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license: other
tags:
- single-cell
- rna-seq
- scRNA-seq
- h5ad
- anndata
- genomics
- benchmark
- shape-analysis
size_categories:
- 1M<n<10M
task_categories:
- tabular-classification
- tabular-regression
pretty_name: scShapeBench
---
# scShapeBench
A benchmark dataset for single-cell shape analysis, containing **2,547,517 cells** across **105 real-world single-cell RNA-seq datasets** in AnnData (`.h5ad`) format.
## Dataset Summary
scShapeBench is a curated collection of real-world single-cell gene expression datasets assembled for benchmarking computational methods in single-cell shape analysis. Each dataset is stored as an individual AnnData file with precomputed PCA embeddings and Leiden clustering.
- **Total cells:** 2,547,517
- **Total datasets:** 105
- **Total size:** ~116 GB
- **Format:** AnnData (.h5ad)
- **Data type:** Real-world (synthetic data to be added in a future release)
## Dataset Structure
```
scShapeBench/
├── data/
│ ├── SCD-0001.h5ad
│ ├── SCD-0002.h5ad
│ ├── ...
│ └── SCD-0112.h5ad
├── cell_metadata.csv # Combined cell-level metadata (2.5M rows)
├── gene_metadata.csv # Combined gene-level metadata
├── dataset_index.csv # Per-file summary: dimensions, size
├── croissant.json # Croissant 1.1 metadata
└── README.md
```
### File Naming
Files are named `SCD-XXXX.h5ad` where XXXX is a zero-padded index. The numbering is not contiguous (e.g., SCD-0031, SCD-0032, SCD-0034–0036 are absent).
### Per-File Contents
Each `.h5ad` file contains:
| Component | Description |
|-----------|-------------|
| `X` | Gene expression matrix (cells × genes), log-normalized |
| `obs` | Cell metadata: `n_genes`, `leiden` (cluster assignment) |
| `var` | Gene metadata: `gene_ids`, `feature_types`, `genome`, `n_cells`, `highly_variable`, etc. |
| `obsm['X_pca']` | Precomputed PCA embeddings |
| `uns` | Clustering and HVG parameters |
### Dataset Index
The `dataset_index.csv` file provides per-file summary statistics:
| Column | Description |
|--------|-------------|
| `file_id` | Dataset identifier (e.g., SCD-0001) |
| `filename` | Filename |
| `n_cells` | Number of cells |
| `n_genes` | Number of genes |
| `file_size_bytes` | File size in bytes |
Dataset sizes range from 1,163 cells (SCD-0006) to 434,340 cells (SCD-0037).
## Usage
```python
import scanpy as sc
import pandas as pd
# Load a single dataset
adata = sc.read_h5ad("data/SCD-0001.h5ad")
print(adata)
# Browse available datasets
index = pd.read_csv("dataset_index.csv")
print(index.sort_values("n_cells", ascending=False).head())
# Load cell metadata across all datasets
cell_meta = pd.read_csv("cell_metadata.csv")
print(cell_meta.groupby("file_id").size())
```
## Croissant Metadata
This dataset includes a `croissant.json` file conforming to the [Croissant 1.1](https://docs.mlcommons.org/croissant/) metadata standard. This enables programmatic discovery and loading of dataset metadata through compatible tools.
## Citation
<!-- Add citation information here when available -->
## License
License to be determined.
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