Metadata-Version: 2.1
Name: Flow2Spatial
Version: 0.1
Summary: Reconstructing spatial proteomics through transfer learning
Home-page: http://pypi.python.org/pypi/Flow2Spatial/
Author: Ruiqiao He
Author-email: ruiqiaohe@gmail.com
License: GPL
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.8.10
Description-Content-Type: text/markdown
License-File: LICENSE

## Flow2Spatial reconstructs spatial proteomics through transfer learning 

Flow2Spatial is the computational part of SPRING (global spatial proteomics with thousands of high-resolution pixels by microfluidics and transfer learning). 

It aims to reconstruct spatial proteomics from the values of parallel-flow projections in SPRING. Leveraging transfer learning, Flow2Spatial can restore fine structure of protein spatial distribution in different tissue types. 


<p align="center">
  <img src='./docs/Flow2Spatial.png'>
</p>
<p align="center">
  Overview of Flow2Spatial.
</p>

### Prerequisites 
    "torch", "shapely", "scikit-image", "cvxpy", 
    "scanpy", "anndata", "scipy", "numpy", "pandas"

Further tutorials please refer to  https://Flow2Spatial.readthedocs.io/. 

### Citation 

