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

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.