Metadata-Version: 2.4
Name: SpatialQuery
Version: 0.0.1
Home-page: https://github.com/ShaokunAn/Spatial-Query
Author: Shaokun An
Author-email: shan12@bwh.harvard.edu
License: MIT
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: setuptools>=68.0.0
Requires-Dist: anndata>=0.8.0
Requires-Dist: pandas>=2.0.3
Requires-Dist: scipy
Requires-Dist: matplotlib>=3.7.5
Requires-Dist: mlxtend>=0.23.1
Requires-Dist: seaborn>=0.13.2
Requires-Dist: scikit-learn>=1.3.2
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
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Dynamic: license
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SpatialQuery is a package for fast query of Spatial Transcriptomics data. 

### Analysis of ST data in SpatialQuery

With annotated ST data as input, SpatialQuery first builds a k-D tree based on spatial location in each FOV for fast query of neighboring cell compositions. It is composed of methods for single-FOV and multiple-FOVs.
In single-FOV, it contains methods:

- identify frequent patterns across FOV
- identify frequent patterns around cell type of interest
- identify statistically significant patterns around cell type of interest

For multiple-FOVs data, it contains methods:

- identify frequent patterns around cell type of interest in specified datasets
- identify statistically significant patterns around cell type of interest in specified datasets
- identify differential patterns across datasets

### Installation

```
pip install -i https://test.pypi.org/simple/ SpatialQuery
```

For more details, please refer to `examples/SpatialQuery-example.ipynb`.
