Subclustering of SCTransformed Integrated dataset

[Pieros123-R]

I have am having trouble finding the correct way to subcluster my data.
I integrated and processed my data in Seurat V5 using the following code:

`merged_Seurat <- merge(Source_01_Seurat, y = c(Source_02_Seurat, Source_03_Seurat, Source_04_Seurat))

merged_Seurat <- JoinLayers(merged_Seurat)

merged_Seurat[["RNA"]] <- split(merged_Seurat[["RNA"]], f = merged_Seurat$"Sample")

merged_Seurat = SCTransform(merged_Seurat)

merged_Seurat <- RunPCA(merged_Seurat, verbose = F)

merged_Seurat <- IntegrateLayers(object = merged_Seurat,
method = RPCAIntegration,
normalization.method = "SCT")

merged_Seurat <- FindNeighbors(merged_Seurat, dims = 1:26, reduction = 'integrated.dr')
merged_Seurat <- FindClusters(merged_Seurat, resolution = 0.28)
merged_Seurat <- RunUMAP(merged_Seurat, dims = 1:26, reduction = 'integrated.dr')`

This leaves me with the merged_Seurat object containing an RNA and an SCT assay.

Now my question is how do I subcluster one specific cluster from this dataset?
Do I go back to the raw counts from the RNA assay and rerun everything including integration, or is there a way to keep the integration?