🧬 Smulders Longevity Extracted Dataset
This dataset was extracted from the publication:
Genetics of human longevity: From variants to genes to pathways
Journal of Internal Medicine, 2023 — Smulders et al.
DOI: 10.1111/joim.13690
It contains structured gene names and SNP identifiers mentioned throughout the paper.
📄 Dataset Description
| Column | Description |
|---|---|
| type | Entry type: Gene or SNP |
| id | The gene name or SNP ID |
The gene names are uppercase identifiers, and SNPs follow the common rs format (e.g., rs429358).
🔧 Usage Instructions
Load in Python
import pandas as pd
df = pd.read_parquet("smulders_longevity_extracted.parquet")
print(df.head())
🚀 Use Cases
- Gene prioritization for longevity research
- Mapping SNPs from literature to existing aging gene databases
- Input for polygenic risk score (PRS) modeling
- Enhancing datasets like LongevityMap with literature-derived signals
📚 Citation
If you use this dataset, please cite the original paper:
Smulders, Y. M., et al. (2023). Genetics of human longevity: From variants to genes to pathways. Journal of Internal Medicine.
https://doi.org/10.1111/joim.13690
🙏 Acknowledgments
Extracted and compiled by Iris Lee for longevity research and hackathon use. ### 🧑💻 Team: MultiModalMillenials. Iris Lee (@iris8090)