---
license: cc-by-nc-4.0
language:
- en
tags:
- antibody
- immunology
- protein
- vdj
- oas
- sabdab
size_categories:
- 100M<n<1B
configs:
- config_name: sabdab
  data_files:
    - split: cased
      path: sabdab/04a_cased.parquet
    - split: clustered
      path: sabdab/04c_clustered.parquet
    - split: prism2
      path: sabdab/prism2_sabdab.parquet
- config_name: paired
  data_files:
    - split: train
      path: paired/train.parquet
    - split: validation
      path: paired/val.parquet
    - split: test
      path: paired/test.parquet
- config_name: unpaired_heavy
  data_files:
    - split: train
      path: unpaired/train/heavy/train_rg*.parquet
    - split: validation
      path: unpaired/val/heavy/val_rg*.parquet
    - split: test
      path: unpaired/test/heavy/test_rg*.parquet
- config_name: unpaired_light
  data_files:
    - split: train
      path: unpaired/train/light/train_rg*.parquet
    - split: test
      path: unpaired/test/light/test_rg*.parquet
---

# PRISM2 Antibody Dataset

Private dataset backing the PRISM2 family of antibody language models trained
at the Romero Lab (Duke University). Bundles the OAS immune-repertoire and
SAbDab structural corpora used for the v6 / v7 unified VDJ runs, plus the
V/D/J gene vocabulary files.

All sequence data has been pre-filtered for the **production** germline-distance
threshold used in PRISM2 training, so what you load here is what the model
trained on — no extra filtering required.

## Layout

```
sabdab/
  04a_cased.parquet         IMGT-numbered, case-annotated antibodies
  04c_clustered.parquet     30%-identity clustered Phase 3 origin set (6,158 rows)
  prism2_sabdab.parquet     Final processed SAbDab for PRISM2

gene_vocab/
  gene_vocabulary.json      Combined V/D/J vocabulary (legacy)
  gene_vocab_v.json         V-gene allele → integer
  gene_vocab_d.json         D-gene allele → integer
  gene_vocab_j.json         J-gene allele → integer

paired/                     OAS paired heavy+light, filtered (heavy ngl≥3, light ngl≥2)
  train.parquet
  val.parquet
  test.parquet

unpaired/                   OAS unpaired, filtered (heavy ngl≥3 OR light ngl≥2)
  train/
    heavy/                  chunked, 7,334 files
    light/                  chunked, 1,291 files
  val/
    heavy/                  chunked, 1,058 files
  test/
    heavy/                  chunked
    light/                  chunked
```

## Filter rationale

The PRISM2 training objective relies on somatic-hypermutation signal; reads
indistinguishable from naive (germline-identical) sequences contribute trivial
targets to the SHM loss. We therefore drop them upstream:

- **Heavy chains**: keep only sequences with germline-distance `num_ngl_muts ≥ 3`.
- **Light chains**: keep only sequences with `num_ngl_muts ≥ 2`.

The `paired/` split applies **both** thresholds (a row is kept iff its heavy
chain has ngl≥3 AND its light chain has ngl≥2). The `unpaired/` split is
per-chain — each row is a single chain and is kept if it passes its own
threshold.

## Chunking convention

Unpaired sets are stored as `*_rg{NNNNN}.parquet` chunks of roughly 100 K rows
each, SNAPPY compressed. The data loader expands the glob and shuffles at the
chunk level, which keeps memory bounded while preserving cross-chunk
randomness.

| Split | Chain | Files |
|---|---|---|
| train | heavy | 7,334 |
| train | light | 1,291 |
| val | heavy | 1,058 |
| val | light | — (not generated upstream) |
| test | heavy | 1,312 |
| test | light | 361 |

The unpaired `test` chunks were re-created from the upstream concat using the
same filter so they match `train/val` layout. `val/light` was absent from the
upstream pipeline and is not present here either.

## Loading

```python
from datasets import load_dataset

# SAbDab structural antibodies
sabdab = load_dataset("RomeroLab-Duke/prism2-antibody-dataset", "sabdab", token=True)

# OAS paired (filtered)
paired = load_dataset("RomeroLab-Duke/prism2-antibody-dataset", "paired", token=True)

# OAS unpaired heavy (chunked — streaming recommended)
heavy = load_dataset(
    "RomeroLab-Duke/prism2-antibody-dataset",
    "unpaired_heavy",
    streaming=True,
    token=True,
)
```

## Source attribution

- **OAS** — Olsen, T. H., Boyles, F., & Deane, C. M. (2022). *Observed Antibody
  Space: A diverse database of cleaned, annotated, and translated unpaired and
  paired antibody sequences*. Protein Science. Downloaded via the official
  bulk-CSV index and re-annotated with ANARCI (IMGT scheme) before
  deduplication, clustering, and the germline filter above.
- **SAbDab** — Dunbar, J., Krawczyk, K., Leem, J., Baker, T., Fuchs, A.,
  Georges, G., Shi, J., & Deane, C. M. (2014). *SAbDab: the structural
  antibody database*. Nucleic Acids Research. Filtered to non-redundant
  structurally resolved antibodies with paired heavy/light annotations.

## License

CC BY-NC 4.0 (research use). OAS itself is CC BY 4.0; SAbDab inherits the
underlying PDB licensing. Commercial use must clear both upstream sources.

## Citation

If you use this dataset, please cite the PRISM2 work and the upstream OAS /
SAbDab references above.