← All datasets
spatial transcriptomics

Mouse spinal cord

NCBI140

bronze Interactive viewer H&E amyotrophic lateral sclerosis ✓ Verified publication
Mouse spinal cord preview
print(sdata)
SpatialData object
├── Images
│     └── 'NCBI140_full_image': DataTree[cyx] (3, 9861, 9264), (3, 4930, 4632), (3, 2465, 2316), (3, 1232, 1158)
├── Shapes
│     └── 'NCBI140_spots': GeoDataFrame shape: (244, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (244, 14979)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI140_full_image (Images), NCBI140_spots (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("BAdoKVc37NRPR7Tx")   # 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/BAdoKVc37NRPR7Tx

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid BAdoKVc37NRPR7Tx
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["BAdoKVc37NRPR7Tx0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Metadata

Technology
spatial transcriptomics
Organism
mouse
Tissue
spinal cord
Condition
amyotrophic lateral sclerosis
Modality
RNA
Observations
244
Tier
bronze
Chemistry
ST 1k
Resolution
9,264 × 9,861 px
mpp
0.685 µm/px
Size
78 MB
Sample ID
NCBI140
License
CC BY-NC-SA 4.0 NonCommercial
Published
Apr 5, 2019

Cite this dataset

doi.org/10.1126/science.aav9776 ↗
BibTeX
@article{Maniatis_2019,
  title = {Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis},
  volume = {364},
  ISSN = {1095-9203},
  url = {http://dx.doi.org/10.1126/science.aav9776},
  DOI = {10.1126/science.aav9776},
  number = {6435},
  journal = {Science},
  publisher = {American Association for the Advancement of Science (AAAS)},
  author = {Maniatis, Silas and Äijö, Tarmo and Vickovic, Sanja and Braine, Catherine and Kang, Kristy and Mollbrink, Annelie and Fagegaltier, Delphine and Andrusivová, Žaneta and Saarenpää, Sami and Saiz-Castro, Gonzalo and Cuevas, Miguel and Watters, Aaron and Lundeberg, Joakim and Bonneau, Richard and Phatnani, Hemali},
  year = {2019},
  month = Apr,
  pages = {89–93}
}

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