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.
CITATION STYLE
Kashima, Y., Sakamoto, Y., Kaneko, K., Seki, M., Suzuki, Y., & Suzuki, A. (2020, September 1). Single-cell sequencing techniques from individual to multiomics analyses. Experimental and Molecular Medicine. Springer Nature. https://doi.org/10.1038/s12276-020-00499-2
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