error in joint clustering

[BhardwajArch]

Hello I am working on multiple samples of visium spatial transcriptome data.

**-> Raw data was analysed in the space ranger and stored in the seurat object list.

Next to remove batch effect ,used PrepSCTIntegration method for Spatial data.**

library(SingleCellExperiment) library(ggplot2) library(BayesSpace)

object.list # object list object.list <- PrepSCTIntegration(object.list = object.list, anchor.features = st.features, verbose = FALSE)

int.anchors <- FindIntegrationAnchors(object.list = object.list, normalization.method = "SCT", verbose = FALSE, anchor.features = st.features)

st.integrated <- IntegrateData(anchorset = int.anchors, normalization.method = "SCT", verbose = TRUE)

st.integrated <- RunPCA(st.integrated, verbose = FALSE)

ss.integrated <- st.integrated

-> For the joint analysis in Bayespace, I changed the seurat object list into sce object list

ss_list <- SplitObject(ss.integrated, split.by = "orig.ident")

A1<- st_list$A1

#Convert to SCE diet.seurat = Seurat::DietSeurat(A1, graphs = "pca") #slim down Seurat obj prior to conversion sceA = as.SingleCellExperiment(diet.seurat, assay = "SCT") #convert seurat to SCE colData(sceA) = cbind(colData(sceA), A1@images$A1@coordinates) #add spatial info to SCE

B1 <- st_list$B1

#Convert to SCE diet.seurat = Seurat::DietSeurat(B1, graphs = "pca") #slim down Seurat obj prior to conversion sceB = as.SingleCellExperiment(diet.seurat, assay = "SCT") #convert seurat to SCE colData(sceB) = cbind(colData(sceB), B1@images$B1@coordinates) #add spatial info to SCE

sce.combined = cbind(sce, sceB, deparse.level = 1)

sce.combined = spatialPreprocess(sce.combined, platform = "Visium", skip.PCA = T, log.normalize = F)

clusterPlot(sce.combined)

It gives me clusters for one image instead of two imaging data.

I would appreciate all the suggestions

[edward130603]

Sorry for the delayed response. I think the issue is because you need to offset the row and/or col values first. The first code chunk under the "Clustering" header in our vignette describes how to do this. Let me know if you run into further issues.