Visium
Human ovary
GSM6506117
silver Interactive viewer H&E ovarian serous adenocarcinoma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM6506117_SP8_hires_image': DataArray[cyx] (3, 2000, 1961)
│ └── 'GSM6506117_SP8_lowres_image': DataArray[cyx] (3, 600, 588)
├── Shapes
│ └── 'GSM6506117_SP8': GeoDataFrame shape: (3180, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3180, 33538)
with coordinate systems:
▸ 'GSM6506117_SP8', with elements:
GSM6506117_SP8_hires_image (Images), GSM6506117_SP8_lowres_image (Images), GSM6506117_SP8 (Shapes)
▸ 'GSM6506117_SP8_downscaled_hires', with elements:
GSM6506117_SP8_hires_image (Images), GSM6506117_SP8 (Shapes)
▸ 'GSM6506117_SP8_downscaled_lowres', with elements:
GSM6506117_SP8_lowres_image (Images), GSM6506117_SP8 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("l07Pkqe3qRs3Lx6d") # 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/l07Pkqe3qRs3Lx6d
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid l07Pkqe3qRs3Lx6d Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["l07Pkqe3qRs3Lx6d0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomics reveals ovarian cancer subclones with different microenvironments→ 8 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- ovary
- Condition
- ovarian serous adenocarcinoma
- Modality
- RNA
- Observations
- 3,180
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 1,961 × 2,000 px
- mpp
- 3.479 µm/px
- Size
- 36 MB
- Sample ID
- GSM6506117
- License
- unknown
- Published
- Aug 29, 2022
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB