Applications of Single-Cell Sequencing for Multiomics

  • Yungang Xu
  • Xiaobo ZhouEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1754)


Single-cell sequencing interrogates the sequence or chromatin information from individual cells with advanced next-generation sequencing technologies. It provides a higher resolution of cellular differences and a better understanding of the underlying genetic and epigenetic mechanisms of an individual cell in the context of its survival and adaptation to microenvironment. However, it is more challenging to perform single-cell sequencing and downstream data analysis, owing to the minimal amount of starting materials, sample loss, and contamination. In addition, due to the picogram level of the amount of nucleic acids used, heavy amplification is often needed during sample preparation of single-cell sequencing, resulting in the uneven coverage, noise, and inaccurate quantification of sequencing data. All these unique properties raise challenges in and thus high demands for computational methods that specifically fit single-cell sequencing data. We here comprehensively survey the current strategies and challenges for multiple single-cell sequencing, including single-cell transcriptome, genome, and epigenome, beginning with a brief introduction to multiple sequencing techniques for single cells.

Key words

Single-cell sequencing Single-cell transcriptome Genome Epigenome Multiomics Allele-specific expression Single nucleotide variant calling Clonal structure 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Center for Systems Medicine, School of Biomedical InformaticsUTHealth at HoustonHoustonUSA
  2. 2.Center for Bioinformatics and Systems BiologyWake Forest School of MedicineWinston-SalemUSA

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