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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...

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Detalles Bibliográficos
Autores principales: Kashima, Yukie, Sakamoto, Yoshitaka, Kaneko, Keiya, Seki, Masahide, Suzuki, Yutaka, Suzuki, Ayako
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080663/
https://www.ncbi.nlm.nih.gov/pubmed/32929221
http://dx.doi.org/10.1038/s12276-020-00499-2
Descripción
Sumario: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.