Visium
Human lung
MISC30
silver Interactive viewer H&E ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ └── 'MISC30_full_image': DataTree[cyx] (3, 17360, 16464), (3, 8680, 8232), (3, 4340, 4116), (3, 2170, 2058)
├── Shapes
│ └── 'MISC30_spots': GeoDataFrame shape: (2729, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2729, 33538)
with coordinate systems:
▸ 'global', with elements:
MISC30_full_image (Images), MISC30_spots (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("eCrD3Y4YJAHr2U8c") # 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/eCrD3Y4YJAHr2U8c
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid eCrD3Y4YJAHr2U8c Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["eCrD3Y4YJAHr2U8c0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
A spatially resolved atlas of the human lung characterizes a gland-associated immune niche→ 20 datasets · publication
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- lung
- Modality
- RNA
- Observations
- 2,729
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 20x
- Resolution
- 16,464 × 17,360 px
- mpp
- 0.456 µm/px
- Size
- 459 MB
- Sample ID
- MISC30
- License
- CC BY-NC-SA 4.0 NonCommercial
- Published
- Dec 21, 2022
Cite this dataset
doi.org/10.1038/s41588-022-01243-4 ↗ BibTeX
@article{Madissoon_2022,
title = {A spatially resolved atlas of the human lung characterizes a gland-associated immune niche},
volume = {55},
ISSN = {1546-1718},
url = {http://dx.doi.org/10.1038/s41588-022-01243-4},
DOI = {10.1038/s41588-022-01243-4},
number = {1},
journal = {Nature Genetics},
publisher = {Springer Science and Business Media LLC},
author = {Madissoon, Elo and Oliver, Amanda J. and Kleshchevnikov, Vitalii and Wilbrey-Clark, Anna and Polanski, Krzysztof and Richoz, Nathan and Ribeiro Orsi, Ana and Mamanova, Lira and Bolt, Liam and Elmentaite, Rasa and Pett, J. Patrick and Huang, Ni and Xu, Chuan and He, Peng and Dabrowska, Monika and Pritchard, Sophie and Tuck, Liz and Prigmore, Elena and Perera, Shani and Knights, Andrew and Oszlanczi, Agnes and Hunter, Adam and Vieira, Sara F. and Patel, Minal and Lindeboom, Rik G. H. and Campos, Lia S. and Matsuo, Kazuhiko and Nakayama, Takashi and Yoshida, Masahiro and Worlock, Kaylee B. and Nikolić, Marko Z. and Georgakopoulos, Nikitas and Mahbubani, Krishnaa T. and Saeb-Parsy, Kourosh and Bayraktar, Omer Ali and Clatworthy, Menna R. and Stegle, Oliver and Kumasaka, Natsuhiko and Teichmann, Sarah A. and Meyer, Kerstin B.},
year = {2022},
month = Dec,
pages = {66–77}
}Source: nature.com ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB