10x Xenium
Human lung
ffpe-human-lung-cancer-data-with-human-immuno-oncology-profiling-panel-and-custom-add-on-1-standard
silver Interactive viewer H&E lung cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 39361, 15513), (3, 19680, 7756), (3, 9840, 3878), (3, 4920, 1939), (3, 2460, 969)
│ └── 'morphology_focus': DataTree[cyx] (1, 20535, 51103), (1, 10267, 25551), (1, 5133, 12775), (1, 2566, 6387), (1, 1283, 3193)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (20535, 51103), (10267, 25551), (5133, 12775), (2566, 6387), (1283, 3193)
│ └── 'nucleus_labels': DataTree[yx] (20535, 51103), (10267, 25551), (5133, 12775), (2566, 6387), (1283, 3193)
├── Points
│ └── 'transcripts': DataFrame with shape: (40257199, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (161000, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (161000, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (161000, 2) (2D shapes)
└── Tables
└── 'table': AnnData (161000, 480)
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("qS0XPrscQdzdOedo") # 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/qS0XPrscQdzdOedo
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid qS0XPrscQdzdOedo Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["qS0XPrscQdzdOedo0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- lung
- Condition
- lung cancer
- Modality
- RNA
- Observations
- 161,000
- Transcripts
- 40,257,199
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 15,513 × 39,361 px
- mpp
- 0.001 µm/px
- Size
- 4.1 GB
- Sample ID
- ffpe-human-lung-cancer-data-with-human-immuno-oncology-profiling-panel-and-custom-add-on-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