Shaow/mouseembryo_seqfish_stereoseq_pair

# Mouse Embryo · paired seqFISH + Stereo-seq slice

Curated, ready-to-load spatial transcriptomics dataset.

## Source

• —Paper: Lohoff et al., Nat. Biotechnol. 2022 (seqFISH); Chen et al., Cell 2022 MOSTA (Stereo-seq)
• —Canonical download: seqFISH: SpatialMouseAtlas; Stereo-seq: MOSTA STDS0000058 (E9.5_E1S1)

## Scale

## Files

• —h5ad/adata_seqfish.h5ad
• —h5ad/adata_stereoseq.h5ad

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)

embryo (seqFISH), celltype_mapped_refined (seqFISH), annotation (Stereo-seq)

## Notes

Cross-platform pair from two studies: seqFISH embryo2 (14,185 cells × 351 genes) + MOSTA E9.5_E1S1 Stereo-seq (5,913 spots × 25,568 genes). 347 genes are shared between the platforms. Use as a benchmark for cross-technology spatial integration.

## Usage

import scanpy as sc
from huggingface_hub import snapshot_download
d = snapshot_download(repo_id='Shaow/mouseembryo_seqfish_stereoseq_pair', repo_type='dataset')
adata_seqfish = sc.read_h5ad(f'{d}/h5ad/adata_seqfish.h5ad')
adata_stereoseq = sc.read_h5ad(f'{d}/h5ad/adata_stereoseq.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.