I am working with 10X scRNA-seq data from the mouse brain. I filtered cells based on outliers in the mitochondrial gene % by cell type. If the cell type had no outliers, I filtered cells that had their highest mt gene % concentrated among cells with low genes and UMI counts. I relied on these plots:
I also dropped cells (from all samples) with <800 genes and <1000 counts because there were a lot of cells with values below these cut-offs:
(The paper where this data comes from also used a cut-off of 800 genes. Not sure what their cut-off was for the UMI counts, though)
At the end, I went from 17,000 to about 9,800 cells. I would really appreciate getting some feedback on my filtering process. I have been following some vignettes out there and I am practicing what I learned on this dataset. I have rerun some QC after filtering and it all looks great to me, but since I am new to this I would like some feedback to know if I am really on the right track. Thanks!