Metadata-Version: 2.4
Name: sc-graft
Version: 0.0.0
Summary: single-cell Graph of Receptors, pAthways, Factors and Targets — external-prior loaders (early placeholder; core model not yet released)
Author-email: Ohbin Kwon <ohbin.kwon01@gmail.com>
License: MIT
Project-URL: Homepage, https://github.com/ObKwon115/sc-graft
Project-URL: Repository, https://github.com/ObKwon115/sc-graft
Project-URL: Issues, https://github.com/ObKwon115/sc-graft/issues
Keywords: single-cell,scRNA-seq,graph-neural-network,cell-signaling,bioinformatics
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Provides-Extra: scenic
Requires-Dist: pandas>=1.5; extra == "scenic"

# sc-graft

**Early placeholder release.** `sc-graft` — a single-cell **G**raph of
**R**eceptors, p**A**thways, **F**actors and **T**argets — is a
biologically-grounded heterogeneous graph transformer for inferring how receptor
signaling propagates to target genes in single cells.

This pre-release ships only a small slice of the **preprocessing** layer: the
**external-prior loaders** (STRING physical PPI, MSigDB gene sets, SCENIC
regulons). The network-construction logic and the model itself are under active
development and are **not included yet**.

```python
from sc_graft import load_string_interactions, read_gmt, gmt_path, load_regulons
```

- Source / docs: https://github.com/ObKwon115/sc-graft
- License: MIT
