Visium
Mouse intestine
GSM7840102
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7840102_V11Y11-297_D_hires_image': DataArray[cyx] (3, 1807, 2000)
│ └── 'GSM7840102_V11Y11-297_D_lowres_image': DataArray[cyx] (3, 542, 600)
├── Shapes
│ └── 'GSM7840102_V11Y11-297_D': GeoDataFrame shape: (3067, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3067, 32285)
with coordinate systems:
▸ 'GSM7840102_V11Y11-297_D', with elements:
GSM7840102_V11Y11-297_D_hires_image (Images), GSM7840102_V11Y11-297_D_lowres_image (Images), GSM7840102_V11Y11-297_D (Shapes)
▸ 'GSM7840102_V11Y11-297_D_downscaled_hires', with elements:
GSM7840102_V11Y11-297_D_hires_image (Images), GSM7840102_V11Y11-297_D (Shapes)
▸ 'GSM7840102_V11Y11-297_D_downscaled_lowres', with elements:
GSM7840102_V11Y11-297_D_lowres_image (Images), GSM7840102_V11Y11-297_D (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("e0VKTfhGqI58lMfW0000")
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("e0VKTfhGqI58lMfW") # 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 e0VKTfhGqI58lMfW0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/e0VKTfhGqI58lMfW
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid e0VKTfhGqI58lMfWLicense: NCBI GEO policy
Part of collection
Spatially restricted immune and microbiota-driven adaptation of the gut [Spatial Transcriptomics]→ 45 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- intestine
- Modality
- RNA
- Observations (spots)
- 3,067
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,807 px
- mpp
- 4.635 µm/px
- Size
- 49.1 MB
- Sample ID
- GSM7840102
- License
- NCBI GEO policy
- Published
- Nov 26, 2024
Cite this dataset
doi.org/10.1038/s41586-024-08216-z ↗ BibTeX
@article{Mayassi_2024,
title = {Spatially restricted immune and microbiota-driven adaptation of the gut},
volume = {636},
ISSN = {1476-4687},
url = {http://dx.doi.org/10.1038/s41586-024-08216-z},
DOI = {10.1038/s41586-024-08216-z},
number = {8042},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
author = {Mayassi, Toufic and Li, Chenhao and Segerstolpe, Åsa and Brown, Eric M. and Weisberg, Rebecca and Nakata, Toru and Yano, Hiroshi and Herbst, Paula and Artis, David and Graham, Daniel B. and Xavier, Ramnik J.},
year = {2024},
month = Nov,
pages = {447–456}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB