Bioinformatics Stack Exchange is a question and answer site for researchers, developers, students, teachers, and end users interested in bioinformatics. It only takes a minute to sign up.
Sign up to join this community
I have been doing single cell analysis based on seurat and I realized after each clustering and reclustering when I run SCTransform, in my code there is vars.to.regress = percent.mt and I was running this everytime. I removed MT- contaminated cells before.
My clustering seems fine though.
Do you think this is very critical thing and I have to analyze everything from scratch?
I think it would be a good idea to at least look at the distribution of mitochondrial gene fraction in your cells. If they mostly have low fractions (e.g. less than 15%), then I wouldn't expect the clustering to be influenced too much by them.
With SCTransform regressing on the percent.mt, I think it's okay to do post-transform filtering, but it'd be a good idea to exclude any cells that have high mitochondrial fraction prior to doing clustering (unless, for whatever reason, those are the cells you're interested in).
