spatial transcriptomics
Mouse spinal cord
NCBI117
silver Interactive viewer H&E amyotrophic lateral sclerosis ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ └── 'NCBI117_full_image': DataTree[cyx] (3, 9898, 9299), (3, 4949, 4649), (3, 2474, 2324), (3, 1237, 1162)
├── Shapes
│ └── 'NCBI117_spots': GeoDataFrame shape: (375, 2) (2D shapes)
└── Tables
└── 'table': AnnData (375, 15169)
with coordinate systems:
▸ 'global', with elements:
NCBI117_full_image (Images), NCBI117_spots (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("ZaKTJ7kpSKt8Mv2i") # 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/ZaKTJ7kpSKt8Mv2i
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ZaKTJ7kpSKt8Mv2i Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["ZaKTJ7kpSKt8Mv2i0000"])[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
- 375
- Tier
- silver
- Chemistry
- ST 1k
- Resolution
- 9,299 × 9,898 px
- mpp
- 0.691 µm/px
- Size
- 115 MB
- Sample ID
- NCBI117
- 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