Visium
Mouse skin of body
GSM8279997
bronze Interactive viewer H&E skin neoplasm Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8279997_B1_mouse_tumor_skin_231204_hires_image': DataArray[cyx] (3, 2000, 1863)
│ └── 'GSM8279997_B1_mouse_tumor_skin_231204_lowres_image': DataArray[cyx] (3, 600, 559)
├── Shapes
│ └── 'GSM8279997_B1_mouse_tumor_skin_231204': GeoDataFrame shape: (1640, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1640, 19465)
with coordinate systems:
▸ 'GSM8279997_B1_mouse_tumor_skin_231204', with elements:
GSM8279997_B1_mouse_tumor_skin_231204_hires_image (Images), GSM8279997_B1_mouse_tumor_skin_231204_lowres_image (Images), GSM8279997_B1_mouse_tumor_skin_231204 (Shapes)
▸ 'GSM8279997_B1_mouse_tumor_skin_231204_downscaled_hires', with elements:
GSM8279997_B1_mouse_tumor_skin_231204_hires_image (Images), GSM8279997_B1_mouse_tumor_skin_231204 (Shapes)
▸ 'GSM8279997_B1_mouse_tumor_skin_231204_downscaled_lowres', with elements:
GSM8279997_B1_mouse_tumor_skin_231204_lowres_image (Images), GSM8279997_B1_mouse_tumor_skin_231204 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("MrwWm9v98pRXkplg0000")
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("MrwWm9v98pRXkplg") # 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 MrwWm9v98pRXkplg0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/MrwWm9v98pRXkplg
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid MrwWm9v98pRXkplgLicense: NCBI GEO policy
Part of collection
In vivo single-cell CRISPR uncovers distinct TNF-α programs in tumor evolution→ 4 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- skin of body
- Condition
- skin neoplasm
- Modality
- RNA
- Observations (spots)
- 1,640
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,863 × 2,000 px
- mpp
- 3.768 µm/px
- Size
- 8.1 MB
- Sample ID
- GSM8279997
- License
- NCBI GEO policy
- Published
- Jul 17, 2024
Cite this dataset
doi.org/10.1038/s41586-024-07663-y ↗ BibTeX
@article{Renz_2024,
title = {In vivo single-cell CRISPR uncovers distinct TNF programmes in tumour evolution},
volume = {632},
ISSN = {1476-4687},
url = {http://dx.doi.org/10.1038/s41586-024-07663-y},
DOI = {10.1038/s41586-024-07663-y},
number = {8024},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
author = {Renz, Peter F. and Ghoshdastider, Umesh and Baghai Sain, Simona and Valdivia-Francia, Fabiola and Khandekar, Ameya and Ormiston, Mark and Bernasconi, Martino and Duré, Clara and Kretz, Jonas A. and Lee, Minkyoung and Hyams, Katie and Forny, Merima and Pohly, Marcel and Ficht, Xenia and Ellis, Stephanie J. and Moor, Andreas E. and Sendoel, Ataman},
year = {2024},
month = July,
pages = {419–428}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB