# Help with Seurat QC ambiguity

I have four PBMC samples from 10X scRNA-seq

> cancer
An object of class Seurat
36601 features across 18338 samples within 1 assay
Active assay: RNA (36601 features, 0 variable features)
>


And this is Seurat QC plot

If I am not wrong, samples were of relatively low quality, with gene expression data revealing the presence of mitochondrial genes, as well as MALAT-1, which are suggestive of poor sample quality (dead/dying cells).

Any way by this plot I filtered cells to remove data that had more than 20 "percent" mitochondrial expression , > 2000 features or < 100 features

cancer <- subset(cancer, subset = nFeature_RNA > 100 & nFeature_RNA < 2000 & percent.mt < 20)


By this I lost most of cells

> cancer
An object of class Seurat
36601 features across 6,883 samples within 1 assay
Active assay: RNA (36601 features, 0 variable features)
>


Please, can somebody experienced in scRNA-seq inspect this plot and my thresholds and tell me if I am wrong, any suggestion, if losing this number of cells is normal

Thank you

From the graphs, you're losing most of the cells through the percent.mitochondrial threshold. The distribution is so broad on that mitochondrial plot that I probably wouldn't filter for mitochondrial expression (except possibly at ~95%). If I did have a lower threshold, I'd put it at around 50% rather than 20%, because that's where there's a change in density on the mitochondrial plot.