Open renyzh5-2 opened 1 month ago
library(SPATAData) library(tidyverse) library(glmGamPoi) library(ggallin) library(hypeR) library(hdf5r) library(reticulate) library(tensorflow) library(Seurat) library(SeuratData) library(SPATA2)#install.packages("./Downloads/theMILOlab-SPATA2-v3.0.3-41-g6bb867d.tar.gz", repos = NULL, type = "source")
seurat_object An object of class Seurat 36601 features across 3382 samples within 1 assay Active assay: Spatial (36601 features, 2000 variable features) 3 layers present: counts, data, scale.data 2 dimensional reductions calculated: pca, umap 1 image present: image
spata_obj <- asSPATA2( object = seurat_object, sample_name = "P8T_Spatial", platform = "VisiumSmall", img_name = "image", img_scale_fct = "hires", assay_name = "Spatial", assay_modality = "gene", verbose = TRUE )
spata_obj <- identifyPixelContent(spata_obj) plotImage(spata_obj)
plotSurface(object = spata_obj, color_by = "VEGFA", pt_clrsp = "Greens 3",pt_size=0.2)
The coordinates don't match with the image. And the image isn‘t colored. How to sovle the issue, thx.
Hello. How did you create the Seurat object in the first place? With Load10X_Spatial()?
Load10X_Spatial()
library(SPATAData) library(tidyverse) library(glmGamPoi) library(ggallin) library(hypeR) library(hdf5r) library(reticulate) library(tensorflow) library(Seurat) library(SeuratData) library(SPATA2)#install.packages("./Downloads/theMILOlab-SPATA2-v3.0.3-41-g6bb867d.tar.gz", repos = NULL, type = "source")
spata_obj <- asSPATA2( object = seurat_object, sample_name = "P8T_Spatial", platform = "VisiumSmall", img_name = "image",
img_scale_fct = "hires", assay_name = "Spatial", assay_modality = "gene", verbose = TRUE )
spata_obj <- identifyPixelContent(spata_obj) plotImage(spata_obj)
plotSurface(object = spata_obj, color_by = "VEGFA", pt_clrsp = "Greens 3",pt_size=0.2)
The coordinates don't match with the image. And the image isn‘t colored. How to sovle the issue, thx.