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.

A 10XGenomics cell ranger report

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…