Shaow/humanbreast_xenium_janesick

# Human Breast Cancer Xenium · Sample 1 Rep1+Rep2

Curated, ready-to-load spatial transcriptomics dataset.

## Source

• —Paper: Janesick et al., Nat. Commun. 2023
• —Canonical download: cf.10xgenomics.com/samples/xenium/1.0.1/XeniumFFPEHumanBreastCancer_Rep{1,2}

## Scale

## Files

• —h5ad/adata_xenium_rep1.h5ad
• —h5ad/adata_xenium_rep2.h5ad
• —Sample1_replicate1/cell_feature_matrix.h5
• —Sample1_replicate1/cells.csv.gz
• —Sample1_replicate2/cell_feature_matrix.h5
• —Sample1_replicate2/cells.csv.gz

Each .h5ad follows the AnnData spec:

• —.X — gene expression matrix (cells × genes), sparse where natural
• —.obs — per-cell annotations (see "Metadata" below)
• —.obsm['spatial'] — (n_cells, 2) float32 spatial coordinates
• —(where present) .layers['count'] — raw integer counts
• —(where present) .obsm['spatial3d'] — (n_cells, 3) float32 (x, y, z=section)

## Metadata (obs columns)

rep

## Notes

Xenium FFPE Human Breast Cancer dataset, 2 technical replicates of Sample 1. Rep1: 167,780 cells × 313 genes; Rep2: 118,752 cells × 313 genes. We ship both the convenient h5ad versions and the original raw outputs (cell_feature_matrix.h5 + cells.csv.gz).

## Usage

import scanpy as sc
from huggingface_hub import snapshot_download
d = snapshot_download(repo_id='Shaow/humanbreast_xenium_janesick', repo_type='dataset',
                       allow_patterns='h5ad/*.h5ad')
adata_rep1 = sc.read_h5ad(f'{d}/h5ad/adata_xenium_rep1.h5ad')
adata_rep2 = sc.read_h5ad(f'{d}/h5ad/adata_xenium_rep2.h5ad')

## Citation

If you use this dataset, please cite the source paper above.

## License

MIT for the curation/preparation. Underlying data inherits the license of the upstream publication (typically CC-BY-4.0); please see the source paper.