---
license: cc-by-4.0
language: en
tags: [biology, single-cell, transcriptomics, coexpression, baseline]
---

# ConvergeCELL Coexpression Baselines — v0.1.0

Per-tissue gene–gene correlation matrices trained on the
[ConvergeCELL Pseudobulk Panel](https://huggingface.co/datasets/nicolas-lynn/vcell-perturbation-panel)
(panel size pb20, restricted to 8,000 HVGs).

Each baseline is a fitted :class:`CoexpressionBaselineModel` — predicts gene
expression via ``Y = (X − μ)/σ @ C @ σ + μ``. Useful as the **co-expression
floor** any foundation model must beat to claim it has learned anything
beyond gene–gene correlation structure.

## Baselines (12)

| Tissue | File | # training samples | Size |
|---|---|---:|---:|
| `skin` | `coexpr_tissue_skin.npz` | 965 | 209 MB |
| `lung` | `coexpr_tissue_lung.npz` | 575 | 130 MB |
| `bone_marrow` | `coexpr_tissue_bone_marrow.npz` | 470 | 116 MB |
| `kidney` | `coexpr_tissue_kidney.npz` | 440 | 95 MB |
| `eye` | `coexpr_tissue_eye.npz` | 400 | 117 MB |
| `liver` | `coexpr_tissue_liver.npz` | 385 | 104 MB |
| `spleen` | `coexpr_tissue_spleen.npz` | 370 | 117 MB |
| `blood` | `coexpr_tissue_blood.npz` | 330 | 72 MB |
| `heart` | `coexpr_tissue_heart.npz` | 280 | 93 MB |
| `islet` | `coexpr_tissue_islet.npz` | 195 | 92 MB |
| `fat` | `coexpr_tissue_fat.npz` | 175 | 131 MB |
| `bladder` | `coexpr_tissue_bladder.npz` | 25 | 45 MB |

## How to load

```python
import virtual_cell.perturbation as isp
adata = ...                                                      # your input AnnData
model = isp.load_model("coexpr-baseline-T_cell", adata=adata)    # downloads from HF + wraps
preds = model.get_expression_predictions(adata)
```

Direct download:

```python
from huggingface_hub import hf_hub_download
import numpy as np

path = hf_hub_download(repo_id="nicolas-lynn/vcell-coexpr-baselines",
                       filename="coexpr_tissue_T_cell.npz",
                       repo_type="dataset")
art = np.load(path, allow_pickle=True)
C, gene_names = art["C"], art["gene_names"].tolist()
```

## Provenance

- **Trained on**: HuggingFace dataset `nicolas-lynn/vcell-perturbation-panel`
  panel size `pb20`, panel version v1.0.0
- **HVG selection**: top 8,000 variable genes via `scanpy.pp.highly_variable_genes`
  (`flavor='seurat_v3'`) on the full panel before group splitting
- **Min samples per group**: 20

## License

CC BY 4.0.