10x Xenium
Human breast
GSM7780153
bronze Interactive viewer breast cancer Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'morphology_focus': DataTree[cyx] (1, 25778, 35416), (1, 12889, 17708), (1, 6444, 8854), (1, 3222, 4427), (1, 1611, 2213)
│ └── 'morphology_mip': DataTree[cyx] (1, 25778, 35416), (1, 12889, 17708), (1, 6444, 8854), (1, 3222, 4427), (1, 1611, 2213)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (25778, 35416), (12889, 17708), (6444, 8854), (3222, 4427), (1611, 2213)
│ └── 'nucleus_labels': DataTree[yx] (25778, 35416), (12889, 17708), (6444, 8854), (3222, 4427), (1611, 2213)
├── Points
│ └── 'transcripts': DataFrame with shape: (42638083, 8) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (167780, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (167780, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (167780, 1) (2D shapes)
└── Tables
└── 'table': AnnData (167780, 313)
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("zwCYn0f7rVjpJ0wp0000")
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("zwCYn0f7rVjpJ0wp") # 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 zwCYn0f7rVjpJ0wp0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/zwCYn0f7rVjpJ0wp
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid zwCYn0f7rVjpJ0wpLicense: NCBI GEO policy
Metadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- breast
- Condition
- breast cancer
- Modality
- RNA
- Observations (cells)
- 167,780
- Transcripts
- 42,638,083
- Tier
- bronze
- Size
- 4.2 GB
- Sample ID
- GSM7780153
- License
- NCBI GEO policy
- Published
- Oct 9, 2023
Cite this dataset
doi.org/10.1038/s41467-023-43458-x ↗ BibTeX
@article{Janesick_2023,
title = {High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis},
volume = {14},
ISSN = {2041-1723},
url = {http://dx.doi.org/10.1038/s41467-023-43458-x},
DOI = {10.1038/s41467-023-43458-x},
number = {1},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
author = {Janesick, Amanda and Shelansky, Robert and Gottscho, Andrew D. and Wagner, Florian and Williams, Stephen R. and Rouault, Morgane and Beliakoff, Ghezal and Morrison, Carolyn A. and Oliveira, Michelli F. and Sicherman, Jordan T. and Kohlway, Andrew and Abousoud, Jawad and Drennon, Tingsheng Yu and Mohabbat, Seayar H. and Taylor, Sarah E. B.},
year = {2023},
month = Dec
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB