Visium
Human ovary
human-ovarian-cancer-1-standard
silver Interactive viewer H&E ovarian cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'Visium_FFPE_Human_Ovarian_Cancer_full_image': DataTree[cyx] (3, 12681, 13772), (3, 6340, 6886), (3, 3170, 3443), (3, 1585, 1721), (3, 792, 860)
│ ├── 'Visium_FFPE_Human_Ovarian_Cancer_hires_image': DataArray[cyx] (3, 1842, 2000)
│ └── 'Visium_FFPE_Human_Ovarian_Cancer_lowres_image': DataArray[cyx] (3, 553, 600)
├── Shapes
│ └── 'Visium_FFPE_Human_Ovarian_Cancer': GeoDataFrame shape: (3455, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3455, 17943)
with coordinate systems:
▸ 'Visium_FFPE_Human_Ovarian_Cancer', with elements:
Visium_FFPE_Human_Ovarian_Cancer_full_image (Images), Visium_FFPE_Human_Ovarian_Cancer_hires_image (Images), Visium_FFPE_Human_Ovarian_Cancer_lowres_image (Images), Visium_FFPE_Human_Ovarian_Cancer (Shapes)
▸ 'Visium_FFPE_Human_Ovarian_Cancer_downscaled_hires', with elements:
Visium_FFPE_Human_Ovarian_Cancer_hires_image (Images), Visium_FFPE_Human_Ovarian_Cancer (Shapes)
▸ 'Visium_FFPE_Human_Ovarian_Cancer_downscaled_lowres', with elements:
Visium_FFPE_Human_Ovarian_Cancer_lowres_image (Images), Visium_FFPE_Human_Ovarian_Cancer (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("V4PqcXdb83DmtG2k") # 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/V4PqcXdb83DmtG2k
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid V4PqcXdb83DmtG2k Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["V4PqcXdb83DmtG2k0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- Visium
- Organism
- human
- Tissue
- ovary
- Condition
- ovarian cancer
- Modality
- RNA
- Observations
- 3,455
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 20x
- Resolution
- 13,772 × 12,681 px
- mpp
- 0.586 µm/px
- Size
- 412 MB
- Sample ID
- human-ovarian-cancer-1-standard
- License
- CC BY 4.0
- Published
- Mar 28, 2022
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