Visium
Human bone marrow
GSM8329295
bronze Interactive viewer H&E plasma cell myeloma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8329295_hMM3_hires_image': DataArray[cyx] (3, 2000, 2000)
│ └── 'GSM8329295_hMM3_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│ └── 'GSM8329295_hMM3': GeoDataFrame shape: (977, 2) (2D shapes)
└── Tables
└── 'table': AnnData (977, 18085)
with coordinate systems:
▸ 'GSM8329295_hMM3', with elements:
GSM8329295_hMM3_hires_image (Images), GSM8329295_hMM3_lowres_image (Images), GSM8329295_hMM3 (Shapes)
▸ 'GSM8329295_hMM3_downscaled_hires', with elements:
GSM8329295_hMM3_hires_image (Images), GSM8329295_hMM3 (Shapes)
▸ 'GSM8329295_hMM3_downscaled_lowres', with elements:
GSM8329295_hMM3_lowres_image (Images), GSM8329295_hMM3 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("8b3AgwK3sL8xjhWw") # 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/8b3AgwK3sL8xjhWw
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 8b3AgwK3sL8xjhWw Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["8b3AgwK3sL8xjhWw0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomics unveils novel potential disease mechanisms associated with the microenvironment in Multiple Myeloma→ 14 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- bone marrow
- Condition
- plasma cell myeloma
- Modality
- RNA
- Observations
- 977
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 2,000 × 2,000 px
- mpp
- 5.462 µm/px
- Size
- 13 MB
- Sample ID
- GSM8329295
- License
- unknown
- Published
- Jun 9, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB