Metadata-Version: 2.5
Name: sigma-omics
Version: 0.1.0a1
Summary: Spatial interface analysis for spatial metabolomics and transcriptomics
Project-URL: Homepage, https://github.com/Elsa-bingxue/SIGMA
Project-URL: Repository, https://github.com/Elsa-bingxue/SIGMA
Project-URL: Issues, https://github.com/Elsa-bingxue/SIGMA/issues
Author-email: Bingxue Du <dubingxue73@gmail.com>
License: MIT
License-File: LICENSE
Keywords: graph neural network,mass spectrometry imaging,spatial metabolomics,spatial omics,tumor boundary
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.10
Requires-Dist: anndata>=0.10
Requires-Dist: numpy>=1.24
Requires-Dist: pandas>=2.0
Requires-Dist: scanpy>=1.10
Requires-Dist: scikit-learn>=1.3
Requires-Dist: scipy>=1.10
Requires-Dist: torch-geometric>=2.5
Requires-Dist: torch>=2.1
Provides-Extra: dev
Requires-Dist: build>=1.2; extra == 'dev'
Requires-Dist: pytest>=8; extra == 'dev'
Requires-Dist: ruff>=0.6; extra == 'dev'
Requires-Dist: twine>=5; extra == 'dev'
Provides-Extra: plot
Requires-Dist: matplotlib>=3.8; extra == 'plot'
Description-Content-Type: text/markdown

# SIGMA (`sigma-omics`)

SIGMA is a Python toolkit for spatial interface analysis integrating mass-spectrometry imaging (MSI) and spatial transcriptomic representations.

> This package is currently an alpha release. Its scientific definitions are
> preserved from the HBC515 reference implementation while the API and
> multi-dataset validation are being completed.

## Install

After the first PyPI release:

```bash
pip install sigma-omics
```

The distribution name is `sigma-omics`; the Python import remains
`sigma_spatial`.

## Install from source

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

## Minimal usage

```python
import scanpy as sc
from sigma_spatial import SIGMA

adata = sc.read_h5ad("sample.h5ad")
SIGMA(seed=0).fit(
    adata,
    annotation_key="annotation",
    tumor_label="Tumor",
    stroma_label="Stroma",
    rna_key="X_harmony",
)

# Main outputs
adata.obs[["sigma_region_probability", "sigma_boundary", "sigma_d_signed"]]
```

## Scope

The package should contain reusable SIGMA computation only. Manuscript-specific simulation, benchmarking, GO enrichment, plotting, and sample-specific analyses should live under `examples/` or a separate analysis repository.
