Visium
Human prostate gland
GSM8558004
bronze H&E prostate cancer Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8558004_NEADT_8_hires_image': DataArray[cyx] (3, 2000, 1128)
│ └── 'GSM8558004_NEADT_8_lowres_image': DataArray[cyx] (3, 600, 339)
├── Shapes
│ └── 'GSM8558004_NEADT_8': GeoDataFrame shape: (3621, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3621, 33538)
with coordinate systems:
▸ 'GSM8558004_NEADT_8', with elements:
GSM8558004_NEADT_8_hires_image (Images), GSM8558004_NEADT_8_lowres_image (Images), GSM8558004_NEADT_8 (Shapes)
▸ 'GSM8558004_NEADT_8_downscaled_hires', with elements:
GSM8558004_NEADT_8_hires_image (Images), GSM8558004_NEADT_8 (Shapes)
▸ 'GSM8558004_NEADT_8_downscaled_lowres', with elements:
GSM8558004_NEADT_8_lowres_image (Images), GSM8558004_NEADT_8 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("lfKpiSI8AR8DgpAC") # 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/lfKpiSI8AR8DgpAC
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid lfKpiSI8AR8DgpAC Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["lfKpiSI8AR8DgpAC0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Single cell and spatial transcriptomics highlight the interaction of club-like cells with immunosuppressive myeloid cells in prostate cancer→ 52 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- prostate gland
- Condition
- prostate cancer
- Modality
- RNA
- Observations
- 3,621
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 1,128 × 2,000 px
- mpp
- 6.526 µm/px
- Size
- 35 MB
- Sample ID
- GSM8558004
- License
- unknown
- Published
- Oct 29, 2024
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB