Datasets:

Sepideh2027
/

Agent

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
Hugging Face: Sepideh2027