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CAJAL: a Python package for the analysis of single-cell morphological data
==========================================================================

CAJAL is a Python package designed to explore and analyze the morphology of cells
and its relationship with other single-cell data using the Gromov-Wasserstein (GW) distance.
This distance quantifies the degree to which the shape of one cell can
be transformed into that of another with minimal stretching or bending. One of the
key benefits of using the GW distance is that it does not require any prior
knowledge or model for the morphology of the cells. This feature makes CAJAL suitable
for studying arbitrarily heterogeneous mixtures of cells with highly complex and diverse
morphologies that may defy straightforward classification.

The morphological distance produced by CAJAL is a bona-fide mathematical distance
in a latent space of cell morphologies. In this latent space, each cell is represented
by a point, and distances between cells indicate the amount of physical deformation
needed to change the morphology of one cell into that of another. By formulating the
problem in this way, CAJAL can make use of standard statistical and machine learning approaches to
define cell populations based on their morphology; dimensionally reduce and visualize
cell morphology spaces; and integrate cell morphology spaces across tissues, technologies,
and with other single-cell data modalities, among other analyses.

.. toctree::
   :maxdepth: 2
   :caption: Overview and Walkthrough

   what-is-cajal
   computing-intracell-distance-matrices
   computing-gw-distances
   benchmarking
   average_swc_shape
   gw_variants
   cellaligner

.. toctree::
   :maxdepth: 1
   :caption: TUTORIALS

   notebooks/Example_1
   notebooks/Example_2
   notebooks/Example_3
   notebooks/Example_4
   notebooks/Example_5
   notebooks/Example_6
   notebooks/Example_7

.. toctree::
   :maxdepth: 2
   :caption: API

   swc
   sample_swc
   sample_mesh
   sample_seg
   run_gw
   qgw
   combined_slb_qgw
   laplacian_score
   average_cell_shapes
   utilities
   unbalanced_gw
   fused_gw
   ternary_plot
   wnn
   subcellular
   subcellular_dl

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Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
