README.md

---
pretty_name: Gene Ontology Annotation UniProt Sample
license: other
tags:
- biology
- gene-ontology
- goa
- uniprot
- protein-annotation
- gaf
- gpa
- parquet
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*.parquet
  - split: test
    path: data/test-*.parquet
---

# Gene Ontology Annotation UniProt

GOA provides high-quality, evidence-coded Gene Ontology annotations for UniProtKB proteins, RNAs, and protein complexes.

This dataset contains the original GOA UniProt source files plus a viewer-friendly Parquet sample/index table. The source `goa_uniprot_all.gaf.gz` and `goa_uniprot_all.gpa.gz` files are very large, so the default Dataset Viewer table contains the first 50,000 parsed annotation rows from each source file, along with a source-file manifest in `metadata/source_files.parquet`.
Use the original compressed files for complete GOA coverage. Use the default Parquet table for quick inspection, schema discovery, examples, and Dataset Viewer previews.

## Splits

The split is deterministic by `annotation_id`: `sha256(annotation_id) % 10`. Bucket `0` is `test`; buckets `1` through `9` are `train`.

| Split | Rows |
|---|---:|
| train | 89,958 |
| test | 10,042 |
| total | 100,000 |

## Source Files

| File | Size |
|---|---:|
| `goa_uniprot_all.gaf.gz` | 15,387,303,487 bytes |
| `goa_uniprot_all.gpa.gz` | 9,462,421,263 bytes |

## Usage

```bash
pip install datasets
```

Load the viewer table:

```python
from datasets import load_dataset

ds = load_dataset("LiteFold/GOA")
print(ds)
print(ds["train"][0])
```

Load one split:

```python
from datasets import load_dataset

train = load_dataset("LiteFold/GOA", split="train")
test = load_dataset("LiteFold/GOA", split="test")
```

Stream rows:

```python
from datasets import load_dataset

stream = load_dataset("LiteFold/GOA", split="train", streaming=True)
for row in stream.take(5):
    print(row["db_object_id"], row["go_id"], row["evidence_code"])
```

Filter the sample for molecular-function GAF rows:

```python
from datasets import load_dataset

ds = load_dataset("LiteFold/GOA", split="train")
mf = ds.filter(lambda row: row["source_format"] == "GAF" and row["aspect"] == "F")
print(mf[0])
```

Download the source manifest:

```python
import pandas as pd
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="LiteFold/GOA",
    repo_type="dataset",
    filename="metadata/source_files.parquet",
)
source_files = pd.read_parquet(path)
print(source_files)
```

Download the full raw files when needed:

```python
from huggingface_hub import hf_hub_download

gaf_path = hf_hub_download(
    repo_id="LiteFold/GOA",
    repo_type="dataset",
    filename="goa_uniprot_all.gaf.gz",
)
```

## Columns

| Column | Description |
|---|---|
| `annotation_id` | Stable SHA-256 ID for the sampled annotation row. |
| `source_file` | Source file: GAF or GPA. |
| `source_format` | Parsed source format, `GAF` or `GPA`. |
| `source_row_number` | Row number within the source annotation stream. |
| `db` | Source database. |
| `db_object_id` | Annotated object identifier. |
| `db_object_symbol` | GAF object symbol, when available. |
| `qualifier` | Raw qualifier field. |
| `qualifiers` | Qualifier field split on `|`. |
| `go_id` | GO identifier. |
| `db_references` | References split on `|`. |
| `evidence_code` | GO or ECO evidence code. |
| `with_from` | With/from field split on `|`. |
| `aspect` | GAF aspect: `F`, `P`, or `C`; missing for GPA rows. |
| `db_object_name` | GAF object name, when available. |
| `db_object_synonyms` | GAF synonyms split on `|`. |
| `db_object_type` | GAF object type, when available. |
| `taxon_ids` | GAF taxon IDs split on `|`. |
| `interacting_taxon_id` | GPA interacting taxon ID, when available. |
| `date` | Annotation date. |
| `assigned_by` | Annotation provider. |
| `annotation_extension` | Annotation extension field. |
| `gene_product_form_id` | Gene product form identifier. |
| `split_bucket` | Deterministic split bucket from `sha256(annotation_id) % 10`. |

# Citaton

```
@article{huntley2015goa,
  title   = {The {GOA} database: Gene Ontology annotation updates for 2015},
  author  = {Huntley, Rachael P. and Sawford, Tony and Mutowo-Meullenet, Prudence and Shypitsyna, Aleksandra and Bonilla, Carlos and Martin, Maria Jesus and O'Donovan, Claire},
  journal = {Nucleic Acids Research},
  volume  = {43},
  number  = {D1},
  pages   = {D1057--D1063},
  year    = {2015},
  doi     = {10.1093/nar/gku1113}
}
```