Visium
Mouse kidney
GSM8659310
silver Interactive viewer H&E malaria No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1_hires_image': DataArray[cyx] (3, 2000, 1972)
│ └── 'GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1_lowres_image': DataArray[cyx] (3, 600, 592)
├── Shapes
│ └── 'GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1': GeoDataFrame shape: (3391, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3391, 38514)
with coordinate systems:
▸ 'GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1', with elements:
GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1_hires_image (Images), GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1_lowres_image (Images), GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1 (Shapes)
▸ 'GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1_downscaled_hires', with elements:
GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1_hires_image (Images), GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1 (Shapes)
▸ 'GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1_downscaled_lowres', with elements:
GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1_lowres_image (Images), GSM8659310_INF_H311_F_Day6_Kidney_GEX47_D1 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("kFkwJSOM5HovKIGn") # 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/kFkwJSOM5HovKIGn
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid kFkwJSOM5HovKIGn Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["kFkwJSOM5HovKIGn0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection→ 150 datasets · time course
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- kidney
- Condition
- malaria
- Modality
- RNA
- Observations
- 3,391
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 1,972 × 2,000 px
- mpp
- 3.414 µm/px
- Size
- 48 MB
- Sample ID
- GSM8659310
- License
- unknown
- Published
- Aug 13, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB