spatial-ATAC-seq
Human thymus
GSM8831039
bronze Interactive viewer H&E ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ └── 'tissue_hires': DataArray[cyx] (3, 2430, 2430)
├── Shapes
│ ├── 'epi_spots': GeoDataFrame shape: (48400, 1) (2D shapes)
│ └── 'epi_spots_for_vitessce': GeoDataFrame shape: (48400, 2) (2D shapes)
└── Tables
└── 'table': AnnData (48400, 617665)
with coordinate systems:
▸ 'global', with elements:
tissue_hires (Images), epi_spots (Shapes), epi_spots_for_vitessce (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("YQvZHJcsvA8HXfrg0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("YQvZHJcsvA8HXfrg") # stem uid: Lamin resolves it to the latest version
sdata = artifact.load() # cache, then load into memory
group = artifact.open() # stream without downloading
path = artifact.cache() # sync into the local cache, returns the path Shell
# sddb client: download the .zarr into data/
sddb-cli download YQvZHJcsvA8HXfrg0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/YQvZHJcsvA8HXfrg
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid YQvZHJcsvA8HXfrgLicense: NCBI GEO policy
Metadata
- Technology
- spatial-ATAC-seq
- Vendor
- Academic
- Organism
- human
- Tissue
- thymus
- Modality
- Epigenomics
- Tier
- bronze
- Resolution
- 2,430 × 2,430 px
- mpp
- 10.000 µm/px
- Size
- 2.3 GB
- Sample ID
- GSM8831039
- License
- NCBI GEO policy
- Published
- May 19, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB