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Genome Biol. 2016 Apr 7;17:63. doi: 10.1186/s13059-016-0927-y.

Design and computational analysis of single-cell RNA-sequencing experiments.

Author information

1
Department of Statistics, University of Wisconsin, Madison, WI, 53706, USA.
2
Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, 53726, USA. kendzior@biostat.wisc.edu.

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.

PMID:
27052890
PMCID:
PMC4823857
DOI:
10.1186/s13059-016-0927-y
[Indexed for MEDLINE]
Free PMC Article

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