10x Xenium
Human rectum
GSM9345493
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20502, 17129), (1, 10251, 8564), (1, 5125, 4282), (1, 2562, 2141), (1, 1281, 1070)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (17182, 16887), (8591, 8443), (4295, 4221), (2147, 2110), (1073, 1055)
│ └── 'nucleus_labels': DataTree[yx] (17137, 16840), (8568, 8420), (4284, 4210), (2142, 2105), (1071, 1052)
├── Points
│ └── 'transcripts': DataFrame with shape: (1864808, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (32120, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (32120, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (32120, 2) (2D shapes)
└── Tables
└── 'table': AnnData (32120, 377)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (Images), cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("MQvsocp0LoBH7JUC") # 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 Load from the CLI
# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/MQvsocp0LoBH7JUC
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid MQvsocp0LoBH7JUC Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["MQvsocp0LoBH7JUC0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- rectum
- Modality
- RNA
- Observations
- 32,120
- Transcripts
- 1,864,808
- Tier
- bronze
- Size
- 319 MB
- Sample ID
- GSM9345493
- License
- unknown
- Published
- Mar 13, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB