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Single-cell sequencing techniques from individual to multiomics analyses

  • 작성자

    관리자
  • 작성일자

    2020-11-23
  • 조회수

    245
Ayako Suzuki ( asuzuki@edu.k.u-tokyo.ac.jp )
2018-present Specially Appointed Associate Professor, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Japan
2015-2018 Research Scientist, Exploratory Oncology Research & Clinical Trial Center, National Cancer Center, Japan
2015-2015 Specially Appointed Assistant Professor, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Japan
2012-2015 PhD, Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Japan
2010-2012 MS, Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Japan

Single-cell sequencing techniques from individual to multiomics analyses

Here, we review single-cell sequencing techniques for individual and multiomics profiling in single cells. We mainly describe single-cell genomic, epigenomic, and transcriptomic methods, and examples of their applications. For the integration of multilayered data sets, such as the transcriptome data derived from single-cell RNA sequencing and chromatin accessibility data derived from single-cell ATAC-seq, there are several computational integration methods. We also describe single-cell experimental methods for the simultaneous measurement of two or more omics layers. We can achieve a detailed understanding of the basic molecular profiles and those associated with disease in each cell by utilizing a large number of single-cell sequencing techniques and the accumulated data sets.

Exp Mol Med. 2020 Sep;52(9):1419-1427. doi: 10.1038/s12276-020-00499-2.
https://pubmed.ncbi.nlm.nih.gov/32929221/