Visium
Mouse intestine
NCBI729
silver Interactive viewer H&E ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ └── 'NCBI729_full_image': DataTree[cyx] (3, 8929, 9901), (3, 4464, 4950), (3, 2232, 2475), (3, 1116, 1237)
├── Shapes
│ └── 'NCBI729_spots': GeoDataFrame shape: (2604, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2604, 31053)
with coordinate systems:
▸ 'global', with elements:
NCBI729_full_image (Images), NCBI729_spots (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("8nQxdXEGN0eRhPlu") # 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/8nQxdXEGN0eRhPlu
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 8nQxdXEGN0eRhPlu Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["8nQxdXEGN0eRhPlu0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
10X Visium Spatial transcriptomics of murine colon in steady state and during recovery after DSS colitis→ 2 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- intestine
- Modality
- RNA
- Observations
- 2,604
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 9,901 × 8,929 px
- mpp
- 0.969 µm/px
- Size
- 255 MB
- Sample ID
- NCBI729
- License
- CC BY-NC-SA 4.0 NonCommercial
- Published
- Dec 5, 2021
Cite this dataset
doi.org/10.1016/j.crmeth.2022.100340 ↗ BibTeX
@article{Lyubetskaya_2022,
title = {Assessment of spatial transcriptomics for oncology discovery},
volume = {2},
ISSN = {2667-2375},
url = {http://dx.doi.org/10.1016/j.crmeth.2022.100340},
DOI = {10.1016/j.crmeth.2022.100340},
number = {11},
journal = {Cell Reports Methods},
publisher = {Elsevier BV},
author = {Lyubetskaya, Anna and Rabe, Brian and Fisher, Andrew and Lewin, Anne and Neuhaus, Isaac and Brett, Constance and Brett, Todd and Pereira, Ethel and Golhar, Ryan and Kebede, Sami and Font-Tello, Alba and Mosure, Kathy and Van Wittenberghe, Nicholas and Mavrakis, Konstantinos J. and MacIsaac, Kenzie and Chen, Benjamin J. and Drokhlyansky, Eugene},
year = {2022},
month = Nov,
pages = {100340}
}Source: NCBI GEO ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB