Visium
Human lung
MEND52
silver Interactive viewer H&E COVID-19 Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'MEND52_full_image': DataTree[cyx] (3, 14438, 14285), (3, 7219, 7142), (3, 3609, 3571), (3, 1804, 1785)
├── Shapes
│ └── 'MEND52_spots': GeoDataFrame shape: (758, 2) (2D shapes)
└── Tables
└── 'table': AnnData (758, 33538)
with coordinate systems:
▸ 'global', with elements:
MEND52_full_image (Images), MEND52_spots (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("0vD8xbza2w1Eivbg") # 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/0vD8xbza2w1Eivbg
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 0vD8xbza2w1Eivbg Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["0vD8xbza2w1Eivbg0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Genome-wide Spatial Expression Profiling in Formalin-fixed Tissues→ 15 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- lung
- Condition
- COVID-19
- Modality
- RNA
- Observations
- 758
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 20x
- Resolution
- 14,285 × 14,438 px
- mpp
- 0.572 µm/px
- Size
- 187 MB
- Sample ID
- MEND52
- License
- CC BY-NC-SA 4.0 NonCommercial
- Published
- Oct 8, 2021
Cite this dataset
doi.org/10.1016/j.xgen.2021.100065 ↗ BibTeX
@article{Gracia_Villacampa_2021,
title = {Genome-wide spatial expression profiling in formalin-fixed tissues},
volume = {1},
ISSN = {2666-979X},
url = {http://dx.doi.org/10.1016/j.xgen.2021.100065},
DOI = {10.1016/j.xgen.2021.100065},
number = {3},
journal = {Cell Genomics},
publisher = {Elsevier BV},
author = {Gracia Villacampa, Eva and Larsson, Ludvig and Mirzazadeh, Reza and Kvastad, Linda and Andersson, Alma and Mollbrink, Annelie and Kokaraki, Georgia and Monteil, Vanessa and Schultz, Niklas and Appelberg, Karin Sofia and Montserrat, Nuria and Zhang, Haibo and Penninger, Josef M. and Miesbach, Wolfgang and Mirazimi, Ali and Carlson, Joseph and Lundeberg, Joakim},
year = {2021},
month = Dec,
pages = {100065}
}Source: NCBI GEO ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB