Single-cell RNA sequencing technologies and bioinformatics pipelines

Byungjin Hwang, Ji Hyun Lee, Duhee Bang

Research output: Contribution to journalReview articlepeer-review

748 Citations (Scopus)


Rapid progress in the development of next-generation sequencing (NGS) technologies in recent years has provided many valuable insights into complex biological systems, ranging from cancer genomics to diverse microbial communities. NGS-based technologies for genomics, transcriptomics, and epigenomics are now increasingly focused on the characterization of individual cells. These single-cell analyses will allow researchers to uncover new and potentially unexpected biological discoveries relative to traditional profiling methods that assess bulk populations. Single-cell RNA sequencing (scRNA-seq), for example, can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track the trajectories of distinct cell lineages in development. In this review, we will focus on technical challenges in single-cell isolation and library preparation and on computational analysis pipelines available for analyzing scRNA-seq data. Further technical improvements at the level of molecular and cell biology and in available bioinformatics tools will greatly facilitate both the basic science and medical applications of these sequencing technologies.

Original languageEnglish
Article number96
JournalExperimental and Molecular Medicine
Issue number8
Publication statusPublished - 2018 Aug 1

Bibliographical note

Funding Information:
This work was supported by a National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MSIP) (NRF-2016R1A5A2008630); Mid-career Researcher Program (2015R1A2A1A10055972); and Bio & Medical Technology Development Program (NRF-2016M3A9B6948494) through the National Research Foundation of Korea funded by the Ministry of Science, ICT, and Future Planning. We also thank Tae Won Yun for assistance with figure illustrations.

Publisher Copyright:
© 2018, The Author(s).

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Medicine
  • Molecular Biology
  • Clinical Biochemistry


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