Seurat analysis without ribosomal genes
0
0
Entering edit mode
13 months ago
firestar ★ 1.6k

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?

single-cell transcriptomics seurat • 604 views
ADD COMMENT

Login before adding your answer.

Traffic: 1963 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6