PopCILA is a multimodal computational framework designed to decompose phenotype-associated intercellular signaling. Guided by diverse phenotypes, PopCILA identifies phenotype-associated signaling at population scale—beginning with ligand–receptor interactions and extendable to downstream transcriptional cascades—and then projects these signals onto single-cell or spatial data to pinpoint specific cellular actors and tissue niches and to resolve intercellular signaling events that underlie phenotypic variation.
PopCILA supports multiple phenotype types, including binary, continuous, ordinal, and right-censored survival outcomes.
PopCILA is implemented in Python 3 and can be installed via:
pip install popcilaThis repository provides two end-to-end tutorials (two tracks):
| Track | Notebook Link |
|---|---|
| Single-cell RNA-seq | 🔗 View Tutorial |
| Spatial Transcriptomics | 🔗 View Tutorial |
💡 Tip: The notebooks are written to be self-contained. Follow the sections in order within each notebook.
If you use PopCILA in your research, please consider citing our paper (coming soon).
- Maintainer: Youpeng Yang
- Email: yangyp33@alumni.sysu.edu.cn
- Issues: Please open a GitHub Issue (recommended)