← All datasets
10x Xenium

Human breast

ffpe-human-breast-with-pre-designed-panel-1-standard__ffpe-human-breast-ilc

silver Interactive viewer breast cancer No linked publication
Human breast preview
print(sdata)
SpatialData object
├── Images
│     ├── 'morphology_focus': DataTree[cyx] (1, 41405, 48511), (1, 20702, 24255), (1, 10351, 12127), (1, 5175, 6063), (1, 2587, 3031)
│     └── 'morphology_mip': DataTree[cyx] (1, 41405, 48511), (1, 20702, 24255), (1, 10351, 12127), (1, 5175, 6063), (1, 2587, 3031)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (41405, 48511), (20702, 24255), (10351, 12127), (5175, 6063), (2587, 3031)
│     └── 'nucleus_labels': DataTree[yx] (41405, 48511), (20702, 24255), (10351, 12127), (5175, 6063), (2587, 3031)
├── Points
│     └── 'transcripts': DataFrame with shape: (43775350, 8) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (356746, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (356746, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (356746, 1) (2D shapes)
└── Tables
      └── 'table': AnnData (356746, 280)
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("lIdqctN6dzjTuvts")   # 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/lIdqctN6dzjTuvts

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid lIdqctN6dzjTuvts
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["lIdqctN6dzjTuvts0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Metadata

Technology
10x Xenium
Organism
human
Tissue
breast
Condition
breast cancer
Modality
RNA
Observations
356,746
Transcripts
43,775,350
Tier
silver
Chemistry
Xenium v1
Size
5.7 GB
Sample ID
ffpe-human-breast-with-pre-designed-panel-1-standard__ffpe-human-breast-ilc
License
CC BY 4.0
Published
Jan 22, 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