I would like to include the ribosomal genes (for normalisation, plotting etc) in the Seurat object but not use them in PCA, UMAP etc, so I remove them from HVGs. This is how I do it with ScaleData approach.

s <- NormalizeData(s, normalization.method="LogNormalize")
s <- FindVariableFeatures(s,selection.method="vst", nfeatures=2500)
# remove ribo genes from hvgs
VariableFeatures(s) <- setdiff(VariableFeatures(s),ribo_genes)
s <- ScaleData(s)
s <- RunPCA(s)

How would one do it with SCT approach?

s <- SCTransform(s)
s <- RunPCA(s)

Wondering if something like this would be a reasonable thing to do?

s <- SCTransform(s,variable.features.n=3500)
# remove ribo genes from hvgs
VariableFeatures(s) <- setdiff(VariableFeatures(s),ribo_genes)
s@assays$SCT@scale.data <- s@assays$SCT@scale.data[VariableFeatures(s),]
s <- RunPCA(s)

Or, is there a better way to do this?