Visium
Mouse hippocampal formation
GSM4656180
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM4656180_CBS1-illumina_hip142078-spatial-illumina_hires_image': DataArray[cyx] (3, 2000, 1882)
│ └── 'GSM4656180_CBS1-illumina_hip142078-spatial-illumina_lowres_image': DataArray[cyx] (3, 600, 565)
├── Shapes
│ └── 'GSM4656180_CBS1-illumina_hip142078-spatial-illumina': GeoDataFrame shape: (2560, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2560, 31053)
with coordinate systems:
▸ 'GSM4656180_CBS1-illumina_hip142078-spatial-illumina', with elements:
GSM4656180_CBS1-illumina_hip142078-spatial-illumina_hires_image (Images), GSM4656180_CBS1-illumina_hip142078-spatial-illumina_lowres_image (Images), GSM4656180_CBS1-illumina_hip142078-spatial-illumina (Shapes)
▸ 'GSM4656180_CBS1-illumina_hip142078-spatial-illumina_downscaled_hires', with elements:
GSM4656180_CBS1-illumina_hip142078-spatial-illumina_hires_image (Images), GSM4656180_CBS1-illumina_hip142078-spatial-illumina (Shapes)
▸ 'GSM4656180_CBS1-illumina_hip142078-spatial-illumina_downscaled_lowres', with elements:
GSM4656180_CBS1-illumina_hip142078-spatial-illumina_lowres_image (Images), GSM4656180_CBS1-illumina_hip142078-spatial-illumina (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("0dnopD5zWse5Gguy") # 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 Load from the CLI
# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/0dnopD5zWse5Gguy
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 0dnopD5zWse5Gguy Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["0dnopD5zWse5Gguy0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
The spatial landscape of gene expression isoforms in tissue sections→ 3 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- hippocampal formation
- Modality
- RNA
- Observations
- 2,560
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 1,882 × 2,000 px
- mpp
- 3.692 µm/px
- Size
- 46 MB
- Sample ID
- GSM4656180
- License
- unknown
- Published
- Aug 26, 2020
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB