Chapter title |
Single-Cell Transcriptome Analysis Using SINCERA Pipeline
|
---|---|
Chapter number | 15 |
Book title |
Transcriptome Data Analysis
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7710-9_15 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7709-3, 978-1-4939-7710-9
|
Authors |
Minzhe Guo, Yan Xu, Guo, Minzhe, Xu, Yan |
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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