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Dissecting Cellular Heterogeneity Using Single-Cell RNA Sequencing

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, homeo-statically regulated, and responds to external perturbations...

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Detalles Bibliográficos
Autores principales: Choi, Yoon Ha, Kim, Jong Kyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Molecular and Cellular Biology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449718/
https://www.ncbi.nlm.nih.gov/pubmed/30764602
http://dx.doi.org/10.14348/molcells.2019.2446
Descripción
Sumario: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, homeo-statically 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.