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---
license: mit
language:
- en
tags:
- biomedical
- clinvar
- genomic-variants
- instruction-tuning
- text-generation
task_categories:
- text-generation
- tabular-classification
size_categories:
- 10K<n<100K
configs:
- config_name: tabular
data_files:
- split: train
path: train.csv
- split: validation
path: valid.csv
- split: test
path: test.csv
- config_name: instruction
data_files:
- split: train
path: biogpt_train.csv
- split: validation
path: biogpt_valid.csv
- split: test
path: biogpt_test.csv
---
**Year:** 2025
**License:** MIT
**Author:** Sepideh Moafi
---
# PathogenAgentAI Instruction Dataset
## Dataset Description
A ClinVar-derived dataset developed as part of the **PathogenAgentAI** research software project. The dataset is released in two parallel formats:
- **Tabular version** (`train.csv`, `valid.csv`, `test.csv`) — structured genomic-variant data for classical ML and analysis.
- **BioGPT instruction version** (`biogpt_train.csv`, `biogpt_valid.csv`, `biogpt_test.csv`) — instruction-style data for fine-tuning biomedical language models.
## Dataset Structure
### Splits
| Split | Tabular file | Instruction file |
|---|---|---|
| Train | `train.csv` | `biogpt_train.csv` |
| Validation | `valid.csv` | `biogpt_valid.csv` |
| Test | `test.csv` | `biogpt_test.csv` |
### Tabular Fields
- `GeneSymbol` (string): Gene symbol (e.g., AP5Z1, ZNF592)
- `ClinicalSignificance` (string): Clinical significance (e.g., Pathogenic, Likely pathogenic, Uncertain significance)
- `Assembly` (string): Genome assembly (e.g., GRCh38)
- `Chromosome` (string): Chromosome number
- `Start` (int64): Variant start position
### Instruction Fields
The `biogpt_*.csv` files are formatted for instruction tuning of biomedical language models (e.g., BioGPT), derived from the same ClinVar source data.
## Source Data
Derived from **ClinVar**, a publicly available archive of reports of the relationships among human variations and phenotypes.
## Intended Use
- Fine-tuning biomedical language models (BioGPT and similar)
- Research on genomic variant interpretation
- Classical ML on structured variant data
- Reproducible biomedical AI experiments
**Not** intended for clinical diagnosis, treatment decisions, or direct clinical use.
## Licensing
Released under the **MIT License**.
## Citation
If you use this dataset in research, please cite:
> BioGPT-ClinVar: Parameter-Efficient Fine-Tuning of a Biomedical Foundation Model.
> Research Square, 2026. DOI: 10.21203/rs.3.rs-10196893/v1
## Contact
**Sepideh Moafi**
GitHub: [AIResearcher20](https://github.com/AIResearcher20)
Hugging Face: [Sepideh2027](https://huggingface.co/Sepideh2027)