GGPUBR: How to Add P-Values Generated Elsewhere to a GGPLOT

Author

Affiliation

Mtro. Santiago Ríos

Cursos Orca

This article describes how to add p-values generated elsewhere to a ggplot using the ggpubr package. The following key ggpubr functions will be used:

stat_pvalue_manual(): Add manually p-values to a ggplot, such as box blots, dot plots and stripcharts.
geom_bracket(): Add brackets with label annotation to a ggplot. Helpers for adding p-value or significance levels to a plot.

You will learn how to:

Add custom p-values created from elsewhere
Add p-values obtained from the rstatix R package
Add brackets with custom p-value labels to a ggplot

Make sure you have the following R packages:

tidyverse for data manipulation and visualization
ggpubr for creating easily publication ready plots
rstatix provides pipe-friendly R functions for easy statistical analyses

Load required R packages:

Add p-values computed from elsewhere

Key R function: stat_pvalue_manual() [in ggpubr package]

stat_pvalue_manual(data, label = NULL)

Add p-values obtained from the rstatix package Create a simple box plot

Pairwise comparisons

Faceted Plots

Grouped plots

Specify manually the y position of the p-values

Create a simple box plot:

Faceted plots: Comparisons between two groups

Faceted Plot: Pairwise comparissons between multiple groups

Grouped plots

Add brackets with custom p-value labels to a ggplot

This section describes the function geom_bracket() [in ggpubr package] for adding brackets with label annotation to a ggplot. It makes it easy to add p-value or significance levels created elsewhere to a plot. Basic brackets with labels

Using plotmath expression and specifying multiple brackets manually

Compute statistical test and add p-values ::: {.cell autorun=‘true’}

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