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Dissecting Cellular Heterogeneity Using Single-Cell RNA Sequencing
- Dissecting Cellular Heterogeneity Using Single-Cell RNA Sequencing
- Choi, Yoon Ha; Kim, Jong Kyoung
- DGIST Authors
- Kim, Jong Kyoung
- Issue Date
- Molecules and Cells, 42(3), 189-199
- Article Type
- Author Keywords
- cellular heterogeneity; RNA sequencing; singlecell; single-cell genomics; single-cell transcriptomics
- GENE-EXPRESSION; TRANSCRIPTIONAL LANDSCAPE; SEQ DATA; GENOME; QUANTIFICATION; VISUALIZATION; CHALLENGES; CYTOMETRY; INFERENCE; IDENTITY
- 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.
- Related Researcher
Kim, Jong Kyoung
Lab of Single-cell Genomics
Single-cell genomics, Bioinformatics, Machine Learning
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- Department of New BiologyLab of Single-cell Genomics1. Journal Articles
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