The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots require some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'-based publication ready plots. This version includes modern R ecosystem compatibility updates and customizable p-value formatting presets (APA, AMA, NEJM, Lancet, GraphPad, and scientific notation) for publication workflows, plus robust sparse-subset handling in statistical annotation layers such as 'stat_compare_means()' and 'geom_pwc()', with informative per-group skip diagnostics for non-comparable subsets.
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Dependency Anatomy Guide
Understanding Dependency Borders
Dependencies are visually distinguished by their border styles to help you understand their relationship to the current package:
Direct Dependencies
Thick solid border: These are dependencies directly specified in the package's DESCRIPTION file (Depends, Imports, Enhances, or LinkingTo).
Recursive Dependencies
Thin solid border: These are dependencies of dependencies (recursive/indirect dependencies). They are initially hidden but can be toggled with the switch button.
Version Constraint Conflicts
Thick border + Info icon: When both direct and recursive dependencies exist for the same package with different version constraints. This indicates the "true" version constraint for the package, as the recursive dependency requires the more strict version constraint.
Understanding the Info Icon
The yellow info circle appears when there are version constraint conflicts between direct and recursive dependencies for the same package. This helps give a more accurate picture of the version constraints for the dependencies of a given package.
Compare Versions
Select an older version above to compare dependencies.