Visium
Mouse brain
ZEN60
silver Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'ZEN60_full_image': DataTree[cyx] (3, 10000, 9901), (3, 5000, 4950), (3, 2500, 2475), (3, 1250, 1237)
├── Shapes
│ └── 'ZEN60_spots': GeoDataFrame shape: (3541, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3541, 31899)
with coordinate systems:
▸ 'global', with elements:
ZEN60_full_image (Images), ZEN60_spots (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("Yl0E3R7l9TEC5ZRR") # 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/Yl0E3R7l9TEC5ZRR
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Yl0E3R7l9TEC5ZRR Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["Yl0E3R7l9TEC5ZRR0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spotiphy: generative modeling in single-cell spatial whole transcriptomics→ 2 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- brain
- Modality
- RNA
- Observations
- 3,541
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 9,901 × 10,000 px
- mpp
- 0.888 µm/px
- Size
- 230 MB
- Sample ID
- ZEN60
- License
- CC BY-NC-SA 4.0 NonCommercial
- Published
- Jan 16, 2024
Cite this dataset
doi.org/10.5281/zenodo.10520022 ↗ BibTeX
@misc{https://doi.org/10.5281/zenodo.10520022,
doi = {10.5281/ZENODO.10520022},
url = {https://zenodo.org/doi/10.5281/zenodo.10520022},
author = {Yang, Jiyuan and Zheng, Ziqian and Yu, Jiyang},
language = {en},
title = {Spotiphy enables single-cell spatial whole transcriptomics across the entire section},
publisher = {Zenodo},
year = {2024},
copyright = {Creative Commons Attribution 4.0 International}
}Source: zenodo.org ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB