10x Xenium
Human pancreas
GSM9372003
bronze Interactive viewer pancreatic adenocarcinoma Provisional

print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataArray[cyx] (1, 30683, 48344)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (30677, 47178), (15338, 23589), (7669, 11794), (3834, 5897), (1917, 2948)
│ └── 'nucleus_labels': DataTree[yx] (30658, 47138), (15329, 23569), (7664, 11784), (3832, 5892), (1916, 2946)
├── Points
│ └── 'transcripts': DataFrame with shape: (58994585, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (133272, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (133272, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (133126, 2) (2D shapes)
└── Tables
└── 'table': AnnData (133272, 5101)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (Images), cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("n9ZxbmGR8CCbUhgN0000")
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("n9ZxbmGR8CCbUhgN") # 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 n9ZxbmGR8CCbUhgN0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/n9ZxbmGR8CCbUhgN
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid n9ZxbmGR8CCbUhgN License: NCBI GEO policy
Part of collection
Neoadjuvant modified FOLFIRINOX plus nivolumab in borderline-resectable pancreatic ductal adenocarcinoma: a pilot phase 1 trial→ 6 datasets · publication
Metadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- pancreas
- Condition
- pancreatic adenocarcinoma
- Modality
- RNA
- Observations (cells)
- 133,272
- Transcripts
- 58,994,585
- Tier
- bronze
- Size
- 2.7 GB
- Sample ID
- GSM9372003
- License
- NCBI GEO policy
- Published
- Dec 15, 2025
Cite this dataset
doi.org/10.1038/s41467-026-68976-2 ↗ BibTeX
@article{Wainberg_2026,
title = {Neoadjuvant modified FOLFIRINOX plus nivolumab in borderline-resectable pancreatic ductal adenocarcinoma: a pilot phase 1 trial},
volume = {17},
ISSN = {2041-1723},
url = {http://dx.doi.org/10.1038/s41467-026-68976-2},
DOI = {10.1038/s41467-026-68976-2},
number = {1},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
author = {Wainberg, Zev A. and Link, Jason M. and Premji, Alykhan and Zheng, Serena and Srienc, Michael and Hammons, McKensie and Kim, Shineui E. and Li, Luyi and Liu, Zeyu and Tsvetkova, Olga and Abt, Evan R. and Rosen, Lee and Kim, Stephen and King, Jonathan and Hines, O. Joe and Girgis, Mark and Sadeghi, Saeed and Olevsky, Olga and Wong, Deborah and Yonemoto, Lisa and Siney, Ann Marie and Kelly, Kim and Kivork, Christine and Tseng, Chi-Hong and Radu, Caius G. and Dawson, David W. and Donahue, Timothy R.},
year = {2026},
month = Jan
} Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB