequence_identity(alignment, mode="shortest")
    # Create tree via neighbor joining
    tree = phylo.neighbor_joining(distances)
    # Convert to NetworkX graph
    # For the graph visualization, the edge directions are unnecessary
    graph = tree.as_graph().to_undirected()

    fig = plt.figure(figsize=(8.0, 8.0))
    ax = fig.gca()
    ax.axis("off")
    # Calculate position of nodes in the plot
    pos = nx.kamada_kawai_layout(graph)
    # Assign the gene names to the nodes that represent a reference index
    node_labels = {i: name for i, name in enumerate(genes)}
    nx.draw_networkx_edges(graph, pos, ax=ax)
    nx.draw_networkx_labels(
        graph,
        pos,
        ax=ax,
        labels=node_labels,
        font_size=7,
        # Draw a white background behind the labeled nodes
        # for better readability
        bbox=dict(pad=0, color="white"),
    )
    fig.tight_layout()

    plt.show()


.. _sphx_glr_download_examples_gallery_sequence_homology_gpcr_evolution.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: gpcr_evolution.ipynb <gpcr_evolution.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: gpcr_evolution.py <gpcr_evolution.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_