Sample 151673
Data obtained from:
- RData file: https://www.dropbox.com/s/f4wcvtdq428y73p/Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata?dl=1 (linked from https://github.com/LieberInstitute/spatialLIBD/blob/ff49a2eaa1eb5477c5df8e46cf1652cdd8ec7244/R/fetch_data.R#L142C18-L142C125)
- Manual layer annotations: https://drive.google.com/drive/folders/10lhz5VY7YfvHrtV40MwaqLmWz56U9eBP?usp=sharing (linked from https://stagate.readthedocs.io/en/latest/T1_DLPFC.html)
- TIFF image: https://spatial-dlpfc.s3.us-east-2.amazonaws.com/images/151673_full_image.tif (linked from https://github.com/LieberInstitute/spatialLIBD/blob/ff49a2eaa1eb5477c5df8e46cf1652cdd8ec7244/README.md?plain=1#L235)
Data conversion
load("Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.Rdata")
saveRDS(sce, file="Human_DLPFC_Visium_processedData_sce_scran_spatialLIBD.rds")
See Jupyter notebook convert_rds_to_adata.ipynb
See Jupyter notebook convert_all_to_spatialdata.ipynb
> library(STexampleData)
> spe <- Visium_humanDLPFC()
> imgData(spe)
DataFrame with 2 rows and 4 columns
sample_id image_id data scaleFactor
<character> <character> <list> <numeric>
1 sample_151673 lowres #### 0.0450045
2 sample_151673 hires #### 0.1500150
> imgData(spe)[1, 'data']
[[1]]
600 x 600 (width x height) LoadedSpatialImage
> imgData(spe)[2, 'data']
[[1]]
2000 x 2000 (width x height) LoadedSpatialImage