10x Xenium
Mouse bone marrow
GSM9035090
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 17123, 45482), (1, 8561, 22741), (1, 4280, 11370), (1, 2140, 5685), (1, 1070, 2842)
├── Labels
│ └── 'cell_labels': DataTree[yx] (17122, 44082), (8561, 22041), (4280, 11020), (2140, 5510), (1070, 2755)
├── Points
│ └── 'transcripts': DataFrame with shape: (16091247, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (246079, 1) (2D shapes)
│ └── 'cell_circles': GeoDataFrame shape: (246079, 2) (2D shapes)
└── Tables
└── 'table': AnnData (246079, 379)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (Images), cell_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("S4VqphBvwVp4vehs0000")
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("S4VqphBvwVp4vehs") # 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 S4VqphBvwVp4vehs0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/S4VqphBvwVp4vehs
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid S4VqphBvwVp4vehsLicense: NCBI GEO policy
Metadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- bone marrow
- Modality
- RNA
- Observations (cells)
- 246,079
- Transcripts
- 16,091,247
- Tier
- bronze
- Size
- 1.5 GB
- Sample ID
- GSM9035090
- License
- NCBI GEO policy
- Published
- Jul 14, 2025
Cite this dataset
doi.org/10.1182/blood.2025028896 ↗ BibTeX
@article{geo:GSM9035090,
doi = {10.1182/blood.2025028896},
title = {GSM9035090},
year = {2025}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB