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Updated: Sep 12, 2025

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 Stachelek1,2, Bhavana Bhat1, David Cobrinik1,3,4,5
1The Vision Center, Department of Surgery, and Saban Research Institute, Children's Hospital Los Angeles, Los Angeles, CA 90027, USA.
Abstract:
Chevreul is an open-source R Bioconductor package and interactive R Shiny app for processing and visualising single-cell RNA sequencing (scRNA-seq) data. Chevreul differs from other scRNA-seq analysis packages in its ease of use, capacity to analyze full-length RNA sequencing data for exon coverage and transcript isoform inference, and support for batch correction. Chevreul enables exploratory analyses of scRNA-seq data using Bioconductor SingleCellExperiment objects (or converted Seurat objects), including batch integration, quality control filtering, read count normalization and transformation, dimensionality reduction, clustering at a range of resolutions, and cluster marker gene identification. Processed data can be visualized in the R Shiny app. Gene or transcript expression can be visualized using PCA, tSNE, UMAP, heatmaps, or violin plots; differential expression can be evaluated with several statistical tests. Chevreul also provides accessible tools for isoform-level analyses and alternative splicing detection. Chevreul empowers researchers without programming experience to analyze full-length scRNA-seq data.
Availability & Implementation:
Chevreul is implemented in R, and the R package and integrated Shiny application are freely available at https://github.com/cobriniklab/chevreul with constituent packages hosted on Bioconductor at https://bioconductor.org/packages/chevreulProcess, https://bioconductor.org/packages/chevreulPlot, and https://bioconductor.org/packages/chevreulShiny.
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