SCpubr: a user-friendly R-package for generating publication-ready visualizations of single-cell transcriptome...

Area of Science:

• Computational Biology
• Genomics
• Bioinformatics

Background:

• Single-cell RNA sequencing (scRNA-seq) is crucial for understanding cellular heterogeneity.
• Standard analysis workflows generate diverse outputs requiring specialized visualizations.
• Existing tools often lack sufficient customization for publication-quality figures.

Purpose of the Study:

• To introduce SCpubr, an R package designed for generating publication-ready visualizations for scRNA-seq data.
• To streamline the process of creating figures from complex single-cell analyses.
• To assist researchers, particularly experimental biologists, in producing journal-standard figures.

Main Methods:

• Development of the SCpubr R package.
• Implementation of concise functions for common scRNA-seq visualization needs.
• Integration with existing R-based analysis workflows (e.g., Seurat, ggplot2).

Main Results:

• SCpubr provides easy-to-use functions for generating high-quality visualizations.
• The package simplifies the conversion of analytical outputs into publication-ready figures.
• Enhanced visualization capabilities for single-cell transcriptome analyses.

Conclusions:

• SCpubr effectively addresses the need for efficient and high-quality figure generation in scRNA-seq research.
• The package empowers researchers to create publication-standard visualizations with less effort.
• SCpubr enhances the accessibility and reproducibility of scRNA-seq data visualization.