Visium

Human intestine

MEND93

silver Interactive viewer H&E ✓ Verified publication

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'MEND93_full_image': DataTree[cyx] (3, 48128, 47616), (3, 24064, 23808), (3, 12032, 11904), (3, 6016, 5952)
├── Shapes
│     └── 'MEND93_spots': GeoDataFrame shape: (3742, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (3742, 17943)
with coordinate systems:
    ▸ 'global', with elements:
        MEND93_full_image (Images), MEND93_spots (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("jIEhOix9p7MQaGOS0000")
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("jIEhOix9p7MQaGOS")   # 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 jIEhOix9p7MQaGOS0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/jIEhOix9p7MQaGOS

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid jIEhOix9p7MQaGOS

Install (Python 3.12+) Docs →

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

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Part of collection

Spatially resolved transcriptomic profiling of degraded→

35 datasets · comparison

Metadata

Technology: Visium
Organism: human
Tissue: intestine
Modality: RNA
Observations (spots): 3,742
Tier: silver
Chemistry: Visium v1
Magnification: 40x
Resolution: 47,616 × 48,128 px
mpp: 0.172 µm/px
Size: 3.9 GB
Sample ID: MEND93
License: CC BY-NC-SA 4.0 NonCommercial
Published: Dec 20, 2022

Cite this dataset

doi.org/10.1038/s41467-023-36071-5 ↗

BibTeX

@article{Mirzazadeh_2023,
  title = {Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples},
  volume = {14},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-023-36071-5},
  DOI = {10.1038/s41467-023-36071-5},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Mirzazadeh, Reza and Andrusivova, Zaneta and Larsson, Ludvig and Newton, Phillip T. and Galicia, Leire Alonso and Abalo, Xesús M. and Avijgan, Mahtab and Kvastad, Linda and Denadai-Souza, Alexandre and Stakenborg, Nathalie and Firsova, Alexandra B. and Shamikh, Alia and Jurek, Aleksandra and Schultz, Niklas and Nistér, Monica and Samakovlis, Christos and Boeckxstaens, Guy and Lundeberg, Joakim},
  year = {2023},
  month = Jan
}

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