| # 🧬 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](https://doi.org/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 | |
| ```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](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`) | |