---
tags:
  - biology
  - genomics
  - bulk-rna-seq
task_categories:
  - text-classification
license: cc-by-4.0
---

# Virtual Cell — Distilled Bulk Encoder Example Dataset

A minimal sample dataset for verifying the data format and running quick
end-to-end checks with
[ConvergeBio/virtual-cell-distil-bulk](https://huggingface.co/ConvergeBio/virtual-cell-distil-bulk).

> **This dataset is not intended for training or evaluation.** It contains a
> small number of samples and is not representative of a real distribution.
> Metrics produced from this dataset should not be interpreted.

## Dataset contents

Derived from a public sepsis bulk RNA-seq study ([GSE185263](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185263)). Preprocessed
into the model's input format as a minimal working example.

| Split | Samples | Class distribution |
|---|---|---|
| train | 88 | 53 sepsis / 35 healthy |
| validation | 22 | 13 sepsis / 9 healthy |

Labels: `0` = healthy, `1` = sepsis.

## Loading

```python
from datasets import load_dataset

ds = load_dataset("ConvergeBio/virtual-cell-distil-bulk-example")
train_ds = ds["train"]
val_ds   = ds["validation"]
```

## Schema

| Column | Shape | Type | Description |
|---|---|---|---|
| `bulk_expression` | [18301] | float32 | Log-normalised bulk gene expression, aligned to `gene_names.txt` |
| `labels` | scalar | int | Class index (0 = healthy, 1 = sepsis) |
| `disease_state` | scalar | str | Original label string |
| `sample_id` | scalar | str | GEO sample accession ID |

## Citation

If you use this dataset, please cite the original study:

```bibtex
@article{baghela2022sepsis,
  author  = {Baghela, A. and others},
  title   = {Predicting sepsis severity at first clinical presentation: The role of endotypes and mechanistic signatures},
  journal = {EBioMedicine},
  year    = {2022},
  volume  = {75},
  pages   = {103776},
  doi     = {10.1016/j.ebiom.2021.103776},
  note    = {GEO accession: GSE185263},
}
```

If you use the Virtual Cell distilled bulk encoder, please also cite:

```bibtex
@article{convergecell2026,
  author = {ConvergeBio},
  title  = {ConvergeCELL: An end-to-end platform from patient transcriptomics to therapeutic hypotheses},
  year   = {2026},
  note   = {Preprint available on bioRxiv},
}
```

## License

[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/deed.en)