Visium
Mouse liver
GSM6661401
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'GSM6661401_Visium6M1_hires_image': DataArray[cyx] (3, 2000, 1864)
├── Shapes
│ └── 'GSM6661401_Visium6M1': GeoDataFrame shape: (3606, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3606, 32285)
with coordinate systems:
▸ 'GSM6661401_Visium6M1', with elements:
GSM6661401_Visium6M1_hires_image (Images), GSM6661401_Visium6M1 (Shapes)
▸ 'GSM6661401_Visium6M1_downscaled_hires', with elements:
GSM6661401_Visium6M1_hires_image (Images), GSM6661401_Visium6M1 (Shapes)
▸ 'GSM6661401_Visium6M1_downscaled_lowres', with elements:
GSM6661401_Visium6M1 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("2wAykG6Toz1MsYWR0000")
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("2wAykG6Toz1MsYWR") # 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 2wAykG6Toz1MsYWR0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/2wAykG6Toz1MsYWR
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 2wAykG6Toz1MsYWRLicense: NCBI GEO policy
Part of collection
Fragment-sequencing unveils local tissue microenvironments at single cell resolution→ 2 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- liver
- Modality
- RNA
- Observations (spots)
- 3,606
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,864 × 2,000 px
- mpp
- 3.764 µm/px
- Size
- 30.8 MB
- Sample ID
- GSM6661401
- License
- NCBI GEO policy
- Published
- Oct 27, 2022
Cite this dataset
doi.org/10.1038/s41467-023-43005-8 ↗ BibTeX
@article{Handler_2023,
title = {Fragment-sequencing unveils local tissue microenvironments at single-cell resolution},
volume = {14},
ISSN = {2041-1723},
url = {http://dx.doi.org/10.1038/s41467-023-43005-8},
DOI = {10.1038/s41467-023-43005-8},
number = {1},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
author = {Handler, Kristina and Bach, Karsten and Borrelli, Costanza and Piscuoglio, Salvatore and Ficht, Xenia and Acar, Ilhan E. and Moor, Andreas E.},
year = {2023},
month = Nov
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB