Visium
Human lymph node
GSM8500539
bronze Interactive viewer H&E diffuse large B-cell lymphoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8500539_Cap.area6_DLBCL_V2_hires_image': DataArray[cyx] (3, 1962, 2000)
│ └── 'GSM8500539_Cap.area6_DLBCL_V2_lowres_image': DataArray[cyx] (3, 589, 600)
├── Shapes
│ └── 'GSM8500539_Cap.area6_DLBCL_V2': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4992, 18085)
with coordinate systems:
▸ 'GSM8500539_Cap.area6_DLBCL_V2', with elements:
GSM8500539_Cap.area6_DLBCL_V2_hires_image (Images), GSM8500539_Cap.area6_DLBCL_V2_lowres_image (Images), GSM8500539_Cap.area6_DLBCL_V2 (Shapes)
▸ 'GSM8500539_Cap.area6_DLBCL_V2_downscaled_hires', with elements:
GSM8500539_Cap.area6_DLBCL_V2_hires_image (Images), GSM8500539_Cap.area6_DLBCL_V2 (Shapes)
▸ 'GSM8500539_Cap.area6_DLBCL_V2_downscaled_lowres', with elements:
GSM8500539_Cap.area6_DLBCL_V2_lowres_image (Images), GSM8500539_Cap.area6_DLBCL_V2 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("WylO2X32Aztw8UNu0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("WylO2X32Aztw8UNu") # stem uid: Lamin resolves it to the 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 Shell
# sddb client: download the .zarr into data/
sddb-cli download WylO2X32Aztw8UNu0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/WylO2X32Aztw8UNu
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid WylO2X32Aztw8UNuLicense: NCBI GEO policy
Part of collection
Spatial transcriptomics characterization of ecosystems in the immune tumor microenvironment of diffuse large B-cell lymphoma→ 9 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- lymph node
- Condition
- diffuse large B-cell lymphoma
- Modality
- RNA
- Observations (spots)
- 4,992
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,962 px
- mpp
- 3.146 µm/px
- Size
- 122 MB
- Sample ID
- GSM8500539
- License
- NCBI GEO policy
- Published
- Apr 29, 2026
Cite this dataset
doi.org/10.1080/2162402x.2026.2660418 ↗ BibTeX
@article{Diaz_Herrero_2026,
title = {Spatial transcriptomics unveils immune cellular ecosystems associated with patient survival in diffuse large B-cell lymphoma},
volume = {15},
ISSN = {2162-402X},
url = {http://dx.doi.org/10.1080/2162402x.2026.2660418},
DOI = {10.1080/2162402x.2026.2660418},
number = {1},
journal = {OncoImmunology},
publisher = {Informa UK Limited},
author = {Diaz-Herrero, Alba and Pelaez-Prestel, Héctor Fernando and Massenet-Regad, Lucile and Veyssiere, Maëva and Calvani, Julien and Cristinelli, Caterina and Lehmann-Che, Jacqueline and Meignin, Véronique and Thieblemont, Catherine and Blanc, Véronique and Soumelis, Vassili and Tonnerre, Pierre},
year = {2026},
month = Apr
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB