Visium
Human pancreas
GSM8915497
bronze Interactive viewer H&E pancreatic ductal adenocarcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8915497_PDAC04_hires_image': DataArray[cyx] (3, 1215, 2000)
│ └── 'GSM8915497_PDAC04_lowres_image': DataArray[cyx] (3, 365, 600)
├── Shapes
│ └── 'GSM8915497_PDAC04': GeoDataFrame shape: (1142, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1142, 17943)
with coordinate systems:
▸ 'GSM8915497_PDAC04', with elements:
GSM8915497_PDAC04_hires_image (Images), GSM8915497_PDAC04_lowres_image (Images), GSM8915497_PDAC04 (Shapes)
▸ 'GSM8915497_PDAC04_downscaled_hires', with elements:
GSM8915497_PDAC04_hires_image (Images), GSM8915497_PDAC04 (Shapes)
▸ 'GSM8915497_PDAC04_downscaled_lowres', with elements:
GSM8915497_PDAC04_lowres_image (Images), GSM8915497_PDAC04 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("qEP9pd4LlyKeufe20000")
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("qEP9pd4LlyKeufe2") # 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 qEP9pd4LlyKeufe20000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/qEP9pd4LlyKeufe2
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid qEP9pd4LlyKeufe2License: NCBI GEO policy
Part of collection
Spatial Proteomics and Transcriptomics Reveal Early Immune Cell Organization in Pancreatic Intraepithelial Neoplasia→ 13 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- pancreas
- Condition
- pancreatic ductal adenocarcinoma
- Modality
- RNA
- Observations (spots)
- 1,142
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,215 px
- mpp
- 5.660 µm/px
- Size
- 2.6 MB
- Sample ID
- GSM8915497
- License
- NCBI GEO policy
- Published
- Jun 16, 2025
Cite this dataset
doi.org/10.1172/jci.insight.191595 ↗ BibTeX
@article{Lyman_2025,
title = {Spatial proteomics and transcriptomics reveal early immune cell organization in pancreatic intraepithelial neoplasia},
volume = {10},
ISSN = {2379-3708},
url = {http://dx.doi.org/10.1172/jci.insight.191595},
DOI = {10.1172/jci.insight.191595},
number = {15},
journal = {JCI Insight},
publisher = {American Society for Clinical Investigation},
author = {Lyman, Melissa R. and Mitchell, Jacob T. and Raghavan, Sidharth and Kagohara, Luciane T. and Huff, Amanda L. and Haldar, Saurav D. and Shin, Sarah M. and Guinn, Samantha and Barrett, Benjamin and Longway, Gabriella and Hernandez, Alexei and Coyne, Erin M. and Yuan, Xuan and Andaloori, Lalitya and Lai, Jiaying and Liu, Yun Zhou and Karchin, Rachel and Gupta, Anuj and Kiemen, Ashley L. and Forjaz, André and Wirtz, Denis and Wu, Pei-Hsun and Deshpande, Atul and Lee, Jae W. and Armstrong, Todd D. and Azad, Nilofer S. and Zimmerman, Jacquelyn W. and Wood, Laura D. and Anders, Robert A. and Thompson, Elizabeth D. and Jaffee, Elizabeth M. and Fertig, Elana J. and Ho, Won Jin and Zaidi, Neeha},
year = {2025},
month = June
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB