Hello everyone, 

This is the first time for me to analyze scRNA data, 
compared to the example in the workflow (Seurat), I notice that I have a large amount of mtDNA, 
I was thinking to incread the percentage of mtDNA so that I don't loose informations but on the other end I don't want to have bad results, do you guys have any suggestion about it ? 

code:
    seurat_object <- subset(seurat_object, subset = nFeature_RNA > 200 & nFeature_RNA < 2500 & percent.mt < 5)


my cells are leukaemia cells and here you can see the image

https://imgur.com/ZNHaMCU


Thank you
[scater](https://bioconductor.org/packages/release/bioc/vignettes/scater/inst/doc/overview.html#3_quality_control) has some nice QC functions that will determine which cells are outliers for QC each metric and remove them. It works on `SingleCellExperiment` objects, which are simple to convert from/to `Seurat` objects. This *feels* a bit better than just arbitrarily setting the thresholds yourself, though the results will be pretty similar. 

But as previously mentioned, a threshold around 10% for mitochondrial reads is pretty standard - just make sure most of your obviously dead cells are removed.