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Xenium

Human skin of back

Xenium spatial transcriptomics datasets from upper back skin of three healthy volunteers under UV-irradiated/non-disinfected, UV-irradiated/disinfected, non-irradiated/non-disinfected, and non-irradiated/disinfected conditions (0052858_003_no_uv_no_micro)

bronze Under review Interactive viewer Provisional
Xenium
print(sdata) 
SpatialData object
├── Images
│     └── 'morphology_focus': DataTree[cyx] (4, 23906, 22817), (4, 11953, 11408), (4, 5976, 5704), (4, 2988, 2852), (4, 1494, 1426)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (23906, 22817), (11953, 11408), (5976, 5704), (2988, 2852), (1494, 1426)
│     └── 'nucleus_labels': DataTree[yx] (23906, 22817), (11953, 11408), (5976, 5704), (2988, 2852), (1494, 1426)
├── Points
│     └── 'transcripts': DataFrame with shape: (2526340, 13) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (10187, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (10187, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (10340, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (10187, 475)
with coordinate systems:
    ▸ 'global', with elements:
        morphology_focus (Images), 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("3YomQvV7XT2OOUiG0000")
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("3YomQvV7XT2OOUiG")   # 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 3YomQvV7XT2OOUiG0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/3YomQvV7XT2OOUiG

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 3YomQvV7XT2OOUiG
Install (Python 3.12+) Docs →

License: CC BY 4.0

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Part of collection
figshare-32190978→
16 datasets · publication

Metadata

Technology
Xenium
Vendor
10x Genomics
Organism
human
Tissue
skin of back
Modality
RNA
Observations (cells)
10,187
Transcripts
2,526,340
Target genes
475
Tier
bronze
Size
1.5 GB
Sample ID
32190978:0052858_003_no_uv_no_micro
License
CC BY 4.0
Published
May 7, 2026
Review
condition (UV / disinfection) from the bundle name

Cite this dataset

doi.org/10.48420/32190978.v1 ↗
BibTeX 
@article{figshare:32190978,
  doi = {10.48420/32190978.v1},
  title = {Xenium spatial transcriptomics datasets from upper back skin of three healthy volunteers under UV-irradiated/non-disinfected, UV-irradiated/disinfected, non-irradiated/non-disinfected, and non-irradiated/disinfected conditions (0052858_002_no_uv_no_micro)},
  year = {2026}
}

Source: figshare.manchester.ac.uk ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB