Adding reproducibility to single cell genomics

What is it about?

This paper is a perspective discussing some of the analytical problems that face newcomers to the field of single cell genomics. This cutting edge technology is revlutionizing integrative genomic analysis because it allows us to study gene function by cell type. However, the statistical analysis of these data types is in its infancy, and many prevalent issues are too often swept under the carpet, which is impeding rigor and reproducibility. The perspective piece discusses five such issues and proposes possible approaches to managing the problems.

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Photo by Ussama Azam on Unsplash

Photo by Ussama Azam on Unsplash

Why is it important?

Newcomers to the field are generally amazed by the degree to which changing one line of code can alter the results and inference. Whether it is clustering cells into types and states, evaluating hypotheses, or controlling for covariates, problems that integrative genomics researchers have faced for decades are exacerbated when it comes to single cell genomics. This paper hopefully makes a contribution to discussion of how we can ensure that reported results are more rigorous and reproducible.

Perspectives