--- 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} } ```