Metadata-Version: 2.1
Name: spatialtis
Version: 0.5.0rc0
Summary: Ultra-fast spatial analysis toolkit for large-scale spatial single-cell data
Home-page: https://github.com/Mr-Milk/SpatialTis
Author-email: yb97643@um.edu.mo
License: Apache License 2.0
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Rust
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

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<img src="https://raw.githubusercontent.com/Mr-Milk/SpatialTis/master/img/Logo.svg" width="200"/>
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# SpatialTis
[![Documentation Status](https://readthedocs.org/projects/spatialtis/badge/?version=latest&style=flat-square)](https://spatialtis.readthedocs.io/en/latest/?badge=latest)
![CI](https://flat.badgen.net/github/status/Mr-Milk/SpatialTis?icon=github&label=CI)
![codecov](https://flat.badgen.net/codecov/c/github/Mr-Milk/SpatialTis)
![pypi](https://flat.badgen.net/pypi/v/spatialtis?color=blue)
![licence](https://flat.badgen.net/github/license/Mr-Milk/SpatialTis)

SpatialTis is an ultra-fast spatial analysis toolkit for large-scale spatial single-cell data.

- ✔️ Spatial Transcriptome (Non single-cell)
- ✔️ Spatial Proteome (Single-cell)
- 🦀 Core algorithms implements in Rust
- 🚀 Parallel processing support

### 🔋 Highlighted spatial analysis

- Cell neighbors search (KD-Tree/R-Tree/Delaunay)
- Cell-Cell Interaction
- Marker spatial co-expression
- Spatial variable genes (current support: SOMDE)
- GCNG: Inferring ligand-receptor using graph convolution network
- Identify neighbor dependent markers

### 📦 Other analysis

  - Spatial distribution
  - Hotspot detection
  - Spatial auto-correlation
  - Spatial heterogeneity

[Quick Start](https://spatialtis.readthedocs.io/en/latest/usage/get_started.html)


## Installation

SpatialTis requires python version >= 3.8

### pypi

Install the basics

```shell
pip install spatialtis
```

For the full features

```shell
pip install 'spatialtis[all]'
```

Install the current development version

```shell
pip install git+https://github.com/Mr-Milk/SpatialTis.git
```

### Docker (Not Available)

The quickest way to run is to use a docker image, it contains all you need to start from cell type identification.

```shell
docker pull spatialtis/spatialtis
```
To run a jupyter notebook from the docker image and mount your data folder to it:
```shell
cd your/data/
docker run -it [--rm] -p 8888:8888
  --mount type=bind,source="$PWD",target=/work \
  spatialtis/spatialtis
# if port 8888 is taken, try `-p 9999:8888` and change to 9999
```


## Low level API

If you are interested in using low level algorithms yourself,
Please refer to [spatialtis_core](https://github.com/Mr-Milk/SpatialTis-core)
It provides clear document for all exposed API.


