Visium
Mouse brain
adult-mouse-brain-section-2-coronal-stains-dapi-anti-gfap-anti-neu-n-1-standard-1-1-0
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'V1_Adult_Mouse_Brain_Coronal_Section_2_full_image': DataTree[cyx] (3, 24240, 24240), (3, 12120, 12120), (3, 6060, 6060), (3, 3030, 3030), (3, 1515, 1515)
│ ├── 'V1_Adult_Mouse_Brain_Coronal_Section_2_hires_image': DataArray[cyx] (3, 2000, 2000)
│ └── 'V1_Adult_Mouse_Brain_Coronal_Section_2_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│ └── 'V1_Adult_Mouse_Brain_Coronal_Section_2': GeoDataFrame shape: (2807, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2807, 32285)
with coordinate systems:
▸ 'V1_Adult_Mouse_Brain_Coronal_Section_2', with elements:
V1_Adult_Mouse_Brain_Coronal_Section_2_full_image (Images), V1_Adult_Mouse_Brain_Coronal_Section_2_hires_image (Images), V1_Adult_Mouse_Brain_Coronal_Section_2_lowres_image (Images), V1_Adult_Mouse_Brain_Coronal_Section_2 (Shapes)
▸ 'V1_Adult_Mouse_Brain_Coronal_Section_2_downscaled_hires', with elements:
V1_Adult_Mouse_Brain_Coronal_Section_2_hires_image (Images), V1_Adult_Mouse_Brain_Coronal_Section_2 (Shapes)
▸ 'V1_Adult_Mouse_Brain_Coronal_Section_2_downscaled_lowres', with elements:
V1_Adult_Mouse_Brain_Coronal_Section_2_lowres_image (Images), V1_Adult_Mouse_Brain_Coronal_Section_2 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("ptVNhymmPjeVfxHw") # 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/ptVNhymmPjeVfxHw
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ptVNhymmPjeVfxHw Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["ptVNhymmPjeVfxHw0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- brain
- Modality
- RNA
- Observations
- 2,807
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 20x
- Resolution
- 24,240 × 24,240 px
- mpp
- 0.308 µm/px
- Size
- 2.7 GB
- Sample ID
- adult-mouse-brain-section-2-coronal-stains-dapi-anti-gfap-anti-neu-n-1-standard-1-1-0
- License
- CC BY 4.0
- Published
- Jun 23, 2020
Cite this dataset
No linked publication found — please cite the data source: 10x Genomics ↗.
Source: 10x Genomics ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB