Visium
Mouse spleen
GSM6042727
bronze Interactive viewer H&E lymphocytic choriomeningitis Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'GSM6042727_Round1_B1_Day7_CD4depl_hires_image': DataArray[cyx] (3, 1987, 2000)
├── Shapes
│ └── 'GSM6042727_Round1_B1_Day7_CD4depl': GeoDataFrame shape: (2177, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2177, 32285)
with coordinate systems:
▸ 'GSM6042727_Round1_B1_Day7_CD4depl', with elements:
GSM6042727_Round1_B1_Day7_CD4depl_hires_image (Images), GSM6042727_Round1_B1_Day7_CD4depl (Shapes)
▸ 'GSM6042727_Round1_B1_Day7_CD4depl_downscaled_hires', with elements:
GSM6042727_Round1_B1_Day7_CD4depl_hires_image (Images), GSM6042727_Round1_B1_Day7_CD4depl (Shapes)
▸ 'GSM6042727_Round1_B1_Day7_CD4depl_downscaled_lowres', with elements:
GSM6042727_Round1_B1_Day7_CD4depl (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("f4JFyttSMJgv3rVZ0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) 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("f4JFyttSMJgv3rVZ") # 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 Shell
# sddb client: download the .zarr into data/
sddb-cli download f4JFyttSMJgv3rVZ0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/f4JFyttSMJgv3rVZ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid f4JFyttSMJgv3rVZLicense: NCBI GEO policy
Part of collection
Spatial RNA-sequencing of day7 and day 21 post-LCMV Cl13 infection following transient CD4+ T cell depletion (Visium)→ 8 datasets · time course
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- spleen
- Condition
- lymphocytic choriomeningitis
- Modality
- RNA
- Observations (spots)
- 2,177
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,987 px
- mpp
- 3.513 µm/px
- Size
- 36.2 MB
- Sample ID
- GSM6042727
- License
- NCBI GEO policy
- Published
- Nov 29, 2022
Cite this dataset
doi.org/10.1016/j.celrep.2022.111736 ↗ BibTeX
@article{Topchyan_2022,
title = {Spatial transcriptomics demonstrates the role of CD4 T cells in effector CD8 T cell differentiation during chronic viral infection},
volume = {41},
ISSN = {2211-1247},
url = {http://dx.doi.org/10.1016/j.celrep.2022.111736},
DOI = {10.1016/j.celrep.2022.111736},
number = {9},
journal = {Cell Reports},
publisher = {Elsevier BV},
author = {Topchyan, Paytsar and Zander, Ryan and Kasmani, Moujtaba Y. and Nguyen, Christine and Brown, Ashley and Lin, Siying and Burns, Robert and Cui, Weiguo},
year = {2022},
month = Nov,
pages = {111736}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB