Single-Cell Transcriptome Analysis Using SINCERA Pipeline

Methods Mol Biol. 2018:1751:209-222. doi: 10.1007/978-1-4939-7710-9_15.


Genome-scale single-cell biology has recently emerged as a powerful technology with important implications for both basic and medical research. There are urgent needs for the development of computational methods or analytic pipelines to facilitate large amounts of single-cell RNA-Seq data analysis. Here, we present a detailed protocol for SINCERA (SINgle CEll RNA-Seq profiling Analysis), a generally applicable analytic pipeline for processing single-cell data from a whole organ or sorted cells. The pipeline supports the analysis for the identification of major cell types, cell type-specific gene signatures, and driving forces of given cell types. In this chapter, we provide step-by-step instructions for the functions and features of SINCERA together with application examples to provide a practical guide for the research community. SINCERA is implemented in R, licensed under the GNU General Public License v3, and freely available from CCHMC PBGE website, .

Keywords: Cell type; Driving force; Pipeline; RNA-Seq; Signature gene; Single-cell.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Computational Biology / methods*
  • Gene Expression Profiling*
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Sequence Analysis, RNA / methods*
  • Single-Cell Analysis / methods*
  • Software*