Xenium
Human pancreas
PanIN and CAF Transitions in Pancreatic Carcinogenesis Revealed with Spatial Data Integration [Xenium]: PanIN1144 (Pancreatic Intraductal Neoplasm, human, pancreas)
silver Interactive viewer ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'morphology_focus': DataTree[cyx] (1, 30783, 48387), (1, 15391, 24193), (1, 7695, 12096), (1, 3847, 6048), (1, 1923, 3024)
│ └── 'morphology_mip': DataTree[cyx] (1, 30783, 48387), (1, 15391, 24193), (1, 7695, 12096), (1, 3847, 6048), (1, 1923, 3024)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (30783, 48387), (15391, 24193), (7695, 12096), (3847, 6048), (1923, 3024)
│ └── 'nucleus_labels': DataTree[yx] (30783, 48387), (15391, 24193), (7695, 12096), (3847, 6048), (1923, 3024)
├── Points
│ └── 'transcripts': DataFrame with shape: (23676177, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (141106, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (141106, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (141106, 1) (2D shapes)
└── Tables
└── 'table': AnnData (141106, 380)
with coordinate systems:
▸ 'global', with elements:
morphology_focus (Images), 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("Z7MYOQsZbCXqAn0D0000")
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("Z7MYOQsZbCXqAn0D") # 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 Z7MYOQsZbCXqAn0D0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/Z7MYOQsZbCXqAn0D
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Z7MYOQsZbCXqAn0DLicense: NCBI GEO policy
Metadata
- Technology
- Xenium
- Vendor
- 10x Genomics
- Organism
- human
- Tissue
- pancreas
- Modality
- RNA
- Observations (cells)
- 141,106
- Transcripts
- 23,676,177
- Target genes
- 380
- Tier
- silver
- Size
- 3.5 GB
- Sample ID
- GSM8273023
- License
- NCBI GEO policy
- Published
- May 20, 2024
Cite this dataset
doi.org/10.1016/j.cels.2024.07.001 ↗ BibTeX
@article{geo:GSE267680,
doi = {10.1016/j.cels.2024.07.001},
title = {PanIN and CAF Transitions in Pancreatic Carcinogenesis Revealed with Spatial Data Integration [Xenium]: PanIN1131_S1A (Pancreatic Intraductal Neoplasm, human, pancreas)},
year = {2024}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB