Get Adjust P Values from Group Comparison

Setting aes(label=..p.adj..) in ggpubr::compare_means() does not show adjust p values. The returned result of this function can be combined with ggpubr::stat_pvalue_manual() to fix this problem.

get_adj_p(
  data,
  .col,
  .grp = "Sample",
  comparisons = NULL,
  method = "wilcox.test",
  p.adjust.method = "fdr",
  p.digits = 3L,
  ...
)

Source

https://github.com/kassambara/ggpubr/issues/143

Arguments

data: a data.frame containing column for groups and column for comparison.
.col: column name for comparison.
.grp: column name for groups.
comparisons: Default is NULL, use all combination in group column. It can be a list of length-2 vectors. The entries in the vector are either the names of 2 values on the x-axis or the 2 integers that correspond to the index of the groups of interest, to be compared.
method: a character string indicating which method to be used for comparing means. It can be 't.test', 'wilcox.test' etc..
p.adjust.method: correction method, default is 'fdr'. Run p.adjust.methods to see all available options.
p.digits: how many significant digits are to be used.
...: other arguments passed to ggpubr::compare_means()

Value

a data.frame containing comparison result

Details

More info see ggpubr::compare_means(), ggpubr::stat_compare_means() and stats::p.adjust().

Examples

library(ggpubr)
#> Loading required package: ggplot2
# T-test
stat.test <- compare_means(
  len ~ dose,
  data = ToothGrowth,
  method = "t.test",
  p.adjust.method = "fdr"
)
stat.test
#> # A tibble: 3 × 8
#>   .y.   group1 group2        p   p.adj p.format p.signif method
#>   <chr> <chr>  <chr>     <dbl>   <dbl> <chr>    <chr>    <chr> 
#> 1 len   0.5    1      1.27e- 7 1.9e- 7 1.3e-07  ****     T-test
#> 2 len   0.5    2      4.40e-14 1.3e-13 4.4e-14  ****     T-test
#> 3 len   1      2      1.91e- 5 1.9e- 5 1.9e-05  ****     T-test
# Create a simple box plot
p <- ggboxplot(ToothGrowth, x = "dose", y = "len")
p


# Add p values
my_comparisons <- list(c("0.5", "1"), c("1", "2"), c("0.5", "2"))
p + stat_compare_means(method = "t.test", comparisons = my_comparisons)


# Try adding adjust p values
# proposed by author of ggpubr
# however it does not work
p + stat_compare_means(aes(label = ..p.adj..), method = "t.test", comparisons = my_comparisons)


# Solution:
# calculate adjust p values and their location
# then use stat_pvalue_manual() function
p_adj <- get_adj_p(ToothGrowth, .col = "len", .grp = "dose")
p_adj
#> # A tibble: 3 × 9
#>   .y.   group1 group2            p p.adj   p.format p.signif method   y.position
#>   <chr> <chr>  <chr>         <dbl> <chr>   <chr>    <chr>    <chr>         <dbl>
#> 1 len   0.5    1      0.00000702   1.1e-05 7.0e-06  ****     Wilcoxon       37.3
#> 2 len   0.5    2      0.0000000841 2.5e-07 8.4e-08  ****     Wilcoxon       40.7
#> 3 len   1      2      0.000177     0.00018 0.00018  ***      Wilcoxon       44.1
p + stat_pvalue_manual(p_adj, label = "p.adj")


# Show selected comparisons
# Of note, p value is ajusted
# for three comparisons, but only
# two are showed in figure
p_adj <- get_adj_p(ToothGrowth,
  .col = "len", .grp = "dose",
  comparisons = list(c("0.5", "1"), c("1", "2"))
)
p + stat_pvalue_manual(p_adj, label = "p.adj")