batch_wilcoxon: Batch Wilcoxon Rank-Sum Test Between Two Groups

In IOBR: Immune Oncology Biological Research

Batch Wilcoxon Rank-Sum Test Between Two Groups

Description

Performs Wilcoxon rank-sum tests (Mann-Whitney U tests) to compare the distribution of specified features between two groups. Computes p-values, adjusts for multiple testing, and ranks features by significance.

Usage

batch_wilcoxon(
  data,
  target = "group",
  feature = NULL,
  feature_manipulation = FALSE
)

Arguments

data	Data frame containing the dataset for analysis.
target	Character string specifying the column name of the grouping variable. Default is '"group"'.
feature	Character vector specifying feature names to analyze. If 'NULL', prompts for selection (interactive mode only). Default is 'NULL'.
feature_manipulation	Logical indicating whether to apply feature manipulation filtering. Default is 'FALSE'.

Value

Tibble with columns:

sig_names

Feature name

p.value

Raw p-value

statistic

Difference in means between groups

p.adj

Adjusted p-value (Benjamini-Hochberg)

log10pvalue

Negative log10-transformed p-value

stars

Significance stars: **** p<0.0001, *** p<0.001, ** p<0.01, * p<0.05, + p<0.5

group1, group2

Mean values for each group

Author(s)

Dongqiang Zeng

Examples

# Create small example data
set.seed(123)
test_data <- data.frame(
  Gender = rep(c("Male", "Female"), each = 50),
  Signature1 = rnorm(100),
  Signature2 = rnorm(100)
)
# Compare features by gender
res <- batch_wilcoxon(
  data = test_data,
  target = "Gender",
  feature = c("Signature1", "Signature2")
)
head(res)

IOBR documentation built on May 30, 2026, 5:07 p.m.