Visium

Mouse skeletal muscle tissue

NCBI649

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Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'NCBI649_full_image': DataTree[cyx] (3, 17075, 16642), (3, 8537, 8321), (3, 4268, 4160), (3, 2134, 2080)
├── Shapes
│     └── 'NCBI649_spots': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4992, 55414)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI649_full_image (Images), NCBI649_spots (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("K7uQsPrpMBnR31rB0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

Python · lamindb

Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("K7uQsPrpMBnR31rB")   # stem uid: Lamin resolves it to the 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

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download K7uQsPrpMBnR31rB0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/K7uQsPrpMBnR31rB

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid K7uQsPrpMBnR31rB

Install (Python 3.12+) Docs →

License: CC BY-NC-SA 4.0 (noncommercial)

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Part of collection

Spatial Total RNA-Sequencing of regenerating mouse hindlimb muscle and Type 1-Lang reovirus-infected mouse heart→

7 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: skeletal muscle tissue
Modality: RNA
Observations (spots): 4,992
Tier: bronze
Chemistry: Visium v1
Magnification: 20x
Resolution: 16,642 × 17,075 px
mpp: 0.563 µm/px
Size: 536 MB
Sample ID: NCBI649
License: CC BY-NC-SA 4.0 NonCommercial
Published: Apr 20, 2022

Cite this dataset

doi.org/10.1038/s41587-022-01517-6 ↗

BibTeX

@article{McKellar_2022,
  title = {Spatial mapping of the total transcriptome by in situ polyadenylation},
  volume = {41},
  ISSN = {1546-1696},
  url = {http://dx.doi.org/10.1038/s41587-022-01517-6},
  DOI = {10.1038/s41587-022-01517-6},
  number = {4},
  journal = {Nature Biotechnology},
  publisher = {Springer Science and Business Media LLC},
  author = {McKellar, David W. and Mantri, Madhav and Hinchman, Meleana M. and Parker, John S. L. and Sethupathy, Praveen and Cosgrove, Benjamin D. and De Vlaminck, Iwijn},
  year = {2022},
  month = Nov,
  pages = {513–520}
}

Source: nature.com ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB