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

.. only:: html

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

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

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

.. _sphx_glr_gallery_biology_plot_breast_cancer_ppi.py:


Breast cancer proteins
======================

This example visualises network of putatively interacting proteins according to the STRING database, filtered to include only entries related to breast cancer.

Vertices are lifted above the edges by increasing their zorder above the edge level, which is 2.

.. GENERATED FROM PYTHON SOURCE LINES 9-45



.. image-sg:: /gallery/biology/images/sphx_glr_plot_breast_cancer_ppi_001.png
   :alt: plot breast cancer ppi
   :srcset: /gallery/biology/images/sphx_glr_plot_breast_cancer_ppi_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import numpy as np
    import pandas as pd
    import networkx as nx
    import matplotlib.pyplot as plt
    import iplotx as ipx


    node_data = pd.read_csv("data/breast_cancer_string_network_coordinates.tsv", sep="\t", index_col=0)
    edge_data = pd.read_csv("data/breast_cancer_string_interactions_short.tsv", sep="\t")

    g = nx.Graph()
    g.add_edges_from(edge_data.iloc[:, :2].values)

    layout = node_data[["x_position", "y_position"]]
    node_data["color_ipx"] = [list(map(lambda x: float(x) / 256.0, x[4:-1].split(","))) for x in node_data["color"]]
    node_data["label_color"] = ["white" if np.mean(x) < 0.4 else "black" for x in node_data["color_ipx"]]


    fig, ax = plt.subplots(figsize=(8, 8))
    ipx.network(
        g,
        layout=layout,
        ax=ax,
        vertex_labels=True,
        vertex_marker="r",
        vertex_size="label",
        vertex_facecolor=node_data["color_ipx"].to_dict(),
        vertex_label_color=node_data["label_color"].to_dict(),
        vertex_edgecolor="k",
        vertex_linewidth=0.5,
        edge_alpha=0.2,
        vertex_zorder=3,

    )
    fig.tight_layout()


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

   **Total running time of the script:** (0 minutes 0.589 seconds)


.. _sphx_glr_download_gallery_biology_plot_breast_cancer_ppi.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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