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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_plot_oncoprint.py:


Breast cancer mutation with Oncoprinter
=======================================

The Dataset is collected from cBioportal:
Breast Invasive Carcinoma (TCGA, PanCancer Atlas)

.. GENERATED FROM PYTHON SOURCE LINES 9-17

.. code-block:: Python

    # sphinx_gallery_thumbnail_number = -1
    import matplotlib.pyplot as plt

    import marsilea as ma
    import marsilea.plotter as mp
    from oncoprinter import OncoPrint









.. GENERATED FROM PYTHON SOURCE LINES 22-23

Load data

.. GENERATED FROM PYTHON SOURCE LINES 23-31

.. code-block:: Python



    onco_data = ma.load_data('oncoprint')
    cna = onco_data['cna']
    mrna_exp = onco_data['mrna_exp']
    methyl_exp = onco_data['methyl_exp']
    clinical = onco_data['clinical']








.. GENERATED FROM PYTHON SOURCE LINES 32-34

Make mRNA expression
--------------------

.. GENERATED FROM PYTHON SOURCE LINES 34-43

.. code-block:: Python



    h = ma.Heatmap(mrna_exp, cmap="gist_heat_r", height=.9, width=5,
                   cbar_kws=dict(orientation="horizontal",
                                 title="mRNA Expression"))
    h.add_title(top="mRNA expression Z-SCORE", align="left", fontsize=10)
    h.add_left(mp.Labels(mrna_exp.index), pad=.1)
    h.render()




.. image-sg:: /auto_examples/images/sphx_glr_plot_oncoprint_001.png
   :alt: plot oncoprint
   :srcset: /auto_examples/images/sphx_glr_plot_oncoprint_001.png, /auto_examples/images/sphx_glr_plot_oncoprint_001_2_00x.png 2.00x
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 44-46

Make Methylation expression
---------------------------

.. GENERATED FROM PYTHON SOURCE LINES 46-55

.. code-block:: Python



    m = ma.Heatmap(methyl_exp.astype(float), height=.6, width=5, cmap="summer_r",
                   cbar_kws=dict(orientation="horizontal",
                                 title="Methylation"))
    m.add_title(top="Methylation", align="left", fontsize=10)
    m.add_left(mp.Labels(methyl_exp.index), pad=.1)
    m.render()




.. image-sg:: /auto_examples/images/sphx_glr_plot_oncoprint_002.png
   :alt: plot oncoprint
   :srcset: /auto_examples/images/sphx_glr_plot_oncoprint_002.png, /auto_examples/images/sphx_glr_plot_oncoprint_002_2_00x.png 2.00x
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 56-58

Create Oncoprint
----------------

.. GENERATED FROM PYTHON SOURCE LINES 58-63

.. code-block:: Python



    op = OncoPrint(cna, name="main")
    op.render()




.. image-sg:: /auto_examples/images/sphx_glr_plot_oncoprint_003.png
   :alt: plot oncoprint
   :srcset: /auto_examples/images/sphx_glr_plot_oncoprint_003.png, /auto_examples/images/sphx_glr_plot_oncoprint_003_2_00x.png 2.00x
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 64-66

Make clinical information
-------------------------

.. GENERATED FROM PYTHON SOURCE LINES 66-75

.. code-block:: Python



    clinical = clinical[op.samples_order]
    tumor_type = clinical.loc['Cancer Type Detailed']
    tumor_colors = mp.Colors(tumor_type, label="Tumor Type", label_loc="left")

    mut_count = clinical.loc['Mutation Count']
    mut_number = mp.Numbers(mut_count, show_value=False, color="orange")








.. GENERATED FROM PYTHON SOURCE LINES 76-77

Add clinical to the oncoprint

.. GENERATED FROM PYTHON SOURCE LINES 77-84

.. code-block:: Python



    op.add_bottom(tumor_colors, size=.2, pad=.1)
    op.add_bottom(mut_number, size=.2, name="mutation_count", pad=.1,
                  legend=False)
    op.render()




.. image-sg:: /auto_examples/images/sphx_glr_plot_oncoprint_004.png
   :alt: plot oncoprint
   :srcset: /auto_examples/images/sphx_glr_plot_oncoprint_004.png, /auto_examples/images/sphx_glr_plot_oncoprint_004_2_00x.png 2.00x
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 85-86

Append expression to the oncoprint

.. GENERATED FROM PYTHON SOURCE LINES 86-90

.. code-block:: Python


    op /= h
    op /= m








.. GENERATED FROM PYTHON SOURCE LINES 91-92

Render

.. GENERATED FROM PYTHON SOURCE LINES 92-101

.. code-block:: Python


    op.set_margin(.2)
    op.add_legends(box_padding=2, stack_size=4)
    op.render()
    mut_ax = op.get_ax("main", "mutation_count")
    mut_ax.set_axis_off()
    mut_ax.text(0, .5, "Mutation Count", rotation=0, ha="right",
                va="center", transform=mut_ax.transAxes)
    plt.show()



.. image-sg:: /auto_examples/images/sphx_glr_plot_oncoprint_005.png
   :alt: plot oncoprint
   :srcset: /auto_examples/images/sphx_glr_plot_oncoprint_005.png, /auto_examples/images/sphx_glr_plot_oncoprint_005_2_00x.png 2.00x
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 12.121 seconds)


.. _sphx_glr_download_auto_examples_plot_oncoprint.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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