spatial transcriptomics
Mouse spinal cord
NCBI44
bronze Interactive viewer H&E amyotrophic lateral sclerosis ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ └── 'NCBI44_full_image': DataTree[cyx] (3, 8195, 7699), (3, 4097, 3849), (3, 2048, 1924), (3, 1024, 962)
├── Shapes
│ └── 'NCBI44_spots': GeoDataFrame shape: (286, 2) (2D shapes)
└── Tables
└── 'table': AnnData (286, 15549)
with coordinate systems:
▸ 'global', with elements:
NCBI44_full_image (Images), NCBI44_spots (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("CcQV8j043lVxRDrn") # 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/CcQV8j043lVxRDrn
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid CcQV8j043lVxRDrn Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["CcQV8j043lVxRDrn0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and open Part of collection
Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis→ 302 datasets · publication
Metadata
- Technology
- spatial transcriptomics
- Organism
- mouse
- Tissue
- spinal cord
- Condition
- amyotrophic lateral sclerosis
- Modality
- RNA
- Observations
- 286
- Tier
- bronze
- Chemistry
- ST 1k
- Resolution
- 7,699 × 8,195 px
- mpp
- 0.839 µm/px
- Size
- 88 MB
- Sample ID
- NCBI44
- 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