Perform Nonparametric Group Comparison

Conducts a Wilcoxon rank-sum test (Mann-Whitney U test) to compare expression values between two groups without assuming normality.

Usage

nonparametric.test(df)

Arguments

df

A data frame containing at least two columns:

expression

Numeric vector of gene expression values.

group

Character or factor vector with exactly two group labels.

Value

A named list with two elements:

p.value

Numeric. P-value from the Wilcoxon rank-sum test.

test

Character. Name of the test used ("Wilcoxon rank-sum").

Details

This test is useful as a robustness check against parametric methods such as the t-test, especially when data are skewed or contain outliers. The result is used by analyze.gene() to populate the robustness field of its return value.

Examples

# \donttest{
analysis.df <- data.frame(
  expression = c(1.2, 2.3, 1.8, 2.1, 3.4, 2.9, 3.1, 2.7,
                 1.5, 2.0, 1.9, 2.4),
  group      = rep(c("normal", "RCC"), each = 6)
)
res <- nonparametric.test(analysis.df)
res$p.value
#> [1] 1
# }