Metadata-Version: 2.2
Name: SC2Spa
Version: 1.3.1
Summary: SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution
Author-email: "Linbu Liao, Won Lab" <linbu.liao@gmail.com>
License: BSD 3-Clause License
        
        Copyright (c) 2023 Linbu Liao, Won Lab
        
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Project-URL: Homepage, https://github.com/linbuliao/SC2Spa
Project-URL: Bug Tracker, https://github.com/pypa/SC2Spa/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE

[![PyPI](https://img.shields.io/pypi/v/SC2Spa?logo=PyPI)](https://pypi.org/project/SC2Spa)
[![Docs](https://img.shields.io/readthedocs/sc2spa)](https://sc2spa.readthedocs.io)

SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution
====================================================================================

<p align="center">
  <img src="./SC2Spa.png" alt="SC2Spa Overview" width="600"/>
</p>

## Install
Install SC2Spa:
```
conda create -n SC2Spa python=3.9
conda activate SC2Spa
pip install SC2Spa
```

## Analysis for the SC2Spa manuscript
The analysis for the SC2Spa manuscript can be found in [this repository](https://github.com/linbuliao/SC2Spa_Notebooks).
The analysis and related data were also uploaded to [Figshare](https://figshare.com/articles/dataset/Datasets_for_high_resolution_spatial_mapping_of_mouse_hippocampus_Slide-seqV2_for_SC2Spa/21829905) and [Zenodo](https://zenodo.org/records/8252715).

## Benchmarking and validation code  
The benchmarking code, including scripts for cross-validation and cross-dataset validation, is available for download as `CV_code.zip` from:
https://figshare.com/ndownloader/files/53089715

## Many more to come!
We will update more on our [Read the Docs page](https://sc2spa.readthedocs.io/en/latest/)

## News

__2023/08/22__

SC2Spa is now on BioRXiv!
https://www.biorxiv.org/content/10.1101/2023.08.22.554277v1
