Visium
Mouse kidney
NCBI598
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'NCBI598_full_image': DataTree[cyx] (3, 11297, 10468), (3, 5648, 5234), (3, 2824, 2617), (3, 1412, 1308)
├── Shapes
│ └── 'NCBI598_spots': GeoDataFrame shape: (1835, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1835, 31053)
with coordinate systems:
▸ 'global', with elements:
NCBI598_full_image (Images), NCBI598_spots (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("1EWiyjxa6QPuxqh2") # 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/1EWiyjxa6QPuxqh2
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 1EWiyjxa6QPuxqh2 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["1EWiyjxa6QPuxqh20000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Integration of spatial and single cell transcriptomics localizes epithelial-immune cross-talk in kidney injury→ 3 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- kidney
- Modality
- RNA
- Observations
- 1,835
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 10,468 × 11,297 px
- mpp
- 0.757 µm/px
- Size
- 242 MB
- Sample ID
- NCBI598
- License
- CC BY-NC-SA 4.0 NonCommercial
- Published
- Jun 1, 2021
Cite this dataset
No linked publication found — please cite the data source.
License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB