High Throughput Single Cell RNA Sequencing, Bioinformatics Analysis and Applications

Adv Exp Med Biol. 2018;1068:33-43. doi: 10.1007/978-981-13-0502-3_4.

Abstract

Single cell sequencing (SCS) can be harnessed to acquire the genomes, transcriptomes and epigenomes from individual cells. Next generation sequencing (NGS) technology is the driving force for single cell sequencing. scRNA-seq requires a lengthy pipeline comprising of single cell sorting, RNA extraction, reverse transcription, amplification, library construction, sequencing and subsequent bioinformatic analysis. Computational algorithms are essential to fulfill many tasks of interest using scRNA-seq data. scRNA-seq has already enabled researchers to revisit long-standing questions in cancer biology, including cancer metastasis, heterogeneity and evolution. Circulating Tumor Cells (CTC) are not only an important mechanism for cancer metastasis, but also provide a possibility to diagnose and monitor cancer in a convenient way independent of surgical resection of the cancer.

Keywords: Bioinformatics; Cancer; Single cell; scRNA-seq.

Publication types

  • Review

MeSH terms

  • Animals
  • Computational Biology / methods*
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Neoplasms / diagnosis
  • Neoplasms / genetics
  • Neoplasms / metabolism
  • RNA / genetics*
  • RNA / metabolism
  • Single-Cell Analysis / methods*
  • Transcriptome

Substances

  • RNA