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

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ID: 315257
2026
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Abstract
Abstract Motivation Single-cell RNA sequencing (scRNA-seq) is now a core technology for resolving cellular heterogeneity in complex samples, and standard analysis workflows produce a wide range of outputs, each requiring tailored visualization. To support this, a wide range of analysis tools have been developed, many of which offer built-in visualizations but leave further customization to the user. Researchers who run standard single-cell workflows in R, often experimental biologists with a working knowledge of Seurat and ggplot2, still spend considerable effort converting analytical outputs into figures that meet journal standards. Results We present SCpubr, an R package that provides concise function calls for generating high-quality, publication-ready visualizations commonly used in single-cell transcriptome analyses. Availability and implementation SCpubr is available on CRAN (https://cran.r-project.org/package=SCpubr), with source code accessible on GitHub (https://github.com/enblacar/SCpubr). Supplementary information Supplementary figures are available at Bioinformatics Advances online. Extensive documentation and tutorials are available via the GitHub Pages site (https://enblacar.github.io/SCpubr-book/). The complete analysis code used to generate all figures in this publication, along with the full R session information and instructions for obtaining the raw input data, is available in GitHub (https://github.com/enblacar/SCpubr-manuscript).
Reference Key
openalex_W7162807449 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Enrique Blanco-Carmona, Marcel Kool
Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag151
URL
https://doi.org/10.1093/bioadv/vbag151
Keywords Keywords not found

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