.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/gallery/sequence/annotation/sigma_domains.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_annotation_sigma_domains.py>`
        to download the full example code.

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

.. _sphx_glr_examples_gallery_sequence_annotation_sigma_domains.py:


Domains of bacterial sigma factors
==================================

This script displays the 4 fundamental domains of the *E. coli*
:math:`\sigma^{70}`-like :math:`\sigma` factors.

.. GENERATED FROM PYTHON SOURCE LINES 8-128



.. image-sg:: /examples/gallery/sequence/annotation/images/sphx_glr_sigma_domains_001.png
   :alt: Domains of E. coli $\sigma$ factors
   :srcset: /examples/gallery/sequence/annotation/images/sphx_glr_sigma_domains_001.png, /examples/gallery/sequence/annotation/images/sphx_glr_sigma_domains_001_2_00x.png 2.00x
   :class: sphx-glr-single-img





.. code-block:: Python


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

    import re
    from collections import OrderedDict
    import matplotlib.pyplot as plt
    import numpy as np
    from matplotlib.patches import FancyBboxPatch, Rectangle
    import biotite.database.entrez as entrez
    import biotite.sequence.io.genbank as gb

    # The names of the sigma factors and the corresponding genes
    genes = OrderedDict(
        {
            r"$\sigma^{70}$": "rpoD",
            r"$\sigma^{24}$": "rpoE",
            r"$\sigma^{28}$": "rpoF",
            r"$\sigma^{32}$": "rpoH",
            r"$\sigma^{38}$": "rpoS",
        }
    )

    # Find SwissProt entries for these genes in NCBI Entrez protein database
    uids = []
    for name, gene in genes.items():
        query = (
            entrez.SimpleQuery(gene, "Gene Name")
            & entrez.SimpleQuery("srcdb_swiss-prot", "Properties")
            & entrez.SimpleQuery("Escherichia coli K-12", "Organism")
        )
        ids = entrez.search(query, "protein")
        # Only one entry per gene in E. coli K-12 is expected
        assert len(ids) == 1
        uids += ids
    # Download corresponding GenBank files as single, merged file
    file = entrez.fetch_single_file(uids, None, "protein", ret_type="gb")

    # Array that will hold for each of the genes and each of the 4 domains
    # the first and last position
    # The array is initally filled with -1, as the value -1 will indicate
    # that the domain does not exist in the sigma factor
    domain_pos = np.full((len(genes), 4, 2), -1, dtype=int)
    # Array that will hold the total sequence length of each sigma factor
    seq_lengths = np.zeros(len(genes), dtype=int)
    # Read the merged file containing multiple GenBank entries
    multi_file = gb.MultiFile.read(file)
    # Iterate over each GenBank entry
    for i, gb_file in enumerate(multi_file):
        _, length, _, _, _, _ = gb.get_locus(gb_file)
        seq_lengths[i] = length
        annotation = gb.get_annotation(gb_file)
        # Find features, that represent a sigma factor domain
        for feature in annotation:
            if (
                feature.key == "Region"
                and "note" in feature.qual
                and "Sigma-70 factor domain" in feature.qual["note"]
            ):
                # Extract the domain number
                # and decrement for 0-based indexing
                #
                # e.g. 'Sigma-70 factor domain-2.' => 1
                #                              ^
                domain_index = (
                    int(
                        re.findall(
                            r"(?<=Sigma-70 factor domain-)\d+", feature.qual["note"]
                        )[0]
                    )
                    - 1
                )
                # Expect a single contiguous location of the domain
                assert len(feature.locs) == 1
                loc = list(feature.locs)[0]
                # Store first and last position of the domain
                domain_pos[i, domain_index, :] = [loc.first, loc.last]

    fig = plt.figure(figsize=(8.0, 4.0))
    ax = fig.gca()
    # The color for each one of the four domains
    colors = ["firebrick", "forestgreen", "dodgerblue", "goldenrod"]
    # Draw each sequence
    for i, (gene_name, domain_pos_for_gene, length) in enumerate(
        zip(genes.keys(), domain_pos, seq_lengths)
    ):
        # Add base line representing the sequence itself
        ax.add_patch(Rectangle((1, i - 0.05), length, 0.1, color="gray"))
        # Draw each domain
        for j, ((first, last), color) in enumerate(zip(domain_pos_for_gene, colors)):
            if first != -1 and last != -1:
                # FancyBboxPatch to get rounded corners in rectangle
                ax.add_patch(
                    FancyBboxPatch(
                        (first, i - 0.4),
                        last - first,
                        0.8,  # color=color,
                        boxstyle="round,pad=0,rounding_size=10",
                        ec="black",
                        fc=color,
                        mutation_aspect=0.02,
                    )
                )
                ax.text(
                    x=(last + first) / 2,
                    y=i,
                    s=rf"$\sigma_{j + 1}$",
                    ha="center",
                    va="center",
                )
    ax.set_xlim(0, max(seq_lengths))
    ax.set_xlabel("Sequence position")
    # Inverted y-axis
    ax.set_yticks(np.arange(len(genes)))
    ax.set_yticklabels(list(genes.keys()))
    ax.set_ylim(len(genes), -1)
    ax.set_title(r"Domains of E. coli $\sigma$ factors")
    fig.tight_layout()

    plt.show()


.. _sphx_glr_download_examples_gallery_sequence_annotation_sigma_domains.py:

.. only:: html

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

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

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: sigma_domains.zip <sigma_domains.zip>`


.. only:: html

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

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