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10x Xenium

Human skin of body

xenium-prime-ffpe-human-skin

silver Interactive viewer H&E melanoma No linked publication
Human skin of body preview
print(sdata)
SpatialData object
├── Images
│     ├── 'he_image': DataTree[cyx] (3, 35787, 18669), (3, 17893, 9334), (3, 8946, 4667), (3, 4473, 2333), (3, 2236, 1166)
│     └── 'morphology_focus': DataTree[cyx] (4, 20294, 42748), (4, 10147, 21374), (4, 5073, 10687), (4, 2536, 5343), (4, 1268, 2671)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (20294, 42748), (10147, 21374), (5073, 10687), (2536, 5343), (1268, 2671)
│     └── 'nucleus_labels': DataTree[yx] (20294, 42748), (10147, 21374), (5073, 10687), (2536, 5343), (1268, 2671)
├── Points
│     └── 'transcripts': DataFrame with shape: (74011892, 13) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (112551, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (112551, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (111719, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (112551, 5006)
with coordinate systems:
    ▸ 'global', with elements:
        he_image (Images), morphology_focus (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("2n9BpkK6JkPPHvba")   # 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/2n9BpkK6JkPPHvba

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 2n9BpkK6JkPPHvba
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["2n9BpkK6JkPPHvba0002"])[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
human
Tissue
skin of body
Condition
melanoma
Modality
RNA
Observations
112,551
Transcripts
74,011,892
Tier
silver
Chemistry
Xenium Prime
Magnification
40x
Resolution
18,669 × 35,787 px
mpp
0.013 µm/px
Size
5.9 GB
Sample ID
xenium-prime-ffpe-human-skin
License
CC BY 4.0
Published
Jul 31, 2024

Cite this dataset

No linked publication found — please cite the data source: 10x Genomics ↗.

Source: 10x Genomics ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB