Best practices for preparation of single cell gene expression samples

OICR's 10X Genomics experts release guidelines for scRNA-seq experiment prep

Proper sample preparation will help avoid creating single cell expression data like this. About 50% of the data is in the lower right cluster of blue points, which is enriched in dying cells and not the focus of the study that this data came from.

We recently put together our best tips and tricks used when starting new single cell gene expression projects with collaborators. The 10X scRNA-seq technical note is available for anyone interested in optimizing their experimental plan, covering considerations around sample quality and also the quantity of cells an experiment will require.

When planning single cell experiments, it often pays dividends to think about sample preparation upstream of any genomics work whatsoever. Our group finds that the best 10X single cell gene expression datasets come from samples where the lab (yours or ours) has spent a considerable amount of time thinking about how to minimize dead or dying cells while maintaining the relative representation of cell subpopulations in the mixture prior to any library preparation. Working out these problems in advance not only helps create cleaner data, it can also minimize overall project cost as it’s very expensive to generate data that’s only going to be removed bioinformatically!

Download the technical note here and start thinking about your single cell experiment today.

About the author

Paul Krzyzanowski is the Director of Genome Technology Translation at OICR and can be found on Twitter @pmkrzyzanowski.

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