Datasets:
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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)
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