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10x Xenium

Human pancreas

ffpe-human-ductal-adenocarcinoma-data-with-human-immuno-oncology-profiling-panel-1-standard

silver Interactive viewer H&E pancreatic ductal adenocarcinoma No linked publication
Human pancreas preview
print(sdata)
SpatialData object
├── Images
│     ├── 'he_image': DataTree[cyx] (3, 41014, 19068), (3, 20507, 9534), (3, 10253, 4767), (3, 5126, 2383), (3, 2563, 1191)
│     └── 'morphology_focus': DataTree[cyx] (1, 27261, 53947), (1, 13630, 26973), (1, 6815, 13486), (1, 3407, 6743), (1, 1703, 3371)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (27261, 53947), (13630, 26973), (6815, 13486), (3407, 6743), (1703, 3371)
│     └── 'nucleus_labels': DataTree[yx] (27261, 53947), (13630, 26973), (6815, 13486), (3407, 6743), (1703, 3371)
├── Points
│     └── 'transcripts': DataFrame with shape: (20734426, 11) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (235099, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (235099, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (235099, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (235099, 380)
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("ZekwKtENflBn6pVp")   # 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/ZekwKtENflBn6pVp

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ZekwKtENflBn6pVp
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["ZekwKtENflBn6pVp0001"])[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
pancreas
Condition
pancreatic ductal adenocarcinoma
Modality
RNA
Observations
235,099
Transcripts
20,734,426
Tier
silver
Chemistry
Xenium v1
Magnification
40x
Resolution
19,068 × 41,014 px
mpp
0.003 µm/px
Size
4.1 GB
Sample ID
ffpe-human-ductal-adenocarcinoma-data-with-human-immuno-oncology-profiling-panel-1-standard
License
CC BY 4.0
Published
May 14, 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