Visium
Human bone tissue
GSM9030939
bronze Interactive viewer H&E osteosarcoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9030939_PatientB_hires_image': DataArray[cyx] (3, 2000, 1955)
│ └── 'GSM9030939_PatientB_lowres_image': DataArray[cyx] (3, 600, 587)
├── Shapes
│ └── 'GSM9030939_PatientB': GeoDataFrame shape: (3020, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3020, 17943)
with coordinate systems:
▸ 'GSM9030939_PatientB', with elements:
GSM9030939_PatientB_hires_image (Images), GSM9030939_PatientB_lowres_image (Images), GSM9030939_PatientB (Shapes)
▸ 'GSM9030939_PatientB_downscaled_hires', with elements:
GSM9030939_PatientB_hires_image (Images), GSM9030939_PatientB (Shapes)
▸ 'GSM9030939_PatientB_downscaled_lowres', with elements:
GSM9030939_PatientB_lowres_image (Images), GSM9030939_PatientB (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("lPbcDoDKYRZnsc5Y0000")
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("lPbcDoDKYRZnsc5Y") # 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 lPbcDoDKYRZnsc5Y0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/lPbcDoDKYRZnsc5Y
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid lPbcDoDKYRZnsc5YLicense: NCBI GEO policy
Part of collection
Immunosuppressive tumor microenvironment of osteosarcoma [Spatial transcriptomics]→ 2 datasets · replicates
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- bone tissue
- Condition
- osteosarcoma
- Modality
- RNA
- Observations (spots)
- 3,020
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,955 × 2,000 px
- mpp
- 3.449 µm/px
- Size
- 29.2 MB
- Sample ID
- GSM9030939
- License
- NCBI GEO policy
- Published
- Jul 15, 2025
Cite this dataset
doi.org/10.3390/cancers17132117 ↗ BibTeX
@article{Taylor_2025,
title = {Immunosuppressive Tumor Microenvironment of Osteosarcoma},
volume = {17},
ISSN = {2072-6694},
url = {http://dx.doi.org/10.3390/cancers17132117},
DOI = {10.3390/cancers17132117},
number = {13},
journal = {Cancers},
publisher = {MDPI AG},
author = {Taylor, Aaron Michael and Sheng, Jianting and Ng, Patrick Kwok Shing and Harder, Jeffrey M. and Kumar, Parveen and Ahn, Ju Young and Cao, Yuliang and Dzis, Alissa M. and Jillette, Nathaniel L. and Goodspeed, Andrew and Bodlak, Avery and Wu, Qian and Isakoff, Michael S. and George, Joshy and Grassmann, Jessica D. S. and Luo, Diane and Flynn, William F. and Courtois, Elise T. and Robson, Paul and Hayashi, Masanori and Paolillo, Alini Trujillo and Petrilli, Antonio Sergio and Caminada de Toledo, Silvia Regina and Balarezo, Fabiola Sara and Lindsay, Adam D. and Hoang, Bang and Wong, Stephen T. C. and Lau, Ching C.},
year = {2025},
month = June,
pages = {2117}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB