Visium
Human pancreas
GSM9051173
silver Interactive viewer H&E pancreatic ductal adenocarcinoma ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9051173_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│ ├── 'GSM9051173_hires_image': DataArray[cyx] (3, 2000, 1744)
│ └── 'GSM9051173_lowres_image': DataArray[cyx] (3, 600, 523)
├── Shapes
│ └── 'GSM9051173': GeoDataFrame shape: (4611, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4611, 18085)
with coordinate systems:
▸ 'GSM9051173', with elements:
GSM9051173_full_image (Images), GSM9051173_hires_image (Images), GSM9051173_lowres_image (Images), GSM9051173 (Shapes)
▸ 'GSM9051173_downscaled_hires', with elements:
GSM9051173_hires_image (Images), GSM9051173 (Shapes)
▸ 'GSM9051173_downscaled_lowres', with elements:
GSM9051173_lowres_image (Images), GSM9051173 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("GdkN2quGouCTy2AT0000")
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("GdkN2quGouCTy2AT") # 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 GdkN2quGouCTy2AT0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/GdkN2quGouCTy2AT
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid GdkN2quGouCTy2ATLicense: NCBI GEO policy
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- pancreas
- Condition
- pancreatic ductal adenocarcinoma
- Modality
- RNA
- Observations (spots)
- 4,611
- Tier
- silver
- Chemistry
- Visium CytAssist v2
- Resolution
- 3,000 × 3,000 px
- mpp
- 2.278 µm/px
- Size
- 113 MB
- Sample ID
- GSM9051173
- License
- NCBI GEO policy
- Published
- Mar 22, 2026
Cite this dataset
doi.org/10.1016/j.canlet.2026.218348 ↗ BibTeX
@article{Fukuda_2026,
title = {MIF-CD74 axis facilitates MDSC infiltration in the tumor microenvironment of pancreatic ductal adenocarcinoma},
volume = {645},
ISSN = {0304-3835},
url = {http://dx.doi.org/10.1016/j.canlet.2026.218348},
DOI = {10.1016/j.canlet.2026.218348},
journal = {Cancer Letters},
publisher = {Elsevier BV},
author = {Fukuda, Hironori and Arai, Kosuke and Hashimoto, Eri and Sekine, Keisuke and Arai, Yasuhito and Hiraoka, Nobuyoshi and Hirata, Aya and Yamashita, Makiko and Narumi, Kenta and Kikuchi, Ayaka and Sawai, Eri and Sawada, Yuria and Sunami, Ayana and Mizoguchi, Yukihiro and Sadahiro, Ryoichi and Aikawa, Yukiko and Henmi, Yasuko and Okumura, Genki and Sugiyama, Eri and Takahashi, Mami and Shibata, Tatsuhiro and Nishito, Yukari and Mizuno, Hideaki and Nara, Satoshi and Esaki, Minoru and Koyama, Shohei and Kitano, Shigehisa and Yoshida, Teruhiko and Ochiai, Atsushi and Tsunoda, Hiroyuki and Aoki, Kazunori},
year = {2026},
month = May,
pages = {218348}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB