Visium
Mouse colon
GSM6210023
bronze Interactive viewer H&E colorectal carcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM6210023_D15_PBS_Visium_hires_image': DataArray[cyx] (3, 2000, 1900)
│ └── 'GSM6210023_D15_PBS_Visium_lowres_image': DataArray[cyx] (3, 600, 570)
├── Shapes
│ └── 'GSM6210023_D15_PBS_Visium': GeoDataFrame shape: (2221, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2221, 32285)
with coordinate systems:
▸ 'GSM6210023_D15_PBS_Visium', with elements:
GSM6210023_D15_PBS_Visium_hires_image (Images), GSM6210023_D15_PBS_Visium_lowres_image (Images), GSM6210023_D15_PBS_Visium (Shapes)
▸ 'GSM6210023_D15_PBS_Visium_downscaled_hires', with elements:
GSM6210023_D15_PBS_Visium_hires_image (Images), GSM6210023_D15_PBS_Visium (Shapes)
▸ 'GSM6210023_D15_PBS_Visium_downscaled_lowres', with elements:
GSM6210023_D15_PBS_Visium_lowres_image (Images), GSM6210023_D15_PBS_Visium (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("d8EojjWNuiKOfwXi0000")
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("d8EojjWNuiKOfwXi") # 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 d8EojjWNuiKOfwXi0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/d8EojjWNuiKOfwXi
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid d8EojjWNuiKOfwXiLicense: NCBI GEO policy
Part of collection
Interleukin 7 therapy changes tumor immune environment to pro-inflammatory through myeloid and T cell interactions [Visium]→ 2 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- colon
- Condition
- colorectal carcinoma
- Modality
- RNA
- Observations (spots)
- 2,221
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,900 × 2,000 px
- mpp
- 3.515 µm/px
- Size
- 35.1 MB
- Sample ID
- GSM6210023
- License
- NCBI GEO policy
- Published
- Mar 5, 2024
Cite this dataset
doi.org/10.1038/s41416-024-02617-7 ↗ BibTeX
@article{Eum_2024,
title = {Single-cell RNA sequencing reveals myeloid and T cell co-stimulation mediated by IL-7 anti-cancer immunotherapy},
volume = {130},
ISSN = {1532-1827},
url = {http://dx.doi.org/10.1038/s41416-024-02617-7},
DOI = {10.1038/s41416-024-02617-7},
number = {8},
journal = {British Journal of Cancer},
publisher = {Springer Science and Business Media LLC},
author = {Eum, Hye Hyeon and Jeong, Dasom and Kim, Nayoung and Jo, Areum and Na, Minsu and Kang, Huiram and Hong, Yourae and Kong, Jin-Sun and Jeong, Gi Heon and Yoo, Seung-Ah and Lee, Hae-Ock},
year = {2024},
month = Feb,
pages = {1388–1401}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB