Visium

Human brain

MISC6

silver Interactive viewer H&E ✓ Verified publication

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'MISC6_full_image': DataTree[cyx] (3, 13332, 13332), (3, 6666, 6666), (3, 3333, 3333), (3, 1666, 1666)
├── Shapes
│     └── 'MISC6_spots': GeoDataFrame shape: (4110, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4110, 33538)
with coordinate systems:
    ▸ 'global', with elements:
        MISC6_full_image (Images), MISC6_spots (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("uXJvkqZuGU7zjhaS0000")
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("uXJvkqZuGU7zjhaS")   # 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 uXJvkqZuGU7zjhaS0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/uXJvkqZuGU7zjhaS

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid uXJvkqZuGU7zjhaS

Install (Python 3.12+) Docs →

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

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Part of collection

spatialLIBD→

12 datasets · publication

Metadata

Technology: Visium
Organism: human
Tissue: brain
Modality: RNA
Observations (spots): 4,110
Tier: silver
Chemistry: Visium v1
Resolution: 13,332 × 13,332 px
mpp: 0.726 µm/px
Size: 475 MB
Sample ID: MISC6
License: CC BY-NC-SA 4.0 NonCommercial
Published: Feb 8, 2021

Cite this dataset

doi.org/10.1038/s41593-020-00787-0 ↗

BibTeX

@article{Maynard_2021,
  title = {Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex},
  volume = {24},
  ISSN = {1546-1726},
  url = {http://dx.doi.org/10.1038/s41593-020-00787-0},
  DOI = {10.1038/s41593-020-00787-0},
  number = {3},
  journal = {Nature Neuroscience},
  publisher = {Springer Science and Business Media LLC},
  author = {Maynard, Kristen R. and Collado-Torres, Leonardo and Weber, Lukas M. and Uytingco, Cedric and Barry, Brianna K. and Williams, Stephen R. and Catallini, Joseph L. and Tran, Matthew N. and Besich, Zachary and Tippani, Madhavi and Chew, Jennifer and Yin, Yifeng and Kleinman, Joel E. and Hyde, Thomas M. and Rao, Nikhil and Hicks, Stephanie C. and Martinowich, Keri and Jaffe, Andrew E.},
  year = {2021},
  month = Feb,
  pages = {425–436}
}

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