Dissecting Cellular Heterogeneity Using Single-Cell RNA Sequencing 
Yoon Ha Choi and Jong Kyoung Kim*
Department of New Biology, DGIST, Daegu 42988, Korea
*Correspondence: jkkim@dgist.ac.kr
Received December 11, 2018; Revised January 9, 2019; Accepted January 9, 2019.; Published online February 12, 2019.
© Korean Society for Molecular and Cellular Biology. All rights reserved.

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit (http://creativecommons.org/licenses/by-nc-sa/3.0/).
ABSTRACT
Cell-to-cell variability in gene expression exists even in a homogeneous population of cells. Dissecting such cellular heterogeneity within a biological system is a prerequisite for understanding how a biological system is developed, homeostatically regulated, and responds to external perturbations. Single-cell RNA sequencing (scRNA-seq) allows the quantitative and unbiased characterization of cellular heterogeneity by providing genome-wide molecular profiles from tens of thousands of individual cells. A major question in analyzing scRNA-seq data is how to account for the observed cell-to-cell variability. In this review, we provide an overview of scRNA-seq protocols, computational approaches for dissecting cellular heterogeneity, and future directions of single-cell transcriptomic analysis.
Keywords: cellular heterogeneity, RNA sequencing, singlecell, single-cell genomics, single-cell transcriptomics


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28 February 2019 Volume 42,
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