Single cell RNA-sequencing: replicability of cell types

Recent technical advances have enabled transcriptomics experiments at an unprecedented scale, and single-cell profiles from neural tissue are accumulating rapidly. There has been considerable effort to use these profiles to understand cell diversity, primarily through unsupervised clustering and differential expression analysis. However, current practices to validate these findings vary. In this review, we describe recent efforts to evaluate clusters from single-cell RNA-sequencing data, and provide a framework for considering current evidence and practices in terms of their capacity to establish principles of cell biology. Single-cell RNA-sequencing has already transformed neuroscience. By facilitating detailed comparative and genetic perturbation analyses, it may provide the tools to uncover fundamental mechanisms of neural diversity throughout the tree of life.