Mitochondrial percentage in Seurat

Question

[zizigolu]

Hi all

I want to use sctransform in Seurat

I don't know if still I should define the mitochondrial percentage or not, if not, how sctransform function knows which percentage suits for my data?

This workaround is correct or the second one please?

# store mitochondrial percentage in object meta data
pbmc <- PercentageFeatureSet(pbmc, pattern = "^MT-", col.name = "percent.mt")

# run sctransform
pbmc <- SCTransform(pbmc, vars.to.regress = "percent.mt", verbose = FALSE)

Or

pbmc <- subset(pbmc, subset = percent.mt < 5)

pbmc <- PercentageFeatureSet(pbmc, pattern = "^MT-", col.name = "percent.mt")

pbmc <- SCTransform(pbmc, vars.to.regress = "percent.mt", verbose = FALSE)

Thank you for any help

[rohitsatyam102]

Hi. I usually filter cells having greater than 25% of mitochondrial gene expression (the cutoff is empirical) i.e. percent.mt < 25 and then regress out "percent.mt". Even I am not sure how exactly SCT uses this column of metadata. Did you find any explanation?