Datasets:
File size: 1,838 Bytes
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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.
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