Visium HD
Glycine max multicellular organism
visium-hd-three-prime-soybean
H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'Visium_HD_3prime_Soybean_full_image': DataTree[cyx] (3, 30402, 37496), (3, 15201, 18748), (3, 7600, 9374), (3, 3800, 4687), (3, 1900, 2343)
│ ├── 'Visium_HD_3prime_Soybean_hires_image': DataArray[cyx] (3, 4865, 6000)
│ └── 'Visium_HD_3prime_Soybean_lowres_image': DataArray[cyx] (3, 487, 600)
├── Shapes
│ ├── 'Visium_HD_3prime_Soybean_square_002um': GeoDataFrame shape: (8403280, 1) (2D shapes)
│ ├── 'Visium_HD_3prime_Soybean_square_008um': GeoDataFrame shape: (525538, 1) (2D shapes)
│ ├── 'Visium_HD_3prime_Soybean_square_016um': GeoDataFrame shape: (131623, 1) (2D shapes)
│ └── 'Visium_HD_3prime_Soybean_square_016um_for_vitessce': GeoDataFrame shape: (131623, 2) (2D shapes)
└── Tables
├── 'square_002um': AnnData (8403280, 47095)
├── 'square_008um': AnnData (525538, 47095)
└── 'square_016um': AnnData (131623, 47095)
with coordinate systems:
▸ 'Visium_HD_3prime_Soybean', with elements:
Visium_HD_3prime_Soybean_full_image (Images), Visium_HD_3prime_Soybean_hires_image (Images), Visium_HD_3prime_Soybean_lowres_image (Images), Visium_HD_3prime_Soybean_square_002um (Shapes), Visium_HD_3prime_Soybean_square_008um (Shapes), Visium_HD_3prime_Soybean_square_016um (Shapes), Visium_HD_3prime_Soybean_square_016um_for_vitessce (Shapes)
▸ 'Visium_HD_3prime_Soybean_downscaled_hires', with elements:
Visium_HD_3prime_Soybean_hires_image (Images), Visium_HD_3prime_Soybean_square_002um (Shapes), Visium_HD_3prime_Soybean_square_008um (Shapes), Visium_HD_3prime_Soybean_square_016um (Shapes), Visium_HD_3prime_Soybean_square_016um_for_vitessce (Shapes)
▸ 'Visium_HD_3prime_Soybean_downscaled_lowres', with elements:
Visium_HD_3prime_Soybean_lowres_image (Images), Visium_HD_3prime_Soybean_square_002um (Shapes), Visium_HD_3prime_Soybean_square_008um (Shapes), Visium_HD_3prime_Soybean_square_016um (Shapes), Visium_HD_3prime_Soybean_square_016um_for_vitessce (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("KeCeonBmHxHsfErT") # 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/KeCeonBmHxHsfErT
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid KeCeonBmHxHsfErT Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["KeCeonBmHxHsfErT0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- Visium HD
- Organism
- glycine max
- Tissue
- multicellular organism
- Modality
- RNA
- Chemistry
- Visium HD v1
- Staining
- H&E
- Magnification
- 40x
- Resolution
- 37,496 × 30,402 px
- mpp
- 0.274 µm/px
- Size
- 3.9 GB
- Sample ID
- visium-hd-three-prime-soybean
- License
- CC BY 4.0
- Published
- Oct 13, 2025
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