Methods and challenges in the analysis of single-cell RNA-sequencing data

Abstract

The recent advent of highly parallelizable single-cell RNA-sequencing technologies has opened a new window into the study of cell differentiation, commitment, and diversity. Rapid advances in the development of these technologies are being accompanied by the design of computational methods tailored to address the challenges presented by the analysis of single-cell RNA-sequencing data. This review provides a concise overview of some of the steps, algorithms, and approaches that are currently used in the analysis of single-cell RNA-sequencing data, with an emphasis on recent developments.