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Adjust p-values Displayed on a GGPlot

Source: R/ggadjust_pvalue.R
ggadjust_pvalue.Rd

Adjust p-values produced by geom_pwc() on a ggplot. This is mainly useful when using facet, where p-values are generally computed and adjusted by panel without taking into account the other panels. In this case, one might want to adjust after the p-values of all panels together.

Usage

ggadjust_pvalue(
  p,
  layer = NULL,
  p.adjust.method = "holm",
  label = "p.adj",
  hide.ns = NULL,
  symnum.args = list(),
  p.format.style = "default",
  p.digits = NULL,
  p.leading.zero = NULL,
  p.min.threshold = NULL,
  p.decimal.mark = NULL,
  signif.cutoffs = NULL,
  signif.symbols = NULL,
  ns.symbol = "ns",
  use.four.stars = FALSE,
  output = c("plot", "stat_test")
)

Arguments

p

a ggplot

layer

An integer indicating the statistical layer rank in the ggplot (in the order added to the plot).

p.adjust.method

method for adjusting p values (see p.adjust). Has impact only in a situation, where multiple pairwise tests are performed; or when there are multiple grouping variables. Ignored when the specified method is "tukey_hsd" or "games_howell_test" because they come with internal p adjustment method. Allowed values include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none". If you don't want to adjust the p value (not recommended), use p.adjust.method = "none".

label

character string specifying label. Can be:

  • the column containing the label (e.g.: label = "p" or label = "p.adj"), where p is the p-value. Other possible values are "p.signif", "p.adj.signif", "p.format", "p.format.signif", "p.adj.format".

  • an expression that can be formatted by the glue() package. For example, when specifying label = "Wilcoxon, p = \{p\}", the expression {p} will be replaced by its value.

  • a combination of plotmath expressions and glue expressions. You may want some of the statistical parameter in italic; for example:label = "Wilcoxon, italic(p)= {p}"

.

hide.ns

can be logical value (TRUE or FALSE) or a character vector ("p.adj" or "p").

symnum.args

a list of arguments to pass to the function symnum for symbolic number coding of p-values. For example, symnum.args = list(cutpoints = c(0, 0.0001, 0.001, 0.01, 0.05, Inf), symbols = c("****", "***", "**", "*", "ns")).

In other words, we use the following convention for symbols indicating statistical significance:

  • ns: p > 0.05

  • *: p <= 0.05

  • **: p <= 0.01

  • ***: p <= 0.001

  • ****: p <= 0.0001

Note: If symnum.args is provided, it takes precedence over signif.cutoffs.

p.format.style

character string specifying the p-value formatting style. One of: "default" (backward compatible, uses scientific notation), "apa" (APA style, no leading zero), "nejm" (NEJM style), "lancet" (Lancet style), "ama" (AMA style), "graphpad" (GraphPad style), or "scientific" (scientific notation for GWAS). See list_p_format_styles for details.

p.digits

integer specifying the number of decimal places for p-values. If provided, overrides the style default.

p.leading.zero

logical indicating whether to include leading zero before decimal point (e.g., "0.05" vs ".05"). If provided, overrides the style default.

p.min.threshold

numeric specifying the minimum p-value to display exactly. Values below this threshold are shown as "< threshold". If provided, overrides the style default.

p.decimal.mark

character string to use as the decimal mark. If NULL, uses getOption("OutDec").

signif.cutoffs

numeric vector of p-value cutoffs in descending order for assigning significance symbols. For example, c(0.10, 0.05, 0.01) means p < 0.10 gets "*", p < 0.05 gets "**", p < 0.01 gets "***". Default is NULL, which uses the package defaults.

signif.symbols

character vector of symbols corresponding to signif.cutoffs. If NULL, auto-generated as "*", "**", "***" (and "****" if use.four.stars = TRUE).

ns.symbol

character string for non-significant results. Default is "ns". Use "" (empty string) to show nothing.

use.four.stars

logical. If TRUE, allows four stars (****) for the most significant level. Default is FALSE.

output

character. Possible values are one of c("plot", "stat_test"). Default is "plot".

Examples

# Data preparation
# :::::::::::::::::::::::::::::::::::::::
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add a random grouping variable
df$group <- factor(rep(c("grp1", "grp2"), 30))
head(df, 3)
#>    len supp dose group
#> 1  4.2   VC  0.5  grp1
#> 2 11.5   VC  0.5  grp2
#> 3  7.3   VC  0.5  grp1

# Boxplot: Two groups by panel
# :::::::::::::::::::::::::::::::::::::::
# Create a box plot
bxp <- ggboxplot(
  df,
  x = "supp", y = "len", fill = "#00AFBB",
  facet.by = "dose"
)
# Make facet and add p-values
bxp <- bxp + geom_pwc(method = "t_test")
bxp

# Adjust all p-values together after
ggadjust_pvalue(
  bxp,
  p.adjust.method = "bonferroni",
  label = "{p.adj.format}{p.adj.signif}", hide.ns = TRUE
)



# Boxplot: Three groups by panel
# :::::::::::::::::::::::::::::::::::::::
# Create a box plot
bxp <- ggboxplot(
  df,
  x = "dose", y = "len", fill = "#00AFBB",
  facet.by = "supp"
)
# Make facet and add p-values
bxp <- bxp + geom_pwc(method = "t_test")
bxp

# Adjust all p-values together after
ggadjust_pvalue(
  bxp,
  p.adjust.method = "bonferroni",
  label = "{p.adj.format}{p.adj.signif}"
)