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Single-Cell Transcriptome Analysis Using SINCERA Pipeline

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Transcriptome Data Analysis

Part of the book series: Methods in Molecular Biology ((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.

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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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Authors and Affiliations

  1. The Perinatal Institute, Section of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA

    Minzhe Guo & Yan Xu

  2. Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA

    Yan Xu

Authors
  1. Minzhe Guo
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  2. Yan Xu
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Correspondence to Yan Xu .

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Editors and Affiliations

  1. Department of Cell Biology and Genetics, School of Basic Medicine, Shenzhen University Health, Science Center, Shenzhen, China

    Yejun Wang

  2. Epigenomics and Computational Biology Lab, Biocomplexity Institute of Virginia Tech, Blacksburg, Virginia, USA

    Ming-an Sun

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Guo, M., Xu, Y. (2018). Single-Cell Transcriptome Analysis Using SINCERA Pipeline. In: Wang, Y., Sun, Ma. (eds) Transcriptome Data Analysis. Methods in Molecular Biology, vol 1751. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7710-9_15

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  • DOI: https://doi.org/10.1007/978-1-4939-7710-9_15

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7709-3

  • Online ISBN: 978-1-4939-7710-9

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