Visium
Mouse brain
GSM7392316
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'GSM7392316_V11L12-109_C1_RNA_hires_image': DataArray[cyx] (3, 2000, 1979)
├── Shapes
│ └── 'GSM7392316_V11L12-109_C1_RNA': GeoDataFrame shape: (2918, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2918, 32285)
with coordinate systems:
▸ 'GSM7392316_V11L12-109_C1_RNA', with elements:
GSM7392316_V11L12-109_C1_RNA_hires_image (Images), GSM7392316_V11L12-109_C1_RNA (Shapes)
▸ 'GSM7392316_V11L12-109_C1_RNA_downscaled_hires', with elements:
GSM7392316_V11L12-109_C1_RNA_hires_image (Images), GSM7392316_V11L12-109_C1_RNA (Shapes)
▸ 'GSM7392316_V11L12-109_C1_RNA_downscaled_lowres', with elements:
GSM7392316_V11L12-109_C1_RNA (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("Db9fRR4t3hAbI801") # 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/Db9fRR4t3hAbI801
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Db9fRR4t3hAbI801 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["Db9fRR4t3hAbI8010000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial Multimodal Analysis: MALDI-MSI and Spatial Transcriptomics within the same tissue section→ 18 datasets · time course
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- brain
- Modality
- RNA
- Observations
- 2,918
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,979 × 2,000 px
- mpp
- 3.518 µm/px
- Size
- 28 MB
- Sample ID
- GSM7392316
- License
- unknown
- Published
- May 21, 2023
Cite this dataset
doi.org/10.1038/s41587-023-01937-y ↗ BibTeX
@article{Vicari_2023,
title = {Spatial multimodal analysis of transcriptomes and metabolomes in tissues},
volume = {42},
ISSN = {1546-1696},
url = {http://dx.doi.org/10.1038/s41587-023-01937-y},
DOI = {10.1038/s41587-023-01937-y},
number = {7},
journal = {Nature Biotechnology},
publisher = {Springer Science and Business Media LLC},
author = {Vicari, Marco and Mirzazadeh, Reza and Nilsson, Anna and Shariatgorji, Reza and Bjärterot, Patrik and Larsson, Ludvig and Lee, Hower and Nilsson, Mats and Foyer, Julia and Ekvall, Markus and Czarnewski, Paulo and Zhang, Xiaoqun and Svenningsson, Per and Käll, Lukas and Andrén, Per E. and Lundeberg, Joakim},
year = {2023},
month = Sept,
pages = {1046–1050}
}Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB