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10x Xenium

Human lung

xenium-human-lung-preview-data-1-standard__preview-human-lung-cancer-with-add-on-2-ffpe

silver Interactive viewer No linked publication
Human lung preview
print(sdata)
SpatialData object
├── Images
│     ├── 'morphology_focus': DataTree[cyx] (1, 51062, 54093), (1, 25531, 27046), (1, 12765, 13523), (1, 6382, 6761), (1, 3191, 3380)
│     └── 'morphology_mip': DataTree[cyx] (1, 51062, 54093), (1, 25531, 27046), (1, 12765, 13523), (1, 6382, 6761), (1, 3191, 3380)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (51062, 54093), (25531, 27046), (12765, 13523), (6382, 6761), (3191, 3380)
│     └── 'nucleus_labels': DataTree[yx] (51062, 54093), (25531, 27046), (12765, 13523), (6382, 6761), (3191, 3380)
├── Points
│     └── 'transcripts': DataFrame with shape: (90638705, 10) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (531165, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (531165, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (531165, 1) (2D shapes)
└── Tables
      └── 'table': AnnData (531165, 392)
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("D2mwXaCts1noLFcj")   # 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/D2mwXaCts1noLFcj

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid D2mwXaCts1noLFcj
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["D2mwXaCts1noLFcj0000"])[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
lung
Modality
RNA
Observations
531,165
Transcripts
90,638,705
Tier
silver
Chemistry
Xenium v1
Size
11 GB
Sample ID
xenium-human-lung-preview-data-1-standard__preview-human-lung-cancer-with-add-on-2-ffpe
License
CC BY 4.0
Published
May 18, 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