Visium
Human uterine cervix
human-cervical-cancer-1-standard
silver Interactive viewer H&E cervical cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'Visium_FFPE_Human_Cervical_Cancer_full_image': DataTree[cyx] (3, 12701, 13761), (3, 6350, 6880), (3, 3175, 3440), (3, 1587, 1720), (3, 793, 860)
│ ├── 'Visium_FFPE_Human_Cervical_Cancer_hires_image': DataArray[cyx] (3, 1846, 2000)
│ └── 'Visium_FFPE_Human_Cervical_Cancer_lowres_image': DataArray[cyx] (3, 554, 600)
├── Shapes
│ └── 'Visium_FFPE_Human_Cervical_Cancer': GeoDataFrame shape: (2781, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2781, 17943)
with coordinate systems:
▸ 'Visium_FFPE_Human_Cervical_Cancer', with elements:
Visium_FFPE_Human_Cervical_Cancer_full_image (Images), Visium_FFPE_Human_Cervical_Cancer_hires_image (Images), Visium_FFPE_Human_Cervical_Cancer_lowres_image (Images), Visium_FFPE_Human_Cervical_Cancer (Shapes)
▸ 'Visium_FFPE_Human_Cervical_Cancer_downscaled_hires', with elements:
Visium_FFPE_Human_Cervical_Cancer_hires_image (Images), Visium_FFPE_Human_Cervical_Cancer (Shapes)
▸ 'Visium_FFPE_Human_Cervical_Cancer_downscaled_lowres', with elements:
Visium_FFPE_Human_Cervical_Cancer_lowres_image (Images), Visium_FFPE_Human_Cervical_Cancer (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("BGDnY0tIezJ9z1LI") # 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/BGDnY0tIezJ9z1LI
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid BGDnY0tIezJ9z1LI Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["BGDnY0tIezJ9z1LI0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- Visium
- Organism
- human
- Tissue
- uterine cervix
- Condition
- cervical cancer
- Modality
- RNA
- Observations
- 2,781
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 20x
- Resolution
- 13,761 × 12,701 px
- mpp
- 0.586 µm/px
- Size
- 442 MB
- Sample ID
- human-cervical-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