Visium

Mouse intestine

MEND30

bronze Interactive viewer H&E ✓ Verified publication

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'MEND30_full_image': DataTree[cyx] (3, 22836, 23596), (3, 11418, 11798), (3, 5709, 5899), (3, 2854, 2949)
├── Shapes
│     └── 'MEND30_spots': GeoDataFrame shape: (1744, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1744, 54838)
with coordinate systems:
    ▸ 'global', with elements:
        MEND30_full_image (Images), MEND30_spots (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("hAwbVCYXzrIgix6j0000")
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("hAwbVCYXzrIgix6j")   # 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 hAwbVCYXzrIgix6j0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/hAwbVCYXzrIgix6j

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid hAwbVCYXzrIgix6j

Install (Python 3.12+) Docs →

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

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Part of collection

spatialRNAseq_heart_raw_suppdata→

8 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: intestine
Modality: RNA
Observations (spots): 1,744
Tier: bronze
Chemistry: Visium v1
Magnification: 20x
Resolution: 23,596 × 22,836 px
mpp: 0.361 µm/px
Size: 613 MB
Sample ID: MEND30
License: CC BY-NC-SA 4.0 NonCommercial
Published: Nov 27, 2021

Cite this dataset

doi.org/10.1038/s44161-022-00138-1 ↗

BibTeX

@article{Mantri_2022,
  title = {Spatiotemporal transcriptomics reveals pathogenesis of viral myocarditis},
  volume = {1},
  ISSN = {2731-0590},
  url = {http://dx.doi.org/10.1038/s44161-022-00138-1},
  DOI = {10.1038/s44161-022-00138-1},
  number = {10},
  journal = {Nature Cardiovascular Research},
  publisher = {Springer Science and Business Media LLC},
  author = {Mantri, Madhav and Hinchman, Meleana M. and McKellar, David W. and Wang, Michael F. Z. and Cross, Shaun T. and Parker, John S. L. and De Vlaminck, Iwijn},
  year = {2022},
  month = Oct,
  pages = {946–960}
}

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