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Transcriptome Analysis of Single Cells
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Single-Cell Transcriptome Analysis Using SINCERA Pipeline.

Minzhe Guo1, Yan Xu2,3

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

Methods in Molecular Biology (Clifton, N.J.)
|March 7, 2018
PubMed
Summary
This summary is machine-generated.

SINCERA is a new R-based pipeline for analyzing single-cell RNA sequencing data. It helps identify cell types, gene signatures, and cell-driving forces from whole organs or sorted cells.

Keywords:
Cell typeDriving forcePipelineRNA-SeqSignature geneSingle-cell

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Area of Science:

  • Genomics
  • Computational Biology
  • Bioinformatics

Background:

  • Single-cell RNA sequencing (scRNA-Seq) generates vast datasets requiring specialized analysis tools.
  • Accurate computational methods are crucial for extracting meaningful biological insights from scRNA-Seq data.

Purpose of the Study:

  • To present SINCERA (SINgle CEll RNA-Seq profiling Analysis), a comprehensive computational pipeline for scRNA-Seq data.
  • To provide a practical, step-by-step guide for researchers analyzing single-cell data.

Main Methods:

  • SINCERA is an R-based analytic pipeline designed for processing scRNA-Seq data.
  • The pipeline facilitates the identification of major cell types and cell type-specific gene signatures.
  • It also supports the analysis of driving forces within specific cell populations.

Main Results:

  • SINCERA offers a generally applicable approach for analyzing single-cell data from whole organs or sorted cells.
  • The pipeline provides detailed instructions and application examples for user-friendly implementation.
  • SINCERA is freely available under the GNU General Public License v3.

Conclusions:

  • SINCERA provides a robust and accessible solution for the computational analysis of large-scale single-cell RNA sequencing datasets.
  • This pipeline empowers researchers in basic and medical fields to effectively identify cell types and gene expression patterns.
  • The availability of SINCERA promotes broader adoption and advancement in single-cell biology research.