Anyone working with single nuclei data should read this paper! (single cell too, but for nuclei data it's essential)
If I could only have one QC metric for single nuclei data, it would be spliced pct / intronic fraction (I think it's more useful even than number of UMIs 🤯).
#SingleCell
If I could only have one QC metric for single nuclei data, it would be spliced pct / intronic fraction (I think it's more useful even than number of UMIs 🤯).
#SingleCell
Reposted from
Tomàs Montserrat Ayuso
Not checking nuclear markers like MALAT1 or intronic reads in your scRNA-seq data?🚨
We show their power to flag low-quality cells—even in top public datasets. It’s time to prioritize better QC for cleaner, more reliable genomics research!
Read more: bmcgenomics.biomedcentral.com/articles/10....
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https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02547-0
Unfortunately the package isn't easily installable from CRAN/Bioconductor. But more flexible to just use velocyto/kallisto anyways. Really wish cellranger would output this statistic to begin with.
https://simpleaf.readthedocs.io/en/latest/
- made at DNA (immature / unspliced / intronic)
- processed in the nucleus (mature / spliced / exonic)
- exported to the cytoplasm (mature / spliced / exonic)
So we have:
whole cell - mixed intronic / exonic
nucleus - more intronic
cytoplasmic debris - *only exonic*
Hopefully more people will use this approach!