This post: “Understanding your 10XGenomics cell ranger report” originally appeared on my labs group blog but I thought that people working with single-cell who are at AGBT might like to read it too.
Understanding your @10Xgenomics cell ranger reports
The 10X Genomics Cell Ranger analysis package delivers some basic QC which can help determine how well your experiment worked. The post describes some of the key metrics users need to review to confirm their experiment is working as planned. The most common issue we see is variability in the number of cells captured. Second to this is the variability in reads per cell; we’re aiming for 50,000-100,000, but have over-sequenced many samples due to poor cell capture. However so far we’ve only run a handful of samples and we’ll need lots more data to determine the root cause of variability…although I suspect a lot comes from the sample.
Over time we’ll look at these numbers across projects and I’m sure as we gather more data about the experiments we’ll learn where the variability is coming from. We’re also starting to work on a single-cell QC database to capture these files (and possibly from other platforms) along with some experimental metadata. Keep an eye out as we’ll be asking you to contribute your data soon…
Sequencing saturation at 99.2% ! Could be interesting to look at a downsampling curve NbUMI= f(Nb reads per cell) to see the saturation of new UMI discovery in your system. A way to explore the PCR bias in 10x droplets compared to plate/C1 protocols.
The 76% Q30 for template read come from Hiseq4000 sequencing ? Really lower with a NextSeq actually. Thanks for sharing all those data James.
Hi Kevin, I’m hoping we can get many users sharing similar data to get a better handle on the upstream issues in single-cell experiments…and that includes you if you’re running scRNA-seq!
Hi james, yes we are running a 10x single cell controler since a few months and it seems really interesting (except for the price per sample ! Multiplexing is a good idea, get the reagents price lower a better one). I was not meaning sharing this dataset, i was more talking about all the comments, blog posts, analysis you provide to the community since a few years. best.
Hi Kevin,
We’re working on a site that’lll allow users to share summarised and anonymised Cell Ranger reports with some metadata to allow people to see what cells work well on the system and what sort of cell handling might be problematic. Once it is live I hope you’ll take a look?
James.
Nice initiative ! I will definitly take a look and share some of our 10x data !
kevin.