title: Design and computational analysis of single-cell RNA-sequencing experiments.
abstract: Single-cell RNA-sequencing (scRNA-seq) has emerged as a revolutionary tool that allows us to address scientific questions that eluded examination just a few years ago. With the advantages of scRNA-seq come computational challenges that are just beginning to be addressed. In this article, we highlight the computational methods available for the design and analysis of scRNA-seq experiments, their advantages and disadvantages in various settings, the open questions for which novel methods are needed, and expected future developments in this exciting area.
authors.affiliation: Department of Statistics, University of Wisconsin, Madison, WI, 53706, USA.
authors.forename: Rhonda
authors.initials: R
authors.lastname: Bacher
authors.affiliation: Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, 53726, USA. kendzior@biostat.wisc.edu.
authors.forename: Christina
authors.initials: C
authors.lastname: Kendziorski
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D017423:Sequence Analysis, RNA / Q000379:methods*; D059010:Single-Cell Analysis / Q000379:methods*