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10x Xenium

Mouse heart left ventricle

GSM8595805

bronze Interactive viewer heart disorder Provisional
Mouse heart left ventricle preview
print(sdata)
SpatialData object
├── Labels
│     ├── 'cell_labels': DataTree[yx] (22660, 25268), (11330, 12634), (5665, 6317), (2832, 3158), (1416, 1579)
│     └── 'nucleus_labels': DataTree[yx] (22521, 24950), (11260, 12475), (5630, 6237), (2815, 3118), (1407, 1559)
├── Points
│     └── 'transcripts': DataFrame with shape: (8131244, 11) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (35946, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (35946, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (35495, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (35946, 475)
with coordinate systems:
    ▸ 'global', with elements:
        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("xVmrmiGLWJbZ0qzQ")   # 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/xVmrmiGLWJbZ0qzQ

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid xVmrmiGLWJbZ0qzQ
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["xVmrmiGLWJbZ0qzQ0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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Metadata

Technology
10x Xenium
Organism
mouse
Tissue
heart left ventricle
Condition
heart disorder
Modality
RNA
Observations
35,946
Transcripts
8,131,244
Tier
bronze
Size
364 MB
Sample ID
GSM8595805
License
unknown
Published
Sep 22, 2025

Cite this dataset

No linked publication found — please cite the data source: NCBI GEO ↗.

Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB