Abstract

Despite breakthroughs in precision medicine during the past decade due to bulk RNA profiling approaches, those conceal gene expression heterogeneity expected in samples and tissues. Recent developments in single-cell RNA sequencing (scRNA-seq) have enabled researchers to dissect this heterogeneity through genome-wide expression profiling at cellular resolution. This new level of information on cell types and cell states may shed light on molecular mechanisms underlying the pathogenesis of complex diseases, leading to the re-evaluation of the current hypothesis discriminating diseases and treatment subgroups. In this chapter, features of the most relevant technologies for single-cell isolation and library preparation for scRNA-seq are presented, and pipelines for data analysis are discussed, including challenging technical aspects specific to single-cell analysis.