DBiT-seq
Mouse kidney
GSM6320945
bronze Interactive viewer ✓ Verified publication
print(sdata)
SpatialData object
├── Shapes
│ ├── 'spots': GeoDataFrame shape: (1296, 1) (2D shapes)
│ └── 'spots_for_vitessce': GeoDataFrame shape: (1296, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1296, 31744)
with coordinate systems:
▸ 'global', with elements:
spots (Shapes), spots_for_vitessce (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("7sS7WE979jMjSM5k0000")
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("7sS7WE979jMjSM5k") # 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 7sS7WE979jMjSM5k0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/7sS7WE979jMjSM5k
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 7sS7WE979jMjSM5kLicense: NCBI GEO policy
Metadata
- Technology
- DBiT-seq
- Organism
- mouse
- Tissue
- kidney
- Modality
- RNA
- Observations (pixels)
- 1,296
- Tier
- bronze
- Size
- 22.2 MB
- Sample ID
- GSM6320945
- License
- NCBI GEO policy
- Published
- Feb 9, 2023
Cite this dataset
doi.org/10.1038/s41467-023-37111-w ↗ BibTeX
@article{geo:GSE207843,
doi = {10.1038/s41467-023-37111-w},
title = {GSM6934375},
year = {2023}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB