---
license: gpl-3.0
tags:
- single-cell
- genomics
---
# Building a causality-aware single-cell RNA-seq foundation model via context-specific causal regulation modeling

scCAFM is a causality-aware foundation model designed for large-scale single-cell transcriptomic analysis. Unlike existing single-cell foundation models that mainly learn associative gene relationships or operate only at the dataset‐ or cell-type level, scCAFM enables cell-specific causal inference at atlas scale while simultaneously learning transferable gene and cell embeddings enriched with causal semantics. By jointly modeling gene regulatory structure and context-dependent embeddings, scCAFM provides a powerful foundation for studying heterogeneous cellular states, developmental trajectories, disease progression, and perturbation responses.

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<img src="Fig1.png" width="90%">
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## Key features
**Structure foundation module (SFM)**
* Efficient, context-aware causal GRN inference in a latent factor space.
* Uses a Mixture-of-Experts (MoE) architecture so different latent experts capture distinct regulatory contexts; this enables per-cell GRN specialization without learning a full causal model per cell.
* Outputs: per-cell directed edges with causal confidence, context assignment, and compact latent summaries.

**Embedding foundation module (EFM)**
* Learns gene and cell embeddings guided by the SFM-inferred causal structure (e.g., contrastive/cause-aware objectives).
* Embeddings are transferable: they improve downstream supervised and unsupervised tasks (drug sensitivity, perturbation response prediction, trajectory/lineage inference).


## Model assets

Model files are stored under `models/`:

* `models/sfm_config.json`
* `models/sfm_model.safetensors`
* `models/cond_dict.json`
* `models/vocab.json`
* `models/vocab.safetensors`

Supporting CSV resources such as `human_tfs.csv`, `mouse_tfs.csv`, `OmniPath.csv`, and `homologous.csv` stay at the repository root.

The source code, training pipeline, and full documentation are maintained in the GitHub repository:

* https://github.com/Catchxu/scCAFM