Single-cell sequencing techniques from individual to multiomics analyses

University of Tokyo researchers review single-cell sequencing techniques for individual and multiomics profiling in single cells. They 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. The researchers 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.

Comparison of scRNA-seq platforms

Characteristics of two major scRNA-seq platforms, C1 and Chromium