10x Xenium
Human ovary
ffpe-human-ovarian-cancer-data-with-human-immuno-oncology-profiling-panel-and-custom-add-on-1-standard
silver Interactive viewer H&E ovarian cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 37330, 21806), (3, 18665, 10903), (3, 9332, 5451), (3, 4666, 2725), (3, 2333, 1362)
│ └── 'morphology_focus': DataTree[cyx] (1, 27241, 45450), (1, 13620, 22725), (1, 6810, 11362), (1, 3405, 5681), (1, 1702, 2840)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (27241, 45450), (13620, 22725), (6810, 11362), (3405, 5681), (1702, 2840)
│ └── 'nucleus_labels': DataTree[yx] (27241, 45450), (13620, 22725), (6810, 11362), (3405, 5681), (1702, 2840)
├── Points
│ └── 'transcripts': DataFrame with shape: (19146340, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (247636, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (247636, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (247636, 2) (2D shapes)
└── Tables
└── 'table': AnnData (247636, 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("BYn8secW0hYoZZmt") # 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/BYn8secW0hYoZZmt
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid BYn8secW0hYoZZmt Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["BYn8secW0hYoZZmt0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- ovary
- Condition
- ovarian cancer
- Modality
- RNA
- Observations
- 247,636
- Transcripts
- 19,146,340
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 21,806 × 37,330 px
- mpp
- 0.001 µm/px
- Size
- 3.9 GB
- Sample ID
- ffpe-human-ovarian-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