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Dissecting Cellular Heterogeneity Using Single-Cell RNA Sequencing

  • Received : 2018.12.11
  • Accepted : 2019.01.09
  • Published : 2019.03.31

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.

E1BJB7_2019_v42n3_189_f0001.png 이미지

Fig. 1. Computational workflow for analyzing scRNA-seq data.

Acknowledgement

Supported by : National Research Foundation of Korea, Ministry of SMEs and Startups

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