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10x Xenium

Human pancreas

human-pancreas-preview-data-xenium-human-multi-tissue-and-cancer-panel-1-standard

silver Interactive viewer malignant pancreatic neoplasm No linked publication
Human pancreas preview
print(sdata)
SpatialData object
├── Images
│     ├── 'morphology_focus': DataTree[cyx] (1, 10345, 36936), (1, 5172, 18468), (1, 2586, 9234), (1, 1293, 4617), (1, 646, 2308)
│     └── 'morphology_mip': DataTree[cyx] (1, 10345, 36936), (1, 5172, 18468), (1, 2586, 9234), (1, 1293, 4617), (1, 646, 2308)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (10345, 36936), (5172, 18468), (2586, 9234), (1293, 4617), (646, 2308)
│     └── 'nucleus_labels': DataTree[yx] (10345, 36936), (5172, 18468), (2586, 9234), (1293, 4617), (646, 2308)
├── Points
│     └── 'transcripts': DataFrame with shape: (13956081, 10) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (103901, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (103901, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (103901, 1) (2D shapes)
└── Tables
      └── 'table': AnnData (103901, 377)
with coordinate systems:
    ▸ 'global', with elements:
        morphology_focus (Images), morphology_mip (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("lnP5VqQCyDjNfHHl")   # 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/lnP5VqQCyDjNfHHl

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid lnP5VqQCyDjNfHHl
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["lnP5VqQCyDjNfHHl0000"])[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
malignant pancreatic neoplasm
Modality
RNA
Observations
103,901
Transcripts
13,956,081
Tier
silver
Chemistry
Xenium v1
Size
1.6 GB
Sample ID
human-pancreas-preview-data-xenium-human-multi-tissue-and-cancer-panel-1-standard
License
CC BY 4.0
Published
Jul 17, 2023

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