10x Xenium

Mouse heart left ventricle

GSM8595803

bronze Interactive viewer Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Labels
│     ├── 'cell_labels': DataTree[yx] (16512, 13203), (8256, 6601), (4128, 3300), (2064, 1650), (1032, 825)
│     └── 'nucleus_labels': DataTree[yx] (15931, 12571), (7965, 6285), (3982, 3142), (1991, 1571), (995, 785)
├── Points
│     └── 'transcripts': DataFrame with shape: (2177306, 11) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (14191, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (14191, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (13983, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (14191, 475)
with coordinate systems:
    ▸ 'global', with elements:
        cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("wzA1pWwR7pe1Zp0m0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

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("wzA1pWwR7pe1Zp0m")   # 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

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download wzA1pWwR7pe1Zp0m0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/wzA1pWwR7pe1Zp0m

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid wzA1pWwR7pe1Zp0m

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Part of collection

Spatiotemporal dynamics of the cardioimmune niche during lesion repair [spatial]→

7 datasets · comparison

Metadata

Technology: 10x Xenium
Organism: mouse
Tissue: heart left ventricle
Modality: RNA
Observations (cells): 14,191
Transcripts: 2,177,306
Tier: bronze
Size: 111 MB
Sample ID: GSM8595803
License: NCBI GEO policy
Published: Sep 22, 2025

Cite this dataset

doi.org/10.1038/s44161-025-00739-6 ↗

BibTeX

@article{geo:GSM8595803,
  doi = {10.1038/s44161-025-00739-6},
  title = {GSM8595803},
  year = {2025}
}

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