Metadata-Version: 2.1
Name: Polyomino-sc
Version: 1.0.0
Summary: An algorithm framework employing multi-layered regional constraints to accurately assign cell locations, enhancing spatial accuracy and resilience to noise.
Home-page: https://github.com/caiquanyou/Polyomino
Author: Cai Quanyou
Author-email: cai_quanyou@gibh.ac.cn
License: UNKNOWN
Description: Mapping cell locations via multi-layer regionalization constraints
        =========================================================================
        
        Introduction
        ------------
        Resolving spatial cell arrangement is crucial for understanding physiological and pathological processes. While scRNA-seq captures gene expression at single-cell resolution, it loses spatial context, and current spatial transcriptomics methods often compromise on throughput or resolution. Existing integration methods face challenges with accuracy and scalability due to noise from molecular diffusion, cell segmentation errors, and disproportionate cell-type representation. We present CellChIP, an algorithm framework employing multi-layered regional constraints to accurately assign cell locations, enhancing spatial accuracy and resilience to noise. Comparative analysis on benchmark datasets demonstrates CellChIP’s superior accuracy and scalability over existing methods. Applied to liver cancer tissue, CellChIP revealed spatial heterogeneity of cDC cells, a detail missed by deconvolution-based techniques, and achieved cell-cell interaction resolution beyond traditional mapping approaches. Additionally, CellChIP outperforms current techniques in computational efficiency and resource usage, particularly with large-scale stereo-seq data, underscoring its potential for broad application.
        
        .. image:: ./overview.png
          :width: 1200
          :align: center
          :alt: Overview of CellChip
        
        Installation
        ------------
        CellChip can be installed either through GitHub or PyPI.
        
        To install from GitHub:
        
        .. code-block:: bash
        
            git clone https://github.com/caiquanyou/CellChip
            cd CellChip
            python setup.py install # or pip install .
        
        Alternatively, install via PyPI using:
        
        .. code-block:: bash
        
            pip install CellChip
        
        Usage
        -----
        After installation, CellChip can be used in Python as follows:
        
        .. code-block:: python
        
            import CellChip as cc
        
        Contributing
        ------------
        Contributions to CellChip are welcome. Please refer to the project's issues and pull requests for areas where you can help.
        
        License
        -------
        (Include license information here if available)
        
        Support and Contact
        -------------------
        For support or to contact the developers, please use the project's GitHub Issues page.
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: MacOS
Requires-Python: >=3.8.0
Description-Content-Type: text/markdown
