Metadata-Version: 2.1
Name: SpatialDM
Version: 0.0.2
Summary: SpatialDM: Spatial co-expression Detected by bivariate Moran
Home-page: https://github.com/leeyoyohku/SpatialDM
Author: ['Zhouxuan Li', 'Tianjie Wang', 'Yuanhua Huang']
Author-email: leeyoyo@connect.hku.hk
License: Apache-2.0
Keywords: Spatial transcriptomics,Spatial association,Ligand-recptor interaction
Platform: UNKNOWN
Requires-Dist: numpy (>=1.9.0)
Requires-Dist: scipy (>=1.4.0)
Requires-Dist: matplotlib
Requires-Dist: statsmodels (>=0.11.1)
Requires-Dist: scanpy
Requires-Dist: pandas
Requires-Dist: sklearn
Requires-Dist: seaborn
Provides-Extra: docs
Requires-Dist: sphinx-bootstrap-theme ; extra == 'docs'

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SpatialDM: Spatial Direct Messaging Detected by bivariate Moran
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About
=====



Installation
============

SpatialDM is available through `PyPI <https://pypi.org/project/spatialdm/>`_. 
To install, type the following command line and add ``-U`` for updates:

.. code-block:: bash

   pip install -U spatialdm

Alternatively, you can install from this GitHub repository for latest (often 
development) version by the following command line:

.. code-block:: bash

   pip install -U git+https://github.com/leeyoyohku/SpatialDM

Installation time: < 1 min



Quick example
=============

Using the build-in melanoma dataset as an example, the following Python script
will compute the p-value indicating whether a certain Ligand-Receptor is 
spatially co-expressed.

.. code-block:: python

  import spatialdm as sdm
  adata = sdm.datasets.melanoma()
  my_sample = sdm.SpatialDM(X=adata.X, spatialcoord=adata.obsm['spatial'])
  my_sample.extract_lr(species='human', min_cell=3)
  my_sample.weight_matrix(l=1.2, cutoff=0.2, single_cell=False)
  my_sample.spatialdm_global(1000, select_num=None, method='permutation')
  sdm.pl.volcano(my_sample)


Detailed Manual
===============

The full manual is at https://spatialdm.readthedocs.io


References
==========

A BioRxiv preprint will be online soon.

