Profiling of Single-Cell Transcriptomes

Wanze Chen, Vincent Gardeux, Antonio Meireles-Filho, Bart Deplancke

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Complex biological systems are composed of multiple cell types whose transcriptional activity can vary due to differences in cell state, environmental stimulation, or intrinsic programs. Conventional bulk analysis methods capture the average transcriptional programs of the cell population, thus missing the unique cellular signature of each single cell. In recent years, the development of single-cell RNA-sequencing (scRNA-seq) technologies has provided a powerful approach to dissect the cellular heterogeneity of complex biological systems. However, such approaches require specialized equipment or are costly. In this article, we describe an improved Smart-seq2-based method to profile the transcriptome of hundreds of single cells simultaneously, without utilizing commercial kits or requiring any specialized single-cell capture/library preparation tools. Moreover, we introduce the Automated Single-cell Analysis Pipeline (ASAP), which allows researchers without strong computational expertise to explore scRNA-seq data using a wide range of commonly used algorithms and sophisticated visualization tools.

Original languageEnglish (US)
Pages (from-to)145-175
Number of pages31
JournalCurrent protocols in mouse biology
Volume7
Issue number3
DOIs
Publication statusPublished - Sep 8 2017
Externally publishedYes

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Keywords

  • analysis pipeline
  • ASAP
  • gene expression
  • scRNA-seq
  • single-cell
  • Smart-seq2
  • tagmentation
  • Tn5
  • transcriptomics
  • Web tool

ASJC Scopus subject areas

  • Medicine(all)

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