.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/reconstruction/compute_scistree.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_reconstruction_compute_scistree.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_reconstruction_compute_scistree.py:


Reconstruct tree by ScisTree
----------------------------

This example shows how to construct a phylogenetic tree using ScisTree on a
binary single-cell genotype matrix.

.. GENERATED FROM PYTHON SOURCE LINES 8-13

.. code-block:: Python


    import scphylo as scp

    # sphinx_gallery_thumbnail_path = "_static/thumbnails/scistree.png"








.. GENERATED FROM PYTHON SOURCE LINES 14-15

First, we load a binary test single-cell genotype data.

.. GENERATED FROM PYTHON SOURCE LINES 15-18

.. code-block:: Python

    df_in = scp.datasets.test()
    df_in.head()






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
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        .dataframe thead th {
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        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>mut0</th>
          <th>mut1</th>
          <th>mut2</th>
          <th>mut3</th>
          <th>mut4</th>
          <th>mut5</th>
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          <th>mut16</th>
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          <th>mut18</th>
          <th>mut19</th>
        </tr>
        <tr>
          <th>cellIDxmutID</th>
          <th></th>
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          <th>cell1</th>
          <td>3</td>
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        <tr>
          <th>cell2</th>
          <td>0</td>
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          <td>0</td>
          <td>0</td>
          <td>0</td>
          <td>0</td>
          <td>0</td>
          <td>1</td>
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          <td>1</td>
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        <tr>
          <th>cell3</th>
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        </tr>
        <tr>
          <th>cell4</th>
          <td>0</td>
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          <td>0</td>
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          <td>0</td>
          <td>0</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 19-21

Next, using :func:`scphylo.tl.scistree` we remove the single-cell noises from the
input.

.. GENERATED FROM PYTHON SOURCE LINES 21-24

.. code-block:: Python

    df_out = scp.tl.scistree(df_in, alpha=0.0000001, beta=0.1)
    df_out.head()





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    running ScisTree with alpha=1e-07, beta=0.1, n_threads=1
    input -- size: 20x20
    input -- 0: 226#, 56.5%
    input -- 1: 94#, 23.5%
    input -- NA: 80#, 20.0%
    input -- CF: False
    output -- size: 20x20
    output -- 0: 271#, 67.8%
    output -- 1: 129#, 32.2%
    output -- NA: 0#, 0.0%
    output -- CF: True
    output -- time: 0.0s (0:00:00.047265)
    flips -- #0->1: 17
    flips -- #1->0: 0
    flips -- #NA->0: 62
    flips -- #NA->1: 18
    rates -- FN: 0.153
    rates -- FP: 0.00000000
    rates -- NA: 0.200
    score -- NLL: 49.047855952735745


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th>HAPLOID 20 20</th>
          <th>mut0</th>
          <th>mut1</th>
          <th>mut2</th>
          <th>mut3</th>
          <th>mut4</th>
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        </tr>
        <tr>
          <th>cellIDxmutID</th>
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          <th></th>
          <th></th>
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      </thead>
      <tbody>
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      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 25-27

Finally, using :func:`scphylo.ul.is_conflict_free_gusfield` we check whether the
inferred genotype matrix is conflict-free or not.

.. GENERATED FROM PYTHON SOURCE LINES 27-29

.. code-block:: Python

    is_cf = scp.ul.is_conflict_free_gusfield(df_out)
    print(is_cf)




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    True





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

   **Total running time of the script:** (0 minutes 0.752 seconds)

**Estimated memory usage:**  10 MB


.. _sphx_glr_download_auto_examples_reconstruction_compute_scistree.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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