How to remove cell cycle effct when analysing scRNA-seq data?

Question

[hsu]

Hi, I am analysing sc-RNA-seq data and I want to remove the cell cycle effect on my data. I found scLVM and f-scLVM can remove the effect of cell cycle gene, but I am confused about the two models.

Do you have any other suggestions or comments on these 2 models? Thank you !

Answer 1

[Kristoffer Vitting-Seerup]

I'd recommend using Seurat for QC, trimming and clustering - it keeps performing as one of the best single cell tools in benchmarks, is easy and fast to use. You can find a general workflow here. With an additional workflow for how to handle cell cycle (which is simply an extention of the scaleData step) here.

[hsu]

I want to remove the effect of cell-cycle genes on other gene expression. Does seurat work on it ?

[Kristoffer Vitting-Seerup]

Yep - the scaleData() removes the cell cycle effect (and other bias/batch unwanted effects) rom all expressed genes - you only have to specify which effects to remove (I think both vignettes have suggestions).