Visium
Human brain
GSM7759705
bronze Interactive viewer H&E brain glioma Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'GSM7759705_Oligodendroglioma8_hires_image': DataArray[cyx] (3, 1944, 2000)
├── Shapes
│ └── 'GSM7759705_Oligodendroglioma8': GeoDataFrame shape: (3567, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3567, 36601)
with coordinate systems:
▸ 'GSM7759705_Oligodendroglioma8', with elements:
GSM7759705_Oligodendroglioma8_hires_image (Images), GSM7759705_Oligodendroglioma8 (Shapes)
▸ 'GSM7759705_Oligodendroglioma8_downscaled_hires', with elements:
GSM7759705_Oligodendroglioma8_hires_image (Images), GSM7759705_Oligodendroglioma8 (Shapes)
▸ 'GSM7759705_Oligodendroglioma8_downscaled_lowres', with elements:
GSM7759705_Oligodendroglioma8 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("iuO0aTjrVSSWy7cB0000")
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("iuO0aTjrVSSWy7cB") # 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 iuO0aTjrVSSWy7cB0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/iuO0aTjrVSSWy7cB
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid iuO0aTjrVSSWy7cBLicense: NCBI GEO policy
Part of collection
Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas→ 17 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- brain
- Condition
- brain glioma
- Modality
- RNA
- Observations (spots)
- 3,567
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,944 px
- mpp
- 3.416 µm/px
- Size
- 26.5 MB
- Sample ID
- GSM7759705
- License
- NCBI GEO policy
- Published
- Jan 2, 2025
Cite this dataset
doi.org/10.1038/s41467-025-59805-z ↗ BibTeX
@article{Webb_2025,
title = {Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas},
volume = {16},
ISSN = {2041-1723},
url = {http://dx.doi.org/10.1038/s41467-025-59805-z},
DOI = {10.1038/s41467-025-59805-z},
number = {1},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
author = {Webb, Michelle G. and Chow, Frances and McCullough, Carmel G. and Zhang, Bohan and Lee, John J. Y. and Bassiouni, Rania and Garrett, Norman E. and Hurth, Kyle and Carpten, John D. and Zada, Gabriel and Craig, David W.},
year = {2025},
month = June
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB