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Single-Cell Transcriptome Analysis Using SINCERA Pipeline

  • Minzhe Guo
  • Yan XuEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1751)

Abstract

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, https://research.cchmc.org/pbge/sincera.html.

Key words

Single-cell RNA-Seq Pipeline Cell type Signature gene Driving force 

Notes

Acknowledgment

This work was supported by the National Heart, Lung, and Blood Institute of National Institutes of Health (http://www.nhlbi.nih.gov, grants U01HL122642 (LungMAP), U01 HL110967 (LRRC), and R01 HL105433). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Copyright information

© Springer Science+Business Media, LLC 2018

Authors and Affiliations

  1. 1.The Perinatal Institute, Section of Neonatology, Perinatal and Pulmonary BiologyCincinnati Children’s Hospital Medical CenterCincinnatiUSA
  2. 2.Division of Biomedical InformaticsCincinnati Children’s Hospital Medical CenterCincinnatiUSA

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