get_adj_p: Get Adjust P Values from Group Comparison

In ShixiangWang/sigminer: Extract, Analyze and Visualize Mutational Signatures for Genomic Variations

Get Adjust P Values from Group Comparison

Description

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.

Usage

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

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()

Details

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

Value

a data.frame containing comparison result

Source

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

Examples

library(ggpubr)
# T-test
stat.test <- compare_means(
  len ~ dose,
  data = ToothGrowth,
  method = "t.test",
  p.adjust.method = "fdr"
)
stat.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
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")

ShixiangWang/sigminer documentation built on March 16, 2024, 12:30 p.m.