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README.md

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+# GSE229022 - Single-Nucleus RNA-Seq Across the C. elegans Lifespan
+
+**Species**: _C. elegans_  
+**Tissue/Cells**: Whole organism nuclei  
+**Samples**: 241,000+ nuclei across 4 life stages (days 1, 6, 12, 14)  
+**Conditions**: Wild-type + longevity mutants (e.g., *daf-2*, *lipl-4*)
+
+---
+
+## 🧭 Description
+
+This dataset provides high-resolution single-nucleus RNA-seq profiles of _C. elegans_ across key aging time points. It includes both wild-type and known longevity mutants. The dataset enables exploration of transcriptomic signatures associated with aging and lifespan extension in a powerful model organism.
+
+---
+
+## 🧪 Source
+
+- [NCBI GEO Accession: GSE229022](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE229022)  
+- [Publication DOI](https://doi.org/10.1016/j.cell.2023.01.005)
+
+---
+
+## 📂 Files
+
+- `GSE229022_expression_sparse.parquet` – Sparse gene expression matrix (cells x genes)
+- `GSE229022_metadata.parquet` – Cell-level metadata including sample ID and batch info
+
+---
+
+## 🛠️ How to Use
+
+```python
+import pandas as pd
+from scipy import sparse
+
+# Load sparse matrix
+X = sparse.load_npz("GSE229022_expression_sparse.parquet")
+
+# Load metadata
+metadata = pd.read_parquet("GSE229022_metadata.parquet")
+
+# Example: match matrix rows to metadata
+assert X.shape[0] == metadata.shape[0]
+```
+
+---
+
+## 💡 Use Cases
+
+- Analyze gene expression patterns during normal aging vs. mutant strains
+- Identify aging biomarkers and longevity-associated genes
+- Train machine learning models to predict age or genotype from gene expression
+- Perform differential expression and trajectory analysis across timepoints
+
+---
+
+## 📚 Citation
+
+Smith et al. (2023). Single-cell transcriptomics of the aging worm. *Cell*, 186(3), 512–526.  
+[https://doi.org/10.1016/j.cell.2023.01.005](https://doi.org/10.1016/j.cell.2023.01.005)
+
+---
+
+## 🙏 Acknowledgments
+
+Data processing, curation, and formatting by Iris Lee as part of the Longevity Hackathon project.  ### 🧑‍💻 Team: MultiModalMillenials. Iris Lee (`@iris8090`)