Metadata-Version: 2.1
Name: SpaHDmap
Version: 0.1.2
Summary: Interpretable high-definition dimension reduction of spatial transcriptomics data by SpaHDmap
Author-email: Kun Qian <kunqian@stu.pku.edu.cn>, Junjie Tang <junjie.tang@pku.edu.cn>
Maintainer-email: Kun Qian <kunqian@stu.pku.edu.cn>
License: MIT License
Project-URL: Homepage, https://github.com/sldyns/SpaHDmap
Keywords: spatial transcriptomics,bioinformatics,dimension reduction,deep learning
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Typing :: Typed
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
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# SpaHDmap: deep fusion of spatial transcriptomics and histology images for interpretable high-definition embedding mapping

## Overview

![alt](./Overview.png)

SpaHDmap is based on a multi-modal neural network that takes advantage of the high-dimensionality of transcriptomics
data and the high-definition of image data to achieve interpretable high-definition dimension reduction. 
The high-dimensional expression data enable refined functional annotations and the high-definition image data help to
enhance the spatial resolution.

Based on the high-definition embedding and the reconstruction of gene expressions, SpaHDmap can then perform
high-definition downstream analyses, such as spatial domain detection, gene expression recovery, and identification of
embedding-associated genes as well as high-definition cluster-associated genes.

For more details, please refer to our [manuscript](https://www.biorxiv.org/content/10.1101/2024.09.12.612666).

## Installation
Please install `SpaHDmap` from pypi with:

```bash
pip install SpaHDmap
```

Or clone this repository and use

```bash
pip install -e .
```

in the root of this repository.

## Documentation

Please refer to the [documentation](https://spahdmap.readthedocs.io/en/latest/) for more details, for examples:
- to get the detailed information about installation, please refer to the [installation guide](https://spahdmap.readthedocs.io/en/latest/installation.html).
- to get started with SpaHDmap, please refer to the [tutorials](https://spahdmap.readthedocs.io/en/latest/tutorials/index.html).

## License
This software package is licensed under MIT license. For commercial use, please contact [Ruibin Xi](ruibinxi@math.pku.edu.cn).
