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Updated: Sep 12, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Chevreul: an R bioconductor package for exploratory analysis of full-length single cell sequencing.

Kevin Stachelek^1,2, Bhavana Bhat¹, David Cobrinik^1,3,4,5

¹The Vision Center, Department of Surgery, and Saban Research Institute, Children's Hospital Los Angeles, Los Angeles, CA 90027, USA.

Gigabyte (Hong Kong, China)

|August 5, 2025

Summary

This summary is machine-generated.

Chevreul is a new R package and Shiny app for single-cell RNA sequencing (scRNA-seq) data analysis. It offers user-friendly tools for full-length transcript analysis, batch correction, and visualization, empowering researchers without extensive programming skills.

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Published on: May 9, 2017

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Single-cell RNA sequencing (scRNA-seq) generates high-dimensional data requiring specialized analysis tools.
Existing scRNA-seq analysis packages may lack comprehensive features for full-length transcript analysis and ease of use.
There is a need for accessible tools that support advanced analyses like isoform inference and batch correction.

Purpose of the Study:

To introduce Chevreul, an open-source R package and Shiny application for scRNA-seq data processing and visualization.
To provide a user-friendly platform for analyzing full-length RNA sequencing data, including exon coverage and transcript isoform inference.
To enable researchers, including those with limited programming experience, to perform complex scRNA-seq analyses.

Main Methods:

Chevreul utilizes R and Bioconductor's SingleCellExperiment objects for data handling.
It incorporates functionalities for batch integration, quality control, normalization, dimensionality reduction, and clustering.
The integrated R Shiny app allows for interactive visualization of processed data using various plots (PCA, tSNE, UMAP, heatmaps, violin plots).

Main Results:

Chevreul facilitates exploratory data analysis, including batch correction and differential expression analysis.
The package supports advanced analyses such as isoform-level analysis and alternative splicing detection.
Processed scRNA-seq data can be effectively visualized through interactive plots in the Shiny application.

Conclusions:

Chevreul offers a comprehensive and accessible solution for scRNA-seq data analysis, particularly for full-length RNA sequencing data.
Its user-friendly interface and advanced analytical capabilities, including isoform analysis, make it a valuable tool for the research community.
The integration of R package and Shiny app enhances the usability and reproducibility of scRNA-seq data exploration and interpretation.