---
license: apache-2.0
task_categories:
  - text-generation
tags:
  - biology
  - genomics
  - dna
  - benchmark
configs:
  - config_name: tata
    data_files:
      - split: train
        path: tata/data.parquet
  - config_name: synonymous_codons
    data_files:
      - split: train
        path: synonymous_codons/data.parquet
---

# Carbon Perturbation Bench

Two **sequence-level perturbation tasks** for evaluating DNA foundation models:

- **`tata`** (5,000 rows): the TATA-box motif inside a real promoter is
  disrupted with random nucleotide substitutions. Probes whether the model
  has internalised eukaryotic promoter architecture (it should assign higher
  log-likelihood to the intact promoter than the perturbed one).
- **`synonymous_codons`** (5,000 rows): codons in a real CDS are replaced
  with synonyms encoding the same amino acid. Probes whether the model has
  learned codon-usage bias (it should prefer native codon usage over the
  synonymous variant).

Both subsets share the same schema:

| column | description |
|---|---|
| `chr`, `start`, `end`, `strand` | hg38 locus |
| `length` | sequence length in bp |
| `original_sequence` | the real (unperturbed) sequence — positive |
| `sequence` | the perturbed sequence — negative control |

## Usage

```python
from datasets import load_dataset

tata = load_dataset("hf-carbon/carbon-perturbation-bench", "tata", split="train")
syn = load_dataset("hf-carbon/carbon-perturbation-bench", "synonymous_codons", split="train")
```

## Eval recipe

Pairwise likelihood discrimination: score `LL(original_sequence)` vs
`LL(sequence)` under the model, and report `mean(LL(real) >= LL(perturbed))`.
A ready-to-run scorer for Carbon, GENERator, and Evo2 lives at
[`evaluation/perturbation_tasks.py`](https://github.com/huggingface/carbon)
in the Carbon release repo.